diff --git a/be/CMakeLists.txt b/be/CMakeLists.txt
index df4b036347ba1f..917a2008d97e21 100644
--- a/be/CMakeLists.txt
+++ b/be/CMakeLists.txt
@@ -625,6 +625,10 @@ if (CMAKE_CXX_COMPILER_ID STREQUAL "Clang")
         set(CXX_COMMON_FLAGS "${CXX_COMMON_FLAGS} -Wno-switch-default")
     endif ()
 else ()
+    if (CMAKE_CXX_COMPILER_VERSION VERSION_GREATER_EQUAL "14.0.0")
+        # ignore error from apache-orc
+        set(CXX_COMMON_FLAGS "${CXX_COMMON_FLAGS} -Wno-error=dangling-reference")
+    endif ()
     set(CXX_GCC_FLAGS "${CXX_GCC_FLAGS} -fcoroutines")
 endif()
 
@@ -773,6 +777,8 @@ endif()
 
 set(WL_START_GROUP "-Wl,--start-group")
 set(WL_END_GROUP "-Wl,--end-group")
+set(WL_LINK_STATIC "-Wl,-Bstatic")
+set(WL_LINK_DYNAMIC "-Wl,-Bdynamic")
 
 # Set starrocks libraries
 set(STARROCKS_LINK_LIBS
@@ -963,7 +969,8 @@ if (NOT ("${MAKE_TEST}" STREQUAL "ON" AND "${BUILD_FOR_SANITIZE}" STREQUAL "ON")
 endif()
 
 set(STARROCKS_LINK_LIBS ${STARROCKS_LINK_LIBS}
-    -lresolv -lbfd -liberty -lc -lm -ldl -rdynamic -pthread -Wl,-wrap=__cxa_throw
+    ${WL_LINK_STATIC} -lbfd
+    ${WL_LINK_DYNAMIC} -lresolv -liberty -lc -lm -ldl -rdynamic -pthread -Wl,-wrap=__cxa_throw
 )
 
 # link gcov if WITH_GCOV is on
diff --git a/be/src/column/adaptive_nullable_column.h b/be/src/column/adaptive_nullable_column.h
index b247bdce6e18fa..0360f8c696a54d 100644
--- a/be/src/column/adaptive_nullable_column.h
+++ b/be/src/column/adaptive_nullable_column.h
@@ -276,9 +276,7 @@ class AdaptiveNullableColumn final : public ColumnFactory<NullableColumn, Adapti
 
     StatusOr<ColumnPtr> upgrade_if_overflow() override {
         materialized_nullable();
-        if (_null_column->capacity_limit_reached()) {
-            return Status::InternalError("Size of NullableColumn exceed the limit");
-        }
+        RETURN_IF_ERROR(_null_column->capacity_limit_reached());
 
         return upgrade_helper_func(&_data_column);
     }
@@ -556,9 +554,9 @@ class AdaptiveNullableColumn final : public ColumnFactory<NullableColumn, Adapti
         return NullableColumn::debug_string();
     }
 
-    bool capacity_limit_reached(std::string* msg = nullptr) const override {
+    Status capacity_limit_reached() const override {
         materialized_nullable();
-        return NullableColumn::capacity_limit_reached(msg);
+        return NullableColumn::capacity_limit_reached();
     }
 
     void check_or_die() const override {
diff --git a/be/src/column/array_column.h b/be/src/column/array_column.h
index 0bc53622db5572..5d930c0eabfe03 100644
--- a/be/src/column/array_column.h
+++ b/be/src/column/array_column.h
@@ -182,8 +182,9 @@ class ArrayColumn final : public ColumnFactory<Column, ArrayColumn> {
 
     std::string debug_string() const override;
 
-    bool capacity_limit_reached(std::string* msg = nullptr) const override {
-        return _elements->capacity_limit_reached(msg) || _offsets->capacity_limit_reached(msg);
+    Status capacity_limit_reached() const override {
+        RETURN_IF_ERROR(_elements->capacity_limit_reached());
+        return _offsets->capacity_limit_reached();
     }
 
     StatusOr<ColumnPtr> upgrade_if_overflow() override;
diff --git a/be/src/column/binary_column.cpp b/be/src/column/binary_column.cpp
index e209e548defa01..b4e5bedc48e856 100644
--- a/be/src/column/binary_column.cpp
+++ b/be/src/column/binary_column.cpp
@@ -24,6 +24,7 @@
 #include "gutil/bits.h"
 #include "gutil/casts.h"
 #include "gutil/strings/fastmem.h"
+#include "gutil/strings/substitute.h"
 #include "util/hash_util.hpp"
 #include "util/mysql_row_buffer.h"
 #include "util/raw_container.h"
@@ -738,45 +739,37 @@ bool BinaryColumnBase<T>::has_large_column() const {
 }
 
 template <typename T>
-bool BinaryColumnBase<T>::capacity_limit_reached(std::string* msg) const {
+Status BinaryColumnBase<T>::capacity_limit_reached() const {
     static_assert(std::is_same_v<T, uint32_t> || std::is_same_v<T, uint64_t>);
     if constexpr (std::is_same_v<T, uint32_t>) {
         // The size limit of a single element is 2^32 - 1.
         // The size limit of all elements is 2^32 - 1.
         // The number limit of elements is 2^32 - 1.
         if (_bytes.size() >= Column::MAX_CAPACITY_LIMIT) {
-            if (msg != nullptr) {
-                msg->append("Total byte size of binary column exceed the limit: " +
-                            std::to_string(Column::MAX_CAPACITY_LIMIT));
-            }
-            return true;
+            return Status::CapacityLimitExceed(
+                    strings::Substitute("Total byte size of binary column exceed the limit: $0",
+                                        std::to_string(Column::MAX_CAPACITY_LIMIT)));
         } else if (_offsets.size() >= Column::MAX_CAPACITY_LIMIT) {
-            if (msg != nullptr) {
-                msg->append("Total row count of binary column exceed the limit: " +
-                            std::to_string(Column::MAX_CAPACITY_LIMIT));
-            }
-            return true;
+            return Status::CapacityLimitExceed(
+                    strings::Substitute("Total row count of binary column exceed the limit: $0",
+                                        std::to_string(Column::MAX_CAPACITY_LIMIT)));
         } else {
-            return false;
+            return Status::OK();
         }
     } else {
         // The size limit of a single element is 2^32 - 1.
         // The size limit of all elements is 2^64 - 1.
         // The number limit of elements is 2^32 - 1.
         if (_bytes.size() >= Column::MAX_LARGE_CAPACITY_LIMIT) {
-            if (msg != nullptr) {
-                msg->append("Total byte size of large binary column exceed the limit: " +
-                            std::to_string(Column::MAX_LARGE_CAPACITY_LIMIT));
-            }
-            return true;
+            return Status::CapacityLimitExceed(
+                    strings::Substitute("Total byte size of large binary column exceed the limit: $0",
+                                        std::to_string(Column::MAX_LARGE_CAPACITY_LIMIT)));
         } else if (_offsets.size() >= Column::MAX_CAPACITY_LIMIT) {
-            if (msg != nullptr) {
-                msg->append("Total row count of large binary column exceed the limit: " +
-                            std::to_string(Column::MAX_CAPACITY_LIMIT));
-            }
-            return true;
+            return Status::CapacityLimitExceed(
+                    strings::Substitute("Total row count of large binary column exceed the limit: $0",
+                                        std::to_string(Column::MAX_CAPACITY_LIMIT)));
         } else {
-            return false;
+            return Status::OK();
         }
     }
 }
diff --git a/be/src/column/binary_column.h b/be/src/column/binary_column.h
index 09bfac117a058b..6e0b59b374daed 100644
--- a/be/src/column/binary_column.h
+++ b/be/src/column/binary_column.h
@@ -339,7 +339,7 @@ class BinaryColumnBase final : public ColumnFactory<Column, BinaryColumnBase<T>>
         return ss.str();
     }
 
-    bool capacity_limit_reached(std::string* msg = nullptr) const override;
+    Status capacity_limit_reached() const override;
 
 private:
     void _build_slices() const;
diff --git a/be/src/column/chunk.h b/be/src/column/chunk.h
index cf382610771115..67de2c8768540c 100644
--- a/be/src/column/chunk.h
+++ b/be/src/column/chunk.h
@@ -277,13 +277,11 @@ class Chunk {
 
     std::string rebuild_csv_row(size_t index, const std::string& delimiter) const;
 
-    bool capacity_limit_reached(std::string* msg = nullptr) const {
+    Status capacity_limit_reached() const {
         for (const auto& column : _columns) {
-            if (column->capacity_limit_reached(msg)) {
-                return true;
-            }
+            RETURN_IF_ERROR(column->capacity_limit_reached());
         }
-        return false;
+        return Status::OK();
     }
 
     query_cache::owner_info& owner_info() { return _owner_info; }
diff --git a/be/src/column/column.h b/be/src/column/column.h
index ec730265a0fc8e..3d86550fb09a71 100644
--- a/be/src/column/column.h
+++ b/be/src/column/column.h
@@ -394,7 +394,7 @@ class Column {
     // The interface will not free memory!!!
     virtual void reset_column() { _delete_state = DEL_NOT_SATISFIED; }
 
-    virtual bool capacity_limit_reached(std::string* msg = nullptr) const = 0;
+    virtual Status capacity_limit_reached() const = 0;
 
     virtual Status accept(ColumnVisitor* visitor) const = 0;
 
diff --git a/be/src/column/column_builder.h b/be/src/column/column_builder.h
index 42534d9ab689bc..221b11ec34a2de 100644
--- a/be/src/column/column_builder.h
+++ b/be/src/column/column_builder.h
@@ -57,7 +57,7 @@ class ColumnBuilder {
     ColumnBuilder(DataColumnPtr column, NullColumnPtr null_column, bool has_null)
             : _column(std::move(column)), _null_column(std::move(null_column)), _has_null(has_null) {}
     //do nothing ctor, members are initialized by its offsprings.
-    explicit ColumnBuilder<Type>(void*) {}
+    explicit ColumnBuilder(void*) {}
 
     void append(const DatumType& value) {
         _null_column->append(DATUM_NOT_NULL);
diff --git a/be/src/column/column_helper.h b/be/src/column/column_helper.h
index ea1a6f0a60dbbb..97d53bb2d353d7 100644
--- a/be/src/column/column_helper.h
+++ b/be/src/column/column_helper.h
@@ -525,8 +525,10 @@ struct ChunkSliceTemplate {
 template <LogicalType ltype>
 struct GetContainer {
     using ColumnType = typename RunTimeTypeTraits<ltype>::ColumnType;
-    const auto& get_data(const Column* column) { return ColumnHelper::as_raw_column<ColumnType>(column)->get_data(); }
-    const auto& get_data(const ColumnPtr& column) {
+    static const auto& get_data(const Column* column) {
+        return ColumnHelper::as_raw_column<ColumnType>(column)->get_data();
+    }
+    static const auto& get_data(const ColumnPtr& column) {
         return ColumnHelper::as_raw_column<ColumnType>(column.get())->get_data();
     }
 };
@@ -534,10 +536,10 @@ struct GetContainer {
 #define GET_CONTAINER(ltype)                                                                  \
     template <>                                                                               \
     struct GetContainer<ltype> {                                                              \
-        const auto& get_data(const Column* column) {                                          \
+        static const auto& get_data(const Column* column) {                                   \
             return ColumnHelper::as_raw_column<BinaryColumn>(column)->get_proxy_data();       \
         }                                                                                     \
-        const auto& get_data(const ColumnPtr& column) {                                       \
+        static const auto& get_data(const ColumnPtr& column) {                                \
             return ColumnHelper::as_raw_column<BinaryColumn>(column.get())->get_proxy_data(); \
         }                                                                                     \
     };
diff --git a/be/src/column/const_column.h b/be/src/column/const_column.h
index 6a2b27000b321c..4edd7449a9958b 100644
--- a/be/src/column/const_column.h
+++ b/be/src/column/const_column.h
@@ -18,6 +18,7 @@
 #include "column/datum.h"
 #include "column/vectorized_fwd.h"
 #include "common/logging.h"
+#include "gutil/strings/substitute.h"
 
 namespace starrocks {
 
@@ -251,15 +252,13 @@ class ConstColumn final : public ColumnFactory<Column, ConstColumn> {
         return ss.str();
     }
 
-    bool capacity_limit_reached(std::string* msg = nullptr) const override {
-        RETURN_IF_UNLIKELY(_data->capacity_limit_reached(msg), true);
+    Status capacity_limit_reached() const override {
+        RETURN_IF_ERROR(_data->capacity_limit_reached());
         if (_size > Column::MAX_CAPACITY_LIMIT) {
-            if (msg != nullptr) {
-                msg->append("Row count of const column reach limit: " + std::to_string(Column::MAX_CAPACITY_LIMIT));
-            }
-            return true;
+            return Status::CapacityLimitExceed(strings::Substitute("Row count of const column reach limit: $0",
+                                                                   std::to_string(Column::MAX_CAPACITY_LIMIT)));
         }
-        return false;
+        return Status::OK();
     }
 
     void check_or_die() const override;
diff --git a/be/src/column/field.h b/be/src/column/field.h
index 6203a4fda0f070..aa057db47648f6 100644
--- a/be/src/column/field.h
+++ b/be/src/column/field.h
@@ -29,22 +29,36 @@
 namespace starrocks {
 
 class Datum;
+class AggStateDesc;
 
 class Field {
 public:
     Field(ColumnId id, std::string_view name, TypeInfoPtr type, starrocks::StorageAggregateType agg,
-          uint8_t short_key_length, bool is_key, bool nullable)
+          AggStateDesc* agg_state_desc, uint8_t short_key_length, bool is_key, bool nullable)
             : _id(id),
               _agg_method(agg),
+              _agg_state_desc(agg_state_desc),
               _name(name),
               _type(std::move(type)),
               _sub_fields(nullptr),
               _short_key_length(short_key_length),
-              _flags(static_cast<uint8_t>((is_key << kIsKeyShift) | (nullable << kNullableShift))) {}
+              _flags(static_cast<uint8_t>((is_key << kIsKeyShift) | (nullable << kNullableShift))) {
+        if (_agg_method == STORAGE_AGGREGATE_AGG_STATE_UNION) {
+            DCHECK(_agg_state_desc != nullptr);
+        }
+    }
+
+    // AggMethod is not STORAGE_AGGREGATE_AGG_STATE_UNION
+    Field(ColumnId id, std::string_view name, TypeInfoPtr type, starrocks::StorageAggregateType agg,
+          uint8_t short_key_length, bool is_key, bool nullable)
+            : Field(id, name, std::move(type), agg, nullptr, short_key_length, is_key, nullable) {
+        DCHECK(_agg_method != STORAGE_AGGREGATE_AGG_STATE_UNION);
+    }
 
     // Non-key field of any type except for ARRAY
     Field(ColumnId id, std::string_view name, LogicalType type, int precision, int scale, bool nullable)
-            : Field(id, name, get_type_info(type, precision, scale), STORAGE_AGGREGATE_NONE, 0, false, nullable) {}
+            : Field(id, name, get_type_info(type, precision, scale), STORAGE_AGGREGATE_NONE, nullptr, 0, false,
+                    nullable) {}
 
     // Non-key field of any type except for DECIMAL32, DECIMAL64, DECIMAL128, and ARRAY
     Field(ColumnId id, std::string_view name, LogicalType type, bool nullable)
@@ -57,7 +71,7 @@ class Field {
 
     // Non-key field of any type
     Field(ColumnId id, std::string_view name, TypeInfoPtr type, bool nullable = true)
-            : Field(id, name, std::move(type), STORAGE_AGGREGATE_NONE, 0, false, nullable) {}
+            : Field(id, name, std::move(type), STORAGE_AGGREGATE_NONE, nullptr, 0, false, nullable) {}
 
     ~Field() { delete _sub_fields; }
 
@@ -66,6 +80,7 @@ class Field {
     Field(const Field& rhs)
             : _id(rhs._id),
               _agg_method(rhs._agg_method),
+              _agg_state_desc(rhs._agg_state_desc),
               _name(rhs._name),
               _type(rhs._type),
               _sub_fields(rhs._sub_fields ? new Buffer<Field>(*rhs._sub_fields) : nullptr),
@@ -76,6 +91,7 @@ class Field {
     Field(Field&& rhs) noexcept
             : _id(rhs._id),
               _agg_method(rhs._agg_method),
+              _agg_state_desc(rhs._agg_state_desc),
               _name(std::move(rhs._name)),
               _type(std::move(rhs._type)),
               _sub_fields(rhs._sub_fields),
@@ -92,6 +108,7 @@ class Field {
             _name = rhs._name;
             _type = rhs._type;
             _agg_method = rhs._agg_method;
+            _agg_state_desc = rhs._agg_state_desc;
             _short_key_length = rhs._short_key_length;
             _flags = rhs._flags;
             _sub_fields = rhs._sub_fields ? new Buffer<Field>(*rhs._sub_fields) : nullptr;
@@ -106,6 +123,7 @@ class Field {
             _name = std::move(rhs._name);
             _type = std::move(rhs._type);
             _agg_method = rhs._agg_method;
+            _agg_state_desc = rhs._agg_state_desc;
             _short_key_length = rhs._short_key_length;
             _flags = rhs._flags;
             _uid = rhs._uid;
@@ -171,6 +189,9 @@ class Field {
     void set_uid(ColumnUID uid) { _uid = uid; }
     const ColumnUID& uid() const { return _uid; }
 
+    void set_agg_state_desc(AggStateDesc* agg_state_desc) { _agg_state_desc = agg_state_desc; }
+    AggStateDesc* get_agg_state_desc() const { return _agg_state_desc; }
+
     static FieldPtr convert_to_dict_field(const Field& field);
 
 private:
@@ -179,6 +200,8 @@ class Field {
 
     ColumnId _id = 0;
     starrocks::StorageAggregateType _agg_method;
+    // agg_state_desc if agg_method is STORAGE_AGGREGATE_AGG_STATE_UNION
+    AggStateDesc* _agg_state_desc;
     CString _name;
     TypeInfoPtr _type = nullptr;
     std::vector<Field>* _sub_fields;
@@ -225,16 +248,17 @@ inline const Field& Field::sub_field(int i) const {
 
 inline FieldPtr Field::with_type(const TypeInfoPtr& type) {
     return std::make_shared<Field>(_id, std::string_view(_name.data(), _name.size()), type, _agg_method,
-                                   _short_key_length, is_key(), is_nullable());
+                                   _agg_state_desc, _short_key_length, is_key(), is_nullable());
 }
 
 inline FieldPtr Field::with_name(std::string_view name) {
-    return std::make_shared<Field>(_id, name, _type, _agg_method, _short_key_length, is_key(), is_nullable());
+    return std::make_shared<Field>(_id, name, _type, _agg_method, _agg_state_desc, _short_key_length, is_key(),
+                                   is_nullable());
 }
 
 inline FieldPtr Field::with_nullable(bool nullable) {
     return std::make_shared<Field>(_id, std::string_view(_name.data(), _name.size()), _type, _agg_method,
-                                   _short_key_length, is_key(), nullable);
+                                   _agg_state_desc, _short_key_length, is_key(), nullable);
 }
 
 inline std::ostream& operator<<(std::ostream& os, const Field& field) {
diff --git a/be/src/column/fixed_length_column_base.cpp b/be/src/column/fixed_length_column_base.cpp
index b29ab265f0e828..308feaa4ba2e13 100644
--- a/be/src/column/fixed_length_column_base.cpp
+++ b/be/src/column/fixed_length_column_base.cpp
@@ -29,11 +29,8 @@ namespace starrocks {
 
 template <typename T>
 StatusOr<ColumnPtr> FixedLengthColumnBase<T>::upgrade_if_overflow() {
-    if (capacity_limit_reached()) {
-        return Status::InternalError("Size of FixedLengthColumn exceed the limit");
-    } else {
-        return nullptr;
-    }
+    RETURN_IF_ERROR(capacity_limit_reached());
+    return nullptr;
 }
 
 template <typename T>
diff --git a/be/src/column/fixed_length_column_base.h b/be/src/column/fixed_length_column_base.h
index e976cce366da36..7ac5a17f5fd672 100644
--- a/be/src/column/fixed_length_column_base.h
+++ b/be/src/column/fixed_length_column_base.h
@@ -21,6 +21,7 @@
 #include "column/datum.h"
 #include "column/vectorized_fwd.h"
 #include "common/statusor.h"
+#include "gutil/strings/substitute.h"
 #include "runtime/decimalv2_value.h"
 #include "types/date_value.hpp"
 #include "types/timestamp_value.h"
@@ -236,15 +237,13 @@ class FixedLengthColumnBase : public ColumnFactory<Column, FixedLengthColumnBase
 
     // The `_data` support one size(> 2^32), but some interface such as update_rows() will use index of uint32_t to
     // access the item, so we should use 2^32 as the limit
-    bool capacity_limit_reached(std::string* msg = nullptr) const override {
+    Status capacity_limit_reached() const override {
         if (_data.size() > Column::MAX_CAPACITY_LIMIT) {
-            if (msg != nullptr) {
-                msg->append("row count of fixed length column exceend the limit: " +
-                            std::to_string(Column::MAX_CAPACITY_LIMIT));
-            }
-            return true;
+            return Status::CapacityLimitExceed(
+                    strings::Substitute("row count of fixed length column exceend the limit: $0",
+                                        std::to_string(Column::MAX_CAPACITY_LIMIT)));
         }
-        return false;
+        return Status::OK();
     }
 
     void check_or_die() const override {}
diff --git a/be/src/column/json_column.cpp b/be/src/column/json_column.cpp
index 46bdb2dc88f91c..f8841a1eec71ee 100644
--- a/be/src/column/json_column.cpp
+++ b/be/src/column/json_column.cpp
@@ -24,6 +24,7 @@
 #include "common/compiler_util.h"
 #include "glog/logging.h"
 #include "gutil/casts.h"
+#include "gutil/strings/substitute.h"
 #include "simd/simd.h"
 #include "types/logical_type.h"
 #include "util/hash_util.hpp"
@@ -430,14 +431,12 @@ void JsonColumn::reset_column() {
     _path_to_index.clear();
 }
 
-bool JsonColumn::capacity_limit_reached(std::string* msg) const {
+Status JsonColumn::capacity_limit_reached() const {
     if (size() > Column::MAX_CAPACITY_LIMIT) {
-        if (msg != nullptr) {
-            msg->append("row count of object column exceed the limit: " + std::to_string(Column::MAX_CAPACITY_LIMIT));
-        }
-        return true;
+        return Status::CapacityLimitExceed(strings::Substitute("row count of object column exceed the limit: $0",
+                                                               std::to_string(Column::MAX_CAPACITY_LIMIT)));
     }
-    return false;
+    return Status::OK();
 }
 
 void JsonColumn::check_or_die() const {
diff --git a/be/src/column/json_column.h b/be/src/column/json_column.h
index ca71de64940d16..935bb84333ed8c 100644
--- a/be/src/column/json_column.h
+++ b/be/src/column/json_column.h
@@ -101,7 +101,7 @@ class JsonColumn final : public ColumnFactory<ObjectColumn<JsonValue>, JsonColum
     void swap_column(Column& rhs) override;
     void reset_column() override;
 
-    bool capacity_limit_reached(std::string* msg = nullptr) const override;
+    Status capacity_limit_reached() const override;
     void check_or_die() const override;
 
     // support flat json on storage
diff --git a/be/src/column/map_column.h b/be/src/column/map_column.h
index 4617b225ff0741..15c3fd9a4e65a9 100644
--- a/be/src/column/map_column.h
+++ b/be/src/column/map_column.h
@@ -164,9 +164,10 @@ class MapColumn final : public ColumnFactory<Column, MapColumn> {
 
     std::string debug_string() const override;
 
-    bool capacity_limit_reached(std::string* msg = nullptr) const override {
-        return _keys->capacity_limit_reached(msg) || _values->capacity_limit_reached(msg) ||
-               _offsets->capacity_limit_reached(msg);
+    Status capacity_limit_reached() const override {
+        RETURN_IF_ERROR(_keys->capacity_limit_reached());
+        RETURN_IF_ERROR(_values->capacity_limit_reached());
+        return _offsets->capacity_limit_reached();
     }
 
     StatusOr<ColumnPtr> upgrade_if_overflow() override;
diff --git a/be/src/column/nullable_column.cpp b/be/src/column/nullable_column.cpp
index ae601bfe6d5245..0aae77ce4297ea 100644
--- a/be/src/column/nullable_column.cpp
+++ b/be/src/column/nullable_column.cpp
@@ -430,9 +430,7 @@ void NullableColumn::check_or_die() const {
 }
 
 StatusOr<ColumnPtr> NullableColumn::upgrade_if_overflow() {
-    if (_null_column->capacity_limit_reached()) {
-        return Status::InternalError("Size of NullableColumn exceed the limit");
-    }
+    RETURN_IF_ERROR(_null_column->capacity_limit_reached());
 
     return upgrade_helper_func(&_data_column);
 }
diff --git a/be/src/column/nullable_column.h b/be/src/column/nullable_column.h
index 3fa7f64dac2fbb..304f57a4d38f04 100644
--- a/be/src/column/nullable_column.h
+++ b/be/src/column/nullable_column.h
@@ -311,8 +311,9 @@ class NullableColumn : public ColumnFactory<Column, NullableColumn> {
         return ss.str();
     }
 
-    bool capacity_limit_reached(std::string* msg = nullptr) const override {
-        return _data_column->capacity_limit_reached(msg) || _null_column->capacity_limit_reached(msg);
+    Status capacity_limit_reached() const override {
+        RETURN_IF_ERROR(_data_column->capacity_limit_reached());
+        return _null_column->capacity_limit_reached();
     }
 
     void check_or_die() const override;
diff --git a/be/src/column/object_column.cpp b/be/src/column/object_column.cpp
index da13ca585a30ec..3e3b061d1666b7 100644
--- a/be/src/column/object_column.cpp
+++ b/be/src/column/object_column.cpp
@@ -328,9 +328,7 @@ std::string ObjectColumn<BitmapValue>::debug_item(size_t idx) const {
 
 template <typename T>
 StatusOr<ColumnPtr> ObjectColumn<T>::upgrade_if_overflow() {
-    if (capacity_limit_reached()) {
-        return Status::InternalError("Size of ObjectColumn exceed the limit");
-    }
+    RETURN_IF_ERROR(capacity_limit_reached());
     return nullptr;
 }
 
diff --git a/be/src/column/object_column.h b/be/src/column/object_column.h
index 25ec0e851ecc73..482b68ec7f1a02 100644
--- a/be/src/column/object_column.h
+++ b/be/src/column/object_column.h
@@ -20,6 +20,7 @@
 #include "column/datum.h"
 #include "column/vectorized_fwd.h"
 #include "common/object_pool.h"
+#include "gutil/strings/substitute.h"
 #include "types/bitmap_value.h"
 #include "types/hll.h"
 #include "util/json.h"
@@ -213,15 +214,12 @@ class ObjectColumn : public ColumnFactory<Column, ObjectColumn<T>> {
         return ss.str();
     }
 
-    bool capacity_limit_reached(std::string* msg = nullptr) const override {
+    Status capacity_limit_reached() const override {
         if (_pool.size() > Column::MAX_CAPACITY_LIMIT) {
-            if (msg != nullptr) {
-                msg->append("row count of object column exceed the limit: " +
-                            std::to_string(Column::MAX_CAPACITY_LIMIT));
-            }
-            return true;
+            return Status::CapacityLimitExceed(strings::Substitute("row count of object column exceed the limit: $0",
+                                                                   std::to_string(Column::MAX_CAPACITY_LIMIT)));
         }
-        return false;
+        return Status::OK();
     }
 
     StatusOr<ColumnPtr> upgrade_if_overflow() override;
@@ -230,7 +228,7 @@ class ObjectColumn : public ColumnFactory<Column, ObjectColumn<T>> {
 
     bool has_large_column() const override { return false; }
 
-    void check_or_die() const {}
+    void check_or_die() const override {}
 
 private:
     // add this to avoid warning clang-diagnostic-overloaded-virtual
diff --git a/be/src/column/struct_column.cpp b/be/src/column/struct_column.cpp
index a921e0ed147368..a1482d5ef2cf86 100644
--- a/be/src/column/struct_column.cpp
+++ b/be/src/column/struct_column.cpp
@@ -447,12 +447,11 @@ void StructColumn::swap_column(Column& rhs) {
     // _field_names dont need swap
 }
 
-bool StructColumn::capacity_limit_reached(std::string* msg) const {
-    bool res = false;
+Status StructColumn::capacity_limit_reached() const {
     for (const auto& column : _fields) {
-        res = res || column->capacity_limit_reached(msg);
+        RETURN_IF_ERROR(column->capacity_limit_reached());
     }
-    return res;
+    return Status::OK();
 }
 
 void StructColumn::check_or_die() const {
diff --git a/be/src/column/struct_column.h b/be/src/column/struct_column.h
index 77532683cc7a44..1bf73ceba349bc 100644
--- a/be/src/column/struct_column.h
+++ b/be/src/column/struct_column.h
@@ -171,7 +171,7 @@ class StructColumn final : public ColumnFactory<Column, StructColumn> {
 
     void reset_column() override;
 
-    bool capacity_limit_reached(std::string* msg = nullptr) const override;
+    Status capacity_limit_reached() const override;
 
     void check_or_die() const override;
 
diff --git a/be/src/common/config.h b/be/src/common/config.h
index 308873f7127be1..0dce0fee0901fd 100644
--- a/be/src/common/config.h
+++ b/be/src/common/config.h
@@ -1251,6 +1251,8 @@ CONF_String(rocksdb_db_options_string, "create_if_missing=true;create_missing_co
 CONF_Int64(local_exchange_buffer_mem_limit_per_driver, "134217728"); // 128MB
 // only used for test. default: 128M
 CONF_mInt64(streaming_agg_limited_memory_size, "134217728");
+// mem limit for partition hash join probe side buffer
+CONF_mInt64(partition_hash_join_probe_limit_size, "134217728");
 // pipeline streaming aggregate chunk buffer size
 CONF_mInt32(streaming_agg_chunk_buffer_size, "1024");
 CONF_mInt64(wait_apply_time, "6000"); // 6s
@@ -1297,7 +1299,7 @@ CONF_mInt32(finish_publish_version_internal, "100");
 
 CONF_mBool(enable_stream_load_verbose_log, "false");
 
-CONF_mInt32(get_txn_status_internal_sec, "30");
+CONF_mInt32(get_txn_status_internal_sec, "10");
 
 CONF_mBool(dump_metrics_with_bvar, "true");
 
@@ -1375,10 +1377,6 @@ CONF_mDouble(connector_sink_mem_urgent_space_ratio, "0.1");
 // .crm file can be removed after 1day.
 CONF_mInt32(unused_crm_file_threshold_second, "86400" /** 1day **/);
 
-// When the keys that we want to delete, number of them is larger than this config,
-// we will fallback and using `DeleteRange` in rocksdb.
-CONF_mInt32(rocksdb_opt_delete_range_limit, "500");
-
 // python envs config
 // create time worker timeout
 CONF_mInt32(create_child_worker_timeout_ms, "1000");
diff --git a/be/src/connector/lake_connector.cpp b/be/src/connector/lake_connector.cpp
index 4ebf6cabfd77fd..62344602785635 100644
--- a/be/src/connector/lake_connector.cpp
+++ b/be/src/connector/lake_connector.cpp
@@ -591,7 +591,6 @@ void LakeDataSource::init_counter(RuntimeState* state) {
     _prefetch_wait_finish_timer = ADD_CHILD_TIMER(_runtime_profile, "PrefetchWaitFinishTime", io_statistics_name);
     _prefetch_pending_timer = ADD_CHILD_TIMER(_runtime_profile, "PrefetchPendingTime", io_statistics_name);
 
-    _json_flatten_timer = ADD_CHILD_TIMER(_runtime_profile, "JsonFlattern", segment_read_name);
     _access_path_hits_counter = ADD_COUNTER(_runtime_profile, "AccessPathHits", TUnit::UNIT);
     _access_path_unhits_counter = ADD_COUNTER(_runtime_profile, "AccessPathUnhits", TUnit::UNIT);
 }
@@ -723,17 +722,19 @@ void LakeDataSource::update_counter() {
         std::string access_path_hits = "AccessPathHits";
         int64_t total = 0;
         for (auto& [k, v] : _reader->stats().flat_json_hits) {
-            auto* path_counter = _runtime_profile->get_counter(fmt::format("[Hit]{}", k));
+            std::string path = fmt::format("[Hit]{}", k);
+            auto* path_counter = _runtime_profile->get_counter(path);
             if (path_counter == nullptr) {
-                path_counter = ADD_CHILD_COUNTER(_runtime_profile, k, TUnit::UNIT, access_path_hits);
+                path_counter = ADD_CHILD_COUNTER(_runtime_profile, path, TUnit::UNIT, access_path_hits);
             }
             total += v;
             COUNTER_UPDATE(path_counter, v);
         }
         for (auto& [k, v] : _reader->stats().merge_json_hits) {
-            auto* path_counter = _runtime_profile->get_counter(fmt::format("[HitMerge]{}", k));
+            std::string merge_path = fmt::format("[HitMerge]{}", k);
+            auto* path_counter = _runtime_profile->get_counter(merge_path);
             if (path_counter == nullptr) {
-                path_counter = ADD_CHILD_COUNTER(_runtime_profile, k, TUnit::UNIT, access_path_hits);
+                path_counter = ADD_CHILD_COUNTER(_runtime_profile, merge_path, TUnit::UNIT, access_path_hits);
             }
             total += v;
             COUNTER_UPDATE(path_counter, v);
@@ -744,9 +745,10 @@ void LakeDataSource::update_counter() {
         std::string access_path_unhits = "AccessPathUnhits";
         int64_t total = 0;
         for (auto& [k, v] : _reader->stats().dynamic_json_hits) {
-            auto* path_counter = _runtime_profile->get_counter(fmt::format("[Unhit]{}", k));
+            std::string path = fmt::format("[Unhit]{}", k);
+            auto* path_counter = _runtime_profile->get_counter(path);
             if (path_counter == nullptr) {
-                path_counter = ADD_CHILD_COUNTER(_runtime_profile, k, TUnit::UNIT, access_path_unhits);
+                path_counter = ADD_CHILD_COUNTER(_runtime_profile, path, TUnit::UNIT, access_path_unhits);
             }
             total += v;
             COUNTER_UPDATE(path_counter, v);
@@ -754,7 +756,23 @@ void LakeDataSource::update_counter() {
         COUNTER_UPDATE(_access_path_unhits_counter, total);
     }
 
-    COUNTER_UPDATE(_json_flatten_timer, _reader->stats().json_flatten_ns);
+    std::string parent_name = "SegmentRead";
+    if (_reader->stats().json_init_ns > 0) {
+        RuntimeProfile::Counter* c = ADD_CHILD_TIMER(_runtime_profile, "FlatJsonInit", parent_name);
+        COUNTER_UPDATE(c, _reader->stats().json_init_ns);
+    }
+    if (_reader->stats().json_cast_ns > 0) {
+        RuntimeProfile::Counter* c = ADD_CHILD_TIMER(_runtime_profile, "FlatJsonCast", parent_name);
+        COUNTER_UPDATE(c, _reader->stats().json_cast_ns);
+    }
+    if (_reader->stats().json_merge_ns > 0) {
+        RuntimeProfile::Counter* c = ADD_CHILD_TIMER(_runtime_profile, "FlatJsonMerge", parent_name);
+        COUNTER_UPDATE(c, _reader->stats().json_merge_ns);
+    }
+    if (_reader->stats().json_flatten_ns > 0) {
+        RuntimeProfile::Counter* c = ADD_CHILD_TIMER(_runtime_profile, "FlatJsonFlatten", parent_name);
+        COUNTER_UPDATE(c, _reader->stats().json_flatten_ns);
+    }
 }
 
 // ================================
diff --git a/be/src/connector/lake_connector.h b/be/src/connector/lake_connector.h
index a89ae49c8983b1..b946b7a1f4886e 100644
--- a/be/src/connector/lake_connector.h
+++ b/be/src/connector/lake_connector.h
@@ -181,7 +181,6 @@ class LakeDataSource final : public DataSource {
     RuntimeProfile::Counter* _prefetch_pending_timer = nullptr;
 
     RuntimeProfile::Counter* _pushdown_access_paths_counter = nullptr;
-    RuntimeProfile::Counter* _json_flatten_timer = nullptr;
     RuntimeProfile::Counter* _access_path_hits_counter = nullptr;
     RuntimeProfile::Counter* _access_path_unhits_counter = nullptr;
 };
diff --git a/be/src/exec/aggregator.cpp b/be/src/exec/aggregator.cpp
index 8564a05174c02e..999ffbdfaa92b7 100644
--- a/be/src/exec/aggregator.cpp
+++ b/be/src/exec/aggregator.cpp
@@ -203,20 +203,6 @@ void AggregatorParams::init() {
 #define ALIGN_TO(size, align) ((size + align - 1) / align * align)
 #define PAD(size, align) (align - (size % align)) % align;
 
-class ThreadLocalStateAllocatorSetter {
-public:
-    ThreadLocalStateAllocatorSetter(Allocator* allocator)
-            : _agg_state_allocator_setter(allocator), _roaring_allocator_setter(allocator) {}
-    ~ThreadLocalStateAllocatorSetter() = default;
-
-private:
-    ThreadLocalAggregateStateAllocatorSetter _agg_state_allocator_setter;
-    ThreadLocalRoaringAllocatorSetter _roaring_allocator_setter;
-};
-
-#define SCOPED_THREAD_LOCAL_STATE_ALLOCATOR_SETTER(allocator) \
-    auto VARNAME_LINENUM(alloc_setter) = ThreadLocalStateAllocatorSetter(allocator)
-
 Aggregator::Aggregator(AggregatorParamsPtr params) : _params(std::move(params)) {
     _allocator = std::make_unique<CountingAllocatorWithHook>();
 }
@@ -395,59 +381,22 @@ Status Aggregator::prepare(RuntimeState* state, ObjectPool* pool, RuntimeProfile
         const TFunction& fn = desc.nodes[0].fn;
         const auto& agg_fn_type = _agg_fn_types[i];
         _is_merge_funcs[i] = aggregate_functions[i].nodes[0].agg_expr.is_merge_agg;
-        // get function
-        if (fn.name.function_name == "count") {
-            bool is_input_nullable =
-                    !fn.arg_types.empty() && (has_outer_join_child || desc.nodes[0].has_nullable_child);
-            auto* func = get_aggregate_function("count", TYPE_BIGINT, TYPE_BIGINT, is_input_nullable);
-            _agg_functions[i] = func;
-        } else {
-            TypeDescriptor return_type = TypeDescriptor::from_thrift(fn.ret_type);
-            TypeDescriptor serde_type = TypeDescriptor::from_thrift(fn.aggregate_fn.intermediate_type);
 
-            TypeDescriptor arg_type = TypeDescriptor::from_thrift(fn.arg_types[0]);
-            // Because intersect_count have two input types.
-            // And intersect_count's first argument's type is alwasy Bitmap,
-            // so we use its second arguments type as input.
-            if (fn.name.function_name == "intersect_count") {
-                arg_type = TypeDescriptor::from_thrift(fn.arg_types[1]);
-            }
-
-            // Because max_by and min_by function have two input types,
-            // so we use its second arguments type as input.
-            if (fn.name.function_name == "max_by" || fn.name.function_name == "min_by") {
-                arg_type = TypeDescriptor::from_thrift(fn.arg_types[1]);
-            }
-
-            // Because windowfunnel have more two input types.
-            // functions registry use 2th args(datetime/date).
-            if (fn.name.function_name == "window_funnel") {
-                arg_type = TypeDescriptor::from_thrift(fn.arg_types[1]);
-            }
-
-            // hack for accepting various arguments
-            if (fn.name.function_name == "exchange_bytes" || fn.name.function_name == "exchange_speed") {
-                arg_type = TypeDescriptor(TYPE_BIGINT);
-            }
-
-            if (fn.name.function_name == "array_union_agg" || fn.name.function_name == "array_unique_agg") {
-                // for array_union_agg use inner type as signature
-                arg_type = arg_type.children[0];
-            }
-
-            const bool use_nullable_fn = agg_fn_type.use_nullable_fn(_use_intermediate_as_output());
-            auto* func = get_aggregate_function(fn.name.function_name, arg_type.type, return_type.type, use_nullable_fn,
-                                                fn.binary_type, state->func_version());
-            if (func == nullptr) {
-                return Status::InternalError(strings::Substitute(
-                        "Invalid agg function plan: $0 with (arg type $1, serde type $2, result type $3, nullable $4)",
-                        fn.name.function_name, type_to_string(arg_type.type), type_to_string(serde_type.type),
-                        type_to_string(return_type.type), use_nullable_fn ? "true" : "false"));
+        // get function
+        auto is_result_nullable_func = [&]() {
+            if (fn.name.function_name == "count") {
+                if (fn.arg_types.empty()) {
+                    return false;
+                }
+                if (has_outer_join_child || desc.nodes[0].has_nullable_child) {
+                    return true;
+                }
+                return false;
+            } else {
+                return agg_fn_type.use_nullable_fn(_use_intermediate_as_output());
             }
-            VLOG_ROW << "get agg function " << func->get_name() << " serde_type " << serde_type << " return_type "
-                     << return_type;
-            _agg_functions[i] = func;
-        }
+        };
+        RETURN_IF_ERROR(_create_aggregate_function(state, fn, is_result_nullable_func(), &_agg_functions[i]));
 
         int node_idx = 0;
         for (int j = 0; j < desc.nodes[0].num_children; ++j) {
@@ -530,6 +479,42 @@ Status Aggregator::prepare(RuntimeState* state, ObjectPool* pool, RuntimeProfile
     return Status::OK();
 }
 
+Status Aggregator::_create_aggregate_function(starrocks::RuntimeState* state, const TFunction& fn,
+                                              bool is_result_nullable, const AggregateFunction** ret) {
+    std::vector<TypeDescriptor> arg_types;
+    for (auto& type : fn.arg_types) {
+        arg_types.push_back(TypeDescriptor::from_thrift(type));
+    }
+
+    // check whether it's _merge/_union combinator if it contains agg state type
+    auto& func_name = fn.name.function_name;
+    // get function
+    if (func_name == "count") {
+        auto* func = get_aggregate_function("count", TYPE_BIGINT, TYPE_BIGINT, is_result_nullable);
+        if (func == nullptr) {
+            return Status::InternalError(strings::Substitute("Invalid agg function plan: $0 ", func_name));
+        }
+        *ret = func;
+    } else {
+        TypeDescriptor return_type = TypeDescriptor::from_thrift(fn.ret_type);
+        TypeDescriptor serde_type = TypeDescriptor::from_thrift(fn.aggregate_fn.intermediate_type);
+        DCHECK_LE(1, fn.arg_types.size());
+        TypeDescriptor arg_type = arg_types[0];
+        auto* func = get_aggregate_function(func_name, return_type, arg_types, is_result_nullable, fn.binary_type,
+                                            state->func_version());
+        if (func == nullptr) {
+            return Status::InternalError(strings::Substitute(
+                    "Invalid agg function plan: $0 with (arg type $1, serde type $2, result type $3, nullable $4)",
+                    func_name, type_to_string(arg_type.type), type_to_string(serde_type.type),
+                    type_to_string(return_type.type), is_result_nullable ? "true" : "false"));
+        }
+        *ret = func;
+        VLOG_ROW << "get agg function " << func->get_name() << " serde_type " << serde_type << " return_type "
+                 << return_type;
+    }
+    return Status::OK();
+}
+
 Status Aggregator::reset_state(starrocks::RuntimeState* state, const std::vector<ChunkPtr>& refill_chunks,
                                pipeline::Operator* refill_op, bool reset_sink_complete) {
     RETURN_IF_ERROR(_reset_state(state, reset_sink_complete));
diff --git a/be/src/exec/aggregator.h b/be/src/exec/aggregator.h
index 2de2c183a7c935..da78d1f036038e 100644
--- a/be/src/exec/aggregator.h
+++ b/be/src/exec/aggregator.h
@@ -400,6 +400,9 @@ class Aggregator : public pipeline::ContextWithDependency {
 
     bool is_streaming_all_states() const { return _streaming_all_states; }
 
+    Status _create_aggregate_function(starrocks::RuntimeState* state, const TFunction& fn, bool is_result_nullable,
+                                      const AggregateFunction** ret);
+
     HashTableKeyAllocator _state_allocator;
 
 protected:
diff --git a/be/src/exec/analytor.cpp b/be/src/exec/analytor.cpp
index b4ee5c87d60c01..95a273d8250222 100644
--- a/be/src/exec/analytor.cpp
+++ b/be/src/exec/analytor.cpp
@@ -586,13 +586,6 @@ Status Analytor::_add_chunk(const ChunkPtr& chunk) {
     const size_t chunk_size = chunk->num_rows();
 
     {
-        auto check_if_overflow = [](Column* column) {
-            std::string msg;
-            if (column->capacity_limit_reached(&msg)) {
-                return Status::InternalError(msg);
-            }
-            return Status::OK();
-        };
         SCOPED_TIMER(_column_resize_timer);
         for (size_t i = 0; i < _agg_fn_ctxs.size(); i++) {
             for (size_t j = 0; j < _agg_expr_ctxs[i].size(); j++) {
@@ -601,20 +594,20 @@ Status Analytor::_add_chunk(const ChunkPtr& chunk) {
                 // When chunk's column is const, maybe need to unpack it.
                 TRY_CATCH_BAD_ALLOC(_append_column(chunk_size, _agg_intput_columns[i][j].get(), column));
 
-                RETURN_IF_ERROR(check_if_overflow(_agg_intput_columns[i][j].get()));
+                RETURN_IF_ERROR(_agg_intput_columns[i][j]->capacity_limit_reached());
             }
         }
 
         for (size_t i = 0; i < _partition_ctxs.size(); i++) {
             ASSIGN_OR_RETURN(ColumnPtr column, _partition_ctxs[i]->evaluate(chunk.get()));
             TRY_CATCH_BAD_ALLOC(_append_column(chunk_size, _partition_columns[i].get(), column));
-            RETURN_IF_ERROR(check_if_overflow(_partition_columns[i].get()));
+            RETURN_IF_ERROR(_partition_columns[i]->capacity_limit_reached());
         }
 
         for (size_t i = 0; i < _order_ctxs.size(); i++) {
             ASSIGN_OR_RETURN(ColumnPtr column, _order_ctxs[i]->evaluate(chunk.get()));
             TRY_CATCH_BAD_ALLOC(_append_column(chunk_size, _order_columns[i].get(), column));
-            RETURN_IF_ERROR(check_if_overflow(_order_columns[i].get()));
+            RETURN_IF_ERROR(_order_columns[i]->capacity_limit_reached());
         }
     }
 
diff --git a/be/src/exec/hash_join_components.cpp b/be/src/exec/hash_join_components.cpp
index b7755416f7f895..86991a632c1058 100644
--- a/be/src/exec/hash_join_components.cpp
+++ b/be/src/exec/hash_join_components.cpp
@@ -14,12 +14,23 @@
 
 #include "exec/hash_join_components.h"
 
+#include <deque>
 #include <memory>
+#include <numeric>
 
 #include "column/vectorized_fwd.h"
+#include "common/config.h"
+#include "common/logging.h"
+#include "common/object_pool.h"
 #include "exec/hash_joiner.h"
 #include "exec/join_hash_map.h"
+#include "exprs/agg/distinct.h"
+#include "exprs/expr_context.h"
 #include "gutil/casts.h"
+#include "runtime/descriptors.h"
+#include "runtime/mem_tracker.h"
+#include "util/cpu_info.h"
+#include "util/runtime_profile.h"
 
 namespace starrocks {
 
@@ -28,12 +39,16 @@ class SingleHashJoinProberImpl final : public HashJoinProberImpl {
     SingleHashJoinProberImpl(HashJoiner& hash_joiner) : HashJoinProberImpl(hash_joiner) {}
     ~SingleHashJoinProberImpl() override = default;
     bool probe_chunk_empty() const override { return _probe_chunk == nullptr; }
+    Status on_input_finished(RuntimeState* state) override { return Status::OK(); }
     Status push_probe_chunk(RuntimeState* state, ChunkPtr&& chunk) override;
     StatusOr<ChunkPtr> probe_chunk(RuntimeState* state) override;
     StatusOr<ChunkPtr> probe_remain(RuntimeState* state, bool* has_remain) override;
-    void reset() override {
+    void reset(RuntimeState* runtime_state) override {
         _probe_chunk.reset();
         _current_probe_has_remain = false;
+        if (_hash_table != nullptr) {
+            _hash_table->reset_probe_state(runtime_state);
+        }
     }
     void set_ht(JoinHashTable* hash_table) { _hash_table = hash_table; }
 
@@ -85,6 +100,241 @@ void HashJoinProber::attach(HashJoinBuilder* builder, const HashJoinProbeMetrics
     _impl = builder->create_prober();
 }
 
+class PartitionChunkChannel {
+public:
+    PartitionChunkChannel(MemTracker* tracker) : _tracker(tracker) {}
+    bool processing() const { return _processing; }
+    void set_processing(bool processing) { _processing = processing; }
+
+    ChunkPtr pull() {
+        auto chunk = std::move(_chunks.front());
+        _tracker->release(chunk->memory_usage());
+        _chunks.pop_front();
+        return chunk;
+    }
+
+    void push(ChunkPtr&& chunk) {
+        _tracker->consume(chunk->memory_usage());
+        _chunks.emplace_back(std::move(chunk));
+    }
+
+    const ChunkPtr& back() { return _chunks.back(); }
+
+    bool is_full() const {
+        return _chunks.size() >= 4 || _tracker->consumption() > config::partition_hash_join_probe_limit_size;
+    }
+
+    size_t size() const { return _chunks.size(); }
+
+    bool is_empty() const { return _chunks.empty() || _chunks.front()->is_empty(); }
+
+    bool not_empty() const { return !is_empty(); }
+
+private:
+    MemTracker* _tracker;
+    std::deque<ChunkPtr> _chunks;
+    bool _processing = false;
+};
+
+class PartitionedHashJoinProberImpl final : public HashJoinProberImpl {
+public:
+    PartitionedHashJoinProberImpl(HashJoiner& hash_joiner) : HashJoinProberImpl(hash_joiner) {}
+    ~PartitionedHashJoinProberImpl() override = default;
+    bool probe_chunk_empty() const override;
+    Status on_input_finished(RuntimeState* state) override;
+    Status push_probe_chunk(RuntimeState* state, ChunkPtr&& chunk) override;
+    StatusOr<ChunkPtr> probe_chunk(RuntimeState* state) override;
+    StatusOr<ChunkPtr> probe_remain(RuntimeState* state, bool* has_remain) override;
+    void reset(RuntimeState* runtime_state) override;
+    void set_probers(std::vector<std::unique_ptr<SingleHashJoinProberImpl>>&& probers) {
+        _probers = std::move(probers);
+        _partition_input_channels.resize(_probers.size(), PartitionChunkChannel(&_mem_tracker));
+    }
+
+private:
+    MemTracker _mem_tracker;
+    bool _all_input_finished = false;
+    int32_t _remain_partition_idx = 0;
+    std::vector<std::unique_ptr<SingleHashJoinProberImpl>> _probers;
+    std::vector<PartitionChunkChannel> _partition_input_channels;
+};
+
+bool PartitionedHashJoinProberImpl::probe_chunk_empty() const {
+    auto& probers = _probers;
+    size_t num_partitions = probers.size();
+
+    if (!_all_input_finished) {
+        for (size_t i = 0; i < num_partitions; ++i) {
+            if (!probers[i]->probe_chunk_empty() || _partition_input_channels[i].processing()) {
+                return false;
+            }
+        }
+    } else {
+        for (size_t i = 0; i < num_partitions; ++i) {
+            if (!probers[i]->probe_chunk_empty() || _partition_input_channels[i].not_empty()) {
+                return false;
+            }
+        }
+    }
+
+    return true;
+}
+
+Status PartitionedHashJoinProberImpl::on_input_finished(RuntimeState* runtime_state) {
+    SCOPED_TIMER(_hash_joiner.probe_metrics().partition_probe_overhead);
+    _all_input_finished = true;
+    auto& probers = _probers;
+    size_t num_partitions = probers.size();
+
+    for (size_t i = 0; i < num_partitions; ++i) {
+        if (_partition_input_channels[i].is_empty()) {
+            continue;
+        }
+        if (!probers[i]->probe_chunk_empty()) {
+            continue;
+        }
+        RETURN_IF_ERROR(probers[i]->push_probe_chunk(runtime_state, _partition_input_channels[i].pull()));
+    }
+    return Status::OK();
+}
+
+Status PartitionedHashJoinProberImpl::push_probe_chunk(RuntimeState* state, ChunkPtr&& chunk) {
+    SCOPED_TIMER(_hash_joiner.probe_metrics().partition_probe_overhead);
+    auto& probers = _probers;
+    auto& partition_keys = _hash_joiner.probe_expr_ctxs();
+
+    size_t num_rows = chunk->num_rows();
+    size_t num_partitions = probers.size();
+    size_t num_partition_cols = partition_keys.size();
+
+    std::vector<ColumnPtr> partition_columns(num_partition_cols);
+    for (size_t i = 0; i < num_partition_cols; ++i) {
+        ASSIGN_OR_RETURN(partition_columns[i], partition_keys[i]->evaluate(chunk.get()));
+    }
+    std::vector<uint32_t> hash_values;
+    {
+        hash_values.assign(num_rows, HashUtil::FNV_SEED);
+
+        for (const ColumnPtr& column : partition_columns) {
+            column->fnv_hash(hash_values.data(), 0, num_rows);
+        }
+        // find partition id
+        for (size_t i = 0; i < hash_values.size(); ++i) {
+            hash_values[i] = HashUtil::fmix32(hash_values[i]) & (num_partitions - 1);
+        }
+    }
+
+    const auto& partitions = hash_values;
+
+    std::vector<uint32_t> selection;
+    selection.resize(chunk->num_rows());
+
+    std::vector<int32_t> channel_row_idx_start_points;
+    channel_row_idx_start_points.assign(num_partitions + 1, 0);
+
+    for (uint32_t i : partitions) {
+        channel_row_idx_start_points[i]++;
+    }
+
+    for (int32_t i = 1; i <= channel_row_idx_start_points.size() - 1; ++i) {
+        channel_row_idx_start_points[i] += channel_row_idx_start_points[i - 1];
+    }
+
+    for (int32_t i = chunk->num_rows() - 1; i >= 0; --i) {
+        selection[channel_row_idx_start_points[partitions[i]] - 1] = i;
+        channel_row_idx_start_points[partitions[i]]--;
+    }
+    _partition_input_channels.resize(num_partitions, PartitionChunkChannel(&_mem_tracker));
+
+    for (size_t i = 0; i < num_partitions; ++i) {
+        auto from = channel_row_idx_start_points[i];
+        auto size = channel_row_idx_start_points[i + 1] - from;
+        if (size == 0) {
+            continue;
+        }
+
+        if (_partition_input_channels[i].is_empty()) {
+            _partition_input_channels[i].push(chunk->clone_empty());
+        }
+
+        if (_partition_input_channels[i].back()->num_rows() + size <= 4096) {
+            _partition_input_channels[i].back()->append_selective(*chunk, selection.data(), from, size);
+        } else {
+            _partition_input_channels[i].push(chunk->clone_empty());
+            _partition_input_channels[i].back()->append_selective(*chunk, selection.data(), from, size);
+        }
+
+        if (_partition_input_channels[i].is_full()) {
+            _partition_input_channels[i].set_processing(true);
+            RETURN_IF_ERROR(probers[i]->push_probe_chunk(state, _partition_input_channels[i].pull()));
+        }
+    }
+
+    return Status::OK();
+}
+
+StatusOr<ChunkPtr> PartitionedHashJoinProberImpl::probe_chunk(RuntimeState* state) {
+    auto& probers = _probers;
+    size_t num_partitions = probers.size();
+    if (_all_input_finished) {
+        for (size_t i = 0; i < num_partitions; ++i) {
+            if (probers[i]->probe_chunk_empty() && _partition_input_channels[i].is_empty()) {
+                continue;
+            }
+            if (probers[i]->probe_chunk_empty()) {
+                RETURN_IF_ERROR(probers[i]->push_probe_chunk(state, _partition_input_channels[i].pull()));
+            }
+            auto chunk = std::make_shared<Chunk>();
+            ASSIGN_OR_RETURN(chunk, probers[i]->probe_chunk(state))
+            return chunk;
+        }
+    } else {
+        for (size_t i = 0; i < num_partitions; ++i) {
+            if (probers[i]->probe_chunk_empty() && !_partition_input_channels[i].processing()) {
+                continue;
+            }
+            if (probers[i]->probe_chunk_empty()) {
+                RETURN_IF_ERROR(probers[i]->push_probe_chunk(state, _partition_input_channels[i].pull()));
+            }
+            _partition_input_channels[i].set_processing(_partition_input_channels[i].size() > 1);
+            auto chunk = std::make_shared<Chunk>();
+            ASSIGN_OR_RETURN(chunk, probers[i]->probe_chunk(state))
+            return chunk;
+        }
+    }
+    CHECK(false);
+
+    return nullptr;
+}
+
+StatusOr<ChunkPtr> PartitionedHashJoinProberImpl::probe_remain(RuntimeState* state, bool* has_remain) {
+    auto& probers = _probers;
+    size_t num_partitions = probers.size();
+    while (_remain_partition_idx < num_partitions) {
+        auto chunk = std::make_shared<Chunk>();
+        bool sub_map_has_remain = false;
+        ASSIGN_OR_RETURN(chunk, probers[_remain_partition_idx]->probe_remain(state, &sub_map_has_remain));
+        if (!sub_map_has_remain) {
+            _remain_partition_idx++;
+        }
+        if (chunk->is_empty()) {
+            continue;
+        }
+        *has_remain = true;
+        return chunk;
+    }
+
+    *has_remain = false;
+    return nullptr;
+}
+
+void PartitionedHashJoinProberImpl::reset(RuntimeState* runtime_state) {
+    _probers.clear();
+    _partition_input_channels.clear();
+    _all_input_finished = false;
+    _remain_partition_idx = 0;
+}
+
 void SingleHashJoinBuilder::create(const HashTableParam& param) {
     _ht.create(param);
 }
@@ -99,11 +349,6 @@ void SingleHashJoinBuilder::reset(const HashTableParam& param) {
     create(param);
 }
 
-void SingleHashJoinBuilder::reset_probe(RuntimeState* state) {
-    _key_columns.clear();
-    _ht.reset_probe_state(state);
-}
-
 bool SingleHashJoinBuilder::anti_join_key_column_has_null() const {
     if (_ht.get_key_columns().size() != 1) {
         return false;
@@ -155,4 +400,388 @@ ChunkPtr SingleHashJoinBuilder::convert_to_spill_schema(const ChunkPtr& chunk) c
     return _ht.convert_to_spill_schema(chunk);
 }
 
+enum class CacheLevel { L2, L3, MEMORY };
+
+class AdaptivePartitionHashJoinBuilder final : public HashJoinBuilder {
+public:
+    AdaptivePartitionHashJoinBuilder(HashJoiner& hash_joiner);
+    ~AdaptivePartitionHashJoinBuilder() override = default;
+
+    void create(const HashTableParam& param) override;
+
+    void close() override;
+
+    void reset(const HashTableParam& param) override;
+
+    Status do_append_chunk(const ChunkPtr& chunk) override;
+
+    Status build(RuntimeState* state) override;
+
+    bool anti_join_key_column_has_null() const override;
+
+    int64_t ht_mem_usage() const override;
+
+    void get_build_info(size_t* bucket_size, float* avg_keys_per_bucket) override;
+
+    size_t get_output_probe_column_count() const override;
+    size_t get_output_build_column_count() const override;
+
+    void visitHt(const std::function<void(JoinHashTable*)>& visitor) override;
+
+    std::unique_ptr<HashJoinProberImpl> create_prober() override;
+
+    void clone_readable(HashJoinBuilder* builder) override;
+
+    ChunkPtr convert_to_spill_schema(const ChunkPtr& chunk) const override;
+
+private:
+    size_t _estimated_row_size(const HashTableParam& param) const;
+    size_t _estimated_probe_cost(const HashTableParam& param) const;
+    template <CacheLevel T>
+    size_t _estimated_build_cost(size_t build_row_size) const;
+    void _adjust_partition_rows(size_t build_row_size);
+
+    void _init_partition_nums(const HashTableParam& param);
+    Status _convert_to_single_partition();
+    Status _append_chunk_to_partitions(const ChunkPtr& chunk);
+
+private:
+    std::vector<std::unique_ptr<SingleHashJoinBuilder>> _builders;
+
+    size_t _partition_num = 0;
+    size_t _partition_join_min_rows = 0;
+    size_t _partition_join_max_rows = 0;
+
+    size_t _probe_estimated_costs = 0;
+
+    size_t _fit_L2_cache_max_rows = 0;
+    size_t _fit_L3_cache_max_rows = 0;
+
+    size_t _L2_cache_size = 0;
+    size_t _L3_cache_size = 0;
+
+    size_t _pushed_chunks = 0;
+};
+
+AdaptivePartitionHashJoinBuilder::AdaptivePartitionHashJoinBuilder(HashJoiner& hash_joiner)
+        : HashJoinBuilder(hash_joiner) {
+    static constexpr size_t DEFAULT_L2_CACHE_SIZE = 1 * 1024 * 1024;
+    static constexpr size_t DEFAULT_L3_CACHE_SIZE = 32 * 1024 * 1024;
+    const auto& cache_sizes = CpuInfo::get_cache_sizes();
+    _L2_cache_size = cache_sizes[CpuInfo::L2_CACHE];
+    _L3_cache_size = cache_sizes[CpuInfo::L3_CACHE];
+    _L2_cache_size = _L2_cache_size ? _L2_cache_size : DEFAULT_L2_CACHE_SIZE;
+    _L3_cache_size = _L3_cache_size ? _L3_cache_size : DEFAULT_L3_CACHE_SIZE;
+}
+
+size_t AdaptivePartitionHashJoinBuilder::_estimated_row_size(const HashTableParam& param) const {
+    size_t estimated_each_row = 0;
+
+    for (auto* tuple : param.build_row_desc->tuple_descriptors()) {
+        for (auto slot : tuple->slots()) {
+            if (param.build_output_slots.contains(slot->id())) {
+                estimated_each_row += get_size_of_fixed_length_type(slot->type().type);
+                estimated_each_row += type_estimated_overhead_bytes(slot->type().type);
+            }
+        }
+    }
+
+    // for hash table bucket
+    estimated_each_row += 4;
+
+    return estimated_each_row;
+}
+
+// We could use a better estimation model.
+size_t AdaptivePartitionHashJoinBuilder::_estimated_probe_cost(const HashTableParam& param) const {
+    size_t size = 0;
+
+    for (auto* tuple : param.probe_row_desc->tuple_descriptors()) {
+        for (auto slot : tuple->slots()) {
+            if (param.probe_output_slots.contains(slot->id())) {
+                size += get_size_of_fixed_length_type(slot->type().type);
+                size += type_estimated_overhead_bytes(slot->type().type);
+            }
+        }
+    }
+    // we define probe cost is bytes size * 6
+    return size * 6;
+}
+
+template <>
+size_t AdaptivePartitionHashJoinBuilder::_estimated_build_cost<CacheLevel::L2>(size_t build_row_size) const {
+    return build_row_size / 2;
+}
+
+template <>
+size_t AdaptivePartitionHashJoinBuilder::_estimated_build_cost<CacheLevel::L3>(size_t build_row_size) const {
+    return build_row_size;
+}
+
+template <>
+size_t AdaptivePartitionHashJoinBuilder::_estimated_build_cost<CacheLevel::MEMORY>(size_t build_row_size) const {
+    return build_row_size * 2;
+}
+
+void AdaptivePartitionHashJoinBuilder::_adjust_partition_rows(size_t build_row_size) {
+    build_row_size = std::max(build_row_size, 4UL);
+    _fit_L2_cache_max_rows = _L2_cache_size / build_row_size;
+    _fit_L3_cache_max_rows = _L3_cache_size / build_row_size;
+
+    // If the hash table is smaller than the L2 cache. we don't think partition hash join is needed.
+    _partition_join_min_rows = _fit_L2_cache_max_rows;
+    // If the hash table after partition can't be loaded to L3. we don't think partition hash join is needed.
+    _partition_join_max_rows = _fit_L3_cache_max_rows * _partition_num;
+
+    if (_probe_estimated_costs + _estimated_build_cost<CacheLevel::L2>(build_row_size) <
+        _estimated_build_cost<CacheLevel::L3>(build_row_size)) {
+        // overhead after hash table partitioning + probe extra cost < cost before partitioning
+        // nothing to do
+    } else if (_probe_estimated_costs + _estimated_build_cost<CacheLevel::L3>(build_row_size) <
+               _estimated_build_cost<CacheLevel::MEMORY>(build_row_size)) {
+        // It is only after this that performance gains can be realized beyond the L3 cache.
+        _partition_join_min_rows = _fit_L3_cache_max_rows;
+    } else {
+        // Partitioned joins don't have performance gains. Not using partition hash join.
+        _partition_num = 1;
+    }
+
+    VLOG_OPERATOR << "TRACE:"
+                  << "partition_num=" << _partition_num << " partition_join_min_rows=" << _partition_join_min_rows
+                  << " partition_join_max_rows=" << _partition_join_max_rows << " probe cost=" << _probe_estimated_costs
+                  << " build cost L2=" << _estimated_build_cost<CacheLevel::L2>(build_row_size)
+                  << " build cost L3=" << _estimated_build_cost<CacheLevel::L3>(build_row_size)
+                  << " build cost Mem=" << _estimated_build_cost<CacheLevel::MEMORY>(build_row_size);
+}
+
+void AdaptivePartitionHashJoinBuilder::_init_partition_nums(const HashTableParam& param) {
+    _partition_num = 16;
+
+    size_t estimated_bytes_each_row = _estimated_row_size(param);
+
+    _probe_estimated_costs = _estimated_probe_cost(param);
+
+    _adjust_partition_rows(estimated_bytes_each_row);
+
+    COUNTER_SET(_hash_joiner.build_metrics().partition_nums, (int64_t)_partition_num);
+}
+
+void AdaptivePartitionHashJoinBuilder::create(const HashTableParam& param) {
+    _init_partition_nums(param);
+    for (size_t i = 0; i < _partition_num; ++i) {
+        _builders.emplace_back(std::make_unique<SingleHashJoinBuilder>(_hash_joiner));
+        _builders.back()->create(param);
+    }
+}
+
+void AdaptivePartitionHashJoinBuilder::close() {
+    for (const auto& builder : _builders) {
+        builder->close();
+    }
+    _builders.clear();
+    _partition_num = 0;
+    _partition_join_min_rows = 0;
+    _partition_join_max_rows = 0;
+    _probe_estimated_costs = 0;
+    _fit_L2_cache_max_rows = 0;
+    _fit_L3_cache_max_rows = 0;
+    _pushed_chunks = 0;
+}
+
+void AdaptivePartitionHashJoinBuilder::reset(const HashTableParam& param) {
+    close();
+    create(param);
+}
+
+bool AdaptivePartitionHashJoinBuilder::anti_join_key_column_has_null() const {
+    return std::any_of(_builders.begin(), _builders.end(),
+                       [](const auto& builder) { return builder->anti_join_key_column_has_null(); });
+}
+
+void AdaptivePartitionHashJoinBuilder::get_build_info(size_t* bucket_size, float* avg_keys_per_bucket) {
+    size_t total_bucket_size = 0;
+    float total_keys_per_bucket = 0;
+    for (const auto& builder : _builders) {
+        size_t bucket_size = 0;
+        float keys_per_bucket = 0;
+        builder->get_build_info(&bucket_size, &keys_per_bucket);
+        total_bucket_size += bucket_size;
+        total_keys_per_bucket += keys_per_bucket;
+    }
+    *bucket_size = total_bucket_size;
+    *avg_keys_per_bucket = total_keys_per_bucket / _builders.size();
+}
+
+size_t AdaptivePartitionHashJoinBuilder::get_output_probe_column_count() const {
+    return _builders[0]->get_output_probe_column_count();
+}
+
+size_t AdaptivePartitionHashJoinBuilder::get_output_build_column_count() const {
+    return _builders[0]->get_output_build_column_count();
+}
+
+int64_t AdaptivePartitionHashJoinBuilder::ht_mem_usage() const {
+    return std::accumulate(_builders.begin(), _builders.end(), 0L,
+                           [](int64_t sum, const auto& builder) { return sum + builder->ht_mem_usage(); });
+}
+
+Status AdaptivePartitionHashJoinBuilder::_convert_to_single_partition() {
+    // merge all partition data to the first partition
+    for (size_t i = 1; i < _partition_num; ++i) {
+        _builders[0]->hash_table().merge_ht(_builders[i]->hash_table());
+    }
+    _builders.resize(1);
+    _partition_num = 1;
+    return Status::OK();
+}
+
+Status AdaptivePartitionHashJoinBuilder::_append_chunk_to_partitions(const ChunkPtr& chunk) {
+    const std::vector<ExprContext*>& build_partition_keys = _hash_joiner.build_expr_ctxs();
+
+    size_t num_rows = chunk->num_rows();
+    size_t num_partitions = _builders.size();
+    size_t num_partition_cols = build_partition_keys.size();
+
+    std::vector<ColumnPtr> partition_columns(num_partition_cols);
+    for (size_t i = 0; i < num_partition_cols; ++i) {
+        ASSIGN_OR_RETURN(partition_columns[i], build_partition_keys[i]->evaluate(chunk.get()));
+    }
+    std::vector<uint32_t> hash_values;
+    {
+        hash_values.assign(num_rows, HashUtil::FNV_SEED);
+
+        for (const ColumnPtr& column : partition_columns) {
+            column->fnv_hash(hash_values.data(), 0, num_rows);
+        }
+        // find partition id
+        for (size_t i = 0; i < hash_values.size(); ++i) {
+            hash_values[i] = HashUtil::fmix32(hash_values[i]) & (num_partitions - 1);
+        }
+    }
+
+    const auto& partitions = hash_values;
+
+    std::vector<uint32_t> selection;
+    selection.resize(chunk->num_rows());
+
+    std::vector<int32_t> channel_row_idx_start_points;
+    channel_row_idx_start_points.assign(num_partitions + 1, 0);
+
+    for (uint32_t i : partitions) {
+        channel_row_idx_start_points[i]++;
+    }
+
+    for (int32_t i = 1; i <= channel_row_idx_start_points.size() - 1; ++i) {
+        channel_row_idx_start_points[i] += channel_row_idx_start_points[i - 1];
+    }
+
+    for (int32_t i = chunk->num_rows() - 1; i >= 0; --i) {
+        selection[channel_row_idx_start_points[partitions[i]] - 1] = i;
+        channel_row_idx_start_points[partitions[i]]--;
+    }
+
+    for (size_t i = 0; i < num_partitions; ++i) {
+        auto from = channel_row_idx_start_points[i];
+        auto size = channel_row_idx_start_points[i + 1] - from;
+        if (size == 0) {
+            continue;
+        }
+        // TODO: make builder implements append with selective
+        auto partition_chunk = chunk->clone_empty();
+        partition_chunk->append_selective(*chunk, selection.data(), from, size);
+        RETURN_IF_ERROR(_builders[i]->append_chunk(std::move(partition_chunk)));
+    }
+    return Status::OK();
+}
+
+Status AdaptivePartitionHashJoinBuilder::do_append_chunk(const ChunkPtr& chunk) {
+    if (_partition_num > 1 && hash_table_row_count() > _partition_join_max_rows) {
+        RETURN_IF_ERROR(_convert_to_single_partition());
+    }
+
+    if (_partition_num > 1 && ++_pushed_chunks % 8 == 0) {
+        size_t build_row_size = ht_mem_usage() / hash_table_row_count();
+        _adjust_partition_rows(build_row_size);
+        if (_partition_num == 1) {
+            RETURN_IF_ERROR(_convert_to_single_partition());
+        }
+    }
+
+    if (_partition_num > 1) {
+        RETURN_IF_ERROR(_append_chunk_to_partitions(chunk));
+    } else {
+        RETURN_IF_ERROR(_builders[0]->do_append_chunk(chunk));
+    }
+
+    return Status::OK();
+}
+
+ChunkPtr AdaptivePartitionHashJoinBuilder::convert_to_spill_schema(const ChunkPtr& chunk) const {
+    return _builders[0]->convert_to_spill_schema(chunk);
+}
+
+Status AdaptivePartitionHashJoinBuilder::build(RuntimeState* state) {
+    DCHECK_EQ(_partition_num, _builders.size());
+
+    if (_partition_num > 1 && hash_table_row_count() < _partition_join_min_rows) {
+        RETURN_IF_ERROR(_convert_to_single_partition());
+    }
+
+    for (auto& builder : _builders) {
+        RETURN_IF_ERROR(builder->build(state));
+    }
+    _ready = true;
+    return Status::OK();
+}
+
+void AdaptivePartitionHashJoinBuilder::visitHt(const std::function<void(JoinHashTable*)>& visitor) {
+    for (auto& builder : _builders) {
+        builder->visitHt(visitor);
+    }
+}
+
+std::unique_ptr<HashJoinProberImpl> AdaptivePartitionHashJoinBuilder::create_prober() {
+    DCHECK_EQ(_partition_num, _builders.size());
+
+    if (_partition_num == 1) {
+        return _builders[0]->create_prober();
+    } else {
+        std::vector<std::unique_ptr<SingleHashJoinProberImpl>> sub_probers;
+        auto prober = std::make_unique<PartitionedHashJoinProberImpl>(_hash_joiner);
+        sub_probers.resize(_partition_num);
+        for (size_t i = 0; i < _builders.size(); ++i) {
+            sub_probers[i].reset(down_cast<SingleHashJoinProberImpl*>(_builders[i]->create_prober().release()));
+        }
+        prober->set_probers(std::move(sub_probers));
+        return prober;
+    }
+}
+
+void AdaptivePartitionHashJoinBuilder::clone_readable(HashJoinBuilder* builder) {
+    for (auto& builder : _builders) {
+        DCHECK(builder->ready());
+    }
+    DCHECK(_ready);
+    DCHECK_EQ(_partition_num, _builders.size());
+    auto other = down_cast<AdaptivePartitionHashJoinBuilder*>(builder);
+    other->_builders.clear();
+    other->_partition_num = _partition_num;
+    other->_partition_join_max_rows = _partition_join_max_rows;
+    other->_partition_join_min_rows = _partition_join_min_rows;
+    other->_ready = _ready;
+    for (size_t i = 0; i < _partition_num; ++i) {
+        other->_builders.emplace_back(std::make_unique<SingleHashJoinBuilder>(_hash_joiner));
+        _builders[i]->clone_readable(other->_builders[i].get());
+    }
+}
+
+HashJoinBuilder* HashJoinBuilderFactory::create(ObjectPool* pool, const HashJoinBuildOptions& options,
+                                                HashJoiner& hash_joiner) {
+    if (options.enable_partitioned_hash_join) {
+        return pool->add(new AdaptivePartitionHashJoinBuilder(hash_joiner));
+    } else {
+        return pool->add(new SingleHashJoinBuilder(hash_joiner));
+    }
+}
+
 } // namespace starrocks
diff --git a/be/src/exec/hash_join_components.h b/be/src/exec/hash_join_components.h
index 3d1a5b08c2a8d7..a582fb14e7bdb9 100644
--- a/be/src/exec/hash_join_components.h
+++ b/be/src/exec/hash_join_components.h
@@ -31,10 +31,11 @@ class HashJoinProberImpl {
 public:
     virtual ~HashJoinProberImpl() = default;
     virtual bool probe_chunk_empty() const = 0;
+    virtual Status on_input_finished(RuntimeState* state) = 0;
     virtual Status push_probe_chunk(RuntimeState* state, ChunkPtr&& chunk) = 0;
     virtual StatusOr<ChunkPtr> probe_chunk(RuntimeState* state) = 0;
     virtual StatusOr<ChunkPtr> probe_remain(RuntimeState* state, bool* has_remain) = 0;
-    virtual void reset() = 0;
+    virtual void reset(RuntimeState* runtime_state) = 0;
 
 protected:
     HashJoinProberImpl(HashJoiner& hash_joiner) : _hash_joiner(hash_joiner) {}
@@ -51,6 +52,13 @@ class HashJoinProber {
         return _impl->push_probe_chunk(state, std::move(chunk));
     }
 
+    Status on_input_finished(RuntimeState* state) {
+        if (_impl == nullptr) {
+            return Status::OK();
+        }
+        return _impl->on_input_finished(state);
+    }
+
     // probe hash table
     StatusOr<ChunkPtr> probe_chunk(RuntimeState* state) { return _impl->probe_chunk(state); }
 
@@ -58,7 +66,7 @@ class HashJoinProber {
         return _impl->probe_remain(state, has_remain);
     }
 
-    void reset() { return _impl->reset(); }
+    void reset(RuntimeState* runtime_state) { return _impl->reset(runtime_state); }
 
     HashJoinProber* clone_empty(ObjectPool* pool) { return pool->add(new HashJoinProber(_hash_joiner)); }
 
@@ -96,10 +104,6 @@ class HashJoinBuilder {
 
     virtual void reset(const HashTableParam& param) = 0;
 
-    virtual void reset_probe(RuntimeState* state) = 0;
-
-    virtual HashJoinBuilder* clone_empty(ObjectPool* pool) = 0;
-
     virtual int64_t ht_mem_usage() const = 0;
 
     // used for check NULL_AWARE_LEFT_ANTI_JOIN build side has null
@@ -118,6 +122,7 @@ class HashJoinBuilder {
 
     virtual std::unique_ptr<HashJoinProberImpl> create_prober() = 0;
 
+    // clone readable to to builder
     virtual void clone_readable(HashJoinBuilder* builder) = 0;
 
     virtual ChunkPtr convert_to_spill_schema(const ChunkPtr& chunk) const = 0;
@@ -148,12 +153,6 @@ class SingleHashJoinBuilder final : public HashJoinBuilder {
 
     Status build(RuntimeState* state) override;
 
-    void reset_probe(RuntimeState* state) override;
-
-    SingleHashJoinBuilder* clone_empty(ObjectPool* pool) override {
-        return pool->add(new SingleHashJoinBuilder(_hash_joiner));
-    }
-
     bool anti_join_key_column_has_null() const override;
 
     int64_t ht_mem_usage() const override { return _ht.mem_usage(); }
@@ -179,4 +178,12 @@ class SingleHashJoinBuilder final : public HashJoinBuilder {
     Columns _key_columns;
 };
 
+struct HashJoinBuildOptions {
+    bool enable_partitioned_hash_join = false;
+};
+
+class HashJoinBuilderFactory {
+public:
+    static HashJoinBuilder* create(ObjectPool* pool, const HashJoinBuildOptions& options, HashJoiner& hash_joiner);
+};
 } // namespace starrocks
\ No newline at end of file
diff --git a/be/src/exec/hash_join_node.cpp b/be/src/exec/hash_join_node.cpp
index 10689bbccd9b25..fd1712e3cf51b8 100644
--- a/be/src/exec/hash_join_node.cpp
+++ b/be/src/exec/hash_join_node.cpp
@@ -145,6 +145,9 @@ Status HashJoinNode::init(const TPlanNode& tnode, RuntimeState* state) {
     if (tnode.hash_join_node.__isset.late_materialization) {
         _enable_late_materialization = tnode.hash_join_node.late_materialization;
     }
+    if (tnode.hash_join_node.__isset.enable_partition_hash_join) {
+        _enable_partition_hash_join = tnode.hash_join_node.enable_partition_hash_join;
+    }
     return Status::OK();
 }
 
@@ -203,6 +206,7 @@ void HashJoinNode::_init_hash_table_param(HashTableParam* param) {
     param->build_output_slots = _output_slots;
     param->probe_output_slots = _output_slots;
     param->enable_late_materialization = _enable_late_materialization;
+    param->enable_partition_hash_join = _enable_partition_hash_join;
 
     std::set<SlotId> predicate_slots;
     for (ExprContext* expr_context : _conjunct_ctxs) {
@@ -472,7 +476,8 @@ pipeline::OpFactories HashJoinNode::_decompose_to_pipeline(pipeline::PipelineBui
     HashJoinerParam param(pool, _hash_join_node, _is_null_safes, _build_expr_ctxs, _probe_expr_ctxs,
                           _other_join_conjunct_ctxs, _conjunct_ctxs, child(1)->row_desc(), child(0)->row_desc(),
                           child(1)->type(), child(0)->type(), child(1)->conjunct_ctxs().empty(), _build_runtime_filters,
-                          _output_slots, _output_slots, _distribution_mode, false, _enable_late_materialization);
+                          _output_slots, _output_slots, _distribution_mode, false, _enable_late_materialization,
+                          _enable_partition_hash_join);
     auto hash_joiner_factory = std::make_shared<starrocks::pipeline::HashJoinerFactory>(param);
 
     // Create a shared RefCountedRuntimeFilterCollector
diff --git a/be/src/exec/hash_join_node.h b/be/src/exec/hash_join_node.h
index d83c0b9fed0bec..f7ea19015b24f8 100644
--- a/be/src/exec/hash_join_node.h
+++ b/be/src/exec/hash_join_node.h
@@ -115,6 +115,7 @@ class HashJoinNode final : public ExecNode {
 
     bool _is_push_down = false;
     bool _enable_late_materialization = false;
+    bool _enable_partition_hash_join = false;
 
     JoinHashTable _ht;
 
diff --git a/be/src/exec/hash_joiner.cpp b/be/src/exec/hash_joiner.cpp
index e7ea8a9f37d133..7101254c86b3c3 100644
--- a/be/src/exec/hash_joiner.cpp
+++ b/be/src/exec/hash_joiner.cpp
@@ -44,6 +44,7 @@ void HashJoinProbeMetrics::prepare(RuntimeProfile* runtime_profile) {
     other_join_conjunct_evaluate_timer = ADD_TIMER(runtime_profile, "OtherJoinConjunctEvaluateTime");
     where_conjunct_evaluate_timer = ADD_TIMER(runtime_profile, "WhereConjunctEvaluateTime");
     probe_counter = ADD_COUNTER(runtime_profile, "probeCount", TUnit::UNIT);
+    partition_probe_overhead = ADD_TIMER(runtime_profile, "PartitionProbeOverhead");
 }
 
 void HashJoinBuildMetrics::prepare(RuntimeProfile* runtime_profile) {
@@ -55,8 +56,8 @@ void HashJoinBuildMetrics::prepare(RuntimeProfile* runtime_profile) {
     runtime_filter_num = ADD_COUNTER(runtime_profile, "RuntimeFilterNum", TUnit::UNIT);
     build_keys_per_bucket = ADD_COUNTER(runtime_profile, "BuildKeysPerBucket%", TUnit::UNIT);
     hash_table_memory_usage = ADD_COUNTER(runtime_profile, "HashTableMemoryUsage", TUnit::BYTES);
-
     partial_runtime_bloom_filter_bytes = ADD_COUNTER(runtime_profile, "PartialRuntimeBloomFilterBytes", TUnit::BYTES);
+    partition_nums = ADD_COUNTER(runtime_profile, "PartitionNums", TUnit::UNIT);
 }
 
 HashJoiner::HashJoiner(const HashJoinerParam& param)
@@ -87,7 +88,11 @@ HashJoiner::HashJoiner(const HashJoinerParam& param)
     if (param._hash_join_node.__isset.build_runtime_filters_from_planner) {
         _build_runtime_filters_from_planner = param._hash_join_node.build_runtime_filters_from_planner;
     }
-    _hash_join_builder = _pool->add(new SingleHashJoinBuilder(*this));
+
+    HashJoinBuildOptions build_options;
+    build_options.enable_partitioned_hash_join = param._enable_partition_hash_join;
+
+    _hash_join_builder = HashJoinBuilderFactory::create(_pool, build_options, *this);
     _hash_join_prober = _pool->add(new HashJoinProber(*this));
     _build_metrics = _pool->add(new HashJoinBuildMetrics());
     _probe_metrics = _pool->add(new HashJoinProbeMetrics());
@@ -247,8 +252,8 @@ Status HashJoiner::push_chunk(RuntimeState* state, ChunkPtr&& chunk) {
     return _hash_join_prober->push_probe_chunk(state, std::move(chunk));
 }
 
-Status HashJoiner::probe_input_finished() {
-    return Status::OK();
+Status HashJoiner::probe_input_finished(RuntimeState* state) {
+    return _hash_join_prober->on_input_finished(state);
 }
 
 StatusOr<ChunkPtr> HashJoiner::pull_chunk(RuntimeState* state) {
@@ -365,9 +370,7 @@ Status HashJoiner::reset_probe(starrocks::RuntimeState* state) {
         return Status::OK();
     }
 
-    _hash_join_prober->reset();
-
-    _hash_join_builder->reset_probe(state);
+    _hash_join_prober->reset(state);
 
     return Status::OK();
 }
diff --git a/be/src/exec/hash_joiner.h b/be/src/exec/hash_joiner.h
index 5d2fa1cc75124b..e671bd6c4b45fa 100644
--- a/be/src/exec/hash_joiner.h
+++ b/be/src/exec/hash_joiner.h
@@ -72,7 +72,7 @@ struct HashJoinerParam {
                     bool build_conjunct_ctxs_is_empty, std::list<RuntimeFilterBuildDescriptor*> build_runtime_filters,
                     std::set<SlotId> build_output_slots, std::set<SlotId> probe_output_slots,
                     const TJoinDistributionMode::type distribution_mode, bool mor_reader_mode,
-                    bool enable_late_materialization)
+                    bool enable_late_materialization, bool enable_partition_hash_join)
             : _pool(pool),
               _hash_join_node(hash_join_node),
               _is_null_safes(std::move(is_null_safes)),
@@ -90,7 +90,8 @@ struct HashJoinerParam {
               _probe_output_slots(std::move(probe_output_slots)),
               _distribution_mode(distribution_mode),
               _mor_reader_mode(mor_reader_mode),
-              _enable_late_materialization(enable_late_materialization) {}
+              _enable_late_materialization(enable_late_materialization),
+              _enable_partition_hash_join(enable_partition_hash_join) {}
 
     HashJoinerParam(HashJoinerParam&&) = default;
     HashJoinerParam(HashJoinerParam&) = default;
@@ -115,6 +116,7 @@ struct HashJoinerParam {
     const TJoinDistributionMode::type _distribution_mode;
     const bool _mor_reader_mode;
     const bool _enable_late_materialization;
+    const bool _enable_partition_hash_join;
 };
 
 inline bool could_short_circuit(TJoinOp::type join_type) {
@@ -143,6 +145,7 @@ struct HashJoinProbeMetrics {
     RuntimeProfile::Counter* where_conjunct_evaluate_timer = nullptr;
     RuntimeProfile::Counter* output_build_column_timer = nullptr;
     RuntimeProfile::Counter* probe_counter = nullptr;
+    RuntimeProfile::Counter* partition_probe_overhead = nullptr;
 
     void prepare(RuntimeProfile* runtime_profile);
 };
@@ -156,8 +159,8 @@ struct HashJoinBuildMetrics {
     RuntimeProfile::Counter* runtime_filter_num = nullptr;
     RuntimeProfile::Counter* build_keys_per_bucket = nullptr;
     RuntimeProfile::Counter* hash_table_memory_usage = nullptr;
-
     RuntimeProfile::Counter* partial_runtime_bloom_filter_bytes = nullptr;
+    RuntimeProfile::Counter* partition_nums = nullptr;
 
     void prepare(RuntimeProfile* runtime_profile);
 };
@@ -210,7 +213,7 @@ class HashJoiner final : public pipeline::ContextWithDependency {
     Status build_ht(RuntimeState* state);
     // probe phase
     Status push_chunk(RuntimeState* state, ChunkPtr&& chunk);
-    Status probe_input_finished();
+    Status probe_input_finished(RuntimeState* state);
     StatusOr<ChunkPtr> pull_chunk(RuntimeState* state);
 
     pipeline::RuntimeInFilters& get_runtime_in_filters() { return _runtime_in_filters; }
@@ -274,10 +277,16 @@ class HashJoiner final : public pipeline::ContextWithDependency {
         return Status::OK();
     }
 
-    const std::vector<ExprContext*> probe_expr_ctxs() { return _probe_expr_ctxs; }
+    const std::vector<ExprContext*>& probe_expr_ctxs() { return _probe_expr_ctxs; }
+    const std::vector<ExprContext*>& build_expr_ctxs() { return _build_expr_ctxs; }
 
     HashJoinProber* new_prober(ObjectPool* pool) { return _hash_join_prober->clone_empty(pool); }
-    HashJoinBuilder* new_builder(ObjectPool* pool) { return _hash_join_builder->clone_empty(pool); }
+    HashJoinBuilder* new_builder(ObjectPool* pool) {
+        // We don't support spill partition hash join now.
+        HashJoinBuildOptions options;
+        options.enable_partitioned_hash_join = false;
+        return HashJoinBuilderFactory::create(pool, options, *this);
+    }
 
     Status filter_probe_output_chunk(ChunkPtr& chunk, JoinHashTable& hash_table) {
         // Probe in JoinHashMap is divided into probe with other_conjuncts and without other_conjuncts.
diff --git a/be/src/exec/join_hash_map.cpp b/be/src/exec/join_hash_map.cpp
index afbe8107586b31..9389cb90e6c66f 100644
--- a/be/src/exec/join_hash_map.cpp
+++ b/be/src/exec/join_hash_map.cpp
@@ -656,6 +656,21 @@ void JoinHashTable::append_chunk(const ChunkPtr& chunk, const Columns& key_colum
     _table_items->row_count += chunk->num_rows();
 }
 
+void JoinHashTable::merge_ht(const JoinHashTable& ht) {
+    _table_items->row_count += ht._table_items->row_count;
+
+    Columns& columns = _table_items->build_chunk->columns();
+    Columns& other_columns = ht._table_items->build_chunk->columns();
+
+    for (size_t i = 0; i < _table_items->build_column_count; i++) {
+        if (!columns[i]->is_nullable() && other_columns[i]->is_nullable()) {
+            // upgrade to nullable column
+            columns[i] = NullableColumn::create(columns[i], NullColumn::create(columns[i]->size(), 0));
+        }
+        columns[i]->append(*other_columns[i], 1, other_columns[i]->size() - 1);
+    }
+}
+
 ChunkPtr JoinHashTable::convert_to_spill_schema(const ChunkPtr& chunk) const {
     DCHECK(chunk != nullptr && chunk->num_rows() > 0);
     ChunkPtr output = std::make_shared<Chunk>();
diff --git a/be/src/exec/join_hash_map.h b/be/src/exec/join_hash_map.h
index 9f4e5eb05b9396..781a466cd63d62 100644
--- a/be/src/exec/join_hash_map.h
+++ b/be/src/exec/join_hash_map.h
@@ -280,6 +280,7 @@ struct HashTableProbeState {
 struct HashTableParam {
     bool with_other_conjunct = false;
     bool enable_late_materialization = false;
+    bool enable_partition_hash_join = false;
     TJoinOp::type join_type = TJoinOp::INNER_JOIN;
     const RowDescriptor* build_row_desc = nullptr;
     const RowDescriptor* probe_row_desc = nullptr;
@@ -833,6 +834,7 @@ class JoinHashTable {
     Status lazy_output(RuntimeState* state, ChunkPtr* probe_chunk, ChunkPtr* result_chunk);
 
     void append_chunk(const ChunkPtr& chunk, const Columns& key_columns);
+    void merge_ht(const JoinHashTable& ht);
     // convert input column to spill schema order
     ChunkPtr convert_to_spill_schema(const ChunkPtr& chunk) const;
 
diff --git a/be/src/exec/mor_processor.cpp b/be/src/exec/mor_processor.cpp
index dd6a881f58b6d4..63a05bbc1a22a0 100644
--- a/be/src/exec/mor_processor.cpp
+++ b/be/src/exec/mor_processor.cpp
@@ -48,7 +48,7 @@ Status IcebergMORProcessor::init(RuntimeState* runtime_state, const MORParams& p
             std::vector<ExprContext*>(), std::vector<ExprContext*>(), *_build_row_desc, *_probe_row_desc,
             TPlanNodeType::HDFS_SCAN_NODE, TPlanNodeType::HDFS_SCAN_NODE, true,
             std::list<RuntimeFilterBuildDescriptor*>(), std::set<SlotId>(), probe_output_slot_ids,
-            TJoinDistributionMode::PARTITIONED, true, false));
+            TJoinDistributionMode::PARTITIONED, true, false, false));
 
     _hash_joiner = _pool.add(new HashJoiner(*param));
     RETURN_IF_ERROR(_hash_joiner->prepare_builder(runtime_state, _runtime_profile));
diff --git a/be/src/exec/parquet_scanner.cpp b/be/src/exec/parquet_scanner.cpp
index 5e6a0945dec2ea..500cba44b14b1d 100644
--- a/be/src/exec/parquet_scanner.cpp
+++ b/be/src/exec/parquet_scanner.cpp
@@ -108,14 +108,6 @@ Status ParquetScanner::append_batch_to_src_chunk(ChunkPtr* chunk) {
         _conv_ctx.current_slot = slot_desc;
         auto* array = _batch->column(column_pos++).get();
         auto& column = (*chunk)->get_column_by_slot_id(slot_desc->id());
-        // for timestamp type, _state->timezone which is specified by user. convert function
-        // obtains timezone from array. thus timezone in array should be rectified to
-        // _state->timezone.
-        if (array->type_id() == ArrowTypeId::TIMESTAMP) {
-            auto* timestamp_type = down_cast<arrow::TimestampType*>(array->type().get());
-            auto& mutable_timezone = (std::string&)timestamp_type->timezone();
-            mutable_timezone = _state->timezone();
-        }
         RETURN_IF_ERROR(convert_array_to_column(_conv_funcs[i].get(), num_elements, array, column, _batch_start_idx,
                                                 _chunk_start_idx, &_chunk_filter, &_conv_ctx));
     }
@@ -321,6 +313,15 @@ Status ParquetScanner::convert_array_to_column(ConvertFuncTree* conv_func, size_
                                                const arrow::Array* array, const ColumnPtr& column,
                                                size_t batch_start_idx, size_t chunk_start_idx, Filter* chunk_filter,
                                                ArrowConvertContext* conv_ctx) {
+    // for timestamp type, state->timezone which is specified by user. convert function
+    // obtains timezone from array. thus timezone in array should be rectified to
+    // state->timezone.
+    if (array->type_id() == ArrowTypeId::TIMESTAMP) {
+        auto* timestamp_type = down_cast<arrow::TimestampType*>(array->type().get());
+        auto& mutable_timezone = (std::string&)timestamp_type->timezone();
+        mutable_timezone = conv_ctx->state->timezone();
+    }
+
     uint8_t* null_data;
     Column* data_column;
     if (column->is_nullable()) {
diff --git a/be/src/exec/parquet_schema_builder.cpp b/be/src/exec/parquet_schema_builder.cpp
index 8a3ac6bc1f9ead..f582520ed9da59 100644
--- a/be/src/exec/parquet_schema_builder.cpp
+++ b/be/src/exec/parquet_schema_builder.cpp
@@ -23,6 +23,7 @@ static Status get_parquet_type_from_group(const ::parquet::schema::NodePtr& node
 static Status get_parquet_type_from_primitive(const ::parquet::schema::NodePtr& node, TypeDescriptor* type_desc);
 static Status get_parquet_type_from_list(const ::parquet::schema::NodePtr& node, TypeDescriptor* type_desc);
 static Status get_parquet_type_from_map(const ::parquet::schema::NodePtr& node, TypeDescriptor* type_desc);
+static Status try_to_infer_struct_type(const ::parquet::schema::NodePtr& node, TypeDescriptor* type_desc);
 
 Status get_parquet_type(const ::parquet::schema::NodePtr& node, TypeDescriptor* type_desc) {
     if (node->is_group()) {
@@ -121,6 +122,11 @@ static Status get_parquet_type_from_group(const ::parquet::schema::NodePtr& node
         return get_parquet_type_from_map(node, type_desc);
     }
 
+    auto st = try_to_infer_struct_type(node, type_desc);
+    if (st.ok()) {
+        return Status::OK();
+    }
+
     // Treat unsupported types as VARCHAR.
     *type_desc = TypeDescriptor::create_varchar_type(TypeDescriptor::MAX_VARCHAR_LENGTH);
     return Status::OK();
@@ -217,4 +223,44 @@ static Status get_parquet_type_from_map(const ::parquet::schema::NodePtr& node,
     return Status::OK();
 }
 
+/*
+try to infer struct type from group node.
+
+parquet does not have struct type, there is no struct definition in parquet.
+try to infer like this.
+group <name> {
+    type field0;
+    type field1;
+    ...
+}
+*/
+static Status try_to_infer_struct_type(const ::parquet::schema::NodePtr& node, TypeDescriptor* type_desc) {
+    // 1st level.
+    // group name
+    DCHECK(node->is_group());
+
+    auto group_node = std::static_pointer_cast<::parquet::schema::GroupNode>(node);
+    int field_count = group_node->field_count();
+    if (field_count == 0) {
+        return Status::Unknown("unknown type");
+    }
+
+    // 2nd level.
+    // field
+    std::vector<std::string> field_names;
+    std::vector<TypeDescriptor> field_types;
+    field_names.reserve(field_count);
+    field_types.reserve(field_count);
+    for (auto i = 0; i < group_node->field_count(); ++i) {
+        const auto& field = group_node->field(i);
+        field_names.emplace_back(field->name());
+        auto& field_type_desc = field_types.emplace_back();
+        RETURN_IF_ERROR(get_parquet_type(field, &field_type_desc));
+    }
+
+    *type_desc = TypeDescriptor::create_struct_type(field_names, field_types);
+
+    return Status::OK();
+}
+
 } //namespace starrocks
\ No newline at end of file
diff --git a/be/src/exec/pipeline/exec_state_reporter.cpp b/be/src/exec/pipeline/exec_state_reporter.cpp
index 8d8407f4ad6def..996f8985ef2ca6 100644
--- a/be/src/exec/pipeline/exec_state_reporter.cpp
+++ b/be/src/exec/pipeline/exec_state_reporter.cpp
@@ -182,6 +182,7 @@ Status ExecStateReporter::report_exec_status(const TReportExecStatusParams& para
                 }
                 coord->reportExecStatus(res, params);
             } else {
+                (void)coord.reopen(config::thrift_rpc_timeout_ms);
                 std::stringstream msg;
                 msg << "ReportExecStatus() to " << fe_addr << " failed:\n" << e.what();
                 LOG(WARNING) << msg.str();
@@ -296,6 +297,7 @@ Status ExecStateReporter::report_epoch(const TMVMaintenanceTasks& params, ExecEn
                 }
                 coord->mvReport(res, params);
             } else {
+                (void)coord.reopen(config::thrift_rpc_timeout_ms);
                 std::stringstream msg;
                 msg << "mvReport() to " << fe_addr << " failed:\n" << e.what();
                 LOG(WARNING) << msg.str();
diff --git a/be/src/exec/pipeline/hashjoin/hash_join_probe_operator.cpp b/be/src/exec/pipeline/hashjoin/hash_join_probe_operator.cpp
index 61158cf0e69ad9..7b4225054fef03 100644
--- a/be/src/exec/pipeline/hashjoin/hash_join_probe_operator.cpp
+++ b/be/src/exec/pipeline/hashjoin/hash_join_probe_operator.cpp
@@ -87,7 +87,7 @@ StatusOr<ChunkPtr> HashJoinProbeOperator::pull_chunk(RuntimeState* state) {
 }
 
 Status HashJoinProbeOperator::set_finishing(RuntimeState* state) {
-    RETURN_IF_ERROR(_join_prober->probe_input_finished());
+    RETURN_IF_ERROR(_join_prober->probe_input_finished(state));
     _join_prober->enter_post_probe_phase();
     return Status::OK();
 }
diff --git a/be/src/exec/pipeline/pipeline_driver.cpp b/be/src/exec/pipeline/pipeline_driver.cpp
index df6ff53a5fd88a..114769e0c5f3d6 100644
--- a/be/src/exec/pipeline/pipeline_driver.cpp
+++ b/be/src/exec/pipeline/pipeline_driver.cpp
@@ -555,7 +555,9 @@ void PipelineDriver::finish_operators(RuntimeState* runtime_state) {
 
 void PipelineDriver::cancel_operators(RuntimeState* runtime_state) {
     if (this->query_ctx()->is_query_expired()) {
-        LOG(WARNING) << "begin to cancel operators for " << to_readable_string();
+        if (_has_log_cancelled.exchange(true) == false) {
+            VLOG_ROW << "begin to cancel operators for " << to_readable_string();
+        }
     }
     for (auto& op : _operators) {
         WARN_IF_ERROR(_mark_operator_cancelled(op, runtime_state),
@@ -805,10 +807,11 @@ Status PipelineDriver::_mark_operator_finished(OperatorPtr& op, RuntimeState* st
 
 Status PipelineDriver::_mark_operator_cancelled(OperatorPtr& op, RuntimeState* state) {
     Status res = _mark_operator_finished(op, state);
-    if (!res.ok()) {
-        LOG(WARNING) << fmt::format("fragment_id {} driver {} cancels operator {} with finished error {}",
-                                    print_id(state->fragment_instance_id()), to_readable_string(), op->get_name(),
-                                    res.message());
+    if (!res.ok() && !res.is_cancelled()) {
+        LOG(WARNING) << fmt::format(
+                "[Driver] failed to finish operator called by cancelling operator [fragment_id={}] [driver={}] "
+                "[operator={}] [error={}]",
+                print_id(state->fragment_instance_id()), to_readable_string(), op->get_name(), res.message());
     }
     auto& op_state = _operator_stages[op->get_id()];
     if (op_state >= OperatorStage::CANCELLED) {
diff --git a/be/src/exec/pipeline/pipeline_driver.h b/be/src/exec/pipeline/pipeline_driver.h
index 4ffa5a56985cde..5f9d1c8b0dcd15 100644
--- a/be/src/exec/pipeline/pipeline_driver.h
+++ b/be/src/exec/pipeline/pipeline_driver.h
@@ -526,6 +526,8 @@ class PipelineDriver {
     size_t _driver_queue_level = 0;
     std::atomic<bool> _in_ready_queue{false};
 
+    std::atomic<bool> _has_log_cancelled{false};
+
     // metrics
     RuntimeProfile::Counter* _total_timer = nullptr;
     RuntimeProfile::Counter* _active_timer = nullptr;
diff --git a/be/src/exec/pipeline/query_context.cpp b/be/src/exec/pipeline/query_context.cpp
index d70c18d40b5c8d..fc8aa6598cca3a 100644
--- a/be/src/exec/pipeline/query_context.cpp
+++ b/be/src/exec/pipeline/query_context.cpp
@@ -375,8 +375,8 @@ QueryContext* QueryContextManager::get_or_register(const TUniqueId& query_id) {
             // lookup query context for the second chance in sc_map
             if (sc_it != sc_map.end()) {
                 auto ctx = std::move(sc_it->second);
-                RETURN_NULL_IF_CTX_CANCELLED(ctx);
                 sc_map.erase(sc_it);
+                RETURN_NULL_IF_CTX_CANCELLED(ctx);
                 auto* raw_ctx_ptr = ctx.get();
                 context_map.emplace(query_id, std::move(ctx));
                 return raw_ctx_ptr;
diff --git a/be/src/exec/pipeline/scan/olap_chunk_source.cpp b/be/src/exec/pipeline/scan/olap_chunk_source.cpp
index 6edf39b5ca9319..d0c469985099aa 100644
--- a/be/src/exec/pipeline/scan/olap_chunk_source.cpp
+++ b/be/src/exec/pipeline/scan/olap_chunk_source.cpp
@@ -173,7 +173,6 @@ void OlapChunkSource::_init_counter(RuntimeState* state) {
     // IOTime
     _io_timer = ADD_CHILD_TIMER(_runtime_profile, "IOTime", IO_TASK_EXEC_TIMER_NAME);
 
-    _json_flatten_timer = ADD_CHILD_TIMER(_runtime_profile, "JsonFlattern", segment_read_name);
     _access_path_hits_counter = ADD_COUNTER(_runtime_profile, "AccessPathHits", TUnit::UNIT);
     _access_path_unhits_counter = ADD_COUNTER(_runtime_profile, "AccessPathUnhits", TUnit::UNIT);
 }
@@ -654,21 +653,23 @@ void OlapChunkSource::_update_counter() {
         COUNTER_UPDATE(c2, _reader->stats().rows_del_filtered);
     }
 
-    if (_reader->stats().flat_json_hits.size() > 0) {
+    if (_reader->stats().flat_json_hits.size() > 0 || _reader->stats().merge_json_hits.size() > 0) {
         std::string access_path_hits = "AccessPathHits";
         int64_t total = 0;
         for (auto& [k, v] : _reader->stats().flat_json_hits) {
-            auto* path_counter = _runtime_profile->get_counter(fmt::format("[Hit]{}", k));
+            std::string path = fmt::format("[Hit]{}", k);
+            auto* path_counter = _runtime_profile->get_counter(path);
             if (path_counter == nullptr) {
-                path_counter = ADD_CHILD_COUNTER(_runtime_profile, k, TUnit::UNIT, access_path_hits);
+                path_counter = ADD_CHILD_COUNTER(_runtime_profile, path, TUnit::UNIT, access_path_hits);
             }
             total += v;
             COUNTER_UPDATE(path_counter, v);
         }
         for (auto& [k, v] : _reader->stats().merge_json_hits) {
-            auto* path_counter = _runtime_profile->get_counter(fmt::format("[HitMerge]{}", k));
+            std::string merge_path = fmt::format("[HitMerge]{}", k);
+            auto* path_counter = _runtime_profile->get_counter(merge_path);
             if (path_counter == nullptr) {
-                path_counter = ADD_CHILD_COUNTER(_runtime_profile, k, TUnit::UNIT, access_path_hits);
+                path_counter = ADD_CHILD_COUNTER(_runtime_profile, merge_path, TUnit::UNIT, access_path_hits);
             }
             total += v;
             COUNTER_UPDATE(path_counter, v);
@@ -679,9 +680,10 @@ void OlapChunkSource::_update_counter() {
         std::string access_path_unhits = "AccessPathUnhits";
         int64_t total = 0;
         for (auto& [k, v] : _reader->stats().dynamic_json_hits) {
-            auto* path_counter = _runtime_profile->get_counter(fmt::format("[Unhit]{}", k));
+            std::string path = fmt::format("[Unhit]{}", k);
+            auto* path_counter = _runtime_profile->get_counter(path);
             if (path_counter == nullptr) {
-                path_counter = ADD_CHILD_COUNTER(_runtime_profile, k, TUnit::UNIT, access_path_unhits);
+                path_counter = ADD_CHILD_COUNTER(_runtime_profile, path, TUnit::UNIT, access_path_unhits);
             }
             total += v;
             COUNTER_UPDATE(path_counter, v);
@@ -689,7 +691,23 @@ void OlapChunkSource::_update_counter() {
         COUNTER_UPDATE(_access_path_unhits_counter, total);
     }
 
-    COUNTER_UPDATE(_json_flatten_timer, _reader->stats().json_flatten_ns);
+    std::string parent_name = "SegmentRead";
+    if (_reader->stats().json_init_ns > 0) {
+        RuntimeProfile::Counter* c = ADD_CHILD_TIMER(_runtime_profile, "FlatJsonInit", parent_name);
+        COUNTER_UPDATE(c, _reader->stats().json_init_ns);
+    }
+    if (_reader->stats().json_cast_ns > 0) {
+        RuntimeProfile::Counter* c = ADD_CHILD_TIMER(_runtime_profile, "FlatJsonCast", parent_name);
+        COUNTER_UPDATE(c, _reader->stats().json_cast_ns);
+    }
+    if (_reader->stats().json_merge_ns > 0) {
+        RuntimeProfile::Counter* c = ADD_CHILD_TIMER(_runtime_profile, "FlatJsonMerge", parent_name);
+        COUNTER_UPDATE(c, _reader->stats().json_merge_ns);
+    }
+    if (_reader->stats().json_flatten_ns > 0) {
+        RuntimeProfile::Counter* c = ADD_CHILD_TIMER(_runtime_profile, "FlatJsonFlatten", parent_name);
+        COUNTER_UPDATE(c, _reader->stats().json_flatten_ns);
+    }
 }
 
 } // namespace starrocks::pipeline
diff --git a/be/src/exec/pipeline/scan/olap_chunk_source.h b/be/src/exec/pipeline/scan/olap_chunk_source.h
index 3348c61dd17426..e52513ac34843e 100644
--- a/be/src/exec/pipeline/scan/olap_chunk_source.h
+++ b/be/src/exec/pipeline/scan/olap_chunk_source.h
@@ -155,7 +155,6 @@ class OlapChunkSource final : public ChunkSource {
     RuntimeProfile::Counter* _total_columns_data_page_count = nullptr;
     RuntimeProfile::Counter* _read_pk_index_timer = nullptr;
     RuntimeProfile::Counter* _pushdown_access_paths_counter = nullptr;
-    RuntimeProfile::Counter* _json_flatten_timer = nullptr;
     RuntimeProfile::Counter* _access_path_hits_counter = nullptr;
     RuntimeProfile::Counter* _access_path_unhits_counter = nullptr;
 };
diff --git a/be/src/exec/schema_scan_node.cpp b/be/src/exec/schema_scan_node.cpp
index 0188f2496c4906..d521be6ce57530 100644
--- a/be/src/exec/schema_scan_node.cpp
+++ b/be/src/exec/schema_scan_node.cpp
@@ -302,8 +302,7 @@ std::vector<std::shared_ptr<pipeline::OperatorFactory>> SchemaScanNode::decompos
         pipeline::PipelineBuilderContext* context) {
     auto exec_group = context->find_exec_group_by_plan_node_id(_id);
     context->set_current_execution_group(exec_group);
-    // the dop of SchemaScanOperator should always be 1.
-    size_t dop = 1;
+    size_t dop = context->dop_of_source_operator(_id);
 
     size_t buffer_capacity = pipeline::ScanOperator::max_buffer_capacity() * dop;
     pipeline::ChunkBufferLimiterPtr buffer_limiter = std::make_unique<pipeline::DynamicChunkBufferLimiter>(
diff --git a/be/src/exec/schema_scanner/schema_materialized_views_scanner.cpp b/be/src/exec/schema_scanner/schema_materialized_views_scanner.cpp
index 790cf9c0bca338..75976a90e8c0cf 100644
--- a/be/src/exec/schema_scanner/schema_materialized_views_scanner.cpp
+++ b/be/src/exec/schema_scanner/schema_materialized_views_scanner.cpp
@@ -60,6 +60,7 @@ SchemaScanner::ColumnDesc SchemaMaterializedViewsScanner::_s_tbls_columns[] = {
          false},
         {"EXTRA_MESSAGE", TypeDescriptor::create_varchar_type(sizeof(StringValue)), sizeof(StringValue), false},
         {"QUERY_REWRITE_STATUS", TypeDescriptor::create_varchar_type(sizeof(StringValue)), sizeof(StringValue), false},
+        {"CREATOR", TypeDescriptor::create_varchar_type(sizeof(StringValue)), sizeof(StringValue), false},
 };
 
 SchemaMaterializedViewsScanner::SchemaMaterializedViewsScanner()
@@ -118,7 +119,8 @@ Status SchemaMaterializedViewsScanner::fill_chunk(ChunkPtr* chunk) {
                            Slice(info.rows),
                            Slice(info.text),
                            Slice(info.extra_message),
-                           Slice(info.query_rewrite_status)};
+                           Slice(info.query_rewrite_status),
+                           Slice(info.creator)};
 
     for (const auto& [slot_id, index] : slot_id_map) {
         Column* column = (*chunk)->get_column_by_slot_id(slot_id).get();
diff --git a/be/src/exec/schema_scanner/schema_tasks_scanner.cpp b/be/src/exec/schema_scanner/schema_tasks_scanner.cpp
index 3bc190bd0af335..99738251bf7ca4 100644
--- a/be/src/exec/schema_scanner/schema_tasks_scanner.cpp
+++ b/be/src/exec/schema_scanner/schema_tasks_scanner.cpp
@@ -30,6 +30,7 @@ SchemaScanner::ColumnDesc SchemaTasksScanner::_s_tbls_columns[] = {
         {"DEFINITION", TypeDescriptor::create_varchar_type(sizeof(StringValue)), sizeof(StringValue), false},
         {"EXPIRE_TIME", TypeDescriptor::from_logical_type(TYPE_DATETIME), sizeof(StringValue), true},
         {"PROPERTIES", TypeDescriptor::create_varchar_type(sizeof(StringValue)), sizeof(StringValue), false},
+        {"CREATOR", TypeDescriptor::create_varchar_type(sizeof(StringValue)), sizeof(StringValue), false},
 };
 
 SchemaTasksScanner::SchemaTasksScanner()
@@ -63,10 +64,8 @@ DatumArray SchemaTasksScanner::_build_row() {
                                 ? TimestampValue::create_from_unixtime(task.create_time, _runtime_state->timezone_obj())
                                 : kNullDatum;
 
-    return {
-            Slice(task.task_name),  create_time, Slice(task.schedule),   Slice(task.catalog), Slice(task.database),
-            Slice(task.definition), expire_time, Slice(task.properties),
-    };
+    return {Slice(task.task_name),  create_time, Slice(task.schedule),   Slice(task.catalog), Slice(task.database),
+            Slice(task.definition), expire_time, Slice(task.properties), Slice(task.creator)};
 }
 
 Status SchemaTasksScanner::fill_chunk(ChunkPtr* chunk) {
diff --git a/be/src/exec/topn_node.cpp b/be/src/exec/topn_node.cpp
index 0a9a0bcbd2b469..dbe96de9139f3c 100644
--- a/be/src/exec/topn_node.cpp
+++ b/be/src/exec/topn_node.cpp
@@ -372,8 +372,9 @@ pipeline::OpFactories TopNNode::decompose_to_pipeline(pipeline::PipelineBuilderC
     bool is_partition_skewed =
             _tnode.sort_node.__isset.analytic_partition_skewed && _tnode.sort_node.analytic_partition_skewed;
     bool need_merge = _analytic_partition_exprs.empty() || is_partition_skewed;
-    bool enable_parallel_merge =
-            _tnode.sort_node.__isset.enable_parallel_merge && _tnode.sort_node.enable_parallel_merge;
+    bool enable_parallel_merge = _tnode.sort_node.__isset.enable_parallel_merge &&
+                                 _tnode.sort_node.enable_parallel_merge &&
+                                 !_sort_exec_exprs.lhs_ordering_expr_ctxs().empty();
 
     OpFactories operators_source_with_sort;
 
diff --git a/be/src/exprs/CMakeLists.txt b/be/src/exprs/CMakeLists.txt
index 2f9b0404ffa8b9..cb1bdb7cda8372 100644
--- a/be/src/exprs/CMakeLists.txt
+++ b/be/src/exprs/CMakeLists.txt
@@ -21,6 +21,7 @@ set(EXPR_FILES
   agg/factory/aggregate_factory.cpp
   agg/factory/aggregate_resolver_approx.cpp
   agg/factory/aggregate_resolver_avg.cpp
+  agg/factory/aggregate_resolver_hypothesis_testing.cpp
   agg/factory/aggregate_resolver_minmaxany.cpp
   agg/factory/aggregate_resolver_others.cpp
   agg/factory/aggregate_resolver_sumcount.cpp
diff --git a/be/src/exprs/agg/aggregate_factory.h b/be/src/exprs/agg/aggregate_factory.h
index 65ac3deda2352b..90b6f7d91c6454 100644
--- a/be/src/exprs/agg/aggregate_factory.h
+++ b/be/src/exprs/agg/aggregate_factory.h
@@ -29,4 +29,7 @@ const AggregateFunction* get_window_function(const std::string& name, LogicalTyp
                                              TFunctionBinaryType::type binary_type = TFunctionBinaryType::BUILTIN,
                                              int func_version = 1);
 
+const AggregateFunction* get_aggregate_function(const std::string& agg_func_name, const TypeDescriptor& return_type,
+                                                const std::vector<TypeDescriptor>& arg_types, bool is_input_nullable,
+                                                TFunctionBinaryType::type binary_type, int func_version = 1);
 } // namespace starrocks
diff --git a/be/src/exprs/agg/aggregate_state_allocator.h b/be/src/exprs/agg/aggregate_state_allocator.h
index b980ee8e909c05..66d7f85dc0933b 100644
--- a/be/src/exprs/agg/aggregate_state_allocator.h
+++ b/be/src/exprs/agg/aggregate_state_allocator.h
@@ -17,6 +17,7 @@
 #include "column/hash_set.h"
 #include "common/config.h"
 #include "runtime/memory/allocator.h"
+#include "runtime/memory/roaring_hook.h"
 
 namespace starrocks {
 
@@ -92,4 +93,20 @@ using SliceHashSetWithAggStateAllocator = phmap::flat_hash_set<SliceWithHash, Ha
 
 template <typename T>
 using VectorWithAggStateAllocator = std::vector<T, AggregateStateAllocator<T>>;
+
+// Thread local aggregate state allocator setter with roaring allocator
+class ThreadLocalStateAllocatorSetter {
+public:
+    ThreadLocalStateAllocatorSetter(Allocator* allocator)
+            : _agg_state_allocator_setter(allocator), _roaring_allocator_setter(allocator) {}
+    ~ThreadLocalStateAllocatorSetter() = default;
+
+private:
+    ThreadLocalAggregateStateAllocatorSetter _agg_state_allocator_setter;
+    ThreadLocalRoaringAllocatorSetter _roaring_allocator_setter;
+};
+
+#define SCOPED_THREAD_LOCAL_STATE_ALLOCATOR_SETTER(allocator) \
+    auto VARNAME_LINENUM(alloc_setter) = ThreadLocalStateAllocatorSetter(allocator)
+
 } // namespace starrocks
diff --git a/be/src/exprs/agg/array_agg.h b/be/src/exprs/agg/array_agg.h
index e4520550a1e299..ac15f44573d2ba 100644
--- a/be/src/exprs/agg/array_agg.h
+++ b/be/src/exprs/agg/array_agg.h
@@ -94,19 +94,12 @@ struct ArrayAggAggregateState {
         return &data_column;
     }
 
-    bool check_overflow(FunctionContext* ctx) const {
-        std::string err_msg;
-        if (UNLIKELY(data_column.capacity_limit_reached(&err_msg))) {
-            ctx->set_error(fmt::format("The column generated by array_agg is overflow: {}", err_msg).c_str());
-            return true;
-        }
-        return false;
-    }
+    bool check_overflow(FunctionContext* ctx) const { return check_overflow(data_column, ctx); }
 
     static bool check_overflow(const Column& col, FunctionContext* ctx) {
-        std::string err_msg;
-        if (UNLIKELY(col.capacity_limit_reached(&err_msg))) {
-            ctx->set_error(fmt::format("The column generated by array_agg is overflow: {}", err_msg).c_str());
+        Status st = col.capacity_limit_reached();
+        if (!st.ok()) {
+            ctx->set_error(fmt::format("The column generated by array_agg is overflow: {}", st.message()).c_str());
             return true;
         }
         return false;
@@ -195,8 +188,9 @@ struct ArrayAggAggregateStateV2 {
     bool check_overflow(FunctionContext* ctx) const {
         std::string err_msg;
         for (size_t i = 0; i < data_columns.size(); i++) {
-            if (UNLIKELY(data_columns[i]->capacity_limit_reached(&err_msg))) {
-                ctx->set_error(fmt::format("The column generated by array_agg is overflow: {}", err_msg).c_str());
+            Status st = data_columns[i]->capacity_limit_reached();
+            if (!st.ok()) {
+                ctx->set_error(fmt::format("The column generated by array_agg is overflow: {}", st.message()).c_str());
                 return true;
             }
         }
@@ -204,9 +198,9 @@ struct ArrayAggAggregateStateV2 {
     }
 
     static bool check_overflow(const Column& col, FunctionContext* ctx) {
-        std::string err_msg;
-        if (UNLIKELY(col.capacity_limit_reached(&err_msg))) {
-            ctx->set_error(fmt::format("The column generated by array_agg is overflow: {}", err_msg).c_str());
+        Status st = col.capacity_limit_reached();
+        if (!st.ok()) {
+            ctx->set_error(fmt::format("The column generated by array_agg is overflow: {}", st.message()).c_str());
             return true;
         }
         return false;
diff --git a/be/src/exprs/agg/avg.h b/be/src/exprs/agg/avg.h
index d3608501c302df..cfdf6d5663df02 100644
--- a/be/src/exprs/agg/avg.h
+++ b/be/src/exprs/agg/avg.h
@@ -211,13 +211,14 @@ class AvgAggregateFunction final
 
     void finalize_to_column(FunctionContext* ctx, ConstAggDataPtr __restrict state, Column* to) const override {
         DCHECK(!to->is_nullable());
+        auto* column = down_cast<ResultColumnType*>(to);
         // In fact, for StarRocks real query, we don't need this check.
         // But for robust, we add this check.
         if (this->data(state).count == 0) {
+            column->append_default();
             return;
         }
 
-        auto* column = down_cast<ResultColumnType*>(to);
         ResultType result;
         if constexpr (lt_is_decimalv2<LT>) {
             result = this->data(state).sum / DecimalV2Value(this->data(state).count, 0);
diff --git a/be/src/exprs/agg/ds_hll_count_distinct.h b/be/src/exprs/agg/ds_hll_count_distinct.h
new file mode 100644
index 00000000000000..e83914e0de2cc2
--- /dev/null
+++ b/be/src/exprs/agg/ds_hll_count_distinct.h
@@ -0,0 +1,240 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include "column/binary_column.h"
+#include "column/object_column.h"
+#include "column/type_traits.h"
+#include "column/vectorized_fwd.h"
+#include "exprs/agg/aggregate.h"
+#include "gutil/casts.h"
+#include "types/hll_sketch.h"
+
+namespace starrocks {
+
+struct HLLSketchState {
+    std::unique_ptr<DataSketchesHll> hll_sketch = nullptr;
+    int64_t memory_usage = 0;
+};
+
+/**
+ * RETURN_TYPE: TYPE_BIGINT
+ * ARGS_TYPE: ALL TYPE
+ * SERIALIZED_TYPE: TYPE_VARCHAR
+ */
+template <LogicalType LT, typename T = RunTimeCppType<LT>>
+class HllSketchAggregateFunction final
+        : public AggregateFunctionBatchHelper<HLLSketchState, HllSketchAggregateFunction<LT, T>> {
+public:
+    using ColumnType = RunTimeColumnType<LT>;
+
+    void reset(FunctionContext* ctx, const Columns& args, AggDataPtr state) const override {
+        if (this->data(state).hll_sketch != nullptr) {
+            ctx->add_mem_usage(-this->data(state).hll_sketch->mem_usage());
+            this->data(state).hll_sketch->clear();
+        }
+    }
+
+    void update_state(FunctionContext* ctx, AggDataPtr state, uint64_t value) const {
+        int64_t prev_memory = this->data(state).hll_sketch->mem_usage();
+        this->data(state).hll_sketch->update(value);
+        ctx->add_mem_usage(this->data(state).hll_sketch->mem_usage() - prev_memory);
+    }
+
+    void update(FunctionContext* ctx, const Column** columns, AggDataPtr __restrict state,
+                size_t row_num) const override {
+        // init state if needed
+        _init_if_needed(ctx, columns, state);
+
+        uint64_t value = 0;
+        const ColumnType* column = down_cast<const ColumnType*>(columns[0]);
+
+        if constexpr (lt_is_string<LT>) {
+            Slice s = column->get_slice(row_num);
+            value = HashUtil::murmur_hash64A(s.data, s.size, HashUtil::MURMUR_SEED);
+        } else {
+            const auto& v = column->get_data();
+            value = HashUtil::murmur_hash64A(&v[row_num], sizeof(v[row_num]), HashUtil::MURMUR_SEED);
+        }
+        update_state(ctx, state, value);
+    }
+
+    void update_batch_single_state_with_frame(FunctionContext* ctx, AggDataPtr __restrict state, const Column** columns,
+                                              int64_t peer_group_start, int64_t peer_group_end, int64_t frame_start,
+                                              int64_t frame_end) const override {
+        // init state if needed
+        _init_if_needed(ctx, columns, state);
+        const ColumnType* column = down_cast<const ColumnType*>(columns[0]);
+        if constexpr (lt_is_string<LT>) {
+            uint64_t value = 0;
+            for (size_t i = frame_start; i < frame_end; ++i) {
+                Slice s = column->get_slice(i);
+                value = HashUtil::murmur_hash64A(s.data, s.size, HashUtil::MURMUR_SEED);
+
+                if (value != 0) {
+                    update_state(ctx, state, value);
+                }
+            }
+        } else {
+            uint64_t value = 0;
+            const auto& v = column->get_data();
+            for (size_t i = frame_start; i < frame_end; ++i) {
+                value = HashUtil::murmur_hash64A(&v[i], sizeof(v[i]), HashUtil::MURMUR_SEED);
+
+                if (value != 0) {
+                    update_state(ctx, state, value);
+                }
+            }
+        }
+    }
+
+    void merge(FunctionContext* ctx, const Column* column, AggDataPtr __restrict state, size_t row_num) const override {
+        DCHECK(column->is_binary());
+        const BinaryColumn* hll_column = down_cast<const BinaryColumn*>(column);
+        DataSketchesHll hll(hll_column->get(row_num).get_slice(), &(this->data(state).memory_usage));
+        if (UNLIKELY(this->data(state).hll_sketch == nullptr)) {
+            this->data(state).hll_sketch = std::make_unique<DataSketchesHll>(
+                    hll.get_lg_config_k(), hll.get_target_type(), &(this->data(state).memory_usage));
+        }
+        int64_t prev_memory = this->data(state).hll_sketch->mem_usage();
+        this->data(state).hll_sketch->merge(hll);
+        ctx->add_mem_usage(this->data(state).hll_sketch->mem_usage() - prev_memory);
+    }
+
+    void get_values(FunctionContext* ctx, ConstAggDataPtr __restrict state, Column* dst, size_t start,
+                    size_t end) const override {
+        DCHECK_GT(end, start);
+        Int64Column* column = down_cast<Int64Column*>(dst);
+        int64_t result = 0L;
+        if (LIKELY(this->data(state).hll_sketch != nullptr)) {
+            result = this->data(state).hll_sketch->estimate_cardinality();
+        }
+        for (size_t i = start; i < end; ++i) {
+            column->get_data()[i] = result;
+        }
+    }
+
+    void serialize_to_column([[maybe_unused]] FunctionContext* ctx, ConstAggDataPtr __restrict state,
+                             Column* to) const override {
+        DCHECK(to->is_binary());
+        auto* column = down_cast<BinaryColumn*>(to);
+        if (UNLIKELY(this->data(state).hll_sketch == nullptr)) {
+            column->append_default();
+        } else {
+            size_t size = this->data(state).hll_sketch->serialize_size();
+            uint8_t result[size];
+            size = this->data(state).hll_sketch->serialize(result);
+            column->append(Slice(result, size));
+        }
+    }
+
+    void convert_to_serialize_format([[maybe_unused]] FunctionContext* ctx, const Columns& src, size_t chunk_size,
+                                     ColumnPtr* dst) const override {
+        const ColumnType* column = down_cast<const ColumnType*>(src[0].get());
+        auto* result = down_cast<BinaryColumn*>((*dst).get());
+
+        Bytes& bytes = result->get_bytes();
+        bytes.reserve(chunk_size * 10);
+        result->get_offset().resize(chunk_size + 1);
+
+        size_t old_size = bytes.size();
+        uint64_t value = 0;
+        uint8_t log_k;
+        datasketches::target_hll_type tgt_type;
+        // convert to const Column*
+        std::vector<const Column*> src_datas;
+        src_datas.reserve(src.size());
+        std::transform(src.begin(), src.end(), std::back_inserter(src_datas),
+                       [](const ColumnPtr& col) { return col.get(); });
+        const Column** src_datas_ptr = src_datas.data();
+        std::tie(log_k, tgt_type) = _parse_hll_sketch_args(ctx, src_datas_ptr);
+        for (size_t i = 0; i < chunk_size; ++i) {
+            int64_t memory_usage = 0;
+            DataSketchesHll hll{log_k, tgt_type, &memory_usage};
+            if constexpr (lt_is_string<LT>) {
+                Slice s = column->get_slice(i);
+                value = HashUtil::murmur_hash64A(s.data, s.size, HashUtil::MURMUR_SEED);
+            } else {
+                auto v = column->get_data()[i];
+                value = HashUtil::murmur_hash64A(&v, sizeof(v), HashUtil::MURMUR_SEED);
+            }
+            if (value != 0) {
+                hll.update(value);
+            }
+
+            size_t new_size = old_size + hll.serialize_size();
+            bytes.resize(new_size);
+            hll.serialize(bytes.data() + old_size);
+
+            result->get_offset()[i + 1] = new_size;
+            old_size = new_size;
+        }
+    }
+
+    void finalize_to_column(FunctionContext* ctx __attribute__((unused)), ConstAggDataPtr __restrict state,
+                            Column* to) const override {
+        DCHECK(to->is_numeric());
+
+        auto* column = down_cast<Int64Column*>(to);
+        if (UNLIKELY(this->data(state).hll_sketch == nullptr)) {
+            column->append(0L);
+        } else {
+            column->append(this->data(state).hll_sketch->estimate_cardinality());
+        }
+    }
+
+    std::string get_name() const override { return "ds_hll_count_distinct"; }
+
+private:
+    // init hll sketch if needed
+    void _init_if_needed(FunctionContext* ctx, const Column** columns, AggDataPtr __restrict state) const {
+        if (UNLIKELY(this->data(state).hll_sketch == nullptr)) {
+            uint8_t log_k;
+            datasketches::target_hll_type tgt_type;
+            std::tie(log_k, tgt_type) = _parse_hll_sketch_args(ctx, columns);
+            this->data(state).hll_sketch = _init_hll_sketch(log_k, tgt_type, &(this->data(state).memory_usage));
+        }
+    }
+
+    // parse log_k and target type from args
+    std::tuple<uint8_t, datasketches::target_hll_type> _parse_hll_sketch_args(FunctionContext* ctx,
+                                                                              const Column** columns) const {
+        uint8_t log_k = DEFAULT_HLL_LOG_K;
+        datasketches::target_hll_type tgt_type = datasketches::HLL_6;
+        if (ctx->get_num_args() == 2) {
+            log_k = (uint8_t)(columns[1]->get(0).get_int32());
+        } else if (ctx->get_num_args() == 3) {
+            log_k = (uint8_t)(columns[1]->get(0).get_int32());
+            std::string tgt_type_str = columns[2]->get(0).get_slice().to_string();
+            std::transform(tgt_type_str.begin(), tgt_type_str.end(), tgt_type_str.begin(), ::toupper);
+            if (tgt_type_str == "HLL_4") {
+                tgt_type = datasketches::HLL_4;
+            } else if (tgt_type_str == "HLL_8") {
+                tgt_type = datasketches::HLL_8;
+            } else {
+                tgt_type = datasketches::HLL_6;
+            }
+        }
+        return {log_k, tgt_type};
+    }
+
+    // init hll sketch with default log_k and target type
+    std::unique_ptr<DataSketchesHll> _init_hll_sketch(uint8_t log_k, datasketches::target_hll_type tgt_type,
+                                                      int64_t* memory_usage) const {
+        return std::make_unique<DataSketchesHll>(log_k, tgt_type, memory_usage);
+    }
+};
+
+} // namespace starrocks
diff --git a/be/src/exprs/agg/factory/aggregate_factory.cpp b/be/src/exprs/agg/factory/aggregate_factory.cpp
index dcc63993f26c7e..d790204ba91eb3 100644
--- a/be/src/exprs/agg/factory/aggregate_factory.cpp
+++ b/be/src/exprs/agg/factory/aggregate_factory.cpp
@@ -15,15 +15,11 @@
 #include "exprs/agg/aggregate_factory.h"
 
 #include <memory>
-#include <tuple>
-#include <unordered_map>
 
-#include "column/type_traits.h"
 #include "exprs/agg/aggregate.h"
 #include "exprs/agg/factory/aggregate_factory.hpp"
 #include "exprs/agg/factory/aggregate_resolver.hpp"
 #include "types/logical_type.h"
-#include "types/logical_type_infra.h"
 #include "udf/java/java_function_fwd.h"
 
 namespace starrocks {
@@ -40,6 +36,7 @@ AggregateFuncResolver::AggregateFuncResolver() {
     register_approx();
     register_others();
     register_retract_functions();
+    register_hypothesis_testing();
 }
 
 AggregateFuncResolver::~AggregateFuncResolver() = default;
@@ -168,4 +165,45 @@ const AggregateFunction* get_window_function(const std::string& name, LogicalTyp
     return nullptr;
 }
 
+const AggregateFunction* get_aggregate_function(const std::string& agg_func_name, const TypeDescriptor& return_type,
+                                                const std::vector<TypeDescriptor>& arg_types, bool is_result_nullable,
+                                                TFunctionBinaryType::type binary_type, int func_version) {
+    // get function
+    if (agg_func_name == "count") {
+        return get_aggregate_function("count", TYPE_BIGINT, TYPE_BIGINT, is_result_nullable);
+    } else {
+        DCHECK_GE(arg_types.size(), 1);
+        TypeDescriptor arg_type = arg_types[0];
+        // Because intersect_count have two input types.
+        // And intersect_count's first argument's type is alwasy Bitmap,
+        // so we use its second arguments type as input.
+        if (agg_func_name == "intersect_count") {
+            arg_type = arg_types[1];
+        }
+
+        // Because max_by and min_by function have two input types,
+        // so we use its second arguments type as input.
+        if (agg_func_name == "max_by" || agg_func_name == "min_by") {
+            arg_type = arg_types[1];
+        }
+
+        // Because windowfunnel have more two input types.
+        // functions registry use 2th args(datetime/date).
+        if (agg_func_name == "window_funnel") {
+            arg_type = arg_types[1];
+        }
+
+        // hack for accepting various arguments
+        if (agg_func_name == "exchange_bytes" || agg_func_name == "exchange_speed") {
+            arg_type = TypeDescriptor(TYPE_BIGINT);
+        }
+
+        if (agg_func_name == "array_union_agg" || agg_func_name == "array_unique_agg") {
+            arg_type = arg_type.children[0];
+        }
+        return get_aggregate_function(agg_func_name, arg_type.type, return_type.type, is_result_nullable, binary_type,
+                                      func_version);
+    }
+}
+
 } // namespace starrocks
diff --git a/be/src/exprs/agg/factory/aggregate_factory.hpp b/be/src/exprs/agg/factory/aggregate_factory.hpp
index a38fb2fa18644b..f8f605bfa7eceb 100644
--- a/be/src/exprs/agg/factory/aggregate_factory.hpp
+++ b/be/src/exprs/agg/factory/aggregate_factory.hpp
@@ -15,8 +15,6 @@
 #pragma once
 
 #include <memory>
-#include <tuple>
-#include <unordered_map>
 
 #include "column/type_traits.h"
 #include "exprs/agg/aggregate.h"
@@ -33,14 +31,15 @@
 #include "exprs/agg/count.h"
 #include "exprs/agg/covariance.h"
 #include "exprs/agg/distinct.h"
+#include "exprs/agg/ds_hll_count_distinct.h"
 #include "exprs/agg/exchange_perf.h"
 #include "exprs/agg/group_concat.h"
 #include "exprs/agg/histogram.h"
 #include "exprs/agg/hll_ndv.h"
-#include "exprs/agg/hll_sketch.h"
 #include "exprs/agg/hll_union.h"
 #include "exprs/agg/hll_union_count.h"
 #include "exprs/agg/intersect_count.h"
+#include "exprs/agg/mann_whitney.h"
 #include "exprs/agg/maxmin.h"
 #include "exprs/agg/maxmin_by.h"
 #include "exprs/agg/nullable_aggregate.h"
@@ -120,6 +119,10 @@ class AggregateFactory {
         return std::make_shared<GroupConcatAggregateFunctionV2>();
     }
 
+    static auto MakeMannWhitneyUTestAggregateFunction() {
+        return std::make_shared<MannWhitneyUTestAggregateFunction>();
+    }
+
     template <LogicalType LT>
     static auto MakeMaxAggregateFunction();
 
diff --git a/be/src/exprs/agg/factory/aggregate_resolver.hpp b/be/src/exprs/agg/factory/aggregate_resolver.hpp
index a9721c5ec7a07e..9bdc9bb862ce23 100644
--- a/be/src/exprs/agg/factory/aggregate_resolver.hpp
+++ b/be/src/exprs/agg/factory/aggregate_resolver.hpp
@@ -22,7 +22,6 @@
 #include "exprs/agg/aggregate.h"
 #include "exprs/agg/factory/aggregate_factory.hpp"
 #include "types/logical_type.h"
-#include "types/logical_type_infra.h"
 #include "udf/java/java_function_fwd.h"
 
 namespace starrocks {
@@ -68,6 +67,7 @@ class AggregateFuncResolver {
     void register_approx();
     void register_others();
     void register_retract_functions();
+    void register_hypothesis_testing();
 
     const std::vector<LogicalType>& aggregate_types() const {
         const static std::vector<LogicalType> kTypes{
diff --git a/be/src/exprs/agg/factory/aggregate_resolver_hypothesis_testing.cpp b/be/src/exprs/agg/factory/aggregate_resolver_hypothesis_testing.cpp
new file mode 100644
index 00000000000000..66f88817876340
--- /dev/null
+++ b/be/src/exprs/agg/factory/aggregate_resolver_hypothesis_testing.cpp
@@ -0,0 +1,26 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "exprs/agg/factory/aggregate_factory.hpp"
+#include "exprs/agg/factory/aggregate_resolver.hpp"
+#include "types/logical_type.h"
+
+namespace starrocks {
+
+void AggregateFuncResolver::register_hypothesis_testing() {
+    add_aggregate_mapping_variadic<TYPE_DOUBLE, TYPE_JSON, MannWhitneyAggregateState>(
+            "mann_whitney_u_test", false, AggregateFactory::MakeMannWhitneyUTestAggregateFunction());
+}
+
+} // namespace starrocks
diff --git a/be/src/exprs/agg/helpers/serialize_helpers.hpp b/be/src/exprs/agg/helpers/serialize_helpers.hpp
new file mode 100644
index 00000000000000..395cc4c6376b75
--- /dev/null
+++ b/be/src/exprs/agg/helpers/serialize_helpers.hpp
@@ -0,0 +1,258 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include <fmt/format.h>
+
+#include <algorithm>
+#include <boost/type_index.hpp>
+#include <cstddef>
+#include <cstdint>
+#include <map>
+#include <set>
+#include <string>
+#include <type_traits>
+#include <unordered_map>
+#include <unordered_set>
+#include <vector>
+
+namespace starrocks {
+
+class SerializeHelpers {
+public:
+    template <typename T>
+    static void serialize(const T* data, uint8_t*& buffer, size_t num_elems = 1) {
+        using T_ = std::remove_cv_t<std::remove_reference_t<T>>;
+        std::copy_n(reinterpret_cast<const uint8_t*>(data), num_elems * sizeof(T), buffer);
+        buffer += num_elems * sizeof(T);
+    }
+
+    template <typename T>
+    static void deserialize(const uint8_t*& buffer, T* data, size_t num_elems = 1) {
+        using T_ = std::remove_cv_t<std::remove_reference_t<T>>;
+        std::copy_n(buffer, num_elems * sizeof(T), reinterpret_cast<uint8_t*>(data));
+        buffer += num_elems * sizeof(T);
+    }
+
+    template <typename T>
+    static void serialize(const T& data, uint8_t*& buffer) {
+        serialize(&data, buffer, 1);
+    }
+
+    template <typename T>
+    static void deserialize(const uint8_t*& buffer, T& data) {
+        deserialize(buffer, &data, 1);
+    }
+
+    static void serialize(const std::string& data, uint8_t*& buffer) {
+        size_t size = data.length();
+        serialize(size, buffer);
+        serialize(data.data(), buffer, size);
+    }
+
+    static void deserialize(const uint8_t*& buffer, std::string& data) {
+        size_t size = 0;
+        deserialize(buffer, size);
+        data.resize(size);
+        deserialize(buffer, data.data(), size);
+    }
+
+    template <typename T>
+    static void serialize(std::vector<T> const& data, uint8_t*& buffer) {
+        size_t size = data.size();
+        serialize(size, buffer);
+        for (auto const& elem : data) {
+            serialize(elem, buffer);
+        }
+    }
+
+    template <typename T>
+    static void deserialize(const uint8_t*& buffer, std::vector<T>& data) {
+        size_t size = 0;
+        deserialize(buffer, size);
+        data.resize(size);
+        for (auto& elem : data) {
+            deserialize(buffer, elem);
+        }
+    }
+
+    template <typename MapType>
+    static typename std::enable_if_t<
+            std::is_same_v<MapType, std::map<typename MapType::key_type, typename MapType::mapped_type>> ||
+                    std::is_same_v<MapType,
+                                   std::unordered_map<typename MapType::key_type, typename MapType::mapped_type>>,
+            void>
+    serialize(MapType const& data, uint8_t*& buffer) {
+        size_t size = data.size();
+        serialize(size, buffer);
+        for (auto const& [key, value] : data) {
+            serialize(key, buffer);
+            serialize(value, buffer);
+        }
+    }
+
+    template <typename MapType>
+    static typename std::enable_if_t<
+            std::is_same_v<MapType, std::map<typename MapType::key_type, typename MapType::mapped_type>> ||
+                    std::is_same_v<MapType,
+                                   std::unordered_map<typename MapType::key_type, typename MapType::mapped_type>>,
+            void>
+    deserialize(const uint8_t*& buffer, MapType& data) {
+        size_t size = 0;
+        deserialize(buffer, size);
+        for (size_t i = 0; i < size; ++i) {
+            typename MapType::key_type key;
+            typename MapType::mapped_type value;
+            deserialize(buffer, key);
+            deserialize(buffer, value);
+            data[std::move(key)] = std::move(value);
+        }
+    }
+
+    template <typename SetType>
+    static typename std::enable_if_t<std::is_same_v<SetType, std::set<typename SetType::key_type>> ||
+                                             std::is_same_v<SetType, std::unordered_set<typename SetType::key_type>>,
+                                     void>
+    serialize(SetType const& data, uint8_t*& buffer) {
+        size_t size = data.size();
+        serialize(size, buffer);
+        for (auto const& key : data) {
+            serialize(key, buffer);
+        }
+    }
+
+    template <typename SetType>
+    static typename std::enable_if_t<std::is_same_v<SetType, std::set<typename SetType::key_type>> ||
+                                             std::is_same_v<SetType, std::unordered_set<typename SetType::key_type>>,
+                                     void>
+    deserialize(const uint8_t*& buffer, SetType& data) {
+        size_t size = 0;
+        deserialize(buffer, size);
+        for (size_t i = 0; i < size; ++i) {
+            typename SetType::key_type key;
+            deserialize(buffer, key);
+            data.emplace(std::move(key));
+        }
+    }
+
+    template <typename ElemType, size_t Length>
+    static void serialize(std::array<ElemType, Length> const& data, uint8_t*& buffer) {
+        for (auto const& elem : data) {
+            serialize(elem, buffer);
+        }
+    }
+
+    template <typename ElemType, size_t Length>
+    static void deserialize(const uint8_t*& buffer, std::array<ElemType, Length>& data) {
+        for (auto& elem : data) {
+            deserialize(buffer, elem);
+        }
+    }
+
+    template <typename T>
+    static size_t serialized_size(T const&) {
+        return sizeof(T);
+    }
+
+    static size_t serialized_size(std::string const& str) { return sizeof(size_t) + sizeof(char) * str.length(); }
+
+    template <typename T>
+    static size_t serialized_size(std::vector<T> const& vec) {
+        size_t size = sizeof(size_t);
+        for (auto const& elem : vec) {
+            size += serialized_size(elem);
+        }
+        return size;
+    }
+
+    template <typename T, size_t Length>
+    static size_t serialized_size(std::array<T, Length> const& vec) {
+        size_t size = 0;
+        for (auto const& elem : vec) {
+            size += serialized_size(elem);
+        }
+        return size;
+    }
+
+    template <typename MapType>
+    static typename std::enable_if_t<
+            std::is_same_v<MapType, std::map<typename MapType::key_type, typename MapType::mapped_type>> ||
+                    std::is_same_v<MapType,
+                                   std::unordered_map<typename MapType::key_type, typename MapType::mapped_type>>,
+            size_t>
+    serialized_size(MapType const& data) {
+        size_t size = sizeof(size_t);
+        for (auto const& [key, value] : data) {
+            size += serialized_size(key) + serialized_size(value);
+        }
+        return size;
+    }
+
+    template <typename SetType>
+    static typename std::enable_if_t<std::is_same_v<SetType, std::set<typename SetType::key_type>> ||
+                                             std::is_same_v<SetType, std::unordered_set<typename SetType::key_type>>,
+                                     size_t>
+    serialized_size(SetType const& data) {
+        size_t size = sizeof(size_t);
+        for (auto const& elem : data) {
+            size += serialized_size(elem);
+        }
+        return size;
+    }
+
+    template <typename... Args>
+    static size_t serialized_size(std::tuple<Args...> const& tuple) {
+        size_t size = 0;
+        std::apply([&size](const auto&... element) { ((size += serialized_size(element)), ...); }, tuple);
+        return size;
+    }
+
+    template <typename... Args>
+    static void serialize(std::tuple<Args...> const& tuple, uint8_t*& buffer) {
+        std::apply([&buffer](const auto&... element) { (serialize(element, buffer), ...); }, tuple);
+    }
+
+    template <typename... Args>
+    static void deserialize(const uint8_t*& buffer, std::tuple<Args...>& tuple) {
+        std::apply([&buffer](auto&... element) { (deserialize(buffer, element), ...); }, tuple);
+    }
+
+    template <typename First, typename... Args>
+    static size_t serialized_size_all(First&& first, Args&&... rest) {
+        if constexpr (sizeof...(rest) == 0) {
+            return serialized_size(first);
+        } else {
+            return serialized_size(first) + serialized_size_all(std::forward<Args>(rest)...);
+        }
+    }
+
+    template <typename First, typename... Args>
+    static void serialize_all(uint8_t*& data, First const& first, Args&&... rest) {
+        serialize(first, data);
+        if constexpr (sizeof...(rest) != 0) {
+            serialize_all(data, std::forward<Args>(rest)...);
+        }
+    }
+
+    template <typename First, typename... Args>
+    static void deserialize_all(const uint8_t*& data, First& first, Args&&... rest) {
+        deserialize(data, first);
+        if constexpr (sizeof...(rest) != 0) {
+            deserialize_all(data, std::forward<Args>(rest)...);
+        }
+    }
+};
+
+} // namespace starrocks
diff --git a/be/src/exprs/agg/hll_sketch.h b/be/src/exprs/agg/hll_sketch.h
deleted file mode 100644
index 8fd51fc3947461..00000000000000
--- a/be/src/exprs/agg/hll_sketch.h
+++ /dev/null
@@ -1,237 +0,0 @@
-// Copyright 2021-present StarRocks, Inc. All rights reserved.
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     https://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-#pragma once
-
-#include "column/binary_column.h"
-#include "column/object_column.h"
-#include "column/type_traits.h"
-#include "column/vectorized_fwd.h"
-#include "exprs/agg/aggregate.h"
-#include "gutil/casts.h"
-
-namespace starrocks {
-
-struct HLLSketchState {
-    std::unique_ptr<DataSketchesHll> hll_sketch = nullptr;
-};
-
-/**
- * RETURN_TYPE: TYPE_BIGINT
- * ARGS_TYPE: ALL TYPE
- * SERIALIZED_TYPE: TYPE_VARCHAR
- */
-template <LogicalType LT, typename T = RunTimeCppType<LT>>
-class HllSketchAggregateFunction final
-        : public AggregateFunctionBatchHelper<HLLSketchState, HllSketchAggregateFunction<LT, T>> {
-public:
-    using ColumnType = RunTimeColumnType<LT>;
-
-    void reset(FunctionContext* ctx, const Columns& args, AggDataPtr state) const override {
-        if (this->data(state).hll_sketch != nullptr) {
-            ctx->add_mem_usage(-this->data(state).hll_sketch->mem_usage());
-            this->data(state).hll_sketch->clear();
-        }
-    }
-
-    void update_state(FunctionContext* ctx, AggDataPtr state, uint64_t value) const {
-        int64_t prev_memory = this->data(state).hll_sketch->mem_usage();
-        this->data(state).hll_sketch->update(value);
-        ctx->add_mem_usage(this->data(state).hll_sketch->mem_usage() - prev_memory);
-    }
-
-    void update(FunctionContext* ctx, const Column** columns, AggDataPtr __restrict state,
-                size_t row_num) const override {
-        // init state if needed
-        _init_if_needed(ctx, columns, state);
-
-        uint64_t value = 0;
-        const ColumnType* column = down_cast<const ColumnType*>(columns[0]);
-
-        if constexpr (lt_is_string<LT>) {
-            Slice s = column->get_slice(row_num);
-            value = HashUtil::murmur_hash64A(s.data, s.size, HashUtil::MURMUR_SEED);
-        } else {
-            const auto& v = column->get_data();
-            value = HashUtil::murmur_hash64A(&v[row_num], sizeof(v[row_num]), HashUtil::MURMUR_SEED);
-        }
-        update_state(ctx, state, value);
-    }
-
-    void update_batch_single_state_with_frame(FunctionContext* ctx, AggDataPtr __restrict state, const Column** columns,
-                                              int64_t peer_group_start, int64_t peer_group_end, int64_t frame_start,
-                                              int64_t frame_end) const override {
-        // init state if needed
-        _init_if_needed(ctx, columns, state);
-        const ColumnType* column = down_cast<const ColumnType*>(columns[0]);
-        if constexpr (lt_is_string<LT>) {
-            uint64_t value = 0;
-            for (size_t i = frame_start; i < frame_end; ++i) {
-                Slice s = column->get_slice(i);
-                value = HashUtil::murmur_hash64A(s.data, s.size, HashUtil::MURMUR_SEED);
-
-                if (value != 0) {
-                    update_state(ctx, state, value);
-                }
-            }
-        } else {
-            uint64_t value = 0;
-            const auto& v = column->get_data();
-            for (size_t i = frame_start; i < frame_end; ++i) {
-                value = HashUtil::murmur_hash64A(&v[i], sizeof(v[i]), HashUtil::MURMUR_SEED);
-
-                if (value != 0) {
-                    update_state(ctx, state, value);
-                }
-            }
-        }
-    }
-
-    void merge(FunctionContext* ctx, const Column* column, AggDataPtr __restrict state, size_t row_num) const override {
-        DCHECK(column->is_binary());
-        const BinaryColumn* hll_column = down_cast<const BinaryColumn*>(column);
-        DataSketchesHll hll(hll_column->get(row_num).get_slice());
-        if (UNLIKELY(this->data(state).hll_sketch == nullptr)) {
-            this->data(state).hll_sketch =
-                    std::make_unique<DataSketchesHll>(hll.get_lg_config_k(), hll.get_target_type());
-        }
-        int64_t prev_memory = this->data(state).hll_sketch->mem_usage();
-        this->data(state).hll_sketch->merge(hll);
-        ctx->add_mem_usage(this->data(state).hll_sketch->mem_usage() - prev_memory);
-    }
-
-    void get_values(FunctionContext* ctx, ConstAggDataPtr __restrict state, Column* dst, size_t start,
-                    size_t end) const override {
-        DCHECK_GT(end, start);
-        Int64Column* column = down_cast<Int64Column*>(dst);
-        int64_t result = 0L;
-        if (LIKELY(this->data(state).hll_sketch != nullptr)) {
-            result = this->data(state).hll_sketch->estimate_cardinality();
-        }
-        for (size_t i = start; i < end; ++i) {
-            column->get_data()[i] = result;
-        }
-    }
-
-    void serialize_to_column([[maybe_unused]] FunctionContext* ctx, ConstAggDataPtr __restrict state,
-                             Column* to) const override {
-        DCHECK(to->is_binary());
-        auto* column = down_cast<BinaryColumn*>(to);
-        if (UNLIKELY(this->data(state).hll_sketch == nullptr)) {
-            column->append_default();
-        } else {
-            size_t size = this->data(state).hll_sketch->serialize_size();
-            uint8_t result[size];
-            size = this->data(state).hll_sketch->serialize(result);
-            column->append(Slice(result, size));
-        }
-    }
-
-    void convert_to_serialize_format([[maybe_unused]] FunctionContext* ctx, const Columns& src, size_t chunk_size,
-                                     ColumnPtr* dst) const override {
-        const ColumnType* column = down_cast<const ColumnType*>(src[0].get());
-        auto* result = down_cast<BinaryColumn*>((*dst).get());
-
-        Bytes& bytes = result->get_bytes();
-        bytes.reserve(chunk_size * 10);
-        result->get_offset().resize(chunk_size + 1);
-
-        size_t old_size = bytes.size();
-        uint64_t value = 0;
-        uint8_t log_k;
-        datasketches::target_hll_type tgt_type;
-        // convert to const Column*
-        std::vector<const Column*> src_datas;
-        src_datas.reserve(src.size());
-        std::transform(src.begin(), src.end(), std::back_inserter(src_datas),
-                       [](const ColumnPtr& col) { return col.get(); });
-        const Column** src_datas_ptr = src_datas.data();
-        std::tie(log_k, tgt_type) = _parse_hll_sketch_args(ctx, src_datas_ptr);
-        for (size_t i = 0; i < chunk_size; ++i) {
-            DataSketchesHll hll{log_k, tgt_type};
-            if constexpr (lt_is_string<LT>) {
-                Slice s = column->get_slice(i);
-                value = HashUtil::murmur_hash64A(s.data, s.size, HashUtil::MURMUR_SEED);
-            } else {
-                auto v = column->get_data()[i];
-                value = HashUtil::murmur_hash64A(&v, sizeof(v), HashUtil::MURMUR_SEED);
-            }
-            if (value != 0) {
-                hll.update(value);
-            }
-
-            size_t new_size = old_size + hll.serialize_size();
-            bytes.resize(new_size);
-            hll.serialize(bytes.data() + old_size);
-
-            result->get_offset()[i + 1] = new_size;
-            old_size = new_size;
-        }
-    }
-
-    void finalize_to_column(FunctionContext* ctx __attribute__((unused)), ConstAggDataPtr __restrict state,
-                            Column* to) const override {
-        DCHECK(to->is_numeric());
-
-        auto* column = down_cast<Int64Column*>(to);
-        if (UNLIKELY(this->data(state).hll_sketch == nullptr)) {
-            column->append(0L);
-        } else {
-            column->append(this->data(state).hll_sketch->estimate_cardinality());
-        }
-    }
-
-    std::string get_name() const override { return "ds_hll_count_distinct"; }
-
-private:
-    // init hll sketch if needed
-    void _init_if_needed(FunctionContext* ctx, const Column** columns, AggDataPtr __restrict state) const {
-        if (UNLIKELY(this->data(state).hll_sketch == nullptr)) {
-            uint8_t log_k;
-            datasketches::target_hll_type tgt_type;
-            std::tie(log_k, tgt_type) = _parse_hll_sketch_args(ctx, columns);
-            this->data(state).hll_sketch = _init_hll_sketch(log_k, tgt_type);
-        }
-    }
-
-    // parse log_k and target type from args
-    std::tuple<uint8_t, datasketches::target_hll_type> _parse_hll_sketch_args(FunctionContext* ctx,
-                                                                              const Column** columns) const {
-        uint8_t log_k = DEFAULT_HLL_LOG_K;
-        datasketches::target_hll_type tgt_type = datasketches::HLL_6;
-        if (ctx->get_num_args() == 2) {
-            log_k = (uint8_t)(columns[1]->get(0).get_int32());
-        } else if (ctx->get_num_args() == 3) {
-            log_k = (uint8_t)(columns[1]->get(0).get_int32());
-            std::string tgt_type_str = columns[2]->get(0).get_slice().to_string();
-            std::transform(tgt_type_str.begin(), tgt_type_str.end(), tgt_type_str.begin(), ::toupper);
-            if (tgt_type_str == "HLL_4") {
-                tgt_type = datasketches::HLL_4;
-            } else if (tgt_type_str == "HLL_8") {
-                tgt_type = datasketches::HLL_8;
-            } else {
-                tgt_type = datasketches::HLL_6;
-            }
-        }
-        return {log_k, tgt_type};
-    }
-
-    // init hll sketch with default log_k and target type
-    std::unique_ptr<DataSketchesHll> _init_hll_sketch(
-            uint8_t log_k = DEFAULT_HLL_LOG_K, datasketches::target_hll_type tgt_type = datasketches::HLL_6) const {
-        return std::make_unique<DataSketchesHll>(log_k, tgt_type);
-    }
-};
-
-} // namespace starrocks
diff --git a/be/src/exprs/agg/hypothesis_testing_common.h b/be/src/exprs/agg/hypothesis_testing_common.h
new file mode 100644
index 00000000000000..f371e57bd4f679
--- /dev/null
+++ b/be/src/exprs/agg/hypothesis_testing_common.h
@@ -0,0 +1,63 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include <cstdint>
+#include <string_view>
+
+namespace starrocks {
+
+class TestingAlternative {
+public:
+    enum Alternative : uint8_t {
+        // The initial value of TestingAlternative is Unknown,
+        // which should be considered as an error
+        // if we encounter a TestingAlternative with a value of Unknown.
+        Unknown = 0,
+        TwoSided,
+        Less,
+        Greater,
+    };
+
+    TestingAlternative(Alternative alternative = Unknown) : _alternative(alternative) {}
+    TestingAlternative(uint8_t alternative) : _alternative(static_cast<Alternative>(alternative)) {}
+
+    static TestingAlternative from_str(std::string_view alternative_str) {
+        TestingAlternative alternative;
+        if (alternative_str == "two-sided") {
+            alternative._alternative = TwoSided;
+        } else if (alternative_str == "less") {
+            alternative._alternative = Less;
+        } else if (alternative_str == "greater") {
+            alternative._alternative = Greater;
+        } else {
+            alternative._alternative = Unknown;
+        }
+        return alternative;
+    }
+
+    friend bool operator==(TestingAlternative const& lhs, TestingAlternative const& rhs) {
+        return lhs._alternative == rhs._alternative;
+    }
+
+    friend bool operator==(TestingAlternative const& lhs, Alternative const& rhs) { return lhs._alternative == rhs; }
+
+    uint8_t value() const { return _alternative; }
+
+private:
+    Alternative _alternative{Unknown};
+};
+
+} // namespace starrocks
diff --git a/be/src/exprs/agg/mann_whitney.h b/be/src/exprs/agg/mann_whitney.h
new file mode 100644
index 00000000000000..11b58663cb3163
--- /dev/null
+++ b/be/src/exprs/agg/mann_whitney.h
@@ -0,0 +1,355 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include <velocypack/Builder.h>
+#include <velocypack/Value.h>
+
+#include <algorithm>
+#include <boost/algorithm/string/case_conv.hpp>
+#include <cctype>
+#include <cmath>
+#include <iterator>
+
+#include "boost/math/distributions/normal.hpp"
+#include "column/type_traits.h"
+#include "column/vectorized_fwd.h"
+#include "exprs/agg/aggregate.h"
+#include "exprs/agg/helpers/serialize_helpers.hpp"
+#include "exprs/agg/hypothesis_testing_common.h"
+#include "exprs/function_context.h"
+#include "exprs/function_helper.h"
+#include "gutil/casts.h"
+#include "types/logical_type.h"
+#include "util/json.h"
+
+namespace starrocks {
+
+class MannWhitneyAggregateState {
+public:
+    MannWhitneyAggregateState() = default;
+    MannWhitneyAggregateState(const uint8_t*& data) { deserialize(data); }
+
+    void init(TestingAlternative alternative, int64_t continuity_correction) {
+        _alternative = alternative;
+        _continuity_correction = continuity_correction;
+    }
+
+    bool is_uninitialized() const { return _alternative == TestingAlternative::Unknown; }
+
+    void update(double x, bool treatment) {
+        _stats[treatment].emplace_back(x);
+        _sorted = false;
+    }
+
+    void merge(MannWhitneyAggregateState const& other) {
+        DCHECK(_alternative == other._alternative);
+        sort_if_not_sorted();
+        other.sort_if_not_sorted();
+        for (size_t idx = 0; idx < 2; ++idx) {
+            std::vector<double> tmp;
+            std::merge(_stats[idx].begin(), _stats[idx].end(), other._stats[idx].begin(), other._stats[idx].end(),
+                       std::back_inserter(tmp));
+            _stats[idx] = tmp;
+        }
+    }
+
+    void serialize(uint8_t*& data) const {
+        DCHECK(!is_uninitialized());
+        sort_if_not_sorted();
+        SerializeHelpers::serialize_all(data, _alternative.value(), _stats, _continuity_correction);
+    }
+
+    void deserialize(const uint8_t*& data) {
+        uint8_t tmp;
+        SerializeHelpers::deserialize_all(data, tmp, _stats, _continuity_correction);
+        _alternative = TestingAlternative(tmp);
+        _sorted = true;
+    }
+
+    size_t serialized_size() const {
+        return SerializeHelpers::serialized_size_all(_alternative.value(), _stats, _continuity_correction);
+    }
+
+    void build_result(vpack::Builder& builder) const {
+        if (_alternative == TestingAlternative::Unknown) {
+            vpack::ObjectBuilder obj_builder(&builder);
+            builder.add("Logical Error", vpack::Value("state not initialized."));
+            return;
+        }
+        // If there's only one state, it's not sorted yet, so sorted it.
+        sort_if_not_sorted();
+        size_t size = _stats[0].size() + _stats[1].size();
+        std::vector<size_t> index(size);
+        std::iota(index.begin(), index.end(), 0);
+        auto data = [this](size_t idx) {
+            if (idx < this->_stats[0].size()) {
+                return this->_stats[0][idx];
+            }
+            return this->_stats[1][idx - this->_stats[0].size()];
+        };
+        std::inplace_merge(index.begin(), index.begin() + _stats[0].size(), index.end(),
+                           [data](size_t lhs, size_t rhs) { return data(lhs) < data(rhs); });
+        DCHECK(std::is_sorted(index.begin(), index.end(),
+                              [data](size_t lhs, size_t rhs) { return data(lhs) < data(rhs); }));
+
+        const double n1 = _stats[0].size();
+        const double n2 = _stats[1].size();
+        double r1 = 0;
+        double tie_correction = 0;
+        size_t left = 0;
+        double tie_numenator = 0;
+        while (left < size) {
+            size_t right = left;
+            while (right < size && data(index[left]) == data(index[right])) {
+                ++right;
+            }
+            auto adjusted = (left + right + 1.) / 2.;
+            auto count_equal = right - left;
+
+            // Scipy implementation throws exception in this case too.
+            if (count_equal == size) {
+                vpack::ObjectBuilder obj_builder(&builder);
+                builder.add("Error", vpack::Value("All numbers in both samples are identical."));
+                return;
+            }
+
+            tie_numenator += std::pow(count_equal, 3) - count_equal;
+            for (size_t iter = left; iter < right; ++iter) {
+                if (index[iter] < n1) {
+                    r1 += adjusted;
+                }
+            }
+            left = right;
+        }
+        tie_correction = 1 - (tie_numenator / (std::pow(size, 3) - size));
+
+        const double u1 = n1 * n2 + (n1 * (n1 + 1.)) / 2. - r1;
+        const double u2 = n1 * n2 - u1;
+
+        /// The distribution of U-statistic under null hypothesis H0  is symmetric with respect to meanrank.
+        const double meanrank = n1 * n2 / 2. + 0.5 * _continuity_correction;
+        const double sd = std::sqrt(tie_correction * n1 * n2 * (n1 + n2 + 1) / 12.0);
+
+        if (std::isnan(sd) || std::isinf(sd) || std::abs(sd) < 1e-7) {
+            vpack::ObjectBuilder obj_builder(&builder);
+            builder.add("Logical Error", vpack::Value(fmt::format("sd({}) is not a valid value.", sd)));
+            return;
+        }
+
+        double u = 0;
+        if (_alternative == TestingAlternative::TwoSided) {
+            u = std::max(u1, u2);
+        } else if (_alternative == TestingAlternative::Less) {
+            u = u1;
+        } else if (_alternative == TestingAlternative::Greater) {
+            u = u2;
+        } else {
+            DCHECK(false);
+        }
+
+        double z = (u - meanrank) / sd;
+        if (_alternative == TestingAlternative::TwoSided) {
+            z = std::abs(z);
+        }
+
+        auto standart_normal_distribution = boost::math::normal_distribution<double>();
+        auto cdf = boost::math::cdf(standart_normal_distribution, z);
+
+        double p_value = 0;
+        if (_alternative == TestingAlternative::TwoSided) {
+            p_value = 2 - 2 * cdf;
+        } else {
+            p_value = 1 - cdf;
+        }
+
+        vpack::ArrayBuilder array_builder(&builder);
+        builder.add(vpack::Value(u2));
+        builder.add(vpack::Value(p_value));
+    }
+
+private:
+    TestingAlternative _alternative;
+    mutable std::array<std::vector<double>, 2> _stats;
+    int64_t _continuity_correction{0};
+    mutable bool _sorted{true};
+
+    void sort_if_not_sorted() const {
+        if (!_sorted) {
+            for (size_t idx = 0; idx < 2; ++idx) {
+                std::sort(_stats[idx].begin(), _stats[idx].end());
+            }
+            _sorted = true;
+        }
+        for (size_t idx = 0; idx < 2; ++idx) {
+            DCHECK(std::is_sorted(_stats[idx].begin(), _stats[idx].end()));
+        }
+    }
+};
+
+class MannWhitneyUTestAggregateFunction
+        : public AggregateFunctionBatchHelper<MannWhitneyAggregateState, MannWhitneyUTestAggregateFunction> {
+public:
+    using DataColumn = RunTimeColumnType<TYPE_DOUBLE>;
+    using DataCppType = RunTimeCppType<TYPE_DOUBLE>;
+    using IndexColumn = RunTimeColumnType<TYPE_BOOLEAN>;
+    using AlternativeColumn = RunTimeColumnType<TYPE_VARCHAR>;
+    using ContinuityCorrectionColumn = RunTimeColumnType<TYPE_BIGINT>;
+    using ResultColumn = RunTimeColumnType<TYPE_JSON>;
+
+    void init_state_if_needed(FunctionContext* ctx, const Column* alternative_col,
+                              const Column* continuity_correction_col, MannWhitneyAggregateState& state) const {
+        if (!state.is_uninitialized()) {
+            return;
+        }
+        init_state(ctx, alternative_col, continuity_correction_col, state);
+    }
+
+    void init_state(FunctionContext* ctx, const Column* alternative_col, const Column* continuity_correction_col,
+                    MannWhitneyAggregateState& state) const {
+        TestingAlternative alternative{TestingAlternative::TwoSided};
+        int64_t continuity_correction = 1;
+
+        if (alternative_col != nullptr) {
+            Slice alternative_slice;
+            FunctionHelper::get_data_of_column<AlternativeColumn>(alternative_col, 0, alternative_slice);
+            auto alternative_str = boost::to_lower_copy(alternative_slice.to_string());
+            TestingAlternative init_alternative = TestingAlternative::from_str(alternative_str);
+            if (init_alternative == TestingAlternative::Unknown) {
+                ctx->set_error(fmt::format("Logical Error: invalid alternative `{}`.", alternative_str).c_str());
+                return;
+            }
+            alternative = init_alternative;
+        }
+
+        if (continuity_correction_col != nullptr) {
+            FunctionHelper::get_data_of_column<ContinuityCorrectionColumn>(continuity_correction_col, 0,
+                                                                           continuity_correction);
+            if (continuity_correction < 0) {
+                ctx->set_error("Logical Error: continuity_correction must be non-negative.");
+                return;
+            }
+        }
+
+        state.init(alternative, continuity_correction);
+    }
+
+    void update(FunctionContext* ctx, const Column** columns, AggDataPtr __restrict state,
+                size_t row_num) const override {
+        const Column* alternative_col = ctx->get_num_args() >= 3 ? columns[2] : nullptr;
+        const Column* continuity_correction_col = ctx->get_num_args() >= 4 ? columns[3] : nullptr;
+        init_state_if_needed(ctx, alternative_col, continuity_correction_col, this->data(state));
+
+        DataCppType x{};
+        const Column* x_col = columns[0];
+        FunctionHelper::get_data_of_column<DataColumn>(x_col, row_num, x);
+
+        if (std::isnan((double)x) || std::isinf((double)x)) {
+            return;
+        }
+
+        bool treatment = false;
+        const Column* treatment_col = columns[1];
+        FunctionHelper::get_data_of_column<IndexColumn>(treatment_col, row_num, treatment);
+
+        this->data(state).update(x, treatment);
+    }
+
+    void merge(FunctionContext* ctx, const Column* column, AggDataPtr __restrict state, size_t row_num) const override {
+        DCHECK(column->is_binary());
+        const uint8_t* serialized_data = reinterpret_cast<const uint8_t*>(column->get(row_num).get_slice().data);
+        if (this->data(state).is_uninitialized()) {
+            this->data(state).deserialize(serialized_data);
+            return;
+        }
+        MannWhitneyAggregateState other(serialized_data);
+        this->data(state).merge(other);
+    }
+
+    void serialize_to_column(FunctionContext* ctx, ConstAggDataPtr __restrict state, Column* to) const override {
+        DCHECK(to->is_binary());
+        auto* column = down_cast<BinaryColumn*>(to);
+        Bytes& bytes = column->get_bytes();
+        size_t old_size = bytes.size();
+        size_t new_size = old_size + this->data(state).serialized_size();
+        bytes.resize(new_size);
+        column->get_offset().emplace_back(new_size);
+        uint8_t* serialized_data = bytes.data() + old_size;
+        this->data(state).serialize(serialized_data);
+    }
+
+    void finalize_to_column(FunctionContext* ctx, ConstAggDataPtr __restrict state, Column* to) const override {
+        if (this->data(state).is_uninitialized()) {
+            ctx->set_error("Internal Error: state not initialized.");
+            return;
+        }
+        vpack::Builder result_builder;
+        this->data(state).build_result(result_builder);
+        JsonValue result_json(result_builder.slice());
+        down_cast<ResultColumn*>(to)->append(std::move(result_json));
+    }
+
+    void convert_to_serialize_format(FunctionContext* ctx, const Columns& src, size_t chunk_size,
+                                     ColumnPtr* dst) const override {
+        TestingAlternative alternative{TestingAlternative::TwoSided};
+        int64_t continuity_correction = 1;
+
+        const Column* alternative_col = ctx->get_num_args() >= 3 ? src[2].get() : nullptr;
+        const Column* continuity_correction_col = ctx->get_num_args() >= 4 ? src[3].get() : nullptr;
+        if (alternative_col != nullptr) {
+            Slice alternative_slice;
+            FunctionHelper::get_data_of_column<AlternativeColumn>(alternative_col, 0, alternative_slice);
+            auto alternative_str = boost::to_lower_copy(alternative_slice.to_string());
+            TestingAlternative init_alternative = TestingAlternative::from_str(alternative_str);
+            if (init_alternative == TestingAlternative::Unknown) {
+                ctx->set_error(fmt::format("Logical Error: invalid alternative `{}`.", alternative_str).c_str());
+                return;
+            }
+            alternative = init_alternative;
+        }
+
+        if (continuity_correction_col != nullptr) {
+            FunctionHelper::get_data_of_column<ContinuityCorrectionColumn>(continuity_correction_col, 0,
+                                                                           continuity_correction);
+            if (continuity_correction < 0) {
+                ctx->set_error("Logical Error: continuity_correction must be non-negative.");
+                return;
+            }
+        }
+
+        for (size_t idx = 0; idx < chunk_size; ++idx) {
+            MannWhitneyAggregateState state;
+            state.init(alternative, continuity_correction);
+
+            DataCppType x{};
+            const Column* x_col = src[0].get();
+            FunctionHelper::get_data_of_column<DataColumn>(x_col, idx, x);
+
+            bool treatment = false;
+            const Column* treatment_col = src[1].get();
+            FunctionHelper::get_data_of_column<IndexColumn>(treatment_col, idx, treatment);
+
+            if (!(std::isnan((double)x) || std::isinf((double)x))) {
+                state.update(x, treatment);
+            }
+
+            serialize_to_column(ctx, reinterpret_cast<AggDataPtr>(&state), dst->get());
+        }
+    }
+
+    std::string get_name() const override { return "mann_whitney_u_test"; }
+};
+
+} // namespace starrocks
diff --git a/be/src/exprs/array_element_expr.cpp b/be/src/exprs/array_element_expr.cpp
index cb042c1a5b0b2b..ca73edf4394ad3 100644
--- a/be/src/exprs/array_element_expr.cpp
+++ b/be/src/exprs/array_element_expr.cpp
@@ -35,7 +35,8 @@ class ArrayElementExpr final : public Expr {
 
     StatusOr<ColumnPtr> evaluate_checked(ExprContext* context, Chunk* chunk) override {
         DCHECK_EQ(2, _children.size());
-        DCHECK_EQ(_type, _children[0]->type().children[0]);
+        // After DLA's complex type prune, ArrayElement expr's type is different from children's type
+        // DCHECK_EQ(_type, _children[0]->type().children[0]);
         ASSIGN_OR_RETURN(ColumnPtr arg0, _children[0]->evaluate_checked(context, chunk));
         ASSIGN_OR_RETURN(ColumnPtr arg1, _children[1]->evaluate_checked(context, chunk));
         size_t num_rows = std::max(arg0->size(), arg1->size());
diff --git a/be/src/exprs/array_functions.tpp b/be/src/exprs/array_functions.tpp
index a39e735c2590b3..5eee8a0b99d7bd 100644
--- a/be/src/exprs/array_functions.tpp
+++ b/be/src/exprs/array_functions.tpp
@@ -1171,7 +1171,7 @@ public:
         if constexpr (HasNull) {
             elements_nulls = elements_null_col->get_data().data();
         }
-        const auto& elements_data = GetContainer<ElementType>().get_data(elements);
+        const auto& elements_data = GetContainer<ElementType>::get_data(elements);
 
         auto* offsets_ptr = offsets->get_data().data();
         auto* null_ptr = null_cols->get_data().data();
diff --git a/be/src/exprs/bitmap_functions.cpp b/be/src/exprs/bitmap_functions.cpp
index e4a2b97c1ffd9f..ff34607b279030 100644
--- a/be/src/exprs/bitmap_functions.cpp
+++ b/be/src/exprs/bitmap_functions.cpp
@@ -700,13 +700,8 @@ StatusOr<ColumnPtr> BitmapFunctions::bitmap_to_binary(FunctionContext* context,
     }
 
     ColumnPtr col = builder.build(ColumnHelper::is_all_const(columns));
-    std::string err_msg;
-    if (col->capacity_limit_reached(&err_msg)) {
-        return Status::InternalError(
-                strings::Substitute("Size of binary column generated by bitmap_to_binary reaches limit: $0", err_msg));
-    } else {
-        return col;
-    }
+    RETURN_IF_ERROR(col->capacity_limit_reached());
+    return col;
 }
 
 StatusOr<ColumnPtr> BitmapFunctions::bitmap_from_binary(FunctionContext* context, const Columns& columns) {
diff --git a/be/src/exprs/debug_expr.cpp b/be/src/exprs/debug_expr.cpp
index b1d0098906f800..5d4b260c96c8ec 100644
--- a/be/src/exprs/debug_expr.cpp
+++ b/be/src/exprs/debug_expr.cpp
@@ -45,12 +45,7 @@ StatusOr<ColumnPtr> DebugFunctions::chunk_check_valid(ExprContext* context, Chun
     size_t num_rows = ptr->num_rows();
     for (const auto& column : ptr->columns()) {
         // check column size capacity
-        std::string msg;
-        column->capacity_limit_reached(&msg);
-        if (!msg.empty()) {
-            DCHECK(false) << "not expected";
-            throw std::runtime_error(msg);
-        }
+        RETURN_IF_ERROR(column->capacity_limit_reached());
         // check column size matched
         if (column->size() != num_rows) {
             DCHECK(false) << "not expected";
diff --git a/be/src/exprs/function_call_expr.cpp b/be/src/exprs/function_call_expr.cpp
index 988c05d4896cc4..b27fe037bb6a61 100644
--- a/be/src/exprs/function_call_expr.cpp
+++ b/be/src/exprs/function_call_expr.cpp
@@ -192,11 +192,7 @@ StatusOr<ColumnPtr> VectorizedFunctionCallExpr::evaluate_checked(starrocks::Expr
     }
     RETURN_IF_ERROR(result);
     if (_fn_desc->check_overflow) {
-        std::string err_msg;
-        if (UNLIKELY(result.value()->capacity_limit_reached(&err_msg))) {
-            return Status::InternalError(
-                    fmt::format("Result column of function {} exceed limit: {}", _fn_desc->name, err_msg));
-        }
+        RETURN_IF_ERROR(result.value()->capacity_limit_reached());
     }
 
     // For no args function call (pi, e)
diff --git a/be/src/exprs/function_helper.h b/be/src/exprs/function_helper.h
index 6f3a15d080fc56..ac953f11cafa54 100644
--- a/be/src/exprs/function_helper.h
+++ b/be/src/exprs/function_helper.h
@@ -17,6 +17,7 @@
 #include "column/column_helper.h"
 #include "column/const_column.h"
 #include "column/type_traits.h"
+#include "gutil/casts.h"
 
 namespace starrocks {
 class FunctionContext;
@@ -37,6 +38,21 @@ class FunctionHelper {
         return ptr;
     }
 
+    /**
+     * get data of column.
+     * @param col, row_num, data 
+     */
+    template <typename ToColumnType, typename CppType>
+    static void get_data_of_column(const Column* col, size_t row_num, CppType& data) {
+        if (col->is_constant()) {
+            auto const_col = down_cast<const ConstColumn*>(col);
+            col = const_col->data_column().get();
+            row_num = 0;
+        }
+        const auto* column = down_cast<const ToColumnType*>(col);
+        data = column->get_data()[row_num];
+    }
+
     /**
      * if ptr is ConstColumn, return data column
      * else return ptr
diff --git a/be/src/exprs/in_const_predicate.cpp b/be/src/exprs/in_const_predicate.cpp
index 71d7a896553feb..1021f2ed16ae54 100644
--- a/be/src/exprs/in_const_predicate.cpp
+++ b/be/src/exprs/in_const_predicate.cpp
@@ -85,7 +85,7 @@ void VectorizedInConstPredicateBuilder::add_values(const ColumnPtr& column, size
     case LogicalType::FIELD_TYPE: {                                            \
         using ColumnType = typename RunTimeTypeTraits<FIELD_TYPE>::ColumnType; \
         auto* in_pred = (VectorizedInConstPredicate<FIELD_TYPE>*)(expr);       \
-        const auto& data_ptr = GetContainer<FIELD_TYPE>().get_data(column);    \
+        const auto& data_ptr = GetContainer<FIELD_TYPE>::get_data(column);     \
         if (in_pred->is_use_array()) {                                         \
             for (size_t j = column_offset; j < data_ptr.size(); j++) {         \
                 in_pred->insert_array(data_ptr[j]);                            \
@@ -103,34 +103,34 @@ void VectorizedInConstPredicateBuilder::add_values(const ColumnPtr& column, size
         }
     } else {
         switch (type) {
-#define M(FIELD_TYPE)                                                                                 \
-    case LogicalType::FIELD_TYPE: {                                                                   \
-        using ColumnType = typename RunTimeTypeTraits<FIELD_TYPE>::ColumnType;                        \
-        auto* in_pred = (VectorizedInConstPredicate<FIELD_TYPE>*)(expr);                              \
-        auto* nullable_column = ColumnHelper::as_raw_column<NullableColumn>(column);                  \
-        const auto& data_array = GetContainer<FIELD_TYPE>().get_data(nullable_column->data_column()); \
-        if (in_pred->is_use_array()) {                                                                \
-            for (size_t j = column_offset; j < data_array.size(); j++) {                              \
-                if (!nullable_column->is_null(j)) {                                                   \
-                    in_pred->insert_array(data_array[j]);                                             \
-                } else {                                                                              \
-                    if (_eq_null) {                                                                   \
-                        in_pred->insert_null();                                                       \
-                    }                                                                                 \
-                }                                                                                     \
-            }                                                                                         \
-        } else {                                                                                      \
-            for (size_t j = column_offset; j < data_array.size(); j++) {                              \
-                if (!nullable_column->is_null(j)) {                                                   \
-                    in_pred->insert(data_array[j]);                                                   \
-                } else {                                                                              \
-                    if (_eq_null) {                                                                   \
-                        in_pred->insert_null();                                                       \
-                    }                                                                                 \
-                }                                                                                     \
-            }                                                                                         \
-        }                                                                                             \
-        break;                                                                                        \
+#define M(FIELD_TYPE)                                                                                \
+    case LogicalType::FIELD_TYPE: {                                                                  \
+        using ColumnType = typename RunTimeTypeTraits<FIELD_TYPE>::ColumnType;                       \
+        auto* in_pred = (VectorizedInConstPredicate<FIELD_TYPE>*)(expr);                             \
+        auto* nullable_column = ColumnHelper::as_raw_column<NullableColumn>(column);                 \
+        const auto& data_array = GetContainer<FIELD_TYPE>::get_data(nullable_column->data_column()); \
+        if (in_pred->is_use_array()) {                                                               \
+            for (size_t j = column_offset; j < data_array.size(); j++) {                             \
+                if (!nullable_column->is_null(j)) {                                                  \
+                    in_pred->insert_array(data_array[j]);                                            \
+                } else {                                                                             \
+                    if (_eq_null) {                                                                  \
+                        in_pred->insert_null();                                                      \
+                    }                                                                                \
+                }                                                                                    \
+            }                                                                                        \
+        } else {                                                                                     \
+            for (size_t j = column_offset; j < data_array.size(); j++) {                             \
+                if (!nullable_column->is_null(j)) {                                                  \
+                    in_pred->insert(data_array[j]);                                                  \
+                } else {                                                                             \
+                    if (_eq_null) {                                                                  \
+                        in_pred->insert_null();                                                      \
+                    }                                                                                \
+                }                                                                                    \
+            }                                                                                        \
+        }                                                                                            \
+        break;                                                                                       \
     }
             APPLY_FOR_ALL_SCALAR_TYPE(M)
 #undef M
diff --git a/be/src/exprs/json_functions.cpp b/be/src/exprs/json_functions.cpp
index 9e47bc48d6a6e6..e4158bc4457035 100644
--- a/be/src/exprs/json_functions.cpp
+++ b/be/src/exprs/json_functions.cpp
@@ -536,8 +536,6 @@ static StatusOr<ColumnPtr> _extract_with_hyper(NativeJsonState* state, const std
                 state->real_path.paths.emplace_back(p);
             }
 
-            state->init_flat = true;
-            state->flat_path = flat_path.substr(1);
             if (in_flat) {
                 state->is_partial_match = false;
                 state->flat_column_type = TargetType;
@@ -545,6 +543,8 @@ static StatusOr<ColumnPtr> _extract_with_hyper(NativeJsonState* state, const std
                 state->is_partial_match = true;
                 state->flat_column_type = TYPE_JSON;
             }
+            state->flat_path = flat_path.substr(1);
+            state->init_flat = true;
         });
     }
     std::vector<std::string> dst_path{state->flat_path};
diff --git a/be/src/exprs/like_predicate.cpp b/be/src/exprs/like_predicate.cpp
index 84aecb671e7c37..813d3bfbf96460 100644
--- a/be/src/exprs/like_predicate.cpp
+++ b/be/src/exprs/like_predicate.cpp
@@ -447,6 +447,48 @@ StatusOr<ColumnPtr> LikePredicate::_predicate_const_regex(FunctionContext* conte
     return result->build(value_column->is_constant());
 }
 
+enum class FastPathType {
+    EQUALS = 0,
+    START_WITH = 1,
+    END_WITH = 2,
+    SUBSTRING = 3,
+    REGEX = 4,
+};
+
+FastPathType extract_fast_path(const Slice& pattern) {
+    if (pattern.empty() || pattern.size < 2) {
+        return FastPathType::REGEX;
+    }
+
+    if (pattern.data[0] == '_' || pattern.data[pattern.size - 1] == '_') {
+        return FastPathType::REGEX;
+    }
+
+    bool is_end_with = pattern.data[0] == '%';
+    bool is_start_with = pattern.data[pattern.size - 1] == '%';
+
+    for (size_t i = 1; i < pattern.size - 1;) {
+        if (pattern.data[i] == '\\') {
+            i += 2;
+        } else {
+            if (pattern.data[i] == '%' || pattern.data[i] == '_') {
+                return FastPathType::REGEX;
+            }
+            i++;
+        }
+    }
+
+    if (is_end_with && is_start_with) {
+        return FastPathType::SUBSTRING;
+    } else if (is_end_with) {
+        return FastPathType::END_WITH;
+    } else if (is_start_with) {
+        return FastPathType::START_WITH;
+    } else {
+        return FastPathType::EQUALS;
+    }
+}
+
 StatusOr<ColumnPtr> LikePredicate::regex_match_full(FunctionContext* context, const starrocks::Columns& columns) {
     const auto& value_column = VECTORIZED_FN_ARGS(0);
     const auto& pattern_column = VECTORIZED_FN_ARGS(1);
@@ -478,18 +520,56 @@ StatusOr<ColumnPtr> LikePredicate::regex_match_full(FunctionContext* context, co
             continue;
         }
 
-        auto re_pattern = LikePredicate::template convert_like_pattern<false>(context, pattern_viewer.value(row));
-
-        re2::RE2 re(re_pattern, opts);
-
-        if (!re.ok()) {
-            context->set_error(strings::Substitute("Invalid regex: $0", re_pattern).c_str());
-            result.append_null();
-            continue;
+        Slice pattern = pattern_viewer.value(row);
+        FastPathType val = extract_fast_path(pattern);
+        switch (val) {
+        case FastPathType::EQUALS: {
+            std::string str_pattern = pattern.to_string();
+            remove_escape_character(&str_pattern);
+            result.append(value_viewer.value(row) == str_pattern);
+            break;
         }
+        case FastPathType::START_WITH: {
+            std::string str_pattern = pattern.to_string();
+            remove_escape_character(&str_pattern);
+            auto pattern_slice = Slice(str_pattern);
+            pattern_slice.remove_suffix(1);
+            result.append(ConstantStartsImpl::apply<Slice, Slice, bool>(value_viewer.value(row), pattern_slice));
+            break;
+        }
+        case FastPathType::END_WITH: {
+            std::string str_pattern = pattern.to_string();
+            remove_escape_character(&str_pattern);
+            auto pattern_slice = Slice(str_pattern);
+            pattern_slice.remove_prefix(1);
+            result.append(ConstantEndsImpl::apply<Slice, Slice, bool>(value_viewer.value(row), pattern_slice));
+            break;
+        }
+        case FastPathType::SUBSTRING: {
+            std::string str_pattern = pattern.to_string();
+            remove_escape_character(&str_pattern);
+            auto pattern_slice = Slice(str_pattern);
+            pattern_slice.remove_prefix(1);
+            pattern_slice.remove_suffix(1);
+            auto searcher = LibcASCIICaseSensitiveStringSearcher(pattern_slice.get_data(), pattern_slice.get_size());
+            /// searcher returns a pointer to the found substring or to the end of `haystack`.
+            const Slice& value = value_viewer.value(row);
+            const char* res_pointer = searcher.search(value.data, value.size);
+            result.append(!!res_pointer);
+            break;
+        }
+        case FastPathType::REGEX: {
+            auto re_pattern = LikePredicate::template convert_like_pattern<false>(context, pattern);
 
-        auto v = RE2::FullMatch(re2::StringPiece(value_viewer.value(row).data, value_viewer.value(row).size), re);
-        result.append(v);
+            re2::RE2 re(re_pattern, opts);
+            if (!re.ok()) {
+                return Status::InvalidArgument(strings::Substitute("Invalid regex: $0", re_pattern));
+            }
+            auto v = RE2::FullMatch(re2::StringPiece(value_viewer.value(row).data, value_viewer.value(row).size), re);
+            result.append(v);
+            break;
+        }
+        }
     }
 
     return result.build(all_const);
diff --git a/be/src/exprs/runtime_filter.h b/be/src/exprs/runtime_filter.h
index 6a4cd90a412f30..4323413f48a34a 100644
--- a/be/src/exprs/runtime_filter.h
+++ b/be/src/exprs/runtime_filter.h
@@ -894,7 +894,7 @@ class RuntimeBloomFilter final : public JoinRuntimeFilter {
             if (const_column->only_null()) {
                 _selection[0] = _has_null;
             } else {
-                const auto& input_data = GetContainer<Type>().get_data(const_column->data_column());
+                const auto& input_data = GetContainer<Type>::get_data(const_column->data_column());
                 _evaluate_min_max(input_data, _selection, 1);
                 if constexpr (can_use_bf) {
                     _rf_test_data<multi_partition>(_selection, input_data, _hash_values, 0);
@@ -904,7 +904,7 @@ class RuntimeBloomFilter final : public JoinRuntimeFilter {
             memset(_selection, sel, size);
         } else if (input_column->is_nullable()) {
             const auto* nullable_column = down_cast<const NullableColumn*>(input_column);
-            const auto& input_data = GetContainer<Type>().get_data(nullable_column->data_column());
+            const auto& input_data = GetContainer<Type>::get_data(nullable_column->data_column());
             _evaluate_min_max(input_data, _selection, size);
             if (nullable_column->has_null()) {
                 const uint8_t* null_data = nullable_column->immutable_null_column_data().data();
@@ -925,7 +925,7 @@ class RuntimeBloomFilter final : public JoinRuntimeFilter {
                 }
             }
         } else {
-            const auto& input_data = GetContainer<Type>().get_data(input_column);
+            const auto& input_data = GetContainer<Type>::get_data(input_column);
             _evaluate_min_max(input_data, _selection, size);
             if constexpr (can_use_bf) {
                 for (int i = 0; i < size; ++i) {
diff --git a/be/src/exprs/runtime_filter_bank.cpp b/be/src/exprs/runtime_filter_bank.cpp
index 193c1ead7fbc4e..418ae366b202dd 100644
--- a/be/src/exprs/runtime_filter_bank.cpp
+++ b/be/src/exprs/runtime_filter_bank.cpp
@@ -125,7 +125,7 @@ struct FilterIniter {
 
         if (column->is_nullable()) {
             auto* nullable_column = ColumnHelper::as_raw_column<NullableColumn>(column);
-            const auto& data_array = GetContainer<ltype>().get_data(nullable_column->data_column().get());
+            const auto& data_array = GetContainer<ltype>::get_data(nullable_column->data_column().get());
             for (size_t j = column_offset; j < data_array.size(); j++) {
                 if (!nullable_column->is_null(j)) {
                     filter->insert(data_array[j]);
@@ -136,7 +136,7 @@ struct FilterIniter {
                 }
             }
         } else {
-            const auto& data_array = GetContainer<ltype>().get_data(column.get());
+            const auto& data_array = GetContainer<ltype>::get_data(column.get());
             for (size_t j = column_offset; j < data_array.size(); j++) {
                 filter->insert(data_array[j]);
             }
diff --git a/be/src/exprs/string_functions.cpp b/be/src/exprs/string_functions.cpp
index 799953d67628ce..499549edc4a638 100644
--- a/be/src/exprs/string_functions.cpp
+++ b/be/src/exprs/string_functions.cpp
@@ -56,7 +56,7 @@ namespace starrocks {
 static const RE2 SUBSTRING_RE(R"((?:\.\*)*([^\.\^\{\[\(\|\)\]\}\+\*\?\$\\]+)(?:\.\*)*)", re2::RE2::Quiet);
 
 #define THROW_RUNTIME_ERROR_IF_EXCEED_LIMIT(col, func_name)                          \
-    if (UNLIKELY(col->capacity_limit_reached())) {                                   \
+    if (UNLIKELY(!col->capacity_limit_reached().ok())) {                             \
         col->reset_column();                                                         \
         throw std::runtime_error("binary column exceed 4G in function " #func_name); \
     }
@@ -2633,7 +2633,8 @@ StatusOr<ColumnPtr> StringFunctions::ascii(FunctionContext* context, const Colum
 }
 
 DEFINE_UNARY_FN_WITH_IMPL(get_charImpl, value) {
-    return std::string((char*)&value, 1);
+    char* p = (char*)&value;
+    return std::string(p, 1);
 }
 
 StatusOr<ColumnPtr> StringFunctions::get_char(FunctionContext* context, const Columns& columns) {
diff --git a/be/src/exprs/subfield_expr.cpp b/be/src/exprs/subfield_expr.cpp
index 30f973061de818..1f314e4394543c 100644
--- a/be/src/exprs/subfield_expr.cpp
+++ b/be/src/exprs/subfield_expr.cpp
@@ -20,6 +20,7 @@
 #include "column/nullable_column.h"
 #include "column/struct_column.h"
 #include "common/object_pool.h"
+#include "exprs/function_helper.h"
 
 namespace starrocks {
 
@@ -39,9 +40,19 @@ class SubfieldExpr final : public Expr {
 
         ASSIGN_OR_RETURN(ColumnPtr col, _children.at(0)->evaluate_checked(context, chunk));
 
-        // Enter multiple subfield for struct type, remain last subfield
-        for (size_t i = 0; i < _used_subfield_names.size() - 1; i++) {
-            std::string fieldname = _used_subfield_names[i];
+        // handle nullable column
+        const size_t num_rows = col->size();
+        NullColumnPtr union_null_column = NullColumn::create(num_rows, false);
+
+        for (size_t i = 0; i < _used_subfield_names.size(); i++) {
+            const std::string& fieldname = _used_subfield_names[i];
+
+            // merge null flags for each level
+            if (col->is_nullable()) {
+                auto* nullable = down_cast<NullableColumn*>(col.get());
+                union_null_column = FunctionHelper::union_null_column(union_null_column, nullable->null_column());
+            }
+
             Column* tmp_col = ColumnHelper::get_data_column(col.get());
             DCHECK(tmp_col->is_struct());
             auto* struct_column = down_cast<StructColumn*>(tmp_col);
@@ -51,40 +62,19 @@ class SubfieldExpr final : public Expr {
             }
         }
 
-        // handle nullable column
-        std::vector<uint8_t> null_flags;
-        size_t num_rows = col->size();
-        null_flags.resize(num_rows, false);
         if (col->is_nullable()) {
             auto* nullable = down_cast<NullableColumn*>(col.get());
-            const uint8_t* nulls = nullable->null_column()->raw_data();
-            std::memcpy(&null_flags[0], &nulls[0], num_rows * sizeof(uint8_t));
-        }
-
-        Column* tmp_col = ColumnHelper::get_data_column(col.get());
-        DCHECK(tmp_col->is_struct());
-        auto* struct_column = down_cast<StructColumn*>(tmp_col);
-
-        std::string fieldname = _used_subfield_names.back();
-        ColumnPtr subfield_column = struct_column->field_column(fieldname);
-        if (subfield_column->is_nullable()) {
-            auto* nullable = down_cast<NullableColumn*>(subfield_column.get());
-            const uint8_t* nulls = nullable->null_column()->raw_data();
-            for (size_t i = 0; i < num_rows; i++) {
-                null_flags[i] |= nulls[i];
-            }
-            subfield_column = nullable->data_column();
+            union_null_column = FunctionHelper::union_null_column(union_null_column, nullable->null_column());
+            col = nullable->data_column();
         }
 
-        NullColumnPtr result_null = NullColumn::create();
-        result_null->get_data().swap(null_flags);
-        DCHECK_EQ(subfield_column->size(), result_null->size());
+        DCHECK_EQ(col->size(), union_null_column->size());
 
-        // We need clone a new subfield column
+        // We need to clone a new subfield column
         if (_copy_flag) {
-            return NullableColumn::create(subfield_column->clone_shared(), result_null);
+            return NullableColumn::create(col->clone_shared(), union_null_column);
         } else {
-            return NullableColumn::create(subfield_column, result_null);
+            return NullableColumn::create(col, union_null_column);
         }
     }
 
diff --git a/be/src/exprs/table_function/java_udtf_function.cpp b/be/src/exprs/table_function/java_udtf_function.cpp
index 9884ab79c1a135..33389ac60cde05 100644
--- a/be/src/exprs/table_function/java_udtf_function.cpp
+++ b/be/src/exprs/table_function/java_udtf_function.cpp
@@ -21,6 +21,7 @@
 #include "column/column_helper.h"
 #include "column/nullable_column.h"
 #include "column/vectorized_fwd.h"
+#include "common/compiler_util.h"
 #include "exprs/table_function/table_function.h"
 #include "gutil/casts.h"
 #include "jni.h"
@@ -137,21 +138,28 @@ std::pair<Columns, UInt32Column::Ptr> JavaUDTFFunction::process(RuntimeState* ru
 
     std::vector<jvalue> call_stack;
     std::vector<jobject> rets;
-    DeferOp defer = DeferOp([&]() {
-        // clean up arrays
-        for (auto& ret : rets) {
-            if (ret) {
-                env->DeleteLocalRef(ret);
-            }
-        }
-    });
     size_t num_rows = cols[0]->size();
     size_t num_cols = cols.size();
     state->set_processed_rows(num_rows);
 
     call_stack.reserve(num_cols);
     rets.resize(num_rows);
+
+    // reserve 16 local refs
+    DeferOp defer = DeferOp([&]() {
+        // clean up arrays
+        env->PopLocalFrame(nullptr);
+    });
+    env->PushLocalFrame(num_cols * num_rows + 16);
+
     for (int i = 0; i < num_rows; ++i) {
+        DeferOp defer = DeferOp([&]() {
+            for (int j = 0; j < num_cols; ++j) {
+                release_jvalue(stateUDTF->method_process()->method_desc[j + 1].is_box, call_stack[j]);
+            }
+            call_stack.clear();
+        });
+
         for (int j = 0; j < num_cols; ++j) {
             auto method_type = stateUDTF->method_process()->method_desc[j + 1];
             jvalue val = cast_to_jvalue<true>(method_type.type, method_type.is_box, cols[j].get(), i);
@@ -160,11 +168,13 @@ std::pair<Columns, UInt32Column::Ptr> JavaUDTFFunction::process(RuntimeState* ru
 
         rets[i] = env->CallObjectMethodA(stateUDTF->handle(), methodID, call_stack.data());
 
-        for (int j = 0; j < num_cols; ++j) {
-            release_jvalue(stateUDTF->method_process()->method_desc[j + 1].is_box, call_stack[j]);
+        if (auto jthr = helper.getEnv()->ExceptionOccurred(); jthr != nullptr) {
+            std::string err = fmt::format("execute UDF Function meet Exception:{}", helper.dumpExceptionString(jthr));
+            LOG(WARNING) << err;
+            helper.getEnv()->ExceptionClear();
+            state->set_status(Status::InternalError(err));
+            return std::make_pair(Columns{}, nullptr);
         }
-
-        call_stack.clear();
     }
 
     // Build Return Type
@@ -185,8 +195,12 @@ std::pair<Columns, UInt32Column::Ptr> JavaUDTFFunction::process(RuntimeState* ru
         for (int j = 0; j < len; ++j) {
             jobject vi = env->GetObjectArrayElement((jobjectArray)rets[i], j);
             LOCAL_REF_GUARD_ENV(env, vi);
+            auto st = check_type_matched(method_desc, vi);
+            if (UNLIKELY(!st.ok())) {
+                state->set_status(st);
+                return std::make_pair(Columns{}, nullptr);
+            }
             append_jvalue(method_desc, col.get(), {.l = vi});
-            release_jvalue(method_desc.is_box, {.l = vi});
         }
     }
 
diff --git a/be/src/exprs/table_function/subdivide_bitmap.h b/be/src/exprs/table_function/subdivide_bitmap.h
index b55f63422c40c7..7617f6421c0b76 100644
--- a/be/src/exprs/table_function/subdivide_bitmap.h
+++ b/be/src/exprs/table_function/subdivide_bitmap.h
@@ -105,17 +105,16 @@ class SubdivideBitmap final : public TableFunction {
                             &compact_offset);
             }
         }
-        std::string err_msg;
-        auto ret = dst_bitmap_col->capacity_limit_reached(&err_msg);
-        if (ret) {
+        Status st = dst_bitmap_col->capacity_limit_reached();
+        if (!st.ok()) {
             state->set_status(Status::InternalError(
-                    fmt::format("Bitmap column generate by subdivide_bitmap reach limit, {}", err_msg)));
+                    fmt::format("Bitmap column generate by subdivide_bitmap reach limit, {}", st.message())));
             return {};
         }
-        ret = dst_offset_col->capacity_limit_reached(&err_msg);
-        if (ret) {
+        st = dst_offset_col->capacity_limit_reached();
+        if (!st.ok()) {
             state->set_status(Status::InternalError(
-                    fmt::format("Offset column generate by subdivide_bitmap reach limit, {}", err_msg)));
+                    fmt::format("Offset column generate by subdivide_bitmap reach limit, {}", st.message())));
             return {};
         }
         dst_columns.emplace_back(std::move(dst_bitmap_col));
diff --git a/be/src/exprs/unary_function.h b/be/src/exprs/unary_function.h
index f705a9afcf5d28..c8ceaf99ebc2c8 100644
--- a/be/src/exprs/unary_function.h
+++ b/be/src/exprs/unary_function.h
@@ -101,7 +101,7 @@ class UnaryFunction {
         result->resize(size);
         auto* r3 = result->get_data().data();
 
-        const auto& data_array = GetContainer<Type>().get_data(v1);
+        const auto& data_array = GetContainer<Type>::get_data(v1);
 
         if constexpr (lt_is_string<Type> || lt_is_binary<Type>) {
             for (int i = 0; i < size; ++i) {
@@ -136,7 +136,6 @@ struct StringUnaryFunction {
         int size = v1->size();
         for (int i = 0; i < size; ++i) {
             std::string ret = OP::template apply<RunTimeCppType<Type>, std::string>(r1[i], std::forward<Args>(args)...);
-            bytes.reserve(ret.size());
             bytes.insert(bytes.end(), (uint8_t*)ret.data(), (uint8_t*)ret.data() + ret.size());
             offset.emplace_back(bytes.size());
         }
diff --git a/be/src/formats/disk_range.hpp b/be/src/formats/disk_range.hpp
index 90641ee320566b..ced8c97c8bdbc2 100644
--- a/be/src/formats/disk_range.hpp
+++ b/be/src/formats/disk_range.hpp
@@ -24,7 +24,7 @@ class DiskRange {
 public:
     DiskRange(const int64_t off, const int64_t len) : _offset(off), _length(len) {
         DCHECK(off >= 0);
-        DCHECK(len > 0);
+        DCHECK(len >= 0);
     }
 
     /**
diff --git a/be/src/formats/parquet/column_reader.cpp b/be/src/formats/parquet/column_reader.cpp
index 47435a32608729..a5f23fd6694931 100644
--- a/be/src/formats/parquet/column_reader.cpp
+++ b/be/src/formats/parquet/column_reader.cpp
@@ -109,12 +109,8 @@ Status ColumnDictFilterContext::rewrite_conjunct_ctxs_to_predicate(StoredColumnR
         predicate = obj_pool.add(
                 new_column_eq_predicate(get_type_info(kDictCodeFieldType), slot_id, std::to_string(dict_codes[0])));
     } else {
-        std::vector<std::string> str_codes;
-        str_codes.reserve(dict_codes.size());
-        for (int code : dict_codes) {
-            str_codes.emplace_back(std::to_string(code));
-        }
-        predicate = obj_pool.add(new_column_in_predicate(get_type_info(kDictCodeFieldType), slot_id, str_codes));
+        predicate = obj_pool.add(new_dictionary_code_in_predicate(get_type_info(kDictCodeFieldType), slot_id,
+                                                                  dict_codes, dict_value_column->size()));
     }
 
     // deal with if NULL works or not.
diff --git a/be/src/formats/parquet/schema.cpp b/be/src/formats/parquet/schema.cpp
index 9799389cb3faae..8311891ed23ab7 100644
--- a/be/src/formats/parquet/schema.cpp
+++ b/be/src/formats/parquet/schema.cpp
@@ -224,6 +224,13 @@ Status SchemaDescriptor::map_to_field(const std::vector<tparquet::SchemaElement>
     //   }
     // }
     //
+
+    // check map's key must be primitive type
+    ASSIGN_OR_RETURN(const auto* key_schema, _get_schema_element(t_schemas, pos + 2));
+    if (is_group(key_schema)) {
+        return Status::InvalidArgument("Map keys must be primitive type.");
+    }
+
     RETURN_IF_ERROR(node_to_field(t_schemas, pos + 2, cur_level_info, key_field, next_pos));
     RETURN_IF_ERROR(node_to_field(t_schemas, pos + 3, cur_level_info, value_field, next_pos));
 
diff --git a/be/src/runtime/CMakeLists.txt b/be/src/runtime/CMakeLists.txt
index 03e77e436a313f..c8cea88e2d6405 100644
--- a/be/src/runtime/CMakeLists.txt
+++ b/be/src/runtime/CMakeLists.txt
@@ -43,6 +43,7 @@ set(RUNTIME_FILES
     load_path_mgr.cpp
     dummy_load_path_mgr.cpp
     types.cpp
+    agg_state_desc.cpp
     mem_tracker.cpp
     data_stream_recvr.cpp
     export_sink.cpp
diff --git a/be/src/runtime/agg_state_desc.cpp b/be/src/runtime/agg_state_desc.cpp
new file mode 100644
index 00000000000000..a10db044f6e7d3
--- /dev/null
+++ b/be/src/runtime/agg_state_desc.cpp
@@ -0,0 +1,124 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "runtime/agg_state_desc.h"
+
+#include <memory>
+
+#include "exprs/agg/aggregate.h"
+#include "exprs/agg/aggregate_factory.h"
+
+namespace starrocks {
+
+// Create a new AggStateDesc from a thrift TTypeDesc.
+AggStateDesc AggStateDesc::from_thrift(const TAggStateDesc& desc) {
+    VLOG(2) << "TAggStateDesc:" << apache::thrift::ThriftDebugString(desc);
+    std::string agg_func_name = desc.agg_func_name;
+    // return type
+    auto return_type = TypeDescriptor::from_thrift(desc.ret_type);
+    // arg types
+    std::vector<TypeDescriptor> arg_types;
+    for (auto& arg_type : desc.arg_types) {
+        arg_types.emplace_back(TypeDescriptor::from_thrift(arg_type));
+    }
+    bool result_nullable = desc.result_nullable;
+    int func_version = desc.func_version;
+    return AggStateDesc{agg_func_name, std::move(return_type), std::move(arg_types), result_nullable, func_version};
+}
+
+// Transform this AggStateDesc to a thrift TTypeDesc.
+void AggStateDesc::to_thrift(TAggStateDesc* t) {
+    t->agg_func_name = _func_name;
+    t->result_nullable = _is_result_nullable;
+    t->func_version = _func_version;
+    // return type
+    t->ret_type = _return_type.to_thrift();
+    // arg types
+    for (auto& arg_type : _arg_types) {
+        t->arg_types.push_back(arg_type.to_thrift());
+    }
+}
+
+AggStateDesc AggStateDesc::from_protobuf(const AggStateDescPB& desc) {
+    auto& agg_func_name = desc.agg_func_name();
+    bool is_result_nullable = desc.is_result_nullable();
+    int func_version = desc.func_version();
+    std::vector<TypeDescriptor> arg_types;
+    // arg types
+    for (auto& arg_type : desc.arg_types()) {
+        arg_types.emplace_back(TypeDescriptor::from_protobuf(arg_type));
+    }
+    // ret type
+    auto ret_type = TypeDescriptor::from_protobuf(desc.ret_type());
+    return AggStateDesc{agg_func_name, std::move(ret_type), std::move(arg_types), is_result_nullable, func_version};
+}
+
+void AggStateDesc::to_protobuf(AggStateDescPB* desc) {
+    desc->set_agg_func_name(this->get_func_name());
+    desc->set_is_result_nullable(this->is_result_nullable());
+    desc->set_func_version(this->get_func_version());
+    // arg types
+    for (auto& arg_type : this->get_arg_types()) {
+        auto* arg_type_pb = desc->add_arg_types();
+        *arg_type_pb = arg_type.to_protobuf();
+    }
+    // ret type
+    auto ret_type_desc = this->get_return_type();
+    auto* ret_type_pb = desc->mutable_ret_type();
+    *ret_type_pb = ret_type_desc.to_protobuf();
+}
+
+void AggStateDesc::thrift_to_protobuf(const TAggStateDesc& desc, AggStateDescPB* pb) {
+    pb->set_agg_func_name(desc.agg_func_name);
+    pb->set_is_result_nullable(desc.result_nullable);
+    pb->set_func_version(desc.func_version);
+    // arg types
+    for (auto& arg_type : desc.arg_types) {
+        auto arg_type_desc = TypeDescriptor::from_thrift(arg_type);
+        auto* arg_type_pb = pb->add_arg_types();
+        *arg_type_pb = arg_type_desc.to_protobuf();
+    }
+    // ret type
+    auto ret_type_desc = TypeDescriptor::from_thrift(desc.ret_type);
+    auto* ret_type_pb = pb->mutable_ret_type();
+    *ret_type_pb = ret_type_desc.to_protobuf();
+}
+
+std::string AggStateDesc::debug_string() const {
+    std::stringstream ss;
+    ss << "[" << _func_name << ", args:<";
+    for (size_t i = 0; i < _arg_types.size(); i++) {
+        if (i != _arg_types.size() - 1) {
+            ss << _arg_types[i] << ", ";
+        } else {
+            ss << _arg_types[i] << ">";
+        }
+    }
+    ss << ", ret:" << _return_type << ", result_nullable:" << _is_result_nullable << ", func_version:" << _func_version
+       << "]";
+    return ss.str();
+}
+
+const AggregateFunction* AggStateDesc::get_agg_state_func(AggStateDesc* agg_state_desc) {
+    DCHECK(agg_state_desc);
+    auto* agg_function = get_aggregate_function(agg_state_desc->get_func_name(), agg_state_desc->get_return_type(),
+                                                agg_state_desc->get_arg_types(), agg_state_desc->is_result_nullable(),
+                                                TFunctionBinaryType::BUILTIN, agg_state_desc->get_func_version());
+    if (agg_function == nullptr) {
+        LOG(WARNING) << "Failed to get aggregate function for " << agg_state_desc->debug_string();
+    }
+    return agg_function;
+}
+
+} // namespace starrocks
\ No newline at end of file
diff --git a/be/src/runtime/agg_state_desc.h b/be/src/runtime/agg_state_desc.h
new file mode 100644
index 00000000000000..592efea31728e8
--- /dev/null
+++ b/be/src/runtime/agg_state_desc.h
@@ -0,0 +1,114 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+#pragma once
+
+#include <gen_cpp/descriptors.pb.h>
+
+#include <memory>
+#include <string>
+#include <vector>
+
+#include "gen_cpp/Types_types.h"
+#include "runtime/types.h"
+
+namespace starrocks {
+
+struct TypeDescriptor;
+
+class AggStateDesc;
+using AggStateDescPtr = std::shared_ptr<AggStateDesc>;
+
+class AggregateFunction;
+
+class AggStateDesc {
+public:
+    AggStateDesc(std::string func_name, TypeDescriptor return_type, std::vector<TypeDescriptor> arg_types,
+                 bool is_result_nullable, int func_version)
+            : _func_name(std::move(func_name)),
+              _return_type(std::move(return_type)),
+              _arg_types(std::move(arg_types)),
+              _is_result_nullable(is_result_nullable),
+              _func_version(func_version) {}
+
+    // copy assignment operator
+    AggStateDesc(const AggStateDesc& other)
+            : _func_name(other._func_name),
+              _return_type(other._return_type),
+              _arg_types(other._arg_types),
+              _is_result_nullable(other._is_result_nullable),
+              _func_version(other._func_version) {}
+    AggStateDesc& operator=(const AggStateDesc& other) {
+        if (this != &other) {
+            this->_func_name = other._func_name;
+            this->_return_type = other._return_type;
+            this->_arg_types = other._arg_types;
+            this->_is_result_nullable = other._is_result_nullable;
+            this->_func_version = other._func_version;
+        }
+        return *this;
+    }
+
+    // move assignment operator
+    AggStateDesc(AggStateDesc&& other) noexcept
+            : _func_name(std::move(other._func_name)),
+              _return_type(std::move(other._return_type)),
+              _arg_types(std::move(other._arg_types)),
+              _is_result_nullable(other._is_result_nullable),
+              _func_version(other._func_version) {}
+    AggStateDesc& operator=(AggStateDesc&& other) noexcept {
+        if (this != &other) {
+            this->_func_name = std::move(other._func_name);
+            this->_return_type = std::move(other._return_type);
+            this->_arg_types = std::move(other._arg_types);
+            this->_is_result_nullable = other._is_result_nullable;
+            this->_func_version = other._func_version;
+        }
+        return *this;
+    }
+
+    const std::string& get_func_name() const { return _func_name; }
+    const TypeDescriptor& get_return_type() const { return _return_type; }
+    const std::vector<TypeDescriptor>& get_arg_types() const { return _arg_types; }
+    bool is_result_nullable() const { return _is_result_nullable; }
+    int get_func_version() const { return _func_version; }
+    std::string debug_string() const;
+
+    // Transform this AggStateDesc to a thrift TTypeDesc.
+    void to_thrift(TAggStateDesc* t);
+    // Transform this AggStateDesc to a protobuf AggStateDescPB.
+    void to_protobuf(AggStateDescPB* desc);
+
+    // Create a new AggStateDesc from a thrift TTypeDesc.
+    static AggStateDesc from_thrift(const TAggStateDesc& desc);
+    // Create a new AggStateDesc from a protobuf AggStateDescPB.
+    static AggStateDesc from_protobuf(const AggStateDescPB& desc);
+    // Convert thrift TAggStateDesc to protobuf AggStateDescPB.
+    static void thrift_to_protobuf(const TAggStateDesc& desc, AggStateDescPB* pb);
+    // Get the aggregate function state descriptor.
+    static const AggregateFunction* get_agg_state_func(AggStateDesc* agg_state_desc);
+
+private:
+    // nested aggregate function name
+    std::string _func_name;
+    // nested aggregate function return type
+    TypeDescriptor _return_type;
+    // nested aggregate function argument types
+    std::vector<TypeDescriptor> _arg_types;
+    // nested aggregate function input is nullable
+    bool _is_result_nullable;
+    // nested aggregate function version
+    int _func_version;
+};
+
+} // namespace starrocks
\ No newline at end of file
diff --git a/be/src/runtime/current_thread.h b/be/src/runtime/current_thread.h
index 9f56f4da9e8309..5c4512484f11c4 100644
--- a/be/src/runtime/current_thread.h
+++ b/be/src/runtime/current_thread.h
@@ -93,6 +93,7 @@ class CurrentThread {
                 _reserved_bytes = prev_reserved;
                 _cache_size -= size;
                 _allocated_cache_size -= size;
+                _total_consumed_bytes -= size;
                 _try_consume_mem_size = size;
             };
             if (_cache_size >= BATCH_SIZE) {
@@ -132,6 +133,7 @@ class CurrentThread {
                 } else {
                     _cache_size -= size;
                     _allocated_cache_size -= size;
+                    _total_consumed_bytes -= size;
                     _try_consume_mem_size = size;
                     tls_exceed_mem_tracker = limit_tracker;
                     return false;
@@ -162,6 +164,7 @@ class CurrentThread {
         void release(int64_t size) {
             _cache_size -= size;
             _deallocated_cache_size += size;
+            _total_consumed_bytes -= size;
             if (_cache_size <= -BATCH_SIZE) {
                 commit(false);
             }
diff --git a/be/src/runtime/runtime_state.cpp b/be/src/runtime/runtime_state.cpp
index e2802e6cf634cd..8997293930d7a4 100644
--- a/be/src/runtime/runtime_state.cpp
+++ b/be/src/runtime/runtime_state.cpp
@@ -262,7 +262,7 @@ void RuntimeState::log_error(const Status& status) {
         return;
     }
 
-    log_error(status);
+    log_error(status.message());
 }
 
 void RuntimeState::get_unreported_errors(std::vector<std::string>* new_errors) {
diff --git a/be/src/runtime/stream_load/stream_load_executor.cpp b/be/src/runtime/stream_load/stream_load_executor.cpp
index 68070aa0ad1193..132f191b180adb 100644
--- a/be/src/runtime/stream_load/stream_load_executor.cpp
+++ b/be/src/runtime/stream_load/stream_load_executor.cpp
@@ -301,7 +301,11 @@ StatusOr<TTransactionStatus::type> get_txn_status(const AuthInfo& auth, std::str
 bool wait_txn_visible_until(const AuthInfo& auth, std::string_view db, std::string_view table, int64_t txn_id,
                             int64_t deadline) {
     while (deadline > UnixSeconds()) {
-        sleep(std::min((int64_t)config::get_txn_status_internal_sec, deadline - UnixSeconds()));
+        auto wait_seconds = std::min((int64_t)config::get_txn_status_internal_sec, deadline - UnixSeconds());
+        LOG(WARNING) << "transaction is not visible now, will wait " << wait_seconds
+                     << " seconds before retrieving the status again, txn_id: " << txn_id;
+        // The following sleep might introduce delay to the commit and publish total time
+        sleep(wait_seconds);
         auto status_or = get_txn_status(auth, db, table, txn_id);
         if (!status_or.ok()) {
             return false;
diff --git a/be/src/runtime/types.cpp b/be/src/runtime/types.cpp
index deaebdedf26962..7a82dca090519c 100644
--- a/be/src/runtime/types.cpp
+++ b/be/src/runtime/types.cpp
@@ -123,9 +123,7 @@ void TypeDescriptor::to_thrift(TTypeDesc* thrift_type) const {
         curr_node.__set_scalar_type(TScalarType());
         TScalarType& scalar_type = curr_node.scalar_type;
         scalar_type.__set_type(starrocks::to_thrift(type));
-        if (len != -1) {
-            scalar_type.__set_len(len);
-        }
+        scalar_type.__set_len(len);
         if (scale != -1) {
             scalar_type.__set_scale(scale);
         }
@@ -159,9 +157,7 @@ void TypeDescriptor::to_protobuf(PTypeDesc* proto_type) const {
         node->set_type(TTypeNodeType::SCALAR);
         PScalarType* scalar_type = node->mutable_scalar_type();
         scalar_type->set_type(starrocks::to_thrift(type));
-        if (len != -1) {
-            scalar_type->set_len(len);
-        }
+        scalar_type->set_len(len);
         if (scale != -1) {
             scalar_type->set_scale(scale);
         }
diff --git a/be/src/storage/aggregate_type.cpp b/be/src/storage/aggregate_type.cpp
index 65d71bc1053a65..b98618702b89b5 100644
--- a/be/src/storage/aggregate_type.cpp
+++ b/be/src/storage/aggregate_type.cpp
@@ -21,18 +21,19 @@
 namespace starrocks {
 
 StorageAggregateType get_aggregation_type_by_string(const std::string& str) {
-    std::string upper_str = str;
-    std::transform(str.begin(), str.end(), upper_str.begin(), ::tolower);
+    std::string lower_str = str;
+    std::transform(str.begin(), str.end(), lower_str.begin(), ::tolower);
 
-    if (upper_str == "none") return STORAGE_AGGREGATE_NONE;
-    if (upper_str == "sum") return STORAGE_AGGREGATE_SUM;
-    if (upper_str == "min") return STORAGE_AGGREGATE_MIN;
-    if (upper_str == "max") return STORAGE_AGGREGATE_MAX;
-    if (upper_str == "replace") return STORAGE_AGGREGATE_REPLACE;
-    if (upper_str == "replace_if_not_null") return STORAGE_AGGREGATE_REPLACE_IF_NOT_NULL;
-    if (upper_str == "hll_union") return STORAGE_AGGREGATE_HLL_UNION;
-    if (upper_str == "bitmap_union") return STORAGE_AGGREGATE_BITMAP_UNION;
-    if (upper_str == "percentile_union") return STORAGE_AGGREGATE_PERCENTILE_UNION;
+    if (lower_str == "none") return STORAGE_AGGREGATE_NONE;
+    if (lower_str == "sum") return STORAGE_AGGREGATE_SUM;
+    if (lower_str == "min") return STORAGE_AGGREGATE_MIN;
+    if (lower_str == "max") return STORAGE_AGGREGATE_MAX;
+    if (lower_str == "replace") return STORAGE_AGGREGATE_REPLACE;
+    if (lower_str == "replace_if_not_null") return STORAGE_AGGREGATE_REPLACE_IF_NOT_NULL;
+    if (lower_str == "hll_union") return STORAGE_AGGREGATE_HLL_UNION;
+    if (lower_str == "bitmap_union") return STORAGE_AGGREGATE_BITMAP_UNION;
+    if (lower_str == "percentile_union") return STORAGE_AGGREGATE_PERCENTILE_UNION;
+    if (lower_str == "agg_state_union") return STORAGE_AGGREGATE_AGG_STATE_UNION;
     LOG(WARNING) << "invalid aggregation type string. [aggregation='" << str << "']";
     return STORAGE_AGGREGATE_UNKNOWN;
 }
@@ -59,6 +60,8 @@ std::string get_string_by_aggregation_type(StorageAggregateType type) {
         return "percentile_union";
     case STORAGE_AGGREGATE_UNKNOWN:
         return "unknown";
+    case STORAGE_AGGREGATE_AGG_STATE_UNION:
+        return "agg_state_union";
     }
     return "";
 }
diff --git a/be/src/storage/aggregate_type.h b/be/src/storage/aggregate_type.h
index 5c71c4670d720c..5cc372fb733b76 100644
--- a/be/src/storage/aggregate_type.h
+++ b/be/src/storage/aggregate_type.h
@@ -29,7 +29,9 @@ enum StorageAggregateType {
     STORAGE_AGGREGATE_BITMAP_UNION = 7,
     // Replace if and only if added value is not null
     STORAGE_AGGREGATE_REPLACE_IF_NOT_NULL = 8,
-    STORAGE_AGGREGATE_PERCENTILE_UNION = 9
+    STORAGE_AGGREGATE_PERCENTILE_UNION = 9,
+    // Generic aggregate function's state union
+    STORAGE_AGGREGATE_AGG_STATE_UNION = 10
 };
 
 StorageAggregateType get_aggregation_type_by_string(const std::string& str);
diff --git a/be/src/storage/chunk_aggregator.cpp b/be/src/storage/chunk_aggregator.cpp
index 83ae8a6dae45de..cafd09ed43d6c5 100644
--- a/be/src/storage/chunk_aggregator.cpp
+++ b/be/src/storage/chunk_aggregator.cpp
@@ -18,13 +18,10 @@
 #include "exec/sorting/sorting.h"
 #include "exprs/agg/aggregate_state_allocator.h"
 #include "gutil/casts.h"
-#include "runtime/memory/mem_hook_allocator.h"
 #include "storage/column_aggregate_func.h"
 
 namespace starrocks {
 
-static MemHookAllocator kDefaultChunkAggregatorAllocator = MemHookAllocator{};
-
 ChunkAggregator::ChunkAggregator(const starrocks::Schema* schema, uint32_t reserve_rows, uint32_t max_aggregate_rows,
                                  double factor, bool is_vertical_merge, bool is_key)
         : _schema(schema),
@@ -173,7 +170,7 @@ void ChunkAggregator::aggregate() {
             _aggregate_loops[_aggregate_loops.size() - 1] += 1;
         }
     }
-    SCOPED_THREAD_LOCAL_AGG_STATE_ALLOCATOR_SETTER(&kDefaultChunkAggregatorAllocator);
+    SCOPED_THREAD_LOCAL_AGG_STATE_ALLOCATOR_SETTER(&kDefaultColumnAggregatorAllocator);
     // 3. Copy the selected key rows
     // 4. Aggregate the value rows
     for (int i = 0; i < _key_fields; ++i) {
@@ -196,7 +193,7 @@ bool ChunkAggregator::is_finish() {
 void ChunkAggregator::aggregate_reset() {
     _aggregate_chunk = ChunkHelper::new_chunk(*_schema, _reserve_rows);
     _aggregate_rows = 0;
-    SCOPED_THREAD_LOCAL_AGG_STATE_ALLOCATOR_SETTER(&kDefaultChunkAggregatorAllocator);
+    SCOPED_THREAD_LOCAL_AGG_STATE_ALLOCATOR_SETTER(&kDefaultColumnAggregatorAllocator);
     for (int i = 0; i < _num_fields; ++i) {
         auto p = _aggregate_chunk->get_column_by_index(i).get();
         _column_aggregator[i]->update_aggregate(p);
@@ -210,7 +207,7 @@ void ChunkAggregator::aggregate_reset() {
 }
 
 ChunkPtr ChunkAggregator::aggregate_result() {
-    SCOPED_THREAD_LOCAL_AGG_STATE_ALLOCATOR_SETTER(&kDefaultChunkAggregatorAllocator);
+    SCOPED_THREAD_LOCAL_AGG_STATE_ALLOCATOR_SETTER(&kDefaultColumnAggregatorAllocator);
     for (int i = 0; i < _num_fields; ++i) {
         _column_aggregator[i]->finalize();
     }
diff --git a/be/src/storage/chunk_helper.cpp b/be/src/storage/chunk_helper.cpp
index 788990a7277fb9..e948e9ca94afd9 100644
--- a/be/src/storage/chunk_helper.cpp
+++ b/be/src/storage/chunk_helper.cpp
@@ -141,6 +141,7 @@ Field ChunkHelper::convert_field(ColumnId id, const TabletColumn& c) {
 
     f.set_short_key_length(c.index_length());
     f.set_aggregate_method(c.aggregation());
+    f.set_agg_state_desc(c.get_agg_state_desc());
     return f;
 }
 
diff --git a/be/src/storage/column_aggregate_func.cpp b/be/src/storage/column_aggregate_func.cpp
index 49bd2c2346f600..470887c3945e6d 100644
--- a/be/src/storage/column_aggregate_func.cpp
+++ b/be/src/storage/column_aggregate_func.cpp
@@ -243,19 +243,34 @@ class AggFuncBasedValueAggregator : public ValueColumnAggregatorBase {
 public:
     AggFuncBasedValueAggregator(const AggregateFunction* agg_func) : _agg_func(agg_func) {
         _state = static_cast<AggDataPtr>(std::aligned_alloc(_agg_func->alignof_size(), _agg_func->size()));
-        _agg_func->create(&_func_ctx, _state);
+        // TODO: create a new FunctionContext by using specific FunctionContext::create_context
+        _func_ctx = new FunctionContext();
+        _agg_func->create(_func_ctx, _state);
+    }
+
+    AggFuncBasedValueAggregator(AggStateDesc* agg_state_desc, std::unique_ptr<AggregateFunction> agg_state_unoin)
+            : _agg_func(agg_state_unoin.get()) {
+        _agg_state_unoin = std::move(agg_state_unoin);
+        _func_ctx = FunctionContext::create_context(nullptr, nullptr, agg_state_desc->get_return_type(),
+                                                    agg_state_desc->get_arg_types());
+        _state = static_cast<AggDataPtr>(std::aligned_alloc(_agg_func->alignof_size(), _agg_func->size()));
+        _agg_func->create(_func_ctx, _state);
     }
 
     ~AggFuncBasedValueAggregator() override {
+        SCOPED_THREAD_LOCAL_AGG_STATE_ALLOCATOR_SETTER(&kDefaultColumnAggregatorAllocator);
         if (_state != nullptr) {
-            _agg_func->destroy(&_func_ctx, _state);
+            _agg_func->destroy(_func_ctx, _state);
             std::free(_state);
         }
+        if (_func_ctx != nullptr) {
+            delete _func_ctx;
+        }
     }
 
     void reset() override {
-        _agg_func->destroy(&_func_ctx, _state);
-        _agg_func->create(&_func_ctx, _state);
+        _agg_func->destroy(_func_ctx, _state);
+        _agg_func->create(_func_ctx, _state);
     }
 
     void update_aggregate(Column* agg) override {
@@ -263,16 +278,16 @@ class AggFuncBasedValueAggregator : public ValueColumnAggregatorBase {
         reset();
     }
 
-    void append_data(Column* agg) override { _agg_func->finalize_to_column(&_func_ctx, _state, agg); }
+    void append_data(Column* agg) override { _agg_func->finalize_to_column(_func_ctx, _state, agg); }
 
     // |data| is readonly.
     void aggregate_impl(int row, const ColumnPtr& data) override {
-        _agg_func->merge(&_func_ctx, data.get(), _state, row);
+        _agg_func->merge(_func_ctx, data.get(), _state, row);
     }
 
     // |data| is readonly.
     void aggregate_batch_impl(int start, int end, const ColumnPtr& input) override {
-        _agg_func->merge_batch_single_state(&_func_ctx, _state, input.get(), start, end - start);
+        _agg_func->merge_batch_single_state(_func_ctx, _state, input.get(), start, end - start);
     }
 
     bool need_deep_copy() const override { return false; };
@@ -305,9 +320,10 @@ class AggFuncBasedValueAggregator : public ValueColumnAggregatorBase {
     }
 
 private:
-    FunctionContext _func_ctx;
     const AggregateFunction* _agg_func;
+    FunctionContext* _func_ctx = nullptr;
     AggDataPtr _state{nullptr};
+    std::unique_ptr<AggregateFunction> _agg_state_unoin = nullptr;
 };
 
 #define CASE_DEFAULT_WARNING(TYPE)                                             \
@@ -417,6 +433,21 @@ ColumnAggregatorPtr ColumnAggregatorFactory::create_value_column_aggregator(cons
         } else {
             return p;
         }
+    } else if (method == STORAGE_AGGREGATE_AGG_STATE_UNION) {
+        if (field->get_agg_state_desc() == nullptr) {
+            CHECK(false) << "Bad agg state union method for column: " << field->name()
+                         << " for its agg state type is null";
+            return nullptr;
+        }
+        auto* agg_state_desc = field->get_agg_state_desc();
+        auto func_name = agg_state_desc->get_func_name();
+        DCHECK_EQ(field->is_nullable(), agg_state_desc->is_result_nullable());
+        auto* agg_func = AggStateDesc::get_agg_state_func(agg_state_desc);
+        CHECK(agg_func != nullptr) << "Unknown aggregate function, name=" << func_name << ", type=" << type
+                                   << ", is_nullable=" << field->is_nullable()
+                                   << ", agg_state_desc=" << agg_state_desc->debug_string();
+        // TODO(fixme): use agg_state_union instead of agg_func
+        return std::make_unique<AggFuncBasedValueAggregator>(std::move(agg_func));
     } else {
         auto func_name = get_string_by_aggregation_type(method);
         // TODO(alvin): To keep compatible with old code, when type must not be the legacy type,
diff --git a/be/src/storage/column_aggregate_func.h b/be/src/storage/column_aggregate_func.h
index a0305d654e45bf..02bfbf11aa38db 100644
--- a/be/src/storage/column_aggregate_func.h
+++ b/be/src/storage/column_aggregate_func.h
@@ -15,9 +15,12 @@
 #pragma once
 
 #include "column/field.h"
+#include "runtime/memory/mem_hook_allocator.h"
 #include "storage/column_aggregator.h"
 
 namespace starrocks {
+
+static MemHookAllocator kDefaultColumnAggregatorAllocator = MemHookAllocator{};
 class ColumnAggregatorFactory {
 public:
     static ColumnAggregatorPtr create_key_column_aggregator(const FieldPtr& field);
diff --git a/be/src/storage/column_in_predicate.cpp b/be/src/storage/column_in_predicate.cpp
index e6f5ec4cbde200..7f6613c8ff53c7 100644
--- a/be/src/storage/column_in_predicate.cpp
+++ b/be/src/storage/column_in_predicate.cpp
@@ -15,13 +15,16 @@
 #include <type_traits>
 
 #include "column/column.h"
+#include "column/column_helper.h"
 #include "column/nullable_column.h"
+#include "column/vectorized_fwd.h"
 #include "gutil/casts.h"
 #include "roaring/roaring.hh"
 #include "storage/column_predicate.h"
 #include "storage/in_predicate_utils.h"
 #include "storage/rowset/bitmap_index_reader.h"
 #include "storage/rowset/bloom_filter.h"
+#include "types/logical_type.h"
 
 namespace starrocks {
 
@@ -365,6 +368,86 @@ class BinaryColumnInPredicate : public ColumnPredicate {
     ItemHashSet<Slice> _slices;
 };
 
+class DictionaryCodeInPredicate : public ColumnPredicate {
+private:
+    enum LogicOp { ASSIGN, AND, OR };
+
+public:
+    DictionaryCodeInPredicate(const TypeInfoPtr& type_info, ColumnId id, const std::vector<int32_t>& operands,
+                              size_t size)
+            : ColumnPredicate(type_info, id), _bit_mask(size) {
+        for (auto item : operands) {
+            DCHECK(item < size);
+            _bit_mask[item] = 1;
+        }
+    }
+
+    ~DictionaryCodeInPredicate() override = default;
+
+    template <LogicOp Op>
+    inline void t_evaluate(const Column* column, uint8_t* sel, uint16_t from, uint16_t to) const {
+        const Int32Column* dict_code_column = down_cast<const Int32Column*>(ColumnHelper::get_data_column(column));
+        std::vector<int32_t> data = dict_code_column->get_data();
+        Filter filter(to - from, 1);
+
+        if (column->has_null()) {
+            const NullColumn* null_column = down_cast<const NullableColumn*>(column)->null_column().get();
+            auto null_data = null_column->get_data();
+            for (auto i = from; i < to; i++) {
+                auto index = data[i] >= _bit_mask.size() ? 0 : data[i];
+                filter[i - from] = (!null_data[i]) & _bit_mask[index];
+            }
+        } else {
+            for (auto i = from; i < to; i++) {
+                filter[i - from] = _bit_mask[data[i]];
+            }
+        }
+
+        for (auto i = from; i < to; i++) {
+            if constexpr (Op == ASSIGN) {
+                sel[i] = filter[i - from];
+            } else if constexpr (Op == AND) {
+                sel[i] &= filter[i - from];
+            } else {
+                sel[i] |= filter[i - from];
+            }
+        }
+    }
+
+    Status evaluate(const Column* column, uint8_t* selection, uint16_t from, uint16_t to) const override {
+        t_evaluate<ASSIGN>(column, selection, from, to);
+        return Status::OK();
+    }
+
+    Status evaluate_and(const Column* column, uint8_t* selection, uint16_t from, uint16_t to) const override {
+        t_evaluate<AND>(column, selection, from, to);
+        return Status::OK();
+    }
+
+    Status evaluate_or(const Column* column, uint8_t* selection, uint16_t from, uint16_t to) const override {
+        t_evaluate<OR>(column, selection, from, to);
+        return Status::OK();
+    }
+
+    bool can_vectorized() const override { return false; }
+
+    PredicateType type() const override { return PredicateType::kInList; }
+
+    Status convert_to(const ColumnPredicate** output, const TypeInfoPtr& target_type_info,
+                      ObjectPool* obj_pool) const override {
+        const auto to_type = target_type_info->type();
+        if (to_type == LogicalType::TYPE_INT) {
+            *output = this;
+            return Status::OK();
+        }
+        CHECK(false) << "Not support, from_type=" << LogicalType::TYPE_INT << ", to_type=" << to_type;
+        return Status::OK();
+    }
+
+private:
+    std::vector<uint8_t> _bit_mask;
+};
+
 template <template <typename, size_t...> typename Set, size_t... Args>
 ColumnPredicate* new_column_in_predicate_generic(const TypeInfoPtr& type_info, ColumnId id,
                                                  const std::vector<std::string>& strs) {
@@ -507,4 +590,19 @@ ColumnPredicate* new_column_in_predicate(const TypeInfoPtr& type_info, ColumnId
     }
 }
 
+ColumnPredicate* new_dictionary_code_in_predicate(const TypeInfoPtr& type, ColumnId id,
+                                                  const std::vector<int32_t>& operands, size_t size) {
+    DCHECK(is_integer_type(type->type()));
+    if (operands.size() <= 3 || size > 1024) {
+        std::vector<std::string> str_codes;
+        str_codes.reserve(operands.size());
+        for (int code : operands) {
+            str_codes.emplace_back(std::to_string(code));
+        }
+        return new_column_in_predicate(type, id, str_codes);
+    } else {
+        return new DictionaryCodeInPredicate(type, id, operands, size);
+    }
+}
+
 } //namespace starrocks
diff --git a/be/src/storage/column_predicate.h b/be/src/storage/column_predicate.h
index 7c9bfeaa4bbe67..e9a5f11845eb9d 100644
--- a/be/src/storage/column_predicate.h
+++ b/be/src/storage/column_predicate.h
@@ -245,6 +245,9 @@ ColumnPredicate* new_column_cmp_predicate(PredicateType predicate, const TypeInf
 
 ColumnPredicate* new_column_in_predicate(const TypeInfoPtr& type, ColumnId id,
                                          const std::vector<std::string>& operands);
+
+ColumnPredicate* new_dictionary_code_in_predicate(const TypeInfoPtr& type, ColumnId id,
+                                                  const std::vector<int32_t>& operands, size_t size);
 ColumnPredicate* new_column_not_in_predicate(const TypeInfoPtr& type, ColumnId id,
                                              const std::vector<std::string>& operands);
 ColumnPredicate* new_column_null_predicate(const TypeInfoPtr& type, ColumnId, bool is_null);
diff --git a/be/src/storage/delta_column_group.cpp b/be/src/storage/delta_column_group.cpp
index cd85692d8aecb5..6f4831d43357db 100644
--- a/be/src/storage/delta_column_group.cpp
+++ b/be/src/storage/delta_column_group.cpp
@@ -23,10 +23,12 @@
 namespace starrocks {
 
 void DeltaColumnGroup::init(int64_t version, const std::vector<std::vector<ColumnUID>>& column_ids,
-                            const std::vector<std::string>& column_files) {
+                            const std::vector<std::string>& column_files,
+                            const std::vector<std::string>& encryption_metas) {
     _version = version;
     _column_uids = column_ids;
     _column_files = column_files;
+    _encryption_metas = encryption_metas;
     _calc_memory_usage();
 }
 
@@ -39,7 +41,13 @@ void DeltaColumnGroup::_calc_memory_usage() {
         total_column_name_size += _column_files[i].length();
     }
 
-    _memory_usage = sizeof(size_t) + sizeof(int64_t) + sizeof(uint32_t) * total_ids + total_column_name_size;
+    size_t total_encryption_meta_size = 0;
+    for (const auto& encryption_meta : _encryption_metas) {
+        total_encryption_meta_size += encryption_meta.length();
+    }
+
+    _memory_usage = sizeof(size_t) + sizeof(int64_t) + sizeof(uint32_t) * total_ids + total_column_name_size +
+                    total_encryption_meta_size;
 }
 
 int DeltaColumnGroup::merge_into_by_version(DeltaColumnGroupList& dcgs, const std::string& dir,
@@ -68,6 +76,9 @@ bool DeltaColumnGroup::merge_by_version(DeltaColumnGroup& dcg, const std::string
     for (size_t suffix = orig_size; suffix < _column_files.size(); ++suffix) {
         _column_files[suffix] =
                 file_name(Rowset::delta_column_group_path(dir, rowset_id, segment_id, _version, suffix));
+        if (dcg.encryption_metas().size() > 0) {
+            _encryption_metas.push_back(dcg.encryption_metas()[suffix - orig_size]);
+        }
     }
 
     _calc_memory_usage();
@@ -108,6 +119,9 @@ Status DeltaColumnGroup::load(int64_t version, const char* data, size_t length)
     for (const auto& column_file : dcg_pb.column_files()) {
         _column_files.push_back(column_file);
     }
+    for (const auto& encryption_meta : dcg_pb.encryption_metas()) {
+        _encryption_metas.push_back(encryption_meta);
+    }
     for (const auto& cids : dcg_pb.column_ids()) {
         _column_uids.emplace_back();
         for (const auto& cid : cids.column_ids()) {
@@ -123,6 +137,9 @@ Status DeltaColumnGroup::load(int64_t version, const DeltaColumnGroupVerPB& dcg_
     for (const auto& column_file : dcg_ver_pb.column_files()) {
         _column_files.push_back(column_file);
     }
+    for (const auto& encryption_meta : dcg_ver_pb.encryption_metas()) {
+        _encryption_metas.push_back(encryption_meta);
+    }
     for (const auto& ucids : dcg_ver_pb.unique_column_ids()) {
         _column_uids.emplace_back();
         for (const auto& cid : ucids.column_ids()) {
@@ -138,6 +155,9 @@ std::string DeltaColumnGroup::save() const {
     for (const auto& column_file : _column_files) {
         dcg_pb.add_column_files(column_file);
     }
+    for (const auto& encryption_meta : _encryption_metas) {
+        dcg_pb.add_encryption_metas(encryption_meta);
+    }
     for (const auto& cids : _column_uids) {
         auto* dcg_col_pb = dcg_pb.add_column_ids();
         for (const auto& cid : cids) {
@@ -158,6 +178,9 @@ std::string DeltaColumnGroupListSerializer::serialize_delta_column_group_list(co
         for (const auto& relative_column_file : dcg->relative_column_files()) {
             dcg_pb.add_column_files(relative_column_file);
         }
+        for (const auto& encryption_meta : dcg->encryption_metas()) {
+            dcg_pb.add_encryption_metas(encryption_meta);
+        }
         for (const auto& cids : dcg->column_ids()) {
             auto* dcg_col_pb = dcg_pb.add_column_ids();
             for (const auto& cid : cids) {
@@ -197,6 +220,7 @@ Status DeltaColumnGroupListSerializer::_deserialize_delta_column_group_list(cons
         auto dcg = std::make_shared<DeltaColumnGroup>();
         std::vector<std::vector<ColumnUID>> column_ids;
         std::vector<std::string> column_files;
+        std::vector<std::string> encryption_metas;
         DCHECK(dcgs_pb.dcgs(i).column_ids().size() == dcgs_pb.dcgs(i).column_files().size());
         for (int j = 0; j < dcgs_pb.dcgs(i).column_ids().size(); ++j) {
             column_ids.emplace_back();
@@ -204,8 +228,11 @@ Status DeltaColumnGroupListSerializer::_deserialize_delta_column_group_list(cons
                 column_ids.back().push_back(cid);
             }
             column_files.push_back(dcgs_pb.dcgs(i).column_files(j));
+            if (j < dcgs_pb.dcgs(i).encryption_metas_size()) {
+                encryption_metas.push_back(dcgs_pb.dcgs(i).encryption_metas(j));
+            }
         }
-        dcg->init(dcgs_pb.versions(i), column_ids, column_files);
+        dcg->init(dcgs_pb.versions(i), column_ids, column_files, encryption_metas);
         dcgs->push_back(dcg);
     }
     return Status::OK();
diff --git a/be/src/storage/delta_column_group.h b/be/src/storage/delta_column_group.h
index 9599386d07d2c7..e235e52eb3bacc 100644
--- a/be/src/storage/delta_column_group.h
+++ b/be/src/storage/delta_column_group.h
@@ -35,7 +35,7 @@ class DeltaColumnGroup {
     DeltaColumnGroup() {}
     ~DeltaColumnGroup() {}
     void init(int64_t version, const std::vector<std::vector<ColumnUID>>& column_ids,
-              const std::vector<std::string>& column_files);
+              const std::vector<std::string>& column_files, const std::vector<std::string>& encryption_metas = {});
     Status load(int64_t version, const char* data, size_t length);
     Status load(int64_t version, const DeltaColumnGroupVerPB& dcg_ver_pb);
     std::string save() const;
@@ -92,6 +92,8 @@ class DeltaColumnGroup {
 
     const std::vector<std::string>& relative_column_files() const { return _column_files; }
 
+    const std::vector<std::string>& encryption_metas() const { return _encryption_metas; }
+
 private:
     void _calc_memory_usage();
 
@@ -99,6 +101,7 @@ class DeltaColumnGroup {
     int64_t _version = 0;
     std::vector<std::vector<ColumnUID>> _column_uids;
     std::vector<std::string> _column_files;
+    std::vector<std::string> _encryption_metas;
     size_t _memory_usage = 0;
 };
 
diff --git a/be/src/storage/kv_store.cpp b/be/src/storage/kv_store.cpp
index 1f8001efd8b948..0fe04ccdbe1f33 100644
--- a/be/src/storage/kv_store.cpp
+++ b/be/src/storage/kv_store.cpp
@@ -341,17 +341,9 @@ std::string KVStore::get_root_path() {
 Status KVStore::OptDeleteRange(ColumnFamilyIndex column_family_index, const std::string& begin_key,
                                const std::string& end_key, WriteBatch* batch) {
     rocksdb::ColumnFamilyHandle* handle = _handles[column_family_index];
-    int key_cnt = 0;
     return iterate_range(column_family_index, begin_key, end_key,
                          [&](std::string_view key, std::string_view value) -> StatusOr<bool> {
-                             if (key_cnt >= config::rocksdb_opt_delete_range_limit) {
-                                 // fallback and use `DeleteRange` instead.
-                                 batch->Clear();
-                                 RETURN_ERROR_IF_FALSE(batch->DeleteRange(handle, begin_key, end_key).ok());
-                                 return false;
-                             }
-                             batch->Delete(handle, key);
-                             key_cnt++;
+                             RETURN_ERROR_IF_FALSE(batch->Delete(handle, key).ok());
                              return true;
                          });
 }
diff --git a/be/src/storage/lake/column_mode_partial_update_handler.cpp b/be/src/storage/lake/column_mode_partial_update_handler.cpp
index fe833479f64924..d4adbbd2b19e37 100644
--- a/be/src/storage/lake/column_mode_partial_update_handler.cpp
+++ b/be/src/storage/lake/column_mode_partial_update_handler.cpp
@@ -16,6 +16,7 @@
 
 #include "common/tracer.h"
 #include "fs/fs_util.h"
+#include "fs/key_cache.h"
 #include "gutil/strings/substitute.h"
 #include "serde/column_array_serde.h"
 #include "storage/chunk_helper.h"
@@ -232,8 +233,13 @@ StatusOr<std::unique_ptr<SegmentWriter>> ColumnModePartialUpdateHandler::_prepar
         const RowsetUpdateStateParams& params, const std::shared_ptr<TabletSchema>& tschema) {
     const std::string path = params.tablet->segment_location(gen_cols_filename(_txn_id));
     WritableFileOptions opts{.sync_on_close = true, .mode = FileSystem::CREATE_OR_OPEN_WITH_TRUNCATE};
-    ASSIGN_OR_RETURN(auto wfile, fs::new_writable_file(opts, path));
     SegmentWriterOptions writer_options;
+    if (config::enable_transparent_data_encryption) {
+        ASSIGN_OR_RETURN(auto pair, KeyCache::instance().create_encryption_meta_pair_using_current_kek());
+        opts.encryption_info = pair.info;
+        writer_options.encryption_meta = std::move(pair.encryption_meta);
+    }
+    ASSIGN_OR_RETURN(auto wfile, fs::new_writable_file(opts, path));
     auto segment_writer = std::make_unique<SegmentWriter>(std::move(wfile), 0, tschema, writer_options);
     RETURN_IF_ERROR(segment_writer->init(false));
     return std::move(segment_writer);
@@ -259,8 +265,9 @@ StatusOr<ChunkPtr> ColumnModePartialUpdateHandler::_read_from_source_segment(con
     }
     uint32_t rowset_id = params.container.rssid_to_rowid().at(rssid);
     // 2. load segment meta.
-    ASSIGN_OR_RETURN(auto segment, params.tablet->tablet_mgr()->load_segment(fileinfo, 0, &footer_size_hint,
-                                                                             lake_io_opts, true, params.tablet_schema));
+    ASSIGN_OR_RETURN(auto segment, params.tablet->tablet_mgr()->load_segment(
+                                           fileinfo, rssid - rowset_id /* segment id inside rowset */,
+                                           &footer_size_hint, lake_io_opts, true, params.tablet_schema));
     SegmentReadOptions seg_options;
     ASSIGN_OR_RETURN(seg_options.fs, FileSystem::CreateSharedFromString(fileinfo.path));
     seg_options.stats = &stats;
@@ -434,7 +441,7 @@ Status ColumnModePartialUpdateHandler::execute(const RowsetUpdateStateParams& pa
     // {{1,2}, {3,4}} -> {"aaa.cols", "bbb.cols"}
     // It means column_1 and column_2 are stored in aaa.cols, and column_3 and column_4 are stored in bbb.cols
     std::map<uint32_t, std::vector<std::vector<ColumnUID>>> dcg_column_ids;
-    std::map<uint32_t, std::vector<std::string>> dcg_column_files;
+    std::map<uint32_t, std::vector<std::pair<std::string, std::string>>> dcg_column_file_with_encryption_metas;
     // 3. read from raw segment file and update file, and generate `.col` files one by one
     for (uint32_t col_index = 0; col_index < update_column_ids.size(); col_index += BATCH_HANDLE_COLUMN_CNT) {
         for (const auto& each : rss_upt_id_to_rowid_pairs) {
@@ -467,13 +474,14 @@ Status ColumnModePartialUpdateHandler::execute(const RowsetUpdateStateParams& pa
             }
             // 3.6 prepare column id list and dcg file list
             dcg_column_ids[each.first].push_back(selective_unique_update_column_ids);
-            dcg_column_files[each.first].push_back(file_name(delta_column_group_writer->segment_path()));
+            dcg_column_file_with_encryption_metas[each.first].emplace_back(
+                    file_name(delta_column_group_writer->segment_path()), delta_column_group_writer->encryption_meta());
             TRACE_COUNTER_INCREMENT("pcu_handle_cnt", 1);
         }
     }
     // 4 generate delta columngroup
     for (const auto& each : rss_upt_id_to_rowid_pairs) {
-        builder->append_dcg(each.first, dcg_column_files[each.first], dcg_column_ids[each.first]);
+        builder->append_dcg(each.first, dcg_column_file_with_encryption_metas[each.first], dcg_column_ids[each.first]);
     }
     builder->apply_column_mode_partial_update(params.op_write);
 
diff --git a/be/src/storage/lake/lake_persistent_index.cpp b/be/src/storage/lake/lake_persistent_index.cpp
index 0c857fd60eb353..235853f30d8780 100644
--- a/be/src/storage/lake/lake_persistent_index.cpp
+++ b/be/src/storage/lake/lake_persistent_index.cpp
@@ -531,8 +531,14 @@ Status LakePersistentIndex::load_dels(const RowsetPtr& rowset, const Schema& pke
     std::unique_ptr<Column> pk_column;
     RETURN_IF_ERROR(PrimaryKeyEncoder::create_column(pkey_schema, &pk_column));
     // Iterate all del files and insert into index.
-    for (const auto& del : rowset->metadata().del_files()) {
-        ASSIGN_OR_RETURN(auto read_file, fs::new_random_access_file(_tablet_mgr->del_location(_tablet_id, del.name())));
+    for (int del_idx = 0; del_idx < rowset->metadata().del_files_size(); ++del_idx) {
+        const auto& del = rowset->metadata().del_files(del_idx);
+        RandomAccessFileOptions ropts;
+        if (!del.encryption_meta().empty()) {
+            ASSIGN_OR_RETURN(ropts.encryption_info, KeyCache::instance().unwrap_encryption_meta(del.encryption_meta()));
+        }
+        ASSIGN_OR_RETURN(auto read_file,
+                         fs::new_random_access_file(ropts, _tablet_mgr->del_location(_tablet_id, del.name())));
         ASSIGN_OR_RETURN(auto read_buffer, read_file->read_all());
         // serialize to column
         auto pkc = pk_column->clone();
diff --git a/be/src/storage/lake/meta_file.cpp b/be/src/storage/lake/meta_file.cpp
index 8b95d87a79938b..584d5c17b79338 100644
--- a/be/src/storage/lake/meta_file.cpp
+++ b/be/src/storage/lake/meta_file.cpp
@@ -53,16 +53,20 @@ void MetaFileBuilder::append_delvec(const DelVectorPtr& delvec, uint32_t segment
     }
 }
 
-void MetaFileBuilder::append_dcg(uint32_t rssid, const std::vector<std::string>& filenames,
+void MetaFileBuilder::append_dcg(uint32_t rssid,
+                                 const std::vector<std::pair<std::string, std::string>>& file_with_encryption_metas,
                                  const std::vector<std::vector<ColumnUID>>& unique_column_id_list) {
     DeltaColumnGroupVerPB& dcg_ver = (*_tablet_meta->mutable_dcg_meta()->mutable_dcgs())[rssid];
     DeltaColumnGroupVerPB new_dcg_ver;
     std::unordered_set<ColumnUID> need_to_remove_cuids_filter;
 
     // 1. append new dcgs
-    DCHECK(filenames.size() == unique_column_id_list.size());
-    for (int i = 0; i < filenames.size(); i++) {
-        new_dcg_ver.add_column_files(filenames[i]);
+    DCHECK(file_with_encryption_metas.size() == unique_column_id_list.size());
+    for (int i = 0; i < file_with_encryption_metas.size(); i++) {
+        new_dcg_ver.add_column_files(file_with_encryption_metas[i].first);
+        if (!file_with_encryption_metas[i].second.empty()) {
+            new_dcg_ver.add_encryption_metas(file_with_encryption_metas[i].second);
+        }
         DeltaColumnGroupColumnIdsPB unique_cids;
         for (const ColumnUID uid : unique_column_id_list[i]) {
             unique_cids.add_column_ids(uid);
@@ -127,6 +131,12 @@ void MetaFileBuilder::apply_opwrite(const TxnLogPB_OpWrite& op_write, const std:
         del_file_with_rid.set_origin_rowset_id(rowset->id());
         // For now, op_offset is always max segment's id
         del_file_with_rid.set_op_offset(std::max(op_write.rowset().segments_size(), 1) - 1);
+        if (op_write.del_encryption_metas_size() > 0) {
+            CHECK(op_write.del_encryption_metas_size() == op_write.dels_size())
+                    << fmt::format("del_encryption_metas_size:{} != dels_size:{}", op_write.del_encryption_metas_size(),
+                                   op_write.dels_size());
+            del_file_with_rid.set_encryption_meta(op_write.del_encryption_metas(i));
+        }
         rowset->add_del_files()->CopyFrom(del_file_with_rid);
     }
     // if rowset don't contain segment files, still inc next_rowset_id
diff --git a/be/src/storage/lake/meta_file.h b/be/src/storage/lake/meta_file.h
index 7b91f3a168635f..5afef49dae4a61 100644
--- a/be/src/storage/lake/meta_file.h
+++ b/be/src/storage/lake/meta_file.h
@@ -40,7 +40,7 @@ class MetaFileBuilder {
     // append delvec to builder's buffer
     void append_delvec(const DelVectorPtr& delvec, uint32_t segment_id);
     // append delta column group to builder
-    void append_dcg(uint32_t rssid, const std::vector<std::string>& filenames,
+    void append_dcg(uint32_t rssid, const std::vector<std::pair<std::string, std::string>>& file_with_encryption_metas,
                     const std::vector<std::vector<ColumnUID>>& unique_column_id_list);
     // handle txn log
     void apply_opwrite(const TxnLogPB_OpWrite& op_write, const std::map<int, FileInfo>& replace_segments,
diff --git a/be/src/storage/memtable.cpp b/be/src/storage/memtable.cpp
index 77d8f5008c9642..434b5d86318e0f 100644
--- a/be/src/storage/memtable.cpp
+++ b/be/src/storage/memtable.cpp
@@ -324,10 +324,9 @@ Status MemTable::flush(SegmentPB* seg_info) {
     if (UNLIKELY(_result_chunk == nullptr)) {
         return Status::OK();
     }
-    std::string msg;
-    if (_result_chunk->capacity_limit_reached(&msg)) {
-        return Status::InternalError(
-                fmt::format("memtable of tablet {} reache the capacity limit, detail msg: {}", _tablet_id, msg));
+    if (auto st = _result_chunk->capacity_limit_reached(); !st.ok()) {
+        return Status::InternalError(fmt::format("memtable of tablet {} reache the capacity limit, detail msg: {}",
+                                                 _tablet_id, st.message()));
     }
     auto scope = IOProfiler::scope(IOProfiler::TAG_LOAD, _tablet_id);
     int64_t duration_ns = 0;
diff --git a/be/src/storage/meta_reader.cpp b/be/src/storage/meta_reader.cpp
index dbcfa2af09cdbb..a59d6031be41b5 100644
--- a/be/src/storage/meta_reader.cpp
+++ b/be/src/storage/meta_reader.cpp
@@ -238,10 +238,6 @@ Status SegmentMetaCollecter::_collect(const std::string& name, ColumnId cid, Col
 }
 
 Status SegmentMetaCollecter::_collect_flat_json(ColumnId cid, Column* column) {
-    if (cid >= _segment->num_columns()) {
-        return Status::NotFound("error column id");
-    }
-
     const ColumnReader* col_reader = _segment->column(cid);
     if (col_reader == nullptr) {
         return Status::NotFound("don't found column");
@@ -279,7 +275,8 @@ Status SegmentMetaCollecter::_collect_dict(ColumnId cid, Column* column, Logical
     }
 
     if (words.size() > DICT_DECODE_MAX_SIZE) {
-        return Status::GlobalDictError("global dict greater than DICT_DECODE_MAX_SIZE");
+        return Status::GlobalDictError(fmt::format("global dict size:{} greater than DICT_DECODE_MAX_SIZE:{}",
+                                                   words.size(), DICT_DECODE_MAX_SIZE));
     }
 
     // array<string> has none dict, return directly
diff --git a/be/src/storage/metadata_util.cpp b/be/src/storage/metadata_util.cpp
index cbc0f756e53488..8b8cc67de16c45 100644
--- a/be/src/storage/metadata_util.cpp
+++ b/be/src/storage/metadata_util.cpp
@@ -65,6 +65,8 @@ static StorageAggregateType t_aggregation_type_to_field_aggregation_method(TAggr
         return STORAGE_AGGREGATE_SUM;
     case TAggregationType::PERCENTILE_UNION:
         return STORAGE_AGGREGATE_PERCENTILE_UNION;
+    case TAggregationType::AGG_STATE_UNION:
+        return STORAGE_AGGREGATE_AGG_STATE_UNION;
     }
     return STORAGE_AGGREGATE_NONE;
 }
@@ -211,7 +213,12 @@ Status t_column_to_pb_column(int32_t unique_id, const TColumn& t_column, ColumnP
     if (t_column.__isset.is_bloom_filter_column) {
         column_pb->set_is_bf_column(t_column.is_bloom_filter_column);
     }
-
+    // agg state type desc
+    if (t_column.__isset.agg_state_desc) {
+        auto& agg_state_desc = t_column.agg_state_desc;
+        auto* agg_state_pb = column_pb->mutable_agg_state_desc();
+        AggStateDesc::thrift_to_protobuf(agg_state_desc, agg_state_pb);
+    }
     return Status::OK();
 }
 
diff --git a/be/src/storage/olap_server.cpp b/be/src/storage/olap_server.cpp
index 5e4e163a1ff4c2..b9186a7921247f 100644
--- a/be/src/storage/olap_server.cpp
+++ b/be/src/storage/olap_server.cpp
@@ -939,8 +939,8 @@ void* StorageEngine::_schedule_apply_thread_callback(void* arg) {
             auto time_point = std::chrono::steady_clock::now();
             while (!_bg_worker_stopped.load(std::memory_order_consume) && !_schedule_apply_tasks.empty() &&
                    _schedule_apply_tasks.top().first <= time_point) {
-                _schedule_apply_tasks.pop();
                 auto tablet_id = _schedule_apply_tasks.top().second;
+                _schedule_apply_tasks.pop();
                 auto tablet = _tablet_manager->get_tablet(tablet_id);
                 if (tablet == nullptr || tablet->updates() == nullptr) {
                     continue;
diff --git a/be/src/storage/rowset/column_iterator.h b/be/src/storage/rowset/column_iterator.h
index a168688e47fba8..e28c5be6ea94f1 100644
--- a/be/src/storage/rowset/column_iterator.h
+++ b/be/src/storage/rowset/column_iterator.h
@@ -61,6 +61,8 @@ struct ColumnIteratorOptions {
     // reader statistics
     OlapReaderStatistics* stats = nullptr;
     bool use_page_cache = false;
+    // temporary data does not allow caching
+    bool temporary_data = false;
     LakeIOOptions lake_io_opts{.fill_data_cache = true};
 
     // check whether column pages are all dictionary encoding.
diff --git a/be/src/storage/rowset/json_column_iterator.cpp b/be/src/storage/rowset/json_column_iterator.cpp
index 5177b6d4aa4ec3..1490cf2a0e6c00 100644
--- a/be/src/storage/rowset/json_column_iterator.cpp
+++ b/be/src/storage/rowset/json_column_iterator.cpp
@@ -134,6 +134,9 @@ Status JsonFlatColumnIterator::init(const ColumnIteratorOptions& opts) {
         for (int i = 0; i < _source_paths.size(); i++) {
             opts.stats->flat_json_hits[_source_paths[i]] += 1;
         }
+        if (has_remain) {
+            opts.stats->flat_json_hits["remain"] += 1;
+        }
         return Status::OK();
     }
 
@@ -162,6 +165,9 @@ Status JsonFlatColumnIterator::init(const ColumnIteratorOptions& opts) {
         for (int i = 0; i < fp.size(); i++) {
             opts.stats->dynamic_json_hits[fp[i]] += 1;
         }
+        if (has_remain) {
+            opts.stats->flat_json_hits["remain"] += 1;
+        }
     }
 
     return Status::OK();
@@ -490,6 +496,9 @@ Status JsonMergeIterator::init(const ColumnIteratorOptions& opts) {
     for (auto& p : _src_paths) {
         opts.stats->merge_json_hits[p] += 1;
     }
+    if (has_remain) {
+        opts.stats->merge_json_hits["remain"] += 1;
+    }
     SCOPED_RAW_TIMER(&_opts.stats->json_init_ns);
     _merger = std::make_unique<JsonMerger>(_src_paths, _src_types, has_remain);
 
diff --git a/be/src/storage/rowset/scalar_column_iterator.cpp b/be/src/storage/rowset/scalar_column_iterator.cpp
index 1b2b46e02b3843..481e4ca1f20a4e 100644
--- a/be/src/storage/rowset/scalar_column_iterator.cpp
+++ b/be/src/storage/rowset/scalar_column_iterator.cpp
@@ -52,8 +52,9 @@ Status ScalarColumnIterator::init(const ColumnIteratorOptions& opts) {
     _opts = opts;
 
     IndexReadOptions index_opts;
-    index_opts.use_page_cache = config::enable_ordinal_index_memory_page_cache || !config::disable_storage_page_cache;
-    index_opts.kept_in_memory = config::enable_ordinal_index_memory_page_cache;
+    index_opts.use_page_cache = !opts.temporary_data &&
+                                (config::enable_ordinal_index_memory_page_cache || !config::disable_storage_page_cache);
+    index_opts.kept_in_memory = !opts.temporary_data && config::enable_ordinal_index_memory_page_cache;
     index_opts.lake_io_opts = opts.lake_io_opts;
     index_opts.read_file = _opts.read_file;
     index_opts.stats = _opts.stats;
@@ -381,8 +382,9 @@ Status ScalarColumnIterator::get_row_ranges_by_zone_map(const std::vector<const
         }
 
         IndexReadOptions opts;
-        opts.use_page_cache = config::enable_zonemap_index_memory_page_cache || !config::disable_storage_page_cache;
-        opts.kept_in_memory = config::enable_zonemap_index_memory_page_cache;
+        opts.use_page_cache = !_opts.temporary_data &&
+                              (config::enable_zonemap_index_memory_page_cache || !config::disable_storage_page_cache);
+        opts.kept_in_memory = !_opts.temporary_data && config::enable_zonemap_index_memory_page_cache;
         opts.lake_io_opts = _opts.lake_io_opts;
         opts.read_file = _opts.read_file;
         opts.stats = _opts.stats;
@@ -422,7 +424,7 @@ Status ScalarColumnIterator::get_row_ranges_by_bloom_filter(const std::vector<co
     }
 
     IndexReadOptions opts;
-    opts.use_page_cache = !config::disable_storage_page_cache;
+    opts.use_page_cache = !_opts.temporary_data && !config::disable_storage_page_cache;
     opts.kept_in_memory = false;
     opts.lake_io_opts = _opts.lake_io_opts;
     opts.read_file = _opts.read_file;
diff --git a/be/src/storage/rowset/segment.cpp b/be/src/storage/rowset/segment.cpp
index 65617427c690d0..8867d803c0d2d5 100644
--- a/be/src/storage/rowset/segment.cpp
+++ b/be/src/storage/rowset/segment.cpp
@@ -485,6 +485,9 @@ StatusOr<std::shared_ptr<Segment>> Segment::new_dcg_segment(const DeltaColumnGro
         tablet_schema = TabletSchema::create_with_uid(_tablet_schema.schema(), dcg.column_ids()[idx]);
     }
     FileInfo info{.path = dcg.column_files(parent_name(_segment_file_info.path))[idx]};
+    if (idx < dcg.encryption_metas().size()) {
+        info.encryption_meta = dcg.encryption_metas()[idx];
+    }
     return Segment::open(_fs, info, 0, tablet_schema, nullptr);
 }
 
diff --git a/be/src/storage/rowset/segment_iterator.cpp b/be/src/storage/rowset/segment_iterator.cpp
index 476085dfe6133f..769c51a3cd2b6c 100644
--- a/be/src/storage/rowset/segment_iterator.cpp
+++ b/be/src/storage/rowset/segment_iterator.cpp
@@ -544,6 +544,7 @@ Status SegmentIterator::_init_column_iterator_by_cid(const ColumnId cid, const C
     ColumnIteratorOptions iter_opts;
     iter_opts.stats = _opts.stats;
     iter_opts.use_page_cache = _opts.use_page_cache;
+    iter_opts.temporary_data = _opts.temporary_data;
     iter_opts.check_dict_encoding = check_dict_enc;
     iter_opts.reader_type = _opts.reader_type;
     iter_opts.lake_io_opts = _opts.lake_io_opts;
@@ -1816,27 +1817,28 @@ Status SegmentIterator::_apply_bitmap_index() {
             cid_2_ucid[field->id()] = field->uid();
         }
 
-        RETURN_IF_ERROR(_bitmap_index_evaluator.init([&cid_2_ucid,
-                                                      this](ColumnId cid) -> StatusOr<BitmapIndexIterator*> {
-            const ColumnUID ucid = cid_2_ucid[cid];
-            // the column's index in this segment file
-            ASSIGN_OR_RETURN(std::shared_ptr<Segment> segment_ptr, _get_dcg_segment(ucid));
-            if (segment_ptr == nullptr) {
-                // find segment from delta column group failed, using main segment
-                segment_ptr = _segment;
-            }
+        RETURN_IF_ERROR(
+                _bitmap_index_evaluator.init([&cid_2_ucid, this](ColumnId cid) -> StatusOr<BitmapIndexIterator*> {
+                    const ColumnUID ucid = cid_2_ucid[cid];
+                    // the column's index in this segment file
+                    ASSIGN_OR_RETURN(std::shared_ptr<Segment> segment_ptr, _get_dcg_segment(ucid));
+                    if (segment_ptr == nullptr) {
+                        // find segment from delta column group failed, using main segment
+                        segment_ptr = _segment;
+                    }
 
-            IndexReadOptions opts;
-            opts.use_page_cache = config::enable_bitmap_index_memory_page_cache || !config::disable_storage_page_cache;
-            opts.kept_in_memory = config::enable_bitmap_index_memory_page_cache;
-            opts.lake_io_opts = _opts.lake_io_opts;
-            opts.read_file = _column_files[cid].get();
-            opts.stats = _opts.stats;
-
-            BitmapIndexIterator* bitmap_iter = nullptr;
-            RETURN_IF_ERROR(segment_ptr->new_bitmap_index_iterator(ucid, opts, &bitmap_iter));
-            return bitmap_iter;
-        }));
+                    IndexReadOptions opts;
+                    opts.use_page_cache = !_opts.temporary_data && (config::enable_bitmap_index_memory_page_cache ||
+                                                                    !config::disable_storage_page_cache);
+                    opts.kept_in_memory = !_opts.temporary_data && config::enable_bitmap_index_memory_page_cache;
+                    opts.lake_io_opts = _opts.lake_io_opts;
+                    opts.read_file = _column_files[cid].get();
+                    opts.stats = _opts.stats;
+
+                    BitmapIndexIterator* bitmap_iter = nullptr;
+                    RETURN_IF_ERROR(segment_ptr->new_bitmap_index_iterator(ucid, opts, &bitmap_iter));
+                    return bitmap_iter;
+                }));
 
         RETURN_IF(!_bitmap_index_evaluator.has_bitmap_index(), Status::OK());
     }
diff --git a/be/src/storage/rowset/segment_options.cpp b/be/src/storage/rowset/segment_options.cpp
index 84c98fdf41804b..fb28c7effacd78 100644
--- a/be/src/storage/rowset/segment_options.cpp
+++ b/be/src/storage/rowset/segment_options.cpp
@@ -63,6 +63,7 @@ Status SegmentReadOptions::convert_to(SegmentReadOptions* dst, const std::vector
     dst->fs = fs;
     dst->stats = stats;
     dst->use_page_cache = use_page_cache;
+    dst->temporary_data = temporary_data;
     dst->profile = profile;
     dst->global_dictmaps = global_dictmaps;
     dst->rowid_range_option = rowid_range_option;
diff --git a/be/src/storage/rowset/segment_options.h b/be/src/storage/rowset/segment_options.h
index 11c93be50c844b..2d8de90c80fab0 100644
--- a/be/src/storage/rowset/segment_options.h
+++ b/be/src/storage/rowset/segment_options.h
@@ -73,6 +73,8 @@ class SegmentReadOptions {
     RuntimeProfile* profile = nullptr;
 
     bool use_page_cache = false;
+    // temporary data does not allow caching
+    bool temporary_data = false;
     LakeIOOptions lake_io_opts{.fill_data_cache = true};
 
     ReaderType reader_type = READER_QUERY;
@@ -81,8 +83,6 @@ class SegmentReadOptions {
     const ColumnIdToGlobalDictMap* global_dictmaps = &EMPTY_GLOBAL_DICTMAPS;
     const std::unordered_set<uint32_t>* unused_output_column_ids = nullptr;
 
-    bool has_delete_pred = false;
-
     /// Mark whether this is the first split of a segment.
     /// A segment may be divided into multiple split to scan concurrently.
     bool is_first_split_of_segment = true;
diff --git a/be/src/storage/rowset/segment_rewriter.cpp b/be/src/storage/rowset/segment_rewriter.cpp
index 47d0df5cbd156f..c352b12edee319 100644
--- a/be/src/storage/rowset/segment_rewriter.cpp
+++ b/be/src/storage/rowset/segment_rewriter.cpp
@@ -129,6 +129,7 @@ Status SegmentRewriter::rewrite_auto_increment(const std::string& src_path, cons
     seg_options.fs = fs;
     seg_options.stats = &stats;
     seg_options.chunk_size = num_rows;
+    seg_options.temporary_data = true;
 
     auto res = rowset->segments()[segment_id]->new_iterator(src_schema, seg_options);
     auto& itr = res.value();
@@ -225,6 +226,7 @@ Status SegmentRewriter::rewrite_auto_increment_lake(
     seg_options.fs = fs;
     seg_options.stats = &stats;
     seg_options.chunk_size = num_rows;
+    seg_options.temporary_data = true;
 
     // Read data from the (partial) segment file generated by this import task
     ASSIGN_OR_RETURN(auto itr, segment->new_iterator(src_schema, seg_options));
@@ -276,40 +278,4 @@ Status SegmentRewriter::rewrite_auto_increment_lake(
     return Status::OK();
 }
 
-Status SegmentRewriter::rewrite(const std::string& src_path, const FileEncryptionInfo& einfo,
-                                const TabletSchemaCSPtr& tschema, std::vector<uint32_t>& column_ids,
-                                std::vector<std::unique_ptr<Column>>& columns, uint32_t segment_id,
-                                const FooterPointerPB& partial_rowset_footer) {
-    ASSIGN_OR_RETURN(auto fs, FileSystem::CreateSharedFromString(src_path));
-    ASSIGN_OR_RETURN(auto read_file,
-                     fs->new_random_access_file(RandomAccessFileOptions{.encryption_info = einfo}, src_path));
-
-    SegmentFooterPB footer;
-    RETURN_IF_ERROR(Segment::parse_segment_footer(read_file.get(), &footer, nullptr, &partial_rowset_footer));
-
-    int64_t trunc_len = partial_rowset_footer.position() + partial_rowset_footer.size();
-    RETURN_IF_ERROR(FileSystemUtil::resize_file(src_path, trunc_len));
-
-    WritableFileOptions fopts{.sync_on_close = true, .mode = FileSystem::MUST_EXIST, .encryption_info = einfo};
-    ASSIGN_OR_RETURN(auto wfile, fs->new_writable_file(fopts, src_path));
-
-    SegmentWriterOptions opts;
-    SegmentWriter writer(std::move(wfile), segment_id, tschema, opts);
-    RETURN_IF_ERROR(writer.init(column_ids, false, &footer));
-
-    auto schema = ChunkHelper::convert_schema(tschema, column_ids);
-    auto chunk = ChunkHelper::new_chunk(schema, columns[0]->size());
-    for (int i = 0; i < columns.size(); ++i) {
-        chunk->get_column_by_index(i).reset(columns[i].release());
-    }
-    uint64_t index_size = 0;
-    uint64_t segment_file_size;
-    RETURN_IF_ERROR(writer.append_chunk(*chunk));
-    RETURN_IF_ERROR(writer.finalize_columns(&index_size));
-    TEST_ERROR_POINT("SegmentRewriter::rewrite4");
-    RETURN_IF_ERROR(writer.finalize_footer(&segment_file_size));
-
-    return Status::OK();
-}
-
 } // namespace starrocks
diff --git a/be/src/storage/rowset/segment_rewriter.h b/be/src/storage/rowset/segment_rewriter.h
index 26ee063640204c..8d02d34355d844 100644
--- a/be/src/storage/rowset/segment_rewriter.h
+++ b/be/src/storage/rowset/segment_rewriter.h
@@ -31,10 +31,6 @@ class SegmentRewriter {
                                          std::vector<uint32_t>& column_ids,
                                          std::vector<std::unique_ptr<Column>>& columns, uint32_t segment_id,
                                          const FooterPointerPB& partial_rowset_footer);
-    // this funciton will append write_column to src_file and rebuild segment footer
-    static Status rewrite(const std::string& src, const FileEncryptionInfo& einfo, const TabletSchemaCSPtr& tschema,
-                          std::vector<uint32_t>& column_ids, std::vector<std::unique_ptr<Column>>& columns,
-                          uint32_t segment_id, const FooterPointerPB& partial_rowseet_footer);
     static Status rewrite_auto_increment(const std::string& src_path, const std::string& dest_path,
                                          const TabletSchemaCSPtr& tschema,
                                          AutoIncrementPartialUpdateState& auto_increment_partial_update_state,
diff --git a/be/src/storage/rowset_column_update_state.cpp b/be/src/storage/rowset_column_update_state.cpp
index 0ce26499e3da8b..b6be164f1d2b77 100644
--- a/be/src/storage/rowset_column_update_state.cpp
+++ b/be/src/storage/rowset_column_update_state.cpp
@@ -300,25 +300,23 @@ Status RowsetColumnUpdateState::_finalize_partial_update_state(Tablet* tablet, R
     return Status::OK();
 }
 
-static int64_t calc_upt_memory_usage_per_row_column(Rowset* rowset) {
-    const auto& txn_meta = rowset->rowset_meta()->get_meta_pb_without_schema().txn_meta();
-    const int64_t total_update_col_cnt = txn_meta.partial_update_column_ids_size();
-    // `num_rows_upt` and `total_update_row_size` could be zero when upgrade from old version,
+int64_t RowsetColumnUpdateState::calc_upt_memory_usage_per_row(Rowset* rowset) {
+    // `num_rows_upt` could be zero after upgrade from old version,
     // then we will return zero and no limit.
-    if ((rowset->num_rows_upt() * total_update_col_cnt) <= 0) return 0;
-    return rowset->total_update_row_size() / (rowset->num_rows_upt() * total_update_col_cnt);
+    if ((rowset->num_rows_upt()) <= 0) return 0;
+    return rowset->total_update_row_size() / rowset->num_rows_upt();
 }
 
 // Read chunk from source segment file and call `update_func` to update it.
 // `update_func` accept ChunkUniquePtr and [start_rowid, end_rowid) range of this chunk.
-static Status read_from_source_segment_and_update(Rowset* rowset, const Schema& schema, Tablet* tablet,
-                                                  OlapReaderStatistics* stats, int64_t version,
-                                                  RowsetSegmentId rowset_seg_id, const std::string& path,
-                                                  const std::function<Status(StreamChunkContainer)>& update_func) {
+static Status read_from_source_segment_and_update(
+        Rowset* rowset, const Schema& schema, Tablet* tablet, OlapReaderStatistics* stats, int64_t version,
+        RowsetSegmentId rowset_seg_id, const std::string& path,
+        const std::function<Status(StreamChunkContainer, bool, int64_t)>& update_func) {
     CHECK_MEM_LIMIT("RowsetColumnUpdateState::read_from_source_segment");
     ASSIGN_OR_RETURN(auto fs, FileSystem::CreateSharedFromString(rowset->rowset_path()));
     // We need to estimate each update rows size before it has been actually updated.
-    const int64_t upt_memory_usage_per_row_column = calc_upt_memory_usage_per_row_column(rowset);
+    const int64_t upt_memory_usage_per_row = RowsetColumnUpdateState::calc_upt_memory_usage_per_row(rowset);
     auto segment = Segment::open(fs, FileInfo{path}, rowset_seg_id.segment_id, rowset->schema());
     if (!segment.ok()) {
         LOG(WARNING) << "Fail to open " << path << ": " << segment.status();
@@ -354,13 +352,16 @@ static Status read_from_source_segment_and_update(Rowset* rowset, const Schema&
             source_chunk_ptr->append(*tmp_chunk_ptr);
             // Avoid too many memory usage and Column overflow, we will limit source chunk's size.
             if (source_chunk_ptr->num_rows() >= INT32_MAX ||
-                (int64_t)source_chunk_ptr->num_rows() * upt_memory_usage_per_row_column * (int64_t)schema.num_fields() >
+                (int64_t)source_chunk_ptr->num_rows() * upt_memory_usage_per_row >
                         config::partial_update_memory_limit_per_worker) {
+                // Because we will handle columns group by group (define by config::vertical_compaction_max_columns_per_group),
+                // so use `upt_memory_usage_per_row` to estimate source chunk future memory cost will be overvalued.
+                // But it's better to be overvalued than undervalued.
                 StreamChunkContainer container = {
                         .chunk_ptr = source_chunk_ptr.get(),
                         .start_rowid = start_rowid,
                         .end_rowid = start_rowid + static_cast<uint32_t>(source_chunk_ptr->num_rows())};
-                RETURN_IF_ERROR(update_func(container));
+                RETURN_IF_ERROR(update_func(container, true /*print log*/, upt_memory_usage_per_row));
                 start_rowid += static_cast<uint32_t>(source_chunk_ptr->num_rows());
                 source_chunk_ptr->reset();
             }
@@ -371,7 +372,7 @@ static Status read_from_source_segment_and_update(Rowset* rowset, const Schema&
                 .chunk_ptr = source_chunk_ptr.get(),
                 .start_rowid = start_rowid,
                 .end_rowid = start_rowid + static_cast<uint32_t>(source_chunk_ptr->num_rows())};
-        RETURN_IF_ERROR(update_func(container));
+        RETURN_IF_ERROR(update_func(container, false /*print log*/, upt_memory_usage_per_row));
         start_rowid += static_cast<uint32_t>(source_chunk_ptr->num_rows());
         source_chunk_ptr->reset();
     }
@@ -759,10 +760,15 @@ Status RowsetColumnUpdateState::finalize(Tablet* tablet, Rowset* rowset, uint32_
                     rowset->rowset_path(), rowsetid_segid.unique_rowset_id, rowsetid_segid.segment_id);
             RETURN_IF_ERROR(read_from_source_segment_and_update(
                     rowset, partial_schema, tablet, &stats, latest_applied_version.major_number(), rowsetid_segid,
-                    seg_path, [&](StreamChunkContainer container) {
-                        VLOG(2) << "RowsetColumnUpdateState read from source segment: [byte usage: "
-                                << container.chunk_ptr->bytes_usage() << " row cnt: " << container.chunk_ptr->num_rows()
-                                << "] row range : [" << container.start_rowid << ", " << container.end_rowid << ")";
+                    seg_path, [&](StreamChunkContainer container, bool print_log, int64_t upt_memory_usage_per_row) {
+                        if (print_log) {
+                            LOG(INFO) << "RowsetColumnUpdateState read from source segment: tablet id:"
+                                      << tablet->tablet_id() << " [byte usage: " << container.chunk_ptr->bytes_usage()
+                                      << " row cnt: " << container.chunk_ptr->num_rows() << "] row range : ["
+                                      << container.start_rowid << ", " << container.end_rowid
+                                      << ") upt_memory_usage_per_row : " << upt_memory_usage_per_row
+                                      << " update column cnt : " << update_column_ids.size();
+                        }
                         const size_t source_chunk_size = container.chunk_ptr->memory_usage();
                         tracker->consume(source_chunk_size);
                         DeferOp tracker_defer([&]() { tracker->release(source_chunk_size); });
diff --git a/be/src/storage/rowset_column_update_state.h b/be/src/storage/rowset_column_update_state.h
index 6bba549141019f..66691e8bdd1c9a 100644
--- a/be/src/storage/rowset_column_update_state.h
+++ b/be/src/storage/rowset_column_update_state.h
@@ -169,6 +169,8 @@ class RowsetColumnUpdateState {
     // For UT test now
     const std::vector<BatchPKsPtr>& upserts() const { return _upserts; }
 
+    static int64_t calc_upt_memory_usage_per_row(Rowset* rowset);
+
 private:
     Status _load_upserts(Rowset* rowset, MemTracker* update_mem_tracker, uint32_t start_idx, uint32_t* end_idx);
 
diff --git a/be/src/storage/schema_change.cpp b/be/src/storage/schema_change.cpp
index 264452d999c230..e0091ca6f496e3 100644
--- a/be/src/storage/schema_change.cpp
+++ b/be/src/storage/schema_change.cpp
@@ -193,7 +193,7 @@ Status HeapChunkMerger::merge(std::vector<ChunkPtr>& chunk_arr, RowsetWriter* ro
     StorageEngine* storage_engine = StorageEngine::instance();
     bool bg_worker_stopped = storage_engine->bg_worker_stopped();
     while (!_heap.empty() && !bg_worker_stopped) {
-        if (tmp_chunk->capacity_limit_reached() || nread >= config::vector_chunk_size) {
+        if (!tmp_chunk->capacity_limit_reached().ok() || nread >= config::vector_chunk_size) {
             if (_tablet->keys_type() == KeysType::AGG_KEYS) {
                 aggregate_chunk(*_aggregator, tmp_chunk, rowset_writer);
             } else {
diff --git a/be/src/storage/segment_replicate_executor.cpp b/be/src/storage/segment_replicate_executor.cpp
index 95315a4ae3883e..5fa276a48454f8 100644
--- a/be/src/storage/segment_replicate_executor.cpp
+++ b/be/src/storage/segment_replicate_executor.cpp
@@ -107,7 +107,7 @@ Status ReplicateChannel::async_segment(SegmentPB* segment, butil::IOBuf& data, b
     _send_request(segment, data, eos);
 
     // 4. wait if eos=true
-    if (eos || _mem_tracker->limit_exceeded()) {
+    if (eos || _mem_tracker->any_limit_exceeded()) {
         RETURN_IF_ERROR(_wait_response(replicate_tablet_infos, failed_tablet_infos));
     }
 
diff --git a/be/src/storage/tablet_schema.cpp b/be/src/storage/tablet_schema.cpp
index 7f02277319cdae..f6fb092476606a 100644
--- a/be/src/storage/tablet_schema.cpp
+++ b/be/src/storage/tablet_schema.cpp
@@ -137,6 +137,9 @@ TabletColumn::TabletColumn(const TabletColumn& rhs)
     if (rhs._extra_fields != nullptr) {
         _extra_fields = new ExtraFields(*rhs._extra_fields);
     }
+    if (rhs._agg_state_desc != nullptr) {
+        _agg_state_desc = new AggStateDesc(*rhs._agg_state_desc);
+    }
 }
 
 TabletColumn::TabletColumn(TabletColumn&& rhs) noexcept
@@ -149,8 +152,10 @@ TabletColumn::TabletColumn(TabletColumn&& rhs) noexcept
           _precision(rhs._precision),
           _scale(rhs._scale),
           _flags(rhs._flags),
-          _extra_fields(rhs._extra_fields) {
+          _extra_fields(rhs._extra_fields),
+          _agg_state_desc(rhs._agg_state_desc) {
     rhs._extra_fields = nullptr;
+    rhs._agg_state_desc = nullptr;
 }
 
 TabletColumn::TabletColumn(const ColumnPB& column) {
@@ -163,6 +168,7 @@ TabletColumn::TabletColumn(const TColumn& column) {
 
 TabletColumn::~TabletColumn() {
     delete _extra_fields;
+    delete _agg_state_desc;
 }
 
 void TabletColumn::swap(TabletColumn* rhs) {
@@ -177,6 +183,7 @@ void TabletColumn::swap(TabletColumn* rhs) {
     swap(_scale, rhs->_scale);
     swap(_flags, rhs->_flags);
     swap(_extra_fields, rhs->_extra_fields);
+    swap(_agg_state_desc, rhs->_agg_state_desc);
 }
 
 TabletColumn& TabletColumn::operator=(const TabletColumn& rhs) {
@@ -243,6 +250,13 @@ void TabletColumn::init_from_pb(const ColumnPB& column) {
         sub_column.init_from_pb(column.children_columns(i));
         add_sub_column(std::move(sub_column));
     }
+    // agg state type info
+    if (column.has_agg_state_desc()) {
+        VLOG(2) << "column contains agg state type info, add into extra fields";
+        auto& agg_state_desc_pb = column.agg_state_desc();
+        auto desc = AggStateDesc::from_protobuf(agg_state_desc_pb);
+        _agg_state_desc = new AggStateDesc(std::move(desc));
+    }
 }
 
 void TabletColumn::init_from_thrift(const TColumn& tcolumn) {
@@ -280,6 +294,11 @@ void TabletColumn::to_schema_pb(ColumnPB* column) const {
     for (int i = 0; i < subcolumn_count(); i++) {
         subcolumn(i).to_schema_pb(column->add_children_columns());
     }
+    if (has_agg_state_desc()) {
+        auto* agg_state_desc = get_agg_state_desc();
+        auto* agg_state_pb = column->mutable_agg_state_desc();
+        agg_state_desc->to_protobuf(agg_state_pb);
+    }
 }
 
 void TabletSchema::append_column(TabletColumn column) {
diff --git a/be/src/storage/tablet_schema.h b/be/src/storage/tablet_schema.h
index 36dda51aa3b718..5e7dec9ec35964 100644
--- a/be/src/storage/tablet_schema.h
+++ b/be/src/storage/tablet_schema.h
@@ -43,6 +43,7 @@
 #include "gen_cpp/Descriptors_types.h"
 #include "gen_cpp/descriptors.pb.h"
 #include "gen_cpp/olap_file.pb.h"
+#include "runtime/agg_state_desc.h"
 #include "storage/aggregate_type.h"
 #include "storage/olap_define.h"
 #include "storage/tablet_index.h"
@@ -159,6 +160,9 @@ class TabletColumn {
         ext->default_value = std::move(value);
     }
 
+    bool has_agg_state_desc() const { return _agg_state_desc != nullptr; }
+    AggStateDesc* get_agg_state_desc() const { return _agg_state_desc; }
+
     void add_sub_column(const TabletColumn& sub_column);
     void add_sub_column(TabletColumn&& sub_column);
     uint32_t subcolumn_count() const { return _extra_fields ? _extra_fields->sub_columns.size() : 0; }
@@ -240,6 +244,7 @@ class TabletColumn {
     uint8_t _flags = 0;
 
     ExtraFields* _extra_fields = nullptr;
+    AggStateDesc* _agg_state_desc = nullptr;
 };
 
 bool operator==(const TabletColumn& a, const TabletColumn& b);
diff --git a/be/src/testutil/deterministic_test_utils.h b/be/src/testutil/deterministic_test_utils.h
index cac134f9b30e16..0b394d5e010178 100644
--- a/be/src/testutil/deterministic_test_utils.h
+++ b/be/src/testutil/deterministic_test_utils.h
@@ -91,12 +91,12 @@ class DeterRandomGenerator {
         }
     }
 
-    void random_cols(int64_t N, vector<int>* v0, vector<int>* v1) {
-        v0->resize(N);
-        v1->resize(N);
-        for (int i = 0; i < N; i++) {
-            (*v0)[i] = (int)random_number();
-            (*v1)[i] = (int)random_number();
+    void random_cols(int64_t N, vector<vector<int>>* cols) {
+        for (auto& each_col : *cols) {
+            each_col.resize(N);
+            for (int i = 0; i < N; i++) {
+                each_col[i] = (int)random_number();
+            }
         }
     }
 
diff --git a/be/src/types/CMakeLists.txt b/be/src/types/CMakeLists.txt
index 191a56b62f1b0b..956737d93a7e3d 100644
--- a/be/src/types/CMakeLists.txt
+++ b/be/src/types/CMakeLists.txt
@@ -19,6 +19,7 @@ add_library(Types STATIC
     bitmap_value.cpp
     date_value.cpp
     hll.cpp
+    hll_sketch.cpp
     logical_type.cpp
     map_type_info.cpp
     struct_type_info.cpp
diff --git a/be/src/types/hll.cpp b/be/src/types/hll.cpp
index ed70eeaf80511b..71da2da3ddd7c8 100644
--- a/be/src/types/hll.cpp
+++ b/be/src/types/hll.cpp
@@ -602,102 +602,4 @@ void HyperLogLog::clear() {
     _hash_set.clear();
 }
 
-DataSketchesHll::DataSketchesHll(const Slice& src) {
-    if (!deserialize(src)) {
-        LOG(WARNING) << "Failed to init DataSketchHll from slice, will be reset to 0.";
-    }
-}
-
-bool DataSketchesHll::is_valid(const Slice& slice) {
-    if (slice.size < 1) {
-        return false;
-    }
-
-    const uint8_t preInts = static_cast<const uint8_t*>((uint8_t*)slice.data)[0];
-    if (preInts == datasketches::hll_constants::HLL_PREINTS ||
-        preInts == datasketches::hll_constants::HASH_SET_PREINTS ||
-        preInts == datasketches::hll_constants::LIST_PREINTS) {
-        return true;
-    } else {
-        return false;
-    }
-}
-
-void DataSketchesHll::update(uint64_t hash_value) {
-    _sketch_union->update(hash_value);
-    this->mark_changed();
-}
-
-void DataSketchesHll::merge(const DataSketchesHll& other) {
-    if (UNLIKELY(_sketch_union == nullptr)) {
-        _sketch_union = std::make_unique<hll_union_type>(other.get_lg_config_k(), alloc_type(&_memory_usage));
-    }
-    auto o_sketch = other.get_hll_sketch();
-    _sketch_union->update(*o_sketch);
-    this->mark_changed();
-}
-
-size_t DataSketchesHll::max_serialized_size() const {
-    if (_sketch_union == nullptr) {
-        return 0;
-    }
-    uint8_t log_k = get_lg_config_k();
-    datasketches::target_hll_type tgt_type = get_target_type();
-    return get_hll_sketch()->get_max_updatable_serialization_bytes(log_k, tgt_type);
-}
-
-size_t DataSketchesHll::serialize_size() const {
-    if (_sketch_union == nullptr) {
-        return 0;
-    }
-    return get_hll_sketch()->get_compact_serialization_bytes();
-}
-
-size_t DataSketchesHll::serialize(uint8_t* dst) const {
-    if (_sketch_union == nullptr) {
-        return 0;
-    }
-    auto serialize_compact = _sketch->serialize_compact();
-    std::copy(serialize_compact.begin(), serialize_compact.end(), dst);
-    return get_hll_sketch()->get_compact_serialization_bytes();
-}
-
-bool DataSketchesHll::deserialize(const Slice& slice) {
-    // can be called only when _sketch_union is empty
-    DCHECK(_sketch_union == nullptr);
-
-    // check if input length is valid
-    if (!is_valid(slice)) {
-        return false;
-    }
-
-    try {
-        auto sketch = std::make_unique<hll_sketch_type>(
-                hll_sketch_type::deserialize((uint8_t*)slice.data, slice.size, alloc_type(&_memory_usage)));
-        _sketch_union = std::make_unique<hll_union_type>(sketch->get_lg_config_k(), alloc_type(&_memory_usage));
-        _sketch_union->update(*sketch);
-        this->mark_changed();
-    } catch (std::logic_error& e) {
-        LOG(WARNING) << "DataSketchesHll deserialize error: " << e.what();
-        return false;
-    }
-
-    return true;
-}
-
-int64_t DataSketchesHll::estimate_cardinality() const {
-    if (_sketch_union == nullptr) {
-        return 0;
-    }
-    return _sketch_union->get_estimate();
-}
-
-std::string DataSketchesHll::to_string() const {
-    if (_sketch_union == nullptr) {
-        return "";
-    }
-    datasketches::string<alloc_type> str = get_hll_sketch()->to_string();
-    return std::string(str.begin(), str.end());
-}
-
 } // namespace starrocks
diff --git a/be/src/types/hll.h b/be/src/types/hll.h
index cd4fd21b277db9..86326bcd97cd87 100644
--- a/be/src/types/hll.h
+++ b/be/src/types/hll.h
@@ -42,9 +42,7 @@
 
 #include "common/compiler_util.h"
 #include "common/logging.h"
-#include "datasketches/hll.hpp"
 #include "gutil/macros.h"
-#include "runtime/memory/counting_allocator.h"
 #include "runtime/memory/mem_chunk.h"
 #include "runtime/memory/mem_chunk_allocator.h"
 #include "types/constexpr.h"
@@ -178,106 +176,4 @@ class HyperLogLog {
     }
 };
 
-class DataSketchesHll {
-public:
-    using alloc_type = STLCountingAllocator<uint8_t>;
-    using hll_sketch_type = datasketches::hll_sketch_alloc<alloc_type>;
-    using hll_union_type = datasketches::hll_union_alloc<alloc_type>;
-    // default lg_k value for HLL
-    static const datasketches::target_hll_type DEFAULT_HLL_TGT_TYPE = datasketches::HLL_6;
-
-    explicit DataSketchesHll(uint8_t log_k, datasketches::target_hll_type tgt_type) : _tgt_type(tgt_type) {
-        this->_sketch_union = std::make_unique<hll_union_type>(log_k, alloc_type(&_memory_usage));
-    }
-
-    DataSketchesHll(const DataSketchesHll& other) = delete;
-    DataSketchesHll& operator=(const DataSketchesHll& other) = delete;
-
-    DataSketchesHll(DataSketchesHll&& other) noexcept
-            : _memory_usage(other._memory_usage),
-              _sketch_union(std::move(other._sketch_union)),
-              _tgt_type(other._tgt_type) {}
-    DataSketchesHll& operator=(DataSketchesHll&& other) noexcept {
-        if (this != &other) {
-            this->_memory_usage = other._memory_usage;
-            this->_sketch_union = std::move(other._sketch_union);
-            this->_tgt_type = other._tgt_type;
-        }
-        return *this;
-    }
-
-    explicit DataSketchesHll(const Slice& src);
-
-    ~DataSketchesHll() = default;
-
-    // Returns sketch's configured lg_k value.
-    uint8_t get_lg_config_k() const {
-        if (UNLIKELY(_sketch_union == nullptr)) {
-            return DEFAULT_HLL_LOG_K;
-        }
-        return _sketch_union->get_lg_config_k();
-    }
-
-    // Returns the sketch's target HLL mode (from #target_hll_type).
-    datasketches::target_hll_type get_target_type() const {
-        if (UNLIKELY(_sketch_union == nullptr)) {
-            return DEFAULT_HLL_TGT_TYPE;
-        }
-        return _sketch_union->get_target_type();
-    }
-
-    // Add a hash value to this HLL value
-    // NOTE: input must be a hash_value
-    void update(uint64_t hash_value);
-
-    // merge with other HLL value
-    void merge(const DataSketchesHll& other);
-
-    // Return max size of serialized binary
-    size_t max_serialized_size() const;
-    int64_t mem_usage() const { return _memory_usage; }
-
-    // Input slice should have enough capacity for serialize, which
-    // can be got through max_serialized_size(). If insufficient buffer
-    // is given, this will cause process crash.
-    // Return actual size of serialized binary.
-    size_t serialize(uint8_t* dst) const;
-
-    // Now, only empty HLL support this funciton.
-    bool deserialize(const Slice& slice);
-
-    int64_t estimate_cardinality() const;
-
-    // No need to check is_valid for datasketches HLL,
-    // return ture for compatibility.
-    static bool is_valid(const Slice& slice);
-
-    // only for debug
-    std::string to_string() const;
-
-    uint64_t serialize_size() const;
-
-    // common interface
-    void clear() { _sketch_union->reset(); }
-
-    // get hll_sketch object which is lazy initialized
-    hll_sketch_type* get_hll_sketch() const {
-        if (_is_changed) {
-            _sketch = std::make_unique<hll_sketch_type>(_sketch_union->get_result(_tgt_type));
-            _is_changed = false;
-        }
-        return _sketch.get();
-    }
-
-    inline void mark_changed() { _is_changed = true; }
-
-private:
-    int64_t _memory_usage = 0;
-    std::unique_ptr<hll_union_type> _sketch_union = nullptr;
-    datasketches::target_hll_type _tgt_type = DEFAULT_HLL_TGT_TYPE;
-    // lazy value of union state
-    mutable std::unique_ptr<hll_sketch_type> _sketch = nullptr;
-    mutable bool _is_changed = true;
-};
-
 } // namespace starrocks
diff --git a/be/src/types/hll_sketch.cpp b/be/src/types/hll_sketch.cpp
new file mode 100644
index 00000000000000..016bc3b82e7bd5
--- /dev/null
+++ b/be/src/types/hll_sketch.cpp
@@ -0,0 +1,124 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#include "types/hll_sketch.h"
+
+#include "common/logging.h"
+#include "runtime/mem_pool.h"
+#include "runtime/string_value.h"
+
+namespace starrocks {
+
+DataSketchesHll::DataSketchesHll(const Slice& src, int64_t* memory_usage) : _memory_usage(memory_usage) {
+    if (!deserialize(src)) {
+        LOG(WARNING) << "Failed to init DataSketchHll from slice, will be reset to 0.";
+    }
+}
+
+bool DataSketchesHll::is_valid(const Slice& slice) {
+    if (slice.size < 1) {
+        return false;
+    }
+
+    const uint8_t preInts = static_cast<const uint8_t*>((uint8_t*)slice.data)[0];
+    if (preInts == datasketches::hll_constants::HLL_PREINTS ||
+        preInts == datasketches::hll_constants::HASH_SET_PREINTS ||
+        preInts == datasketches::hll_constants::LIST_PREINTS) {
+        return true;
+    } else {
+        return false;
+    }
+}
+
+void DataSketchesHll::update(uint64_t hash_value) {
+    _sketch_union->update(hash_value);
+    this->mark_changed();
+}
+
+void DataSketchesHll::merge(const DataSketchesHll& other) {
+    if (UNLIKELY(_sketch_union == nullptr)) {
+        _sketch_union = std::make_unique<hll_union_type>(other.get_lg_config_k(), alloc_type(_memory_usage));
+    }
+    auto o_sketch = other.get_hll_sketch();
+    _sketch_union->update(*o_sketch);
+    this->mark_changed();
+}
+
+size_t DataSketchesHll::max_serialized_size() const {
+    if (_sketch_union == nullptr) {
+        return 0;
+    }
+    uint8_t log_k = get_lg_config_k();
+    datasketches::target_hll_type tgt_type = get_target_type();
+    return get_hll_sketch()->get_max_updatable_serialization_bytes(log_k, tgt_type);
+}
+
+size_t DataSketchesHll::serialize_size() const {
+    if (_sketch_union == nullptr) {
+        return 0;
+    }
+    return get_hll_sketch()->get_compact_serialization_bytes();
+}
+
+size_t DataSketchesHll::serialize(uint8_t* dst) const {
+    if (_sketch_union == nullptr) {
+        return 0;
+    }
+    auto serialize_compact = _sketch->serialize_compact();
+    std::copy(serialize_compact.begin(), serialize_compact.end(), dst);
+    return get_hll_sketch()->get_compact_serialization_bytes();
+}
+
+bool DataSketchesHll::deserialize(const Slice& slice) {
+    // can be called only when _sketch_union is empty
+    DCHECK(_sketch_union == nullptr);
+
+    // check if input length is valid
+    if (!is_valid(slice)) {
+        return false;
+    }
+
+    try {
+        auto sketch = std::make_unique<hll_sketch_type>(
+                hll_sketch_type::deserialize((uint8_t*)slice.data, slice.size, alloc_type(_memory_usage)));
+        _sketch_union = std::make_unique<hll_union_type>(sketch->get_lg_config_k(), alloc_type(_memory_usage));
+        _sketch_union->update(*sketch);
+        this->mark_changed();
+    } catch (std::logic_error& e) {
+        LOG(WARNING) << "DataSketchesHll deserialize error: " << e.what();
+        return false;
+    }
+
+    return true;
+}
+
+int64_t DataSketchesHll::estimate_cardinality() const {
+    if (_sketch_union == nullptr) {
+        return 0;
+    }
+    return _sketch_union->get_estimate();
+}
+
+std::string DataSketchesHll::to_string() const {
+    if (_sketch_union == nullptr) {
+        return "";
+    }
+    datasketches::string<alloc_type> str = get_hll_sketch()->to_string();
+    return std::string(str.begin(), str.end());
+}
+
+} // namespace starrocks
diff --git a/be/src/types/hll_sketch.h b/be/src/types/hll_sketch.h
new file mode 100644
index 00000000000000..b4db90268f7d73
--- /dev/null
+++ b/be/src/types/hll_sketch.h
@@ -0,0 +1,143 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#pragma once
+
+#include <memory>
+#include <string>
+
+#include "datasketches/hll.hpp"
+#include "runtime/memory/counting_allocator.h"
+#include "runtime/memory/mem_chunk.h"
+#include "runtime/memory/mem_chunk_allocator.h"
+
+namespace starrocks {
+
+class Slice;
+
+class DataSketchesHll {
+public:
+    using alloc_type = STLCountingAllocator<uint8_t>;
+    using hll_sketch_type = datasketches::hll_sketch_alloc<alloc_type>;
+    using hll_union_type = datasketches::hll_union_alloc<alloc_type>;
+    // default lg_k value for HLL
+    static const datasketches::target_hll_type DEFAULT_HLL_TGT_TYPE = datasketches::HLL_6;
+
+    explicit DataSketchesHll(uint8_t log_k, datasketches::target_hll_type tgt_type, int64_t* memory_usage)
+            : _memory_usage(memory_usage), _tgt_type(tgt_type) {
+        this->_sketch_union = std::make_unique<hll_union_type>(log_k, alloc_type(_memory_usage));
+    }
+
+    DataSketchesHll(const DataSketchesHll& other) = delete;
+    DataSketchesHll& operator=(const DataSketchesHll& other) = delete;
+
+    DataSketchesHll(DataSketchesHll&& other) noexcept
+            : _memory_usage(std::move(other._memory_usage)),
+              _sketch_union(std::move(other._sketch_union)),
+              _tgt_type(other._tgt_type) {}
+    DataSketchesHll& operator=(DataSketchesHll&& other) noexcept {
+        if (this != &other) {
+            this->_memory_usage = std::move(other._memory_usage);
+            this->_sketch_union = std::move(other._sketch_union);
+            this->_tgt_type = other._tgt_type;
+        }
+        return *this;
+    }
+
+    explicit DataSketchesHll(const Slice& src, int64_t* memory_usage);
+
+    ~DataSketchesHll() = default;
+
+    // Returns sketch's configured lg_k value.
+    uint8_t get_lg_config_k() const {
+        if (UNLIKELY(_sketch_union == nullptr)) {
+            return DEFAULT_HLL_LOG_K;
+        }
+        return _sketch_union->get_lg_config_k();
+    }
+
+    // Returns the sketch's target HLL mode (from #target_hll_type).
+    datasketches::target_hll_type get_target_type() const {
+        if (UNLIKELY(_sketch_union == nullptr)) {
+            return DEFAULT_HLL_TGT_TYPE;
+        }
+        return _sketch_union->get_target_type();
+    }
+
+    // Add a hash value to this HLL value
+    // NOTE: input must be a hash_value
+    void update(uint64_t hash_value);
+
+    // merge with other HLL value
+    void merge(const DataSketchesHll& other);
+
+    // Return max size of serialized binary
+    size_t max_serialized_size() const;
+    int64_t mem_usage() const { return _memory_usage == nullptr ? 0L : *_memory_usage; }
+
+    // Input slice should have enough capacity for serialize, which
+    // can be got through max_serialized_size(). If insufficient buffer
+    // is given, this will cause process crash.
+    // Return actual size of serialized binary.
+    size_t serialize(uint8_t* dst) const;
+
+    // Now, only empty HLL support this funciton.
+    bool deserialize(const Slice& slice);
+
+    int64_t estimate_cardinality() const;
+
+    // No need to check is_valid for datasketches HLL,
+    // return ture for compatibility.
+    static bool is_valid(const Slice& slice);
+
+    // only for debug
+    std::string to_string() const;
+
+    uint64_t serialize_size() const;
+
+    // common interface
+    void clear() {
+        if (_sketch_union != nullptr) {
+            _sketch_union->reset();
+            _is_changed = true; // Mark as changed after reset
+        }
+    }
+
+    // get hll_sketch object which is lazy initialized
+    hll_sketch_type* get_hll_sketch() const {
+        if (_is_changed) {
+            if (_sketch_union == nullptr) {
+                return nullptr;
+            }
+            _sketch = std::make_unique<hll_sketch_type>(_sketch_union->get_result(_tgt_type));
+            _is_changed = false;
+        }
+        return _sketch.get();
+    }
+
+    inline void mark_changed() { _is_changed = true; }
+
+private:
+    int64_t* _memory_usage;
+    std::unique_ptr<hll_union_type> _sketch_union = nullptr;
+    datasketches::target_hll_type _tgt_type = DEFAULT_HLL_TGT_TYPE;
+    // lazy value of union state
+    mutable std::unique_ptr<hll_sketch_type> _sketch = nullptr;
+    mutable bool _is_changed = true;
+};
+
+} // namespace starrocks
diff --git a/be/src/udf/java/java_data_converter.cpp b/be/src/udf/java/java_data_converter.cpp
index b4030e60ed6498..d6a4ef4fb41ea3 100644
--- a/be/src/udf/java/java_data_converter.cpp
+++ b/be/src/udf/java/java_data_converter.cpp
@@ -21,6 +21,8 @@
 #include "column/type_traits.h"
 #include "common/compiler_util.h"
 #include "common/status.h"
+#include "udf/java/java_udf.h"
+#include "util/defer_op.h"
 
 #define APPLY_FOR_NUMBERIC_TYPE(M) \
     M(TYPE_BOOLEAN)                \
@@ -161,7 +163,8 @@ void assign_jvalue(MethodTypeDescriptor method_type_desc, Column* col, int row_n
         if (val.l == nullptr) {
             col->append_nulls(1);
         } else {
-            auto slice = helper.sliceVal((jstring)val.l);
+            std::string buffer;
+            auto slice = helper.sliceVal((jstring)val.l, &buffer);
             col->append_datum(Datum(slice));
         }
         break;
@@ -209,7 +212,8 @@ void append_jvalue(MethodTypeDescriptor method_type_desc, Column* col, jvalue va
             APPEND_BOX_TYPE(TYPE_DOUBLE, double)
 
         case TYPE_VARCHAR: {
-            auto slice = helper.sliceVal((jstring)val.l);
+            std::string buffer;
+            auto slice = helper.sliceVal((jstring)val.l, &buffer);
             col->append_datum(Datum(slice));
             break;
         }
@@ -220,6 +224,50 @@ void append_jvalue(MethodTypeDescriptor method_type_desc, Column* col, jvalue va
     }
 }
 
+Status check_type_matched(MethodTypeDescriptor method_type_desc, jobject val) {
+    if (val == nullptr) {
+        return Status::OK();
+    }
+    auto& helper = JVMFunctionHelper::getInstance();
+    auto* env = helper.getEnv();
+
+    switch (method_type_desc.type) {
+#define INSTANCE_OF_TYPE(NAME, TYPE)                                                            \
+    case NAME: {                                                                                \
+        if (!env->IsInstanceOf(val, helper.TYPE##_class())) {                                   \
+            auto clazz = env->GetObjectClass(val);                                              \
+            LOCAL_REF_GUARD(clazz);                                                             \
+            return Status::InternalError(fmt::format("Type not matched, expect {}, but got {}", \
+                                                     helper.to_string(helper.TYPE##_class()),   \
+                                                     helper.to_string(clazz)));                 \
+        }                                                                                       \
+        break;                                                                                  \
+    }
+        INSTANCE_OF_TYPE(TYPE_BOOLEAN, uint8_t)
+        INSTANCE_OF_TYPE(TYPE_TINYINT, int8_t)
+        INSTANCE_OF_TYPE(TYPE_SMALLINT, int16_t)
+        INSTANCE_OF_TYPE(TYPE_INT, int32_t)
+        INSTANCE_OF_TYPE(TYPE_BIGINT, int64_t)
+        INSTANCE_OF_TYPE(TYPE_FLOAT, float)
+        INSTANCE_OF_TYPE(TYPE_DOUBLE, double)
+    case TYPE_VARCHAR: {
+        std::string buffer;
+        if (!env->IsInstanceOf(val, helper.string_clazz())) {
+            auto clazz = env->GetObjectClass(val);
+            LOCAL_REF_GUARD(clazz);
+            return Status::InternalError(
+                    fmt::format("Type not matched, expect string, but got {}", helper.to_string(clazz)));
+        }
+        break;
+    }
+    default:
+        DCHECK(false) << "unsupport UDF TYPE" << method_type_desc.type;
+        break;
+    }
+
+    return Status::OK();
+}
+
 Status ConvertDirectBufferVistor::do_visit(const NullableColumn& column) {
     const auto& null_data = column.immutable_null_column_data();
     _buffers.emplace_back((void*)null_data.data(), null_data.size());
diff --git a/be/src/udf/java/java_data_converter.h b/be/src/udf/java/java_data_converter.h
index a54818f096e754..e94f45d3189520 100644
--- a/be/src/udf/java/java_data_converter.h
+++ b/be/src/udf/java/java_data_converter.h
@@ -63,4 +63,5 @@ template <bool handle_null>
 jvalue cast_to_jvalue(LogicalType type, bool is_boxed, const Column* col, int row_num);
 void release_jvalue(bool is_boxed, jvalue val);
 void append_jvalue(MethodTypeDescriptor method_type_desc, Column* col, jvalue val);
+Status check_type_matched(MethodTypeDescriptor method_type_desc, jobject val);
 } // namespace starrocks
diff --git a/be/src/udf/java/java_udf.cpp b/be/src/udf/java/java_udf.cpp
index 77c9270b0dbaa7..be918425ebd126 100644
--- a/be/src/udf/java/java_udf.cpp
+++ b/be/src/udf/java/java_udf.cpp
@@ -417,10 +417,6 @@ Slice JVMFunctionHelper::sliceVal(jstring jstr, std::string* buffer) {
     return {buffer->data(), buffer->length()};
 }
 
-Slice JVMFunctionHelper::sliceVal(jstring jstr) {
-    return {_env->GetStringUTFChars(jstr, nullptr)};
-}
-
 std::string JVMFunctionHelper::to_jni_class_name(const std::string& name) {
     std::string jni_class_name;
     auto inserter = std::inserter(jni_class_name, jni_class_name.end());
diff --git a/be/src/udf/java/java_udf.h b/be/src/udf/java/java_udf.h
index cda2ebd47bf691..078b3ad423b310 100644
--- a/be/src/udf/java/java_udf.h
+++ b/be/src/udf/java/java_udf.h
@@ -37,9 +37,10 @@ extern "C" JNIEnv* getJNIEnv(void);
     jmethodID _value_of_##TYPE;     \
     jmethodID _val_##TYPE;
 
-#define DECLARE_NEW_BOX(TYPE, CLAZZ) \
-    jobject new##CLAZZ(TYPE value);  \
-    TYPE val##TYPE(jobject obj);
+#define DECLARE_NEW_BOX(PRIM_CLAZZ, TYPE, CLAZZ) \
+    jobject new##CLAZZ(TYPE value);              \
+    TYPE val##TYPE(jobject obj);                 \
+    jclass TYPE##_class() { return _class_##PRIM_CLAZZ; }
 
 namespace starrocks {
 class DirectByteBuffer;
@@ -59,6 +60,7 @@ class JVMFunctionHelper {
     // Arrays.toString()
     std::string array_to_string(jobject object);
     // Object::toString()
+    bool equals(jobject obj1, jobject obj2);
     std::string to_string(jobject obj);
     std::string to_cxx_string(jstring str);
     std::string dumpExceptionString(jthrowable throwable);
@@ -117,19 +119,19 @@ class JVMFunctionHelper {
     jobject list_get(jobject obj, int idx);
     int list_size(jobject obj);
 
-    DECLARE_NEW_BOX(uint8_t, Boolean)
-    DECLARE_NEW_BOX(int8_t, Byte)
-    DECLARE_NEW_BOX(int16_t, Short)
-    DECLARE_NEW_BOX(int32_t, Integer)
-    DECLARE_NEW_BOX(int64_t, Long)
-    DECLARE_NEW_BOX(float, Float)
-    DECLARE_NEW_BOX(double, Double)
+    DECLARE_NEW_BOX(boolean, uint8_t, Boolean)
+    DECLARE_NEW_BOX(byte, int8_t, Byte)
+    DECLARE_NEW_BOX(short, int16_t, Short)
+    DECLARE_NEW_BOX(int, int32_t, Integer)
+    DECLARE_NEW_BOX(long, int64_t, Long)
+    DECLARE_NEW_BOX(float, float, Float)
+    DECLARE_NEW_BOX(double, double, Double)
 
     jobject newString(const char* data, size_t size);
-
-    Slice sliceVal(jstring jstr);
     size_t string_length(jstring jstr);
+
     Slice sliceVal(jstring jstr, std::string* buffer);
+    jclass string_clazz() { return _string_class; }
     // replace '.' as '/'
     // eg: java.lang.Integer -> java/lang/Integer
     static std::string to_jni_class_name(const std::string& name);
diff --git a/be/src/util/cpu_info.h b/be/src/util/cpu_info.h
index 695c26c1576740..9585d69cf3de45 100644
--- a/be/src/util/cpu_info.h
+++ b/be/src/util/cpu_info.h
@@ -82,6 +82,18 @@ class CpuInfo {
 
     static std::string debug_string();
 
+    static const std::vector<long>& get_cache_sizes() {
+        static std::vector<long> cache_sizes;
+        static std::vector<long> cache_line_sizes;
+
+        if (cache_sizes.empty()) {
+            cache_sizes.resize(NUM_CACHE_LEVELS);
+            cache_line_sizes.resize(NUM_CACHE_LEVELS);
+            _get_cache_info(cache_sizes.data(), cache_line_sizes.data());
+        }
+        return cache_sizes;
+    }
+
 private:
     /// Initialize NUMA-related state - called from Init();
     static void _init_numa();
diff --git a/be/src/util/json_flattener.cpp b/be/src/util/json_flattener.cpp
index 18576899a19834..f866af518da494 100644
--- a/be/src/util/json_flattener.cpp
+++ b/be/src/util/json_flattener.cpp
@@ -505,13 +505,20 @@ void JsonPathDeriver::_finalize() {
 
     // sort by name, just for stable order
     size_t limit = config::json_flat_column_max > 0 ? config::json_flat_column_max : std::numeric_limits<size_t>::max();
+    std::sort(hit_leaf.begin(), hit_leaf.end(), [&](const auto& a, const auto& b) {
+        auto desc_a = _derived_maps[a.first];
+        auto desc_b = _derived_maps[b.first];
+        return desc_a.hits > desc_b.hits;
+    });
+    for (size_t i = limit; i < hit_leaf.size(); i++) {
+        hit_leaf[i].first->remain = true;
+    }
+    if (hit_leaf.size() > limit) {
+        _has_remain |= true;
+        hit_leaf.resize(limit);
+    }
     std::sort(hit_leaf.begin(), hit_leaf.end(), [](const auto& a, const auto& b) { return a.second < b.second; });
     for (auto& [node, path] : hit_leaf) {
-        if (_paths.size() >= limit) {
-            node->remain = true;
-            _has_remain |= true;
-            continue;
-        }
         node->index = _paths.size();
         _paths.emplace_back(path.substr(1));
         _types.emplace_back(node->type);
diff --git a/be/src/util/thrift_server.cpp b/be/src/util/thrift_server.cpp
index d7c6b6bfa53a4e..61cd8c28964436 100644
--- a/be/src/util/thrift_server.cpp
+++ b/be/src/util/thrift_server.cpp
@@ -355,6 +355,7 @@ Status ThriftServer::start() {
                 BackendOptions::get_service_bind_address_without_bracket(), _port);
         //      server_socket->setAcceptTimeout(500);
         fe_server_transport.reset(server_socket);
+        server_socket->setKeepAlive(true);
 
         if (transport_factory == nullptr) {
             transport_factory.reset(new apache::thrift::transport::TBufferedTransportFactory());
diff --git a/be/test/CMakeLists.txt b/be/test/CMakeLists.txt
index b0a78d0ef3e3c0..37da4963a205fb 100644
--- a/be/test/CMakeLists.txt
+++ b/be/test/CMakeLists.txt
@@ -351,6 +351,7 @@ set(EXEC_FILES
         ./storage/persistent_index_consistency_test.cpp
         ./storage/meta_reader_test.cpp
         ./storage/dictionary_cache_manager_test.cpp
+        ./runtime/agg_state_desc_test.cpp
         ./runtime/buffer_control_block_test.cpp
         ./runtime/data_stream_mgr_test.cpp
         ./runtime/datetime_value_test.cpp
diff --git a/be/test/column/field_test.cpp b/be/test/column/field_test.cpp
index 669deadd913b58..d09f96162f0287 100644
--- a/be/test/column/field_test.cpp
+++ b/be/test/column/field_test.cpp
@@ -16,6 +16,8 @@
 
 #include <gtest/gtest.h>
 
+#include "exprs/anyval_util.h"
+#include "runtime/agg_state_desc.h"
 #include "storage/aggregate_type.h"
 
 namespace starrocks {
@@ -161,4 +163,48 @@ TEST(FieldTest, test_with_nullable) {
     ASSERT_EQ(10, field2->short_key_length());
 }
 
+TEST(FieldTest, test_with_agg_state_desc) {
+    std::vector<TypeDescriptor> arg_types = {TypeDescriptor::from_logical_type(TYPE_SMALLINT)};
+    auto return_type = AnyValUtil::column_type_to_type_desc(TypeDescriptor::from_logical_type(TYPE_DOUBLE));
+    AggStateDesc desc("avg", return_type, arg_types, true, 1);
+
+    // copy assignment
+    {
+        Field field1(1, "c1", get_type_info(TYPE_DOUBLE), STORAGE_AGGREGATE_AGG_STATE_UNION, &desc, 10, true, true);
+        ASSERT_TRUE(field1.get_agg_state_desc() != nullptr);
+
+        auto field2 = field1;
+        ASSERT_TRUE(field2.get_agg_state_desc() != nullptr);
+    }
+
+    // move assignment
+    {
+        auto field1 = std::make_shared<Field>(1, "c1", get_type_info(TYPE_DOUBLE), STORAGE_AGGREGATE_AGG_STATE_UNION,
+                                              &desc, 10, true, true);
+        ASSERT_EQ(1, field1->id());
+
+        auto field2 = std::move(field1);
+        ASSERT_TRUE(field2->get_agg_state_desc() != nullptr);
+    }
+
+    // with_name
+    {
+        auto field1 = std::make_shared<Field>(1, "c1", get_type_info(TYPE_DOUBLE), STORAGE_AGGREGATE_AGG_STATE_UNION,
+                                              &desc, 10, true, true);
+        ASSERT_EQ(1, field1->id());
+        ASSERT_TRUE(field1->get_agg_state_desc() != nullptr);
+        FieldPtr field2 = field1->with_name("c2");
+        ASSERT_TRUE(field2->get_agg_state_desc() != nullptr);
+    }
+    // with_nullable
+    {
+        auto field1 = std::make_shared<Field>(1, "c1", get_type_info(TYPE_DOUBLE), STORAGE_AGGREGATE_AGG_STATE_UNION,
+                                              &desc, 10, true, true);
+        ASSERT_EQ(1, field1->id());
+        ASSERT_TRUE(field1->get_agg_state_desc() != nullptr);
+        FieldPtr field2 = field1->with_nullable(false);
+        ASSERT_TRUE(field2->get_agg_state_desc() != nullptr);
+    }
+}
+
 } // namespace starrocks
diff --git a/be/test/exec/parquet_scanner_test.cpp b/be/test/exec/parquet_scanner_test.cpp
index c5a8ff2d29f479..15b192c123251b 100644
--- a/be/test/exec/parquet_scanner_test.cpp
+++ b/be/test/exec/parquet_scanner_test.cpp
@@ -701,16 +701,26 @@ TEST_F(ParquetScannerTest, get_file_schema) {
               {"col_json_map_timestamp",
                TypeDescriptor::create_map_type(TypeDescriptor::from_logical_type(TYPE_DATETIME),
                                                TypeDescriptor::from_logical_type(TYPE_INT))},
-              {"col_json_struct", TypeDescriptor::create_varchar_type(1048576)},
+              {"col_json_struct",
+               TypeDescriptor::create_struct_type({"s0", "s1"}, {TypeDescriptor::from_logical_type(TYPE_INT),
+                                                                 TypeDescriptor::create_varchar_type(1048576)})},
               {"col_json_list_list", TypeDescriptor::create_array_type(TypeDescriptor::create_array_type(
                                              TypeDescriptor::from_logical_type(TYPE_INT)))},
               {"col_json_map_list",
                TypeDescriptor::create_map_type(
                        TypeDescriptor::create_varchar_type(1048576),
                        TypeDescriptor::create_array_type(TypeDescriptor::from_logical_type(TYPE_INT)))},
-              {"col_json_list_struct", TypeDescriptor::create_array_type(TypeDescriptor::create_varchar_type(1048576))},
-              {"col_json_struct_struct", TypeDescriptor::create_varchar_type(1048576)},
-              {"col_json_struct_string", TypeDescriptor::create_varchar_type(1048576)},
+              {"col_json_list_struct", TypeDescriptor::create_array_type(TypeDescriptor::create_struct_type(
+                                               {"s0", "s1"}, {TypeDescriptor::from_logical_type(TYPE_INT),
+                                                              TypeDescriptor::create_varchar_type(1048576)}))},
+              {"col_json_struct_struct",
+               TypeDescriptor::create_struct_type(
+                       {"s0", "s1"},
+                       {TypeDescriptor::from_logical_type(TYPE_INT),
+                        TypeDescriptor::create_struct_type({"s2"}, {TypeDescriptor::from_logical_type(TYPE_INT)})})},
+              {"col_json_struct_string",
+               TypeDescriptor::create_struct_type({"s0", "s1"}, {TypeDescriptor::from_logical_type(TYPE_INT),
+                                                                 TypeDescriptor::create_varchar_type(1048576)})},
               {"col_json_json_string", TypeDescriptor::create_varchar_type(1048576)}}},
             {test_exec_dir + "/test_data/parquet_data/decimal.parquet",
              {{"col_decimal32", TypeDescriptor::create_decimalv3_type(TYPE_DECIMAL32, 9, 2)},
diff --git a/be/test/exprs/agg/aggregate_test.cpp b/be/test/exprs/agg/aggregate_test.cpp
index e02ca316a24bbe..9cbb3242539b75 100644
--- a/be/test/exprs/agg/aggregate_test.cpp
+++ b/be/test/exprs/agg/aggregate_test.cpp
@@ -2682,4 +2682,29 @@ TEST_F(AggregateTest, test_array_agg_nullable_distinct) {
     ASSERT_EQ(26, offsets->get_data().back());
 }
 
+TEST_F(AggregateTest, test_get_aggregate_function_by_type) {
+    {
+        std::vector<TypeDescriptor> arg_types = {
+                AnyValUtil::column_type_to_type_desc(TypeDescriptor::from_logical_type(TYPE_VARCHAR)),
+                AnyValUtil::column_type_to_type_desc(TypeDescriptor::from_logical_type(TYPE_INT))};
+        auto return_type = AnyValUtil::column_type_to_type_desc(TypeDescriptor::from_logical_type(TYPE_ARRAY));
+        auto* array_agg_func =
+                get_aggregate_function("array_agg2", return_type, arg_types, true, TFunctionBinaryType::BUILTIN);
+        ASSERT_TRUE(array_agg_func != nullptr);
+    }
+    {
+        std::vector<TypeDescriptor> arg_types = {TypeDescriptor::from_logical_type(TYPE_VARCHAR)};
+        auto return_type = AnyValUtil::column_type_to_type_desc(TypeDescriptor::from_logical_type(TYPE_VARCHAR));
+        auto* agg_func =
+                get_aggregate_function("group_concat", return_type, arg_types, true, TFunctionBinaryType::BUILTIN);
+        ASSERT_TRUE(agg_func != nullptr);
+    }
+    {
+        std::vector<TypeDescriptor> arg_types = {TypeDescriptor::from_logical_type(TYPE_SMALLINT)};
+        auto return_type = AnyValUtil::column_type_to_type_desc(TypeDescriptor::from_logical_type(TYPE_DOUBLE));
+        auto* agg_func = get_aggregate_function("avg", return_type, arg_types, true, TFunctionBinaryType::BUILTIN);
+        ASSERT_TRUE(agg_func != nullptr);
+    }
+}
+
 } // namespace starrocks
diff --git a/be/test/exprs/subfield_expr_test.cpp b/be/test/exprs/subfield_expr_test.cpp
index bf59811bf1c429..933e1b1600f6b9 100644
--- a/be/test/exprs/subfield_expr_test.cpp
+++ b/be/test/exprs/subfield_expr_test.cpp
@@ -233,11 +233,10 @@ TEST_F(SubfieldExprTest, subfield_multi_level_test) {
     expr->add_child(new_fake_const_expr(column, struct_type));
     auto result = expr->evaluate(nullptr, nullptr);
     EXPECT_TRUE(result->is_nullable());
-    auto subfield_column = ColumnHelper::get_data_column(result.get());
-    EXPECT_EQ(3, subfield_column->size());
-    EXPECT_EQ("'smith'", subfield_column->debug_item(0));
-    EXPECT_EQ("''", subfield_column->debug_item(1));
-    EXPECT_EQ("'cruise'", subfield_column->debug_item(2));
+    EXPECT_EQ(3, result->size());
+    EXPECT_EQ("'smith'", result->debug_item(0));
+    EXPECT_EQ("NULL", result->debug_item(1));
+    EXPECT_EQ("'cruise'", result->debug_item(2));
 }
 
 } // namespace starrocks
\ No newline at end of file
diff --git a/be/test/formats/disk_range_test.cpp b/be/test/formats/disk_range_test.cpp
index d511cdb2bc54f2..20fcaec53b371c 100644
--- a/be/test/formats/disk_range_test.cpp
+++ b/be/test/formats/disk_range_test.cpp
@@ -41,6 +41,33 @@ TEST(DiskRangeTest, TestMergeTinyDiskRanges) {
     EXPECT_EQ(900 * KB, merged_disk_ranges.at(0).length());
 }
 
+// unordered DiskRange + DiskRange's length = 0 + duplicate DiskRange + Overlap DiskRange
+TEST(DiskRangeTest, TestDiskRangesRobust) {
+    std::vector<DiskRange> disk_ranges{};
+    constexpr int64_t KB = 1024;
+    // unordered
+    disk_ranges.emplace_back(800 * KB, 100 * KB);
+    // duplicate
+    disk_ranges.emplace_back(0, 1 * KB);
+    disk_ranges.emplace_back(0, 1 * KB);
+    disk_ranges.emplace_back(0, 1 * KB);
+    // overlap
+    disk_ranges.emplace_back(10 * KB, 30 * KB);
+    disk_ranges.emplace_back(15 * KB, 45 * KB);
+    disk_ranges.emplace_back(850 * KB, 150 * KB);
+    // length = 0 + duplicate
+    disk_ranges.emplace_back(40 * KB, 0 * KB);
+    disk_ranges.emplace_back(900 * KB, 0 * KB);
+    disk_ranges.emplace_back(900 * KB, 0 * KB);
+    disk_ranges.emplace_back(900 * KB, 0 * KB);
+    std::vector<DiskRange> merged_disk_ranges{};
+    DiskRangeHelper::merge_adjacent_disk_ranges(disk_ranges, config::io_coalesce_read_max_distance_size,
+                                                config::io_coalesce_read_max_buffer_size, merged_disk_ranges);
+    EXPECT_EQ(1, merged_disk_ranges.size());
+    EXPECT_EQ(0, merged_disk_ranges.at(0).offset());
+    EXPECT_EQ(1000 * KB, merged_disk_ranges.at(0).length());
+}
+
 TEST(DiskRangeTest, TestMergeBigDiskRanges) {
     std::vector<DiskRange> disk_ranges{};
     constexpr int64_t MB = 1024 * 1024;
diff --git a/be/test/formats/parquet/file_reader_test.cpp b/be/test/formats/parquet/file_reader_test.cpp
index 74f3fb292742d4..c1373aa37fe53d 100644
--- a/be/test/formats/parquet/file_reader_test.cpp
+++ b/be/test/formats/parquet/file_reader_test.cpp
@@ -3264,6 +3264,18 @@ TEST_F(FileReaderTest, TestIsNullStatistics) {
     EXPECT_EQ(file_reader->_row_group_readers.size(), 0);
 }
 
+TEST_F(FileReaderTest, TestMapKeyIsStruct) {
+    const std::string filename = "./be/test/formats/parquet/test_data/map_key_is_struct.parquet";
+    auto file = _create_file(filename);
+    auto file_reader =
+            std::make_shared<FileReader>(config::vector_chunk_size, file.get(), std::filesystem::file_size(filename));
+
+    auto ctx = _create_file_random_read_context(filename);
+    Status status = file_reader->init(ctx);
+    ASSERT_FALSE(status.ok());
+    ASSERT_EQ("Map keys must be primitive type.", status.message());
+}
+
 TEST_F(FileReaderTest, TestInFilterStatitics) {
     // there are 4 row groups
     const std::string multi_rg_file = "./be/test/formats/parquet/test_data/page_index_big_page.parquet";
diff --git a/be/test/formats/parquet/test_data/map_key_is_struct.parquet b/be/test/formats/parquet/test_data/map_key_is_struct.parquet
new file mode 100644
index 00000000000000..20485500a00c43
Binary files /dev/null and b/be/test/formats/parquet/test_data/map_key_is_struct.parquet differ
diff --git a/be/test/runtime/agg_state_desc_test.cpp b/be/test/runtime/agg_state_desc_test.cpp
new file mode 100644
index 00000000000000..80fda24fec5d57
--- /dev/null
+++ b/be/test/runtime/agg_state_desc_test.cpp
@@ -0,0 +1,61 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "runtime/agg_state_desc.h"
+
+#include <gtest/gtest.h>
+
+#include <string>
+
+#include "exprs/anyval_util.h"
+#include "runtime/mem_pool.h"
+
+namespace starrocks {
+
+TEST(AggStateDescTest, Basic) {
+    {
+        std::vector<TypeDescriptor> arg_types = {
+                AnyValUtil::column_type_to_type_desc(TypeDescriptor::from_logical_type(TYPE_VARCHAR)),
+                AnyValUtil::column_type_to_type_desc(TypeDescriptor::from_logical_type(TYPE_INT))};
+        auto return_type = AnyValUtil::column_type_to_type_desc(TypeDescriptor::from_logical_type(TYPE_ARRAY));
+        AggStateDesc desc("array_agg2", return_type, arg_types, true, 1);
+        ASSERT_EQ("array_agg2", desc.get_func_name());
+        ASSERT_EQ(true, desc.is_result_nullable());
+        ASSERT_EQ(1, desc.get_func_version());
+        auto* agg_func = AggStateDesc::get_agg_state_func(&desc);
+        ASSERT_TRUE(agg_func != nullptr);
+    }
+    {
+        std::vector<TypeDescriptor> arg_types = {TypeDescriptor::from_logical_type(TYPE_VARCHAR)};
+        auto return_type = AnyValUtil::column_type_to_type_desc(TypeDescriptor::from_logical_type(TYPE_VARCHAR));
+        AggStateDesc desc("group_concat", return_type, arg_types, true, 1);
+        ASSERT_EQ("group_concat", desc.get_func_name());
+        ASSERT_EQ(true, desc.is_result_nullable());
+        ASSERT_EQ(1, desc.get_func_version());
+        auto* agg_func = AggStateDesc::get_agg_state_func(&desc);
+        ASSERT_TRUE(agg_func != nullptr);
+    }
+    {
+        std::vector<TypeDescriptor> arg_types = {TypeDescriptor::from_logical_type(TYPE_SMALLINT)};
+        auto return_type = AnyValUtil::column_type_to_type_desc(TypeDescriptor::from_logical_type(TYPE_DOUBLE));
+        AggStateDesc desc("avg", return_type, arg_types, true, 1);
+        ASSERT_EQ("avg", desc.get_func_name());
+        ASSERT_EQ(true, desc.is_result_nullable());
+        ASSERT_EQ(1, desc.get_func_version());
+        auto* agg_func = AggStateDesc::get_agg_state_func(&desc);
+        ASSERT_TRUE(agg_func != nullptr);
+    }
+}
+
+} // namespace starrocks
diff --git a/be/test/runtime/type_descriptor_test.cpp b/be/test/runtime/type_descriptor_test.cpp
index c1fea309a4e2a0..884ede6c350d22 100644
--- a/be/test/runtime/type_descriptor_test.cpp
+++ b/be/test/runtime/type_descriptor_test.cpp
@@ -33,6 +33,7 @@ TEST_F(TypeDescriptorTest, test_from_thrift) {
         ttype_desc.types.back().__set_type(TTypeNodeType::SCALAR);
         ttype_desc.types.back().__set_scalar_type(TScalarType());
         ttype_desc.types.back().scalar_type.__set_type(TPrimitiveType::INT);
+        ttype_desc.types.back().scalar_type.__set_len(-1);
 
         auto t = TypeDescriptor::from_thrift(ttype_desc);
         ASSERT_FALSE(t.is_complex_type());
@@ -49,6 +50,7 @@ TEST_F(TypeDescriptorTest, test_from_thrift) {
         ttype_desc.types.back().__set_type(TTypeNodeType::SCALAR);
         ttype_desc.types.back().__set_scalar_type(TScalarType());
         ttype_desc.types.back().scalar_type.__set_type(TPrimitiveType::FLOAT);
+        ttype_desc.types.back().scalar_type.__set_len(-1);
 
         auto t = TypeDescriptor::from_thrift(ttype_desc);
         ASSERT_FALSE(t.is_complex_type());
@@ -65,6 +67,7 @@ TEST_F(TypeDescriptorTest, test_from_thrift) {
         ttype_desc.types.back().__set_type(TTypeNodeType::SCALAR);
         ttype_desc.types.back().__set_scalar_type(TScalarType());
         ttype_desc.types.back().scalar_type.__set_type(TPrimitiveType::DOUBLE);
+        ttype_desc.types.back().scalar_type.__set_len(-1);
 
         auto t = TypeDescriptor::from_thrift(ttype_desc);
         ASSERT_FALSE(t.is_complex_type());
@@ -83,6 +86,7 @@ TEST_F(TypeDescriptorTest, test_from_thrift) {
         ttype_desc.types.back().scalar_type.__set_type(TPrimitiveType::DECIMALV2);
         ttype_desc.types.back().scalar_type.__set_precision(4);
         ttype_desc.types.back().scalar_type.__set_scale(6);
+        ttype_desc.types.back().scalar_type.__set_len(-1);
 
         auto t = TypeDescriptor::from_thrift(ttype_desc);
         ASSERT_FALSE(t.is_complex_type());
diff --git a/be/test/storage/column_predicate_test.cpp b/be/test/storage/column_predicate_test.cpp
index a9cfce68f3f517..a73121d9a01576 100644
--- a/be/test/storage/column_predicate_test.cpp
+++ b/be/test/storage/column_predicate_test.cpp
@@ -1640,6 +1640,77 @@ TEST(ColumnPredicateTest, test_in) {
     }
 }
 
+// NOLINTNEXTLINE
+TEST(ColumnPredicateTest, test_dict_in) {
+    {
+        std::unique_ptr<ColumnPredicate> p(
+                new_dictionary_code_in_predicate(get_type_info(TYPE_INT), 0, {3, 4, 6, 8, 10}, 200));
+        auto c = ChunkHelper::column_from_field_type(TYPE_INT, true);
+        c->append_datum(Datum(1));
+        c->append_datum(Datum(2));
+        c->append_datum(Datum(3));
+        (void)c->append_nulls(1);
+        c->append_datum(Datum(4));
+        c->append_datum(Datum(5));
+        c->append_datum(Datum(3));
+        c->append_datum(Datum(4));
+
+        ASSERT_EQ(PredicateType::kInList, p->type());
+        ASSERT_FALSE(p->can_vectorized());
+
+        // ---------------------------------------------
+        // evaluate()
+        // ---------------------------------------------
+        std::vector<uint8_t> buff(8);
+        p->evaluate(c.get(), buff.data(), 0, 8);
+        ASSERT_EQ("0,0,1,0,1,0,1,1", to_string(buff));
+
+        buff.assign(8, 0);
+        p->evaluate(c.get(), buff.data(), 1, 3);
+        ASSERT_EQ("0,0,1,0,0,0,0,0", to_string(buff));
+
+        // ---------------------------------------------
+        // evaluate_and()
+        // ---------------------------------------------
+        buff.assign(8, 1);
+        p->evaluate_and(c.get(), buff.data(), 0, 8);
+        ASSERT_EQ("0,0,1,0,1,0,1,1", to_string(buff));
+
+        p->evaluate_and(c.get(), buff.data(), 1, 3);
+        ASSERT_EQ("0,0,1,0,1,0,1,1", to_string(buff));
+
+        buff.assign(8, 0);
+        p->evaluate_and(c.get(), buff.data(), 0, 8);
+        ASSERT_EQ("0,0,0,0,0,0,0,0", to_string(buff));
+
+        buff[3] = 1;
+        p->evaluate_and(c.get(), buff.data(), 0, 8);
+        ASSERT_EQ("0,0,0,0,0,0,0,0", to_string(buff));
+
+        buff[2] = 1;
+        p->evaluate_and(c.get(), buff.data(), 2, 4);
+        ASSERT_EQ("0,0,1,0,0,0,0,0", to_string(buff));
+
+        // ---------------------------------------------
+        // evaluate_or()
+        // ---------------------------------------------
+        buff.assign(8, 0);
+        p->evaluate_or(c.get(), buff.data(), 0, 8);
+        ASSERT_EQ("0,0,1,0,1,0,1,1", to_string(buff));
+
+        p->evaluate_or(c.get(), buff.data(), 2, 4);
+        ASSERT_EQ("0,0,1,0,1,0,1,1", to_string(buff));
+
+        buff.assign(8, 1);
+        p->evaluate_or(c.get(), buff.data(), 0, 8);
+        ASSERT_EQ("1,1,1,1,1,1,1,1", to_string(buff));
+
+        buff[0] = 0;
+        p->evaluate_or(c.get(), buff.data(), 2, 4);
+        ASSERT_EQ("0,1,1,1,1,1,1,1", to_string(buff));
+    }
+}
+
 // NOLINTNEXTLINE
 TEST(ColumnPredicateTest, test_no_in) {
     {
diff --git a/be/test/storage/delta_column_group_test.cpp b/be/test/storage/delta_column_group_test.cpp
index a52d6be9360262..afadf09c9bde99 100644
--- a/be/test/storage/delta_column_group_test.cpp
+++ b/be/test/storage/delta_column_group_test.cpp
@@ -16,11 +16,14 @@
 
 #include <gtest/gtest.h>
 
+#include "fs/key_cache.h"
+
 namespace starrocks {
 
 TEST(TestDeltaColumnGroup, testLoad) {
+    auto ep = KeyCache::instance().create_plain_random_encryption_meta_pair().value();
     DeltaColumnGroup dcg;
-    dcg.init(100, {{1, 10, 100}}, {"abc0.cols"});
+    dcg.init(100, {{1, 10, 100}}, {"abc0.cols"}, {ep.encryption_meta});
     std::string pb_str = dcg.save();
     DeltaColumnGroup new_dcg;
     ASSERT_TRUE(new_dcg.load(100, pb_str.data(), pb_str.length()).ok());
@@ -36,11 +39,18 @@ TEST(TestDeltaColumnGroup, testLoad) {
             ASSERT_TRUE(v1[i][j] == v2[i][j]);
         }
     }
+    DeltaColumnGroup dcg2;
+    dcg2.init(100, {{2, 12}}, {"abc1.cols"}, {ep.encryption_meta});
+    RowsetId rowset_id;
+    rowset_id.init(100, 100, 0, 0);
+    dcg.merge_by_version(dcg2, "tmp", rowset_id, 100);
+    ASSERT_EQ(2, dcg.encryption_metas().size());
 };
 
 TEST(TestDeltaColumnGroup, testGet) {
+    auto ep = KeyCache::instance().create_plain_random_encryption_meta_pair().value();
     DeltaColumnGroup dcg;
-    dcg.init(100, {{10, 1, 100}}, {"abc.cols"});
+    dcg.init(100, {{10, 1, 100}}, {"abc.cols"}, {ep.encryption_meta});
     ASSERT_TRUE(0 == dcg.get_column_idx(10).first);
     ASSERT_TRUE(0 == dcg.get_column_idx(10).second);
 
@@ -58,6 +68,7 @@ TEST(TestDeltaColumnGroup, testGet) {
 };
 
 TEST(TestDeltaColumnGroup, testGC) {
+    auto ep = KeyCache::instance().create_plain_random_encryption_meta_pair().value();
     // test1
     {
         // 1 -> {1, 2, 3}
@@ -68,9 +79,14 @@ TEST(TestDeltaColumnGroup, testGC) {
         DeltaColumnGroupList dcgs;
         for (ColumnUID i = 1; i <= 20; i++) {
             DeltaColumnGroup dcg;
-            dcg.init((int64_t)i, {{i, i + 1, i + 2}}, {"abc.cols"});
+            dcg.init((int64_t)i, {{i, i + 1, i + 2}}, {"abc.cols"}, {ep.encryption_meta});
             dcgs.push_back(std::make_shared<DeltaColumnGroup>(dcg));
         }
+        DeltaColumnGroupListPB pb;
+        DeltaColumnGroupListSerializer::serialize_delta_column_group_list(dcgs, &pb);
+        DeltaColumnGroupList dcgs_deserialized;
+        DeltaColumnGroupListSerializer::deserialize_delta_column_group_list(pb, &dcgs_deserialized);
+        ASSERT_EQ(dcgs.size(), dcgs_deserialized.size());
         const std::string path = "/asd/";
         std::vector<std::string> clear_files;
         DeltaColumnGroupListHelper::garbage_collection(dcgs, TabletSegmentId(100, 100), 10, path, &garbage_dcgs,
@@ -94,7 +110,7 @@ TEST(TestDeltaColumnGroup, testGC) {
         DeltaColumnGroupList dcgs;
         for (uint32_t i = 1; i <= 20; i++) {
             DeltaColumnGroup dcg;
-            dcg.init((int64_t)i, {{1, 2, 3}}, {"abc.cols"});
+            dcg.init((int64_t)i, {{1, 2, 3}}, {"abc.cols"}, {ep.encryption_meta});
             dcgs.push_back(std::make_shared<DeltaColumnGroup>(dcg));
         }
         const std::string path = "/asd/";
@@ -121,7 +137,7 @@ TEST(TestDeltaColumnGroup, testGC) {
         for (ColumnUID i = 1; i <= 20; i++) {
             DeltaColumnGroup dcg;
             ColumnUID shift = i % 2;
-            dcg.init((int64_t)i, {{1 + shift, 2 + shift, 3 + shift}}, {"abc.cols"});
+            dcg.init((int64_t)i, {{1 + shift, 2 + shift, 3 + shift}}, {"abc.cols"}, {ep.encryption_meta});
             dcgs.push_back(std::make_shared<DeltaColumnGroup>(dcg));
         }
         const std::string path = "/asd/";
@@ -149,7 +165,7 @@ TEST(TestDeltaColumnGroup, testGC) {
         for (ColumnUID i = 1; i <= 20; i++) {
             DeltaColumnGroup dcg;
             ColumnUID shift = i % 3;
-            dcg.init((int64_t)i, {{1 + shift, 2 + shift, 3 + shift}}, {"abc.cols"});
+            dcg.init((int64_t)i, {{1 + shift, 2 + shift, 3 + shift}}, {"abc.cols"}, {ep.encryption_meta});
             dcgs.push_back(std::make_shared<DeltaColumnGroup>(dcg));
         }
         const std::string path = "/asd/";
@@ -168,6 +184,7 @@ TEST(TestDeltaColumnGroup, testGC) {
 };
 
 TEST(TestDeltaColumnGroup, testDeltaColumnGroupVerPBLoad) {
+    auto ep = KeyCache::instance().create_plain_random_encryption_meta_pair().value();
     // version 10 -> aaa.cols -> <3, 4>
     // version 11 -> bbb.cols -> <5, 6>
     // version 12 -> ccc.cols -> <7, 8>
@@ -178,6 +195,9 @@ TEST(TestDeltaColumnGroup, testDeltaColumnGroupVerPBLoad) {
     dcg_ver.add_column_files("aaa.cols");
     dcg_ver.add_column_files("bbb.cols");
     dcg_ver.add_column_files("ccc.cols");
+    dcg_ver.add_encryption_metas(ep.encryption_meta);
+    dcg_ver.add_encryption_metas(ep.encryption_meta);
+    dcg_ver.add_encryption_metas(ep.encryption_meta);
     DeltaColumnGroupColumnIdsPB unique_cids;
     unique_cids.add_column_ids(3);
     unique_cids.add_column_ids(4);
diff --git a/be/test/storage/kv_store_test.cpp b/be/test/storage/kv_store_test.cpp
index 424a218e1c1b7a..0a4d548d52058c 100644
--- a/be/test/storage/kv_store_test.cpp
+++ b/be/test/storage/kv_store_test.cpp
@@ -155,35 +155,4 @@ TEST_F(KVStoreTest, TestOpDeleteRange) {
     }
 }
 
-TEST_F(KVStoreTest, TestOpDeleteRangeFallback) {
-    // insert 10 keys
-    for (int i = 0; i < 10; i++) {
-        std::string key = fmt::format("key_{:016x}", i);
-        std::string value = fmt::format("val_{:016x}", i);
-        ASSERT_TRUE(_kv_store->put(META_COLUMN_FAMILY_INDEX, key, value).ok());
-    }
-    for (int i = 0; i < 10; i++) {
-        std::string key = fmt::format("key_{:016x}", i);
-        std::string value_get;
-        ASSERT_TRUE(_kv_store->get(META_COLUMN_FAMILY_INDEX, key, &value_get).ok());
-        ASSERT_TRUE(value_get == fmt::format("val_{:016x}", i));
-    }
-    int32_t old_val = config::rocksdb_opt_delete_range_limit;
-    config::rocksdb_opt_delete_range_limit = 5;
-    // delete range from 0 ~ 9
-    rocksdb::WriteBatch wb;
-    ASSERT_TRUE(_kv_store
-                        ->OptDeleteRange(META_COLUMN_FAMILY_INDEX, fmt::format("key_{:016x}", 0),
-                                         fmt::format("key_{:016x}", 10), &wb)
-                        .ok());
-    ASSERT_TRUE(_kv_store->write_batch(&wb).ok());
-    // check result
-    for (int i = 0; i < 10; i++) {
-        std::string key = fmt::format("key_{:016x}", i);
-        std::string value_get;
-        ASSERT_TRUE(_kv_store->get(META_COLUMN_FAMILY_INDEX, key, &value_get).is_not_found());
-    }
-    config::rocksdb_opt_delete_range_limit = old_val;
-}
-
 } // namespace starrocks
diff --git a/be/test/storage/lake/lake_primary_key_consistency_test.cpp b/be/test/storage/lake/lake_primary_key_consistency_test.cpp
index 94130d9a370b7b..43f2002bf1a4ff 100644
--- a/be/test/storage/lake/lake_primary_key_consistency_test.cpp
+++ b/be/test/storage/lake/lake_primary_key_consistency_test.cpp
@@ -51,7 +51,9 @@ enum PICT_OP {
     COMPACT = 3,
     RELOAD = 4,
     UPSERT_WITH_BATCH_PUB = 5,
-    MAX = 6,
+    PARTIAL_UPDATE_ROW = 6,
+    PARTIAL_UPDATE_COLUMN = 7,
+    MAX = 8,
 };
 
 static const std::string kTestGroupPath = "./test_lake_primary_key_consistency";
@@ -66,20 +68,27 @@ class Replayer {
     enum ReplayerOP {
         UPSERT,
         ERASE,
+        PARTIAL_UPSERT,
+        PARTIAL_UPDATE,
     };
     void upsert(const ChunkPtr& chunk) { _redo_logs.emplace_back(ReplayerOP::UPSERT, chunk); }
 
     void erase(const ChunkPtr& chunk) { _redo_logs.emplace_back(ReplayerOP::ERASE, chunk); }
 
+    void partial_upsert(const ChunkPtr& chunk) { _redo_logs.emplace_back(ReplayerOP::PARTIAL_UPSERT, chunk); }
+
+    void partial_update(const ChunkPtr& chunk) { _redo_logs.emplace_back(ReplayerOP::PARTIAL_UPDATE, chunk); }
+
     bool check(const ChunkPtr& chunk) {
-        std::map<int, int> tmp_chunk;
+        std::map<int, std::pair<int, int>> tmp_chunk;
         for (int i = 0; i < chunk->num_rows(); i++) {
             if (tmp_chunk.count(chunk->columns()[0]->get(i).get_int32()) > 0) {
                 // duplicate pk
                 LOG(ERROR) << "duplicate pk: " << chunk->columns()[0]->get(i).get_int32();
                 return false;
             }
-            tmp_chunk[chunk->columns()[0]->get(i).get_int32()] = chunk->columns()[1]->get(i).get_int32();
+            tmp_chunk[chunk->columns()[0]->get(i).get_int32()] = {chunk->columns()[1]->get(i).get_int32(),
+                                                                  chunk->columns()[2]->get(i).get_int32()};
         }
         if (tmp_chunk.size() != _replayer_index.size()) {
             LOG(ERROR) << "inconsistency row number, actual : " << tmp_chunk.size()
@@ -87,6 +96,22 @@ class Replayer {
             return false;
         }
         for (const auto& each : _replayer_index) {
+            // check vals
+            auto iter = tmp_chunk.find(each.first);
+            if (iter == tmp_chunk.end()) {
+                LOG(ERROR) << "inconsistency result, mismatch key : " << each.first;
+                return false;
+            }
+            if (iter->second.first != each.second.first) {
+                LOG(ERROR) << "inconsistency result, mismatch c1 : " << iter->second.first << " : "
+                           << each.second.first;
+                return false;
+            }
+            if (iter->second.second != each.second.second) {
+                LOG(ERROR) << "inconsistency result, mismatch c2 : " << iter->second.second << " : "
+                           << each.second.second;
+                return false;
+            }
             tmp_chunk.erase(each.first);
         }
         if (!tmp_chunk.empty()) {
@@ -102,13 +127,31 @@ class Replayer {
             if (log.first == ReplayerOP::UPSERT) {
                 // Upsert
                 for (int i = 0; i < chunk->num_rows(); i++) {
-                    _replayer_index[chunk->columns()[0]->get(i).get_int32()] = chunk->columns()[1]->get(i).get_int32();
+                    _replayer_index[chunk->columns()[0]->get(i).get_int32()] = {
+                            chunk->columns()[1]->get(i).get_int32(), chunk->columns()[2]->get(i).get_int32()};
                 }
-            } else {
+            } else if (log.first == ReplayerOP::ERASE) {
                 // Delete
                 for (int i = 0; i < chunk->num_rows(); i++) {
                     _replayer_index.erase(chunk->columns()[0]->get(i).get_int32());
                 }
+            } else if (log.first == ReplayerOP::PARTIAL_UPSERT || log.first == ReplayerOP::PARTIAL_UPDATE) {
+                // Partial update
+                for (int i = 0; i < chunk->num_rows(); i++) {
+                    auto iter = _replayer_index.find(chunk->columns()[0]->get(i).get_int32());
+                    if (iter != _replayer_index.end()) {
+                        _replayer_index[chunk->columns()[0]->get(i).get_int32()] = {
+                                chunk->columns()[1]->get(i).get_int32(), iter->second.second};
+                    } else if (log.first == ReplayerOP::PARTIAL_UPSERT) {
+                        // insert new record with default val
+                        _replayer_index[chunk->columns()[0]->get(i).get_int32()] = {
+                                chunk->columns()[1]->get(i).get_int32(), 0};
+                    } else {
+                        // do nothing
+                    }
+                }
+            } else {
+                // do nothing
             }
         }
     }
@@ -117,26 +160,33 @@ class Replayer {
 
 private:
     std::vector<std::pair<ReplayerOP, ChunkPtr>> _redo_logs;
-    std::map<int, int> _replayer_index;
+    std::map<int, std::pair<int, int>> _replayer_index;
 };
 
 class LakePrimaryKeyConsistencyTest : public TestBase, testing::WithParamInterface<PrimaryKeyParam> {
 public:
     LakePrimaryKeyConsistencyTest() : TestBase(kTestGroupPath) {
-        _tablet_metadata = generate_simple_tablet_metadata(PRIMARY_KEYS);
+        _tablet_metadata = generate_tablet_metadata(PRIMARY_KEYS);
         _tablet_metadata->set_enable_persistent_index(true);
         _tablet_metadata->set_persistent_index_type(GetParam().persistent_index_type);
 
         _slots.emplace_back(0, "c0", TypeDescriptor{LogicalType::TYPE_INT});
+        _partial_slots.emplace_back(0, "c0", TypeDescriptor{LogicalType::TYPE_INT});
         _slots.emplace_back(1, "c1", TypeDescriptor{LogicalType::TYPE_INT});
-        _slots.emplace_back(2, "__op", TypeDescriptor{LogicalType::TYPE_INT});
+        _partial_slots.emplace_back(1, "c1", TypeDescriptor{LogicalType::TYPE_INT});
+        _slots.emplace_back(2, "c2", TypeDescriptor{LogicalType::TYPE_INT});
+        _slots.emplace_back(3, "__op", TypeDescriptor{LogicalType::TYPE_INT});
         _slot_pointers.emplace_back(&_slots[0]);
         _slot_pointers.emplace_back(&_slots[1]);
+        _partial_slot_pointers.emplace_back(&_partial_slots[0]);
+        _partial_slot_pointers.emplace_back(&_partial_slots[1]);
         _slot_pointers.emplace_back(&_slots[2]);
+        _slot_pointers.emplace_back(&_slots[3]);
 
         _slot_cid_map.emplace(0, 0);
         _slot_cid_map.emplace(1, 1);
         _slot_cid_map.emplace(2, 2);
+        _slot_cid_map.emplace(3, 3);
 
         _tablet_schema = TabletSchema::create(_tablet_metadata->schema());
         _schema = std::make_shared<Schema>(ChunkHelper::convert_schema(_tablet_schema));
@@ -144,12 +194,14 @@ class LakePrimaryKeyConsistencyTest : public TestBase, testing::WithParamInterfa
 
         _random_generator = std::make_unique<DeterRandomGenerator<int, PICT_OP>>(MaxNumber, MaxN, _seed, 0, INT64_MAX);
         std::vector<WeightedItem<PICT_OP>> items;
-        items.emplace_back(PICT_OP::UPSERT, 35);
+        items.emplace_back(PICT_OP::UPSERT, 30);
         items.emplace_back(PICT_OP::DELETE, 15);
         items.emplace_back(PICT_OP::GET, 5);
         items.emplace_back(PICT_OP::COMPACT, 10);
         items.emplace_back(PICT_OP::RELOAD, 10);
-        items.emplace_back(PICT_OP::UPSERT_WITH_BATCH_PUB, 25);
+        items.emplace_back(PICT_OP::UPSERT_WITH_BATCH_PUB, 20);
+        items.emplace_back(PICT_OP::PARTIAL_UPDATE_ROW, 5);
+        items.emplace_back(PICT_OP::PARTIAL_UPDATE_COLUMN, 5);
         _random_op_selector = std::make_unique<WeightedRandomOpSelector<int, PICT_OP>>(_random_generator.get(), items);
         _io_failure_generator =
                 std::make_unique<IOFailureGenerator<int, PICT_OP>>(_random_generator.get(), io_failure_percent);
@@ -179,24 +231,88 @@ class LakePrimaryKeyConsistencyTest : public TestBase, testing::WithParamInterfa
         config::enable_pk_strict_memcheck = _old_enable_pk_strict_memcheck;
     }
 
+    std::shared_ptr<TabletMetadataPB> generate_tablet_metadata(KeysType keys_type) {
+        auto metadata = std::make_shared<TabletMetadata>();
+        metadata->set_id(next_id());
+        metadata->set_version(1);
+        metadata->set_cumulative_point(0);
+        metadata->set_next_rowset_id(1);
+        //
+        //  | column | type | KEY | NULL |
+        //  +--------+------+-----+------+
+        //  |   c0   |  INT | YES |  NO  |
+        //  |   c1   |  INT | NO  |  NO  |
+        //  |   c2   |  INT | NO  |  NO  |
+        auto schema = metadata->mutable_schema();
+        schema->set_keys_type(keys_type);
+        schema->set_id(next_id());
+        schema->set_num_short_key_columns(1);
+        schema->set_num_rows_per_row_block(65535);
+        auto c0 = schema->add_column();
+        {
+            c0->set_unique_id(next_id());
+            c0->set_name("c0");
+            c0->set_type("INT");
+            c0->set_is_key(true);
+            c0->set_is_nullable(false);
+        }
+        auto c1 = schema->add_column();
+        {
+            c1->set_unique_id(next_id());
+            c1->set_name("c1");
+            c1->set_type("INT");
+            c1->set_is_key(false);
+            c1->set_is_nullable(false);
+            c1->set_aggregation(keys_type == DUP_KEYS ? "NONE" : "REPLACE");
+        }
+        auto c2 = schema->add_column();
+        {
+            c2->set_unique_id(next_id());
+            c2->set_name("c2");
+            c2->set_type("INT");
+            c2->set_is_key(false);
+            c2->set_is_nullable(false);
+            c2->set_aggregation(keys_type == DUP_KEYS ? "NONE" : "REPLACE");
+        }
+        return metadata;
+    }
+
     std::pair<ChunkPtr, std::vector<uint32_t>> gen_upsert_data(bool is_upsert) {
         const size_t chunk_size = (size_t)_random_generator->random_n();
-        std::vector<int> v0(chunk_size);
-        std::vector<int> v1(chunk_size);
-        std::vector<uint8_t> v2(chunk_size, is_upsert ? TOpType::UPSERT : TOpType::DELETE);
-        _random_generator->random_cols(chunk_size, &v0, &v1);
+        std::vector<std::vector<int>> cols(3);
+        std::vector<uint8_t> v3(chunk_size, is_upsert ? TOpType::UPSERT : TOpType::DELETE);
+        _random_generator->random_cols(chunk_size, &cols);
+
+        auto c0 = Int32Column::create();
+        auto c1 = Int32Column::create();
+        auto c2 = Int32Column::create();
+        auto c3 = Int8Column::create();
+        c0->append_numbers(cols[0].data(), cols[0].size() * sizeof(int));
+        c1->append_numbers(cols[1].data(), cols[1].size() * sizeof(int));
+        c2->append_numbers(cols[2].data(), cols[2].size() * sizeof(int));
+        c3->append_numbers(v3.data(), v3.size() * sizeof(uint8_t));
+        auto indexes = std::vector<uint32_t>(chunk_size);
+        for (uint32_t i = 0; i < chunk_size; i++) {
+            indexes[i] = i;
+        }
+        return {std::make_shared<Chunk>(Columns{c0, c1, c2, c3}, _slot_cid_map), std::move(indexes)};
+    }
+
+    std::pair<ChunkPtr, std::vector<uint32_t>> gen_partial_update_data() {
+        const size_t chunk_size = (size_t)_random_generator->random_n();
+        std::vector<std::vector<int>> cols(2);
+        std::vector<uint8_t> v3(chunk_size, TOpType::UPSERT);
+        _random_generator->random_cols(chunk_size, &cols);
 
         auto c0 = Int32Column::create();
         auto c1 = Int32Column::create();
-        auto c2 = Int8Column::create();
-        c0->append_numbers(v0.data(), v0.size() * sizeof(int));
-        c1->append_numbers(v1.data(), v1.size() * sizeof(int));
-        c2->append_numbers(v2.data(), v2.size() * sizeof(uint8_t));
+        c0->append_numbers(cols[0].data(), cols[0].size() * sizeof(int));
+        c1->append_numbers(cols[1].data(), cols[1].size() * sizeof(int));
         auto indexes = std::vector<uint32_t>(chunk_size);
         for (uint32_t i = 0; i < chunk_size; i++) {
             indexes[i] = i;
         }
-        return {std::make_shared<Chunk>(Columns{c0, c1, c2}, _slot_cid_map), std::move(indexes)};
+        return {std::make_shared<Chunk>(Columns{c0, c1}, _slot_cid_map), std::move(indexes)};
     }
 
     ChunkPtr read(int64_t tablet_id, int64_t version) {
@@ -244,6 +360,40 @@ class LakePrimaryKeyConsistencyTest : public TestBase, testing::WithParamInterfa
         return Status::OK();
     }
 
+    Status partial_update_op(PartialUpdateMode mode) {
+        auto txn_id = next_id();
+        ASSIGN_OR_ABORT(auto delta_writer, DeltaWriterBuilder()
+                                                   .set_tablet_manager(_tablet_mgr.get())
+                                                   .set_tablet_id(_tablet_metadata->id())
+                                                   .set_txn_id(txn_id)
+                                                   .set_partition_id(_partition_id)
+                                                   .set_mem_tracker(_mem_tracker.get())
+                                                   .set_schema_id(_tablet_schema->id())
+                                                   .set_slot_descriptors(&_partial_slot_pointers)
+                                                   .set_partial_update_mode(mode)
+                                                   .build());
+        RETURN_IF_ERROR(delta_writer->open());
+        size_t upsert_size = _random_generator->random() % MaxUpsert;
+        for (int i = 0; i < upsert_size; i++) {
+            auto chunk_index = gen_partial_update_data();
+            RETURN_IF_ERROR(
+                    delta_writer->write(*(chunk_index.first), chunk_index.second.data(), chunk_index.second.size()));
+            if (mode == PartialUpdateMode::ROW_MODE) {
+                // upsert
+                _replayer->partial_upsert(chunk_index.first);
+            } else {
+                // update
+                _replayer->partial_update(chunk_index.first);
+            }
+        }
+        RETURN_IF_ERROR(delta_writer->finish_with_txnlog());
+        delta_writer->close();
+        // Publish version
+        RETURN_IF_ERROR(publish_single_version(_tablet_metadata->id(), _version + 1, txn_id));
+        _version++;
+        return Status::OK();
+    }
+
     Status upsert_with_batch_pub_op() {
         size_t batch_cnt = std::max(_random_generator->random() % MaxBatchCnt, (size_t)1);
         std::vector<int64_t> txn_ids;
@@ -352,6 +502,12 @@ class LakePrimaryKeyConsistencyTest : public TestBase, testing::WithParamInterfa
             case UPSERT_WITH_BATCH_PUB:
                 st = upsert_with_batch_pub_op();
                 break;
+            case PARTIAL_UPDATE_ROW:
+                st = partial_update_op(PartialUpdateMode::ROW_MODE);
+                break;
+            case PARTIAL_UPDATE_COLUMN:
+                st = partial_update_op(PartialUpdateMode::COLUMN_UPDATE_MODE);
+                break;
             default:
                 break;
             }
@@ -385,6 +541,8 @@ class LakePrimaryKeyConsistencyTest : public TestBase, testing::WithParamInterfa
     int64_t _partition_id = next_id();
     std::vector<SlotDescriptor> _slots;
     std::vector<SlotDescriptor*> _slot_pointers;
+    std::vector<SlotDescriptor> _partial_slots;
+    std::vector<SlotDescriptor*> _partial_slot_pointers;
     Chunk::SlotHashMap _slot_cid_map;
     int64_t _version = 0;
 
@@ -403,6 +561,7 @@ class LakePrimaryKeyConsistencyTest : public TestBase, testing::WithParamInterfa
 TEST_P(LakePrimaryKeyConsistencyTest, test_local_pk_consistency) {
     _seed = 1719499276; //time(nullptr);
     _run_second = 50;   // 50 second
+    LOG(INFO) << "LakePrimaryKeyConsistencyTest begin, seed : " << _seed;
     auto st = run_random_tests();
     if (!st.ok()) {
         LOG(FATAL) << "run_random_tests fail, st : " << st << " seed : " << _seed;
diff --git a/be/test/storage/lake/meta_file_test.cpp b/be/test/storage/lake/meta_file_test.cpp
index e0383e366ca628..d1d0260086c1be 100644
--- a/be/test/storage/lake/meta_file_test.cpp
+++ b/be/test/storage/lake/meta_file_test.cpp
@@ -274,9 +274,9 @@ TEST_F(MetaFileTest, test_dcg) {
         rowset_metadata.add_segments("bbb.dat");
         TxnLogPB_OpWrite op_write;
         op_write.mutable_rowset()->CopyFrom(rowset_metadata);
-        std::vector<std::string> filenames;
-        filenames.push_back("aaa.cols");
-        filenames.push_back("bbb.cols");
+        std::vector<std::pair<std::string, std::string>> filenames;
+        filenames.emplace_back("aaa.cols", "");
+        filenames.emplace_back("bbb.cols", "");
         std::vector<std::vector<ColumnUID>> unique_column_id_list;
         unique_column_id_list.push_back({3, 4, 5});
         unique_column_id_list.push_back({6, 7, 8});
@@ -294,8 +294,8 @@ TEST_F(MetaFileTest, test_dcg) {
         rowset_metadata.add_segments("ccc.dat");
         TxnLogPB_OpWrite op_write;
         op_write.mutable_rowset()->CopyFrom(rowset_metadata);
-        std::vector<std::string> filenames;
-        filenames.push_back("ccc.cols");
+        std::vector<std::pair<std::string, std::string>> filenames;
+        filenames.emplace_back("ccc.cols", "");
         std::vector<std::vector<ColumnUID>> unique_column_id_list;
         unique_column_id_list.push_back({4, 7});
         builder.append_dcg(110, filenames, unique_column_id_list);
@@ -313,8 +313,8 @@ TEST_F(MetaFileTest, test_dcg) {
         rowset_metadata.add_segments("ddd.dat");
         TxnLogPB_OpWrite op_write;
         op_write.mutable_rowset()->CopyFrom(rowset_metadata);
-        std::vector<std::string> filenames;
-        filenames.push_back("ddd.cols");
+        std::vector<std::pair<std::string, std::string>> filenames;
+        filenames.emplace_back("ddd.cols", "");
         std::vector<std::vector<ColumnUID>> unique_column_id_list;
         unique_column_id_list.push_back({3, 5});
         builder.append_dcg(110, filenames, unique_column_id_list);
diff --git a/be/test/storage/rowset/segment_rewriter_test.cpp b/be/test/storage/rowset/segment_rewriter_test.cpp
index 4a7e8c281af588..a1c65581eb662c 100644
--- a/be/test/storage/rowset/segment_rewriter_test.cpp
+++ b/be/test/storage/rowset/segment_rewriter_test.cpp
@@ -159,54 +159,6 @@ TEST_F(SegmentRewriterTest, rewrite_test) {
         }
     }
     EXPECT_EQ(count, num_rows);
-
-    // add useless string to partial segment
-    WritableFileOptions wopts2{
-            .sync_on_close = true, .mode = FileSystem::MUST_EXIST, .encryption_info = encryption_pair.info};
-    ASSIGN_OR_ABORT(auto wblock_tmp, _fs->new_writable_file(wopts2, file_name));
-    for (int i = 0; i < 10; i++) {
-        wblock_tmp->append("test");
-    }
-
-    std::vector<std::unique_ptr<Column>> new_write_columns(read_column_ids.size());
-    for (auto i = 0; i < read_column_ids.size(); ++i) {
-        const auto read_column_id = read_column_ids[i];
-        auto tablet_column = tablet_schema->column(read_column_id);
-        auto column = ChunkHelper::column_from_field_type(tablet_column.type(), tablet_column.is_nullable());
-        new_write_columns[i] = column->clone_empty();
-        for (auto j = 0; j < num_rows; ++j) {
-            new_write_columns[i]->append_datum(Datum(static_cast<int32_t>(j + read_column_ids[i])));
-        }
-    }
-    ASSERT_OK(SegmentRewriter::rewrite(file_name, encryption_pair.info, tablet_schema, read_column_ids,
-                                       new_write_columns, partial_segment->id(), partial_rowset_footer));
-    auto rewrite_segment = *Segment::open(
-            _fs, FileInfo{.path = file_name, .encryption_meta = encryption_pair.encryption_meta}, 0, tablet_schema);
-
-    ASSERT_EQ(rewrite_segment->num_rows(), num_rows);
-    res = rewrite_segment->new_iterator(schema, seg_options);
-    ASSERT_FALSE(res.status().is_end_of_file() || !res.ok() || res.value() == nullptr);
-    auto rewrite_seg_iterator = res.value();
-
-    count = 0;
-    chunk = ChunkHelper::new_chunk(schema, chunk_size);
-    while (true) {
-        chunk->reset();
-        auto st = rewrite_seg_iterator->get_next(chunk.get());
-        if (st.is_end_of_file()) {
-            break;
-        }
-        ASSERT_FALSE(!st.ok());
-        for (auto i = 0; i < chunk->num_rows(); ++i) {
-            EXPECT_EQ(count, chunk->get(i)[0].get_int32());
-            EXPECT_EQ(count + 1, chunk->get(i)[1].get_int32());
-            EXPECT_EQ(count + 2, chunk->get(i)[2].get_int32());
-            EXPECT_EQ(count + 3, chunk->get(i)[3].get_int32());
-            EXPECT_EQ(count + 4, chunk->get(i)[4].get_int32());
-            ++count;
-        }
-    }
-    EXPECT_EQ(count, num_rows);
 }
 
 } // namespace starrocks
diff --git a/be/test/storage/rowset/segment_test.cpp b/be/test/storage/rowset/segment_test.cpp
index b3939f710b5028..cc1ac7ca4c2b59 100644
--- a/be/test/storage/rowset/segment_test.cpp
+++ b/be/test/storage/rowset/segment_test.cpp
@@ -42,6 +42,7 @@
 #include "column/datum_tuple.h"
 #include "common/logging.h"
 #include "fs/fs_memory.h"
+#include "fs/key_cache.h"
 #include "gutil/strings/substitute.h"
 #include "runtime/mem_pool.h"
 #include "runtime/mem_tracker.h"
@@ -273,6 +274,14 @@ TEST_F(SegmentReaderWriterTest, TestHorizontalWrite) {
         r = segment->new_column_iterator_or_default(column, nullptr);
         ASSERT_TRUE(r.ok()) << r.status();
     }
+    // test new_dcg_segment
+    {
+        auto ep = KeyCache::instance().create_plain_random_encryption_meta_pair().value();
+        DeltaColumnGroup dcg;
+        dcg.init(1, {{1}}, {"abc0.cols"}, {ep.encryption_meta});
+        auto r = segment->new_dcg_segment(dcg, 0, nullptr);
+        ASSERT_FALSE(r.ok());
+    }
 }
 
 // NOLINTNEXTLINE
diff --git a/be/test/storage/rowset_column_partial_update_test.cpp b/be/test/storage/rowset_column_partial_update_test.cpp
index 2d0cc721cbc83a..c8ad63a18cb732 100644
--- a/be/test/storage/rowset_column_partial_update_test.cpp
+++ b/be/test/storage/rowset_column_partial_update_test.cpp
@@ -1219,6 +1219,10 @@ TEST_P(RowsetColumnPartialUpdateTest, partial_update_with_source_chunk_limit) {
             return (int16_t)(k1 % 100 + 1) == v1 && (int32_t)(k1 % 1000 + 2) == v2;
         }
     }));
+    // check `calc_upt_memory_usage_per_row`
+    for (int i = 10; i < 20; i++) {
+        ASSERT_TRUE(RowsetColumnUpdateState::calc_upt_memory_usage_per_row(rowsets[i].get()) > 0);
+    }
     config::vector_chunk_size = old_vector_chunk_size;
     config::partial_update_memory_limit_per_worker = old_partial_update_memory_limit_per_worker;
     final_check(tablet, rowsets);
diff --git a/be/test/util/json_flattener_test.cpp b/be/test/util/json_flattener_test.cpp
index 05a3b9232f73b0..414293e0835e62 100644
--- a/be/test/util/json_flattener_test.cpp
+++ b/be/test/util/json_flattener_test.cpp
@@ -270,4 +270,85 @@ TEST_F(JsonFlattenerTest, testMiddleJson) {
     EXPECT_EQ(R"({"g1": 123})", result[1]->debug_item(1));
 }
 
+TEST_F(JsonFlattenerTest, testSortHitNums) {
+    // clang-format off
+    std::vector<std::string> jsons = {
+    R"({"k1": 10, "k2": 20, "k3": 30, "k4": 40, "k5": 50, "k6": 60, "k7": 70, "k8": 80,  "k9": 90,  "a10": 100, "k11": 110, "h12": 120, "k13": 130, "g14": 140, "k15": 150, "z16": 160, "e17": 170, "c18": 180, "a19": 190, "b20": 200})",
+    R"({"k2": 25, "k3": 35, "k4": 45, "k5": 55, "k6": 65, "k7": 75, "k8": 85,  "k9": 95,  "a10": 105, "k11": 115, "h12": 125, "k13": 135, "g14": 145, "k15": 155, "z16": 165, "e17": 175, "c18": 185, "a19": 195, "b20": 205})",
+    R"({"k3": 32, "k4": 42, "k5": 52, "k6": 62, "k7": 72, "k8": 82,  "k9": 92,  "a10": 102, "k11": 112, "h12": 122, "k13": 132, "g14": 142, "k15": 152, "z16": 162, "e17": 172, "c18": 182, "a19": 192, "b20": 202})",
+    R"({"k4": 48, "k5": 58, "k6": 68, "k7": 78, "k8": 88,  "k9": 98,  "a10": 108, "k11": 118, "h12": 128, "k13": 138, "g14": 148, "k15": 158, "z16": 168, "e17": 178, "c18": 188, "a19": 198, "b20": 208})",
+    R"({"k5": 54, "k6": 64, "k7": 74, "k8": 84,  "k9": 94,  "a10": 104, "k11": 114, "h12": 124, "k13": 134, "g14": 144, "k15": 154, "z16": 164, "e17": 174, "c18": 184, "a19": 194, "b20": 204})",
+    R"({"k6": 66, "k7": 76, "k8": 86,  "k9": 96,  "a10": 106, "k11": 116, "h12": 126, "k13": 136, "g14": 146, "k15": 156, "z16": 166, "e17": 176, "c18": 186, "a19": 196, "b20": 206})",
+    R"({"k7": 79, "k8": 89,  "k9": 99,  "a10": 109, "k11": 119, "h12": 129, "k13": 139, "g14": 149, "k15": 159, "z16": 169, "e17": 179, "c18": 189, "a19": 199, "b20": 209})",
+    R"({"k8": 81,  "k9": 91,  "a10": 101, "k11": 111, "h12": 121, "k13": 131, "g14": 141, "k15": 151, "z16": 161, "e17": 171, "c18": 181, "a19": 191, "b20": 201})",
+    R"({"k9": 93,  "a10": 103, "k11": 113, "h12": 123, "k13": 133, "g14": 143, "k15": 153, "z16": 163, "e17": 173, "c18": 183, "a19": 193, "b20": 203})",
+    R"({"a10": 107, "k11": 117, "h12": 127, "k13": 137, "g14": 147, "k15": 157, "z16": 167, "e17": 177, "c18": 187, "a19": 197, "b20": 207})",
+   R"({"k11": 130, "h12": 140, "k13": 150, "g14": 160, "k15": 170, "z16": 180, "e17": 190, "c18": 200, "a19": 210, "b20": 220})",
+   R"({"h12": 145, "k13": 155, "g14": 165, "k15": 175, "z16": 185, "e17": 195, "c18": 205, "a19": 215, "b20": 225})",
+   R"({"k13": 152, "g14": 162, "k15": 172, "z16": 182, "e17": 192, "c18": 202, "a19": 212, "b20": 222})",
+   R"({"g14": 168, "k15": 178, "z16": 188, "e17": 198, "c18": 208, "a19": 218, "b20": 228})",
+   R"({"k15": 174, "z16": 184, "e17": 194, "c18": 204, "a19": 214, "b20": 224})",
+   R"({"z16": 186, "e17": 196, "c18": 206, "a19": 216, "b20": 226})",
+   R"({"e17": 199, "c18": 209, "a19": 219, "b20": 229})",
+   R"({"c18": 201, "a19": 211, "b20": 221})",
+   R"({"a19": 213, "b20": 223})",
+   R"({"b20": 227})"
+    };
+    // clang-format on
+
+    ColumnPtr input = JsonColumn::create();
+    JsonColumn* json_input = down_cast<JsonColumn*>(input.get());
+    for (const auto& json : jsons) {
+        ASSIGN_OR_ABORT(auto json_value, JsonValue::parse(json));
+        json_input->append(&json_value);
+    }
+
+    {
+        config::json_flat_sparsity_factor = 0.3;
+        JsonPathDeriver jf;
+        jf.derived({json_input});
+
+        auto& result = jf.flat_paths();
+        std::vector<std::string> paths = {"a10", "a19", "b20", "c18", "e17", "g14", "h12", "k11",
+                                          "k13", "k15", "k6",  "k7",  "k8",  "k9",  "z16"};
+        EXPECT_EQ(true, jf.has_remain_json());
+        EXPECT_EQ(paths, result);
+    }
+
+    {
+        config::json_flat_sparsity_factor = 0.4;
+        JsonPathDeriver jf;
+        jf.derived({json_input});
+
+        auto& result = jf.flat_paths();
+        std::vector<std::string> paths = {"a10", "a19", "b20", "c18", "e17", "g14", "h12",
+                                          "k11", "k13", "k15", "k8",  "k9",  "z16"};
+        EXPECT_EQ(true, jf.has_remain_json());
+        EXPECT_EQ(paths, result);
+    }
+
+    {
+        config::json_flat_sparsity_factor = 0.8;
+        JsonPathDeriver jf;
+        jf.derived({json_input});
+
+        auto& result = jf.flat_paths();
+        std::vector<std::string> paths = {"a19", "b20", "c18", "e17", "z16"};
+        EXPECT_EQ(true, jf.has_remain_json());
+        EXPECT_EQ(paths, result);
+    }
+
+    {
+        config::json_flat_sparsity_factor = 0;
+        JsonPathDeriver jf;
+        jf.derived({json_input});
+
+        auto& result = jf.flat_paths();
+        std::vector<std::string> paths = {"a10", "a19", "b20", "c18", "e17", "g14", "h12", "k1", "k11", "k13",
+                                          "k15", "k2",  "k3",  "k4",  "k5",  "k6",  "k7",  "k8", "k9",  "z16"};
+        EXPECT_EQ(true, jf.has_remain_json());
+        EXPECT_EQ(paths, result);
+    }
+}
+
 } // namespace starrocks
diff --git a/bin/start_backend.sh b/bin/start_backend.sh
index 26fba7f493ad18..4e72334432aa45 100755
--- a/bin/start_backend.sh
+++ b/bin/start_backend.sh
@@ -219,7 +219,7 @@ if [ ${RUN_LOG_CONSOLE} -eq 1 ] ; then
     export GLOG_logtostderr=1
 else
     # redirect stdout/stderr to ${LOG_FILE}
-    exec &>> ${LOG_FILE}
+    exec >> ${LOG_FILE} 2>&1
 fi
 
 echo "start time: $(date), server uptime: $(uptime)"
diff --git a/bin/start_fe.sh b/bin/start_fe.sh
index aafcfd1e6583b9..a021571e26c1ad 100755
--- a/bin/start_fe.sh
+++ b/bin/start_fe.sh
@@ -225,7 +225,7 @@ if [ ${RUN_LOG_CONSOLE} -eq 1 ] ; then
     echo -e "\nsys_log_to_console = true" >> $STARROCKS_HOME/conf/fe.conf
 else
     # redirect all subsequent commands' stdout/stderr into $LOG_FILE
-    exec &>> $LOG_FILE
+    exec >> $LOG_FILE 2>&1
 fi
 
 echo "using java version $JAVA_VERSION"
diff --git a/build.sh b/build.sh
index 5f8f1dbfe88f07..f8d651d37cc38d 100755
--- a/build.sh
+++ b/build.sh
@@ -100,7 +100,9 @@ Usage: $0 <options>
                         Turning this option on automatically disables ccache.
      --with-tenann
                         build with vector index tenann library
-
+     --with-compress-debug-symbol {ON|OFF}
+                        build with compressing debug symbol. (default: $WITH_COMPRESS)
+     -h,--help          Show this help message
   Eg.
     $0                                           build all
     $0 --be                                      build Backend without clean
@@ -115,8 +117,7 @@ Usage: $0 <options>
 
 OPTS=$(getopt \
   -n $0 \
-  -o '' \
-  -o 'h' \
+  -o 'hj:' \
   -l 'be' \
   -l 'fe' \
   -l 'spark-dpp' \
@@ -133,7 +134,7 @@ OPTS=$(getopt \
   -l 'enable-shared-data' \
   -l 'output-compile-time' \
   -l 'with-tenann' \
-  -o 'j:' \
+  -l 'with-compress-debug-symbol:' \
   -l 'help' \
   -- "$@")
 
@@ -246,6 +247,7 @@ else
             --without-starcache) WITH_STARCACHE=OFF; shift ;;
             --output-compile-time) OUTPUT_COMPILE_TIME=ON; shift ;;
             --with-tenann) WITH_TENANN=ON; shift ;;
+            --with-compress-debug-symbol) WITH_COMPRESS=$2 ; shift 2 ;;
             -h) HELP=1; shift ;;
             --help) HELP=1; shift ;;
             -j) PARALLEL=$2; shift 2 ;;
@@ -266,30 +268,30 @@ if [ ${CLEAN} -eq 1 ] && [ ${BUILD_BE} -eq 0 ] && [ ${BUILD_FE} -eq 0 ] && [ ${B
 fi
 
 echo "Get params:
-    BUILD_BE            -- $BUILD_BE
-    BE_CMAKE_TYPE       -- $BUILD_TYPE
-    BUILD_FE            -- $BUILD_FE
-    BUILD_SPARK_DPP     -- $BUILD_SPARK_DPP
-    BUILD_HIVE_UDF      -- $BUILD_HIVE_UDF
-    CCACHE              -- ${CCACHE}
-    CLEAN               -- $CLEAN
-    RUN_UT              -- $RUN_UT
-    WITH_GCOV           -- $WITH_GCOV
-    WITH_BENCH          -- $WITH_BENCH
-    WITH_CLANG_TIDY     -- $WITH_CLANG_TIDY
-    WITH_COMPRESS       -- $WITH_COMPRESS
-    WITH_STARCACHE      -- $WITH_STARCACHE
-    ENABLE_SHARED_DATA  -- $USE_STAROS
-    USE_AVX2            -- $USE_AVX2
-    USE_AVX512          -- $USE_AVX512
-    USE_SSE4_2          -- $USE_SSE4_2
-    JEMALLOC_DEBUG      -- $JEMALLOC_DEBUG
-    PARALLEL            -- $PARALLEL
-    ENABLE_QUERY_DEBUG_TRACE -- $ENABLE_QUERY_DEBUG_TRACE
-    ENABLE_FAULT_INJECTION -- $ENABLE_FAULT_INJECTION
-    BUILD_JAVA_EXT      -- $BUILD_JAVA_EXT
-    OUTPUT_COMPILE_TIME   -- $OUTPUT_COMPILE_TIME
-    WITH_TENANN   -- $WITH_TENANN
+    BUILD_BE                    -- $BUILD_BE
+    BE_CMAKE_TYPE               -- $BUILD_TYPE
+    BUILD_FE                    -- $BUILD_FE
+    BUILD_SPARK_DPP             -- $BUILD_SPARK_DPP
+    BUILD_HIVE_UDF              -- $BUILD_HIVE_UDF
+    CCACHE                      -- ${CCACHE}
+    CLEAN                       -- $CLEAN
+    RUN_UT                      -- $RUN_UT
+    WITH_GCOV                   -- $WITH_GCOV
+    WITH_BENCH                  -- $WITH_BENCH
+    WITH_CLANG_TIDY             -- $WITH_CLANG_TIDY
+    WITH_COMPRESS_DEBUG_SYMBOL  -- $WITH_COMPRESS
+    WITH_STARCACHE              -- $WITH_STARCACHE
+    ENABLE_SHARED_DATA          -- $USE_STAROS
+    USE_AVX2                    -- $USE_AVX2
+    USE_AVX512                  -- $USE_AVX512
+    USE_SSE4_2                  -- $USE_SSE4_2
+    JEMALLOC_DEBUG              -- $JEMALLOC_DEBUG
+    PARALLEL                    -- $PARALLEL
+    ENABLE_QUERY_DEBUG_TRACE    -- $ENABLE_QUERY_DEBUG_TRACE
+    ENABLE_FAULT_INJECTION      -- $ENABLE_FAULT_INJECTION
+    BUILD_JAVA_EXT              -- $BUILD_JAVA_EXT
+    OUTPUT_COMPILE_TIME         -- $OUTPUT_COMPILE_TIME
+    WITH_TENANN                 -- $WITH_TENANN
 "
 
 check_tool()
diff --git a/docker/dockerfiles/dev-env/dev-env.Dockerfile b/docker/dockerfiles/dev-env/dev-env.Dockerfile
index 201db462006bbc..742b361bb9fdcc 100644
--- a/docker/dockerfiles/dev-env/dev-env.Dockerfile
+++ b/docker/dockerfiles/dev-env/dev-env.Dockerfile
@@ -22,7 +22,7 @@ ARG predownload_thirdparty=false
 ARG thirdparty_url=https://cdn-thirdparty.starrocks.com/starrocks-thirdparty-main-20240411.tar
 ARG commit_id
 # check thirdparty/starlet-artifacts-version.sh, to get the right tag
-ARG starlet_tag=v3.3-rc3
+ARG starlet_tag=v3.3-rc5
 # build for which linux distro: centos7|ubuntu
 ARG distro=ubuntu
 # Token to access artifacts in private github repositories.
diff --git a/docker/dockerfiles/toolchains/toolchains-centos7.Dockerfile b/docker/dockerfiles/toolchains/toolchains-centos7.Dockerfile
index c0441a1170b3ad..239e665f941c9f 100644
--- a/docker/dockerfiles/toolchains/toolchains-centos7.Dockerfile
+++ b/docker/dockerfiles/toolchains/toolchains-centos7.Dockerfile
@@ -3,6 +3,7 @@
 #  DOCKER_BUILDKIT=1 docker build --rm=true -f docker/dockerfiles/toolchains/toolchains-centos7.Dockerfile -t toolchains-centos7:latest docker/dockerfiles/toolchains/
 
 ARG GCC_INSTALL_HOME=/opt/rh/gcc-toolset-10/root/usr
+ARG GCC_10_DOWNLOAD_URL=https://ftp.gnu.org/gnu/gcc/gcc-10.3.0/gcc-10.3.0.tar.gz
 ARG GCC_DOWNLOAD_URL=https://ftp.gnu.org/gnu/gcc/gcc-14.2.0/gcc-14.2.0.tar.gz
 ARG CMAKE_INSTALL_HOME=/opt/cmake
 ARG MAVEN_VERSION=3.6.3
@@ -10,7 +11,7 @@ ARG MAVEN_INSTALL_HOME=/opt/maven
 # Can't upgrade to a later version, due to incompatible changes between 2.31 and 2.32
 ARG BINUTILS_DOWNLOAD_URL=https://ftp.gnu.org/gnu/binutils/binutils-2.30.tar.bz2
 # install epel-release directly from the url link
-ARG EPEL_RPM_URL=https://dl.fedoraproject.org/pub/epel/epel-release-latest-7.noarch.rpm
+ARG EPEL_RPM_URL=https://archives.fedoraproject.org/pub/archive/epel/7/x86_64/Packages/e/epel-release-7-14.noarch.rpm
 
 FROM centos:centos7 AS fixed-centos7-image
 # Fix the centos mirrorlist, due to official list is gone after EOL
@@ -24,8 +25,18 @@ RUN yum install -y gcc gcc-c++ make automake curl wget gzip gunzip zip bzip2 fil
 
 FROM base-builder AS gcc-builder
 ARG GCC_INSTALL_HOME
+ARG GCC_10_DOWNLOAD_URL
 ARG GCC_DOWNLOAD_URL
-RUN mkdir -p /workspace/gcc && \
+# build gcc-10
+RUN mkdir -p /workspace/gcc-10 && \
+    cd /workspace/gcc-10 &&    \
+    wget --progress=dot:mega --no-check-certificate $GCC_10_DOWNLOAD_URL -O ../gcc-10.tar.gz && \
+    tar -xzf ../gcc-10.tar.gz --strip-components=1 && \
+    ./contrib/download_prerequisites && \
+    ./configure --disable-multilib --enable-languages=c,c++ --prefix=/workspace/gcc-10/install
+RUN cd /workspace/gcc-10 && make -j`nproc` && make install
+# build gcc-14
+RUN mkdir -p /workspace/gcc && export CC=/workspace/gcc-10/install/bin/gcc && export CXX=/workspace/gcc-10/install/bin/g++ && \
     cd /workspace/gcc &&    \
     wget --progress=dot:mega --no-check-certificate $GCC_DOWNLOAD_URL -O ../gcc.tar.gz && \
     tar -xzf ../gcc.tar.gz --strip-components=1 && \
@@ -57,9 +68,8 @@ ARG EPEL_RPM_URL
 
 LABEL org.opencontainers.image.source="https://github.com/starrocks/starrocks"
 
-RUN yum-config-manager --add-repo https://cli.github.com/packages/rpm/gh-cli.repo && yum install -y gh
-
-RUN yum install -y ${EPEL_RPM_URL} && yum install -y wget unzip bzip2 patch bison byacc flex autoconf automake make \
+RUN yum-config-manager --add-repo https://cli.github.com/packages/rpm/gh-cli.repo && yum install -y gh && \
+        yum install -y ${EPEL_RPM_URL} && yum install -y wget unzip bzip2 patch bison byacc flex autoconf automake make \
         libtool which git ccache binutils-devel python3 file java-11-openjdk java-11-openjdk-devel java-11-openjdk-jmods less psmisc && \
         yum clean all && rm -rf /var/cache/yum
 
diff --git a/docs/docusaurus/.gitignore b/docs/docusaurus/.gitignore
index d9ea6155d3024b..a6f450de331f5b 100644
--- a/docs/docusaurus/.gitignore
+++ b/docs/docusaurus/.gitignore
@@ -1,12 +1,14 @@
 # Dependencies
+oldsidebars.json
 /node_modules
 
 # Production
 /build
 /docs
 **/versioned_docs/**
-**/docusaurus-plugin-content-docs/**
+**/docusaurus-plugin-content-docs/current/**
 i18n/zh/docusaurus-plugin-content-docs-releasenotes/current/*.md
+i18n/zh/docusaurus-plugin-content-blog/**
 /static/releasenotes
 /releasenotes
 /common
diff --git a/docs/docusaurus/Dockerfile b/docs/docusaurus/Dockerfile
index e2fd5e75527294..7c2a97e750ed23 100644
--- a/docs/docusaurus/Dockerfile
+++ b/docs/docusaurus/Dockerfile
@@ -1,7 +1,7 @@
-FROM node:18.18.2
+FROM node:21
 
 WORKDIR /app/docusaurus
-ENV NODE_OPTIONS="--max-old-space-size=4096"
+ENV NODE_OPTIONS="--max-old-space-size=8192"
 
 RUN apt update && apt install -y neovim
 
diff --git a/docs/docusaurus/docusaurus.config.js b/docs/docusaurus/docusaurus.config.js
index f2a6b9b3afa18b..aa2848ce219076 100644
--- a/docs/docusaurus/docusaurus.config.js
+++ b/docs/docusaurus/docusaurus.config.js
@@ -131,7 +131,7 @@ const config = {
         items: [
           {
             type: 'docSidebar',
-            sidebarId: 'English',
+            sidebarId: 'docs',
             position: 'left',
             label: 'Documentation',
           },
diff --git a/docs/docusaurus/i18n/zh/code.json b/docs/docusaurus/i18n/zh/code.json
new file mode 100644
index 00000000000000..6771eb638a085f
--- /dev/null
+++ b/docs/docusaurus/i18n/zh/code.json
@@ -0,0 +1,420 @@
+{
+  "theme.ErrorPageContent.title": {
+    "message": "页面已崩溃。",
+    "description": "The title of the fallback page when the page crashed"
+  },
+  "theme.BackToTopButton.buttonAriaLabel": {
+    "message": "回到顶部",
+    "description": "The ARIA label for the back to top button"
+  },
+  "theme.blog.archive.title": {
+    "message": "历史博文",
+    "description": "The page & hero title of the blog archive page"
+  },
+  "theme.blog.archive.description": {
+    "message": "历史博文",
+    "description": "The page & hero description of the blog archive page"
+  },
+  "theme.blog.paginator.navAriaLabel": {
+    "message": "博文列表分页导航",
+    "description": "The ARIA label for the blog pagination"
+  },
+  "theme.blog.paginator.newerEntries": {
+    "message": "较新的博文",
+    "description": "The label used to navigate to the newer blog posts page (previous page)"
+  },
+  "theme.blog.paginator.olderEntries": {
+    "message": "较旧的博文",
+    "description": "The label used to navigate to the older blog posts page (next page)"
+  },
+  "theme.blog.post.paginator.navAriaLabel": {
+    "message": "博文分页导航",
+    "description": "The ARIA label for the blog posts pagination"
+  },
+  "theme.blog.post.paginator.newerPost": {
+    "message": "较新一篇",
+    "description": "The blog post button label to navigate to the newer/previous post"
+  },
+  "theme.blog.post.paginator.olderPost": {
+    "message": "较旧一篇",
+    "description": "The blog post button label to navigate to the older/next post"
+  },
+  "theme.blog.post.plurals": {
+    "message": "{count} 篇博文",
+    "description": "Pluralized label for \"{count} posts\". Use as much plural forms (separated by \"|\") as your language support (see https://www.unicode.org/cldr/cldr-aux/charts/34/supplemental/language_plural_rules.html)"
+  },
+  "theme.blog.tagTitle": {
+    "message": "{nPosts} 含有标签「{tagName}」",
+    "description": "The title of the page for a blog tag"
+  },
+  "theme.tags.tagsPageLink": {
+    "message": "查看所有标签",
+    "description": "The label of the link targeting the tag list page"
+  },
+  "theme.colorToggle.ariaLabel": {
+    "message": "切换浅色/暗黑模式（当前为{mode}）",
+    "description": "The ARIA label for the navbar color mode toggle"
+  },
+  "theme.colorToggle.ariaLabel.mode.dark": {
+    "message": "暗黑模式",
+    "description": "The name for the dark color mode"
+  },
+  "theme.colorToggle.ariaLabel.mode.light": {
+    "message": "浅色模式",
+    "description": "The name for the light color mode"
+  },
+  "theme.docs.breadcrumbs.navAriaLabel": {
+    "message": "页面路径",
+    "description": "The ARIA label for the breadcrumbs"
+  },
+  "theme.docs.DocCard.categoryDescription": {
+    "message": "{count} 个项目",
+    "description": "The default description for a category card in the generated index about how many items this category includes"
+  },
+  "theme.docs.paginator.navAriaLabel": {
+    "message": "文件选项卡",
+    "description": "The ARIA label for the docs pagination"
+  },
+  "theme.docs.paginator.previous": {
+    "message": "上一页",
+    "description": "The label used to navigate to the previous doc"
+  },
+  "theme.docs.paginator.next": {
+    "message": "下一页",
+    "description": "The label used to navigate to the next doc"
+  },
+  "theme.docs.tagDocListPageTitle.nDocsTagged": {
+    "message": "{count} 篇文档带有标签",
+    "description": "Pluralized label for \"{count} docs tagged\". Use as much plural forms (separated by \"|\") as your language support (see https://www.unicode.org/cldr/cldr-aux/charts/34/supplemental/language_plural_rules.html)"
+  },
+  "theme.docs.tagDocListPageTitle": {
+    "message": "{nDocsTagged}「{tagName}」",
+    "description": "The title of the page for a docs tag"
+  },
+  "theme.docs.versionBadge.label": {
+    "message": "版本：{versionLabel}"
+  },
+  "theme.docs.versions.unreleasedVersionLabel": {
+    "message": "此为 {siteTitle} {versionLabel} 版尚未发行的文档。",
+    "description": "The label used to tell the user that he's browsing an unreleased doc version"
+  },
+  "theme.docs.versions.unmaintainedVersionLabel": {
+    "message": "此为 {siteTitle} {versionLabel} 版的文档，现已不再积极维护。",
+    "description": "The label used to tell the user that he's browsing an unmaintained doc version"
+  },
+  "theme.docs.versions.latestVersionSuggestionLabel": {
+    "message": "最新的文档请参阅 {latestVersionLink} ({versionLabel})。",
+    "description": "The label used to tell the user to check the latest version"
+  },
+  "theme.docs.versions.latestVersionLinkLabel": {
+    "message": "最新版本",
+    "description": "The label used for the latest version suggestion link label"
+  },
+  "theme.common.editThisPage": {
+    "message": "编辑此页",
+    "description": "The link label to edit the current page"
+  },
+  "theme.common.headingLinkTitle": {
+    "message": "{heading}的直接链接",
+    "description": "Title for link to heading"
+  },
+  "theme.lastUpdated.atDate": {
+    "message": "于 {date} ",
+    "description": "The words used to describe on which date a page has been last updated"
+  },
+  "theme.lastUpdated.byUser": {
+    "message": "由 {user} ",
+    "description": "The words used to describe by who the page has been last updated"
+  },
+  "theme.lastUpdated.lastUpdatedAtBy": {
+    "message": "最后{byUser}{atDate}更新",
+    "description": "The sentence used to display when a page has been last updated, and by who"
+  },
+  "theme.navbar.mobileVersionsDropdown.label": {
+    "message": "选择版本",
+    "description": "The label for the navbar versions dropdown on mobile view"
+  },
+  "theme.NotFound.title": {
+    "message": "找不到页面",
+    "description": "The title of the 404 page"
+  },
+  "theme.tags.tagsListLabel": {
+    "message": "标签：",
+    "description": "The label alongside a tag list"
+  },
+  "theme.admonition.caution": {
+    "message": "警告",
+    "description": "The default label used for the Caution admonition (:::caution)"
+  },
+  "theme.admonition.danger": {
+    "message": "危险",
+    "description": "The default label used for the Danger admonition (:::danger)"
+  },
+  "theme.admonition.info": {
+    "message": "信息",
+    "description": "The default label used for the Info admonition (:::info)"
+  },
+  "theme.admonition.note": {
+    "message": "备注",
+    "description": "The default label used for the Note admonition (:::note)"
+  },
+  "theme.admonition.tip": {
+    "message": "提示",
+    "description": "The default label used for the Tip admonition (:::tip)"
+  },
+  "theme.admonition.warning": {
+    "message": "注意",
+    "description": "The default label used for the Warning admonition (:::warning)"
+  },
+  "theme.AnnouncementBar.closeButtonAriaLabel": {
+    "message": "关闭",
+    "description": "The ARIA label for close button of announcement bar"
+  },
+  "theme.blog.sidebar.navAriaLabel": {
+    "message": "最近博文导航",
+    "description": "The ARIA label for recent posts in the blog sidebar"
+  },
+  "theme.CodeBlock.copied": {
+    "message": "复制成功",
+    "description": "The copied button label on code blocks"
+  },
+  "theme.CodeBlock.copyButtonAriaLabel": {
+    "message": "复制代码到剪贴板",
+    "description": "The ARIA label for copy code blocks button"
+  },
+  "theme.CodeBlock.copy": {
+    "message": "复制",
+    "description": "The copy button label on code blocks"
+  },
+  "theme.CodeBlock.wordWrapToggle": {
+    "message": "切换自动换行",
+    "description": "The title attribute for toggle word wrapping button of code block lines"
+  },
+  "theme.DocSidebarItem.expandCategoryAriaLabel": {
+    "message": "展开侧边栏分类 '{label}'",
+    "description": "The ARIA label to expand the sidebar category"
+  },
+  "theme.DocSidebarItem.collapseCategoryAriaLabel": {
+    "message": "折叠侧边栏分类 '{label}'",
+    "description": "The ARIA label to collapse the sidebar category"
+  },
+  "theme.NavBar.navAriaLabel": {
+    "message": "主导航",
+    "description": "The ARIA label for the main navigation"
+  },
+  "theme.navbar.mobileLanguageDropdown.label": {
+    "message": "选择语言",
+    "description": "The label for the mobile language switcher dropdown"
+  },
+  "theme.TOCCollapsible.toggleButtonLabel": {
+    "message": "本页总览",
+    "description": "The label used by the button on the collapsible TOC component"
+  },
+  "theme.NotFound.p1": {
+    "message": "我们找不到您要找的页面。",
+    "description": "The first paragraph of the 404 page"
+  },
+  "theme.NotFound.p2": {
+    "message": "请联系原始链接来源网站的所有者，并告知他们链接已损坏。",
+    "description": "The 2nd paragraph of the 404 page"
+  },
+  "theme.blog.post.readMore": {
+    "message": "阅读更多",
+    "description": "The label used in blog post item excerpts to link to full blog posts"
+  },
+  "theme.blog.post.readMoreLabel": {
+    "message": "阅读 {title} 的全文",
+    "description": "The ARIA label for the link to full blog posts from excerpts"
+  },
+  "theme.blog.post.readingTime.plurals": {
+    "message": "阅读需 {readingTime} 分钟",
+    "description": "Pluralized label for \"{readingTime} min read\". Use as much plural forms (separated by \"|\") as your language support (see https://www.unicode.org/cldr/cldr-aux/charts/34/supplemental/language_plural_rules.html)"
+  },
+  "theme.docs.breadcrumbs.home": {
+    "message": "主页面",
+    "description": "The ARIA label for the home page in the breadcrumbs"
+  },
+  "theme.docs.sidebar.collapseButtonTitle": {
+    "message": "收起侧边栏",
+    "description": "The title attribute for collapse button of doc sidebar"
+  },
+  "theme.docs.sidebar.collapseButtonAriaLabel": {
+    "message": "收起侧边栏",
+    "description": "The title attribute for collapse button of doc sidebar"
+  },
+  "theme.docs.sidebar.navAriaLabel": {
+    "message": "文档侧边栏",
+    "description": "The ARIA label for the sidebar navigation"
+  },
+  "theme.docs.sidebar.closeSidebarButtonAriaLabel": {
+    "message": "关闭导航栏",
+    "description": "The ARIA label for close button of mobile sidebar"
+  },
+  "theme.navbar.mobileSidebarSecondaryMenu.backButtonLabel": {
+    "message": "← 回到主菜单",
+    "description": "The label of the back button to return to main menu, inside the mobile navbar sidebar secondary menu (notably used to display the docs sidebar)"
+  },
+  "theme.docs.sidebar.toggleSidebarButtonAriaLabel": {
+    "message": "切换导航栏",
+    "description": "The ARIA label for hamburger menu button of mobile navigation"
+  },
+  "theme.docs.sidebar.expandButtonTitle": {
+    "message": "展开侧边栏",
+    "description": "The ARIA label and title attribute for expand button of doc sidebar"
+  },
+  "theme.docs.sidebar.expandButtonAriaLabel": {
+    "message": "展开侧边栏",
+    "description": "The ARIA label and title attribute for expand button of doc sidebar"
+  },
+  "theme.SearchBar.seeAll": {
+    "message": "查看全部 {count} 个结果"
+  },
+  "theme.SearchPage.documentsFound.plurals": {
+    "message": "找到 {count} 份文件",
+    "description": "Pluralized label for \"{count} documents found\". Use as much plural forms (separated by \"|\") as your language support (see https://www.unicode.org/cldr/cldr-aux/charts/34/supplemental/language_plural_rules.html)"
+  },
+  "theme.SearchPage.existingResultsTitle": {
+    "message": "「{query}」的搜索结果",
+    "description": "The search page title for non-empty query"
+  },
+  "theme.SearchPage.emptyResultsTitle": {
+    "message": "在文档中搜索",
+    "description": "The search page title for empty query"
+  },
+  "theme.SearchPage.inputPlaceholder": {
+    "message": "在此输入搜索字词",
+    "description": "The placeholder for search page input"
+  },
+  "theme.SearchPage.inputLabel": {
+    "message": "搜索",
+    "description": "The ARIA label for search page input"
+  },
+  "theme.SearchPage.algoliaLabel": {
+    "message": "通过 Algolia 搜索",
+    "description": "The ARIA label for Algolia mention"
+  },
+  "theme.SearchPage.noResultsText": {
+    "message": "未找到任何结果",
+    "description": "The paragraph for empty search result"
+  },
+  "theme.SearchPage.fetchingNewResults": {
+    "message": "正在获取新的搜索结果...",
+    "description": "The paragraph for fetching new search results"
+  },
+  "theme.SearchBar.label": {
+    "message": "搜索",
+    "description": "The ARIA label and placeholder for search button"
+  },
+  "theme.SearchModal.searchBox.resetButtonTitle": {
+    "message": "清除查询",
+    "description": "The label and ARIA label for search box reset button"
+  },
+  "theme.SearchModal.searchBox.cancelButtonText": {
+    "message": "取消",
+    "description": "The label and ARIA label for search box cancel button"
+  },
+  "theme.SearchModal.startScreen.recentSearchesTitle": {
+    "message": "最近搜索",
+    "description": "The title for recent searches"
+  },
+  "theme.SearchModal.startScreen.noRecentSearchesText": {
+    "message": "没有最近搜索",
+    "description": "The text when no recent searches"
+  },
+  "theme.SearchModal.startScreen.saveRecentSearchButtonTitle": {
+    "message": "保存这个搜索",
+    "description": "The label for save recent search button"
+  },
+  "theme.SearchModal.startScreen.removeRecentSearchButtonTitle": {
+    "message": "从历史记录中删除这个搜索",
+    "description": "The label for remove recent search button"
+  },
+  "theme.SearchModal.startScreen.favoriteSearchesTitle": {
+    "message": "收藏",
+    "description": "The title for favorite searches"
+  },
+  "theme.SearchModal.startScreen.removeFavoriteSearchButtonTitle": {
+    "message": "从收藏列表中删除这个搜索",
+    "description": "The label for remove favorite search button"
+  },
+  "theme.SearchModal.errorScreen.titleText": {
+    "message": "无法获取结果",
+    "description": "The title for error screen of search modal"
+  },
+  "theme.SearchModal.errorScreen.helpText": {
+    "message": "你可能需要检查网络连接。",
+    "description": "The help text for error screen of search modal"
+  },
+  "theme.SearchModal.footer.selectText": {
+    "message": "选中",
+    "description": "The explanatory text of the action for the enter key"
+  },
+  "theme.SearchModal.footer.selectKeyAriaLabel": {
+    "message": "Enter 键",
+    "description": "The ARIA label for the Enter key button that makes the selection"
+  },
+  "theme.SearchModal.footer.navigateText": {
+    "message": "导航",
+    "description": "The explanatory text of the action for the Arrow up and Arrow down key"
+  },
+  "theme.SearchModal.footer.navigateUpKeyAriaLabel": {
+    "message": "向上键",
+    "description": "The ARIA label for the Arrow up key button that makes the navigation"
+  },
+  "theme.SearchModal.footer.navigateDownKeyAriaLabel": {
+    "message": "向下键",
+    "description": "The ARIA label for the Arrow down key button that makes the navigation"
+  },
+  "theme.SearchModal.footer.closeText": {
+    "message": "关闭",
+    "description": "The explanatory text of the action for Escape key"
+  },
+  "theme.SearchModal.footer.closeKeyAriaLabel": {
+    "message": "Esc 键",
+    "description": "The ARIA label for the Escape key button that close the modal"
+  },
+  "theme.SearchModal.footer.searchByText": {
+    "message": "搜索提供",
+    "description": "The text explain that the search is making by Algolia"
+  },
+  "theme.SearchModal.noResultsScreen.noResultsText": {
+    "message": "没有结果：",
+    "description": "The text explains that there are no results for the following search"
+  },
+  "theme.SearchModal.noResultsScreen.suggestedQueryText": {
+    "message": "试试搜索",
+    "description": "The text for the suggested query when no results are found for the following search"
+  },
+  "theme.SearchModal.noResultsScreen.reportMissingResultsText": {
+    "message": "认为这个查询应该有结果？",
+    "description": "The text for the question where the user thinks there are missing results"
+  },
+  "theme.SearchModal.noResultsScreen.reportMissingResultsLinkText": {
+    "message": "请告知我们。",
+    "description": "The text for the link to report missing results"
+  },
+  "theme.SearchModal.placeholder": {
+    "message": "搜索文档",
+    "description": "The placeholder of the input of the DocSearch pop-up modal"
+  },
+  "theme.ErrorPageContent.tryAgain": {
+    "message": "重试",
+    "description": "The label of the button to try again rendering when the React error boundary captures an error"
+  },
+  "theme.common.skipToMainContent": {
+    "message": "跳到主要内容",
+    "description": "The skip to content label used for accessibility, allowing to rapidly navigate to main content with keyboard tab/enter navigation"
+  },
+  "theme.tags.tagsPageTitle": {
+    "message": "标签",
+    "description": "The title of the tag list page"
+  },
+  "theme.unlistedContent.title": {
+    "message": "未列出页",
+    "description": "The unlisted content banner title"
+  },
+  "theme.unlistedContent.message": {
+    "message": "此页面未列出。搜索引擎不会对其索引，只有拥有直接链接的用户才能访问。",
+    "description": "The unlisted content banner message"
+  }
+}
diff --git a/docs/docusaurus/i18n/zh/docusaurus-plugin-content-docs/current.json b/docs/docusaurus/i18n/zh/docusaurus-plugin-content-docs/current.json
new file mode 100644
index 00000000000000..6533e4b9ea4711
--- /dev/null
+++ b/docs/docusaurus/i18n/zh/docusaurus-plugin-content-docs/current.json
@@ -0,0 +1,554 @@
+{
+  "version.label": {
+    "message": "current",
+    "description": "The label for version current"
+  },
+  "sidebar.docs.category.Introduction to StarRocks": {
+    "message": "产品简介",
+    "description": "The label for category Introduction to StarRocks in sidebar docs"
+  },
+  "sidebar.docs.category.Quick Start": {
+    "message": "快速开始",
+    "description": "The label for category Quick Start in sidebar docs"
+  },
+  "sidebar.docs.category.Project Help": {
+    "message": "技术支持",
+    "description": "The label for category Project Help in sidebar docs"
+  },
+  "sidebar.docs.category.Deployment": {
+    "message": "部署 StarRocks",
+    "description": "The label for category Deployment in sidebar docs"
+  },
+  "sidebar.docs.category.Preparation": {
+    "message": "前期准备",
+    "description": "The label for category Preparation in sidebar docs"
+  },
+  "sidebar.docs.category.Shared-nothing deployment": {
+    "message": "存算一体模式部署",
+    "description": "The label for category Shared-nothing deployment in sidebar docs"
+  },
+  "sidebar.docs.category.Shared-data deployment": {
+    "message": "存算分离模式部署",
+    "description": "The label for category Shared-data deployment in sidebar docs"
+  },
+  "sidebar.docs.category.Manage your deployment": {
+    "message": "后期管理",
+    "description": "The label for category Manage your deployment in sidebar docs"
+  },
+  "sidebar.docs.category.Table Design": {
+    "message": "表设计",
+    "description": "The label for category Table Design in sidebar docs"
+  },
+  "sidebar.docs.category.Table types": {
+    "message": "表类型",
+    "description": "The label for category Table types in sidebar docs"
+  },
+  "sidebar.docs.category.Data distribution": {
+    "message": "数据分布",
+    "description": "The label for category Data distribution in sidebar docs"
+  },
+  "sidebar.docs.category.Indexes": {
+    "message": "索引",
+    "description": "The label for category Indexes in sidebar docs"
+  },
+  "sidebar.docs.category.Data Loading": {
+    "message": "导入数据",
+    "description": "The label for category Data Loading in sidebar docs"
+  },
+  "sidebar.docs.category.Loading overview": {
+    "message": "导入概览",
+    "description": "The label for category Loading overview in sidebar docs"
+  },
+  "sidebar.docs.category.Load from Object Storage": {
+    "message": "从对象存储导入",
+    "description": "The label for category Load from Object Storage in sidebar docs"
+  },
+  "sidebar.docs.category.Load data from Apache Kafka": {
+    "message": "从 Apache Kafka® 导入",
+    "description": "The label for category Load data from Apache Kafka in sidebar docs"
+  },
+  "sidebar.docs.category.Load data from Apache Spark": {
+    "message": "从 Apache Spark™ 导入",
+    "description": "The label for category Load data from Apache Spark in sidebar docs"
+  },
+  "sidebar.docs.category.Data Unloading": {
+    "message": "导出数据",
+    "description": "The label for category Data Unloading in sidebar docs"
+  },
+  "sidebar.docs.category.Data Lakes": {
+    "message": "数据湖",
+    "description": "The label for category Data Lakes in sidebar docs"
+  },
+  "sidebar.docs.category.Catalog": {
+    "message": "数据目录",
+    "description": "The label for category Catalog in sidebar docs"
+  },
+  "sidebar.docs.category.Data cache": {
+    "message": "Data cache",
+    "description": "The label for category Data cache in sidebar docs"
+  },
+  "sidebar.docs.category.Query Acceleration": {
+    "message": "查询加速",
+    "description": "The label for category Query Acceleration in sidebar docs"
+  },
+  "sidebar.docs.category.Asynchronous materialized views": {
+    "message": "异步物化视图",
+    "description": "The label for category Asynchronous materialized views in sidebar docs"
+  },
+  "sidebar.docs.category.Use cases": {
+    "message": "使用场景",
+    "description": "The label for category Use cases in sidebar docs"
+  },
+  "sidebar.docs.category.Computing the number of distinct values": {
+    "message": "数据去重",
+    "description": "The label for category Computing the number of distinct values in sidebar docs"
+  },
+  "sidebar.docs.category.Integrations": {
+    "message": "外部系统集成",
+    "description": "The label for category Integrations in sidebar docs"
+  },
+  "sidebar.docs.category.Cloud Authentication": {
+    "message": "CSP 认证鉴权",
+    "description": "The label for category Cloud Authentication in sidebar docs"
+  },
+  "sidebar.docs.category.Streaming Data": {
+    "message": "实时导入",
+    "description": "The label for category Streaming Data in sidebar docs"
+  },
+  "sidebar.docs.category.Apache Kafka": {
+    "message": "Apache Kafka",
+    "description": "The label for category Apache Kafka in sidebar docs"
+  },
+  "sidebar.docs.category.StarRocks Pipe": {
+    "message": "StarRocks Pipe",
+    "description": "The label for category StarRocks Pipe in sidebar docs"
+  },
+  "sidebar.docs.category.Batch Loading Data": {
+    "message": "批量导入",
+    "description": "The label for category Batch Loading Data in sidebar docs"
+  },
+  "sidebar.docs.category.Loading Tools": {
+    "message": "导入工具",
+    "description": "The label for category Loading Tools in sidebar docs"
+  },
+  "sidebar.docs.category.BI Tools": {
+    "message": "BI 工具",
+    "description": "The label for category BI Tools in sidebar docs"
+  },
+  "sidebar.docs.category.IDE Tools": {
+    "message": "IDE 工具",
+    "description": "The label for category IDE Tools in sidebar docs"
+  },
+  "sidebar.docs.category.Administration": {
+    "message": "管理手册",
+    "description": "The label for category Administration in sidebar docs"
+  },
+  "sidebar.docs.category.Configuration": {
+    "message": "配置项",
+    "description": "The label for category Configuration in sidebar docs"
+  },
+  "sidebar.docs.category.Management": {
+    "message": "运维集群",
+    "description": "The label for category Management in sidebar docs"
+  },
+  "sidebar.docs.category.Monitor and Alert": {
+    "message": "监控报警",
+    "description": "The label for category Monitor and Alert in sidebar docs"
+  },
+  "sidebar.docs.category.Resource management": {
+    "message": "管理资源",
+    "description": "The label for category Resource management in sidebar docs"
+  },
+  "sidebar.docs.category.User Privileges and Authentication": {
+    "message": "管理用户权限",
+    "description": "The label for category User Privileges and Authentication in sidebar docs"
+  },
+  "sidebar.docs.category.Performance Tuning": {
+    "message": "性能调优",
+    "description": "The label for category Performance Tuning in sidebar docs"
+  },
+  "sidebar.docs.category.Query Profile": {
+    "message": "Query Profile",
+    "description": "The label for category Query Profile in sidebar docs"
+  },
+  "sidebar.docs.category.Reference": {
+    "message": "参考手册",
+    "description": "The label for category Reference in sidebar docs"
+  },
+  "sidebar.docs.category.Data Types": {
+    "message": "数据类型",
+    "description": "The label for category Data Types in sidebar docs"
+  },
+  "sidebar.docs.category.Numeric": {
+    "message": "数值类型",
+    "description": "The label for category Numeric in sidebar docs"
+  },
+  "sidebar.docs.category.String": {
+    "message": "字符串类型",
+    "description": "The label for category String in sidebar docs"
+  },
+  "sidebar.docs.category.Date and Time": {
+    "message": "日期类型",
+    "description": "The label for category Date and Time in sidebar docs"
+  },
+  "sidebar.docs.category.Semi-structured": {
+    "message": "半结构化类型",
+    "description": "The label for category Semi-structured in sidebar docs"
+  },
+  "sidebar.docs.category.Other": {
+    "message": "其他类型",
+    "description": "The label for category Other in sidebar docs"
+  },
+  "sidebar.docs.category.SQL Statements": {
+    "message": "SQL 参考",
+    "description": "The label for category SQL Statements in sidebar docs"
+  },
+  "sidebar.docs.category.SQL Statements.link.generated-index.title": {
+    "message": "SQL Statements",
+    "description": "The generated-index page title for category SQL Statements in sidebar docs"
+  },
+  "sidebar.docs.category.User account management": {
+    "message": "用户账户管理",
+    "description": "The label for category User account management in sidebar docs"
+  },
+  "sidebar.docs.category.Cluster management": {
+    "message": "集群管理",
+    "description": "The label for category Cluster management in sidebar docs"
+  },
+  "sidebar.docs.category.Nodes and processes": {
+    "message": "节点和进程",
+    "description": "The label for category Nodes and processes in sidebar docs"
+  },
+  "sidebar.docs.category.Configuration variables": {
+    "message": "系统配置和变量",
+    "description": "The label for category Configuration variables in sidebar docs"
+  },
+  "sidebar.docs.category.Resource group": {
+    "message": "资源组",
+    "description": "The label for category Resource group in sidebar docs"
+  },
+  "sidebar.docs.category.Storage volume": {
+    "message": "存储卷",
+    "description": "The label for category Storage volume in sidebar docs"
+  },
+  "sidebar.docs.category.Tablet and replica": {
+    "message": "Tablet，Replica 检查修复",
+    "description": "The label for category Tablet and replica in sidebar docs"
+  },
+  "sidebar.docs.category.File": {
+    "message": "文件",
+    "description": "The label for category File in sidebar docs"
+  },
+  "sidebar.docs.category.SQL blacklist": {
+    "message": "SQL 黑名单",
+    "description": "The label for category SQL blacklist in sidebar docs"
+  },
+  "sidebar.docs.category.Plugin": {
+    "message": "插件",
+    "description": "The label for category Plugin in sidebar docs"
+  },
+  "sidebar.docs.category.Execution plan and profile": {
+    "message": "执行计划和 Profile",
+    "description": "The label for category Execution plan and profile in sidebar docs"
+  },
+  "sidebar.docs.category.Loading and unloading": {
+    "message": "导入导出",
+    "description": "The label for category Loading and unloading in sidebar docs"
+  },
+  "sidebar.docs.category.ETL": {
+    "message": "ETL",
+    "description": "The label for category ETL in sidebar docs"
+  },
+  "sidebar.docs.category.pipe": {
+    "message": "pipe",
+    "description": "The label for category pipe in sidebar docs"
+  },
+  "sidebar.docs.category.routine_load": {
+    "message": "routine_load",
+    "description": "The label for category routine_load in sidebar docs"
+  },
+  "sidebar.docs.category.unloading": {
+    "message": "导入导出",
+    "description": "The label for category unloading in sidebar docs"
+  },
+  "sidebar.docs.category.Database": {
+    "message": "Database",
+    "description": "The label for category Database in sidebar docs"
+  },
+  "sidebar.docs.category.Resource": {
+    "message": "资源",
+    "description": "The label for category Resource in sidebar docs"
+  },
+  "sidebar.docs.category.Table, bucket, partition, and index": {
+    "message": "表，分区，分桶，索引",
+    "description": "The label for category Table, bucket, partition, and index in sidebar docs"
+  },
+  "sidebar.docs.category.View": {
+    "message": "视图",
+    "description": "The label for category View in sidebar docs"
+  },
+  "sidebar.docs.category.Materialized View": {
+    "message": "物化视图",
+    "description": "The label for category Materialized View in sidebar docs"
+  },
+  "sidebar.docs.category.Function": {
+    "message": "函数",
+    "description": "The label for category Function in sidebar docs"
+  },
+  "sidebar.docs.category.CBO statistics": {
+    "message": "CBO 统计信息",
+    "description": "The label for category CBO statistics in sidebar docs"
+  },
+  "sidebar.docs.category.Backup and restore": {
+    "message": "备份与恢复",
+    "description": "The label for category Backup and restore in sidebar docs"
+  },
+  "sidebar.docs.category.SQL Functions": {
+    "message": "函数参考",
+    "description": "The label for category SQL Functions in sidebar docs"
+  },
+  "sidebar.docs.category.aggregate-functions": {
+    "message": "聚合函数",
+    "description": "The label for category aggregate-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.array-functions": {
+    "message": "Array 函数",
+    "description": "The label for category array-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.binary-functions": {
+    "message": "Binary 函数",
+    "description": "The label for category binary-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.bit-functions": {
+    "message": "Bit 函数",
+    "description": "The label for category bit-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.bitmap-functions": {
+    "message": "Bitmap 函数",
+    "description": "The label for category bitmap-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.condition-functions": {
+    "message": "条件函数",
+    "description": "The label for category condition-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.crytographic-functions": {
+    "message": "加密函数",
+    "description": "The label for category crytographic-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.date-time-functions": {
+    "message": "时间日期函数",
+    "description": "The label for category date-time-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.dict-functions": {
+    "message": "字典函数",
+    "description": "The label for category dict-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.hash-functions": {
+    "message": "Hash 函数",
+    "description": "The label for category hash-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.json-functions": {
+    "message": "JSON 函数",
+    "description": "The label for category json-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.json-constructor-functions": {
+    "message": "JSON 构造函数",
+    "description": "The label for category json-constructor-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.json-query-and-processing-functions": {
+    "message": "JSON 查询和处理函数",
+    "description": "The label for category json-query-and-processing-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.like-predicate-functions": {
+    "message": "模糊/正则匹配函数",
+    "description": "The label for category like-predicate-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.map-functions": {
+    "message": "Map 函数",
+    "description": "The label for category map-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.math-functions": {
+    "message": "数学函数",
+    "description": "The label for category math-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.percentile-functions": {
+    "message": "百分位函数",
+    "description": "The label for category percentile-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.scalar-functions": {
+    "message": "标量函数",
+    "description": "The label for category scalar-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.spatial-functions": {
+    "message": "地理位置函数",
+    "description": "The label for category spatial-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.string-functions": {
+    "message": "字符串函数",
+    "description": "The label for category string-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.struct-functions": {
+    "message": "Struct 函数",
+    "description": "The label for category struct-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.table-functions": {
+    "message": "table-functions",
+    "description": "The label for category table-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.utility-functions": {
+    "message": "工具函数",
+    "description": "The label for category utility-functions in sidebar.docs"
+  },
+  "sidebar.docs.category.Information Schema": {
+    "message": "Information Schema",
+    "description": "The label for category Information Schema in sidebar docs"
+  },
+  "sidebar.docs.category.System Metadatabase": {
+    "message": "System Metadatabase",
+    "description": "The label for category System Metadatabase in sidebar docs"
+  },
+  "sidebar.docs.category.HTTP API": {
+    "message": "HTTP API",
+    "description": "The label for category HTTP API in sidebar docs"
+  },
+  "sidebar.docs.category.FAQ": {
+    "message": "常见问题解答",
+    "description": "The label for category FAQ in sidebar docs"
+  },
+  "sidebar.docs.category.Data Migration": {
+    "message": "Data Migration",
+    "description": "The label for category Data Migration in sidebar docs"
+  },
+  "sidebar.docs.category.Benchmarks": {
+    "message": "性能测试",
+    "description": "The label for category Benchmarks in sidebar docs"
+  },
+  "sidebar.docs.category.Developers": {
+    "message": "开发指南",
+    "description": "The label for category Developers in sidebar docs"
+  },
+  "sidebar.docs.category.build-starrocks": {
+    "message": "build-starrocks",
+    "description": "The label for category build-starrocks in sidebar docs"
+  },
+  "sidebar.docs.category.code-style-guides": {
+    "message": "code-style-guides",
+    "description": "The label for category code-style-guides in sidebar docs"
+  },
+  "sidebar.docs.category.development-environment": {
+    "message": "development-environment",
+    "description": "The label for category development-environment in sidebar docs"
+  },
+  "sidebar.docs.category.trace-tools": {
+    "message": "trace-tools",
+    "description": "The label for category trace-tools in sidebar docs"
+  },
+  "sidebar.docs.link.Kettle connector": {
+    "message": "Kettle connector",
+    "description": "The label for link Kettle connector in sidebar docs, linking to https://github.com/StarRocks/starrocks-connector-for-kettle"
+  },
+  "sidebar.docs.link.DBT": {
+    "message": "DBT",
+    "description": "The label for link DBT in sidebar docs, linking to https://github.com/StarRocks/dbt-starrocks/blob/main/README.md"
+  },
+  "sidebar.docs.category.Aggregate": {
+    "message": "聚合函数",
+    "description": "The label for category Aggregate in sidebar docs"
+  },
+  "sidebar.docs.category.Array": {
+    "message": "Array 函数",
+    "description": "The label for category Array in sidebar docs"
+  },
+  "sidebar.docs.category.Binary": {
+    "message": "Binary 函数",
+    "description": "The label for category Binary in sidebar docs"
+  },
+  "sidebar.docs.category.Bit": {
+    "message": "Bit 函数",
+    "description": "The label for category Bit in sidebar docs"
+  },
+  "sidebar.docs.category.Bitmap": {
+    "message": "Bitmap 函数",
+    "description": "The label for category Bitmap in sidebar docs"
+  },
+  "sidebar.docs.category.Condition": {
+    "message": "条件函数",
+    "description": "The label for category Condition in sidebar docs"
+  },
+  "sidebar.docs.category.Cryptographic": {
+    "message": "加密函数",
+    "description": "The label for category Cryptographic in sidebar docs"
+  },
+  "sidebar.docs.category.Date and time": {
+    "message": "时间日期函数",
+    "description": "The label for category Date and time in sidebar docs"
+  },
+  "sidebar.docs.category.Dictionary": {
+    "message": "字典函数",
+    "description": "The label for category Dictionary in sidebar docs"
+  },
+  "sidebar.docs.category.Hash": {
+    "message": "Hash 函数",
+    "description": "The label for category Hash in sidebar docs"
+  },
+  "sidebar.docs.category.JSON": {
+    "message": "JSON 函数",
+    "description": "The label for category JSON in sidebar docs"
+  },
+  "sidebar.docs.category.JSON Constructor": {
+    "message": "JSON 构造函数",
+    "description": "The label for category JSON Constructor in sidebar docs"
+  },
+  "sidebar.docs.category.JSON query and processing": {
+    "message": "JSON 查询和处理函数",
+    "description": "The label for category JSON query and processing in sidebar docs"
+  },
+  "sidebar.docs.category.Pattern matching": {
+    "message": "模糊/正则匹配函数",
+    "description": "The label for category Pattern matching in sidebar docs"
+  },
+  "sidebar.docs.category.Map": {
+    "message": "Map 函数",
+    "description": "The label for category Map in sidebar docs"
+  },
+  "sidebar.docs.category.Math": {
+    "message": "数学函数",
+    "description": "The label for category Math in sidebar docs"
+  },
+  "sidebar.docs.category.Percentile": {
+    "message": "百分位函数",
+    "description": "The label for category Percentile in sidebar docs"
+  },
+  "sidebar.docs.category.Scalar": {
+    "message": "标量函数",
+    "description": "The label for category Scalar in sidebar docs"
+  },
+  "sidebar.docs.category.Spatial": {
+    "message": "地理位置函数",
+    "description": "The label for category Spatial in sidebar docs"
+  },
+  "sidebar.docs.category.Struct": {
+    "message": "Struct 函数",
+    "description": "The label for category Struct in sidebar docs"
+  },
+  "sidebar.docs.category.Table": {
+    "message": "Table",
+    "description": "The label for category Table in sidebar docs"
+  },
+  "sidebar.docs.category.Utility": {
+    "message": "工具函数",
+    "description": "The label for category Utility in sidebar docs"
+  },
+  "sidebar.docs.category.Data types": {
+    "message": "数据类型",
+    "description": "The label for category Data types in sidebar docs"
+  },
+  "sidebar.docs.category.SQL statements": {
+    "message": "SQL 参考",
+    "description": "The label for category SQL statements in sidebar docs"
+  },
+  "sidebar.docs.category.系统元数据库": {
+    "message": "系统元数据库",
+    "description": "The label for category 系统元数据库 in sidebar docs"
+  }
+}
diff --git a/docs/docusaurus/i18n/zh/docusaurus-theme-classic/footer.json b/docs/docusaurus/i18n/zh/docusaurus-theme-classic/footer.json
new file mode 100644
index 00000000000000..297a8736f8a0aa
--- /dev/null
+++ b/docs/docusaurus/i18n/zh/docusaurus-theme-classic/footer.json
@@ -0,0 +1,14 @@
+{
+  "link.title.Docs": {
+    "message": "Docs",
+    "description": "The title of the footer links column with title=Docs in the footer"
+  },
+  "link.item.label.Documentation": {
+    "message": "Documentation",
+    "description": "The label of footer link with label=Documentation linking to /docs/introduction/StarRocks_intro"
+  },
+  "copyright": {
+    "message": "Docs built with Docusaurus.",
+    "description": "The footer copyright"
+  }
+}
diff --git a/docs/docusaurus/i18n/zh/docusaurus-theme-classic/navbar.json b/docs/docusaurus/i18n/zh/docusaurus-theme-classic/navbar.json
new file mode 100644
index 00000000000000..c160ba7a8f155b
--- /dev/null
+++ b/docs/docusaurus/i18n/zh/docusaurus-theme-classic/navbar.json
@@ -0,0 +1,18 @@
+{
+  "title": {
+    "message": "StarRocks",
+    "description": "The title in the navbar"
+  },
+  "logo.alt": {
+    "message": "StarRocks Logo",
+    "description": "The alt text of navbar logo"
+  },
+  "item.label.Documentation": {
+    "message": "Documentation",
+    "description": "Navbar item with label Documentation"
+  },
+  "item.label.GitHub": {
+    "message": "GitHub",
+    "description": "Navbar item with label GitHub"
+  }
+}
diff --git a/docs/docusaurus/package.json b/docs/docusaurus/package.json
index 98cbb0aa4dc958..293bdc052bd247 100644
--- a/docs/docusaurus/package.json
+++ b/docs/docusaurus/package.json
@@ -18,9 +18,9 @@
   "dependencies": {
     "@algolia/client-search": "^4.20.0",
     "@docsearch/react": "3",
-    "@docusaurus/core": "^3.1.1",
-    "@docusaurus/preset-classic": "^3.1.1",
-    "@docusaurus/theme-search-algolia": "^3.1.1",
+    "@docusaurus/core": "^3.5.2",
+    "@docusaurus/preset-classic": "^3.5.2",
+    "@docusaurus/theme-search-algolia": "^3.5.2",
     "@mdx-js/react": "^3.0.0",
     "clsx": "^2.0.0",
     "fs-extra": "^11.1.1",
@@ -29,8 +29,8 @@
     "react-dom": "^18.2.0"
   },
   "devDependencies": {
-    "@docusaurus/module-type-aliases": "^3.1.1",
-    "@docusaurus/types": "^3.1.1"
+    "@docusaurus/module-type-aliases": "^3.5.2",
+    "@docusaurus/types": "^3.5.2"
   },
   "browserslist": {
     "production": [
diff --git a/docs/docusaurus/scripts/docker-build.sh b/docs/docusaurus/scripts/docker-build.sh
index 0ca404be73d506..d0c2fe89a34496 100755
--- a/docs/docusaurus/scripts/docker-build.sh
+++ b/docs/docusaurus/scripts/docker-build.sh
@@ -6,6 +6,7 @@ docker run --rm --interactive --tty \
 	-e DISABLE_VERSIONING=true \
 	--volume $DOCS_DIR/docusaurus/sidebars.json:/app/docusaurus/sidebars.json \
 	--volume $DOCS_DIR/en:/app/docusaurus/docs \
+	--volume "$DOCS_DIR/docusaurus/i18n:/app/docusaurus/i18n" \
 	--volume "$DOCS_DIR/zh:/app/docusaurus/i18n/zh/docusaurus-plugin-content-docs/current" \
 	-p 3000:3000 \
 	docs-build /app/docusaurus/scripts/build-and-serve.sh
diff --git a/docs/docusaurus/sidebars.json b/docs/docusaurus/sidebars.json
index 3c0f625c1f1873..2a49d57a3ee3fa 100644
--- a/docs/docusaurus/sidebars.json
+++ b/docs/docusaurus/sidebars.json
@@ -1,5 +1,5 @@
 {
-    "English": [
+    "docs": [
         "introduction/StarRocks_intro",
         {
             "type": "category",
@@ -84,10 +84,13 @@
                         "id": "deployment/shared_data/shared_data"
                     },
                     "items": [
+                        "deployment/shared_data/hdfs",
+                        "deployment/shared_data/other",
                         "deployment/shared_data/s3",
                         "deployment/shared_data/gcs",
                         "deployment/shared_data/azure",
                         "deployment/shared_data/minio",
+                        "deployment/shared_data/hdfs",
                         "deployment/shared_data/feature-support-shared-data"
                     ]
                 },
@@ -202,6 +205,7 @@
                 },
                 "loading/StreamLoad",
                 "loading/hdfs_load",
+                "loading/cloud_storage_load",
                 {
                     "type": "category",
                     "label": "Load data from Apache Kafka",
@@ -334,23 +338,9 @@
                                 "using_starrocks/create_partitioned_materialized_view"
                             ]
                         },
-                        {
-                            "type": "category",
-                            "label": "Usage",
-                            "link": {
-                                "type": "doc",
-                                "id": "using_starrocks/usage/intro"
-                            },
-                            "items": [
-                                "using_starrocks/usage/create",
-                                "using_starrocks/usage/alter",
-                                "using_starrocks/usage/drop",
-                                "using_starrocks/usage/show",
-                                "using_starrocks/usage/information_schema-materialized_views",
-                                "using_starrocks/troubleshooting_asynchronous_materialized_views",
-                                "using_starrocks/feature-support-asynchronous-materialized-views"
-                            ]
-                        }
+                        "using_starrocks/mv_ref",
+                        "using_starrocks/troubleshooting_asynchronous_materialized_views",
+                        "using_starrocks/feature-support-asynchronous-materialized-views"
                     ]
                 },
                 "using_starrocks/Colocate_join",
@@ -631,816 +621,39 @@
             "type": "category",
             "label": "Reference",
             "link": {
-                "type": "doc",
-                "id": "reference/reference"
+                "type": "generated-index"
             },
             "items": [
                 {
-                    "type": "category",
-                    "label": "Data Types",
-                    "link": {
-                        "type": "doc",
-                        "id": "sql-reference/data-types/data-type-list"
-                    },
-                    "items": [
-                        {
-                            "type": "category",
-                            "label": "Numeric",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/data-types/numeric/numeric"
-                            },
-                            "items": [
-                                "sql-reference/data-types/numeric/TINYINT",
-                                "sql-reference/data-types/numeric/SMALLINT",
-                                "sql-reference/data-types/numeric/INT",
-                                "sql-reference/data-types/numeric/BIGINT",
-                                "sql-reference/data-types/numeric/LARGEINT",
-                                "sql-reference/data-types/numeric/DECIMAL",
-                                "sql-reference/data-types/numeric/DOUBLE",
-                                "sql-reference/data-types/numeric/FLOAT",
-                                "sql-reference/data-types/numeric/BOOLEAN"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "String",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/data-types/string-type/string-type"
-                            },
-                            "items": [
-                                "sql-reference/data-types/string-type/STRING",
-                                "sql-reference/data-types/string-type/BINARY",
-                                "sql-reference/data-types/string-type/CHAR",
-                                "sql-reference/data-types/string-type/VARCHAR"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Date",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/data-types/date-types/date-types"
-                            },
-                            "items": [
-                                "sql-reference/data-types/date-types/DATE",
-                                "sql-reference/data-types/date-types/DATETIME"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Semi-structured",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/data-types/semi_structured/semi_structured"
-                            },
-                            "items": [
-                                "sql-reference/data-types/semi_structured/Array",
-                                "sql-reference/data-types/semi_structured/JSON",
-                                "sql-reference/data-types/semi_structured/Map",
-                                "sql-reference/data-types/semi_structured/STRUCT"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Other",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/data-types/other-data-types/other-data-types"
-                            },
-                            "items": [
-                                "sql-reference/data-types/other-data-types/BITMAP",
-                                "sql-reference/data-types/other-data-types/HLL"
-                            ]
-                        }
-                    ]
-                },
-                "sql-reference/sql-statements/keywords",
+                    "type": "autogenerated",
+                    "dirName": "sql-reference"
+                }
+            ]
+        },
+        {
+            "type": "category",
+            "label": "FAQ",
+            "link": {
+                "type": "doc",
+                "id": "faq/faq"
+            },
+            "items": [
+                "faq/Deploy_faq",
                 {
                     "type": "category",
-                    "label": "SQL Statements",
-                    "link": {
-                        "type": "doc",
-                        "id": "sql-reference/sql-statements/all-commands"
-                    },
+                    "label": "Data Migration",
                     "items": [
                         {
                             "type": "category",
-                            "label": "User Account Management",
+                            "label": "Data Loading",
                             "items": [
                                 {
                                     "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-statements/account-management"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Cluster Management",
-                            "items": [
-                                {
-                                    "type": "category",
-                                    "label": "Nodes and processes",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/ALTER_SYSTEM",
-                                        "sql-reference/sql-statements/Administration/CANCEL_DECOMMISSION",
-                                        "sql-reference/sql-statements/Administration/KILL",
-                                        "sql-reference/sql-statements/Administration/SHOW_BACKENDS",
-                                        "sql-reference/sql-statements/Administration/SHOW_BROKER",
-                                        "sql-reference/sql-statements/Administration/SHOW_COMPUTE_NODES",
-                                        "sql-reference/sql-statements/Administration/SHOW_FRONTENDS",
-                                        "sql-reference/sql-statements/Administration/SHOW_PROC",
-                                        "sql-reference/sql-statements/Administration/SHOW_PROCESSLIST",
-                                        "sql-reference/sql-statements/Administration/SHOW_RUNNING_QUERIES",
-                                        "sql-reference/sql-statements/Administration/ADD_BACKEND_BLACKLIST",
-                                        "sql-reference/sql-statements/Administration/DELETE_BACKEND_BLACKLIST",
-                                        "sql-reference/sql-statements/Administration/SHOW_BACKEND_BLACKLIST"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "Resource group",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/ALTER_RESOURCE_GROUP",
-                                        "sql-reference/sql-statements/Administration/CREATE_RESOURCE_GROUP",
-                                        "sql-reference/sql-statements/Administration/DROP_RESOURCE_GROUP",
-                                        "sql-reference/sql-statements/Administration/SHOW_RESOURCE_GROUP",
-                                        "sql-reference/sql-statements/Administration/SHOW_USAGE_RESOURCE_GROUPS"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "Storage volume",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/ALTER_STORAGE_VOLUME",
-                                        "sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME",
-                                        "sql-reference/sql-statements/Administration/DESC_STORAGE_VOLUME",
-                                        "sql-reference/sql-statements/Administration/DROP_STORAGE_VOLUME",
-                                        "sql-reference/sql-statements/Administration/SET_DEFAULT_STORAGE_VOLUME",
-                                        "sql-reference/sql-statements/Administration/SHOW_STORAGE_VOLUMES"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "Tablet and replica",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/ADMIN_CANCEL_REPAIR",
-                                        "sql-reference/sql-statements/Administration/ADMIN_CHECK_TABLET",
-                                        "sql-reference/sql-statements/Administration/ADMIN_REPAIR",
-                                        "sql-reference/sql-statements/Administration/ADMIN_SET_PARTITION_VERSION",
-                                        "sql-reference/sql-statements/Administration/ADMIN_SET_REPLICA_STATUS",
-                                        "sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_DISTRIBUTION",
-                                        "sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_STATUS",
-                                        "sql-reference/sql-statements/Administration/SHOW_TABLE_STATUS"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "Configurations and variables",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG",
-                                        "sql-reference/sql-statements/Administration/ADMIN_SHOW_CONFIG",
-                                        "sql-reference/sql-statements/Administration/SET",
-                                        "sql-reference/sql-statements/Administration/SHOW_VARIABLES"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "File",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/CREATE_FILE",
-                                        "sql-reference/sql-statements/Administration/DROP_FILE",
-                                        "sql-reference/sql-statements/Administration/SHOW_FILE"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "SQL Blacklist",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/ADD_SQLBLACKLIST",
-                                        "sql-reference/sql-statements/Administration/SHOW_SQLBLACKLIST",
-                                        "sql-reference/sql-statements/Administration/DELETE_SQLBLACKLIST"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "Plugin",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/INSTALL_PLUGIN",
-                                        "sql-reference/sql-statements/Administration/SHOW_PLUGINS",
-                                        "sql-reference/sql-statements/Administration/UNINSTALL_PLUGIN"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "Execution plan and profile",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/ANALYZE_PROFILE",
-                                        "sql-reference/sql-statements/Administration/EXPLAIN",
-                                        "sql-reference/sql-statements/Administration/EXPLAIN_ANALYZE",
-                                        "sql-reference/sql-statements/Administration/SHOW_PROFILELIST"
-                                    ]
-                                }
-                            ]
-                        },
-                        "sql-reference/sql-statements/general_DDL",
-                        "sql-reference/sql-statements/general_DML",
-                        {
-                            "type": "category",
-                            "label": "Loading, unloading",
-                            "items": [
-                                "sql-reference/sql-statements/data-manipulation/ALTER_LOAD",
-                                "sql-reference/sql-statements/data-manipulation/BROKER_LOAD",
-                                "sql-reference/sql-statements/data-manipulation/CANCEL_LOAD",
-                                "sql-reference/sql-statements/data-manipulation/INSERT",
-                                {
-                                    "type": "category",
-                                    "label": "ROUTINE LOAD",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD",
-                                        "sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD",
-                                        "sql-reference/sql-statements/data-manipulation/PAUSE_ROUTINE_LOAD",
-                                        "sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD_TASK",
-                                        "sql-reference/sql-statements/data-manipulation/STOP_ROUTINE_LOAD"
-                                    ]
-                                },
-                                "sql-reference/sql-statements/data-manipulation/SHOW_LOAD",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_TRANSACTION",
-                                "sql-reference/sql-statements/data-manipulation/SPARK_LOAD",
-                                "sql-reference/sql-statements/data-manipulation/STREAM_LOAD",
-                                {
-                                    "type": "category",
-                                    "label": "PIPE",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-manipulation/ALTER_PIPE",
-                                        "sql-reference/sql-statements/data-manipulation/CREATE_PIPE",
-                                        "sql-reference/sql-statements/data-manipulation/DROP_PIPE",
-                                        "sql-reference/sql-statements/data-manipulation/RETRY_FILE",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_PIPES",
-                                        "sql-reference/sql-statements/data-manipulation/SUSPEND_or_RESUME_PIPE"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "Unloading",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-manipulation/EXPORT",
-                                        "sql-reference/sql-statements/data-manipulation/CANCEL_EXPORT",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_EXPORT"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "ETL tasks",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-manipulation/DROP_TASK",
-                                        "sql-reference/sql-statements/data-manipulation/SUBMIT_TASK"
-                                    ]
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Catalog, database, resource",
-                            "items": [
-                                {
-                                    "type": "category",
-                                    "label": "Catalog",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG",
-                                        "sql-reference/sql-statements/data-definition/DROP_CATALOG",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "Database",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-definition/ALTER_DATABASE",
-                                        "sql-reference/sql-statements/data-definition/CREATE_DATABASE",
-                                        "sql-reference/sql-statements/data-definition/DROP_DATABASE",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_CREATE_DATABASE",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_DATA",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_DATABASES"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "Resource",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-definition/ALTER_RESOURCE",
-                                        "sql-reference/sql-statements/data-definition/CREATE_RESOURCE",
-                                        "sql-reference/sql-statements/data-definition/DROP_RESOURCE",
-                                        "sql-reference/sql-statements/data-definition/SHOW_RESOURCES"
-                                    ]
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Table, partition, bucket, index",
-                            "items": [
-                                "sql-reference/sql-statements/data-definition/ALTER_TABLE",
-                                "sql-reference/sql-statements/data-definition/CANCEL_ALTER_TABLE",
-                                "sql-reference/sql-statements/data-definition/CREATE_INDEX",
-                                "sql-reference/sql-statements/data-definition/CREATE_TABLE",
-                                "sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT",
-                                "sql-reference/sql-statements/data-definition/CREATE_TABLE_LIKE",
-                                "sql-reference/sql-statements/data-manipulation/DELETE",
-                                "sql-reference/sql-statements/data-definition/DROP_INDEX",
-                                "sql-reference/sql-statements/data-definition/DROP_TABLE",
-                                "sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE",
-                                "sql-reference/sql-statements/data-manipulation/SELECT",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_ALTER",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_DELETE",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_DYNAMIC_PARTITION_TABLES",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_FULL_COLUMNS",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_INDEX",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_PARTITIONS",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_TABLES",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_TABLET",
-                                "sql-reference/sql-statements/data-definition/TRUNCATE_TABLE",
-                                "sql-reference/sql-statements/data-manipulation/UPDATE"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "View, Materialized view",
-                            "items": [
-                                {
-                                    "type": "category",
-                                    "label": "View",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-definition/ALTER_VIEW",
-                                        "sql-reference/sql-statements/data-definition/CREATE_VIEW",
-                                        "sql-reference/sql-statements/data-definition/DROP_VIEW",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_CREATE_VIEW"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "Materialized view",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW",
-                                        "sql-reference/sql-statements/data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW",
-                                        "sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW",
-                                        "sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW",
-                                        "sql-reference/sql-statements/data-manipulation/REFRESH_MATERIALIZED_VIEW",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_CREATE_MATERIALIZED_VIEW",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW"
-                                    ]
+                                    "dirName": "faq/loading"
                                 }
                             ]
                         },
-                        {
-                            "type": "category",
-                            "label": "Function",
-                            "items": [
-                                "sql-reference/sql-statements/data-definition/CREATE_FUNCTION",
-                                "sql-reference/sql-statements/data-definition/DROP_FUNCTION",
-                                "sql-reference/sql-statements/data-definition/SHOW_FUNCTIONS"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "CBO statistics",
-                            "items": [
-                                "sql-reference/sql-statements/data-definition/ANALYZE_TABLE",
-                                "sql-reference/sql-statements/data-definition/CREATE_ANALYZE",
-                                "sql-reference/sql-statements/data-definition/DROP_ANALYZE",
-                                "sql-reference/sql-statements/data-definition/DROP_STATS",
-                                "sql-reference/sql-statements/data-definition/KILL_ANALYZE",
-                                "sql-reference/sql-statements/data-definition/SHOW_ANALYZE_JOB",
-                                "sql-reference/sql-statements/data-definition/SHOW_ANALYZE_STATUS",
-                                "sql-reference/sql-statements/data-definition/SHOW_META"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Backup and restore",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/sql-statements/data-definition/backup_restore/backup_restore"
-                            },
-                            "items": [
-                                "sql-reference/sql-statements/data-definition/backup_restore/BACKUP",
-                                "sql-reference/sql-statements/data-definition/backup_restore/CANCEL_BACKUP",
-                                "sql-reference/sql-statements/data-definition/backup_restore/CANCEL_RESTORE",
-                                "sql-reference/sql-statements/data-definition/backup_restore/CREATE_REPOSITORY",
-                                "sql-reference/sql-statements/data-definition/backup_restore/DROP_REPOSITORY",
-                                "sql-reference/sql-statements/data-definition/backup_restore/RECOVER",
-                                "sql-reference/sql-statements/data-definition/backup_restore/RESTORE",
-                                "sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_BACKUP",
-                                "sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_REPOSITORIES",
-                                "sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_SNAPSHOT"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Utility Commands",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-statements/Utility"
-                                }
-                            ]
-                        }
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "SQL Functions",
-                    "link": {
-                        "type": "doc",
-                        "id": "sql-reference/sql-functions/function-list"
-                    },
-                    "items": [
-                        "sql-reference/sql-functions/JAVA_UDF",
-                        "integrations/hive_bitmap_udf",
-                        "sql-reference/sql-functions/Window_function",
-                        "sql-reference/sql-functions/Lambda_expression",
-                        {
-                            "type": "category",
-                            "label": "Aggregate Functions",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/aggregate-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Array Functions",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/array-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Bit Functions",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/bit-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Bitmap Functions",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/bitmap-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "JSON Functions",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/sql-functions/json-functions/overview-of-json-functions-and-operators"
-                            },
-                            "items": [
-                                "sql-reference/sql-functions/json-functions/json-operators",
-                                {
-                                    "type": "category",
-                                    "label": "JSON constructor functions",
-                                    "link": {
-                                        "type": "doc",
-                                        "id": "cover_pages/functions_json_constructor"
-                                    },
-                                    "items": [
-                                        "sql-reference/sql-functions/json-functions/json-constructor-functions/json_array",
-                                        "sql-reference/sql-functions/json-functions/json-constructor-functions/json_object",
-                                        "sql-reference/sql-functions/json-functions/json-constructor-functions/parse_json"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "JSON query and processing functions",
-                                    "link": {
-                                        "type": "doc",
-                                        "id": "cover_pages/functions_json_query"
-                                    },
-                                    "items": [
-                                        {
-                                            "type": "autogenerated",
-                                            "dirName": "sql-reference/sql-functions/json-functions/json-query-and-processing-functions"
-                                        }
-                                    ]
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Map Functions",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/overview-pages/map-functions"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/map-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Binary Functions",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_binary"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/binary-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Conditional Functions",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_conditional"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/condition-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Cryptographic Functions",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_crypto"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/crytographic-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Date and Time Functions",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_date"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/date-time-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Geospatial Functions",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_geo"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/spatial-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Math Functions",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_math"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/math-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "String Functions",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_string"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/string-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Pattern Matching Functions",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_like"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/like-predicate-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Percentile Functions",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_percentile"
-                            },
-                            "items": [
-                                "sql-reference/sql-functions/percentile-functions/percentile_approx",
-                                "sql-reference/sql-functions/percentile-functions/percentile_cont",
-                                "sql-reference/sql-functions/percentile-functions/percentile_disc",
-                                "sql-reference/sql-functions/percentile-functions/percentile_approx_raw",
-                                "sql-reference/sql-functions/percentile-functions/percentile_empty",
-                                "sql-reference/sql-functions/percentile-functions/percentile_hash",
-                                "sql-reference/sql-functions/percentile-functions/percentile_union"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Scalar Functions",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_scalar"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/scalar-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Struct Functions",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_struct"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/struct-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Table Functions",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_table"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/table-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Utility Functions",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_utility"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/utility-functions"
-                                }
-                            ]
-                        },
-                        "sql-reference/sql-functions/cast",
-                        {
-                            "type": "category",
-                            "label": "Hash functions",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/hash-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Dictionary functions",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/dict-functions"
-                                }
-                            ]
-                        }
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "Information Schema",
-                    "link": {
-                        "type": "doc",
-                        "id": "reference/overview-pages/information_schema"
-                    },
-                    "items": [
-                        {
-                            "type": "autogenerated",
-                            "dirName": "reference/information_schema"
-                        }
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "System Metadatabase",
-                    "link": {
-                        "type": "doc",
-                        "id": "reference/overview-pages/sys"
-                    },
-                    "items": [
-                        {
-                            "type": "autogenerated",
-                            "dirName": "reference/sys"
-                        }
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "HTTP API",
-                    "link": {
-                        "type": "doc",
-                        "id": "reference/overview-pages/http_api"
-                    },
-                    "items": [
-                        {
-                            "type": "autogenerated",
-                            "dirName": "reference/HTTP_API"
-                        }
-                    ]
-                },
-                "sql-reference/sql-statements/auto_increment",
-                "sql-reference/sql-statements/generated_columns",
-                "sql-reference/sql-statements/prepared_statement",
-                "reference/System_variable",
-                "reference/user_defined_variables",
-                "reference/System_limit",
-                "reference/aws_iam_policies",
-                "reference/Error_code"
-            ]
-        },
-        {
-            "type": "category",
-            "label": "FAQ",
-            "link": {
-                "type": "doc",
-                "id": "faq/faq"
-            },
-            "items": [
-                "faq/Deploy_faq",
-                {
-                    "type": "category",
-                    "label": "Data Migration",
-                    "items": [
-                        {
-                            "type": "category",
-                            "label": "Data Loading",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "faq/loading"
-                                }
-                            ]
-                        },
-                        "faq/Exporting_faq"
+                        "faq/Exporting_faq"
                     ]
                 },
                 "faq/datalake",
@@ -1480,1488 +693,5 @@
                 }
             ]
         }
-    ],
-    "Chinese": [
-        "introduction/StarRocks_intro",
-        {
-            "type": "category",
-            "label": "产品简介",
-            "link": {
-                "type": "doc",
-                "id": "introduction/introduction"
-            },
-            "items": [
-                "introduction/what_is_starrocks",
-                "introduction/Architecture",
-                "introduction/Features"
-            ]
-        },
-        {
-            "type": "category",
-            "label": "快速开始",
-            "link": {
-                "type": "doc",
-                "id": "quick_start/quick_start"
-            },
-            "items": [
-                "quick_start/shared-nothing",
-                "quick_start/shared-data",
-                "quick_start/iceberg",
-                "quick_start/helm"
-            ]
-        },
-        {
-            "type": "category",
-            "label": "技术支持",
-            "link": {
-                "type": "doc",
-                "id": "project_help/project_help"
-            },
-            "items": [
-                "project_help/slack"
-            ]
-        },
-        {
-            "type": "category",
-            "label": "部署 StarRocks",
-            "link": {
-                "type": "doc",
-                "id": "deployment/deployment_overview"
-            },
-            "items": [
-                {
-                    "type": "category",
-                    "label": "前期准备",
-                    "link": {
-                        "type": "doc",
-                        "id": "cover_pages/deployment_preparation"
-                    },
-                    "items": [
-                        "deployment/deployment_prerequisites",
-                        "deployment/plan_cluster",
-                        "deployment/environment_configurations",
-                        "deployment/prepare_deployment_files"
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "存算一体模式部署",
-                    "link": {
-                        "type": "doc",
-                        "id": "cover_pages/shared_nothing_deployment"
-                    },
-                    "items": [
-                        "deployment/deploy_manually",
-                        "deployment/sr_operator",
-                        "deployment/helm"
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "存算分离模式部署",
-                    "link": {
-                        "type": "doc",
-                        "id": "deployment/shared_data/shared_data"
-                    },
-                    "items": [
-                        "deployment/shared_data/s3",
-                        "deployment/shared_data/gcs",
-                        "deployment/shared_data/azure",
-                        "deployment/shared_data/minio",
-                        "deployment/shared_data/hdfs",
-                        "deployment/shared_data/other",
-                        "deployment/shared_data/feature-support-shared-data"
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "后期管理",
-                    "link": {
-                        "type": "doc",
-                        "id": "cover_pages/manage_deployment"
-                    },
-                    "items": [
-                        "deployment/post_deployment_setup",
-                        "deployment/upgrade",
-                        "deployment/downgrade"
-                    ]
-                }
-            ]
-        },
-        {
-            "type": "category",
-            "label": "表设计",
-            "link": {
-                "type": "doc",
-                "id": "table_design/catalog_db_tbl"
-            },
-            "items": [
-                "table_design/StarRocks_table_design",
-                {
-                    "type": "category",
-                    "label": "表类型",
-                    "link": {
-                        "type": "doc",
-                        "id": "table_design/table_types/table_types"
-                    },
-                    "items": [
-                        "table_design/table_types/table_capabilities",
-                        "table_design/table_types/primary_key_table",
-                        "table_design/table_types/duplicate_key_table",
-                        "table_design/table_types/aggregate_table",
-                        "table_design/table_types/unique_key_table"
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "数据分布",
-                    "link": {
-                        "type": "doc",
-                        "id": "table_design/Data_distribution"
-                    },
-                    "items": [
-                        "table_design/expression_partitioning",
-                        "table_design/list_partitioning",
-                        "table_design/dynamic_partitioning",
-                        "table_design/Temporary_partition",
-                        "table_design/feature-support-data-distribution"
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "索引",
-                    "link": {
-                        "type": "doc",
-                        "id": "table_design/indexes/indexes_overview"
-                    },
-                    "items": [
-                        "table_design/indexes/Prefix_index_sort_key",
-                        "table_design/indexes/Bitmap_index",
-                        "table_design/indexes/Bloomfilter_index",
-                        "table_design/indexes/Ngram_Bloom_Filter_Index",
-                        "table_design/indexes/inverted_index"
-                    ]
-                },
-                "table_design/data_compression",
-                "table_design/hybrid_table"
-            ]
-        },
-        {
-            "type": "category",
-            "label": "导入数据",
-            "link": {
-                "type": "doc",
-                "id": "loading/loading"
-            },
-            "items": [
-                {
-                    "type": "category",
-                    "label": "导入概览",
-                    "link": {
-                        "type": "doc",
-                        "id": "loading/loading_introduction/loading_overview"
-                    },
-                    "items": [
-                        "loading/loading_introduction/Loading_intro",
-                        "loading/loading_introduction/loading_concepts",
-                        "loading/loading_introduction/loading_considerations",
-                        "loading/loading_introduction/feature-support-loading-and-unloading"
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "从对象存储导入",
-                    "link": {
-                        "type": "doc",
-                        "id": "loading/objectstorage"
-                    },
-                    "items": [
-                        "loading/s3",
-                        "loading/azure",
-                        "loading/gcs",
-                        "loading/minio"
-                    ]
-                },
-                "loading/StreamLoad",
-                "loading/hdfs_load",
-                "loading/cloud_storage_load",
-                {
-                    "type": "category",
-                    "label": "从 Apache Kafka® 导入",
-                    "link": {
-                        "type": "doc",
-                        "id": "cover_pages/loading_kafka"
-                    },
-                    "items": [
-                        "loading/Kafka-connector-starrocks",
-                        "loading/RoutineLoad"
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "从 Apache Spark™ 导入",
-                    "link": {
-                        "type": "doc",
-                        "id": "cover_pages/loading_spark"
-                    },
-                    "items": [
-                        "loading/Spark-connector-starrocks",
-                        "loading/SparkLoad"
-                    ]
-                },
-                "loading/InsertInto",
-                "loading/Stream_Load_transaction_interface",
-                "loading/Flink_cdc_load",
-                "loading/Flink-connector-starrocks",
-                "loading/Load_to_Primary_Key_tables",
-                "loading/Etl_in_loading",
-                "loading/loading_tools",
-                "loading/load_concept/strict_mode"
-            ]
-        },
-        {
-            "type": "category",
-            "label": "导出数据",
-            "link": {
-                "type": "doc",
-                "id": "unloading/unloading"
-            },
-            "items": [
-                "unloading/Export",
-                "unloading/Spark_connector",
-                "unloading/Flink_connector",
-                "unloading/unload_using_insert_into_files",
-                "unloading/feature-support-loading-and-unloading"
-            ]
-        },
-        {
-            "type": "category",
-            "label": "数据湖",
-            "link": {
-                "type": "doc",
-                "id": "data_source/data_lakes"
-            },
-            "items": [
-                {
-                    "type": "category",
-                    "label": "Catalog",
-                    "link": {
-                        "type": "doc",
-                        "id": "data_source/catalog/catalog_intro"
-                    },
-                    "items": [
-                        "data_source/catalog/catalog_overview",
-                        "data_source/catalog/default_catalog",
-                        "data_source/catalog/hive_catalog",
-                        "data_source/catalog/iceberg_catalog",
-                        "data_source/catalog/hudi_catalog",
-                        "data_source/catalog/deltalake_catalog",
-                        "data_source/catalog/jdbc_catalog",
-                        "data_source/catalog/elasticsearch_catalog",
-                        "data_source/catalog/paimon_catalog",
-                        "data_source/catalog/unified_catalog",
-                        "data_source/catalog/maxcompute_catalog",
-                        "data_source/catalog/kudu_catalog",
-                        "data_source/icebergtutorial",
-                        "data_source/catalog/query_external_data"
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "Data cache",
-                    "link": {
-                        "type": "doc",
-                        "id": "cover_pages/data_cache"
-                    },
-                    "items": [
-                        "data_source/data_cache",
-                        "data_source/data_cache_warmup",
-                        "data_source/data_cache_observe"
-                    ]
-                },
-                "data_source/External_table",
-                "data_source/file_external_table",
-                "data_source/datalake_faq",
-                "data_source/feature-support-data-lake-analytics"
-            ]
-        },
-        {
-            "type": "category",
-            "label": "查询加速",
-            "link": {
-                "type": "doc",
-                "id": "cover_pages/query_acceleration"
-            },
-            "items": [
-                "using_starrocks/Cost_based_optimizer",
-                "using_starrocks/Materialized_view-single_table",
-                {
-                    "type": "category",
-                    "label": "异步物化视图",
-                    "link": {
-                        "type": "doc",
-                        "id": "using_starrocks/Materialized_view"
-                    },
-                    "items": [
-                        {
-                            "type": "category",
-                            "label": "使用场景",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/mv_use_cases"
-                            },
-                            "items": [
-                                "using_starrocks/data_modeling_with_materialized_views",
-                                "using_starrocks/query_rewrite_with_materialized_views",
-                                "using_starrocks/data_lake_query_acceleration_with_materialized_views",
-                                "using_starrocks/create_partitioned_materialized_view"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Usage",
-                            "link": {
-                                "type": "doc",
-                                "id": "using_starrocks/usage/intro"
-                            },
-                            "items": [
-                                "using_starrocks/usage/create",
-                                "using_starrocks/usage/alter",
-                                "using_starrocks/usage/drop",
-                                "using_starrocks/usage/show",
-                                "using_starrocks/usage/information_schema-materialized_views",
-                                "using_starrocks/troubleshooting_asynchronous_materialized_views",
-                                "using_starrocks/feature-support-asynchronous-materialized-views"
-                            ]
-                        }
-                    ]
-                },
-                "using_starrocks/Colocate_join",
-                "using_starrocks/Lateral_join",
-                "using_starrocks/query_cache",
-                "using_starrocks/block_cache",
-                {
-                    "type": "category",
-                    "label": "数据去重",
-                    "link": {
-                        "type": "doc",
-                        "id": "cover_pages/distinct_values"
-                    },
-                    "items": [
-                        "using_starrocks/Using_bitmap",
-                        "using_starrocks/Using_HLL"
-                    ]
-                },
-                "using_starrocks/sorted_aggregate",
-                "using_starrocks/query_acceleration_with_auto_increment",
-                "using_starrocks/Flat_json"
-            ]
-        },
-        {
-            "type": "category",
-            "label": "外部系统集成",
-            "link": {
-                "type": "doc",
-                "id": "integrations/integrations"
-            },
-            "items": [
-                {
-                    "type": "category",
-                    "label": "CSP 认证鉴权",
-                    "description": "AWS、Azure、及 GCP 资源认证鉴权",
-                    "link": {
-                        "type": "doc",
-                        "id": "cover_pages/csp_auth"
-                    },
-                    "items": [
-                        "integrations/authenticate_to_aws_resources",
-                        "integrations/authenticate_to_azure_storage",
-                        "integrations/authenticate_to_gcs"
-                    ]
-                },
-                "integrations/data_lakes",
-                {
-                    "type": "category",
-                    "label": "实时导入",
-                    "description": "通过 Kafka、Flink、或 StarRocks 工具实现数据流实时导入",
-                    "link": {
-                        "type": "doc",
-                        "id": "integrations/streaming"
-                    },
-                    "items": [
-                        "integrations/streaming/flink",
-                        {
-                            "type": "category",
-                            "label": "Apache Kafka",
-                            "description": "从 Kafka 导入实时数据流",
-                            "link": {
-                                "type": "doc",
-                                "id": "integrations/streaming/apache_kafka"
-                            },
-                            "items": [
-                                "integrations/streaming/kafka/Kafka-connector-starrocks",
-                                "integrations/streaming/kafka/RoutineLoad",
-                                "loading/automq-routine-load"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "StarRocks Pipe",
-                            "description": "实现大规模、持续数据导入的理想工具",
-                            "link": {
-                                "type": "doc",
-                                "id": "integrations/streaming/pipe"
-                            },
-                            "items": [
-                                "integrations/streaming/pipe/hdfs",
-                                "integrations/streaming/pipe/s3"
-                            ]
-                        },
-                        "integrations/streaming/rising_wave"
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "批量导入",
-                    "description": "批量导入与数据转换",
-                    "link": {
-                        "type": "doc",
-                        "id": "cover_pages/batch_loading_integration"
-                    },
-                    "items": [
-                        "integrations/batch/Spark-connector-starrocks",
-                        "integrations/batch/SparkLoad"
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "导入工具",
-                    "description": "更多导入工具集成",
-                    "link": {
-                        "type": "doc",
-                        "id": "integrations/loading_tools/loading_tools_integration"
-                    },
-                    "items": [
-                        "integrations/loading_tools/SMT",
-                        "integrations/loading_tools/DataX-starrocks-writer",
-                        "integrations/loading_tools/CloudCanal",
-                        {
-                            "type": "link",
-                            "label": "Kettle connector",
-                            "description": "Integrations with Kettle",
-                            "href": "https://github.com/StarRocks/starrocks-connector-for-kettle"
-                        }
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "BI 工具",
-                    "link": {
-                        "type": "doc",
-                        "id": "cover_pages/bi_tools"
-                    },
-                    "items": [
-                        "integrations/BI_integrations/Superset",
-                        "integrations/BI_integrations/FineBI",
-                        "integrations/BI_integrations/Hex",
-                        "integrations/BI_integrations/Querybook",
-                        "integrations/BI_integrations/QuickBI",
-                        "integrations/BI_integrations/Tableau_Desktop",
-                        "integrations/BI_integrations/Metabase"
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "IDE 工具",
-                    "link": {
-                        "type": "doc",
-                        "id": "cover_pages/ide_tools"
-                    },
-                    "items": [
-                        "integrations/IDE_integrations/DataGrip",
-                        "integrations/IDE_integrations/Dataphin",
-                        "integrations/IDE_integrations/DBeaver",
-                        "integrations/IDE_integrations/jupysql"
-                    ]
-                },
-                {
-                    "type": "doc",
-                    "id": "integrations/other_integrations/datadog_support"
-                },
-                {
-                    "type": "link",
-                    "label": "DBT",
-                    "description": "通过 DBT 实现数据建模与转换",
-                    "href": "https://github.com/StarRocks/dbt-starrocks/blob/main/README.md"
-                }
-            ]
-        },
-        {
-            "type": "category",
-            "label": "管理手册",
-            "link": {
-                "type": "doc",
-                "id": "administration/administration"
-            },
-            "items": [
-                {
-                    "type": "category",
-                    "label": "配置项",
-                    "link": {
-                        "type": "doc",
-                        "id": "administration/management/configuration"
-                    },
-                    "items": [
-                        "administration/management/FE_configuration",
-                        "administration/management/BE_configuration"
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "运维集群",
-                    "link": {
-                        "type": "doc",
-                        "id": "administration/management/management"
-                    },
-                    "items": [
-                        "administration/management/Scale_up_down",
-                        "administration/management/BE_blacklist",
-                        "administration/management/Backup_and_restore",
-                        {
-                            "type": "category",
-                            "label": "监控报警",
-                            "link": {
-                                "type": "doc",
-                                "id": "administration/management/monitoring/Monitor_and_Alert"
-                            },
-                            "items": [
-                                "administration/management/monitoring/metrics",
-                                "administration/management/monitoring/metrics-materialized_view",
-                                "administration/management/monitoring/metrics-shared-data"
-                            ]
-                        },
-                        "administration/management/audit_loader",
-                        "administration/management/enable_fqdn",
-                        "administration/management/timezone",
-                        "administration/management/monitor_manage_big_queries",
-                        {
-                            "type": "category",
-                            "label": "管理资源",
-                            "link": {
-                                "type": "doc",
-                                "id": "administration/management/resource_management/resource_management"
-                            },
-                            "items": [
-                                "administration/management/resource_management/resource_group",
-                                "administration/management/resource_management/query_queues",
-                                "administration/management/resource_management/Query_management",
-                                "administration/management/resource_management/Memory_management",
-                                "administration/management/resource_management/spill_to_disk",
-                                "administration/management/resource_management/Load_balance",
-                                "administration/management/resource_management/Replica",
-                                "administration/management/resource_management/be_label",
-                                "administration/management/resource_management/Blacklist",
-                                "administration/management/resource_management/filemanager"
-                            ]
-                        }
-                    ]
-                },
-                "administration/Data_recovery",
-                "administration/Meta_recovery",
-                "administration/data_migration_tool",
-                {
-                    "type": "category",
-                    "label": "管理用户权限",
-                    "link": {
-                        "type": "doc",
-                        "id": "administration/user_privs/privilege_overview"
-                    },
-                    "items": [
-                        "administration/user_privs/privilege_item",
-                        "administration/user_privs/User_privilege",
-                        "administration/user_privs/ranger_plugin",
-                        "administration/user_privs/Authentication",
-                        "administration/user_privs/privilege_faq"
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "性能调优",
-                    "link": {
-                        "type": "doc",
-                        "id": "cover_pages/performance_tuning"
-                    },
-                    "items": [
-                        "administration/Query_planning",
-                        {
-                            "type": "category",
-                            "label": "Query Profile",
-                            "link": {
-                                "type": "doc",
-                                "id": "administration/query_profile_overview"
-                            },
-                            "items": [
-                                "administration/query_profile_text_based_analysis",
-                                "administration/query_profile_details"
-                            ]
-                        },
-                        "administration/Profiling"
-                    ]
-                }
-            ]
-        },
-        {
-            "type": "category",
-            "label": "参考手册",
-            "link": {
-                "type": "doc",
-                "id": "reference/reference"
-            },
-            "items": [
-                {
-                    "type": "category",
-                    "label": "数据类型",
-                    "link": {
-                        "type": "doc",
-                        "id": "sql-reference/data-types/data-type-list"
-                    },
-                    "items": [
-                        {
-                            "type": "category",
-                            "label": "数值类型",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/data-types/numeric/numeric"
-                            },
-                            "items": [
-                                "sql-reference/data-types/numeric/TINYINT",
-                                "sql-reference/data-types/numeric/SMALLINT",
-                                "sql-reference/data-types/numeric/INT",
-                                "sql-reference/data-types/numeric/BIGINT",
-                                "sql-reference/data-types/numeric/LARGEINT",
-                                "sql-reference/data-types/numeric/DECIMAL",
-                                "sql-reference/data-types/numeric/DOUBLE",
-                                "sql-reference/data-types/numeric/FLOAT",
-                                "sql-reference/data-types/numeric/BOOLEAN"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "字符串类型",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/data-types/string-type/string-type"
-                            },
-                            "items": [
-                                "sql-reference/data-types/string-type/STRING",
-                                "sql-reference/data-types/string-type/BINARY",
-                                "sql-reference/data-types/string-type/CHAR",
-                                "sql-reference/data-types/string-type/VARCHAR"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "日期类型",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/data-types/date-types/date-types"
-                            },
-                            "items": [
-                                "sql-reference/data-types/date-types/DATE",
-                                "sql-reference/data-types/date-types/DATETIME"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "半结构化类型",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/data-types/semi_structured/semi_structured"
-                            },
-                            "items": [
-                                "sql-reference/data-types/semi_structured/Array",
-                                "sql-reference/data-types/semi_structured/JSON",
-                                "sql-reference/data-types/semi_structured/Map",
-                                "sql-reference/data-types/semi_structured/STRUCT"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "其他类型",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/data-types/other-data-types/other-data-types"
-                            },
-                            "items": [
-                                "sql-reference/data-types/other-data-types/BITMAP",
-                                "sql-reference/data-types/other-data-types/HLL"
-                            ]
-                        }
-                    ]
-                },
-                "sql-reference/sql-statements/keywords",
-                {
-                    "type": "category",
-                    "label": "SQL 参考",
-                    "link": {
-                        "type": "doc",
-                        "id": "sql-reference/sql-statements/all-commands"
-                    },
-                    "items": [
-                        {
-                            "type": "category",
-                            "label": "用户账户管理",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-statements/account-management"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "集群管理",
-                            "items": [
-                                {
-                                    "type": "category",
-                                    "label": "节点和进程",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/ALTER_SYSTEM",
-                                        "sql-reference/sql-statements/Administration/CANCEL_DECOMMISSION",
-                                        "sql-reference/sql-statements/Administration/KILL",
-                                        "sql-reference/sql-statements/Administration/SHOW_BACKENDS",
-                                        "sql-reference/sql-statements/Administration/SHOW_BROKER",
-                                        "sql-reference/sql-statements/Administration/SHOW_COMPUTE_NODES",
-                                        "sql-reference/sql-statements/Administration/SHOW_FRONTENDS",
-                                        "sql-reference/sql-statements/Administration/SHOW_PROC",
-                                        "sql-reference/sql-statements/Administration/SHOW_PROCESSLIST",
-                                        "sql-reference/sql-statements/Administration/SHOW_RUNNING_QUERIES",
-                                        "sql-reference/sql-statements/Administration/ADD_BACKEND_BLACKLIST",
-                                        "sql-reference/sql-statements/Administration/DELETE_BACKEND_BLACKLIST",
-                                        "sql-reference/sql-statements/Administration/SHOW_BACKEND_BLACKLIST"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "资源组",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/CREATE_RESOURCE_GROUP",
-                                        "sql-reference/sql-statements/Administration/ALTER_RESOURCE_GROUP",
-                                        "sql-reference/sql-statements/Administration/DROP_RESOURCE_GROUP",
-                                        "sql-reference/sql-statements/Administration/SHOW_RESOURCE_GROUP",
-                                        "sql-reference/sql-statements/Administration/SHOW_USAGE_RESOURCE_GROUPS"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "存储卷",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/ALTER_STORAGE_VOLUME",
-                                        "sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME",
-                                        "sql-reference/sql-statements/Administration/DESC_STORAGE_VOLUME",
-                                        "sql-reference/sql-statements/Administration/DROP_STORAGE_VOLUME",
-                                        "sql-reference/sql-statements/Administration/SET_DEFAULT_STORAGE_VOLUME",
-                                        "sql-reference/sql-statements/Administration/SHOW_STORAGE_VOLUMES"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "Tablet，Replica 检查修复",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/ADMIN_CANCEL_REPAIR",
-                                        "sql-reference/sql-statements/Administration/ADMIN_CHECK_TABLET",
-                                        "sql-reference/sql-statements/Administration/ADMIN_REPAIR",
-                                        "sql-reference/sql-statements/Administration/ADMIN_SET_PARTITION_VERSION",
-                                        "sql-reference/sql-statements/Administration/ADMIN_SET_REPLICA_STATUS",
-                                        "sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_DISTRIBUTION",
-                                        "sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_STATUS",
-                                        "sql-reference/sql-statements/Administration/SHOW_TABLE_STATUS"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "系统配置和变量",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG",
-                                        "sql-reference/sql-statements/Administration/ADMIN_SHOW_CONFIG",
-                                        "sql-reference/sql-statements/Administration/SET",
-                                        "sql-reference/sql-statements/Administration/SHOW_VARIABLES"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "文件",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/CREATE_FILE",
-                                        "sql-reference/sql-statements/Administration/DROP_FILE",
-                                        "sql-reference/sql-statements/Administration/SHOW_FILE"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "SQL 黑名单",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/ADD_SQLBLACKLIST",
-                                        "sql-reference/sql-statements/Administration/SHOW_SQLBLACKLIST",
-                                        "sql-reference/sql-statements/Administration/DELETE_SQLBLACKLIST"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "插件",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/INSTALL_PLUGIN",
-                                        "sql-reference/sql-statements/Administration/SHOW_PLUGINS",
-                                        "sql-reference/sql-statements/Administration/UNINSTALL_PLUGIN"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "执行计划和 Profile",
-                                    "items": [
-                                        "sql-reference/sql-statements/Administration/ANALYZE_PROFILE",
-                                        "sql-reference/sql-statements/Administration/EXPLAIN",
-                                        "sql-reference/sql-statements/Administration/EXPLAIN_ANALYZE",
-                                        "sql-reference/sql-statements/Administration/SHOW_PROFILELIST"
-                                    ]
-                                }
-                            ]
-                        },
-                        "sql-reference/sql-statements/general_DDL",
-                        "sql-reference/sql-statements/general_DML",
-                        {
-                            "type": "category",
-                            "label": "导入导出",
-                            "items": [
-                                "sql-reference/sql-statements/data-manipulation/ALTER_LOAD",
-                                "sql-reference/sql-statements/data-manipulation/BROKER_LOAD",
-                                "sql-reference/sql-statements/data-manipulation/CANCEL_LOAD",
-                                "sql-reference/sql-statements/data-manipulation/INSERT",
-                                {
-                                    "type": "category",
-                                    "label": "ROUTINE LOAD",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD",
-                                        "sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD",
-                                        "sql-reference/sql-statements/data-manipulation/PAUSE_ROUTINE_LOAD",
-                                        "sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD_TASK",
-                                        "sql-reference/sql-statements/data-manipulation/STOP_ROUTINE_LOAD"
-                                    ]
-                                },
-                                "sql-reference/sql-statements/data-manipulation/SHOW_LOAD",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_TRANSACTION",
-                                "sql-reference/sql-statements/data-manipulation/SPARK_LOAD",
-                                "sql-reference/sql-statements/data-manipulation/STREAM_LOAD",
-                                {
-                                    "type": "category",
-                                    "label": "PIPE",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-manipulation/ALTER_PIPE",
-                                        "sql-reference/sql-statements/data-manipulation/CREATE_PIPE",
-                                        "sql-reference/sql-statements/data-manipulation/DROP_PIPE",
-                                        "sql-reference/sql-statements/data-manipulation/RETRY_FILE",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_PIPES",
-                                        "sql-reference/sql-statements/data-manipulation/SUSPEND_or_RESUME_PIPE"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "导出",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-manipulation/EXPORT",
-                                        "sql-reference/sql-statements/data-manipulation/CANCEL_EXPORT",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_EXPORT"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "ETL 任务",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-manipulation/DROP_TASK",
-                                        "sql-reference/sql-statements/data-manipulation/SUBMIT_TASK"
-                                    ]
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "数据目录，数据库，资源",
-                            "items": [
-                                {
-                                    "type": "category",
-                                    "label": "Catalog",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG",
-                                        "sql-reference/sql-statements/data-definition/DROP_CATALOG",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "Database",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-definition/ALTER_DATABASE",
-                                        "sql-reference/sql-statements/data-definition/CREATE_DATABASE",
-                                        "sql-reference/sql-statements/data-definition/DROP_DATABASE",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_CREATE_DATABASE",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_DATA",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_DATABASES"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "Resource",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-definition/ALTER_RESOURCE",
-                                        "sql-reference/sql-statements/data-definition/CREATE_RESOURCE",
-                                        "sql-reference/sql-statements/data-definition/DROP_RESOURCE",
-                                        "sql-reference/sql-statements/data-definition/SHOW_RESOURCES"
-                                    ]
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "表，分区，分桶，索引",
-                            "items": [
-                                "sql-reference/sql-statements/data-definition/ALTER_TABLE",
-                                "sql-reference/sql-statements/data-definition/CANCEL_ALTER_TABLE",
-                                "sql-reference/sql-statements/data-definition/CREATE_INDEX",
-                                "sql-reference/sql-statements/data-definition/CREATE_TABLE",
-                                "sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT",
-                                "sql-reference/sql-statements/data-definition/CREATE_TABLE_LIKE",
-                                "sql-reference/sql-statements/data-manipulation/DELETE",
-                                "sql-reference/sql-statements/data-definition/DROP_INDEX",
-                                "sql-reference/sql-statements/data-definition/DROP_TABLE",
-                                "sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE",
-                                "sql-reference/sql-statements/data-manipulation/SELECT",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_ALTER",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_DELETE",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_DYNAMIC_PARTITION_TABLES",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_FULL_COLUMNS",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_INDEX",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_PARTITIONS",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_TABLES",
-                                "sql-reference/sql-statements/data-manipulation/SHOW_TABLET",
-                                "sql-reference/sql-statements/data-definition/TRUNCATE_TABLE",
-                                "sql-reference/sql-statements/data-manipulation/UPDATE"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "视图，物化视图",
-                            "items": [
-                                {
-                                    "type": "category",
-                                    "label": "视图",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-definition/ALTER_VIEW",
-                                        "sql-reference/sql-statements/data-definition/CREATE_VIEW",
-                                        "sql-reference/sql-statements/data-definition/DROP_VIEW",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_CREATE_VIEW"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "物化视图",
-                                    "items": [
-                                        "sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW",
-                                        "sql-reference/sql-statements/data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW",
-                                        "sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW",
-                                        "sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW",
-                                        "sql-reference/sql-statements/data-manipulation/REFRESH_MATERIALIZED_VIEW",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_CREATE_MATERIALIZED_VIEW",
-                                        "sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW"
-                                    ]
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "函数",
-                            "items": [
-                                "sql-reference/sql-statements/data-definition/CREATE_FUNCTION",
-                                "sql-reference/sql-statements/data-definition/DROP_FUNCTION",
-                                "sql-reference/sql-statements/data-definition/SHOW_FUNCTIONS"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "CBO 统计信息",
-                            "items": [
-                                "sql-reference/sql-statements/data-definition/ANALYZE_TABLE",
-                                "sql-reference/sql-statements/data-definition/CREATE_ANALYZE",
-                                "sql-reference/sql-statements/data-definition/DROP_ANALYZE",
-                                "sql-reference/sql-statements/data-definition/DROP_STATS",
-                                "sql-reference/sql-statements/data-definition/KILL_ANALYZE",
-                                "sql-reference/sql-statements/data-definition/SHOW_ANALYZE_JOB",
-                                "sql-reference/sql-statements/data-definition/SHOW_ANALYZE_STATUS",
-                                "sql-reference/sql-statements/data-definition/SHOW_META"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "备份与恢复",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/sql-statements/data-definition/backup_restore/backup_restore"
-                            },
-                            "items": [
-                                "sql-reference/sql-statements/data-definition/backup_restore/BACKUP",
-                                "sql-reference/sql-statements/data-definition/backup_restore/CANCEL_BACKUP",
-                                "sql-reference/sql-statements/data-definition/backup_restore/CANCEL_RESTORE",
-                                "sql-reference/sql-statements/data-definition/backup_restore/CREATE_REPOSITORY",
-                                "sql-reference/sql-statements/data-definition/backup_restore/DROP_REPOSITORY",
-                                "sql-reference/sql-statements/data-definition/backup_restore/RECOVER",
-                                "sql-reference/sql-statements/data-definition/backup_restore/RESTORE",
-                                "sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_BACKUP",
-                                "sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_REPOSITORIES",
-                                "sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_SNAPSHOT"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "辅助命令",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-statements/Utility"
-                                }
-                            ]
-                        }
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "函数参考",
-                    "link": {
-                        "type": "doc",
-                        "id": "sql-reference/sql-functions/function-list"
-                    },
-                    "items": [
-                        "sql-reference/sql-functions/JAVA_UDF",
-                        "integrations/hive_bitmap_udf",
-                        "sql-reference/sql-functions/Window_function",
-                        "sql-reference/sql-functions/Lambda_expression",
-                        {
-                            "type": "category",
-                            "label": "聚合函数",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/aggregate-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Array 函数",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/array-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Bit 函数",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/bit-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Bitmap 函数",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/bitmap-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "JSON 函数",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/sql-functions/json-functions/overview-of-json-functions-and-operators"
-                            },
-                            "items": [
-                                "sql-reference/sql-functions/json-functions/json-operators",
-                                {
-                                    "type": "category",
-                                    "label": "JSON 构造函数",
-                                    "link": {
-                                        "type": "doc",
-                                        "id": "cover_pages/functions_json_constructor"
-                                    },
-                                    "items": [
-                                        "sql-reference/sql-functions/json-functions/json-constructor-functions/json_array",
-                                        "sql-reference/sql-functions/json-functions/json-constructor-functions/json_object",
-                                        "sql-reference/sql-functions/json-functions/json-constructor-functions/parse_json"
-                                    ]
-                                },
-                                {
-                                    "type": "category",
-                                    "label": "JSON 查询和处理函数",
-                                    "link": {
-                                        "type": "doc",
-                                        "id": "cover_pages/functions_json_query"
-                                    },
-                                    "items": [
-                                        {
-                                            "type": "autogenerated",
-                                            "dirName": "sql-reference/sql-functions/json-functions/json-query-and-processing-functions"
-                                        }
-                                    ]
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Map 函数",
-                            "link": {
-                                "type": "doc",
-                                "id": "sql-reference/overview-pages/map-functions"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/map-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Binary 函数",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_binary"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/binary-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "条件函数",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_conditional"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/condition-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "加密函数",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_crypto"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/crytographic-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "时间日期函数",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_date"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/date-time-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "地理位置函数",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_geo"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/spatial-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "数学函数",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_math"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/math-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "字符串函数",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_string"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/string-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "模糊/正则匹配函数",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_like"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/like-predicate-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "百分位函数",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_percentile"
-                            },
-                            "items": [
-                                "sql-reference/sql-functions/percentile-functions/percentile_approx",
-                                "sql-reference/sql-functions/percentile-functions/percentile_cont",
-                                "sql-reference/sql-functions/percentile-functions/percentile_disc",
-                                "sql-reference/sql-functions/percentile-functions/percentile_approx_raw",
-                                "sql-reference/sql-functions/percentile-functions/percentile_empty",
-                                "sql-reference/sql-functions/percentile-functions/percentile_hash",
-                                "sql-reference/sql-functions/percentile-functions/percentile_union"
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "标量函数",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_scalar"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/scalar-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "Struct 函数",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_struct"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/struct-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "表函数",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_table"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/table-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "工具函数",
-                            "link": {
-                                "type": "doc",
-                                "id": "cover_pages/functions_utility"
-                            },
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/utility-functions"
-                                }
-                            ]
-                        },
-                        "sql-reference/sql-functions/cast",
-                        {
-                            "type": "category",
-                            "label": "Hash 函数",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/hash-functions"
-                                }
-                            ]
-                        },
-                        {
-                            "type": "category",
-                            "label": "字典函数",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "sql-reference/sql-functions/dict-functions"
-                                }
-                            ]
-                        }
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "Information Schema",
-                    "link": {
-                        "type": "doc",
-                        "id": "reference/overview-pages/information_schema"
-                    },
-                    "items": [
-                        {
-                            "type": "autogenerated",
-                            "dirName": "reference/information_schema"
-                        }
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "系统元数据库",
-                    "link": {
-                        "type": "doc",
-                        "id": "reference/overview-pages/sys"
-                    },
-                    "items": [
-                        {
-                            "type": "autogenerated",
-                            "dirName": "reference/sys"
-                        }
-                    ]
-                },
-                {
-                    "type": "category",
-                    "label": "HTTP API",
-                    "link": {
-                        "type": "doc",
-                        "id": "reference/overview-pages/http_api"
-                    },
-                    "items": [
-                        {
-                            "type": "autogenerated",
-                            "dirName": "reference/HTTP_API"
-                        }
-                    ]
-                },
-                "sql-reference/sql-statements/auto_increment",
-                "sql-reference/sql-statements/generated_columns",
-                "sql-reference/sql-statements/prepared_statement",
-                "reference/System_variable",
-                "reference/user_defined_variables",
-                "reference/System_limit",
-                "reference/aws_iam_policies",
-                "reference/Error_code"
-            ]
-        },
-        {
-            "type": "category",
-            "label": "常见问题解答",
-            "link": {
-                "type": "doc",
-                "id": "faq/faq"
-            },
-            "items": [
-                "faq/Deploy_faq",
-                {
-                    "type": "category",
-                    "label": "导入导出",
-                    "items": [
-                        {
-                            "type": "category",
-                            "label": "导入",
-                            "items": [
-                                {
-                                    "type": "autogenerated",
-                                    "dirName": "faq/loading"
-                                }
-                            ]
-                        },
-                        "faq/Exporting_faq"
-                    ]
-                },
-                "faq/datalake",
-                "faq/Sql_faq",
-                "faq/Dump_query",
-                "faq/Others"
-            ]
-        },
-        {
-            "type": "category",
-            "label": "性能测试",
-            "link": {
-                "type": "doc",
-                "id": "benchmarking/benchmarking"
-            },
-            "collapsed": true,
-            "collapsible": true,
-            "items": [
-                "benchmarking/SSB_Benchmarking",
-                "benchmarking/TPC-H_Benchmarking",
-                "benchmarking/TPC_DS_Benchmark"
-            ]
-        },
-        {
-            "type": "category",
-            "label": "开发指南",
-            "link": {
-                "type": "doc",
-                "id": "cover_pages/developers"
-            },
-            "collapsed": true,
-            "collapsible": true,
-            "items": [
-                {
-                    "type": "autogenerated",
-                    "dirName": "developers"
-                }
-            ]
-        }
     ]
 }
diff --git a/docs/docusaurus/src/components/Features/index.js b/docs/docusaurus/src/components/Features/index.js
index cbbc3d5959fd53..90cfd2abe438bd 100644
--- a/docs/docusaurus/src/components/Features/index.js
+++ b/docs/docusaurus/src/components/Features/index.js
@@ -25,7 +25,7 @@ const ChineseFeatureList = [
   },
   {
     title: '导入数据',
-    url: '../../loading/Loading_intro/',
+    url: '../../loading/loading_introduction/Loading_intro/',
     description: (
       <>
         数据清洗、转换、导入
@@ -52,7 +52,7 @@ const ChineseFeatureList = [
   },
   {
     title: '半结构化类型',
-    url: '../../sql-reference/overview-pages/semi_structured/',
+    url: '../../category/semi-structured/',
     description: (
       <>
         JSON, map, struct, array
@@ -79,7 +79,7 @@ const ChineseFeatureList = [
   },
   {
     title: '参考手册',
-    url: '../../reference/',
+    url: '../../category/reference/',
     description: (
       <>
         SQL 语法、命令、函数、变量
@@ -127,7 +127,7 @@ const EnglishFeatureList = [
   },
   {
     title: 'Data Loading',
-    url: '../../loading/Loading_intro/',
+    url: '../../loading/loading_introduction/Loading_intro/',
     description: (
       <>
         Clean, transform, and load
@@ -154,7 +154,7 @@ const EnglishFeatureList = [
   },
   {
     title: 'Work with semi-structured data',
-    url: '../../sql-reference/overview-pages/semi_structured/',
+    url: '../../category/semi-structured/',
     description: (
       <>
         JSON, map, struct, array
@@ -181,7 +181,7 @@ const EnglishFeatureList = [
   },
   {
     title: 'Reference',
-    url: '../../reference/',
+    url: '../../category/reference/',
     description: (
       <>
         SQL, functions, error codes, …
diff --git a/docs/docusaurus/yarn.lock b/docs/docusaurus/yarn.lock
index b6108d1c01e9b7..4a791ad20fd36c 100644
--- a/docs/docusaurus/yarn.lock
+++ b/docs/docusaurus/yarn.lock
@@ -162,6 +162,14 @@
     "@babel/highlight" "^7.23.4"
     chalk "^2.4.2"
 
+"@babel/code-frame@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/code-frame/-/code-frame-7.24.7.tgz#882fd9e09e8ee324e496bd040401c6f046ef4465"
+  integrity sha512-BcYH1CVJBO9tvyIZ2jVeXgSIMvGZ2FDRvDdOIVQyuklNKSsx+eppDEBq/g47Ayw+RqNFE+URvOShmf+f/qwAlA==
+  dependencies:
+    "@babel/highlight" "^7.24.7"
+    picocolors "^1.0.0"
+
 "@babel/compat-data@^7.22.6", "@babel/compat-data@^7.22.9", "@babel/compat-data@^7.23.2":
   version "7.23.2"
   resolved "https://registry.yarnpkg.com/@babel/compat-data/-/compat-data-7.23.2.tgz#6a12ced93455827037bfb5ed8492820d60fc32cc"
@@ -172,21 +180,26 @@
   resolved "https://registry.yarnpkg.com/@babel/compat-data/-/compat-data-7.23.5.tgz#ffb878728bb6bdcb6f4510aa51b1be9afb8cfd98"
   integrity sha512-uU27kfDRlhfKl+w1U6vp16IuvSLtjAxdArVXPa9BvLkrr7CYIsxH5adpHObeAGY/41+syctUWOZ140a2Rvkgjw==
 
-"@babel/core@^7.19.6":
-  version "7.23.2"
-  resolved "https://registry.yarnpkg.com/@babel/core/-/core-7.23.2.tgz#ed10df0d580fff67c5f3ee70fd22e2e4c90a9f94"
-  integrity sha512-n7s51eWdaWZ3vGT2tD4T7J6eJs3QoBXydv7vkUM06Bf1cbVD2Kc2UrkzhiQwobfV7NwOnQXYL7UBJ5VPU+RGoQ==
+"@babel/compat-data@^7.25.2", "@babel/compat-data@^7.25.4":
+  version "7.25.4"
+  resolved "https://registry.yarnpkg.com/@babel/compat-data/-/compat-data-7.25.4.tgz#7d2a80ce229890edcf4cc259d4d696cb4dae2fcb"
+  integrity sha512-+LGRog6RAsCJrrrg/IO6LGmpphNe5DiK30dGjCoxxeGv49B10/3XYGxPsAwrDlMFcFEvdAUavDT8r9k/hSyQqQ==
+
+"@babel/core@^7.21.3":
+  version "7.25.2"
+  resolved "https://registry.yarnpkg.com/@babel/core/-/core-7.25.2.tgz#ed8eec275118d7613e77a352894cd12ded8eba77"
+  integrity sha512-BBt3opiCOxUr9euZ5/ro/Xv8/V7yJ5bjYMqG/C1YAo8MIKAnumZalCN+msbci3Pigy4lIQfPUpfMM27HMGaYEA==
   dependencies:
     "@ampproject/remapping" "^2.2.0"
-    "@babel/code-frame" "^7.22.13"
-    "@babel/generator" "^7.23.0"
-    "@babel/helper-compilation-targets" "^7.22.15"
-    "@babel/helper-module-transforms" "^7.23.0"
-    "@babel/helpers" "^7.23.2"
-    "@babel/parser" "^7.23.0"
-    "@babel/template" "^7.22.15"
-    "@babel/traverse" "^7.23.2"
-    "@babel/types" "^7.23.0"
+    "@babel/code-frame" "^7.24.7"
+    "@babel/generator" "^7.25.0"
+    "@babel/helper-compilation-targets" "^7.25.2"
+    "@babel/helper-module-transforms" "^7.25.2"
+    "@babel/helpers" "^7.25.0"
+    "@babel/parser" "^7.25.0"
+    "@babel/template" "^7.25.0"
+    "@babel/traverse" "^7.25.2"
+    "@babel/types" "^7.25.2"
     convert-source-map "^2.0.0"
     debug "^4.1.0"
     gensync "^1.0.0-beta.2"
@@ -234,6 +247,16 @@
     "@jridgewell/trace-mapping" "^0.3.17"
     jsesc "^2.5.1"
 
+"@babel/generator@^7.25.0", "@babel/generator@^7.25.4":
+  version "7.25.5"
+  resolved "https://registry.yarnpkg.com/@babel/generator/-/generator-7.25.5.tgz#b31cf05b3fe8c32d206b6dad03bb0aacbde73450"
+  integrity sha512-abd43wyLfbWoxC6ahM8xTkqLpGB2iWBVyuKC9/srhFunCd1SDNrV1s72bBpK4hLj8KLzHBBcOblvLQZBNw9r3w==
+  dependencies:
+    "@babel/types" "^7.25.4"
+    "@jridgewell/gen-mapping" "^0.3.5"
+    "@jridgewell/trace-mapping" "^0.3.25"
+    jsesc "^2.5.1"
+
 "@babel/helper-annotate-as-pure@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/helper-annotate-as-pure/-/helper-annotate-as-pure-7.22.5.tgz#e7f06737b197d580a01edf75d97e2c8be99d3882"
@@ -241,6 +264,13 @@
   dependencies:
     "@babel/types" "^7.22.5"
 
+"@babel/helper-annotate-as-pure@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/helper-annotate-as-pure/-/helper-annotate-as-pure-7.24.7.tgz#5373c7bc8366b12a033b4be1ac13a206c6656aab"
+  integrity sha512-BaDeOonYvhdKw+JoMVkAixAAJzG2jVPIwWoKBPdYuY9b452e2rPuI9QPYh3KpofZ3pW2akOmwZLOiOsHMiqRAg==
+  dependencies:
+    "@babel/types" "^7.24.7"
+
 "@babel/helper-builder-binary-assignment-operator-visitor@^7.22.5":
   version "7.22.15"
   resolved "https://registry.yarnpkg.com/@babel/helper-builder-binary-assignment-operator-visitor/-/helper-builder-binary-assignment-operator-visitor-7.22.15.tgz#5426b109cf3ad47b91120f8328d8ab1be8b0b956"
@@ -248,6 +278,14 @@
   dependencies:
     "@babel/types" "^7.22.15"
 
+"@babel/helper-builder-binary-assignment-operator-visitor@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/helper-builder-binary-assignment-operator-visitor/-/helper-builder-binary-assignment-operator-visitor-7.24.7.tgz#37d66feb012024f2422b762b9b2a7cfe27c7fba3"
+  integrity sha512-xZeCVVdwb4MsDBkkyZ64tReWYrLRHlMN72vP7Bdm3OUOuyFZExhsHUUnuWnm2/XOlAJzR0LfPpB56WXZn0X/lA==
+  dependencies:
+    "@babel/traverse" "^7.24.7"
+    "@babel/types" "^7.24.7"
+
 "@babel/helper-compilation-targets@^7.22.15", "@babel/helper-compilation-targets@^7.22.5", "@babel/helper-compilation-targets@^7.22.6":
   version "7.22.15"
   resolved "https://registry.yarnpkg.com/@babel/helper-compilation-targets/-/helper-compilation-targets-7.22.15.tgz#0698fc44551a26cf29f18d4662d5bf545a6cfc52"
@@ -270,6 +308,17 @@
     lru-cache "^5.1.1"
     semver "^6.3.1"
 
+"@babel/helper-compilation-targets@^7.24.7", "@babel/helper-compilation-targets@^7.24.8", "@babel/helper-compilation-targets@^7.25.2":
+  version "7.25.2"
+  resolved "https://registry.yarnpkg.com/@babel/helper-compilation-targets/-/helper-compilation-targets-7.25.2.tgz#e1d9410a90974a3a5a66e84ff55ef62e3c02d06c"
+  integrity sha512-U2U5LsSaZ7TAt3cfaymQ8WHh0pxvdHoEk6HVpaexxixjyEquMh0L0YNJNM6CTGKMXV1iksi0iZkGw4AcFkPaaw==
+  dependencies:
+    "@babel/compat-data" "^7.25.2"
+    "@babel/helper-validator-option" "^7.24.8"
+    browserslist "^4.23.1"
+    lru-cache "^5.1.1"
+    semver "^6.3.1"
+
 "@babel/helper-create-class-features-plugin@^7.22.11", "@babel/helper-create-class-features-plugin@^7.22.15", "@babel/helper-create-class-features-plugin@^7.22.5":
   version "7.22.15"
   resolved "https://registry.yarnpkg.com/@babel/helper-create-class-features-plugin/-/helper-create-class-features-plugin-7.22.15.tgz#97a61b385e57fe458496fad19f8e63b63c867de4"
@@ -285,6 +334,19 @@
     "@babel/helper-split-export-declaration" "^7.22.6"
     semver "^6.3.1"
 
+"@babel/helper-create-class-features-plugin@^7.24.7", "@babel/helper-create-class-features-plugin@^7.25.0", "@babel/helper-create-class-features-plugin@^7.25.4":
+  version "7.25.4"
+  resolved "https://registry.yarnpkg.com/@babel/helper-create-class-features-plugin/-/helper-create-class-features-plugin-7.25.4.tgz#57eaf1af38be4224a9d9dd01ddde05b741f50e14"
+  integrity sha512-ro/bFs3/84MDgDmMwbcHgDa8/E6J3QKNTk4xJJnVeFtGE+tL0K26E3pNxhYz2b67fJpt7Aphw5XcploKXuCvCQ==
+  dependencies:
+    "@babel/helper-annotate-as-pure" "^7.24.7"
+    "@babel/helper-member-expression-to-functions" "^7.24.8"
+    "@babel/helper-optimise-call-expression" "^7.24.7"
+    "@babel/helper-replace-supers" "^7.25.0"
+    "@babel/helper-skip-transparent-expression-wrappers" "^7.24.7"
+    "@babel/traverse" "^7.25.4"
+    semver "^6.3.1"
+
 "@babel/helper-create-regexp-features-plugin@^7.18.6", "@babel/helper-create-regexp-features-plugin@^7.22.5":
   version "7.22.15"
   resolved "https://registry.yarnpkg.com/@babel/helper-create-regexp-features-plugin/-/helper-create-regexp-features-plugin-7.22.15.tgz#5ee90093914ea09639b01c711db0d6775e558be1"
@@ -294,6 +356,15 @@
     regexpu-core "^5.3.1"
     semver "^6.3.1"
 
+"@babel/helper-create-regexp-features-plugin@^7.24.7", "@babel/helper-create-regexp-features-plugin@^7.25.0", "@babel/helper-create-regexp-features-plugin@^7.25.2":
+  version "7.25.2"
+  resolved "https://registry.yarnpkg.com/@babel/helper-create-regexp-features-plugin/-/helper-create-regexp-features-plugin-7.25.2.tgz#24c75974ed74183797ffd5f134169316cd1808d9"
+  integrity sha512-+wqVGP+DFmqwFD3EH6TMTfUNeqDehV3E/dl+Sd54eaXqm17tEUNbEIn4sVivVowbvUpOtIGxdo3GoXyDH9N/9g==
+  dependencies:
+    "@babel/helper-annotate-as-pure" "^7.24.7"
+    regexpu-core "^5.3.1"
+    semver "^6.3.1"
+
 "@babel/helper-define-polyfill-provider@^0.4.3":
   version "0.4.3"
   resolved "https://registry.yarnpkg.com/@babel/helper-define-polyfill-provider/-/helper-define-polyfill-provider-0.4.3.tgz#a71c10f7146d809f4a256c373f462d9bba8cf6ba"
@@ -305,6 +376,17 @@
     lodash.debounce "^4.0.8"
     resolve "^1.14.2"
 
+"@babel/helper-define-polyfill-provider@^0.6.2":
+  version "0.6.2"
+  resolved "https://registry.yarnpkg.com/@babel/helper-define-polyfill-provider/-/helper-define-polyfill-provider-0.6.2.tgz#18594f789c3594acb24cfdb4a7f7b7d2e8bd912d"
+  integrity sha512-LV76g+C502biUK6AyZ3LK10vDpDyCzZnhZFXkH1L75zHPj68+qc8Zfpx2th+gzwA2MzyK+1g/3EPl62yFnVttQ==
+  dependencies:
+    "@babel/helper-compilation-targets" "^7.22.6"
+    "@babel/helper-plugin-utils" "^7.22.5"
+    debug "^4.1.1"
+    lodash.debounce "^4.0.8"
+    resolve "^1.14.2"
+
 "@babel/helper-environment-visitor@^7.22.20", "@babel/helper-environment-visitor@^7.22.5":
   version "7.22.20"
   resolved "https://registry.yarnpkg.com/@babel/helper-environment-visitor/-/helper-environment-visitor-7.22.20.tgz#96159db61d34a29dba454c959f5ae4a649ba9167"
@@ -332,6 +414,14 @@
   dependencies:
     "@babel/types" "^7.23.0"
 
+"@babel/helper-member-expression-to-functions@^7.24.8":
+  version "7.24.8"
+  resolved "https://registry.yarnpkg.com/@babel/helper-member-expression-to-functions/-/helper-member-expression-to-functions-7.24.8.tgz#6155e079c913357d24a4c20480db7c712a5c3fb6"
+  integrity sha512-LABppdt+Lp/RlBxqrh4qgf1oEH/WxdzQNDJIu5gC/W1GyvPVrOBiItmmM8wan2fm4oYqFuFfkXmlGpLQhPY8CA==
+  dependencies:
+    "@babel/traverse" "^7.24.8"
+    "@babel/types" "^7.24.8"
+
 "@babel/helper-module-imports@^7.22.15", "@babel/helper-module-imports@^7.22.5":
   version "7.22.15"
   resolved "https://registry.yarnpkg.com/@babel/helper-module-imports/-/helper-module-imports-7.22.15.tgz#16146307acdc40cc00c3b2c647713076464bdbf0"
@@ -339,6 +429,14 @@
   dependencies:
     "@babel/types" "^7.22.15"
 
+"@babel/helper-module-imports@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/helper-module-imports/-/helper-module-imports-7.24.7.tgz#f2f980392de5b84c3328fc71d38bd81bbb83042b"
+  integrity sha512-8AyH3C+74cgCVVXow/myrynrAGv+nTVg5vKu2nZph9x7RcRwzmh0VFallJuFTZ9mx6u4eSdXZfcOzSqTUm0HCA==
+  dependencies:
+    "@babel/traverse" "^7.24.7"
+    "@babel/types" "^7.24.7"
+
 "@babel/helper-module-transforms@^7.22.5", "@babel/helper-module-transforms@^7.23.0":
   version "7.23.0"
   resolved "https://registry.yarnpkg.com/@babel/helper-module-transforms/-/helper-module-transforms-7.23.0.tgz#3ec246457f6c842c0aee62a01f60739906f7047e"
@@ -361,6 +459,16 @@
     "@babel/helper-split-export-declaration" "^7.22.6"
     "@babel/helper-validator-identifier" "^7.22.20"
 
+"@babel/helper-module-transforms@^7.24.7", "@babel/helper-module-transforms@^7.24.8", "@babel/helper-module-transforms@^7.25.0", "@babel/helper-module-transforms@^7.25.2":
+  version "7.25.2"
+  resolved "https://registry.yarnpkg.com/@babel/helper-module-transforms/-/helper-module-transforms-7.25.2.tgz#ee713c29768100f2776edf04d4eb23b8d27a66e6"
+  integrity sha512-BjyRAbix6j/wv83ftcVJmBt72QtHI56C7JXZoG2xATiLpmoC7dpd8WnkikExHDVPpi/3qCmO6WY1EaXOluiecQ==
+  dependencies:
+    "@babel/helper-module-imports" "^7.24.7"
+    "@babel/helper-simple-access" "^7.24.7"
+    "@babel/helper-validator-identifier" "^7.24.7"
+    "@babel/traverse" "^7.25.2"
+
 "@babel/helper-optimise-call-expression@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/helper-optimise-call-expression/-/helper-optimise-call-expression-7.22.5.tgz#f21531a9ccbff644fdd156b4077c16ff0c3f609e"
@@ -368,11 +476,23 @@
   dependencies:
     "@babel/types" "^7.22.5"
 
+"@babel/helper-optimise-call-expression@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/helper-optimise-call-expression/-/helper-optimise-call-expression-7.24.7.tgz#8b0a0456c92f6b323d27cfd00d1d664e76692a0f"
+  integrity sha512-jKiTsW2xmWwxT1ixIdfXUZp+P5yURx2suzLZr5Hi64rURpDYdMW0pv+Uf17EYk2Rd428Lx4tLsnjGJzYKDM/6A==
+  dependencies:
+    "@babel/types" "^7.24.7"
+
 "@babel/helper-plugin-utils@^7.0.0", "@babel/helper-plugin-utils@^7.10.4", "@babel/helper-plugin-utils@^7.12.13", "@babel/helper-plugin-utils@^7.14.5", "@babel/helper-plugin-utils@^7.18.6", "@babel/helper-plugin-utils@^7.22.5", "@babel/helper-plugin-utils@^7.8.0", "@babel/helper-plugin-utils@^7.8.3":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/helper-plugin-utils/-/helper-plugin-utils-7.22.5.tgz#dd7ee3735e8a313b9f7b05a773d892e88e6d7295"
   integrity sha512-uLls06UVKgFG9QD4OeFYLEGteMIAa5kpTPcFL28yuCIIzsf6ZyKZMllKVOCZFhiZ5ptnwX4mtKdWCBE/uT4amg==
 
+"@babel/helper-plugin-utils@^7.24.7", "@babel/helper-plugin-utils@^7.24.8":
+  version "7.24.8"
+  resolved "https://registry.yarnpkg.com/@babel/helper-plugin-utils/-/helper-plugin-utils-7.24.8.tgz#94ee67e8ec0e5d44ea7baeb51e571bd26af07878"
+  integrity sha512-FFWx5142D8h2Mgr/iPVGH5G7w6jDn4jUSpZTyDnQO0Yn7Ks2Kuz6Pci8H6MPCoUJegd/UZQ3tAvfLCxQSnWWwg==
+
 "@babel/helper-remap-async-to-generator@^7.22.20", "@babel/helper-remap-async-to-generator@^7.22.5":
   version "7.22.20"
   resolved "https://registry.yarnpkg.com/@babel/helper-remap-async-to-generator/-/helper-remap-async-to-generator-7.22.20.tgz#7b68e1cb4fa964d2996fd063723fb48eca8498e0"
@@ -382,6 +502,15 @@
     "@babel/helper-environment-visitor" "^7.22.20"
     "@babel/helper-wrap-function" "^7.22.20"
 
+"@babel/helper-remap-async-to-generator@^7.24.7", "@babel/helper-remap-async-to-generator@^7.25.0":
+  version "7.25.0"
+  resolved "https://registry.yarnpkg.com/@babel/helper-remap-async-to-generator/-/helper-remap-async-to-generator-7.25.0.tgz#d2f0fbba059a42d68e5e378feaf181ef6055365e"
+  integrity sha512-NhavI2eWEIz/H9dbrG0TuOicDhNexze43i5z7lEqwYm0WEZVTwnPpA0EafUTP7+6/W79HWIP2cTe3Z5NiSTVpw==
+  dependencies:
+    "@babel/helper-annotate-as-pure" "^7.24.7"
+    "@babel/helper-wrap-function" "^7.25.0"
+    "@babel/traverse" "^7.25.0"
+
 "@babel/helper-replace-supers@^7.22.5", "@babel/helper-replace-supers@^7.22.9":
   version "7.22.20"
   resolved "https://registry.yarnpkg.com/@babel/helper-replace-supers/-/helper-replace-supers-7.22.20.tgz#e37d367123ca98fe455a9887734ed2e16eb7a793"
@@ -391,6 +520,15 @@
     "@babel/helper-member-expression-to-functions" "^7.22.15"
     "@babel/helper-optimise-call-expression" "^7.22.5"
 
+"@babel/helper-replace-supers@^7.24.7", "@babel/helper-replace-supers@^7.25.0":
+  version "7.25.0"
+  resolved "https://registry.yarnpkg.com/@babel/helper-replace-supers/-/helper-replace-supers-7.25.0.tgz#ff44deac1c9f619523fe2ca1fd650773792000a9"
+  integrity sha512-q688zIvQVYtZu+i2PsdIu/uWGRpfxzr5WESsfpShfZECkO+d2o+WROWezCi/Q6kJ0tfPa5+pUGUlfx2HhrA3Bg==
+  dependencies:
+    "@babel/helper-member-expression-to-functions" "^7.24.8"
+    "@babel/helper-optimise-call-expression" "^7.24.7"
+    "@babel/traverse" "^7.25.0"
+
 "@babel/helper-simple-access@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/helper-simple-access/-/helper-simple-access-7.22.5.tgz#4938357dc7d782b80ed6dbb03a0fba3d22b1d5de"
@@ -398,6 +536,14 @@
   dependencies:
     "@babel/types" "^7.22.5"
 
+"@babel/helper-simple-access@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/helper-simple-access/-/helper-simple-access-7.24.7.tgz#bcade8da3aec8ed16b9c4953b74e506b51b5edb3"
+  integrity sha512-zBAIvbCMh5Ts+b86r/CjU+4XGYIs+R1j951gxI3KmmxBMhCg4oQMsv6ZXQ64XOm/cvzfU1FmoCyt6+owc5QMYg==
+  dependencies:
+    "@babel/traverse" "^7.24.7"
+    "@babel/types" "^7.24.7"
+
 "@babel/helper-skip-transparent-expression-wrappers@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/helper-skip-transparent-expression-wrappers/-/helper-skip-transparent-expression-wrappers-7.22.5.tgz#007f15240b5751c537c40e77abb4e89eeaaa8847"
@@ -405,6 +551,14 @@
   dependencies:
     "@babel/types" "^7.22.5"
 
+"@babel/helper-skip-transparent-expression-wrappers@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/helper-skip-transparent-expression-wrappers/-/helper-skip-transparent-expression-wrappers-7.24.7.tgz#5f8fa83b69ed5c27adc56044f8be2b3ea96669d9"
+  integrity sha512-IO+DLT3LQUElMbpzlatRASEyQtfhSE0+m465v++3jyyXeBTBUjtVZg28/gHeV5mrTJqvEKhKroBGAvhW+qPHiQ==
+  dependencies:
+    "@babel/traverse" "^7.24.7"
+    "@babel/types" "^7.24.7"
+
 "@babel/helper-split-export-declaration@^7.22.6":
   version "7.22.6"
   resolved "https://registry.yarnpkg.com/@babel/helper-split-export-declaration/-/helper-split-export-declaration-7.22.6.tgz#322c61b7310c0997fe4c323955667f18fcefb91c"
@@ -422,11 +576,21 @@
   resolved "https://registry.yarnpkg.com/@babel/helper-string-parser/-/helper-string-parser-7.23.4.tgz#9478c707febcbbe1ddb38a3d91a2e054ae622d83"
   integrity sha512-803gmbQdqwdf4olxrX4AJyFBV/RTr3rSmOj0rKwesmzlfhYNDEs+/iOcznzpNWlJlIlTJC2QfPFcHB6DlzdVLQ==
 
+"@babel/helper-string-parser@^7.24.8":
+  version "7.24.8"
+  resolved "https://registry.yarnpkg.com/@babel/helper-string-parser/-/helper-string-parser-7.24.8.tgz#5b3329c9a58803d5df425e5785865881a81ca48d"
+  integrity sha512-pO9KhhRcuUyGnJWwyEgnRJTSIZHiT+vMD0kPeD+so0l7mxkMT19g3pjY9GTnHySck/hDzq+dtW/4VgnMkippsQ==
+
 "@babel/helper-validator-identifier@^7.22.20":
   version "7.22.20"
   resolved "https://registry.yarnpkg.com/@babel/helper-validator-identifier/-/helper-validator-identifier-7.22.20.tgz#c4ae002c61d2879e724581d96665583dbc1dc0e0"
   integrity sha512-Y4OZ+ytlatR8AI+8KZfKuL5urKp7qey08ha31L8b3BwewJAoJamTzyvxPR/5D+KkdJCGPq/+8TukHBlY10FX9A==
 
+"@babel/helper-validator-identifier@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/helper-validator-identifier/-/helper-validator-identifier-7.24.7.tgz#75b889cfaf9e35c2aaf42cf0d72c8e91719251db"
+  integrity sha512-rR+PBcQ1SMQDDyF6X0wxtG8QyLCgUB0eRAGguqRLfkCA87l7yAP7ehq8SNj96OOGTO8OBV70KhuFYcIkHXOg0w==
+
 "@babel/helper-validator-option@^7.22.15":
   version "7.22.15"
   resolved "https://registry.yarnpkg.com/@babel/helper-validator-option/-/helper-validator-option-7.22.15.tgz#694c30dfa1d09a6534cdfcafbe56789d36aba040"
@@ -437,6 +601,11 @@
   resolved "https://registry.yarnpkg.com/@babel/helper-validator-option/-/helper-validator-option-7.23.5.tgz#907a3fbd4523426285365d1206c423c4c5520307"
   integrity sha512-85ttAOMLsr53VgXkTbkx8oA6YTfT4q7/HzXSLEYmjcSTJPMPQtvq1BD79Byep5xMUYbGRzEpDsjUf3dyp54IKw==
 
+"@babel/helper-validator-option@^7.24.7", "@babel/helper-validator-option@^7.24.8":
+  version "7.24.8"
+  resolved "https://registry.yarnpkg.com/@babel/helper-validator-option/-/helper-validator-option-7.24.8.tgz#3725cdeea8b480e86d34df15304806a06975e33d"
+  integrity sha512-xb8t9tD1MHLungh/AIoWYN+gVHaB9kwlu8gffXGSt3FFEIT7RjS+xWbc2vUD1UTZdIpKj/ab3rdqJ7ufngyi2Q==
+
 "@babel/helper-wrap-function@^7.22.20":
   version "7.22.20"
   resolved "https://registry.yarnpkg.com/@babel/helper-wrap-function/-/helper-wrap-function-7.22.20.tgz#15352b0b9bfb10fc9c76f79f6342c00e3411a569"
@@ -446,14 +615,14 @@
     "@babel/template" "^7.22.15"
     "@babel/types" "^7.22.19"
 
-"@babel/helpers@^7.23.2":
-  version "7.23.2"
-  resolved "https://registry.yarnpkg.com/@babel/helpers/-/helpers-7.23.2.tgz#2832549a6e37d484286e15ba36a5330483cac767"
-  integrity sha512-lzchcp8SjTSVe/fPmLwtWVBFC7+Tbn8LGHDVfDp9JGxpAY5opSaEFgt8UQvrnECWOTdji2mOWMz1rOhkHscmGQ==
+"@babel/helper-wrap-function@^7.25.0":
+  version "7.25.0"
+  resolved "https://registry.yarnpkg.com/@babel/helper-wrap-function/-/helper-wrap-function-7.25.0.tgz#dab12f0f593d6ca48c0062c28bcfb14ebe812f81"
+  integrity sha512-s6Q1ebqutSiZnEjaofc/UKDyC4SbzV5n5SrA2Gq8UawLycr3i04f1dX4OzoQVnexm6aOCh37SQNYlJ/8Ku+PMQ==
   dependencies:
-    "@babel/template" "^7.22.15"
-    "@babel/traverse" "^7.23.2"
-    "@babel/types" "^7.23.0"
+    "@babel/template" "^7.25.0"
+    "@babel/traverse" "^7.25.0"
+    "@babel/types" "^7.25.0"
 
 "@babel/helpers@^7.23.6":
   version "7.23.6"
@@ -464,6 +633,14 @@
     "@babel/traverse" "^7.23.6"
     "@babel/types" "^7.23.6"
 
+"@babel/helpers@^7.25.0":
+  version "7.25.0"
+  resolved "https://registry.yarnpkg.com/@babel/helpers/-/helpers-7.25.0.tgz#e69beb7841cb93a6505531ede34f34e6a073650a"
+  integrity sha512-MjgLZ42aCm0oGjJj8CtSM3DB8NOOf8h2l7DCTePJs29u+v7yO/RBX9nShlKMgFnRks/Q4tBAe7Hxnov9VkGwLw==
+  dependencies:
+    "@babel/template" "^7.25.0"
+    "@babel/types" "^7.25.0"
+
 "@babel/highlight@^7.22.13":
   version "7.22.20"
   resolved "https://registry.yarnpkg.com/@babel/highlight/-/highlight-7.22.20.tgz#4ca92b71d80554b01427815e06f2df965b9c1f54"
@@ -482,7 +659,17 @@
     chalk "^2.4.2"
     js-tokens "^4.0.0"
 
-"@babel/parser@^7.22.15", "@babel/parser@^7.22.7", "@babel/parser@^7.23.0":
+"@babel/highlight@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/highlight/-/highlight-7.24.7.tgz#a05ab1df134b286558aae0ed41e6c5f731bf409d"
+  integrity sha512-EStJpq4OuY8xYfhGVXngigBJRWxftKX9ksiGDnmlY3o7B/V7KIAc9X4oiK87uPJSc/vs5L869bem5fhZa8caZw==
+  dependencies:
+    "@babel/helper-validator-identifier" "^7.24.7"
+    chalk "^2.4.2"
+    js-tokens "^4.0.0"
+    picocolors "^1.0.0"
+
+"@babel/parser@^7.22.15", "@babel/parser@^7.23.0":
   version "7.23.0"
   resolved "https://registry.yarnpkg.com/@babel/parser/-/parser-7.23.0.tgz#da950e622420bf96ca0d0f2909cdddac3acd8719"
   integrity sha512-vvPKKdMemU85V9WE/l5wZEmImpCtLqbnTvqDS2U1fJ96KrxoW7KrXhNsNCblQlg8Ck4b85yxdTyelsMUgFUXiw==
@@ -492,6 +679,28 @@
   resolved "https://registry.yarnpkg.com/@babel/parser/-/parser-7.23.6.tgz#ba1c9e512bda72a47e285ae42aff9d2a635a9e3b"
   integrity sha512-Z2uID7YJ7oNvAI20O9X0bblw7Qqs8Q2hFy0R9tAfnfLkp5MW0UH9eUvnDSnFwKZ0AvgS1ucqR4KzvVHgnke1VQ==
 
+"@babel/parser@^7.25.0", "@babel/parser@^7.25.4":
+  version "7.25.4"
+  resolved "https://registry.yarnpkg.com/@babel/parser/-/parser-7.25.4.tgz#af4f2df7d02440286b7de57b1c21acfb2a6f257a"
+  integrity sha512-nq+eWrOgdtu3jG5Os4TQP3x3cLA8hR8TvJNjD8vnPa20WGycimcparWnLK4jJhElTK6SDyuJo1weMKO/5LpmLA==
+  dependencies:
+    "@babel/types" "^7.25.4"
+
+"@babel/plugin-bugfix-firefox-class-in-computed-class-key@^7.25.3":
+  version "7.25.3"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-bugfix-firefox-class-in-computed-class-key/-/plugin-bugfix-firefox-class-in-computed-class-key-7.25.3.tgz#dca427b45a6c0f5c095a1c639dfe2476a3daba7f"
+  integrity sha512-wUrcsxZg6rqBXG05HG1FPYgsP6EvwF4WpBbxIpWIIYnH8wG0gzx3yZY3dtEHas4sTAOGkbTsc9EGPxwff8lRoA==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.8"
+    "@babel/traverse" "^7.25.3"
+
+"@babel/plugin-bugfix-safari-class-field-initializer-scope@^7.25.0":
+  version "7.25.0"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-bugfix-safari-class-field-initializer-scope/-/plugin-bugfix-safari-class-field-initializer-scope-7.25.0.tgz#cd0c583e01369ef51676bdb3d7b603e17d2b3f73"
+  integrity sha512-Bm4bH2qsX880b/3ziJ8KD711LT7z4u8CFudmjqle65AZj/HNUFhEf90dqYv6O86buWvSBmeQDjv0Tn2aF/bIBA==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.8"
+
 "@babel/plugin-bugfix-safari-id-destructuring-collision-in-function-expression@^7.22.15":
   version "7.22.15"
   resolved "https://registry.yarnpkg.com/@babel/plugin-bugfix-safari-id-destructuring-collision-in-function-expression/-/plugin-bugfix-safari-id-destructuring-collision-in-function-expression-7.22.15.tgz#02dc8a03f613ed5fdc29fb2f728397c78146c962"
@@ -499,6 +708,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-bugfix-safari-id-destructuring-collision-in-function-expression@^7.25.0":
+  version "7.25.0"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-bugfix-safari-id-destructuring-collision-in-function-expression/-/plugin-bugfix-safari-id-destructuring-collision-in-function-expression-7.25.0.tgz#749bde80356b295390954643de7635e0dffabe73"
+  integrity sha512-lXwdNZtTmeVOOFtwM/WDe7yg1PL8sYhRk/XH0FzbR2HDQ0xC+EnQ/JHeoMYSavtU115tnUk0q9CDyq8si+LMAA==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.8"
+
 "@babel/plugin-bugfix-v8-spread-parameters-in-optional-chaining@^7.22.15":
   version "7.22.15"
   resolved "https://registry.yarnpkg.com/@babel/plugin-bugfix-v8-spread-parameters-in-optional-chaining/-/plugin-bugfix-v8-spread-parameters-in-optional-chaining-7.22.15.tgz#2aeb91d337d4e1a1e7ce85b76a37f5301781200f"
@@ -508,6 +724,23 @@
     "@babel/helper-skip-transparent-expression-wrappers" "^7.22.5"
     "@babel/plugin-transform-optional-chaining" "^7.22.15"
 
+"@babel/plugin-bugfix-v8-spread-parameters-in-optional-chaining@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-bugfix-v8-spread-parameters-in-optional-chaining/-/plugin-bugfix-v8-spread-parameters-in-optional-chaining-7.24.7.tgz#e4eabdd5109acc399b38d7999b2ef66fc2022f89"
+  integrity sha512-+izXIbke1T33mY4MSNnrqhPXDz01WYhEf3yF5NbnUtkiNnm+XBZJl3kNfoK6NKmYlz/D07+l2GWVK/QfDkNCuQ==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/helper-skip-transparent-expression-wrappers" "^7.24.7"
+    "@babel/plugin-transform-optional-chaining" "^7.24.7"
+
+"@babel/plugin-bugfix-v8-static-class-fields-redefine-readonly@^7.25.0":
+  version "7.25.0"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-bugfix-v8-static-class-fields-redefine-readonly/-/plugin-bugfix-v8-static-class-fields-redefine-readonly-7.25.0.tgz#3a82a70e7cb7294ad2559465ebcb871dfbf078fb"
+  integrity sha512-tggFrk1AIShG/RUQbEwt2Tr/E+ObkfwrPjR6BjbRvsx24+PSjK8zrq0GWPNCjo8qpRx4DuJzlcvWJqlm+0h3kw==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.8"
+    "@babel/traverse" "^7.25.0"
+
 "@babel/plugin-proposal-private-property-in-object@7.21.0-placeholder-for-preset-env.2":
   version "7.21.0-placeholder-for-preset-env.2"
   resolved "https://registry.yarnpkg.com/@babel/plugin-proposal-private-property-in-object/-/plugin-proposal-private-property-in-object-7.21.0-placeholder-for-preset-env.2.tgz#7844f9289546efa9febac2de4cfe358a050bd703"
@@ -555,6 +788,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-syntax-import-assertions@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-syntax-import-assertions/-/plugin-syntax-import-assertions-7.24.7.tgz#2a0b406b5871a20a841240586b1300ce2088a778"
+  integrity sha512-Ec3NRUMoi8gskrkBe3fNmEQfxDvY8bgfQpz6jlk/41kX9eUjvpyqWU7PBP/pLAvMaSQjbMNKJmvX57jP+M6bPg==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-syntax-import-attributes@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-syntax-import-attributes/-/plugin-syntax-import-attributes-7.22.5.tgz#ab840248d834410b829f569f5262b9e517555ecb"
@@ -562,6 +802,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-syntax-import-attributes@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-syntax-import-attributes/-/plugin-syntax-import-attributes-7.24.7.tgz#b4f9ea95a79e6912480c4b626739f86a076624ca"
+  integrity sha512-hbX+lKKeUMGihnK8nvKqmXBInriT3GVjzXKFriV3YC6APGxMbP8RZNFwy91+hocLXq90Mta+HshoB31802bb8A==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-syntax-import-meta@^7.10.4":
   version "7.10.4"
   resolved "https://registry.yarnpkg.com/@babel/plugin-syntax-import-meta/-/plugin-syntax-import-meta-7.10.4.tgz#ee601348c370fa334d2207be158777496521fd51"
@@ -583,6 +830,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-syntax-jsx@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-syntax-jsx/-/plugin-syntax-jsx-7.24.7.tgz#39a1fa4a7e3d3d7f34e2acc6be585b718d30e02d"
+  integrity sha512-6ddciUPe/mpMnOKv/U+RSd2vvVy+Yw/JfBB0ZHYjEZt9NLHmCUylNYlsbqCCS1Bffjlb0fCwC9Vqz+sBz6PsiQ==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-syntax-logical-assignment-operators@^7.10.4":
   version "7.10.4"
   resolved "https://registry.yarnpkg.com/@babel/plugin-syntax-logical-assignment-operators/-/plugin-syntax-logical-assignment-operators-7.10.4.tgz#ca91ef46303530448b906652bac2e9fe9941f699"
@@ -646,6 +900,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-syntax-typescript@^7.24.7":
+  version "7.25.4"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-syntax-typescript/-/plugin-syntax-typescript-7.25.4.tgz#04db9ce5a9043d9c635e75ae7969a2cd50ca97ff"
+  integrity sha512-uMOCoHVU52BsSWxPOMVv5qKRdeSlPuImUCB2dlPuBSU+W2/ROE7/Zg8F2Kepbk+8yBa68LlRKxO+xgEVWorsDg==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.8"
+
 "@babel/plugin-syntax-unicode-sets-regex@^7.18.6":
   version "7.18.6"
   resolved "https://registry.yarnpkg.com/@babel/plugin-syntax-unicode-sets-regex/-/plugin-syntax-unicode-sets-regex-7.18.6.tgz#d49a3b3e6b52e5be6740022317580234a6a47357"
@@ -661,6 +922,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-arrow-functions@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-arrow-functions/-/plugin-transform-arrow-functions-7.24.7.tgz#4f6886c11e423bd69f3ce51dbf42424a5f275514"
+  integrity sha512-Dt9LQs6iEY++gXUwY03DNFat5C2NbO48jj+j/bSAz6b3HgPs39qcPiYt77fDObIcFwj3/C2ICX9YMwGflUoSHQ==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-async-generator-functions@^7.23.2":
   version "7.23.2"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-async-generator-functions/-/plugin-transform-async-generator-functions-7.23.2.tgz#054afe290d64c6f576f371ccc321772c8ea87ebb"
@@ -671,6 +939,16 @@
     "@babel/helper-remap-async-to-generator" "^7.22.20"
     "@babel/plugin-syntax-async-generators" "^7.8.4"
 
+"@babel/plugin-transform-async-generator-functions@^7.25.4":
+  version "7.25.4"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-async-generator-functions/-/plugin-transform-async-generator-functions-7.25.4.tgz#2afd4e639e2d055776c9f091b6c0c180ed8cf083"
+  integrity sha512-jz8cV2XDDTqjKPwVPJBIjORVEmSGYhdRa8e5k5+vN+uwcjSrSxUaebBRa4ko1jqNF2uxyg8G6XYk30Jv285xzg==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.8"
+    "@babel/helper-remap-async-to-generator" "^7.25.0"
+    "@babel/plugin-syntax-async-generators" "^7.8.4"
+    "@babel/traverse" "^7.25.4"
+
 "@babel/plugin-transform-async-to-generator@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-async-to-generator/-/plugin-transform-async-to-generator-7.22.5.tgz#c7a85f44e46f8952f6d27fe57c2ed3cc084c3775"
@@ -680,6 +958,15 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/helper-remap-async-to-generator" "^7.22.5"
 
+"@babel/plugin-transform-async-to-generator@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-async-to-generator/-/plugin-transform-async-to-generator-7.24.7.tgz#72a3af6c451d575842a7e9b5a02863414355bdcc"
+  integrity sha512-SQY01PcJfmQ+4Ash7NE+rpbLFbmqA2GPIgqzxfFTL4t1FKRq4zTms/7htKpoCUI9OcFYgzqfmCdH53s6/jn5fA==
+  dependencies:
+    "@babel/helper-module-imports" "^7.24.7"
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/helper-remap-async-to-generator" "^7.24.7"
+
 "@babel/plugin-transform-block-scoped-functions@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-block-scoped-functions/-/plugin-transform-block-scoped-functions-7.22.5.tgz#27978075bfaeb9fa586d3cb63a3d30c1de580024"
@@ -687,6 +974,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-block-scoped-functions@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-block-scoped-functions/-/plugin-transform-block-scoped-functions-7.24.7.tgz#a4251d98ea0c0f399dafe1a35801eaba455bbf1f"
+  integrity sha512-yO7RAz6EsVQDaBH18IDJcMB1HnrUn2FJ/Jslc/WtPPWcjhpUJXU/rjbwmluzp7v/ZzWcEhTMXELnnsz8djWDwQ==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-block-scoping@^7.23.0":
   version "7.23.0"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-block-scoping/-/plugin-transform-block-scoping-7.23.0.tgz#8744d02c6c264d82e1a4bc5d2d501fd8aff6f022"
@@ -694,6 +988,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-block-scoping@^7.25.0":
+  version "7.25.0"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-block-scoping/-/plugin-transform-block-scoping-7.25.0.tgz#23a6ed92e6b006d26b1869b1c91d1b917c2ea2ac"
+  integrity sha512-yBQjYoOjXlFv9nlXb3f1casSHOZkWr29NX+zChVanLg5Nc157CrbEX9D7hxxtTpuFy7Q0YzmmWfJxzvps4kXrQ==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.8"
+
 "@babel/plugin-transform-class-properties@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-class-properties/-/plugin-transform-class-properties-7.22.5.tgz#97a56e31ad8c9dc06a0b3710ce7803d5a48cca77"
@@ -702,6 +1003,14 @@
     "@babel/helper-create-class-features-plugin" "^7.22.5"
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-class-properties@^7.25.4":
+  version "7.25.4"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-class-properties/-/plugin-transform-class-properties-7.25.4.tgz#bae7dbfcdcc2e8667355cd1fb5eda298f05189fd"
+  integrity sha512-nZeZHyCWPfjkdU5pA/uHiTaDAFUEqkpzf1YoQT2NeSynCGYq9rxfyI3XpQbfx/a0hSnFH6TGlEXvae5Vi7GD8g==
+  dependencies:
+    "@babel/helper-create-class-features-plugin" "^7.25.4"
+    "@babel/helper-plugin-utils" "^7.24.8"
+
 "@babel/plugin-transform-class-static-block@^7.22.11":
   version "7.22.11"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-class-static-block/-/plugin-transform-class-static-block-7.22.11.tgz#dc8cc6e498f55692ac6b4b89e56d87cec766c974"
@@ -711,6 +1020,15 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/plugin-syntax-class-static-block" "^7.14.5"
 
+"@babel/plugin-transform-class-static-block@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-class-static-block/-/plugin-transform-class-static-block-7.24.7.tgz#c82027ebb7010bc33c116d4b5044fbbf8c05484d"
+  integrity sha512-HMXK3WbBPpZQufbMG4B46A90PkuuhN9vBCb5T8+VAHqvAqvcLi+2cKoukcpmUYkszLhScU3l1iudhrks3DggRQ==
+  dependencies:
+    "@babel/helper-create-class-features-plugin" "^7.24.7"
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/plugin-syntax-class-static-block" "^7.14.5"
+
 "@babel/plugin-transform-classes@^7.22.15":
   version "7.22.15"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-classes/-/plugin-transform-classes-7.22.15.tgz#aaf4753aee262a232bbc95451b4bdf9599c65a0b"
@@ -726,6 +1044,18 @@
     "@babel/helper-split-export-declaration" "^7.22.6"
     globals "^11.1.0"
 
+"@babel/plugin-transform-classes@^7.25.4":
+  version "7.25.4"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-classes/-/plugin-transform-classes-7.25.4.tgz#d29dbb6a72d79f359952ad0b66d88518d65ef89a"
+  integrity sha512-oexUfaQle2pF/b6E0dwsxQtAol9TLSO88kQvym6HHBWFliV2lGdrPieX+WgMRLSJDVzdYywk7jXbLPuO2KLTLg==
+  dependencies:
+    "@babel/helper-annotate-as-pure" "^7.24.7"
+    "@babel/helper-compilation-targets" "^7.25.2"
+    "@babel/helper-plugin-utils" "^7.24.8"
+    "@babel/helper-replace-supers" "^7.25.0"
+    "@babel/traverse" "^7.25.4"
+    globals "^11.1.0"
+
 "@babel/plugin-transform-computed-properties@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-computed-properties/-/plugin-transform-computed-properties-7.22.5.tgz#cd1e994bf9f316bd1c2dafcd02063ec261bb3869"
@@ -734,6 +1064,14 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/template" "^7.22.5"
 
+"@babel/plugin-transform-computed-properties@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-computed-properties/-/plugin-transform-computed-properties-7.24.7.tgz#4cab3214e80bc71fae3853238d13d097b004c707"
+  integrity sha512-25cS7v+707Gu6Ds2oY6tCkUwsJ9YIDbggd9+cu9jzzDgiNq7hR/8dkzxWfKWnTic26vsI3EsCXNd4iEB6e8esQ==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/template" "^7.24.7"
+
 "@babel/plugin-transform-destructuring@^7.23.0":
   version "7.23.0"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-destructuring/-/plugin-transform-destructuring-7.23.0.tgz#6447aa686be48b32eaf65a73e0e2c0bd010a266c"
@@ -741,6 +1079,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-destructuring@^7.24.8":
+  version "7.24.8"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-destructuring/-/plugin-transform-destructuring-7.24.8.tgz#c828e814dbe42a2718a838c2a2e16a408e055550"
+  integrity sha512-36e87mfY8TnRxc7yc6M9g9gOB7rKgSahqkIKwLpz4Ppk2+zC2Cy1is0uwtuSG6AE4zlTOUa+7JGz9jCJGLqQFQ==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.8"
+
 "@babel/plugin-transform-dotall-regex@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-dotall-regex/-/plugin-transform-dotall-regex-7.22.5.tgz#dbb4f0e45766eb544e193fb00e65a1dd3b2a4165"
@@ -749,6 +1094,14 @@
     "@babel/helper-create-regexp-features-plugin" "^7.22.5"
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-dotall-regex@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-dotall-regex/-/plugin-transform-dotall-regex-7.24.7.tgz#5f8bf8a680f2116a7207e16288a5f974ad47a7a0"
+  integrity sha512-ZOA3W+1RRTSWvyqcMJDLqbchh7U4NRGqwRfFSVbOLS/ePIP4vHB5e8T8eXcuqyN1QkgKyj5wuW0lcS85v4CrSw==
+  dependencies:
+    "@babel/helper-create-regexp-features-plugin" "^7.24.7"
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-duplicate-keys@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-duplicate-keys/-/plugin-transform-duplicate-keys-7.22.5.tgz#b6e6428d9416f5f0bba19c70d1e6e7e0b88ab285"
@@ -756,6 +1109,21 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-duplicate-keys@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-duplicate-keys/-/plugin-transform-duplicate-keys-7.24.7.tgz#dd20102897c9a2324e5adfffb67ff3610359a8ee"
+  integrity sha512-JdYfXyCRihAe46jUIliuL2/s0x0wObgwwiGxw/UbgJBr20gQBThrokO4nYKgWkD7uBaqM7+9x5TU7NkExZJyzw==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+
+"@babel/plugin-transform-duplicate-named-capturing-groups-regex@^7.25.0":
+  version "7.25.0"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-duplicate-named-capturing-groups-regex/-/plugin-transform-duplicate-named-capturing-groups-regex-7.25.0.tgz#809af7e3339466b49c034c683964ee8afb3e2604"
+  integrity sha512-YLpb4LlYSc3sCUa35un84poXoraOiQucUTTu8X1j18JV+gNa8E0nyUf/CjZ171IRGr4jEguF+vzJU66QZhn29g==
+  dependencies:
+    "@babel/helper-create-regexp-features-plugin" "^7.25.0"
+    "@babel/helper-plugin-utils" "^7.24.8"
+
 "@babel/plugin-transform-dynamic-import@^7.22.11":
   version "7.22.11"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-dynamic-import/-/plugin-transform-dynamic-import-7.22.11.tgz#2c7722d2a5c01839eaf31518c6ff96d408e447aa"
@@ -764,6 +1132,14 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/plugin-syntax-dynamic-import" "^7.8.3"
 
+"@babel/plugin-transform-dynamic-import@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-dynamic-import/-/plugin-transform-dynamic-import-7.24.7.tgz#4d8b95e3bae2b037673091aa09cd33fecd6419f4"
+  integrity sha512-sc3X26PhZQDb3JhORmakcbvkeInvxz+A8oda99lj7J60QRuPZvNAk9wQlTBS1ZynelDrDmTU4pw1tyc5d5ZMUg==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/plugin-syntax-dynamic-import" "^7.8.3"
+
 "@babel/plugin-transform-exponentiation-operator@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-exponentiation-operator/-/plugin-transform-exponentiation-operator-7.22.5.tgz#402432ad544a1f9a480da865fda26be653e48f6a"
@@ -772,6 +1148,14 @@
     "@babel/helper-builder-binary-assignment-operator-visitor" "^7.22.5"
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-exponentiation-operator@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-exponentiation-operator/-/plugin-transform-exponentiation-operator-7.24.7.tgz#b629ee22645f412024297d5245bce425c31f9b0d"
+  integrity sha512-Rqe/vSc9OYgDajNIK35u7ot+KeCoetqQYFXM4Epf7M7ez3lWlOjrDjrwMei6caCVhfdw+mIKD4cgdGNy5JQotQ==
+  dependencies:
+    "@babel/helper-builder-binary-assignment-operator-visitor" "^7.24.7"
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-export-namespace-from@^7.22.11":
   version "7.22.11"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-export-namespace-from/-/plugin-transform-export-namespace-from-7.22.11.tgz#b3c84c8f19880b6c7440108f8929caf6056db26c"
@@ -780,6 +1164,14 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/plugin-syntax-export-namespace-from" "^7.8.3"
 
+"@babel/plugin-transform-export-namespace-from@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-export-namespace-from/-/plugin-transform-export-namespace-from-7.24.7.tgz#176d52d8d8ed516aeae7013ee9556d540c53f197"
+  integrity sha512-v0K9uNYsPL3oXZ/7F9NNIbAj2jv1whUEtyA6aujhekLs56R++JDQuzRcP2/z4WX5Vg/c5lE9uWZA0/iUoFhLTA==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/plugin-syntax-export-namespace-from" "^7.8.3"
+
 "@babel/plugin-transform-for-of@^7.22.15":
   version "7.22.15"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-for-of/-/plugin-transform-for-of-7.22.15.tgz#f64b4ccc3a4f131a996388fae7680b472b306b29"
@@ -787,6 +1179,14 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-for-of@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-for-of/-/plugin-transform-for-of-7.24.7.tgz#f25b33f72df1d8be76399e1b8f3f9d366eb5bc70"
+  integrity sha512-wo9ogrDG1ITTTBsy46oGiN1dS9A7MROBTcYsfS8DtsImMkHk9JXJ3EWQM6X2SUw4x80uGPlwj0o00Uoc6nEE3g==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/helper-skip-transparent-expression-wrappers" "^7.24.7"
+
 "@babel/plugin-transform-function-name@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-function-name/-/plugin-transform-function-name-7.22.5.tgz#935189af68b01898e0d6d99658db6b164205c143"
@@ -796,6 +1196,15 @@
     "@babel/helper-function-name" "^7.22.5"
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-function-name@^7.25.1":
+  version "7.25.1"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-function-name/-/plugin-transform-function-name-7.25.1.tgz#b85e773097526c1a4fc4ba27322748643f26fc37"
+  integrity sha512-TVVJVdW9RKMNgJJlLtHsKDTydjZAbwIsn6ySBPQaEAUU5+gVvlJt/9nRmqVbsV/IBanRjzWoaAQKLoamWVOUuA==
+  dependencies:
+    "@babel/helper-compilation-targets" "^7.24.8"
+    "@babel/helper-plugin-utils" "^7.24.8"
+    "@babel/traverse" "^7.25.1"
+
 "@babel/plugin-transform-json-strings@^7.22.11":
   version "7.22.11"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-json-strings/-/plugin-transform-json-strings-7.22.11.tgz#689a34e1eed1928a40954e37f74509f48af67835"
@@ -804,6 +1213,14 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/plugin-syntax-json-strings" "^7.8.3"
 
+"@babel/plugin-transform-json-strings@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-json-strings/-/plugin-transform-json-strings-7.24.7.tgz#f3e9c37c0a373fee86e36880d45b3664cedaf73a"
+  integrity sha512-2yFnBGDvRuxAaE/f0vfBKvtnvvqU8tGpMHqMNpTN2oWMKIR3NqFkjaAgGwawhqK/pIN2T3XdjGPdaG0vDhOBGw==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/plugin-syntax-json-strings" "^7.8.3"
+
 "@babel/plugin-transform-literals@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-literals/-/plugin-transform-literals-7.22.5.tgz#e9341f4b5a167952576e23db8d435849b1dd7920"
@@ -811,6 +1228,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-literals@^7.25.2":
+  version "7.25.2"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-literals/-/plugin-transform-literals-7.25.2.tgz#deb1ad14fc5490b9a65ed830e025bca849d8b5f3"
+  integrity sha512-HQI+HcTbm9ur3Z2DkO+jgESMAMcYLuN/A7NRw9juzxAezN9AvqvUTnpKP/9kkYANz6u7dFlAyOu44ejuGySlfw==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.8"
+
 "@babel/plugin-transform-logical-assignment-operators@^7.22.11":
   version "7.22.11"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-logical-assignment-operators/-/plugin-transform-logical-assignment-operators-7.22.11.tgz#24c522a61688bde045b7d9bc3c2597a4d948fc9c"
@@ -819,6 +1243,14 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/plugin-syntax-logical-assignment-operators" "^7.10.4"
 
+"@babel/plugin-transform-logical-assignment-operators@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-logical-assignment-operators/-/plugin-transform-logical-assignment-operators-7.24.7.tgz#a58fb6eda16c9dc8f9ff1c7b1ba6deb7f4694cb0"
+  integrity sha512-4D2tpwlQ1odXmTEIFWy9ELJcZHqrStlzK/dAOWYyxX3zT0iXQB6banjgeOJQXzEc4S0E0a5A+hahxPaEFYftsw==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/plugin-syntax-logical-assignment-operators" "^7.10.4"
+
 "@babel/plugin-transform-member-expression-literals@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-member-expression-literals/-/plugin-transform-member-expression-literals-7.22.5.tgz#4fcc9050eded981a468347dd374539ed3e058def"
@@ -826,6 +1258,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-member-expression-literals@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-member-expression-literals/-/plugin-transform-member-expression-literals-7.24.7.tgz#3b4454fb0e302e18ba4945ba3246acb1248315df"
+  integrity sha512-T/hRC1uqrzXMKLQ6UCwMT85S3EvqaBXDGf0FaMf4446Qx9vKwlghvee0+uuZcDUCZU5RuNi4781UQ7R308zzBw==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-modules-amd@^7.23.0":
   version "7.23.0"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-modules-amd/-/plugin-transform-modules-amd-7.23.0.tgz#05b2bc43373faa6d30ca89214731f76f966f3b88"
@@ -834,6 +1273,14 @@
     "@babel/helper-module-transforms" "^7.23.0"
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-modules-amd@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-modules-amd/-/plugin-transform-modules-amd-7.24.7.tgz#65090ed493c4a834976a3ca1cde776e6ccff32d7"
+  integrity sha512-9+pB1qxV3vs/8Hdmz/CulFB8w2tuu6EB94JZFsjdqxQokwGa9Unap7Bo2gGBGIvPmDIVvQrom7r5m/TCDMURhg==
+  dependencies:
+    "@babel/helper-module-transforms" "^7.24.7"
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-modules-commonjs@^7.23.0":
   version "7.23.0"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-modules-commonjs/-/plugin-transform-modules-commonjs-7.23.0.tgz#b3dba4757133b2762c00f4f94590cf6d52602481"
@@ -843,6 +1290,15 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/helper-simple-access" "^7.22.5"
 
+"@babel/plugin-transform-modules-commonjs@^7.24.7", "@babel/plugin-transform-modules-commonjs@^7.24.8":
+  version "7.24.8"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-modules-commonjs/-/plugin-transform-modules-commonjs-7.24.8.tgz#ab6421e564b717cb475d6fff70ae7f103536ea3c"
+  integrity sha512-WHsk9H8XxRs3JXKWFiqtQebdh9b/pTk4EgueygFzYlTKAg0Ud985mSevdNjdXdFBATSKVJGQXP1tv6aGbssLKA==
+  dependencies:
+    "@babel/helper-module-transforms" "^7.24.8"
+    "@babel/helper-plugin-utils" "^7.24.8"
+    "@babel/helper-simple-access" "^7.24.7"
+
 "@babel/plugin-transform-modules-systemjs@^7.23.0":
   version "7.23.0"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-modules-systemjs/-/plugin-transform-modules-systemjs-7.23.0.tgz#77591e126f3ff4132a40595a6cccd00a6b60d160"
@@ -853,6 +1309,16 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/helper-validator-identifier" "^7.22.20"
 
+"@babel/plugin-transform-modules-systemjs@^7.25.0":
+  version "7.25.0"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-modules-systemjs/-/plugin-transform-modules-systemjs-7.25.0.tgz#8f46cdc5f9e5af74f3bd019485a6cbe59685ea33"
+  integrity sha512-YPJfjQPDXxyQWg/0+jHKj1llnY5f/R6a0p/vP4lPymxLu7Lvl4k2WMitqi08yxwQcCVUUdG9LCUj4TNEgAp3Jw==
+  dependencies:
+    "@babel/helper-module-transforms" "^7.25.0"
+    "@babel/helper-plugin-utils" "^7.24.8"
+    "@babel/helper-validator-identifier" "^7.24.7"
+    "@babel/traverse" "^7.25.0"
+
 "@babel/plugin-transform-modules-umd@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-modules-umd/-/plugin-transform-modules-umd-7.22.5.tgz#4694ae40a87b1745e3775b6a7fe96400315d4f98"
@@ -861,6 +1327,14 @@
     "@babel/helper-module-transforms" "^7.22.5"
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-modules-umd@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-modules-umd/-/plugin-transform-modules-umd-7.24.7.tgz#edd9f43ec549099620df7df24e7ba13b5c76efc8"
+  integrity sha512-3aytQvqJ/h9z4g8AsKPLvD4Zqi2qT+L3j7XoFFu1XBlZWEl2/1kWnhmAbxpLgPrHSY0M6UA02jyTiwUVtiKR6A==
+  dependencies:
+    "@babel/helper-module-transforms" "^7.24.7"
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-named-capturing-groups-regex@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-named-capturing-groups-regex/-/plugin-transform-named-capturing-groups-regex-7.22.5.tgz#67fe18ee8ce02d57c855185e27e3dc959b2e991f"
@@ -869,6 +1343,14 @@
     "@babel/helper-create-regexp-features-plugin" "^7.22.5"
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-named-capturing-groups-regex@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-named-capturing-groups-regex/-/plugin-transform-named-capturing-groups-regex-7.24.7.tgz#9042e9b856bc6b3688c0c2e4060e9e10b1460923"
+  integrity sha512-/jr7h/EWeJtk1U/uz2jlsCioHkZk1JJZVcc8oQsJ1dUlaJD83f4/6Zeh2aHt9BIFokHIsSeDfhUmju0+1GPd6g==
+  dependencies:
+    "@babel/helper-create-regexp-features-plugin" "^7.24.7"
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-new-target@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-new-target/-/plugin-transform-new-target-7.22.5.tgz#1b248acea54ce44ea06dfd37247ba089fcf9758d"
@@ -876,6 +1358,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-new-target@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-new-target/-/plugin-transform-new-target-7.24.7.tgz#31ff54c4e0555cc549d5816e4ab39241dfb6ab00"
+  integrity sha512-RNKwfRIXg4Ls/8mMTza5oPF5RkOW8Wy/WgMAp1/F1yZ8mMbtwXW+HDoJiOsagWrAhI5f57Vncrmr9XeT4CVapA==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-nullish-coalescing-operator@^7.22.11":
   version "7.22.11"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-nullish-coalescing-operator/-/plugin-transform-nullish-coalescing-operator-7.22.11.tgz#debef6c8ba795f5ac67cd861a81b744c5d38d9fc"
@@ -884,6 +1373,14 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/plugin-syntax-nullish-coalescing-operator" "^7.8.3"
 
+"@babel/plugin-transform-nullish-coalescing-operator@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-nullish-coalescing-operator/-/plugin-transform-nullish-coalescing-operator-7.24.7.tgz#1de4534c590af9596f53d67f52a92f12db984120"
+  integrity sha512-Ts7xQVk1OEocqzm8rHMXHlxvsfZ0cEF2yomUqpKENHWMF4zKk175Y4q8H5knJes6PgYad50uuRmt3UJuhBw8pQ==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/plugin-syntax-nullish-coalescing-operator" "^7.8.3"
+
 "@babel/plugin-transform-numeric-separator@^7.22.11":
   version "7.22.11"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-numeric-separator/-/plugin-transform-numeric-separator-7.22.11.tgz#498d77dc45a6c6db74bb829c02a01c1d719cbfbd"
@@ -892,6 +1389,14 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/plugin-syntax-numeric-separator" "^7.10.4"
 
+"@babel/plugin-transform-numeric-separator@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-numeric-separator/-/plugin-transform-numeric-separator-7.24.7.tgz#bea62b538c80605d8a0fac9b40f48e97efa7de63"
+  integrity sha512-e6q1TiVUzvH9KRvicuxdBTUj4AdKSRwzIyFFnfnezpCfP2/7Qmbb8qbU2j7GODbl4JMkblitCQjKYUaX/qkkwA==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/plugin-syntax-numeric-separator" "^7.10.4"
+
 "@babel/plugin-transform-object-rest-spread@^7.22.15":
   version "7.22.15"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-object-rest-spread/-/plugin-transform-object-rest-spread-7.22.15.tgz#21a95db166be59b91cde48775310c0df6e1da56f"
@@ -903,6 +1408,16 @@
     "@babel/plugin-syntax-object-rest-spread" "^7.8.3"
     "@babel/plugin-transform-parameters" "^7.22.15"
 
+"@babel/plugin-transform-object-rest-spread@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-object-rest-spread/-/plugin-transform-object-rest-spread-7.24.7.tgz#d13a2b93435aeb8a197e115221cab266ba6e55d6"
+  integrity sha512-4QrHAr0aXQCEFni2q4DqKLD31n2DL+RxcwnNjDFkSG0eNQ/xCavnRkfCUjsyqGC2OviNJvZOF/mQqZBw7i2C5Q==
+  dependencies:
+    "@babel/helper-compilation-targets" "^7.24.7"
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/plugin-syntax-object-rest-spread" "^7.8.3"
+    "@babel/plugin-transform-parameters" "^7.24.7"
+
 "@babel/plugin-transform-object-super@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-object-super/-/plugin-transform-object-super-7.22.5.tgz#794a8d2fcb5d0835af722173c1a9d704f44e218c"
@@ -911,6 +1426,14 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/helper-replace-supers" "^7.22.5"
 
+"@babel/plugin-transform-object-super@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-object-super/-/plugin-transform-object-super-7.24.7.tgz#66eeaff7830bba945dd8989b632a40c04ed625be"
+  integrity sha512-A/vVLwN6lBrMFmMDmPPz0jnE6ZGx7Jq7d6sT/Ev4H65RER6pZ+kczlf1DthF5N0qaPHBsI7UXiE8Zy66nmAovg==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/helper-replace-supers" "^7.24.7"
+
 "@babel/plugin-transform-optional-catch-binding@^7.22.11":
   version "7.22.11"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-optional-catch-binding/-/plugin-transform-optional-catch-binding-7.22.11.tgz#461cc4f578a127bb055527b3e77404cad38c08e0"
@@ -919,6 +1442,14 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/plugin-syntax-optional-catch-binding" "^7.8.3"
 
+"@babel/plugin-transform-optional-catch-binding@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-optional-catch-binding/-/plugin-transform-optional-catch-binding-7.24.7.tgz#00eabd883d0dd6a60c1c557548785919b6e717b4"
+  integrity sha512-uLEndKqP5BfBbC/5jTwPxLh9kqPWWgzN/f8w6UwAIirAEqiIVJWWY312X72Eub09g5KF9+Zn7+hT7sDxmhRuKA==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/plugin-syntax-optional-catch-binding" "^7.8.3"
+
 "@babel/plugin-transform-optional-chaining@^7.22.15", "@babel/plugin-transform-optional-chaining@^7.23.0":
   version "7.23.0"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-optional-chaining/-/plugin-transform-optional-chaining-7.23.0.tgz#73ff5fc1cf98f542f09f29c0631647d8ad0be158"
@@ -928,6 +1459,15 @@
     "@babel/helper-skip-transparent-expression-wrappers" "^7.22.5"
     "@babel/plugin-syntax-optional-chaining" "^7.8.3"
 
+"@babel/plugin-transform-optional-chaining@^7.24.7", "@babel/plugin-transform-optional-chaining@^7.24.8":
+  version "7.24.8"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-optional-chaining/-/plugin-transform-optional-chaining-7.24.8.tgz#bb02a67b60ff0406085c13d104c99a835cdf365d"
+  integrity sha512-5cTOLSMs9eypEy8JUVvIKOu6NgvbJMnpG62VpIHrTmROdQ+L5mDAaI40g25k5vXti55JWNX5jCkq3HZxXBQANw==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.8"
+    "@babel/helper-skip-transparent-expression-wrappers" "^7.24.7"
+    "@babel/plugin-syntax-optional-chaining" "^7.8.3"
+
 "@babel/plugin-transform-parameters@^7.22.15":
   version "7.22.15"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-parameters/-/plugin-transform-parameters-7.22.15.tgz#719ca82a01d177af358df64a514d64c2e3edb114"
@@ -935,6 +1475,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-parameters@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-parameters/-/plugin-transform-parameters-7.24.7.tgz#5881f0ae21018400e320fc7eb817e529d1254b68"
+  integrity sha512-yGWW5Rr+sQOhK0Ot8hjDJuxU3XLRQGflvT4lhlSY0DFvdb3TwKaY26CJzHtYllU0vT9j58hc37ndFPsqT1SrzA==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-private-methods@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-private-methods/-/plugin-transform-private-methods-7.22.5.tgz#21c8af791f76674420a147ae62e9935d790f8722"
@@ -943,6 +1490,14 @@
     "@babel/helper-create-class-features-plugin" "^7.22.5"
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-private-methods@^7.25.4":
+  version "7.25.4"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-private-methods/-/plugin-transform-private-methods-7.25.4.tgz#9bbefbe3649f470d681997e0b64a4b254d877242"
+  integrity sha512-ao8BG7E2b/URaUQGqN3Tlsg+M3KlHY6rJ1O1gXAEUnZoyNQnvKyH87Kfg+FoxSeyWUB8ISZZsC91C44ZuBFytw==
+  dependencies:
+    "@babel/helper-create-class-features-plugin" "^7.25.4"
+    "@babel/helper-plugin-utils" "^7.24.8"
+
 "@babel/plugin-transform-private-property-in-object@^7.22.11":
   version "7.22.11"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-private-property-in-object/-/plugin-transform-private-property-in-object-7.22.11.tgz#ad45c4fc440e9cb84c718ed0906d96cf40f9a4e1"
@@ -953,6 +1508,16 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/plugin-syntax-private-property-in-object" "^7.14.5"
 
+"@babel/plugin-transform-private-property-in-object@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-private-property-in-object/-/plugin-transform-private-property-in-object-7.24.7.tgz#4eec6bc701288c1fab5f72e6a4bbc9d67faca061"
+  integrity sha512-9z76mxwnwFxMyxZWEgdgECQglF2Q7cFLm0kMf8pGwt+GSJsY0cONKj/UuO4bOH0w/uAel3ekS4ra5CEAyJRmDA==
+  dependencies:
+    "@babel/helper-annotate-as-pure" "^7.24.7"
+    "@babel/helper-create-class-features-plugin" "^7.24.7"
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/plugin-syntax-private-property-in-object" "^7.14.5"
+
 "@babel/plugin-transform-property-literals@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-property-literals/-/plugin-transform-property-literals-7.22.5.tgz#b5ddabd73a4f7f26cd0e20f5db48290b88732766"
@@ -960,12 +1525,19 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
-"@babel/plugin-transform-react-constant-elements@^7.18.12":
-  version "7.22.5"
-  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-react-constant-elements/-/plugin-transform-react-constant-elements-7.22.5.tgz#6dfa7c1c37f7d7279e417ceddf5a04abb8bb9c29"
-  integrity sha512-BF5SXoO+nX3h5OhlN78XbbDrBOffv+AxPP2ENaJOVqjWCgBDeOY3WcaUcddutGSfoap+5NEQ/q/4I3WZIvgkXA==
+"@babel/plugin-transform-property-literals@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-property-literals/-/plugin-transform-property-literals-7.24.7.tgz#f0d2ed8380dfbed949c42d4d790266525d63bbdc"
+  integrity sha512-EMi4MLQSHfd2nrCqQEWxFdha2gBCqU4ZcCng4WBGZ5CJL4bBRW0ptdqqDdeirGZcpALazVVNJqRmsO8/+oNCBA==
   dependencies:
-    "@babel/helper-plugin-utils" "^7.22.5"
+    "@babel/helper-plugin-utils" "^7.24.7"
+
+"@babel/plugin-transform-react-constant-elements@^7.21.3":
+  version "7.25.1"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-react-constant-elements/-/plugin-transform-react-constant-elements-7.25.1.tgz#71a665ed16ce618067d05f4a98130207349d82ae"
+  integrity sha512-SLV/giH/V4SmloZ6Dt40HjTGTAIkxn33TVIHxNGNvo8ezMhrxBkzisj4op1KZYPIOHFLqhv60OHvX+YRu4xbmQ==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.8"
 
 "@babel/plugin-transform-react-display-name@^7.22.5":
   version "7.22.5"
@@ -1008,6 +1580,14 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     regenerator-transform "^0.15.2"
 
+"@babel/plugin-transform-regenerator@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-regenerator/-/plugin-transform-regenerator-7.24.7.tgz#021562de4534d8b4b1851759fd7af4e05d2c47f8"
+  integrity sha512-lq3fvXPdimDrlg6LWBoqj+r/DEWgONuwjuOuQCSYgRroXDH/IdM1C0IZf59fL5cHLpjEH/O6opIRBbqv7ELnuA==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+    regenerator-transform "^0.15.2"
+
 "@babel/plugin-transform-reserved-words@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-reserved-words/-/plugin-transform-reserved-words-7.22.5.tgz#832cd35b81c287c4bcd09ce03e22199641f964fb"
@@ -1015,6 +1595,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-reserved-words@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-reserved-words/-/plugin-transform-reserved-words-7.24.7.tgz#80037fe4fbf031fc1125022178ff3938bb3743a4"
+  integrity sha512-0DUq0pHcPKbjFZCfTss/pGkYMfy3vFWydkUBd9r0GHpIyfs2eCDENvqadMycRS9wZCXR41wucAfJHJmwA0UmoQ==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-runtime@^7.22.9":
   version "7.23.2"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-runtime/-/plugin-transform-runtime-7.23.2.tgz#c956a3f8d1aa50816ff6c30c6288d66635c12990"
@@ -1034,6 +1621,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-shorthand-properties@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-shorthand-properties/-/plugin-transform-shorthand-properties-7.24.7.tgz#85448c6b996e122fa9e289746140aaa99da64e73"
+  integrity sha512-KsDsevZMDsigzbA09+vacnLpmPH4aWjcZjXdyFKGzpplxhbeB4wYtury3vglQkg6KM/xEPKt73eCjPPf1PgXBA==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-spread@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-spread/-/plugin-transform-spread-7.22.5.tgz#6487fd29f229c95e284ba6c98d65eafb893fea6b"
@@ -1042,6 +1636,14 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/helper-skip-transparent-expression-wrappers" "^7.22.5"
 
+"@babel/plugin-transform-spread@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-spread/-/plugin-transform-spread-7.24.7.tgz#e8a38c0fde7882e0fb8f160378f74bd885cc7bb3"
+  integrity sha512-x96oO0I09dgMDxJaANcRyD4ellXFLLiWhuwDxKZX5g2rWP1bTPkBSwCYv96VDXVT1bD9aPj8tppr5ITIh8hBng==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/helper-skip-transparent-expression-wrappers" "^7.24.7"
+
 "@babel/plugin-transform-sticky-regex@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-sticky-regex/-/plugin-transform-sticky-regex-7.22.5.tgz#295aba1595bfc8197abd02eae5fc288c0deb26aa"
@@ -1049,6 +1651,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-sticky-regex@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-sticky-regex/-/plugin-transform-sticky-regex-7.24.7.tgz#96ae80d7a7e5251f657b5cf18f1ea6bf926f5feb"
+  integrity sha512-kHPSIJc9v24zEml5geKg9Mjx5ULpfncj0wRpYtxbvKyTtHCYDkVE3aHQ03FrpEo4gEe2vrJJS1Y9CJTaThA52g==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-template-literals@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-template-literals/-/plugin-transform-template-literals-7.22.5.tgz#8f38cf291e5f7a8e60e9f733193f0bcc10909bff"
@@ -1056,6 +1665,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-template-literals@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-template-literals/-/plugin-transform-template-literals-7.24.7.tgz#a05debb4a9072ae8f985bcf77f3f215434c8f8c8"
+  integrity sha512-AfDTQmClklHCOLxtGoP7HkeMw56k1/bTQjwsfhL6pppo/M4TOBSq+jjBUBLmV/4oeFg4GWMavIl44ZeCtmmZTw==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-typeof-symbol@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-typeof-symbol/-/plugin-transform-typeof-symbol-7.22.5.tgz#5e2ba478da4b603af8673ff7c54f75a97b716b34"
@@ -1063,6 +1679,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-typeof-symbol@^7.24.8":
+  version "7.24.8"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-typeof-symbol/-/plugin-transform-typeof-symbol-7.24.8.tgz#383dab37fb073f5bfe6e60c654caac309f92ba1c"
+  integrity sha512-adNTUpDCVnmAE58VEqKlAA6ZBlNkMnWD0ZcW76lyNFN3MJniyGFZfNwERVk8Ap56MCnXztmDr19T4mPTztcuaw==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.8"
+
 "@babel/plugin-transform-typescript@^7.22.15":
   version "7.22.15"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-typescript/-/plugin-transform-typescript-7.22.15.tgz#15adef906451d86349eb4b8764865c960eb54127"
@@ -1073,6 +1696,17 @@
     "@babel/helper-plugin-utils" "^7.22.5"
     "@babel/plugin-syntax-typescript" "^7.22.5"
 
+"@babel/plugin-transform-typescript@^7.24.7":
+  version "7.25.2"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-typescript/-/plugin-transform-typescript-7.25.2.tgz#237c5d10de6d493be31637c6b9fa30b6c5461add"
+  integrity sha512-lBwRvjSmqiMYe/pS0+1gggjJleUJi7NzjvQ1Fkqtt69hBa/0t1YuW/MLQMAPixfwaQOHUXsd6jeU3Z+vdGv3+A==
+  dependencies:
+    "@babel/helper-annotate-as-pure" "^7.24.7"
+    "@babel/helper-create-class-features-plugin" "^7.25.0"
+    "@babel/helper-plugin-utils" "^7.24.8"
+    "@babel/helper-skip-transparent-expression-wrappers" "^7.24.7"
+    "@babel/plugin-syntax-typescript" "^7.24.7"
+
 "@babel/plugin-transform-unicode-escapes@^7.22.10":
   version "7.22.10"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-unicode-escapes/-/plugin-transform-unicode-escapes-7.22.10.tgz#c723f380f40a2b2f57a62df24c9005834c8616d9"
@@ -1080,6 +1714,13 @@
   dependencies:
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-unicode-escapes@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-unicode-escapes/-/plugin-transform-unicode-escapes-7.24.7.tgz#2023a82ced1fb4971630a2e079764502c4148e0e"
+  integrity sha512-U3ap1gm5+4edc2Q/P+9VrBNhGkfnf+8ZqppY71Bo/pzZmXhhLdqgaUl6cuB07O1+AQJtCLfaOmswiNbSQ9ivhw==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-unicode-property-regex@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-unicode-property-regex/-/plugin-transform-unicode-property-regex-7.22.5.tgz#098898f74d5c1e86660dc112057b2d11227f1c81"
@@ -1088,6 +1729,14 @@
     "@babel/helper-create-regexp-features-plugin" "^7.22.5"
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-unicode-property-regex@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-unicode-property-regex/-/plugin-transform-unicode-property-regex-7.24.7.tgz#9073a4cd13b86ea71c3264659590ac086605bbcd"
+  integrity sha512-uH2O4OV5M9FZYQrwc7NdVmMxQJOCCzFeYudlZSzUAHRFeOujQefa92E74TQDVskNHCzOXoigEuoyzHDhaEaK5w==
+  dependencies:
+    "@babel/helper-create-regexp-features-plugin" "^7.24.7"
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-unicode-regex@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-unicode-regex/-/plugin-transform-unicode-regex-7.22.5.tgz#ce7e7bb3ef208c4ff67e02a22816656256d7a183"
@@ -1096,6 +1745,14 @@
     "@babel/helper-create-regexp-features-plugin" "^7.22.5"
     "@babel/helper-plugin-utils" "^7.22.5"
 
+"@babel/plugin-transform-unicode-regex@^7.24.7":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-unicode-regex/-/plugin-transform-unicode-regex-7.24.7.tgz#dfc3d4a51127108099b19817c0963be6a2adf19f"
+  integrity sha512-hlQ96MBZSAXUq7ltkjtu3FJCCSMx/j629ns3hA3pXnBXjanNP0LHi+JpPeA81zaWgVK1VGH95Xuy7u0RyQ8kMg==
+  dependencies:
+    "@babel/helper-create-regexp-features-plugin" "^7.24.7"
+    "@babel/helper-plugin-utils" "^7.24.7"
+
 "@babel/plugin-transform-unicode-sets-regex@^7.22.5":
   version "7.22.5"
   resolved "https://registry.yarnpkg.com/@babel/plugin-transform-unicode-sets-regex/-/plugin-transform-unicode-sets-regex-7.22.5.tgz#77788060e511b708ffc7d42fdfbc5b37c3004e91"
@@ -1104,7 +1761,104 @@
     "@babel/helper-create-regexp-features-plugin" "^7.22.5"
     "@babel/helper-plugin-utils" "^7.22.5"
 
-"@babel/preset-env@^7.19.4", "@babel/preset-env@^7.22.9":
+"@babel/plugin-transform-unicode-sets-regex@^7.25.4":
+  version "7.25.4"
+  resolved "https://registry.yarnpkg.com/@babel/plugin-transform-unicode-sets-regex/-/plugin-transform-unicode-sets-regex-7.25.4.tgz#be664c2a0697ffacd3423595d5edef6049e8946c"
+  integrity sha512-qesBxiWkgN1Q+31xUE9RcMk79eOXXDCv6tfyGMRSs4RGlioSg2WVyQAm07k726cSE56pa+Kb0y9epX2qaXzTvA==
+  dependencies:
+    "@babel/helper-create-regexp-features-plugin" "^7.25.2"
+    "@babel/helper-plugin-utils" "^7.24.8"
+
+"@babel/preset-env@^7.20.2":
+  version "7.25.4"
+  resolved "https://registry.yarnpkg.com/@babel/preset-env/-/preset-env-7.25.4.tgz#be23043d43a34a2721cd0f676c7ba6f1481f6af6"
+  integrity sha512-W9Gyo+KmcxjGahtt3t9fb14vFRWvPpu5pT6GBlovAK6BTBcxgjfVMSQCfJl4oi35ODrxP6xx2Wr8LNST57Mraw==
+  dependencies:
+    "@babel/compat-data" "^7.25.4"
+    "@babel/helper-compilation-targets" "^7.25.2"
+    "@babel/helper-plugin-utils" "^7.24.8"
+    "@babel/helper-validator-option" "^7.24.8"
+    "@babel/plugin-bugfix-firefox-class-in-computed-class-key" "^7.25.3"
+    "@babel/plugin-bugfix-safari-class-field-initializer-scope" "^7.25.0"
+    "@babel/plugin-bugfix-safari-id-destructuring-collision-in-function-expression" "^7.25.0"
+    "@babel/plugin-bugfix-v8-spread-parameters-in-optional-chaining" "^7.24.7"
+    "@babel/plugin-bugfix-v8-static-class-fields-redefine-readonly" "^7.25.0"
+    "@babel/plugin-proposal-private-property-in-object" "7.21.0-placeholder-for-preset-env.2"
+    "@babel/plugin-syntax-async-generators" "^7.8.4"
+    "@babel/plugin-syntax-class-properties" "^7.12.13"
+    "@babel/plugin-syntax-class-static-block" "^7.14.5"
+    "@babel/plugin-syntax-dynamic-import" "^7.8.3"
+    "@babel/plugin-syntax-export-namespace-from" "^7.8.3"
+    "@babel/plugin-syntax-import-assertions" "^7.24.7"
+    "@babel/plugin-syntax-import-attributes" "^7.24.7"
+    "@babel/plugin-syntax-import-meta" "^7.10.4"
+    "@babel/plugin-syntax-json-strings" "^7.8.3"
+    "@babel/plugin-syntax-logical-assignment-operators" "^7.10.4"
+    "@babel/plugin-syntax-nullish-coalescing-operator" "^7.8.3"
+    "@babel/plugin-syntax-numeric-separator" "^7.10.4"
+    "@babel/plugin-syntax-object-rest-spread" "^7.8.3"
+    "@babel/plugin-syntax-optional-catch-binding" "^7.8.3"
+    "@babel/plugin-syntax-optional-chaining" "^7.8.3"
+    "@babel/plugin-syntax-private-property-in-object" "^7.14.5"
+    "@babel/plugin-syntax-top-level-await" "^7.14.5"
+    "@babel/plugin-syntax-unicode-sets-regex" "^7.18.6"
+    "@babel/plugin-transform-arrow-functions" "^7.24.7"
+    "@babel/plugin-transform-async-generator-functions" "^7.25.4"
+    "@babel/plugin-transform-async-to-generator" "^7.24.7"
+    "@babel/plugin-transform-block-scoped-functions" "^7.24.7"
+    "@babel/plugin-transform-block-scoping" "^7.25.0"
+    "@babel/plugin-transform-class-properties" "^7.25.4"
+    "@babel/plugin-transform-class-static-block" "^7.24.7"
+    "@babel/plugin-transform-classes" "^7.25.4"
+    "@babel/plugin-transform-computed-properties" "^7.24.7"
+    "@babel/plugin-transform-destructuring" "^7.24.8"
+    "@babel/plugin-transform-dotall-regex" "^7.24.7"
+    "@babel/plugin-transform-duplicate-keys" "^7.24.7"
+    "@babel/plugin-transform-duplicate-named-capturing-groups-regex" "^7.25.0"
+    "@babel/plugin-transform-dynamic-import" "^7.24.7"
+    "@babel/plugin-transform-exponentiation-operator" "^7.24.7"
+    "@babel/plugin-transform-export-namespace-from" "^7.24.7"
+    "@babel/plugin-transform-for-of" "^7.24.7"
+    "@babel/plugin-transform-function-name" "^7.25.1"
+    "@babel/plugin-transform-json-strings" "^7.24.7"
+    "@babel/plugin-transform-literals" "^7.25.2"
+    "@babel/plugin-transform-logical-assignment-operators" "^7.24.7"
+    "@babel/plugin-transform-member-expression-literals" "^7.24.7"
+    "@babel/plugin-transform-modules-amd" "^7.24.7"
+    "@babel/plugin-transform-modules-commonjs" "^7.24.8"
+    "@babel/plugin-transform-modules-systemjs" "^7.25.0"
+    "@babel/plugin-transform-modules-umd" "^7.24.7"
+    "@babel/plugin-transform-named-capturing-groups-regex" "^7.24.7"
+    "@babel/plugin-transform-new-target" "^7.24.7"
+    "@babel/plugin-transform-nullish-coalescing-operator" "^7.24.7"
+    "@babel/plugin-transform-numeric-separator" "^7.24.7"
+    "@babel/plugin-transform-object-rest-spread" "^7.24.7"
+    "@babel/plugin-transform-object-super" "^7.24.7"
+    "@babel/plugin-transform-optional-catch-binding" "^7.24.7"
+    "@babel/plugin-transform-optional-chaining" "^7.24.8"
+    "@babel/plugin-transform-parameters" "^7.24.7"
+    "@babel/plugin-transform-private-methods" "^7.25.4"
+    "@babel/plugin-transform-private-property-in-object" "^7.24.7"
+    "@babel/plugin-transform-property-literals" "^7.24.7"
+    "@babel/plugin-transform-regenerator" "^7.24.7"
+    "@babel/plugin-transform-reserved-words" "^7.24.7"
+    "@babel/plugin-transform-shorthand-properties" "^7.24.7"
+    "@babel/plugin-transform-spread" "^7.24.7"
+    "@babel/plugin-transform-sticky-regex" "^7.24.7"
+    "@babel/plugin-transform-template-literals" "^7.24.7"
+    "@babel/plugin-transform-typeof-symbol" "^7.24.8"
+    "@babel/plugin-transform-unicode-escapes" "^7.24.7"
+    "@babel/plugin-transform-unicode-property-regex" "^7.24.7"
+    "@babel/plugin-transform-unicode-regex" "^7.24.7"
+    "@babel/plugin-transform-unicode-sets-regex" "^7.25.4"
+    "@babel/preset-modules" "0.1.6-no-external-plugins"
+    babel-plugin-polyfill-corejs2 "^0.4.10"
+    babel-plugin-polyfill-corejs3 "^0.10.6"
+    babel-plugin-polyfill-regenerator "^0.6.1"
+    core-js-compat "^3.37.1"
+    semver "^6.3.1"
+
+"@babel/preset-env@^7.22.9":
   version "7.23.2"
   resolved "https://registry.yarnpkg.com/@babel/preset-env/-/preset-env-7.23.2.tgz#1f22be0ff0e121113260337dbc3e58fafce8d059"
   integrity sha512-BW3gsuDD+rvHL2VO2SjAUNTBe5YrjsTiDyqamPDWY723na3/yPQ65X5oQkFVJZ0o50/2d+svm1rkPoJeR1KxVQ==
@@ -1211,7 +1965,18 @@
     "@babel/plugin-transform-react-jsx-development" "^7.22.5"
     "@babel/plugin-transform-react-pure-annotations" "^7.22.5"
 
-"@babel/preset-typescript@^7.18.6", "@babel/preset-typescript@^7.22.5":
+"@babel/preset-typescript@^7.21.0":
+  version "7.24.7"
+  resolved "https://registry.yarnpkg.com/@babel/preset-typescript/-/preset-typescript-7.24.7.tgz#66cd86ea8f8c014855671d5ea9a737139cbbfef1"
+  integrity sha512-SyXRe3OdWwIwalxDg5UtJnJQO+YPcTfwiIY2B0Xlddh9o7jpWLvv8X1RthIeDOxQ+O1ML5BLPCONToObyVQVuQ==
+  dependencies:
+    "@babel/helper-plugin-utils" "^7.24.7"
+    "@babel/helper-validator-option" "^7.24.7"
+    "@babel/plugin-syntax-jsx" "^7.24.7"
+    "@babel/plugin-transform-modules-commonjs" "^7.24.7"
+    "@babel/plugin-transform-typescript" "^7.24.7"
+
+"@babel/preset-typescript@^7.22.5":
   version "7.23.2"
   resolved "https://registry.yarnpkg.com/@babel/preset-typescript/-/preset-typescript-7.23.2.tgz#c8de488130b7081f7e1482936ad3de5b018beef4"
   integrity sha512-u4UJc1XsS1GhIGteM8rnGiIvf9rJpiVgMEeCnwlLA7WJPC+jcXWJAGxYmeqs5hOZD8BbAfnV5ezBOxQbb4OUxA==
@@ -1251,7 +2016,16 @@
     "@babel/parser" "^7.22.15"
     "@babel/types" "^7.22.15"
 
-"@babel/traverse@^7.22.8", "@babel/traverse@^7.23.2":
+"@babel/template@^7.24.7", "@babel/template@^7.25.0":
+  version "7.25.0"
+  resolved "https://registry.yarnpkg.com/@babel/template/-/template-7.25.0.tgz#e733dc3134b4fede528c15bc95e89cb98c52592a"
+  integrity sha512-aOOgh1/5XzKvg1jvVz7AVrx2piJ2XBi227DHmbY6y+bM9H2FlN+IfecYu4Xl0cNiiVejlsCri89LUsbj8vJD9Q==
+  dependencies:
+    "@babel/code-frame" "^7.24.7"
+    "@babel/parser" "^7.25.0"
+    "@babel/types" "^7.25.0"
+
+"@babel/traverse@^7.22.8":
   version "7.23.2"
   resolved "https://registry.yarnpkg.com/@babel/traverse/-/traverse-7.23.2.tgz#329c7a06735e144a506bdb2cad0268b7f46f4ad8"
   integrity sha512-azpe59SQ48qG6nu2CzcMLbxUudtN+dOM9kDbUqGq3HXUJRlo7i8fvPoxQUzYgLZ4cMVmuZgm8vvBpNeRhd6XSw==
@@ -1283,7 +2057,29 @@
     debug "^4.3.1"
     globals "^11.1.0"
 
-"@babel/types@^7.20.0", "@babel/types@^7.22.15", "@babel/types@^7.22.19", "@babel/types@^7.22.5", "@babel/types@^7.23.0", "@babel/types@^7.4.4":
+"@babel/traverse@^7.24.7", "@babel/traverse@^7.24.8", "@babel/traverse@^7.25.0", "@babel/traverse@^7.25.1", "@babel/traverse@^7.25.2", "@babel/traverse@^7.25.3", "@babel/traverse@^7.25.4":
+  version "7.25.4"
+  resolved "https://registry.yarnpkg.com/@babel/traverse/-/traverse-7.25.4.tgz#648678046990f2957407e3086e97044f13c3e18e"
+  integrity sha512-VJ4XsrD+nOvlXyLzmLzUs/0qjFS4sK30te5yEFlvbbUNEgKaVb2BHZUpAL+ttLPQAHNrsI3zZisbfha5Cvr8vg==
+  dependencies:
+    "@babel/code-frame" "^7.24.7"
+    "@babel/generator" "^7.25.4"
+    "@babel/parser" "^7.25.4"
+    "@babel/template" "^7.25.0"
+    "@babel/types" "^7.25.4"
+    debug "^4.3.1"
+    globals "^11.1.0"
+
+"@babel/types@^7.21.3", "@babel/types@^7.24.7", "@babel/types@^7.24.8", "@babel/types@^7.25.0", "@babel/types@^7.25.2", "@babel/types@^7.25.4":
+  version "7.25.4"
+  resolved "https://registry.yarnpkg.com/@babel/types/-/types-7.25.4.tgz#6bcb46c72fdf1012a209d016c07f769e10adcb5f"
+  integrity sha512-zQ1ijeeCXVEh+aNL0RlmkPkG8HUiDcU2pzQQFjtbntgAczRASFzj4H+6+bV+dy1ntKR14I/DypeuRG1uma98iQ==
+  dependencies:
+    "@babel/helper-string-parser" "^7.24.8"
+    "@babel/helper-validator-identifier" "^7.24.7"
+    to-fast-properties "^2.0.0"
+
+"@babel/types@^7.22.15", "@babel/types@^7.22.19", "@babel/types@^7.22.5", "@babel/types@^7.23.0", "@babel/types@^7.4.4":
   version "7.23.0"
   resolved "https://registry.yarnpkg.com/@babel/types/-/types-7.23.0.tgz#8c1f020c9df0e737e4e247c0619f58c68458aaeb"
   integrity sha512-0oIyUfKoI3mSqMvsxBdclDwxXKXAUA8v/apZbc+iSyARYou1o8ZGDxbUYyLFoW2arqS2jDGqJuZvv1d/io1axg==
@@ -1326,10 +2122,10 @@
     "@docsearch/css" "3.5.2"
     algoliasearch "^4.19.1"
 
-"@docusaurus/core@3.1.1", "@docusaurus/core@^3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/core/-/core-3.1.1.tgz#29ce8df7a3d3d12ee8962d6d86133b87235ff17b"
-  integrity sha512-2nQfKFcf+MLEM7JXsXwQxPOmQAR6ytKMZVSx7tVi9HEm9WtfwBH1fp6bn8Gj4zLUhjWKCLoysQ9/Wm+EZCQ4yQ==
+"@docusaurus/core@3.5.2", "@docusaurus/core@^3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/core/-/core-3.5.2.tgz#3adedb90e7b6104592f1231043bd6bf91680c39c"
+  integrity sha512-4Z1WkhCSkX4KO0Fw5m/Vuc7Q3NxBG53NE5u59Rs96fWkMPZVSrzEPP16/Nk6cWb/shK7xXPndTmalJtw7twL/w==
   dependencies:
     "@babel/core" "^7.23.3"
     "@babel/generator" "^7.23.3"
@@ -1341,15 +2137,12 @@
     "@babel/runtime" "^7.22.6"
     "@babel/runtime-corejs3" "^7.22.6"
     "@babel/traverse" "^7.22.8"
-    "@docusaurus/cssnano-preset" "3.1.1"
-    "@docusaurus/logger" "3.1.1"
-    "@docusaurus/mdx-loader" "3.1.1"
-    "@docusaurus/react-loadable" "5.5.2"
-    "@docusaurus/utils" "3.1.1"
-    "@docusaurus/utils-common" "3.1.1"
-    "@docusaurus/utils-validation" "3.1.1"
-    "@slorber/static-site-generator-webpack-plugin" "^4.0.7"
-    "@svgr/webpack" "^6.5.1"
+    "@docusaurus/cssnano-preset" "3.5.2"
+    "@docusaurus/logger" "3.5.2"
+    "@docusaurus/mdx-loader" "3.5.2"
+    "@docusaurus/utils" "3.5.2"
+    "@docusaurus/utils-common" "3.5.2"
+    "@docusaurus/utils-validation" "3.5.2"
     autoprefixer "^10.4.14"
     babel-loader "^9.1.3"
     babel-plugin-dynamic-import-node "^2.3.3"
@@ -1363,12 +2156,13 @@
     copy-webpack-plugin "^11.0.0"
     core-js "^3.31.1"
     css-loader "^6.8.1"
-    css-minimizer-webpack-plugin "^4.2.2"
-    cssnano "^5.1.15"
+    css-minimizer-webpack-plugin "^5.0.1"
+    cssnano "^6.1.2"
     del "^6.1.1"
     detect-port "^1.5.1"
     escape-html "^1.0.3"
     eta "^2.2.0"
+    eval "^0.1.8"
     file-loader "^6.2.0"
     fs-extra "^11.1.1"
     html-minifier-terser "^7.2.0"
@@ -1377,12 +2171,13 @@
     leven "^3.1.0"
     lodash "^4.17.21"
     mini-css-extract-plugin "^2.7.6"
+    p-map "^4.0.0"
     postcss "^8.4.26"
     postcss-loader "^7.3.3"
     prompts "^2.4.2"
     react-dev-utils "^12.0.1"
     react-helmet-async "^1.3.0"
-    react-loadable "npm:@docusaurus/react-loadable@5.5.2"
+    react-loadable "npm:@docusaurus/react-loadable@6.0.0"
     react-loadable-ssr-addon-v5-slorber "^1.0.1"
     react-router "^5.3.4"
     react-router-config "^5.1.1"
@@ -1401,34 +2196,32 @@
     webpack-merge "^5.9.0"
     webpackbar "^5.0.2"
 
-"@docusaurus/cssnano-preset@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/cssnano-preset/-/cssnano-preset-3.1.1.tgz#03a4cb8e6d41654d7ff5ed79fddd73fd224feea4"
-  integrity sha512-LnoIDjJWbirdbVZDMq+4hwmrTl2yHDnBf9MLG9qyExeAE3ac35s4yUhJI8yyTCdixzNfKit4cbXblzzqMu4+8g==
+"@docusaurus/cssnano-preset@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/cssnano-preset/-/cssnano-preset-3.5.2.tgz#6c1f2b2f9656f978c4694c84ab24592b04dcfab3"
+  integrity sha512-D3KiQXOMA8+O0tqORBrTOEQyQxNIfPm9jEaJoALjjSjc2M/ZAWcUfPQEnwr2JB2TadHw2gqWgpZckQmrVWkytA==
   dependencies:
-    cssnano-preset-advanced "^5.3.10"
-    postcss "^8.4.26"
-    postcss-sort-media-queries "^4.4.1"
+    cssnano-preset-advanced "^6.1.2"
+    postcss "^8.4.38"
+    postcss-sort-media-queries "^5.2.0"
     tslib "^2.6.0"
 
-"@docusaurus/logger@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/logger/-/logger-3.1.1.tgz#423e8270c00a57b1b3a0cc8a3ee0a4c522a68387"
-  integrity sha512-BjkNDpQzewcTnST8trx4idSoAla6zZ3w22NqM/UMcFtvYJgmoE4layuTzlfql3VFPNuivvj7BOExa/+21y4X2Q==
+"@docusaurus/logger@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/logger/-/logger-3.5.2.tgz#1150339ad56844b30734115c19c580f3b25cf5ed"
+  integrity sha512-LHC540SGkeLfyT3RHK3gAMK6aS5TRqOD4R72BEU/DE2M/TY8WwEUAMY576UUc/oNJXv8pGhBmQB6N9p3pt8LQw==
   dependencies:
     chalk "^4.1.2"
     tslib "^2.6.0"
 
-"@docusaurus/mdx-loader@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/mdx-loader/-/mdx-loader-3.1.1.tgz#f79290abc5044bef1d7ecac4eccec887058b8e03"
-  integrity sha512-xN2IccH9+sv7TmxwsDJNS97BHdmlqWwho+kIVY4tcCXkp+k4QuzvWBeunIMzeayY4Fu13A6sAjHGv5qm72KyGA==
+"@docusaurus/mdx-loader@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/mdx-loader/-/mdx-loader-3.5.2.tgz#99781641372c5037bcbe09bb8ade93a0e0ada57d"
+  integrity sha512-ku3xO9vZdwpiMIVd8BzWV0DCqGEbCP5zs1iHfKX50vw6jX8vQo0ylYo1YJMZyz6e+JFJ17HYHT5FzVidz2IflA==
   dependencies:
-    "@babel/parser" "^7.22.7"
-    "@babel/traverse" "^7.22.8"
-    "@docusaurus/logger" "3.1.1"
-    "@docusaurus/utils" "3.1.1"
-    "@docusaurus/utils-validation" "3.1.1"
+    "@docusaurus/logger" "3.5.2"
+    "@docusaurus/utils" "3.5.2"
+    "@docusaurus/utils-validation" "3.5.2"
     "@mdx-js/mdx" "^3.0.0"
     "@slorber/remark-comment" "^1.0.0"
     escape-html "^1.0.3"
@@ -1451,33 +2244,33 @@
     vfile "^6.0.1"
     webpack "^5.88.1"
 
-"@docusaurus/module-type-aliases@3.1.1", "@docusaurus/module-type-aliases@^3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/module-type-aliases/-/module-type-aliases-3.1.1.tgz#b304402b0535a13ebd4c0db1c368d2604d54d02f"
-  integrity sha512-xBJyx0TMfAfVZ9ZeIOb1awdXgR4YJMocIEzTps91rq+hJDFJgJaylDtmoRhUxkwuYmNK1GJpW95b7DLztSBJ3A==
+"@docusaurus/module-type-aliases@3.5.2", "@docusaurus/module-type-aliases@^3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/module-type-aliases/-/module-type-aliases-3.5.2.tgz#4e8f9c0703e23b2e07ebfce96598ec83e4dd2a9e"
+  integrity sha512-Z+Xu3+2rvKef/YKTMxZHsEXp1y92ac0ngjDiExRdqGTmEKtCUpkbNYH8v5eXo5Ls+dnW88n6WTa+Q54kLOkwPg==
   dependencies:
-    "@docusaurus/react-loadable" "5.5.2"
-    "@docusaurus/types" "3.1.1"
+    "@docusaurus/types" "3.5.2"
     "@types/history" "^4.7.11"
     "@types/react" "*"
     "@types/react-router-config" "*"
     "@types/react-router-dom" "*"
     react-helmet-async "*"
-    react-loadable "npm:@docusaurus/react-loadable@5.5.2"
+    react-loadable "npm:@docusaurus/react-loadable@6.0.0"
 
-"@docusaurus/plugin-content-blog@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-content-blog/-/plugin-content-blog-3.1.1.tgz#16f4fd723227b2158461bba6b9bcc18c1926f7ea"
-  integrity sha512-ew/3VtVoG3emoAKmoZl7oKe1zdFOsI0NbcHS26kIxt2Z8vcXKCUgK9jJJrz0TbOipyETPhqwq4nbitrY3baibg==
-  dependencies:
-    "@docusaurus/core" "3.1.1"
-    "@docusaurus/logger" "3.1.1"
-    "@docusaurus/mdx-loader" "3.1.1"
-    "@docusaurus/types" "3.1.1"
-    "@docusaurus/utils" "3.1.1"
-    "@docusaurus/utils-common" "3.1.1"
-    "@docusaurus/utils-validation" "3.1.1"
-    cheerio "^1.0.0-rc.12"
+"@docusaurus/plugin-content-blog@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-content-blog/-/plugin-content-blog-3.5.2.tgz#649c07c34da7603645f152bcebdf75285baed16b"
+  integrity sha512-R7ghWnMvjSf+aeNDH0K4fjyQnt5L0KzUEnUhmf1e3jZrv3wogeytZNN6n7X8yHcMsuZHPOrctQhXWnmxu+IRRg==
+  dependencies:
+    "@docusaurus/core" "3.5.2"
+    "@docusaurus/logger" "3.5.2"
+    "@docusaurus/mdx-loader" "3.5.2"
+    "@docusaurus/theme-common" "3.5.2"
+    "@docusaurus/types" "3.5.2"
+    "@docusaurus/utils" "3.5.2"
+    "@docusaurus/utils-common" "3.5.2"
+    "@docusaurus/utils-validation" "3.5.2"
+    cheerio "1.0.0-rc.12"
     feed "^4.2.2"
     fs-extra "^11.1.1"
     lodash "^4.17.21"
@@ -1488,18 +2281,20 @@
     utility-types "^3.10.0"
     webpack "^5.88.1"
 
-"@docusaurus/plugin-content-docs@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-content-docs/-/plugin-content-docs-3.1.1.tgz#f2eddebf351dd8dd504a2c26061165c519e1f964"
-  integrity sha512-lhFq4E874zw0UOH7ujzxnCayOyAt0f9YPVYSb9ohxrdCM8B4szxitUw9rIX4V9JLLHVoqIJb6k+lJJ1jrcGJ0A==
-  dependencies:
-    "@docusaurus/core" "3.1.1"
-    "@docusaurus/logger" "3.1.1"
-    "@docusaurus/mdx-loader" "3.1.1"
-    "@docusaurus/module-type-aliases" "3.1.1"
-    "@docusaurus/types" "3.1.1"
-    "@docusaurus/utils" "3.1.1"
-    "@docusaurus/utils-validation" "3.1.1"
+"@docusaurus/plugin-content-docs@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-content-docs/-/plugin-content-docs-3.5.2.tgz#adcf6c0bd9a9818eb192ab831e0069ee62d31505"
+  integrity sha512-Bt+OXn/CPtVqM3Di44vHjE7rPCEsRCB/DMo2qoOuozB9f7+lsdrHvD0QCHdBs0uhz6deYJDppAr2VgqybKPlVQ==
+  dependencies:
+    "@docusaurus/core" "3.5.2"
+    "@docusaurus/logger" "3.5.2"
+    "@docusaurus/mdx-loader" "3.5.2"
+    "@docusaurus/module-type-aliases" "3.5.2"
+    "@docusaurus/theme-common" "3.5.2"
+    "@docusaurus/types" "3.5.2"
+    "@docusaurus/utils" "3.5.2"
+    "@docusaurus/utils-common" "3.5.2"
+    "@docusaurus/utils-validation" "3.5.2"
     "@types/react-router-config" "^5.0.7"
     combine-promises "^1.1.0"
     fs-extra "^11.1.1"
@@ -1509,126 +2304,118 @@
     utility-types "^3.10.0"
     webpack "^5.88.1"
 
-"@docusaurus/plugin-content-pages@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-content-pages/-/plugin-content-pages-3.1.1.tgz#05aec68c2abeac2140c7a16d4c5b506bf4d19fb2"
-  integrity sha512-NQHncNRAJbyLtgTim9GlEnNYsFhuCxaCNkMwikuxLTiGIPH7r/jpb7O3f3jUMYMebZZZrDq5S7om9a6rvB/YCA==
-  dependencies:
-    "@docusaurus/core" "3.1.1"
-    "@docusaurus/mdx-loader" "3.1.1"
-    "@docusaurus/types" "3.1.1"
-    "@docusaurus/utils" "3.1.1"
-    "@docusaurus/utils-validation" "3.1.1"
+"@docusaurus/plugin-content-pages@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-content-pages/-/plugin-content-pages-3.5.2.tgz#2b59e43f5bc5b5176ff01835de706f1c65c2e68b"
+  integrity sha512-WzhHjNpoQAUz/ueO10cnundRz+VUtkjFhhaQ9jApyv1a46FPURO4cef89pyNIOMny1fjDz/NUN2z6Yi+5WUrCw==
+  dependencies:
+    "@docusaurus/core" "3.5.2"
+    "@docusaurus/mdx-loader" "3.5.2"
+    "@docusaurus/types" "3.5.2"
+    "@docusaurus/utils" "3.5.2"
+    "@docusaurus/utils-validation" "3.5.2"
     fs-extra "^11.1.1"
     tslib "^2.6.0"
     webpack "^5.88.1"
 
-"@docusaurus/plugin-debug@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-debug/-/plugin-debug-3.1.1.tgz#cee5aae1fef288fb93f68894db79a2612e313d3f"
-  integrity sha512-xWeMkueM9wE/8LVvl4+Qf1WqwXmreMjI5Kgr7GYCDoJ8zu4kD+KaMhrh7py7MNM38IFvU1RfrGKacCEe2DRRfQ==
+"@docusaurus/plugin-debug@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-debug/-/plugin-debug-3.5.2.tgz#c25ca6a59e62a17c797b367173fe80c06fdf2f65"
+  integrity sha512-kBK6GlN0itCkrmHuCS6aX1wmoWc5wpd5KJlqQ1FyrF0cLDnvsYSnh7+ftdwzt7G6lGBho8lrVwkkL9/iQvaSOA==
   dependencies:
-    "@docusaurus/core" "3.1.1"
-    "@docusaurus/types" "3.1.1"
-    "@docusaurus/utils" "3.1.1"
+    "@docusaurus/core" "3.5.2"
+    "@docusaurus/types" "3.5.2"
+    "@docusaurus/utils" "3.5.2"
     fs-extra "^11.1.1"
     react-json-view-lite "^1.2.0"
     tslib "^2.6.0"
 
-"@docusaurus/plugin-google-analytics@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-google-analytics/-/plugin-google-analytics-3.1.1.tgz#bfc58205b4fcaf3222e04f9c3542f3bef9804887"
-  integrity sha512-+q2UpWTqVi8GdlLoSlD5bS/YpxW+QMoBwrPrUH/NpvpuOi0Of7MTotsQf9JWd3hymZxl2uu1o3PIrbpxfeDFDQ==
+"@docusaurus/plugin-google-analytics@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-google-analytics/-/plugin-google-analytics-3.5.2.tgz#1143e78d1461d3c74a2746f036d25b18d4a2608d"
+  integrity sha512-rjEkJH/tJ8OXRE9bwhV2mb/WP93V441rD6XnM6MIluu7rk8qg38iSxS43ga2V2Q/2ib53PcqbDEJDG/yWQRJhQ==
   dependencies:
-    "@docusaurus/core" "3.1.1"
-    "@docusaurus/types" "3.1.1"
-    "@docusaurus/utils-validation" "3.1.1"
+    "@docusaurus/core" "3.5.2"
+    "@docusaurus/types" "3.5.2"
+    "@docusaurus/utils-validation" "3.5.2"
     tslib "^2.6.0"
 
-"@docusaurus/plugin-google-gtag@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-google-gtag/-/plugin-google-gtag-3.1.1.tgz#7e8b5aa6847a12461c104a65a335f4a45dae2f28"
-  integrity sha512-0mMPiBBlQ5LFHTtjxuvt/6yzh8v7OxLi3CbeEsxXZpUzcKO/GC7UA1VOWUoBeQzQL508J12HTAlR3IBU9OofSw==
+"@docusaurus/plugin-google-gtag@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-google-gtag/-/plugin-google-gtag-3.5.2.tgz#60b5a9e1888c4fa16933f7c5cb5f2f2c31caad3a"
+  integrity sha512-lm8XL3xLkTPHFKKjLjEEAHUrW0SZBSHBE1I+i/tmYMBsjCcUB5UJ52geS5PSiOCFVR74tbPGcPHEV/gaaxFeSA==
   dependencies:
-    "@docusaurus/core" "3.1.1"
-    "@docusaurus/types" "3.1.1"
-    "@docusaurus/utils-validation" "3.1.1"
+    "@docusaurus/core" "3.5.2"
+    "@docusaurus/types" "3.5.2"
+    "@docusaurus/utils-validation" "3.5.2"
     "@types/gtag.js" "^0.0.12"
     tslib "^2.6.0"
 
-"@docusaurus/plugin-google-tag-manager@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-google-tag-manager/-/plugin-google-tag-manager-3.1.1.tgz#e1aae4d821e786d133386b4ae6e6fe66a4bc0089"
-  integrity sha512-d07bsrMLdDIryDtY17DgqYUbjkswZQr8cLWl4tzXrt5OR/T/zxC1SYKajzB3fd87zTu5W5klV5GmUwcNSMXQXA==
+"@docusaurus/plugin-google-tag-manager@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-google-tag-manager/-/plugin-google-tag-manager-3.5.2.tgz#7a37334d2e7f00914d61ad05bc09391c4db3bfda"
+  integrity sha512-QkpX68PMOMu10Mvgvr5CfZAzZQFx8WLlOiUQ/Qmmcl6mjGK6H21WLT5x7xDmcpCoKA/3CegsqIqBR+nA137lQg==
   dependencies:
-    "@docusaurus/core" "3.1.1"
-    "@docusaurus/types" "3.1.1"
-    "@docusaurus/utils-validation" "3.1.1"
+    "@docusaurus/core" "3.5.2"
+    "@docusaurus/types" "3.5.2"
+    "@docusaurus/utils-validation" "3.5.2"
     tslib "^2.6.0"
 
-"@docusaurus/plugin-sitemap@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-sitemap/-/plugin-sitemap-3.1.1.tgz#8828bf5e2922273aad207a35189f22913e6a0dfd"
-  integrity sha512-iJ4hCaMmDaUqRv131XJdt/C/jJQx8UreDWTRqZKtNydvZVh/o4yXGRRFOplea1D9b/zpwL1Y+ZDwX7xMhIOTmg==
-  dependencies:
-    "@docusaurus/core" "3.1.1"
-    "@docusaurus/logger" "3.1.1"
-    "@docusaurus/types" "3.1.1"
-    "@docusaurus/utils" "3.1.1"
-    "@docusaurus/utils-common" "3.1.1"
-    "@docusaurus/utils-validation" "3.1.1"
+"@docusaurus/plugin-sitemap@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/plugin-sitemap/-/plugin-sitemap-3.5.2.tgz#9c940b27f3461c54d65295cf4c52cb20538bd360"
+  integrity sha512-DnlqYyRAdQ4NHY28TfHuVk414ft2uruP4QWCH//jzpHjqvKyXjj2fmDtI8RPUBh9K8iZKFMHRnLtzJKySPWvFA==
+  dependencies:
+    "@docusaurus/core" "3.5.2"
+    "@docusaurus/logger" "3.5.2"
+    "@docusaurus/types" "3.5.2"
+    "@docusaurus/utils" "3.5.2"
+    "@docusaurus/utils-common" "3.5.2"
+    "@docusaurus/utils-validation" "3.5.2"
     fs-extra "^11.1.1"
     sitemap "^7.1.1"
     tslib "^2.6.0"
 
-"@docusaurus/preset-classic@^3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/preset-classic/-/preset-classic-3.1.1.tgz#15fd80012529dafd7e01cc0bce59d39ee6ad6bf5"
-  integrity sha512-jG4ys/hWYf69iaN/xOmF+3kjs4Nnz1Ay3CjFLDtYa8KdxbmUhArA9HmP26ru5N0wbVWhY+6kmpYhTJpez5wTyg==
-  dependencies:
-    "@docusaurus/core" "3.1.1"
-    "@docusaurus/plugin-content-blog" "3.1.1"
-    "@docusaurus/plugin-content-docs" "3.1.1"
-    "@docusaurus/plugin-content-pages" "3.1.1"
-    "@docusaurus/plugin-debug" "3.1.1"
-    "@docusaurus/plugin-google-analytics" "3.1.1"
-    "@docusaurus/plugin-google-gtag" "3.1.1"
-    "@docusaurus/plugin-google-tag-manager" "3.1.1"
-    "@docusaurus/plugin-sitemap" "3.1.1"
-    "@docusaurus/theme-classic" "3.1.1"
-    "@docusaurus/theme-common" "3.1.1"
-    "@docusaurus/theme-search-algolia" "3.1.1"
-    "@docusaurus/types" "3.1.1"
-
-"@docusaurus/react-loadable@5.5.2", "react-loadable@npm:@docusaurus/react-loadable@5.5.2":
-  version "5.5.2"
-  resolved "https://registry.yarnpkg.com/@docusaurus/react-loadable/-/react-loadable-5.5.2.tgz#81aae0db81ecafbdaee3651f12804580868fa6ce"
-  integrity sha512-A3dYjdBGuy0IGT+wyLIGIKLRE+sAk1iNk0f1HjNDysO7u8lhL4N3VEm+FAubmJbAztn94F7MxBTPmnixbiyFdQ==
-  dependencies:
-    "@types/react" "*"
-    prop-types "^15.6.2"
-
-"@docusaurus/theme-classic@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/theme-classic/-/theme-classic-3.1.1.tgz#0a188c787fc4bf2bb525cc30c7aa34e555ee96b8"
-  integrity sha512-GiPE/jbWM8Qv1A14lk6s9fhc0LhPEQ00eIczRO4QL2nAQJZXkjPG6zaVx+1cZxPFWbAsqSjKe2lqkwF3fGkQ7Q==
-  dependencies:
-    "@docusaurus/core" "3.1.1"
-    "@docusaurus/mdx-loader" "3.1.1"
-    "@docusaurus/module-type-aliases" "3.1.1"
-    "@docusaurus/plugin-content-blog" "3.1.1"
-    "@docusaurus/plugin-content-docs" "3.1.1"
-    "@docusaurus/plugin-content-pages" "3.1.1"
-    "@docusaurus/theme-common" "3.1.1"
-    "@docusaurus/theme-translations" "3.1.1"
-    "@docusaurus/types" "3.1.1"
-    "@docusaurus/utils" "3.1.1"
-    "@docusaurus/utils-common" "3.1.1"
-    "@docusaurus/utils-validation" "3.1.1"
+"@docusaurus/preset-classic@^3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/preset-classic/-/preset-classic-3.5.2.tgz#977f78510bbc556aa0539149eef960bb7ab52bd9"
+  integrity sha512-3ihfXQ95aOHiLB5uCu+9PRy2gZCeSZoDcqpnDvf3B+sTrMvMTr8qRUzBvWkoIqc82yG5prCboRjk1SVILKx6sg==
+  dependencies:
+    "@docusaurus/core" "3.5.2"
+    "@docusaurus/plugin-content-blog" "3.5.2"
+    "@docusaurus/plugin-content-docs" "3.5.2"
+    "@docusaurus/plugin-content-pages" "3.5.2"
+    "@docusaurus/plugin-debug" "3.5.2"
+    "@docusaurus/plugin-google-analytics" "3.5.2"
+    "@docusaurus/plugin-google-gtag" "3.5.2"
+    "@docusaurus/plugin-google-tag-manager" "3.5.2"
+    "@docusaurus/plugin-sitemap" "3.5.2"
+    "@docusaurus/theme-classic" "3.5.2"
+    "@docusaurus/theme-common" "3.5.2"
+    "@docusaurus/theme-search-algolia" "3.5.2"
+    "@docusaurus/types" "3.5.2"
+
+"@docusaurus/theme-classic@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/theme-classic/-/theme-classic-3.5.2.tgz#602ddb63d987ab1f939e3760c67bc1880f01c000"
+  integrity sha512-XRpinSix3NBv95Rk7xeMF9k4safMkwnpSgThn0UNQNumKvmcIYjfkwfh2BhwYh/BxMXQHJ/PdmNh22TQFpIaYg==
+  dependencies:
+    "@docusaurus/core" "3.5.2"
+    "@docusaurus/mdx-loader" "3.5.2"
+    "@docusaurus/module-type-aliases" "3.5.2"
+    "@docusaurus/plugin-content-blog" "3.5.2"
+    "@docusaurus/plugin-content-docs" "3.5.2"
+    "@docusaurus/plugin-content-pages" "3.5.2"
+    "@docusaurus/theme-common" "3.5.2"
+    "@docusaurus/theme-translations" "3.5.2"
+    "@docusaurus/types" "3.5.2"
+    "@docusaurus/utils" "3.5.2"
+    "@docusaurus/utils-common" "3.5.2"
+    "@docusaurus/utils-validation" "3.5.2"
     "@mdx-js/react" "^3.0.0"
     clsx "^2.0.0"
     copy-text-to-clipboard "^3.2.0"
-    infima "0.2.0-alpha.43"
+    infima "0.2.0-alpha.44"
     lodash "^4.17.21"
     nprogress "^0.2.0"
     postcss "^8.4.26"
@@ -1639,18 +2426,15 @@
     tslib "^2.6.0"
     utility-types "^3.10.0"
 
-"@docusaurus/theme-common@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/theme-common/-/theme-common-3.1.1.tgz#5a16893928b8379c9e83aef01d753e7e142459e2"
-  integrity sha512-38urZfeMhN70YaXkwIGXmcUcv2CEYK/2l4b05GkJPrbEbgpsIZM3Xc+Js2ehBGGZmfZq8GjjQ5RNQYG+MYzCYg==
-  dependencies:
-    "@docusaurus/mdx-loader" "3.1.1"
-    "@docusaurus/module-type-aliases" "3.1.1"
-    "@docusaurus/plugin-content-blog" "3.1.1"
-    "@docusaurus/plugin-content-docs" "3.1.1"
-    "@docusaurus/plugin-content-pages" "3.1.1"
-    "@docusaurus/utils" "3.1.1"
-    "@docusaurus/utils-common" "3.1.1"
+"@docusaurus/theme-common@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/theme-common/-/theme-common-3.5.2.tgz#b507ab869a1fba0be9c3c9d74f2f3d74c3ac78b2"
+  integrity sha512-QXqlm9S6x9Ibwjs7I2yEDgsCocp708DrCrgHgKwg2n2AY0YQ6IjU0gAK35lHRLOvAoJUfCKpQAwUykB0R7+Eew==
+  dependencies:
+    "@docusaurus/mdx-loader" "3.5.2"
+    "@docusaurus/module-type-aliases" "3.5.2"
+    "@docusaurus/utils" "3.5.2"
+    "@docusaurus/utils-common" "3.5.2"
     "@types/history" "^4.7.11"
     "@types/react" "*"
     "@types/react-router-config" "*"
@@ -1660,19 +2444,19 @@
     tslib "^2.6.0"
     utility-types "^3.10.0"
 
-"@docusaurus/theme-search-algolia@3.1.1", "@docusaurus/theme-search-algolia@^3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/theme-search-algolia/-/theme-search-algolia-3.1.1.tgz#5170cd68cc59d150416b070bdc6d15c363ddf5e1"
-  integrity sha512-tBH9VY5EpRctVdaAhT+b1BY8y5dyHVZGFXyCHgTrvcXQy5CV4q7serEX7U3SveNT9zksmchPyct6i1sFDC4Z5g==
+"@docusaurus/theme-search-algolia@3.5.2", "@docusaurus/theme-search-algolia@^3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/theme-search-algolia/-/theme-search-algolia-3.5.2.tgz#466c83ca7e8017d95ae6889ccddc5ef8bf6b61c6"
+  integrity sha512-qW53kp3VzMnEqZGjakaV90sst3iN1o32PH+nawv1uepROO8aEGxptcq2R5rsv7aBShSRbZwIobdvSYKsZ5pqvA==
   dependencies:
     "@docsearch/react" "^3.5.2"
-    "@docusaurus/core" "3.1.1"
-    "@docusaurus/logger" "3.1.1"
-    "@docusaurus/plugin-content-docs" "3.1.1"
-    "@docusaurus/theme-common" "3.1.1"
-    "@docusaurus/theme-translations" "3.1.1"
-    "@docusaurus/utils" "3.1.1"
-    "@docusaurus/utils-validation" "3.1.1"
+    "@docusaurus/core" "3.5.2"
+    "@docusaurus/logger" "3.5.2"
+    "@docusaurus/plugin-content-docs" "3.5.2"
+    "@docusaurus/theme-common" "3.5.2"
+    "@docusaurus/theme-translations" "3.5.2"
+    "@docusaurus/utils" "3.5.2"
+    "@docusaurus/utils-validation" "3.5.2"
     algoliasearch "^4.18.0"
     algoliasearch-helper "^3.13.3"
     clsx "^2.0.0"
@@ -1682,18 +2466,18 @@
     tslib "^2.6.0"
     utility-types "^3.10.0"
 
-"@docusaurus/theme-translations@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/theme-translations/-/theme-translations-3.1.1.tgz#117e91ba5e3a8178cb59f3028bf41de165a508c1"
-  integrity sha512-xvWQFwjxHphpJq5fgk37FXCDdAa2o+r7FX8IpMg+bGZBNXyWBu3MjZ+G4+eUVNpDhVinTc+j6ucL0Ain5KCGrg==
+"@docusaurus/theme-translations@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/theme-translations/-/theme-translations-3.5.2.tgz#38f9ebf2a5d860397022206a05fef66c08863c89"
+  integrity sha512-GPZLcu4aT1EmqSTmbdpVrDENGR2yObFEX8ssEFYTCiAIVc0EihNSdOIBTazUvgNqwvnoU1A8vIs1xyzc3LITTw==
   dependencies:
     fs-extra "^11.1.1"
     tslib "^2.6.0"
 
-"@docusaurus/types@3.1.1", "@docusaurus/types@^3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/types/-/types-3.1.1.tgz#747c9dee8cf7c3b0e5ee7351bac5e9c4fdc7f259"
-  integrity sha512-grBqOLnubUecgKFXN9q3uit2HFbCxTWX4Fam3ZFbMN0sWX9wOcDoA7lwdX/8AmeL20Oc4kQvWVgNrsT8bKRvzg==
+"@docusaurus/types@3.5.2", "@docusaurus/types@^3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/types/-/types-3.5.2.tgz#058019dbeffbee2d412c3f72569e412a727f9608"
+  integrity sha512-N6GntLXoLVUwkZw7zCxwy9QiuEXIcTVzA9AkmNw16oc0AP3SXLrMmDMMBIfgqwuKWa6Ox6epHol9kMtJqekACw==
   dependencies:
     "@mdx-js/mdx" "^3.0.0"
     "@types/history" "^4.7.11"
@@ -1705,31 +2489,35 @@
     webpack "^5.88.1"
     webpack-merge "^5.9.0"
 
-"@docusaurus/utils-common@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/utils-common/-/utils-common-3.1.1.tgz#b48fade63523fd40f3adb67b47c3371e5183c20b"
-  integrity sha512-eGne3olsIoNfPug5ixjepZAIxeYFzHHnor55Wb2P57jNbtVaFvij/T+MS8U0dtZRFi50QU+UPmRrXdVUM8uyMg==
+"@docusaurus/utils-common@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/utils-common/-/utils-common-3.5.2.tgz#4d7f5e962fbca3e2239d80457aa0e4bd3d8f7e0a"
+  integrity sha512-i0AZjHiRgJU6d7faQngIhuHKNrszpL/SHQPgF1zH4H+Ij6E9NBYGy6pkcGWToIv7IVPbs+pQLh1P3whn0gWXVg==
   dependencies:
     tslib "^2.6.0"
 
-"@docusaurus/utils-validation@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/utils-validation/-/utils-validation-3.1.1.tgz#3a747349ed05aee0e4d543552b41f3c9467ee731"
-  integrity sha512-KlY4P9YVDnwL+nExvlIpu79abfEv6ZCHuOX4ZQ+gtip+Wxj0daccdReIWWtqxM/Fb5Cz1nQvUCc7VEtT8IBUAA==
+"@docusaurus/utils-validation@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/utils-validation/-/utils-validation-3.5.2.tgz#1b2b2f02082781cc8ce713d4c85e88d6d2fc4eb3"
+  integrity sha512-m+Foq7augzXqB6HufdS139PFxDC5d5q2QKZy8q0qYYvGdI6nnlNsGH4cIGsgBnV7smz+mopl3g4asbSDvMV0jA==
   dependencies:
-    "@docusaurus/logger" "3.1.1"
-    "@docusaurus/utils" "3.1.1"
+    "@docusaurus/logger" "3.5.2"
+    "@docusaurus/utils" "3.5.2"
+    "@docusaurus/utils-common" "3.5.2"
+    fs-extra "^11.2.0"
     joi "^17.9.2"
     js-yaml "^4.1.0"
+    lodash "^4.17.21"
     tslib "^2.6.0"
 
-"@docusaurus/utils@3.1.1":
-  version "3.1.1"
-  resolved "https://registry.yarnpkg.com/@docusaurus/utils/-/utils-3.1.1.tgz#e822d14704e4b3bb451ca464a7cc56aea9b55a45"
-  integrity sha512-ZJfJa5cJQtRYtqijsPEnAZoduW6sjAQ7ZCWSZavLcV10Fw0Z3gSaPKA/B4micvj2afRZ4gZxT7KfYqe5H8Cetg==
+"@docusaurus/utils@3.5.2":
+  version "3.5.2"
+  resolved "https://registry.yarnpkg.com/@docusaurus/utils/-/utils-3.5.2.tgz#17763130215f18d7269025903588ef7fb373e2cb"
+  integrity sha512-33QvcNFh+Gv+C2dP9Y9xWEzMgf3JzrpL2nW9PopidiohS1nDcyknKRx2DWaFvyVTTYIkkABVSr073VTj/NITNA==
   dependencies:
-    "@docusaurus/logger" "3.1.1"
-    "@svgr/webpack" "^6.5.1"
+    "@docusaurus/logger" "3.5.2"
+    "@docusaurus/utils-common" "3.5.2"
+    "@svgr/webpack" "^8.1.0"
     escape-string-regexp "^4.0.0"
     file-loader "^6.2.0"
     fs-extra "^11.1.1"
@@ -1740,10 +2528,12 @@
     js-yaml "^4.1.0"
     lodash "^4.17.21"
     micromatch "^4.0.5"
+    prompts "^2.4.2"
     resolve-pathname "^3.0.0"
     shelljs "^0.8.5"
     tslib "^2.6.0"
     url-loader "^4.1.1"
+    utility-types "^3.10.0"
     webpack "^5.88.1"
 
 "@hapi/hoek@^9.0.0":
@@ -1786,6 +2576,15 @@
     "@jridgewell/sourcemap-codec" "^1.4.10"
     "@jridgewell/trace-mapping" "^0.3.9"
 
+"@jridgewell/gen-mapping@^0.3.5":
+  version "0.3.5"
+  resolved "https://registry.yarnpkg.com/@jridgewell/gen-mapping/-/gen-mapping-0.3.5.tgz#dcce6aff74bdf6dad1a95802b69b04a2fcb1fb36"
+  integrity sha512-IzL8ZoEDIBRWEzlCcRhOaCupYyN5gdIK+Q6fbFdPDg6HqX6jpkItn7DFIpW9LQzXG6Df9sA7+OKnq0qlz/GaQg==
+  dependencies:
+    "@jridgewell/set-array" "^1.2.1"
+    "@jridgewell/sourcemap-codec" "^1.4.10"
+    "@jridgewell/trace-mapping" "^0.3.24"
+
 "@jridgewell/resolve-uri@^3.1.0":
   version "3.1.1"
   resolved "https://registry.yarnpkg.com/@jridgewell/resolve-uri/-/resolve-uri-3.1.1.tgz#c08679063f279615a3326583ba3a90d1d82cc721"
@@ -1796,6 +2595,11 @@
   resolved "https://registry.yarnpkg.com/@jridgewell/set-array/-/set-array-1.1.2.tgz#7c6cf998d6d20b914c0a55a91ae928ff25965e72"
   integrity sha512-xnkseuNADM0gt2bs+BvhO0p78Mk762YnZdsuzFV018NoG1Sj1SCQvpSqa7XUaTam5vAGasABV9qXASMKnFMwMw==
 
+"@jridgewell/set-array@^1.2.1":
+  version "1.2.1"
+  resolved "https://registry.yarnpkg.com/@jridgewell/set-array/-/set-array-1.2.1.tgz#558fb6472ed16a4c850b889530e6b36438c49280"
+  integrity sha512-R8gLRTZeyp03ymzP/6Lil/28tGeGEzhx1q2k703KGWRAI1VdvPIXdG70VJc2pAMw3NA6JKL5hhFu1sJX0Mnn/A==
+
 "@jridgewell/source-map@^0.3.3":
   version "0.3.5"
   resolved "https://registry.yarnpkg.com/@jridgewell/source-map/-/source-map-0.3.5.tgz#a3bb4d5c6825aab0d281268f47f6ad5853431e91"
@@ -1817,6 +2621,14 @@
     "@jridgewell/resolve-uri" "^3.1.0"
     "@jridgewell/sourcemap-codec" "^1.4.14"
 
+"@jridgewell/trace-mapping@^0.3.18", "@jridgewell/trace-mapping@^0.3.24", "@jridgewell/trace-mapping@^0.3.25":
+  version "0.3.25"
+  resolved "https://registry.yarnpkg.com/@jridgewell/trace-mapping/-/trace-mapping-0.3.25.tgz#15f190e98895f3fc23276ee14bc76b675c2e50f0"
+  integrity sha512-vNk6aEwybGtawWmy/PzwnGDOjCkLWSD2wqvjGGAgOAwCGWySYXfYoxt00IJkTF+8Lb57DwOb3Aa0o9CApepiYQ==
+  dependencies:
+    "@jridgewell/resolve-uri" "^3.1.0"
+    "@jridgewell/sourcemap-codec" "^1.4.14"
+
 "@leichtgewicht/ip-codec@^2.0.1":
   version "2.0.4"
   resolved "https://registry.yarnpkg.com/@leichtgewicht/ip-codec/-/ip-codec-2.0.4.tgz#b2ac626d6cb9c8718ab459166d4bb405b8ffa78b"
@@ -1946,120 +2758,111 @@
     micromark-util-character "^1.1.0"
     micromark-util-symbol "^1.0.1"
 
-"@slorber/static-site-generator-webpack-plugin@^4.0.7":
-  version "4.0.7"
-  resolved "https://registry.yarnpkg.com/@slorber/static-site-generator-webpack-plugin/-/static-site-generator-webpack-plugin-4.0.7.tgz#fc1678bddefab014e2145cbe25b3ce4e1cfc36f3"
-  integrity sha512-Ug7x6z5lwrz0WqdnNFOMYrDQNTPAprvHLSh6+/fmml3qUiz6l5eq+2MzLKWtn/q5K5NpSiFsZTP/fck/3vjSxA==
-  dependencies:
-    eval "^0.1.8"
-    p-map "^4.0.0"
-    webpack-sources "^3.2.2"
-
-"@svgr/babel-plugin-add-jsx-attribute@^6.5.1":
-  version "6.5.1"
-  resolved "https://registry.yarnpkg.com/@svgr/babel-plugin-add-jsx-attribute/-/babel-plugin-add-jsx-attribute-6.5.1.tgz#74a5d648bd0347bda99d82409d87b8ca80b9a1ba"
-  integrity sha512-9PYGcXrAxitycIjRmZB+Q0JaN07GZIWaTBIGQzfaZv+qr1n8X1XUEJ5rZ/vx6OVD9RRYlrNnXWExQXcmZeD/BQ==
+"@svgr/babel-plugin-add-jsx-attribute@8.0.0":
+  version "8.0.0"
+  resolved "https://registry.yarnpkg.com/@svgr/babel-plugin-add-jsx-attribute/-/babel-plugin-add-jsx-attribute-8.0.0.tgz#4001f5d5dd87fa13303e36ee106e3ff3a7eb8b22"
+  integrity sha512-b9MIk7yhdS1pMCZM8VeNfUlSKVRhsHZNMl5O9SfaX0l0t5wjdgu4IDzGB8bpnGBBOjGST3rRFVsaaEtI4W6f7g==
 
-"@svgr/babel-plugin-remove-jsx-attribute@*":
+"@svgr/babel-plugin-remove-jsx-attribute@8.0.0":
   version "8.0.0"
   resolved "https://registry.yarnpkg.com/@svgr/babel-plugin-remove-jsx-attribute/-/babel-plugin-remove-jsx-attribute-8.0.0.tgz#69177f7937233caca3a1afb051906698f2f59186"
   integrity sha512-BcCkm/STipKvbCl6b7QFrMh/vx00vIP63k2eM66MfHJzPr6O2U0jYEViXkHJWqXqQYjdeA9cuCl5KWmlwjDvbA==
 
-"@svgr/babel-plugin-remove-jsx-empty-expression@*":
+"@svgr/babel-plugin-remove-jsx-empty-expression@8.0.0":
   version "8.0.0"
   resolved "https://registry.yarnpkg.com/@svgr/babel-plugin-remove-jsx-empty-expression/-/babel-plugin-remove-jsx-empty-expression-8.0.0.tgz#c2c48104cfd7dcd557f373b70a56e9e3bdae1d44"
   integrity sha512-5BcGCBfBxB5+XSDSWnhTThfI9jcO5f0Ai2V24gZpG+wXF14BzwxxdDb4g6trdOux0rhibGs385BeFMSmxtS3uA==
 
-"@svgr/babel-plugin-replace-jsx-attribute-value@^6.5.1":
-  version "6.5.1"
-  resolved "https://registry.yarnpkg.com/@svgr/babel-plugin-replace-jsx-attribute-value/-/babel-plugin-replace-jsx-attribute-value-6.5.1.tgz#fb9d22ea26d2bc5e0a44b763d4c46d5d3f596c60"
-  integrity sha512-8DPaVVE3fd5JKuIC29dqyMB54sA6mfgki2H2+swh+zNJoynC8pMPzOkidqHOSc6Wj032fhl8Z0TVn1GiPpAiJg==
-
-"@svgr/babel-plugin-svg-dynamic-title@^6.5.1":
-  version "6.5.1"
-  resolved "https://registry.yarnpkg.com/@svgr/babel-plugin-svg-dynamic-title/-/babel-plugin-svg-dynamic-title-6.5.1.tgz#01b2024a2b53ffaa5efceaa0bf3e1d5a4c520ce4"
-  integrity sha512-FwOEi0Il72iAzlkaHrlemVurgSQRDFbk0OC8dSvD5fSBPHltNh7JtLsxmZUhjYBZo2PpcU/RJvvi6Q0l7O7ogw==
-
-"@svgr/babel-plugin-svg-em-dimensions@^6.5.1":
-  version "6.5.1"
-  resolved "https://registry.yarnpkg.com/@svgr/babel-plugin-svg-em-dimensions/-/babel-plugin-svg-em-dimensions-6.5.1.tgz#dd3fa9f5b24eb4f93bcf121c3d40ff5facecb217"
-  integrity sha512-gWGsiwjb4tw+ITOJ86ndY/DZZ6cuXMNE/SjcDRg+HLuCmwpcjOktwRF9WgAiycTqJD/QXqL2f8IzE2Rzh7aVXA==
-
-"@svgr/babel-plugin-transform-react-native-svg@^6.5.1":
-  version "6.5.1"
-  resolved "https://registry.yarnpkg.com/@svgr/babel-plugin-transform-react-native-svg/-/babel-plugin-transform-react-native-svg-6.5.1.tgz#1d8e945a03df65b601551097d8f5e34351d3d305"
-  integrity sha512-2jT3nTayyYP7kI6aGutkyfJ7UMGtuguD72OjeGLwVNyfPRBD8zQthlvL+fAbAKk5n9ZNcvFkp/b1lZ7VsYqVJg==
-
-"@svgr/babel-plugin-transform-svg-component@^6.5.1":
-  version "6.5.1"
-  resolved "https://registry.yarnpkg.com/@svgr/babel-plugin-transform-svg-component/-/babel-plugin-transform-svg-component-6.5.1.tgz#48620b9e590e25ff95a80f811544218d27f8a250"
-  integrity sha512-a1p6LF5Jt33O3rZoVRBqdxL350oge54iZWHNI6LJB5tQ7EelvD/Mb1mfBiZNAan0dt4i3VArkFRjA4iObuNykQ==
-
-"@svgr/babel-preset@^6.5.1":
-  version "6.5.1"
-  resolved "https://registry.yarnpkg.com/@svgr/babel-preset/-/babel-preset-6.5.1.tgz#b90de7979c8843c5c580c7e2ec71f024b49eb828"
-  integrity sha512-6127fvO/FF2oi5EzSQOAjo1LE3OtNVh11R+/8FXa+mHx1ptAaS4cknIjnUA7e6j6fwGGJ17NzaTJFUwOV2zwCw==
-  dependencies:
-    "@svgr/babel-plugin-add-jsx-attribute" "^6.5.1"
-    "@svgr/babel-plugin-remove-jsx-attribute" "*"
-    "@svgr/babel-plugin-remove-jsx-empty-expression" "*"
-    "@svgr/babel-plugin-replace-jsx-attribute-value" "^6.5.1"
-    "@svgr/babel-plugin-svg-dynamic-title" "^6.5.1"
-    "@svgr/babel-plugin-svg-em-dimensions" "^6.5.1"
-    "@svgr/babel-plugin-transform-react-native-svg" "^6.5.1"
-    "@svgr/babel-plugin-transform-svg-component" "^6.5.1"
-
-"@svgr/core@^6.5.1":
-  version "6.5.1"
-  resolved "https://registry.yarnpkg.com/@svgr/core/-/core-6.5.1.tgz#d3e8aa9dbe3fbd747f9ee4282c1c77a27410488a"
-  integrity sha512-/xdLSWxK5QkqG524ONSjvg3V/FkNyCv538OIBdQqPNaAta3AsXj/Bd2FbvR87yMbXO2hFSWiAe/Q6IkVPDw+mw==
-  dependencies:
-    "@babel/core" "^7.19.6"
-    "@svgr/babel-preset" "^6.5.1"
-    "@svgr/plugin-jsx" "^6.5.1"
+"@svgr/babel-plugin-replace-jsx-attribute-value@8.0.0":
+  version "8.0.0"
+  resolved "https://registry.yarnpkg.com/@svgr/babel-plugin-replace-jsx-attribute-value/-/babel-plugin-replace-jsx-attribute-value-8.0.0.tgz#8fbb6b2e91fa26ac5d4aa25c6b6e4f20f9c0ae27"
+  integrity sha512-KVQ+PtIjb1BuYT3ht8M5KbzWBhdAjjUPdlMtpuw/VjT8coTrItWX6Qafl9+ji831JaJcu6PJNKCV0bp01lBNzQ==
+
+"@svgr/babel-plugin-svg-dynamic-title@8.0.0":
+  version "8.0.0"
+  resolved "https://registry.yarnpkg.com/@svgr/babel-plugin-svg-dynamic-title/-/babel-plugin-svg-dynamic-title-8.0.0.tgz#1d5ba1d281363fc0f2f29a60d6d936f9bbc657b0"
+  integrity sha512-omNiKqwjNmOQJ2v6ge4SErBbkooV2aAWwaPFs2vUY7p7GhVkzRkJ00kILXQvRhA6miHnNpXv7MRnnSjdRjK8og==
+
+"@svgr/babel-plugin-svg-em-dimensions@8.0.0":
+  version "8.0.0"
+  resolved "https://registry.yarnpkg.com/@svgr/babel-plugin-svg-em-dimensions/-/babel-plugin-svg-em-dimensions-8.0.0.tgz#35e08df300ea8b1d41cb8f62309c241b0369e501"
+  integrity sha512-mURHYnu6Iw3UBTbhGwE/vsngtCIbHE43xCRK7kCw4t01xyGqb2Pd+WXekRRoFOBIY29ZoOhUCTEweDMdrjfi9g==
+
+"@svgr/babel-plugin-transform-react-native-svg@8.1.0":
+  version "8.1.0"
+  resolved "https://registry.yarnpkg.com/@svgr/babel-plugin-transform-react-native-svg/-/babel-plugin-transform-react-native-svg-8.1.0.tgz#90a8b63998b688b284f255c6a5248abd5b28d754"
+  integrity sha512-Tx8T58CHo+7nwJ+EhUwx3LfdNSG9R2OKfaIXXs5soiy5HtgoAEkDay9LIimLOcG8dJQH1wPZp/cnAv6S9CrR1Q==
+
+"@svgr/babel-plugin-transform-svg-component@8.0.0":
+  version "8.0.0"
+  resolved "https://registry.yarnpkg.com/@svgr/babel-plugin-transform-svg-component/-/babel-plugin-transform-svg-component-8.0.0.tgz#013b4bfca88779711f0ed2739f3f7efcefcf4f7e"
+  integrity sha512-DFx8xa3cZXTdb/k3kfPeaixecQLgKh5NVBMwD0AQxOzcZawK4oo1Jh9LbrcACUivsCA7TLG8eeWgrDXjTMhRmw==
+
+"@svgr/babel-preset@8.1.0":
+  version "8.1.0"
+  resolved "https://registry.yarnpkg.com/@svgr/babel-preset/-/babel-preset-8.1.0.tgz#0e87119aecdf1c424840b9d4565b7137cabf9ece"
+  integrity sha512-7EYDbHE7MxHpv4sxvnVPngw5fuR6pw79SkcrILHJ/iMpuKySNCl5W1qcwPEpU+LgyRXOaAFgH0KhwD18wwg6ug==
+  dependencies:
+    "@svgr/babel-plugin-add-jsx-attribute" "8.0.0"
+    "@svgr/babel-plugin-remove-jsx-attribute" "8.0.0"
+    "@svgr/babel-plugin-remove-jsx-empty-expression" "8.0.0"
+    "@svgr/babel-plugin-replace-jsx-attribute-value" "8.0.0"
+    "@svgr/babel-plugin-svg-dynamic-title" "8.0.0"
+    "@svgr/babel-plugin-svg-em-dimensions" "8.0.0"
+    "@svgr/babel-plugin-transform-react-native-svg" "8.1.0"
+    "@svgr/babel-plugin-transform-svg-component" "8.0.0"
+
+"@svgr/core@8.1.0":
+  version "8.1.0"
+  resolved "https://registry.yarnpkg.com/@svgr/core/-/core-8.1.0.tgz#41146f9b40b1a10beaf5cc4f361a16a3c1885e88"
+  integrity sha512-8QqtOQT5ACVlmsvKOJNEaWmRPmcojMOzCz4Hs2BGG/toAp/K38LcsMRyLp349glq5AzJbCEeimEoxaX6v/fLrA==
+  dependencies:
+    "@babel/core" "^7.21.3"
+    "@svgr/babel-preset" "8.1.0"
     camelcase "^6.2.0"
-    cosmiconfig "^7.0.1"
+    cosmiconfig "^8.1.3"
+    snake-case "^3.0.4"
 
-"@svgr/hast-util-to-babel-ast@^6.5.1":
-  version "6.5.1"
-  resolved "https://registry.yarnpkg.com/@svgr/hast-util-to-babel-ast/-/hast-util-to-babel-ast-6.5.1.tgz#81800bd09b5bcdb968bf6ee7c863d2288fdb80d2"
-  integrity sha512-1hnUxxjd83EAxbL4a0JDJoD3Dao3hmjvyvyEV8PzWmLK3B9m9NPlW7GKjFyoWE8nM7HnXzPcmmSyOW8yOddSXw==
+"@svgr/hast-util-to-babel-ast@8.0.0":
+  version "8.0.0"
+  resolved "https://registry.yarnpkg.com/@svgr/hast-util-to-babel-ast/-/hast-util-to-babel-ast-8.0.0.tgz#6952fd9ce0f470e1aded293b792a2705faf4ffd4"
+  integrity sha512-EbDKwO9GpfWP4jN9sGdYwPBU0kdomaPIL2Eu4YwmgP+sJeXT+L7bMwJUBnhzfH8Q2qMBqZ4fJwpCyYsAN3mt2Q==
   dependencies:
-    "@babel/types" "^7.20.0"
+    "@babel/types" "^7.21.3"
     entities "^4.4.0"
 
-"@svgr/plugin-jsx@^6.5.1":
-  version "6.5.1"
-  resolved "https://registry.yarnpkg.com/@svgr/plugin-jsx/-/plugin-jsx-6.5.1.tgz#0e30d1878e771ca753c94e69581c7971542a7072"
-  integrity sha512-+UdQxI3jgtSjCykNSlEMuy1jSRQlGC7pqBCPvkG/2dATdWo082zHTTK3uhnAju2/6XpE6B5mZ3z4Z8Ns01S8Gw==
+"@svgr/plugin-jsx@8.1.0":
+  version "8.1.0"
+  resolved "https://registry.yarnpkg.com/@svgr/plugin-jsx/-/plugin-jsx-8.1.0.tgz#96969f04a24b58b174ee4cd974c60475acbd6928"
+  integrity sha512-0xiIyBsLlr8quN+WyuxooNW9RJ0Dpr8uOnH/xrCVO8GLUcwHISwj1AG0k+LFzteTkAA0GbX0kj9q6Dk70PTiPA==
   dependencies:
-    "@babel/core" "^7.19.6"
-    "@svgr/babel-preset" "^6.5.1"
-    "@svgr/hast-util-to-babel-ast" "^6.5.1"
+    "@babel/core" "^7.21.3"
+    "@svgr/babel-preset" "8.1.0"
+    "@svgr/hast-util-to-babel-ast" "8.0.0"
     svg-parser "^2.0.4"
 
-"@svgr/plugin-svgo@^6.5.1":
-  version "6.5.1"
-  resolved "https://registry.yarnpkg.com/@svgr/plugin-svgo/-/plugin-svgo-6.5.1.tgz#0f91910e988fc0b842f88e0960c2862e022abe84"
-  integrity sha512-omvZKf8ixP9z6GWgwbtmP9qQMPX4ODXi+wzbVZgomNFsUIlHA1sf4fThdwTWSsZGgvGAG6yE+b/F5gWUkcZ/iQ==
+"@svgr/plugin-svgo@8.1.0":
+  version "8.1.0"
+  resolved "https://registry.yarnpkg.com/@svgr/plugin-svgo/-/plugin-svgo-8.1.0.tgz#b115b7b967b564f89ac58feae89b88c3decd0f00"
+  integrity sha512-Ywtl837OGO9pTLIN/onoWLmDQ4zFUycI1g76vuKGEz6evR/ZTJlJuz3G/fIkb6OVBJ2g0o6CGJzaEjfmEo3AHA==
   dependencies:
-    cosmiconfig "^7.0.1"
-    deepmerge "^4.2.2"
-    svgo "^2.8.0"
+    cosmiconfig "^8.1.3"
+    deepmerge "^4.3.1"
+    svgo "^3.0.2"
 
-"@svgr/webpack@^6.5.1":
-  version "6.5.1"
-  resolved "https://registry.yarnpkg.com/@svgr/webpack/-/webpack-6.5.1.tgz#ecf027814fc1cb2decc29dc92f39c3cf691e40e8"
-  integrity sha512-cQ/AsnBkXPkEK8cLbv4Dm7JGXq2XrumKnL1dRpJD9rIO2fTIlJI9a1uCciYG1F2aUsox/hJQyNGbt3soDxSRkA==
+"@svgr/webpack@^8.1.0":
+  version "8.1.0"
+  resolved "https://registry.yarnpkg.com/@svgr/webpack/-/webpack-8.1.0.tgz#16f1b5346f102f89fda6ec7338b96a701d8be0c2"
+  integrity sha512-LnhVjMWyMQV9ZmeEy26maJk+8HTIbd59cH4F2MJ439k9DqejRisfFNGAPvRYlKETuh9LrImlS8aKsBgKjMA8WA==
   dependencies:
-    "@babel/core" "^7.19.6"
-    "@babel/plugin-transform-react-constant-elements" "^7.18.12"
-    "@babel/preset-env" "^7.19.4"
+    "@babel/core" "^7.21.3"
+    "@babel/plugin-transform-react-constant-elements" "^7.21.3"
+    "@babel/preset-env" "^7.20.2"
     "@babel/preset-react" "^7.18.6"
-    "@babel/preset-typescript" "^7.18.6"
-    "@svgr/core" "^6.5.1"
-    "@svgr/plugin-jsx" "^6.5.1"
-    "@svgr/plugin-svgo" "^6.5.1"
+    "@babel/preset-typescript" "^7.21.0"
+    "@svgr/core" "8.1.0"
+    "@svgr/plugin-jsx" "8.1.0"
+    "@svgr/plugin-svgo" "8.1.0"
 
 "@szmarczak/http-timer@^5.0.1":
   version "5.0.1"
@@ -2745,7 +3548,7 @@ at-least-node@^1.0.0:
   resolved "https://registry.yarnpkg.com/at-least-node/-/at-least-node-1.0.0.tgz#602cd4b46e844ad4effc92a8011a3c46e0238dc2"
   integrity sha512-+q/t7Ekv1EDY2l6Gda6LLiX14rU9TV20Wa3ofeQmwPFZbOMo9DXrLbOjFaaclkXKWidIaopwAObQDqwWtGUjqg==
 
-autoprefixer@^10.4.12, autoprefixer@^10.4.14:
+autoprefixer@^10.4.14:
   version "10.4.16"
   resolved "https://registry.yarnpkg.com/autoprefixer/-/autoprefixer-10.4.16.tgz#fad1411024d8670880bdece3970aa72e3572feb8"
   integrity sha512-7vd3UC6xKp0HLfua5IjZlcXvGAGy7cBAXTg2lyQ/8WpNhd6SiZ8Be+xm3FyBSYJx5GKcpRCzBh7RH4/0dnY+uQ==
@@ -2757,6 +3560,18 @@ autoprefixer@^10.4.12, autoprefixer@^10.4.14:
     picocolors "^1.0.0"
     postcss-value-parser "^4.2.0"
 
+autoprefixer@^10.4.19:
+  version "10.4.20"
+  resolved "https://registry.yarnpkg.com/autoprefixer/-/autoprefixer-10.4.20.tgz#5caec14d43976ef42e32dcb4bd62878e96be5b3b"
+  integrity sha512-XY25y5xSv/wEoqzDyXXME4AFfkZI0P23z6Fs3YgymDnKJkCGOnkL0iTxCa85UTqaSgfcqyf3UA6+c7wUvx/16g==
+  dependencies:
+    browserslist "^4.23.3"
+    caniuse-lite "^1.0.30001646"
+    fraction.js "^4.3.7"
+    normalize-range "^0.1.2"
+    picocolors "^1.0.1"
+    postcss-value-parser "^4.2.0"
+
 babel-loader@^9.1.3:
   version "9.1.3"
   resolved "https://registry.yarnpkg.com/babel-loader/-/babel-loader-9.1.3.tgz#3d0e01b4e69760cc694ee306fe16d358aa1c6f9a"
@@ -2772,6 +3587,15 @@ babel-plugin-dynamic-import-node@^2.3.3:
   dependencies:
     object.assign "^4.1.0"
 
+babel-plugin-polyfill-corejs2@^0.4.10:
+  version "0.4.11"
+  resolved "https://registry.yarnpkg.com/babel-plugin-polyfill-corejs2/-/babel-plugin-polyfill-corejs2-0.4.11.tgz#30320dfe3ffe1a336c15afdcdafd6fd615b25e33"
+  integrity sha512-sMEJ27L0gRHShOh5G54uAAPaiCOygY/5ratXuiyb2G46FmlSpc9eFCzYVyDiPxfNbwzA7mYahmjQc5q+CZQ09Q==
+  dependencies:
+    "@babel/compat-data" "^7.22.6"
+    "@babel/helper-define-polyfill-provider" "^0.6.2"
+    semver "^6.3.1"
+
 babel-plugin-polyfill-corejs2@^0.4.6:
   version "0.4.6"
   resolved "https://registry.yarnpkg.com/babel-plugin-polyfill-corejs2/-/babel-plugin-polyfill-corejs2-0.4.6.tgz#b2df0251d8e99f229a8e60fc4efa9a68b41c8313"
@@ -2781,6 +3605,14 @@ babel-plugin-polyfill-corejs2@^0.4.6:
     "@babel/helper-define-polyfill-provider" "^0.4.3"
     semver "^6.3.1"
 
+babel-plugin-polyfill-corejs3@^0.10.6:
+  version "0.10.6"
+  resolved "https://registry.yarnpkg.com/babel-plugin-polyfill-corejs3/-/babel-plugin-polyfill-corejs3-0.10.6.tgz#2deda57caef50f59c525aeb4964d3b2f867710c7"
+  integrity sha512-b37+KR2i/khY5sKmWNVQAnitvquQbNdWy6lJdsr0kmquCKEEUgMKK4SboVM3HtfnZilfjr4MMQ7vY58FVWDtIA==
+  dependencies:
+    "@babel/helper-define-polyfill-provider" "^0.6.2"
+    core-js-compat "^3.38.0"
+
 babel-plugin-polyfill-corejs3@^0.8.5:
   version "0.8.6"
   resolved "https://registry.yarnpkg.com/babel-plugin-polyfill-corejs3/-/babel-plugin-polyfill-corejs3-0.8.6.tgz#25c2d20002da91fe328ff89095c85a391d6856cf"
@@ -2796,6 +3628,13 @@ babel-plugin-polyfill-regenerator@^0.5.3:
   dependencies:
     "@babel/helper-define-polyfill-provider" "^0.4.3"
 
+babel-plugin-polyfill-regenerator@^0.6.1:
+  version "0.6.2"
+  resolved "https://registry.yarnpkg.com/babel-plugin-polyfill-regenerator/-/babel-plugin-polyfill-regenerator-0.6.2.tgz#addc47e240edd1da1058ebda03021f382bba785e"
+  integrity sha512-2R25rQZWP63nGwaAswvDazbPXfrM3HwVoBXK6HcqeKrSrL/JqcC/rDcf95l4r7LXLyxDXc8uQDa064GubtCABg==
+  dependencies:
+    "@babel/helper-define-polyfill-provider" "^0.6.2"
+
 bail@^2.0.0:
   version "2.0.2"
   resolved "https://registry.yarnpkg.com/bail/-/bail-2.0.2.tgz#d26f5cd8fe5d6f832a31517b9f7c356040ba6d5d"
@@ -2897,7 +3736,7 @@ braces@^3.0.2, braces@~3.0.2:
   dependencies:
     fill-range "^7.0.1"
 
-browserslist@^4.0.0, browserslist@^4.14.5, browserslist@^4.18.1, browserslist@^4.21.10, browserslist@^4.21.4, browserslist@^4.21.9, browserslist@^4.22.1:
+browserslist@^4.0.0, browserslist@^4.14.5, browserslist@^4.18.1, browserslist@^4.21.10, browserslist@^4.21.9, browserslist@^4.22.1:
   version "4.22.1"
   resolved "https://registry.yarnpkg.com/browserslist/-/browserslist-4.22.1.tgz#ba91958d1a59b87dab6fed8dfbcb3da5e2e9c619"
   integrity sha512-FEVc202+2iuClEhZhrWy6ZiAcRLvNMyYcxZ8raemul1DYVOVdFsbqckWLdsixQZCpJlwe77Z3UTalE7jsjnKfQ==
@@ -2917,6 +3756,16 @@ browserslist@^4.22.2:
     node-releases "^2.0.14"
     update-browserslist-db "^1.0.13"
 
+browserslist@^4.23.0, browserslist@^4.23.1, browserslist@^4.23.3:
+  version "4.23.3"
+  resolved "https://registry.yarnpkg.com/browserslist/-/browserslist-4.23.3.tgz#debb029d3c93ebc97ffbc8d9cbb03403e227c800"
+  integrity sha512-btwCFJVjI4YWDNfau8RhZ+B1Q/VLoUITrm3RlP6y1tYGWIOa+InuYiRGXUBXo8nA1qKmHMyLB/iVQg5TT4eFoA==
+  dependencies:
+    caniuse-lite "^1.0.30001646"
+    electron-to-chromium "^1.5.4"
+    node-releases "^2.0.18"
+    update-browserslist-db "^1.1.0"
+
 buffer-from@^1.0.0:
   version "1.1.2"
   resolved "https://registry.yarnpkg.com/buffer-from/-/buffer-from-1.1.2.tgz#2b146a6fd72e80b4f55d255f35ed59a3a9a41bd5"
@@ -2992,15 +3841,15 @@ caniuse-api@^3.0.0:
     lodash.memoize "^4.1.2"
     lodash.uniq "^4.5.0"
 
-caniuse-lite@^1.0.0, caniuse-lite@^1.0.30001538, caniuse-lite@^1.0.30001541:
-  version "1.0.30001559"
-  resolved "https://registry.yarnpkg.com/caniuse-lite/-/caniuse-lite-1.0.30001559.tgz#95a982440d3d314c471db68d02664fb7536c5a30"
-  integrity sha512-cPiMKZgqgkg5LY3/ntGeLFUpi6tzddBNS58A4tnTgQw1zON7u2sZMU7SzOeVH4tj20++9ggL+V6FDOFMTaFFYA==
+caniuse-lite@^1.0.0, caniuse-lite@^1.0.30001538, caniuse-lite@^1.0.30001541, caniuse-lite@^1.0.30001565:
+  version "1.0.30001651"
+  resolved "https://registry.npmjs.org/caniuse-lite/-/caniuse-lite-1.0.30001651.tgz"
+  integrity sha512-9Cf+Xv1jJNe1xPZLGuUXLNkE1BoDkqRqYyFJ9TDYSqhduqA4hu4oR9HluGoWYQC/aj8WHjsGVV+bwkh0+tegRg==
 
-caniuse-lite@^1.0.30001565:
-  version "1.0.30001570"
-  resolved "https://registry.yarnpkg.com/caniuse-lite/-/caniuse-lite-1.0.30001570.tgz#b4e5c1fa786f733ab78fc70f592df6b3f23244ca"
-  integrity sha512-+3e0ASu4sw1SWaoCtvPeyXp+5PsjigkSt8OXZbF9StH5pQWbxEjLAZE3n8Aup5udop1uRiKA7a4utUk/uoSpUw==
+caniuse-lite@^1.0.30001646:
+  version "1.0.30001653"
+  resolved "https://registry.yarnpkg.com/caniuse-lite/-/caniuse-lite-1.0.30001653.tgz#b8af452f8f33b1c77f122780a4aecebea0caca56"
+  integrity sha512-XGWQVB8wFQ2+9NZwZ10GxTYC5hk0Fa+q8cSkr0tgvMhYhMHP/QC+WTgrePMDBWiWc/pV+1ik82Al20XOK25Gcw==
 
 ccount@^2.0.0:
   version "2.0.1"
@@ -3066,7 +3915,7 @@ cheerio-select@^2.1.0:
     domhandler "^5.0.3"
     domutils "^3.0.1"
 
-cheerio@^1.0.0-rc.12:
+cheerio@1.0.0-rc.12:
   version "1.0.0-rc.12"
   resolved "https://registry.yarnpkg.com/cheerio/-/cheerio-1.0.0-rc.12.tgz#788bf7466506b1c6bf5fae51d24a2c4d62e47683"
   integrity sha512-VqR8m68vM46BNnuZ5NtnGBKIE/DfN0cRIzg9n40EIq9NOv90ayxLBXA8fXC5gquFRGJSTRqBq25Jt2ECLR431Q==
@@ -3178,7 +4027,7 @@ color-name@~1.1.4:
   resolved "https://registry.yarnpkg.com/color-name/-/color-name-1.1.4.tgz#c2a09a87acbde69543de6f63fa3995c826c536a2"
   integrity sha512-dOy+3AuW3a2wNbZHIuMZpTcgjGuLU/uBL/ubcZF9OXbDo8ff4O8yVp5Bf0efS8uEoYo5q4Fx7dY9OgQGXgAsQA==
 
-colord@^2.9.1:
+colord@^2.9.3:
   version "2.9.3"
   resolved "https://registry.yarnpkg.com/colord/-/colord-2.9.3.tgz#4f8ce919de456f1d5c1c368c307fe20f3e59fb43"
   integrity sha512-jeC1axXpnb0/2nn/Y1LPuLdgXBLH7aDcHu4KEKfqw3CUhX7ZpfBSlPKyqXE6btIgEzfWtrX3/tyBCaCvXvMkOw==
@@ -3338,6 +4187,13 @@ core-js-compat@^3.31.0, core-js-compat@^3.33.1:
   dependencies:
     browserslist "^4.22.1"
 
+core-js-compat@^3.37.1, core-js-compat@^3.38.0:
+  version "3.38.1"
+  resolved "https://registry.yarnpkg.com/core-js-compat/-/core-js-compat-3.38.1.tgz#2bc7a298746ca5a7bcb9c164bcb120f2ebc09a09"
+  integrity sha512-JRH6gfXxGmrzF3tZ57lFx97YARxCXPaMzPo6jELZhv88pBH5VXpQ+y0znKGlFnzuaihqhLbefxSJxWJMPtfDzw==
+  dependencies:
+    browserslist "^4.23.3"
+
 core-js-pure@^3.30.2:
   version "3.33.2"
   resolved "https://registry.yarnpkg.com/core-js-pure/-/core-js-pure-3.33.2.tgz#644830db2507ef84d068a70980ccd99c275f5fa6"
@@ -3364,18 +4220,7 @@ cosmiconfig@^6.0.0:
     path-type "^4.0.0"
     yaml "^1.7.2"
 
-cosmiconfig@^7.0.1:
-  version "7.1.0"
-  resolved "https://registry.yarnpkg.com/cosmiconfig/-/cosmiconfig-7.1.0.tgz#1443b9afa596b670082ea46cbd8f6a62b84635f6"
-  integrity sha512-AdmX6xUzdNASswsFtmwSt7Vj8po9IuqXm0UXz7QKPuEUmPB4XyjGfaAr2PSuELMwkRMVH1EpIkX5bTZGRB3eCA==
-  dependencies:
-    "@types/parse-json" "^4.0.0"
-    import-fresh "^3.2.1"
-    parse-json "^5.0.0"
-    path-type "^4.0.0"
-    yaml "^1.10.0"
-
-cosmiconfig@^8.2.0:
+cosmiconfig@^8.1.3, cosmiconfig@^8.2.0:
   version "8.3.6"
   resolved "https://registry.yarnpkg.com/cosmiconfig/-/cosmiconfig-8.3.6.tgz#060a2b871d66dba6c8538ea1118ba1ac16f5fae3"
   integrity sha512-kcZ6+W5QzcJ3P1Mt+83OUv/oHFqZHIx8DuxG6eZ5RGMERoLqp4BuGjhHLYGK+Kf5XVkQvqBSmAy/nGWN3qDgEA==
@@ -3401,10 +4246,10 @@ crypto-random-string@^4.0.0:
   dependencies:
     type-fest "^1.0.1"
 
-css-declaration-sorter@^6.3.1:
-  version "6.4.1"
-  resolved "https://registry.yarnpkg.com/css-declaration-sorter/-/css-declaration-sorter-6.4.1.tgz#28beac7c20bad7f1775be3a7129d7eae409a3a71"
-  integrity sha512-rtdthzxKuyq6IzqX6jEcIzQF/YqccluefyCYheovBOLhFT/drQA9zj/UbRAa9J7C0o6EG6u3E6g+vKkay7/k3g==
+css-declaration-sorter@^7.2.0:
+  version "7.2.0"
+  resolved "https://registry.yarnpkg.com/css-declaration-sorter/-/css-declaration-sorter-7.2.0.tgz#6dec1c9523bc4a643e088aab8f09e67a54961024"
+  integrity sha512-h70rUM+3PNFuaBDTLe8wF/cdWu+dOZmb7pJt8Z2sedYbAcQVQV/tEchueg3GWxwqS0cxtbxmaHEdkNACqcvsow==
 
 css-loader@^6.8.1:
   version "6.8.1"
@@ -3420,17 +4265,17 @@ css-loader@^6.8.1:
     postcss-value-parser "^4.2.0"
     semver "^7.3.8"
 
-css-minimizer-webpack-plugin@^4.2.2:
-  version "4.2.2"
-  resolved "https://registry.yarnpkg.com/css-minimizer-webpack-plugin/-/css-minimizer-webpack-plugin-4.2.2.tgz#79f6199eb5adf1ff7ba57f105e3752d15211eb35"
-  integrity sha512-s3Of/4jKfw1Hj9CxEO1E5oXhQAxlayuHO2y/ML+C6I9sQ7FdzfEV6QgMLN3vI+qFsjJGIAFLKtQK7t8BOXAIyA==
-  dependencies:
-    cssnano "^5.1.8"
-    jest-worker "^29.1.2"
-    postcss "^8.4.17"
-    schema-utils "^4.0.0"
-    serialize-javascript "^6.0.0"
-    source-map "^0.6.1"
+css-minimizer-webpack-plugin@^5.0.1:
+  version "5.0.1"
+  resolved "https://registry.yarnpkg.com/css-minimizer-webpack-plugin/-/css-minimizer-webpack-plugin-5.0.1.tgz#33effe662edb1a0bf08ad633c32fa75d0f7ec565"
+  integrity sha512-3caImjKFQkS+ws1TGcFn0V1HyDJFq1Euy589JlD6/3rV2kj+w7r5G9WDMgSHvpvXHNZ2calVypZWuEDQd9wfLg==
+  dependencies:
+    "@jridgewell/trace-mapping" "^0.3.18"
+    cssnano "^6.0.1"
+    jest-worker "^29.4.3"
+    postcss "^8.4.24"
+    schema-utils "^4.0.1"
+    serialize-javascript "^6.0.1"
 
 css-select@^4.1.3:
   version "4.3.0"
@@ -3454,13 +4299,21 @@ css-select@^5.1.0:
     domutils "^3.0.1"
     nth-check "^2.0.1"
 
-css-tree@^1.1.2, css-tree@^1.1.3:
-  version "1.1.3"
-  resolved "https://registry.yarnpkg.com/css-tree/-/css-tree-1.1.3.tgz#eb4870fb6fd7707327ec95c2ff2ab09b5e8db91d"
-  integrity sha512-tRpdppF7TRazZrjJ6v3stzv93qxRcSsFmW6cX0Zm2NVKpxE1WV1HblnghVv9TreireHkqI/VDEsfolRF1p6y7Q==
+css-tree@^2.3.1:
+  version "2.3.1"
+  resolved "https://registry.yarnpkg.com/css-tree/-/css-tree-2.3.1.tgz#10264ce1e5442e8572fc82fbe490644ff54b5c20"
+  integrity sha512-6Fv1DV/TYw//QF5IzQdqsNDjx/wc8TrMBZsqjL9eW01tWb7R7k/mq+/VXfJCl7SoD5emsJop9cOByJZfs8hYIw==
   dependencies:
-    mdn-data "2.0.14"
-    source-map "^0.6.1"
+    mdn-data "2.0.30"
+    source-map-js "^1.0.1"
+
+css-tree@~2.2.0:
+  version "2.2.1"
+  resolved "https://registry.yarnpkg.com/css-tree/-/css-tree-2.2.1.tgz#36115d382d60afd271e377f9c5f67d02bd48c032"
+  integrity sha512-OA0mILzGc1kCOCSJerOeqDxDQ4HOh+G8NbOJFOTgOCzpw7fCBubk0fEyxp8AgOL/jvLgYA/uV0cMbe43ElF1JA==
+  dependencies:
+    mdn-data "2.0.28"
+    source-map-js "^1.0.1"
 
 css-what@^6.0.1, css-what@^6.1.0:
   version "6.1.0"
@@ -3472,73 +4325,74 @@ cssesc@^3.0.0:
   resolved "https://registry.yarnpkg.com/cssesc/-/cssesc-3.0.0.tgz#37741919903b868565e1c09ea747445cd18983ee"
   integrity sha512-/Tb/JcjK111nNScGob5MNtsntNM1aCNUDipB/TkwZFhyDrrE47SOx/18wF2bbjgc3ZzCSKW1T5nt5EbFoAz/Vg==
 
-cssnano-preset-advanced@^5.3.10:
-  version "5.3.10"
-  resolved "https://registry.yarnpkg.com/cssnano-preset-advanced/-/cssnano-preset-advanced-5.3.10.tgz#25558a1fbf3a871fb6429ce71e41be7f5aca6eef"
-  integrity sha512-fnYJyCS9jgMU+cmHO1rPSPf9axbQyD7iUhLO5Df6O4G+fKIOMps+ZbU0PdGFejFBBZ3Pftf18fn1eG7MAPUSWQ==
-  dependencies:
-    autoprefixer "^10.4.12"
-    cssnano-preset-default "^5.2.14"
-    postcss-discard-unused "^5.1.0"
-    postcss-merge-idents "^5.1.1"
-    postcss-reduce-idents "^5.2.0"
-    postcss-zindex "^5.1.0"
-
-cssnano-preset-default@^5.2.14:
-  version "5.2.14"
-  resolved "https://registry.yarnpkg.com/cssnano-preset-default/-/cssnano-preset-default-5.2.14.tgz#309def4f7b7e16d71ab2438052093330d9ab45d8"
-  integrity sha512-t0SFesj/ZV2OTylqQVOrFgEh5uanxbO6ZAdeCrNsUQ6fVuXwYTxJPNAGvGTxHbD68ldIJNec7PyYZDBrfDQ+6A==
-  dependencies:
-    css-declaration-sorter "^6.3.1"
-    cssnano-utils "^3.1.0"
-    postcss-calc "^8.2.3"
-    postcss-colormin "^5.3.1"
-    postcss-convert-values "^5.1.3"
-    postcss-discard-comments "^5.1.2"
-    postcss-discard-duplicates "^5.1.0"
-    postcss-discard-empty "^5.1.1"
-    postcss-discard-overridden "^5.1.0"
-    postcss-merge-longhand "^5.1.7"
-    postcss-merge-rules "^5.1.4"
-    postcss-minify-font-values "^5.1.0"
-    postcss-minify-gradients "^5.1.1"
-    postcss-minify-params "^5.1.4"
-    postcss-minify-selectors "^5.2.1"
-    postcss-normalize-charset "^5.1.0"
-    postcss-normalize-display-values "^5.1.0"
-    postcss-normalize-positions "^5.1.1"
-    postcss-normalize-repeat-style "^5.1.1"
-    postcss-normalize-string "^5.1.0"
-    postcss-normalize-timing-functions "^5.1.0"
-    postcss-normalize-unicode "^5.1.1"
-    postcss-normalize-url "^5.1.0"
-    postcss-normalize-whitespace "^5.1.1"
-    postcss-ordered-values "^5.1.3"
-    postcss-reduce-initial "^5.1.2"
-    postcss-reduce-transforms "^5.1.0"
-    postcss-svgo "^5.1.0"
-    postcss-unique-selectors "^5.1.1"
-
-cssnano-utils@^3.1.0:
-  version "3.1.0"
-  resolved "https://registry.yarnpkg.com/cssnano-utils/-/cssnano-utils-3.1.0.tgz#95684d08c91511edfc70d2636338ca37ef3a6861"
-  integrity sha512-JQNR19/YZhz4psLX/rQ9M83e3z2Wf/HdJbryzte4a3NSuafyp9w/I4U+hx5C2S9g41qlstH7DEWnZaaj83OuEA==
+cssnano-preset-advanced@^6.1.2:
+  version "6.1.2"
+  resolved "https://registry.yarnpkg.com/cssnano-preset-advanced/-/cssnano-preset-advanced-6.1.2.tgz#82b090872b8f98c471f681d541c735acf8b94d3f"
+  integrity sha512-Nhao7eD8ph2DoHolEzQs5CfRpiEP0xa1HBdnFZ82kvqdmbwVBUr2r1QuQ4t1pi+D1ZpqpcO4T+wy/7RxzJ/WPQ==
+  dependencies:
+    autoprefixer "^10.4.19"
+    browserslist "^4.23.0"
+    cssnano-preset-default "^6.1.2"
+    postcss-discard-unused "^6.0.5"
+    postcss-merge-idents "^6.0.3"
+    postcss-reduce-idents "^6.0.3"
+    postcss-zindex "^6.0.2"
+
+cssnano-preset-default@^6.1.2:
+  version "6.1.2"
+  resolved "https://registry.yarnpkg.com/cssnano-preset-default/-/cssnano-preset-default-6.1.2.tgz#adf4b89b975aa775f2750c89dbaf199bbd9da35e"
+  integrity sha512-1C0C+eNaeN8OcHQa193aRgYexyJtU8XwbdieEjClw+J9d94E41LwT6ivKH0WT+fYwYWB0Zp3I3IZ7tI/BbUbrg==
+  dependencies:
+    browserslist "^4.23.0"
+    css-declaration-sorter "^7.2.0"
+    cssnano-utils "^4.0.2"
+    postcss-calc "^9.0.1"
+    postcss-colormin "^6.1.0"
+    postcss-convert-values "^6.1.0"
+    postcss-discard-comments "^6.0.2"
+    postcss-discard-duplicates "^6.0.3"
+    postcss-discard-empty "^6.0.3"
+    postcss-discard-overridden "^6.0.2"
+    postcss-merge-longhand "^6.0.5"
+    postcss-merge-rules "^6.1.1"
+    postcss-minify-font-values "^6.1.0"
+    postcss-minify-gradients "^6.0.3"
+    postcss-minify-params "^6.1.0"
+    postcss-minify-selectors "^6.0.4"
+    postcss-normalize-charset "^6.0.2"
+    postcss-normalize-display-values "^6.0.2"
+    postcss-normalize-positions "^6.0.2"
+    postcss-normalize-repeat-style "^6.0.2"
+    postcss-normalize-string "^6.0.2"
+    postcss-normalize-timing-functions "^6.0.2"
+    postcss-normalize-unicode "^6.1.0"
+    postcss-normalize-url "^6.0.2"
+    postcss-normalize-whitespace "^6.0.2"
+    postcss-ordered-values "^6.0.2"
+    postcss-reduce-initial "^6.1.0"
+    postcss-reduce-transforms "^6.0.2"
+    postcss-svgo "^6.0.3"
+    postcss-unique-selectors "^6.0.4"
+
+cssnano-utils@^4.0.2:
+  version "4.0.2"
+  resolved "https://registry.yarnpkg.com/cssnano-utils/-/cssnano-utils-4.0.2.tgz#56f61c126cd0f11f2eef1596239d730d9fceff3c"
+  integrity sha512-ZR1jHg+wZ8o4c3zqf1SIUSTIvm/9mU343FMR6Obe/unskbvpGhZOo1J6d/r8D1pzkRQYuwbcH3hToOuoA2G7oQ==
 
-cssnano@^5.1.15, cssnano@^5.1.8:
-  version "5.1.15"
-  resolved "https://registry.yarnpkg.com/cssnano/-/cssnano-5.1.15.tgz#ded66b5480d5127fcb44dac12ea5a983755136bf"
-  integrity sha512-j+BKgDcLDQA+eDifLx0EO4XSA56b7uut3BQFH+wbSaSTuGLuiyTa/wbRYthUXX8LC9mLg+WWKe8h+qJuwTAbHw==
+cssnano@^6.0.1, cssnano@^6.1.2:
+  version "6.1.2"
+  resolved "https://registry.yarnpkg.com/cssnano/-/cssnano-6.1.2.tgz#4bd19e505bd37ee7cf0dc902d3d869f6d79c66b8"
+  integrity sha512-rYk5UeX7VAM/u0lNqewCdasdtPK81CgX8wJFLEIXHbV2oldWRgJAsZrdhRXkV1NJzA2g850KiFm9mMU2HxNxMA==
   dependencies:
-    cssnano-preset-default "^5.2.14"
-    lilconfig "^2.0.3"
-    yaml "^1.10.2"
+    cssnano-preset-default "^6.1.2"
+    lilconfig "^3.1.1"
 
-csso@^4.2.0:
-  version "4.2.0"
-  resolved "https://registry.yarnpkg.com/csso/-/csso-4.2.0.tgz#ea3a561346e8dc9f546d6febedd50187cf389529"
-  integrity sha512-wvlcdIbf6pwKEk7vHj8/Bkc0B4ylXZruLvOgs9doS5eOsOpuodOV2zJChSpkp+pRpYQLQMeF04nr3Z68Sta9jA==
+csso@^5.0.5:
+  version "5.0.5"
+  resolved "https://registry.yarnpkg.com/csso/-/csso-5.0.5.tgz#f9b7fe6cc6ac0b7d90781bb16d5e9874303e2ca6"
+  integrity sha512-0LrrStPOdJj+SPCCrGhzryycLjwcgUSHBtxNA8aIDxf0GLsRh1cKYhB00Gd1lDOS4yGH69+SNn13+TWbVHETFQ==
   dependencies:
-    css-tree "^1.1.2"
+    css-tree "~2.2.0"
 
 csstype@^3.0.2:
   version "3.1.2"
@@ -3578,7 +4432,7 @@ deep-extend@^0.6.0:
   resolved "https://registry.yarnpkg.com/deep-extend/-/deep-extend-0.6.0.tgz#c4fa7c95404a17a9c3e8ca7e1537312b736330ac"
   integrity sha512-LOHxIOaPYdHlJRtCQfDIVZtfw/ufM8+rVj649RIHzcm/vGwQRXFt6OPqIFWsm2XEMrNIEtWR64sY1LEKD2vAOA==
 
-deepmerge@^4.2.2:
+deepmerge@^4.2.2, deepmerge@^4.3.1:
   version "4.3.1"
   resolved "https://registry.yarnpkg.com/deepmerge/-/deepmerge-4.3.1.tgz#44b5f2147cd3b00d4b56137685966f26fd25dd4a"
   integrity sha512-3sUqbMEc77XqpdNO7FRyRog+eW3ph+GYCbj+rK+uYyRMuwsVy0rMiVtPn+QJlKFvWP/1PYpapqYn0Me2knFn+A==
@@ -3801,6 +4655,11 @@ electron-to-chromium@^1.4.601:
   resolved "https://registry.yarnpkg.com/electron-to-chromium/-/electron-to-chromium-1.4.615.tgz#b1c41839962d2e4e63dca05519da9040e34848c2"
   integrity sha512-/bKPPcgZVUziECqDc+0HkT87+0zhaWSZHNXqF8FLd2lQcptpmUFwoCSWjCdOng9Gdq+afKArPdEg/0ZW461Eng==
 
+electron-to-chromium@^1.5.4:
+  version "1.5.13"
+  resolved "https://registry.yarnpkg.com/electron-to-chromium/-/electron-to-chromium-1.5.13.tgz#1abf0410c5344b2b829b7247e031f02810d442e6"
+  integrity sha512-lbBcvtIJ4J6sS4tb5TLp1b4LyfCdMkwStzXPyAgVgTRAsep4bvrAGaBOP7ZJtQMNJpSQ9SqG4brWOroNaQtm7Q==
+
 emoji-regex@^8.0.0:
   version "8.0.0"
   resolved "https://registry.yarnpkg.com/emoji-regex/-/emoji-regex-8.0.0.tgz#e818fd69ce5ccfcb404594f842963bf53164cc37"
@@ -3866,6 +4725,11 @@ escalade@^3.1.1:
   resolved "https://registry.yarnpkg.com/escalade/-/escalade-3.1.1.tgz#d8cfdc7000965c5a0174b4a82eaa5c0552742e40"
   integrity sha512-k0er2gUkLf8O0zKJiAhmkTnJlTvINGv7ygDNPbeIsX/TJjGJZHuh9B2UxbsaEkmlEo9MfhrSzmhIlhRlI2GXnw==
 
+escalade@^3.1.2:
+  version "3.1.2"
+  resolved "https://registry.yarnpkg.com/escalade/-/escalade-3.1.2.tgz#54076e9ab29ea5bf3d8f1ed62acffbb88272df27"
+  integrity sha512-ErCHMCae19vR8vQGe50xIsVomy19rg6gFu3+r3jkEO46suLMWBksvVyoGgQV+jOfl84ZSOSlmv6Gxa89PmTGmA==
+
 escape-goat@^4.0.0:
   version "4.0.0"
   resolved "https://registry.yarnpkg.com/escape-goat/-/escape-goat-4.0.0.tgz#9424820331b510b0666b98f7873fe11ac4aa8081"
@@ -4236,7 +5100,7 @@ forwarded@0.2.0:
   resolved "https://registry.yarnpkg.com/forwarded/-/forwarded-0.2.0.tgz#2269936428aad4c15c7ebe9779a84bf0b2a81811"
   integrity sha512-buRG0fpBtRHSTCOASe6hD258tEubFoRLb4ZNA6NxMVHNw2gOcwHo9wyablzMzOA5z9xA9L1KNjk/Nt6MT9aYow==
 
-fraction.js@^4.3.6:
+fraction.js@^4.3.6, fraction.js@^4.3.7:
   version "4.3.7"
   resolved "https://registry.yarnpkg.com/fraction.js/-/fraction.js-4.3.7.tgz#06ca0085157e42fda7f9e726e79fefc4068840f7"
   integrity sha512-ZsDfxO51wGAXREY55a7la9LScWpwv9RxIrYABrlvOFBlH/ShPnrtsXeuUIfXKKOVicNxQ+o8JTbJvjS4M89yew==
@@ -4255,6 +5119,15 @@ fs-extra@^11.1.1:
     jsonfile "^6.0.1"
     universalify "^2.0.0"
 
+fs-extra@^11.2.0:
+  version "11.2.0"
+  resolved "https://registry.yarnpkg.com/fs-extra/-/fs-extra-11.2.0.tgz#e70e17dfad64232287d01929399e0ea7c86b0e5b"
+  integrity sha512-PmDi3uwK5nFuXh7XDTlVnS17xJS7vW36is2+w3xcv8SVxiB4NyATf4ctkVY5bkSjX0Y4nbvZCq1/EjtEyr9ktw==
+  dependencies:
+    graceful-fs "^4.2.0"
+    jsonfile "^6.0.1"
+    universalify "^2.0.0"
+
 fs-extra@^9.0.0:
   version "9.1.0"
   resolved "https://registry.yarnpkg.com/fs-extra/-/fs-extra-9.1.0.tgz#5954460c764a8da2094ba3554bf839e6b9a7c86d"
@@ -4804,7 +5677,7 @@ immer@^9.0.7:
   resolved "https://registry.yarnpkg.com/immer/-/immer-9.0.21.tgz#1e025ea31a40f24fb064f1fef23e931496330176"
   integrity sha512-bc4NBHqOqSfRW7POMkHd51LvClaeMXpm8dx0e8oE2GORbq5aRK7Bxl4FyzVLdGtLmvLKL7BTDBG5ACQm4HWjTA==
 
-import-fresh@^3.1.0, import-fresh@^3.2.1, import-fresh@^3.3.0:
+import-fresh@^3.1.0, import-fresh@^3.3.0:
   version "3.3.0"
   resolved "https://registry.yarnpkg.com/import-fresh/-/import-fresh-3.3.0.tgz#37162c25fcb9ebaa2e6e53d5b4d88ce17d9e0c2b"
   integrity sha512-veYYhQa+D1QBKznvhUHxb8faxlrwUnxseDAbAp457E0wLNio2bOSKnjYDhMj+YiAq61xrMGhQk9iXVk5FzgQMw==
@@ -4827,10 +5700,10 @@ indent-string@^4.0.0:
   resolved "https://registry.yarnpkg.com/indent-string/-/indent-string-4.0.0.tgz#624f8f4497d619b2d9768531d58f4122854d7251"
   integrity sha512-EdDDZu4A2OyIK7Lr/2zG+w5jmbuk1DVBnEwREQvBzspBJkCEbRa8GxU1lghYcaGJCnRWibjDXlq779X1/y5xwg==
 
-infima@0.2.0-alpha.43:
-  version "0.2.0-alpha.43"
-  resolved "https://registry.yarnpkg.com/infima/-/infima-0.2.0-alpha.43.tgz#f7aa1d7b30b6c08afef441c726bac6150228cbe0"
-  integrity sha512-2uw57LvUqW0rK/SWYnd/2rRfxNA5DDNOh33jxF7fy46VWoNhGxiUQyVZHbBMjQ33mQem0cjdDVwgWVAmlRfgyQ==
+infima@0.2.0-alpha.44:
+  version "0.2.0-alpha.44"
+  resolved "https://registry.yarnpkg.com/infima/-/infima-0.2.0-alpha.44.tgz#9cd9446e473b44d49763f48efabe31f32440861d"
+  integrity sha512-tuRkUSO/lB3rEhLJk25atwAjgLuzq070+pOW8XcvpHky/YbENnRRdPd85IBkyeTgttmOy5ah+yHYsK1HhUd4lQ==
 
 inflight@^1.0.4:
   version "1.0.6"
@@ -5103,7 +5976,7 @@ jest-worker@^27.4.5:
     merge-stream "^2.0.0"
     supports-color "^8.0.0"
 
-jest-worker@^29.1.2:
+jest-worker@^29.4.3:
   version "29.7.0"
   resolved "https://registry.yarnpkg.com/jest-worker/-/jest-worker-29.7.0.tgz#acad073acbbaeb7262bd5389e1bcf43e10058d4a"
   integrity sha512-eIz2msL/EzL9UFTFFx7jBTkeZfku0yUAyZZZmJ93H2TYEiroIx2PQjEXcwYtYl8zXCxb+PAmA2hLIt/6ZEkPHw==
@@ -5230,10 +6103,10 @@ leven@^3.1.0:
   resolved "https://registry.yarnpkg.com/leven/-/leven-3.1.0.tgz#77891de834064cccba82ae7842bb6b14a13ed7f2"
   integrity sha512-qsda+H8jTaUaN/x5vzW2rzc+8Rw4TAQ/4KjB46IwK5VH+IlVeeeje/EoZRpiXvIqjFgK84QffqPztGI3VBLG1A==
 
-lilconfig@^2.0.3:
-  version "2.1.0"
-  resolved "https://registry.yarnpkg.com/lilconfig/-/lilconfig-2.1.0.tgz#78e23ac89ebb7e1bfbf25b18043de756548e7f52"
-  integrity sha512-utWOt/GHzuUxnLKxB6dk81RoOeoNeHgbrXiuGk4yyF5qlRz+iIVWu56E2fqGHFrXz0QNUhLB/8nKqvRH66JKGQ==
+lilconfig@^3.1.1:
+  version "3.1.2"
+  resolved "https://registry.yarnpkg.com/lilconfig/-/lilconfig-3.1.2.tgz#e4a7c3cb549e3a606c8dcc32e5ae1005e62c05cb"
+  integrity sha512-eop+wDAvpItUys0FWkHIKeC9ybYrTGbU41U5K7+bttZZeohvnY7M9dZ5kB21GNWiFT2q1OoPTvncPCgSOVO5ow==
 
 lines-and-columns@^1.1.6:
   version "1.2.4"
@@ -5590,10 +6463,15 @@ mdast-util-to-string@^4.0.0:
   dependencies:
     "@types/mdast" "^4.0.0"
 
-mdn-data@2.0.14:
-  version "2.0.14"
-  resolved "https://registry.yarnpkg.com/mdn-data/-/mdn-data-2.0.14.tgz#7113fc4281917d63ce29b43446f701e68c25ba50"
-  integrity sha512-dn6wd0uw5GsdswPFfsgMp5NSB0/aDe6fK94YJV/AJDYXL6HVLWBsxeq7js7Ad+mU2K9LAlwpk6kN2D5mwCPVow==
+mdn-data@2.0.28:
+  version "2.0.28"
+  resolved "https://registry.yarnpkg.com/mdn-data/-/mdn-data-2.0.28.tgz#5ec48e7bef120654539069e1ae4ddc81ca490eba"
+  integrity sha512-aylIc7Z9y4yzHYAJNuESG3hfhC+0Ibp/MAMiaOZgNv4pmEdFyfZhhhny4MNiAfWdBQ1RQ2mfDWmM1x8SvGyp8g==
+
+mdn-data@2.0.30:
+  version "2.0.30"
+  resolved "https://registry.yarnpkg.com/mdn-data/-/mdn-data-2.0.30.tgz#ce4df6f80af6cfbe218ecd5c552ba13c4dfa08cc"
+  integrity sha512-GaqWWShW4kv/G9IEucWScBx9G1/vsFZZJUO+tD26M8J8z3Kw5RDQjaoZe03YAClgeS/SWPOcb4nkFBTEi5DUEA==
 
 media-typer@0.3.0:
   version "0.3.0"
@@ -6152,6 +7030,11 @@ nanoid@^3.3.6:
   resolved "https://registry.yarnpkg.com/nanoid/-/nanoid-3.3.6.tgz#443380c856d6e9f9824267d960b4236ad583ea4c"
   integrity sha512-BGcqMMJuToF7i1rt+2PWSNVnWIkGCU78jBG3RxO/bZlnZPK2Cmi2QaffxGO/2RvWi9sL+FAiRiXMgsyxQ1DIDA==
 
+nanoid@^3.3.7:
+  version "3.3.7"
+  resolved "https://registry.yarnpkg.com/nanoid/-/nanoid-3.3.7.tgz#d0c301a691bc8d54efa0a2226ccf3fe2fd656bd8"
+  integrity sha512-eSRppjcPIatRIMC1U6UngP8XFcz8MQWGQdt1MTBQ7NaAmvXDfvNxbvWV3x2y6CdEUciCSsDHDQZbhYaB8QEo2g==
+
 negotiator@0.6.3:
   version "0.6.3"
   resolved "https://registry.yarnpkg.com/negotiator/-/negotiator-0.6.3.tgz#58e323a72fedc0d6f9cd4d31fe49f51479590ccd"
@@ -6195,6 +7078,11 @@ node-releases@^2.0.14:
   resolved "https://registry.yarnpkg.com/node-releases/-/node-releases-2.0.14.tgz#2ffb053bceb8b2be8495ece1ab6ce600c4461b0b"
   integrity sha512-y10wOWt8yZpqXmOgRo77WaHEmhYQYGNA6y421PKsKYWEK8aW+cqAphborZDhqfyKrbZEN92CN1X2KbafY2s7Yw==
 
+node-releases@^2.0.18:
+  version "2.0.18"
+  resolved "https://registry.yarnpkg.com/node-releases/-/node-releases-2.0.18.tgz#f010e8d35e2fe8d6b2944f03f70213ecedc4ca3f"
+  integrity sha512-d9VeXT4SJ7ZeOqGX6R5EM022wpL+eWPooLI+5UpWn2jCT1aosUQEhQP214x33Wkwx3JQMvIm+tIoVOdodFS40g==
+
 normalize-path@^3.0.0, normalize-path@~3.0.0:
   version "3.0.0"
   resolved "https://registry.yarnpkg.com/normalize-path/-/normalize-path-3.0.0.tgz#0dcd69ff23a1c9b11fd0978316644a0388216a65"
@@ -6205,11 +7093,6 @@ normalize-range@^0.1.2:
   resolved "https://registry.yarnpkg.com/normalize-range/-/normalize-range-0.1.2.tgz#2d10c06bdfd312ea9777695a4d28439456b75942"
   integrity sha512-bdok/XvKII3nUpklnV6P2hxtMNrCboOjAcyBuQnWEhO665FwrSNRxU+AqpsyvO6LgGYPspN+lu5CLtw4jPRKNA==
 
-normalize-url@^6.0.1:
-  version "6.1.0"
-  resolved "https://registry.yarnpkg.com/normalize-url/-/normalize-url-6.1.0.tgz#40d0885b535deffe3f3147bec877d05fe4c5668a"
-  integrity sha512-DlL+XwOy3NxAQ8xuC0okPgK46iuVNAK01YN7RueYBqqFeGsBjV9XmCAzAdgt+667bCl5kPh9EqKKDwnaPG1I7A==
-
 normalize-url@^8.0.0:
   version "8.0.0"
   resolved "https://registry.yarnpkg.com/normalize-url/-/normalize-url-8.0.0.tgz#593dbd284f743e8dcf6a5ddf8fadff149c82701a"
@@ -6524,6 +7407,11 @@ picocolors@^1.0.0:
   resolved "https://registry.yarnpkg.com/picocolors/-/picocolors-1.0.0.tgz#cb5bdc74ff3f51892236eaf79d68bc44564ab81c"
   integrity sha512-1fygroTLlHu66zi26VoTDv8yRgm0Fccecssto+MhsZ0D/DGW2sm8E8AjW7NU5VVTRt5GxbeZ5qBuJr+HyLYkjQ==
 
+picocolors@^1.0.1:
+  version "1.0.1"
+  resolved "https://registry.yarnpkg.com/picocolors/-/picocolors-1.0.1.tgz#a8ad579b571952f0e5d25892de5445bcfe25aaa1"
+  integrity sha512-anP1Z8qwhkbmu7MFP5iTt+wQKXgwzf7zTyGlcdzabySa9vd0Xt392U0rVmz9poOaBj0uHJKyyo9/upk0HrEQew==
+
 picomatch@^2.0.4, picomatch@^2.2.1, picomatch@^2.2.3, picomatch@^2.3.1:
   version "2.3.1"
   resolved "https://registry.yarnpkg.com/picomatch/-/picomatch-2.3.1.tgz#3ba3833733646d9d3e4995946c1365a67fb07a42"
@@ -6543,58 +7431,58 @@ pkg-up@^3.1.0:
   dependencies:
     find-up "^3.0.0"
 
-postcss-calc@^8.2.3:
-  version "8.2.4"
-  resolved "https://registry.yarnpkg.com/postcss-calc/-/postcss-calc-8.2.4.tgz#77b9c29bfcbe8a07ff6693dc87050828889739a5"
-  integrity sha512-SmWMSJmB8MRnnULldx0lQIyhSNvuDl9HfrZkaqqE/WHAhToYsAvDq+yAsA/kIyINDszOp3Rh0GFoNuH5Ypsm3Q==
+postcss-calc@^9.0.1:
+  version "9.0.1"
+  resolved "https://registry.yarnpkg.com/postcss-calc/-/postcss-calc-9.0.1.tgz#a744fd592438a93d6de0f1434c572670361eb6c6"
+  integrity sha512-TipgjGyzP5QzEhsOZUaIkeO5mKeMFpebWzRogWG/ysonUlnHcq5aJe0jOjpfzUU8PeSaBQnrE8ehR0QA5vs8PQ==
   dependencies:
-    postcss-selector-parser "^6.0.9"
+    postcss-selector-parser "^6.0.11"
     postcss-value-parser "^4.2.0"
 
-postcss-colormin@^5.3.1:
-  version "5.3.1"
-  resolved "https://registry.yarnpkg.com/postcss-colormin/-/postcss-colormin-5.3.1.tgz#86c27c26ed6ba00d96c79e08f3ffb418d1d1988f"
-  integrity sha512-UsWQG0AqTFQmpBegeLLc1+c3jIqBNB0zlDGRWR+dQ3pRKJL1oeMzyqmH3o2PIfn9MBdNrVPWhDbT769LxCTLJQ==
+postcss-colormin@^6.1.0:
+  version "6.1.0"
+  resolved "https://registry.yarnpkg.com/postcss-colormin/-/postcss-colormin-6.1.0.tgz#076e8d3fb291fbff7b10e6b063be9da42ff6488d"
+  integrity sha512-x9yX7DOxeMAR+BgGVnNSAxmAj98NX/YxEMNFP+SDCEeNLb2r3i6Hh1ksMsnW8Ub5SLCpbescQqn9YEbE9554Sw==
   dependencies:
-    browserslist "^4.21.4"
+    browserslist "^4.23.0"
     caniuse-api "^3.0.0"
-    colord "^2.9.1"
+    colord "^2.9.3"
     postcss-value-parser "^4.2.0"
 
-postcss-convert-values@^5.1.3:
-  version "5.1.3"
-  resolved "https://registry.yarnpkg.com/postcss-convert-values/-/postcss-convert-values-5.1.3.tgz#04998bb9ba6b65aa31035d669a6af342c5f9d393"
-  integrity sha512-82pC1xkJZtcJEfiLw6UXnXVXScgtBrjlO5CBmuDQc+dlb88ZYheFsjTn40+zBVi3DkfF7iezO0nJUPLcJK3pvA==
+postcss-convert-values@^6.1.0:
+  version "6.1.0"
+  resolved "https://registry.yarnpkg.com/postcss-convert-values/-/postcss-convert-values-6.1.0.tgz#3498387f8efedb817cbc63901d45bd1ceaa40f48"
+  integrity sha512-zx8IwP/ts9WvUM6NkVSkiU902QZL1bwPhaVaLynPtCsOTqp+ZKbNi+s6XJg3rfqpKGA/oc7Oxk5t8pOQJcwl/w==
   dependencies:
-    browserslist "^4.21.4"
+    browserslist "^4.23.0"
     postcss-value-parser "^4.2.0"
 
-postcss-discard-comments@^5.1.2:
-  version "5.1.2"
-  resolved "https://registry.yarnpkg.com/postcss-discard-comments/-/postcss-discard-comments-5.1.2.tgz#8df5e81d2925af2780075840c1526f0660e53696"
-  integrity sha512-+L8208OVbHVF2UQf1iDmRcbdjJkuBF6IS29yBDSiWUIzpYaAhtNl6JYnYm12FnkeCwQqF5LeklOu6rAqgfBZqQ==
+postcss-discard-comments@^6.0.2:
+  version "6.0.2"
+  resolved "https://registry.yarnpkg.com/postcss-discard-comments/-/postcss-discard-comments-6.0.2.tgz#e768dcfdc33e0216380623652b0a4f69f4678b6c"
+  integrity sha512-65w/uIqhSBBfQmYnG92FO1mWZjJ4GL5b8atm5Yw2UgrwD7HiNiSSNwJor1eCFGzUgYnN/iIknhNRVqjrrpuglw==
 
-postcss-discard-duplicates@^5.1.0:
-  version "5.1.0"
-  resolved "https://registry.yarnpkg.com/postcss-discard-duplicates/-/postcss-discard-duplicates-5.1.0.tgz#9eb4fe8456706a4eebd6d3b7b777d07bad03e848"
-  integrity sha512-zmX3IoSI2aoenxHV6C7plngHWWhUOV3sP1T8y2ifzxzbtnuhk1EdPwm0S1bIUNaJ2eNbWeGLEwzw8huPD67aQw==
+postcss-discard-duplicates@^6.0.3:
+  version "6.0.3"
+  resolved "https://registry.yarnpkg.com/postcss-discard-duplicates/-/postcss-discard-duplicates-6.0.3.tgz#d121e893c38dc58a67277f75bb58ba43fce4c3eb"
+  integrity sha512-+JA0DCvc5XvFAxwx6f/e68gQu/7Z9ud584VLmcgto28eB8FqSFZwtrLwB5Kcp70eIoWP/HXqz4wpo8rD8gpsTw==
 
-postcss-discard-empty@^5.1.1:
-  version "5.1.1"
-  resolved "https://registry.yarnpkg.com/postcss-discard-empty/-/postcss-discard-empty-5.1.1.tgz#e57762343ff7f503fe53fca553d18d7f0c369c6c"
-  integrity sha512-zPz4WljiSuLWsI0ir4Mcnr4qQQ5e1Ukc3i7UfE2XcrwKK2LIPIqE5jxMRxO6GbI3cv//ztXDsXwEWT3BHOGh3A==
+postcss-discard-empty@^6.0.3:
+  version "6.0.3"
+  resolved "https://registry.yarnpkg.com/postcss-discard-empty/-/postcss-discard-empty-6.0.3.tgz#ee39c327219bb70473a066f772621f81435a79d9"
+  integrity sha512-znyno9cHKQsK6PtxL5D19Fj9uwSzC2mB74cpT66fhgOadEUPyXFkbgwm5tvc3bt3NAy8ltE5MrghxovZRVnOjQ==
 
-postcss-discard-overridden@^5.1.0:
-  version "5.1.0"
-  resolved "https://registry.yarnpkg.com/postcss-discard-overridden/-/postcss-discard-overridden-5.1.0.tgz#7e8c5b53325747e9d90131bb88635282fb4a276e"
-  integrity sha512-21nOL7RqWR1kasIVdKs8HNqQJhFxLsyRfAnUDm4Fe4t4mCWL9OJiHvlHPjcd8zc5Myu89b/7wZDnOSjFgeWRtw==
+postcss-discard-overridden@^6.0.2:
+  version "6.0.2"
+  resolved "https://registry.yarnpkg.com/postcss-discard-overridden/-/postcss-discard-overridden-6.0.2.tgz#4e9f9c62ecd2df46e8fdb44dc17e189776572e2d"
+  integrity sha512-j87xzI4LUggC5zND7KdjsI25APtyMuynXZSujByMaav2roV6OZX+8AaCUcZSWqckZpjAjRyFDdpqybgjFO0HJQ==
 
-postcss-discard-unused@^5.1.0:
-  version "5.1.0"
-  resolved "https://registry.yarnpkg.com/postcss-discard-unused/-/postcss-discard-unused-5.1.0.tgz#8974e9b143d887677304e558c1166d3762501142"
-  integrity sha512-KwLWymI9hbwXmJa0dkrzpRbSJEh0vVUd7r8t0yOGPcfKzyJJxFM8kLyC5Ev9avji6nY95pOp1W6HqIrfT+0VGw==
+postcss-discard-unused@^6.0.5:
+  version "6.0.5"
+  resolved "https://registry.yarnpkg.com/postcss-discard-unused/-/postcss-discard-unused-6.0.5.tgz#c1b0e8c032c6054c3fbd22aaddba5b248136f338"
+  integrity sha512-wHalBlRHkaNnNwfC8z+ppX57VhvS+HWgjW508esjdaEYr3Mx7Gnn2xA4R/CKf5+Z9S5qsqC+Uzh4ueENWwCVUA==
   dependencies:
-    postcss-selector-parser "^6.0.5"
+    postcss-selector-parser "^6.0.16"
 
 postcss-loader@^7.3.3:
   version "7.3.3"
@@ -6605,63 +7493,63 @@ postcss-loader@^7.3.3:
     jiti "^1.18.2"
     semver "^7.3.8"
 
-postcss-merge-idents@^5.1.1:
-  version "5.1.1"
-  resolved "https://registry.yarnpkg.com/postcss-merge-idents/-/postcss-merge-idents-5.1.1.tgz#7753817c2e0b75d0853b56f78a89771e15ca04a1"
-  integrity sha512-pCijL1TREiCoog5nQp7wUe+TUonA2tC2sQ54UGeMmryK3UFGIYKqDyjnqd6RcuI4znFn9hWSLNN8xKE/vWcUQw==
+postcss-merge-idents@^6.0.3:
+  version "6.0.3"
+  resolved "https://registry.yarnpkg.com/postcss-merge-idents/-/postcss-merge-idents-6.0.3.tgz#7b9c31c7bc823c94bec50f297f04e3c2b838ea65"
+  integrity sha512-1oIoAsODUs6IHQZkLQGO15uGEbK3EAl5wi9SS8hs45VgsxQfMnxvt+L+zIr7ifZFIH14cfAeVe2uCTa+SPRa3g==
   dependencies:
-    cssnano-utils "^3.1.0"
+    cssnano-utils "^4.0.2"
     postcss-value-parser "^4.2.0"
 
-postcss-merge-longhand@^5.1.7:
-  version "5.1.7"
-  resolved "https://registry.yarnpkg.com/postcss-merge-longhand/-/postcss-merge-longhand-5.1.7.tgz#24a1bdf402d9ef0e70f568f39bdc0344d568fb16"
-  integrity sha512-YCI9gZB+PLNskrK0BB3/2OzPnGhPkBEwmwhfYk1ilBHYVAZB7/tkTHFBAnCrvBBOmeYyMYw3DMjT55SyxMBzjQ==
+postcss-merge-longhand@^6.0.5:
+  version "6.0.5"
+  resolved "https://registry.yarnpkg.com/postcss-merge-longhand/-/postcss-merge-longhand-6.0.5.tgz#ba8a8d473617c34a36abbea8dda2b215750a065a"
+  integrity sha512-5LOiordeTfi64QhICp07nzzuTDjNSO8g5Ksdibt44d+uvIIAE1oZdRn8y/W5ZtYgRH/lnLDlvi9F8btZcVzu3w==
   dependencies:
     postcss-value-parser "^4.2.0"
-    stylehacks "^5.1.1"
+    stylehacks "^6.1.1"
 
-postcss-merge-rules@^5.1.4:
-  version "5.1.4"
-  resolved "https://registry.yarnpkg.com/postcss-merge-rules/-/postcss-merge-rules-5.1.4.tgz#2f26fa5cacb75b1402e213789f6766ae5e40313c"
-  integrity sha512-0R2IuYpgU93y9lhVbO/OylTtKMVcHb67zjWIfCiKR9rWL3GUk1677LAqD/BcHizukdZEjT8Ru3oHRoAYoJy44g==
+postcss-merge-rules@^6.1.1:
+  version "6.1.1"
+  resolved "https://registry.yarnpkg.com/postcss-merge-rules/-/postcss-merge-rules-6.1.1.tgz#7aa539dceddab56019469c0edd7d22b64c3dea9d"
+  integrity sha512-KOdWF0gju31AQPZiD+2Ar9Qjowz1LTChSjFFbS+e2sFgc4uHOp3ZvVX4sNeTlk0w2O31ecFGgrFzhO0RSWbWwQ==
   dependencies:
-    browserslist "^4.21.4"
+    browserslist "^4.23.0"
     caniuse-api "^3.0.0"
-    cssnano-utils "^3.1.0"
-    postcss-selector-parser "^6.0.5"
+    cssnano-utils "^4.0.2"
+    postcss-selector-parser "^6.0.16"
 
-postcss-minify-font-values@^5.1.0:
-  version "5.1.0"
-  resolved "https://registry.yarnpkg.com/postcss-minify-font-values/-/postcss-minify-font-values-5.1.0.tgz#f1df0014a726083d260d3bd85d7385fb89d1f01b"
-  integrity sha512-el3mYTgx13ZAPPirSVsHqFzl+BBBDrXvbySvPGFnQcTI4iNslrPaFq4muTkLZmKlGk4gyFAYUBMH30+HurREyA==
+postcss-minify-font-values@^6.1.0:
+  version "6.1.0"
+  resolved "https://registry.yarnpkg.com/postcss-minify-font-values/-/postcss-minify-font-values-6.1.0.tgz#a0e574c02ee3f299be2846369211f3b957ea4c59"
+  integrity sha512-gklfI/n+9rTh8nYaSJXlCo3nOKqMNkxuGpTn/Qm0gstL3ywTr9/WRKznE+oy6fvfolH6dF+QM4nCo8yPLdvGJg==
   dependencies:
     postcss-value-parser "^4.2.0"
 
-postcss-minify-gradients@^5.1.1:
-  version "5.1.1"
-  resolved "https://registry.yarnpkg.com/postcss-minify-gradients/-/postcss-minify-gradients-5.1.1.tgz#f1fe1b4f498134a5068240c2f25d46fcd236ba2c"
-  integrity sha512-VGvXMTpCEo4qHTNSa9A0a3D+dxGFZCYwR6Jokk+/3oB6flu2/PnPXAh2x7x52EkY5xlIHLm+Le8tJxe/7TNhzw==
+postcss-minify-gradients@^6.0.3:
+  version "6.0.3"
+  resolved "https://registry.yarnpkg.com/postcss-minify-gradients/-/postcss-minify-gradients-6.0.3.tgz#ca3eb55a7bdb48a1e187a55c6377be918743dbd6"
+  integrity sha512-4KXAHrYlzF0Rr7uc4VrfwDJ2ajrtNEpNEuLxFgwkhFZ56/7gaE4Nr49nLsQDZyUe+ds+kEhf+YAUolJiYXF8+Q==
   dependencies:
-    colord "^2.9.1"
-    cssnano-utils "^3.1.0"
+    colord "^2.9.3"
+    cssnano-utils "^4.0.2"
     postcss-value-parser "^4.2.0"
 
-postcss-minify-params@^5.1.4:
-  version "5.1.4"
-  resolved "https://registry.yarnpkg.com/postcss-minify-params/-/postcss-minify-params-5.1.4.tgz#c06a6c787128b3208b38c9364cfc40c8aa5d7352"
-  integrity sha512-+mePA3MgdmVmv6g+30rn57USjOGSAyuxUmkfiWpzalZ8aiBkdPYjXWtHuwJGm1v5Ojy0Z0LaSYhHaLJQB0P8Jw==
+postcss-minify-params@^6.1.0:
+  version "6.1.0"
+  resolved "https://registry.yarnpkg.com/postcss-minify-params/-/postcss-minify-params-6.1.0.tgz#54551dec77b9a45a29c3cb5953bf7325a399ba08"
+  integrity sha512-bmSKnDtyyE8ujHQK0RQJDIKhQ20Jq1LYiez54WiaOoBtcSuflfK3Nm596LvbtlFcpipMjgClQGyGr7GAs+H1uA==
   dependencies:
-    browserslist "^4.21.4"
-    cssnano-utils "^3.1.0"
+    browserslist "^4.23.0"
+    cssnano-utils "^4.0.2"
     postcss-value-parser "^4.2.0"
 
-postcss-minify-selectors@^5.2.1:
-  version "5.2.1"
-  resolved "https://registry.yarnpkg.com/postcss-minify-selectors/-/postcss-minify-selectors-5.2.1.tgz#d4e7e6b46147b8117ea9325a915a801d5fe656c6"
-  integrity sha512-nPJu7OjZJTsVUmPdm2TcaiohIwxP+v8ha9NehQ2ye9szv4orirRU3SDdtUmKH+10nzn0bAyOXZ0UEr7OpvLehg==
+postcss-minify-selectors@^6.0.4:
+  version "6.0.4"
+  resolved "https://registry.yarnpkg.com/postcss-minify-selectors/-/postcss-minify-selectors-6.0.4.tgz#197f7d72e6dd19eed47916d575d69dc38b396aff"
+  integrity sha512-L8dZSwNLgK7pjTto9PzWRoMbnLq5vsZSTu8+j1P/2GB8qdtGQfn+K1uSvFgYvgh83cbyxT5m43ZZhUMTJDSClQ==
   dependencies:
-    postcss-selector-parser "^6.0.5"
+    postcss-selector-parser "^6.0.16"
 
 postcss-modules-extract-imports@^3.0.0:
   version "3.0.0"
@@ -6691,100 +7579,107 @@ postcss-modules-values@^4.0.0:
   dependencies:
     icss-utils "^5.0.0"
 
-postcss-normalize-charset@^5.1.0:
-  version "5.1.0"
-  resolved "https://registry.yarnpkg.com/postcss-normalize-charset/-/postcss-normalize-charset-5.1.0.tgz#9302de0b29094b52c259e9b2cf8dc0879879f0ed"
-  integrity sha512-mSgUJ+pd/ldRGVx26p2wz9dNZ7ji6Pn8VWBajMXFf8jk7vUoSrZ2lt/wZR7DtlZYKesmZI680qjr2CeFF2fbUg==
+postcss-normalize-charset@^6.0.2:
+  version "6.0.2"
+  resolved "https://registry.yarnpkg.com/postcss-normalize-charset/-/postcss-normalize-charset-6.0.2.tgz#1ec25c435057a8001dac942942a95ffe66f721e1"
+  integrity sha512-a8N9czmdnrjPHa3DeFlwqst5eaL5W8jYu3EBbTTkI5FHkfMhFZh1EGbku6jhHhIzTA6tquI2P42NtZ59M/H/kQ==
 
-postcss-normalize-display-values@^5.1.0:
-  version "5.1.0"
-  resolved "https://registry.yarnpkg.com/postcss-normalize-display-values/-/postcss-normalize-display-values-5.1.0.tgz#72abbae58081960e9edd7200fcf21ab8325c3da8"
-  integrity sha512-WP4KIM4o2dazQXWmFaqMmcvsKmhdINFblgSeRgn8BJ6vxaMyaJkwAzpPpuvSIoG/rmX3M+IrRZEz2H0glrQNEA==
+postcss-normalize-display-values@^6.0.2:
+  version "6.0.2"
+  resolved "https://registry.yarnpkg.com/postcss-normalize-display-values/-/postcss-normalize-display-values-6.0.2.tgz#54f02764fed0b288d5363cbb140d6950dbbdd535"
+  integrity sha512-8H04Mxsb82ON/aAkPeq8kcBbAtI5Q2a64X/mnRRfPXBq7XeogoQvReqxEfc0B4WPq1KimjezNC8flUtC3Qz6jg==
   dependencies:
     postcss-value-parser "^4.2.0"
 
-postcss-normalize-positions@^5.1.1:
-  version "5.1.1"
-  resolved "https://registry.yarnpkg.com/postcss-normalize-positions/-/postcss-normalize-positions-5.1.1.tgz#ef97279d894087b59325b45c47f1e863daefbb92"
-  integrity sha512-6UpCb0G4eofTCQLFVuI3EVNZzBNPiIKcA1AKVka+31fTVySphr3VUgAIULBhxZkKgwLImhzMR2Bw1ORK+37INg==
+postcss-normalize-positions@^6.0.2:
+  version "6.0.2"
+  resolved "https://registry.yarnpkg.com/postcss-normalize-positions/-/postcss-normalize-positions-6.0.2.tgz#e982d284ec878b9b819796266f640852dbbb723a"
+  integrity sha512-/JFzI441OAB9O7VnLA+RtSNZvQ0NCFZDOtp6QPFo1iIyawyXg0YI3CYM9HBy1WvwCRHnPep/BvI1+dGPKoXx/Q==
   dependencies:
     postcss-value-parser "^4.2.0"
 
-postcss-normalize-repeat-style@^5.1.1:
-  version "5.1.1"
-  resolved "https://registry.yarnpkg.com/postcss-normalize-repeat-style/-/postcss-normalize-repeat-style-5.1.1.tgz#e9eb96805204f4766df66fd09ed2e13545420fb2"
-  integrity sha512-mFpLspGWkQtBcWIRFLmewo8aC3ImN2i/J3v8YCFUwDnPu3Xz4rLohDO26lGjwNsQxB3YF0KKRwspGzE2JEuS0g==
+postcss-normalize-repeat-style@^6.0.2:
+  version "6.0.2"
+  resolved "https://registry.yarnpkg.com/postcss-normalize-repeat-style/-/postcss-normalize-repeat-style-6.0.2.tgz#f8006942fd0617c73f049dd8b6201c3a3040ecf3"
+  integrity sha512-YdCgsfHkJ2jEXwR4RR3Tm/iOxSfdRt7jplS6XRh9Js9PyCR/aka/FCb6TuHT2U8gQubbm/mPmF6L7FY9d79VwQ==
   dependencies:
     postcss-value-parser "^4.2.0"
 
-postcss-normalize-string@^5.1.0:
-  version "5.1.0"
-  resolved "https://registry.yarnpkg.com/postcss-normalize-string/-/postcss-normalize-string-5.1.0.tgz#411961169e07308c82c1f8c55f3e8a337757e228"
-  integrity sha512-oYiIJOf4T9T1N4i+abeIc7Vgm/xPCGih4bZz5Nm0/ARVJ7K6xrDlLwvwqOydvyL3RHNf8qZk6vo3aatiw/go3w==
+postcss-normalize-string@^6.0.2:
+  version "6.0.2"
+  resolved "https://registry.yarnpkg.com/postcss-normalize-string/-/postcss-normalize-string-6.0.2.tgz#e3cc6ad5c95581acd1fc8774b309dd7c06e5e363"
+  integrity sha512-vQZIivlxlfqqMp4L9PZsFE4YUkWniziKjQWUtsxUiVsSSPelQydwS8Wwcuw0+83ZjPWNTl02oxlIvXsmmG+CiQ==
   dependencies:
     postcss-value-parser "^4.2.0"
 
-postcss-normalize-timing-functions@^5.1.0:
-  version "5.1.0"
-  resolved "https://registry.yarnpkg.com/postcss-normalize-timing-functions/-/postcss-normalize-timing-functions-5.1.0.tgz#d5614410f8f0b2388e9f240aa6011ba6f52dafbb"
-  integrity sha512-DOEkzJ4SAXv5xkHl0Wa9cZLF3WCBhF3o1SKVxKQAa+0pYKlueTpCgvkFAHfk+Y64ezX9+nITGrDZeVGgITJXjg==
+postcss-normalize-timing-functions@^6.0.2:
+  version "6.0.2"
+  resolved "https://registry.yarnpkg.com/postcss-normalize-timing-functions/-/postcss-normalize-timing-functions-6.0.2.tgz#40cb8726cef999de984527cbd9d1db1f3e9062c0"
+  integrity sha512-a+YrtMox4TBtId/AEwbA03VcJgtyW4dGBizPl7e88cTFULYsprgHWTbfyjSLyHeBcK/Q9JhXkt2ZXiwaVHoMzA==
   dependencies:
     postcss-value-parser "^4.2.0"
 
-postcss-normalize-unicode@^5.1.1:
-  version "5.1.1"
-  resolved "https://registry.yarnpkg.com/postcss-normalize-unicode/-/postcss-normalize-unicode-5.1.1.tgz#f67297fca3fea7f17e0d2caa40769afc487aa030"
-  integrity sha512-qnCL5jzkNUmKVhZoENp1mJiGNPcsJCs1aaRmURmeJGES23Z/ajaln+EPTD+rBeNkSryI+2WTdW+lwcVdOikrpA==
+postcss-normalize-unicode@^6.1.0:
+  version "6.1.0"
+  resolved "https://registry.yarnpkg.com/postcss-normalize-unicode/-/postcss-normalize-unicode-6.1.0.tgz#aaf8bbd34c306e230777e80f7f12a4b7d27ce06e"
+  integrity sha512-QVC5TQHsVj33otj8/JD869Ndr5Xcc/+fwRh4HAsFsAeygQQXm+0PySrKbr/8tkDKzW+EVT3QkqZMfFrGiossDg==
   dependencies:
-    browserslist "^4.21.4"
+    browserslist "^4.23.0"
     postcss-value-parser "^4.2.0"
 
-postcss-normalize-url@^5.1.0:
-  version "5.1.0"
-  resolved "https://registry.yarnpkg.com/postcss-normalize-url/-/postcss-normalize-url-5.1.0.tgz#ed9d88ca82e21abef99f743457d3729a042adcdc"
-  integrity sha512-5upGeDO+PVthOxSmds43ZeMeZfKH+/DKgGRD7TElkkyS46JXAUhMzIKiCa7BabPeIy3AQcTkXwVVN7DbqsiCew==
+postcss-normalize-url@^6.0.2:
+  version "6.0.2"
+  resolved "https://registry.yarnpkg.com/postcss-normalize-url/-/postcss-normalize-url-6.0.2.tgz#292792386be51a8de9a454cb7b5c58ae22db0f79"
+  integrity sha512-kVNcWhCeKAzZ8B4pv/DnrU1wNh458zBNp8dh4y5hhxih5RZQ12QWMuQrDgPRw3LRl8mN9vOVfHl7uhvHYMoXsQ==
   dependencies:
-    normalize-url "^6.0.1"
     postcss-value-parser "^4.2.0"
 
-postcss-normalize-whitespace@^5.1.1:
-  version "5.1.1"
-  resolved "https://registry.yarnpkg.com/postcss-normalize-whitespace/-/postcss-normalize-whitespace-5.1.1.tgz#08a1a0d1ffa17a7cc6efe1e6c9da969cc4493cfa"
-  integrity sha512-83ZJ4t3NUDETIHTa3uEg6asWjSBYL5EdkVB0sDncx9ERzOKBVJIUeDO9RyA9Zwtig8El1d79HBp0JEi8wvGQnA==
+postcss-normalize-whitespace@^6.0.2:
+  version "6.0.2"
+  resolved "https://registry.yarnpkg.com/postcss-normalize-whitespace/-/postcss-normalize-whitespace-6.0.2.tgz#fbb009e6ebd312f8b2efb225c2fcc7cf32b400cd"
+  integrity sha512-sXZ2Nj1icbJOKmdjXVT9pnyHQKiSAyuNQHSgRCUgThn2388Y9cGVDR+E9J9iAYbSbLHI+UUwLVl1Wzco/zgv0Q==
   dependencies:
     postcss-value-parser "^4.2.0"
 
-postcss-ordered-values@^5.1.3:
-  version "5.1.3"
-  resolved "https://registry.yarnpkg.com/postcss-ordered-values/-/postcss-ordered-values-5.1.3.tgz#b6fd2bd10f937b23d86bc829c69e7732ce76ea38"
-  integrity sha512-9UO79VUhPwEkzbb3RNpqqghc6lcYej1aveQteWY+4POIwlqkYE21HKWaLDF6lWNuqCobEAyTovVhtI32Rbv2RQ==
+postcss-ordered-values@^6.0.2:
+  version "6.0.2"
+  resolved "https://registry.yarnpkg.com/postcss-ordered-values/-/postcss-ordered-values-6.0.2.tgz#366bb663919707093451ab70c3f99c05672aaae5"
+  integrity sha512-VRZSOB+JU32RsEAQrO94QPkClGPKJEL/Z9PCBImXMhIeK5KAYo6slP/hBYlLgrCjFxyqvn5VC81tycFEDBLG1Q==
   dependencies:
-    cssnano-utils "^3.1.0"
+    cssnano-utils "^4.0.2"
     postcss-value-parser "^4.2.0"
 
-postcss-reduce-idents@^5.2.0:
-  version "5.2.0"
-  resolved "https://registry.yarnpkg.com/postcss-reduce-idents/-/postcss-reduce-idents-5.2.0.tgz#c89c11336c432ac4b28792f24778859a67dfba95"
-  integrity sha512-BTrLjICoSB6gxbc58D5mdBK8OhXRDqud/zodYfdSi52qvDHdMwk+9kB9xsM8yJThH/sZU5A6QVSmMmaN001gIg==
+postcss-reduce-idents@^6.0.3:
+  version "6.0.3"
+  resolved "https://registry.yarnpkg.com/postcss-reduce-idents/-/postcss-reduce-idents-6.0.3.tgz#b0d9c84316d2a547714ebab523ec7d13704cd486"
+  integrity sha512-G3yCqZDpsNPoQgbDUy3T0E6hqOQ5xigUtBQyrmq3tn2GxlyiL0yyl7H+T8ulQR6kOcHJ9t7/9H4/R2tv8tJbMA==
   dependencies:
     postcss-value-parser "^4.2.0"
 
-postcss-reduce-initial@^5.1.2:
-  version "5.1.2"
-  resolved "https://registry.yarnpkg.com/postcss-reduce-initial/-/postcss-reduce-initial-5.1.2.tgz#798cd77b3e033eae7105c18c9d371d989e1382d6"
-  integrity sha512-dE/y2XRaqAi6OvjzD22pjTUQ8eOfc6m/natGHgKFBK9DxFmIm69YmaRVQrGgFlEfc1HePIurY0TmDeROK05rIg==
+postcss-reduce-initial@^6.1.0:
+  version "6.1.0"
+  resolved "https://registry.yarnpkg.com/postcss-reduce-initial/-/postcss-reduce-initial-6.1.0.tgz#4401297d8e35cb6e92c8e9586963e267105586ba"
+  integrity sha512-RarLgBK/CrL1qZags04oKbVbrrVK2wcxhvta3GCxrZO4zveibqbRPmm2VI8sSgCXwoUHEliRSbOfpR0b/VIoiw==
   dependencies:
-    browserslist "^4.21.4"
+    browserslist "^4.23.0"
     caniuse-api "^3.0.0"
 
-postcss-reduce-transforms@^5.1.0:
-  version "5.1.0"
-  resolved "https://registry.yarnpkg.com/postcss-reduce-transforms/-/postcss-reduce-transforms-5.1.0.tgz#333b70e7758b802f3dd0ddfe98bb1ccfef96b6e9"
-  integrity sha512-2fbdbmgir5AvpW9RLtdONx1QoYG2/EtqpNQbFASDlixBbAYuTcJ0dECwlqNqH7VbaUnEnh8SrxOe2sRIn24XyQ==
+postcss-reduce-transforms@^6.0.2:
+  version "6.0.2"
+  resolved "https://registry.yarnpkg.com/postcss-reduce-transforms/-/postcss-reduce-transforms-6.0.2.tgz#6fa2c586bdc091a7373caeee4be75a0f3e12965d"
+  integrity sha512-sB+Ya++3Xj1WaT9+5LOOdirAxP7dJZms3GRcYheSPi1PiTMigsxHAdkrbItHxwYHr4kt1zL7mmcHstgMYT+aiA==
   dependencies:
     postcss-value-parser "^4.2.0"
 
-postcss-selector-parser@^6.0.2, postcss-selector-parser@^6.0.4, postcss-selector-parser@^6.0.5, postcss-selector-parser@^6.0.9:
+postcss-selector-parser@^6.0.11, postcss-selector-parser@^6.0.16:
+  version "6.1.2"
+  resolved "https://registry.yarnpkg.com/postcss-selector-parser/-/postcss-selector-parser-6.1.2.tgz#27ecb41fb0e3b6ba7a1ec84fff347f734c7929de"
+  integrity sha512-Q8qQfPiZ+THO/3ZrOrO0cJJKfpYCagtMUkXbnEfmgUjwXg6z/WBeOyS9APBBPCTSiDV+s4SwQGu8yFsiMRIudg==
+  dependencies:
+    cssesc "^3.0.0"
+    util-deprecate "^1.0.2"
+
+postcss-selector-parser@^6.0.2, postcss-selector-parser@^6.0.4:
   version "6.0.13"
   resolved "https://registry.yarnpkg.com/postcss-selector-parser/-/postcss-selector-parser-6.0.13.tgz#d05d8d76b1e8e173257ef9d60b706a8e5e99bf1b"
   integrity sha512-EaV1Gl4mUEV4ddhDnv/xtj7sxwrwxdetHdWUGnT4VJQf+4d05v6lHYZr8N573k5Z0BViss7BDhfWtKS3+sfAqQ==
@@ -6792,39 +7687,39 @@ postcss-selector-parser@^6.0.2, postcss-selector-parser@^6.0.4, postcss-selector
     cssesc "^3.0.0"
     util-deprecate "^1.0.2"
 
-postcss-sort-media-queries@^4.4.1:
-  version "4.4.1"
-  resolved "https://registry.yarnpkg.com/postcss-sort-media-queries/-/postcss-sort-media-queries-4.4.1.tgz#04a5a78db3921eb78f28a1a781a2e68e65258128"
-  integrity sha512-QDESFzDDGKgpiIh4GYXsSy6sek2yAwQx1JASl5AxBtU1Lq2JfKBljIPNdil989NcSKRQX1ToiaKphImtBuhXWw==
+postcss-sort-media-queries@^5.2.0:
+  version "5.2.0"
+  resolved "https://registry.yarnpkg.com/postcss-sort-media-queries/-/postcss-sort-media-queries-5.2.0.tgz#4556b3f982ef27d3bac526b99b6c0d3359a6cf97"
+  integrity sha512-AZ5fDMLD8SldlAYlvi8NIqo0+Z8xnXU2ia0jxmuhxAU+Lqt9K+AlmLNJ/zWEnE9x+Zx3qL3+1K20ATgNOr3fAA==
   dependencies:
-    sort-css-media-queries "2.1.0"
+    sort-css-media-queries "2.2.0"
 
-postcss-svgo@^5.1.0:
-  version "5.1.0"
-  resolved "https://registry.yarnpkg.com/postcss-svgo/-/postcss-svgo-5.1.0.tgz#0a317400ced789f233a28826e77523f15857d80d"
-  integrity sha512-D75KsH1zm5ZrHyxPakAxJWtkyXew5qwS70v56exwvw542d9CRtTo78K0WeFxZB4G7JXKKMbEZtZayTGdIky/eA==
+postcss-svgo@^6.0.3:
+  version "6.0.3"
+  resolved "https://registry.yarnpkg.com/postcss-svgo/-/postcss-svgo-6.0.3.tgz#1d6e180d6df1fa8a3b30b729aaa9161e94f04eaa"
+  integrity sha512-dlrahRmxP22bX6iKEjOM+c8/1p+81asjKT+V5lrgOH944ryx/OHpclnIbGsKVd3uWOXFLYJwCVf0eEkJGvO96g==
   dependencies:
     postcss-value-parser "^4.2.0"
-    svgo "^2.7.0"
+    svgo "^3.2.0"
 
-postcss-unique-selectors@^5.1.1:
-  version "5.1.1"
-  resolved "https://registry.yarnpkg.com/postcss-unique-selectors/-/postcss-unique-selectors-5.1.1.tgz#a9f273d1eacd09e9aa6088f4b0507b18b1b541b6"
-  integrity sha512-5JiODlELrz8L2HwxfPnhOWZYWDxVHWL83ufOv84NrcgipI7TaeRsatAhK4Tr2/ZiYldpK/wBvw5BD3qfaK96GA==
+postcss-unique-selectors@^6.0.4:
+  version "6.0.4"
+  resolved "https://registry.yarnpkg.com/postcss-unique-selectors/-/postcss-unique-selectors-6.0.4.tgz#983ab308896b4bf3f2baaf2336e14e52c11a2088"
+  integrity sha512-K38OCaIrO8+PzpArzkLKB42dSARtC2tmG6PvD4b1o1Q2E9Os8jzfWFfSy/rixsHwohtsDdFtAWGjFVFUdwYaMg==
   dependencies:
-    postcss-selector-parser "^6.0.5"
+    postcss-selector-parser "^6.0.16"
 
 postcss-value-parser@^4.1.0, postcss-value-parser@^4.2.0:
   version "4.2.0"
   resolved "https://registry.yarnpkg.com/postcss-value-parser/-/postcss-value-parser-4.2.0.tgz#723c09920836ba6d3e5af019f92bc0971c02e514"
   integrity sha512-1NNCs6uurfkVbeXG4S8JFT9t19m45ICnif8zWLd5oPSZ50QnwMfK+H3jv408d4jw/7Bttv5axS5IiHoLaVNHeQ==
 
-postcss-zindex@^5.1.0:
-  version "5.1.0"
-  resolved "https://registry.yarnpkg.com/postcss-zindex/-/postcss-zindex-5.1.0.tgz#4a5c7e5ff1050bd4c01d95b1847dfdcc58a496ff"
-  integrity sha512-fgFMf0OtVSBR1va1JNHYgMxYk73yhn/qb4uQDq1DLGYolz8gHCyr/sesEuGUaYs58E3ZJRcpoGuPVoB7Meiq9A==
+postcss-zindex@^6.0.2:
+  version "6.0.2"
+  resolved "https://registry.yarnpkg.com/postcss-zindex/-/postcss-zindex-6.0.2.tgz#e498304b83a8b165755f53db40e2ea65a99b56e1"
+  integrity sha512-5BxW9l1evPB/4ZIc+2GobEBoKC+h8gPGCMi+jxsYvd2x0mjq7wazk6DrP71pStqxE9Foxh5TVnonbWpFZzXaYg==
 
-postcss@^8.4.17, postcss@^8.4.21, postcss@^8.4.26:
+postcss@^8.4.21, postcss@^8.4.26:
   version "8.4.31"
   resolved "https://registry.yarnpkg.com/postcss/-/postcss-8.4.31.tgz#92b451050a9f914da6755af352bdc0192508656d"
   integrity sha512-PS08Iboia9mts/2ygV3eLpY5ghnUcfLV/EXTOW1E2qYxJKGGBUtNjN76FYHnMs36RmARn41bC0AZmn+rR0OVpQ==
@@ -6833,6 +7728,15 @@ postcss@^8.4.17, postcss@^8.4.21, postcss@^8.4.26:
     picocolors "^1.0.0"
     source-map-js "^1.0.2"
 
+postcss@^8.4.24, postcss@^8.4.38:
+  version "8.4.41"
+  resolved "https://registry.yarnpkg.com/postcss/-/postcss-8.4.41.tgz#d6104d3ba272d882fe18fc07d15dc2da62fa2681"
+  integrity sha512-TesUflQ0WKZqAvg52PWL6kHgLKP6xB6heTOdoYM0Wt2UHyxNa4K25EZZMgKns3BH1RLVbZCREPpLY0rhnNoHVQ==
+  dependencies:
+    nanoid "^3.3.7"
+    picocolors "^1.0.1"
+    source-map-js "^1.2.0"
+
 pretty-error@^4.0.0:
   version "4.0.0"
   resolved "https://registry.yarnpkg.com/pretty-error/-/pretty-error-4.0.0.tgz#90a703f46dd7234adb46d0f84823e9d1cb8f10d6"
@@ -7061,6 +7965,13 @@ react-loadable-ssr-addon-v5-slorber@^1.0.1:
   dependencies:
     "@babel/runtime" "^7.10.3"
 
+"react-loadable@npm:@docusaurus/react-loadable@6.0.0":
+  version "6.0.0"
+  resolved "https://registry.yarnpkg.com/@docusaurus/react-loadable/-/react-loadable-6.0.0.tgz#de6c7f73c96542bd70786b8e522d535d69069dc4"
+  integrity sha512-YMMxTUQV/QFSnbgrP3tjDzLHRg7vsbMn8e9HAa8o/1iXoiomo48b7sk/kkmWEuWNDPJVlKSJRB6Y2fHqdJk+SQ==
+  dependencies:
+    "@types/react" "*"
+
 react-router-config@^5.1.1:
   version "5.1.1"
   resolved "https://registry.yarnpkg.com/react-router-config/-/react-router-config-5.1.1.tgz#0f4263d1a80c6b2dc7b9c1902c9526478194a988"
@@ -7444,7 +8355,7 @@ schema-utils@^3.0.0, schema-utils@^3.1.1, schema-utils@^3.2.0:
     ajv "^6.12.5"
     ajv-keywords "^3.5.2"
 
-schema-utils@^4.0.0:
+schema-utils@^4.0.0, schema-utils@^4.0.1:
   version "4.2.0"
   resolved "https://registry.yarnpkg.com/schema-utils/-/schema-utils-4.2.0.tgz#70d7c93e153a273a805801882ebd3bff20d89c8b"
   integrity sha512-L0jRsrPpjdckP3oPug3/VxNKt2trR8TcabrM6FOAAlvC/9Phcmm+cuAgTlxBqdBR1WJx7Naj9WHw+aOmheSVbw==
@@ -7670,6 +8581,14 @@ slash@^4.0.0:
   resolved "https://registry.yarnpkg.com/slash/-/slash-4.0.0.tgz#2422372176c4c6c5addb5e2ada885af984b396a7"
   integrity sha512-3dOsAHXXUkQTpOYcoAxLIorMTp4gIQr5IW3iVb7A7lFIp0VHhnynm9izx6TssdrIcVIESAlVjtnO2K8bg+Coew==
 
+snake-case@^3.0.4:
+  version "3.0.4"
+  resolved "https://registry.yarnpkg.com/snake-case/-/snake-case-3.0.4.tgz#4f2bbd568e9935abdfd593f34c691dadb49c452c"
+  integrity sha512-LAOh4z89bGQvl9pFfNF8V146i7o7/CqFPbqzYgP+yYzDIDeS9HaNFtXABamRW+AQzEVODcvE79ljJ+8a9YSdMg==
+  dependencies:
+    dot-case "^3.0.4"
+    tslib "^2.0.3"
+
 sockjs@^0.3.24:
   version "0.3.24"
   resolved "https://registry.yarnpkg.com/sockjs/-/sockjs-0.3.24.tgz#c9bc8995f33a111bea0395ec30aa3206bdb5ccce"
@@ -7679,10 +8598,15 @@ sockjs@^0.3.24:
     uuid "^8.3.2"
     websocket-driver "^0.7.4"
 
-sort-css-media-queries@2.1.0:
-  version "2.1.0"
-  resolved "https://registry.yarnpkg.com/sort-css-media-queries/-/sort-css-media-queries-2.1.0.tgz#7c85e06f79826baabb232f5560e9745d7a78c4ce"
-  integrity sha512-IeWvo8NkNiY2vVYdPa27MCQiR0MN0M80johAYFVxWWXQ44KU84WNxjslwBHmc/7ZL2ccwkM7/e6S5aiKZXm7jA==
+sort-css-media-queries@2.2.0:
+  version "2.2.0"
+  resolved "https://registry.yarnpkg.com/sort-css-media-queries/-/sort-css-media-queries-2.2.0.tgz#aa33cf4a08e0225059448b6c40eddbf9f1c8334c"
+  integrity sha512-0xtkGhWCC9MGt/EzgnvbbbKhqWjl1+/rncmhTh5qCpbYguXh6S/qwePfv/JQ8jePXXmqingylxoC49pCkSPIbA==
+
+source-map-js@^1.0.1, source-map-js@^1.2.0:
+  version "1.2.0"
+  resolved "https://registry.yarnpkg.com/source-map-js/-/source-map-js-1.2.0.tgz#16b809c162517b5b8c3e7dcd315a2a5c2612b2af"
+  integrity sha512-itJW8lvSA0TXEphiRoawsCksnlf8SyvmFzIhltqAHluXd88pkCd+cXJVHTDwdCr0IzwptSm035IHQktUu1QUMg==
 
 source-map-js@^1.0.2:
   version "1.0.2"
@@ -7697,7 +8621,7 @@ source-map-support@~0.5.20:
     buffer-from "^1.0.0"
     source-map "^0.6.0"
 
-source-map@^0.6.0, source-map@^0.6.1, source-map@~0.6.0:
+source-map@^0.6.0, source-map@~0.6.0:
   version "0.6.1"
   resolved "https://registry.yarnpkg.com/source-map/-/source-map-0.6.1.tgz#74722af32e9614e9c287a8d0bbde48b5e2f1a263"
   integrity sha512-UjgapumWlbMhkBgzT7Ykc5YXUT46F0iKu8SGXq0bcwP5dz/h0Plj6enJqjz1Zbq2l5WaqYnrVbwWOWMyF3F47g==
@@ -7745,11 +8669,6 @@ srcset@^4.0.0:
   resolved "https://registry.yarnpkg.com/srcset/-/srcset-4.0.0.tgz#336816b665b14cd013ba545b6fe62357f86e65f4"
   integrity sha512-wvLeHgcVHKO8Sc/H/5lkGreJQVeYMm9rlmt8PuR1xE31rIuXhuzznUUqAt8MqLhB3MqJdFzlNAfpcWnxiFUcPw==
 
-stable@^0.1.8:
-  version "0.1.8"
-  resolved "https://registry.yarnpkg.com/stable/-/stable-0.1.8.tgz#836eb3c8382fe2936feaf544631017ce7d47a3cf"
-  integrity sha512-ji9qxRnOVfcuLDySj9qzhGSEFVobyt1kIOSkj1qZzYLzq7Tos/oUUWvotUPQLlrsidqsK6tBH89Bc9kL5zHA6w==
-
 statuses@2.0.1:
   version "2.0.1"
   resolved "https://registry.yarnpkg.com/statuses/-/statuses-2.0.1.tgz#55cb000ccf1d48728bd23c685a063998cf1a1b63"
@@ -7855,13 +8774,13 @@ style-to-object@^0.4.0:
   dependencies:
     inline-style-parser "0.1.1"
 
-stylehacks@^5.1.1:
-  version "5.1.1"
-  resolved "https://registry.yarnpkg.com/stylehacks/-/stylehacks-5.1.1.tgz#7934a34eb59d7152149fa69d6e9e56f2fc34bcc9"
-  integrity sha512-sBpcd5Hx7G6seo7b1LkpttvTz7ikD0LlH5RmdcBNb6fFR0Fl7LQwHDFr300q4cwUqi+IYrFGmsIHieMBfnN/Bw==
+stylehacks@^6.1.1:
+  version "6.1.1"
+  resolved "https://registry.yarnpkg.com/stylehacks/-/stylehacks-6.1.1.tgz#543f91c10d17d00a440430362d419f79c25545a6"
+  integrity sha512-gSTTEQ670cJNoaeIp9KX6lZmm8LJ3jPB5yJmX8Zq/wQxOsAFXV3qjWzHas3YYk1qesuVIyYWWUpZ0vSE/dTSGg==
   dependencies:
-    browserslist "^4.21.4"
-    postcss-selector-parser "^6.0.4"
+    browserslist "^4.23.0"
+    postcss-selector-parser "^6.0.16"
 
 supports-color@^5.3.0:
   version "5.5.0"
@@ -7894,18 +8813,18 @@ svg-parser@^2.0.4:
   resolved "https://registry.yarnpkg.com/svg-parser/-/svg-parser-2.0.4.tgz#fdc2e29e13951736140b76cb122c8ee6630eb6b5"
   integrity sha512-e4hG1hRwoOdRb37cIMSgzNsxyzKfayW6VOflrwvR+/bzrkyxY/31WkbgnQpgtrNp1SdpJvpUAGTa/ZoiPNDuRQ==
 
-svgo@^2.7.0, svgo@^2.8.0:
-  version "2.8.0"
-  resolved "https://registry.yarnpkg.com/svgo/-/svgo-2.8.0.tgz#4ff80cce6710dc2795f0c7c74101e6764cfccd24"
-  integrity sha512-+N/Q9kV1+F+UeWYoSiULYo4xYSDQlTgb+ayMobAXPwMnLvop7oxKMo9OzIrX5x3eS4L4f2UHhc9axXwY8DpChg==
+svgo@^3.0.2, svgo@^3.2.0:
+  version "3.3.2"
+  resolved "https://registry.yarnpkg.com/svgo/-/svgo-3.3.2.tgz#ad58002652dffbb5986fc9716afe52d869ecbda8"
+  integrity sha512-OoohrmuUlBs8B8o6MB2Aevn+pRIH9zDALSR+6hhqVfa6fRwG/Qw9VUMSMW9VNg2CFc/MTIfabtdOVl9ODIJjpw==
   dependencies:
     "@trysound/sax" "0.2.0"
     commander "^7.2.0"
-    css-select "^4.1.3"
-    css-tree "^1.1.3"
-    csso "^4.2.0"
+    css-select "^5.1.0"
+    css-tree "^2.3.1"
+    css-what "^6.1.0"
+    csso "^5.0.5"
     picocolors "^1.0.0"
-    stable "^0.1.8"
 
 tapable@^1.0.0:
   version "1.1.3"
@@ -8144,6 +9063,14 @@ update-browserslist-db@^1.0.13:
     escalade "^3.1.1"
     picocolors "^1.0.0"
 
+update-browserslist-db@^1.1.0:
+  version "1.1.0"
+  resolved "https://registry.yarnpkg.com/update-browserslist-db/-/update-browserslist-db-1.1.0.tgz#7ca61c0d8650766090728046e416a8cde682859e"
+  integrity sha512-EdRAaAyk2cUE1wOf2DkEhzxqOQvFOoRJFNS6NeyJ01Gp2beMRpBAINjM2iDXE3KCuKhwnvHIQCJm6ThL2Z+HzQ==
+  dependencies:
+    escalade "^3.1.2"
+    picocolors "^1.0.1"
+
 update-notifier@^6.0.2:
   version "6.0.2"
   resolved "https://registry.yarnpkg.com/update-notifier/-/update-notifier-6.0.2.tgz#a6990253dfe6d5a02bd04fbb6a61543f55026b60"
@@ -8339,7 +9266,7 @@ webpack-merge@^5.9.0:
     flat "^5.0.2"
     wildcard "^2.0.0"
 
-webpack-sources@^3.2.2, webpack-sources@^3.2.3:
+webpack-sources@^3.2.3:
   version "3.2.3"
   resolved "https://registry.yarnpkg.com/webpack-sources/-/webpack-sources-3.2.3.tgz#2d4daab8451fd4b240cc27055ff6a0c2ccea0cde"
   integrity sha512-/DyMEOrDgLKKIG0fmvtz+4dUX/3Ghozwgm6iPp8KRhvn+eQf9+Q7GWxVNMk3+uCPWfdXYC4ExGBckIXdFEfH1w==
@@ -8480,7 +9407,7 @@ yallist@^4.0.0:
   resolved "https://registry.yarnpkg.com/yallist/-/yallist-4.0.0.tgz#9bb92790d9c0effec63be73519e11a35019a3a72"
   integrity sha512-3wdGidZyq5PB084XLES5TpOSRA3wjXAlIWMhum2kRcv/41Sn2emQ0dycQW4uZXLejwKvg6EsvbdlVL+FYEct7A==
 
-yaml@^1.10.0, yaml@^1.10.2, yaml@^1.7.2:
+yaml@^1.7.2:
   version "1.10.2"
   resolved "https://registry.yarnpkg.com/yaml/-/yaml-1.10.2.tgz#2301c5ffbf12b467de8da2333a459e29e7920e4b"
   integrity sha512-r3vXyErRCYJ7wg28yvBY5VSoAF8ZvlcW9/BwUzEtUsjvX/DKs24dIkuwjtuprwJJHsbyUbLApepYTR1BN4uHrg==
diff --git a/docs/en/_assets/commonMarkdown/FE_config_method.md b/docs/en/_assets/commonMarkdown/FE_config_method.md
index 3ad13a4233ca05..e069a9cab44343 100644
--- a/docs/en/_assets/commonMarkdown/FE_config_method.md
+++ b/docs/en/_assets/commonMarkdown/FE_config_method.md
@@ -4,6 +4,6 @@ FE parameters are classified into dynamic parameters and static parameters.
 
 - Static parameters can only be configured and adjusted in the FE configuration file **fe.conf**. **After you modify this file, you must restart your FE for the changes to take effect.**
 
-Whether a parameter is a dynamic parameter is indicated by the `IsMutable` column in the output of [ADMIN SHOW CONFIG](../../sql-reference/sql-statements/Administration/ADMIN_SHOW_CONFIG.md). `TRUE` indicates a dynamic parameter.
+Whether a parameter is a dynamic parameter is indicated by the `IsMutable` column in the output of [ADMIN SHOW CONFIG](../../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SHOW_CONFIG.md). `TRUE` indicates a dynamic parameter.
 
 Note that both dynamic and static FE parameters can be configured in the **fe.conf** file.
diff --git a/docs/en/_assets/commonMarkdown/loadMethodIntro.md b/docs/en/_assets/commonMarkdown/loadMethodIntro.md
index 02dbdaf461a497..d5cc7a640afa5e 100644
--- a/docs/en/_assets/commonMarkdown/loadMethodIntro.md
+++ b/docs/en/_assets/commonMarkdown/loadMethodIntro.md
@@ -1,7 +1,7 @@
 
-- Synchronous loading using [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md)+[`FILES()`](../../sql-reference/sql-functions/table-functions/files.md)
-- Asynchronous loading using [Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)
-- Continuous asynchronous loading using [Pipe](../../sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md)
+- Synchronous loading using [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md)+[`FILES()`](../../sql-reference/sql-functions/table-functions/files.md)
+- Asynchronous loading using [Broker Load](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)
+- Continuous asynchronous loading using [Pipe](../../sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md)
 
 Each of these options has its own advantages, which are detailed in the following sections.
 
diff --git a/docs/en/_assets/commonMarkdown/sharedDataUse.md b/docs/en/_assets/commonMarkdown/sharedDataUse.md
index 38bf919e884c67..395008c9a9ad0e 100644
--- a/docs/en/_assets/commonMarkdown/sharedDataUse.md
+++ b/docs/en/_assets/commonMarkdown/sharedDataUse.md
@@ -1,5 +1,5 @@
 
-For more information on how to create a storage volume for other object storages and set the default storage volume, see [CREATE STORAGE VOLUME](../../sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md) and [SET DEFAULT STORAGE VOLUME](../../sql-reference/sql-statements/Administration/SET_DEFAULT_STORAGE_VOLUME.md).
+For more information on how to create a storage volume for other object storages and set the default storage volume, see [CREATE STORAGE VOLUME](../../sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md) and [SET DEFAULT STORAGE VOLUME](../../sql-reference/sql-statements/cluster-management/storage_volume/SET_DEFAULT_STORAGE_VOLUME.md).
 
 ### Create a database and a cloud-native table
 
@@ -69,7 +69,7 @@ Whether to allow data to be written into object storage asynchronously. Default:
 
 ### View table information
 
-You can view the information of tables in a specific database using `SHOW PROC "/dbs/<db_id>"`. See [SHOW PROC](../../sql-reference/sql-statements/Administration/SHOW_PROC.md) for more information.
+You can view the information of tables in a specific database using `SHOW PROC "/dbs/<db_id>"`. See [SHOW PROC](../../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROC.md) for more information.
 
 Example:
 
@@ -90,7 +90,7 @@ Shared-data StarRocks clusters support all loading methods provided by StarRocks
 
 ### Query in a shared-data StarRocks cluster
 
-Tables in a shared-data StarRocks cluster support all types of queries provided by StarRocks. See StarRocks [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) for more information.
+Tables in a shared-data StarRocks cluster support all types of queries provided by StarRocks. See StarRocks [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) for more information.
 
 > **NOTE**
 >
diff --git a/docs/en/administration/Data_recovery.md b/docs/en/administration/Data_recovery.md
index 73bcfc49c2c6e8..152549348c45c3 100644
--- a/docs/en/administration/Data_recovery.md
+++ b/docs/en/administration/Data_recovery.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Data Recovery
diff --git a/docs/en/administration/Meta_recovery.md b/docs/en/administration/Meta_recovery.md
index f66c2d981acc0d..ca60e775d4518f 100644
--- a/docs/en/administration/Meta_recovery.md
+++ b/docs/en/administration/Meta_recovery.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Metadata Recovery
diff --git a/docs/en/administration/Profiling.md b/docs/en/administration/Profiling.md
index 66ab31ecafef4c..348bac4743a585 100644
--- a/docs/en/administration/Profiling.md
+++ b/docs/en/administration/Profiling.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Performance Optimization
diff --git a/docs/en/administration/Query_planning.md b/docs/en/administration/Query_planning.md
index 3f369b89e6bef8..ae8b14d2fb1a8c 100644
--- a/docs/en/administration/Query_planning.md
+++ b/docs/en/administration/Query_planning.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Query analysis
@@ -16,7 +16,7 @@ Query performance in StarRocks is determined by query planning and query executi
 
 A query plan provides the DBA with a macro perspective to access query information. A query plan is the key to query performance and a good resource for the DBA to reference. The following code snippet uses `TPCDS query96` as an example to show how to view a query plan.
 
-Use the [EXPLAIN](../sql-reference/sql-statements/Administration/EXPLAIN.md) statement to view the plan of a query.
+Use the [EXPLAIN](../sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN.md) statement to view the plan of a query.
 
 ~~~SQL
 EXPLAIN select  count(*)
@@ -204,9 +204,9 @@ Query hints are directives or comments that explicitly suggest the query optimiz
 
 ### System variable hint
 
-You can use a `SET_VAR` hint to set one or more [system variables](../reference/System_variable.md) in SELECT and SUBMIT TASK statements, and then execute the statements. You can also use a `SET_VAR` hint in the SELECT clause included in other statements, such as CREATE MATERIALIZED VIEW AS SELECT and CREATE VIEW AS SELECT. Note that if the `SET_VAR` hint is used in the SELECT clause of CTE, the `SET_VAR` hint does not take effect even if the statement is executed successfully.
+You can use a `SET_VAR` hint to set one or more [system variables](../sql-reference/System_variable.md) in SELECT and SUBMIT TASK statements, and then execute the statements. You can also use a `SET_VAR` hint in the SELECT clause included in other statements, such as CREATE MATERIALIZED VIEW AS SELECT and CREATE VIEW AS SELECT. Note that if the `SET_VAR` hint is used in the SELECT clause of CTE, the `SET_VAR` hint does not take effect even if the statement is executed successfully.
 
-Compared with [the general usage of system variables](../reference/System_variable.md) which takes effect at the session level, the `SET_VAR` hint takes effect at the statement level and does not impact the entire session.
+Compared with [the general usage of system variables](../sql-reference/System_variable.md) which takes effect at the session level, the `SET_VAR` hint takes effect at the statement level and does not impact the entire session.
 
 #### Syntax
 
@@ -243,9 +243,9 @@ AS SELECT /*+ SET_VAR(query_timeout=500) */ * from dual;
 
 ### User-defined variable hint
 
-You can use a `SET_USER_VARIABLE` hint to set one or more [user-defined variables](../reference/user_defined_variables.md) in the SELECT statements or INSERT statements. If other statements contain a SELECT clause, you can also use the `SET_USER_VARIABLE` hint in that SELECT clause. Other statements can be SELECT statements and INSERT statements, but cannot be CREATE MATERIALIZED VIEW AS SELECT statements and CREATE VIEW AS SELECT statements. Note that if the `SET_USER_VARIABLE` hint is used in the SELECT clause of CTE, the `SET_USER_VARIABLE` hint does not take effect even if the statement is executed successfully. Since v3.2.4, StarRocks supports the user-defined variable hint.
+You can use a `SET_USER_VARIABLE` hint to set one or more [user-defined variables](../sql-reference/user_defined_variables.md) in the SELECT statements or INSERT statements. If other statements contain a SELECT clause, you can also use the `SET_USER_VARIABLE` hint in that SELECT clause. Other statements can be SELECT statements and INSERT statements, but cannot be CREATE MATERIALIZED VIEW AS SELECT statements and CREATE VIEW AS SELECT statements. Note that if the `SET_USER_VARIABLE` hint is used in the SELECT clause of CTE, the `SET_USER_VARIABLE` hint does not take effect even if the statement is executed successfully. Since v3.2.4, StarRocks supports the user-defined variable hint.
 
-Compared with [the general usage of user-defined variables](../reference/user_defined_variables.md) which takes effect at the session level, the `SET_USER_VARIABLE` hint takes effect at the statement level and does not impact the entire session.
+Compared with [the general usage of user-defined variables](../sql-reference/user_defined_variables.md) which takes effect at the session level, the `SET_USER_VARIABLE` hint takes effect at the statement level and does not impact the entire session.
 
 #### Syntax
 
diff --git a/docs/en/administration/administration.mdx b/docs/en/administration/administration.mdx
index ef658b3b7dc142..1c7f53abef88bf 100644
--- a/docs/en/administration/administration.mdx
+++ b/docs/en/administration/administration.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Administration
diff --git a/docs/en/administration/data_migration_tool.md b/docs/en/administration/data_migration_tool.md
index adefdc3f5f1d0d..e628277070ce73 100644
--- a/docs/en/administration/data_migration_tool.md
+++ b/docs/en/administration/data_migration_tool.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Cross-cluster Data Migration Tool
diff --git a/docs/en/administration/management/BE_blacklist.md b/docs/en/administration/management/BE_blacklist.md
index 0839e094488a60..d5d4d9bec537d6 100644
--- a/docs/en/administration/management/BE_blacklist.md
+++ b/docs/en/administration/management/BE_blacklist.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Manage BE Blacklist
@@ -19,7 +19,7 @@ By default, StarRocks can automatically manage the BE Blacklist, adding the BE n
 
 ## Add a BE to the blacklist
 
-You can manually add a BE node to the BE Blacklist using [ADD BACKEND BLACKLIST](../../sql-reference/sql-statements/Administration/ADD_BACKEND_BLACKLIST.md). In this statement, you must specify the ID of the BE node to be blacklisted. You can obtain the BE ID by executing [SHOW BACKENDS](../../sql-reference/sql-statements/Administration/SHOW_BACKENDS.md).
+You can manually add a BE node to the BE Blacklist using [ADD BACKEND BLACKLIST](../../sql-reference/sql-statements/cluster-management/nodes_processes/ADD_BACKEND_BLACKLIST.md). In this statement, you must specify the ID of the BE node to be blacklisted. You can obtain the BE ID by executing [SHOW BACKENDS](../../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKENDS.md).
 
 Example:
 
@@ -36,7 +36,7 @@ ADD BACKEND BLACKLIST 10001;
 
 ## Remove a BE from blacklist
 
-You can manually remove a BE node from the BE Blacklist using [DELETE BACKEND BLACKLIST](../../sql-reference/sql-statements/Administration/DELETE_BACKEND_BLACKLIST.md). In this statement, you must also specify the ID of the BE node.
+You can manually remove a BE node from the BE Blacklist using [DELETE BACKEND BLACKLIST](../../sql-reference/sql-statements/cluster-management/nodes_processes/DELETE_BACKEND_BLACKLIST.md). In this statement, you must also specify the ID of the BE node.
 
 Example:
 
@@ -46,7 +46,7 @@ DELETE BACKEND BLACKLIST 10001;
 
 ## View BE Blacklist
 
-You can view the BE nodes in the BE Blacklist using [SHOW BACKEND BLACKLIST](../../sql-reference/sql-statements/Administration/SHOW_BACKEND_BLACKLIST.md).
+You can view the BE nodes in the BE Blacklist using [SHOW BACKEND BLACKLIST](../../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKEND_BLACKLIST.md).
 
 Example:
 
@@ -77,4 +77,4 @@ You can configure the automatic management of the BE Blacklist using the followi
 - `black_host_history_sec`: The time duration for retaining historical connection failures of BE nodes in the BE Blacklist.
 - `black_host_connect_failures_within_time`: The threshold of connection failures allowed for a blacklisted BE node.
 
-If a BE node is added to the BE Blacklist automatically, StarRocks will assess its connectivity and judge whether it can be removed from the BE Blacklist. Within `black_host_history_sec`, only if a blacklisted BE node has fewer connection failures than the threshold set in `black_host_connect_failures_within_time`, it can be removed from the BE Blacklist.
\ No newline at end of file
+If a BE node is added to the BE Blacklist automatically, StarRocks will assess its connectivity and judge whether it can be removed from the BE Blacklist. Within `black_host_history_sec`, only if a blacklisted BE node has fewer connection failures than the threshold set in `black_host_connect_failures_within_time`, it can be removed from the BE Blacklist.
diff --git a/docs/en/administration/management/BE_configuration.md b/docs/en/administration/management/BE_configuration.md
index fbc8a68c5d2e00..46fac975afaae8 100644
--- a/docs/en/administration/management/BE_configuration.md
+++ b/docs/en/administration/management/BE_configuration.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 import BEConfigMethod from '../../_assets/commonMarkdown/BE_config_method.md'
@@ -4455,7 +4455,7 @@ When this value is set to less than `0`, the system uses the product of its abso
 <!--
 ##### get_txn_status_internal_sec
 
-- Default: 30
+- Default: 10
 - Type: Int
 - Unit: Seconds
 - Is mutable: Yes
diff --git a/docs/en/administration/management/Backup_and_restore.md b/docs/en/administration/management/Backup_and_restore.md
index 422a9e3777523a..13fc0915a6bfac 100644
--- a/docs/en/administration/management/Backup_and_restore.md
+++ b/docs/en/administration/management/Backup_and_restore.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Back up and restore data
@@ -26,7 +26,7 @@ If you have stored a large amount of data in a table, we recommend that you back
 
 ### Create a repository
 
-Before backing up data, you need to create a repository, which is used to store data snapshots in a remote storage system. You can create multiple repositories in a StarRocks cluster. For detailed instructions, see [CREATE REPOSITORY](../../sql-reference/sql-statements/data-definition/backup_restore/CREATE_REPOSITORY.md).
+Before backing up data, you need to create a repository, which is used to store data snapshots in a remote storage system. You can create multiple repositories in a StarRocks cluster. For detailed instructions, see [CREATE REPOSITORY](../../sql-reference/sql-statements/backup_restore/CREATE_REPOSITORY.md).
 
 - Create a repository in HDFS
 
@@ -107,11 +107,11 @@ PROPERTIES(
 >
 > StarRocks supports creating repositories in Google GCS only according to the S3A protocol. Therefore, when you create repositories in Google GCS, you must replace the prefix in the GCS URI you pass as a repository location in `ON LOCATION` with `s3a://`.
 
-After the repository is created, you can check the repository via [SHOW REPOSITORIES](../../sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_REPOSITORIES.md). After restoring data, you can delete the repository in StarRocks using [DROP REPOSITORY](../../sql-reference/sql-statements/data-definition/backup_restore/DROP_REPOSITORY.md). However, data snapshots backed up in the remote storage system cannot be deleted through StarRocks. You need to delete them manually in the remote storage system.
+After the repository is created, you can check the repository via [SHOW REPOSITORIES](../../sql-reference/sql-statements/backup_restore/SHOW_REPOSITORIES.md). After restoring data, you can delete the repository in StarRocks using [DROP REPOSITORY](../../sql-reference/sql-statements/backup_restore/DROP_REPOSITORY.md). However, data snapshots backed up in the remote storage system cannot be deleted through StarRocks. You need to delete them manually in the remote storage system.
 
 ### Back up a data snapshot
 
-After the repository is created, you need to create a data snapshot and back up it in the remote repository. For detailed instructions, see [BACKUP](../../sql-reference/sql-statements/data-definition/backup_restore/BACKUP.md).
+After the repository is created, you need to create a data snapshot and back up it in the remote repository. For detailed instructions, see [BACKUP](../../sql-reference/sql-statements/backup_restore/BACKUP.md).
 
 The following example creates a data snapshot `sr_member_backup` for the table `sr_member` in the database `sr_hub` and backs up it in the repository `test_repo`.
 
@@ -130,7 +130,7 @@ StarRocks supports BACKUP and RESTORE operations on the following levels of gran
 
 :::
 
-BACKUP is an asynchronous operation. You can check the status of a BACKUP job using [SHOW BACKUP](../../sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_BACKUP.md), or cancel a BACKUP job using [CANCEL BACKUP](../../sql-reference/sql-statements/data-definition/backup_restore/CANCEL_BACKUP.md).
+BACKUP is an asynchronous operation. You can check the status of a BACKUP job using [SHOW BACKUP](../../sql-reference/sql-statements/backup_restore/SHOW_BACKUP.md), or cancel a BACKUP job using [CANCEL BACKUP](../../sql-reference/sql-statements/backup_restore/CANCEL_BACKUP.md).
 
 ## Restore or migrate data
 
@@ -142,7 +142,7 @@ To migrate data to another StarRocks cluster, you need to create a repository wi
 
 ### Check the snapshot
 
-Before restoring data, you can check the snapshots in a specified repository using [SHOW SNAPSHOT](../../sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_SNAPSHOT.md).
+Before restoring data, you can check the snapshots in a specified repository using [SHOW SNAPSHOT](../../sql-reference/sql-statements/backup_restore/SHOW_SNAPSHOT.md).
 
 The following example checks the snapshot information in `test_repo`.
 
@@ -158,7 +158,7 @@ mysql> SHOW SNAPSHOT ON test_repo;
 
 ### Restore data via the snapshot
 
-You can use the [RESTORE](../../sql-reference/sql-statements/data-definition/backup_restore/RESTORE.md) statement to restore data snapshots in the remote storage system to the current or other StarRocks clusters.
+You can use the [RESTORE](../../sql-reference/sql-statements/backup_restore/RESTORE.md) statement to restore data snapshots in the remote storage system to the current or other StarRocks clusters.
 
 The following example restores the data snapshot `sr_member_backup` in `test_repo` on the table `sr_member`. It only restores ONE data replica.
 
@@ -181,7 +181,7 @@ StarRocks supports BACKUP and RESTORE operations on the following levels of gran
 
 :::
 
-RESTORE is an asynchronous operation. You can check the status of a RESTORE job using [SHOW RESTORE](../../sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_RESTORE.md), or cancel a RESTORE job using [CANCEL RESTORE](../../sql-reference/sql-statements/data-definition/backup_restore/CANCEL_RESTORE.md).
+RESTORE is an asynchronous operation. You can check the status of a RESTORE job using [SHOW RESTORE](../../sql-reference/sql-statements/backup_restore/SHOW_RESTORE.md), or cancel a RESTORE job using [CANCEL RESTORE](../../sql-reference/sql-statements/backup_restore/CANCEL_RESTORE.md).
 
 ## Configure BACKUP or RESTORE jobs
 
@@ -216,10 +216,10 @@ During BACKUP and RESTORE of a database, StarRocks does as follows:
 
 Any error encountered throughout the RESTORE process will not block the process.
 
-After RESTORE, you can check the status of the materialized view using [SHOW MATERIALIZED VIEWS](../../sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md).
+After RESTORE, you can check the status of the materialized view using [SHOW MATERIALIZED VIEWS](../../sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md).
 
 - If the materialized view is active, it can be used directly.
-- If the materialized view is inactive, it might be because its base tables are not restored. After all the base tables are restored, you can use [ALTER MATERIALIZED VIEW](../../sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md) to re-activate the materialized view.
+- If the materialized view is inactive, it might be because its base tables are not restored. After all the base tables are restored, you can use [ALTER MATERIALIZED VIEW](../../sql-reference/sql-statements/materialized_view/ALTER_MATERIALIZED_VIEW.md) to re-activate the materialized view.
 
 ## Usage notes
 
diff --git a/docs/en/administration/management/FE_configuration.md b/docs/en/administration/management/FE_configuration.md
index 8860c212b62a8c..4853ce7a730ebd 100644
--- a/docs/en/administration/management/FE_configuration.md
+++ b/docs/en/administration/management/FE_configuration.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 import FEConfigMethod from '../../_assets/commonMarkdown/FE_config_method.md'
@@ -20,7 +20,7 @@ After your FE is started, you can run the ADMIN SHOW FRONTEND CONFIG command on
 ADMIN SHOW FRONTEND CONFIG [LIKE "pattern"];
 ```
 
-For detailed description of the returned fields, see [ADMIN SHOW CONFIG](../../sql-reference/sql-statements/Administration/ADMIN_SHOW_CONFIG.md).
+For detailed description of the returned fields, see [ADMIN SHOW CONFIG](../../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SHOW_CONFIG.md).
 
 :::note
 You must have administrator privileges to run cluster administration-related commands.
@@ -30,7 +30,7 @@ You must have administrator privileges to run cluster administration-related com
 
 ### Configure FE dynamic parameters
 
-You can configure or modify the settings of FE dynamic parameters using [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md).
+You can configure or modify the settings of FE dynamic parameters using [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md).
 
 ```SQL
 ADMIN SET FRONTEND CONFIG ("key" = "value");
@@ -2133,7 +2133,7 @@ ADMIN SET FRONTEND CONFIG ("key" = "value");
 - Type: Long
 - Unit: Seconds
 - Is mutable: Yes
-- Description: The maximum time for each Routine Load task within the cluster to consume data. Since v3.1.0, Routine Load job supports a new parameter `task_consume_second` in [job_properties](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md#job_properties). This parameter applies to individual load tasks within a Routine Load job, which is more flexible.
+- Description: The maximum time for each Routine Load task within the cluster to consume data. Since v3.1.0, Routine Load job supports a new parameter `task_consume_second` in [job_properties](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md#job_properties). This parameter applies to individual load tasks within a Routine Load job, which is more flexible.
 - Introduced in: -
 
 ##### routine_load_task_timeout_second
@@ -2142,7 +2142,7 @@ ADMIN SET FRONTEND CONFIG ("key" = "value");
 - Type: Long
 - Unit: Seconds
 - Is mutable: Yes
-- Description: The timeout duration for each Routine Load task within the cluster. Since v3.1.0, Routine Load job supports a new parameter `task_timeout_second` in [job_properties](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md#job_properties). This parameter applies to individual load tasks within a Routine Load job, which is more flexible.
+- Description: The timeout duration for each Routine Load task within the cluster. Since v3.1.0, Routine Load job supports a new parameter `task_timeout_second` in [job_properties](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md#job_properties). This parameter applies to individual load tasks within a Routine Load job, which is more flexible.
 - Introduced in: -
 
 <!--
@@ -2380,7 +2380,7 @@ ADMIN SET FRONTEND CONFIG ("key" = "value");
 - Type: Long
 - Unit: Seconds
 - Is mutable: Yes
-- Description: The longest duration the metadata can be retained after a database, table, or partition is dropped. If this duration expires, the data will be deleted and cannot be recovered through the [RECOVER](../../sql-reference/sql-statements/data-definition/backup_restore/RECOVER.md) command.
+- Description: The longest duration the metadata can be retained after a database, table, or partition is dropped. If this duration expires, the data will be deleted and cannot be recovered through the [RECOVER](../../sql-reference/sql-statements/backup_restore/RECOVER.md) command.
 - Introduced in: -
 
 ##### enable_auto_tablet_distribution
@@ -2473,7 +2473,7 @@ ADMIN SET FRONTEND CONFIG ("key" = "value");
 > **NOTE**
 >
 > - StarRocks shared-data clusters supports this parameter from v3.3.0.
-> - If you need to configure the fast schema evolution for a specific table, such as disabling fast schema evolution for a specific table, you can set the table property [`fast_schema_evolution`](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md#set-fast-schema-evolution) at table creation.
+> - If you need to configure the fast schema evolution for a specific table, such as disabling fast schema evolution for a specific table, you can set the table property [`fast_schema_evolution`](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md#set-fast-schema-evolution) at table creation.
 
 ##### recover_with_empty_tablet
 
@@ -4577,6 +4577,15 @@ ADMIN SET FRONTEND CONFIG ("key" = "value");
 - Description: In each RESTORE operation, the maximum number of download tasks StarRocks assigned to a BE node. When this item is set to less than or equal to 0, no limit is imposed on the task number.
 - Introduced in: v3.1.0
 
+##### enable_colocate_restore
+
+- Default: false
+- Type: Boolean
+- Unit: -
+- Is mutable: Yes
+- Description: Whether to enable Backup and Restore for Colocate Tables. `true` indicates enabling Backup and Restore for Colocate Tables and `false` indicates disabling it.
+- Introduced in: v3.2.10, v3.3.3
+
 <!--
 ##### enable_persistent_index_by_default
 
diff --git a/docs/en/administration/management/Scale_up_down.md b/docs/en/administration/management/Scale_up_down.md
index 302927790183f9..86d7d7543dd456 100644
--- a/docs/en/administration/management/Scale_up_down.md
+++ b/docs/en/administration/management/Scale_up_down.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Scale in and out
diff --git a/docs/en/administration/management/audit_loader.md b/docs/en/administration/management/audit_loader.md
index 28eacab9ceea1e..820785a6ed5922 100644
--- a/docs/en/administration/management/audit_loader.md
+++ b/docs/en/administration/management/audit_loader.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Manage audit logs within StarRocks via AuditLoader
@@ -10,7 +10,7 @@ StarRocks stores its audit logs in the local file **fe/log/fe.audit.log** rather
 
 ## Create a table to store audit logs
 
-Create a database and a table in your StarRocks cluster to store its audit logs. See [CREATE DATABASE](../../sql-reference/sql-statements/data-definition/CREATE_DATABASE.md) and [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) for detailed instructions.
+Create a database and a table in your StarRocks cluster to store its audit logs. See [CREATE DATABASE](../../sql-reference/sql-statements/Database/CREATE_DATABASE.md) and [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) for detailed instructions.
 
 Because the fields of audit logs vary among different StarRocks versions, you must choose among the following examples to create a table that is compatible with your StarRocks.
 
@@ -111,11 +111,11 @@ Execute the following statement along with the path you copied to install AuditL
 INSTALL PLUGIN FROM "<absolute_path_to_package>";
 ```
 
-See [INSTALL PLUGIN](../../sql-reference/sql-statements/Administration/INSTALL_PLUGIN.md) for detailed instructions.
+See [INSTALL PLUGIN](../../sql-reference/sql-statements/cluster-management/plugin/INSTALL_PLUGIN.md) for detailed instructions.
 
 ## Verify the installation and query audit logs
 
-1. You can check if the installation is successful via [SHOW PLUGINS](../../sql-reference/sql-statements/Administration/SHOW_PLUGINS.md).
+1. You can check if the installation is successful via [SHOW PLUGINS](../../sql-reference/sql-statements/cluster-management/plugin/SHOW_PLUGINS.md).
 
     In the following example, the `Status` of the plugin `AuditLoader` is `INSTALLED`,  meaning installation is successful.
 
diff --git a/docs/en/administration/management/configuration.mdx b/docs/en/administration/management/configuration.mdx
index 3553a3d32b59d4..5e926d6fbaec78 100644
--- a/docs/en/administration/management/configuration.mdx
+++ b/docs/en/administration/management/configuration.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Configuration
diff --git a/docs/en/administration/management/enable_fqdn.md b/docs/en/administration/management/enable_fqdn.md
index 389e682fe0f485..c752df2dfc6668 100644
--- a/docs/en/administration/management/enable_fqdn.md
+++ b/docs/en/administration/management/enable_fqdn.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Enable FQDN access
diff --git a/docs/en/administration/management/management.mdx b/docs/en/administration/management/management.mdx
index 284c1ae317a99b..2b5897ca52bd3e 100644
--- a/docs/en/administration/management/management.mdx
+++ b/docs/en/administration/management/management.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Management
diff --git a/docs/en/administration/management/monitor_manage_big_queries.md b/docs/en/administration/management/monitor_manage_big_queries.md
index af6d1577d34ccd..78ca07938553b4 100644
--- a/docs/en/administration/management/monitor_manage_big_queries.md
+++ b/docs/en/administration/management/monitor_manage_big_queries.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Monitor and manage big queries
@@ -107,7 +107,7 @@ You can also decide how to deal with these queued queries by configuring the max
   SET GLOBAL query_queue_pending_timeout_second = 480;
   ```
 
-You can check whether a query is pending using [SHOW PROCESSLIST](../../sql-reference/sql-statements/Administration/SHOW_PROCESSLIST.md).
+You can check whether a query is pending using [SHOW PROCESSLIST](../../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROCESSLIST.md).
 
 ```Plain
 mysql> SHOW PROCESSLIST;
@@ -126,7 +126,7 @@ From v3.0 onwards, StarRocks supports viewing the queries that are currently pro
 
 ### Monitor via MySQL client
 
-1. You can view the queries that are currently processed (`current_queries`) using [SHOW PROC](../../sql-reference/sql-statements/Administration/SHOW_PROC.md).
+1. You can view the queries that are currently processed (`current_queries`) using [SHOW PROC](../../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROC.md).
 
    ```SQL
    SHOW PROC '/current_queries';
@@ -187,7 +187,7 @@ In addition to MySQL client, you can use the FE console for visualized, interact
 
 ### Manually terminate big queries
 
-If any big queries bypass the precautions you have set and threaten the system availability, you can terminate them manually using the corresponding connection ID in the [KILL](../../sql-reference/sql-statements/Administration/KILL.md) statement:
+If any big queries bypass the precautions you have set and threaten the system availability, you can terminate them manually using the corresponding connection ID in the [KILL](../../sql-reference/sql-statements/cluster-management/nodes_processes/KILL.md) statement:
 
 ```SQL
 KILL QUERY <ConnectionId>;
@@ -247,7 +247,7 @@ To enable SQL Blacklist, execute the following statement:
 ADMIN SET FRONTEND CONFIG ("enable_sql_blacklist" = "true");
 ```
 
-Then you can add the regular expression that represents the SQL pattern to SQL Blacklist using [ADD SQLBLACKLIST](../../sql-reference/sql-statements/Administration/ADD_SQLBLACKLIST.md).
+Then you can add the regular expression that represents the SQL pattern to SQL Blacklist using [ADD SQLBLACKLIST](../../sql-reference/sql-statements/cluster-management/sql_blacklist/ADD_SQLBLACKLIST.md).
 
 The following example adds `COUNT(DISTINCT)` to SQL Blacklist:
 
diff --git a/docs/en/administration/management/monitoring/Monitor_and_Alert.md b/docs/en/administration/management/monitoring/Monitor_and_Alert.md
index 9395333391a657..aea761a2939593 100644
--- a/docs/en/administration/management/monitoring/Monitor_and_Alert.md
+++ b/docs/en/administration/management/monitoring/Monitor_and_Alert.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Monitor and Alert with Prometheus and Grafana
diff --git a/docs/en/administration/management/monitoring/metrics-materialized_view.md b/docs/en/administration/management/monitoring/metrics-materialized_view.md
index bbab4d2df2c9cb..504c32f7f8fbe5 100644
--- a/docs/en/administration/management/monitoring/metrics-materialized_view.md
+++ b/docs/en/administration/management/monitoring/metrics-materialized_view.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Monitoring Metrics for Asynchronous Materialized Views
diff --git a/docs/en/administration/management/monitoring/metrics-shared-data.md b/docs/en/administration/management/monitoring/metrics-shared-data.md
index 7239b301ce53f7..dc7837740d0ce0 100644
--- a/docs/en/administration/management/monitoring/metrics-shared-data.md
+++ b/docs/en/administration/management/monitoring/metrics-shared-data.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Monitoring Metrics for Shared-data Clusters
diff --git a/docs/en/administration/management/monitoring/metrics.md b/docs/en/administration/management/monitoring/metrics.md
index 7986d14175acc5..01769922670afa 100644
--- a/docs/en/administration/management/monitoring/metrics.md
+++ b/docs/en/administration/management/monitoring/metrics.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # General Monitoring Metrics
diff --git a/docs/en/administration/management/resource_management/Blacklist.md b/docs/en/administration/management/resource_management/Blacklist.md
index 142730893efaa1..94b287323bbed0 100644
--- a/docs/en/administration/management/resource_management/Blacklist.md
+++ b/docs/en/administration/management/resource_management/Blacklist.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Blacklist Management
diff --git a/docs/en/administration/management/resource_management/Load_balance.md b/docs/en/administration/management/resource_management/Load_balance.md
index 13f680745ee35d..f89954c208057c 100644
--- a/docs/en/administration/management/resource_management/Load_balance.md
+++ b/docs/en/administration/management/resource_management/Load_balance.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Load Balancing
diff --git a/docs/en/administration/management/resource_management/Memory_management.md b/docs/en/administration/management/resource_management/Memory_management.md
index 80b1002eaebdab..919a1c23a08f50 100644
--- a/docs/en/administration/management/resource_management/Memory_management.md
+++ b/docs/en/administration/management/resource_management/Memory_management.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Memory Management
diff --git a/docs/en/administration/management/resource_management/Query_management.md b/docs/en/administration/management/resource_management/Query_management.md
index 860166b6d4d3c2..3f93f0eeb89ed5 100644
--- a/docs/en/administration/management/resource_management/Query_management.md
+++ b/docs/en/administration/management/resource_management/Query_management.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Query Management
diff --git a/docs/en/administration/management/resource_management/Replica.md b/docs/en/administration/management/resource_management/Replica.md
index 995098654cc216..1597e1fade5563 100644
--- a/docs/en/administration/management/resource_management/Replica.md
+++ b/docs/en/administration/management/resource_management/Replica.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Replica management
diff --git a/docs/en/administration/management/resource_management/be_label.md b/docs/en/administration/management/resource_management/be_label.md
index 30f824ea7167c4..920deb6da6245c 100644
--- a/docs/en/administration/management/resource_management/be_label.md
+++ b/docs/en/administration/management/resource_management/be_label.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Add labels on BEs
diff --git a/docs/en/administration/management/resource_management/filemanager.md b/docs/en/administration/management/resource_management/filemanager.md
index 1bd78aedf956fa..fdd37b11e49d98 100644
--- a/docs/en/administration/management/resource_management/filemanager.md
+++ b/docs/en/administration/management/resource_management/filemanager.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # File manager
@@ -14,7 +14,7 @@ With file manager, you can create, view, and delete files, such as the files tha
 
 - Configure the following parameters for each FE.
   - `small_file_dir`: the path in which the uploaded files are stored. The default path is `small_files/`, which is in the runtime directory of the FE. You need to specify this parameter in the **fe.conf** file and then restart the FE to allow the change to take effect.
-  - `max_small_file_size_bytes`: the maximum size of a single file. The default value of this parameter is 1 MB. If the size of a file exceeds the value of this parameter, the file cannot be created. You can specify this parameter by using the [ADMIN SET CONFIG](../../../sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md) statement.
+  - `max_small_file_size_bytes`: the maximum size of a single file. The default value of this parameter is 1 MB. If the size of a file exceeds the value of this parameter, the file cannot be created. You can specify this parameter by using the [ADMIN SET CONFIG](../../../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md) statement.
   - `max_small_file_number`: the maximum number of files that can be created within a cluster. The default value of this parameter is 100. If the number of files that you have created reaches the value of this parameter, you cannot continue creating files. You can specify this parameter by using the ADMIN SET CONFIG statement.
 
 > Note: Increasing the values of the two parameters causes an increase in the memory usage of the FE. Therefore, we recommend that you do not increase the values of the two parameters unless necessary.
@@ -25,15 +25,15 @@ With file manager, you can create, view, and delete files, such as the files tha
 
 ## Create a file
 
-You can execute the CREATE FILE statement to create a file. For more information, see [CREATE FILE](../../../sql-reference/sql-statements/Administration/CREATE_FILE.md). After a file is created, the file is uploaded and persisted in StarRocks.
+You can execute the CREATE FILE statement to create a file. For more information, see [CREATE FILE](../../../sql-reference/sql-statements/cluster-management/file/CREATE_FILE.md). After a file is created, the file is uploaded and persisted in StarRocks.
 
 ## View a file
 
-You can execute the SHOW FILE statement to view the information about a file stored in a database. For more information, see [SHOW FILE](../../../sql-reference/sql-statements/Administration/SHOW_FILE.md).
+You can execute the SHOW FILE statement to view the information about a file stored in a database. For more information, see [SHOW FILE](../../../sql-reference/sql-statements/cluster-management/file/SHOW_FILE.md).
 
 ## Delete a file
 
-You can execute the DROP FILE statement to delete a file. For more information, see [DROP FILE](../../../sql-reference/sql-statements/Administration/DROP_FILE.md).
+You can execute the DROP FILE statement to delete a file. For more information, see [DROP FILE](../../../sql-reference/sql-statements/cluster-management/file/DROP_FILE.md).
 
 ## How an FE and a BE use a file
 
diff --git a/docs/en/administration/management/resource_management/query_queues.md b/docs/en/administration/management/resource_management/query_queues.md
index df13df1d1bef99..9aa1644c14854c 100644
--- a/docs/en/administration/management/resource_management/query_queues.md
+++ b/docs/en/administration/management/resource_management/query_queues.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Query queues
@@ -117,7 +117,7 @@ You can view information related to query queues using the following methods.
 
 ### SHOW PROC
 
-You can check the number of running queries, and memory and CPU usages in BE nodes using [SHOW PROC](../../../sql-reference/sql-statements/Administration/SHOW_PROC.md):
+You can check the number of running queries, and memory and CPU usages in BE nodes using [SHOW PROC](../../../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROC.md):
 
 ```Plain
 mysql> SHOW PROC '/backends'\G
@@ -130,7 +130,7 @@ mysql> SHOW PROC '/backends'\G
 
 ### SHOW PROCESSLIST
 
-You can check if a query is in a queue (when `IsPending` is `true`) using [SHOW PROCESSLIST](../../../sql-reference/sql-statements/Administration/SHOW_PROCESSLIST.md):
+You can check if a query is in a queue (when `IsPending` is `true`) using [SHOW PROCESSLIST](../../../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROCESSLIST.md):
 
 ```Plain
 mysql> SHOW PROCESSLIST;
diff --git a/docs/en/administration/management/resource_management/resource_group.md b/docs/en/administration/management/resource_management/resource_group.md
index 877a7edae9b4d5..17f2606d07893c 100644
--- a/docs/en/administration/management/resource_management/resource_group.md
+++ b/docs/en/administration/management/resource_management/resource_group.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Resource group
@@ -382,7 +382,7 @@ The following FE metrics only provide statistics within the current FE node:
 
 ### View resource group usage information
 
-From v3.1.4 onwards, StarRocks supports the SQL statement [SHOW USAGE RESOURCE GROUPS](../../../sql-reference/sql-statements/Administration/SHOW_USAGE_RESOURCE_GROUPS.md), which is used to display usage information for each resource group across BEs. The descriptions of each field are as follows:
+From v3.1.4 onwards, StarRocks supports the SQL statement [SHOW USAGE RESOURCE GROUPS](../../../sql-reference/sql-statements/cluster-management/resource_group/SHOW_USAGE_RESOURCE_GROUPS.md), which is used to display usage information for each resource group across BEs. The descriptions of each field are as follows:
 
 - `Name`: The name of the resource group.
 - `Id`: The ID of the resource group.
diff --git a/docs/en/administration/management/resource_management/resource_management.mdx b/docs/en/administration/management/resource_management/resource_management.mdx
index d5807edd3c2478..7599f535206d84 100644
--- a/docs/en/administration/management/resource_management/resource_management.mdx
+++ b/docs/en/administration/management/resource_management/resource_management.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Resource Management
diff --git a/docs/en/administration/management/resource_management/spill_to_disk.md b/docs/en/administration/management/resource_management/spill_to_disk.md
index 22d19fab2fb559..8580b140e731c4 100644
--- a/docs/en/administration/management/resource_management/spill_to_disk.md
+++ b/docs/en/administration/management/resource_management/spill_to_disk.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Spill to disk
@@ -61,7 +61,7 @@ Follow these steps to enable intermediate result spilling:
 From v3.3.0 onwards, StarRocks supports spilling intermediate results to object storage.
 
 :::tip
-Before enabling spilling to object storage, you must create a storage volume to define the object storage you want to use. For detailed instruction on creating a storage volume, see [CREATE STORAGE VOLUME](../../../sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md).
+Before enabling spilling to object storage, you must create a storage volume to define the object storage you want to use. For detailed instruction on creating a storage volume, see [CREATE STORAGE VOLUME](../../../sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md).
 :::
 
 After you have enabled spilling in the previous step, you can further set these system variables to allow the intermediate results to be spilled to object storage:
diff --git a/docs/en/administration/management/timezone.md b/docs/en/administration/management/timezone.md
index 4dfea2ccfe805e..7d23bf617d07f7 100644
--- a/docs/en/administration/management/timezone.md
+++ b/docs/en/administration/management/timezone.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Configure a time zone
diff --git a/docs/en/administration/query_profile_details.md b/docs/en/administration/query_profile_details.md
index 78e7c5d3a76b27..c800a3bcd8ca11 100644
--- a/docs/en/administration/query_profile_details.md
+++ b/docs/en/administration/query_profile_details.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Query Profile Structure and Metrics
diff --git a/docs/en/administration/query_profile_overview.md b/docs/en/administration/query_profile_overview.md
index b6cc9b263063ed..3b78e6703d2927 100644
--- a/docs/en/administration/query_profile_overview.md
+++ b/docs/en/administration/query_profile_overview.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Query Profile Overview
diff --git a/docs/en/administration/query_profile_text_based_analysis.md b/docs/en/administration/query_profile_text_based_analysis.md
index 8593912c6b1e9f..9e3e3b471c97f0 100644
--- a/docs/en/administration/query_profile_text_based_analysis.md
+++ b/docs/en/administration/query_profile_text_based_analysis.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Text-based Query Profile Visualized Analysis
@@ -8,7 +8,7 @@ This topic introduces how to obtain and analyze text-based Query Profiles throug
 
 ## Analyze Profiles of Existing Queries Using ANALYZE PROFILE
 
-To analyze the text-based Profile of an existing (historical or running) query in you cluster, you first need to use the [SHOW PROFILELIST](../sql-reference/sql-statements/Administration/SHOW_PROFILELIST.md) statement to obtain a summary of the query. This command lists all queries that have finished successfully, failed with error, and those are still running (for more than 10 seconds and not yet finished). Through this statement, you can get the corresponding Query ID for subsequent analysis. The syntax is as follows:
+To analyze the text-based Profile of an existing (historical or running) query in you cluster, you first need to use the [SHOW PROFILELIST](../sql-reference/sql-statements/cluster-management/plan_profile/SHOW_PROFILELIST.md) statement to obtain a summary of the query. This command lists all queries that have finished successfully, failed with error, and those are still running (for more than 10 seconds and not yet finished). Through this statement, you can get the corresponding Query ID for subsequent analysis. The syntax is as follows:
 
 ```SQL
 SHOW PROFILELIST [LIMIT <num>];
@@ -35,7 +35,7 @@ Output:
 +--------------------------------------+---------------------+-------+----------+-----------------------------------------------------------------------------------------------------------------------------------+
 ```
 
-Once you have the Query ID, you can proceed with Query Profile analysis using the [ANALYZE PROFILE](../sql-reference/sql-statements/Administration/ANALYZE_PROFILE.md) statement. The syntax is as follows:
+Once you have the Query ID, you can proceed with Query Profile analysis using the [ANALYZE PROFILE](../sql-reference/sql-statements/cluster-management/plan_profile/ANALYZE_PROFILE.md) statement. The syntax is as follows:
 
 ```SQL
 ANALYZE PROFILE FROM '<Query_ID>' [, <Node_ID> [, ...] ]
@@ -87,7 +87,7 @@ Example:
 
 ## Simulate a query for Profile Analysis Using EXPLAIN ANALYZE
 
-StarRocks provides the [EXPLAIN ANALYZE](../sql-reference/sql-statements/Administration/EXPLAIN_ANALYZE.md) statement, allowing you to simulate and analyze the profile of a query directly. The syntax is as follows:
+StarRocks provides the [EXPLAIN ANALYZE](../sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN_ANALYZE.md) statement, allowing you to simulate and analyze the profile of a query directly. The syntax is as follows:
 
 ```SQL
 EXPLAIN ANALYZE <sql_statement>
diff --git a/docs/en/administration/stargo.md b/docs/en/administration/stargo.md
index 49dca1deea0885..1c4b52829aa2b1 100644
--- a/docs/en/administration/stargo.md
+++ b/docs/en/administration/stargo.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Deploy and Manage StarRocks with StarGo
diff --git a/docs/en/administration/user_privs/Authentication.md b/docs/en/administration/user_privs/Authentication.md
index 496add9c62694d..614965fb1d98f7 100644
--- a/docs/en/administration/user_privs/Authentication.md
+++ b/docs/en/administration/user_privs/Authentication.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Authentication methods
diff --git a/docs/en/administration/user_privs/User_privilege.md b/docs/en/administration/user_privs/User_privilege.md
index 16afb125555561..bdfee3a854b644 100644
--- a/docs/en/administration/user_privs/User_privilege.md
+++ b/docs/en/administration/user_privs/User_privilege.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Manage user privileges
diff --git a/docs/en/administration/user_privs/privilege_faq.md b/docs/en/administration/user_privs/privilege_faq.md
index 6dc3da485d2311..88d5a8bd11dd5c 100644
--- a/docs/en/administration/user_privs/privilege_faq.md
+++ b/docs/en/administration/user_privs/privilege_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Privilege FAQ
diff --git a/docs/en/administration/user_privs/privilege_item.md b/docs/en/administration/user_privs/privilege_item.md
index a0cb9c94b9b2ab..e174799ce3400d 100644
--- a/docs/en/administration/user_privs/privilege_item.md
+++ b/docs/en/administration/user_privs/privilege_item.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Privileges supported by StarRocks
diff --git a/docs/en/administration/user_privs/privilege_overview.md b/docs/en/administration/user_privs/privilege_overview.md
index 213c384d8f3e0f..898d450d5248fa 100644
--- a/docs/en/administration/user_privs/privilege_overview.md
+++ b/docs/en/administration/user_privs/privilege_overview.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Overview of privileges
diff --git a/docs/en/administration/user_privs/ranger_plugin.md b/docs/en/administration/user_privs/ranger_plugin.md
index f592523d24d5ed..6158a00874b60e 100644
--- a/docs/en/administration/user_privs/ranger_plugin.md
+++ b/docs/en/administration/user_privs/ranger_plugin.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Manage permissions with Apache Ranger
diff --git a/docs/en/benchmarking/SSB_Benchmarking.md b/docs/en/benchmarking/SSB_Benchmarking.md
index 5094b2bd3e9c5e..e64c92e4b032d1 100644
--- a/docs/en/benchmarking/SSB_Benchmarking.md
+++ b/docs/en/benchmarking/SSB_Benchmarking.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # SSB Flat-table Benchmarking
diff --git a/docs/en/benchmarking/TPC-H_Benchmarking.md b/docs/en/benchmarking/TPC-H_Benchmarking.md
index 2c07f4b60d4bc0..119a54af5dae15 100644
--- a/docs/en/benchmarking/TPC-H_Benchmarking.md
+++ b/docs/en/benchmarking/TPC-H_Benchmarking.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # TPC-H Benchmark
diff --git a/docs/en/benchmarking/TPC_DS_Benchmark.md b/docs/en/benchmarking/TPC_DS_Benchmark.md
index 257dfe1754f904..9ee2199bff4983 100644
--- a/docs/en/benchmarking/TPC_DS_Benchmark.md
+++ b/docs/en/benchmarking/TPC_DS_Benchmark.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # TPC-DS Benchmarking
diff --git a/docs/en/benchmarking/benchmarking.mdx b/docs/en/benchmarking/benchmarking.mdx
index 61ca589a908a6f..c4f11c856ed70b 100644
--- a/docs/en/benchmarking/benchmarking.mdx
+++ b/docs/en/benchmarking/benchmarking.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Benchmarks
diff --git a/docs/en/benchmarking/tpc_ds_99_sql.md b/docs/en/benchmarking/tpc_ds_99_sql.md
index e0c286ee3e122f..d2c588bff736d5 100644
--- a/docs/en/benchmarking/tpc_ds_99_sql.md
+++ b/docs/en/benchmarking/tpc_ds_99_sql.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # TPC-DS test SQL
diff --git a/docs/en/cover_pages/batch_loading_integration.mdx b/docs/en/cover_pages/batch_loading_integration.mdx
index cff4d123ec1c84..826e9d32fa7711 100644
--- a/docs/en/cover_pages/batch_loading_integration.mdx
+++ b/docs/en/cover_pages/batch_loading_integration.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/en/cover_pages/bi_tools.mdx b/docs/en/cover_pages/bi_tools.mdx
index 919fd01bdc70c7..3e89471a2095f6 100644
--- a/docs/en/cover_pages/bi_tools.mdx
+++ b/docs/en/cover_pages/bi_tools.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Business Intelligence
diff --git a/docs/en/cover_pages/csp_auth.mdx b/docs/en/cover_pages/csp_auth.mdx
index 3f16c1f22f2d29..e82f0de84b861d 100644
--- a/docs/en/cover_pages/csp_auth.mdx
+++ b/docs/en/cover_pages/csp_auth.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # CSP authentication
diff --git a/docs/en/cover_pages/data_cache.mdx b/docs/en/cover_pages/data_cache.mdx
index 097067f95aeda4..8e94dc650320d8 100644
--- a/docs/en/cover_pages/data_cache.mdx
+++ b/docs/en/cover_pages/data_cache.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Data Cache
diff --git a/docs/en/cover_pages/deployment_preparation.mdx b/docs/en/cover_pages/deployment_preparation.mdx
index b1e706541920a0..3906b1bb4e4fd4 100644
--- a/docs/en/cover_pages/deployment_preparation.mdx
+++ b/docs/en/cover_pages/deployment_preparation.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/en/cover_pages/developers.mdx b/docs/en/cover_pages/developers.mdx
index b1e706541920a0..3906b1bb4e4fd4 100644
--- a/docs/en/cover_pages/developers.mdx
+++ b/docs/en/cover_pages/developers.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/en/cover_pages/distinct_values.mdx b/docs/en/cover_pages/distinct_values.mdx
index b1e706541920a0..3906b1bb4e4fd4 100644
--- a/docs/en/cover_pages/distinct_values.mdx
+++ b/docs/en/cover_pages/distinct_values.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/en/cover_pages/functions_binary.mdx b/docs/en/cover_pages/functions_binary.mdx
deleted file mode 100644
index b1e706541920a0..00000000000000
--- a/docs/en/cover_pages/functions_binary.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/cover_pages/functions_conditional.mdx b/docs/en/cover_pages/functions_conditional.mdx
deleted file mode 100644
index b1e706541920a0..00000000000000
--- a/docs/en/cover_pages/functions_conditional.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/cover_pages/functions_crypto.mdx b/docs/en/cover_pages/functions_crypto.mdx
deleted file mode 100644
index b1e706541920a0..00000000000000
--- a/docs/en/cover_pages/functions_crypto.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/cover_pages/functions_date.mdx b/docs/en/cover_pages/functions_date.mdx
deleted file mode 100644
index b1e706541920a0..00000000000000
--- a/docs/en/cover_pages/functions_date.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/cover_pages/functions_geo.mdx b/docs/en/cover_pages/functions_geo.mdx
deleted file mode 100644
index b1e706541920a0..00000000000000
--- a/docs/en/cover_pages/functions_geo.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/cover_pages/functions_json_constructor.mdx b/docs/en/cover_pages/functions_json_constructor.mdx
deleted file mode 100644
index b1e706541920a0..00000000000000
--- a/docs/en/cover_pages/functions_json_constructor.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/cover_pages/functions_json_query.mdx b/docs/en/cover_pages/functions_json_query.mdx
deleted file mode 100644
index b1e706541920a0..00000000000000
--- a/docs/en/cover_pages/functions_json_query.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/cover_pages/functions_like.mdx b/docs/en/cover_pages/functions_like.mdx
deleted file mode 100644
index b1e706541920a0..00000000000000
--- a/docs/en/cover_pages/functions_like.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/cover_pages/functions_math.mdx b/docs/en/cover_pages/functions_math.mdx
deleted file mode 100644
index b1e706541920a0..00000000000000
--- a/docs/en/cover_pages/functions_math.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/cover_pages/functions_percentile.mdx b/docs/en/cover_pages/functions_percentile.mdx
deleted file mode 100644
index b1e706541920a0..00000000000000
--- a/docs/en/cover_pages/functions_percentile.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/cover_pages/functions_scalar.mdx b/docs/en/cover_pages/functions_scalar.mdx
deleted file mode 100644
index b1e706541920a0..00000000000000
--- a/docs/en/cover_pages/functions_scalar.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/cover_pages/functions_string.mdx b/docs/en/cover_pages/functions_string.mdx
deleted file mode 100644
index b1e706541920a0..00000000000000
--- a/docs/en/cover_pages/functions_string.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/cover_pages/functions_struct.mdx b/docs/en/cover_pages/functions_struct.mdx
deleted file mode 100644
index b1e706541920a0..00000000000000
--- a/docs/en/cover_pages/functions_struct.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/cover_pages/functions_table.mdx b/docs/en/cover_pages/functions_table.mdx
deleted file mode 100644
index b1e706541920a0..00000000000000
--- a/docs/en/cover_pages/functions_table.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/cover_pages/functions_utility.mdx b/docs/en/cover_pages/functions_utility.mdx
deleted file mode 100644
index b1e706541920a0..00000000000000
--- a/docs/en/cover_pages/functions_utility.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/cover_pages/ide_tools.mdx b/docs/en/cover_pages/ide_tools.mdx
index 53472f1f185899..0155e99e5cab80 100644
--- a/docs/en/cover_pages/ide_tools.mdx
+++ b/docs/en/cover_pages/ide_tools.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # SQL IDE tools
diff --git a/docs/en/cover_pages/loading_kafka.mdx b/docs/en/cover_pages/loading_kafka.mdx
index b1e706541920a0..3906b1bb4e4fd4 100644
--- a/docs/en/cover_pages/loading_kafka.mdx
+++ b/docs/en/cover_pages/loading_kafka.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/en/cover_pages/loading_spark.mdx b/docs/en/cover_pages/loading_spark.mdx
index b1e706541920a0..3906b1bb4e4fd4 100644
--- a/docs/en/cover_pages/loading_spark.mdx
+++ b/docs/en/cover_pages/loading_spark.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/en/cover_pages/manage_deployment.mdx b/docs/en/cover_pages/manage_deployment.mdx
index b1e706541920a0..3906b1bb4e4fd4 100644
--- a/docs/en/cover_pages/manage_deployment.mdx
+++ b/docs/en/cover_pages/manage_deployment.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/en/cover_pages/mv_use_cases.mdx b/docs/en/cover_pages/mv_use_cases.mdx
index b1e706541920a0..3906b1bb4e4fd4 100644
--- a/docs/en/cover_pages/mv_use_cases.mdx
+++ b/docs/en/cover_pages/mv_use_cases.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/en/cover_pages/performance_tuning.mdx b/docs/en/cover_pages/performance_tuning.mdx
index b1e706541920a0..3906b1bb4e4fd4 100644
--- a/docs/en/cover_pages/performance_tuning.mdx
+++ b/docs/en/cover_pages/performance_tuning.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/en/cover_pages/query_acceleration.mdx b/docs/en/cover_pages/query_acceleration.mdx
index b1e706541920a0..3906b1bb4e4fd4 100644
--- a/docs/en/cover_pages/query_acceleration.mdx
+++ b/docs/en/cover_pages/query_acceleration.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/en/cover_pages/shared_nothing_deployment.mdx b/docs/en/cover_pages/shared_nothing_deployment.mdx
index b1e706541920a0..3906b1bb4e4fd4 100644
--- a/docs/en/cover_pages/shared_nothing_deployment.mdx
+++ b/docs/en/cover_pages/shared_nothing_deployment.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/en/data_source/External_table.md b/docs/en/data_source/External_table.md
index 83e59b3403bb63..823579e28f7dd0 100644
--- a/docs/en/data_source/External_table.md
+++ b/docs/en/data_source/External_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # External table
@@ -591,7 +591,7 @@ SHOW RESOURCES;
 DROP RESOURCE "hive0";
 ~~~
 
-You can modify `hive.metastore.uris` of a Hive resource in StarRocks 2.3 and later versions. For more information, see [ALTER RESOURCE](../sql-reference/sql-statements/data-definition/ALTER_RESOURCE.md).
+You can modify `hive.metastore.uris` of a Hive resource in StarRocks 2.3 and later versions. For more information, see [ALTER RESOURCE](../sql-reference/sql-statements/Resource/ALTER_RESOURCE.md).
 
 ### Create a database
 
@@ -800,7 +800,7 @@ The following table describes the related parameters.
 | iceberg.catalog.type | The catalog type of the resource. Both Hive catalog and custom catalog are supported. If you specify a Hive catalog, set the value to `HIVE`. If you specify a custom catalog, set the value to `CUSTOM`. |
 | iceberg.catalog-impl   | The fully qualified class name of the custom catalog. FEs search for the catalog based on this name. If the catalog contains custom configuration items, you must add them to the `PROPERTIES` parameter as key-value pairs when you create an Iceberg external table. |
 
-You can modify `hive.metastore.uris` and `iceberg.catalog-impl`of a Iceberg resource in StarRocks 2.3 and later versions. For more information, see [ALTER RESOURCE](../sql-reference/sql-statements/data-definition/ALTER_RESOURCE.md).
+You can modify `hive.metastore.uris` and `iceberg.catalog-impl`of a Iceberg resource in StarRocks 2.3 and later versions. For more information, see [ALTER RESOURCE](../sql-reference/sql-statements/Resource/ALTER_RESOURCE.md).
 
 ##### View Iceberg resources
 
@@ -945,7 +945,7 @@ The following table describes the parameters.
 | type                | The type of the Hudi resource. Set the vaue to hudi.         |
 | hive.metastore.uris | The Thrift URI of the Hive metastore to which the Hudi resource connects. After connecting the Hudi resource to a Hive metastore, you can create and manage Hudi tables by using Hive. The Thrift URI is in the `<IP address of the Hive metastore>:<Port number of the Hive metastore>` format. The default port number is 9083. |
 
-From v2.3 onwards, StarRocks allows changing the `hive.metastore.uris` value of a Hudi resource. For more information, see [ALTER RESOURCE](../sql-reference/sql-statements/data-definition/ALTER_RESOURCE.md).
+From v2.3 onwards, StarRocks allows changing the `hive.metastore.uris` value of a Hudi resource. For more information, see [ALTER RESOURCE](../sql-reference/sql-statements/Resource/ALTER_RESOURCE.md).
 
 ##### View Hudi resources
 
diff --git a/docs/en/data_source/catalog/catalog_intro.mdx b/docs/en/data_source/catalog/catalog_intro.mdx
index eda574abf3a0b2..1849e188a4b00f 100644
--- a/docs/en/data_source/catalog/catalog_intro.mdx
+++ b/docs/en/data_source/catalog/catalog_intro.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 keywords: ['catalog']
 ---
 
diff --git a/docs/en/data_source/catalog/catalog_overview.md b/docs/en/data_source/catalog/catalog_overview.md
index 5598f1aa2a7ce6..32c9ed1a448a4c 100644
--- a/docs/en/data_source/catalog/catalog_overview.md
+++ b/docs/en/data_source/catalog/catalog_overview.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Overview
@@ -39,7 +39,7 @@ Currently, StarRocks provides two types of catalogs: internal catalog and extern
 
 ## Access catalog
 
-You can use the [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) statement to switch to a specified catalog in the current session. Then, you can query data by using that catalog.
+You can use the [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) statement to switch to a specified catalog in the current session. Then, you can query data by using that catalog.
 
 ## Query data
 
diff --git a/docs/en/data_source/catalog/default_catalog.md b/docs/en/data_source/catalog/default_catalog.md
index 5cb560614adb09..070d14946f4ac3 100644
--- a/docs/en/data_source/catalog/default_catalog.md
+++ b/docs/en/data_source/catalog/default_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Default catalog
@@ -14,7 +14,7 @@ StarRocks 2.3 and later provide an internal catalog to manage the internal data
    - If you use the MySQL client to connect the StarRocks cluster, you go to `default_catalog` by default after connecting.
    - If you use JDBC to connect the StarRocks cluster, you can go directly to the destination database in the default catalog by specifying `default_catalog.db_name` when connecting.
 
-2. (Optional) Use [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) to view databases:
+2. (Optional) Use [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) to view databases:
 
       ```SQL
       SHOW DATABASES;
@@ -26,25 +26,25 @@ StarRocks 2.3 and later provide an internal catalog to manage the internal data
       SHOW DATABASES FROM <catalog_name>;
       ```
 
-3. (Optional) Use [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) to switch to the destination catalog in the current session:
+3. (Optional) Use [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) to switch to the destination catalog in the current session:
 
     ```SQL
     SET CATALOG <catalog_name>;
     ```
 
-    Then, use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to specify the active database in the current session:
+    Then, use [USE](../../sql-reference/sql-statements/Database/USE.md) to specify the active database in the current session:
 
     ```SQL
     USE <db_name>;
     ```
 
-    Or, you can use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to directly go to the active database in the destination catalog:
+    Or, you can use [USE](../../sql-reference/sql-statements/Database/USE.md) to directly go to the active database in the destination catalog:
 
     ```SQL
     USE <catalog_name>.<db_name>;
     ```
 
-4. Use [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) to query internal data:
+4. Use [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query internal data:
 
       ```SQL
       SELECT * FROM <table_name>;
diff --git a/docs/en/data_source/catalog/deltalake_catalog.md b/docs/en/data_source/catalog/deltalake_catalog.md
index 1a312eb462e4d3..73035fa2d6915b 100644
--- a/docs/en/data_source/catalog/deltalake_catalog.md
+++ b/docs/en/data_source/catalog/deltalake_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 5
 ---
 
@@ -7,7 +7,7 @@ toc_max_heading_level: 5
 
 A Delta Lake catalog is a kind of external catalog that enables you to query data from Delta Lake without ingestion.
 
-Also, you can directly transform and load data from Delta Lake by using [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) based on Delta Lake catalogs. StarRocks supports Delta Lake catalogs from v2.5 onwards.
+Also, you can directly transform and load data from Delta Lake by using [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) based on Delta Lake catalogs. StarRocks supports Delta Lake catalogs from v2.5 onwards.
 
 To ensure successful SQL workloads on your Delta Lake cluster, your StarRocks cluster must be able to access the storage system and metastore of your Delta Lake cluster. StarRocks supports the following storage systems and metastores:
 
@@ -761,13 +761,13 @@ PROPERTIES
 
 ## View Delta Lake catalogs
 
-You can use [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
+You can use [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a Delta Lake catalog named `deltalake_catalog_glue`:
+You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a Delta Lake catalog named `deltalake_catalog_glue`:
 
 ```SQL
 SHOW CREATE CATALOG deltalake_catalog_glue;
@@ -777,7 +777,7 @@ SHOW CREATE CATALOG deltalake_catalog_glue;
 
 You can use one of the following methods to switch to a Delta Lake catalog and a database in it:
 
-- Use [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) to specify a Delta Lake catalog in the current session, and then use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to specify an active database:
+- Use [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) to specify a Delta Lake catalog in the current session, and then use [USE](../../sql-reference/sql-statements/Database/USE.md) to specify an active database:
 
   ```SQL
   -- Switch to a specified catalog in the current session:
@@ -786,7 +786,7 @@ You can use one of the following methods to switch to a Delta Lake catalog and a
   USE <db_name>
   ```
 
-- Directly use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to switch to a Delta Lake catalog and a database in it:
+- Directly use [USE](../../sql-reference/sql-statements/Database/USE.md) to switch to a Delta Lake catalog and a database in it:
 
   ```SQL
   USE <catalog_name>.<db_name>
@@ -794,7 +794,7 @@ You can use one of the following methods to switch to a Delta Lake catalog and a
 
 ## Drop a Delta Lake catalog
 
-You can use [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) to drop an external catalog.
+You can use [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) to drop an external catalog.
 
 The following example drops a Delta Lake catalog named `deltalake_catalog_glue`:
 
@@ -820,7 +820,7 @@ You can use one of the following syntaxes to view the schema of a Delta Lake tab
 
 ## Query a Delta Lake table
 
-1. Use [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) to view the databases in your Delta Lake cluster:
+1. Use [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) to view the databases in your Delta Lake cluster:
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>
@@ -828,7 +828,7 @@ You can use one of the following syntaxes to view the schema of a Delta Lake tab
 
 2. [Switch to a Delta Lake Catalog and a database in it](#switch-to-a-delta-lake-catalog-and-a-database-in-it).
 
-3. Use [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the destination table in the specified database:
+3. Use [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the destination table in the specified database:
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10
diff --git a/docs/en/data_source/catalog/elasticsearch_catalog.md b/docs/en/data_source/catalog/elasticsearch_catalog.md
index 54dfe53f0afe2d..7b133bbb62bae5 100644
--- a/docs/en/data_source/catalog/elasticsearch_catalog.md
+++ b/docs/en/data_source/catalog/elasticsearch_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 ---
 
diff --git a/docs/en/data_source/catalog/hive_catalog.md b/docs/en/data_source/catalog/hive_catalog.md
index 1222500f3abd6a..d7e44731b6c74e 100644
--- a/docs/en/data_source/catalog/hive_catalog.md
+++ b/docs/en/data_source/catalog/hive_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 5
 ---
 
@@ -8,8 +8,8 @@ toc_max_heading_level: 5
 A Hive catalog is a kind of external catalog that is supported by StarRocks from v2.4 onwards. Within Hive catalogs, you can:
 
 - Directly query data stored in Hive without the need to manually create tables.
-- Use [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) or asynchronous materialized views (which are supported from v2.5 onwards) to process data stored in Hive and load the data into StarRocks.
-- Perform operations on StarRocks to create or drop Hive databases and tables, or sink data from StarRocks tables to Parquet-formatted (supported from v3.2 onwards) and ORC- or Textfile-formatted (supported from v3.3 onwards) Hive tables by using [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md).
+- Use [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) or asynchronous materialized views (which are supported from v2.5 onwards) to process data stored in Hive and load the data into StarRocks.
+- Perform operations on StarRocks to create or drop Hive databases and tables, or sink data from StarRocks tables to Parquet-formatted (supported from v3.2 onwards) and ORC- or Textfile-formatted (supported from v3.3 onwards) Hive tables by using [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md).
 
 To ensure successful SQL workloads on your Hive cluster, your StarRocks cluster must be able to access the storage system and metastore of your Hive cluster. StarRocks supports the following storage systems and metastores:
 
@@ -38,7 +38,7 @@ To ensure successful SQL workloads on your Hive cluster, your StarRocks cluster
   - Parquet and ORC files support the following compression formats: NO_COMPRESSION, SNAPPY, LZ4, ZSTD, and GZIP.
   - Textfile files support the NO_COMPRESSION compression format.
 
-  You can use the session variable [`connector_sink_compression_codec`](../../reference/System_variable.md#connector_sink_compression_codec) to specify the compression algorithm used for sinking data to Hive tables.
+  You can use the session variable [`connector_sink_compression_codec`](../../sql-reference/System_variable.md#connector_sink_compression_codec) to specify the compression algorithm used for sinking data to Hive tables.
 
 ## Integration preparations
 
@@ -795,13 +795,13 @@ PROPERTIES
 
 ## View Hive catalogs
 
-You can use [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
+You can use [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a Hive catalog named `hive_catalog_glue`:
+You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a Hive catalog named `hive_catalog_glue`:
 
 ```SQL
 SHOW CREATE CATALOG hive_catalog_glue;
@@ -811,7 +811,7 @@ SHOW CREATE CATALOG hive_catalog_glue;
 
 You can use one of the following methods to switch to a Hive catalog and a database in it:
 
-- Use [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) to specify a Hive catalog in the current session, and then use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to specify an active database:
+- Use [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) to specify a Hive catalog in the current session, and then use [USE](../../sql-reference/sql-statements/Database/USE.md) to specify an active database:
 
   ```SQL
   -- Switch to a specified catalog in the current session:
@@ -820,7 +820,7 @@ You can use one of the following methods to switch to a Hive catalog and a datab
   USE <db_name>
   ```
 
-- Directly use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to switch to a Hive catalog and a database in it:
+- Directly use [USE](../../sql-reference/sql-statements/Database/USE.md) to switch to a Hive catalog and a database in it:
 
   ```SQL
   USE <catalog_name>.<db_name>
@@ -828,7 +828,7 @@ You can use one of the following methods to switch to a Hive catalog and a datab
 
 ## Drop a Hive catalog
 
-You can use [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) to drop an external catalog.
+You can use [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) to drop an external catalog.
 
 The following example drops a Hive catalog named `hive_catalog_glue`:
 
@@ -854,7 +854,7 @@ You can use one of the following syntaxes to view the schema of a Hive table:
 
 ## Query a Hive table
 
-1. Use [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) to view the databases in your Hive cluster:
+1. Use [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) to view the databases in your Hive cluster:
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>
@@ -862,7 +862,7 @@ You can use one of the following syntaxes to view the schema of a Hive table:
 
 2. [Switch to a Hive Catalog and a database in it](#switch-to-a-hive-catalog-and-a-database-in-it).
 
-3. Use [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the destination table in the specified database:
+3. Use [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the destination table in the specified database:
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10
@@ -899,7 +899,7 @@ GRANT SELECT ON ALL TABLES IN ALL DATABASES TO ROLE hive_role_table;
 
 ## Create a Hive database
 
-Similar to the internal catalog of StarRocks, if you have the [CREATE DATABASE](../../administration/user_privs/privilege_item.md#catalog) privilege on a Hive catalog, you can use the [CREATE DATABASE](../../sql-reference/sql-statements/data-definition/CREATE_DATABASE.md) statement to create a database in that Hive catalog. This feature is supported from v3.2 onwards.
+Similar to the internal catalog of StarRocks, if you have the [CREATE DATABASE](../../administration/user_privs/privilege_item.md#catalog) privilege on a Hive catalog, you can use the [CREATE DATABASE](../../sql-reference/sql-statements/Database/CREATE_DATABASE.md) statement to create a database in that Hive catalog. This feature is supported from v3.2 onwards.
 
 :::note
 
@@ -932,7 +932,7 @@ The `prefix` varies based on the storage system you use:
 
 ## Drop a Hive database
 
-Similar to the internal databases of StarRocks, if you have the [DROP](../../administration/user_privs/privilege_item.md#database) privilege on a Hive database, you can use the [DROP DATABASE](../../sql-reference/sql-statements/data-definition/DROP_DATABASE.md) statement to drop that Hive database. This feature is supported from v3.2 onwards. You can only drop empty databases.
+Similar to the internal databases of StarRocks, if you have the [DROP](../../administration/user_privs/privilege_item.md#database) privilege on a Hive database, you can use the [DROP DATABASE](../../sql-reference/sql-statements/Database/DROP_DATABASE.md) statement to drop that Hive database. This feature is supported from v3.2 onwards. You can only drop empty databases.
 
 :::note
 
@@ -950,7 +950,7 @@ DROP DATABASE <database_name>
 
 ## Create a Hive table
 
-Similar to the internal databases of StarRocks, if you have the [CREATE TABLE](../../administration/user_privs/privilege_item.md#database) privilege on a Hive database, you can use the [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md), [CREATE TABLE AS SELECT (CTAS)](../../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md), or [CREATE TABLE LIKE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE_LIKE.md) statement to create a managed table in that Hive database.
+Similar to the internal databases of StarRocks, if you have the [CREATE TABLE](../../administration/user_privs/privilege_item.md#database) privilege on a Hive database, you can use the [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md), [CREATE TABLE AS SELECT ../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.mdELECT.md), or [CREATE TABL../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_LIKE.md_LIKE.md) statement to create a managed table in that Hive database.
 
 This feature is supported since v3.2 in which version StarRocks only supports creating Parquet-formatted Hive tables. From v3.3 onwards, StarRocks also supports creating ORC- and Textfile-formatted Hive tables.
 
@@ -1020,7 +1020,7 @@ The following table describes a few key properties.
 | ----------------- | ------------------------------------------------------------ |
 | location          | The file path in which you want to create the managed table. When you use HMS as metastore, you do not need to specify the `location` parameter, because StarRocks will create the table in the default file path of the current Hive catalog. When you use AWS Glue as metadata service:<ul><li>If you have specified the `location` parameter for the database in which you want to create the table, you do not need to specify the `location` parameter for the table. As such, the table defaults to the file path of the database to which it belongs. </li><li>If you have not specified the `location` for the database in which you want to create the table, you must specify the `location` parameter for the table.</li></ul> |
 | file_format       | The file format of the managed table. Supported file formats are Parquet, ORC, and Textfile. ORC and Textfile formats are supported from v3.3 onwards. Valid values: `parquet`, `orc`, and `textfile`. Default value: `parquet`. |
-| compression_codec | The compression algorithm used for the managed table. This property is deprecated in v3.2.3, since which version the compression algorithm used for sinking data to Hive tables is uniformly controlled by the session variable [connector_sink_compression_codec](../../reference/System_variable.md#connector_sink_compression_codec). |
+| compression_codec | The compression algorithm used for the managed table. This property is deprecated in v3.2.3, since which version the compression algorithm used for sinking data to Hive tables is uniformly controlled by the session variable [connector_sink_compression_codec](../../sql-reference/System_variable.md#connector_sink_compression_codec). |
 
 ### Examples
 
@@ -1058,16 +1058,16 @@ The following DDLs use the default file format Parquet as an example.
 
 ## Sink data to a Hive table
 
-Similar to the internal tables of StarRocks, if you have the [INSERT](../../administration/user_privs/privilege_item.md#table) privilege on a Hive table (which can be a managed table or an external table), you can use the [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md) statement to sink the data of a StarRocks table to that Hive table.
+Similar to the internal tables of StarRocks, if you have the [INSERT](../../administration/user_privs/privilege_item.md#table) privilege on a Hive table (which can be a managed table or an external table), you can use the [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md) statement to sink the data of a StarRocks table to that Hive table.
 
 This feature is supported since v3.2 in which version data can be sunk only to Parquet-formatted Hive tables. From v3.3 onwards, StarRocks also supports sinking data to ORC- and Textfile-formatted Hive tables.
 
-Note that sinking data to external tables is disabled by default. To sink data to external tables, you must set the [system variable `ENABLE_WRITE_HIVE_EXTERNAL_TABLE`](../../reference/System_variable.md) to `true`.
+Note that sinking data to external tables is disabled by default. To sink data to external tables, you must set the [system variable `ENABLE_WRITE_HIVE_EXTERNAL_TABLE`](../../sql-reference/System_variable.md) to `true`.
 
 :::note
 
 - You can grant and revoke privileges by using [GRANT](../../sql-reference/sql-statements/account-management/GRANT.md) and [REVOKE](../../sql-reference/sql-statements/account-management/REVOKE.md).
-- You can use the session variable [connector_sink_compression_codec](../../reference/System_variable.md#connector_sink_compression_codec) to specify the compression algorithm used for sinking data to Hive tables.
+- You can use the session variable [connector_sink_compression_codec](../../sql-reference/System_variable.md#connector_sink_compression_codec) to specify the compression algorithm used for sinking data to Hive tables.
 
 :::
 
@@ -1156,7 +1156,7 @@ The following DMLs use the default file format Parquet as an example.
 
 ## Drop a Hive table
 
-Similar to the internal tables of StarRocks, if you have the [DROP](../../administration/user_privs/privilege_item.md#table) privilege on a Hive table, you can use the [DROP TABLE](../../sql-reference/sql-statements/data-definition/DROP_TABLE.md) statement to drop that Hive table. This feature is supported from v3.1 onwards. Note that currently StarRocks supports dropping only managed tables of Hive.
+Similar to the internal tables of StarRocks, if you have the [DROP](../../administration/user_privs/privilege_item.md#table) privilege on a Hive table, you can use the [DROP TABLE](../../sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md) statement to drop that Hive table. This feature is supported from v3.1 onwards. Note that currently StarRocks supports dropping only managed tables of Hive.
 
 :::note
 
@@ -1176,7 +1176,7 @@ DROP TABLE <table_name> FORCE
 
 ### Manual update
 
-By default, StarRocks caches the metadata of Hive and automatically updates the metadata in asynchronous mode to deliver better performance. Additionally, after some schema changes or table updates are made on a Hive table, you can also use [REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE.md) to manually update its metadata, thereby ensuring that StarRocks can obtain up-to-date metadata at its earliest opportunity and generate appropriate execution plans:
+By default, StarRocks caches the metadata of Hive and automatically updates the metadata in asynchronous mode to deliver better performance. Additionally, after some schema changes or table updates are made on a Hive table, you can also use [REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/table_bucket_part_index/REFRESH_EXTERNAL_TABLE.md) to manually update its metadata, thereby ensuring that StarRocks can obtain up-to-date metadata at its earliest opportunity and generate appropriate execution plans:
 
 ```SQL
 REFRESH EXTERNAL TABLE <table_name> [PARTITION ('partition_name', ...)]
@@ -1277,9 +1277,9 @@ From v2.5.5 onwards, StarRocks can periodically refresh the cached metadata of t
 
 | Configuration item                                           | Default                              | Description                          |
 | ------------------------------------------------------------ | ------------------------------------ | ------------------------------------ |
-| enable_background_refresh_connector_metadata                 | `true` in v3.0<br />`false` in v2.5  | Whether to enable the periodic Hive metadata cache refresh. After it is enabled, StarRocks polls the metastore (Hive Metastore or AWS Glue) of your Hive cluster, and refreshes the cached metadata of the frequently accessed Hive catalogs to perceive data changes. `true` indicates to enable the Hive metadata cache refresh, and `false` indicates to disable it. This item is an [FE dynamic parameter](../../administration/management/FE_configuration.md#configure-fe-dynamic-parameters). You can modify it using the [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md) command. |
-| background_refresh_metadata_interval_millis                  | `600000` (10 minutes)                | The interval between two consecutive Hive metadata cache refreshes. Unit: millisecond. This item is an [FE dynamic parameter](../../administration/management/FE_configuration.md#configure-fe-dynamic-parameters). You can modify it using the [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md) command. |
-| background_refresh_metadata_time_secs_since_last_access_secs | `86400` (24 hours)                   | The expiration time of a Hive metadata cache refresh task. For the Hive catalog that has been accessed, if it has not been accessed for more than the specified time, StarRocks stops refreshing its cached metadata. For the Hive catalog that has not been accessed, StarRocks will not refresh its cached metadata. Unit: second. This item is an [FE dynamic parameter](../../administration/management/FE_configuration.md#configure-fe-dynamic-parameters). You can modify it using the [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md) command. |
+| enable_background_refresh_connector_metadata                 | `true` in v3.0<br />`false` in v2.5  | Whether to enable the periodic Hive metadata cache refresh. After it is enabled, StarRocks polls the metastore (Hive Metastore or AWS Glue) of your Hive cluster, and refreshes the cached metadata of the frequently accessed Hive catalogs to perceive data changes. `true` indicates to enable the Hive metadata cache refresh, and `false` indicates to disable it. This item is an [FE dynamic parameter](../../administration/management/FE_configuration.md#configure-fe-dynamic-parameters). You can modify it using the [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md) command. |
+| background_refresh_metadata_interval_millis                  | `600000` (10 minutes)                | The interval between two consecutive Hive metadata cache refreshes. Unit: millisecond. This item is an [FE dynamic parameter](../../administration/management/FE_configuration.md#configure-fe-dynamic-parameters). You can modify it using the [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md) command. |
+| background_refresh_metadata_time_secs_since_last_access_secs | `86400` (24 hours)                   | The expiration time of a Hive metadata cache refresh task. For the Hive catalog that has been accessed, if it has not been accessed for more than the specified time, StarRocks stops refreshing its cached metadata. For the Hive catalog that has not been accessed, StarRocks will not refresh its cached metadata. Unit: second. This item is an [FE dynamic parameter](../../administration/management/FE_configuration.md#configure-fe-dynamic-parameters). You can modify it using the [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md) command. |
 
 Using the periodic Hive metadata cache refresh feature and the metadata automatic asynchronous update policy together significantly accelerates data access, reduces the read load from external data sources, and improves query performance.
 
diff --git a/docs/en/data_source/catalog/hudi_catalog.md b/docs/en/data_source/catalog/hudi_catalog.md
index aa4b18ee590186..29cc03db30a706 100644
--- a/docs/en/data_source/catalog/hudi_catalog.md
+++ b/docs/en/data_source/catalog/hudi_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 5
 ---
 
@@ -7,7 +7,7 @@ toc_max_heading_level: 5
 
 A Hudi catalog is a kind of external catalog that enables you to query data from Apache Hudi without ingestion.
 
-Also, you can directly transform and load data from Hudi by using [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) based on Hudi catalogs. StarRocks supports Hudi catalogs from v2.4 onwards.
+Also, you can directly transform and load data from Hudi by using [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) based on Hudi catalogs. StarRocks supports Hudi catalogs from v2.4 onwards.
 
 To ensure successful SQL workloads on your Hudi cluster, your StarRocks cluster must be able to access the storage system and metastore of your Hudi cluster. StarRocks supports the following storage systems and metastores:
 
@@ -759,13 +759,13 @@ PROPERTIES
 
 ## View Hudi catalogs
 
-You can use [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
+You can use [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a Hudi catalog named `hudi_catalog_glue`:
+You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a Hudi catalog named `hudi_catalog_glue`:
 
 ```SQL
 SHOW CREATE CATALOG hudi_catalog_glue;
@@ -775,7 +775,7 @@ SHOW CREATE CATALOG hudi_catalog_glue;
 
 You can use one of the following methods to switch to a Hudi catalog and a database in it:
 
-- Use [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) to specify a Hudi catalog in the current session, and then use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to specify an active database:
+- Use [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) to specify a Hudi catalog in the current session, and then use [USE](../../sql-reference/sql-statements/Database/USE.md) to specify an active database:
 
   ```SQL
   -- Switch to a specified catalog in the current session:
@@ -784,7 +784,7 @@ You can use one of the following methods to switch to a Hudi catalog and a datab
   USE <db_name>
   ```
 
-- Directly use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to switch to a Hudi catalog and a database in it:
+- Directly use [USE](../../sql-reference/sql-statements/Database/USE.md) to switch to a Hudi catalog and a database in it:
 
   ```SQL
   USE <catalog_name>.<db_name>
@@ -792,7 +792,7 @@ You can use one of the following methods to switch to a Hudi catalog and a datab
 
 ## Drop a Hudi catalog
 
-You can use [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) to drop an external catalog.
+You can use [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) to drop an external catalog.
 
 The following example drops a Hudi catalog named `hudi_catalog_glue`:
 
@@ -818,7 +818,7 @@ You can use one of the following syntaxes to view the schema of a Hudi table:
 
 ## Query a Hudi table
 
-1. Use [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) to view the databases in your Hudi cluster:
+1. Use [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) to view the databases in your Hudi cluster:
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>
@@ -826,7 +826,7 @@ You can use one of the following syntaxes to view the schema of a Hudi table:
 
 2. [Switch to a Hudi Catalog and a database in it](#switch-to-a-hudi-catalog-and-a-database-in-it).
 
-3. Use [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the destination table in the specified database:
+3. Use [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the destination table in the specified database:
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10
@@ -844,7 +844,7 @@ INSERT INTO default_catalog.olap_db.olap_tbl SELECT * FROM hudi_table
 
 ### Manual update
 
-By default, StarRocks caches the metadata of Hudi and automatically updates the metadata in asynchronous mode to deliver better performance. Additionally, after some schema changes or table updates are made on a Hudi table, you can also use [REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE.md) to manually update its metadata, thereby ensuring that StarRocks can obtain up-to-date metadata at its earliest opportunity and generate appropriate execution plans:
+By default, StarRocks caches the metadata of Hudi and automatically updates the metadata in asynchronous mode to deliver better performance. Additionally, after some schema changes or table updates are made on a Hudi table, you can also use [REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/table_bucket_part_index/REFRESH_EXTERNAL_TABLE.md) to manually update its metadata, thereby ensuring that StarRocks can obtain up-to-date metadata at its earliest opportunity and generate appropriate execution plans:
 
 ```SQL
 REFRESH EXTERNAL TABLE <table_name> [PARTITION ('partition_name', ...)]
diff --git a/docs/en/data_source/catalog/iceberg_catalog.md b/docs/en/data_source/catalog/iceberg_catalog.md
index 9327ff5a0067f3..8df6b84b8c2206 100644
--- a/docs/en/data_source/catalog/iceberg_catalog.md
+++ b/docs/en/data_source/catalog/iceberg_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 5
 ---
 import Tabs from '@theme/Tabs';
@@ -14,8 +14,8 @@ Try it in this [hands-on tutorial](../../quick_start/iceberg.md)
 An Iceberg catalog is a type of external catalog that is supported by StarRocks from v2.4 onwards. With Iceberg catalogs, you can:
 
 - Directly query data stored in Iceberg without the need to manually create tables.
-- Use [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) or asynchronous materialized views (which are supported from v2.5 onwards) to process data stored in Iceberg and load the data into StarRocks.
-- Perform operations on StarRocks to create or drop Iceberg databases and tables, or sink data from StarRocks tables to Parquet-formatted Iceberg tables by using [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) (this feature is supported from v3.1 onwards).
+- Use [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) or asynchronous materialized views (which are supported from v2.5 onwards) to process data stored in Iceberg and load the data into StarRocks.
+- Perform operations on StarRocks to create or drop Iceberg databases and tables, or sink data from StarRocks tables to Parquet-formatted Iceberg tables by using [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) (this feature is supported from v3.1 onwards).
 
 To ensure successful SQL workloads on your Iceberg cluster, your StarRocks cluster must be able to access the storage system and metastore of your Iceberg cluster. StarRocks supports the following storage systems and metastores:
 
@@ -938,13 +938,13 @@ PROPERTIES
 
 ### View Iceberg catalogs
 
-You can use [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
+You can use [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of an Iceberg catalog named `iceberg_catalog_glue`:
+You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of an Iceberg catalog named `iceberg_catalog_glue`:
 
 ```SQL
 SHOW CREATE CATALOG iceberg_catalog_glue;
@@ -956,7 +956,7 @@ SHOW CREATE CATALOG iceberg_catalog_glue;
 
 You can use one of the following methods to switch to an Iceberg catalog and a database in it:
 
-- Use [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) to specify an Iceberg catalog in the current session, and then use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to specify an active database:
+- Use [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) to specify an Iceberg catalog in the current session, and then use [USE](../../sql-reference/sql-statements/Database/USE.md) to specify an active database:
 
   ```SQL
   -- Switch to a specified catalog in the current session:
@@ -965,7 +965,7 @@ You can use one of the following methods to switch to an Iceberg catalog and a d
   USE <db_name>
   ```
 
-- Directly use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to switch to an Iceberg catalog and a database in it:
+- Directly use [USE](../../sql-reference/sql-statements/Database/USE.md) to switch to an Iceberg catalog and a database in it:
 
   ```SQL
   USE <catalog_name>.<db_name>
@@ -975,7 +975,7 @@ You can use one of the following methods to switch to an Iceberg catalog and a d
 
 ### Drop an Iceberg catalog
 
-You can use [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) to drop an external catalog.
+You can use [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) to drop an external catalog.
 
 The following example drops an Iceberg catalog named `iceberg_catalog_glue`:
 
@@ -1005,7 +1005,7 @@ You can use one of the following syntaxes to view the schema of an Iceberg table
 
 ### Query an Iceberg table
 
-1. Use [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) to view the databases in your Iceberg cluster:
+1. Use [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) to view the databases in your Iceberg cluster:
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>
@@ -1013,7 +1013,7 @@ You can use one of the following syntaxes to view the schema of an Iceberg table
 
 2. [Switch to an Iceberg catalog and a database in it](#switch-to-an-iceberg-catalog-and-a-database-in-it).
 
-3. Use [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the destination table in the specified database:
+3. Use [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the destination table in the specified database:
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10
@@ -1023,7 +1023,7 @@ You can use one of the following syntaxes to view the schema of an Iceberg table
 
 ### Create an Iceberg database
 
-Similar to the internal catalog of StarRocks, if you have the [CREATE DATABASE](../../administration/user_privs/privilege_item.md#catalog) privilege on an Iceberg catalog, you can use the [CREATE DATABASE](../../sql-reference/sql-statements/data-definition/CREATE_DATABASE.md) statement to create databases in that Iceberg catalog. This feature is supported from v3.1 onwards.
+Similar to the internal catalog of StarRocks, if you have the [CREATE DATABASE](../../administration/user_privs/privilege_item.md#catalog) privilege on an Iceberg catalog, you can use the [CREATE DATABASE](../../sql-reference/sql-statements/Database/CREATE_DATABASE.md) statement to create databases in that Iceberg catalog. This feature is supported from v3.1 onwards.
 
 :::tip
 
@@ -1076,7 +1076,7 @@ The `prefix` varies based on the storage system you use:
 
 ### Drop an Iceberg database
 
-Similar to the internal databases of StarRocks, if you have the [DROP](../../administration/user_privs/privilege_item.md#database) privilege on an Iceberg database, you can use the [DROP DATABASE](../../sql-reference/sql-statements/data-definition/DROP_DATABASE.md) statement to drop that Iceberg database. This feature is supported from v3.1 onwards. You can only drop empty databases.
+Similar to the internal databases of StarRocks, if you have the [DROP](../../administration/user_privs/privilege_item.md#database) privilege on an Iceberg database, you can use the [DROP DATABASE](../../sql-reference/sql-statements/Database/DROP_DATABASE.md) statement to drop that Iceberg database. This feature is supported from v3.1 onwards. You can only drop empty databases.
 
 When you drop an Iceberg database, the database's file path on your HDFS cluster or cloud storage will not be dropped along with the database.
 
@@ -1090,7 +1090,7 @@ DROP DATABASE <database_name>;
 
 ### Create an Iceberg table
 
-Similar to the internal databases of StarRocks, if you have the [CREATE TABLE](../../administration/user_privs/privilege_item.md#database) privilege on an Iceberg database, you can use the [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) or [CREATE TABLE AS SELECT (CTAS)](../../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md) statement to create a table in that Iceberg database. This feature is supported from v3.1 onwards.
+Similar to the internal databases of StarRocks, if you have the [CREATE TABLE](../../administration/user_privs/privilege_item.md#database) privilege on an Iceberg database, you can use the [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) or [CREATE TABLE AS SELECT ../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.mdELECT.md) statement to create a table in that Iceberg database. This feature is supported from v3.1 onwards.
 
 [Switch to an Iceberg catalog and a database in it](#switch-to-an-iceberg-catalog-and-a-database-in-it), and then use the following syntax to create an Iceberg table in that database.
 
@@ -1156,7 +1156,7 @@ Description: The file format of the Iceberg table. Only the Parquet format is su
 
 ###### compression_codec
 
-Description: The compression algorithm used for the Iceberg table. The supported compression algorithms are SNAPPY, GZIP, ZSTD, and LZ4. Default value: `gzip`. This property is deprecated in v3.2.3, since which version the compression algorithm used for sinking data to Iceberg tables is uniformly controlled by the session variable [connector_sink_compression_codec](../../reference/System_variable.md#connector_sink_compression_codec).
+Description: The compression algorithm used for the Iceberg table. The supported compression algorithms are SNAPPY, GZIP, ZSTD, and LZ4. Default value: `gzip`. This property is deprecated in v3.2.3, since which version the compression algorithm used for sinking data to Iceberg tables is uniformly controlled by the session variable [connector_sink_compression_codec](../../sql-reference/System_variable.md#connector_sink_compression_codec).
 
 ---
 
@@ -1196,7 +1196,7 @@ Description: The compression algorithm used for the Iceberg table. The supported
 
 ### Sink data to an Iceberg table
 
-Similar to the internal tables of StarRocks, if you have the [INSERT](../../administration/user_privs/privilege_item.md#table) privilege on an Iceberg table, you can use the [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md) statement to sink the data of a StarRocks table to that Iceberg table (currently only Parquet-formatted Iceberg tables are supported). This feature is supported from v3.1 onwards.
+Similar to the internal tables of StarRocks, if you have the [INSERT](../../administration/user_privs/privilege_item.md#table) privilege on an Iceberg table, you can use the [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md) statement to sink the data of a StarRocks table to that Iceberg table (currently only Parquet-formatted Iceberg tables are supported). This feature is supported from v3.1 onwards.
 
 [Switch to an Iceberg catalog and a database in it](#switch-to-an-iceberg-catalog-and-a-database-in-it), and then use the following syntax to sink the data of StarRocks table to a Parquet-formatted Iceberg table in that database.
 
@@ -1303,7 +1303,7 @@ The partitions into which you want to load data. You must specify all partition
 
 ### Drop an Iceberg table
 
-Similar to the internal tables of StarRocks, if you have the [DROP](../../administration/user_privs/privilege_item.md#table) privilege on an Iceberg table, you can use the [DROP TABLE](../../sql-reference/sql-statements/data-definition/DROP_TABLE.md) statement to drop that Iceberg table. This feature is supported from v3.1 onwards.
+Similar to the internal tables of StarRocks, if you have the [DROP](../../administration/user_privs/privilege_item.md#table) privilege on an Iceberg table, you can use the [DROP TABLE](../../sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md) statement to drop that Iceberg table. This feature is supported from v3.1 onwards.
 
 When you drop an Iceberg table, the table's file path and data on your HDFS cluster or cloud storage will not be dropped along with the table.
 
diff --git a/docs/en/data_source/catalog/jdbc_catalog.md b/docs/en/data_source/catalog/jdbc_catalog.md
index fa9f15f96aee44..b0e8d29634525a 100644
--- a/docs/en/data_source/catalog/jdbc_catalog.md
+++ b/docs/en/data_source/catalog/jdbc_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 ---
 
@@ -9,7 +9,7 @@ StarRocks supports JDBC catalogs from v3.0 onwards.
 
 A JDBC catalog is a kind of external catalog that enables you to query data from data sources accessed through JDBC without ingestion.
 
-Also, you can directly transform and load data from JDBC data sources by using [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) based on JDBC catalogs.
+Also, you can directly transform and load data from JDBC data sources by using [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) based on JDBC catalogs.
 
 JDBC catalogs support MySQL and PostgreSQL from v3.0 onwards, and Oracle and SQLServer since v3.2.9 and v3.3.1.
 
@@ -111,13 +111,13 @@ PROPERTIES
 
 ## View JDBC catalogs
 
-You can use [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
+You can use [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a JDBC catalog named `jdbc0`:
+You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a JDBC catalog named `jdbc0`:
 
 ```SQL
 SHOW CREATE CATALOG jdbc0;
@@ -125,7 +125,7 @@ SHOW CREATE CATALOG jdbc0;
 
 ## Drop a JDBC catalog
 
-You can use [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) to drop a JDBC catalog.
+You can use [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) to drop a JDBC catalog.
 
 The following example drops a JDBC catalog named `jdbc0`:
 
@@ -135,31 +135,31 @@ DROP Catalog jdbc0;
 
 ## Query a table in a JDBC catalog
 
-1. Use [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) to view the databases in your JDBC-compatible cluster:
+1. Use [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) to view the databases in your JDBC-compatible cluster:
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>;
    ```
 
-2. Use [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) to switch to the destination catalog in the current session:
+2. Use [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) to switch to the destination catalog in the current session:
 
     ```SQL
     SET CATALOG <catalog_name>;
     ```
 
-    Then, use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to specify the active database in the current session:
+    Then, use [USE](../../sql-reference/sql-statements/Database/USE.md) to specify the active database in the current session:
 
     ```SQL
     USE <db_name>;
     ```
 
-    Or, you can use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to directly specify the active database in the destination catalog:
+    Or, you can use [USE](../../sql-reference/sql-statements/Database/USE.md) to directly specify the active database in the destination catalog:
 
     ```SQL
     USE <catalog_name>.<db_name>;
     ```
 
-3. Use [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the destination table in the specified database:
+3. Use [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the destination table in the specified database:
 
    ```SQL
    SELECT * FROM <table_name>;
diff --git a/docs/en/data_source/catalog/kudu_catalog.md b/docs/en/data_source/catalog/kudu_catalog.md
index 3d4d34cba09255..ec6c27e8d351fb 100644
--- a/docs/en/data_source/catalog/kudu_catalog.md
+++ b/docs/en/data_source/catalog/kudu_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English" 
+displayed_sidebar: docs
 ---
 
 # [Experimental] Kudu catalog
@@ -8,7 +8,7 @@ StarRocks supports Kudu catalogs from v3.3 onwards.
 
 A Kudu catalog is a kind of external catalog that enables you to query data from Apache Kudu without ingestion.
 
-Also, you can directly transform and load data from Kudu by using [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) based on Kudu catalogs.
+Also, you can directly transform and load data from Kudu by using [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) based on Kudu catalogs.
 
 To ensure successful SQL workloads on your Kudu cluster, your StarRocks cluster needs to integrate with the following important components:
 
@@ -115,13 +115,13 @@ The following table describes the parameter you need to configure in `CatalogPar
 
 ## View Kudu catalogs
 
-You can use [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
+You can use [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a Kudu catalog named `kudu_catalog`:
+You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a Kudu catalog named `kudu_catalog`:
 
 ```SQL
 SHOW CREATE CATALOG kudu_catalog;
@@ -129,7 +129,7 @@ SHOW CREATE CATALOG kudu_catalog;
 
 ## Drop a Kudu catalog
 
-You can use [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) to drop an external catalog.
+You can use [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) to drop an external catalog.
 
 The following example drops a Kudu catalog named `kudu_catalog`:
 
@@ -155,31 +155,31 @@ You can use one of the following syntaxes to view the schema of a Kudu table:
 
 ## Query a Kudu table
 
-1. Use [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) to view the databases in your Kudu cluster:
+1. Use [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) to view the databases in your Kudu cluster:
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>;
    ```
 
-2. Use [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) to switch to the destination catalog in the current session:
+2. Use [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) to switch to the destination catalog in the current session:
 
    ```SQL
    SET CATALOG <catalog_name>;
    ```
 
-   Then, use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to specify the active database in the current session:
+   Then, use [USE](../../sql-reference/sql-statements/Database/USE.md) to specify the active database in the current session:
 
    ```SQL
    USE <db_name>;
    ```
 
-   Or, you can use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to directly specify the active database in the destination catalog:
+   Or, you can use [USE](../../sql-reference/sql-statements/Database/USE.md) to directly specify the active database in the destination catalog:
 
    ```SQL
    USE <catalog_name>.<db_name>;
    ```
 
-3. Use [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the destination table in the specified database:
+3. Use [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the destination table in the specified database:
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10;
diff --git a/docs/en/data_source/catalog/maxcompute_catalog.md b/docs/en/data_source/catalog/maxcompute_catalog.md
index 0e25e7914b00b9..a5e6032a201645 100644
--- a/docs/en/data_source/catalog/maxcompute_catalog.md
+++ b/docs/en/data_source/catalog/maxcompute_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 ---
 
@@ -9,7 +9,7 @@ StarRocks supports Alibaba Cloud MaxCompute (previously known as ODPS) catalogs
 
 A MaxCompute catalog is a kind of external catalog that enables you to query data from MaxCompute without ingestion.
 
-With MaxCompute catalogs, you also can directly transform and load the data from MaxCompute by using [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md).
+With MaxCompute catalogs, you also can directly transform and load the data from MaxCompute by using [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md).
 
 ## Usage notes
 
@@ -113,14 +113,14 @@ PROPERTIES (
 
 ## View MaxCompute catalogs
 
-You can use [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md)
+You can use [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md)
 to query all catalogs in the current StarRocks cluster:
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a MaxCompute catalog named `odps_catalog`:
+You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a MaxCompute catalog named `odps_catalog`:
 
 ```SQL
 SHOW CREATE CATALOG odps_catalog;
@@ -128,7 +128,7 @@ SHOW CREATE CATALOG odps_catalog;
 
 ## Drop a MaxCompute catalog
 
-You can use [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) to drop an external catalog.
+You can use [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) to drop an external catalog.
 
 The following example drops a MaxCompute catalog named `odps_catalog`:
 
@@ -154,31 +154,31 @@ You can use one of the following syntaxes to view the schema of a MaxCompute tab
 
 ## Query a MaxCompute table
 
-1. Use [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) to view the databases in your MaxCompute cluster:
+1. Use [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) to view the databases in your MaxCompute cluster:
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>;
    ```
 
-2. Use [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) to switch to the destination catalog in the current session:
+2. Use [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) to switch to the destination catalog in the current session:
 
    ```SQL
    SET CATALOG <catalog_name>;
    ```
 
-   Then, use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to specify the active database in the current session:
+   Then, use [USE](../../sql-reference/sql-statements/Database/USE.md) to specify the active database in the current session:
 
    ```SQL
    USE <db_name>;
    ```
 
-   Or, you can use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to directly specify the active database in the destination catalog:
+   Or, you can use [USE](../../sql-reference/sql-statements/Database/USE.md) to directly specify the active database in the destination catalog:
 
    ```SQL
    USE <catalog_name>.<db_name>;
    ```
 
-3. Use [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the destination table in the specified database:
+3. Use [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the destination table in the specified database:
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10;
@@ -228,7 +228,7 @@ The TIMESTAMP type will lose precision due to type conversion in StarRocks.
 
 In the current version, MaxCompute catalogs cannot automatically collect CBO statistics for MaxCompute tables, and consequently the optimizer may not be able to generate the optimal query plans. As such, manually scanning the CBO statistics for MaxCompute tables and importing them into StarRocks can effectively expedite queries.
 
-Suppose that there is a MaxCompute table named `mc_table` in your MaxCompute cluster. You can create a manual collection task for collecting CBO statistics by using [ANALYZE TABLE](../../sql-reference/sql-statements/data-definition/ANALYZE_TABLE.md):
+Suppose that there is a MaxCompute table named `mc_table` in your MaxCompute cluster. You can create a manual collection task for collecting CBO statistics by using [ANALYZE TABLE](../../sql-reference/sql-statements/cbo_stats/ANALYZE_TABLE.md):
 
 ```SQL
 ANALYZE TABLE mc_table;
@@ -236,7 +236,7 @@ ANALYZE TABLE mc_table;
 
 ## Manually update metadata cache
 
-By default, StarRocks caches the metadata of MaxCompute to improve query performance. Therefore, after making schema changes or other updates to a MaxCompute table, you can use [REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE.md) to manually update the metadata of the table, thereby ensuring that StarRocks can obtain the most recent metadata promptly:
+By default, StarRocks caches the metadata of MaxCompute to improve query performance. Therefore, after making schema changes or other updates to a MaxCompute table, you can use [REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/table_bucket_part_index/REFRESH_EXTERNAL_TABLE.md) to manually update the metadata of the table, thereby ensuring that StarRocks can obtain the most recent metadata promptly:
 
 ```SQL
 REFRESH EXTERNAL TABLE <table_name> [PARTITION ('partition_name', ...)]
diff --git a/docs/en/data_source/catalog/paimon_catalog.md b/docs/en/data_source/catalog/paimon_catalog.md
index 3471cce7e85404..0490686b7856f1 100644
--- a/docs/en/data_source/catalog/paimon_catalog.md
+++ b/docs/en/data_source/catalog/paimon_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 5
 ---
 
@@ -9,7 +9,7 @@ StarRocks supports Paimon catalogs from v3.1 onwards.
 
 A Paimon catalog is a kind of external catalog that enables you to query data from Apache Paimon without ingestion.
 
-Also, you can directly transform and load data from Paimon by using [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) based on Paimon catalogs.
+Also, you can directly transform and load data from Paimon by using [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) based on Paimon catalogs.
 
 To ensure successful SQL workloads on your Paimon cluster, your StarRocks cluster must be able to access the storage system and metastore of your Paimon cluster. StarRocks supports the following storage systems and metastores:
 
@@ -603,13 +603,13 @@ PROPERTIES
 
 ## View Paimon catalogs
 
-You can use [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
+You can use [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a Paimon catalog named `paimon_catalog_fs`:
+You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a Paimon catalog named `paimon_catalog_fs`:
 
 ```SQL
 SHOW CREATE CATALOG paimon_catalog_fs;
@@ -617,7 +617,7 @@ SHOW CREATE CATALOG paimon_catalog_fs;
 
 ## Drop a Paimon catalog
 
-You can use [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) to drop an external catalog.
+You can use [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) to drop an external catalog.
 
 The following example drops a Paimon catalog named `paimon_catalog_fs`:
 
@@ -643,31 +643,31 @@ You can use one of the following syntaxes to view the schema of a Paimon table:
 
 ## Query a Paimon table
 
-1. Use [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) to view the databases in your Paimon cluster:
+1. Use [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) to view the databases in your Paimon cluster:
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>;
    ```
 
-2. Use [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) to switch to the destination catalog in the current session:
+2. Use [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) to switch to the destination catalog in the current session:
 
    ```SQL
    SET CATALOG <catalog_name>;
    ```
 
-   Then, use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to specify the active database in the current session:
+   Then, use [USE](../../sql-reference/sql-statements/Database/USE.md) to specify the active database in the current session:
 
    ```SQL
    USE <db_name>;
    ```
 
-   Or, you can use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to directly specify the active database in the destination catalog:
+   Or, you can use [USE](../../sql-reference/sql-statements/Database/USE.md) to directly specify the active database in the destination catalog:
 
    ```SQL
    USE <catalog_name>.<db_name>;
    ```
 
-3. Use [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the destination table in the specified database:
+3. Use [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the destination table in the specified database:
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10;
diff --git a/docs/en/data_source/catalog/query_external_data.md b/docs/en/data_source/catalog/query_external_data.md
index 72b42460c072d8..4e5471550c087d 100644
--- a/docs/en/data_source/catalog/query_external_data.md
+++ b/docs/en/data_source/catalog/query_external_data.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Query external data
@@ -16,13 +16,13 @@ This topic guides you through querying data from external data sources by using
    - If you use the MySQL client to connect the StarRocks cluster, you go to `default_catalog` by default after connecting.
    - If you use JDBC to connect the StarRocks cluster, you can go directly to the destination database in the default catalog by specifying `default_catalog.db_name` when connecting.
 
-2. (Optional) Execute the following statement to view all the catalogs and find the external catalog you have created. See [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) to check the output of this statement.
+2. (Optional) Execute the following statement to view all the catalogs and find the external catalog you have created. See [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) to check the output of this statement.
 
       ```SQL
       SHOW CATALOGS;
       ```
 
-3. (Optional) Execute the following statement to view all the databases in the external catalog. See [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) to check the output of this statement.
+3. (Optional) Execute the following statement to view all the databases in the external catalog. See [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) to check the output of this statement.
 
       ```SQL
       SHOW DATABASES FROM catalog_name;
@@ -34,7 +34,7 @@ This topic guides you through querying data from external data sources by using
       USE catalog_name.db_name;
       ```
 
-5. Query external data. For more usages of the SELECT statement, see [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md).
+5. Query external data. For more usages of the SELECT statement, see [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md).
 
       ```SQL
       SELECT * FROM table_name;
diff --git a/docs/en/data_source/catalog/unified_catalog.md b/docs/en/data_source/catalog/unified_catalog.md
index 78ba5968ea3d72..edda599146aa4c 100644
--- a/docs/en/data_source/catalog/unified_catalog.md
+++ b/docs/en/data_source/catalog/unified_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 5
 ---
 
@@ -8,7 +8,7 @@ toc_max_heading_level: 5
 A unified catalog is a type of external catalog that is provided by StarRocks from v3.2 onwards to handle tables from Apache Hive™, Apache Iceberg, Apache Hudi, Delta Lake, and Apache Kudu data sources as a unified data source without ingestion. With unified catalogs, you can:
 
 - Directly query data stored in Hive, Iceberg, Hudi, Delta Lake, and Kudu without the need to manually create tables.
-- Use [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) or asynchronous materialized views (which are supported from v2.5 onwards) to process data stored in Hive, Iceberg, Hudi, Delta Lake, and Kudu and load the data into StarRocks.
+- Use [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) or asynchronous materialized views (which are supported from v2.5 onwards) to process data stored in Hive, Iceberg, Hudi, Delta Lake, and Kudu and load the data into StarRocks.
 - Perform operations on StarRocks to create or drop Hive and Iceberg databases and tables.
 
 To ensure successful SQL workloads on your unified data source, your StarRocks cluster must be able to access the storage system and metastore of your unified data source. StarRocks supports the following storage systems and metastores:
@@ -29,9 +29,9 @@ One unified catalog supports integrations with only a single storage system and
 
 - See the "Usage notes" section in [Hive catalog](../../data_source/catalog/hive_catalog.md), [Iceberg catalog](../../data_source/catalog/iceberg_catalog.md), [Hudi catalog](../../data_source/catalog/hudi_catalog.md), [Delta Lake catalog](../../data_source/catalog/deltalake_catalog.md), and [Kudu catalog](../../data_source/catalog/kudu_catalog.md) to understand the file formats and data types supported.
 
-- Format-specific operations are supported only for specific table formats. For example, [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) and [DROP TABLE](../../sql-reference/sql-statements/data-definition/DROP_TABLE.md) are supported only for Hive and Iceberg, and [REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE.md) is supported only for Hive and Hudi.
+- Format-specific operations are supported only for specific table formats. For example, [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) and [DROP TABLE](../../sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md) are supported only for Hive and Iceberg, and [REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/table_bucket_part_index/REFRESH_EXTERNAL_TABLE.md) is supported only for Hive and Hudi.
 
-  When you create a table within a unified catalog by using the [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) statement, use the `ENGINE` parameter to specify the table format (Hive or Iceberg).
+  When you create a table within a unified catalog by using the [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) statement, use the `ENGINE` parameter to specify the table format (Hive or Iceberg).
 
 ## Integration preparations
 
@@ -758,13 +758,13 @@ PROPERTIES
 
 ## View unified catalogs
 
-You can use [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
+You can use [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) to query all catalogs in the current StarRocks cluster:
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a unified catalog named `unified_catalog_glue`:
+You can also use [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) to query the creation statement of an external catalog. The following example queries the creation statement of a unified catalog named `unified_catalog_glue`:
 
 ```SQL
 SHOW CREATE CATALOG unified_catalog_glue;
@@ -774,7 +774,7 @@ SHOW CREATE CATALOG unified_catalog_glue;
 
 You can use one of the following methods to switch to a unified catalog and a database in it:
 
-- Use [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) to specify a unified catalog in the current session, and then use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to specify an active database:
+- Use [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) to specify a unified catalog in the current session, and then use [USE](../../sql-reference/sql-statements/Database/USE.md) to specify an active database:
 
   ```SQL
   -- Switch to a specified catalog in the current session:
@@ -783,7 +783,7 @@ You can use one of the following methods to switch to a unified catalog and a da
   USE <db_name>
   ```
 
-- Directly use [USE](../../sql-reference/sql-statements/data-definition/USE.md) to switch to a unified catalog and a database in it:
+- Directly use [USE](../../sql-reference/sql-statements/Database/USE.md) to switch to a unified catalog and a database in it:
 
   ```SQL
   USE <catalog_name>.<db_name>
@@ -791,7 +791,7 @@ You can use one of the following methods to switch to a unified catalog and a da
 
 ## Drop a unified catalog
 
-You can use [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) to drop an external catalog.
+You can use [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) to drop an external catalog.
 
 The following example drops a unified catalog named `unified_catalog_glue`:
 
@@ -819,7 +819,7 @@ You can use one of the following syntaxes to view the schema of a table from a u
 
 To query data from a unified catalog, follow these steps:
 
-1. Use [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) to view the databases in your unified data source with which the unified catalog is associated:
+1. Use [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) to view the databases in your unified data source with which the unified catalog is associated:
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>
@@ -827,7 +827,7 @@ To query data from a unified catalog, follow these steps:
 
 2. [Switch to a Hive Catalog and a database in it](#switch-to-a-unified-catalog-and-a-database-in-it).
 
-3. Use [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the destination table in the specified database:
+3. Use [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the destination table in the specified database:
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10
@@ -835,7 +835,7 @@ To query data from a unified catalog, follow these steps:
 
 ## Load data from Hive, Iceberg, Hudi, Delta Lake, or Kudu
 
-You can use [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) to load the data of a Hive, Iceberg, Hudi, Delta Lake, or Kudu table into a StarRocks table created within a unified catalog.
+You can use [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) to load the data of a Hive, Iceberg, Hudi, Delta Lake, or Kudu table into a StarRocks table created within a unified catalog.
 
 The following example loads the data of the Hive table `hive_table` into the StarRocks table `test_tbl` created in the database `test_database` that belongs to the unified catalog `unified_catalog`:
 
@@ -878,7 +878,7 @@ The `prefix` varies based on the storage system you use:
 
 ## Drop a database from a unified catalog
 
-Similar to the internal databases of StarRocks, if you have the [DROP](../../administration/user_privs/privilege_overview.md#database) privilege on a database created within a unified catalog, you can use the [DROP DATABASE](../../sql-reference/sql-statements/data-definition/DROP_DATABASE.md) statement to drop that database. You can only drop empty databases.
+Similar to the internal databases of StarRocks, if you have the [DROP](../../administration/user_privs/privilege_overview.md#database) privilege on a database created within a unified catalog, you can use the [DROP DATABASE](../../sql-reference/sql-statements/Database/DROP_DATABASE.md) statement to drop that database. You can only drop empty databases.
 
 > **NOTE**
 >
@@ -896,7 +896,7 @@ DROP DATABASE <database_name>
 
 ## Create a table in a unified catalog
 
-Similar to the internal databases of StarRocks, if you have the [CREATE TABLE](../../administration/user_privs/privilege_overview.md#database) privilege on a database created within a unified catalog, you can use the [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) or [CREATE TABLE AS SELECT (CTAS)](../../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md) statement to create a table in that database.
+Similar to the internal databases of StarRocks, if you have the [CREATE TABLE](../../administration/user_privs/privilege_overview.md#database) privilege on a database created within a unified catalog, you can use the [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) or [CREATE TABLE AS SELECT ../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.mdELECT.md) statement to create a table in that database.
 
 > **NOTE**
 >
@@ -904,7 +904,7 @@ Similar to the internal databases of StarRocks, if you have the [CREATE TABLE](.
 
 StarRocks supports creating only Hive and Iceberg tables in unified catalogs.
 
-[Switch to a Hive Catalog and a database in it](#switch-to-a-unified-catalog-and-a-database-in-it). Then, use [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) to create a Hive or Iceberg table in that database:
+[Switch to a Hive Catalog and a database in it](#switch-to-a-unified-catalog-and-a-database-in-it). Then, use [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) to create a Hive or Iceberg table in that database:
 
 ```SQL
 CREATE TABLE <table_name>
@@ -930,7 +930,7 @@ PARTITION BY (id,dt);
 
 ## Sink data to a table in a unified catalog
 
-Similar to the internal tables of StarRocks, if you have the [INSERT](../../administration/user_privs/privilege_overview.md#table) privilege on a table created within a unified catalog, you can use the [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md) statement to sink the data of a StarRocks table to that Unified Catalog table (currently only Parquet-formatted Unified Catalog tables are supported).
+Similar to the internal tables of StarRocks, if you have the [INSERT](../../administration/user_privs/privilege_overview.md#table) privilege on a table created within a unified catalog, you can use the [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md) statement to sink the data of a StarRocks table to that Unified Catalog table (currently only Parquet-formatted Unified Catalog tables are supported).
 
 > **NOTE**
 >
@@ -938,7 +938,7 @@ Similar to the internal tables of StarRocks, if you have the [INSERT](../../admi
 
 StarRocks supports sinking data only to Hive and Iceberg tables in unified catalogs.
 
-[Switch to a Hive Catalog and a database in it](#switch-to-a-unified-catalog-and-a-database-in-it). Then, use [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) to insert data into a Hive or Iceberg table in that database:
+[Switch to a Hive Catalog and a database in it](#switch-to-a-unified-catalog-and-a-database-in-it). Then, use [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) to insert data into a Hive or Iceberg table in that database:
 
 ```SQL
 INSERT {INTO | OVERWRITE} <table_name>
@@ -965,7 +965,7 @@ VALUES
 
 ## Drop a table from a unified catalog
 
-Similar to the internal tables of StarRocks, if you have the [DROP](../../administration/user_privs/privilege_overview.md#table) privilege on a table created within a unified catalog, you can use the [DROP TABLE](../../sql-reference/sql-statements/data-definition/DROP_TABLE.md) statement to drop that table.
+Similar to the internal tables of StarRocks, if you have the [DROP](../../administration/user_privs/privilege_overview.md#table) privilege on a table created within a unified catalog, you can use the [DROP TABLE](../../sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md) statement to drop that table.
 
 > **NOTE**
 >
@@ -973,7 +973,7 @@ Similar to the internal tables of StarRocks, if you have the [DROP](../../admini
 
 StarRocks supports dropping only Hive and Iceberg tables from unified catalogs.
 
-[Switch to a Hive Catalog and a database in it](#switch-to-a-unified-catalog-and-a-database-in-it). Then, use [DROP TABLE](../../sql-reference/sql-statements/data-definition/DROP_TABLE.md) to drop a Hive or Iceberg table in that database:
+[Switch to a Hive Catalog and a database in it](#switch-to-a-unified-catalog-and-a-database-in-it). Then, use [DROP TABLE](../../sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md) to drop a Hive or Iceberg table in that database:
 
 ```SQL
 DROP TABLE <table_name>
diff --git a/docs/en/data_source/data_cache.md b/docs/en/data_source/data_cache.md
index 320a4a04025f5e..30ddb939b053cd 100644
--- a/docs/en/data_source/data_cache.md
+++ b/docs/en/data_source/data_cache.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Data Cache
@@ -97,7 +97,7 @@ mysql> explain verbose select col1 from hudi_table;
 
 `dataCacheOptions={populate: false}` indicates that the cache will not be populated because the query will scan all partitions.
 
-You can also fine tune the population behavior of Data Cache via the Session Variable [populdate_datacache_mode](../reference/System_variable.md#populate_datacache_mode).
+You can also fine tune the population behavior of Data Cache via the Session Variable [populdate_datacache_mode](../sql-reference/System_variable.md#populate_datacache_mode).
 
 ### Population mode
 
@@ -111,7 +111,7 @@ StarRocks supports populating Data Cache in synchronous or asynchronous mode.
 
   In asynchronous population mode, the system tries to cache the accessed data in the background, in order to minimize the impact on read performance. Asynchronous population can reduce the performance impact of cache population on initial reads, but the population efficiency is lower than synchronous population. Typically, a single query cannot guarantee that all the accessed data can be cached. Multiple attempts may be needed to cache all the accessed data.
 
-From v3.3.0, asynchronous cache population is enabled by default. You can change the population mode by setting the session variable [enable_datacache_async_populate_mode](../reference/System_variable.md).
+From v3.3.0, asynchronous cache population is enabled by default. You can change the population mode by setting the session variable [enable_datacache_async_populate_mode](../sql-reference/System_variable.md).
 
 ## Footer Cache
 
@@ -247,10 +247,10 @@ You can configure Data Cache using the following system variables and BE paramet
 
 ### System variables
 
-- [populdate_datacache_mode](../reference/System_variable.md#populate_datacache_mode)
-- [enable_datacache_io_adaptor](../reference/System_variable.md#enable_datacache_io_adaptor)
-- [enable_file_metacache](../reference/System_variable.md#enable_file_metacache)
-- [enable_datacache_async_populate_mode](../reference/System_variable.md)
+- [populdate_datacache_mode](../sql-reference/System_variable.md#populate_datacache_mode)
+- [enable_datacache_io_adaptor](../sql-reference/System_variable.md#enable_datacache_io_adaptor)
+- [enable_file_metacache](../sql-reference/System_variable.md#enable_file_metacache)
+- [enable_datacache_async_populate_mode](../sql-reference/System_variable.md)
 
 ### BE Parameters
 
diff --git a/docs/en/data_source/data_cache_observe.md b/docs/en/data_source/data_cache_observe.md
index 8dc08d6d902d20..affe68e565c6dd 100644
--- a/docs/en/data_source/data_cache_observe.md
+++ b/docs/en/data_source/data_cache_observe.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Data Cache observability
diff --git a/docs/en/data_source/data_cache_warmup.md b/docs/en/data_source/data_cache_warmup.md
index 241a5cfffb5af3..5e4ae7d07468a9 100644
--- a/docs/en/data_source/data_cache_warmup.md
+++ b/docs/en/data_source/data_cache_warmup.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Data cache warmup
@@ -105,7 +105,7 @@ In verbose mode,  an extra metric will be returned:
 
 ## Periodic scheduling of CACHE SELECT tasks
 
-You can use CACHE SELECT with [SUBMIT TASK](../sql-reference/sql-statements/data-manipulation/SUBMIT_TASK.md) to achieve periodic warmup. For example, the following case warms up the `lineitem` table every 5 minutes:
+You can use CACHE SELECT with [SUBMIT TASK](../sql-reference/sql-statements/loading_unloading/ETL/SUBMIT_TASK.md) to achieve periodic warmup. For example, the following case warms up the `lineitem` table every 5 minutes:
 
 ```plaintext
 mysql> submit task always_cache schedule every(interval 5 minute) as cache select l_orderkey
diff --git a/docs/en/data_source/data_lakes.mdx b/docs/en/data_source/data_lakes.mdx
index 4aed51acb1c7e3..13300e9856047b 100644
--- a/docs/en/data_source/data_lakes.mdx
+++ b/docs/en/data_source/data_lakes.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 import DataLakeIntro from '../_assets/commonMarkdown/datalakeIntro.md'
 
diff --git a/docs/en/data_source/datalake_faq.md b/docs/en/data_source/datalake_faq.md
index 94c31a978ebc77..4bdfb52744d0f1 100644
--- a/docs/en/data_source/datalake_faq.md
+++ b/docs/en/data_source/datalake_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Data lake FAQ
diff --git a/docs/en/data_source/feature-support-data-lake-analytics.md b/docs/en/data_source/feature-support-data-lake-analytics.md
index 708264892338c2..f2a11d9a1c27f8 100644
--- a/docs/en/data_source/feature-support-data-lake-analytics.md
+++ b/docs/en/data_source/feature-support-data-lake-analytics.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_label: "Feature Support"
 ---
 
diff --git a/docs/en/data_source/file_external_table.md b/docs/en/data_source/file_external_table.md
index be90d69483cea7..a816cafa673b96 100644
--- a/docs/en/data_source/file_external_table.md
+++ b/docs/en/data_source/file_external_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # File external table
@@ -17,7 +17,7 @@ This feature is supported from StarRocks v2.5.
 
 ## Limits
 
-- File external tables must be created in databases within the [default_catalog](../data_source/catalog/default_catalog.md). You can run [SHOW CATALOGS](../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) to query catalogs created in the cluster.
+- File external tables must be created in databases within the [default_catalog](../data_source/catalog/default_catalog.md). You can run [SHOW CATALOGS](../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) to query catalogs created in the cluster.
 - Only Parquet, ORC, Avro, RCFile, and SequenceFile data files are supported.
 - You can only use file external tables to query data in the target data file. Data write operations such as INSERT, DELETE, and DROP are not supported.
 
@@ -27,7 +27,7 @@ Before you create a file external table, you must configure your StarRocks clust
 
 ## Create a database (Optional)
 
-After connecting to your StarRocks cluster, you can create a file external table in an existing database or create a new database to manage file external tables. To query existing databases in the cluster, run [SHOW DATABASES](../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md). Then you can run `USE <db_name>` to switch to the target database.
+After connecting to your StarRocks cluster, you can create a file external table in an existing database or create a new database to manage file external tables. To query existing databases in the cluster, run [SHOW DATABASES](../sql-reference/sql-statements/Database/SHOW_DATABASES.md). Then you can run `USE <db_name>` to switch to the target database.
 
 The syntax for creating a database is as follows.
 
@@ -285,4 +285,4 @@ SELECT * FROM t0;
 
 ## Manage file external tables
 
-You can view the schema of the table using [DESC](../sql-reference/sql-statements/Utility/DESCRIBE.md) or drop the table using [DROP TABLE](../sql-reference/sql-statements/data-definition/DROP_TABLE.md).
+You can view the schema of the table using [DESC](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md) or drop the table using [DROP TABLE](../sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md).
diff --git a/docs/en/data_source/icebergtutorial.mdx b/docs/en/data_source/icebergtutorial.mdx
index 959608fed7a767..c1039b77f283ee 100644
--- a/docs/en/data_source/icebergtutorial.mdx
+++ b/docs/en/data_source/icebergtutorial.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: English
+displayed_sidebar: docs
 sidebar_label: Iceberg Lakehouse tutorial
 title: Iceberg Lakehouse tutorial
 description: Iceberg lakehouse in Docker
diff --git a/docs/en/deployment/deploy_manually.md b/docs/en/deployment/deploy_manually.md
index 0efe90c0386964..695f34737e14ac 100644
--- a/docs/en/deployment/deploy_manually.md
+++ b/docs/en/deployment/deploy_manually.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Deploy StarRocks manually
@@ -373,7 +373,7 @@ The following procedures are performed on a MySQL client. You must have MySQL cl
 
    If the field `Alive` is `true`, this CN node is properly started and added to the cluster.
 
-   After CNs are properly started and you want to use CNs during queries, set the system variables `SET prefer_compute_node = true;` and `SET use_compute_nodes = -1;`. For more information, see [System variables](../reference/System_variable.md#descriptions-of-variables).
+   After CNs are properly started and you want to use CNs during queries, set the system variables `SET prefer_compute_node = true;` and `SET use_compute_nodes = -1;`. For more information, see [System variables](../sql-reference/System_variable.md#descriptions-of-variables).
 
 ## Step 5: (Optional) Deploy a high-availability FE cluster
 
@@ -400,7 +400,7 @@ A high-availability FE cluster requires at least THREE Follower FE nodes in the
    > **NOTE**
    >
    > - You can use the preceding command to add a single Follower FE nodes each time.
-   > - If you want to add Observer FE nodes, execute `ALTER SYSTEM ADD OBSERVER "<fe_address>:<edit_log_port>"=`. For detailed instructions, see [ALTER SYSTEM - FE](../sql-reference/sql-statements/Administration/ALTER_SYSTEM.md).
+   > - If you want to add Observer FE nodes, execute `ALTER SYSTEM ADD OBSERVER "<fe_address>:<edit_log_port>"=`. For detailed instructions, see [ALTER SYSTEM - FE](../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md).
 
 3. Launch a terminal on the new FE instance, create a dedicated directory for metadata storage, navigate to the directory that stores the StarRocks FE deployment files, and modify the FE configuration file **fe/conf/fe.conf**. For more instructions, see [Step 1: Start the Leader FE node](#step-1-start-the-leader-fe-node). Basically, you can repeat the procedures in Step 1 **except for the command used to start the FE node**.
   
diff --git a/docs/en/deployment/deployment_overview.md b/docs/en/deployment/deployment_overview.md
index 0aa296b668a78a..b4a848a9f43865 100644
--- a/docs/en/deployment/deployment_overview.md
+++ b/docs/en/deployment/deployment_overview.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Deployment overview
diff --git a/docs/en/deployment/deployment_prerequisites.md b/docs/en/deployment/deployment_prerequisites.md
index 4a3b882141ed38..e3741b32cd5006 100644
--- a/docs/en/deployment/deployment_prerequisites.md
+++ b/docs/en/deployment/deployment_prerequisites.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Deployment prerequisites
diff --git a/docs/en/deployment/downgrade.md b/docs/en/deployment/downgrade.md
index f764b97043d20d..c227460ffb05a3 100644
--- a/docs/en/deployment/downgrade.md
+++ b/docs/en/deployment/downgrade.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Downgrade StarRocks
@@ -99,7 +99,7 @@ After the compatibility configuration and the availability test, you can downgra
 
 1. Create a metadata snapshot.
 
-   a. Run [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/Administration/ALTER_SYSTEM.md) to create a meatedata snapshot.
+   a. Run [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) to create a meatedata snapshot.
 
    b. You can check whether the image file has been synchronized by viewing the log file **fe.log** of the Leader FE. A record of log like "push image.* from subdir [] to other nodes. totally xx nodes, push successful xx nodes" suggests that the image file has been successfully synchronized. 
 
diff --git a/docs/en/deployment/environment_configurations.md b/docs/en/deployment/environment_configurations.md
index d6294b74f81331..94172f26152737 100644
--- a/docs/en/deployment/environment_configurations.md
+++ b/docs/en/deployment/environment_configurations.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Check environment configurations
diff --git a/docs/en/deployment/helm.md b/docs/en/deployment/helm.md
index c806a45d83583a..9a294e35f46653 100644
--- a/docs/en/deployment/helm.md
+++ b/docs/en/deployment/helm.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Deploy StarRocks with Helm
diff --git a/docs/en/deployment/plan_cluster.md b/docs/en/deployment/plan_cluster.md
index 85056d40832367..397affe891bdb9 100644
--- a/docs/en/deployment/plan_cluster.md
+++ b/docs/en/deployment/plan_cluster.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Plan StarRocks cluster
diff --git a/docs/en/deployment/post_deployment_setup.md b/docs/en/deployment/post_deployment_setup.md
index f0eacfc2170158..f5b85773fdb853 100644
--- a/docs/en/deployment/post_deployment_setup.md
+++ b/docs/en/deployment/post_deployment_setup.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Post-deployment setup
@@ -77,7 +77,7 @@ To allow your StarRocks cluster to work properly in production, you need to set
   SET GLOBAL pipeline_dop = 0;
   ```
 
-For more information about system variables, see [System variables](../reference/System_variable.md).
+For more information about system variables, see [System variables](../sql-reference/System_variable.md).
 
 ## Set user property
 
diff --git a/docs/en/deployment/prepare_deployment_files.md b/docs/en/deployment/prepare_deployment_files.md
index 19db5d10c2a45f..37cc99e37bc506 100644
--- a/docs/en/deployment/prepare_deployment_files.md
+++ b/docs/en/deployment/prepare_deployment_files.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Prepare deployment files
diff --git a/docs/en/deployment/shared_data/azure.md b/docs/en/deployment/shared_data/azure.md
index a763ff7fb432b0..ceaadffccbf2e9 100644
--- a/docs/en/deployment/shared_data/azure.md
+++ b/docs/en/deployment/shared_data/azure.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Use Azure Blob Storage for shared-data
@@ -19,7 +19,7 @@ import SharedDataUse from '../../_assets/commonMarkdown/sharedDataUse.md'
 
 The deployment of a shared-data StarRocks cluster is similar to that of a shared-nothing StarRocks cluster. The only difference is that you need to deploy CNs instead of BEs in a shared-data cluster. This section only lists the extra FE and CN configuration items you need to add in the configuration files of FE and CN **fe.conf** and **cn.conf** when you deploy a shared-data StarRocks cluster. For detailed instructions on deploying a StarRocks cluster, see [Deploy StarRocks](../../deployment/deploy_manually.md).
 
-> **Note**
+> **NOTE**
 >
 > Do not start the cluster until after it is configured for shared-storage in the next section of this document.
 
@@ -29,8 +29,9 @@ Before starting the cluster configure the FEs and CNs. An example configuration
 
 ### Example FE configuration for Azure Blob Storage
 
-The example shared-data additions for your `fe.conf` can be added to the `fe.conf` file on each
-of your FE nodes.
+The example shared-data additions for your `fe.conf` can be added to the `fe.conf` file on each of your FE nodes.
+
+- If you use the shared key to access Azure Blob Storage, add the following configuration items:
 
   ```Properties
   run_mode = shared_data
@@ -73,13 +74,12 @@ of your FE nodes.
 The running mode of the StarRocks cluster. Valid values:
 
 - `shared_data`
-- `shared_nothing` (Default).
+- `shared_nothing` (Default)
 
-> **Note**
->
-> You cannot adopt the `shared_data` and `shared_nothing` modes simultaneously for a StarRocks cluster. Mixed deployment is not supported.
+> **NOTE**
 >
-> Do not change `run_mode` after the cluster is deployed. Otherwise, the cluster fails to restart. The transformation from a shared-nothing cluster to a shared-data cluster or vice versa is not supported.
+> - You cannot adopt the `shared_data` and `shared_nothing` modes simultaneously for a StarRocks cluster. Mixed deployment is not supported.
+> - Do not change `run_mode` after the cluster is deployed. Otherwise, the cluster fails to restart. The transformation from a shared-nothing cluster to a shared-data cluster or vice versa is not supported.
 
 #### cloud_native_meta_port
 
@@ -105,13 +105,14 @@ Supported from v3.1.0.
 The type of object storage you use. In shared-data mode, StarRocks supports storing data in Azure Blob (supported from v3.1.1 onwards), and object storages that are compatible with the S3 protocol (such as AWS S3, Google GCP, and MinIO). Valid value:
 
 - `S3` (Default)
-- `AZBLOB`.
+- `AZBLOB`
+- `HDFS`
 
-> Note
->
-> If you specify this parameter as `S3`, you must add the parameters prefixed by `aws_s3`.
+> **NOTE**
 >
-> If you specify this parameter as `AZBLOB`, you must add the parameters prefixed by `azure_blob`.
+> - If you specify this parameter as `S3`, you must add the parameters prefixed by `aws_s3`.
+> - If you specify this parameter as `AZBLOB`, you must add the parameters prefixed by `azure_blob`.
+> - If you specify this parameter as `HDFS`, you must add the parameter `cloud_native_hdfs_url`.
 
 #### azure_blob_path
 
@@ -129,7 +130,7 @@ The Shared Key used to authorize requests for your Azure Blob Storage.
 
 The shared access signatures (SAS) used to authorize requests for your Azure Blob Storage.
 
-> **Note**
+> **NOTE**
 >
 > Only credential-related configuration items can be modified after your shared-data StarRocks cluster is created. If you changed the original storage path-related configuration items, the databases and tables you created before the change become read-only, and you cannot load data into them.
 
diff --git a/docs/en/deployment/shared_data/feature-support-shared-data.md b/docs/en/deployment/shared_data/feature-support-shared-data.md
index 604aaa54d7a341..74c66f98706739 100644
--- a/docs/en/deployment/shared_data/feature-support-shared-data.md
+++ b/docs/en/deployment/shared_data/feature-support-shared-data.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_label: "Feature Support"
 ---
 
@@ -182,7 +182,7 @@ CANCEL COMPACTION WHERE TXN_ID = 123;
 
 ### Manual Compaction
 
-From v3.1, StarRocks offers a SQL statement for manual Compaction. You can specify the table or partitions for compaction. For more information, refer to [Manual Compaction](../../sql-reference/sql-statements/data-definition/ALTER_TABLE.md#manual-compaction).
+From v3.1, StarRocks offers a SQL statement for manual Compaction. You can specify the table or partitions for compaction. For more information, refer to [Manual Compaction](../../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md#manual-compaction).
 
 ## Primary Key tables
 
diff --git a/docs/en/deployment/shared_data/gcs.md b/docs/en/deployment/shared_data/gcs.md
index c3c26947db2211..9ecae2d532ef58 100644
--- a/docs/en/deployment/shared_data/gcs.md
+++ b/docs/en/deployment/shared_data/gcs.md
@@ -1,8 +1,8 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
-# Deploy StarRocks using GCS
+# Use GCS for shared-data
 
 import SharedDataIntro from '../../_assets/commonMarkdown/sharedDataIntro.md'
 import SharedDataCNconf from '../../_assets/commonMarkdown/sharedDataCNconf.md'
@@ -19,7 +19,7 @@ import SharedDataUse from '../../_assets/commonMarkdown/sharedDataUse.md'
 
 The deployment of a shared-data StarRocks cluster is similar to that of a shared-nothing StarRocks cluster. The only difference is that you need to deploy CNs instead of BEs in a shared-data cluster. This section only lists the extra FE and CN configuration items you need to add in the configuration files of FE and CN **fe.conf** and **cn.conf** when you deploy a shared-data StarRocks cluster. For detailed instructions on deploying a StarRocks cluster, see [Deploy StarRocks](../../deployment/deploy_manually.md).
 
-> **Note**
+> **NOTE**
 >
 > Do not start the cluster until after it is configured for shared-storage in the next section of this document.
 
@@ -29,28 +29,25 @@ Before starting the cluster configure the FEs and CNs. An example configuration
 
 ### Example FE configuration for GCS
 
-The example shared-data additions for your `fe.conf` can be added to the `fe.conf` file on each
-of your FE nodes. Because GCS storage is accessed using the
-[Cloud Storage XML API](https://cloud.google.com/storage/docs/xml-api/overview), the parameters
-use the prefix `aws_s3`.
+The example shared-data additions for your `fe.conf` can be added to the `fe.conf` file on each of your FE nodes. Because GCS storage is accessed using the [Cloud Storage XML API](https://cloud.google.com/storage/docs/xml-api/overview), the parameters use the prefix `aws_s3`.
 
-  ```Properties
-  run_mode = shared_data
-  cloud_native_meta_port = <meta_port>
-  cloud_native_storage_type = S3
+```Properties
+run_mode = shared_data
+cloud_native_meta_port = <meta_port>
+cloud_native_storage_type = S3
 
-  # For example, testbucket/subpath
-  aws_s3_path = <s3_path>
+# For example, testbucket/subpath
+aws_s3_path = <s3_path>
 
-  # For example: us-east1
-  aws_s3_region = <region>
+# For example: us-east1
+aws_s3_region = <region>
 
-  # For example: https://storage.googleapis.com
-  aws_s3_endpoint = <endpoint_url>
+# For example: https://storage.googleapis.com
+aws_s3_endpoint = <endpoint_url>
 
-  aws_s3_access_key = <HMAC access_key>
-  aws_s3_secret_key = <HMAC secret_key>
-  ```
+aws_s3_access_key = <HMAC access_key>
+aws_s3_secret_key = <HMAC secret_key>
+```
 
 ### All FE parameters related to shared-storage with GCS
 
@@ -59,13 +56,12 @@ use the prefix `aws_s3`.
 The running mode of the StarRocks cluster. Valid values:
 
 - `shared_data`
-- `shared_nothing` (Default).
+- `shared_nothing` (Default)
 
-> **Note**
+> **NOTE**
 >
-> You cannot adopt the `shared_data` and `shared_nothing` modes simultaneously for a StarRocks cluster. Mixed deployment is not supported.
->
-> Do not change `run_mode` after the cluster is deployed. Otherwise, the cluster fails to restart. The transformation from a shared-nothing cluster to a shared-data cluster or vice versa is not supported.
+> - You cannot adopt the `shared_data` and `shared_nothing` modes simultaneously for a StarRocks cluster. Mixed deployment is not supported.
+> - Do not change `run_mode` after the cluster is deployed. Otherwise, the cluster fails to restart. The transformation from a shared-nothing cluster to a shared-data cluster or vice versa is not supported.
 
 #### cloud_native_meta_port
 
@@ -91,7 +87,14 @@ Supported from v3.1.0.
 The type of object storage you use. In shared-data mode, StarRocks supports storing data in Azure Blob (supported from v3.1.1 onwards), and object storages that are compatible with the S3 protocol (such as AWS S3, Google GCS, and MinIO). Valid value:
 
 - `S3` (Default)
-- `AZBLOB`.
+- `AZBLOB`
+- `HDFS`
+
+> **NOTE**
+>
+> - If you specify this parameter as `S3`, you must add the parameters prefixed by `aws_s3`.
+> - If you specify this parameter as `AZBLOB`, you must add the parameters prefixed by `azure_blob`.
+> - If you specify this parameter as `HDFS`, you must add the parameter `cloud_native_hdfs_url`.
 
 #### aws_s3_path
 
@@ -110,7 +113,7 @@ The region in which your S3 bucket resides, for example, `us-west-2`.
 Whether to use Instance Profile and Assumed Role as credential methods for accessing GCS. Valid values:
 
 - `true`
-- `false` (Default).
+- `false` (Default)
 
 If you use IAM user-based credential (Access Key and Secret Key) to access GCS, you must specify this item as `false`, and specify `aws_s3_access_key` and `aws_s3_secret_key`.
 
@@ -136,7 +139,7 @@ The ARN of the IAM role that has privileges on your GCS bucket in which your dat
 
 The external ID of the AWS account that is used for cross-account access to your GCS bucket.
 
-> **Note**
+> **NOTE**
 >
 > Only credential-related configuration items can be modified after your shared-data StarRocks cluster is created. If you changed the original storage path-related configuration items, the databases and tables you created before the change become read-only, and you cannot load data into them.
 
@@ -156,7 +159,7 @@ enable_load_volume_from_conf = false
 
 <SharedDataUseIntro />
 
-The following example creates a storage volume `def_volume` for a GCS bucket `defaultbucket` with an HMAC Access Key and Secret Key, enables the [Partitioned Prefix](../../sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md#partitioned-prefix) feature, and sets it as the default storage volume:
+The following example creates a storage volume `def_volume` for a GCS bucket `defaultbucket` with an HMAC Access Key and Secret Key, enables the [Partitioned Prefix](../../sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md#partitioned-prefix) feature, and sets it as the default storage volume:
 
 ```SQL
 CREATE STORAGE VOLUME def_volume
diff --git a/docs/en/deployment/shared_data/hdfs.md b/docs/en/deployment/shared_data/hdfs.md
index 532ee382a31104..948647e706e706 100644
--- a/docs/en/deployment/shared_data/hdfs.md
+++ b/docs/en/deployment/shared_data/hdfs.md
@@ -1,5 +1,124 @@
 ---
-unlisted: true
+displayed_sidebar: docs
 ---
 
-This document only exists in the Chinese docs
+# Use HDFS for shared-data
+
+import SharedDataIntro from '../../_assets/commonMarkdown/sharedDataIntro.md'
+import SharedDataCNconf from '../../_assets/commonMarkdown/sharedDataCNconf.md'
+import SharedDataUseIntro from '../../_assets/commonMarkdown/sharedDataUseIntro.md'
+import SharedDataUse from '../../_assets/commonMarkdown/sharedDataUse.md'
+
+<SharedDataIntro />
+
+## Architecture
+
+![Shared-data Architecture](../../_assets/share_data_arch.png)
+
+## Deploy a shared-data StarRocks cluster
+
+The deployment of a shared-data StarRocks cluster is similar to that of a shared-nothing StarRocks cluster. The only difference is that you need to deploy CNs instead of BEs in a shared-data cluster. This section only lists the extra FE and CN configuration items you need to add in the configuration files of FE and CN **fe.conf** and **cn.conf** when you deploy a shared-data StarRocks cluster. For detailed instructions on deploying a StarRocks cluster, see [Deploy StarRocks](../../deployment/deploy_manually.md).
+
+> **NOTE**
+>
+> Do not start the cluster until after it is configured for shared-storage in the next section of this document.
+
+## Configure FE nodes for shared-data StarRocks
+
+Before starting FEs, add the following configuration items in the FE configuration file **fe.conf**.
+
+### Example FE configurations for HDFS
+
+These are example shared-data additions for your `fe.conf` file on each of your FE nodes.
+
+```Properties
+run_mode = shared_data
+cloud_native_meta_port = <meta_port>
+cloud_native_storage_type = HDFS
+
+# Example: hdfs://127.0.0.1:9000/user/starrocks/
+cloud_native_hdfs_url = <hdfs_url>
+```
+
+### All FE parameters related to shared-storage with HDFS
+
+#### run_mode
+
+The running mode of the StarRocks cluster. Valid values:
+
+- `shared_data`
+- `shared_nothing` (Default)
+
+> **NOTE**
+>
+> - You cannot adopt the `shared_data` and `shared_nothing` modes simultaneously for a StarRocks cluster. Mixed deployment is not supported.
+> - Do not change `run_mode` after the cluster is deployed. Otherwise, the cluster fails to restart. The transformation from a shared-nothing cluster to a shared-data cluster or vice versa is not supported.
+
+#### cloud_native_meta_port
+
+The cloud-native meta service RPC port.
+
+- Default: `6090`
+
+#### enable_load_volume_from_conf
+
+Whether to allow StarRocks to create the default storage volume by using the object storage-related properties specified in the FE configuration file. Valid values:
+
+- `true` (Default) If you specify this item as `true` when creating a new shared-data cluster, StarRocks creates the built-in storage volume `builtin_storage_volume` using the object storage-related properties in the FE configuration file, and sets it as the default storage volume. However, if you have not specified the object storage-related properties, StarRocks fails to start.
+- `false` If you specify this item as `false` when creating a new shared-data cluster, StarRocks starts directly without creating the built-in storage volume. You must manually create a storage volume and set it as the default storage volume before creating any object in StarRocks. For more information, see [Create the default storage volume](#use-your-shared-data-starrocks-cluster).
+
+Supported from v3.1.0.
+
+> **CAUTION**
+>
+> We strongly recommend you leave this item as `true` while you are upgrading an existing shared-data cluster from v3.0. If you specify this item as `false`, the databases and tables you created before the upgrade become read-only, and you cannot load data into them.
+
+#### cloud_native_storage_type
+
+The type of object storage you use. In shared-data mode, StarRocks supports storing data in Azure Blob (supported from v3.1.1 onwards), and object storages that are compatible with the S3 protocol (such as AWS S3, Google GCP, and MinIO). Valid value:
+
+- `S3` (Default)
+- `AZBLOB`
+- `HDFS`
+
+> **NOTE**
+>
+> - If you specify this parameter as `S3`, you must add the parameters prefixed by `aws_s3`.
+> - If you specify this parameter as `AZBLOB`, you must add the parameters prefixed by `azure_blob`.
+> - If you specify this parameter as `HDFS`, you must add the parameter `cloud_native_hdfs_url`.
+
+#### cloud_native_hdfs_url
+
+The URL of your HDFS storage, for example, `hdfs://127.0.0.1:9000/user/xxx/starrocks/`.
+
+> **NOTE**
+>
+> Only credential-related configuration items can be modified after your shared-data StarRocks cluster is created. If you changed the original storage path-related configuration items, the databases and tables you created before the change become read-only, and you cannot load data into them.
+
+If you want to create the default storage volume manually after the cluster is created, you only need to add the following configuration items:
+
+```Properties
+run_mode = shared_data
+cloud_native_meta_port = <meta_port>
+enable_load_volume_from_conf = false
+```
+
+## Configure CN nodes for shared-data StarRocks
+
+<SharedDataCNconf />
+
+## Use your shared-data StarRocks cluster
+
+<SharedDataUseIntro />
+
+The following example creates a storage volume `def_volume` for an HDFS storage, enables the storage volume, and sets it as the default storage volume:
+
+```SQL
+CREATE STORAGE VOLUME def_volume
+TYPE = HDFS
+LOCATIONS = ("hdfs://127.0.0.1:9000/user/starrocks/");
+
+SET def_volume AS DEFAULT STORAGE VOLUME;
+```
+
+<SharedDataUse />
diff --git a/docs/en/deployment/shared_data/minio.md b/docs/en/deployment/shared_data/minio.md
index bb452a6c664bc4..852c5489ff2e3f 100644
--- a/docs/en/deployment/shared_data/minio.md
+++ b/docs/en/deployment/shared_data/minio.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Use MinIO for shared-data
@@ -19,22 +19,49 @@ import SharedDataUse from '../../_assets/commonMarkdown/sharedDataUse.md'
 
 The deployment of a shared-data StarRocks cluster is similar to that of a shared-nothing StarRocks cluster. The only difference is that you need to deploy CNs instead of BEs in a shared-data cluster. This section only lists the extra FE and CN configuration items you need to add in the configuration files of FE and CN **fe.conf** and **cn.conf** when you deploy a shared-data StarRocks cluster. For detailed instructions on deploying a StarRocks cluster, see [Deploy StarRocks](../../deployment/deploy_manually.md).
 
-### Configure FE nodes for shared-data StarRocks
+> **NOTE**
+>
+> Do not start the cluster until after it is configured for shared-storage in the next section of this document.
+
+## Configure FE nodes for shared-data StarRocks
 
 Before starting FEs, add the following configuration items in the FE configuration file **fe.conf**.
 
+### Example FE configurations for MinIO
+
+These are example shared-data additions for your `fe.conf` file on each of your FE nodes. The parameters use the prefix `aws_s3`.
+
+```Properties
+run_mode = shared_data
+cloud_native_meta_port = <meta_port>
+cloud_native_storage_type = S3
+
+# Example: testbucket/subpath
+aws_s3_path = <s3_path>
+
+# Example: us-east1
+aws_s3_region = <region>
+
+# Example: http://172.26.xx.xxx:39000
+aws_s3_endpoint = <endpoint_url>
+
+aws_s3_access_key = <minio_access_key>
+aws_s3_secret_key = <minio_secret_key>
+```
+
+### All FE parameters related to shared-storage with MinIO
+
 #### run_mode
 
 The running mode of the StarRocks cluster. Valid values:
 
 - `shared_data`
-- `shared_nothing` (Default).
+- `shared_nothing` (Default)
 
-> **Note**
+> **NOTE**
 >
-> You cannot adopt the `shared_data` and `shared_nothing` modes simultaneously for a StarRocks cluster. Mixed deployment is not supported.
->
-> Do not change `run_mode` after the cluster is deployed. Otherwise, the cluster fails to restart. The transformation from a shared-nothing cluster to a shared-data cluster or vice versa is not supported.
+> - You cannot adopt the `shared_data` and `shared_nothing` modes simultaneously for a StarRocks cluster. Mixed deployment is not supported.
+> - Do not change `run_mode` after the cluster is deployed. Otherwise, the cluster fails to restart. The transformation from a shared-nothing cluster to a shared-data cluster or vice versa is not supported.
 
 #### cloud_native_meta_port
 
@@ -60,13 +87,14 @@ Supported from v3.1.0.
 The type of object storage you use. In shared-data mode, StarRocks supports storing data in Azure Blob (supported from v3.1.1 onwards), and object storages that are compatible with the S3 protocol (such as AWS S3, Google GCP, and MinIO). Valid value:
 
 - `S3` (Default)
-- `AZBLOB`.
+- `AZBLOB`
+- `HDFS`
 
-> Note
->
-> If you specify this parameter as `S3`, you must add the parameters prefixed by `aws_s3`.
+> **NOTE**
 >
-> If you specify this parameter as `AZBLOB`, you must add the parameters prefixed by `azure_blob`.
+> - If you specify this parameter as `S3`, you must add the parameters prefixed by `aws_s3`.
+> - If you specify this parameter as `AZBLOB`, you must add the parameters prefixed by `azure_blob`.
+> - If you specify this parameter as `HDFS`, you must add the parameter `cloud_native_hdfs_url`.
 
 #### aws_s3_path
 
@@ -85,14 +113,14 @@ The region in which your S3 bucket resides, for example, `us-west-2`.
 Whether to use the [AWS SDK default credentials provider chain](https://docs.aws.amazon.com/AWSJavaSDK/latest/javadoc/com/amazonaws/auth/DefaultAWSCredentialsProviderChain.html). Valid values:
 
 - `true`
-- `false` (Default).
+- `false` (Default)
 
 #### aws_s3_use_instance_profile
 
 Whether to use Instance Profile and Assumed Role as credential methods for accessing S3. Valid values:
 
 - `true`
-- `false` (Default).
+- `false` (Default)
 
 If you use IAM user-based credential (Access Key and Secret Key) to access S3, you must specify this item as `false`, and specify `aws_s3_access_key` and `aws_s3_secret_key`.
 
@@ -118,7 +146,7 @@ The ARN of the IAM role that has privileges on your S3 bucket in which your data
 
 The external ID of the AWS account that is used for cross-account access to your S3 bucket.
 
-> **Note**
+> **NOTE**
 >
 > Only credential-related configuration items can be modified after your shared-data StarRocks cluster is created. If you changed the original storage path-related configuration items, the databases and tables you created before the change become read-only, and you cannot load data into them.
 
@@ -138,7 +166,7 @@ enable_load_volume_from_conf = false
 
 <SharedDataUseIntro />
 
-The following example creates a storage volume `def_volume` for a MinIO bucket `defaultbucket` with Access Key and Secret Key credentials, enables the [Partitioned Prefix](../../sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md#partitioned-prefix) feature, and sets it as the default storage volume:
+The following example creates a storage volume `def_volume` for a MinIO bucket `defaultbucket` with Access Key and Secret Key credentials, enables the [Partitioned Prefix](../../sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md#partitioned-prefix) feature, and sets it as the default storage volume:
 
 ```SQL
 CREATE STORAGE VOLUME def_volume
diff --git a/docs/en/deployment/shared_data/s3.md b/docs/en/deployment/shared_data/s3.md
index 544520d201dca8..e2e33daf867585 100644
--- a/docs/en/deployment/shared_data/s3.md
+++ b/docs/en/deployment/shared_data/s3.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Use S3 for shared-data
@@ -19,7 +19,7 @@ import SharedDataUse from '../../_assets/commonMarkdown/sharedDataUse.md'
 
 The deployment of a shared-data StarRocks cluster is similar to that of a shared-nothing StarRocks cluster. The only difference is that you need to deploy CNs instead of BEs in a shared-data cluster. This section only lists the extra FE and CN configuration items you need to add in the configuration files of FE and CN **fe.conf** and **cn.conf** when you deploy a shared-data StarRocks cluster. For detailed instructions on deploying a StarRocks cluster, see [Deploy StarRocks](../../deployment/deploy_manually.md).
 
-> **Note**
+> **NOTE**
 >
 > Do not start the cluster until after it is configured for shared-storage in the next section of this document.
 
@@ -29,9 +29,7 @@ Before starting the cluster configure the FEs and CNs. Example configurations ar
 
 ### Example FE configurations for S3
 
-These are example shared-data additions for your `fe.conf` file on each
-of your FE nodes. The examples differ based on the AWS authentication
-method being used.
+These are example shared-data additions for your `fe.conf` file on each of your FE nodes. The examples differ based on the AWS authentication method being used.
 
 #### Default authentication credentials
 
@@ -180,13 +178,12 @@ Please make sure you have granted access to both FE and CN nodes in the cluster.
 The running mode of the StarRocks cluster. Valid values: 
 
 - `shared_data`
-- `shared_nothing` (Default).
+- `shared_nothing` (Default)
 
-> **Note**
+> **NOTE**
 >
-> You cannot adopt the `shared_data` and `shared_nothing` modes simultaneously for a StarRocks cluster. Mixed deployment is not supported.
->
-> Do not change `run_mode` after the cluster is deployed. Otherwise, the cluster fails to restart. The transformation from a shared-nothing cluster to a shared-data cluster or vice versa is not supported.
+> - You cannot adopt the `shared_data` and `shared_nothing` modes simultaneously for a StarRocks cluster. Mixed deployment is not supported.
+> - Do not change `run_mode` after the cluster is deployed. Otherwise, the cluster fails to restart. The transformation from a shared-nothing cluster to a shared-data cluster or vice versa is not supported.
 
 #### cloud_native_meta_port
 
@@ -212,7 +209,14 @@ Supported from v3.1.0.
 The type of object storage you use. In shared-data mode, StarRocks supports storing data in Azure Blob (supported from v3.1.1 onwards), and object storages that are compatible with the S3 protocol (such as AWS S3, Google GCP, and MinIO). Valid value:
 
 - `S3` (Default)
-- `AZBLOB`.
+- `AZBLOB`
+- `HDFS`
+
+> **NOTE**
+>
+> - If you specify this parameter as `S3`, you must add the parameters prefixed by `aws_s3`.
+> - If you specify this parameter as `AZBLOB`, you must add the parameters prefixed by `azure_blob`.
+> - If you specify this parameter as `HDFS`, you must add the parameter `cloud_native_hdfs_url`.
 
 #### aws_s3_path
 
@@ -231,14 +235,14 @@ The region in which your S3 bucket resides, for example, `us-west-2`.
 Whether to use the [AWS SDK default credentials provider chain](https://docs.aws.amazon.com/AWSJavaSDK/latest/javadoc/com/amazonaws/auth/DefaultAWSCredentialsProviderChain.html). Valid values:
 
 - `true`
-- `false` (Default).
+- `false` (Default)
 
 #### aws_s3_use_instance_profile
 
 Whether to use Instance Profile and Assumed Role as credential methods for accessing S3. Valid values:
 
 - `true`
-- `false` (Default).
+- `false` (Default)
 
 If you use IAM user-based credential (Access Key and Secret Key) to access S3, you must specify this item as `false`, and specify `aws_s3_access_key` and `aws_s3_secret_key`.
 
@@ -264,7 +268,7 @@ The ARN of the IAM role that has privileges on your S3 bucket in which your data
 
 The external ID of the AWS account that is used for cross-account access to your S3 bucket.
 
-> **Note**
+> **NOTE**
 >
 > Only credential-related configuration items can be modified after your shared-data StarRocks cluster is created. If you changed the original storage path-related configuration items, the databases and tables you created before the change become read-only, and you cannot load data into them.
 
@@ -277,13 +281,14 @@ enable_load_volume_from_conf = false
 ```
 
 ## Configure CN nodes for shared-data StarRocks
+
 <SharedDataCNconf />
 
 ## Use your shared-data StarRocks cluster
 
 <SharedDataUseIntro />
 
-The following example creates a storage volume `def_volume` for an AWS S3 bucket `defaultbucket` with the IAM user-based credential (Access Key and Secret Key), enables the [Partitioned Prefix](../../sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md#partitioned-prefix) feature, and sets it as the default storage volume:
+The following example creates a storage volume `def_volume` for an AWS S3 bucket `defaultbucket` with the IAM user-based credential (Access Key and Secret Key), enables the [Partitioned Prefix](../../sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md#partitioned-prefix) feature, and sets it as the default storage volume:
 
 ```SQL
 CREATE STORAGE VOLUME def_volume
diff --git a/docs/en/deployment/shared_data/shared_data.mdx b/docs/en/deployment/shared_data/shared_data.mdx
index e0874340747491..c25e75d1001026 100644
--- a/docs/en/deployment/shared_data/shared_data.mdx
+++ b/docs/en/deployment/shared_data/shared_data.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Deploying shared-data clusters
diff --git a/docs/en/deployment/sr_operator.md b/docs/en/deployment/sr_operator.md
index 979887f2c81a30..c6a9eea6a18eab 100644
--- a/docs/en/deployment/sr_operator.md
+++ b/docs/en/deployment/sr_operator.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Deploy StarRocks with Operator
diff --git a/docs/en/deployment/upgrade.md b/docs/en/deployment/upgrade.md
index 5255cfc84e4f23..91a8c4dbcd0e04 100644
--- a/docs/en/deployment/upgrade.md
+++ b/docs/en/deployment/upgrade.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Upgrade StarRocks
@@ -36,7 +36,7 @@ The version of StarRocks is represented by three numbers in the form **Major.Min
 >
 > Suppose you need to perform consecutive minor version upgrades, for example, 2.4->2.5->3.0->3.1->3.2, or you have downgraded your cluster after a failed upgrade and you want to upgrade the cluster again, for example, 2.5->3.0->2.5->3.0. To prevent metadata upgrade failure for some Follower FEs, perform the following steps between two consecutive upgrades or after the downgrade before the second trial of upgrade:
 >
-> 1. Run [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/Administration/ALTER_SYSTEM.md) to create a new image.
+> 1. Run [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) to create a new image.
 > 2. Wait for the new image to be synchronized to all Follower FEs.
 >
 > You can check whether the image file has been synchronized by viewing the log file **fe.log** of the Leader FE. A record of log like "push image.* from subdir [] to other nodes. totally xx nodes, push successful xx nodes" suggests that the image file has been successfully synchronized.
diff --git a/docs/en/developers/How_to_Contribute.md b/docs/en/developers/How_to_Contribute.md
index 8b42f45a9aec04..d1f296c76d88a7 100644
--- a/docs/en/developers/How_to_Contribute.md
+++ b/docs/en/developers/How_to_Contribute.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Contribute to StarRocks
diff --git a/docs/en/developers/build-starrocks/Build_in_docker.md b/docs/en/developers/build-starrocks/Build_in_docker.md
index bc3bfea0c79be6..9114f293baa5f7 100644
--- a/docs/en/developers/build-starrocks/Build_in_docker.md
+++ b/docs/en/developers/build-starrocks/Build_in_docker.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Compile StarRocks with Docker
diff --git a/docs/en/developers/build-starrocks/build_starrocks_on_ubuntu.md b/docs/en/developers/build-starrocks/build_starrocks_on_ubuntu.md
index 582d15af6ae034..b8d9bb652379a3 100644
--- a/docs/en/developers/build-starrocks/build_starrocks_on_ubuntu.md
+++ b/docs/en/developers/build-starrocks/build_starrocks_on_ubuntu.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Compile StarRocks on Ubuntu
diff --git a/docs/en/developers/build-starrocks/handbook.md b/docs/en/developers/build-starrocks/handbook.md
index 4446a8f87dbd95..5d0acc68ce0c3f 100644
--- a/docs/en/developers/build-starrocks/handbook.md
+++ b/docs/en/developers/build-starrocks/handbook.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # How to build StarRocks
diff --git a/docs/en/developers/code-style-guides/protobuf-guides.md b/docs/en/developers/code-style-guides/protobuf-guides.md
index 5dc877ba949c58..26ef490c123539 100644
--- a/docs/en/developers/code-style-guides/protobuf-guides.md
+++ b/docs/en/developers/code-style-guides/protobuf-guides.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Rules
diff --git a/docs/en/developers/code-style-guides/restful-api-standard.md b/docs/en/developers/code-style-guides/restful-api-standard.md
index c8716dae21b0d7..4375897fd302d0 100644
--- a/docs/en/developers/code-style-guides/restful-api-standard.md
+++ b/docs/en/developers/code-style-guides/restful-api-standard.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # StarRocks Restful API Standard
diff --git a/docs/en/developers/code-style-guides/thrift-guides.md b/docs/en/developers/code-style-guides/thrift-guides.md
index 20fd5ed43fe9ea..d999666d837958 100644
--- a/docs/en/developers/code-style-guides/thrift-guides.md
+++ b/docs/en/developers/code-style-guides/thrift-guides.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Rules
diff --git a/docs/en/developers/debuginfo.md b/docs/en/developers/debuginfo.md
index 5d8626c16cb671..bc3a0ac8682aba 100644
--- a/docs/en/developers/debuginfo.md
+++ b/docs/en/developers/debuginfo.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Use the debuginfo file for debugging
diff --git a/docs/en/developers/development-environment/IDEA.md b/docs/en/developers/development-environment/IDEA.md
index 0a841cf7d1c1fb..dffad085b2809c 100644
--- a/docs/en/developers/development-environment/IDEA.md
+++ b/docs/en/developers/development-environment/IDEA.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Setup StarRocks FE development environment on IDEA
diff --git a/docs/en/developers/development-environment/ide-setup.md b/docs/en/developers/development-environment/ide-setup.md
index 69a16774a724e4..4c6b384ee8e17f 100644
--- a/docs/en/developers/development-environment/ide-setup.md
+++ b/docs/en/developers/development-environment/ide-setup.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Setup IDE  for developing StarRocks
diff --git a/docs/en/developers/trace-tools/Trace.md b/docs/en/developers/trace-tools/Trace.md
index 0230c04323929e..fa3b960b9439bc 100644
--- a/docs/en/developers/trace-tools/Trace.md
+++ b/docs/en/developers/trace-tools/Trace.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 ### Background
diff --git a/docs/en/developers/trace-tools/query_trace_profile.md b/docs/en/developers/trace-tools/query_trace_profile.md
index 4d945cbdcaad72..42a09fec290d7c 100644
--- a/docs/en/developers/trace-tools/query_trace_profile.md
+++ b/docs/en/developers/trace-tools/query_trace_profile.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Query Trace Profile
diff --git a/docs/en/ecosystem_release/flink_connector.md b/docs/en/ecosystem_release/flink_connector.md
index 37fc4dc050350a..db12fda0cbb1a7 100644
--- a/docs/en/ecosystem_release/flink_connector.md
+++ b/docs/en/ecosystem_release/flink_connector.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Releases of StarRocks Connector for Flink
diff --git a/docs/en/ecosystem_release/kafka_connector.md b/docs/en/ecosystem_release/kafka_connector.md
index 4f8a32bc67b250..d086e77deb7f3f 100644
--- a/docs/en/ecosystem_release/kafka_connector.md
+++ b/docs/en/ecosystem_release/kafka_connector.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Releases of StarRocks Connector for Kafka
diff --git a/docs/en/ecosystem_release/spark_connector.md b/docs/en/ecosystem_release/spark_connector.md
index 15108238a623dc..9840880435724f 100644
--- a/docs/en/ecosystem_release/spark_connector.md
+++ b/docs/en/ecosystem_release/spark_connector.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Releases of StarRocks Connector for Spark
diff --git a/docs/en/ecosystem_release/starrocks-kubernetes-operator.md b/docs/en/ecosystem_release/starrocks-kubernetes-operator.md
index 6b6c5a99ef49bd..1117d15cef51b0 100644
--- a/docs/en/ecosystem_release/starrocks-kubernetes-operator.md
+++ b/docs/en/ecosystem_release/starrocks-kubernetes-operator.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Releases of Kubernetes Operator for StarRocks
diff --git a/docs/en/faq/Deploy_faq.md b/docs/en/faq/Deploy_faq.md
index 41b1ae9382b5ee..b5addaefff764d 100644
--- a/docs/en/faq/Deploy_faq.md
+++ b/docs/en/faq/Deploy_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Deployment
@@ -102,7 +102,7 @@ This error may occur during data loading into Primary Key tables. During data lo
 Patches to this bug (Primary Key tables do not support BE disk space re-balancing) is still under active development. Currently, you can fix it in either of the following two ways:
 
 - Manually distribute data among disks. For example, copy the directory from the disk with a high space usage to a disk with a larger space.
-- If the data on these disks is not important, we recommend you delete the disks and modify the disk path. If this error persists, use [TRUNCATE TABLE](../sql-reference/sql-statements/data-definition/TRUNCATE_TABLE.md) to clear data in the table to free up some space.
+- If the data on these disks is not important, we recommend you delete the disks and modify the disk path. If this error persists, use [TRUNCATE TABLE](../sql-reference/sql-statements/table_bucket_part_index/TRUNCATE_TABLE.md) to clear data in the table to free up some space.
 
 ## Why does the error "Fe type:unknown ,is ready :false." occur when I start an FE during the cluster restart?
 
diff --git a/docs/en/faq/Dump_query.md b/docs/en/faq/Dump_query.md
index 983082baa93e2a..c5d7bf73faa266 100644
--- a/docs/en/faq/Dump_query.md
+++ b/docs/en/faq/Dump_query.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # query_dump interface
diff --git a/docs/en/faq/Exporting_faq.md b/docs/en/faq/Exporting_faq.md
index 29995579ff6369..12861e46c15d2a 100644
--- a/docs/en/faq/Exporting_faq.md
+++ b/docs/en/faq/Exporting_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Data Export
diff --git a/docs/en/faq/Others.md b/docs/en/faq/Others.md
index d4096d103bebdf..c13c1ab76b578f 100644
--- a/docs/en/faq/Others.md
+++ b/docs/en/faq/Others.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Other FAQ
diff --git a/docs/en/faq/Sql_faq.md b/docs/en/faq/Sql_faq.md
index de1e7a449c46f2..c9dbb4a5d39384 100644
--- a/docs/en/faq/Sql_faq.md
+++ b/docs/en/faq/Sql_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # SQL query
@@ -125,7 +125,7 @@ No, use functions to change "2021-10" to "2021-10-01" and then use "2021-10-01"
 
 ## Where can I query the size of a StarRocks database or table?
 
-You can use the [SHOW DATA](../sql-reference/sql-statements/data-manipulation/SHOW_DATA.md) command.
+You can use the [SHOW DATA](../sql-reference/sql-statements/Database/SHOW_DATA.md) command.
 
 `SHOW DATA;` displays the data size and replicas of all tables in the current database.
 
diff --git a/docs/en/faq/datalake.mdx b/docs/en/faq/datalake.mdx
index 0164c6adc08cfc..83cd11f0d5d28c 100644
--- a/docs/en/faq/datalake.mdx
+++ b/docs/en/faq/datalake.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_label: Datalake FAQ
 title: Datalake FAQ
 ---
diff --git a/docs/en/faq/faq.mdx b/docs/en/faq/faq.mdx
index 9eb804591e91c9..581e2e0d053ce3 100644
--- a/docs/en/faq/faq.mdx
+++ b/docs/en/faq/faq.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # FAQs
diff --git a/docs/en/faq/loading/Broker_load_faq.md b/docs/en/faq/loading/Broker_load_faq.md
index 8587ffbf7d1f6c..fca8cbcc6666c6 100644
--- a/docs/en/faq/loading/Broker_load_faq.md
+++ b/docs/en/faq/loading/Broker_load_faq.md
@@ -1,12 +1,12 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Broker Load
 
 ## 1. Does Broker Load support re-running load jobs that have been run successfully and are in the FINISHED state?
 
-Broker Load does not support re-running load jobs that have been run successfully and are in the FINISHED state. Also, to prevent data loss and duplication, Broker Load does not allow reusing the labels of successfully run load jobs. You can use [SHOW LOAD](../../sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md) to view the history of load jobs and find the load job that you want to re-run. Then, you can copy the information of that load job and use the job information, except the label, to create another load job.
+Broker Load does not support re-running load jobs that have been run successfully and are in the FINISHED state. Also, to prevent data loss and duplication, Broker Load does not allow reusing the labels of successfully run load jobs. You can use [SHOW LOAD](../../sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md) to view the history of load jobs and find the load job that you want to re-run. Then, you can copy the information of that load job and use the job information, except the label, to create another load job.
 
 ## 2. When I load data from HDFS by using Broker Load, what do I do if the date and time values loaded into the destination StarRocks table are 8 hours later than the date and time values from the source data file?
 
@@ -18,11 +18,11 @@ The source data file has different column names than the destination StarRocks t
 
 ## 4. The Broker Load job does not report errors, but why am I unable to query the loaded data?
 
-Broker Load is an asynchronous loading method. The load job may still fail even if the load statement does not return errors. After you run a Broker Load job, you can use [SHOW LOAD](../../sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md) to view the result and `errmsg` of the load job. Then, you can modify the job configuration and retry.
+Broker Load is an asynchronous loading method. The load job may still fail even if the load statement does not return errors. After you run a Broker Load job, you can use [SHOW LOAD](../../sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md) to view the result and `errmsg` of the load job. Then, you can modify the job configuration and retry.
 
 ## 5. What do I do if the "failed to send batch" or "TabletWriter add batch with unknown id" error occurs?
 
-The amount of time taken to write the data exceeds the upper limit, causing a timeout error. To resolve this issue, modify the settings of the [session variable](../../reference/System_variable.md) `query_timeout` and the [BE configuration item](../../administration/management/BE_configuration.md#configure-be-static-parameters) `streaming_load_rpc_max_alive_time_sec` based on your business requirements.
+The amount of time taken to write the data exceeds the upper limit, causing a timeout error. To resolve this issue, modify the settings of the [session variable](../../sql-reference/System_variable.md) `query_timeout` and the [BE configuration item](../../administration/management/BE_configuration.md#configure-be-static-parameters) `streaming_load_rpc_max_alive_time_sec` based on your business requirements.
 
 ## 6. What do I do if the "LOAD-RUN-FAIL; msg:OrcScannerAdapter::init_include_columns. col name = xxx not found" error occurs?
 
@@ -37,7 +37,7 @@ SET
 )
 ```
 
-The preceding example maps the `tmp_c1` and `tmp_c2` columns of the source data file onto the `name` and `id`  columns of the destination StarRocks table, respectively. If you do not specify the `SET` clause, the column names specified in the `column_list` parameter are used to declare the column mapping. For more information, see [BROKER LOAD](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+The preceding example maps the `tmp_c1` and `tmp_c2` columns of the source data file onto the `name` and `id`  columns of the destination StarRocks table, respectively. If you do not specify the `SET` clause, the column names specified in the `column_list` parameter are used to declare the column mapping. For more information, see [BROKER LOAD](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 > **NOTICE**
 >
diff --git a/docs/en/faq/loading/DataX_faq.md b/docs/en/faq/loading/DataX_faq.md
index c37e8daa71e815..79a5ac7b30b338 100644
--- a/docs/en/faq/loading/DataX_faq.md
+++ b/docs/en/faq/loading/DataX_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # DataX
diff --git a/docs/en/faq/loading/Flink_connector_faq.md b/docs/en/faq/loading/Flink_connector_faq.md
index a813d1fa92ac05..23f9f75da48ae0 100644
--- a/docs/en/faq/loading/Flink_connector_faq.md
+++ b/docs/en/faq/loading/Flink_connector_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Flink Connector
diff --git a/docs/en/faq/loading/Insert_into_faq.md b/docs/en/faq/loading/Insert_into_faq.md
index 0519631af5d044..2cc8e0c1b478d7 100644
--- a/docs/en/faq/loading/Insert_into_faq.md
+++ b/docs/en/faq/loading/Insert_into_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Insert Into
diff --git a/docs/en/faq/loading/Loading_faq.md b/docs/en/faq/loading/Loading_faq.md
index 0a5a92c28486c4..cf2c545b9d45a9 100644
--- a/docs/en/faq/loading/Loading_faq.md
+++ b/docs/en/faq/loading/Loading_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Data loading common questions
@@ -48,7 +48,7 @@ Before you submit a load job, we recommend that you calculate the approximate am
 
 ## 3. What do I do if the "ETL_QUALITY_UNSATISFIED; msg:quality not good enough to cancel" error occurs?
 
-Execute [SHOW LOAD](../../sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md), and use the error URL in the returned execution result to view the error details.
+Execute [SHOW LOAD](../../sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md), and use the error URL in the returned execution result to view the error details.
 
 Common data quality errors are as follows:
 
diff --git a/docs/en/faq/loading/Routine_load_faq.md b/docs/en/faq/loading/Routine_load_faq.md
index 7476ae416244e0..d351f66e1dcc42 100644
--- a/docs/en/faq/loading/Routine_load_faq.md
+++ b/docs/en/faq/loading/Routine_load_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Routine Load
@@ -23,15 +23,15 @@ Parameter description:
 - `alive_be_number`: the number of BE nodes alive.
 - `partition_number`: the number of partitions to be consumed.
 - `desired_concurrent_number`: the desired load task parallelism for a Routine Load job. The default value is `3`. You can set a higher value for this parameter to increase the actual load task parallelism.
-  - If you have not created a Routine Load job, you need to set this parameter when using [CREATE ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md) to create a Routine Load job.
-  - If you have already created a Routine Load job, you need to use [ALTER ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD.md) to modify this parameter.
+  - If you have not created a Routine Load job, you need to set this parameter when using [CREATE ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md) to create a Routine Load job.
+  - If you have already created a Routine Load job, you need to use [ALTER ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md) to modify this parameter.
 - `max_routine_load_task_concurrent_num`: the default maximum task parallelism for a Routine Load job. The default value is `5`. This parameter is a an FE dynamic parameter. For more information and the configuration method, see [Parameter configuration](../../administration/management/FE_configuration.md#loading-and-unloading).
 
 Therefore, when the number of partitions to be consumed and the number of BE nodes alive are greater than the other two parameters, you can increase the values of `desired_concurrent_number` and `max_routine_load_task_concurrent_num` parameters to increase the actual load task parallelism.
 
 For example, the number of partitions to be consumed is `7`, the number of live BE nodes is `5`, and `max_routine_load_task_concurrent_num` is the default value `5`. At this time, if you need to increase the load task parallelism to the upper limit, you need to set `desired_concurrent_number` to `5` (the default value is `3`). Then, the actual task parallelism `min(5,7,5,5)` is computed to be `5`.
 
-For more parameter descriptions, see [CREATE ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md).
+For more parameter descriptions, see [CREATE ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md).
 
 **Method 2: Increase the amount of data consumed by a Routine Load task from one or more partitions.**
 
@@ -57,7 +57,7 @@ If the field `left_bytes` is less than `0`, it means that the amount of data con
 
   **Cause analysis:** The consumer offset of the load job does not exist in the Kafka partition.
 
-  **Solution:** You can execute [SHOW ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) and check the latest consumer offset of the load job in the parameter `Progress`. Then, you can verify if the corresponding message exists in the Kafka partition. If it does not exist, it may be because
+  **Solution:** You can execute [SHOW ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) and check the latest consumer offset of the load job in the parameter `Progress`. Then, you can verify if the corresponding message exists in the Kafka partition. If it does not exist, it may be because
 
   - The consumer offset specified when the load job is created is an offset in the future.
   - The message at the specified consumer offset in the Kafka partition has been removed before being consumed by the load job. It is recommended to set a reasonable Kafka log cleaning policy and parameters, such as `log.retention.hours and log.retention.bytes`, based on the loading speed.
@@ -68,9 +68,9 @@ If the field `left_bytes` is less than `0`, it means that the amount of data con
 
   **Solution:** You can troubleshoot and fix the issue by using error messages in the fields `ReasonOfStateChanged` and `ErrorLogUrls`.
 
-  - If it is caused by incorrect data format in the data source, you need to check the data format and fix the issue. After successfully fixing the issue, you can use [RESUME ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md) to resume the paused load job.
+  - If it is caused by incorrect data format in the data source, you need to check the data format and fix the issue. After successfully fixing the issue, you can use [RESUME ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md) to resume the paused load job.
 
-  - If it is because that StarRocks cannot parse the data format in the data source, you need to adjust the threshold `max_error_number`. You can first execute [SHOW ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) to view the value of `max_error_number`, and then use [ALTER ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD.md) to increase the threshold. After modifying the threshold, you can use [RESUME ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md) to resume the paused load job.
+  - If it is because that StarRocks cannot parse the data format in the data source, you need to adjust the threshold `max_error_number`. You can first execute [SHOW ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) to view the value of `max_error_number`, and then use [ALTER ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md) to increase the threshold. After modifying the threshold, you can use [RESUME ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md) to resume the paused load job.
 
 ## What do I do if the result of SHOW ROUTINE LOAD shows that the load job is in the `CANCELLED` state?
 
diff --git a/docs/en/faq/loading/Stream_load_faq.md b/docs/en/faq/loading/Stream_load_faq.md
index 137178bda195df..e120f99c32166f 100644
--- a/docs/en/faq/loading/Stream_load_faq.md
+++ b/docs/en/faq/loading/Stream_load_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Stream Load
@@ -15,7 +15,7 @@ In v2.5 and earlier, Stream Load does not support skipping the first few rows of
 - In the load command or statement, use `-H "where: <column_name> != '<column_name>'"` to filter out the first few rows of the CSV file. `<column_name>` is any of the column names held in the first few rows. Note that StarRocks first transforms and then filters the source data. Therefore, if the column names in the first few rows fail to be transformed into their matching destination data types, `NULL` values are returned for them. This means the destination StarRocks table cannot contain columns that are set to `NOT NULL`.
 - In the load command or statement, add `-H "max_filter_ratio:0.01"` to set a maximum error tolerance that is 1% or lower but can tolerate a few error rows, thereby allowing StarRocks to ignore the data transformation failures in the first few rows. In this case, the Stream Load job can still succeed even if `ErrorURL` is returned to indicate error rows. Do not set `max_filter_ratio` to a large value. If you set `max_filter_ratio` to a large value, some important data quality issues may be missed.
 
-From v3.0 onwards, Stream Load supports the `skip_header` parameter, which specifies whether to skip the first few rows of a CSV file. For more information,see [CSV parameters](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md#csv-parameters).
+From v3.0 onwards, Stream Load supports the `skip_header` parameter, which specifies whether to skip the first few rows of a CSV file. For more information,see [CSV parameters](../../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md#csv-parameters).
 
 ## 2. The data to be loaded into the partition column is not of standard DATE or INT type. For example, the data is in a format like 202106.00. How do I transform the data if I load it by using Stream Load?
 
diff --git a/docs/en/faq/loading/synchronize_mysql_into_sr.md b/docs/en/faq/loading/synchronize_mysql_into_sr.md
index 8fb6e83fe6e09b..ca04b0696a725b 100644
--- a/docs/en/faq/loading/synchronize_mysql_into_sr.md
+++ b/docs/en/faq/loading/synchronize_mysql_into_sr.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Synchronize data from MySQL in real time
diff --git a/docs/en/integrations/BI_integrations/FineBI.md b/docs/en/integrations/BI_integrations/FineBI.md
index 66c8832f02ab98..0fa5dd9e8852f2 100644
--- a/docs/en/integrations/BI_integrations/FineBI.md
+++ b/docs/en/integrations/BI_integrations/FineBI.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # FineBI
diff --git a/docs/en/integrations/BI_integrations/Hex.md b/docs/en/integrations/BI_integrations/Hex.md
index 5cf0febf7227b4..d50d646e17babc 100644
--- a/docs/en/integrations/BI_integrations/Hex.md
+++ b/docs/en/integrations/BI_integrations/Hex.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Hex
diff --git a/docs/en/integrations/BI_integrations/Metabase.md b/docs/en/integrations/BI_integrations/Metabase.md
index cac7d8dc8ebfb8..94b1075a54e407 100644
--- a/docs/en/integrations/BI_integrations/Metabase.md
+++ b/docs/en/integrations/BI_integrations/Metabase.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Metabase
diff --git a/docs/en/integrations/BI_integrations/Querybook.md b/docs/en/integrations/BI_integrations/Querybook.md
index ad85c5c42b1599..9ccba555569509 100644
--- a/docs/en/integrations/BI_integrations/Querybook.md
+++ b/docs/en/integrations/BI_integrations/Querybook.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Querybook
diff --git a/docs/en/integrations/BI_integrations/QuickBI.md b/docs/en/integrations/BI_integrations/QuickBI.md
index ee0af76fa4e476..aa6cc6a30b69b4 100644
--- a/docs/en/integrations/BI_integrations/QuickBI.md
+++ b/docs/en/integrations/BI_integrations/QuickBI.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # QuickBI
diff --git a/docs/en/integrations/BI_integrations/Superset.md b/docs/en/integrations/BI_integrations/Superset.md
index 759a3a1df90424..c78c7a71a2b261 100644
--- a/docs/en/integrations/BI_integrations/Superset.md
+++ b/docs/en/integrations/BI_integrations/Superset.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Apache Superset
diff --git a/docs/en/integrations/BI_integrations/Tableau_Desktop.md b/docs/en/integrations/BI_integrations/Tableau_Desktop.md
index aa4aa854c2be79..3ddae81e6f4cd1 100644
--- a/docs/en/integrations/BI_integrations/Tableau_Desktop.md
+++ b/docs/en/integrations/BI_integrations/Tableau_Desktop.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Tableau Desktop
diff --git a/docs/en/integrations/IDE_integrations/DBeaver.md b/docs/en/integrations/IDE_integrations/DBeaver.md
index 965290b9716f70..f522c3bbe8a5a6 100644
--- a/docs/en/integrations/IDE_integrations/DBeaver.md
+++ b/docs/en/integrations/IDE_integrations/DBeaver.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # DBeaver
diff --git a/docs/en/integrations/IDE_integrations/DataGrip.md b/docs/en/integrations/IDE_integrations/DataGrip.md
index cf048885b52323..889e844086fdbc 100644
--- a/docs/en/integrations/IDE_integrations/DataGrip.md
+++ b/docs/en/integrations/IDE_integrations/DataGrip.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # DataGrip
diff --git a/docs/en/integrations/IDE_integrations/Dataphin.md b/docs/en/integrations/IDE_integrations/Dataphin.md
index 7b0a7ca28e84e8..cb073bf9ecf200 100644
--- a/docs/en/integrations/IDE_integrations/Dataphin.md
+++ b/docs/en/integrations/IDE_integrations/Dataphin.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Dataphin
diff --git a/docs/en/integrations/IDE_integrations/jupysql.md b/docs/en/integrations/IDE_integrations/jupysql.md
index 0d7729424300fc..d5ab7df0cdf4bd 100644
--- a/docs/en/integrations/IDE_integrations/jupysql.md
+++ b/docs/en/integrations/IDE_integrations/jupysql.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 description: "Jupyter notebooks with StarRocks"
 ---
 
diff --git a/docs/en/integrations/authenticate_to_aws_resources.md b/docs/en/integrations/authenticate_to_aws_resources.md
index f39cf594458065..f024939d75546b 100644
--- a/docs/en/integrations/authenticate_to_aws_resources.md
+++ b/docs/en/integrations/authenticate_to_aws_resources.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_label: AWS
 description: "This topic describes how to authenticate with AWS"
 ---
@@ -40,19 +40,19 @@ Next step, create an IAM policy based on the type of AWS resource you want to ac
 
 For the IAM policy you will need to access a specific AWS resource, see the following sections:
 
-- [Batch load data from AWS S3](../reference/aws_iam_policies.md#batch-load-data-from-aws-s3)
-- [Read/write AWS S3](../reference/aws_iam_policies.md#readwrite-aws-s3)
-- [Integrate with AWS Glue](../reference/aws_iam_policies.md#integrate-with-aws-glue)
+- [Batch load data from AWS S3](../sql-reference/aws_iam_policies.md#batch-load-data-from-aws-s3)
+- [Read/write AWS S3](../sql-reference/aws_iam_policies.md#readwrite-aws-s3)
+- [Integrate with AWS Glue](../sql-reference/aws_iam_policies.md#integrate-with-aws-glue)
 
 ### Preparation for instance profile-based authentication
 
-Attach the [IAM policies](../reference/aws_iam_policies.md) for accessing the required AWS resources to the EC2 instance role.
+Attach the [IAM policies](../sql-reference/aws_iam_policies.md) for accessing the required AWS resources to the EC2 instance role.
 
 ### Preparation for assumed role-based authentication
 
 #### Create IAM roles and attach policies to them
 
-Create one or more IAM roles, depending on the AWS resources you want to access. See [Creating IAM roles](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_create.html). Then, attach the [IAM policies](../reference/aws_iam_policies.md) for accessing the required AWS resources to the IAM roles you create.
+Create one or more IAM roles, depending on the AWS resources you want to access. See [Creating IAM roles](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_create.html). Then, attach the [IAM policies](../sql-reference/aws_iam_policies.md) for accessing the required AWS resources to the IAM roles you create.
 
 For example, you want your StarRocks cluster to access AWS S3 and AWS Glue. In this situation, you can choose to create one IAM role (for example, `s3_assumed_role`), and attach the policy for accessing AWS S3 and the policy for accessing AWS Glue both to that role. Alternatively, you can choose to create two different IAM roles (for example, `s3_assumed_role` and `glue_assumed_role`), and attach these policies to the two different roles respectively (that is, attach the policy for accessing AWS S3 to `s3_assumed_role` and the policy for accessing AWS Glue to `glue_assumed_role`).
 
@@ -118,7 +118,7 @@ Configure your EC2 instance role as follows:
 
 Create an IAM user. See [Creating an IAM user in your AWS account](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_users_create.html).
 
-Then, attach the [IAM policies](../reference/aws_iam_policies.md) for accessing the required AWS resources to the IAM user you create.
+Then, attach the [IAM policies](../sql-reference/aws_iam_policies.md) for accessing the required AWS resources to the IAM user you create.
 
 ## Comparison between authentication methods
 
@@ -352,7 +352,7 @@ PROPERTIES
 
 You can use LOAD LABEL to load data from AWS S3.
 
-The following examples load the data from all Parquet data files stored in the `s3a://test-bucket/test_brokerload_ingestion` path into the `test_ingestion_2` table in an existing database named `test_s3_db`. For detailed syntax and parameters, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+The following examples load the data from all Parquet data files stored in the `s3a://test-bucket/test_brokerload_ingestion` path into the `test_ingestion_2` table in an existing database named `test_s3_db`. For detailed syntax and parameters, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 #### Instance profile-based authentication
 
diff --git a/docs/en/integrations/authenticate_to_azure_storage.md b/docs/en/integrations/authenticate_to_azure_storage.md
index 057acceb526b85..0b43f1c4620da6 100644
--- a/docs/en/integrations/authenticate_to_azure_storage.md
+++ b/docs/en/integrations/authenticate_to_azure_storage.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_label: Microsoft Azure Storage
 description: "This topic describes how to authenticate with Azure"
 ---
@@ -19,7 +19,7 @@ StarRocks supports the following types of Azure Storage accounts:
 - Azure Data Lake Storage Gen1
 - Azure Data Lake Storage Gen2
 
-In this topic, Hive catalog, file external table, and Broker Load are used as examples to show how StarRocks integrates with Azure Storage by using these types of Azure Storage accounts. For information about the parameters in the examples, see [Hive catalog](../data_source/catalog/hive_catalog.md), [File external table](../data_source/file_external_table.md), and [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+In this topic, Hive catalog, file external table, and Broker Load are used as examples to show how StarRocks integrates with Azure Storage by using these types of Azure Storage accounts. For information about the parameters in the examples, see [Hive catalog](../data_source/catalog/hive_catalog.md), [File external table](../data_source/file_external_table.md), and [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 ## Blob Storage
 
@@ -39,7 +39,7 @@ StarRocks supports using one of the following authentication methods to access B
 
 #### External catalog
 
-Configure `azure.blob.storage_account` and `azure.blob.shared_key` as follows in the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) statement:
+Configure `azure.blob.storage_account` and `azure.blob.shared_key` as follows in the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) statement:
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_azure
@@ -54,7 +54,7 @@ PROPERTIES
 
 #### File external table
 
-Configure `azure.blob.storage_account`, `azure.blob.shared_key`, and the file path (`path`) as follows in the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) statement:
+Configure `azure.blob.storage_account`, `azure.blob.shared_key`, and the file path (`path`) as follows in the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) statement:
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_azure
@@ -74,7 +74,7 @@ PROPERTIES
 
 #### Broker Load
 
-Configure `azure.blob.storage_account`, `azure.blob.shared_key`, and the file path (`DATA INFILE`) as follows in the [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) statement:
+Configure `azure.blob.storage_account`, `azure.blob.shared_key`, and the file path (`DATA INFILE`) as follows in the [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) statement:
 
 ```SQL
 LOAD LABEL test_db.label000
@@ -94,7 +94,7 @@ WITH BROKER
 
 #### External catalog
 
-Configure `azure.blob.storage_account`, `azure.blob.container`, and `azure.blob.sas_token` as follows in the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) statement:
+Configure `azure.blob.storage_account`, `azure.blob.container`, and `azure.blob.sas_token` as follows in the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) statement:
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_azure
@@ -110,7 +110,7 @@ PROPERTIES
 
 #### File external table
 
-Configure `azure.blob.storage_account`, `azure.blob.container`, `azure.blob.sas_token`, and the file path (`path`) as follows in the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) statement:
+Configure `azure.blob.storage_account`, `azure.blob.container`, `azure.blob.sas_token`, and the file path (`path`) as follows in the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) statement:
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_azure
@@ -131,7 +131,7 @@ PROPERTIES
 
 #### Broker load
 
-Configure `azure.blob.storage_account`, `azure.blob.container`, `azure.blob.sas_token`, and the file path (`DATA INFILE`) as follows in the [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) statement:
+Configure `azure.blob.storage_account`, `azure.blob.container`, `azure.blob.sas_token`, and the file path (`DATA INFILE`) as follows in the [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) statement:
 
 ```SQL
 LOAD LABEL test_db.label000
@@ -163,7 +163,7 @@ StarRocks supports using one of the following authentication methods to access D
 
 #### External catalog
 
-Configure `azure.adls1.use_managed_service_identity` as follows in the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) statement:
+Configure `azure.adls1.use_managed_service_identity` as follows in the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) statement:
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_azure
@@ -177,7 +177,7 @@ PROPERTIES
 
 #### File external table
 
-Configure `azure.adls1.use_managed_service_identity` and the file path (`path`) as follows in the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) statement:
+Configure `azure.adls1.use_managed_service_identity` and the file path (`path`) as follows in the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) statement:
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_azure
@@ -196,7 +196,7 @@ PROPERTIES
 
 #### Broker Load
 
-Configure `azure.adls1.use_managed_service_identity` and the file path (`DATA INFILE`) as follows in the [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) statement:
+Configure `azure.adls1.use_managed_service_identity` and the file path (`DATA INFILE`) as follows in the [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) statement:
 
 ```SQL
 LOAD LABEL test_db.label000
@@ -215,7 +215,7 @@ WITH BROKER
 
 #### External catalog
 
-Configure `azure.adls1.oauth2_client_id`, `azure.adls1.oauth2_credential`, and `azure.adls1.oauth2_endpoint` as follows in the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) statement:
+Configure `azure.adls1.oauth2_client_id`, `azure.adls1.oauth2_credential`, and `azure.adls1.oauth2_endpoint` as follows in the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) statement:
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_azure
@@ -231,7 +231,7 @@ PROPERTIES
 
 #### File external table
 
-Configure `azure.adls1.oauth2_client_id`, `azure.adls1.oauth2_credential`, `azure.adls1.oauth2_endpoint`, and the file path (`path`) as follows in the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) statement:
+Configure `azure.adls1.oauth2_client_id`, `azure.adls1.oauth2_credential`, `azure.adls1.oauth2_endpoint`, and the file path (`path`) as follows in the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) statement:
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_azure
@@ -252,7 +252,7 @@ PROPERTIES
 
 #### Broker Load
 
-Configure `azure.adls1.oauth2_client_id`, `azure.adls1.oauth2_credential`, `azure.adls1.oauth2_endpoint`, and the file path (`DATA INFILE`) as follows in the [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) statement:
+Configure `azure.adls1.oauth2_client_id`, `azure.adls1.oauth2_credential`, `azure.adls1.oauth2_endpoint`, and the file path (`DATA INFILE`) as follows in the [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) statement:
 
 ```SQL
 LOAD LABEL test_db.label000
@@ -294,7 +294,7 @@ Before you start, you need to make the following preparations:
 
 #### External catalog
 
-Configure `azure.adls2.oauth2_use_managed_identity`, `azure.adls2.oauth2_tenant_id`, and `azure.adls2.oauth2_client_id` as follows in the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) statement:
+Configure `azure.adls2.oauth2_use_managed_identity`, `azure.adls2.oauth2_tenant_id`, and `azure.adls2.oauth2_client_id` as follows in the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) statement:
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_azure
@@ -310,7 +310,7 @@ PROPERTIES
 
 #### File external table
 
-Configure `azure.adls2.oauth2_use_managed_identity`, `azure.adls2.oauth2_tenant_id`, `azure.adls2.oauth2_client_id`, and the file path (`path`) as follows in the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) statement:
+Configure `azure.adls2.oauth2_use_managed_identity`, `azure.adls2.oauth2_tenant_id`, `azure.adls2.oauth2_client_id`, and the file path (`path`) as follows in the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) statement:
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_azure
@@ -331,7 +331,7 @@ PROPERTIES
 
 #### Broker Load
 
-Configure `azure.adls2.oauth2_use_managed_identity`, `azure.adls2.oauth2_tenant_id`, `azure.adls2.oauth2_client_id`, and the file path (`DATA INFILE`) as follows in the [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) statement:
+Configure `azure.adls2.oauth2_use_managed_identity`, `azure.adls2.oauth2_tenant_id`, `azure.adls2.oauth2_client_id`, and the file path (`DATA INFILE`) as follows in the [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) statement:
 
 ```SQL
 LOAD LABEL test_db.label000
@@ -352,7 +352,7 @@ WITH BROKER
 
 #### External catalog
 
-Configure `azure.adls2.storage_account` and `azure.adls2.shared_key` as follows in the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) statement:
+Configure `azure.adls2.storage_account` and `azure.adls2.shared_key` as follows in the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) statement:
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_azure
@@ -367,7 +367,7 @@ PROPERTIES
 
 #### File external table
 
-Configure `azure.adls2.storage_account`, `azure.adls2.shared_key`, and the file path (`path`) as follows in the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) statement:
+Configure `azure.adls2.storage_account`, `azure.adls2.shared_key`, and the file path (`path`) as follows in the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) statement:
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_azure
@@ -387,7 +387,7 @@ PROPERTIES
 
 #### Broker Load
 
-Configure `azure.adls2.storage_account`, `azure.adls2.shared_key`, and the file path (`DATA INFILE`) as follows in the [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) statement:
+Configure `azure.adls2.storage_account`, `azure.adls2.shared_key`, and the file path (`DATA INFILE`) as follows in the [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) statement:
 
 ```SQL
 LOAD LABEL test_db.label000
@@ -409,7 +409,7 @@ Before you start, you need to create a service principal, create a role assignme
 
 #### External catalog
 
-Configure `azure.adls2.oauth2_client_id`, `azure.adls2.oauth2_client_secret`, and `azure.adls2.oauth2_client_endpoint` as follows in the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) statement:
+Configure `azure.adls2.oauth2_client_id`, `azure.adls2.oauth2_client_secret`, and `azure.adls2.oauth2_client_endpoint` as follows in the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) statement:
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_azure
@@ -425,7 +425,7 @@ PROPERTIES
 
 #### File external table
 
-Configure `azure.adls2.oauth2_client_id`, `azure.adls2.oauth2_client_secret`, `azure.adls2.oauth2_client_endpoint`, and the file path (`path`) as follows in the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) statement:
+Configure `azure.adls2.oauth2_client_id`, `azure.adls2.oauth2_client_secret`, `azure.adls2.oauth2_client_endpoint`, and the file path (`path`) as follows in the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) statement:
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_azure
@@ -446,7 +446,7 @@ PROPERTIES
 
 #### Broker Load
 
-Configure `azure.adls2.oauth2_client_id`, `azure.adls2.oauth2_client_secret`, `azure.adls2.oauth2_client_endpoint`, and the file path (`DATA INFILE`) as follows in the [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) statement:
+Configure `azure.adls2.oauth2_client_id`, `azure.adls2.oauth2_client_secret`, `azure.adls2.oauth2_client_endpoint`, and the file path (`DATA INFILE`) as follows in the [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) statement:
 
 ```SQL
 LOAD LABEL test_db.label000
diff --git a/docs/en/integrations/authenticate_to_gcs.md b/docs/en/integrations/authenticate_to_gcs.md
index acc1207e7bfcc8..20f9c462d9b301 100644
--- a/docs/en/integrations/authenticate_to_gcs.md
+++ b/docs/en/integrations/authenticate_to_gcs.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_label: Google Cloud Storage (GCS)
 description: "This topic describes how to authenticate with GCS"
 ---
@@ -31,7 +31,7 @@ StarRocks can authenticate to GCS in the following scenarios:
 - Query Parquet and ORC files in GCS.
 - Query [Hive](../data_source/catalog/hive_catalog.md), [Iceberg](../data_source/catalog/iceberg_catalog.md), [Hudi](../data_source/catalog/hudi_catalog.md), and [Delta Lake](../data_source/catalog/deltalake_catalog.md) tables in GCS.
 
-In this topic, [Hive catalog](../data_source/catalog/hive_catalog.md), [file external table](../data_source/file_external_table.md), and [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) are used as examples to show how StarRocks integrates with GCS in different scenarios. For information about `StorageCredentialParams` in the examples, see the "[Parameters](../integrations/authenticate_to_gcs.md#parameters)" section of this topic.
+In this topic, [Hive catalog](../data_source/catalog/hive_catalog.md), [file external table](../data_source/file_external_table.md), and [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) are used as examples to show how StarRocks integrates with GCS in different scenarios. For information about `StorageCredentialParams` in the examples, see the "[Parameters](../integrations/authenticate_to_gcs.md#parameters)" section of this topic.
 
 > **NOTE**
 >
@@ -39,7 +39,7 @@ In this topic, [Hive catalog](../data_source/catalog/hive_catalog.md), [file ext
 
 ### External catalog
 
-Use the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) statement to create a Hive catalog named `hive_catalog_gcs` as follows, in order to query files from GCS:
+Use the [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) statement to create a Hive catalog named `hive_catalog_gcs` as follows, in order to query files from GCS:
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_gcs
@@ -53,7 +53,7 @@ PROPERTIES
 
 ### File external table
 
-Use the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) statement to create a file external table named `external_table_gcs` as follows, in order to query a data file named `test_file_external_tbl` from GCS without any metastore:
+Use the [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) statement to create a file external table named `external_table_gcs` as follows, in order to query a data file named `test_file_external_tbl` from GCS without any metastore:
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_gcs
@@ -72,7 +72,7 @@ PROPERTIES
 
 ### Broker load
 
-Use the [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) statement to create a Broker Load job whose label is `test_db.label000`, in order to batch load data from GCS into the StarRocks table `target_table`:
+Use the [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) statement to create a Broker Load job whose label is `test_db.label000`, in order to batch load data from GCS into the StarRocks table `target_table`:
 
 ```SQL
 LOAD LABEL test_db.label000
diff --git a/docs/en/integrations/batch/Spark-connector-starrocks.mdx b/docs/en/integrations/batch/Spark-connector-starrocks.mdx
index 15a98d245f1326..0b94f7136bfca5 100644
--- a/docs/en/integrations/batch/Spark-connector-starrocks.mdx
+++ b/docs/en/integrations/batch/Spark-connector-starrocks.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_position: 2
 sidebar_label: StarRocks Spark Connector
 description: "Load using Spark DataFrames or Spark SQL"
diff --git a/docs/en/integrations/batch/SparkLoad.mdx b/docs/en/integrations/batch/SparkLoad.mdx
index f57cec32cf66a6..d3029494acd5e4 100644
--- a/docs/en/integrations/batch/SparkLoad.mdx
+++ b/docs/en/integrations/batch/SparkLoad.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_position: 2
 sidebar_label: Apache Spark Load
 description: "Load data in bulk using Spark Load"
diff --git a/docs/en/integrations/data_lakes.mdx b/docs/en/integrations/data_lakes.mdx
index 809acf06016690..cfb2e132d18182 100644
--- a/docs/en/integrations/data_lakes.mdx
+++ b/docs/en/integrations/data_lakes.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 import DataLakeIntro from '../_assets/commonMarkdown/datalakeIntro.md'
 
diff --git a/docs/en/integrations/hive_bitmap_udf.md b/docs/en/integrations/hive_bitmap_udf.md
deleted file mode 100644
index dd51b8d4f390bf..00000000000000
--- a/docs/en/integrations/hive_bitmap_udf.md
+++ /dev/null
@@ -1,213 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# Hive Bitmap UDF
-
-Hive Bitmap UDF provides UDFs that can be directly used in Hive. They can be used to generate Bitmap data and perform Bitmap-related calculations.
-
-The Bitmap format defined by Hive Bitmap UDF is consistent with the format in StarRocks and can be directly used for loading Bitmap data into StarRocks and unloading Bitmap data from StarRocks to Hive.
-
-Applicable scenarios:
-
-- The amount of raw data is large and directly loading these data into StarRocks for computing will cause tremendous pressure on StarRocks clusters. The desired solution is generating Bitmap data in Hive and then loading Bitmap into StarRocks.
-- Export the Bitmap data generated in StarRocks to Hive for other systems to use.
-
-Supported source and target data types:
-
-- v3.1 and later support loading and unloading data of these types: String, Base64, and Binary.
-- v2.5 and v3.0 only support loading and unloading of String and Base64 data.
-
-## Hive Bitmap UDFs that can be generated
-
-- com.starrocks.hive.udf.UDAFBitmapAgg
-
-  Combines multiple rows of non-null values in a column into one row of Bitmap values, which is equivalent to StarRocks' built-in aggregate function [bitmap_agg](../sql-reference/sql-functions/bitmap-functions/bitmap_agg.md).
-
-- com.starrocks.hive.udf.UDAFBitmapUnion
-
-  Calculates the union of a set of bitmaps, which is equivalent to StarRocks' built-in aggregate function [bitmap_union](../sql-reference/sql-functions/bitmap-functions/bitmap_union.md).
-
-- com.starrocks.hive.udf.UDFBase64ToBitmap
-
-  Converts a base64-encoded string into a bitmap, which is equivalent to StarRocks' built-in function [base64_to_bitmap](../sql-reference/sql-functions/bitmap-functions/base64_to_bitmap.md).
-
-- com.starrocks.hive.udf.UDFBitmapAnd
-
-  Calculates the intersection of two bitmaps, which is equivalent to StarRocks' built-in function [bitmap_and](../sql-reference/sql-functions/bitmap-functions/bitmap_and.md).
-
-- com.starrocks.hive.udf.UDFBitmapCount
-
-  Counts the number of values in the bitmap, which is equivalent to StarRocks' built-in function [bitmap_count](../sql-reference/sql-functions/bitmap-functions/bitmap_count.md).
-
-- com.starrocks.hive.udf.UDFBitmapFromString
-
-  Converts a comma-separated string to a bitmap, equivalent to StarRocks' built-in function [bitmap_from_string](../sql-reference/sql-functions/bitmap-functions/bitmap_from_string.md).
-
-- com.starrocks.hive.udf.UDFBitmapOr
-
-  Calculates the union of two bitmaps, equivalent to StarRocks' built-in function [bitmap_or](../sql-reference/sql-functions/bitmap-functions/bitmap_or.md).
-
-- com.starrocks.hive.udf.UDFBitmapToBase64
-
-  Converts Bitmap to Base64 string, equivalent to StarRocks' built-in function [bitmap_to_base64](../sql-reference/sql-functions/bitmap-functions/bitmap_to_base64.md).
-
-- com.starrocks.hive.udf.UDFBitmapToString
-
-  Converts a bitmap to a comma-separated string, equivalent to StarRocks' built-in function [bitmap_to_string](../sql-reference/sql-functions/bitmap-functions/bitmap_to_string.md).
-
-- com.starrocks.hive.udf.UDFBitmapXor
-
-  Calculates the set of unique elements in two Bitmaps, which is equivalent to StarRocks' built-in function [bitmap_xor](../sql-reference/sql-functions/bitmap-functions/bitmap_xor.md).
-
-## How to use
-
-1. Compile and generate Hive UDF on the FE.
-
-   ```bash
-   ./build.sh --hive-udf
-   ```
-
-   A JAR package `hive-udf-1.0.0.jar` will be generated in the `fe/hive-udf/` directory.
-
-2. Upload the JAR package to HDFS.
-
-   ```bash
-   hadoop  fs -put -f ./hive-udf-1.0.0.jar hdfs://<hdfs_ip>:<hdfs_port>/hive-udf-1.0.0.jar
-   ```
-
-3. Load the JAR package to Hive.
-
-   ```bash
-   hive> add jar hdfs://<hdfs_ip>:<hdfs_port>/hive-udf-1.0.0.jar;
-   ```
-
-4. Load UDF functions.
-
-   ```sql
-   hive> create temporary function bitmap_agg as 'com.starrocks.hive.udf.UDAFBitmapAgg';
-   hive> create temporary function bitmap_union as 'com.starrocks.hive.udf.UDAFBitmapUnion';
-   hive> create temporary function base64_to_bitmap as 'com.starrocks.hive.udf.UDFBase64ToBitmap';
-   hive> create temporary function bitmap_and as 'com.starrocks.hive.udf.UDFBitmapAnd';
-   hive> create temporary function bitmap_count as 'com.starrocks.hive.udf.UDFBitmapCount';
-   hive> create temporary function bitmap_from_string as 'com.starrocks.hive.udf.UDFBitmapFromString';
-   hive> create temporary function bitmap_or as 'com.starrocks.hive.udf.UDFBitmapOr';
-   hive> create temporary function bitmap_to_base64 as 'com.starrocks.hive.udf.UDFBitmapToBase64';
-   hive> create temporary function bitmap_to_string as 'com.starrocks.hive.udf.UDFBitmapToString';
-   hive> create temporary function bitmap_xor as 'com.starrocks.hive.udf.UDFBitmapXor';
-   ```
-
-## Usage examples
-
-### Generate Bitmap in Hive and load it into StarRocks in Binary format
-
-1. Create a Hive source table.
-
-   ```sql
-   hive> create table t_src(c1 bigint, c2 bigint) stored as parquet;
-
-   hive> insert into t_src values (1,1), (1,2), (1,3), (2,4), (2,5);
-
-   hive> select * from t_src;
-   1       1
-   1       2
-   1       3
-   2       4
-   2       5
-   ```
-
-2. Create a Hive bitmap table.
-
-   ```sql
-   hive> create table t_bitmap(c1 bigint, c2 binary) stored as parquet;
-   ```
-
-   Hive generates bitmap through UDFBitmapAgg and writes it into the bitmap table.
-
-   ```sql
-   hive> insert into t_bitmap select c1, bitmap_agg(c2) from t_src group by c1;
-   ```
-
-3. Create a StarRocks Bitmap table.
-
-   ```sql
-   mysql> create table t1(c1 int, c2 bitmap bitmap_union) aggregate key(c1)  distributed by hash(c1);
-   ```
-
-4. Load Bitmap data into StarRocks in different ways.
-
-   - Load data via the [files](../sql-reference/sql-functions/table-functions/files.md) function.
-
-   ```sql
-   mysql> insert into t1 select c1, bitmap_from_binary(c2) from files (
-       "path" = "hdfs://<hdfs_ip>:<hdfs_port>/<hdfs_db>/t_bitmap/*",
-       "format"="parquet",
-       "compression" = "uncompressed"
-       );
-   ```
-
-   - Load data via [Hive Catalog](../data_source/catalog/hive_catalog.md).
-
-   ```sql
-   mysql> insert into t1 select c1, bitmap_from_binary(c2) from hive_catalog_hms.xxx_db.t_bitmap;
-   ```
-
-5. View the results.
-
-   ```sql
-   mysql> select c1, bitmap_to_string(c2) from t1;                                                                                                                                                                                                                                   
-   +------+----------------------+                                                                                                                                                                                                                                                   
-   | c1   | bitmap_to_string(c2) |
-   +------+----------------------+
-   |    1 | 1,2,3                |
-   |    2 | 4,5                  |
-   +------+----------------------+
-   ```
-
-### Export Bitmap from StarRocks to Hive
-
-1. Create a Bitmap table in StarRocks and write data into this table.
-
-   ```sql
-   mysql> create table t1(c1 int, c2 bitmap bitmap_union) aggregate key(c1) buckets 3 distributed by hash(c1);
-
-   mysql> select c1, bitmap_to_string(c2) from t1;                                                                                                                                                                                                                                   
-   +------+----------------------+                                                                                                                                                                                                                                                   
-   | c1   | bitmap_to_string(c2) |
-   +------+----------------------+
-   |    1 | 1,2,3                |
-   |    2 | 4,5                  |
-   +------+----------------------+
-   ```
-
-2. Create a Bitmap table in Hive.
-
-   ```sql
-   hive> create table t_bitmap(c1 bigint, c2 binary) stored as parquet;
-   ```
-
-3. Export data in different ways.
-
-   - Export data via INSERT INTO FILES (Binary format).
-
-   ```sql
-   mysql> insert into files (
-       "path" = "hdfs://<hdfs_ip>:<hdfs_port>/<hdfs_db>/t_bitmap/",
-       "format"="parquet",
-       "compression" = "uncompressed"
-   ) select c1, bitmap_to_binary(c2) as c2 from t1;
-   ```
-
-   - Export data via [Hive Catalog](../data_source/catalog/hive_catalog.md) (Binary format).
-
-   ```sql
-   mysql> insert into hive_catalog_hms.<hdfs_db>.t_bitmap select c1, bitmap_to_binary(c2) from t1;
-   ```
-
-4. View results in Hive.
-
-   ```plain
-   hive> select c1, bitmap_to_string(c2) from t_bitmap;
-   1       1,2,3
-   2       4,5
-   ```
diff --git a/docs/en/integrations/integrations.mdx b/docs/en/integrations/integrations.mdx
index 39931997f02764..601efbd91edab9 100644
--- a/docs/en/integrations/integrations.mdx
+++ b/docs/en/integrations/integrations.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Integrations
diff --git a/docs/en/integrations/loading_tools/CloudCanal.md b/docs/en/integrations/loading_tools/CloudCanal.md
index 39d748d597b74b..3fb0a7ffc0b74e 100644
--- a/docs/en/integrations/loading_tools/CloudCanal.md
+++ b/docs/en/integrations/loading_tools/CloudCanal.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Load data using CloudCanal
diff --git a/docs/en/integrations/loading_tools/DataX-starrocks-writer.md b/docs/en/integrations/loading_tools/DataX-starrocks-writer.md
index b0e947608f2216..dfe8cfcb28ae59 100644
--- a/docs/en/integrations/loading_tools/DataX-starrocks-writer.md
+++ b/docs/en/integrations/loading_tools/DataX-starrocks-writer.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # DataX writer
diff --git a/docs/en/integrations/loading_tools/SMT.md b/docs/en/integrations/loading_tools/SMT.md
index 8edbfa1de58af8..aa28c9dc5ca29e 100644
--- a/docs/en/integrations/loading_tools/SMT.md
+++ b/docs/en/integrations/loading_tools/SMT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: English
+displayed_sidebar: docs
 ---
 
 # StarRocks Migration Tool (SMT) 
diff --git a/docs/en/integrations/loading_tools/loading_tools_integration.mdx b/docs/en/integrations/loading_tools/loading_tools_integration.mdx
index 9605a7abf1caa6..fe51f690a5697d 100644
--- a/docs/en/integrations/loading_tools/loading_tools_integration.mdx
+++ b/docs/en/integrations/loading_tools/loading_tools_integration.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 <head>
diff --git a/docs/en/integrations/other_integrations/datadog_support.md b/docs/en/integrations/other_integrations/datadog_support.md
index 9026644d2f444e..518f050f8ae254 100644
--- a/docs/en/integrations/other_integrations/datadog_support.md
+++ b/docs/en/integrations/other_integrations/datadog_support.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 description: Monitor with Datadog
 sidebar_label: Datadog
 ---
diff --git a/docs/en/integrations/streaming.mdx b/docs/en/integrations/streaming.mdx
index 214d002d9c2a39..6d889a3f204b34 100644
--- a/docs/en/integrations/streaming.mdx
+++ b/docs/en/integrations/streaming.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Streaming data
diff --git a/docs/en/integrations/streaming/apache_kafka.mdx b/docs/en/integrations/streaming/apache_kafka.mdx
index 2a38c6c0378090..3ba39c7f8c0630 100644
--- a/docs/en/integrations/streaming/apache_kafka.mdx
+++ b/docs/en/integrations/streaming/apache_kafka.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_label: Apache Kafka
 description: "Continuously load data from Apache Kafka"
 title: Apache Kafka
diff --git a/docs/en/integrations/streaming/flink.mdx b/docs/en/integrations/streaming/flink.mdx
index 1469cfbadb586c..007177e5ea053d 100644
--- a/docs/en/integrations/streaming/flink.mdx
+++ b/docs/en/integrations/streaming/flink.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_position: 1
 sidebar_label: Apache Flink
 description: "Continuously load data from Apache Flink"
diff --git a/docs/en/integrations/streaming/kafka/Kafka-connector-starrocks.mdx b/docs/en/integrations/streaming/kafka/Kafka-connector-starrocks.mdx
index c0128e0e677e03..39397029dd9c5f 100644
--- a/docs/en/integrations/streaming/kafka/Kafka-connector-starrocks.mdx
+++ b/docs/en/integrations/streaming/kafka/Kafka-connector-starrocks.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_position: 2
 sidebar_label: Kafka connector
 description: "Continuous streaming from Kafka"
diff --git a/docs/en/integrations/streaming/kafka/RoutineLoad.mdx b/docs/en/integrations/streaming/kafka/RoutineLoad.mdx
index 462b779ad19a6e..21b6c1f765d441 100644
--- a/docs/en/integrations/streaming/kafka/RoutineLoad.mdx
+++ b/docs/en/integrations/streaming/kafka/RoutineLoad.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_position: 2
 sidebar_label: Routine Load
 description: "Load CSV, JSON, or Avro format from a Kafka topic"
diff --git a/docs/en/integrations/streaming/pipe.mdx b/docs/en/integrations/streaming/pipe.mdx
index d4a704f5dd4d2b..2130e5ed30acd0 100644
--- a/docs/en/integrations/streaming/pipe.mdx
+++ b/docs/en/integrations/streaming/pipe.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 import Content from '../../_assets/commonMarkdown/pipeAdvantages.md'
diff --git a/docs/en/integrations/streaming/pipe/hdfs.mdx b/docs/en/integrations/streaming/pipe/hdfs.mdx
index f034a349d54908..3c8c5658a772c2 100644
--- a/docs/en/integrations/streaming/pipe/hdfs.mdx
+++ b/docs/en/integrations/streaming/pipe/hdfs.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_position: 2
 sidebar_label: HDFS
 description: "Pipe example using loading from HDFS"
diff --git a/docs/en/integrations/streaming/pipe/s3.mdx b/docs/en/integrations/streaming/pipe/s3.mdx
index 51eb3048c33285..b2f447887fe27b 100644
--- a/docs/en/integrations/streaming/pipe/s3.mdx
+++ b/docs/en/integrations/streaming/pipe/s3.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_position: 2
 sidebar_label: S3
 description: "Pipe example loading from S3"
diff --git a/docs/en/integrations/streaming/rising_wave.md b/docs/en/integrations/streaming/rising_wave.md
index 338cbcd36d16e9..cfdf2405097fd1 100644
--- a/docs/en/integrations/streaming/rising_wave.md
+++ b/docs/en/integrations/streaming/rising_wave.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Sink data from RisingWave to StarRocks
diff --git a/docs/en/integrations/superset_support.md b/docs/en/integrations/superset_support.md
index 5ff6a1a718b6cf..92a3c759cde8c4 100644
--- a/docs/en/integrations/superset_support.md
+++ b/docs/en/integrations/superset_support.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Superset Support
diff --git a/docs/en/introduction/Architecture.md b/docs/en/introduction/Architecture.md
index a86cbfb12466e8..6283fc4e315236 100644
--- a/docs/en/introduction/Architecture.md
+++ b/docs/en/introduction/Architecture.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Architecture
diff --git a/docs/en/introduction/Features.md b/docs/en/introduction/Features.md
index 21b061d83d33f5..9c0d1118e66a9e 100644
--- a/docs/en/introduction/Features.md
+++ b/docs/en/introduction/Features.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Features
diff --git a/docs/en/introduction/StarRocks_intro.md b/docs/en/introduction/StarRocks_intro.md
index 7de07df541fb57..c55a34cdc29aaf 100644
--- a/docs/en/introduction/StarRocks_intro.md
+++ b/docs/en/introduction/StarRocks_intro.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # StarRocks
diff --git a/docs/en/introduction/introduction.mdx b/docs/en/introduction/introduction.mdx
index bf1f92236ad5ee..750b2920cfecd0 100644
--- a/docs/en/introduction/introduction.mdx
+++ b/docs/en/introduction/introduction.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Introduction
diff --git a/docs/en/introduction/what_is_starrocks.md b/docs/en/introduction/what_is_starrocks.md
index 405d6a3e5a6452..3081a1e7d4d740 100644
--- a/docs/en/introduction/what_is_starrocks.md
+++ b/docs/en/introduction/what_is_starrocks.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # What is StarRocks?
diff --git a/docs/en/loading/BrokerLoad.md b/docs/en/loading/BrokerLoad.md
index 0137a39a5f4b20..a25d0b1ed5bb27 100644
--- a/docs/en/loading/BrokerLoad.md
+++ b/docs/en/loading/BrokerLoad.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Load data from HDFS or cloud storage
@@ -8,7 +8,7 @@ import InsertPrivNote from '../_assets/commonMarkdown/insertPrivNote.md'
 
 StarRocks provides the loading method MySQL-based Broker Load to help you load a large amount of data from HDFS or cloud storage into StarRocks.
 
-Broker Load runs in asynchronous loading mode. After you submit a load job, StarRocks asynchronously runs the job. You need to use the [SHOW LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md) statement or the `curl` command to check the result of the job.
+Broker Load runs in asynchronous loading mode. After you submit a load job, StarRocks asynchronously runs the job. You need to use the [SHOW LOAD](../sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md) statement or the `curl` command to check the result of the job.
 
 Broker Load supports single-table loads and multi-table loads. You can load one or multiple data files into one or multiple destination tables by running one Broker Load job. Broker Load ensures the transactional atomicity of each load job that is run to load multiple data files. Atomicity means that the loading of multiple data files in one load job must all succeed or fail. It never happens that the loading of some data files succeeds while the loading of the other files fails.
 
@@ -22,7 +22,7 @@ In v2.4 and earlier, StarRocks depends on brokers to set up connections between
 
 From v2.5 onwards, StarRocks no longer depends on brokers to set up connections between your StarRocks cluster and your external storage system when it runs a Broker Load job. Therefore, you no longer need to specify a broker in the load statement, but you still need to retain the `WITH BROKER` keyword. This is called "broker-free loading."
 
-When your data is stored in HDFS, you may encounter situations where broker-free loading does not work. This can happen when your data is stored across multiple HDFS clusters or when you have configured multiple Kerberos users. In these situations, you can resort to using broker-based loading instead. To do this successfully, make sure that at least one independent broker group is deployed. For information about how to specify authentication configuration and HA configuration in these situations, see [HDFS](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#hdfs).
+When your data is stored in HDFS, you may encounter situations where broker-free loading does not work. This can happen when your data is stored across multiple HDFS clusters or when you have configured multiple Kerberos users. In these situations, you can resort to using broker-based loading instead. To do this successfully, make sure that at least one independent broker group is deployed. For information about how to specify authentication configuration and HA configuration in these situations, see [HDFS](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#hdfs).
 
 ## Supported data file formats
 
@@ -67,7 +67,7 @@ The following figure shows the workflow of a Broker Load job.
 
 ### Create a multi-table load job
 
-This topic uses CSV as an example to describe how to load multiple data files into multiple tables. For information about how to load data in other file formats and about the syntax and parameter descriptions for Broker Load, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+This topic uses CSV as an example to describe how to load multiple data files into multiple tables. For information about how to load data in other file formats and about the syntax and parameter descriptions for Broker Load, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 Note that in StarRocks some literals are used as reserved keywords by the SQL language. Do not directly use these keywords in SQL statements. If you want to use such a keyword in an SQL statement, enclose it in a pair of backticks (`). See [Keywords](../sql-reference/sql-statements/keywords.md).
 
@@ -152,7 +152,7 @@ PROPERTIES
 );
 ```
 
-In the preceding example, `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For more information, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#hdfs).
+In the preceding example, `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For more information, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#hdfs).
 
 #### Load data from AWS S3
 
@@ -181,7 +181,7 @@ WITH BROKER
 >
 > Broker Load supports accessing AWS S3 only according to the S3A protocol. Therefore, when you load data from AWS S3, you must replace `s3://` in the S3 URI you pass as the file path with `s3a://`.
 
-In the preceding example, `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For more information, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#aws-s3).
+In the preceding example, `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For more information, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#aws-s3).
 
 From v3.1 onwards, StarRocks supports directly loading the data of Parquet-formatted or ORC-formatted files from AWS S3 by using the INSERT command and the TABLE keyword, saving you from the trouble of creating an external table first. For more information, see [Load data using INSERT > Insert data directly from files in an external source using TABLE keyword](../loading/InsertInto.md#insert-data-directly-from-files-in-an-external-source-using-files).
 
@@ -212,7 +212,7 @@ WITH BROKER
 >
 > Broker Load supports accessing Google GCS only according to the gs protocol. Therefore, when you load data from Google GCS, you must include `gs://` as the prefix in the GCS URI that you pass as the file path.
 
-In the preceding example, `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For more information, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#google-gcs).
+In the preceding example, `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For more information, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#google-gcs).
 
 #### Load data from other S3-compatible storage system
 
@@ -237,7 +237,7 @@ WITH BROKER
 );
 ```
 
-In the preceding example, `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For more information, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#other-s3-compatible-storage-system).
+In the preceding example, `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For more information, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#other-s3-compatible-storage-system).
 
 #### Load data from Microsoft Azure Storage
 
@@ -274,7 +274,7 @@ WITH BROKER
   >   - If your Data Lake Storage Gen2 allows access only via HTTP, use `abfs://` as the prefix, for example, `abfs://<container>@<storage_account>.dfs.core.windows.net/<file_name>`.
   >   - If your Data Lake Storage Gen2 allows access only via HTTPS, use `abfss://` as the prefix, for example, `abfss://<container>@<storage_account>.dfs.core.windows.net/<file_name>`.
 
-In the preceding example, `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For more information, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#microsoft-azure-storage).
+In the preceding example, `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For more information, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#microsoft-azure-storage).
 
 #### Query data
 
@@ -343,7 +343,7 @@ WITH BROKER
 );
 ```
 
-In the preceding examples, `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For more information, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#aws-s3).
+In the preceding examples, `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For more information, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#aws-s3).
 
 ### View a load job
 
@@ -351,7 +351,7 @@ Broker Load allows you to view a lob job by using the SHOW LOAD statement or the
 
 #### Use SHOW LOAD
 
-For more information, see [SHOW LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md).
+For more information, see [SHOW LOAD](../sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md).
 
 #### Use curl
 
@@ -394,7 +394,7 @@ The following table describes the parameters in `jobInfo`.
 
 ### Cancel a load job
 
-When a load job is not in the **CANCELLED** or **FINISHED** stage, you can use the [CANCEL LOAD](../sql-reference/sql-statements/data-manipulation/CANCEL_LOAD.md) statement to cancel the job.
+When a load job is not in the **CANCELLED** or **FINISHED** stage, you can use the [CANCEL LOAD](../sql-reference/sql-statements/loading_unloading/CANCEL_LOAD.md) statement to cancel the job.
 
 For example, you can execute the following statement to cancel a load job, whose label is `label1`, in the database `test_db`:
 
@@ -430,4 +430,4 @@ The [FE configuration item](../administration/management/FE_configuration.md) `m
 
 In StarRocks v2.4 and earlier, if the total number of Broker Load jobs that are submitted within a specific period of time exceeds the maximum number, excessive jobs are queued and scheduled based on their submission time.
 
-Since StarRocks v2.5, if the total number of Broker Load jobs that are submitted within a specific period of time exceeds the maximum number, excessive jobs are queued and scheduled based on their priorities. You can specify a priority for a job by using the `priority` parameter at job creation. See [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#opt_properties). You can also use [ALTER LOAD](../sql-reference/sql-statements/data-manipulation/ALTER_LOAD.md) to modify the priority of an existing job that is in the **QUEUEING** or **LOADING** state.
+Since StarRocks v2.5, if the total number of Broker Load jobs that are submitted within a specific period of time exceeds the maximum number, excessive jobs are queued and scheduled based on their priorities. You can specify a priority for a job by using the `priority` parameter at job creation. See [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#opt_properties). You can also use [ALTER LOAD](../sql-reference/sql-statements/loading_unloading/ALTER_LOAD.md) to modify the priority of an existing job that is in the **QUEUEING** or **LOADING** state.
diff --git a/docs/en/loading/Etl_in_loading.md b/docs/en/loading/Etl_in_loading.md
index dff109d7b44eaf..15cdf9cdc47be0 100644
--- a/docs/en/loading/Etl_in_loading.md
+++ b/docs/en/loading/Etl_in_loading.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Transform data at loading
@@ -8,7 +8,7 @@ import InsertPrivNote from '../_assets/commonMarkdown/insertPrivNote.md'
 
 StarRocks supports data transformation at loading.
 
-This feature supports [Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md), [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md), and [Routine Load](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md) but does not support [Spark Load](../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md).
+This feature supports [Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md), [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md), and [Routine Load](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md) but does not support [Spark Load](../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md).
 
 <InsertPrivNote />
 
@@ -148,7 +148,7 @@ curl --location-trusted -u <username>:<password> \
 >
 > If you choose Stream Load, you must use the `columns` parameter to temporarily name the columns of the data file to create a column mapping between the data file and the StarRocks table.
 
-For detailed syntax and parameter descriptions, see [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md).
+For detailed syntax and parameter descriptions, see [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md).
 
 #### Load data from an HDFS cluster
 
@@ -170,7 +170,7 @@ WITH BROKER;
 >
 > If you choose Broker Load, you must use the `column_list` parameter to temporarily name the columns of the data file to create a column mapping between the data file and the StarRocks table.
 
-For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 #### Load data from a Kafka cluster
 
@@ -192,7 +192,7 @@ FROM KAFKA
 >
 > If you choose Routine Load, you must use the `COLUMNS` parameter to temporarily name the columns of the data file to create a column mapping between the data file and the StarRocks table.
 
-For detailed syntax and parameter descriptions, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md).
+For detailed syntax and parameter descriptions, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md).
 
 ### Query data
 
@@ -244,7 +244,7 @@ curl --location-trusted -u <username>:<password> \
     http://<fe_host>:<fe_http_port>/api/test_db/table1/_stream_load
 ```
 
-For detailed syntax and parameter descriptions, see [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md).
+For detailed syntax and parameter descriptions, see [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md).
 
 #### Load data from an HDFS cluster
 
@@ -263,7 +263,7 @@ LOAD LABEL test_db.label2
 WITH BROKER;
 ```
 
-For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 #### Load data from a Kafka cluster
 
@@ -282,7 +282,7 @@ FROM KAFKA
 );
 ```
 
-For detailed syntax and parameter descriptions, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md).
+For detailed syntax and parameter descriptions, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md).
 
 ### Query data
 
@@ -337,7 +337,7 @@ curl --location-trusted -u <username>:<password> \
 >
 > - Stream Load does not support `column_name = function(column_name)` but supports `column_name = function(column_name)`.
 
-For detailed syntax and parameter descriptions, see [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md).
+For detailed syntax and parameter descriptions, see [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md).
 
 #### Load data from an HDFS cluster
 
@@ -360,7 +360,7 @@ WITH BROKER;
 >
 > You must first use the `column_list` parameter to temporarily name **all columns** of the data file, and then use the SET clause to temporarily name the new columns that you want to generate from the original columns of the data file. As shown in the preceding example, the only column of `file2.csv` is temporarily named as `date` in the `column_list` parameter, and then the `year=year(date)`, `month=month(date)`, and `day=day(date)` functions are invoked in the SET clause to generate three new columns, which are temporarily named as `year`, `month`, and `day`.
 
-For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 #### Load data from a Kafka cluster
 
@@ -382,7 +382,7 @@ FROM KAFKA
 >
 > In the `COLUMNS` parameter, you must first temporarily name **all columns** of the data file, and then temporarily name the new columns that you want to generate from the original columns of the data file. As shown in the preceding example, the only column of `file2.csv` is temporarily named as `date`, and then the `year=year(date)`, `month=month(date)`, and `day=day(date)` functions are invoked to generate three new columns, which are temporarily named as `year`, `month`, and `day`.
 
-For detailed syntax and parameter descriptions, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md).
+For detailed syntax and parameter descriptions, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md).
 
 ### Query data
 
@@ -442,7 +442,7 @@ WITH BROKER;
 >
 > In the preceding example, the `date` partition field in the specified file path is equivalent to the `event_date` column of `table1`. Therefore, you need to use the SET clause to map the `date` partition field onto the `event_date` column. If the partition field in the specified file path has the same name as a column of the StarRocks table, you do not need to use the SET clause to create a mapping.
 
-For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 ### Query data
 
diff --git a/docs/en/loading/Flink-connector-starrocks.md b/docs/en/loading/Flink-connector-starrocks.md
index 7244af38a1579b..9f1709169a113e 100644
--- a/docs/en/loading/Flink-connector-starrocks.md
+++ b/docs/en/loading/Flink-connector-starrocks.md
@@ -1,10 +1,10 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Continuously load data from Apache Flink®
 
-StarRocks provides a self-developed connector named StarRocks Connector for Apache Flink® (Flink connector for short) to help you load data into a StarRocks table by using Flink. The basic principle is to accumulate the data and then load it all at a time into StarRocks through [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md).
+StarRocks provides a self-developed connector named StarRocks Connector for Apache Flink® (Flink connector for short) to help you load data into a StarRocks table by using Flink. The basic principle is to accumulate the data and then load it all at a time into StarRocks through [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md).
 
 The Flink connector supports DataStream API, Table API & SQL, and Python API. It has a higher and more stable performance than [flink-connector-jdbc](https://nightlies.apache.org/flink/flink-docs-master/docs/connectors/table/jdbc/) provided by Apache Flink®.
 
@@ -201,7 +201,7 @@ In your Maven project's `pom.xml` file, add the Flink connector as a dependency
 
 **Required**: No<br/>
 **Default value**: NONE<br/>
-**Description**: The parameters that are used to control Stream Load behavior. For example, the parameter `sink.properties.format` specifies the format used for Stream Load, such as CSV or JSON. For a list of supported parameters and their descriptions, see [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md).
+**Description**: The parameters that are used to control Stream Load behavior. For example, the parameter `sink.properties.format` specifies the format used for Stream Load, such as CSV or JSON. For a list of supported parameters and their descriptions, see [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md).
 
 ### sink.properties.format
 
@@ -225,7 +225,7 @@ In your Maven project's `pom.xml` file, add the Flink connector as a dependency
 
 **Required**: No<br/>
 **Default value**: 0<br/>
-**Description**: The maximum error tolerance of the Stream Load. It's the maximum percentage of data records that can be filtered out due to inadequate data quality. Valid values: `0` to `1`. Default value: `0`. See [Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md) for details.
+**Description**: The maximum error tolerance of the Stream Load. It's the maximum percentage of data records that can be filtered out due to inadequate data quality. Valid values: `0` to `1`. Default value: `0`. See [Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md) for details.
 
 ### sink.properties.partial_update
 
@@ -243,7 +243,7 @@ In your Maven project's `pom.xml` file, add the Flink connector as a dependency
 
 **Required**: No<br/>
 **Default value**: false<br/>
-**Description**: Specifies whether to enable the strict mode for Stream Load. It affects the loading behavior when there are unqualified rows, such as inconsistent column values. Valid values: `true` and `false`. Default value: `false`. See [Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md) for details.
+**Description**: Specifies whether to enable the strict mode for Stream Load. It affects the loading behavior when there are unqualified rows, such as inconsistent column values. Valid values: `true` and `false`. Default value: `false`. See [Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md) for details.
 
 ## Data type mapping between Flink and StarRocks
 
@@ -584,7 +584,7 @@ Since v1.2.9, the Flink connector for StarRocks is integrated into this framewor
 
 For quick start, see [Streaming ELT from MySQL to StarRocks using Flink CDC 3.0 with StarRocks Pipeline Connector](https://nightlies.apache.org/flink/flink-cdc-docs-stable/docs/get-started/quickstart/mysql-to-starrocks).
 
-It is advised to use StarRocks v3.2.1 and later versions to enable [fast_schema_evolution](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md#set-fast-schema-evolution). It will improve the speed of adding or dropping columns and reduce resource usage.
+It is advised to use StarRocks v3.2.1 and later versions to enable [fast_schema_evolution](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md#set-fast-schema-evolution). It will improve the speed of adding or dropping columns and reduce resource usage.
 
 ## Best practices
 
diff --git a/docs/en/loading/Flink_cdc_load.md b/docs/en/loading/Flink_cdc_load.md
index 40438547790376..8da8eeca37e2f0 100644
--- a/docs/en/loading/Flink_cdc_load.md
+++ b/docs/en/loading/Flink_cdc_load.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Realtime synchronization from MySQL
diff --git a/docs/en/loading/InsertInto.md b/docs/en/loading/InsertInto.md
index 02ca6e1f8dea46..e13d1359f3b26c 100644
--- a/docs/en/loading/InsertInto.md
+++ b/docs/en/loading/InsertInto.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Load data using INSERT
@@ -23,10 +23,10 @@ StarRocks v2.4 further supports overwriting data into a table by using INSERT OV
 ## Precautions
 
 - You can cancel a synchronous INSERT transaction only by pressing the **Ctrl** and **C** keys from your MySQL client.
-- You can submit an asynchronous INSERT task using [SUBMIT TASK](../sql-reference/sql-statements/data-manipulation/SUBMIT_TASK.md).
+- You can submit an asynchronous INSERT task using [SUBMIT TASK](../sql-reference/sql-statements/loading_unloading/ETL/SUBMIT_TASK.md).
 - As for the current version of StarRocks, the INSERT transaction fails by default if the data of any rows does not comply with the schema of the table. For example, the INSERT transaction fails if the length of a field in any row exceeds the length limit for the mapping field in the table. You can set the session variable `enable_insert_strict` to `false` to allow the transaction to continue by filtering out the rows that mismatch the table.
 - If you execute the INSERT statement frequently to load small batches of data into StarRocks, excessive data versions are generated. It severely affects query performance. We recommend that, in production, you should not load data with the INSERT command too often or use it as a routine for data loading on a daily basis. If your application or analytic scenario demand solutions to loading streaming data or small data batches separately, we recommend you use Apache Kafka® as your data source and load the data via [Routine Load](../loading/RoutineLoad.md).
-- If you execute the INSERT OVERWRITE statement, StarRocks creates temporary partitions for the partitions which store the original data, inserts new data into the temporary partitions, and [swaps the original partitions with the temporary partitions](../sql-reference/sql-statements/data-definition/ALTER_TABLE.md#use-a-temporary-partition-to-replace-the-current-partition). All these operations are executed in the FE Leader node. Hence, if the FE Leader node crashes while executing INSERT OVERWRITE command, the whole load transaction will fail, and the temporary partitions will be truncated.
+- If you execute the INSERT OVERWRITE statement, StarRocks creates temporary partitions for the partitions which store the original data, inserts new data into the temporary partitions, and [swaps the original partitions with the temporary partitions](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md#use-a-temporary-partition-to-replace-the-current-partition). All these operations are executed in the FE Leader node. Hence, if the FE Leader node crashes while executing INSERT OVERWRITE command, the whole load transaction will fail, and the temporary partitions will be truncated.
 
 ## Preparation
 
@@ -115,7 +115,7 @@ DISTRIBUTED BY HASH(user);
 
 ## Insert data via INSERT INTO VALUES
 
-You can append one or more rows to a specific table by using INSERT INTO VALUES command. Multiple rows are separated by comma (,). For detailed instructions and parameter references, see [SQL Reference - INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md).
+You can append one or more rows to a specific table by using INSERT INTO VALUES command. Multiple rows are separated by comma (,). For detailed instructions and parameter references, see [SQL Reference - INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md).
 
 > **CAUTION**
 >
@@ -133,7 +133,7 @@ VALUES
 
 ## Insert data via INSERT INTO SELECT
 
-You can load the result of a query on a data source table into the target table via INSERT INTO SELECT command. INSERT INTO SELECT command performs ETL operations on the data from the data source table, and loads the data into an internal table in StarRocks. The data source can be one or more internal or external tables, or even data files on cloud storage. The target table MUST be an internal table in StarRocks. For detailed instructions and parameter references, see [SQL Reference - INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md).
+You can load the result of a query on a data source table into the target table via INSERT INTO SELECT command. INSERT INTO SELECT command performs ETL operations on the data from the data source table, and loads the data into an internal table in StarRocks. The data source can be one or more internal or external tables, or even data files on cloud storage. The target table MUST be an internal table in StarRocks. For detailed instructions and parameter references, see [SQL Reference - INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md).
 
 ### Insert data from an internal or external table into an internal table
 
@@ -215,7 +215,7 @@ INSERT INTO insert_wiki_edit
 
 ## Overwrite data via INSERT OVERWRITE VALUES
 
-You can overwrite a specific table with one or more rows by using INSERT OVERWRITE VALUES command. Multiple rows are separated by comma (,). For detailed instructions and parameter references, see [SQL Reference - INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md).
+You can overwrite a specific table with one or more rows by using INSERT OVERWRITE VALUES command. Multiple rows are separated by comma (,). For detailed instructions and parameter references, see [SQL Reference - INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md).
 
 > **CAUTION**
 >
@@ -255,7 +255,7 @@ VALUES
 
 ## Overwrite data via INSERT OVERWRITE SELECT
 
-You can overwrite a table with the result of a query on a data source table via INSERT OVERWRITE SELECT command. INSERT OVERWRITE SELECT statement performs ETL operations on the data from one or more internal or external tables, and overwrites an internal table with the data For detailed instructions and parameter references, see [SQL Reference - INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md).
+You can overwrite a table with the result of a query on a data source table via INSERT OVERWRITE SELECT command. INSERT OVERWRITE SELECT statement performs ETL operations on the data from one or more internal or external tables, and overwrites an internal table with the data For detailed instructions and parameter references, see [SQL Reference - INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md).
 
 > **NOTE**
 >
@@ -399,7 +399,7 @@ mysql> SELECT * FROM insert_generated_columns;
 
 ## Load data asynchronously using INSERT
 
-Loading data with INSERT submits a synchronous transaction, which may fail because of session interruption or timeout. You can submit an asynchronous INSERT transaction using [SUBMIT TASK](../sql-reference/sql-statements/data-manipulation/SUBMIT_TASK.md). This feature is supported since StarRocks v2.5.
+Loading data with INSERT submits a synchronous transaction, which may fail because of session interruption or timeout. You can submit an asynchronous INSERT transaction using [SUBMIT TASK](../sql-reference/sql-statements/loading_unloading/ETL/SUBMIT_TASK.md). This feature is supported since StarRocks v2.5.
 
 - The following example asynchronously inserts the data from the source table to the target table `insert_wiki_edit`.
 
@@ -466,7 +466,7 @@ You can locate the problem by checking the log with `tracking_url`.
 
 ### Check via Information Schema
 
-You can use the [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) statement to query the results of one or more load jobs from the `loads` table in the `information_schema` database. This feature is supported from v3.1 onwards.
+You can use the [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) statement to query the results of one or more load jobs from the `loads` table in the `information_schema` database. This feature is supported from v3.1 onwards.
 
 Example 1: Query the results of load jobs executed on the `load_test` database, sort the results by creation time (`CREATE_TIME`) in descending order, and only return the top result.
 
@@ -514,7 +514,7 @@ REJECTED_RECORD_PATH: NULL
 1 row in set (0.01 sec)
 ```
 
-For information about the fields in the return results, see [Information Schema > loads](../reference/information_schema/loads.md).
+For information about the fields in the return results, see [Information Schema > loads](../sql-reference/information_schema/loads.md).
 
 ### Check via curl command
 
diff --git a/docs/en/loading/Json_loading.md b/docs/en/loading/Json_loading.md
index 93b36a30cf4738..d2dcffb5a86af9 100644
--- a/docs/en/loading/Json_loading.md
+++ b/docs/en/loading/Json_loading.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Introduction
diff --git a/docs/en/loading/Kafka-connector-starrocks.md b/docs/en/loading/Kafka-connector-starrocks.md
index a93b43a27ec3bc..68191bd18cb2f6 100644
--- a/docs/en/loading/Kafka-connector-starrocks.md
+++ b/docs/en/loading/Kafka-connector-starrocks.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Load data using Kafka connector
@@ -302,13 +302,13 @@ The data is successfully loaded when the above result is returned.
 
 **Required**:<br/>
 **Default value**:<br/>
-**Description**: Stream Load parameters o control load behavior. For example, the parameter `sink.properties.format` specifies the format used for Stream Load, such as CSV or JSON. For a list of supported parameters and their descriptions, see [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md).
+**Description**: Stream Load parameters o control load behavior. For example, the parameter `sink.properties.format` specifies the format used for Stream Load, such as CSV or JSON. For a list of supported parameters and their descriptions, see [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md).
 
 ### sink.properties.format
 
 **Required**: NO<br/>
 **Default value**: json<br/>
-**Description**: The format used for Stream Load. The Kafka connector will transform each batch of data to the format before sending them to StarRocks. Valid values: `csv` and `json`. For more information, see [CSV parameters](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md#csv-parameters) and [JSON parameters](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md#json-parameters).
+**Description**: The format used for Stream Load. The Kafka connector will transform each batch of data to the format before sending them to StarRocks. Valid values: `csv` and `json`. For more information, see [CSV parameters](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md#csv-parameters) and [JSON parameters](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md#json-parameters).
 
 ### sink.properties.partial_update
 
diff --git a/docs/en/loading/Load_to_Primary_Key_tables.md b/docs/en/loading/Load_to_Primary_Key_tables.md
index a0c00c8bf1c719..d6e390b0dc2f37 100644
--- a/docs/en/loading/Load_to_Primary_Key_tables.md
+++ b/docs/en/loading/Load_to_Primary_Key_tables.md
@@ -1,12 +1,12 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Change data through loading
 
 import InsertPrivNote from '../_assets/commonMarkdown/insertPrivNote.md'
 
-[Primary Key tables](../table_design/table_types/primary_key_table.md) provided by StarRocks allow you to make data changes to StarRocks tables by running [Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md), [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md), or [Routine Load](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md) jobs. These data changes include inserts, updates, and deletions. However, Primary Key tables do not support changing data by using [Spark Load](../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md) or [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md).
+[Primary Key tables](../table_design/table_types/primary_key_table.md) provided by StarRocks allow you to make data changes to StarRocks tables by running [Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md), [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md), or [Routine Load](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md) jobs. These data changes include inserts, updates, and deletions. However, Primary Key tables do not support changing data by using [Spark Load](../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md) or [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md).
 
 StarRocks also supports partial updates and conditional updates.
 
@@ -62,7 +62,7 @@ If you choose Routine Load, make sure that topics are created in your Apache Kaf
 
 ## Basic operations
 
-This section provides examples of how to make data changes to a StarRocks table through loading. For detailed syntax and parameter descriptions, see [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md), [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md), and [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md).
+This section provides examples of how to make data changes to a StarRocks table through loading. For detailed syntax and parameter descriptions, see [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md), [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md), and [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md).
 
 ### UPSERT
 
diff --git a/docs/en/loading/Loading_data_template.md b/docs/en/loading/Loading_data_template.md
index 7e66a46a6f3b79..1dd58710d040c5 100644
--- a/docs/en/loading/Loading_data_template.md
+++ b/docs/en/loading/Loading_data_template.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 unlisted: true
 ---
 
@@ -397,4 +397,4 @@ INSERT INTO user_behavior_declared
 - This document only covered IAM user-based authentication. For other options please see [authenticate to AWS resources](../integrations/authenticate_to_aws_resources.md).
 - The [AWS CLI Command Reference](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/s3/index.html) covers the S3 URI in detail.
 - Learn more about [table design](../table_design/StarRocks_table_design.md).
-- Broker Load provides many more configuration and use options than those in the above examples, the details are in [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)
+- Broker Load provides many more configuration and use options than those in the above examples, the details are in [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)
diff --git a/docs/en/loading/RoutineLoad.md b/docs/en/loading/RoutineLoad.md
index bb315ddaa800ca..e86f81f09f02d3 100644
--- a/docs/en/loading/RoutineLoad.md
+++ b/docs/en/loading/RoutineLoad.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Load data using Routine Load
@@ -48,7 +48,7 @@ Routine Load now supports consuming CSV, JSON, and Avro (supported since v3.0.1)
 ### Workflow
 
 1. **Create a Routine Load job.**
-   To load data from Kafka, you need to create a Routine Load job by running the [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md) statement. The FE parses the statement, and creates the job according to the properties you have specified.
+   To load data from Kafka, you need to create a Routine Load job by running the [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md) statement. The FE parses the statement, and creates the job according to the properties you have specified.
 
 2. **The FE splits the job into multiple load tasks.**
 
@@ -64,20 +64,20 @@ Routine Load now supports consuming CSV, JSON, and Avro (supported since v3.0.1)
 
 3. **Multiple load tasks run concurrently to consume the messages from multiple Kafka topic partitions, and load the data into StarRocks**
 
-   1. **The FE schedules and submits load tasks**: the FE schedules the load tasks in the queue on a timely basis, and assigns them to selected Coordinator BE nodes. The interval between load tasks is defined by the configuration item `max_batch_interval`. The FE distributes the load tasks evenly to all BE nodes. See [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md#examples) for more information about `max_batch_interval`.
+   1. **The FE schedules and submits load tasks**: the FE schedules the load tasks in the queue on a timely basis, and assigns them to selected Coordinator BE nodes. The interval between load tasks is defined by the configuration item `max_batch_interval`. The FE distributes the load tasks evenly to all BE nodes. See [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md#examples) for more information about `max_batch_interval`.
 
    2. The Coordinator BE starts the load task, consumes messages in partitions, parses and filters the data. A load task lasts until the pre-defined amount of messages are consumed or the pre-defined time limit is reached. The message batch size and time limit are defined in the FE configurations `max_routine_load_batch_size` and `routine_load_task_consume_second`. For detailed information, see [FE Configuration](../administration/management/FE_configuration.md). The Coordinator BE then distributes the messages to the Executor BEs. The Executor BEs write the messages to disks.
 
          > **NOTE**
          >
-         > StarRocks supports access to Kafka via security protocols including SASL_SSL, SAS_PLAINTEXT, SSL, and PLAINTEXT. This topic uses connecting to Kafka via PLAINTEXT as an example. If you need to connect to Kafka via other security protocols, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md).
+         > StarRocks supports access to Kafka via security protocols including SASL_SSL, SAS_PLAINTEXT, SSL, and PLAINTEXT. This topic uses connecting to Kafka via PLAINTEXT as an example. If you need to connect to Kafka via other security protocols, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md).
 
 4. **The FE generates new load tasks to load data continuously.**
    After the Executor BEs has written the data to disks, the Coordinator BE reports the result of the load task to the FE. Based on the result, the FE then generates new load tasks to load the data continuously. Or the FE retries the failed tasks to make sure the data loaded into StarRocks is neither lost nor duplicated.
 
 ## Create a Routine Load job
 
-The following three examples describe how to consume CSV-format, JSON-format and Avro-format data in Kafka, and load the data into StarRocks by creating a Routine Load job. For detailed syntax and parameter descriptions, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md).
+The following three examples describe how to consume CSV-format, JSON-format and Avro-format data in Kafka, and load the data into StarRocks by creating a Routine Load job. For detailed syntax and parameter descriptions, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md).
 
 ### Load CSV-format data
 
@@ -138,7 +138,7 @@ FROM KAFKA
 );
 ```
 
-After submitting the load job, you can execute the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) statement to check the status of the load job.
+After submitting the load job, you can execute the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) statement to check the status of the load job.
 
 - **load job name**
 
@@ -164,7 +164,7 @@ After submitting the load job, you can execute the [SHOW ROUTINE LOAD](../sql-re
     "property.kafka_default_offsets" = "OFFSET_BEGINNING"
     ```
 
-  For detailed information, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md).
+  For detailed information, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md).
 
 - **Data mapping and transformation**
 
@@ -196,7 +196,7 @@ After submitting the load job, you can execute the [SHOW ROUTINE LOAD](../sql-re
 
   In the example, the number of BE nodes that are alive is `5`, the number of the pre-specified Kafka topic partitions is `5`, and the value of `max_routine_load_task_concurrent_num` is `5`. To increase the actual load task concurrency, you can increase the `desired_concurrent_number` from the default value `3` to `5`.
 
-  For more about the properties, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md). For detailed instructions on accelerating the loading, see [Routine Load FAQ](../faq/loading/Routine_load_faq.md).
+  For more about the properties, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md). For detailed instructions on accelerating the loading, see [Routine Load FAQ](../faq/loading/Routine_load_faq.md).
 
 ### Load JSON-format data
 
@@ -258,7 +258,7 @@ FROM KAFKA
 );
 ```
 
-After submitting the load job, you can execute the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) statement to check the status of the load job.
+After submitting the load job, you can execute the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) statement to check the status of the load job.
 
 - **Data format**
 
@@ -383,7 +383,7 @@ FROM KAFKA
   >
   > You do not need to specify the `COLUMNS` parameter if the names and number of the fields in the Avro record completely match those of columns in the StarRocks table.
 
-After submitting the load job, you can execute the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) statement to check the status of the load job.
+After submitting the load job, you can execute the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) statement to check the status of the load job.
 
 #### Data types mapping
 
@@ -422,9 +422,9 @@ The data type mapping between the Avro data fields you want to load and the Star
 
 ### Check a load job
 
-Execute the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) statement to check the status of the load job `example_tbl2_ordertest2`. StarRocks returns the execution state `State`, the statistical information (including the total rows consumed and the total rows loaded) `Statistics`,  and the progress of the load job `progress`.
+Execute the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) statement to check the status of the load job `example_tbl2_ordertest2`. StarRocks returns the execution state `State`, the statistical information (including the total rows consumed and the total rows loaded) `Statistics`,  and the progress of the load job `progress`.
 
-If the state of the load job is automatically changed to **PAUSED**, it is possibly because the number of error rows has exceeded the threshold. For detailed instructions on setting this threshold, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md). You can check the files `ReasonOfStateChanged` and `ErrorLogUrls` to identify and troubleshoot the problem. Having fixed the problem, you can then execute the [RESUME ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md) statement to resume the **PAUSED** load job.
+If the state of the load job is automatically changed to **PAUSED**, it is possibly because the number of error rows has exceeded the threshold. For detailed instructions on setting this threshold, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md). You can check the files `ReasonOfStateChanged` and `ErrorLogUrls` to identify and troubleshoot the problem. Having fixed the problem, you can then execute the [RESUME ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md) statement to resume the **PAUSED** load job.
 
 If the state of the load job is **CANCELLED**, it is possibly because the load job encounters an exception (such as the table has been dropped). You can check the files `ReasonOfStateChanged` and `ErrorLogUrls` to identify and troubleshoot the problem. However, you cannot resume a **CANCELLED** load job.
 
@@ -457,7 +457,7 @@ ReasonOfStateChanged:
 
 ### Check a load task
 
-Execute the [SHOW ROUTINE LOAD TASK](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD_TASK.md) statement to check the load tasks of the load job `example_tbl2_ordertest2`, such as how many tasks are currently running, the Kafka topic partitions that are consumed and the consumption progress `DataSourceProperties`, and the corresponding Coordinator BE node `BeId`.
+Execute the [SHOW ROUTINE LOAD TASK](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD_TASK.md) statement to check the load tasks of the load job `example_tbl2_ordertest2`, such as how many tasks are currently running, the Kafka topic partitions that are consumed and the consumption progress `DataSourceProperties`, and the corresponding Coordinator BE node `BeId`.
 
 ```SQL
 MySQL [example_db]> SHOW ROUTINE LOAD TASK WHERE JobName = "example_tbl2_ordertest2" \G
@@ -501,7 +501,7 @@ DataSourceProperties: {"0":2,"3":0}
 
 ## Pause a load job
 
-You can execute the [PAUSE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/PAUSE_ROUTINE_LOAD.md) statement to pause a load job. The state of the load job will be **PAUSED** after the statement is executed. However, it has not stopped. You can execute the [RESUME ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md) statement to resume it. You can also check its status with the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) statement.
+You can execute the [PAUSE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/PAUSE_ROUTINE_LOAD.md) statement to pause a load job. The state of the load job will be **PAUSED** after the statement is executed. However, it has not stopped. You can execute the [RESUME ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md) statement to resume it. You can also check its status with the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) statement.
 
 The following example pauses the load job `example_tbl2_ordertest2`:
 
@@ -511,7 +511,7 @@ PAUSE ROUTINE LOAD FOR example_tbl2_ordertest2;
 
 ## Resume a load job
 
-You can execute the [RESUME ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md) statement to resume a paused load job. The state of the load job will be **NEED_SCHEDULE** temporarily (because the load job is being re-scheduled), and then become **RUNNING**. You can check its status with the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) statement.
+You can execute the [RESUME ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md) statement to resume a paused load job. The state of the load job will be **NEED_SCHEDULE** temporarily (because the load job is being re-scheduled), and then become **RUNNING**. You can check its status with the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) statement.
 
 The following example resumes the paused load job `example_tbl2_ordertest2`:
 
@@ -521,7 +521,7 @@ RESUME ROUTINE LOAD FOR example_tbl2_ordertest2;
 
 ## Alter a load job
 
-Before altering a load job, you must pause it with the [PAUSE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/PAUSE_ROUTINE_LOAD.md) statement. Then you can execute the [ALTER ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD.md). After altering it, you can execute the [RESUME ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md) statement to resume it, and check its status with the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) statement.
+Before altering a load job, you must pause it with the [PAUSE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/PAUSE_ROUTINE_LOAD.md) statement. Then you can execute the [ALTER ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md). After altering it, you can execute the [RESUME ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md) statement to resume it, and check its status with the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) statement.
 
 Suppose the number of the BE nodes that are alive increases to `6` and the Kafka topic partitions to be consumed is `"0,1,2,3,4,5,6,7"`. If you want to increase the actual load task concurrency, you can execute the following statement to increase the number of desired task concurrency `desired_concurrent_number` to `6` (greater than or equal to the number of BE nodes that are alive), and specify the Kafka topic partitions and initial offsets.
 
@@ -544,7 +544,7 @@ FROM kafka
 
 ## Stop a load job
 
-You can execute the [STOP ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/STOP_ROUTINE_LOAD.md) statement to stop a load job. The state of the load job will be **STOPPED** after the statement is executed, and you cannot resume a stopped load job. You cannot check the status of a stopped load job with the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) statement.
+You can execute the [STOP ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/STOP_ROUTINE_LOAD.md) statement to stop a load job. The state of the load job will be **STOPPED** after the statement is executed, and you cannot resume a stopped load job. You cannot check the status of a stopped load job with the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) statement.
 
 The following example stops the load job `example_tbl2_ordertest2`:
 
diff --git a/docs/en/loading/Spark-connector-starrocks.md b/docs/en/loading/Spark-connector-starrocks.md
index ec5a8ab889e986..c53ed9c9f6f3cc 100644
--- a/docs/en/loading/Spark-connector-starrocks.md
+++ b/docs/en/loading/Spark-connector-starrocks.md
@@ -1,10 +1,10 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Load data using Spark connector (recommended)
 
-StarRocks provides a self-developed connector named StarRocks Connector for Apache Spark™ (Spark connector for short) to help you load data into a StarRocks table by using Spark. The basic principle is to accumulate the data and then load it all at a time into StarRocks through [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md). The Spark connector is implemented based on Spark DataSource V2. A DataSource can be created by using Spark DataFrames or Spark SQL. And both batch and structured streaming modes are supported.
+StarRocks provides a self-developed connector named StarRocks Connector for Apache Spark™ (Spark connector for short) to help you load data into a StarRocks table by using Spark. The basic principle is to accumulate the data and then load it all at a time into StarRocks through [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md). The Spark connector is implemented based on Spark DataSource V2. A DataSource can be created by using Spark DataFrames or Spark SQL. And both batch and structured streaming modes are supported.
 
 > **NOTICE**
 >
@@ -176,7 +176,7 @@ Directly download the corresponding version of the Spark connector JAR from the
 
 **Required**:  NO<br/>
 **Default value**:  None<br/>
-**Description**:  The parameters that are used to control Stream Load behavior.  For example, the parameter `starrocks.write.properties.format` specifies the format of the data to be loaded, such as CSV or JSON. For a list of supported parameters and their descriptions, see [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md).
+**Description**:  The parameters that are used to control Stream Load behavior.  For example, the parameter `starrocks.write.properties.format` specifies the format of the data to be loaded, such as CSV or JSON. For a list of supported parameters and their descriptions, see [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md).
 
 ### starrocks.write.properties.format
 
diff --git a/docs/en/loading/SparkLoad.md b/docs/en/loading/SparkLoad.md
index 9eb9223f45cae7..8794ce34947c6c 100644
--- a/docs/en/loading/SparkLoad.md
+++ b/docs/en/loading/SparkLoad.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Load data in bulk using Spark Load
@@ -145,7 +145,7 @@ PROPERTIES
 `PROPERTIES` includes parameters relating to the Apache Spark™ resource, as follows:
 > **Note**
 >
-> For detailed description of Apache Spark™ resource PROPERTIES, please see [CREATE RESOURCE](../sql-reference/sql-statements/data-definition/CREATE_RESOURCE.md)
+> For detailed description of Apache Spark™ resource PROPERTIES, please see [CREATE RESOURCE](../sql-reference/sql-statements/Resource/CREATE_RESOURCE.md)
 
 - Spark related parameters:
   - `type`: Resource type, required, currently only supports `spark`.
@@ -173,7 +173,7 @@ PROPERTIES
 The above is a description of parameters for loading through Broker process. If you intend to load data without Broker process, the following should be noted.
 
 - You do not need to specify `broker`.
-- If you need to configure user authentication, and HA for NameNode nodes, you need to configure the parameters in the hdfs-site.xml file in the HDFS cluster, see [broker_properties](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#hdfs) for descriptions of parameters. and you need to move the **hdfs-site.xml** file under **$FE_HOME/conf** for each FE and **$BE_HOME/conf** for each BE.
+- If you need to configure user authentication, and HA for NameNode nodes, you need to configure the parameters in the hdfs-site.xml file in the HDFS cluster, see [broker_properties](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#hdfs) for descriptions of parameters. and you need to move the **hdfs-site.xml** file under **$FE_HOME/conf** for each FE and **$BE_HOME/conf** for each BE.
 
 > Note
 >
diff --git a/docs/en/loading/StreamLoad.md b/docs/en/loading/StreamLoad.md
index 34c6e1e73dc5e5..86dc3e736414f1 100644
--- a/docs/en/loading/StreamLoad.md
+++ b/docs/en/loading/StreamLoad.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 keywords: ['Stream Load']
 ---
 
@@ -9,8 +9,8 @@ import InsertPrivNote from '../_assets/commonMarkdown/insertPrivNote.md'
 
 StarRocks provides two methods of loading data from a local file system:
 
-- Synchronous loading using [Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)
-- Asynchronous loading using [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)
+- Synchronous loading using [Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)
+- Asynchronous loading using [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)
 
 Each of these options has its own advantages:
 
@@ -64,7 +64,7 @@ Stream Load does not support loading the data of a CSV file that contains a JSON
 
 ### Typical example
 
-This section uses curl as an example to describe how to load the data of a CSV or JSON file from your local file system into StarRocks. For detailed syntax and parameter descriptions, see [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md).
+This section uses curl as an example to describe how to load the data of a CSV or JSON file from your local file system into StarRocks. For detailed syntax and parameter descriptions, see [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md).
 
 Note that in StarRocks some literals are used as reserved keywords by the SQL language. Do not directly use these keywords in SQL statements. If you want to use such a keyword in an SQL statement, enclose it in a pair of backticks (`). See [Keywords](../sql-reference/sql-statements/keywords.md).
 
@@ -126,7 +126,7 @@ curl --location-trusted -u <username>:<password> -H "label:123" \
 :::note
 
 - If you use an account for which no password is set, you need to input only `<username>:`.
-- You can use [SHOW FRONTENDS](../sql-reference/sql-statements/Administration/SHOW_FRONTENDS.md) to view the IP address and HTTP port of the FE node.
+- You can use [SHOW FRONTENDS](../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_FRONTENDS.md) to view the IP address and HTTP port of the FE node.
 
 :::
 
@@ -149,7 +149,7 @@ SELECT * FROM table1;
 
 #### Load JSON data
 
-Since v3.2.7, Stream Load supports compressing JSON data during transmission, reducing network bandwidth overhead. Users can specify different compression algorithms using parameters `compression` and `Content-Encoding`. Supported compression algorithms including GZIP, BZIP2, LZ4_FRAME, and ZSTD. For the syntax, see [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md).
+Since v3.2.7, Stream Load supports compressing JSON data during transmission, reducing network bandwidth overhead. Users can specify different compression algorithms using parameters `compression` and `Content-Encoding`. Supported compression algorithms including GZIP, BZIP2, LZ4_FRAME, and ZSTD. For the syntax, see [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md).
 
 ##### Prepare datasets
 
@@ -203,7 +203,7 @@ curl -v --location-trusted -u <username>:<password> -H "strict_mode: true" \
 :::note
 
 - If you use an account for which no password is set, you need to input only `<username>:`.
-- You can use [SHOW FRONTENDS](../sql-reference/sql-statements/Administration/SHOW_FRONTENDS.md) to view the IP address and HTTP port of the FE node.
+- You can use [SHOW FRONTENDS](../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_FRONTENDS.md) to view the IP address and HTTP port of the FE node.
 
 :::
 
@@ -225,7 +225,7 @@ In the preceding example, the value of `code` in `example2.json` is multiplied b
 
 :::
 
-For detailed mappings between `jsonpaths`, `columns`, and the columns of the StarRocks table, see the "Column mappings" section in [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md).
+For detailed mappings between `jsonpaths`, `columns`, and the columns of the StarRocks table, see the "Column mappings" section in [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md).
 
 After the load is complete, you can query `table2` to verify that the load is successful:
 
@@ -241,7 +241,7 @@ SELECT * FROM table2;
 
 #### Check Stream Load progress
 
-After a load job is complete, StarRocks returns the result of the job in JSON format. For more information, see the "Return value" section in [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md).
+After a load job is complete, StarRocks returns the result of the job in JSON format. For more information, see the "Return value" section in [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md).
 
 Stream Load does not allow you to query the result of a load job by using the SHOW LOAD statement.
 
@@ -283,7 +283,7 @@ This section describes some system parameters that you need to configure if you
 
   :::
 
-  Stream Load also provides the `timeout` parameter, which allows you to specify the timeout period of an individual load job. For more information, see [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md).
+  Stream Load also provides the `timeout` parameter, which allows you to specify the timeout period of an individual load job. For more information, see [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md).
 
 ### Usage notes
 
@@ -300,7 +300,7 @@ Broker Load is an asynchronous loading method. After you submit a load job, Star
 ### Limits
 
 - Currently Broker Load supports loading from a local file system only through a single broker whose version is v2.5 or later.
-- Highly concurrent queries against a single broker may cause issues such as timeout and OOM. To mitigate the impact, you can use the `pipeline_dop` variable (see [System variable](../reference/System_variable.md#pipeline_dop)) to set the query parallelism for Broker Load. For queries against a single broker, we recommend that you set `pipeline_dop` to a value smaller than `16`.
+- Highly concurrent queries against a single broker may cause issues such as timeout and OOM. To mitigate the impact, you can use the `pipeline_dop` variable (see [System variable](../sql-reference/System_variable.md#pipeline_dop)) to set the query parallelism for Broker Load. For queries against a single broker, we recommend that you set `pipeline_dop` to a value smaller than `16`.
 
 ### Typical example
 
@@ -379,13 +379,13 @@ This job has four main sections:
 - `LOAD` declaration: The source URI, source data format, and destination table name.
 - `PROPERTIES`: The timeout value and any other properties to apply to the load job.
 
-For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 #### Check Broker Load progress
 
-In v3.0 and earlier, use the [SHOW LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md) statement or the curl command to view the progress of Broker Load jobs.
+In v3.0 and earlier, use the [SHOW LOAD](../sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md) statement or the curl command to view the progress of Broker Load jobs.
 
-In v3.1 and later, you can view the progress of Broker Load jobs from the [`information_schema.loads`](../reference/information_schema/loads.md) view:
+In v3.1 and later, you can view the progress of Broker Load jobs from the [`information_schema.loads`](../sql-reference/information_schema/loads.md) view:
 
 ```SQL
 SELECT * FROM information_schema.loads;
@@ -418,7 +418,7 @@ SELECT * FROM mytable;
 
 #### Cancel a Broker Load job
 
-When a load job is not in the **CANCELLED** or **FINISHED** stage, you can use the [CANCEL LOAD](../sql-reference/sql-statements/data-manipulation/CANCEL_LOAD.md) statement to cancel the job.
+When a load job is not in the **CANCELLED** or **FINISHED** stage, you can use the [CANCEL LOAD](../sql-reference/sql-statements/loading_unloading/CANCEL_LOAD.md) statement to cancel the job.
 
 For example, you can execute the following statement to cancel a load job, whose label is `label_local`, in the database `mydatabase`:
 
@@ -462,6 +462,6 @@ This section introduces the second way. Detailed operations are as follows:
    - `BROKER`: You do not need to specify the broker name.
    - `PROPERTIES`: The timeout value and any other properties to apply to the load job.
 
-   For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+   For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 After you submit a job, you can view the load progress or cancel the job as needed. For detailed operations, see "[Check Broker Load progress](#check-broker-load-progress)" and "[Cancel a Broker Load job](#cancel-a-broker-load-job) in this topic.
diff --git a/docs/en/loading/Stream_Load_transaction_interface.md b/docs/en/loading/Stream_Load_transaction_interface.md
index 36c3e086915c4c..e487b93e5bc3d2 100644
--- a/docs/en/loading/Stream_Load_transaction_interface.md
+++ b/docs/en/loading/Stream_Load_transaction_interface.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 keywords: ['Stream Load']
 ---
 
@@ -500,4 +500,4 @@ curl --location-trusted -u <jack>:<123456> -H "label:streamload_txn_example1_tab
 
 For information about the suitable application scenarios and supported data file formats of Stream Load and about how Stream Load works, see [Loading from a local file system via Stream Load](../loading/StreamLoad.md#loading-from-a-local-file-system-via-stream-load).
 
-For information about the syntax and parameters for creating Stream Load jobs, see [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md).
+For information about the syntax and parameters for creating Stream Load jobs, see [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md).
diff --git a/docs/en/loading/automq-routine-load.md b/docs/en/loading/automq-routine-load.md
index 6ec35fdd0536ac..8c416165021a33 100644
--- a/docs/en/loading/automq-routine-load.md
+++ b/docs/en/loading/automq-routine-load.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 description: Cloud based Kafka from AutoMQ
 ---
 
diff --git a/docs/en/loading/azure.md b/docs/en/loading/azure.md
index af612c658b4388..41506e979178ef 100644
--- a/docs/en/loading/azure.md
+++ b/docs/en/loading/azure.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 keywords: ['Broker Load']
 ---
@@ -10,8 +10,8 @@ import InsertPrivNote from '../_assets/commonMarkdown/insertPrivNote.md'
 
 StarRocks provides the following options for loading data from Azure:
 
-- Synchronous loading using [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md)+[`FILES()`](../sql-reference/sql-functions/table-functions/files.md)
-- Asynchronous loading using [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)
+- Synchronous loading using [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md)+[`FILES()`](../sql-reference/sql-functions/table-functions/files.md)
+- Asynchronous loading using [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)
 
 Each of these options has its own advantages, which are detailed in the following sections.
 
@@ -52,9 +52,9 @@ This method is available from v3.2 onwards and currently supports only the Parqu
 
 With `FILES()`, you can:
 
-- Query the data directly from Azure using [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md).
-- Create and load a table using [CREATE TABLE AS SELECT](../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md) (CTAS).
-- Load the data into an existing table using [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md).
+- Query the data directly from Azure using [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md).
+- Create and load a table using [CREATE TABLE AS SELECT](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md) (CTAS).
+- Load the data into an existing table using [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md).
 
 ### Typical examples
 
@@ -127,7 +127,7 @@ SELECT * FROM FILES
 );
 ```
 
-After creating the table, you can view its schema by using [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md):
+After creating the table, you can view its schema by using [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md):
 
 ```SQL
 DESCRIBE user_behavior_inferred;
@@ -270,13 +270,13 @@ The system returns a query result similar to the following, indicating that the
 
 #### Check load progress
 
-You can query the progress of INSERT jobs from the [`loads`](../reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards. Example:
+You can query the progress of INSERT jobs from the [`loads`](../sql-reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards. Example:
 
 ```SQL
 SELECT * FROM information_schema.loads ORDER BY JOB_ID DESC;
 ```
 
-For information about the fields provided in the `loads` view, see [`loads`](../reference/information_schema/loads.md).
+For information about the fields provided in the `loads` view, see [`loads`](../sql-reference/information_schema/loads.md).
 
 If you have submitted multiple load jobs, you can filter on the `LABEL` associated with the job. Example:
 
@@ -395,17 +395,17 @@ This job has four main sections:
 - `BROKER`: The connection details for the source.
 - `PROPERTIES`: The timeout value and any other properties to apply to the load job.
 
-For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 #### Check load progress
 
-You can query the progress of Broker Load jobs from the [`loads`](../reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards.
+You can query the progress of Broker Load jobs from the [`loads`](../sql-reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards.
 
 ```SQL
 SELECT * FROM information_schema.loads \G
 ```
 
-For information about the fields provided in the `loads` view, see [`loads`](../reference/information_schema/loads.md).
+For information about the fields provided in the `loads` view, see [`loads`](../sql-reference/information_schema/loads.md).
 
 If you have submitted multiple load jobs, you can filter on the `LABEL` associated with the job:
 
diff --git a/docs/en/loading/cloud_storage_load.md b/docs/en/loading/cloud_storage_load.md
index 23ad5008d99ae4..ee06e4ab7a425e 100644
--- a/docs/en/loading/cloud_storage_load.md
+++ b/docs/en/loading/cloud_storage_load.md
@@ -1,12 +1,12 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Load data from cloud storage
 
 import InsertPrivNote from '../_assets/commonMarkdown/insertPrivNote.md'
 
-StarRocks supports using one of the following methods to load huge amounts of data from cloud storage: [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) and [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md).
+StarRocks supports using one of the following methods to load huge amounts of data from cloud storage: [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) and [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md).
 
 In v3.0 and earlier, StarRocks only supports Broker Load, which runs in asynchronous loading mode. After you submit a load job, StarRocks asynchronously runs the job. You can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information, see the "[View a load job](#view-a-load-job)" section of this topic.
 
@@ -18,7 +18,7 @@ Additionally, Broker Load supports data transformation at data loading and suppo
 
 From v3.1 onwards, StarRocks supports directly loading the data of specific file formats from AWS S3 by using the INSERT command and the FILES keyword, saving you from the trouble of creating an external table first. For more information, see [INSERT > Insert data directly from files in an external source using FILES keyword](../loading/InsertInto.md#insert-data-directly-from-files-in-an-external-source-using-files).
 
-This topic focuses on using [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) to load data from cloud storage.
+This topic focuses on using [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) to load data from cloud storage.
 
 ## Supported data file formats
 
@@ -99,7 +99,7 @@ The following figure shows the workflow of a Broker Load job.
 
 Note that Broker Load supports accessing AWS S3 according to the S3 or S3A protocol. Therefore, when you load data from AWS S3, you can include `s3://` or `s3a://` as the prefix in the S3 URI that you pass as the file path (`DATA INFILE`).
 
-Also, note that the following examples use the CSV file format and the instance profile-based authentication method. For information about how to load data in other formats and about the authentication parameters that you need to configure when using other authentication methods, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+Also, note that the following examples use the CSV file format and the instance profile-based authentication method. For information about how to load data in other formats and about the authentication parameters that you need to configure when using other authentication methods, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 ### Load a single data file into a single table
 
@@ -130,7 +130,7 @@ PROPERTIES
 
 After you submit the load job, you can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information, see the "[View a load job](#view-a-load-job)" section of this topic.
 
-After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the data of `table1`:
+After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the data of `table1`:
 
 ```SQL
 SELECT * FROM table1;
@@ -174,7 +174,7 @@ PROPERTIES
 
 After you submit the load job, you can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information, see the "[View a load job](#view-a-load-job)" section of this topic.
 
-After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the data of `table1`:
+After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the data of `table1`:
 
 ```SQL
 SELECT * FROM table1;
@@ -227,7 +227,7 @@ PROPERTIES
 
 After you submit the load job, you can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information, see the "[View a load job](#view-a-load-job)" section of this topic.
 
-After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the data of `table1` and `table2`:
+After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the data of `table1` and `table2`:
 
 1. Query `table1`:
 
@@ -263,7 +263,7 @@ After you confirm that the load job is successful, you can use [SELECT](../sql-r
 
 Note that Broker Load supports accessing Google GCS only according to the gs protocol. Therefore, when you load data from Google GCS, you must include `gs://` as the prefix in the GCS URI that you pass as the file path (`DATA INFILE`).
 
-Also, note that the following examples use the CSV file format and the VM-based authentication method. For information about how to load data in other formats and about the authentication parameters that you need to configure when using other authentication methods, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+Also, note that the following examples use the CSV file format and the VM-based authentication method. For information about how to load data in other formats and about the authentication parameters that you need to configure when using other authentication methods, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 ### Load a single data file into a single table
 
@@ -293,7 +293,7 @@ PROPERTIES
 
 After you submit the load job, you can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information, see the "[View a load job](#view-a-load-job)" section of this topic.
 
-After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the data of `table1`:
+After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the data of `table1`:
 
 ```SQL
 SELECT * FROM table1;
@@ -336,7 +336,7 @@ PROPERTIES
 
 After you submit the load job, you can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information, see the "[View a load job](#view-a-load-job)" section of this topic.
 
-After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the data of `table1`:
+After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the data of `table1`:
 
 ```SQL
 SELECT * FROM table1;
@@ -388,7 +388,7 @@ PROPERTIES
 
 After you submit the load job, you can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information, see the "[View a load job](#view-a-load-job)" section of this topic.
 
-After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the data of `table1` and `table2`:
+After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the data of `table1` and `table2`:
 
 1. Query `table1`:
 
@@ -432,7 +432,7 @@ Note that when you load data from Azure Storage, you need to determine which pre
   - If your Data Lake Storage Gen2 allows access only via HTTP, use `abfs://` as the prefix, for example, `abfs://<container>@<storage_account>.dfs.core.windows.net/<file_name>`.
   - If your Data Lake Storage Gen2 allows access only via HTTPS, use `abfss://` as the prefix, for example, `abfss://<container>@<storage_account>.dfs.core.windows.net/<file_name>`.
 
-Also, note that the following examples use the CSV file format, Azure Blob Storage, and the shared key-based authentication method. For information about how to load data in other formats and about the authentication parameters that you need to configure when using other Azure storage services and authentication methods, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+Also, note that the following examples use the CSV file format, Azure Blob Storage, and the shared key-based authentication method. For information about how to load data in other formats and about the authentication parameters that you need to configure when using other Azure storage services and authentication methods, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 ### Load a single data file into a single table
 
@@ -463,7 +463,7 @@ PROPERTIES
 
 After you submit the load job, you can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information, see the "[View a load job](#view-a-load-job)" section of this topic.
 
-After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the data of `table1`:
+After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the data of `table1`:
 
 ```SQL
 SELECT * FROM table1;
@@ -507,7 +507,7 @@ PROPERTIES
 
 After you submit the load job, you can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information, see the "[View a load job](#view-a-load-job)" section of this topic.
 
-After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the data of `table1`:
+After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the data of `table1`:
 
 ```SQL
 SELECT * FROM table1;
@@ -560,7 +560,7 @@ PROPERTIES
 
 After you submit the load job, you can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information, see the "[View a load job](#view-a-load-job)" section of this topic.
 
-After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the data of `table1` and `table2`:
+After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the data of `table1` and `table2`:
 
 1. Query `table1`:
 
@@ -594,7 +594,7 @@ After you confirm that the load job is successful, you can use [SELECT](../sql-r
 
 ## Load data from an S3-compatible storage system
 
-The following examples use the CSV file format and the MinIO storage system. For information about how to load data in other formats, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+The following examples use the CSV file format and the MinIO storage system. For information about how to load data in other formats, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 ### Load a single data file into a single table
 
@@ -628,7 +628,7 @@ PROPERTIES
 
 After you submit the load job, you can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information, see the "[View a load job](#view-a-load-job)" section of this topic.
 
-After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the data of `table1`:
+After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the data of `table1`:
 
 ```SQL
 SELECT * FROM table1;
@@ -675,7 +675,7 @@ PROPERTIES
 
 After you submit the load job, you can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information, see the "[View a load job](#view-a-load-job)" section of this topic.
 
-After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the data of `table1`:
+After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the data of `table1`:
 
 ```SQL
 SELECT * FROM table1;
@@ -731,7 +731,7 @@ PROPERTIES
 
 After you submit the load job, you can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information, see the "[View a load job](#view-a-load-job)" section of this topic.
 
-After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) to query the data of `table1` and `table2`:
+After you confirm that the load job is successful, you can use [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) to query the data of `table1` and `table2`:
 
 1. Query `table1`:
 
@@ -765,7 +765,7 @@ After you confirm that the load job is successful, you can use [SELECT](../sql-r
 
 ## View a load job
 
-Use the [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) statement to query the results of one or more load jobs from the `loads` table in the `information_schema` database. This feature is supported from v3.1 onwards.
+Use the [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) statement to query the results of one or more load jobs from the `loads` table in the `information_schema` database. This feature is supported from v3.1 onwards.
 
 Example 1: Query the results of load jobs executed on the `test_db` database. In the query statement, specify that a maximum of two results can be returned and the return results must be sorted by creation time (`CREATE_TIME`) in descending order.
 
@@ -865,11 +865,11 @@ The following result is returned:
 REJECTED_RECORD_PATH: 172.26.95.92:/home/disk1/sr/be/storage/rejected_record/test_db/label_brokerload_unqualifiedtest_0728/6/404a20b1e4db4d27_8aa9af1e8d6d8bdc
 ```
 
-For information about the fields in the return results, see [Information Schema > loads](../reference/information_schema/loads.md).
+For information about the fields in the return results, see [Information Schema > loads](../sql-reference/information_schema/loads.md).
 
 ## Cancel a load job
 
-When a load job is not in the **CANCELLED** or **FINISHED** stage, you can use the [CANCEL LOAD](../sql-reference/sql-statements/data-manipulation/CANCEL_LOAD.md) statement to cancel the job.
+When a load job is not in the **CANCELLED** or **FINISHED** stage, you can use the [CANCEL LOAD](../sql-reference/sql-statements/loading_unloading/CANCEL_LOAD.md) statement to cancel the job.
 
 For example, you can execute the following statement to cancel a load job, whose label is `label1`, in the database `test_db`:
 
diff --git a/docs/en/loading/gcs.md b/docs/en/loading/gcs.md
index 359311cdae99d0..2c3cf58c61d82d 100644
--- a/docs/en/loading/gcs.md
+++ b/docs/en/loading/gcs.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 keywords: ['Broker Load']
 ---
@@ -10,8 +10,8 @@ import InsertPrivNote from '../_assets/commonMarkdown/insertPrivNote.md'
 
 StarRocks provides the following options for loading data from GCS:
 
-- Synchronous loading using [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md)+[`FILES()`](../sql-reference/sql-functions/table-functions/files.md)
-- Asynchronous loading using [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)
+- Synchronous loading using [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md)+[`FILES()`](../sql-reference/sql-functions/table-functions/files.md)
+- Asynchronous loading using [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)
 
 Each of these options has its own advantages, which are detailed in the following sections.
 
@@ -52,9 +52,9 @@ This method is available from v3.2 onwards and currently supports only the Parqu
 
 With `FILES()`, you can:
 
-- Query the data directly from GCS using [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md).
-- Create and load a table using [CREATE TABLE AS SELECT](../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md) (CTAS).
-- Load the data into an existing table using [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md).
+- Query the data directly from GCS using [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md).
+- Create and load a table using [CREATE TABLE AS SELECT](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md) (CTAS).
+- Load the data into an existing table using [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md).
 
 ### Typical examples
 
@@ -137,7 +137,7 @@ SELECT * FROM FILES
 >
 > Substitute the credentials in the above command with your own credentials. Any valid service account email, key, and secret can be used, as the object is readable by any GCP authenticated user.
 
-After creating the table, you can view its schema by using [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md):
+After creating the table, you can view its schema by using [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md):
 
 ```SQL
 DESCRIBE user_behavior_inferred;
@@ -285,13 +285,13 @@ The system returns a query result similar to the following, indicating that the
 
 #### Check load progress
 
-You can query the progress of INSERT jobs from the [`loads`](../reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards. Example:
+You can query the progress of INSERT jobs from the [`loads`](../sql-reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards. Example:
 
 ```SQL
 SELECT * FROM information_schema.loads ORDER BY JOB_ID DESC;
 ```
 
-For information about the fields provided in the `loads` view, see [`loads`](../reference/information_schema/loads.md).
+For information about the fields provided in the `loads` view, see [`loads`](../sql-reference/information_schema/loads.md).
 
 If you have submitted multiple load jobs, you can filter on the `LABEL` associated with the job. Example:
 
@@ -416,17 +416,17 @@ This job has four main sections:
 - `BROKER`: The connection details for the source.
 - `PROPERTIES`: The timeout value and any other properties to apply to the load job.
 
-For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 #### Check load progress
 
-You can query the progress of INSERT jobs from the [`loads`](../reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards.
+You can query the progress of INSERT jobs from the [`loads`](../sql-reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards.
 
 ```SQL
 SELECT * FROM information_schema.loads;
 ```
 
-For information about the fields provided in the `loads` view, see [`loads`](../reference/information_schema/loads.md).
+For information about the fields provided in the `loads` view, see [`loads`](../sql-reference/information_schema/loads.md).
 
 If you have submitted multiple load jobs, you can filter on the `LABEL` associated with the job. Example:
 
diff --git a/docs/en/loading/hdfs_load.md b/docs/en/loading/hdfs_load.md
index 8bccd8a992ded4..d2c55df020f0b5 100644
--- a/docs/en/loading/hdfs_load.md
+++ b/docs/en/loading/hdfs_load.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 keywords: ['Broker Load']
 ---
@@ -40,9 +40,9 @@ This method is available from v3.1 onwards and currently supports only the Parqu
 
 With `FILES()`, you can:
 
-- Query the data directly from HDFS using [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md).
-- Create and load a table using [CREATE TABLE AS SELECT](../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md) (CTAS).
-- Load the data into an existing table using [INSERT](../sql-reference/sql-statements/data-manipulation/SELECT.md).
+- Query the data directly from HDFS using [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md).
+- Create and load a table using [CREATE TABLE AS SELECT](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md) (CTAS).
+- Load the data into an existing table using [INSERT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md).
 
 ### Typical examples
 
@@ -117,7 +117,7 @@ SELECT * FROM FILES
 );
 ```
 
-After creating the table, you can view its schema by using [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md):
+After creating the table, you can view its schema by using [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md):
 
 ```SQL
 DESCRIBE user_behavior_inferred;
@@ -261,13 +261,13 @@ The following query result is returned, indicating that the data has been succes
 
 #### Check load progress
 
-You can query the progress of INSERT jobs from the [`loads`](../reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards. Example:
+You can query the progress of INSERT jobs from the [`loads`](../sql-reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards. Example:
 
 ```SQL
 SELECT * FROM information_schema.loads ORDER BY JOB_ID DESC;
 ```
 
-For information about the fields provided in the `loads` view, see [`loads`](../reference/information_schema/loads.md).
+For information about the fields provided in the `loads` view, see [`loads`](../sql-reference/information_schema/loads.md).
 
 If you have submitted multiple load jobs, you can filter on the `LABEL` associated with the job. Example:
 
@@ -387,7 +387,7 @@ This job has four main sections:
 - `BROKER`: The connection details for the source.
 - `PROPERTIES`: The timeout value and any other properties to apply to the load job.
 
-For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 #### Check load progress
 
@@ -397,7 +397,7 @@ You can query the progress of Broker Load jobs from the `information_schema.load
 SELECT * FROM information_schema.loads;
 ```
 
-For information about the fields provided in the `loads` view, see [Information Schema](../reference/information_schema/loads.md)).
+For information about the fields provided in the `loads` view, see [Information Schema](../sql-reference/information_schema/loads.md)).
 
 If you have submitted multiple load jobs, you can filter on the `LABEL` associated with the job. Example:
 
@@ -524,11 +524,11 @@ This job has four main sections:
 - `INSERT_SQL`: The INSERT INTO SELECT FROM FILES statement that is used to load data from the specified source data file to the destination table.
 - `PROPERTIES`: A set of optional parameters that specify how to execute the pipe. These include `AUTO_INGEST`, `POLL_INTERVAL`, `BATCH_SIZE`, and `BATCH_FILES`. Specify these properties in the `"key" = "value"` format.
 
-For detailed syntax and parameter descriptions, see [CREATE PIPE](../sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md).
+For detailed syntax and parameter descriptions, see [CREATE PIPE](../sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md).
 
 #### Check load progress
 
-- Query the progress of Pipe jobs by using [SHOW PIPES](../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md).
+- Query the progress of Pipe jobs by using [SHOW PIPES](../sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md).
 
   ```SQL
   SHOW PIPES;
@@ -550,7 +550,7 @@ For detailed syntax and parameter descriptions, see [CREATE PIPE](../sql-referen
   1 row in set (0.00 sec)
   ```
 
-- Query the progress of Pipe jobs from the [`pipes`](../reference/information_schema/pipes.md) view in the StarRocks Information Schema.
+- Query the progress of Pipe jobs from the [`pipes`](../sql-reference/information_schema/pipes.md) view in the StarRocks Information Schema.
 
   ```SQL
   SELECT * FROM information_schema.pipes;
@@ -574,7 +574,7 @@ For detailed syntax and parameter descriptions, see [CREATE PIPE](../sql-referen
 
 #### Check file status
 
-You can query the load status of the files loaded from the [`pipe_files`](../reference/information_schema/pipe_files.md) view in the StarRocks Information Schema.
+You can query the load status of the files loaded from the [`pipe_files`](../sql-reference/information_schema/pipe_files.md) view in the StarRocks Information Schema.
 
 ```SQL
 SELECT * FROM information_schema.pipe_files;
@@ -602,4 +602,4 @@ FINISH_LOAD_TIME: 2023-11-17 16:13:22
 
 #### Manage Pipes
 
-You can alter, suspend or resume, drop, or query the pipes you have created and retry to load specific data files. For more information, see [ALTER PIPE](../sql-reference/sql-statements/data-manipulation/ALTER_PIPE.md), [SUSPEND or RESUME PIPE](../sql-reference/sql-statements/data-manipulation/SUSPEND_or_RESUME_PIPE.md), [DROP PIPE](../sql-reference/sql-statements/data-manipulation/DROP_PIPE.md), [SHOW PIPES](../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md), and [RETRY FILE](../sql-reference/sql-statements/data-manipulation/RETRY_FILE.md).
+You can alter, suspend or resume, drop, or query the pipes you have created and retry to load specific data files. For more information, see [ALTER PIPE](../sql-reference/sql-statements/loading_unloading/pipe/ALTER_PIPE.md), [SUSPEND or RESUME PIPE](../sql-reference/sql-statements/loading_unloading/pipe/SUSPEND_or_RESUME_PIPE.md), [DROP PIPE](../sql-reference/sql-statements/loading_unloading/pipe/DROP_PIPE.md), [SHOW PIPES](../sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md), and [RETRY FILE](../sql-reference/sql-statements/loading_unloading/pipe/RETRY_FILE.md).
diff --git a/docs/en/loading/load_concept/strict_mode.md b/docs/en/loading/load_concept/strict_mode.md
index a0bb543e0ad509..187206b697cc8c 100644
--- a/docs/en/loading/load_concept/strict_mode.md
+++ b/docs/en/loading/load_concept/strict_mode.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Strict mode
@@ -21,7 +21,7 @@ Note the following points:
 
 - In actual business scenarios, both qualified and unqualified rows may contain `NULL` values. If the destination columns do not allow `NULL` values, StarRocks reports errors and filters out the rows that contain `NULL` values.
 
-- The maximum percentage of unqualified rows that can be filtered out for a [Stream Load](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md), [Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md), [Routine Load](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md), or [Spark Load](../../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md) job is controlled by an optional job property `max_filter_ratio`. [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md) does not support setting the `max_filter_ratio` property.
+- The maximum percentage of unqualified rows that can be filtered out for a [Stream Load](../../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md), [Broker Load](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md), [Routine Load](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md), or [Spark Load](../../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md) job is controlled by an optional job property `max_filter_ratio`. [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md) does not support setting the `max_filter_ratio` property.
 
 For example, you want to load four rows that hold `\N` (`\N` denotes a `NULL` value), `abc`, `2000`, and `1` values respectively in a column from a CSV-formatted data file into a StarRocks table, and the data type of the destination StarRocks table column is TINYINT [-128, 127].
 
@@ -61,9 +61,9 @@ If strict mode is enabled, StarRocks loads only the rows that hold `\N` or `1` a
 
 ## Set strict mode
 
-If you run a [Stream Load](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md), [Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md), [Routine Load](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md), or [Spark Load](../../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md) job to load data, use the `strict_mode` parameter to set strict mode for the load job. Valid values are `true` and `false`. The default value is `false`. The value `true` enables strict mode, and the value `false` disables strict mode.
+If you run a [Stream Load](../../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md), [Broker Load](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md), [Routine Load](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md), or [Spark Load](../../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md) job to load data, use the `strict_mode` parameter to set strict mode for the load job. Valid values are `true` and `false`. The default value is `false`. The value `true` enables strict mode, and the value `false` disables strict mode.
 
-If you execute [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md) to load data, use the `enable_insert_strict` session variable to set strict mode. Valid values are `true` and `false`. The default value is `true`. The value `true` enables strict mode, and the value `false` disables strict mode.
+If you execute [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md) to load data, use the `enable_insert_strict` session variable to set strict mode. Valid values are `true` and `false`. The default value is `true`. The value `true` enables strict mode, and the value `false` disables strict mode.
 
 Examples are as follows:
 
@@ -76,7 +76,7 @@ curl --location-trusted -u <username>:<password> \
     http://<fe_host>:<fe_http_port>/api/<database_name>/<table_name>/_stream_load
 ```
 
-For detailed syntax and parameters about Stream Load, see [STREAM LOAD](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md).
+For detailed syntax and parameters about Stream Load, see [STREAM LOAD](../../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md).
 
 ### Broker Load
 
@@ -97,7 +97,7 @@ PROPERTIES
 )
 ```
 
-The preceding code snippet uses HDFS as an example. For detailed syntax and parameters about Broker Load, see [BROKER LOAD](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+The preceding code snippet uses HDFS as an example. For detailed syntax and parameters about Broker Load, see [BROKER LOAD](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 ### Routine Load
 
@@ -114,7 +114,7 @@ FROM KAFKA
 )
 ```
 
-The preceding code snippet uses Apache Kafka® as an example. For detailed syntax and parameters about Routine Load, see [CREATE ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md).
+The preceding code snippet uses Apache Kafka® as an example. For detailed syntax and parameters about Routine Load, see [CREATE ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md).
 
 ### Spark Load
 
@@ -136,7 +136,7 @@ PROPERTIES
 )
 ```
 
-The preceding code snippet uses HDFS as an example. For detailed syntax and parameters about Spark Load, see [SPARK LOAD](../../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md).
+The preceding code snippet uses HDFS as an example. For detailed syntax and parameters about Spark Load, see [SPARK LOAD](../../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md).
 
 ### INSERT
 
@@ -145,4 +145,4 @@ SET enable_insert_strict = {true | false};
 INSERT INTO <table_name> ...
 ```
 
-For detailed syntax and parameters about INSERT, see [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md).
+For detailed syntax and parameters about INSERT, see [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md).
diff --git a/docs/en/loading/load_from_pulsar.md b/docs/en/loading/load_from_pulsar.md
index bb94d792058cae..fd701ebb1afabc 100644
--- a/docs/en/loading/load_from_pulsar.md
+++ b/docs/en/loading/load_from_pulsar.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # [Preview] Continuously load data from Apache® Pulsar™
@@ -48,7 +48,7 @@ The type of a subscription is defined when a consumer connects to it, and the ty
 
 ## Create a Routine Load job
 
-The following examples describe how to consume CSV-formatted messages in Pulsar, and load the data into StarRocks by creating a Routine Load job. For detailed instruction and reference, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md).
+The following examples describe how to consume CSV-formatted messages in Pulsar, and load the data into StarRocks by creating a Routine Load job. For detailed instruction and reference, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md).
 
 ```SQL
 CREATE ROUTINE LOAD load_test.routine_wiki_edit_1 ON routine_wiki_edit
@@ -73,7 +73,7 @@ FROM PULSAR
 );
 ```
 
-When Routine Load is created to consume data from Pulsar, most input parameters except for `data_source_properties` are the same as consuming data from Kafka . For descriptions about parameters except data_source_properties `data_source_properties` , see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md).
+When Routine Load is created to consume data from Pulsar, most input parameters except for `data_source_properties` are the same as consuming data from Kafka . For descriptions about parameters except data_source_properties `data_source_properties` , see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md).
 
 The parameters related to `data_source_properties` and their descriptions are as follows:
 
@@ -95,7 +95,7 @@ Routine Load supports the following custom parameters for Pulsar.
 
 ### Check a load job
 
-Execute the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation//SHOW_ROUTINE_LOAD.md) statement to check the status of the load job `routine_wiki_edit_1`. StarRocks returns the execution state `State`, the statistical information (including the total rows consumed and the total rows loaded) `Statistics`, and the progress of the load job `progress`.
+Execute the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) statement to check the status of the load job `routine_wiki_edit_1`. StarRocks returns the execution state `State`, the statistical information (including the total rows consumed and the total rows loaded) `Statistics`, and the progress of the load job `progress`.
 
 When you check a Routine Load job that consumes data from Pulsar, most returned parameters except for `progress` are the same as consuming data from Kafka.  `progress` refers to backlog, that is the number of unacked messages in a partition.
 
@@ -125,7 +125,7 @@ ReasonOfStateChanged:
 
 ### Check a load task
 
-Execute the [SHOW ROUTINE LOAD TASK](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD_TASK.md) statement to check the load tasks of the load job `routine_wiki_edit_1`, such as how many tasks are running, the Kafka topic partitions that are consumed and the consumption progress `DataSourceProperties`, and the corresponding Coordinator BE node `BeId`.
+Execute the [SHOW ROUTINE LOAD TASK](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD_TASK.md) statement to check the load tasks of the load job `routine_wiki_edit_1`, such as how many tasks are running, the Kafka topic partitions that are consumed and the consumption progress `DataSourceProperties`, and the corresponding Coordinator BE node `BeId`.
 
 ```SQL
 MySQL [example_db]> SHOW ROUTINE LOAD TASK WHERE JobName = "routine_wiki_edit_1" \G
@@ -133,7 +133,7 @@ MySQL [example_db]> SHOW ROUTINE LOAD TASK WHERE JobName = "routine_wiki_edit_1"
 
 ## Alter a load job
 
-Before altering a load job, you must pause it by using the [PAUSE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/PAUSE_ROUTINE_LOAD.md) statement. Then you can execute the [ALTER ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD.md). After altering it, you can execute the [RESUME ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md) statement to resume it, and check its status by using the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) statement.
+Before altering a load job, you must pause it by using the [PAUSE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/PAUSE_ROUTINE_LOAD.md) statement. Then you can execute the [ALTER ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md). After altering it, you can execute the [RESUME ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md) statement to resume it, and check its status by using the [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) statement.
 
 When Routine Load is used to consume data from Pulsar, most returned parameters except for `data_source_properties` are the same as consuming data from Kafka.
 
diff --git a/docs/en/loading/loading.mdx b/docs/en/loading/loading.mdx
index acdbc52e48e264..373d3aabf363c7 100644
--- a/docs/en/loading/loading.mdx
+++ b/docs/en/loading/loading.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Data loading
diff --git a/docs/en/loading/loading_introduction/Loading_intro.md b/docs/en/loading/loading_introduction/Loading_intro.md
index 25be05b0a5ab65..99ee82fdfd3264 100644
--- a/docs/en/loading/loading_introduction/Loading_intro.md
+++ b/docs/en/loading/loading_introduction/Loading_intro.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 3
 ---
 
@@ -63,7 +63,7 @@ In the following sections, "batch" or "batch loading" refers to the loading of a
 
 **Data volume:** 10 GB or less
 
-### [Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)
+### [Broker Load](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)
 
 **Business scenario:**
 
@@ -74,7 +74,7 @@ In the following sections, "batch" or "batch loading" refers to the loading of a
 
 **Data volume:** Dozens of GB to hundreds of GB
 
-### [Pipe](../../sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md)
+### [Pipe](../../sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md)
 
 **Business scenario:** Batch load or stream data from HDFS or AWS S3.
 
@@ -88,7 +88,7 @@ This loading method is supported from v3.2 onwards.
 
 **Data volume:** 100 GB to 1 TB or more
 
-### [Routine Load](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md)
+### [Routine Load](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md)
 
 **Business scenario:** Stream data from Kafka.
 
@@ -96,7 +96,7 @@ This loading method is supported from v3.2 onwards.
 
 **Data volume:** MBs to GBs of data as mini-batches
 
-### [Spark Load](../../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md)
+### [Spark Load](../../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md)
 
 **Business scenario:** Batch load data of Apache Hive™ tables stored in HDFS by using Spark clusters.
 
diff --git a/docs/en/loading/loading_introduction/feature-support-loading-and-unloading.md b/docs/en/loading/loading_introduction/feature-support-loading-and-unloading.md
index 2fd4d1b490cba0..e17a33ee6c0557 100644
--- a/docs/en/loading/loading_introduction/feature-support-loading-and-unloading.md
+++ b/docs/en/loading/loading_introduction/feature-support-loading-and-unloading.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_label: "Feature Support"
 ---
 
diff --git a/docs/en/loading/loading_introduction/loading_concepts.md b/docs/en/loading/loading_introduction/loading_concepts.md
index f682bc8d950588..6e960c39e22a68 100644
--- a/docs/en/loading/loading_introduction/loading_concepts.md
+++ b/docs/en/loading/loading_introduction/loading_concepts.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 ---
 
@@ -27,7 +27,7 @@ StarRocks supports two communication protocols that can be used to submit load j
 
 ## Data types
 
-StarRocks supports loading data of all data types. You only need to take note of the limits on the loading of a few specific data types. For more information, see [Data types](../../sql-reference/data-types/data-type-list.md).
+StarRocks supports loading data of all data types. You only need to take note of the limits on the loading of a few specific data types. For more information, see [Data types](../../sql-reference/data-types/README.md).
 
 ## Strict mode
 
@@ -67,11 +67,11 @@ In asynchronous loading mode, after you submit a load job, StarRocks immediately
 
 :::tip
 
-You can set different write quorum for tables, that is, how many replicas are required to return loading success before StarRocks can determine the loading task is successful. You can specify write quorum by adding the property `write_quorum` when you [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md), or add this property to an existing table using [ALTER TABLE](../../sql-reference/sql-statements/data-definition/ALTER_TABLE.md).
+You can set different write quorum for tables, that is, how many replicas are required to return loading success before StarRocks can determine the loading task is successful. You can specify write quorum by adding the property `write_quorum` when you [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md), or add this property to an existing table using [ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md).
 
 :::
 
-StarRocks provides four loading methods that support asynchronous loading: [Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md), [Pipe](../../sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md), [Routine Load](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md), and [Spark Load](../../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md).
+StarRocks provides four loading methods that support asynchronous loading: [Broker Load](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md), [Pipe](../../sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md), [Routine Load](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md), and [Spark Load](../../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md).
 
 The process of asynchronous loading is as follows:
 
diff --git a/docs/en/loading/loading_introduction/loading_considerations.md b/docs/en/loading/loading_introduction/loading_considerations.md
index ae6274be43d2e2..8c189f081490c5 100644
--- a/docs/en/loading/loading_introduction/loading_considerations.md
+++ b/docs/en/loading/loading_introduction/loading_considerations.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 ---
 
@@ -11,7 +11,7 @@ This topic describes some system limits and configurations that you need to cons
 
 StarRocks provides parameters for you to limit the memory usage for each load job, thereby reducing memory consumption, especially in high concurrency scenarios. However, do not specify an excessively low memory usage limit. If the memory usage limit is excessively low, data may be frequently flushed from memory to disk because the memory usage for load jobs reaches the specified limit. We recommend that you specify a proper memory usage limit based on your business scenario.
 
-The parameters that are used to limit memory usage vary for each loading method. For more information, see [Stream Load](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md), [Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md), [Routine Load](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md), [Spark Load](../../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md), and [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md). Note that a load job usually runs on multiple BEs or CNs. Therefore, the parameters limit the memory usage of each load job on each involved BE or CN rather than the total memory usage of the load job on all involved BEs or CNs.
+The parameters that are used to limit memory usage vary for each loading method. For more information, see [Stream Load](../../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md), [Broker Load](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md), [Routine Load](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md), [Spark Load](../../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md), and [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md). Note that a load job usually runs on multiple BEs or CNs. Therefore, the parameters limit the memory usage of each load job on each involved BE or CN rather than the total memory usage of the load job on all involved BEs or CNs.
 
 StarRocks also provides parameters for you to limit the total memory usage of all load jobs that run on each individual BE or CN. For more information, see the "[System configurations](#system-configurations)" section below.
 
@@ -71,7 +71,7 @@ You can configure the following parameters in the configuration file **be.conf**
 
 ### System variable configurations
 
-You can configure the following [system variable](../../reference/System_variable.md):
+You can configure the following [system variable](../../sql-reference/System_variable.md):
 
 - `query_timeout`
 
diff --git a/docs/en/loading/loading_introduction/loading_overview.mdx b/docs/en/loading/loading_introduction/loading_overview.mdx
index b5463a68213b51..e6ea999889bdd8 100644
--- a/docs/en/loading/loading_introduction/loading_overview.mdx
+++ b/docs/en/loading/loading_introduction/loading_overview.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Loading overview
diff --git a/docs/en/loading/loading_tools.md b/docs/en/loading/loading_tools.md
index 8d768eee197a95..07ddf94ce69c65 100644
--- a/docs/en/loading/loading_tools.md
+++ b/docs/en/loading/loading_tools.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: English
+displayed_sidebar: docs
 ---
 
 # Load data using tools
diff --git a/docs/en/loading/minio.md b/docs/en/loading/minio.md
index ebe1838d99733b..69b9d633ec545d 100644
--- a/docs/en/loading/minio.md
+++ b/docs/en/loading/minio.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 ---
 
@@ -9,8 +9,8 @@ import InsertPrivNote from '../_assets/commonMarkdown/insertPrivNote.md'
 
 StarRocks provides the following options for loading data from MinIO:
 
-- Synchronous loading using [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md)+[`FILES()`](../sql-reference/sql-functions/table-functions/files.md)
-- Asynchronous loading using [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)
+- Synchronous loading using [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md)+[`FILES()`](../sql-reference/sql-functions/table-functions/files.md)
+- Asynchronous loading using [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)
 
 Each of these options has its own advantages, which are detailed in the following sections.
 
@@ -58,9 +58,9 @@ This method is available from v3.1 onwards and currently supports only the Parqu
 
 With `FILES()`, you can:
 
-- Query the data directly from MinIO using [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md).
-- Create and load a table using [CREATE TABLE AS SELECT](../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md) (CTAS).
-- Load the data into an existing table using [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md).
+- Query the data directly from MinIO using [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md).
+- Create and load a table using [CREATE TABLE AS SELECT](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md) (CTAS).
+- Load the data into an existing table using [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md).
 
 ### Typical examples
 
@@ -177,7 +177,7 @@ Query OK, 10000000 rows affected (3.17 sec)
 {'label':'insert_a5da3ff5-9ee4-11ee-90b0-02420a060004', 'status':'VISIBLE', 'txnId':'17'}
 ```
 
-After creating the table, you can view its schema by using [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md):
+After creating the table, you can view its schema by using [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md):
 
 ```SQL
 DESCRIBE user_behavior_inferred;
@@ -343,13 +343,13 @@ The following query result is returned, indicating that the data has been succes
 
 #### Check load progress
 
-You can query the progress of INSERT jobs from the [`loads`](../reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards. Example:
+You can query the progress of INSERT jobs from the [`loads`](../sql-reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards. Example:
 
 ```SQL
 SELECT * FROM information_schema.loads ORDER BY JOB_ID DESC;
 ```
 
-For information about the fields provided in the `loads` view, see [`loads`](../reference/information_schema/loads.md).
+For information about the fields provided in the `loads` view, see [`loads`](../sql-reference/information_schema/loads.md).
 
 If you have submitted multiple load jobs, you can filter on the `LABEL` associated with the job. Example:
 
@@ -521,17 +521,17 @@ This job has four main sections:
 - `BROKER`: The connection details for the source.
 - `PROPERTIES`: The timeout value and any other properties to apply to the load job.
 
-For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 #### Check load progress
 
-You can query the progress of Broker Load jobs from the [`loads`](../reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards.
+You can query the progress of Broker Load jobs from the [`loads`](../sql-reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards.
 
 ```SQL
 SELECT * FROM information_schema.loads;
 ```
 
-For information about the fields provided in the `loads` view, see [`loads`](../reference/information_schema/loads.md).
+For information about the fields provided in the `loads` view, see [`loads`](../sql-reference/information_schema/loads.md).
 
 If you have submitted multiple load jobs, you can filter on the `LABEL` associated with the job. Example:
 
@@ -626,7 +626,7 @@ Note that Pipe is typically used with:
 - datasets that are in multiple files
 - datasets that grow over time
 
-This example uses only one small file and is only intended to introduce the Pipe functionality. See the [FILES](../sql-reference/sql-functions/table-functions/files.md) and [CREATE PIPE](../sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md) docs.
+This example uses only one small file and is only intended to introduce the Pipe functionality. See the [FILES](../sql-reference/sql-functions/table-functions/files.md) and [CREATE PIPE](../sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md) docs.
 
 #### Create a database and a table
 
@@ -691,11 +691,11 @@ This job has four main sections:
 - `INSERT_SQL`: The INSERT INTO SELECT FROM FILES statement that is used to load data from the specified source data file to the destination table.
 - `PROPERTIES`: A set of optional parameters that specify how to execute the pipe. These include `AUTO_INGEST`, `POLL_INTERVAL`, `BATCH_SIZE`, and `BATCH_FILES`. Specify these properties in the `"key" = "value"` format.
 
-For detailed syntax and parameter descriptions, see [CREATE PIPE](../sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md).
+For detailed syntax and parameter descriptions, see [CREATE PIPE](../sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md).
 
 #### Check load progress
 
-- Query the progress of Pipe jobs by using [SHOW PIPES](../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md).
+- Query the progress of Pipe jobs by using [SHOW PIPES](../sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md).
 
 ```sql
 SHOW PIPES\G
@@ -716,5 +716,5 @@ DATABASE_NAME: mydatabase
 
 #### Manage Pipe jobs
 
-You can alter, suspend or resume, drop, or query the pipes you have created and retry to load specific data files. For more information, see [ALTER PIPE](../sql-reference/sql-statements/data-manipulation/ALTER_PIPE.md), [SUSPEND or RESUME PIPE](../sql-reference/sql-statements/data-manipulation/SUSPEND_or_RESUME_PIPE.md), [DROP PIPE](../sql-reference/sql-statements/data-manipulation/DROP_PIPE.md), [SHOW PIPES](../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md), and [RETRY FILE](../sql-reference/sql-statements/data-manipulation/RETRY_FILE.md).
+You can alter, suspend or resume, drop, or query the pipes you have created and retry to load specific data files. For more information, see [ALTER PIPE](../sql-reference/sql-statements/loading_unloading/pipe/ALTER_PIPE.md), [SUSPEND or RESUME PIPE](../sql-reference/sql-statements/loading_unloading/pipe/SUSPEND_or_RESUME_PIPE.md), [DROP PIPE](../sql-reference/sql-statements/loading_unloading/pipe/DROP_PIPE.md), [SHOW PIPES](../sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md), and [RETRY FILE](../sql-reference/sql-statements/loading_unloading/pipe/RETRY_FILE.md).
 -->
diff --git a/docs/en/loading/objectstorage.mdx b/docs/en/loading/objectstorage.mdx
index d442f405e43351..289ae91cd5eac6 100644
--- a/docs/en/loading/objectstorage.mdx
+++ b/docs/en/loading/objectstorage.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 description: "Load from S3, GCS, Azure, and MinIO"
 ---
 
diff --git a/docs/en/loading/s3.md b/docs/en/loading/s3.md
index 0d44b2565d026b..e0e35ac09eb453 100644
--- a/docs/en/loading/s3.md
+++ b/docs/en/loading/s3.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 keywords: ['Broker Load']
 ---
@@ -30,7 +30,7 @@ In this topic, we provide you with a sample dataset in an S3 bucket, `s3://starr
 
 ### Gather authentication details
 
-The examples in this topic use IAM user-based authentication. To ensure that you have permission to read data from AWS S3, we recommend that you read [Preparation for IAM user-based authentication](../integrations/authenticate_to_aws_resources.md) and follow the instructions to create an IAM user with proper [IAM policies](../reference/aws_iam_policies.md) configured.
+The examples in this topic use IAM user-based authentication. To ensure that you have permission to read data from AWS S3, we recommend that you read [Preparation for IAM user-based authentication](../integrations/authenticate_to_aws_resources.md) and follow the instructions to create an IAM user with proper [IAM policies](../sql-reference/aws_iam_policies.md) configured.
 
 In a nutshell, if you practice IAM user-based authentication, you need to gather information about the following AWS resources:
 
@@ -51,9 +51,9 @@ This method is available from v3.1 onwards and currently supports only the Parqu
 
 With `FILES()`, you can:
 
-- Query the data directly from S3 using [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md).
-- Create and load a table using [CREATE TABLE AS SELECT](../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md) (CTAS).
-- Load the data into an existing table using [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md).
+- Query the data directly from S3 using [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md).
+- Create and load a table using [CREATE TABLE AS SELECT](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md) (CTAS).
+- Load the data into an existing table using [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md).
 
 ### Typical examples
 
@@ -136,7 +136,7 @@ SELECT * FROM FILES
 >
 > Substitute your credentials for `AAA` and `BBB` in the above command. Any valid `aws.s3.access_key` and `aws.s3.secret_key` can be used, as the object is readable by any AWS authenticated user.
 
-After creating the table, you can view its schema by using [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md):
+After creating the table, you can view its schema by using [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md):
 
 ```SQL
 DESCRIBE user_behavior_inferred;
@@ -283,13 +283,13 @@ The following query result is returned, indicating that the data has been succes
 
 #### Check load progress
 
-You can query the progress of INSERT jobs from the [`loads`](../reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards. Example:
+You can query the progress of INSERT jobs from the [`loads`](../sql-reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards. Example:
 
 ```SQL
 SELECT * FROM information_schema.loads ORDER BY JOB_ID DESC;
 ```
 
-For information about the fields provided in the `loads` view, see [`loads`](../reference/information_schema/loads.md).
+For information about the fields provided in the `loads` view, see [`loads`](../sql-reference/information_schema/loads.md).
 
 If you have submitted multiple load jobs, you can filter on the `LABEL` associated with the job. Example:
 
@@ -415,17 +415,17 @@ This job has four main sections:
 - `BROKER`: The connection details for the source.
 - `PROPERTIES`: The timeout value and any other properties to apply to the load job.
 
-For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+For detailed syntax and parameter descriptions, see [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 #### Check load progress
 
-You can query the progress of the Broker Load job from the [`loads`](../reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards.
+You can query the progress of the Broker Load job from the [`loads`](../sql-reference/information_schema/loads.md) view in the StarRocks Information Schema. This feature is supported from v3.1 onwards.
 
 ```SQL
 SELECT * FROM information_schema.loads WHERE LABEL = 'user_behavior';
 ```
 
-For information about the fields provided in the `loads` view, see [`loads`](../reference/information_schema/loads.md).
+For information about the fields provided in the `loads` view, see [`loads`](../sql-reference/information_schema/loads.md).
 
 This record shows a state of `LOADING`, and the progress is 39%. If you see something similar, then run the command again until you see a state of `FINISHED`.
 
@@ -570,11 +570,11 @@ This job has four main sections:
 - `INSERT_SQL`: The INSERT INTO SELECT FROM FILES statement that is used to load data from the specified source data file to the destination table.
 - `PROPERTIES`: A set of optional parameters that specify how to execute the pipe. These include `AUTO_INGEST`, `POLL_INTERVAL`, `BATCH_SIZE`, and `BATCH_FILES`. Specify these properties in the `"key" = "value"` format.
 
-For detailed syntax and parameter descriptions, see [CREATE PIPE](../sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md).
+For detailed syntax and parameter descriptions, see [CREATE PIPE](../sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md).
 
 #### Check load progress
 
-- Query the progress of the Pipe job by using [SHOW PIPES](../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md) in the current database to which the Pipe job belongs.
+- Query the progress of the Pipe job by using [SHOW PIPES](../sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md) in the current database to which the Pipe job belongs.
 
   ```SQL
   SHOW PIPES WHERE NAME = 'user_behavior_pipe' \G
@@ -601,7 +601,7 @@ For detailed syntax and parameter descriptions, see [CREATE PIPE](../sql-referen
   1 row in set (0.02 sec)
   ```
 
-- Query the progress of the Pipe job from the [`pipes`](../reference/information_schema/pipes.md) view in the StarRocks Information Schema.
+- Query the progress of the Pipe job from the [`pipes`](../sql-reference/information_schema/pipes.md) view in the StarRocks Information Schema.
 
   ```SQL
   SELECT * FROM information_schema.pipes WHERE pipe_name = 'user_behavior_replica' \G
@@ -629,7 +629,7 @@ For detailed syntax and parameter descriptions, see [CREATE PIPE](../sql-referen
 
 #### Check file status
 
-You can query the load status of the files loaded from the [`pipe_files`](../reference/information_schema/pipe_files.md) view in the StarRocks Information Schema.
+You can query the load status of the files loaded from the [`pipe_files`](../sql-reference/information_schema/pipe_files.md) view in the StarRocks Information Schema.
 
 ```SQL
 SELECT * FROM information_schema.pipe_files WHERE pipe_name = 'user_behavior_replica' \G
@@ -656,4 +656,4 @@ FINISH_LOAD_TIME: 2023-11-09 15:35:42
 
 #### Manage Pipe jobs
 
-You can alter, suspend or resume, drop, or query the pipes you have created and retry to load specific data files. For more information, see [ALTER PIPE](../sql-reference/sql-statements/data-manipulation/ALTER_PIPE.md), [SUSPEND or RESUME PIPE](../sql-reference/sql-statements/data-manipulation/SUSPEND_or_RESUME_PIPE.md), [DROP PIPE](../sql-reference/sql-statements/data-manipulation/DROP_PIPE.md), [SHOW PIPES](../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md), and [RETRY FILE](../sql-reference/sql-statements/data-manipulation/RETRY_FILE.md).
+You can alter, suspend or resume, drop, or query the pipes you have created and retry to load specific data files. For more information, see [ALTER PIPE](../sql-reference/sql-statements/loading_unloading/pipe/ALTER_PIPE.md), [SUSPEND or RESUME PIPE](../sql-reference/sql-statements/loading_unloading/pipe/SUSPEND_or_RESUME_PIPE.md), [DROP PIPE](../sql-reference/sql-statements/loading_unloading/pipe/DROP_PIPE.md), [SHOW PIPES](../sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md), and [RETRY FILE](../sql-reference/sql-statements/loading_unloading/pipe/RETRY_FILE.md).
diff --git a/docs/en/project_help/project_help.mdx b/docs/en/project_help/project_help.mdx
index 6fd2c6af1f4835..2492683d965d98 100644
--- a/docs/en/project_help/project_help.mdx
+++ b/docs/en/project_help/project_help.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Project Help
diff --git a/docs/en/project_help/slack.md b/docs/en/project_help/slack.md
index 09204a2d1a9124..e12c4cbdbc48cf 100644
--- a/docs/en/project_help/slack.md
+++ b/docs/en/project_help/slack.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_label: Community Chat
 description: Slack with the community
 ---
diff --git a/docs/en/quick_start/helm.md b/docs/en/quick_start/helm.md
index 5826edabae0bc6..7fc8b8b51e98c6 100644
--- a/docs/en/quick_start/helm.md
+++ b/docs/en/quick_start/helm.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 description: Use Helm to deploy StarRocks
 toc_max_heading_level: 2
 ---
@@ -609,7 +609,7 @@ There is more to learn; we intentionally glossed over the data transformation do
 
 Default [`values.yaml`](https://github.com/StarRocks/starrocks-kubernetes-operator/blob/main/helm-charts/charts/kube-starrocks/values.yaml)
 
-[Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)
+[Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)
 
 The [Motor Vehicle Collisions - Crashes](https://data.cityofnewyork.us/Public-Safety/Motor-Vehicle-Collisions-Crashes/h9gi-nx95) dataset is provided by New York City subject to these [terms of use](https://www.nyc.gov/home/terms-of-use.page) and [privacy policy](https://www.nyc.gov/home/privacy-policy.page).
 
diff --git a/docs/en/quick_start/hudi.md b/docs/en/quick_start/hudi.md
index 70c46b07962d43..e6f80d578a64ac 100644
--- a/docs/en/quick_start/hudi.md
+++ b/docs/en/quick_start/hudi.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_position: 4
 description: Data Lakehouse with Apache Hudi
 toc_max_heading_level: 3
diff --git a/docs/en/quick_start/iceberg.md b/docs/en/quick_start/iceberg.md
index 19e7c3b4f837fc..08d88a0557676f 100644
--- a/docs/en/quick_start/iceberg.md
+++ b/docs/en/quick_start/iceberg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_position: 3
 description: Data Lakehouse with Apache Iceberg
 toc_max_heading_level: 2
diff --git a/docs/en/quick_start/quick_start.mdx b/docs/en/quick_start/quick_start.mdx
index f35392360be6cc..6d2a3afee57521 100644
--- a/docs/en/quick_start/quick_start.mdx
+++ b/docs/en/quick_start/quick_start.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 description: Deploy StarRocks with Docker Compose, Helm, and StarRocks Operator
 ---
 
diff --git a/docs/en/quick_start/routine-load.md b/docs/en/quick_start/routine-load.md
index e8601f592edef8..3227d3d98a8588 100644
--- a/docs/en/quick_start/routine-load.md
+++ b/docs/en/quick_start/routine-load.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_position: 2
 toc_max_heading_level: 2
 description: Kafka routine load with shared-data storage
diff --git a/docs/en/quick_start/shared-data.md b/docs/en/quick_start/shared-data.md
index f370deb13eb3b5..695f86eeee57ed 100644
--- a/docs/en/quick_start/shared-data.md
+++ b/docs/en/quick_start/shared-data.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_position: 2
 description: Separate compute and storage
 ---
@@ -508,7 +508,7 @@ There is more to learn; we intentionally glossed over the data transform done du
 
 [Materialized views](../cover_pages/mv_use_cases.mdx)
 
-[Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)
+[Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)
 
 The [Motor Vehicle Collisions - Crashes](https://data.cityofnewyork.us/Public-Safety/Motor-Vehicle-Collisions-Crashes/h9gi-nx95) dataset is provided by New York City subject to these [terms of use](https://www.nyc.gov/home/terms-of-use.page) and [privacy policy](https://www.nyc.gov/home/privacy-policy.page).
 
diff --git a/docs/en/quick_start/shared-nothing.md b/docs/en/quick_start/shared-nothing.md
index c98674b46412aa..96737d33a25dee 100644
--- a/docs/en/quick_start/shared-nothing.md
+++ b/docs/en/quick_start/shared-nothing.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_position: 1
 description: "StarRocks in Docker: Query real data with JOINs"
 ---
@@ -230,7 +230,7 @@ There is more to learn; we intentionally glossed over the data transformation do
 
 [Materialized views](../cover_pages/mv_use_cases.mdx)
 
-[Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)
+[Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)
 
 The [Motor Vehicle Collisions - Crashes](https://data.cityofnewyork.us/Public-Safety/Motor-Vehicle-Collisions-Crashes/h9gi-nx95) dataset is provided by New York City subject to these [terms of use](https://www.nyc.gov/home/terms-of-use.page) and [privacy policy](https://www.nyc.gov/home/privacy-policy.page).
 
diff --git a/docs/en/reference/Error_code.md b/docs/en/reference/Error_code.md
deleted file mode 100644
index aa0c661212088d..00000000000000
--- a/docs/en/reference/Error_code.md
+++ /dev/null
@@ -1,149 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# Error Codes
-
-This section describes the common error codes for query requests.
-
-|Serial number|Error code|Error message|
-| --- | --- | --- |
-|1005| Table creation failed. Returns a specific reason. |
-|1007| Cannot create a database with the same name.|
-|1008| Cannot delete non-existent database. |
-|1044| Cannot access unauthorized database. |
-|1045| Username and password do not match and therefore cannot access the system. |
-|1046|The target database is not specified. |
-|1047|An invalid command is specified. |
-|1049| An invalid database is specified. |
-|1050| A table with the same name already exists.|
-|1051| An invalid table is specified. |
-|1052| The specified column name is ambiguous and therefore the corresponding column cannot be uniquely identified. |
-|1053|An illegal data column was specified for the Semi-Join/Anti-Join query. |
-|1054|The specified column does not exist in the table.|
-|1058|The number of columns selected in the query statement does not match the number of columns in the query result. |
-|1060|There are duplicate column names. |
-|1064|There is no surviving BE node. |
-|1066|Duplicate table alias appears in the query statement. |
-|1094|Thread ID is invalid. |
-|1095|The non-owner of a thread cannot terminate the thread. |
-|1096|The query statement does not specify the table to be queried.|
-|1102|The database name is incorrect. |
-|1104|The table name is incorrect.|
-|1105|Other errors. |
-|1110|Duplicate columns were specified in the subquery.|
-|1111|Illegal use of aggregation function in `WHERE` clause|
-|1113| The set of columns in the new table cannot be empty. |
-|1115|Unsupported character sets are used.|
-|1130|An unauthorized IP address is used by the client. |
-|1132|No permission to change user password.|
-|1141| Specified entries don’t have privileges to revoke. |
-|1142|An unauthorized action was performed. |
-|1166| The data column name is incorrect. |
-|1193| System variable has invalid name |
-|1203| The number of active connections used exceeded the limit. |
-|1211| Not allowed to create new users. |
-|1227| The user has performed an out-of-authority operation. |
-|1228|Session variables cannot be modified by the `SET GLOBAL` command. |
-|1229|Global variables should be modified by the `SET GLOBAL` command. |
-|1230|Related system variables do not have default values. |
-|1231|An invalid value was set for a system variable.|
-|1232|A value of the wrong data type was set for a system variable. |
-|1248|No alias was set for an inline view.|
-|1251|The client does not support the user authentication protocol required by the server. |
-|1286|The storage engine is incorrectly configured. |
-|1298|The time zone is incorrectly configured.|
-|1347|The object does not match the expected type. |
-|1353|The specified column number in the `Select` clause of the view is not equal to the defined column number. |
-|1364|No default value is set for columns that do not allow NULL values. |
-|1372|The password is not long enough. |
-|1396|The performed operation failed.|
-|1471|The specified table is not allowed to insert data. |
-|1507|Delete nonexistent partition, and no condition is specified to only delete existing partitions. |
-|1508|All partitions should be deleted by a delete table operation. |
-|1517|There are duplicate partition names.|
-|1524|The specified plugin has not been loaded.|
-|1567|The name of the partition is incorrect. |
-|1621|The specified system variable is read-only. |
-|1735|The specified partition name does not exist in the table.|
-|1748|Data cannot be inserted into a table that does not have a partition.|
-|1749|The specified partition does not exist. |
-|5000|The specified table is not an OLAP table. |
-|5001|The specified storage path is invalid. |
-|5002|The name of the specified column should be displayed.|
-|5003|The dimension column should be preceded by the index column. |
-|5004|The table should contain at least 1 dimension column. |
-|5005|The cluster ID is invalid. |
-|5006|Invalid query plan. |
-|5007|Conflicting query plans. |
-|5008|The data insert is only available for data tables with partitions. |
-|5009|The `PARTITION` clause cannot be used to insert data into tables without partitions. |
-|5010|The number of columns in the table to be created is not equal to the number of columns in the `SELECT` clause. |
-|5011|Table reference could not be accessed. |
-|5012|The specified value is not a valid number. |
-|5013|The time unit is not supported. |
-|5014|The table status is not normal. |
-|5015|The partition status is not normal. |
-|5016| A data import job exists in the partition. |
-|5017| The specified column is not a dimension column. |
-|5018| The format of the value is invalid. |
-|5019| The data replica does not match the version. |
-|5021| The BE node is offline. |
-|5022| The number of partitions in a non-partitioned table is not 1|
-|5023| No action was specified in the statement used to modify the table or data. |
-|5024| Job execution timed out. |
-|5025| Data insertion failed. |
-|5026| An unsupported data type was used when creating a table via the `SELECT` statement. |
-|5027| The specified parameter was not set. |
-|5028| The specified cluster was not found. |
-|5030| The user does not have permission to access the cluster. |
-|5031| No parameter specified or invalid parameter. |
-|5032| The number of cluster instances was not specified. |
-|5034| A cluster with the same name already exists.|
-|5035| The number of cluster instances is incorrectly configured. |
-|5036|Insufficient BE nodes in the cluster. |
-|5037|All databases should be deleted before deleting the cluster.|
-|5038| The BE node with the specified ID does not exist in the cluster.|
-|5040|No cluster with the same name exists.|
-|5042|No permissions. |
-|5043|The number of instances should be greater than 0.|
-|5046|Source cluster does not exist.|
-|5047| Destination cluster does not exist. |
-|5048| Source database does not exist. |
-|5049| Destination database does not exist.|
-|5050| No cluster selected. |
-|5051| The source database should be associated with the destination database first. |
-|5052| Intra-cluster error: BE node information is incorrect. |
-|5053| There is no migration task from the source database to the destination database. |
-|5054| The specified database has been associated with the destination database, or data is being migrated. |
-|5055| Database associations or data migrations cannot be performed within the same cluster. |
-|5056| Database cannot be deleted: it is associated with another database or data is being migrated.|
-|5056| Database cannot be renamed: it is associated with another database or data is being migrated. |
-|5056| Insufficient BE nodes in the cluster. |
-|5056| The specified number of BE nodes already exists in the cluster. |
-|5059| There are BE nodes in the cluster that are in the offline state. |
-|5063| The type name is incorrect. |
-|5064| Generic error message.|
-|5063|The Colocate feature has been disabled by the administrator. |
-|5063|A colocate data table with the same name does not exist. |
-|5063|The Colocate table must be an OLAP table.|
-|5063|Colocate tables should have the same number of replicas. |
-|5063|Colocate tables should have the same number of split buckets. |
-|5063|Colocate tables should have the same number of partition columns. |
-|5063|Colocate tables should have the same data type of partitioned columns. |
-|5064|The specified table is not a colocate table.|
-|5065|The specified operation is invalid.|
-|5065|The specified time unit is illegal. The correct units are `DAY`, `WEEK`, and `MONTH`. |
-|5066|The start value of the dynamic partition should be less than 0.|
-|5066|The start value of the dynamic partition is not a valid number. |
-|5066|The end value of the dynamic partition should be greater than 0. |
-|5066|The end value of the dynamic partition is not a valid number. |
-|5066|The end value of the dynamic partition is null. |
-|5067|The bucket number of the dynamic partition should be greater than 0. |
-|5067|The bucket number of the dynamic partition is not a valid number. |
-|5066| The bucket number of the dynamic partition is empty. |
-|5068| Whether to allow dynamic partition where the value is not a valid boolean: true or false. |
-|5069| The name of the specified dynamic partition has an illegal prefix. |
-|5070| The specified operation is disabled. |
-|5071| The number of replicas of the dynamic partition should be greater than 0.|
-|5072| The number of replicas of the dynamic partition is not a valid number. |
diff --git a/docs/en/reference/HTTP_API/SQL.md b/docs/en/reference/HTTP_API/SQL.md
deleted file mode 100644
index 51117d90746b03..00000000000000
--- a/docs/en/reference/HTTP_API/SQL.md
+++ /dev/null
@@ -1,207 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# HTTP SQL API
-
-## Description
-
-StarRocks v3.2.0 introduces the HTTP SQL API for users to perform various types of queries using HTTP. Currently, this API supports SELECT, SHOW, EXPLAIN, and KILL statements.
-
-Syntax using the curl command:
-
-```shell
-curl -X POST 'http://<fe_ip>:<fe_http_port>/api/v1/catalogs/<catalog_name>/databases/<database_name>/sql' \
-   -u '<username>:<password>'  -d '{"query": "<sql_query>;", "sessionVariables":{"<var_name>":<var_value>}}' \
-   --header "Content-Type: application/json"
-```
-
-## Request message
-
-### Request line
-
-```shell
-POST 'http://<fe_ip>:<fe_http_port>/api/v1/catalogs/<catalog_name>/databases/<database_name>/sql'
-```
-
-| Field                    | Description                                                  |
-| ------------------------ | :----------------------------------------------------------- |
-|  fe_ip                   | FE node IP address.                                                  |
-|  fe_http_port            | FE HTTP port.                                           |
-|  catalog_name            | The catalog name. In v3.2.0, you can use this API to query only StarRocks internal tables, which means `<catalog_name>` can only be set to `default_catalog`. Since v3.2.1, you can use this API to query tables in [external catalogs](../../data_source/catalog/catalog_overview.md). |
-|  database_name           | The database name. If no database name is specified in the request line and a table name is used in the SQL query, you must prefix the table name with its database name, for example, `database_name.table_name`. |
-
-- Query data across databases in a specified catalog. If a table is used in the SQL query, you must prefix the table name with its database name.
-
-   ```shell
-   POST /api/v1/catalogs/<catalog_name>/sql
-   ```
-
-- Query data from a specified catalog and database.
-
-   ```shell
-   POST /api/v1/catalogs/<catalog_name>/databases/<database_name>/sql
-   ```
-
-### Authentication method
-
-```shell
-Authorization: Basic <credentials>
-```
-
-Basic authentication is used, that is, enter the username and password for `credentials` (`-u '<username>:<password>'`). If no password is set for the username, you can pass in only `<username>:` and leave the password empty. For example, if the root account is used, you can enter `-u 'root:'`.
-
-### Request body
-
-```shell
--d '{"query": "<sql_query>;", "sessionVariables":{"<var_name>":<var_value>}}'
-```
-
-| Field                    | Description                                                  |
-| ------------------------ | :----------------------------------------------------------- |
-| query                    | The SQL query, in STRING format. Only SELECT, SHOW, EXPLAIN, and KILL statements are supported. You can run only one SQL query for an HTTP request. |
-| sessionVariables         | The [session variable](../System_variable.md) you want to set for the query, in JSON format. This field is optional. Default is empty. The session variable you set takes effect for the same connection and becomes ineffective when the connection is closed. |
-
-### Request header
-
-```shell
---header "Content-Type: application/json"
-```
-
-This header indicates that the request body is a JSON string.
-
-## Response message
-
-### Status code
-
-- 200: HTTP request succeeded and the server is normal before data is sent to the client.
-- 4xx: HTTP request error, which indicates a client error.
-- `500 Internal Server Error`: HTTP request succeeded but the server encounters an error before data is sent to the client.
-- 503: HTTP request succeeded but the FE cannot provide service.
-
-### Response header
-
-`content-type` indicates the format of the response body. Newline delimited JSON is used, which means the response body consists of multiple JSON objects that are separated by `\n`.
-
-|                      | Description                                                  |
-| -------------------- | :----------------------------------------------------------- |
-| content-type         | The format is Newline delimited JSON, defaults to "application/x-ndjson charset=UTF-8". |
-| X-StarRocks-Query-Id | Query ID.                                                          |
-
-### Response body
-
-#### Failed before the request is sent
-
-Request fails on the client side or the server encounters an error before it returns data to the client. The response body is in the following format, where `msg` is the error information.
-
-```json
-{
-   "status":"FAILED",
-   "msg":"xxx"
-}
-```
-
-#### Failed after the request is sent
-
-Part of the result is returned and the HTTP status code is 200. Data sending is suspended, the connection is closed, and the error is logged.
-
-#### Succeeded
-
-Each row in the response message is a JSON object. JSON objects separated by `\n`.
-
-- For a SELECT statement, the following JSON objects are returned.
-
-| Object       | Description                                                  |
-| ------------ | :----------------------------------------------------------- |
-| `connectionId` | Connection ID. You can cancel a query that is pending for a long time by calling KILL `<connectionId>`. |
-| `meta`        | Represents a column. The key is `meta` and the value is a JSON array, where each object in the array represents a column. |
-| `data`         | The data row, where the key is `data` and the value is a JSON  array which contains a row of data. |
-| `statistics`   | Statistical information of the query.                                       |
-
-- For a SHOW statement, `meta`, `data`, and `statistics` are returned.
-- For the EXPLAIN statement, an `explain` object is returned to show detailed execution plan of the query.
-
-The following example uses `\n` as the separator. StarRocks transmits data using HTTP chunked mode. Each time the FE obtains a data chunk, it streams the data chunk to the client. The client can parse data by row, which eliminates the need for data caching and the need to wait for the entire data, reducing memory consumption for the client.
-
-```json
-{"connectionId": 7}\n
-{"meta": [
-    {
-      "name": "stock_symbol",
-      "type": "varchar"
-    },
-    {
-      "name": "closing_price",
-      "type": "decimal64(8, 2)"
-    },
-    {
-      "name": "closing_date",
-      "type": "datetime"
-    }
-  ]}\n
-{"data": ["JDR", 12.86, "2014-10-02 00:00:00"]}\n
-{"data": ["JDR",14.8, "2014-10-10 00:00:00"]}\n
-...
-{"statistics": {"scanRows": 0,"scanBytes": 0,"returnRows": 9}}
-```
-
-## Examples
-
-### Run a SELECT query
-
-- Query data from a StarRocks internal table (`catalog_name` is `default_catalog`).
-
-  ```shell
-  curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:' -d '{"query": "select * from agg;"}' --header "Content-Type: application/json"
-  ```
-
-  Result:
-
-  ```json
-  {"connectionId":49}
-  {"meta":[{"name":"no","type":"int(11)"},{"name":"k","type":"decimal64(10, 2)"},{"name":"v","type":"decimal64(10, 2)"}]}
-  {"data":[1,"10.00",null]}
-  {"data":[2,"10.00","11.00"]}
-  {"data":[2,"20.00","22.00"]}
-  {"data":[2,"25.00",null]}
-  {"data":[2,"30.00","35.00"]}
-  {"statistics":{"scanRows":0,"scanBytes":0,"returnRows":5}}
-  ```
-
-- Query data from an Iceberg table.
-
-  ```shell
-  curl -X POST 'http://172.26.93.145:8030/api/v1/catalogs/iceberg_catalog/databases/ywb/sql' -u 'root:' -d '{"query": "select * from iceberg_analyze;"}' --header "Content-Type: application/json"
-  ```
-
-  Result:
-
-  ```json
-  {"connectionId":13}
-  {"meta":[{"name":"k1","type":"int(11)"},{"name":"k2","type":"int(11)"}]}
-  {"data":[1,2]}
-  {"data":[1,1]}
-  {"statistics":{"scanRows":0,"scanBytes":0,"returnRows":2}}
-  ```
-
-### Cancel a query
-
-To cancel a query that run an unexpected long time, you can close the connection. StarRocks will cancel this query when it detects the connection is closed.
-
-You can also call KILL `connectionId` to cancel this query. For example:
-
-```shell
-curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:' -d '{"query": "kill 17;"}' --header "Content-Type: application/json"
-```
-
-You can obtain the `connectionId` from the response body or by calling SHOW PROCESSLIST. For example:
-
-```shell
-curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:' -d '{"query": "show processlist;"}' --header "Content-Type: application/json"
-```
-
-### Run a query with a session variable set for this query
-
-```shell
-curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:'  -d '{"query": "SHOW VARIABLES;", "sessionVariables":{"broadcast_row_limit":14000000}}'  --header "Content-Type: application/json"
-```
diff --git a/docs/en/reference/System_limit.md b/docs/en/reference/System_limit.md
deleted file mode 100644
index ef152a79841f3f..00000000000000
--- a/docs/en/reference/System_limit.md
+++ /dev/null
@@ -1,38 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# System limits
-
-This topic describes the rules and limits that apply when you use StarRocks.
-
-- StarRocks uses the MySQL protocol for communication. You can connect to the StarRocks cluster via a MySQL client or JDBC. We recommend that you use a MySQL client whose version is 5.1 or later. Versions earlier than 5.1 do not support usernames that are longer than 16 characters.
-
-- Naming conventions for objects such as catalogs, databases, tables, views, partitions, columns, indexes, usernames, roles, repositories, resources, storage volumes, and pipes:
-
-  - The name can only consist of digits (0-9), letters (a-z or A-Z), and underscores (\_). **Usernames can be all digits.**
-  - The name can start with a letter or an underscore (\_).
-  - The name cannot exceed 64 characters in length, **among which:**
-    - Database name cannot exceed 256 characters.
-    - Table name and column name cannot exceed 1024 characters.
-    - Username cannot exceed 128 characters.
-  - Column name (column alias), partition name, and index name are **not** case-sensitive. Other names are **case-sensitive**.
-
-- Naming conventions for labels:
-  You can specify the label of a job when you load data. The label name can consist of digits (0-9), letters (a-z or A-Z), and underscores (\_), and cannot exceed 128 characters in length. The label name has no requirement for the starting character.
-
-- When you create a table, the key column cannot be of the FLOAT or DOUBLE type. You can use the DECIMAL type to represent decimals.
-
-- The maximum length of a VARCHAR value varies in different versions:
-
-  - In versions earlier than StarRocks 2.1, the length ranges from 1 to 65533 bytes.
-  - [Preview] In StarRocks 2.1 and later versions, the length ranges from 1 to 1048576 bytes. Maximum length of a VARCHAR value = Maximum row size (1048578 bytes) - Length prefix (2 bytes). The length prefix indicates the number of bytes in the value.
-  - The default length is 1 byte.
-
-- StarRocks supports only UTF-8 encoding, not GBK.
-
-- StarRocks does not support modifying column names in tables.
-
-- StarRocks does not support modifying the table types of an existing table. For example, you cannot change a Duplicate Key table to a Primary Key table. You must create a new table.
-
-- By default, a query can be nested with a maximum of 10,000 subqueries, which is controlled by the FE parameter `expr_children_limit`.
diff --git a/docs/en/reference/System_variable.md b/docs/en/reference/System_variable.md
deleted file mode 100644
index c4940d985d9442..00000000000000
--- a/docs/en/reference/System_variable.md
+++ /dev/null
@@ -1,1047 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# System variables
-
-StarRocks provides many system variables that can be set and modified to suit your requirements. This section describes the variables supported by StarRocks. You can view the settings of these variables by running the [SHOW VARIABLES](../sql-reference/sql-statements/Administration/SHOW_VARIABLES.md) command on your MySQL client. You can also use the [SET](../sql-reference/sql-statements/Administration/SET.md) command to dynamically set or modify variables. You can make these variables take effect globally on the entire system, only in the current session, or only in a single query statement.
-
-The variables in StarRocks refer to the variable sets in MySQL, but **some variables are only compatible with the MySQL client protocol and do not function on the MySQL database**.
-
-> **NOTE**
->
-> Any user has the privilege to run SHOW VARIABLES and make a variable take effect at session level. However, only users with the SYSTEM-level OPERATE privilege can make a variable take effect globally. Globally effective variables take effect on all the future sessions (excluding the current session).
->
-> If you want to make a setting change for the current session and also make that setting change apply to all future sessions, you can make the change twice, once without the `GLOBAL` modifier and once with it. For example:
->
-> ```SQL
-> SET query_mem_limit = 137438953472; -- Apply to the current session.
-> SET GLOBAL query_mem_limit = 137438953472; -- Apply to all future sessions.
-> ```
-
-## Variable hierarchy and types
-
-StarRocks supports three types (levels) of variables: global variables, session variables, and `SET_VAR` hints. Their hierarchical relationship is as follows:
-
-* Global variables take effect on global level, and can be overridden by session variables and `SET_VAR` hints.
-* Session variables take effect only on the current session, and can be overridden by `SET_VAR` hints.
-* `SET_VAR` hints take effect only on the current query statement.
-
-## View variables
-
-You can view all or some variables by using `SHOW VARIABLES [LIKE 'xxx']`. Example:
-
-```SQL
--- Show all variables in the system.
-SHOW VARIABLES;
-
--- Show variables that match a certain pattern.
-SHOW VARIABLES LIKE '%time_zone%';
-```
-
-## Set variables
-
-### Set variables globally or for a single session
-
-You can set variables to take effect **globally** or **only on the current session**. When set to global, the new value will be used for all the future sessions, while the current session still uses the original value. When set to "current session only", the variable will only take effect on the current session.
-
-A variable set by `SET <var_name> = xxx;` only takes effect for the current session. Example:
-
-```SQL
-SET query_mem_limit = 137438953472;
-
-SET forward_to_master = true;
-
-SET time_zone = "Asia/Shanghai";
-```
-
-A variable set by `SET GLOBAL <var_name> = xxx;` takes effect globally. Example:
-
-```SQL
-SET GLOBAL query_mem_limit = 137438953472;
-```
-
-The following variables only take effect globally. They cannot take effect for a single session, which means you must use `SET GLOBAL <var_name> = xxx;` for these variables. If you try to set such a variable for a single session (`SET <var_name> = xxx;`), an error is returned.
-
-* activate_all_roles_on_login
-* character_set_database
-* default_rowset_type
-* enable_query_queue_select
-* enable_query_queue_statistic
-* enable_query_queue_load
-* init_connect
-* lower_case_table_names
-* license
-* language
-* query_cache_size
-* query_queue_fresh_resource_usage_interval_ms
-* query_queue_concurrency_limit
-* query_queue_mem_used_pct_limit
-* query_queue_cpu_used_permille_limit
-* query_queue_pending_timeout_second
-* query_queue_max_queued_queries
-* system_time_zone
-* version_comment
-* version
-
-In addition, variable settings also support constant expressions, such as:
-
-```SQL
-SET query_mem_limit = 10 * 1024 * 1024 * 1024;
-```
-
- ```SQL
-SET forward_to_master = concat('tr', 'u', 'e');
-```
-
-### Set variables in a single query statement
-
-In some scenarios, you may need to set variables specifically for certain queries. By using the `SET_VAR` hint, you can set session variables that will take effect only within a single statement.
-
-StarRocks supports using `SET_VAR` in the following statements;
-
-- SELECT
-- INSERT (from v3.1.12 and v3.2.0 onwards)
-- UPDATE (from v3.1.12 and v3.2.0 onwards)
-- DELETE (from v3.1.12 and v3.2.0 onwards)
-
-`SET_VAR` can only be placed after the above keywords and enclosed in `/*+...*/`.
-
-Example:
-
-```sql
-SELECT /*+ SET_VAR(query_mem_limit = 8589934592) */ name FROM people ORDER BY name;
-
-SELECT /*+ SET_VAR(query_timeout = 1) */ sleep(3);
-
-UPDATE /*+ SET_VAR(query_timeout=100) */ tbl SET c1 = 2 WHERE c1 = 1;
-
-DELETE /*+ SET_VAR(query_mem_limit = 8589934592) */
-FROM my_table PARTITION p1
-WHERE k1 = 3;
-
-INSERT /*+ SET_VAR(query_timeout = 10000000) */
-INTO insert_wiki_edit
-    SELECT * FROM FILES(
-        "path" = "s3://inserttest/parquet/insert_wiki_edit_append.parquet",
-        "format" = "parquet",
-        "aws.s3.access_key" = "XXXXXXXXXX",
-        "aws.s3.secret_key" = "YYYYYYYYYY",
-        "aws.s3.region" = "us-west-2"
-);
-```
-
-You can also set multiple variables in a single statement. Example:
-
-```sql
-SELECT /*+ SET_VAR
-  (
-  exec_mem_limit = 515396075520,
-  query_timeout=10000000,
-  batch_size=4096,
-  parallel_fragment_exec_instance_num=32
-  )
-  */ * FROM TABLE;
-```
-
-## Descriptions of variables
-
-The variables are described **in alphabetical order**. Variables with the `global` label can only take effect globally. Other variables can take effect either globally or for a single session.
-
-### activate_all_roles_on_login (global)
-
-* **Description**: Whether to enable all roles (including default roles and granted roles) for a StarRocks user when the user connects to the StarRocks cluster.
-  * If enabled (`true`), all roles of the user are activated at user login. This takes precedence over the roles set by [SET DEFAULT ROLE](../sql-reference/sql-statements/account-management/SET_DEFAULT_ROLE.md).
-  * If disabled (`false`), the roles set by SET DEFAULT ROLE are activated.
-* **Default**: false
-* **Introduced in**: v3.0
-
-If you want to activate the roles assigned to you in a session, use the [SET ROLE](../sql-reference/sql-statements/account-management/SET_DEFAULT_ROLE.md) command.
-
-### auto_increment_increment
-
-Used for MySQL client compatibility. No practical usage.
-
-### autocommit
-
-Used for MySQL client compatibility. No practical usage.
-
-### chunk_size
-
-* **Description**: Used to specify the number of rows of a single packet transmitted by each node during query execution. The default is 4096, i.e., every 4096 rows of data generated by the source node is packaged and sent to the destination node. A larger number of rows will improve the query throughput in large data volume scenarios, but may increase the query latency in small data volume scenarios. Also, it may increase the memory overhead of the query. We recommend to set `batch_size` between 1024 to 4096.
-* **Default**: 4096
-
-### big_query_profile_threshold
-
-* **Description**: Used to set the threshold for big queries. When the session variable `enable_profile` is set to `false` and the amount of time taken by a query exceeds the threshold specified by the variable `big_query_profile_threshold`, a profile is generated for that query.
-
-  Note: In versions v3.1.5 to v3.1.7, as well as v3.2.0 to v3.2.2, we introduced the `big_query_profile_second_threshold` for setting the threshold for big queries. In versions v3.1.8, v3.2.3, and subsequent releases, this parameter has been replaced by `big_query_profile_threshold` to offer more flexible configuration options.
-* **Default**: 0
-* **Unit**: Second
-* **Data type**: String
-* **Introduced in**: v3.1
-
-### catalog
-
-* **Description**: Used to specify the catalog to which the session belongs.
-* **Default**: default_catalog
-* **Data type**: String
-* **Introduced in**: v3.2.4
-
-### cbo_decimal_cast_string_strict
-
-* **Description**: Controls how the CBO converts data from the DECIMAL type to the STRING type. If this variable is set to `true`, the logic built in v2.5.x and later versions prevails and the system implements strict conversion (namely, the system truncates the generated string and fills 0s based on the scale length). If this variable is set to `false`, the logic built in versions earlier than v2.5.x prevails and the system processes all valid digits to generate a string.
-* **Default**: true
-* **Introduced in**: v2.5.14
-
-### cbo_enable_low_cardinality_optimize
-
-* **Description**: Whether to enable low cardinality optimization. After this feature is enabled, the performance of querying STRING columns improves by about three times.
-* **Default**: true
-
-### cbo_eq_base_type
-
-* **Description**: Specifies the data type used for data comparison between DECIMAL data and STRING data. The default value is `VARCHAR`, and DECIMAL is also a valid value. **This variable takes effect only for `=` and `!=` comparison.**
-* **Data type**: String
-* **Introduced in**: v2.5.14
-
-### cbo_materialized_view_rewrite_related_mvs_limit
-
-* **Description**: Specifies the maximum number of candidate materialized views allowed during query planning.
-* **Default**: 64
-* **Introduced in**: v3.1.9, v3.2.5
-
-### cbo_prune_subfield
-
-* **Description**: Whether to enable JSON subfield pruning. This variable must be used with the BE dynamic parameter `enable_json_flat`. Otherwise, it may degrade JSON data query performance.
-* **Default**: false
-* **Data type**: Int
-* **Introduced in**: v3.3.0
-
-### enable_sync_materialized_view_rewrite
-
-* **Description**: Whether to enable query rewrite based on synchronous materialized views.
-* **Default**: true
-* **Introduced in**: v3.1.11, v3.2.5
-
-### query_including_mv_names
-
-* **Description**: Specifies the name of the asynchronous materialized views to include in query execution. You can use this variable to limit the number of candidate materialized views and improve the query rewrite performance in the optimizer. This item takes effect prior to `query_excluding_mv_names`.
-* **Default**: empty
-* **Data type**: String
-* **Introduced in**: v3.1.11, v3.2.5
-
-### query_excluding_mv_names(
-
-* **Description**: Specifies the name of the asynchronous materialized views to exclude from query execution. You can use this variable to limit the number of candidate materialized views and reduce the time of query rewrite in the optimizer. `query_including_mv_names` takes effect prior to this item.
-* **Default**: empty
-* **Data type**: String
-* **Introduced in**: v3.1.11, v3.2.5
-
-### optimizer_materialized_view_timelimit
-
-* **Description**: Specifies the maximum time that one materialized view rewrite rule can consume. When the threshold is reached, this rule will not be used for query rewrite.
-* **Default**: 1000
-* **Unit**: ms
-* **Introduced in**: v3.1.9, v3.2.5
-
-### enable_materialized_view_agg_pushdown_rewrite
-
-* **Description**: Whether to enable aggregation pushdown for materialized view query rewrite. If it is set to `true`, aggregate functions will be pushed down to Scan Operator during query execution and rewritten by the materialized view before the Join Operator is executed. This will relieve the data expansion caused by Join and thereby improve the query performance. For detailed information about the scenarios and limitations of this feature, see [Aggregation pushdown](../using_starrocks/query_rewrite_with_materialized_views.md#aggregation-pushdown).
-* **Default**: false
-* **Introduced in**: v3.3.0
-
-### enable_materialized_view_text_match_rewrite
-
-* **Description**: Whether to enable text-based materialized view rewrite. When this item is set to true, the optimizer will compare the query with the existing materialized views. A query will be rewritten if the abstract syntax tree of the materialized view's definition matches that of the query or its sub-query.
-* **Default**: true
-* **Introduced in**: v3.2.5, v3.3.0
-
-### materialized_view_subuqery_text_match_max_count
-
-* **Description**: Specifies the maximum number of times that the system checks whether a query's sub-query matches the materialized views' definition.
-* **Default**: 4
-* **Introduced in**: v3.2.5, v3.3.0
-
-### enable_force_rule_based_mv_rewrite
-
-* **Description**: Whether to enable query rewrite for queries against multiple tables in the optimizer's rule-based optimization phase. Enabling this feature will improve the robustness of the query rewrite. However, it will also increase the time consumption if the query misses the materialized view.
-* **Default**: true
-* **Introduced in**: v3.3.0
-
-### enable_view_based_mv_rewrite
-
-* **Description**: Whether to enable query rewrite for logical view-based materialized views. If this item is set to `true`, the logical view is used as a unified node to rewrite the queries against itself for better performance. If this item is set to `false`, the system transcribes the queries against logical views into queries against physical tables or materialized views and then rewrites them.
-* **Default**: false
-* **Introduced in**: v3.1.9, v3.2.5, v3.3.0
-
-### enable_materialized_view_union_rewrite
-
-* **Description**: Whether to enable materialized view union rewrite. If this item is set to `true`, the system seeks to compensate the predicates using UNION ALL when the predicates in the materialized view cannot satisfy the query's predicates.
-* **Default**: true
-* **Introduced in**: v2.5.20, v3.1.9, v3.2.7, v3.3.0
-
-### enable_materialized_view_plan_cache
-
-* **Description**: Whether to enable materialized view plan cache, which can optimize the automatic rewrite performance of materialized views. Setting it to `true` indicates enabling it.
-* **Default**: true
-* **Introduced in**: v2.5.13, v3.0.7, v3.1.4, v3.2.0, v3.3.0
-
-### follower_query_forward_mode
-
-* **Description**: Specifies to which FE nodes the query statements are routed.
-
-  * Valid values:
-
-    * `default`: Routes the query statement to the Leader FE or Follower FEs, depending on the Follower's replay progress. If the Follower FE nodes have not completed replay progress, queries will be routed to the Leader FE node. If the replay progress is complete, queries will be preferentially routed to the Follower FE node.
-    * `leader`: Routes the query statement to the Leader FE.
-    * `follower`: Routes the query statement to Follower FE.
-
-* **Default**: default
-* **Data type**: String
-* **Introduced in**: v2.5.20, v3.1.9, v3.2.7, v3.3.0
-
-### character_set_database (global)
-
-* **Data type**: StringThe character set supported by StarRocks. Only UTF8 (`utf8`) is supported.
-* **Default**: utf8
-* **Data type**: String
-
-### connector_io_tasks_per_scan_operator
-
-* **Description**: The maximum number of concurrent I/O tasks that can be issued by a scan operator during external table queries. The value is an integer. Currently, StarRocks can adaptively adjust the number of concurrent I/O tasks when querying external tables. This feature is controlled by the variable `enable_connector_adaptive_io_tasks`, which is enabled by default.
-* **Default**: 16
-* **Data type**: Int
-* **Introduced in**: v2.5
-
-### connector_sink_compression_codec
-
-* **Description**: Specifies the compression algorithm used for writing data into Hive tables or Iceberg tables, or exporting data with Files().
-* **Valid values**: `uncompressed`, `snappy`, `lz4`, `zstd`, and `gzip`.
-* **Default**: uncompressed
-* **Data type**: String
-* **Introduced in**: v3.2.3
-
-### connector_sink_target_max_file_size
-
-* **Description**: Specifies the maximum size of target file for writing data into Hive tables or Iceberg tables, or exporting data with Files(). The limit is not exact and is applied on a best-effort basis.
-* **Unit**: Bytes
-* **Default**: 1073741824
-* **Data type**: Long
-* **Introduced in**: v3.3.0
-
-### count_distinct_column_buckets
-
-* **Description**: The number of buckets for the COUNT DISTINCT column in a group-by-count-distinct query. This variable takes effect only when `enable_distinct_column_bucketization` is set to `true`.
-* **Default**: 1024
-* **Introduced in**: v2.5
-
-### default_rowset_type (global)
-
-Used to set the default storage format used by the storage engine of the computing node. The currently supported storage formats are `alpha` and `beta`.
-
-### default_table_compression
-
-* **Description**: The default compression algorithm for table storage. Supported compression algorithms are `snappy, lz4, zlib, zstd`.
-
-  Note that if you specified the `compression` property in a CREATE TABLE statement, the compression algorithm specified by `compression` takes effect.
-
-* **Default**: lz4_frame
-* **Introduced in**: v3.0
-
-### disable_colocate_join
-
-* **Description**: Used to control whether the Colocation Join is enabled. The default value is `false`, meaning the feature is enabled. When this feature is disabled, query planning will not attempt to execute Colocation Join.
-* **Default**: false
-
-### disable_streaming_preaggregations
-
-Used to enable the streaming pre-aggregations. The default value is `false`, meaning it is enabled.
-
-### div_precision_increment
-
-Used for MySQL client compatibility. No practical usage.
-
-<!--
-### enable_collect_table_level_scan_stats (Invisible to users)
-
-This variable is introduced to solve compatibility issues.
-
-Default value: `true`.
--->
-
-### enable_datacache_async_populate_mode
-
-* **Description**: Whether to populate the data cache in asynchronous mode. By default, the system uses the synchronous mode to populate data cache, that is, populating the cache while querying data.
-* **Default**: false
-* **Introduced in**: v3.2.7
-
-### enable_connector_adaptive_io_tasks
-
-* **Description**: Whether to adaptively adjust the number of concurrent I/O tasks when querying external tables. Default value is `true`. If this feature is not enabled, you can manually set the number of concurrent I/O tasks using the variable `connector_io_tasks_per_scan_operator`.
-* **Default**: true
-* **Introduced in**: v2.5
-
-### enable_distinct_column_bucketization
-
-* **Description**: Whether to enable bucketization for the COUNT DISTINCT colum in a group-by-count-distinct query. Use the `select a, count(distinct b) from t group by a;` query as an example. If the GROUP BY colum `a` is a low-cardinality column and the COUNT DISTINCT column `b` is a high-cardinality column which has severe data skew, performance bottleneck will occur. In this situation, you can split data in the COUNT DISTINCT column into multiple buckets to balance data and prevent data skew. You must use this variable with the variable `count_distinct_column_buckets`.
-
-  You can also enable bucketization for the COUNT DISTINCT column by adding the `skew` hint to your query, for example, `select a,count(distinct [skew] b) from t group by a;`.
-
-* **Default**: false, which means this feature is disabled.
-* **Introduced in**: v2.5
-
-### enable_gin_filter
-
-* **Description**: Whether to utilize the [fulltext inverted index](../table_design/indexes/inverted_index.md) during queries.
-* **Default**: true
-* **Introduced in**: v3.3.0
-
-### enable_group_level_query_queue (global)
-
-* **Description**: Whether to enable resource group-level [query queue](../administration/management/resource_management/query_queues.md).
-* **Default**: false, which means this feature is disabled.
-* **Introduced in**: v3.1.4
-
-### enable_iceberg_metadata_cache
-
-* **Description**: Whether to cache pointers and partition names for Iceberg tables. From v3.2.1 to v3.2.3, this parameter is set to `true` by default, regardless of what metastore service is used. In v3.2.4 and later, if the Iceberg cluster uses AWS Glue as metastore, this parameter still defaults to `true`. However, if the Iceberg cluster uses other metastore service such as Hive metastore, this parameter defaults to `false`.
-* **Introduced in**: v3.2.1
-
-### enable_insert_strict
-
-Used to enable the strict mode when loading data using the INSERT statement. The default value is `true`, indicating the strict mode is enabled by default. For more information, see [Strict mode](../loading/load_concept/strict_mode.md).
-
-### enable_materialized_view_for_insert
-
-* **Description**: Whether to allow StarRocks to rewrite queries in INSERT INTO SELECT statements.
-* **Default**: false, which means Query Rewrite in such scenarios is disabled by default.
-* **Introduced in**: v2.5.18, v3.0.9, v3.1.7, v3.2.2
-
-### enable_rule_based_materialized_view_rewrite
-
-* **Description**: Controls whether to enable rule-based materialized view query rewrite. This variable is mainly used in single-table query rewrite. * **Default**: true
-* **Data type**: Boolean
-* **Introduced in**: v2.5
-
-### enable_short_circuit
-
-* **Description**: Whether to enable short circuiting for queries. Default: `false`. If it is set to `true`, when the query meets the criteria (to evaluate whether the query is a point query): the conditional columns in the WHERE clause include all primary key columns, and the operators in the WHERE clause are `=` or `IN`, the query takes the short circuit.
-* **Default**: false
-* **Introduced in**: v3.2.3
-
-### enable_spill
-
-* **Description**: Whether to enable intermediate result spilling. Default: `false`. If it is set to `true`, StarRocks spills the intermediate results to disk to reduce the memory usage when processing aggregate, sort, or join operators in queries.
-* **Default**: false
-* **Introduced in**: v3.0
-
-### enable_spill_to_remote_storage
-
-* **Description**: Whether to enable intermediate result spilling to object storage. If it is set to `true`, StarRocks spills the intermediate results to the storage volume specified in `spill_storage_volume` after the capacity limit of the local disk is reached. For more information, see [Spill to object storage](../administration/management/resource_management/spill_to_disk.md#spill-intermediate-result-to-object-storage).
-* **Default**: false
-* **Introduced in**: v3.3.0
-
-### enable_strict_order_by
-
-* **Description**: Used to check whether the column name referenced in ORDER BY is ambiguous. When this variable is set to the default value `TRUE`, an error is reported for such a query pattern: Duplicate alias is used in different expressions of the query and this alias is also a sorting field in ORDER BY, for example, `select distinct t1.* from tbl1 t1 order by t1.k1;`. The logic is the same as that in v2.3 and earlier. When this variable is set to `FALSE`, a loose deduplication mechanism is used, which processes such queries as valid SQL queries.
-* **Default**: true
-* **Introduced in**: v2.5.18 and v3.1.7
-
-### enable_profile
-
-* **Description**: Specifies whether to send the profile of a query for analysis. The default value is `false`, which means no profile is required.
-
-  By default, a profile is sent to the FE only when a query error occurs in the BE. Profile sending causes network overhead and therefore affects high concurrency.
-
-  If you need to analyze the profile of a query, you can set this variable to `true`. After the query is completed, the profile can be viewed on the web page of the currently connected FE (address: `fe_host:fe_http_port/query`). This page displays the profiles of the latest 100 queries with `enable_profile` turned on.
-
-* **Default**: false
-
-### enable_query_queue_load (global)
-
-* **Description**: Boolean value to enable query queues for loading tasks.
-* **Default**: false
-
-### enable_query_queue_select (global)
-
-* **Description**: Whether to enable query queues for SELECT queries.
-* **Default**: false
-
-### enable_query_queue_statistic (global)
-
-* **Description**: Whether to enable query queues for statistics queries.
-* **Default**: false
-
-### enable_query_tablet_affinity
-
-* **Description**: Boolean value to control whether to direct multiple queries against the same tablet to a fixed replica.
-
-  In scenarios where the table to query has a large number of tablets, this feature significantly improves query performance because the meta information and data of the tablet can be cached in memory more quickly.
-
-  However, if there are some hotspot tablets, this feature may degrade the query performance because it directs the queries to the same BE, making it unable to fully use the resources of multiple BEs in high-concurrency scenarios.
-
-* **Default**: false, which means the system selects a replica for each query.
-* **Introduced in**: v2.5.6, v3.0.8, v3.1.4, and v3.2.0.
-
-
-### enable_lake_tablet_internal_parallel
-
-* **Description**: Whether to enable Parallel Scan for Cloud-native tables in a shared-data cluster.
-* **Default**: false
-* **Data type**: Boolean
-* **Introduced in**: v3.3.0
-
-### tablet_internal_parallel_mode
-
-* **Description**: Internal Parallel Scan strategy of tablets. Valid Values:
-  * `auto`: When the number of Tablets to be scanned on BE or CN nodes is less than the Degree of Parallelism (DOP), the system automatically determines whether Parallel Scan is needed based on the estimated size of the Tablets.
-  * `force_split`: Forces the splitting of Tablets and performs Parallel Scan.
-* **Default**: auto
-* **Data type**: String
-* **Introduced in**: v2.5.0
-
-### enable_scan_datacache
-
-* **Description**: Specifies whether to enable the Data Cache feature. After this feature is enabled, StarRocks caches hot data read from external storage systems into blocks, which accelerates queries and analysis. For more information, see [Data Cache](../data_source/data_cache.md). In versions prior to 3.2, this variable was named as `enable_scan_block_cache`.
-* **Default**: false
-* **Introduced in**: v2.5
-
-### populate_datacache_mode
-
-* **Description**: Specifies the population behavior of Data Cache when reading data blocks from external storage systems. Valid values:
-  * `auto` (default): the system automatically caches data selectively based on the population rule.
-  * `always`: Always cache the data.
-  * `never`: Never cache the data.
-* **Default**: auto
-* **Introduced in**: v3.3.2
-
-### enable_datacache_io_adaptor
-
-* **Description**: Whether to enable the Data Cache I/O Adaptor. Setting this to `true` enables the feature. When this feature is enabled, the system automatically routes some cache requests to remote storage when the disk I/O load is high, reducing disk pressure.
-* **Default**: true
-* **Introduced in**: v3.3.0
-
-### enable_file_metacache
-
-* **Description**: Whether to enable metadata cache for files in remote storage (Footer Cache). Setting this to `true` enables the feature. Footer Cache directly caches the parsed Footer object in memory. When the same file's Footer is accessed in subsequent queries, the object descriptor can be obtained directly from the cache, avoiding repetitive parsing. This feature uses the memory module of the Data Cache for data caching. Therefore, you must ensure that the BE parameter `datacache_enable` is set to `true` and configure a reasonable value for `datacache_mem_size`.
-* **Default**: true
-* **Introduced in**: v3.3.0
-
-### enable_tablet_internal_parallel
-
-* **Description**: Whether to enable adaptive parallel scanning of tablets. After this feature is enabled, multiple threads can be used to scan one tablet by segment, increasing the scan concurrency.
-* **Default**: true
-* **Introduced in**: v2.3
-
-### enable_query_cache
-
-* **Description**: Specifies whether to enable the Query Cache feature. Valid values: true and false. `true` specifies to enable this feature, and `false` specifies to disable this feature. When this feature is enabled, it works only for queries that meet the conditions specified in the application scenarios of [Query Cache](../using_starrocks/query_cache.md#application-scenarios).
-* **Default**: false
-* **Introduced in**: v2.5
-
-### enable_adaptive_sink_dop
-
-* **Description**: Specifies whether to enable adaptive parallelism for data loading. After this feature is enabled, the system automatically sets load parallelism for INSERT INTO and Broker Load jobs, which is equivalent to the mechanism of `pipeline_dop`. For a newly deployed v2.5 StarRocks cluster, the value is `true` by default. For a v2.5 cluster upgraded from v2.4, the value is `false`.
-* **Default**: false
-* **Introduced in**: v2.5
-
-### enable_pipeline_engine
-
-* **Description**: Specifies whether to enable the pipeline execution engine. `true` indicates enabled and `false` indicates the opposite. Default value: `true`.
-* **Default**: true
-
-### enable_sort_aggregate
-
-* **Description**: Specifies whether to enable sorted streaming. `true` indicates sorted streaming is enabled to sort data in data streams.
-* **Default**: false
-* **Introduced in**: v2.5
-
-### enable_global_runtime_filter
-
-Whether to enable global runtime filter (RF for short). RF filters data at runtime. Data filtering often occurs in the Join stage. During multi-table joins, optimizations such as predicate pushdown are used to filter data, in order to reduce the number of scanned rows for Join and the I/O in the Shuffle stage, thereby speeding up the query.
-
-StarRocks offers two types of RF: Local RF and Global RF. Local RF is suitable for Broadcast Hash Join and Global RF is suitable for Shuffle Join.
-
-Default value: `true`, which means global RF is enabled. If this feature is disabled, global RF does not take effect. Local RF can still work.
-
-### enable_multicolumn_global_runtime_filter
-
-Whether to enable multi-column global runtime filter. Default value: `false`, which means multi-column global RF is disabled.
-
-If a Join (other than Broadcast Join and Replicated Join) has multiple equi-join conditions:
-
-* If this feature is disabled, only Local RF works.
-* If this feature is enabled, multi-column Global RF takes effect and carries `multi-column` in the partition by clause.
-
-### enable_write_hive_external_table
-
-* **Description**: Whether to allow for sinking data to external tables of Hive.
-* **Default**: false
-* **Introduced in**: v3.2
-
-### event_scheduler
-
-Used for MySQL client compatibility. No practical usage.
-
-### enable_strict_type
-
-* **Description**: Whether to allow implicit conversions for all compound predicates and for all expressions in the WHERE clause.
-* **Default**: false
-* **Introduced in**: v3.1
-
-### force_streaming_aggregate
-
-Used to control whether the aggregation node enables streaming aggregation for computing. The default value is false, meaning the feature is not enabled.
-
-### forward_to_leader
-
-Used to specify whether some commands will be forwarded to the leader FE for execution. Alias: `forward_to_master`. The default value is `false`, meaning not forwarding to the leader FE. There are multiple FEs in a StarRocks cluster, one of which is the leader FE. Normally, users can connect to any FE for full-featured operations. However, some information is only available on the leader FE.
-
-For example, if the SHOW BACKENDS command is not forwarded to the leader FE, only basic information (for example, whether the node is alive) can be viewed. Forwarding to the leader FE can get more detailed information including the node start time and last heartbeat time.
-
-The commands affected by this variable are as follows:
-
-* SHOW FRONTENDS: Forwarding to the leader FE allows users to view the last heartbeat message.
-
-* SHOW BACKENDS: Forwarding to the leader FE allows users to view the boot time, last heartbeat information, and disk capacity information.
-
-* SHOW BROKER: Forwarding to the leader FE allows users to view the boot time and last heartbeat information.
-
-* SHOW TABLET
-
-* ADMIN SHOW REPLICA DISTRIBUTION
-
-* ADMIN SHOW REPLICA STATUS: Forwarding to the leader FE allows users to view the tablet information stored in the metadata of the leader FE. Normally, the tablet information should be the same in the metadata of different FEs. If an error occurs, you can use this method to compare the metadata of the current FE and the leader FE.
-
-* Show PROC: Forwarding to the leader FE allows users to view the PROC information stored in the metadata. This is mainly used for metadata comparison.
-
-### group_concat_max_len
-
-* **Description**: The maximum length of string returned by the [group_concat](../sql-reference/sql-functions/string-functions/group_concat.md) function.
-* **Default**: 1024
-* **Min value**: 4
-* **Unit**: Characters
-* **Data type**: Long
-
-### hash_join_push_down_right_table
-
-* **Description**: Used to control whether the data of the left table can be filtered by using the filter condition against the right table in the Join query. If so, it can reduce the amount of data that needs to be processed during the query.
-**Default**: `true` indicates the operation is allowed and the system decides whether the left table can be filtered. `false` indicates the operation is disabled. The default value is `true`.
-
-### init_connect (global)
-
-Used for MySQL client compatibility. No practical usage.
-
-### interactive_timeout
-
-Used for MySQL client compatibility. No practical usage.
-
-### io_tasks_per_scan_operator
-
-* **Description**: The number of concurrent I/O tasks that can be issued by a scan operator. Increase this value if you want to access remote storage systems such as HDFS or S3 but the latency is high. However, a larger value causes more memory consumption.
-* **Default**: 4
-* **Data type**: Int
-* **Introduced in**: v2.5
-
-### language (global)
-
-Used for MySQL client compatibility. No practical usage.
-
-### license (global)
-
-* **Description**: Displays the license of StarRocks.
-* **Default**: Apache License 2.0
-
-### load_mem_limit
-
-Specifies the memory limit for the import operation. The default value is 0, meaning that this variable is not used and `query_mem_limit` is used instead.
-
-This variable is only used for the `INSERT` operation which involves both query and import. If the user does not set this variable, the memory limit for both query and import will be set as `exec_mem_limit`. Otherwise, the memory limit for query will be set as `exec_mem_limit` and the memory limit for import will be as `load_mem_limit`.
-
-Other import methods such as `BROKER LOAD`, `STREAM LOAD` still use `exec_mem_limit` for memory limit.
-
-### log_rejected_record_num (v3.1 and later)
-
-Specifies the maximum number of unqualified data rows that can be logged. Valid values: `0`, `-1`, and any non-zero positive integer. Default value: `0`.
-
-* The value `0` specifies that data rows that are filtered out will not be logged.
-* The value `-1` specifies that all data rows that are filtered out will be logged.
-* A non-zero positive integer such as `n` specifies that up to `n` data rows that are filtered out can be logged on each BE.
-
-### lower_case_table_names (global)
-
-Used for MySQL client compatibility. No practical usage. Table names in StarRocks are case-sensitive.
-
-### materialized_view_rewrite_mode (v3.2 and later)
-
-Specifies the query rewrite mode of asynchronous materialized views. Valid values:
-
-* `disable`: Disable automatic query rewrite of asynchronous materialized views.
-* `default` (Default value): Enable automatic query rewrite of asynchronous materialized views, and allow the optimizer to decide whether a query can be rewritten using the materialized view based on the cost. If the query cannot be rewritten, it directly scans the data in the base table.
-* `default_or_error`: Enable automatic query rewrite of asynchronous materialized views, and allow the optimizer to decide whether a query can be rewritten using the materialized view based on the cost. If the query cannot be rewritten, an error is returned.
-* `force`: Enable automatic query rewrite of asynchronous materialized views, and the optimizer prioritizes query rewrite using the materialized view. If the query cannot be rewritten, it directly scans the data in the base table.
-* `force_or_error`: Enable automatic query rewrite of asynchronous materialized views, and the optimizer prioritizes query rewrite using the materialized view. If the query cannot be rewritten, an error is returned.
-
-### max_allowed_packet
-
-* **Description**: Used for compatibility with the JDBC connection pool C3P0. This variable specifies the maximum size of packets that can be transmitted between the client and server.
-* **Default**: 33554432 (32 MB). You can raise this value if the client reports "PacketTooBigException".
-* **Unit**: Byte
-* **Data type**: Int
-
-### max_pushdown_conditions_per_column
-
-* **Description**: The maximum number of predicates that can be pushed down for a column.
-* **Default**: -1, indicating that the value in the `be.conf` file is used. If this variable is set to a value greater than 0, the value in `be.conf` is ignored.
-* **Data type**: Int
-
-### max_scan_key_num
-
-* **Description**: The maximum number of scan key segmented by each query.
-* **Default**: -1, indicating that the value in the `be.conf` file is used. If this variable is set to a value greater than 0, the value in `be.conf` is ignored.
-
-### nested_mv_rewrite_max_level
-
-* **Description**: The maximum levels of nested materialized views that can be used for query rewrite.
-* **Value range**: [1, +∞). The value of `1` indicates that only materialized views created on base tables can be used for query rewrite.
-* **Default**: 3
-* **Data type**: Int
-
-### net_buffer_length
-
-Used for MySQL client compatibility. No practical usage.
-
-### net_read_timeout
-
-Used for MySQL client compatibility. No practical usage.
-
-### net_write_timeout
-
-Used for MySQL client compatibility. No practical usage.
-
-### new_planner_optimize_timeout
-
-* **Description**: The timeout duration of the query optimizer. When the optimizer times out, an error is returned and the query is stopped, which affects the query performance. You can set this variable to a larger value based on your query or contact StarRocks technical support for troubleshooting. A timeout often occurs when a query has too many joins.
-* **Default**: 3000
-* **Unit**: ms
-
-### parallel_exchange_instance_num
-
-Used to set the number of exchange nodes that an upper-level node uses to receive data from a lower-level node in the execution plan. The default value is -1, meaning the number of exchange nodes is equal to the number of execution instances of the lower-level node. When  this variable is set to be greater than 0 but smaller than the number of execution instances of the lower-level node, the number of exchange nodes equals the set value.
-
-In a distributed query execution plan, the upper-level node usually has one or more exchange nodes to receive data from the execution instances of the lower-level node on different BEs. Usually the number of exchange nodes is equal to the number of execution instances of the lower-level node.
-
-In some aggregation query scenarios where the amount of data decreases drastically after aggregation, you can try to modify this variable to a smaller value to reduce the resource overhead. An example would be running aggregation queries using the Duplicate Key table.
-
-### parallel_fragment_exec_instance_num
-
-Used to set the number of instances used to scan nodes on each BE. The default value is 1.
-
-A query plan typically produces a set of scan ranges. This data is distributed across multiple BE nodes. A BE node will have one or more scan ranges, and by default, each BE node's set of scan ranges is processed by only one execution instance. When machine resources suffice, you can increase this variable to allow more execution instances to process a scan range simultaneously for efficiency purposes.
-
-The number of scan instances determines the number of other execution nodes in the upper level, such as aggregation nodes and join nodes. Therefore, it increases the concurrency of the entire query plan execution. Modifying this variable will help  improve efficiency, but larger values will consume more machine resources, such as CPU, memory, and disk IO.
-
-### partial_update_mode
-
-* **Description**: Used to control the mode of partial updates. Valid values:
-
-  * `auto` (default): The system automatically determines the mode of partial updates by analyzing the UPDATE statement and the columns involved.
-  * `column`: The column mode is used for the partial updates, which is particularly suitable for the partial updates which involve a small number of columns and a large number of rows.
-
-  For more information, see [UPDATE](../sql-reference/sql-statements/data-manipulation/UPDATE.md#partial-updates-in-column-mode-since-v31).
-* **Default**: auto
-* **Introduced in**: v3.1
-
-### performance_schema (global)
-
-Used for compatibility with MySQL JDBC versions 8.0.16 and above. No practical usage.
-
-### prefer_compute_node
-
-* **Description**: Specifies whether the FEs distribute query execution plans to CN nodes. Valid values:
-  * `true`: indicates that the FEs distribute query execution plans to CN nodes.
-  * `false`: indicates that the FEs do not distribute query execution plans to CN nodes.
-* **Default**: false
-* **Introduced in**: v2.4
-
-### pipeline_dop
-
-* **Description**: The parallelism of a pipeline instance, which is used to adjust the query concurrency. Default value: 0, indicating the system automatically adjusts the parallelism of each pipeline instance. You can also set this variable to a value greater than 0. Generally, set the value to half the number of physical CPU cores.
-
-  From v3.0 onwards, StarRocks adaptively adjusts this variable based on query parallelism.
-
-* **Default**: 0
-* **Data type**: Int
-
-### pipeline_profile_level
-
-* **Description**: Controls the level of the query profile. A query profile often has five layers: Fragment, FragmentInstance, Pipeline, PipelineDriver, and Operator. Different levels provide different details of the profile:
-
-  * 0: StarRocks combines metrics of the profile and shows only a few core metrics.
-  * 1: default value. StarRocks simplifies the profile and combines metrics of the profile to reduce profile layers.
-  * 2: StarRocks retains all the layers of the profile. The profile size is large in this scenario, especially when the SQL query is complex. This value is not recommended.
-
-* **Default**: 1
-* **Data type**: Int
-
-### query_cache_entry_max_bytes
-
-* **Description**: The threshold for triggering the Passthrough mode. When the number of bytes or rows from the computation results of a specific tablet accessed by a query exceeds the threshold specified by `query_cache_entry_max_bytes` or `query_cache_entry_max_rows`, the query is switched to Passthrough mode.
-* **Valid values**: 0 to 9223372036854775807
-* **Default**: 4194304
-* **Unit**: Byte
-* **Introduced in**: v2.5
-
-### query_cache_entry_max_rows
-
-* **Description**: The upper limit of rows that can be cached. See the description in `query_cache_entry_max_bytes`. Default value: .
-* **Default**: 409600
-* **Introduced in**: v2.5
-
-### query_cache_agg_cardinality_limit
-
-* **Description**: The upper limit of cardinality for GROUP BY in Query Cache. Query Cache is not enabled if the rows generated by GROUP BY exceeds this value. Default value: 5000000. If `query_cache_entry_max_bytes` or `query_cache_entry_max_rows` is set to 0, the Passthrough mode is used even when no computation results are generated from the involved tablets.
-* **Default**: 5000000
-* **Data type**: Long
-* **Introduced in**: v2.5
-
-### query_cache_size (global)
-
-Used for MySQL client compatibility. No practical use.
-
-### query_cache_type
-
-Used for compatibility with JDBC connection pool C3P0. No practical use.
-
-### query_mem_limit
-
-* **Description**: Used to set the memory limit of a query on each BE node. The default value is 0, which means no limit for it. This item takes effect only after Pipeline Engine is enabled. When the `Memory Exceed Limit` error happens, you could try to increase this variable.
-* **Default**: 0, which means no limit.
-* **Unit**: Byte
-
-### query_queue_concurrency_limit (global)
-
-* **Description**: The upper limit of concurrent queries on a BE. It takes effect only after being set greater than `0`.
-* **Default**: 0
-* **Data type**: Int
-
-### query_queue_cpu_used_permille_limit (global)
-
-* **Description**: The upper limit of CPU usage permille (CPU usage * 1000) on a BE. It takes effect only after being set greater than `0`.
-* **Value range**: [0, 1000]
-* **Default**: `0`
-
-### query_queue_max_queued_queries (global)
-
-* **Description**: The upper limit of queries in a queue. When this threshold is reached, incoming queries are rejected. It takes effect only after being set greater than `0`.
-* **Default**: `1024`.
-
-### query_queue_mem_used_pct_limit (global)
-
-* **Description**: The upper limit of memory usage percentage on a BE. It takes effect only after being set greater than `0`.
-* **Value range**: [0, 1]
-* **Default**: 0
-
-### query_queue_pending_timeout_second (global)
-
-* **Description**: The maximum timeout of a pending query in a queue. When this threshold is reached, the corresponding query is rejected.
-* **Default**: 300
-* **Unit**: Second
-
-### query_timeout
-
-* **Description**: Used to set the query timeout in "seconds". This variable will act on all query statements in the current connection, as well as INSERT statements. The default value is 300 seconds.
-* **Value range**: [1, 259200]
-* **Default**: 300
-* **Data type**: Int
-* **Unit**: Second
-
-### range_pruner_max_predicate
-
-* **Description**: The maximum number of IN predicates that can be used for Range partition pruning. Default value: 100. A value larger than 100 may cause the system to scan all tablets, which compromises the query performance.
-* **Default**: 100
-* **Introduced in**: v3.0
-
-### rewrite_count_distinct_to_bitmap_hll
-
-Used to decide whether to rewrite count distinct queries to bitmap_union_count and hll_union_agg.
-
-### runtime_filter_on_exchange_node
-
-* **Description**: Whether to place GRF on Exchange Node after GRF is pushed down across the Exchange operator to a lower-level operator. The default value is `false`, which means GRF will not be placed on Exchange Node after it is pushed down across the Exchange operator to a lower-level operator. This prevents repetitive use of GRF and reduces the computation time.
-
-  However, GRF delivery is a "try-best" process. If the lower-level operator fails to receive the GRF but the GRF is not placed on Exchange Node, data cannot be filtered, which compromises filter performance. `true` means GRF will still be placed on Exchange Node even after it is pushed down across the Exchange operator to a lower-level operator.
-
-* **Default**: false
-
-### runtime_join_filter_push_down_limit
-
-* **Description**: The maximum number of rows allowed for the Hash table based on which Bloom filter Local RF is generated. Local RF will not be generated if this value is exceeded. This variable prevents the generation of an excessively long Local RF.
-* **Default**: 1024000
-* **Data type**: Int
-
-### runtime_profile_report_interval
-
-* **Description**: The time interval at which runtime profiles are reported.
-* **Default**: 10
-* **Unit**: Second
-* **Data type**: Int
-* **Introduced in**: v3.1.0
-
-### spill_mode (3.0 and later)
-
-The execution mode of intermediate result spilling. Valid values:
-
-* `auto`: Spilling is automatically triggered when the memory usage threshold is reached.
-* `force`: StarRocks forcibly executes spilling for all relevant operators, regardless of memory usage.
-
-This variable takes effect only when the variable `enable_spill` is set to `true`.
-
-### spill_storage_volume
-
-* **Description**: The storage volume with which you want to store the intermediate results of queries that triggered spilling. For more information, see [Spill to object storage](../administration/management/resource_management/spill_to_disk.md#spill-intermediate-result-to-object-storage).
-* **Default**: Empty string
-* **Introduced in**: v3.3.0
-
-### SQL_AUTO_IS_NULL
-
-Used for compatibility with the JDBC connection pool C3P0. No practical usage.
-
-### sql_dialect
-
-* **Description**: The SQL dialect that is used. For example, you can run the `set sql_dialect = 'trino';` command to set the SQL dialect to Trino, so you can use Trino-specific SQL syntax and functions in your queries.
-
-  > **NOTICE**
-  >
-  > After you configure StarRocks to use the Trino dialect, identifiers in queries are not case-sensitive by default. Therefore, you must specify names in lowercase for your databases and tables at database and table creation. If you specify database and table names in uppercase, queries against these databases and tables will fail.
-
-* **Data type**: StarRocks
-* **Introduced in**: v3.0
-
-### sql_mode
-
-Used to specify the SQL mode to accommodate certain SQL dialects. Valid values include:
-
-* `PIPES_AS_CONCAT`: The pipe symbol `|` is used to concatenate strings, for example, `select 'hello ' || 'world'`.
-* `ONLY_FULL_GROUP_BY` (Default): The SELECT LIST can only contain GROUP BY columns or aggregate functions.
-* `ALLOW_THROW_EXCEPTION`: returns an error instead of NULL when type conversion fails.
-* `FORBID_INVALID_DATE`: prohibits invalid dates.
-* `MODE_DOUBLE_LITERAL`: interprets floating-point types as DOUBLE rather than DECIMAL.
-* `SORT_NULLS_LAST`: places NULL values at the end after sorting.
-* `ERROR_IF_OVERFLOW`: returns an error instead of NULL in the case of arithmetic overflow. Currently, only the DECIMAL data type supports this option.
-* `GROUP_CONCAT_LEGACY`: uses the `group_concat` syntax of v2.5 and earlier. This option is supported from v3.0.9 and v3.1.6.
-
-You can set only one SQL mode, for example:
-
-```SQL
-set sql_mode = 'PIPES_AS_CONCAT';
-```
-
-Or, you can set multiple modes at a time, for example:
-
-```SQL
-set sql_mode = 'PIPES_AS_CONCAT,ERROR_IF_OVERFLOW,GROUP_CONCAT_LEGACY';
-```
-
-### sql_safe_updates
-
-Used for MySQL client compatibility. No practical usage.
-
-### sql_select_limit
-
-Used for MySQL client compatibility. No practical usage.
-
-### statistic_collect_parallel
-
-* **Description**: Used to adjust the parallelism of statistics collection tasks that can run on BEs. Default value: 1. You can increase this value to speed up collection tasks.
-* **Default**: 1
-* **Data type**: Int
-
-### storage_engine
-
-The types of engines supported by StarRocks:
-
-* olap (default): StarRocks system-owned engine.
-* mysql: MySQL external tables.
-* broker: Access external tables through a broker program.
-* elasticsearch or es: Elasticsearch external tables.
-* hive: Hive external tables.
-* iceberg: Iceberg external tables, supported from v2.1.
-* hudi: Hudi external tables, supported from v2.2.
-* jdbc: external table for JDBC-compatible databases, supported from v2.3.
-
-### streaming_preaggregation_mode
-
-Used to specify the preaggregation mode for the first phase of GROUP BY. If the preaggregation effect in the first phase is not satisfactory, you can use the streaming mode, which performs simple data serialization before streaming data to the destination. Valid values:
-
-* `auto`: The system first tries local preaggregation. If the effect is not satisfactory, it switches to the streaming mode. This is the default value.
-* `force_preaggregation`: The system directly performs local preaggregation.
-* `force_streaming`: The system directly performs streaming.
-
-### system_time_zone
-
-Used to display the time zone of the current system. Cannot be changed.
-
-### time_zone
-
-Used to set the time zone of the current session. The time zone can affect the results of certain time functions.
-
-### trace_log_mode
-
-* **Description**: Used to control where to output the logs of query trace profiles. Valid values:
-  * `command`: Return query trace profile logs as the **Explain String** after executing TRACE LOGS.
-  * `file`: Return query trace profile logs in the FE log file **fe.log** with the class name being `FileLogTracer`.
-
-* **Default**: `command`
-* **Data type**: String
-* **Introduced in**: v3.2.0
-
-### transaction_read_only
-
-* **Description**: Used for MySQL 5.8 compatibility. The alias is `tx_read_only`. This variable specifies the transaction access mode. `ON` indicates read only and `OFF` indicates readable and writable.
-* **Default**: OFF
-* **Introduced in**: v2.5.18, v3.0.9, v3.1.7
-
-### tx_isolation
-
-Used for MySQL client compatibility. No practical usage. The alias is `transaction_isolation`.
-
-### use_compute_nodes
-
-* **Description**: The maximum number of CN nodes that can be used. This variable is valid when `prefer_compute_node=true`. Valid values:
-
-  * `-1`: indicates that all CN nodes are used.
-  * `0`: indicates that no CN nodes are used.
-* **Default**: -1
-* **Data type**: Int
-* **Introduced in**: v2.4
-
-### use_v2_rollup
-
-Used to control the query to fetch data using the rollup index of the segment v2 storage format. This variable is used for validation when going online with segment v2. It is not recommended for other cases.
-
-### vectorized_engine_enable (deprecated from v2.4 onwards)
-
-Used to control whether the vectorized engine is used to execute queries. A value of `true` indicates that the vectorized engine is used, otherwise the non-vectorized engine is used. The default is `true`. This feature is enabled by default from v2.4 onwards and therefore, is deprecated.
-
-### version (global)
-
-The MySQL server version returned to the client. The value is the same as FE parameter `mysql_server_version`.
-
-### version_comment (global)
-
-The StarRocks version. Cannot be changed.
-
-### wait_timeout
-
-* **Description**: The number of seconds the server waits for activity on a non-interactive connection before closing it. If a client does not interact with StarRocks for this length of time, StarRocks will actively close the connection.
-* **Default**: 28800 (8 hours).
-* **Unit**: Second
-* **Data type**: Int
-
-### orc_use_column_names
-
-* **Description**: Used to specify how columns are matched when StarRocks reads ORC files from Hive. The default value is `false`, which means columns in ORC files are read based on their ordinal positions in the Hive table definition. If this variable is set to `true`, columns are read based on their names.
-* **Default**: false
-* **Introduced in**: v3.1.10
diff --git a/docs/en/reference/aws_iam_policies.md b/docs/en/reference/aws_iam_policies.md
deleted file mode 100644
index b9d054103809d0..00000000000000
--- a/docs/en/reference/aws_iam_policies.md
+++ /dev/null
@@ -1,128 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# AWS IAM policies
-
-A policy in AWS IAM declares a set of permissions on a specific AWS resource. After creating a policy, you need to attach it to an IAM role or user. As such, the IAM role or user is assigned the permissions declared in the policy to access the specified AWS resource.
-
-Different operations in StarRocks require you to have access permissions on different AWS resources, and therefore you need to configure different policies.
-
-This topic provides the IAM policies that you need to configure for StarRocks to integrate with different AWS resources in various business scenarios when you choose [the instance profile, assumed role, or IAM user-based authentication method](../integrations/authenticate_to_aws_resources.md#preparations).
-
-## Batch load data from AWS S3
-
-If you want to load data from your S3 bucket, configure the following IAM policy:
-
-> **NOTICE**
->
-> Replace `<bucket_name>` in the following JSON policy template with the name of your S3 bucket that stores your data files.
-
-```SQL
-{
-  "Version": "2012-10-17",
-  "Statement": [
-      {
-          "Sid": "s3",
-          "Effect": "Allow",
-          "Action": [
-              "s3:GetObject"
-          ],
-          "Resource": [
-              "arn:aws:s3:::<bucket_name>/*"
-          ]
-      },
-      {
-          "Sid": "s3list",
-          "Effect": "Allow",
-          "Action": [
-              "s3:ListBucket"
-          ],
-          "Resource": [
-              "arn:aws:s3:::<bucket_name>"
-          ]
-      }
-  ]
-}
-```
-
-## Read/write AWS S3
-
-If you want to query data from your S3 bucket, configure the following IAM policy:
-
-> **NOTICE**
->
-> Replace `<bucket_name>` in the following JSON policy template with the name of your S3 bucket that stores your data files.
-
-```SQL
-{
-  "Version": "2012-10-17",
-  "Statement": [
-      {
-          "Sid": "s3",
-          "Effect": "Allow",
-          "Action": [
-              "s3:PutObject",
-              "s3:GetObject",
-              "s3:DeleteObject"
-          ],
-          "Resource": [
-              "arn:aws:s3:::<bucket_name>/*"
-          ]
-      },
-      {
-          "Sid": "s3list",
-          "Effect": "Allow",
-          "Action": [
-              "s3:ListBucket"
-          ],
-          "Resource": [
-              "arn:aws:s3:::<bucket_name>"
-          ]
-      }
-  ]
-}
-```
-
-## Integrate with AWS Glue
-
-If you want to integrate with your AWS Glue Data Catalog, configure the following IAM policy:
-
-```SQL
-{
-    "Version": "2012-10-17",
-    "Statement": [
-      {
-          "Effect": "Allow",
-          "Action": [
-                "glue:BatchCreatePartition",
-                "glue:UpdateDatabase",
-                "glue:GetConnections",
-                "glue:CreateTable",
-                "glue:DeleteDatabase",
-                "glue:BatchUpdatePartition",
-                "glue:GetTables",
-                "glue:GetTableVersions",
-                "glue:GetPartitions",
-                "glue:UpdateTable",
-                "glue:BatchGetPartition",
-                "glue:DeleteTable",
-                "glue:GetDatabases",
-                "glue:GetDevEndpoint",
-                "glue:GetTable",
-                "glue:GetDatabase",
-                "glue:GetPartition",
-                "glue:GetDevEndpoints",
-                "glue:GetConnection",
-                "glue:CreateDatabase",
-                "glue:CreatePartition",
-                "glue:DeletePartition",
-                "glue:UpdatePartition"
-          ],
-          "Resource": [
-              "*"
-            ]
-        }
-    ]
-}
-```
diff --git a/docs/en/reference/information_schema/be_bvars.md b/docs/en/reference/information_schema/be_bvars.md
deleted file mode 100644
index f1136ef4f8cb6e..00000000000000
--- a/docs/en/reference/information_schema/be_bvars.md
+++ /dev/null
@@ -1,15 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# be_bvars
-
-`be_bvars` provides statistical information regarding bRPC. You can view RPC latency, QPS, and other statistics for some components of StarRocks.
-
-The following fields are provided in `be_bvars`:
-
-| **Field** | **Description**                                              |
-| --------- | ------------------------------------------------------------ |
-| BE_ID     | ID of the BE where the bvar is located.                      |
-| NAME      | Name of the bvar.                                            |
-| DESC      | Description of the bvar, including important statistical information. |
diff --git a/docs/en/reference/information_schema/be_cloud_native_compactions.md b/docs/en/reference/information_schema/be_cloud_native_compactions.md
deleted file mode 100644
index ba34072f26d714..00000000000000
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----
-displayed_sidebar: "English"
----
-
-# be_cloud_native_compactions
-
-`be_cloud_native_compactions` provides information on compaction transactions running on CNs (or BEs for v3.0) of a shared-data cluster. A compaction transaction is divided into multiple tasks on the tablet level, and each row in `be_cloud_native_compactions` corresponds to a task in the compaction transaction.
-
-The following fields are provided in `be_cloud_native_compactions`:
-
-| **Field**   | **Description**                                              |
-| ----------- | ------------------------------------------------------------ |
-| BE_ID       | ID of the CN (BE).                                           |
-| TXN_ID      | ID of the compaction transaction. It can be duplicated because each compaction transaction may have multiple tasks. |
-| TABLET_ID   | ID of the tablet the task corresponds to.                    |
-| VERSION     | Version of the data that is input to the task.               |
-| SKIPPED     | Whether the task is skipped.                                 |
-| RUNS        | Number of task executions. A value greater than `1` indicates that retries have occurred. |
-| START_TIME  | Task start time.                                             |
-| FINISH_TIME | Task finish time. `NULL` is returned if the task is still in progress. |
-| PROGRESS    | Percentage of progress, ranging from 0 to 100.               |
-| STATUS      | Task status.                                                 |
-
diff --git a/docs/en/reference/information_schema/be_compactions.md b/docs/en/reference/information_schema/be_compactions.md
deleted file mode 100644
index caa9796f28c0a8..00000000000000
--- a/docs/en/reference/information_schema/be_compactions.md
+++ /dev/null
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----
-displayed_sidebar: "English"
----
-
-# be_compactions
-
-`be_compactions` provides statistical information on compaction tasks.
-
-The following fields are provided in `be_compactions`:
-
-| **Field**                         | **Description**                                         |
-| --------------------------------- | ------------------------------------------------------- |
-| BE_ID                             | ID of the BE.                                           |
-| CANDIDATES_NUM                    | Number of candidates for compaction tasks.              |
-| BASE_COMPACTION_CONCURRENCY       | Number of base compaction tasks that are running.       |
-| CUMULATIVE_COMPACTION_CONCURRENCY | Number of cumulative compaction tasks that are running. |
-| LATEST_COMPACTION_SCORE           | Compaction score of the last compaction task.           |
-| CANDIDATE_MAX_SCORE               | The maximum compaction score of the task candidate.     |
-| MANUAL_COMPACTION_CONCURRENCY     | Number of manual compaction tasks that are running.     |
-| MANUAL_COMPACTION_CANDIDATES_NUM  | Number of candidates for manual compaction tasks.       |
diff --git a/docs/en/reference/information_schema/character_sets.md b/docs/en/reference/information_schema/character_sets.md
deleted file mode 100644
index 71da1014493ec2..00000000000000
--- a/docs/en/reference/information_schema/character_sets.md
+++ /dev/null
@@ -1,16 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# character_sets
-
-`character_sets` identifies the character sets available.
-
-The following fields are provided in `character_sets`:
-
-| **Field**            | **Description**                                              |
-| -------------------- | ------------------------------------------------------------ |
-| CHARACTER_SET_NAME   | The character set name.                                      |
-| DEFAULT_COLLATE_NAME | The default collation for the character set.                 |
-| DESCRIPTION          | A description of the character set.                          |
-| MAXLEN               | The maximum number of bytes required to store one character. |
diff --git a/docs/en/reference/information_schema/collations.md b/docs/en/reference/information_schema/collations.md
deleted file mode 100644
index f085d4e4fc68a4..00000000000000
--- a/docs/en/reference/information_schema/collations.md
+++ /dev/null
@@ -1,18 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# collations
-
-`collations` contains the available collations.
-
-The following fields are provided in `collations`:
-
-| **Field**          | **Description**                                              |
-| ------------------ | ------------------------------------------------------------ |
-| COLLATION_NAME     | The collation name.                                          |
-| CHARACTER_SET_NAME | The name of the character set with which the collation is associated. |
-| ID                 | The collation ID.                                            |
-| IS_DEFAULT         | Whether the collation is the default for its character set.  |
-| IS_COMPILED        | Whether the character set is compiled into the server.       |
-| SORTLEN            | This is related to the amount of memory required to sort strings expressed in the character set. |
diff --git a/docs/en/reference/information_schema/column_privileges.md b/docs/en/reference/information_schema/column_privileges.md
deleted file mode 100644
index 155ac1b3244423..00000000000000
--- a/docs/en/reference/information_schema/column_privileges.md
+++ /dev/null
@@ -1,25 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# column_privileges
-
-:::note
-
-This view does not apply to the available features in StarRocks.
-
-:::
-
-`column_privileges` identifies all privileges granted on columns to a currently enabled role or by a currently enabled role.
-
-The following fields are provided in `column_privileges`:
-
-| **Field**      | **Description**                                              |
-| -------------- | ------------------------------------------------------------ |
-| GRANTEE        | The name of the user to which the privilege is granted.      |
-| TABLE_CATALOG  | The name of the catalog to which the table containing the column belongs. This value is always `def`. |
-| TABLE_SCHEMA   | The name of the database to which the table containing the column belongs. |
-| TABLE_NAME     | The name of the table containing the column.                 |
-| COLUMN_NAME    | The name of the column.                                      |
-| PRIVILEGE_TYPE | The privilege granted. The value can be any privilege that can be granted at the column level. Each row lists a single privilege, so there is one row per column privilege held by the grantee. |
-| IS_GRANTABLE   | `YES` if the user has the `GRANT OPTION` privilege, `NO` otherwise. The output does not list `GRANT OPTION` as a separate row with `PRIVILEGE_TYPE='GRANT OPTION'`. |
diff --git a/docs/en/reference/information_schema/columns.md b/docs/en/reference/information_schema/columns.md
deleted file mode 100644
index 60c74a0d9171a2..00000000000000
--- a/docs/en/reference/information_schema/columns.md
+++ /dev/null
@@ -1,40 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# columns
-
-`columns` contains information about all table columns (or view columns).
-
-:::note
-The metadata of [synchronous materialized views](../../using_starrocks/Materialized_view-single_table.md) is not recorded in `columns`. You can access it by executing `SHOW PROC '/dbs/db/table/index_schema'`.
-:::
-
-The following fields are provided in `columns`:
-
-| **Field**                | **Description**                                              |
-| ------------------------ | ------------------------------------------------------------ |
-| TABLE_CATALOG            | The name of the catalog to which the table containing the column belongs. This value is always `NULL`. |
-| TABLE_SCHEMA             | The name of the database to which the table containing the column belongs. |
-| TABLE_NAME               | The name of the table containing the column.                 |
-| COLUMN_NAME              | The name of the column.                                      |
-| ORDINAL_POSITION         | The ordinal position of the column within the table.         |
-| COLUMN_DEFAULT           | The default value for the column. This is `NULL` if the column has an explicit default of `NULL`, or if the column definition includes no `DEFAULT` clause. |
-| IS_NULLABLE              | The column nullability. The value is `YES` if `NULL` values can be stored in the column, `NO` if not. |
-| DATA_TYPE                | The column data type. The `DATA_TYPE` value is the type name only with no other information. The `COLUMN_TYPE` value contains the type name and possibly other information such as the precision or length. |
-| CHARACTER_MAXIMUM_LENGTH | For string columns, the maximum length in characters.        |
-| CHARACTER_OCTET_LENGTH   | For string columns, the maximum length in bytes.             |
-| NUMERIC_PRECISION        | For numeric columns, the numeric precision.                  |
-| NUMERIC_SCALE            | For numeric columns, the numeric scale.                      |
-| DATETIME_PRECISION       | For temporal columns, the fractional seconds precision.      |
-| CHARACTER_SET_NAME       | For character string columns, the character set name.        |
-| COLLATION_NAME           | For character string columns, the collation name.            |
-| COLUMN_TYPE              | The column data type.<br />The `DATA_TYPE` value is the type name only with no other information. The `COLUMN_TYPE` value contains the type name and possibly other information such as the precision or length. |
-| COLUMN_KEY               | Whether the column is indexed:<ul><li>If `COLUMN_KEY` is empty, the column either is not indexed or is indexed only as a secondary column in a multiple-column, nonunique index.</li><li>If `COLUMN_KEY` is `PRI`, the column is a `PRIMARY KEY` or is one of the columns in a multiple-column `PRIMARY KEY`.</li><li>If `COLUMN_KEY` is `UNI`, the column is the first column of a `UNIQUE` index. (A `UNIQUE` index permits multiple `NULL` values, but you can tell whether the column permits `NULL` by checking the `Null` column.)</li><li>If `COLUMN_KEY` is `DUP`, the column is the first column of a nonunique index in which multiple occurrences of a given value are permitted within the column.</li></ul>If more than one of the `COLUMN_KEY` values applies to a given column of a table, `COLUMN_KEY` displays the one with the highest priority, in the order `PRI`, `UNI`, `DUP`.<br />A `UNIQUE` index may be displayed as `PRI` if it cannot contain `NULL` values and there is no `PRIMARY KEY` in the table. A `UNIQUE` index may display as `MUL` if several columns form a composite `UNIQUE` index; although the combination of the columns is unique, each column can still hold multiple occurrences of a given value. |
-| EXTRA                    | Any additional information that is available about a given column. |
-| PRIVILEGES               | The privileges you have for the column.                      |
-| COLUMN_COMMENT           | Any comment included in the column definition.               |
-| COLUMN_SIZE              |                                                              |
-| DECIMAL_DIGITS           |                                                              |
-| GENERATION_EXPRESSION    | For generated columns, displays the expression used to compute column values. Empty for nongenerated columns. |
-| SRS_ID                   | This value applies to spatial columns. It contains the column `SRID` value that indicates the spatial reference system for values stored in the column. |
diff --git a/docs/en/reference/information_schema/engines.md b/docs/en/reference/information_schema/engines.md
deleted file mode 100644
index 02a721dfa452b9..00000000000000
--- a/docs/en/reference/information_schema/engines.md
+++ /dev/null
@@ -1,24 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# engines
-
-:::note
-
-This view does not apply to the available features in StarRocks.
-
-:::
-
-`engines` provides information about storage engines.
-
-The following fields are provided in `engines`:
-
-| **Field**    | **Description**                                              |
-| ------------ | ------------------------------------------------------------ |
-| ENGINE       | The name of the storage engine.                              |
-| SUPPORT      | The server's level of support for the storage engine. Valid values:<ul><li>`YES`: The engine is supported and active.</li><li>`DEFAULT`: Like `YES`, plus this is the default engine.</li><li>`NO`: The engine is not supported.</li><li>`DISABLED`: The engine is supported but has been disabled.</li></ul> |
-| COMMENT      | A brief description of the storage engine.                   |
-| TRANSACTIONS | Whether the storage engine supports transactions.            |
-| XA           | Whether the storage engine supports XA transactions.         |
-| SAVEPOINTS   | Whether the storage engine supports savepoints.              |
diff --git a/docs/en/reference/information_schema/events.md b/docs/en/reference/information_schema/events.md
deleted file mode 100644
index 24c80c926709e2..00000000000000
--- a/docs/en/reference/information_schema/events.md
+++ /dev/null
@@ -1,42 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# events
-
-:::note
-
-This view does not apply to the available features in StarRocks.
-
-:::
-
-`events` provides information about Event Manager events.
-
-The following fields are provided in `events`:
-
-| **Field**            | **Description**                                              |
-| -------------------- | ------------------------------------------------------------ |
-| EVENT_CATALOG        | The name of the catalog to which the event belongs. This value is always `def`. |
-| EVENT_SCHEMA         | The name of the database to which the event belongs.         |
-| EVENT_NAME           | The name of the event.                                       |
-| DEFINER              | The user named in the `DEFINER` clause (often the user who created the event). |
-| TIME_ZONE            | The event time zone, which is the time zone used for scheduling the event and that is in effect within the event as it executes. The default value is `SYSTEM`. |
-| EVENT_BODY           | The language used for the statements in the event's `DO` clause. The value is always `SQL`. |
-| EVENT_DEFINITION     | The text of the SQL statement making up the event's `DO` clause; in other words, the statement executed by this event. |
-| EVENT_TYPE           | The event repetition type, either `ONE TIME` (transient) or `RECURRING` (repeating). |
-| EXECUTE_AT           | For a one-time event, this is the `DATETIME` value specified in the `AT` clause of the `CREATE EVENT` statement used to create the event, or of the last `ALTER EVENT` statement that modified the event. The value shown in this column reflects the addition or subtraction of any `INTERVAL` value included in the event's `AT` clause. For example, if an event is created using `ON SCHEDULE AT CURRENT_DATETIME + '1:6' DAY_HOUR`, and the event was created at 2018-02-09 14:05:30, the value shown in this column would be `'2018-02-10 20:05:30'`. If the event's timing is determined by an `EVERY` clause instead of an `AT` clause (that is, if the event is recurring), the value of this column is `NULL`. |
-| INTERVAL_VALUE       | For a recurring event, the number of intervals to wait between event executions. For a transient event, the value is always `NULL`. |
-| INTERVAL_FIELD       | The time units used for the interval which a recurring event waits before repeating. For a transient event, the value is always `NULL`. |
-| SQL_MODE             | The SQL mode in effect when the event was created or altered, and under which the event executes. |
-| STARTS               | The start date and time for a recurring event. This is displayed as a `DATETIME` value, and is `NULL` if no start date and time are defined for the event. For a transient event, this column is always `NULL`. For a recurring event whose definition includes a `STARTS` clause, this column contains the corresponding `DATETIME` value. As with the `EXECUTE_AT` column, this value resolves any expressions used. If there is no `STARTS` clause affecting the timing of the event, this column is `NULL`. |
-| ENDS                 | For a recurring event whose definition includes a `ENDS` clause, this column contains the corresponding `DATETIME` value. As with the `EXECUTE_AT` column, this value resolves any expressions used. If there is no `ENDS` clause affecting the timing of the event, this column is `NULL`. |
-| STATUS               | The event status. One of `ENABLED`, `DISABLED`, or `SLAVESIDE_DISABLED`. `SLAVESIDE_DISABLED` indicates that the creation of the event occurred on another MySQL server acting as a replication source and replicated to the current MySQL server which is acting as a replica, but the event is not presently being executed on the replica. |
-| ON_COMPLETION        | Valid values: `PRESERVE` and `NOT PRESERVE`.                 |
-| CREATED              | The date and time when the event was created. This is a `DATETIME` value. |
-| LAST_ALTERED         | The date and time when the event was last modified. This is a `DATETIME` value. If the event has not been modified since its creation, this value is the same as the `CREATED` value. |
-| LAST_EXECUTED        | The date and time when the event last executed. This is a `DATETIME` value. If the event has never executed, this column is `NULL`.`LAST_EXECUTED` indicates when the event started. As a result, the `ENDS` column is never less than `LAST_EXECUTED`. |
-| EVENT_COMMENT        | The text of the comment, if the event has one. If not, this value is empty. |
-| ORIGINATOR           | The server ID of the MySQL server on which the event was created; used in replication. This value may be updated by `ALTER EVENT` to the server ID of the server on which that statement occurs, if executed on a replication source. The default value is 0. |
-| CHARACTER_SET_CLIENT | The session value of the `character_set_client` system variable when the event was created. |
-| COLLATION_CONNECTION | The session value of the `collation_connection` system variable when the event was created. |
-| DATABASE_COLLATION   | The collation of the database with which the event is associated. |
diff --git a/docs/en/reference/information_schema/global_variables.md b/docs/en/reference/information_schema/global_variables.md
deleted file mode 100644
index 02338c7b7d3386..00000000000000
--- a/docs/en/reference/information_schema/global_variables.md
+++ /dev/null
@@ -1,14 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# global_variables
-
-`global_variables` provides information about global variables.
-
-The following fields are provided in `global_variables`:
-
-| **Field**      | **Description**        |
-| -------------- | ---------------------- |
-| VARIABLE_NAME  | Name of the variable.  |
-| VARIABLE_VALUE | Value of the variable. |
diff --git a/docs/en/reference/information_schema/key_column_usage.md b/docs/en/reference/information_schema/key_column_usage.md
deleted file mode 100644
index bab9bf5ac34159..00000000000000
--- a/docs/en/reference/information_schema/key_column_usage.md
+++ /dev/null
@@ -1,30 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# key_column_usage
-
-:::note
-
-This view does not apply to the available features in StarRocks.
-
-:::
-
-`key_column_usage` identifies all columns that are restricted by some unique, primary key, or foreign key constraint.
-
-The following fields are provided in `key_column_usage`:
-
-| **Field**                     | **Description**                                              |
-| ----------------------------- | ------------------------------------------------------------ |
-| CONSTRAINT_CATALOG            | The name of the catalog to which the constraint belongs. This value is always `def`. |
-| CONSTRAINT_SCHEMA             | The name of the database to which the constraint belongs.    |
-| CONSTRAINT_NAME               | The name of the constraint.                                  |
-| TABLE_CATALOG                 | The name of the catalog to which the table belongs. This value is always `def`. |
-| TABLE_SCHEMA                  | The name of the database to which the table belongs.         |
-| TABLE_NAME                    | The name of the table that has the constraint.               |
-| COLUMN_NAME                   | The name of the column that has the constraint.If the constraint is a foreign key, then this is the column of the foreign key, not the column that the foreign key references. |
-| ORDINAL_POSITION              | The column's position within the constraint, not the column's position within the table. Column positions are numbered beginning with 1. |
-| POSITION_IN_UNIQUE_CONSTRAINT | `NULL` for unique and primary-key constraints. For foreign-key constraints, this column is the ordinal position in key of the table that is being referenced. |
-| REFERENCED_TABLE_SCHEMA       | The name of the schema referenced by the constraint.         |
-| REFERENCED_TABLE_NAME         | The name of the table referenced by the constraint.          |
-| REFERENCED_COLUMN_NAME        | The name of the column referenced by the constraint.         |
diff --git a/docs/en/reference/information_schema/load_tracking_logs.md b/docs/en/reference/information_schema/load_tracking_logs.md
deleted file mode 100644
index 6e005d1cd7894c..00000000000000
--- a/docs/en/reference/information_schema/load_tracking_logs.md
+++ /dev/null
@@ -1,36 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# load_tracking_logs
-
-`load_tracking_logs` provides error logs of load jobs. This view is supported from StarRocks v3.0 onwards.
-
-The following fields are provided in `load_tracking_logs`:
-
-| **Field**     | **Description**                            |
-| ------------- | ------------------------------------------ |
-| ID            | The ID of the load.                        |
-| JOB_ID        | The ID of the load job(deprecated).                    |
-| LABEL         | The label of the load job.                 |
-| DATABASE_NAME | The database that the load job belongs to. |
-| TRACKING_LOG  | Errors (if any) of the load job.           |
-
-:::tip
-To query the view `load_tracking_logs` you will need to filter on either a `JOB_ID` or a `LABEL`.
-
-You can retrieve the `JOB_ID` or `LABEL` of a load job from the view `information_schema.loads`.
-
-Example:
-
-```sql
-SELECT * from information_schema.load_tracking_logs WHERE label ='user_behavior'\G
-*************************** 1. row ***************************
-       JOB_ID: 10141
-        LABEL: user_behavior
-DATABASE_NAME: mydatabase
- TRACKING_LOG: NULL
-         TYPE: BROKER
-1 row in set (0.02 sec)
-```
-:::
diff --git a/docs/en/reference/information_schema/loads.md b/docs/en/reference/information_schema/loads.md
deleted file mode 100644
index 9d81fdc6f70205..00000000000000
--- a/docs/en/reference/information_schema/loads.md
+++ /dev/null
@@ -1,35 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# loads
-
-`loads` provides the results of load jobs. This view is supported from StarRocks v3.1 onwards. Currently, you can only view the results of [Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) and [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md) jobs from this view.
-
-The following fields are provided in `loads`:
-
-| **Field**            | **Description**                                              |
-| -------------------- | ------------------------------------------------------------ |
-| JOB_ID               | The unique ID assigned by StarRocks to identify the load job. |
-| LABEL                | The label of the load job.                                   |
-| DATABASE_NAME        | The name of the database to which the destination StarRocks tables belong. |
-| STATE                | The state of the load job. Valid values:<ul><li>`PENDING`: The load job is created.</li><li>`QUEUEING`: The load job is in the queue waiting to be scheduled.</li><li>`LOADING`: The load job is running.</li><li>`PREPARED`: The transaction has been committed.</li><li>`FINISHED`: The load job succeeded.</li><li>`CANCELLED`: The load job failed.</li></ul>For more information, see the "Asynchronous loading" section in [Loading concepts](../../loading/loading_introduction/loading_concepts.md#asynchronous-loading). |
-| PROGRESS             | The progress of the ETL stage and LOADING stage of the load job. |
-| TYPE                 | The type of the load job. For Broker Load, the return value is `BROKER`. For INSERT, the return value is `INSERT`. |
-| PRIORITY             | The priority of the load job. Valid values: `HIGHEST`, `HIGH`, `NORMAL`, `LOW`, and `LOWEST`. |
-| SCAN_ROWS            | The number of data rows that are scanned.                    |
-| FILTERED_ROWS        | The number of data rows that are filtered out due to inadequate data quality. |
-| UNSELECTED_ROWS      | The number of data rows that are filtered out due to the conditions specified in the WHERE clause. |
-| SINK_ROWS            | The number of data rows that are loaded.                     |
-| ETL_INFO             | The ETL details of the load job. A non-empty value is returned only for Spark Load. For any other types of load jobs, an empty value is returned. |
-| TASK_INFO            | The task execution details of the load job, such as the `timeout` and `max_filter_ratio` settings. |
-| CREATE_TIME          | The time at which the load job was created. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
-| ETL_START_TIME       | The start time of the ETL stage of the load job. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
-| ETL_FINISH_TIME      | The end time of the ETL stage of the load job. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
-| LOAD_START_TIME      | The start time of the LOADING stage of the load job. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
-| LOAD_FINISH_TIME     | The end time of the LOADING stage of the load job. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
-| JOB_DETAILS          | The details about the data loaded, such as the number of bytes and the number of files. |
-| ERROR_MSG            | The error message of the load job. If the load job did not encounter any error, `NULL` is returned. |
-| TRACKING_URL         | The URL from which you can access the unqualified data row samples detected in the load job. You can use the `curl` or `wget` command to access the URL and obtain the unqualified data row samples. If no unqualified data is detected, `NULL` is returned. |
-| TRACKING_SQL         | The SQL statement that can be used to query the tracking log of the load job. A SQL statement is returned only when the load job involves unqualified data rows. If the load job does not involve any unqualified data rows, `NULL` is returned. |
-| REJECTED_RECORD_PATH | The path from which you can access all the unqualified data rows that are filtered out in the load job. The number of unqualified data rows logged is determined by the `log_rejected_record_num` parameter configured in the load job. You can use the `wget` command to access the path. If the load job does not involve any unqualified data rows, `NULL` is returned. |
diff --git a/docs/en/reference/information_schema/materialized_views.md b/docs/en/reference/information_schema/materialized_views.md
deleted file mode 100644
index 6a1a09172214c7..00000000000000
--- a/docs/en/reference/information_schema/materialized_views.md
+++ /dev/null
@@ -1,34 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# materialized_views
-
-`materialized_views` provides information about all materialized views.
-
-The following fields are provided in `materialized_views`:
-
-| **Field**                            | **Description**                                              |
-| ------------------------------------ | ------------------------------------------------------------ |
-| MATERIALIZED_VIEW_ID                 | ID of the materialized view.                                 |
-| TABLE_SCHEMA                         | Database in which the materialized view resides.             |
-| TABLE_NAME                           | Name of the materialized view.                               |
-| REFRESH_TYPE                         | Refresh type of the materialized view. Valid values: `ROLLUP` (synchronous materialized view), `ASYNC` (asynchronous refresh materialized view), and `MANUAL` (manual refresh materialized view). When the value is `ROLLUP`, all fields related to activation status and refresh are empry.  |
-| IS_ACTIVE                            | Indicates whether the materialized view is active. Inactive materialized views cannot be refreshed or queried. |
-| INACTIVE_REASON                      | The reason that the materialized view is inactive.           |
-| PARTITION_TYPE                       | Type of partitioning strategy for the materialized view.     |
-| TASK_ID                              | ID of the task responsible for refreshing the materialized view. |
-| TASK_NAME                            | Name of the task responsible for refreshing the materialized view. |
-| LAST_REFRESH_START_TIME              | Start time of the most recent refresh task.                  |
-| LAST_REFRESH_FINISHED_TIME           | End time of the most recent refresh task.                    |
-| LAST_REFRESH_DURATION                | Duration of the most recent refresh task.                    |
-| LAST_REFRESH_STATE                   | State of the most recent refresh task.                       |
-| LAST_REFRESH_FORCE_REFRESH           | Indicates whether the most recent refresh task was a force refresh. |
-| LAST_REFRESH_START_PARTITION         | Starting partition for the most recent refresh task.         |
-| LAST_REFRESH_END_PARTITION           | Ending partition for the most recent refresh task.           |
-| LAST_REFRESH_BASE_REFRESH_PARTITIONS | Base table partitions involved in the most recent refresh task. |
-| LAST_REFRESH_MV_REFRESH_PARTITIONS   | Materialized view partitions refreshed in the most recent refresh task. |
-| LAST_REFRESH_ERROR_CODE              | Error code of the most recent refresh task.                  |
-| LAST_REFRESH_ERROR_MESSAGE           | Error message of the most recent refresh task.               |
-| TABLE_ROWS                           | Number of data rows in the materialized view, based on approximate background statistics. |
-| MATERIALIZED_VIEW_DEFINITION         | SQL definition of the materialized view.                     |
diff --git a/docs/en/reference/information_schema/partitions.md b/docs/en/reference/information_schema/partitions.md
deleted file mode 100644
index 8ac174d66cd37e..00000000000000
--- a/docs/en/reference/information_schema/partitions.md
+++ /dev/null
@@ -1,42 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# partitions
-
-:::note
-
-This view does not apply to the available features in StarRocks.
-
-:::
-
-`partitions` provides information about table partitions.
-
-The following fields are provided in `partitions`:
-
-| **Field**                  | **Description**                                              |
-| -------------------------- | ------------------------------------------------------------ |
-| TABLE_CATALOG              | The name of the catalog to which the table belongs. This value is always `def`. |
-| TABLE_SCHEMA               | The name of the database to which the table belongs.         |
-| TABLE_NAME                 | The name of the table containing the partition.              |
-| PARTITION_NAME             | The name of the partition.                                   |
-| SUBPARTITION_NAME          | If the `PARTITIONS` table row represents a subpartition, the name of subpartition; otherwise `NULL`.For `NDB`: This value is always `NULL`. |
-| PARTITION_ORDINAL_POSITION | All partitions are indexed in the same order as they are defined, with `1` being the number assigned to the first partition. The indexing can change as partitions are added, dropped, and reorganized; the number shown is this column reflects the current order, taking into account any indexing changes. |
-| PARTITION_METHOD           | Valid values: `RANGE`, `LIST`, `HASH`, `LINEAR HASH`, `KEY`, or `LINEAR KEY`. |
-| SUBPARTITION_METHOD        | Valid values: `HASH`, `LINEAR HASH`, `KEY`, or `LINEAR KEY`  |
-| PARTITION_EXPRESSION       | The expression for the partitioning function used in the `CREATE TABLE` or `ALTER TABLE` statement that created the table's current partitioning scheme. |
-| SUBPARTITION_EXPRESSION    | This works in the same fashion for the subpartitioning expression that defines the subpartitioning for a table as `PARTITION_EXPRESSION` does for the partitioning expression used to define a table's partitioning. If the table has no subpartitions, this column is `NULL`. |
-| PARTITION_DESCRIPTION      | This column is used for RANGE and LIST partitions. For a `RANGE` partition, it contains the value set in the partition's `VALUES LESS THAN` clause, which can be either an integer or `MAXVALUE`. For a `LIST` partition, this column contains the values defined in the partition's `VALUES IN` clause, which is a list of comma-separated integer values.For partitions whose `PARTITION_METHOD` is other than `RANGE` or `LIST`, this column is always `NULL`. |
-| TABLE_ROWS                 | The number of table rows in the partition.                   |
-| AVG_ROW_LENGTH             | The average length of the rows stored in this partition or subpartition, in bytes. This is the same as `DATA_LENGTH` divided by `TABLE_ROWS`. |
-| DATA_LENGTH                | The total length of all rows stored in this partition or subpartition, in bytes; that is, the total number of bytes stored in the partition or subpartition. |
-| MAX_DATA_LENGTH            | The maximum number of bytes that can be stored in this partition or subpartition. |
-| INDEX_LENGTH               | The length of the index file for this partition or subpartition, in bytes. |
-| DATA_FREE                  | The number of bytes allocated to the partition or subpartition but not used. |
-| CREATE_TIME                | The time that the partition or subpartition was created.     |
-| UPDATE_TIME                | The time that the partition or subpartition was last modified. |
-| CHECK_TIME                 | The last time that the table to which this partition or subpartition belongs was checked. |
-| CHECKSUM                   | The checksum value, if any; otherwise `NULL`.                |
-| PARTITION_COMMENT          | The text of the comment, if the partition has one. If not, this value is empty. |
-| NODEGROUP                  | This is the nodegroup to which the partition belongs.        |
-| TABLESPACE_NAME            | The name of the tablespace to which the partition belongs.   |
diff --git a/docs/en/reference/information_schema/pipe_files.md b/docs/en/reference/information_schema/pipe_files.md
deleted file mode 100644
index f9def68d3b134b..00000000000000
--- a/docs/en/reference/information_schema/pipe_files.md
+++ /dev/null
@@ -1,24 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# pipe_files
-
-`pipe_files` provides the status of the data files to be loaded via a specified pipe. This view is supported from StarRocks v3.2 onwards.
-
-The following fields are provided in `pipe_files`:
-
-| **Field**        | **Description**                                              |
-| ---------------- | ------------------------------------------------------------ |
-| DATABASE_NAME    | The name of the database in which the pipe is stored.        |
-| PIPE_ID          | The unique ID of the pipe.                                   |
-| PIPE_NAME        | The name of the pipe.                                        |
-| FILE_NAME        | The name of the data file.                                   |
-| FILE_VERSION     | The digest of the data file.                                 |
-| FILE_SIZE        | The size of the data file. Unit: bytes.                      |
-| LAST_MODIFIED    | The last time when the data file was modified. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
-| LOAD_STATE       | The load status of the data file. Valid values: `UNLOADED`, `LOADING`, `FINISHED`, and `ERROR`. |
-| STAGED_TIME      | The date and time when the data file was first recorded by the pipe. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
-| START_LOAD_TIME  | The date and time when the loading of the data file began. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
-| FINISH_LOAD_TIME | The date and time when the loading of the data file finished. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
-| ERROR_MSG        | The details about the load error for the data file.          |
diff --git a/docs/en/reference/information_schema/pipes.md b/docs/en/reference/information_schema/pipes.md
deleted file mode 100644
index 5b08da8bab1e8d..00000000000000
--- a/docs/en/reference/information_schema/pipes.md
+++ /dev/null
@@ -1,26 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# pipes
-
-`pipes` provides information about all pipes stored in the current or specified database. This view is supported from StarRocks v3.2 onwards.
-
-:::note
-
-You can also use [SHOW PIPES](../../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md) to view the pipes stored in a specified database or in the current database in use. This command is also supported from v3.2 onwards.
-
-:::
-
-The following fields are provided in `pipes`:
-
-| **Field**     | **Description**                                              |
-| ------------- | ------------------------------------------------------------ |
-| DATABASE_NAME | The name of the database in which the pipe is stored.        |
-| PIPE_ID       | The unique ID of the pipe.                                   |
-| PIPE_NAME     | The name of the pipe.                                        |
-| TABLE_NAME    | The name of the destination table. Format: `<database_name>.<table_name>`. |
-| STATE         | The status of the pipe. Valid values: `RUNNING`, `FINISHED`, `SUSPENDED`, and `ERROR`. |
-| LOAD_STATUS   | The overall status of the data files to be loaded via the pipe, including the following sub-fields:<ul><li>`loadedFiles`: the number of data files that have been loaded.</li><li>`loadedBytes`: the volume of data that has been loaded, measured in bytes.</li><li>`loadingFiles`: the number of data files that are being loaded.</li></ul> |
-| LAST_ERROR    | The details about the last error that occurred during the pipe execution. Default value: `NULL`. |
-| CREATED_TIME  | The date and time when the pipe was created. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
diff --git a/docs/en/reference/information_schema/referential_constraints.md b/docs/en/reference/information_schema/referential_constraints.md
deleted file mode 100644
index b2200a464f5a7b..00000000000000
--- a/docs/en/reference/information_schema/referential_constraints.md
+++ /dev/null
@@ -1,29 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# referential_constraints
-
-:::note
-
-This view does not apply to the available features in StarRocks.
-
-:::
-
-`referential_constraints` contains all referential (foreign key) constraints.
-
-The following fields are provided in `referential_constraints`:
-
-| **Field**                 | **Description**                                              |
-| ------------------------- | ------------------------------------------------------------ |
-| CONSTRAINT_CATALOG        | The name of the catalog to which the constraint belongs. This value is always `def`. |
-| CONSTRAINT_SCHEMA         | The name of the database to which the constraint belongs.    |
-| CONSTRAINT_NAME           | The name of the constraint.                                  |
-| UNIQUE_CONSTRAINT_CATALOG | The name of the catalog containing the unique constraint that the constraint references. This value is always `def`. |
-| UNIQUE_CONSTRAINT_SCHEMA  | The name of the schema containing the unique constraint that the constraint references. |
-| UNIQUE_CONSTRAINT_NAME    | The name of the unique constraint that the constraint references. |
-| MATCH_OPTION              | The value of the constraint `MATCH` attribute. The only valid value at this time is `NONE`. |
-| UPDATE_RULE               | The value of the constraint `ON UPDATE` attribute. Valid values: `CASCADE`, `SET NULL`, `SET DEFAULT`, `RESTRICT`, and `NO ACTION`. |
-| DELETE_RULE               | The value of the constraint `ON DELETE` attribute. Valid values: `CASCADE`, `SET NULL`, `SET DEFAULT`, `RESTRICT`, and `NO ACTION`. |
-| TABLE_NAME                | The name of the table. This value is the same as in the `TABLE_CONSTRAINTS` table. |
-| REFERENCED_TABLE_NAME     | The name of the table referenced by the constraint.          |
diff --git a/docs/en/reference/information_schema/routines.md b/docs/en/reference/information_schema/routines.md
deleted file mode 100644
index bb291829dc98d2..00000000000000
--- a/docs/en/reference/information_schema/routines.md
+++ /dev/null
@@ -1,41 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# routines
-
-:::note
-
-This view does not apply to the available features in StarRocks.
-
-:::
-
-`routines` contains all stored routines (stored procedures and stored functions).
-
-The following fields are provided in `routine`:
-
-| **Field**            | **Description**                                              |
-| -------------------- | ------------------------------------------------------------ |
-| SPECIFIC_NAME        | The name of the routine.                                     |
-| ROUTINE_CATALOG      | The name of the catalog to which the routine belongs. This value is always `def`. |
-| ROUTINE_SCHEMA       | The name of the database to which the routine belongs.       |
-| ROUTINE_NAME         | The name of the routine.                                     |
-| ROUTINE_TYPE         | `PROCEDURE` for stored procedures, `FUNCTION` for stored functions. |
-| DTD_IDENTIFIER       | If the routine is a stored function, the return value data type. If the routine is a stored procedure, this value is empty. |
-| ROUTINE_BODY         | The language used for the routine definition. This value is always `SQL`. |
-| ROUTINE_DEFINITION   | The text of the SQL statement executed by the routine.       |
-| EXTERNAL_NAME        | This value is always `NULL`.                                 |
-| EXTERNAL_LANGUAGE    | The language of the stored routine.                          |
-| PARAMETER_STYLE      | This value is always `SQL`.                                  |
-| IS_DETERMINISTIC     | `YES` or `NO`, depending on whether the routine is defined with the `DETERMINISTIC` characteristic. |
-| SQL_DATA_ACCESS      | The data access characteristic for the routine. The value is one of `CONTAINS SQL`, `NO SQL`, `READS SQL DATA`, or `MODIFIES SQL DATA`. |
-| SQL_PATH             | This value is always `NULL`.                                 |
-| SECURITY_TYPE        | The routine `SQL SECURITY` characteristic. The value is one of `DEFINER` or `INVOKER`. |
-| CREATED              | The date and time when the routine was created. This is a `DATETIME` value. |
-| LAST_ALTERED         | The date and time when the routine was last modified. This is a `DATETIME` value. If the routine has not been modified since its creation, this value is the same as the `CREATED` value. |
-| SQL_MODE             | The SQL mode in effect when the routine was created or altered, and under which the routine executes. |
-| ROUTINE_COMMENT      | The text of the comment, if the routine has one. If not, this value is empty. |
-| DEFINER              | The user named in the `DEFINER` clause (often the user who created the routine). |
-| CHARACTER_SET_CLIENT |                                                              |
-| COLLATION_CONNECTION |                                                              |
-| DATABASE_COLLATION   | The collation of the database with which the routine is associated. |
\ No newline at end of file
diff --git a/docs/en/reference/information_schema/schema_privileges.md b/docs/en/reference/information_schema/schema_privileges.md
deleted file mode 100644
index b755d7d229e001..00000000000000
--- a/docs/en/reference/information_schema/schema_privileges.md
+++ /dev/null
@@ -1,23 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# schema_privileges
-
-:::note
-
-This view does not apply to the available features in StarRocks.
-
-:::
-
-`schema_privileges` provides information about database privileges.
-
-The following fields are provided in `schema_privileges`:
-
-| **Field**      | **Description**                                              |
-| -------------- | ------------------------------------------------------------ |
-| GRANTEE        | The name of the user to which the privilege is granted.      |
-| TABLE_CATALOG  | The name of the catalog to which the schema belongs. This value is always `def`. |
-| TABLE_SCHEMA   | The name of the schema.                                      |
-| PRIVILEGE_TYPE | The privilege granted. Each row lists a single privilege, so there is one row per schema privilege held by the grantee. |
-| IS_GRANTABLE   | `YES` if the user has the `GRANT OPTION` privilege, `NO` otherwise. The output does not list `GRANT OPTION` as a separate row with `PRIVILEGE_TYPE='GRANT OPTION'`. |
diff --git a/docs/en/reference/information_schema/schemata.md b/docs/en/reference/information_schema/schemata.md
deleted file mode 100644
index 36a6368ed40868..00000000000000
--- a/docs/en/reference/information_schema/schemata.md
+++ /dev/null
@@ -1,17 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# schemata
-
-`schemata` provides information about databases.
-
-The following fields are provided in `schemata`:
-
-| **Field**                  | **Description**                                              |
-| -------------------------- | ------------------------------------------------------------ |
-| CATALOG_NAME               | The name of the catalog to which the schema belongs. This value is always `NULL`. |
-| SCHEMA_NAME                | The name of the schema.                                      |
-| DEFAULT_CHARACTER_SET_NAME | The schema default character set.                            |
-| DEFAULT_COLLATION_NAME     | The schema default collation.                                |
-| SQL_PATH                   | This value is always `NULL`.                                 |
diff --git a/docs/en/reference/information_schema/session_variables.md b/docs/en/reference/information_schema/session_variables.md
deleted file mode 100644
index dcedced0495ac1..00000000000000
--- a/docs/en/reference/information_schema/session_variables.md
+++ /dev/null
@@ -1,14 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# session_variables
-
-`session_variables` provides information about session variables.
-
-The following fields are provided in `session_variables`:
-
-| **Field**      | **Description**        |
-| -------------- | ---------------------- |
-| VARIABLE_NAME  | Name of the variable.  |
-| VARIABLE_VALUE | Value of the variable. |
diff --git a/docs/en/reference/information_schema/statistics.md b/docs/en/reference/information_schema/statistics.md
deleted file mode 100644
index 58dc1d167e6bd9..00000000000000
--- a/docs/en/reference/information_schema/statistics.md
+++ /dev/null
@@ -1,34 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# statistics
-
-:::note
-
-This view does not apply to the available features in StarRocks.
-
-:::
-
-`statistics` provides information about table indexes.
-
-The following fields are provided in `statistics`:
-
-| **Field**     | **Description**                                              |
-| ------------- | ------------------------------------------------------------ |
-| TABLE_CATALOG | The name of the catalog to which the table containing the index belongs. This value is always `def`. |
-| TABLE_SCHEMA  | The name of the database to which the table containing the index belongs. |
-| TABLE_NAME    | The name of the table containing the index.                  |
-| NON_UNIQUE    | 0 if the index cannot contain duplicates, 1 if it can.       |
-| INDEX_SCHEMA  | The name of the database to which the index belongs.         |
-| INDEX_NAME    | The name of the index. If the index is the primary key, the name is always `PRIMARY`. |
-| SEQ_IN_INDEX  | The column sequence number in the index, starting with 1.    |
-| COLUMN_NAME   | The column name. See also the description for the `EXPRESSION` column. |
-| COLLATION     | How the column is sorted in the index. This can have values `A` (ascending), `D` (descending), or `NULL` (not sorted). |
-| CARDINALITY   | An estimate of the number of unique values in the index.     |
-| SUB_PART      | The index prefix. That is, the number of indexed characters if the column is only partly indexed, `NULL` if the entire column is indexed. |
-| PACKED        | Indicates how the key is packed. `NULL` if it is not.        |
-| NULLABLE      | Contains `YES` if the column may contain `NULL` values and `''` if not. |
-| INDEX_TYPE    | The index method used (`BTREE`, `FULLTEXT`, `HASH`, `RTREE`). |
-| COMMENT       | Information about the index not described in its own column, such as `disabled` if the index is disabled. |
-| INDEX_COMMENT | Any comment provided for the index with a `COMMENT` attribute when the index was created. |
diff --git a/docs/en/reference/information_schema/table_constraints.md b/docs/en/reference/information_schema/table_constraints.md
deleted file mode 100644
index 6c5d58caad49be..00000000000000
--- a/docs/en/reference/information_schema/table_constraints.md
+++ /dev/null
@@ -1,24 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# table_constraints
-
-:::note
-
-This view does not apply to the available features in StarRocks.
-
-:::
-
-`table_constraints` describes which tables have constraints.
-
-The following fields are provided in `table_constraints`:
-
-| **Field**          | **Description**                                              |
-| ------------------ | ------------------------------------------------------------ |
-| CONSTRAINT_CATALOG | The name of the catalog to which the constraint belongs. This value is always `def`. |
-| CONSTRAINT_SCHEMA  | The name of the database to which the constraint belongs.    |
-| CONSTRAINT_NAME    | The name of the constraint.                                  |
-| TABLE_SCHEMA       | The name of the database to which the table belongs.         |
-| TABLE_NAME         | The name of the table.                                       |
-| CONSTRAINT_TYPE    | The type of constraint.                                      |
diff --git a/docs/en/reference/information_schema/table_privileges.md b/docs/en/reference/information_schema/table_privileges.md
deleted file mode 100644
index 7514b40943ad56..00000000000000
--- a/docs/en/reference/information_schema/table_privileges.md
+++ /dev/null
@@ -1,24 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# table_privileges
-
-:::note
-
-This view does not apply to the available features in StarRocks.
-
-:::
-
-`table_privileges` provides information about table privileges.
-
-The following fields are provided in `table_privileges`:
-
-| **Field**      | **Description**                                              |
-| -------------- | ------------------------------------------------------------ |
-| GRANTEE        | The name of the user to which the privilege is granted.      |
-| TABLE_CATALOG  | The name of the catalog to which the table belongs. This value is always `def`. |
-| TABLE_SCHEMA   | The name of the database to which the table belongs.         |
-| TABLE_NAME     | The name of the table.                                       |
-| PRIVILEGE_TYPE | The privilege granted. The value can be any privilege that can be granted at the table level. |
-| IS_GRANTABLE   | `YES` if the user has the `GRANT OPTION` privilege, `NO` otherwise. The output does not list `GRANT OPTION` as a separate row with `PRIVILEGE_TYPE='GRANT OPTION'`. |
diff --git a/docs/en/reference/information_schema/tables.md b/docs/en/reference/information_schema/tables.md
deleted file mode 100644
index 21d93f759ee37a..00000000000000
--- a/docs/en/reference/information_schema/tables.md
+++ /dev/null
@@ -1,33 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# tables
-
-`tables` provides information about tables.
-
-The following fields are provided in `tables`:
-
-| **Field**       | **Description**                                              |
-| --------------- | ------------------------------------------------------------ |
-| TABLE_CATALOG   | Name of the catalog that stores the table.                   |
-| TABLE_SCHEMA    | Name of the database that stores the table.                  |
-| TABLE_NAME      | Name of the table.                                           |
-| TABLE_TYPE      | Type of the table. Valid values: `BASE TABLE` or `VIEW`.     |
-| ENGINE          | Engine type of the table. Valid values: `StarRocks`, `MySQL`, `MEMORY` or an empty string. |
-| VERSION         | Applies to a feature not available in StarRocks.             |
-| ROW_FORMAT      | Applies to a feature not available in StarRocks.             |
-| TABLE_ROWS      | Row count of the table.                                      |
-| AVG_ROW_LENGTH  | Average row length (size) of the table. It is equivalent to `DATA_LENGTH`/`TABLE_ROWS`. Unit: Byte. |
-| DATA_LENGTH     | Data length (size) of the table. Unit: Byte.                 |
-| MAX_DATA_LENGTH | Applies to a feature not available in StarRocks.             |
-| INDEX_LENGTH    | Applies to a feature not available in StarRocks.             |
-| DATA_FREE       | Applies to a feature not available in StarRocks.             |
-| AUTO_INCREMENT  | Applies to a feature not available in StarRocks.             |
-| CREATE_TIME     | The time when the table was created.                          |
-| UPDATE_TIME     | The last time when the table was updated.                     |
-| CHECK_TIME      | The last time when a consistency check was performed on the table. |
-| TABLE_COLLATION | The default collation of the table.                          |
-| CHECKSUM        | Applies to a feature not available in StarRocks.             |
-| CREATE_OPTIONS  | Applies to a feature not available in StarRocks.             |
-| TABLE_COMMENT   | Comment on the table.                                        |
diff --git a/docs/en/reference/information_schema/tables_config.md b/docs/en/reference/information_schema/tables_config.md
deleted file mode 100644
index 1ce62f3d8a8d23..00000000000000
--- a/docs/en/reference/information_schema/tables_config.md
+++ /dev/null
@@ -1,24 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# tables_config
-
-`tables_config` provides information about the configuration of tables.
-
-The following fields are provided in `tables_config`:
-
-| **Field**        | **Description**                                              |
-| ---------------- | ------------------------------------------------------------ |
-| TABLE_SCHEMA     | Name of the database that stores the table.                  |
-| TABLE_NAME       | Name of the table.                                           |
-| TABLE_ENGINE     | Engine type of the table.                                    |
-| TABLE_MODEL      | Data model of the table. Valid values: `DUP_KEYS`, `AGG_KEYS`, `UNQ_KEYS` or `PRI_KEYS`. |
-| PRIMARY_KEY      | Primary key of a Primary Key table or a Unique Key table. An empty string is returned if the table is not a Primary Key table or a Unique Key table. |
-| PARTITION_KEY    | Partitioning columns of the table.                       |
-| DISTRIBUTE_KEY   | Bucketing columns of the table.                          |
-| DISTRIBUTE_TYPE  | Data distribution method of the table.                   |
-| DISTRUBTE_BUCKET | Number of buckets in the table.                              |
-| SORT_KEY         | Sort keys of the table.                                      |
-| PROPERTIES       | Properties of the table.                                     |
-| TABLE_ID         | ID of the table.                                             |
diff --git a/docs/en/reference/information_schema/task_runs.md b/docs/en/reference/information_schema/task_runs.md
deleted file mode 100644
index 76ff2ceb60d35a..00000000000000
--- a/docs/en/reference/information_schema/task_runs.md
+++ /dev/null
@@ -1,24 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# task_runs
-
-`task_runs` provides information about the execution of asynchronous tasks.
-
-The following fields are provided in `task_runs`:
-
-| **Field**     | **Description**                                              |
-| ------------- | ------------------------------------------------------------ |
-| QUERY_ID      | ID of the query.                                             |
-| TASK_NAME     | Name of the task.                                            |
-| CREATE_TIME   | Time when the task was created.                               |
-| FINISH_TIME   | Time when the task finished.                                 |
-| STATE         | State of the task. Valid values: `PENDING`, `RUNNING`, `FAILED`, and `SUCCESS`. From v3.1.12, a new state `MERGED` is added especially for materialized view refresh tasks. When a new refresh task is submitted and the old task is still in the pending queue, these tasks will be merged and their priority level will be maintained.  |
-| DATABASE      | Database where the task belongs.                             |
-| DEFINITION    | SQL definition of the task.                                  |
-| EXPIRE_TIME   | Time when the task expires.                                  |
-| ERROR_CODE    | Error code of the task.                                      |
-| ERROR_MESSAGE | Error message of the task.                                   |
-| PROGRESS      | The progress of the task.                                    |
-| EXTRA_MESSAGE | Extra message for the task, for example, the partition information in an asynchronous materialized view creation task. |
diff --git a/docs/en/reference/information_schema/tasks.md b/docs/en/reference/information_schema/tasks.md
deleted file mode 100644
index b0a4a8eba8a0da..00000000000000
--- a/docs/en/reference/information_schema/tasks.md
+++ /dev/null
@@ -1,18 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# tasks
-
-`tasks` provides information about asynchronous tasks.
-
-The following fields are provided in `tasks`:
-
-| **Field**   | **Description**                                              |
-| ----------- | ------------------------------------------------------------ |
-| TASK_NAME   | Name of the task.                                            |
-| CREATE_TIME | Time when the task was created.                               |
-| SCHEDULE    | Task schedule. If the task is regularly triggered, this field displays `START xxx EVERY xxx`. |
-| DATABASE    | Database where the task belongs.                             |
-| DEFINITION  | SQL definition of the task.                                  |
-| EXPIRE_TIME | Time when the task expires.                                  |
diff --git a/docs/en/reference/information_schema/triggers.md b/docs/en/reference/information_schema/triggers.md
deleted file mode 100644
index 9981ccc2957023..00000000000000
--- a/docs/en/reference/information_schema/triggers.md
+++ /dev/null
@@ -1,40 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# triggers
-
-:::note
-
-This view does not apply to the available features in StarRocks.
-
-:::
-
-`triggers` provides information about triggers.
-
-The following fields are provided in `triggers`:
-
-| **Field**                  | **Description**                                              |
-| -------------------------- | ------------------------------------------------------------ |
-| TRIGGER_CATALOG            | The name of the catalog to which the trigger belongs. This value is always `def`. |
-| TRIGGER_SCHEMA             | The name of the database to which the trigger belongs.       |
-| TRIGGER_NAME               | The name of the trigger.                                     |
-| EVENT_MANIPULATION         | The trigger event. This is the type of operation on the associated table for which the trigger activates. The value is `INSERT` (a row was inserted), `DELETE` (a row was deleted), or `UPDATE` (a row was modified). |
-| EVENT_OBJECT_CATALOG       | Every trigger is associated with exactly one table. The catalog in which this table occurs. |
-| EVENT_OBJECT_SCHEMA        | Every trigger is associated with exactly one table. The database in which this table occurs. |
-| EVENT_OBJECT_TABLE         | The name of the table that the trigger is associated with.   |
-| ACTION_ORDER               | The ordinal position of the trigger's action within the list of triggers on the same table with the same `EVENT_MANIPULATION` and `ACTION_TIMING` values. |
-| ACTION_CONDITION           | This value is always `NULL`.                                 |
-| ACTION_STATEMENT           | The trigger body; that is, the statement executed when the trigger activates. This text uses UTF-8 encoding. |
-| ACTION_ORIENTATION         | This value is always `ROW`.                                  |
-| ACTION_TIMING              | Whether the trigger activates before or after the triggering event. The value is `BEFORE` or `AFTER`. |
-| ACTION_REFERENCE_OLD_TABLE | This value is always `NULL`.                                 |
-| ACTION_REFERENCE_NEW_TABLE | This value is always `NULL`.                                 |
-| ACTION_REFERENCE_OLD_ROW   | The old column identifiers. The value is always `OLD`.       |
-| ACTION_REFERENCE_NEW_ROW   | The new column identifiers. The value is always `NEW`.       |
-| CREATED                    | The date and time when the trigger was created. This is a `DATETIME(2)` value (with a fractional part in hundredths of seconds) for triggers. |
-| SQL_MODE                   | The SQL mode in effect when the trigger was created, and under which the trigger executes. |
-| DEFINER                    | The user named in the `DEFINER` clause (often the user who created the trigger). |
-| CHARACTER_SET_CLIENT       |                                                              |
-| COLLATION_CONNECTION       |                                                              |
-| DATABASE_COLLATION         | The collation of the database with which the trigger is associated. |
diff --git a/docs/en/reference/information_schema/user_privileges.md b/docs/en/reference/information_schema/user_privileges.md
deleted file mode 100644
index a5102a8c6eddbf..00000000000000
--- a/docs/en/reference/information_schema/user_privileges.md
+++ /dev/null
@@ -1,22 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# user_privileges
-
-:::note
-
-This view does not apply to the available features in StarRocks.
-
-:::
-
-`user_privileges` provides information about user privileges.
-
-The following fields are provided in `user_privileges`:
-
-| **Field**      | **Description**                                              |
-| -------------- | ------------------------------------------------------------ |
-| GRANTEE        | The name of the user to which the privilege is granted.      |
-| TABLE_CATALOG  | The name of the catalog. This value is always `def`.         |
-| PRIVILEGE_TYPE | The privilege granted. The value can be any privilege that can be granted at the global level. |
-| IS_GRANTABLE   | `YES` if the user has the `GRANT OPTION` privilege, `NO` otherwise. The output does not list `GRANT OPTION` as a separate row with `PRIVILEGE_TYPE='GRANT OPTION'`. |
diff --git a/docs/en/reference/information_schema/views.md b/docs/en/reference/information_schema/views.md
deleted file mode 100644
index 438eed0a6e8bcb..00000000000000
--- a/docs/en/reference/information_schema/views.md
+++ /dev/null
@@ -1,23 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# views
-
-`views` provides information about all user-defined views.
-
-The following fields are provided in `views`:
-
-| **Field**            | **Description**                                              |
-| -------------------- | ------------------------------------------------------------ |
-| TABLE_CATALOG        | The name of the catalog to which the view belongs. This value is always `def`. |
-| TABLE_SCHEMA         | The name of the database to which the view belongs.          |
-| TABLE_NAME           | The name of the view.                                        |
-| VIEW_DEFINITION      | The `SELECT` statement that provides the definition of the view. |
-| CHECK_OPTION         | The value of the `CHECK_OPTION` attribute. The value is one of `NONE`, `CASCADE`, or `LOCAL`. |
-| IS_UPDATABLE         | Whether the view is updatable. The flag is set to `YES` (true) if `UPDATE` and `DELETE` (and similar operations) are legal for the view. Otherwise, the flag is set to `NO` (false). If a view is not updatable, statements such `UPDATE`, `DELETE`, and `INSERT` are illegal and are rejected. |
-| DEFINER              | The user of the user who created the view.                   |
-| SECURITY_TYPE        | The view `SQL SECURITY` characteristic. The value is one of `DEFINER` or `INVOKER`. |
-| CHARACTER_SET_CLIENT |                                                              |
-| COLLATION_CONNECTION |                                                              |
-
diff --git a/docs/en/reference/overview-pages/http_api.mdx b/docs/en/reference/overview-pages/http_api.mdx
deleted file mode 100644
index 84b12bb5ef2bbb..00000000000000
--- a/docs/en/reference/overview-pages/http_api.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-#
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/reference/overview-pages/information_schema.md b/docs/en/reference/overview-pages/information_schema.md
deleted file mode 100644
index f0ea5f83398838..00000000000000
--- a/docs/en/reference/overview-pages/information_schema.md
+++ /dev/null
@@ -1,82 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# Information Schema
-
-The StarRocks Information Schema is a database within each StarRocks instance. Information Schema contains several read-only, system-defined views that store extensive metadata information of all objects that the StarRocks instance maintains. The StarRocks Information Schema is based on the SQL-92 ANSI Information Schema, but with the addition of views and functions that are specific to StarRocks.
-
-From v3.2.0, The StarRocks Information Schema supports manage metadata for external catalogs.
-
-## View metadata via Information Schema
-
-You can view the metadata information within a StarRocks instance by querying the content of views in Information Schema.
-
-The following example checks metadata information about a table named `table1` in StarRocks by querying the view `tables`.
-
-```Plain
-MySQL > SELECT * FROM information_schema.tables WHERE TABLE_NAME like 'table1'\G
-*************************** 1. row ***************************
-  TABLE_CATALOG: def
-   TABLE_SCHEMA: test_db
-     TABLE_NAME: table1
-     TABLE_TYPE: BASE TABLE
-         ENGINE: StarRocks
-        VERSION: NULL
-     ROW_FORMAT: 
-     TABLE_ROWS: 4
- AVG_ROW_LENGTH: 1657
-    DATA_LENGTH: 6630
-MAX_DATA_LENGTH: NULL
-   INDEX_LENGTH: NULL
-      DATA_FREE: NULL
- AUTO_INCREMENT: NULL
-    CREATE_TIME: 2023-06-13 11:37:00
-    UPDATE_TIME: 2023-06-13 11:38:06
-     CHECK_TIME: NULL
-TABLE_COLLATION: utf8_general_ci
-       CHECKSUM: NULL
- CREATE_OPTIONS: 
-  TABLE_COMMENT: 
-1 row in set (0.01 sec)
-```
-
-## Views in Information Schema
-
-The StarRocks Information Schema contains the following metadata views:
-
-| **View**                                                    | **Description**                                              |
-| ----------------------------------------------------------- | ------------------------------------------------------------ |
-| [be_bvars](../information_schema/be_bvars.md)                                       | `be_bvars` provides statistical information regarding bRPC.  |
-| [be_cloud_native_compactions](../information_schema/be_cloud_native_compactions.md) | `be_cloud_native_compactions` provides information on compaction transactions running on CNs (or BEs for v3.0) of a shared-data cluster. |
-| [be_compactions](../information_schema/be_compactions.md)                           | `be_compactions` provides statistical information on compaction tasks. |
-| [character_sets](../information_schema/character_sets.md)                           | `character_sets` identifies the character sets available.    |
-| [collations](../information_schema/collations.md)                                   | `collations` contains the collations available.              |
-| [column_privileges](../information_schema/column_privileges.md)                     | `column_privileges` identifies all privileges granted on columns to a currently enabled role or by a currently enabled role. |
-| [columns](../information_schema/columns.md)                                         | `columns` contains information about all table columns (or view columns). |
-| [engines](../information_schema/engines.md)                                         | `engines` provides information about storage engines.        |
-| [events](../information_schema/events.md)                                           | `events` provides information about Event Manager events.    |
-| [global_variables](../information_schema/global_variables.md)                       | `global_variables` provides information about global variables. |
-| [key_column_usage](../information_schema/key_column_usage.md)                       | `key_column_usage` identifies all columns that are restricted by some unique, primary key, or foreign key constraint. |
-| [load_tracking_logs](../information_schema/load_tracking_logs.md)                   | `load_tracking_logs` provides error information (if any) of load jobs. |
-| [loads](../information_schema/loads.md)                                             | `loads` provides the results of load jobs. Currently, you can only view the results of [Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) and [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md) jobs from this view. |
-| [materialized_views](../information_schema/materialized_views.md)                   | `materialized_views` provides information about all asynchronous materialized views. |
-| [partitions](../information_schema/partitions.md)                                   | `partitions` provides information about table partitions.    |
-| [pipe_files](../information_schema/pipe_files.md)                                   | `pipe_files` provides the status of the data files to be loaded via a specified pipe. |
-| [pipes](../information_schema/pipes.md)                                             | `pipes` provides information about all pipes stored in the current or specified database. |
-| [referential_constraints](../information_schema/referential_constraints.md)         | `referential_constraints` contains all referential (foreign key) constraints. |
-| [routines](../information_schema/routines.md)                                       | `routines` contains all stored routines (stored procedures and stored functions). |
-| [schema_privileges](../information_schema/schema_privileges.md)                     | `schema_privileges` provides information about database privileges. |
-| [schemata](../information_schema/schemata.md)                                       | `schemata` provides information about databases.             |
-| [session_variables](../information_schema/session_variables.md)                     | `session_variables` provides information about session variables. |
-| [statistics](../information_schema/statistics.md)                                   | `statistics` provides information about table indexes.       |
-| [table_constraints](../information_schema/table_constraints.md)                     | `table_constraints` describes which tables have constraints. |
-| [table_privileges](../information_schema/table_privileges.md)                       | `table_privileges` provides information about table privileges. |
-| [tables](../information_schema/tables.md)                                           | `tables` provides information about tables.                  |
-| [tables_config](../information_schema/tables_config.md)                             | `tables_config` provides information about the configuration of tables. |
-| [task_runs](../information_schema/task_runs.md)                                     | `task_runs` provides information about the execution of asynchronous tasks. |
-| [tasks](../information_schema/tasks.md)                                             | `tasks` provides information about asynchronous tasks.       |
-| [triggers](../information_schema/triggers.md)                                       | `triggers` provides information about triggers.              |
-| [user_privileges](../information_schema/user_privileges.md)                         | `user_privileges` provides information about user privileges. |
-| [views](../information_schema/views.md)                                             | `views` provides information about all user-defined views.   |
-
diff --git a/docs/en/reference/overview-pages/sys.md b/docs/en/reference/overview-pages/sys.md
deleted file mode 100644
index 8d31c66ca4f53a..00000000000000
--- a/docs/en/reference/overview-pages/sys.md
+++ /dev/null
@@ -1,69 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# System metadatabase
-
-This topic describes how to view the exclusive metadata of your StarRocks cluster via system-defined views.
-
-Each StarRocks cluster maintains a database `sys`, which contains several read-only, system-defined views. These metadata views provide a unified, easy-to-use interface that allows you to have an overall insight into the privilege structure, object dependencies, and other information within your StarRocks cluster.
-
-## View metadata information via `sys`
-
-You can view the exclusive metadata information within a StarRocks instance by querying the content of views in `sys`.
-
-The following example checks the privileges granted to user-defined roles by querying the view `grants_to_roles`.
-
-```Plain
-MySQL > SELECT * FROM sys.grants_to_roles LIMIT 5\G
-*************************** 1. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: db_test
-    OBJECT_NAME: tbl1
-    OBJECT_TYPE: TABLE
- PRIVILEGE_TYPE: SELECT, ALTER
-   IS_GRANTABLE: NO
-*************************** 2. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: db_test
-    OBJECT_NAME: tbl2
-    OBJECT_TYPE: TABLE
- PRIVILEGE_TYPE: SELECT
-   IS_GRANTABLE: YES
-*************************** 3. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: db_test
-    OBJECT_NAME: mv_test
-    OBJECT_TYPE: MATERIALIZED VIEW
- PRIVILEGE_TYPE: SELECT
-   IS_GRANTABLE: YES
-*************************** 4. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: NULL
-OBJECT_DATABASE: NULL
-    OBJECT_NAME: NULL
-    OBJECT_TYPE: SYSTEM
- PRIVILEGE_TYPE: CREATE RESOURCE GROUP
-   IS_GRANTABLE: NO
-```
-
-## Views in `sys`
-
-`sys` contains the following metadata views:
-
-| **View**             | **Description**                                                               |
-| -------------------- | ----------------------------------------------------------------------------- |
-| [grants_to_roles](../sys/grants_to_roles.md)         | Records the information of privileges that are granted to user-defined roles. |
-| [grants_to_users](../sys/grants_to_users.md)         | Records the information of privileges that are granted to users.              |
-| [role_edges](../sys/role_edges.md)                   | Records the grantees of roles.                                                |
-| [object_dependencies](../sys/object_dependencies.md) | Records the dependency relationship of asynchronous materialized views.       |
-
-:::note
-
-As per their scenarios of applications, views in `sys` are only accessible to some `admin` roles by default. Depending on your specific needs, you can grant other users the SELECT privilege on these views.
-
-:::
-
diff --git a/docs/en/reference/reference.mdx b/docs/en/reference/reference.mdx
deleted file mode 100644
index 035f8d58ffebb9..00000000000000
--- a/docs/en/reference/reference.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# Reference
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/reference/sys/grants_to_roles.md b/docs/en/reference/sys/grants_to_roles.md
deleted file mode 100644
index 14fc97164b50bd..00000000000000
--- a/docs/en/reference/sys/grants_to_roles.md
+++ /dev/null
@@ -1,63 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# grants_to_roles
-
-You can view the privileges granted to user-defined roles by querying the view `grants_to_roles`.
-
-:::note
-
-By default, only users or roles with the `user_admin` role can access this view. You can grant other users the SELECT privilege on this view using [GRANT](../../sql-reference/sql-statements/account-management/GRANT.md).
-
-:::
-
-The following fields are provided in `grants_to_roles`:
-
-| **Field**       | **Description**                                              |
-| --------------- | ------------------------------------------------------------ |
-| GRANTEE         | The role to whom this privilege is granted. Only user-defined roles will be listed in this view, and system-defined ones will not. |
-| OBJECT_CATALOG  | The catalog to which the object belongs. `NULL` is returned if the privilege is a SYSTEM, RESOURCE GROUP, RESOURCE, USER, or GLOBAL FUNCTION level privilege. |
-| OBJECT_DATABASE | The database to which the object belongs. `NULL` is returned if the privilege is a SYSTEM, RESOURCE GROUP, RESOURCE, USER, GLOBAL FUNCTION, or CATALOG level privilege. |
-| OBJECT_NAME     | The table to which the object belongs. `NULL` is returned if the privilege is a SYSTEM, RESOURCE GROUP, RESOURCE, USER, GLOBAL FUNCTION, CATALOG, or DATABASE level privilege. |
-| OBJECT_TYPE     | The type of the object.                                      |
-| PRIVILEGE_TYPE  | The type of the privilege. Different privileges on the same object will be merged and returned in a single row. As shown in the following example, `role_test` has the SELECT and ALTER privileges on `default_catalog.db_test.tbl1`. |
-| IS_GRANTABLE    | Whether the grantee has the grant option.                    |
-
-Example:
-
-```Plain
-MySQL > SELECT * FROM sys.grants_to_roles LIMIT 5\G
-*************************** 1. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: db_test
-    OBJECT_NAME: tbl1
-    OBJECT_TYPE: TABLE
- PRIVILEGE_TYPE: SELECT, ALTER
-   IS_GRANTABLE: NO
-*************************** 2. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: db_test
-    OBJECT_NAME: tbl2
-    OBJECT_TYPE: TABLE
- PRIVILEGE_TYPE: SELECT
-   IS_GRANTABLE: YES
-*************************** 3. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: db_test
-    OBJECT_NAME: mv_test
-    OBJECT_TYPE: MATERIALIZED VIEW
- PRIVILEGE_TYPE: SELECT
-   IS_GRANTABLE: YES
-*************************** 4. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: NULL
-OBJECT_DATABASE: NULL
-    OBJECT_NAME: NULL
-    OBJECT_TYPE: SYSTEM
- PRIVILEGE_TYPE: CREATE RESOURCE GROUP
-   IS_GRANTABLE: NO
-```
diff --git a/docs/en/reference/sys/grants_to_users.md b/docs/en/reference/sys/grants_to_users.md
deleted file mode 100644
index 4c13ec492279d3..00000000000000
--- a/docs/en/reference/sys/grants_to_users.md
+++ /dev/null
@@ -1,48 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# grants_to_users
-
-You can view the privileges granted to users by querying the view `grants_to_users`.
-
-:::note
-
-By default, only users or roles with the `user_admin` role can access this view. You can grant other users the SELECT privilege on this view using [GRANT](../../sql-reference/sql-statements/account-management/GRANT.md).
-
-:::
-
-The following fields are provided in `grants_to_users`:
-
-| **Field**       | **Description**                                              |
-| --------------- | ------------------------------------------------------------ |
-| GRANTEE         | The user to whom this privilege is granted.                  |
-| OBJECT_CATALOG  | The catalog to which the object belongs. `NULL` is returned if the privilege is a SYSTEM, RESOURCE GROUP, RESOURCE, USER, or GLOBAL FUNCTION level privilege. |
-| OBJECT_DATABASE | The database to which the object belongs. `NULL` is returned if the privilege is a SYSTEM, RESOURCE GROUP, RESOURCE, USER, GLOBAL FUNCTION, or CATALOG level privilege. |
-| OBJECT_NAME     | The table to which the object belongs. `NULL` is returned if the privilege is a SYSTEM, RESOURCE GROUP, RESOURCE, USER, GLOBAL FUNCTION, CATALOG, or DATABASE level privilege. |
-| OBJECT_TYPE     | The type of the object.                                      |
-| PRIVILEGE_TYPE  | The type of the privilege. Different privileges on the same object will be merged and returned in a single row. As shown in the following example, `'user1'@'%'` has the SELECT and DROP privileges on `default_catalog.db_test.view_test`. |
-| IS_GRANTABLE    | Whether the grantee has the grant option.                    |
-
-Example:
-
-```Plain
-MySQL > SELECT * FROM sys.grants_to_users LIMIT 5\G
-*************************** 1. row ***************************
-        GRANTEE: 'user1'@'%'
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: db_test
-    OBJECT_NAME: view_test
-    OBJECT_TYPE: VIEW
- PRIVILEGE_TYPE: SELECT, DROP
-   IS_GRANTABLE: NO
-*************************** 2. row ***************************
-        GRANTEE: 'user2'@'%'
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: simo
-    OBJECT_NAME: view_test
-    OBJECT_TYPE: VIEW
- PRIVILEGE_TYPE: SELECT
-   IS_GRANTABLE: NO
-```
-
diff --git a/docs/en/reference/sys/object_dependencies.md b/docs/en/reference/sys/object_dependencies.md
deleted file mode 100644
index e65a4338474362..00000000000000
--- a/docs/en/reference/sys/object_dependencies.md
+++ /dev/null
@@ -1,52 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# object_dependencies
-
-You can view the dependency relationship of asynchronous materialized views by querying the view `object_dependencies`.
-
-The following fields are provided in `object_dependencies`:
-
-| **Field**           | **Description**                                              |
-| ------------------- | ------------------------------------------------------------ |
-| object_id           | ID of the object.                                            |
-| object_name         | The name of the object.                                      |
-| object_database     | The Database where the object is located.                    |
-| object_catalog      | The catalog where the object is located. This field is always `default_catalog`. |
-| object_type         | The type of the object. This field is always `MATERIALIZED_VIEW`. |
-| ref_object_id       | ID of the referenced object.                                 |
-| ref_object_name     | The name of the referenced object.                           |
-| ref_object_database | The database where the referenced object is located.         |
-| ref_object_catalog  | The catalog where the referenced object is located.          |
-| ref_object_type     | The type of the referenced object.                           |
-
-Example:
-
-```Plain
-MySQL > SELECT * FROM sys.object_dependencies\G
-*************************** 1. row ***************************
-          object_id: 11115
-        object_name: mv2
-    object_database: test_db
-     object_catalog: default_catalog
-        object_type: MATERIALIZED_VIEW
-      ref_object_id: 11092
-    ref_object_name: mv1
-ref_object_database: test_db
- ref_object_catalog: default_catalog
-    ref_object_type: MATERIALIZED_VIEW
-*************************** 2. row ***************************
-          object_id: 11092
-        object_name: mv1
-    object_database: test_db
-     object_catalog: default_catalog
-        object_type: MATERIALIZED_VIEW
-      ref_object_id: 11074
-    ref_object_name: test_tbl
-ref_object_database: test_db
- ref_object_catalog: default_catalog
-    ref_object_type: OLAP
-```
-
-The above example indicates that the materialized view `mv1` is created based on the StarRocks internal table `test_tbl`, and the materialized view `mv2` is created based on the materialized view `mv1`.
diff --git a/docs/en/reference/sys/role_edges.md b/docs/en/reference/sys/role_edges.md
deleted file mode 100644
index 3cf951aed3d67b..00000000000000
--- a/docs/en/reference/sys/role_edges.md
+++ /dev/null
@@ -1,42 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# role_edges
-
-You can view the grantees of roles by querying the view `role_edges`.
-
-:::note
-
-By default, only users or roles with the `user_admin` role can access this view. You can grant other users the SELECT privilege on this view using [GRANT](../../sql-reference/sql-statements/account-management/GRANT.md).
-
-:::
-
-The following fields are provided in `role_edges`:
-
-| **Field** | **Description**                                              |
-| --------- | ------------------------------------------------------------ |
-| FROM_ROLE | The role that is granted. Multiple records with the same `FROM_ROLE` can be returned because a role can be granted to multiple roles and users. |
-| TO_ROLE   | The role to whom the current `FROM_ROLE` is granted. `NULL` is returned if the current `FROM_ROLE` is granted to a user. |
-| TO_USER   | The user to whom the current `FROM_ROLE` is granted. `NULL` is returned if the current `FROM_ROLE` is granted to a role. |
-
-Example:
-
-```Plain
-MySQL > SELECT * FROM sys.role_edges;
-+------------+------------+---------------+
-| FROM_ROLE  | TO_ROLE    | TO_USER       |
-+------------+------------+---------------+
-| dba_leader | director   | NULL          |
-| dba        | dba_leader | NULL          |
-| dba        | NULL       | 'aneesh'@'%'  |
-| dba        | NULL       | 'chelsea'@'%' |
-| dba_leader | NULL       | 'albert'@'%'  |
-| director   | NULL       | 'stan'@'%'    |
-| root       | NULL       | 'root'@'%'    |
-+------------+------------+---------------+
-```
-
-The following diagram illustrates the nesting relation of the granted roles in the preceding example:
-
-![role_edges](../../_assets/role_edges.png)
\ No newline at end of file
diff --git a/docs/en/reference/user_defined_variables.md b/docs/en/reference/user_defined_variables.md
deleted file mode 100644
index caeadb9cb7f170..00000000000000
--- a/docs/en/reference/user_defined_variables.md
+++ /dev/null
@@ -1,74 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# User-defined variables
-
-This topic describes how to declare and use user-defined variables.
-
-StarRocks 2.5 and later versions support user-defined variables. These variables are used to store specific values that are referenced in later SQL statements, thereby simplifying the writing of SQL statements and avoiding duplicate computation.
-
-## Usage notes
-
-- User-defined variables are variables, which can be created by the user and exist in the session. This means that no one can access user-defined variables that have been declared by another user, and when the session is closed these variables expire.
-- StarRocks does not support using the SHOW statement to display existing user-defined variables.
-- The following types of values cannot be declared as user-defined variables: BITMAP, HLL, and PERCENTILE. User-defined variables of the JSON type are converted to the STRING type for storage.
-- From v3.2.7 onwards, StarRocks supports the ARRAY type as a user-defined variable.
-
-## Declare user-defined variables
-
-### Syntax
-
-```Plain
-SET @var_name = expr [, ...];
-```
-
-> **NOTE**
->
-> - All variables must be preceded by a single at sign (@).
-> - Multiple variables can be declared in the same SET statement and need to be separated with commas (`,`).
-> - You can declare the same variable multiple times. The newly declared value overwrites the original value.
-> - If an undeclared variable is used, the value of the variable is `NULL` by default, and the NULL type is STRING.
-
-### Parameters
-
-| **Parameter** | **Required** | **Description**                                              |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| var_name      | Yes          | The name of the user-defined variable. The naming conventions are as follows:<ul><li>The name can contain letters, digits (0-9), and underscores (\_). </li><li>The name cannot exceed 64 characters in length.</li></ul>You can declare a string as a user-defined variable, such as @'my-var', @"my-var", and @\`my-var\`. User-defined variables of the STRING type can contain characters other than letters, digits, and underscores (_), such as periods (.). |
-| expr          | Yes          | The value of the user-defined variable. You can specify a number (such as 43) or a complex expression (such as the value returned by a SELECT statement) for this parameter. The data type of the variable is the same as the data type of the result returned by the expression. |
-
-### Examples
-
-Example 1: Declare a number as a user-defined variable.
-
-```SQL
-SET @var = 43;
-```
-
-Example 2: Declare the value returned by a SELECT query as a user-defined variable.
-
-```SQL
-SET @var = (SELECT SUM(v1) FROM test);
-```
-
-Example 3: Declare multiple user-defined variables in the same SET statement.
-
-```SQL
-SET @v1=1, @v2=2;
-```
-
-## Use user-defined variables in SQL
-
-- Simplifies the writing of SQL statements. For example, when you execute the following SELECT statement, StarRocks parses `@var` as `1`.
-
-  ```Plain
-  SET @var = 1;
-  SELECT @var, v1 from test;
-  ```
-
-- Avoids duplicate computation. For example, when you execute the following SELECT statement, StarRocks parses `@var` as the result returned by the `select sum(c1) from tbl` command.
-
-  ```Plain
-  SET @var = (select sum(c1) from tbl);
-  SELECT @var, v1 from test;
-  ```
diff --git a/docs/en/release_notes/release-1.19.md b/docs/en/release_notes/release-1.19.md
index 405bb84b5436a8..f75500b6b16628 100644
--- a/docs/en/release_notes/release-1.19.md
+++ b/docs/en/release_notes/release-1.19.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 1.19
diff --git a/docs/en/release_notes/release-2.0.md b/docs/en/release_notes/release-2.0.md
index c533804a264aae..376595e356f795 100644
--- a/docs/en/release_notes/release-2.0.md
+++ b/docs/en/release_notes/release-2.0.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 2.0
diff --git a/docs/en/release_notes/release-2.1.md b/docs/en/release_notes/release-2.1.md
index 5d2e3862ca555b..f9fa2c303ae858 100644
--- a/docs/en/release_notes/release-2.1.md
+++ b/docs/en/release_notes/release-2.1.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 2.1
diff --git a/docs/en/release_notes/release-2.2.md b/docs/en/release_notes/release-2.2.md
index 8c8a36c1b23c0a..3ca8653ff2dc46 100644
--- a/docs/en/release_notes/release-2.2.md
+++ b/docs/en/release_notes/release-2.2.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 2.2
diff --git a/docs/en/release_notes/release-2.3.md b/docs/en/release_notes/release-2.3.md
index 4027aa81a602bd..6404786e52f078 100644
--- a/docs/en/release_notes/release-2.3.md
+++ b/docs/en/release_notes/release-2.3.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 2.3
diff --git a/docs/en/release_notes/release-2.4.md b/docs/en/release_notes/release-2.4.md
index 53a435d272af5e..12ab2bae3b6e05 100644
--- a/docs/en/release_notes/release-2.4.md
+++ b/docs/en/release_notes/release-2.4.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 2.4
diff --git a/docs/en/release_notes/release-2.5.md b/docs/en/release_notes/release-2.5.md
index 45b02486d87565..3e59dce7853b7d 100644
--- a/docs/en/release_notes/release-2.5.md
+++ b/docs/en/release_notes/release-2.5.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 2.5
diff --git a/docs/en/release_notes/release-3.0.md b/docs/en/release_notes/release-3.0.md
index 45e160c5afbbf5..391dc130e11abc 100644
--- a/docs/en/release_notes/release-3.0.md
+++ b/docs/en/release_notes/release-3.0.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 3.0
diff --git a/docs/en/release_notes/release-3.1.md b/docs/en/release_notes/release-3.1.md
index 766344226e7259..c899111aad53cb 100644
--- a/docs/en/release_notes/release-3.1.md
+++ b/docs/en/release_notes/release-3.1.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 3.1
diff --git a/docs/en/release_notes/release-3.2.md b/docs/en/release_notes/release-3.2.md
index 6e9dda73e76d14..09165c657c5ba7 100644
--- a/docs/en/release_notes/release-3.2.md
+++ b/docs/en/release_notes/release-3.2.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 3.2
diff --git a/docs/en/release_notes/release-3.3.md b/docs/en/release_notes/release-3.3.md
index 3e8ac1664c4a65..9bd74136c80f55 100644
--- a/docs/en/release_notes/release-3.3.md
+++ b/docs/en/release_notes/release-3.3.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 3.3
diff --git a/docs/en/sql-reference/Error_code.md b/docs/en/sql-reference/Error_code.md
new file mode 100644
index 00000000000000..3eeb680dfb8e00
--- /dev/null
+++ b/docs/en/sql-reference/Error_code.md
@@ -0,0 +1,149 @@
+---
+displayed_sidebar: docs
+---
+
+# Error Codes
+
+This section describes the common error codes for query requests.
+
+|Serial number|Error code|Error message|
+| --- | --- | --- |
+|1005| Table creation failed. Returns a specific reason. |
+|1007| Cannot create a database with the same name.|
+|1008| Cannot delete non-existent database. |
+|1044| Cannot access unauthorized database. |
+|1045| Username and password do not match and therefore cannot access the system. |
+|1046|The target database is not specified. |
+|1047|An invalid command is specified. |
+|1049| An invalid database is specified. |
+|1050| A table with the same name already exists.|
+|1051| An invalid table is specified. |
+|1052| The specified column name is ambiguous and therefore the corresponding column cannot be uniquely identified. |
+|1053|An illegal data column was specified for the Semi-Join/Anti-Join query. |
+|1054|The specified column does not exist in the table.|
+|1058|The number of columns selected in the query statement does not match the number of columns in the query result. |
+|1060|There are duplicate column names. |
+|1064|There is no surviving BE node. |
+|1066|Duplicate table alias appears in the query statement. |
+|1094|Thread ID is invalid. |
+|1095|The non-owner of a thread cannot terminate the thread. |
+|1096|The query statement does not specify the table to be queried.|
+|1102|The database name is incorrect. |
+|1104|The table name is incorrect.|
+|1105|Other errors. |
+|1110|Duplicate columns were specified in the subquery.|
+|1111|Illegal use of aggregation function in `WHERE` clause|
+|1113| The set of columns in the new table cannot be empty. |
+|1115|Unsupported character sets are used.|
+|1130|An unauthorized IP address is used by the client. |
+|1132|No permission to change user password.|
+|1141| Specified entries don’t have privileges to revoke. |
+|1142|An unauthorized action was performed. |
+|1166| The data column name is incorrect. |
+|1193| System variable has invalid name |
+|1203| The number of active connections used exceeded the limit. |
+|1211| Not allowed to create new users. |
+|1227| The user has performed an out-of-authority operation. |
+|1228|Session variables cannot be modified by the `SET GLOBAL` command. |
+|1229|Global variables should be modified by the `SET GLOBAL` command. |
+|1230|Related system variables do not have default values. |
+|1231|An invalid value was set for a system variable.|
+|1232|A value of the wrong data type was set for a system variable. |
+|1248|No alias was set for an inline view.|
+|1251|The client does not support the user authentication protocol required by the server. |
+|1286|The storage engine is incorrectly configured. |
+|1298|The time zone is incorrectly configured.|
+|1347|The object does not match the expected type. |
+|1353|The specified column number in the `Select` clause of the view is not equal to the defined column number. |
+|1364|No default value is set for columns that do not allow NULL values. |
+|1372|The password is not long enough. |
+|1396|The performed operation failed.|
+|1471|The specified table is not allowed to insert data. |
+|1507|Delete nonexistent partition, and no condition is specified to only delete existing partitions. |
+|1508|All partitions should be deleted by a delete table operation. |
+|1517|There are duplicate partition names.|
+|1524|The specified plugin has not been loaded.|
+|1567|The name of the partition is incorrect. |
+|1621|The specified system variable is read-only. |
+|1735|The specified partition name does not exist in the table.|
+|1748|Data cannot be inserted into a table that does not have a partition.|
+|1749|The specified partition does not exist. |
+|5000|The specified table is not an OLAP table. |
+|5001|The specified storage path is invalid. |
+|5002|The name of the specified column should be displayed.|
+|5003|The dimension column should be preceded by the index column. |
+|5004|The table should contain at least 1 dimension column. |
+|5005|The cluster ID is invalid. |
+|5006|Invalid query plan. |
+|5007|Conflicting query plans. |
+|5008|The data insert is only available for data tables with partitions. |
+|5009|The `PARTITION` clause cannot be used to insert data into tables without partitions. |
+|5010|The number of columns in the table to be created is not equal to the number of columns in the `SELECT` clause. |
+|5011|Table reference could not be accessed. |
+|5012|The specified value is not a valid number. |
+|5013|The time unit is not supported. |
+|5014|The table status is not normal. |
+|5015|The partition status is not normal. |
+|5016| A data import job exists in the partition. |
+|5017| The specified column is not a dimension column. |
+|5018| The format of the value is invalid. |
+|5019| The data replica does not match the version. |
+|5021| The BE node is offline. |
+|5022| The number of partitions in a non-partitioned table is not 1|
+|5023| No action was specified in the statement used to modify the table or data. |
+|5024| Job execution timed out. |
+|5025| Data insertion failed. |
+|5026| An unsupported data type was used when creating a table via the `SELECT` statement. |
+|5027| The specified parameter was not set. |
+|5028| The specified cluster was not found. |
+|5030| The user does not have permission to access the cluster. |
+|5031| No parameter specified or invalid parameter. |
+|5032| The number of cluster instances was not specified. |
+|5034| A cluster with the same name already exists.|
+|5035| The number of cluster instances is incorrectly configured. |
+|5036|Insufficient BE nodes in the cluster. |
+|5037|All databases should be deleted before deleting the cluster.|
+|5038| The BE node with the specified ID does not exist in the cluster.|
+|5040|No cluster with the same name exists.|
+|5042|No permissions. |
+|5043|The number of instances should be greater than 0.|
+|5046|Source cluster does not exist.|
+|5047| Destination cluster does not exist. |
+|5048| Source database does not exist. |
+|5049| Destination database does not exist.|
+|5050| No cluster selected. |
+|5051| The source database should be associated with the destination database first. |
+|5052| Intra-cluster error: BE node information is incorrect. |
+|5053| There is no migration task from the source database to the destination database. |
+|5054| The specified database has been associated with the destination database, or data is being migrated. |
+|5055| Database associations or data migrations cannot be performed within the same cluster. |
+|5056| Database cannot be deleted: it is associated with another database or data is being migrated.|
+|5056| Database cannot be renamed: it is associated with another database or data is being migrated. |
+|5056| Insufficient BE nodes in the cluster. |
+|5056| The specified number of BE nodes already exists in the cluster. |
+|5059| There are BE nodes in the cluster that are in the offline state. |
+|5063| The type name is incorrect. |
+|5064| Generic error message.|
+|5063|The Colocate feature has been disabled by the administrator. |
+|5063|A colocate data table with the same name does not exist. |
+|5063|The Colocate table must be an OLAP table.|
+|5063|Colocate tables should have the same number of replicas. |
+|5063|Colocate tables should have the same number of split buckets. |
+|5063|Colocate tables should have the same number of partition columns. |
+|5063|Colocate tables should have the same data type of partitioned columns. |
+|5064|The specified table is not a colocate table.|
+|5065|The specified operation is invalid.|
+|5065|The specified time unit is illegal. The correct units are `DAY`, `WEEK`, and `MONTH`. |
+|5066|The start value of the dynamic partition should be less than 0.|
+|5066|The start value of the dynamic partition is not a valid number. |
+|5066|The end value of the dynamic partition should be greater than 0. |
+|5066|The end value of the dynamic partition is not a valid number. |
+|5066|The end value of the dynamic partition is null. |
+|5067|The bucket number of the dynamic partition should be greater than 0. |
+|5067|The bucket number of the dynamic partition is not a valid number. |
+|5066| The bucket number of the dynamic partition is empty. |
+|5068| Whether to allow dynamic partition where the value is not a valid boolean: true or false. |
+|5069| The name of the specified dynamic partition has an illegal prefix. |
+|5070| The specified operation is disabled. |
+|5071| The number of replicas of the dynamic partition should be greater than 0.|
+|5072| The number of replicas of the dynamic partition is not a valid number. |
diff --git a/docs/en/sql-reference/How_to_Write_Functions_Documentation.md b/docs/en/sql-reference/How_to_Write_Functions_Documentation.md
index 6c615b7e1b282e..8b3f06814b4fbf 100644
--- a/docs/en/sql-reference/How_to_Write_Functions_Documentation.md
+++ b/docs/en/sql-reference/How_to_Write_Functions_Documentation.md
@@ -1,5 +1,6 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
+unlisted: true
 ---
 
 # convert_tz
diff --git a/docs/en/sql-reference/SQL_command_template.md b/docs/en/sql-reference/SQL_command_template.md
index ca02ef9b1247d9..a630c1aca8eb8b 100644
--- a/docs/en/sql-reference/SQL_command_template.md
+++ b/docs/en/sql-reference/SQL_command_template.md
@@ -1,5 +1,6 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
+unlisted: true
 ---
 
 # SQL statement template
diff --git a/docs/en/sql-reference/System_limit.md b/docs/en/sql-reference/System_limit.md
new file mode 100644
index 00000000000000..bb313ed804fb97
--- /dev/null
+++ b/docs/en/sql-reference/System_limit.md
@@ -0,0 +1,38 @@
+---
+displayed_sidebar: docs
+---
+
+# System limits
+
+This topic describes the rules and limits that apply when you use StarRocks.
+
+- StarRocks uses the MySQL protocol for communication. You can connect to the StarRocks cluster via a MySQL client or JDBC. We recommend that you use a MySQL client whose version is 5.1 or later. Versions earlier than 5.1 do not support usernames that are longer than 16 characters.
+
+- Naming conventions for objects such as catalogs, databases, tables, views, partitions, columns, indexes, usernames, roles, repositories, resources, storage volumes, and pipes:
+
+  - The name can only consist of digits (0-9), letters (a-z or A-Z), and underscores (\_). **Usernames can be all digits.**
+  - The name can start with a letter or an underscore (\_).
+  - The name cannot exceed 64 characters in length, **among which:**
+    - Database name cannot exceed 256 characters.
+    - Table name and column name cannot exceed 1024 characters.
+    - Username cannot exceed 128 characters.
+  - Column name (column alias), partition name, and index name are **not** case-sensitive. Other names are **case-sensitive**.
+
+- Naming conventions for labels:
+  You can specify the label of a job when you load data. The label name can consist of digits (0-9), letters (a-z or A-Z), and underscores (\_), and cannot exceed 128 characters in length. The label name has no requirement for the starting character.
+
+- When you create a table, the key column cannot be of the FLOAT or DOUBLE type. You can use the DECIMAL type to represent decimals.
+
+- The maximum length of a VARCHAR value varies in different versions:
+
+  - In versions earlier than StarRocks 2.1, the length ranges from 1 to 65533 bytes.
+  - [Preview] In StarRocks 2.1 and later versions, the length ranges from 1 to 1048576 bytes. Maximum length of a VARCHAR value = Maximum row size (1048578 bytes) - Length prefix (2 bytes). The length prefix indicates the number of bytes in the value.
+  - The default length is 1 byte.
+
+- StarRocks supports only UTF-8 encoding, not GBK.
+
+- StarRocks does not support modifying column names in tables.
+
+- StarRocks does not support modifying the table types of an existing table. For example, you cannot change a Duplicate Key table to a Primary Key table. You must create a new table.
+
+- By default, a query can be nested with a maximum of 10,000 subqueries, which is controlled by the FE parameter `expr_children_limit`.
diff --git a/docs/en/sql-reference/System_variable.md b/docs/en/sql-reference/System_variable.md
new file mode 100644
index 00000000000000..e0dab84ff8482a
--- /dev/null
+++ b/docs/en/sql-reference/System_variable.md
@@ -0,0 +1,1047 @@
+---
+displayed_sidebar: docs
+---
+
+# System variables
+
+StarRocks provides many system variables that can be set and modified to suit your requirements. This section describes the variables supported by StarRocks. You can view the settings of these variables by running the [SHOW VARIABLES](sql-statements/cluster-management/config_vars/SHOW_VARIABLES.md) command on your MySQL client. You can also use the [SET](sql-statements/cluster-management/config_vars/SET.md) command to dynamically set or modify variables. You can make these variables take effect globally on the entire system, only in the current session, or only in a single query statement.
+
+The variables in StarRocks refer to the variable sets in MySQL, but **some variables are only compatible with the MySQL client protocol and do not function on the MySQL database**.
+
+> **NOTE**
+>
+> Any user has the privilege to run SHOW VARIABLES and make a variable take effect at session level. However, only users with the SYSTEM-level OPERATE privilege can make a variable take effect globally. Globally effective variables take effect on all the future sessions (excluding the current session).
+>
+> If you want to make a setting change for the current session and also make that setting change apply to all future sessions, you can make the change twice, once without the `GLOBAL` modifier and once with it. For example:
+>
+> ```SQL
+> SET query_mem_limit = 137438953472; -- Apply to the current session.
+> SET GLOBAL query_mem_limit = 137438953472; -- Apply to all future sessions.
+> ```
+
+## Variable hierarchy and types
+
+StarRocks supports three types (levels) of variables: global variables, session variables, and `SET_VAR` hints. Their hierarchical relationship is as follows:
+
+* Global variables take effect on global level, and can be overridden by session variables and `SET_VAR` hints.
+* Session variables take effect only on the current session, and can be overridden by `SET_VAR` hints.
+* `SET_VAR` hints take effect only on the current query statement.
+
+## View variables
+
+You can view all or some variables by using `SHOW VARIABLES [LIKE 'xxx']`. Example:
+
+```SQL
+-- Show all variables in the system.
+SHOW VARIABLES;
+
+-- Show variables that match a certain pattern.
+SHOW VARIABLES LIKE '%time_zone%';
+```
+
+## Set variables
+
+### Set variables globally or for a single session
+
+You can set variables to take effect **globally** or **only on the current session**. When set to global, the new value will be used for all the future sessions, while the current session still uses the original value. When set to "current session only", the variable will only take effect on the current session.
+
+A variable set by `SET <var_name> = xxx;` only takes effect for the current session. Example:
+
+```SQL
+SET query_mem_limit = 137438953472;
+
+SET forward_to_master = true;
+
+SET time_zone = "Asia/Shanghai";
+```
+
+A variable set by `SET GLOBAL <var_name> = xxx;` takes effect globally. Example:
+
+```SQL
+SET GLOBAL query_mem_limit = 137438953472;
+```
+
+The following variables only take effect globally. They cannot take effect for a single session, which means you must use `SET GLOBAL <var_name> = xxx;` for these variables. If you try to set such a variable for a single session (`SET <var_name> = xxx;`), an error is returned.
+
+* activate_all_roles_on_login
+* character_set_database
+* default_rowset_type
+* enable_query_queue_select
+* enable_query_queue_statistic
+* enable_query_queue_load
+* init_connect
+* lower_case_table_names
+* license
+* language
+* query_cache_size
+* query_queue_fresh_resource_usage_interval_ms
+* query_queue_concurrency_limit
+* query_queue_mem_used_pct_limit
+* query_queue_cpu_used_permille_limit
+* query_queue_pending_timeout_second
+* query_queue_max_queued_queries
+* system_time_zone
+* version_comment
+* version
+
+In addition, variable settings also support constant expressions, such as:
+
+```SQL
+SET query_mem_limit = 10 * 1024 * 1024 * 1024;
+```
+
+ ```SQL
+SET forward_to_master = concat('tr', 'u', 'e');
+```
+
+### Set variables in a single query statement
+
+In some scenarios, you may need to set variables specifically for certain queries. By using the `SET_VAR` hint, you can set session variables that will take effect only within a single statement.
+
+StarRocks supports using `SET_VAR` in the following statements;
+
+- SELECT
+- INSERT (from v3.1.12 and v3.2.0 onwards)
+- UPDATE (from v3.1.12 and v3.2.0 onwards)
+- DELETE (from v3.1.12 and v3.2.0 onwards)
+
+`SET_VAR` can only be placed after the above keywords and enclosed in `/*+...*/`.
+
+Example:
+
+```sql
+SELECT /*+ SET_VAR(query_mem_limit = 8589934592) */ name FROM people ORDER BY name;
+
+SELECT /*+ SET_VAR(query_timeout = 1) */ sleep(3);
+
+UPDATE /*+ SET_VAR(query_timeout=100) */ tbl SET c1 = 2 WHERE c1 = 1;
+
+DELETE /*+ SET_VAR(query_mem_limit = 8589934592) */
+FROM my_table PARTITION p1
+WHERE k1 = 3;
+
+INSERT /*+ SET_VAR(query_timeout = 10000000) */
+INTO insert_wiki_edit
+    SELECT * FROM FILES(
+        "path" = "s3://inserttest/parquet/insert_wiki_edit_append.parquet",
+        "format" = "parquet",
+        "aws.s3.access_key" = "XXXXXXXXXX",
+        "aws.s3.secret_key" = "YYYYYYYYYY",
+        "aws.s3.region" = "us-west-2"
+);
+```
+
+You can also set multiple variables in a single statement. Example:
+
+```sql
+SELECT /*+ SET_VAR
+  (
+  exec_mem_limit = 515396075520,
+  query_timeout=10000000,
+  batch_size=4096,
+  parallel_fragment_exec_instance_num=32
+  )
+  */ * FROM TABLE;
+```
+
+## Descriptions of variables
+
+The variables are described **in alphabetical order**. Variables with the `global` label can only take effect globally. Other variables can take effect either globally or for a single session.
+
+### activate_all_roles_on_login (global)
+
+* **Description**: Whether to enable all roles (including default roles and granted roles) for a StarRocks user when the user connects to the StarRocks cluster.
+  * If enabled (`true`), all roles of the user are activated at user login. This takes precedence over the roles set by [SET DEFAULT ROLE](sql-statements/account-management/SET_DEFAULT_ROLE.md).
+  * If disabled (`false`), the roles set by SET DEFAULT ROLE are activated.
+* **Default**: false
+* **Introduced in**: v3.0
+
+If you want to activate the roles assigned to you in a session, use the [SET ROLE](sql-statements/account-management/SET_DEFAULT_ROLE.md) command.
+
+### auto_increment_increment
+
+Used for MySQL client compatibility. No practical usage.
+
+### autocommit
+
+Used for MySQL client compatibility. No practical usage.
+
+### chunk_size
+
+* **Description**: Used to specify the number of rows of a single packet transmitted by each node during query execution. The default is 4096, i.e., every 4096 rows of data generated by the source node is packaged and sent to the destination node. A larger number of rows will improve the query throughput in large data volume scenarios, but may increase the query latency in small data volume scenarios. Also, it may increase the memory overhead of the query. We recommend to set `batch_size` between 1024 to 4096.
+* **Default**: 4096
+
+### big_query_profile_threshold
+
+* **Description**: Used to set the threshold for big queries. When the session variable `enable_profile` is set to `false` and the amount of time taken by a query exceeds the threshold specified by the variable `big_query_profile_threshold`, a profile is generated for that query.
+
+  Note: In versions v3.1.5 to v3.1.7, as well as v3.2.0 to v3.2.2, we introduced the `big_query_profile_second_threshold` for setting the threshold for big queries. In versions v3.1.8, v3.2.3, and subsequent releases, this parameter has been replaced by `big_query_profile_threshold` to offer more flexible configuration options.
+* **Default**: 0
+* **Unit**: Second
+* **Data type**: String
+* **Introduced in**: v3.1
+
+### catalog
+
+* **Description**: Used to specify the catalog to which the session belongs.
+* **Default**: default_catalog
+* **Data type**: String
+* **Introduced in**: v3.2.4
+
+### cbo_decimal_cast_string_strict
+
+* **Description**: Controls how the CBO converts data from the DECIMAL type to the STRING type. If this variable is set to `true`, the logic built in v2.5.x and later versions prevails and the system implements strict conversion (namely, the system truncates the generated string and fills 0s based on the scale length). If this variable is set to `false`, the logic built in versions earlier than v2.5.x prevails and the system processes all valid digits to generate a string.
+* **Default**: true
+* **Introduced in**: v2.5.14
+
+### cbo_enable_low_cardinality_optimize
+
+* **Description**: Whether to enable low cardinality optimization. After this feature is enabled, the performance of querying STRING columns improves by about three times.
+* **Default**: true
+
+### cbo_eq_base_type
+
+* **Description**: Specifies the data type used for data comparison between DECIMAL data and STRING data. The default value is `VARCHAR`, and DECIMAL is also a valid value. **This variable takes effect only for `=` and `!=` comparison.**
+* **Data type**: String
+* **Introduced in**: v2.5.14
+
+### cbo_materialized_view_rewrite_related_mvs_limit
+
+* **Description**: Specifies the maximum number of candidate materialized views allowed during query planning.
+* **Default**: 64
+* **Introduced in**: v3.1.9, v3.2.5
+
+### cbo_prune_subfield
+
+* **Description**: Whether to enable JSON subfield pruning. This variable must be used with the BE dynamic parameter `enable_json_flat`. Otherwise, it may degrade JSON data query performance.
+* **Default**: false
+* **Data type**: Int
+* **Introduced in**: v3.3.0
+
+### enable_sync_materialized_view_rewrite
+
+* **Description**: Whether to enable query rewrite based on synchronous materialized views.
+* **Default**: true
+* **Introduced in**: v3.1.11, v3.2.5
+
+### query_including_mv_names
+
+* **Description**: Specifies the name of the asynchronous materialized views to include in query execution. You can use this variable to limit the number of candidate materialized views and improve the query rewrite performance in the optimizer. This item takes effect prior to `query_excluding_mv_names`.
+* **Default**: empty
+* **Data type**: String
+* **Introduced in**: v3.1.11, v3.2.5
+
+### query_excluding_mv_names(
+
+* **Description**: Specifies the name of the asynchronous materialized views to exclude from query execution. You can use this variable to limit the number of candidate materialized views and reduce the time of query rewrite in the optimizer. `query_including_mv_names` takes effect prior to this item.
+* **Default**: empty
+* **Data type**: String
+* **Introduced in**: v3.1.11, v3.2.5
+
+### optimizer_materialized_view_timelimit
+
+* **Description**: Specifies the maximum time that one materialized view rewrite rule can consume. When the threshold is reached, this rule will not be used for query rewrite.
+* **Default**: 1000
+* **Unit**: ms
+* **Introduced in**: v3.1.9, v3.2.5
+
+### enable_materialized_view_agg_pushdown_rewrite
+
+* **Description**: Whether to enable aggregation pushdown for materialized view query rewrite. If it is set to `true`, aggregate functions will be pushed down to Scan Operator during query execution and rewritten by the materialized view before the Join Operator is executed. This will relieve the data expansion caused by Join and thereby improve the query performance. For detailed information about the scenarios and limitations of this feature, see [Aggregation pushdown](../using_starrocks/query_rewrite_with_materialized_views.md#aggregation-pushdown).
+* **Default**: false
+* **Introduced in**: v3.3.0
+
+### enable_materialized_view_text_match_rewrite
+
+* **Description**: Whether to enable text-based materialized view rewrite. When this item is set to true, the optimizer will compare the query with the existing materialized views. A query will be rewritten if the abstract syntax tree of the materialized view's definition matches that of the query or its sub-query.
+* **Default**: true
+* **Introduced in**: v3.2.5, v3.3.0
+
+### materialized_view_subuqery_text_match_max_count
+
+* **Description**: Specifies the maximum number of times that the system checks whether a query's sub-query matches the materialized views' definition.
+* **Default**: 4
+* **Introduced in**: v3.2.5, v3.3.0
+
+### enable_force_rule_based_mv_rewrite
+
+* **Description**: Whether to enable query rewrite for queries against multiple tables in the optimizer's rule-based optimization phase. Enabling this feature will improve the robustness of the query rewrite. However, it will also increase the time consumption if the query misses the materialized view.
+* **Default**: true
+* **Introduced in**: v3.3.0
+
+### enable_view_based_mv_rewrite
+
+* **Description**: Whether to enable query rewrite for logical view-based materialized views. If this item is set to `true`, the logical view is used as a unified node to rewrite the queries against itself for better performance. If this item is set to `false`, the system transcribes the queries against logical views into queries against physical tables or materialized views and then rewrites them.
+* **Default**: false
+* **Introduced in**: v3.1.9, v3.2.5, v3.3.0
+
+### enable_materialized_view_union_rewrite
+
+* **Description**: Whether to enable materialized view union rewrite. If this item is set to `true`, the system seeks to compensate the predicates using UNION ALL when the predicates in the materialized view cannot satisfy the query's predicates.
+* **Default**: true
+* **Introduced in**: v2.5.20, v3.1.9, v3.2.7, v3.3.0
+
+### enable_materialized_view_plan_cache
+
+* **Description**: Whether to enable materialized view plan cache, which can optimize the automatic rewrite performance of materialized views. Setting it to `true` indicates enabling it.
+* **Default**: true
+* **Introduced in**: v2.5.13, v3.0.7, v3.1.4, v3.2.0, v3.3.0
+
+### follower_query_forward_mode
+
+* **Description**: Specifies to which FE nodes the query statements are routed.
+
+  * Valid values:
+
+    * `default`: Routes the query statement to the Leader FE or Follower FEs, depending on the Follower's replay progress. If the Follower FE nodes have not completed replay progress, queries will be routed to the Leader FE node. If the replay progress is complete, queries will be preferentially routed to the Follower FE node.
+    * `leader`: Routes the query statement to the Leader FE.
+    * `follower`: Routes the query statement to Follower FE.
+
+* **Default**: default
+* **Data type**: String
+* **Introduced in**: v2.5.20, v3.1.9, v3.2.7, v3.3.0
+
+### character_set_database (global)
+
+* **Data type**: StringThe character set supported by StarRocks. Only UTF8 (`utf8`) is supported.
+* **Default**: utf8
+* **Data type**: String
+
+### connector_io_tasks_per_scan_operator
+
+* **Description**: The maximum number of concurrent I/O tasks that can be issued by a scan operator during external table queries. The value is an integer. Currently, StarRocks can adaptively adjust the number of concurrent I/O tasks when querying external tables. This feature is controlled by the variable `enable_connector_adaptive_io_tasks`, which is enabled by default.
+* **Default**: 16
+* **Data type**: Int
+* **Introduced in**: v2.5
+
+### connector_sink_compression_codec
+
+* **Description**: Specifies the compression algorithm used for writing data into Hive tables or Iceberg tables, or exporting data with Files().
+* **Valid values**: `uncompressed`, `snappy`, `lz4`, `zstd`, and `gzip`.
+* **Default**: uncompressed
+* **Data type**: String
+* **Introduced in**: v3.2.3
+
+### connector_sink_target_max_file_size
+
+* **Description**: Specifies the maximum size of target file for writing data into Hive tables or Iceberg tables, or exporting data with Files(). The limit is not exact and is applied on a best-effort basis.
+* **Unit**: Bytes
+* **Default**: 1073741824
+* **Data type**: Long
+* **Introduced in**: v3.3.0
+
+### count_distinct_column_buckets
+
+* **Description**: The number of buckets for the COUNT DISTINCT column in a group-by-count-distinct query. This variable takes effect only when `enable_distinct_column_bucketization` is set to `true`.
+* **Default**: 1024
+* **Introduced in**: v2.5
+
+### default_rowset_type (global)
+
+Used to set the default storage format used by the storage engine of the computing node. The currently supported storage formats are `alpha` and `beta`.
+
+### default_table_compression
+
+* **Description**: The default compression algorithm for table storage. Supported compression algorithms are `snappy, lz4, zlib, zstd`.
+
+  Note that if you specified the `compression` property in a CREATE TABLE statement, the compression algorithm specified by `compression` takes effect.
+
+* **Default**: lz4_frame
+* **Introduced in**: v3.0
+
+### disable_colocate_join
+
+* **Description**: Used to control whether the Colocation Join is enabled. The default value is `false`, meaning the feature is enabled. When this feature is disabled, query planning will not attempt to execute Colocation Join.
+* **Default**: false
+
+### disable_streaming_preaggregations
+
+Used to enable the streaming pre-aggregations. The default value is `false`, meaning it is enabled.
+
+### div_precision_increment
+
+Used for MySQL client compatibility. No practical usage.
+
+<!--
+### enable_collect_table_level_scan_stats (Invisible to users)
+
+This variable is introduced to solve compatibility issues.
+
+Default value: `true`.
+-->
+
+### enable_datacache_async_populate_mode
+
+* **Description**: Whether to populate the data cache in asynchronous mode. By default, the system uses the synchronous mode to populate data cache, that is, populating the cache while querying data.
+* **Default**: false
+* **Introduced in**: v3.2.7
+
+### enable_connector_adaptive_io_tasks
+
+* **Description**: Whether to adaptively adjust the number of concurrent I/O tasks when querying external tables. Default value is `true`. If this feature is not enabled, you can manually set the number of concurrent I/O tasks using the variable `connector_io_tasks_per_scan_operator`.
+* **Default**: true
+* **Introduced in**: v2.5
+
+### enable_distinct_column_bucketization
+
+* **Description**: Whether to enable bucketization for the COUNT DISTINCT colum in a group-by-count-distinct query. Use the `select a, count(distinct b) from t group by a;` query as an example. If the GROUP BY colum `a` is a low-cardinality column and the COUNT DISTINCT column `b` is a high-cardinality column which has severe data skew, performance bottleneck will occur. In this situation, you can split data in the COUNT DISTINCT column into multiple buckets to balance data and prevent data skew. You must use this variable with the variable `count_distinct_column_buckets`.
+
+  You can also enable bucketization for the COUNT DISTINCT column by adding the `skew` hint to your query, for example, `select a,count(distinct [skew] b) from t group by a;`.
+
+* **Default**: false, which means this feature is disabled.
+* **Introduced in**: v2.5
+
+### enable_gin_filter
+
+* **Description**: Whether to utilize the [fulltext inverted index](../table_design/indexes/inverted_index.md) during queries.
+* **Default**: true
+* **Introduced in**: v3.3.0
+
+### enable_group_level_query_queue (global)
+
+* **Description**: Whether to enable resource group-level [query queue](../administration/management/resource_management/query_queues.md).
+* **Default**: false, which means this feature is disabled.
+* **Introduced in**: v3.1.4
+
+### enable_iceberg_metadata_cache
+
+* **Description**: Whether to cache pointers and partition names for Iceberg tables. From v3.2.1 to v3.2.3, this parameter is set to `true` by default, regardless of what metastore service is used. In v3.2.4 and later, if the Iceberg cluster uses AWS Glue as metastore, this parameter still defaults to `true`. However, if the Iceberg cluster uses other metastore service such as Hive metastore, this parameter defaults to `false`.
+* **Introduced in**: v3.2.1
+
+### enable_insert_strict
+
+Used to enable the strict mode when loading data using the INSERT statement. The default value is `true`, indicating the strict mode is enabled by default. For more information, see [Strict mode](../loading/load_concept/strict_mode.md).
+
+### enable_materialized_view_for_insert
+
+* **Description**: Whether to allow StarRocks to rewrite queries in INSERT INTO SELECT statements.
+* **Default**: false, which means Query Rewrite in such scenarios is disabled by default.
+* **Introduced in**: v2.5.18, v3.0.9, v3.1.7, v3.2.2
+
+### enable_rule_based_materialized_view_rewrite
+
+* **Description**: Controls whether to enable rule-based materialized view query rewrite. This variable is mainly used in single-table query rewrite. * **Default**: true
+* **Data type**: Boolean
+* **Introduced in**: v2.5
+
+### enable_short_circuit
+
+* **Description**: Whether to enable short circuiting for queries. Default: `false`. If it is set to `true`, when the query meets the criteria (to evaluate whether the query is a point query): the conditional columns in the WHERE clause include all primary key columns, and the operators in the WHERE clause are `=` or `IN`, the query takes the short circuit.
+* **Default**: false
+* **Introduced in**: v3.2.3
+
+### enable_spill
+
+* **Description**: Whether to enable intermediate result spilling. Default: `false`. If it is set to `true`, StarRocks spills the intermediate results to disk to reduce the memory usage when processing aggregate, sort, or join operators in queries.
+* **Default**: false
+* **Introduced in**: v3.0
+
+### enable_spill_to_remote_storage
+
+* **Description**: Whether to enable intermediate result spilling to object storage. If it is set to `true`, StarRocks spills the intermediate results to the storage volume specified in `spill_storage_volume` after the capacity limit of the local disk is reached. For more information, see [Spill to object storage](../administration/management/resource_management/spill_to_disk.md#spill-intermediate-result-to-object-storage).
+* **Default**: false
+* **Introduced in**: v3.3.0
+
+### enable_strict_order_by
+
+* **Description**: Used to check whether the column name referenced in ORDER BY is ambiguous. When this variable is set to the default value `TRUE`, an error is reported for such a query pattern: Duplicate alias is used in different expressions of the query and this alias is also a sorting field in ORDER BY, for example, `select distinct t1.* from tbl1 t1 order by t1.k1;`. The logic is the same as that in v2.3 and earlier. When this variable is set to `FALSE`, a loose deduplication mechanism is used, which processes such queries as valid SQL queries.
+* **Default**: true
+* **Introduced in**: v2.5.18 and v3.1.7
+
+### enable_profile
+
+* **Description**: Specifies whether to send the profile of a query for analysis. The default value is `false`, which means no profile is required.
+
+  By default, a profile is sent to the FE only when a query error occurs in the BE. Profile sending causes network overhead and therefore affects high concurrency.
+
+  If you need to analyze the profile of a query, you can set this variable to `true`. After the query is completed, the profile can be viewed on the web page of the currently connected FE (address: `fe_host:fe_http_port/query`). This page displays the profiles of the latest 100 queries with `enable_profile` turned on.
+
+* **Default**: false
+
+### enable_query_queue_load (global)
+
+* **Description**: Boolean value to enable query queues for loading tasks.
+* **Default**: false
+
+### enable_query_queue_select (global)
+
+* **Description**: Whether to enable query queues for SELECT queries.
+* **Default**: false
+
+### enable_query_queue_statistic (global)
+
+* **Description**: Whether to enable query queues for statistics queries.
+* **Default**: false
+
+### enable_query_tablet_affinity
+
+* **Description**: Boolean value to control whether to direct multiple queries against the same tablet to a fixed replica.
+
+  In scenarios where the table to query has a large number of tablets, this feature significantly improves query performance because the meta information and data of the tablet can be cached in memory more quickly.
+
+  However, if there are some hotspot tablets, this feature may degrade the query performance because it directs the queries to the same BE, making it unable to fully use the resources of multiple BEs in high-concurrency scenarios.
+
+* **Default**: false, which means the system selects a replica for each query.
+* **Introduced in**: v2.5.6, v3.0.8, v3.1.4, and v3.2.0.
+
+
+### enable_lake_tablet_internal_parallel
+
+* **Description**: Whether to enable Parallel Scan for Cloud-native tables in a shared-data cluster.
+* **Default**: false
+* **Data type**: Boolean
+* **Introduced in**: v3.3.0
+
+### tablet_internal_parallel_mode
+
+* **Description**: Internal Parallel Scan strategy of tablets. Valid Values:
+  * `auto`: When the number of Tablets to be scanned on BE or CN nodes is less than the Degree of Parallelism (DOP), the system automatically determines whether Parallel Scan is needed based on the estimated size of the Tablets.
+  * `force_split`: Forces the splitting of Tablets and performs Parallel Scan.
+* **Default**: auto
+* **Data type**: String
+* **Introduced in**: v2.5.0
+
+### enable_scan_datacache
+
+* **Description**: Specifies whether to enable the Data Cache feature. After this feature is enabled, StarRocks caches hot data read from external storage systems into blocks, which accelerates queries and analysis. For more information, see [Data Cache](../data_source/data_cache.md). In versions prior to 3.2, this variable was named as `enable_scan_block_cache`.
+* **Default**: false
+* **Introduced in**: v2.5
+
+### populate_datacache_mode
+
+* **Description**: Specifies the population behavior of Data Cache when reading data blocks from external storage systems. Valid values:
+  * `auto` (default): the system automatically caches data selectively based on the population rule.
+  * `always`: Always cache the data.
+  * `never`: Never cache the data.
+* **Default**: auto
+* **Introduced in**: v3.3.2
+
+### enable_datacache_io_adaptor
+
+* **Description**: Whether to enable the Data Cache I/O Adaptor. Setting this to `true` enables the feature. When this feature is enabled, the system automatically routes some cache requests to remote storage when the disk I/O load is high, reducing disk pressure.
+* **Default**: true
+* **Introduced in**: v3.3.0
+
+### enable_file_metacache
+
+* **Description**: Whether to enable metadata cache for files in remote storage (Footer Cache). Setting this to `true` enables the feature. Footer Cache directly caches the parsed Footer object in memory. When the same file's Footer is accessed in subsequent queries, the object descriptor can be obtained directly from the cache, avoiding repetitive parsing. This feature uses the memory module of the Data Cache for data caching. Therefore, you must ensure that the BE parameter `datacache_enable` is set to `true` and configure a reasonable value for `datacache_mem_size`.
+* **Default**: true
+* **Introduced in**: v3.3.0
+
+### enable_tablet_internal_parallel
+
+* **Description**: Whether to enable adaptive parallel scanning of tablets. After this feature is enabled, multiple threads can be used to scan one tablet by segment, increasing the scan concurrency.
+* **Default**: true
+* **Introduced in**: v2.3
+
+### enable_query_cache
+
+* **Description**: Specifies whether to enable the Query Cache feature. Valid values: true and false. `true` specifies to enable this feature, and `false` specifies to disable this feature. When this feature is enabled, it works only for queries that meet the conditions specified in the application scenarios of [Query Cache](../using_starrocks/query_cache.md#application-scenarios).
+* **Default**: false
+* **Introduced in**: v2.5
+
+### enable_adaptive_sink_dop
+
+* **Description**: Specifies whether to enable adaptive parallelism for data loading. After this feature is enabled, the system automatically sets load parallelism for INSERT INTO and Broker Load jobs, which is equivalent to the mechanism of `pipeline_dop`. For a newly deployed v2.5 StarRocks cluster, the value is `true` by default. For a v2.5 cluster upgraded from v2.4, the value is `false`.
+* **Default**: false
+* **Introduced in**: v2.5
+
+### enable_pipeline_engine
+
+* **Description**: Specifies whether to enable the pipeline execution engine. `true` indicates enabled and `false` indicates the opposite. Default value: `true`.
+* **Default**: true
+
+### enable_sort_aggregate
+
+* **Description**: Specifies whether to enable sorted streaming. `true` indicates sorted streaming is enabled to sort data in data streams.
+* **Default**: false
+* **Introduced in**: v2.5
+
+### enable_global_runtime_filter
+
+Whether to enable global runtime filter (RF for short). RF filters data at runtime. Data filtering often occurs in the Join stage. During multi-table joins, optimizations such as predicate pushdown are used to filter data, in order to reduce the number of scanned rows for Join and the I/O in the Shuffle stage, thereby speeding up the query.
+
+StarRocks offers two types of RF: Local RF and Global RF. Local RF is suitable for Broadcast Hash Join and Global RF is suitable for Shuffle Join.
+
+Default value: `true`, which means global RF is enabled. If this feature is disabled, global RF does not take effect. Local RF can still work.
+
+### enable_multicolumn_global_runtime_filter
+
+Whether to enable multi-column global runtime filter. Default value: `false`, which means multi-column global RF is disabled.
+
+If a Join (other than Broadcast Join and Replicated Join) has multiple equi-join conditions:
+
+* If this feature is disabled, only Local RF works.
+* If this feature is enabled, multi-column Global RF takes effect and carries `multi-column` in the partition by clause.
+
+### enable_write_hive_external_table
+
+* **Description**: Whether to allow for sinking data to external tables of Hive.
+* **Default**: false
+* **Introduced in**: v3.2
+
+### event_scheduler
+
+Used for MySQL client compatibility. No practical usage.
+
+### enable_strict_type
+
+* **Description**: Whether to allow implicit conversions for all compound predicates and for all expressions in the WHERE clause.
+* **Default**: false
+* **Introduced in**: v3.1
+
+### force_streaming_aggregate
+
+Used to control whether the aggregation node enables streaming aggregation for computing. The default value is false, meaning the feature is not enabled.
+
+### forward_to_leader
+
+Used to specify whether some commands will be forwarded to the leader FE for execution. Alias: `forward_to_master`. The default value is `false`, meaning not forwarding to the leader FE. There are multiple FEs in a StarRocks cluster, one of which is the leader FE. Normally, users can connect to any FE for full-featured operations. However, some information is only available on the leader FE.
+
+For example, if the SHOW BACKENDS command is not forwarded to the leader FE, only basic information (for example, whether the node is alive) can be viewed. Forwarding to the leader FE can get more detailed information including the node start time and last heartbeat time.
+
+The commands affected by this variable are as follows:
+
+* SHOW FRONTENDS: Forwarding to the leader FE allows users to view the last heartbeat message.
+
+* SHOW BACKENDS: Forwarding to the leader FE allows users to view the boot time, last heartbeat information, and disk capacity information.
+
+* SHOW BROKER: Forwarding to the leader FE allows users to view the boot time and last heartbeat information.
+
+* SHOW TABLET
+
+* ADMIN SHOW REPLICA DISTRIBUTION
+
+* ADMIN SHOW REPLICA STATUS: Forwarding to the leader FE allows users to view the tablet information stored in the metadata of the leader FE. Normally, the tablet information should be the same in the metadata of different FEs. If an error occurs, you can use this method to compare the metadata of the current FE and the leader FE.
+
+* Show PROC: Forwarding to the leader FE allows users to view the PROC information stored in the metadata. This is mainly used for metadata comparison.
+
+### group_concat_max_len
+
+* **Description**: The maximum length of string returned by the [group_concat](sql-functions/string-functions/group_concat.md) function.
+* **Default**: 1024
+* **Min value**: 4
+* **Unit**: Characters
+* **Data type**: Long
+
+### hash_join_push_down_right_table
+
+* **Description**: Used to control whether the data of the left table can be filtered by using the filter condition against the right table in the Join query. If so, it can reduce the amount of data that needs to be processed during the query.
+**Default**: `true` indicates the operation is allowed and the system decides whether the left table can be filtered. `false` indicates the operation is disabled. The default value is `true`.
+
+### init_connect (global)
+
+Used for MySQL client compatibility. No practical usage.
+
+### interactive_timeout
+
+Used for MySQL client compatibility. No practical usage.
+
+### io_tasks_per_scan_operator
+
+* **Description**: The number of concurrent I/O tasks that can be issued by a scan operator. Increase this value if you want to access remote storage systems such as HDFS or S3 but the latency is high. However, a larger value causes more memory consumption.
+* **Default**: 4
+* **Data type**: Int
+* **Introduced in**: v2.5
+
+### language (global)
+
+Used for MySQL client compatibility. No practical usage.
+
+### license (global)
+
+* **Description**: Displays the license of StarRocks.
+* **Default**: Apache License 2.0
+
+### load_mem_limit
+
+Specifies the memory limit for the import operation. The default value is 0, meaning that this variable is not used and `query_mem_limit` is used instead.
+
+This variable is only used for the `INSERT` operation which involves both query and import. If the user does not set this variable, the memory limit for both query and import will be set as `exec_mem_limit`. Otherwise, the memory limit for query will be set as `exec_mem_limit` and the memory limit for import will be as `load_mem_limit`.
+
+Other import methods such as `BROKER LOAD`, `STREAM LOAD` still use `exec_mem_limit` for memory limit.
+
+### log_rejected_record_num (v3.1 and later)
+
+Specifies the maximum number of unqualified data rows that can be logged. Valid values: `0`, `-1`, and any non-zero positive integer. Default value: `0`.
+
+* The value `0` specifies that data rows that are filtered out will not be logged.
+* The value `-1` specifies that all data rows that are filtered out will be logged.
+* A non-zero positive integer such as `n` specifies that up to `n` data rows that are filtered out can be logged on each BE.
+
+### lower_case_table_names (global)
+
+Used for MySQL client compatibility. No practical usage. Table names in StarRocks are case-sensitive.
+
+### materialized_view_rewrite_mode (v3.2 and later)
+
+Specifies the query rewrite mode of asynchronous materialized views. Valid values:
+
+* `disable`: Disable automatic query rewrite of asynchronous materialized views.
+* `default` (Default value): Enable automatic query rewrite of asynchronous materialized views, and allow the optimizer to decide whether a query can be rewritten using the materialized view based on the cost. If the query cannot be rewritten, it directly scans the data in the base table.
+* `default_or_error`: Enable automatic query rewrite of asynchronous materialized views, and allow the optimizer to decide whether a query can be rewritten using the materialized view based on the cost. If the query cannot be rewritten, an error is returned.
+* `force`: Enable automatic query rewrite of asynchronous materialized views, and the optimizer prioritizes query rewrite using the materialized view. If the query cannot be rewritten, it directly scans the data in the base table.
+* `force_or_error`: Enable automatic query rewrite of asynchronous materialized views, and the optimizer prioritizes query rewrite using the materialized view. If the query cannot be rewritten, an error is returned.
+
+### max_allowed_packet
+
+* **Description**: Used for compatibility with the JDBC connection pool C3P0. This variable specifies the maximum size of packets that can be transmitted between the client and server.
+* **Default**: 33554432 (32 MB). You can raise this value if the client reports "PacketTooBigException".
+* **Unit**: Byte
+* **Data type**: Int
+
+### max_pushdown_conditions_per_column
+
+* **Description**: The maximum number of predicates that can be pushed down for a column.
+* **Default**: -1, indicating that the value in the `be.conf` file is used. If this variable is set to a value greater than 0, the value in `be.conf` is ignored.
+* **Data type**: Int
+
+### max_scan_key_num
+
+* **Description**: The maximum number of scan key segmented by each query.
+* **Default**: -1, indicating that the value in the `be.conf` file is used. If this variable is set to a value greater than 0, the value in `be.conf` is ignored.
+
+### nested_mv_rewrite_max_level
+
+* **Description**: The maximum levels of nested materialized views that can be used for query rewrite.
+* **Value range**: [1, +∞). The value of `1` indicates that only materialized views created on base tables can be used for query rewrite.
+* **Default**: 3
+* **Data type**: Int
+
+### net_buffer_length
+
+Used for MySQL client compatibility. No practical usage.
+
+### net_read_timeout
+
+Used for MySQL client compatibility. No practical usage.
+
+### net_write_timeout
+
+Used for MySQL client compatibility. No practical usage.
+
+### new_planner_optimize_timeout
+
+* **Description**: The timeout duration of the query optimizer. When the optimizer times out, an error is returned and the query is stopped, which affects the query performance. You can set this variable to a larger value based on your query or contact StarRocks technical support for troubleshooting. A timeout often occurs when a query has too many joins.
+* **Default**: 3000
+* **Unit**: ms
+
+### parallel_exchange_instance_num
+
+Used to set the number of exchange nodes that an upper-level node uses to receive data from a lower-level node in the execution plan. The default value is -1, meaning the number of exchange nodes is equal to the number of execution instances of the lower-level node. When  this variable is set to be greater than 0 but smaller than the number of execution instances of the lower-level node, the number of exchange nodes equals the set value.
+
+In a distributed query execution plan, the upper-level node usually has one or more exchange nodes to receive data from the execution instances of the lower-level node on different BEs. Usually the number of exchange nodes is equal to the number of execution instances of the lower-level node.
+
+In some aggregation query scenarios where the amount of data decreases drastically after aggregation, you can try to modify this variable to a smaller value to reduce the resource overhead. An example would be running aggregation queries using the Duplicate Key table.
+
+### parallel_fragment_exec_instance_num
+
+Used to set the number of instances used to scan nodes on each BE. The default value is 1.
+
+A query plan typically produces a set of scan ranges. This data is distributed across multiple BE nodes. A BE node will have one or more scan ranges, and by default, each BE node's set of scan ranges is processed by only one execution instance. When machine resources suffice, you can increase this variable to allow more execution instances to process a scan range simultaneously for efficiency purposes.
+
+The number of scan instances determines the number of other execution nodes in the upper level, such as aggregation nodes and join nodes. Therefore, it increases the concurrency of the entire query plan execution. Modifying this variable will help  improve efficiency, but larger values will consume more machine resources, such as CPU, memory, and disk IO.
+
+### partial_update_mode
+
+* **Description**: Used to control the mode of partial updates. Valid values:
+
+  * `auto` (default): The system automatically determines the mode of partial updates by analyzing the UPDATE statement and the columns involved.
+  * `column`: The column mode is used for the partial updates, which is particularly suitable for the partial updates which involve a small number of columns and a large number of rows.
+
+  For more information, see [UPDATE](sql-statements/table_bucket_part_index/UPDATE.md#partial-updates-in-column-mode-since-v31).
+* **Default**: auto
+* **Introduced in**: v3.1
+
+### performance_schema (global)
+
+Used for compatibility with MySQL JDBC versions 8.0.16 and above. No practical usage.
+
+### prefer_compute_node
+
+* **Description**: Specifies whether the FEs distribute query execution plans to CN nodes. Valid values:
+  * `true`: indicates that the FEs distribute query execution plans to CN nodes.
+  * `false`: indicates that the FEs do not distribute query execution plans to CN nodes.
+* **Default**: false
+* **Introduced in**: v2.4
+
+### pipeline_dop
+
+* **Description**: The parallelism of a pipeline instance, which is used to adjust the query concurrency. Default value: 0, indicating the system automatically adjusts the parallelism of each pipeline instance. You can also set this variable to a value greater than 0. Generally, set the value to half the number of physical CPU cores.
+
+  From v3.0 onwards, StarRocks adaptively adjusts this variable based on query parallelism.
+
+* **Default**: 0
+* **Data type**: Int
+
+### pipeline_profile_level
+
+* **Description**: Controls the level of the query profile. A query profile often has five layers: Fragment, FragmentInstance, Pipeline, PipelineDriver, and Operator. Different levels provide different details of the profile:
+
+  * 0: StarRocks combines metrics of the profile and shows only a few core metrics.
+  * 1: default value. StarRocks simplifies the profile and combines metrics of the profile to reduce profile layers.
+  * 2: StarRocks retains all the layers of the profile. The profile size is large in this scenario, especially when the SQL query is complex. This value is not recommended.
+
+* **Default**: 1
+* **Data type**: Int
+
+### query_cache_entry_max_bytes
+
+* **Description**: The threshold for triggering the Passthrough mode. When the number of bytes or rows from the computation results of a specific tablet accessed by a query exceeds the threshold specified by `query_cache_entry_max_bytes` or `query_cache_entry_max_rows`, the query is switched to Passthrough mode.
+* **Valid values**: 0 to 9223372036854775807
+* **Default**: 4194304
+* **Unit**: Byte
+* **Introduced in**: v2.5
+
+### query_cache_entry_max_rows
+
+* **Description**: The upper limit of rows that can be cached. See the description in `query_cache_entry_max_bytes`. Default value: .
+* **Default**: 409600
+* **Introduced in**: v2.5
+
+### query_cache_agg_cardinality_limit
+
+* **Description**: The upper limit of cardinality for GROUP BY in Query Cache. Query Cache is not enabled if the rows generated by GROUP BY exceeds this value. Default value: 5000000. If `query_cache_entry_max_bytes` or `query_cache_entry_max_rows` is set to 0, the Passthrough mode is used even when no computation results are generated from the involved tablets.
+* **Default**: 5000000
+* **Data type**: Long
+* **Introduced in**: v2.5
+
+### query_cache_size (global)
+
+Used for MySQL client compatibility. No practical use.
+
+### query_cache_type
+
+Used for compatibility with JDBC connection pool C3P0. No practical use.
+
+### query_mem_limit
+
+* **Description**: Used to set the memory limit of a query on each BE node. The default value is 0, which means no limit for it. This item takes effect only after Pipeline Engine is enabled. When the `Memory Exceed Limit` error happens, you could try to increase this variable.
+* **Default**: 0, which means no limit.
+* **Unit**: Byte
+
+### query_queue_concurrency_limit (global)
+
+* **Description**: The upper limit of concurrent queries on a BE. It takes effect only after being set greater than `0`.
+* **Default**: 0
+* **Data type**: Int
+
+### query_queue_cpu_used_permille_limit (global)
+
+* **Description**: The upper limit of CPU usage permille (CPU usage * 1000) on a BE. It takes effect only after being set greater than `0`.
+* **Value range**: [0, 1000]
+* **Default**: `0`
+
+### query_queue_max_queued_queries (global)
+
+* **Description**: The upper limit of queries in a queue. When this threshold is reached, incoming queries are rejected. It takes effect only after being set greater than `0`.
+* **Default**: `1024`.
+
+### query_queue_mem_used_pct_limit (global)
+
+* **Description**: The upper limit of memory usage percentage on a BE. It takes effect only after being set greater than `0`.
+* **Value range**: [0, 1]
+* **Default**: 0
+
+### query_queue_pending_timeout_second (global)
+
+* **Description**: The maximum timeout of a pending query in a queue. When this threshold is reached, the corresponding query is rejected.
+* **Default**: 300
+* **Unit**: Second
+
+### query_timeout
+
+* **Description**: Used to set the query timeout in "seconds". This variable will act on all query statements in the current connection, as well as INSERT statements. The default value is 300 seconds.
+* **Value range**: [1, 259200]
+* **Default**: 300
+* **Data type**: Int
+* **Unit**: Second
+
+### range_pruner_max_predicate
+
+* **Description**: The maximum number of IN predicates that can be used for Range partition pruning. Default value: 100. A value larger than 100 may cause the system to scan all tablets, which compromises the query performance.
+* **Default**: 100
+* **Introduced in**: v3.0
+
+### rewrite_count_distinct_to_bitmap_hll
+
+Used to decide whether to rewrite count distinct queries to bitmap_union_count and hll_union_agg.
+
+### runtime_filter_on_exchange_node
+
+* **Description**: Whether to place GRF on Exchange Node after GRF is pushed down across the Exchange operator to a lower-level operator. The default value is `false`, which means GRF will not be placed on Exchange Node after it is pushed down across the Exchange operator to a lower-level operator. This prevents repetitive use of GRF and reduces the computation time.
+
+  However, GRF delivery is a "try-best" process. If the lower-level operator fails to receive the GRF but the GRF is not placed on Exchange Node, data cannot be filtered, which compromises filter performance. `true` means GRF will still be placed on Exchange Node even after it is pushed down across the Exchange operator to a lower-level operator.
+
+* **Default**: false
+
+### runtime_join_filter_push_down_limit
+
+* **Description**: The maximum number of rows allowed for the Hash table based on which Bloom filter Local RF is generated. Local RF will not be generated if this value is exceeded. This variable prevents the generation of an excessively long Local RF.
+* **Default**: 1024000
+* **Data type**: Int
+
+### runtime_profile_report_interval
+
+* **Description**: The time interval at which runtime profiles are reported.
+* **Default**: 10
+* **Unit**: Second
+* **Data type**: Int
+* **Introduced in**: v3.1.0
+
+### spill_mode (3.0 and later)
+
+The execution mode of intermediate result spilling. Valid values:
+
+* `auto`: Spilling is automatically triggered when the memory usage threshold is reached.
+* `force`: StarRocks forcibly executes spilling for all relevant operators, regardless of memory usage.
+
+This variable takes effect only when the variable `enable_spill` is set to `true`.
+
+### spill_storage_volume
+
+* **Description**: The storage volume with which you want to store the intermediate results of queries that triggered spilling. For more information, see [Spill to object storage](../administration/management/resource_management/spill_to_disk.md#spill-intermediate-result-to-object-storage).
+* **Default**: Empty string
+* **Introduced in**: v3.3.0
+
+### SQL_AUTO_IS_NULL
+
+Used for compatibility with the JDBC connection pool C3P0. No practical usage.
+
+### sql_dialect
+
+* **Description**: The SQL dialect that is used. For example, you can run the `set sql_dialect = 'trino';` command to set the SQL dialect to Trino, so you can use Trino-specific SQL syntax and functions in your queries.
+
+  > **NOTICE**
+  >
+  > After you configure StarRocks to use the Trino dialect, identifiers in queries are not case-sensitive by default. Therefore, you must specify names in lowercase for your databases and tables at database and table creation. If you specify database and table names in uppercase, queries against these databases and tables will fail.
+
+* **Data type**: StarRocks
+* **Introduced in**: v3.0
+
+### sql_mode
+
+Used to specify the SQL mode to accommodate certain SQL dialects. Valid values include:
+
+* `PIPES_AS_CONCAT`: The pipe symbol `|` is used to concatenate strings, for example, `select 'hello ' || 'world'`.
+* `ONLY_FULL_GROUP_BY` (Default): The SELECT LIST can only contain GROUP BY columns or aggregate functions.
+* `ALLOW_THROW_EXCEPTION`: returns an error instead of NULL when type conversion fails.
+* `FORBID_INVALID_DATE`: prohibits invalid dates.
+* `MODE_DOUBLE_LITERAL`: interprets floating-point types as DOUBLE rather than DECIMAL.
+* `SORT_NULLS_LAST`: places NULL values at the end after sorting.
+* `ERROR_IF_OVERFLOW`: returns an error instead of NULL in the case of arithmetic overflow. Currently, only the DECIMAL data type supports this option.
+* `GROUP_CONCAT_LEGACY`: uses the `group_concat` syntax of v2.5 and earlier. This option is supported from v3.0.9 and v3.1.6.
+
+You can set only one SQL mode, for example:
+
+```SQL
+set sql_mode = 'PIPES_AS_CONCAT';
+```
+
+Or, you can set multiple modes at a time, for example:
+
+```SQL
+set sql_mode = 'PIPES_AS_CONCAT,ERROR_IF_OVERFLOW,GROUP_CONCAT_LEGACY';
+```
+
+### sql_safe_updates
+
+Used for MySQL client compatibility. No practical usage.
+
+### sql_select_limit
+
+Used for MySQL client compatibility. No practical usage.
+
+### statistic_collect_parallel
+
+* **Description**: Used to adjust the parallelism of statistics collection tasks that can run on BEs. Default value: 1. You can increase this value to speed up collection tasks.
+* **Default**: 1
+* **Data type**: Int
+
+### storage_engine
+
+The types of engines supported by StarRocks:
+
+* olap (default): StarRocks system-owned engine.
+* mysql: MySQL external tables.
+* broker: Access external tables through a broker program.
+* elasticsearch or es: Elasticsearch external tables.
+* hive: Hive external tables.
+* iceberg: Iceberg external tables, supported from v2.1.
+* hudi: Hudi external tables, supported from v2.2.
+* jdbc: external table for JDBC-compatible databases, supported from v2.3.
+
+### streaming_preaggregation_mode
+
+Used to specify the preaggregation mode for the first phase of GROUP BY. If the preaggregation effect in the first phase is not satisfactory, you can use the streaming mode, which performs simple data serialization before streaming data to the destination. Valid values:
+
+* `auto`: The system first tries local preaggregation. If the effect is not satisfactory, it switches to the streaming mode. This is the default value.
+* `force_preaggregation`: The system directly performs local preaggregation.
+* `force_streaming`: The system directly performs streaming.
+
+### system_time_zone
+
+Used to display the time zone of the current system. Cannot be changed.
+
+### time_zone
+
+Used to set the time zone of the current session. The time zone can affect the results of certain time functions.
+
+### trace_log_mode
+
+* **Description**: Used to control where to output the logs of query trace profiles. Valid values:
+  * `command`: Return query trace profile logs as the **Explain String** after executing TRACE LOGS.
+  * `file`: Return query trace profile logs in the FE log file **fe.log** with the class name being `FileLogTracer`.
+
+* **Default**: `command`
+* **Data type**: String
+* **Introduced in**: v3.2.0
+
+### transaction_read_only
+
+* **Description**: Used for MySQL 5.8 compatibility. The alias is `tx_read_only`. This variable specifies the transaction access mode. `ON` indicates read only and `OFF` indicates readable and writable.
+* **Default**: OFF
+* **Introduced in**: v2.5.18, v3.0.9, v3.1.7
+
+### tx_isolation
+
+Used for MySQL client compatibility. No practical usage. The alias is `transaction_isolation`.
+
+### use_compute_nodes
+
+* **Description**: The maximum number of CN nodes that can be used. This variable is valid when `prefer_compute_node=true`. Valid values:
+
+  * `-1`: indicates that all CN nodes are used.
+  * `0`: indicates that no CN nodes are used.
+* **Default**: -1
+* **Data type**: Int
+* **Introduced in**: v2.4
+
+### use_v2_rollup
+
+Used to control the query to fetch data using the rollup index of the segment v2 storage format. This variable is used for validation when going online with segment v2. It is not recommended for other cases.
+
+### vectorized_engine_enable (deprecated from v2.4 onwards)
+
+Used to control whether the vectorized engine is used to execute queries. A value of `true` indicates that the vectorized engine is used, otherwise the non-vectorized engine is used. The default is `true`. This feature is enabled by default from v2.4 onwards and therefore, is deprecated.
+
+### version (global)
+
+The MySQL server version returned to the client. The value is the same as FE parameter `mysql_server_version`.
+
+### version_comment (global)
+
+The StarRocks version. Cannot be changed.
+
+### wait_timeout
+
+* **Description**: The number of seconds the server waits for activity on a non-interactive connection before closing it. If a client does not interact with StarRocks for this length of time, StarRocks will actively close the connection.
+* **Default**: 28800 (8 hours).
+* **Unit**: Second
+* **Data type**: Int
+
+### orc_use_column_names
+
+* **Description**: Used to specify how columns are matched when StarRocks reads ORC files from Hive. The default value is `false`, which means columns in ORC files are read based on their ordinal positions in the Hive table definition. If this variable is set to `true`, columns are read based on their names.
+* **Default**: false
+* **Introduced in**: v3.1.10
diff --git a/docs/en/sql-reference/aws_iam_policies.md b/docs/en/sql-reference/aws_iam_policies.md
new file mode 100644
index 00000000000000..7ef928c9c22df9
--- /dev/null
+++ b/docs/en/sql-reference/aws_iam_policies.md
@@ -0,0 +1,128 @@
+---
+displayed_sidebar: docs
+---
+
+# AWS IAM policies
+
+A policy in AWS IAM declares a set of permissions on a specific AWS resource. After creating a policy, you need to attach it to an IAM role or user. As such, the IAM role or user is assigned the permissions declared in the policy to access the specified AWS resource.
+
+Different operations in StarRocks require you to have access permissions on different AWS resources, and therefore you need to configure different policies.
+
+This topic provides the IAM policies that you need to configure for StarRocks to integrate with different AWS resources in various business scenarios when you choose [the instance profile, assumed role, or IAM user-based authentication method](../integrations/authenticate_to_aws_resources.md#preparations).
+
+## Batch load data from AWS S3
+
+If you want to load data from your S3 bucket, configure the following IAM policy:
+
+> **NOTICE**
+>
+> Replace `<bucket_name>` in the following JSON policy template with the name of your S3 bucket that stores your data files.
+
+```SQL
+{
+  "Version": "2012-10-17",
+  "Statement": [
+      {
+          "Sid": "s3",
+          "Effect": "Allow",
+          "Action": [
+              "s3:GetObject"
+          ],
+          "Resource": [
+              "arn:aws:s3:::<bucket_name>/*"
+          ]
+      },
+      {
+          "Sid": "s3list",
+          "Effect": "Allow",
+          "Action": [
+              "s3:ListBucket"
+          ],
+          "Resource": [
+              "arn:aws:s3:::<bucket_name>"
+          ]
+      }
+  ]
+}
+```
+
+## Read/write AWS S3
+
+If you want to query data from your S3 bucket, configure the following IAM policy:
+
+> **NOTICE**
+>
+> Replace `<bucket_name>` in the following JSON policy template with the name of your S3 bucket that stores your data files.
+
+```SQL
+{
+  "Version": "2012-10-17",
+  "Statement": [
+      {
+          "Sid": "s3",
+          "Effect": "Allow",
+          "Action": [
+              "s3:PutObject",
+              "s3:GetObject",
+              "s3:DeleteObject"
+          ],
+          "Resource": [
+              "arn:aws:s3:::<bucket_name>/*"
+          ]
+      },
+      {
+          "Sid": "s3list",
+          "Effect": "Allow",
+          "Action": [
+              "s3:ListBucket"
+          ],
+          "Resource": [
+              "arn:aws:s3:::<bucket_name>"
+          ]
+      }
+  ]
+}
+```
+
+## Integrate with AWS Glue
+
+If you want to integrate with your AWS Glue Data Catalog, configure the following IAM policy:
+
+```SQL
+{
+    "Version": "2012-10-17",
+    "Statement": [
+      {
+          "Effect": "Allow",
+          "Action": [
+                "glue:BatchCreatePartition",
+                "glue:UpdateDatabase",
+                "glue:GetConnections",
+                "glue:CreateTable",
+                "glue:DeleteDatabase",
+                "glue:BatchUpdatePartition",
+                "glue:GetTables",
+                "glue:GetTableVersions",
+                "glue:GetPartitions",
+                "glue:UpdateTable",
+                "glue:BatchGetPartition",
+                "glue:DeleteTable",
+                "glue:GetDatabases",
+                "glue:GetDevEndpoint",
+                "glue:GetTable",
+                "glue:GetDatabase",
+                "glue:GetPartition",
+                "glue:GetDevEndpoints",
+                "glue:GetConnection",
+                "glue:CreateDatabase",
+                "glue:CreatePartition",
+                "glue:DeletePartition",
+                "glue:UpdatePartition"
+          ],
+          "Resource": [
+              "*"
+            ]
+        }
+    ]
+}
+```
diff --git a/docs/en/sql-reference/data-types/README.md b/docs/en/sql-reference/data-types/README.md
new file mode 100644
index 00000000000000..d7467f8799612e
--- /dev/null
+++ b/docs/en/sql-reference/data-types/README.md
@@ -0,0 +1,12 @@
+---
+sidebar_position: 1
+displayed_sidebar: docs
+---
+
+# Data type overview
+
+import DocCardList from '@theme/DocCardList';
+
+StarRocks supports the following data types: [Numeric](#numeric), [String](#string), [Date](#date), [Semi-structured](#semi-structured), and [Others](#others). You can define columns of these types when you create a table.
+
+<DocCardList />
diff --git a/docs/en/sql-reference/data-types/_category_.yml b/docs/en/sql-reference/data-types/_category_.yml
new file mode 100644
index 00000000000000..9e37077d1bb42d
--- /dev/null
+++ b/docs/en/sql-reference/data-types/_category_.yml
@@ -0,0 +1,7 @@
+position: 10 # float position is supported
+label: 'Data types'
+collapsible: true
+collapsed: true
+link:
+  type: doc
+  id: README
diff --git a/docs/en/sql-reference/data-types/data-type-list.md b/docs/en/sql-reference/data-types/data-type-list.md
deleted file mode 100644
index 83c14065a3a441..00000000000000
--- a/docs/en/sql-reference/data-types/data-type-list.md
+++ /dev/null
@@ -1,44 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# Data type overview
-
-StarRocks supports the following data types: [Numeric](#numeric), [String](#string), [Date](#date), [Semi-structured](#semi-structured), and [Others](#others). You can define columns of these types when you create a table.
-
-## Numeric
-
-- [TINYINT](./numeric/TINYINT.md)
-- [SMALLINT](./numeric/SMALLINT.md)
-- [INT](./numeric/INT.md)
-- [BIGINT](./numeric/BIGINT.md)
-- [LARGEINT](./numeric/LARGEINT.md)
-- [DECIMAL](./numeric/DECIMAL.md)
-- [DOUBLE](./numeric/DOUBLE.md)
-- [FLOAT](./numeric/FLOAT.md)
-- [BOOLEAN](./numeric/BOOLEAN.md)
-- PERCENTILE
-
-## String
-
-- [CHAR](./string-type/CHAR.md)
-- [STRING](./string-type/STRING.md)
-- [VARCHAR](./string-type/VARCHAR.md)
-- [BINARY](./string-type/BINARY.md)
-
-## Date
-
-- [DATE](./date-types/DATE.md)
-- [DATETIME](./date-types/DATETIME.md)
-
-## Semi-structured
-
-- [ARRAY](./semi_structured/Array.md)
-- [JSON](./semi_structured/JSON.md)
-- [MAP](./semi_structured/Map.md)
-- [STRUCT](./semi_structured/STRUCT.md)
-
-## Others
-
-- [BITMAP](./other-data-types/BITMAP.md)
-- [HLL](./other-data-types/HLL.md)
diff --git a/docs/en/sql-reference/data-types/date-types/DATE.md b/docs/en/sql-reference/data-types/date-types/DATE.md
index 40c88d6c8d2055..ac350ed1d35e83 100644
--- a/docs/en/sql-reference/data-types/date-types/DATE.md
+++ b/docs/en/sql-reference/data-types/date-types/DATE.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # DATE
diff --git a/docs/en/sql-reference/data-types/date-types/DATETIME.md b/docs/en/sql-reference/data-types/date-types/DATETIME.md
index 9d3a3ed035d320..803f4774c285d7 100644
--- a/docs/en/sql-reference/data-types/date-types/DATETIME.md
+++ b/docs/en/sql-reference/data-types/date-types/DATETIME.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # DATETIME
diff --git a/docs/en/sql-reference/data-types/date-types/_category_.yml b/docs/en/sql-reference/data-types/date-types/_category_.yml
new file mode 100644
index 00000000000000..515e70a3977f0e
--- /dev/null
+++ b/docs/en/sql-reference/data-types/date-types/_category_.yml
@@ -0,0 +1,6 @@
+position: 30 # float position is supported
+label: 'Date and Time'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/data-types/date-types/date-types.mdx b/docs/en/sql-reference/data-types/date-types/date-types.mdx
deleted file mode 100644
index 84b12bb5ef2bbb..00000000000000
--- a/docs/en/sql-reference/data-types/date-types/date-types.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-#
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/sql-reference/data-types/numeric/BIGINT.md b/docs/en/sql-reference/data-types/numeric/BIGINT.md
index 33cad31c07f264..245c8fe7c834df 100644
--- a/docs/en/sql-reference/data-types/numeric/BIGINT.md
+++ b/docs/en/sql-reference/data-types/numeric/BIGINT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # BIGINT
diff --git a/docs/en/sql-reference/data-types/numeric/BOOLEAN.md b/docs/en/sql-reference/data-types/numeric/BOOLEAN.md
index 8df19e89640839..9f8aab792bdbb9 100644
--- a/docs/en/sql-reference/data-types/numeric/BOOLEAN.md
+++ b/docs/en/sql-reference/data-types/numeric/BOOLEAN.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # BOOLEAN
diff --git a/docs/en/sql-reference/data-types/numeric/DECIMAL.md b/docs/en/sql-reference/data-types/numeric/DECIMAL.md
index db35ef02002d4c..fce86817647a45 100644
--- a/docs/en/sql-reference/data-types/numeric/DECIMAL.md
+++ b/docs/en/sql-reference/data-types/numeric/DECIMAL.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # DECIMAL
diff --git a/docs/en/sql-reference/data-types/numeric/DOUBLE.md b/docs/en/sql-reference/data-types/numeric/DOUBLE.md
index 7d389ab8dd0676..4a50eceabab7d6 100644
--- a/docs/en/sql-reference/data-types/numeric/DOUBLE.md
+++ b/docs/en/sql-reference/data-types/numeric/DOUBLE.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # DOUBLE
diff --git a/docs/en/sql-reference/data-types/numeric/FLOAT.md b/docs/en/sql-reference/data-types/numeric/FLOAT.md
index a6a857fe6de39c..3c3298ac417299 100644
--- a/docs/en/sql-reference/data-types/numeric/FLOAT.md
+++ b/docs/en/sql-reference/data-types/numeric/FLOAT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # FLOAT
diff --git a/docs/en/sql-reference/data-types/numeric/INT.md b/docs/en/sql-reference/data-types/numeric/INT.md
index a6816ef32eafb6..f513caa22ed65c 100644
--- a/docs/en/sql-reference/data-types/numeric/INT.md
+++ b/docs/en/sql-reference/data-types/numeric/INT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # INT
diff --git a/docs/en/sql-reference/data-types/numeric/LARGEINT.md b/docs/en/sql-reference/data-types/numeric/LARGEINT.md
index e088935a50f02d..ec351f5513d67d 100644
--- a/docs/en/sql-reference/data-types/numeric/LARGEINT.md
+++ b/docs/en/sql-reference/data-types/numeric/LARGEINT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # LARGEINT
diff --git a/docs/en/sql-reference/data-types/numeric/SMALLINT.md b/docs/en/sql-reference/data-types/numeric/SMALLINT.md
index 8aa6fa0f752c58..c91e053c11689b 100644
--- a/docs/en/sql-reference/data-types/numeric/SMALLINT.md
+++ b/docs/en/sql-reference/data-types/numeric/SMALLINT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # SMALLINT
diff --git a/docs/en/sql-reference/data-types/numeric/TINYINT.md b/docs/en/sql-reference/data-types/numeric/TINYINT.md
index 76dfb0568182bb..876296c5e8e72a 100644
--- a/docs/en/sql-reference/data-types/numeric/TINYINT.md
+++ b/docs/en/sql-reference/data-types/numeric/TINYINT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # TINYINT
diff --git a/docs/en/sql-reference/data-types/numeric/_category_.yml b/docs/en/sql-reference/data-types/numeric/_category_.yml
new file mode 100644
index 00000000000000..130be4990b369e
--- /dev/null
+++ b/docs/en/sql-reference/data-types/numeric/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Numeric'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/data-types/numeric/numeric.mdx b/docs/en/sql-reference/data-types/numeric/numeric.mdx
deleted file mode 100644
index 84b12bb5ef2bbb..00000000000000
--- a/docs/en/sql-reference/data-types/numeric/numeric.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-#
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/sql-reference/data-types/other-data-types/BITMAP.md b/docs/en/sql-reference/data-types/other-data-types/BITMAP.md
index 80f9b30306c065..537f9250122844 100644
--- a/docs/en/sql-reference/data-types/other-data-types/BITMAP.md
+++ b/docs/en/sql-reference/data-types/other-data-types/BITMAP.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # BITMAP
diff --git a/docs/en/sql-reference/data-types/other-data-types/HLL.md b/docs/en/sql-reference/data-types/other-data-types/HLL.md
index 735cfbaba4c651..6a1628996586b9 100644
--- a/docs/en/sql-reference/data-types/other-data-types/HLL.md
+++ b/docs/en/sql-reference/data-types/other-data-types/HLL.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # HLL (HyperLogLog)
diff --git a/docs/en/sql-reference/data-types/other-data-types/_category_.yml b/docs/en/sql-reference/data-types/other-data-types/_category_.yml
new file mode 100644
index 00000000000000..5c6532f389a23d
--- /dev/null
+++ b/docs/en/sql-reference/data-types/other-data-types/_category_.yml
@@ -0,0 +1,6 @@
+position: 50 # float position is supported
+label: 'Other'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/data-types/other-data-types/other-data-types.mdx b/docs/en/sql-reference/data-types/other-data-types/other-data-types.mdx
deleted file mode 100644
index ac5ff12d021e0b..00000000000000
--- a/docs/en/sql-reference/data-types/other-data-types/other-data-types.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# Other
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/sql-reference/data-types/semi_structured/Array.md b/docs/en/sql-reference/data-types/semi_structured/Array.md
index 7b48dc2ba3c126..e44378b3a66462 100644
--- a/docs/en/sql-reference/data-types/semi_structured/Array.md
+++ b/docs/en/sql-reference/data-types/semi_structured/Array.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ARRAY
@@ -197,7 +197,7 @@ INSERT INTO t0 VALUES(1, [1,2,3]);
 
 ### Use Broker Load to load arrays from ORC or Parquet files
 
-  The array type in StarRocks corresponds to the list structure in ORC and Parquet files, which eliminates the need for you to specify different data types in StarRocks. For more information about data loading, see [Broker load](../../sql-statements/data-manipulation/BROKER_LOAD.md).
+  The array type in StarRocks corresponds to the list structure in ORC and Parquet files, which eliminates the need for you to specify different data types in StarRocks. For more information about data loading, see [Broker load](../../sql-statements/loading_unloading/BROKER_LOAD.md).
 
 ### Use Stream Load or Routine Load to load CSV-formatted arrays
 
diff --git a/docs/en/sql-reference/data-types/semi_structured/JSON.md b/docs/en/sql-reference/data-types/semi_structured/JSON.md
index 0ca89bcd5730f1..defb82033918ad 100644
--- a/docs/en/sql-reference/data-types/semi_structured/JSON.md
+++ b/docs/en/sql-reference/data-types/semi_structured/JSON.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # JSON
@@ -54,7 +54,7 @@ INSERT INTO tj (id, j) VALUES (4, json_object('a', 4, 'b', false));
   - If you want to load a root JSON object, set `jsonpaths` to `$`.
   - If you want to load specific values of a JSON object, set `jsonpaths` to `$.a`, in which `a` specifies a key. For more information about JSON path expressions supported in StarRocks, see [JSON path](../../sql-functions/json-functions/overview-of-json-functions-and-operators.md#json-path-expressions).
 
-- Method 3: Use Broker Load to load a Parquet file and store the file as JSON data. For more information, see [Broker Load](../../sql-statements/data-manipulation/BROKER_LOAD.md).
+- Method 3: Use Broker Load to load a Parquet file and store the file as JSON data. For more information, see [Broker Load](../../sql-statements/loading_unloading/BROKER_LOAD.md).
 
 StarRocks supports the following data type conversions at Parquet file loading.
 
diff --git a/docs/en/sql-reference/data-types/semi_structured/Map.md b/docs/en/sql-reference/data-types/semi_structured/Map.md
index 9d597b7eab764e..30963ae07ecc64 100644
--- a/docs/en/sql-reference/data-types/semi_structured/Map.md
+++ b/docs/en/sql-reference/data-types/semi_structured/Map.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # MAP
@@ -104,7 +104,7 @@ select map() as empty_map; -- Return {}.
 
 ## Load MAP data into StarRocks
 
-You can load map data into StarRocks using two methods: [INSERT INTO](../../../loading/InsertInto.md), and [ORC/Parquet loading](../../sql-statements/data-manipulation/BROKER_LOAD.md).
+You can load map data into StarRocks using two methods: [INSERT INTO](../../../loading/InsertInto.md), and [ORC/Parquet loading](../../sql-statements/loading_unloading/BROKER_LOAD.md).
 
 Note that StarRocks will remove duplicate keys of each map when loading MAP data.
 
@@ -122,7 +122,7 @@ Note that StarRocks will remove duplicate keys of each map when loading MAP data
 
 ### Load MAP data from ORC and Parquet files
 
-The MAP data type in StarRocks corresponds to the map structure in ORC or Parquet format. No additional specification is needed. You can load MAP data from ORC or Parquet files by following the instructions in [ORC/Parquet loading](../../sql-statements/data-manipulation/BROKER_LOAD.md).
+The MAP data type in StarRocks corresponds to the map structure in ORC or Parquet format. No additional specification is needed. You can load MAP data from ORC or Parquet files by following the instructions in [ORC/Parquet loading](../../sql-statements/loading_unloading/BROKER_LOAD.md).
 
 ## Access MAP data
 
diff --git a/docs/en/sql-reference/data-types/semi_structured/STRUCT.md b/docs/en/sql-reference/data-types/semi_structured/STRUCT.md
index 12cbf5e5f89c34..37c035ef95b099 100644
--- a/docs/en/sql-reference/data-types/semi_structured/STRUCT.md
+++ b/docs/en/sql-reference/data-types/semi_structured/STRUCT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # STRUCT
@@ -78,7 +78,7 @@ select named_struct('a', 1, 'b', 2, 'c', 3, 'd', 4) as numbers; -- Return {"a":1
 
 ## Load STRUCT data
 
-You can load STRUCT data into StarRocks using two methods: [INSERT INTO](../../../loading/InsertInto.md), and [ORC/Parquet loading](../../sql-statements/data-manipulation/BROKER_LOAD.md).
+You can load STRUCT data into StarRocks using two methods: [INSERT INTO](../../../loading/InsertInto.md), and [ORC/Parquet loading](../../sql-statements/loading_unloading/BROKER_LOAD.md).
 
 Note that StarRocks automatically casts the data type into the corresponding STRUCT type.
 
@@ -103,7 +103,7 @@ SELECT * FROM t0;
 
 ### Load STRUCT data from ORC/Parquet files
 
-The STRUCT data type in StarRocks corresponds to the nested columns structure in ORC or Parquet format. No additional specification is needed. You can load STRUCT data from ORC or Parquet files by following the instructions in [ORC/Parquet loading](../../sql-statements/data-manipulation/BROKER_LOAD.md).
+The STRUCT data type in StarRocks corresponds to the nested columns structure in ORC or Parquet format. No additional specification is needed. You can load STRUCT data from ORC or Parquet files by following the instructions in [ORC/Parquet loading](../../sql-statements/loading_unloading/BROKER_LOAD.md).
 
 ## Access STRUCT fields
 
diff --git a/docs/en/sql-reference/data-types/semi_structured/_category_.yml b/docs/en/sql-reference/data-types/semi_structured/_category_.yml
new file mode 100644
index 00000000000000..d8625ba59066e1
--- /dev/null
+++ b/docs/en/sql-reference/data-types/semi_structured/_category_.yml
@@ -0,0 +1,6 @@
+position: 40 # float position is supported
+label: 'Semi-structured'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/data-types/semi_structured/semi_structured.mdx b/docs/en/sql-reference/data-types/semi_structured/semi_structured.mdx
deleted file mode 100644
index 1ac9624ebbd068..00000000000000
--- a/docs/en/sql-reference/data-types/semi_structured/semi_structured.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# Work with semi-structured data
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/sql-reference/data-types/string-type/BINARY.md b/docs/en/sql-reference/data-types/string-type/BINARY.md
index 6f7542ac8c2449..f40faba0b34c19 100644
--- a/docs/en/sql-reference/data-types/string-type/BINARY.md
+++ b/docs/en/sql-reference/data-types/string-type/BINARY.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # BINARY/VARBINARY
@@ -73,7 +73,7 @@ StarRocks supports the following ways to load data and store it as BINARY type.
     INSERT INTO test_binary select 7, to_binary('abab', 'utf8');
     ```
 
-- Method 3: Use Broker Load to load a Parquet or ORC file and store the file as BINARY data. For more information, see [Broker Load](../../sql-statements/data-manipulation/BROKER_LOAD.md).
+- Method 3: Use Broker Load to load a Parquet or ORC file and store the file as BINARY data. For more information, see [Broker Load](../../sql-statements/loading_unloading/BROKER_LOAD.md).
 
   - For Parquet files, convert `parquet::Type::type::BYTE_ARRAY` to `TYPE_VARBINARY` directly.
   - For ORC files, convert `orc::BINARY` to `TYPE_VARBINARY` directly.
diff --git a/docs/en/sql-reference/data-types/string-type/CHAR.md b/docs/en/sql-reference/data-types/string-type/CHAR.md
index c8222a29b3c367..0511442e86c010 100644
--- a/docs/en/sql-reference/data-types/string-type/CHAR.md
+++ b/docs/en/sql-reference/data-types/string-type/CHAR.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # CHAR
diff --git a/docs/en/sql-reference/data-types/string-type/STRING.md b/docs/en/sql-reference/data-types/string-type/STRING.md
index bc5f4ee12403d0..fd70dda329e1d0 100644
--- a/docs/en/sql-reference/data-types/string-type/STRING.md
+++ b/docs/en/sql-reference/data-types/string-type/STRING.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # STRING
diff --git a/docs/en/sql-reference/data-types/string-type/VARCHAR.md b/docs/en/sql-reference/data-types/string-type/VARCHAR.md
index 78631b5671ac98..f3f13d3b5b2a86 100644
--- a/docs/en/sql-reference/data-types/string-type/VARCHAR.md
+++ b/docs/en/sql-reference/data-types/string-type/VARCHAR.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # VARCHAR
diff --git a/docs/en/sql-reference/data-types/string-type/_category_.yml b/docs/en/sql-reference/data-types/string-type/_category_.yml
new file mode 100644
index 00000000000000..9de7cb7c42f467
--- /dev/null
+++ b/docs/en/sql-reference/data-types/string-type/_category_.yml
@@ -0,0 +1,6 @@
+position: 20 # float position is supported
+label: 'String'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/data-types/string-type/string-type.mdx b/docs/en/sql-reference/data-types/string-type/string-type.mdx
deleted file mode 100644
index 84b12bb5ef2bbb..00000000000000
--- a/docs/en/sql-reference/data-types/string-type/string-type.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-#
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/sql-reference/http_sql_api.md b/docs/en/sql-reference/http_sql_api.md
new file mode 100644
index 00000000000000..b6b9245a5594db
--- /dev/null
+++ b/docs/en/sql-reference/http_sql_api.md
@@ -0,0 +1,207 @@
+---
+displayed_sidebar: docs
+---
+
+# HTTP SQL API
+
+## Description
+
+StarRocks v3.2.0 introduces the HTTP SQL API for users to perform various types of queries using HTTP. Currently, this API supports SELECT, SHOW, EXPLAIN, and KILL statements.
+
+Syntax using the curl command:
+
+```shell
+curl -X POST 'http://<fe_ip>:<fe_http_port>/api/v1/catalogs/<catalog_name>/databases/<database_name>/sql' \
+   -u '<username>:<password>'  -d '{"query": "<sql_query>;", "sessionVariables":{"<var_name>":<var_value>}}' \
+   --header "Content-Type: application/json"
+```
+
+## Request message
+
+### Request line
+
+```shell
+POST 'http://<fe_ip>:<fe_http_port>/api/v1/catalogs/<catalog_name>/databases/<database_name>/sql'
+```
+
+| Field                    | Description                                                  |
+| ------------------------ | :----------------------------------------------------------- |
+|  fe_ip                   | FE node IP address.                                                  |
+|  fe_http_port            | FE HTTP port.                                           |
+|  catalog_name            | The catalog name. In v3.2.0, you can use this API to query only StarRocks internal tables, which means `<catalog_name>` can only be set to `default_catalog`. Since v3.2.1, you can use this API to query tables in [external catalogs](../data_source/catalog/catalog_overview.md). |
+|  database_name           | The database name. If no database name is specified in the request line and a table name is used in the SQL query, you must prefix the table name with its database name, for example, `database_name.table_name`. |
+
+- Query data across databases in a specified catalog. If a table is used in the SQL query, you must prefix the table name with its database name.
+
+   ```shell
+   POST /api/v1/catalogs/<catalog_name>/sql
+   ```
+
+- Query data from a specified catalog and database.
+
+   ```shell
+   POST /api/v1/catalogs/<catalog_name>/databases/<database_name>/sql
+   ```
+
+### Authentication method
+
+```shell
+Authorization: Basic <credentials>
+```
+
+Basic authentication is used, that is, enter the username and password for `credentials` (`-u '<username>:<password>'`). If no password is set for the username, you can pass in only `<username>:` and leave the password empty. For example, if the root account is used, you can enter `-u 'root:'`.
+
+### Request body
+
+```shell
+-d '{"query": "<sql_query>;", "sessionVariables":{"<var_name>":<var_value>}}'
+```
+
+| Field                    | Description                                                  |
+| ------------------------ | :----------------------------------------------------------- |
+| query                    | The SQL query, in STRING format. Only SELECT, SHOW, EXPLAIN, and KILL statements are supported. You can run only one SQL query for an HTTP request. |
+| sessionVariables         | The [session variable](./System_variable.md) you want to set for the query, in JSON format. This field is optional. Default is empty. The session variable you set takes effect for the same connection and becomes ineffective when the connection is closed. |
+
+### Request header
+
+```shell
+--header "Content-Type: application/json"
+```
+
+This header indicates that the request body is a JSON string.
+
+## Response message
+
+### Status code
+
+- 200: HTTP request succeeded and the server is normal before data is sent to the client.
+- 4xx: HTTP request error, which indicates a client error.
+- `500 Internal Server Error`: HTTP request succeeded but the server encounters an error before data is sent to the client.
+- 503: HTTP request succeeded but the FE cannot provide service.
+
+### Response header
+
+`content-type` indicates the format of the response body. Newline delimited JSON is used, which means the response body consists of multiple JSON objects that are separated by `\n`.
+
+|                      | Description                                                  |
+| -------------------- | :----------------------------------------------------------- |
+| content-type         | The format is Newline delimited JSON, defaults to "application/x-ndjson charset=UTF-8". |
+| X-StarRocks-Query-Id | Query ID.                                                          |
+
+### Response body
+
+#### Failed before the request is sent
+
+Request fails on the client side or the server encounters an error before it returns data to the client. The response body is in the following format, where `msg` is the error information.
+
+```json
+{
+   "status":"FAILED",
+   "msg":"xxx"
+}
+```
+
+#### Failed after the request is sent
+
+Part of the result is returned and the HTTP status code is 200. Data sending is suspended, the connection is closed, and the error is logged.
+
+#### Succeeded
+
+Each row in the response message is a JSON object. JSON objects separated by `\n`.
+
+- For a SELECT statement, the following JSON objects are returned.
+
+| Object       | Description                                                  |
+| ------------ | :----------------------------------------------------------- |
+| `connectionId` | Connection ID. You can cancel a query that is pending for a long time by calling KILL `<connectionId>`. |
+| `meta`        | Represents a column. The key is `meta` and the value is a JSON array, where each object in the array represents a column. |
+| `data`         | The data row, where the key is `data` and the value is a JSON  array which contains a row of data. |
+| `statistics`   | Statistical information of the query.                                       |
+
+- For a SHOW statement, `meta`, `data`, and `statistics` are returned.
+- For the EXPLAIN statement, an `explain` object is returned to show detailed execution plan of the query.
+
+The following example uses `\n` as the separator. StarRocks transmits data using HTTP chunked mode. Each time the FE obtains a data chunk, it streams the data chunk to the client. The client can parse data by row, which eliminates the need for data caching and the need to wait for the entire data, reducing memory consumption for the client.
+
+```json
+{"connectionId": 7}\n
+{"meta": [
+    {
+      "name": "stock_symbol",
+      "type": "varchar"
+    },
+    {
+      "name": "closing_price",
+      "type": "decimal64(8, 2)"
+    },
+    {
+      "name": "closing_date",
+      "type": "datetime"
+    }
+  ]}\n
+{"data": ["JDR", 12.86, "2014-10-02 00:00:00"]}\n
+{"data": ["JDR",14.8, "2014-10-10 00:00:00"]}\n
+...
+{"statistics": {"scanRows": 0,"scanBytes": 0,"returnRows": 9}}
+```
+
+## Examples
+
+### Run a SELECT query
+
+- Query data from a StarRocks internal table (`catalog_name` is `default_catalog`).
+
+  ```shell
+  curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:' -d '{"query": "select * from agg;"}' --header "Content-Type: application/json"
+  ```
+
+  Result:
+
+  ```json
+  {"connectionId":49}
+  {"meta":[{"name":"no","type":"int(11)"},{"name":"k","type":"decimal64(10, 2)"},{"name":"v","type":"decimal64(10, 2)"}]}
+  {"data":[1,"10.00",null]}
+  {"data":[2,"10.00","11.00"]}
+  {"data":[2,"20.00","22.00"]}
+  {"data":[2,"25.00",null]}
+  {"data":[2,"30.00","35.00"]}
+  {"statistics":{"scanRows":0,"scanBytes":0,"returnRows":5}}
+  ```
+
+- Query data from an Iceberg table.
+
+  ```shell
+  curl -X POST 'http://172.26.93.145:8030/api/v1/catalogs/iceberg_catalog/databases/ywb/sql' -u 'root:' -d '{"query": "select * from iceberg_analyze;"}' --header "Content-Type: application/json"
+  ```
+
+  Result:
+
+  ```json
+  {"connectionId":13}
+  {"meta":[{"name":"k1","type":"int(11)"},{"name":"k2","type":"int(11)"}]}
+  {"data":[1,2]}
+  {"data":[1,1]}
+  {"statistics":{"scanRows":0,"scanBytes":0,"returnRows":2}}
+  ```
+
+### Cancel a query
+
+To cancel a query that run an unexpected long time, you can close the connection. StarRocks will cancel this query when it detects the connection is closed.
+
+You can also call KILL `connectionId` to cancel this query. For example:
+
+```shell
+curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:' -d '{"query": "kill 17;"}' --header "Content-Type: application/json"
+```
+
+You can obtain the `connectionId` from the response body or by calling SHOW PROCESSLIST. For example:
+
+```shell
+curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:' -d '{"query": "show processlist;"}' --header "Content-Type: application/json"
+```
+
+### Run a query with a session variable set for this query
+
+```shell
+curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:'  -d '{"query": "SHOW VARIABLES;", "sessionVariables":{"broadcast_row_limit":14000000}}'  --header "Content-Type: application/json"
+```
diff --git a/docs/en/sql-reference/information_schema/be_bvars.md b/docs/en/sql-reference/information_schema/be_bvars.md
new file mode 100644
index 00000000000000..e03786b336c2c0
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/be_bvars.md
@@ -0,0 +1,15 @@
+---
+displayed_sidebar: docs
+---
+
+# be_bvars
+
+`be_bvars` provides statistical information regarding bRPC. You can view RPC latency, QPS, and other statistics for some components of StarRocks.
+
+The following fields are provided in `be_bvars`:
+
+| **Field** | **Description**                                              |
+| --------- | ------------------------------------------------------------ |
+| BE_ID     | ID of the BE where the bvar is located.                      |
+| NAME      | Name of the bvar.                                            |
+| DESC      | Description of the bvar, including important statistical information. |
diff --git a/docs/en/sql-reference/information_schema/be_cloud_native_compactions.md b/docs/en/sql-reference/information_schema/be_cloud_native_compactions.md
new file mode 100644
index 00000000000000..6eb8904c888f5d
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/be_cloud_native_compactions.md
@@ -0,0 +1,23 @@
+---
+displayed_sidebar: docs
+---
+
+# be_cloud_native_compactions
+
+`be_cloud_native_compactions` provides information on compaction transactions running on CNs (or BEs for v3.0) of a shared-data cluster. A compaction transaction is divided into multiple tasks on the tablet level, and each row in `be_cloud_native_compactions` corresponds to a task in the compaction transaction.
+
+The following fields are provided in `be_cloud_native_compactions`:
+
+| **Field**   | **Description**                                              |
+| ----------- | ------------------------------------------------------------ |
+| BE_ID       | ID of the CN (BE).                                           |
+| TXN_ID      | ID of the compaction transaction. It can be duplicated because each compaction transaction may have multiple tasks. |
+| TABLET_ID   | ID of the tablet the task corresponds to.                    |
+| VERSION     | Version of the data that is input to the task.               |
+| SKIPPED     | Whether the task is skipped.                                 |
+| RUNS        | Number of task executions. A value greater than `1` indicates that retries have occurred. |
+| START_TIME  | Task start time.                                             |
+| FINISH_TIME | Task finish time. `NULL` is returned if the task is still in progress. |
+| PROGRESS    | Percentage of progress, ranging from 0 to 100.               |
+| STATUS      | Task status.                                                 |
+
diff --git a/docs/en/sql-reference/information_schema/be_compactions.md b/docs/en/sql-reference/information_schema/be_compactions.md
new file mode 100644
index 00000000000000..e2f350bb549031
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/be_compactions.md
@@ -0,0 +1,20 @@
+---
+displayed_sidebar: docs
+---
+
+# be_compactions
+
+`be_compactions` provides statistical information on compaction tasks.
+
+The following fields are provided in `be_compactions`:
+
+| **Field**                         | **Description**                                         |
+| --------------------------------- | ------------------------------------------------------- |
+| BE_ID                             | ID of the BE.                                           |
+| CANDIDATES_NUM                    | Number of candidates for compaction tasks.              |
+| BASE_COMPACTION_CONCURRENCY       | Number of base compaction tasks that are running.       |
+| CUMULATIVE_COMPACTION_CONCURRENCY | Number of cumulative compaction tasks that are running. |
+| LATEST_COMPACTION_SCORE           | Compaction score of the last compaction task.           |
+| CANDIDATE_MAX_SCORE               | The maximum compaction score of the task candidate.     |
+| MANUAL_COMPACTION_CONCURRENCY     | Number of manual compaction tasks that are running.     |
+| MANUAL_COMPACTION_CANDIDATES_NUM  | Number of candidates for manual compaction tasks.       |
diff --git a/docs/en/sql-reference/information_schema/character_sets.md b/docs/en/sql-reference/information_schema/character_sets.md
new file mode 100644
index 00000000000000..5a195674a8a79d
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/character_sets.md
@@ -0,0 +1,16 @@
+---
+displayed_sidebar: docs
+---
+
+# character_sets
+
+`character_sets` identifies the character sets available.
+
+The following fields are provided in `character_sets`:
+
+| **Field**            | **Description**                                              |
+| -------------------- | ------------------------------------------------------------ |
+| CHARACTER_SET_NAME   | The character set name.                                      |
+| DEFAULT_COLLATE_NAME | The default collation for the character set.                 |
+| DESCRIPTION          | A description of the character set.                          |
+| MAXLEN               | The maximum number of bytes required to store one character. |
diff --git a/docs/en/sql-reference/information_schema/collations.md b/docs/en/sql-reference/information_schema/collations.md
new file mode 100644
index 00000000000000..bdca7918db06e5
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/collations.md
@@ -0,0 +1,18 @@
+---
+displayed_sidebar: docs
+---
+
+# collations
+
+`collations` contains the available collations.
+
+The following fields are provided in `collations`:
+
+| **Field**          | **Description**                                              |
+| ------------------ | ------------------------------------------------------------ |
+| COLLATION_NAME     | The collation name.                                          |
+| CHARACTER_SET_NAME | The name of the character set with which the collation is associated. |
+| ID                 | The collation ID.                                            |
+| IS_DEFAULT         | Whether the collation is the default for its character set.  |
+| IS_COMPILED        | Whether the character set is compiled into the server.       |
+| SORTLEN            | This is related to the amount of memory required to sort strings expressed in the character set. |
diff --git a/docs/en/sql-reference/information_schema/column_privileges.md b/docs/en/sql-reference/information_schema/column_privileges.md
new file mode 100644
index 00000000000000..1dbf267f36761d
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/column_privileges.md
@@ -0,0 +1,25 @@
+---
+displayed_sidebar: docs
+---
+
+# column_privileges
+
+:::note
+
+This view does not apply to the available features in StarRocks.
+
+:::
+
+`column_privileges` identifies all privileges granted on columns to a currently enabled role or by a currently enabled role.
+
+The following fields are provided in `column_privileges`:
+
+| **Field**      | **Description**                                              |
+| -------------- | ------------------------------------------------------------ |
+| GRANTEE        | The name of the user to which the privilege is granted.      |
+| TABLE_CATALOG  | The name of the catalog to which the table containing the column belongs. This value is always `def`. |
+| TABLE_SCHEMA   | The name of the database to which the table containing the column belongs. |
+| TABLE_NAME     | The name of the table containing the column.                 |
+| COLUMN_NAME    | The name of the column.                                      |
+| PRIVILEGE_TYPE | The privilege granted. The value can be any privilege that can be granted at the column level. Each row lists a single privilege, so there is one row per column privilege held by the grantee. |
+| IS_GRANTABLE   | `YES` if the user has the `GRANT OPTION` privilege, `NO` otherwise. The output does not list `GRANT OPTION` as a separate row with `PRIVILEGE_TYPE='GRANT OPTION'`. |
diff --git a/docs/en/sql-reference/information_schema/columns.md b/docs/en/sql-reference/information_schema/columns.md
new file mode 100644
index 00000000000000..9bb9ec2790d8d1
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/columns.md
@@ -0,0 +1,40 @@
+---
+displayed_sidebar: docs
+---
+
+# columns
+
+`columns` contains information about all table columns (or view columns).
+
+:::note
+The metadata of [synchronous materialized views](../../using_starrocks/Materialized_view-single_table.md) is not recorded in `columns`. You can access it by executing `SHOW PROC '/dbs/db/table/index_schema'`.
+:::
+
+The following fields are provided in `columns`:
+
+| **Field**                | **Description**                                              |
+| ------------------------ | ------------------------------------------------------------ |
+| TABLE_CATALOG            | The name of the catalog to which the table containing the column belongs. This value is always `NULL`. |
+| TABLE_SCHEMA             | The name of the database to which the table containing the column belongs. |
+| TABLE_NAME               | The name of the table containing the column.                 |
+| COLUMN_NAME              | The name of the column.                                      |
+| ORDINAL_POSITION         | The ordinal position of the column within the table.         |
+| COLUMN_DEFAULT           | The default value for the column. This is `NULL` if the column has an explicit default of `NULL`, or if the column definition includes no `DEFAULT` clause. |
+| IS_NULLABLE              | The column nullability. The value is `YES` if `NULL` values can be stored in the column, `NO` if not. |
+| DATA_TYPE                | The column data type. The `DATA_TYPE` value is the type name only with no other information. The `COLUMN_TYPE` value contains the type name and possibly other information such as the precision or length. |
+| CHARACTER_MAXIMUM_LENGTH | For string columns, the maximum length in characters.        |
+| CHARACTER_OCTET_LENGTH   | For string columns, the maximum length in bytes.             |
+| NUMERIC_PRECISION        | For numeric columns, the numeric precision.                  |
+| NUMERIC_SCALE            | For numeric columns, the numeric scale.                      |
+| DATETIME_PRECISION       | For temporal columns, the fractional seconds precision.      |
+| CHARACTER_SET_NAME       | For character string columns, the character set name.        |
+| COLLATION_NAME           | For character string columns, the collation name.            |
+| COLUMN_TYPE              | The column data type.<br />The `DATA_TYPE` value is the type name only with no other information. The `COLUMN_TYPE` value contains the type name and possibly other information such as the precision or length. |
+| COLUMN_KEY               | Whether the column is indexed:<ul><li>If `COLUMN_KEY` is empty, the column either is not indexed or is indexed only as a secondary column in a multiple-column, nonunique index.</li><li>If `COLUMN_KEY` is `PRI`, the column is a `PRIMARY KEY` or is one of the columns in a multiple-column `PRIMARY KEY`.</li><li>If `COLUMN_KEY` is `UNI`, the column is the first column of a `UNIQUE` index. (A `UNIQUE` index permits multiple `NULL` values, but you can tell whether the column permits `NULL` by checking the `Null` column.)</li><li>If `COLUMN_KEY` is `DUP`, the column is the first column of a nonunique index in which multiple occurrences of a given value are permitted within the column.</li></ul>If more than one of the `COLUMN_KEY` values applies to a given column of a table, `COLUMN_KEY` displays the one with the highest priority, in the order `PRI`, `UNI`, `DUP`.<br />A `UNIQUE` index may be displayed as `PRI` if it cannot contain `NULL` values and there is no `PRIMARY KEY` in the table. A `UNIQUE` index may display as `MUL` if several columns form a composite `UNIQUE` index; although the combination of the columns is unique, each column can still hold multiple occurrences of a given value. |
+| EXTRA                    | Any additional information that is available about a given column. |
+| PRIVILEGES               | The privileges you have for the column.                      |
+| COLUMN_COMMENT           | Any comment included in the column definition.               |
+| COLUMN_SIZE              |                                                              |
+| DECIMAL_DIGITS           |                                                              |
+| GENERATION_EXPRESSION    | For generated columns, displays the expression used to compute column values. Empty for nongenerated columns. |
+| SRS_ID                   | This value applies to spatial columns. It contains the column `SRID` value that indicates the spatial reference system for values stored in the column. |
diff --git a/docs/en/sql-reference/information_schema/engines.md b/docs/en/sql-reference/information_schema/engines.md
new file mode 100644
index 00000000000000..85d2850923d568
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/engines.md
@@ -0,0 +1,24 @@
+---
+displayed_sidebar: docs
+---
+
+# engines
+
+:::note
+
+This view does not apply to the available features in StarRocks.
+
+:::
+
+`engines` provides information about storage engines.
+
+The following fields are provided in `engines`:
+
+| **Field**    | **Description**                                              |
+| ------------ | ------------------------------------------------------------ |
+| ENGINE       | The name of the storage engine.                              |
+| SUPPORT      | The server's level of support for the storage engine. Valid values:<ul><li>`YES`: The engine is supported and active.</li><li>`DEFAULT`: Like `YES`, plus this is the default engine.</li><li>`NO`: The engine is not supported.</li><li>`DISABLED`: The engine is supported but has been disabled.</li></ul> |
+| COMMENT      | A brief description of the storage engine.                   |
+| TRANSACTIONS | Whether the storage engine supports transactions.            |
+| XA           | Whether the storage engine supports XA transactions.         |
+| SAVEPOINTS   | Whether the storage engine supports savepoints.              |
diff --git a/docs/en/sql-reference/information_schema/events.md b/docs/en/sql-reference/information_schema/events.md
new file mode 100644
index 00000000000000..4e730a7700699d
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/events.md
@@ -0,0 +1,42 @@
+---
+displayed_sidebar: docs
+---
+
+# events
+
+:::note
+
+This view does not apply to the available features in StarRocks.
+
+:::
+
+`events` provides information about Event Manager events.
+
+The following fields are provided in `events`:
+
+| **Field**            | **Description**                                              |
+| -------------------- | ------------------------------------------------------------ |
+| EVENT_CATALOG        | The name of the catalog to which the event belongs. This value is always `def`. |
+| EVENT_SCHEMA         | The name of the database to which the event belongs.         |
+| EVENT_NAME           | The name of the event.                                       |
+| DEFINER              | The user named in the `DEFINER` clause (often the user who created the event). |
+| TIME_ZONE            | The event time zone, which is the time zone used for scheduling the event and that is in effect within the event as it executes. The default value is `SYSTEM`. |
+| EVENT_BODY           | The language used for the statements in the event's `DO` clause. The value is always `SQL`. |
+| EVENT_DEFINITION     | The text of the SQL statement making up the event's `DO` clause; in other words, the statement executed by this event. |
+| EVENT_TYPE           | The event repetition type, either `ONE TIME` (transient) or `RECURRING` (repeating). |
+| EXECUTE_AT           | For a one-time event, this is the `DATETIME` value specified in the `AT` clause of the `CREATE EVENT` statement used to create the event, or of the last `ALTER EVENT` statement that modified the event. The value shown in this column reflects the addition or subtraction of any `INTERVAL` value included in the event's `AT` clause. For example, if an event is created using `ON SCHEDULE AT CURRENT_DATETIME + '1:6' DAY_HOUR`, and the event was created at 2018-02-09 14:05:30, the value shown in this column would be `'2018-02-10 20:05:30'`. If the event's timing is determined by an `EVERY` clause instead of an `AT` clause (that is, if the event is recurring), the value of this column is `NULL`. |
+| INTERVAL_VALUE       | For a recurring event, the number of intervals to wait between event executions. For a transient event, the value is always `NULL`. |
+| INTERVAL_FIELD       | The time units used for the interval which a recurring event waits before repeating. For a transient event, the value is always `NULL`. |
+| SQL_MODE             | The SQL mode in effect when the event was created or altered, and under which the event executes. |
+| STARTS               | The start date and time for a recurring event. This is displayed as a `DATETIME` value, and is `NULL` if no start date and time are defined for the event. For a transient event, this column is always `NULL`. For a recurring event whose definition includes a `STARTS` clause, this column contains the corresponding `DATETIME` value. As with the `EXECUTE_AT` column, this value resolves any expressions used. If there is no `STARTS` clause affecting the timing of the event, this column is `NULL`. |
+| ENDS                 | For a recurring event whose definition includes a `ENDS` clause, this column contains the corresponding `DATETIME` value. As with the `EXECUTE_AT` column, this value resolves any expressions used. If there is no `ENDS` clause affecting the timing of the event, this column is `NULL`. |
+| STATUS               | The event status. One of `ENABLED`, `DISABLED`, or `SLAVESIDE_DISABLED`. `SLAVESIDE_DISABLED` indicates that the creation of the event occurred on another MySQL server acting as a replication source and replicated to the current MySQL server which is acting as a replica, but the event is not presently being executed on the replica. |
+| ON_COMPLETION        | Valid values: `PRESERVE` and `NOT PRESERVE`.                 |
+| CREATED              | The date and time when the event was created. This is a `DATETIME` value. |
+| LAST_ALTERED         | The date and time when the event was last modified. This is a `DATETIME` value. If the event has not been modified since its creation, this value is the same as the `CREATED` value. |
+| LAST_EXECUTED        | The date and time when the event last executed. This is a `DATETIME` value. If the event has never executed, this column is `NULL`.`LAST_EXECUTED` indicates when the event started. As a result, the `ENDS` column is never less than `LAST_EXECUTED`. |
+| EVENT_COMMENT        | The text of the comment, if the event has one. If not, this value is empty. |
+| ORIGINATOR           | The server ID of the MySQL server on which the event was created; used in replication. This value may be updated by `ALTER EVENT` to the server ID of the server on which that statement occurs, if executed on a replication source. The default value is 0. |
+| CHARACTER_SET_CLIENT | The session value of the `character_set_client` system variable when the event was created. |
+| COLLATION_CONNECTION | The session value of the `collation_connection` system variable when the event was created. |
+| DATABASE_COLLATION   | The collation of the database with which the event is associated. |
diff --git a/docs/en/sql-reference/information_schema/global_variables.md b/docs/en/sql-reference/information_schema/global_variables.md
new file mode 100644
index 00000000000000..4be5518eb22946
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/global_variables.md
@@ -0,0 +1,14 @@
+---
+displayed_sidebar: docs
+---
+
+# global_variables
+
+`global_variables` provides information about global variables.
+
+The following fields are provided in `global_variables`:
+
+| **Field**      | **Description**        |
+| -------------- | ---------------------- |
+| VARIABLE_NAME  | Name of the variable.  |
+| VARIABLE_VALUE | Value of the variable. |
diff --git a/docs/en/sql-reference/information_schema/information_schema.md b/docs/en/sql-reference/information_schema/information_schema.md
new file mode 100644
index 00000000000000..712e01cbec7b6f
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/information_schema.md
@@ -0,0 +1,50 @@
+---
+displayed_sidebar: docs
+---
+
+# Information Schema
+
+import DocCardList from '@theme/DocCardList';
+
+The StarRocks Information Schema is a database within each StarRocks instance. Information Schema contains several read-only, system-defined views that store extensive metadata information of all objects that the StarRocks instance maintains. The StarRocks Information Schema is based on the SQL-92 ANSI Information Schema, but with the addition of views and functions that are specific to StarRocks.
+
+From v3.2.0, The StarRocks Information Schema supports manage metadata for external catalogs.
+
+## View metadata via Information Schema
+
+You can view the metadata information within a StarRocks instance by querying the content of views in Information Schema.
+
+The following example checks metadata information about a table named `table1` in StarRocks by querying the view `tables`.
+
+```Plain
+MySQL > SELECT * FROM information_schema.tables WHERE TABLE_NAME like 'table1'\G
+*************************** 1. row ***************************
+  TABLE_CATALOG: def
+   TABLE_SCHEMA: test_db
+     TABLE_NAME: table1
+     TABLE_TYPE: BASE TABLE
+         ENGINE: StarRocks
+        VERSION: NULL
+     ROW_FORMAT: 
+     TABLE_ROWS: 4
+ AVG_ROW_LENGTH: 1657
+    DATA_LENGTH: 6630
+MAX_DATA_LENGTH: NULL
+   INDEX_LENGTH: NULL
+      DATA_FREE: NULL
+ AUTO_INCREMENT: NULL
+    CREATE_TIME: 2023-06-13 11:37:00
+    UPDATE_TIME: 2023-06-13 11:38:06
+     CHECK_TIME: NULL
+TABLE_COLLATION: utf8_general_ci
+       CHECKSUM: NULL
+ CREATE_OPTIONS: 
+  TABLE_COMMENT: 
+1 row in set (0.01 sec)
+```
+
+## Views in Information Schema
+
+The StarRocks Information Schema contains the following metadata views:
+
+<DocCardList />
diff --git a/docs/en/sql-reference/information_schema/key_column_usage.md b/docs/en/sql-reference/information_schema/key_column_usage.md
new file mode 100644
index 00000000000000..013d92bfe24b2c
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/key_column_usage.md
@@ -0,0 +1,30 @@
+---
+displayed_sidebar: docs
+---
+
+# key_column_usage
+
+:::note
+
+This view does not apply to the available features in StarRocks.
+
+:::
+
+`key_column_usage` identifies all columns that are restricted by some unique, primary key, or foreign key constraint.
+
+The following fields are provided in `key_column_usage`:
+
+| **Field**                     | **Description**                                              |
+| ----------------------------- | ------------------------------------------------------------ |
+| CONSTRAINT_CATALOG            | The name of the catalog to which the constraint belongs. This value is always `def`. |
+| CONSTRAINT_SCHEMA             | The name of the database to which the constraint belongs.    |
+| CONSTRAINT_NAME               | The name of the constraint.                                  |
+| TABLE_CATALOG                 | The name of the catalog to which the table belongs. This value is always `def`. |
+| TABLE_SCHEMA                  | The name of the database to which the table belongs.         |
+| TABLE_NAME                    | The name of the table that has the constraint.               |
+| COLUMN_NAME                   | The name of the column that has the constraint.If the constraint is a foreign key, then this is the column of the foreign key, not the column that the foreign key references. |
+| ORDINAL_POSITION              | The column's position within the constraint, not the column's position within the table. Column positions are numbered beginning with 1. |
+| POSITION_IN_UNIQUE_CONSTRAINT | `NULL` for unique and primary-key constraints. For foreign-key constraints, this column is the ordinal position in key of the table that is being referenced. |
+| REFERENCED_TABLE_SCHEMA       | The name of the schema referenced by the constraint.         |
+| REFERENCED_TABLE_NAME         | The name of the table referenced by the constraint.          |
+| REFERENCED_COLUMN_NAME        | The name of the column referenced by the constraint.         |
diff --git a/docs/en/sql-reference/information_schema/load_tracking_logs.md b/docs/en/sql-reference/information_schema/load_tracking_logs.md
new file mode 100644
index 00000000000000..44b12355023097
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/load_tracking_logs.md
@@ -0,0 +1,36 @@
+---
+displayed_sidebar: docs
+---
+
+# load_tracking_logs
+
+`load_tracking_logs` provides error logs of load jobs. This view is supported from StarRocks v3.0 onwards.
+
+The following fields are provided in `load_tracking_logs`:
+
+| **Field**     | **Description**                            |
+| ------------- | ------------------------------------------ |
+| ID            | The ID of the load.                        |
+| JOB_ID        | The ID of the load job(deprecated).                    |
+| LABEL         | The label of the load job.                 |
+| DATABASE_NAME | The database that the load job belongs to. |
+| TRACKING_LOG  | Errors (if any) of the load job.           |
+
+:::tip
+To query the view `load_tracking_logs` you will need to filter on either a `JOB_ID` or a `LABEL`.
+
+You can retrieve the `JOB_ID` or `LABEL` of a load job from the view `information_schema.loads`.
+
+Example:
+
+```sql
+SELECT * from information_schema.load_tracking_logs WHERE label ='user_behavior'\G
+*************************** 1. row ***************************
+       JOB_ID: 10141
+        LABEL: user_behavior
+DATABASE_NAME: mydatabase
+ TRACKING_LOG: NULL
+         TYPE: BROKER
+1 row in set (0.02 sec)
+```
+:::
diff --git a/docs/en/sql-reference/information_schema/loads.md b/docs/en/sql-reference/information_schema/loads.md
new file mode 100644
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+---
+displayed_sidebar: docs
+---
+
+# loads
+
+`loads` provides the results of load jobs. This view is supported from StarRocks v3.1 onwards. Currently, you can only view the results of [Broker Load](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) and [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md) jobs from this view.
+
+The following fields are provided in `loads`:
+
+| **Field**            | **Description**                                              |
+| -------------------- | ------------------------------------------------------------ |
+| JOB_ID               | The unique ID assigned by StarRocks to identify the load job. |
+| LABEL                | The label of the load job.                                   |
+| DATABASE_NAME        | The name of the database to which the destination StarRocks tables belong. |
+| STATE                | The state of the load job. Valid values:<ul><li>`PENDING`: The load job is created.</li><li>`QUEUEING`: The load job is in the queue waiting to be scheduled.</li><li>`LOADING`: The load job is running.</li><li>`PREPARED`: The transaction has been committed.</li><li>`FINISHED`: The load job succeeded.</li><li>`CANCELLED`: The load job failed.</li></ul>For more information, see the "Asynchronous loading" section in [Loading concepts](../../loading/loading_introduction/loading_concepts.md#asynchronous-loading). |
+| PROGRESS             | The progress of the ETL stage and LOADING stage of the load job. |
+| TYPE                 | The type of the load job. For Broker Load, the return value is `BROKER`. For INSERT, the return value is `INSERT`. |
+| PRIORITY             | The priority of the load job. Valid values: `HIGHEST`, `HIGH`, `NORMAL`, `LOW`, and `LOWEST`. |
+| SCAN_ROWS            | The number of data rows that are scanned.                    |
+| FILTERED_ROWS        | The number of data rows that are filtered out due to inadequate data quality. |
+| UNSELECTED_ROWS      | The number of data rows that are filtered out due to the conditions specified in the WHERE clause. |
+| SINK_ROWS            | The number of data rows that are loaded.                     |
+| ETL_INFO             | The ETL details of the load job. A non-empty value is returned only for Spark Load. For any other types of load jobs, an empty value is returned. |
+| TASK_INFO            | The task execution details of the load job, such as the `timeout` and `max_filter_ratio` settings. |
+| CREATE_TIME          | The time at which the load job was created. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
+| ETL_START_TIME       | The start time of the ETL stage of the load job. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
+| ETL_FINISH_TIME      | The end time of the ETL stage of the load job. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
+| LOAD_START_TIME      | The start time of the LOADING stage of the load job. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
+| LOAD_FINISH_TIME     | The end time of the LOADING stage of the load job. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
+| JOB_DETAILS          | The details about the data loaded, such as the number of bytes and the number of files. |
+| ERROR_MSG            | The error message of the load job. If the load job did not encounter any error, `NULL` is returned. |
+| TRACKING_URL         | The URL from which you can access the unqualified data row samples detected in the load job. You can use the `curl` or `wget` command to access the URL and obtain the unqualified data row samples. If no unqualified data is detected, `NULL` is returned. |
+| TRACKING_SQL         | The SQL statement that can be used to query the tracking log of the load job. A SQL statement is returned only when the load job involves unqualified data rows. If the load job does not involve any unqualified data rows, `NULL` is returned. |
+| REJECTED_RECORD_PATH | The path from which you can access all the unqualified data rows that are filtered out in the load job. The number of unqualified data rows logged is determined by the `log_rejected_record_num` parameter configured in the load job. You can use the `wget` command to access the path. If the load job does not involve any unqualified data rows, `NULL` is returned. |
diff --git a/docs/en/sql-reference/information_schema/materialized_views.md b/docs/en/sql-reference/information_schema/materialized_views.md
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+---
+displayed_sidebar: docs
+---
+
+# materialized_views
+
+`materialized_views` provides information about all materialized views.
+
+The following fields are provided in `materialized_views`:
+
+| **Field**                            | **Description**                                              |
+| ------------------------------------ | ------------------------------------------------------------ |
+| MATERIALIZED_VIEW_ID                 | ID of the materialized view.                                 |
+| TABLE_SCHEMA                         | Database in which the materialized view resides.             |
+| TABLE_NAME                           | Name of the materialized view.                               |
+| REFRESH_TYPE                         | Refresh type of the materialized view. Valid values: `ROLLUP` (synchronous materialized view), `ASYNC` (asynchronous refresh materialized view), and `MANUAL` (manual refresh materialized view). When the value is `ROLLUP`, all fields related to activation status and refresh are empry.  |
+| IS_ACTIVE                            | Indicates whether the materialized view is active. Inactive materialized views cannot be refreshed or queried. |
+| INACTIVE_REASON                      | The reason that the materialized view is inactive.           |
+| PARTITION_TYPE                       | Type of partitioning strategy for the materialized view.     |
+| TASK_ID                              | ID of the task responsible for refreshing the materialized view. |
+| TASK_NAME                            | Name of the task responsible for refreshing the materialized view. |
+| LAST_REFRESH_START_TIME              | Start time of the most recent refresh task.                  |
+| LAST_REFRESH_FINISHED_TIME           | End time of the most recent refresh task.                    |
+| LAST_REFRESH_DURATION                | Duration of the most recent refresh task.                    |
+| LAST_REFRESH_STATE                   | State of the most recent refresh task.                       |
+| LAST_REFRESH_FORCE_REFRESH           | Indicates whether the most recent refresh task was a force refresh. |
+| LAST_REFRESH_START_PARTITION         | Starting partition for the most recent refresh task.         |
+| LAST_REFRESH_END_PARTITION           | Ending partition for the most recent refresh task.           |
+| LAST_REFRESH_BASE_REFRESH_PARTITIONS | Base table partitions involved in the most recent refresh task. |
+| LAST_REFRESH_MV_REFRESH_PARTITIONS   | Materialized view partitions refreshed in the most recent refresh task. |
+| LAST_REFRESH_ERROR_CODE              | Error code of the most recent refresh task.                  |
+| LAST_REFRESH_ERROR_MESSAGE           | Error message of the most recent refresh task.               |
+| TABLE_ROWS                           | Number of data rows in the materialized view, based on approximate background statistics. |
+| MATERIALIZED_VIEW_DEFINITION         | SQL definition of the materialized view.                     |
diff --git a/docs/en/sql-reference/information_schema/partitions.md b/docs/en/sql-reference/information_schema/partitions.md
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+---
+displayed_sidebar: docs
+---
+
+# partitions
+
+:::note
+
+This view does not apply to the available features in StarRocks.
+
+:::
+
+`partitions` provides information about table partitions.
+
+The following fields are provided in `partitions`:
+
+| **Field**                  | **Description**                                              |
+| -------------------------- | ------------------------------------------------------------ |
+| TABLE_CATALOG              | The name of the catalog to which the table belongs. This value is always `def`. |
+| TABLE_SCHEMA               | The name of the database to which the table belongs.         |
+| TABLE_NAME                 | The name of the table containing the partition.              |
+| PARTITION_NAME             | The name of the partition.                                   |
+| SUBPARTITION_NAME          | If the `PARTITIONS` table row represents a subpartition, the name of subpartition; otherwise `NULL`.For `NDB`: This value is always `NULL`. |
+| PARTITION_ORDINAL_POSITION | All partitions are indexed in the same order as they are defined, with `1` being the number assigned to the first partition. The indexing can change as partitions are added, dropped, and reorganized; the number shown is this column reflects the current order, taking into account any indexing changes. |
+| PARTITION_METHOD           | Valid values: `RANGE`, `LIST`, `HASH`, `LINEAR HASH`, `KEY`, or `LINEAR KEY`. |
+| SUBPARTITION_METHOD        | Valid values: `HASH`, `LINEAR HASH`, `KEY`, or `LINEAR KEY`  |
+| PARTITION_EXPRESSION       | The expression for the partitioning function used in the `CREATE TABLE` or `ALTER TABLE` statement that created the table's current partitioning scheme. |
+| SUBPARTITION_EXPRESSION    | This works in the same fashion for the subpartitioning expression that defines the subpartitioning for a table as `PARTITION_EXPRESSION` does for the partitioning expression used to define a table's partitioning. If the table has no subpartitions, this column is `NULL`. |
+| PARTITION_DESCRIPTION      | This column is used for RANGE and LIST partitions. For a `RANGE` partition, it contains the value set in the partition's `VALUES LESS THAN` clause, which can be either an integer or `MAXVALUE`. For a `LIST` partition, this column contains the values defined in the partition's `VALUES IN` clause, which is a list of comma-separated integer values.For partitions whose `PARTITION_METHOD` is other than `RANGE` or `LIST`, this column is always `NULL`. |
+| TABLE_ROWS                 | The number of table rows in the partition.                   |
+| AVG_ROW_LENGTH             | The average length of the rows stored in this partition or subpartition, in bytes. This is the same as `DATA_LENGTH` divided by `TABLE_ROWS`. |
+| DATA_LENGTH                | The total length of all rows stored in this partition or subpartition, in bytes; that is, the total number of bytes stored in the partition or subpartition. |
+| MAX_DATA_LENGTH            | The maximum number of bytes that can be stored in this partition or subpartition. |
+| INDEX_LENGTH               | The length of the index file for this partition or subpartition, in bytes. |
+| DATA_FREE                  | The number of bytes allocated to the partition or subpartition but not used. |
+| CREATE_TIME                | The time that the partition or subpartition was created.     |
+| UPDATE_TIME                | The time that the partition or subpartition was last modified. |
+| CHECK_TIME                 | The last time that the table to which this partition or subpartition belongs was checked. |
+| CHECKSUM                   | The checksum value, if any; otherwise `NULL`.                |
+| PARTITION_COMMENT          | The text of the comment, if the partition has one. If not, this value is empty. |
+| NODEGROUP                  | This is the nodegroup to which the partition belongs.        |
+| TABLESPACE_NAME            | The name of the tablespace to which the partition belongs.   |
diff --git a/docs/en/sql-reference/information_schema/pipe_files.md b/docs/en/sql-reference/information_schema/pipe_files.md
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+---
+displayed_sidebar: docs
+---
+
+# pipe_files
+
+`pipe_files` provides the status of the data files to be loaded via a specified pipe. This view is supported from StarRocks v3.2 onwards.
+
+The following fields are provided in `pipe_files`:
+
+| **Field**        | **Description**                                              |
+| ---------------- | ------------------------------------------------------------ |
+| DATABASE_NAME    | The name of the database in which the pipe is stored.        |
+| PIPE_ID          | The unique ID of the pipe.                                   |
+| PIPE_NAME        | The name of the pipe.                                        |
+| FILE_NAME        | The name of the data file.                                   |
+| FILE_VERSION     | The digest of the data file.                                 |
+| FILE_SIZE        | The size of the data file. Unit: bytes.                      |
+| LAST_MODIFIED    | The last time when the data file was modified. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
+| LOAD_STATE       | The load status of the data file. Valid values: `UNLOADED`, `LOADING`, `FINISHED`, and `ERROR`. |
+| STAGED_TIME      | The date and time when the data file was first recorded by the pipe. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
+| START_LOAD_TIME  | The date and time when the loading of the data file began. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
+| FINISH_LOAD_TIME | The date and time when the loading of the data file finished. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
+| ERROR_MSG        | The details about the load error for the data file.          |
diff --git a/docs/en/sql-reference/information_schema/pipes.md b/docs/en/sql-reference/information_schema/pipes.md
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+---
+displayed_sidebar: docs
+---
+
+# pipes
+
+`pipes` provides information about all pipes stored in the current or specified database. This view is supported from StarRocks v3.2 onwards.
+
+:::note
+
+You can also use [SHOW PIPES](../../sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md) to view the pipes stored in a specified database or in the current database in use. This command is also supported from v3.2 onwards.
+
+:::
+
+The following fields are provided in `pipes`:
+
+| **Field**     | **Description**                                              |
+| ------------- | ------------------------------------------------------------ |
+| DATABASE_NAME | The name of the database in which the pipe is stored.        |
+| PIPE_ID       | The unique ID of the pipe.                                   |
+| PIPE_NAME     | The name of the pipe.                                        |
+| TABLE_NAME    | The name of the destination table. Format: `<database_name>.<table_name>`. |
+| STATE         | The status of the pipe. Valid values: `RUNNING`, `FINISHED`, `SUSPENDED`, and `ERROR`. |
+| LOAD_STATUS   | The overall status of the data files to be loaded via the pipe, including the following sub-fields:<ul><li>`loadedFiles`: the number of data files that have been loaded.</li><li>`loadedBytes`: the volume of data that has been loaded, measured in bytes.</li><li>`loadingFiles`: the number of data files that are being loaded.</li></ul> |
+| LAST_ERROR    | The details about the last error that occurred during the pipe execution. Default value: `NULL`. |
+| CREATED_TIME  | The date and time when the pipe was created. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
diff --git a/docs/en/sql-reference/information_schema/referential_constraints.md b/docs/en/sql-reference/information_schema/referential_constraints.md
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+---
+displayed_sidebar: docs
+---
+
+# referential_constraints
+
+:::note
+
+This view does not apply to the available features in StarRocks.
+
+:::
+
+`referential_constraints` contains all referential (foreign key) constraints.
+
+The following fields are provided in `referential_constraints`:
+
+| **Field**                 | **Description**                                              |
+| ------------------------- | ------------------------------------------------------------ |
+| CONSTRAINT_CATALOG        | The name of the catalog to which the constraint belongs. This value is always `def`. |
+| CONSTRAINT_SCHEMA         | The name of the database to which the constraint belongs.    |
+| CONSTRAINT_NAME           | The name of the constraint.                                  |
+| UNIQUE_CONSTRAINT_CATALOG | The name of the catalog containing the unique constraint that the constraint references. This value is always `def`. |
+| UNIQUE_CONSTRAINT_SCHEMA  | The name of the schema containing the unique constraint that the constraint references. |
+| UNIQUE_CONSTRAINT_NAME    | The name of the unique constraint that the constraint references. |
+| MATCH_OPTION              | The value of the constraint `MATCH` attribute. The only valid value at this time is `NONE`. |
+| UPDATE_RULE               | The value of the constraint `ON UPDATE` attribute. Valid values: `CASCADE`, `SET NULL`, `SET DEFAULT`, `RESTRICT`, and `NO ACTION`. |
+| DELETE_RULE               | The value of the constraint `ON DELETE` attribute. Valid values: `CASCADE`, `SET NULL`, `SET DEFAULT`, `RESTRICT`, and `NO ACTION`. |
+| TABLE_NAME                | The name of the table. This value is the same as in the `TABLE_CONSTRAINTS` table. |
+| REFERENCED_TABLE_NAME     | The name of the table referenced by the constraint.          |
diff --git a/docs/en/sql-reference/information_schema/routines.md b/docs/en/sql-reference/information_schema/routines.md
new file mode 100644
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--- /dev/null
+++ b/docs/en/sql-reference/information_schema/routines.md
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+---
+displayed_sidebar: docs
+---
+
+# routines
+
+:::note
+
+This view does not apply to the available features in StarRocks.
+
+:::
+
+`routines` contains all stored routines (stored procedures and stored functions).
+
+The following fields are provided in `routine`:
+
+| **Field**            | **Description**                                              |
+| -------------------- | ------------------------------------------------------------ |
+| SPECIFIC_NAME        | The name of the routine.                                     |
+| ROUTINE_CATALOG      | The name of the catalog to which the routine belongs. This value is always `def`. |
+| ROUTINE_SCHEMA       | The name of the database to which the routine belongs.       |
+| ROUTINE_NAME         | The name of the routine.                                     |
+| ROUTINE_TYPE         | `PROCEDURE` for stored procedures, `FUNCTION` for stored functions. |
+| DTD_IDENTIFIER       | If the routine is a stored function, the return value data type. If the routine is a stored procedure, this value is empty. |
+| ROUTINE_BODY         | The language used for the routine definition. This value is always `SQL`. |
+| ROUTINE_DEFINITION   | The text of the SQL statement executed by the routine.       |
+| EXTERNAL_NAME        | This value is always `NULL`.                                 |
+| EXTERNAL_LANGUAGE    | The language of the stored routine.                          |
+| PARAMETER_STYLE      | This value is always `SQL`.                                  |
+| IS_DETERMINISTIC     | `YES` or `NO`, depending on whether the routine is defined with the `DETERMINISTIC` characteristic. |
+| SQL_DATA_ACCESS      | The data access characteristic for the routine. The value is one of `CONTAINS SQL`, `NO SQL`, `READS SQL DATA`, or `MODIFIES SQL DATA`. |
+| SQL_PATH             | This value is always `NULL`.                                 |
+| SECURITY_TYPE        | The routine `SQL SECURITY` characteristic. The value is one of `DEFINER` or `INVOKER`. |
+| CREATED              | The date and time when the routine was created. This is a `DATETIME` value. |
+| LAST_ALTERED         | The date and time when the routine was last modified. This is a `DATETIME` value. If the routine has not been modified since its creation, this value is the same as the `CREATED` value. |
+| SQL_MODE             | The SQL mode in effect when the routine was created or altered, and under which the routine executes. |
+| ROUTINE_COMMENT      | The text of the comment, if the routine has one. If not, this value is empty. |
+| DEFINER              | The user named in the `DEFINER` clause (often the user who created the routine). |
+| CHARACTER_SET_CLIENT |                                                              |
+| COLLATION_CONNECTION |                                                              |
+| DATABASE_COLLATION   | The collation of the database with which the routine is associated. |
\ No newline at end of file
diff --git a/docs/en/sql-reference/information_schema/schema_privileges.md b/docs/en/sql-reference/information_schema/schema_privileges.md
new file mode 100644
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+++ b/docs/en/sql-reference/information_schema/schema_privileges.md
@@ -0,0 +1,23 @@
+---
+displayed_sidebar: docs
+---
+
+# schema_privileges
+
+:::note
+
+This view does not apply to the available features in StarRocks.
+
+:::
+
+`schema_privileges` provides information about database privileges.
+
+The following fields are provided in `schema_privileges`:
+
+| **Field**      | **Description**                                              |
+| -------------- | ------------------------------------------------------------ |
+| GRANTEE        | The name of the user to which the privilege is granted.      |
+| TABLE_CATALOG  | The name of the catalog to which the schema belongs. This value is always `def`. |
+| TABLE_SCHEMA   | The name of the schema.                                      |
+| PRIVILEGE_TYPE | The privilege granted. Each row lists a single privilege, so there is one row per schema privilege held by the grantee. |
+| IS_GRANTABLE   | `YES` if the user has the `GRANT OPTION` privilege, `NO` otherwise. The output does not list `GRANT OPTION` as a separate row with `PRIVILEGE_TYPE='GRANT OPTION'`. |
diff --git a/docs/en/sql-reference/information_schema/schemata.md b/docs/en/sql-reference/information_schema/schemata.md
new file mode 100644
index 00000000000000..adc97fb0d1158a
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/schemata.md
@@ -0,0 +1,17 @@
+---
+displayed_sidebar: docs
+---
+
+# schemata
+
+`schemata` provides information about databases.
+
+The following fields are provided in `schemata`:
+
+| **Field**                  | **Description**                                              |
+| -------------------------- | ------------------------------------------------------------ |
+| CATALOG_NAME               | The name of the catalog to which the schema belongs. This value is always `NULL`. |
+| SCHEMA_NAME                | The name of the schema.                                      |
+| DEFAULT_CHARACTER_SET_NAME | The schema default character set.                            |
+| DEFAULT_COLLATION_NAME     | The schema default collation.                                |
+| SQL_PATH                   | This value is always `NULL`.                                 |
diff --git a/docs/en/sql-reference/information_schema/session_variables.md b/docs/en/sql-reference/information_schema/session_variables.md
new file mode 100644
index 00000000000000..921ceedb8361b1
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/session_variables.md
@@ -0,0 +1,14 @@
+---
+displayed_sidebar: docs
+---
+
+# session_variables
+
+`session_variables` provides information about session variables.
+
+The following fields are provided in `session_variables`:
+
+| **Field**      | **Description**        |
+| -------------- | ---------------------- |
+| VARIABLE_NAME  | Name of the variable.  |
+| VARIABLE_VALUE | Value of the variable. |
diff --git a/docs/en/sql-reference/information_schema/statistics.md b/docs/en/sql-reference/information_schema/statistics.md
new file mode 100644
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+++ b/docs/en/sql-reference/information_schema/statistics.md
@@ -0,0 +1,34 @@
+---
+displayed_sidebar: docs
+---
+
+# statistics
+
+:::note
+
+This view does not apply to the available features in StarRocks.
+
+:::
+
+`statistics` provides information about table indexes.
+
+The following fields are provided in `statistics`:
+
+| **Field**     | **Description**                                              |
+| ------------- | ------------------------------------------------------------ |
+| TABLE_CATALOG | The name of the catalog to which the table containing the index belongs. This value is always `def`. |
+| TABLE_SCHEMA  | The name of the database to which the table containing the index belongs. |
+| TABLE_NAME    | The name of the table containing the index.                  |
+| NON_UNIQUE    | 0 if the index cannot contain duplicates, 1 if it can.       |
+| INDEX_SCHEMA  | The name of the database to which the index belongs.         |
+| INDEX_NAME    | The name of the index. If the index is the primary key, the name is always `PRIMARY`. |
+| SEQ_IN_INDEX  | The column sequence number in the index, starting with 1.    |
+| COLUMN_NAME   | The column name. See also the description for the `EXPRESSION` column. |
+| COLLATION     | How the column is sorted in the index. This can have values `A` (ascending), `D` (descending), or `NULL` (not sorted). |
+| CARDINALITY   | An estimate of the number of unique values in the index.     |
+| SUB_PART      | The index prefix. That is, the number of indexed characters if the column is only partly indexed, `NULL` if the entire column is indexed. |
+| PACKED        | Indicates how the key is packed. `NULL` if it is not.        |
+| NULLABLE      | Contains `YES` if the column may contain `NULL` values and `''` if not. |
+| INDEX_TYPE    | The index method used (`BTREE`, `FULLTEXT`, `HASH`, `RTREE`). |
+| COMMENT       | Information about the index not described in its own column, such as `disabled` if the index is disabled. |
+| INDEX_COMMENT | Any comment provided for the index with a `COMMENT` attribute when the index was created. |
diff --git a/docs/en/sql-reference/information_schema/table_constraints.md b/docs/en/sql-reference/information_schema/table_constraints.md
new file mode 100644
index 00000000000000..6d6df182adee33
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/table_constraints.md
@@ -0,0 +1,24 @@
+---
+displayed_sidebar: docs
+---
+
+# table_constraints
+
+:::note
+
+This view does not apply to the available features in StarRocks.
+
+:::
+
+`table_constraints` describes which tables have constraints.
+
+The following fields are provided in `table_constraints`:
+
+| **Field**          | **Description**                                              |
+| ------------------ | ------------------------------------------------------------ |
+| CONSTRAINT_CATALOG | The name of the catalog to which the constraint belongs. This value is always `def`. |
+| CONSTRAINT_SCHEMA  | The name of the database to which the constraint belongs.    |
+| CONSTRAINT_NAME    | The name of the constraint.                                  |
+| TABLE_SCHEMA       | The name of the database to which the table belongs.         |
+| TABLE_NAME         | The name of the table.                                       |
+| CONSTRAINT_TYPE    | The type of constraint.                                      |
diff --git a/docs/en/sql-reference/information_schema/table_privileges.md b/docs/en/sql-reference/information_schema/table_privileges.md
new file mode 100644
index 00000000000000..0fe64bb5cbe29b
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/table_privileges.md
@@ -0,0 +1,24 @@
+---
+displayed_sidebar: docs
+---
+
+# table_privileges
+
+:::note
+
+This view does not apply to the available features in StarRocks.
+
+:::
+
+`table_privileges` provides information about table privileges.
+
+The following fields are provided in `table_privileges`:
+
+| **Field**      | **Description**                                              |
+| -------------- | ------------------------------------------------------------ |
+| GRANTEE        | The name of the user to which the privilege is granted.      |
+| TABLE_CATALOG  | The name of the catalog to which the table belongs. This value is always `def`. |
+| TABLE_SCHEMA   | The name of the database to which the table belongs.         |
+| TABLE_NAME     | The name of the table.                                       |
+| PRIVILEGE_TYPE | The privilege granted. The value can be any privilege that can be granted at the table level. |
+| IS_GRANTABLE   | `YES` if the user has the `GRANT OPTION` privilege, `NO` otherwise. The output does not list `GRANT OPTION` as a separate row with `PRIVILEGE_TYPE='GRANT OPTION'`. |
diff --git a/docs/en/sql-reference/information_schema/tables.md b/docs/en/sql-reference/information_schema/tables.md
new file mode 100644
index 00000000000000..a747ee07630695
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/tables.md
@@ -0,0 +1,33 @@
+---
+displayed_sidebar: docs
+---
+
+# tables
+
+`tables` provides information about tables.
+
+The following fields are provided in `tables`:
+
+| **Field**       | **Description**                                              |
+| --------------- | ------------------------------------------------------------ |
+| TABLE_CATALOG   | Name of the catalog that stores the table.                   |
+| TABLE_SCHEMA    | Name of the database that stores the table.                  |
+| TABLE_NAME      | Name of the table.                                           |
+| TABLE_TYPE      | Type of the table. Valid values: `BASE TABLE` or `VIEW`.     |
+| ENGINE          | Engine type of the table. Valid values: `StarRocks`, `MySQL`, `MEMORY` or an empty string. |
+| VERSION         | Applies to a feature not available in StarRocks.             |
+| ROW_FORMAT      | Applies to a feature not available in StarRocks.             |
+| TABLE_ROWS      | Row count of the table.                                      |
+| AVG_ROW_LENGTH  | Average row length (size) of the table. It is equivalent to `DATA_LENGTH`/`TABLE_ROWS`. Unit: Byte. |
+| DATA_LENGTH     | Data length (size) of the table. Unit: Byte.                 |
+| MAX_DATA_LENGTH | Applies to a feature not available in StarRocks.             |
+| INDEX_LENGTH    | Applies to a feature not available in StarRocks.             |
+| DATA_FREE       | Applies to a feature not available in StarRocks.             |
+| AUTO_INCREMENT  | Applies to a feature not available in StarRocks.             |
+| CREATE_TIME     | The time when the table was created.                          |
+| UPDATE_TIME     | The last time when the table was updated.                     |
+| CHECK_TIME      | The last time when a consistency check was performed on the table. |
+| TABLE_COLLATION | The default collation of the table.                          |
+| CHECKSUM        | Applies to a feature not available in StarRocks.             |
+| CREATE_OPTIONS  | Applies to a feature not available in StarRocks.             |
+| TABLE_COMMENT   | Comment on the table.                                        |
diff --git a/docs/en/sql-reference/information_schema/tables_config.md b/docs/en/sql-reference/information_schema/tables_config.md
new file mode 100644
index 00000000000000..30e1472d0fdf35
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/tables_config.md
@@ -0,0 +1,24 @@
+---
+displayed_sidebar: docs
+---
+
+# tables_config
+
+`tables_config` provides information about the configuration of tables.
+
+The following fields are provided in `tables_config`:
+
+| **Field**        | **Description**                                              |
+| ---------------- | ------------------------------------------------------------ |
+| TABLE_SCHEMA     | Name of the database that stores the table.                  |
+| TABLE_NAME       | Name of the table.                                           |
+| TABLE_ENGINE     | Engine type of the table.                                    |
+| TABLE_MODEL      | Data model of the table. Valid values: `DUP_KEYS`, `AGG_KEYS`, `UNQ_KEYS` or `PRI_KEYS`. |
+| PRIMARY_KEY      | Primary key of a Primary Key table or a Unique Key table. An empty string is returned if the table is not a Primary Key table or a Unique Key table. |
+| PARTITION_KEY    | Partitioning columns of the table.                       |
+| DISTRIBUTE_KEY   | Bucketing columns of the table.                          |
+| DISTRIBUTE_TYPE  | Data distribution method of the table.                   |
+| DISTRUBTE_BUCKET | Number of buckets in the table.                              |
+| SORT_KEY         | Sort keys of the table.                                      |
+| PROPERTIES       | Properties of the table.                                     |
+| TABLE_ID         | ID of the table.                                             |
diff --git a/docs/en/sql-reference/information_schema/task_runs.md b/docs/en/sql-reference/information_schema/task_runs.md
new file mode 100644
index 00000000000000..6398e321045ba6
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/task_runs.md
@@ -0,0 +1,24 @@
+---
+displayed_sidebar: docs
+---
+
+# task_runs
+
+`task_runs` provides information about the execution of asynchronous tasks.
+
+The following fields are provided in `task_runs`:
+
+| **Field**     | **Description**                                              |
+| ------------- | ------------------------------------------------------------ |
+| QUERY_ID      | ID of the query.                                             |
+| TASK_NAME     | Name of the task.                                            |
+| CREATE_TIME   | Time when the task was created.                               |
+| FINISH_TIME   | Time when the task finished.                                 |
+| STATE         | State of the task. Valid values: `PENDING`, `RUNNING`, `FAILED`, and `SUCCESS`. From v3.1.12, a new state `MERGED` is added especially for materialized view refresh tasks. When a new refresh task is submitted and the old task is still in the pending queue, these tasks will be merged and their priority level will be maintained.  |
+| DATABASE      | Database where the task belongs.                             |
+| DEFINITION    | SQL definition of the task.                                  |
+| EXPIRE_TIME   | Time when the task expires.                                  |
+| ERROR_CODE    | Error code of the task.                                      |
+| ERROR_MESSAGE | Error message of the task.                                   |
+| PROGRESS      | The progress of the task.                                    |
+| EXTRA_MESSAGE | Extra message for the task, for example, the partition information in an asynchronous materialized view creation task. |
diff --git a/docs/en/sql-reference/information_schema/tasks.md b/docs/en/sql-reference/information_schema/tasks.md
new file mode 100644
index 00000000000000..4bce1acd6c4b17
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/tasks.md
@@ -0,0 +1,18 @@
+---
+displayed_sidebar: docs
+---
+
+# tasks
+
+`tasks` provides information about asynchronous tasks.
+
+The following fields are provided in `tasks`:
+
+| **Field**   | **Description**                                              |
+| ----------- | ------------------------------------------------------------ |
+| TASK_NAME   | Name of the task.                                            |
+| CREATE_TIME | Time when the task was created.                               |
+| SCHEDULE    | Task schedule. If the task is regularly triggered, this field displays `START xxx EVERY xxx`. |
+| DATABASE    | Database where the task belongs.                             |
+| DEFINITION  | SQL definition of the task.                                  |
+| EXPIRE_TIME | Time when the task expires.                                  |
diff --git a/docs/en/sql-reference/information_schema/triggers.md b/docs/en/sql-reference/information_schema/triggers.md
new file mode 100644
index 00000000000000..3e42bf79b038d6
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/triggers.md
@@ -0,0 +1,40 @@
+---
+displayed_sidebar: docs
+---
+
+# triggers
+
+:::note
+
+This view does not apply to the available features in StarRocks.
+
+:::
+
+`triggers` provides information about triggers.
+
+The following fields are provided in `triggers`:
+
+| **Field**                  | **Description**                                              |
+| -------------------------- | ------------------------------------------------------------ |
+| TRIGGER_CATALOG            | The name of the catalog to which the trigger belongs. This value is always `def`. |
+| TRIGGER_SCHEMA             | The name of the database to which the trigger belongs.       |
+| TRIGGER_NAME               | The name of the trigger.                                     |
+| EVENT_MANIPULATION         | The trigger event. This is the type of operation on the associated table for which the trigger activates. The value is `INSERT` (a row was inserted), `DELETE` (a row was deleted), or `UPDATE` (a row was modified). |
+| EVENT_OBJECT_CATALOG       | Every trigger is associated with exactly one table. The catalog in which this table occurs. |
+| EVENT_OBJECT_SCHEMA        | Every trigger is associated with exactly one table. The database in which this table occurs. |
+| EVENT_OBJECT_TABLE         | The name of the table that the trigger is associated with.   |
+| ACTION_ORDER               | The ordinal position of the trigger's action within the list of triggers on the same table with the same `EVENT_MANIPULATION` and `ACTION_TIMING` values. |
+| ACTION_CONDITION           | This value is always `NULL`.                                 |
+| ACTION_STATEMENT           | The trigger body; that is, the statement executed when the trigger activates. This text uses UTF-8 encoding. |
+| ACTION_ORIENTATION         | This value is always `ROW`.                                  |
+| ACTION_TIMING              | Whether the trigger activates before or after the triggering event. The value is `BEFORE` or `AFTER`. |
+| ACTION_REFERENCE_OLD_TABLE | This value is always `NULL`.                                 |
+| ACTION_REFERENCE_NEW_TABLE | This value is always `NULL`.                                 |
+| ACTION_REFERENCE_OLD_ROW   | The old column identifiers. The value is always `OLD`.       |
+| ACTION_REFERENCE_NEW_ROW   | The new column identifiers. The value is always `NEW`.       |
+| CREATED                    | The date and time when the trigger was created. This is a `DATETIME(2)` value (with a fractional part in hundredths of seconds) for triggers. |
+| SQL_MODE                   | The SQL mode in effect when the trigger was created, and under which the trigger executes. |
+| DEFINER                    | The user named in the `DEFINER` clause (often the user who created the trigger). |
+| CHARACTER_SET_CLIENT       |                                                              |
+| COLLATION_CONNECTION       |                                                              |
+| DATABASE_COLLATION         | The collation of the database with which the trigger is associated. |
diff --git a/docs/en/sql-reference/information_schema/user_privileges.md b/docs/en/sql-reference/information_schema/user_privileges.md
new file mode 100644
index 00000000000000..a8a00c473f5af1
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/user_privileges.md
@@ -0,0 +1,22 @@
+---
+displayed_sidebar: docs
+---
+
+# user_privileges
+
+:::note
+
+This view does not apply to the available features in StarRocks.
+
+:::
+
+`user_privileges` provides information about user privileges.
+
+The following fields are provided in `user_privileges`:
+
+| **Field**      | **Description**                                              |
+| -------------- | ------------------------------------------------------------ |
+| GRANTEE        | The name of the user to which the privilege is granted.      |
+| TABLE_CATALOG  | The name of the catalog. This value is always `def`.         |
+| PRIVILEGE_TYPE | The privilege granted. The value can be any privilege that can be granted at the global level. |
+| IS_GRANTABLE   | `YES` if the user has the `GRANT OPTION` privilege, `NO` otherwise. The output does not list `GRANT OPTION` as a separate row with `PRIVILEGE_TYPE='GRANT OPTION'`. |
diff --git a/docs/en/sql-reference/information_schema/views.md b/docs/en/sql-reference/information_schema/views.md
new file mode 100644
index 00000000000000..6718fa245eb718
--- /dev/null
+++ b/docs/en/sql-reference/information_schema/views.md
@@ -0,0 +1,23 @@
+---
+displayed_sidebar: docs
+---
+
+# views
+
+`views` provides information about all user-defined views.
+
+The following fields are provided in `views`:
+
+| **Field**            | **Description**                                              |
+| -------------------- | ------------------------------------------------------------ |
+| TABLE_CATALOG        | The name of the catalog to which the view belongs. This value is always `def`. |
+| TABLE_SCHEMA         | The name of the database to which the view belongs.          |
+| TABLE_NAME           | The name of the view.                                        |
+| VIEW_DEFINITION      | The `SELECT` statement that provides the definition of the view. |
+| CHECK_OPTION         | The value of the `CHECK_OPTION` attribute. The value is one of `NONE`, `CASCADE`, or `LOCAL`. |
+| IS_UPDATABLE         | Whether the view is updatable. The flag is set to `YES` (true) if `UPDATE` and `DELETE` (and similar operations) are legal for the view. Otherwise, the flag is set to `NO` (false). If a view is not updatable, statements such `UPDATE`, `DELETE`, and `INSERT` are illegal and are rejected. |
+| DEFINER              | The user of the user who created the view.                   |
+| SECURITY_TYPE        | The view `SQL SECURITY` characteristic. The value is one of `DEFINER` or `INVOKER`. |
+| CHARACTER_SET_CLIENT |                                                              |
+| COLLATION_CONNECTION |                                                              |
+
diff --git a/docs/en/sql-reference/overview-pages/map-functions.mdx b/docs/en/sql-reference/overview-pages/map-functions.mdx
deleted file mode 100644
index 55d8992836be49..00000000000000
--- a/docs/en/sql-reference/overview-pages/map-functions.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# Map functions
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/sql-reference/sql-functions/JAVA_UDF.md b/docs/en/sql-reference/sql-functions/JAVA_UDF.md
index e1650a9d313ae6..504b22ffa68da2 100644
--- a/docs/en/sql-reference/sql-functions/JAVA_UDF.md
+++ b/docs/en/sql-reference/sql-functions/JAVA_UDF.md
@@ -1,5 +1,6 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
+sidebar_position: 0.9
 ---
 
 # Java UDFs
@@ -521,7 +522,7 @@ Run the following command to query UDFs:
 SHOW [GLOBAL] FUNCTIONS;
 ```
 
-For more information, see [SHOW FUNCTIONS](../sql-statements/data-definition/SHOW_FUNCTIONS.md).
+For more information, see [SHOW FUNCTIONS](../sql-statements/Function/SHOW_FUNCTIONS.md).
 
 ## Drop a UDF
 
@@ -531,7 +532,7 @@ Run the following command to drop a UDF:
 DROP [GLOBAL] FUNCTION <function_name>(arg_type [, ...]);
 ```
 
-For more information, see [DROP FUNCTION](../sql-statements/data-definition/DROP_FUNCTION.md).
+For more information, see [DROP FUNCTION](../sql-statements/Function/DROP_FUNCTION.md).
 
 ## Mapping between SQL data types and Java data types
 
diff --git a/docs/en/sql-reference/sql-functions/Lambda_expression.md b/docs/en/sql-reference/sql-functions/Lambda_expression.md
index 90d5f6ac385ec3..2b33783f023d1d 100644
--- a/docs/en/sql-reference/sql-functions/Lambda_expression.md
+++ b/docs/en/sql-reference/sql-functions/Lambda_expression.md
@@ -1,5 +1,6 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
+sidebar_position: 0.9
 ---
 
 # Lambda expression
diff --git a/docs/en/sql-reference/sql-functions/Python_UDF.md b/docs/en/sql-reference/sql-functions/Python_UDF.md
index 7c02670117ceb3..cd2fa50decd562 100644
--- a/docs/en/sql-reference/sql-functions/Python_UDF.md
+++ b/docs/en/sql-reference/sql-functions/Python_UDF.md
@@ -1,5 +1,6 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
+sidebar_position: 0.9
 ---
 
 # Python UDF
diff --git a/docs/en/sql-reference/sql-functions/README.md b/docs/en/sql-reference/sql-functions/README.md
new file mode 100644
index 00000000000000..2e1883a0232e0a
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/README.md
@@ -0,0 +1,12 @@
+---
+displayed_sidebar: docs
+sidebar_position: 0.5
+---
+
+# Functions
+
+import DocCardList from '@theme/DocCardList';
+
+StarRocks offers a rich set of functions to facilitate data queries and analysis. In addition to commonly used functions, StarRocks supports semi-structured functions such as ARRAY, JSON, MAP, and STRUCT functions. It also supports higher-order [Lambda functions](Lambda_expression.md). If these functions cannot meet your business requirements, you can use [Java UDF](JAVA_UDF.md) to compile functions. StarRocks also provides [Hive Bitmap UDFs](hive_bitmap_udf.md). You can generate Bitmap data in Hive and then load Bitmap into StarRocks. You can also export the Bitmap data generated in StarRocks to Hive for other systems to use.
+
+<DocCardList />
diff --git a/docs/en/sql-reference/sql-functions/Window_function.md b/docs/en/sql-reference/sql-functions/Window_function.md
index 16da0727a1fef2..a0d42b57d82192 100644
--- a/docs/en/sql-reference/sql-functions/Window_function.md
+++ b/docs/en/sql-reference/sql-functions/Window_function.md
@@ -1,6 +1,7 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 keywords: ['analytic']
+sidebar_position: 0.9
 ---
 
 # Window functions
diff --git a/docs/en/sql-reference/sql-functions/_category_.yml b/docs/en/sql-reference/sql-functions/_category_.yml
new file mode 100644
index 00000000000000..9541a950886706
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/_category_.yml
@@ -0,0 +1,7 @@
+position: 10 # float position is supported
+label: 'SQL Functions'
+collapsible: true
+collapsed: true
+link:
+  type: doc
+  id: README
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/_category_.yml b/docs/en/sql-reference/sql-functions/aggregate-functions/_category_.yml
new file mode 100644
index 00000000000000..f4729c708013db
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Aggregate'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/any_value.md b/docs/en/sql-reference/sql-functions/aggregate-functions/any_value.md
index 654c10077e27d9..ea9769b791b680 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/any_value.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/any_value.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # any_value
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/approx_count_distinct.md b/docs/en/sql-reference/sql-functions/aggregate-functions/approx_count_distinct.md
index db00713e3b5a99..359ce2b666b12e 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/approx_count_distinct.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/approx_count_distinct.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # approx_count_distinct
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/approx_top_k.md b/docs/en/sql-reference/sql-functions/aggregate-functions/approx_top_k.md
index 9989dd3dd452e2..3b8e9d581d30b8 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/approx_top_k.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/approx_top_k.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # approx_top_k
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/avg.md b/docs/en/sql-reference/sql-functions/aggregate-functions/avg.md
index 7925a6681e4e37..61851f108f3caa 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/avg.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/avg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # avg
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/bitmap.md b/docs/en/sql-reference/sql-functions/aggregate-functions/bitmap.md
index d97cbcf138695b..ae7d4aaf293c3d 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/bitmap.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/corr.md b/docs/en/sql-reference/sql-functions/aggregate-functions/corr.md
index b1d97e9cd1de13..751fa1f8866e5a 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/corr.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/corr.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # corr
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/count.md b/docs/en/sql-reference/sql-functions/aggregate-functions/count.md
index 1bf0a89ad8f9e0..44ac5c27340d56 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/count.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/count.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/count_if.md b/docs/en/sql-reference/sql-functions/aggregate-functions/count_if.md
index 790f2212e0b100..c0e6b6c24d66f7 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/count_if.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/count_if.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # count_if
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/covar_pop.md b/docs/en/sql-reference/sql-functions/aggregate-functions/covar_pop.md
index 8ba9b1e02655d7..48f96967e13e05 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/covar_pop.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/covar_pop.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # covar_pop
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/covar_samp.md b/docs/en/sql-reference/sql-functions/aggregate-functions/covar_samp.md
index c7deb3a2a2b66f..f8a5462836cdb5 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/covar_samp.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/covar_samp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # covar_samp
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/group_concat.md b/docs/en/sql-reference/sql-functions/aggregate-functions/group_concat.md
index 86a79ba9725bd7..2269c849cbac57 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/group_concat.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/group_concat.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # group_concat
@@ -33,7 +33,7 @@ VARCHAR GROUP_CONCAT([DISTINCT] expr [,expr ...]
 
 Returns a string value for each group and returns NULL if there are no non-NULL values.
 
-You can limit the length of the string returned by group_concat by setting the [session variable](../../../reference/System_variable.md) `group_concat_max_len`, which defaults to 1024. Minimum value: 4. Unit: characters.
+You can limit the length of the string returned by group_concat by setting the [session variable](../../System_variable.md) `group_concat_max_len`, which defaults to 1024. Minimum value: 4. Unit: characters.
 
 Example:
 
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/grouping.md b/docs/en/sql-reference/sql-functions/aggregate-functions/grouping.md
index 6fe0cd0b8faa41..8dcfd4b7860b72 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/grouping.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/grouping.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # grouping
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/grouping_id.md b/docs/en/sql-reference/sql-functions/aggregate-functions/grouping_id.md
index bc5fc7dfc376a3..ac7ca6e98360b0 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/grouping_id.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/grouping_id.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/hll_raw_agg.md b/docs/en/sql-reference/sql-functions/aggregate-functions/hll_raw_agg.md
index e53af36f333a58..6238efc3942e08 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/hll_raw_agg.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/hll_raw_agg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # hll_raw_agg
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/hll_union.md b/docs/en/sql-reference/sql-functions/aggregate-functions/hll_union.md
index 63480d6e0a40e9..cb3b14ff6e4f2f 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/hll_union.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/hll_union.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/hll_union_agg.md b/docs/en/sql-reference/sql-functions/aggregate-functions/hll_union_agg.md
index 18fc0f7fe50397..1ce5b70fe9eb23 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/hll_union_agg.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/hll_union_agg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # hll_union_agg
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/mann_whitney_u_test.md b/docs/en/sql-reference/sql-functions/aggregate-functions/mann_whitney_u_test.md
new file mode 100644
index 00000000000000..875949d7be2b83
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/mann_whitney_u_test.md
@@ -0,0 +1,125 @@
+---
+displayed_sidebar: "docs"
+---
+
+# mann_whitney_u_test
+
+## Description
+
+Performs the Mann-Whitney rank test on samples derived from two populations. The Mann-Whitney U test is a non-parametric test that can be used to determine if two populations were selected from the same distribution.
+
+## Syntax
+
+```Haskell
+MANN_WHITNEY_U_TEST (sample_data, sample_treatment[, alternative[, continuity_correction]])
+```
+
+## Parameters
+
+- `sample_data`: the value of sample data. It must be of numeric data types.
+
+- `sample_treatment`: the index of sample data. where each element indicates the treatment group that the corresponding sample belongs to. The values should be of type boolean, with `false` representing the first group and `true` representing the second group.
+
+- `alternative` (optional): A const string specifying the alternative hypothesis. It can be one of the following: 
+- - 'two-sided': The default value. Tests whether the means of the two populations are different.
+- - 'less': Tests whether the mean of the first population is less than the mean of the second population.
+- - 'greater': Tests whether the mean of the first population is greater than the mean of the second population.
+
+- `continuity_correction` (optional): A const boolean value indicating whether to apply a continuity correction. The continuity correction adjusts the U statistic by `0.5` towards the mean of the U distribution, which can improve the accuracy of the test for small sample sizes. The default value is `true`.
+
+## Return value
+
+The function returns a json array containing the following two elements:
+
+The Mann-Whitney U statistic and the p-value associated with the test.
+
+## Usage notes
+
+This function ignores NULLs.
+
+## Examples
+
+Suppose there is a table named `testing_data` with the following data.
+
+```sql
+create table testing_data (
+    id int, 
+    score int, 
+    treatment boolean
+)
+properties(
+    "replication_num" = "1"
+);
+
+insert into testing_data values 
+    (1, 80, false), 
+    (2, 100, false), 
+    (3, NULL, false), 
+    (4, 60, true), 
+    (5, 70, true), 
+    (6, 85, true);
+```
+
+
+```Plain
+select * from testing_data;
++------+-------+-----------+
+| id   | score | treatment |
++------+-------+-----------+
+|    1 |    80 |         0 |
+|    2 |   100 |         0 |
+|    3 |  NULL |         0 |
+|    4 |    60 |         1 |
+|    5 |    70 |         1 |
+|    6 |    85 |         1 |
++------+-------+-----------+
+```
+
+Query:
+
+```SQL
+SELECT MANN_WHITNEY_U_TEST(score, treatment) FROM testing_data;
+```
+
+Result:
+
+```Plain
++---------------------------------------+
+| mann_whitney_u_test(score, treatment) |
++---------------------------------------+
+| [5, 0.38647623077123283]              |
++---------------------------------------+
+```
+
+Query:
+
+```SQL
+SELECT MANN_WHITNEY_U_TEST(score, treatment, 'less') FROM testing_data;
+```
+
+Result:
+
+```Plain
++-----------------------------------------------+
+| mann_whitney_u_test(score, treatment, 'less') |
++-----------------------------------------------+
+| [5, 0.9255426634106172]                       |
++-----------------------------------------------+
+```
+
+
+Query:
+
+```SQL
+SELECT MANN_WHITNEY_U_TEST(score, treatment, 'two-sided', 0) FROM testing_data;
+```
+
+Result:
+
+```Plain
++-------------------------------------------------------+
+| mann_whitney_u_test(score, treatment, 'two-sided', 0) |
++-------------------------------------------------------+
+| [5, 0.2482130789899235]                               |
++-------------------------------------------------------+
+```
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/max.md b/docs/en/sql-reference/sql-functions/aggregate-functions/max.md
index 71d07f24a39fc2..3b83304bda3ddb 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/max.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/max.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # max
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/max_by.md b/docs/en/sql-reference/sql-functions/aggregate-functions/max_by.md
index 7a74d32e88f9b6..f3037c57647f96 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/max_by.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/max_by.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # max_by
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/min.md b/docs/en/sql-reference/sql-functions/aggregate-functions/min.md
index d4a784571cad69..c70e190265b326 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/min.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/min.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # min
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/min_by.md b/docs/en/sql-reference/sql-functions/aggregate-functions/min_by.md
index 59164317cfb210..e0590a0de46815 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/min_by.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/min_by.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # min_by
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/multi_distinct_count.md b/docs/en/sql-reference/sql-functions/aggregate-functions/multi_distinct_count.md
index 6d8a890e2445e7..d44936bd2293e6 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/multi_distinct_count.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/multi_distinct_count.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # multi_distinct_count
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/multi_distinct_sum.md b/docs/en/sql-reference/sql-functions/aggregate-functions/multi_distinct_sum.md
index d6e6ff4abc00ff..051b4668bd043d 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/multi_distinct_sum.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/multi_distinct_sum.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # multi_distinct_sum
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_approx.md b/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_approx.md
index 2681b897fa7eeb..69739128240817 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_approx.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_approx.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # percentile_approx
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_cont.md b/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_cont.md
index 1ad5d1a5ff9fd3..ebf46624900918 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_cont.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_cont.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # percentile_cont
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_disc.md b/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_disc.md
index 347032cf56621b..e376680eac31fc 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_disc.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_disc.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # percentile_disc
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_disc_lc.md b/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_disc_lc.md
index 549f6e18f04476..59def9f668e194 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_disc_lc.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/percentile_disc_lc.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # percentile_disc_lc
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/retention.md b/docs/en/sql-reference/sql-functions/aggregate-functions/retention.md
index ef5c32b3c6eae8..a69b38bb15d8d8 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/retention.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/retention.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # retention
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/std.md b/docs/en/sql-reference/sql-functions/aggregate-functions/std.md
index 799ca48ba6f49e..915dd52c3a886d 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/std.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/std.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # std
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/stddev.md b/docs/en/sql-reference/sql-functions/aggregate-functions/stddev.md
index 4ab294f9864b2f..1ca7f451887133 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/stddev.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/stddev.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/stddev_samp.md b/docs/en/sql-reference/sql-functions/aggregate-functions/stddev_samp.md
index 3aebef6ddb5643..e75938f46b4bb0 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/stddev_samp.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/stddev_samp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # stddev_samp
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/sum.md b/docs/en/sql-reference/sql-functions/aggregate-functions/sum.md
index 174231cbc57bdf..beb81182a30552 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/sum.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/sum.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # sum
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/var_samp.md b/docs/en/sql-reference/sql-functions/aggregate-functions/var_samp.md
index f3bc0883706c8d..5cae5f2bbbb73b 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/var_samp.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/var_samp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # var_samp,variance_samp
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/variance.md b/docs/en/sql-reference/sql-functions/aggregate-functions/variance.md
index 50d2e4fb3c3c59..9604a19544ceac 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/variance.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/variance.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # variance,var_pop,variance_pop
diff --git a/docs/en/sql-reference/sql-functions/aggregate-functions/window_funnel.md b/docs/en/sql-reference/sql-functions/aggregate-functions/window_funnel.md
index 23333b7f560162..2514b8a35b852d 100644
--- a/docs/en/sql-reference/sql-functions/aggregate-functions/window_funnel.md
+++ b/docs/en/sql-reference/sql-functions/aggregate-functions/window_funnel.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # window_funnel
diff --git a/docs/en/sql-reference/sql-functions/array-functions/_category_.yml b/docs/en/sql-reference/sql-functions/array-functions/_category_.yml
new file mode 100644
index 00000000000000..c24a753ad6cf55
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/array-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Array'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/array-functions/all_match.md b/docs/en/sql-reference/sql-functions/array-functions/all_match.md
index 4aa3b0865b767a..844ffdde8aa317 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/all_match.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/all_match.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # all_match
diff --git a/docs/en/sql-reference/sql-functions/array-functions/any_match.md b/docs/en/sql-reference/sql-functions/array-functions/any_match.md
index 83ef9777a23251..33ba7032d99658 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/any_match.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/any_match.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # any_match
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_agg.md b/docs/en/sql-reference/sql-functions/array-functions/array_agg.md
index 8851f7ff7cb542..1ba3464d78354c 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_agg.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_agg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_agg
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_append.md b/docs/en/sql-reference/sql-functions/array-functions/array_append.md
index 68036da0761337..dc91b43ce76a9f 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_append.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_append.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_append
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_avg.md b/docs/en/sql-reference/sql-functions/array-functions/array_avg.md
index 9363a7052a6689..e7767f92094af7 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_avg.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_avg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_avg
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_concat.md b/docs/en/sql-reference/sql-functions/array-functions/array_concat.md
index 07304328bc7b86..7bb84e57277007 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_concat.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_concat.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_concat
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_contains.md b/docs/en/sql-reference/sql-functions/array-functions/array_contains.md
index db658ca21da243..e10c6213cdef6e 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_contains.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_contains.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_contains
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_contains_all.md b/docs/en/sql-reference/sql-functions/array-functions/array_contains_all.md
index a9cdd6ff440638..87bec8cf4d398b 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_contains_all.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_contains_all.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_contains_all
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_contains_seq.md b/docs/en/sql-reference/sql-functions/array-functions/array_contains_seq.md
index 53983da25f53c7..500da3d30e9bdd 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_contains_seq.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_contains_seq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_contains_seq
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_cum_sum.md b/docs/en/sql-reference/sql-functions/array-functions/array_cum_sum.md
index 053f3bce58232a..004344b73b2c32 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_cum_sum.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_cum_sum.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_cum_sum
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_difference.md b/docs/en/sql-reference/sql-functions/array-functions/array_difference.md
index 346ac35ac3dacb..73ee5244ac4bdf 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_difference.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_difference.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_difference
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_distinct.md b/docs/en/sql-reference/sql-functions/array-functions/array_distinct.md
index 427c4c6162b0d8..856d4f4d986d3c 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_distinct.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_distinct.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_distinct
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_filter.md b/docs/en/sql-reference/sql-functions/array-functions/array_filter.md
index 84bb4d00c778ac..e21e549f7f56a8 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_filter.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_filter.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_filter
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_generate.md b/docs/en/sql-reference/sql-functions/array-functions/array_generate.md
index 1e49e9775fcc8b..cd857d35e80695 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_generate.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_generate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_generate
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_intersect.md b/docs/en/sql-reference/sql-functions/array-functions/array_intersect.md
index 1e6ce97105c9d2..9fbb0189941091 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_intersect.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_intersect.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_intersect
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_join.md b/docs/en/sql-reference/sql-functions/array-functions/array_join.md
index e9990180aa5491..3b62e8d7c267b5 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_join.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_join.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_join
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_length.md b/docs/en/sql-reference/sql-functions/array-functions/array_length.md
index 8e52fa10cc74d8..26112bb001c477 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_length.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_length.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_length
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_map.md b/docs/en/sql-reference/sql-functions/array-functions/array_map.md
index ab9dbdd3f73165..040fa650d4e118 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_map.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_map.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_map
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_max.md b/docs/en/sql-reference/sql-functions/array-functions/array_max.md
index e96b325a675326..759957cbdea2f4 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_max.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_max.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_max
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_min.md b/docs/en/sql-reference/sql-functions/array-functions/array_min.md
index 1ecf4371121806..e3393bfc2836d4 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_min.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_min.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_min
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_position.md b/docs/en/sql-reference/sql-functions/array-functions/array_position.md
index 784f2896268e5e..a0b3703de0e979 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_position.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_position.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_position
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_remove.md b/docs/en/sql-reference/sql-functions/array-functions/array_remove.md
index 4e09a00580c212..f0a5774061b1cf 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_remove.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_remove.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_remove
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_repeat.md b/docs/en/sql-reference/sql-functions/array-functions/array_repeat.md
index 31f65d798505a1..b73035be14c0da 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_repeat.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_repeat.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_repeat
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_slice.md b/docs/en/sql-reference/sql-functions/array-functions/array_slice.md
index 19fd642ef626d8..bcf2c3b0f8bb1d 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_slice.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_slice.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_slice
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_sort.md b/docs/en/sql-reference/sql-functions/array-functions/array_sort.md
index 807343c123784d..28d8c8fa28c35b 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_sort.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_sort.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_sort
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_sortby.md b/docs/en/sql-reference/sql-functions/array-functions/array_sortby.md
index f243f79d177e73..048c2e7ad3c204 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_sortby.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_sortby.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_sortby
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_sum.md b/docs/en/sql-reference/sql-functions/array-functions/array_sum.md
index b153958e5380ae..1b8067d204764c 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_sum.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_sum.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_sum
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_to_bitmap.md b/docs/en/sql-reference/sql-functions/array-functions/array_to_bitmap.md
index ba495e4924f91c..374d2209fb2cef 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_to_bitmap.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_to_bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_to_bitmap
diff --git a/docs/en/sql-reference/sql-functions/array-functions/array_unique_agg.md b/docs/en/sql-reference/sql-functions/array-functions/array_unique_agg.md
index 56c95233d14de8..feef244ea74035 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/array_unique_agg.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/array_unique_agg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # array_unique_agg
diff --git a/docs/en/sql-reference/sql-functions/array-functions/arrays_overlap.md b/docs/en/sql-reference/sql-functions/array-functions/arrays_overlap.md
index b4768a16b05726..0043a336ebd5da 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/arrays_overlap.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/arrays_overlap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # arrays_overlap
diff --git a/docs/en/sql-reference/sql-functions/array-functions/cardinality.md b/docs/en/sql-reference/sql-functions/array-functions/cardinality.md
index b9375515e3b589..3e580aa305abdc 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/cardinality.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/cardinality.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # cardinality
diff --git a/docs/en/sql-reference/sql-functions/array-functions/element_at.md b/docs/en/sql-reference/sql-functions/array-functions/element_at.md
index 151a7bd13fb218..6d6756882640f3 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/element_at.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/element_at.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # element_at
diff --git a/docs/en/sql-reference/sql-functions/array-functions/reverse.md b/docs/en/sql-reference/sql-functions/array-functions/reverse.md
index f75790a8f3ca7a..4460443fc761fa 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/reverse.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/reverse.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # reverse
diff --git a/docs/en/sql-reference/sql-functions/array-functions/unnest.md b/docs/en/sql-reference/sql-functions/array-functions/unnest.md
index 5600dd7316500a..82d700e342b642 100644
--- a/docs/en/sql-reference/sql-functions/array-functions/unnest.md
+++ b/docs/en/sql-reference/sql-functions/array-functions/unnest.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # unnest
diff --git a/docs/en/sql-reference/sql-functions/binary-functions/_category_.yml b/docs/en/sql-reference/sql-functions/binary-functions/_category_.yml
new file mode 100644
index 00000000000000..82fd779dce11d4
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/binary-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Binary'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/binary-functions/from_binary.md b/docs/en/sql-reference/sql-functions/binary-functions/from_binary.md
index 36706747f321d6..f5ac9d93e67bee 100644
--- a/docs/en/sql-reference/sql-functions/binary-functions/from_binary.md
+++ b/docs/en/sql-reference/sql-functions/binary-functions/from_binary.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # from_binary
diff --git a/docs/en/sql-reference/sql-functions/binary-functions/to_binary.md b/docs/en/sql-reference/sql-functions/binary-functions/to_binary.md
index 74e16f51a63030..c040cbbd68d63e 100644
--- a/docs/en/sql-reference/sql-functions/binary-functions/to_binary.md
+++ b/docs/en/sql-reference/sql-functions/binary-functions/to_binary.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # to_binary
diff --git a/docs/en/sql-reference/sql-functions/bit-functions/_category_.yml b/docs/en/sql-reference/sql-functions/bit-functions/_category_.yml
new file mode 100644
index 00000000000000..2b97cf60922fef
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/bit-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Bit'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/bit-functions/bit_shift_left.md b/docs/en/sql-reference/sql-functions/bit-functions/bit_shift_left.md
index 050da7e43aaa6f..163c1a5caa3ef5 100644
--- a/docs/en/sql-reference/sql-functions/bit-functions/bit_shift_left.md
+++ b/docs/en/sql-reference/sql-functions/bit-functions/bit_shift_left.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bit_shift_left
diff --git a/docs/en/sql-reference/sql-functions/bit-functions/bit_shift_right.md b/docs/en/sql-reference/sql-functions/bit-functions/bit_shift_right.md
index 48b20f89ab69c8..88540909ddcad7 100644
--- a/docs/en/sql-reference/sql-functions/bit-functions/bit_shift_right.md
+++ b/docs/en/sql-reference/sql-functions/bit-functions/bit_shift_right.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bit_shift_right_logical
diff --git a/docs/en/sql-reference/sql-functions/bit-functions/bit_shift_right_logical.md b/docs/en/sql-reference/sql-functions/bit-functions/bit_shift_right_logical.md
index d06394ce1b28b6..65da68fee756d5 100644
--- a/docs/en/sql-reference/sql-functions/bit-functions/bit_shift_right_logical.md
+++ b/docs/en/sql-reference/sql-functions/bit-functions/bit_shift_right_logical.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bit_shift_right
diff --git a/docs/en/sql-reference/sql-functions/bit-functions/bitand.md b/docs/en/sql-reference/sql-functions/bit-functions/bitand.md
index e7ed5ea817cea2..b7f8972fc3df5a 100644
--- a/docs/en/sql-reference/sql-functions/bit-functions/bitand.md
+++ b/docs/en/sql-reference/sql-functions/bit-functions/bitand.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitand
diff --git a/docs/en/sql-reference/sql-functions/bit-functions/bitnot.md b/docs/en/sql-reference/sql-functions/bit-functions/bitnot.md
index 2e3f626eae1ed9..bb715d7c72c344 100644
--- a/docs/en/sql-reference/sql-functions/bit-functions/bitnot.md
+++ b/docs/en/sql-reference/sql-functions/bit-functions/bitnot.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitnot
diff --git a/docs/en/sql-reference/sql-functions/bit-functions/bitor.md b/docs/en/sql-reference/sql-functions/bit-functions/bitor.md
index e9154d89155c85..eecefff71ef7b8 100644
--- a/docs/en/sql-reference/sql-functions/bit-functions/bitor.md
+++ b/docs/en/sql-reference/sql-functions/bit-functions/bitor.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitor
diff --git a/docs/en/sql-reference/sql-functions/bit-functions/bitxor.md b/docs/en/sql-reference/sql-functions/bit-functions/bitxor.md
index 64f7fe8a2298ce..0a738b0344783c 100644
--- a/docs/en/sql-reference/sql-functions/bit-functions/bitxor.md
+++ b/docs/en/sql-reference/sql-functions/bit-functions/bitxor.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/_category_.yml b/docs/en/sql-reference/sql-functions/bitmap-functions/_category_.yml
new file mode 100644
index 00000000000000..2a6f9412bc5082
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Bitmap'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/base64_to_bitmap.md b/docs/en/sql-reference/sql-functions/bitmap-functions/base64_to_bitmap.md
index 87fb4553be50f3..632a7ab1e62d0c 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/base64_to_bitmap.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/base64_to_bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # base64_to_bitmap
@@ -48,7 +48,7 @@ Create a database named `bitmapdb` and a table named `bitmap`. Use Stream Load t
     );
     ```
 
-2. Use [Stream Load](../../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md) to import JSON data into `bitmap_table`.
+2. Use [Stream Load](../../sql-statements/loading_unloading/STREAM_LOAD.md) to import JSON data into `bitmap_table`.
 
     Suppose there is a JSON file named **simpledata**. This file has the following content and `userid` is a Base64-encoded string.
 
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_agg.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_agg.md
index 1f2bcfa1b39f79..023819fd680152 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_agg.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_agg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_agg
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_and.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_and.md
index ba46e81893f8a6..abdba85fe9f113 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_and.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_and.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_and
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_andnot.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_andnot.md
index 636a099d8afd11..75888fb047b4fa 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_andnot.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_andnot.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_andnot
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_contains.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_contains.md
index 739e5e62f647fc..66dad22aac481e 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_contains.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_contains.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_contains
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_count.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_count.md
index 471f79d90a6246..8966c4e39d5ec1 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_count.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_count.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_count
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_empty.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_empty.md
index c9fd41f0ce7b0f..39482ee59c05e2 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_empty.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_empty.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_empty
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_from_binary.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_from_binary.md
index 9544ad13f7ac20..0c2ab531813eee 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_from_binary.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_from_binary.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_from_binary
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_from_string.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_from_string.md
index 7de13bfd80d170..6d3d562611609a 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_from_string.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_from_string.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_from_string
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_has_any.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_has_any.md
index da56f80d2629e3..a568a4f7d548f7 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_has_any.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_has_any.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_has_any
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_hash.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_hash.md
index 41e35eb6b2691e..b0b1afa4abafea 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_hash.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_hash.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_hash
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_intersect.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_intersect.md
index 005c73cfd094fa..fb3590e9bd1f5f 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_intersect.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_intersect.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_intersect
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_max.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_max.md
index f2cdaedd4aec04..e178837ddd38a7 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_max.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_max.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_max
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_min.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_min.md
index 7d57d952af100e..6dd3a568dc1612 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_min.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_min.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_min
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_or.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_or.md
index 6ddae275a18996..20b0e9b9af9137 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_or.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_or.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_or
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_remove.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_remove.md
index d2ddd8598b2a25..19a0255ef27ae5 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_remove.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_remove.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_remove
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_subset_in_range.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_subset_in_range.md
index e359567db829f7..e9ec144e345d38 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_subset_in_range.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_subset_in_range.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_subset_in_range
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_subset_limit.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_subset_limit.md
index a5d16fd992634c..38f14726a00df1 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_subset_limit.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_subset_limit.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_subset_limit
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_array.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_array.md
index 37e3512c0050f7..e8246d5aa00776 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_array.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_array.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_to_array
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_base64.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_base64.md
index 284d1776a9165f..aaa26c163fd511 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_base64.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_base64.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_to_base64
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_binary.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_binary.md
index 3fb5324f9b6ab4..0f43ae3fba9953 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_binary.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_binary.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_to_binary
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_string.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_string.md
index 65f99a980ab50f..f30c2459c4606a 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_string.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_to_string.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_to_string
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_union.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_union.md
index 4f79c8ad38eeb5..494efdc6498bc4 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_union.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_union.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_union
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_union_count.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_union_count.md
index 9cf8dd150e2b02..85bfd0fb98caad 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_union_count.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_union_count.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_union_count
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_union_int.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_union_int.md
index 9daf8b9707e2bf..a5dbbda3d40634 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_union_int.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_union_int.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_union_int
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_xor.md b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_xor.md
index 188dea7f365b1f..092c91480f0b52 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_xor.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/bitmap_xor.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bitmap_xor
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/intersect_count.md b/docs/en/sql-reference/sql-functions/bitmap-functions/intersect_count.md
index bf516736303ace..a85add84ebc002 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/intersect_count.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/intersect_count.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # intersect_count
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/sub_bitmap.md b/docs/en/sql-reference/sql-functions/bitmap-functions/sub_bitmap.md
index 2e9700c4f932b4..dfec4138355ee8 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/sub_bitmap.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/sub_bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # sub_bitmap
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/subdivide_bitmap.md b/docs/en/sql-reference/sql-functions/bitmap-functions/subdivide_bitmap.md
index 4b6779ef2c4e73..daaa8b64fea6e4 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/subdivide_bitmap.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/subdivide_bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # subdivide_bitmap
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/to_bitmap.md b/docs/en/sql-reference/sql-functions/bitmap-functions/to_bitmap.md
index aed6a524d85c80..6a599339573298 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/to_bitmap.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/to_bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # to_bitmap
diff --git a/docs/en/sql-reference/sql-functions/bitmap-functions/unnest_bitmap.md b/docs/en/sql-reference/sql-functions/bitmap-functions/unnest_bitmap.md
index 7d0ccf355ab844..b2d67c1a770a85 100644
--- a/docs/en/sql-reference/sql-functions/bitmap-functions/unnest_bitmap.md
+++ b/docs/en/sql-reference/sql-functions/bitmap-functions/unnest_bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # unnest_bitmap
diff --git a/docs/en/sql-reference/sql-functions/cast.md b/docs/en/sql-reference/sql-functions/cast.md
index 0f326797d2c95f..fdd699539b412e 100644
--- a/docs/en/sql-reference/sql-functions/cast.md
+++ b/docs/en/sql-reference/sql-functions/cast.md
@@ -1,5 +1,6 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
+sidebar_position: 0.9
 ---
 
 # CAST
diff --git a/docs/en/sql-reference/sql-functions/condition-functions/_category_.yml b/docs/en/sql-reference/sql-functions/condition-functions/_category_.yml
new file mode 100644
index 00000000000000..0946216e77f455
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/condition-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Condition'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/condition-functions/case_when.md b/docs/en/sql-reference/sql-functions/condition-functions/case_when.md
index 93559994cd6c0c..457fdaf6b7bc24 100644
--- a/docs/en/sql-reference/sql-functions/condition-functions/case_when.md
+++ b/docs/en/sql-reference/sql-functions/condition-functions/case_when.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # case
diff --git a/docs/en/sql-reference/sql-functions/condition-functions/coalesce.md b/docs/en/sql-reference/sql-functions/condition-functions/coalesce.md
index 18fbf44c477743..17babf1953f683 100644
--- a/docs/en/sql-reference/sql-functions/condition-functions/coalesce.md
+++ b/docs/en/sql-reference/sql-functions/condition-functions/coalesce.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # coalesce
diff --git a/docs/en/sql-reference/sql-functions/condition-functions/if.md b/docs/en/sql-reference/sql-functions/condition-functions/if.md
index ee9965bf548005..dcb328ebd2944c 100644
--- a/docs/en/sql-reference/sql-functions/condition-functions/if.md
+++ b/docs/en/sql-reference/sql-functions/condition-functions/if.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # if
diff --git a/docs/en/sql-reference/sql-functions/condition-functions/ifnull.md b/docs/en/sql-reference/sql-functions/condition-functions/ifnull.md
index 9d1e2594aede69..674c480e60c5b9 100644
--- a/docs/en/sql-reference/sql-functions/condition-functions/ifnull.md
+++ b/docs/en/sql-reference/sql-functions/condition-functions/ifnull.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ifnull
diff --git a/docs/en/sql-reference/sql-functions/condition-functions/nullif.md b/docs/en/sql-reference/sql-functions/condition-functions/nullif.md
index f805077bb13206..73695868fd2d8a 100644
--- a/docs/en/sql-reference/sql-functions/condition-functions/nullif.md
+++ b/docs/en/sql-reference/sql-functions/condition-functions/nullif.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # nullif
diff --git a/docs/en/sql-reference/sql-functions/crytographic-functions/_category_.yml b/docs/en/sql-reference/sql-functions/crytographic-functions/_category_.yml
new file mode 100644
index 00000000000000..54ec65236c3b7e
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/crytographic-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Cryptographic'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/crytographic-functions/aes_decrypt.md b/docs/en/sql-reference/sql-functions/crytographic-functions/aes_decrypt.md
index da78be57cab425..b3c96fc6d2d32e 100644
--- a/docs/en/sql-reference/sql-functions/crytographic-functions/aes_decrypt.md
+++ b/docs/en/sql-reference/sql-functions/crytographic-functions/aes_decrypt.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # aes_decrypt
diff --git a/docs/en/sql-reference/sql-functions/crytographic-functions/aes_encrypt.md b/docs/en/sql-reference/sql-functions/crytographic-functions/aes_encrypt.md
index 220491bcf54a34..265c0995159823 100644
--- a/docs/en/sql-reference/sql-functions/crytographic-functions/aes_encrypt.md
+++ b/docs/en/sql-reference/sql-functions/crytographic-functions/aes_encrypt.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # aes_encrypt
diff --git a/docs/en/sql-reference/sql-functions/crytographic-functions/base64_decode_binary.md b/docs/en/sql-reference/sql-functions/crytographic-functions/base64_decode_binary.md
index 49a4c3f7069d9f..38266d28d26058 100644
--- a/docs/en/sql-reference/sql-functions/crytographic-functions/base64_decode_binary.md
+++ b/docs/en/sql-reference/sql-functions/crytographic-functions/base64_decode_binary.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # base64_decode_binary
diff --git a/docs/en/sql-reference/sql-functions/crytographic-functions/base64_decode_string.md b/docs/en/sql-reference/sql-functions/crytographic-functions/base64_decode_string.md
index cf72148d2744f1..1d9c2724379cf8 100644
--- a/docs/en/sql-reference/sql-functions/crytographic-functions/base64_decode_string.md
+++ b/docs/en/sql-reference/sql-functions/crytographic-functions/base64_decode_string.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # base64_decode_string
diff --git a/docs/en/sql-reference/sql-functions/crytographic-functions/from_base64.md b/docs/en/sql-reference/sql-functions/crytographic-functions/from_base64.md
index a44297da0dd3e6..74751979871c82 100644
--- a/docs/en/sql-reference/sql-functions/crytographic-functions/from_base64.md
+++ b/docs/en/sql-reference/sql-functions/crytographic-functions/from_base64.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # from_base64
diff --git a/docs/en/sql-reference/sql-functions/crytographic-functions/md5.md b/docs/en/sql-reference/sql-functions/crytographic-functions/md5.md
index 9822f2ebfc4964..a4c57c9c216d96 100644
--- a/docs/en/sql-reference/sql-functions/crytographic-functions/md5.md
+++ b/docs/en/sql-reference/sql-functions/crytographic-functions/md5.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # md5
diff --git a/docs/en/sql-reference/sql-functions/crytographic-functions/md5sum.md b/docs/en/sql-reference/sql-functions/crytographic-functions/md5sum.md
index d3667eb8b73f0e..43492ba9ad44b2 100644
--- a/docs/en/sql-reference/sql-functions/crytographic-functions/md5sum.md
+++ b/docs/en/sql-reference/sql-functions/crytographic-functions/md5sum.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # md5sum
diff --git a/docs/en/sql-reference/sql-functions/crytographic-functions/md5sum_numeric.md b/docs/en/sql-reference/sql-functions/crytographic-functions/md5sum_numeric.md
index 04962742b47edf..73038958e3380c 100644
--- a/docs/en/sql-reference/sql-functions/crytographic-functions/md5sum_numeric.md
+++ b/docs/en/sql-reference/sql-functions/crytographic-functions/md5sum_numeric.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # md5sum_numeric
diff --git a/docs/en/sql-reference/sql-functions/crytographic-functions/sha2.md b/docs/en/sql-reference/sql-functions/crytographic-functions/sha2.md
index bda5cd07bd270b..44598e0bbaba4c 100644
--- a/docs/en/sql-reference/sql-functions/crytographic-functions/sha2.md
+++ b/docs/en/sql-reference/sql-functions/crytographic-functions/sha2.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # sha2
diff --git a/docs/en/sql-reference/sql-functions/crytographic-functions/sm3.md b/docs/en/sql-reference/sql-functions/crytographic-functions/sm3.md
index 62fc6d7a5bbf55..ce72f0cfe83c0d 100644
--- a/docs/en/sql-reference/sql-functions/crytographic-functions/sm3.md
+++ b/docs/en/sql-reference/sql-functions/crytographic-functions/sm3.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # sm3
diff --git a/docs/en/sql-reference/sql-functions/crytographic-functions/to_base64.md b/docs/en/sql-reference/sql-functions/crytographic-functions/to_base64.md
index a9839e274f0050..1a9da93b857ce3 100644
--- a/docs/en/sql-reference/sql-functions/crytographic-functions/to_base64.md
+++ b/docs/en/sql-reference/sql-functions/crytographic-functions/to_base64.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # to_base64
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/_category_.yml b/docs/en/sql-reference/sql-functions/date-time-functions/_category_.yml
new file mode 100644
index 00000000000000..ae0b773cbde8e6
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Date and time'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/add_months.md b/docs/en/sql-reference/sql-functions/date-time-functions/add_months.md
index a3b97e3b294ff7..e34fc60dbd8988 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/add_months.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/add_months.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # add_months
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/adddate.md b/docs/en/sql-reference/sql-functions/date-time-functions/adddate.md
index 539621493bf6e1..62cb0e65b6284e 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/adddate.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/adddate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # adddate,date_add
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/convert_tz.md b/docs/en/sql-reference/sql-functions/date-time-functions/convert_tz.md
index 477d35e1c936ee..5a8f90cbda6845 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/convert_tz.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/convert_tz.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # convert_tz
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/curdate.md b/docs/en/sql-reference/sql-functions/date-time-functions/curdate.md
index a976035bb5f055..155e5719bc7f8d 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/curdate.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/curdate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # curdate,current_date
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/current_timestamp.md b/docs/en/sql-reference/sql-functions/date-time-functions/current_timestamp.md
index 0d14f99b256369..d3a44c7362448d 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/current_timestamp.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/current_timestamp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # current_timestamp
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/curtime.md b/docs/en/sql-reference/sql-functions/date-time-functions/curtime.md
index eccabaa0bf1b65..6c5fecfaff347d 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/curtime.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/curtime.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # curtime,current_time
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/date.md b/docs/en/sql-reference/sql-functions/date-time-functions/date.md
index 4cc003ca3727a2..39fb506f51770f 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/date.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/date.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # date
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/date_add.md b/docs/en/sql-reference/sql-functions/date-time-functions/date_add.md
index 81564988e42989..54422240499d34 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/date_add.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/date_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # date_add,adddate
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/date_diff.md b/docs/en/sql-reference/sql-functions/date-time-functions/date_diff.md
index b5cc8820ed5c05..832fa15b432beb 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/date_diff.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/date_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # date_diff
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/date_format.md b/docs/en/sql-reference/sql-functions/date-time-functions/date_format.md
index 48c001362732b8..1e8d27957be8c0 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/date_format.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/date_format.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # date_format
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/date_slice.md b/docs/en/sql-reference/sql-functions/date-time-functions/date_slice.md
index 5b099e70991d5d..154fb7bba553db 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/date_slice.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/date_slice.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # date_slice
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/date_sub.md b/docs/en/sql-reference/sql-functions/date-time-functions/date_sub.md
index 50ed8c389e4135..0fe75d8a2088fd 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/date_sub.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/date_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # date_sub,subdate
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/date_trunc.md b/docs/en/sql-reference/sql-functions/date-time-functions/date_trunc.md
index 5d54a0b48b83f2..4a35f8f3a67539 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/date_trunc.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/date_trunc.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # date_trunc
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/datediff.md b/docs/en/sql-reference/sql-functions/date-time-functions/datediff.md
index 29fc3920c89b2c..393cceda68ec1a 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/datediff.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/datediff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # datediff
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/day.md b/docs/en/sql-reference/sql-functions/date-time-functions/day.md
index a46460b5498b95..fb34d60abebf74 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/day.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/day.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # day
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/day_of_week_iso.md b/docs/en/sql-reference/sql-functions/date-time-functions/day_of_week_iso.md
index 38c6e78d5e81de..11efe059945df8 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/day_of_week_iso.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/day_of_week_iso.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # dayofweek_iso
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/dayname.md b/docs/en/sql-reference/sql-functions/date-time-functions/dayname.md
index 49ed0850608a93..4997a957cc2a85 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/dayname.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/dayname.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # dayname
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/dayofmonth.md b/docs/en/sql-reference/sql-functions/date-time-functions/dayofmonth.md
index 2507fba4cf530c..b24287ccfceed3 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/dayofmonth.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/dayofmonth.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # dayofmonth
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/dayofweek.md b/docs/en/sql-reference/sql-functions/date-time-functions/dayofweek.md
index 51bd56f10a246e..e45e1bbba7b0aa 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/dayofweek.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/dayofweek.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # dayofweek
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/dayofyear.md b/docs/en/sql-reference/sql-functions/date-time-functions/dayofyear.md
index a5c0b14727464c..3b090eb7aa7ad2 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/dayofyear.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/dayofyear.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # dayofyear
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/days_add.md b/docs/en/sql-reference/sql-functions/date-time-functions/days_add.md
index fa5b4867048399..7613d1e57a9dc3 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/days_add.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/days_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # days_add
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/days_diff.md b/docs/en/sql-reference/sql-functions/date-time-functions/days_diff.md
index e3d21470e147a8..bcd493151cadd2 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/days_diff.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/days_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # days_diff
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/days_sub.md b/docs/en/sql-reference/sql-functions/date-time-functions/days_sub.md
index 7f71a30659678a..303cce3bd955dc 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/days_sub.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/days_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # days_sub
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/from_days.md b/docs/en/sql-reference/sql-functions/date-time-functions/from_days.md
index c708723ac25ce4..0280862f2bc157 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/from_days.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/from_days.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # from_days
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/from_unixtime.md b/docs/en/sql-reference/sql-functions/date-time-functions/from_unixtime.md
index 785ba8f1200513..84bdba97f3e03a 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/from_unixtime.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/from_unixtime.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # from_unixtime
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/hour.md b/docs/en/sql-reference/sql-functions/date-time-functions/hour.md
index 515f9a664dbd13..56671c80876609 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/hour.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/hour.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # hour
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/hours_add.md b/docs/en/sql-reference/sql-functions/date-time-functions/hours_add.md
index 8e3ef324a4ebf3..df64a1f791af0a 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/hours_add.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/hours_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # hours_add
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/hours_diff.md b/docs/en/sql-reference/sql-functions/date-time-functions/hours_diff.md
index bdc27baea41553..6352f64e25e91f 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/hours_diff.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/hours_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # hours_diff
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/hours_sub.md b/docs/en/sql-reference/sql-functions/date-time-functions/hours_sub.md
index 1a4c74dfc055dd..5ab8bc334674a4 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/hours_sub.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/hours_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # hours_sub
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/jodatime_format.md b/docs/en/sql-reference/sql-functions/date-time-functions/jodatime_format.md
index e14f8c750d6659..a4a2e659015c52 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/jodatime_format.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/jodatime_format.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # jodatime_format
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/last_day.md b/docs/en/sql-reference/sql-functions/date-time-functions/last_day.md
index b5e52db22fd562..0ccd2db93a34c9 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/last_day.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/last_day.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # last_day
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/makedate.md b/docs/en/sql-reference/sql-functions/date-time-functions/makedate.md
index 1d3f6e2ea319ba..55c9cb2006cf7e 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/makedate.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/makedate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # makedate
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/microseconds_add.md b/docs/en/sql-reference/sql-functions/date-time-functions/microseconds_add.md
index bb4bcf2fad22da..0ae8faf05380da 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/microseconds_add.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/microseconds_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # microseconds_add
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/microseconds_sub.md b/docs/en/sql-reference/sql-functions/date-time-functions/microseconds_sub.md
index 7c6fd6d95fd58e..a5e1f38a576d37 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/microseconds_sub.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/microseconds_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # microseconds_sub
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/milliseconds_diff.md b/docs/en/sql-reference/sql-functions/date-time-functions/milliseconds_diff.md
index 2f8e2402c9b1e0..28aca6711ceda6 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/milliseconds_diff.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/milliseconds_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # milliseconds_diff
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/minute.md b/docs/en/sql-reference/sql-functions/date-time-functions/minute.md
index a9faf4747319ad..497df473b41f23 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/minute.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/minute.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # minute
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/minutes_add.md b/docs/en/sql-reference/sql-functions/date-time-functions/minutes_add.md
index 8e10a9a2c53898..4837e4ef39ec36 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/minutes_add.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/minutes_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # minutes_add
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/minutes_diff.md b/docs/en/sql-reference/sql-functions/date-time-functions/minutes_diff.md
index 13cda7b0d7cf2f..a891aa5314d85f 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/minutes_diff.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/minutes_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # minutes_diff
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/minutes_sub.md b/docs/en/sql-reference/sql-functions/date-time-functions/minutes_sub.md
index 92671f918dfbf0..0b81ce40fac5e3 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/minutes_sub.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/minutes_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # minutes_sub
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/month.md b/docs/en/sql-reference/sql-functions/date-time-functions/month.md
index 7933b6f19dd03b..97c50a41cd4d72 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/month.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/month.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # month
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/monthname.md b/docs/en/sql-reference/sql-functions/date-time-functions/monthname.md
index 5755e7a6148e64..1642cf3ee1cd58 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/monthname.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/monthname.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # monthname
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/months_add.md b/docs/en/sql-reference/sql-functions/date-time-functions/months_add.md
index 2ac1ace418aa6f..2f47f78454c009 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/months_add.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/months_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # months_add
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/months_diff.md b/docs/en/sql-reference/sql-functions/date-time-functions/months_diff.md
index 06bb1e3077a79f..f0b0a53443c8b8 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/months_diff.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/months_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # months_diff
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/months_sub.md b/docs/en/sql-reference/sql-functions/date-time-functions/months_sub.md
index 477581ae9debcb..4805dc46d59b85 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/months_sub.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/months_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # months_sub
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/next_day.md b/docs/en/sql-reference/sql-functions/date-time-functions/next_day.md
index a94dad44e8edb6..e3849eaa7a777f 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/next_day.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/next_day.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # next_day
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/now.md b/docs/en/sql-reference/sql-functions/date-time-functions/now.md
index 0108b4fddc31a6..b1efe22f337e4e 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/now.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/now.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # now, current_timestamp, localtime, localtimestamp
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/previous_day.md b/docs/en/sql-reference/sql-functions/date-time-functions/previous_day.md
index 53a5f0c20f9ae7..092ecc46a3c51f 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/previous_day.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/previous_day.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # previous_day
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/quarter.md b/docs/en/sql-reference/sql-functions/date-time-functions/quarter.md
index da4f3b67f5ef39..39dc341a942b18 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/quarter.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/quarter.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # quarter
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/second.md b/docs/en/sql-reference/sql-functions/date-time-functions/second.md
index b9e6375faf47d9..2df9e978a6ece8 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/second.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/second.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # second
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/seconds_add.md b/docs/en/sql-reference/sql-functions/date-time-functions/seconds_add.md
index 6b68d03cf3c9c6..80a97d6ce1ca4b 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/seconds_add.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/seconds_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # seconds_add
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/seconds_diff.md b/docs/en/sql-reference/sql-functions/date-time-functions/seconds_diff.md
index 0d2f6a6516d29b..b40e8b8f63f31c 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/seconds_diff.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/seconds_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # seconds_diff
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/seconds_sub.md b/docs/en/sql-reference/sql-functions/date-time-functions/seconds_sub.md
index abc9f962717490..f9db77cc1a611e 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/seconds_sub.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/seconds_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # seconds_sub
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/str2date.md b/docs/en/sql-reference/sql-functions/date-time-functions/str2date.md
index 36b3b9d39e7adf..eb6d5c00e6d485 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/str2date.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/str2date.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # str2date
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/str_to_date.md b/docs/en/sql-reference/sql-functions/date-time-functions/str_to_date.md
index 46a0ab5c25213b..4b5097d2c040f3 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/str_to_date.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/str_to_date.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # str_to_date
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/str_to_jodatime.md b/docs/en/sql-reference/sql-functions/date-time-functions/str_to_jodatime.md
index 3be76e82506839..b4a1c0dc7d676b 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/str_to_jodatime.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/str_to_jodatime.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # str_to_jodatime
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/time_slice.md b/docs/en/sql-reference/sql-functions/date-time-functions/time_slice.md
index f6e56e6c62c0f6..4154478232d7fd 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/time_slice.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/time_slice.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # time_slice
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/time_to_sec.md b/docs/en/sql-reference/sql-functions/date-time-functions/time_to_sec.md
index 0a0d82c459f11d..fccfdad72dc609 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/time_to_sec.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/time_to_sec.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # time_to_sec
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/timediff.md b/docs/en/sql-reference/sql-functions/date-time-functions/timediff.md
index b3a55ad12c636c..98279d72d2d43b 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/timediff.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/timediff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # timediff
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/timestamp.md b/docs/en/sql-reference/sql-functions/date-time-functions/timestamp.md
index 1d6e87fc99bab4..36104099703aeb 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/timestamp.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/timestamp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # timestamp
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/timestampadd.md b/docs/en/sql-reference/sql-functions/date-time-functions/timestampadd.md
index d7302d5bae31fa..8c8b868f26ff17 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/timestampadd.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/timestampadd.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # timestampadd
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/timestampdiff.md b/docs/en/sql-reference/sql-functions/date-time-functions/timestampdiff.md
index 394f99a73fc7fe..e23a85d73e96af 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/timestampdiff.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/timestampdiff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # timestampdiff
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/to_date.md b/docs/en/sql-reference/sql-functions/date-time-functions/to_date.md
index eac769d7f3a902..2131543428f27b 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/to_date.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/to_date.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # to_date
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/to_days.md b/docs/en/sql-reference/sql-functions/date-time-functions/to_days.md
index 38d1cf8a8b34c7..24ed742fd38d5b 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/to_days.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/to_days.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # to_days
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/to_iso8601.md b/docs/en/sql-reference/sql-functions/date-time-functions/to_iso8601.md
index fe701e3812daea..efac050ef78ae9 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/to_iso8601.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/to_iso8601.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # to_iso8601
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/to_tera_date.md b/docs/en/sql-reference/sql-functions/date-time-functions/to_tera_date.md
index 12d453ed633386..b9033a10218f65 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/to_tera_date.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/to_tera_date.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # to_tera_date
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/to_tera_timestamp.md b/docs/en/sql-reference/sql-functions/date-time-functions/to_tera_timestamp.md
index 158bd3db6f7807..b651180bbbe75c 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/to_tera_timestamp.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/to_tera_timestamp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # to_tera_timestamp
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/unix_timestamp.md b/docs/en/sql-reference/sql-functions/date-time-functions/unix_timestamp.md
index f085fe624564b2..936225f5bcf59b 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/unix_timestamp.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/unix_timestamp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # unix_timestamp
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/utc_time.md b/docs/en/sql-reference/sql-functions/date-time-functions/utc_time.md
index 125df6b72da576..b0fe0af99c58f7 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/utc_time.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/utc_time.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # utc_time
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/utc_timestamp.md b/docs/en/sql-reference/sql-functions/date-time-functions/utc_timestamp.md
index cc02e469147662..02f399680b55f0 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/utc_timestamp.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/utc_timestamp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # utc_timestamp
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/week.md b/docs/en/sql-reference/sql-functions/date-time-functions/week.md
index 5bd6b99f67cc2d..6c44643c0e49ec 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/week.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/week.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # week
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/week_iso.md b/docs/en/sql-reference/sql-functions/date-time-functions/week_iso.md
index 94e3550a5d4f41..64fdf54d0188bc 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/week_iso.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/week_iso.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # week_iso
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/weekofyear.md b/docs/en/sql-reference/sql-functions/date-time-functions/weekofyear.md
index 97a5175278e600..67d9a2c9480e52 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/weekofyear.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/weekofyear.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # weekofyear
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/weeks_add.md b/docs/en/sql-reference/sql-functions/date-time-functions/weeks_add.md
index 483996bf652ca7..28f00079d0196d 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/weeks_add.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/weeks_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # weeks_add
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/weeks_diff.md b/docs/en/sql-reference/sql-functions/date-time-functions/weeks_diff.md
index cee2b7a89b94d5..bbaadb653f816f 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/weeks_diff.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/weeks_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # weeks_diff
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/weeks_sub.md b/docs/en/sql-reference/sql-functions/date-time-functions/weeks_sub.md
index b1142a59906484..e517abe95926fe 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/weeks_sub.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/weeks_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # weeks_sub
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/year.md b/docs/en/sql-reference/sql-functions/date-time-functions/year.md
index c44541be9cc9c0..a9785bb7dda35a 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/year.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/year.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # year
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/years_add.md b/docs/en/sql-reference/sql-functions/date-time-functions/years_add.md
index 8558b011ec0ae6..53e1d75c7a5f0a 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/years_add.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/years_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # years_add
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/years_diff.md b/docs/en/sql-reference/sql-functions/date-time-functions/years_diff.md
index 7646aa2e1a9270..0b09447c41c6ec 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/years_diff.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/years_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # years_diff
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/years_sub.md b/docs/en/sql-reference/sql-functions/date-time-functions/years_sub.md
index c07abf6b222646..7b574b718d5b03 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/years_sub.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/years_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # years_sub
diff --git a/docs/en/sql-reference/sql-functions/date-time-functions/yearweek.md b/docs/en/sql-reference/sql-functions/date-time-functions/yearweek.md
index 42f0161456755e..c6042b11a41536 100644
--- a/docs/en/sql-reference/sql-functions/date-time-functions/yearweek.md
+++ b/docs/en/sql-reference/sql-functions/date-time-functions/yearweek.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # yearweek
diff --git a/docs/en/sql-reference/sql-functions/dict-functions/_category_.yml b/docs/en/sql-reference/sql-functions/dict-functions/_category_.yml
new file mode 100644
index 00000000000000..35d3585d5e712b
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/dict-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Dictionary'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/dict-functions/dict_mapping.md b/docs/en/sql-reference/sql-functions/dict-functions/dict_mapping.md
index 120d3d22b8263e..7bc7721f87dc0e 100644
--- a/docs/en/sql-reference/sql-functions/dict-functions/dict_mapping.md
+++ b/docs/en/sql-reference/sql-functions/dict-functions/dict_mapping.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # dict_mapping
diff --git a/docs/en/sql-reference/sql-functions/function-list.md b/docs/en/sql-reference/sql-functions/function-list.md
deleted file mode 100644
index 1ba5dada1e25a6..00000000000000
--- a/docs/en/sql-reference/sql-functions/function-list.md
+++ /dev/null
@@ -1,466 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# Function list
-
-StarRocks offers a rich set of functions to facilitate data queries and analysis. In addition to commonly used functions, StarRocks supports semi-structured functions such as ARRAY, JSON, MAP, and STRUCT functions. It also supports higher-order [Lambda functions](Lambda_expression.md). If these functions cannot meet your business requirements, you can use [Java UDF](JAVA_UDF.md) to compile functions. StarRocks also provides [Hive Bitmap UDFs](../../integrations/hive_bitmap_udf.md). You can generate Bitmap data in Hive and then load Bitmap into StarRocks. You can also export the Bitmap data generated in StarRocks to Hive for other systems to use.
-
-You can find a built-in function based on the following categories:
-
-- [Function list](#function-list)
-  - [Aggregate functions](#aggregate-functions)
-  - [Array functions](#array-functions)
-  - [Binary functions](#binary-functions)
-  - [Bit functions](#bit-functions)
-  - [Bitmap functions](#bitmap-functions)
-  - [Conditional functions](#conditional-functions)
-  - [Cryptographic functions](#cryptographic-functions)
-  - [Date and time functions](#date-and-time-functions)
-  - [Geographic functions](#geographic-functions)
-  - [Hash functions](#hash-functions)
-  - [JSON functions](#json-functions)
-  - [String functions](#string-functions)
-  - [Map functions](#map-functions)
-  - [Math functions](#math-functions)
-  - [Pattern matching functions](#pattern-matching-functions)
-  - [Percentile functions](#percentile-functions)
-  - [Scalar functions](#scalar-functions)
-  - [Struct functions](#struct-functions)
-  - [Table functions](#table-functions)
-  - [Utility functions](#utility-functions)
-  - [Dictionary functions](#dictionary-functions)
-
-## Aggregate functions
-
-- [any_value](./aggregate-functions/any_value.md)
-- [approx_count_distinct](./aggregate-functions/approx_count_distinct.md)
-- [approx_top_k](./aggregate-functions/approx_top_k.md)
-- [array_agg](./array-functions/array_agg.md)
-- [avg](./aggregate-functions/avg.md)
-- [bitmap](./aggregate-functions/bitmap.md)
-- [bitmap_agg](./bitmap-functions/bitmap_agg.md)
-- [corr](./aggregate-functions/corr.md)
-- [covar_pop](./aggregate-functions/covar_pop.md)
-- [covar_samp](./aggregate-functions/covar_samp.md)
-- [count](./aggregate-functions/count.md)
-- [count_if](./aggregate-functions/count_if.md)
-- [group_concat](./string-functions/group_concat.md)
-- [grouping](./aggregate-functions/grouping.md)
-- [grouping_id](./aggregate-functions/grouping_id.md)
-- [hll_raw_agg](./aggregate-functions/hll_raw_agg.md)
-- [hll_union](./aggregate-functions/hll_union.md)
-- [hll_union_agg](./aggregate-functions/hll_union_agg.md)
-- [max](./aggregate-functions/max.md)
-- [max_by](./aggregate-functions/max_by.md)
-- [min](./aggregate-functions/min.md)
-- [min_by](./aggregate-functions/min_by.md)
-- [multi_distinct_sum](./aggregate-functions/multi_distinct_sum.md)
-- [multi_distinct_count](./aggregate-functions/multi_distinct_count.md)
-- [percentile_approx](./aggregate-functions/percentile_approx.md)
-- [percentile_cont](./aggregate-functions/percentile_cont.md)
-- [percentile_disc](./aggregate-functions/percentile_disc.md)
-- [retention](./aggregate-functions/retention.md)
-- [stddev, stddev_pop](./aggregate-functions/stddev.md)
-- [stddev_samp](./aggregate-functions/stddev_samp.md)
-- [sum](./aggregate-functions/sum.md)
-- [variance, variance_pop, var_pop](./aggregate-functions/variance.md)
-- [var_samp](./aggregate-functions/var_samp.md)
-- [window_funnel](./aggregate-functions/window_funnel.md)
-
-## Array functions
-
-- [all_match](./array-functions/all_match.md)
-- [any_match](./array-functions/any_match.md)
-- [array_agg](./array-functions/array_agg.md)
-- [array_append](./array-functions/array_append.md)
-- [array_avg](./array-functions/array_avg.md)
-- [array_concat](./array-functions/array_concat.md)
-- [array_contains](./array-functions/array_contains.md)
-- [array_contains_all](./array-functions/array_contains_all.md)
-- [array_contains_seq](./array-functions/array_contains_seq.md)
-- [array_cum_sum](./array-functions/array_cum_sum.md)
-- [array_difference](./array-functions/array_difference.md)
-- [array_distinct](./array-functions/array_distinct.md)
-- [array_filter](./array-functions/array_filter.md)
-- [array_generate](./array-functions/array_generate.md)
-- [array_intersect](./array-functions/array_intersect.md)
-- [array_join](./array-functions/array_join.md)
-- [array_length](./array-functions/array_length.md)
-- [array_map](./array-functions/array_map.md)
-- [array_max](./array-functions/array_max.md)
-- [array_min](./array-functions/array_min.md)
-- [array_position](./array-functions/array_position.md)
-- [array_remove](./array-functions/array_remove.md)
-- [array_slice](./array-functions/array_slice.md)
-- [array_sort](./array-functions/array_sort.md)
-- [array_sortby](./array-functions/array_sortby.md)
-- [array_sum](./array-functions/array_sum.md)
-- [arrays_overlap](./array-functions/arrays_overlap.md)
-- [array_to_bitmap](./array-functions/array_to_bitmap.md)
-- [array_unique_agg](./array-functions/array_unique_agg.md)
-- [cardinality](./array-functions/cardinality.md)
-- [element_at](./array-functions/element_at.md)
-- [reverse](./string-functions/reverse.md)
-- [unnest](./array-functions/unnest.md)
-- [array_repeat](./array-functions/array_repeat.md)
-
-## Binary functions
-
-- [to_binary](./binary-functions/to_binary.md)
-- [from_binary](./binary-functions/from_binary.md)
-
-## Bit functions
-
-- [bitand](./bit-functions/bitand.md)
-- [bitnot](./bit-functions/bitnot.md)
-- [bitor](./bit-functions/bitor.md)
-- [bitxor](./bit-functions/bitxor.md)
-- [bit_shift_left](./bit-functions/bit_shift_left.md)
-- [bit_shift_right](./bit-functions/bit_shift_right.md)
-- [bit_shift_right_logical](./bit-functions/bit_shift_right_logical.md)
-
-## Bitmap functions
-
-- [base64_to_bitmap](./bitmap-functions/base64_to_bitmap.md)
-- [bitmap_agg](./bitmap-functions/bitmap_agg.md)
-- [bitmap_and](./bitmap-functions/bitmap_and.md)
-- [bitmap_andnot](./bitmap-functions/bitmap_andnot.md)
-- [bitmap_contains](./bitmap-functions/bitmap_contains.md)
-- [bitmap_count](./bitmap-functions/bitmap_count.md)
-- [bitmap_from_binary](./bitmap-functions/bitmap_from_binary.md)
-- [bitmap_from_string](./bitmap-functions/bitmap_from_string.md)
-- [bitmap_empty](./bitmap-functions/bitmap_empty.md)
-- [bitmap_has_any](./bitmap-functions/bitmap_has_any.md)
-- [bitmap_hash](./bitmap-functions/bitmap_hash.md)
-- [bitmap_intersect](./bitmap-functions/bitmap_intersect.md)
-- [bitmap_max](./bitmap-functions/bitmap_max.md)
-- [bitmap_min](./bitmap-functions/bitmap_min.md)
-- [bitmap_or](./bitmap-functions/bitmap_or.md)
-- [bitmap_remove](./bitmap-functions/bitmap_remove.md)
-- [bitmap_to_array](./bitmap-functions/bitmap_to_array.md)
-- [bitmap_to_base64](./bitmap-functions/bitmap_to_base64.md)
-- [bitmap_to_binary](./bitmap-functions/bitmap_to_binary.md)
-- [bitmap_to_string](./bitmap-functions/bitmap_to_string.md)
-- [bitmap_union](./bitmap-functions/bitmap_union.md)
-- [bitmap_union_count](./bitmap-functions/bitmap_union_count.md)
-- [bitmap_union_int](./bitmap-functions/bitmap_union_int.md)
-- [bitmap_xor](./bitmap-functions/bitmap_xor.md)
-- [intersect_count](./bitmap-functions/intersect_count.md)
-- [subdivide_bitmap](./bitmap-functions/subdivide_bitmap.md)
-- [sub_bitmap](./bitmap-functions/sub_bitmap.md)
-- [to_bitmap](./bitmap-functions/to_bitmap.md)
-- [unnest_bitmap](./bitmap-functions/unnest_bitmap.md)
-
-## Conditional functions
-
-- [case](./condition-functions/case_when.md)
-- [coalesce](./condition-functions/coalesce.md)
-- [if](./condition-functions/if.md)
-- [ifnull](./condition-functions/ifnull.md)
-- [nullif](./condition-functions/nullif.md)
-
-## Cryptographic functions
-
-- [aes_encrypt](./crytographic-functions/aes_encrypt.md)
-- [aes_decrypt](./crytographic-functions/aes_decrypt.md)
-- [base64_decode_binary](./crytographic-functions/base64_decode_binary.md)
-- [base64_decode_string](./crytographic-functions/base64_decode_string.md)
-- [from_base64](./crytographic-functions/from_base64.md)
-- [md5](./crytographic-functions/md5.md)
-- [md5sum](./crytographic-functions/md5sum.md)
-- [md5sum_numeric](./crytographic-functions/md5sum_numeric.md)
-- [sha2](./crytographic-functions/sha2.md)
-- [sm3](./crytographic-functions/sm3.md)
-- [to_base64](./crytographic-functions/from_base64.md)
-
-## Date and time functions
-
-- [add_months](./date-time-functions/add_months.md)
-- [adddate](./date-time-functions/adddate.md)
-- [convert_tz](./date-time-functions/convert_tz.md)
-- [current_date, curdate](./date-time-functions/curdate.md)
-- [current_time, curtime](./date-time-functions/curtime.md)
-- [current_timestamp](./date-time-functions/current_timestamp.md)
-- [date](./date-time-functions/date.md)
-- [date_add, adddate](./date-time-functions/date_add.md)
-- [date_diff](./date-time-functions/date_diff.md)
-- [date_format](./date-time-functions/date_format.md)
-- [date_slice](./date-time-functions/date_slice.md)
-- [date_sub, subdate](./date-time-functions/date_sub.md)
-- [date_trunc](./date-time-functions/date_trunc.md)
-- [datediff](./date-time-functions/datediff.md)
-- [day](./date-time-functions/day.md)
-- [dayofweek_iso](./date-time-functions/day_of_week_iso.md)
-- [dayname](./date-time-functions/dayname.md)
-- [dayofmonth](./date-time-functions/dayofmonth.md)
-- [dayofweek](./date-time-functions/dayofweek.md)
-- [dayofyear](./date-time-functions/dayofyear.md)
-- [days_add](./date-time-functions/days_add.md)
-- [days_diff](./date-time-functions/days_diff.md)
-- [days_sub](./date-time-functions/days_sub.md)
-- [from_days](./date-time-functions/from_days.md)
-- [from_unixtime](./date-time-functions/from_unixtime.md)
-- [hour](./date-time-functions/hour.md)
-- [hours_add](./date-time-functions/hours_add.md)
-- [hours_diff](./date-time-functions/hours_diff.md)
-- [hours_sub](./date-time-functions/hours_sub.md)
-- [jodatime_format](./date-time-functions/jodatime_format.md)
-- [last_day](./date-time-functions/last_day.md)
-- [makedate](./date-time-functions/makedate.md)
-- [microseconds_add](./date-time-functions/microseconds_add.md)
-- [microseconds_sub](./date-time-functions/microseconds_sub.md)
-- [milliseconds_diff](./date-time-functions/milliseconds_diff.md)
-- [minute](./date-time-functions/minute.md)
-- [minutes_add](./date-time-functions/minutes_add.md)
-- [minutes_diff](./date-time-functions/minutes_diff.md)
-- [minutes_sub](./date-time-functions/minutes_sub.md)
-- [month](./date-time-functions/month.md)
-- [monthname](./date-time-functions/monthname.md)
-- [months_add](./date-time-functions/months_add.md)
-- [months_diff](./date-time-functions/months_diff.md)
-- [months_sub](./date-time-functions/months_sub.md)
-- [next_day](./date-time-functions/next_day.md)
-- [now](./date-time-functions/now.md)
-- [previous_day](./date-time-functions/previous_day.md)
-- [quarter](./date-time-functions/quarter.md)
-- [second](./date-time-functions/second.md)
-- [seconds_add](./date-time-functions/seconds_add.md)
-- [seconds_diff](./date-time-functions/seconds_diff.md)
-- [seconds_sub](./date-time-functions/seconds_sub.md)
-- [str2date](./date-time-functions/str2date.md)
-- [str_to_date](./date-time-functions/str_to_date.md)
-- [str_to_jodatime](./date-time-functions/str_to_jodatime.md)
-- [time_slice](./date-time-functions/time_slice.md)
-- [time_to_sec](./date-time-functions/time_to_sec.md)
-- [timediff](./date-time-functions/timediff.md)
-- [timestamp](./date-time-functions/timestamp.md)
-- [timestampadd](./date-time-functions/timestampadd.md)
-- [timestampdiff](./date-time-functions/timestampdiff.md)
-- [to_date](./date-time-functions/to_date.md)
-- [to_days](./date-time-functions/to_days.md)
-- [to_iso8601](./date-time-functions/to_iso8601.md)
-- [to_tera_date](./date-time-functions/to_tera_date.md)
-- [to_tera_timestamp](./date-time-functions/to_tera_timestamp.md)
-- [unix_timestamp](./date-time-functions/unix_timestamp.md)
-- [utc_timestamp](./date-time-functions/utc_timestamp.md)
-- [week](./date-time-functions/week.md)
-- [week_iso](./date-time-functions/week_iso.md)
-- [weekofyear](./date-time-functions/weekofyear.md)
-- [weeks_add](./date-time-functions/weeks_add.md)
-- [weeks_diff](./date-time-functions/weeks_diff.md)
-- [weeks_sub](./date-time-functions/weeks_sub.md)
-- [year](./date-time-functions/year.md)
-- [yearweek](./date-time-functions/yearweek.md)
-- [years_add](./date-time-functions/years_add.md)
-- [years_diff](./date-time-functions/years_diff.md)
-- [years_sub](./date-time-functions/years_sub.md)
-
-## Geographic functions
-
-- [ST_AsText, ST_AsWKT](./spatial-functions/st_astext.md)
-- [st_circle](./spatial-functions/st_circle.md)
-- [st_contains](./spatial-functions/st_contains.md)
-- [st_distance_sphere](./spatial-functions/st_distance_sphere.md)
-- [st_geometryfromtext](./spatial-functions/st_geometryfromtext.md)
-- [st_linefromtext, ST_LineStringFromText](./spatial-functions/st_linefromtext.md)
-- [st_point](./spatial-functions/st_point.md)
-- [st_polygon](./spatial-functions/st_polygon.md)
-- [st_x](./spatial-functions/st_x.md)
-- [st_y](./spatial-functions/st_y.md)
-
-## Hash functions
-
-- [murmur_hash3_32](./hash-functions/murmur_hash3_32.md)
-- [xx_hash3_64](./hash-functions/xx_hash3_64.md)
-
-## JSON functions
-
-- [json_array](./json-functions/json-constructor-functions/json_array.md)
-- [json_object](./json-functions/json-constructor-functions/json_object.md)
-- [parse_json](./json-functions/json-constructor-functions/parse_json.md)
-- [Arrow function](./json-functions/json-query-and-processing-functions/arrow-function.md)
-- [cast](./json-functions/json-query-and-processing-functions/cast.md)
-- [get_json_bool](./json-functions/json-query-and-processing-functions/get_json_bool.md)
-- [get_json_double](./json-functions/json-query-and-processing-functions/get_json_double.md)
-- [get_json_int](./json-functions/json-query-and-processing-functions/get_json_int.md)
-- [get_json_string, get_json_object](./json-functions/json-query-and-processing-functions/get_json_string.md)
-- [json_each](./json-functions/json-query-and-processing-functions/json_each.md)
-- [json_exists](./json-functions/json-query-and-processing-functions/json_exists.md)
-- [json_length](./json-functions/json-query-and-processing-functions/json_length.md)
-- [json_keys](./json-functions/json-query-and-processing-functions/json_keys.md)
-- [json_query](./json-functions/json-query-and-processing-functions/json_query.md)
-- [json_string](./json-functions/json-query-and-processing-functions/json_string.md)
-- [to_json](./json-functions/json-query-and-processing-functions/to_json.md)
-
-## String functions
-
-- [append_trailing_char_if_absent](./string-functions/append_trailing_char_if_absent.md)
-- [ascii](./string-functions/ascii.md)
-- [char](./string-functions/char.md)
-- [char_length](./string-functions/char_length.md)
-- [character_length](./string-functions/character_length.md)
-- [concat](./string-functions/concat.md)
-- [concat_ws](./string-functions/concat_ws.md)
-- [crc32](./string-functions/crc32.md)
-- [ends_with](./string-functions/ends_with.md)
-- [find_in_set](./string-functions/find_in_set.md)
-- [group_concat](./string-functions/group_concat.md)
-- [hex](./string-functions/hex.md)
-- [hex_decode_binary](./string-functions/hex_decode_binary.md)
-- [hex_decode_string](./string-functions/hex_decode_string.md)
-- [instr](./string-functions/instr.md)
-- [lcase](./string-functions/lcase.md)
-- [left](./string-functions/left.md)
-- [length](./string-functions/length.md)
-- [locate](./string-functions/locate.md)
-- [lower](./string-functions/lower.md)
-- [lpad](./string-functions/lpad.md)
-- [ltrim](./string-functions/ltrim.md)
-- [money_format](./string-functions/money_format.md)
-- [ngram_search](./string-functions/ngram_search.md)
-- [null_or_empty](./string-functions/null_or_empty.md)
-- [parse_url](./string-functions/parse_url.md)
-- [repeat](./string-functions/repeat.md)
-- [replace](./string-functions/replace.md)
-- [reverse](./string-functions/reverse.md)
-- [right](./string-functions/right.md)
-- [rpad](./string-functions/rpad.md)
-- [rtrim](./string-functions/rtrim.md)
-- [space](./string-functions/space.md)
-- [split](./string-functions/split.md)
-- [split_part](./string-functions/split_part.md)
-- [starts_with](./string-functions/starts_with.md)
-- [strleft](./string-functions/strleft.md)
-- [strright](./string-functions/strright.md)
-- [str_to_map](./string-functions/str_to_map.md)
-- [substr, substring](./string-functions/substring.md)
-- [substring_index](./string-functions/substring_index.md)
-- [translate](./string-functions/translate.md)
-- [trim](./string-functions/trim.md)
-- [ucase](./string-functions/ucase.md)
-- [unhex](./string-functions/unhex.md)
-- [upper](./string-functions/upper.md)
-- [url_decode](./string-functions/url_decode.md)
-- [url_encode](./string-functions/url_encode.md)
-- [url_extract_host](./string-functions/url_extract_host.md)
-- [url_extract_parameter](./string-functions/url_extract_parameter.md)
-
-## Map functions
-
-- [cardinality](./map-functions/cardinality.md)
-- [distinct_map_keys](./map-functions/distinct_map_keys.md)
-- [element_at](./map-functions/element_at.md)
-- [map_apply](./map-functions/map_apply.md)
-- [map_concat](./map-functions/map_concat.md)
-- [map_filter](./map-functions/map_filter.md)
-- [map_from_arrays](./map-functions/map_from_arrays.md)
-- [map_keys](./map-functions/map_keys.md)
-- [map_size](./map-functions/map_size.md)
-- [map_values](./map-functions/map_values.md)
-- [transform_keys](./map-functions/transform_keys.md)
-- [transform_values](./map-functions/transform_values.md)
-
-## Math functions
-
-- [abs](./math-functions/abs.md)
-- [acos](./math-functions/acos.md)
-- [asin](./math-functions/asin.md)
-- [atan](./math-functions/atan.md)
-- [atan2](./math-functions/atan2.md)
-- [bin](./math-functions/bin.md)
-- [cbrt](./math-functions/cbrt.md)
-- [ceil, dceil](./math-functions/ceil.md)
-- [ceiling](./math-functions/ceiling.md)
-- [conv](./math-functions/conv.md)
-- [cos](./math-functions/cos.md)
-- [cosh](./math-functions/cosh.md)
-- [cosine_similarity](./math-functions/cos_similarity.md)
-- [cosine_similarity_norm](./math-functions/cos_similarity_norm.md)
-- [cot](./math-functions/cot.md)
-- [degrees](./math-functions/degrees.md)
-- [divide](./math-functions/divide.md)
-- [e](./math-functions/e.md)
-- [expexp, dexp](./math-functions/exp.md)
-- [floor, dfloor](./math-functions/floor.md)
-- [fmod](./math-functions/fmod.md)
-- [greatest](./math-functions/greatest.md)
-- [least](./math-functions/least.md)
-- [ln, dlog1, log](./math-functions/ln.md)
-- [log](./math-functions/log.md)
-- [log2](./math-functions/log2.md)
-- [log10, dlog10](./math-functions/log10.md)
-- [mod](./math-functions/mod.md)
-- [multiply](./math-functions/multiply.md)
-- [negative](./math-functions/negative.md)
-- [pi](./math-functions/pi.md)
-- [pmod](./math-functions/pmod.md)
-- [positive](./math-functions/positive.md)
-- [pow, power, dpow, fpow](./math-functions/pow.md)
-- [radians](./math-functions/radians.md)
-- [rand, random](./math-functions/rand.md)
-- [round, dround](./math-functions/round.md)
-- [sign](./math-functions/sign.md)
-- [sin](./math-functions/sin.md)
-- [sinh](./math-functions/sinh.md)
-- [sqrt, dsqrt](./math-functions/sqrt.md)
-- [square](./math-functions/square.md)
-- [tan](./math-functions/tan.md)
-- [tanh](./math-functions/tanh.md)
-- [truncate](./math-functions/truncate.md)
-
-## Pattern matching functions
-
-- [like](./like-predicate-functions/like.md)
-- [regexp](./like-predicate-functions/regexp.md)
-- [regexp_extract](./like-predicate-functions/regexp_extract.md)
-- [regexp_extract_all](./like-predicate-functions/regexp_extract_all.md)
-- [regexp_replace](./like-predicate-functions/regexp_replace.md)
-
-## Percentile functions
-
-- [percentile_approx_raw](./percentile-functions/percentile_approx_raw.md)
-- [percentile_empty](./percentile-functions/percentile_empty.md)
-- [percentile_hash](./percentile-functions/percentile_hash.md)
-- [percentile_union](./percentile-functions/percentile_union.md)
-
-## Scalar functions
-
-- [hll_cardinality](./scalar-functions/hll_cardinality.md)
-- [hll_empty](./scalar-functions/hll_empty.md)
-- [hll_hash](./scalar-functions/hll_hash.md)
-
-## Struct functions
-
-- [named_struct](./struct-functions/named_struct.md)
-- [row](./struct-functions/row.md)
-
-## Table functions
-
-- [files](./table-functions/files.md)
-- [generate_series](./table-functions/generate_series.md)
-- [json_each](./json-functions/json-query-and-processing-functions/json_each.md)
-- [subdivide_bitmap](./bitmap-functions/subdivide_bitmap.md)
-- [unnest](./array-functions/unnest.md)
-- [unnest_bitmap](./bitmap-functions/unnest_bitmap.md)
-
-## Utility functions
-
-- [catalog](./utility-functions/catalog.md)
-- [current_role](./utility-functions/current_role.md)
-- [current_version](./utility-functions/current_version.md)
-- [database](./utility-functions/database.md)
-- [get_query_profile](./utility-functions/get_query_profile.md)
-- [host_name](./utility-functions/host_name.md)
-- [isnull](./utility-functions/isnull.md)
-- [isnotnull](./utility-functions/isnotnull.md)
-- [is_role_in_session](./utility-functions/is_role_in_session.md)
-- [last_query_id](./utility-functions/last_query_id.md)
-- [sleep](./utility-functions/sleep.md)
-- [uuid](./utility-functions/uuid.md)
-- [uuid_numeric](./utility-functions/uuid_numeric.md)
-- [version](./utility-functions/version.md)
-
-## Dictionary functions
-
-[dict_mapping](./dict-functions/dict_mapping.md)
diff --git a/docs/en/sql-reference/sql-functions/hash-functions/_category_.yml b/docs/en/sql-reference/sql-functions/hash-functions/_category_.yml
new file mode 100644
index 00000000000000..9f144b392a1fa0
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/hash-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Hash'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/hash-functions/murmur_hash3_32.md b/docs/en/sql-reference/sql-functions/hash-functions/murmur_hash3_32.md
index 0e5681d793db09..79889f339dc33d 100644
--- a/docs/en/sql-reference/sql-functions/hash-functions/murmur_hash3_32.md
+++ b/docs/en/sql-reference/sql-functions/hash-functions/murmur_hash3_32.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # murmur_hash3_32
diff --git a/docs/en/sql-reference/sql-functions/hash-functions/xx_hash3_128.md b/docs/en/sql-reference/sql-functions/hash-functions/xx_hash3_128.md
index 3963d4ea50e36d..96287d6cfd8a60 100644
--- a/docs/en/sql-reference/sql-functions/hash-functions/xx_hash3_128.md
+++ b/docs/en/sql-reference/sql-functions/hash-functions/xx_hash3_128.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # xx_hash3_128
diff --git a/docs/en/sql-reference/sql-functions/hash-functions/xx_hash3_64.md b/docs/en/sql-reference/sql-functions/hash-functions/xx_hash3_64.md
index 22fda77331daaf..f298c2779a4996 100644
--- a/docs/en/sql-reference/sql-functions/hash-functions/xx_hash3_64.md
+++ b/docs/en/sql-reference/sql-functions/hash-functions/xx_hash3_64.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # xx_hash3_64
diff --git a/docs/en/sql-reference/sql-functions/hive_bitmap_udf.md b/docs/en/sql-reference/sql-functions/hive_bitmap_udf.md
new file mode 100644
index 00000000000000..6e00cc3202b85b
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/hive_bitmap_udf.md
@@ -0,0 +1,214 @@
+---
+displayed_sidebar: docs
+sidebar_position: 0.9
+---
+
+# Hive Bitmap UDF
+
+Hive Bitmap UDF provides UDFs that can be directly used in Hive. They can be used to generate Bitmap data and perform Bitmap-related calculations.
+
+The Bitmap format defined by Hive Bitmap UDF is consistent with the format in StarRocks and can be directly used for loading Bitmap data into StarRocks and unloading Bitmap data from StarRocks to Hive.
+
+Applicable scenarios:
+
+- The amount of raw data is large and directly loading these data into StarRocks for computing will cause tremendous pressure on StarRocks clusters. The desired solution is generating Bitmap data in Hive and then loading Bitmap into StarRocks.
+- Export the Bitmap data generated in StarRocks to Hive for other systems to use.
+
+Supported source and target data types:
+
+- v3.1 and later support loading and unloading data of these types: String, Base64, and Binary.
+- v2.5 and v3.0 only support loading and unloading of String and Base64 data.
+
+## Hive Bitmap UDFs that can be generated
+
+- com.starrocks.hive.udf.UDAFBitmapAgg
+
+  Combines multiple rows of non-null values in a column into one row of Bitmap values, which is equivalent to StarRocks' built-in aggregate function [bitmap_agg](bitmap-functions/bitmap_agg.md).
+
+- com.starrocks.hive.udf.UDAFBitmapUnion
+
+  Calculates the union of a set of bitmaps, which is equivalent to StarRocks' built-in aggregate function [bitmap_union](bitmap-functions/bitmap_union.md).
+
+- com.starrocks.hive.udf.UDFBase64ToBitmap
+
+  Converts a base64-encoded string into a bitmap, which is equivalent to StarRocks' built-in function [base64_to_bitmap](bitmap-functions/base64_to_bitmap.md).
+
+- com.starrocks.hive.udf.UDFBitmapAnd
+
+  Calculates the intersection of two bitmaps, which is equivalent to StarRocks' built-in function [bitmap_and](bitmap-functions/bitmap_and.md).
+
+- com.starrocks.hive.udf.UDFBitmapCount
+
+  Counts the number of values in the bitmap, which is equivalent to StarRocks' built-in function [bitmap_count](bitmap-functions/bitmap_count.md).
+
+- com.starrocks.hive.udf.UDFBitmapFromString
+
+  Converts a comma-separated string to a bitmap, equivalent to StarRocks' built-in function [bitmap_from_string](bitmap-functions/bitmap_from_string.md).
+
+- com.starrocks.hive.udf.UDFBitmapOr
+
+  Calculates the union of two bitmaps, equivalent to StarRocks' built-in function [bitmap_or](bitmap-functions/bitmap_or.md).
+
+- com.starrocks.hive.udf.UDFBitmapToBase64
+
+  Converts Bitmap to Base64 string, equivalent to StarRocks' built-in function [bitmap_to_base64](bitmap-functions/bitmap_to_base64.md).
+
+- com.starrocks.hive.udf.UDFBitmapToString
+
+  Converts a bitmap to a comma-separated string, equivalent to StarRocks' built-in function [bitmap_to_string](bitmap-functions/bitmap_to_string.md).
+
+- com.starrocks.hive.udf.UDFBitmapXor
+
+  Calculates the set of unique elements in two Bitmaps, which is equivalent to StarRocks' built-in function [bitmap_xor](bitmap-functions/bitmap_xor.md).
+
+## How to use
+
+1. Compile and generate Hive UDF on the FE.
+
+   ```bash
+   ./build.sh --hive-udf
+   ```
+
+   A JAR package `hive-udf-1.0.0.jar` will be generated in the `fe/hive-udf/` directory.
+
+2. Upload the JAR package to HDFS.
+
+   ```bash
+   hadoop  fs -put -f ./hive-udf-1.0.0.jar hdfs://<hdfs_ip>:<hdfs_port>/hive-udf-1.0.0.jar
+   ```
+
+3. Load the JAR package to Hive.
+
+   ```bash
+   hive> add jar hdfs://<hdfs_ip>:<hdfs_port>/hive-udf-1.0.0.jar;
+   ```
+
+4. Load UDF functions.
+
+   ```sql
+   hive> create temporary function bitmap_agg as 'com.starrocks.hive.udf.UDAFBitmapAgg';
+   hive> create temporary function bitmap_union as 'com.starrocks.hive.udf.UDAFBitmapUnion';
+   hive> create temporary function base64_to_bitmap as 'com.starrocks.hive.udf.UDFBase64ToBitmap';
+   hive> create temporary function bitmap_and as 'com.starrocks.hive.udf.UDFBitmapAnd';
+   hive> create temporary function bitmap_count as 'com.starrocks.hive.udf.UDFBitmapCount';
+   hive> create temporary function bitmap_from_string as 'com.starrocks.hive.udf.UDFBitmapFromString';
+   hive> create temporary function bitmap_or as 'com.starrocks.hive.udf.UDFBitmapOr';
+   hive> create temporary function bitmap_to_base64 as 'com.starrocks.hive.udf.UDFBitmapToBase64';
+   hive> create temporary function bitmap_to_string as 'com.starrocks.hive.udf.UDFBitmapToString';
+   hive> create temporary function bitmap_xor as 'com.starrocks.hive.udf.UDFBitmapXor';
+   ```
+
+## Usage examples
+
+### Generate Bitmap in Hive and load it into StarRocks in Binary format
+
+1. Create a Hive source table.
+
+   ```sql
+   hive> create table t_src(c1 bigint, c2 bigint) stored as parquet;
+
+   hive> insert into t_src values (1,1), (1,2), (1,3), (2,4), (2,5);
+
+   hive> select * from t_src;
+   1       1
+   1       2
+   1       3
+   2       4
+   2       5
+   ```
+
+2. Create a Hive bitmap table.
+
+   ```sql
+   hive> create table t_bitmap(c1 bigint, c2 binary) stored as parquet;
+   ```
+
+   Hive generates bitmap through UDFBitmapAgg and writes it into the bitmap table.
+
+   ```sql
+   hive> insert into t_bitmap select c1, bitmap_agg(c2) from t_src group by c1;
+   ```
+
+3. Create a StarRocks Bitmap table.
+
+   ```sql
+   mysql> create table t1(c1 int, c2 bitmap bitmap_union) aggregate key(c1)  distributed by hash(c1);
+   ```
+
+4. Load Bitmap data into StarRocks in different ways.
+
+   - Load data via the [files](table-functions/files.md) function.
+
+   ```sql
+   mysql> insert into t1 select c1, bitmap_from_binary(c2) from files (
+       "path" = "hdfs://<hdfs_ip>:<hdfs_port>/<hdfs_db>/t_bitmap/*",
+       "format"="parquet",
+       "compression" = "uncompressed"
+       );
+   ```
+
+   - Load data via [Hive Catalog](../../data_source/catalog/hive_catalog.md).
+
+   ```sql
+   mysql> insert into t1 select c1, bitmap_from_binary(c2) from hive_catalog_hms.xxx_db.t_bitmap;
+   ```
+
+5. View the results.
+
+   ```sql
+   mysql> select c1, bitmap_to_string(c2) from t1;                                                                                                                                                                                                                                   
+   +------+----------------------+                                                                                                                                                                                                                                                   
+   | c1   | bitmap_to_string(c2) |
+   +------+----------------------+
+   |    1 | 1,2,3                |
+   |    2 | 4,5                  |
+   +------+----------------------+
+   ```
+
+### Export Bitmap from StarRocks to Hive
+
+1. Create a Bitmap table in StarRocks and write data into this table.
+
+   ```sql
+   mysql> create table t1(c1 int, c2 bitmap bitmap_union) aggregate key(c1) buckets 3 distributed by hash(c1);
+
+   mysql> select c1, bitmap_to_string(c2) from t1;                                                                                                                                                                                                                                   
+   +------+----------------------+                                                                                                                                                                                                                                                   
+   | c1   | bitmap_to_string(c2) |
+   +------+----------------------+
+   |    1 | 1,2,3                |
+   |    2 | 4,5                  |
+   +------+----------------------+
+   ```
+
+2. Create a Bitmap table in Hive.
+
+   ```sql
+   hive> create table t_bitmap(c1 bigint, c2 binary) stored as parquet;
+   ```
+
+3. Export data in different ways.
+
+   - Export data via INSERT INTO FILES (Binary format).
+
+   ```sql
+   mysql> insert into files (
+       "path" = "hdfs://<hdfs_ip>:<hdfs_port>/<hdfs_db>/t_bitmap/",
+       "format"="parquet",
+       "compression" = "uncompressed"
+   ) select c1, bitmap_to_binary(c2) as c2 from t1;
+   ```
+
+   - Export data via [Hive Catalog](../../data_source/catalog/hive_catalog.md) (Binary format).
+
+   ```sql
+   mysql> insert into hive_catalog_hms.<hdfs_db>.t_bitmap select c1, bitmap_to_binary(c2) from t1;
+   ```
+
+4. View results in Hive.
+
+   ```plain
+   hive> select c1, bitmap_to_string(c2) from t_bitmap;
+   1       1,2,3
+   2       4,5
+   ```
diff --git a/docs/en/sql-reference/sql-functions/json-functions/_category_.yml b/docs/en/sql-reference/sql-functions/json-functions/_category_.yml
new file mode 100644
index 00000000000000..1b6bc9478d4b33
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/json-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'JSON'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-constructor-functions/_category_.yml b/docs/en/sql-reference/sql-functions/json-functions/json-constructor-functions/_category_.yml
new file mode 100644
index 00000000000000..c86aacd930b347
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-constructor-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'JSON Constructor'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-constructor-functions/json_array.md b/docs/en/sql-reference/sql-functions/json-functions/json-constructor-functions/json_array.md
index bb2f15f3d38991..3254b514719191 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-constructor-functions/json_array.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-constructor-functions/json_array.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # json_array
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-constructor-functions/json_object.md b/docs/en/sql-reference/sql-functions/json-functions/json-constructor-functions/json_object.md
index bf814bf8e86416..5af3c8c7bf4042 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-constructor-functions/json_object.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-constructor-functions/json_object.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # json_object
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-constructor-functions/parse_json.md b/docs/en/sql-reference/sql-functions/json-functions/json-constructor-functions/parse_json.md
index 17cd0c3e5f5f54..7b92fddb280a28 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-constructor-functions/parse_json.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-constructor-functions/parse_json.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # parse_json
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-operators.md b/docs/en/sql-reference/sql-functions/json-functions/json-operators.md
index bd2e492e8adf13..2d2a406d8cbcd3 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-operators.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-operators.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # JSON operators
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/_category_.yml b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/_category_.yml
new file mode 100644
index 00000000000000..b89ec251f97fec
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'JSON query and processing'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/arrow-function.md b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/arrow-function.md
index 3f8447de36834a..6c02e7ae8ef94f 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/arrow-function.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/arrow-function.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Arrow function
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/cast.md b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/cast.md
index bc57a96ec56ab6..82e1a8f4fe5c24 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/cast.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/cast.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # cast
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_bool.md b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_bool.md
index f52051ea8d8eff..316c649299a867 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_bool.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_bool.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # get_json_bool
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_double.md b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_double.md
index 58c67c5f4e9560..f88a5a5223b57c 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_double.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_double.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # get_json_double
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_int.md b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_int.md
index 29683a4ce202a8..e93109df2d79f9 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_int.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_int.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # get_json_int
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_string.md b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_string.md
index 2d15c917e98313..20a8bdaca4ae0c 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_string.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_string.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # get_json_string,get_json_object
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_each.md b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_each.md
index c1c00be382a381..5220f525512120 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_each.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_each.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # json_each
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_exists.md b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_exists.md
index 71a887cec13ff1..e24e3dccb70b79 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_exists.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_exists.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # json_exists
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_keys.md b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_keys.md
index 5c77688f8e78a8..859947d0825184 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_keys.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_keys.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # json_keys
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_length.md b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_length.md
index 9a2ef2374b07d6..dcbccb06b40c70 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_length.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_length.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # json_length
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_query.md b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_query.md
index 393a60ade2396b..6faccf15f384ec 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_query.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_query.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # json_query
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_string.md b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_string.md
index 7e11384e3317f1..d07d9773141e49 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_string.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_string.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # json_string
diff --git a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/to_json.md b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/to_json.md
index 525d45e2c6bd9e..c75edfb28eb181 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/to_json.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/to_json.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # to_json
@@ -62,5 +62,5 @@ select to_json(named_struct("k1", cast(null as string), "k2", "v2"));
 
 - [Map data type](../../../data-types/semi_structured/Map.md)
 - [Struct data type](../../../data-types/semi_structured/STRUCT.md)
-- [Map functions](../../function-list.md#map-functions)
-- [Struct functions](../../function-list.md#struct-functions)
+- [Map functions](../../README.md#map-functions)
+- [Struct functions](../../README.md#struct-functions)
diff --git a/docs/en/sql-reference/sql-functions/json-functions/overview-of-json-functions-and-operators.md b/docs/en/sql-reference/sql-functions/json-functions/overview-of-json-functions-and-operators.md
index e07ab080c21d84..c94d55b3875652 100644
--- a/docs/en/sql-reference/sql-functions/json-functions/overview-of-json-functions-and-operators.md
+++ b/docs/en/sql-reference/sql-functions/json-functions/overview-of-json-functions-and-operators.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Overview of JSON functions and operators
diff --git a/docs/en/sql-reference/sql-functions/like-predicate-functions/_category_.yml b/docs/en/sql-reference/sql-functions/like-predicate-functions/_category_.yml
new file mode 100644
index 00000000000000..2606911f6c6051
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/like-predicate-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Pattern matching'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/like-predicate-functions/like.md b/docs/en/sql-reference/sql-functions/like-predicate-functions/like.md
index e8423454876b5b..7c544e1d8e4a62 100644
--- a/docs/en/sql-reference/sql-functions/like-predicate-functions/like.md
+++ b/docs/en/sql-reference/sql-functions/like-predicate-functions/like.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # like
diff --git a/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp.md b/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp.md
index ca9b3125b5d484..d5a9442d8c9a57 100644
--- a/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp.md
+++ b/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # regexp
diff --git a/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_extract.md b/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_extract.md
index 2a0f559898f390..45b6f32338914e 100644
--- a/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_extract.md
+++ b/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_extract.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # regexp_extract
diff --git a/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_extract_all.md b/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_extract_all.md
index 5c54b57e5c137a..3fd03b34c7f3bd 100644
--- a/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_extract_all.md
+++ b/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_extract_all.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # regexp_extract_all
diff --git a/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_replace.md b/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_replace.md
index ec01ebbd364963..46ddb4c3cae199 100644
--- a/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_replace.md
+++ b/docs/en/sql-reference/sql-functions/like-predicate-functions/regexp_replace.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # regexp_replace
diff --git a/docs/en/sql-reference/sql-functions/map-functions/_category_.yml b/docs/en/sql-reference/sql-functions/map-functions/_category_.yml
new file mode 100644
index 00000000000000..9769b2af74e5fc
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/map-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Map'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/map-functions/cardinality.md b/docs/en/sql-reference/sql-functions/map-functions/cardinality.md
index 7221cb009caaf3..9520c69be9c4e5 100644
--- a/docs/en/sql-reference/sql-functions/map-functions/cardinality.md
+++ b/docs/en/sql-reference/sql-functions/map-functions/cardinality.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # cardinality
diff --git a/docs/en/sql-reference/sql-functions/map-functions/distinct_map_keys.md b/docs/en/sql-reference/sql-functions/map-functions/distinct_map_keys.md
index 097621b70acb22..337c674d02e218 100644
--- a/docs/en/sql-reference/sql-functions/map-functions/distinct_map_keys.md
+++ b/docs/en/sql-reference/sql-functions/map-functions/distinct_map_keys.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # distinct_map_keys
diff --git a/docs/en/sql-reference/sql-functions/map-functions/element_at.md b/docs/en/sql-reference/sql-functions/map-functions/element_at.md
index e849ec164f7a2c..73164a353ca68c 100644
--- a/docs/en/sql-reference/sql-functions/map-functions/element_at.md
+++ b/docs/en/sql-reference/sql-functions/map-functions/element_at.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # element_at
diff --git a/docs/en/sql-reference/sql-functions/map-functions/map_apply.md b/docs/en/sql-reference/sql-functions/map-functions/map_apply.md
index d13beeabdaa8a3..5772136525b8fc 100644
--- a/docs/en/sql-reference/sql-functions/map-functions/map_apply.md
+++ b/docs/en/sql-reference/sql-functions/map-functions/map_apply.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # map_apply
diff --git a/docs/en/sql-reference/sql-functions/map-functions/map_concat.md b/docs/en/sql-reference/sql-functions/map-functions/map_concat.md
index fadce65a587925..9e32d60ba0d7e2 100644
--- a/docs/en/sql-reference/sql-functions/map-functions/map_concat.md
+++ b/docs/en/sql-reference/sql-functions/map-functions/map_concat.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # map_concat
diff --git a/docs/en/sql-reference/sql-functions/map-functions/map_filter.md b/docs/en/sql-reference/sql-functions/map-functions/map_filter.md
index d1a10b7bd8376f..e187c808c6e2da 100644
--- a/docs/en/sql-reference/sql-functions/map-functions/map_filter.md
+++ b/docs/en/sql-reference/sql-functions/map-functions/map_filter.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # map_filter
diff --git a/docs/en/sql-reference/sql-functions/map-functions/map_from_arrays.md b/docs/en/sql-reference/sql-functions/map-functions/map_from_arrays.md
index 6c5e4544db0c79..d3bed314ca8c7f 100644
--- a/docs/en/sql-reference/sql-functions/map-functions/map_from_arrays.md
+++ b/docs/en/sql-reference/sql-functions/map-functions/map_from_arrays.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # map_from_arrays
diff --git a/docs/en/sql-reference/sql-functions/map-functions/map_keys.md b/docs/en/sql-reference/sql-functions/map-functions/map_keys.md
index 85cd5eafcd9ec0..ee7527f5fc31c5 100644
--- a/docs/en/sql-reference/sql-functions/map-functions/map_keys.md
+++ b/docs/en/sql-reference/sql-functions/map-functions/map_keys.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # map_keys
diff --git a/docs/en/sql-reference/sql-functions/map-functions/map_size.md b/docs/en/sql-reference/sql-functions/map-functions/map_size.md
index 997aa4d6d5c986..d45e0ec8ee79b1 100644
--- a/docs/en/sql-reference/sql-functions/map-functions/map_size.md
+++ b/docs/en/sql-reference/sql-functions/map-functions/map_size.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # map_size
diff --git a/docs/en/sql-reference/sql-functions/map-functions/map_values.md b/docs/en/sql-reference/sql-functions/map-functions/map_values.md
index f456a65dc61e53..624d761b95f690 100644
--- a/docs/en/sql-reference/sql-functions/map-functions/map_values.md
+++ b/docs/en/sql-reference/sql-functions/map-functions/map_values.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # map_values
diff --git a/docs/en/sql-reference/sql-functions/map-functions/transform_keys.md b/docs/en/sql-reference/sql-functions/map-functions/transform_keys.md
index 43ffad1d1099eb..b4fc63afb3b068 100644
--- a/docs/en/sql-reference/sql-functions/map-functions/transform_keys.md
+++ b/docs/en/sql-reference/sql-functions/map-functions/transform_keys.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # transform_keys
diff --git a/docs/en/sql-reference/sql-functions/map-functions/transform_values.md b/docs/en/sql-reference/sql-functions/map-functions/transform_values.md
index 2869bdf50f6456..64fa6633e52da3 100644
--- a/docs/en/sql-reference/sql-functions/map-functions/transform_values.md
+++ b/docs/en/sql-reference/sql-functions/map-functions/transform_values.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # transform_values
diff --git a/docs/en/sql-reference/sql-functions/math-functions/_category_.yml b/docs/en/sql-reference/sql-functions/math-functions/_category_.yml
new file mode 100644
index 00000000000000..95e6e7f27c143f
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/math-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Math'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/math-functions/abs.md b/docs/en/sql-reference/sql-functions/math-functions/abs.md
index 9686c70411d2e1..af4c358c4d20e9 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/abs.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/abs.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # abs
diff --git a/docs/en/sql-reference/sql-functions/math-functions/acos.md b/docs/en/sql-reference/sql-functions/math-functions/acos.md
index d060635a56b1c1..ec03eeead17f8b 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/acos.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/acos.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # acos
diff --git a/docs/en/sql-reference/sql-functions/math-functions/asin.md b/docs/en/sql-reference/sql-functions/math-functions/asin.md
index 738b660e3f4686..228bee91ecef27 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/asin.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/asin.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # asin
diff --git a/docs/en/sql-reference/sql-functions/math-functions/atan.md b/docs/en/sql-reference/sql-functions/math-functions/atan.md
index 9f02876fefda30..2ba10e87ceef5f 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/atan.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/atan.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # atan
diff --git a/docs/en/sql-reference/sql-functions/math-functions/atan2.md b/docs/en/sql-reference/sql-functions/math-functions/atan2.md
index 3d889faf019750..d052c13181154c 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/atan2.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/atan2.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # atan2
diff --git a/docs/en/sql-reference/sql-functions/math-functions/bin.md b/docs/en/sql-reference/sql-functions/math-functions/bin.md
index 8a9756c6e53759..3dda991ba77184 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/bin.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/bin.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # bin
diff --git a/docs/en/sql-reference/sql-functions/math-functions/cbrt.md b/docs/en/sql-reference/sql-functions/math-functions/cbrt.md
index 5bf066894c7574..79a75bf549c488 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/cbrt.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/cbrt.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # cbrt
diff --git a/docs/en/sql-reference/sql-functions/math-functions/ceil.md b/docs/en/sql-reference/sql-functions/math-functions/ceil.md
index 8cb8f46c3049bb..f3ef4ab44a1a94 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/ceil.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/ceil.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ceil, dceil
diff --git a/docs/en/sql-reference/sql-functions/math-functions/ceiling.md b/docs/en/sql-reference/sql-functions/math-functions/ceiling.md
index a5feb87b349591..d62daa60f5cfb1 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/ceiling.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/ceiling.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ceiling
diff --git a/docs/en/sql-reference/sql-functions/math-functions/conv.md b/docs/en/sql-reference/sql-functions/math-functions/conv.md
index 5a6946c666da55..6e7c83be4b7f58 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/conv.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/conv.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # conv
diff --git a/docs/en/sql-reference/sql-functions/math-functions/cos.md b/docs/en/sql-reference/sql-functions/math-functions/cos.md
index facfdb3c49e587..65268e725db16a 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/cos.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/cos.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # cos
diff --git a/docs/en/sql-reference/sql-functions/math-functions/cos_similarity.md b/docs/en/sql-reference/sql-functions/math-functions/cos_similarity.md
index 52b8b0907577b5..c67cd4736538b1 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/cos_similarity.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/cos_similarity.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # cos_similarity
diff --git a/docs/en/sql-reference/sql-functions/math-functions/cos_similarity_norm.md b/docs/en/sql-reference/sql-functions/math-functions/cos_similarity_norm.md
index 3a69b03615b2e5..e944d057129eb3 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/cos_similarity_norm.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/cos_similarity_norm.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # cos_similarity_norm
diff --git a/docs/en/sql-reference/sql-functions/math-functions/cosh.md b/docs/en/sql-reference/sql-functions/math-functions/cosh.md
index f0a89f60bf4b3c..fd335646f49f8c 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/cosh.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/cosh.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # cosh
diff --git a/docs/en/sql-reference/sql-functions/math-functions/cot.md b/docs/en/sql-reference/sql-functions/math-functions/cot.md
index f4ff03ef79ee33..c2d12e0b69a266 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/cot.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/cot.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # cot
diff --git a/docs/en/sql-reference/sql-functions/math-functions/degrees.md b/docs/en/sql-reference/sql-functions/math-functions/degrees.md
index 596585ffd3546c..f937418f928674 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/degrees.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/degrees.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # degrees
diff --git a/docs/en/sql-reference/sql-functions/math-functions/divide.md b/docs/en/sql-reference/sql-functions/math-functions/divide.md
index da20eaa2737ea1..fbe528b0ed9d3f 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/divide.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/divide.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # divide
diff --git a/docs/en/sql-reference/sql-functions/math-functions/e.md b/docs/en/sql-reference/sql-functions/math-functions/e.md
index 1c764a0732fdeb..9ab12f24b5a9ae 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/e.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/e.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # e
diff --git a/docs/en/sql-reference/sql-functions/math-functions/exp.md b/docs/en/sql-reference/sql-functions/math-functions/exp.md
index f37174ca011337..5beaafca2520ba 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/exp.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/exp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # exp,dexp
diff --git a/docs/en/sql-reference/sql-functions/math-functions/floor.md b/docs/en/sql-reference/sql-functions/math-functions/floor.md
index d9afe3c45fdef5..53660a2830b42a 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/floor.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/floor.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # floor, dfloor
diff --git a/docs/en/sql-reference/sql-functions/math-functions/fmod.md b/docs/en/sql-reference/sql-functions/math-functions/fmod.md
index 570f7b25e321c0..37d0eadb04c98b 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/fmod.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/fmod.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # fmod
diff --git a/docs/en/sql-reference/sql-functions/math-functions/greatest.md b/docs/en/sql-reference/sql-functions/math-functions/greatest.md
index f432c915cec40c..4b9fa8525559eb 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/greatest.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/greatest.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # greatest
diff --git a/docs/en/sql-reference/sql-functions/math-functions/least.md b/docs/en/sql-reference/sql-functions/math-functions/least.md
index 4aef378b842fe6..1f66250327f615 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/least.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/least.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # least
diff --git a/docs/en/sql-reference/sql-functions/math-functions/ln.md b/docs/en/sql-reference/sql-functions/math-functions/ln.md
index ac438977e259c3..862016e78362d2 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/ln.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/ln.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ln, dlog1, log
diff --git a/docs/en/sql-reference/sql-functions/math-functions/log.md b/docs/en/sql-reference/sql-functions/math-functions/log.md
index 7f7f535ab0b0cb..f28f011e8791fd 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/log.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/log.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # log
diff --git a/docs/en/sql-reference/sql-functions/math-functions/log10.md b/docs/en/sql-reference/sql-functions/math-functions/log10.md
index cc473934c942c4..a6ae860145b661 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/log10.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/log10.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # log10, dlog10
diff --git a/docs/en/sql-reference/sql-functions/math-functions/log2.md b/docs/en/sql-reference/sql-functions/math-functions/log2.md
index abacb24a6d761d..8b2e6b5cf3b1b7 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/log2.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/log2.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # log2
diff --git a/docs/en/sql-reference/sql-functions/math-functions/mod.md b/docs/en/sql-reference/sql-functions/math-functions/mod.md
index a6dfdf4821c7db..1ed79894fe9b10 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/mod.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/mod.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # mod
diff --git a/docs/en/sql-reference/sql-functions/math-functions/multiply.md b/docs/en/sql-reference/sql-functions/math-functions/multiply.md
index c43db614659c3d..33866c970d1c29 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/multiply.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/multiply.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # multiply
diff --git a/docs/en/sql-reference/sql-functions/math-functions/negative.md b/docs/en/sql-reference/sql-functions/math-functions/negative.md
index aebd97b35214f3..d281c84160f11a 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/negative.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/negative.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # negative
diff --git a/docs/en/sql-reference/sql-functions/math-functions/pi.md b/docs/en/sql-reference/sql-functions/math-functions/pi.md
index 7069f86654ae8b..d8780eb195036a 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/pi.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/pi.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # pi
diff --git a/docs/en/sql-reference/sql-functions/math-functions/pmod.md b/docs/en/sql-reference/sql-functions/math-functions/pmod.md
index cb1f1e2e137773..b930b2e8503647 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/pmod.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/pmod.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # pmod
diff --git a/docs/en/sql-reference/sql-functions/math-functions/positive.md b/docs/en/sql-reference/sql-functions/math-functions/positive.md
index 25fdd4af7c0630..89383a707e9b6a 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/positive.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/positive.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # positive
diff --git a/docs/en/sql-reference/sql-functions/math-functions/pow.md b/docs/en/sql-reference/sql-functions/math-functions/pow.md
index 3937c3eb3d86ce..5d973d868aba0c 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/pow.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/pow.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # pow, power, dpow, fpow
diff --git a/docs/en/sql-reference/sql-functions/math-functions/radians.md b/docs/en/sql-reference/sql-functions/math-functions/radians.md
index 8b5b4c2304b6dc..67195e0a6643c3 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/radians.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/radians.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # radians
diff --git a/docs/en/sql-reference/sql-functions/math-functions/rand.md b/docs/en/sql-reference/sql-functions/math-functions/rand.md
index d30123edeac844..83fd426ebe7630 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/rand.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/rand.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # rand, random
diff --git a/docs/en/sql-reference/sql-functions/math-functions/round.md b/docs/en/sql-reference/sql-functions/math-functions/round.md
index cc2a87587b3993..320dfbec376aca 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/round.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/round.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # round, dround
diff --git a/docs/en/sql-reference/sql-functions/math-functions/sign.md b/docs/en/sql-reference/sql-functions/math-functions/sign.md
index f5a135ba684ab7..49b7b804568ba2 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/sign.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/sign.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # sign
diff --git a/docs/en/sql-reference/sql-functions/math-functions/sin.md b/docs/en/sql-reference/sql-functions/math-functions/sin.md
index 5b421bbd536ec9..1a9469b573c4ee 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/sin.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/sin.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # sin
diff --git a/docs/en/sql-reference/sql-functions/math-functions/sinh.md b/docs/en/sql-reference/sql-functions/math-functions/sinh.md
index 09c3ca14a6fbd2..aabea0b596b7f8 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/sinh.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/sinh.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # sinh
diff --git a/docs/en/sql-reference/sql-functions/math-functions/sqrt.md b/docs/en/sql-reference/sql-functions/math-functions/sqrt.md
index 00ffc871712f33..a75ceadea8b252 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/sqrt.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/sqrt.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # sqrt, dsqrt
diff --git a/docs/en/sql-reference/sql-functions/math-functions/square.md b/docs/en/sql-reference/sql-functions/math-functions/square.md
index aedc09dfb21e11..a6a8ed0a975ddd 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/square.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/square.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # square
diff --git a/docs/en/sql-reference/sql-functions/math-functions/tan.md b/docs/en/sql-reference/sql-functions/math-functions/tan.md
index 829c85e0c0c0fc..f4b39af639217e 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/tan.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/tan.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # tan
diff --git a/docs/en/sql-reference/sql-functions/math-functions/tanh.md b/docs/en/sql-reference/sql-functions/math-functions/tanh.md
index e0f902613ec549..324ed6bdc793d7 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/tanh.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/tanh.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # tanh
diff --git a/docs/en/sql-reference/sql-functions/math-functions/truncate.md b/docs/en/sql-reference/sql-functions/math-functions/truncate.md
index f1a25d60c0163c..b98a3e8455074c 100644
--- a/docs/en/sql-reference/sql-functions/math-functions/truncate.md
+++ b/docs/en/sql-reference/sql-functions/math-functions/truncate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # truncate
diff --git a/docs/en/sql-reference/sql-functions/percentile-functions/_category_.yml b/docs/en/sql-reference/sql-functions/percentile-functions/_category_.yml
new file mode 100644
index 00000000000000..ca9a69980a7b93
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/percentile-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Percentile'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/percentile-functions/percentile_approx.mdx b/docs/en/sql-reference/sql-functions/percentile-functions/percentile_approx.mdx
index c515dc534956ba..51c76827799e49 100644
--- a/docs/en/sql-reference/sql-functions/percentile-functions/percentile_approx.mdx
+++ b/docs/en/sql-reference/sql-functions/percentile-functions/percentile_approx.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_label: percentile_approx
 title: percentile_approx
 ---
diff --git a/docs/en/sql-reference/sql-functions/percentile-functions/percentile_approx_raw.md b/docs/en/sql-reference/sql-functions/percentile-functions/percentile_approx_raw.md
index ed23645fee744a..6b30661d3d193b 100644
--- a/docs/en/sql-reference/sql-functions/percentile-functions/percentile_approx_raw.md
+++ b/docs/en/sql-reference/sql-functions/percentile-functions/percentile_approx_raw.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # percentile_approx_raw
diff --git a/docs/en/sql-reference/sql-functions/percentile-functions/percentile_cont.mdx b/docs/en/sql-reference/sql-functions/percentile-functions/percentile_cont.mdx
index e924853670ff98..9ed829c9ccd068 100644
--- a/docs/en/sql-reference/sql-functions/percentile-functions/percentile_cont.mdx
+++ b/docs/en/sql-reference/sql-functions/percentile-functions/percentile_cont.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_label: percentile_cont
 title: percentile_cont
 ---
diff --git a/docs/en/sql-reference/sql-functions/percentile-functions/percentile_disc.mdx b/docs/en/sql-reference/sql-functions/percentile-functions/percentile_disc.mdx
index 026f7bfd0403ea..647663cb477540 100644
--- a/docs/en/sql-reference/sql-functions/percentile-functions/percentile_disc.mdx
+++ b/docs/en/sql-reference/sql-functions/percentile-functions/percentile_disc.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_label: percentile_disc
 title: percentile_disc
 ---
diff --git a/docs/en/sql-reference/sql-functions/percentile-functions/percentile_empty.md b/docs/en/sql-reference/sql-functions/percentile-functions/percentile_empty.md
index e54336fe66d8c9..88a6a1557de0ba 100644
--- a/docs/en/sql-reference/sql-functions/percentile-functions/percentile_empty.md
+++ b/docs/en/sql-reference/sql-functions/percentile-functions/percentile_empty.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # percentile_empty
diff --git a/docs/en/sql-reference/sql-functions/percentile-functions/percentile_hash.md b/docs/en/sql-reference/sql-functions/percentile-functions/percentile_hash.md
index 73dcb722f40941..184ee7ef0c9432 100644
--- a/docs/en/sql-reference/sql-functions/percentile-functions/percentile_hash.md
+++ b/docs/en/sql-reference/sql-functions/percentile-functions/percentile_hash.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # percentile_hash
diff --git a/docs/en/sql-reference/sql-functions/percentile-functions/percentile_union.md b/docs/en/sql-reference/sql-functions/percentile-functions/percentile_union.md
index 0e5c089de7ecb3..ea98da14080df6 100644
--- a/docs/en/sql-reference/sql-functions/percentile-functions/percentile_union.md
+++ b/docs/en/sql-reference/sql-functions/percentile-functions/percentile_union.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # percentile_union
diff --git a/docs/en/sql-reference/sql-functions/scalar-functions/_category_.yml b/docs/en/sql-reference/sql-functions/scalar-functions/_category_.yml
new file mode 100644
index 00000000000000..733fd5d4d3525f
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/scalar-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Scalar'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/scalar-functions/hll_cardinality.md b/docs/en/sql-reference/sql-functions/scalar-functions/hll_cardinality.md
index 5a394dedfb9430..24fdf6101314d5 100644
--- a/docs/en/sql-reference/sql-functions/scalar-functions/hll_cardinality.md
+++ b/docs/en/sql-reference/sql-functions/scalar-functions/hll_cardinality.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # hll_cardinality
diff --git a/docs/en/sql-reference/sql-functions/scalar-functions/hll_empty.md b/docs/en/sql-reference/sql-functions/scalar-functions/hll_empty.md
index d3328186371c15..390cc77be89feb 100644
--- a/docs/en/sql-reference/sql-functions/scalar-functions/hll_empty.md
+++ b/docs/en/sql-reference/sql-functions/scalar-functions/hll_empty.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # hll_empty
diff --git a/docs/en/sql-reference/sql-functions/scalar-functions/hll_hash.md b/docs/en/sql-reference/sql-functions/scalar-functions/hll_hash.md
index 98e2a6dc93d0ac..a40b57d6e9dd58 100644
--- a/docs/en/sql-reference/sql-functions/scalar-functions/hll_hash.md
+++ b/docs/en/sql-reference/sql-functions/scalar-functions/hll_hash.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # hll_hash
diff --git a/docs/en/sql-reference/sql-functions/spatial-functions/_category_.yml b/docs/en/sql-reference/sql-functions/spatial-functions/_category_.yml
new file mode 100644
index 00000000000000..e2a90b1358831c
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/spatial-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Spatial'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/spatial-functions/st_astext.md b/docs/en/sql-reference/sql-functions/spatial-functions/st_astext.md
index f252487d2a91d4..b6902e8fc88cb5 100644
--- a/docs/en/sql-reference/sql-functions/spatial-functions/st_astext.md
+++ b/docs/en/sql-reference/sql-functions/spatial-functions/st_astext.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ST_AsText,ST_AsWKT
diff --git a/docs/en/sql-reference/sql-functions/spatial-functions/st_circle.md b/docs/en/sql-reference/sql-functions/spatial-functions/st_circle.md
index ffd876e50e6dfc..4c2ac56ca86968 100644
--- a/docs/en/sql-reference/sql-functions/spatial-functions/st_circle.md
+++ b/docs/en/sql-reference/sql-functions/spatial-functions/st_circle.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ST_Circle
diff --git a/docs/en/sql-reference/sql-functions/spatial-functions/st_contains.md b/docs/en/sql-reference/sql-functions/spatial-functions/st_contains.md
index 579c626af870c1..ff9dc3398b2eb3 100644
--- a/docs/en/sql-reference/sql-functions/spatial-functions/st_contains.md
+++ b/docs/en/sql-reference/sql-functions/spatial-functions/st_contains.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ST_Contains
diff --git a/docs/en/sql-reference/sql-functions/spatial-functions/st_distance_sphere.md b/docs/en/sql-reference/sql-functions/spatial-functions/st_distance_sphere.md
index 56a2f14b07625b..fe5d8af0d05baf 100644
--- a/docs/en/sql-reference/sql-functions/spatial-functions/st_distance_sphere.md
+++ b/docs/en/sql-reference/sql-functions/spatial-functions/st_distance_sphere.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ST_Distance_Sphere
diff --git a/docs/en/sql-reference/sql-functions/spatial-functions/st_geometryfromtext.md b/docs/en/sql-reference/sql-functions/spatial-functions/st_geometryfromtext.md
index b3c78f62d82f86..325651de94c039 100644
--- a/docs/en/sql-reference/sql-functions/spatial-functions/st_geometryfromtext.md
+++ b/docs/en/sql-reference/sql-functions/spatial-functions/st_geometryfromtext.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ST_GeometryFromText,ST_GeomFromText
diff --git a/docs/en/sql-reference/sql-functions/spatial-functions/st_linefromtext.md b/docs/en/sql-reference/sql-functions/spatial-functions/st_linefromtext.md
index 0c7d13b8922c5f..14c40386fa035f 100644
--- a/docs/en/sql-reference/sql-functions/spatial-functions/st_linefromtext.md
+++ b/docs/en/sql-reference/sql-functions/spatial-functions/st_linefromtext.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ST_LineFromText,ST_LineStringFromText
diff --git a/docs/en/sql-reference/sql-functions/spatial-functions/st_point.md b/docs/en/sql-reference/sql-functions/spatial-functions/st_point.md
index 665a0ab86d9c79..0af424aeefcca7 100644
--- a/docs/en/sql-reference/sql-functions/spatial-functions/st_point.md
+++ b/docs/en/sql-reference/sql-functions/spatial-functions/st_point.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ST_Point
diff --git a/docs/en/sql-reference/sql-functions/spatial-functions/st_polygon.md b/docs/en/sql-reference/sql-functions/spatial-functions/st_polygon.md
index 081199d5633e2f..ad62a2847c27a9 100644
--- a/docs/en/sql-reference/sql-functions/spatial-functions/st_polygon.md
+++ b/docs/en/sql-reference/sql-functions/spatial-functions/st_polygon.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ST_Polygon,ST_PolyFromText,ST_PolygonFromText
diff --git a/docs/en/sql-reference/sql-functions/spatial-functions/st_x.md b/docs/en/sql-reference/sql-functions/spatial-functions/st_x.md
index 6d1268a72de61f..e992d588f52009 100644
--- a/docs/en/sql-reference/sql-functions/spatial-functions/st_x.md
+++ b/docs/en/sql-reference/sql-functions/spatial-functions/st_x.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ST_X
diff --git a/docs/en/sql-reference/sql-functions/spatial-functions/st_y.md b/docs/en/sql-reference/sql-functions/spatial-functions/st_y.md
index 3416a50af2875b..65a4a46f973b92 100644
--- a/docs/en/sql-reference/sql-functions/spatial-functions/st_y.md
+++ b/docs/en/sql-reference/sql-functions/spatial-functions/st_y.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ST_Y
diff --git a/docs/en/sql-reference/sql-functions/string-functions/_category_.yml b/docs/en/sql-reference/sql-functions/string-functions/_category_.yml
new file mode 100644
index 00000000000000..8a64f2862638bc
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/string-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'String'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/string-functions/append_trailing_char_if_absent.md b/docs/en/sql-reference/sql-functions/string-functions/append_trailing_char_if_absent.md
index d80d70594dda67..efafbefdc75cbf 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/append_trailing_char_if_absent.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/append_trailing_char_if_absent.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # append_trailing_char_if_absent
diff --git a/docs/en/sql-reference/sql-functions/string-functions/ascii.md b/docs/en/sql-reference/sql-functions/string-functions/ascii.md
index 5a346d3748f6ad..09557c35cf7c41 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/ascii.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/ascii.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ascii
diff --git a/docs/en/sql-reference/sql-functions/string-functions/char.md b/docs/en/sql-reference/sql-functions/string-functions/char.md
index f64748dcb8d57f..bbeebc2c4e14d4 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/char.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/char.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # char 
diff --git a/docs/en/sql-reference/sql-functions/string-functions/char_length.md b/docs/en/sql-reference/sql-functions/string-functions/char_length.md
index ad750ce099b64e..7814351f13f8bb 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/char_length.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/char_length.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # char_length
diff --git a/docs/en/sql-reference/sql-functions/string-functions/character_length.md b/docs/en/sql-reference/sql-functions/string-functions/character_length.md
index 44f6cc1a661aeb..ff72661b730491 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/character_length.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/character_length.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # character_length
diff --git a/docs/en/sql-reference/sql-functions/string-functions/concat.md b/docs/en/sql-reference/sql-functions/string-functions/concat.md
index 0688bbf818720e..322bcddd38fa3d 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/concat.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/concat.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # concat
diff --git a/docs/en/sql-reference/sql-functions/string-functions/concat_ws.md b/docs/en/sql-reference/sql-functions/string-functions/concat_ws.md
index a715b700ec71c3..bddd18fc59a54f 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/concat_ws.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/concat_ws.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # concat_ws
diff --git a/docs/en/sql-reference/sql-functions/string-functions/crc32.md b/docs/en/sql-reference/sql-functions/string-functions/crc32.md
index 0678c485e77781..4a256c4e82af98 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/crc32.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/crc32.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # crc32
diff --git a/docs/en/sql-reference/sql-functions/string-functions/ends_with.md b/docs/en/sql-reference/sql-functions/string-functions/ends_with.md
index 4550499507c23a..707f4cab147781 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/ends_with.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/ends_with.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ends_with
diff --git a/docs/en/sql-reference/sql-functions/string-functions/find_in_set.md b/docs/en/sql-reference/sql-functions/string-functions/find_in_set.md
index fa118865d475e6..86204a99459953 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/find_in_set.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/find_in_set.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # find_in_set
diff --git a/docs/en/sql-reference/sql-functions/string-functions/group_concat.md b/docs/en/sql-reference/sql-functions/string-functions/group_concat.md
index fa1f66dc78ab7c..e674ecdf177936 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/group_concat.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/group_concat.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # group_concat
@@ -33,7 +33,7 @@ VARCHAR GROUP_CONCAT([DISTINCT] expr [,expr ...]
 
 Returns a string value for each group and returns NULL if there are no non-NULL values.
 
-You can limit the length of the string returned by group_concat by setting the [session variable](../../../reference/System_variable.md) `group_concat_max_len`, which defaults to 1024. Minimum value: 4. Unit: characters.
+You can limit the length of the string returned by group_concat by setting the [session variable](../../System_variable.md) `group_concat_max_len`, which defaults to 1024. Minimum value: 4. Unit: characters.
 
 Example:
 
diff --git a/docs/en/sql-reference/sql-functions/string-functions/hex.md b/docs/en/sql-reference/sql-functions/string-functions/hex.md
index b8bbb79dcc4efa..3b46f2eff9094b 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/hex.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/hex.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # hex
diff --git a/docs/en/sql-reference/sql-functions/string-functions/hex_decode_binary.md b/docs/en/sql-reference/sql-functions/string-functions/hex_decode_binary.md
index 3f3822fd221f9a..ee77b1372b3850 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/hex_decode_binary.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/hex_decode_binary.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # hex_decode_binary
diff --git a/docs/en/sql-reference/sql-functions/string-functions/hex_decode_string.md b/docs/en/sql-reference/sql-functions/string-functions/hex_decode_string.md
index 47ab2ecdaf1f24..c7f1b6e35170fb 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/hex_decode_string.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/hex_decode_string.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # hex_decode_string
diff --git a/docs/en/sql-reference/sql-functions/string-functions/instr.md b/docs/en/sql-reference/sql-functions/string-functions/instr.md
index f9cefe97e1c20e..727cec048fbf13 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/instr.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/instr.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # instr
diff --git a/docs/en/sql-reference/sql-functions/string-functions/lcase.md b/docs/en/sql-reference/sql-functions/string-functions/lcase.md
index 1e06f567cd6a14..8b88b3ae0e20eb 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/lcase.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/lcase.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # lcase
diff --git a/docs/en/sql-reference/sql-functions/string-functions/left.md b/docs/en/sql-reference/sql-functions/string-functions/left.md
index 05c88a1908872d..41c78fdb3d45d4 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/left.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/left.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # left
diff --git a/docs/en/sql-reference/sql-functions/string-functions/length.md b/docs/en/sql-reference/sql-functions/string-functions/length.md
index 9fc2b02ea9e82e..5b67f047a64998 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/length.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/length.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # length
diff --git a/docs/en/sql-reference/sql-functions/string-functions/locate.md b/docs/en/sql-reference/sql-functions/string-functions/locate.md
index d03fc6eb8884fd..9e33d0ff039272 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/locate.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/locate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # locate
diff --git a/docs/en/sql-reference/sql-functions/string-functions/lower.md b/docs/en/sql-reference/sql-functions/string-functions/lower.md
index 98b66d7252877b..3b5b8acc5e8e2a 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/lower.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/lower.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # lower
diff --git a/docs/en/sql-reference/sql-functions/string-functions/lpad.md b/docs/en/sql-reference/sql-functions/string-functions/lpad.md
index 39ba1c5e7edcfd..7f521dd6ca5868 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/lpad.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/lpad.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # lpad
diff --git a/docs/en/sql-reference/sql-functions/string-functions/ltrim.md b/docs/en/sql-reference/sql-functions/string-functions/ltrim.md
index 412a55b5f264cf..90b990f02a53ca 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/ltrim.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/ltrim.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ltrim
diff --git a/docs/en/sql-reference/sql-functions/string-functions/money_format.md b/docs/en/sql-reference/sql-functions/string-functions/money_format.md
index 801bb7970d718a..91196ff059608b 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/money_format.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/money_format.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # money_format
diff --git a/docs/en/sql-reference/sql-functions/string-functions/ngram_search.md b/docs/en/sql-reference/sql-functions/string-functions/ngram_search.md
index ab4f83f7597d47..3bcaf2128dcc82 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/ngram_search.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/ngram_search.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ngram_search
diff --git a/docs/en/sql-reference/sql-functions/string-functions/null_or_empty.md b/docs/en/sql-reference/sql-functions/string-functions/null_or_empty.md
index 3e1ec1b02bb121..67d60b308d3eb2 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/null_or_empty.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/null_or_empty.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # null_or_empty
diff --git a/docs/en/sql-reference/sql-functions/string-functions/parse_url.md b/docs/en/sql-reference/sql-functions/string-functions/parse_url.md
index e22064c4812aee..d706750e78035a 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/parse_url.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/parse_url.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # parse_url
diff --git a/docs/en/sql-reference/sql-functions/string-functions/regexp_split.md b/docs/en/sql-reference/sql-functions/string-functions/regexp_split.md
index f8e32d39c71c9e..09e8951751fca4 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/regexp_split.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/regexp_split.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # regexp_split
diff --git a/docs/en/sql-reference/sql-functions/string-functions/repeat.md b/docs/en/sql-reference/sql-functions/string-functions/repeat.md
index a20dbe7f3b3d9e..b86c669d916e5a 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/repeat.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/repeat.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # repeat
diff --git a/docs/en/sql-reference/sql-functions/string-functions/replace.md b/docs/en/sql-reference/sql-functions/string-functions/replace.md
index 21b81116f35da4..4efe31ed7d0338 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/replace.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/replace.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # replace
diff --git a/docs/en/sql-reference/sql-functions/string-functions/reverse.md b/docs/en/sql-reference/sql-functions/string-functions/reverse.md
index f75790a8f3ca7a..4460443fc761fa 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/reverse.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/reverse.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # reverse
diff --git a/docs/en/sql-reference/sql-functions/string-functions/right.md b/docs/en/sql-reference/sql-functions/string-functions/right.md
index eafe8baf3c7a4a..fec4b5f414603d 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/right.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/right.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # right
diff --git a/docs/en/sql-reference/sql-functions/string-functions/rpad.md b/docs/en/sql-reference/sql-functions/string-functions/rpad.md
index 01a0a9d3c1fac5..680247e591a384 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/rpad.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/rpad.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # rpad
diff --git a/docs/en/sql-reference/sql-functions/string-functions/rtrim.md b/docs/en/sql-reference/sql-functions/string-functions/rtrim.md
index b323a57066600a..0952db12aa2357 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/rtrim.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/rtrim.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # rtrim
diff --git a/docs/en/sql-reference/sql-functions/string-functions/space.md b/docs/en/sql-reference/sql-functions/string-functions/space.md
index a5c9ac5fdecbed..1816bcfd2941e8 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/space.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/space.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # space
diff --git a/docs/en/sql-reference/sql-functions/string-functions/split.md b/docs/en/sql-reference/sql-functions/string-functions/split.md
index 97b1d73fca53c4..3bc85008ac4c01 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/split.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/split.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # split
diff --git a/docs/en/sql-reference/sql-functions/string-functions/split_part.md b/docs/en/sql-reference/sql-functions/string-functions/split_part.md
index ad70b284923dc1..5b801d85504e50 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/split_part.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/split_part.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # split_part
diff --git a/docs/en/sql-reference/sql-functions/string-functions/starts_with.md b/docs/en/sql-reference/sql-functions/string-functions/starts_with.md
index 64134b8a8a4bc5..75cebb22668079 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/starts_with.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/starts_with.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # starts_with
diff --git a/docs/en/sql-reference/sql-functions/string-functions/str_to_map.md b/docs/en/sql-reference/sql-functions/string-functions/str_to_map.md
index 9d747c784577f8..8c2952024a37de 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/str_to_map.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/str_to_map.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # str_to_map
diff --git a/docs/en/sql-reference/sql-functions/string-functions/strcmp.md b/docs/en/sql-reference/sql-functions/string-functions/strcmp.md
index cd5351d8fc2d7a..8da540add19ad9 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/strcmp.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/strcmp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # strcmp
diff --git a/docs/en/sql-reference/sql-functions/string-functions/strleft.md b/docs/en/sql-reference/sql-functions/string-functions/strleft.md
index a5c282d93653ff..796db22c5475c7 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/strleft.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/strleft.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # strleft
diff --git a/docs/en/sql-reference/sql-functions/string-functions/strright.md b/docs/en/sql-reference/sql-functions/string-functions/strright.md
index a74849416a7b32..8b4b98f8f6d769 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/strright.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/strright.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # strright
diff --git a/docs/en/sql-reference/sql-functions/string-functions/substring.md b/docs/en/sql-reference/sql-functions/string-functions/substring.md
index 5d5966ecc2fe34..5730c56061854e 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/substring.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/substring.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # substring, substr
diff --git a/docs/en/sql-reference/sql-functions/string-functions/substring_index.md b/docs/en/sql-reference/sql-functions/string-functions/substring_index.md
index 82b7e72ef20377..9c9ae79586efa2 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/substring_index.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/substring_index.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # substring_index
diff --git a/docs/en/sql-reference/sql-functions/string-functions/translate.md b/docs/en/sql-reference/sql-functions/string-functions/translate.md
index 59ee6630e77a3f..9cfbc0e3c8bf9a 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/translate.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/translate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # translate
diff --git a/docs/en/sql-reference/sql-functions/string-functions/trim.md b/docs/en/sql-reference/sql-functions/string-functions/trim.md
index a3a345dde9cff2..91e2f0480042c3 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/trim.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/trim.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # trim
diff --git a/docs/en/sql-reference/sql-functions/string-functions/ucase.md b/docs/en/sql-reference/sql-functions/string-functions/ucase.md
index 4a1b3ff6d39499..704685b7728229 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/ucase.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/ucase.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ucase
diff --git a/docs/en/sql-reference/sql-functions/string-functions/unhex.md b/docs/en/sql-reference/sql-functions/string-functions/unhex.md
index c875aca0d168ee..3b7164a6be203e 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/unhex.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/unhex.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # unhex
diff --git a/docs/en/sql-reference/sql-functions/string-functions/upper.md b/docs/en/sql-reference/sql-functions/string-functions/upper.md
index 4f3021361c5a43..82a7fde1a54be0 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/upper.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/upper.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # upper
diff --git a/docs/en/sql-reference/sql-functions/string-functions/url_decode.md b/docs/en/sql-reference/sql-functions/string-functions/url_decode.md
index c2cc0af9482976..b21f570f2b9794 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/url_decode.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/url_decode.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # url_decode
diff --git a/docs/en/sql-reference/sql-functions/string-functions/url_encode.md b/docs/en/sql-reference/sql-functions/string-functions/url_encode.md
index 5402f832aeb4e4..b20aaf27e8f7f5 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/url_encode.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/url_encode.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # url_encode
diff --git a/docs/en/sql-reference/sql-functions/string-functions/url_extract_host.md b/docs/en/sql-reference/sql-functions/string-functions/url_extract_host.md
index 737e0507c613fa..71829552bd078f 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/url_extract_host.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/url_extract_host.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # url_extract_host
diff --git a/docs/en/sql-reference/sql-functions/string-functions/url_extract_parameter.md b/docs/en/sql-reference/sql-functions/string-functions/url_extract_parameter.md
index 57e17bdf9343b6..bbfa30c80f0df8 100644
--- a/docs/en/sql-reference/sql-functions/string-functions/url_extract_parameter.md
+++ b/docs/en/sql-reference/sql-functions/string-functions/url_extract_parameter.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # url_extract_parameter
diff --git a/docs/en/sql-reference/sql-functions/struct-functions/_category_.yml b/docs/en/sql-reference/sql-functions/struct-functions/_category_.yml
new file mode 100644
index 00000000000000..1f305a29eeeb3f
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/struct-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Struct'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/struct-functions/named_struct.md b/docs/en/sql-reference/sql-functions/struct-functions/named_struct.md
index 6e5938df95624a..ace24c98f9f34f 100644
--- a/docs/en/sql-reference/sql-functions/struct-functions/named_struct.md
+++ b/docs/en/sql-reference/sql-functions/struct-functions/named_struct.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # named_struct
diff --git a/docs/en/sql-reference/sql-functions/struct-functions/row.md b/docs/en/sql-reference/sql-functions/struct-functions/row.md
index 0cb65e3f72f12a..dcfbc92dbf598c 100644
--- a/docs/en/sql-reference/sql-functions/struct-functions/row.md
+++ b/docs/en/sql-reference/sql-functions/struct-functions/row.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # row
diff --git a/docs/en/sql-reference/sql-functions/table-functions/_category_.yml b/docs/en/sql-reference/sql-functions/table-functions/_category_.yml
new file mode 100644
index 00000000000000..d09d0046fa1701
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/table-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Table'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/table-functions/files.md b/docs/en/sql-reference/sql-functions/table-functions/files.md
index be290dc75ece56..7bad70b2e95a3b 100644
--- a/docs/en/sql-reference/sql-functions/table-functions/files.md
+++ b/docs/en/sql-reference/sql-functions/table-functions/files.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # FILES
@@ -8,7 +8,7 @@ displayed_sidebar: "English"
 
 Defines data files in remote storage.
 
-From v3.1.0 onwards, StarRocks supports defining read-only files in remote storage using the table function FILES(). It can access remote storage with the path-related properties of the files, infers the table schema of the data in the files, and returns the data rows. You can directly query the data rows using [SELECT](../../sql-statements/data-manipulation/SELECT.md), load the data rows into an existing table using [INSERT](../../sql-statements/data-manipulation/INSERT.md), or create a new table and load the data rows into it using [CREATE TABLE AS SELECT](../../sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md).
+From v3.1.0 onwards, StarRocks supports defining read-only files in remote storage using the table function FILES(). It can access remote storage with the path-related properties of the files, infers the table schema of the data in the files, and returns the data rows. You can directly query the data rows using [SELECT](../../sql-statements/table_bucket_part_index/SELECT.md), load the data rows into an existing table using [INSERT](../../sql-statements/loading_unloading/INSERT.md), or create a new table and load the data rows into it using [CREATE TABLE AS SELECT](../../sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md).
 
 From v3.2.0 onwards, FILES() supports writing data into files in remote storage. You can [use INSERT INTO FILES() to unload data from StarRocks to remote storage](../../../unloading/unload_using_insert_into_files.md).
 
diff --git a/docs/en/sql-reference/sql-functions/table-functions/generate_series.md b/docs/en/sql-reference/sql-functions/table-functions/generate_series.md
index ae7f096b685ac6..1b276e22ba6b10 100644
--- a/docs/en/sql-reference/sql-functions/table-functions/generate_series.md
+++ b/docs/en/sql-reference/sql-functions/table-functions/generate_series.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # generate_series
diff --git a/docs/en/sql-reference/sql-functions/utility-functions/_category_.yml b/docs/en/sql-reference/sql-functions/utility-functions/_category_.yml
new file mode 100644
index 00000000000000..a38cc02676a28a
--- /dev/null
+++ b/docs/en/sql-reference/sql-functions/utility-functions/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Utility'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-functions/utility-functions/catalog.md b/docs/en/sql-reference/sql-functions/utility-functions/catalog.md
index d169f220463114..59c11fc83a8669 100644
--- a/docs/en/sql-reference/sql-functions/utility-functions/catalog.md
+++ b/docs/en/sql-reference/sql-functions/utility-functions/catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # catalog
@@ -55,4 +55,4 @@ select catalog();
 
 ## See also
 
-[SET CATALOG](../../sql-statements/data-definition/SET_CATALOG.md): Switches to a destination catalog.
+[SET CATALOG](../../sql-statements/Catalog/SET_CATALOG.md): Switches to a destination catalog.
diff --git a/docs/en/sql-reference/sql-functions/utility-functions/current_role.md b/docs/en/sql-reference/sql-functions/utility-functions/current_role.md
index 599a591505f35f..d04f94a8658b8e 100644
--- a/docs/en/sql-reference/sql-functions/utility-functions/current_role.md
+++ b/docs/en/sql-reference/sql-functions/utility-functions/current_role.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # current_role
diff --git a/docs/en/sql-reference/sql-functions/utility-functions/current_version.md b/docs/en/sql-reference/sql-functions/utility-functions/current_version.md
index 6f27dc7d43a608..0ee5f807a83132 100644
--- a/docs/en/sql-reference/sql-functions/utility-functions/current_version.md
+++ b/docs/en/sql-reference/sql-functions/utility-functions/current_version.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # current_version
diff --git a/docs/en/sql-reference/sql-functions/utility-functions/database.md b/docs/en/sql-reference/sql-functions/utility-functions/database.md
index 6b88e5ebd02b39..a685e13e20d4dd 100644
--- a/docs/en/sql-reference/sql-functions/utility-functions/database.md
+++ b/docs/en/sql-reference/sql-functions/utility-functions/database.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # database
@@ -39,4 +39,4 @@ select database();
 
 ## See also
 
-[USE](../../sql-statements/data-definition/USE.md): Switches to a destination database.
+[USE](../../sql-statements/Database/USE.md): Switches to a destination database.
diff --git a/docs/en/sql-reference/sql-functions/utility-functions/get_query_profile.md b/docs/en/sql-reference/sql-functions/utility-functions/get_query_profile.md
index b2b26e9072bb08..c1c4e4aad3d919 100644
--- a/docs/en/sql-reference/sql-functions/utility-functions/get_query_profile.md
+++ b/docs/en/sql-reference/sql-functions/utility-functions/get_query_profile.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # get_query_profile
diff --git a/docs/en/sql-reference/sql-functions/utility-functions/host_name.md b/docs/en/sql-reference/sql-functions/utility-functions/host_name.md
index 75508a29d417ff..6983f9b7c2709c 100644
--- a/docs/en/sql-reference/sql-functions/utility-functions/host_name.md
+++ b/docs/en/sql-reference/sql-functions/utility-functions/host_name.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # host_name
diff --git a/docs/en/sql-reference/sql-functions/utility-functions/is_role_in_session.md b/docs/en/sql-reference/sql-functions/utility-functions/is_role_in_session.md
index b816dc4f7b7596..53bb011103f651 100644
--- a/docs/en/sql-reference/sql-functions/utility-functions/is_role_in_session.md
+++ b/docs/en/sql-reference/sql-functions/utility-functions/is_role_in_session.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # is_role_in_session
diff --git a/docs/en/sql-reference/sql-functions/utility-functions/isnotnull.md b/docs/en/sql-reference/sql-functions/utility-functions/isnotnull.md
index 7cd266752d6b31..361c247bd3c831 100644
--- a/docs/en/sql-reference/sql-functions/utility-functions/isnotnull.md
+++ b/docs/en/sql-reference/sql-functions/utility-functions/isnotnull.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # isnotnull
diff --git a/docs/en/sql-reference/sql-functions/utility-functions/isnull.md b/docs/en/sql-reference/sql-functions/utility-functions/isnull.md
index bb2be619f3da39..c613bd9f38b06d 100644
--- a/docs/en/sql-reference/sql-functions/utility-functions/isnull.md
+++ b/docs/en/sql-reference/sql-functions/utility-functions/isnull.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # isnull
diff --git a/docs/en/sql-reference/sql-functions/utility-functions/last_query_id.md b/docs/en/sql-reference/sql-functions/utility-functions/last_query_id.md
index 018baf876ab98e..89fd0ed906c15e 100644
--- a/docs/en/sql-reference/sql-functions/utility-functions/last_query_id.md
+++ b/docs/en/sql-reference/sql-functions/utility-functions/last_query_id.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # last_query_id
diff --git a/docs/en/sql-reference/sql-functions/utility-functions/sleep.md b/docs/en/sql-reference/sql-functions/utility-functions/sleep.md
index dd80134b22f838..22ac28e175abc0 100644
--- a/docs/en/sql-reference/sql-functions/utility-functions/sleep.md
+++ b/docs/en/sql-reference/sql-functions/utility-functions/sleep.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # sleep
diff --git a/docs/en/sql-reference/sql-functions/utility-functions/uuid.md b/docs/en/sql-reference/sql-functions/utility-functions/uuid.md
index bd04f49ad08674..f6b7262753e21b 100644
--- a/docs/en/sql-reference/sql-functions/utility-functions/uuid.md
+++ b/docs/en/sql-reference/sql-functions/utility-functions/uuid.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # uuid
diff --git a/docs/en/sql-reference/sql-functions/utility-functions/uuid_numeric.md b/docs/en/sql-reference/sql-functions/utility-functions/uuid_numeric.md
index 2079783571eb61..a553af3359fff9 100644
--- a/docs/en/sql-reference/sql-functions/utility-functions/uuid_numeric.md
+++ b/docs/en/sql-reference/sql-functions/utility-functions/uuid_numeric.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # uuid_numeric
diff --git a/docs/en/sql-reference/sql-functions/utility-functions/version.md b/docs/en/sql-reference/sql-functions/utility-functions/version.md
index f3a507a06e5072..a0b402cc8b18cc 100644
--- a/docs/en/sql-reference/sql-functions/utility-functions/version.md
+++ b/docs/en/sql-reference/sql-functions/utility-functions/version.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # version
diff --git a/docs/en/sql-reference/sql-statements/Administration/ADD_BACKEND_BLACKLIST.md b/docs/en/sql-reference/sql-statements/Administration/ADD_BACKEND_BLACKLIST.md
deleted file mode 100644
index 74ddc9b2c535a5..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/ADD_BACKEND_BLACKLIST.md
+++ /dev/null
@@ -1,49 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ADD BACKEND BLACKLIST
-
-## Description
-
-Adds a BE node to the BE Blacklist. You can manually add BE nodes to the blacklist to forbid the usage of the nodes in query execution, thereby avoiding frequent query failures or other unexpected behaviors caused by failed connections to the BE nodes.
-
-This feature is supported from v3.3.0 onwards. For more information, see [Manage BE Blacklist](../../../administration/management/BE_blacklist.md).
-
-:::note
-
-Only users with the SYSTEM-level BLACKLIST privilege can perform this operation.
-
-:::
-
-By default, StarRocks can automatically manage the BE Blacklist, adding the BE nodes that have lost connection to the blacklist and removing them from the blacklist when the connection is reestablished. However, StarRocks will not remove the BE node from the blacklist if the node is manually blacklisted.
-
-## Syntax
-
-```SQL
-ADD BACKEND BLACKLIST <be_id>[, ...]
-```
-
-## Parameters
-
-`be_id`: ID of the BE node to be blacklisted. You can obtain the BE ID by executing [SHOW BACKENDS](./SHOW_BACKENDS.md).
-
-## Examples
-
-```SQL
--- Obtain BE ID.
-SHOW BACKENDS\G
-*************************** 1. row ***************************
-            BackendId: 10001
-                   IP: xxx.xx.xx.xxx
-                   ...
--- Add BE to the blacklist.
-ADD BACKEND BLACKLIST 10001;
-```
-
-## Relevant SQLs
-
-- [DELETE BACKEND BLACKLIST](./DELETE_BACKEND_BLACKLIST.md)
-- [SHOW BACKEND BLACKLIST](./SHOW_BACKEND_BLACKLIST.md)
-- [SHOW BACKENDS](./SHOW_BACKENDS.md)
-
diff --git a/docs/en/sql-reference/sql-statements/Administration/ADD_SQLBLACKLIST.md b/docs/en/sql-reference/sql-statements/Administration/ADD_SQLBLACKLIST.md
deleted file mode 100644
index 6e9818dd77b27c..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/ADD_SQLBLACKLIST.md
+++ /dev/null
@@ -1,64 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ADD SQLBLACKLIST
-
-## Description
-
-Adds a regular expression to the SQL blacklist to forbid certain SQL patterns. When the SQL Blacklist feature is enabled, StarRocks compares all SQL statements to be executed against the SQL regular expressions in the blacklist. StarRocks does not execute SQLs that match any regular expression in the blacklist and returns an error. This prevents certain SQLs from triggering cluster crashes or unexpected behavior.
-
-For more about SQL Blacklist, see [Manage SQL Blacklist](../../../administration/management/resource_management/Blacklist.md).
-
-:::tip
-
-- This operation requires the SYSTEM-level BLACKLIST privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-- Currently, StarRocks supports adding SELECT statements to the SQL Blacklist.
-
-:::
-
-## Syntax
-
-```SQL
-ADD SQLBLACKLIST "<sql_reg_expr>"
-```
-
-## Parameter
-
-`sql_reg_expr`: the regular expression that is used to specify a certain SQL pattern. To distinguish the special characters in the SQL statement and those in the regular expression, you need to use the escape character `\` as a prefix for the special characters in the SQL statement, such as `(`, `)`, and `+`. Whereas `(` and `)` have been often used in SQL statements, StarRocks can identify `(` and `)` in SQL statements directly. You do not need to use the escape character for `(` and `)`.
-
-## Examples
-
-Example 1: Add `count(\*)` to the SQL blacklist.
-
-```Plain
-mysql> ADD SQLBLACKLIST "select count(\\*) from .+";
-```
-
-Example 2: Add `count(distinct )` to the SQL blacklist.
-
-```Plain
-mysql> ADD SQLBLACKLIST "select count(distinct .+) from .+";
-```
-
-Example 3: Add `order by limit x, y, 1 <= x <=7, 5 <=y <=7` to the SQL blacklist.
-
-```Plain
-mysql> ADD SQLBLACKLIST "select id_int from test_all_type_select1 
-    order by id_int 
-    limit [1-7], [5-7]";
-```
-
-Example 4: Add a complex SQL regular expression to the SQL blacklist. This example is to demonstrate how to use escape characters for `*` and `-` in SQL statements.
-
-```Plain
-mysql> ADD SQLBLACKLIST 
-    "select id_int \\* 4, id_tinyint, id_varchar 
-        from test_all_type_nullable 
-    except select id_int, id_tinyint, id_varchar 
-        from test_basic 
-    except select (id_int \\* 9 \\- 8) \\/ 2, id_tinyint, id_varchar 
-        from test_all_type_nullable2 
-    except select id_int, id_tinyint, id_varchar 
-        from test_basic_nullable";
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/ADMIN_CANCEL_REPAIR.md b/docs/en/sql-reference/sql-statements/Administration/ADMIN_CANCEL_REPAIR.md
deleted file mode 100644
index 4041a77c4bdf4b..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/ADMIN_CANCEL_REPAIR.md
+++ /dev/null
@@ -1,33 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ADMIN CANCEL REPAIR
-
-## Description
-
-This statement is used to cancel repairing specified tables or partitions with high priority.
-
-:::tip
-
-This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```sql
-ADMIN CANCEL REPAIR TABLE table_name[ PARTITION (p1,...)]
-```
-
-Note
->
-> This statement only indicates that the system will no longer repair sharding replicas of specified tables or partitions with high priority. It still repairs these copies by default scheduling.
-
-## Examples
-
-1. Cancel high priority repair
-
-    ```sql
-    ADMIN CANCEL REPAIR TABLE tbl PARTITION(p1);
-    ```
diff --git a/docs/en/sql-reference/sql-statements/Administration/ADMIN_CHECK_TABLET.md b/docs/en/sql-reference/sql-statements/Administration/ADMIN_CHECK_TABLET.md
deleted file mode 100644
index 93a220bce364cb..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/ADMIN_CHECK_TABLET.md
+++ /dev/null
@@ -1,39 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ADMIN CHECK TABLET
-
-## Description
-
-This statement is used to check a group of tablets.
-
-:::tip
-
-This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```sql
-ADMIN CHECK TABLE (tablet_id1, tablet_id2, ...)
-PROPERTIES("type" = "...")
-```
-
-Note:
-
-1. The "type" property in tablet id and PROPERTIES must be specified.
-
-2. Currently, "type" only supports:
-
-   Consistency: Check the consistency of replicas of the tablet. This command is asynchronous. After sending it, StarRocks will start checking the consistency among corresponding tablets. The final results will be shown in the InconsistentTabletNum column in the result of SHOW PROC "/statistic".
-
-## Examples
-
-1. Check the consistency of replicas on a group of specified tablets
-
-    ```sql
-    ADMIN CHECK TABLET (10000, 10001)
-    PROPERTIES("type" = "consistency");
-    ```
diff --git a/docs/en/sql-reference/sql-statements/Administration/ADMIN_REPAIR.md b/docs/en/sql-reference/sql-statements/Administration/ADMIN_REPAIR.md
deleted file mode 100644
index 5e29d0566e82b2..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/ADMIN_REPAIR.md
+++ /dev/null
@@ -1,40 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ADMIN REPAIR
-
-## Description
-
-This statement is used to try and fix the specified tables or partitions first.
-
-:::tip
-
-This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```sql
-ADMIN REPAIR TABLE table_name[ PARTITION (p1,...)]
-```
-
-Note:
-
-1. This statement only means that the system attempts to repair sharding replicas of specified tables or partitions with high priority without the guarantee that the repair will be successful. Users can view the repair status through ADMIN SHOW REPLICA STATUS command.
-2. The default timeout is 14400 seconds (4 hours). Timeout means the system will not repair sharding replicas of specified tables or partitions with high priority. In case of timeout, the command needs to be used again for the intended settings.
-
-## Examples
-
-1. Attempt to repair specified tables
-
-    ```sql
-    ADMIN REPAIR TABLE tbl1;
-    ```
-
-2. Attempt to fix specified partition
-
-    ```sql
-    ADMIN REPAIR TABLE tbl1 PARTITION (p1, p2);
-    ```
diff --git a/docs/en/sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md b/docs/en/sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md
deleted file mode 100644
index 2dd99fdd2150ee..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md
+++ /dev/null
@@ -1,31 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ADMIN SET CONFIG
-
-## Description
-
-This statement is used to set configuration items for the cluster (Currently, only FE dynamic configuration items can be set using this command). You can view these configuration items using the [ADMIN SHOW FRONTEND CONFIG](ADMIN_SET_CONFIG.md) command.
-
-The configurations will be restored to the default values in the `fe.conf` file after the FE restarts. Therefore, we recommend that you also modify the configuration items in `fe.conf` to prevent the loss of modifications.
-
-:::tip
-
-This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```sql
-ADMIN SET FRONTEND CONFIG ("key" = "value")
-```
-
-## Examples
-
-1. Set `disable_balance` to `true`.
-
-    ```sql
-    ADMIN SET FRONTEND CONFIG ("disable_balance" = "true");
-    ```
diff --git a/docs/en/sql-reference/sql-statements/Administration/ADMIN_SET_PARTITION_VERSION.md b/docs/en/sql-reference/sql-statements/Administration/ADMIN_SET_PARTITION_VERSION.md
deleted file mode 100644
index 88afba830ab060..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/ADMIN_SET_PARTITION_VERSION.md
+++ /dev/null
@@ -1,51 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ADMIN SET PARTITION VERSION
-
-## Description
-
-Sets a partition to a specific data version.
-
-Note that manually setting the partition version is a high-risk operation and is recommended only when problems occur in the cluster metadata. In normal circumstances, the version of a partition is consistent with that of the tablets within.
-
-:::tip
-
-This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```sql
-ADMIN SET TABLE <table_name> PARTITION ( <partition_name> | <partition_id> ) 
-TO VERSION <version>
-```
-
-## Parameters
-
-- `table_name`: The name of the table to which the partition belongs.
-- `partition_name`: The name of the partition. You need to specify a partition using either `partition_name` or `partition_id`. For non-partitioned tables, `partition_name` is the same as the table name.
-- `partition_id`: The ID of the partition. You need to specify a partition using either `partition_name` or `partition_id`. For tables with the random bucketing strategy, you can only use `partition_id` to specify the partition.
-- `version`: The version you want to set for the partition.
-
-## Examples
-
-1. Set the version of the non-partitioned table `t1` to `10`.
-
-    ```sql
-    ADMIN SET TABLE t1 PARTITION(t1) TO VERSION 10;
-    ```
-
-2. Set the version of partition `p1` in table `t2` to `10`.
-
-    ```sql
-    ADMIN SET TABLE t2 PARTITION(p1) TO VERSION 10;
-    ```
-
-3. Set the version of the partition whose ID is `123456` to `10`. `t3` is a table with the random bucketing strategy.
-
-    ```sql
-    ADMIN SET TABLE t3 PARTITION('123456') TO VERSION 10;
-    ```
diff --git a/docs/en/sql-reference/sql-statements/Administration/ADMIN_SET_REPLICA_STATUS.md b/docs/en/sql-reference/sql-statements/Administration/ADMIN_SET_REPLICA_STATUS.md
deleted file mode 100644
index 9eaa2b38c5a269..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/ADMIN_SET_REPLICA_STATUS.md
+++ /dev/null
@@ -1,52 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ADMIN SET REPLICA STATUS
-
-## Description
-
-This statement is used to set the status of the specified replicas.
-
-This command currently only used to manually set the status of some replicas to BAD or OK, allowing the system to automatically repair these replicas.
-
-:::tip
-
-This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```sql
-ADMIN SET REPLICA STATUS
-PROPERTIES ("key" = "value", ...)
-```
-
-The following attributes are currently supported:
-
-"table_id': required. Specify a Tablet Id.
-
-"backend_id": required. Specify a Backend Id.
-
-"status": required. Specify the status. Currently only "bad" and "ok" are supported.
-
-If the specified replica does not exist or its status is bad, the replica will be ignored.
-
-Note:
-
-Replicas set to Bad status may be dropped immediately, please proceed with caution.
-
-## Examples
-
-1. Set the replica status of tablet 10003 on BE 10001 to bad.
-
-    ```sql
-    ADMIN SET REPLICA STATUS PROPERTIES("tablet_id" = "10003", "backend_id" = "10001", "status" = "bad");
-    ```
-
-2. Set the replica status of tablet 10003 on BE 10001 to ok.
-
-    ```sql
-    ADMIN SET REPLICA STATUS PROPERTIES("tablet_id" = "10003", "backend_id" = "10001", "status" = "ok");
-    ```
diff --git a/docs/en/sql-reference/sql-statements/Administration/ADMIN_SHOW_CONFIG.md b/docs/en/sql-reference/sql-statements/Administration/ADMIN_SHOW_CONFIG.md
deleted file mode 100644
index daf2a1d3e60044..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/ADMIN_SHOW_CONFIG.md
+++ /dev/null
@@ -1,56 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ADMIN SHOW CONFIG
-
-## Description
-
-Displays the configuration of the current cluster (Currently, only FE configuration items can be displayed). For detailed description of these configuration items, see [Configuration](../../../administration/management/FE_configuration.md).
-
-If you want to set or modify a configuration item, use [ADMIN SET CONFIG](ADMIN_SET_CONFIG.md).
-
-:::tip
-
-This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```sql
-ADMIN SHOW FRONTEND CONFIG [LIKE "pattern"]
-```
-
-Note:
-
-Description of the return parameters:
-
-```plain text
-1. Key:        Configuration item name
-2. Value:      Configuration item value
-3. Type:       Configuration item type 
-4. IsMutable:  Whether it can be set through the ADMIN SET CONFIG command
-5. MasterOnly: Whether it only applies to leader FE
-6. Comment:    Configuration item description 
-```
-
-## Examples
-
-1. View the configuration of the current FE node.
-
-    ```sql
-    ADMIN SHOW FRONTEND CONFIG;
-    ```
-
-2. Search for the configuration of the current FE node by using the `like` predicate.  
-
-    ```plain text
-    mysql> ADMIN SHOW FRONTEND CONFIG LIKE '%check_java_version%';
-    +--------------------+-------+---------+-----------+------------+---------+
-    | Key                | Value | Type    | IsMutable | MasterOnly | Comment |
-    +--------------------+-------+---------+-----------+------------+---------+
-    | check_java_version | true  | boolean | false     | false      |         |
-    +--------------------+-------+---------+-----------+------------+---------+
-    1 row in set (0.00 sec)
-    ```
diff --git a/docs/en/sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_DISTRIBUTION.md b/docs/en/sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_DISTRIBUTION.md
deleted file mode 100644
index 4ba11039376cb5..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_DISTRIBUTION.md
+++ /dev/null
@@ -1,39 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ADMIN SHOW REPLICA DISTRIBUTION
-
-## Description
-
-This statement is used to show the distribution status of a table or a partition replica.
-
-:::tip
-
-This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```sql
-ADMIN SHOW REPLICA DISTRIBUTION FROM [db_name.]tbl_name [PARTITION (p1, ...)]
-```
-
-Note:
-
-The Graph column in the result shows the distribution ratio of replicas graphically.
-
-## Examples
-
-1. View the replica distribution of tables
-
-    ```sql
-    ADMIN SHOW REPLICA DISTRIBUTION FROM tbl1;
-    ```
-
-2. View the replica distribution of partitions in the table
-
-    ```sql
-    ADMIN SHOW REPLICA DISTRIBUTION FROM db1.tbl1 PARTITION(p1, p2);
-    ```
diff --git a/docs/en/sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_STATUS.md b/docs/en/sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_STATUS.md
deleted file mode 100644
index b4599716df04e1..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_STATUS.md
+++ /dev/null
@@ -1,58 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ADMIN SHOW REPLICA STATUS
-
-## Description
-
-This statement is used to show the status of replicas for a table or a partition.
-
-:::tip
-
-This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```sql
-ADMIN SHOW REPLICA STATUS FROM [db_name.]tbl_name [PARTITION (p1, ...)]
-[where_clause]
-```
-
-```sql
-where_clause:
-WHERE STATUS [!]= "replica_status"
-```
-
-```plain text
-replica_status:
-OK:            The replica is healthy
-DEAD:          The Backend of replica is not available
-VERSION_ERROR: The replica data version is missing
-SCHEMA_ERROR:  The schema hash of replica is incorrect
-MISSING:       The replica does not exist
-```
-
-## Examples
-
-1. View the status of all replicas of the table.
-
-    ```sql
-    ADMIN SHOW REPLICA STATUS FROM db1.tbl1;
-    ```
-
-2. View the replica of a partition with the status of VERSION_ERROR.
-
-    ```sql
-    ADMIN SHOW REPLICA STATUS FROM tbl1 PARTITION (p1, p2)
-    WHERE STATUS = "VERSION_ERROR";
-    ```
-
-3. View all unhealthy replicas of the table.
-
-    ```sql
-    ADMIN SHOW REPLICA STATUS FROM tbl1
-    WHERE STATUS != "OK";
-    ```
diff --git a/docs/en/sql-reference/sql-statements/Administration/ALTER_RESOURCE_GROUP.md b/docs/en/sql-reference/sql-statements/Administration/ALTER_RESOURCE_GROUP.md
deleted file mode 100644
index 4927098e5e22e4..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/ALTER_RESOURCE_GROUP.md
+++ /dev/null
@@ -1,64 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ALTER RESOURCE GROUP
-
-## Description
-
-Alters the configuration of a resource group.
-
-:::tip
-
-This operation requires the ALTER privilege on the target resource group. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```SQL
-ALTER RESOURCE GROUP resource_group_name
-{  ADD CLASSIFIER1, CLASSIFIER2, ...
- | DROP (CLASSIFIER_ID_1, CLASSIFIER_ID_2, ...)
- | DROP ALL
- | WITH resource_limit 
-};
-```
-
-## Parameters
-
-| **Parameter**       | **Description**                                              |
-| ------------------- | ------------------------------------------------------------ |
-| resource_group_name | Name of the resource group to be altered.                    |
-| ADD                 | Add classifiers to the resource group. See [CREATE RESOURCE GROUP - Parameters](../Administration/CREATE_RESOURCE_GROUP.md) for more information on how to define a classifier. |
-| DROP                | Drop classifiers from the resource group via classifier IDs. You can check the ID of a classifier via [SHOW RESOURCE GROUP](../Administration/SHOW_RESOURCE_GROUP.md) statement. |
-| DROP ALL            | Drop all classifiers from the resource group.                |
-| WITH                | Modify the resource limits of the resource group. See [CREATE RESOURCE GROUP - Parameters](../Administration/CREATE_RESOURCE_GROUP.md) for more information on how to set resource limits. |
-
-## Examples
-
-Example 1: Adds a new classifier to the resource group `rg1`.
-
-```SQL
-ALTER RESOURCE GROUP rg1 ADD (user='root', query_type in ('select'));
-```
-
-Example 2: Drops classifiers with ID `300040`, `300041`, and `300041` from the resource group `rg1`.
-
-```SQL
-ALTER RESOURCE GROUP rg1 DROP (300040, 300041, 300041);
-```
-
-Example 3: Drops all classifiers from the resource group `rg1`.
-
-```SQL
-ALTER RESOURCE GROUP rg1 DROP ALL;
-```
-
-Example 4: modifies the resource limits of the resource group `rg1`.
-
-```SQL
-ALTER RESOURCE GROUP rg1 WITH (
-    'cpu_core_limit' = '20'
-);
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/ALTER_STORAGE_VOLUME.md b/docs/en/sql-reference/sql-statements/Administration/ALTER_STORAGE_VOLUME.md
deleted file mode 100644
index 3d03e4fab136ea..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/ALTER_STORAGE_VOLUME.md
+++ /dev/null
@@ -1,60 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ALTER STORAGE VOLUME
-
-## Description
-
-Alters the credential properties, comment, or status (`enabled`) of a storage volume. For more about the properties of a storage volume, see [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md). This feature is supported from v3.1.
-
-> **CAUTION**
->
-> - Only users with the ALTER privilege on a specific storage volume can perform this operation.
-> - The `TYPE`, `LOCATIONS`, and other path-related properties of an existing storage volume cannot be altered. You can only alter its credential-related properties. If you changed the path-related configuration items, the databases and tables you created before the change become read-only, and you cannot load data into them.
-> - When `enabled` is `false`, the corresponding storage volume cannot be referenced.
-
-## Syntax
-
-```SQL
-ALTER STORAGE VOLUME [ IF EXISTS ] <storage_volume_name>
-{ COMMENT '<comment_string>'
-| SET ("key" = "value"[,...]) }
-```
-
-## Parameters
-
-| **Parameter**       | **Description**                          |
-| ------------------- | ---------------------------------------- |
-| storage_volume_name | The name of the storage volume to alter. |
-| COMMENT             | The comment on the storage volume.       |
-
-For detailed information on the properties that can be altered or added, see [CREATE STORAGE VOLUME - PROPERTIES](./CREATE_STORAGE_VOLUME.md#properties).
-
-## Examples
-
-Example 1: Disable the storage volume `my_s3_volume`.
-
-```Plain
-MySQL > ALTER STORAGE VOLUME my_s3_volume
-    -> SET ("enabled" = "false");
-Query OK, 0 rows affected (0.01 sec)
-```
-
-Example 2: Alter the credential information of the storage volume `my_s3_volume`.
-
-```Plain
-MySQL > ALTER STORAGE VOLUME my_s3_volume
-    -> SET (
-    ->     "aws.s3.use_instance_profile" = "true"
-    -> );
-Query OK, 0 rows affected (0.00 sec)
-```
-
-## Relevant SQL statements
-
-- [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)
-- [DROP STORAGE VOLUME](./DROP_STORAGE_VOLUME.md)
-- [SET DEFAULT STORAGE VOLUME](./SET_DEFAULT_STORAGE_VOLUME.md)
-- [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md)
-- [SHOW STORAGE VOLUMES](./SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/en/sql-reference/sql-statements/Administration/ALTER_SYSTEM.md b/docs/en/sql-reference/sql-statements/Administration/ALTER_SYSTEM.md
deleted file mode 100644
index e94725c04c964d..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/ALTER_SYSTEM.md
+++ /dev/null
@@ -1,210 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ALTER SYSTEM
-
-## Description
-
-Manages FE, BE, CN, Broker nodes, and metadata snapshots in a cluster.
-
-> **NOTE**
->
-> Only the `cluster_admin` role has the privilege to perform this operation.
-
-## Syntax and parameters
-
-### FE
-
-- Add a Follower FE.
-
-  ```SQL
-  ALTER SYSTEM ADD FOLLOWER "<fe_host>:<edit_log_port>"[, ...]
-  ```
-
-  You can check the status of the new Follower FE by executing `SHOW PROC '/frontends'\G`.
-
-- Drop a Follower FE.
-
-  ```SQL
-  ALTER SYSTEM DROP FOLLOWER "<fe_host>:<edit_log_port>"[, ...]
-  ```
-
-- Add an Observer FE.
-
-  ```SQL
-  ALTER SYSTEM ADD OBSERVER "<fe_host>:<edit_log_port>"[, ...]
-  ```
-
-  You can check the status of the new Observer FE by executing `SHOW PROC '/frontends'\G`.
-
-- Drop an Observer FE.
-
-  ```SQL
-  ALTER SYSTEM DROP OBSERVER "<fe_host>:<edit_log_port>"[, ...]
-  ```
-
-| **Parameter**      | **Required** | **Description**                                                     |
-| ------------------ | ------------ | ------------------------------------------------------------------- |
-| fe_host            | Yes          | The host name or IP address of the FE instance. Use the value of configuration item `priority_networks` if your instance has multiple IP addresses. |
-| edit_log_port      | Yes          | BDB JE communication port of the FE node. Default: `9010`.          |
-
-### BE
-
-- Add a BE node.
-
-  ```SQL
-  ALTER SYSTEM ADD BACKEND "<be_host>:<heartbeat_service_port>"[, ...]
-  ```
-
-  You can check the status of the new BE by executing [SHOW BACKENDS](../Administration/SHOW_BACKENDS.md).
-
-- Drop a BE node.
-
-  > **NOTE**
-  >
-  > You cannot drop the BE node that stores the tablets of single-replica tables.
-
-  ```SQL
-  ALTER SYSTEM DROP BACKEND "<be_host>:<heartbeat_service_port>"[, ...]
-  ```
-
-- Decommission a BE node.
-
-  ```SQL
-  ALTER SYSTEM DECOMMISSION BACKEND "<be_host>:<heartbeat_service_port>"[, ...]
-  ```
-
-  Unlike dropping a BE node, which is removing it forcibly from the cluster, decommissioning a BE means removing it safely. It is an asynchronous operation. When a BE is decommissioned, the data on the BE is first migrated to other BEs, and then the BE is removed from the cluster. Data loading and query will not be affected during the data migration. You can check whether the operation is successful using [SHOW BACKENDS](../Administration/SHOW_BACKENDS.md). If the operation is successful, the decommissioned BE will not be returned. If the operation fails, the BE will still be online. You can manually cancel the operation using [CANCEL DECOMMISSION](../Administration/CANCEL_DECOMMISSION.md).
-
-| **Parameter**          | **Required** | **Description**                                                                            |
-| ---------------------- | ------------ | ------------------------------------------------------------------------------------------ |
-| be_host                | Yes          | The host name or IP address of the BE instance. Use the value of configuration item `priority_networks` if your instance has multiple IP addresses.|
-| heartbeat_service_port | Yes          | BE heartbeat service port. BE uses this port to receive heartbeat from FE. Default: `9050`.|
-
-### CN
-
-- Add a CN node.
-
-  ```SQL
-  ALTER SYSTEM ADD COMPUTE NODE "<cn_host>:<heartbeat_service_port>"[, ...]
-  ```
-
-  You can check the status of the new CN by executing [SHOW COMPUTE NODES](../Administration/SHOW_COMPUTE_NODES.md).
-
-- Drop a CN node.
-
-  ```SQL
-  ALTER SYSTEM DROP COMPUTE NODE "<cn_host>:<heartbeat_service_port>"[, ...]
-  ```
-
-> **NOTE**
->
-> You cannot decommission a CN node using the `ALTER SYSTEM DECOMMISSION` command.
-
-| **Parameter**          | **Required** | **Description**                                                                            |
-| ---------------------- | ------------ | ------------------------------------------------------------------------------------------ |
-| cn_host                | Yes          | The host name or IP address of the CN instance. Use the value of configuration item `priority_networks` if your instance has multiple IP addresses.|
-| heartbeat_service_port | Yes          | CN heartbeat service port. CN uses this port to receive heartbeat from FE. Default: `9050`.|
-
-### Broker
-
-- Add Broker nodes. You can use Broker nodes to load data from HDFS or cloud storage into StarRocks. For more information, see [Load data from HDFS](../../../loading/hdfs_load.md) or [Load data from cloud storage](../../../loading/cloud_storage_load.md).
-
-  ```SQL
-  ALTER SYSTEM ADD BROKER <broker_name> "<broker_host>:<broker_ipc_port>"[, ...]
-  ```
-
-  You can add multiple Broker nodes with one SQL. Each `<broker_host>:<broker_ipc_port>` pair represents one Broker node. And they share a common `broker_name`. You can check the status of the new Broker node by executing [SHOW BROKER](../Administration/SHOW_BROKER.md).
-
-- Drop Broker nodes.
-
-> **CAUTION**
->
-> Dropping a Broker node terminates the tasks currently running on it.
-
-  - Drop one or multiple Broker nodes with the same `broker_name`.
-
-    ```SQL
-    ALTER SYSTEM DROP BROKER <broker_name> "<broker_host>:<broker_ipc_port>"[, ...]
-    ```
-
-  - Drop all Broker nodes with the same `broker_name`.
-
-    ```SQL
-    ALTER SYSTEM DROP ALL BROKER <broker_name>
-    ```
-
-| **Parameter**   | **Required** | **Description**                                                              |
-| --------------- | ------------ | ---------------------------------------------------------------------------- |
-| broker_name     | Yes          | The name of the Broker node(s). Multiple Broker nodes can use the same name. |
-| broker_host     | Yes          | The host name or IP address of the Broker instance. Use the value of configuration item `priority_networks` if your instance has multiple IP addresses.|
-| broker_ipc_port | Yes          | The thrift server port on the Broker node. The Broker node uses it to receive requests from FE or BE. Default: `8000`. |
-
-### Create image
-
-Create an image file. An image file is a snapshot of the FE metadata.
-
-```SQL
-ALTER SYSTEM CREATE IMAGE
-```
-
-Creating an image is an asynchronous operation on the Leader FE. You can check the start time and end time of the operation in the FE log file **fe.log**. A log like `triggering a new checkpoint manually...` indicates that the image creation has started, and a log like `finished save image...` indicates the image has been created.
-
-## Usage notes
-
-- Adding and dropping FE, BE, CN, or Broker nodes are synchronous operations. You cannot cancel the node dropping operations.
-- You cannot drop the FE node in a single-FE cluster.
-- You cannot directly drop the Leader FE node in a multi-FE cluster. To drop it, you must first restart it. After StarRocks elects a new Leader FE, you can then drop the previous one.
-- You cannot drop BE nodes if the number of the remained BE nodes is less than the number of data replicas. For example, if you have three BE nodes in your cluster and you store your data in three replicas, you cannot drop any of the BE nodes. And if you have four BE nodes and three replicas, you can drop one BE node.
-- The difference between dropping and decommissioning a BE node is that, when you drop a BE node, StarRocks removes it forcibly from the cluster and make up the dropped tablets after the removal, and when you decommission a BE node, StarRocks first migrates the tablets on the decommissioned BE node to others, and then removes the node.
-
-## Examples
-
-Example 1: Add a Follower FE node.
-
-```SQL
-ALTER SYSTEM ADD FOLLOWER "x.x.x.x:9010";
-```
-
-Example 2: Drop two Observer FE nodes simultaneously.
-
-```SQL
-ALTER SYSTEM DROP OBSERVER "x.x.x.x:9010","x.x.x.x:9010";
-```
-
-Example 3: Add a BE node.
-
-```SQL
-ALTER SYSTEM ADD BACKEND "x.x.x.x:9050";
-```
-
-Example 4: Drop two BE nodes simultaneously.
-
-```SQL
-ALTER SYSTEM DROP BACKEND "x.x.x.x:9050", "x.x.x.x:9050";
-```
-
-Example 5: Decommission two BE nodes simultaneously.
-
-```SQL
-ALTER SYSTEM DECOMMISSION BACKEND "x.x.x.x:9050", "x.x.x.x:9050";
-```
-
-Example 6: Add two Broker nodes with the same `broker_name` - `hdfs`.
-
-```SQL
-ALTER SYSTEM ADD BROKER hdfs "x.x.x.x:8000", "x.x.x.x:8000";
-```
-
-Example 7: Drop two Broker nodes from `amazon_s3`.
-
-```SQL
-ALTER SYSTEM DROP BROKER amazon_s3 "x.x.x.x:8000", "x.x.x.x:8000";
-```
-
-Example 8: Drop all Broker nodes in `amazon_s3`.
-
-```SQL
-ALTER SYSTEM DROP ALL BROKER amazon_s3;
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/ANALYZE_PROFILE.md b/docs/en/sql-reference/sql-statements/Administration/ANALYZE_PROFILE.md
deleted file mode 100644
index cb92d9ddb56a70..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/ANALYZE_PROFILE.md
+++ /dev/null
@@ -1,43 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ANALYZE PROFILE
-
-## Description
-
-Analyzes a specific query profile on a per-fragment basis, and displays it in a tree structure. For more information about query profile, see [Query Profile Overview](../../../administration/query_profile_overview.md).
-
-This feature is supported from v3.1 onwards.
-
-> **CAUTION**
->
-> Only users with the SELECT privilege on a specific table can perform this operation.
-
-## Syntax
-
-```SQL
-ANALYZE PROFILE FROM '<query_id>', [<plan_node_id>[, ...] ]
-```
-
-## Parameters
-
-| **Parameter** | **Description**                                              |
-| ------------- | ------------------------------------------------------------ |
-| query_id      | The ID of the query. You can obtain it using [SHOW PROFILELIST](./SHOW_PROFILELIST.md). |
-| plan_node_id  | The ID of the plan node in the profile. You can specify this parameter to view the detailed metrics of the corresponding plan node(s). If this parameter is not specified, only the summary metrics of all plan nodes are displayed. |
-
-## Examples
-
-Example 1: Querying the Query Profile without specifying node ID.
-
-![img](../../../_assets/Profile/text_based_profile_without_node_id.jpeg)
-
-Example 2: Querying the Query Profile and specifying node ID as `0`. StarRocks returns all detailed metrics for Node ID `0` and highlights metrics with high usage for easier problem identification.
-
-![img](../../../_assets/Profile/text_based_profile_with_node_id.jpeg)
-
-## Relevant SQLs
-
-- [SHOW PROFILELIST](./SHOW_PROFILELIST.md)
-- [EXPLAIN ANALYZE](./EXPLAIN_ANALYZE.md)
diff --git a/docs/en/sql-reference/sql-statements/Administration/CANCEL_DECOMMISSION.md b/docs/en/sql-reference/sql-statements/Administration/CANCEL_DECOMMISSION.md
deleted file mode 100644
index 131fe103c46172..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/CANCEL_DECOMMISSION.md
+++ /dev/null
@@ -1,29 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CANCEL DECOMMISSION
-
-## Description
-
-This statement is used to undo a node decommission.
-
-:::tip
-
-Only the `cluster_admin` role has the privilege to perform this operation. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-Syntax:
-
-```sql
-CANCEL DECOMMISSION BACKEND "<host>:<heartbeat_port>"[,"<host>:<heartbeat_port>"...]
-```
-
-## Examples
-
-1. Cancel decommission of two nodes.
-
-    ```sql
-    CANCEL DECOMMISSION BACKEND "host1:port", "host2:port";
-    ```
diff --git a/docs/en/sql-reference/sql-statements/Administration/CREATE_FILE.md b/docs/en/sql-reference/sql-statements/Administration/CREATE_FILE.md
deleted file mode 100644
index 36b30adea8f9e1..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/CREATE_FILE.md
+++ /dev/null
@@ -1,66 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE FILE
-
-You can execute the CREATE FILE statement to create a file. After a file is created, the file is uploaded and persisted in StarRocks. In a database, only an admin user can create and delete files, and all users who have permission to access the database can use the files that belong to the database.
-
-:::tip
-
-This operation requires the SYSTEM-level FILE privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Basic concepts
-
-**File**: refers to the file that is created and saved in StarRocks. After a file is created and stored in StarRocks, StarRocks assigns a unique ID to the file. You can find a file based on the database name, catalog, and file name.
-
-## Syntax
-
-```SQL
-CREATE FILE "file_name" [IN database]
-[properties]
-```
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                              |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| file_name     | Yes          | The name of the file.                                        |
-| database      | No           | The database to which the file belongs. If you do not specify this parameter, this parameter defaults to the name of the database that you access in the current session. |
-| properties    | Yes          | The properties of the file. The following table describes the configuration items of properties. |
-
-**Configuration items of** **`properties`**
-
-| **Configuration item** | **Required** | **Description**                                              |
-| ---------------------- | ------------ | ------------------------------------------------------------ |
-| url                    | Yes          | The URL from which you can download the file. Only an unauthenticated HTTP URL is supported. After the file is stored in StarRocks, the URL is no longer needed. |
-| catalog                | Yes          | The category to which the file belongs. You can specify a catalog based on your business requirements. However, in some situations, you must set this parameter to a specific catalog. For example, if you load data from Kafka, StarRocks searches for files in the catalog from the Kafka data source. |
-| MD5                    | No           | The message-digest algorithm that is used to check a file. If you specify this parameter, StarRocks checks the file after the file is downloaded. |
-
-## Examples
-
-- Create a file named  **test.pem** under the category named kafka.
-
-```SQL
-CREATE FILE "test.pem"
-PROPERTIES
-(
-    "url" = "https://starrocks-public.oss-cn-xxxx.aliyuncs.com/key/test.pem",
-    "catalog" = "kafka"
-);
-```
-
-- Create a file named **client.key** under the category named my_catalog.
-
-```SQL
-CREATE FILE "client.key"
-IN my_database
-PROPERTIES
-(
-    "url" = "http://test.bj.bcebos.com/kafka-key/client.key",
-    "catalog" = "my_catalog",
-    "md5" = "b5bb901bf10f99205b39a46ac3557dd9"
-);
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/CREATE_RESOURCE_GROUP.md b/docs/en/sql-reference/sql-statements/Administration/CREATE_RESOURCE_GROUP.md
deleted file mode 100644
index a9a1b80b92b5f2..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/CREATE_RESOURCE_GROUP.md
+++ /dev/null
@@ -1,79 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE RESOURCE GROUP
-
-## Description
-
-Creates a resource group.
-
-For more information, see [Resource group](../../../administration/management/resource_management/resource_group.md).
-
-:::tip
-
-This operation requires the SYSTEM-level CREATE RESOURCE GROUP privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```SQL
-CREATE RESOURCE GROUP resource_group_name 
-TO CLASSIFIER1, CLASSIFIER2, ...
-WITH resource_limit
-```
-
-## Parameters
-
-- `resource_group_name`: The name of the resource group to be created.
-
-- `CLASSIFIER`: Classifiers used to filter the queries on which resource limits are imposed. You must specify a classifier using `"key"="value"` pairs. You can set multiple classifiers for a resource group.
-
-  Parameters for classifiers are listed below:
-
-    | **Parameter** | **Required** | **Description**                                              |
-    | ------------- | ------------ | ------------------------------------------------------------ |
-    | user          | No           | The name of user.                                            |
-    | role          | No           | The role of user.                                            |
-    | query_type    | No           | The type of query. `SELECT` and `INSERT` (from v2.5) are supported. When INSERT tasks hit a resource group with `query_type` as `insert`, the BE node reserves the specified CPU resources for the tasks.   |
-    | source_ip     | No           | The CIDR block from which the query is initiated.            |
-    | db            | No           | The database which the query accesses. It can be specified by strings separated by commas (,). |
-    | plan_cpu_cost_range | No     | The estimated CPU cost range of the query. Its value has an equivalent meaning with the field `PlanCpuCost` in  **fe.audit.log**, and has no unit. The format is `[DOUBLE, DOUBLE)`. The default value is NULL, indicating no such restriction. This parameter is supported from v3.1.4 onwards.                  |
-    | plan_mem_cost_range | No     | The estimated memory cost range of the query. Its value has an equivalent meaning with the field `PlanMemCost` in  **fe.audit.log**, and has no unit. The format is `[DOUBLE, DOUBLE)`. The default value is NULL, indicating no such restriction. This parameter is supported from v3.1.4 onwards.               |
-
-- `resource_limit`: Resource limits to be imposed on the resource group. You must specify resource limits using `"key"="value"` pairs. You can set multiple resource limits for a resource group.
-
-  Parameters for resource limits are listed below:
-
-    | **Parameter**              | **Required** | **Description**                                              |
-    | -------------------------- | ------------ | ------------------------------------------------------------ |
-    | cpu_core_limit             | No           | The soft limit for the number of CPU cores that can be allocated to the resource group on the BE. In actual business scenarios, CPU cores that are allocated to the resource group proportionally scale based on the availability of CPU cores on the BE. Valid values: any non-zero positive integer. |
-    | mem_limit                  | No           | The percentage of memory that can be used for queries in the total memory that is provided by the BE. Unit: %. Valid values: (0, 1). |
-    | concurrency_limit          | No           | The upper limit of concurrent queries in a resource group. It is used to avoid system overload caused by too many concurrent queries. |
-    | max_cpu_cores              | No           | The CPU core limit for this resource group on a single BE node. It takes effect only when it is set to greater than `0`. Range: [0, `avg_be_cpu_cores`], where `avg_be_cpu_cores` represents the average number of CPU cores across all BE nodes. Default: 0. |
-    | big_query_cpu_second_limit | No           | The upper time limit of CPU occupation for a big query. Concurrent queries add up the time. The unit is second. |
-    | big_query_scan_rows_limit  | No           | The upper limit of row counts that can be scanned by a big query. |
-    | big_query_mem_limit        | No           | The upper limit of memory usage of a big query. The unit is byte. |
-    | type                       | No           | The type of resource group. Valid values: <br />`short_query`: When queries from the `short_query` resource group are running, the BE node reserves the CPU cores defined in `short_query.cpu_core_limit`. CPU cores for all `normal` resource groups are limited to "the total CPU cores - `short_query.cpu_core_limit`". <br />`normal`: When no query from the `short_query` resource group is running, the CPU core limit above is not imposed on the `normal` resource groups. <br />Note that you can create only ONE `short_query` resource group in a cluster. |
-
-## Example
-
-Example 1: Creates the resource group `rg1` based on multiple classifiers.
-
-```SQL
-CREATE RESOURCE GROUP rg1
-TO 
-    (user='rg1_user1', role='rg1_role1', query_type in ('select'), source_ip='192.168.x.x/24'),
-    (user='rg1_user2', query_type in ('select'), source_ip='192.168.x.x/24'),
-    (user='rg1_user3', source_ip='192.168.x.x/24'),
-    (user='rg1_user4'),
-    (db='db1')
-WITH ('cpu_core_limit' = '10',
-      'mem_limit' = '20%',
-      'type' = 'normal',
-      'big_query_cpu_second_limit' = '100',
-      'big_query_scan_rows_limit' = '100000',
-      'big_query_mem_limit' = '1073741824'
-);
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md b/docs/en/sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md
deleted file mode 100644
index fd6f967720a210..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md
+++ /dev/null
@@ -1,220 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE STORAGE VOLUME
-
-## Description
-
-Creates a storage volume for a remote storage system. This feature is supported from v3.1.
-
-A storage volume consists of the properties and credential information of the remote data storage. You can reference a storage volume when you create databases and cloud-native tables in a shared-data StarRocks cluster.
-
-> **CAUTION**
->
-> Only users with the CREATE STORAGE VOLUME privilege on the SYSTEM level can perform this operation.
-
-## Syntax
-
-```SQL
-CREATE STORAGE VOLUME [IF NOT EXISTS] <storage_volume_name>
-TYPE = { S3 | AZBLOB }
-LOCATIONS = ('<remote_storage_path>')
-[ COMMENT '<comment_string>' ]
-PROPERTIES
-("key" = "value",...)
-```
-
-## Parameters
-
-| **Parameter**       | **Description**                                              |
-| ------------------- | ------------------------------------------------------------ |
-| storage_volume_name | The name of the storage volume. Please note that you cannot create a storage volume named `builtin_storage_volume` because it is used to create the builtin storage volume. For the naming conventions, see [System limits](../../../reference/System_limit.md).|
-| TYPE                | The type of the remote storage system. Valid values: `S3` and `AZBLOB`. `S3` indicates AWS S3 or S3-compatible storage systems. `AZBLOB` indicates Azure Blob Storage (supported from v3.1.1 onwards). |
-| LOCATIONS           | The storage locations. The format is as follows:<ul><li>For AWS S3 or S3 protocol-compatible storage systems: `s3://<s3_path>`. `<s3_path>` must be an absolute path, for example, `s3://testbucket/subpath`. Note that if you want to enable the [Partitioned Prefix](#partitioned-prefix) feature for the storage volume, you can only specify the bucket name, and specifying a sub-path is not allowed.</li><li>For Azure Blob Storage: `azblob://<azblob_path>`. `<azblob_path>` must be an absolute path, for example, `azblob://testcontainer/subpath`.</li></ul> |
-| COMMENT             | The comment on the storage volume.                           |
-| PROPERTIES          | Parameters in the `"key" = "value"` pairs used to specify the properties and credential information to access the remote storage system. For detailed information, see [PROPERTIES](#properties). |
-
-### PROPERTIES
-
-The table below lists all available properties of storage volumes. Following the table are the usage instructions of these properties, categorized by different scenarios from the perspectives of [Credential information](#credential-information) and [Features](#features).
-
-| **Property**                        | **Description**                                              |
-| ----------------------------------- | ------------------------------------------------------------ |
-| enabled                             | Whether to enable this storage volume. Default: `false`. Disabled storage volume cannot be referenced. |
-| aws.s3.region                       | The region in which your S3 bucket resides, for example, `us-west-2`. |
-| aws.s3.endpoint                     | The endpoint URL used to access your S3 bucket, for example, `https://s3.us-west-2.amazonaws.com`. [Preview] From v3.3.0 onwards, the Amazon S3 Express One Zone storage class is supported, for example, `https://s3express.us-west-2.amazonaws.com`.   |
-| aws.s3.use_aws_sdk_default_behavior | Whether to use the default authentication credential of AWS SDK. Valid values: `true` and `false` (Default). |
-| aws.s3.use_instance_profile         | Whether to use Instance Profile and Assumed Role as credential methods for accessing S3. Valid values: `true` and `false` (Default).<ul><li>If you use IAM user-based credential (Access Key and Secret Key) to access S3, you must specify this item as `false`, and specify `aws.s3.access_key` and `aws.s3.secret_key`.</li><li>If you use Instance Profile to access S3, you must specify this item as `true`.</li><li>If you use Assumed Role to access S3, you must specify this item as `true`, and specify `aws.s3.iam_role_arn`.</li><li>And if you use an external AWS account, you must specify this item as `true`, and specify `aws.s3.iam_role_arn` and `aws.s3.external_id`.</li></ul> |
-| aws.s3.access_key                   | The Access Key ID used to access your S3 bucket.             |
-| aws.s3.secret_key                   | The Secret Access Key used to access your S3 bucket.         |
-| aws.s3.iam_role_arn                 | The ARN of the IAM role that has privileges on your S3 bucket in which your data files are stored. |
-| aws.s3.external_id                  | The external ID of the AWS account that is used for cross-account access to your S3 bucket. |
-| azure.blob.endpoint   | The endpoint of your Azure Blob Storage Account, for example, `https://test.blob.core.windows.net`. |
-| azure.blob.shared_key | The Shared Key used to authorize requests for your Azure Blob Storage. |
-| azure.blob.sas_token  | The shared access signatures (SAS) used to authorize requests for your Azure Blob Storage. |
-| aws.s3.enable_partitioned_prefix    | Whether to enable the Partitioned Prefix feature for the storage volume. Default: `false`. For more information about this feature, see [Partitioned Prefix](#partitioned-prefix). |
-| aws.s3.num_partitioned_prefix       | The number of prefixes to be created for the storage volume. Default: `256`. Valid range: [4, 1024].|
-
-#### Credential information
-
-##### AWS S3
-
-- If you use the default authentication credential of AWS SDK to access S3, set the following properties:
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "aws.s3.region" = "<region>",
-  "aws.s3.endpoint" = "<endpoint_url>",
-  "aws.s3.use_aws_sdk_default_behavior" = "true"
-  ```
-
-- If you use IAM user-based credential (Access Key and Secret Key) to access S3, set the following properties:
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "aws.s3.region" = "<region>",
-  "aws.s3.endpoint" = "<endpoint_url>",
-  "aws.s3.use_aws_sdk_default_behavior" = "false",
-  "aws.s3.use_instance_profile" = "false",
-  "aws.s3.access_key" = "<access_key>",
-  "aws.s3.secret_key" = "<secrete_key>"
-  ```
-
-- If you use Instance Profile to access S3, set the following properties:
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "aws.s3.region" = "<region>",
-  "aws.s3.endpoint" = "<endpoint_url>",
-  "aws.s3.use_aws_sdk_default_behavior" = "false",
-  "aws.s3.use_instance_profile" = "true"
-  ```
-
-- If you use Assumed Role to access S3, set the following properties:
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "aws.s3.region" = "<region>",
-  "aws.s3.endpoint" = "<endpoint_url>",
-  "aws.s3.use_aws_sdk_default_behavior" = "false",
-  "aws.s3.use_instance_profile" = "true",
-  "aws.s3.iam_role_arn" = "<role_arn>"
-  ```
-
-- If you use Assumed Role to access S3 from an external AWS account, set the following properties:
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "aws.s3.region" = "<region>",
-  "aws.s3.endpoint" = "<endpoint_url>",
-  "aws.s3.use_aws_sdk_default_behavior" = "false",
-  "aws.s3.use_instance_profile" = "true",
-  "aws.s3.iam_role_arn" = "<role_arn>",
-  "aws.s3.external_id" = "<external_id>"
-  ```
-
-##### GCS
-
-If you use GCP Cloud Storage, set the following properties:
-
-```SQL
-"enabled" = "{ true | false }",
-
--- For example: us-east-1
-"aws.s3.region" = "<region>",
-
--- For example: https://storage.googleapis.com
-"aws.s3.endpoint" = "<endpoint_url>",
-
-"aws.s3.access_key" = "<access_key>",
-"aws.s3.secret_key" = "<secrete_key>"
-```
-
-##### MinIO
-
-If you use MinIO, set the following properties:
-
-```SQL
-"enabled" = "{ true | false }",
-
--- For example: us-east-1
-"aws.s3.region" = "<region>",
-
--- For example: http://172.26.xx.xxx:39000
-"aws.s3.endpoint" = "<endpoint_url>",
-
-"aws.s3.access_key" = "<access_key>",
-"aws.s3.secret_key" = "<secrete_key>"
-```
-
-##### Azure Blob Storage
-
-Creating a storage volume on Azure Blob Storage is supported from v3.1.1 onwards.
-
-- If you use Shared Key to access Azure Blob Storage, set the following properties:
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "azure.blob.endpoint" = "<endpoint_url>",
-  "azure.blob.shared_key" = "<shared_key>"
-  ```
-
-- If you use shared access signatures (SAS) to access Azure Blob Storage, set the following properties:
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "azure.blob.endpoint" = "<endpoint_url>",
-  "azure.blob.sas_token" = "<sas_token>"
-  ```
-
-:::note
-The hierarchical namespace must be disabled when you create the Azure Blob Storage Account.
-:::
-
-#### Features
-
-##### Partitioned Prefix
-
-From v3.2.4, StarRocks supports creating storage volumes with the Partitioned Prefix feature for S3-compatible object storage systems. When this feature is enabled, StarRocks stores the data into multiple, uniformly prefixed partitions (sub-paths) under the bucket. It can easily multiply StarRocks' read and write performance on data files stored in the bucket because the QPS or throughput limit of the bucket is per partition.
-
-To enable this feature, set the following properties in addition to the above credential-related parameters:
-
-```SQL
-"aws.s3.enable_partitioned_prefix" = "{ true | false }",
-"aws.s3.num_partitioned_prefix" = "<INT>"
-```
-
-:::note
-- The Partitioned Prefix feature is only supported for S3-compatible object storage systems, that is, the `TYPE` of the storage volume must be `S3`.
-- `LOCATIONS` of the storage volume must only contain the bucket name, for example, `s3://testbucket`. Specifying a sub-path after the bucket name is not allowed.
-- Both properties are immutable once the storage volume is created.
-- You cannot enable this feature when create a storage volume by using the FE configuration file **fe.conf**.
-:::
-
-## Examples
-
-Example 1: Create a storage volume `my_s3_volume` for the AWS S3 bucket `defaultbucket`, use the IAM user-based credential (Access Key and Secret Key) to access S3, and enable it.
-
-```SQL
-CREATE STORAGE VOLUME my_s3_volume
-TYPE = S3
-LOCATIONS = ("s3://defaultbucket/test/")
-PROPERTIES
-(
-    "aws.s3.region" = "us-west-2",
-    "aws.s3.endpoint" = "https://s3.us-west-2.amazonaws.com",
-    "aws.s3.use_aws_sdk_default_behavior" = "false",
-    "aws.s3.use_instance_profile" = "false",
-    "aws.s3.access_key" = "xxxxxxxxxx",
-    "aws.s3.secret_key" = "yyyyyyyyyy"
-);
-```
-
-## Relevant SQL statements
-
-- [ALTER STORAGE VOLUME](./ALTER_STORAGE_VOLUME.md)
-- [DROP STORAGE VOLUME](./DROP_STORAGE_VOLUME.md)
-- [SET DEFAULT STORAGE VOLUME](./SET_DEFAULT_STORAGE_VOLUME.md)
-- [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md)
-- [SHOW STORAGE VOLUMES](./SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/en/sql-reference/sql-statements/Administration/DELETE_BACKEND_BLACKLIST.md b/docs/en/sql-reference/sql-statements/Administration/DELETE_BACKEND_BLACKLIST.md
deleted file mode 100644
index caba83d3450359..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/DELETE_BACKEND_BLACKLIST.md
+++ /dev/null
@@ -1,40 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DELETE BACKEND BLACKLIST
-
-## Description
-
-Removes a BE node from the BE Blacklist. Please note that StarRocks will not remove the BE nodes that are manually blacklisted by users.
-
-This feature is supported from v3.3.0 onwards. For more information, see [Manage BE Blacklist](../../../administration/management/BE_blacklist.md).
-
-:::note
-
-Only users with the SYSTEM-level BLACKLIST privilege can perform this operation.
-
-:::
-
-## Syntax
-
-```SQL
-DELETE BACKEND BLACKLIST <be_id>[, ...]
-```
-
-## Parameters
-
-`be_id`: ID of the BE node to be removed from the blacklist. You can obtain the ID of the blacklisted BE by executing [SHOW BACKEND BLACKLIST](./SHOW_BACKEND_BLACKLIST.md).
-
-## Examples
-
-```SQL
-DELETE BACKEND BLACKLIST 10001;
-```
-
-## Relevant SQLs
-
-- [ADD BACKEND BLACKLIST](./ADD_BACKEND_BLACKLIST.md)
-- [SHOW BACKEND BLACKLIST](./SHOW_BACKEND_BLACKLIST.md)
-- [SHOW BACKENDS](./SHOW_BACKENDS.md)
-
diff --git a/docs/en/sql-reference/sql-statements/Administration/DELETE_SQLBLACKLIST.md b/docs/en/sql-reference/sql-statements/Administration/DELETE_SQLBLACKLIST.md
deleted file mode 100644
index 2a5b144aa7eb5b..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/DELETE_SQLBLACKLIST.md
+++ /dev/null
@@ -1,41 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DELETE SQLBLACKLIST
-
-## Description
-
-Deletes an SQL regular expression from the SQL blacklist.
-
-For more about SQL Blacklist, see [Manage SQL Blacklist](../../../administration/management/resource_management/Blacklist.md).
-
-:::tip
-
-This operation requires the SYSTEM-level BLACKLIST privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```SQL
-DELETE SQLBLACKLIST <sql_index_number>
-```
-
-## Parameter
-
-`sql_index_number`: the index number of the SQL regular expression in the blacklist. Separate multiple index numbers with a comma (,) and a space. You can obtain the index number using [SHOW SQLBLACKLIST](../Administration/SHOW_SQLBLACKLIST.md).
-
-## Examples
-
-```Plain
-mysql> DELETE SQLBLACKLIST 3, 4;
-
-mysql> SHOW SQLBLACKLIST;
-+-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| Index | Forbidden SQL                                                                                                                                                                                                                                                                                          |
-+-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| 1     | select count\(\*\) from .+                                                                                                                                                                                                                                                                             |
-| 2     | select id_int \* 4, id_tinyint, id_varchar from test_all_type_nullable except select id_int, id_tinyint, id_varchar from test_basic except select \(id_int \* 9 \- 8\) \/ 2, id_tinyint, id_varchar from test_all_type_nullable2 except select id_int, id_tinyint, id_varchar from test_basic_nullable |
-+-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/DESC_STORAGE_VOLUME.md b/docs/en/sql-reference/sql-statements/Administration/DESC_STORAGE_VOLUME.md
deleted file mode 100644
index 2ba3785a01b59f..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/DESC_STORAGE_VOLUME.md
+++ /dev/null
@@ -1,62 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DESC STORAGE VOLUME
-
-## Description
-
-Describes a storage volume. This feature is supported from v3.1.
-
-> **CAUTION**
->
-> Only users with the USAGE privilege on a specific storage volume can perform this operation.
-
-## Syntax
-
-```SQL
-DESC[RIBE] STORAGE VOLUME <storage_volume_name>
-```
-
-## Parameters
-
-| **Parameter**       | **Description**                             |
-| ------------------- | ------------------------------------------- |
-| storage_volume_name | The name of the storage volume to describe. |
-
-## Return value
-
-| **Return** | **Description**                                              |
-| ---------- | ------------------------------------------------------------ |
-| Name       | The name of the storage volume.                              |
-| Type       | The type of the remote storage system. Valid values: `S3` and `AZBLOB`. |
-| IsDefault  | Whether the storage volume is the default storage volume.    |
-| Location   | The location of the remote storage system.                   |
-| Params     | The credential information used to access the remote storage system. |
-| Enabled    | Whether the storage volume is enabled.                       |
-| Comment    | The comment on the storage volume.                           |
-
-## Examples
-
-Example 1: Describe the storage volume `my_s3_volume`.
-
-```Plain
-MySQL > DESCRIBE STORAGE VOLUME my_s3_volume\G
-*************************** 1. row ***************************
-     Name: my_s3_volume
-     Type: S3
-IsDefault: false
- Location: s3://defaultbucket/test/
-   Params: {"aws.s3.access_key":"xxxxxxxxxx","aws.s3.secret_key":"yyyyyyyyyy","aws.s3.endpoint":"https://s3.us-west-2.amazonaws.com","aws.s3.region":"us-west-2","aws.s3.use_instance_profile":"true","aws.s3.use_aws_sdk_default_behavior":"false"}
-  Enabled: false
-  Comment: 
-1 row in set (0.00 sec)
-```
-
-## Relevant SQL statements
-
-- [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)
-- [ALTER STORAGE VOLUME](./ALTER_STORAGE_VOLUME.md)
-- [DROP STORAGE VOLUME](./DROP_STORAGE_VOLUME.md)
-- [SET DEFAULT STORAGE VOLUME](./SET_DEFAULT_STORAGE_VOLUME.md)
-- [SHOW STORAGE VOLUMES](./SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/en/sql-reference/sql-statements/Administration/DROP_FILE.md b/docs/en/sql-reference/sql-statements/Administration/DROP_FILE.md
deleted file mode 100644
index df357339b21fe8..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/DROP_FILE.md
+++ /dev/null
@@ -1,44 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP FILE
-
-## Description
-
-You can execute the DROP FILE statement to delete a file. When you use this statement to delete a file, the file is deleted both in frontend (FE) memory and in Berkeley DB Java Edition (BDBJE).
-
-:::tip
-
-This operation requires the SYSTEM-level FILE privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```SQL
-DROP FILE "file_name" [FROM database]
-[properties]
-```
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                              |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| file_name     | Yes          | The name of the file.                                        |
-| database      | No           | The database to which a file belongs.                        |
-| properties    | Yes          | The properties of the file. The following table describes the configuration items of properties. |
-
-**Configuration items of** **`properties`**
-
-| **Configuration items** | **Required** | **Description**                       |
-| ----------------------- | ------------ | ------------------------------------- |
-| catalog                 | Yes          | The category to which a file belongs. |
-
-## Examples
-
-Delete a file named **ca.pem**.
-
-```SQL
-DROP FILE "ca.pem" properties("catalog" = "kafka");
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/DROP_RESOURCE_GROUP.md b/docs/en/sql-reference/sql-statements/Administration/DROP_RESOURCE_GROUP.md
deleted file mode 100644
index 00e88c8bf4e347..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/DROP_RESOURCE_GROUP.md
+++ /dev/null
@@ -1,35 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP RESOURCE GROUP
-
-## Description
-
-Drops the specified resource group.
-
-:::tip
-
-This operation requires the DROP privilege on the target resource group. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```SQL
-DROP RESOURCE GROUP <resource_group_name>
-```
-
-## Parameters
-
-| **Parameter**       | **Description**                           |
-| ------------------- | ----------------------------------------- |
-| resource_group_name | Name of the resource group to be dropped. |
-
-## Example
-
-Example 1: Drops the resource group `rg1`.
-
-```SQL
-DROP RESOURCE GROUP rg1;
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/DROP_STORAGE_VOLUME.md b/docs/en/sql-reference/sql-statements/Administration/DROP_STORAGE_VOLUME.md
deleted file mode 100644
index 21fbc356246c78..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/DROP_STORAGE_VOLUME.md
+++ /dev/null
@@ -1,44 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP STORAGE VOLUME
-
-## Description
-
-Drops a storage volume. Dropped storage volumes cannot be referenced anymore. This feature is supported from v3.1.
-
-> **CAUTION**
->
-> - Only users with the DROP privilege on a specific storage volume can perform this operation.
-> - The default storage volume and the built-in storage volume `builtin_storage_volume` cannot be dropped. You can use [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md) to check whether a storage volume is the default storage volume.
-> - Storage volumes that are referenced by existing databases or cloud-native tables cannot be dropped.
-
-## Syntax
-
-```SQL
-DROP STORAGE VOLUME [ IF EXISTS ] <storage_volume_name>
-```
-
-## Parameters
-
-| **Parameter**       | **Description**                         |
-| ------------------- | --------------------------------------- |
-| storage_volume_name | The name of the storage volume to drop. |
-
-## Examples
-
-Example 1: Drop the storage volume `my_s3_volume`.
-
-```Plain
-MySQL > DROP STORAGE VOLUME my_s3_volume;
-Query OK, 0 rows affected (0.01 sec)
-```
-
-## Relevant SQL statements
-
-- [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)
-- [ALTER STORAGE VOLUME](./ALTER_STORAGE_VOLUME.md)
-- [SET DEFAULT STORAGE VOLUME](./SET_DEFAULT_STORAGE_VOLUME.md)
-- [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md)
-- [SHOW STORAGE VOLUMES](./SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/en/sql-reference/sql-statements/Administration/EXPLAIN.md b/docs/en/sql-reference/sql-statements/Administration/EXPLAIN.md
deleted file mode 100644
index 2e228dc6f68cca..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/EXPLAIN.md
+++ /dev/null
@@ -1,438 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# EXPLAIN
-
-## Description
-
-Shows the logical or physical execution plans for a query statement. For instructions on how to analyze a query plan, refer to [Plan analysis](../../../administration/Query_planning.md#plan-analysis).
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```SQL
-EXPLAIN [ LOGICAL | VERBOSE | COSTS ] <query>
-```
-
-:::tip
-
-The level of execution plan detail returned: EXPLAIN LOGICAL < EXPLAIN < EXPLAIN VERBOSE < EXPLAIN COSTS.
-
-In most cases, using EXPLAIN is sufficient. EXPLAIN VERBOSE and EXPLAIN COSTS will print a lot of internal information, which is mainly used for debugging the execution plan.
-
-:::
-
-## Parameters
-
-| **Parameter** | **Description**                                            |
-| ------------- | ---------------------------------------------------------- |
-| LOGICAL       | Shows the simple logical execution plans.                  |
-| VERBOSE       | Shows the detailed logical execution plans, including data types, nullable information, and optimization strategy. |
-| COSTS         | Shows the detailed logical execution plans, including column statisitics. |
-| query         | The query statement whose execution plan you want to view. |
-
-## Return value
-
-Returns the execution plan of the input query statement.
-
-| **Return**     | **Description**                                                                  |
-| -------------- |----------------------------------------------------------------------------------|
-| avgRowSize     | The average size of the scanned data rows.                                       |
-| cardinality    | The total number of data rows in the scanned table.                              |
-| colocate       | Whether the table is in colocate mode.                                           |
-| numNodes       | The number of nodes to scan.                                                     |
-| rollup         | The Rollup materialized view that is used.                                       |
-| preaggregation | The status of preaggregation.                                                    |
-| predicates     | Predicates in the query.                                                         |
-| column statistics | The statictics of the column，sequence: MIN, MAX, NULL numbers，average size，and cardinality. |
-
-## Examples
-
-### EXPLAIN
-
-```Plain
-MySQL tpcds> explain select 
-    sr_customer_sk as ctr_customer_sk, 
-    sr_store_sk as ctr_store_sk, 
-    sum(SR_RETURN_AMT) as ctr_total_return 
-  from 
-    store_returns, 
-    date_dim 
-  where 
-    sr_returned_date_sk = d_date_sk and d_year = 2000 
-  group by 
-    sr_customer_sk, 
-    sr_store_sk
-+-----------------------------------------------------------------------------+
-| Explain String                                                              |
-+-----------------------------------------------------------------------------+
-| PLAN FRAGMENT 0                                                             |
-|  OUTPUT EXPRS:5: sr_customer_sk | 9: sr_store_sk | 49: sum                  |
-|   PARTITION: UNPARTITIONED                                                  |
-|                                                                             |
-|   RESULT SINK                                                               |
-|                                                                             |
-|   9:EXCHANGE                                                                |
-|                                                                             |
-| PLAN FRAGMENT 1                                                             |
-|  OUTPUT EXPRS:                                                              |
-|   PARTITION: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk            |
-|                                                                             |
-|   STREAM DATA SINK                                                          |
-|     EXCHANGE ID: 09                                                         |
-|     UNPARTITIONED                                                           |
-|                                                                             |
-|   8:AGGREGATE (merge finalize)                                              |
-|   |  output: sum(49: sum)                                                   |
-|   |  group by: 5: sr_customer_sk, 9: sr_store_sk                            |
-|   |                                                                         |
-|   7:EXCHANGE                                                                |
-|                                                                             |
-| PLAN FRAGMENT 2                                                             |
-|  OUTPUT EXPRS:                                                              |
-|   PARTITION: RANDOM                                                         |
-|                                                                             |
-|   STREAM DATA SINK                                                          |
-|     EXCHANGE ID: 07                                                         |
-|     HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                     |
-|                                                                             |
-|   6:AGGREGATE (update serialize)                                            |
-|   |  STREAMING                                                              |
-|   |  output: sum(12: sr_return_amt)                                         |
-|   |  group by: 5: sr_customer_sk, 9: sr_store_sk                            |
-|   |                                                                         |
-|   5:Project                                                                 |
-|   |  <slot 5> : 5: sr_customer_sk                                           |
-|   |  <slot 9> : 9: sr_store_sk                                              |
-|   |  <slot 12> : 12: sr_return_amt                                          |
-|   |                                                                         |
-|   4:HASH JOIN                                                               |
-|   |  join op: INNER JOIN (BROADCAST)                                        |
-|   |  colocate: false, reason:                                               |
-|   |  equal join conjunct: 3: sr_returned_date_sk = 21: d_date_sk            |
-|   |                                                                         |
-|   |----3:EXCHANGE                                                           |
-|   |                                                                         |
-|   0:OlapScanNode                                                            |
-|      TABLE: store_returns                                                   |
-|      PREAGGREGATION: ON                                                     |
-|      PREDICATES: 3: sr_returned_date_sk IS NOT NULL                         |
-|      partitions=1/1                                                         |
-|      rollup: store_returns                                                  |
-|      tabletRatio=10/10                                                      |
-|      tabletList=10241,10243,10245,10247,10249,10251,10253,10255,10257,10259 |
-|      cardinality=277502                                                     |
-|      avgRowSize=20.0                                                        |
-|                                                                             |
-| PLAN FRAGMENT 3                                                             |
-|  OUTPUT EXPRS:                                                              |
-|   PARTITION: RANDOM                                                         |
-|                                                                             |
-|   STREAM DATA SINK                                                          |
-|     EXCHANGE ID: 03                                                         |
-|     UNPARTITIONED                                                           |
-|                                                                             |
-|   2:Project                                                                 |
-|   |  <slot 21> : 21: d_date_sk                                              |
-|   |                                                                         |
-|   1:OlapScanNode                                                            |
-|      TABLE: date_dim                                                        |
-|      PREAGGREGATION: ON                                                     |
-|      PREDICATES: 27: d_year = 2000                                          |
-|      partitions=1/1                                                         |
-|      rollup: date_dim                                                       |
-|      tabletRatio=5/5                                                        |
-|      tabletList=11543,11545,11547,11549,11551                               |
-|      cardinality=362                                                        |
-|      avgRowSize=8.0                                                         |
-+-----------------------------------------------------------------------------+
-79 rows in set
-```
-
-### EXPLAIN LOGICAL
-
-```Plain
-MySQL tpcds> explain logical select 
-    sr_customer_sk as ctr_customer_sk, 
-    sr_store_sk as ctr_store_sk, 
-    sum(SR_RETURN_AMT) as ctr_total_return 
-  from 
-    store_returns, 
-    date_dim 
-  where 
-    sr_returned_date_sk = d_date_sk and d_year = 2000 
-  group by 
-    sr_customer_sk, 
-    sr_store_sk
- 
-+---------------------------------------------------------------------------------------------------------------------------------+
-| Explain String                                                                                                                  |
-+---------------------------------------------------------------------------------------------------------------------------------+
-| - Output => [5:sr_customer_sk, 9:sr_store_sk, 49:sum]                                                                           |
-|     - AGGREGATE(GLOBAL) [5:sr_customer_sk, 9:sr_store_sk]                                                                       |
-|             Estimates: {row: 49728, cpu: 795660.58, memory: 795660.58, network: 0.00, cost: 8405375.45}                         |
-|             49:sum := sum(49:sum)                                                                                               |
-|         - EXCHANGE(SHUFFLE) [5, 9]                                                                                              |
-|                 Estimates: {row: 49728, cpu: 79566.06, memory: 0.00, network: 0.00, cost: 6416223.99}                           |
-|             - AGGREGATE(LOCAL) [5:sr_customer_sk, 9:sr_store_sk]                                                                |
-|                     Estimates: {row: 49728, cpu: 119349.09, memory: 79566.06, network: 0.00, cost: 6376440.96}                  |
-|                     49:sum := sum(12:sr_return_amt)                                                                             |
-|                 - HASH/INNER JOIN [3:sr_returned_date_sk = 21:d_date_sk] => [5:sr_customer_sk, 9:sr_store_sk, 12:sr_return_amt] |
-|                         Estimates: {row: 49728, cpu: 6744977.39, memory: 1446.51, network: 0.00, cost: 6157634.30}              |
-|                     - SCAN [store_returns] => [3:sr_returned_date_sk, 5:sr_customer_sk, 9:sr_store_sk, 12:sr_return_amt]        |
-|                             Estimates: {row: 277502, cpu: 5550040.00, memory: 0.00, network: 0.00, cost: 2775020.00}            |
-|                             partitionRatio: 1/1, tabletRatio: 10/10                                                             |
-|                             predicate: 3:sr_returned_date_sk IS NOT NULL                                                        |
-|                     - EXCHANGE(BROADCAST)                                                                                       |
-|                             Estimates: {row: 361, cpu: 1446.51, memory: 1446.51, network: 1446.51, cost: 7232.57}               |
-|                         - SCAN [date_dim] => [21:d_date_sk]                                                                     |
-|                                 Estimates: {row: 361, cpu: 2893.03, memory: 0.00, network: 0.00, cost: 1446.51}                 |
-|                                 partitionRatio: 1/1, tabletRatio: 5/5                                                           |
-|                                 predicate: 27:d_year = 2000                                                                     |
-+---------------------------------------------------------------------------------------------------------------------------------+
-21 rows in set
-```
-
-### EXPLAIN VERBOSE
-
-```Plain
-MySQL tpcds> explain verbose select 
-    sr_customer_sk as ctr_customer_sk, 
-    sr_store_sk as ctr_store_sk, 
-    sum(SR_RETURN_AMT) as ctr_total_return 
-  from 
-    store_returns, 
-    date_dim 
-  where 
-    sr_returned_date_sk = d_date_sk and d_year = 2000 
-  group by 
-    sr_customer_sk, 
-    sr_store_sk
- 
-+---------------------------------------------------------------------------------------------------------------------------------------------------------+
-| Explain String                                                                                                                                          |
-+---------------------------------------------------------------------------------------------------------------------------------------------------------+
-| RESOURCE GROUP: default_wg                                                                                                                              |
-|                                                                                                                                                         |
-| PLAN FRAGMENT 0(F04)                                                                                                                                    |
-|   Fragment Cost: 0.0                                                                                                                                    |
-|   Output Exprs:5: sr_customer_sk | 9: sr_store_sk | 49: sum                                                                                             |
-|   Input Partition: UNPARTITIONED                                                                                                                        |
-|   RESULT SINK                                                                                                                                           |
-|                                                                                                                                                         |
-|   9:EXCHANGE                                                                                                                                            |
-|      cardinality: 49729                                                                                                                                 |
-|                                                                                                                                                         |
-| PLAN FRAGMENT 1(F03)                                                                                                                                    |
-|   Fragment Cost: 2028934.4876271961                                                                                                                     |
-|                                                                                                                                                         |
-|   Input Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                  |
-|   OutPut Partition: UNPARTITIONED                                                                                                                       |
-|   OutPut Exchange Id: 09                                                                                                                                |
-|                                                                                                                                                         |
-|   8:AGGREGATE (merge finalize)                                                                                                                          |
-|   |  aggregate: sum[([49: sum, DECIMAL128(38,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true]         |
-|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |                                                                                                                                                     |
-|   7:EXCHANGE                                                                                                                                            |
-|      distribution type: SHUFFLE                                                                                                                         |
-|      partition exprs: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                       |
-|      cardinality: 49729                                                                                                                                 |
-|                                                                                                                                                         |
-| PLAN FRAGMENT 2(F00)                                                                                                                                    |
-|   Fragment Cost: 6376440.959353934                                                                                                                      |
-|                                                                                                                                                         |
-|   Input Partition: RANDOM                                                                                                                               |
-|   OutPut Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                 |
-|   OutPut Exchange Id: 07                                                                                                                                |
-|                                                                                                                                                         |
-|   6:AGGREGATE (update serialize)                                                                                                                        |
-|   |  STREAMING                                                                                                                                          |
-|   |  aggregate: sum[([12: sr_return_amt, DECIMAL64(7,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true] |
-|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |                                                                                                                                                     |
-|   5:Project                                                                                                                                             |
-|   |  output columns:                                                                                                                                    |
-|   |  5 <-> [5: sr_customer_sk, INT, true]                                                                                                               |
-|   |  9 <-> [9: sr_store_sk, INT, true]                                                                                                                  |
-|   |  12 <-> [12: sr_return_amt, DECIMAL64(7,2), true]                                                                                                   |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |                                                                                                                                                     |
-|   4:HASH JOIN                                                                                                                                           |
-|   |  join op: INNER JOIN (BROADCAST)                                                                                                                    |
-|   |  equal join conjunct: [3: sr_returned_date_sk, INT, true] = [21: d_date_sk, INT, false]                                                             |
-|   |  build runtime filters:                                                                                                                             |
-|   |  - filter_id = 0, build_expr = (21: d_date_sk), remote = false                                                                                      |
-|   |  output columns: 5, 9, 12                                                                                                                           |
-|   |  can local shuffle: true                                                                                                                            |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |                                                                                                                                                     |
-|   |----3:EXCHANGE                                                                                                                                       |
-|   |       distribution type: BROADCAST                                                                                                                  |
-|   |       cardinality: 362                                                                                                                              |
-|   |                                                                                                                                                     |
-|   0:OlapScanNode                                                                                                                                        |
-|      table: store_returns, rollup: store_returns                                                                                                        |
-|      preAggregation: on                                                                                                                                 |
-|      Predicates: 3: sr_returned_date_sk IS NOT NULL                                                                                                     |
-|      partitionsRatio=1/1, tabletsRatio=10/10                                                                                                            |
-|      tabletList=10241,10243,10245,10247,10249,10251,10253,10255,10257,10259                                                                             |
-|      actualRows=287514, avgRowSize=20.0                                                                                                                 |
-|      cardinality: 277502                                                                                                                                |
-|      probe runtime filters:                                                                                                                             |
-|      - filter_id = 0, probe_expr = (3: sr_returned_date_sk)                                                                                             |
-|                                                                                                                                                         |
-| PLAN FRAGMENT 3(F01)                                                                                                                                    |
-|   Fragment Cost: 1446.5148514851485                                                                                                                     |
-|                                                                                                                                                         |
-|   Input Partition: RANDOM                                                                                                                               |
-|   OutPut Partition: UNPARTITIONED                                                                                                                       |
-|   OutPut Exchange Id: 03                                                                                                                                |
-|                                                                                                                                                         |
-|   2:Project                                                                                                                                             |
-|   |  output columns:                                                                                                                                    |
-|   |  21 <-> [21: d_date_sk, INT, false]                                                                                                                 |
-|   |  cardinality: 362                                                                                                                                   |
-|   |                                                                                                                                                     |
-|   1:OlapScanNode                                                                                                                                        |
-|      table: date_dim, rollup: date_dim                                                                                                                  |
-|      preAggregation: on                                                                                                                                 |
-|      Predicates: [27: d_year, INT, false] = 2000                                                                                                        |
-|      partitionsRatio=1/1, tabletsRatio=5/5                                                                                                              |
-|      tabletList=11543,11545,11547,11549,11551                                                                                                           |
-|      actualRows=73049, avgRowSize=8.0                                                                                                                   |
-|      cardinality: 362                                                                                                                                   |
-+---------------------------------------------------------------------------------------------------------------------------------------------------------+
-```
-
-### EXPLAIN COSTS
-
-```Plain
-+---------------------------------------------------------------------------------------------------------------------------------------------------------+
-| Explain String                                                                                                                                          |
-+---------------------------------------------------------------------------------------------------------------------------------------------------------+
-| PLAN FRAGMENT 0(F04)                                                                                                                                    |
-|   Output Exprs:5: sr_customer_sk | 9: sr_store_sk | 49: sum                                                                                             |
-|   Input Partition: UNPARTITIONED                                                                                                                        |
-|   RESULT SINK                                                                                                                                           |
-|                                                                                                                                                         |
-|   9:EXCHANGE                                                                                                                                            |
-|      cardinality: 49729                                                                                                                                 |
-|                                                                                                                                                         |
-| PLAN FRAGMENT 1(F03)                                                                                                                                    |
-|                                                                                                                                                         |
-|   Input Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                  |
-|   OutPut Partition: UNPARTITIONED                                                                                                                       |
-|   OutPut Exchange Id: 09                                                                                                                                |
-|                                                                                                                                                         |
-|   8:AGGREGATE (merge finalize)                                                                                                                          |
-|   |  aggregate: sum[([49: sum, DECIMAL128(38,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true]         |
-|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |  column statistics:                                                                                                                                 |
-|   |  * sr_customer_sk-->[1.0, 100000.0, 2.010867271218169E-5, 4.0, 49728.786461450894] ESTIMATE                                                         |
-|   |  * sr_store_sk-->[1.0, 10.0, 0.14285714285714285, 4.0, 6.0] ESTIMATE                                                                                |
-|   |  * sum-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                                    |
-|   |                                                                                                                                                     |
-|   7:EXCHANGE                                                                                                                                            |
-|      distribution type: SHUFFLE                                                                                                                         |
-|      partition exprs: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                       |
-|      cardinality: 49729                                                                                                                                 |
-|                                                                                                                                                         |
-| PLAN FRAGMENT 2(F00)                                                                                                                                    |
-|                                                                                                                                                         |
-|   Input Partition: RANDOM                                                                                                                               |
-|   OutPut Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                 |
-|   OutPut Exchange Id: 07                                                                                                                                |
-|                                                                                                                                                         |
-|   6:AGGREGATE (update serialize)                                                                                                                        |
-|   |  STREAMING                                                                                                                                          |
-|   |  aggregate: sum[([12: sr_return_amt, DECIMAL64(7,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true] |
-|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |  column statistics:                                                                                                                                 |
-|   |  * sr_customer_sk-->[1.0, 100000.0, 2.010867271218169E-5, 4.0, 49728.786461450894] ESTIMATE                                                         |
-|   |  * sr_store_sk-->[1.0, 10.0, 0.14285714285714285, 4.0, 6.0] ESTIMATE                                                                                |
-|   |  * sum-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                                    |
-|   |                                                                                                                                                     |
-|   5:Project                                                                                                                                             |
-|   |  output columns:                                                                                                                                    |
-|   |  5 <-> [5: sr_customer_sk, INT, true]                                                                                                               |
-|   |  9 <-> [9: sr_store_sk, INT, true]                                                                                                                  |
-|   |  12 <-> [12: sr_return_amt, DECIMAL64(7,2), true]                                                                                                   |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |  column statistics:                                                                                                                                 |
-|   |  * sr_customer_sk-->[1.0, 100000.0, 0.034836564480338346, 4.0, 49728.786461450894] ESTIMATE                                                         |
-|   |  * sr_store_sk-->[1.0, 10.0, 0.034996556689413386, 4.0, 6.0] ESTIMATE                                                                               |
-|   |  * sr_return_amt-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                          |
-|   |                                                                                                                                                     |
-|   4:HASH JOIN                                                                                                                                           |
-|   |  join op: INNER JOIN (BROADCAST)                                                                                                                    |
-|   |  equal join conjunct: [3: sr_returned_date_sk, INT, true] = [21: d_date_sk, INT, false]                                                             |
-|   |  build runtime filters:                                                                                                                             |
-|   |  - filter_id = 0, build_expr = (21: d_date_sk), remote = false                                                                                      |
-|   |  output columns: 5, 9, 12                                                                                                                           |
-|   |  can local shuffle: true                                                                                                                            |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |  column statistics:                                                                                                                                 |
-|   |  * sr_returned_date_sk-->[2450820.0, 2452822.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                               |
-|   |  * sr_customer_sk-->[1.0, 100000.0, 0.034836564480338346, 4.0, 49728.786461450894] ESTIMATE                                                         |
-|   |  * sr_store_sk-->[1.0, 10.0, 0.034996556689413386, 4.0, 6.0] ESTIMATE                                                                               |
-|   |  * sr_return_amt-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                          |
-|   |  * d_date_sk-->[2450820.0, 2452822.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                                         |
-|   |                                                                                                                                                     |
-|   |----3:EXCHANGE                                                                                                                                       |
-|   |       distribution type: BROADCAST                                                                                                                  |
-|   |       cardinality: 362                                                                                                                              |
-|   |                                                                                                                                                     |
-|   0:OlapScanNode                                                                                                                                        |
-|      table: store_returns, rollup: store_returns                                                                                                        |
-|      preAggregation: on                                                                                                                                 |
-|      Predicates: 3: sr_returned_date_sk IS NOT NULL                                                                                                     |
-|      partitionsRatio=1/1, tabletsRatio=10/10                                                                                                            |
-|      tabletList=10241,10243,10245,10247,10249,10251,10253,10255,10257,10259                                                                             |
-|      actualRows=287514, avgRowSize=20.0                                                                                                                 |
-|      cardinality: 277502                                                                                                                                |
-|      probe runtime filters:                                                                                                                             |
-|      - filter_id = 0, probe_expr = (3: sr_returned_date_sk)                                                                                             |
-|      column statistics:                                                                                                                                 |
-|      * sr_returned_date_sk-->[2450820.0, 2452822.0, 0.0, 4.0, 2018.0] ESTIMATE                                                                          |
-|      * sr_customer_sk-->[1.0, 100000.0, 0.034836564480338346, 4.0, 86524.0] ESTIMATE                                                                    |
-|      * sr_store_sk-->[1.0, 10.0, 0.034996556689413386, 4.0, 6.0] ESTIMATE                                                                               |
-|      * sr_return_amt-->[0.0, 16917.12, 0.034878301578357924, 8.0, 113968.0] ESTIMATE                                                                    |
-|                                                                                                                                                         |
-| PLAN FRAGMENT 3(F01)                                                                                                                                    |
-|                                                                                                                                                         |
-|   Input Partition: RANDOM                                                                                                                               |
-|   OutPut Partition: UNPARTITIONED                                                                                                                       |
-|   OutPut Exchange Id: 03                                                                                                                                |
-|                                                                                                                                                         |
-|   2:Project                                                                                                                                             |
-|   |  output columns:                                                                                                                                    |
-|   |  21 <-> [21: d_date_sk, INT, false]                                                                                                                 |
-|   |  cardinality: 362                                                                                                                                   |
-|   |  column statistics:                                                                                                                                 |
-|   |  * d_date_sk-->[2415022.0, 2488070.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                                         |
-|   |                                                                                                                                                     |
-|   1:OlapScanNode                                                                                                                                        |
-|      table: date_dim, rollup: date_dim                                                                                                                  |
-|      preAggregation: on                                                                                                                                 |
-|      Predicates: [27: d_year, INT, false] = 2000                                                                                                        |
-|      partitionsRatio=1/1, tabletsRatio=5/5                                                                                                              |
-|      tabletList=11543,11545,11547,11549,11551                                                                                                           |
-|      actualRows=73049, avgRowSize=8.0                                                                                                                   |
-|      cardinality: 362                                                                                                                                   |
-|      column statistics:                                                                                                                                 |
-|      * d_date_sk-->[2415022.0, 2488070.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                                         |
-|      * d_year-->[2000.0, 2000.0, 0.0, 4.0, 202.0] ESTIMATE                                                                                              |
-+---------------------------------------------------------------------------------------------------------------------------------------------------------+
-114 rows in set
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/EXPLAIN_ANALYZE.md b/docs/en/sql-reference/sql-statements/Administration/EXPLAIN_ANALYZE.md
deleted file mode 100644
index aef549d31e1dc0..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/EXPLAIN_ANALYZE.md
+++ /dev/null
@@ -1,44 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# EXPLAIN ANALYZE
-
-## Description
-
-Executes the specified SQL statement, and shows the query profile of this statement. For more information about query profile, see [Query Profile Overview](../../../administration/query_profile_overview.md).
-
-This feature is supported from v3.1 onwards.
-
-> **CAUTION**
->
-> Only users with the SELECT or INSERT privilege on a specific table can perform this operation.
-
-## Syntax
-
-```SQL
-EXPLAIN ANALYZE <statement>
-```
-
-## Parameters
-
-`statement`: the SQL statement of which to show the query profile. Both [SELECT](../data-manipulation/SELECT.md) and [INSERT INTO](../data-manipulation/INSERT.md) are supported.
-
-## Usage notes
-
-Please note that when you analyze the profiles of an INSERT INTO statement, no data will actually be inserted. By default, the transaction is aborted, ensuring that no unintended changes are made to the data in the process of profile analysis.
-
-## Examples
-
-Example 1: Simulate and analyze a SELECT statement. The query result are discarded.
-
-![img](../../../_assets/Profile/text_based_explain_analyze_select.jpeg)
-
-Example 2: Simulate and analyze an INSERT INTO statement. The loading transaction will be aborted.
-
-![img](../../../_assets/Profile/text_based_explain_analyze_insert.jpeg)
-
-## Relevant SQLs
-
-- [SHOW PROFILELIST](./SHOW_PROFILELIST.md)
-- [ANALYZE PROFILE](./EXPLAIN_ANALYZE.md)
diff --git a/docs/en/sql-reference/sql-statements/Administration/INSTALL_PLUGIN.md b/docs/en/sql-reference/sql-statements/Administration/INSTALL_PLUGIN.md
deleted file mode 100644
index d6212e6ad99556..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/INSTALL_PLUGIN.md
+++ /dev/null
@@ -1,57 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# INSTALL PLUGIN
-
-## Description
-
-This statement is used to install a plugin.
-
-:::tip
-
-This operation requires the SYSTEM-level PLUGIN privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```sql
-INSTALL PLUGIN FROM [source] [PROPERTIES ("key"="value", ...)]
-```
-
-3 types of sources are supported:
-
-```plain text
-1. An absolute path that directs to a zip file
-2. An absolute path that directs to a plugin directory 
-3. A http or https download link that directs to a zip file
-```
-
-PROPERTIES supports setting some configurations of plugins, such as setting the  md5sum value of the zip file, etc.
-
-## Examples
-
-1. Install a plugin from local zip file:
-
-    ```sql
-    INSTALL PLUGIN FROM "/home/users/starrocks/auditdemo.zip";
-    ```
-
-2. Install a plugin from local inpath:
-
-    ```sql
-    INSTALL PLUGIN FROM "/home/users/starrocks/auditdemo/";
-    ```
-
-3. Download and install a plugin:
-
-    ```sql
-    INSTALL PLUGIN FROM "http://mywebsite.com/plugin.zip";
-    ```
-
-4. Download and install a plugin. Meanwhile, set the md5sum value of the zip file:
-
-    ```sql
-    INSTALL PLUGIN FROM "http://mywebsite.com/plugin.zip" PROPERTIES("md5sum" = "73877f6029216f4314d712086a146570");
-    ```
diff --git a/docs/en/sql-reference/sql-statements/Administration/KILL.md b/docs/en/sql-reference/sql-statements/Administration/KILL.md
deleted file mode 100644
index e61b434a25555e..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/KILL.md
+++ /dev/null
@@ -1,43 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# KILL
-
-## Description
-
-Terminates a connection or a query currently being performed by threads executing within StarRocks.
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```SQL
-KILL [ CONNECTION | QUERY ] <processlist_id>
-```
-
-## Parameters
-
-| **Parameter**            | **Description**                                              |
-| ------------------------ | ------------------------------------------------------------ |
-| Modifier:<ul><li>CONNECTION</li><li>QUERY</li></ul> | <ul><li>With a `CONNECTION` modifier, the KILL statement terminates the connection associated with the given `processlist_id`, after terminating any statement the connection is executing.</li><li>With a `QUERY` modifier, the KILL statement terminates the statement the connection is currently executing, but leaves the connection itself intact.</li><li>If no modifier is present, the default is `CONNECTION`.</li></ul> |
-| processlist_id           | The ID of the thread you want to terminate. You can get the IDs of the threads that are being executed using [SHOW PROCESSLIST](../Administration/SHOW_PROCESSLIST.md). |
-
-## Examples
-
-```Plain
-mysql> SHOW FULL PROCESSLIST;
-+------+------+---------------------+--------+---------+---------------------+------+-------+-----------------------+-----------+
-| Id   | User | Host                | Db     | Command | ConnectionStartTime | Time | State | Info                  | IsPending |
-+------+------+---------------------+--------+---------+---------------------+------+-------+-----------------------+-----------+
-|   20 | root | xxx.xx.xxx.xx:xxxxx | sr_hub | Query   | 2023-01-05 16:30:19 |    0 | OK    | show full processlist | false     |
-+------+------+---------------------+--------+---------+---------------------+------+-------+-----------------------+-----------+
-1 row in set (0.01 sec)
-
-mysql> KILL 20;
-Query OK, 0 rows affected (0.00 sec)
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/SET.md b/docs/en/sql-reference/sql-statements/Administration/SET.md
deleted file mode 100644
index ac9570f8914ae4..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SET.md
+++ /dev/null
@@ -1,54 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SET
-
-## Description
-
-Sets the specified system variables or user-defined variables for StarRocks. You can view the system variables of StarRocks using [SHOW VARIABLES](../Administration/SHOW_VARIABLES.md). For details about system variables, see [System Variables](../../../reference/System_variable.md). For details about user-defined variables, see [User-defined variables](../../../reference/user_defined_variables.md).
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```SQL
-SET [ GLOBAL | SESSION ] <variable_name> = <value> [, <variable_name> = <value>] ...
-```
-
-## Parameters
-
-| **Parameter**          | **Description**                                              |
-| ---------------------- | ------------------------------------------------------------ |
-| Modifier:<ul><li>GLOBAL</li><li>SESSION</li></ul> | <ul><li>With a `GLOBAL` modifier, the statement sets the variables globally.</li><li>With a `SESSION` modifier, the statement sets the variables within the session. `LOCAL` is a synonym for `SESSION`.</li><li>If no modifier is present, the default is `SESSION`.</li></ul>For details about global and session variables, see [System Variables](../../../reference/System_variable.md).<br/>**NOTE**<br/>Only users with the ADMIN privilege can set the variables globally. |
-| variable_name          | The name of the variable.                                    |
-| value                  | The value of the variable.                                   |
-
-## Examples
-
-Example 1: Set the `time_zone` to `Asia/Shanghai` within the session.
-
-```Plain
-mysql> SET time_zone = "Asia/Shanghai";
-Query OK, 0 rows affected (0.00 sec)
-```
-
-Example 2: Set the `exec_mem_limit` to `2147483648` globally.
-
-```Plain
-mysql> SET GLOBAL exec_mem_limit = 2147483648;
-Query OK, 0 rows affected (0.00 sec)
-```
-
-Example 3: Set multiple global variables. Add the `GLOBAL` keyword before each variable.
-
-```Plain
-mysql> SET 
-       GLOBAL exec_mem_limit = 2147483648,
-       GLOBAL time_zone = "Asia/Shanghai";
-Query OK, 0 rows affected (0.00 sec)
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/SET_DEFAULT_STORAGE_VOLUME.md b/docs/en/sql-reference/sql-statements/Administration/SET_DEFAULT_STORAGE_VOLUME.md
deleted file mode 100644
index df448bccfd4aab..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SET_DEFAULT_STORAGE_VOLUME.md
+++ /dev/null
@@ -1,44 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SET DEFAULT STORAGE VOLUME
-
-## Description
-
-Sets a storage volume as the default storage volume. After creating a storage volume for an external data source, you can set it as the default storage volume of your StarRocks cluster. This feature is supported from v3.1.
-
-> **CAUTION**
->
-> - Only users with the USAGE privilege on a specific storage volume can perform this operation.
-> - The default storage volume cannot be dropped or disabled.
-> - You must set the default storage volume for a shared-data StarRocks cluster because StarRocks stores the system statistics information in the default storage volume.
-
-## Syntax
-
-```SQL
-SET <storage_volume_name> AS DEFAULT STORAGE VOLUME
-```
-
-## Parameters
-
-| **Parameter**       | **Description**                                              |
-| ------------------- | ------------------------------------------------------------ |
-| storage_volume_name | The name of the storage volume to be set as the default storage volume. |
-
-## Examples
-
-Example 1: Set the storage volume `my_s3_volume` as the default storage volume.
-
-```SQL
-MySQL > SET my_s3_volume AS DEFAULT STORAGE VOLUME;
-Query OK, 0 rows affected (0.01 sec)
-```
-
-## Relevant SQL statements
-
-- [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)
-- [ALTER STORAGE VOLUME](./ALTER_STORAGE_VOLUME.md)
-- [DROP STORAGE VOLUME](./DROP_STORAGE_VOLUME.md)
-- [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md)
-- [SHOW STORAGE VOLUMES](./SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_BACKENDS.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_BACKENDS.md
deleted file mode 100644
index d74dc3dbadcfd3..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_BACKENDS.md
+++ /dev/null
@@ -1,76 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW BACKENDS
-
-## Description
-
-Shows the information of all BE nodes in the cluster.
-
-:::tip
-
-Only users with the SYSTEM-level OPERATE privilege or the `cluster_admin` role can perform this operation.
-
-:::
-
-## Syntax
-
-```SQL
-SHOW BACKENDS
-```
-
-## Return
-
-```SQL
-+-----------+-----------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+--------------------+--------------------------------------------------------+-------------------+-------------+----------+-------------------+------------+------------+------------------+----------+
-| BackendId | IP        | HeartbeatPort | BePort | HttpPort | BrpcPort | LastStartTime       | LastHeartbeat       | Alive | SystemDecommissioned | ClusterDecommissioned | TabletNum | DataUsedCapacity | AvailCapacity | TotalCapacity | UsedPct | MaxDiskUsedPct | ErrMsg | Version            | Status                                                 | DataTotalCapacity | DataUsedPct | CpuCores | NumRunningQueries | MemUsedPct | CpuUsedPct | DataCacheMetrics | Location |
-+-----------+-----------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+--------------------+--------------------------------------------------------+-------------------+-------------+----------+-------------------+------------+------------+------------------+----------+
-```
-
-| **Return**            | **Description**                                              |
-| --------------------- | ------------------------------------------------------------ |
-| BackendId             | The ID of the BE node.                                       |
-| IP                    | The IP address of the BE node.                               |
-| HeartbeatPort         | The heartbeat port of the BE node. It is used to receive heartbeats from the FE node. |
-| BePort                | Thrift server port of the BE node. It is used to receive requests from the FE node. |
-| HttpPort              | HTTP server port of the BE node. It is used to access the BE node via web page. |
-| BrpcPort              | bRPC port of the BE node. It is used for communication across BE nodes. |
-| LastStartTime         | The last time when the BE node is started.                   |
-| LastHeartbeat         | The last time when the FE node sends a heartbeat and the BE responds.|
-| Alive                 | Whether the BE node is alive or not.<ul><li>`true`: the BE node is alive.</li><li>`false`: the BE node is not alive. </li></ul> |
-| SystemDecommissioned  | Whether the BE node is decommissioned or not. Before it is decommissioned, the BE node migrates the data to other BE nodes. Data loading and queries are not affected during migration.<ul><li>`true`: the cluster has marked the BE node as decommissioned. The data could be successfully migrated or migrating.</li><li>`false`: the BE node is running.</li></ul> |
-| ClusterDecommissioned | This parameter is used for system compatibility.             |
-| TabletNum             | The number of tablets on the BE node.                        |
-| DataUsedCapacity      | The storage capacity occupied by the data file.              |
-| AvailCapacity         | Available storage capacity in the BE node.                   |
-| TotalCapacity         | The total storage capacity. It is equivalent to `DataUsedCapacity` + `AvailCapacity` + Storage capacity occupied by the non-data files. |
-| UsedPct               | The percentage of the used storage capacity.                 |
-| MaxDiskUsedPct        | If a BE node has multiple directories to store data, this parameter shows the maximum percentage of the used storage capacity among all directories. |
-| ErrMsg                | The error message returned when the BE node fails to receive the heartbeat from the FE node. |
-| Version               | The StarRocks version of cluster.                            |
-| Status                | The last time when the BE node reports the tablet number to the FE node. Displayed in JSON format. |
-| DataTotalCapacity     | It is equivalent to `DataUsedCapacity` + `AvailCapacity`. It indicates the sum of the storage capacity occupied by the data file and the available storage capacity in the BE node. |
-| DataUsedPct           |  It is equivalent to `DataUsedCapacity`/`DataTotalCapacity`. It indicates the proportion of the storage capacity occupied by the data file to the sum of the data-occupied storage capacity and the available storage capacity. |
-| CpuCores              | The number of CPU cores in the BE node.                      |
-| NumRunningQueries     | The number of running queries on the BE node.                |
-| MemUsedPct            | The percentage of used memory.                               |
-| CpuUsedPct            | The percentage of used CPU cores.                            |
-| DataCacheMetrics      | The status of Data Cache:<ul><li>`Disabled`: Disabled</li><li>`Normal`: Normal </li><li>`Abnormal`: Abnormal </li><li>`Updating`: Data Cache is being updating, for example, scaling. </li></ul>                      |
-| Location              | The label of the BE node. For more information, see [Add labels on BEs](../../../administration/management/resource_management/be_label.md).                     |
-
-## Example
-
-View the information of all BE nodes in the cluster.
-
-```Plain
-SHOW BACKENDS;
-
-+-----------+---------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+----------------------+--------------------------------------------------------+-------------------+-------------+----------+
-| BackendId | IP      | HeartbeatPort | BePort | HttpPort | BrpcPort | LastStartTime       | LastHeartbeat       | Alive | SystemDecommissioned | ClusterDecommissioned | TabletNum | DataUsedCapacity | AvailCapacity | TotalCapacity | UsedPct | MaxDiskUsedPct | ErrMsg | Version              | Status                                                 | DataTotalCapacity | DataUsedPct | CpuCores |
-+-----------+---------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+----------------------+--------------------------------------------------------+-------------------+-------------+----------+
-| 10002     | x.x.x.x | 9254          | 9260   | 8238     | 8260     | 2022-09-08 14:37:10 | 2022-09-08 15:14:21 | true  | false                | false                 | 21753     | 25.122 GB        | 1.088 TB      | 1.968 TB      | 44.72 % | 44.72 %        |        | MAIN-RELEASE-d094052 | {"lastSuccessReportTabletsTime":"2022-09-08 15:14:13"} | 1.113 TB          | 2.20 %      | 16       |
-| 10003     | x.x.x.x | 9254          | 9260   | 8238     | 8260     | 2022-09-08 14:37:20 | 2022-09-08 15:14:21 | true  | false                | false                 | 21754     | 25.121 GB        | 1.169 TB      | 1.968 TB      | 40.61 % | 40.61 %        |        | MAIN-RELEASE-d094052 | {"lastSuccessReportTabletsTime":"2022-09-08 15:14:22"} | 1.194 TB          | 2.06 %      | 16       |
-| 10004     | x.x.x.x | 9254          | 9260   | 8238     | 8260     | 2022-09-08 14:37:39 | 2022-09-08 15:14:21 | true  | false                | false                 | 21754     | 25.112 GB        | 1.172 TB      | 1.968 TB      | 40.46 % | 40.46 %        |        | MAIN-RELEASE-d094052 | {"lastSuccessReportTabletsTime":"2022-09-08 15:13:42"} | 1.197 TB          | 2.05 %      | 16       |
-+-----------+---------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+----------------------+--------------------------------------------------------+-------------------+-------------+----------+
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_BACKEND_BLACKLIST.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_BACKEND_BLACKLIST.md
deleted file mode 100644
index 6c2c4e72bee3ae..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_BACKEND_BLACKLIST.md
+++ /dev/null
@@ -1,50 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW BACKEND BLACKLIST
-
-## Description
-
-Shows the BE nodes in the BE Blacklist.
-
-This feature is supported from v3.3.0 onwards. For more information, see [Manage BE Blacklist](../../../administration/management/BE_blacklist.md).
-
-:::note
-
-Only users with the SYSTEM-level BLACKLIST privilege can perform this operation.
-
-:::
-
-## Syntax
-
-```SQL
-SHOW BACKEND BLACKLIST
-```
-
-## Return value
-
-| **Return**                   | **Description**                                              |
-| ---------------------------- | ------------------------------------------------------------ |
-| AddBlackListType             | How the BE node was added to the blacklist. `MANUAL` indicates it is manually blacklisted by the user. `AUTO` indicates it is automatically blacklisted by StarRocks. |
-| LostConnectionTime           | For the `MANUAL` type, it indicates the time when the BE node was manually added to the blacklist.<br />For the `AUTO` type, it indicates the time when the last successful connection was established. |
-| LostConnectionNumberInPeriod | The number of disconnections detected within `CheckTimePeriod(s)`. |
-| CheckTimePeriod(s)           | The interval at which StarRocks checks the connection status of the blacklisted BE nodes. Its value is evaluated to the value you specified for the FE configuration item `black_host_history_sec`. Unit: Seconds. |
-
-## Examples
-
-```SQL
-SHOW BACKEND BLACKLIST;
-+-----------+------------------+---------------------+------------------------------+--------------------+
-| BackendId | AddBlackListType | LostConnectionTime  | LostConnectionNumberInPeriod | CheckTimePeriod(s) |
-+-----------+------------------+---------------------+------------------------------+--------------------+
-| 10001     | MANUAL           | 2024-04-28 11:52:09 | 0                            | 5                  |
-+-----------+------------------+---------------------+------------------------------+--------------------+
-```
-
-## Relevant SQLs
-
-- [ADD BACKEND BLACKLIST](./ADD_BACKEND_BLACKLIST.md)
-- [DELETE BACKEND BLACKLIST](./DELETE_BACKEND_BLACKLIST.md)
-- [SHOW BACKENDS](./SHOW_BACKENDS.md)
-
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_BROKER.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_BROKER.md
deleted file mode 100644
index c27eb58ecdd718..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_BROKER.md
+++ /dev/null
@@ -1,28 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW BROKER
-
-## Description
-
-This statement is used to view broker that currently exists.
-
-:::tip
-
-Only users with the SYSTEM-level OPERATE privilege or the `cluster_admin` role can perform this operation.
-
-:::
-
-## Syntax
-
-```sql
-SHOW BROKER
-```
-
-Note:
-
-1. LastStartTime represents the latest BE start-up time.
-2. LastHeartbeat represents the latest heartbeat.
-3. Alive indicates whether the node survives.
-4. ErrMsg is used to display error messages when the heartbeat fails.
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_COMPUTE_NODES.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_COMPUTE_NODES.md
deleted file mode 100644
index 2c5c4c4cdf56db..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_COMPUTE_NODES.md
+++ /dev/null
@@ -1,88 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW COMPUTE NODES
-
-## Description
-
-Shows the information of all CN nodes in the cluster.
-
-:::tip
-
-Only users with the SYSTEM-level OPERATE privilege or the `cluster_admin` role can perform this operation.
-
-:::
-
-## Syntax
-
-```SQL
-SHOW COMPUTE NODES
-```
-
-## Return
-
-```SQL
-+---------------+--------------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+--------+--------------------+----------+-------------------+------------+------------+----------------+-------------+----------+-------------------+-----------+
-| ComputeNodeId | IP           | HeartbeatPort | BePort | HttpPort | BrpcPort | LastStartTime       | LastHeartbeat       | Alive | SystemDecommissioned | ClusterDecommissioned | ErrMsg | Version            | CpuCores | NumRunningQueries | MemUsedPct | CpuUsedPct | HasStoragePath | StarletPort | WorkerId | WarehouseName     | TabletNum |
-+---------------+--------------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+--------+--------------------+----------+-------------------+------------+------------+----------------+-------------+----------+-------------------+-----------+
-```
-
-The following table describes the parameters returned by this statement.
-
-| **Parameter**        | **Description**                                                   |
-| -------------------- | ----------------------------------------------------------------- |
-| ComputeNodeId        | The ID of the CN node.                                            |
-| IP                   | The IP address of the CN node.                                    |
-| HeartbeatPort        | The heartbeat port of the CN node. It is used to receive heartbeats from the FE node. |
-| BePort               | Thrift server port of the CN node. It is used to receive requests from the FE node. |
-| HttpPort             | HTTP server port of the CN node. It is used to access the CN node via web page. |
-| BrpcPort             | bRPC port of the CN node. It is used for communication across CN nodes. |
-| LastStartTime        | The last time at which the CN node starts.                        |
-| LastHeartbeat        | The last time at which the CN node sends a heartbeat.             |
-| Alive                | Whether the CN node is alive or not.<ul><li>`true`: the CN node is alive.</li><li>`false`: the CN node is not alive. </li></ul> |
-| SystemDecommissioned | If the value of the parameter is `true`, the CN node is removed from your StarRocks cluster. |
-| ClusterDecommissioned | This parameter is used for system compatibility.                 |
-| ErrMsg               | The error message if the CN node fails to send a heartbeat.       |
-| Version              | The StarRocks version of the CN node.                             |
-| CpuCores             | The number of CPU cores in the CN node.                           |
-| NumRunningQueries    | The number of running queries on the CN node.                     |
-| MemUsedPct           | The percentage of used memory.                                    |
-| CpuUsedPct           | The percentage of used CPU cores.                                 |
-| HasStoragePath       | Whether the CN node has storage paths configured.                 |
-| StarletPort          | The `starlet_port` of the CN node. It is an extra agent service port. |
-| WorkerId             | The ID of the CN node for internal scheduling.                    |
-| WarehouseName        | The name of the warehouse to which the CN node belongs. The value is always `default_warehouse`. |
-| TabletNum            | The number of tablets (of cached data) on the CN node.            |
-
-## Example
-
-View the information of all CN nodes in the cluster.
-
-```Plain
-MySQL > SHOW COMPUTE NODES\G
-*************************** 1. row ***************************
-        ComputeNodeId: 10001
-                   IP: x.x.x.x
-        HeartbeatPort: 9050
-               BePort: 9060
-             HttpPort: 8040
-             BrpcPort: 8060
-        LastStartTime: 2024-05-14 15:45:34
-        LastHeartbeat: 2024-05-14 15:47:59
-                Alive: true
- SystemDecommissioned: false
-ClusterDecommissioned: false
-               ErrMsg: 
-              Version: 3.3.0-rc01-3b8cb0c
-             CpuCores: 4
-    NumRunningQueries: 0
-           MemUsedPct: 1.95 %
-           CpuUsedPct: 0.0 %
-       HasStoragePath: true
-          StarletPort: 8167
-             WorkerId: 1
-        WarehouseName: default_warehouse
-            TabletNum: 58
-1 row in set (0.00 sec)
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_FILE.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_FILE.md
deleted file mode 100644
index 88fe80f6a962f6..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_FILE.md
+++ /dev/null
@@ -1,41 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW FILE
-
-You can execute the SHOW FILE statement to view the information about a file stored in a database.
-
-:::tip
-
-Users with any privilege on the database to which a file belongs can perform this operation. If a file belongs to a database, all users that have access to this database can use this file.
-
-:::
-
-## Syntax
-
-```SQL
-SHOW FILE [FROM database]
-```
-
-The file information returned by this statement is as follows:
-
-- `FileId`: the globally unique ID of the file.
-
-- `DbName`: the database to which the file belongs.
-
-- `Catalog`: the category to which the file belongs.
-
-- `FileName`: the name of the file.
-
-- `FileSize`: the size of the file. The unit is bytes.
-
-- `MD5`: the message-digest algorithm that is used to check the file.
-
-## Examples
-
-View the file stored in `my_database`.
-
-```SQL
-SHOW FILE FROM my_database;
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_FRONTENDS.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_FRONTENDS.md
deleted file mode 100644
index da587b2c5313df..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_FRONTENDS.md
+++ /dev/null
@@ -1,31 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW FRONTENDS
-
-## Description
-
-This statement is used to view FE nodes.
-
-:::tip
-
-Only users with the SYSTEM-level OPERATE privilege or the `cluster_admin` role can perform this operation.
-
-:::
-
-## Syntax
-
-```sql
-SHOW FRONTENDS
-```
-
-Note:
-
-1. Name represents the name of FE node in BDBJE.
-2. Join being true means this node has already joined the cluster. But it does not mean that the node is still in the cluster, as it may be missing.
-3. Alive indicates whether the node survives.
-4. ReplayedJournalId represents the maximum metadata log ID that the node has currently replayed.
-5. LastHeartbeat is the latest heartbeat.
-6. IsHelper indicates whether the node is a helper node from BDBJE.
-7. ErrMsg is used to display error messages when the heartbeat fails.
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_PLUGINS.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_PLUGINS.md
deleted file mode 100644
index d57262d21c42e0..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_PLUGINS.md
+++ /dev/null
@@ -1,31 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW PLUGINS
-
-## Description
-
-This statement is used to view the installed plugins.
-
-:::tip
-
-This operation requires the SYSTEM-level PLUGIN privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```sql
-SHOW PLUGINS
-```
-
-This command will display all built-in plugins and custom plugins.
-
-## Examples
-
-1. Show the installed plugins:
-
-    ```sql
-    SHOW PLUGINS;
-    ```
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_PROC.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_PROC.md
deleted file mode 100644
index 8b3e415ebc83a6..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_PROC.md
+++ /dev/null
@@ -1,444 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW PROC
-
-## Description
-
-Shows certain indicators of the StarRocks cluster.
-
-:::tip
-
-This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```SQL
-SHOW PROC { '/backends' | '/compute_nodes' | '/dbs' 
-          | '/jobs' | '/statistic' | '/tasks' | '/frontends' 
-          | '/brokers' | '/resources' | '/load_error_hub' 
-          | '/transactions' | '/monitor' | '/current_queries' 
-          | '/current_backend_instances' | '/cluster_balance' 
-          | '/routine_loads' | '/colocation_group' | '/catalog' }
-```
-
-## Parameters
-
-| **Parameter**                | **Description**                                              |
-| ---------------------------- | ------------------------------------------------------------ |
-| '/backends'                  | Shows the information of BE nodes in the cluster.            |
-| '/compute_nodes'             | Shows the information of CN nodes in the cluster.            |
-| '/dbs'                       | Shows the information of databases in the cluster.           |
-| '/jobs'                      | Shows the information of jobs in the cluster.                |
-| '/statistic'                 | Shows the statistics of each database in the cluster.        |
-| '/tasks'                     | Shows the total number of all generic tasks and the failed tasks in the cluster. |
-| '/frontends'                 | Shows the information of FE nodes in the cluster.            |
-| '/brokers'                   | Shows the information of Broker nodes in the cluster.        |
-| '/resources'                 | Shows the information of resources in the cluster.           |
-| '/load_error_hub'            | Shows the configuration of the cluster's Load Error Hub, which is used to manage error messages of loading jobs. |
-| '/transactions'              | Shows the information of transactions in the cluster.        |
-| '/monitor'                   | Shows the monitoring information in the cluster.             |
-| '/current_queries'           | Shows the information of running queries on the current FE node. |
-| '/current_backend_instances' | Shows the BE nodes that are processing requests in the cluster. |
-| '/cluster_balance'           | Shows the load balance information in the cluster.           |
-| '/routine_loads'             | Shows the information of Routine Load in the cluster.        |
-| '/colocation_group'          | Shows the information of Colocate Join groups in the cluster. |
-| '/catalog'                   | Shows the information of catalogs in the cluster.            |
-
-## Examples
-
-Example 1: Shows the information of BE nodes in the cluster.
-
-```Plain
-mysql> SHOW PROC '/backends'\G
-*************************** 1. row ***************************
-            BackendId: 10004
-                   IP: xxx.xx.92.200
-        HeartbeatPort: 9354
-               BePort: 9360
-             HttpPort: 8338
-             BrpcPort: 8360
-        LastStartTime: 2023-04-21 09:56:10
-        LastHeartbeat: 2023-04-21 09:56:10
-                Alive: true
- SystemDecommissioned: false
-ClusterDecommissioned: false
-            TabletNum: 2199
-     DataUsedCapacity: 0.000 
-        AvailCapacity: 584.578 GB
-        TotalCapacity: 1.968 TB
-              UsedPct: 71.00 %
-       MaxDiskUsedPct: 71.00 %
-               ErrMsg: 
-              Version: BRANCH-3.0-RELEASE-8eb8705
-               Status: {"lastSuccessReportTabletsTime":"N/A"}
-    DataTotalCapacity: 584.578 GB
-          DataUsedPct: 0.00 %
-             CpuCores: 16
-    NumRunningQueries: 0
-           MemUsedPct: 0.52 %
-           CpuUsedPct: 0.0 %
-```
-
-| **Return**            | **Description**                                              |
-| --------------------- | ------------------------------------------------------------ |
-| BackendId             | ID of the BE node.                                           |
-| IP                    | IP address of the BE node.                                   |
-| HeartbeatPort         | Heartbeat service port of the BE node.                       |
-| BePort                | Thrift Server port of the BE node.                           |
-| HttpPort              | HTTP Server port of the BE node.                             |
-| BrpcPort              | bRPC port of the BE node.                                    |
-| LastStartTime         | The last time when the BE node was started.                  |
-| LastHeartbeat         | The last time when the BE node received a heartbeat.         |
-| Alive                 | If the BE node is alive.                                     |
-| SystemDecommissioned  | If the BE node is decommissioned.                            |
-| ClusterDecommissioned | If the BE node is decommissioned within the cluster.         |
-| TabletNum             | Number of tablets in the BE node.                            |
-| DataUsedCapacity      | Storage capacity that is used for data in the BE node.       |
-| AvailCapacity         | Available storage capacity in the BE node.                   |
-| TotalCapacity         | Total storage capacity in the BE node.                       |
-| UsedPct               | Percentage at which the storage capacity is used in the BE node. |
-| MaxDiskUsedPct        | The maximum percentage at which the storage capacity is used in the BE node. |
-| ErrMsg                | Error messages in the BE node.                               |
-| Version               | StarRocks version of the BE node.                            |
-| Status                | Status information of the BE node, including the last time when the BE node reported tablets. |
-| DataTotalCapacity     | Total of used and available data storage capacity. The sum of `DataUsedCapacity` and `AvailCapacity`. |
-| DataUsedPct           | Percentage at which the data storage takes up the total data capacity (DataUsedCapacity/DataTotalCapacity). |
-| CpuCores              | Number of CPU cores in the BE node.                          |
-| NumRunningQueries     | The number of queries currently running in the cluster.      |
-| MemUsedPct            | The current memory usage percentage.                                 |
-| CpuUsedPct            | The current CPU usage percentage.                                    |
-
-Example 2: Shows the information of databases in the cluster.
-
-```Plain
-mysql> SHOW PROC '/dbs';
-+---------+------------------------+----------+----------------+--------------------------+---------------------+
-| DbId    | DbName                 | TableNum | Quota          | LastConsistencyCheckTime | ReplicaQuota        |
-+---------+------------------------+----------+----------------+--------------------------+---------------------+
-| 1       | information_schema     | 22       | 8388608.000 TB | NULL                     | 9223372036854775807 |
-| 840997  | tpcds_100g             | 25       | 1024.000 GB    | NULL                     | 1073741824          |
-| 1275196 | _statistics_           | 3        | 8388608.000 TB | 2022-09-06 23:00:58      | 9223372036854775807 |
-| 1286207 | tpcds_n                | 24       | 8388608.000 TB | NULL                     | 9223372036854775807 |
-| 1381289 | test                   | 6        | 8388608.000 TB | 2022-01-14 23:10:18      | 9223372036854775807 |
-| 6186781 | test_stddev            | 1        | 8388608.000 TB | 2022-09-06 23:00:58      | 9223372036854775807 |
-+---------+------------------------+----------+----------------+--------------------------+---------------------+
-```
-
-| **Return**               | **Description**                                   |
-| ------------------------ | ------------------------------------------------- |
-| DbId                     | Database ID.                                      |
-| DbName                   | Database name.                                    |
-| TableNum                 | Number of tables in the database.                 |
-| Quota                    | Storage quota of the database.                    |
-| LastConsistencyCheckTime | The last time when consistency check is executed. |
-| ReplicaQuota             | Data replica quota of the database.               |
-
-Example 3: Shows the information of jobs in the cluster.
-
-```Plain
-mysql> SHOW PROC '/jobs';
-+-------+--------------------------------------+
-| DbId  | DbName                               |
-+-------+--------------------------------------+
-| 10005 | default_cluster:_statistics_         |
-| 0     | default_cluster:information_schema   |
-| 12711 | default_cluster:starrocks_audit_db__ |
-+-------+--------------------------------------+
-3 rows in set (0.00 sec)
-
-mysql> SHOW PROC '/jobs/10005';
-+---------------+---------+---------+----------+-----------+-------+
-| JobType       | Pending | Running | Finished | Cancelled | Total |
-+---------------+---------+---------+----------+-----------+-------+
-| load          | 0       | 0       | 3        | 0         | 3     |
-| rollup        | 0       | 0       | 0        | 0         | 0     |
-| schema_change | 0       | 0       | 0        | 0         | 0     |
-| export        | 0       | 0       | 0        | 0         | 0     |
-+---------------+---------+---------+----------+-----------+-------+
-4 rows in set (0.00 sec)
-```
-
-| **Return** | **Description**                    |
-| ---------- | ---------------------------------- |
-| DbId       | Database ID.                       |
-| DbName     | Database name.                     |
-| JobType    | Job type.                          |
-| Pending    | Number of jobs that are pending.   |
-| Running    | Number of jobs that are running.   |
-| Finished   | Number of jobs that are finished.  |
-| Cancelled  | Number of jobs that are cancelled. |
-| Total      | Total number of jobs.              |
-
-Example 4: Shows the statistics of each database in the cluster.
-
-```Plain
-mysql> SHOW PROC '/statistic';
-+--------+----------------------------------------------------------+----------+--------------+----------+-----------+------------+--------------------+-----------------------+------------------+---------------------+
-| DbId   | DbName                                                   | TableNum | PartitionNum | IndexNum | TabletNum | ReplicaNum | UnhealthyTabletNum | InconsistentTabletNum | CloningTabletNum | ErrorStateTabletNum |
-+--------+----------------------------------------------------------+----------+--------------+----------+-----------+------------+--------------------+-----------------------+------------------+---------------------+
-| 10004  | _statistics_                                             | 3        | 3            | 3        | 30        | 60         | 0                  | 0                     | 0                | 0                   |
-| 1      | information_schema                                       | 0        | 0            | 0        | 0         | 0          | 0                  | 0                     | 0                | 0                   |
-| 92498  | stream_load_test_db_03afc714_b1cb_11ed_a82c_00163e237e98 | 0        | 0            | 0        | 0         | 0          | 0                  | 0                     | 0                | 0                   |
-| 92542  | stream_load_test_db_79876e92_b1da_11ed_b50e_00163e237e98 | 1        | 1            | 1        | 3         | 3          | 0                  | 0                     | 0                | 0                   |
-| 115476 | testdb                                                   | 0        | 0            | 0        | 0         | 0          | 0                  | 0                     | 0                | 0                   |
-| 10002  | zq_test                                                  | 8        | 8            | 8        | 5043      | 7063       | 0                  | 0                     | 0                | 2                   |
-| Total  | 6                                                        | 12       | 12           | 12       | 5076      | 7126       | 0                  | 0                     | 0                | 2                   |
-+--------+----------------------------------------------------------+----------+--------------+----------+-----------+------------+--------------------+-----------------------+------------------+---------------------+
-7 rows in set (0.01 sec)
-
-mysql> show proc '/statistic/10002';
-+------------------+---------------------+----------------+-------------------+
-| UnhealthyTablets | InconsistentTablets | CloningTablets | ErrorStateTablets |
-+------------------+---------------------+----------------+-------------------+
-| []               | []                  | []             | [116703, 116706]  |
-+------------------+---------------------+----------------+-------------------+
-```
-
-| **Return**            | **Description**                                              |
-| --------------------- | ------------------------------------------------------------ |
-| DbId                  | Database ID.                                                 |
-| DbName                | Database name.                                               |
-| TableNum              | Number of tables in the database.                            |
-| PartitionNum          | Number of partitions in the database.                        |
-| IndexNum              | Number of indexes in the database.                           |
-| TabletNum             | Number of tablets in the database.                           |
-| ReplicaNum            | Number of replicas in the database.                          |
-| UnhealthyTabletNum    | Number of unfinished (unhealthy) tablets in the database during data redistribution. |
-| InconsistentTabletNum | Number of inconsistent tablets in the database.              |
-| CloningTabletNum      | Number of tablets that are being cloned in the database.     |
-| ErrorStateTabletNum   | In a Primary Key type table, the number of tablets in Error state. |
-| ErrorStateTablets     | In a Primary Key type table, the IDs of the tablets in Error state. |
-
-Example 5: Shows the total number of all generic tasks and the failed tasks in the cluster.
-
-```Plain
-mysql> SHOW PROC '/tasks';
-+-------------------------+-----------+----------+
-| TaskType                | FailedNum | TotalNum |
-+-------------------------+-----------+----------+
-| CREATE                  | 0         | 0        |
-| DROP                    | 0         | 0        |
-| PUSH                    | 0         | 0        |
-| CLONE                   | 0         | 0        |
-| STORAGE_MEDIUM_MIGRATE  | 0         | 0        |
-| ROLLUP                  | 0         | 0        |
-| SCHEMA_CHANGE           | 0         | 0        |
-| CANCEL_DELETE           | 0         | 0        |
-| MAKE_SNAPSHOT           | 0         | 0        |
-| RELEASE_SNAPSHOT        | 0         | 0        |
-| CHECK_CONSISTENCY       | 0         | 0        |
-| UPLOAD                  | 0         | 0        |
-| DOWNLOAD                | 0         | 0        |
-| CLEAR_REMOTE_FILE       | 0         | 0        |
-| MOVE                    | 0         | 0        |
-| REALTIME_PUSH           | 0         | 0        |
-| PUBLISH_VERSION         | 0         | 0        |
-| CLEAR_ALTER_TASK        | 0         | 0        |
-| CLEAR_TRANSACTION_TASK  | 0         | 0        |
-| RECOVER_TABLET          | 0         | 0        |
-| STREAM_LOAD             | 0         | 0        |
-| UPDATE_TABLET_META_INFO | 0         | 0        |
-| ALTER                   | 0         | 0        |
-| INSTALL_PLUGIN          | 0         | 0        |
-| UNINSTALL_PLUGIN        | 0         | 0        |
-| NUM_TASK_TYPE           | 0         | 0        |
-| Total                   | 0         | 0        |
-+-------------------------+-----------+----------+
-```
-
-| **Return** | **Description**         |
-| ---------- | ----------------------- |
-| TaskType   | Task type.              |
-| FailedNum  | Number of failed tasks. |
-| TotalNum   | Total number of tasks.  |
-
-Example 6: Shows the information of FE nodes in the cluster.
-
-```Plain
-mysql> SHOW PROC '/frontends';
-+----------------------------------+---------------+-------------+----------+-----------+---------+----------+------------+-------+-------+-------------------+---------------+----------+---------------+-----------+---------+
-| Name                             | IP            | EditLogPort | HttpPort | QueryPort | RpcPort | Role     | ClusterId  | Join  | Alive | ReplayedJournalId | LastHeartbeat | IsHelper | ErrMsg        | StartTime | Version |
-+----------------------------------+---------------+-------------+----------+-----------+---------+----------+------------+-------+-------+-------------------+---------------+----------+---------------+-----------+---------+
-| xxx.xx.xx.xxx_9009_1600088918395 | xxx.xx.xx.xxx | 9009        | 7390     | 0         | 0       | FOLLOWER | 1747363037 | false | false | 0                 | NULL          | true     | got exception | NULL      | NULL    |
-+----------------------------------+---------------+-------------+----------+-----------+---------+----------+------------+-------+-------+-------------------+---------------+----------+---------------+-----------+---------+
-```
-
-| **Return**        | **Description**                                        |
-| ----------------- | ------------------------------------------------------ |
-| Name              | FE node name.                                          |
-| IP                | IP address of the FE node.                             |
-| EditLogPort       | Port for communication between FE nodes.               |
-| HttpPort          | HTTP Server port of the FE node.                       |
-| QueryPort         | MySQL Server port of the FE node.                      |
-| RpcPort           | RPC port of the FE node.                               |
-| Role              | Role of the FE node (Leader, Follower, or Observer).   |
-| ClusterId         | Cluster ID.                                            |
-| Join              | If the FE node has joined a cluster.                   |
-| Alive             | If the FE node is alive.                               |
-| ReplayedJournalId | The largest metadata ID that the FE node has replayed. |
-| LastHeartbeat     | The last time when the FE node sent a heartbeat.       |
-| IsHelper          | If the FE node is the BDBJE helper node.               |
-| ErrMsg            | Error messages in the FE node.                         |
-| StartTime         | Time when the FE node is started.                      |
-| Version           | StarRocks version of the FE node.                      |
-
-Example 7: Shows the information of Broker nodes in the cluster.
-
-```Plain
-mysql> SHOW PROC '/brokers';
-+-------------+---------------+------+-------+---------------+---------------------+--------+
-| Name        | IP            | Port | Alive | LastStartTime | LastUpdateTime      | ErrMsg |
-+-------------+---------------+------+-------+---------------+---------------------+--------+
-| hdfs_broker | xxx.xx.xx.xxx | 8500 | true  | NULL          | 2022-10-10 16:37:59 |        |
-| hdfs_broker | xxx.xx.xx.xxx | 8500 | true  | NULL          | 2022-10-10 16:37:59 |        |
-| hdfs_broker | xxx.xx.xx.xxx | 8500 | true  | NULL          | 2022-10-10 16:37:59 |        |
-+-------------+---------------+------+-------+---------------+---------------------+--------+
-```
-
-| **Return**     | **Description**                                              |
-| -------------- | ------------------------------------------------------------ |
-| Name           | Broker node name.                                            |
-| IP             | IP address of the broker node.                               |
-| Port           | Thrift Server port of the broker node. The port is used to receive requests. |
-| Alive          | If the broker node is alive.                                 |
-| LastStartTime  | The last time when the broker node was started.              |
-| LastUpdateTime | The last time when the broker node was updated.              |
-| ErrMsg         | Error message in the broker node.                            |
-
-Example 8: Shows the information of resources in the cluster.
-
-```Plain
-mysql> SHOW PROC '/resources';
-+-------------------------+--------------+---------------------+------------------------------+
-| Name                    | ResourceType | Key                 | Value                        |
-+-------------------------+--------------+---------------------+------------------------------+
-| hive_resource_stability | hive         | hive.metastore.uris | thrift://xxx.xx.xxx.xxx:9083 |
-| hive2                   | hive         | hive.metastore.uris | thrift://xxx.xx.xx.xxx:9083  |
-+-------------------------+--------------+---------------------+------------------------------+
-```
-
-| **Return**   | **Description** |
-| ------------ | --------------- |
-| Name         | Resource name.  |
-| ResourceType | Resource type.  |
-| Key          | Resource key.   |
-| Value        | Resource value. |
-
-Example 9: Shows the information of transactions in the cluster.
-
-```Plain
-mysql> SHOW PROC '/transactions';
-+-------+--------------------------------------+
-| DbId  | DbName                               |
-+-------+--------------------------------------+
-| 10005 | default_cluster:_statistics_         |
-| 12711 | default_cluster:starrocks_audit_db__ |
-+-------+--------------------------------------+
-2 rows in set (0.00 sec)
-
-mysql> SHOW PROC '/transactions/10005';
-+----------+--------+
-| State    | Number |
-+----------+--------+
-| running  | 0      |
-| finished | 4      |
-+----------+--------+
-2 rows in set (0.00 sec)
-```
-
-| **Return** | **Description**               |
-| ---------- | ----------------------------- |
-| DbId       | Database ID.                  |
-| DbName     | Database name.                |
-| State      | The state of the transaction. |
-| Number     | Number of transactions.       |
-
-Example 10: Shows the monitoring information in the cluster.
-
-```Plain
-mysql> SHOW PROC '/monitor';
-+------+------+
-| Name | Info |
-+------+------+
-| jvm  |      |
-+------+------+
-```
-
-| **Return** | **Description**  |
-| ---------- | ---------------- |
-| Name       | JVM name.        |
-| Info       | JVM information. |
-
-Example 11: Shows the load balance information in the cluster.
-
-```Plain
-mysql> SHOW PROC '/cluster_balance';
-+-------------------+--------+
-| Item              | Number |
-+-------------------+--------+
-| cluster_load_stat | 1      |
-| working_slots     | 3      |
-| sched_stat        | 1      |
-| priority_repair   | 0      |
-| pending_tablets   | 2001   |
-| running_tablets   | 0      |
-| history_tablets   | 1000   |
-+-------------------+--------+
-```
-
-| **Return** | **Description**                                  |
-| ---------- | ------------------------------------------------ |
-| Item       | Sub-command item in `cluster_balance`. <ul><li>cluster_load_stat: The current load status of the cluster.</li><li>working_slots: The number of currently available working slots.</li><li>sched_stat: The current status of the scheduler.</li><li>priority_repair: The number of Tablet repair tasks that are prioritized.</li><li>pending_tablets: The number of Tablets waiting to be processed.</li><li>running_tablets: The number of Tablets currently being repaired.</li><li>history_tablets: The total number of Tablets repaired historically.</li></ul>         |
-| Number     | Number of each sub-command in `cluster_balance`. |
-
-Example 12: Shows the information of Colocate Join groups in the cluster.
-
-```Plain
-mysql> SHOW PROC '/colocation_group';
-+-----------------+----------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------+------------+----------------+-------------+----------+
-| GroupId         | GroupName                  | TableIds                                                                                                                                          | BucketsNum | ReplicationNum | DistCols    | IsStable |
-+-----------------+----------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------+------------+----------------+-------------+----------+
-| 24010.177354    | 24010_lineitem_str_g1      | 177672                                                                                                                                            | 12         | 1              | varchar(-1) | true     |
-| 24010.182146    | 24010_lineitem_str_g2      | 182144                                                                                                                                            | 192        | 1              | varchar(-1) | true     |
-| 1439318.1735496 | 1439318_group_agent_uid    | 1735677, 1738390                                                                                                                                  | 12         | 2              | bigint(20)  | true     |
-| 24010.37804     | 24010_gsdaf2449s9e         | 37802                                                                                                                                             | 192        | 1              | int(11)     | true     |
-| 174844.175370   | 174844_groupa4             | 175368, 591307, 591362, 591389, 591416                                                                                                            | 12         | 1              | int(11)     | true     |
-| 24010.30587     | 24010_group2               | 30585, 30669                                                                                                                                      | 12         | 1              | int(11)     | true     |
-| 10005.181366    | 10005_lineorder_str_normal | 181364                                                                                                                                            | 192        | 1              | varchar(-1) | true     |
-| 1904968.5973175 | 1904968_groupa2            | 5973173                                                                                                                                           | 12         | 1              | int(11)     | true     |
-| 24010.182535    | 24010_lineitem_str_g3      | 182533                                                                                                                                            | 192        | 1              | varchar(-1) | true     |
-+-----------------+----------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------+------------+----------------+-------------+----------+
-```
-
-| **Return**     | **Description**                                 |
-| -------------- | ----------------------------------------------- |
-| GroupId        | Colocate Join Group ID.                         |
-| GroupName      | Colocate Join Group name.                       |
-| TableIds       | IDs of tables in the Colocate Join Group.       |
-| BucketsNum     | Buckets in the Colocate Join Group.             |
-| ReplicationNum | Replications in the Colocate Join Group.        |
-| DistCols       | Distribution column of the Colocate Join Group. |
-| IsStable       | If the Colocate Join Group is stable.           |
-
-Example 13: Shows the information of catalogs in the cluster.
-
-```Plain
-mysql> SHOW PROC '/catalog';
-+--------------------------------------------------------------+----------+----------------------+
-| Catalog                                                      | Type     | Comment              |
-+--------------------------------------------------------------+----------+----------------------+
-| resource_mapping_inside_catalog_hive_hive2                   | hive     | mapping hive catalog |
-| resource_mapping_inside_catalog_hive_hive_resource_stability | hive     | mapping hive catalog |
-| default_catalog                                              | Internal | Internal Catalog     |
-+--------------------------------------------------------------+----------+----------------------+
-```
-
-| **Return** | **Description**           |
-| ---------- | ------------------------- |
-| Catalog    | Catalog name.             |
-| Type       | Catalog type.             |
-| Comment    | Comments for the catalog. |
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_PROCESSLIST.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_PROCESSLIST.md
deleted file mode 100644
index fc8bf022116453..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_PROCESSLIST.md
+++ /dev/null
@@ -1,58 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW PROCESSLIST
-
-## Description
-
-Lists the operations currently being performed by threads executing within the server. The current version of StarRocks only supports listing queries.
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```SQL
-SHOW [FULL] PROCESSLIST
-```
-
-## Parameter
-
-| Parameter | Required | Description                                                                                                                      |
-| --------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------- |
-| FULL      | No       | If you specify this parameter, the complete SQL statement will be displayed. Otherwise, only the first 100 characters of the statement are displayed. |
-
-## Return
-
-| Return              | Description                                                  |
-| ------------------- | ------------------------------------------------------------ |
-| Id                  | Connection ID.                                               |
-| User                | The name of the user who runs the operation.                 |
-| Host                | The hostname of the client which runs the operation.         |
-| Db                  | The name of the database where the operation is executed.    |
-| Command             | The type of the command.                                     |
-| ConnectionStartTime | Time when the connection starts.                             |
-| Time                | The time (in second) since the operation has entered the current state. |
-| State               | The state of the operation.                                  |
-| Info                | The command that the operation is executing.                 |
-
-## Usage note
-
-If the current user is `root`, this statement lists the operations of all users in the cluster. Otherwise, only operations of the current user are listed.
-
-## Example
-
-Example 1: lists the operations state via the user `root`.
-
-```Plain
-SHOW PROCESSLIST;
-+------+------+---------------------+-------+---------+---------------------+------+-------+------------------+
-| Id   | User | Host                | Db    | Command | ConnectionStartTime | Time | State | Info             |
-+------+------+---------------------+-------+---------+---------------------+------+-------+------------------+
-|  0   | root | x.x.x.x:xxxx        | tpcds | Query   | 2022-10-09 19:58:25 |    0 | OK    | SHOW PROCESSLIST |
-+------+------+---------------------+-------+---------+---------------------+------+-------+------------------+
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_PROFILELIST.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_PROFILELIST.md
deleted file mode 100644
index 693fb4ed1af050..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_PROFILELIST.md
+++ /dev/null
@@ -1,46 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW PROFILELIST
-
-## Description
-
-Lists the query profile records cached in your StarRocks cluster. For more information about query profile, see [Query Profile Overview](../../../administration/query_profile_overview.md).
-
-This feature is supported from v3.1 onwards.
-
-No privilege is required to perform this operation.
-
-## Syntax
-
-```SQL
-SHOW PROFILELIST [LIMIT n]
-```
-
-## Parameters
-
-`LIMIT n`: lists n most recent records.
-
-## Return value
-
-| **Return** | **Description**                                              |
-| ---------- | ------------------------------------------------------------ |
-| QueryId    | The ID of the query.                                         |
-| StartTime  | The start time of the query.                                 |
-| Time       | The latency of the query.                                    |
-| State      | The status of the query, including:`Error`: The query encounters an error.`Finished`: The query is finished.`Running`: The query is running. |
-| Statement  | The statement of the query.                                  |
-
-## Examples
-
-Example 1: Show five most recent query profile records.
-
-```SQL
-SHOW PROFILELIST LIMIT 5;
-```
-
-## Relevant SQLs
-
-- [ANALYZE PROFILE](./ANALYZE_PROFILE.md)
-- [EXPLAIN ANALYZE](./EXPLAIN_ANALYZE.md)
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_RESOURCE_GROUP.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_RESOURCE_GROUP.md
deleted file mode 100644
index 4e5d7cd180e9de..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_RESOURCE_GROUP.md
+++ /dev/null
@@ -1,62 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW RESOURCE GROUP
-
-## Description
-
-Shows the information of resource groups.
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```SQL
-SHOW { RESOURCE GROUPS [ALL] | RESOURCE GROUP <resource_group_name> }
-```
-
-## Parameters
-
-| **Parameter**       | **Description**                                              |
-| ------------------- | ------------------------------------------------------------ |
-| RESOURCE GROUPS     | Show the resource groups that match the current user.        |
-| ALL                 | Specify this parameter to show all resource groups in the cluster. |
-| RESOURCE GROUP      | Show the specified resource group.                           |
-| resource_group_name | Name of the resource group to be shown.                      |
-
-## Return
-
-| **Return**                 | **Description**                                              |
-| -------------------------- | ------------------------------------------------------------ |
-| name                       | Name of the resource group.                                  |
-| id                         | ID of the resource group.                                    |
-| cpu_core_limit             | CPU core limit of the resource group.                        |
-| mem_limit                  | Memory limit of the resource group.                          |
-| big_query_cpu_second_limit | Big query upper time limit of the resource group.            |
-| big_query_scan_rows_limit  | Big query scan row limit of the resource group.              |
-| big_query_mem_limit        | Big query memory limit of the resource group.                |
-| concurrency_limit          | Concurrency limit of the resource group.                     |
-| type                       | Type of resource group.                                      |
-| classifiers                | Classifiers that are associated with the resource group. `id` is the ID of the classifier, and `weight` is the degree of matching. |
-
-## Examples
-
-Example 1: Shows all resource groups in the cluster.
-
-```Plain
-mysql> SHOW RESOURCE GROUPS ALL;
-+-------+--------+----------------+-----------+----------------------------+---------------------------+---------------------+-------------------+--------+------------------------------------------------------------------------------------------------------------------+
-| name  | id     | cpu_core_limit | mem_limit | big_query_cpu_second_limit | big_query_scan_rows_limit | big_query_mem_limit | concurrency_limit | type   | classifiers                                                                                                      |
-+-------+--------+----------------+-----------+----------------------------+---------------------------+---------------------+-------------------+--------+------------------------------------------------------------------------------------------------------------------+
-| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625127, weight=4.459375, user=rg1_user1, role=rg1_role1, query_type in (SELECT), source_ip=172.26.xxx.xx/24) |
-| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625128, weight=3.459375, user=rg1_user2, query_type in (SELECT), source_ip=172.26.xxx.xx/24)                 |
-| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625129, weight=2.359375, user=rg1_user3, source_ip=172.26.xxx.xx/24)                                         |
-| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625130, weight=1.0, user=rg1_user4)                                                                          |
-| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625131, weight=10.0, db='db1')                                                                                |
-+-------+--------+----------------+-----------+----------------------------+---------------------------+---------------------+-------------------+--------+------------------------------------------------------------------------------------------------------------------+
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_RUNNING_QUERIES.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_RUNNING_QUERIES.md
deleted file mode 100644
index 52c1988d36b287..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_RUNNING_QUERIES.md
+++ /dev/null
@@ -1,46 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW RUNNING QUERIES
-
-## Description
-
-Shows the information of all queries that are running or pending in the query queue. This feature is supported from v3.1.4 onwards.
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```SQL
-SHOW RUNNING QUERIES
-```
-
-## Return
-
-- `QueryId`: The ID of the query.
-- `ResourceGroupId`: The ID of the resource group that the query hit. When there is no hit on a user-defined resource group, it will be displayed as "-".
-- `StartTime`: The start time of the query.
-- `PendingTimeout`: The time when the PENDING query will time out in the queue.
-- `QueryTimeout`: The time when the query times out.
-- `State`: The queue state of the query, where "PENDING" indicates it is in the queue, and "RUNNING" indicates it is currently executing.
-- `Slots`: The logical resource quantity requested by the query, currently fixed at `1`.
-- `Frontend`: The FE node that initiated the query.
-- `FeStartTime`: The start time of the FE node that initiated the query.
-
-## Example
-
-```Plain
-MySQL [(none)]> SHOW RUNNING QUERIES;
-+--------------------------------------+-----------------+---------------------+---------------------+---------------------+-----------+-------+---------------------------------+---------------------+
-| QueryId                              | ResourceGroupId | StartTime           | PendingTimeout      | QueryTimeout        |   State   | Slots | Frontend                        | FeStartTime         |
-+--------------------------------------+-----------------+---------------------+---------------------+---------------------+-----------+-------+---------------------------------+---------------------+
-| a46f68c6-3b49-11ee-8b43-00163e10863a | -               | 2023-08-15 16:56:37 | 2023-08-15 17:01:37 | 2023-08-15 17:01:37 |  RUNNING  | 1     | 127.00.00.01_9010_1692069711535 | 2023-08-15 16:37:03 |
-| a6935989-3b49-11ee-935a-00163e13bca3 | 12003           | 2023-08-15 16:56:40 | 2023-08-15 17:01:40 | 2023-08-15 17:01:40 |  RUNNING  | 1     | 127.00.00.02_9010_1692069658426 | 2023-08-15 16:37:03 |
-| a7b5e137-3b49-11ee-8b43-00163e10863a | 12003           | 2023-08-15 16:56:42 | 2023-08-15 17:01:42 | 2023-08-15 17:01:42 |  PENDING  | 1     | 127.00.00.03_9010_1692069711535 | 2023-08-15 16:37:03 |
-+--------------------------------------+-----------------+---------------------+---------------------+---------------------+-----------+-------+---------------------------------+---------------------+
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_SQLBLACKLIST.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_SQLBLACKLIST.md
deleted file mode 100644
index 62cde5b2d65539..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_SQLBLACKLIST.md
+++ /dev/null
@@ -1,44 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW SQLBLACKLIST
-
-## Description
-
-Shows the SQL regular expressions in the SQL blacklist.
-
-For more about SQL Blacklist, see [Manage SQL Blacklist](../../../administration/management/resource_management/Blacklist.md).
-
-:::tip
-
-This operation requires the SYSTEM-level BLACKLIST privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```SQL
-SHOW SQLBLACKLIST
-```
-
-## Return value
-
-| **Return**    | **Description**                                              |
-| ------------- | ------------------------------------------------------------ |
-| Index         | The index number of the SQL regular expression that has been added to the blacklist. |
-| Forbidden SQL | The SQL regular expression that has been added to the blacklist. |
-
-## Examples
-
-```Plain
-mysql> SHOW SQLBLACKLIST;
-+-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| Index | Forbidden SQL                                                                                                                                                                                                                                                                                          |
-+-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| 1     | select count\(\*\) from .+                                                                                                                                                                                                                                                                             |
-| 2     | select id_int \* 4, id_tinyint, id_varchar from test_all_type_nullable except select id_int, id_tinyint, id_varchar from test_basic except select \(id_int \* 9 \- 8\) \/ 2, id_tinyint, id_varchar from test_all_type_nullable2 except select id_int, id_tinyint, id_varchar from test_basic_nullable |
-| 3     | select id_int from test_all_type_select1 order by id_int limit [1-7], [5-7]                                                                                                                                                                                                                            |
-| 4     | select count\(distinct .+\) from .+                                                                                                                                                                                                                                                                    |
-+-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_STORAGE_VOLUMES.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_STORAGE_VOLUMES.md
deleted file mode 100644
index 6c45559b3044a2..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_STORAGE_VOLUMES.md
+++ /dev/null
@@ -1,55 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW STORAGE VOLUMES
-
-## Description
-
-Shows the storage volumes in your StarRocks cluster. This feature is supported from v3.1.
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```SQL
-SHOW STORAGE VOLUMES [ LIKE '<pattern>' ]
-```
-
-## Parameters
-
-| **Parameter** | **Description**                                |
-| ------------- | ---------------------------------------------- |
-| pattern       | The pattern used to match the storage volumes. |
-
-## Return value
-
-| **Return**     | **Description**                 |
-| -------------- | ------------------------------- |
-| Storage Volume | The name of the storage volume. |
-
-## Examples
-
-Example 1: Show all storage volumes in the StarRocks cluster.
-
-```Plain
-MySQL > SHOW STORAGE VOLUMES;
-+----------------+
-| Storage Volume |
-+----------------+
-| my_s3_volume   |
-+----------------+
-1 row in set (0.01 sec)
-```
-
-## Relevant SQL statements
-
-- [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)
-- [ALTER STORAGE VOLUME](./ALTER_STORAGE_VOLUME.md)
-- [DROP STORAGE VOLUME](./DROP_STORAGE_VOLUME.md)
-- [SET DEFAULT STORAGE VOLUME](./SET_DEFAULT_STORAGE_VOLUME.md)
-- [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md)
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_TABLE_STATUS.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_TABLE_STATUS.md
deleted file mode 100644
index 619f22cff06aa7..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_TABLE_STATUS.md
+++ /dev/null
@@ -1,40 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW TABLE STATUS
-
-## Description
-
-This statement is used to view some of the information in Table.
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```sql
-SHOW TABLE STATUS
-[FROM db] [LIKE "pattern"]
-```
-
-> Note
->
-> This statement is mainly compatible with MySQL syntax. At present, it only shows a few information, such as Comment.
-
-## Examples
-
-1. View all the information of tables under the current database.
-
-    ```SQL
-    SHOW TABLE STATUS;
-    ```
-
-2. View all the information of tables whose names contain example and who are under specified databases.
-
-    ```SQL
-    SHOW TABLE STATUS FROM db LIKE "%example%";
-    ```
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_USAGE_RESOURCE_GROUPS.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_USAGE_RESOURCE_GROUPS.md
deleted file mode 100644
index 2bf5a4a0d9b9e7..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_USAGE_RESOURCE_GROUPS.md
+++ /dev/null
@@ -1,52 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW USAGE RESOURCE GROUPS
-
-## Description
-
-Shows the usage information of resource groups. This feature is supported from v3.1.4 onwards.
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```SQL
-SHOW USAGE RESOURCE GROUPS
-```
-
-## Return
-
-- `Name`: The name of the resource group.
-- `Id`: The ID of the resource group.
-- `Backend`: The BE's IP or FQDN.
-- `BEInUseCpuCores`: The number of CPU cores currently in use by this resource group on this BE. This value is an approximate estimate.
-- `BEInUseMemBytes`: The number of memory bytes currently in use by this resource group on this BE.
-- `BERunningQueries`: The number of queries from this resource group that are still running on this BE.
-
-## Usage notes
-
-- BEs periodically report this resource usage information to the Leader FE at the interval specified in `report_resource_usage_interval_ms`, which is by default set to 1 second.
-- The results will only show rows where at least one of `BEInUseCpuCores`/`BEInUseMemBytes`/`BERunningQueries` is a positive number. In other words, the information is displayed only when a resource group is actively using some resources on a BE.
-
-## Example
-
-```Plain
-MySQL [(none)]> SHOW USAGE RESOURCE GROUPS;
-+------------+----+-----------+-----------------+-----------------+------------------+
-| Name       | Id | Backend   | BEInUseCpuCores | BEInUseMemBytes | BERunningQueries |
-+------------+----+-----------+-----------------+-----------------+------------------+
-| default_wg | 0  | 127.0.0.1 | 0.100           | 1               | 5                |
-+------------+----+-----------+-----------------+-----------------+------------------+
-| default_wg | 0  | 127.0.0.2 | 0.200           | 2               | 6                |
-+------------+----+-----------+-----------------+-----------------+------------------+
-| wg1        | 0  | 127.0.0.1 | 0.300           | 3               | 7                |
-+------------+----+-----------+-----------------+-----------------+------------------+
-| wg2        | 0  | 127.0.0.1 | 0.400           | 4               | 8                |
-+------------+----+-----------+-----------------+-----------------+------------------+
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/SHOW_VARIABLES.md b/docs/en/sql-reference/sql-statements/Administration/SHOW_VARIABLES.md
deleted file mode 100644
index 403c0f4f6d7b56..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SHOW_VARIABLES.md
+++ /dev/null
@@ -1,95 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW VARIABLES
-
-## Description
-
-Shows the system variables of StarRocks. For details about system variables, see [System Variables](../../../reference/System_variable.md).
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```SQL
-SHOW [ GLOBAL | SESSION ] VARIABLES
-    [ LIKE <pattern> | WHERE <expr> ]
-```
-
-## Parameters
-
-| **Parameter**          | **Description**                                              |
-| ---------------------- | ------------------------------------------------------------ |
-| Modifier:<ul><li>GLOBAL</li><li>SESSION</li></ul> | <ul><li>With a `GLOBAL` modifier, the statement displays global system variable values. These are the values used to initialize the corresponding session variables for new connections to StarRocks. If a variable has no global value, no value is displayed.</li><li>With a `SESSION` modifier, the statement displays the system variable values that are in effect for the current connection. If a variable has no session value, the global value is displayed. `LOCAL` is a synonym for `SESSION`.</li><li>If no modifier is present, the default is `SESSION`.</li></ul> |
-| pattern                | The pattern used to match the variable by the variable name with the LIKE clause. You can use the % wildcard in this parameter. |
-| expr                   | The expression used to match the variable by the variable name `variable_name` or the variable value `value` with the WHERE clause. |
-
-## Return value
-
-| **Return**    | **Description**            |
-| ------------- | -------------------------- |
-| Variable_name | The name of the variable.  |
-| Value         | The value of the variable. |
-
-## Examples
-
-Example 1: Show a variable by exactly matching the variable name with the LIKE clause.
-
-```Plain
-mysql> SHOW VARIABLES LIKE 'wait_timeout';
-+---------------+-------+
-| Variable_name | Value |
-+---------------+-------+
-| wait_timeout  | 28800 |
-+---------------+-------+
-1 row in set (0.01 sec)
-```
-
-Example 2: Show variables by approximately matching the variable name with the LIKE clause and the wildcard (%).
-
-```Plain
-mysql> SHOW VARIABLES LIKE '%imeou%';
-+------------------------------------+-------+
-| Variable_name                      | Value |
-+------------------------------------+-------+
-| interactive_timeout                | 3600  |
-| net_read_timeout                   | 60    |
-| net_write_timeout                  | 60    |
-| new_planner_optimize_timeout       | 3000  |
-| query_delivery_timeout             | 300   |
-| query_queue_pending_timeout_second | 300   |
-| query_timeout                      | 300   |
-| tx_visible_wait_timeout            | 10    |
-| wait_timeout                       | 28800 |
-+------------------------------------+-------+
-9 rows in set (0.00 sec)
-```
-
-Example 3: Show a variable by exactly matching the variable name with the WHERE clause.
-
-```Plain
-mysql> show variables where variable_name = 'wait_timeout';
-+---------------+-------+
-| Variable_name | Value |
-+---------------+-------+
-| wait_timeout  | 28800 |
-+---------------+-------+
-1 row in set (0.17 sec)
-```
-
-Example 4: Show a variable by exactly matching the value of the variable with the WHERE clause.
-
-```Plain
-mysql> show variables where value = '28800';
-+---------------+-------+
-| Variable_name | Value |
-+---------------+-------+
-| wait_timeout  | 28800 |
-+---------------+-------+
-1 row in set (0.70 sec)
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/SYNC.md b/docs/en/sql-reference/sql-statements/Administration/SYNC.md
deleted file mode 100644
index 9b55a320644de4..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/SYNC.md
+++ /dev/null
@@ -1,28 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SYNC
-
-Synchronizes the data consistency among different sessions.
-
-Currently, StarRocks can only guarantee consistency within the same session, that is, only the session that initiated the data write operation can read the latest data immediately after the operation succeeds. If you want to read the latest data immediately from other sessions, you must synchronize the data consistency using the SYNC statement. Generally, there will be a millisecond-level latency among sessions if you do not execute this statement.
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```SQL
-SYNC
-```
-
-## Examples
-
-```Plain
-mysql> SYNC;
-Query OK, 0 rows affected (0.00 sec)
-```
diff --git a/docs/en/sql-reference/sql-statements/Administration/UNINSTALL_PLUGIN.md b/docs/en/sql-reference/sql-statements/Administration/UNINSTALL_PLUGIN.md
deleted file mode 100644
index a2c462f10de391..00000000000000
--- a/docs/en/sql-reference/sql-statements/Administration/UNINSTALL_PLUGIN.md
+++ /dev/null
@@ -1,33 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# UNINSTALL PLUGIN
-
-## Description
-
-This statement is used to uninstall a plugin.
-
-:::tip
-
-This operation requires the SYSTEM-level PLUGIN privilege. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```SQL
-UNINSTALL PLUGIN <plugin_name>
-```
-
-plugin_name can be viewed through SHOW PLUGINS command
-
-Only non-builtin plugins can be uninstalled.
-
-## Examples
-
-1. Uninstall a plugin:
-
-    ```SQL
-    UNINSTALL PLUGIN auditdemo;
-    ```
diff --git a/docs/en/sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md b/docs/en/sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md
new file mode 100644
index 00000000000000..a54e1c28e9f1d3
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md
@@ -0,0 +1,140 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE EXTERNAL CATALOG
+
+## Description
+
+Creates an external catalog. You can use external catalogs to query data in external data sources without loading data into StarRocks or creating external tables. Currently, you can create the following types of external catalogs:
+
+- [Hive catalog](../../../data_source/catalog/hive_catalog.md): used for querying data from Apache Hive™.
+- [Iceberg catalog](../../../data_source/catalog/iceberg_catalog.md): used for querying data from Apache Iceberg.
+- [Hudi catalog](../../../data_source/catalog/hudi_catalog.md): used for querying data from Apache Hudi.
+- [Delta Lake catalog](../../../data_source/catalog/deltalake_catalog.md): used to query data from Delta Lake.
+- [JDBC catalog](../../../data_source/catalog/jdbc_catalog.md): used to query data from JDBC-compatible data sources.
+- [Elasticsearch catalog](../../../data_source/catalog/elasticsearch_catalog.md): used to query data from Elasticsearch. Elasticsearch catalogs are supported from v3.1 onwards.
+- [Paimon catalog](../../../data_source/catalog/paimon_catalog.md): used to query data from Apache Paimon. Paimon catalogs are supported from v3.1 onwards.
+- [Unified catalog](../../../data_source/catalog/unified_catalog.md): used to query data from from Hive, Iceberg, Hudi, and Delta Lake data sources as a unified data source. Unified catalogs are supported from v3.2 onwards.
+
+> **NOTE**
+>
+> - In v3.0 and later, this statement requires SYSTEM-level CREATE EXTERNAL CATALOG privilege.
+> - Before you create external catalogs, configure your StarRocks cluster to meet the requirements of the data storage system (such as Amazon S3), metadata service (such as Hive metastore), and authenticating service (such as Kerberos) of external data sources. For more information, see the "Before you begin" section in each [external catalog topic](../../../data_source/catalog/catalog_overview.md).
+
+## Syntax
+
+```SQL
+CREATE EXTERNAL CATALOG [IF NOT EXISTS] <catalog_name>
+[COMMENT <comment>]
+PROPERTIES ("key"="value", ...)
+```
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                              |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| catalog_name  | Yes          | The name of the external catalog. For the naming conventions, see [System limits](../../System_limit.md). |
+| comment       | No           | The description of the external catalog. |
+| PROPERTIES    | Yes          | The properties of an external catalog. Configure properties based on the types of external catalogs. For more information, see [Hive catalog](../../../data_source/catalog/hive_catalog.md), [Iceberg catalog](../../../data_source/catalog/iceberg_catalog.md), [Hudi catalog](../../../data_source/catalog/hudi_catalog.md), [Delta Lake catalog](../../../data_source/catalog/deltalake_catalog.md), and [JDBC Catalog](../../../data_source/catalog/jdbc_catalog.md). |
+
+## Examples
+
+Example 1: Create a Hive catalog named `hive_metastore_catalog`. The corresponding Hive cluster uses Hive metastore as its metadata service.
+
+```SQL
+CREATE EXTERNAL CATALOG hive_metastore_catalog
+PROPERTIES(
+   "type"="hive", 
+   "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
+);
+```
+
+Example 2: Create a Hive catalog named `hive_glue_catalog`. The corresponding Hive cluster uses AWS Glue as its metadata service.
+
+```SQL
+CREATE EXTERNAL CATALOG hive_glue_catalog
+PROPERTIES(
+    "type"="hive", 
+    "hive.metastore.type"="glue",
+    "aws.hive.metastore.glue.aws-access-key"="xxxxxx",
+    "aws.hive.metastore.glue.aws-secret-key"="xxxxxxxxxxxx",
+    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
+);
+```
+
+Example 3: Create an Iceberg catalog named `iceberg_metastore_catalog`. The corresponding Iceberg cluster uses Hive metastore as its metadata service.
+
+```SQL
+CREATE EXTERNAL CATALOG iceberg_metastore_catalog
+PROPERTIES(
+    "type"="iceberg",
+    "iceberg.catalog.type"="hive",
+    "iceberg.catalog.hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
+);
+```
+
+Example 4: Create an Iceberg catalog named `iceberg_glue_catalog`. The corresponding Iceberg cluster uses AWS Glue as its metadata service.
+
+```SQL
+CREATE EXTERNAL CATALOG iceberg_glue_catalog
+PROPERTIES(
+    "type"="iceberg", 
+    "iceberg.catalog.type"="glue",
+    "aws.hive.metastore.glue.aws-access-key"="xxxxx",
+    "aws.hive.metastore.glue.aws-secret-key"="xxxxxxxxxxxx",
+    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
+);
+```
+
+Example 5: Create a Hudi catalog named `hudi_metastore_catalog`. The corresponding Hudi cluster uses Hive metastore as its metadata service.
+
+```SQL
+CREATE EXTERNAL CATALOG hudi_metastore_catalog
+PROPERTIES(
+    "type"="hudi",
+    "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
+);
+```
+
+Example 6: Create a Hudi catalog named `hudi_glue_catalog`. The corresponding Hudi cluster uses AWS Glue as its metadata service.
+
+```SQL
+CREATE EXTERNAL CATALOG hudi_glue_catalog
+PROPERTIES(
+    "type"="hudi", 
+    "hive.metastore.type"="glue",
+    "aws.hive.metastore.glue.aws-access-key"="xxxxxx",
+    "aws.hive.metastore.glue.aws-secret-key"="xxxxxxxxxxxx",
+    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
+);
+```
+
+Example 7: Create a Delta Lake catalog named `delta_metastore_catalog`. The corresponding Delta Lake service uses Hive metastore as its metadata service.
+
+```SQL
+CREATE EXTERNAL CATALOG delta_metastore_catalog
+PROPERTIES(
+    "type"="deltalake",
+    "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
+);
+```
+
+Example 8: Create a Delta Lake catalog named `delta_glue_catalog`. The corresponding Delta Lake service uses AWS Glue as its metadata service.
+
+```SQL
+CREATE EXTERNAL CATALOG delta_glue_catalog
+PROPERTIES(
+    "type"="deltalake", 
+    "hive.metastore.type"="glue",
+    "aws.hive.metastore.glue.aws-access-key"="xxxxxx",
+    "aws.hive.metastore.glue.aws-secret-key"="xxxxxxxxxxxx",
+    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
+);
+```
+
+## References
+
+- To view all catalogs in your StarRocks cluster, see [SHOW CATALOGS](SHOW_CATALOGS.md).
+- To view the creation statement of an external catalog, see [SHOW CREATE CATALOG](SHOW_CREATE_CATALOG.md).
+- To delete an external catalog from your StarRocks cluster, see [DROP CATALOG](DROP_CATALOG.md).
diff --git a/docs/en/sql-reference/sql-statements/Catalog/DROP_CATALOG.md b/docs/en/sql-reference/sql-statements/Catalog/DROP_CATALOG.md
new file mode 100644
index 00000000000000..4a9590ab02b172
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Catalog/DROP_CATALOG.md
@@ -0,0 +1,37 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP CATALOG
+
+## Description
+
+Deletes an external catalog. The internal catalog cannot be deleted. A StarRocks cluster has only one internal catalog named `default_catalog`.
+
+## Syntax
+
+```SQL
+DROP CATALOG [IF EXISTS] <catalog_name>
+```
+
+## Parameters
+
+`catalog_name`: The name of an external catalog.
+
+## Examples
+
+Create a Hive catalog named `hive1`.
+
+```SQL
+CREATE EXTERNAL CATALOG hive1
+PROPERTIES(
+  "type"="hive", 
+  "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
+);
+```
+
+Delete the Hive catalog.
+
+```SQL
+DROP CATALOG hive1;
+```
diff --git a/docs/en/sql-reference/sql-statements/Catalog/SET_CATALOG.md b/docs/en/sql-reference/sql-statements/Catalog/SET_CATALOG.md
new file mode 100644
index 00000000000000..b72c35d7db16a3
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Catalog/SET_CATALOG.md
@@ -0,0 +1,37 @@
+---
+displayed_sidebar: docs
+---
+
+# SET CATALOG
+
+Switches to a specified catalog in the current session.
+
+This command is supported from v3.0 onwards.
+
+> **NOTE**
+>
+> For a newly deployed StarRocks v3.1 cluster, you must have the USAGE privilege on the destination external catalog if you want to run SET CATALOG to switch to that catalog. You can use [GRANT](../account-management/GRANT.md) to grant the required privileges. For a v3.1 cluster upgraded from an earlier version, you can run SET CATALOG with the inherited privilege.
+
+## Syntax
+
+```SQL
+SET CATALOG <catalog_name>
+```
+
+## Parameter
+
+`catalog_name`: the name of the catalog to use in the current session. You can switch to an internal or external catalog. If the catalog that you specify does not exist, an exception is thrown.
+
+## Examples
+
+Run the following command to switch to a Hive catalog named `hive_metastore` in the current session:
+
+```SQL
+SET CATALOG hive_metastore;
+```
+
+Run the following command to switch to the internal catalog `default_catalog` in the current session:
+
+```SQL
+SET CATALOG default_catalog;
+```
diff --git a/docs/en/sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md b/docs/en/sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md
new file mode 100644
index 00000000000000..6b35eeb68df9c9
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md
@@ -0,0 +1,55 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW CATALOGS
+
+## Description
+
+Query all catalogs in the current StarRocks cluster, including the internal catalog and external catalogs.
+
+> **NOTE**
+>
+> SHOW CATALOGS returns external catalogs to users who have the USAGE privilege on that external catalog. If users or roles do not have this privilege on any external catalog, this command returns only the default_catalog.
+
+## Syntax
+
+```SQL
+SHOW CATALOGS
+```
+
+## Output
+
+```SQL
++----------+--------+----------+
+| Catalog  | Type   | Comment  |
++----------+--------+----------+
+```
+
+The following table describes the fields returned by this statement.
+
+| **Field** | **Description**                                              |
+| ------------- | ------------------------------------------------------------ |
+| Catalog       | The catalog name.                                            |
+| Type          | The catalog type. `Internal` is returned if the catalog is `default_catalog`. The corresponding catalog type is returned if the catalog is an external catalog, such as `Hive`, `Hudi`, or `Iceberg`. |
+| Comment       | The comments of a catalog. StarRocks does not support adding comments to an external catalog. Therefore, the value is `NULL` for an external catalog. If the catalog is `default_catalog`, the comment is `An internal catalog contains this cluster's self-managed tables.` by default. `default_catalog` is the only internal catalog in a StarRocks cluster. |
+
+## Examples
+
+Query all catalogs in the current cluster.
+
+```SQL
+SHOW CATALOGS\G
+*************************** 1. row ***************************
+Catalog: default_catalog
+   Type: Internal
+Comment: An internal catalog contains this cluster's self-managed tables.
+*************************** 2. row ***************************
+Catalog: hudi_catalog
+   Type: Hudi
+Comment: NULL
+*************************** 3. row ***************************
+Catalog: iceberg_catalog
+   Type: Iceberg
+Comment: NULL
+```
diff --git a/docs/en/sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md b/docs/en/sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md
new file mode 100644
index 00000000000000..92515a4c5dcc6f
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md
@@ -0,0 +1,70 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW CREATE CATALOG
+
+## Description
+
+Queries the creation statement of an external catalog, including:
+
+- [Hive Catalog](../../../data_source/catalog/hive_catalog.md)
+- [Iceberg Catalog](../../../data_source/catalog/iceberg_catalog.md)
+- [Hudi Catalog](../../../data_source/catalog/hudi_catalog.md)
+- [Delta Lake Catalog](../../../data_source/catalog/deltalake_catalog.md)
+- [JDBC catalog](../../../data_source/catalog/jdbc_catalog.md) (since v3.0)
+- [Unified catalog](../../../data_source/catalog/unified_catalog.md) (since v3.2)
+- [MaxCompute catalog](../../../data_source/catalog/maxcompute_catalog.md) (since v3.3)
+
+Note that authentication-related information in the return result will be anonymized.
+
+This command is supported from v3.0 onwards.
+
+## Syntax
+
+```SQL
+SHOW CREATE CATALOG <catalog_name>;
+```
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                              |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| catalog_name  | Yes          | The name of the catalog whose creation statement you want to view. |
+
+## Return result
+
+```Plain
++------------+-----------------+
+| Catalog    | Create Catalog  |
++------------+-----------------+
+```
+
+| **Field**  | **Description**                                        |
+| -------------- | ------------------------------------------------------ |
+| Catalog        | The name of the catalog.                               |
+| Create Catalog | The statement that was executed to create the catalog. |
+
+## Examples
+
+The following example queries the creation statement of a Hive catalog named `hive_catalog_hms`:
+
+```SQL
+SHOW CREATE CATALOG hive_catalog_hms;
+```
+
+The return result is as follows:
+
+```SQL
+CREATE EXTERNAL CATALOG `hive_catalog_hms`
+PROPERTIES ("aws.s3.access_key"  =  "AK******M4",
+"hive.metastore.type"  =  "glue",
+"aws.s3.secret_key"  =  "iV******iD",
+"aws.glue.secret_key"  =  "iV******iD",
+"aws.s3.use_instance_profile"  =  "false",
+"aws.s3.region"  =  "us-west-1",
+"aws.glue.region"  =  "us-west-1",
+"type"  =  "hive",
+"aws.glue.access_key"  =  "AK******M4"
+)
+```
diff --git a/docs/en/sql-reference/sql-statements/Catalog/_category_.yml b/docs/en/sql-reference/sql-statements/Catalog/_category_.yml
new file mode 100644
index 00000000000000..e96c64cf0ca698
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Catalog/_category_.yml
@@ -0,0 +1,6 @@
+position: 50 # float position is supported
+label: 'Catalog'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-statements/Database/ALTER_DATABASE.md b/docs/en/sql-reference/sql-statements/Database/ALTER_DATABASE.md
new file mode 100644
index 00000000000000..e51d03fed72801
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Database/ALTER_DATABASE.md
@@ -0,0 +1,74 @@
+---
+displayed_sidebar: docs
+---
+
+# ALTER DATABASE
+
+## Description
+
+Configures the properties of the specified database.
+
+:::tip
+
+This operation requires the ALTER privilege on the target database. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+1. Set database data quota in B/K/KB/M/MB/G/GB/T/TB/P/PB.
+
+    ```sql
+    ALTER DATABASE <db_name> SET DATA QUOTA <quota>;
+    ```
+
+2. Rename a database.
+
+    ```sql
+    ALTER DATABASE <db_name> RENAME <new_db_name>;
+    ```
+
+3. Set database replica quota.
+
+    ```sql
+    ALTER DATABASE <db_name> SET REPLICA QUOTA <quota>;
+    ```
+
+Note:
+
+```plain text
+- After renaming the database, use REVOKE and GRANT commands to modify the corresponding user permission if necessary.
+- The database's default data quota and the default replica quota are 2^63-1.
+```
+
+## Examples
+
+1. Set data quota for a database.
+
+    ```SQL
+    ALTER DATABASE example_db SET DATA QUOTA 10995116277760B;
+    -- The above unit is bytes, equivalent to the following statement.
+    ALTER DATABASE example_db SET DATA QUOTA 10T;
+    ALTER DATABASE example_db SET DATA QUOTA 100G;
+    ALTER DATABASE example_db SET DATA QUOTA 200M;
+    ```
+
+2. Rename the database `example_db` as `example_db2`.
+
+    ```SQL
+    ALTER DATABASE example_db RENAME example_db2;
+    ```
+
+3. Set database replica quota.
+
+    ```SQL
+    ALTER DATABASE example_db SET REPLICA QUOTA 102400;
+    ```
+
+## References
+
+- [CREATE DATABASE](CREATE_DATABASE.md)
+- [USE](USE.md)
+- [SHOW DATABASES](SHOW_DATABASES.md)
+- [DESC](../table_bucket_part_index/DESCRIBE.md)
+- [DROP DATABASE](DROP_DATABASE.md)
diff --git a/docs/en/sql-reference/sql-statements/Database/CREATE_DATABASE.md b/docs/en/sql-reference/sql-statements/Database/CREATE_DATABASE.md
new file mode 100644
index 00000000000000..47ca23555ce14a
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Database/CREATE_DATABASE.md
@@ -0,0 +1,53 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE DATABASE
+
+## Description
+
+This statement is used to create databases.
+
+:::tip
+
+This operation requires the CREATE DATABASE privilege on the target catalog. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```sql
+CREATE DATABASE [IF NOT EXISTS] <db_name>
+[PROPERTIES ("key"="value", ...)]
+```
+
+## Parameters
+
+`db_name`: the name of the database to create. For the naming conventions, see [System limits](../../System_limit.md).
+
+**PROPERTIES (Optional)**
+
+`storage_volume`: Specifies the name of the storage volume that is used to store the database in a shared-data cluster.
+
+## Examples
+
+1. Create the database `db_test`.
+
+   ```sql
+   CREATE DATABASE db_test;
+   ```
+
+2. Create the cloud-native database `cloud_db` with the storage volume `s3_storage_volume`.
+
+   ```sql
+   CREATE DATABASE cloud_db
+   PROPERTIES ("storage_volume"="s3_storage_volume");
+   ```
+
+## References
+
+- [SHOW CREATE DATABASE](SHOW_CREATE_DATABASE.md)
+- [USE](USE.md)
+- [SHOW DATABASES](SHOW_DATABASES.md)
+- [DESC](../table_bucket_part_index/DESCRIBE.md)
+- [DROP DATABASE](DROP_DATABASE.md)
diff --git a/docs/en/sql-reference/sql-statements/Database/DROP_DATABASE.md b/docs/en/sql-reference/sql-statements/Database/DROP_DATABASE.md
new file mode 100644
index 00000000000000..52ccaee99e70ec
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Database/DROP_DATABASE.md
@@ -0,0 +1,41 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP DATABASE
+
+## Description
+
+Drops a database in StarRocks.
+
+> **NOTE**
+>
+> This operation requires the DROP privilege on the destination database.
+
+## Syntax
+
+```sql
+DROP DATABASE [IF EXISTS] <db_name> [FORCE]
+```
+
+Take note of the following points:
+
+- After executing DROP DATABASE to drop a database, you can restore the dropped database by using the [RECOVER](../backup_restore/RECOVER.md) statement within a specified retention period (the default retention period spans one day), but the pipes (supported from v3.2 onwards) that have been dropped along with the database cannot be recovered.
+- If you execute `DROP DATABASE FORCE` to drop a database, the database is deleted directly without any checks on whether there are unfinished activities in it and cannot be recovered. Generally, this operation is not recommended.
+- If you drop a database, all pipes (supported from v3.2 onwards) that belong to the database are dropped along with the database.
+
+## Examples
+
+1. Drop database db_text.
+
+    ```sql
+    DROP DATABASE db_test;
+    ```
+
+## References
+
+- [CREATE DATABASE](CREATE_DATABASE.md)
+- [SHOW CREATE DATABASE](SHOW_CREATE_DATABASE.md)
+- [USE](USE.md)
+- [DESC](../table_bucket_part_index/DESCRIBE.md)
+- [SHOW DATABASES](SHOW_DATABASES.md)
diff --git a/docs/en/sql-reference/sql-statements/Database/SHOW_CREATE_DATABASE.md b/docs/en/sql-reference/sql-statements/Database/SHOW_CREATE_DATABASE.md
new file mode 100644
index 00000000000000..0ac10b47d05b9a
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Database/SHOW_CREATE_DATABASE.md
@@ -0,0 +1,42 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW CREATE DATABASE
+
+Shows the SQL command used to create a database.
+
+## Syntax
+
+```sql
+SHOW CREATE DATABASE <db_name>
+```
+
+## Parameters
+
+`db_name`: the database name, required.
+
+## Returns
+
+- `Database`: the database name
+
+- `Create Database`: the SQL command used to create the database
+
+## Examples
+
+```sql
+mysql > show create database zj_test;
++----------+---------------------------+
+| Database | Create Database           |
++----------+---------------------------+
+| zj_test  | CREATE DATABASE `zj_test` |
++----------+---------------------------+
+```
+
+## References
+
+- [CREATE DATABASE](CREATE_DATABASE.md)
+- [SHOW DATABASES](SHOW_DATABASES.md)
+- [USE](USE.md)
+- [DESC](../table_bucket_part_index/DESCRIBE.md)
+- [DROP DATABASE](DROP_DATABASE.md)
diff --git a/docs/en/sql-reference/sql-statements/Database/SHOW_DATA.md b/docs/en/sql-reference/sql-statements/Database/SHOW_DATA.md
new file mode 100644
index 00000000000000..f6e66da6719a32
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Database/SHOW_DATA.md
@@ -0,0 +1,53 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW DATA
+
+## Description
+
+This statement is used to display the amount of data, the number of copies, and the number of statistical rows in a database or a database table.
+
+Syntax:
+
+```sql
+SHOW DATA [FROM <db_name>[.<table_name>]]
+```
+
+Note:
+
+1. If the FROM clause is not specified, the amount of data and copies subdivided into each table in the current db will be displayed. Where the data volume is the total data volume of all replicas. The number of copies is the number of copies of all partitions of the table and all materialized views.
+2. If the FROM clause is specified, the amount of data, the number of copies and the number of statistical rows subdivided into each materialized view under the table are displayed. Where the data volume is the total data volume of all replicas. The number of copies is the number of copies of all partitions corresponding to the materialized view. The number of statistical rows is the number of statistical rows of all partitions corresponding to the materialized view.
+3. When counting the number of rows, the copy with the largest number of rows among multiple copies shall prevail.
+4. The Total row in the result set represents the summary row. The Quota row represents the quota set by the current database. The Left line represents the remaining quota.
+
+## Examples
+
+Example 1: Display the data volume, copy quantity, summary data volume and summary copy quantity of each table in the current database.
+
+```plain text
+SHOW DATA;
++-----------+-------------+--------------+
+| TableName | Size        | ReplicaCount |
++-----------+-------------+--------------+
+| tbl1      | 900.000 B   | 6            |
+| tbl2      | 500.000 B   | 3            |
+| Total     | 1.400 KB    | 9            |
+| Quota     | 1024.000 GB | 1073741824   |
+| Left      | 1021.921 GB | 1073741815   |
++-----------+-------------+--------------+
+```
+
+Example 2: Display the amount of breakdown data, the number of copies, and the number of statistical rows in the specified table.
+
+```plain text
+SHOW DATA FROM example_db.test;
++-----------+-----------+-----------+--------------+----------+
+| TableName | IndexName | Size      | ReplicaCount | RowCount |
++-----------+-----------+-----------+--------------+----------+
+| test      | r1        | 10.000MB  | 30           | 10000    |
+|           | r2        | 20.000MB  | 30           | 20000    |
+|           | test2     | 50.000MB  | 30           | 50000    |
+|           | Total     | 80.000    | 90           |          |
++-----------+-----------+-----------+--------------+----------+
+```
diff --git a/docs/en/sql-reference/sql-statements/Database/SHOW_DATABASES.md b/docs/en/sql-reference/sql-statements/Database/SHOW_DATABASES.md
new file mode 100644
index 00000000000000..39e248ce69f660
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Database/SHOW_DATABASES.md
@@ -0,0 +1,69 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW DATABASES
+
+## Description
+
+Views databases in your current StarRocks cluster or an external data source. StarRocks supports viewing databases of an external data source from v2.3 onwards.
+
+## Syntax
+
+```SQL
+SHOW DATABASES [FROM <catalog_name>]
+```
+
+## Parameters
+
+| **Parameter**     | **Required** | **Description**                                              |
+| ----------------- | ------------ | ------------------------------------------------------------ |
+| catalog_name      | No           | The name of the internal catalog or an external catalog.<ul><li>If you do not specify the parameter or specify the name of the internal catalog, which is `default_catalog`, you can view databases in your current StarRocks cluster.</li><li>If you set the value of the parameter to the name of an external catalog, you can view databases in the corresponding external data source. You can run [SHOW CATALOGS](../Catalog/SHOW_CATALOGS.md) to view internal and external catalogs.</li></ul> |
+
+## Examples
+
+Example 1: View databases in your current StarRocks cluster.
+
+```SQL
+SHOW DATABASES;
+```
+
+Or
+
+```SQL
+SHOW DATABASES FROM default_catalog;
+```
+
+The output of the preceding statements is as follows.
+
+```SQL
++----------+
+| Database |
++----------+
+| db1      |
+| db2      |
+| db3      |
++----------+
+```
+
+Example 2: View databases in a Hive cluster by using the `Hive1` external catalog.
+
+```SQL
+SHOW DATABASES FROM hive1;
+
++-----------+
+| Database  |
++-----------+
+| hive_db1  |
+| hive_db2  |
+| hive_db3  |
++-----------+
+```
+
+## References
+
+- [CREATE DATABASE](CREATE_DATABASE.md)
+- [SHOW CREATE DATABASE](SHOW_CREATE_DATABASE.md)
+- [USE](USE.md)
+- [DESC](../table_bucket_part_index/DESCRIBE.md)
+- [DROP DATABASE](DROP_DATABASE.md)
diff --git a/docs/en/sql-reference/sql-statements/Database/USE.md b/docs/en/sql-reference/sql-statements/Database/USE.md
new file mode 100644
index 00000000000000..6d9ba17a769a3d
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Database/USE.md
@@ -0,0 +1,48 @@
+---
+displayed_sidebar: docs
+---
+
+# USE
+
+## Description
+
+Specifies the active database for your session. You can then perform operations, such as creating tables and executing queries.
+
+## Syntax
+
+```SQL
+USE [<catalog_name>.]<db_name>
+```
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                              |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| catalog_name  | No           | The catalog name.<ul><li>If this parameter is not specified, a database in `default_catalog` is used by default.</li><li>You must specify this parameter when you use a database from an external catalog. For more information, see Example 2.</li><li>You must specify this parameter when you switch databases between different catalogs. For more information, see Example 3.</li></ul>For more information about catalogs, see [Overview](../../../data_source/catalog/catalog_overview.md). |
+| db_name       | Yes          | The database name. The database must exist.                  |
+
+## Examples
+
+Example 1: Use `example_db` from `default_catalog` as the active database of your session.
+
+```SQL
+USE default_catalog.example_db;
+```
+
+Or
+
+```SQL
+USE example_db;
+```
+
+Example 2: Use `example_db` from `hive_catalog` as the active database of your session.
+
+```SQL
+USE hive_catalog.example_db;
+```
+
+Example 3: Switch the active database of your session from `hive_catalog.example_table1` to `iceberg_catalog.example_table2`.
+
+```SQL
+USE iceberg_catalog.example_table2;
+```
diff --git a/docs/en/sql-reference/sql-statements/Database/_category_.yml b/docs/en/sql-reference/sql-statements/Database/_category_.yml
new file mode 100644
index 00000000000000..880f366cbf8695
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Database/_category_.yml
@@ -0,0 +1,6 @@
+position: 60 # float position is supported
+label: 'Database'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-statements/Function/CREATE_FUNCTION.md b/docs/en/sql-reference/sql-statements/Function/CREATE_FUNCTION.md
new file mode 100644
index 00000000000000..21e9919221c27f
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Function/CREATE_FUNCTION.md
@@ -0,0 +1,37 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE FUNCTION
+
+## Description
+
+Creates a user-defined function (UDF). Currently, you can only create Java UDFs, including Scalar functions, user-defined aggregate functions (UDAFs), user-defined window functions (UDWFs), and user-defined table functions (UDTFs).
+
+**For details about how to compile, create, and use a Java UDF, see [Java UDF](../../sql-functions/JAVA_UDF.md).**
+
+> **NOTE**
+>
+> To create a global UDF, you must have the SYSTEM-level CREATE GLOBAL FUNCTION privilege. To create a database-wide UDF, you must have the DATABASE-level CREATE FUNCTION privilege.
+
+## Syntax
+
+```sql
+CREATE [OR REPLACE] [GLOBAL] [AGGREGATE | TABLE] FUNCTION function_name
+(arg_type [, ...])
+RETURNS return_type
+PROPERTIES ("key" = "value" [, ...])
+```
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                     |
+| ------------- | -------- | ------------------------------------------------------------ |
+| OR REPLACE    | No       | If a function exists sharing the same function signature, it will be replaced. Supported from v3.4.  |
+| GLOBAL        | No       | Whether to create a global UDF, supported from v3.0.  |
+| AGGREGATE     | No       | Whether to create a UDAF or UDWF.       |
+| TABLE         | No       | Whether to create a UDTF. If both `AGGREGATE` and `TABLE` are not specified, a Scalar function is created.               |
+| function_name | Yes      | The name of the function you want to create. You can include the name of the database in this parameter, for example,`db1.my_func`. If `function_name` includes the database name, the UDF is created in that database. Otherwise, the UDF is created in the current database. The name of the new function and its parameters cannot be the same as an existing name in the destination database. Otherwise, the function cannot be created. The creation succeeds if the function name is the same but the parameters are different. |
+| arg_type      | Yes      | Argument type of the function. The added argument can be represented by `, ...`. For the supported data types, see [Java UDF](../../sql-functions/JAVA_UDF.md#mapping-between-sql-data-types-and-java-data-types).|
+| return_type   | Yes      | The return type of the function. For the supported data types, see [Java UDF](../../sql-functions/JAVA_UDF.md#mapping-between-sql-data-types-and-java-data-types). |
+| PROPERTIES    | Yes      | Properties of the function, which vary depending on the type of the UDF to create. For details, see [Java UDF](../../sql-functions/JAVA_UDF.md#step-6-create-the-udf-in-starrocks). |
diff --git a/docs/en/sql-reference/sql-statements/Function/DROP_FUNCTION.md b/docs/en/sql-reference/sql-statements/Function/DROP_FUNCTION.md
new file mode 100644
index 00000000000000..dc3457212d2d07
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Function/DROP_FUNCTION.md
@@ -0,0 +1,31 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP FUNCTION
+
+## Description
+
+Deletes a custom function. The function can only be deleted when its name and parameter type are consistent.
+
+Only the owner of the custom function have the permissions to delete the function.
+
+### Syntax
+
+```sql
+DROP FUNCTION function_name(arg_type [, ...])
+```
+
+### Parameters
+
+`function_name`: the name of function to be dropped.
+
+`arg_type`: the argument type of function to be dropped.
+
+## Examples
+
+1. Drop a function.
+
+    ```sql
+    DROP FUNCTION my_add(INT, INT)
+    ```
diff --git a/docs/en/sql-reference/sql-statements/Function/SHOW_FUNCTIONS.md b/docs/en/sql-reference/sql-statements/Function/SHOW_FUNCTIONS.md
new file mode 100644
index 00000000000000..b3c1b3ace3e5fc
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Function/SHOW_FUNCTIONS.md
@@ -0,0 +1,57 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW FUNCTIONS
+
+## Description
+
+Queries all the custom (or built-in) functions under a database. If no database is specified, the current database is used by default.
+
+## Syntax
+
+```sql
+SHOW [FULL] [BUILTIN] FUNCTIONS [IN|FROM db] [LIKE 'function_pattern']
+```
+
+## Parameters
+
+```plain text
+full: indicates showing all the functions. 
+
+builtin: indicates showing functions provided by the system.
+
+db: the name of the database to query.
+
+function_pattern: the pattern used to filter function name. 
+```
+
+## Examples
+
+```Plain Text
+mysql> show full functions in testDb\G
+*************************** 1. row ***************************
+        Signature: my_add(INT,INT)
+      Return Type: INT
+    Function Type: Scalar
+Intermediate Type: NULL
+       Properties: {"symbol":"_ZN9starrocks_udf6AddUdfEPNS_15FunctionContextERKNS_6IntValES4_","object_file":"http://host:port/libudfsample.so","md5":"cfe7a362d10f3aaf6c49974ee0f1f878"}
+*************************** 2. row ***************************
+        Signature: my_count(BIGINT)
+      Return Type: BIGINT
+    Function Type: Aggregate
+Intermediate Type: NULL
+       Properties: {"object_file":"http://host:port/libudasample.so","finalize_fn":"_ZN9starrocks_udf13CountFinalizeEPNS_15FunctionContextERKNS_9BigIntValE","init_fn":"_ZN9starrocks_udf9CountInitEPNS_15FunctionContextEPNS_9BigIntValE","merge_fn":"_ZN9starrocks_udf10CountMergeEPNS_15FunctionContextERKNS_9BigIntValEPS2_","md5":"37d185f80f95569e2676da3d5b5b9d2f","update_fn":"_ZN9starrocks_udf11CountUpdateEPNS_15FunctionContextERKNS_6IntValEPNS_9BigIntValE"}
+
+2 rows in set (0.00 sec)
+mysql> show builtin functions in testDb like 'year%';
++---------------+
+| Function Name |
++---------------+
+| year          |
+| years_add     |
+| years_diff    |
+| years_sub     |
++---------------+
+2 rows in set (0.00 sec)
+```
diff --git a/docs/en/sql-reference/sql-statements/Function/_category_.yml b/docs/en/sql-reference/sql-statements/Function/_category_.yml
new file mode 100644
index 00000000000000..398d19d7c597b1
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Function/_category_.yml
@@ -0,0 +1,6 @@
+position: 110 # float position is supported
+label: 'Function'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-statements/Resource/ALTER_RESOURCE.md b/docs/en/sql-reference/sql-statements/Resource/ALTER_RESOURCE.md
new file mode 100644
index 00000000000000..df8068dde560c0
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Resource/ALTER_RESOURCE.md
@@ -0,0 +1,37 @@
+---
+displayed_sidebar: docs
+---
+
+# ALTER RESOURCE
+
+## Description
+
+You can use the ALTER RESOURCE statement to modify the properties of a resource.
+
+## Syntax
+
+```SQL
+ALTER RESOURCE 'resource_name' SET PROPERTIES ("key"="value", ...)
+```
+
+## Parameters
+
+- `resource_name`: the name of the resource to be modified.
+
+- `PROPERTIES ("key"="value", ...)`: the properties of the resource. You can modify different properties based on resource types. Currently, StarRocks supports modifying the URI of the Hive metastore of the following resources.
+  - Apache Iceberg resources support modifying the following properties:
+    - `iceberg.catalog-impl`: the fully qualified class name of [custom catalog](../../../data_source/External_table.md).
+    - `iceberg.catalog.hive.metastore.uris`: the URI of the Hive metastore.
+  - Apache Hive™ resources and Apache Hudi resources support modifying `hive.metastore.uris`, which indicates the URI of the Hive metastore.
+
+## Usage notes
+
+After you reference a resource to create an external table, if you modify the URI of the Hive metastore of this resource, the external table becomes unavailable. If you still want to use the external table to query data, make sure that the new metastore contains a table whose name and schema are the same as that in the original metastore.
+
+## Examples
+
+Modify the URI of the Hive metastore of Hive resource `hive0`.
+
+```SQL
+ALTER RESOURCE 'hive0' SET PROPERTIES ("hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083")
+```
diff --git a/docs/en/sql-reference/sql-statements/Resource/CREATE_RESOURCE.md b/docs/en/sql-reference/sql-statements/Resource/CREATE_RESOURCE.md
new file mode 100644
index 00000000000000..c028ec80e6a820
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Resource/CREATE_RESOURCE.md
@@ -0,0 +1,82 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE RESOURCE
+
+## Description
+
+Creates resources. The following types of resources can be created: Apache Spark™, Apache Hive™, Apache Iceberg, Apache Hudi, and JDBC. Spark resources are used in [Spark Load](../../../loading/SparkLoad.md) to manage loading information, such as YARN configurations, storage path of intermediate data, and Broker configurations. Hive, Iceberg, Hudi, and JDBC resources are used for managing data source access information involved in querying [External tables](../../../data_source/External_table.md).
+
+:::tip
+
+- Only users with the SYSTEM-level CREATE RESOURCE privilege can perform this operation.
+- You can create JDBC resources only in StarRocks v2.3 and later.
+
+:::
+
+## Syntax
+
+```sql
+CREATE [EXTERNAL] RESOURCE "resource_name"
+PROPERTIES ("key"="value", ...)
+```
+
+## Parameters
+
+- `resource_name`: the name of the resource to create. For the naming conventions, see [System limits](../../System_limit.md).
+
+- `PROPERTIES`: specifies the properties of the resource type. The PROPERTIES vary depending on the resource type. See Examples for details.
+
+## Examples
+
+1. Create a Spark resource named spark0 in yarn Cluster mode.
+
+    ```sql
+    CREATE EXTERNAL RESOURCE "spark0"
+    PROPERTIES
+    (
+        "type" = "spark",
+        "spark.master" = "yarn",
+        "spark.submit.deployMode" = "cluster",
+        "spark.jars" = "xxx.jar,yyy.jar",
+        "spark.files" = "/tmp/aaa,/tmp/bbb",
+        "spark.executor.memory" = "1g",
+        "spark.yarn.queue" = "queue0",
+        "spark.hadoop.yarn.resourcemanager.address" = "127.0.0.1:9999",
+        "spark.hadoop.fs.defaultFS" = "hdfs://127.0.0.1:10000",
+        "working_dir" = "hdfs://127.0.0.1:10000/tmp/starrocks",
+        "broker" = "broker0",
+        "broker.username" = "user0",
+        "broker.password" = "password0"
+    );
+    ```
+
+    Parameters related to Spark are as follows:
+
+    ```plain text
+    1. spark.master: required. Currently, yarn and spark ://host:port. are supported. 
+    2. spark.submit.deployMode: deployment mode of the Spark program is required. Support cluster and client.
+    3. spark.hadoop.yarn.resourcemanager.address: required when master is yarn.
+    4. spark.hadoop.fs.defaultFS: required when master is yarn.
+    5. Other parameters are optional. Please refer to http://spark.apache.org/docs/latest/configuration.html
+    ```
+
+    If Spark is used for ETL, working_DIR and broker need to be specified. The instructions are as follows:
+
+    ```plain text
+    working_dir: Directory used by ETL. It is required when spark is used as ETL resource. For example: hdfs://host:port/tmp/starrocks.
+    broker: Name of broker. It is required when spark is used as ETL resource and needs to be configured beforehand by using `ALTER SYSTEM ADD BROKER` command. 
+    broker.property_key: It is the property information needed to be specified when broker reads the intermediate files created by ETL. 
+    ```
+
+2. Create a Hive resource named hive0.
+
+    ```sql
+    CREATE EXTERNAL RESOURCE "hive0"
+    PROPERTIES
+    (
+        "type" = "hive",
+        "hive.metastore.uris" = "thrift://10.10.44.98:9083"
+    );
+    ```
diff --git a/docs/en/sql-reference/sql-statements/Resource/DROP_RESOURCE.md b/docs/en/sql-reference/sql-statements/Resource/DROP_RESOURCE.md
new file mode 100644
index 00000000000000..d86fcfe45b827b
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Resource/DROP_RESOURCE.md
@@ -0,0 +1,29 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP RESOURCE
+
+## Description
+
+This statement is used to drop an existing resource. Only root or superuser can drop resources.
+
+Syntax:
+
+```sql
+DROP RESOURCE 'resource_name'
+```
+
+## Examples
+
+1. Drop Spark resource named spark0.
+
+    ```SQL
+    DROP RESOURCE 'spark0';
+    ```
+
+2. Drop Hive resource named hive0.
+
+    ```SQL
+    DROP RESOURCE 'hive0';
+    ```
diff --git a/docs/en/sql-reference/sql-statements/Resource/SHOW_RESOURCES.md b/docs/en/sql-reference/sql-statements/Resource/SHOW_RESOURCES.md
new file mode 100644
index 00000000000000..3b6b0fa45217c8
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Resource/SHOW_RESOURCES.md
@@ -0,0 +1,15 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW RESOURCES
+
+## Description
+
+This statement is used to show the resources that the users have permissions to use. Ordinary users can only use the resources they have permission to use, while root or admin users can show all resources.
+
+Syntax:
+
+```sql
+SHOW RESOURCES
+```
diff --git a/docs/en/sql-reference/sql-statements/Resource/_category_.yml b/docs/en/sql-reference/sql-statements/Resource/_category_.yml
new file mode 100644
index 00000000000000..064c79f03f6a27
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/Resource/_category_.yml
@@ -0,0 +1,6 @@
+position: 70 # float position is supported
+label: 'Resource'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-statements/Utility/DESCRIBE.md b/docs/en/sql-reference/sql-statements/Utility/DESCRIBE.md
deleted file mode 100644
index bf9acbc7be93c7..00000000000000
--- a/docs/en/sql-reference/sql-statements/Utility/DESCRIBE.md
+++ /dev/null
@@ -1,118 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DESC
-
-## Description
-
-You can use the statement to perform the following operations:
-
-- View the schema of a table stored in your StarRocks cluster, along with the type of the [sort key](../../../table_design/indexes/Prefix_index_sort_key.md) and [materialized view](../../../using_starrocks/Materialized_view.md) of the table.
-- View the schema of a table stored in the following external data sources, such as Apache Hive™. Note that you can perform this operation only in StarRocks 2.4 and later versions.
-
-## Syntax
-
-```SQL
-DESC[RIBE] [catalog_name.][db_name.]table_name [ALL];
-```
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                              |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| catalog_name  | No           | The name of the internal catalog or an external catalog. <ul><li>If you set the value of the parameter to the name of the internal catalog, which is `default_catalog`, you can view the schema of the table stored in your StarRocks cluster. </li><li>If you set the value of the parameter to the name of an external catalog, you can view the schema of the table stored in the external data source.</li></ul> |
-| db_name       | No           | The database name.                                           |
-| table_name    | Yes          | The table name.                                              |
-| ALL           | No           | <ul><li>If this keyword is specified, you can view the type of the sort key, materialized view, and schema of a table stored in your StarRocks cluster. If this keyword is not specified, you only view the table schema. </li><li>Do not specify this keyword when you view the schema of a table stored in an external data source.</li></ul> |
-
-## Output
-
-```Plain
-+-----------+---------------+-------+------+------+-----+---------+-------+
-| IndexName | IndexKeysType | Field | Type | Null | Key | Default | Extra |
-+-----------+---------------+-------+------+------+-----+---------+-------+
-```
-
-The following table describes the parameters returned by this statement.
-
-| **Parameter** | **Description**                                              |
-| ------------- | ------------------------------------------------------------ |
-| IndexName     | The table name. If you view the schema of a table stored in an external data source, this parameter is not returned. |
-| IndexKeysType | The type of the sort key of the table. If you view the schema of a table stored in an external data source, this parameter is not returned. |
-| Field         | The column name.                                             |
-| Type          | The data type of the column.                                 |
-| Null          | Whether the column values can be NULL. <ul><li>`yes`: indicates the values can be NULL. </li><li>`no`: indicates the values cannot be NULL. </li></ul>|
-| Key           | Whether the column is used as the sort key. <ul><li>`true`: indicates the column is used as the sort key. </li><li>`false`: indicates the column is not used as the sort key. </li></ul>|
-| Default       | The default value for the data type of the column. If the data type does not have a default value, a NULL is returned. |
-| Extra         | <ul><li>If you see the schema of a table stored in your StarRocks cluster, this field displays the following information about the column: <ul><li>The aggregate function used by the column, such as `SUM` and `MIN`. </li><li>Whether a bloom filter index is created on the column. If so, the value of `Extra` is `BLOOM_FILTER`. </li></ul></li><li>If you see the schema of a table stored in external data sources, this field displays whether the column is the partition column. If the column is the partition column, the value of `Extra` is `partition key`. </li></ul>|
-
-> Note: For information about how a materialized view is displayed in the output, see Example 2.
-
-## Examples
-
-Example 1: View the schema of `example_table` stored in your StarRocks cluster.
-
-```SQL
-DESC example_table;
-```
-
-Or
-
-```SQL
-DESC default_catalog.example_db.example_table;
-```
-
-The output of the preceding statements is as follows.
-
-```Plain
-+-------+---------------+------+-------+---------+-------+
-| Field | Type          | Null | Key   | Default | Extra |
-+-------+---------------+------+-------+---------+-------+
-| k1    | TINYINT       | Yes  | true  | NULL    |       |
-| k2    | DECIMAL(10,2) | Yes  | true  | 10.5    |       |
-| k3    | CHAR(10)      | Yes  | false | NULL    |       |
-| v1    | INT           | Yes  | false | NULL    |       |
-+-------+---------------+------+-------+---------+-------+
-```
-
-Example 2: View the schema, type of the sort key, and materialized view of `sales_records` stored in your StarRocks cluster. In the following example, one materialized view `store_amt` is created based on `sales_records`.
-
-```Plain
-DESC db1.sales_records ALL;
-
-+---------------+---------------+-----------+--------+------+-------+---------+-------+
-| IndexName     | IndexKeysType | Field     | Type   | Null | Key   | Default | Extra |
-+---------------+---------------+-----------+--------+------+-------+---------+-------+
-| sales_records | DUP_KEYS      | record_id | INT    | Yes  | true  | NULL    |       |
-|               |               | seller_id | INT    | Yes  | true  | NULL    |       |
-|               |               | store_id  | INT    | Yes  | true  | NULL    |       |
-|               |               | sale_date | DATE   | Yes  | false | NULL    | NONE  |
-|               |               | sale_amt  | BIGINT | Yes  | false | NULL    | NONE  |
-|               |               |           |        |      |       |         |       |
-| store_amt     | AGG_KEYS      | store_id  | INT    | Yes  | true  | NULL    |       |
-|               |               | sale_amt  | BIGINT | Yes  | false | NULL    | SUM   |
-+---------------+---------------+-----------+--------+------+-------+---------+-------+
-```
-
-Example 3: View the schema of `hive_table` stored in your Hive cluster.
-
-```Plain
-DESC hive_catalog.hive_db.hive_table;
-
-+-------+----------------+------+-------+---------+---------------+ 
-| Field | Type           | Null | Key   | Default | Extra         | 
-+-------+----------------+------+-------+---------+---------------+ 
-| id    | INT            | Yes  | false | NULL    |               | 
-| name  | VARCHAR(65533) | Yes  | false | NULL    |               | 
-| date  | DATE           | Yes  | false | NULL    | partition key | 
-+-------+----------------+------+-------+---------+---------------+
-```
-
-## References
-
-- [CREATE DATABASE](../data-definition/CREATE_DATABASE.md)
-- [SHOW CREATE DATABASE](../data-manipulation/SHOW_CREATE_DATABASE.md)
-- [USE](../data-definition/USE.md)
-- [SHOW DATABASES](../data-manipulation/SHOW_DATABASES.md)
-- [DROP DATABASE](../data-definition/DROP_DATABASE.md)
diff --git a/docs/en/sql-reference/sql-statements/View/ALTER_VIEW.md b/docs/en/sql-reference/sql-statements/View/ALTER_VIEW.md
new file mode 100644
index 00000000000000..c8f5eb4e0389a7
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/View/ALTER_VIEW.md
@@ -0,0 +1,39 @@
+---
+displayed_sidebar: docs
+---
+
+# ALTER VIEW
+
+## Description
+
+Modifies the definition of a view.
+
+## Syntax
+
+```sql
+ALTER VIEW
+[db_name.]view_name
+(column1[ COMMENT "col comment"][, column2, ...])
+AS query_stmt
+```
+
+Note:
+
+1. View is logical, where the data isn't stored in the physical medium. The view will be used as a subquery in the statement when queried. Therefore, modifying the definition of views is equivalent to modifying query_stmt.
+2. query_stmt is arbitrarily supported SQL.
+
+## Examples
+
+Alter `example_view` on `example_db`.
+
+```sql
+ALTER VIEW example_db.example_view
+(
+c1 COMMENT "column 1",
+c2 COMMENT "column 2",
+c3 COMMENT "column 3"
+)
+AS SELECT k1, k2, SUM(v1) 
+FROM example_table
+GROUP BY k1, k2
+```
diff --git a/docs/en/sql-reference/sql-statements/View/CREATE_VIEW.md b/docs/en/sql-reference/sql-statements/View/CREATE_VIEW.md
new file mode 100644
index 00000000000000..910b2ebe69b0c6
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/View/CREATE_VIEW.md
@@ -0,0 +1,79 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE VIEW
+
+## Description
+
+Creates a view.
+
+A view, or a logical view, is a virtual table whose data is derived from a query against other existing physical tables. Therefore, a view uses no physical storage, and all queries against the view are equivalent to sub-queries of the query statement used to build the view.
+
+For information about materialized views supported by StarRocks, see [Synchronous materialized views](../../../using_starrocks/Materialized_view-single_table.md) and [Asynchronous materialized views](../../../using_starrocks/Materialized_view.md).
+
+:::tip
+Only users with the CREATE VIEW privilege on a specific database can perform this operation.
+:::
+
+## Syntax
+
+```SQL
+CREATE [OR REPLACE] VIEW [IF NOT EXISTS]
+[<database>.]<view_name>
+(
+    <column_name>[ COMMENT 'column comment']
+    [, <column_name>[ COMMENT 'column comment'], ...]
+)
+[COMMENT 'view comment']
+AS <query_statement>
+```
+
+## Parameters
+
+| **Parameter**   | **Description**                                              |
+| --------------- | ------------------------------------------------------------ |
+| OR REPLACE      | Replace an existing view.                                    |
+| database        | The name of the database where the view resides.             |
+| view_name       | The name of the view. For the naming conventions, see [System limits](../../System_limit.md).             |
+| column_name     | The name of the column(s) in the view. Note that the columns in the view and the columns queried in the `query_statement` must agree in number. |
+| COMMENT         | The comment on the column in the view or the view itself.    |
+| query_statement | The query statement used to create the view. It can be any query statement supported by StarRocks. |
+
+## Usage notes
+
+- Querying a view requires the SELECT privilege on the view and on its corresponding base tables.
+- If the query statement used to build a view cannot be executed due to the Schema Change on the base tables, StarRocks returns an error when you query the view.
+
+## Examples
+
+Example 1: Create a view named `example_view` in `example_db` with an aggregate query against `example_table`.
+
+```SQL
+CREATE VIEW example_db.example_view (k1, k2, k3, v1)
+AS
+SELECT c1 as k1, k2, k3, SUM(v1) FROM example_table
+WHERE k1 = 20160112 GROUP BY k1,k2,k3;
+```
+
+Example 2: Create a view named `example_view` in the database `example_db` with an aggregate query against the table `example_table`, and specify comments for the view and each column in it.
+
+```SQL
+CREATE VIEW example_db.example_view
+(
+    k1 COMMENT 'first key',
+    k2 COMMENT 'second key',
+    k3 COMMENT 'third key',
+    v1 COMMENT 'first value'
+)
+COMMENT 'my first view'
+AS
+SELECT c1 as k1, k2, k3, SUM(v1) FROM example_table
+WHERE k1 = 20160112 GROUP BY k1,k2,k3;
+```
+
+## Relevant SQLs
+
+- [SHOW CREATE VIEW](SHOW_CREATE_VIEW.md)
+- [ALTER VIEW](ALTER_VIEW.md)
+- [DROP VIEW](DROP_VIEW.md)
diff --git a/docs/en/sql-reference/sql-statements/View/DROP_VIEW.md b/docs/en/sql-reference/sql-statements/View/DROP_VIEW.md
new file mode 100644
index 00000000000000..a7adba94f93fe6
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/View/DROP_VIEW.md
@@ -0,0 +1,24 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP VIEW
+
+## Description
+
+This statement is used to drop a logical view VIEW
+
+## Syntax
+
+```sql
+DROP VIEW [IF EXISTS]
+[db_name.]view_name
+```
+
+## Examples
+
+1. If it exists, then drop the view example_view on example_db.
+
+    ```sql
+    DROP VIEW IF EXISTS example_db.example_view;
+    ```
diff --git a/docs/en/sql-reference/sql-statements/View/SHOW_CREATE_VIEW.md b/docs/en/sql-reference/sql-statements/View/SHOW_CREATE_VIEW.md
new file mode 100644
index 00000000000000..6552be268b5e25
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/View/SHOW_CREATE_VIEW.md
@@ -0,0 +1,75 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW CREATE VIEW
+
+Returns the CREATE statement that was used to create a given view. The CREATE VIEW statement helps you understand how the view is defined and provides a reference for you to modify or reconstruct the view. Note that the SHOW CREATE VIEW statement requires you to have the `SELECT` privilege on the view and the table based on which the view is created.
+
+From v2.5.4 onwards, you can use SHOW CREATE VIEW to query the statement that is used to create a **materialized view**.
+
+## Syntax
+
+```SQL
+SHOW CREATE VIEW [db_name.]view_name
+```
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                              |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| db_name       | No           | The database name. If this parameter is not specified, the CREATE VIEW statement of a given view in your current database is returned by default. |
+| view_name     | Yes          | The view name.                                               |
+
+## Output
+
+```SQL
++---------+--------------+----------------------+----------------------+
+| View    | Create View  | character_set_client | collation_connection |
++---------+--------------+----------------------+----------------------+
+```
+
+The following table describes the parameters returned by this statement.
+
+| **Parameter**        | **Description**                                              |
+| -------------------- | ------------------------------------------------------------ |
+| View                 | The view name.                                               |
+| Create View          | The CREATE VIEW statement of the view.                       |
+| character_set_client | The character set the client uses to send statements to StarRocks. |
+| collation_connection | The rules for comparing characters in a character set.       |
+
+## Examples
+
+Create a table named `example_table`.
+
+```SQL
+CREATE TABLE example_table
+(
+    k1 TINYINT,
+    k2 DECIMAL(10, 2) DEFAULT "10.5",
+    v1 CHAR(10) REPLACE,
+    v2 INT SUM
+)
+ENGINE = olap
+AGGREGATE KEY(k1, k2)
+DISTRIBUTED BY HASH(k1);
+```
+
+Create a view named `example_view` based on `example_table`.
+
+```SQL
+CREATE VIEW example_view (k1, k2, k3, v1)
+AS SELECT k1, k2, k3, v1 FROM example_table;
+```
+
+Display the CREATE VIEW statement of `example_view`.
+
+```Plain
+SHOW CREATE VIEW example_db.example_view;
+
++--------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------+----------------------+
+| View         | Create View                                                                                                                                                                                                                                                                                                                     | character_set_client | collation_connection |
++--------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------+----------------------+
+| example_view | CREATE VIEW `example_view` (k1, k2, k3, v1) COMMENT "VIEW" AS SELECT `default_cluster:db1`.`example_table`.`k1` AS `k1`, `default_cluster:db1`.`example_table`.`k2` AS `k2`, `default_cluster:db1`.`example_table`.`k3` AS `k3`, `default_cluster:db1`.`example_table`.`v1` AS `v1` FROM `default_cluster:db1`.`example_table`; | utf8                 | utf8_general_ci      |
++--------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------+----------------------+
+```
diff --git a/docs/en/sql-reference/sql-statements/View/_category_.yml b/docs/en/sql-reference/sql-statements/View/_category_.yml
new file mode 100644
index 00000000000000..5e9a6dcf2232f2
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/View/_category_.yml
@@ -0,0 +1,6 @@
+position: 90 # float position is supported
+label: 'View'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-statements/_category_.yml b/docs/en/sql-reference/sql-statements/_category_.yml
new file mode 100644
index 00000000000000..1703e6e3c2f4a7
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/_category_.yml
@@ -0,0 +1,6 @@
+position: 50 # float position is supported
+label: 'SQL statements'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/sql-statements/account-management/ALTER_USER.md b/docs/en/sql-reference/sql-statements/account-management/ALTER_USER.md
index 068994b3942a38..d5430813162901 100644
--- a/docs/en/sql-reference/sql-statements/account-management/ALTER_USER.md
+++ b/docs/en/sql-reference/sql-statements/account-management/ALTER_USER.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # ALTER USER
diff --git a/docs/en/sql-reference/sql-statements/account-management/CREATE_ROLE.md b/docs/en/sql-reference/sql-statements/account-management/CREATE_ROLE.md
index db5f6f5d52a6bb..e1076a0ca6bc85 100644
--- a/docs/en/sql-reference/sql-statements/account-management/CREATE_ROLE.md
+++ b/docs/en/sql-reference/sql-statements/account-management/CREATE_ROLE.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # CREATE ROLE
@@ -20,7 +20,7 @@ CREATE ROLE <role_name>
 
 ## Parameters
 
-`role_name`: the name of the role. For the naming conventions, see [System limits](../../../reference/System_limit.md).
+`role_name`: the name of the role. For the naming conventions, see [System limits](../../System_limit.md).
 
 Note that the created role name cannot be the same as [system-defined roles](../../../administration/user_privs/privilege_overview.md#system-defined-roles): `root`, `cluster_admin`, `db_admin`, `user_admin`, and `public`.
 
diff --git a/docs/en/sql-reference/sql-statements/account-management/CREATE_USER.md b/docs/en/sql-reference/sql-statements/account-management/CREATE_USER.md
index aaa9929ff8520e..faf6a8d0a82054 100644
--- a/docs/en/sql-reference/sql-statements/account-management/CREATE_USER.md
+++ b/docs/en/sql-reference/sql-statements/account-management/CREATE_USER.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # CREATE USER
@@ -22,7 +22,7 @@ CREATE USER [IF NOT EXISTS] <user_identity> [auth_option] [DEFAULT ROLE <role_na
 
 - `user_identity` consists of two parts, "user_name" and "host", in the format of `username@'userhost'`.  For the "host" part, you can use `%` for fuzzy match. If "host" is not specified, "%" is used by default, meaning that the user can connect to StarRocks from any host.
 
-  For the naming conventions of usernames, see [System limits](../../../reference/System_limit.md).
+  For the naming conventions of usernames, see [System limits](../../System_limit.md).
 
 - `auth_option` specifies the authentication method. Currently, three authentication methods are supported: StarRocks native password, mysql_native_password, and "authentication_ldap_simple". StarRocks native password is the same as mysql_native_password in logic but slightly differs in syntax. One user identity can use only one authentication method.
 
diff --git a/docs/en/sql-reference/sql-statements/account-management/DROP_ROLE.md b/docs/en/sql-reference/sql-statements/account-management/DROP_ROLE.md
index d1faf0b3f8180d..176b114884f286 100644
--- a/docs/en/sql-reference/sql-statements/account-management/DROP_ROLE.md
+++ b/docs/en/sql-reference/sql-statements/account-management/DROP_ROLE.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # DROP ROLE
diff --git a/docs/en/sql-reference/sql-statements/account-management/DROP_USER.md b/docs/en/sql-reference/sql-statements/account-management/DROP_USER.md
index 4362dc687c4279..a86d22fb84cae5 100644
--- a/docs/en/sql-reference/sql-statements/account-management/DROP_USER.md
+++ b/docs/en/sql-reference/sql-statements/account-management/DROP_USER.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # DROP USER
diff --git a/docs/en/sql-reference/sql-statements/account-management/EXECUTE_AS.md b/docs/en/sql-reference/sql-statements/account-management/EXECUTE_AS.md
index 90bea6428e880e..07ba284c8bd745 100644
--- a/docs/en/sql-reference/sql-statements/account-management/EXECUTE_AS.md
+++ b/docs/en/sql-reference/sql-statements/account-management/EXECUTE_AS.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # EXECUTE AS
diff --git a/docs/en/sql-reference/sql-statements/account-management/GRANT.md b/docs/en/sql-reference/sql-statements/account-management/GRANT.md
index 745fbf30868325..c702bac84f807d 100644
--- a/docs/en/sql-reference/sql-statements/account-management/GRANT.md
+++ b/docs/en/sql-reference/sql-statements/account-management/GRANT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 ---
 
diff --git a/docs/en/sql-reference/sql-statements/account-management/REVOKE.md b/docs/en/sql-reference/sql-statements/account-management/REVOKE.md
index 09fc3d82a15bc8..e093bfe0da5853 100644
--- a/docs/en/sql-reference/sql-statements/account-management/REVOKE.md
+++ b/docs/en/sql-reference/sql-statements/account-management/REVOKE.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # REVOKE
diff --git a/docs/en/sql-reference/sql-statements/account-management/SET_DEFAULT_ROLE.md b/docs/en/sql-reference/sql-statements/account-management/SET_DEFAULT_ROLE.md
index ad018b2c55ef9a..d7b6d93d31dbda 100644
--- a/docs/en/sql-reference/sql-statements/account-management/SET_DEFAULT_ROLE.md
+++ b/docs/en/sql-reference/sql-statements/account-management/SET_DEFAULT_ROLE.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # SET DEFAULT ROLE
diff --git a/docs/en/sql-reference/sql-statements/account-management/SET_PASSWORD.md b/docs/en/sql-reference/sql-statements/account-management/SET_PASSWORD.md
index 7f9ffcdf413701..25878c7d8126ce 100644
--- a/docs/en/sql-reference/sql-statements/account-management/SET_PASSWORD.md
+++ b/docs/en/sql-reference/sql-statements/account-management/SET_PASSWORD.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # SET PASSWORD
diff --git a/docs/en/sql-reference/sql-statements/account-management/SET_PROPERTY.md b/docs/en/sql-reference/sql-statements/account-management/SET_PROPERTY.md
index 14a31aea1289e2..829f6d244d4059 100644
--- a/docs/en/sql-reference/sql-statements/account-management/SET_PROPERTY.md
+++ b/docs/en/sql-reference/sql-statements/account-management/SET_PROPERTY.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # SET PROPERTY
diff --git a/docs/en/sql-reference/sql-statements/account-management/SET_ROLE.md b/docs/en/sql-reference/sql-statements/account-management/SET_ROLE.md
index 40d5e887407cfb..bb6f64dec490c6 100644
--- a/docs/en/sql-reference/sql-statements/account-management/SET_ROLE.md
+++ b/docs/en/sql-reference/sql-statements/account-management/SET_ROLE.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # SET ROLE
diff --git a/docs/en/sql-reference/sql-statements/account-management/SHOW_AUTHENTICATION.md b/docs/en/sql-reference/sql-statements/account-management/SHOW_AUTHENTICATION.md
index 4621701d8c7279..457c4f4cfebafe 100644
--- a/docs/en/sql-reference/sql-statements/account-management/SHOW_AUTHENTICATION.md
+++ b/docs/en/sql-reference/sql-statements/account-management/SHOW_AUTHENTICATION.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # SHOW AUTHENTICATION
diff --git a/docs/en/sql-reference/sql-statements/account-management/SHOW_GRANTS.md b/docs/en/sql-reference/sql-statements/account-management/SHOW_GRANTS.md
index b44282feb4a5da..4af6d7f6b841e9 100644
--- a/docs/en/sql-reference/sql-statements/account-management/SHOW_GRANTS.md
+++ b/docs/en/sql-reference/sql-statements/account-management/SHOW_GRANTS.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # SHOW GRANTS
diff --git a/docs/en/sql-reference/sql-statements/account-management/SHOW_PROPERTY.md b/docs/en/sql-reference/sql-statements/account-management/SHOW_PROPERTY.md
index 6b4bf590fec6ad..8250482e7b52b0 100644
--- a/docs/en/sql-reference/sql-statements/account-management/SHOW_PROPERTY.md
+++ b/docs/en/sql-reference/sql-statements/account-management/SHOW_PROPERTY.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # SHOW PROPERTY
diff --git a/docs/en/sql-reference/sql-statements/account-management/SHOW_ROLES.md b/docs/en/sql-reference/sql-statements/account-management/SHOW_ROLES.md
index 273769d8318e13..9288976a617cb2 100644
--- a/docs/en/sql-reference/sql-statements/account-management/SHOW_ROLES.md
+++ b/docs/en/sql-reference/sql-statements/account-management/SHOW_ROLES.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # SHOW ROLES
diff --git a/docs/en/sql-reference/sql-statements/account-management/SHOW_USERS.md b/docs/en/sql-reference/sql-statements/account-management/SHOW_USERS.md
index 310e9d2594903c..a643c2598dcdc6 100644
--- a/docs/en/sql-reference/sql-statements/account-management/SHOW_USERS.md
+++ b/docs/en/sql-reference/sql-statements/account-management/SHOW_USERS.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # SHOW USERS
diff --git a/docs/en/sql-reference/sql-statements/account-management/_category_.yml b/docs/en/sql-reference/sql-statements/account-management/_category_.yml
new file mode 100644
index 00000000000000..4b730b7567e9a1
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/account-management/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'User account management'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/sql-statements/all-commands.md b/docs/en/sql-reference/sql-statements/all-commands.md
deleted file mode 100644
index 35a07064a36e2a..00000000000000
--- a/docs/en/sql-reference/sql-statements/all-commands.md
+++ /dev/null
@@ -1,291 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# All statements
-
-This topic lists all the SQL statements supported by StarRocks and categorizes these statements by their functions.
-
-- [All statements](#all-statements)
-  - [User account management](#user-account-management)
-  - [Cluster management](#cluster-management)
-    - [Nodes and processes](#nodes-and-processes)
-    - [Resource group](#resource-group)
-    - [Storage volume](#storage-volume)
-    - [Check and repair table, tablet, and replica](#check-and-repair-table-tablet-and-replica)
-    - [Configurations and variables](#configurations-and-variables)
-    - [Files](#files)
-    - [SQL Blacklist](#sql-blacklist)
-    - [Plugin](#plugin)
-    - [Execution plan and query profile](#execution-plan-and-query-profile)
-  - [Loading, unloading](#loading-unloading)
-    - [Routine load](#routine-load)
-    - [Other load](#other-load)
-    - [Pipe](#pipe)
-    - [Unloading](#unloading)
-    - [ETL task](#etl-task)
-  - [Catalog, database, resource](#catalog-database-resource)
-    - [Catalog](#catalog)
-    - [Database](#database)
-    - [Resource](#resource)
-  - [Table, partition, bucket, index](#table-partition-bucket-index)
-  - [View, materialized view](#view-materialized-view)
-    - [View](#view)
-    - [Materialized view](#materialized-view)
-  - [Function](#function)
-  - [CBO statistics](#cbo-statistics)
-  - [Backup and restore](#backup-and-restore)
-  - [Utility commands](#utility-commands)
-
-## User account management
-
-Manages users, roles, and privileges.
-
-- [ALTER USER](./account-management/ALTER_USER.md)
-- [CREATE ROLE](./account-management/CREATE_ROLE.md)
-- [CREATE USER](./account-management/CREATE_USER.md)
-- [DROP ROLE](./account-management/DROP_ROLE.md)
-- [DROP USER](./account-management/DROP_USER.md)
-- [EXECUTE AS](./account-management/EXECUTE_AS.md)
-- [GRANT](./account-management/GRANT.md)
-- [REVOKE](./account-management/REVOKE.md)
-- [SET DEFAULT ROLE](./account-management/SET_DEFAULT_ROLE.md)
-- [SET PASSWORD](./account-management/SET_PASSWORD.md)
-- [SET PROPERTY](./account-management/SET_PROPERTY.md)
-- [SET ROLE](./account-management/SET_ROLE.md)
-- [SHOW AUTHENTICATION](./account-management/SHOW_AUTHENTICATION.md)
-- [SHOW GRANTS](./account-management/SHOW_GRANTS.md)
-- [SHOW PROPERTY](./account-management/SHOW_PROPERTY.md)
-- [SHOW ROLES](./account-management/SHOW_ROLES.md)
-- [SHOW USERS](./account-management/SHOW_USERS.md)
-
-## Cluster management
-
-Manages clusters, including FEs, BEs, compute nodes (CN), brokers, resource groups, storage volumes, tables, tablets, replicas, files, variables, plugins, and SQL blacklist.
-
-### Nodes and processes
-
-- [ALTER SYSTEM](./Administration/ALTER_SYSTEM.md)
-- [CANCEL DECOMMISSION](./Administration/CANCEL_DECOMMISSION.md)
-- [KILL](./Administration/KILL.md)
-- [SHOW BACKENDS](./Administration/SHOW_BACKENDS.md)
-- [SHOW BROKER](./Administration/SHOW_BROKER.md)
-- [SHOW COMPUTE NODES](./Administration/SHOW_COMPUTE_NODES.md)
-- [SHOW FRONTENDS](./Administration/SHOW_FRONTENDS.md)
-- [SHOW PROC](./Administration/SHOW_PROC.md)
-- [SHOW PROCESSLIST](./Administration/SHOW_PROCESSLIST.md)
-- [SHOW RUNNING QUERIES](./Administration/SHOW_RUNNING_QUERIES.md)
-- [ADD BACKEND BLACKLIST](./Administration/ADD_BACKEND_BLACKLIST.md)
-- [DELETE BACKEND BLACKLIST](./Administration/DELETE_BACKEND_BLACKLIST.md)
-- [SHOW BACKEND BLACKLIST](./Administration/SHOW_BACKEND_BLACKLIST.md)
-- [SYNC](./Administration/SYNC.md)
-
-### Resource group
-
-- [ALTER RESOURCE GROUP](./Administration/ALTER_RESOURCE_GROUP.md)
-- [CREATE RESOURCE GROUP](./Administration/CREATE_RESOURCE_GROUP.md)
-- [DROP RESOURCE GROUP](./Administration/DROP_RESOURCE_GROUP.md)
-- [SHOW RESOURCE GROUP](./Administration/SHOW_RESOURCE_GROUP.md)
-- [SHOW USAGE RESOURCE GROUPS](./Administration/SHOW_USAGE_RESOURCE_GROUPS.md)
-
-### Storage volume
-
-- [ALTER STORAGE VOLUME](./Administration/ALTER_STORAGE_VOLUME.md)
-- [CREATE STORAGE VOLUME](./Administration/CREATE_STORAGE_VOLUME.md)
-- [DESC STORAGE VOLUME](./Administration/DESC_STORAGE_VOLUME.md)
-- [DROP STORAGE VOLUME](./Administration/DROP_STORAGE_VOLUME.md)
-- [SET DEFAULT STORAGE VOLUME](./Administration/SET_DEFAULT_STORAGE_VOLUME.md)
-- [SHOW STORAGE VOLUMES](./Administration/SHOW_STORAGE_VOLUMES.md)
-
-### Check and repair table, tablet, and replica
-
-- [ADMIN CANCEL REPAIR TABLE](./Administration/ADMIN_CANCEL_REPAIR.md)
-- [ADMIN CHECK TABLET](./Administration/ADMIN_CHECK_TABLET.md)
-- [ADMIN REPAIR TABLE](./Administration/ADMIN_REPAIR.md)
-- [ADMIN SET REPLICA STATUS](./Administration/ADMIN_SET_REPLICA_STATUS.md)
-- [ADMIN SET PARTITION VERSION](./Administration/ADMIN_SET_PARTITION_VERSION.md)
-- [ADMIN SHOW REPLICA DISTRIBUTION](./Administration/ADMIN_SHOW_REPLICA_DISTRIBUTION.md)
-- [ADMIN SHOW REPLICA STATUS](./Administration/ADMIN_SHOW_REPLICA_STATUS.md)
-- [SHOW TABLE STATUS](./Administration/SHOW_TABLE_STATUS.md)
-
-### Configurations and variables
-
-- [ADMIN SET CONFIG](./Administration/ADMIN_SET_CONFIG.md)
-- [ADMIN SHOW CONFIG](./Administration/ADMIN_SHOW_CONFIG.md)
-- [SET (variable)](./Administration/SET.md)
-- [SHOW VARIABLES](./Administration/SHOW_VARIABLES.md)
-
-### Files
-
-- [CREATE FILE](./Administration/CREATE_FILE.md)
-- [DROP FILE](./Administration/DROP_FILE.md)
-- [SHOW FILE](./Administration/SHOW_FILE.md)
-
-### SQL Blacklist
-
-- [ADD SQLBLACKLIST](./Administration/ADD_SQLBLACKLIST.md)
-- [SHOW SQLBLACKLIST](./Administration/SHOW_SQLBLACKLIST.md)
-- [DELETE SQLBLACKLIST](./Administration/DELETE_SQLBLACKLIST.md)
-
-### Plugin
-
-- [INSTALL PLUGIN](./Administration/INSTALL_PLUGIN.md)
-- [SHOW PLUGINS](./Administration/SHOW_PLUGINS.md)
-- [UNINSTALL PLUGIN](./Administration/UNINSTALL_PLUGIN.md)
-
-### Execution plan and query profile
-
-- [ANALYZE PROFILE](./Administration/ANALYZE_PROFILE.md)
-- [EXPLAIN](./Administration/EXPLAIN.md)
-- [EXPLAIN ANALYZE](./Administration/EXPLAIN_ANALYZE.md)
-- [SHOW PROFILELIST](./Administration/SHOW_PROFILELIST.md)
-
-## Loading, unloading
-
-### Routine load
-
-- [ALTER ROUTINE LOAD](./data-manipulation/ALTER_ROUTINE_LOAD.md)
-- [CREATE ROUTINE LOAD](./data-manipulation/CREATE_ROUTINE_LOAD.md)
-- [PAUSE ROUTINE LOAD](./data-manipulation/PAUSE_ROUTINE_LOAD.md)
-- [RESUME ROUTINE LOAD](./data-manipulation/RESUME_ROUTINE_LOAD.md)
-- [SHOW ROUTINE LOAD](./data-manipulation/SHOW_ROUTINE_LOAD.md)
-- [SHOW ROUTINE LOAD TASK](./data-manipulation/SHOW_ROUTINE_LOAD_TASK.md)
-- [STOP ROUTINE LOAD](./data-manipulation/STOP_ROUTINE_LOAD.md)
-
-### Other load
-
-- [ALTER LOAD](./data-manipulation/ALTER_LOAD.md)
-- [BROKER LOAD](./data-manipulation/BROKER_LOAD.md)
-- [CANCEL LOAD](./data-manipulation/CANCEL_LOAD.md)
-- [INSERT](./data-manipulation/INSERT.md)
-- [SHOW LOAD](./data-manipulation/SHOW_LOAD.md)
-- [SHOW TRANSACTION](./data-manipulation/SHOW_TRANSACTION.md)
-- [SPARK LOAD](./data-manipulation/SPARK_LOAD.md)
-- [STREAM LOAD](./data-manipulation/STREAM_LOAD.md)
-
-### Pipe
-
-- [ALTER PIPE](./data-manipulation/ALTER_PIPE.md)
-- [CREATE PIPE](./data-manipulation/CREATE_PIPE.md)
-- [DROP PIPE](./data-manipulation/DROP_PIPE.md)
-- [RETRY FILE](./data-manipulation/RETRY_FILE.md)
-- [SHOW PIPES](./data-manipulation/SHOW_PIPES.md)
-- [SUSPEND or RESUME PIPE](./data-manipulation/SUSPEND_or_RESUME_PIPE.md)
-
-### Unloading
-
-- [CANCEL EXPORT](./data-manipulation/CANCEL_EXPORT.md)
-- [EXPORT](./data-manipulation/EXPORT.md)
-- [SHOW EXPORT](./data-manipulation/SHOW_EXPORT.md)
-
-### ETL task
-
-- [DROP TASK](./data-manipulation/DROP_TASK.md)
-- [SUBMIT TASK](./data-manipulation/SUBMIT_TASK.md)
-
-## Catalog, database, resource
-
-### Catalog
-
-- [CREATE EXTERNAL CATALOG](./data-definition/CREATE_EXTERNAL_CATALOG.md)
-- [DROP CATALOG](./data-definition/DROP_CATALOG.md)
-- [SET CATALOG](./data-definition/SET_CATALOG.md)
-- [SHOW CATALOGS](./data-manipulation/SHOW_CATALOGS.md)
-- [SHOW CREATE CATALOG](./data-manipulation/SHOW_CREATE_CATALOG.md)
-
-### Database
-
-- [ALTER DATABASE](./data-definition/ALTER_DATABASE.md)
-- [CREATE DATABASE](./data-definition/CREATE_DATABASE.md)
-- [DROP DATABASE](./data-definition/DROP_DATABASE.md)
-- [SHOW CREATE DATABASE](./data-manipulation/SHOW_CREATE_DATABASE.md)
-- [SHOW DATA](./data-manipulation/SHOW_DATA.md)
-- [SHOW DATABASES](./data-manipulation/SHOW_DATABASES.md)
-
-### Resource
-
-- [ALTER RESOURCE](./data-definition/ALTER_RESOURCE.md)
-- [CREATE RESOURCE](./data-definition/CREATE_RESOURCE.md)
-- [DROP RESOURCE](./data-definition/DROP_RESOURCE.md)
-- [SHOW RESOURCES](./data-definition/SHOW_RESOURCES.md)
-
-## Table, partition, bucket, index
-
-- [ALTER TABLE](./data-definition/ALTER_TABLE.md)
-- [CANCEL ALTER TABLE](./data-definition/CANCEL_ALTER_TABLE.md)
-- [CREATE INDEX](./data-definition/CREATE_INDEX.md)
-- [CREATE TABLE](./data-definition/CREATE_TABLE.md)
-- [CREATE TABLE AS SELECT](./data-definition/CREATE_TABLE_AS_SELECT.md)
-- [CREATE TABLE LIKE](./data-definition/CREATE_TABLE_LIKE.md)
-- [DELETE](./data-manipulation/DELETE.md)
-- [DROP INDEX](./data-definition/DROP_INDEX.md)
-- [DROP TABLE](./data-definition/DROP_TABLE.md)
-- [REFRESH EXTERNAL TABLE](./data-definition/REFRESH_EXTERNAL_TABLE.md)
-- [SELECT](./data-manipulation/SELECT.md)
-- [SHOW ALTER TABLE](./data-manipulation/SHOW_ALTER.md)
-- [SHOW CREATE TABLE](./data-manipulation/SHOW_CREATE_TABLE.md)
-- [SHOW DELETE](./data-manipulation/SHOW_DELETE.md)
-- [SHOW DYNAMIC PARTITION TABLES](./data-manipulation/SHOW_DYNAMIC_PARTITION_TABLES.md)
-- [SHOW FULL COLUMNS](./data-manipulation/SHOW_FULL_COLUMNS.md)
-- [SHOW INDEX](./data-manipulation/SHOW_INDEX.md)
-- [SHOW PARTITIONS](./data-manipulation/SHOW_PARTITIONS.md)
-- [SHOW TABLES](./data-manipulation/SHOW_TABLES.md)
-- [SHOW TABLET](./data-manipulation/SHOW_TABLET.md)
-- [TRUNCATE TABLE](./data-definition/TRUNCATE_TABLE.md)
-- [UPDATE](./data-manipulation/UPDATE.md)
-
-## View, materialized view
-
-### View
-
-- [ALTER VIEW](./data-definition/ALTER_VIEW.md)
-- [CREATE VIEW](./data-definition/CREATE_VIEW.md)
-- [DROP VIEW](./data-definition/DROP_VIEW.md)
-- [SHOW CREATE VIEW](./data-manipulation/SHOW_CREATE_VIEW.md)
-
-### Materialized view
-
-- [ALTER MATERIALIZED VIEW](./data-definition/ALTER_MATERIALIZED_VIEW.md)
-- [CANCEL REFRESH MATERIALIZED VIEW](./data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW.md)
-- [CREATE MATERIALIZED VIEW](./data-definition/CREATE_MATERIALIZED_VIEW.md)
-- [DROP MATERIALIZED VIEW](./data-definition/DROP_MATERIALIZED_VIEW.md)
-- [REFRESH MATERIALIZED VIEW](./data-manipulation/REFRESH_MATERIALIZED_VIEW.md)
-- [SHOW ALTER MATERIALIZED VIEW](./data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW.md)
-- [SHOW CREATE MATERIALIZED VIEW](./data-manipulation/SHOW_CREATE_MATERIALIZED_VIEW.md)
-- [SHOW MATERIALIZED VIEWS](./data-manipulation/SHOW_MATERIALIZED_VIEW.md)
-
-## Function
-
-- [CREATE FUNCTION](./data-definition/CREATE_FUNCTION.md)
-- [DROP FUNCTION](./data-definition/DROP_FUNCTION.md)
-- [SHOW FUNCTIONS](./data-definition/SHOW_FUNCTIONS.md)
-
-## CBO statistics
-
-- [ANALYZE TABLE](./data-definition/ANALYZE_TABLE.md)
-- [CREATE ANALYZE](./data-definition/CREATE_ANALYZE.md)
-- [DROP ANALYZE](./data-definition/DROP_ANALYZE.md)
-- [DROP STATS](./data-definition/DROP_STATS.md)
-- [KILL ANALYZE](./data-definition/KILL_ANALYZE.md)
-- [SHOW ANALYZE JOB](./data-definition/SHOW_ANALYZE_JOB.md)
-- [SHOW ANALYZE STATUS](./data-definition/SHOW_ANALYZE_STATUS.md)
-- [SHOW META](./data-definition/SHOW_META.md)
-
-## Backup and restore
-
-- [BACKUP](./data-definition/backup_restore/BACKUP.md)
-- [CANCEL BACKUP](./data-definition/backup_restore/CANCEL_BACKUP.md)
-- [CANCEL RESTORE](./data-definition/backup_restore/CANCEL_RESTORE.md)
-- [CREATE REPOSITORY](./data-definition/backup_restore/CREATE_REPOSITORY.md)
-- [DROP REPOSITORY](./data-definition/backup_restore/DROP_REPOSITORY.md)
-- [RECOVER](./data-definition/backup_restore/RECOVER.md)
-- [RESTORE](./data-definition/backup_restore/RESTORE.md)
-- [SHOW BACKUP](./data-manipulation/backup_restore/SHOW_BACKUP.md)
-- [SHOW REPOSITORIES](./data-manipulation/backup_restore/SHOW_REPOSITORIES.md)
-- [SHOW RESTORE](./data-manipulation/backup_restore/SHOW_RESTORE.md)
-- [SHOW SNAPSHOT](./data-manipulation/backup_restore/SHOW_SNAPSHOT.md)
-
-## Utility commands
-
-- [DESC](./Utility/DESCRIBE.md)
-- [USE](./data-definition/USE.md)
diff --git a/docs/en/sql-reference/sql-statements/auto_increment.md b/docs/en/sql-reference/sql-statements/auto_increment.md
deleted file mode 100644
index 079d1e4b355eba..00000000000000
--- a/docs/en/sql-reference/sql-statements/auto_increment.md
+++ /dev/null
@@ -1,399 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# AUTO_INCREMENT
-
-Since version 3.0, StarRocks supports the `AUTO_INCREMENT` column attribute, which can simplify data management. This topic introduces the application scenarios, usage and features of the `AUTO_INCREMENT` column attribute.
-
-## Introduction
-
-When a new data row is loaded into a table and values are not specified for the `AUTO_INCREMENT` column, StarRocks automatically assigns an integer value for the row's `AUTO_INCREMENT` column as its unique ID across the table. The subsequent values for the `AUTO_INCREMENT` column automatically increase at a specific step starting from the ID of the row. An `AUTO_INCREMENT` column can be used to simplify data management and speed up some queries. Here are some application scenarios of an `AUTO_INCREMENT` column:
-
-- Serve as primary keys: An `AUTO_INCREMENT` column can be used as the primary key to ensure that each row has a unique ID and make it easy to query and manage data.
-- Join tables: When multiple tables are joined, an `AUTO_INCREMENT` column can be used as the Join Key, which can expedite queries compared to using a column whose data type is STRING, for example, UUID.
-- Count the number of distinct values in a high-cardinality column: An `AUTO_INCREMENT` column can be used to represent the unique value column in a dictionary. Compared to directly counting distinct STRING values, counting distinct integer values of the `AUTO_INCREMENT` column can sometimes improve the query speed by several times or even tens of times.
-
-You need to specify an `AUTO_INCREMENT` column in the CREATE TABLE statement. The data types of an `AUTO_INCREMENT` column must be BIGINT. The value for an AUTO_INCREMENT column can be [implicitly assigned or explicitly specified](#assign-values-for-auto_increment-column). It starts from 1, and increments by 1 for each new row.
-
-## Basic operations
-
-### Specify `AUTO_INCREMENT` column at table creation
-
-Create a table named `test_tbl1` with two columns, `id` and `number`. Specify the column `number` as the `AUTO_INCREMENT` column.
-
-```SQL
-CREATE TABLE test_tbl1
-(
-    id BIGINT NOT NULL, 
-    number BIGINT NOT NULL AUTO_INCREMENT
-) 
-PRIMARY KEY (id) 
-DISTRIBUTED BY HASH(id)
-PROPERTIES("replicated_storage" = "true");
-```
-
-### Assign values for `AUTO_INCREMENT` column
-
-#### Assign values implicitly
-
-When you load data into a StarRocks table, you do not need to specify the values for the `AUTO_INCREMENT` column. StarRocks automatically assigns unique integer values for that column and inserts them into the table.
-
-```SQL
-INSERT INTO test_tbl1 (id) VALUES (1);
-INSERT INTO test_tbl1 (id) VALUES (2);
-INSERT INTO test_tbl1 (id) VALUES (3),(4),(5);
-```
-
-View data in the table.
-
-```SQL
-mysql > SELECT * FROM test_tbl1 ORDER BY id;
-+------+--------+
-| id   | number |
-+------+--------+
-|    1 |      1 |
-|    2 |      2 |
-|    3 |      3 |
-|    4 |      4 |
-|    5 |      5 |
-+------+--------+
-5 rows in set (0.02 sec)
-```
-
-When you load data into a StarRocks table, you can also specify the values as `DEFAULT` for the `AUTO_INCREMENT` column. StarRocks automatically assigns unique integer values for that column and inserts them into the table.
-
-```SQL
-INSERT INTO test_tbl1 (id, number) VALUES (6, DEFAULT);
-```
-
-View data in the table.
-
-```SQL
-mysql > SELECT * FROM test_tbl1 ORDER BY id;
-+------+--------+
-| id   | number |
-+------+--------+
-|    1 |      1 |
-|    2 |      2 |
-|    3 |      3 |
-|    4 |      4 |
-|    5 |      5 |
-|    6 |      6 |
-+------+--------+
-6 rows in set (0.02 sec)
-```
-
-In actual usage, the following result may be returned when you view the data in the table. This is because StarRocks cannot guarantee that the values for the `AUTO_INCREMENT` column are strictly monotonic. But StarRocks can guarantee that the values roughly increase in chronological order. For more information, see [Monotonicity](#monotonicity).
-
-```SQL
-mysql > SELECT * FROM test_tbl1 ORDER BY id;
-+------+--------+
-| id   | number |
-+------+--------+
-|    1 |      1 |
-|    2 | 100001 |
-|    3 | 200001 |
-|    4 | 200002 |
-|    5 | 200003 |
-|    6 | 200004 |
-+------+--------+
-6 rows in set (0.01 sec)
-```
-
-#### Specify values explicitly
-
-You can also explicitly specify the values for the `AUTO_INCREMENT` column and insert them into the table.
-
-```SQL
-INSERT INTO test_tbl1 (id, number) VALUES (7, 100);
-
--- view data in the table.
-
-mysql > SELECT * FROM test_tbl1 ORDER BY id;
-+------+--------+
-| id   | number |
-+------+--------+
-|    1 |      1 |
-|    2 | 100001 |
-|    3 | 200001 |
-|    4 | 200002 |
-|    5 | 200003 |
-|    6 | 200004 |
-|    7 |    100 |
-+------+--------+
-7 rows in set (0.01 sec)
-```
-
-Moreover, explicitly specifying values does not affect the subsequent values generated by StarRocks for newly inserted data rows.
-
-```SQL
-INSERT INTO test_tbl1 (id) VALUES (8);
-
--- view data in the table.
-
-mysql > SELECT * FROM test_tbl1 ORDER BY id;
-+------+--------+
-| id   | number |
-+------+--------+
-|    1 |      1 |
-|    2 | 100001 |
-|    3 | 200001 |
-|    4 | 200002 |
-|    5 | 200003 |
-|    6 | 200004 |
-|    7 |    100 |
-|    8 |      2 |
-+------+--------+
-8 rows in set (0.01 sec)
-```
-
-**NOTICE**
-
-We recommend that you do not use implicitly assigned values and explicitly specified values for the `AUTO_INCREMENT` column at the same time. Because the specified values may be the same as the values generated by StarRocks, breaking the [global uniqueness of auto-incremented IDs](#uniqueness).
-
-## Basic features
-
-### Uniqueness
-
-In general, StarRocks guarantees that the values for a `AUTO_INCREMENT` column are globally unique across a table. We recommend that you do not implicitly assign and explicitly specify the values for the `AUTO_INCREMENT` column at the same time. If you do so, it may break the global uniqueness of auto-incremented IDs. Here is a simple example: Create a table named `test_tbl2` with two columns, `id` and `number`. Specify the column `number` as the `AUTO_INCREMENT` column.
-
-```SQL
-CREATE TABLE test_tbl2
-(
-    id BIGINT NOT NULL,
-    number BIGINT NOT NULL AUTO_INCREMENT
- ) 
-PRIMARY KEY (id) 
-DISTRIBUTED BY HASH(id)
-PROPERTIES("replicated_storage" = "true");
-```
-
-Implicitly assign and explicitly specify the values for the `AUTO_INCREMENT` column `number` in the table `test_tbl2`.
-
-```SQL
-INSERT INTO test_tbl2 (id, number) VALUES (1, DEFAULT);
-INSERT INTO test_tbl2 (id, number) VALUES (2, 2);
-INSERT INTO test_tbl2 (id) VALUES (3);
-```
-
-Query the table `test_tbl2`.
-
-```SQL
-mysql > SELECT * FROM test_tbl2 ORDER BY id;
-+------+--------+
-| id   | number |
-+------+--------+
-|    1 |      1 |
-|    2 |      2 |
-|    3 | 100001 |
-+------+--------+
-3 rows in set (0.08 sec)
-```
-
-### Monotonicity
-
-In order to improve the performance of allocating auto-incremented IDs, BEs cache some auto-incremented IDs locally. In this situation, StarRocks cannot guarantee that the values for the `AUTO_INCREMENT` column are strictly monotonic. It can only be ensured that the values roughly increase in chronological order.
-
-> **NOTE**
->
-> The number of auto-incremented IDs cached by the BEs is determined by the FE dynamic parameter `auto_increment_cache_size`, which defaults to `100,000`. You can modify the value by using `ADMIN SET FRONTEND CONFIG ("auto_increment_cache_size" = "xxx");`
-
-For example, a StarRocks cluster has one FE node and two BE nodes. Create a table named `test_tbl3` and insert five rows of data as follows:
-
-```SQL
-CREATE TABLE test_tbl3
-(
-    id BIGINT NOT NULL,
-    number BIGINT NOT NULL AUTO_INCREMENT
-) 
-PRIMARY KEY (id)
-DISTRIBUTED BY HASH(id)
-PROPERTIES("replicated_storage" = "true");
-
-INSERT INTO test_tbl3 VALUES (1, DEFAULT);
-INSERT INTO test_tbl3 VALUES (2, DEFAULT);
-INSERT INTO test_tbl3 VALUES (3, DEFAULT);
-INSERT INTO test_tbl3 VALUES (4, DEFAULT);
-INSERT INTO test_tbl3 VALUES (5, DEFAULT);
-```
-
-The auto-incremented IDs in the table `test_tbl3` do not monotonically increase, because the two BE nodes cache auto-incremented IDs, [1, 100000] and [100001, 200000], respectively. When data is loaded by using multiple INSERT statements, the data is sent to different BE nodes which allocate auto-incremented IDs independently. Therefore, it cannot be guaranteed that auto-incremented IDs are strictly monotonic.
-
-```SQL
-mysql > SELECT * FROM test_tbl3 ORDER BY id;
-+------+--------+
-| id   | number |
-+------+--------+
-|    1 |      1 |
-|    2 | 100001 |
-|    3 | 200001 |
-|    4 |      2 |
-|    5 | 100002 |
-+------+--------+
-5 rows in set (0.07 sec)
-```
-
-## Partial updates and `AUTO_INCREMENT` column
-
-This section explains how to update only a few specified columns in a table that contains an `AUTO_INCREMENT` column.
-
-> **NOTE**
->
-> Currently, only Primary Key tables support partial updates.
-
-### `AUTO_INCREMENT` column is primary key
-
-You need to specify the primary key during partial updates. Therefore, if the `AUTO_INCREMENT` column is the primary key or part of the primary key, the user behavior for partial updates is exactly the same as when the `AUTO_INCREMENT` column is not defined.
-
-1. Create a table `test_tbl4` in the database `example_db` and insert one data row.
-
-    ```SQL
-    -- Create a table.
-    CREATE TABLE test_tbl4
-    (
-        id BIGINT AUTO_INCREMENT,
-        name BIGINT NOT NULL,
-        job1 BIGINT NOT NULL,
-        job2 BIGINT NOT NULL
-    ) 
-    PRIMARY KEY (id, name)
-    DISTRIBUTED BY HASH(id)
-    PROPERTIES("replicated_storage" = "true");
-
-    -- Prepared data.
-    mysql > INSERT INTO test_tbl4 (id, name, job1, job2) VALUES (0, 0, 1, 1);
-    Query OK, 1 row affected (0.04 sec)
-    {'label':'insert_6af28e77-7d2b-11ed-af6e-02424283676b', 'status':'VISIBLE', 'txnId':'152'}
-
-    -- Query the table.
-    mysql > SELECT * FROM test_tbl4 ORDER BY id;
-    +------+------+------+------+
-    | id   | name | job1 | job2 |
-    +------+------+------+------+
-    |    0 |    0 |    1 |    1 |
-    +------+------+------+------+
-    1 row in set (0.01 sec)
-    ```
-
-2. Prepare the CSV file **my_data4.csv** to update table `test_tbl4`. The CSV file includes values for the `AUTO_INCREMENT` column and does not include values for the column `job1`. The primary key of the first row already exists in table `test_tbl4`, while the primary key of the second row does not exist in the table.
-
-    ```Plaintext
-    0,0,99
-    1,1,99
-    ```
-
-3. Run a [Stream Load](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md) job and use the CSV file to update table `test_tbl4`.
-
-    ```Bash
-    curl --location-trusted -u <username>:<password> -H "label:1" \
-        -H "column_separator:," \
-        -H "partial_update:true" \
-        -H "columns:id,name,job2" \
-        -T my_data4.csv -XPUT \
-        http://<fe_host>:<fe_http_port>/api/example_db/test_tbl4/_stream_load
-    ```
-
-4. Query the updated table. The first row of data already exists in table `test_tbl4`, and the value for the column `job1` remains unchanged. The second row of data is newly inserted, and because the default value for the column `job1` is not specified, the partial update framework directly sets the value for this column to `0`.
-
-    ```SQL
-    mysql > SELECT * FROM test_tbl4 ORDER BY id;
-    +------+------+------+------+
-    | id   | name | job1 | job2 |
-    +------+------+------+------+
-    |    0 |    0 |    1 |   99 |
-    |    1 |    1 |    0 |   99 |
-    +------+------+------+------+
-    2 rows in set (0.01 sec)
-    ```
-
-### `AUTO_INCREMENT` column is not primary key
-
-If the `AUTO_INCREMENT` column is not a primary key or a part of the primary key, and auto-incremented IDs are not provided in a Stream Load job, the following situations occur:
-
-- If the row already exists in the table, StarRocks does not update the auto-incremented ID.
-- If the row is newly loaded into the table, StarRocks generates a new auto-incremented ID.
-
-This feature can be used to build a dictionary table for quickly computing distinct STRING values.
-
-1. In the database `example_db`, create a table `test_tbl5` and specify the column `job1` as the `AUTO_INCREMENT` column and insert a data row into the table `test_tbl5`.
-
-    ```SQL
-    -- Create a table.
-    CREATE TABLE test_tbl5
-    (
-        id BIGINT NOT NULL,
-        name BIGINT NOT NULL,
-        job1 BIGINT NOT NULL AUTO_INCREMENT,
-        job2 BIGINT NOT NULL
-    )
-    PRIMARY KEY (id, name)
-    DISTRIBUTED BY HASH(id)
-    PROPERTIES("replicated_storage" = "true");
-
-    -- Prepare data.
-    mysql > INSERT INTO test_tbl5 VALUES (0, 0, -1, -1);
-    Query OK, 1 row affected (0.04 sec)
-    {'label':'insert_458d9487-80f6-11ed-ae56-aa528ccd0ebf', 'status':'VISIBLE', 'txnId':'94'}
-
-    -- Query the table.
-    mysql > SELECT * FROM test_tbl5 ORDER BY id;
-    +------+------+------+------+
-    | id   | name | job1 | job2 |
-    +------+------+------+------+
-    |    0 |    0 |   -1 |   -1 |
-    +------+------+------+------+
-    1 row in set (0.01 sec)
-    ```
-
-2. Prepare a CSV file **my_data5.csv** to update table `test_tbl5`. The CSV file does not contain values for the `AUTO_INCREMENT` column `job1`. The primary key of the first row already exists in the table while the primary keys of the second and third rows do not.
-
-    ```Plaintext
-    0,0,99
-    1,1,99
-    2,2,99
-    ```
-
-3. Run a [Stream Load](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md) job to load data from the CSV file into table `test_tbl5`.
-
-    ```Bash
-    curl --location-trusted -u <username>:<password> -H "label:2" \
-        -H "column_separator:," \
-        -H "partial_update:true" \
-        -H "columns: id,name,job2" \
-        -T my_data5.csv -XPUT \
-        http://<fe_host>:<fe_http_port>/api/example_db/test_tbl5/_stream_load
-    ```
-
-4. Query the updated table. The first row of data already exists in table `test_tbl5`, so the `AUTO_INCREMENT` column `job1` retains its original value. The second and third rows of data are newly inserted, so StarRocks generate new values for the `AUTO_INCREMENT` column `job1`.
-
-    ```SQL
-    mysql > SELECT * FROM test_tbl5 ORDER BY id;
-    +------+------+--------+------+
-    | id   | name | job1   | job2 |
-    +------+------+--------+------+
-    |    0 |    0 |     -1 |   99 |
-    |    1 |    1 |      1 |   99 |
-    |    2 |    2 | 100001 |   99 |
-    +------+------+--------+------+
-    3 rows in set (0.01 sec)
-    ```
-
-## Limits
-
-- When a table with an `AUTO_INCREMENT` column is created, `'replicated_storage' = 'true'` must be set to ensure that all replicas have the same auto-incremented IDs.
-- Each table can have only one `AUTO_INCREMENT` column.
-- The data type of the `AUTO_INCREMENT` column must be BIGINT.
-- The `AUTO_INCREMENT` column must be `NOT NULL` and does not have a default value.
-- You can delete data from a Primary Key table with an `AUTO_INCREMENT` column. However, if the `AUTO_INCREMENT` column is not the primary key or part of the primary key, you need to note the following limits when you delete data in the following scenarios:
-
-  - During the DELETE operation, there is also a load job for partial updates, which only contains UPSERT operations. If both the UPSERT and DELETE operations hit the same data row and the UPSERT operation is executed after the DELETE operation, the UPSERT operation may not take effect.
-  - There is a load job for partial updates, which includes multiple UPSERT and DELETE operations on the same data row. If a certain UPSERT operation is executed after the DELETE operation, the UPSERT operation may not take effect.
-
-- Adding the `AUTO_INCREMENT` attribute by using ALTER TABLE is not supported.
-- Since version 3.1, StarRocks's shared-data mode supports the `AUTO_INCREMENT` attribute.
-- StarRocks does not support specifying the starting value and step size for the `AUTO_INCREMENT` column.
-
-## Keywords
-
-AUTO_INCREMENT, AUTO INCREMENT
diff --git a/docs/en/sql-reference/sql-statements/backup_restore/BACKUP.md b/docs/en/sql-reference/sql-statements/backup_restore/BACKUP.md
new file mode 100644
index 00000000000000..ae225900914e93
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/backup_restore/BACKUP.md
@@ -0,0 +1,83 @@
+---
+displayed_sidebar: docs
+---
+
+# BACKUP
+
+## Description
+
+Backs up data in a specified database, table, or partition. Currently, StarRocks only supports backing up data in OLAP tables.
+
+BACKUP is an asynchronous operation. You can check the status of a BACKUP job status using [SHOW BACKUP](./SHOW_BACKUP.md), or cancel a BACKUP job using [CANCEL BACKUP](./CANCEL_BACKUP.md). You can view the snapshot information using [SHOW SNAPSHOT](./SHOW_SNAPSHOT.md).
+
+> **CAUTION**
+>
+> - Only users with the ADMIN privilege can back up data.
+> - In each database, only one running BACKUP or RESTORE job is allowed each time. Otherwise, StarRocks returns an error.
+> - StarRocks does not support specifying data compression algorithm for data backup.
+
+## Syntax
+
+```SQL
+BACKUP SNAPSHOT <db_name>.<snapshot_name>
+TO <repository_name>
+[ ON ( <table_name> [ PARTITION ( <partition_name> [, ...] ) ]
+       [, ...] ) ]
+[ PROPERTIES ("key"="value" [, ...] ) ]
+```
+
+## Parameters
+
+| **Parameter**   | **Description**                                              |
+| --------------- | ------------------------------------------------------------ |
+| db_name         | Name of the database that stores the data to be backed up.   |
+| snapshot_name   | Specify a name for the data snapshot. Globally unique.       |
+| repository_name | Repository name. You can create a repository using [CREATE REPOSITORY](./CREATE_REPOSITORY.md). |
+| ON              | Name of the tables to be backed up. The whole database is backed up if this parameter is not specified. |
+| PARTITION       | Name of the partitions to be backed up. The whole table is backed up if this parameter is not specified. |
+| PROPERTIES      | Properties of the data snapshot. Valid keys:`type`: Backup type. Currently, only full backup `FULL` is supported. Default: `FULL`.`timeout`: Task timeout. Unit: second. Default: `86400`. |
+
+## Examples
+
+Example 1: Backs up the database `example_db` to the repository `example_repo`.
+
+```SQL
+BACKUP SNAPSHOT example_db.snapshot_label1
+TO example_repo
+PROPERTIES ("type" = "full");
+```
+
+Example 2: Backs up the table `example_tbl` in `example_db` to `example_repo`.
+
+```SQL
+BACKUP SNAPSHOT example_db.snapshot_label2
+TO example_repo
+ON (example_tbl);
+```
+
+Example 2: Backs up the partitions `p1` and `p2` of `example_tbl` and the table `example_tbl2` in `example_db` to `example_repo`.
+
+```SQL
+BACKUP SNAPSHOT example_db.snapshot_label3
+TO example_repo
+ON(
+    example_tbl PARTITION (p1, p2),
+    example_tbl2
+);
+```
+
+## Usage notes
+
+- Performing backup and restore operations on global, database, table, and partition levels requires different privileges.
+- In each database, only one running BACKUP or RESTORE job is allowed each time. Otherwise, StarRocks returns an error.
+- Because BACKUP and RESTORE jobs occupy many resources of your StarRocks cluster, you can back up and restore your data while your StarRocks cluster is not heavily loaded.
+- StarRocks does not support specifying data compression algorithms for data backup.
+- Because data is backed up as snapshots, the data loaded upon snapshot generation is not included in the snapshot. Therefore, if you load data into the old cluster after the snapshot is generated and before the RESTORE job is completed, you also need to load the data into the cluster that data is restored into. It is recommended that you load data into both clusters in parallel for a period of time after the data migration is complete, and then migrate your application to the new cluster after verifying the correctness of the data and services.
+- Before the RESTORE job is completed, you cannot operate the table to be restored.
+- Primary Key tables cannot be restored to a StarRocks cluster earlier than v2.5.
+- You do not need to create the table to be restored in the new cluster before restoring it. The RESTORE job automatically creates it.
+- If there is an existing table that has a duplicated name with the table to be restored, StarRocks first checks whether or not the schema of the existing table matches that of the table to be restored. If the schemas match, StarRocks overwrites the existing table with the data in the snapshot. If the schema does not match, the RESTORE job fails. You can either rename the table to be restored using the keyword `AS`, or delete the existing table before restoring data.
+- If the RESTORE job overwrites an existing database, table, or partition, the overwritten data cannot be restored after the job enters the COMMIT phase. If the RESTORE job fails or is canceled at this point, the data may be corrupted and inaccessible. In this case, you can only perform the RESTORE operation again and wait for the job to complete. Therefore, we recommend that you do not restore data by overwriting unless you are sure that the current data is no longer used. The overwrite operation first checks metadata consistency between the snapshot and the existing database, table, or partition. If an inconsistency is detected, the RESTORE operation cannot be performed.
+- Currently, StarRocks does not support backing up and restoring logical views.
+- Currently, StarRocks does not support backing up and restoring the configuration data related to user accounts, privileges, and resource groups.
+- Currently, StarRocks does not support backing up and restoring the Colocate Join relationship among tables.
diff --git a/docs/en/sql-reference/sql-statements/backup_restore/CANCEL_BACKUP.md b/docs/en/sql-reference/sql-statements/backup_restore/CANCEL_BACKUP.md
new file mode 100644
index 00000000000000..53608afa6d2226
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/backup_restore/CANCEL_BACKUP.md
@@ -0,0 +1,29 @@
+---
+displayed_sidebar: docs
+---
+
+# CANCEL BACKUP
+
+## Description
+
+Cancels an ongoing BACKUP task in a specified database.
+
+## Syntax
+
+```SQL
+CANCEL BACKUP FROM <db_name>
+```
+
+## Parameters
+
+| **Parameter** | **Description**                                       |
+| ------------- | ----------------------------------------------------- |
+| db_name       | Name of the database that the BACKUP task belongs to. |
+
+## Examples
+
+Example 1: Cancels the BACKUP task under the database `example_db`.
+
+```SQL
+CANCEL BACKUP FROM example_db;
+```
diff --git a/docs/en/sql-reference/sql-statements/backup_restore/CANCEL_RESTORE.md b/docs/en/sql-reference/sql-statements/backup_restore/CANCEL_RESTORE.md
new file mode 100644
index 00000000000000..1e45e4f6fa68c0
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/backup_restore/CANCEL_RESTORE.md
@@ -0,0 +1,33 @@
+---
+displayed_sidebar: docs
+---
+
+# CANCEL RESTORE
+
+## Description
+
+Cancels an ongoing RESTORE task in a specified database.
+
+> **CAUTION**
+>
+> If a RESTORE task is canceled during the COMMIT phase, the restored data will be corrupted and inaccessible. In this case, you can only perform the RESTORE operation again and wait for the job to complete.
+
+## Syntax
+
+```SQL
+CANCEL RESTORE FROM <db_name>
+```
+
+## Parameters
+
+| **Parameter** | **Description**                                        |
+| ------------- | ------------------------------------------------------ |
+| db_name       | Name of the database that the RESTORE task belongs to. |
+
+## Examples
+
+Example 1: Cancels the RESTORE task under the database `example_db`.
+
+```SQL
+CANCEL RESTORE FROM example_db;
+```
diff --git a/docs/en/sql-reference/sql-statements/backup_restore/CREATE_REPOSITORY.md b/docs/en/sql-reference/sql-statements/backup_restore/CREATE_REPOSITORY.md
new file mode 100644
index 00000000000000..3fc4854bbee613
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/backup_restore/CREATE_REPOSITORY.md
@@ -0,0 +1,107 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE REPOSITORY
+
+## Description
+
+Creates a repository in a remote storage system that is used to store data snapshots for backing up and restoring data.
+
+> **CAUTION**
+>
+> Only users with the ADMIN privilege can create a repository.
+
+For detailed instructions on deleting a repository, see [DROP REPOSITORY](./DROP_REPOSITORY.md).
+
+## Syntax
+
+```SQL
+CREATE [READ ONLY] REPOSITORY <repository_name>
+WITH BROKER
+ON LOCATION "<repository_location>"
+PROPERTIES ("key"="value", ...)
+```
+
+## Parameters
+
+| **Parameter**       | **Description**                                              |
+| ------------------- | ------------------------------------------------------------ |
+| READ ONLY           | Create a read-only repository. Note that you can only restore data from a read-only repository. When creating the same repository for two clusters to migrate data, you can create a read-only repository for the new cluster and only grant it RESTORE permissions.|
+| repository_name     | Repository name. For the naming conventions, see [System limits](../../System_limit.md).                           |
+| repository_location | Location of the repository in the remote storage system.     |
+| PROPERTIES          |The credential method for accessing the remote storage system. |
+
+**PROPERTIES**:
+
+StarRocks supports creating repositories in HDFS, AWS S3, and Google GCS.
+
+- For HDFS:
+  - "username": The username of the account that you want to use to access the NameNode of the HDFS cluster.
+  - "password": The password of the account that you want to use to access the NameNode of the HDFS cluster.
+
+- For AWS S3:
+  - "aws.s3.use_instance_profile": Whether or not to allow instance profile and assumed role as credential methods for accessing AWS S3. Default: `false`.
+
+    - If you use IAM user-based credential (Access Key and Secret Key) to access AWS S3, you don't need to specify this parameter, and you need to specify "aws.s3.access_key", "aws.s3.secret_key", and "aws.s3.endpoint".
+    - If you use Instance Profile to access AWS S3, you need to set this parameter to `true` and specify "aws.s3.region".
+    - If you use Assumed Role to access AWS S3, you need to set this parameter to `true` and specify "aws.s3.iam_role_arn" and "aws.s3.region".
+  
+  - "aws.s3.access_key": The Access Key ID that you can use to access the Amazon S3 bucket.
+  - "aws.s3.secret_key": The Secret Access Key that you can use to access the Amazon S3 bucket.
+  - "aws.s3.endpoint": The endpoint that you can use to access the Amazon S3 bucket.
+  - "aws.s3.iam_role_arn": The ARN of the IAM role that has privileges on the AWS S3 bucket in which your data files are stored. If you want to use assumed role as the credential method for accessing AWS S3, you must specify this parameter. Then, StarRocks will assume this role when it analyzes your Hive data by using a Hive catalog.
+  - "aws.s3.region": The region in which your AWS S3 bucket resides. Example: `us-west-1`.
+
+> **NOTE**
+>
+> StarRocks supports creating repositories in AWS S3 only according to the S3A protocol. Therefore, when you create repositories in AWS S3, you must replace `s3://` in the S3 URI you pass as a repository location in `ON LOCATION` with `s3a://`.
+
+- For Google GCS:
+  - "fs.s3a.access.key": The Access Key that you can use to access the Google GCS bucket.
+  - "fs.s3a.secret.key": The Secret Key that you can use to access the Google GCS bucket.
+  - "fs.s3a.endpoint": The endpoint that you can use to access the Google GCS bucket.
+
+> **NOTE**
+>
+> StarRocks supports creating repositories in Google GCS only according to the S3A protocol. Therefore, when you create repositories in Google GCS, you must replace the prefix in the GCS URI you pass as a repository location in `ON LOCATION` with `s3a://`.
+
+## Examples
+
+Example 1: Create a repository named `hdfs_repo` in an Apache™ Hadoop® cluster.
+
+```SQL
+CREATE REPOSITORY hdfs_repo
+WITH BROKER
+ON LOCATION "hdfs://x.x.x.x:yyyy/repo_dir/backup"
+PROPERTIES(
+    "username" = "xxxxxxxx",
+    "password" = "yyyyyyyy"
+);
+```
+
+Example 2: Create a read-only repository named `s3_repo` in the Amazon S3 bucket `bucket_s3`.
+
+```SQL
+CREATE READ ONLY REPOSITORY s3_repo
+WITH BROKER
+ON LOCATION "s3a://bucket_s3/backup"
+PROPERTIES(
+    "aws.s3.access_key" = "XXXXXXXXXXXXXXXXX",
+    "aws.s3.secret_key" = "yyyyyyyyyyyyyyyyy",
+    "aws.s3.endpoint" = "s3.us-east-1.amazonaws.com"
+);
+```
+
+Example 3: Create a repository named `gcs_repo` in the Google GCS bucket `bucket_gcs`.
+
+```SQL
+CREATE REPOSITORY gcs_repo
+WITH BROKER
+ON LOCATION "s3a://bucket_gcs/backup"
+PROPERTIES(
+    "fs.s3a.access.key" = "xxxxxxxxxxxxxxxxxxxx",
+    "fs.s3a.secret.key" = "yyyyyyyyyyyyyyyyyyyy",
+    "fs.s3a.endpoint" = "storage.googleapis.com"
+);
+```
diff --git a/docs/en/sql-reference/sql-statements/backup_restore/DROP_REPOSITORY.md b/docs/en/sql-reference/sql-statements/backup_restore/DROP_REPOSITORY.md
new file mode 100644
index 00000000000000..be804276bd21f5
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/backup_restore/DROP_REPOSITORY.md
@@ -0,0 +1,34 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP REPOSITORY
+
+## Description
+
+Deletes a repository. Repositories are used to store data snapshots for data backup and restoration.
+
+> **CAUTION**
+>
+> - Only root user and superuser can delete a repository.
+> - This operation only deletes the mapping of the repository in StarRocks, and does not delete the actual data. You need to delete it manually in the remote storage system. After deletion, you can map to that repository again by specifying the same remote storage system path.
+
+## Syntax
+
+```SQL
+DROP REPOSITORY <repository_name>
+```
+
+## Parameters
+
+| **Parameter**   | **Description**                       |
+| --------------- | ------------------------------------- |
+| repository_name | Name of the repository to be deleted. |
+
+## Example
+
+Example 1: deletes a repository named `oss_repo`.
+
+```SQL
+DROP REPOSITORY `oss_repo`;
+```
diff --git a/docs/en/sql-reference/sql-statements/backup_restore/RECOVER.md b/docs/en/sql-reference/sql-statements/backup_restore/RECOVER.md
new file mode 100644
index 00000000000000..4b256303c0af69
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/backup_restore/RECOVER.md
@@ -0,0 +1,56 @@
+---
+displayed_sidebar: docs
+---
+
+# RECOVER
+
+## Description
+
+Recovers a database, table, or partition that was dropped by using the DROP command. The dropped database, table, or partition can be recovered within the period specified by the FE parameter `catalog_trash_expire_second` (1 day by default).
+
+Data deleted by using [TRUNCATE TABLE](../table_bucket_part_index/TRUNCATE_TABLE.md) cannot be recovered.
+
+## Syntax
+
+1. Recover a database.
+
+    ```sql
+    RECOVER DATABASE <db_name>
+    ```
+
+2. Recover a table.
+
+    ```sql
+    RECOVER TABLE [<db_name>.]<table_name>
+    ```
+
+3. Recover a partition.
+
+    ```sql
+    RECOVER PARTITION <partition_name> FROM [<db_name>.]<table_name>
+    ```
+
+Note:
+
+1. This command can only recover metadata deleted some time ago (1 day by default). You can change the duration by adjusting the FE parameter `catalog_trash_expire_second`.
+2. If the metadata is deleted with identical metadata created, the previous one will not be recovered.
+
+## Examples
+
+1. Recover database `example_db`.
+
+    ```sql
+    RECOVER DATABASE example_db;
+    ```
+
+2. Recover table `example_tbl`.
+
+    ```sql
+    RECOVER TABLE example_db.example_tbl;
+    ```
+
+3. Recover partition `p1` in the `example_tbl` table.
+
+    ```sql
+    RECOVER PARTITION p1 FROM example_tbl;
+    ```
diff --git a/docs/en/sql-reference/sql-statements/backup_restore/RESTORE.md b/docs/en/sql-reference/sql-statements/backup_restore/RESTORE.md
new file mode 100644
index 00000000000000..caf6a19b250575
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/backup_restore/RESTORE.md
@@ -0,0 +1,83 @@
+---
+displayed_sidebar: docs
+---
+
+# RESTORE
+
+## Description
+
+Restores data to a specified database, table, or partition. Currently, StarRocks only supports restoring data to OLAP tables.
+
+RESTORE is an asynchronous operation. You can check the status of a RESTORE job using [SHOW RESTORE](./SHOW_RESTORE.md), or cancel a RESTORE job using [CANCEL RESTORE](./CANCEL_RESTORE.md).
+
+> **CAUTION**
+>
+> - Only users with the ADMIN privilege can restore data.
+> - In each database, only one running BACKUP or RESTORE job is allowed each time. Otherwise, StarRocks returns an error.
+
+## Syntax
+
+```SQL
+RESTORE SNAPSHOT <db_name>.<snapshot_name>
+FROM <repository_name>
+[ ON ( <table_name> [ PARTITION ( <partition_name> [, ...] ) ]
+    [ AS <table_alias>] [, ...] ) ]
+PROPERTIES ("key"="value", ...)
+```
+
+## Parameters
+
+| **Parameter**   | **Description**                                              |
+| --------------- | ------------------------------------------------------------ |
+| db_name         | Name of the database that the data is restored to.           |
+| snapshot_name   | Name for the data snapshot.                                  |
+| repository_name | Repository name.                                             |
+| ON              | Name of the tables to restore. The whole database is restored if this parameter is not specified. |
+| PARTITION       | Name of the partitions to be restored. The whole table is restored if this parameter is not specified. You can view the partition name using [SHOW PARTITIONS](../table_bucket_part_index/SHOW_PARTITIONS.md). |
+| PROPERTIES      | Properties of the RESTORE operation. Valid keys:<ul><li>`backup_timestamp`: Backup timestamp. **Required**. You can view backup timestamps using [SHOW SNAPSHOT](./SHOW_SNAPSHOT.md).</li><li>`replication_num`: Specify the number of replicas to be restored. Default: `3`.</li><li>`meta_version`: This parameter is only used as a temporary solution to restore the data backed up by the earlier version of StarRocks. The latest version of the backed up data already contains `meta version`, and you do not need to specify it.</li><li>`timeout`: Task timeout. Unit: second. Default: `86400`.</li></ul> |
+
+## Examples
+
+Example 1: Restores the table `backup_tbl` in the snapshot `snapshot_label1` from the `example_repo` repository to the database `example_db`, and the backup timestamp is `2018-05-04-16-45-08`. Restores one replica.
+
+```SQL
+RESTORE SNAPSHOT example_db.snapshot_label1
+FROM example_repo
+ON ( backup_tbl )
+PROPERTIES
+(
+    "backup_timestamp"="2018-05-04-16-45-08",
+    "replication_num" = "1"
+);
+```
+
+Example 2: Restores partitions `p1` and `p2` of table `backup_tbl` in `snapshot_label2` and table `backup_tbl2` from `example_repo` to database `example_db`, and rename `backup_tbl2` to `new_tbl`. The backup timestamp is `2018-05-04-17-11-01`. Restores three replicas by default.
+
+```SQL
+RESTORE SNAPSHOT example_db.snapshot_label2
+FROM example_repo
+ON(
+    backup_tbl PARTITION (p1, p2),
+    backup_tbl2 AS new_tbl
+)
+PROPERTIES
+(
+    "backup_timestamp"="2018-05-04-17-11-01"
+);
+```
+
+## Usage notes
+
+- Performing backup and restore operations on global, database, table, and partition levels requires different privileges.
+- In each database, only one running BACKUP or RESTORE job is allowed each time. Otherwise, StarRocks returns an error.
+- Because BACKUP and RESTORE jobs occupy many resources of your StarRocks cluster, you can back up and restore your data while your StarRocks cluster is not heavily loaded.
+- StarRocks does not support specifying data compression algorithms for data backup.
+- Because data is backed up as snapshots, the data loaded upon snapshot generation is not included in the snapshot. Therefore, if you load data into the old cluster after the snapshot is generated and before the RESTORE job is completed, you also need to load the data into the cluster that data is restored into. It is recommended that you load data into both clusters in parallel for a period of time after the data migration is complete, and then migrate your application to the new cluster after verifying the correctness of the data and services.
+- Before the RESTORE job is completed, you cannot operate the table to be restored.
+- Primary Key tables cannot be restored to a StarRocks cluster earlier than v2.5.
+- You do not need to create the table to be restored in the new cluster before restoring it. The RESTORE job automatically creates it.
+- If there is an existing table that has a duplicated name with the table to be restored, StarRocks first checks whether or not the schema of the existing table matches that of the table to be restored. If the schemas match, StarRocks overwrites the existing table with the data in the snapshot. If the schema does not match, the RESTORE job fails. You can either rename the table to be restored using the keyword `AS`, or delete the existing table before restoring data.
+- If the RESTORE job overwrites an existing database, table, or partition, the overwritten data cannot be restored after the job enters the COMMIT phase. If the RESTORE job fails or is canceled at this point, the data may be corrupted and inaccessible. In this case, you can only perform the RESTORE operation again and wait for the job to complete. Therefore, we recommend that you do not restore data by overwriting unless you are sure that the current data is no longer used. The overwrite operation first checks metadata consistency between the snapshot and the existing database, table, or partition. If an inconsistency is detected, the RESTORE operation cannot be performed.
+- Currently, StarRocks does not support backing up and restoring logical views.
+- Currently, StarRocks does not support backing up and restoring the configuration data related to user accounts, privileges, and resource groups.
+- Currently, StarRocks does not support backing up and restoring the Colocate Join relationship among tables.
diff --git a/docs/en/sql-reference/sql-statements/backup_restore/SHOW_BACKUP.md b/docs/en/sql-reference/sql-statements/backup_restore/SHOW_BACKUP.md
new file mode 100644
index 00000000000000..9ee788e87f8284
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/backup_restore/SHOW_BACKUP.md
@@ -0,0 +1,52 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW BACKUP
+
+## Description
+
+Views the last BACKUP task in a specified database.
+
+> **NOTE**
+>
+> Only the information of the last BACKUP task is saved in StarRocks.
+
+## Syntax
+
+```SQL
+SHOW BACKUP [FROM <db_name>]
+```
+
+## Parameters
+
+| **Parameter** | **Description**                                       |
+| ------------- | ----------------------------------------------------- |
+| db_name       | Name of the database that the BACKUP task belongs to. |
+
+## Return
+
+| **Return**           | **Description**                                              |
+| -------------------- | ------------------------------------------------------------ |
+| JobId                | Unique job ID.                                               |
+| SnapshotName         | Name of the data snapshot.                                   |
+| DbName               | Name of the database that the BACKUP task belongs to.        |
+| State                | Current state of the BACKUP task:<ul><li>PENDING: Initial state after submitting a job.</li><li>SNAPSHOTING: Creating snapshot.</li><li>UPLOAD_SNAPSHOT: Snapshot complete, ready for upload.</li><li>UPLOADING: Uploading snapshot.</li><li>SAVE_META: Creating local metadata files.</li><li>UPLOAD_INFO: Uploading metadata files and information of the BACKUP task.</li><li>FINISHED: BACKUP task finished.</li><li>CANCELLED: BACKUP task failed or cancelled.</li></ul> |
+| BackupObjs           | Backed up objects.                                           |
+| CreateTime           | Task submission time.                                        |
+| SnapshotFinishedTime | Snapshot completion time.                                    |
+| UploadFinishedTime   | Snapshot upload completion time.                             |
+| FinishedTime         | Task completion Time.                                        |
+| UnfinishedTasks      | Unfinished subtask IDs in the SNAPSHOTING and UPLOADING phases. |
+| Progress             | The progress of snapshot uploading tasks.                             |
+| TaskErrMsg           | Error messages.                                              |
+| Status               | Status information.                                          |
+| Timeout              | Task timeout. Unit: second.                                  |
+
+## Examples
+
+Example 1: Views the last BACKUP task in the database `example_db`.
+
+```SQL
+SHOW BACKUP FROM example_db;
+```
diff --git a/docs/en/sql-reference/sql-statements/backup_restore/SHOW_REPOSITORIES.md b/docs/en/sql-reference/sql-statements/backup_restore/SHOW_REPOSITORIES.md
new file mode 100644
index 00000000000000..6610f9c2e4deb5
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/backup_restore/SHOW_REPOSITORIES.md
@@ -0,0 +1,35 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW REPOSITORIES
+
+## Description
+
+Views the repositories created in StarRocks.
+
+## Syntax
+
+```SQL
+SHOW REPOSITORIES
+```
+
+## Return
+
+| **Return** | **Description**                                          |
+| ---------- | -------------------------------------------------------- |
+| RepoId     | Repository ID.                                           |
+| RepoName   | Repository name.                                         |
+| CreateTime | Repository creation time.                                |
+| IsReadOnly | If the repository is read-only.                          |
+| Location   | Location of the repository in the remote storage system. |
+| Broker     | Broker used to create the repository.                    |
+| ErrMsg     | Error message during connection to the repository.       |
+
+## Examples
+
+Example 1: Views the repositories created in StarRocks.
+
+```SQL
+SHOW REPOSITORIES;
+```
diff --git a/docs/en/sql-reference/sql-statements/backup_restore/SHOW_RESTORE.md b/docs/en/sql-reference/sql-statements/backup_restore/SHOW_RESTORE.md
new file mode 100644
index 00000000000000..eeee01de276b94
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/backup_restore/SHOW_RESTORE.md
@@ -0,0 +1,56 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW RESTORE
+
+## Description
+
+Views the last RESTORE task in a specified database.
+
+> **NOTE**
+>
+> Only the information of the last RESTORE task is saved in StarRocks.
+
+## Syntax
+
+```SQL
+SHOW RESTORE [FROM <db_name>]
+```
+
+## Parameters
+
+| **Parameter** | **Description**                                        |
+| ------------- | ------------------------------------------------------ |
+| db_name       | Name of the database that the RESTORE task belongs to. |
+
+## Return
+
+| **Return**           | **Description**                                              |
+| -------------------- | ------------------------------------------------------------ |
+| JobId                | Unique job ID.                                               |
+| Label                | Name of the data snapshot.                                   |
+| Timestamp            | Backup timestamp.                                            |
+| DbName               | Name of the database that the RESTORE task belongs to.       |
+| State                | Current state of the RESTORE task:<ul><li>PENDING: Initial state after submitting a job.</li><li>SNAPSHOTING: Executing the local snapshot.</li><li>DOWNLOAD: Submitting snapshot download task.</li><li>DOWNLOADING: Downloading the snapshot.</li><li>COMMIT: To commit the downloaded snapshot.</li><li>COMMITTING: Committing the downloaded snapshot.</li><li>FINISHED: RESTORE task finished.</li><li>CANCELLED: RESTORE task failed or cancelled.</li></ul> |
+| AllowLoad            | If loading data is allowed during the RESTORE task.          |
+| ReplicationNum       | Number of replicas to be restored.                           |
+| RestoreObjs          | The restored objects (tables and partitions).                |
+| CreateTime           | Task submission time.                                        |
+| MetaPreparedTime     | Local metadata completion time.                              |
+| SnapshotFinishedTime | Snapshot completion time.                                    |
+| DownloadFinishedTime | Snapshot download completion time.                           |
+| FinishedTime         | Task completion Time.                                        |
+| UnfinishedTasks      | Unfinished subtask IDs in the SNAPSHOTTING, DOWNLOADING, and COMMITTING phases. |
+| Progress             | The progress of snapshot downloading tasks.                  |
+| TaskErrMsg           | Error messages.                                              |
+| Status               | Status information.                                          |
+| Timeout              | Task timeout. Unit: second.                                  |
+
+## Examples
+
+Example 1: Views the last RESTORE task in the database `example_db`.
+
+```SQL
+SHOW RESTORE FROM example_db;
+```
diff --git a/docs/en/sql-reference/sql-statements/backup_restore/SHOW_SNAPSHOT.md b/docs/en/sql-reference/sql-statements/backup_restore/SHOW_SNAPSHOT.md
new file mode 100644
index 00000000000000..620e2d5ff6c222
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/backup_restore/SHOW_SNAPSHOT.md
@@ -0,0 +1,56 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW SNAPSHOT
+
+## Description
+
+Views data snapshots in a specified repository. For more information, see [data backup and restoration](../../../administration/management/Backup_and_restore.md).
+
+## Syntax
+
+```SQL
+SHOW SNAPSHOT ON <repo_name>
+[WHERE SNAPSHOT = <snapshot_name> [AND TIMESTAMP = <backup_timestamp>]]
+```
+
+## Parameters
+
+| **Parameter**    | **Description**                                      |
+| ---------------- | ---------------------------------------------------- |
+| repo_name        | Name of the repository that the snapshot belongs to. |
+| snapshot_nam     | Name of the snapshot.                                |
+| backup_timestamp | Backup timestamp of the snapshot.                    |
+
+## Return
+
+| **Return** | **Description**                                              |
+| ---------- | ------------------------------------------------------------ |
+| Snapshot   | Name of the snapshot.                                        |
+| Timestamp  | Backup timestamp of the snapshot.                            |
+| Status     | Displays `OK` if the snapshot is okay. Displays error message if the snapshot is not okay. |
+| Database   | Name of the database that the snapshot belongs to.           |
+| Details    | JSON-formatted directory and structure of the snapshot.      |
+
+## Example
+
+Example 1: Views snapshots in repository `example_repo`.
+
+```SQL
+SHOW SNAPSHOT ON example_repo;
+```
+
+Example 2: Views the snapshot named `backup1` in repository `example_repo`.
+
+```SQL
+SHOW SNAPSHOT ON example_repo
+WHERE SNAPSHOT = "backup1";
+```
+
+Example 3: Views the snapshot named `backup1` with backup timestamp `2018-05-05-15-34-26` in repository `example_repo`.
+
+```SQL
+SHOW SNAPSHOT ON example_repo 
+WHERE SNAPSHOT = "backup1" AND TIMESTAMP = "2018-05-05-15-34-26";
+```
diff --git a/docs/en/sql-reference/sql-statements/backup_restore/_category_.yml b/docs/en/sql-reference/sql-statements/backup_restore/_category_.yml
new file mode 100644
index 00000000000000..71c6464bd7e9a8
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/backup_restore/_category_.yml
@@ -0,0 +1,6 @@
+position: 130 # float position is supported
+label: 'Backup and restore'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-statements/backup_restore/backup_restore.mdx b/docs/en/sql-reference/sql-statements/backup_restore/backup_restore.mdx
new file mode 100644
index 00000000000000..9983b2f1462b60
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/backup_restore/backup_restore.mdx
@@ -0,0 +1,8 @@
+---
+displayed_sidebar: docs
+---
+
+# Backup and restore
+
+import DocCardList from '@theme/DocCardList';
+
diff --git a/docs/en/sql-reference/sql-statements/cbo_stats/ANALYZE_TABLE.md b/docs/en/sql-reference/sql-statements/cbo_stats/ANALYZE_TABLE.md
new file mode 100644
index 00000000000000..a37ffb1832d744
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cbo_stats/ANALYZE_TABLE.md
@@ -0,0 +1,124 @@
+---
+displayed_sidebar: docs
+---
+
+# ANALYZE TABLE
+
+## Description
+
+Creates a manual collection task for collecting CBO statistics. By default, manual collection is a synchronous operation. You can also set it to an asynchronous operation. In asynchronous mode, after you run ANALYZE TABLE, the system immediately returns whether this statement is successful. However, the collection task will be running in the background and you do not have to wait for the result. You can check the status of the task by running SHOW ANALYZE STATUS. Asynchronous collection is suitable for tables with large data volume, whereas synchronous collection is suitable for tables with small data volume.
+
+**Manual collection tasks are run only once after creation. You do not need to delete manual collection tasks.**
+
+This statement is supported from v2.4.
+
+### Manually collect basic statistics
+
+For more information about basic statistics, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md#basic-statistics).
+
+#### Syntax
+
+```SQL
+ANALYZE [FULL|SAMPLE] TABLE tbl_name (col_name [,col_name])
+[WITH SYNC | ASYNC MODE]
+PROPERTIES (property [,property])
+```
+
+#### Parameter description
+
+- Collection type
+  - FULL: indicates full collection.
+  - SAMPLE: indicates sampled collection.
+  - If no collection type is specified, full collection is used by default.
+
+- `col_name`: columns from which to collect statistics. Separate multiple columns with commas (`,`). If this parameter is not specified, the entire table is collected.
+
+- [WITH SYNC | ASYNC MODE]: whether to run the manual collection task in synchronous or asynchronous mode. Synchronous collection is used by default if you do not specify this parameter.
+
+- `PROPERTIES`: custom parameters. If `PROPERTIES` is not specified, the default settings in the `fe.conf` file are used. The properties that are actually used can be viewed via the `Properties` column in the output of SHOW ANALYZE STATUS.
+
+| **PROPERTIES**                | **Type** | **Default value** | **Description**                                              |
+| ----------------------------- | -------- | ----------------- | ------------------------------------------------------------ |
+| statistic_sample_collect_rows | INT      | 200000            | The minimum number of rows to collect for sampled collection.If the parameter value exceeds the actual number of rows in your table, full collection is performed. |
+
+#### Examples
+
+Example 1: Manual full collection
+
+```SQL
+-- Manually collect full stats of a table using default settings.
+ANALYZE TABLE tbl_name;
+
+-- Manually collect full stats of a table using default settings.
+ANALYZE FULL TABLE tbl_name;
+
+-- Manually collect stats of specified columns in a table using default settings.
+ANALYZE TABLE tbl_name(c1, c2, c3);
+```
+
+Example 2: Manual sampled collection
+
+```SQL
+-- Manually collect partial stats of a table using default settings.
+ANALYZE SAMPLE TABLE tbl_name;
+
+-- Manually collect stats of specified columns in a table, with the number of rows to collect specified.
+ANALYZE SAMPLE TABLE tbl_name (v1, v2, v3) PROPERTIES(
+    "statistic_sample_collect_rows" = "1000000"
+);
+```
+
+### Manually collect histograms
+
+For more information about histograms, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md#histogram).
+
+#### Syntax
+
+```SQL
+ANALYZE TABLE tbl_name UPDATE HISTOGRAM ON col_name [, col_name]
+[WITH SYNC | ASYNC MODE]
+[WITH N BUCKETS]
+PROPERTIES (property [,property]);
+```
+
+#### Parameter description
+
+- `col_name`: columns from which to collect statistics. Separate multiple columns with commas (`,`). If this parameter is not specified, the entire table is collected. This parameter is required for histograms.
+
+- [WITH SYNC | ASYNC MODE]: whether to run the manual collection task in synchronous or asynchronous mode. Synchronous collection is used by default if you do not specify this parameter.
+
+- `WITH N BUCKETS`: `N` is the number of buckets for histogram collection. If not specified, the default value in `fe.conf` is used.
+
+- PROPERTIES: custom parameters. If `PROPERTIES` is not specified, the default settings in `fe.conf` are used. The properties that are actually used can be viewed via the `Properties` column in the output of SHOW ANALYZE STATUS.
+
+| **PROPERTIES**                 | **Type** | **Default value** | **Description**                                              |
+| ------------------------------ | -------- | ----------------- | ------------------------------------------------------------ |
+| statistic_sample_collect_rows  | INT      | 200000            | The minimum number of rows to collect. If the parameter value exceeds the actual number of rows in your table, full collection is performed. |
+| histogram_buckets_size         | LONG     | 64                | The default bucket number for a histogram.                   |
+| histogram_mcv_size             | INT      | 100               | The number of most common values (MCV) for a histogram.      |
+| histogram_sample_ratio         | FLOAT    | 0.1               | The sampling ratio for a histogram.                          |
+| histogram_max_sample_row_count | LONG     | 10000000          | The maximum number of rows to collect for a histogram.       |
+
+The number of rows to collect for a histogram is controlled by multiple parameters. It is the larger value between `statistic_sample_collect_rows` and table row count * `histogram_sample_ratio`. The number cannot exceed the value specified by `histogram_max_sample_row_count`. If the value is exceeded, `histogram_max_sample_row_count` takes precedence.
+
+#### Examples
+
+```SQL
+-- Manually collect histograms on v1 using the default settings.
+ANALYZE TABLE tbl_name UPDATE HISTOGRAM ON v1;
+
+-- Manually collect histograms on v1 and v2, with 32 buckets, 32 MCVs, and 50% sampling ratio.
+ANALYZE TABLE tbl_name UPDATE HISTOGRAM ON v1,v2 WITH 32 BUCKETS 
+PROPERTIES(
+   "histogram_mcv_size" = "32",
+   "histogram_sample_ratio" = "0.5"
+);
+```
+
+## References
+
+[SHOW ANALYZE STATUS](SHOW_ANALYZE_STATUS.md): view the status of a manual collection task.
+
+[KILL ANALYZE](KILL_ANALYZE.md): cancel a manual collection task that is running.
+
+For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/cbo_stats/CREATE_ANALYZE.md b/docs/en/sql-reference/sql-statements/cbo_stats/CREATE_ANALYZE.md
new file mode 100644
index 00000000000000..2cf3ca9af664ab
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cbo_stats/CREATE_ANALYZE.md
@@ -0,0 +1,88 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE ANALYZE
+
+## Description
+
+Customizes an automatic collection task for collecting CBO statistics.
+
+By default, StarRocks automatically collects full statistics of a table. It checks for any data updates every 5 minutes. If data change is detected, data collection will be automatically triggered. If you do not want to use automatic full collection, you can set the FE configuration item `enable_collect_full_statistic` to `false` and customize a collection task.
+
+Before creating a custom automatic collection task, you must disable automatic full collection (`enable_collect_full_statistic = false`). Otherwise, custom tasks cannot take effect.
+
+This statement is supported from v2.4.
+
+## Syntax
+
+```SQL
+-- Automatically collect stats of all databases.
+CREATE ANALYZE [FULL|SAMPLE] ALL PROPERTIES (property [,property])
+
+-- Automatically collect stats of all tables in a database.
+CREATE ANALYZE [FULL|SAMPLE] DATABASE db_name
+PROPERTIES (property [,property])
+
+-- Automatically collect stats of specified columns in a table.
+CREATE ANALYZE [FULL|SAMPLE] TABLE tbl_name (col_name [,col_name])
+PROPERTIES (property [,property])
+```
+
+## Parameter description
+
+- Collection type
+  - FULL: indicates full collection.
+  - SAMPLE: indicates sampled collection.
+  - If no collection type is specified, sampled collection is used by default.
+
+- `col_name`: columns from which to collect statistics. Separate multiple columns with commas (`,`). If this parameter is not specified, the entire table is collected.
+
+- `PROPERTIES`: custom parameters. If `PROPERTIES` is not specified, the default settings in `fe.conf` are used. The properties that are actually used can be viewed via the `Properties` column in the output of SHOW ANALYZE JOB.
+
+| **PROPERTIES**                        | **Type** | **Default value** | **Description**                                              |
+| ------------------------------------- | -------- | ----------------- | ------------------------------------------------------------ |
+| statistic_auto_collect_ratio          | FLOAT    | 0.8               | The threshold for determining  whether the statistics for automatic collection are healthy. If the statistics health is below this threshold, automatic collection is triggered. |
+| statistics_max_full_collect_data_size | INT      | 100               | The size of the largest partition for automatic collection to collect data. Unit: GB.If a partition exceeds this value, full collection is discarded and sampled collection is performed instead. |
+| statistic_sample_collect_rows         | INT      | 200000            | The minimum number of rows to collect.If the parameter value exceeds the actual number of rows in your table, full collection is performed. |
+
+## Examples
+
+Example 1: Automatic full collection
+
+```SQL
+-- Automatically collect full stats of all databases.
+CREATE ANALYZE ALL;
+
+-- Automatically collect full stats of a database.
+CREATE ANALYZE DATABASE db_name;
+
+-- Automatically collect full stats of all tables in a database.
+CREATE ANALYZE FULL DATABASE db_name;
+
+-- Automatically collect full stats of specified columns in a table.
+CREATE ANALYZE TABLE tbl_name(c1, c2, c3); 
+```
+
+Example 2: Automatic sampled collection
+
+```SQL
+-- Automatically collect stats of all tables in a database using default settings.
+CREATE ANALYZE SAMPLE DATABASE db_name;
+
+-- Automatically collect stats of specified columns in a table, with statistics health and the number of rows to collect specified.
+CREATE ANALYZE SAMPLE TABLE tbl_name(c1, c2, c3) PROPERTIES(
+   "statistic_auto_collect_ratio" = "0.5",
+   "statistic_sample_collect_rows" = "1000000"
+);
+```
+
+## References
+
+[SHOW ANALYZE JOB](SHOW_ANALYZE_JOB.md): view the status of a custom collection task.
+
+[DROP ANALYZE](DROP_ANALYZE.md): delete a custom collection task.
+
+[KILL ANALYZE](KILL_ANALYZE.md): cancel a custom collection task that is running.
+
+For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/cbo_stats/DROP_ANALYZE.md b/docs/en/sql-reference/sql-statements/cbo_stats/DROP_ANALYZE.md
new file mode 100644
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--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cbo_stats/DROP_ANALYZE.md
@@ -0,0 +1,37 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP ANALYZE
+
+## Description
+
+Deletes a custom collection task.
+
+By default, StarRocks automatically collects full statistics of a table. It checks for any data updates every 5 minutes. If data change is detected, data collection will be automatically triggered. If you do not want to use automatic full collection, you can set the FE configuration item `enable_collect_full_statistic` to `false` and customize a collection task.
+
+This statement is supported from v2.4.
+
+## Syntax
+
+```SQL
+DROP ANALYZE <ID>
+```
+
+The task ID can be obtained by using the SHOW ANALYZE JOB statement.
+
+## Examples
+
+```SQL
+DROP ANALYZE 266030;
+```
+
+## References
+
+[CREATE ANALYZE](CREATE_ANALYZE.md): customize an automatic collection task.
+
+[SHOW ANALYZE JOB](SHOW_ANALYZE_JOB.md): view the status of an automatic collection task.
+
+[KILL ANALYZE](KILL_ANALYZE.md): cancel a custom collection task that is running.
+
+For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/cbo_stats/DROP_STATS.md b/docs/en/sql-reference/sql-statements/cbo_stats/DROP_STATS.md
new file mode 100644
index 00000000000000..3ad79250eaec4e
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cbo_stats/DROP_STATS.md
@@ -0,0 +1,31 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP STATS
+
+## Description
+
+Deletes CBO statistics, which include basic statistics and histograms. For more information, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md#basic-statistics).
+
+You can delete statistical information you do not need. When you delete statistics, both the data and metadata of the statistics are deleted, as well as the statistics in expired cache. Note that if an automatic collection task is ongoing, previously deleted statistics may be collected again. You can use `SHOW ANALYZE STATUS` to view the history of collection tasks.
+
+This statement is supported from v2.4.
+
+## Syntax
+
+### Delete basic statistics
+
+```SQL
+DROP STATS tbl_name
+```
+
+### Delete histograms
+
+```SQL
+ANALYZE TABLE tbl_name DROP HISTOGRAM ON col_name [, col_name];
+```
+
+## References
+
+For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/cbo_stats/KILL_ANALYZE.md b/docs/en/sql-reference/sql-statements/cbo_stats/KILL_ANALYZE.md
new file mode 100644
index 00000000000000..d9800a45689e21
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cbo_stats/KILL_ANALYZE.md
@@ -0,0 +1,27 @@
+---
+displayed_sidebar: docs
+---
+
+# KILL ANALYZE
+
+## Description
+
+Cancels a **running** collection task, including manual and custom automatic tasks.
+
+This statement is supported from v2.4.
+
+## Syntax
+
+```SQL
+KILL ANALYZE <ID>
+```
+
+The task ID for a manual collection task can be obtained from SHOW ANALYZE STATUS. The task ID for a custom collection task can be obtained from SHOW ANALYZE SHOW ANALYZE JOB.
+
+## References
+
+[SHOW ANALYZE STATUS](SHOW_ANALYZE_STATUS.md)
+
+[SHOW ANALYZE JOB](SHOW_ANALYZE_JOB.md)
+
+For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/cbo_stats/SHOW_ANALYZE_JOB.md b/docs/en/sql-reference/sql-statements/cbo_stats/SHOW_ANALYZE_JOB.md
new file mode 100644
index 00000000000000..d9aa968ab61d54
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cbo_stats/SHOW_ANALYZE_JOB.md
@@ -0,0 +1,54 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW ANALYZE JOB
+
+## Description
+
+Views the information and status of custom collection tasks.
+
+By default, StarRocks automatically collects full statistics of a table. It checks for any data updates every 5 minutes. If data change is detected, data collection will be automatically triggered. If you do not want to use automatic full collection, you can set the FE configuration item `enable_collect_full_statistic` to `false` and customize a collection task.
+
+This statement is supported from v2.4.
+
+## Syntax
+
+```SQL
+SHOW ANALYZE JOB [WHERE]
+```
+
+You can filter results by using the WHERE clause. The statement returns the following columns.
+
+| **Column**   | **Description**                                              |
+| ------------ | ------------------------------------------------------------ |
+| Id           | The ID of the collection task.                               |
+| Database     | The database name.                                           |
+| Table        | The table name.                                              |
+| Columns      | The column names.                                            |
+| Type         | The type of statistics, including `FULL` and `SAMPLE`.       |
+| Schedule     | The type of scheduling. The type is `SCHEDULE` for an automatic task. |
+| Properties   | Custom parameters.                                           |
+| Status       | The task status, including PENDING, RUNNING, SUCCESS, and FAILED. |
+| LastWorkTime | The time of the last collection.                             |
+| Reason       | The reason why the task failed. NULL is returned if task execution was successful. |
+
+## Examples
+
+```SQL
+-- View all the custom collection tasks.
+SHOW ANALYZE JOB
+
+-- View custom collection tasks of database `test`.
+SHOW ANALYZE JOB where `database` = 'test';
+```
+
+## References
+
+[CREATE ANALYZE](CREATE_ANALYZE.md): customize an automatic collection task.
+
+[DROP ANALYZE](DROP_ANALYZE.md): delete a custom collection task.
+
+[KILL ANALYZE](KILL_ANALYZE.md): cancel a custom collection task that is running.
+
+For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/cbo_stats/SHOW_ANALYZE_STATUS.md b/docs/en/sql-reference/sql-statements/cbo_stats/SHOW_ANALYZE_STATUS.md
new file mode 100644
index 00000000000000..94e5fcb5c9f896
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cbo_stats/SHOW_ANALYZE_STATUS.md
@@ -0,0 +1,45 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW ANALYZE STATUS
+
+## Description
+
+Views the status of collection tasks.
+
+This statement cannot be used to view the status of custom collection tasks. To view the status of custom collection tasks, use SHOW ANALYZE JOB.
+
+This statement is supported from v2.4.
+
+## Syntax
+
+```SQL
+SHOW ANALYZE STATUS [WHERE]
+```
+
+You can use `LIKE` or `WHERE` to filter the information to return.
+
+This statement returns the following columns.
+
+| **List name** | **Description**                                              |
+| ------------- | ------------------------------------------------------------ |
+| Id            | The ID of the collection task.                               |
+| Database      | The database name.                                           |
+| Table         | The table name.                                              |
+| Columns       | The column names.                                            |
+| Type          | The type of statistics, including FULL, SAMPLE, and HISTOGRAM. |
+| Schedule      | The type of scheduling. `ONCE` means manual and `SCHEDULE` means automatic. |
+| Status        | The status of the task.                                      |
+| StartTime     | The time when the task starts executing.                     |
+| EndTime       | The time when the task execution ends.                       |
+| Properties    | Custom parameters.                                           |
+| Reason        | The reason why the task failed. NULL is returned if the execution was successful. |
+
+## References
+
+[ANALYZE TABLE](ANALYZE_TABLE.md): create a manual collection task.
+
+[KILL ANALYZE](KILL_ANALYZE.md): cancel a custom collection task that is running.
+
+For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/cbo_stats/SHOW_META.md b/docs/en/sql-reference/sql-statements/cbo_stats/SHOW_META.md
new file mode 100644
index 00000000000000..34de41f28596c8
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cbo_stats/SHOW_META.md
@@ -0,0 +1,54 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW META
+
+## Description
+
+Views metadata of CBO statistics, including basic statistics and histograms.
+
+This statement is supported from v2.4.
+
+### View metadata of basic statistics
+
+#### Syntax
+
+```SQL
+SHOW STATS META [WHERE]
+```
+
+This statement returns the following columns.
+
+| **Column** | **Description**                                              |
+| ---------- | ------------------------------------------------------------ |
+| Database   | The database name.                                           |
+| Table      | The table name.                                              |
+| Columns    | The column names.                                            |
+| Type       | The type of statistics. `FULL` means full collection and `SAMPLE` means sampled collection. |
+| UpdateTime | The latest statistics update time for the current table.     |
+| Properties | Custom parameters.                                           |
+| Healthy    | The health of statistical information.                       |
+
+### View metadata of histograms
+
+#### Syntax
+
+```SQL
+SHOW HISTOGRAM META [WHERE];
+```
+
+This statement returns the following columns.
+
+| **Column** | **Description**                                              |
+| ---------- | ------------------------------------------------------------ |
+| Database   | The database name.                                           |
+| Table      | The table name.                                              |
+| Column     | The columns.                                                 |
+| Type       | Type of statistics. The value is `HISTOGRAM` for histograms. |
+| UpdateTime | The latest statistics update time for the current table.     |
+| Properties | Custom parameters.                                           |
+
+## References
+
+For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/cbo_stats/_category_.yml b/docs/en/sql-reference/sql-statements/cbo_stats/_category_.yml
new file mode 100644
index 00000000000000..f98e89c6eab815
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cbo_stats/_category_.yml
@@ -0,0 +1,6 @@
+position: 120 # float position is supported
+label: 'CBO statistics'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/_category_.yml b/docs/en/sql-reference/sql-statements/cluster-management/_category_.yml
new file mode 100644
index 00000000000000..876d069f42647d
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/_category_.yml
@@ -0,0 +1,6 @@
+position: 20 # float position is supported
+label: 'Cluster management'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md b/docs/en/sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md
new file mode 100644
index 00000000000000..cce2f4c4f785b0
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md
@@ -0,0 +1,31 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN SET CONFIG
+
+## Description
+
+This statement is used to set configuration items for the cluster (Currently, only FE dynamic configuration items can be set using this command). You can view these configuration items using the [ADMIN SHOW FRONTEND CONFIG](ADMIN_SET_CONFIG.md) command.
+
+The configurations will be restored to the default values in the `fe.conf` file after the FE restarts. Therefore, we recommend that you also modify the configuration items in `fe.conf` to prevent the loss of modifications.
+
+:::tip
+
+This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```sql
+ADMIN SET FRONTEND CONFIG ("key" = "value")
+```
+
+## Examples
+
+1. Set `disable_balance` to `true`.
+
+    ```sql
+    ADMIN SET FRONTEND CONFIG ("disable_balance" = "true");
+    ```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SHOW_CONFIG.md b/docs/en/sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SHOW_CONFIG.md
new file mode 100644
index 00000000000000..e3126729cee722
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SHOW_CONFIG.md
@@ -0,0 +1,56 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN SHOW CONFIG
+
+## Description
+
+Displays the configuration of the current cluster (Currently, only FE configuration items can be displayed). For detailed description of these configuration items, see [Configuration](../../../../administration/management/FE_configuration.md).
+
+If you want to set or modify a configuration item, use [ADMIN SET CONFIG](ADMIN_SET_CONFIG.md).
+
+:::tip
+
+This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```sql
+ADMIN SHOW FRONTEND CONFIG [LIKE "pattern"]
+```
+
+Note:
+
+Description of the return parameters:
+
+```plain text
+1. Key:        Configuration item name
+2. Value:      Configuration item value
+3. Type:       Configuration item type 
+4. IsMutable:  Whether it can be set through the ADMIN SET CONFIG command
+5. MasterOnly: Whether it only applies to leader FE
+6. Comment:    Configuration item description 
+```
+
+## Examples
+
+1. View the configuration of the current FE node.
+
+    ```sql
+    ADMIN SHOW FRONTEND CONFIG;
+    ```
+
+2. Search for the configuration of the current FE node by using the `like` predicate.  
+
+    ```plain text
+    mysql> ADMIN SHOW FRONTEND CONFIG LIKE '%check_java_version%';
+    +--------------------+-------+---------+-----------+------------+---------+
+    | Key                | Value | Type    | IsMutable | MasterOnly | Comment |
+    +--------------------+-------+---------+-----------+------------+---------+
+    | check_java_version | true  | boolean | false     | false      |         |
+    +--------------------+-------+---------+-----------+------------+---------+
+    1 row in set (0.00 sec)
+    ```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/config_vars/SET.md b/docs/en/sql-reference/sql-statements/cluster-management/config_vars/SET.md
new file mode 100644
index 00000000000000..02155159efb43b
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/config_vars/SET.md
@@ -0,0 +1,54 @@
+---
+displayed_sidebar: docs
+---
+
+# SET
+
+## Description
+
+Sets the specified system variables or user-defined variables for StarRocks. You can view the system variables of StarRocks using [SHOW VARIABLES](./SHOW_VARIABLES.md). For details about system variables, see [System Variables](../../../System_variable.md). For details about user-defined variables, see [User-defined variables](../../../user_defined_variables.md).
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```SQL
+SET [ GLOBAL | SESSION ] <variable_name> = <value> [, <variable_name> = <value>] ...
+```
+
+## Parameters
+
+| **Parameter**          | **Description**                                              |
+| ---------------------- | ------------------------------------------------------------ |
+| Modifier:<ul><li>GLOBAL</li><li>SESSION</li></ul> | <ul><li>With a `GLOBAL` modifier, the statement sets the variables globally.</li><li>With a `SESSION` modifier, the statement sets the variables within the session. `LOCAL` is a synonym for `SESSION`.</li><li>If no modifier is present, the default is `SESSION`.</li></ul>For details about global and session variables, see [System Variables](../../../System_variable.md).<br/>**NOTE**<br/>Only users with the ADMIN privilege can set the variables globally. |
+| variable_name          | The name of the variable.                                    |
+| value                  | The value of the variable.                                   |
+
+## Examples
+
+Example 1: Set the `time_zone` to `Asia/Shanghai` within the session.
+
+```Plain
+mysql> SET time_zone = "Asia/Shanghai";
+Query OK, 0 rows affected (0.00 sec)
+```
+
+Example 2: Set the `exec_mem_limit` to `2147483648` globally.
+
+```Plain
+mysql> SET GLOBAL exec_mem_limit = 2147483648;
+Query OK, 0 rows affected (0.00 sec)
+```
+
+Example 3: Set multiple global variables. Add the `GLOBAL` keyword before each variable.
+
+```Plain
+mysql> SET 
+       GLOBAL exec_mem_limit = 2147483648,
+       GLOBAL time_zone = "Asia/Shanghai";
+Query OK, 0 rows affected (0.00 sec)
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/config_vars/SHOW_VARIABLES.md b/docs/en/sql-reference/sql-statements/cluster-management/config_vars/SHOW_VARIABLES.md
new file mode 100644
index 00000000000000..9f4105a3bd3ee7
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/config_vars/SHOW_VARIABLES.md
@@ -0,0 +1,95 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW VARIABLES
+
+## Description
+
+Shows the system variables of StarRocks. For details about system variables, see [System Variables](../../../System_variable.md).
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```SQL
+SHOW [ GLOBAL | SESSION ] VARIABLES
+    [ LIKE <pattern> | WHERE <expr> ]
+```
+
+## Parameters
+
+| **Parameter**          | **Description**                                              |
+| ---------------------- | ------------------------------------------------------------ |
+| Modifier:<ul><li>GLOBAL</li><li>SESSION</li></ul> | <ul><li>With a `GLOBAL` modifier, the statement displays global system variable values. These are the values used to initialize the corresponding session variables for new connections to StarRocks. If a variable has no global value, no value is displayed.</li><li>With a `SESSION` modifier, the statement displays the system variable values that are in effect for the current connection. If a variable has no session value, the global value is displayed. `LOCAL` is a synonym for `SESSION`.</li><li>If no modifier is present, the default is `SESSION`.</li></ul> |
+| pattern                | The pattern used to match the variable by the variable name with the LIKE clause. You can use the % wildcard in this parameter. |
+| expr                   | The expression used to match the variable by the variable name `variable_name` or the variable value `value` with the WHERE clause. |
+
+## Return value
+
+| **Return**    | **Description**            |
+| ------------- | -------------------------- |
+| Variable_name | The name of the variable.  |
+| Value         | The value of the variable. |
+
+## Examples
+
+Example 1: Show a variable by exactly matching the variable name with the LIKE clause.
+
+```Plain
+mysql> SHOW VARIABLES LIKE 'wait_timeout';
++---------------+-------+
+| Variable_name | Value |
++---------------+-------+
+| wait_timeout  | 28800 |
++---------------+-------+
+1 row in set (0.01 sec)
+```
+
+Example 2: Show variables by approximately matching the variable name with the LIKE clause and the wildcard (%).
+
+```Plain
+mysql> SHOW VARIABLES LIKE '%imeou%';
++------------------------------------+-------+
+| Variable_name                      | Value |
++------------------------------------+-------+
+| interactive_timeout                | 3600  |
+| net_read_timeout                   | 60    |
+| net_write_timeout                  | 60    |
+| new_planner_optimize_timeout       | 3000  |
+| query_delivery_timeout             | 300   |
+| query_queue_pending_timeout_second | 300   |
+| query_timeout                      | 300   |
+| tx_visible_wait_timeout            | 10    |
+| wait_timeout                       | 28800 |
++------------------------------------+-------+
+9 rows in set (0.00 sec)
+```
+
+Example 3: Show a variable by exactly matching the variable name with the WHERE clause.
+
+```Plain
+mysql> show variables where variable_name = 'wait_timeout';
++---------------+-------+
+| Variable_name | Value |
++---------------+-------+
+| wait_timeout  | 28800 |
++---------------+-------+
+1 row in set (0.17 sec)
+```
+
+Example 4: Show a variable by exactly matching the value of the variable with the WHERE clause.
+
+```Plain
+mysql> show variables where value = '28800';
++---------------+-------+
+| Variable_name | Value |
++---------------+-------+
+| wait_timeout  | 28800 |
++---------------+-------+
+1 row in set (0.70 sec)
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/config_vars/_category_.yml b/docs/en/sql-reference/sql-statements/cluster-management/config_vars/_category_.yml
new file mode 100644
index 00000000000000..2df228a8dabd84
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/config_vars/_category_.yml
@@ -0,0 +1,6 @@
+position: 20 # float position is supported
+label: 'Configuration variables'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/file/CREATE_FILE.md b/docs/en/sql-reference/sql-statements/cluster-management/file/CREATE_FILE.md
new file mode 100644
index 00000000000000..aa76dda2a4d0a7
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/file/CREATE_FILE.md
@@ -0,0 +1,66 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE FILE
+
+You can execute the CREATE FILE statement to create a file. After a file is created, the file is uploaded and persisted in StarRocks. In a database, only an admin user can create and delete files, and all users who have permission to access the database can use the files that belong to the database.
+
+:::tip
+
+This operation requires the SYSTEM-level FILE privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Basic concepts
+
+**File**: refers to the file that is created and saved in StarRocks. After a file is created and stored in StarRocks, StarRocks assigns a unique ID to the file. You can find a file based on the database name, catalog, and file name.
+
+## Syntax
+
+```SQL
+CREATE FILE "file_name" [IN database]
+[properties]
+```
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                              |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| file_name     | Yes          | The name of the file.                                        |
+| database      | No           | The database to which the file belongs. If you do not specify this parameter, this parameter defaults to the name of the database that you access in the current session. |
+| properties    | Yes          | The properties of the file. The following table describes the configuration items of properties. |
+
+**Configuration items of** **`properties`**
+
+| **Configuration item** | **Required** | **Description**                                              |
+| ---------------------- | ------------ | ------------------------------------------------------------ |
+| url                    | Yes          | The URL from which you can download the file. Only an unauthenticated HTTP URL is supported. After the file is stored in StarRocks, the URL is no longer needed. |
+| catalog                | Yes          | The category to which the file belongs. You can specify a catalog based on your business requirements. However, in some situations, you must set this parameter to a specific catalog. For example, if you load data from Kafka, StarRocks searches for files in the catalog from the Kafka data source. |
+| MD5                    | No           | The message-digest algorithm that is used to check a file. If you specify this parameter, StarRocks checks the file after the file is downloaded. |
+
+## Examples
+
+- Create a file named  **test.pem** under the category named kafka.
+
+```SQL
+CREATE FILE "test.pem"
+PROPERTIES
+(
+    "url" = "https://starrocks-public.oss-cn-xxxx.aliyuncs.com/key/test.pem",
+    "catalog" = "kafka"
+);
+```
+
+- Create a file named **client.key** under the category named my_catalog.
+
+```SQL
+CREATE FILE "client.key"
+IN my_database
+PROPERTIES
+(
+    "url" = "http://test.bj.bcebos.com/kafka-key/client.key",
+    "catalog" = "my_catalog",
+    "md5" = "b5bb901bf10f99205b39a46ac3557dd9"
+);
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/file/DROP_FILE.md b/docs/en/sql-reference/sql-statements/cluster-management/file/DROP_FILE.md
new file mode 100644
index 00000000000000..a1861521072a95
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/file/DROP_FILE.md
@@ -0,0 +1,44 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP FILE
+
+## Description
+
+You can execute the DROP FILE statement to delete a file. When you use this statement to delete a file, the file is deleted both in frontend (FE) memory and in Berkeley DB Java Edition (BDBJE).
+
+:::tip
+
+This operation requires the SYSTEM-level FILE privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```SQL
+DROP FILE "file_name" [FROM database]
+[properties]
+```
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                              |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| file_name     | Yes          | The name of the file.                                        |
+| database      | No           | The database to which a file belongs.                        |
+| properties    | Yes          | The properties of the file. The following table describes the configuration items of properties. |
+
+**Configuration items of** **`properties`**
+
+| **Configuration items** | **Required** | **Description**                       |
+| ----------------------- | ------------ | ------------------------------------- |
+| catalog                 | Yes          | The category to which a file belongs. |
+
+## Examples
+
+Delete a file named **ca.pem**.
+
+```SQL
+DROP FILE "ca.pem" properties("catalog" = "kafka");
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/file/SHOW_FILE.md b/docs/en/sql-reference/sql-statements/cluster-management/file/SHOW_FILE.md
new file mode 100644
index 00000000000000..1e261fa02b5d49
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/file/SHOW_FILE.md
@@ -0,0 +1,41 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW FILE
+
+You can execute the SHOW FILE statement to view the information about a file stored in a database.
+
+:::tip
+
+Users with any privilege on the database to which a file belongs can perform this operation. If a file belongs to a database, all users that have access to this database can use this file.
+
+:::
+
+## Syntax
+
+```SQL
+SHOW FILE [FROM database]
+```
+
+The file information returned by this statement is as follows:
+
+- `FileId`: the globally unique ID of the file.
+
+- `DbName`: the database to which the file belongs.
+
+- `Catalog`: the category to which the file belongs.
+
+- `FileName`: the name of the file.
+
+- `FileSize`: the size of the file. The unit is bytes.
+
+- `MD5`: the message-digest algorithm that is used to check the file.
+
+## Examples
+
+View the file stored in `my_database`.
+
+```SQL
+SHOW FILE FROM my_database;
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/file/_category_.yml b/docs/en/sql-reference/sql-statements/cluster-management/file/_category_.yml
new file mode 100644
index 00000000000000..d7b3513ec3f3d3
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/file/_category_.yml
@@ -0,0 +1,6 @@
+position: 60 # float position is supported
+label: 'File'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/ADD_BACKEND_BLACKLIST.md b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/ADD_BACKEND_BLACKLIST.md
new file mode 100644
index 00000000000000..e9163a750652bb
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/ADD_BACKEND_BLACKLIST.md
@@ -0,0 +1,49 @@
+---
+displayed_sidebar: docs
+---
+
+# ADD BACKEND BLACKLIST
+
+## Description
+
+Adds a BE node to the BE Blacklist. You can manually add BE nodes to the blacklist to forbid the usage of the nodes in query execution, thereby avoiding frequent query failures or other unexpected behaviors caused by failed connections to the BE nodes.
+
+This feature is supported from v3.3.0 onwards. For more information, see [Manage BE Blacklist](../../../../administration/management/BE_blacklist.md).
+
+:::note
+
+Only users with the SYSTEM-level BLACKLIST privilege can perform this operation.
+
+:::
+
+By default, StarRocks can automatically manage the BE Blacklist, adding the BE nodes that have lost connection to the blacklist and removing them from the blacklist when the connection is reestablished. However, StarRocks will not remove the BE node from the blacklist if the node is manually blacklisted.
+
+## Syntax
+
+```SQL
+ADD BACKEND BLACKLIST <be_id>[, ...]
+```
+
+## Parameters
+
+`be_id`: ID of the BE node to be blacklisted. You can obtain the BE ID by executing [SHOW BACKENDS](SHOW_BACKENDS.md).
+
+## Examples
+
+```SQL
+-- Obtain BE ID.
+SHOW BACKENDS\G
+*************************** 1. row ***************************
+            BackendId: 10001
+                   IP: xxx.xx.xx.xxx
+                   ...
+-- Add BE to the blacklist.
+ADD BACKEND BLACKLIST 10001;
+```
+
+## Relevant SQLs
+
+- [DELETE BACKEND BLACKLIST](./DELETE_BACKEND_BLACKLIST.md)
+- [SHOW BACKEND BLACKLIST](./SHOW_BACKEND_BLACKLIST.md)
+- [SHOW BACKENDS](SHOW_BACKENDS.md)
+
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md
new file mode 100644
index 00000000000000..f65f8a593fd356
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md
@@ -0,0 +1,210 @@
+---
+displayed_sidebar: docs
+---
+
+# ALTER SYSTEM
+
+## Description
+
+Manages FE, BE, CN, Broker nodes, and metadata snapshots in a cluster.
+
+> **NOTE**
+>
+> Only the `cluster_admin` role has the privilege to perform this operation.
+
+## Syntax and parameters
+
+### FE
+
+- Add a Follower FE.
+
+  ```SQL
+  ALTER SYSTEM ADD FOLLOWER "<fe_host>:<edit_log_port>"[, ...]
+  ```
+
+  You can check the status of the new Follower FE by executing `SHOW PROC '/frontends'\G`.
+
+- Drop a Follower FE.
+
+  ```SQL
+  ALTER SYSTEM DROP FOLLOWER "<fe_host>:<edit_log_port>"[, ...]
+  ```
+
+- Add an Observer FE.
+
+  ```SQL
+  ALTER SYSTEM ADD OBSERVER "<fe_host>:<edit_log_port>"[, ...]
+  ```
+
+  You can check the status of the new Observer FE by executing `SHOW PROC '/frontends'\G`.
+
+- Drop an Observer FE.
+
+  ```SQL
+  ALTER SYSTEM DROP OBSERVER "<fe_host>:<edit_log_port>"[, ...]
+  ```
+
+| **Parameter**      | **Required** | **Description**                                                     |
+| ------------------ | ------------ | ------------------------------------------------------------------- |
+| fe_host            | Yes          | The host name or IP address of the FE instance. Use the value of configuration item `priority_networks` if your instance has multiple IP addresses. |
+| edit_log_port      | Yes          | BDB JE communication port of the FE node. Default: `9010`.          |
+
+### BE
+
+- Add a BE node.
+
+  ```SQL
+  ALTER SYSTEM ADD BACKEND "<be_host>:<heartbeat_service_port>"[, ...]
+  ```
+
+  You can check the status of the new BE by executing [SHOW BACKENDS](SHOW_BACKENDS.md).
+
+- Drop a BE node.
+
+  > **NOTE**
+  >
+  > You cannot drop the BE node that stores the tablets of single-replica tables.
+
+  ```SQL
+  ALTER SYSTEM DROP BACKEND "<be_host>:<heartbeat_service_port>"[, ...]
+  ```
+
+- Decommission a BE node.
+
+  ```SQL
+  ALTER SYSTEM DECOMMISSION BACKEND "<be_host>:<heartbeat_service_port>"[, ...]
+  ```
+
+  Unlike dropping a BE node, which is removing it forcibly from the cluster, decommissioning a BE means removing it safely. It is an asynchronous operation. When a BE is decommissioned, the data on the BE is first migrated to other BEs, and then the BE is removed from the cluster. Data loading and query will not be affected during the data migration. You can check whether the operation is successful using [SHOW BACKENDS](SHOW_BACKENDS.md). If the operation is successful, the decommissioned BE will not be returned. If the operation fails, the BE will still be online. You can manually cancel the operation using [CANCEL DECOMMISSION](CANCEL_DECOMMISSION.md).
+
+| **Parameter**          | **Required** | **Description**                                                                            |
+| ---------------------- | ------------ | ------------------------------------------------------------------------------------------ |
+| be_host                | Yes          | The host name or IP address of the BE instance. Use the value of configuration item `priority_networks` if your instance has multiple IP addresses.|
+| heartbeat_service_port | Yes          | BE heartbeat service port. BE uses this port to receive heartbeat from FE. Default: `9050`.|
+
+### CN
+
+- Add a CN node.
+
+  ```SQL
+  ALTER SYSTEM ADD COMPUTE NODE "<cn_host>:<heartbeat_service_port>"[, ...]
+  ```
+
+  You can check the status of the new CN by executing [SHOW COMPUTE NODES](SHOW_COMPUTE_NODES.md).
+
+- Drop a CN node.
+
+  ```SQL
+  ALTER SYSTEM DROP COMPUTE NODE "<cn_host>:<heartbeat_service_port>"[, ...]
+  ```
+
+> **NOTE**
+>
+> You cannot decommission a CN node using the `ALTER SYSTEM DECOMMISSION` command.
+
+| **Parameter**          | **Required** | **Description**                                                                            |
+| ---------------------- | ------------ | ------------------------------------------------------------------------------------------ |
+| cn_host                | Yes          | The host name or IP address of the CN instance. Use the value of configuration item `priority_networks` if your instance has multiple IP addresses.|
+| heartbeat_service_port | Yes          | CN heartbeat service port. CN uses this port to receive heartbeat from FE. Default: `9050`.|
+
+### Broker
+
+- Add Broker nodes. You can use Broker nodes to load data from HDFS or cloud storage into StarRocks. For more information, see [Load data from HDFS](../../../../loading/hdfs_load.md) or [Load data from cloud storage](../../../../loading/cloud_storage_load.md).
+
+  ```SQL
+  ALTER SYSTEM ADD BROKER <broker_name> "<broker_host>:<broker_ipc_port>"[, ...]
+  ```
+
+  You can add multiple Broker nodes with one SQL. Each `<broker_host>:<broker_ipc_port>` pair represents one Broker node. And they share a common `broker_name`. You can check the status of the new Broker node by executing [SHOW BROKER](SHOW_BROKER.md).
+
+- Drop Broker nodes.
+
+> **CAUTION**
+>
+> Dropping a Broker node terminates the tasks currently running on it.
+
+  - Drop one or multiple Broker nodes with the same `broker_name`.
+
+    ```SQL
+    ALTER SYSTEM DROP BROKER <broker_name> "<broker_host>:<broker_ipc_port>"[, ...]
+    ```
+
+  - Drop all Broker nodes with the same `broker_name`.
+
+    ```SQL
+    ALTER SYSTEM DROP ALL BROKER <broker_name>
+    ```
+
+| **Parameter**   | **Required** | **Description**                                                              |
+| --------------- | ------------ | ---------------------------------------------------------------------------- |
+| broker_name     | Yes          | The name of the Broker node(s). Multiple Broker nodes can use the same name. |
+| broker_host     | Yes          | The host name or IP address of the Broker instance. Use the value of configuration item `priority_networks` if your instance has multiple IP addresses.|
+| broker_ipc_port | Yes          | The thrift server port on the Broker node. The Broker node uses it to receive requests from FE or BE. Default: `8000`. |
+
+### Create image
+
+Create an image file. An image file is a snapshot of the FE metadata.
+
+```SQL
+ALTER SYSTEM CREATE IMAGE
+```
+
+Creating an image is an asynchronous operation on the Leader FE. You can check the start time and end time of the operation in the FE log file **fe.log**. A log like `triggering a new checkpoint manually...` indicates that the image creation has started, and a log like `finished save image...` indicates the image has been created.
+
+## Usage notes
+
+- Adding and dropping FE, BE, CN, or Broker nodes are synchronous operations. You cannot cancel the node dropping operations.
+- You cannot drop the FE node in a single-FE cluster.
+- You cannot directly drop the Leader FE node in a multi-FE cluster. To drop it, you must first restart it. After StarRocks elects a new Leader FE, you can then drop the previous one.
+- You cannot drop BE nodes if the number of the remained BE nodes is less than the number of data replicas. For example, if you have three BE nodes in your cluster and you store your data in three replicas, you cannot drop any of the BE nodes. And if you have four BE nodes and three replicas, you can drop one BE node.
+- The difference between dropping and decommissioning a BE node is that, when you drop a BE node, StarRocks removes it forcibly from the cluster and make up the dropped tablets after the removal, and when you decommission a BE node, StarRocks first migrates the tablets on the decommissioned BE node to others, and then removes the node.
+
+## Examples
+
+Example 1: Add a Follower FE node.
+
+```SQL
+ALTER SYSTEM ADD FOLLOWER "x.x.x.x:9010";
+```
+
+Example 2: Drop two Observer FE nodes simultaneously.
+
+```SQL
+ALTER SYSTEM DROP OBSERVER "x.x.x.x:9010","x.x.x.x:9010";
+```
+
+Example 3: Add a BE node.
+
+```SQL
+ALTER SYSTEM ADD BACKEND "x.x.x.x:9050";
+```
+
+Example 4: Drop two BE nodes simultaneously.
+
+```SQL
+ALTER SYSTEM DROP BACKEND "x.x.x.x:9050", "x.x.x.x:9050";
+```
+
+Example 5: Decommission two BE nodes simultaneously.
+
+```SQL
+ALTER SYSTEM DECOMMISSION BACKEND "x.x.x.x:9050", "x.x.x.x:9050";
+```
+
+Example 6: Add two Broker nodes with the same `broker_name` - `hdfs`.
+
+```SQL
+ALTER SYSTEM ADD BROKER hdfs "x.x.x.x:8000", "x.x.x.x:8000";
+```
+
+Example 7: Drop two Broker nodes from `amazon_s3`.
+
+```SQL
+ALTER SYSTEM DROP BROKER amazon_s3 "x.x.x.x:8000", "x.x.x.x:8000";
+```
+
+Example 8: Drop all Broker nodes in `amazon_s3`.
+
+```SQL
+ALTER SYSTEM DROP ALL BROKER amazon_s3;
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/CANCEL_DECOMMISSION.md b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/CANCEL_DECOMMISSION.md
new file mode 100644
index 00000000000000..279437ddf19a26
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/CANCEL_DECOMMISSION.md
@@ -0,0 +1,29 @@
+---
+displayed_sidebar: docs
+---
+
+# CANCEL DECOMMISSION
+
+## Description
+
+This statement is used to undo a node decommission.
+
+:::tip
+
+Only the `cluster_admin` role has the privilege to perform this operation. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+Syntax:
+
+```sql
+CANCEL DECOMMISSION BACKEND "<host>:<heartbeat_port>"[,"<host>:<heartbeat_port>"...]
+```
+
+## Examples
+
+1. Cancel decommission of two nodes.
+
+    ```sql
+    CANCEL DECOMMISSION BACKEND "host1:port", "host2:port";
+    ```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/DELETE_BACKEND_BLACKLIST.md b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/DELETE_BACKEND_BLACKLIST.md
new file mode 100644
index 00000000000000..72af3a3f8a9669
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/DELETE_BACKEND_BLACKLIST.md
@@ -0,0 +1,40 @@
+---
+displayed_sidebar: docs
+---
+
+# DELETE BACKEND BLACKLIST
+
+## Description
+
+Removes a BE node from the BE Blacklist. Please note that StarRocks will not remove the BE nodes that are manually blacklisted by users.
+
+This feature is supported from v3.3.0 onwards. For more information, see [Manage BE Blacklist](../../../../administration/management/BE_blacklist.md).
+
+:::note
+
+Only users with the SYSTEM-level BLACKLIST privilege can perform this operation.
+
+:::
+
+## Syntax
+
+```SQL
+DELETE BACKEND BLACKLIST <be_id>[, ...]
+```
+
+## Parameters
+
+`be_id`: ID of the BE node to be removed from the blacklist. You can obtain the ID of the blacklisted BE by executing [SHOW BACKEND BLACKLIST](./SHOW_BACKEND_BLACKLIST.md).
+
+## Examples
+
+```SQL
+DELETE BACKEND BLACKLIST 10001;
+```
+
+## Relevant SQLs
+
+- [ADD BACKEND BLACKLIST](./ADD_BACKEND_BLACKLIST.md)
+- [SHOW BACKEND BLACKLIST](./SHOW_BACKEND_BLACKLIST.md)
+- [SHOW BACKENDS](SHOW_BACKENDS.md)
+
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/KILL.md b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/KILL.md
new file mode 100644
index 00000000000000..7c63a6188e268e
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/KILL.md
@@ -0,0 +1,43 @@
+---
+displayed_sidebar: docs
+---
+
+# KILL
+
+## Description
+
+Terminates a connection or a query currently being performed by threads executing within StarRocks.
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```SQL
+KILL [ CONNECTION | QUERY ] <processlist_id>
+```
+
+## Parameters
+
+| **Parameter**            | **Description**                                              |
+| ------------------------ | ------------------------------------------------------------ |
+| Modifier:<ul><li>CONNECTION</li><li>QUERY</li></ul> | <ul><li>With a `CONNECTION` modifier, the KILL statement terminates the connection associated with the given `processlist_id`, after terminating any statement the connection is executing.</li><li>With a `QUERY` modifier, the KILL statement terminates the statement the connection is currently executing, but leaves the connection itself intact.</li><li>If no modifier is present, the default is `CONNECTION`.</li></ul> |
+| processlist_id           | The ID of the thread you want to terminate. You can get the IDs of the threads that are being executed using [SHOW PROCESSLIST](SHOW_PROCESSLIST.md). |
+
+## Examples
+
+```Plain
+mysql> SHOW FULL PROCESSLIST;
++------+------+---------------------+--------+---------+---------------------+------+-------+-----------------------+-----------+
+| Id   | User | Host                | Db     | Command | ConnectionStartTime | Time | State | Info                  | IsPending |
++------+------+---------------------+--------+---------+---------------------+------+-------+-----------------------+-----------+
+|   20 | root | xxx.xx.xxx.xx:xxxxx | sr_hub | Query   | 2023-01-05 16:30:19 |    0 | OK    | show full processlist | false     |
++------+------+---------------------+--------+---------+---------------------+------+-------+-----------------------+-----------+
+1 row in set (0.01 sec)
+
+mysql> KILL 20;
+Query OK, 0 rows affected (0.00 sec)
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKENDS.md b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKENDS.md
new file mode 100644
index 00000000000000..6d686bd7d5e0cd
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKENDS.md
@@ -0,0 +1,76 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW BACKENDS
+
+## Description
+
+Shows the information of all BE nodes in the cluster.
+
+:::tip
+
+Only users with the SYSTEM-level OPERATE privilege or the `cluster_admin` role can perform this operation.
+
+:::
+
+## Syntax
+
+```SQL
+SHOW BACKENDS
+```
+
+## Return
+
+```SQL
++-----------+-----------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+--------------------+--------------------------------------------------------+-------------------+-------------+----------+-------------------+------------+------------+------------------+----------+
+| BackendId | IP        | HeartbeatPort | BePort | HttpPort | BrpcPort | LastStartTime       | LastHeartbeat       | Alive | SystemDecommissioned | ClusterDecommissioned | TabletNum | DataUsedCapacity | AvailCapacity | TotalCapacity | UsedPct | MaxDiskUsedPct | ErrMsg | Version            | Status                                                 | DataTotalCapacity | DataUsedPct | CpuCores | NumRunningQueries | MemUsedPct | CpuUsedPct | DataCacheMetrics | Location |
++-----------+-----------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+--------------------+--------------------------------------------------------+-------------------+-------------+----------+-------------------+------------+------------+------------------+----------+
+```
+
+| **Return**            | **Description**                                              |
+| --------------------- | ------------------------------------------------------------ |
+| BackendId             | The ID of the BE node.                                       |
+| IP                    | The IP address of the BE node.                               |
+| HeartbeatPort         | The heartbeat port of the BE node. It is used to receive heartbeats from the FE node. |
+| BePort                | Thrift server port of the BE node. It is used to receive requests from the FE node. |
+| HttpPort              | HTTP server port of the BE node. It is used to access the BE node via web page. |
+| BrpcPort              | bRPC port of the BE node. It is used for communication across BE nodes. |
+| LastStartTime         | The last time when the BE node is started.                   |
+| LastHeartbeat         | The last time when the FE node sends a heartbeat and the BE responds.|
+| Alive                 | Whether the BE node is alive or not.<ul><li>`true`: the BE node is alive.</li><li>`false`: the BE node is not alive. </li></ul> |
+| SystemDecommissioned  | Whether the BE node is decommissioned or not. Before it is decommissioned, the BE node migrates the data to other BE nodes. Data loading and queries are not affected during migration.<ul><li>`true`: the cluster has marked the BE node as decommissioned. The data could be successfully migrated or migrating.</li><li>`false`: the BE node is running.</li></ul> |
+| ClusterDecommissioned | This parameter is used for system compatibility.             |
+| TabletNum             | The number of tablets on the BE node.                        |
+| DataUsedCapacity      | The storage capacity occupied by the data file.              |
+| AvailCapacity         | Available storage capacity in the BE node.                   |
+| TotalCapacity         | The total storage capacity. It is equivalent to `DataUsedCapacity` + `AvailCapacity` + Storage capacity occupied by the non-data files. |
+| UsedPct               | The percentage of the used storage capacity.                 |
+| MaxDiskUsedPct        | If a BE node has multiple directories to store data, this parameter shows the maximum percentage of the used storage capacity among all directories. |
+| ErrMsg                | The error message returned when the BE node fails to receive the heartbeat from the FE node. |
+| Version               | The StarRocks version of cluster.                            |
+| Status                | The last time when the BE node reports the tablet number to the FE node. Displayed in JSON format. |
+| DataTotalCapacity     | It is equivalent to `DataUsedCapacity` + `AvailCapacity`. It indicates the sum of the storage capacity occupied by the data file and the available storage capacity in the BE node. |
+| DataUsedPct           |  It is equivalent to `DataUsedCapacity`/`DataTotalCapacity`. It indicates the proportion of the storage capacity occupied by the data file to the sum of the data-occupied storage capacity and the available storage capacity. |
+| CpuCores              | The number of CPU cores in the BE node.                      |
+| NumRunningQueries     | The number of running queries on the BE node.                |
+| MemUsedPct            | The percentage of used memory.                               |
+| CpuUsedPct            | The percentage of used CPU cores.                            |
+| DataCacheMetrics      | The status of Data Cache:<ul><li>`Disabled`: Disabled</li><li>`Normal`: Normal </li><li>`Abnormal`: Abnormal </li><li>`Updating`: Data Cache is being updating, for example, scaling. </li></ul>                      |
+| Location              | The label of the BE node. For more information, see [Add labels on BEs](../../../../administration/management/resource_management/be_label.md).                     |
+
+## Example
+
+View the information of all BE nodes in the cluster.
+
+```Plain
+SHOW BACKENDS;
+
++-----------+---------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+----------------------+--------------------------------------------------------+-------------------+-------------+----------+
+| BackendId | IP      | HeartbeatPort | BePort | HttpPort | BrpcPort | LastStartTime       | LastHeartbeat       | Alive | SystemDecommissioned | ClusterDecommissioned | TabletNum | DataUsedCapacity | AvailCapacity | TotalCapacity | UsedPct | MaxDiskUsedPct | ErrMsg | Version              | Status                                                 | DataTotalCapacity | DataUsedPct | CpuCores |
++-----------+---------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+----------------------+--------------------------------------------------------+-------------------+-------------+----------+
+| 10002     | x.x.x.x | 9254          | 9260   | 8238     | 8260     | 2022-09-08 14:37:10 | 2022-09-08 15:14:21 | true  | false                | false                 | 21753     | 25.122 GB        | 1.088 TB      | 1.968 TB      | 44.72 % | 44.72 %        |        | MAIN-RELEASE-d094052 | {"lastSuccessReportTabletsTime":"2022-09-08 15:14:13"} | 1.113 TB          | 2.20 %      | 16       |
+| 10003     | x.x.x.x | 9254          | 9260   | 8238     | 8260     | 2022-09-08 14:37:20 | 2022-09-08 15:14:21 | true  | false                | false                 | 21754     | 25.121 GB        | 1.169 TB      | 1.968 TB      | 40.61 % | 40.61 %        |        | MAIN-RELEASE-d094052 | {"lastSuccessReportTabletsTime":"2022-09-08 15:14:22"} | 1.194 TB          | 2.06 %      | 16       |
+| 10004     | x.x.x.x | 9254          | 9260   | 8238     | 8260     | 2022-09-08 14:37:39 | 2022-09-08 15:14:21 | true  | false                | false                 | 21754     | 25.112 GB        | 1.172 TB      | 1.968 TB      | 40.46 % | 40.46 %        |        | MAIN-RELEASE-d094052 | {"lastSuccessReportTabletsTime":"2022-09-08 15:13:42"} | 1.197 TB          | 2.05 %      | 16       |
++-----------+---------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+----------------------+--------------------------------------------------------+-------------------+-------------+----------+
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKEND_BLACKLIST.md b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKEND_BLACKLIST.md
new file mode 100644
index 00000000000000..24efc571b4ef6c
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKEND_BLACKLIST.md
@@ -0,0 +1,50 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW BACKEND BLACKLIST
+
+## Description
+
+Shows the BE nodes in the BE Blacklist.
+
+This feature is supported from v3.3.0 onwards. For more information, see [Manage BE Blacklist](../../../../administration/management/BE_blacklist.md).
+
+:::note
+
+Only users with the SYSTEM-level BLACKLIST privilege can perform this operation.
+
+:::
+
+## Syntax
+
+```SQL
+SHOW BACKEND BLACKLIST
+```
+
+## Return value
+
+| **Return**                   | **Description**                                              |
+| ---------------------------- | ------------------------------------------------------------ |
+| AddBlackListType             | How the BE node was added to the blacklist. `MANUAL` indicates it is manually blacklisted by the user. `AUTO` indicates it is automatically blacklisted by StarRocks. |
+| LostConnectionTime           | For the `MANUAL` type, it indicates the time when the BE node was manually added to the blacklist.<br />For the `AUTO` type, it indicates the time when the last successful connection was established. |
+| LostConnectionNumberInPeriod | The number of disconnections detected within `CheckTimePeriod(s)`. |
+| CheckTimePeriod(s)           | The interval at which StarRocks checks the connection status of the blacklisted BE nodes. Its value is evaluated to the value you specified for the FE configuration item `black_host_history_sec`. Unit: Seconds. |
+
+## Examples
+
+```SQL
+SHOW BACKEND BLACKLIST;
++-----------+------------------+---------------------+------------------------------+--------------------+
+| BackendId | AddBlackListType | LostConnectionTime  | LostConnectionNumberInPeriod | CheckTimePeriod(s) |
++-----------+------------------+---------------------+------------------------------+--------------------+
+| 10001     | MANUAL           | 2024-04-28 11:52:09 | 0                            | 5                  |
++-----------+------------------+---------------------+------------------------------+--------------------+
+```
+
+## Relevant SQLs
+
+- [ADD BACKEND BLACKLIST](./ADD_BACKEND_BLACKLIST.md)
+- [DELETE BACKEND BLACKLIST](./DELETE_BACKEND_BLACKLIST.md)
+- [SHOW BACKENDS](SHOW_BACKENDS.md)
+
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BROKER.md b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BROKER.md
new file mode 100644
index 00000000000000..295fb782689e09
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BROKER.md
@@ -0,0 +1,28 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW BROKER
+
+## Description
+
+This statement is used to view broker that currently exists.
+
+:::tip
+
+Only users with the SYSTEM-level OPERATE privilege or the `cluster_admin` role can perform this operation.
+
+:::
+
+## Syntax
+
+```sql
+SHOW BROKER
+```
+
+Note:
+
+1. LastStartTime represents the latest BE start-up time.
+2. LastHeartbeat represents the latest heartbeat.
+3. Alive indicates whether the node survives.
+4. ErrMsg is used to display error messages when the heartbeat fails.
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_COMPUTE_NODES.md b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_COMPUTE_NODES.md
new file mode 100644
index 00000000000000..3fd0ce00d485a0
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_COMPUTE_NODES.md
@@ -0,0 +1,88 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW COMPUTE NODES
+
+## Description
+
+Shows the information of all CN nodes in the cluster.
+
+:::tip
+
+Only users with the SYSTEM-level OPERATE privilege or the `cluster_admin` role can perform this operation.
+
+:::
+
+## Syntax
+
+```SQL
+SHOW COMPUTE NODES
+```
+
+## Return
+
+```SQL
++---------------+--------------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+--------+--------------------+----------+-------------------+------------+------------+----------------+-------------+----------+-------------------+-----------+
+| ComputeNodeId | IP           | HeartbeatPort | BePort | HttpPort | BrpcPort | LastStartTime       | LastHeartbeat       | Alive | SystemDecommissioned | ClusterDecommissioned | ErrMsg | Version            | CpuCores | NumRunningQueries | MemUsedPct | CpuUsedPct | HasStoragePath | StarletPort | WorkerId | WarehouseName     | TabletNum |
++---------------+--------------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+--------+--------------------+----------+-------------------+------------+------------+----------------+-------------+----------+-------------------+-----------+
+```
+
+The following table describes the parameters returned by this statement.
+
+| **Parameter**        | **Description**                                                   |
+| -------------------- | ----------------------------------------------------------------- |
+| ComputeNodeId        | The ID of the CN node.                                            |
+| IP                   | The IP address of the CN node.                                    |
+| HeartbeatPort        | The heartbeat port of the CN node. It is used to receive heartbeats from the FE node. |
+| BePort               | Thrift server port of the CN node. It is used to receive requests from the FE node. |
+| HttpPort             | HTTP server port of the CN node. It is used to access the CN node via web page. |
+| BrpcPort             | bRPC port of the CN node. It is used for communication across CN nodes. |
+| LastStartTime        | The last time at which the CN node starts.                        |
+| LastHeartbeat        | The last time at which the CN node sends a heartbeat.             |
+| Alive                | Whether the CN node is alive or not.<ul><li>`true`: the CN node is alive.</li><li>`false`: the CN node is not alive. </li></ul> |
+| SystemDecommissioned | If the value of the parameter is `true`, the CN node is removed from your StarRocks cluster. |
+| ClusterDecommissioned | This parameter is used for system compatibility.                 |
+| ErrMsg               | The error message if the CN node fails to send a heartbeat.       |
+| Version              | The StarRocks version of the CN node.                             |
+| CpuCores             | The number of CPU cores in the CN node.                           |
+| NumRunningQueries    | The number of running queries on the CN node.                     |
+| MemUsedPct           | The percentage of used memory.                                    |
+| CpuUsedPct           | The percentage of used CPU cores.                                 |
+| HasStoragePath       | Whether the CN node has storage paths configured.                 |
+| StarletPort          | The `starlet_port` of the CN node. It is an extra agent service port. |
+| WorkerId             | The ID of the CN node for internal scheduling.                    |
+| WarehouseName        | The name of the warehouse to which the CN node belongs. The value is always `default_warehouse`. |
+| TabletNum            | The number of tablets (of cached data) on the CN node.            |
+
+## Example
+
+View the information of all CN nodes in the cluster.
+
+```Plain
+MySQL > SHOW COMPUTE NODES\G
+*************************** 1. row ***************************
+        ComputeNodeId: 10001
+                   IP: x.x.x.x
+        HeartbeatPort: 9050
+               BePort: 9060
+             HttpPort: 8040
+             BrpcPort: 8060
+        LastStartTime: 2024-05-14 15:45:34
+        LastHeartbeat: 2024-05-14 15:47:59
+                Alive: true
+ SystemDecommissioned: false
+ClusterDecommissioned: false
+               ErrMsg: 
+              Version: 3.3.0-rc01-3b8cb0c
+             CpuCores: 4
+    NumRunningQueries: 0
+           MemUsedPct: 1.95 %
+           CpuUsedPct: 0.0 %
+       HasStoragePath: true
+          StarletPort: 8167
+             WorkerId: 1
+        WarehouseName: default_warehouse
+            TabletNum: 58
+1 row in set (0.00 sec)
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_FRONTENDS.md b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_FRONTENDS.md
new file mode 100644
index 00000000000000..38cbd5b44c9dd6
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_FRONTENDS.md
@@ -0,0 +1,31 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW FRONTENDS
+
+## Description
+
+This statement is used to view FE nodes.
+
+:::tip
+
+Only users with the SYSTEM-level OPERATE privilege or the `cluster_admin` role can perform this operation.
+
+:::
+
+## Syntax
+
+```sql
+SHOW FRONTENDS
+```
+
+Note:
+
+1. Name represents the name of FE node in BDBJE.
+2. Join being true means this node has already joined the cluster. But it does not mean that the node is still in the cluster, as it may be missing.
+3. Alive indicates whether the node survives.
+4. ReplayedJournalId represents the maximum metadata log ID that the node has currently replayed.
+5. LastHeartbeat is the latest heartbeat.
+6. IsHelper indicates whether the node is a helper node from BDBJE.
+7. ErrMsg is used to display error messages when the heartbeat fails.
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROC.md b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROC.md
new file mode 100644
index 00000000000000..91b73c7194995e
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROC.md
@@ -0,0 +1,444 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW PROC
+
+## Description
+
+Shows certain indicators of the StarRocks cluster.
+
+:::tip
+
+This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```SQL
+SHOW PROC { '/backends' | '/compute_nodes' | '/dbs' 
+          | '/jobs' | '/statistic' | '/tasks' | '/frontends' 
+          | '/brokers' | '/resources' | '/load_error_hub' 
+          | '/transactions' | '/monitor' | '/current_queries' 
+          | '/current_backend_instances' | '/cluster_balance' 
+          | '/routine_loads' | '/colocation_group' | '/catalog' }
+```
+
+## Parameters
+
+| **Parameter**                | **Description**                                              |
+| ---------------------------- | ------------------------------------------------------------ |
+| '/backends'                  | Shows the information of BE nodes in the cluster.            |
+| '/compute_nodes'             | Shows the information of CN nodes in the cluster.            |
+| '/dbs'                       | Shows the information of databases in the cluster.           |
+| '/jobs'                      | Shows the information of jobs in the cluster.                |
+| '/statistic'                 | Shows the statistics of each database in the cluster.        |
+| '/tasks'                     | Shows the total number of all generic tasks and the failed tasks in the cluster. |
+| '/frontends'                 | Shows the information of FE nodes in the cluster.            |
+| '/brokers'                   | Shows the information of Broker nodes in the cluster.        |
+| '/resources'                 | Shows the information of resources in the cluster.           |
+| '/load_error_hub'            | Shows the configuration of the cluster's Load Error Hub, which is used to manage error messages of loading jobs. |
+| '/transactions'              | Shows the information of transactions in the cluster.        |
+| '/monitor'                   | Shows the monitoring information in the cluster.             |
+| '/current_queries'           | Shows the information of running queries on the current FE node. |
+| '/current_backend_instances' | Shows the BE nodes that are processing requests in the cluster. |
+| '/cluster_balance'           | Shows the load balance information in the cluster.           |
+| '/routine_loads'             | Shows the information of Routine Load in the cluster.        |
+| '/colocation_group'          | Shows the information of Colocate Join groups in the cluster. |
+| '/catalog'                   | Shows the information of catalogs in the cluster.            |
+
+## Examples
+
+Example 1: Shows the information of BE nodes in the cluster.
+
+```Plain
+mysql> SHOW PROC '/backends'\G
+*************************** 1. row ***************************
+            BackendId: 10004
+                   IP: xxx.xx.92.200
+        HeartbeatPort: 9354
+               BePort: 9360
+             HttpPort: 8338
+             BrpcPort: 8360
+        LastStartTime: 2023-04-21 09:56:10
+        LastHeartbeat: 2023-04-21 09:56:10
+                Alive: true
+ SystemDecommissioned: false
+ClusterDecommissioned: false
+            TabletNum: 2199
+     DataUsedCapacity: 0.000 
+        AvailCapacity: 584.578 GB
+        TotalCapacity: 1.968 TB
+              UsedPct: 71.00 %
+       MaxDiskUsedPct: 71.00 %
+               ErrMsg: 
+              Version: BRANCH-3.0-RELEASE-8eb8705
+               Status: {"lastSuccessReportTabletsTime":"N/A"}
+    DataTotalCapacity: 584.578 GB
+          DataUsedPct: 0.00 %
+             CpuCores: 16
+    NumRunningQueries: 0
+           MemUsedPct: 0.52 %
+           CpuUsedPct: 0.0 %
+```
+
+| **Return**            | **Description**                                              |
+| --------------------- | ------------------------------------------------------------ |
+| BackendId             | ID of the BE node.                                           |
+| IP                    | IP address of the BE node.                                   |
+| HeartbeatPort         | Heartbeat service port of the BE node.                       |
+| BePort                | Thrift Server port of the BE node.                           |
+| HttpPort              | HTTP Server port of the BE node.                             |
+| BrpcPort              | bRPC port of the BE node.                                    |
+| LastStartTime         | The last time when the BE node was started.                  |
+| LastHeartbeat         | The last time when the BE node received a heartbeat.         |
+| Alive                 | If the BE node is alive.                                     |
+| SystemDecommissioned  | If the BE node is decommissioned.                            |
+| ClusterDecommissioned | If the BE node is decommissioned within the cluster.         |
+| TabletNum             | Number of tablets in the BE node.                            |
+| DataUsedCapacity      | Storage capacity that is used for data in the BE node.       |
+| AvailCapacity         | Available storage capacity in the BE node.                   |
+| TotalCapacity         | Total storage capacity in the BE node.                       |
+| UsedPct               | Percentage at which the storage capacity is used in the BE node. |
+| MaxDiskUsedPct        | The maximum percentage at which the storage capacity is used in the BE node. |
+| ErrMsg                | Error messages in the BE node.                               |
+| Version               | StarRocks version of the BE node.                            |
+| Status                | Status information of the BE node, including the last time when the BE node reported tablets. |
+| DataTotalCapacity     | Total of used and available data storage capacity. The sum of `DataUsedCapacity` and `AvailCapacity`. |
+| DataUsedPct           | Percentage at which the data storage takes up the total data capacity (DataUsedCapacity/DataTotalCapacity). |
+| CpuCores              | Number of CPU cores in the BE node.                          |
+| NumRunningQueries     | The number of queries currently running in the cluster.      |
+| MemUsedPct            | The current memory usage percentage.                                 |
+| CpuUsedPct            | The current CPU usage percentage.                                    |
+
+Example 2: Shows the information of databases in the cluster.
+
+```Plain
+mysql> SHOW PROC '/dbs';
++---------+------------------------+----------+----------------+--------------------------+---------------------+
+| DbId    | DbName                 | TableNum | Quota          | LastConsistencyCheckTime | ReplicaQuota        |
++---------+------------------------+----------+----------------+--------------------------+---------------------+
+| 1       | information_schema     | 22       | 8388608.000 TB | NULL                     | 9223372036854775807 |
+| 840997  | tpcds_100g             | 25       | 1024.000 GB    | NULL                     | 1073741824          |
+| 1275196 | _statistics_           | 3        | 8388608.000 TB | 2022-09-06 23:00:58      | 9223372036854775807 |
+| 1286207 | tpcds_n                | 24       | 8388608.000 TB | NULL                     | 9223372036854775807 |
+| 1381289 | test                   | 6        | 8388608.000 TB | 2022-01-14 23:10:18      | 9223372036854775807 |
+| 6186781 | test_stddev            | 1        | 8388608.000 TB | 2022-09-06 23:00:58      | 9223372036854775807 |
++---------+------------------------+----------+----------------+--------------------------+---------------------+
+```
+
+| **Return**               | **Description**                                   |
+| ------------------------ | ------------------------------------------------- |
+| DbId                     | Database ID.                                      |
+| DbName                   | Database name.                                    |
+| TableNum                 | Number of tables in the database.                 |
+| Quota                    | Storage quota of the database.                    |
+| LastConsistencyCheckTime | The last time when consistency check is executed. |
+| ReplicaQuota             | Data replica quota of the database.               |
+
+Example 3: Shows the information of jobs in the cluster.
+
+```Plain
+mysql> SHOW PROC '/jobs';
++-------+--------------------------------------+
+| DbId  | DbName                               |
++-------+--------------------------------------+
+| 10005 | default_cluster:_statistics_         |
+| 0     | default_cluster:information_schema   |
+| 12711 | default_cluster:starrocks_audit_db__ |
++-------+--------------------------------------+
+3 rows in set (0.00 sec)
+
+mysql> SHOW PROC '/jobs/10005';
++---------------+---------+---------+----------+-----------+-------+
+| JobType       | Pending | Running | Finished | Cancelled | Total |
++---------------+---------+---------+----------+-----------+-------+
+| load          | 0       | 0       | 3        | 0         | 3     |
+| rollup        | 0       | 0       | 0        | 0         | 0     |
+| schema_change | 0       | 0       | 0        | 0         | 0     |
+| export        | 0       | 0       | 0        | 0         | 0     |
++---------------+---------+---------+----------+-----------+-------+
+4 rows in set (0.00 sec)
+```
+
+| **Return** | **Description**                    |
+| ---------- | ---------------------------------- |
+| DbId       | Database ID.                       |
+| DbName     | Database name.                     |
+| JobType    | Job type.                          |
+| Pending    | Number of jobs that are pending.   |
+| Running    | Number of jobs that are running.   |
+| Finished   | Number of jobs that are finished.  |
+| Cancelled  | Number of jobs that are cancelled. |
+| Total      | Total number of jobs.              |
+
+Example 4: Shows the statistics of each database in the cluster.
+
+```Plain
+mysql> SHOW PROC '/statistic';
++--------+----------------------------------------------------------+----------+--------------+----------+-----------+------------+--------------------+-----------------------+------------------+---------------------+
+| DbId   | DbName                                                   | TableNum | PartitionNum | IndexNum | TabletNum | ReplicaNum | UnhealthyTabletNum | InconsistentTabletNum | CloningTabletNum | ErrorStateTabletNum |
++--------+----------------------------------------------------------+----------+--------------+----------+-----------+------------+--------------------+-----------------------+------------------+---------------------+
+| 10004  | _statistics_                                             | 3        | 3            | 3        | 30        | 60         | 0                  | 0                     | 0                | 0                   |
+| 1      | information_schema                                       | 0        | 0            | 0        | 0         | 0          | 0                  | 0                     | 0                | 0                   |
+| 92498  | stream_load_test_db_03afc714_b1cb_11ed_a82c_00163e237e98 | 0        | 0            | 0        | 0         | 0          | 0                  | 0                     | 0                | 0                   |
+| 92542  | stream_load_test_db_79876e92_b1da_11ed_b50e_00163e237e98 | 1        | 1            | 1        | 3         | 3          | 0                  | 0                     | 0                | 0                   |
+| 115476 | testdb                                                   | 0        | 0            | 0        | 0         | 0          | 0                  | 0                     | 0                | 0                   |
+| 10002  | zq_test                                                  | 8        | 8            | 8        | 5043      | 7063       | 0                  | 0                     | 0                | 2                   |
+| Total  | 6                                                        | 12       | 12           | 12       | 5076      | 7126       | 0                  | 0                     | 0                | 2                   |
++--------+----------------------------------------------------------+----------+--------------+----------+-----------+------------+--------------------+-----------------------+------------------+---------------------+
+7 rows in set (0.01 sec)
+
+mysql> show proc '/statistic/10002';
++------------------+---------------------+----------------+-------------------+
+| UnhealthyTablets | InconsistentTablets | CloningTablets | ErrorStateTablets |
++------------------+---------------------+----------------+-------------------+
+| []               | []                  | []             | [116703, 116706]  |
++------------------+---------------------+----------------+-------------------+
+```
+
+| **Return**            | **Description**                                              |
+| --------------------- | ------------------------------------------------------------ |
+| DbId                  | Database ID.                                                 |
+| DbName                | Database name.                                               |
+| TableNum              | Number of tables in the database.                            |
+| PartitionNum          | Number of partitions in the database.                        |
+| IndexNum              | Number of indexes in the database.                           |
+| TabletNum             | Number of tablets in the database.                           |
+| ReplicaNum            | Number of replicas in the database.                          |
+| UnhealthyTabletNum    | Number of unfinished (unhealthy) tablets in the database during data redistribution. |
+| InconsistentTabletNum | Number of inconsistent tablets in the database.              |
+| CloningTabletNum      | Number of tablets that are being cloned in the database.     |
+| ErrorStateTabletNum   | In a Primary Key type table, the number of tablets in Error state. |
+| ErrorStateTablets     | In a Primary Key type table, the IDs of the tablets in Error state. |
+
+Example 5: Shows the total number of all generic tasks and the failed tasks in the cluster.
+
+```Plain
+mysql> SHOW PROC '/tasks';
++-------------------------+-----------+----------+
+| TaskType                | FailedNum | TotalNum |
++-------------------------+-----------+----------+
+| CREATE                  | 0         | 0        |
+| DROP                    | 0         | 0        |
+| PUSH                    | 0         | 0        |
+| CLONE                   | 0         | 0        |
+| STORAGE_MEDIUM_MIGRATE  | 0         | 0        |
+| ROLLUP                  | 0         | 0        |
+| SCHEMA_CHANGE           | 0         | 0        |
+| CANCEL_DELETE           | 0         | 0        |
+| MAKE_SNAPSHOT           | 0         | 0        |
+| RELEASE_SNAPSHOT        | 0         | 0        |
+| CHECK_CONSISTENCY       | 0         | 0        |
+| UPLOAD                  | 0         | 0        |
+| DOWNLOAD                | 0         | 0        |
+| CLEAR_REMOTE_FILE       | 0         | 0        |
+| MOVE                    | 0         | 0        |
+| REALTIME_PUSH           | 0         | 0        |
+| PUBLISH_VERSION         | 0         | 0        |
+| CLEAR_ALTER_TASK        | 0         | 0        |
+| CLEAR_TRANSACTION_TASK  | 0         | 0        |
+| RECOVER_TABLET          | 0         | 0        |
+| STREAM_LOAD             | 0         | 0        |
+| UPDATE_TABLET_META_INFO | 0         | 0        |
+| ALTER                   | 0         | 0        |
+| INSTALL_PLUGIN          | 0         | 0        |
+| UNINSTALL_PLUGIN        | 0         | 0        |
+| NUM_TASK_TYPE           | 0         | 0        |
+| Total                   | 0         | 0        |
++-------------------------+-----------+----------+
+```
+
+| **Return** | **Description**         |
+| ---------- | ----------------------- |
+| TaskType   | Task type.              |
+| FailedNum  | Number of failed tasks. |
+| TotalNum   | Total number of tasks.  |
+
+Example 6: Shows the information of FE nodes in the cluster.
+
+```Plain
+mysql> SHOW PROC '/frontends';
++----------------------------------+---------------+-------------+----------+-----------+---------+----------+------------+-------+-------+-------------------+---------------+----------+---------------+-----------+---------+
+| Name                             | IP            | EditLogPort | HttpPort | QueryPort | RpcPort | Role     | ClusterId  | Join  | Alive | ReplayedJournalId | LastHeartbeat | IsHelper | ErrMsg        | StartTime | Version |
++----------------------------------+---------------+-------------+----------+-----------+---------+----------+------------+-------+-------+-------------------+---------------+----------+---------------+-----------+---------+
+| xxx.xx.xx.xxx_9009_1600088918395 | xxx.xx.xx.xxx | 9009        | 7390     | 0         | 0       | FOLLOWER | 1747363037 | false | false | 0                 | NULL          | true     | got exception | NULL      | NULL    |
++----------------------------------+---------------+-------------+----------+-----------+---------+----------+------------+-------+-------+-------------------+---------------+----------+---------------+-----------+---------+
+```
+
+| **Return**        | **Description**                                        |
+| ----------------- | ------------------------------------------------------ |
+| Name              | FE node name.                                          |
+| IP                | IP address of the FE node.                             |
+| EditLogPort       | Port for communication between FE nodes.               |
+| HttpPort          | HTTP Server port of the FE node.                       |
+| QueryPort         | MySQL Server port of the FE node.                      |
+| RpcPort           | RPC port of the FE node.                               |
+| Role              | Role of the FE node (Leader, Follower, or Observer).   |
+| ClusterId         | Cluster ID.                                            |
+| Join              | If the FE node has joined a cluster.                   |
+| Alive             | If the FE node is alive.                               |
+| ReplayedJournalId | The largest metadata ID that the FE node has replayed. |
+| LastHeartbeat     | The last time when the FE node sent a heartbeat.       |
+| IsHelper          | If the FE node is the BDBJE helper node.               |
+| ErrMsg            | Error messages in the FE node.                         |
+| StartTime         | Time when the FE node is started.                      |
+| Version           | StarRocks version of the FE node.                      |
+
+Example 7: Shows the information of Broker nodes in the cluster.
+
+```Plain
+mysql> SHOW PROC '/brokers';
++-------------+---------------+------+-------+---------------+---------------------+--------+
+| Name        | IP            | Port | Alive | LastStartTime | LastUpdateTime      | ErrMsg |
++-------------+---------------+------+-------+---------------+---------------------+--------+
+| hdfs_broker | xxx.xx.xx.xxx | 8500 | true  | NULL          | 2022-10-10 16:37:59 |        |
+| hdfs_broker | xxx.xx.xx.xxx | 8500 | true  | NULL          | 2022-10-10 16:37:59 |        |
+| hdfs_broker | xxx.xx.xx.xxx | 8500 | true  | NULL          | 2022-10-10 16:37:59 |        |
++-------------+---------------+------+-------+---------------+---------------------+--------+
+```
+
+| **Return**     | **Description**                                              |
+| -------------- | ------------------------------------------------------------ |
+| Name           | Broker node name.                                            |
+| IP             | IP address of the broker node.                               |
+| Port           | Thrift Server port of the broker node. The port is used to receive requests. |
+| Alive          | If the broker node is alive.                                 |
+| LastStartTime  | The last time when the broker node was started.              |
+| LastUpdateTime | The last time when the broker node was updated.              |
+| ErrMsg         | Error message in the broker node.                            |
+
+Example 8: Shows the information of resources in the cluster.
+
+```Plain
+mysql> SHOW PROC '/resources';
++-------------------------+--------------+---------------------+------------------------------+
+| Name                    | ResourceType | Key                 | Value                        |
++-------------------------+--------------+---------------------+------------------------------+
+| hive_resource_stability | hive         | hive.metastore.uris | thrift://xxx.xx.xxx.xxx:9083 |
+| hive2                   | hive         | hive.metastore.uris | thrift://xxx.xx.xx.xxx:9083  |
++-------------------------+--------------+---------------------+------------------------------+
+```
+
+| **Return**   | **Description** |
+| ------------ | --------------- |
+| Name         | Resource name.  |
+| ResourceType | Resource type.  |
+| Key          | Resource key.   |
+| Value        | Resource value. |
+
+Example 9: Shows the information of transactions in the cluster.
+
+```Plain
+mysql> SHOW PROC '/transactions';
++-------+--------------------------------------+
+| DbId  | DbName                               |
++-------+--------------------------------------+
+| 10005 | default_cluster:_statistics_         |
+| 12711 | default_cluster:starrocks_audit_db__ |
++-------+--------------------------------------+
+2 rows in set (0.00 sec)
+
+mysql> SHOW PROC '/transactions/10005';
++----------+--------+
+| State    | Number |
++----------+--------+
+| running  | 0      |
+| finished | 4      |
++----------+--------+
+2 rows in set (0.00 sec)
+```
+
+| **Return** | **Description**               |
+| ---------- | ----------------------------- |
+| DbId       | Database ID.                  |
+| DbName     | Database name.                |
+| State      | The state of the transaction. |
+| Number     | Number of transactions.       |
+
+Example 10: Shows the monitoring information in the cluster.
+
+```Plain
+mysql> SHOW PROC '/monitor';
++------+------+
+| Name | Info |
++------+------+
+| jvm  |      |
++------+------+
+```
+
+| **Return** | **Description**  |
+| ---------- | ---------------- |
+| Name       | JVM name.        |
+| Info       | JVM information. |
+
+Example 11: Shows the load balance information in the cluster.
+
+```Plain
+mysql> SHOW PROC '/cluster_balance';
++-------------------+--------+
+| Item              | Number |
++-------------------+--------+
+| cluster_load_stat | 1      |
+| working_slots     | 3      |
+| sched_stat        | 1      |
+| priority_repair   | 0      |
+| pending_tablets   | 2001   |
+| running_tablets   | 0      |
+| history_tablets   | 1000   |
++-------------------+--------+
+```
+
+| **Return** | **Description**                                  |
+| ---------- | ------------------------------------------------ |
+| Item       | Sub-command item in `cluster_balance`. <ul><li>cluster_load_stat: The current load status of the cluster.</li><li>working_slots: The number of currently available working slots.</li><li>sched_stat: The current status of the scheduler.</li><li>priority_repair: The number of Tablet repair tasks that are prioritized.</li><li>pending_tablets: The number of Tablets waiting to be processed.</li><li>running_tablets: The number of Tablets currently being repaired.</li><li>history_tablets: The total number of Tablets repaired historically.</li></ul>         |
+| Number     | Number of each sub-command in `cluster_balance`. |
+
+Example 12: Shows the information of Colocate Join groups in the cluster.
+
+```Plain
+mysql> SHOW PROC '/colocation_group';
++-----------------+----------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------+------------+----------------+-------------+----------+
+| GroupId         | GroupName                  | TableIds                                                                                                                                          | BucketsNum | ReplicationNum | DistCols    | IsStable |
++-----------------+----------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------+------------+----------------+-------------+----------+
+| 24010.177354    | 24010_lineitem_str_g1      | 177672                                                                                                                                            | 12         | 1              | varchar(-1) | true     |
+| 24010.182146    | 24010_lineitem_str_g2      | 182144                                                                                                                                            | 192        | 1              | varchar(-1) | true     |
+| 1439318.1735496 | 1439318_group_agent_uid    | 1735677, 1738390                                                                                                                                  | 12         | 2              | bigint(20)  | true     |
+| 24010.37804     | 24010_gsdaf2449s9e         | 37802                                                                                                                                             | 192        | 1              | int(11)     | true     |
+| 174844.175370   | 174844_groupa4             | 175368, 591307, 591362, 591389, 591416                                                                                                            | 12         | 1              | int(11)     | true     |
+| 24010.30587     | 24010_group2               | 30585, 30669                                                                                                                                      | 12         | 1              | int(11)     | true     |
+| 10005.181366    | 10005_lineorder_str_normal | 181364                                                                                                                                            | 192        | 1              | varchar(-1) | true     |
+| 1904968.5973175 | 1904968_groupa2            | 5973173                                                                                                                                           | 12         | 1              | int(11)     | true     |
+| 24010.182535    | 24010_lineitem_str_g3      | 182533                                                                                                                                            | 192        | 1              | varchar(-1) | true     |
++-----------------+----------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------+------------+----------------+-------------+----------+
+```
+
+| **Return**     | **Description**                                 |
+| -------------- | ----------------------------------------------- |
+| GroupId        | Colocate Join Group ID.                         |
+| GroupName      | Colocate Join Group name.                       |
+| TableIds       | IDs of tables in the Colocate Join Group.       |
+| BucketsNum     | Buckets in the Colocate Join Group.             |
+| ReplicationNum | Replications in the Colocate Join Group.        |
+| DistCols       | Distribution column of the Colocate Join Group. |
+| IsStable       | If the Colocate Join Group is stable.           |
+
+Example 13: Shows the information of catalogs in the cluster.
+
+```Plain
+mysql> SHOW PROC '/catalog';
++--------------------------------------------------------------+----------+----------------------+
+| Catalog                                                      | Type     | Comment              |
++--------------------------------------------------------------+----------+----------------------+
+| resource_mapping_inside_catalog_hive_hive2                   | hive     | mapping hive catalog |
+| resource_mapping_inside_catalog_hive_hive_resource_stability | hive     | mapping hive catalog |
+| default_catalog                                              | Internal | Internal Catalog     |
++--------------------------------------------------------------+----------+----------------------+
+```
+
+| **Return** | **Description**           |
+| ---------- | ------------------------- |
+| Catalog    | Catalog name.             |
+| Type       | Catalog type.             |
+| Comment    | Comments for the catalog. |
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROCESSLIST.md b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROCESSLIST.md
new file mode 100644
index 00000000000000..d0ce170886cf19
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROCESSLIST.md
@@ -0,0 +1,58 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW PROCESSLIST
+
+## Description
+
+Lists the operations currently being performed by threads executing within the server. The current version of StarRocks only supports listing queries.
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```SQL
+SHOW [FULL] PROCESSLIST
+```
+
+## Parameter
+
+| Parameter | Required | Description                                                                                                                      |
+| --------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------- |
+| FULL      | No       | If you specify this parameter, the complete SQL statement will be displayed. Otherwise, only the first 100 characters of the statement are displayed. |
+
+## Return
+
+| Return              | Description                                                  |
+| ------------------- | ------------------------------------------------------------ |
+| Id                  | Connection ID.                                               |
+| User                | The name of the user who runs the operation.                 |
+| Host                | The hostname of the client which runs the operation.         |
+| Db                  | The name of the database where the operation is executed.    |
+| Command             | The type of the command.                                     |
+| ConnectionStartTime | Time when the connection starts.                             |
+| Time                | The time (in second) since the operation has entered the current state. |
+| State               | The state of the operation.                                  |
+| Info                | The command that the operation is executing.                 |
+
+## Usage note
+
+If the current user is `root`, this statement lists the operations of all users in the cluster. Otherwise, only operations of the current user are listed.
+
+## Example
+
+Example 1: lists the operations state via the user `root`.
+
+```Plain
+SHOW PROCESSLIST;
++------+------+---------------------+-------+---------+---------------------+------+-------+------------------+
+| Id   | User | Host                | Db    | Command | ConnectionStartTime | Time | State | Info             |
++------+------+---------------------+-------+---------+---------------------+------+-------+------------------+
+|  0   | root | x.x.x.x:xxxx        | tpcds | Query   | 2022-10-09 19:58:25 |    0 | OK    | SHOW PROCESSLIST |
++------+------+---------------------+-------+---------+---------------------+------+-------+------------------+
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_RUNNING_QUERIES.md b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_RUNNING_QUERIES.md
new file mode 100644
index 00000000000000..72d9cd2d37366b
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_RUNNING_QUERIES.md
@@ -0,0 +1,46 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW RUNNING QUERIES
+
+## Description
+
+Shows the information of all queries that are running or pending in the query queue. This feature is supported from v3.1.4 onwards.
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```SQL
+SHOW RUNNING QUERIES
+```
+
+## Return
+
+- `QueryId`: The ID of the query.
+- `ResourceGroupId`: The ID of the resource group that the query hit. When there is no hit on a user-defined resource group, it will be displayed as "-".
+- `StartTime`: The start time of the query.
+- `PendingTimeout`: The time when the PENDING query will time out in the queue.
+- `QueryTimeout`: The time when the query times out.
+- `State`: The queue state of the query, where "PENDING" indicates it is in the queue, and "RUNNING" indicates it is currently executing.
+- `Slots`: The logical resource quantity requested by the query, currently fixed at `1`.
+- `Frontend`: The FE node that initiated the query.
+- `FeStartTime`: The start time of the FE node that initiated the query.
+
+## Example
+
+```Plain
+MySQL [(none)]> SHOW RUNNING QUERIES;
++--------------------------------------+-----------------+---------------------+---------------------+---------------------+-----------+-------+---------------------------------+---------------------+
+| QueryId                              | ResourceGroupId | StartTime           | PendingTimeout      | QueryTimeout        |   State   | Slots | Frontend                        | FeStartTime         |
++--------------------------------------+-----------------+---------------------+---------------------+---------------------+-----------+-------+---------------------------------+---------------------+
+| a46f68c6-3b49-11ee-8b43-00163e10863a | -               | 2023-08-15 16:56:37 | 2023-08-15 17:01:37 | 2023-08-15 17:01:37 |  RUNNING  | 1     | 127.00.00.01_9010_1692069711535 | 2023-08-15 16:37:03 |
+| a6935989-3b49-11ee-935a-00163e13bca3 | 12003           | 2023-08-15 16:56:40 | 2023-08-15 17:01:40 | 2023-08-15 17:01:40 |  RUNNING  | 1     | 127.00.00.02_9010_1692069658426 | 2023-08-15 16:37:03 |
+| a7b5e137-3b49-11ee-8b43-00163e10863a | 12003           | 2023-08-15 16:56:42 | 2023-08-15 17:01:42 | 2023-08-15 17:01:42 |  PENDING  | 1     | 127.00.00.03_9010_1692069711535 | 2023-08-15 16:37:03 |
++--------------------------------------+-----------------+---------------------+---------------------+---------------------+-----------+-------+---------------------------------+---------------------+
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SYNC.md b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SYNC.md
new file mode 100644
index 00000000000000..9ca3cd0c17af01
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/SYNC.md
@@ -0,0 +1,28 @@
+---
+displayed_sidebar: docs
+---
+
+# SYNC
+
+Synchronizes the data consistency among different sessions.
+
+Currently, StarRocks can only guarantee consistency within the same session, that is, only the session that initiated the data write operation can read the latest data immediately after the operation succeeds. If you want to read the latest data immediately from other sessions, you must synchronize the data consistency using the SYNC statement. Generally, there will be a millisecond-level latency among sessions if you do not execute this statement.
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```SQL
+SYNC
+```
+
+## Examples
+
+```Plain
+mysql> SYNC;
+Query OK, 0 rows affected (0.00 sec)
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/_category_.yml b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/_category_.yml
new file mode 100644
index 00000000000000..0586fb776632f3
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/nodes_processes/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: 'Nodes and processes'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/plan_profile/ANALYZE_PROFILE.md b/docs/en/sql-reference/sql-statements/cluster-management/plan_profile/ANALYZE_PROFILE.md
new file mode 100644
index 00000000000000..8434f8ec8ae411
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/plan_profile/ANALYZE_PROFILE.md
@@ -0,0 +1,43 @@
+---
+displayed_sidebar: docs
+---
+
+# ANALYZE PROFILE
+
+## Description
+
+Analyzes a specific query profile on a per-fragment basis, and displays it in a tree structure. For more information about query profile, see [Query Profile Overview](../../../../administration/query_profile_overview.md).
+
+This feature is supported from v3.1 onwards.
+
+> **CAUTION**
+>
+> Only users with the SELECT privilege on a specific table can perform this operation.
+
+## Syntax
+
+```SQL
+ANALYZE PROFILE FROM '<query_id>', [<plan_node_id>[, ...] ]
+```
+
+## Parameters
+
+| **Parameter** | **Description**                                              |
+| ------------- | ------------------------------------------------------------ |
+| query_id      | The ID of the query. You can obtain it using [SHOW PROFILELIST](./SHOW_PROFILELIST.md). |
+| plan_node_id  | The ID of the plan node in the profile. You can specify this parameter to view the detailed metrics of the corresponding plan node(s). If this parameter is not specified, only the summary metrics of all plan nodes are displayed. |
+
+## Examples
+
+Example 1: Querying the Query Profile without specifying node ID.
+
+![img](../../../../_assets/Profile/text_based_profile_without_node_id.jpeg)
+
+Example 2: Querying the Query Profile and specifying node ID as `0`. StarRocks returns all detailed metrics for Node ID `0` and highlights metrics with high usage for easier problem identification.
+
+![img](../../../../_assets/Profile/text_based_profile_with_node_id.jpeg)
+
+## Relevant SQLs
+
+- [SHOW PROFILELIST](./SHOW_PROFILELIST.md)
+- [EXPLAIN ANALYZE](./EXPLAIN_ANALYZE.md)
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN.md b/docs/en/sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN.md
new file mode 100644
index 00000000000000..2761681d61461f
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN.md
@@ -0,0 +1,438 @@
+---
+displayed_sidebar: docs
+---
+
+# EXPLAIN
+
+## Description
+
+Shows the logical or physical execution plans for a query statement. For instructions on how to analyze a query plan, refer to [Plan analysis](../../../../administration/Query_planning.md#plan-analysis).
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```SQL
+EXPLAIN [ LOGICAL | VERBOSE | COSTS ] <query>
+```
+
+:::tip
+
+The level of execution plan detail returned: EXPLAIN LOGICAL < EXPLAIN < EXPLAIN VERBOSE < EXPLAIN COSTS.
+
+In most cases, using EXPLAIN is sufficient. EXPLAIN VERBOSE and EXPLAIN COSTS will print a lot of internal information, which is mainly used for debugging the execution plan.
+
+:::
+
+## Parameters
+
+| **Parameter** | **Description**                                            |
+| ------------- | ---------------------------------------------------------- |
+| LOGICAL       | Shows the simple logical execution plans.                  |
+| VERBOSE       | Shows the detailed logical execution plans, including data types, nullable information, and optimization strategy. |
+| COSTS         | Shows the detailed logical execution plans, including column statisitics. |
+| query         | The query statement whose execution plan you want to view. |
+
+## Return value
+
+Returns the execution plan of the input query statement.
+
+| **Return**     | **Description**                                                                  |
+| -------------- |----------------------------------------------------------------------------------|
+| avgRowSize     | The average size of the scanned data rows.                                       |
+| cardinality    | The total number of data rows in the scanned table.                              |
+| colocate       | Whether the table is in colocate mode.                                           |
+| numNodes       | The number of nodes to scan.                                                     |
+| rollup         | The Rollup materialized view that is used.                                       |
+| preaggregation | The status of preaggregation.                                                    |
+| predicates     | Predicates in the query.                                                         |
+| column statistics | The statictics of the column，sequence: MIN, MAX, NULL numbers，average size，and cardinality. |
+
+## Examples
+
+### EXPLAIN
+
+```Plain
+MySQL tpcds> explain select 
+    sr_customer_sk as ctr_customer_sk, 
+    sr_store_sk as ctr_store_sk, 
+    sum(SR_RETURN_AMT) as ctr_total_return 
+  from 
+    store_returns, 
+    date_dim 
+  where 
+    sr_returned_date_sk = d_date_sk and d_year = 2000 
+  group by 
+    sr_customer_sk, 
+    sr_store_sk
++-----------------------------------------------------------------------------+
+| Explain String                                                              |
++-----------------------------------------------------------------------------+
+| PLAN FRAGMENT 0                                                             |
+|  OUTPUT EXPRS:5: sr_customer_sk | 9: sr_store_sk | 49: sum                  |
+|   PARTITION: UNPARTITIONED                                                  |
+|                                                                             |
+|   RESULT SINK                                                               |
+|                                                                             |
+|   9:EXCHANGE                                                                |
+|                                                                             |
+| PLAN FRAGMENT 1                                                             |
+|  OUTPUT EXPRS:                                                              |
+|   PARTITION: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk            |
+|                                                                             |
+|   STREAM DATA SINK                                                          |
+|     EXCHANGE ID: 09                                                         |
+|     UNPARTITIONED                                                           |
+|                                                                             |
+|   8:AGGREGATE (merge finalize)                                              |
+|   |  output: sum(49: sum)                                                   |
+|   |  group by: 5: sr_customer_sk, 9: sr_store_sk                            |
+|   |                                                                         |
+|   7:EXCHANGE                                                                |
+|                                                                             |
+| PLAN FRAGMENT 2                                                             |
+|  OUTPUT EXPRS:                                                              |
+|   PARTITION: RANDOM                                                         |
+|                                                                             |
+|   STREAM DATA SINK                                                          |
+|     EXCHANGE ID: 07                                                         |
+|     HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                     |
+|                                                                             |
+|   6:AGGREGATE (update serialize)                                            |
+|   |  STREAMING                                                              |
+|   |  output: sum(12: sr_return_amt)                                         |
+|   |  group by: 5: sr_customer_sk, 9: sr_store_sk                            |
+|   |                                                                         |
+|   5:Project                                                                 |
+|   |  <slot 5> : 5: sr_customer_sk                                           |
+|   |  <slot 9> : 9: sr_store_sk                                              |
+|   |  <slot 12> : 12: sr_return_amt                                          |
+|   |                                                                         |
+|   4:HASH JOIN                                                               |
+|   |  join op: INNER JOIN (BROADCAST)                                        |
+|   |  colocate: false, reason:                                               |
+|   |  equal join conjunct: 3: sr_returned_date_sk = 21: d_date_sk            |
+|   |                                                                         |
+|   |----3:EXCHANGE                                                           |
+|   |                                                                         |
+|   0:OlapScanNode                                                            |
+|      TABLE: store_returns                                                   |
+|      PREAGGREGATION: ON                                                     |
+|      PREDICATES: 3: sr_returned_date_sk IS NOT NULL                         |
+|      partitions=1/1                                                         |
+|      rollup: store_returns                                                  |
+|      tabletRatio=10/10                                                      |
+|      tabletList=10241,10243,10245,10247,10249,10251,10253,10255,10257,10259 |
+|      cardinality=277502                                                     |
+|      avgRowSize=20.0                                                        |
+|                                                                             |
+| PLAN FRAGMENT 3                                                             |
+|  OUTPUT EXPRS:                                                              |
+|   PARTITION: RANDOM                                                         |
+|                                                                             |
+|   STREAM DATA SINK                                                          |
+|     EXCHANGE ID: 03                                                         |
+|     UNPARTITIONED                                                           |
+|                                                                             |
+|   2:Project                                                                 |
+|   |  <slot 21> : 21: d_date_sk                                              |
+|   |                                                                         |
+|   1:OlapScanNode                                                            |
+|      TABLE: date_dim                                                        |
+|      PREAGGREGATION: ON                                                     |
+|      PREDICATES: 27: d_year = 2000                                          |
+|      partitions=1/1                                                         |
+|      rollup: date_dim                                                       |
+|      tabletRatio=5/5                                                        |
+|      tabletList=11543,11545,11547,11549,11551                               |
+|      cardinality=362                                                        |
+|      avgRowSize=8.0                                                         |
++-----------------------------------------------------------------------------+
+79 rows in set
+```
+
+### EXPLAIN LOGICAL
+
+```Plain
+MySQL tpcds> explain logical select 
+    sr_customer_sk as ctr_customer_sk, 
+    sr_store_sk as ctr_store_sk, 
+    sum(SR_RETURN_AMT) as ctr_total_return 
+  from 
+    store_returns, 
+    date_dim 
+  where 
+    sr_returned_date_sk = d_date_sk and d_year = 2000 
+  group by 
+    sr_customer_sk, 
+    sr_store_sk
+ 
++---------------------------------------------------------------------------------------------------------------------------------+
+| Explain String                                                                                                                  |
++---------------------------------------------------------------------------------------------------------------------------------+
+| - Output => [5:sr_customer_sk, 9:sr_store_sk, 49:sum]                                                                           |
+|     - AGGREGATE(GLOBAL) [5:sr_customer_sk, 9:sr_store_sk]                                                                       |
+|             Estimates: {row: 49728, cpu: 795660.58, memory: 795660.58, network: 0.00, cost: 8405375.45}                         |
+|             49:sum := sum(49:sum)                                                                                               |
+|         - EXCHANGE(SHUFFLE) [5, 9]                                                                                              |
+|                 Estimates: {row: 49728, cpu: 79566.06, memory: 0.00, network: 0.00, cost: 6416223.99}                           |
+|             - AGGREGATE(LOCAL) [5:sr_customer_sk, 9:sr_store_sk]                                                                |
+|                     Estimates: {row: 49728, cpu: 119349.09, memory: 79566.06, network: 0.00, cost: 6376440.96}                  |
+|                     49:sum := sum(12:sr_return_amt)                                                                             |
+|                 - HASH/INNER JOIN [3:sr_returned_date_sk = 21:d_date_sk] => [5:sr_customer_sk, 9:sr_store_sk, 12:sr_return_amt] |
+|                         Estimates: {row: 49728, cpu: 6744977.39, memory: 1446.51, network: 0.00, cost: 6157634.30}              |
+|                     - SCAN [store_returns] => [3:sr_returned_date_sk, 5:sr_customer_sk, 9:sr_store_sk, 12:sr_return_amt]        |
+|                             Estimates: {row: 277502, cpu: 5550040.00, memory: 0.00, network: 0.00, cost: 2775020.00}            |
+|                             partitionRatio: 1/1, tabletRatio: 10/10                                                             |
+|                             predicate: 3:sr_returned_date_sk IS NOT NULL                                                        |
+|                     - EXCHANGE(BROADCAST)                                                                                       |
+|                             Estimates: {row: 361, cpu: 1446.51, memory: 1446.51, network: 1446.51, cost: 7232.57}               |
+|                         - SCAN [date_dim] => [21:d_date_sk]                                                                     |
+|                                 Estimates: {row: 361, cpu: 2893.03, memory: 0.00, network: 0.00, cost: 1446.51}                 |
+|                                 partitionRatio: 1/1, tabletRatio: 5/5                                                           |
+|                                 predicate: 27:d_year = 2000                                                                     |
++---------------------------------------------------------------------------------------------------------------------------------+
+21 rows in set
+```
+
+### EXPLAIN VERBOSE
+
+```Plain
+MySQL tpcds> explain verbose select 
+    sr_customer_sk as ctr_customer_sk, 
+    sr_store_sk as ctr_store_sk, 
+    sum(SR_RETURN_AMT) as ctr_total_return 
+  from 
+    store_returns, 
+    date_dim 
+  where 
+    sr_returned_date_sk = d_date_sk and d_year = 2000 
+  group by 
+    sr_customer_sk, 
+    sr_store_sk
+ 
++---------------------------------------------------------------------------------------------------------------------------------------------------------+
+| Explain String                                                                                                                                          |
++---------------------------------------------------------------------------------------------------------------------------------------------------------+
+| RESOURCE GROUP: default_wg                                                                                                                              |
+|                                                                                                                                                         |
+| PLAN FRAGMENT 0(F04)                                                                                                                                    |
+|   Fragment Cost: 0.0                                                                                                                                    |
+|   Output Exprs:5: sr_customer_sk | 9: sr_store_sk | 49: sum                                                                                             |
+|   Input Partition: UNPARTITIONED                                                                                                                        |
+|   RESULT SINK                                                                                                                                           |
+|                                                                                                                                                         |
+|   9:EXCHANGE                                                                                                                                            |
+|      cardinality: 49729                                                                                                                                 |
+|                                                                                                                                                         |
+| PLAN FRAGMENT 1(F03)                                                                                                                                    |
+|   Fragment Cost: 2028934.4876271961                                                                                                                     |
+|                                                                                                                                                         |
+|   Input Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                  |
+|   OutPut Partition: UNPARTITIONED                                                                                                                       |
+|   OutPut Exchange Id: 09                                                                                                                                |
+|                                                                                                                                                         |
+|   8:AGGREGATE (merge finalize)                                                                                                                          |
+|   |  aggregate: sum[([49: sum, DECIMAL128(38,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true]         |
+|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |                                                                                                                                                     |
+|   7:EXCHANGE                                                                                                                                            |
+|      distribution type: SHUFFLE                                                                                                                         |
+|      partition exprs: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                       |
+|      cardinality: 49729                                                                                                                                 |
+|                                                                                                                                                         |
+| PLAN FRAGMENT 2(F00)                                                                                                                                    |
+|   Fragment Cost: 6376440.959353934                                                                                                                      |
+|                                                                                                                                                         |
+|   Input Partition: RANDOM                                                                                                                               |
+|   OutPut Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                 |
+|   OutPut Exchange Id: 07                                                                                                                                |
+|                                                                                                                                                         |
+|   6:AGGREGATE (update serialize)                                                                                                                        |
+|   |  STREAMING                                                                                                                                          |
+|   |  aggregate: sum[([12: sr_return_amt, DECIMAL64(7,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true] |
+|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |                                                                                                                                                     |
+|   5:Project                                                                                                                                             |
+|   |  output columns:                                                                                                                                    |
+|   |  5 <-> [5: sr_customer_sk, INT, true]                                                                                                               |
+|   |  9 <-> [9: sr_store_sk, INT, true]                                                                                                                  |
+|   |  12 <-> [12: sr_return_amt, DECIMAL64(7,2), true]                                                                                                   |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |                                                                                                                                                     |
+|   4:HASH JOIN                                                                                                                                           |
+|   |  join op: INNER JOIN (BROADCAST)                                                                                                                    |
+|   |  equal join conjunct: [3: sr_returned_date_sk, INT, true] = [21: d_date_sk, INT, false]                                                             |
+|   |  build runtime filters:                                                                                                                             |
+|   |  - filter_id = 0, build_expr = (21: d_date_sk), remote = false                                                                                      |
+|   |  output columns: 5, 9, 12                                                                                                                           |
+|   |  can local shuffle: true                                                                                                                            |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |                                                                                                                                                     |
+|   |----3:EXCHANGE                                                                                                                                       |
+|   |       distribution type: BROADCAST                                                                                                                  |
+|   |       cardinality: 362                                                                                                                              |
+|   |                                                                                                                                                     |
+|   0:OlapScanNode                                                                                                                                        |
+|      table: store_returns, rollup: store_returns                                                                                                        |
+|      preAggregation: on                                                                                                                                 |
+|      Predicates: 3: sr_returned_date_sk IS NOT NULL                                                                                                     |
+|      partitionsRatio=1/1, tabletsRatio=10/10                                                                                                            |
+|      tabletList=10241,10243,10245,10247,10249,10251,10253,10255,10257,10259                                                                             |
+|      actualRows=287514, avgRowSize=20.0                                                                                                                 |
+|      cardinality: 277502                                                                                                                                |
+|      probe runtime filters:                                                                                                                             |
+|      - filter_id = 0, probe_expr = (3: sr_returned_date_sk)                                                                                             |
+|                                                                                                                                                         |
+| PLAN FRAGMENT 3(F01)                                                                                                                                    |
+|   Fragment Cost: 1446.5148514851485                                                                                                                     |
+|                                                                                                                                                         |
+|   Input Partition: RANDOM                                                                                                                               |
+|   OutPut Partition: UNPARTITIONED                                                                                                                       |
+|   OutPut Exchange Id: 03                                                                                                                                |
+|                                                                                                                                                         |
+|   2:Project                                                                                                                                             |
+|   |  output columns:                                                                                                                                    |
+|   |  21 <-> [21: d_date_sk, INT, false]                                                                                                                 |
+|   |  cardinality: 362                                                                                                                                   |
+|   |                                                                                                                                                     |
+|   1:OlapScanNode                                                                                                                                        |
+|      table: date_dim, rollup: date_dim                                                                                                                  |
+|      preAggregation: on                                                                                                                                 |
+|      Predicates: [27: d_year, INT, false] = 2000                                                                                                        |
+|      partitionsRatio=1/1, tabletsRatio=5/5                                                                                                              |
+|      tabletList=11543,11545,11547,11549,11551                                                                                                           |
+|      actualRows=73049, avgRowSize=8.0                                                                                                                   |
+|      cardinality: 362                                                                                                                                   |
++---------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
+
+### EXPLAIN COSTS
+
+```Plain
++---------------------------------------------------------------------------------------------------------------------------------------------------------+
+| Explain String                                                                                                                                          |
++---------------------------------------------------------------------------------------------------------------------------------------------------------+
+| PLAN FRAGMENT 0(F04)                                                                                                                                    |
+|   Output Exprs:5: sr_customer_sk | 9: sr_store_sk | 49: sum                                                                                             |
+|   Input Partition: UNPARTITIONED                                                                                                                        |
+|   RESULT SINK                                                                                                                                           |
+|                                                                                                                                                         |
+|   9:EXCHANGE                                                                                                                                            |
+|      cardinality: 49729                                                                                                                                 |
+|                                                                                                                                                         |
+| PLAN FRAGMENT 1(F03)                                                                                                                                    |
+|                                                                                                                                                         |
+|   Input Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                  |
+|   OutPut Partition: UNPARTITIONED                                                                                                                       |
+|   OutPut Exchange Id: 09                                                                                                                                |
+|                                                                                                                                                         |
+|   8:AGGREGATE (merge finalize)                                                                                                                          |
+|   |  aggregate: sum[([49: sum, DECIMAL128(38,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true]         |
+|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |  column statistics:                                                                                                                                 |
+|   |  * sr_customer_sk-->[1.0, 100000.0, 2.010867271218169E-5, 4.0, 49728.786461450894] ESTIMATE                                                         |
+|   |  * sr_store_sk-->[1.0, 10.0, 0.14285714285714285, 4.0, 6.0] ESTIMATE                                                                                |
+|   |  * sum-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                                    |
+|   |                                                                                                                                                     |
+|   7:EXCHANGE                                                                                                                                            |
+|      distribution type: SHUFFLE                                                                                                                         |
+|      partition exprs: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                       |
+|      cardinality: 49729                                                                                                                                 |
+|                                                                                                                                                         |
+| PLAN FRAGMENT 2(F00)                                                                                                                                    |
+|                                                                                                                                                         |
+|   Input Partition: RANDOM                                                                                                                               |
+|   OutPut Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                 |
+|   OutPut Exchange Id: 07                                                                                                                                |
+|                                                                                                                                                         |
+|   6:AGGREGATE (update serialize)                                                                                                                        |
+|   |  STREAMING                                                                                                                                          |
+|   |  aggregate: sum[([12: sr_return_amt, DECIMAL64(7,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true] |
+|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |  column statistics:                                                                                                                                 |
+|   |  * sr_customer_sk-->[1.0, 100000.0, 2.010867271218169E-5, 4.0, 49728.786461450894] ESTIMATE                                                         |
+|   |  * sr_store_sk-->[1.0, 10.0, 0.14285714285714285, 4.0, 6.0] ESTIMATE                                                                                |
+|   |  * sum-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                                    |
+|   |                                                                                                                                                     |
+|   5:Project                                                                                                                                             |
+|   |  output columns:                                                                                                                                    |
+|   |  5 <-> [5: sr_customer_sk, INT, true]                                                                                                               |
+|   |  9 <-> [9: sr_store_sk, INT, true]                                                                                                                  |
+|   |  12 <-> [12: sr_return_amt, DECIMAL64(7,2), true]                                                                                                   |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |  column statistics:                                                                                                                                 |
+|   |  * sr_customer_sk-->[1.0, 100000.0, 0.034836564480338346, 4.0, 49728.786461450894] ESTIMATE                                                         |
+|   |  * sr_store_sk-->[1.0, 10.0, 0.034996556689413386, 4.0, 6.0] ESTIMATE                                                                               |
+|   |  * sr_return_amt-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                          |
+|   |                                                                                                                                                     |
+|   4:HASH JOIN                                                                                                                                           |
+|   |  join op: INNER JOIN (BROADCAST)                                                                                                                    |
+|   |  equal join conjunct: [3: sr_returned_date_sk, INT, true] = [21: d_date_sk, INT, false]                                                             |
+|   |  build runtime filters:                                                                                                                             |
+|   |  - filter_id = 0, build_expr = (21: d_date_sk), remote = false                                                                                      |
+|   |  output columns: 5, 9, 12                                                                                                                           |
+|   |  can local shuffle: true                                                                                                                            |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |  column statistics:                                                                                                                                 |
+|   |  * sr_returned_date_sk-->[2450820.0, 2452822.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                               |
+|   |  * sr_customer_sk-->[1.0, 100000.0, 0.034836564480338346, 4.0, 49728.786461450894] ESTIMATE                                                         |
+|   |  * sr_store_sk-->[1.0, 10.0, 0.034996556689413386, 4.0, 6.0] ESTIMATE                                                                               |
+|   |  * sr_return_amt-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                          |
+|   |  * d_date_sk-->[2450820.0, 2452822.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                                         |
+|   |                                                                                                                                                     |
+|   |----3:EXCHANGE                                                                                                                                       |
+|   |       distribution type: BROADCAST                                                                                                                  |
+|   |       cardinality: 362                                                                                                                              |
+|   |                                                                                                                                                     |
+|   0:OlapScanNode                                                                                                                                        |
+|      table: store_returns, rollup: store_returns                                                                                                        |
+|      preAggregation: on                                                                                                                                 |
+|      Predicates: 3: sr_returned_date_sk IS NOT NULL                                                                                                     |
+|      partitionsRatio=1/1, tabletsRatio=10/10                                                                                                            |
+|      tabletList=10241,10243,10245,10247,10249,10251,10253,10255,10257,10259                                                                             |
+|      actualRows=287514, avgRowSize=20.0                                                                                                                 |
+|      cardinality: 277502                                                                                                                                |
+|      probe runtime filters:                                                                                                                             |
+|      - filter_id = 0, probe_expr = (3: sr_returned_date_sk)                                                                                             |
+|      column statistics:                                                                                                                                 |
+|      * sr_returned_date_sk-->[2450820.0, 2452822.0, 0.0, 4.0, 2018.0] ESTIMATE                                                                          |
+|      * sr_customer_sk-->[1.0, 100000.0, 0.034836564480338346, 4.0, 86524.0] ESTIMATE                                                                    |
+|      * sr_store_sk-->[1.0, 10.0, 0.034996556689413386, 4.0, 6.0] ESTIMATE                                                                               |
+|      * sr_return_amt-->[0.0, 16917.12, 0.034878301578357924, 8.0, 113968.0] ESTIMATE                                                                    |
+|                                                                                                                                                         |
+| PLAN FRAGMENT 3(F01)                                                                                                                                    |
+|                                                                                                                                                         |
+|   Input Partition: RANDOM                                                                                                                               |
+|   OutPut Partition: UNPARTITIONED                                                                                                                       |
+|   OutPut Exchange Id: 03                                                                                                                                |
+|                                                                                                                                                         |
+|   2:Project                                                                                                                                             |
+|   |  output columns:                                                                                                                                    |
+|   |  21 <-> [21: d_date_sk, INT, false]                                                                                                                 |
+|   |  cardinality: 362                                                                                                                                   |
+|   |  column statistics:                                                                                                                                 |
+|   |  * d_date_sk-->[2415022.0, 2488070.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                                         |
+|   |                                                                                                                                                     |
+|   1:OlapScanNode                                                                                                                                        |
+|      table: date_dim, rollup: date_dim                                                                                                                  |
+|      preAggregation: on                                                                                                                                 |
+|      Predicates: [27: d_year, INT, false] = 2000                                                                                                        |
+|      partitionsRatio=1/1, tabletsRatio=5/5                                                                                                              |
+|      tabletList=11543,11545,11547,11549,11551                                                                                                           |
+|      actualRows=73049, avgRowSize=8.0                                                                                                                   |
+|      cardinality: 362                                                                                                                                   |
+|      column statistics:                                                                                                                                 |
+|      * d_date_sk-->[2415022.0, 2488070.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                                         |
+|      * d_year-->[2000.0, 2000.0, 0.0, 4.0, 202.0] ESTIMATE                                                                                              |
++---------------------------------------------------------------------------------------------------------------------------------------------------------+
+114 rows in set
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN_ANALYZE.md b/docs/en/sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN_ANALYZE.md
new file mode 100644
index 00000000000000..b9a4ce54016c82
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN_ANALYZE.md
@@ -0,0 +1,44 @@
+---
+displayed_sidebar: docs
+---
+
+# EXPLAIN ANALYZE
+
+## Description
+
+Executes the specified SQL statement, and shows the query profile of this statement. For more information about query profile, see [Query Profile Overview](../../../../administration/query_profile_overview.md).
+
+This feature is supported from v3.1 onwards.
+
+> **CAUTION**
+>
+> Only users with the SELECT or INSERT privilege on a specific table can perform this operation.
+
+## Syntax
+
+```SQL
+EXPLAIN ANALYZE <statement>
+```
+
+## Parameters
+
+`statement`: the SQL statement of which to show the query profile. Both [SELECT](../../table_bucket_part_index/SELECT.md) and [INSERT INTO](../../loading_unloading/INSERT.md) are supported.
+
+## Usage notes
+
+Please note that when you analyze the profiles of an INSERT INTO statement, no data will actually be inserted. By default, the transaction is aborted, ensuring that no unintended changes are made to the data in the process of profile analysis.
+
+## Examples
+
+Example 1: Simulate and analyze a SELECT statement. The query result are discarded.
+
+![img](../../../../_assets/Profile/text_based_explain_analyze_select.jpeg)
+
+Example 2: Simulate and analyze an INSERT INTO statement. The loading transaction will be aborted.
+
+![img](../../../../_assets/Profile/text_based_explain_analyze_insert.jpeg)
+
+## Relevant SQLs
+
+- [SHOW PROFILELIST](./SHOW_PROFILELIST.md)
+- [ANALYZE PROFILE](./EXPLAIN_ANALYZE.md)
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/plan_profile/SHOW_PROFILELIST.md b/docs/en/sql-reference/sql-statements/cluster-management/plan_profile/SHOW_PROFILELIST.md
new file mode 100644
index 00000000000000..e12ca9f924773e
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/plan_profile/SHOW_PROFILELIST.md
@@ -0,0 +1,46 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW PROFILELIST
+
+## Description
+
+Lists the query profile records cached in your StarRocks cluster. For more information about query profile, see [Query Profile Overview](../../../../administration/query_profile_overview.md).
+
+This feature is supported from v3.1 onwards.
+
+No privilege is required to perform this operation.
+
+## Syntax
+
+```SQL
+SHOW PROFILELIST [LIMIT n]
+```
+
+## Parameters
+
+`LIMIT n`: lists n most recent records.
+
+## Return value
+
+| **Return** | **Description**                                              |
+| ---------- | ------------------------------------------------------------ |
+| QueryId    | The ID of the query.                                         |
+| StartTime  | The start time of the query.                                 |
+| Time       | The latency of the query.                                    |
+| State      | The status of the query, including:`Error`: The query encounters an error.`Finished`: The query is finished.`Running`: The query is running. |
+| Statement  | The statement of the query.                                  |
+
+## Examples
+
+Example 1: Show five most recent query profile records.
+
+```SQL
+SHOW PROFILELIST LIMIT 5;
+```
+
+## Relevant SQLs
+
+- [ANALYZE PROFILE](./ANALYZE_PROFILE.md)
+- [EXPLAIN ANALYZE](./EXPLAIN_ANALYZE.md)
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/plan_profile/_category_.yml b/docs/en/sql-reference/sql-statements/cluster-management/plan_profile/_category_.yml
new file mode 100644
index 00000000000000..02ddec67efa91c
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/plan_profile/_category_.yml
@@ -0,0 +1,6 @@
+position: 90 # float position is supported
+label: 'Execution plan and profile'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/plugin/INSTALL_PLUGIN.md b/docs/en/sql-reference/sql-statements/cluster-management/plugin/INSTALL_PLUGIN.md
new file mode 100644
index 00000000000000..2d1bae6281c380
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/plugin/INSTALL_PLUGIN.md
@@ -0,0 +1,57 @@
+---
+displayed_sidebar: docs
+---
+
+# INSTALL PLUGIN
+
+## Description
+
+This statement is used to install a plugin.
+
+:::tip
+
+This operation requires the SYSTEM-level PLUGIN privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```sql
+INSTALL PLUGIN FROM [source] [PROPERTIES ("key"="value", ...)]
+```
+
+3 types of sources are supported:
+
+```plain text
+1. An absolute path that directs to a zip file
+2. An absolute path that directs to a plugin directory 
+3. A http or https download link that directs to a zip file
+```
+
+PROPERTIES supports setting some configurations of plugins, such as setting the  md5sum value of the zip file, etc.
+
+## Examples
+
+1. Install a plugin from local zip file:
+
+    ```sql
+    INSTALL PLUGIN FROM "/home/users/starrocks/auditdemo.zip";
+    ```
+
+2. Install a plugin from local inpath:
+
+    ```sql
+    INSTALL PLUGIN FROM "/home/users/starrocks/auditdemo/";
+    ```
+
+3. Download and install a plugin:
+
+    ```sql
+    INSTALL PLUGIN FROM "http://mywebsite.com/plugin.zip";
+    ```
+
+4. Download and install a plugin. Meanwhile, set the md5sum value of the zip file:
+
+    ```sql
+    INSTALL PLUGIN FROM "http://mywebsite.com/plugin.zip" PROPERTIES("md5sum" = "73877f6029216f4314d712086a146570");
+    ```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/plugin/SHOW_PLUGINS.md b/docs/en/sql-reference/sql-statements/cluster-management/plugin/SHOW_PLUGINS.md
new file mode 100644
index 00000000000000..08b132cfb5704b
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/plugin/SHOW_PLUGINS.md
@@ -0,0 +1,31 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW PLUGINS
+
+## Description
+
+This statement is used to view the installed plugins.
+
+:::tip
+
+This operation requires the SYSTEM-level PLUGIN privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```sql
+SHOW PLUGINS
+```
+
+This command will display all built-in plugins and custom plugins.
+
+## Examples
+
+1. Show the installed plugins:
+
+    ```sql
+    SHOW PLUGINS;
+    ```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/plugin/UNINSTALL_PLUGIN.md b/docs/en/sql-reference/sql-statements/cluster-management/plugin/UNINSTALL_PLUGIN.md
new file mode 100644
index 00000000000000..06997e24bc8216
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/plugin/UNINSTALL_PLUGIN.md
@@ -0,0 +1,33 @@
+---
+displayed_sidebar: docs
+---
+
+# UNINSTALL PLUGIN
+
+## Description
+
+This statement is used to uninstall a plugin.
+
+:::tip
+
+This operation requires the SYSTEM-level PLUGIN privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```SQL
+UNINSTALL PLUGIN <plugin_name>
+```
+
+plugin_name can be viewed through SHOW PLUGINS command
+
+Only non-builtin plugins can be uninstalled.
+
+## Examples
+
+1. Uninstall a plugin:
+
+    ```SQL
+    UNINSTALL PLUGIN auditdemo;
+    ```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/plugin/_category_.yml b/docs/en/sql-reference/sql-statements/cluster-management/plugin/_category_.yml
new file mode 100644
index 00000000000000..f054aca6cfc8e5
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/plugin/_category_.yml
@@ -0,0 +1,6 @@
+position: 80 # float position is supported
+label: 'Plugin'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/resource_group/ALTER_RESOURCE_GROUP.md b/docs/en/sql-reference/sql-statements/cluster-management/resource_group/ALTER_RESOURCE_GROUP.md
new file mode 100644
index 00000000000000..09aa2e23d51ac9
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/resource_group/ALTER_RESOURCE_GROUP.md
@@ -0,0 +1,64 @@
+---
+displayed_sidebar: docs
+---
+
+# ALTER RESOURCE GROUP
+
+## Description
+
+Alters the configuration of a resource group.
+
+:::tip
+
+This operation requires the ALTER privilege on the target resource group. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```SQL
+ALTER RESOURCE GROUP resource_group_name
+{  ADD CLASSIFIER1, CLASSIFIER2, ...
+ | DROP (CLASSIFIER_ID_1, CLASSIFIER_ID_2, ...)
+ | DROP ALL
+ | WITH resource_limit 
+};
+```
+
+## Parameters
+
+| **Parameter**       | **Description**                                              |
+| ------------------- | ------------------------------------------------------------ |
+| resource_group_name | Name of the resource group to be altered.                    |
+| ADD                 | Add classifiers to the resource group. See [CREATE RESOURCE GROUP - Parameters](CREATE_RESOURCE_GROUP.md) for more information on how to define a classifier. |
+| DROP                | Drop classifiers from the resource group via classifier IDs. You can check the ID of a classifier via [SHOW RESOURCE GROUP](SHOW_RESOURCE_GROUP.md) statement. |
+| DROP ALL            | Drop all classifiers from the resource group.                |
+| WITH                | Modify the resource limits of the resource group. See [CREATE RESOURCE GROUP - Parameters](CREATE_RESOURCE_GROUP.md) for more information on how to set resource limits. |
+
+## Examples
+
+Example 1: Adds a new classifier to the resource group `rg1`.
+
+```SQL
+ALTER RESOURCE GROUP rg1 ADD (user='root', query_type in ('select'));
+```
+
+Example 2: Drops classifiers with ID `300040`, `300041`, and `300041` from the resource group `rg1`.
+
+```SQL
+ALTER RESOURCE GROUP rg1 DROP (300040, 300041, 300041);
+```
+
+Example 3: Drops all classifiers from the resource group `rg1`.
+
+```SQL
+ALTER RESOURCE GROUP rg1 DROP ALL;
+```
+
+Example 4: modifies the resource limits of the resource group `rg1`.
+
+```SQL
+ALTER RESOURCE GROUP rg1 WITH (
+    'cpu_core_limit' = '20'
+);
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/resource_group/CREATE_RESOURCE_GROUP.md b/docs/en/sql-reference/sql-statements/cluster-management/resource_group/CREATE_RESOURCE_GROUP.md
new file mode 100644
index 00000000000000..09f73db9c843e6
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/resource_group/CREATE_RESOURCE_GROUP.md
@@ -0,0 +1,79 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE RESOURCE GROUP
+
+## Description
+
+Creates a resource group.
+
+For more information, see [Resource group](../../../../administration/management/resource_management/resource_group.md).
+
+:::tip
+
+This operation requires the SYSTEM-level CREATE RESOURCE GROUP privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```SQL
+CREATE RESOURCE GROUP resource_group_name 
+TO CLASSIFIER1, CLASSIFIER2, ...
+WITH resource_limit
+```
+
+## Parameters
+
+- `resource_group_name`: The name of the resource group to be created.
+
+- `CLASSIFIER`: Classifiers used to filter the queries on which resource limits are imposed. You must specify a classifier using `"key"="value"` pairs. You can set multiple classifiers for a resource group.
+
+  Parameters for classifiers are listed below:
+
+    | **Parameter** | **Required** | **Description**                                              |
+    | ------------- | ------------ | ------------------------------------------------------------ |
+    | user          | No           | The name of user.                                            |
+    | role          | No           | The role of user.                                            |
+    | query_type    | No           | The type of query. `SELECT` and `INSERT` (from v2.5) are supported. When INSERT tasks hit a resource group with `query_type` as `insert`, the BE node reserves the specified CPU resources for the tasks.   |
+    | source_ip     | No           | The CIDR block from which the query is initiated.            |
+    | db            | No           | The database which the query accesses. It can be specified by strings separated by commas (,). |
+    | plan_cpu_cost_range | No     | The estimated CPU cost range of the query. Its value has an equivalent meaning with the field `PlanCpuCost` in  **fe.audit.log**, and has no unit. The format is `[DOUBLE, DOUBLE)`. The default value is NULL, indicating no such restriction. This parameter is supported from v3.1.4 onwards.                  |
+    | plan_mem_cost_range | No     | The estimated memory cost range of the query. Its value has an equivalent meaning with the field `PlanMemCost` in  **fe.audit.log**, and has no unit. The format is `[DOUBLE, DOUBLE)`. The default value is NULL, indicating no such restriction. This parameter is supported from v3.1.4 onwards.               |
+
+- `resource_limit`: Resource limits to be imposed on the resource group. You must specify resource limits using `"key"="value"` pairs. You can set multiple resource limits for a resource group.
+
+  Parameters for resource limits are listed below:
+
+    | **Parameter**              | **Required** | **Description**                                              |
+    | -------------------------- | ------------ | ------------------------------------------------------------ |
+    | cpu_core_limit             | No           | The soft limit for the number of CPU cores that can be allocated to the resource group on the BE. In actual business scenarios, CPU cores that are allocated to the resource group proportionally scale based on the availability of CPU cores on the BE. Valid values: any non-zero positive integer. |
+    | mem_limit                  | No           | The percentage of memory that can be used for queries in the total memory that is provided by the BE. Unit: %. Valid values: (0, 1). |
+    | concurrency_limit          | No           | The upper limit of concurrent queries in a resource group. It is used to avoid system overload caused by too many concurrent queries. |
+    | max_cpu_cores              | No           | The CPU core limit for this resource group on a single BE node. It takes effect only when it is set to greater than `0`. Range: [0, `avg_be_cpu_cores`], where `avg_be_cpu_cores` represents the average number of CPU cores across all BE nodes. Default: 0. |
+    | big_query_cpu_second_limit | No           | The upper time limit of CPU occupation for a big query. Concurrent queries add up the time. The unit is second. |
+    | big_query_scan_rows_limit  | No           | The upper limit of row counts that can be scanned by a big query. |
+    | big_query_mem_limit        | No           | The upper limit of memory usage of a big query. The unit is byte. |
+    | type                       | No           | The type of resource group. Valid values: <br />`short_query`: When queries from the `short_query` resource group are running, the BE node reserves the CPU cores defined in `short_query.cpu_core_limit`. CPU cores for all `normal` resource groups are limited to "the total CPU cores - `short_query.cpu_core_limit`". <br />`normal`: When no query from the `short_query` resource group is running, the CPU core limit above is not imposed on the `normal` resource groups. <br />Note that you can create only ONE `short_query` resource group in a cluster. |
+
+## Example
+
+Example 1: Creates the resource group `rg1` based on multiple classifiers.
+
+```SQL
+CREATE RESOURCE GROUP rg1
+TO 
+    (user='rg1_user1', role='rg1_role1', query_type in ('select'), source_ip='192.168.x.x/24'),
+    (user='rg1_user2', query_type in ('select'), source_ip='192.168.x.x/24'),
+    (user='rg1_user3', source_ip='192.168.x.x/24'),
+    (user='rg1_user4'),
+    (db='db1')
+WITH ('cpu_core_limit' = '10',
+      'mem_limit' = '20%',
+      'type' = 'normal',
+      'big_query_cpu_second_limit' = '100',
+      'big_query_scan_rows_limit' = '100000',
+      'big_query_mem_limit' = '1073741824'
+);
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/resource_group/DROP_RESOURCE_GROUP.md b/docs/en/sql-reference/sql-statements/cluster-management/resource_group/DROP_RESOURCE_GROUP.md
new file mode 100644
index 00000000000000..bf7dd7579bfb98
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/resource_group/DROP_RESOURCE_GROUP.md
@@ -0,0 +1,35 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP RESOURCE GROUP
+
+## Description
+
+Drops the specified resource group.
+
+:::tip
+
+This operation requires the DROP privilege on the target resource group. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```SQL
+DROP RESOURCE GROUP <resource_group_name>
+```
+
+## Parameters
+
+| **Parameter**       | **Description**                           |
+| ------------------- | ----------------------------------------- |
+| resource_group_name | Name of the resource group to be dropped. |
+
+## Example
+
+Example 1: Drops the resource group `rg1`.
+
+```SQL
+DROP RESOURCE GROUP rg1;
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/resource_group/SHOW_RESOURCE_GROUP.md b/docs/en/sql-reference/sql-statements/cluster-management/resource_group/SHOW_RESOURCE_GROUP.md
new file mode 100644
index 00000000000000..15336ed331d30c
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/resource_group/SHOW_RESOURCE_GROUP.md
@@ -0,0 +1,62 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW RESOURCE GROUP
+
+## Description
+
+Shows the information of resource groups.
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```SQL
+SHOW { RESOURCE GROUPS [ALL] | RESOURCE GROUP <resource_group_name> }
+```
+
+## Parameters
+
+| **Parameter**       | **Description**                                              |
+| ------------------- | ------------------------------------------------------------ |
+| RESOURCE GROUPS     | Show the resource groups that match the current user.        |
+| ALL                 | Specify this parameter to show all resource groups in the cluster. |
+| RESOURCE GROUP      | Show the specified resource group.                           |
+| resource_group_name | Name of the resource group to be shown.                      |
+
+## Return
+
+| **Return**                 | **Description**                                              |
+| -------------------------- | ------------------------------------------------------------ |
+| name                       | Name of the resource group.                                  |
+| id                         | ID of the resource group.                                    |
+| cpu_core_limit             | CPU core limit of the resource group.                        |
+| mem_limit                  | Memory limit of the resource group.                          |
+| big_query_cpu_second_limit | Big query upper time limit of the resource group.            |
+| big_query_scan_rows_limit  | Big query scan row limit of the resource group.              |
+| big_query_mem_limit        | Big query memory limit of the resource group.                |
+| concurrency_limit          | Concurrency limit of the resource group.                     |
+| type                       | Type of resource group.                                      |
+| classifiers                | Classifiers that are associated with the resource group. `id` is the ID of the classifier, and `weight` is the degree of matching. |
+
+## Examples
+
+Example 1: Shows all resource groups in the cluster.
+
+```Plain
+mysql> SHOW RESOURCE GROUPS ALL;
++-------+--------+----------------+-----------+----------------------------+---------------------------+---------------------+-------------------+--------+------------------------------------------------------------------------------------------------------------------+
+| name  | id     | cpu_core_limit | mem_limit | big_query_cpu_second_limit | big_query_scan_rows_limit | big_query_mem_limit | concurrency_limit | type   | classifiers                                                                                                      |
++-------+--------+----------------+-----------+----------------------------+---------------------------+---------------------+-------------------+--------+------------------------------------------------------------------------------------------------------------------+
+| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625127, weight=4.459375, user=rg1_user1, role=rg1_role1, query_type in (SELECT), source_ip=172.26.xxx.xx/24) |
+| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625128, weight=3.459375, user=rg1_user2, query_type in (SELECT), source_ip=172.26.xxx.xx/24)                 |
+| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625129, weight=2.359375, user=rg1_user3, source_ip=172.26.xxx.xx/24)                                         |
+| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625130, weight=1.0, user=rg1_user4)                                                                          |
+| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625131, weight=10.0, db='db1')                                                                                |
++-------+--------+----------------+-----------+----------------------------+---------------------------+---------------------+-------------------+--------+------------------------------------------------------------------------------------------------------------------+
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/resource_group/SHOW_USAGE_RESOURCE_GROUPS.md b/docs/en/sql-reference/sql-statements/cluster-management/resource_group/SHOW_USAGE_RESOURCE_GROUPS.md
new file mode 100644
index 00000000000000..9cd1aa1601629c
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/resource_group/SHOW_USAGE_RESOURCE_GROUPS.md
@@ -0,0 +1,52 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW USAGE RESOURCE GROUPS
+
+## Description
+
+Shows the usage information of resource groups. This feature is supported from v3.1.4 onwards.
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```SQL
+SHOW USAGE RESOURCE GROUPS
+```
+
+## Return
+
+- `Name`: The name of the resource group.
+- `Id`: The ID of the resource group.
+- `Backend`: The BE's IP or FQDN.
+- `BEInUseCpuCores`: The number of CPU cores currently in use by this resource group on this BE. This value is an approximate estimate.
+- `BEInUseMemBytes`: The number of memory bytes currently in use by this resource group on this BE.
+- `BERunningQueries`: The number of queries from this resource group that are still running on this BE.
+
+## Usage notes
+
+- BEs periodically report this resource usage information to the Leader FE at the interval specified in `report_resource_usage_interval_ms`, which is by default set to 1 second.
+- The results will only show rows where at least one of `BEInUseCpuCores`/`BEInUseMemBytes`/`BERunningQueries` is a positive number. In other words, the information is displayed only when a resource group is actively using some resources on a BE.
+
+## Example
+
+```Plain
+MySQL [(none)]> SHOW USAGE RESOURCE GROUPS;
++------------+----+-----------+-----------------+-----------------+------------------+
+| Name       | Id | Backend   | BEInUseCpuCores | BEInUseMemBytes | BERunningQueries |
++------------+----+-----------+-----------------+-----------------+------------------+
+| default_wg | 0  | 127.0.0.1 | 0.100           | 1               | 5                |
++------------+----+-----------+-----------------+-----------------+------------------+
+| default_wg | 0  | 127.0.0.2 | 0.200           | 2               | 6                |
++------------+----+-----------+-----------------+-----------------+------------------+
+| wg1        | 0  | 127.0.0.1 | 0.300           | 3               | 7                |
++------------+----+-----------+-----------------+-----------------+------------------+
+| wg2        | 0  | 127.0.0.1 | 0.400           | 4               | 8                |
++------------+----+-----------+-----------------+-----------------+------------------+
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/resource_group/_category_.yml b/docs/en/sql-reference/sql-statements/cluster-management/resource_group/_category_.yml
new file mode 100644
index 00000000000000..615184df402891
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/resource_group/_category_.yml
@@ -0,0 +1,6 @@
+position: 20 # float position is supported
+label: 'Resource group'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/sql_blacklist/ADD_SQLBLACKLIST.md b/docs/en/sql-reference/sql-statements/cluster-management/sql_blacklist/ADD_SQLBLACKLIST.md
new file mode 100644
index 00000000000000..e11c364e303ec9
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/sql_blacklist/ADD_SQLBLACKLIST.md
@@ -0,0 +1,64 @@
+---
+displayed_sidebar: docs
+---
+
+# ADD SQLBLACKLIST
+
+## Description
+
+Adds a regular expression to the SQL blacklist to forbid certain SQL patterns. When the SQL Blacklist feature is enabled, StarRocks compares all SQL statements to be executed against the SQL regular expressions in the blacklist. StarRocks does not execute SQLs that match any regular expression in the blacklist and returns an error. This prevents certain SQLs from triggering cluster crashes or unexpected behavior.
+
+For more about SQL Blacklist, see [Manage SQL Blacklist](../../../../administration/management/resource_management/Blacklist.md).
+
+:::tip
+
+- This operation requires the SYSTEM-level BLACKLIST privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+- Currently, StarRocks supports adding SELECT statements to the SQL Blacklist.
+
+:::
+
+## Syntax
+
+```SQL
+ADD SQLBLACKLIST "<sql_reg_expr>"
+```
+
+## Parameter
+
+`sql_reg_expr`: the regular expression that is used to specify a certain SQL pattern. To distinguish the special characters in the SQL statement and those in the regular expression, you need to use the escape character `\` as a prefix for the special characters in the SQL statement, such as `(`, `)`, and `+`. Whereas `(` and `)` have been often used in SQL statements, StarRocks can identify `(` and `)` in SQL statements directly. You do not need to use the escape character for `(` and `)`.
+
+## Examples
+
+Example 1: Add `count(\*)` to the SQL blacklist.
+
+```Plain
+mysql> ADD SQLBLACKLIST "select count(\\*) from .+";
+```
+
+Example 2: Add `count(distinct )` to the SQL blacklist.
+
+```Plain
+mysql> ADD SQLBLACKLIST "select count(distinct .+) from .+";
+```
+
+Example 3: Add `order by limit x, y, 1 <= x <=7, 5 <=y <=7` to the SQL blacklist.
+
+```Plain
+mysql> ADD SQLBLACKLIST "select id_int from test_all_type_select1 
+    order by id_int 
+    limit [1-7], [5-7]";
+```
+
+Example 4: Add a complex SQL regular expression to the SQL blacklist. This example is to demonstrate how to use escape characters for `*` and `-` in SQL statements.
+
+```Plain
+mysql> ADD SQLBLACKLIST 
+    "select id_int \\* 4, id_tinyint, id_varchar 
+        from test_all_type_nullable 
+    except select id_int, id_tinyint, id_varchar 
+        from test_basic 
+    except select (id_int \\* 9 \\- 8) \\/ 2, id_tinyint, id_varchar 
+        from test_all_type_nullable2 
+    except select id_int, id_tinyint, id_varchar 
+        from test_basic_nullable";
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/sql_blacklist/DELETE_SQLBLACKLIST.md b/docs/en/sql-reference/sql-statements/cluster-management/sql_blacklist/DELETE_SQLBLACKLIST.md
new file mode 100644
index 00000000000000..a6d64de3ee03f6
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/sql_blacklist/DELETE_SQLBLACKLIST.md
@@ -0,0 +1,41 @@
+---
+displayed_sidebar: docs
+---
+
+# DELETE SQLBLACKLIST
+
+## Description
+
+Deletes an SQL regular expression from the SQL blacklist.
+
+For more about SQL Blacklist, see [Manage SQL Blacklist](../../../../administration/management/resource_management/Blacklist.md).
+
+:::tip
+
+This operation requires the SYSTEM-level BLACKLIST privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```SQL
+DELETE SQLBLACKLIST <sql_index_number>
+```
+
+## Parameter
+
+`sql_index_number`: the index number of the SQL regular expression in the blacklist. Separate multiple index numbers with a comma (,) and a space. You can obtain the index number using [SHOW SQLBLACKLIST](SHOW_SQLBLACKLIST.md).
+
+## Examples
+
+```Plain
+mysql> DELETE SQLBLACKLIST 3, 4;
+
+mysql> SHOW SQLBLACKLIST;
++-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| Index | Forbidden SQL                                                                                                                                                                                                                                                                                          |
++-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| 1     | select count\(\*\) from .+                                                                                                                                                                                                                                                                             |
+| 2     | select id_int \* 4, id_tinyint, id_varchar from test_all_type_nullable except select id_int, id_tinyint, id_varchar from test_basic except select \(id_int \* 9 \- 8\) \/ 2, id_tinyint, id_varchar from test_all_type_nullable2 except select id_int, id_tinyint, id_varchar from test_basic_nullable |
++-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/sql_blacklist/SHOW_SQLBLACKLIST.md b/docs/en/sql-reference/sql-statements/cluster-management/sql_blacklist/SHOW_SQLBLACKLIST.md
new file mode 100644
index 00000000000000..26c6708cac0be8
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/sql_blacklist/SHOW_SQLBLACKLIST.md
@@ -0,0 +1,44 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW SQLBLACKLIST
+
+## Description
+
+Shows the SQL regular expressions in the SQL blacklist.
+
+For more about SQL Blacklist, see [Manage SQL Blacklist](../../../../administration/management/resource_management/Blacklist.md).
+
+:::tip
+
+This operation requires the SYSTEM-level BLACKLIST privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```SQL
+SHOW SQLBLACKLIST
+```
+
+## Return value
+
+| **Return**    | **Description**                                              |
+| ------------- | ------------------------------------------------------------ |
+| Index         | The index number of the SQL regular expression that has been added to the blacklist. |
+| Forbidden SQL | The SQL regular expression that has been added to the blacklist. |
+
+## Examples
+
+```Plain
+mysql> SHOW SQLBLACKLIST;
++-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| Index | Forbidden SQL                                                                                                                                                                                                                                                                                          |
++-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| 1     | select count\(\*\) from .+                                                                                                                                                                                                                                                                             |
+| 2     | select id_int \* 4, id_tinyint, id_varchar from test_all_type_nullable except select id_int, id_tinyint, id_varchar from test_basic except select \(id_int \* 9 \- 8\) \/ 2, id_tinyint, id_varchar from test_all_type_nullable2 except select id_int, id_tinyint, id_varchar from test_basic_nullable |
+| 3     | select id_int from test_all_type_select1 order by id_int limit [1-7], [5-7]                                                                                                                                                                                                                            |
+| 4     | select count\(distinct .+\) from .+                                                                                                                                                                                                                                                                    |
++-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/sql_blacklist/_category_.yml b/docs/en/sql-reference/sql-statements/cluster-management/sql_blacklist/_category_.yml
new file mode 100644
index 00000000000000..1e3d688ded764b
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/sql_blacklist/_category_.yml
@@ -0,0 +1,6 @@
+position: 70 # float position is supported
+label: 'SQL blacklist'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/ALTER_STORAGE_VOLUME.md b/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/ALTER_STORAGE_VOLUME.md
new file mode 100644
index 00000000000000..08eb832df74490
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/ALTER_STORAGE_VOLUME.md
@@ -0,0 +1,60 @@
+---
+displayed_sidebar: docs
+---
+
+# ALTER STORAGE VOLUME
+
+## Description
+
+Alters the credential properties, comment, or status (`enabled`) of a storage volume. For more about the properties of a storage volume, see [CREATE STORAGE VOLUME](CREATE_STORAGE_VOLUME.md). This feature is supported from v3.1.
+
+> **CAUTION**
+>
+> - Only users with the ALTER privilege on a specific storage volume can perform this operation.
+> - The `TYPE`, `LOCATIONS`, and other path-related properties of an existing storage volume cannot be altered. You can only alter its credential-related properties. If you changed the path-related configuration items, the databases and tables you created before the change become read-only, and you cannot load data into them.
+> - When `enabled` is `false`, the corresponding storage volume cannot be referenced.
+
+## Syntax
+
+```SQL
+ALTER STORAGE VOLUME [ IF EXISTS ] <storage_volume_name>
+{ COMMENT '<comment_string>'
+| SET ("key" = "value"[,...]) }
+```
+
+## Parameters
+
+| **Parameter**       | **Description**                          |
+| ------------------- | ---------------------------------------- |
+| storage_volume_name | The name of the storage volume to alter. |
+| COMMENT             | The comment on the storage volume.       |
+
+For detailed information on the properties that can be altered or added, see [CREATE STORAGE VOLUME - PROPERTIES](CREATE_STORAGE_VOLUME.md#properties).
+
+## Examples
+
+Example 1: Disable the storage volume `my_s3_volume`.
+
+```Plain
+MySQL > ALTER STORAGE VOLUME my_s3_volume
+    -> SET ("enabled" = "false");
+Query OK, 0 rows affected (0.01 sec)
+```
+
+Example 2: Alter the credential information of the storage volume `my_s3_volume`.
+
+```Plain
+MySQL > ALTER STORAGE VOLUME my_s3_volume
+    -> SET (
+    ->     "aws.s3.use_instance_profile" = "true"
+    -> );
+Query OK, 0 rows affected (0.00 sec)
+```
+
+## Relevant SQL statements
+
+- [CREATE STORAGE VOLUME](CREATE_STORAGE_VOLUME.md)
+- [DROP STORAGE VOLUME](DROP_STORAGE_VOLUME.md)
+- [SET DEFAULT STORAGE VOLUME](SET_DEFAULT_STORAGE_VOLUME.md)
+- [DESC STORAGE VOLUME](DESC_STORAGE_VOLUME.md)
+- [SHOW STORAGE VOLUMES](SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md b/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md
new file mode 100644
index 00000000000000..9826974947b58c
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md
@@ -0,0 +1,364 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE STORAGE VOLUME
+
+## Description
+
+Creates a storage volume for a remote storage system. This feature is supported from v3.1.
+
+A storage volume consists of the properties and credential information of the remote data storage. You can reference a storage volume when you create databases and cloud-native tables in a shared-data StarRocks cluster.
+
+> **CAUTION**
+>
+> Only users with the CREATE STORAGE VOLUME privilege on the SYSTEM level can perform this operation.
+
+## Syntax
+
+```SQL
+CREATE STORAGE VOLUME [IF NOT EXISTS] <storage_volume_name>
+TYPE = { S3 | HDFS | AZBLOB }
+LOCATIONS = ('<remote_storage_path>')
+[ COMMENT '<comment_string>' ]
+PROPERTIES
+("key" = "value",...)
+```
+
+## Parameters
+
+| **Parameter**       | **Description**                                              |
+| ------------------- | ------------------------------------------------------------ |
+| storage_volume_name | The name of the storage volume. Please note that you cannot create a storage volume named `builtin_storage_volume` because it is used to create the builtin storage volume. For the naming conventions, see [System limits](../../../System_limit.md).|
+| TYPE                | The type of the remote storage system. Valid values: `S3`, `HDFS` and `AZBLOB`. `S3` indicates AWS S3 or S3-compatible storage systems. `AZBLOB` indicates Azure Blob Storage (supported from v3.1.1 onwards). `HDFS` indicates an HDFS cluster.  |
+| LOCATIONS           | The storage locations. The format is as follows:<ul><li>For AWS S3 or S3 protocol-compatible storage systems: `s3://<s3_path>`. `<s3_path>` must be an absolute path, for example, `s3://testbucket/subpath`. Note that if you want to enable the [Partitioned Prefix](#partitioned-prefix) feature for the storage volume, you can only specify the bucket name, and specifying a sub-path is not allowed.</li><li>For Azure Blob Storage: `azblob://<azblob_path>`. `<azblob_path>` must be an absolute path, for example, `azblob://testcontainer/subpath`.</li><li>For HDFS: `hdfs://<host>:<port>/<hdfs_path>`. `<hdfs_path>` must be an absolute path, for example, `hdfs://127.0.0.1:9000/user/xxx/starrocks`.</li><li>For WebHDFS: `webhdfs://<host>:<http_port>/<hdfs_path>`, where `<http_port>` is the HTTP port of the NameNode. `<hdfs_path>` must be an absolute path, for example, `webhdfs://127.0.0.1:50070/user/xxx/starrocks`.</li><li>For ViewFS：`viewfs://<ViewFS_cluster>/<viewfs_path>`, where `<ViewFS_cluster>` is the ViewFS cluster name. `<viewfs_path>` must be an absolute path, for example, `viewfs://myviewfscluster/user/xxx/starrocks`.</li></ul> |
+| COMMENT             | The comment on the storage volume.                           |
+| PROPERTIES          | Parameters in the `"key" = "value"` pairs used to specify the properties and credential information to access the remote storage system. For detailed information, see [PROPERTIES](#properties). |
+
+### PROPERTIES
+
+The table below lists all available properties of storage volumes. Following the table are the usage instructions of these properties, categorized by different scenarios from the perspectives of [Credential information](#credential-information) and [Features](#features).
+
+| **Property**                        | **Description**                                              |
+| ----------------------------------- | ------------------------------------------------------------ |
+| enabled                             | Whether to enable this storage volume. Default: `false`. Disabled storage volume cannot be referenced. |
+| aws.s3.region                       | The region in which your S3 bucket resides, for example, `us-west-2`. |
+| aws.s3.endpoint                     | The endpoint URL used to access your S3 bucket, for example, `https://s3.us-west-2.amazonaws.com`. [Preview] From v3.3.0 onwards, the Amazon S3 Express One Zone storage class is supported, for example, `https://s3express.us-west-2.amazonaws.com`.   |
+| aws.s3.use_aws_sdk_default_behavior | Whether to use the default authentication credential of AWS SDK. Valid values: `true` and `false` (Default). |
+| aws.s3.use_instance_profile         | Whether to use Instance Profile and Assumed Role as credential methods for accessing S3. Valid values: `true` and `false` (Default).<ul><li>If you use IAM user-based credential (Access Key and Secret Key) to access S3, you must specify this item as `false`, and specify `aws.s3.access_key` and `aws.s3.secret_key`.</li><li>If you use Instance Profile to access S3, you must specify this item as `true`.</li><li>If you use Assumed Role to access S3, you must specify this item as `true`, and specify `aws.s3.iam_role_arn`.</li><li>And if you use an external AWS account, you must specify this item as `true`, and specify `aws.s3.iam_role_arn` and `aws.s3.external_id`.</li></ul> |
+| aws.s3.access_key                   | The Access Key ID used to access your S3 bucket.             |
+| aws.s3.secret_key                   | The Secret Access Key used to access your S3 bucket.         |
+| aws.s3.iam_role_arn                 | The ARN of the IAM role that has privileges on your S3 bucket in which your data files are stored. |
+| aws.s3.external_id                  | The external ID of the AWS account that is used for cross-account access to your S3 bucket. |
+| azure.blob.endpoint                 | The endpoint of your Azure Blob Storage Account, for example, `https://test.blob.core.windows.net`. |
+| azure.blob.shared_key               | The Shared Key used to authorize requests for your Azure Blob Storage. |
+| azure.blob.sas_token                | The shared access signatures (SAS) used to authorize requests for your Azure Blob Storage. |
+| hadoop.security.authentication      | The authentication method. Valid values: `simple`(Default) and `kerberos`. `simple` indicates simple authentication, that is, username. `kerberos` indicates Kerberos authentication. |
+| username                            | Username used to access the NameNode in the HDFS cluster.                      |
+| hadoop.security.kerberos.ticket.cache.path | The path that stores the kinit-generated Ticket Cache.                   |
+| dfs.nameservices                    | Name of the HDFS cluster                                        |
+| dfs.ha.namenodes.`<ha_cluster_name\>`                   | Name of the NameNode. Multiple names must be separated by commas (,). No space is allowed in the double quotes. `<ha_cluster_name>` is the name of the HDFS service specified in `dfs.nameservices`. |
+| dfs.namenode.rpc-address.`<ha_cluster_name\>`.`<NameNode\>` | The RPC address information of the NameNode. `<NameNode>` is the name of the NameNode specified in `dfs.ha.namenodes.<ha_cluster_name>`. |
+| dfs.client.failover.proxy.provider                    | The provider of the NameNode for client connection. The default value is `org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider`. |
+| fs.viewfs.mounttable.`<ViewFS_cluster\>`.link./`<viewfs_path\>` | The path to the ViewFS cluster to be mounted. Multiple paths must be separated by commas (,). `<ViewFS_cluster>` is the ViewFS cluster name specified in `LOCATIONS`. |
+| aws.s3.enable_partitioned_prefix    | Whether to enable the Partitioned Prefix feature for the storage volume. Default: `false`. For more information about this feature, see [Partitioned Prefix](#partitioned-prefix). |
+| aws.s3.num_partitioned_prefix       | The number of prefixes to be created for the storage volume. Default: `256`. Valid range: [4, 1024].|
+
+#### Credential information
+
+##### AWS S3
+
+- If you use the default authentication credential of AWS SDK to access S3, set the following properties:
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "aws.s3.region" = "<region>",
+  "aws.s3.endpoint" = "<endpoint_url>",
+  "aws.s3.use_aws_sdk_default_behavior" = "true"
+  ```
+
+- If you use IAM user-based credential (Access Key and Secret Key) to access S3, set the following properties:
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "aws.s3.region" = "<region>",
+  "aws.s3.endpoint" = "<endpoint_url>",
+  "aws.s3.use_aws_sdk_default_behavior" = "false",
+  "aws.s3.use_instance_profile" = "false",
+  "aws.s3.access_key" = "<access_key>",
+  "aws.s3.secret_key" = "<secrete_key>"
+  ```
+
+- If you use Instance Profile to access S3, set the following properties:
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "aws.s3.region" = "<region>",
+  "aws.s3.endpoint" = "<endpoint_url>",
+  "aws.s3.use_aws_sdk_default_behavior" = "false",
+  "aws.s3.use_instance_profile" = "true"
+  ```
+
+- If you use Assumed Role to access S3, set the following properties:
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "aws.s3.region" = "<region>",
+  "aws.s3.endpoint" = "<endpoint_url>",
+  "aws.s3.use_aws_sdk_default_behavior" = "false",
+  "aws.s3.use_instance_profile" = "true",
+  "aws.s3.iam_role_arn" = "<role_arn>"
+  ```
+
+- If you use Assumed Role to access S3 from an external AWS account, set the following properties:
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "aws.s3.region" = "<region>",
+  "aws.s3.endpoint" = "<endpoint_url>",
+  "aws.s3.use_aws_sdk_default_behavior" = "false",
+  "aws.s3.use_instance_profile" = "true",
+  "aws.s3.iam_role_arn" = "<role_arn>",
+  "aws.s3.external_id" = "<external_id>"
+  ```
+
+##### GCS
+
+If you use GCP Cloud Storage, set the following properties:
+
+```SQL
+"enabled" = "{ true | false }",
+
+-- For example: us-east-1
+"aws.s3.region" = "<region>",
+
+-- For example: https://storage.googleapis.com
+"aws.s3.endpoint" = "<endpoint_url>",
+
+"aws.s3.access_key" = "<access_key>",
+"aws.s3.secret_key" = "<secrete_key>"
+```
+
+##### MinIO
+
+If you use MinIO, set the following properties:
+
+```SQL
+"enabled" = "{ true | false }",
+
+-- For example: us-east-1
+"aws.s3.region" = "<region>",
+
+-- For example: http://172.26.xx.xxx:39000
+"aws.s3.endpoint" = "<endpoint_url>",
+
+"aws.s3.access_key" = "<access_key>",
+"aws.s3.secret_key" = "<secrete_key>"
+```
+
+##### Azure Blob Storage
+
+Creating a storage volume on Azure Blob Storage is supported from v3.1.1 onwards.
+
+- If you use Shared Key to access Azure Blob Storage, set the following properties:
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "azure.blob.endpoint" = "<endpoint_url>",
+  "azure.blob.shared_key" = "<shared_key>"
+  ```
+
+- If you use shared access signatures (SAS) to access Azure Blob Storage, set the following properties:
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "azure.blob.endpoint" = "<endpoint_url>",
+  "azure.blob.sas_token" = "<sas_token>"
+  ```
+
+:::note
+The hierarchical namespace must be disabled when you create the Azure Blob Storage Account.
+:::
+
+##### HDFS
+
+- If you do not use authentication to access HDFS, set the following properties:
+
+  ```SQL
+  "enabled" = "{ true | false }"
+  ```
+
+- If you are using simple authentication (supported from v3.2) to access HDFS, set the following properties:
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "hadoop.security.authentication" = "simple",
+  "username" = "<hdfs_username>"
+  ```
+
+- If you are using Kerberos Ticket Cache authentication (supported since v3.2) to access HDFS, set the following properties:
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "hadoop.security.authentication" = "kerberos",
+  "hadoop.security.kerberos.ticket.cache.path" = "<ticket_cache_path>"
+  ```
+
+  > **CAUTION**
+  >
+  > - This setting only forces the system to use KeyTab to access HDFS via Kerberos. Make sure that each BE or CN node has access to the KeyTab files. Also make sure that the **/etc/krb5.conf** file is set up correctly.
+  > - The Ticket cache is generated by an external kinit tool. Make sure you have a crontab or similar periodic task to refresh the tickets.
+
+- If your HDFS cluster is enabled for NameNode HA configuration (supported since v3.2), additionally set the following properties:
+
+  ```SQL
+  "dfs.nameservices" = "<ha_cluster_name>",
+  "dfs.ha.namenodes.<ha_cluster_name>" = "<NameNode1>,<NameNode2> [, ...]",
+  "dfs.namenode.rpc-address.<ha_cluster_name>.<NameNode1>" = "<hdfs_host>:<hdfs_port>",
+  "dfs.namenode.rpc-address.<ha_cluster_name>.<NameNode2>" = "<hdfs_host>:<hdfs_port>",
+  [...]
+  "dfs.client.failover.proxy.provider.<ha_cluster_name>" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
+  ```
+
+  For more information, see [HDFS HA Documentation](https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HDFSHighAvailabilityWithNFS.html).
+
+  - If you are using WebHDFS (supported since v3.2), set the following properties:
+
+  ```SQL
+  "enabled" = "{ true | false }"
+  ```
+
+  For more information, see [WebHDFS Documentation](https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/WebHDFS.html).
+
+- If you are using Hadoop ViewFS (supported since v3.2), set the following properties:
+
+  ```SQL
+  -- Replace <ViewFS_cluster> with the name of the ViewFS cluster.
+  "fs.viewfs.mounttable.<ViewFS_cluster>.link./<viewfs_path_1>" = "hdfs://<hdfs_host_1>:<hdfs_port_1>/<hdfs_path_1>",
+  "fs.viewfs.mounttable.<ViewFS_cluster>.link./<viewfs_path_2>" = "hdfs://<hdfs_host_2>:<hdfs_port_2>/<hdfs_path_2>",
+  [, ...]
+  ```
+
+  For more information, see [ViewFS Documentation](https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/ViewFs.html).
+
+#### Features
+
+##### Partitioned Prefix
+
+From v3.2.4, StarRocks supports creating storage volumes with the Partitioned Prefix feature for S3-compatible object storage systems. When this feature is enabled, StarRocks stores the data into multiple, uniformly prefixed partitions (sub-paths) under the bucket. It can easily multiply StarRocks' read and write performance on data files stored in the bucket because the QPS or throughput limit of the bucket is per partition.
+
+To enable this feature, set the following properties in addition to the above credential-related parameters:
+
+```SQL
+"aws.s3.enable_partitioned_prefix" = "{ true | false }",
+"aws.s3.num_partitioned_prefix" = "<INT>"
+```
+
+:::note
+- The Partitioned Prefix feature is only supported for S3-compatible object storage systems, that is, the `TYPE` of the storage volume must be `S3`.
+- `LOCATIONS` of the storage volume must only contain the bucket name, for example, `s3://testbucket`. Specifying a sub-path after the bucket name is not allowed.
+- Both properties are immutable once the storage volume is created.
+- You cannot enable this feature when create a storage volume by using the FE configuration file **fe.conf**.
+:::
+
+## Examples
+
+Example 1: Create a storage volume `my_s3_volume` for the AWS S3 bucket `defaultbucket`, use the IAM user-based credential (Access Key and Secret Key) to access S3, and enable it.
+
+```SQL
+CREATE STORAGE VOLUME my_s3_volume
+TYPE = S3
+LOCATIONS = ("s3://defaultbucket/test/")
+PROPERTIES
+(
+    "aws.s3.region" = "us-west-2",
+    "aws.s3.endpoint" = "https://s3.us-west-2.amazonaws.com",
+    "aws.s3.use_aws_sdk_default_behavior" = "false",
+    "aws.s3.use_instance_profile" = "false",
+    "aws.s3.access_key" = "xxxxxxxxxx",
+    "aws.s3.secret_key" = "yyyyyyyyyy"
+);
+```
+
+Example 2: Create a storage volume `my_hdfs_volume` for HDFS and enable it.
+
+```SQL
+CREATE STORAGE VOLUME my_hdfs_volume
+TYPE = HDFS
+LOCATIONS = ("hdfs://127.0.0.1:9000/sr/test/")
+PROPERTIES
+(
+    "enabled" = "true"
+);
+```
+
+Example 3: Create a storage volume `hdfsvolumehadoop` for HDFS using simple authentication.
+
+```sql
+CREATE STORAGE VOLUME hdfsvolumehadoop
+TYPE = HDFS
+LOCATIONS = ("hdfs://127.0.0.1:9000/sr/test/")
+PROPERTIES(
+    "hadoop.security.authentication" = "simple",
+    "username" = "starrocks"
+);
+```
+
+Example 4: Use Kerberos Ticket Cache authentication to access HDFS and create storage volume `hdfsvolkerberos`.
+
+```sql
+CREATE STORAGE VOLUME hdfsvolkerberos
+TYPE = HDFS
+LOCATIONS = ("hdfs://127.0.0.1:9000/sr/test/")
+PROPERTIES(
+    "hadoop.security.authentication" = "kerberos",
+    "hadoop.security.kerberos.ticket.cache.path" = "/path/to/ticket/cache/path"
+);
+```
+
+Example 5: Create storage volume `hdfsvolha` for an HDFS cluster with NameNode HA configuration enabled.
+
+```sql
+CREATE STORAGE VOLUME hdfsvolha
+TYPE = HDFS
+LOCATIONS = ("hdfs://myhacluster/data/sr")
+PROPERTIES(
+    "dfs.nameservices" = "myhacluster",
+    "dfs.ha.namenodes.myhacluster" = "nn1,nn2,nn3",
+    "dfs.namenode.rpc-address.myhacluster.nn1" = "machine1.example.com:8020",
+    "dfs.namenode.rpc-address.myhacluster.nn2" = "machine2.example.com:8020",
+    "dfs.namenode.rpc-address.myhacluster.nn3" = "machine3.example.com:8020",
+    "dfs.namenode.http-address.myhacluster.nn1" = "machine1.example.com:9870",
+    "dfs.namenode.http-address.myhacluster.nn2" = "machine2.example.com:9870",
+    "dfs.namenode.http-address.myhacluster.nn3" = "machine3.example.com:9870",
+    "dfs.client.failover.proxy.provider.myhacluster" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
+);
+```
+
+Example 6: Create a storage volume `webhdfsvol` for WebHDFS.
+
+```sql
+CREATE STORAGE VOLUME webhdfsvol
+TYPE = HDFS
+LOCATIONS = ("webhdfs://namenode:9870/data/sr");
+```
+
+Example 7: Create a storage volume `viewfsvol` using Hadoop ViewFS.
+
+```sql
+CREATE STORAGE VOLUME viewfsvol
+TYPE = HDFS
+LOCATIONS = ("viewfs://clusterX/data/sr")
+PROPERTIES(
+    "fs.viewfs.mounttable.clusterX.link./data" = "hdfs://nn1-clusterx.example.com:8020/data",
+    "fs.viewfs.mounttable.clusterX.link./project" = "hdfs://nn2-clusterx.example.com:8020/project"
+);
+```
+
+## Relevant SQL statements
+
+- [ALTER STORAGE VOLUME](ALTER_STORAGE_VOLUME.md)
+- [DROP STORAGE VOLUME](DROP_STORAGE_VOLUME.md)
+- [SET DEFAULT STORAGE VOLUME](SET_DEFAULT_STORAGE_VOLUME.md)
+- [DESC STORAGE VOLUME](DESC_STORAGE_VOLUME.md)
+- [SHOW STORAGE VOLUMES](SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/DESC_STORAGE_VOLUME.md b/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/DESC_STORAGE_VOLUME.md
new file mode 100644
index 00000000000000..010928a581dbd2
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/DESC_STORAGE_VOLUME.md
@@ -0,0 +1,62 @@
+---
+displayed_sidebar: docs
+---
+
+# DESC STORAGE VOLUME
+
+## Description
+
+Describes a storage volume. This feature is supported from v3.1.
+
+> **CAUTION**
+>
+> Only users with the USAGE privilege on a specific storage volume can perform this operation.
+
+## Syntax
+
+```SQL
+DESC[RIBE] STORAGE VOLUME <storage_volume_name>
+```
+
+## Parameters
+
+| **Parameter**       | **Description**                             |
+| ------------------- | ------------------------------------------- |
+| storage_volume_name | The name of the storage volume to describe. |
+
+## Return value
+
+| **Return** | **Description**                                              |
+| ---------- | ------------------------------------------------------------ |
+| Name       | The name of the storage volume.                              |
+| Type       | The type of the remote storage system. Valid values: `S3` and `AZBLOB`. |
+| IsDefault  | Whether the storage volume is the default storage volume.    |
+| Location   | The location of the remote storage system.                   |
+| Params     | The credential information used to access the remote storage system. |
+| Enabled    | Whether the storage volume is enabled.                       |
+| Comment    | The comment on the storage volume.                           |
+
+## Examples
+
+Example 1: Describe the storage volume `my_s3_volume`.
+
+```Plain
+MySQL > DESCRIBE STORAGE VOLUME my_s3_volume\G
+*************************** 1. row ***************************
+     Name: my_s3_volume
+     Type: S3
+IsDefault: false
+ Location: s3://defaultbucket/test/
+   Params: {"aws.s3.access_key":"xxxxxxxxxx","aws.s3.secret_key":"yyyyyyyyyy","aws.s3.endpoint":"https://s3.us-west-2.amazonaws.com","aws.s3.region":"us-west-2","aws.s3.use_instance_profile":"true","aws.s3.use_aws_sdk_default_behavior":"false"}
+  Enabled: false
+  Comment: 
+1 row in set (0.00 sec)
+```
+
+## Relevant SQL statements
+
+- [CREATE STORAGE VOLUME](CREATE_STORAGE_VOLUME.md)
+- [ALTER STORAGE VOLUME](ALTER_STORAGE_VOLUME.md)
+- [DROP STORAGE VOLUME](DROP_STORAGE_VOLUME.md)
+- [SET DEFAULT STORAGE VOLUME](SET_DEFAULT_STORAGE_VOLUME.md)
+- [SHOW STORAGE VOLUMES](SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/DROP_STORAGE_VOLUME.md b/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/DROP_STORAGE_VOLUME.md
new file mode 100644
index 00000000000000..0f04019628a79d
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/DROP_STORAGE_VOLUME.md
@@ -0,0 +1,44 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP STORAGE VOLUME
+
+## Description
+
+Drops a storage volume. Dropped storage volumes cannot be referenced anymore. This feature is supported from v3.1.
+
+> **CAUTION**
+>
+> - Only users with the DROP privilege on a specific storage volume can perform this operation.
+> - The default storage volume and the built-in storage volume `builtin_storage_volume` cannot be dropped. You can use [DESC STORAGE VOLUME](DESC_STORAGE_VOLUME.md) to check whether a storage volume is the default storage volume.
+> - Storage volumes that are referenced by existing databases or cloud-native tables cannot be dropped.
+
+## Syntax
+
+```SQL
+DROP STORAGE VOLUME [ IF EXISTS ] <storage_volume_name>
+```
+
+## Parameters
+
+| **Parameter**       | **Description**                         |
+| ------------------- | --------------------------------------- |
+| storage_volume_name | The name of the storage volume to drop. |
+
+## Examples
+
+Example 1: Drop the storage volume `my_s3_volume`.
+
+```Plain
+MySQL > DROP STORAGE VOLUME my_s3_volume;
+Query OK, 0 rows affected (0.01 sec)
+```
+
+## Relevant SQL statements
+
+- [CREATE STORAGE VOLUME](CREATE_STORAGE_VOLUME.md)
+- [ALTER STORAGE VOLUME](ALTER_STORAGE_VOLUME.md)
+- [SET DEFAULT STORAGE VOLUME](SET_DEFAULT_STORAGE_VOLUME.md)
+- [DESC STORAGE VOLUME](DESC_STORAGE_VOLUME.md)
+- [SHOW STORAGE VOLUMES](SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/SET_DEFAULT_STORAGE_VOLUME.md b/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/SET_DEFAULT_STORAGE_VOLUME.md
new file mode 100644
index 00000000000000..1111347fb110cf
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/SET_DEFAULT_STORAGE_VOLUME.md
@@ -0,0 +1,44 @@
+---
+displayed_sidebar: docs
+---
+
+# SET DEFAULT STORAGE VOLUME
+
+## Description
+
+Sets a storage volume as the default storage volume. After creating a storage volume for an external data source, you can set it as the default storage volume of your StarRocks cluster. This feature is supported from v3.1.
+
+> **CAUTION**
+>
+> - Only users with the USAGE privilege on a specific storage volume can perform this operation.
+> - The default storage volume cannot be dropped or disabled.
+> - You must set the default storage volume for a shared-data StarRocks cluster because StarRocks stores the system statistics information in the default storage volume.
+
+## Syntax
+
+```SQL
+SET <storage_volume_name> AS DEFAULT STORAGE VOLUME
+```
+
+## Parameters
+
+| **Parameter**       | **Description**                                              |
+| ------------------- | ------------------------------------------------------------ |
+| storage_volume_name | The name of the storage volume to be set as the default storage volume. |
+
+## Examples
+
+Example 1: Set the storage volume `my_s3_volume` as the default storage volume.
+
+```SQL
+MySQL > SET my_s3_volume AS DEFAULT STORAGE VOLUME;
+Query OK, 0 rows affected (0.01 sec)
+```
+
+## Relevant SQL statements
+
+- [CREATE STORAGE VOLUME](CREATE_STORAGE_VOLUME.md)
+- [ALTER STORAGE VOLUME](ALTER_STORAGE_VOLUME.md)
+- [DROP STORAGE VOLUME](DROP_STORAGE_VOLUME.md)
+- [DESC STORAGE VOLUME](DESC_STORAGE_VOLUME.md)
+- [SHOW STORAGE VOLUMES](SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/SHOW_STORAGE_VOLUMES.md b/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/SHOW_STORAGE_VOLUMES.md
new file mode 100644
index 00000000000000..99b792032b2642
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/SHOW_STORAGE_VOLUMES.md
@@ -0,0 +1,55 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW STORAGE VOLUMES
+
+## Description
+
+Shows the storage volumes in your StarRocks cluster. This feature is supported from v3.1.
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```SQL
+SHOW STORAGE VOLUMES [ LIKE '<pattern>' ]
+```
+
+## Parameters
+
+| **Parameter** | **Description**                                |
+| ------------- | ---------------------------------------------- |
+| pattern       | The pattern used to match the storage volumes. |
+
+## Return value
+
+| **Return**     | **Description**                 |
+| -------------- | ------------------------------- |
+| Storage Volume | The name of the storage volume. |
+
+## Examples
+
+Example 1: Show all storage volumes in the StarRocks cluster.
+
+```Plain
+MySQL > SHOW STORAGE VOLUMES;
++----------------+
+| Storage Volume |
++----------------+
+| my_s3_volume   |
++----------------+
+1 row in set (0.01 sec)
+```
+
+## Relevant SQL statements
+
+- [CREATE STORAGE VOLUME](CREATE_STORAGE_VOLUME.md)
+- [ALTER STORAGE VOLUME](ALTER_STORAGE_VOLUME.md)
+- [DROP STORAGE VOLUME](DROP_STORAGE_VOLUME.md)
+- [SET DEFAULT STORAGE VOLUME](SET_DEFAULT_STORAGE_VOLUME.md)
+- [DESC STORAGE VOLUME](DESC_STORAGE_VOLUME.md)
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/_category_.yml b/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/_category_.yml
new file mode 100644
index 00000000000000..fd1d4bde34dce3
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/storage_volume/_category_.yml
@@ -0,0 +1,6 @@
+position: 30 # float position is supported
+label: 'Storage volume'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_CANCEL_REPAIR.md b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_CANCEL_REPAIR.md
new file mode 100644
index 00000000000000..752e91a43e6073
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_CANCEL_REPAIR.md
@@ -0,0 +1,33 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN CANCEL REPAIR
+
+## Description
+
+This statement is used to cancel repairing specified tables or partitions with high priority.
+
+:::tip
+
+This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```sql
+ADMIN CANCEL REPAIR TABLE table_name[ PARTITION (p1,...)]
+```
+
+Note
+>
+> This statement only indicates that the system will no longer repair sharding replicas of specified tables or partitions with high priority. It still repairs these copies by default scheduling.
+
+## Examples
+
+1. Cancel high priority repair
+
+    ```sql
+    ADMIN CANCEL REPAIR TABLE tbl PARTITION(p1);
+    ```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_CHECK_TABLET.md b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_CHECK_TABLET.md
new file mode 100644
index 00000000000000..f73123c7e9072a
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_CHECK_TABLET.md
@@ -0,0 +1,39 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN CHECK TABLET
+
+## Description
+
+This statement is used to check a group of tablets.
+
+:::tip
+
+This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```sql
+ADMIN CHECK TABLE (tablet_id1, tablet_id2, ...)
+PROPERTIES("type" = "...")
+```
+
+Note:
+
+1. The "type" property in tablet id and PROPERTIES must be specified.
+
+2. Currently, "type" only supports:
+
+   Consistency: Check the consistency of replicas of the tablet. This command is asynchronous. After sending it, StarRocks will start checking the consistency among corresponding tablets. The final results will be shown in the InconsistentTabletNum column in the result of SHOW PROC "/statistic".
+
+## Examples
+
+1. Check the consistency of replicas on a group of specified tablets
+
+    ```sql
+    ADMIN CHECK TABLET (10000, 10001)
+    PROPERTIES("type" = "consistency");
+    ```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_REPAIR.md b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_REPAIR.md
new file mode 100644
index 00000000000000..e181bbe6345ae4
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_REPAIR.md
@@ -0,0 +1,40 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN REPAIR
+
+## Description
+
+This statement is used to try and fix the specified tables or partitions first.
+
+:::tip
+
+This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```sql
+ADMIN REPAIR TABLE table_name[ PARTITION (p1,...)]
+```
+
+Note:
+
+1. This statement only means that the system attempts to repair sharding replicas of specified tables or partitions with high priority without the guarantee that the repair will be successful. Users can view the repair status through ADMIN SHOW REPLICA STATUS command.
+2. The default timeout is 14400 seconds (4 hours). Timeout means the system will not repair sharding replicas of specified tables or partitions with high priority. In case of timeout, the command needs to be used again for the intended settings.
+
+## Examples
+
+1. Attempt to repair specified tables
+
+    ```sql
+    ADMIN REPAIR TABLE tbl1;
+    ```
+
+2. Attempt to fix specified partition
+
+    ```sql
+    ADMIN REPAIR TABLE tbl1 PARTITION (p1, p2);
+    ```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SET_PARTITION_VERSION.md b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SET_PARTITION_VERSION.md
new file mode 100644
index 00000000000000..3c6a7c7cabcce6
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SET_PARTITION_VERSION.md
@@ -0,0 +1,51 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN SET PARTITION VERSION
+
+## Description
+
+Sets a partition to a specific data version.
+
+Note that manually setting the partition version is a high-risk operation and is recommended only when problems occur in the cluster metadata. In normal circumstances, the version of a partition is consistent with that of the tablets within.
+
+:::tip
+
+This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```sql
+ADMIN SET TABLE <table_name> PARTITION ( <partition_name> | <partition_id> ) 
+TO VERSION <version>
+```
+
+## Parameters
+
+- `table_name`: The name of the table to which the partition belongs.
+- `partition_name`: The name of the partition. You need to specify a partition using either `partition_name` or `partition_id`. For non-partitioned tables, `partition_name` is the same as the table name.
+- `partition_id`: The ID of the partition. You need to specify a partition using either `partition_name` or `partition_id`. For tables with the random bucketing strategy, you can only use `partition_id` to specify the partition.
+- `version`: The version you want to set for the partition.
+
+## Examples
+
+1. Set the version of the non-partitioned table `t1` to `10`.
+
+    ```sql
+    ADMIN SET TABLE t1 PARTITION(t1) TO VERSION 10;
+    ```
+
+2. Set the version of partition `p1` in table `t2` to `10`.
+
+    ```sql
+    ADMIN SET TABLE t2 PARTITION(p1) TO VERSION 10;
+    ```
+
+3. Set the version of the partition whose ID is `123456` to `10`. `t3` is a table with the random bucketing strategy.
+
+    ```sql
+    ADMIN SET TABLE t3 PARTITION('123456') TO VERSION 10;
+    ```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SET_REPLICA_STATUS.md b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SET_REPLICA_STATUS.md
new file mode 100644
index 00000000000000..3d9049cd24692a
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SET_REPLICA_STATUS.md
@@ -0,0 +1,52 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN SET REPLICA STATUS
+
+## Description
+
+This statement is used to set the status of the specified replicas.
+
+This command currently only used to manually set the status of some replicas to BAD or OK, allowing the system to automatically repair these replicas.
+
+:::tip
+
+This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```sql
+ADMIN SET REPLICA STATUS
+PROPERTIES ("key" = "value", ...)
+```
+
+The following attributes are currently supported:
+
+"table_id': required. Specify a Tablet Id.
+
+"backend_id": required. Specify a Backend Id.
+
+"status": required. Specify the status. Currently only "bad" and "ok" are supported.
+
+If the specified replica does not exist or its status is bad, the replica will be ignored.
+
+Note:
+
+Replicas set to Bad status may be dropped immediately, please proceed with caution.
+
+## Examples
+
+1. Set the replica status of tablet 10003 on BE 10001 to bad.
+
+    ```sql
+    ADMIN SET REPLICA STATUS PROPERTIES("tablet_id" = "10003", "backend_id" = "10001", "status" = "bad");
+    ```
+
+2. Set the replica status of tablet 10003 on BE 10001 to ok.
+
+    ```sql
+    ADMIN SET REPLICA STATUS PROPERTIES("tablet_id" = "10003", "backend_id" = "10001", "status" = "ok");
+    ```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SHOW_REPLICA_DISTRIBUTION.md b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SHOW_REPLICA_DISTRIBUTION.md
new file mode 100644
index 00000000000000..3c97de0f1a3d85
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SHOW_REPLICA_DISTRIBUTION.md
@@ -0,0 +1,39 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN SHOW REPLICA DISTRIBUTION
+
+## Description
+
+This statement is used to show the distribution status of a table or a partition replica.
+
+:::tip
+
+This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```sql
+ADMIN SHOW REPLICA DISTRIBUTION FROM [db_name.]tbl_name [PARTITION (p1, ...)]
+```
+
+Note:
+
+The Graph column in the result shows the distribution ratio of replicas graphically.
+
+## Examples
+
+1. View the replica distribution of tables
+
+    ```sql
+    ADMIN SHOW REPLICA DISTRIBUTION FROM tbl1;
+    ```
+
+2. View the replica distribution of partitions in the table
+
+    ```sql
+    ADMIN SHOW REPLICA DISTRIBUTION FROM db1.tbl1 PARTITION(p1, p2);
+    ```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SHOW_REPLICA_STATUS.md b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SHOW_REPLICA_STATUS.md
new file mode 100644
index 00000000000000..7448e48c0accb1
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SHOW_REPLICA_STATUS.md
@@ -0,0 +1,58 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN SHOW REPLICA STATUS
+
+## Description
+
+This statement is used to show the status of replicas for a table or a partition.
+
+:::tip
+
+This operation requires the SYSTEM-level OPERATE privilege. You can follow the instructions in [GRANT](../../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```sql
+ADMIN SHOW REPLICA STATUS FROM [db_name.]tbl_name [PARTITION (p1, ...)]
+[where_clause]
+```
+
+```sql
+where_clause:
+WHERE STATUS [!]= "replica_status"
+```
+
+```plain text
+replica_status:
+OK:            The replica is healthy
+DEAD:          The Backend of replica is not available
+VERSION_ERROR: The replica data version is missing
+SCHEMA_ERROR:  The schema hash of replica is incorrect
+MISSING:       The replica does not exist
+```
+
+## Examples
+
+1. View the status of all replicas of the table.
+
+    ```sql
+    ADMIN SHOW REPLICA STATUS FROM db1.tbl1;
+    ```
+
+2. View the replica of a partition with the status of VERSION_ERROR.
+
+    ```sql
+    ADMIN SHOW REPLICA STATUS FROM tbl1 PARTITION (p1, p2)
+    WHERE STATUS = "VERSION_ERROR";
+    ```
+
+3. View all unhealthy replicas of the table.
+
+    ```sql
+    ADMIN SHOW REPLICA STATUS FROM tbl1
+    WHERE STATUS != "OK";
+    ```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/SHOW_TABLE_STATUS.md b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/SHOW_TABLE_STATUS.md
new file mode 100644
index 00000000000000..a917dbce7d8b5a
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/SHOW_TABLE_STATUS.md
@@ -0,0 +1,40 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW TABLE STATUS
+
+## Description
+
+This statement is used to view some of the information in Table.
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```sql
+SHOW TABLE STATUS
+[FROM db] [LIKE "pattern"]
+```
+
+> Note
+>
+> This statement is mainly compatible with MySQL syntax. At present, it only shows a few information, such as Comment.
+
+## Examples
+
+1. View all the information of tables under the current database.
+
+    ```SQL
+    SHOW TABLE STATUS;
+    ```
+
+2. View all the information of tables whose names contain example and who are under specified databases.
+
+    ```SQL
+    SHOW TABLE STATUS FROM db LIKE "%example%";
+    ```
diff --git a/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/_category_.yml b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/_category_.yml
new file mode 100644
index 00000000000000..57ff4764ef6e2e
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/cluster-management/tablet_replica/_category_.yml
@@ -0,0 +1,6 @@
+position: 40 # float position is supported
+label: 'Tablet and replica'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/en/sql-reference/sql-statements/data-definition/ALTER_DATABASE.md b/docs/en/sql-reference/sql-statements/data-definition/ALTER_DATABASE.md
deleted file mode 100644
index 353ccbf0d56c50..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/ALTER_DATABASE.md
+++ /dev/null
@@ -1,74 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ALTER DATABASE
-
-## Description
-
-Configures the properties of the specified database.
-
-:::tip
-
-This operation requires the ALTER privilege on the target database. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-1. Set database data quota in B/K/KB/M/MB/G/GB/T/TB/P/PB.
-
-    ```sql
-    ALTER DATABASE <db_name> SET DATA QUOTA <quota>;
-    ```
-
-2. Rename a database.
-
-    ```sql
-    ALTER DATABASE <db_name> RENAME <new_db_name>;
-    ```
-
-3. Set database replica quota.
-
-    ```sql
-    ALTER DATABASE <db_name> SET REPLICA QUOTA <quota>;
-    ```
-
-Note:
-
-```plain text
-- After renaming the database, use REVOKE and GRANT commands to modify the corresponding user permission if necessary.
-- The database's default data quota and the default replica quota are 2^63-1.
-```
-
-## Examples
-
-1. Set data quota for a database.
-
-    ```SQL
-    ALTER DATABASE example_db SET DATA QUOTA 10995116277760B;
-    -- The above unit is bytes, equivalent to the following statement.
-    ALTER DATABASE example_db SET DATA QUOTA 10T;
-    ALTER DATABASE example_db SET DATA QUOTA 100G;
-    ALTER DATABASE example_db SET DATA QUOTA 200M;
-    ```
-
-2. Rename the database `example_db` as `example_db2`.
-
-    ```SQL
-    ALTER DATABASE example_db RENAME example_db2;
-    ```
-
-3. Set database replica quota.
-
-    ```SQL
-    ALTER DATABASE example_db SET REPLICA QUOTA 102400;
-    ```
-
-## References
-
-- [CREATE DATABASE](CREATE_DATABASE.md)
-- [USE](../data-definition/USE.md)
-- [SHOW DATABASES](../data-manipulation/SHOW_DATABASES.md)
-- [DESC](../Utility/DESCRIBE.md)
-- [DROP DATABASE](../data-definition/DROP_DATABASE.md)
diff --git a/docs/en/sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md
deleted file mode 100644
index 00412e934dafe4..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md
+++ /dev/null
@@ -1,118 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ALTER MATERIALIZED VIEW
-
-## Description
-
-This SQL statement can:
-
-- Alter the name of an asynchronous materialized view.
-- Alter the refresh strategy of an asynchronous materialized view.
-- Alter the status of an asynchronous materialized view to active or inactive.
-- Perform an atomic swap between two asynchronous materialized views.
-- Alter the properties of an asynchronous materialized view.
-
-  You can use this SQL statement to alter the following properties:
-
-  - `partition_ttl_number`
-  - `partition_refresh_number`
-  - `resource_group`
-  - `auto_refresh_partitions_limit`
-  - `excluded_trigger_tables`
-  - `mv_rewrite_staleness_second`
-  - `unique_constraints`
-  - `foreign_key_constraints`
-  - `colocate_with`
-  - All session variable-related properties. For information on session variables, see [System variables](../../../reference/System_variable.md).
-
-:::tip
-
-- This operation requires the ALTER privilege on the target materialized view. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-- ALTER MATERIALIZED VIEW does not support directly modifying the query statement used to build the materialized view. You can build a new materialized view and swap it with the original one using ALTER MATERIALIZED VIEW SWAP WITH.
-
-:::
-
-## Syntax
-
-```SQL
-ALTER MATERIALIZED VIEW [db_name.]<mv_name> 
-    { RENAME [db_name.]<new_mv_name> 
-    | REFRESH <new_refresh_scheme_desc> 
-    | ACTIVE | INACTIVE 
-    | SWAP WITH [db_name.]<mv2_name>
-    | SET ( "<key>" = "<value>"[,...]) }
-```
-
-## Parameters
-
-| **Parameter**           | **Required** | **Description**                                              |
-| ----------------------- | ------------ | ------------------------------------------------------------ |
-| mv_name                 | yes          | The name of the materialized view to alter.                  |
-| new_refresh_scheme_desc | no           | New refresh strategy, see [SQL Reference - CREATE MATERIALIZED VIEW - Parameters](../data-definition/CREATE_MATERIALIZED_VIEW.md#parameters) for details. |
-| new_mv_name             | no           | New name for the materialized view.                          |
-| ACTIVE                  | no           |Set the status of the materialized view to active. StarRocks automatically sets a materialized view to inactive if any of its base tables is changed, for example, dropped and re-created, to prevent the situation that original metadata mismatches the changed base table. Inactive materialized views cannot be used for query acceleration or query rewrite. You can use this SQL to activate the materialized view after changing the base tables. |
-| INACTIVE                | no           | Set the status of the materialized view to inactive. An inactive asynchronous materialized view cannot be refreshed. But you can still query it as a table. |
-| SWAP WITH               | no           | Perform an atomic exchange with another asynchronous materialized view after necessary consistency checks. |
-| key                     | no           | The name of the property to alter, see [SQL Reference - CREATE MATERIALIZED VIEW - Parameters](../data-definition/CREATE_MATERIALIZED_VIEW.md#parameters) for details.<br />**NOTE**<br />If you want to alter a session variable-related property of the materialized view, you must add a `session.` prefix to the property, for example, `session.query_timeout`. You do not need to specify the prefix for non-session properties, for example, `mv_rewrite_staleness_second`. |
-| value                   | no           | The value of the property to alter.                         |
-
-## Example
-
-Example 1: Alter the name of the materialized view.
-
-```SQL
-ALTER MATERIALIZED VIEW lo_mv1 RENAME lo_mv1_new_name;
-```
-
-Example 2: Alter the refresh interval of the materialized view.
-
-```SQL
-ALTER MATERIALIZED VIEW lo_mv2 REFRESH ASYNC EVERY(INTERVAL 1 DAY);
-```
-
-Example 3: Alter the timeout duration for the materialized view refresh tasks to 1 hour (default).
-
-```SQL
-ALTER MATERIALIZED VIEW mv1 SET ("session.query_timeout" = "3600");
-```
-
-Example 4: Alter the materialized view's status to active.
-
-```SQL
-ALTER MATERIALIZED VIEW order_mv ACTIVE;
-```
-
-Example 5: Perform an atomic exchange between materialized views `order_mv` and `order_mv1`.
-
-```SQL
-ALTER MATERIALIZED VIEW order_mv SWAP WITH order_mv1;
-```
-
-Example 6: Enable profile for the materialized view refresh process. This feature is enabled by default.
-
-```SQL
-ALTER MATERIALIZED VIEW mv1 SET ("session.enable_profile" = "true");
-```
-
-Example 7: Enable intermediate result spilling for the materialized view refresh process, and set the mode of spilling to `force`. Intermediate result spilling is enabled by default since v3.1.
-
-```SQL
--- Enable spilling during materialized view refresh.
-ALTER MATERIALIZED VIEW mv1 SET ("session.enable_spill" = "true");
--- Set spill_mode to force (the default value is auto).
-ALTER MATERIALIZED VIEW mv1 SET ("session.spill_mode" = "force");
-```
-
-Example 8: Alter the optimizer timeout duration for materialized view to 30 seconds (default since v3.3) if its query statement contains external tables or multiple joins.
-
-```SQL
-ALTER MATERIALIZED VIEW mv1 SET ("session.new_planner_optimize_timeout" = "30000");
-```
-
-Example 9: Alter the query rewrite staleness time for the materialized view to 600 seconds.
-
-```SQL
-ALTER MATERIALIZED VIEW mv1 SET ("mv_rewrite_staleness_second" = "600");
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/ALTER_RESOURCE.md b/docs/en/sql-reference/sql-statements/data-definition/ALTER_RESOURCE.md
deleted file mode 100644
index d68eed94fc48eb..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/ALTER_RESOURCE.md
+++ /dev/null
@@ -1,37 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ALTER RESOURCE
-
-## Description
-
-You can use the ALTER RESOURCE statement to modify the properties of a resource.
-
-## Syntax
-
-```SQL
-ALTER RESOURCE 'resource_name' SET PROPERTIES ("key"="value", ...)
-```
-
-## Parameters
-
-- `resource_name`: the name of the resource to be modified.
-
-- `PROPERTIES ("key"="value", ...)`: the properties of the resource. You can modify different properties based on resource types. Currently, StarRocks supports modifying the URI of the Hive metastore of the following resources.
-  - Apache Iceberg resources support modifying the following properties:
-    - `iceberg.catalog-impl`: the fully qualified class name of [custom catalog](../../../data_source/External_table.md).
-    - `iceberg.catalog.hive.metastore.uris`: the URI of the Hive metastore.
-  - Apache Hive™ resources and Apache Hudi resources support modifying `hive.metastore.uris`, which indicates the URI of the Hive metastore.
-
-## Usage notes
-
-After you reference a resource to create an external table, if you modify the URI of the Hive metastore of this resource, the external table becomes unavailable. If you still want to use the external table to query data, make sure that the new metastore contains a table whose name and schema are the same as that in the original metastore.
-
-## Examples
-
-Modify the URI of the Hive metastore of Hive resource `hive0`.
-
-```SQL
-ALTER RESOURCE 'hive0' SET PROPERTIES ("hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083")
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/ALTER_TABLE.md b/docs/en/sql-reference/sql-statements/data-definition/ALTER_TABLE.md
deleted file mode 100644
index e9f61a9c62da00..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/ALTER_TABLE.md
+++ /dev/null
@@ -1,1239 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ALTER TABLE
-
-## Description
-
-Modifies an existing table, including:
-
-- [Rename table, partition, index, or column](#rename)
-- [Modify table comment](#alter-table-comment-from-v31)
-- [Modify partitions (add/delete partitions and modify partition attributes)](#modify-partition)
-- [Modify the bucketing method and number of buckets](#modify-the-bucketing-method-and-number-of-buckets-from-v32)
-- [Modify columns (add/delete columns and change the order of columns)](#modify-columns-adddelete-columns-change-the-order-of-columns)
-- [Create/delete rollup index](#modify-rollup-index)
-- [Modify bitmap index](#modify-bitmap-indexes)
-- [Modify table properties](#modify-table-properties)
-- [Atomic swap](#swap)
-- [Manual data version compaction](#manual-compaction-from-31)
-
-:::tip
-This operation requires the ALTER privilege on the destination table.
-:::
-
-## Syntax
-
-```SQL
-ALTER TABLE [<db_name>.]<tbl_name>
-alter_clause1[, alter_clause2, ...]
-```
-
-`alter_clause` can held the following operations: rename, comment, partition, bucket, column, rollup index, bitmap index, table property, swap, and compaction.
-
-- rename: renames a table, rollup index, partition, or column (supported from **v3.3.2 onwards**).
-- comment: modifies the table comment (supported from **v3.1 onwards**).
-- partition: modifies partition properties, drops a partition, or adds a partition.
-- bucket: modifies the bucketing method and number of buckets.
-- column: adds, drops, or reorders columns, or modifies column type.
-- rollup index: creates or drops a rollup index.
-- bitmap index: modifies index (only Bitmap index can be modified).
-- swap: atomic exchange of two tables.
-- compaction: performs manual compaction to merge versions of loaded data (supported from **v3.1 onwards**).
-
-## Limits and usage notes
-
-- Operations on partition, column, and rollup index cannot be performed in one ALTER TABLE statement.
-- Column comments cannot be modified.
-- One table can have only one ongoing schema change operation at a time. You cannot run two schema change commands on a table at the same time.
-- Operations on bucket, column and rollup index are asynchronous operations. A success message is return immediately after the task is submitted. You can run the [SHOW ALTER TABLE](../data-manipulation/SHOW_ALTER.md) command to check the progress, and run the [CANCEL ALTER TABLE](../data-definition/CANCEL_ALTER_TABLE.md) command to cancel the operation.
-- Operations on rename, comment, partition, bitmap index and swap are synchronous operations, and a command return indicates that the execution is finished.
-
-### Rename
-
-Rename supports modification of table name, rollup index, and partition name.
-
-#### Rename a table
-
-```sql
-ALTER TABLE <tbl_name> RENAME <new_tbl_name>
-```
-
-#### Rename a rollup index
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-RENAME ROLLUP <old_rollup_name> <new_rollup_name>
-```
-
-#### Rename a partition
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-RENAME PARTITION <old_partition_name> <new_partition_name>
-```
-
-#### Rename a column
-
-From v3.3.2 onwards, StarRocks supports renaming columns.
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-RENAME COLUMN <old_col_name> [ TO ] <new_col_name>
-```
-
-:::note
-
-- After renaming a column from A to B, adding a new column named A is not supported.
-- Materialized views built on a renamed column will not take effect. You must rebuild them upon the column with the new name.
-
-:::
-
-### Alter table comment (from v3.1)
-
-Syntax:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name> COMMENT = "<new table comment>";
-```
-
-:::tip
-Currently, column comments cannot be modified.
-:::
-
-### Modify partition
-
-#### ADD PARTITION(S)
-
-You can choose to add range partitions or list partitions.
-
-Syntax：
-
-- Range partitions
-
-    ```SQL
-    ALTER TABLE
-        ADD { single_range_partition | multi_range_partitions } [distribution_desc] ["key"="value"];
-
-    single_range_partition ::=
-        PARTITION [IF NOT EXISTS] <partition_name> VALUES partition_key_desc
-
-    partition_key_desc ::=
-        { LESS THAN { MAXVALUE | value_list }
-        | [ value_list , value_list ) } -- Note that [ represents a left-closed interval.
-
-    value_list ::=
-        ( <value> [, ...] )
-
-    multi_range_partitions ::=
-        { PARTITIONS START ("<start_date_value>") END ("<end_date_value>") EVERY ( INTERVAL <N> <time_unit> )
-        | PARTITIONS START ("<start_integer_value>") END ("<end_integer_value>") EVERY ( <granularity> ) } -- The partition column values still need to be enclosed in double quotes even if the partition column values specified by START and END are integers. However, the interval values in the EVERY clause do not need to be enclosed in double quotes.
-    ```
-
-- List partitions
-
-    ```SQL
-    ALTER TABLE
-        ADD PARTITION <partition_name> VALUES IN (value_list) [distribution_desc] ["key"="value"];
-
-    value_list ::=
-        value_item [, ...]
-
-    value_item ::=
-        { <value> | ( <value> [, ...] ) }
-    ```
-
-Parameters:
-
-- Partition-related parameters:
-
-  - For range partitions, you can add a single range partition (`single_range_partition`) or multiple range partitions in batch (`multi_range_partitions`).
-  - For list partitions, you can only add a single list partition.
-
-- `distribution_desc`:
-
-   You can set the number of buckets for the new partition separately, but you cannot set the bucketing method separately.
-
-- `"key"="value"`:
-
-   You can set properties for the new partition. For details, see [CREATE TABLE](./CREATE_TABLE.md#properties).
-
-Examples:
-
-- Range partitions
-
-  - If the partition column is specified as `event_day` at table creation, for example `PARTITION BY RANGE(event_day)`, and a new partition needs to be added after table creation, you can execute:
-
-    ```sql
-    ALTER TABLE site_access ADD PARTITION p4 VALUES LESS THAN ("2020-04-30");
-    ```
-
-  - If the partition column is specified as `datekey` at table creation, for example `PARTITION BY RANGE (datekey)`, and multiple partitions need to be added in batch after table creation, you can execute:
-
-    ```sql
-    ALTER TABLE site_access
-        ADD PARTITIONS START ("2021-01-05") END ("2021-01-10") EVERY (INTERVAL 1 DAY);
-    ```
-
-- List partitions
-
-  - If a single partition column is specified at table creation, for example `PARTITION BY LIST (city)`, and a new partition needs to be added after table creation, you can execute:
-
-    ```sql
-    ALTER TABLE t_recharge_detail2
-    ADD PARTITION pCalifornia VALUES IN ("Los Angeles","San Francisco","San Diego");
-    ```
-
-  - If multiple partition columns are specified at table creation, for example `PARTITION BY LIST (dt,city)`, and a new partition needs to be added after table creation, you can execute:
-
-    ```sql
-    ALTER TABLE t_recharge_detail4 
-    ADD PARTITION p202204_California VALUES IN
-    (
-        ("2022-04-01", "Los Angeles"),
-        ("2022-04-01", "San Francisco"),
-        ("2022-04-02", "Los Angeles"),
-        ("2022-04-02", "San Francisco")
-    );
-    ```
-
-#### DROP PARTITION(S)
-
-- Drop a single partition:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-DROP PARTITION [ IF EXISTS ] <partition_name> [ FORCE ]
-```
-
-- Drop partitions in batch (Supported from v3.3.1):
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-DROP PARTITIONS [ IF EXISTS ]  { partition_name_list | multi_range_partitions } [ FORCE ]
-
-partion_name_list ::= ( <partition_name> [, ... ] )
-
-multi_range_partitions ::=
-    { START ("<start_date_value>") END ("<end_date_value>") EVERY ( INTERVAL <N> <time_unit> )
-    | START ("<start_integer_value>") END ("<end_integer_value>") EVERY ( <granularity> ) } -- The partition column values still need to be enclosed in double quotes even if the partition column values are integers. However, the interval values in the EVERY clause do not need to be enclosed in double quotes.
-```
-
-Notes for `multi_range_partitions`:
-
-- It only appiles to Range Partitioning.
-- The parameters involved is consistent with those in [ADD PARTITION(S)](#add-partitions).
-- It only supports partitions with a single Partition Key.
-
-:::note
-
-- Keep at least one partition for partitioned tables.
-- If FORCE is not specified, you can recover the dropped partitions by using the [RECOVER](./backup_restore/RECOVER.md) command within a specified period (1 day by default).
-- If FORCE is specified, the partitions will be deleted directly regardless of whether there are any unfinished operations on the partitions, and they cannot be recovered. Thus, generally, this operation is not recommended.
-
-:::
-
-#### Add a temporary partition
-
-Syntax:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name> 
-ADD TEMPORARY PARTITION [IF NOT EXISTS] <partition_name>
-partition_desc ["key"="value"]
-[DISTRIBUTED BY HASH (k1[,k2 ...]) [BUCKETS num]]
-```
-
-#### Use a temporary partition to replace the current partition
-
-Syntax:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-REPLACE PARTITION <partition_name>
-partition_desc ["key"="value"]
-WITH TEMPORARY PARTITION
-partition_desc ["key"="value"]
-[PROPERTIES ("key"="value", ...)]
-```
-
-#### Drop a temporary partition
-
-Syntax:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-DROP TEMPORARY PARTITION <partition_name>
-```
-
-#### Modify partition properties
-
-**Syntax**
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-MODIFY PARTITION { <partition_name> | ( <partition1_name> [, <partition2_name> ...] ) | (*) }
-SET ("key" = "value", ...);
-```
-
-**Usages**
-
-- The following properties of a partition can be modified:
-
-  - storage_medium
-  - storage_cooldown_ttl or storage_cooldown_time
-  - replication_num
-
-- For the table that has only one partition, the partition name is the same as the table name. If the table is divided into multiple partitions, you can use `(*)`to modify the properties of all partitions, which is more convenient.
-
-- Execute `SHOW PARTITIONS FROM <tbl_name>` to view the partition properties after modification.
-
-### Modify the bucketing method and number of buckets (from v3.2)
-
-Syntax:
-
-```SQL
-ALTER TABLE [<db_name>.]<table_name>
-[ partition_names ]
-[ distribution_desc ]
-
-partition_names ::= 
-    (PARTITION | PARTITIONS) ( <partition_name> [, <partition_name> ...] )
-
-distribution_desc ::=
-    DISTRIBUTED BY RANDOM [ BUCKETS <num> ] |
-    DISTRIBUTED BY HASH ( <column_name> [, <column_name> ...] ) [ BUCKETS <num> ]
-```
-
-Example:
-
-For example, the original table is a Duplicate Key table where hash bucketing is used and the number of buckets is automatically set by StarRocks.
-
-```SQL
-CREATE TABLE IF NOT EXISTS details (
-    event_time DATETIME NOT NULL COMMENT "datetime of event",
-    event_type INT NOT NULL COMMENT "type of event",
-    user_id INT COMMENT "id of user",
-    device_code INT COMMENT "device code",
-    channel INT COMMENT ""
-)
-DUPLICATE KEY(event_time, event_type)
-PARTITION BY date_trunc('day', event_time)
-DISTRIBUTED BY HASH(user_id);
-
--- Insert data of several days
-INSERT INTO details (event_time, event_type, user_id, device_code, channel) VALUES
--- Data of November 26th
-('2023-11-26 08:00:00', 1, 101, 12345, 2),
-('2023-11-26 09:15:00', 2, 102, 54321, 3),
-('2023-11-26 10:30:00', 1, 103, 98765, 1),
--- Data of November 27th
-('2023-11-27 08:30:00', 1, 104, 11111, 2),
-('2023-11-27 09:45:00', 2, 105, 22222, 3),
-('2023-11-27 11:00:00', 1, 106, 33333, 1),
--- Data of November 28th
-('2023-11-28 08:00:00', 1, 107, 44444, 2),
-('2023-11-28 09:15:00', 2, 108, 55555, 3),
-('2023-11-28 10:30:00', 1, 109, 66666, 1);
-```
-
-#### Modify the bucketing method only
-
-> **NOTICE**
->
-> - The modification is applied to all partitions in the table and cannot be applied to specific partitions only.
-> - Although only the bucketing method needs to be modified, the number of buckets still needs to be specified in the command using `BUCKETS <num>`. If `BUCKETS <num>` is not specified, it means that the number of buckets is automatically determined by StarRocks.
-
-- The bucketing method is modified to random bucketing from hash bucketing and the number of buckets remains automatically set by StarRocks.
-
-  ```SQL
-  ALTER TABLE details DISTRIBUTED BY RANDOM;
-  ```
-
-- The keys for hash bucketing are modified to `user_id, event_time` from `event_time, event_type`. And the number of buckets remains automatically set by StarRocks.
-
-  ```SQL
-  ALTER TABLE details DISTRIBUTED BY HASH(user_id, event_time);
-  ```
-
-#### Modify the number of buckets only
-
-> **NOTICE**
->
-> Although only the number of buckets needs to be modified, the bucketing method still needs to be specified in the command, for example, `HASH(user_id)`.
-
-- Modify the number of buckets for all partitions to 10 from being automatically set by StarRocks.
-
-  ```SQL
-  ALTER TABLE details DISTRIBUTED BY HASH(user_id) BUCKETS 10;
-  ```
-
-- Modify the number of buckets for specified partitions to 15 from being automatically set by StarRocks.
-
-  ```SQL
-  ALTER TABLE details PARTITIONS (p20231127, p20231128) DISTRIBUTED BY HASH(user_id) BUCKETS 15 ;
-  ```
-
-  > **NOTE**
-  >
-  > Partition names can be viewed by executing `SHOW PARTITIONS FROM <table_name>;`.
-
-#### Modify both the bucketing method and the number of buckets
-
-> **NOTICE**
->
-> The modification is applied to all partitions in the table and cannot be applied to specific partitions only.
-
-- Modify the bucketing method from hash bucketing to random bucketing, and change the number of buckets to 10 from being automatically set by StarRocks.
-
-   ```SQL
-   ALTER TABLE details DISTRIBUTED BY RANDOM BUCKETS 10;
-   ```
-
-- Modify the key for hash bucketing, and change the number of buckets to 10 from being automatically set by StarRocks. The key used for hashing bucketing is modified to `user_id, event_time` from the original `event_time, event_type`. The number of buckets is modified to 10 from automatically set by StarRocks.
-
-  ```SQL
-  ALTER TABLE details DISTRIBUTED BY HASH(user_id, event_time) BUCKETS 10;
-  ``
-
-### Modify columns (add/delete columns, change the order of columns)
-
-#### Add a column to the specified location of the specified index
-
-Syntax:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-ADD COLUMN column_name column_type [KEY | agg_type] [DEFAULT "default_value"]
-[AFTER column_name|FIRST]
-[TO rollup_index_name]
-[PROPERTIES ("key"="value", ...)]
-```
-
-Note:
-
-1. If you add a value column to an Aggregate table, you need to specify agg_type.
-2. If you add a key column to a non-Aggregate table (such as a Duplicate Key table), you need to specify the KEY keyword.
-3. You cannot add a column that already exists in the base index to the rollup index. (You can recreate a rollup index if needed.)
-
-#### Add multiple columns to specified index
-
-Syntax:
-
-- Add multiple columns
-
-  ```sql
-  ALTER TABLE [<db_name>.]<tbl_name>
-  ADD COLUMN (column_name1 column_type [KEY | agg_type] DEFAULT "default_value", ...)
-  [TO rollup_index_name]
-  [PROPERTIES ("key"="value", ...)]
-  ```
-
-- Add multiple columns and use AFTER to specify locations of the added columns
-
-  ```sql
-  ALTER TABLE [<db_name>.]<tbl_name>
-  ADD COLUMN column_name1 column_type [KEY | agg_type] DEFAULT "default_value" AFTER column_name,
-  ADD COLUMN column_name2 column_type [KEY | agg_type] DEFAULT "default_value" AFTER column_name
-  [, ...]
-  [TO rollup_index_name]
-  [PROPERTIES ("key"="value", ...)]
-  ```
-
-Note:
-
-1. If you add a value column to an Aggregate table, you need to specify `agg_type`.
-
-2. If you add a key column to a non-Aggregate table, you need to specify the KEY keyword.
-
-3. You cannot add a column that already exists in the base index to the rollup index. (You can create another rollup index if needed.)
-
-#### Add a generated column (from v3.1)
-
-Syntax:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-ADD COLUMN col_name data_type [NULL] AS generation_expr [COMMENT 'string']
-```
-
-You can add a generated column and specify its expression. [The generated column](../generated_columns.md) can be used to precompute and store the results of expressions, which significantly accelerates queries with the same complex expressions. Since v3.1, StarRocks supports generated columns.
-
-#### Drop a column from specified index
-
-Syntax:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-DROP COLUMN column_name
-[FROM rollup_index_name];
-```
-
-Note:
-
-1. You cannot drop partition column.
-2. If the column is dropped from the base index, it will also be dropped if it is included in the rollup index.
-
-#### Modify the column type and column position of specified index
-
-Syntax:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-MODIFY COLUMN column_name column_type [KEY | agg_type] [NULL | NOT NULL] [DEFAULT "default_value"]
-[AFTER column_name|FIRST]
-[FROM rollup_index_name]
-[PROPERTIES ("key"="value", ...)]
-```
-
-Note:
-
-1. If you modify the value column in aggregation models, you need to specify agg_type.
-2. If you modify the key column in non-aggregation models, you need to specify the KEY keyword.
-3. Only the type of column can be modified. The other properties of the column remain as they are currently. (i.e. other properties need to be explicitly written in the statement according to the original property, see example 8 in the [column](#column) part).
-4. The partition column cannot be modified.
-5. The following types of conversions are currently supported (accuracy loss is guaranteed by the user).
-
-   - Convert TINYINT/SMALLINT/INT/BIGINT to TINYINT/SMALLINT/INT/BIGINT/DOUBLE.
-   - Convert TINYINT/SMALLINT/INT/BIGINT/LARGEINT/FLOAT/DOUBLE/DECIMAL to VARCHAR. VARCHAR supports modification of maximum length.
-   - Convert VARCHAR to TINYINT/SMALLINT/INT/BIGINT/LARGEINT/FLOAT/DOUBLE.
-   - Convert VARCHAR to DATE (currently support six formats: "%Y-%m-%d", "%y-%m-%d", "%Y%m%d", "%y%m%d", "%Y/%m/%d, "%y/%m/%d")
-   - Convert DATETIME to DATE(only year-month-day information is retained, i.e.  `2019-12-09 21:47:05` `<-->` `2019-12-09`)
-   - Convert DATE to DATETIME (set hour, minute, second to zero, For example: `2019-12-09` `<-->` `2019-12-09 00:00:00`)
-   - Convert FLOAT to DOUBLE
-   - Convert INT to DATE (If the INT data fails to convert, the original data remains the same)
-
-6. Conversion from NULL to NOT NULL is not supported.
-
-#### Reorder the columns of specified index
-
-Syntax:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-ORDER BY (column_name1, column_name2, ...)
-[FROM rollup_index_name]
-[PROPERTIES ("key"="value", ...)]
-```
-
-Note:
-
-- All columns in the index must be written.
-- The value column is listed after the key column.
-
-#### Modify the sort key
-
-Since v3.0, the sort keys for the Primary Key tables can be modified. v3.3 extends this support to Duplicate Key tables, Aggregate tables, and Unique Key tables.
-
-The sort keys in Duplicate Key tables and Primary Key tables can be combination of any sort columns. The sort keys in Aggregate tables and Unique Key tables must include all key columns, but the order of the columns does not need to be same as the key columns.
-
-Syntax:
-
-```SQL
-ALTER TABLE [<db_name>.]<table_name>
-[ order_desc ]
-
-order_desc ::=
-    ORDER BY <column_name> [, <column_name> ...]
-```
-
-Example: modify the sort keys in Primary Key tables.
-
-For example, the original table is a Primary Key table where the sort key and the primary key are coupled, which is `dt, order_id`.
-
-```SQL
-create table orders (
-    dt date NOT NULL,
-    order_id bigint NOT NULL,
-    user_id int NOT NULL,
-    merchant_id int NOT NULL,
-    good_id int NOT NULL,
-    good_name string NOT NULL,
-    price int NOT NULL,
-    cnt int NOT NULL,
-    revenue int NOT NULL,
-    state tinyint NOT NULL
-) PRIMARY KEY (dt, order_id)
-PARTITION BY date_trunc('day', dt)
-DISTRIBUTED BY HASH(order_id);
-```
-
-Decouple the sort key from the primary key, and modify the sort key to `dt, revenue, state`.
-
-```SQL
-ALTER TABLE orders ORDER BY (dt, revenue, state);
-```
-
-#### Modify a STRUCT column to add or drop a field
-
-From v3.2.10 and v3.3.2 onwards, StarRocks supports modifying a STRUCT column to add or drop a field, which can be nested or within an ARRAY type.
-
-Syntax:
-
-```sql
--- Add a field
-ALTER TABLE [<db_name>.]<tbl_name>
-MODIFY COLUMN <column_name> ADD FIELD <field_name> <field_type> [AFTER <prior_field_name> |FIRST]
-
--- Drop a field
-ALTER TABLE [<db_name>.]<tbl_name>
-MODIFY COLUMN <column_name> DROP FIELD <field_name>
-```
-
-Parameters:
-
-- `field_name`: The name of the field to be added or removed. This can be a simple field name, indicating a top-dimension field, for example, `new_field_name`, or a Column Access Path, representing a nested field, for example, `lv1_k1.lv2_k2.new_field_name`.
-- `prior_field_name`: The field preceding the newly added field. Used in conjunction with the AFTER keyword to specify the order of the new field. You do not need to specify this parameter if the FIRST keyword is used, indicating the new field should be the first field. The dimension of `prior_field_name` is determined by `field_name` and does not need to be specified explicitly.
-
-For more usage instructions, see [Example - Column -14](#column).
-
-:::note
-
-- Currently, this feature is only supported in shared-nothing clusters.
-- The table must have the `fast_schema_evolution` property enabled.
-- Adding or dropping fields in the STRUCT type within a MAP type is not supported.
-- Newly added fields cannot have default values or attributes such as Nullable specified. They default to being Nullable, with a default value of null.
-- After this feature is used, downgrading the cluster directly to a version that does not support this feature is not allowed.
-
-:::
-
-
-### Modify rollup index
-
-#### Create a rollup index
-
-Syntax:
-
-```SQL
-ALTER TABLE [<db_name>.]<tbl_name> 
-ADD ROLLUP rollup_name (column_name1, column_name2, ...)
-[FROM from_index_name]
-[PROPERTIES ("key"="value", ...)]
-```
-
-PROPERTIES: Support setting timeout time and the default timeout time is one day.
-
-Example:
-
-```SQL
-ALTER TABLE [<db_name>.]<tbl_name> 
-ADD ROLLUP r1(col1,col2) from r0;
-```
-
-#### Create rollup indexes in batches
-
-Syntax:
-
-```SQL
-ALTER TABLE [<db_name>.]<tbl_name>
-ADD ROLLUP [rollup_name (column_name1, column_name2, ...)
-[FROM from_index_name]
-[PROPERTIES ("key"="value", ...)],...];
-```
-
-Example:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-ADD ROLLUP r1(col1,col2) from r0, r2(col3,col4) from r0;
-```
-
-Note:
-
-1. If from_index_name is not specified, then create from base index by default.
-2. The columns in the rollup table must be existing columns in from_index.
-3. In properties, user can specify the storage format. See CREATE TABLE for details.
-
-#### Drop a rollup index
-
-Syntax:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-DROP ROLLUP rollup_name [PROPERTIES ("key"="value", ...)];
-```
-
-Example:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name> DROP ROLLUP r1;
-```
-
-#### Batch drop rollup indexes
-
-Syntax:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-DROP ROLLUP [rollup_name [PROPERTIES ("key"="value", ...)],...];
-```
-
-Example:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name> DROP ROLLUP r1, r2;
-```
-
-Note: You cannot drop the base index.
-
-### Modify bitmap indexes
-
-Bitmap index supports the following modifications:
-
-#### Create a bitmap index
-
-Syntax:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-ADD INDEX index_name (column [, ...],) [USING BITMAP] [COMMENT 'balabala'];
-```
-
-Note:
-
-```plain text
-1. Bitmap index is only supported for the current version.
-2. A BITMAP index is created only in a single column.
-```
-
-#### Drop an bitmap index
-
-Syntax:
-
-```sql
-DROP INDEX index_name;
-```
-
-### Modify table properties
-
-Syntax:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-SET ("key" = "value",...)
-```
-
-Currently, StarRocks supports modifying the following table properties:
-
-- `replication_num`
-- `default.replication_num`
-- `storage_cooldown_ttl`
-- `storage_cooldown_time`
-- Dynamic partitioning related properties
-- `enable_persistent_index`
-- `bloom_filter_columns`
-- `colocate_with`
-- `bucket_size` (supported since 3.2)
-
-Note:
-You can also modify the properties by merging into the above operation on column. See the [following examples](#examples).
-
-### Swap
-
-Swap supports atomic exchange of two tables.
-
-Syntax:
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-SWAP WITH <tbl_name>;
-```
-
-### Manual compaction (from 3.1)
-
-StarRocks uses a compaction mechanism to merge different versions of loaded data. This feature can combine small files into large files, which effectively improves query performance.
-
-Before v3.1, compaction is performed in two ways:
-
-- Automatic compaction by system: Compaction is performed at the BE level in the background. Users cannot specify database or table for compaction.
-- Users can perform compaction by calling an HTTP interface.
-
-Starting from v3.1, StarRocks offers a SQL interface for users to manually perform compaction by running SQL commands. They can choose a specific table or partition for compaction. This provides more flexibility and control over the compaction process.
-
-Shared-data clusters support this feature from v3.3.0 onwards.
-
-Syntax:
-
-```SQL
-ALTER TABLE <tbl_name> [ BASE | CUMULATIVE ] COMPACT [ <partition_name> | ( <partition1_name> [, <partition2_name> ...] ) ]
-```
-
-That is:
-
-```SQL
--- Perform compaction on the entire table.
-ALTER TABLE <tbl_name> COMPACT
-
--- Perform compaction on a single partition.
-ALTER TABLE <tbl_name> COMPACT <partition_name>
-
--- Perform compaction on multiple partitions.
-ALTER TABLE <tbl_name> COMPACT (<partition1_name>[,<partition2_name>,...])
-
--- Perform cumulative compaction.
-ALTER TABLE <tbl_name> CUMULATIVE COMPACT (<partition1_name>[,<partition2_name>,...])
-
--- Perform base compaction.
-ALTER TABLE <tbl_name> BASE COMPACT (<partition1_name>[,<partition2_name>,...])
-```
-
-The `be_compactions` table in the `information_schema` database records compaction results. You can run `SELECT * FROM information_schema.be_compactions;` to query data versions after compaction.
-
-## Examples
-
-### Table
-
-1. Modify the default number of replicas of the table, which is used as the default number of replicas for newly added partitions.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    SET ("default.replication_num" = "2");
-    ```
-
-2. Modify the actual number of replicas of a single-partition table.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    SET ("replication_num" = "3");
-    ```
-
-3. Modify data writing and replication mode among replicas.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    SET ("replicated_storage" = "false");
-    ```
-
-   This example sets the data writing and replication mode among replicas to "leaderless replication", which means data is written to multiple replicas at the same time without differentiating primary and secondary replicas. For more information, see the `replicated_storage` parameter in [CREATE TABLE](CREATE_TABLE.md).
-
-### Partition
-
-1. Add a partition and use the default bucketing mode. The existing partition is [MIN, 2013-01-01). The added partition is [2013-01-01, 2014-01-01).
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD PARTITION p1 VALUES LESS THAN ("2014-01-01");
-    ```
-
-2. Add a partition and use the new number of buckets.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD PARTITION p1 VALUES LESS THAN ("2015-01-01")
-    DISTRIBUTED BY HASH(k1);
-    ```
-
-3. Add a partition and use the new number of replicas.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD PARTITION p1 VALUES LESS THAN ("2015-01-01")
-    ("replication_num"="1");
-    ```
-
-4. Alter the number of replicas for a partition.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    MODIFY PARTITION p1 SET("replication_num"="1");
-    ```
-
-5. Batch alter the number of replicas for specified partitions.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    MODIFY PARTITION (p1, p2, p4) SET("replication_num"="1");
-    ```
-
-6. Batch alter the storage medium of all partitions.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    MODIFY PARTITION (*) SET("storage_medium"="HDD");
-    ```
-
-7. Drop a partition.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    DROP PARTITION p1;
-    ```
-
-8. Add a partition that has upper and lower boundaries.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD PARTITION p1 VALUES [("2014-01-01"), ("2014-02-01"));
-    ```
-
-### Rollup index
-
-1. Create an rollup index `example_rollup_index` based on the base index (k1,k2,k3,v1,v2). Column-based storage is used.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD ROLLUP example_rollup_index(k1, k3, v1, v2)
-    PROPERTIES("storage_type"="column");
-    ```
-
-2. Create an index `example_rollup_index2` based on `example_rollup_index(k1,k3,v1,v2)`.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD ROLLUP example_rollup_index2 (k1, v1)
-    FROM example_rollup_index;
-    ```
-
-3. Create an index `example_rollup_index3` based on the base index (k1, k2, k3, v1). The rollup timeout time is set to one hour.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD ROLLUP example_rollup_index3(k1, k3, v1)
-    PROPERTIES("storage_type"="column", "timeout" = "3600");
-    ```
-
-4. Drop an index `example_rollup_index2`.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    DROP ROLLUP example_rollup_index2;
-    ```
-
-### Column
-
-1. Add a key column `new_col` (non-aggregate column) after the `col1` column of `example_rollup_index`.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD COLUMN new_col INT KEY DEFAULT "0" AFTER col1
-    TO example_rollup_index;
-    ```
-
-2. Add a value column `new_col` (non-aggregate column) after the `col1` column of `example_rollup_index`.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD COLUMN new_col INT DEFAULT "0" AFTER col1
-    TO example_rollup_index;
-    ```
-
-3. Add a key column `new_col` (aggregate column) after the `col1` column of `example_rollup_index`.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD COLUMN new_col INT DEFAULT "0" AFTER col1
-    TO example_rollup_index;
-    ```
-
-4. Add a value column `new_col SUM` (aggregate column) after the `col1` column of `example_rollup_index`.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD COLUMN new_col INT SUM DEFAULT "0" AFTER col1
-    TO example_rollup_index;
-    ```
-
-5. Add multiple columns to `example_rollup_index` (aggregate).
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD COLUMN (col1 INT DEFAULT "1", col2 FLOAT SUM DEFAULT "2.3")
-    TO example_rollup_index;
-    ```
-
-6. Add multiple columns to `example_rollup_index` (aggregate) and specify the locations of the added columns using `AFTER`.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD COLUMN col1 INT DEFAULT "1" AFTER `k1`,
-    ADD COLUMN col2 FLOAT SUM AFTER `v2`,
-    TO example_rollup_index;
-    ```
-
-7. Drop a column from `example_rollup_index`.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    DROP COLUMN col2
-    FROM example_rollup_index;
-    ```
-
-8. Modify the column type of col1 of the base index to BIGINT and put it after `col2`.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    MODIFY COLUMN col1 BIGINT DEFAULT "1" AFTER col2;
-    ```
-
-9. Modify the maximum length of the `val1` column of the base index to 64. The original length is 32.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    MODIFY COLUMN val1 VARCHAR(64) REPLACE DEFAULT "abc";
-    ```
-
-10. Reorder the columns in `example_rollup_index`. The original column order is k1, k2, k3, v1, v2.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ORDER BY (k3,k1,k2,v2,v1)
-    FROM example_rollup_index;
-    ```
-
-11. Perform two operations (ADD COLUMN and ORDER BY) at one time.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD COLUMN v2 INT MAX DEFAULT "0" AFTER k2 TO example_rollup_index,
-    ORDER BY (k3,k1,k2,v2,v1) FROM example_rollup_index;
-    ```
-
-12. Alter the bloomfilter columns of the table.
-
-     ```sql
-     ALTER TABLE example_db.my_table
-     SET ("bloom_filter_columns"="k1,k2,k3");
-     ```
-
-     This operation can also be merged into the above column operation (note that the syntax of multiple clauses is slightly different).
-
-     ```sql
-     ALTER TABLE example_db.my_table
-     DROP COLUMN col2
-     PROPERTIES ("bloom_filter_columns"="k1,k2,k3");
-     ```
-
-13. Modify the data type of multiple columns in a single statement.
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    MODIFY COLUMN k1 VARCHAR(100) KEY NOT NULL,
-    MODIFY COLUMN v2 DOUBLE DEFAULT "1" AFTER v1;
-    ```
-
-14. Add and drop fields in STRUCT-type data.
-
-    **Prerequisites**: Create a table and insert a row of data.
-
-    ```sql
-    CREATE TABLE struct_test(
-        c0 INT,
-        c1 STRUCT<v1 INT, v2 STRUCT<v4 INT, v5 INT>, v3 INT>,
-        c2 STRUCT<v1 INT, v2 ARRAY<STRUCT<v3 INT, v4 STRUCT<v5 INT, v6 INT>>>>
-    )
-    DUPLICATE KEY(c0)
-    DISTRIBUTED BY HASH(`c0`) BUCKETS 1
-    PROPERTIES (
-        "fast_schema_evolution" = "true"
-    );
-    INSERT INTO struct_test VALUES (
-        1, 
-        ROW(1, ROW(2, 3), 4), 
-        ROW(5, [ROW(6, ROW(7, 8)), ROW(9, ROW(10, 11))])
-    );
-    ```
-
-    ```plain
-    mysql> SELECT * FROM struct_test\G
-    *************************** 1. row ***************************
-    c0: 1
-    c1: {"v1":1,"v2":{"v4":2,"v5":3},"v3":4}
-    c2: {"v1":5,"v2":[{"v3":6,"v4":{"v5":7,"v6":8}},{"v3":9,"v4":{"v5":10,"v6":11}}]}
-    ```
-
-    - Add a new field to a STRUCT-type column.
-
-    ```sql
-    ALTER TABLE struct_test MODIFY COLUMN c1 ADD FIELD v4 INT AFTER v2;
-    ```
-
-    ```plain
-    mysql> SELECT * FROM struct_test\G
-    *************************** 1. row ***************************
-    c0: 1
-    c1: {"v1":1,"v2":{"v4":2,"v5":3},"v4":null,"v3":4}
-    c2: {"v1":5,"v2":[{"v3":6,"v4":{"v5":7,"v6":8}},{"v3":9,"v4":{"v5":10,"v6":11}}]}
-    ```
-
-    - Add a new field to a nested STRUCT type.
-
-    ```sql
-    ALTER TABLE struct_test MODIFY COLUMN c1 ADD FIELD v2.v6 INT FIRST;
-    ```
-
-    ```plain
-    mysql> SELECT * FROM struct_test\G
-    *************************** 1. row ***************************
-    c0: 1
-    c1: {"v1":1,"v2":{"v6":null,"v4":2,"v5":3},"v4":null,"v3":4}
-    c2: {"v1":5,"v2":[{"v3":6,"v4":{"v5":7,"v6":8}},{"v3":9,"v4":{"v5":10,"v6":11}}]}
-    ```
-
-    - Add a new field to a STRUCT type in an array.
-
-    ```sql
-    ALTER TABLE struct_test MODIFY COLUMN c2 ADD FIELD v2.[*].v7 INT AFTER v3;
-    ```
-
-    ```plain
-    mysql> SELECT * FROM struct_test\G
-    *************************** 1. row ***************************
-    c0: 1
-    c1: {"v1":1,"v2":{"v6":null,"v4":2,"v5":3},"v4":null,"v3":4}
-    c2: {"v1":5,"v2":[{"v3":6,"v7":null,"v4":{"v5":7,"v6":8}},{"v3":9,"v7":null,"v4":{"v5":10,"v6":11}}]}
-    ```
-
-    - Drop a field from a STRUCT-type column.
-
-    ```sql
-    ALTER TABLE struct_test MODIFY COLUMN c1 DROP FIELD v3;
-    ```
-
-    ```plain
-    mysql> SELECT * FROM struct_test\G
-    *************************** 1. row ***************************
-    c0: 1
-    c1: {"v1":1,"v2":{"v6":null,"v4":2,"v5":3},"v4":null}
-    c2: {"v1":5,"v2":[{"v3":6,"v7":null,"v4":{"v5":7,"v6":8}},{"v3":9,"v7":null,"v4":{"v5":10,"v6":11}}]}
-    ```
-
-    - Drop a field from a nested STRUCT type.
-
-    ```sql
-    ALTER TABLE struct_test MODIFY COLUMN c1 DROP FIELD v2.v4;
-    ```
-
-    ```plain
-    mysql> SELECT * FROM struct_test\G
-    *************************** 1. row ***************************
-    c0: 1
-    c1: {"v1":1,"v2":{"v6":null,"v5":3},"v4":null}
-    c2: {"v1":5,"v2":[{"v3":6,"v7":null,"v4":{"v5":7,"v6":8}},{"v3":9,"v7":null,"v4":{"v5":10,"v6":11}}]}
-    ```
-
-    - Drop a field from a STRUCT type in an array.
-
-    ```sql
-    ALTER TABLE struct_test MODIFY COLUMN c2 DROP FIELD v2.[*].v3;
-    ```
-
-    ```plain
-    mysql> SELECT * FROM struct_test\G
-    *************************** 1. row ***************************
-    c0: 1
-    c1: {"v1":1,"v2":{"v6":null,"v5":3},"v4":null}
-    c2: {"v1":5,"v2":[{"v7":null,"v4":{"v5":7,"v6":8}},{"v7":null,"v4":{"v5":10,"v6":11}}]}
-    ```
-
-### Table property
-
-1. Alter the Colocate property of the table.
-
-     ```sql
-     ALTER TABLE example_db.my_table
-     SET ("colocate_with" = "t1");
-     ```
-
-2. Alter the dynamic partition property of the table.
-
-     ```sql
-     ALTER TABLE example_db.my_table
-     SET ("dynamic_partition.enable" = "false");
-     ```
-
-     If you need to add dynamic partition properties to a table with no dynamic partition properties configured, you need to specify all the dynamic partition properties.
-
-     ```sql
-     ALTER TABLE example_db.my_table
-     SET (
-         "dynamic_partition.enable" = "true",
-         "dynamic_partition.time_unit" = "DAY",
-         "dynamic_partition.end" = "3",
-         "dynamic_partition.prefix" = "p",
-         "dynamic_partition.buckets" = "32"
-         );
-     ```
-
-### Rename
-
-1. Rename `table1` to `table2`.
-
-    ```sql
-    ALTER TABLE table1 RENAME table2;
-    ```
-
-2. Rename rollup index `rollup1` of `example_table` to `rollup2`.
-
-    ```sql
-    ALTER TABLE example_table RENAME ROLLUP rollup1 rollup2;
-    ```
-
-3. Rename partition `p1` of `example_table` to `p2`.
-
-    ```sql
-    ALTER TABLE example_table RENAME PARTITION p1 p2;
-    ```
-
-### Bitmap index
-
-1. Create a bitmap index for column `siteid` in `table1`.
-
-    ```sql
-    ALTER TABLE table1
-    ADD INDEX index_1 (siteid) [USING BITMAP] COMMENT 'balabala';
-    ```
-
-2. Drop the bitmap index of column `siteid` in `table1`.
-
-    ```sql
-    ALTER TABLE table1
-    DROP INDEX index_1;
-    ```
-
-### Swap
-
-Atomic swap between `table1` and `table2`.
-
-```sql
-ALTER TABLE table1 SWAP WITH table2
-```
-
-### Manual compaction
-
-```sql
-CREATE TABLE compaction_test( 
-    event_day DATE,
-    pv BIGINT)
-DUPLICATE KEY(event_day)
-PARTITION BY date_trunc('month', event_day)
-DISTRIBUTED BY HASH(event_day) BUCKETS 8
-PROPERTIES("replication_num" = "3");
-
-INSERT INTO compaction_test VALUES
-('2023-02-14', 2),
-('2033-03-01',2);
-{'label':'insert_734648fa-c878-11ed-90d6-00163e0dcbfc', 'status':'VISIBLE', 'txnId':'5008'}
-
-INSERT INTO compaction_test VALUES
-('2023-02-14', 2),('2033-03-01',2);
-{'label':'insert_85c95c1b-c878-11ed-90d6-00163e0dcbfc', 'status':'VISIBLE', 'txnId':'5009'}
-
-ALTER TABLE compaction_test COMPACT;
-
-ALTER TABLE compaction_test COMPACT p203303;
-
-ALTER TABLE compaction_test COMPACT (p202302,p203303);
-
-ALTER TABLE compaction_test CUMULATIVE COMPACT (p202302,p203303);
-
-ALTER TABLE compaction_test BASE COMPACT (p202302,p203303);
-```
-
-## References
-
-- [CREATE TABLE](./CREATE_TABLE.md)
-- [SHOW CREATE TABLE](../data-manipulation/SHOW_CREATE_TABLE.md)
-- [SHOW TABLES](../data-manipulation/SHOW_TABLES.md)
-- [SHOW ALTER TABLE](../data-manipulation/SHOW_ALTER.md)
-- [DROP TABLE](./DROP_TABLE.md)
diff --git a/docs/en/sql-reference/sql-statements/data-definition/ALTER_VIEW.md b/docs/en/sql-reference/sql-statements/data-definition/ALTER_VIEW.md
deleted file mode 100644
index 9edc087fdf2bf4..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/ALTER_VIEW.md
+++ /dev/null
@@ -1,39 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ALTER VIEW
-
-## Description
-
-Modifies the definition of a view.
-
-## Syntax
-
-```sql
-ALTER VIEW
-[db_name.]view_name
-(column1[ COMMENT "col comment"][, column2, ...])
-AS query_stmt
-```
-
-Note:
-
-1. View is logical, where the data isn't stored in the physical medium. The view will be used as a subquery in the statement when queried. Therefore, modifying the definition of views is equivalent to modifying query_stmt.
-2. query_stmt is arbitrarily supported SQL.
-
-## Examples
-
-Alter `example_view` on `example_db`.
-
-```sql
-ALTER VIEW example_db.example_view
-(
-c1 COMMENT "column 1",
-c2 COMMENT "column 2",
-c3 COMMENT "column 3"
-)
-AS SELECT k1, k2, SUM(v1) 
-FROM example_table
-GROUP BY k1, k2
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/ANALYZE_TABLE.md b/docs/en/sql-reference/sql-statements/data-definition/ANALYZE_TABLE.md
deleted file mode 100644
index b014e478ca52da..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/ANALYZE_TABLE.md
+++ /dev/null
@@ -1,124 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ANALYZE TABLE
-
-## Description
-
-Creates a manual collection task for collecting CBO statistics. By default, manual collection is a synchronous operation. You can also set it to an asynchronous operation. In asynchronous mode, after you run ANALYZE TABLE, the system immediately returns whether this statement is successful. However, the collection task will be running in the background and you do not have to wait for the result. You can check the status of the task by running SHOW ANALYZE STATUS. Asynchronous collection is suitable for tables with large data volume, whereas synchronous collection is suitable for tables with small data volume.
-
-**Manual collection tasks are run only once after creation. You do not need to delete manual collection tasks.**
-
-This statement is supported from v2.4.
-
-### Manually collect basic statistics
-
-For more information about basic statistics, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md#basic-statistics).
-
-#### Syntax
-
-```SQL
-ANALYZE [FULL|SAMPLE] TABLE tbl_name (col_name [,col_name])
-[WITH SYNC | ASYNC MODE]
-PROPERTIES (property [,property])
-```
-
-#### Parameter description
-
-- Collection type
-  - FULL: indicates full collection.
-  - SAMPLE: indicates sampled collection.
-  - If no collection type is specified, full collection is used by default.
-
-- `col_name`: columns from which to collect statistics. Separate multiple columns with commas (`,`). If this parameter is not specified, the entire table is collected.
-
-- [WITH SYNC | ASYNC MODE]: whether to run the manual collection task in synchronous or asynchronous mode. Synchronous collection is used by default if you do not specify this parameter.
-
-- `PROPERTIES`: custom parameters. If `PROPERTIES` is not specified, the default settings in the `fe.conf` file are used. The properties that are actually used can be viewed via the `Properties` column in the output of SHOW ANALYZE STATUS.
-
-| **PROPERTIES**                | **Type** | **Default value** | **Description**                                              |
-| ----------------------------- | -------- | ----------------- | ------------------------------------------------------------ |
-| statistic_sample_collect_rows | INT      | 200000            | The minimum number of rows to collect for sampled collection.If the parameter value exceeds the actual number of rows in your table, full collection is performed. |
-
-#### Examples
-
-Example 1: Manual full collection
-
-```SQL
--- Manually collect full stats of a table using default settings.
-ANALYZE TABLE tbl_name;
-
--- Manually collect full stats of a table using default settings.
-ANALYZE FULL TABLE tbl_name;
-
--- Manually collect stats of specified columns in a table using default settings.
-ANALYZE TABLE tbl_name(c1, c2, c3);
-```
-
-Example 2: Manual sampled collection
-
-```SQL
--- Manually collect partial stats of a table using default settings.
-ANALYZE SAMPLE TABLE tbl_name;
-
--- Manually collect stats of specified columns in a table, with the number of rows to collect specified.
-ANALYZE SAMPLE TABLE tbl_name (v1, v2, v3) PROPERTIES(
-    "statistic_sample_collect_rows" = "1000000"
-);
-```
-
-### Manually collect histograms
-
-For more information about histograms, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md#histogram).
-
-#### Syntax
-
-```SQL
-ANALYZE TABLE tbl_name UPDATE HISTOGRAM ON col_name [, col_name]
-[WITH SYNC | ASYNC MODE]
-[WITH N BUCKETS]
-PROPERTIES (property [,property]);
-```
-
-#### Parameter description
-
-- `col_name`: columns from which to collect statistics. Separate multiple columns with commas (`,`). If this parameter is not specified, the entire table is collected. This parameter is required for histograms.
-
-- [WITH SYNC | ASYNC MODE]: whether to run the manual collection task in synchronous or asynchronous mode. Synchronous collection is used by default if you do not specify this parameter.
-
-- `WITH N BUCKETS`: `N` is the number of buckets for histogram collection. If not specified, the default value in `fe.conf` is used.
-
-- PROPERTIES: custom parameters. If `PROPERTIES` is not specified, the default settings in `fe.conf` are used. The properties that are actually used can be viewed via the `Properties` column in the output of SHOW ANALYZE STATUS.
-
-| **PROPERTIES**                 | **Type** | **Default value** | **Description**                                              |
-| ------------------------------ | -------- | ----------------- | ------------------------------------------------------------ |
-| statistic_sample_collect_rows  | INT      | 200000            | The minimum number of rows to collect. If the parameter value exceeds the actual number of rows in your table, full collection is performed. |
-| histogram_buckets_size         | LONG     | 64                | The default bucket number for a histogram.                   |
-| histogram_mcv_size             | INT      | 100               | The number of most common values (MCV) for a histogram.      |
-| histogram_sample_ratio         | FLOAT    | 0.1               | The sampling ratio for a histogram.                          |
-| histogram_max_sample_row_count | LONG     | 10000000          | The maximum number of rows to collect for a histogram.       |
-
-The number of rows to collect for a histogram is controlled by multiple parameters. It is the larger value between `statistic_sample_collect_rows` and table row count * `histogram_sample_ratio`. The number cannot exceed the value specified by `histogram_max_sample_row_count`. If the value is exceeded, `histogram_max_sample_row_count` takes precedence.
-
-#### Examples
-
-```SQL
--- Manually collect histograms on v1 using the default settings.
-ANALYZE TABLE tbl_name UPDATE HISTOGRAM ON v1;
-
--- Manually collect histograms on v1 and v2, with 32 buckets, 32 MCVs, and 50% sampling ratio.
-ANALYZE TABLE tbl_name UPDATE HISTOGRAM ON v1,v2 WITH 32 BUCKETS 
-PROPERTIES(
-   "histogram_mcv_size" = "32",
-   "histogram_sample_ratio" = "0.5"
-);
-```
-
-## References
-
-[SHOW ANALYZE STATUS](../data-definition/SHOW_ANALYZE_STATUS.md): view the status of a manual collection task.
-
-[KILL ANALYZE](../data-definition/KILL_ANALYZE.md): cancel a manual collection task that is running.
-
-For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/data-definition/CANCEL_ALTER_TABLE.md b/docs/en/sql-reference/sql-statements/data-definition/CANCEL_ALTER_TABLE.md
deleted file mode 100644
index 0c3f8f38bc5bac..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/CANCEL_ALTER_TABLE.md
+++ /dev/null
@@ -1,56 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CANCEL ALTER TABLE
-
-## Description
-
-Cancels the execution of the ongoing ALTER TABLE operation, including:
-
-- Modify columns.
-- Optimize table schema (from v3.2), including modifying the bucketing method and the number of buckets.
-- Create and delete the rollup index.
-
-> **NOTICE**
->
-> - This statement is a synchronous operation.
-> - This statement requires you to have the `ALTER_PRIV` privilege on the table.
-> - This statement only supports canceling asynchronous operations using ALTER TABLE (as mentioned above) and does not support canceling synchronous operations using ALTER TABLE, such as rename.
-
-## Syntax
-
-   ```SQL
-   CANCEL ALTER TABLE { COLUMN | OPTIMIZE | ROLLUP } FROM [db_name.]table_name
-   ```
-
-## Parameters
-
-- `{COLUMN ｜ OPTIMIZE | ROLLUP}`
-
-  - If `COLUMN` is specified, this statement cancels operations of modifying columns.
-  - If `OPTIMIZE` is specified, this statement cancels operations of optimizing table schema.
-  - If `ROLLUP` is specified, this statement cancels operations of adding or deleting the rollup index.
-
-- `db_name`: optional. The name of the database to which the table belongs. If this parameter is not specified, your current database is used by default.
-- `table_name`: required. The table name.
-
-## Examples
-
-1. Cancel the operation of modifying columns for `example_table` in the database `example_db`.
-
-   ```SQL
-   CANCEL ALTER TABLE COLUMN FROM example_db.example_table;
-   ```
-
-2. Cancel the operation of optimizing table schema for `example_table` in the database `example_db`.
-
-   ```SQL
-   CANCEL ALTER TABLE OPTIMIZE FROM example_db.example_table;
-   ```
-
-3. Cancel the operation of adding or deleting the rollup index for `example_table` in the current database.
-
-   ```SQL
-   CANCEL ALTER TABLE ROLLUP FROM example_table;
-   ```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/CREATE_ANALYZE.md b/docs/en/sql-reference/sql-statements/data-definition/CREATE_ANALYZE.md
deleted file mode 100644
index f6e580a5ffe27e..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/CREATE_ANALYZE.md
+++ /dev/null
@@ -1,88 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE ANALYZE
-
-## Description
-
-Customizes an automatic collection task for collecting CBO statistics.
-
-By default, StarRocks automatically collects full statistics of a table. It checks for any data updates every 5 minutes. If data change is detected, data collection will be automatically triggered. If you do not want to use automatic full collection, you can set the FE configuration item `enable_collect_full_statistic` to `false` and customize a collection task.
-
-Before creating a custom automatic collection task, you must disable automatic full collection (`enable_collect_full_statistic = false`). Otherwise, custom tasks cannot take effect.
-
-This statement is supported from v2.4.
-
-## Syntax
-
-```SQL
--- Automatically collect stats of all databases.
-CREATE ANALYZE [FULL|SAMPLE] ALL PROPERTIES (property [,property])
-
--- Automatically collect stats of all tables in a database.
-CREATE ANALYZE [FULL|SAMPLE] DATABASE db_name
-PROPERTIES (property [,property])
-
--- Automatically collect stats of specified columns in a table.
-CREATE ANALYZE [FULL|SAMPLE] TABLE tbl_name (col_name [,col_name])
-PROPERTIES (property [,property])
-```
-
-## Parameter description
-
-- Collection type
-  - FULL: indicates full collection.
-  - SAMPLE: indicates sampled collection.
-  - If no collection type is specified, sampled collection is used by default.
-
-- `col_name`: columns from which to collect statistics. Separate multiple columns with commas (`,`). If this parameter is not specified, the entire table is collected.
-
-- `PROPERTIES`: custom parameters. If `PROPERTIES` is not specified, the default settings in `fe.conf` are used. The properties that are actually used can be viewed via the `Properties` column in the output of SHOW ANALYZE JOB.
-
-| **PROPERTIES**                        | **Type** | **Default value** | **Description**                                              |
-| ------------------------------------- | -------- | ----------------- | ------------------------------------------------------------ |
-| statistic_auto_collect_ratio          | FLOAT    | 0.8               | The threshold for determining  whether the statistics for automatic collection are healthy. If the statistics health is below this threshold, automatic collection is triggered. |
-| statistics_max_full_collect_data_size | INT      | 100               | The size of the largest partition for automatic collection to collect data. Unit: GB.If a partition exceeds this value, full collection is discarded and sampled collection is performed instead. |
-| statistic_sample_collect_rows         | INT      | 200000            | The minimum number of rows to collect.If the parameter value exceeds the actual number of rows in your table, full collection is performed. |
-
-## Examples
-
-Example 1: Automatic full collection
-
-```SQL
--- Automatically collect full stats of all databases.
-CREATE ANALYZE ALL;
-
--- Automatically collect full stats of a database.
-CREATE ANALYZE DATABASE db_name;
-
--- Automatically collect full stats of all tables in a database.
-CREATE ANALYZE FULL DATABASE db_name;
-
--- Automatically collect full stats of specified columns in a table.
-CREATE ANALYZE TABLE tbl_name(c1, c2, c3); 
-```
-
-Example 2: Automatic sampled collection
-
-```SQL
--- Automatically collect stats of all tables in a database using default settings.
-CREATE ANALYZE SAMPLE DATABASE db_name;
-
--- Automatically collect stats of specified columns in a table, with statistics health and the number of rows to collect specified.
-CREATE ANALYZE SAMPLE TABLE tbl_name(c1, c2, c3) PROPERTIES(
-   "statistic_auto_collect_ratio" = "0.5",
-   "statistic_sample_collect_rows" = "1000000"
-);
-```
-
-## References
-
-[SHOW ANALYZE JOB](../data-definition/SHOW_ANALYZE_JOB.md): view the status of a custom collection task.
-
-[DROP ANALYZE](../data-definition/DROP_ANALYZE.md): delete a custom collection task.
-
-[KILL ANALYZE](../data-definition/KILL_ANALYZE.md): cancel a custom collection task that is running.
-
-For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/data-definition/CREATE_DATABASE.md b/docs/en/sql-reference/sql-statements/data-definition/CREATE_DATABASE.md
deleted file mode 100644
index c25f4a4d3f3454..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/CREATE_DATABASE.md
+++ /dev/null
@@ -1,53 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE DATABASE
-
-## Description
-
-This statement is used to create databases.
-
-:::tip
-
-This operation requires the CREATE DATABASE privilege on the target catalog. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```sql
-CREATE DATABASE [IF NOT EXISTS] <db_name>
-[PROPERTIES ("key"="value", ...)]
-```
-
-## Parameters
-
-`db_name`: the name of the database to create. For the naming conventions, see [System limits](../../../reference/System_limit.md).
-
-**PROPERTIES (Optional)**
-
-`storage_volume`: Specifies the name of the storage volume that is used to store the database in a shared-data cluster.
-
-## Examples
-
-1. Create the database `db_test`.
-
-   ```sql
-   CREATE DATABASE db_test;
-   ```
-
-2. Create the cloud-native database `cloud_db` with the storage volume `s3_storage_volume`.
-
-   ```sql
-   CREATE DATABASE cloud_db
-   PROPERTIES ("storage_volume"="s3_storage_volume");
-   ```
-
-## References
-
-- [SHOW CREATE DATABASE](../data-manipulation/SHOW_CREATE_DATABASE.md)
-- [USE](../data-definition/USE.md)
-- [SHOW DATABASES](../data-manipulation/SHOW_DATABASES.md)
-- [DESC](../Utility/DESCRIBE.md)
-- [DROP DATABASE](../data-definition/DROP_DATABASE.md)
diff --git a/docs/en/sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md b/docs/en/sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md
deleted file mode 100644
index 33f6cfa1f6fa61..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md
+++ /dev/null
@@ -1,140 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE EXTERNAL CATALOG
-
-## Description
-
-Creates an external catalog. You can use external catalogs to query data in external data sources without loading data into StarRocks or creating external tables. Currently, you can create the following types of external catalogs:
-
-- [Hive catalog](../../../data_source/catalog/hive_catalog.md): used for querying data from Apache Hive™.
-- [Iceberg catalog](../../../data_source/catalog/iceberg_catalog.md): used for querying data from Apache Iceberg.
-- [Hudi catalog](../../../data_source/catalog/hudi_catalog.md): used for querying data from Apache Hudi.
-- [Delta Lake catalog](../../../data_source/catalog/deltalake_catalog.md): used to query data from Delta Lake.
-- [JDBC catalog](../../../data_source/catalog/jdbc_catalog.md): used to query data from JDBC-compatible data sources.
-- [Elasticsearch catalog](../../../data_source/catalog/elasticsearch_catalog.md): used to query data from Elasticsearch. Elasticsearch catalogs are supported from v3.1 onwards.
-- [Paimon catalog](../../../data_source/catalog/paimon_catalog.md): used to query data from Apache Paimon. Paimon catalogs are supported from v3.1 onwards.
-- [Unified catalog](../../../data_source/catalog/unified_catalog.md): used to query data from from Hive, Iceberg, Hudi, and Delta Lake data sources as a unified data source. Unified catalogs are supported from v3.2 onwards.
-
-> **NOTE**
->
-> - In v3.0 and later, this statement requires SYSTEM-level CREATE EXTERNAL CATALOG privilege.
-> - Before you create external catalogs, configure your StarRocks cluster to meet the requirements of the data storage system (such as Amazon S3), metadata service (such as Hive metastore), and authenticating service (such as Kerberos) of external data sources. For more information, see the "Before you begin" section in each [external catalog topic](../../../data_source/catalog/catalog_overview.md).
-
-## Syntax
-
-```SQL
-CREATE EXTERNAL CATALOG [IF NOT EXISTS] <catalog_name>
-[COMMENT <comment>]
-PROPERTIES ("key"="value", ...)
-```
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                              |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| catalog_name  | Yes          | The name of the external catalog. For the naming conventions, see [System limits](../../../reference/System_limit.md). |
-| comment       | No           | The description of the external catalog. |
-| PROPERTIES    | Yes          | The properties of an external catalog. Configure properties based on the types of external catalogs. For more information, see [Hive catalog](../../../data_source/catalog/hive_catalog.md), [Iceberg catalog](../../../data_source/catalog/iceberg_catalog.md), [Hudi catalog](../../../data_source/catalog/hudi_catalog.md), [Delta Lake catalog](../../../data_source/catalog/deltalake_catalog.md), and [JDBC Catalog](../../../data_source/catalog/jdbc_catalog.md). |
-
-## Examples
-
-Example 1: Create a Hive catalog named `hive_metastore_catalog`. The corresponding Hive cluster uses Hive metastore as its metadata service.
-
-```SQL
-CREATE EXTERNAL CATALOG hive_metastore_catalog
-PROPERTIES(
-   "type"="hive", 
-   "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
-);
-```
-
-Example 2: Create a Hive catalog named `hive_glue_catalog`. The corresponding Hive cluster uses AWS Glue as its metadata service.
-
-```SQL
-CREATE EXTERNAL CATALOG hive_glue_catalog
-PROPERTIES(
-    "type"="hive", 
-    "hive.metastore.type"="glue",
-    "aws.hive.metastore.glue.aws-access-key"="xxxxxx",
-    "aws.hive.metastore.glue.aws-secret-key"="xxxxxxxxxxxx",
-    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
-);
-```
-
-Example 3: Create an Iceberg catalog named `iceberg_metastore_catalog`. The corresponding Iceberg cluster uses Hive metastore as its metadata service.
-
-```SQL
-CREATE EXTERNAL CATALOG iceberg_metastore_catalog
-PROPERTIES(
-    "type"="iceberg",
-    "iceberg.catalog.type"="hive",
-    "iceberg.catalog.hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
-);
-```
-
-Example 4: Create an Iceberg catalog named `iceberg_glue_catalog`. The corresponding Iceberg cluster uses AWS Glue as its metadata service.
-
-```SQL
-CREATE EXTERNAL CATALOG iceberg_glue_catalog
-PROPERTIES(
-    "type"="iceberg", 
-    "iceberg.catalog.type"="glue",
-    "aws.hive.metastore.glue.aws-access-key"="xxxxx",
-    "aws.hive.metastore.glue.aws-secret-key"="xxxxxxxxxxxx",
-    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
-);
-```
-
-Example 5: Create a Hudi catalog named `hudi_metastore_catalog`. The corresponding Hudi cluster uses Hive metastore as its metadata service.
-
-```SQL
-CREATE EXTERNAL CATALOG hudi_metastore_catalog
-PROPERTIES(
-    "type"="hudi",
-    "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
-);
-```
-
-Example 6: Create a Hudi catalog named `hudi_glue_catalog`. The corresponding Hudi cluster uses AWS Glue as its metadata service.
-
-```SQL
-CREATE EXTERNAL CATALOG hudi_glue_catalog
-PROPERTIES(
-    "type"="hudi", 
-    "hive.metastore.type"="glue",
-    "aws.hive.metastore.glue.aws-access-key"="xxxxxx",
-    "aws.hive.metastore.glue.aws-secret-key"="xxxxxxxxxxxx",
-    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
-);
-```
-
-Example 7: Create a Delta Lake catalog named `delta_metastore_catalog`. The corresponding Delta Lake service uses Hive metastore as its metadata service.
-
-```SQL
-CREATE EXTERNAL CATALOG delta_metastore_catalog
-PROPERTIES(
-    "type"="deltalake",
-    "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
-);
-```
-
-Example 8: Create a Delta Lake catalog named `delta_glue_catalog`. The corresponding Delta Lake service uses AWS Glue as its metadata service.
-
-```SQL
-CREATE EXTERNAL CATALOG delta_glue_catalog
-PROPERTIES(
-    "type"="deltalake", 
-    "hive.metastore.type"="glue",
-    "aws.hive.metastore.glue.aws-access-key"="xxxxxx",
-    "aws.hive.metastore.glue.aws-secret-key"="xxxxxxxxxxxx",
-    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
-);
-```
-
-## References
-
-- To view all catalogs in your StarRocks cluster, see [SHOW CATALOGS](../data-manipulation/SHOW_CATALOGS.md).
-- To view the creation statement of an external catalog, see [SHOW CREATE CATALOG](../data-manipulation/SHOW_CREATE_CATALOG.md).
-- To delete an external catalog from your StarRocks cluster, see [DROP CATALOG](../data-definition/DROP_CATALOG.md).
diff --git a/docs/en/sql-reference/sql-statements/data-definition/CREATE_FUNCTION.md b/docs/en/sql-reference/sql-statements/data-definition/CREATE_FUNCTION.md
deleted file mode 100644
index 3822665ccf27fd..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/CREATE_FUNCTION.md
+++ /dev/null
@@ -1,37 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE FUNCTION
-
-## Description
-
-Creates a user-defined function (UDF). Currently, you can only create Java UDFs, including Scalar functions, user-defined aggregate functions (UDAFs), user-defined window functions (UDWFs), and user-defined table functions (UDTFs).
-
-**For details about how to compile, create, and use a Java UDF, see [Java UDF](../../sql-functions/JAVA_UDF.md).**
-
-> **NOTE**
->
-> To create a global UDF, you must have the SYSTEM-level CREATE GLOBAL FUNCTION privilege. To create a database-wide UDF, you must have the DATABASE-level CREATE FUNCTION privilege.
-
-## Syntax
-
-```sql
-CREATE [OR REPLACE] [GLOBAL] [AGGREGATE | TABLE] FUNCTION function_name
-(arg_type [, ...])
-RETURNS return_type
-PROPERTIES ("key" = "value" [, ...])
-```
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                     |
-| ------------- | -------- | ------------------------------------------------------------ |
-| OR REPLACE    | No       | If a function exists sharing the same function signature, it will be replaced. Supported from v3.4.  |
-| GLOBAL        | No       | Whether to create a global UDF, supported from v3.0.  |
-| AGGREGATE     | No       | Whether to create a UDAF or UDWF.       |
-| TABLE         | No       | Whether to create a UDTF. If both `AGGREGATE` and `TABLE` are not specified, a Scalar function is created.               |
-| function_name | Yes      | The name of the function you want to create. You can include the name of the database in this parameter, for example,`db1.my_func`. If `function_name` includes the database name, the UDF is created in that database. Otherwise, the UDF is created in the current database. The name of the new function and its parameters cannot be the same as an existing name in the destination database. Otherwise, the function cannot be created. The creation succeeds if the function name is the same but the parameters are different. |
-| arg_type      | Yes      | Argument type of the function. The added argument can be represented by `, ...`. For the supported data types, see [Java UDF](../../sql-functions/JAVA_UDF.md#mapping-between-sql-data-types-and-java-data-types).|
-| return_type   | Yes      | The return type of the function. For the supported data types, see [Java UDF](../../sql-functions/JAVA_UDF.md#mapping-between-sql-data-types-and-java-data-types). |
-| PROPERTIES    | Yes      | Properties of the function, which vary depending on the type of the UDF to create. For details, see [Java UDF](../../sql-functions/JAVA_UDF.md#step-6-create-the-udf-in-starrocks). |
diff --git a/docs/en/sql-reference/sql-statements/data-definition/CREATE_INDEX.md b/docs/en/sql-reference/sql-statements/data-definition/CREATE_INDEX.md
deleted file mode 100644
index f4992cea3bacd8..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/CREATE_INDEX.md
+++ /dev/null
@@ -1,34 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE INDEX
-
-## Description
-
-This statement is used to create indexes. You can use this statement to create only Bitmap indexes. For usage notes and scenarios of Bitmap indexes, see [Bitmap index](../../../table_design/indexes/Bitmap_index.md).
-
-:::tip
-
-This operation requires the ALTER privilege on the target table. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-## Syntax
-
-```sql
-CREATE INDEX index_name ON table_name (column [, ...],) [USING BITMAP] [COMMENT 'balabala']
-```
-
-Note:
-
-1. For the naming conventions of indexes, see [System limits](../../../reference/System_limit.md).
-2. One column can have only one BITMAP index. If a column already has an index, you cannot create one more index on it.
-
-## Examples
-
-1. Create bitmap index for `siteid` on `table1`.
-
-    ```sql
-    CREATE INDEX index_name ON table1 (siteid) USING BITMAP COMMENT 'balabala';
-    ```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md
deleted file mode 100644
index 47ddb38e686831..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md
+++ /dev/null
@@ -1,867 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE MATERIALIZED VIEW
-
-## Description
-
-Creates a materialized view. For usage information about materialized views, see [Synchronous materialized view](../../../using_starrocks/Materialized_view-single_table.md) and [Asynchronous materialized view](../../../using_starrocks/Materialized_view.md).
-
-> **CAUTION**
->
-> Only users with the CREATE MATERIALIZED VIEW privilege in the database where the base table resides can create a materialized view.
-
-Creating a materialized view is an asynchronous operation. Running this command successfully indicates that the task of creating the materialized view is submitted successfully. You can view the building status of a synchronous materialized view in a database via [SHOW ALTER MATERIALIZED VIEW](../data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW.md) command, and view that of an asynchronous materialized view by querying the metadata views [`tasks`](../../../reference/information_schema/tasks.md) and [`task_runs`](../../../reference/information_schema/task_runs.md) in [Information Schema](../../../reference/overview-pages/information_schema.md).
-
-StarRocks supports asynchronous materialized views from v2.4. The major differences between asynchronous materialized views and synchronous materialized views in previous versions are as follows:
-
-|                       | **Single-table aggregation** | **Multi-table join** | **Query rewrite** | **Refresh strategy** | **Base table** |
-| --------------------- | ---------------------------- | -------------------- | ----------------- | -------------------- | -------------- |
-| **ASYNC MV** | Yes | Yes | Yes | <ul><li>Asynchronous refresh</li><li>Manual refresh</li></ul> | Multiple tables from:<ul><li>Default catalog</li><li>External catalogs (v2.5)</li><li>Existing materialized views (v2.5)</li><li>Existing views (v3.1)</li></ul> |
-| **SYNC MV (Rollup)**  | Limited choices of aggregate functions | No | Yes | Synchronous refresh during data loading | Single table in the default catalog |
-
-## Synchronous materialized view
-
-### Syntax
-
-```SQL
-CREATE MATERIALIZED VIEW [IF NOT EXISTS] [database.]<mv_name>
-[COMMENT ""]
-[PROPERTIES ("key"="value", ...)]
-AS 
-<query_statement>
-```
-
-Parameters in brackets [] are optional.
-
-### Parameters
-
-**mv_name** (required)
-
-The name of the materialized view. The naming requirements are as follows:
-
-- The name must consist of letters (a-z or A-Z), digits (0-9), or underscores (\_), and it can only start with a letter.
-- The length of the name cannot exceed 64 characters.
-- The name is case-sensitive.
-
-**COMMENT** (optional)
-
-Comment on the materialized view. Note that `COMMENT` must be placed after `mv_name`. Otherwise, the materialized view cannot be created.
-
-**query_statement** (required)
-
-The query statement to create the materialized view. Its result is the data in the materialized view. The syntax is as follows:
-
-```SQL
-SELECT select_expr[, select_expr ...]
-[WHERE where_expr]
-[GROUP BY column_name[, column_name ...]]
-[ORDER BY column_name[, column_name ...]]
-```
-
-- select_expr (required)
-
-  All columns in the query statement, that is, all columns in the materialized view schema. This parameter supports the following values:
-
-  - Simple columns or aggregate columns such as `SELECT a, abs(b), min(c) FROM table_a`, where `a`, `b`, and `c` are the names of columns in the base table. If you do not specify column names for the materialized view, StarRocks automatically assigns names to the columns.
-  - Expressions such as `SELECT a+1 AS x, b+2 AS y, c*c AS z FROM table_a`, where `a+1`, `b+2` and `c*c` are the expressions that reference the columns in the base tables, and `x`, `y` and `z` are the aliases assigned to the columns in the materialized view.
-
-  > **NOTE**
-  >
-  > - You must specify at least one column in `select_expr`.
-  > - When creating a synchronous materialized view with an aggregate function, you must specify the GROUP BY clause, and specify at least one GROUP BY column in `select_expr`.
-  > - Synchronous materialized views do not support clauses such as JOIN and the HAVING clause of GROUP BY.
-  > - From v3.1 onwards, each synchronous materialized view can support more than one aggregate function for each column of the base table, for example, query statements such as `select b, sum(a), min(a) from table group by b`.
-  > - From v3.1 onwards, synchronous materialized views support complex expressions for SELECT and aggregate functions, for example, query statements such as `select b, sum(a + 1) as sum_a1, min(cast (a as bigint)) as min_a from table group by b` or `select abs(b) as col1, a + 1 as col2, cast(a as bigint) as col3 from table`. The following restrictions are imposed on the complex expression used for synchronous materialized views:
-  >   - Each complex expression must have an alias and different aliases must be assigned to different complex expressions among all the synchronous materialized views of a base table. For example, query statements `select b, sum(a + 1) as sum_a from table group by b` and `select b, sum(a) as sum_a from table group by b` cannot be used to create synchronous materialized views for a same base table. You can set different aliases for a complex expression.
-  >   - You can check whether your queries are rewritten by the synchronous materialized views created with complex expressions by executing `EXPLAIN <sql_statement>`. For more information, see [Query analysis](../../../administration/Query_planning.md).
-
-- WHERE (optional)
-
-  From v3.1.8 onwards, synchronous materialized views support the WHERE clause which can filter rows used for the materialized view.
-
-- GROUP BY (optional)
-
-  The GROUP BY column of the query. If this parameter is not specified, the data will not be grouped by default.
-
-- ORDER BY (optional)
-
-  The ORDER BY column of the query.
-
-  - Columns in the ORDER BY clause must be declared in the same order as the columns in `select_expr`.
-  - If the query statement contains a GROUP BY clause, the ORDER BY columns must be identical to the GROUP BY columns.
-  - If this parameter is not specified, the system will automatically supplement the ORDER BY column according to the following rules:
-    - If the materialized view is the AGGREGATE type, all GROUP BY columns are automatically used as sort keys.
-    - If the materialized view is not the AGGREGATE type, StarRocks automatically selects sort keys based on the prefix columns.
-
-### Query a synchronous materialized view
-
-Because a synchronous materialized view is essentially an index of the base table rather than a physical table, you can only query a synchronous materialized view using the hint `[_SYNC_MV_]`:
-
-```SQL
--- Do not omit the brackets [] in the hint.
-SELECT * FROM <mv_name> [_SYNC_MV_];
-```
-
-> **CAUTION**
->
-> Currently, StarRocks automatically generates names for columns in a synchronous materialized view even if you have specified aliases for them.
-
-### Automatic query rewrite with synchronous materialized view
-
-When a query that follows the pattern of a synchronous materialized view is executed, the original query statement is automatically rewritten and the intermediate results stored in the materialized view are used.
-
-The following table shows the correspondence between the aggregate function in the original query and the aggregate function used to construct the materialized view. You can select the corresponding aggregate function to build a materialized view according to your business scenario.
-
-| **aggregate function in the original query**           | **aggregate function of the materialized view** |
-| ------------------------------------------------------ | ----------------------------------------------- |
-| sum                                                    | sum                                             |
-| min                                                    | min                                             |
-| max                                                    | max                                             |
-| count                                                  | count                                           |
-| bitmap_union, bitmap_union_count, count(distinct)      | bitmap_union                                    |
-| hll_raw_agg, hll_union_agg, ndv, approx_count_distinct | hll_union                                       |
-| percentile_approx, percentile_union                    | percentile_union                                |
-
-## Asynchronous materialized view
-
-### Syntax
-
-```SQL
-CREATE MATERIALIZED VIEW [IF NOT EXISTS] [database.]<mv_name>
-[COMMENT ""]
--- distribution_desc
-[DISTRIBUTED BY HASH(<bucket_key>[,<bucket_key2> ...]) [BUCKETS <bucket_number>]]
--- refresh_desc
-[REFRESH 
--- refresh_moment
-    [IMMEDIATE | DEFERRED]
--- refresh_scheme
-    [ASYNC | ASYNC [START (<start_time>)] EVERY (INTERVAL <refresh_interval>) | MANUAL]
-]
--- partition_expression
-[PARTITION BY 
-    {<date_column> | date_trunc(fmt, <date_column>)}
-]
--- order_by_expression
-[ORDER BY (<sort_key>)]
-[PROPERTIES ("key"="value", ...)]
-AS 
-<query_statement>
-```
-
-Parameters in brackets [] are optional.
-
-### Parameters
-
-**mv_name** (required)
-
-The name of the materialized view. The naming requirements are as follows:
-
-- The name must consist of letters (a-z or A-Z), digits (0-9), or underscores (\_), and it can only start with a letter.
-- The length of the name cannot exceed 64 characters.
-- The name is case-sensitive.
-
-> **CAUTION**
->
-> Multiple materialized views can be created on the same base table, but the names of the materialized views in the same database cannot be duplicated.
-
-**COMMENT** (optional)
-
-Comment on the materialized view. Note that `COMMENT` must be placed after `mv_name`. Otherwise, the materialized view cannot be created.
-
-**distribution_desc** (optional)
-
-The bucketing strategy of the asynchronous materialized view. StarRocks supports hash bucketing and random bucketing (from v3.1 onwards). If you do not specify this parameter, StarRocks uses the random bucketing strategy and automatically sets the number of buckets.
-
-> **NOTE**
->
-> While creating an asynchronous materialized view, you must specify either `distribution_desc` or `refresh_scheme`, or both.
-
-- **Hash bucketing**:
-
-  Syntax
-
-  ```SQL
-  DISTRIBUTED BY HASH (<bucket_key1>[,<bucket_key2> ...]) [BUCKETS <bucket_number>]
-  ```
-
-  For more information, see [Data distribution](../../../table_design/Data_distribution.md#data-distribution).
-
-  > **NOTE**
-  >
-  > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../../../table_design/Data_distribution.md#set-the-number-of-buckets).
-
-- **Random bucketing**:
-
-  If you choose the random bucketing strategy and allow StarRocks to set the number of buckets automatically, you do not need to specify `distribution_desc`. However, if you want to set the number of buckets manually, you can refer to the following syntax:
-
-  ```SQL
-  DISTRIBUTED BY RANDOM BUCKETS <bucket_number>
-  ```
-
-  > **CAUTION**
-  >
-  > Asynchronous materialized views with a random bucketing strategy cannot be assigned to a colocation group.
-
-  For more information, see [Random bucketing](../../../table_design/Data_distribution.md#random-bucketing-since-v31)
-
-**refresh_moment** (optional)
-
-The refresh moment of the materialized view. Default value: `IMMEDIATE`. Valid values:
-
-- `IMMEDIATE`: Refresh the asynchronous materialized view immediately after it is created.
-- `DEFERRED`: The asynchronous materialized view is not refreshed after it is created. You can manually refresh the materialized view or schedule regular refresh tasks.
-
-**refresh_scheme** (optional)
-
-> **NOTE**
->
-> While creating an asynchronous materialized view, you must specify either `distribution_desc` or `refresh_scheme`, or both.
-
-The refresh strategy of the asynchronous materialized view. Valid values:
-
-- `ASYNC`: Automatic refresh mode. Each time the base table data changes, the materialized view is automatically refreshed.
-- `ASYNC [START (<start_time>)] EVERY(INTERVAL <interval>)`: Regular refresh mode. The materialized view is refreshed regularly at the interval defined. You can specify the interval as `EVERY (interval n day/hour/minute/second)` using the following units: `DAY`, `HOUR`, `MINUTE`, and `SECOND`. The default value is `10 MINUTE`. You can further specify the refresh start time as `START('yyyy-MM-dd hh:mm:ss')`. If the start time is not specified, the current time is used. Example: `ASYNC START ('2023-09-12 16:30:25') EVERY (INTERVAL 5 MINUTE)`.
-- `MANUAL`: Manual refresh mode. The materialized view will not be refreshed unless you trigger a refresh task manually.
-
-If this parameter is not specified, the default value `MANUAL` is used.
-
-**partition_expression** (optional)
-
-The partitioning strategy of the asynchronous materialized view. As for the current version of StarRocks, only one partition expression is supported when creating an asynchronous materialized view.
-
-> **CAUTION**
->
-> Currently, asynchronous materialized views do not support the list partitioning strategy.
-
-Valid values:
-
-- `column_name`: The name of the column used for partitioning. The expression `PARTITION BY dt` means to partition the materialized view according to the `dt` column.
-- `date_trunc` function: The function used to truncate the time unit. `PARTITION BY date_trunc("MONTH", dt)` means that the `dt` column is truncated to month as the unit for partitioning. The `date_trunc` function supports truncating time to units including `YEAR`, `MONTH`, `DAY`, `HOUR`, and `MINUTE`.
-- `str2date` function: The function used to partition string type parititions of base table into materialized view's partition. `PARTITION BY str2date(dt, "%Y%m%d")` means that the `dt` column is a string date type whose date format is `"%Y%m%d"`. The `str2date` function supports a lot of date formats, you can refer to [str2date](../../sql-functions/date-time-functions/str2date.md) for more information. Supported from v3.1.4.
-- `time_slice` or `date_slice` functions: From v3.1 onwards, you can further use these functions to convert the given time into the beginning or end of a time interval based on the specified time granularity, for example, `PARTITION BY date_trunc("MONTH", time_slice(dt, INTERVAL 7 DAY))` where time_slice and date_slice must have a finer granularity than date_trunc. You can use them to specify a GROUP BY column with a finer granularity than that of the partitioning key, for example, `GROUP BY time_slice(dt, INTERVAL 1 MINUTE) PARTITION BY date_trunc('DAY', ts)`.
-
-If this parameter is not specified, no partitioning strategy is adopted by default.
-
-**order_by_expression** (optional)
-
-The sort key of the asynchronous materialized view. If you do not specify the sort key, StarRocks chooses some of the prefix columns from SELECT columns as the sort keys. For example, in `select a, b, c, d`, sort keys can be `a` and `b`. This parameter is supported from StarRocks v3.0 onwards.
-
-**PROPERTIES** (optional)
-
-Properties of the asynchronous materialized view. You can modify the properties of an existing materialized view using [ALTER MATERIALIZED VIEW](./ALTER_MATERIALIZED_VIEW.md).
-
-- `session.`: If you want to alter a session variable-related property of the materialized view, you must add a `session.` prefix to the property, for example, `session.query_timeout`. You do not need to specify the prefix for non-session properties, for example, `mv_rewrite_staleness_second`.
-- `replication_num`: The number of materialized view replicas to create.
-- `storage_medium`: Storage medium type. Valid values: `HDD` and `SSD`.
-- `storage_cooldown_time`: the storage cooldown time for a partition. If both HDD and SSD storage mediums are used, data in the SSD storage is moved to the HDD storage after the time specified by this property. Format: "yyyy-MM-dd HH:mm:ss". The specified time must be later than the current time. If this property is not explicitly specified, the storage cooldown is not performed by default.
-- `partition_ttl`: The time-to-live (TTL) for partitions. Partitions whose data is within the specified time range are retained. Expired partitions are deleted automatically. Unit: `YEAR`, `MONTH`, `DAY`, `HOUR`, and `MINUTE`. For example, you can specify this property as `2 MONTH`. This property is recommended over `partition_ttl_number`. It is supported from v3.1.5 onwards.
-- `partition_ttl_number`: The number of most recent materialized view partitions to retain. For the partitions with a start time earlier than the current time, after the number of these partitions exceeds this value, less recent partitions will be deleted. StarRocks will periodically check materialized view partitions according to the time interval specified in the FE configuration item `dynamic_partition_check_interval_seconds`, and automatically delete expired partitions. If you enabled the [dynamic partitioning](../../../table_design/dynamic_partitioning.md) strategy, the partitions created in advance are not counted in. When the value is `-1`, all partitions of the materialized view will be preserved. Default: `-1`.
-- `partition_refresh_number`: In a single refresh, the maximum number of partitions to refresh. If the number of partitions to be refreshed exceeds this value, StarRocks will split the refresh task and complete it in batches. Only when the previous batch of partitions is refreshed successfully, StarRocks will continue to refresh the next batch of partitions until all partitions are refreshed. If any of the partitions fail to be refreshed, no subsequent refresh tasks will be generated. When the value is `-1`, the refresh task will not be split. The default value is changed from `-1` to `1` since v3.3, meaning StarRocks refeshes partitions one by one.
-- `excluded_trigger_tables`: If a base table of the materialized view is listed here, the automatic refresh task will not be triggered when the data in the base table is changed. This parameter only applies to load-triggered refresh strategy, and is usually used together with the property `auto_refresh_partitions_limit`. Format: `[db_name.]table_name`. When the value is an empty string, any data change in all base tables triggers the refresh of the corresponding materialized view. The default value is an empty string.
-- `auto_refresh_partitions_limit`: The number of most recent materialized view partitions that need to be refreshed when a materialized view refresh is triggered. You can use this property to limit the refresh range and reduce the refresh cost. However, because not all the partitions are refreshed, the data in the materialized view may not be consistent with the base table. Default: `-1`. When the value is `-1`, all partitions will be refreshed. When the value is a positive integer N, StarRocks sorts the existing partitions in chronological order, and refreshes the current partition and N-1 most recent partitions. If the number of partitions is less than N, StarRocks refreshes all existing partitions. If there are dynamic partitions created in advance in your materialized view, StarRocks refreshes all pre-created partitions.
-- `mv_rewrite_staleness_second`: If the materialized view's last refresh is within the time interval specified in this property, this materialized view can be used directly for query rewrite, regardless of whether the data in the base tables changes. If the last refresh is before this time interval, StarRocks checks whether the base tables have been updated to determine whether the materialized view can be used for query rewrite. Unit: Second. This property is supported from v3.0.
-- `colocate_with`: The colocation group of the asynchronous materialized view. See [Colocate Join](../../../using_starrocks/Colocate_join.md) for further information. This property is supported from v3.0.
-- `unique_constraints` and `foreign_key_constraints`: The Unique Key constraints and Foreign Key constraints when you create an asynchronous materialized view for query rewrite in the View Delta Join scenario. See [Asynchronous materialized view - Rewrite queries in View Delta Join scenario](../../../using_starrocks/query_rewrite_with_materialized_views.md) for further information. This property is supported from v3.0.
-
-  > **CAUTION**
-  >
-  > The Unique Key constraints and Foreign Key constraints are only used for query rewrite. The Foreign Key constraint checks are not guaranteed when data is loaded into the table. You must ensure the data loaded into the table meets the constraints.
-
-- `resource_group`: The resource group to which the refresh tasks of the materialized view belong. The default value of this property is `default_mv_wg`, which is a system-defined resource group specifically used for materialized view refresh. The `cpu_core_limit` of `default_mv_wg` is `1`, `mem_limit` is `0.8`. For more about resource groups, see [Resource group](../../../administration/management/resource_management/resource_group.md).
-- `query_rewrite_consistency`: The query rewrite rule for the asynchronous materialized views. This property is supported from v3.2. Valid values:
-  - `disable`: Disable automatic query rewrite of the asynchronous materialized view.
-  - `checked` (Default value): Enable automatic query rewrite only when the materialized view meets the timeliness requirement, which means:
-    - If `mv_rewrite_staleness_second` is not specified, the materialized view can be used for query rewrite only when its data is consistent with the data in all base tables.
-    - If `mv_rewrite_staleness_second` is specified, the materialized view can be used for query rewrite when its last refresh is within the staleness time interval.
-  - `loose`: Enable automatic query rewrite directly, and no consistency check is required.
-- `storage_volume`: The name of the storage volume used to store the asynchronous materialized view you want to create if you are using a shared-data cluster. This property is supported from v3.1 onwards. If this property is not specified, the default storage volume is used. Example: `"storage_volume" = "def_volume"`.
-- `force_external_table_query_rewrite`: Whether to enable query rewrite for external catalog-based materialized views. This property is supported from v3.2. Valid values:
-  - `true`(Default value since v3.3): Enable query rewrite for external catalog-based materialized views.
-  - `false`: Disable query rewrite for external catalog-based materialized views.
-
-  Because strong data consistency is not guaranteed between base tables and external catalog-based materialized views, this feature is set to `false` by default. When this feature is enabled, the materialized view is used for query rewrite in accordance with the rule specified in `query_rewrite_consistency`.
-- `enable_query_rewrite`: Whether to use the materialized view for query rewrite. When there are many materialized views, query rewrite based on materialized views can impact the optimizer's time consumption. With this property, you can control whether the materialized view can be used for query rewrite. This feature is supported from v3.3.0 onwards. Valid values:
-  - `default` (Default): The system will not perform semantic checks on the materialized view, but only the SPJG-type materialized views can be used for query rewrite. Note that if the text-based query rewrite is enabled, non-SPJG-type materialized views can also be used for query rewrite.
-  - `true`: The system will perform semantic checks when creating or modifying the materialized view. If the materialized view is not eligible for query rewrite (that is, the definition of the materialized view is not an SPJG-type query), a failure will be returned.
-  - `false`: The materialized view will not be used for query rewrite.
-- [Preview] `transparent_mv_rewrite_mode`: Specifies the transparent rewrite mode for **queries directly against the materialized view**. This feature is supported from v3.3.0 onwards. Valid values:
-  - `false` (Default, compatible with the behavior in earlier versions): Queries directly against the materialized view will not be rewritten, and are only returned with the existing data in the materialized view. Their query results may be different from those of queries based on the definition of the materialized view according to the refresh status (data consistency) of the materialized view.
-  - `true`: Queries directly against the materialized view will be rewritten and returned with the most updated data, which is consistent with the result of the materialized view definition query. Please note that when the materialized view is inactive or does not support transparent query rewrite, these queries will be executed as the materialized view definition query.
-  - `transparent_or_error`: Queries directly against the materialized view will be rewritten whenever they are eligible. If the materialized view is inactive or does not support transparent query rewrite, these queries will be returned with an error.
-  - `transparent_or_default` Queries directly against the materialized view will be rewritten whenever they are eligible. If the materialized view is inactive or does not support transparent query rewrite, these queries will be returned with the existing data in the materialized view.
-
-**query_statement** (required)
-
-The query statement to create the asynchronous materialized view. From v3.1.6 onwards, StarRocks supports creating asynchronous materialized views with Common Table Expression (CTE).
-
-> **CAUTION**
->
-> Currently, StarRocks does not support creating asynchronous materialized views with base tables created with the list partitioning strategy.
-
-### Query an asynchronous materialized view
-
-An asynchronous materialized view is a physical table. You can operate it as any regular table **except that you cannot directly load data into an asynchronous materialized view**.
-
-### Automatic query rewrite with asynchronous materialized view
-
-StarRocks v2.5 supports automatic and transparent query rewrite based on the SPJG-type asynchronous materialized views. The SPJG-type materialized views refer to materialized views whose plan only includes Scan, Filter, Project, and Aggregate types of operators. The SPJG-type materialized views query rewrite includes single table query rewrite, Join query rewrite, aggregation query rewrite, Union query rewrite and query rewrite based on nested materialized views.
-
-See [Asynchronous materialized view -  Rewrite queries with the asynchronous materialized view](../../../using_starrocks/query_rewrite_with_materialized_views.md) for further information.
-
-### Supported data types
-
-- Asynchronous materialized views created based on the StarRocks default catalog support the following data types:
-
-  - **Date**: DATE, DATETIME
-  - **String**: CHAR, VARCHAR
-  - **Numeric**: BOOLEAN, TINYINT, SMALLINT, INT, BIGINT, LARGEINT, FLOAT, DOUBLE, DECIMAL, PERCENTILE
-  - **Semi-structured**: ARRAY, JSON, MAP (from v3.1 onwards), STRUCT (from v3.1 onwards)
-  - **Other**: BITMAP, HLL
-
-> **NOTE**
->
-> BITMAP, HLL, and PERCENTILE have been supported since v2.4.5.
-
-- Asynchronous materialized views created based on the StarRocks external catalogs support the following data types:
-
-  - Hive Catalog
-
-    - **Numeric**: INT/INTEGER, BIGINT, DOUBLE, FLOAT, DECIMAL
-    - **Date**: TIMESTAMP
-    - **String**: STRING, VARCHAR, CHAR
-    - **Semi-structured**: ARRAY
-
-  - Hudi Catalog
-
-    - **Numeric**: BOOLEAN, INT, LONG, FLOAT, DOUBLE, DECIMAL
-    - **Date**: DATE, TimeMillis/TimeMicros, TimestampMillis/TimestampMicros
-    - **String**: STRING
-    - **Semi-structured**: ARRAY
-
-  - Iceberg Catalog
-
-    - **Numeric**: BOOLEAN, INT, LONG, FLOAT, DOUBLE, DECIMAL(P, S)
-    - **Date**: DATE, TIME, TIMESTAMP
-    - **String**: STRING, UUID, FIXED(L), BINARY
-    - **Semi-structured**: LIST
-
-## Usage notes
-
-- The current version of StarRocks does not support creating multiple materialized views at the same time. A new materialized view can only be created when the one before is completed.
-
-- About synchronous materialized views:
-
-  - Synchronous materialized views only support aggregate functions on a single column. Query statements in the form of `sum(a+b)` are not supported.
-  - Synchronous materialized views support only one aggregate function for each column of the base table. Query statements such as `select sum(a), min(a) from table` are not supported.
-  - When creating a synchronous materialized view with an aggregate function, you must specify the GROUP BY clause, and specify at least one GROUP BY column in SELECT.
-  - Synchronous materialized views do not support clauses such as JOIN, and the HAVING clause of GROUP BY.
-  - When using ALTER TABLE DROP COLUMN to drop a specific column in a base table, you must ensure that all synchronous materialized views of the base table do not contain the dropped column, otherwise, the drop operation will fail. Before you drop the column, you must first drop all synchronous materialized views that contain the column.
-  - Creating too many synchronous materialized views for a table will affect the data load efficiency. When data is being loaded to the base table, the data in the synchronous materialized view and the base table will be updated synchronously. If a base table contains `n` synchronous materialized views, the efficiency of loading data into the base table is about the same as the efficiency of loading data into `n` tables.
-
-- About nested asynchronous materialized views:
-
-  - The refresh strategy for each materialized view only applies to the corresponding materialized view.
-  - Currently, StarRocks does not limit the number of nesting levels. In a production environment, we recommend that the number of nesting layers not exceed THREE.
-
-- About external catalog asynchronous materialized views:
-
-  - External catalog materialized view only support async fixed-interval refresh and manual refresh.
-  - Strict consistency is not guaranteed between the materialized view and the base tables in the external catalog.
-  - Currently, building materialized views based on external resources is not supported.
-  - Currently, StarRocks cannot perceive if the base table data in the external catalog has changed, so all partitions will be refreshed by default every time the base table is refreshed. You can manually refresh only some of partitions using [REFRESH MATERIALIZED VIEW](../data-manipulation/REFRESH_MATERIALIZED_VIEW.md).
-
-## Examples
-
-### Examples of synchronous materialized views
-
-The schema of the base table is as follows:
-
-```Plain Text
-mysql> desc duplicate_table;
-+-------+--------+------+------+---------+-------+
-| Field | Type   | Null | Key  | Default | Extra |
-+-------+--------+------+------+---------+-------+
-| k1    | INT    | Yes  | true | N/A     |       |
-| k2    | INT    | Yes  | true | N/A     |       |
-| k3    | BIGINT | Yes  | true | N/A     |       |
-| k4    | BIGINT | Yes  | true | N/A     |       |
-+-------+--------+------+------+---------+-------+
-```
-
-Example 1: Create a synchronous materialized view that only contains the columns of the original table (k1, k2).
-
-```sql
-create materialized view k1_k2 as
-select k1, k2 from duplicate_table;
-```
-
-The materialized view contains only two columns k1 and k2 without any aggregation.
-
-```plain text
-+-----------------+-------+--------+------+------+---------+-------+
-| IndexName       | Field | Type   | Null | Key  | Default | Extra |
-+-----------------+-------+--------+------+------+---------+-------+
-| k1_k2           | k1    | INT    | Yes  | true | N/A     |       |
-|                 | k2    | INT    | Yes  | true | N/A     |       |
-+-----------------+-------+--------+------+------+---------+-------+
-```
-
-Example 2: Create a synchronous materialized view sorted by k2.
-
-```sql
-create materialized view k2_order as
-select k2, k1 from duplicate_table order by k2;
-```
-
-The materialized view's schema is shown below. The materialized view contains only two columns k2 and k1, where column k2 is a sort column without any aggregation.
-
-```plain text
-+-----------------+-------+--------+------+-------+---------+-------+
-| IndexName       | Field | Type   | Null | Key   | Default | Extra |
-+-----------------+-------+--------+------+-------+---------+-------+
-| k2_order        | k2    | INT    | Yes  | true  | N/A     |       |
-|                 | k1    | INT    | Yes  | false | N/A     | NONE  |
-+-----------------+-------+--------+------+-------+---------+-------+
-```
-
-Example 3: Create a synchronous materialized view grouped by k1 and k2, and a SUM aggregation on k3.
-
-```sql
-create materialized view k1_k2_sumk3 as
-select k1, k2, sum(k3) from duplicate_table group by k1, k2;
-```
-
-The materialized view's schema is shown below. The materialized view contains three columns k1, k2 and sum (k3), where k1, k2 are grouped columns, and sum (k3) is the sum of the k3 columns grouped according to k1 and k2.
-
-```plain text
-+-----------------+-------+--------+------+-------+---------+-------+
-| IndexName       | Field | Type   | Null | Key   | Default | Extra |
-+-----------------+-------+--------+------+-------+---------+-------+
-| k1_k2_sumk3     | k1    | INT    | Yes  | true  | N/A     |       |
-|                 | k2    | INT    | Yes  | true  | N/A     |       |
-|                 | k3    | BIGINT | Yes  | false | N/A     | SUM   |
-+-----------------+-------+--------+------+-------+---------+-------+
-```
-
-Because the materialized view does not declare a sort column, and it adopts an aggregation function, StarRocks supplements the grouped columns k1 and k2 by default.
-
-Example 4: Create a synchronous materialized view to remove duplicate rows.
-
-```sql
-create materialized view deduplicate as
-select k1, k2, k3, k4 from duplicate_table group by k1, k2, k3, k4;
-```
-
-The materialized view's schema is shown below. The materialized view contains k1, k2, k3, and k4 columns, and there are no duplicate rows.
-
-```plain text
-+-----------------+-------+--------+------+-------+---------+-------+
-| IndexName       | Field | Type   | Null | Key   | Default | Extra |
-+-----------------+-------+--------+------+-------+---------+-------+
-| deduplicate     | k1    | INT    | Yes  | true  | N/A     |       |
-|                 | k2    | INT    | Yes  | true  | N/A     |       |
-|                 | k3    | BIGINT | Yes  | true  | N/A     |       |
-|                 | k4    | BIGINT | Yes  | true  | N/A     |       |
-+-----------------+-------+--------+------+-------+---------+-------+
-```
-
-Example 5: Create a non-aggregated synchronous materialized view that does not declare a sort column.
-
-The schema of the base table is shown below:
-
-```plain text
-+-------+--------------+------+-------+---------+-------+
-| Field | Type         | Null | Key   | Default | Extra |
-+-------+--------------+------+-------+---------+-------+
-| k1    | TINYINT      | Yes  | true  | N/A     |       |
-| k2    | SMALLINT     | Yes  | true  | N/A     |       |
-| k3    | INT          | Yes  | true  | N/A     |       |
-| k4    | BIGINT       | Yes  | true  | N/A     |       |
-| k5    | DECIMAL(9,0) | Yes  | true  | N/A     |       |
-| k6    | DOUBLE       | Yes  | false | N/A     | NONE  |
-| k7    | VARCHAR(20)  | Yes  | false | N/A     | NONE  |
-+-------+--------------+------+-------+---------+-------+
-```
-
-The materialized view contains k3, k4, k5, k6, and k7 columns, and no sort column is declared. Create the materialized view with the following statement:
-
-```sql
-create materialized view mv_1 as
-select k3, k4, k5, k6, k7 from all_type_table;
-```
-
-StarRocks automatically uses k3, k4, and k5 as the sort columns by default. The sum of the bytes occupied by these three column types is 4 (INT) + 8 (BIGINT) + 16 (DECIMAL) = 28 < 36. So these three columns are added as sort columns.
-
-The materialized view's schema is as follows.
-
-```plain text
-+----------------+-------+--------------+------+-------+---------+-------+
-| IndexName      | Field | Type         | Null | Key   | Default | Extra |
-+----------------+-------+--------------+------+-------+---------+-------+
-| mv_1           | k3    | INT          | Yes  | true  | N/A     |       |
-|                | k4    | BIGINT       | Yes  | true  | N/A     |       |
-|                | k5    | DECIMAL(9,0) | Yes  | true  | N/A     |       |
-|                | k6    | DOUBLE       | Yes  | false | N/A     | NONE  |
-|                | k7    | VARCHAR(20)  | Yes  | false | N/A     | NONE  |
-+----------------+-------+--------------+------+-------+---------+-------+
-```
-
-It can be observed that the `key` field of the k3, k4, and k5 columns is `true`, which indicates that they are the sort keys. The key field of the k6, and k7 columns is `false`, which indicates that they are not the sort keys.
-
-Example 6: Create a synchronous materialized view that contains the WHERE clause and complex expressions.
-
-```SQL
--- Create the base table: user_event
-CREATE TABLE user_event (
-      ds date   NOT NULL,
-      id  varchar(256)    NOT NULL,
-      user_id int DEFAULT NULL,
-      user_id1    varchar(256)    DEFAULT NULL,
-      user_id2    varchar(256)    DEFAULT NULL,
-      column_01   int DEFAULT NULL,
-      column_02   int DEFAULT NULL,
-      column_03   int DEFAULT NULL,
-      column_04   int DEFAULT NULL,
-      column_05   int DEFAULT NULL,
-      column_06   DECIMAL(12,2)   DEFAULT NULL,
-      column_07   DECIMAL(12,3)   DEFAULT NULL,
-      column_08   JSON   DEFAULT NULL,
-      column_09   DATETIME    DEFAULT NULL,
-      column_10   DATETIME    DEFAULT NULL,
-      column_11   DATE    DEFAULT NULL,
-      column_12   varchar(256)    DEFAULT NULL,
-      column_13   varchar(256)    DEFAULT NULL,
-      column_14   varchar(256)    DEFAULT NULL,
-      column_15   varchar(256)    DEFAULT NULL,
-      column_16   varchar(256)    DEFAULT NULL,
-      column_17   varchar(256)    DEFAULT NULL,
-      column_18   varchar(256)    DEFAULT NULL,
-      column_19   varchar(256)    DEFAULT NULL,
-      column_20   varchar(256)    DEFAULT NULL,
-      column_21   varchar(256)    DEFAULT NULL,
-      column_22   varchar(256)    DEFAULT NULL,
-      column_23   varchar(256)    DEFAULT NULL,
-      column_24   varchar(256)    DEFAULT NULL,
-      column_25   varchar(256)    DEFAULT NULL,
-      column_26   varchar(256)    DEFAULT NULL,
-      column_27   varchar(256)    DEFAULT NULL,
-      column_28   varchar(256)    DEFAULT NULL,
-      column_29   varchar(256)    DEFAULT NULL,
-      column_30   varchar(256)    DEFAULT NULL,
-      column_31   varchar(256)    DEFAULT NULL,
-      column_32   varchar(256)    DEFAULT NULL,
-      column_33   varchar(256)    DEFAULT NULL,
-      column_34   varchar(256)    DEFAULT NULL,
-      column_35   varchar(256)    DEFAULT NULL,
-      column_36   varchar(256)    DEFAULT NULL,
-      column_37   varchar(256)    DEFAULT NULL
-  )
-  PARTITION BY date_trunc("day", ds)
-  DISTRIBUTED BY hash(id);
-
-  -- Create the materialized view with the WHERE clause and complex expresssions.
-  CREATE MATERIALIZED VIEW test_mv1
-  AS 
-  SELECT
-  ds,
-  column_19,
-  column_36,
-  sum(column_01) as column_01_sum,
-  bitmap_union(to_bitmap( user_id)) as user_id_dist_cnt,
-  bitmap_union(to_bitmap(case when column_01 > 1 and column_34 IN ('1','34')   then user_id2 else null end)) as filter_dist_cnt_1,
-  bitmap_union(to_bitmap( case when column_02 > 60 and column_35 IN ('11','13') then  user_id2 else null end)) as filter_dist_cnt_2,
-  bitmap_union(to_bitmap(case when column_03 > 70 and column_36 IN ('21','23') then  user_id2 else null end)) as filter_dist_cnt_3,
-  bitmap_union(to_bitmap(case when column_04 > 20 and column_27 IN ('31','27') then  user_id2 else null end)) as filter_dist_cnt_4,
-  bitmap_union(to_bitmap( case when column_05 > 90 and column_28 IN ('41','43') then  user_id2 else null end)) as filter_dist_cnt_5
-  FROM user_event
-  WHERE ds >= '2023-11-02'
-  GROUP BY
-  ds,
-  column_19,
-  column_36;
- ```
-
-### Examples of asynchronous materialized views
-
-The following examples are based on the base tables below:
-
-```SQL
-CREATE TABLE `lineorder` (
-  `lo_orderkey` int(11) NOT NULL COMMENT "",
-  `lo_linenumber` int(11) NOT NULL COMMENT "",
-  `lo_custkey` int(11) NOT NULL COMMENT "",
-  `lo_partkey` int(11) NOT NULL COMMENT "",
-  `lo_suppkey` int(11) NOT NULL COMMENT "",
-  `lo_orderdate` int(11) NOT NULL COMMENT "",
-  `lo_orderpriority` varchar(16) NOT NULL COMMENT "",
-  `lo_shippriority` int(11) NOT NULL COMMENT "",
-  `lo_quantity` int(11) NOT NULL COMMENT "",
-  `lo_extendedprice` int(11) NOT NULL COMMENT "",
-  `lo_ordtotalprice` int(11) NOT NULL COMMENT "",
-  `lo_discount` int(11) NOT NULL COMMENT "",
-  `lo_revenue` int(11) NOT NULL COMMENT "",
-  `lo_supplycost` int(11) NOT NULL COMMENT "",
-  `lo_tax` int(11) NOT NULL COMMENT "",
-  `lo_commitdate` int(11) NOT NULL COMMENT "",
-  `lo_shipmode` varchar(11) NOT NULL COMMENT ""
-) ENGINE=OLAP
-DUPLICATE KEY(`lo_orderkey`)
-COMMENT "OLAP"
-PARTITION BY RANGE(`lo_orderdate`)
-(PARTITION p1 VALUES [("-2147483648"), ("19930101")),
-PARTITION p2 VALUES [("19930101"), ("19940101")),
-PARTITION p3 VALUES [("19940101"), ("19950101")),
-PARTITION p4 VALUES [("19950101"), ("19960101")),
-PARTITION p5 VALUES [("19960101"), ("19970101")),
-PARTITION p6 VALUES [("19970101"), ("19980101")),
-PARTITION p7 VALUES [("19980101"), ("19990101")))
-DISTRIBUTED BY HASH(`lo_orderkey`);
-
-CREATE TABLE IF NOT EXISTS `customer` (
-  `c_custkey` int(11) NOT NULL COMMENT "",
-  `c_name` varchar(26) NOT NULL COMMENT "",
-  `c_address` varchar(41) NOT NULL COMMENT "",
-  `c_city` varchar(11) NOT NULL COMMENT "",
-  `c_nation` varchar(16) NOT NULL COMMENT "",
-  `c_region` varchar(13) NOT NULL COMMENT "",
-  `c_phone` varchar(16) NOT NULL COMMENT "",
-  `c_mktsegment` varchar(11) NOT NULL COMMENT ""
-) ENGINE=OLAP
-DUPLICATE KEY(`c_custkey`)
-COMMENT "OLAP"
-DISTRIBUTED BY HASH(`c_custkey`);
-
-CREATE TABLE IF NOT EXISTS `dates` (
-  `d_datekey` int(11) NOT NULL COMMENT "",
-  `d_date` varchar(20) NOT NULL COMMENT "",
-  `d_dayofweek` varchar(10) NOT NULL COMMENT "",
-  `d_month` varchar(11) NOT NULL COMMENT "",
-  `d_year` int(11) NOT NULL COMMENT "",
-  `d_yearmonthnum` int(11) NOT NULL COMMENT "",
-  `d_yearmonth` varchar(9) NOT NULL COMMENT "",
-  `d_daynuminweek` int(11) NOT NULL COMMENT "",
-  `d_daynuminmonth` int(11) NOT NULL COMMENT "",
-  `d_daynuminyear` int(11) NOT NULL COMMENT "",
-  `d_monthnuminyear` int(11) NOT NULL COMMENT "",
-  `d_weeknuminyear` int(11) NOT NULL COMMENT "",
-  `d_sellingseason` varchar(14) NOT NULL COMMENT "",
-  `d_lastdayinweekfl` int(11) NOT NULL COMMENT "",
-  `d_lastdayinmonthfl` int(11) NOT NULL COMMENT "",
-  `d_holidayfl` int(11) NOT NULL COMMENT "",
-  `d_weekdayfl` int(11) NOT NULL COMMENT ""
-) ENGINE=OLAP
-DUPLICATE KEY(`d_datekey`)
-COMMENT "OLAP"
-DISTRIBUTED BY HASH(`d_datekey`);
-
-CREATE TABLE IF NOT EXISTS `supplier` (
-  `s_suppkey` int(11) NOT NULL COMMENT "",
-  `s_name` varchar(26) NOT NULL COMMENT "",
-  `s_address` varchar(26) NOT NULL COMMENT "",
-  `s_city` varchar(11) NOT NULL COMMENT "",
-  `s_nation` varchar(16) NOT NULL COMMENT "",
-  `s_region` varchar(13) NOT NULL COMMENT "",
-  `s_phone` varchar(16) NOT NULL COMMENT ""
-) ENGINE=OLAP
-DUPLICATE KEY(`s_suppkey`)
-COMMENT "OLAP"
-DISTRIBUTED BY HASH(`s_suppkey`);
-
-CREATE TABLE IF NOT EXISTS `part` (
-  `p_partkey` int(11) NOT NULL COMMENT "",
-  `p_name` varchar(23) NOT NULL COMMENT "",
-  `p_mfgr` varchar(7) NOT NULL COMMENT "",
-  `p_category` varchar(8) NOT NULL COMMENT "",
-  `p_brand` varchar(10) NOT NULL COMMENT "",
-  `p_color` varchar(12) NOT NULL COMMENT "",
-  `p_type` varchar(26) NOT NULL COMMENT "",
-  `p_size` int(11) NOT NULL COMMENT "",
-  `p_container` varchar(11) NOT NULL COMMENT ""
-) ENGINE=OLAP
-DUPLICATE KEY(`p_partkey`)
-COMMENT "OLAP"
-DISTRIBUTED BY HASH(`p_partkey`);
-
-create table orders ( 
-    dt date NOT NULL, 
-    order_id bigint NOT NULL, 
-    user_id int NOT NULL, 
-    merchant_id int NOT NULL, 
-    good_id int NOT NULL, 
-    good_name string NOT NULL, 
-    price int NOT NULL, 
-    cnt int NOT NULL, 
-    revenue int NOT NULL, 
-    state tinyint NOT NULL 
-) 
-PRIMARY KEY (dt, order_id) 
-PARTITION BY RANGE(`dt`) 
-( PARTITION p20210820 VALUES [('2021-08-20'), ('2021-08-21')), 
-PARTITION p20210821 VALUES [('2021-08-21'), ('2021-08-22')) ) 
-DISTRIBUTED BY HASH(order_id)
-PROPERTIES (
-    "replication_num" = "3", 
-    "enable_persistent_index" = "true"
-);
-```
-
-Example 1: Create a non-partitioned materialized view.
-
-```SQL
-CREATE MATERIALIZED VIEW lo_mv1
-DISTRIBUTED BY HASH(`lo_orderkey`)
-REFRESH ASYNC
-AS
-select
-    lo_orderkey, 
-    lo_custkey, 
-    sum(lo_quantity) as total_quantity, 
-    sum(lo_revenue) as total_revenue, 
-    count(lo_shipmode) as shipmode_count
-from lineorder 
-group by lo_orderkey, lo_custkey 
-order by lo_orderkey;
-```
-
-Example 2: Create a partitioned materialized view.
-
-```SQL
-CREATE MATERIALIZED VIEW lo_mv2
-PARTITION BY `lo_orderdate`
-DISTRIBUTED BY HASH(`lo_orderkey`)
-REFRESH ASYNC START('2023-07-01 10:00:00') EVERY (interval 1 day)
-AS
-select
-    lo_orderkey,
-    lo_orderdate,
-    lo_custkey, 
-    sum(lo_quantity) as total_quantity, 
-    sum(lo_revenue) as total_revenue, 
-    count(lo_shipmode) as shipmode_count
-from lineorder 
-group by lo_orderkey, lo_orderdate, lo_custkey
-order by lo_orderkey;
-
--- Use the date_trunc() function to partition the materialized view by month.
-CREATE MATERIALIZED VIEW order_mv1
-PARTITION BY date_trunc('month', `dt`)
-DISTRIBUTED BY HASH(`order_id`)
-REFRESH ASYNC START('2023-07-01 10:00:00') EVERY (interval 1 day)
-AS
-select
-    dt,
-    order_id,
-    user_id,
-    sum(cnt) as total_cnt,
-    sum(revenue) as total_revenue, 
-    count(state) as state_count
-from orders
-group by dt, order_id, user_id;
-```
-
-Example 3: Create an asynchronous materialized view.
-
-```SQL
-CREATE MATERIALIZED VIEW flat_lineorder
-DISTRIBUTED BY HASH(`lo_orderkey`)
-REFRESH MANUAL
-AS
-SELECT
-    l.LO_ORDERKEY AS LO_ORDERKEY,
-    l.LO_LINENUMBER AS LO_LINENUMBER,
-    l.LO_CUSTKEY AS LO_CUSTKEY,
-    l.LO_PARTKEY AS LO_PARTKEY,
-    l.LO_SUPPKEY AS LO_SUPPKEY,
-    l.LO_ORDERDATE AS LO_ORDERDATE,
-    l.LO_ORDERPRIORITY AS LO_ORDERPRIORITY,
-    l.LO_SHIPPRIORITY AS LO_SHIPPRIORITY,
-    l.LO_QUANTITY AS LO_QUANTITY,
-    l.LO_EXTENDEDPRICE AS LO_EXTENDEDPRICE,
-    l.LO_ORDTOTALPRICE AS LO_ORDTOTALPRICE,
-    l.LO_DISCOUNT AS LO_DISCOUNT,
-    l.LO_REVENUE AS LO_REVENUE,
-    l.LO_SUPPLYCOST AS LO_SUPPLYCOST,
-    l.LO_TAX AS LO_TAX,
-    l.LO_COMMITDATE AS LO_COMMITDATE,
-    l.LO_SHIPMODE AS LO_SHIPMODE,
-    c.C_NAME AS C_NAME,
-    c.C_ADDRESS AS C_ADDRESS,
-    c.C_CITY AS C_CITY,
-    c.C_NATION AS C_NATION,
-    c.C_REGION AS C_REGION,
-    c.C_PHONE AS C_PHONE,
-    c.C_MKTSEGMENT AS C_MKTSEGMENT,
-    s.S_NAME AS S_NAME,
-    s.S_ADDRESS AS S_ADDRESS,
-    s.S_CITY AS S_CITY,
-    s.S_NATION AS S_NATION,
-    s.S_REGION AS S_REGION,
-    s.S_PHONE AS S_PHONE,
-    p.P_NAME AS P_NAME,
-    p.P_MFGR AS P_MFGR,
-    p.P_CATEGORY AS P_CATEGORY,
-    p.P_BRAND AS P_BRAND,
-    p.P_COLOR AS P_COLOR,
-    p.P_TYPE AS P_TYPE,
-    p.P_SIZE AS P_SIZE,
-    p.P_CONTAINER AS P_CONTAINER FROM lineorder AS l 
-INNER JOIN customer AS c ON c.C_CUSTKEY = l.LO_CUSTKEY
-INNER JOIN supplier AS s ON s.S_SUPPKEY = l.LO_SUPPKEY
-INNER JOIN part AS p ON p.P_PARTKEY = l.LO_PARTKEY;
-```
-
-Example 4: Create a partitioned materialized view and use `str2date` to transform the STRING type partition key of the base table into the date type as for the materialized view.
-
-``` SQL
-
--- Hive Table with string partition column.
-CREATE TABLE `part_dates` (
-  `d_date` varchar(20) DEFAULT NULL,
-  `d_dayofweek` varchar(10) DEFAULT NULL,
-  `d_month` varchar(11) DEFAULT NULL,
-  `d_year` int(11) DEFAULT NULL,
-  `d_yearmonthnum` int(11) DEFAULT NULL,
-  `d_yearmonth` varchar(9) DEFAULT NULL,
-  `d_daynuminweek` int(11) DEFAULT NULL,
-  `d_daynuminmonth` int(11) DEFAULT NULL,
-  `d_daynuminyear` int(11) DEFAULT NULL,
-  `d_monthnuminyear` int(11) DEFAULT NULL,
-  `d_weeknuminyear` int(11) DEFAULT NULL,
-  `d_sellingseason` varchar(14) DEFAULT NULL,
-  `d_lastdayinweekfl` int(11) DEFAULT NULL,
-  `d_lastdayinmonthfl` int(11) DEFAULT NULL,
-  `d_holidayfl` int(11) DEFAULT NULL,
-  `d_weekdayfl` int(11) DEFAULT NULL,
-  `d_datekey` varchar(11) DEFAULT NULL
-) partition by (d_datekey);
-
-
--- Create the materialied view  with `str2date`.
-CREATE MATERIALIZED VIEW IF NOT EXISTS `test_mv` 
-PARTITION BY str2date(`d_datekey`,'%Y%m%d')
-DISTRIBUTED BY HASH(`d_date`, `d_month`, `d_month`) 
-REFRESH MANUAL 
-AS
-SELECT
-`d_date` ,
-  `d_dayofweek`,
-  `d_month` ,
-  `d_yearmonthnum` ,
-  `d_yearmonth` ,
-  `d_daynuminweek`,
-  `d_daynuminmonth`,
-  `d_daynuminyear` ,
-  `d_monthnuminyear` ,
-  `d_weeknuminyear` ,
-  `d_sellingseason`,
-  `d_lastdayinweekfl`,
-  `d_lastdayinmonthfl`,
-  `d_holidayfl` ,
-  `d_weekdayfl`,
-   `d_datekey`
-FROM
- `hive_catalog`.`ssb_1g_orc`.`part_dates` ;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/CREATE_RESOURCE.md b/docs/en/sql-reference/sql-statements/data-definition/CREATE_RESOURCE.md
deleted file mode 100644
index 2fc1b631d5929d..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/CREATE_RESOURCE.md
+++ /dev/null
@@ -1,82 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE RESOURCE
-
-## Description
-
-Creates resources. The following types of resources can be created: Apache Spark™, Apache Hive™, Apache Iceberg, Apache Hudi, and JDBC. Spark resources are used in [Spark Load](../../../loading/SparkLoad.md) to manage loading information, such as YARN configurations, storage path of intermediate data, and Broker configurations. Hive, Iceberg, Hudi, and JDBC resources are used for managing data source access information involved in querying [External tables](../../../data_source/External_table.md).
-
-:::tip
-
-- Only users with the SYSTEM-level CREATE RESOURCE privilege can perform this operation.
-- You can create JDBC resources only in StarRocks v2.3 and later.
-
-:::
-
-## Syntax
-
-```sql
-CREATE [EXTERNAL] RESOURCE "resource_name"
-PROPERTIES ("key"="value", ...)
-```
-
-## Parameters
-
-- `resource_name`: the name of the resource to create. For the naming conventions, see [System limits](../../../reference/System_limit.md).
-
-- `PROPERTIES`: specifies the properties of the resource type. The PROPERTIES vary depending on the resource type. See Examples for details.
-
-## Examples
-
-1. Create a Spark resource named spark0 in yarn Cluster mode.
-
-    ```sql
-    CREATE EXTERNAL RESOURCE "spark0"
-    PROPERTIES
-    (
-        "type" = "spark",
-        "spark.master" = "yarn",
-        "spark.submit.deployMode" = "cluster",
-        "spark.jars" = "xxx.jar,yyy.jar",
-        "spark.files" = "/tmp/aaa,/tmp/bbb",
-        "spark.executor.memory" = "1g",
-        "spark.yarn.queue" = "queue0",
-        "spark.hadoop.yarn.resourcemanager.address" = "127.0.0.1:9999",
-        "spark.hadoop.fs.defaultFS" = "hdfs://127.0.0.1:10000",
-        "working_dir" = "hdfs://127.0.0.1:10000/tmp/starrocks",
-        "broker" = "broker0",
-        "broker.username" = "user0",
-        "broker.password" = "password0"
-    );
-    ```
-
-    Parameters related to Spark are as follows:
-
-    ```plain text
-    1. spark.master: required. Currently, yarn and spark ://host:port. are supported. 
-    2. spark.submit.deployMode: deployment mode of the Spark program is required. Support cluster and client.
-    3. spark.hadoop.yarn.resourcemanager.address: required when master is yarn.
-    4. spark.hadoop.fs.defaultFS: required when master is yarn.
-    5. Other parameters are optional. Please refer to http://spark.apache.org/docs/latest/configuration.html
-    ```
-
-    If Spark is used for ETL, working_DIR and broker need to be specified. The instructions are as follows:
-
-    ```plain text
-    working_dir: Directory used by ETL. It is required when spark is used as ETL resource. For example: hdfs://host:port/tmp/starrocks.
-    broker: Name of broker. It is required when spark is used as ETL resource and needs to be configured beforehand by using `ALTER SYSTEM ADD BROKER` command. 
-    broker.property_key: It is the property information needed to be specified when broker reads the intermediate files created by ETL. 
-    ```
-
-2. Create a Hive resource named hive0.
-
-    ```sql
-    CREATE EXTERNAL RESOURCE "hive0"
-    PROPERTIES
-    (
-        "type" = "hive",
-        "hive.metastore.uris" = "thrift://10.10.44.98:9083"
-    );
-    ```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/CREATE_TABLE.md b/docs/en/sql-reference/sql-statements/data-definition/CREATE_TABLE.md
deleted file mode 100644
index 2544904921433e..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/CREATE_TABLE.md
+++ /dev/null
@@ -1,1048 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE TABLE
-
-Create a new table in StarRocks.
-
-:::tip
-This operation requires the CREATE TABLE privilege on the destination database.
-:::
-
-## Syntax
-
-```SQL
-CREATE [EXTERNAL] [TEMPORARY] TABLE [IF NOT EXISTS] [database.]table_name
-(column_definition1[, column_definition2, ...]
-[, index_definition1[, index_definition12,]])
-[ENGINE = [olap|mysql|elasticsearch|hive|hudi|iceberg|jdbc]]
-[key_desc]
-[COMMENT "table comment"]
-[partition_desc]
-[distribution_desc]
-[rollup_index]
-[ORDER BY (column_definition1,...)]
-[PROPERTIES ("key"="value", ...)]
-[BROKER PROPERTIES ("key"="value", ...)]
-```
-
-## Parameters
-
-:::tip
-
-- The table name, partition name, column name, and index name you create must follow the naming conventions in [System limits](../../../reference/System_limit.md).
-- When you specify database name, table name, column name, or partition name, note that some literals are used as reserved keywords in StarRocks. Do not directly use these keywords in SQL statements. If you want to use such a keyword in an SQL statement, enclose it in a pair of backticks (`). See [Keywords](../../../sql-reference/sql-statements/keywords.md) for these reserved keywords.
-
-:::
-
-### column_definition
-
-Syntax:
-
-```SQL
-col_name col_type [agg_type] [NULL | NOT NULL] [DEFAULT "default_value"] [AUTO_INCREMENT] [AS generation_expr]
-```
-
-**col_name**: column name.
-
-Note that normally you cannot create a column whose name is initiated with `__op` or `__row` because these name formats are reserved for special purposes in StarRocks and creating such columns may result in undefined behavior. If you do need to create such column, set the FE dynamic parameter [`allow_system_reserved_names`](../../../administration/management/FE_configuration.md#allow_system_reserved_names) to `TRUE`.
-
-**col_type**: Column type. Specific column information, such as types and ranges:
-
-- TINYINT (1 byte): Ranges from -2^7 + 1 to 2^7 - 1.
-- SMALLINT (2 bytes): Ranges from -2^15 + 1 to 2^15 - 1.
-- INT (4 bytes): Ranges from -2^31 + 1 to 2^31 - 1.
-- BIGINT (8 bytes): Ranges from -2^63 + 1 to 2^63 - 1.
-- LARGEINT (16 bytes): Ranges from -2^127 + 1 to 2^127 - 1.
-- FLOAT (4 bytes): Supports scientific notation.
-- DOUBLE (8 bytes): Supports scientific notation.
-- DECIMAL[(precision, scale)] (16 bytes)
-
-  - Default value: DECIMAL(10, 0)
-  - precision: 1 ~ 38
-  - scale: 0 ~ precision
-  - Integer part: precision - scale
-
-    Scientific notation is not supported.
-
-- DATE (3 bytes): Ranges from 0000-01-01 to 9999-12-31.
-- DATETIME (8 bytes): Ranges from 0000-01-01 00:00:00 to 9999-12-31 23:59:59.
-- CHAR[(length)]: Fixed length string. Range: 1 ~ 255. Default value: 1.
-- VARCHAR[(length)]: A variable-length string. The default value is 1. Unit: bytes. In versions earlier than StarRocks 2.1, the value range of `length` is 1–65533. [Preview] In StarRocks 2.1 and later versions, the value range of `length` is 1–1048576.
-- HLL (1~16385 bytes): For HLL type, there's no need to specify length or default value. The length will be controlled within the system according to data aggregation. HLL column can only be queried or used by [hll_union_agg](../../sql-functions/aggregate-functions/hll_union_agg.md), [Hll_cardinality](../../sql-functions/scalar-functions/hll_cardinality.md), and [hll_hash](../../sql-functions/scalar-functions/hll_hash.md).
-- BITMAP: Bitmap type does not require specified length or default value. It represents a set of unsigned bigint numbers. The largest element could be up to 2^64 - 1.
-
-**agg_type**: aggregation type. If not specified, this column is key column.
-If specified, it is value column. The aggregation types supported are as follows:
-
-- SUM, MAX, MIN, REPLACE
-- HLL_UNION (only for HLL type)
-- BITMAP_UNION(only for BITMAP)
-- REPLACE_IF_NOT_NULL: This means the imported data will only be replaced when it is of non-null value. If it is of null value, StarRocks will retain the original value.
-
-> NOTE
->
-> - When the column of aggregation type BITMAP_UNION is imported, its original data types must be TINYINT, SMALLINT, INT, and BIGINT.
-> - If NOT NULL is specified by REPLACE_IF_NOT_NULL column when the table was created, StarRocks will still convert the data to NULL without sending an error report to the user. With this, the user can import selected columns.
-
-This aggregation type applies ONLY to the Aggregate table whose key_desc type is AGGREGATE KEY. Since v3.1.9, `REPLACE_IF_NOT_NULL` newly supports the columns of the BITMAP type.
-
-**NULL | NOT NULL**: Whether the column is allowed to be `NULL`. By default, `NULL` is specified for all columns in a table that uses the Duplicate Key, Aggregate, or Unique Key table. In a table that uses the Primary Key table, by default, value columns are specified with `NULL`, whereas key columns are specified with `NOT NULL`. If `NULL` values are included in the raw data, present them with `\N`. StarRocks treats `\N` as `NULL` during data loading.
-
-**DEFAULT "default_value"**: the default value of a column. When you load data into StarRocks, if the source field mapped onto the column is empty, StarRocks automatically fills the default value in the column. You can specify a default value in one of the following ways:
-
-- **DEFAULT current_timestamp**: Use the current time as the default value. For more information, see [current_timestamp()](../../sql-functions/date-time-functions/current_timestamp.md).
-- **DEFAULT `<default_value>`**: Use a given value of the column data type as the default value. For example, if the data type of the column is VARCHAR, you can specify a VARCHAR string, such as beijing, as the default value, as presented in `DEFAULT "beijing"`. Note that default values cannot be any of the following types: ARRAY, BITMAP, JSON, HLL, and BOOLEAN.
-- **DEFAULT (\<expr\>)**: Use the result returned by a given function as the default value. Only the [uuid()](../../sql-functions/utility-functions/uuid.md) and [uuid_numeric()](../../sql-functions/utility-functions/uuid_numeric.md) expressions are supported.
-
-**AUTO_INCREMENT**: specifies an `AUTO_INCREMENT` column. The data types of `AUTO_INCREMENT` columns must be BIGINT. Auto-incremented IDs start from 1 and increase at a step of 1. For more information about `AUTO_INCREMENT` columns, see [AUTO_INCREMENT](../../sql-statements/auto_increment.md). Since v3.0, StarRocks supports `AUTO_INCREMENT` columns.
-
-**AS generation_expr**: specifies the generated column and its expression. [The generated column](../generated_columns.md) can be used to precompute and store the results of expressions, which significantly accelerates queries with the same complex expressions. Since v3.1, StarRocks supports generated columns.
-
-### index_definition
-
-```SQL
-INDEX index_name (col_name[, col_name, ...]) [USING BITMAP] COMMENT 'xxxxxx'
-```
-
-For more information about parameter descriptions and usage notes, see [Bitmap indexing](../../../table_design/indexes/Bitmap_index.md#create-an-index).
-
-### ENGINE type
-
-Default value: `olap`. If this parameter is not specified, an OLAP table (StarRocks native table) is created by default.
-
-Optional value: `mysql`, `elasticsearch`, `hive`, `jdbc` (2.3 and later), `iceberg`, and `hudi` (2.2 and later). If you want to create an external table to query external data sources, specify `CREATE EXTERNAL TABLE` and set `ENGINE` to any of these values. You can refer to [External table](../../../data_source/External_table.md) for more information.
-
-**From v3.0 onwards, we recommend that you use catalogs to query data from Hive, Iceberg, Hudi, and JDBC data sources. External tables are deprecated. For more information, see [Hive catalog](../../../data_source/catalog/hive_catalog.md), [Iceberg catalog](../../../data_source/catalog/iceberg_catalog.md), [Hudi catalog](../../../data_source/catalog/hudi_catalog.md), and [JDBC catalog](../../../data_source/catalog/jdbc_catalog.md).**
-
-**From v3.1 onwards, StarRocks supports creating Parquet-formatted tables in Iceberg catalogs, and you can insert data to these Parquet-formatted Iceberg tables by using [INSERT INTO](../data-manipulation/INSERT.md). See [Create an Iceberg table](../../../data_source/catalog/iceberg_catalog.md#create-an-iceberg-table).**
-
-**From v3.2 onwards, StarRocks supports creating Parquet-formatted tables in Hive catalogs, and supports sinking data to these Parquet-formatted Hive tables by using [INSERT INTO](../data-manipulation/INSERT.md). From v3.3 onwards, StarRocks supports creating ORC- and Textfile-formatted tables in Hive catalogs, and supports sinking data to these ORC- and Textfile-formatted Hive tables by using [INSERT INTO](../data-manipulation/INSERT.md). For more information, see [Create a Hive table](../../../data_source/catalog/hive_catalog.md#create-a-hive-table) and [Sink data to a Hive table](../../../data_source/catalog/hive_catalog.md#sink-data-to-a-hive-table).**
-
-- For MySQL, specify the following properties:
-
-    ```plaintext
-    PROPERTIES (
-        "host" = "mysql_server_host",
-        "port" = "mysql_server_port",
-        "user" = "your_user_name",
-        "password" = "your_password",
-        "database" = "database_name",
-        "table" = "table_name"
-    )
-    ```
-
-    Note:
-
-    "table_name" in MySQL should indicate the real table name. In contrast, "table_name" in CREATE TABLE statement indicates the name of this mysql table on StarRocks. They can either be different or the same.
-
-    The aim of creating MySQL tables in StarRocks is to access MySQL database. StarRocks itself does not maintain or store any MySQL data.
-
-- For Elasticsearch, specify the following properties:
-
-    ```plaintext
-    PROPERTIES (
-
-    "hosts" = "http://192.168.0.1:8200,http://192.168.0.2:8200",
-    "user" = "root",
-    "password" = "root",
-    "index" = "tindex",
-    "type" = "doc"
-    )
-    ```
-
-  - `hosts`: the URL that is used to connect your Elasticsearch cluster. You can specify one or more URLs.
-  - `user`: the account of the root user that is used to log in to your Elasticsearch cluster for which basic authentication is enabled.
-  - `password`: the password of the preceding root account.
-  - `index`: the index of the StarRocks table in your Elasticsearch cluster. The index name is the same as the StarRocks table name. You can set this parameter to the alias of the StarRocks table.
-  - `type`: the type of index. The default value is `doc`.
-
-- For Hive, specify the following properties:
-
-    ```plaintext
-    PROPERTIES (
-
-        "database" = "hive_db_name",
-        "table" = "hive_table_name",
-        "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083"
-    )
-    ```
-
-    Here, database is the name of the corresponding database in Hive table. Table is the name of Hive table. `hive.metastore.uris` is the server address.
-
-- For JDBC, specify the following properties:
-
-    ```plaintext
-    PROPERTIES (
-    "resource"="jdbc0",
-    "table"="dest_tbl"
-    )
-    ```
-
-    `resource` is the JDBC resource name and `table` is the destination table.
-
-- For Iceberg, specify the following properties:
-
-   ```plaintext
-    PROPERTIES (
-    "resource" = "iceberg0", 
-    "database" = "iceberg", 
-    "table" = "iceberg_table"
-    )
-    ```
-
-    `resource` is the Iceberg resource name. `database` is the Iceberg database. `table` is the Iceberg table.
-
-- For Hudi, specify the following properties:
-
-  ```plaintext
-    PROPERTIES (
-    "resource" = "hudi0", 
-    "database" = "hudi", 
-    "table" = "hudi_table" 
-    )
-    ```
-
-### key_desc
-
-Syntax:
-
-```SQL
-key_type(k1[,k2 ...])
-```
-
-Data is sequenced in specified key columns and has different attributes for different key types:
-
-- AGGREGATE KEY: Identical content in key columns will be aggregated into value columns according to the specified aggregation type. It usually applies to business scenarios such as financial statements and multi-dimensional analysis.
-- UNIQUE KEY/PRIMARY KEY: Identical content in key columns will be replaced in value columns according to the import sequence. It can be applied to make addition, deletion, modification and query on key columns.
-- DUPLICATE KEY: Identical content in key columns, which also exists in StarRocks at the same time. It can be used to store detailed data or data with no aggregation attributes. **DUPLICATE KEY is the default type. Data will be sequenced according to key columns.**
-
-> **NOTE**
->
-> Value columns do not need to specify aggregation types when other key_type is used to create tables with the exception of AGGREGATE KEY.
-
-### COMMENT
-
-You can add a table comment when you create a table, optional. Note that COMMENT must be placed after `key_desc`. Otherwise, the table cannot be created.
-
-From v3.1 onwards, you can modify the table comment suing `ALTER TABLE <table_name> COMMENT = "new table comment"`.
-
-### partition_desc
-
-Partition description can be used in the following ways:
-
-#### Create partitions dynamically
-
-[Dynamic partitioning](../../../table_design/dynamic_partitioning.md) provides a time-to-live (TTL) management for partitions. StarRocks automatically creates new partitions in advance and removes expired partitions to ensure data freshness. To enable this feature, you can configure Dynamic partitioning related properties at table creation.
-
-#### Create partitions one by one
-
-**Specify only the upper bound for a partition**
-
-Syntax:
-
-```sql
-PARTITION BY RANGE ( <partitioning_column1> [, <partitioning_column2>, ... ] )
-  PARTITION <partition1_name> VALUES LESS THAN ("<upper_bound_for_partitioning_column1>" [ , "<upper_bound_for_partitioning_column2>", ... ] )
-  [ ,
-  PARTITION <partition2_name> VALUES LESS THAN ("<upper_bound_for_partitioning_column1>" [ , "<upper_bound_for_partitioning_column2>", ... ] )
-  , ... ] 
-)
-```
-
-Note:
-
-Please use specified key columns and specified value ranges for partitioning.
-
-- For the naming conventions of partitions, see [System limits](../../../reference/System_limit.md).
-- Before v3.3.0, columns for the range partitioning only support the following types: TINYINT, SMALLINT, INT, BIGINT, LARGEINT, DATE, and DATETIME. Since v3.3.0, three specific time functions can be used as columns for the range partitioning. For detailed usage, see [Data distribution](../../../table_design/Data_distribution.md#manually-create-partitions).
-- Partitions are left closed and right open. The left boundary of the first partition is of minimum value.
-- NULL value is stored only in partitions that contain minimum values. When the partition containing the minimum value is deleted, NULL values can no longer be imported.
-- Partition columns can either be single columns or multiple columns. The partition values are the default minimum values.
-- When only one column is specified as the partitioning column, you can set `MAXVALUE` as the upper bound for the partitioning column of the most recent partition.
-
-  ```SQL
-  PARTITION BY RANGE (pay_dt) (
-    PARTITION p1 VALUES LESS THAN ("20210102"),
-    PARTITION p2 VALUES LESS THAN ("20210103"),
-    PARTITION p3 VALUES LESS THAN MAXVALUE
-  )
-  ```
-
-Please note:
-
-- Partitions are often used for managing data related to time.
-- When data backtracking is needed, you may want to consider emptying the first partition for adding partitions later when necessary.
-
-**Specify both the lower and upper bounds for a partition**
-
-Syntax:
-
-```SQL
-PARTITION BY RANGE ( <partitioning_column1> [, <partitioning_column2>, ... ] )
-(
-    PARTITION <partition_name1> VALUES [( "<lower_bound_for_partitioning_column1>" [ , "<lower_bound_for_partitioning_column2>", ... ] ), ( "<upper_bound_for_partitioning_column1?" [ , "<upper_bound_for_partitioning_column2>", ... ] ) ) 
-    [,
-    PARTITION <partition_name2> VALUES [( "<lower_bound_for_partitioning_column1>" [ , "<lower_bound_for_partitioning_column2>", ... ] ), ( "<upper_bound_for_partitioning_column1>" [ , "<upper_bound_for_partitioning_column2>", ... ] ) ) 
-    , ...]
-)
-```
-
-Note:
-
-- Fixed Range is more flexible than LESS THAN. You can customize the left and right partitions.
-- Fixed Range is the same as LESS THAN in the other aspects.
-- When only one column is specified as the partitioning column, you can set `MAXVALUE` as the upper bound for the partitioning column of the most recent partition.
-
-  ```SQL
-  PARTITION BY RANGE (pay_dt) (
-    PARTITION p202101 VALUES [("20210101"), ("20210201")),
-    PARTITION p202102 VALUES [("20210201"), ("20210301")),
-    PARTITION p202103 VALUES [("20210301"), (MAXVALUE))
-  )
-  ```
-
-#### Create multiple partitions in a batch
-
-Syntax
-
-- If the partitioning column is of a date type.
-
-    ```sql
-    PARTITION BY RANGE (<partitioning_column>) (
-        START ("<start_date>") END ("<end_date>") EVERY (INTERVAL <N> <time_unit>)
-    )
-    ```
-
-- If the partitioning column is of an integer type.
-
-    ```sql
-    PARTITION BY RANGE (<partitioning_column>) (
-        START ("<start_integer>") END ("<end_integer>") EVERY (<partitioning_granularity>)
-    )
-    ```
-
-Description
-
-You can specify the start and end values in `START()` and `END()` and the time unit or partitioning granularity in `EVERY()` to create multiple partitions in a batch.
-
-- Before v3.3.0, columns for the range partitioning only support the following types: TINYINT, SMALLINT, INT, BIGINT, LARGEINT, DATE, and DATETIME. Since v3.3.0, three specific time functions can be used as columns for the range partitioning. For detailed usage, see [Data distribution](../../../table_design/Data_distribution.md#manually-create-partitions).
-- If the partitioning column is of a date type, you need to use the `INTERVAL` keyword to specify the time interval. You can specify the time unit as hour (since v3.0), day, week, month, or year. The naming conventions of partitions are the same as those for dynamic partitions.
-
-For more information, see [Data distribution](../../../table_design/Data_distribution.md).
-
-### distribution_desc
-
-StarRocks supports hash bucketing and random bucketing. If you do not configure bucketing, StarRocks uses random bucketing and automatically sets the number of buckets by default.
-
-- Random bucketing (since v3.1)
-
-  For data in a partition, StarRocks distributes the data randomly across all buckets, which is not based on specific column values. And if you want StarRocks to automatically set the number of buckets, you do not need to specify any bucketing configurations. If you choose to manually specify the number of buckets, the syntax is as follows:
-
-  ```SQL
-  DISTRIBUTED BY RANDOM BUCKETS <num>
-  ```
-  
-  However, note that the query performance provided by random bucketing may not be ideal when you query massive amounts of data and frequently use certain columns as conditional columns. In this scenario, it is recommended to use hash bucketing. Because only a small number of buckets need to be scanned and computed, significantly improving query performance.
-
-  **Precautions**
-  - You can only use random bucketing to create Duplicate Key tables.
-  - You can not specify a [Colocation Group](../../../using_starrocks/Colocate_join.md) for a table bucketed randomly.
-  - [Spark Load](../../../loading/SparkLoad.md) cannot be used to load data into tables bucketed randomly.
-  - Since StarRocks v2.5.7, you do not need to set the number of buckets when you create a table. StarRocks automatically sets the number of buckets. If you want to set this parameter, see [Set the number of buckets](../../../table_design/Data_distribution.md#set-the-number-of-buckets).
-
-  For more information, see [Random bucketing](../../../table_design/Data_distribution.md#random-bucketing-since-v31).
-
-- Hash bucketing
-
-  Syntax:
-
-  ```SQL
-  DISTRIBUTED BY HASH (k1[,k2 ...]) [BUCKETS num]
-  ```
-
-  Data in partitions can be subdivided into buckets based on the hash values of the bucketing columns and the number of buckets. We recommend that you choose the column that meets the following two requirements as the bucketing column.
-
-  - High cardinality column such as ID
-  - Column that is often used as a filter in queries
-
-  If such a column does not exist, you can determine the bucketing column according to the complexity of queries.
-
-  - If the query is complex, we recommend that you select a high cardinality column as the bucketing column to ensure balanced data distribution among buckets and improve cluster resource utilization.
-  - If the query is relatively simple, we recommend that you select the column that is often used as the query condition as the bucketing column to improve query efficiency.
-
-  If partition data cannot be evenly distributed into each bucket by using one bucketing column, you can choose multiple bucketing columns (at most three). For more information, see [Choose bucketing columns](../../../table_design/Data_distribution.md#hash-bucketing).
-
-  **Precautions**:
-
-  - **When you create a table, you must specify its bucketing columns**.
-  - The values of bucketing columns cannot be updated.
-  - Bucketing columns cannot be modified after they are specified.
-  - Since StarRocks v2.5.7, you do not need to set the number of buckets when you create a table. StarRocks automatically sets the number of buckets. If you want to set this parameter, see [Set the number of buckets](../../../table_design/Data_distribution.md#set-the-number-of-buckets).
-
-### ORDER BY
-
-Since v3.0, Primary Key tables support defining sort keys using `ORDER BY`. Since v3.3, Duplicate Key tables, Aggregate tables, and Unique Key tables support defining sort keys using `ORDER BY`.
-
-For more descriptions of sort keys, see [Sort keys and prefix indexes](../../../table_design/indexes/Prefix_index_sort_key.md).
-
-### TEMPORARY
-
-Creates a temporary table. From v3.3.1, StarRocks supports creating temporary tables in the Default Catalog. For more information, see [Temporary Table](../../../table_design/StarRocks_table_design.md#temporary-table).
-
-:::note
-When creating a temporary table, you must set `ENGINE` to `olap`.
-:::
-
-### PROPERTIES
-
-#### Specify initial storage medium, automatic storage cooldown time, replica number
-
-If the engine type is `OLAP`, you can specify initial storage medium (`storage_medium`), automatic storage cooldown time (`storage_cooldown_time`) or time interval (`storage_cooldown_ttl`), and replica number (`replication_num`) when you create a table.
-
-The scope where the properties take effect: If the table has only one partition, the properties belong to the table. If the table is divided into multiple partitions, the properties belong to each partition. And when you need to configure different properties for specified partitions, you can execute [ALTER TABLE ... ADD PARTITION or ALTER TABLE ... MODIFY PARTITION](../data-definition/ALTER_TABLE.md) after table creation.
-
-**Set initial storage medium and automatic storage cooldown time**
-
-```sql
-PROPERTIES (
-    "storage_medium" = "[SSD|HDD]",
-    { "storage_cooldown_ttl" = "<num> { YEAR | MONTH | DAY | HOUR } "
-    | "storage_cooldown_time" = "yyyy-MM-dd HH:mm:ss" }
-)
-```
-
-- `storage_medium`: the initial storage medium, which can be set to `SSD` or `HDD`. Make sure that the type of storage medium you explicitly specified is consistent with the BE disk types for your StarRocks cluster specified in the BE static parameter `storage_root_path`.<br />
-
-    If the FE configuration item `enable_strict_storage_medium_check` is set to `true`, the system strictly checks BE disk type when you create a table. If the storage medium you specified in CREATE TABLE is inconsistent with BE disk type, an error "Failed to find enough host in all backends with storage medium is SSD|HDD." is returned and table creation fails. If `enable_strict_storage_medium_check` is set to `false`, the system ignores this error and forcibly creates the table. However, cluster disk space may be unevenly distributed after data is loaded.<br />
-
-    From v2.3.6, v2.4.2, v2.5.1, and v3.0 onwards, the system automatically infers storage medium based on BE disk type if `storage_medium` is not explicitly specified.<br />
-
-  - The system automatically sets this parameter to SSD in the following scenarios:
-
-    - The disk types reported by BEs (`storage_root_path`) contain only SSD.
-    - The disk types reported by BEs (`storage_root_path`) contain both SSD and HDD. Note that from v2.3.10, v2.4.5, v2.5.4, and v3.0 onwards, the system sets `storage_medium` to SSD when `storage_root_path` reported by BEs contain both SSD and HDD and the property `storage_cooldown_time` is specified.
-
-  - The system automatically sets this parameter to HDD in the following scenarios:
-
-    - The disk types reported by BEs (`storage_root_path`) contain only HDD.
-    - From 2.3.10, 2.4.5, 2.5.4, and 3.0 onwards,  the system sets `storage_medium` to HDD when `storage_root_path` reported by BEs contain both SSD and HDD and the property `storage_cooldown_time` is not specified.
-
-- `storage_cooldown_ttl` or `storage_cooldown_time`: the automatic storage cooldown time or time interval. Automatic storage cooldown refers to automatically migrate data from SSD to HDD. This feature is only effective when the initial storage medium is SSD.
-
-  **Parameter**
-
-  - `storage_cooldown_ttl`: the **time interval** of automatic storage cooldown for the partitions in this table. If you need to retain the most recent partitions on SSD and automatically cool down older partitions to HDD after a certain time interval, you can use this parameter. The automatic storage cooldown time for each partition is calculated using the value of this parameter plus the upper time bound of the partition.
-
-  The supported values are `<num> YEAR`, `<num> MONTH`, `<num> DAY`, and `<num> HOUR`. `<num>` is a non-negative integer. The default value is null, indicating that storage cooldown is not automatically performed.
-
-  For example, you specify the value as `"storage_cooldown_ttl"="1 DAY"` when creating the table, and the partition `p20230801` with a range of `[2023-08-01 00:00:00,2023-08-02 00:00:00)` exists. The automatic storage cooldown time for this partition is `2023-08-03 00:00:00`, which is `2023-08-02 00:00:00 + 1 DAY`. If you specify the value as `"storage_cooldown_ttl"="0 DAY"` when creating the table, the automatic storage cooldown time for this partition is `2023-08-02 00:00:00`.
-
-  - `storage_cooldown_time`: the automatic storage cooldown time (**absolute time**) when the table is cooled down from SSD to HDD. The specified time needs to be later than the current time. Format: "yyyy-MM-dd HH:mm:ss". When you need to configure different properties for specified partitions, you can execute [ALTER TABLE ... ADD PARTITION or ALTER TABLE ... MODIFY PARTITION](../data-definition/ALTER_TABLE.md).
-
-**Usages**
-
-- The comparison between the parameters related to automatic storage cooldown is as follows:
-  - `storage_cooldown_ttl`: A table property that specifies the time interval of automatic storage cooldown for partitions in the table. The system automatically cools down a partition at the time `the value of this parameter plus the upper time bound of the partition`. So automatic storage cooldown is performed at the partition granularity, which is more flexible.
-  - `storage_cooldown_time`: A table property that specifies the automatic storage cooldown time (**absolute time**) for this table. Also, you can configure different properties for specified partitions after table creation.
-  - `storage_cooldown_second`: A static FE parameter that specifies the automatic storage cooldown latency for all tables within the cluster.
-
-- The table property `storage_cooldown_ttl` or `storage_cooldown_time` takes precedence over the FE static parameter `storage_cooldown_second`.
-- When configuring these parameters, you need to specify `"storage_medium = "SSD"`.
-- If you do not configure these parameters, automatic storage cooldown is not be automatically performed.
-- Execute `SHOW PARTITIONS FROM <table_name>` to view the automatic storage cooldown time for each partition.
-
-**Limit**
-
-- Expression and List partitioning are not supported.
-- The partition column need to be of date type.
-- Multiple partition columns are not supported.
-- Primary Key tables are not supported.
-
-**Set the number of replicas for each tablet in partitions**
-
-`replication_num`: number of replicas for each table in the partitions. Default number: `3`.
-
-```sql
-PROPERTIES (
-    "replication_num" = "<num>"
-)
-```
-
-#### Add bloom filter index for a column
-
-If the Engine type is olap, you can specify a column to adopt bloom filter indexes.
-
-The following limits apply when you use bloom filter index:
-
-- You can create bloom filter indexes for all columns of a Duplicate Key or Primary Key table. For an Aggregate table or Unique Key table, you can only create bloom filter indexes for key columns.
-- TINYINT, FLOAT, DOUBLE, and DECIMAL columns do not support creating bloom filter indexes.
-- Bloom filter indexes can only improve the performance of queries that contain the `in` and `=` operators, such as `Select xxx from table where x in {}` and `Select xxx from table where column = xxx`. More discrete values in this column will result in more precise queries.
-
-For more information, see [Bloom filter indexing](../../../table_design/indexes/Bloomfilter_index.md)
-
-```SQL
-PROPERTIES (
-    "bloom_filter_columns"="k1,k2,k3"
-)
-```
-
-#### Use Colocate Join
-
-If you want to use Colocate Join attributes, specify it in `properties`.
-
-```SQL
-PROPERTIES (
-    "colocate_with"="table1"
-)
-```
-
-#### Configure dynamic partitions
-
-If you want to use dynamic partition attributes, please specify it in properties.
-
-```SQL
-PROPERTIES (
-
-    "dynamic_partition.enable" = "true|false",
-    "dynamic_partition.time_unit" = "DAY|WEEK|MONTH",
-    "dynamic_partition.start" = "${integer_value}",
-    "dynamic_partition.end" = "${integer_value}",
-    "dynamic_partition.prefix" = "${string_value}",
-    "dynamic_partition.buckets" = "${integer_value}"
-```
-
-**`PROPERTIES`**
-
-| Parameter                   | Required | Description                                                  |
-| --------------------------- | -------- | ------------------------------------------------------------ |
-| dynamic_partition.enable    | No       | Whether to enable dynamic partitioning. Valid values: `TRUE` and `FALSE`. Default value: `TRUE`. |
-| dynamic_partition.time_unit | Yes      | The time granularity for dynamically created  partitions. It is a required parameter. Valid values: `DAY`, `WEEK`, and `MONTH`. The time granularity determines the suffix format for dynamically created partitions.<br/>  - If the value is `DAY`, the suffix format for dynamically created partitions is `yyyyMMdd`. An example partition name suffix is `20200321`.<br/>  - If the value is `WEEK`, the suffix format for dynamically created partitions is `yyyy_ww`, for example `2020_13` for the 13th week of 2020.<br/>  - If the value is `MONTH`, the suffix format for dynamically created partitions is `yyyyMM`, for example `202003`. |
-| dynamic_partition.start     | No       | The starting offset of dynamic partitioning. The value of this parameter must be a negative integer. The partitions before this offset will be deleted based on the current day, week, or month which is determined by `dynamic_partition.time_unit`. The default value is `Integer.MIN_VALUE`, namely, -2147483648, which means that historical partitions will not be deleted. |
-| dynamic_partition.end       | Yes      | The end offset of dynamic partitioning. The value of this parameter must be a positive integer. The partitions from the current day, week, or month to the end offset will be created in advance. |
-| dynamic_partition.prefix    | No       | The prefix added to the names of dynamic partitions. Default value: `p`. |
-| dynamic_partition.buckets   | No       | The number of buckets per dynamic partition. The default value is the same as the number of buckets determined by the reserved word `BUCKETS` or automatically set by StarRocks. |
-
-#### Specify the bucket size (`bucket_size`) for tables configured with random bucketing
-
-Since v3.2, for tables configured with random bucketing, you can specify the bucket size by using the `bucket_size` parameter in `PROPERTIES` at table creation to enable the on-demand and dynamic increase of the number of buckets. Unit: B.
-
-```sql
-PROPERTIES (
-    "bucket_size" = "1073741824"
-)
-```
-
-#### Set data compression algorithm
-
-You can specify a data compression algorithm for a table by adding property `compression` when you create a table.
-
-The valid values of `compression` are:
-
-- `LZ4`: the LZ4 algorithm.
-- `ZSTD`: the Zstandard algorithm.
-- `ZLIB`: the zlib algorithm.
-- `SNAPPY`: the Snappy algorithm.
-
-From v3.3.2 onwards, StarRocks supports specifying the compression level for zstd compression format during table creation.
-
-Syntax:
-
-```sql
-PROPERTIES ("compression" = "zstd(<compression_level>)")
-```
-
-`compression_level`: the compression level for ZSTD compression format. Type: Integer. Range: [1,22]. Default: `3` (Recommended). The greater the number, the higher the compression ratio. The higher the compression level, the more time consumption for compression and decompression.
-
-Example:
-
-```sql
-PROPERTIES ("compression" = "zstd(3)")
-```
-
-For more information about how to choose a suitable data compression algorithm, see [Data compression](../../../table_design/data_compression.md).
-
-#### Set write quorum for data loading
-
-If your StarRocks cluster has multiple data replicas, you can set different write quorum for tables, that is, how many replicas are required to return loading success before StarRocks can determine the loading task is successful. You can specify write quorum by adding the property `write_quorum` when you create a table. This property is supported from v2.5.
-
-The valid values of `write_quorum` are:
-
-- `MAJORITY`: Default value. When the **majority** of data replicas return loading success, StarRocks returns loading task success. Otherwise, StarRocks returns loading task failed.
-- `ONE`: When **one** of the data replicas returns loading success, StarRocks returns loading task success. Otherwise, StarRocks returns loading task failed.
-- `ALL`: When **all** of the data replicas return loading success, StarRocks returns loading task success. Otherwise, StarRocks returns loading task failed.
-
-> **CAUTION**
->
-> - Setting a low write quorum for loading increases the risk of data inaccessibility and even loss. For example, you load data into a table with one write quorum in a StarRocks cluster of two replicas, and the data was successfully loaded into only one replica. Despite that StarRocks determines the loading task succeeded, there is only one surviving replica of the data. If the server which stores the tablets of loaded data goes down, the data in these tablets becomes inaccessible. And if the disk of the server is damaged, the data is lost.
-> - StarRocks returns the loading task status only after all data replicas have returned the status. StarRocks will not return the loading task status when there are replicas whose loading status is unknown. In a replica, loading timeout is also considered as loading failed.
-
-#### Specify data writing and replication mode among replicas
-
-If your StarRocks cluster has multiple data replicas, you can specify the `replicated_storage` parameter in `PROPERTIES` to configure the data writing and replication mode among replicas.
-
-- `true` (default in v3.0 and later) indicates "single leader replication", which means data is written only to the primary replica. Other replicas synchronize data from the primary replica. This mode significantly reduces CPU cost caused by data writing to multiple replicas. It is supported from v2.5.
-- `false` (default in v2.5) indicates "leaderless replication", which means data is directly written to multiple replicas, without differentiating primary and secondary replicas. The CPU cost is multiplied by the number of replicas.
-
-In most cases, using the default value gains better data writing performance. If you want to change the data writing and replication mode among replicas, run the ALTER TABLE command. Example:
-
-```sql
-    ALTER TABLE example_db.my_table
-    SET ("replicated_storage" = "false");
-```
-
-#### Create rollup in bulk
-
-You can create rollup in bulk when you create a table.
-
-Syntax:
-
-```SQL
-ROLLUP (rollup_name (column_name1, column_name2, ...)
-[FROM from_index_name]
-[PROPERTIES ("key"="value", ...)],...)
-```
-
-#### Define Unique Key constraints and Foreign Key constraints for View Delta Join query rewrite
-
-To enable query rewrite in the View Delta Join scenario, you must define the Unique Key constraints `unique_constraints` and Foreign Key constraints `foreign_key_constraints` for the table to be joined in the Delta Join. See [Asynchronous materialized view - Rewrite queries in View Delta Join scenario](../../../using_starrocks/query_rewrite_with_materialized_views.md#query-delta-join-rewrite) for further information.
-
-```SQL
-PROPERTIES (
-    "unique_constraints" = "<unique_key>[, ...]",
-    "foreign_key_constraints" = "
-    (<child_column>[, ...]) 
-    REFERENCES 
-    [catalog_name].[database_name].<parent_table_name>(<parent_column>[, ...])
-    [;...]
-    "
-)
-```
-
-- `child_column`: the Foreign Key of the table. You can define multiple `child_column`.
-- `catalog_name`: the name of the catalog where the table to join resides. The default catalog is used if this parameter is not specified.
-- `database_name`: the name of the database where the table to join resides. The current database is used if this parameter is not specified.
-- `parent_table_name`: the name of the table to join.
-- `parent_column`: the column to be joined. They must be the Primary Keys or Unique Keys of the corresponding tables.
-
-> **CAUTION**
->
-> - `unique_constraints` and `foreign_key_constraints` are only used for query rewrite. Foreign Key constraints checks are not guaranteed when data is loaded into the table. You must ensure the data loaded into the table meets the constraints.
-> - The primary keys of a Primary Key table or the unique keys of a Unique Key table are, by default, the corresponding `unique_constraints`. You do not need to set it manually.
-> - The `child_column` in a table's `foreign_key_constraints` must be referenced to a `unique_key` in another table's `unique_constraints`.
-> - The number of `child_column` and `parent_column` must agree.
-> - The data types of the `child_column` and the corresponding `parent_column` must match.
-
-#### Create cloud-native tables for StarRocks Shared-data cluster
-
-To use your StarRocks Shared-data cluster, you must create cloud-native tables with the following properties:
-
-```SQL
-PROPERTIES (
-    "storage_volume" = "<storage_volume_name>",
-    "datacache.enable" = "{ true | false }",
-    "datacache.partition_duration" = "<string_value>",
-    "enable_async_write_back" = "{ true | false }"
-)
-```
-
-- `storage_volume`: The name of the storage volume used to store the cloud-native table you want to create. If this property is not specified, the default storage volume is used. This property is supported from v3.1 onwards.
-
-- `datacache.enable`: Whether to enable the local disk cache. Default: `true`.
-
-  - When this property is set to `true`, the data to be loaded is simultaneously written into the object storage and the local disk (as the cache for query acceleration).
-  - When this property is set to `false`, the data is loaded only into the object storage.
-
-  > **NOTE**
-  >
-  > To enable the local disk cache, you must specify the directory of the disk in the BE configuration item `storage_root_path`. For more information, see [BE Configuration items](../../../administration/management/BE_configuration.md).
-
-- `datacache.partition_duration`: The validity duration of the hot data. When the local disk cache is enabled, all data is loaded into the cache. When the cache is full, StarRocks deletes the less recently used data from the cache. When a query needs to scan the deleted data, StarRocks checks if the data is within the duration of validity. If the data is within the duration, StarRocks loads the data into the cache again. If the data is not within the duration, StarRocks does not load it into the cache. This property is a string value that can be specified with the following units: `YEAR`, `MONTH`, `DAY`, and `HOUR`, for example, `7 DAY` and `12 HOUR`. If it is not specified, all data is cached as the hot data.
-
-  > **NOTE**
-  >
-  > This property is available only when `datacache.enable` is set to `true`.
-
-- `enable_async_write_back`: Whether to allow data to be written into object storage asynchronously. Default: `false`.
-
-  - When this property is set to `true`, the load task returns success as soon as the data is written into the local disk cache, and the data is written into the object storage asynchronously. This allows better loading performance, but it also risks data reliability under potential system failures.
-  - When this property is set to `false`, the load task returns success only after the data is written into both object storage and the local disk cache. This guarantees higher availability but leads to lower loading performance.
-
-#### Set fast schema evolution
-
-`fast_schema_evolution`: Whether to enable fast schema evolution for the table. Valid values are `TRUE` or `FALSE` (default). Enabling fast schema evolution can increase the speed of schema changes and reduce resource usage when columns are added or dropped. Currently, this property can only be enabled at table creation, and it cannot be modified using [ALTER TABLE](../../sql-statements/data-definition/ALTER_TABLE.md) after table creation.
-  > **NOTE**
-  >
-  > - This parameter is supported for shared-nothing clusters since v3.2.0, and shared-data clusters since v3.3.0.
-  > - If you need to configure fast schema evolution at the cluster level, such as disabling fast schema evolution within the StarRocks cluster, you can set the FE dynamic parameter [`enable_fast_schema_evolution`](../../../administration/management/FE_configuration.md#enable_fast_schema_evolution).
-
-## Examples
-
-### Create an Aggregate table that uses Hash bucketing and columnar storage
-
-```SQL
-CREATE TABLE example_db.table_hash
-(
-    k1 TINYINT,
-    k2 DECIMAL(10, 2) DEFAULT "10.5",
-    v1 CHAR(10) REPLACE,
-    v2 INT SUM
-)
-ENGINE=olap
-AGGREGATE KEY(k1, k2)
-COMMENT "my first starrocks table"
-DISTRIBUTED BY HASH(k1)
-PROPERTIES ("storage_type"="column");
-```
-
-### Create an Aggregate table and set the storage medium and cooldown time
-
-```SQL
-CREATE TABLE example_db.table_hash
-(
-    k1 BIGINT,
-    k2 LARGEINT,
-    v1 VARCHAR(2048) REPLACE,
-    v2 SMALLINT SUM DEFAULT "10"
-)
-ENGINE=olap
-UNIQUE KEY(k1, k2)
-DISTRIBUTED BY HASH (k1, k2)
-PROPERTIES(
-    "storage_type"="column",
-    "storage_medium" = "SSD",
-    "storage_cooldown_time" = "2015-06-04 00:00:00"
-);
-```
-
-Or
-
-```SQL
-CREATE TABLE example_db.table_hash
-(
-    k1 BIGINT,
-    k2 LARGEINT,
-    v1 VARCHAR(2048) REPLACE,
-    v2 SMALLINT SUM DEFAULT "10"
-)
-ENGINE=olap
-PRIMARY KEY(k1, k2)
-DISTRIBUTED BY HASH (k1, k2)
-PROPERTIES(
-    "storage_type"="column",
-    "storage_medium" = "SSD",
-    "storage_cooldown_time" = "2015-06-04 00:00:00"
-);
-```
-
-### Create a Duplicate Key table that uses Range partition, Hash bucketing, and column-based storage, and set the storage medium and cooldown time
-
-LESS THAN
-
-```SQL
-CREATE TABLE example_db.table_range
-(
-    k1 DATE,
-    k2 INT,
-    k3 SMALLINT,
-    v1 VARCHAR(2048),
-    v2 DATETIME DEFAULT "2014-02-04 15:36:00"
-)
-ENGINE=olap
-DUPLICATE KEY(k1, k2, k3)
-PARTITION BY RANGE (k1)
-(
-    PARTITION p1 VALUES LESS THAN ("2014-01-01"),
-    PARTITION p2 VALUES LESS THAN ("2014-06-01"),
-    PARTITION p3 VALUES LESS THAN ("2014-12-01")
-)
-DISTRIBUTED BY HASH(k2)
-PROPERTIES(
-    "storage_medium" = "SSD", 
-    "storage_cooldown_time" = "2015-06-04 00:00:00"
-);
-```
-
-Note:
-
-This statement will create three data partitions:
-
-```SQL
-( {    MIN     },   {"2014-01-01"} )
-[ {"2014-01-01"},   {"2014-06-01"} )
-[ {"2014-06-01"},   {"2014-12-01"} )
-```
-
-Data outside these ranges will be not be loaded.
-
-Fixed Range
-
-```SQL
-CREATE TABLE table_range
-(
-    k1 DATE,
-    k2 INT,
-    k3 SMALLINT,
-    v1 VARCHAR(2048),
-    v2 DATETIME DEFAULT "2014-02-04 15:36:00"
-)
-ENGINE=olap
-DUPLICATE KEY(k1, k2, k3)
-PARTITION BY RANGE (k1, k2, k3)
-(
-    PARTITION p1 VALUES [("2014-01-01", "10", "200"), ("2014-01-01", "20", "300")),
-    PARTITION p2 VALUES [("2014-06-01", "100", "200"), ("2014-07-01", "100", "300"))
-)
-DISTRIBUTED BY HASH(k2)
-PROPERTIES(
-    "storage_medium" = "SSD"
-);
-```
-
-### Create a MySQL external table
-
-```SQL
-CREATE EXTERNAL TABLE example_db.table_mysql
-(
-    k1 DATE,
-    k2 INT,
-    k3 SMALLINT,
-    k4 VARCHAR(2048),
-    k5 DATETIME
-)
-ENGINE=mysql
-PROPERTIES
-(
-    "host" = "127.0.0.1",
-    "port" = "8239",
-    "user" = "mysql_user",
-    "password" = "mysql_passwd",
-    "database" = "mysql_db_test",
-    "table" = "mysql_table_test"
-)
-```
-
-### Create a table that contains HLL columns
-
-```SQL
-CREATE TABLE example_db.example_table
-(
-    k1 TINYINT,
-    k2 DECIMAL(10, 2) DEFAULT "10.5",
-    v1 HLL HLL_UNION,
-    v2 HLL HLL_UNION
-)
-ENGINE=olap
-AGGREGATE KEY(k1, k2)
-DISTRIBUTED BY HASH(k1)
-PROPERTIES ("storage_type"="column");
-```
-
-### Create a table containing BITMAP_UNION aggregation type
-
-The original data type of `v1` and `v2` columns must be TINYINT, SMALLINT, or INT.
-
-```SQL
-CREATE TABLE example_db.example_table
-(
-    k1 TINYINT,
-    k2 DECIMAL(10, 2) DEFAULT "10.5",
-    v1 BITMAP BITMAP_UNION,
-    v2 BITMAP BITMAP_UNION
-)
-ENGINE=olap
-AGGREGATE KEY(k1, k2)
-DISTRIBUTED BY HASH(k1)
-PROPERTIES ("storage_type"="column");
-```
-
-### Create two tables that support Colocate Join
-
-```SQL
-CREATE TABLE `t1` 
-(
-     `id` int(11) COMMENT "",
-    `value` varchar(8) COMMENT ""
-) 
-ENGINE=OLAP
-DUPLICATE KEY(`id`)
-DISTRIBUTED BY HASH(`id`)
-PROPERTIES 
-(
-    "colocate_with" = "t1"
-);
-
-CREATE TABLE `t2` 
-(
-    `id` int(11) COMMENT "",
-    `value` varchar(8) COMMENT ""
-) 
-ENGINE=OLAP
-DUPLICATE KEY(`id`)
-DISTRIBUTED BY HASH(`id`)
-PROPERTIES 
-(
-    "colocate_with" = "t1"
-);
-```
-
-### Create a table with bitmap index
-
-```SQL
-CREATE TABLE example_db.table_hash
-(
-    k1 TINYINT,
-    k2 DECIMAL(10, 2) DEFAULT "10.5",
-    v1 CHAR(10) REPLACE,
-    v2 INT SUM,
-    INDEX k1_idx (k1) USING BITMAP COMMENT 'xxxxxx'
-)
-ENGINE=olap
-AGGREGATE KEY(k1, k2)
-COMMENT "my first starrocks table"
-DISTRIBUTED BY HASH(k1)
-PROPERTIES ("storage_type"="column");
-```
-
-### Create a dynamic partition table
-
-The dynamic partitioning function must be enabled ("dynamic_partition.enable" = "true") in FE configuration. For more information, see [Configure dynamic partitions](#configure-dynamic-partitions).
-
-This example creates partitions for the next three days and deletes partitions created three days ago. For example, if today is 2020-01-08, partitions with the following names will be created: p20200108, p20200109, p20200110, p20200111, and their ranges are:
-
-```plaintext
-[types: [DATE]; keys: [2020-01-08]; ‥types: [DATE]; keys: [2020-01-09]; )
-[types: [DATE]; keys: [2020-01-09]; ‥types: [DATE]; keys: [2020-01-10]; )
-[types: [DATE]; keys: [2020-01-10]; ‥types: [DATE]; keys: [2020-01-11]; )
-[types: [DATE]; keys: [2020-01-11]; ‥types: [DATE]; keys: [2020-01-12]; )
-```
-
-```SQL
-CREATE TABLE example_db.dynamic_partition
-(
-    k1 DATE,
-    k2 INT,
-    k3 SMALLINT,
-    v1 VARCHAR(2048),
-    v2 DATETIME DEFAULT "2014-02-04 15:36:00"
-)
-ENGINE=olap
-DUPLICATE KEY(k1, k2, k3)
-PARTITION BY RANGE (k1)
-(
-    PARTITION p1 VALUES LESS THAN ("2014-01-01"),
-    PARTITION p2 VALUES LESS THAN ("2014-06-01"),
-    PARTITION p3 VALUES LESS THAN ("2014-12-01")
-)
-DISTRIBUTED BY HASH(k2)
-PROPERTIES(
-    "storage_medium" = "SSD",
-    "dynamic_partition.enable" = "true",
-    "dynamic_partition.time_unit" = "DAY",
-    "dynamic_partition.start" = "-3",
-    "dynamic_partition.end" = "3",
-    "dynamic_partition.prefix" = "p",
-    "dynamic_partition.buckets" = "10"
-);
-```
-
-### Create a table where multiple partitions are created in a batch, and an integer type column is specified as partitioning column
-
-  In the following example, the partitioning column `datekey` is of the INT type. All the partitions are created by only one simple partition clause  `START ("1") END ("5") EVERY (1)`. The range of all the partitions starts from `1` and ends at `5`, with a partition granularity of `1`:
-  > **NOTE**
-  >
-  > The partitioning column values in **START()** and **END()** need to be wrapped in quotation marks, while the partition granularity in the **EVERY()** does not need to be wrapped in quotation marks.
-
-  ```SQL
-  CREATE TABLE site_access (
-      datekey INT,
-      site_id INT,
-      city_code SMALLINT,
-      user_name VARCHAR(32),
-      pv BIGINT DEFAULT '0'
-  )
-  ENGINE=olap
-  DUPLICATE KEY(datekey, site_id, city_code, user_name)
-  PARTITION BY RANGE (datekey) (START ("1") END ("5") EVERY (1)
-  )
-  DISTRIBUTED BY HASH(site_id)
-  PROPERTIES ("replication_num" = "3");
-  ```
-
-### Create a Hive external table
-
-Before you create a Hive external table, you must have created a Hive resource and database. For more information, see [External table](../../../data_source/External_table.md#deprecated-hive-external-table).
-
-```SQL
-CREATE EXTERNAL TABLE example_db.table_hive
-(
-    k1 TINYINT,
-    k2 VARCHAR(50),
-    v INT
-)
-ENGINE=hive
-PROPERTIES
-(
-    "resource" = "hive0",
-    "database" = "hive_db_name",
-    "table" = "hive_table_name"
-);
-```
-
-### Create a Primary Key table and specify the sort key
-
-Suppose that you need to analyze user behavior in real time from dimensions such as users' address and last active time. When you create a table, you can define the `user_id` column as the primary key and define the combination of the `address` and `last_active` columns as the sort key.
-
-```SQL
-create table users (
-    user_id bigint NOT NULL,
-    name string NOT NULL,
-    email string NULL,
-    address string NULL,
-    age tinyint NULL,
-    sex tinyint NULL,
-    last_active datetime,
-    property0 tinyint NOT NULL,
-    property1 tinyint NOT NULL,
-    property2 tinyint NOT NULL,
-    property3 tinyint NOT NULL
-) 
-PRIMARY KEY (`user_id`)
-DISTRIBUTED BY HASH(`user_id`)
-ORDER BY(`address`,`last_active`)
-PROPERTIES(
-    "replication_num" = "3",
-    "enable_persistent_index" = "true"
-);
-```
-
-### Create a partitioned temporary table
-
-```SQL
-CREATE TEMPORARY TABLE example_db.temp_table
-(
-    k1 DATE,
-    k2 INT,
-    k3 SMALLINT,
-    v1 VARCHAR(2048),
-    v2 DATETIME DEFAULT "2014-02-04 15:36:00"
-)
-ENGINE=olap
-DUPLICATE KEY(k1, k2, k3)
-PARTITION BY RANGE (k1)
-(
-    PARTITION p1 VALUES LESS THAN ("2014-01-01"),
-    PARTITION p2 VALUES LESS THAN ("2014-06-01"),
-    PARTITION p3 VALUES LESS THAN ("2014-12-01")
-)
-DISTRIBUTED BY HASH(k2);
-```
-
-## References
-
-- [SHOW CREATE TABLE](../data-manipulation/SHOW_CREATE_TABLE.md)
-- [SHOW TABLES](../data-manipulation/SHOW_TABLES.md)
-- [USE](USE.md)
-- [ALTER TABLE](ALTER_TABLE.md)
-- [DROP TABLE](DROP_TABLE.md)
diff --git a/docs/en/sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md b/docs/en/sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md
deleted file mode 100644
index f23f0c0bd16dc6..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md
+++ /dev/null
@@ -1,261 +0,0 @@
----
-displayed_sidebar: "English"
-keywords: ['CTAS']
----
-
-# CREATE TABLE AS SELECT
-
-## Description
-
-You can use the CREATE TABLE AS SELECT (CTAS) statement to synchronously or asynchronously query a table and create a new table based on the query result, and then insert the query result into the new table.
-
-You can submit an asynchronous CTAS task using [SUBMIT TASK](../data-manipulation/SUBMIT_TASK.md).
-
-## Syntax
-
-- Synchronously query a table and create a new table based on the query result, and then insert the query result into the new table.
-
-  ```SQL
-  CREATE [TEMPORARY] TABLE [IF NOT EXISTS] [database.]table_name
-  [column_name1 [, column_name2, ...]]
-  [index_definition1 [, index_definition2, ...]]
-  [key_desc]
-  [COMMENT "table comment"]
-  [partition_desc]
-  [distribution_desc]
-  [ORDER BY (column_name1 [, column_name2, ...])]
-  [PROPERTIES ("key"="value", ...)]
-  AS SELECT query
-  [ ... ]
-  ```
-
-- Asynchronously query a table and create a new table based on the query result, and then insert the query result into the new table.
-
-  ```SQL
-  SUBMIT [/*+ SET_VAR(key=value) */] TASK [[database.]<task_name>]AS
-  CREATE TABLE [IF NOT EXISTS] [database.]table_name
-  [column_name1 [, column_name2, ...]]
-  [index_definition1 [, index_definition2, ...]]
-  [key_desc]
-  [COMMENT "table comment"]
-  [partition_desc]
-  [distribution_desc]
-  [ORDER BY (column_name1 [, column_name2, ...])]
-  [PROPERTIES ("key"="value", ...)] AS SELECT query
-  [ ... ]
-  ```
-
-## Parameters
-
-| **Parameter**     | **Required** | **Description**                                              |
-| ----------------- | ------------ | ------------------------------------------------------------ |
-| TEMPORARY         | No           | Creates a temporary table. From v3.3.1, StarRocks supports creating temporary tables in the Default Catalog. For more information, see [Temporary Table](../../../table_design/StarRocks_table_design.md#temporary-table). Currently, StarRocks does not support creating temporary tables with asynchronous tasks by using SUBMIT TASK. |
-| column_name       | No          | The name of a column in the new table. You do not need to specify the data type for the column. StarRocks automatically specifies an appropriate data type for the column. StarRocks converts FLOAT and DOUBLE data into DECIMAL(38,9) data. StarRocks also converts CHAR, VARCHAR, and STRING data into VARCHAR(65533) data. |
-| index_definition| No          | Since v3.1.8, a bitmap index can be created for the new table. The syntax is `INDEX index_name (col_name[, col_name, ...]) [USING BITMAP] COMMENT 'xxxxxx'`. For more information about parameter descriptions and usage notes, see [Bitmap indexes](../../../table_design/indexes/Bitmap_index.md). |
-| key_desc          | No           | The syntax is `key_type ( <col_name1> [, <col_name2> , ...])`.<br />**Parameters**:<ul><li>`key_type`: [the key type of the new table](../../../table_design/table_types/table_types.md). Valid values: `DUPLICATE KEY` and `PRIMARY KEY`. Default value: `DUPLICATE KEY`.</li><li> `col_name`: the column to form the key.</li></ul> |
-| COMMENT           | No           | The comment of the new table.                                |
-| partition_desc    | No           | The partitioning method of the new table. By default, if you do not specify this parameter, the new table has no partition. For more information about partitioning, see [CREATE TABLE](./CREATE_TABLE.md#partition_desc). |
-| distribution_desc | No           | The bucketing method of the new table. If you do not specify this parameter, the bucket column defaults to the column with the highest cardinality collected by the cost-based optimizer (CBO). The number of buckets defaults to 10. If the CBO does not collect information about the cardinality, the bucket column defaults to the first column in the new table. For more information about bucketing, see [CREATE TABLE](./CREATE_TABLE.md#distribution_desc). |
-| ORDER BY | No | Since v3.1.8, a sort key can be specified for the new table if the new table is a Primary Key table. The sort key can be a combination of any columns. A Primary Key table is a table for which `PRIMARY KEY (xxx)` is specified at table creation.|
-| Properties        | No           | The properties of the new table.                             |
-| AS SELECT query   | Yes          | The query result.  You can specify columns in `... AS SELECT query`, for example, `... AS SELECT a, b, c FROM table_a;`. In this example, `a`, `b`, and `c` indicates the column names of the table that is queried. If you do not specify the column names of the new table, the column names of the new table are also `a`, `b`, and `c`. You can specify expressions in `... AS SELECT query`, for example, `... AS SELECT a+1 AS x, b+2 AS y, c*c AS z FROM table_a;`. In this example, `a+1`, `b+2`, and `c*c` indicates the column names of the table that is queried, and `x`, `y`, and `z` indicates the column names of the new table. Note:  The number of columns in the new table need to be the same as the number of the columns specified in the SELECT statement . We recommend that you use column names that are easy to identify. |
-
-## Usage notes
-
-- The CTAS statement can only create a new table that meets the following requirements:
-  - `ENGINE` is `OLAP`.
-
-  - The table is a Duplicate Key table by default. You can also specify it as a Primary Key table in `key_desc`.
-
-  - The sort keys are the first three columns, and the storage space of the data types of these three columns does not exceed 36 bytes.
-
-- The CTAS statement does not support setting indexes for a newly created table.
-
-- If the CTAS statement fails to execute due to reasons, such as an FE restart, one of the following issues may occur:
-  - A new table is created successfully but does not contain data.
-
-  - A new table fails to be created.
-
-- After a new table is created, if multiple methods (such as INSERT INTO) are used to insert data into the new table, the method that completes the INSERT operation first will insert its data into the new table.
-
-- After a new table is created, you need to manually grant permissions on this table to users.
-
-- If you do not specify a name for a Task when you asynchronously query a table and create a new table based on the query result, StarRocks automatically generates a name for the Task.
-
-## Examples
-
-Example 1: Synchronously query a table `order` and create a new table `order_new` based on the query result, and then insert the query result into the new table.
-
-```SQL
-CREATE TABLE order_new
-AS SELECT * FROM order;
-```
-
-Example 2: Synchronously query the `k1`, `k2`, and `k3` columns in the table `order` and create a new table `order_new` based on the query result, and then insert the query result into the new table. Additionally, set the column names of the new table to `a`, `b`, and `c`.
-
-```SQL
-CREATE TABLE order_new (a, b, c)
-AS SELECT k1, k2, k3 FROM order;
-```
-
-or
-
-```SQL
-CREATE TABLE order_new
-AS SELECT k1 AS a, k2 AS b, k3 AS c FROM order;
-```
-
-Example 3: Synchronously query the largest value of the `salary` column in the table `employee` and create a new table `employee_new` based on the query result, and then insert the query result into the new table. Additionally, set the column name of the new table to `salary_max`.
-
-```SQL
-CREATE TABLE employee_new
-AS SELECT MAX(salary) AS salary_max FROM employee;
-```
-
-After data is inserted, query the new table.
-
-```SQL
-SELECT * FROM employee_new;
-
-+------------+
-| salary_max |
-+------------+
-|   10000    |
-+------------+
-```
-
-Example 4: Synchronously query the `customer_id` and `first_name` columns in the table `customers` and create a new table `customers_new` based on the query result, and then insert the query result into the new table. Additionally, set the column names of the new table to `customer_id_new` and `first_name_new`. Also, build a bitmap index for the column `customer_id_new` in the new table.
-
-```SQL
-CREATE TABLE customers_new 
-(   customer_id_new,
-    first_name_new,
-    INDEX idx_bitmap_customer_id (customer_id_new) USING BITMAP
-) 
-AS SELECT customer_id,first_name FROM customers;
-```
-
-Example 5: Synchronously query a table `customers` and create a new table `customers_new` based on the query result, and then insert the query result into the new table. Additionally, specify the new table as a Primary Key table, and specify its sort key as `first_name` and `last_name`.
-
-```SQL
-CREATE TABLE customers_pk
-PRIMARY KEY (customer_id)
-ORDER BY (first_name,last_name)
-AS SELECT  * FROM customers;
-```
-
-Example 6: Use CTAS to create a Primary Key table. Note that the number of data rows in the Primary Key table may be less than that in the query result. It is because the [Primary Key](../../../table_design/table_types/primary_key_table.md) table only stores the most recent data row among a group of rows that have the same primary key.
-
-```SQL
-CREATE TABLE employee_new
-PRIMARY KEY(order_id)
-AS SELECT
-    order_list.order_id,
-    sum(goods.price) as total
-FROM order_list INNER JOIN goods ON goods.item_id1 = order_list.item_id2
-GROUP BY order_id;
-```
-
-Example 7: Synchronously query four tables, including `lineorder`, `customer`, `supplier`, and `part` and create a new table `lineorder_flat` based on the query result, and then insert the query result to the new table. Additionally, specify the partitioning method and bucketing method for the new table.
-
-```SQL
-CREATE TABLE lineorder_flat
-PARTITION BY RANGE(`LO_ORDERDATE`)
-(
-    START ("1993-01-01") END ("1999-01-01") EVERY (INTERVAL 1 YEAR)
-)
-DISTRIBUTED BY HASH(`LO_ORDERKEY`) AS SELECT
-    l.LO_ORDERKEY AS LO_ORDERKEY,
-    l.LO_LINENUMBER AS LO_LINENUMBER,
-    l.LO_CUSTKEY AS LO_CUSTKEY,
-    l.LO_PARTKEY AS LO_PARTKEY,
-    l.LO_SUPPKEY AS LO_SUPPKEY,
-    l.LO_ORDERDATE AS LO_ORDERDATE,
-    l.LO_ORDERPRIORITY AS LO_ORDERPRIORITY,
-    l.LO_SHIPPRIORITY AS LO_SHIPPRIORITY,
-    l.LO_QUANTITY AS LO_QUANTITY,
-    l.LO_EXTENDEDPRICE AS LO_EXTENDEDPRICE,
-    l.LO_ORDTOTALPRICE AS LO_ORDTOTALPRICE,
-    l.LO_DISCOUNT AS LO_DISCOUNT,
-    l.LO_REVENUE AS LO_REVENUE,
-    l.LO_SUPPLYCOST AS LO_SUPPLYCOST,
-    l.LO_TAX AS LO_TAX,
-    l.LO_COMMITDATE AS LO_COMMITDATE,
-    l.LO_SHIPMODE AS LO_SHIPMODE,
-    c.C_NAME AS C_NAME,
-    c.C_ADDRESS AS C_ADDRESS,
-    c.C_CITY AS C_CITY,
-    c.C_NATION AS C_NATION,
-    c.C_REGION AS C_REGION,
-    c.C_PHONE AS C_PHONE,
-    c.C_MKTSEGMENT AS C_MKTSEGMENT,
-    s.S_NAME AS S_NAME,
-    s.S_ADDRESS AS S_ADDRESS,
-    s.S_CITY AS S_CITY,
-    s.S_NATION AS S_NATION,
-    s.S_REGION AS S_REGION,
-    s.S_PHONE AS S_PHONE,
-    p.P_NAME AS P_NAME,
-    p.P_MFGR AS P_MFGR,
-    p.P_CATEGORY AS P_CATEGORY,
-    p.P_BRAND AS P_BRAND,
-    p.P_COLOR AS P_COLOR,
-    p.P_TYPE AS P_TYPE,
-    p.P_SIZE AS P_SIZE,
-    p.P_CONTAINER AS P_CONTAINER FROM lineorder AS l
-INNER JOIN customer AS c ON c.C_CUSTKEY = l.LO_CUSTKEY
-INNER JOIN supplier AS s ON s.S_SUPPKEY = l.LO_SUPPKEY
-INNER JOIN part AS p ON p.P_PARTKEY = l.LO_PARTKEY;
-```
-
-Example 8: Asynchronously query the table `order_detail` and create a new table `order_statistics` based on the query result, and then insert the query result into the new table.
-
-```plaintext
-SUBMIT TASK AS CREATE TABLE order_statistics AS SELECT COUNT(*) as count FROM order_detail;
-
-+-------------------------------------------+-----------+
-| TaskName                                  | Status    |
-+-------------------------------------------+-----------+
-| ctas-df6f7930-e7c9-11ec-abac-bab8ee315bf2 | SUBMITTED |
-+-------------------------------------------+-----------+
-```
-
-Check information of the Task.
-
-```SQL
-SELECT * FROM INFORMATION_SCHEMA.tasks;
-
--- Information of the Task
-
-TASK_NAME: ctas-df6f7930-e7c9-11ec-abac-bab8ee315bf2
-CREATE_TIME: 2022-06-14 14:07:06
-SCHEDULE: MANUAL
-DATABASE: default_cluster:test
-DEFINITION: CREATE TABLE order_statistics AS SELECT COUNT(*) as cnt FROM order_detail
-EXPIRE_TIME: 2022-06-17 14:07:06
-```
-
-Check the state of the TaskRun.
-
-```SQL
-SELECT * FROM INFORMATION_SCHEMA.task_runs;
-
--- State of the TaskRun
-
-QUERY_ID: 37bd2b63-eba8-11ec-8d41-bab8ee315bf2
-TASK_NAME: ctas-df6f7930-e7c9-11ec-abac-bab8ee315bf2
-CREATE_TIME: 2022-06-14 14:07:06
-FINISH_TIME: 2022-06-14 14:07:07
-STATE: SUCCESS
-DATABASE: 
-DEFINITION: CREATE TABLE order_statistics AS SELECT COUNT(*) as cnt FROM order_detail
-EXPIRE_TIME: 2022-06-17 14:07:06
-ERROR_CODE: 0
-ERROR_MESSAGE: NULL
-```
-
-Query the new table when the state of the TaskRun is `SUCCESS`.
-
-```SQL
-SELECT * FROM order_statistics;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/CREATE_TABLE_LIKE.md b/docs/en/sql-reference/sql-statements/data-definition/CREATE_TABLE_LIKE.md
deleted file mode 100644
index e25952754616ce..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/CREATE_TABLE_LIKE.md
+++ /dev/null
@@ -1,156 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE TABLE LIKE
-
-## Description
-
-Creates an identical empty table based on the definition of another table. The definition includes column definition, partitions, and table properties. You can copy an external table such as MySQL.
-
-v3.2 allows you to specify a different partitioning method, bucketing method, and properties for the new table than the source table.
-
-:::tip
-This operation requires the CREATE TABLE privilege on the database in which you want to create a table, and the `SELECT` privilege on the source table based on which to create a table.
-:::
-
-## Syntax
-
-- Syntax supported in versions earlier than v3.2.
-
-```sql
-CREATE [EXTERNAL] TABLE [IF NOT EXISTS] [database.]<table_name>
-LIKE [database.]<source_table_name>
-```
-
-- v3.2 supports specifying properties for the new table.
-
-```sql
-CREATE [TEMPORARY] [EXTERNAL] TABLE [IF NOT EXISTS] [database.]<table_name>
-[partition_desc]
-[distribution_desc]
-[PROPERTIES ("key" = "value",...)]
-LIKE [database.]<source_table_name>
-```
-
-## Parameters
-
-- `TEMPORARY`: Creates a temporary table. From v3.3.1, StarRocks supports creating temporary tables in the Default Catalog. For more information, see [Temporary Table](../../../table_design/StarRocks_table_design.md#temporary-table).
-- `database`: the database.
-- `table_name`: the name of the table you want to create. For the naming conventions, see [System limits](../../../reference/System_limit.md).
-- `source_table_name`: the name of the source table you want to copy.
-- - `partition_desc`: the partitioning method. For more information, see [CREATE TABLE](./CREATE_TABLE.md#partition_desc).
-- `distribution_desc`: the bucketing method. For more information, see [CREATE TABLE](./CREATE_TABLE.md#distribution_desc).
-- `PROPERTIES`: the properties of the table. All the table properties are supported. For more information, see [ALTER TABLE](./ALTER_TABLE.md#modify-table-properties).
-
-## Examples
-
-Suppose there is a table `orders` in database `test1`.
-
-```sql
-create table orders (
-    dt date NOT NULL,
-    order_id bigint NOT NULL,
-    user_id int NOT NULL,
-    merchant_id int NOT NULL,
-    good_id int NOT NULL,
-    good_name string NOT NULL,
-    price int NOT NULL,
-    cnt int NOT NULL,
-    revenue int NOT NULL,
-    state tinyint NOT NULL
-) PRIMARY KEY (dt, order_id)
-PARTITION BY RANGE(`dt`) (
-    PARTITION p20210820 VALUES [('2021-08-20'), ('2021-08-21')),
-    PARTITION p20210821 VALUES [('2021-08-21'), ('2021-08-22')),
-    PARTITION p20210929 VALUES [('2021-09-29'), ('2021-09-30')),
-    PARTITION p20210930 VALUES [('2021-09-30'), ('2021-10-01'))
-) DISTRIBUTED BY HASH(order_id)
-PROPERTIES (
-    "replication_num" = "3",
-    "enable_persistent_index" = "true"
-);
-```
-
-Example 1: In database `test1`, create an empty table `order_1` that has the same table structure as `orders`.
-
- ```sql
-CREATE TABLE test1.order_1 LIKE test1.orders;
-```
-
-```plaintext
-show create table order_1\G
-*************************** 1. row ***************************
-       Table: order_1
-Create Table: CREATE TABLE `order_1` (
-  `dt` date NOT NULL COMMENT "",
-  `order_id` bigint(20) NOT NULL COMMENT "",
-  `user_id` int(11) NOT NULL COMMENT "",
-  `merchant_id` int(11) NOT NULL COMMENT "",
-  `good_id` int(11) NOT NULL COMMENT "",
-  `good_name` varchar(65533) NOT NULL COMMENT "",
-  `price` int(11) NOT NULL COMMENT "",
-  `cnt` int(11) NOT NULL COMMENT "",
-  `revenue` int(11) NOT NULL COMMENT "",
-  `state` tinyint(4) NOT NULL COMMENT ""
-) ENGINE=OLAP 
-PRIMARY KEY(`dt`, `order_id`)
-PARTITION BY RANGE(`dt`)
-(PARTITION p20210820 VALUES [("2021-08-20"), ("2021-08-21")),
-PARTITION p20210821 VALUES [("2021-08-21"), ("2021-08-22")),
-PARTITION p20210929 VALUES [("2021-09-29"), ("2021-09-30")),
-PARTITION p20210930 VALUES [("2021-09-30"), ("2021-10-01")))
-DISTRIBUTED BY HASH(`order_id`)
-PROPERTIES (
-"replication_num" = "3",
-"in_memory" = "false",
-"enable_persistent_index" = "true",
-"replicated_storage" = "true",
-"compression" = "LZ4"
-);
-```
-
-Example 2: Create an empty table `order_2` based on `orders` and specify properties for `order_2`.
-
-```sql
-CREATE TABLE order_2
-PARTITION BY date_trunc('day',dt)
-DISTRIBUTED BY hash(dt)
-PROPERTIES ("replication_num" = "1")
-LIKE orders;
-```
-
-```plaintext
-show create table order_2\G
-*************************** 1. row ***************************
-       Table: order_2
-Create Table: CREATE TABLE `order_2` (
-  `dt` date NOT NULL COMMENT "",
-  `order_id` bigint(20) NOT NULL COMMENT "",
-  `user_id` int(11) NOT NULL COMMENT "",
-  `merchant_id` int(11) NOT NULL COMMENT "",
-  `good_id` int(11) NOT NULL COMMENT "",
-  `good_name` varchar(65533) NOT NULL COMMENT "",
-  `price` int(11) NOT NULL COMMENT "",
-  `cnt` int(11) NOT NULL COMMENT "",
-  `revenue` int(11) NOT NULL COMMENT "",
-  `state` tinyint(4) NOT NULL COMMENT ""
-) ENGINE=OLAP 
-PRIMARY KEY(`dt`, `order_id`)
-PARTITION BY RANGE(date_trunc('day', dt))
-()
-DISTRIBUTED BY HASH(`dt`)
-PROPERTIES (
-"replication_num" = "1",
-"in_memory" = "false",
-"enable_persistent_index" = "true",
-"replicated_storage" = "true",
-"compression" = "LZ4"
-);
-```
-
-Example 3: Create an empty table `table2` that has the same table structure as MySQL external table `table1`.
-
-```sql
-CREATE TABLE test1.table2 LIKE test1.table1
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/CREATE_VIEW.md b/docs/en/sql-reference/sql-statements/data-definition/CREATE_VIEW.md
deleted file mode 100644
index f936a3170aa8f3..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/CREATE_VIEW.md
+++ /dev/null
@@ -1,79 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE VIEW
-
-## Description
-
-Creates a view.
-
-A view, or a logical view, is a virtual table whose data is derived from a query against other existing physical tables. Therefore, a view uses no physical storage, and all queries against the view are equivalent to sub-queries of the query statement used to build the view.
-
-For information about materialized views supported by StarRocks, see [Synchronous materialized views](../../../using_starrocks/Materialized_view-single_table.md) and [Asynchronous materialized views](../../../using_starrocks/Materialized_view.md).
-
-:::tip
-Only users with the CREATE VIEW privilege on a specific database can perform this operation.
-:::
-
-## Syntax
-
-```SQL
-CREATE [OR REPLACE] VIEW [IF NOT EXISTS]
-[<database>.]<view_name>
-(
-    <column_name>[ COMMENT 'column comment']
-    [, <column_name>[ COMMENT 'column comment'], ...]
-)
-[COMMENT 'view comment']
-AS <query_statement>
-```
-
-## Parameters
-
-| **Parameter**   | **Description**                                              |
-| --------------- | ------------------------------------------------------------ |
-| OR REPLACE      | Replace an existing view.                                    |
-| database        | The name of the database where the view resides.             |
-| view_name       | The name of the view. For the naming conventions, see [System limits](../../../reference/System_limit.md).             |
-| column_name     | The name of the column(s) in the view. Note that the columns in the view and the columns queried in the `query_statement` must agree in number. |
-| COMMENT         | The comment on the column in the view or the view itself.    |
-| query_statement | The query statement used to create the view. It can be any query statement supported by StarRocks. |
-
-## Usage notes
-
-- Querying a view requires the SELECT privilege on the view and on its corresponding base tables.
-- If the query statement used to build a view cannot be executed due to the Schema Change on the base tables, StarRocks returns an error when you query the view.
-
-## Examples
-
-Example 1: Create a view named `example_view` in `example_db` with an aggregate query against `example_table`.
-
-```SQL
-CREATE VIEW example_db.example_view (k1, k2, k3, v1)
-AS
-SELECT c1 as k1, k2, k3, SUM(v1) FROM example_table
-WHERE k1 = 20160112 GROUP BY k1,k2,k3;
-```
-
-Example 2: Create a view named `example_view` in the database `example_db` with an aggregate query against the table `example_table`, and specify comments for the view and each column in it.
-
-```SQL
-CREATE VIEW example_db.example_view
-(
-    k1 COMMENT 'first key',
-    k2 COMMENT 'second key',
-    k3 COMMENT 'third key',
-    v1 COMMENT 'first value'
-)
-COMMENT 'my first view'
-AS
-SELECT c1 as k1, k2, k3, SUM(v1) FROM example_table
-WHERE k1 = 20160112 GROUP BY k1,k2,k3;
-```
-
-## Relevant SQLs
-
-- [SHOW CREATE VIEW](../data-manipulation/SHOW_CREATE_VIEW.md)
-- [ALTER VIEW](./ALTER_VIEW.md)
-- [DROP VIEW](./DROP_VIEW.md)
diff --git a/docs/en/sql-reference/sql-statements/data-definition/DROP_ANALYZE.md b/docs/en/sql-reference/sql-statements/data-definition/DROP_ANALYZE.md
deleted file mode 100644
index 3729dee3b8a8a3..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/DROP_ANALYZE.md
+++ /dev/null
@@ -1,37 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP ANALYZE
-
-## Description
-
-Deletes a custom collection task.
-
-By default, StarRocks automatically collects full statistics of a table. It checks for any data updates every 5 minutes. If data change is detected, data collection will be automatically triggered. If you do not want to use automatic full collection, you can set the FE configuration item `enable_collect_full_statistic` to `false` and customize a collection task.
-
-This statement is supported from v2.4.
-
-## Syntax
-
-```SQL
-DROP ANALYZE <ID>
-```
-
-The task ID can be obtained by using the SHOW ANALYZE JOB statement.
-
-## Examples
-
-```SQL
-DROP ANALYZE 266030;
-```
-
-## References
-
-[CREATE ANALYZE](../data-definition/CREATE_ANALYZE.md): customize an automatic collection task.
-
-[SHOW ANALYZE JOB](../data-definition/SHOW_ANALYZE_JOB.md): view the status of an automatic collection task.
-
-[KILL ANALYZE](../data-definition/KILL_ANALYZE.md): cancel a custom collection task that is running.
-
-For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/data-definition/DROP_CATALOG.md b/docs/en/sql-reference/sql-statements/data-definition/DROP_CATALOG.md
deleted file mode 100644
index 90907d3ad5f690..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/DROP_CATALOG.md
+++ /dev/null
@@ -1,37 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP CATALOG
-
-## Description
-
-Deletes an external catalog. The internal catalog cannot be deleted. A StarRocks cluster has only one internal catalog named `default_catalog`.
-
-## Syntax
-
-```SQL
-DROP CATALOG [IF EXISTS] <catalog_name>
-```
-
-## Parameters
-
-`catalog_name`: The name of an external catalog.
-
-## Examples
-
-Create a Hive catalog named `hive1`.
-
-```SQL
-CREATE EXTERNAL CATALOG hive1
-PROPERTIES(
-  "type"="hive", 
-  "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
-);
-```
-
-Delete the Hive catalog.
-
-```SQL
-DROP CATALOG hive1;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/DROP_DATABASE.md b/docs/en/sql-reference/sql-statements/data-definition/DROP_DATABASE.md
deleted file mode 100644
index 8e4174e79c1d9a..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/DROP_DATABASE.md
+++ /dev/null
@@ -1,41 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP DATABASE
-
-## Description
-
-Drops a database in StarRocks.
-
-> **NOTE**
->
-> This operation requires the DROP privilege on the destination database.
-
-## Syntax
-
-```sql
-DROP DATABASE [IF EXISTS] <db_name> [FORCE]
-```
-
-Take note of the following points:
-
-- After executing DROP DATABASE to drop a database, you can restore the dropped database by using the [RECOVER](../data-definition/backup_restore/RECOVER.md) statement within a specified retention period (the default retention period spans one day), but the pipes (supported from v3.2 onwards) that have been dropped along with the database cannot be recovered.
-- If you execute `DROP DATABASE FORCE` to drop a database, the database is deleted directly without any checks on whether there are unfinished activities in it and cannot be recovered. Generally, this operation is not recommended.
-- If you drop a database, all pipes (supported from v3.2 onwards) that belong to the database are dropped along with the database.
-
-## Examples
-
-1. Drop database db_text.
-
-    ```sql
-    DROP DATABASE db_test;
-    ```
-
-## References
-
-- [CREATE DATABASE](../data-definition/CREATE_DATABASE.md)
-- [SHOW CREATE DATABASE](../data-manipulation/SHOW_CREATE_DATABASE.md)
-- [USE](../data-definition/USE.md)
-- [DESC](../Utility/DESCRIBE.md)
-- [SHOW DATABASES](../data-manipulation/SHOW_DATABASES.md)
diff --git a/docs/en/sql-reference/sql-statements/data-definition/DROP_FUNCTION.md b/docs/en/sql-reference/sql-statements/data-definition/DROP_FUNCTION.md
deleted file mode 100644
index d864289a5fe705..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/DROP_FUNCTION.md
+++ /dev/null
@@ -1,31 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP FUNCTION
-
-## Description
-
-Deletes a custom function. The function can only be deleted when its name and parameter type are consistent.
-
-Only the owner of the custom function have the permissions to delete the function.
-
-### Syntax
-
-```sql
-DROP FUNCTION function_name(arg_type [, ...])
-```
-
-### Parameters
-
-`function_name`: the name of function to be dropped.
-
-`arg_type`: the argument type of function to be dropped.
-
-## Examples
-
-1. Drop a function.
-
-    ```sql
-    DROP FUNCTION my_add(INT, INT)
-    ```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/DROP_INDEX.md b/docs/en/sql-reference/sql-statements/data-definition/DROP_INDEX.md
deleted file mode 100644
index a0eaad11fccf55..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/DROP_INDEX.md
+++ /dev/null
@@ -1,21 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP INDEX
-
-## Description
-
-This statement is used to drop a specified index on a table. Currently, only bitmap index is supported in this version.
-
-:::tip
-
-This operation requires the ALTER privilege on the target table. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
-
-:::
-
-Syntax:
-
-```sql
-DROP INDEX index_name ON [db_name.]table_name
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW.md
deleted file mode 100644
index 4d4fc3a83588b9..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW.md
+++ /dev/null
@@ -1,78 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP MATERIALIZED VIEW
-
-## Description
-
-Drops a materialized view.
-
-You cannot drop a synchronous materialized view that is being created in process with this command. To drop a synchronous materialized view that is being created in process, see [Synchronous materialized View - Drop an unfinished materialized view](../../../using_starrocks/Materialized_view-single_table.md#drop-an-unfinished-synchronous-materialized-view) for further instructions.
-
-:::tip
-
-This operation requires the DROP privilege on the target materialized view.
-
-:::
-
-## Syntax
-
-```SQL
-DROP MATERIALIZED VIEW [IF EXISTS] [database.]mv_name
-```
-
-Parameters in brackets [] is optional.
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                              |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| IF EXISTS     | no           | If this parameter is specified, StarRocks will not throw an exception when deleting a materialized view that does not exist. If this parameter is not specified, the system will throw an exception when deleting a materialized view that does not exist. |
-| mv_name       | yes          | The name of the materialized view to delete.                 |
-
-## Examples
-
-Example 1: Drop an existing materialized view
-
-1. View all existing materialized views in the database.
-
-  ```Plain
-  MySQL > SHOW MATERIALIZED VIEWS\G
-  *************************** 1. row ***************************
-              id: 470740
-          name: order_mv1
-  database_name: default_cluster:sr_hub
-        text: SELECT `sr_hub`.`orders`.`dt` AS `dt`, `sr_hub`.`orders`.`order_id` AS `order_id`, `sr_hub`.`orders`.`user_id` AS `user_id`, sum(`sr_hub`.`orders`.`cnt`) AS `total_cnt`, sum(`sr_hub`.`orders`.`revenue`) AS `total_revenue`, count(`sr_hub`.`orders`.`state`) AS `state_count` FROM `sr_hub`.`orders` GROUP BY `sr_hub`.`orders`.`dt`, `sr_hub`.`orders`.`order_id`, `sr_hub`.`orders`.`user_id`
-          rows: 0
-  1 rows in set (0.00 sec)
-  ```
-
-2. Drop the materialized view `order_mv1`.
-
-  ```SQL
-  DROP MATERIALIZED VIEW order_mv1;
-  ```
-
-3. Check if the dropped materialized view exists.
-
-  ```Plain
-  MySQL > SHOW MATERIALIZED VIEWS;
-  Empty set (0.01 sec)
-  ```
-
-Example 2: Drop a non-existing materialized view
-
-- If the parameter `IF EXISTS` is specified, StarRocks will not throw an exception when deleting a materialized view that does not exist.
-
-```Plain
-MySQL > DROP MATERIALIZED VIEW IF EXISTS k1_k2;
-Query OK, 0 rows affected (0.00 sec)
-```
-
-- If the parameter `IF EXISTS` is not specified, the system will throw an exception when deleting a materialized view that does not exist.
-
-```Plain
-MySQL > DROP MATERIALIZED VIEW k1_k2;
-ERROR 1064 (HY000): Materialized view k1_k2 is not find
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/DROP_RESOURCE.md b/docs/en/sql-reference/sql-statements/data-definition/DROP_RESOURCE.md
deleted file mode 100644
index 13b4a60740c2a1..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/DROP_RESOURCE.md
+++ /dev/null
@@ -1,29 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP RESOURCE
-
-## Description
-
-This statement is used to drop an existing resource. Only root or superuser can drop resources.
-
-Syntax:
-
-```sql
-DROP RESOURCE 'resource_name'
-```
-
-## Examples
-
-1. Drop Spark resource named spark0.
-
-    ```SQL
-    DROP RESOURCE 'spark0';
-    ```
-
-2. Drop Hive resource named hive0.
-
-    ```SQL
-    DROP RESOURCE 'hive0';
-    ```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/DROP_STATS.md b/docs/en/sql-reference/sql-statements/data-definition/DROP_STATS.md
deleted file mode 100644
index a0101b2ac63911..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/DROP_STATS.md
+++ /dev/null
@@ -1,31 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP STATS
-
-## Description
-
-Deletes CBO statistics, which include basic statistics and histograms. For more information, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md#basic-statistics).
-
-You can delete statistical information you do not need. When you delete statistics, both the data and metadata of the statistics are deleted, as well as the statistics in expired cache. Note that if an automatic collection task is ongoing, previously deleted statistics may be collected again. You can use `SHOW ANALYZE STATUS` to view the history of collection tasks.
-
-This statement is supported from v2.4.
-
-## Syntax
-
-### Delete basic statistics
-
-```SQL
-DROP STATS tbl_name
-```
-
-### Delete histograms
-
-```SQL
-ANALYZE TABLE tbl_name DROP HISTOGRAM ON col_name [, col_name];
-```
-
-## References
-
-For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/data-definition/DROP_TABLE.md b/docs/en/sql-reference/sql-statements/data-definition/DROP_TABLE.md
deleted file mode 100644
index c06300c9d55321..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/DROP_TABLE.md
+++ /dev/null
@@ -1,49 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP TABLE
-
-## Description
-
-This statement is used to delete a table.
-
-## Syntax
-
-```sql
-DROP [TEMPORARY] TABLE [IF EXISTS] [db_name.]table_name [FORCE]
-```
-
-Note:
-
-- After a table is dropped, you can use the [RECOVER](../data-definition/backup_restore/RECOVER.md) statement to restore the table within a specified period (1 day by default).
-- If DROP Table FORCE is executed, the table will be deleted directly and cannot be recovered without checking whether there are unfinished activities in the database. Generally, this operation is not recommended.
-- Once dropped, temporary tables cannot be restored using RECOVER.
-
-## Examples
-
-1. Drop a table.
-
-    ```sql
-    DROP TABLE my_table;
-    ```
-
-2. If it exists, then drop the table on the specified database.
-
-    ```sql
-    DROP TABLE IF EXISTS example_db.my_table;
-    ```
-
-3. Force to drop the table and clear its data on disk.
-
-    ```sql
-    DROP TABLE my_table FORCE;
-    ```
-
-## References
-
-- [CREATE TABLE](CREATE_TABLE.md)
-- [SHOW TABLES](../data-manipulation/SHOW_TABLES.md)
-- [SHOW CREATE TABLE](../data-manipulation/SHOW_CREATE_TABLE.md)
-- [ALTER TABLE](ALTER_TABLE.md)
-- [SHOW ALTER TABLE](../data-manipulation/SHOW_ALTER.md)
diff --git a/docs/en/sql-reference/sql-statements/data-definition/DROP_VIEW.md b/docs/en/sql-reference/sql-statements/data-definition/DROP_VIEW.md
deleted file mode 100644
index cc525693aeaeee..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/DROP_VIEW.md
+++ /dev/null
@@ -1,24 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP VIEW
-
-## Description
-
-This statement is used to drop a logical view VIEW
-
-## Syntax
-
-```sql
-DROP VIEW [IF EXISTS]
-[db_name.]view_name
-```
-
-## Examples
-
-1. If it exists, then drop the view example_view on example_db.
-
-    ```sql
-    DROP VIEW IF EXISTS example_db.example_view;
-    ```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/KILL_ANALYZE.md b/docs/en/sql-reference/sql-statements/data-definition/KILL_ANALYZE.md
deleted file mode 100644
index f487f7472a2fea..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/KILL_ANALYZE.md
+++ /dev/null
@@ -1,27 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# KILL ANALYZE
-
-## Description
-
-Cancels a **running** collection task, including manual and custom automatic tasks.
-
-This statement is supported from v2.4.
-
-## Syntax
-
-```SQL
-KILL ANALYZE <ID>
-```
-
-The task ID for a manual collection task can be obtained from SHOW ANALYZE STATUS. The task ID for a custom collection task can be obtained from SHOW ANALYZE SHOW ANALYZE JOB.
-
-## References
-
-[SHOW ANALYZE STATUS](../data-definition/SHOW_ANALYZE_STATUS.md)
-
-[SHOW ANALYZE JOB](../data-definition/SHOW_ANALYZE_JOB.md)
-
-For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE.md b/docs/en/sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE.md
deleted file mode 100644
index 7c87cb003bd20e..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE.md
+++ /dev/null
@@ -1,101 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# REFRESH EXTERNAL TABLE
-
-## Description
-
-Updates metadata cached in StarRocks. The metadata is from tables in data lakes. This statement is used in the following scenarios:
-
-- **External table**: When using a Hive external table or Hudi external table to query data in Apache Hive™ or Apache Hudi, you can execute this statement to update the metadata of a Hive table or Hudi table cached in StarRocks.
-- **External catalog**: When using a [Hive catalog](../../../data_source/catalog/hive_catalog.md), [Hudi catalog](../../../data_source/catalog/hudi_catalog.md), [Delta Lake catalog](../../../data_source/catalog/deltalake_catalog.md), or [MaxCompute Catalog](../../../data_source/catalog/maxcompute_catalog.md) (since v3.3) to query data in the corresponding data source, you can execute this statement to update the metadata cached in StarRocks.
-
-## Basic concepts
-
-- **Hive external table**: is created and stored in StarRocks. You can use it to query Hive data.
-- **Hudi external table**: is created and stored in StarRocks. You can use it to query Hudi data.
-- **Hive table**: is created and stored in Hive.
-- **Hudi table**: is created and stored in Hudi.
-
-## Syntaxes and parameters
-
-The following describes the syntaxes and parameters based on different cases:
-
-- External table
-
-    ```SQL
-    REFRESH EXTERNAL TABLE table_name 
-    [PARTITION ('partition_name', ...)]
-    ```
-
-    | **Parameter**  | **Required** | **Description**                                              |
-    | -------------- | ------------ | ------------------------------------------------------------ |
-    | table_name     | Yes          | The name of a Hive external table or Hudi external table.    |
-    | partition_name | No           | The names of the partitions of a Hive table or Hudi table. Specifying this parameter updates the metadata of the partitions of the Hive table and Hudi table cached in StarRocks. |
-
-- External catalog
-
-    ```SQL
-    REFRESH EXTERNAL TABLE [external_catalog.][db_name.]table_name
-    [PARTITION ('partition_name', ...)]
-    ```
-
-    | **Parameter**    | **Required** | **Description**                                              |
-    | ---------------- | ------------ | ------------------------------------------------------------ |
-    | external_catalog | No           | The name of the external catalog, which supports Hive, Hudi, Delta Lake, and MaxCompute (since v3.3) catalogs.                  |
-    | db_name          | No           | The name of the database where the destination table resides. |
-    | table_name       | Yes          | The name of the table.                    |
-    | partition_name   | No           | The names of the partitions. Specifying this parameter updates the metadata of the partitions of the destination table cached in StarRocks. |
-
-## Usage notes
-
-Only users who have the `ALTER_PRIV` privilege can execute this statement to update the metadata of Hive tables and Hudi tables cached in StarRocks.
-
-## Examples
-
-Usage examples in different cases are as follows:
-
-### External table
-
-Example 1: Update the cached metadata of the corresponding Hive table in StarRocks by specifying the external table `hive1`.
-
-```SQL
-REFRESH EXTERNAL TABLE hive1;
-```
-
-Example 2: Update the cached metadata of the partitions of the corresponding Hudi table in StarRocks by specifying the external table `hudi1` and the partitions in that table.
-
-```SQL
-REFRESH EXTERNAL TABLE hudi1
-PARTITION ('date=2022-12-20', 'date=2022-12-21');
-```
-
-### External catalog
-
-Example 1: Update the metadata of `hive_table` cached in StarRocks.
-
-```SQL
-REFRESH EXTERNAL TABLE hive_catalog.hive_db.hive_table;
-```
-
-Or
-
-```SQL
-USE hive_catalog.hive_db;
-REFRESH EXTERNAL TABLE hive_table;
-```
-
-Example 2: Update the metadata of the second-level partition `p2` in `hive_table` cached in StarRocks.
-
-```SQL
-USE hive_catalog.hive_db;
-REFRESH EXTERNAL TABLE hive_table PARTITION ('p1=${date}/p2=${hour}');
-```
-
-Example 3: Update the metadata of the partitions of `hudi_table` cached in StarRocks.
-
-```SQL
-REFRESH EXTERNAL TABLE hudi_catalog.hudi_db.hudi_table
-PARTITION ('date=2022-12-20', 'date=2022-12-21');
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/SET_CATALOG.md b/docs/en/sql-reference/sql-statements/data-definition/SET_CATALOG.md
deleted file mode 100644
index 399bb64aa5cb8a..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/SET_CATALOG.md
+++ /dev/null
@@ -1,37 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SET CATALOG
-
-Switches to a specified catalog in the current session.
-
-This command is supported from v3.0 onwards.
-
-> **NOTE**
->
-> For a newly deployed StarRocks v3.1 cluster, you must have the USAGE privilege on the destination external catalog if you want to run SET CATALOG to switch to that catalog. You can use [GRANT](../account-management/GRANT.md) to grant the required privileges. For a v3.1 cluster upgraded from an earlier version, you can run SET CATALOG with the inherited privilege.
-
-## Syntax
-
-```SQL
-SET CATALOG <catalog_name>
-```
-
-## Parameter
-
-`catalog_name`: the name of the catalog to use in the current session. You can switch to an internal or external catalog. If the catalog that you specify does not exist, an exception is thrown.
-
-## Examples
-
-Run the following command to switch to a Hive catalog named `hive_metastore` in the current session:
-
-```SQL
-SET CATALOG hive_metastore;
-```
-
-Run the following command to switch to the internal catalog `default_catalog` in the current session:
-
-```SQL
-SET CATALOG default_catalog;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/SHOW_ANALYZE_JOB.md b/docs/en/sql-reference/sql-statements/data-definition/SHOW_ANALYZE_JOB.md
deleted file mode 100644
index df9d802a8e7390..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/SHOW_ANALYZE_JOB.md
+++ /dev/null
@@ -1,54 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW ANALYZE JOB
-
-## Description
-
-Views the information and status of custom collection tasks.
-
-By default, StarRocks automatically collects full statistics of a table. It checks for any data updates every 5 minutes. If data change is detected, data collection will be automatically triggered. If you do not want to use automatic full collection, you can set the FE configuration item `enable_collect_full_statistic` to `false` and customize a collection task.
-
-This statement is supported from v2.4.
-
-## Syntax
-
-```SQL
-SHOW ANALYZE JOB [WHERE]
-```
-
-You can filter results by using the WHERE clause. The statement returns the following columns.
-
-| **Column**   | **Description**                                              |
-| ------------ | ------------------------------------------------------------ |
-| Id           | The ID of the collection task.                               |
-| Database     | The database name.                                           |
-| Table        | The table name.                                              |
-| Columns      | The column names.                                            |
-| Type         | The type of statistics, including `FULL` and `SAMPLE`.       |
-| Schedule     | The type of scheduling. The type is `SCHEDULE` for an automatic task. |
-| Properties   | Custom parameters.                                           |
-| Status       | The task status, including PENDING, RUNNING, SUCCESS, and FAILED. |
-| LastWorkTime | The time of the last collection.                             |
-| Reason       | The reason why the task failed. NULL is returned if task execution was successful. |
-
-## Examples
-
-```SQL
--- View all the custom collection tasks.
-SHOW ANALYZE JOB
-
--- View custom collection tasks of database `test`.
-SHOW ANALYZE JOB where `database` = 'test';
-```
-
-## References
-
-[CREATE ANALYZE](../data-definition/CREATE_ANALYZE.md): customize an automatic collection task.
-
-[DROP ANALYZE](../data-definition/DROP_ANALYZE.md): delete a custom collection task.
-
-[KILL ANALYZE](../data-definition/KILL_ANALYZE.md): cancel a custom collection task that is running.
-
-For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/data-definition/SHOW_ANALYZE_STATUS.md b/docs/en/sql-reference/sql-statements/data-definition/SHOW_ANALYZE_STATUS.md
deleted file mode 100644
index 429e9aad837d5e..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/SHOW_ANALYZE_STATUS.md
+++ /dev/null
@@ -1,45 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW ANALYZE STATUS
-
-## Description
-
-Views the status of collection tasks.
-
-This statement cannot be used to view the status of custom collection tasks. To view the status of custom collection tasks, use SHOW ANALYZE JOB.
-
-This statement is supported from v2.4.
-
-## Syntax
-
-```SQL
-SHOW ANALYZE STATUS [WHERE]
-```
-
-You can use `LIKE` or `WHERE` to filter the information to return.
-
-This statement returns the following columns.
-
-| **List name** | **Description**                                              |
-| ------------- | ------------------------------------------------------------ |
-| Id            | The ID of the collection task.                               |
-| Database      | The database name.                                           |
-| Table         | The table name.                                              |
-| Columns       | The column names.                                            |
-| Type          | The type of statistics, including FULL, SAMPLE, and HISTOGRAM. |
-| Schedule      | The type of scheduling. `ONCE` means manual and `SCHEDULE` means automatic. |
-| Status        | The status of the task.                                      |
-| StartTime     | The time when the task starts executing.                     |
-| EndTime       | The time when the task execution ends.                       |
-| Properties    | Custom parameters.                                           |
-| Reason        | The reason why the task failed. NULL is returned if the execution was successful. |
-
-## References
-
-[ANALYZE TABLE](../data-definition/ANALYZE_TABLE.md): create a manual collection task.
-
-[KILL ANALYZE](../data-definition/KILL_ANALYZE.md): cancel a custom collection task that is running.
-
-For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/data-definition/SHOW_FUNCTIONS.md b/docs/en/sql-reference/sql-statements/data-definition/SHOW_FUNCTIONS.md
deleted file mode 100644
index 256dd1b412006f..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/SHOW_FUNCTIONS.md
+++ /dev/null
@@ -1,57 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW FUNCTIONS
-
-## Description
-
-Queries all the custom (or built-in) functions under a database. If no database is specified, the current database is used by default.
-
-## Syntax
-
-```sql
-SHOW [FULL] [BUILTIN] FUNCTIONS [IN|FROM db] [LIKE 'function_pattern']
-```
-
-## Parameters
-
-```plain text
-full: indicates showing all the functions. 
-
-builtin: indicates showing functions provided by the system.
-
-db: the name of the database to query.
-
-function_pattern: the pattern used to filter function name. 
-```
-
-## Examples
-
-```Plain Text
-mysql> show full functions in testDb\G
-*************************** 1. row ***************************
-        Signature: my_add(INT,INT)
-      Return Type: INT
-    Function Type: Scalar
-Intermediate Type: NULL
-       Properties: {"symbol":"_ZN9starrocks_udf6AddUdfEPNS_15FunctionContextERKNS_6IntValES4_","object_file":"http://host:port/libudfsample.so","md5":"cfe7a362d10f3aaf6c49974ee0f1f878"}
-*************************** 2. row ***************************
-        Signature: my_count(BIGINT)
-      Return Type: BIGINT
-    Function Type: Aggregate
-Intermediate Type: NULL
-       Properties: {"object_file":"http://host:port/libudasample.so","finalize_fn":"_ZN9starrocks_udf13CountFinalizeEPNS_15FunctionContextERKNS_9BigIntValE","init_fn":"_ZN9starrocks_udf9CountInitEPNS_15FunctionContextEPNS_9BigIntValE","merge_fn":"_ZN9starrocks_udf10CountMergeEPNS_15FunctionContextERKNS_9BigIntValEPS2_","md5":"37d185f80f95569e2676da3d5b5b9d2f","update_fn":"_ZN9starrocks_udf11CountUpdateEPNS_15FunctionContextERKNS_6IntValEPNS_9BigIntValE"}
-
-2 rows in set (0.00 sec)
-mysql> show builtin functions in testDb like 'year%';
-+---------------+
-| Function Name |
-+---------------+
-| year          |
-| years_add     |
-| years_diff    |
-| years_sub     |
-+---------------+
-2 rows in set (0.00 sec)
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/SHOW_META.md b/docs/en/sql-reference/sql-statements/data-definition/SHOW_META.md
deleted file mode 100644
index e09089be90ffbc..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/SHOW_META.md
+++ /dev/null
@@ -1,54 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW META
-
-## Description
-
-Views metadata of CBO statistics, including basic statistics and histograms.
-
-This statement is supported from v2.4.
-
-### View metadata of basic statistics
-
-#### Syntax
-
-```SQL
-SHOW STATS META [WHERE]
-```
-
-This statement returns the following columns.
-
-| **Column** | **Description**                                              |
-| ---------- | ------------------------------------------------------------ |
-| Database   | The database name.                                           |
-| Table      | The table name.                                              |
-| Columns    | The column names.                                            |
-| Type       | The type of statistics. `FULL` means full collection and `SAMPLE` means sampled collection. |
-| UpdateTime | The latest statistics update time for the current table.     |
-| Properties | Custom parameters.                                           |
-| Healthy    | The health of statistical information.                       |
-
-### View metadata of histograms
-
-#### Syntax
-
-```SQL
-SHOW HISTOGRAM META [WHERE];
-```
-
-This statement returns the following columns.
-
-| **Column** | **Description**                                              |
-| ---------- | ------------------------------------------------------------ |
-| Database   | The database name.                                           |
-| Table      | The table name.                                              |
-| Column     | The columns.                                                 |
-| Type       | Type of statistics. The value is `HISTOGRAM` for histograms. |
-| UpdateTime | The latest statistics update time for the current table.     |
-| Properties | Custom parameters.                                           |
-
-## References
-
-For more information about collecting statistics for CBO, see [Gather statistics for CBO](../../../using_starrocks/Cost_based_optimizer.md).
diff --git a/docs/en/sql-reference/sql-statements/data-definition/SHOW_RESOURCES.md b/docs/en/sql-reference/sql-statements/data-definition/SHOW_RESOURCES.md
deleted file mode 100644
index 32ada5a6ad3ecc..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/SHOW_RESOURCES.md
+++ /dev/null
@@ -1,15 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW RESOURCES
-
-## Description
-
-This statement is used to show the resources that the users have permissions to use. Ordinary users can only use the resources they have permission to use, while root or admin users can show all resources.
-
-Syntax:
-
-```sql
-SHOW RESOURCES
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/TRUNCATE_TABLE.md b/docs/en/sql-reference/sql-statements/data-definition/TRUNCATE_TABLE.md
deleted file mode 100644
index 5f93220b4c0eea..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/TRUNCATE_TABLE.md
+++ /dev/null
@@ -1,37 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# TRUNCATE TABLE
-
-## Description
-
-This statement is used to truncate the specified table and partition data.
-
-Syntax:
-
-```sql
-TRUNCATE TABLE [db.]tbl[ PARTITION(p1, p2, ...)]
-```
-
-Note:
-
-1. This statement is used to truncate data while retaining tables or partitions.
-2. Unlike DELETE, this statement can only empty the specified tables or partitions as a whole, and filtering conditions cannot be added.
-3. Unlike DELETE, using this method to clear data will not affect query performance.
-4. This statement directly deletes data. The deleted data cannot be recovered.
-5. The table on which you perform this operation must be in the NORMAL state. For example, you cannot perform TRUNCATE TABLE on a table with SCHEMA CHANGE going on.
-
-## Examples
-
-1. Truncate table `tbl` under `example_db`.
-
-    ```sql
-    TRUNCATE TABLE example_db.tbl;
-    ```
-
-2. Truncate partitions `p1` and `p2` in table `tbl`.
-
-    ```sql
-    TRUNCATE TABLE tbl PARTITION(p1, p2);
-    ```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/USE.md b/docs/en/sql-reference/sql-statements/data-definition/USE.md
deleted file mode 100644
index 6510976983bea3..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/USE.md
+++ /dev/null
@@ -1,48 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# USE
-
-## Description
-
-Specifies the active database for your session. You can then perform operations, such as creating tables and executing queries.
-
-## Syntax
-
-```SQL
-USE [<catalog_name>.]<db_name>
-```
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                              |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| catalog_name  | No           | The catalog name.<ul><li>If this parameter is not specified, a database in `default_catalog` is used by default.</li><li>You must specify this parameter when you use a database from an external catalog. For more information, see Example 2.</li><li>You must specify this parameter when you switch databases between different catalogs. For more information, see Example 3.</li></ul>For more information about catalogs, see [Overview](../../../data_source/catalog/catalog_overview.md). |
-| db_name       | Yes          | The database name. The database must exist.                  |
-
-## Examples
-
-Example 1: Use `example_db` from `default_catalog` as the active database of your session.
-
-```SQL
-USE default_catalog.example_db;
-```
-
-Or
-
-```SQL
-USE example_db;
-```
-
-Example 2: Use `example_db` from `hive_catalog` as the active database of your session.
-
-```SQL
-USE hive_catalog.example_db;
-```
-
-Example 3: Switch the active database of your session from `hive_catalog.example_table1` to `iceberg_catalog.example_table2`.
-
-```SQL
-USE iceberg_catalog.example_table2;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/BACKUP.md b/docs/en/sql-reference/sql-statements/data-definition/backup_restore/BACKUP.md
deleted file mode 100644
index f4b45b72f7257c..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/BACKUP.md
+++ /dev/null
@@ -1,83 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# BACKUP
-
-## Description
-
-Backs up data in a specified database, table, or partition. Currently, StarRocks only supports backing up data in OLAP tables.
-
-BACKUP is an asynchronous operation. You can check the status of a BACKUP job status using [SHOW BACKUP](../../data-manipulation/backup_restore/SHOW_BACKUP.md), or cancel a BACKUP job using [CANCEL BACKUP](../../data-definition/backup_restore/CANCEL_BACKUP.md). You can view the snapshot information using [SHOW SNAPSHOT](../../data-manipulation/backup_restore/SHOW_SNAPSHOT.md).
-
-> **CAUTION**
->
-> - Only users with the ADMIN privilege can back up data.
-> - In each database, only one running BACKUP or RESTORE job is allowed each time. Otherwise, StarRocks returns an error.
-> - StarRocks does not support specifying data compression algorithm for data backup.
-
-## Syntax
-
-```SQL
-BACKUP SNAPSHOT <db_name>.<snapshot_name>
-TO <repository_name>
-[ ON ( <table_name> [ PARTITION ( <partition_name> [, ...] ) ]
-       [, ...] ) ]
-[ PROPERTIES ("key"="value" [, ...] ) ]
-```
-
-## Parameters
-
-| **Parameter**   | **Description**                                              |
-| --------------- | ------------------------------------------------------------ |
-| db_name         | Name of the database that stores the data to be backed up.   |
-| snapshot_name   | Specify a name for the data snapshot. Globally unique.       |
-| repository_name | Repository name. You can create a repository using [CREATE REPOSITORY](../../data-definition/backup_restore/CREATE_REPOSITORY.md). |
-| ON              | Name of the tables to be backed up. The whole database is backed up if this parameter is not specified. |
-| PARTITION       | Name of the partitions to be backed up. The whole table is backed up if this parameter is not specified. |
-| PROPERTIES      | Properties of the data snapshot. Valid keys:`type`: Backup type. Currently, only full backup `FULL` is supported. Default: `FULL`.`timeout`: Task timeout. Unit: second. Default: `86400`. |
-
-## Examples
-
-Example 1: Backs up the database `example_db` to the repository `example_repo`.
-
-```SQL
-BACKUP SNAPSHOT example_db.snapshot_label1
-TO example_repo
-PROPERTIES ("type" = "full");
-```
-
-Example 2: Backs up the table `example_tbl` in `example_db` to `example_repo`.
-
-```SQL
-BACKUP SNAPSHOT example_db.snapshot_label2
-TO example_repo
-ON (example_tbl);
-```
-
-Example 2: Backs up the partitions `p1` and `p2` of `example_tbl` and the table `example_tbl2` in `example_db` to `example_repo`.
-
-```SQL
-BACKUP SNAPSHOT example_db.snapshot_label3
-TO example_repo
-ON(
-    example_tbl PARTITION (p1, p2),
-    example_tbl2
-);
-```
-
-## Usage notes
-
-- Performing backup and restore operations on global, database, table, and partition levels requires different privileges.
-- In each database, only one running BACKUP or RESTORE job is allowed each time. Otherwise, StarRocks returns an error.
-- Because BACKUP and RESTORE jobs occupy many resources of your StarRocks cluster, you can back up and restore your data while your StarRocks cluster is not heavily loaded.
-- StarRocks does not support specifying data compression algorithms for data backup.
-- Because data is backed up as snapshots, the data loaded upon snapshot generation is not included in the snapshot. Therefore, if you load data into the old cluster after the snapshot is generated and before the RESTORE job is completed, you also need to load the data into the cluster that data is restored into. It is recommended that you load data into both clusters in parallel for a period of time after the data migration is complete, and then migrate your application to the new cluster after verifying the correctness of the data and services.
-- Before the RESTORE job is completed, you cannot operate the table to be restored.
-- Primary Key tables cannot be restored to a StarRocks cluster earlier than v2.5.
-- You do not need to create the table to be restored in the new cluster before restoring it. The RESTORE job automatically creates it.
-- If there is an existing table that has a duplicated name with the table to be restored, StarRocks first checks whether or not the schema of the existing table matches that of the table to be restored. If the schemas match, StarRocks overwrites the existing table with the data in the snapshot. If the schema does not match, the RESTORE job fails. You can either rename the table to be restored using the keyword `AS`, or delete the existing table before restoring data.
-- If the RESTORE job overwrites an existing database, table, or partition, the overwritten data cannot be restored after the job enters the COMMIT phase. If the RESTORE job fails or is canceled at this point, the data may be corrupted and inaccessible. In this case, you can only perform the RESTORE operation again and wait for the job to complete. Therefore, we recommend that you do not restore data by overwriting unless you are sure that the current data is no longer used. The overwrite operation first checks metadata consistency between the snapshot and the existing database, table, or partition. If an inconsistency is detected, the RESTORE operation cannot be performed.
-- Currently, StarRocks does not support backing up and restoring logical views.
-- Currently, StarRocks does not support backing up and restoring the configuration data related to user accounts, privileges, and resource groups.
-- Currently, StarRocks does not support backing up and restoring the Colocate Join relationship among tables.
diff --git a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/CANCEL_BACKUP.md b/docs/en/sql-reference/sql-statements/data-definition/backup_restore/CANCEL_BACKUP.md
deleted file mode 100644
index a1bb0a1b2fdc35..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/CANCEL_BACKUP.md
+++ /dev/null
@@ -1,29 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CANCEL BACKUP
-
-## Description
-
-Cancels an ongoing BACKUP task in a specified database.
-
-## Syntax
-
-```SQL
-CANCEL BACKUP FROM <db_name>
-```
-
-## Parameters
-
-| **Parameter** | **Description**                                       |
-| ------------- | ----------------------------------------------------- |
-| db_name       | Name of the database that the BACKUP task belongs to. |
-
-## Examples
-
-Example 1: Cancels the BACKUP task under the database `example_db`.
-
-```SQL
-CANCEL BACKUP FROM example_db;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/CANCEL_RESTORE.md b/docs/en/sql-reference/sql-statements/data-definition/backup_restore/CANCEL_RESTORE.md
deleted file mode 100644
index beb92e47be0261..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/CANCEL_RESTORE.md
+++ /dev/null
@@ -1,33 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CANCEL RESTORE
-
-## Description
-
-Cancels an ongoing RESTORE task in a specified database.
-
-> **CAUTION**
->
-> If a RESTORE task is canceled during the COMMIT phase, the restored data will be corrupted and inaccessible. In this case, you can only perform the RESTORE operation again and wait for the job to complete.
-
-## Syntax
-
-```SQL
-CANCEL RESTORE FROM <db_name>
-```
-
-## Parameters
-
-| **Parameter** | **Description**                                        |
-| ------------- | ------------------------------------------------------ |
-| db_name       | Name of the database that the RESTORE task belongs to. |
-
-## Examples
-
-Example 1: Cancels the RESTORE task under the database `example_db`.
-
-```SQL
-CANCEL RESTORE FROM example_db;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/CREATE_REPOSITORY.md b/docs/en/sql-reference/sql-statements/data-definition/backup_restore/CREATE_REPOSITORY.md
deleted file mode 100644
index 46522558458fc1..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/CREATE_REPOSITORY.md
+++ /dev/null
@@ -1,107 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE REPOSITORY
-
-## Description
-
-Creates a repository in a remote storage system that is used to store data snapshots for backing up and restoring data.
-
-> **CAUTION**
->
-> Only users with the ADMIN privilege can create a repository.
-
-For detailed instructions on deleting a repository, see [DROP REPOSITORY](../../data-definition/backup_restore/DROP_REPOSITORY.md).
-
-## Syntax
-
-```SQL
-CREATE [READ ONLY] REPOSITORY <repository_name>
-WITH BROKER
-ON LOCATION "<repository_location>"
-PROPERTIES ("key"="value", ...)
-```
-
-## Parameters
-
-| **Parameter**       | **Description**                                              |
-| ------------------- | ------------------------------------------------------------ |
-| READ ONLY           | Create a read-only repository. Note that you can only restore data from a read-only repository. When creating the same repository for two clusters to migrate data, you can create a read-only repository for the new cluster and only grant it RESTORE permissions.|
-| repository_name     | Repository name. For the naming conventions, see [System limits](../../../../reference/System_limit.md).                           |
-| repository_location | Location of the repository in the remote storage system.     |
-| PROPERTIES          |The credential method for accessing the remote storage system. |
-
-**PROPERTIES**:
-
-StarRocks supports creating repositories in HDFS, AWS S3, and Google GCS.
-
-- For HDFS:
-  - "username": The username of the account that you want to use to access the NameNode of the HDFS cluster.
-  - "password": The password of the account that you want to use to access the NameNode of the HDFS cluster.
-
-- For AWS S3:
-  - "aws.s3.use_instance_profile": Whether or not to allow instance profile and assumed role as credential methods for accessing AWS S3. Default: `false`.
-
-    - If you use IAM user-based credential (Access Key and Secret Key) to access AWS S3, you don't need to specify this parameter, and you need to specify "aws.s3.access_key", "aws.s3.secret_key", and "aws.s3.endpoint".
-    - If you use Instance Profile to access AWS S3, you need to set this parameter to `true` and specify "aws.s3.region".
-    - If you use Assumed Role to access AWS S3, you need to set this parameter to `true` and specify "aws.s3.iam_role_arn" and "aws.s3.region".
-  
-  - "aws.s3.access_key": The Access Key ID that you can use to access the Amazon S3 bucket.
-  - "aws.s3.secret_key": The Secret Access Key that you can use to access the Amazon S3 bucket.
-  - "aws.s3.endpoint": The endpoint that you can use to access the Amazon S3 bucket.
-  - "aws.s3.iam_role_arn": The ARN of the IAM role that has privileges on the AWS S3 bucket in which your data files are stored. If you want to use assumed role as the credential method for accessing AWS S3, you must specify this parameter. Then, StarRocks will assume this role when it analyzes your Hive data by using a Hive catalog.
-  - "aws.s3.region": The region in which your AWS S3 bucket resides. Example: `us-west-1`.
-
-> **NOTE**
->
-> StarRocks supports creating repositories in AWS S3 only according to the S3A protocol. Therefore, when you create repositories in AWS S3, you must replace `s3://` in the S3 URI you pass as a repository location in `ON LOCATION` with `s3a://`.
-
-- For Google GCS:
-  - "fs.s3a.access.key": The Access Key that you can use to access the Google GCS bucket.
-  - "fs.s3a.secret.key": The Secret Key that you can use to access the Google GCS bucket.
-  - "fs.s3a.endpoint": The endpoint that you can use to access the Google GCS bucket.
-
-> **NOTE**
->
-> StarRocks supports creating repositories in Google GCS only according to the S3A protocol. Therefore, when you create repositories in Google GCS, you must replace the prefix in the GCS URI you pass as a repository location in `ON LOCATION` with `s3a://`.
-
-## Examples
-
-Example 1: Create a repository named `hdfs_repo` in an Apache™ Hadoop® cluster.
-
-```SQL
-CREATE REPOSITORY hdfs_repo
-WITH BROKER
-ON LOCATION "hdfs://x.x.x.x:yyyy/repo_dir/backup"
-PROPERTIES(
-    "username" = "xxxxxxxx",
-    "password" = "yyyyyyyy"
-);
-```
-
-Example 2: Create a read-only repository named `s3_repo` in the Amazon S3 bucket `bucket_s3`.
-
-```SQL
-CREATE READ ONLY REPOSITORY s3_repo
-WITH BROKER
-ON LOCATION "s3a://bucket_s3/backup"
-PROPERTIES(
-    "aws.s3.access_key" = "XXXXXXXXXXXXXXXXX",
-    "aws.s3.secret_key" = "yyyyyyyyyyyyyyyyy",
-    "aws.s3.endpoint" = "s3.us-east-1.amazonaws.com"
-);
-```
-
-Example 3: Create a repository named `gcs_repo` in the Google GCS bucket `bucket_gcs`.
-
-```SQL
-CREATE REPOSITORY gcs_repo
-WITH BROKER
-ON LOCATION "s3a://bucket_gcs/backup"
-PROPERTIES(
-    "fs.s3a.access.key" = "xxxxxxxxxxxxxxxxxxxx",
-    "fs.s3a.secret.key" = "yyyyyyyyyyyyyyyyyyyy",
-    "fs.s3a.endpoint" = "storage.googleapis.com"
-);
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/DROP_REPOSITORY.md b/docs/en/sql-reference/sql-statements/data-definition/backup_restore/DROP_REPOSITORY.md
deleted file mode 100644
index 406b2605501a9f..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/DROP_REPOSITORY.md
+++ /dev/null
@@ -1,34 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP REPOSITORY
-
-## Description
-
-Deletes a repository. Repositories are used to store data snapshots for data backup and restoration.
-
-> **CAUTION**
->
-> - Only root user and superuser can delete a repository.
-> - This operation only deletes the mapping of the repository in StarRocks, and does not delete the actual data. You need to delete it manually in the remote storage system. After deletion, you can map to that repository again by specifying the same remote storage system path.
-
-## Syntax
-
-```SQL
-DROP REPOSITORY <repository_name>
-```
-
-## Parameters
-
-| **Parameter**   | **Description**                       |
-| --------------- | ------------------------------------- |
-| repository_name | Name of the repository to be deleted. |
-
-## Example
-
-Example 1: deletes a repository named `oss_repo`.
-
-```SQL
-DROP REPOSITORY `oss_repo`;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/RECOVER.md b/docs/en/sql-reference/sql-statements/data-definition/backup_restore/RECOVER.md
deleted file mode 100644
index 12d90e55457be1..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/RECOVER.md
+++ /dev/null
@@ -1,56 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# RECOVER
-
-## Description
-
-Recovers a database, table, or partition that was dropped by using the DROP command. The dropped database, table, or partition can be recovered within the period specified by the FE parameter `catalog_trash_expire_second` (1 day by default).
-
-Data deleted by using [TRUNCATE TABLE](../TRUNCATE_TABLE.md) cannot be recovered.
-
-## Syntax
-
-1. Recover a database.
-
-    ```sql
-    RECOVER DATABASE <db_name>
-    ```
-
-2. Recover a table.
-
-    ```sql
-    RECOVER TABLE [<db_name>.]<table_name>
-    ```
-
-3. Recover a partition.
-
-    ```sql
-    RECOVER PARTITION <partition_name> FROM [<db_name>.]<table_name>
-    ```
-
-Note:
-
-1. This command can only recover metadata deleted some time ago (1 day by default). You can change the duration by adjusting the FE parameter `catalog_trash_expire_second`.
-2. If the metadata is deleted with identical metadata created, the previous one will not be recovered.
-
-## Examples
-
-1. Recover database `example_db`.
-
-    ```sql
-    RECOVER DATABASE example_db;
-    ```
-
-2. Recover table `example_tbl`.
-
-    ```sql
-    RECOVER TABLE example_db.example_tbl;
-    ```
-
-3. Recover partition `p1` in the `example_tbl` table.
-
-    ```sql
-    RECOVER PARTITION p1 FROM example_tbl;
-    ```
diff --git a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/RESTORE.md b/docs/en/sql-reference/sql-statements/data-definition/backup_restore/RESTORE.md
deleted file mode 100644
index ca50c57c0c32e4..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/RESTORE.md
+++ /dev/null
@@ -1,83 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# RESTORE
-
-## Description
-
-Restores data to a specified database, table, or partition. Currently, StarRocks only supports restoring data to OLAP tables.
-
-RESTORE is an asynchronous operation. You can check the status of a RESTORE job using [SHOW RESTORE](../../data-manipulation/backup_restore/SHOW_RESTORE.md), or cancel a RESTORE job using [CANCEL RESTORE](../../data-definition/backup_restore/CANCEL_RESTORE.md).
-
-> **CAUTION**
->
-> - Only users with the ADMIN privilege can restore data.
-> - In each database, only one running BACKUP or RESTORE job is allowed each time. Otherwise, StarRocks returns an error.
-
-## Syntax
-
-```SQL
-RESTORE SNAPSHOT <db_name>.<snapshot_name>
-FROM <repository_name>
-[ ON ( <table_name> [ PARTITION ( <partition_name> [, ...] ) ]
-    [ AS <table_alias>] [, ...] ) ]
-PROPERTIES ("key"="value", ...)
-```
-
-## Parameters
-
-| **Parameter**   | **Description**                                              |
-| --------------- | ------------------------------------------------------------ |
-| db_name         | Name of the database that the data is restored to.           |
-| snapshot_name   | Name for the data snapshot.                                  |
-| repository_name | Repository name.                                             |
-| ON              | Name of the tables to restore. The whole database is restored if this parameter is not specified. |
-| PARTITION       | Name of the partitions to be restored. The whole table is restored if this parameter is not specified. You can view the partition name using [SHOW PARTITIONS](../../data-manipulation/SHOW_PARTITIONS.md). |
-| PROPERTIES      | Properties of the RESTORE operation. Valid keys:<ul><li>`backup_timestamp`: Backup timestamp. **Required**. You can view backup timestamps using [SHOW SNAPSHOT](../../data-manipulation/backup_restore/SHOW_SNAPSHOT.md).</li><li>`replication_num`: Specify the number of replicas to be restored. Default: `3`.</li><li>`meta_version`: This parameter is only used as a temporary solution to restore the data backed up by the earlier version of StarRocks. The latest version of the backed up data already contains `meta version`, and you do not need to specify it.</li><li>`timeout`: Task timeout. Unit: second. Default: `86400`.</li></ul> |
-
-## Examples
-
-Example 1: Restores the table `backup_tbl` in the snapshot `snapshot_label1` from the `example_repo` repository to the database `example_db`, and the backup timestamp is `2018-05-04-16-45-08`. Restores one replica.
-
-```SQL
-RESTORE SNAPSHOT example_db.snapshot_label1
-FROM example_repo
-ON ( backup_tbl )
-PROPERTIES
-(
-    "backup_timestamp"="2018-05-04-16-45-08",
-    "replication_num" = "1"
-);
-```
-
-Example 2: Restores partitions `p1` and `p2` of table `backup_tbl` in `snapshot_label2` and table `backup_tbl2` from `example_repo` to database `example_db`, and rename `backup_tbl2` to `new_tbl`. The backup timestamp is `2018-05-04-17-11-01`. Restores three replicas by default.
-
-```SQL
-RESTORE SNAPSHOT example_db.snapshot_label2
-FROM example_repo
-ON(
-    backup_tbl PARTITION (p1, p2),
-    backup_tbl2 AS new_tbl
-)
-PROPERTIES
-(
-    "backup_timestamp"="2018-05-04-17-11-01"
-);
-```
-
-## Usage notes
-
-- Performing backup and restore operations on global, database, table, and partition levels requires different privileges.
-- In each database, only one running BACKUP or RESTORE job is allowed each time. Otherwise, StarRocks returns an error.
-- Because BACKUP and RESTORE jobs occupy many resources of your StarRocks cluster, you can back up and restore your data while your StarRocks cluster is not heavily loaded.
-- StarRocks does not support specifying data compression algorithms for data backup.
-- Because data is backed up as snapshots, the data loaded upon snapshot generation is not included in the snapshot. Therefore, if you load data into the old cluster after the snapshot is generated and before the RESTORE job is completed, you also need to load the data into the cluster that data is restored into. It is recommended that you load data into both clusters in parallel for a period of time after the data migration is complete, and then migrate your application to the new cluster after verifying the correctness of the data and services.
-- Before the RESTORE job is completed, you cannot operate the table to be restored.
-- Primary Key tables cannot be restored to a StarRocks cluster earlier than v2.5.
-- You do not need to create the table to be restored in the new cluster before restoring it. The RESTORE job automatically creates it.
-- If there is an existing table that has a duplicated name with the table to be restored, StarRocks first checks whether or not the schema of the existing table matches that of the table to be restored. If the schemas match, StarRocks overwrites the existing table with the data in the snapshot. If the schema does not match, the RESTORE job fails. You can either rename the table to be restored using the keyword `AS`, or delete the existing table before restoring data.
-- If the RESTORE job overwrites an existing database, table, or partition, the overwritten data cannot be restored after the job enters the COMMIT phase. If the RESTORE job fails or is canceled at this point, the data may be corrupted and inaccessible. In this case, you can only perform the RESTORE operation again and wait for the job to complete. Therefore, we recommend that you do not restore data by overwriting unless you are sure that the current data is no longer used. The overwrite operation first checks metadata consistency between the snapshot and the existing database, table, or partition. If an inconsistency is detected, the RESTORE operation cannot be performed.
-- Currently, StarRocks does not support backing up and restoring logical views.
-- Currently, StarRocks does not support backing up and restoring the configuration data related to user accounts, privileges, and resource groups.
-- Currently, StarRocks does not support backing up and restoring the Colocate Join relationship among tables.
diff --git a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/backup_restore.mdx b/docs/en/sql-reference/sql-statements/data-definition/backup_restore/backup_restore.mdx
deleted file mode 100644
index b38cc2e13e92c1..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-definition/backup_restore/backup_restore.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# Backup and restore
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/ALTER_LOAD.md b/docs/en/sql-reference/sql-statements/data-manipulation/ALTER_LOAD.md
deleted file mode 100644
index 4defb6e37367b8..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/ALTER_LOAD.md
+++ /dev/null
@@ -1,42 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ALTER LOAD
-
-## Description
-
-Changes the priority of a Broker Load job that is in the **QUEUEING** or **LOADING** state. This statement is supported since v2.5.
-
-> **NOTE**
->
-> Changing the priority of a Broker Load job that is in the **LOADING** state does not affect the execution of the job.
-
-## Syntax
-
-```SQL
-ALTER LOAD FOR <label_name>
-PROPERTIES
-(
-    'priority'='{LOWEST | LOW | NORMAL | HIGH | HIGHEST}'
-)
-```
-
-## Parameters
-
-| **Parameter** | **Required** | Description                                                  |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| label_name    | Yes          | The label of the load job. Format: `[<database_name>.]<label_name>`. See [BROKER LOAD](../data-manipulation/BROKER_LOAD.md#database_name-and-label_name). |
-| priority      | Yes          | The new priority that you want to specify for the load job. Valid values: `LOWEST`, `LOW`, `NORMAL`, `HIGH`, and `HIGHEST`. See [BROKER LOAD](../data-manipulation/BROKER_LOAD.md). |
-
-## Examples
-
-Suppose that you have a Broker Load job whose label is `test_db.label1` and the job is in the **QUEUEING** state. If you want to run the job at the soonest, you can run the following command to change the priority of the job to `HIGHEST`:
-
-```SQL
-ALTER LOAD FOR test_db.label1
-PROPERTIES
-(
-    'priority'='HIGHEST'
-);
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/ALTER_PIPE.md b/docs/en/sql-reference/sql-statements/data-manipulation/ALTER_PIPE.md
deleted file mode 100644
index 6f224ead90dccf..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/ALTER_PIPE.md
+++ /dev/null
@@ -1,54 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ALTER PIPE
-
-## Description
-
-Alters the settings of the properties of a pipe. This command is supported from v3.2 onwards.
-
-## Syntax
-
-```SQL
-ALTER PIPE [db_name.]<pipe_name> 
-SET PROPERTY
-(
-    "<key>" = <value>[, "<key>" = "<value>" ...]
-) 
-```
-
-## Parameters
-
-### db_name
-
-The name of the database to which the pipe belongs.
-
-### pipe_name
-
-The name of the pipe.
-
-### PROPERTIES
-
-The properties whose settings you want to alter for the pipe. Format: `"key" = "value"`. For more information about the properties supported, see [CREATE PIPE](../../../sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md).
-
-## Examples
-
-Change the setting of the `AUTO_INGEST` property to `FALSE` for the pipe named `user_behavior_replica` in the database named `mydatabase`:
-
-```SQL
-USE mydatabase;
-ALTER PIPE user_behavior_replica
-SET
-(
-    "AUTO_INGEST" = "FALSE"
-);
-```
-
-## References
-
-- [CREATE PIPE](../data-manipulation/CREATE_PIPE.md)
-- [DROP PIPE](../data-manipulation/DROP_PIPE.md)
-- [SHOW PIPES](../data-manipulation/SHOW_PIPES.md)
-- [SUSPEND or RESUME PIPE](../data-manipulation/SUSPEND_or_RESUME_PIPE.md)
-- [RETRY FILE](../data-manipulation/RETRY_FILE.md)
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD.md b/docs/en/sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD.md
deleted file mode 100644
index 17ec841430e6cc..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD.md
+++ /dev/null
@@ -1,128 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# ALTER ROUTINE LOAD
-
-import RoutineLoadPrivNote from '../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
-
-## Description
-
-Alters a Routine Load job that is in the `PAUSED` state. You can execute PAUSE ROUTINE LOAD to pause a Routine Load job.
-
-After successfully altering a Routine Load job, you can:
-
-- Check the modifications made to the Routine Load job by using [SHOW ROUTINE LOAD](./SHOW_ROUTINE_LOAD.md).
-- Resume the Routine Load job by using [RESUME ROUTINE LOAD](./RESUME_ROUTINE_LOAD.md).
-
-<RoutineLoadPrivNote />
-
-## Syntax
-
-```SQL
-ALTER ROUTINE LOAD FOR [<db_name>.]<job_name>
-[load_properties]
-[job_properties]
-FROM data_source
-[data_source_properties]
-```
-
-## Parameters
-
-- **`[<db_name>.]<job_name>`**
-  - **`db_name`**: Optional. The name of the StarRocks database.
-  - **`job_name`:** Required. The name of the Routine Load job to be altered.
-- **`load_properties`**
-
-   The properties of the source data to be loaded. The syntax is as follows:
-
-   ```SQL
-   [COLUMNS TERMINATED BY '<column_separator>'],
-   [ROWS TERMINATED BY '<row_separator>'],
-   [COLUMNS ([<column_name> [, ...] ] [, column_assignment [, ...] ] )],
-   [WHERE <expr>],
-   [PARTITION ([ <partition_name> [, ...] ])]
-   [TEMPORARY PARTITION (<temporary_partition1_name>[,<temporary_partition2_name>,...])]
-   ```
-
-   For detailed parameter descriptions, see [CREATE ROUTINE LOAD](./CREATE_ROUTINE_LOAD.md#load_properties).
-
-- **`job_properties`**
-
-  The properties of the load job. The syntax is as follows:
-
-  ```SQL
-  PROPERTIES ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
-  ```
-
-  Only the following parameters can be altered:
-
-  - `desired_concurrent_number`
-
-  - `max_error_number`
-
-  - `max_batch_interval`
-
-  - `max_batch_rows`
-
-  - `max_batch_size`
-
-  - `jsonpaths`
-
-  - `json_root`
-
-  - `strip_outer_array`
-
-  - `strict_mode`
-
-  - `timezone`
-
-  For detailed parameter descriptions, see [CREATE ROUTINE LOAD](./CREATE_ROUTINE_LOAD.md#job_properties).
-
-- **`data_source`** **and** **`data_source_properties`**
-
-  - **`data_source`**
-
-    Required. The source of the data you want to load. Valid value: `KAFKA`.
-
-  - **`data_source_properties`**
-
-    The properties of the data source. Currently, only the following properties can be altered:
-    - `kafka_partitions` and `kafka_offsets`: Note that StarRocks only supports modifying the offset of Kafka partitions that have already been consumed but does not support adding new Kafka partitions.
-    - `property.*`: Custom parameters for the data source Kafka, such as `property.kafka_default_offsets`.
-
-## Examples
-
-1. The following example increases the value of the property `desired_concurrent_number` of the load job to `5` in order to increase the parallelism of load tasks. For details on task parallelism, see [how to improve load performance](../../../faq/loading/Routine_load_faq.md#how-can-i-improve-loading-performance).
-
-   ```SQL
-   ALTER ROUTINE LOAD FOR example_tbl_ordertest
-   PROPERTIES
-   (
-   "desired_concurrent_number" = "5"
-   );
-   ```
-
-2. The following example alters the load job's properties and data source information at the same time.
-
-   ```SQL
-   ALTER ROUTINE LOAD FOR example_tbl_ordertest
-   PROPERTIES
-   (
-   "desired_concurrent_number" = "5"
-   )
-   FROM KAFKA
-   (
-   "kafka_partitions" = "0, 1, 2",
-   "kafka_offsets" = "100, 200, 100",
-   "property.group.id" = "new_group"
-   );
-   ```
-
-3. The following example alters the filtering condition and the StarRocks partitions that data is loaded into at the same time.
-
-   ```SQL
-   ALTER ROUTINE LOAD FOR example_tbl_ordertest
-   WHERE pay_dt < 2023-06-31
-   PARTITION (p202306);
-   ```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md b/docs/en/sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md
deleted file mode 100644
index 8434667b8030be..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md
+++ /dev/null
@@ -1,1294 +0,0 @@
----
-displayed_sidebar: "English"
-toc_max_heading_level: 5
----
-
-# BROKER LOAD
-
-import InsertPrivNote from '../../../_assets/commonMarkdown/insertPrivNote.md'
-
-## Description
-
-StarRocks provides the MySQL-based loading method Broker Load. After you submit a load job, StarRocks asynchronously runs the job. You can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information about the background information, principles, supported data file formats, how to perform single-table loads and multi-table loads, and how to view job results, see [Load data from HDFS](../../../loading/hdfs_load.md) and [Load data from cloud storage](../../../loading/cloud_storage_load.md).
-
-<InsertPrivNote />
-
-## Syntax
-
-```SQL
-LOAD LABEL [<database_name>.]<label_name>
-(
-    data_desc[, data_desc ...]
-)
-WITH BROKER
-(
-    StorageCredentialParams
-)
-[PROPERTIES
-(
-    opt_properties
-)
-]
-```
-
-Note that in StarRocks some literals are used as reserved keywords by the SQL language. Do not directly use these keywords in SQL statements. If you want to use such a keyword in an SQL statement, enclose it in a pair of backticks (`). See [Keywords](../../../sql-reference/sql-statements/keywords.md).
-
-## Parameters
-
-### database_name and label_name
-
-`label_name` specifies the label of the load job. For the naming conventions, see [System limits](../../../reference/System_limit.md).
-
-`database_name` optionally specifies the name of the database to which the destination table belongs.
-
-Each load job has a label that is unique across the entire database. You can use the label of a load job to view the execution status of the load job and prevent repeatedly loading the same data. When a load job enters the **FINISHED** state, its label cannot be reused. Only the label of a load job that has entered the **CANCELLED** state can be reused. In most cases, the label of a load job is reused to retry that load job and load the same data, thereby implementing Exactly-Once semantics.
-
-For label naming conventions, see [System limits](../../../reference/System_limit.md).
-
-### data_desc
-
-The description of a batch of data to be loaded. Each `data_desc` descriptor declares information such as the data source, ETL functions, destination StarRocks table, and destination partitions.
-
-Broker Load supports loading multiple data files at a time. In one load job, you can use multiple `data_desc` descriptors to declare multiple data files you want to load, or use one `data_desc` descriptor to declare one file path from which you want to load all data files in it. Broker Load can also ensure the transactional atomicity of each load job that is run to load multiple data files. Atomicity means that the loading of multiple data files in one load job must all succeed or fail. It never happens that the loading of some data files succeeds while the loading of the other files fails.
-
-`data_desc` supports the following syntax:
-
-```SQL
-DATA INFILE ("<file_path>"[, "<file_path>" ...])
-[NEGATIVE]
-INTO TABLE <table_name>
-[PARTITION (<partition1_name>[, <partition2_name> ...])]
-[TEMPORARY PARTITION (<temporary_partition1_name>[, <temporary_partition2_name> ...])]
-[COLUMNS TERMINATED BY "<column_separator>"]
-[ROWS TERMINATED BY "<row_separator>"]
-[FORMAT AS "CSV | Parquet | ORC"]
-[(format_type_options)]
-[(column_list)]
-[COLUMNS FROM PATH AS (<partition_field_name>[, <partition_field_name> ...])]
-[SET <k1=f1(v1)>[, <k2=f2(v2)> ...]]
-[WHERE predicate]
-```
-
-`data_desc` must include the following parameters:
-
-- `file_path`
-
-  Specifies the save path of one or more data files you want to load.
-
-  You can specify this parameter as the save path of one data file. For example, you can specify this parameter as `"hdfs://<hdfs_host>:<hdfs_port>/user/data/tablename/20210411"` to load a data file named `20210411` from the path `/user/data/tablename` on the HDFS server.
-
-  You can also specify this parameter as the save path of multiple data files by using wildcards `?`, `*`, `[]`, `{}`, or `^`. See [Wildcard reference](https://hadoop.apache.org/docs/stable/api/org/apache/hadoop/fs/FileSystem.html#globStatus-org.apache.hadoop.fs.Path-). For example, you can specify this parameter as `"hdfs://<hdfs_host>:<hdfs_port>/user/data/tablename/*/*"` or `"hdfs://<hdfs_host>:<hdfs_port>/user/data/tablename/dt=202104*/*"` to load the data files from all partitions or only `202104` partitions in the path `/user/data/tablename` on the HDFS server.
-
-  > **NOTE**
-  >
-  > Wildcards can also be used to specify intermediate paths.
-
-  In the preceding examples, the `hdfs_host` and `hdfs_port` parameters are described as follows:
-
-  - `hdfs_host`: the IP address of the NameNode host in the HDFS cluster.
-
-  - `hdfs_host`: the FS port of the NameNode host in the HDFS cluster. The default port number is `9000`.
-
-  > **NOTICE**
-  >
-  > - Broker Load supports accessing AWS S3 according to the S3 or S3A protocol. Therefore, when you load data from AWS S3, you can include `s3://` or `s3a://` as the prefix in the S3 URI that you pass as the file path.
-  > - Broker Load supports accessing Google GCS only according to the gs protocol. Therefore, when you load data from Google GCS, you must include `gs://` as the prefix in the GCS URI that you pass as the file path.
-  > - When you load data from Blob Storage, you must use the wasb or wasbs protocol to access your data:
-  >   - If your storage account allows access over HTTP, use the wasb protocol and write the file path as `wasb://<container_name>@<storage_account_name>.blob.core.windows.net/<path>/<file_name>/*`.
-  >   - If your storage account allows access over HTTPS, use the wasbs protocol and write the file path as `wasbs://<container_name>@<storage_account_name>.blob.core.windows.net/<path>/<file_name>/*`.
-  > - When you load data from Data Lake Storage Gen2, you must use the abfs or abfss protocol to access your data:
-  >   - If your storage account allows access over HTTP, use the abfs protocol and write the file path as `abfs://<container_name>@<storage_account_name>.dfs.core.windows.net/<file_name>`.
-  >   - If your storage account allows access over HTTPS, use the abfss protocol and write the file path as `abfss://<container_name>@<storage_account_name>.dfs.core.windows.net/<file_name>`.
-  > - When you load data from Data Lake Storage Gen1, you must use the adl protocol to access your data and write the file path as `adl://<data_lake_storage_gen1_name>.azuredatalakestore.net/<path>/<file_name>`.
-
-- `INTO TABLE`
-
-  Specifies the name of the destination StarRocks table.
-
-`data_desc` can also optionally include the following parameters:
-
-- `NEGATIVE`
-
-  Revokes the loading of a specific batch of data. To achieve this, you need to load the same batch of data with the `NEGATIVE` keyword specified.
-
-  > **NOTE**
-  >
-  > This parameter is valid only when the StarRocks table is an Aggregate table and all its value columns are computed by the `sum` function.
-
-- `PARTITION`
-
-   Specifies the partitions into which you want to load data. By default, if you do not specify this parameter, the source data will be loaded into all partitions of the StarRocks table.
-
-- `TEMPORARY PARTITION`
-
-  Specifies the name of the [temporary partition](../../../table_design/Temporary_partition.md) into which you want to load data. You can specify multiple temporary partitions, which must be separated by commas (,).
-
-- `COLUMNS TERMINATED BY`
-
-  Specifies the column separator used in the data file. By default, if you do not specify this parameter, this parameter defaults to `\t`, indicating tab. The column separator you specify using this parameter must be the same as the column separator that is actually used in the data file. Otherwise, the load job will fail due to inadequate data quality, and its `State` will be `CANCELLED`.
-
-  Broker Load jobs are submitted according to the MySQL protocol. StarRocks and MySQL both escape characters in the load requests. Therefore, if the column separator is an invisible character such as tab, you must add a backslash (\) preceding the column separator. For example, you must input `\\t` if the column separator is `\t`, and you must input `\\n` if the column separator is `\n`. Apache Hive™ files use `\x01` as their column separator, so you must input `\\x01` if the data file is from Hive.
-
-  > **NOTE**
-  >
-  > - For CSV data, you can use a UTF-8 string, such as a comma (,), tab, or pipe (|), whose length does not exceed 50 bytes as a text delimiter.
-  > - Null values are denoted by using `\N`. For example, a data file consists of three columns, and a record from that data file holds data in the first and third columns but no data in the second column. In this situation, you need to use `\N` in the second column to denote a null value. This means the record must be compiled as `a,\N,b` instead of `a,,b`. `a,,b` denotes that the second column of the record holds an empty string.
-
-- `ROWS TERMINATED BY`
-
-  Specifies the row separator used in the data file. By default, if you do not specify this parameter, this parameter defaults to `\n`, indicating line break. The row separator you specify using this parameter must be the same as the row separator that is actually used in the data file. Otherwise, the load job will fail due to inadequate data quality, and its `State` will be `CANCELLED`. This parameter is supported from v2.5.4 onwards.
-
-  For the usage notes about the row separator, see the usage notes for the preceding `COLUMNS TERMINATED BY` parameter.
-
-- `FORMAT AS`
-
-  Specifies the format of the data file. Valid values: `CSV`, `Parquet`, and `ORC`. By default, if you do not specify this parameter, StarRocks determines the data file format based on the filename extension **.csv**, **.parquet**, or **.orc** specified in the `file_path` parameter.
-
-- `format_type_options`
-
-  Specifies CSV format options when `FORMAT AS` is set to `CSV`. Syntax:
-
-  ```JSON
-  (
-      key = value
-      key = value
-      ...
-  )
-  ```
-
-  > **NOTE**
-  >
-  > `format_type_options` is supported in v3.0 and later.
-
-  The following table describes the options.
-
-  | **Parameter** | **Description**                                              |
-  | ------------- | ------------------------------------------------------------ |
-  | skip_header   | Specifies whether to skip the first rows of the data file when the data file is in CSV format. Type: INTEGER. Default value: `0`.<br />In some CSV-formatted data files, the first rows at the beginning are used to define metadata such as column names and column data types. By setting the `skip_header` parameter, you can enable StarRocks to skip the first rows of the data file during data loading. For example, if you set this parameter to `1`, StarRocks skips the first row of the data file during data loading.<br />The first rows at the beginning in the data file must be separated by using the row separator that you specify in the load statement. |
-  | trim_space    | Specifies whether to remove spaces preceding and following column separators from the data file when the data file is in CSV format. Type: BOOLEAN. Default value: `false`.<br />For some databases, spaces are added to column separators when you export data as a CSV-formatted data file. Such spaces are called leading spaces or trailing spaces depending on their locations. By setting the `trim_space` parameter, you can enable StarRocks to remove such unnecessary spaces during data loading.<br />Note that StarRocks does not remove the spaces (including leading spaces and trailing spaces) within a field wrapped in a pair of `enclose`-specified characters. For example, the following field values use pipe (<code class="language-text">&#124;</code>) as the column separator and double quotation marks (`"`) as the `enclose`-specified character:<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124; "Love StarRocks" &#124;</code> <br />If you set `trim_space` to `true`, StarRocks processes the preceding field values as follows:<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> |
-  | enclose       | Specifies the character that is used to wrap the field values in the data file according to [RFC4180](https://www.rfc-editor.org/rfc/rfc4180) when the data file is in CSV format. Type: single-byte character. Default value: `NONE`. The most prevalent characters are single quotation mark (`'`) and double quotation mark (`"`).<br />All special characters (including row separators and column separators) wrapped by using the `enclose`-specified character are considered normal symbols. StarRocks can do more than RFC4180 as it allows you to specify any single-byte character as the `enclose`-specified character.<br />If a field value contains an `enclose`-specified character, you can use the same character to escape that `enclose`-specified character. For example, you set `enclose` to `"`, and a field value is `a "quoted" c`. In this case, you can enter the field value as `"a ""quoted"" c"` into the data file. |
-  | escape        | Specifies the character that is used to escape various special characters, such as row separators, column separators, escape characters, and `enclose`-specified characters, which are then considered by StarRocks to be common characters and are parsed as part of the field values in which they reside. Type: single-byte character. Default value: `NONE`. The most prevalent character is slash (`\`), which must be written as double slashes (`\\`) in SQL statements.<br />**NOTE**<br />The character specified by `escape` is applied to both inside and outside of each pair of `enclose`-specified characters.<br />Two examples are as follows:<ul><li>When you set `enclose` to `"` and `escape` to `\`, StarRocks parses `"say \"Hello world\""` into `say "Hello world"`.</li><li>Assume that the column separator is comma (`,`). When you set `escape` to `\`, StarRocks parses `a, b\, c` into two separate field values: `a` and `b, c`.</li></ul> |
-
-- `column_list`
-
-  Specifies the column mapping between the data file and the StarRocks table. Syntax: `(<column_name>[, <column_name> ...])`. The columns declared in `column_list` are mapped by name onto the StarRocks table columns.
-
-  > **NOTE**
-  >
-  > If the columns of the data file are mapped in sequence onto the columns of the StarRocks table, you do not need to specify `column_list`.
-
-  If you want to skip a specific column of the data file, you only need to temporarily name that column as different from any of the StarRocks table columns. For more information, see [Transform data at loading](../../../loading/Etl_in_loading.md).
-
-- `COLUMNS FROM PATH AS`
-
-  Extracts the information about one or more partition fields from the file path you specify. This parameter is valid only when the file path contains partition fields.
-
-  For example, if the data file is stored in the path `/path/col_name=col_value/file1` in which `col_name` is a partition field and can be mapped onto a column of the StarRocks table, you can specify this parameter as `col_name`. As such, StarRocks extracts `col_value` values from the path and loads them into the StarRocks table column onto which `col_name` is mapped.
-
-  > **NOTE**
-  >
-  > This parameter is available only when you load data from HDFS.
-
-- `SET`
-
-  Specifies one or more functions that you want to use to convert a column of the data file. Examples:
-
-  - The StarRocks table consists of three columns, which are `col1`, `col2`, and `col3` in sequence. The data file consists of four columns, among which the first two columns are mapped in sequence onto `col1` and `col2` of the StarRocks table and the sum of the last two columns is mapped onto `col3` of the StarRocks table. In this case, you need to specify `column_list` as `(col1,col2,tmp_col3,tmp_col4)` and specify `(col3=tmp_col3+tmp_col4)` in the SET clause to implement data conversion.
-  - The StarRocks table consists of three columns, which are `year`, `month`, and `day` in sequence. The data file consists of only one column that accommodates date and time values in `yyyy-mm-dd hh:mm:ss` format. In this case, you need to specify `column_list` as `(tmp_time)` and specify `(year = year(tmp_time), month=month(tmp_time), day=day(tmp_time))` in the SET clause to implement data conversion.
-
-- `WHERE`
-
-  Specifies the conditions based on which you want to filter the source data. StarRocks loads only the source data that meets the filter conditions specified in the WHERE clause.
-
-### WITH BROKER
-
-In v2.3 and earlier, input `WITH BROKER "<broker_name>"` to specify the broker you want to use. From v2.5 onwards, you no longer need to specify a broker, but you still need to retain the `WITH BROKER` keyword.
-
-### StorageCredentialParams
-
-The authentication information used by StarRocks to access your storage system.
-
-#### HDFS
-
-Open-source HDFS supports two authentication methods: simple authentication and Kerberos authentication. Broker Load uses simple authentication by default. Open-source HDFS also supports configuring an HA mechanism for the NameNode. If you choose open-source HDFS as your storage system, you can specify the authentication configuration and HA configuration as follows:
-
-- Authentication configuration
-
-  - If you use simple authentication, configure `StorageCredentialParams` as follows:
-
-    ```Plain
-    "hadoop.security.authentication" = "simple",
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-    ```
-
-    The following table describes the parameters in `StorageCredentialParams`.
-
-    | Parameter                       | Description                                                  |
-    | ------------------------------- | ------------------------------------------------------------ |
-    | hadoop.security.authentication  | The authentication method. Valid values: `simple` and `kerberos`. Default value: `simple`. `simple` represents simple authentication, meaning no authentication, and `kerberos` represents Kerberos authentication. |
-    | username                        | The username of the account that you want to use to access the NameNode of the HDFS cluster. |
-    | password                        | The password of the account that you want to use to access the NameNode of the HDFS cluster. |
-
-  - If you use Kerberos authentication, configure `StorageCredentialParams` as follows:
-
-    ```Plain
-    "hadoop.security.authentication" = "kerberos",
-    "kerberos_principal" = "nn/zelda1@ZELDA.COM",
-    "kerberos_keytab" = "/keytab/hive.keytab",
-    "kerberos_keytab_content" = "YWFhYWFh"
-    ```
-
-    The following table describes the parameters in `StorageCredentialParams`.
-
-    | Parameter                       | Description                                                  |
-    | ------------------------------- | ------------------------------------------------------------ |
-    | hadoop.security.authentication  | The authentication method. Valid values: `simple` and `kerberos`. Default value: `simple`. `simple` represents simple authentication, meaning no authentication, and `kerberos` represents Kerberos authentication. |
-    | kerberos_principal              | The Kerberos principal to be authenticated. Each principal consists of the following three parts to ensure that it is unique across the HDFS cluster:<ul><li>`username` or `servicename`: The name of the principal.</li><li>`instance`: the name of the server that hosts the node to be authenticated in the HDFS cluster. The server name helps ensure that the principal is unique, for example, when the HDFS cluster consists of multiple DataNodes that each are independently authenticated.</li><li>`realm`: The name of the realm. The realm name must be capitalized.</li></ul>Example: `nn/zelda1@ZELDA.COM`. |
-    | kerberos_keytab                 | The save path of the Kerberos keytab file. |
-    | kerberos_keytab_content         | The Base64-encoded content of the the Kerberos keytab file. You can choose to specify either `kerberos_keytab` or `kerberos_keytab_content`. |
-
-- HA configuration
-
-  You can configure an HA mechanism for the NameNode of the HDFS cluster. This way, if the NameNode is switched over to another node, StarRocks can automatically identify the new node that serves as the NameNode. This includes the following scenarios:
-
-  - If you load data from a single HDFS cluster that has one Kerberos user configured, both broker-based loading and broker-free loading are supported.
-  
-    - To perform broker-based loading, make sure that at least one independent broker group is deployed, and place the `hdfs-site.xml` file to the `{deploy}/conf` path on the broker node that serves the HDFS cluster. StarRocks will add the `{deploy}/conf` path to the environment variable `CLASSPATH` upon broker startup, allowing the brokers to read information about the HDFS cluster nodes.
-  
-    - To perform broker-free loading, place the `hdfs-site.xml` file to the `{deploy}/conf` paths of each FE node and each BE or CN node.
-  
-  - If you load data from a single HDFS cluster that has multiple Kerberos users configured, only broker-based loading is supported. Make sure that at least one independent broker group is deployed, and place the `hdfs-site.xml` file to the `{deploy}/conf` path on the broker node that serves the HDFS cluster. StarRocks will add the `{deploy}/conf` path to the environment variable `CLASSPATH` upon broker startup, allowing the brokers to read information about the HDFS cluster nodes.
-
-  - If you load data from multiple HDFS clusters (regardless of whether one or multiple Kerberos users are configured), only broker-based loading is supported. Make sure that at least one independent broker group is deployed for each of these HDFS clusters, and take one of the following actions to enable the brokers to read information about the HDFS cluster nodes:
-
-    - Place the `hdfs-site.xml` file to the `{deploy}/conf` path on the broker node that serves each HDFS cluster. StarRocks will add the `{deploy}/conf` path to the environment variable `CLASSPATH` upon broker startup, allowing the brokers to read information about the nodes in that HDFS cluster.
-
-    - Add the following HA configuration at job creation:
-
-      ```Plain
-      "dfs.nameservices" = "ha_cluster",
-      "dfs.ha.namenodes.ha_cluster" = "ha_n1,ha_n2",
-      "dfs.namenode.rpc-address.ha_cluster.ha_n1" = "<hdfs_host>:<hdfs_port>",
-      "dfs.namenode.rpc-address.ha_cluster.ha_n2" = "<hdfs_host>:<hdfs_port>",
-      "dfs.client.failover.proxy.provider" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
-      ```
-
-      The following table describes the parameters in the HA configuration.
-
-      | Parameter                          | Description                                                  |
-      | ---------------------------------- | ------------------------------------------------------------ |
-      | dfs.nameservices                   | The name of the HDFS cluster.                                |
-      | dfs.ha.namenodes.XXX               | The name of the NameNode in the HDFS cluster. If you specify multiple NameNode names, separate them with commas (`,`). `xxx` is the HDFS cluster name that you have specified in `dfs.nameservices`. |
-      | dfs.namenode.rpc-address.XXX.NN    | The RPC address of the NameNode in the HDFS cluster. `NN` is the NameNode name that you have specified in `dfs.ha.namenodes.XXX`. |
-      | dfs.client.failover.proxy.provider | The provider of the NameNode to which the client will connect. Default value: `org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider`. |
-
-  > **NOTE**
-  >
-  > You can use the [SHOW BROKER](../Administration/SHOW_BROKER.md) statement to check for brokers that are deployed in your StarRocks cluster.
-
-#### AWS S3
-
-If you choose AWS S3 as your storage system, take one of the following actions:
-
-- To choose the instance profile-based authentication method, configure `StorageCredentialParams` as follows:
-
-  ```SQL
-  "aws.s3.use_instance_profile" = "true",
-  "aws.s3.region" = "<aws_s3_region>"
-  ```
-
-- To choose the assumed role-based authentication method, configure `StorageCredentialParams` as follows:
-
-  ```SQL
-  "aws.s3.use_instance_profile" = "true",
-  "aws.s3.iam_role_arn" = "<iam_role_arn>",
-  "aws.s3.region" = "<aws_s3_region>"
-  ```
-
-- To choose the IAM user-based authentication method, configure `StorageCredentialParams` as follows:
-
-  ```SQL
-  "aws.s3.use_instance_profile" = "false",
-  "aws.s3.access_key" = "<iam_user_access_key>",
-  "aws.s3.secret_key" = "<iam_user_secret_key>",
-  "aws.s3.region" = "<aws_s3_region>"
-  ```
-
-The following table describes the parameters you need to configure in `StorageCredentialParams`.
-
-| Parameter                   | Required | Description                                                  |
-| --------------------------- | -------- | ------------------------------------------------------------ |
-| aws.s3.use_instance_profile | Yes      | Specifies whether to enable the credential methods instance profile and assumed role. Valid values: `true` and `false`. Default value: `false`. |
-| aws.s3.iam_role_arn         | No       | The ARN of the IAM role that has privileges on your AWS S3 bucket. If you choose assumed role as the credential method for accessing AWS S3, you must specify this parameter. |
-| aws.s3.region               | Yes      | The region in which your AWS S3 bucket resides. Example: `us-west-1`. |
-| aws.s3.access_key           | No       | The access key of your IAM user. If you choose IAM user as the credential method for accessing AWS S3, you must specify this parameter. |
-| aws.s3.secret_key           | No       | The secret key of your IAM user. If you choose IAM user as the credential method for accessing AWS S3, you must specify this parameter. |
-
-For information about how to choose an authentication method for accessing AWS S3 and how to configure an access control policy in AWS IAM Console, see [Authentication parameters for accessing AWS S3](../../../integrations/authenticate_to_aws_resources.md#authentication-parameters-for-accessing-aws-s3).
-
-#### Google GCS
-
-If you choose Google GCS as your storage system, take one of the following actions:
-
-- To choose the VM-based authentication method, configure `StorageCredentialParams` as follows:
-
-  ```SQL
-  "gcp.gcs.use_compute_engine_service_account" = "true"
-  ```
-
-  The following table describes the parameters you need to configure in `StorageCredentialParams`.
-
-  | **Parameter**                              | **Default value** | **Value** **example** | **Description**                                              |
-  | ------------------------------------------ | ----------------- | --------------------- | ------------------------------------------------------------ |
-  | gcp.gcs.use_compute_engine_service_account | false             | true                  | Specifies whether to directly use the service account that is bound to your Compute Engine. |
-
-- To choose the service account-based authentication method, configure `StorageCredentialParams` as follows:
-
-  ```SQL
-  "gcp.gcs.service_account_email" = "<google_service_account_email>",
-  "gcp.gcs.service_account_private_key_id" = "<google_service_private_key_id>",
-  "gcp.gcs.service_account_private_key" = "<google_service_private_key>"
-  ```
-
-  The following table describes the parameters you need to configure in `StorageCredentialParams`.
-
-  | **Parameter**                          | **Default value** | **Value** **example**                                        | **Description**                                              |
-  | -------------------------------------- | ----------------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
-  | gcp.gcs.service_account_email          | ""                | `"user@hello.iam.gserviceaccount.com"` | The email address in the JSON file generated at the creation of the service account. |
-  | gcp.gcs.service_account_private_key_id | ""                | "61d257bd8479547cb3e04f0b9b6b9ca07af3b7ea"                   | The private key ID in the JSON file generated at the creation of the service account. |
-  | gcp.gcs.service_account_private_key    | ""                | "-----BEGIN PRIVATE KEY----xxxx-----END PRIVATE KEY-----\n"  | The private key in the JSON file generated at the creation of the service account. |
-
-- To choose the impersonation-based authentication method, configure `StorageCredentialParams` as follows:
-
-  - Make a VM instance impersonate a service account:
-
-    ```SQL
-    "gcp.gcs.use_compute_engine_service_account" = "true",
-    "gcp.gcs.impersonation_service_account" = "<assumed_google_service_account_email>"
-    ```
-
-    The following table describes the parameters you need to configure in `StorageCredentialParams`.
-
-    | **Parameter**                              | **Default value** | **Value** **example** | **Description**                                              |
-    | ------------------------------------------ | ----------------- | --------------------- | ------------------------------------------------------------ |
-    | gcp.gcs.use_compute_engine_service_account | false             | true                  | Specifies whether to directly use the service account that is bound to your Compute Engine. |
-    | gcp.gcs.impersonation_service_account      | ""                | "hello"               | The service account that you want to impersonate.            |
-
-  - Make a service account (named as meta service account) impersonate another service account (named as data service account):
-
-    ```SQL
-    "gcp.gcs.service_account_email" = "<google_service_account_email>",
-    "gcp.gcs.service_account_private_key_id" = "<meta_google_service_account_email>",
-    "gcp.gcs.service_account_private_key" = "<meta_google_service_account_email>",
-    "gcp.gcs.impersonation_service_account" = "<data_google_service_account_email>"
-    ```
-
-    The following table describes the parameters you need to configure in `StorageCredentialParams`.
-
-    | **Parameter**                          | **Default value** | **Value** **example**                                        | **Description**                                              |
-    | -------------------------------------- | ----------------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
-    | gcp.gcs.service_account_email          | ""                | `"user@hello.iam.gserviceaccount.com"` | The email address in the JSON file generated at the creation of the meta service account. |
-    | gcp.gcs.service_account_private_key_id | ""                | "61d257bd8479547cb3e04f0b9b6b9ca07af3b7ea"                   | The private key ID in the JSON file generated at the creation of the meta service account. |
-    | gcp.gcs.service_account_private_key    | ""                | "-----BEGIN PRIVATE KEY----xxxx-----END PRIVATE KEY-----\n"  | The private key in the JSON file generated at the creation of the meta service account. |
-    | gcp.gcs.impersonation_service_account  | ""                | "hello"                                                      | The data service account that you want to impersonate.       |
-
-#### Other S3-compatible storage system
-
-If you choose other S3-compatible storage system, such as MinIO, configure `StorageCredentialParams` as follows:
-
-```SQL
-"aws.s3.enable_ssl" = "false",
-"aws.s3.enable_path_style_access" = "true",
-"aws.s3.endpoint" = "<s3_endpoint>",
-"aws.s3.access_key" = "<iam_user_access_key>",
-"aws.s3.secret_key" = "<iam_user_secret_key>"
-```
-
-The following table describes the parameters you need to configure in `StorageCredentialParams`.
-
-| Parameter                        | Required | Description                                                  |
-| -------------------------------- | -------- | ------------------------------------------------------------ |
-| aws.s3.enable_ssl                | Yes      | Specifies whether to enable SSL connection. Valid values: `true` and `false`. Default value: `true`. |
-| aws.s3.enable_path_style_access  | Yes      | Specifies whether to enable path-style URL access. Valid values: `true` and `false`. Default value: `false`. For MinIO, you must set the value to `true`. |
-| aws.s3.endpoint                  | Yes      | The endpoint that is used to connect to your S3-compatible storage system instead of AWS S3. |
-| aws.s3.access_key                | Yes      | The access key of your IAM user. |
-| aws.s3.secret_key                | Yes      | The secret key of your IAM user. |
-
-#### Microsoft Azure Storage
-
-##### Azure Blob Storage
-
-If you choose Blob Storage as your storage system, take one of the following actions:
-
-- To choose the Shared Key authentication method, configure `StorageCredentialParams` as follows:
-
-  ```SQL
-  "azure.blob.storage_account" = "<storage_account_name>",
-  "azure.blob.shared_key" = "<storage_account_shared_key>"
-  ```
-
-  The following table describes the parameters you need to configure in `StorageCredentialParams`.
-
-  | **Parameter**              | **Required** | **Description**                              |
-  | -------------------------- | ------------ | -------------------------------------------- |
-  | azure.blob.storage_account | Yes          | The username of your Blob Storage account.   |
-  | azure.blob.shared_key      | Yes          | The shared key of your Blob Storage account. |
-
-- To choose the SAS Token authentication method, configure `StorageCredentialParams` as follows:
-
-  ```SQL
-  "azure.blob.storage_account" = "<storage_account_name>",
-  "azure.blob.container" = "<container_name>",
-  "azure.blob.sas_token" = "<storage_account_SAS_token>"
-  ```
-
-  The following table describes the parameters you need to configure in `StorageCredentialParams`.
-
-  | **Parameter**             | **Required** | **Description**                                              |
-  | ------------------------- | ------------ | ------------------------------------------------------------ |
-  | azure.blob.storage_account| Yes          | The username of your Blob Storage account.                   |
-  | azure.blob.container      | Yes          | The name of the blob container that stores your data.        |
-  | azure.blob.sas_token      | Yes          | The SAS token that is used to access your Blob Storage account. |
-
-##### Azure Data Lake Storage Gen2
-
-If you choose Data Lake Storage Gen2 as your storage system, take one of the following actions:
-
-- To choose the Managed Identity authentication method, configure `StorageCredentialParams` as follows:
-
-  ```SQL
-  "azure.adls2.oauth2_use_managed_identity" = "true",
-  "azure.adls2.oauth2_tenant_id" = "<service_principal_tenant_id>",
-  "azure.adls2.oauth2_client_id" = "<service_client_id>"
-  ```
-
-  The following table describes the parameters you need to configure in `StorageCredentialParams`.
-
-  | **Parameter**                           | **Required** | **Description**                                              |
-  | --------------------------------------- | ------------ | ------------------------------------------------------------ |
-  | azure.adls2.oauth2_use_managed_identity | Yes          | Specifies whether to enable the Managed Identity authentication method. Set the value to `true`. |
-  | azure.adls2.oauth2_tenant_id            | Yes          | The ID of the tenant whose data you want to access.          |
-  | azure.adls2.oauth2_client_id            | Yes          | The client (application) ID of the managed identity.         |
-
-- To choose the Shared Key authentication method, configure `StorageCredentialParams` as follows:
-
-  ```SQL
-  "azure.adls2.storage_account" = "<storage_account_name>",
-  "azure.adls2.shared_key" = "<storage_account_shared_key>"
-  ```
-
-  The following table describes the parameters you need to configure in `StorageCredentialParams`.
-
-  | **Parameter**               | **Required** | **Description**                                              |
-  | --------------------------- | ------------ | ------------------------------------------------------------ |
-  | azure.adls2.storage_account | Yes          | The username of your Data Lake Storage Gen2 storage account. |
-  | azure.adls2.shared_key      | Yes          | The shared key of your Data Lake Storage Gen2 storage account. |
-
-- To choose the Service Principal authentication method, configure `StorageCredentialParams` as follows:
-
-  ```SQL
-  "azure.adls2.oauth2_client_id" = "<service_client_id>",
-  "azure.adls2.oauth2_client_secret" = "<service_principal_client_secret>",
-  "azure.adls2.oauth2_client_endpoint" = "<service_principal_client_endpoint>"
-  ```
-
-  The following table describes the parameters you need to configure `in StorageCredentialParams`.
-
-  | **Parameter**                      | **Required** | **Description**                                              |
-  | ---------------------------------- | ------------ | ------------------------------------------------------------ |
-  | azure.adls2.oauth2_client_id       | Yes          | The client (application) ID of the service principal.        |
-  | azure.adls2.oauth2_client_secret   | Yes          | The value of the new client (application) secret created.    |
-  | azure.adls2.oauth2_client_endpoint | Yes          | The OAuth 2.0 token endpoint (v1) of the service principal or application. |
-
-##### Azure Data Lake Storage Gen1
-
-If you choose Data Lake Storage Gen1 as your storage system, take one of the following actions:
-
-- To choose the Managed Service Identity authentication method, configure `StorageCredentialParams` as follows:
-
-  ```SQL
-  "azure.adls1.use_managed_service_identity" = "true"
-  ```
-
-  The following table describes the parameters you need to configure in `StorageCredentialParams`.
-
-  | **Parameter**                            | **Required** | **Description**                                              |
-  | ---------------------------------------- | ------------ | ------------------------------------------------------------ |
-  | azure.adls1.use_managed_service_identity | Yes          | Specifies whether to enable the Managed Service Identity authentication method. Set the value to `true`. |
-
-- To choose the Service Principal authentication method, configure `StorageCredentialParams` as follows:
-
-  ```SQL
-  "azure.adls1.oauth2_client_id" = "<application_client_id>",
-  "azure.adls1.oauth2_credential" = "<application_client_credential>",
-  "azure.adls1.oauth2_endpoint" = "<OAuth_2.0_authorization_endpoint_v2>"
-  ```
-
-  The following table describes the parameters you need to configure in `StorageCredentialParams`.
-
-  | **Parameter**                 | **Required** | **Description**                                              |
-  | ----------------------------- | ------------ | ------------------------------------------------------------ |
-  | azure.adls1.oauth2_client_id  | Yes          | The client (application) ID of the .                         |
-  | azure.adls1.oauth2_credential | Yes          | The value of the new client (application) secret created.    |
-  | azure.adls1.oauth2_endpoint   | Yes          | The OAuth 2.0 token endpoint (v1) of the service principal or application. |
-
-### opt_properties
-
-Specifies some optional parameters whose settings are applied to the entire load job. Syntax:
-
-```Plain
-PROPERTIES ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
-```
-
-The following parameters are supported:
-
-- `timeout`
-
-  Specifies the timeout period of the load job. Unit: second. The default timeout period is 4 hours. We recommend that you specify a timeout period shorter than 6 hours. If the load job does not finish within the timeout period, StarRocks cancels the load job and the status of the load job becomes **CANCELLED**.
-
-  > **NOTE**
-  >
-  > In most cases, you do not need to set the timeout period. We recommend that you set the timeout period only when the load job cannot finish within the default timeout period.
-
-  Use the following formula to infer the timeout period:
-
-  **Timeout period > (Total size of the data files to be loaded x Total number of the data files to be loaded and the materialized views created on the data files)/Average load speed**
-
-  > **NOTE**
-  >
-  > "Average load speed" is the average load speed for your entire StarRocks cluster. The average load speed varies for each cluster depending on the server configuration and the maximum number of concurrent query tasks allowed for the cluster. You can infer the average load speed based on the load speeds of historical load jobs.
-
-  Suppose that you want to load a 1-GB data file on which two materialized views are created into a StarRocks cluster whose average load speed is 10 MB/s. The amount of time required for the data load is approximately 102 seconds.
-
-  (1 x 1024 x 3)/10 = 307.2 (second)
-
-  For this example, we recommend that you set the timeout period to a value greater than 308 seconds.
-
-- `max_filter_ratio`
-
-  Specifies the maximum error tolerance of the load job. The maximum error tolerance is the maximum percentage of rows that can be filtered out as a result of inadequate data quality. Valid values: `0`~`1`. Default value: `0`.
-
-  - If you set this parameter to `0`, StarRocks does not ignore unqualified rows during loading. As such, if the source data contains unqualified rows, the load job fails. This helps ensure the correctness of the data loaded into StarRocks.
-
-  - If you set this parameter to a value greater than `0`, StarRocks can ignore unqualified rows during loading. As such, the load job can succeed even if the source data contains unqualified rows.
-
-    > **NOTE**
-    >
-    > Rows that are filtered out due to inadequate data quality do not include rows that are filtered out by the WHERE clause.
-
-  If the load job fails because the maximum error tolerance is set to `0`, you can use [SHOW LOAD](../../../sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md) to view the job result. Then, determine whether unqualified rows can be filtered out. If unqualified rows can be filtered out, calculate the maximum error tolerance based on the values returned for `dpp.abnorm.ALL` and `dpp.norm.ALL` in the job result, adjust the maximum error tolerance, and submit the load job again. The formula for calculating the maximum error tolerance is as follows:
-
-  `max_filter_ratio` = [`dpp.abnorm.ALL`/(`dpp.abnorm.ALL` + `dpp.norm.ALL`)]
-
-  The sum of the values returned for `dpp.abnorm.ALL` and `dpp.norm.ALL` is the total number of rows to be loaded.
-
-- `log_rejected_record_num`
-
-  Specifies the maximum number of unqualified data rows that can be logged. This parameter is supported from v3.1 onwards. Valid values: `0`, `-1`, and any non-zero positive integer. Default value: `0`.
-  
-  - The value `0` specifies that data rows that are filtered out will not be logged.
-  - The value `-1` specifies that all data rows that are filtered out will be logged.
-  - A non-zero positive integer such as `n` specifies that up to `n` data rows that are filtered out can be logged on each BE.
-
-- `load_mem_limit`
-
-  Specifies the maximum amount of memory that can be provided to the load job. The value of this parameter cannot exceed the upper memory limit supported by each BE or CN node. Unit: bytes: The default memory limit is 2 GB.
-
-- `strict_mode`
-
-  Specifies whether to enable the [strict mode](../../../loading/load_concept/strict_mode.md). Valid values: `true` and `false`. Default value: `false`. `true` specifies to enable the strict mode, and `false` specifies to disable the strict mode.
-
-- `timezone`
-
-  Specifies the time zone of the load job. Default value: `Asia/Shanghai`. The time zone setting affects the results returned by functions such as strftime, alignment_timestamp, and from_unixtime. For more information, see [Configure a time zone](../../../administration/management/timezone.md). The time zone specified in the `timezone` parameter is a session-level time zone.
-
-- `priority`
-
-  Specifies the priority of the load job. Valid values: `LOWEST`, `LOW`, `NORMAL`, `HIGH`, and `HIGHEST`. Default value: `NORMAL`. Broker Load provides the [FE parameter](../../../administration/management/FE_configuration.md) `max_broker_load_job_concurrency`, determines the maximum number of Broker Load jobs that can be concurrently run within your StarRocks cluster. If the number of Broker Load jobs that are submitted within the specified time period exceeds the maximum number, excessive jobs will be waiting to be scheduled based on their priorities.
-
-  You can use the [ALTER LOAD](../../../sql-reference/sql-statements/data-manipulation/ALTER_LOAD.md) statement to change the priority of an existing load job that is in the `QUEUEING` or `LOADING` state.
-
-  StarRocks allows setting the `priority` parameter for a Broker Load job since v2.5.
-
-- `partial_update`
-
-  Whether to use partial updates. Valid values: `TRUE` and `FALSE`. Default value: `FALSE`, indicating to disable this feature.
-
-- `partial_update_mode`
-
-  Specifies the mode for partial updates. Valid values: `row` and `column`. <ul><li> The value `row` (default) means partial updates in row mode, which is more suitable for real-time updates with many columns and small batches.</li><li>The value `column` means partial updates in column mode, which is more suitable for batch updates with few columns and many rows. In such scenarios, enabling the column mode offers faster update speeds. For example, in a table with 100 columns, if only 10 columns (10% of the total) are updated for all rows, the update speed of the column mode is 10 times faster.</li></ul>
-
-- `merge_condition`
-
-  Specifies the name of the column you want to use as the condition to determine whether updates can take effect. The update from a source record to a destination record takes effect only when the source data record has a greater or equal value than the destination data record in the specified column.
-  
-  Broker Load supports conditional updates since v3.1. For more information, see [Change data through loading](../../../loading/Load_to_Primary_Key_tables.md#conditional-updates).
-  
-  > **NOTE**
-  >
-  > The column that you specify cannot be a primary key column. Additionally, only tables that use the Primary Key table support conditional updates.
-
-StarRocks supports loading JSON data from v3.2.3 onwards. The parameters are as follows:
-
-- jsonpaths
-
-  The names of the keys that you want to load from the JSON data file. You need to specify this parameter only when you load JSON data by using the matched mode. The value of this parameter is in JSON format. See [Configure column mapping for JSON data loading](#configure-column-mapping-for-json-data-loading).
-
-- strip_outer_array
-
-  Specifies whether to strip the outermost array structure. Valid values: `true` and `false`. Default value: `false`.
-  
-  In real-world business scenarios, the JSON data may have an outermost array structure as indicated by a pair of square brackets `[]`. In this situation, we recommend that you set this parameter to `true`, so StarRocks removes the outermost square brackets `[]` and loads each inner array as a separate data record. If you set this parameter to `false`, StarRocks parses the entire JSON data file into one array and loads the array as a single data record. For example, the JSON data is `[ {"category" : 1, "author" : 2}, {"category" : 3, "author" : 4} ]`. If you set this parameter to `true`,  `{"category" : 1, "author" : 2}` and `{"category" : 3, "author" : 4}` are parsed into separate data records that are loaded into separate StarRocks table rows.
-
-- json_root
-
-  The root element of the JSON data that you want to load from the JSON data file. You need to specify this parameter only when you load JSON data by using the matched mode. The value of this parameter is a valid JsonPath string. By default, the value of this parameter is empty, indicating that all data of the JSON data file will be loaded. For more information, see the "[Load JSON data using matched mode with root element specified](#load-json-data-using-matched-mode-with-root-element-specified)" section of this topic.
-
-<!-- - ignore_json_size
-
-  Specifies whether to check the size of the JSON body in the HTTP request.
-  
-  > **NOTE**
-  >
-  > By default, the size of the JSON body in an HTTP request cannot exceed 100 MB. If the JSON body exceeds 100 MB in size, an error "The size of this batch exceed the max size [104857600] of json type data data [8617627793]. Set ignore_json_size to skip check, although it may lead huge memory consuming." is reported. To prevent this error, you can add `"ignore_json_size:true"` in the HTTP request header to instruct StarRocks not to check the JSON body size.
--->
-When you load JSON data, also note that the size per JSON object cannot exceed 4 GB. If an individual JSON object in the JSON data file exceeds 4 GB in size, an error "This parser can't support a document that big." is reported.
-
-## Column mapping
-
-### Configure column mapping for CSV data loading
-
-If the columns of the data file can be mapped one on one in sequence to the columns of the StarRocks table, you do not need to configure the column mapping between the data file and the StarRocks table.
-
-If the columns of the data file cannot be mapped one on one in sequence to the columns of the StarRocks table, you need to use the `columns` parameter to configure the column mapping between the data file and the StarRocks table. This includes the following two use cases:
-
-- **Same number of columns but different column sequence.** **Also, the data from the data file does not need to be computed by functions before it is loaded into the matching StarRocks table columns.**
-
-  In the `columns` parameter, you need to specify the names of the StarRocks table columns in the same sequence as how the data file columns are arranged.
-
-  For example, the StarRocks table consists of three columns, which are `col1`, `col2`, and `col3` in sequence, and the data file also consists of three columns, which can be mapped to the StarRocks table columns `col3`, `col2`, and `col1` in sequence. In this case, you need to specify `"columns: col3, col2, col1"`.
-
-- **Different number of columns and different column sequence. Also, the data from the data file needs to be computed by functions before it is loaded into the matching StarRocks table columns.**
-
-  In the `columns` parameter, you need to specify the names of the StarRocks table columns in the same sequence as how the data file columns are arranged and specify the functions you want to use to compute the data. Two examples are as follows:
-
-  - The StarRocks table consists of three columns, which are `col1`, `col2`, and `col3` in sequence. The data file consists of four columns, among which the first three columns can be mapped in sequence to the StarRocks table columns `col1`, `col2`, and `col3` and the fourth column cannot be mapped to any of the StarRocks table columns. In this case, you need to temporarily specify a name for the fourth column of the data file, and the temporary name must be different from any of the StarRocks table column names. For example, you can specify `"columns: col1, col2, col3, temp"`, in which the fourth column of the data file is temporarily named `temp`.
-  - The StarRocks table consists of three columns, which are `year`, `month`, and `day` in sequence. The data file consists of only one column that accommodates date and time values in `yyyy-mm-dd hh:mm:ss` format. In this case, you can specify `"columns: col, year = year(col), month=month(col), day=day(col)"`, in which `col` is the temporary name of the data file column and the functions `year = year(col)`, `month=month(col)`, and `day=day(col)` are used to extract data from the data file column `col` and loads the data into the mapping StarRocks table columns. For example, `year = year(col)` is used to extract the `yyyy` data from the data file column `col` and loads the data into the StarRocks table column `year`.
-
-For detailed examples, see [Configure column mapping](#configure-column-mapping).
-
-### Configure column mapping for JSON data loading
-
-If the keys of the JSON document have the same names as the columns of the StarRocks table, you can load the JSON-formatted data by using the simple mode. In simple mode, you do not need to specify the `jsonpaths` parameter. This mode requires that the JSON-formatted data must be an object as indicated by curly brackets `{}`, such as `{"category": 1, "author": 2, "price": "3"}`. In this example, `category`, `author`, and `price` are key names, and these keys can be mapped one on one by name to the columns `category`, `author`, and `price` of the StarRocks table.
-
-If the keys of the JSON document have different names than the columns of the StarRocks table, you can load the JSON-formatted data by using the matched mode. In matched mode, you need to use the `jsonpaths` and `COLUMNS` parameters to specify the column mapping between the JSON document and the StarRocks table:
-
-- In the `jsonpaths` parameter, specify the JSON keys in the sequence as how they are arranged in the JSON document.
-- In the `COLUMNS` parameter, specify the mapping between the JSON keys and the StarRocks table columns:
-  - The column names specified in the `COLUMNS` parameter are mapped one on one in sequence to the JSON keys.
-  - The column names specified in the `COLUMNS` parameter are mapped one on one by name to the StarRocks table columns.
-
-For examples about loading JSON-formatted data by using the matched mode, see [Load JSON data using matched mode](#load-json-data-using-matched-mode).
-
-## Related configuration items
-
-The [FE configuration item](../../../administration/management/FE_configuration.md) `max_broker_load_job_concurrency` specifies the maximum number of Broker Load jobs that can be concurrently run within your StarRocks cluster.
-
-In StarRocks v2.4 and earlier, if the total number of Broker Load jobs that are submitted within a specific period of time exceeds the maximum number, excessive jobs will be queued and scheduled based on their submission time.
-
-Since StarRocks v2.5, if the total number of Broker Load jobs that are submitted within a specific period of time exceeds the maximum number, excessive jobs are queued and scheduled based on their priorities. You can specify a priority for a job by using the `priority` parameter described above. You can use [ALTER LOAD](../data-manipulation/ALTER_LOAD.md) to modify the priority of an existing job that is in the **QUEUEING** or **LOADING** state.
-
-## Job splitting and concurrent running
-
-A Broker Load job can be split into one or more tasks that concurrently run. The tasks within a load job are run within a single transaction. They must all succeed or fail. StarRocks splits each load job based on how you declare `data_desc` in the `LOAD` statement:
-
-- If you declare multiple `data_desc` parameters, each of which specifies a distinct table, a task is generated to load the data of each table.
-
-- If you declare multiple `data_desc` parameters, each of which specifies a distinct partition for the same table, a task is generated to load the data of each partition.
-
-Additionally, each task can be further split into one or more instances, which are evenly distributed to and concurrently run on the BEs or CNs of your StarRocks cluster. StarRocks splits each task based on the FE parameter [`min_bytes_per_broker_scanner`](../../../administration/management/FE_configuration.md) and the number of BE or CN nodes. You can use the following formula to calculate the number of instances in an individual task:
-
-**Number of instances in an individual task = min(Amount of data to be loaded by an individual task/`min_bytes_per_broker_scanner`, Number of BE/CN nodes)**
-
-In most cases, only one `data_desc` is declared for each load job, each load job is split into only one task, and the task is split into the same number of instances as the number of BE or CN nodes.
-
-## Examples
-
-This section uses HDFS as an example to describe various load configurations.
-
-### Load CSV data
-
-This section uses CSV as an example to explain the various parameter configurations that you can use to meet your diverse load requirements.
-
-#### Set timeout period
-
-Your StarRocks database `test_db` contains a table named `table1`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example1.csv` also consists of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table1`.
-
-If you want to load all data from `example1.csv` into `table1` within up to 3600 seconds, run the following command:
-
-```SQL
-LOAD LABEL test_db.label1
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example1.csv")
-    INTO TABLE table1
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-)
-PROPERTIES
-(
-    "timeout" = "3600"
-);
-```
-
-#### Set maximum error tolerance
-
-Your StarRocks database `test_db` contains a table named `table2`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example2.csv` also consists of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table2`.
-
-If you want to load all data from `example2.csv` into `table2` with a maximum error tolerance of `0.1`, run the following command:
-
-```SQL
-LOAD LABEL test_db.label2
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example2.csv")
-    INTO TABLE table2
-
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-)
-PROPERTIES
-(
-    "max_filter_ratio" = "0.1"
-);
-```
-
-#### Load all data files from a file path
-
-Your StarRocks database `test_db` contains a table named `table3`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-All data files stored in the `/user/starrocks/data/input/` path of your HDFS cluster also each consist of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table3`. The column separator used in these data files is `\x01`.
-
-If you want to load data from all these data files stored in the `hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/` path into `table3`, run the following command:
-
-```SQL
-LOAD LABEL test_db.label3
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/*")
-    INTO TABLE table3
-    COLUMNS TERMINATED BY "\\x01"
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-#### Set NameNode HA mechanism
-
-Your StarRocks database `test_db` contains a table named `table4`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example4.csv` also consists of three columns, which are mapped onto `col1`, `col2`, and `col3` of `table4`.
-
-If you want to load all data from `example4.csv` into `table4` with an HA mechanism configured for the NameNode, run the following command:
-
-```SQL
-LOAD LABEL test_db.label4
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example4.csv")
-    INTO TABLE table4
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>",
-    "dfs.nameservices" = "my_ha",
-    "dfs.ha.namenodes.my_ha" = "my_namenode1, my_namenode2","dfs.namenode.rpc-address.my_ha.my_namenode1" = "nn1_host:rpc_port",
-    "dfs.namenode.rpc-address.my_ha.my_namenode2" = "nn2_host:rpc_port",
-    "dfs.client.failover.proxy.provider" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
-);
-```
-
-#### Set Kerberos authentication
-
-Your StarRocks database `test_db` contains a table named `table5`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example5.csv` also consists of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table5`.
-
-If you want to load all data from `example5.csv` into `table5` with Kerberos authentication configured and the keytab file path specified, run the following command:
-
-```SQL
-LOAD LABEL test_db.label5
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example5.csv")
-    INTO TABLE table5
-    COLUMNS TERMINATED BY "\t"
-)
-WITH BROKER
-(
-    "hadoop.security.authentication" = "kerberos",
-    "kerberos_principal" = "starrocks@YOUR.COM",
-    "kerberos_keytab" = "/home/starRocks/starRocks.keytab"
-);
-```
-
-#### Revoke data loading
-
-Your StarRocks database `test_db` contains a table named `table6`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example6.csv` also consists of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table6`.
-
-You have loaded all data from `example6.csv` into `table6` by running a Broker Load job.
-
-If you want to revoke the data you have loaded, run the following command:
-
-```SQL
-LOAD LABEL test_db.label6
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example6.csv")
-    NEGATIVE
-    INTO TABLE table6
-    COLUMNS TERMINATED BY "\t"
-)
-WITH BROKER
-(
-    "hadoop.security.authentication" = "kerberos",
-    "kerberos_principal" = "starrocks@YOUR.COM",
-    "kerberos_keytab" = "/home/starRocks/starRocks.keytab"
-);
-```
-
-#### Specify destination partitions
-
-Your StarRocks database `test_db` contains a table named `table7`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example7.csv` also consists of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table7`.
-
-If you want to load all data from `example7.csv` into two partitions, `p1` and `p2`, of `table7`, run the following command:
-
-```SQL
-LOAD LABEL test_db.label7
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example7.csv")
-    INTO TABLE table7
-    PARTITION (p1, p2)
-    COLUMNS TERMINATED BY ","
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-#### Configure column mapping
-
-Your StarRocks database `test_db` contains a table named `table8`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example8.csv` also consists of three columns, which are mapped in sequence onto `col2`, `col1`, and `col3` of `table8`.
-
-If you want to load all data from `example8.csv` into `table8`, run the following command:
-
-```SQL
-LOAD LABEL test_db.label8
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example8.csv")
-    INTO TABLE table8
-    COLUMNS TERMINATED BY ","
-    (col2, col1, col3)
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-> **NOTE**
->
-> In the preceding example, the columns of `example8.csv` cannot be mapped onto the columns of `table8` in the same sequence as how these columns are arranged in `table8`. Therefore, you need to use `column_list` to configure the column mapping between `example8.csv` and `table8`.
-
-#### Set filter conditions
-
-Your StarRocks database `test_db` contains a table named `table9`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example9.csv` also consists of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table9`.
-
-If you want to load only the data records whose values in the first column are greater than `20180601` from `example9.csv` into `table9`, run the following command:
-
-```SQL
-LOAD LABEL test_db.label9
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example9.csv")
-    INTO TABLE table9
-    (col1, col2, col3)
-    where col1 > 20180601
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-> **NOTE**
->
-> In the preceding example, the columns of `example9.csv` can be mapped onto the columns of `table9` in the same sequence as how these columns are arranged in `table9`, but you need to use the WHERE clause to specify column-based filter conditions. Therefore, you need to use `column_list` to configure the column mapping between `example9.csv` and `table9`.
-
-#### Load data into tables containing HLL-type columns
-
-Your StarRocks database `test_db` contains a table named `table10`. The table consists of four columns, which are `id`, `col1`, `col2`, and `col3` in sequence. `col1` and `col2` are defined as HLL-type columns.
-
-Your data file `example10.csv` consists of three columns, among which the first column is mapped onto `id` of `table10` and the second and third columns are mapped in sequence onto `col1` and `col2` of `table10`. The values in the second and third columns of `example10.csv` can be converted into HLL-type data by using functions before they are loaded into `col1` and `col2` of `table10`.
-
-If you want to load all data from `example10.csv` into `table10`, run the following command:
-
-```SQL
-LOAD LABEL test_db.label10
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example10.csv")
-    INTO TABLE table10
-    COLUMNS TERMINATED BY ","
-    (id, temp1, temp2)
-    SET
-    (
-        col1 = hll_hash(temp1),
-        col2 = hll_hash(temp2),
-        col3 = empty_hll()
-     )
- )
- WITH BROKER
- (
-     "username" = "<hdfs_username>",
-     "password" = "<hdfs_password>"
- );
-```
-
-> **NOTE**
->
-> In the preceding example, the three columns of `example10.csv` are named `id`, `temp1`, and `temp2` in sequence by using `column_list`. Then, functions are used to convert data as follows:
->
-> - The `hll_hash` function is used to convert the values in `temp1` and `temp2` of `example10.csv` into HLL-type data and map `temp1` and `temp2` of `example10.csv` onto `col1` and `col2` of `table10`.
->
-> - The `hll_empty` function is used to fill the specified default value into `col3` of `table10`.
-
-For usage of the functions `hll_hash` and `hll_empty`, see [hll_hash](../../sql-functions/scalar-functions/hll_hash.md) and [hll_empty](../../sql-functions/scalar-functions/hll_empty.md).
-
-#### Extract partition field values from file path
-
-Broker Load supports parsing the values of specific partition fields contained in a file path based on the column definitions of the destination StarRocks table. This feature of StarRocks is similar to the Partition Discovery feature of Apache Spark™.
-
-Your StarRocks database `test_db` contains a table named `table11`. The table consists of five columns, which are `col1`, `col2`, `col3`, `city`, and `utc_date` in sequence.
-
-The file path `/user/starrocks/data/input/dir/city=beijing` of your HDFS cluster contains the following data files:
-
-- `/user/starrocks/data/input/dir/city=beijing/utc_date=2019-06-26/0000.csv`
-
-- `/user/starrocks/data/input/dir/city=beijing/utc_date=2019-06-26/0001.csv`
-
-These data files each consist of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table11`.
-
-If you want to load data from all data files from the file path `/user/starrocks/data/input/dir/city=beijing/utc_date=*/*` into `table11` and, at the same time, you want to extract the values of the partition fields `city` and `utc_date` contained in the file path and load the extracted values into `city` and `utc_date` of `table11`, run the following command:
-
-```SQL
-LOAD LABEL test_db.label11
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/dir/city=beijing/*/*")
-    INTO TABLE table11
-    FORMAT AS "csv"
-    (col1, col2, col3)
-    COLUMNS FROM PATH AS (city, utc_date)
-    SET (uniq_id = md5sum(k1, city))
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-#### Extract partition field values from `%3A`-included file path
-
-In HDFS, file paths cannot contain colons (:). All colons (:) will be converted into `%3A`.
-
-Your StarRocks database `test_db` contains a table named `table12`. The table consists of three columns, which are `data_time`, `col1`, and `col2` in sequence. The table schema is as follows:
-
-```SQL
-data_time DATETIME,
-col1        INT,
-col2        INT
-```
-
-The file path `/user/starrocks/data` of your HDFS cluster contains the following data files:
-
-- `/user/starrocks/data/data_time=2020-02-17 00%3A00%3A00/example12.csv`
-
-- `/user/starrocks/data/data_time=2020-02-18 00%3A00%3A00/example12.csv`
-
-If you want to load all data from `example12.csv` into `table12` and, at the same time, you want to extract the values of the partition field `data_time` from the file path and load the extracted values into `data_time` of `table12`, run the following command:
-
-```SQL
-LOAD LABEL test_db.label12
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/*/example12.csv")
-    INTO TABLE table12
-    COLUMNS TERMINATED BY ","
-    FORMAT AS "csv"
-    (col1,col2)
-    COLUMNS FROM PATH AS (data_time)
-    SET (data_time = str_to_date(data_time, '%Y-%m-%d %H%%3A%i%%3A%s'))
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-> **NOTE**
->
-> In the preceding example, the values extracted from the partition field `data_time` are strings that contain `%3A`, such as `2020-02-17 00%3A00%3A00`. Therefore, you need to use the `str_to_date` function to convert the strings into DATETIME-type data before they are loaded into `data_time` of `table8`.
-
-#### Setting `format_type_options`
-
-Your StarRocks database `test_db` contains a table named `table13`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example13.csv` also consists of three columns, which are mapped in sequence onto `col2`, `col1`, and `col3` of `table13`.
-
-If you want to load all data from `example13.csv` into `table13`, with the intention of skipping the first two rows of `example13.csv`, removing the spaces preceding and following column separators, and setting `enclose` to `\` and `escape` to `\`, run the following command:
-
-```SQL
-LOAD LABEL test_db.label13
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/*/example13.csv")
-    INTO TABLE table13
-    COLUMNS TERMINATED BY ","
-    FORMAT AS "CSV"
-    (
-        skip_header = 2
-        trim_space = TRUE
-        enclose = "\""
-        escape = "\\"
-    )
-    (col2, col1, col3)
-)
-WITH BROKER
-(
-    "username" = "hdfs_username",
-    "password" = "hdfs_password"
-)
-PROPERTIES
-(
-    "timeout" = "3600"
-);
-```
-
-### Load Parquet data
-
-This section describes some parameters settings you need to take note of when you load Parquet data.
-
-Your StarRocks database `test_db` contains a table named `table13`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example13.parquet` also consists of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table13`.
-
-If you want to load all data from `example13.parquet` into `table13`, run the following command:
-
-```SQL
-LOAD LABEL test_db.label13
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example13.parquet")
-    INTO TABLE table13
-    FORMAT AS "parquet"
-    (col1, col2, col3)
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-> **NOTE**
->
-> By default, when you load Parquet data, StarRocks determines the data file format based on whether the filename contains the extension **.parquet**. If the filename does not contain the extension **.parquet**, you must use `FORMAT AS` to specify the data file format as `Parquet`.
-
-### Load ORC data
-
-This section describes some parameters settings you need to take note of when you load ORC data.
-
-Your StarRocks database `test_db` contains a table named `table14`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example14.orc` also contains three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table14`.
-
-If you want to load all data from `example14.orc` into `table14`, run the following command:
-
-```SQL
-LOAD LABEL test_db.label14
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example14.orc")
-    INTO TABLE table14
-    FORMAT AS "orc"
-    (col1, col2, col3)
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-> **NOTE**
->
-> - By default, when you load ORC data, StarRocks determines the data file format based on whether the filename contains the extension **.orc**. If the filename does not contain the extension **.orc**, you must use `FORMAT AS` to specify the data file format as `ORC`.
->
-> - In StarRocks v2.3 and earlier, if the data file contains ARRAY-type columns, you must make sure that the columns of the ORC data file have the same names as their mapping columns in the StarRocks table and the columns cannot be specified in the SET clause.
-
-### Load JSON data
-
-This section describes the parameter settings that you need to take note of when you load JSON data.
-
-Your StarRocks database `test_db` contains a table named `tbl1`, whose schema is as follows:
-
-```SQL
-`category` varchar(512) NULL COMMENT "",
-`author` varchar(512) NULL COMMENT "",
-`title` varchar(512) NULL COMMENT "",
-`price` double NULL COMMENT ""
-```
-
-#### Load JSON data using simple mode
-
-Suppose that your data file `example1.json` consists of the following data:
-
-```JSON
-{"category":"C++","author":"avc","title":"C++ primer","price":895}
-```
-
-To load all data from `example1.json` into `tbl1`, run the following command:
-
-```SQL
-LOAD LABEL test_db.label15
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example1.csv")
-    INTO TABLE tbl1
-    FORMAT AS "json"
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-> **NOTE**
->
-> In the preceding example, the parameters `columns` and `jsonpaths` are not specified. Therefore, the keys in `example1.json` are mapped by name onto the columns of `tbl1`.
-
-#### Load JSON data using matched mode
-
-StarRocks performs the following steps to match and process JSON data:
-
-1. (Optional) Strips the outermost array structure as instructed by the `strip_outer_array` parameter setting.
-
-   > **NOTE**
-   >
-   > This step is performed only when the outermost layer of the JSON data is an array structure as indicated by a pair of square brackets `[]`. You need to set `strip_outer_array` to `true`.
-
-2. (Optional) Matches the root element of the JSON data as instructed by the `json_root` parameter setting.
-
-   > **NOTE**
-   >
-   > This step is performed only when the JSON data has a root element. You need to specify the root element by using the `json_root` parameter.
-
-3. Extracts the specified JSON data as instructed by the `jsonpaths` parameter setting.
-
-##### Load JSON data using matched mode without root element specified
-
-Suppose that your data file `example2.json` consists of the following data:
-
-```JSON
-[
-    {"category":"xuxb111","author":"1avc","title":"SayingsoftheCentury","price":895},
-    {"category":"xuxb222","author":"2avc","title":"SayingsoftheCentury","price":895},
-    {"category":"xuxb333","author":"3avc","title":"SayingsoftheCentury","price":895}
-]
-```
-
-To load only `category`, `author`, and `price` from `example2.json`, run the following command:
-
-```SQL
-LOAD LABEL test_db.label16
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example2.csv")
-    INTO TABLE tbl1
-    FORMAT AS "json"
-    (category, price, author)
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-)
-PROPERTIES
-(
-    "strip_outer_array" = "true",
-    "jsonpaths" = "[\"$.category\",\"$.price\",\"$.author\"]"
-);
-```
-
-> **NOTE**
->
-> In the preceding example, the outermost layer of the JSON data is an array structure as indicated by a pair of square brackets `[]`. The array structure consists of multiple JSON objects that each represent a data record. Therefore, you need to set `strip_outer_array` to `true` to strip the outermost array structure. The key **title** that you do not want to load is ignored during loading.
-
-##### Load JSON data using matched mode with root element specified
-
-Suppose your data file `example3.json` consists of the following data:
-
-```JSON
-{
-    "id": 10001,
-    "RECORDS":[
-        {"category":"11","title":"SayingsoftheCentury","price":895,"timestamp":1589191587},
-        {"category":"22","author":"2avc","price":895,"timestamp":1589191487},
-        {"category":"33","author":"3avc","title":"SayingsoftheCentury","timestamp":1589191387}
-    ],
-    "comments": ["3 records", "there will be 3 rows"]
-}
-```
-
-To load only `category`, `author`, and `price` from `example3.json`, run the following command:
-
-```SQL
-LOAD LABEL test_db.label17
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example3.csv")
-    INTO TABLE tbl1
-    FORMAT AS "json"
-    (category, price, author)
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-)
-PROPERTIES
-(
-    "json_root"="$.RECORDS",
-    "strip_outer_array" = "true",
-    "jsonpaths" = "[\"$.category\",\"$.price\",\"$.author\"]"
-);
-```
-
-> **NOTE**
->
-> In the preceding example, the outermost layer of the JSON data is an array structure as indicated by a pair of square brackets `[]`. The array structure consists of multiple JSON objects that each represent a data record. Therefore, you need to set `strip_outer_array` to `true` to strip the outermost array structure. The keys `title` and `timestamp` that you do not want to load are ignored during loading. Additionally, the `json_root` parameter is used to specify the root element, which is an array, of the JSON data.
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/CANCEL_EXPORT.md b/docs/en/sql-reference/sql-statements/data-manipulation/CANCEL_EXPORT.md
deleted file mode 100644
index 082aaba471d78c..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/CANCEL_EXPORT.md
+++ /dev/null
@@ -1,43 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CANCEL EXPORT
-
-## Description
-
-Cancels a given data unloading job. Unloading jobs with the state `CANCELLED` or `FINISHED` cannot be canceled. Canceling an unloading job is an asynchronous process. You can use the [SHOW EXPORT](../data-manipulation/SHOW_EXPORT.md) statement to check whether an unloading job is successfully canceled. The unloading job is successfully canceled if the value of `State` is `CANCELLED`.
-
-The CANCEL EXPORT statement requires that you have at least one of the following privileges on the database to which the given unloading job belongs: `SELECT_PRIV`, `LOAD_PRIV`, `ALTER_PRIV`, `CREATE_PRIV`, `DROP_PRIV`, and `USAGE_PRIV`. For more information about privilege descriptions, see [GRANT](../account-management/GRANT.md).
-
-## Syntax
-
-```SQL
-CANCEL EXPORT
-[FROM db_name]
-WHERE QUERYID = "query_id"
-```
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                              |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| db_name       | No           | The name of the databases to which the unloading job belongs. If this parameter is not specified, an unloading job in your current database is canceled. |
-| query_id      | Yes          | The query ID of the unloading job. You can obtain the ID by using the [LAST_QUERY_ID()](../../sql-functions/utility-functions/last_query_id.md) function. Note that this function only returns the latest query ID. |
-
-## Examples
-
-Example 1: Cancel an unloading job whose query ID is `921d8f80-7c9d-11eb-9342-acde48001121` in the current database.
-
-```SQL
-CANCEL EXPORT
-WHERE queryid = "921d8f80-7c9d-11eb-9342-acde48001121";
-```
-
-Example 2: Cancel an unloading job whose query ID is `921d8f80-7c9d-11eb-9342-acde48001121` in the `example_db` database.
-
-```SQL
-CANCEL EXPORT 
-FROM example_db 
-WHERE queryid = "921d8f80-7c9d-11eb-9342-acde48001122";
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/CANCEL_LOAD.md b/docs/en/sql-reference/sql-statements/data-manipulation/CANCEL_LOAD.md
deleted file mode 100644
index 9e4a43587f7543..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/CANCEL_LOAD.md
+++ /dev/null
@@ -1,43 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CANCEL LOAD
-
-## Description
-
-Cancels a given load job: [Broker Load](../data-manipulation/BROKER_LOAD.md), [Spark Load](../data-manipulation/SPARK_LOAD.md), or [INSERT](./INSERT.md). A load job in the `PREPARED`, `CANCELLED` or `FINISHED` state cannot be canceled.
-
-Canceling a load job is an asynchronous process. You can use the [SHOW LOAD](../data-manipulation/SHOW_LOAD.md) statement to check whether a load job is successfully canceled. The load job is successfully canceled if the value of `State` is `CANCELLED` and the value of `type` (displayed in `ErrorMsg`) is `USER_CANCEL`.
-
-## Syntax
-
-```SQL
-CANCEL LOAD
-[FROM db_name]
-WHERE LABEL = "label_name"
-```
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                              |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| db_name       | No           | The name of the database to which the load job belongs. If this parameter is not specified, a load job in your current database is canceled by default. |
-| label_name    | Yes          | The label of the load job.                                   |
-
-## Examples
-
-Example 1: Cancel the load job whose label is `example_label` in the current database.
-
-```SQL
-CANCEL LOAD
-WHERE LABEL = "example_label";
-```
-
-Example 2: Cancel the load job whose label is `example_label` in the `example_db` database.
-
-```SQL
-CANCEL LOAD
-FROM example_db
-WHERE LABEL = "example_label";
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW.md
deleted file mode 100644
index 9ba4c6d9cf667a..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW.md
+++ /dev/null
@@ -1,38 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CANCEL REFRESH MATERIALIZED VIEW
-
-## Description
-
-Cancels a refresh task for an asynchronous materialized view.
-
-:::tip
-
-This operation requires the REFRESH privilege on the target materialized view.
-
-:::
-
-## Syntax
-
-```SQL
-CANCEL REFRESH MATERIALIZED VIEW [<database_name>.]<materialized_view_name> [FORCE]
-```
-
-## Parameters
-
-| **Parameter**          | **Required** | **Description**                                              |
-| ---------------------- | ------------ | ------------------------------------------------------------ |
-| database_name          | No           | Name of the database where the materialized view resides. If this parameter is not specified, the current database is used. |
-| materialized_view_name | Yes          | Name of the materialized view.                               |
-| FORCE                  | NO           | Forces to cancel the running materialized view refresh task. |
-
-## Examples
-
-Example 1: Cancel the refresh task for the ASYNC refresh materialized view `lo_mv1`.
-
-```SQL
-CANCEL REFRESH MATERIALIZED VIEW lo_mv1;
-CANCEL REFRESH MATERIALIZED VIEW lo_mv1 FORCE;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md b/docs/en/sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md
deleted file mode 100644
index b5f5855b3e811f..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md
+++ /dev/null
@@ -1,86 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE PIPE
-
-## Description
-
-Creates a new pipe for defining the INSERT INTO SELECT FROM FILES statement used by the system to load data from a specified source data file to a destination table. This command is supported from v3.2 onwards.
-
-## Syntax
-
-```SQL
-CREATE [OR REPLACE] PIPE [db_name.]<pipe_name> 
-[PROPERTIES ("<key>" = "<value>"[, "<key> = <value>" ...])]
-AS <INSERT_SQL>
-```
-
-StarRocks supports CREATE [OR REPLACE] PIPE from v3.2.3 onwards. When you use CREATE [OR REPLACE] PIPE to create a pipe and the pipe name specified in `pipe_name` is the same as the name of an existing pipe in the current database, the existing database is replaced by the new pipe.
-
-## Parameters
-
-### db_name
-
-The unique name of the database to which the pipe belongs.
-
-> **NOTICE**
->
-> Each pipe belongs to a specific database. If you drop the database to which a pipe belongs, the pipe is deleted along with the database, and cannot be recovered even if the database is recovered.
-
-### pipe_name
-
-The name of the pipe. The pipe name must be unique within the database in which the pipe is created. For the naming conventions, see [System limits](../../../reference/System_limit.md).
-
-### INSERT_SQL
-
-The INSERT INTO SELECT FROM FILES statement that is used to load data from the specified source data file to the destination table.
-
-For more information about the FILES() table function, see [FILES](../../../sql-reference/sql-functions/table-functions/files.md).
-
-### PROPERTIES
-
-A set of optional parameters that specify how to execute the pipe. Format: `"key" = "value"`.
-
-| Property      | Default value | Description                                                  |
-| :------------ | :------------ | :----------------------------------------------------------- |
-| AUTO_INGEST   | `TRUE`        | Whether to enable automatic incremental data loads. Valid values: `TRUE` and `FALSE`. If you set this parameter to `TRUE`, automatic incremental data loads are enabled. If you set this parameter to `FALSE`, the system loads only the source data file content specified at job creation and subsequent new or updated file content will not be loaded. For a bulk load, you can set this parameter to `FALSE`. |
-| POLL_INTERVAL | `300` second | The polling interval for automatic incremental data loads.   |
-| BATCH_SIZE    | `1GB`         | The size of data to be loaded as a batch. If you do not include a unit in the parameter value, the default unit byte is used. |
-| BATCH_FILES   | `256`         | The number of source data files to be loaded as a batch.     |
-
-## Examples
-
-Create a pipe named `user_behavior_replica` in the current database to load the data of the sample dataset `s3://starrocks-examples/user_behavior_ten_million_rows.parquet` to the `user_behavior_replica` table:
-
-```SQL
-CREATE PIPE user_behavior_replica
-PROPERTIES
-(
-    "AUTO_INGEST" = "TRUE"
-)
-AS
-INSERT INTO user_behavior_replica
-SELECT * FROM FILES
-(
-    "path" = "s3://starrocks-examples/user_behavior_ten_million_rows.parquet",
-    "format" = "parquet",
-    "aws.s3.region" = "us-east-1",
-    "aws.s3.access_key" = "AAAAAAAAAAAAAAAAAAAA",
-    "aws.s3.secret_key" = "BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB"
-); 
-```
-
-> **NOTE**
->
-> Substitute your credentials for `AAA` and `BBB` in the above command. Any valid `aws.s3.access_key` and `aws.s3.secret_key` can be used, as the object is readable by any AWS authenticated user.
-
-This example uses the IAM user-based authentication method and a Parquet file that has the same schema as the StarRocks table. For more information about the other authentication methods and the CREATE PIPE usage, see [Authenticate to AWS resources](../../../integrations/authenticate_to_aws_resources.md) and [FILES](../../../sql-reference/sql-functions/table-functions/files.md).
-
-## References
-
-- [ALTER PIPE](../data-manipulation/ALTER_PIPE.md)
-- [DROP PIPE](../data-manipulation/DROP_PIPE.md)
-- [SHOW PIPES](../data-manipulation/SHOW_PIPES.md)
-- [SUSPEND or RESUME PIPE](../data-manipulation/SUSPEND_or_RESUME_PIPE.md)
-- [RETRY FILE](../data-manipulation/RETRY_FILE.md)
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md b/docs/en/sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md
deleted file mode 100644
index 95c6e3ed7d3a37..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md
+++ /dev/null
@@ -1,968 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# CREATE ROUTINE LOAD
-
-:::tip
-Try Routine Load out in this [Quick Start](../../../quick_start/routine-load.md)
-:::
-
-Routine Load can continuously consume messages from Apache Kafka® and load data into StarRocks. Routine Load can consume CSV, JSON, and Avro (supported since v3.0.1) data from a Kafka cluster and access Kafka via multiple security protocols, including `plaintext`, `ssl`, `sasl_plaintext`, and `sasl_ssl`.
-
-This topic describes the syntax, parameters, and examples of the CREATE ROUTINE LOAD statement.
-
-> **NOTE**
->
-> - For information about the application scenarios, principles, and basic operations of Routine Load, see [Load data using Routine Load](../../../loading/RoutineLoad.md).
-> - You can load data into StarRocks tables only as a user who has the INSERT privilege on those StarRocks tables. If you do not have the INSERT privilege, follow the instructions provided in [GRANT](../account-management/GRANT.md) to grant the INSERT privilege to the user that you use to connect to your StarRocks cluster.
-
-## Syntax
-
-```SQL
-CREATE ROUTINE LOAD <database_name>.<job_name> ON <table_name>
-[load_properties]
-[job_properties]
-FROM data_source
-[data_source_properties]
-```
-
-## Parameters
-
-### `database_name`, `job_name`, `table_name`
-
-`database_name`
-
-Optional. The name of the StarRocks database.
-
-`job_name`
-
-Required. The name of the Routine Load job. A table may receive data from multiple Routine Load jobs.  We recommend that you set a meaningful Routine Load job name by using identifiable information, for example, Kafka topic name and the approximate job creation time, to distinguish multiple Routine Load jobs. The name of the Routine Load job must be unique within the same database.
-
-`table_name`
-
-Required. The name of the StarRocks table to which data is loaded.
-
-### `load_properties`
-
-Optional. The properties of the data. Syntax:
-
-```SQL
-[COLUMNS TERMINATED BY '<column_separator>'],
-[ROWS TERMINATED BY '<row_separator>'],
-[COLUMNS (<column1_name>[, <column2_name>, <column_assignment>, ... ])],
-[WHERE <expr>],
-[PARTITION (<partition1_name>[, <partition2_name>, ...])]
-[TEMPORARY PARTITION (<temporary_partition1_name>[, <temporary_partition2_name>, ...])]
-```
-
-`COLUMNS TERMINATED BY`
-
-The column separator for CSV-formatted data. The default column separator is `\t` (Tab). For example, you can use `COLUMNS TERMINATED BY ","` to specify the column separator as a comma.
-
-> **Note**
->
-> - Ensure that the column separator specified here is the same as the column separator in the data to be ingested.
-> - You can use a UTF-8 string, such as a comma (,), tab, or pipe (|), whose length does not exceed 50 bytes as a text delimiter.
-> - Null values are denoted by using `\N`. For example, a data record consists of three columns, and the data record holds data in the first and third columns but does not hold data in the second column. In this situation, you need to use `\N` in the second column to denote a null value. This means the record must be compiled as `a,\N,b` instead of `a,,b`. `a,,b` denotes that the second column of the record holds an empty string.
-
-`ROWS TERMINATED BY`
-
-The row separator for CSV-formatted data. The default row separator is `\n`.
-
-`COLUMNS`
-
-The mapping between the columns in the source data and the columns in the StarRocks table. For more information, see [Column mapping](#column-mapping) in this topic.
-
-- `column_name`: If a column of the source data can be mapped to a column of the StarRocks table without any computation, you only need to specify the column name. These columns can be referred to as mapped columns.
-- `column_assignment`: If a column of the source data cannot be directly mapped to a column of the StarRocks table, and the column's values must be computed by using functions before data loading, you must specify the computation function in `expr`. These columns can be referred to as derived columns.
-  It is recommended to place derived columns after mapped columns because StarRocks first parses mapped columns.
-
-`WHERE`
-
-The filter condition. Only data that meets the filter condition can be loaded into StarRocks. For example, if you only want to ingest rows whose `col1` value is greater than `100` and `col2` value is equal to `1000`, you can use `WHERE col1 > 100 and col2 = 1000`.
-
-> **NOTE**
->
-> The columns specified in the filter condition can be source columns or derived columns.
-
-`PARTITION`
-
-If a StarRocks table is distributed on partitions p0, p1, p2 and p3, and you want to load the data only to p1, p2, and p3 in StarRocks and filter out the data that will be stored in p0, then you can specify `PARTITION(p1, p2, p3)` as a filter condition. By default, if you do not specify this parameter, the data will be loaded into all the partitions. Example:
-
-```SQL
-PARTITION (p1, p2, p3)
-```
-
-`TEMPORARY PARTITION`
-
-The name of the [temporary partition](../../../table_design/Temporary_partition.md) into which you want to load data. You can specify multiple temporary partitions, which must be separated by commas (,).
-
-### `job_properties`
-
-Required. The properties of the load job. Syntax:
-
-```SQL
-PROPERTIES ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
-```
-
-| **Property**              | **Required** | **Description**                                              |
-| ------------------------- | ------------ | ------------------------------------------------------------ |
-| desired_concurrent_number | No           | The expected task parallelism of a single Routine Load job. Default value: `3`. The actual task parallelism is determined by the minimum value of the multiple parameters: `min(alive_be_number, partition_number, desired_concurrent_number, max_routine_load_task_concurrent_num)`. <ul><li>`alive_be_number`: the number of alive BE nodes.</li><li>`partition_number`: the number of partitions to be consumed.</li><li>`desired_concurrent_number`: the expected task parallelism of a single Routine Load  job. Default value: `3`.</li><li>`max_routine_load_task_concurrent_num`: the default maximum task parallelism of a Routine Load job, which is `5`. See [FE dynamic parameter](../../../administration/management/FE_configuration.md#configure-fe-dynamic-parameters).</li></ul>The maximum actual task parallelism is determined by either the number of alive BE nodes or the number of partitions to be consumed.|
-| max_batch_interval        | No           | The scheduling interval for a task, that is, how often a task is executed. Unit: seconds. Value range: `5` ~ `60`. Default value: `10`. It is recommended to set a value larger than `10`. If the scheduling is shorter than 10 seconds, too many tablet versions are generated due to an excessively high loading frequency. |
-| max_batch_rows            | No           | This property is only used to define the window of error detection. The window is the number of rows of data consumed by a single Routine Load task. The value is `10 * max_batch_rows`. The default value is `10 * 200000 = 2000000`. The Routine Load task detects error data in the error detection window. Error data refers to data that StarRocks cannot parse, such as invalid JSON-formatted data. |
-| max_error_number          | No           | The maximum number of error data rows allowed within an error detection window. If the number of error data rows exceeds this value, the load job will pause. You can execute [SHOW ROUTINE LOAD](./SHOW_ROUTINE_LOAD.md)  and view the error logs by using `ErrorLogUrls`. After that, you can correct the error in Kafka according to the error logs. The default value is `0`, which means error rows are not allowed. <br />**NOTE** <br /> <ul><li>Error data rows do not include data rows that are filtered out by the WHERE clause.</li><li>This parameter, along with the next parameter `max_filter_ratio`, controls the maximum number of error data records. When `max_filter_ratio` is not set, the value of this parameter takes effect. When `max_filter_ratio` is set, the load job pauses as soon as the number of error data record reaches either the threshold set by this parameter or the `max_filter_ratio` parameter.</li></ul>|
-|max_filter_ratio|No|The maximum error tolerance of the load job. The error tolerance is the maximum percentage of data records that can be filtered out due to inadequate data quality in all data records requested by the load job. Valid values: `0` to `1`. Default value: `0`.<br/>We recommend that you retain the default value `0`. This way, if unqualified data records are detected, the load job pauses, thereby ensuring data correctness.<br/>If you want to ignore unqualified data records, you can set this parameter to a value greater than `0`. This way, the load job can succeed even if the data file contains unqualified data records.  <br/>**NOTE**<br/><ul><li>Unqualified data records do not include data records that are filtered out by the WHERE clause.</li><li>This parameter, along with the last parameter `max_error_number`, controls the maximum number of error data records. When this parameter is not set, the value of the `max_error_number` parameter takes effect. When this parameter is set, the load job pauses as soon as the number of error data records reaches either the threshold set by this parameter or the `max_error_number` parameter.</li></ul>|
-| strict_mode               | No           | Specifies whether to enable the [strict mode](../../../loading/load_concept/strict_mode.md). Valid values: `true` and `false`. Default value: `false`. When the strict mode is enabled, if the value for a column in the loaded data is `NULL` but the target table does not allow a `NULL` value for this column, the data row will be filtered out. |
-| log_rejected_record_num | No | Specifies the maximum number of unqualified data rows that can be logged. This parameter is supported from v3.1 onwards. Valid values: `0`, `-1`, and any non-zero positive integer. Default value: `0`.<ul><li>The value `0` specifies that data rows that are filtered out will not be logged.</li><li>The value `-1` specifies that all data rows that are filtered out will be logged.</li><li>A non-zero positive integer such as `n` specifies that up to `n` data rows that are filtered out can be logged on each BE.</li></ul> |
-| timezone                  | No           | The time zone used by the load job. Default value: `Asia/Shanghai`. The value of this parameter affects the results returned by functions such as strftime(), alignment_timestamp(), and from_unixtime(). The time zone specified by this parameter is a session-level time zone. For more information, see [Configure a time zone](../../../administration/management/timezone.md). |
-| partial_update | No | Whether to use partial updates. Valid values: `TRUE` and `FALSE`. Default value: `FALSE`, indicating to disable this feature. |
-| merge_condition           | No           | Specifies the name of the column you want to use as the condition to determine whether to update data. Data will be updated only when the value of the data to be loaded into this column is greater than or equal to the current value of this column. For more information, see [Change data through loading](../../../loading/Load_to_Primary_Key_tables.md).<br />**NOTE**<br />Only Primary Key tables support conditional updates. The column that you specify cannot be a primary key column. |
-| format                    | No           | The format of the data to be loaded. Valid values: `CSV`, `JSON`, and `Avro` (supported since v3.0.1). Default value: `CSV`. |
-| trim_space                | No           | Specifies whether to remove spaces preceding and following column separators from the data file when the data file is in CSV format. Type: BOOLEAN. Default value: `false`.<br />For some databases, spaces are added to column separators when you export data as a CSV-formatted data file. Such spaces are called leading spaces or trailing spaces depending on their locations. By setting the `trim_space` parameter, you can enable StarRocks to remove such unnecessary spaces during data loading.<br />Note that StarRocks does not remove the spaces (including leading spaces and trailing spaces) within a field wrapped in a pair of `enclose`-specified characters. For example, the following field values use pipe (<code class="language-text">&#124;</code>) as the column separator and double quotation marks (`"`) as the `enclose`-specified character: <code class="language-text">&#124; "Love StarRocks" &#124;</code>. If you set `trim_space` to `true`, StarRocks processes the preceding field values as <code class="language-text">&#124;"Love StarRocks"&#124;</code>. |
-| enclose                   | No           | Specifies the character that is used to wrap the field values in the data file according to [RFC4180](https://www.rfc-editor.org/rfc/rfc4180) when the data file is in CSV format. Type: single-byte character. Default value: `NONE`. The most prevalent characters are single quotation mark (`'`) and double quotation mark (`"`).<br />All special characters (including row separators and column separators) wrapped by using the `enclose`-specified character are considered normal symbols. StarRocks can do more than RFC4180 as it allows you to specify any single-byte character as the `enclose`-specified character.<br />If a field value contains an `enclose`-specified character, you can use the same character to escape that `enclose`-specified character. For example, you set `enclose` to `"`, and a field value is `a "quoted" c`. In this case, you can enter the field value as `"a ""quoted"" c"` into the data file. |
-| escape                    | No           | Specifies the character that is used to escape various special characters, such as row separators, column separators, escape characters, and `enclose`-specified characters, which are then considered by StarRocks to be common characters and are parsed as part of the field values in which they reside. Type: single-byte character. Default value: `NONE`. The most prevalent character is slash (`\`), which must be written as double slashes (`\\`) in SQL statements.<br />**NOTE**<br />The character specified by `escape` is applied to both inside and outside of each pair of `enclose`-specified characters.<br />Two examples are as follows:<br /><ul><li>When you set `enclose` to `"` and `escape` to `\`, StarRocks parses `"say \"Hello world\""` into `say "Hello world"`.</li><li>Assume that the column separator is comma (`,`). When you set `escape` to `\`, StarRocks parses `a, b\, c` into two separate field values: `a` and `b, c`.</li></ul> |
-| strip_outer_array         | No           | Specifies whether to strip the outermost array structure of the JSON-formatted data. Valid values: `true` and `false`. Default value: `false`. In real-world business scenarios, JSON-formatted data may have an outermost array structure as indicated by a pair of square brackets `[]`. In this situation, we recommend that you set this parameter to `true`, so StarRocks removes the outermost square brackets `[]` and loads each inner array as a separate data record. If you set this parameter to `false`, StarRocks parses the entire JSON-formatted data into one array and loads the array as a single data record. Use the JSON-formatted data `[{"category" : 1, "author" : 2}, {"category" : 3, "author" : 4} ]` as an example. If you set this parameter to `true`, `{"category" : 1, "author" : 2}` and `{"category" : 3, "author" : 4}` are parsed as two separate data records and are loaded into two StarRocks data rows. |
-| jsonpaths                 | No           | The names of the fields that you want to load from JSON-formatted data. The value of this parameter is a valid JsonPath expression. For more information, see [StarRocks table contains derived columns whose values are generated by using expressions](#starrocks-table-contains-derived-columns-whose-values-are-generated-by-using-expressions)) in this topic. |
-| json_root                 | No           | The root element of the JSON-formatted data to load. StarRocks extracts the elements of the root node through `json_root` for parsing. By default, the value of this parameter is empty, indicating that all JSON-formatted data will be loaded. For more information, see [Specify the root element of the JSON-formatted data to be loaded](#specify-the-root-element-of-the-json-formatted-data-to-be-loaded) in this topic. |
-| task_consume_second | No | The maximum time for each Routine Load task within the specified Routine Load job to consume data. Unit: second. Unlike the [FE dynamic parameters](../../../administration/management/FE_configuration.md) `routine_load_task_consume_second` (which applies to all Routine Load jobs within the cluster), this parameter is specific to an individual Routine Load job, which is more flexible. This parameter is supported since v3.1.0.<ul> <li>When `task_consume_second` and `task_timeout_second` are not configured, StarRocks uses the FE dynamic parameters `routine_load_task_consume_second` and `routine_load_task_timeout_second` to control the load behavior.</li> <li>When only `task_consume_second` is configured, the default value for `task_timeout_second` is calculated as `task_consume_second` * 4.</li> <li>When only `task_timeout_second` is configured, the default value for `task_consume_second` is calculated as `task_timeout_second`/4.</li> </ul> |
-|task_timeout_second|No|The timeout duration for each Routine Load task within the specified Routine Load job. Unit: second. Unlike the [FE dynamic parameter](../../../administration/management/FE_configuration.md) `routine_load_task_timeout_second` (which applies to all Routine Load jobs within the cluster), this parameter is specific to an individual Routine Load job, which is more flexible. This parameter is supported since v3.1.0. <ul> <li>When `task_consume_second` and `task_timeout_second` are not configured, StarRocks uses the FE dynamic parameters `routine_load_task_consume_second` and `routine_load_task_timeout_second` to control the load behavior.</li> <li>When only `task_timeout_second` is configured, the default value for `task_consume_second` is calculated as `task_timeout_second`/4.</li> <li>When only `task_consume_second` is configured, the default value for `task_timeout_second` is calculated as `task_consume_second` * 4.</li> </ul>|
-
-### `data_source`, `data_source_properties`
-
-Required. The data source and relevant properties.
-
-```sql
-FROM <data_source>
- ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
-```
-
-`data_source`
-
-Required. The source of the data you want to load. Valid value: `KAFKA`.
-
-`data_source_properties`
-
-The properties of the data source.
-
-| Property          | Required | Description                                                  |
-| ----------------- | -------- | ------------------------------------------------------------ |
-| kafka_broker_list | Yes      | Kafka's broker connection information. The format is `<kafka_broker_ip>:<broker_ port>`. Multiple brokers are separated by commas (,). The default port used by Kafka brokers is `9092`. Example:`"kafka_broker_list" = ""xxx.xx.xxx.xx:9092,xxx.xx.xxx.xx:9092"`. |
-| kafka_topic       | Yes      | The  Kafka topic to be consumed. A Routine Load job can only consume messages from one topic. |
-| kafka_partitions  | No       | The Kafka partitions to be consumed, for example, `"kafka_partitions" = "0, 1, 2, 3"`. If this property is not specified, all partitions are consumed by default. |
-| kafka_offsets     | No       | The starting offset from which to consume data in a Kafka partition as specified in `kafka_partitions`. If this property is not specified, the Routine Load job consumes data starting from the latest offsets in `kafka_partitions`. Valid values:<ul><li>A specific offset: consumes data starting from a specific offset.</li><li>`OFFSET_BEGINNING`: consumes data starting from the earliest offset possible.</li><li>`OFFSET_END`: consumes data starting from the latest offset.</li></ul> Multiple starting offsets are separated by commas (,), for example, `"kafka_offsets" = "1000, OFFSET_BEGINNING, OFFSET_END, 2000"`.|
-| property.kafka_default_offsets| No| The default starting offset for all consumer partitions. The supported values for this property are same as those for the `kafka_offsets` property.|
-| confluent.schema.registry.url|No |The URL of the Schema Registry where the Avro schema is registered. StarRocks retrieves the Avro schema by using this URL. The format is as follows:<br />`confluent.schema.registry.url = http[s]://[<schema-registry-api-key>:<schema-registry-api-secret>@]<hostname or ip address>[:<port>]`|
-
-#### More data source-related properties
-
-You can specify additional data source (Kafka) related properties, which are equivalent to using the Kafka command line `--property`. For more supported properties, see the properties for a Kafka consumer client in [librdkafka configuration properties](https://github.com/confluentinc/librdkafka/blob/master/CONFIGURATION.md).
-
-> **NOTE**
->
-> If the value of a property is a file name, add the keyword `FILE:` preceding the file name. For information about how to create a file, see [CREATE FILE](../Administration/CREATE_FILE.md).
-
-- **Specify the default initial offset for all the partitions to be consumed**
-
-```SQL
-"property.kafka_default_offsets" = "OFFSET_BEGINNING"
-```
-
-- **Specify the ID of the consumer group used by the Routine Load job**
-
-```SQL
-"property.group.id" = "group_id_0"
-```
-
-If `property.group.id` is not specified, StarRocks generates a random value based on the name of the Routine Load job, in the format of `{job_name}_{random uuid}`, such as `simple_job_0a64fe25-3983-44b2-a4d8-f52d3af4c3e8`.
-
-- **Specify the security protocol and relevant parameters used by BE to access Kafka**
-
-  The security protocol can be specified as `plaintext` (default), `ssl`, `sasl_plaintext`, or `sasl_ssl`. And you need to configure the related parameters according to the specified security protocol.
-
-  When the security protocol is set to `sasl_plaintext` or `sasl_ssl`, the following SASL authentication mechanisms are supported:
-
-  - PLAIN
-  - SCRAM-SHA-256 and SCRAM-SHA-512
-  - OAUTHBEARER
-  - GSSAPI (Kerberos)
-
-  **Examples:**
-
-  - Access Kafka using the SSL security protocol:
-
-    ```SQL
-    "property.security.protocol" = "ssl", -- Specify the security protocol as SSL.
-    "property.ssl.ca.location" = "FILE:ca-cert", -- File or directory path to CA certificate(s) for verifying the kafka broker's key.
-    -- If the Kafka server enables client authentication, the following three parameters are also required:
-    "property.ssl.certificate.location" = "FILE:client.pem", -- Path to the client's public key used for authentication.
-    "property.ssl.key.location" = "FILE:client.key", -- Path to the client's private key used for authentication.
-    "property.ssl.key.password" = "xxxxxx" -- Password for the client's private key.
-    ```
-
-  - Access Kafka using the SASL_PLAINTEXT security protocol and SASL/PLAIN authentication mechanism:
-
-    ```SQL
-    "property.security.protocol" = "SASL_PLAINTEXT", -- Specify the security protocol as SASL_PLAINTEXT.
-    "property.sasl.mechanism" = "PLAIN", -- Specify the SASL mechanism as PLAIN which is a simple username/password authentication mechanism.
-    "property.sasl.username" = "admin",  -- SASL username.
-    "property.sasl.password" = "xxxxxx"  -- SASL password.
-    ```
-
-  - Access Kafka using the SASL_PLAINTEXT security protocol and SASL/GSSAPI (Kerberos) authentication mechanism:
-
-    ```sql
-    "property.security.protocol" = "SASL_PLAINTEXT", -- Specify the security protocol as SASL_PLAINTEXT.
-    "property.sasl.mechanism" = "GSSAPI", -- Specify the SASL authentication mechanism as GSSAPI. Default value is GSSAPI.
-    "property.sasl.kerberos.service.name" = "kafka", -- The broker service name. Default value is kafka.
-    "property.sasl.kerberos.keytab" = "/home/starrocks/starrocks.keytab", -- The client keytab location.
-    "property.sasl.kerberos.principal" = "starrocks@YOUR.COM" -- The Kerberos principal.
-    ```
-
-    :::note
-
-    - Since StarRocks v3.1.4, SASL/GSSAPI (Kerberos) authentication is supported.
-    - SASL related modules need to be installed on the BE machine.
-
-        ```bash
-        # Debian/Ubuntu:
-        sudo apt-get install libsasl2-modules-gssapi-mit libsasl2-dev
-        # CentOS/Redhat:
-        sudo yum install cyrus-sasl-gssapi cyrus-sasl-devel
-        ```
-
-    :::
-
-### FE and BE configuration items
-
-For FE and BE configuration items related to Routine Load, see [configuration items](../../../administration/management/FE_configuration.md).
-
-## Column mapping
-
-### Configure column mapping for loading CSV-formatted data
-
-If the columns of the  CSV-formatted data can be mapped one on one in sequence to the columns of the StarRocks table, you do not need to configure the column mapping between the data and the StarRocks table.
-
-If the columns of the CSV-formatted data cannot be mapped one on one in sequence to the columns of the StarRocks table, you need to use the `columns` parameter to configure the column mapping between the data file and the StarRocks table. This includes the following two use cases:
-
-- **Same number of columns but different column sequence. Also, the data from the data file does not need to be computed by functions before it is loaded into the matching StarRocks table columns.**
-
-  - In the `columns` parameter, you need to specify the names of the StarRocks table columns in the same sequence as how the data file columns are arranged.
-
-  - For example, the StarRocks table consists of three columns, which are `col1`, `col2`, and `col3` in sequence, and the data file also consists of three columns, which can be mapped to the StarRocks table columns `col3`, `col2`, and `col1` in sequence. In this case, you need to specify `"columns: col3, col2, col1"`.
-
-- **Different number of columns and different column sequence. Also, the data from the data file needs to be computed by functions before it is loaded into the matching StarRocks table columns.**
-
-  In the `columns` parameter, you need to specify the names of the StarRocks table columns in the same sequence as how the data file columns are arranged and specify the functions you want to use to compute the data. Two examples are as follows:
-
-  - The StarRocks table consists of three columns, which are `col1`, `col2`, and `col3` in sequence. The data file consists of four columns, among which the first three columns can be mapped in sequence to the StarRocks table columns `col1`, `col2`, and `col3` and the fourth column cannot be mapped to any of the StarRocks table columns. In this case, you need to temporarily specify a name for the fourth column of the data file, and the temporary name must be different from any of the StarRocks table column names. For example, you can specify `"columns: col1, col2, col3, temp"`, in which the fourth column of the data file is temporarily named `temp`.
-  - The StarRocks table consists of three columns, which are `year`, `month`, and `day` in sequence. The data file consists of only one column that accommodates date and time values in `yyyy-mm-dd hh:mm:ss` format. In this case, you can specify `"columns: col, year = year(col), month=month(col), day=day(col)"`, in which `col` is the temporary name of the data file column and the functions `year = year(col)`, `month=month(col)`, and `day=day(col)` are used to extract data from the data file column `col` and loads the data into the mapping StarRocks table columns. For example, `year = year(col)` is used to extract the `yyyy` data from the data file column `col` and loads the data into the StarRocks table column `year`.
-
-For more examples, see [Configure column mapping](#configure-column-mapping).
-
-### Configure column mapping for loading JSON-formatted or Avro-formatted data
-
-> **NOTE**
->
-> Since v3.0.1, StarRocks supports loading Avro data by using Routine Load. When you load JSON or Avro data, the configuration for column mapping and transformation is the same. Therefore, in this section, JSON data is used as an example to introduce the configuration.
-
-If the keys of the JSON-formatted data have the same names as the columns of the StarRocks table, you can load the JSON-formatted data by using the simple mode. In simple mode, you do not need to specify the `jsonpaths` parameter. This mode requires that the JSON-formatted data must be an object as indicated by curly brackets `{}`, such as `{"category": 1, "author": 2, "price": "3"}`. In this example, `category`, `author`, and `price` are key names, and these keys can be mapped one on one by name to the columns `category`, `author`, and `price` of the StarRocks table. For examples, please see [simple mode](#starrocks-table-column-names-consistent-with-json-key-names).
-
-If the keys of the JSON-formatted data have different names than the columns of the StarRocks table, you can load the JSON-formatted data by using the matched mode. In matched mode, you need to use the `jsonpaths` and `COLUMNS` parameters to specify the column mapping between the JSON-formatted data and the StarRocks table:
-
-- In the `jsonpaths` parameter, specify the JSON keys in the sequence as how they are arranged in the JSON-formatted data.
-- In the `COLUMNS` parameter, specify the mapping between the JSON keys and the StarRocks table columns:
-  - The column names specified in the `COLUMNS` parameter are mapped one on one in sequence to the JSON-formatted data.
-  - The column names specified in the `COLUMNS` parameter are mapped one on one by name to the StarRocks table columns.
-
-For examples, see [StarRocks table contains derived columns whose values are generated by using expressions](#starrocks-table-contains-derived-columns-whose-values-are-generated-by-using-expressions).
-
-## Examples
-
-### Load  CSV-formatted data
-
-This section uses  CSV-formatted data as an example to describe how you can employ various parameter settings and combinations to meet your diverse loading requirements.
-
-**Prepare a dataset**
-
-Suppose you want to load CSV-formatted data from a Kafka topic named `ordertest1`.Every message in the dataset includes six columns: order ID, payment date, customer name, nationality, gender, and price.
-
-```plaintext
-2020050802,2020-05-08,Johann Georg Faust,Deutschland,male,895
-2020050802,2020-05-08,Julien Sorel,France,male,893
-2020050803,2020-05-08,Dorian Grey,UK,male,1262
-2020050901,2020-05-09,Anna Karenina,Russia,female,175
-2020051001,2020-05-10,Tess Durbeyfield,US,female,986
-2020051101,2020-05-11,Edogawa Conan,japan,male,8924
-```
-
-**Create a table**
-
-According to the columns of CSV-formatted data, create a table named `example_tbl1` in the database `example_db`.
-
-```SQL
-CREATE TABLE example_db.example_tbl1 ( 
-    `order_id` bigint NOT NULL COMMENT "Order ID",
-    `pay_dt` date NOT NULL COMMENT "Payment date", 
-    `customer_name` varchar(26) NULL COMMENT "Customer name", 
-    `nationality` varchar(26) NULL COMMENT "Nationality", 
-    `gender` varchar(26) NULL COMMENT "Gender", 
-    `price` double NULL COMMENT "Price") 
-DUPLICATE KEY (order_id,pay_dt) 
-DISTRIBUTED BY HASH(`order_id`); 
-```
-
-#### Consume data starting from specified offsets for specified partitions
-
-If the Routine Load job needs to consume data starting from specified partitions and offsets, you need to configure the parameters `kafka_partitions` and `kafka_offsets`.
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest1",
-    "kafka_partitions" ="0,1,2,3,4", -- partitions to be consumed
-    "kafka_offsets" = "1000, OFFSET_BEGINNING, OFFSET_END, 2000" -- corresponding initial offsets
-);
-```
-
-#### Improve loading performance by increasing task parallelism
-
-To improve loading performance and avoid accumulative consumption, you can increase task parallelism by increasing the `desired_concurrent_number` value when you create the Routine Load job. Task parallelism allows splitting one Routine Load job into as many parallel tasks as possible.
-
-> **Note**
->
-> For more ways to improve loading performance, see [Routine Load FAQ](../../../faq/loading/Routine_load_faq.md).
-
-Note that the actual task parallelism is determined by the minimum value among the following multiple parameters:
-
-```SQL
-min(alive_be_number, partition_number, desired_concurrent_number, max_routine_load_task_concurrent_num)
-```
-
-> **Note**
->
-> The maximum actual task parallelism is either the number of alive BE nodes or the number of partitions to be consumed.
-
-Therefore, when the number of alive BE nodes and the number of partitions to be consumed are greater than the values of the other two parameters `max_routine_load_task_concurrent_num` and `desired_concurrent_number`, you can increase the values of the other two parameters to increase the actual task parallelism.
-
-Assume that the number of partitions to be consumed is 7, the number of alive BE nodes is 5, and `max_routine_load_task_concurrent_num` is the default value `5`. If you want to increase the actual task parallelism, you can set `desired_concurrent_number` to `5` (the default value is `3`). In this case, the actual task parallelism `min(5,7,5,5)` is configured at `5`.
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
-PROPERTIES
-(
-"desired_concurrent_number" = "5" -- set the value of desired_concurrent_number to 5
-)
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest1"
-);
-```
-
-#### Configure column mapping
-
-If the sequence of columns in the CSV-formatted data is inconsistent with the columns in the target table, assuming that the fifth column in the CSV-formatted data does not need to be imported to the target table, you need to specify the column mapping between the CSV-formatted data and the target table through the `COLUMNS` parameter.
-
-**Target database and table**
-
-Create the target table `example_tbl2` in the target database `example_db` according to the columns in the CSV-formatted data. In this scenario, you need to create five columns corresponding to the five columns in the CSV-formatted data, except for the fifth column that stores gender.
-
-```SQL
-CREATE TABLE example_db.example_tbl2 ( 
-    `order_id` bigint NOT NULL COMMENT "Order ID",
-    `pay_dt` date NOT NULL COMMENT "Payment date", 
-    `customer_name` varchar(26) NULL COMMENT "Customer name", 
-    `nationality` varchar(26) NULL COMMENT "Nationality", 
-    `price` double NULL COMMENT "Price"
-) 
-DUPLICATE KEY (order_id,pay_dt) 
-DISTRIBUTED BY HASH(order_id); 
-```
-
-**Routine Load job**
-
-In this example, since the fifth column in the CSV-formatted data does not need to be loaded to the target table, the fifth column is temporarily named `temp_gender` in `COLUMNS`, and the other columns are directly mapped to the table `example_tbl2`.
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl2_ordertest1 ON example_tbl2
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, temp_gender, price)
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest1"
-);
-```
-
-#### Set filter conditions
-
-If you want to load only data that meets certain conditions, you can set filter conditions in the `WHERE` clause, for example, `price > 100.`
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl2_ordertest1 ON example_tbl2
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price),
-WHERE price > 100 -- set the filter condition
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest1"
-);
-```
-
-#### Enable strict mode to filter out rows with NULL values
-
-In `PROPERTIES`, you can set `"strict_mode" = "true"`, which means that the Routine Load job is in strict mode.  If there is a `NULL` value in a source column, but the destination StarRocks table column does not allow NULL values, the row that holds a NULL value in the source column is filtered out.
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
-PROPERTIES
-(
-"strict_mode" = "true" -- enable the strict mode
-)
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest1"
-);
-```
-
-#### Set error tolerance
-
-If your business scenario has low tolerance for unqualified data, you need to set the error detection window and the maximum number of error data rows by configuring the parameters `max_batch_rows` and `max_error_number`. When the number of error data rows within an error detection window exceeds the value of `max_error_number`, the Routine Load job pauses.
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
-PROPERTIES
-(
-"max_batch_rows" = "100000",-- The value of max_batch_rows multiplied by 10 equals the error detection window.
-"max_error_number" = "100" -- The maximum number of error data rows allowed within an error detection window.
-)
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest1"
-);
-```
-
-#### Specify the security protocol as SSL and configure the related parameters
-
-If you need to specify the security protocol as SSL used by BE to access Kafka, you need to configure `"property.security.protocol" = "ssl"` and related parameters.
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
-PROPERTIES
-(
--- Specify the security protocol as SSL.
-"property.security.protocol" = "ssl",
--- The location of the CA certificate.
-"property.ssl.ca.location" = "FILE:ca-cert",
--- If authentication is enabled for Kafka clients, you need to configure the following properties:
--- The location of the Kafka client's public key.
-"property.ssl.certificate.location" = "FILE:client.pem",
--- The location of the Kafka client's private key.
-"property.ssl.key.location" = "FILE:client.key",
--- The password to the Kafka client's private key.
-"property.ssl.key.password" = "abcdefg"
-)
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest1"
-);
-```
-
-#### Setting trim_space, enclose, and escape
-
-Suppose you want to load CSV-formatted data from a Kafka topic named `test_csv`. Every message in the dataset includes six columns: order ID, payment date, customer name, nationality, gender, and price.
-
-```Plaintext
- "2020050802" , "2020-05-08" , "Johann Georg Faust" , "Deutschland" , "male" , "895"
- "2020050802" , "2020-05-08" , "Julien Sorel" , "France" , "male" , "893"
- "2020050803" , "2020-05-08" , "Dorian Grey\,Lord Henry" , "UK" , "male" , "1262"
- "2020050901" , "2020-05-09" , "Anna Karenina" , "Russia" , "female" , "175"
- "2020051001" , "2020-05-10" , "Tess Durbeyfield" , "US" , "female" , "986"
- "2020051101" , "2020-05-11" , "Edogawa Conan" , "japan" , "male" , "8924"
-```
-
-If you want to load all data from the Kafka topic `test_csv` into `example_tbl1`, with the intention of removing the spaces preceding and following column separators and setting `enclose` to `"` and `escape` to `\`, run the following command:
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl1_test_csv ON example_tbl1
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
-PROPERTIES
-(
-    "trim_space"="true",
-    "enclose"="\"",
-    "escape"="\\",
-)
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic"="test_csv",
-    "property.kafka_default_offsets"="OFFSET_BEGINNING"
-);
-```
-
-### Load  JSON-formatted data
-
-#### StarRocks table column names consistent with JSON key names
-
-**Prepare a dataset**
-
-For example, the following JSON-formatted data exists in the Kafka topic `ordertest2`.
-
-```SQL
-{"commodity_id": "1", "customer_name": "Mark Twain", "country": "US","pay_time": 1589191487,"price": 875}
-{"commodity_id": "2", "customer_name": "Oscar Wilde", "country": "UK","pay_time": 1589191487,"price": 895}
-{"commodity_id": "3", "customer_name": "Antoine de Saint-Exupéry","country": "France","pay_time": 1589191487,"price": 895}
-```
-
-> **Note** Each JSON object must be in one Kafka message. Otherwise, an error that indicates a failure in parsing JSON-formatted data occurs.
-
-**Target database and table**
-
-Create table `example_tbl3` in the target database `example_db` in the StarRocks cluster. The column names are consistent with the keys names in the JSON-formatted data.
-
-```SQL
-CREATE TABLE example_db.example_tbl3 ( 
-    commodity_id varchar(26) NULL, 
-    customer_name varchar(26) NULL, 
-    country varchar(26) NULL, 
-    pay_time bigint(20) NULL, 
-    price double SUM NULL COMMENT "Price") 
-AGGREGATE KEY(commodity_id,customer_name,country,pay_time)
-DISTRIBUTED BY HASH(commodity_id); 
-```
-
-**Routine Load job**
-
-You can use the simple mode for the Routine Load job. That is, you do not need to specify `jsonpaths` and `COLUMNS` parameters when creating the Routine Load job. StarRocks extracts the keys of JSON-formatted data in the topic `ordertest2` of the Kafka cluster according to the column names of the target table `example_tbl3` and loads the JSON-formatted data into the target table.
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl3_ordertest2 ON example_tbl3
-PROPERTIES
-(
-    "format" = "json"
- )
-FROM KAFKA
-(
-    "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest2"
-);
-```
-
-> **Note**
->
-> - If the outermost layer of the JSON-formatted data is an array structure, you need to set `"strip_outer_array"="true"` in `PROPERTIES` to strip the outermost array structure. Additionally, when you need to specify `jsonpaths`, the root element of the entire JSON-formatted data is the flattened JSON object because the outermost array structure of the JSON-formatted data is stripped.
-> - You can use `json_root` to specify the root element of the JSON-formatted data.
-
-#### StarRocks table contains derived columns whose values are generated by using expressions
-
-**Prepare a dataset**
-
-For example, the following JSON-formatted data exists in the topic `ordertest2` of the Kafka cluster.
-
-```SQL
-{"commodity_id": "1", "customer_name": "Mark Twain", "country": "US","pay_time": 1589191487,"price": 875}
-{"commodity_id": "2", "customer_name": "Oscar Wilde", "country": "UK","pay_time": 1589191487,"price": 895}
-{"commodity_id": "3", "customer_name": "Antoine de Saint-Exupéry","country": "France","pay_time": 1589191487,"price": 895}
-```
-
-**Target database and table**
-
-Create a table named `example_tbl4` in the database `example_db` in the StarRocks cluster. The column `pay_dt` is a derived column whose values are generated by computing values of the key `pay_time` in the JSON-formatted data.
-
-```SQL
-CREATE TABLE example_db.example_tbl4 ( 
-    `commodity_id` varchar(26) NULL, 
-    `customer_name` varchar(26) NULL, 
-    `country` varchar(26) NULL,
-    `pay_time` bigint(20) NULL,  
-    `pay_dt` date NULL, 
-    `price` double SUM NULL) 
-AGGREGATE KEY(`commodity_id`,`customer_name`,`country`,`pay_time`,`pay_dt`) 
-DISTRIBUTED BY HASH(`commodity_id`); 
-```
-
-**Routine Load job**
-
-You can use the matched mode for the Routine Load job. That is, you need to specify `jsonpaths` and `COLUMNS` parameters when creating the Routine Load job.
-
-You need to specify the keys of the JSON-formatted data and arrange them in sequence in the `jsonpaths` parameter.
-
-And since the values in the key `pay_time` of the JSON-formatted data need to be converted to the DATE type before the values are stored in the `pay_dt` column of the `example_tbl4` table, you need to specify the computation by using `pay_dt=from_unixtime(pay_time,'%Y%m%d')` in `COLUMNS`. The values of other keys in the JSON-formatted data can be directly mapped to the `example_tbl4` table.
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl4_ordertest2 ON example_tbl4
-COLUMNS(commodity_id, customer_name, country, pay_time, pay_dt=from_unixtime(pay_time, '%Y%m%d'), price)
-PROPERTIES
-(
-    "format" = "json",
-    "jsonpaths" = "[\"$.commodity_id\",\"$.customer_name\",\"$.country\",\"$.pay_time\",\"$.price\"]"
- )
-FROM KAFKA
-(
-    "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest2"
-);
-```
-
-> **Note**
->
-> - If the outermost layer of the JSON data is an array structure, you need to set `"strip_outer_array"="true"` in the `PROPERTIES` to strip the outermost array structure. Additionally, when you need to specify `jsonpaths`, the root element of the entire JSON data is the flattened JSON object because the outermost array structure of the JSON data is stripped.
-> - You can use `json_root` to specify the root element of the JSON-formatted data.
-
-#### StarRocks table contains derived column whose values are generated by using CASE expression
-
-**Prepare a dataset**
-
-For example, the following JSON-formatted data exists in the Kafka topic `topic-expr-test`.
-
-```JSON
-{"key1":1, "key2": 21}
-{"key1":12, "key2": 22}
-{"key1":13, "key2": 23}
-{"key1":14, "key2": 24}
-```
-
-**Target database and table**
-
-Create a table named `tbl_expr_test` in the database `example_db` in the StarRocks cluster. The target table `tbl_expr_test` contains two columns, where the values of the `col2` column need to be computed by using case expression on JSON data.
-
-```SQL
-CREATE TABLE tbl_expr_test (
-    col1 string, col2 string)
-DISTRIBUTED BY HASH (col1);
-```
-
-**Routine Load job**
-
-Because the values in the `col2` column in the target table are generated using a CASE expression, you need to specify the corresponding expression in the `COLUMNS` parameter for the Routine load job.
-
-```SQL
-CREATE ROUTINE LOAD rl_expr_test ON tbl_expr_test
-COLUMNS (
-      key1,
-      key2,
-      col1 = key1,
-      col2 = CASE WHEN key1 = "1" THEN "key1=1" 
-                  WHEN key1 = "12" THEN "key1=12"
-                  ELSE "nothing" END) 
-PROPERTIES ("format" = "json")
-FROM KAFKA
-(
-    "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "topic-expr-test"
-);
-```
-
-**Query StarRocks table**
-
-Query the StarRocks table. The result shows that the values in the `col2` column are the output of the CASE expression.
-
-```SQL
-MySQL [example_db]> SELECT * FROM tbl_expr_test;
-+------+---------+
-| col1 | col2    |
-+------+---------+
-| 1    | key1=1  |
-| 12   | key1=12 |
-| 13   | nothing |
-| 14   | nothing |
-+------+---------+
-4 rows in set (0.015 sec)
-```
-
-#### Specify the root element of the JSON-formatted data to be loaded
-
-You need to use `json_root` to specify the root element of the JSON-formatted data to be loaded and the value must be a valid JsonPath expression.
-
-**Prepare a dataset**
-
-For example, the following JSON-formatted data exists in the topic `ordertest3` of the Kafka cluster. And the root element of the JSON-formatted data to be loaded is `$.RECORDS`.
-
-```SQL
-{"RECORDS":[{"commodity_id": "1", "customer_name": "Mark Twain", "country": "US","pay_time": 1589191487,"price": 875},{"commodity_id": "2", "customer_name": "Oscar Wilde", "country": "UK","pay_time": 1589191487,"price": 895},{"commodity_id": "3", "customer_name": "Antoine de Saint-Exupéry","country": "France","pay_time": 1589191487,"price": 895}]}
-```
-
-**Target database and table**
-
-Create a table named `example_tbl3` in the database `example_db` in the StarRocks cluster.
-
-```SQL
-CREATE TABLE example_db.example_tbl3 ( 
-    commodity_id varchar(26) NULL, 
-    customer_name varchar(26) NULL, 
-    country varchar(26) NULL, 
-    pay_time bigint(20) NULL, 
-    price double SUM NULL) 
-AGGREGATE KEY(commodity_id,customer_name,country,pay_time) 
-ENGINE=OLAP
-DISTRIBUTED BY HASH(commodity_id); 
-```
-
-**Routine Load job**
-
-You can set `"json_root" = "$.RECORDS"` in `PROPERTIES` to specify the root element of the JSON-formatted data to be loaded. Also, since the JSON-formatted data to be loaded is in an array structure, you must also set `"strip_outer_array" = "true"` to strip the outermost array structure.
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl3_ordertest3 ON example_tbl3
-PROPERTIES
-(
-    "format" = "json",
-    "json_root" = "$.RECORDS",
-    "strip_outer_array" = "true"
- )
-FROM KAFKA
-(
-    "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest2"
-);
-```
-
-### Load Avro-formatted data
-
-Since v3.0.1, StarRocks supports loading Avro data by using Routine Load.
-
-#### Avro schema is simple
-
-Suppose the Avro schema is relatively simple, and you need to load all fields of the Avro data.
-
-**Prepare a dataset**
-
-- **Avro schema**
-
-    1. Create the following Avro schema file `avro_schema1.avsc`:
-
-        ```json
-        {
-            "type": "record",
-            "name": "sensor_log",
-            "fields" : [
-                {"name": "id", "type": "long"},
-                {"name": "name", "type": "string"},
-                {"name": "checked", "type" : "boolean"},
-                {"name": "data", "type": "double"},
-                {"name": "sensor_type", "type": {"type": "enum", "name": "sensor_type_enum", "symbols" : ["TEMPERATURE", "HUMIDITY", "AIR-PRESSURE"]}}  
-            ]
-        }
-        ```
-
-    2. Register the Avro schema in the [Schema Registry](https://docs.confluent.io/platform/current/schema-registry/index.html).
-
-- **Avro data**
-
-Prepare the Avro data and send it to the Kafka topic `topic_1`.
-
-**Target database and table**
-
-According to the fields of Avro data, create a table `sensor_log1` in the target database `sensor` in the StarRocks cluster. The column names of the table must match the field names in the Avro data. For the data types mapping when Avro data is loaded into StarRocks, see [Data types mapping](#Data types mapping).
-
-```SQL
-CREATE TABLE sensor.sensor_log1 ( 
-    `id` bigint NOT NULL COMMENT "sensor id",
-    `name` varchar(26) NOT NULL COMMENT "sensor name", 
-    `checked` boolean NOT NULL COMMENT "checked", 
-    `data` double NULL COMMENT "sensor data", 
-    `sensor_type` varchar(26) NOT NULL COMMENT "sensor type"
-) 
-ENGINE=OLAP 
-DUPLICATE KEY (id) 
-DISTRIBUTED BY HASH(`id`); 
-```
-
-**Routine Load job**
-
-You can use the simple mode for the Routine Load job. That is, you do not need to specify the parameter `jsonpaths` when creating the Routine Load job. Execute the following statement to submit a Routine Load job named `sensor_log_load_job1` to consume the Avro messages in the Kafka topic `topic_1` and load the data into the table `sensor_log1` in the database `sensor`.
-
-```sql
-CREATE ROUTINE LOAD sensor.sensor_log_load_job1 ON sensor_log1  
-PROPERTIES  
-(  
-  "format" = "avro"  
-)  
-FROM KAFKA  
-(  
-  "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>,...",
-  "confluent.schema.registry.url" = "http://172.xx.xxx.xxx:8081",  
-  "kafka_topic"= "topic_1",  
-  "kafka_partitions" = "0,1,2,3,4,5",  
-  "property.kafka_default_offsets" = "OFFSET_BEGINNING"  
-);
-```
-
-#### Avro schema contains a nested record-type field
-
-Suppose the Avro schema contains a nested record-type field, and you need to load the subfield in a nested record-type field into StarRocks.
-
-**Prepare a dataset**
-
-- **Avro schema**
-
-    1. Create the following Avro schema file `avro_schema2.avsc`. The outer Avro record includes five fields which are `id`, `name`, `checked`, `sensor_type`, and `data` in sequence. And the field `data` has a nested record `data_record`.
-
-        ```JSON
-        {
-            "type": "record",
-            "name": "sensor_log",
-            "fields" : [
-                {"name": "id", "type": "long"},
-                {"name": "name", "type": "string"},
-                {"name": "checked", "type" : "boolean"},
-                {"name": "sensor_type", "type": {"type": "enum", "name": "sensor_type_enum", "symbols" : ["TEMPERATURE", "HUMIDITY", "AIR-PRESSURE"]}},
-                {"name": "data", "type": 
-                    {
-                        "type": "record",
-                        "name": "data_record",
-                        "fields" : [
-                            {"name": "data_x", "type" : "boolean"},
-                            {"name": "data_y", "type": "long"}
-                        ]
-                    }
-                }
-            ]
-        }
-        ```
-
-    2. Register the Avro schema in the [Schema Registry](https://docs.confluent.io/platform/current/schema-registry/index.html).
-
-- **Avro data**
-
-Prepare the Avro data and send it to the Kafka topic `topic_2`.
-
-**Target database and table**
-
-According to the fields of Avro data, create a table `sensor_log2` in the target database `sensor` in the StarRocks cluster.
-
-Suppose that in addition to loading the fields `id`, `name`, `checked`, and `sensor_type` of the outer Record, you also need to load the subfield `data_y` in the nested Record `data_record`.
-
-```sql
-CREATE TABLE sensor.sensor_log2 ( 
-    `id` bigint NOT NULL COMMENT "sensor id",
-    `name` varchar(26) NOT NULL COMMENT "sensor name", 
-    `checked` boolean NOT NULL COMMENT "checked", 
-    `sensor_type` varchar(26) NOT NULL COMMENT "sensor type",
-    `data_y` long NULL COMMENT "sensor data" 
-) 
-ENGINE=OLAP 
-DUPLICATE KEY (id) 
-DISTRIBUTED BY HASH(`id`); 
-```
-
-**Routine Load job**
-
-Submit the load job, use `jsonpaths` to specify the fields of the Avro data that need to be loaded. Note that for the subfield `data_y` in the nested Record, you need to specify its `jsonpath` as `"$.data.data_y"`.
-
-```sql
-CREATE ROUTINE LOAD sensor.sensor_log_load_job2 ON sensor_log2  
-PROPERTIES  
-(  
-  "format" = "avro",
-  "jsonpaths" = "[\"$.id\",\"$.name\",\"$.checked\",\"$.sensor_type\",\"$.data.data_y\"]"
-)  
-FROM KAFKA  
-(  
-  "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>,...",
-  "confluent.schema.registry.url" = "http://172.xx.xxx.xxx:8081",  
-  "kafka_topic" = "topic_1",  
-  "kafka_partitions" = "0,1,2,3,4,5",  
-  "property.kafka_default_offsets" = "OFFSET_BEGINNING"  
-);
-```
-
-#### Avro schema contains a Union field
-
-**Prepare a dataset**
-
-Suppose the Avro schema contains a Union field, and you need to load the Union field into StarRocks.
-
-- **Avro schema**
-
-    1. Create the following Avro schema file `avro_schema3.avsc`. The outer Avro record includes five fields which are `id`, `name`, `checked`, `sensor_type`, and `data` in sequence. And the field `data` is of Union type and includes two elements, `null` and a nested record `data_record`.
-
-        ```JSON
-        {
-            "type": "record",
-            "name": "sensor_log",
-            "fields" : [
-                {"name": "id", "type": "long"},
-                {"name": "name", "type": "string"},
-                {"name": "checked", "type" : "boolean"},
-                {"name": "sensor_type", "type": {"type": "enum", "name": "sensor_type_enum", "symbols" : ["TEMPERATURE", "HUMIDITY", "AIR-PRESSURE"]}},
-                {"name": "data", "type": [null,
-                        {
-                            "type": "record",
-                            "name": "data_record",
-                            "fields" : [
-                                {"name": "data_x", "type" : "boolean"},
-                                {"name": "data_y", "type": "long"}
-                            ]
-                        }
-                    ]
-                }
-            ]
-        }
-        ```
-
-    2. Register the Avro schema in the [Schema Registry](https://docs.confluent.io/platform/current/schema-registry/index.html).
-
-- **Avro data**
-
-Prepare the Avro data and send it to the Kafka topic `topic_3`.
-
-**Target database and table**
-
-According to the fields of Avro data, create a table `sensor_log3` in the target database `sensor` in the StarRocks cluster.
-
-Suppose that in addition to loading the fields `id`, `name`, `checked`, and `sensor_type` of the outer Record, you also need to load the field `data_y` of the element `data_record` in the Union type field `data`.
-
-```sql
-CREATE TABLE sensor.sensor_log3 ( 
-    `id` bigint NOT NULL COMMENT "sensor id",
-    `name` varchar(26) NOT NULL COMMENT "sensor name", 
-    `checked` boolean NOT NULL COMMENT "checked", 
-    `sensor_type` varchar(26) NOT NULL COMMENT "sensor type",
-    `data_y` long NULL COMMENT "sensor data" 
-) 
-ENGINE=OLAP 
-DUPLICATE KEY (id) 
-DISTRIBUTED BY HASH(`id`); 
-```
-
-**Routine Load job**
-
-Submit the load job, use `jsonpaths` to specify the fields that need to be loaded in the Avro data. Note that for the field `data_y`, you need to specify its `jsonpath` as `"$.data.data_y"`.
-
-```sql
-CREATE ROUTINE LOAD sensor.sensor_log_load_job3 ON sensor_log3  
-PROPERTIES  
-(  
-  "format" = "avro",
-  "jsonpaths" = "[\"$.id\",\"$.name\",\"$.checked\",\"$.sensor_type\",\"$.data.data_y\"]"
-)  
-FROM KAFKA  
-(  
-  "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>,...",
-  "confluent.schema.registry.url" = "http://172.xx.xxx.xxx:8081",  
-  "kafka_topic" = "topic_1",  
-  "kafka_partitions" = "0,1,2,3,4,5",  
-  "property.kafka_default_offsets" = "OFFSET_BEGINNING"  
-);
-```
-
-When the value for the Union type field `data` is `null`, the value loaded into the column `data_y` in the StarRocks table is `null`. When the value for the Union type field `data` is a data record, the value loaded into the column `data_y` is of Long type.
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/DELETE.md b/docs/en/sql-reference/sql-statements/data-manipulation/DELETE.md
deleted file mode 100644
index bdcebf428aaab5..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/DELETE.md
+++ /dev/null
@@ -1,394 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DELETE
-
-Deletes data rows from a table based on the specified conditions. The table can be a partitioned or non-partitioned table.
-
-For Duplicate Key tables, Aggregate tables, and Unique Key tables, you can delete data from specified partitions. From v2.3, Primary Key tables support complete `DELETE...WHERE` semantics, which allows you to delete data rows based on the primary key, any column, or the results of a subquery. From v3.0, StarRocks enriches the `DELETE...WHERE` semantics with multi-table joins and common table expressions (CTEs). If you need to join Primary Key tables with other tables in the database, you can reference these other tables in the USING clause or CTE.
-
-## Usage notes
-
-- You must have privileges on the table and database you want to perform DELETE.
-- Frequent DELETE operations are not recommended. If needed, perform such operations during off-peak hours.
-- The DELETE operation only deletes data in the table. The table remains. To drop the table, run [DROP TABLE](../data-definition/DROP_TABLE.md).
-- To prevent misoperations from deleting data in the entire table, you must specify the WHERE clause in the DELETE statement.
-- The deleted rows are not immediately cleaned. They are marked as "deleted" and will be temporarily saved in Segment. Physically, the rows are removed only after data version merge (compaction) is completed.
-- This operation also deletes data of the materialized views that reference this table.
-
-## Duplicate Key tables, Aggregate tables, and Unique Key tables
-
-### Syntax
-
-```SQL
-DELETE FROM  [<db_name>.]<table_name> [PARTITION <partition_name>]
-WHERE
-column_name1 op { value | value_list } [ AND column_name2 op { value | value_list } ...]
-```
-
-### Parameters
-
-| **Parameter**         | **Required** | **Description**                                                     |
-| :--------------- | :------- | :----------------------------------------------------------- |
-| `db_name`        | No       | The database to which the destination table belongs. If this parameter is not specified, the current database is used by default.      |
-| `table_name`     | Yes      | The table from which you want to delete data.   |
-| `partition_name` | No       | The partition from which you want to delete data.  |
-| `column_name`    | Yes      | The column you want to use as the DELETE condition. You can specify one or more columns.   |
-| `op`             | Yes      | The operator used in the DELETE condition. The supported operators are `=`, `>`, `<`, `>=`, `<=`, `!=`, `IN`, and `NOT IN`. |
-
-### Limits and usage notes
-
-- For Duplicate Key tables, you can use **any column** as the DELETE condition. For Aggregate tables and Unique Key tables, only **key columns** can be used as the DELETE condition.
-
-- The conditions that you specify must be in the AND relation. If you want to specify conditions in OR relation, you must specify the conditions in separate DELETE statements.
-
-- For Duplicate Key tables, Aggregate tables, and Unique Key tables, the DELETE statement does not support using subquery results as conditions.
-
-### Impacts
-
-After you execute the DELETE statement, the query performance of your cluster may deteriorate for a period of time (before compaction is completed). The degree of deterioration varies based on the number of conditions that you specify. A larger number of conditions indicates a higher degree of deterioration.
-
-### Examples
-
-#### Create a table and insert data
-
-The following example creates a partitioned Duplicate Key table.
-
-```SQL
-CREATE TABLE `my_table` (
-    `date` date NOT NULL,
-    `k1` int(11) NOT NULL COMMENT "",
-    `k2` varchar(65533) NULL DEFAULT "" COMMENT "")
-DUPLICATE KEY(`date`)
-PARTITION BY RANGE(`date`)
-(
-    PARTITION p1 VALUES [('2022-03-11'), ('2022-03-12')),
-    PARTITION p2 VALUES [('2022-03-12'), ('2022-03-13'))
-)
-DISTRIBUTED BY HASH(`date`)
-PROPERTIES
-("replication_num" = "3");
-
-INSERT INTO `my_table` VALUES
-('2022-03-11', 3, 'abc'),
-('2022-03-11', 2, 'acb'),
-('2022-03-11', 4, 'abc'),
-('2022-03-12', 2, 'bca'),
-('2022-03-12', 4, 'cba'),
-('2022-03-12', 5, 'cba');
-```
-
-#### Query data
-
-```plain
-select * from my_table order by date;
-+------------+------+------+
-| date       | k1   | k2   |
-+------------+------+------+
-| 2022-03-11 |    3 | abc  |
-| 2022-03-11 |    2 | acb  |
-| 2022-03-11 |    4 | abc  |
-| 2022-03-12 |    2 | bca  |
-| 2022-03-12 |    4 | cba  |
-| 2022-03-12 |    5 | cba  |
-+------------+------+------+
-```
-
-#### Delete data
-
-##### Delete data from a specified partition
-
-Delete rows whose `k1` values are `3` from the `p1` partition.
-
-```plain
-DELETE FROM my_table PARTITION p1
-WHERE k1 = 3;
-
--- The query result shows rows whose `k1` values are `3` are deleted.
-
-select * from my_table partition (p1);
-+------------+------+------+
-| date       | k1   | k2   |
-+------------+------+------+
-| 2022-03-11 |    2 | acb  |
-| 2022-03-11 |    4 | abc  |
-+------------+------+------+
-```
-
-##### Delete data from a specified partition using AND
-
-Delete rows whose `k1` values are greater than or equal to `3` and whose `k2` values are `"abc"` from the `p1` partition.
-
-```plain
-DELETE FROM my_table PARTITION p1
-WHERE k1 >= 3 AND k2 = "abc";
-
-select * from my_table partition (p1);
-+------------+------+------+
-| date       | k1   | k2   |
-+------------+------+------+
-| 2022-03-11 |    2 | acb  |
-+------------+------+------+
-```
-
-##### Delete data from all partitions
-
-Delete rows whose `k2` values are `"abc"` or `"cba"` from all partitions.
-
-```plain
-DELETE FROM my_table
-WHERE  k2 in ("abc", "cba");
-
-select * from my_table order by date;
-+------------+------+------+
-| date       | k1   | k2   |
-+------------+------+------+
-| 2022-03-11 |    2 | acb  |
-| 2022-03-12 |    2 | bca  |
-+------------+------+------+
-```
-
-## Primary Key tables
-
-From v2.3, Primary Key tables support complete `DELETE...WHERE` semantics, which allows you to delete data rows based on the primary key, any column, or a subquery.
-
-### Syntax
-
-```SQL
-[ WITH <with_query> [, ...] ]
-DELETE FROM <table_name>
-[ USING <from_item> [, ...] ]
-[ WHERE <where_condition> ]
-```
-
-### Parameters
-
-|   **Parameter**   | **Required** | **Description**                                              |
-| :---------------: | :----------- | :----------------------------------------------------------- |
-|   `with_query`    | No           | One or more CTEs that can be referenced by name in a DELETE statement. CTEs are temporary result sets that can improve the readability of complex statements. |
-|   `table_name`    | Yes          | The table from which you want to delete data.                |
-|    `from_item`    | No           | One or more other tables in the database. These tables can be joined with the table being operated based on the condition specified in the WHERE clause. Based on the result set of the join query, StarRocks deletes the matched rows from the table being operated. For example, if the USING clause is `USING t1 WHERE t0.pk = t1.pk;`, StarRocks converts the table expression in the USING clause to `t0 JOIN t1 ON t0.pk=t1.pk;` when executing the DELETE statement. |
-| `where_condition` | Yes          | The condition based on which you want to delete rows. Only rows that meet the WHERE condition can be deleted. This parameter is required, because it helps prevent you from accidentally deleting the entire table. If you want to delete the entire table, you can use 'WHERE true'. |
-
-### Limits and usage notes
-
-- Primary Key tables do not support deleting data from a specified partition, for example, `DELETE FROM <table_name> PARTITION <partition_id> WHERE <where_condition>`.
-- The following comparison operators are supported: `=`, `>`, `<`, `>=`, `<=`, `!=`, `IN`, `NOT IN`.
-- The following logical operators are supported: `AND` and `OR`.
-- You cannot use the DELETE statement to run concurrent DELETE operations or to delete data at data loading. If you perform such operations, the atomicity, consistency, isolation, and durability (ACID) of transactions may not be ensured.
-
-### Examples
-
-#### Create a table and insert data
-
-Create a Primary Key table named `score_board`:
-
-```sql
-CREATE TABLE `score_board` (
-  `id` int(11) NOT NULL COMMENT "",
-  `name` varchar(65533) NULL DEFAULT "" COMMENT "",
-  `score` int(11) NOT NULL DEFAULT "0" COMMENT ""
-) ENGINE=OLAP
-PRIMARY KEY(`id`)
-COMMENT "OLAP"
-DISTRIBUTED BY HASH(`id`)
-PROPERTIES (
-"replication_num" = "3",
-"storage_format" = "DEFAULT",
-"enable_persistent_index" = "false"
-);
-
-INSERT INTO score_board VALUES
-(0, 'Jack', 21),
-(1, 'Bob', 21),
-(2, 'Stan', 21),
-(3, 'Sam', 22);
-```
-
-#### Query data
-
-Execute the following statement to insert data into the `score_board` table:
-
-```Plain
-select * from score_board;
-+------+------+------+
-| id   | name | score|
-+------+------+------+
-|    0 | Jack |   21 |
-|    1 | Bob  |   21 |
-|    2 | Stan |   21 |
-|    3 | Sam  |   22 |
-+------+------+------+
-4 rows in set (0.00 sec)
-```
-
-#### Delete data
-
-##### Delete data by primary key
-
-You can specify the primary key in the DELETE statement, so StarRocks does not need to scan the entire table.
-
-Delete rows whose `id` values are `0` from the `score_board` table.
-
-```Plain
-DELETE FROM score_board WHERE id = 0;
-
-select * from score_board;
-+------+------+------+
-| id   | name | score|
-+------+------+------+
-|    1 | Bob  |   21 |
-|    2 | Stan |   21 |
-|    3 | Sam  |   22 |
-+------+------+------+
-```
-
-##### Delete data by condition
-
-Example 1: Delete rows whose `score` values are `22` from the `score_board` table.
-
-```Plain
-DELETE FROM score_board WHERE score = 22;
-
-select * from score_board;
-+------+------+------+
-| id   | name | score|
-+------+------+------+
-|    0 | Jack |   21 |
-|    1 | Bob  |   21 |
-|    2 | Stan |   21 |
-+------+------+------+
-```
-
-Example 2: Delete rows whose `score` values are less than `22` from the `score_board` table.
-
-```Plain
-DELETE FROM score_board WHERE score < 22;
-
-select * from score_board;
-+------+------+------+
-| id   | name | score|
-+------+------+------+
-|    3 | Sam  |   22 |
-+------+------+------+
-```
-
-Example 3: Delete rows whose `score` values are less than `22` and whose `name` values are not `Bob` from the `score_board` table.
-
-```Plain
-DELETE FROM score_board WHERE score < 22 and name != "Bob";
-
-select * from score_board;
-+------+------+------+
-| id   | name | score|
-+------+------+------+
-|    1 | Bob  |   21 |
-|    3 | Sam  |   22 |
-+------+------+------+
-2 rows in set (0.00 sec)
-```
-
-##### Delete data by subquery result
-
-You can nest one or more subqueries in the `DELETE` statement and use the subquery results as conditions.
-
-Before you delete data, execute the following statement to create another table named `users`:
-
-```SQL
-CREATE TABLE `users` (
-  `uid` int(11) NOT NULL COMMENT "",
-  `name` varchar(65533) NOT NULL COMMENT "",
-  `country` varchar(65533) NULL COMMENT ""
-) ENGINE=OLAP
-PRIMARY KEY(`uid`)
-COMMENT "OLAP"
-DISTRIBUTED BY HASH(`uid`)
-PROPERTIES (
-"replication_num" = "3",
-"storage_format" = "DEFAULT",
-"enable_persistent_index" = "false"
-);
-```
-
-Insert data into the `users` table:
-
-```SQL
-INSERT INTO users VALUES
-(0, "Jack", "China"),
-(2, "Stan", "USA"),
-(1, "Bob", "China"),
-(3, "Sam", "USA");
-```
-
-```plain
-select * from users;
-+------+------+---------+
-| uid  | name | country |
-+------+------+---------+
-|    0 | Jack | China   |
-|    1 | Bob  | China   |
-|    2 | Stan | USA     |
-|    3 | Sam  | USA     |
-+------+------+---------+
-4 rows in set (0.00 sec)
-```
-
-Nest a subquery to find the rows whose `country` values are `China` from the `users` table, and delete the rows, which have the same `name` values as the rows returned from the subquery, from the `score_board` table. You can use one of the following methods to fulfill the purpose:
-
-- Method 1
-
-```plain
-DELETE FROM score_board
-WHERE name IN (select name from users where country = "China");
-    
-select * from score_board;
-+------+------+------+
-| id   | name | score|
-+------+------+------+
-|    2 | Stan |   21 |
-|    3 | Sam  |   22 |
-+------+------+------+
-```
-
-- Method 2
-
-```plain
-DELETE FROM score_board
-WHERE EXISTS (select name from users
-              where score_board.name = users.name and country = "China");
-    
-select * from score_board;
-+------+------+-------+
-| id   | name | score |
-+------+------+-------+
-|    2 | Stan |    21 |
-|    3 | Sam  |    22 |
-+------+------+-------+
-2 rows in set (0.00 sec)
-```
-
-##### Delete data by using multi-table join or CTE
-
-To delete all movies produced by the producer "foo", you can execute the following statement:
-
-```SQL
-DELETE FROM films USING producers
-WHERE producer_id = producers.id
-    AND producers.name = 'foo';
-```
-
-You can also use a CTE to rewrite the above statement to improve readability.
-
-```SQL
-WITH foo_producers as (
-    SELECT * from producers
-    where producers.name = 'foo'
-)
-DELETE FROM films USING foo_producers
-WHERE producer_id = foo_producers.id;
-```
-
-## References
-
-[SHOW DELETE](./SHOW_DELETE.md): queries historical DELETE operations that were successfully performed on Duplicate Key tables, Aggregate tables, and Unique Key tables.
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/DROP_PIPE.md b/docs/en/sql-reference/sql-statements/data-manipulation/DROP_PIPE.md
deleted file mode 100644
index 8986f3ba48b430..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/DROP_PIPE.md
+++ /dev/null
@@ -1,42 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP PIPE
-
-## Description
-
-Drops a pipe and the related jobs and metadata. Executing this statement on a pipe does not revoke the data that has been loaded via this pipe. This command is supported from v3.2 onwards.
-
-## Syntax
-
-```SQL
-DROP PIPE [IF EXISTS] [db_name.]<pipe_name>
-```
-
-## Parameters
-
-### db_name
-
-The name of the database to which the pipe belongs.
-
-### pipe_name
-
-The name of the pipe.
-
-## Examples
-
-Drop the pipe named `user_behavior_replica` in the database named `mydatabase`:
-
-```SQL
-USE mydatabase;
-DROP PIPE user_behavior_replica;
-```
-
-## References
-
-- [CREATE PIPE](../data-manipulation/CREATE_PIPE.md)
-- [ALTER PIPE](../data-manipulation/ALTER_PIPE.md)
-- [SHOW PIPES](../data-manipulation/SHOW_PIPES.md)
-- [SUSPEND or RESUME PIPE](../data-manipulation/SUSPEND_or_RESUME_PIPE.md)
-- [RETRY FILE](../data-manipulation/RETRY_FILE.md)
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/DROP_TASK.md b/docs/en/sql-reference/sql-statements/data-manipulation/DROP_TASK.md
deleted file mode 100644
index 8fe392fa7d6e13..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/DROP_TASK.md
+++ /dev/null
@@ -1,61 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# DROP TASK
-
-## Description
-
-Drops an asynchronous ETL task submitted using [SUBMIT TASK](./SUBMIT_TASK.md). This feature has been supported since StarRocks v2.5.7.
-
-> **NOTE**
->
-> Dropping a task with DROP TASK simultaneously cancels the corresponding TaskRun.
-
-## Syntax
-
-```SQL
-DROP TASK `<task_name>` [FORCE]
-```
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**               |
-| ------------- | ------------ | ----------------------------- |
-| task_name     | Yes          | The name of the task to drop. Please wrap the task name with backticks (`) to prevent any parse failure. |
-| FORCE         | No           | Forces to drop the task. |
-
-## Usage notes
-
-You can check the information of asynchronous tasks by querying the metadata views `tasks` and `task_runs` in Information Schema.
-
-```SQL
-SELECT * FROM INFORMATION_SCHEMA.tasks;
-SELECT * FROM information_schema.tasks WHERE task_name = '<task_name>';
-SELECT * FROM information_schema.task_runs;
-SELECT * FROM information_schema.task_runs WHERE task_name = '<task_name>';
-```
-
-You can obtain the `task_name` of materialized view refresh tasks by using the SHOW MATERIALIZED VIEWS statement.
-
-```SQL
-SHOW MATERIALIZED VIEWS;
-SHOW MATERIALIZED VIEWS WHERE name = '<mv_name>';
-```
-
-## Examples
-
-```Plain
-MySQL > SUBMIT /*+set_var(query_timeout=100000)*/ TASK `ctas` AS
-    -> CREATE TABLE insert_wiki_edit_new
-    -> AS SELECT * FROM source_wiki_edit;
-+----------+-----------+
-| TaskName | Status    |
-+----------+-----------+
-| ctas     | SUBMITTED |
-+----------+-----------+
-1 row in set (1.19 sec)
-
-MySQL > DROP TASK `ctas`;
-Query OK, 0 rows affected (0.35 sec)
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/EXPORT.md b/docs/en/sql-reference/sql-statements/data-manipulation/EXPORT.md
deleted file mode 100644
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--- a/docs/en/sql-reference/sql-statements/data-manipulation/EXPORT.md
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----
-displayed_sidebar: "English"
----
-
-# EXPORT
-
-## Description
-
-Exports the data of a table to a specified location.
-
-This is an asynchronous operation. The export result is returned after you submit the export task. You can use [SHOW EXPORT](../../../sql-reference/sql-statements/data-manipulation/SHOW_EXPORT.md) to view the progress of the export task.
-
-> **NOTICE**
->
-> You can export data out of StarRocks tables only as a user who has the EXPORT privilege on those StarRocks tables. If you do not have the EXPORT privilege, follow the instructions provided in [GRANT](../account-management/GRANT.md) to grant the EXPORT privilege to the user that you use to connect to your StarRocks cluster.
-
-## Syntax
-
-```SQL
-EXPORT TABLE <table_name>
-[PARTITION (<partition_name>[, ...])]
-[(<column_name>[, ...])]
-TO <export_path>
-[opt_properties]
-WITH BROKER
-[broker_properties]
-```
-
-## Parameters
-
-- `table_name`
-
-  The name of the table. StarRocks supports exporting the data of tables whose `engine` is `olap` or `mysql`.
-
-- `partition_name`
-
-  The partitions from which you want to export data. By default, if you do not specify this parameter, StarRocks exports the data from all partitions of the table.
-
-- `column_name`
-
-  The columns from which you want to export data. The sequence of columns that you specify by using this parameter can differ from the schema of the table. By default, if you do not specify this parameter, StarRocks exports the data from all columns of the table.
-
-- `export_path`
-
-  The location to which you want to export the data of the table. If the location contains a path, make sure that the path ends with a slash (/). Otherwise, the part following the last slash (/) in the path will be used as the prefix to the name of the exported file. By default, `data_` is used as the file name prefix if no file name prefix is specified.
-
-- `opt_properties`
-
-  Optional properties that you can configure for the export task.
-
-  Syntax:
-
-  ```SQL
-  [PROPERTIES ("<key>"="<value>", ...)]
-  ```
-
-  | **Property**     | **Description**                                              |
-  | ---------------- | ------------------------------------------------------------ |
-  | column_separator | The column separator that you want to use in the exported file. Default value: `\t`. |
-  | line_delimiter   | The row separator that you want to use in the exported file. Default value: `\n`. |
-  | load_mem_limit   | The maximum memory that is allowed for the export task on each individual BE. Unit: bytes. The default maximum memory is 2 GB. |
-  | timeout          | The amount of time after which the export task times out. Unit: second. Default value: `86400`, meaning 1 day. |
-  | include_query_id | Specifies whether the name of the exported file contains `query_id`. Valid values: `true` and `false`. The value `true` specifies that the file name contains `query_id`, and the value `false` specifies that the file name does not contain `query_id`. |
-
-- `WITH BROKER`
-
-  In v2.4 and earlier, input `WITH BROKER "<broker_name>"` to specify the broker you want to use. From v2.5 onwards, you no longer need to specify a broker, but you still need to retain the `WITH BROKER` keyword. For more information, see [Export data using EXPORT > Background information](../../../unloading/Export.md#background-information).
-
-- `broker_properties`
-
-  The information that is used to authenticate the source data. The authentication information varies depending on the data source. For more information, see [BROKER LOAD](../../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
-
-## Examples
-
-### Export all data of a table to HDFS
-
-The following example exports all data of the `testTbl` table to the `hdfs://<hdfs_host>:<hdfs_port>/a/b/c/` path of an HDFS cluster:
-
-```SQL
-EXPORT TABLE testTbl 
-TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
-WITH BROKER
-(
-        "username"="xxx",
-        "password"="yyy"
-);
-```
-
-### Export the data of specified partitions of a table to HDFS
-
-The following example exports the data of two partitions, `p1` and `p2`, of the `testTbl` table to the `hdfs://<hdfs_host>:<hdfs_port>/a/b/c/` path of an HDFS cluster:
-
-```SQL
-EXPORT TABLE testTbl
-PARTITION (p1,p2) 
-TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
-WITH BROKER
-(
-        "username"="xxx",
-        "password"="yyy"
-);
-```
-
-### Export all data of a table to HDFS with column separator specified
-
-The following example exports all data of the `testTbl` table to the `hdfs://<hdfs_host>:<hdfs_port>/a/b/c/` path of an HDFS cluster and specifies that commas (`,`) is used as the column separator:
-
-```SQL
-EXPORT TABLE testTbl 
-TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
-PROPERTIES
-(
-    "column_separator"=","
-) 
-WITH BROKER
-(
-    "username"="xxx",
-    "password"="yyy"
-);
-```
-
-The following example exports all data of the `testTbl` table to the `hdfs://<hdfs_host>:<hdfs_port>/a/b/c/` path of an HDFS cluster and specifies that `\x01` (the default column separator supported by Hive) is used as the column separator:
-
-```SQL
-EXPORT TABLE testTbl 
-TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
-PROPERTIES
-(
-    "column_separator"="\\x01"
-) 
-WITH BROKER;
-```
-
-### Export all data of a table to HDFS with file name prefix specified
-
-The following example exports all data of the `testTbl` table to the `hdfs://<hdfs_host>:<hdfs_port>/a/b/c/` path of an HDFS cluster and specifies that `testTbl_` is used as the prefix to the name of the exported file:
-
-```SQL
-EXPORT TABLE testTbl 
-TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/testTbl_" 
-WITH BROKER;
-```
-
-### Export data to AWS S3
-
-The following example exports all data of the `testTbl` table to the `s3-package/export/` path of an AWS S3 bucket:
-
-```SQL
-EXPORT TABLE testTbl 
-TO "s3a://s3-package/export/"
-WITH BROKER
-(
-    "aws.s3.access_key" = "xxx",
-    "aws.s3.secret_key" = "yyy",
-    "aws.s3.region" = "zzz"
-);
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/INSERT.md b/docs/en/sql-reference/sql-statements/data-manipulation/INSERT.md
deleted file mode 100644
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--- a/docs/en/sql-reference/sql-statements/data-manipulation/INSERT.md
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----
-displayed_sidebar: "English"
----
-
-# INSERT
-
-## Description
-
-Inserts data into a specific table or overwrites a specific table with data. For detailed information about the application scenarios, see [Load data with INSERT](../../../loading/InsertInto.md). From v3.2.0 onwards, INSERT supports writing data into files in remote storage. You can [use INSERT INTO FILES() to unload data from StarRocks to remote storage](../../../unloading/unload_using_insert_into_files.md).
-
-You can submit an asynchronous INSERT task using [SUBMIT TASK](./SUBMIT_TASK.md).
-
-## Syntax
-
-- **Data loading**:
-
-  ```sql
-  INSERT { INTO | OVERWRITE } [db_name.]<table_name>
-  [ PARTITION (<partition_name> [, ...] ) ]
-  [ TEMPORARY PARTITION (<temporary_partition_name> [, ...] ) ]
-  [ WITH LABEL <label>]
-  [ (<column_name>[, ...]) ]
-  { VALUES ( { <expression> | DEFAULT } [, ...] ) | <query> }
-  ```
-
-- **Data unloading**:
-
-  ```sql
-  INSERT INTO FILES()
-  [ WITH LABEL <label> ]
-  { VALUES ( { <expression> | DEFAULT } [, ...] ) | <query> }
-  ```
-
-## Parameters
-
-| **Parameter** | Description                                                  |
-| ------------- | ------------------------------------------------------------ |
-| INTO          | To append data to the table.                                 |
-| OVERWRITE     | To overwrite the table with data.                            |
-| table_name    | The name of the table into which you want to load data. It can be specified with the database the table resides as `db_name.table_name`. |
-| PARTITION    |  The partitions into which you want to load the data. You can specify multiple partitions, which must be separated by commas (,). It must be set to partitions that exist in the destination table. If you specify this parameter, the data will be inserted only into the specified partitions. If you do not specify this parameter, the data will be inserted into all partitions. |
-| TEMPORARY PARTITION |The name of the [temporary partition](../../../table_design/Temporary_partition.md) into which you want to load data. You can specify multiple temporary partitions, which must be separated by commas (,).|
-| label         | The unique identification label for each data load transaction within the database. If it is not specified, the system automatically generates one for the transaction. We recommend you specify the label for the transaction. Otherwise, you cannot check the transaction status if a connection error occurs and no result is returned. You can check the transaction status via `SHOW LOAD WHERE label="label"` statement. For the naming conventions of labels, see [System Limits](../../../reference/System_limit.md). |
-| column_name   | The name of the destination column(s) to load data in. It must be set as columns that exist in the destination table. The destination columns you specify are mapped one on one in sequence to the columns of the source table, regardless of what the destination column names are. If no destination column is specified, the default value is all columns in the destination table. If the specified column in the source table does not exist in the destination column, the default value will be written to this column, and the transaction will fail if the specified column does not have a default value. If the column type of the source table is inconsistent with that of the destination table, the system will perform an implicit conversion on the mismatched column. If the conversion fails, a syntax parsing error will be returned.<br />**NOTE**<br />From v3.3.1, specifying a column list in the INSERT INTO statement on a Primary Key table will perform Partial Updates (instead of Full Upsert in earlier versions). If the column list is not specified, the system will perform Full Upsert. |
-| expression    | Expression that assigns values to the column.                |
-| DEFAULT       | Assigns default value to the column.                         |
-| query         | Query statement whose result will be loaded into the destination table. It can be any SQL statement supported by StarRocks. |
-| FILES()       | Table function [FILES()](../../sql-functions/table-functions/files.md). You can use this function to unload data into remote storage. For more information, see [Use INSERT INTO FILES() to unload data to remote storage](../../../unloading/unload_using_insert_into_files.md). |
-
-## Return
-
-```Plain
-Query OK, 5 rows affected, 2 warnings (0.05 sec)
-{'label':'insert_load_test', 'status':'VISIBLE', 'txnId':'1008'}
-```
-
-| Return        | Description                                                  |
-| ------------- | ------------------------------------------------------------ |
-| rows affected | Indicates how many rows are loaded. `warnings` indicates the rows that are filtered out. |
-| label         | The unique identification label for each data load transaction within the database. It can be assigned by user or automatically by the system. |
-| status        | Indicates if the loaded data is visible. `VISIBLE`: the data is successfully loaded and visible. `COMMITTED`: the data is successfully loaded but invisible for now. |
-| txnId         | The ID number corresponding to each INSERT transaction.      |
-
-## Usage notes
-
-- As for the current version, when StarRocks executes the INSERT INTO statement, if any row of data mismatches the destination table format (for example, the string is too long), the INSERT transaction fails by default. You can set the session variable `enable_insert_strict` to `false` so that the system filters out the data that mismatches the destination table format and continues to execute the transaction.
-
-- After INSERT OVERWRITE statement is executed, StarRocks creates temporary partitions for the partitions that store the original data, inserts data into the temporary partitions, and swaps the original partitions with the temporary partitions. All these operations are executed in the Leader FE node. Therefore, if the Leader FE node crashes while executing INSERT OVERWRITE statement, the whole load transaction fails, and the temporary partitions are deleted.
-
-## Example
-
-The following examples are based on table `test`, which contains two columns `c1` and `c2`. The `c2` column has a default value of DEFAULT.
-
-- Import a row of data into the `test` table.
-
-```SQL
-INSERT INTO test VALUES (1, 2);
-INSERT INTO test (c1, c2) VALUES (1, 2);
-INSERT INTO test (c1, c2) VALUES (1, DEFAULT);
-INSERT INTO test (c1) VALUES (1);
-```
-
-When no destination column is specified, the columns are loaded in sequence into the destination table by default. Therefore, in the above example, the outcomes of the first and second SQL statements are the same.
-
-If a destination column (with or without data inserted) uses DEFAULT as the value, the column will use the default value as the loaded data. Therefore, in the above example, the outputs of the third and fourth statements are the same.
-
-- Load multiple rows of data into the `test` table at one time.
-
-```SQL
-INSERT INTO test VALUES (1, 2), (3, 2 + 2);
-INSERT INTO test (c1, c2) VALUES (1, 2), (3, 2 * 2);
-INSERT INTO test (c1, c2) VALUES (1, DEFAULT), (3, DEFAULT);
-INSERT INTO test (c1) VALUES (1), (3);
-```
-
-Because the results of expressions are equivalent, the outcomes of the first and second statements are the same. The outcomes of the third and fourth statements are the same because they both use default value.
-
-- Import a query statement result into the `test` table.
-
-```SQL
-INSERT INTO test SELECT * FROM test2;
-INSERT INTO test (c1, c2) SELECT * from test2;
-```
-
-- Import a query result into the `test` table, and specify partition and label.
-
-```SQL
-INSERT INTO test PARTITION(p1, p2) WITH LABEL `label1` SELECT * FROM test2;
-INSERT INTO test WITH LABEL `label1` (c1, c2) SELECT * from test2;
-```
-
-- Overwrite the `test` table with a query result, and specify partition and label.
-
-```SQL
-INSERT OVERWRITE test PARTITION(p1, p2) WITH LABEL `label1` SELECT * FROM test3;
-INSERT OVERWRITE test WITH LABEL `label1` (c1, c2) SELECT * from test3;
-```
-
-The following example inserts data rows from the Parquet file **parquet/insert_wiki_edit_append.parquet** within the AWS S3 bucket `inserttest` into the table `insert_wiki_edit`:
-
-```Plain
-INSERT INTO insert_wiki_edit
-    SELECT * FROM FILES(
-        "path" = "s3://inserttest/parquet/insert_wiki_edit_append.parquet",
-        "format" = "parquet",
-        "aws.s3.access_key" = "XXXXXXXXXX",
-        "aws.s3.secret_key" = "YYYYYYYYYY",
-        "aws.s3.region" = "ap-southeast-1"
-);
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/PAUSE_ROUTINE_LOAD.md b/docs/en/sql-reference/sql-statements/data-manipulation/PAUSE_ROUTINE_LOAD.md
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--- a/docs/en/sql-reference/sql-statements/data-manipulation/PAUSE_ROUTINE_LOAD.md
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----
-displayed_sidebar: "English"
----
-
-# PAUSE ROUTINE LOAD
-
-import RoutineLoadPrivNote from '../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
-
-## Description
-
-Pauses a Routine Load job but does not terminate this job. You can execute [RESUME ROUTINE LOAD](./RESUME_ROUTINE_LOAD.md) to resume it. After the load job is paused, you can execute [SHOW ROUTINE LOAD](./SHOW_ROUTINE_LOAD.md) and [ALTER ROUTINE LOAD](./ALTER_ROUTINE_LOAD.md) to view and modify information about the paused load job.
-
-<RoutineLoadPrivNote />
-
-## Syntax
-
-```SQL
-PAUSE ROUTINE LOAD FOR [db_name.]<job_name>;
-```
-
-## Parameters
-
-| Parameter | Required | Description                                                  |
-| --------- | -------- | ------------------------------------------------------------ |
-| db_name   |          | The name of the database to which the Routine Load job belongs. |
-| job_name  | ✅        | The name of the Routine Load job. A table may have multiple Routine Load jobs, it is recommended to set a meaningful Routine Load job name by using identifiable information, for example, Kafka topic name or time when you create the load job, to distinguish multiple routine load jobs.  The name of the Routine Load job must be unique within the same database |
-
-## Examples
-
-Pause the Routine Load job `example_tbl1_ordertest1` in the database `example_db`.
-
-```sql
-PAUSE ROUTINE LOAD FOR example_db.example_tbl1_ordertest1;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/REFRESH_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/data-manipulation/REFRESH_MATERIALIZED_VIEW.md
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--- a/docs/en/sql-reference/sql-statements/data-manipulation/REFRESH_MATERIALIZED_VIEW.md
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----
-displayed_sidebar: "English"
----
-
-# REFRESH MATERIALIZED VIEW
-
-## Description
-
-Manually refresh a specific asynchronous materialized view or partitions within.
-
-> **CAUTION**
->
-> You can only manually refresh materialized views that adopt ASYNC or MANUAL refresh strategy. You can check the refresh strategy of an asynchronous materialized view using [SHOW MATERIALIZED VIEWS](../data-manipulation/SHOW_MATERIALIZED_VIEW.md).
-> This operation requires the REFRESH privilege on the target materialized view.
-
-## Syntax
-
-```SQL
-REFRESH MATERIALIZED VIEW [database.]mv_name
-[PARTITION START ("<partition_start_date>") END ("<partition_end_date>")]
-[FORCE]
-[WITH { SYNC | ASYNC } MODE]
-```
-
-## Parameters
-
-| **Parameter**             | **Required** | **Description**                                        |
-| ------------------------- | ------------ | ------------------------------------------------------ |
-| mv_name                   | yes          | The name of the materialized view to refresh manually. |
-| PARTITION START () END () | no           | Manually refresh partitions within a certain time interval. |
-| partition_start_date      | no           | The start date of the partitions to refresh manually.  |
-| partition_end_date        | no           | The end date of the partitions to refresh manually.    |
-| FORCE                     | no           | If you specify this parameter, StarRocks forcibly refreshes the corresponding materialized view or partitions. If you do not specify this parameter, StarRocks automatically judges if the data is updated and refreshes the partition only when needed.  |
-| WITH ... MODE             | no           | Make a synchronous or asynchronous call of the refresh task. `SYNC` indicates making a synchronous call of the refresh task, and StarRocks returns the task result only when the task succeeds or fails. `ASYNC` indicates making an asynchronous call of the refresh task, and StarRocks returns success right after the task is submitted, leaving the task to be executed asynchronously in the background. You can check the refresh task status of an asynchronous materialized view by querying the `tasks` and `task_runs` metadata views in StarRocks' Information Schema. For more information, see [Check the execution status of asynchronous materialized view](../../../using_starrocks/Materialized_view.md#check-the-execution-status-of-asynchronous-materialized-view). Default: `ASYNC`. Supported from v2.5.8 and v3.1.0 onwards. |
-
-> **CAUTION**
->
-> When refreshing materialized views created based on the external catalogs, StarRocks refreshes all partitions in the materialized views.
-
-## Examples
-
-Example 1: Manually refresh a specific materialized view via an asynchronous call.
-
-```Plain
-REFRESH MATERIALIZED VIEW lo_mv1;
-
-REFRESH MATERIALIZED VIEW lo_mv1 WITH ASYNC MODE;
-```
-
-Example 2: Manually refresh certain partitions of a specific materialized view.
-
-```Plain
-REFRESH MATERIALIZED VIEW lo_mv1 
-PARTITION START ("2020-02-01") END ("2020-03-01");
-```
-
-Example 3: Forcibly refresh certain partitions of a specific materialized view.
-
-```Plain
-REFRESH MATERIALIZED VIEW lo_mv1
-PARTITION START ("2020-02-01") END ("2020-03-01") FORCE;
-```
-
-Example 4: Manually refresh a materialized view via a synchronous call.
-
-```Plain
-REFRESH MATERIALIZED VIEW lo_mv1 WITH SYNC MODE;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md b/docs/en/sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md
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index 746db0532dcfef..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md
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----
-displayed_sidebar: "English"
----
-
-# RESUME ROUTINE LOAD
-
-import RoutineLoadPrivNote from '../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
-
-## Description
-
-Resumes a Routine load job. The job will temporarily enter **NEED_SCHEDULE** state because the job is being re-scheduled. And after some time, the job will be resumed to **RUNNING** state, continuing consuming messages from the data source and loading data. You can check the job's information using the [SHOW ROUTINE LOAD](./SHOW_ROUTINE_LOAD.md) statement.
-
-<RoutineLoadPrivNote />
-
-## Syntax
-
-```SQL
-RESUME ROUTINE LOAD FOR [db_name.]<job_name>
-```
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                              |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| db_name       |              | The name of the database to which the Routine Load job belongs. |
-| job_name      | ✅            | The name of the Routine Load job.                            |
-
-## Examples
-
-Resume the Routine Load job `example_tbl1_ordertest1` in the database `example_db`.
-
-```SQL
-RESUME ROUTINE LOAD FOR example_db.example_tbl1_ordertest1;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/RETRY_FILE.md b/docs/en/sql-reference/sql-statements/data-manipulation/RETRY_FILE.md
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index cb4922e3fb8afc..00000000000000
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-# RETRY FILE
-
-## Description
-
-Retries to load all data files or a specific data file in a pipe. This command is supported from v3.2 onwards.
-
-## Syntax
-
-```SQL
-ALTER PIPE [ IF EXISTS ] <pipe_name> { RETRY ALL | RETRY FILE '<file_name>' }
-```
-
-## Parameters
-
-### pipe_name
-
-The name of the pipe.
-
-### file_name
-
-The storage path of the data file that you want to retry to load. Note that you must specify the full storage path of the file. If the file you specify does not belong to the pipe you specify in `pipe_name`, an error is returned.
-
-## Examples
-
-The following example retries to load all data files in a pipe named `user_behavior_replica`:
-
-```SQL
-ALTER PIPE [ IF EXISTS ] user_behavior_replica RETRY ALL;
-```
-
-The following example retries to load the data file `s3://starrocks-examples/user_behavior_ten_million_rows.parquet` in a pipe named `user_behavior_replica`:
-
-```SQL
-ALTER PIPE [ IF EXISTS ] user_behavior_replica RETRY FILE 's3://starrocks-examples/user_behavior_ten_million_rows.parquet';
-```
-
-## References
-
-- [CREATE PIPE](../data-manipulation/CREATE_PIPE.md)
-- [ALTER PIPE](../data-manipulation/ALTER_PIPE.md)
-- [DROP PIPE](../data-manipulation/DROP_PIPE.md)
-- [SHOW PIPES](../data-manipulation/SHOW_PIPES.md)
-- [SUSPEND or RESUME PIPE](../data-manipulation/SUSPEND_or_RESUME_PIPE.md)
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SELECT.md b/docs/en/sql-reference/sql-statements/data-manipulation/SELECT.md
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--- a/docs/en/sql-reference/sql-statements/data-manipulation/SELECT.md
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----
-displayed_sidebar: "English"
----
-
-# SELECT
-
-## Description
-
-Queries data from one or more tables, views, or materialized views. The SELECT statement generally consists of the following clauses:
-
-- [WITH](#with)
-- [WHERE and operators](#where-and-operators)
-- [GROUP BY](#group-by)
-- [HAVING](#having)
-- [UNION](#union)
-- [INTERSECT](#intersect)
-- [EXCEPT/MINUS](#exceptminus)
-- [ORDER BY](#order-by)
-- [LIMIT](#limit)
-- [OFFSET](#offset)
-- [Joins](#join)
-- [Subqueries](#subquery)
-- [DISTINCT](#distinct)
-- [Alias](#alias)
-
-SELECT can work as an independent statement or a clause nested in other statements. The output of the SELECT clause can be used as the input of other statements.
-
-StarRocks' query statement basically conforms to the SQL92 standard. Here is a brief description of the supported SELECT usage.
-
-> **NOTE**
->
-> To query data from tables, views, or materialized views in a StarRocks internal table, you must have the SELECT privilege on these objects. To query data from tables, views, or materialized views in an external data source, you must have the USAGE privilege on the corresponding external catalog.
-
-### WITH
-
-A clause that can be added before a SELECT statement to define an alias for a complex expression that is referenced multiple times inside SELECT.
-
-Similar to CRATE VIEW, but the table and column names defined in the clause do not persist after the query ends and do not conflict with names in the actual table or VIEW.
-
-The benefits of using a WITH clause are:
-
-Convenient and easy to maintain, reducing duplication within queries.
-
- It is easier to read and understand SQL code by abstracting the most complex parts of a query into separate blocks.
-
-Examples:
-
-```sql
--- Define one subquery at the outer level, and another at the inner level as part of the
--- initial stage of the UNION ALL query.
-
-with t1 as (select 1),t2 as (select 2)
-select * from t1 union all select * from t2;
-```
-
-### Join
-
-Join operations combine data from two or more tables and then return a result set of some columns from some of them.
-
-StarRocks supports self joins, cross joins, inner joins, outer joins, semi joins, and anti joins. Outer joins include left joins, right joins, and full joins.
-
-Syntax:
-
-```sql
-SELECT select_list FROM
-table_or_subquery1 [INNER] JOIN table_or_subquery2 |
-table_or_subquery1 {LEFT [OUTER] | RIGHT [OUTER] | FULL [OUTER]} JOIN table_or_subquery2 |
-table_or_subquery1 {LEFT | RIGHT} SEMI JOIN table_or_subquery2 |
-table_or_subquery1 {LEFT | RIGHT} ANTI JOIN table_or_subquery2 |
-[ ON col1 = col2 [AND col3 = col4 ...] |
-USING (col1 [, col2 ...]) ]
-[other_join_clause ...]
-[ WHERE where_clauses ]
-```
-
-```sql
-SELECT select_list FROM
-table_or_subquery1, table_or_subquery2 [, table_or_subquery3 ...]
-[other_join_clause ...]
-WHERE
-col1 = col2 [AND col3 = col4 ...]
-```
-
-```sql
-SELECT select_list FROM
-table_or_subquery1 CROSS JOIN table_or_subquery2
-[other_join_clause ...]
-[ WHERE where_clauses ]
-```
-
-#### Self Join
-
-StarRocks supports self-joins, which are self-joins and self-joins. For example, different columns of the same table are joined.
-
-There is actually no special syntax to identify self-join. The conditions on both sides of a join in a self-join come from the same table.
-
-We need to assign them different aliases.
-
-Examples:
-
-```sql
-SELECT lhs.id, rhs.parent, lhs.c1, rhs.c2 FROM tree_data lhs, tree_data rhs WHERE lhs.id = rhs.parent;
-```
-
-#### Cross Join
-
-Cross join can produce a lot of results, so cross join should be used with caution.
-
-Even if you need to use cross join, you need to use filter conditions and ensure that fewer results are returned. Example:
-
-```sql
-SELECT * FROM t1, t2;
-
-SELECT * FROM t1 CROSS JOIN t2;
-```
-
-#### Inner Join
-
-Inner join is the most well-known and commonly used join. Returns results from columns requested by two similar tables, joined if the columns of both tables contain the same value.
-
-If a column name of both tables is the same, we need to use the full name (in the form of table_name.column_name) or alias the column name.
-
-Examples:
-
-The following three queries are equivalent.
-
-```sql
-SELECT t1.id, c1, c2 FROM t1, t2 WHERE t1.id = t2.id;
-
-SELECT t1.id, c1, c2 FROM t1 JOIN t2 ON t1.id = t2.id;
-
-SELECT t1.id, c1, c2 FROM t1 INNER JOIN t2 ON t1.id = t2.id;
-```
-
-#### Outer Join
-
-Outer join returns the left or right table or all rows of both. If there is no matching data in another table, set it to NULL. Example:
-
-```sql
-SELECT * FROM t1 LEFT OUTER JOIN t2 ON t1.id = t2.id;
-
-SELECT * FROM t1 RIGHT OUTER JOIN t2 ON t1.id = t2.id;
-
-SELECT * FROM t1 FULL OUTER JOIN t2 ON t1.id = t2.id;
-```
-
-#### Equivalent and unequal join
-
-Usually, users use the most equal join, which requires the operator of the join condition to be an equal sign.
-
-Unequal join can be used on join conditions!=, Equal sign. Unequal joins produce a large number of results and may exceed the memory limit during calculation.
-
-Use with caution. Unequal join only supports inner join. Example:
-
-```sql
-SELECT t1.id, c1, c2 FROM t1 INNER JOIN t2 ON t1.id = t2.id;
-
-SELECT t1.id, c1, c2 FROM t1 INNER JOIN t2 ON t1.id > t2.id;
-```
-
-#### Semi Join
-
-Left semi join returns only the rows in the left table that match the data in the right table, regardless of how many rows match the data in the right table.
-
-This row of the left table is returned at most once. Right semi join works similarly, except that the data returned is a right table.
-
-Examples:
-
-```sql
-SELECT t1.c1, t1.c2, t1.c2 FROM t1 LEFT SEMI JOIN t2 ON t1.id = t2.id;
-```
-
-#### Anti Join
-
-Left anti join only returns rows from the left table that do not match the right table.
-
-Right anti join reverses this comparison, returning only rows from the right table that do not match the left table. Example:
-
-```sql
-SELECT t1.c1, t1.c2, t1.c2 FROM t1 LEFT ANTI JOIN t2 ON t1.id = t2.id;
-```
-
-#### Equi-join and Non-equi-join
-
-The various joins supported by StarRocks can be classified as equi-joins and non-equi-joins depending on the join conditions specified in the joins.
-
-| **Equi-joins**         | Self joins, cross joins, inner joins, outer joins, semi joins, and anti joins |
-| -------------------------- | ------------------------------------------------------------ |
-| **Non-equi-joins** | cross joins, inner joins, left semi joins, left anti joins, and outer joins   |
-
-- Equi-joins
-  
-  An equi-join uses a join condition in which two join items are combined by the `=` operator. Example: `a JOIN b ON a.id = b.id`.
-
-- Non-equi-joins
-  
-  A non-equi-join uses a join condition in which two join items are combined by a comparison operator such as `<`, `<=`, `>`, `>=`, or `<>`. Example: `a JOIN b ON a.id < b.id`. Non-equi-joins run slower than equi-joins. We recommend that you exercise caution when you use non-equi-joins.
-
-  The following two examples show how to run non-equi-joins:
-
-  ```SQL
-  SELECT t1.id, c1, c2 
-  FROM t1 
-  INNER JOIN t2 ON t1.id < t2.id;
-    
-  SELECT t1.id, c1, c2 
-  FROM t1 
-  LEFT JOIN t2 ON t1.id > t2.id;
-  ```
-
-### ORDER BY
-
-The ORDER BY clause of a SELECT statement sorts the result set by comparing the values from one or more columns.
-
-ORDER BY is a time- and resource-consuming operation because all the results must be sent to one node for merging before the results can be sorted. Sorting consumes more memory resources than a query without ORDER BY.
-
-Therefore, if you only need the first `N` results from the sorted result set, you can use the LIMIT clause, which reduces memory usage and network overhead. If the LIMIT clause is not specified, the first 65535 results are returned by default.
-
-Syntax:
-
-```sql
-ORDER BY <column_name> 
-    [ASC | DESC]
-    [NULLS FIRST | NULLS LAST]
-```
-
-`ASC` specifies that the results should be returned in ascending order. `DESC` specifies that the results should be returned in descending order. If the order is not specified, ASC (ascending) is the default. Example:
-
-```sql
-select * from big_table order by tiny_column, short_column desc;
-```
-
-Sort order for NULL values: `NULLS FIRST` indicates that NULL values should be returned before non-NULL values. `NULLS LAST` indicates that NULL values should be returned after non-NULL values.
-
-Examples:
-
-```sql
-select  *  from  sales_record  order by  employee_id  nulls first;
-```
-
-### GROUP BY
-
-The GROUP BY clause is often used with aggregate functions such as COUNT(), SUM(), AVG(), MIN(), and MAX().
-
-The column specified by GROUP BY will not participate in the aggregation operation. The GROUP BY clause can be added with the Having clause to filter the results produced by the aggregate function.
-
-Examples:
-
-```sql
-select tiny_column, sum(short_column)
-from small_table 
-group by tiny_column;
-```
-
-```plain text
-+-------------+---------------------+
-| tiny_column |  sum('short_column')|
-+-------------+---------------------+
-|      1      |        2            |
-|      2      |        1            |
-+-------------+---------------------+
-```
-
-#### Syntax
-
-  ```sql
-  SELECT ...
-  FROM ...
-  [ ... ]
-  GROUP BY [
-      , ... |
-      GROUPING SETS [, ...] (  groupSet [ , groupSet [ , ... ] ] ) |
-      ROLLUP(expr  [ , expr [ , ... ] ]) |
-      CUBE(expr  [ , expr [ , ... ] ])
-      ]
-  [ ... ]
-  ```
-
-#### Parameters
-
-  `groupSet` represents a set composed of columns, aliases or expressions in the select list.  `groupSet ::= { ( expr  [ , expr [ , ... ] ] )}`
-
-  `expr`  indicates the column, alias or expression in the select list.
-
-#### Note
-
-StarRocks supports syntax like PostgreSQL. The syntax examples are as follows:
-
-  ```sql
-  SELECT a, b, SUM( c ) FROM tab1 GROUP BY GROUPING SETS ( (a, b), (a), (b), ( ) );
-  SELECT a, b,c, SUM( d ) FROM tab1 GROUP BY ROLLUP(a,b,c)
-  SELECT a, b,c, SUM( d ) FROM tab1 GROUP BY CUBE(a,b,c)
-  ```
-
-  `ROLLUP(a,b,c)` is equivalent to the following`GROUPING SETS` statement:
-
-  ```sql
-  GROUPING SETS (
-  (a,b,c),
-  ( a, b ),
-  ( a),
-  ( )
-  )
-  ```
-
-  `CUBE ( a, b, c )`  is equivalent to the following`GROUPING SETS` statement:
-
-  ```sql
-  GROUPING SETS (
-  ( a, b, c ),
-  ( a, b ),
-  ( a,    c ),
-  ( a       ),
-  (    b, c ),
-  (    b    ),
-  (       c ),
-  (         )
-  )
-  ```
-
-#### Examples
-
-  The following is an example of actual data:
-
-  ```plain text
-  SELECT * FROM t;
-  +------+------+------+
-  | k1   | k2   | k3   |
-  +------+------+------+
-  | a    | A    |    1 |
-  | a    | A    |    2 |
-  | a    | B    |    1 |
-  | a    | B    |    3 |
-  | b    | A    |    1 |
-  | b    | A    |    4 |
-  | b    | B    |    1 |
-  | b    | B    |    5 |
-  +------+------+------+
-  8 rows in set (0.01 sec)
-
-  SELECT k1, k2, SUM(k3) FROM t GROUP BY GROUPING SETS ( (k1, k2), (k2), (k1), ( ) );
-  +------+------+-----------+
-  | k1   | k2   | sum(`k3`) |
-  +------+------+-----------+
-  | b    | B    |         6 |
-  | a    | B    |         4 |
-  | a    | A    |         3 |
-  | b    | A    |         5 |
-  | NULL | B    |        10 |
-  | NULL | A    |         8 |
-  | a    | NULL |         7 |
-  | b    | NULL |        11 |
-  | NULL | NULL |        18 |
-  +------+------+-----------+
-  9 rows in set (0.06 sec)
-
-  > SELECT k1, k2, GROUPING_ID(k1,k2), SUM(k3) FROM t GROUP BY GROUPING SETS ((k1, k2), (k1), (k2), ());
-  +------+------+---------------+----------------+
-  | k1   | k2   | grouping_id(k1,k2) | sum(`k3`) |
-  +------+------+---------------+----------------+
-  | a    | A    |             0 |              3 |
-  | a    | B    |             0 |              4 |
-  | a    | NULL |             1 |              7 |
-  | b    | A    |             0 |              5 |
-  | b    | B    |             0 |              6 |
-  | b    | NULL |             1 |             11 |
-  | NULL | A    |             2 |              8 |
-  | NULL | B    |             2 |             10 |
-  | NULL | NULL |             3 |             18 |
-  +------+------+---------------+----------------+
-  9 rows in set (0.02 sec)
-  ```
-
-GROUP BY `GROUPING SETS` ｜ `CUBE` ｜ `ROLLUP` is an extension of the GROUP BY clause. It can realize the aggregation of groups of multiple sets in a GROUP BY clause. The result is equivalent to the UNION operation of multiple corresponding GROUP BY clauses.
-
-GROUP BY clause is a special case of GROUP BY GROUPING SETS containing only one element. For example, the GROUPING SETS statement:
-
-  ```sql
-  SELECT a, b, SUM( c ) FROM tab1 GROUP BY GROUPING SETS ( (a, b), (a), (b), ( ) );
-  ```
-
-  The query result is equivalent to:
-
-  ```sql
-  SELECT a, b, SUM( c ) FROM tab1 GROUP BY a, b
-  UNION
-  SELECT a, null, SUM( c ) FROM tab1 GROUP BY a
-  UNION
-  SELECT null, b, SUM( c ) FROM tab1 GROUP BY b
-  UNION
-  SELECT null, null, SUM( c ) FROM tab1
-  ```
-
-  `GROUPING(expr)` indicates whether a column is an aggregate column. If it is an aggregate column, it is 0, otherwise it is 1.
-
-  `GROUPING_ID(expr  [ , expr [ , ... ] ])` is similar to GROUPING. GROUPING_ ID calculates the bitmap value of a column list according to the specified column order, and each bit is the value of GROUPING.
-  
-  GROUPING_ID() function returns the decimal value of the bit vector.
-
-### HAVING
-
-The HAVING clause does not filter row data in a table, but filters the results of aggregate functions.
-
-Generally speaking, HAVING is used with aggregate functions (such as COUNT(), SUM(), AVG(), MIN(), MAX()) and GROUP BY clauses.
-
-Examples:
-
-```sql
-select tiny_column, sum(short_column) 
-from small_table 
-group by tiny_column 
-having sum(short_column) = 1;
-```
-
-```plain text
-+-------------+---------------------+
-|tiny_column  | sum('short_column') |
-+-------------+---------------------+
-|         2   |        1            |
-+-------------+---------------------+
-
-1 row in set (0.07 sec)
-```
-
-```sql
-select tiny_column, sum(short_column) 
-from small_table 
-group by tiny_column 
-having tiny_column > 1;
-```
-
-```plain text
-+-------------+---------------------+
-|tiny_column  | sum('short_column') |
-+-------------+---------------------+
-|      2      |          1          |
-+-------------+---------------------+
-
-1 row in set (0.07 sec)
-```
-
-### LIMIT
-
-LIMIT clauses are used to limit the maximum number of rows returned. Setting the maximum number of rows returned can help StarRocks optimize memory usage.
-
-This clause is mainly used in the following scenarios:
-
-Returns the result of the top-N query.
-
-Think about what's included in the table below.
-
-The size of the query result set needs to be limited because of the large amount of data in the table or because the where clause does not filter too much data.
-
-Instructions for use: The value of the LIMIT clause must be a numeric literal constant.
-
-Examples:
-
-```plain text
-mysql> select tiny_column from small_table limit 1;
-
-+-------------+
-|tiny_column  |
-+-------------+
-|     1       |
-+-------------+
-
-1 row in set (0.02 sec)
-```
-
-```plain text
-mysql> select tiny_column from small_table limit 10000;
-
-+-------------+
-|tiny_column  |
-+-------------+
-|      1      |
-|      2      |
-+-------------+
-
-2 rows in set (0.01 sec)
-```
-
-### OFFSET
-
-The OFFSET clause causes the result set to skip the first few rows and return the following results directly.
-
-The result set defaults to start at line 0, so offset 0 and no offset return the same results.
-
-Generally speaking, OFFSET clauses need to be used with ORDER BY and LIMIT clauses to be valid.
-
-Examples:
-
-```plain text
-mysql> select varchar_column from big_table order by varchar_column limit 3;
-
-+----------------+
-| varchar_column | 
-+----------------+
-|    beijing     | 
-|    chongqing   | 
-|    tianjin     | 
-+----------------+
-
-3 rows in set (0.02 sec)
-```
-
-```plain text
-mysql> select varchar_column from big_table order by varchar_column limit 1 offset 0;
-
-+----------------+
-|varchar_column  |
-+----------------+
-|     beijing    |
-+----------------+
-
-1 row in set (0.01 sec)
-```
-
-```plain text
-mysql> select varchar_column from big_table order by varchar_column limit 1 offset 1;
-
-+----------------+
-|varchar_column  |
-+----------------+
-|    chongqing   | 
-+----------------+
-
-1 row in set (0.01 sec)
-```
-
-```plain text
-mysql> select varchar_column from big_table order by varchar_column limit 1 offset 2;
-
-+----------------+
-|varchar_column  |
-+----------------+
-|     tianjin    |     
-+----------------+
-
-1 row in set (0.02 sec)
-```
-
-Note: It is allowed to use offset syntax without order by, but offset does not make sense at this time.
-
-In this case, only the limit value is taken, and the offset value is ignored. So without order by.
-
-Offset exceeds the maximum number of rows in the result set and is still a result. It is recommended that users use offset with order by.
-
-### UNION
-
-Combines the result of multiple queries.
-
-**Syntax:**
-
-```sql
-query_1 UNION [DISTINCT | ALL] query_2
-```
-
-- DISTINCT (default) returns only unique rows. UNION is equivalent to UNION DISTINCT.
-- ALL combines all rows, including duplicates. Since de-duplication is memory intensive, queries using UNION ALL are faster and less memory-consuming. For better performance, use UNION ALL.
-
-> **NOTE**
->
-> Each query statement must return the same number of columns and the columns must have compatible data types.
-
-**Examples:**
-
-Create tables `select1` and `select2`.
-
-```SQL
-CREATE TABLE select1(
-    id          INT,
-    price       INT
-    )
-DISTRIBUTED BY HASH(id);
-
-INSERT INTO select1 VALUES
-    (1,2),
-    (1,2),
-    (2,3),
-    (5,6),
-    (5,6);
-
-CREATE TABLE select2(
-    id          INT,
-    price       INT
-    )
-DISTRIBUTED BY HASH(id);
-
-INSERT INTO select2 VALUES
-    (2,3),
-    (3,4),
-    (5,6),
-    (7,8);
-```
-
-Example 1: Return all IDs in the two tables, including duplicates.
-
-```Plaintext
-mysql> (select id from select1) union all (select id from select2) order by id;
-
-+------+
-| id   |
-+------+
-|    1 |
-|    1 |
-|    2 |
-|    2 |
-|    3 |
-|    5 |
-|    5 |
-|    5 |
-|    7 |
-+------+
-11 rows in set (0.02 sec)
-```
-
-Example 2: Return all the unique IDs in the two tables. The following two statements are equivalent.
-
-```Plaintext
-mysql> (select id from select1) union (select id from select2) order by id;
-
-+------+
-| id   |
-+------+
-|    1 |
-|    2 |
-|    3 |
-|    5 |
-|    7 |
-+------+
-6 rows in set (0.01 sec)
-
-mysql> (select id from select1) union distinct (select id from select2) order by id;
-+------+
-| id   |
-+------+
-|    1 |
-|    2 |
-|    3 |
-|    5 |
-|    7 |
-+------+
-5 rows in set (0.02 sec)
-```
-
-Example 3: Return the first three IDs among all the unique IDs in the two tables. The following two statements are equivalent.
-
-```SQL
-mysql> (select id from select1) union distinct (select id from select2)
-order by id
-limit 3;
-++------+
-| id   |
-+------+
-|    1 |
-|    2 |
-|    3 |
-+------+
-4 rows in set (0.11 sec)
-
-mysql> select * from (select id from select1 union distinct select id from select2) as t1
-order by id
-limit 3;
-+------+
-| id   |
-+------+
-|    1 |
-|    2 |
-|    3 |
-+------+
-3 rows in set (0.01 sec)
-```
-
-### **INTERSECT**
-
-Calculates the intersection of the results of multiple queries, that is, the results that appear in all the result sets. This clause returns only unique rows among the result sets. The ALL keyword is not supported.
-
-**Syntax:**
-
-```SQL
-query_1 INTERSECT [DISTINCT] query_2
-```
-
-> **NOTE**
->
-> - INTERSECT is equivalent to INTERSECT DISTINCT.
-> - Each query statement must return the same number of columns and the columns must have compatible data types.
-
-**Examples:**
-
-The two tables in UNION  are used.
-
-Return distinct `(id, price)` combinations that are common to both tables. The following two statements are equivalent.
-
-```Plaintext
-mysql> (select id, price from select1) intersect (select id, price from select2)
-order by id;
-
-+------+-------+
-| id   | price |
-+------+-------+
-|    2 |     3 |
-|    5 |     6 |
-+------+-------+
-
-mysql> (select id, price from select1) intersect distinct (select id, price from select2)
-order by id;
-
-+------+-------+
-| id   | price |
-+------+-------+
-|    2 |     3 |
-|    5 |     6 |
-+------+-------+
-```
-
-### **EXCEPT/MINUS**
-
-Returns distinct results of the left-hand query that do not exist in the right-hand query. EXCEPT is equivalent to MINUS.
-
-**Syntax:**
-
-```SQL
-query_1 {EXCEPT | MINUS} [DISTINCT] query_2
-```
-
-> **NOTE**
->
-> - EXCEPT is equivalent to EXCEPT DISTINCT. The ALL keyword is not supported.
-> - Each query statement must return the same number of columns and the columns must have compatible data types.
-
-**Examples:**
-
-The two tables in UNION  are used.
-
-Return distinct `(id, price)` combinations in `select1` that cannot be found in `select2`.
-
-```Plaintext
-mysql> (select id, price from select1) except (select id, price from select2)
-order by id;
-+------+-------+
-| id   | price |
-+------+-------+
-|    1 |     2 |
-+------+-------+
-
-mysql> (select id, price from select1) minus (select id, price from select2)
-order by id;
-+------+-------+
-| id   | price |
-+------+-------+
-|    1 |     2 |
-+------+-------+
-```
-
-### DISTINCT
-
-The DISTINCT keyword deduplicates the result set. Example:
-
-```SQL
--- Returns the unique values from one column.
-select distinct tiny_column from big_table limit 2;
-
--- Returns the unique combinations of values from multiple columns.
-select distinct tiny_column, int_column from big_table limit 2;
-```
-
-DISTINCT can be used with aggregate functions (usually count functions), and count (distinct) is used to calculate how many different combinations are contained on one or more columns.
-
-```SQL
--- Counts the unique values from one column.
-select count(distinct tiny_column) from small_table;
-```
-
-```plain text
-+-------------------------------+
-| count(DISTINCT 'tiny_column') |
-+-------------------------------+
-|             2                 |
-+-------------------------------+
-1 row in set (0.06 sec)
-```
-
-```SQL
--- Counts the unique combinations of values from multiple columns.
-select count(distinct tiny_column, int_column) from big_table limit 2;
-```
-
-StarRocks supports multiple aggregate functions using distinct at the same time.
-
-```SQL
--- Count the unique value from multiple aggregation function separately.
-select count(distinct tiny_column, int_column), count(distinct varchar_column) from big_table;
-```
-
-### Subquery
-
-Subqueries are categorized into two types in terms of relevance:
-
-- A noncorrelated subquery obtains its results independently of its outer query.
-- A correlated subquery requires values from its outer query.
-
-#### Noncorrelated subquery
-
-Noncorrelated subqueries support [NOT] IN and EXISTS.
-
-Example:
-
-```sql
-SELECT x FROM t1 WHERE x [NOT] IN (SELECT y FROM t2);
-
-SELECT * FROM t1 WHERE (x,y) [NOT] IN (SELECT x,y FROM t2 LIMIT 2);
-
-SELECT x FROM t1 WHERE EXISTS (SELECT y FROM t2 WHERE y = 1);
-```
-
-From v3.0 onwards, you can specify multiple fields in the WHERE clause of `SELECT... FROM... WHERE... [NOT] IN`, for example, `WHERE (x,y)` in the second SELECT statement.
-
-#### Correlated subquery
-
-Related subqueries support [NOT] IN and [NOT] EXISTS.
-
-Example:
-
-```sql
-SELECT * FROM t1 WHERE x [NOT] IN (SELECT a FROM t2 WHERE t1.y = t2.b);
-
-SELECT * FROM t1 WHERE [NOT] EXISTS (SELECT a FROM t2 WHERE t1.y = t2.b);
-```
-
-Subqueries also support scalar quantum queries. It can be divided into irrelevant scalar quantum query, related scalar quantum query and scalar quantum query as parameters of the general function.
-
-Examples:
-
-1. Uncorrelated scalar quantum query with predicate = sign. For example, output information about the person with the highest wage.
-
-    ```sql
-    SELECT name FROM table WHERE salary = (SELECT MAX(salary) FROM table);
-    ```
-
-2. Uncorrelated scalar quantum queries with predicates `>`, `<` etc. For example, output information about people who are paid more than average.
-
-    ```sql
-    SELECT name FROM table WHERE salary > (SELECT AVG(salary) FROM table);
-    ```
-
-3. Related scalar quantum queries. For example, output the highest salary information for each department.
-
-    ```sql
-    SELECT name FROM table a WHERE salary = (SELECT MAX(salary) FROM table b WHERE b.Department= a.Department);
-    ```
-
-4. Scalar quantum queries are used as parameters of ordinary functions.
-
-    ```sql
-    SELECT name FROM table WHERE salary = abs((SELECT MAX(salary) FROM table));
-    ```
-
-### Where and Operators
-
-SQL operators are a series of functions used for comparison and are widely used in where clauses of select statements.
-
-#### Arithmetic operator
-
-Arithmetic operators usually appear in expressions that contain left, right, and most often left operands
-
-**+and-**: can be used as a unit or as a 2-ary operator. When used as a unit operator, such as +1, -2.5 or -col_ name, which means the value is multiplied by +1 or -1.
-
-So the cell operator + returns an unchanged value, and the cell operator - changes the symbol bits of that value.
-
-Users can overlay two cell operators, such as +5 (returning a positive value), -+2 or +2 (returning a negative value), but users cannot use two consecutive - signs.
-
-Because--is interpreted as a comment in the following statement (when a user can use two-signs, a space or parenthesis is required between the two-signs, such as-(-2) or - -2, which actually results in + 2).
-
-When + or - is a binary operator, such as 2+2, 3+1.5, or col1+col2, it means that the left value is added or subtracted from the right value. Both left and right values must be numeric types.
-
-**and/**: represent multiplication and division, respectively. The operands on both sides must be data types. When two numbers are multiplied.
-
-Smaller operands may be promoted if needed (e.g., SMALLINT to INT or BIGINT), and the result of the expression will be promoted to the next larger type.
-
-For example, TINYINT multiplied by INT will produce a BIGINT type of result. When two numbers are multiplied, both operands and expression results are interpreted as DOUBLE types to avoid loss of precision.
-
-If the user wants to convert the result of the expression to another type, it needs to be converted using the CAST function.
-
-**%**: Modulation operator. Returns the remainder of the left operand divided by the right operand. Both left and right operands must be integers.
-
-**&, |and ^**: The bitwise operator returns the result of bitwise AND, bitwise OR, bitwise XOR operations on two operands. Both operands require an integer type.
-
-If the types of the two operands of a bitwise operator are inconsistent, the operands of a smaller type are promoted to the operands of a larger type, and the corresponding bitwise operations are performed.
-
-Multiple arithmetic operators can appear in an expression, and the user can enclose the corresponding arithmetic expression in parentheses. Arithmetic operators usually do not have corresponding mathematical functions to express the same functions as arithmetic operators.
-
-For example, we don't have the MOD() function to represent the% operator. Conversely, mathematical functions do not have corresponding arithmetic operators. For example, the power function POW() does not have a corresponding ** exponentiation operator.
-
- Users can find out which arithmetic functions we support through the Mathematical Functions section.
-
-#### Between Operator
-
-In a where clause, expressions may be compared with both upper and lower bounds. If the expression is greater than or equal to the lower bound and less than or equal to the upper bound, the result of the comparison is true.
-
-Syntax:
-
-```sql
-expression BETWEEN lower_bound AND upper_bound
-```
-
-Data type: Usually an expression evaluates to a numeric type, which also supports other data types. If you must ensure that both the lower and upper bounds are comparable characters, you can use the cast() function.
-
- Instructions for use: If the operand is of type string, note that a long string starting with an upper bound will not match the upper bound, which is larger than the upper bound. For example, "between'A'and'M' will not match 'MJ'.
-
- If you need to make sure the expression works correctly, you can use functions such as upper(), lower(), substr(), trim().
-
-Example:
-
-```sql
-select c1 from t1 where month between 1 and 6;
-```
-
-#### Comparison operators
-
-Comparison operators are used to compare two values. `=`, `!=`, `>=` apply to all data types.
-
-The `<>` and `!=` operators are equivalent, which indicate that two values are not equal.
-
-#### In Operator
-
-The In operator compares to the VALUE collection and returns TRUE if it can match any of the elements in the collection.
-
-Parameters and VALUE collections must be comparable. All expressions using the IN operator can be written as equivalent comparisons connected with OR, but the syntax of IN is simpler, more precise, and easier for StarRocks to optimize.
-
-Examples:
-
-```sql
-select * from small_table where tiny_column in (1,2);
-```
-
-#### Like Operator
-
-This operator is used to compare to a string. ''matches a single character,'%' matches multiple characters. The parameter must match the complete string. Typically, placing'%'at the end of a string is more practical.
-
-Examples:
-
-```plain text
-mysql> select varchar_column from small_table where varchar_column like 'm%';
-
-+----------------+
-|varchar_column  |
-+----------------+
-|     milan      |
-+----------------+
-
-1 row in set (0.02 sec)
-```
-
-```plain
-mysql> select varchar_column from small_table where varchar_column like 'm____';
-
-+----------------+
-| varchar_column | 
-+----------------+
-|    milan       | 
-+----------------+
-
-1 row in set (0.01 sec)
-```
-
-#### Logical Operator
-
-Logical operators return a BOOL value, including unit and multiple operators, each of which handles parameters that are expressions that return BOOL values. Supported operators are:
-
-AND: 2-ary operator, the AND operator returns TRUE if the parameters on the left and right are both calculated as TRUE.
-
-OR: 2-ary operator that returns TRUE if one of the parameters on the left and right is calculated as TRUE. If both parameters are FALSE, the OR operator returns FALSE.
-
-NOT: Unit operator, the result of inverting an expression. If the parameter is TRUE, the operator returns FALSE; If the parameter is FALSE, the operator returns TRUE.
-
-Examples:
-
-```plain text
-mysql> select true and true;
-
-+-------------------+
-| (TRUE) AND (TRUE) | 
-+-------------------+
-|         1         | 
-+-------------------+
-
-1 row in set (0.00 sec)
-```
-
-```plain text
-mysql> select true and false;
-
-+--------------------+
-| (TRUE) AND (FALSE) | 
-+--------------------+
-|         0          | 
-+--------------------+
-
-1 row in set (0.01 sec)
-```
-
-```plain text
-mysql> select true or false;
-
-+-------------------+
-| (TRUE) OR (FALSE) | 
-+-------------------+
-|        1          | 
-+-------------------+
-
-1 row in set (0.01 sec)
-```
-
-```plain text
-mysql> select not true;
-
-+----------+
-| NOT TRUE | 
-+----------+
-|     0    | 
-+----------+
-
-1 row in set (0.01 sec)
-```
-
-#### Regular Expression Operator
-
-Determines whether the regular expression is matched. Using POSIX standard regular expressions,'^'matches the first part of the string,'$' matches the end of the string.
-
-"." matches any single character, "*" matches zero or more options, "+" matches one or more options, "?" means greedy representation, and so on. Regular expressions need to match complete values, not just parts of strings.
-
-If you want to match the middle part, the front part of the regular expression can be written as'^. 'or'.'. '^'and'$' are usually omitted. The RLIKE operator and the REGEXP operator are synonyms.
-
-The'|'operator is an optional operator. Regular expressions on either side of'|' only need to satisfy one side condition. The'|'operator and regular expressions on both sides usually need to be enclosed in ().
-
-Examples:
-
-```plain text
-mysql> select varchar_column from small_table where varchar_column regexp '(mi|MI).*';
-
-+----------------+
-| varchar_column | 
-+----------------+
-|     milan      |       
-+----------------+
-
-1 row in set (0.01 sec)
-```
-
-```plain text
-mysql> select varchar_column from small_table where varchar_column regexp 'm.*';
-
-+----------------+
-| varchar_column | 
-+----------------+
-|     milan      |  
-+----------------+
-
-1 row in set (0.01 sec)
-```
-
-### Alias
-
-When you write the names of tables, columns, or expressions that contain columns in a query, you can assign them an alias. Aliases are usually shorter and better to remember than original names.
-
-When an alias is needed, you can simply add an AS clause after the table, column, and expression names in the select list or from list. The AS keyword is optional. You can also specify aliases directly after the original name without using AS.
-
-If an alias or other identifier has the same name as an internal [StarRocks keyword](../keywords.md), you need to enclose the name in a pair of backticks, for example, `rank`.
-
-Aliases are case-sensitive, but column aliases and expression aliases are not case-sensitive.
-
-Examples:
-
-```sql
-select tiny_column as name, int_column as sex from big_table;
-
-select sum(tiny_column) as total_count from big_table;
-
-select one.tiny_column, two.int_column from small_table one, <br/> big_table two where one.tiny_column = two.tiny_column;
-```
-
-### PIVOT
-
-The PIVOT operation is an advanced feature in SQL that allows you to transform rows into columns in a table, which is particularly useful for creating pivot tables. This comes in handy when dealing with database reports or analytics, especially when you need to summarize or categorize data for presentation.
-
-Actually, the PIVOT is a syntax sugar, which can simplify the writing of the query statement like `sum(case when ... then ... end)`.
-
-#### Syntax
-
-```sql
-pivot:
-SELECT ...
-FROM ...
-PIVOT (
-  aggregate_function(<expr>) [[AS] alias] [, aggregate_function(<expr>) [[AS] alias] ...]
-  FOR <pivot_column>
-  IN (<pivot_value>)
-)
-
-pivot_column:
-<column_name> 
-| (<column_name> [, <column_name> ...])
-
-pivot_value:
-<literal> [, <literal> ...]
-| (<literal>, <literal> ...) [, (<literal>, <literal> ...)]
-```
-
-#### Parameters
-
-In a PIVOT operation, you need to specify several key components:
-
-- aggregate_function(): An aggregate function such as SUM, AVG, COUNT, etc., used to summarize the data.
-- alias: An alias for the aggregated result, making the outcome more understandable.
-- FOR pivot_column: Specifies the column name on which the row-to-column transformation will be performed.
-- IN (pivot_value): Specifies the specific values of the pivot_column that will be transformed into columns.
-
-#### Examples
-
-```sql
-create table t1 (c0 int, c1 int, c2 int, c3 int);
-SELECT * FROM t1 PIVOT (SUM(c1) AS sum_c1, AVG(c2) AS avg_c2 FOR c3 IN (1, 2, 3, 4, 5));
--- The result is equivalent to the following query:
-SELECT SUM(CASE WHEN c3 = 1 THEN c1 ELSE NULL END) AS sum_c1_1,
-       AVG(CASE WHEN c3 = 1 THEN c2 ELSE NULL END) AS avg_c2_1,
-       SUM(CASE WHEN c3 = 2 THEN c1 ELSE NULL END) AS sum_c1_2,
-       AVG(CASE WHEN c3 = 2 THEN c2 ELSE NULL END) AS avg_c2_2,
-       SUM(CASE WHEN c3 = 3 THEN c1 ELSE NULL END) AS sum_c1_3,
-       AVG(CASE WHEN c3 = 3 THEN c2 ELSE NULL END) AS avg_c2_3,
-       SUM(CASE WHEN c3 = 4 THEN c1 ELSE NULL END) AS sum_c1_4,
-       AVG(CASE WHEN c3 = 4 THEN c2 ELSE NULL END) AS avg_c2_4,
-       SUM(CASE WHEN c3 = 5 THEN c1 ELSE NULL END) AS sum_c1_5,
-       AVG(CASE WHEN c3 = 5 THEN c2 ELSE NULL END) AS avg_c2_5
-FROM t1
-GROUP BY c0;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_ALTER.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_ALTER.md
deleted file mode 100644
index d460dfc0829cfc..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_ALTER.md
+++ /dev/null
@@ -1,69 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW ALTER TABLE
-
-## Description
-
-Shows the execution of the ongoing ALTER TABLE operations, including:
-
-- Modify columns.
-- Optimize table schema (from v3.2), including modifying the bucketing method and the number of buckets.
-- Create and delete the rollup index.
-
-## Syntax
-
-- Show the execution of operations of modifying columns or optimizing table schema.
-
-    ```sql
-    SHOW ALTER TABLE { COLUMN | OPTIMIZE } [FROM db_name] [WHERE TableName|CreateTime|FinishTime|State] [ORDER BY] [LIMIT]
-    ```
-
-- Show the execution of operations of adding or deleting the rollup index.
-
-    ```sql
-    SHOW ALTER TABLE ROLLUP [FROM db_name]
-    ```
-
-## Parameters
-
-- `{COLUMN ｜ OPTIMIZE | ROLLUP}`:
-
-  - If `COLUMN` is specified, this statement shows operations of modifying columns.
-  - If `OPTIMIZE` is specified, this statement shows operations of optimizing table structure.
-  - If `ROLLUP` is specified, this statement shows operations of adding or deleting the rollup index.
-
-- `db_name`: optional. If `db_name` is not specified, the current database is used by default.
-
-## Examples
-
-1. Show the execution of operations of modifying columns, optimizing table schema, and creating or deleting the rollup index in the current database.
-
-    ```sql
-    SHOW ALTER TABLE COLUMN;
-    SHOW ALTER TABLE OPTIMIZE;
-    SHOW ALTER TABLE ROLLUP;
-    ```
-
-2. Show the execution of operations related to modifying columns, optimizing table schema, and creating or deleting the rollup index in a specified database.
-
-    ```sql
-    SHOW ALTER TABLE COLUMN FROM example_db;
-    SHOW ALTER TABLE OPTIMIZE FROM example_db;
-    SHOW ALTER TABLE ROLLUP FROM example_db;
-    ```
-
-3. Show the execution of the most recent operation of modifying columns or optimizing table schema in a specified table.
-
-    ```sql
-    SHOW ALTER TABLE COLUMN WHERE TableName = "table1" ORDER BY CreateTime DESC LIMIT 1;
-    SHOW ALTER TABLE OPTIMIZE WHERE TableName = "table1" ORDER BY CreateTime DESC LIMIT 1; 
-    ```
-
-## References
-
-- [CREATE TABLE](../data-definition/CREATE_TABLE.md)
-- [ALTER TABLE](../data-definition/ALTER_TABLE.md)
-- [SHOW TABLES](../data-manipulation/SHOW_TABLES.md)
-- [SHOW CREATE TABLE](../data-manipulation/SHOW_CREATE_TABLE.md)
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW.md
deleted file mode 100644
index 387049ac176e6d..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW.md
+++ /dev/null
@@ -1,81 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW ALTER MATERIALIZED VIEW
-
-## Description
-
-Shows the building status of synchronous materialized views.
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```SQL
-SHOW ALTER MATERIALIZED VIEW [ { FROM | IN } db_name]
-```
-
-Parameters in brackets [] is optional.
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                              |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| db_name       | no           | The name of the database to which the materialized view resides. If this parameter is not specified, the current database is used by default. |
-
-## Returns
-
-| **Return**      | **Description**                                  |
-| --------------- | ------------------------------------------------ |
-| JobId           | The ID of refresh job.                           |
-| TableName       | The name of the table.                           |
-| CreateTime      | The time when refresh job is created.            |
-| FinishedTime    | The time when refresh job is finished.           |
-| BaseIndexName   | The name of the base table.                      |
-| RollupIndexName | The name of the materialized view.               |
-| RollupId        | The ID of the materialized view rollup.          |
-| TransactionId   | The ID of transaction that waits to be executed. |
-| State           | The state of the job.                            |
-| Msg             | Error message.                                   |
-| Progress        | Progress of the refresh job.                     |
-| Timeout         | Timeout for the refresh job.                     |
-
-## Examples
-
-Example 1: building status of synchronous materialized views
-
-```Plain
-MySQL > SHOW ALTER MATERIALIZED VIEW\G
-*************************** 1. row ***************************
-          JobId: 475991
-      TableName: lineorder
-     CreateTime: 2022-08-24 19:46:53
-   FinishedTime: 2022-08-24 19:47:15
-  BaseIndexName: lineorder
-RollupIndexName: lo_mv_sync_1
-       RollupId: 475992
-  TransactionId: 33067
-          State: FINISHED
-            Msg: 
-       Progress: NULL
-        Timeout: 86400
-*************************** 2. row ***************************
-          JobId: 477337
-      TableName: lineorder
-     CreateTime: 2022-08-24 19:47:25
-   FinishedTime: 2022-08-24 19:47:45
-  BaseIndexName: lineorder
-RollupIndexName: lo_mv_sync_2
-       RollupId: 477338
-  TransactionId: 33068
-          State: FINISHED
-            Msg: 
-       Progress: NULL
-        Timeout: 86400
-2 rows in set (0.00 sec)
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md
deleted file mode 100644
index da4caf2f8e718d..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md
+++ /dev/null
@@ -1,55 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW CATALOGS
-
-## Description
-
-Query all catalogs in the current StarRocks cluster, including the internal catalog and external catalogs.
-
-> **NOTE**
->
-> SHOW CATALOGS returns external catalogs to users who have the USAGE privilege on that external catalog. If users or roles do not have this privilege on any external catalog, this command returns only the default_catalog.
-
-## Syntax
-
-```SQL
-SHOW CATALOGS
-```
-
-## Output
-
-```SQL
-+----------+--------+----------+
-| Catalog  | Type   | Comment  |
-+----------+--------+----------+
-```
-
-The following table describes the fields returned by this statement.
-
-| **Field** | **Description**                                              |
-| ------------- | ------------------------------------------------------------ |
-| Catalog       | The catalog name.                                            |
-| Type          | The catalog type. `Internal` is returned if the catalog is `default_catalog`. The corresponding catalog type is returned if the catalog is an external catalog, such as `Hive`, `Hudi`, or `Iceberg`. |
-| Comment       | The comments of a catalog. StarRocks does not support adding comments to an external catalog. Therefore, the value is `NULL` for an external catalog. If the catalog is `default_catalog`, the comment is `An internal catalog contains this cluster's self-managed tables.` by default. `default_catalog` is the only internal catalog in a StarRocks cluster. |
-
-## Examples
-
-Query all catalogs in the current cluster.
-
-```SQL
-SHOW CATALOGS\G
-*************************** 1. row ***************************
-Catalog: default_catalog
-   Type: Internal
-Comment: An internal catalog contains this cluster's self-managed tables.
-*************************** 2. row ***************************
-Catalog: hudi_catalog
-   Type: Hudi
-Comment: NULL
-*************************** 3. row ***************************
-Catalog: iceberg_catalog
-   Type: Iceberg
-Comment: NULL
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md
deleted file mode 100644
index 47c63ca6ca3479..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md
+++ /dev/null
@@ -1,70 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW CREATE CATALOG
-
-## Description
-
-Queries the creation statement of an external catalog, including:
-
-- [Hive Catalog](../../../data_source/catalog/hive_catalog.md)
-- [Iceberg Catalog](../../../data_source/catalog/iceberg_catalog.md)
-- [Hudi Catalog](../../../data_source/catalog/hudi_catalog.md)
-- [Delta Lake Catalog](../../../data_source/catalog/deltalake_catalog.md)
-- [JDBC catalog](../../../data_source/catalog/jdbc_catalog.md) (since v3.0)
-- [Unified catalog](../../../data_source/catalog/unified_catalog.md) (since v3.2)
-- [MaxCompute catalog](../../../data_source/catalog/maxcompute_catalog.md) (since v3.3)
-
-Note that authentication-related information in the return result will be anonymized.
-
-This command is supported from v3.0 onwards.
-
-## Syntax
-
-```SQL
-SHOW CREATE CATALOG <catalog_name>;
-```
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                              |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| catalog_name  | Yes          | The name of the catalog whose creation statement you want to view. |
-
-## Return result
-
-```Plain
-+------------+-----------------+
-| Catalog    | Create Catalog  |
-+------------+-----------------+
-```
-
-| **Field**  | **Description**                                        |
-| -------------- | ------------------------------------------------------ |
-| Catalog        | The name of the catalog.                               |
-| Create Catalog | The statement that was executed to create the catalog. |
-
-## Examples
-
-The following example queries the creation statement of a Hive catalog named `hive_catalog_hms`:
-
-```SQL
-SHOW CREATE CATALOG hive_catalog_hms;
-```
-
-The return result is as follows:
-
-```SQL
-CREATE EXTERNAL CATALOG `hive_catalog_hms`
-PROPERTIES ("aws.s3.access_key"  =  "AK******M4",
-"hive.metastore.type"  =  "glue",
-"aws.s3.secret_key"  =  "iV******iD",
-"aws.glue.secret_key"  =  "iV******iD",
-"aws.s3.use_instance_profile"  =  "false",
-"aws.s3.region"  =  "us-west-1",
-"aws.glue.region"  =  "us-west-1",
-"type"  =  "hive",
-"aws.glue.access_key"  =  "AK******M4"
-)
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_DATABASE.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_DATABASE.md
deleted file mode 100644
index a4cbb2fe735094..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_DATABASE.md
+++ /dev/null
@@ -1,42 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW CREATE DATABASE
-
-Shows the SQL command used to create a database.
-
-## Syntax
-
-```sql
-SHOW CREATE DATABASE <db_name>
-```
-
-## Parameters
-
-`db_name`: the database name, required.
-
-## Returns
-
-- `Database`: the database name
-
-- `Create Database`: the SQL command used to create the database
-
-## Examples
-
-```sql
-mysql > show create database zj_test;
-+----------+---------------------------+
-| Database | Create Database           |
-+----------+---------------------------+
-| zj_test  | CREATE DATABASE `zj_test` |
-+----------+---------------------------+
-```
-
-## References
-
-- [CREATE DATABASE](../data-definition/CREATE_DATABASE.md)
-- [SHOW DATABASES](SHOW_DATABASES.md)
-- [USE](../data-definition/USE.md)
-- [DESC](../Utility/DESCRIBE.md)
-- [DROP DATABASE](../data-definition/DROP_DATABASE.md)
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_MATERIALIZED_VIEW.md
deleted file mode 100644
index 4fa4f32b4aa74c..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_MATERIALIZED_VIEW.md
+++ /dev/null
@@ -1,56 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW CREATE MATERIALIZED VIEW
-
-## Description
-
-Shows the definition of a specific asynchronous materialized view.
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```SQL
-SHOW CREATE MATERIALIZED VIEW [database.]<mv_name>
-```
-
-Parameters in brackets [] is optional.
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                            |
-| ------------- | ------------ | ------------------------------------------ |
-| mv_name       | yes          | The name of the materialized view to show. |
-
-## Returns
-
-| **Return**               | **Description**                          |
-| ------------------------ | ---------------------------------------- |
-| Materialized View        | The name of the materialized view.       |
-| Create Materialized View | The definition of the materialized view. |
-
-## Examples
-
-Example 1: Show the definition of a specific materialized view
-
-```Plain
-MySQL > SHOW CREATE MATERIALIZED VIEW lo_mv1\G
-*************************** 1. row ***************************
-       Materialized View: lo_mv1
-Create Materialized View: CREATE MATERIALIZED VIEW `lo_mv1`
-COMMENT "MATERIALIZED_VIEW"
-DISTRIBUTED BY HASH(`lo_orderkey`) 
-REFRESH ASYNC
-PROPERTIES (
-"replication_num" = "3",
-"storage_medium" = "HDD"
-)
-AS SELECT `wlc_test`.`lineorder`.`lo_orderkey` AS `lo_orderkey`, `wlc_test`.`lineorder`.`lo_custkey` AS `lo_custkey`, sum(`wlc_test`.`lineorder`.`lo_quantity`) AS `total_quantity`, sum(`wlc_test`.`lineorder`.`lo_revenue`) AS `total_revenue`, count(`wlc_test`.`lineorder`.`lo_shipmode`) AS `shipmode_count` FROM `wlc_test`.`lineorder` GROUP BY `wlc_test`.`lineorder`.`lo_orderkey`, `wlc_test`.`lineorder`.`lo_custkey` ORDER BY `wlc_test`.`lineorder`.`lo_orderkey` ASC ;
-1 row in set (0.01 sec)
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE.md
deleted file mode 100644
index ac4b2201ef1c4e..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE.md
+++ /dev/null
@@ -1,141 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW CREATE TABLE
-
-Returns the CREATE TABLE statement that was used to create a given table.
-
-> **NOTE**
->
-> In versions earlier than v3.0, the SHOW CREATE TABLE statement requires you to have the `SELECT_PRIV` privilege on the table. Since v3.0, the SHOW CREATE TABLE statement requires you to have the `SELECT` privilege on the table.
-
-Since v3.0, you can use the SHOW CREATE TABLE statement to view the CREATE TABLE statements of the tables that are managed by an external catalog and are stored in Apache Hive™, Apache Iceberg, Apache Hudi, or Delta Lake.
-
-Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../../../table_design/Data_distribution.md#set-the-number-of-buckets).
-
-- If you specified the number of buckets when creating a table, the output of SHOW CREATE TABLE will display the number of buckets.
-- If you did not specify the number of buckets when creating a table, the output of SHOW CREATE TABLE will not display the number of buckets. You can run [SHOW PARTITIONS](SHOW_PARTITIONS.md) to view the number of buckets for each partition.
-
-In versions earlier than v2.5.7, you are required to set the number of buckets when creating a table. Therefore, SHOW CREATE TABLE displays the number of buckets by default.
-
-## Syntax
-
-```SQL
-SHOW CREATE TABLE [db_name.]table_name
-```
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                              |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| db_name       | No           | The database name. If this parameter is not specified, the CREATE TABLE statement of a given table in your current database is returned by default. |
-| table_name    | Yes          | The table name.                                              |
-
-## Output
-
-```Plain
-+-----------+----------------+
-| Table     | Create Table   |                                               
-+-----------+----------------+
-```
-
-The following table describes the parameters returned by this statement.
-
-| **Parameter** | **Description**                          |
-| ------------- | ---------------------------------------- |
-| Table         | The table name.                          |
-| Create Table  | The CREATE TABLE statement of the table. |
-
-## Examples
-
-### Bucket number is not specified
-
-Create a table named `example_table` with no bucket number specified in DISTRIBUTED BY.
-
-```SQL
-CREATE TABLE example_table
-(
-    k1 TINYINT,
-    k2 DECIMAL(10, 2) DEFAULT "10.5",
-    v1 CHAR(10) REPLACE,
-    v2 INT SUM
-)
-ENGINE = olap
-AGGREGATE KEY(k1, k2)
-COMMENT "my first starrocks table"
-DISTRIBUTED BY HASH(k1);
-```
-
-Run SHOW CREATE TABLE to display the CREATE TABLE statement of `example_table`. No bucket number is displayed in DISTRIBUTED BY. Note that if you did not specify PROPERTIES when you create the table, the default properties are displayed in the output of SHOW CREATE TABLE.
-
-```Plain
-SHOW CREATE TABLE example_table\G
-*************************** 1. row ***************************
-       Table: example_table
-Create Table: CREATE TABLE `example_table` (
-  `k1` tinyint(4) NULL COMMENT "",
-  `k2` decimal64(10, 2) NULL DEFAULT "10.5" COMMENT "",
-  `v1` char(10) REPLACE NULL COMMENT "",
-  `v2` int(11) SUM NULL COMMENT ""
-) ENGINE=OLAP 
-AGGREGATE KEY(`k1`, `k2`)
-COMMENT "my first starrocks table"
-DISTRIBUTED BY HASH(`k1`)
-PROPERTIES (
-"replication_num" = "3",
-"in_memory" = "false",
-"enable_persistent_index" = "false",
-"replicated_storage" = "true",
-"compression" = "LZ4"
-);
-```
-
-### Bucket number is specified
-
-Create a table named `example_table1` with bucket number set to 10 in DISTRIBUTED BY.
-
-```SQL
-CREATE TABLE example_table1
-(
-    k1 TINYINT,
-    k2 DECIMAL(10, 2) DEFAULT "10.5",
-    v1 CHAR(10) REPLACE,
-    v2 INT SUM
-)
-ENGINE = olap
-AGGREGATE KEY(k1, k2)
-COMMENT "my first starrocks table"
-DISTRIBUTED BY HASH(k1) BUCKETS 10;
-```
-
-Run SHOW CREATE TABLE to display the CREATE TABLE statement of `example_table`. The bucket number (`BUCKETS 10`) is displayed in DISTRIBUTED BY. Note that if you did not specify PROPERTIES when you create the table, the default properties are displayed in the output of SHOW CREATE TABLE.
-
-```plain
-SHOW CREATE TABLE example_table1\G
-*************************** 1. row ***************************
-       Table: example_table1
-Create Table: CREATE TABLE `example_table1` (
-  `k1` tinyint(4) NULL COMMENT "",
-  `k2` decimal64(10, 2) NULL DEFAULT "10.5" COMMENT "",
-  `v1` char(10) REPLACE NULL COMMENT "",
-  `v2` int(11) SUM NULL COMMENT ""
-) ENGINE=OLAP 
-AGGREGATE KEY(`k1`, `k2`)
-COMMENT "my first starrocks table"
-DISTRIBUTED BY HASH(`k1`) BUCKETS 10 
-PROPERTIES (
-"replication_num" = "3",
-"in_memory" = "false",
-"enable_persistent_index" = "false",
-"replicated_storage" = "true",
-"compression" = "LZ4"
-);
-```
-
-## References
-
-- [CREATE TABLE](../data-definition/CREATE_TABLE.md)
-- [SHOW TABLES](../data-manipulation/SHOW_TABLES.md)
-- [ALTER TABLE](../data-definition/ALTER_TABLE.md)
-- [DROP TABLE](../data-definition/DROP_TABLE.md)
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_VIEW.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_VIEW.md
deleted file mode 100644
index 8af4143c25ad42..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_VIEW.md
+++ /dev/null
@@ -1,75 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW CREATE VIEW
-
-Returns the CREATE statement that was used to create a given view. The CREATE VIEW statement helps you understand how the view is defined and provides a reference for you to modify or reconstruct the view. Note that the SHOW CREATE VIEW statement requires you to have the `SELECT` privilege on the view and the table based on which the view is created.
-
-From v2.5.4 onwards, you can use SHOW CREATE VIEW to query the statement that is used to create a **materialized view**.
-
-## Syntax
-
-```SQL
-SHOW CREATE VIEW [db_name.]view_name
-```
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                              |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| db_name       | No           | The database name. If this parameter is not specified, the CREATE VIEW statement of a given view in your current database is returned by default. |
-| view_name     | Yes          | The view name.                                               |
-
-## Output
-
-```SQL
-+---------+--------------+----------------------+----------------------+
-| View    | Create View  | character_set_client | collation_connection |
-+---------+--------------+----------------------+----------------------+
-```
-
-The following table describes the parameters returned by this statement.
-
-| **Parameter**        | **Description**                                              |
-| -------------------- | ------------------------------------------------------------ |
-| View                 | The view name.                                               |
-| Create View          | The CREATE VIEW statement of the view.                       |
-| character_set_client | The character set the client uses to send statements to StarRocks. |
-| collation_connection | The rules for comparing characters in a character set.       |
-
-## Examples
-
-Create a table named `example_table`.
-
-```SQL
-CREATE TABLE example_table
-(
-    k1 TINYINT,
-    k2 DECIMAL(10, 2) DEFAULT "10.5",
-    v1 CHAR(10) REPLACE,
-    v2 INT SUM
-)
-ENGINE = olap
-AGGREGATE KEY(k1, k2)
-DISTRIBUTED BY HASH(k1);
-```
-
-Create a view named `example_view` based on `example_table`.
-
-```SQL
-CREATE VIEW example_view (k1, k2, k3, v1)
-AS SELECT k1, k2, k3, v1 FROM example_table;
-```
-
-Display the CREATE VIEW statement of `example_view`.
-
-```Plain
-SHOW CREATE VIEW example_db.example_view;
-
-+--------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------+----------------------+
-| View         | Create View                                                                                                                                                                                                                                                                                                                     | character_set_client | collation_connection |
-+--------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------+----------------------+
-| example_view | CREATE VIEW `example_view` (k1, k2, k3, v1) COMMENT "VIEW" AS SELECT `default_cluster:db1`.`example_table`.`k1` AS `k1`, `default_cluster:db1`.`example_table`.`k2` AS `k2`, `default_cluster:db1`.`example_table`.`k3` AS `k3`, `default_cluster:db1`.`example_table`.`v1` AS `v1` FROM `default_cluster:db1`.`example_table`; | utf8                 | utf8_general_ci      |
-+--------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------+----------------------+
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_DATA.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_DATA.md
deleted file mode 100644
index a603502749d911..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_DATA.md
+++ /dev/null
@@ -1,53 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW DATA
-
-## Description
-
-This statement is used to display the amount of data, the number of copies, and the number of statistical rows in a database or a database table.
-
-Syntax:
-
-```sql
-SHOW DATA [FROM <db_name>[.<table_name>]]
-```
-
-Note:
-
-1. If the FROM clause is not specified, the amount of data and copies subdivided into each table in the current db will be displayed. Where the data volume is the total data volume of all replicas. The number of copies is the number of copies of all partitions of the table and all materialized views.
-2. If the FROM clause is specified, the amount of data, the number of copies and the number of statistical rows subdivided into each materialized view under the table are displayed. Where the data volume is the total data volume of all replicas. The number of copies is the number of copies of all partitions corresponding to the materialized view. The number of statistical rows is the number of statistical rows of all partitions corresponding to the materialized view.
-3. When counting the number of rows, the copy with the largest number of rows among multiple copies shall prevail.
-4. The Total row in the result set represents the summary row. The Quota row represents the quota set by the current database. The Left line represents the remaining quota.
-
-## Examples
-
-Example 1: Display the data volume, copy quantity, summary data volume and summary copy quantity of each table in the current database.
-
-```plain text
-SHOW DATA;
-+-----------+-------------+--------------+
-| TableName | Size        | ReplicaCount |
-+-----------+-------------+--------------+
-| tbl1      | 900.000 B   | 6            |
-| tbl2      | 500.000 B   | 3            |
-| Total     | 1.400 KB    | 9            |
-| Quota     | 1024.000 GB | 1073741824   |
-| Left      | 1021.921 GB | 1073741815   |
-+-----------+-------------+--------------+
-```
-
-Example 2: Display the amount of breakdown data, the number of copies, and the number of statistical rows in the specified table.
-
-```plain text
-SHOW DATA FROM example_db.test;
-+-----------+-----------+-----------+--------------+----------+
-| TableName | IndexName | Size      | ReplicaCount | RowCount |
-+-----------+-----------+-----------+--------------+----------+
-| test      | r1        | 10.000MB  | 30           | 10000    |
-|           | r2        | 20.000MB  | 30           | 20000    |
-|           | test2     | 50.000MB  | 30           | 50000    |
-|           | Total     | 80.000    | 90           |          |
-+-----------+-----------+-----------+--------------+----------+
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md
deleted file mode 100644
index 7928b6169d486e..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md
+++ /dev/null
@@ -1,69 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW DATABASES
-
-## Description
-
-Views databases in your current StarRocks cluster or an external data source. StarRocks supports viewing databases of an external data source from v2.3 onwards.
-
-## Syntax
-
-```SQL
-SHOW DATABASES [FROM <catalog_name>]
-```
-
-## Parameters
-
-| **Parameter**     | **Required** | **Description**                                              |
-| ----------------- | ------------ | ------------------------------------------------------------ |
-| catalog_name      | No           | The name of the internal catalog or an external catalog.<ul><li>If you do not specify the parameter or specify the name of the internal catalog, which is `default_catalog`, you can view databases in your current StarRocks cluster.</li><li>If you set the value of the parameter to the name of an external catalog, you can view databases in the corresponding external data source. You can run [SHOW CATALOGS](SHOW_CATALOGS.md) to view internal and external catalogs.</li></ul> |
-
-## Examples
-
-Example 1: View databases in your current StarRocks cluster.
-
-```SQL
-SHOW DATABASES;
-```
-
-Or
-
-```SQL
-SHOW DATABASES FROM default_catalog;
-```
-
-The output of the preceding statements is as follows.
-
-```SQL
-+----------+
-| Database |
-+----------+
-| db1      |
-| db2      |
-| db3      |
-+----------+
-```
-
-Example 2: View databases in a Hive cluster by using the `Hive1` external catalog.
-
-```SQL
-SHOW DATABASES FROM hive1;
-
-+-----------+
-| Database  |
-+-----------+
-| hive_db1  |
-| hive_db2  |
-| hive_db3  |
-+-----------+
-```
-
-## References
-
-- [CREATE DATABASE](../data-definition/CREATE_DATABASE.md)
-- [SHOW CREATE DATABASE](SHOW_CREATE_DATABASE.md)
-- [USE](../data-definition/USE.md)
-- [DESC](../Utility/DESCRIBE.md)
-- [DROP DATABASE](../data-definition/DROP_DATABASE.md)
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_DELETE.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_DELETE.md
deleted file mode 100644
index bea555f20e22c1..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_DELETE.md
+++ /dev/null
@@ -1,41 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW DELETE
-
-## Description
-
-Queries historical DELETE operations that were successfully performed on Duplicate Key, Unique Key, and Aggregate tables in a specified database. For more information about data deletion, see [DELETE](DELETE.md).
-
-Note that this command cannot be used to query DELETE operations that were performed on Primary Key tables.
-
-## Syntax
-
-```sql
-SHOW DELETE [FROM <db_name>]
-```
-
-`db_name`: the database name, optional. If this parameter is not specified, the current database is used by default.
-
-Return fields:
-
-- `TableName`: the table from which data is deleted.
-- `PartitionName`: the partition from which data is deleted. If the table is a non-partitioned table, `*` is displayed.
-- `CreateTime`: the time when the DELETE task was created.
-- `DeleteCondition`: the specified DELETE condition.
-- `State`: the status of the DELETE task.
-
-## Examples
-
-Show all historical DELETE operations of `database`.
-
-```sql
-SHOW DELETE FROM database;
-
-+------------+---------------+---------------------+-----------------+----------+
-| TableName  | PartitionName | CreateTime          | DeleteCondition | State    |
-+------------+---------------+---------------------+-----------------+----------+
-| mail_merge | *             | 2023-03-14 10:39:03 | name EQ "Peter" | FINISHED |
-+------------+---------------+---------------------+-----------------+----------+
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_DYNAMIC_PARTITION_TABLES.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_DYNAMIC_PARTITION_TABLES.md
deleted file mode 100644
index 57d10cae17f4aa..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_DYNAMIC_PARTITION_TABLES.md
+++ /dev/null
@@ -1,40 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW DYNAMIC PARTITION TABLES
-
-## Description
-
-This statement is used to display the status of all the partitioned tables for which dynamic partitioning properties are configured in a database.
-
-## Syntax
-
-```sql
-SHOW DYNAMIC PARTITION TABLES FROM <db_name>
-```
-
-This statement returns the following fields:
-
-- TableName: the name of the table.
-- Enable: whether dynamic partitioning is enabled.
-- TimeUnit: the time granularity for the partitions.
-- Start: the starting offset of dynamic partitioning.
-- End: the end offset of dynamic partitioning.
-- Prefix: the prefix of the partition name.
-- Buckets: the number of buckets per partition.
-- ReplicationNum: the number of replicas for the table.
-- StartOf
-- LastUpdateTime: the time when the table was last updated.
-- LastSchedulerTime: the time when data in the table was last scheduled.
-- State: the status of the table.
-- LastCreatePartitionMsg: the message for the latest partition creation operation.
-- LastDropPartitionMsg: the message for the latest partition dropping operation.
-
-## Examples
-
-Display the status of all the partitioned tables for which dynamic partitioning properties are configured in `db_test`.
-
-```sql
-SHOW DYNAMIC PARTITION TABLES FROM db_test;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_EXPORT.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_EXPORT.md
deleted file mode 100644
index c0da22c9780182..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_EXPORT.md
+++ /dev/null
@@ -1,138 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW EXPORT
-
-## Description
-
-Queries the execution information of export jobs that meet the specified conditions.
-
-## Syntax
-
-```SQL
-SHOW EXPORT
-[ FROM <db_name> ]
-[
-WHERE
-    [ QUERYID = <query_id> ]
-    [ STATE = { "PENDING" | "EXPORTING" | "FINISHED" | "CANCELLED" } ]
-]
-[ ORDER BY <field_name> [ ASC | DESC ] [, ... ] ]
-[ LIMIT <count> ]
-```
-
-## Parameters
-
-This statement can contain the following optional clauses:
-
-- FROM
-
-  Specifies the name of the database that you want to query. If you do not specify a FROM clause, StarRocks queries the current database.
-
-- WHERE
-
-  Specifies the conditions based on which you want to filter export jobs. Only the export jobs that meet the specified conditions are returned in the result set of the query.
-
-  | **Parameter** | **Required** | **Description**                                              |
-  | ------------- | ------------ | ------------------------------------------------------------ |
-  | QUERYID       | No           | The ID of the export job that you want to query. This parameter is used to query the execution information of a single export job. |
-  | STATE         | No           | The status of the export jobs that you want to query. Valid values:<ul><li>`PENDING`: specifies to query export jobs that are waiting to be scheduled.</li><li>`EXPORTING`: specifies to query export jobs that are being executed.</li><li>`FINISHED`: specifies to query export jobs that have been successfully completed.</li><li>`CANCELLED`: specifies to query export jobs that have failed.</li></ul> |
-
-- ORDER BY
-
-  Specifies the name of the field based on which you want to sort the export job records in the result set of the query. You can specify multiple fields, which must be separated with commas (`,`). Additionally, you can use the `ASC` or `DESC` keyword to specify that the export job records are sorted in ascending or descending order based on the specified field.
-
-- LIMIT
-
-  Restricts the result set of the query to a specified maximum number of rows. Valid values: positive integer. If you do not specify a LIMIT clause, StarRocks returns all export jobs that meet the specified conditions.
-
-## Return result
-
-For example, query the execution information of an export job whose ID is `edee47f0-abe1-11ec-b9d1-00163e1e238f`:
-
-```SQL
-SHOW EXPORT
-WHERE QUERYID = "edee47f0-abe1-11ec-b9d1-00163e1e238f";
-```
-
-The following execution information is returned:
-
-```SQL
-     JobId: 14008
-   QueryId: edee47f0-abe1-11ec-b9d1-00163e1e238f
-     State: FINISHED
-  Progress: 100%
-  TaskInfo: {"partitions":["*"],"column separator":"\t","columns":["*"],"tablet num":10,"broker":"","coord num":1,"db":"db0","tbl":"tbl_simple","row delimiter":"\n","mem limit":2147483648}
-      Path: hdfs://127.0.0.1:9000/users/230320/
-CreateTime: 2023-03-20 11:16:14
- StartTime: 2023-03-20 11:16:17
-FinishTime: 2023-03-20 11:16:26
-   Timeout: 7200
-```
-
-The parameters in the return result are described as follows:
-
-- `JobId`: the ID of the export job.
-- `QueryId`: the ID of the query.
-- `State`: the status of the export job.
-
-  Valid values:
-
-  - `PENDING`: The export job is waiting to be scheduled.
-  - `EXPORTING`: The export job is being executed.
-  - `FINISHED`: The export job has been successfully completed.
-  - `CANCELLED`: The export job has failed.
-
-- `Progress`: the progress of the export job. The progress is measured in the unit of query plans. Suppose that the export job is divided into 10 query plans and three of them have finished. In this case, the progress of the export job is 30%. For more information, see ["Export data using EXPORT > Workflow"](../../../unloading/Export.md#workflow).
-- `TaskInfo`: the information of the export job.
-
-  The information is a JSON object that consists of the following keys:
-
-  - `partitions`: the partitions on which the exported data resides. If a wildcard (`*`) is returned as a value for this key, the export job is run to export data from all partitions.
-  - `column separator`: the column separator used in the exported data file.
-  - `columns`: the names of the columns whose data is exported.
-  - `tablet num`: the total number of tablets that are exported.
-  - `broker`: In v2.4 and earlier, this field is used to return the name of the broker that is used by the export job. From v2.5 onwards, this field returns an empty string. For more information, see ["Export data using EXPORT > Background information"](../../../unloading/Export.md#background-information).
-  - `coord num`: the number of query plans into which the export job is divided.
-  - `db`: the name of the database to which the exported data belongs.
-  - `tbl`: the name of the table to which the exported data belongs
-  - `row delimiter`: the row separator used in the exported data file.
-  - `mem limit`: the maximum amount of memory allowed for the export job. Unit: bytes.
-
-- `Path`: the path to which the exported data is stored on the remote storage.
-- `CreateTime`: the time when the export job was created.
-- `StartTime`: the time when the export job started to be scheduled.
-- `FinishTime`: the time when the export job was finished.
-- `Timeout`: the amount of time that the export job took than expected. Unit: seconds. The time is counted from `CreateTime`.
-- `ErrorMsg`: the reason why the export job throws an error. This field is returned only when the export job encounters an error.
-
-## Examples
-
-- Query all export jobs in the current database:
-
-  ```SQL
-  SHOW EXPORT;
-  ```
-
-- Query the export job whose ID is `921d8f80-7c9d-11eb-9342-acde48001122` in the database `example_db`:
-
-  ```SQL
-  SHOW EXPORT FROM example_db
-  WHERE queryid = "921d8f80-7c9d-11eb-9342-acde48001122";
-  ```
-
-- Query export jobs that are in the `EXPORTING` state in the database `example_db` and specify to sort the export job records in the result set by `StartTime` in ascending order:
-
-  ```SQL
-  SHOW EXPORT FROM example_db
-  WHERE STATE = "exporting"
-  ORDER BY StartTime ASC;
-  ```
-
-- Query all export jobs in the database `example_db` and specify to sort the export job records in the result set by `StartTime` in descending order:
-
-  ```SQL
-  SHOW EXPORT FROM example_db
-  ORDER BY StartTime DESC;
-  ```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_FULL_COLUMNS.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_FULL_COLUMNS.md
deleted file mode 100644
index 019157d8a24dd6..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_FULL_COLUMNS.md
+++ /dev/null
@@ -1,29 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW FULL COLUMNS
-
-## Description
-
-This statement is used to show content in columns from specified tables.
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```sql
-SHOW FULL COLUMNS FROM <tbl_name>
-```
-
-## Examples
-
-1. View column content from specified tables.  
-
-    ```sql
-    SHOW FULL COLUMNS FROM tbl;
-    ```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_INDEX.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_INDEX.md
deleted file mode 100644
index ce72e627dac9f5..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_INDEX.md
+++ /dev/null
@@ -1,31 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW INDEX
-
-## Description
-
-This statement is used to show information related to index in a table. It currently only supports bitmap index.
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```sql
-SHOW INDEX[ES] FROM [db_name.]table_name [FROM database]
-Or
-SHOW KEY[S] FROM [db_name.]table_name [FROM database]
-```
-
-## Examples
-
-1. Show all indexes under the specified table_name:
-
-    ```sql
-    SHOW INDEX FROM example_db.table_name;
-    ```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md
deleted file mode 100644
index 56a87e4aa03082..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md
+++ /dev/null
@@ -1,176 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW LOAD
-
-## Description
-
-Displays information of all load jobs or given load jobs in a database. This statement can only display load jobs that are created by using [Broker Load](../data-manipulation/BROKER_LOAD.md), [INSERT](./INSERT.md), or [Spark Load](../data-manipulation/SPARK_LOAD.md). You can also view information of load jobs via the `curl` command. From v3.1 onwards, we recommend that you use the [SELECT](../data-manipulation/SELECT.md) statement to query the results of Broker Load or Insert jobs from the [`loads`](../../../reference/information_schema/loads.md) table in the `information_schema` database. For more information, see [Load data from HDFS](../../../loading/hdfs_load.md), [Load data from cloud storage](../../../loading/cloud_storage_load.md), [Load data using INSERT](../../../loading/InsertInto.md), and [Bulk load using Apache Spark™](../../../loading/SparkLoad.md).
-
-In addition to the preceding loading methods, StarRocks supports using Stream Load and Routine Load to load data. Stream Load is a synchronous operation and will directly return information of Stream Load jobs. Routine Load is an asynchronous operation where you can use the [SHOW ROUTINE LOAD](../data-manipulation/SHOW_ROUTINE_LOAD.md) statement to display information of Routine Load jobs.
-
-## Syntax
-
-```SQL
-SHOW LOAD [ FROM db_name ]
-[
-   WHERE [ LABEL { = "label_name" | LIKE "label_matcher" } ]
-         [ [AND] STATE = { "PENDING" | "ETL" | "LOADING" | "FINISHED" | "CANCELLED" } ]
-]
-[ ORDER BY field_name [ ASC | DESC ] ]
-[ LIMIT { [offset, ] limit | limit OFFSET offset } ]
-```
-
-> **Note**
->
-> You can add the `\G` option to the statement (such as `SHOW LOAD WHERE LABEL = "label1"\G;`) to vertically display output rather than in the usual horizontal table format. For more information, see [Example 1](#examples).
-
-## Parameters
-
-| **Parameter**                     | **Required** | **Description**                                              |
-| --------------------------------- | ------------ | ------------------------------------------------------------ |
-| db_name                           | No           | The database name. If this parameter is not specified, your current database is used by default. |
-| LABEL = "label_name"              | No           | The labels of load jobs.                                     |
-| LABEL LIKE "label_matcher"        | No           | If this parameter is specified, the information of load jobs whose labels contain `label_matcher` is returned. |
-| AND                               | No           | <ul><li>If you specify only one filter condition in the WHERE clause, do not specify this keyword. Example: `WHERE STATE = "PENDING"`.</li><li>If you specify two or three filter conditions in the WHERE clause, you must specify this keyword. Example: `WHERE LABEL = "label_name" AND STATE = "PENDING"`. </li></ul>|
-| STATE                             | No           | The states of load jobs. The states vary based on loading methods.<ul><li>Broker Load<ul><li>`PENDING`: The load job is created.</li><li>`QUEUEING`: The load job is in the queue waiting to be scheduled.</li><li>`LOADING`: The load job is running.</li><li>`PREPARED`: The transaction has been committed.</li><li>`FINISHED`: The load job succeeded.</li><li>`CANCELLED`: The load job failed.</li></ul></li><li>Spark Load<ul><li>`PENDING`: Your StarRocks cluster is preparing configurations related to ETL and then submits an ETL job to your Apache Spark™ cluster.</li><li>`ETL`: Your Spark cluster is executing the ETL job and then writes the data into the corresponding HDFS cluster.</li><li>`LOADING`: The data in the HDFS cluster is being loaded to your StarRocks cluster, which means the load job is running.</li><li>`PREPARED`: The transaction has been committed.</li><li>`FINISHED`: The load job succeeded.</li><li>`CANCELLED`: The load job failed.</li></ul></li><li>INSERT<ul><li>`FINISHED`: The load job succeeded.</li><li>`CANCELLED`: The load job failed.</li></ul></li></ul>If the `STATE` parameter is not specified, the information of load jobs in all states is returned by default. If the `STATE` parameter is specified, only the information of load jobs in the given state is returned. For example, `STATE = "PENDING"` returns the information of load jobs in the `PENDING` state. |
-| ORDER BY field_name [ASC \| DESC] | No           | If this parameter is specified, the output is sorted in ascending or descending order based on a field. The following fields are supported: `JobId`, `Label`, `State`, `Progress`, `Type`, `EtlInfo`, `TaskInfo`, `ErrorMsg`, `CreateTime`, `EtlStartTime`, `EtlFinishTime`, `LoadStartTime`, `LoadFinishTime`, `URL`, and `JobDetails`.<ul><li>To sort the output in ascending order, specify `ORDER BY field_name ASC`.</li><li>To sort the output in descending order, specify `ORDER BY field_name DESC`.</li></ul>If you do not specify the field and the sort order, the output is sorted in ascending order of `JobId` by default. |
-| LIMIT limit                       | No           | The number of load jobs that are allowed to display. If this parameter is not specified, the information of all load jobs that match the filter conditions are displayed. If this parameter is specified, for example, `LIMIT 10`, only the information of 10 load jobs that match filter conditions are returned. |
-| OFFSET offset                     | No           | The `offset` parameter defines the number of load jobs to be skipped. For example, `OFFSET 5` skips the first five load jobs and returns the rest. The value of the `offset` parameter defaults to `0`. |
-
-## Output
-
-```SQL
-+-------+-------+-------+----------+------+---------+----------+----------+------------+--------------+---------------+---------------+----------------+-----+------------+
-| JobId | Label | State | Progress | Type | Priority | EtlInfo | TaskInfo | ErrorMsg | CreateTime | EtlStartTime | EtlFinishTime | LoadStartTime | LoadFinishTime | URL | JobDetails |
-+-------+-------+-------+----------+------+---------+----------+----------+------------+--------------+---------------+---------------+----------------+-----+------------+
-```
-
-The output of this statement varies based on loading methods.
-
-| **Field**      | **Broker Load**                                              | **Spark Load**                                               | **INSERT**                                                   |
-| -------------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
-| JobId          | The unique ID assigned by StarRocks to identify the load job in your StarRocks cluster. | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The field has the same meaning in a INSERT job as it does in a Broker Load job. |
-| Label          | The label of the load job. The label of a load job is unique within a database but can be duplicate across different databases. | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The field has the same meaning in a INSERT job as it does in a Broker Load job. |
-| State          | The state of the load job.<ul><li>`PENDING`: The load job is created.</li><li>`QUEUEING`: The load job is in the queue waiting to be scheduled.</li><li>`LOADING`: The load job is running.</li><li>`PREPARED`: The transaction has been committed.</li><li>`FINISHED`: The load job succeeded.</li><li>`CANCELLED`: The load job failed.</li></ul> | The state of the load job.<ul><li>`PENDING`: Your StarRocks cluster is preparing configurations related to ETL and then submits an ETL job to your Spark cluster.</li><li>`ETL`: Your Spark cluster is executing the ETL job and then writes the data into the corresponding HDFS cluster.</li><li>`LOADING`: The data in the HDFS cluster is being loaded to your StarRocks cluster, which means the load job is running.</li><li>`PREPARED`: The transaction has been committed.</li><li>`FINISHED`: The load job succeeded.</li><li>`CANCELLED`: The load job failed.</li></ul> | The state of the load job.<ul><li>`FINISHED`: The load job succeeded.</li><li>`CANCELLED`: The load job failed.</li></ul> |
-| Progress       | The stage of the load job. A Broker Load job only has the `LOAD` stage, which ranges from 0% to 100% to describe the progress of the stage. When the load job enters the `LOAD` stage, `LOADING` is returned for the `State` parameter. A Broker Load job does not have the `ETL` stage. The `ETL` parameter is valid only for a Spark Load job.<br />**Note**<ul><li>The formula to calculate the progress of the `LOAD` stage: Number of StarRocks tables that complete data loading/Number of StarRocks tables that you plan to load data into * 100%.</li><li>When all data is loaded into StarRocks, `99%` is returned for the `LOAD` parameter. Then, loaded data starts taking effect in StarRocks. After the data takes effect, `100%` is returned for the `LOAD` parameter.</li><li>The progress of the `LOAD` stage is not linear. Therefore, the value of the `LOAD` parameter may not change over a period of time even if data loading is still ongoing.</li></ul> | The stage of the load job. A Spark Load job has two stages:<ul><li>`ETL`: ranges from 0% to 100% to describe the progress of the `ETL` stage.</li><li>`LOAD`: ranges from 0% to 100% to describe the progress of the `Load` stage. </li></ul>When the load job enters the `ETL` stage, `ETL` is returned for the `State` parameter. When the load job moves to the `LOAD` stage, `LOADING` is returned for the `State` parameter. <br />The **Note** is the same as those for Broker Load. | The stage of the load job. An INSERT job only has the `LOAD` stage, which ranges from 0% to 100% to describe the progress of the stage. When the load job enters the `LOAD` stage, `LOADING` is returned for the `State` parameter. An INSERT job does not have the `ETL` stage. The `ETL` parameter is valid only for a Spark Load job.<br />The **Note** is the same as those for Broker Load. |
-| Type           | The method of the load job. The value of this parameter defaults to `BROKER`. | The method of the load job. The value of this parameter defaults to `SPARK`. | The method of the load job. The value of this parameter defaults to `INSERT`. |
-| Priority       | The priority of the load job. Valid values: LOWEST, LOW, NORMAL, HIGH, and HIGHEST. | - | - |
-| EtlInfo        | The metrics related to ETL.<ul><li>`unselected.rows`: The number of rows that are filtered out by the WHERE clause.</li><li>`dpp.abnorm.ALL`: The number of rows that are filtered out due to data quality issues, which refers to mismatches between source tables and StarRocks tables in, for example, the data type and the number of columns.</li><li>`dpp.norm.ALL`: The number of rows that are loaded into your StarRocks cluster.</li></ul>The sum of the preceding metrics is the total number of rows of raw data. You can use the following formula to calculate whether the percentage of unqualified data exceeds the value of the `max-filter-ratio` parameter:`dpp.abnorm.ALL`/(`unselected.rows` + `dpp.abnorm.ALL` + `dpp.norm.ALL`). | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The metrics related to ETL. An INSERT job does not have the `ETL` stage. Therefore, `NULL` is returned. |
-| TaskInfo       | The parameters that are specified when you create the load job.<ul><li>`resource`: This parameter is valid only in a Spark Load job.</li><li>`timeout`: The time period that a load job is allowed to run. Unit: seconds.</li><li>`max-filter-ratio`: The largest percentage of rows that are filtered out due to data quality issues.</li></ul>For more information, see [BROKER LOAD](../data-manipulation/BROKER_LOAD.md). | The parameters that are specified when you create the load job.<ul><li>`resource`: The resource name.</li><li>`timeout`: The time period that a load job is allowed to run. Unit: seconds.</li><li>`max-filter-ratio`: The largest percentage of rows that are filtered out due to data quality issues.</li></ul>For more information, see [SPARK LOAD](../data-manipulation/SPARK_LOAD.md). | The parameters that are specified when you create the load job.<ul><li>`resource`: This parameter is valid only in a Spark Load job.</li><li>`timeout`: The time period that a load job is allowed to run. Unit: seconds.</li><li>`max-filter-ratio`: The largest percentage of rows that are filtered out due to data quality issues.</li></ul>For more information, see [INSERT](./INSERT.md). |
-| ErrorMsg       | The error message returned when the load job fails. When the state of the loading job is `PENDING`, `LOADING`, or `FINISHED`, `NULL` is returned for the `ErrorMsg` field. When the state of the loading job is `CANCELLED`, the value returned for the `ErrorMsg` field consists of two parts: `type` and `msg`.<ul><li>The `type` part can be any of the following values:<ul><li>`USER_CANCEL`: The load job was manually canceled.</li><li>`ETL_SUBMIT_FAIL`: The load job failed to be submitted.</li><li>`ETL-QUALITY-UNSATISFIED`: The load job failed because the percentage of unqualified data exceeds the value of the `max-filter-ratio` parameter.</li><li>`LOAD-RUN-FAIL`: The load job failed in the `LOAD` stage.</li><li>`TIMEOUT`: The load job failed to finish within the specified timeout period.</li><li>`UNKNOWN`: The load job failed due to an unknown error.</li></ul></li><li>The `msg` part provides the detailed cause of the load failure.</li></ul> | The error message returned when the load job fails. When the state of the loading job is `PENDING`, `LOADING`, or `FINISHED`, `NULL` is returned for the `ErrorMsg` field. When the state of the loading job is `CANCELLED`, the value returned for the `ErrorMsg` field consists of two parts: `type` and `msg`.<ul><li>The `type` part can be any of the following values:<ul><li>`USER_CANCEL`: The load job was manually canceled.</li><li>`ETL_SUBMIT_FAIL`: StarRocks failed to submit an ETL job to Spark.</li><li>`ETL-RUN-FAIL`: Spark failed to execute the ETL job. </li><li>`ETL-QUALITY-UNSATISFIED`: The load job failed because the percentage of unqualified data exceeds the value of the `max-filter-ratio` parameter.</li><li>`LOAD-RUN-FAIL`: The load job failed in the `LOAD` stage.</li><li>`TIMEOUT`: The load job failed to finish within the specified timeout period.</li><li>`UNKNOWN`: The load job failed due to an unknown error.</li></ul></li><li>The `msg` part provides the detailed cause of the load failure.</li></ul> | The error message returned when the load job fails. When the state of the loading job is `FINISHED`, `NULL` is returned for the `ErrorMsg` field. When the state of the loading job is `CANCELLED`, the value returned for the `ErrorMsg` field consists of two parts: `type` and `msg`.<ul><li>The `type` part can be any of the following values:<ul><li>`USER_CANCEL`: The load job was manually canceled.</li><li>`ETL_SUBMIT_FAIL`: The load job failed to be submitted.</li><li>`ETL_RUN_FAIL`: The load job failed to run.</li><li>`ETL_QUALITY_UNSATISFIED`: The load job failed due to quality issues of raw data.</li><li>`LOAD-RUN-FAIL`: The load job failed in the `LOAD` stage.</li><li>`TIMEOUT`: The load job failed to finish within the specified timeout period.</li><li>`UNKNOWN`: The load job failed due to an unknown error.</li><li>`TXN_UNKNOWN`: The load job failed because the state of the transaction of the load job is unknown.</li></ul></li><li>The `msg` part provides the detailed cause of the load failure.</li></ul> |
-| CreateTime     | The time at which the load job was created.                  | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The field has the same meaning in a INSERT job as it does in a Broker Load job. |
-| EtlStartTime   | A Broker Load job does not have the `ETL` stage. Therefore, the value of this field is the same as the value of the `LoadStartTime` field. | The time at which the `ETL` stage starts.                    | An INSERT job does not have the `ETL` stage. Therefore, the value of this field is the same as the value of the `LoadStartTime` field. |
-| EtlFinishTime  | A Broker Load job does not have the `ETL` stage. Therefore, the value of this field is the same as the value of the `LoadStartTime` field. | The time at which the `ETL` stage finishes.                  | An INSERT job does not have the `ETL` stage. Therefore, the value of this field is the same as the value of the `LoadStartTime` field. |
-| LoadStartTime  | The time at which the `LOAD` stage starts.                   | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The field has the same meaning in a INSERT job as it does in a Broker Load job. |
-| LoadFinishTime | The time at which the load job finishes.                     | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The field has the same meaning in a INSERT job as it does in a Broker Load job. |
-| URL            | The URL that is used to access the unqualified data detected in the load job. You can use the `curl` or `wget` command to access the URL and obtain the unqualified data. If no unqualified data is detected, `NULL` is returned. | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The field has the same meaning in a INSERT job as it does in a Broker Load job. |
-| JobDetails     | Other information related to the load job.<ul><li>`Unfinished backends`: The ID of the BE that does not complete data loading.</li><li>`ScannedRows`: The total number of rows that are loaded into StarRocks and the number of rows that are filtered out.</li><li>`TaskNumber`: A load job can be split into one or more tasks that concurrently run. This field indicates the number of load tasks.</li><li>`All backends`: The ID of the BE that is executing data loading.</li><li>`FileNumber`: The number of source data files.</li><li>`FileSize`: The data volume of source data files. Unit: bytes.</li></ul> | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The field has the same meaning in a INSERT job as it does in a Broker Load job. |
-
-## Usage notes
-
-- The information returned by the SHOW LOAD statement is valid for 3 days from `LoadFinishTime` of a load job. After 3 days, the information cannot be displayed. You can use the `label_keep_max_second` parameter to modify the default validity period.
-
-    ```SQL
-    ADMIN SET FRONTEND CONFIG ("label_keep_max_second" = "value");
-    ```
-
-- If the value of the `LoadStartTime` field is `N/A` for a long time, it means that load jobs heavily pile up. We recommended that you reduce the frequency of creating load jobs.
-- Total time period consumed by a load job = `LoadFinishTime` - `CreateTime`.
-- Total time period a load job consumed in the `LOAD` stage = `LoadFinishTime` - `LoadStartTime`.
-
-## Examples
-
-Example 1: Vertically display all load jobs in your current database.
-
-```plaintext
-SHOW LOAD\G
-*************************** 1. row ***************************
-         JobId: 976331
-         Label: duplicate_table_with_null
-         State: FINISHED
-      Progress: ETL:100%; LOAD:100%
-          Type: BROKER
-      Priority: NORMAL
-       EtlInfo: unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546
-      TaskInfo: resource:N/A; timeout(s):300; max_filter_ratio:0.0
-      ErrorMsg: NULL
-    CreateTime: 2022-10-17 19:35:00
-  EtlStartTime: 2022-10-17 19:35:04
- EtlFinishTime: 2022-10-17 19:35:04
- LoadStartTime: 2022-10-17 19:35:04
-LoadFinishTime: 2022-10-17 19:35:06
-           URL: NULL
-    JobDetails: {"Unfinished backends":{"b90a703c-6e5a-4fcb-a8e1-94eca5be0b8f":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"b90a703c-6e5a-4fcb-a8e1-94eca5be0b8f":[10004]},"FileNumber":1,"FileSize":548622}
-```
-
-Example 2: Display two load jobs whose labels contain the string `null` in your current database.
-
-```plaintext
-SHOW LOAD 
-WHERE LABEL LIKE "null" 
-LIMIT 2;
-
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| JobId | Label                     | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                                                                                | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL                                                                            | JobDetails                                                                                                                                                                                              |
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| 10082 | duplicate_table_with_null | FINISHED | ETL:100%; LOAD:100% | BROKER | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:N/A; timeout(s):300; max_filter_ratio:0.0                                                      | NULL     | 2022-08-02 14:53:27 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:31 | NULL                                                                           | {"Unfinished backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[10002]},"FileNumber":1,"FileSize":548622} |
-| 10103 | unique_table_with_null    | FINISHED | ETL:100%; LOAD:100% | SPARK  | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:test_spark_resource_07af473a_1230_11ed_b483_00163e0e550b; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:56:06 | 2022-08-02 14:56:19 | 2022-08-02 14:56:41 | 2022-08-02 14:56:41 | 2022-08-02 14:56:44 | http://emr-header-1.cluster-49091:20888/proxy/application_1655710334658_26391/ | {"Unfinished backends":{"00000000-0000-0000-0000-000000000000":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"00000000-0000-0000-0000-000000000000":[-1]},"FileNumber":1,"FileSize":8790855}   |
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-```
-
-Example 3: Display the load jobs whose labels contain the string `table` in `example_db`. In addition, the load jobs returned are displayed in descending order of the `LoadStartTime` field.
-
-```plaintext
-SHOW LOAD FROM example_db 
-WHERE LABEL Like "table" 
-ORDER BY LoadStartTime DESC;
-
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| JobId | Label                     | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                                                                                | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL                                                                            | JobDetails                                                                                                                                                                                              |
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| 10103 | unique_table_with_null    | FINISHED | ETL:100%; LOAD:100% | SPARK  | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:test_spark_resource_07af473a_1230_11ed_b483_00163e0e550b; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:56:06 | 2022-08-02 14:56:19 | 2022-08-02 14:56:41 | 2022-08-02 14:56:41 | 2022-08-02 14:56:44 | http://emr-header-1.cluster-49091:20888/proxy/application_1655710334658_26391/ | {"Unfinished backends":{"00000000-0000-0000-0000-000000000000":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"00000000-0000-0000-0000-000000000000":[-1]},"FileNumber":1,"FileSize":8790855}   |
-| 10082 | duplicate_table_with_null | FINISHED | ETL:100%; LOAD:100% | BROKER | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:N/A; timeout(s):300; max_filter_ratio:0.0                                                      | NULL     | 2022-08-02 14:53:27 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:31 | NULL                                                                           | {"Unfinished backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[10002]},"FileNumber":1,"FileSize":548622} |
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-```
-
-Example 4: Display the load job whose label is `duplicate_table_with_null` and state is `FINISHED` in `example_db`.
-
-```plaintext
-SHOW LOAD FROM example_db 
-WHERE LABEL = "duplicate_table_with_null" AND STATE = "FINISHED";
-
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+----------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| JobId | Label                     | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                           | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL  | JobDetails                                                                                                                                                                                              |
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+----------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| 10082 | duplicate_table_with_null | FINISHED | ETL:100%; LOAD:100% | BROKER | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:N/A; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:53:27 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:31 | NULL | {"Unfinished backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[10002]},"FileNumber":1,"FileSize":548622} |
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+----------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-```
-
-Example 5: Skip the first load job and display the next two load jobs. In addition, these two load jobs are sorted in ascending order.
-
-```plaintext
-SHOW LOAD FROM example_db 
-ORDER BY CreateTime ASC 
-LIMIT 2 OFFSET 1;
-```
-
-Or
-
-```plaintext
-SHOW LOAD FROM example_db 
-ORDER BY CreateTime ASC 
-LIMIT 1,2;
-```
-
-The output of the preceding statements is as follows.
-
-```plaintext
-+-------+---------------------------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| JobId | Label                                       | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                                                                                | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL                                                                            | JobDetails                                                                                                                                                                                            |
-+-------+---------------------------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| 10103 | unique_table_with_null                      | FINISHED | ETL:100%; LOAD:100% | SPARK  | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:test_spark_resource_07af473a_1230_11ed_b483_00163e0e550b; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:56:06 | 2022-08-02 14:56:19 | 2022-08-02 14:56:41 | 2022-08-02 14:56:41 | 2022-08-02 14:56:44 | http://emr-header-1.cluster-49091:20888/proxy/application_1655710334658_26391/ | {"Unfinished backends":{"00000000-0000-0000-0000-000000000000":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"00000000-0000-0000-0000-000000000000":[-1]},"FileNumber":1,"FileSize":8790855} |
-| 10120 | insert_3a57b595-1230-11ed-b075-00163e14c85e | FINISHED | ETL:100%; LOAD:100% | INSERT | NULL                                                    | resource:N/A; timeout(s):3600; max_filter_ratio:0.0                                                     | NULL     | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 |                                                                                | {"Unfinished backends":{},"ScannedRows":0,"TaskNumber":0,"All backends":{},"FileNumber":0,"FileSize":0}                                                                                               |
-+-------+---------------------------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md
deleted file mode 100644
index c3cb009b5e6c33..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md
+++ /dev/null
@@ -1,170 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW MATERIALIZED VIEWS
-
-## Description
-
-Shows all or one specific asynchronous materialized view.
-
-Since v3.0, the name of this statement is changed from SHOW MATERIALIZED VIEW to SHOW MATERIALIZED VIEWS.
-
-:::tip
-
-This operation does not require privileges.
-
-:::
-
-## Syntax
-
-```SQL
-SHOW MATERIALIZED VIEWS
-[FROM db_name]
-[
-WHERE NAME { = "mv_name" | LIKE "mv_name_matcher"}
-]
-```
-
-:::note
-
-Since v3.3, `SHOW MATERIALIZED VIEWS` command will track the state of all task_runs if a refresh task consists of multiple partitions/task_runs to refresh. Only when all task_runs are success, `last_refresh_state` will return `SUCCESS`.
-
-:::
-
-## Parameters
-
-| **Parameter**   | **Required** | **Description**                                              |
-| --------------- | ------------ | ------------------------------------------------------------ |
-| db_name         | no           | The name of the database to which the materialized view resides. If this parameter is not specified, the current database is used by default. |
-| mv_name         | no           | The name of the materialized view to show.                   |
-| mv_name_matcher | no           | The matcher used to filter materialized views.               |
-
-## Returns
-
-| **Return**                 | **Description**                                              |
-| -------------------------- | ------------------------------------------------------------ |
-| id                         | The ID of the materialized view.                             |
-| database_name              | The name of the database in which the materialized view resides. |
-| name                       | The name of the materialized view.                           |
-| refresh_type               | The refresh type of the materialized view, including ROLLUP, MANUAL, ASYNC, and INCREMENTAL. |
-| is_active                  | Whether the materialized view state is active. Valid Value: `true` and `false`. |
-| partition_type             | The partition type of the materialized view, including RANGE and UNPARTITIONED.                |
-| task_id                    | ID of the materialized view refresh task.                  |
-| task_name                  | Name of the materialized view refresh task.                |
-| last_refresh_start_time    | The start time of the last refresh of the materialized view. |
-| last_refresh_finished_time | The end time of the last refresh of the materialized view.   |
-| last_refresh_duration      | The time taken by the last refresh. Unit: seconds.           |
-| last_refresh_state         | The status of the last refresh, including PENDING, RUNNING, FAILED, and SUCCESS. |
-| last_refresh_force_refresh | Whether the last refresh is a FORCE refresh.                 |
-| last_refresh_start_partition | The start partition of the last refresh in the materialized view. |
-| last_refresh_end_partition | The end partition of the last refresh in the materialized view. |
-| last_refresh_base_refresh_partitions | The base table partitions that were refreshed in the last refresh. |
-| last_refresh_mv_refresh_partitions | The materialized view partitions that were refreshed in the last refresh. |
-| last_refresh_error_code    | The error code for the last failed refresh of the materialized view (if the materialized view state is not active). |
-| last_refresh_error_message | The reason why the last refresh failed (if the materialized view state is not active). |
-| rows                       | The number of data rows in the materialized view.            |
-| text                       | The statement used to create the materialized view.          |
-
-## Examples
-
-The following examples is based on this business scenario:
-
-```Plain
--- Create Table: customer
-CREATE TABLE customer ( C_CUSTKEY     INTEGER NOT NULL,
-                        C_NAME        VARCHAR(25) NOT NULL,
-                        C_ADDRESS     VARCHAR(40) NOT NULL,
-                        C_NATIONKEY   INTEGER NOT NULL,
-                        C_PHONE       CHAR(15) NOT NULL,
-                        C_ACCTBAL     double   NOT NULL,
-                        C_MKTSEGMENT  CHAR(10) NOT NULL,
-                        C_COMMENT     VARCHAR(117) NOT NULL,
-                        PAD char(1) NOT NULL)
-    ENGINE=OLAP
-DUPLICATE KEY(`c_custkey`)
-COMMENT "OLAP"
-DISTRIBUTED BY HASH(`c_custkey`)
-PROPERTIES (
-"replication_num" = "3",
-"storage_format" = "DEFAULT"
-);
-
--- Create MV: customer_mv
-CREATE MATERIALIZED VIEW customer_mv
-DISTRIBUTED BY HASH(c_custkey)
-REFRESH MANUAL
-PROPERTIES (
-    "replication_num" = "3"
-)
-AS SELECT
-              c_custkey, c_phone, c_acctbal, count(1) as c_count, sum(c_acctbal) as c_sum
-   FROM
-              customer
-   GROUP BY c_custkey, c_phone, c_acctbal;
-
--- Refresh the MV
-REFRESH MATERIALIZED VIEW customer_mv;
-```
-
-Example 1: Show a specific materialized view.
-
-```Plain
-mysql> SHOW MATERIALIZED VIEWS WHERE NAME='customer_mv'\G
-*************************** 1. row ***************************
-                        id: 10142
-                      name: customer_mv
-             database_name: test
-              refresh_type: MANUAL
-                 is_active: true
-   last_refresh_start_time: 2023-02-17 10:27:33
-last_refresh_finished_time: 2023-02-17 10:27:33
-     last_refresh_duration: 0
-        last_refresh_state: SUCCESS
-             inactive_code: 0
-           inactive_reason:
-                      text: CREATE MATERIALIZED VIEW `customer_mv`
-COMMENT "MATERIALIZED_VIEW"
-DISTRIBUTED BY HASH(`c_custkey`)
-REFRESH MANUAL
-PROPERTIES (
-"replication_num" = "3",
-"storage_medium" = "HDD"
-)
-AS SELECT `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`, count(1) AS `c_count`, sum(`customer`.`c_acctbal`) AS `c_sum`
-FROM `test`.`customer`
-GROUP BY `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`;
-                      rows: 0
-1 row in set (0.11 sec)
-```
-
-Example 2: Show materialized views by matching the name.
-
-```Plain
-mysql> SHOW MATERIALIZED VIEWS WHERE NAME LIKE 'customer_mv'\G
-*************************** 1. row ***************************
-                        id: 10142
-                      name: customer_mv
-             database_name: test
-              refresh_type: MANUAL
-                 is_active: true
-   last_refresh_start_time: 2023-02-17 10:27:33
-last_refresh_finished_time: 2023-02-17 10:27:33
-     last_refresh_duration: 0
-        last_refresh_state: SUCCESS
-             inactive_code: 0
-           inactive_reason:
-                      text: CREATE MATERIALIZED VIEW `customer_mv`
-COMMENT "MATERIALIZED_VIEW"
-DISTRIBUTED BY HASH(`c_custkey`)
-REFRESH MANUAL
-PROPERTIES (
-"replication_num" = "3",
-"storage_medium" = "HDD"
-)
-AS SELECT `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`, count(1) AS `c_count`, sum(`customer`.`c_acctbal`) AS `c_sum`
-FROM `test`.`customer`
-GROUP BY `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`;
-                      rows: 0
-1 row in set (0.12 sec)
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_PARTITIONS.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_PARTITIONS.md
deleted file mode 100644
index 100d0fc129c6cb..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_PARTITIONS.md
+++ /dev/null
@@ -1,100 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW PARTITIONS
-
-## Description
-
-Displays partition information, including common partitions and [temporary partitions](../../../table_design/Temporary_partition.md).
-
-## Syntax
-
-```sql
-SHOW [TEMPORARY] PARTITIONS FROM [db_name.]table_name [WHERE] [ORDER BY] [LIMIT]
-```
-
-> NOTE
->
-> This syntax only supports StarRocks tables (`"ENGINE" = "OLAP"`).
-> Since v3.0, this operation requires the SELECT privilege on the specified table. For v2.5 and earlier versions, this operation requires the SELECT__PRIV privilege on the specified table.
-
-## Description of return fields
-
-```plaintext
-+-------------+---------------+----------------+---------------------+--------------------+--------+--------------+-------+--------------------+---------+----------------+---------------+---------------------+--------------------------+----------+------------+----------+
-| PartitionId | PartitionName | VisibleVersion | VisibleVersionTime  | VisibleVersionHash | State  | PartitionKey | Range | DistributionKey    | Buckets | ReplicationNum | StorageMedium | CooldownTime        | LastConsistencyCheckTime | DataSize | IsInMemory | RowCount |
-+-------------+---------------+----------------+---------------------+--------------------+--------+--------------+-------+--------------------+---------+----------------+---------------+---------------------+--------------------------+----------+------------+----------+
-```
-
-| **Field**                | **Description**                                              |
-| ------------------------ | ------------------------------------------------------------ |
-| PartitionId              | The ID of the partition.                                |
-| PartitionName            | The name of the partition.                                   |
-| VisibleVersion           | The version number of the last successful load transaction. The version number increases by 1 with each successful load transaction. |
-| VisibleVersionTime       | The timestamp of the last successful load transaction.       |
-| VisibleVersionHash       | The hash value for the version number of the last successful load transaction. |
-| State                    | The status of the partition. Fixed value: `Normal`.           |
-| PartitionKey             | The partition key that consists of one or more partition columns. |
-| Range                    | The range of the partition, which is a right half-open interval. |
-| DistributionKey          | The bucket key of hash bucketing.                            |
-| Buckets                  | The number of buckets for the partition.                     |
-| ReplicationNum           | The number of replicas per tablet in the partition.        |
-| StorageMedium            | The storage medium to store the data in the partition. The value `HHD` indicates hard disk drives, and the value `SSD` indicates solid-state drives. |
-| CooldownTime             | The cooldown time for data in the partition. If the initial storage medium is SSD, the storage medium is switched from SSD to HDD after the time specified by this parameter. Format: "yyyy-MM-dd HH:mm:ss". |
-| LastConsistencyCheckTime | The time of the last consistency check. `NULL` indicates no consistency check was performed. |
-| DataSize                 | The size of data in the partition.                          |
-| IsInMemory               | Whether all data in the partition is stored in memory.          |
-| RowCount                 | The number of data rows of the partition.                    |
-| MaxCS                    | The maximum Compaction Score of the partition. For shared-data clusters only.                    |
-
-## Examples
-
-1. Display information of all regular partitions from the specified table `site_access` under the specified database `test`.
-
-    ```SQL
-    MySQL > show partitions from test.site_access\G
-    *************************** 1. row ***************************
-                PartitionId: 20990
-            PartitionName: p2019 
-            VisibleVersion: 1
-        VisibleVersionTime: 2023-08-08 15:45:13
-        VisibleVersionHash: 0
-                    State: NORMAL
-                PartitionKey: datekey
-                    Range: [types: [DATE]; keys: [2019-01-01]; ..types: [DATE]; keys: [2020-01-01]; )
-            DistributionKey: site_id
-                    Buckets: 6
-            ReplicationNum: 3
-            StorageMedium: HDD
-                CooldownTime: 9999-12-31 23:59:59
-    LastConsistencyCheckTime: NULL
-                    DataSize:  4KB   
-                IsInMemory: false
-                    RowCount: 3 
-    1 row in set (0.00 sec)
-    ```
-
-2. Display information of all temporary partitions from the specified table `site_access` under the specified database `test`.
-
-    ```sql
-    SHOW TEMPORARY PARTITIONS FROM test.site_access;
-    ```
-
-3. Display the information of the specified partition `p1` of the specified table `site_access` under the specified database `test`.
-
-    ```sql
-    -- Regular partition
-    SHOW PARTITIONS FROM test.site_access WHERE PartitionName = "p1";
-    -- Temporary partition
-    SHOW TEMPORARY PARTITIONS FROM test.site_access WHERE PartitionName = "p1";
-    ```
-
-4. Display the latest partition information of the specified table `site_access` under the specified database `test`.
-
-    ```sql
-    -- Regular partition
-    SHOW PARTITIONS FROM test.site_access ORDER BY PartitionId DESC LIMIT 1;
-    -- Temporary partition
-    SHOW TEMPORARY PARTITIONS FROM test.site_access ORDER BY PartitionId DESC LIMIT 1;
-    ```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md
deleted file mode 100644
index 6f827ac99bbcc6..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md
+++ /dev/null
@@ -1,82 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW PIPES
-
-## Description
-
-Lists the pipes stored in a specified database or in the current database in use. This command is supported from v3.2 onwards.
-
-## Syntax
-
-```SQL
-SHOW PIPES [FROM <db_name>]
-[
-   WHERE [ NAME { = "<pipe_name>" | LIKE "pipe_matcher" } ]
-         [ [AND] STATE = { "SUSPENDED" | "RUNNING" | "ERROR" } ]
-]
-[ ORDER BY <field_name> [ ASC | DESC ] ]
-[ LIMIT { [offset, ] limit | limit OFFSET offset } ]
-```
-
-## Parameters
-
-### FROM `<db_name>`
-
-The name of the database for which you want to query pipes. If you do not specify this parameter, the system returns the pipes for the current database in use.
-
-### WHERE
-
-The criteria based on which to query pipes.
-
-### ORDER BY `<field_name>`
-
-The field by which you want to sort the records returned.
-
-### LIMIT
-
-The maximum number of records you want the system to return.
-
-## Return result
-
-The command output consists of the following fields.
-
-| **Field**     | **Description**                                              |
-| ------------- | ------------------------------------------------------------ |
-| DATABASE_NAME | The name of the database in which the pipe is stored.        |
-| PIPE_ID       | The unique ID of the pipe.                                   |
-| PIPE_NAME     | The name of the pipe.                                        |
-| TABLE_NAME    | The name of the destination StarRocks table.                 |
-| STATE         | The status of the pipe. Valid values: `RUNNING`, `FINISHED`, `SUSPENDED`, and `ERROR`. |
-| LOAD_STATUS   | The overall status of the data files to be loaded via the pipe, including the following sub-fields:<ul><li>`loadedFiles`: the number of data files that have been loaded.</li><li>`loadedBytes`: the volume of data that has been loaded, measured in bytes.</li><li>`LastLoadedTime`: the date and time when the last data file was loaded. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`.</li></ul> |
-| LAST_ERROR    | The details about the last error that occurred during the pipe execution. Default value: `NULL`. |
-| CREATED_TIME  | The date and time when the pipe was created. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
-
-## Examples
-
-### Query all pipes
-
-Switch to the database named `mydatabase` and show all the pipes in it:
-
-```SQL
-USE mydatabase;
-SHOW PIPES \G
-```
-
-### Query a specified pipe
-
-Switch to the database named `mydatabase` and show the pipe named `user_behavior_replica` in it:
-
-```SQL
-USE mydatabase;
-SHOW PIPES WHERE NAME = 'user_behavior_replica' \G
-```
-
-## References
-
-- [CREATE PIPE](../data-manipulation/CREATE_PIPE.md)
-- [ALTER PIPE](../data-manipulation/ALTER_PIPE.md)
-- [DROP PIPE](../data-manipulation/DROP_PIPE.md)
-- [SUSPEND or RESUME PIPE](../data-manipulation/SUSPEND_or_RESUME_PIPE.md)
-- [RETRY FILE](../data-manipulation/RETRY_FILE.md)
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md
deleted file mode 100644
index ce42e08599a7a7..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md
+++ /dev/null
@@ -1,126 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW ROUTINE LOAD
-
-import RoutineLoadPrivNote from '../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
-
-## Description
-
-Shows the execution information of Routine Load jobs.
-
-<RoutineLoadPrivNote />
-
-## Syntax
-
-```SQL
-SHOW [ALL] ROUTINE LOAD [ FOR [<db_name>.]<job_name> | FROM <db_name> ]
-[ WHERE [ STATE = { "NEED_SCHEDULE" | "RUNNING" | "PAUSED" | "UNSTABLE" | "STOPPED" | "CANCELLED"  } ] ]
-[ ORDER BY field_name [ ASC | DESC ] ]
-[ LIMIT { [offset, ] limit | limit OFFSET offset } ]
-```
-
-:::tip
-
-You can add the `\G` option to the statement (such as `SHOW ROUTINE LOAD FOR <job_name>\G`) to vertically display the return result rather than in the usual horizontal table format.
-
-:::
-
-## Parameters
-
-| **Parameter**                     | **Required** | **Description**                                              |
-| --------------------------------- | ------------ | ------------------------------------------------------------ |
-| db_name                           | No           | The name of the database to which the load job belongs. Note that this parameter is required if the `FROM` clause is used. |
-| job_name                          | No           | The name of the load job. Note that this parameter is required if the `FOR` clause is used.         |
-| ALL                               | No           | Displays all load jobs, including those in the `STOPPED` or  `CANCELLED` states. |
-| STATE                             | No           |  The status of the load job.                                       |
-| ORDER BY field_name [ASC \| DESC] | No           | Sorts the return result in ascending or descending order based on the specified field. The following fields are supported: `Id`, `Name`, `CreateTime`, `PauseTime`, `EndTime`, `TableName`, `State`, and `CurrentTaskNum`.<ul><li>To sort the return result in ascending order, specify `ORDER BY field_name ASC`.</li><li>To sort the return result in descending order, specify `ORDER BY field_name DESC`.</li></ul>If you do not specify the field or the sort order, the return result is sorted in ascending order of `Id` by default. |
-| LIMIT limit                       | No           | The number of load jobs that will be returned. For example, if `LIMIT 10` is specified, only the information of 10 load jobs that match filter conditions will be returned. If this parameter is not specified, the information of all load jobs that match the filter conditions are displayed.  |
-| OFFSET offset                     | No           | The `offset` parameter defines the number of load jobs to be skipped. For example, `OFFSET 5` skips the first five load jobs and returns the rest. The value of the `offset` parameter defaults to `0`. |
-
-## Output
-
-| **Parameter**        | **Description**                                              |
-| -------------------- | ------------------------------------------------------------ |
-| Id                   | The globally unique ID of the load job, generated automatically by StarRocks. |
-| Name                 | The name of the load job.                                        |
-| CreateTime           | The date and time when the load job was created.             |
-| PauseTime            | The date and time when the load job entered `PAUSED` state.  |
-| EndTime              | The date and time when the load job entered `STOPPED` state. |
-| DbName               | The database to which the target table of the load job belongs.  |
-| TableName            | The target table of the load job.                                |
-| State                | The status of the load job, including:<ul><li>`NEED_SCHEDULE`: The load job is waiting to be scheduled. After you use CREATE ROUTINE LOAD or RESUME ROUTINE LOAD to create or resume a Routine Load job, the load job first enters the `NEED_SCHEDULE` state.</li><li>`RUNNING`: The load job is running. You can view the consumption progress of the Routine Load job through `Statistic` and `Progress`.</li><li>`PAUSED`: The load job is paused. You can refer to `ReasonOfStateChanged` and `ErrorLogUrls` for troubleshooting. After fixing the error, you can use RESUME ROUTINE LOAD to resume the Routine Load job.</li><li>`CANCELLED`: The load job is cancelled. You can refer to `ReasonOfStateChanged` and `ErrorLogUrls` for troubleshooting. However, after fixing the error, you cannot recover the load job in this state.</li><li>`STOPPED`: The load job is stopped. You cannot recover the load job in this state.</li><li>`UNSTABLE`: The load job is unstable. A Routine Load job is set in the `UNSTABLE` state if any task within the Routine Load job lags (namely, the difference between the timestamp of the message being consumed and the current time exceeds this FE parameter [`routine_load_unstable_threshold_second`](../../../administration/management/FE_configuration.md#routine_load_unstable_threshold_second), and unconsumed messages exist in the data source.)</li></ul> |
-| DataSourceType       | The type of the data source. Fixed value: `KAFKA`.           |
-| CurrentTaskNum       | The current number of tasks in the load job.                     |
-| JobProperties        | The properties of the load job, such as partitions to be consumed and column mapping. |
-| DataSourceProperties | The properties of the data source, such as Topic and the list of addresses and ports of brokers in the Kafka cluster. |
-| CustomProperties     | The additional data source-related properties defined in the load job. |
-| Statistic            | The statistic of loading data, such as successfully loaded rows, total rows, and received data volume. |
-| Progress             | The progress (measured in the offset) of consuming messages in partitions of the topic. |
-| TimestampProgress    | The progress (measured in the timestamp) of consuming messages in partitions of the topic. |
-| ReasonOfStateChanged | The reasons for the load job being in CANCELLED or PAUSED state. |
-| ErrorLogUrls         | The URL of error logs. You can use the `curl` or `wget` command to  access the URL. |
-| TrackingSQL          | The SQL command that you can directly run to query the error log information recorded in the `information_schema` database. |
-| OtherMsg             | The information about all failed load tasks of the Routine Load job. |
-| LatestSourcePosition | The position of latest message in each partition of the topic, which helps check the latencies of data loading. |
-
-## Examples
-
-If a load job is successfully started and stays in the RUNNING state, the returned result might be as follows:
-
-```SQL
-MySQL [example_db]> SHOW ROUTINE LOAD FOR example_tbl_ordertest1\G
-*************************** 1. row ***************************
-                  Id: 10204
-                Name: example_tbl_ordertest1
-          CreateTime: 2023-12-21 21:01:31
-           PauseTime: NULL
-             EndTime: NULL
-              DbName: example_db
-           TableName: example_tbl
-               State: RUNNING
-      DataSourceType: KAFKA
-      CurrentTaskNum: 1
-       JobProperties: {"partitions":"*","rowDelimiter":"\t","partial_update":"false","columnToColumnExpr":"order_id,pay_dt,customer_name,nationality,temp_gender,price","maxBatchIntervalS":"10","partial_update_mode":"null","whereExpr":"*","timezone":"Asia/Shanghai","format":"csv","columnSeparator":"','","log_rejected_record_num":"0","taskTimeoutSecond":"60","json_root":"","maxFilterRatio":"1.0","strict_mode":"false","jsonpaths":"","taskConsumeSecond":"15","desireTaskConcurrentNum":"5","maxErrorNum":"0","strip_outer_array":"false","currentTaskConcurrentNum":"1","maxBatchRows":"200000"}
-DataSourceProperties: {"topic":"lilyliuyitest4csv","currentKafkaPartitions":"0","brokerList":"xxx.xx.xx.xxx:9092"}
-    CustomProperties: {"kafka_default_offsets":"OFFSET_BEGINNING","group.id":"example_tbl_ordertest1_b05da08f-9b9d-4fe1-b1f2-25d7116d617c"}
-           Statistic: {"receivedBytes":313,"errorRows":0,"committedTaskNum":1,"loadedRows":6,"loadRowsRate":0,"abortedTaskNum":0,"totalRows":6,"unselectedRows":0,"receivedBytesRate":0,"taskExecuteTimeMs":699}
-            Progress: {"0":"5"}
-   TimestampProgress: {"0":"1686143856061"}
-ReasonOfStateChanged: 
-        ErrorLogUrls: 
-         TrackingSQL: 
-            OtherMsg: 
-LatestSourcePosition: {"0":"6"}
-1 row in set (0.01 sec)
-```
-
-If a load job is in the `PAUSED` or `CANCELLED` state due to exceptions, you can troubleshoot based on the `ReasonOfStateChanged`, `ErrorLogUrls`, `TrackingSQL`, and `OtherMsg` fields in the return result.
-
-```SQL
-MySQL [example_db]> SHOW ROUTINE LOAD FOR example_tbl_ordertest2\G
-*************************** 1. row ***************************
-                  Id: 10204
-                Name: example_tbl_ordertest2
-          CreateTime: 2023-12-22 12:13:18
-           PauseTime: 2023-12-22 12:13:38
-             EndTime: NULL
-              DbName: example_db
-           TableName: example_tbl
-               State: PAUSED
-      DataSourceType: KAFKA
-      CurrentTaskNum: 0
-       JobProperties: {"partitions":"*","rowDelimiter":"\t","partial_update":"false","columnToColumnExpr":"order_id,pay_dt,customer_name,nationality,temp_gender,price","maxBatchIntervalS":"10","partial_update_mode":"null","whereExpr":"*","timezone":"Asia/Shanghai","format":"csv","columnSeparator":"','","log_rejected_record_num":"0","taskTimeoutSecond":"60","json_root":"","maxFilterRatio":"1.0","strict_mode":"false","jsonpaths":"","taskConsumeSecond":"15","desireTaskConcurrentNum":"5","maxErrorNum":"0","strip_outer_array":"false","currentTaskConcurrentNum":"1","maxBatchRows":"200000"}
-DataSourceProperties: {"topic":"mytest","currentKafkaPartitions":"0","brokerList":"xxx.xx.xx.xxx:9092"}
-    CustomProperties: {"kafka_default_offsets":"OFFSET_BEGINNING","group.id":"example_tbl_ordertest2_b3fada0f-6721-4ad1-920d-e4bf6d6ea7f7"}
-           Statistic: {"receivedBytes":541,"errorRows":10,"committedTaskNum":1,"loadedRows":6,"loadRowsRate":0,"abortedTaskNum":0,"totalRows":16,"unselectedRows":0,"receivedBytesRate":0,"taskExecuteTimeMs":646}
-            Progress: {"0":"19"}
-   TimestampProgress: {"0":"1702623900871"}
-ReasonOfStateChanged: ErrorReason{errCode = 102, msg='current error rows is more than max error num'}
-        ErrorLogUrls: http://xxx.xx.xx.xxx:8040/api/_load_error_log?file=error_log_b25dcc7e642344b2_b0b342b9de0567db
-         TrackingSQL: select tracking_log from information_schema.load_tracking_logs where job_id=10204
-            OtherMsg: 
-LatestSourcePosition: {"0":"20"}
-1 row in set (0.00 sec)
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD_TASK.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD_TASK.md
deleted file mode 100644
index 7f8683d52fc75e..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD_TASK.md
+++ /dev/null
@@ -1,70 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW ROUTINE LOAD TASK
-
-import RoutineLoadPrivNote from '../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
-
-## Description
-
-Shows the execution information of load tasks within a Routine Load job.
-
-:::note
-
-- <RoutineLoadPrivNote />
-
-- For the relationship between a Routine Load job and the load tasks in it, see [Load data using Routine Load](../../../loading/RoutineLoad.md#basic-concepts)
-
-:::
-
-## Syntax
-
-```SQL
-SHOW ROUTINE LOAD TASK
-[  FROM <db_name>]
-[  WHERE JobName = <job_name> ]
-```
-
-:::note
-
-You can add the `\G` option to the statement (such as `SHOW ROUTINE LOAD TASK WHERE JobName = <job_name>\G`) to vertically display the return result rather than in the usual horizontal table format.
-
-:::
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                             |
-| ------------- | ------------ | ----------------------------------------------------------- |
-| db_name       | No           | The name of the database to which the Routine Load job belongs. |
-| JobName       | No           | The name of the Routine Load job.                               |
-
-## Output
-
-| **Parameter**        | **Description**                                              |
-| -------------------- | ------------------------------------------------------------ |
-| TaskId               | The globally unique ID of the load task, automatically generated by StarRocks. |
-| TxnId                | The ID of the transaction to which the load task belongs.        |
-| TxnStatus            | The status of the transaction to which the load task belongs. `UNKNOWN` indicates that the transaction is not started yet, possibly because the load task is not dispatched or executed. |
-| JobId                | The ID of the load job.                                          |
-| CreateTime           | The date and time when the load task was created.            |
-| LastScheduledTime    | The date and time when the load task was last scheduled.     |
-| ExecuteStartTime     | The date and time when the load task was executed.           |
-| Timeout              | The timeout period for the load task, controlled by the FE parameter [`routine_load_task_timeout_second`](../../../administration/management/FE_configuration.md#routine_load_task_timeout_second) and the `task_timeout_second` parameter in [job_properties](./CREATE_ROUTINE_LOAD.md#job_properties) for the Routine Load job. |
-| BeId                 | The ID of the BE that executes the load task.                    |
-| DataSourceProperties | The load task's progress (measured in the offset) of consuming messages in partitions of the topic. |
-| Message              | The information returned for the load task, including task error information. |
-
-## Examples
-
-View all load tasks in the Routine Load job `example_tbl_ordertest`.
-
-```SQL
-MySQL [example_db]> SHOW ROUTINE LOAD TASK WHERE JobName = "example_tbl_ordertest";  
-+--------------------------------------+-------+-----------+-------+---------------------+---------------------+------------------+---------+------+------------------------------------+-----------------------------------------------------------------------------+
-| TaskId                               | TxnId | TxnStatus | JobId | CreateTime          | LastScheduledTime   | ExecuteStartTime | Timeout | BeId | DataSourceProperties               | Message                                                                     |
-+--------------------------------------+-------+-----------+-------+---------------------+---------------------+------------------+---------+------+------------------------------------+-----------------------------------------------------------------------------+
-| abde6998-c19a-43d6-b48c-6ca7e14144a3 | -1    | UNKNOWN   | 10208 | 2023-12-22 12:46:10 | 2023-12-22 12:47:00 | NULL             | 60      | -1   | Progress:{"0":6},LatestOffset:null | there is no new data in kafka/pulsar, wait for 10 seconds to schedule again |
-+--------------------------------------+-------+-----------+-------+---------------------+---------------------+------------------+---------+------+------------------------------------+-----------------------------------------------------------------------------+
-1 row in set (0.00 sec)
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_TABLES.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_TABLES.md
deleted file mode 100644
index edeb42757ef793..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_TABLES.md
+++ /dev/null
@@ -1,86 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW TABLES
-
-## Description
-
-Displays all tables in a StarRocks database or a database in an external data source, for example, Hive, Iceberg, Hudi, or Delta Lake.
-
-> **NOTE**
->
-> To view tables in an external data source, you must have the USAGE privilege on the external catalog that corresponds to that data source.
-
-## Syntax
-
-```sql
-SHOW TABLES [FROM <catalog_name>.<db_name>]
-```
-
-## Parameters
-
-| **Parameter**          | **Required** | **Description**                                                     |
-| ----------------- | -------- | ------------------------------------------------------------ |
-| catalog_name | No       | The name of the internal catalog or an external catalog.<ul><li>If you do not specify this parameter or set it to `default_catalog`, tables in StarRocks databases are returned.</li><li>If you set this parameter to the name of an external catalog, tables in databases of an external data source are returned.</li></ul> You can run [SHOW CATALOGS](SHOW_CATALOGS.md) to view internal and external catalogs.|
-| db_name | No       | The database name. If not specified, the current database is used by default. |
-
-## Examples
-
-Example 1: View tables in database `example_db` of the `default_catalog` after connecting to the StarRocks cluster. The following two statements are equivalent.
-
-```plain
-show tables from example_db;
-+----------------------------+
-| Tables_in_example_db       |
-+----------------------------+
-| depts                      |
-| depts_par                  |
-| emps                       |
-| emps2                      |
-+----------------------------+
-
-show tables from default_catalog.example_db;
-+----------------------------+
-| Tables_in_example_db       |
-+----------------------------+
-| depts                      |
-| depts_par                  |
-| emps                       |
-| emps2                      |
-+----------------------------+
-```
-
-Example 2: View tables in the current database `example_db` after connecting to this database.
-
-```plain
-show tables;
-+----------------------------+
-| Tables_in_example_db       |
-+----------------------------+
-| depts                      |
-| depts_par                  |
-| emps                       |
-| emps2                      |
-+----------------------------+
-```
-
-Example 2: View tables in database `hudi_db` of the external catalog `hudi_catalog`.
-
-```plain
-show tables from hudi_catalog.hudi_db;
-+----------------------------+
-| Tables_in_hudi_db          |
-+----------------------------+
-| hudi_sync_mor              |
-| hudi_table1                |
-+----------------------------+
-```
-
-Alternatively, you can run SET CATALOG to switch to the external catalog `hudi_catalog` and then run `SHOW TABLES FROM hudi_db;`.
-
-## References
-
-- [SHOW CATALOGS](SHOW_CATALOGS.md): Views all catalogs in a StarRocks cluster.
-- [SHOW DATABASES](SHOW_DATABASES.md): Views all databases in the internal catalog or an external catalog.
-- [SET CATALOG](../data-definition/SET_CATALOG.md): Switches between catalogs.
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_TABLET.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_TABLET.md
deleted file mode 100644
index 5f248156120f63..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_TABLET.md
+++ /dev/null
@@ -1,226 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW TABLET
-
-## Description
-
-Displays tablet related information.
-
-> **NOTE**
->
-> For v3.0 and later, this operation requires the SYSTEM-level OPERATE privilege and TABLE-level SELECT privilege. For v2.5 and earlier, this operation requires the ADMIN_PRIV privilege.
-
-## Syntax
-
-### Query information of tablets in a table or a partition
-
-```sql
-SHOW TABLET
-FROM [<db_name>.]<table_name>
-[PARTITION(<partition_name>, ...)]
-[
-WHERE [version = <version_number>] 
-    [[AND] backendid = <backend_id>] 
-    [[AND] STATE = "NORMAL"|"ALTER"|"CLONE"|"DECOMMISSION"]
-]
-[ORDER BY <field_name> [ASC | DESC]]
-[LIMIT [<offset>,]<limit>]
-```
-
-| **Parameter**       | **Required** | **Description**                                                     |
-| -------------- | -------- | ------------------------------------------------------------ |
-| db_name        | No       | The database name. If you do not specify this parameter, the current database is used by default.                     |
-| table_name     | Yes       | The name of the table from which you want to query tablet information. You must specify this parameter. Otherwise, an error is returned.                                                     |
-| partition_name | No       | The name of the partition from which you want to query tablet information.                                                     |
-| version_number | No       | The data version number.                                                   |
-| backend_id     | No       | The ID of the BE where the replica of the tablet is located.                                 |
-| STATE          | No       | The status of tablet replicas. <ul><li>`NORMAL`: The replica is normal.</li><li>`ALTER`: A Rollup or schema change is being performed on the replica.</li><li>`CLONE`: The replica is being cloned. (Replicas in this state are not available for use). </li><li>`DECOMMISSION`: The replica is being decommissioned. </li></ul> |
-| field_name     | No       | The field by which the results are sorted. All the fields returned by `SHOW TABLET FROM <table_name>` are sortable.<ul><li>If you want to display results in ascending order, use `ORDER BY field_name ASC`. </li><li>If you want to display results in descending order, use `ORDER BY field_name DESC`.</li></ul> |
-| offset         | No       | The number of tablets to skip from the results. For example, `OFFSET 5` means to skip the first five tablets. Default value: 0. |
-| limit          | No       | The number of tablets to return. For example, `LIMIT 10` means to return only 10 tablets. If this parameter is not specified, all the tablets that meet the filter conditions are returned. |
-
-### Query information of a single tablet
-
-After obtaining all tablet IDs using `SHOW TABLET FROM <table_name>`, you can query the information of a single tablet.
-
-```sql
-SHOW TABLET <tablet_id>
-```
-
-| **Parameter**  | **Required** | **Description**       |
-| --------- | -------- | -------------- |
-| tablet_id | Yes       | Tablet ID |
-
-## Description of return fields
-
-### Query information of tablets in a table or a partition
-
-```plain
-+----------+-----------+-----------+------------+---------+-------------+-------------------+-----------------------+------------------+----------------------+---------------+----------+----------+--------+-------------------------+--------------+------------------+--------------+----------+----------+-------------------+
-| TabletId | ReplicaId | BackendId | SchemaHash | Version | VersionHash | LstSuccessVersion | LstSuccessVersionHash | LstFailedVersion | LstFailedVersionHash | LstFailedTime | DataSize | RowCount | State  | LstConsistencyCheckTime | CheckVersion | CheckVersionHash | VersionCount | PathHash | MetaUrl  | CompactionStatus  |
-+----------+-----------+-----------+------------+---------+-------------+-------------------+-----------------------+------------------+----------------------+---------------+----------+----------+--------+-------------------------+--------------+------------------+--------------+----------+----------+-------------------+
-```
-
-| **Field**                | **Description**                        |
-| ----------------------- | ------------------------------- |
-| TabletId                | Table ID.                   |
-| ReplicaId               | Replica ID.                      |
-| BackendId               | The ID of the BE where the replica is located.  |
-| SchemaHash              | Schema hash (randomly generated).        |
-| Version                 | Data version number.                     |
-| VersionHash             | Hash of data version number.              |
-| LstSuccessVersion       | The last successfully loaded version.        |
-| LstSuccessVersionHash   | The hash of the last successfully loaded version. |
-| LstFailedVersion        | The version of the last failed loading. `-1` indicates no version failed to be loaded. |
-| LstFailedVersionHash    | The hash of the last failed version. |
-| LstFailedTime           | The time of the last failed loading. `NULL` indicates there is no load failure.       |
-| DataSize                | Data size of the tablet.          |
-| RowCount                | The number of data rows of the tablet.            |
-| State                   | Replica status of the tablet.           |
-| LstConsistencyCheckTime | The time of the last consistency check. `NULL` indicates no consistency check was performed. |
-| CheckVersion            | The data version on which consistency check was performed. `-1` indicates no version was checked.    |
-| CheckVersionHash        | The hash of the version on which consistency check was performed.         |
-| VersionCount            | The total number of data versions.                      |
-| PathHash                | The hash of the directory in which the tablet is stored.        |
-| MetaUrl                 | The URL used to query more meta information.     |
-| CompactionStatus        | The URL used to query data version compaction status.    |
-
-### Query information of a specific tablet
-
-```Plain
-+--------+-----------+---------------+-----------+------+---------+-------------+---------+--------+-----------+
-| DbName | TableName | PartitionName | IndexName | DbId | TableId | PartitionId | IndexId | IsSync | DetailCmd |
-+--------+-----------+---------------+-----------+------+---------+-------------+---------+--------+-----------+
-```
-
-| **Field**      | **Description**                                                     |
-| ------------- | ------------------------------------------------------------ |
-| DbName        | The name of the database to which the tablet belongs.      |
-| TableName     | The name of the table to which the tablet belongs.         |
-| PartitionName | The name of the partition to which the tablet belongs.     |
-| IndexName     | The index name.                                            |
-| DbId          | The database ID.                                           |
-| TableId       | The table ID.                                              |
-| PartitionId   | The partition ID.                                          |
-| IndexId       | The index ID.                                              |
-| IsSync        | Whether data on the tablet is consistent with table meta. `true` indicates data is consistent and the tablet is normal. `false` indicates data is missing on the tablet. |
-| DetailCmd     | The URL used to query more information.                    |
-
-## Examples
-
-Create table `test_show_tablet` in the database `example_db`.
-
-```sql
-CREATE TABLE `test_show_tablet` (
-  `k1` date NULL COMMENT "",
-  `k2` datetime NULL COMMENT "",
-  `k3` char(20) NULL COMMENT "",
-  `k4` varchar(20) NULL COMMENT "",
-  `k5` boolean NULL COMMENT "",
-  `k6` tinyint(4) NULL COMMENT "",
-  `k7` smallint(6) NULL COMMENT "",
-  `k8` int(11) NULL COMMENT "",
-  `k9` bigint(20) NULL COMMENT "",
-  `k10` largeint(40) NULL COMMENT "",
-  `k11` float NULL COMMENT "",
-  `k12` double NULL COMMENT "",
-  `k13` decimal128(27, 9) NULL COMMENT ""
-) ENGINE=OLAP 
-DUPLICATE KEY(`k1`, `k2`, `k3`, `k4`, `k5`)
-COMMENT "OLAP"
-PARTITION BY RANGE(`k1`)
-(PARTITION p20210101 VALUES [("2021-01-01"), ("2021-01-02")),
-PARTITION p20210102 VALUES [("2021-01-02"), ("2021-01-03")),
-PARTITION p20210103 VALUES [("2021-01-03"), ("2021-01-04")),
-PARTITION p20210104 VALUES [("2021-01-04"), ("2021-01-05")),
-PARTITION p20210105 VALUES [("2021-01-05"), ("2021-01-06")),
-PARTITION p20210106 VALUES [("2021-01-06"), ("2021-01-07")),
-PARTITION p20210107 VALUES [("2021-01-07"), ("2021-01-08")),
-PARTITION p20210108 VALUES [("2021-01-08"), ("2021-01-09")),
-PARTITION p20210109 VALUES [("2021-01-09"), ("2021-01-10")))
-DISTRIBUTED BY HASH(`k1`, `k2`, `k3`);
-```
-
-- Example 1: Query information of all the tablets in the specified table. The following example excerpts information of only one tablet from the return information.
-
-    ```plain
-        mysql> show tablet from example_db.test_show_tablet\G
-        *************************** 1. row ***************************
-                TabletId: 9588955
-                ReplicaId: 9588956
-                BackendId: 10004
-                SchemaHash: 0
-                    Version: 1
-                VersionHash: 0
-          LstSuccessVersion: 1
-      LstSuccessVersionHash: 0
-           LstFailedVersion: -1
-       LstFailedVersionHash: 0
-            LstFailedTime: NULL
-                DataSize: 0B
-                RowCount: 0
-                    State: NORMAL
-    LstConsistencyCheckTime: NULL
-            CheckVersion: -1
-        CheckVersionHash: 0
-            VersionCount: 1
-                PathHash: 0
-                 MetaUrl: http://172.26.92.141:8038/api/meta/header/9588955
-        CompactionStatus: http://172.26.92.141:8038/api/compaction/show?tablet_id=9588955
-    ```
-
-- Example 2: Query information of tablet 9588955.
-
-    ```plain
-        mysql> show tablet 9588955\G
-        *************************** 1. row ***************************
-        DbName: example_db
-        TableName: test_show_tablet
-        PartitionName: p20210103
-        IndexName: test_show_tablet
-            DbId: 11145
-        TableId: 9588953
-    PartitionId: 9588946
-        IndexId: 9588954
-        IsSync: true
-        DetailCmd: SHOW PROC '/dbs/11145/9588953/partitions/9588946/9588954/9588955';
-    ```
-
-- Example 3: Query information of tablets in partition `p20210103`.
-
-    ```sql
-    SHOW TABLET FROM test_show_tablet partition(p20210103);
-    ```
-
-- Example 4: Return information of 10 tablets.
-
-    ```sql
-        SHOW TABLET FROM test_show_tablet limit 10;
-    ```
-
-- Example 5: Return information of 10 tablets with an offset 5.
-
-    ```sql
-    SHOW TABLET FROM test_show_tablet limit 5,10;
-    ```
-
-- Example 6: Filter tablets by `backendid`, `version`, and `state`.
-
-    ```sql
-        SHOW TABLET FROM test_show_tablet
-        WHERE backendid = 10004 and version = 1 and state = "NORMAL";
-    ```
-
-- Example 7: Sort tablets by `version`.
-
-    ```sql
-        SHOW TABLET FROM table_name where backendid = 10004 order by version;
-    ```
-
-- Example 8: Return information of tablets whose index name is `test_show_tablet`.
-
-    ```sql
-    SHOW TABLET FROM test_show_tablet where indexname = "test_show_tablet";
-    ```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_TRANSACTION.md b/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_TRANSACTION.md
deleted file mode 100644
index bbb5766f50ad3d..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SHOW_TRANSACTION.md
+++ /dev/null
@@ -1,65 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW TRANSACTION
-
-## Description
-
-This syntax is used to view the transaction details of the specified transaction id.
-
-Syntax:
-
-```sql
-SHOW TRANSACTION
-[FROM <db_name>]
-WHERE id = transaction_id
-```
-
-Examples of returned results:
-
-```plain text
-TransactionId: 4005
-Label: insert_8d807d5d-bcdd-46eb-be6d-3fa87aa4952d
-Coordinator: FE: 10.74.167.16
-TransactionStatus: VISIBLE
-LoadJobSourceType: INSERT_STREAMING
-PrepareTime: 2020-01-09 14:59:07
-CommitTime: 2020-01-09 14:59:09
-FinishTime: 2020-01-09 14:59:09
-Reason:
-ErrorReplicasCount: 0
-ListenerId: -1
-TimeoutMs: 300000
-```
-
-* TransactionId: transaction id
-* Label: import the label corresponding to the task
-* Coordinator: the node responsible for transaction coordination
-* TransactionStatus: transaction status
-* PREPARE: preparation stage
-* COMMITTED: the transaction succeeded, but the data is not visible
-* VISIBLE: the transaction is successful and the data is visible
-* ABORTED: transaction failed
-* LoadJobSourceType: type of import task.
-* PrepareTime: transaction start time
-* CommitTime: the time when the transaction is successfully committed
-* FinishTime: the time when the data is visible
-* Reason: error message
-* ErrorReplicasCount: number of replicas with errors
-* ListenerId: id of the related import job
-* TimeoutMs: transaction timeout, in milliseconds
-
-## Examples
-
-1. To view a transaction with id 4005:
-
-    ```sql
-    SHOW TRANSACTION WHERE ID=4005;
-    ```
-
-2. In the specified dB, view the transaction with id 4005:
-
-    ```sql
-    SHOW TRANSACTION FROM db WHERE ID=4005;
-    ```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md b/docs/en/sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md
deleted file mode 100644
index c12142529a0f02..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md
+++ /dev/null
@@ -1,276 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SPARK LOAD
-
-## Description
-
-Spark load preprocesses the imported data through external spark resources, improves the import performance of a large amount of StarRocks data, and saves the computing resources of StarRocks cluster. It is mainly used in the scenario of initial migration and large amount of data import into StarRocks.
-
-Spark load is an asynchronous import method. Users need to create Spark type import tasks through MySQL protocol and view the import results through`SHOW LOAD`.
-
-> **NOTICE**
->
-> - You can load data into StarRocks tables only as a user who has the INSERT privilege on those StarRocks tables. If you do not have the INSERT privilege, follow the instructions provided in [GRANT](../account-management/GRANT.md) to grant the INSERT privilege to the user that you use to connect to your StarRocks cluster.
-> - When Spark Load is used to load data into a StarRocks table, the bucketing column of the StarRocks table cannot be of DATE, DATETIME, or DECIMAL type.
-
-Syntax
-
-```sql
-LOAD LABEL load_label
-(
-data_desc1[, data_desc2, ...]
-)
-WITH RESOURCE resource_name
-[resource_properties]
-[opt_properties]
-```
-
-1.load_label
-
-Label of the currently imported batch. Unique within a database.
-
-Syntax:
-
-```sql
-[database_name.]your_label
-```
-
-2.data_desc
-
-Used to describe a batch of imported data.
-
-Syntax:
-
-```sql
-DATA INFILE
-(
-"file_path1"[, file_path2, ...]
-)
-[NEGATIVE]
-INTO TABLE `table_name`
-[PARTITION (p1, p2)]
-[COLUMNS TERMINATED BY "column_separator"]
-[FORMAT AS "file_type"]
-[(column_list)]
-[COLUMNS FROM PATH AS (col2, ...)]
-[SET (k1 = func(k2))]
-[WHERE predicate]
-
-DATA FROM TABLE hive_external_tbl
-[NEGATIVE]
-INTO TABLE tbl_name
-[PARTITION (p1, p2)]
-[SET (k1=f1(xx), k2=f2(xx))]
-[WHERE predicate]
-```
-
-Note
-
-```plain text
-file_path:
-
-The file path can be specified to one file, or the * wildcard can be used to specify all files in a directory. Wildcards must match files, not directories.
-
-hive_external_tbl:
-
-hive external table name.
-It is required that the columns in the imported starrocks table must exist in the hive external table.
-Each load task only supports loading from one Hive external table.
-Cannot be used with file_ path mode at the same time.
-
-PARTITION:
-
-If this parameter is specified, only the specified partition will be imported, and the data outside the imported partition will be filtered out.
-If not specified, all partitions of table will be imported by default.
-
-NEGATIVE:
-
-If this parameter is specified, it is equivalent to loading a batch of "negative" data. Used to offset the same batch of previously imported data.
-This parameter is only applicable when the value column exists and the aggregation type of the value column is SUM only.
-
-column_separator:
-
-Specifies the column separator in the import file. Default is \ t
-If it is an invisible character, you need to prefix it with \ \ x and use hexadecimal to represent the separator.
-For example, the separator of hive file \ x01 is specified as "\ \ x01"
-
-file_type:
-
-Used to specify the type of imported file. Currently, supported file types are csv, orc, and parquet.
-
-column_list:
-
-Used to specify the correspondence between the columns in the import file and the columns in the table.
-When you need to skip a column in the import file, specify the column as a column name that does not exist in the table.
-
-Syntax:
-(col_name1, col_name2, ...)
-
-SET:
-
-If specify this parameter, you can convert a column of the source file according to the function, and then import the converted results into table. Syntax is column_name = expression.
-Only Spark SQL build_in functions are supported. Please refer to https://spark.apache.org/docs/2.4.6/api/sql/index.html.
-Give a few examples to help understand.
-Example 1: there are three columns "c1, c2, c3" in the table, and the first two columns in the source file correspond to (c1, c2), and the sum of the last two columns corresponds to C3; then columns (c1, c2, tmp_c3, tmp_c4) set (c3 = tmp_c3 + tmp_c4) needs to be specified;
-Example 2: there are three columns "year, month and day" in the table, and there is only one time column in the source file in the format of "2018-06-01 01:02:03".
-Then you can specify columns (tmp_time) set (year = year (tmp_time), month = month (tmp_time), day = day (tmp_time)) to complete the import.
-
-WHERE:
-
-Filter the transformed data, and only the data that meets the where condition can be imported. Only the column names in the table can be referenced in the WHERE statement
-```
-
-3.resource_name
-
-The name of the spark resource used can be viewed through `SHOW RESOURCES` command.
-
-4.resource_properties
-
-When you have a temporary need, such as modifying the Spark and HDFS configurations, you can set the parameters here, which takes effect only in this specific spark loading job and not to affect the existing configurations in the StarRocks cluster.
-
-5.opt_properties
-
-Used to specify some special parameters.
-
-Syntax:
-
-```sql
-[PROPERTIES ("key"="value", ...)]
-```
-
-You can specify the following parameters:
-timeout:         specifies the timeout of the import operation. The default timeout is 4 hours. In seconds.
-max_filter_ratio:the maximum allowable data proportion that can be filtered (for reasons such as non-standard data). The default is zero tolerance.
-strict mode:     whether to strictly restrict the data. The default is false.
-timezone:         specifies the time zone of some functions affected by the time zone, such as strftime / alignment_timestamp/from_unixtime, etc. Please refer to the [time zone] document for details. If not specified, the "Asia / Shanghai" time zone is used.
-
-6.Import data format example
-
-int (TINYINT/SMALLINT/INT/BIGINT/LARGEINT): 1, 1000, 1234
-float (FLOAT/DOUBLE/DECIMAL): 1.1, 0.23, .356
-date (DATE/DATETIME) :2017-10-03, 2017-06-13 12:34:03.
-(Note: for other date formats, you can use strftime or time_format function to convert in the Import command) string class (CHAR/VARCHAR): "I am a student", "a"
-
-NULL value: \ N
-
-## Examples
-
-1. Import a batch of data from HDFS, and specify the timeout time and filtering ratio. Use the name my_ spark resources for spark.
-
-    ```sql
-    LOAD LABEL example_db.label1
-    (
-    DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/file")
-    INTO TABLE `my_table`
-    )
-    WITH RESOURCE 'my_spark'
-    PROPERTIES
-    (
-        "timeout" = "3600",
-        "max_filter_ratio" = "0.1"
-    );
-    ```
-
-    Where hdfs_host is the host of namenode, hdfs_port is fs.defaultfs port (default 9000)
-
-2. Import a batch of "negative" data from HDFS, specify the separator as comma, use the wildcard * to specify all files in the directory, and specify the temporary parameters of spark resources.
-
-    ```sql
-    LOAD LABEL example_db.label3
-    (
-    DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/*")
-    NEGATIVE
-    INTO TABLE `my_table`
-    COLUMNS TERMINATED BY ","
-    )
-    WITH RESOURCE 'my_spark'
-    (
-        "spark.executor.memory" = "3g",
-        "broker.username" = "hdfs_user",
-        "broker.password" = "hdfs_passwd"
-    );
-    ```
-
-3. Import a batch of data from HDFS, specify the partition, and do some conversion on the columns of the imported file, as follows:
-
-    ```plain text
-    The table structure is:
-    k1 varchar(20)
-    k2 int
-    
-    Assume that the data file has only one line of data:
-    
-    Adele,1,1
-    
-    Each column in the data file corresponds to each column specified in the import statement:
-    k1,tmp_k2,tmp_k3
-    
-    The conversion is as follows:
-    
-    1. k1: no conversion
-    2. k2:is the sum of tmp_ k2 and tmp_k3
-    
-    LOAD LABEL example_db.label6
-    (
-    DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/file")
-    INTO TABLE `my_table`
-    PARTITION (p1, p2)
-    COLUMNS TERMINATED BY ","
-    (k1, tmp_k2, tmp_k3)
-    SET (
-    k2 = tmp_k2 + tmp_k3
-    )
-    )
-    WITH RESOURCE 'my_spark';
-    ```
-
-4. Extract the partition field in the file path
-
-    If necessary, the partitioned fields in the file path will be resolved according to the field types defined in the table, similar to the function of Partition Discovery in Spark
-
-    ```sql
-    LOAD LABEL example_db.label10
-    (
-    DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/dir/city=beijing/*/*")
-    INTO TABLE `my_table`
-    (k1, k2, k3)
-    COLUMNS FROM PATH AS (city, utc_date)
-    SET (uniq_id = md5sum(k1, city))
-    )
-    WITH RESOURCE 'my_spark';
-    ```
-
-    `hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/dir/city=beijing`  The directory includes the following files:
-
-    `[hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/dir/city=beijing/utc_date=2019-06-26/0000.csv, hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/dir/city=beijing/utc_date=2019-06-26/0001.csv, ...]`
-
-    The city and utc_date field in the file path are extracted
-
-5. Filter the data to be imported. Only columns with k1 value greater than 10 can be imported.
-
-    ```sql
-    LOAD LABEL example_db.label10
-    (
-    DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/file")
-    INTO TABLE `my_table`
-    WHERE k1 > 10
-    )
-    WITH RESOURCE 'my_spark';
-    ```
-
-6. Import from the hive external table and convert the uuid column in the source table to the bitmap type through the global dictionary.
-
-    ```sql
-    LOAD LABEL db1.label1
-    (
-    DATA FROM TABLE hive_t1
-    INTO TABLE tbl1
-    SET
-    (
-    uuid=bitmap_dict(uuid)
-    )
-    )
-    WITH RESOURCE 'my_spark';
-    ```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/STOP_ROUTINE_LOAD.md b/docs/en/sql-reference/sql-statements/data-manipulation/STOP_ROUTINE_LOAD.md
deleted file mode 100644
index 34131c68ab486b..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/STOP_ROUTINE_LOAD.md
+++ /dev/null
@@ -1,41 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# STOP ROUTINE LOAD
-
-import RoutineLoadPrivNote from '../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
-
-## Description
-
-Stops a Routine Load job.
-
-<RoutineLoadPrivNote />
-
-::: warning
-
-- A stopped Routine Load job cannot be resumed. Therefore, please proceed with caution when executing this statement.
-- If you only need to pause the Routine Load job, you can execute [PAUSE ROUTINE LOAD](./PAUSE_ROUTINE_LOAD.md).
-
-:::
-
-## Syntax
-
-```SQL
-STOP ROUTINE LOAD FOR [db_name.]<job_name>
-```
-
-## Parameters
-
-| **Parameter** | **Required** | **Description**                                              |
-| ------------- | ------------ | ------------------------------------------------------------ |
-| db_name       |              | The name of the database to which the Routine Load job belongs. |
-| job_name      | ✅            | The name of the Routine Load job.                            |
-
-## Examples
-
-Stop the Routine Load job `example_tbl1_ordertest1` in the database `example_db`.
-
-```SQL
-STOP ROUTINE LOAD FOR example_db.example_tbl1_ordertest1;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md b/docs/en/sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md
deleted file mode 100644
index fc57efd66f8a0a..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md
+++ /dev/null
@@ -1,555 +0,0 @@
----
-displayed_sidebar: "English"
-toc_max_heading_level: 4
----
-
-# STREAM LOAD
-
-:::tip
-The [StarRocks in Docker](../../../quick_start/shared-nothing.md) quick start features Stream Load. Give it a try for hands-on experience and a detailed explanation of a realistic ETL flow.
-:::
-
-## Description
-
-StarRocks provides the loading method HTTP-based Stream Load to help you load data from a local file system or a streaming data source. After you submit a load job, StarRocks synchronously runs the job, and returns the result of the job after the job finishes. You can determine whether the job is successful based on the job result. For information about the application scenarios, limits, principles, and supported data file formats of Stream Load, see [Loading from a local file system via Stream Load](../../../loading/StreamLoad.md#loading-from-a-local-file-system-via-stream-load).
-
-Since v3.2.7, Stream Load supports compressing JSON data during transmission, reducing network bandwidth overhead. Users can specify different compression algorithms using parameters `compression` and `Content-Encoding`. Supported compression algorithms including GZIP, BZIP2, LZ4_FRAME, and ZSTD. For more information, see [data_desc](#data_desc).
-
-> **NOTICE**
->
-> - After you load data into a StarRocks table by using Stream Load, the data of the materialized views that are created on that table is also updated.
-> - You can load data into StarRocks tables only as a user who has the INSERT privilege on those StarRocks tables. If you do not have the INSERT privilege, follow the instructions provided in [GRANT](../account-management/GRANT.md) to grant the INSERT privilege to the user that you use to connect to your StarRocks cluster.
-
-## Syntax
-
-```Bash
-curl --location-trusted -u <username>:<password> -XPUT <url>
-(
-    data_desc
-)
-[opt_properties]        
-```
-
-This topic uses curl as an example to describe how to load data by using Stream Load. In addition to curl, you can also use other HTTP-compatible tools or languages to perform Stream Load. Load-related parameters are included in HTTP request header fields. When you input these parameters, take note of the following points:
-
-- You can use chunked transfer encoding, as demonstrated in this topic. If you do not choose chunked transfer encoding, you must input a `Content-Length` header field to indicate the length of content to be transferred, thereby ensuring data integrity.
-
-  > **NOTE**
-  >
-  > If you use curl to perform Stream Load, StarRocks automatically adds a `Content-Length` header field and you do not need manually input it.
-
-- You must add an `Expect` header field and specify its value as `100-continue`, as in `"Expect:100-continue"`. This helps prevent unnecessary data transfers and reduce resource overheads in case your job request is denied.
-
-Note that in StarRocks some literals are used as reserved keywords by the SQL language. Do not directly use these keywords in SQL statements. If you want to use such a keyword in an SQL statement, enclose it in a pair of backticks (`). See [Keywords](../../../sql-reference/sql-statements/keywords.md).
-
-## Parameters
-
-### username and password
-
-Specify the username and password of the account that you use to connect to your StarRocks cluster. This is a required parameter. If you use an account for which no password is set, you need to input only `<username>:`.
-
-### XPUT
-
-Specifies the HTTP request method. This is a required parameter. Stream Load supports only the PUT method.
-
-### url
-
-Specifies the URL of the StarRocks table. Syntax:
-
-```Plain
-http://<fe_host>:<fe_http_port>/api/<database_name>/<table_name>/_stream_load
-```
-
-The following table describes the parameters in the URL.
-
-| Parameter     | Required | Description                                                  |
-| ------------- | -------- | ------------------------------------------------------------ |
-| fe_host       | Yes      | The IP address of the FE node in your StarRocks cluster.<br/>**NOTE**<br/>If you submit the load job to a specific BE or CN node, you must input the IP address of the BE or CN node. |
-| fe_http_port  | Yes      | The HTTP port number of the FE node in your StarRocks cluster. The default port number is `8030`.<br/>**NOTE**<br/>If you submit the load job to a specific BE or CN node, you must input the HTTP port number of the BE or CN node. The default port number is `8030`. |
-| database_name | Yes      | The name of the database to which the StarRocks table belongs. |
-| table_name    | Yes      | The name of the StarRocks table.                             |
-
-> **NOTE**
->
-> You can use [SHOW FRONTENDS](../Administration/SHOW_FRONTENDS.md) to view the IP address and HTTP port of the FE node.
-
-### data_desc
-
-Describes the data file that you want to load. The `data_desc` descriptor can include the data file's name, format, column separator, row separator, destination partitions, and column mapping against the StarRocks table. Syntax:
-
-```Bash
--T <file_path>
--H "format: CSV | JSON"
--H "column_separator: <column_separator>"
--H "row_delimiter: <row_delimiter>"
--H "columns: <column1_name>[, <column2_name>, ... ]"
--H "partitions: <partition1_name>[, <partition2_name>, ...]"
--H "temporary_partitions: <temporary_partition1_name>[, <temporary_partition2_name>, ...]"
--H "jsonpaths: [ \"<json_path1>\"[, \"<json_path2>\", ...] ]"
--H "strip_outer_array: true | false"
--H "json_root: <json_path>"
--H "ignore_json_size: true | false"
--H "compression: <compression_algorithm> | Content-Encoding: <compression_algorithm>"
-```
-
-The parameters in the `data_desc` descriptor can be divided into three types: common parameters, CSV parameters, and JSON parameters.
-
-#### Common parameters
-
-| Parameter  | Required | Description                                                  |
-| ---------- | -------- | ------------------------------------------------------------ |
-| file_path  | Yes      | The save path of the data file. You can optionally include the extension of the file name. |
-| format     | No       | The format of the data file. Valid values: `CSV` and `JSON`. Default value: `CSV`. |
-| partitions | No       | The partitions into which you want to load the data file. By default, if you do not specify this parameter, StarRocks loads the data file into all partitions of the StarRocks table. |
-| temporary_partitions|  No       | The name of the [temporary partition](../../../table_design/Temporary_partition.md) into which you want to load data file. You can specify multiple temporary partitions, which must be separated by commas (,).|
-| columns    | No       | The column mapping between the data file and the StarRocks table.<br/>If the fields in the data file can be mapped in sequence onto the columns in the StarRocks table, you do not need to specify this parameter. Instead, you can use this parameter to implement data conversions. For example, if you load a CSV data file and the file consists of two columns that can be mapped in sequence onto the two columns, `id` and `city`, of the StarRocks table, you can specify `"columns: city,tmp_id, id = tmp_id * 100"`. For more information, see the "[Column mapping](#column-mapping)" section in this topic. |
-
-#### CSV parameters
-
-| Parameter        | Required | Description                                                  |
-| ---------------- | -------- | ------------------------------------------------------------ |
-| column_separator | No       | The characters that are used in the data file to separate fields. If you do not specify this parameter, this parameter defaults to `\t`, which indicates tab.<br/>Make sure that the column separator you specify by using this parameter is the same as the column separator used in the data file.<br/>**NOTE**<br/>For CSV data, you can use a UTF-8 string, such as a comma (,), tab, or pipe (\|), whose length does not exceed 50 bytes as a text delimiter. |
-| row_delimiter    | No       | The characters that are used in the data file to separate rows. If you do not specify this parameter, this parameter defaults to `\n`. |
-| skip_header      | No       | Specifies whether to skip the first few rows of the data file when the data file is in CSV format. Type: INTEGER. Default value: `0`.<br />In some CSV-formatted data files, the first few rows at the beginning are used to define metadata such as column names and column data types. By setting the `skip_header` parameter, you can enable StarRocks to skip the first few rows of the data file during data loading. For example, if you set this parameter to `1`, StarRocks skips the first row of the data file during data loading.<br />The first few rows at the beginning in the data file must be separated by using the row separator that you specify in the load command. |
-| trim_space       | No       | Specifies whether to remove spaces preceding and following column separators from the data file when the data file is in CSV format. Type: BOOLEAN. Default value: `false`.<br />For some databases, spaces are added to column separators when you export data as a CSV-formatted data file. Such spaces are called leading spaces or trailing spaces depending on their locations. By setting the `trim_space` parameter, you can enable StarRocks to remove such unnecessary spaces during data loading.<br />Note that StarRocks does not remove the spaces (including leading spaces and trailing spaces) within a field wrapped in a pair of `enclose`-specified characters. For example, the following field values use pipe (<code class="language-text">&#124;</code>) as the column separator and double quotation marks (`"`) as the `enclose`-specified character:<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124; "Love StarRocks" &#124;</code> <br />If you set `trim_space` to `true`, StarRocks processes the preceding field values as follows:<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> |
-| enclose          | No       | Specifies the character that is used to wrap the field values in the data file according to [RFC4180](https://www.rfc-editor.org/rfc/rfc4180) when the data file is in CSV format. Type: single-byte character. Default value: `NONE`. The most prevalent characters are single quotation mark (`'`) and double quotation mark (`"`).<br />All special characters (including row separators and column separators) wrapped by using the `enclose`-specified character are considered normal symbols. StarRocks can do more than RFC4180 as it allows you to specify any single-byte character as the `enclose`-specified character.<br />If a field value contains an `enclose`-specified character, you can use the same character to escape that `enclose`-specified character. For example, you set `enclose` to `"`, and a field value is `a "quoted" c`. In this case, you can enter the field value as `"a ""quoted"" c"` into the data file. |
-| escape           | No       | Specifies the character that is used to escape various special characters, such as row separators, column separators, escape characters, and `enclose`-specified characters, which are then considered by StarRocks to be common characters and are parsed as part of the field values in which they reside. Type: single-byte character. Default value: `NONE`. The most prevalent character is slash (`\`), which must be written as double slashes (`\\`) in SQL statements.<br />**NOTE**<br />The character specified by `escape` is applied to both inside and outside of each pair of `enclose`-specified characters.<br />Two examples are as follows:<ul><li>When you set `enclose` to `"` and `escape` to `\`, StarRocks parses `"say \"Hello world\""` into `say "Hello world"`.</li><li>Assume that the column separator is comma (`,`). When you set `escape` to `\`, StarRocks parses `a, b\, c` into two separate field values: `a` and `b, c`.</li></ul> |
-
-> **NOTE**
->
-> - For CSV data, you can use a UTF-8 string, such as a comma (,), tab, or pipe (|), whose length does not exceed 50 bytes as a text delimiter.
-> - Null values are denoted by using `\N`. For example, a data file consists of three columns, and a record from that data file holds data in the first and third columns but no data in the second column. In this situation, you need to use `\N` in the second column to denote a null value. This means the record must be compiled as `a,\N,b` instead of `a,,b`. `a,,b` denotes that the second column of the record holds an empty string.
-> - The format options, including `skip_header`, `trim_space`, `enclose`, and `escape`, are supported in v3.0 and later.
-
-#### JSON parameters
-
-| Parameter         | Required | Description                                                  |
-| ----------------- | -------- | ------------------------------------------------------------ |
-| jsonpaths         | No       | The names of the keys that you want to load from the JSON data file. You need to specify this parameter only when you load JSON data by using the matched mode. The value of this parameter is in JSON format. See [Configure column mapping for JSON data loading](#configure-column-mapping-for-json-data-loading).           |
-| strip_outer_array | No       | Specifies whether to strip the outermost array structure. Valid values: `true` and `false`. Default value: `false`.<br/>In real-world business scenarios, the JSON data may have an outermost array structure as indicated by a pair of square brackets `[]`. In this situation, we recommend that you set this parameter to `true`, so StarRocks removes the outermost square brackets `[]` and loads each inner array as a separate data record. If you set this parameter to `false`, StarRocks parses the entire JSON data file into one array and loads the array as a single data record.<br/>For example, the JSON data is `[ {"category" : 1, "author" : 2}, {"category" : 3, "author" : 4} ]`. If you set this parameter to `true`,  `{"category" : 1, "author" : 2}` and `{"category" : 3, "author" : 4}` are parsed into separate data records that are loaded into separate StarRocks table rows. |
-| json_root         | No       | The root element of the JSON data that you want to load from the JSON data file. You need to specify this parameter only when you load JSON data by using the matched mode. The value of this parameter is a valid JsonPath string. By default, the value of this parameter is empty, indicating that all data of the JSON data file will be loaded. For more information, see the "[Load JSON data using matched mode with root element specified](#load-json-data-using-matched-mode-with-root-element-specified)" section of this topic. |
-| ignore_json_size  | No       | Specifies whether to check the size of the JSON body in the HTTP request.<br/>**NOTE**<br/>By default, the size of the JSON body in an HTTP request cannot exceed 100 MB. If the JSON body exceeds 100 MB in size, an error "The size of this batch exceed the max size [104857600] of json type data data [8617627793]. Set ignore_json_size to skip check, although it may lead huge memory consuming." is reported. To prevent this error, you can add `"ignore_json_size:true"` in the HTTP request header to instruct StarRocks not to check the JSON body size. |
-| compression, Content-Encoding | NO | The encoding algorithm that is applied to the data during transmission. Supported algorithms include GZIP, BZIP2, LZ4_FRAME, and ZSTD. Example: `curl --location-trusted -u root:  -v 'http://127.0.0.1:18030/api/db0/tbl_simple/_stream_load' \-X PUT  -H "expect:100-continue" \-H 'format: json' -H 'compression: lz4_frame'   -T ./b.json.lz4`. |
-
-When you load JSON data, also note that the size per JSON object cannot exceed 4 GB. If an individual JSON object in the JSON data file exceeds 4 GB in size, an error "This parser can't support a document that big." is reported.
-
-### opt_properties
-
-Specifies some optional parameters, which are applied to the entire load job. Syntax:
-
-```Bash
--H "label: <label_name>"
--H "where: <condition1>[, <condition2>, ...]"
--H "max_filter_ratio: <num>"
--H "timeout: <num>"
--H "strict_mode: true | false"
--H "timezone: <string>"
--H "load_mem_limit: <num>"
--H "partial_update: true | false"
--H "partial_update_mode: row | column"
--H "merge_condition: <column_name>"
-```
-
-The following table describes the optional parameters.
-
-| Parameter        | Required | Description                                                  |
-| ---------------- | -------- | ------------------------------------------------------------ |
-| label            | No       | The label of the load job. If you do not specify this parameter, StarRocks automatically generates a label for the load job.<br/>StarRocks does not allow you to use one label to load a data batch multiple times. As such, StarRocks prevents the same data from being repeatedly loaded. For label naming conventions, see [System limits](../../../reference/System_limit.md).<br/>By default, StarRocks retains the labels of load jobs that were successfully completed over the most recent three days. You can use the [FE parameter](../../../administration/management/FE_configuration.md) `label_keep_max_second` to change the label retention period. |
-| where            | No       | The conditions based on which StarRocks filters the pre-processed data. StarRocks loads only the pre-processed data that meets the filter conditions specified in the WHERE clause. |
-| max_filter_ratio | No       | The maximum error tolerance of the load job. The error tolerance is the maximum percentage of data records that can be filtered out due to inadequate data quality in all data records requested by the load job. Valid values: `0` to `1`. Default value: `0`.<br/>We recommend that you retain the default value `0`. This way, if unqualified data records are detected, the load job fails, thereby ensuring data correctness.<br/>If you want to ignore unqualified data records, you can set this parameter to a value greater than `0`. This way, the load job can succeed even if the data file contains unqualified data records.<br/>**NOTE**<br/>Unqualified data records do not include data records that are filtered out by the WHERE clause. |
-| log_rejected_record_num | No           | Specifies the maximum number of unqualified data rows that can be logged. This parameter is supported from v3.1 onwards. Valid values: `0`, `-1`, and any non-zero positive integer. Default value: `0`.<ul><li>The value `0` specifies that data rows that are filtered out will not be logged.</li><li>The value `-1` specifies that all data rows that are filtered out will be logged.</li><li>A non-zero positive integer such as `n` specifies that up to `n` data rows that are filtered out can be logged on each BE or CN.</li></ul> |
-| timeout          | No       | The timeout period of the load job. Valid values: `1` to `259200`. Unit: second. Default value: `600`.<br/>**NOTE**In addition to the `timeout` parameter, you can also use the [FE parameter](../../../administration/management/FE_configuration.md) `stream_load_default_timeout_second` to centrally control the timeout period for all Stream Load jobs in your StarRocks cluster. If you specify the `timeout` parameter, the timeout period specified by the `timeout` parameter prevails. If you do not specify the `timeout` parameter, the timeout period specified by the `stream_load_default_timeout_second` parameter prevails. |
-| strict_mode      | No       | Specifies whether to enable the [strict mode](../../../loading/load_concept/strict_mode.md). Valid values: `true` and `false`. Default value: `false`.  The value `true` specifies to enable the strict mode, and the value `false` specifies to disable the strict mode. |
-| timezone         | No       | The time zone used by the load job. Default value: `Asia/Shanghai`. The value of this parameter affects the results returned by functions such as strftime, alignment_timestamp, and from_unixtime. The time zone specified by this parameter is a session-level time zone. For more information, see [Configure a time zone](../../../administration/management/timezone.md). |
-| load_mem_limit   | No       | The maximum amount of memory that can be provisioned to the load job. Unit: bytes. By default, the maximum memory size for a load job is 2 GB. The value of this parameter cannot exceed the maximum amount of memory that can be provisioned to each BE or CN. |
-| partial_update | No | Whether to use partial updates. Valid values: `TRUE` and `FALSE`. Default value: `FALSE`, indicating to disable this feature. |
-| partial_update_mode | No | Specifies the mode for partial updates. Valid values: `row` and `column`. <ul><li> The value `row` (default) means partial updates in row mode, which is more suitable for real-time updates with many columns and small batches.</li><li>The value `column` means partial updates in column mode, which is more suitable for batch updates with few columns and many rows. In such scenarios, enabling the column mode offers faster update speeds. For example, in a table with 100 columns, if only 10 columns (10% of the total) are updated for all rows, the update speed of the column mode is 10 times faster.</li></ul> |
-| merge_condition  | No       | Specifies the name of the column you want to use as the condition to determine whether updates can take effect. The update from a source record to a destination record takes effect only when the source data record has a greater or equal value than the destination data record in the specified column. StarRocks supports conditional updates since v2.5. For more information, see [Change data through loading](../../../loading/Load_to_Primary_Key_tables.md). <br/>**NOTE**<br/>The column that you specify cannot be a primary key column. Additionally, only tables that use the Primary Key table support conditional updates. |
-
-## Column mapping
-
-### Configure column mapping for CSV data loading
-
-If the columns of the data file can be mapped one on one in sequence to the columns of the StarRocks table, you do not need to configure the column mapping between the data file and the StarRocks table.
-
-If the columns of the data file cannot be mapped one on one in sequence to the columns of the StarRocks table, you need to use the `columns` parameter to configure the column mapping between the data file and the StarRocks table. This includes the following two use cases:
-
-- **Same number of columns but different column sequence.** **Also, the data from the data file does not need to be computed by functions before it is loaded into the matching StarRocks table columns.**
-
-  In the `columns` parameter, you need to specify the names of the StarRocks table columns in the same sequence as how the data file columns are arranged.
-
-  For example, the StarRocks table consists of three columns, which are `col1`, `col2`, and `col3` in sequence, and the data file also consists of three columns, which can be mapped to the StarRocks table columns `col3`, `col2`, and `col1` in sequence. In this case, you need to specify `"columns: col3, col2, col1"`.
-
-- **Different number of columns and different column sequence. Also, the data from the data file needs to be computed by functions before it is loaded into the matching StarRocks table columns.**
-
-  In the `columns` parameter, you need to specify the names of the StarRocks table columns in the same sequence as how the data file columns are arranged and specify the functions you want to use to compute the data. Two examples are as follows:
-
-  - The StarRocks table consists of three columns, which are `col1`, `col2`, and `col3` in sequence. The data file consists of four columns, among which the first three columns can be mapped in sequence to the StarRocks table columns `col1`, `col2`, and `col3` and the fourth column cannot be mapped to any of the StarRocks table columns. In this case, you need to temporarily specify a name for the fourth column of the data file, and the temporary name must be different from any of the StarRocks table column names. For example, you can specify `"columns: col1, col2, col3, temp"`, in which the fourth column of the data file is temporarily named `temp`.
-  - The StarRocks table consists of three columns, which are `year`, `month`, and `day` in sequence. The data file consists of only one column that accommodates date and time values in `yyyy-mm-dd hh:mm:ss` format. In this case, you can specify `"columns: col, year = year(col), month=month(col), day=day(col)"`, in which `col` is the temporary name of the data file column and the functions `year = year(col)`, `month=month(col)`, and `day=day(col)` are used to extract data from the data file column `col` and loads the data into the mapping StarRocks table columns. For example, `year = year(col)` is used to extract the `yyyy` data from the data file column `col` and loads the data into the StarRocks table column `year`.
-
-For detailed examples, see [Configure column mapping](#configure-column-mapping).
-
-### Configure column mapping for JSON data loading
-
-If the keys of the JSON document have the same names as the columns of the StarRocks table, you can load the JSON-formatted data by using the simple mode. In simple mode, you do not need to specify the `jsonpaths` parameter. This mode requires that the JSON-formatted data must be an object as indicated by curly brackets `{}`, such as `{"category": 1, "author": 2, "price": "3"}`. In this example, `category`, `author`, and `price` are key names, and these keys can be mapped one on one by name to the columns `category`, `author`, and `price` of the StarRocks table.
-
-If the keys of the JSON document have different names than the columns of the StarRocks table, you can load the JSON-formatted data by using the matched mode. In matched mode, you need to use the `jsonpaths` and `COLUMNS` parameters to specify the column mapping between the JSON document and the StarRocks table:
-
-- In the `jsonpaths` parameter, specify the JSON keys in the sequence as how they are arranged in the JSON document.
-- In the `COLUMNS` parameter, specify the mapping between the JSON keys and the StarRocks table columns:
-  - The column names specified in the `COLUMNS` parameter are mapped one on one in sequence to the JSON keys.
-  - The column names specified in the `COLUMNS` parameter are mapped one on one by name to the StarRocks table columns.
-
-For examples about loading JSON-formatted data by using the matched mode, see [Load JSON data using matched mode](#load-json-data-using-matched-mode).
-
-## Return value
-
-After the load job finishes, StarRocks returns the job result in JSON format. Example:
-
-```JSON
-{
-    "TxnId": 1003,
-    "Label": "label123",
-    "Status": "Success",
-    "Message": "OK",
-    "NumberTotalRows": 1000000,
-    "NumberLoadedRows": 999999,
-    "NumberFilteredRows": 1,
-    "NumberUnselectedRows": 0,
-    "LoadBytes": 40888898,
-    "LoadTimeMs": 2144,
-    "BeginTxnTimeMs": 0,
-    "StreamLoadPlanTimeMs": 1,
-    "ReadDataTimeMs": 0,
-    "WriteDataTimeMs": 11,
-    "CommitAndPublishTimeMs": 16,
-}
-```
-
-The following table describes the parameters in the returned job result.
-
-| Parameter              | Description                                                  |
-| ---------------------- | ------------------------------------------------------------ |
-| TxnId                  | The transaction ID of the load job.                          |
-| Label                  | The label of the load job.                                   |
-| Status                 | The final status of the data loaded.<ul><li>`Success`: The data is successfully loaded and can be queried.</li><li>`Publish Timeout`: The load job is successfully submitted, but the data still cannot be queried. You do not need to retry to load the data.</li><li>`Label Already Exists`: The label of the load job has been used for another load job. The data may have been successfully loaded or is being loaded.</li><li>`Fail`: The data failed to be loaded. You can retry the load job.</li></ul> |
-| Message                | The status of the load job. If the load job fails, the detailed failure cause is returned. |
-| NumberTotalRows        | The total number of data records that are read.              |
-| NumberLoadedRows       | The total number of data records that are successfully loaded. This parameter is valid only when the value returned for `Status` is `Success`. |
-| NumberFilteredRows     | The number of data records that are filtered out due to inadequate data quality. |
-| NumberUnselectedRows   | The number of data records that are filtered out by the WHERE clause. |
-| LoadBytes              | The amount of data that is loaded. Unit: bytes.              |
-| LoadTimeMs             | The amount of time that is taken by the load job. Unit: ms.  |
-| BeginTxnTimeMs         | The amount of time that is taken to run a transaction for the load job. |
-| StreamLoadPlanTimeMs   | The amount of time that is taken to generate a execution plan for the load job. |
-| ReadDataTimeMs         | The amount of time that is taken to read data for the load job. |
-| WriteDataTimeMs        | The amount of time that is taken to write data for the load job. |
-| CommitAndPublishTimeMs | The amount of time that is taken to commit and publish data for the load job. |
-
-If the load job fails, StarRocks also returns `ErrorURL`. Example:
-
-```JSON
-{"ErrorURL": "http://172.26.195.68:8045/api/_load_error_log?file=error_log_3a4eb8421f0878a6_9a54df29fd9206be"}
-```
-
-`ErrorURL` provides a URL from which you can obtain details about unqualified data records that have been filtered out. You can specify the maximum number of unqualified data rows that can be logged by using the optional parameter `log_rejected_record_num`, which is set when you submit a load job.
-
-You can run `curl "url"` to directly view details about the filtered-out, unqualified data records. You can also run `wget "url"` to export the details about these data records:
-
-```Bash
-wget http://172.26.195.68:8045/api/_load_error_log?file=error_log_3a4eb8421f0878a6_9a54df29fd9206be
-```
-
-The exported data record details are saved to a local file with a name similar to `_load_error_log?file=error_log_3a4eb8421f0878a6_9a54df29fd9206be`. You can use the `cat` command to view the file.
-
-Then, you can adjust the configuration of the load job, and submit the load job again.
-
-## Examples
-
-### Load CSV data
-
-This section CSV data as an example to describe how you can employ various parameter settings and combinations to meet your diverse loading requirements.
-
-#### Set timeout period
-
-Your StarRocks database `test_db` contains a table named `table1`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example1.csv` also consists of three columns, which can be mapped in sequence onto `col1`, `col2`, and `col3` of `table1`.
-
-If you want to load all data from `example1.csv` into `table1` within up to 100 seconds, run the following command:
-
-```Bash
-curl --location-trusted -u <username>:<password> -H "label:label1" \
-    -H "Expect:100-continue" \
-    -H "timeout:100" \
-    -H "max_filter_ratio:0.2" \
-    -T example1.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table1/_stream_load
-```
-
-#### Set error tolerance
-
-Your StarRocks database `test_db` contains a table named `table2`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example2.csv` also consists of three columns, which can be mapped in sequence onto `col1`, `col2`, and `col3` of `table2`.
-
-If you want to load all data from `example2.csv` into `table2` with a maximum error tolerance of `0.2`, run the following command:
-
-```Bash
-curl --location-trusted -u <username>:<password> -H "label:label2" \
-    -H "Expect:100-continue" \
-    -H "max_filter_ratio:0.2" \
-    -T example2.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table2/_stream_load
-```
-
-#### Configure column mapping
-
-Your StarRocks database `test_db` contains a table named `table3`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example3.csv` also consists of three columns, which can be mapped in sequence onto `col2`, `col1`, and `col3` of `table3`.
-
-If you want to load all data from `example3.csv` into `table3`, run the following command:
-
-```Bash
-curl --location-trusted -u <username>:<password>  -H "label:label3" \
-    -H "Expect:100-continue" \
-    -H "columns: col2, col1, col3" \
-    -T example3.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table3/_stream_load
-```
-
-> **NOTE**
->
-> In the preceding example, the columns of `example3.csv` cannot be mapped onto the columns of `table3` in the same sequence as how these columns are arranged in `table3`. Therefore, you need to use the `columns` parameter to configure the column mapping between `example3.csv` and `table3`.
-
-#### Set filter conditions
-
-Your StarRocks database `test_db` contains a table named `table4`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example4.csv` also consists of three columns, which can be mapped in sequence onto `col1`, `col2`, and `col3` of `table4`.
-
-If you want to load only the data records whose values in the first column of `example4.csv` are equal to `20180601` into `table4`, run the following command:
-
-```Bash
-curl --location-trusted -u <username>:<password> -H "label:label4" \
-    -H "Expect:100-continue" \
-    -H "columns: col1, col2, col3]"\
-    -H "where: col1 = 20180601" \
-    -T example4.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table4/_stream_load
-```
-
-> **NOTE**
->
-> In the preceding example, `example4.csv` and `table4` have the same number of columns that can be mapped in sequence, but you need to use the WHERE clause to specify column-based filter conditions. Therefore, you need to use the `columns` parameter to define temporary names for the columns of `example4.csv`.
-
-#### Set destination partitions
-
-Your StarRocks database `test_db` contains a table named `table5`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example5.csv` also consists of three columns, which can be mapped in sequence onto `col1`, `col2`, and `col3` of `table5`.
-
-If you want to load all data from `example5.csv` into partitions `p1` and `p2` of `table5`, run the following command:
-
-```Bash
-curl --location-trusted -u <username>:<password>  -H "label:label5" \
-    -H "Expect:100-continue" \
-    -H "partitions: p1, p2" \
-    -T example5.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table5/_stream_load
-```
-
-#### Set strict mode and time zone
-
-Your StarRocks database `test_db` contains a table named `table6`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example6.csv` also consists of three columns, which can be mapped in sequence onto `col1`, `col2`, and `col3` of `table6`.
-
-If you want to load all data from `example6.csv` into `table6` by using the strict mode and the time zone `Africa/Abidjan`, run the following command:
-
-```Bash
-curl --location-trusted -u <username>:<password> \
-    -H "Expect:100-continue" \
-    -H "strict_mode: true" \
-    -H "timezone: Africa/Abidjan" \
-    -T example6.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table6/_stream_load
-```
-
-#### Load data into tables containing HLL-type columns
-
-Your StarRocks database `test_db` contains a table named `table7`. The table consists of two HLL-type columns, which are `col1` and `col2` in sequence.
-
-Your data file `example7.csv` also consists of two columns, among which the first column can be mapped onto `col1` of `table7` and the second column cannot be mapped onto any column of `table7`. The values in the first column of `example7.csv` can be converted into HLL-type data by using functions before they are loaded into `col1` of `table7`.
-
-If you want to load data from `example7.csv` into `table7`, run the following command:
-
-```Bash
-curl --location-trusted -u <username>:<password> \
-    -H "Expect:100-continue" \
-    -H "columns: temp1, temp2, col1=hll_hash(temp1), col2=hll_empty()" \
-    -T example7.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table7/_stream_load
-```
-
-> **NOTE**
->
-> In the preceding example, the two columns of `example7.csv` are named `temp1` and `temp2` in sequence by using the `columns` parameter. Then, functions are used to convert data as follows:
->
-> - The `hll_hash` function is used to convert the values in `temp1` of `example7.csv` into HLL-type data and map `temp1` of `example7.csv` onto `col1` of `table7`.
->
-> - The `hll_empty` function is used to fill the specified default value into `col2` of `table7`.
-
-For usage of the functions `hll_hash` and `hll_empty`, see [hll_hash](../../sql-functions/scalar-functions/hll_hash.md) and [hll_empty](../../sql-functions/scalar-functions/hll_empty.md).
-
-#### Load data into tables containing BITMAP-type columns
-
-Your StarRocks database `test_db` contains a table named `table8`. The table consists of two BITMAP-type columns, which are `col1` and `col2`, in sequence.
-
-Your data file `example8.csv` also consists of two columns, among which the first column can be mapped onto `col1` of `table8` and the second column cannot be mapped onto any column of `table8`. The values in the first column of `example8.csv` can be converted by using functions before they are loaded into `col1` of `table8`.
-
-If you want to load data from `example8.csv` into `table8`, run the following command:
-
-```Bash
-curl --location-trusted -u <username>:<password> \
-    -H "Expect:100-continue" \
-    -H "columns: temp1, temp2, col1=to_bitmap(temp1), col2=bitmap_empty()" \
-    -T example8.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table8/_stream_load
-```
-
-> **NOTE**
->
-> In the preceding example, the two columns of `example8.csv` are named `temp1` and `temp2` in sequence by using the `columns` parameter. Then, functions are used to convert data as follows:
->
-> - The `to_bitmap` function is used to convert the values in `temp1` of `example8.csv` into BITMAP-type data and map `temp1` of `example8.csv` onto `col1` of `table8`.
->
-> - The `bitmap_empty` function is used to fill the specified default value into `col2` of `table8`.
-
-For usage of the functions `to_bitmap` and `bitmap_empty`, see [to_bitmap](../../../sql-reference/sql-functions/bitmap-functions/to_bitmap.md) and [bitmap_empty](../../../sql-reference/sql-functions/bitmap-functions/bitmap_empty.md).
-
-#### Setting `skip_header`, `trim_space`, `enclose`, and `escape`
-
-Your StarRocks database `test_db` contains a table named `table9`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
-
-Your data file `example9.csv` also consists of three columns, which are mapped in sequence onto `col2`, `col1`, and `col3` of `table13`.
-
-If you want to load all data from `example9.csv` into `table9`, with the intention of skipping the first five rows of `example9.csv`, removing the spaces preceding and following column separators, and setting `enclose` to `\` and `escape` to `\`, run the following command:
-
-```Bash
-curl --location-trusted -u <username>:<password> -H "label:3875" \
-    -H "Expect:100-continue" \
-    -H "trim_space: true" -H "skip_header: 5" \
-    -H "column_separator:," -H "enclose:\"" -H "escape:\\" \
-    -H "columns: col2, col1, col3" \
-    -T example9.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/tbl9/_stream_load
-```
-
-### Load JSON data
-
-This section describes the parameter settings that you need to take note of when you load JSON data.
-
-Your StarRocks database `test_db` contains a table named `tbl1`, whose schema is as follows:
-
-```SQL
-`category` varchar(512) NULL COMMENT "",`author` varchar(512) NULL COMMENT "",`title` varchar(512) NULL COMMENT "",`price` double NULL COMMENT ""
-```
-
-#### Load JSON data using simple mode
-
-Suppose that your data file `example1.json` consists of the following data:
-
-```JSON
-{"category":"C++","author":"avc","title":"C++ primer","price":895}
-```
-
-To load all data from `example1.json` into `tbl1`, run the following command:
-
-```Bash
-curl --location-trusted -u <username>:<password> -H "label:label6" \
-    -H "Expect:100-continue" \
-    -H "format: json" \
-    -T example1.json -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/tbl1/_stream_load
-```
-
-> **NOTE**
->
-> In the preceding example, the parameters `columns` and `jsonpaths` are not specified. Therefore, the keys in `example1.json` are mapped by name onto the columns of `tbl1`.
-
-To increase throughput, Stream Load supports loading multiple data records all at once. Example:
-
-```JSON
-[{"category":"C++","author":"avc","title":"C++ primer","price":89.5},{"category":"Java","author":"avc","title":"Effective Java","price":95},{"category":"Linux","author":"avc","title":"Linux kernel","price":195}]
-```
-
-#### Load JSON data using matched mode
-
-StarRocks performs the following steps to match and process JSON data:
-
-1. (Optional) Strips the outermost array structure as instructed by the `strip_outer_array` parameter setting.
-
-   > **NOTE**
-   >
-   > This step is performed only when the outermost layer of the JSON data is an array structure as indicated by a pair of square brackets `[]`. You need to set `strip_outer_array` to `true`.
-
-2. (Optional) Matches the root element of the JSON data as instructed by the `json_root` parameter setting.
-
-   > **NOTE**
-   >
-   > This step is performed only when the JSON data has a root element. You need to specify the root element by using the `json_root` parameter.
-
-3. Extracts the specified JSON data as instructed by the `jsonpaths` parameter setting.
-
-##### Load JSON data using matched mode without root element specified
-
-Suppose that your data file `example2.json` consists of the following data:
-
-```JSON
-[{"category":"xuxb111","author":"1avc","title":"SayingsoftheCentury","price":895},{"category":"xuxb222","author":"2avc","title":"SayingsoftheCentury","price":895},{"category":"xuxb333","author":"3avc","title":"SayingsoftheCentury","price":895}]
-```
-
-To load only `category`, `author`, and `price` from `example2.json`, run the following command:
-
-```Bash
-curl --location-trusted -u <username>:<password> -H "label:label7" \
-    -H "Expect:100-continue" \
-    -H "format: json" \
-    -H "strip_outer_array: true" \
-    -H "jsonpaths: [\"$.category\",\"$.price\",\"$.author\"]" \
-    -H "columns: category, price, author" \
-    -T example2.json -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/tbl1/_stream_load
-```
-
-> **NOTE**
->
-> In the preceding example, the outermost layer of the JSON data is an array structure as indicated by a pair of square brackets `[]`. The array structure consists of multiple JSON objects that each represent a data record. Therefore, you need to set `strip_outer_array` to `true` to strip the outermost array structure. The key **title** that you do not want to load is ignored during loading.
-
-##### Load JSON data using matched mode with root element specified
-
-Suppose your data file `example3.json` consists of the following data:
-
-```JSON
-{"id": 10001,"RECORDS":[{"category":"11","title":"SayingsoftheCentury","price":895,"timestamp":1589191587},{"category":"22","author":"2avc","price":895,"timestamp":1589191487},{"category":"33","author":"3avc","title":"SayingsoftheCentury","timestamp":1589191387}],"comments": ["3 records", "there will be 3 rows"]}
-```
-
-To load only `category`, `author`, and `price` from `example3.json`, run the following command:
-
-```Bash
-curl --location-trusted -u <username>:<password> \
-    -H "Expect:100-continue" \
-    -H "format: json" \
-    -H "json_root: $.RECORDS" \
-    -H "strip_outer_array: true" \
-    -H "jsonpaths: [\"$.category\",\"$.price\",\"$.author\"]" \
-    -H "columns: category, price, author" -H "label:label8" \
-    -T example3.json -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/tbl1/_stream_load
-```
-
-> **NOTE**
->
-> In the preceding example, the outermost layer of the JSON data is an array structure as indicated by a pair of square brackets `[]`. The array structure consists of multiple JSON objects that each represent a data record. Therefore, you need to set `strip_outer_array` to `true` to strip the outermost array structure. The keys `title` and `timestamp` that you do not want to load are ignored during loading. Additionally, the `json_root` parameter is used to specify the root element, which is an array, of the JSON data.
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SUBMIT_TASK.md b/docs/en/sql-reference/sql-statements/data-manipulation/SUBMIT_TASK.md
deleted file mode 100644
index d788b568fe56f7..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SUBMIT_TASK.md
+++ /dev/null
@@ -1,119 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SUBMIT TASK
-
-## Description
-
-Submits an ETL statement as an asynchronous task.
-
-You can use this statement to:
-
-- execute long-running tasks in the background (supported from v2.5 onwards)
-- schedule a task at a regular interval (supported from v3.3 onwards)
-
-Supported statements include:
-
-- [CREATE TABLE AS SELECT](../data-definition/CREATE_TABLE_AS_SELECT.md) (from v3.0 onwards)
-- [INSERT](./INSERT.md) (from v3.0 onwards)
-- [CACHE SELECT](../../../data_source/data_cache_warmup.md) (from v3.3 onwards)
-
-You can view the list of tasks by querying `INFORMATION_SCHEMA.tasks`, or view the execution history of tasks by querying `INFORMATION_SCHEMA.task_runs`. For more information, see [Usage Notes](#usage-notes).
-
-You can drop an asynchronous task using [DROP TASK](./DROP_TASK.md).
-
-## Syntax
-
-```SQL
-SUBMIT TASK <task_name> 
-[SCHEDULE [START(<schedule_start>)] EVERY(INTERVAL <schedule_interval>) ]
-[PROPERTIES(<"key" = "value"[, ...]>)]
-AS <etl_statement>
-```
-
-## Parameters
-
-| **Parameter**      | **Required** | **Description**                                                                                     |
-| -------------      | ------------ | ---------------------------------------------------------------------------------------------------- |
-| task_name          | Yes     | The name of the task.                                                                               |
-| schedule_start     | No      | The start time for the scheduled task.                                                                 |
-| schedule_interval  | No      | The interval at which the scheduled task is executed, with a minimum interval of 10 seconds.          |
-| etl_statement      | Yes     | The ETL statement that you want to submit as an asynchronous task. StarRocks currently supports submitting asynchronous tasks for [CREATE TABLE AS SELECT](../data-definition/CREATE_TABLE_AS_SELECT.md) and [INSERT](./INSERT.md). |
-
-## Usage notes
-
-This statement creates a Task, which is a template for storing a task that executes the ETL statement. You can check the information of the Task by querying the metadata view [`tasks` in Information Schema](../../../reference/information_schema/tasks.md).
-
-```SQL
-SELECT * FROM INFORMATION_SCHEMA.tasks;
-SELECT * FROM information_schema.tasks WHERE task_name = '<task_name>';
-```
-
-After you run the Task, a TaskRun is generated accordingly. A TaskRun indicates a task that executes the ETL statement. A TaskRun has the following states:
-
-- `PENDING`: The task waits to be run.
-- `RUNNING`: The task is running.
-- `FAILED`: The task failed.
-- `SUCCESS`: The task runs successfully.
-
-You can check the state of a TaskRun by querying the metadata view [`task_runs` in Information Schema](../../../reference/information_schema/task_runs.md).
-
-```SQL
-SELECT * FROM INFORMATION_SCHEMA.task_runs;
-SELECT * FROM information_schema.task_runs WHERE task_name = '<task_name>';
-```
-
-## Configure via FE configuration items
-
-You can configure asynchronous ETL tasks using the following FE configuration items:
-
-| **Parameter**                | **Default value** | **Description**                                              |
-| ---------------------------- | ----------------- | ------------------------------------------------------------ |
-| task_ttl_second              | 86400             | The period during which a Task is valid. Unit: seconds. Tasks that exceed the validity period are deleted. |
-| task_check_interval_second   | 3600              | The time interval to delete invalid Tasks. Unit: seconds.    |
-| task_runs_ttl_second         | 86400             | The period during which a TaskRun is valid. Unit: seconds. TaskRuns that exceed the validity period are deleted automatically. Additionally, TaskRuns in the `FAILED` and `SUCCESS` states are also deleted automatically. |
-| task_runs_concurrency        | 4                 | The maximum number of TaskRuns that can be run in parallel.  |
-| task_runs_queue_length       | 500               | The maximum number of TaskRuns that are pending for running. If the number exceeds the default value, the incoming tasks will be suspended. |
-| task_runs_max_history_number | 10000             | The maximum number of TaskRun records to retain. |
-| task_min_schedule_interval_s | 10                | The minimum interval for Task execution. Unit: seconds. |
-
-## Examples
-
-Example 1: Submit an asynchronous task for `CREATE TABLE tbl1 AS SELECT * FROM src_tbl`, and specify the task name as `etl0`:
-
-```SQL
-SUBMIT TASK etl0 AS CREATE TABLE tbl1 AS SELECT * FROM src_tbl;
-```
-
-Example 2: Submit an asynchronous task for `INSERT INTO tbl2 SELECT * FROM src_tbl`, and specify the task name as `etl1`:
-
-```SQL
-SUBMIT TASK etl1 AS INSERT INTO tbl2 SELECT * FROM src_tbl;
-```
-
-Example 3: Submit an asynchronous task for `INSERT OVERWRITE tbl3 SELECT * FROM src_tbl`:
-
-```SQL
-SUBMIT TASK AS INSERT OVERWRITE tbl3 SELECT * FROM src_tbl;
-```
-
-Example 4: Submit an asynchronous task for `INSERT OVERWRITE insert_wiki_edit SELECT * FROM source_wiki_edit` without specifying the task name, and extend the query timeout to `100000` seconds using the hint:
-
-```SQL
-SUBMIT /*+set_var(query_timeout=100000)*/ TASK AS
-INSERT OVERWRITE insert_wiki_edit
-SELECT * FROM source_wiki_edit;
-```
-
-Example 5: Create an asynchronous task for an INSERT OVERWRITE statement. The task will be regularly executed at an interval of 1 minute.
-
-```SQL
-SUBMIT TASK
-SCHEDULE EVERY(INTERVAL 1 MINUTE)
-AS
-INSERT OVERWRITE insert_wiki_edit
-    SELECT dt, user_id, count(*) 
-    FROM source_wiki_edit 
-    GROUP BY dt, user_id;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/SUSPEND_or_RESUME_PIPE.md b/docs/en/sql-reference/sql-statements/data-manipulation/SUSPEND_or_RESUME_PIPE.md
deleted file mode 100644
index 6fa7e889ead8d7..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/SUSPEND_or_RESUME_PIPE.md
+++ /dev/null
@@ -1,58 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SUSPEND or RESUME PIPE
-
-## Description
-
-Suspends or resumes a pipe:
-
-- When a load job is in progress (namely, in the `RUNNING` state), suspending (`SUSPEND`) the pipe for the job interrupts the job.
-- When a load job encounters errors, resuming (`RESUME`) the pipe for the job will continue to run the erroneous job.
-
-This command is supported from v3.2 onwards.
-
-## Syntax
-
-```SQL
-ALTER PIPE [ IF EXISTS ] <pipe_name> { SUSPEND | RESUME [ IF SUSPENDED ] }
-```
-
-## Parameters
-
-### pipe_name
-
-The name of the pipe.
-
-## Examples
-
-### Suspend a pipe
-
-Suspend the pipe named `user_behavior_replica` (which is in the `RUNNING` state) in the database named `mydatabase`:
-
-```SQL
-USE mydatabase;
-ALTER PIPE user_behavior_replica SUSPEND;
-```
-
-If you use [SHOW PIPES](../../../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md) to query the pipe, you can see that its state has changed to `SUSPEND`.
-
-### Resume a pipe
-
-Resume the pipe named `user_behavior_replica` in the database named `mydatabase`:
-
-```SQL
-USE mydatabase;
-ALTER PIPE user_behavior_replica RESUME;
-```
-
-If you use [SHOW PIPES](../../../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md) to query the pipe, you can see that its state has changed to `RUNNING`.
-
-## References
-
-- [CREATE PIPE](../data-manipulation/CREATE_PIPE.md)
-- [ALTER PIPE](../data-manipulation/ALTER_PIPE.md)
-- [DROP PIPE](../data-manipulation/DROP_PIPE.md)
-- [SHOW PIPES](../data-manipulation/SHOW_PIPES.md)
-- [RETRY FILE](../data-manipulation/RETRY_FILE.md)
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/UPDATE.md b/docs/en/sql-reference/sql-statements/data-manipulation/UPDATE.md
deleted file mode 100644
index fd2fd4044f6a0b..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/UPDATE.md
+++ /dev/null
@@ -1,176 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# UPDATE
-
-Updates rows in a Primary Key table.
-
-StarRocks supports the UPDATE statement since v2.3, which only supports single-table UPDATE and does not support common table expressions (CTEs). Starting from version 3.0, StarRocks enriches the syntax to support multi-table joins and CTEs. If you need to join the table to be updated with other tables in the database, you can reference these other tables in the FROM clause or CTE. Since version 3.1, the UPDATE statement supports the partial updates in column mode, which is suitable for scenarios involving a small number of columns but a large number of rows, resulting in faster update speeds.
-
-This command requires the UPDATE privilege on the table you want to update.
-
-## Usage notes
-
-When executing the UPDATE statement involving multiple tables, StarRocks converts the table expression in the FROM clause of the UPDATE statement into an equivalent JOIN query statement. Therefore, make sure that the table expression that you specify in the FROM clause of the UPDATE statement supports this conversion. For example, the UPDATE statement is 'UPDATE t0 SET v1=t1.v1 FROM t1 WHERE t0.pk = t1.pk;'. The table expression in the FROM clause can be converted to 't0 JOIN t1 ON t0.pk=t1.pk;'. StarRocks matches the data rows to be updated based on the result set of the JOIN query. It is possible that multiple rows in the result set match a certain row in the table to be updated. In this scenario, that row is updated based on the value of a random row among these multiple rows.
-
-## Syntax
-
-### Single-table UPDATE
-
-If the data rows of the table to be updated meet the WHERE condition, the specified columns of these data rows are assigned new values.
-
-```SQL
-[ WITH <with_query> [, ...] ]
-UPDATE <table_name>
-    SET <column_name> = <expression> [, ...]
-    WHERE <where_condition>
-```
-
-### Multi-table UPDATE
-
-The result set from the multi-table join is matched against the table to be updated. If the data rows of the table to be updated match the result set and meet the WHERE condition, the specified columns of these data rows are assigned new values.
-
-```SQL
-[ WITH <with_query> [, ...] ]
-UPDATE <table_name>
-    SET <column_name> = <expression> [, ...]
-    [ FROM <from_item> [, ...] ]
-    WHERE <where_condition>
-```
-
-## Parameters
-
-`with_query`
-
-One or more CTEs that can be referenced by name in an UPDATE statement. CTEs are temporary result sets that can improve the readability of complex statements.
-
-`table_name`
-
-The name of the table to be updated.
-
-`column_name`
-
-The name of the column to be updated. It cannot include the table name. For example, 'UPDATE t1 SET col = 1' is not valid.
-
-`expression`
-
-The expression that assigns new values to the column.
-
-`from_item`
-
-One or more other tables in the database. These tables can be joined with the table to be updated based on the condition specified in the WHERE clause. The values of the rows in the result set are used to update the values for the specified columns in the matched rows in the table to be updated. For example, if the FROM clause is `FROM t1 WHERE t0.pk = t1.pk`, StarRocks converts the table expression in the FROM clause to `t0 JOIN t1 ON t0.pk=t1.pk` when executing the UPDATE statement.
-
-`where_condition`
-
-The condition based on which you want to update rows. Only rows that meet the WHERE condition can be updated. This parameter is required, because it helps prevent you from accidentally updating the entire table. If you want to update the entire table, you can use 'WHERE true'. However, this parameter is not required for [partial updates in column mode](#partial-updates-in-column-mode-since-v31).
-
-## Partial updates in column mode (since v3.1)
-
-Partial updates in column mode are suitable for scenarios where only a small number of columns, but a large number of rows need to be updated. In such scenarios, enabling the column mode offers faster update speeds. For example, in a table with 100 columns, if only 10 columns (10% of the total) are updated for all rows, the update speed of the column mode is 10 times faster.
-
-The system variable `partial_update_mode` controls the mode of partial updates and supports the following values:
-
-- `auto` (default): The system automatically determines the mode of partial updates by analyzing the UPDATE statement and the columns involved. If the following criteria are met, the system automatically uses the column mode:
-  - The percentage of updated columns compared to the total number of columns is less than 30%, and the number of updated columns is fewer than 4.
-  - The update statement does not use a WHERE condition.
-
-  Otherwise, the system does not use the column mode.
-- `column`: The column mode is used for the partial updates, which is particularly suitable for the partial updates which involve a small number of columns and a large number of rows.
-
-You can use `EXPLAIN UPDATE xxx` to view the mode of partial updates.
-
-## Examples
-
-### Single-table UPDATE
-
-Create a table `Employees` to record employee information and insert five data rows into the table.
-
-```SQL
-CREATE TABLE Employees (
-    EmployeeID INT,
-    Name VARCHAR(50),
-    Salary DECIMAL(10, 2)
-)
-PRIMARY KEY (EmployeeID) 
-DISTRIBUTED BY HASH (EmployeeID)
-PROPERTIES ("replication_num" = "3");
-
-INSERT INTO Employees VALUES
-    (1, 'John Doe', 5000),
-    (2, 'Jane Smith', 6000),
-    (3, 'Robert Johnson', 5500),
-    (4, 'Emily Williams', 4500),
-    (5, 'Michael Brown', 7000);
-```
-
-If you need to give a 10% raise to all employees, you can execute the following statement:
-
-```SQL
-UPDATE Employees
-SET Salary = Salary * 1.1  -- Increase the salary by 10%.
-WHERE true;
-```
-
-If you need to give a 10% raise to employees with salaries lower than the average salary, you can execute the following statement:
-
-```SQL
-UPDATE Employees
-SET Salary = Salary * 1.1   -- Increase the salary by 10%.
-WHERE Salary < (SELECT AVG(Salary) FROM Employees);
-```
-
-You can also use a CTE to rewrite the above statement to improve readability.
-
-```SQL
-WITH AvgSalary AS (
-    SELECT AVG(Salary) AS AverageSalary
-    FROM Employees
-)
-UPDATE Employees
-SET Salary = Salary * 1.1   -- Increase the salary by 10%.
-FROM AvgSalary
-WHERE Employees.Salary < AvgSalary.AverageSalary;
-```
-
-### Multi-table UPDATE
-
-Create a table `Accounts` to record account information and insert three data rows into the table.
-
-```SQL
-CREATE TABLE Accounts (
-    Accounts_id BIGINT NOT NULL,
-    Name VARCHAR(26) NOT NULL,
-    Sales_person VARCHAR(50) NOT NULL
-) 
-PRIMARY KEY (Accounts_id)
-DISTRIBUTED BY HASH (Accounts_id)
-PROPERTIES ("replication_num" = "3");
-
-INSERT INTO Accounts VALUES
-    (1,'Acme Corporation','John Doe'),
-    (2,'Acme Corporation','Robert Johnson'),
-    (3,'Acme Corporation','Lily Swift');
-```
-
-If you need to give a 10% raise to employees in the table `Employees` who manage accounts for Acme Corporation, you can execute the following statement:
-
-```SQL
-UPDATE Employees
-SET Salary = Salary * 1.1  -- Increase the salary by 10%.
-FROM Accounts
-WHERE Accounts.name = 'Acme Corporation'
-    AND Employees.Name = Accounts.Sales_person;
-```
-
-You can also use a CTE to rewrite the above statement to improve readability.
-
-```SQL
-WITH Acme_Accounts as (
-    SELECT * from Accounts
-    WHERE Accounts.name = 'Acme Corporation'
-)
-UPDATE Employees SET Salary = Salary * 1.1 -- Increase the salary by 10%.
-FROM Acme_Accounts
-WHERE Employees.Name = Acme_Accounts.Sales_person;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_BACKUP.md b/docs/en/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_BACKUP.md
deleted file mode 100644
index 8487de23814e27..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_BACKUP.md
+++ /dev/null
@@ -1,52 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW BACKUP
-
-## Description
-
-Views the last BACKUP task in a specified database.
-
-> **NOTE**
->
-> Only the information of the last BACKUP task is saved in StarRocks.
-
-## Syntax
-
-```SQL
-SHOW BACKUP [FROM <db_name>]
-```
-
-## Parameters
-
-| **Parameter** | **Description**                                       |
-| ------------- | ----------------------------------------------------- |
-| db_name       | Name of the database that the BACKUP task belongs to. |
-
-## Return
-
-| **Return**           | **Description**                                              |
-| -------------------- | ------------------------------------------------------------ |
-| JobId                | Unique job ID.                                               |
-| SnapshotName         | Name of the data snapshot.                                   |
-| DbName               | Name of the database that the BACKUP task belongs to.        |
-| State                | Current state of the BACKUP task:<ul><li>PENDING: Initial state after submitting a job.</li><li>SNAPSHOTING: Creating snapshot.</li><li>UPLOAD_SNAPSHOT: Snapshot complete, ready for upload.</li><li>UPLOADING: Uploading snapshot.</li><li>SAVE_META: Creating local metadata files.</li><li>UPLOAD_INFO: Uploading metadata files and information of the BACKUP task.</li><li>FINISHED: BACKUP task finished.</li><li>CANCELLED: BACKUP task failed or cancelled.</li></ul> |
-| BackupObjs           | Backed up objects.                                           |
-| CreateTime           | Task submission time.                                        |
-| SnapshotFinishedTime | Snapshot completion time.                                    |
-| UploadFinishedTime   | Snapshot upload completion time.                             |
-| FinishedTime         | Task completion Time.                                        |
-| UnfinishedTasks      | Unfinished subtask IDs in the SNAPSHOTING and UPLOADING phases. |
-| Progress             | The progress of snapshot uploading tasks.                             |
-| TaskErrMsg           | Error messages.                                              |
-| Status               | Status information.                                          |
-| Timeout              | Task timeout. Unit: second.                                  |
-
-## Examples
-
-Example 1: Views the last BACKUP task in the database `example_db`.
-
-```SQL
-SHOW BACKUP FROM example_db;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_REPOSITORIES.md b/docs/en/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_REPOSITORIES.md
deleted file mode 100644
index 50034295c2cf1b..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_REPOSITORIES.md
+++ /dev/null
@@ -1,35 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW REPOSITORIES
-
-## Description
-
-Views the repositories created in StarRocks.
-
-## Syntax
-
-```SQL
-SHOW REPOSITORIES
-```
-
-## Return
-
-| **Return** | **Description**                                          |
-| ---------- | -------------------------------------------------------- |
-| RepoId     | Repository ID.                                           |
-| RepoName   | Repository name.                                         |
-| CreateTime | Repository creation time.                                |
-| IsReadOnly | If the repository is read-only.                          |
-| Location   | Location of the repository in the remote storage system. |
-| Broker     | Broker used to create the repository.                    |
-| ErrMsg     | Error message during connection to the repository.       |
-
-## Examples
-
-Example 1: Views the repositories created in StarRocks.
-
-```SQL
-SHOW REPOSITORIES;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_RESTORE.md b/docs/en/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_RESTORE.md
deleted file mode 100644
index e2882729b76dd1..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_RESTORE.md
+++ /dev/null
@@ -1,56 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW RESTORE
-
-## Description
-
-Views the last RESTORE task in a specified database.
-
-> **NOTE**
->
-> Only the information of the last RESTORE task is saved in StarRocks.
-
-## Syntax
-
-```SQL
-SHOW RESTORE [FROM <db_name>]
-```
-
-## Parameters
-
-| **Parameter** | **Description**                                        |
-| ------------- | ------------------------------------------------------ |
-| db_name       | Name of the database that the RESTORE task belongs to. |
-
-## Return
-
-| **Return**           | **Description**                                              |
-| -------------------- | ------------------------------------------------------------ |
-| JobId                | Unique job ID.                                               |
-| Label                | Name of the data snapshot.                                   |
-| Timestamp            | Backup timestamp.                                            |
-| DbName               | Name of the database that the RESTORE task belongs to.       |
-| State                | Current state of the RESTORE task:<ul><li>PENDING: Initial state after submitting a job.</li><li>SNAPSHOTING: Executing the local snapshot.</li><li>DOWNLOAD: Submitting snapshot download task.</li><li>DOWNLOADING: Downloading the snapshot.</li><li>COMMIT: To commit the downloaded snapshot.</li><li>COMMITTING: Committing the downloaded snapshot.</li><li>FINISHED: RESTORE task finished.</li><li>CANCELLED: RESTORE task failed or cancelled.</li></ul> |
-| AllowLoad            | If loading data is allowed during the RESTORE task.          |
-| ReplicationNum       | Number of replicas to be restored.                           |
-| RestoreObjs          | The restored objects (tables and partitions).                |
-| CreateTime           | Task submission time.                                        |
-| MetaPreparedTime     | Local metadata completion time.                              |
-| SnapshotFinishedTime | Snapshot completion time.                                    |
-| DownloadFinishedTime | Snapshot download completion time.                           |
-| FinishedTime         | Task completion Time.                                        |
-| UnfinishedTasks      | Unfinished subtask IDs in the SNAPSHOTTING, DOWNLOADING, and COMMITTING phases. |
-| Progress             | The progress of snapshot downloading tasks.                  |
-| TaskErrMsg           | Error messages.                                              |
-| Status               | Status information.                                          |
-| Timeout              | Task timeout. Unit: second.                                  |
-
-## Examples
-
-Example 1: Views the last RESTORE task in the database `example_db`.
-
-```SQL
-SHOW RESTORE FROM example_db;
-```
diff --git a/docs/en/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_SNAPSHOT.md b/docs/en/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_SNAPSHOT.md
deleted file mode 100644
index bb03ae3c331346..00000000000000
--- a/docs/en/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_SNAPSHOT.md
+++ /dev/null
@@ -1,56 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# SHOW SNAPSHOT
-
-## Description
-
-Views data snapshots in a specified repository. For more information, see [data backup and restoration](../../../../administration/management/Backup_and_restore.md).
-
-## Syntax
-
-```SQL
-SHOW SNAPSHOT ON <repo_name>
-[WHERE SNAPSHOT = <snapshot_name> [AND TIMESTAMP = <backup_timestamp>]]
-```
-
-## Parameters
-
-| **Parameter**    | **Description**                                      |
-| ---------------- | ---------------------------------------------------- |
-| repo_name        | Name of the repository that the snapshot belongs to. |
-| snapshot_nam     | Name of the snapshot.                                |
-| backup_timestamp | Backup timestamp of the snapshot.                    |
-
-## Return
-
-| **Return** | **Description**                                              |
-| ---------- | ------------------------------------------------------------ |
-| Snapshot   | Name of the snapshot.                                        |
-| Timestamp  | Backup timestamp of the snapshot.                            |
-| Status     | Displays `OK` if the snapshot is okay. Displays error message if the snapshot is not okay. |
-| Database   | Name of the database that the snapshot belongs to.           |
-| Details    | JSON-formatted directory and structure of the snapshot.      |
-
-## Example
-
-Example 1: Views snapshots in repository `example_repo`.
-
-```SQL
-SHOW SNAPSHOT ON example_repo;
-```
-
-Example 2: Views the snapshot named `backup1` in repository `example_repo`.
-
-```SQL
-SHOW SNAPSHOT ON example_repo
-WHERE SNAPSHOT = "backup1";
-```
-
-Example 3: Views the snapshot named `backup1` with backup timestamp `2018-05-05-15-34-26` in repository `example_repo`.
-
-```SQL
-SHOW SNAPSHOT ON example_repo 
-WHERE SNAPSHOT = "backup1" AND TIMESTAMP = "2018-05-05-15-34-26";
-```
diff --git a/docs/en/sql-reference/sql-statements/general_DDL.md b/docs/en/sql-reference/sql-statements/general_DDL.md
deleted file mode 100644
index 8aed9fc557bf66..00000000000000
--- a/docs/en/sql-reference/sql-statements/general_DDL.md
+++ /dev/null
@@ -1,89 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# General DDL
-
-- [General DDL](#general-ddl)
-  - [CREATE](#create)
-  - [ALTER](#alter)
-  - [DROP](#drop)
-  - [REFRESH](#refresh)
-  - [TRUNCATE TABLE](#truncate-table)
-  - [BACKUP and RESTORE](#backup-and-restore)
-  - [SET](#set)
-  - [CANCEL](#cancel)
-  - [KILL](#kill)
-  - [Utility commands](#utility-commands)
-
-## CREATE
-
-- [ANALYZE TABLE](./data-definition/ANALYZE_TABLE.md)
-- [CREATE ANALYZE](./data-definition/CREATE_ANALYZE.md)
-- [CREATE DATABASE](./data-definition/CREATE_DATABASE.md)
-- [CREATE EXTERNAL CATALOG](./data-definition/CREATE_EXTERNAL_CATALOG.md)
-- [CREATE FUNCTION](./data-definition/CREATE_FUNCTION.md)
-- [CREATE IDEX](./data-definition/CREATE_INDEX.md)
-- [CREATE MATERIALIZED VIEW](./data-definition/CREATE_MATERIALIZED_VIEW.md)
-- [CREATE REPOSITORY](./data-definition/backup_restore/CREATE_REPOSITORY.md)
-- [CREATE RESOURCE](./data-definition/CREATE_RESOURCE.md)
-- [CREATE TABLE](./data-definition/CREATE_TABLE.md)
-- [CREATE TABLE AS SELECT](./data-definition/CREATE_TABLE_AS_SELECT.md)
-- [CREATE TABLE LIKE](./data-definition/CREATE_TABLE_LIKE.md)
-- [CREATE VIEW](./data-definition/CREATE_VIEW.md)
-
-## ALTER
-
-- [ALTER DATABASE](./data-definition/ALTER_DATABASE.md)
-- [ALTER MATERIALIZED VIEW](./data-definition/ALTER_MATERIALIZED_VIEW.md)
-- [ALTER RESOURCE](./data-definition/ALTER_RESOURCE.md)
-- [ALTER TABLE](./data-definition/ALTER_TABLE.md)
-- [ALTER VIEW](./data-definition/ALTER_VIEW.md)
-
-## DROP
-
-- [DROP ANALYZE](./data-definition/DROP_ANALYZE.md)
-- [DROP CATALOG](./data-definition/DROP_CATALOG.md)
-- [DROP DATABASE](./data-definition/DROP_DATABASE.md)
-- [DROP FUNCTION](./data-definition/DROP_FUNCTION.md)
-- [DROP MATERIALIZED VIEW](./data-definition/DROP_MATERIALIZED_VIEW.md)
-- [DROP REPOSITORY](./data-definition/backup_restore/DROP_REPOSITORY.md)
-- [DROP RESOURCE](./data-definition/DROP_RESOURCE.md)
-- [DROP STATS](./data-definition/DROP_STATS.md)
-- [DROP TABLE](./data-definition/DROP_TABLE.md)
-- [DROP VIEW](./data-definition/DROP_VIEW.md)
-
-## REFRESH
-
-- [REFRESH EXTERNAL TABLE](./data-definition/REFRESH_EXTERNAL_TABLE.md)
-- [REFRESH MATERIALIZED VIEW](./data-manipulation/REFRESH_MATERIALIZED_VIEW.md)
-
-## TRUNCATE TABLE
-
-- [TRUNCATE TABLE](./data-definition/TRUNCATE_TABLE.md)
-
-## BACKUP and RESTORE
-
-- [BACKUP](./data-definition/backup_restore/BACKUP.md)
-- [RECOVER](./data-definition/backup_restore/RECOVER.md)
-- [RESTORE](./data-definition/backup_restore/RESTORE.md)
-
-## SET
-
-- [SET CATALOG](./data-definition/SET_CATALOG.md)
-
-## CANCEL
-
-- [CANCEL ALTER TABLE](./data-definition/CANCEL_ALTER_TABLE.md)
-- [CANCEL BACKUP](./data-definition/backup_restore/CANCEL_BACKUP.md)
-- [CANCEL REFRESH MATERIALIZED VIEW](./data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW.md)
-- [CANCEL RESTORE](./data-definition/backup_restore/CANCEL_RESTORE.md)
-
-## KILL
-
-- [KILL ANALYZE](./data-definition/KILL_ANALYZE.md)
-
-## Utility commands
-
-- [USE](../sql-statements/data-definition/USE.md)
-- [DESC](../sql-statements/Utility/DESCRIBE.md)
diff --git a/docs/en/sql-reference/sql-statements/general_DML.md b/docs/en/sql-reference/sql-statements/general_DML.md
deleted file mode 100644
index a4f476aac6869d..00000000000000
--- a/docs/en/sql-reference/sql-statements/general_DML.md
+++ /dev/null
@@ -1,91 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# General DML
-
-- [General DML](#general-dml)
-  - [Loading](#loading)
-  - [Unloading](#unloading)
-  - [ETL task](#etl-task)
-  - [SHOW](#show)
-  - [DELETE](#delete)
-  - [UPDATE](#update)
-  - [SELECT](#select)
-
-## Loading
-
-- [ALTER LOAD](./data-manipulation/ALTER_LOAD.md)
-- [ALTER PIPE](./data-manipulation/ALTER_PIPE.md)
-- [ALTER ROUTINE LOAD](./data-manipulation/ALTER_ROUTINE_LOAD.md)
-- [BROKER LOAD](./data-manipulation/BROKER_LOAD.md)
-- [CANCEL LOAD](./data-manipulation/CANCEL_LOAD.md)
-- [CREATE PIPE](./data-manipulation/CREATE_PIPE.md)
-- [CREATE ROUTINE LOAD](./data-manipulation/CREATE_ROUTINE_LOAD.md)
-- [DROP PIPE](./data-manipulation/DROP_PIPE.md)
-- [INSERT](./data-manipulation/INSERT.md)
-- [PAUSE ROUTINE LOAD](./data-manipulation/PAUSE_ROUTINE_LOAD.md)
-- [RESUME ROUTINE LOAD](./data-manipulation/RESUME_ROUTINE_LOAD.md)
-- [RETRY FILE](./data-manipulation/RETRY_FILE.md)
-- [SHOW LOAD](./data-manipulation/SHOW_LOAD.md)
-- [SHOW PIPES](./data-manipulation/SHOW_PIPES.md)
-- [SHOW ROUTINE LOAD](./data-manipulation/SHOW_ROUTINE_LOAD.md)
-- [SHOW ROUTINE LOAD TASK](./data-manipulation/SHOW_ROUTINE_LOAD_TASK.md)
-- [SHOW TRANSACTION](./data-manipulation/SHOW_TRANSACTION.md)
-- [STOP ROUTINE LOAD](./data-manipulation/STOP_ROUTINE_LOAD.md)
-- [SPARK LOAD](./data-manipulation/SPARK_LOAD.md)
-- [STREAM LOAD](./data-manipulation/STREAM_LOAD.md)
-- [SUSPEND or RESUME PIPE](./data-manipulation/SUSPEND_or_RESUME_PIPE.md)
-
-## Unloading
-
-- [EXPORT](./data-manipulation/EXPORT.md)
-- [CANCEL EXPORT](./data-manipulation/CANCEL_EXPORT.md)
-- [SHOW EXPORT](./data-manipulation/SHOW_EXPORT.md)
-
-## ETL task
-
-- [DROP TASK](./data-manipulation/DROP_TASK.md)
-- [SUBMIT TASK](./data-manipulation/SUBMIT_TASK.md)
-
-## SHOW
-
-- [SHOW ANALYZE JOB](./data-definition/SHOW_ANALYZE_JOB.md)
-- [SHOW ANALYZE STATUS](./data-definition/SHOW_ANALYZE_STATUS.md)
-- [SHOW ALTER TABLE](./data-manipulation/SHOW_ALTER.md)
-- [SHOW ALTER MATERIALIZED VIEW](./data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW.md)
-- [SHOW BACKUP](./data-manipulation/backup_restore/SHOW_BACKUP.md)
-- [SHOW CATALOGS](./data-manipulation/SHOW_CATALOGS.md)
-- [SHOW CREATE CATALOG](./data-manipulation/SHOW_CREATE_CATALOG.md)
-- [SHOW CREATE DATABASE](./data-manipulation/SHOW_CREATE_DATABASE.md)
-- [SHOW CREATE MATERIALIZED VIEW](./data-manipulation/SHOW_CREATE_MATERIALIZED_VIEW.md)
-- [SHOW CREATE TABLE](./data-manipulation/SHOW_CREATE_TABLE.md)
-- [SHOW CREATE VIEW](./data-manipulation/SHOW_CREATE_VIEW.md)
-- [SHOW DATA](./data-manipulation/SHOW_DATA.md)
-- [SHOW DATABASES](./data-manipulation/SHOW_DATABASES.md)
-- [SHOW DELETE](./data-manipulation/SHOW_DELETE.md)
-- [SHOW DYNAMIC PARTITION TABLES](./data-manipulation/SHOW_DYNAMIC_PARTITION_TABLES.md)
-- [SHOW FULL COLUMNS](./data-manipulation//SHOW_FULL_COLUMNS.md)
-- [SHOW FUNCTIONS](./data-definition/SHOW_FUNCTIONS.md)
-- [SHOW INDEX](./data-manipulation//SHOW_INDEX.md)
-- [SHOW META](./data-definition/SHOW_META.md)
-- [SHOW MATERIALIZED VIEWS](./data-manipulation/SHOW_MATERIALIZED_VIEW.md)
-- [SHOW PARTITIONS](./data-manipulation/SHOW_PARTITIONS.md)
-- [SHOW REPOSITORIES](./data-manipulation/backup_restore/SHOW_REPOSITORIES.md)
-- [SHOW RESOURCES](./data-definition/SHOW_RESOURCES.md)
-- [SHOW RESTORE](./data-manipulation/backup_restore/SHOW_RESTORE.md)
-- [SHOW SNAPSHOT](./data-manipulation/backup_restore/SHOW_SNAPSHOT.md)
-- [SHOW TABLES](./data-manipulation/SHOW_TABLES.md)
-- [SHOW TABLET](./data-manipulation/SHOW_TABLET.md)
-
-## DELETE
-
-- [DELETE](./data-manipulation/DELETE.md)
-
-## UPDATE
-
-- [UPDATE](./data-manipulation/UPDATE.md)
-
-## SELECT
-
-- [SELECT](./data-manipulation/SELECT.md)
diff --git a/docs/en/sql-reference/sql-statements/generated_columns.md b/docs/en/sql-reference/sql-statements/generated_columns.md
index 73bc31e4e812a4..f1dc55b2b60631 100644
--- a/docs/en/sql-reference/sql-statements/generated_columns.md
+++ b/docs/en/sql-reference/sql-statements/generated_columns.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Generated columns
@@ -45,7 +45,7 @@ DISTRIBUTED BY HASH(id);
 
 - Generated columns must be defined after regular columns.
 - Aggregate functions cannot be used in the expressions for generated columns.
-- The expressions for generated column cannot reference other generated columns or [auto-increment columns](./auto_increment.md), but the expressions can reference multiple regular columns.
+- The expressions for generated column cannot reference other generated columns or [auto-increment columns](table_bucket_part_index/auto_increment.md), but the expressions can reference multiple regular columns.
 - The data type of a generated column must match the data type of the result generated by the expression for the generated column.
 - Generated columns cannot be created on Aggregate tables.
 
diff --git a/docs/en/sql-reference/sql-statements/keywords.md b/docs/en/sql-reference/sql-statements/keywords.md
index 1b68c5d4168880..b94f6dc559a186 100644
--- a/docs/en/sql-reference/sql-statements/keywords.md
+++ b/docs/en/sql-reference/sql-statements/keywords.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Keywords
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/ALTER_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/ALTER_LOAD.md
new file mode 100644
index 00000000000000..6ccbc6be732d66
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/ALTER_LOAD.md
@@ -0,0 +1,42 @@
+---
+displayed_sidebar: docs
+---
+
+# ALTER LOAD
+
+## Description
+
+Changes the priority of a Broker Load job that is in the **QUEUEING** or **LOADING** state. This statement is supported since v2.5.
+
+> **NOTE**
+>
+> Changing the priority of a Broker Load job that is in the **LOADING** state does not affect the execution of the job.
+
+## Syntax
+
+```SQL
+ALTER LOAD FOR <label_name>
+PROPERTIES
+(
+    'priority'='{LOWEST | LOW | NORMAL | HIGH | HIGHEST}'
+)
+```
+
+## Parameters
+
+| **Parameter** | **Required** | Description                                                  |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| label_name    | Yes          | The label of the load job. Format: `[<database_name>.]<label_name>`. See [BROKER LOAD](BROKER_LOAD.md#database_name-and-label_name). |
+| priority      | Yes          | The new priority that you want to specify for the load job. Valid values: `LOWEST`, `LOW`, `NORMAL`, `HIGH`, and `HIGHEST`. See [BROKER LOAD](BROKER_LOAD.md). |
+
+## Examples
+
+Suppose that you have a Broker Load job whose label is `test_db.label1` and the job is in the **QUEUEING** state. If you want to run the job at the soonest, you can run the following command to change the priority of the job to `HIGHEST`:
+
+```SQL
+ALTER LOAD FOR test_db.label1
+PROPERTIES
+(
+    'priority'='HIGHEST'
+);
+```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md
new file mode 100644
index 00000000000000..92ebc04eb3be09
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md
@@ -0,0 +1,1294 @@
+---
+displayed_sidebar: docs
+toc_max_heading_level: 5
+---
+
+# BROKER LOAD
+
+import InsertPrivNote from '../../../_assets/commonMarkdown/insertPrivNote.md'
+
+## Description
+
+StarRocks provides the MySQL-based loading method Broker Load. After you submit a load job, StarRocks asynchronously runs the job. You can use `SELECT * FROM information_schema.loads` to query the job result. This feature is supported from v3.1 onwards. For more information about the background information, principles, supported data file formats, how to perform single-table loads and multi-table loads, and how to view job results, see [Load data from HDFS](../../../loading/hdfs_load.md) and [Load data from cloud storage](../../../loading/cloud_storage_load.md).
+
+<InsertPrivNote />
+
+## Syntax
+
+```SQL
+LOAD LABEL [<database_name>.]<label_name>
+(
+    data_desc[, data_desc ...]
+)
+WITH BROKER
+(
+    StorageCredentialParams
+)
+[PROPERTIES
+(
+    opt_properties
+)
+]
+```
+
+Note that in StarRocks some literals are used as reserved keywords by the SQL language. Do not directly use these keywords in SQL statements. If you want to use such a keyword in an SQL statement, enclose it in a pair of backticks (`). See [Keywords](../keywords.md).
+
+## Parameters
+
+### database_name and label_name
+
+`label_name` specifies the label of the load job. For the naming conventions, see [System limits](../../System_limit.md).
+
+`database_name` optionally specifies the name of the database to which the destination table belongs.
+
+Each load job has a label that is unique across the entire database. You can use the label of a load job to view the execution status of the load job and prevent repeatedly loading the same data. When a load job enters the **FINISHED** state, its label cannot be reused. Only the label of a load job that has entered the **CANCELLED** state can be reused. In most cases, the label of a load job is reused to retry that load job and load the same data, thereby implementing Exactly-Once semantics.
+
+For label naming conventions, see [System limits](../../System_limit.md).
+
+### data_desc
+
+The description of a batch of data to be loaded. Each `data_desc` descriptor declares information such as the data source, ETL functions, destination StarRocks table, and destination partitions.
+
+Broker Load supports loading multiple data files at a time. In one load job, you can use multiple `data_desc` descriptors to declare multiple data files you want to load, or use one `data_desc` descriptor to declare one file path from which you want to load all data files in it. Broker Load can also ensure the transactional atomicity of each load job that is run to load multiple data files. Atomicity means that the loading of multiple data files in one load job must all succeed or fail. It never happens that the loading of some data files succeeds while the loading of the other files fails.
+
+`data_desc` supports the following syntax:
+
+```SQL
+DATA INFILE ("<file_path>"[, "<file_path>" ...])
+[NEGATIVE]
+INTO TABLE <table_name>
+[PARTITION (<partition1_name>[, <partition2_name> ...])]
+[TEMPORARY PARTITION (<temporary_partition1_name>[, <temporary_partition2_name> ...])]
+[COLUMNS TERMINATED BY "<column_separator>"]
+[ROWS TERMINATED BY "<row_separator>"]
+[FORMAT AS "CSV | Parquet | ORC"]
+[(format_type_options)]
+[(column_list)]
+[COLUMNS FROM PATH AS (<partition_field_name>[, <partition_field_name> ...])]
+[SET <k1=f1(v1)>[, <k2=f2(v2)> ...]]
+[WHERE predicate]
+```
+
+`data_desc` must include the following parameters:
+
+- `file_path`
+
+  Specifies the save path of one or more data files you want to load.
+
+  You can specify this parameter as the save path of one data file. For example, you can specify this parameter as `"hdfs://<hdfs_host>:<hdfs_port>/user/data/tablename/20210411"` to load a data file named `20210411` from the path `/user/data/tablename` on the HDFS server.
+
+  You can also specify this parameter as the save path of multiple data files by using wildcards `?`, `*`, `[]`, `{}`, or `^`. See [Wildcard reference](https://hadoop.apache.org/docs/stable/api/org/apache/hadoop/fs/FileSystem.html#globStatus-org.apache.hadoop.fs.Path-). For example, you can specify this parameter as `"hdfs://<hdfs_host>:<hdfs_port>/user/data/tablename/*/*"` or `"hdfs://<hdfs_host>:<hdfs_port>/user/data/tablename/dt=202104*/*"` to load the data files from all partitions or only `202104` partitions in the path `/user/data/tablename` on the HDFS server.
+
+  > **NOTE**
+  >
+  > Wildcards can also be used to specify intermediate paths.
+
+  In the preceding examples, the `hdfs_host` and `hdfs_port` parameters are described as follows:
+
+  - `hdfs_host`: the IP address of the NameNode host in the HDFS cluster.
+
+  - `hdfs_host`: the FS port of the NameNode host in the HDFS cluster. The default port number is `9000`.
+
+  > **NOTICE**
+  >
+  > - Broker Load supports accessing AWS S3 according to the S3 or S3A protocol. Therefore, when you load data from AWS S3, you can include `s3://` or `s3a://` as the prefix in the S3 URI that you pass as the file path.
+  > - Broker Load supports accessing Google GCS only according to the gs protocol. Therefore, when you load data from Google GCS, you must include `gs://` as the prefix in the GCS URI that you pass as the file path.
+  > - When you load data from Blob Storage, you must use the wasb or wasbs protocol to access your data:
+  >   - If your storage account allows access over HTTP, use the wasb protocol and write the file path as `wasb://<container_name>@<storage_account_name>.blob.core.windows.net/<path>/<file_name>/*`.
+  >   - If your storage account allows access over HTTPS, use the wasbs protocol and write the file path as `wasbs://<container_name>@<storage_account_name>.blob.core.windows.net/<path>/<file_name>/*`.
+  > - When you load data from Data Lake Storage Gen2, you must use the abfs or abfss protocol to access your data:
+  >   - If your storage account allows access over HTTP, use the abfs protocol and write the file path as `abfs://<container_name>@<storage_account_name>.dfs.core.windows.net/<file_name>`.
+  >   - If your storage account allows access over HTTPS, use the abfss protocol and write the file path as `abfss://<container_name>@<storage_account_name>.dfs.core.windows.net/<file_name>`.
+  > - When you load data from Data Lake Storage Gen1, you must use the adl protocol to access your data and write the file path as `adl://<data_lake_storage_gen1_name>.azuredatalakestore.net/<path>/<file_name>`.
+
+- `INTO TABLE`
+
+  Specifies the name of the destination StarRocks table.
+
+`data_desc` can also optionally include the following parameters:
+
+- `NEGATIVE`
+
+  Revokes the loading of a specific batch of data. To achieve this, you need to load the same batch of data with the `NEGATIVE` keyword specified.
+
+  > **NOTE**
+  >
+  > This parameter is valid only when the StarRocks table is an Aggregate table and all its value columns are computed by the `sum` function.
+
+- `PARTITION`
+
+   Specifies the partitions into which you want to load data. By default, if you do not specify this parameter, the source data will be loaded into all partitions of the StarRocks table.
+
+- `TEMPORARY PARTITION`
+
+  Specifies the name of the [temporary partition](../../../table_design/Temporary_partition.md) into which you want to load data. You can specify multiple temporary partitions, which must be separated by commas (,).
+
+- `COLUMNS TERMINATED BY`
+
+  Specifies the column separator used in the data file. By default, if you do not specify this parameter, this parameter defaults to `\t`, indicating tab. The column separator you specify using this parameter must be the same as the column separator that is actually used in the data file. Otherwise, the load job will fail due to inadequate data quality, and its `State` will be `CANCELLED`.
+
+  Broker Load jobs are submitted according to the MySQL protocol. StarRocks and MySQL both escape characters in the load requests. Therefore, if the column separator is an invisible character such as tab, you must add a backslash (\) preceding the column separator. For example, you must input `\\t` if the column separator is `\t`, and you must input `\\n` if the column separator is `\n`. Apache Hive™ files use `\x01` as their column separator, so you must input `\\x01` if the data file is from Hive.
+
+  > **NOTE**
+  >
+  > - For CSV data, you can use a UTF-8 string, such as a comma (,), tab, or pipe (|), whose length does not exceed 50 bytes as a text delimiter.
+  > - Null values are denoted by using `\N`. For example, a data file consists of three columns, and a record from that data file holds data in the first and third columns but no data in the second column. In this situation, you need to use `\N` in the second column to denote a null value. This means the record must be compiled as `a,\N,b` instead of `a,,b`. `a,,b` denotes that the second column of the record holds an empty string.
+
+- `ROWS TERMINATED BY`
+
+  Specifies the row separator used in the data file. By default, if you do not specify this parameter, this parameter defaults to `\n`, indicating line break. The row separator you specify using this parameter must be the same as the row separator that is actually used in the data file. Otherwise, the load job will fail due to inadequate data quality, and its `State` will be `CANCELLED`. This parameter is supported from v2.5.4 onwards.
+
+  For the usage notes about the row separator, see the usage notes for the preceding `COLUMNS TERMINATED BY` parameter.
+
+- `FORMAT AS`
+
+  Specifies the format of the data file. Valid values: `CSV`, `Parquet`, and `ORC`. By default, if you do not specify this parameter, StarRocks determines the data file format based on the filename extension **.csv**, **.parquet**, or **.orc** specified in the `file_path` parameter.
+
+- `format_type_options`
+
+  Specifies CSV format options when `FORMAT AS` is set to `CSV`. Syntax:
+
+  ```JSON
+  (
+      key = value
+      key = value
+      ...
+  )
+  ```
+
+  > **NOTE**
+  >
+  > `format_type_options` is supported in v3.0 and later.
+
+  The following table describes the options.
+
+  | **Parameter** | **Description**                                              |
+  | ------------- | ------------------------------------------------------------ |
+  | skip_header   | Specifies whether to skip the first rows of the data file when the data file is in CSV format. Type: INTEGER. Default value: `0`.<br />In some CSV-formatted data files, the first rows at the beginning are used to define metadata such as column names and column data types. By setting the `skip_header` parameter, you can enable StarRocks to skip the first rows of the data file during data loading. For example, if you set this parameter to `1`, StarRocks skips the first row of the data file during data loading.<br />The first rows at the beginning in the data file must be separated by using the row separator that you specify in the load statement. |
+  | trim_space    | Specifies whether to remove spaces preceding and following column separators from the data file when the data file is in CSV format. Type: BOOLEAN. Default value: `false`.<br />For some databases, spaces are added to column separators when you export data as a CSV-formatted data file. Such spaces are called leading spaces or trailing spaces depending on their locations. By setting the `trim_space` parameter, you can enable StarRocks to remove such unnecessary spaces during data loading.<br />Note that StarRocks does not remove the spaces (including leading spaces and trailing spaces) within a field wrapped in a pair of `enclose`-specified characters. For example, the following field values use pipe (<code class="language-text">&#124;</code>) as the column separator and double quotation marks (`"`) as the `enclose`-specified character:<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124; "Love StarRocks" &#124;</code> <br />If you set `trim_space` to `true`, StarRocks processes the preceding field values as follows:<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> |
+  | enclose       | Specifies the character that is used to wrap the field values in the data file according to [RFC4180](https://www.rfc-editor.org/rfc/rfc4180) when the data file is in CSV format. Type: single-byte character. Default value: `NONE`. The most prevalent characters are single quotation mark (`'`) and double quotation mark (`"`).<br />All special characters (including row separators and column separators) wrapped by using the `enclose`-specified character are considered normal symbols. StarRocks can do more than RFC4180 as it allows you to specify any single-byte character as the `enclose`-specified character.<br />If a field value contains an `enclose`-specified character, you can use the same character to escape that `enclose`-specified character. For example, you set `enclose` to `"`, and a field value is `a "quoted" c`. In this case, you can enter the field value as `"a ""quoted"" c"` into the data file. |
+  | escape        | Specifies the character that is used to escape various special characters, such as row separators, column separators, escape characters, and `enclose`-specified characters, which are then considered by StarRocks to be common characters and are parsed as part of the field values in which they reside. Type: single-byte character. Default value: `NONE`. The most prevalent character is slash (`\`), which must be written as double slashes (`\\`) in SQL statements.<br />**NOTE**<br />The character specified by `escape` is applied to both inside and outside of each pair of `enclose`-specified characters.<br />Two examples are as follows:<ul><li>When you set `enclose` to `"` and `escape` to `\`, StarRocks parses `"say \"Hello world\""` into `say "Hello world"`.</li><li>Assume that the column separator is comma (`,`). When you set `escape` to `\`, StarRocks parses `a, b\, c` into two separate field values: `a` and `b, c`.</li></ul> |
+
+- `column_list`
+
+  Specifies the column mapping between the data file and the StarRocks table. Syntax: `(<column_name>[, <column_name> ...])`. The columns declared in `column_list` are mapped by name onto the StarRocks table columns.
+
+  > **NOTE**
+  >
+  > If the columns of the data file are mapped in sequence onto the columns of the StarRocks table, you do not need to specify `column_list`.
+
+  If you want to skip a specific column of the data file, you only need to temporarily name that column as different from any of the StarRocks table columns. For more information, see [Transform data at loading](../../../loading/Etl_in_loading.md).
+
+- `COLUMNS FROM PATH AS`
+
+  Extracts the information about one or more partition fields from the file path you specify. This parameter is valid only when the file path contains partition fields.
+
+  For example, if the data file is stored in the path `/path/col_name=col_value/file1` in which `col_name` is a partition field and can be mapped onto a column of the StarRocks table, you can specify this parameter as `col_name`. As such, StarRocks extracts `col_value` values from the path and loads them into the StarRocks table column onto which `col_name` is mapped.
+
+  > **NOTE**
+  >
+  > This parameter is available only when you load data from HDFS.
+
+- `SET`
+
+  Specifies one or more functions that you want to use to convert a column of the data file. Examples:
+
+  - The StarRocks table consists of three columns, which are `col1`, `col2`, and `col3` in sequence. The data file consists of four columns, among which the first two columns are mapped in sequence onto `col1` and `col2` of the StarRocks table and the sum of the last two columns is mapped onto `col3` of the StarRocks table. In this case, you need to specify `column_list` as `(col1,col2,tmp_col3,tmp_col4)` and specify `(col3=tmp_col3+tmp_col4)` in the SET clause to implement data conversion.
+  - The StarRocks table consists of three columns, which are `year`, `month`, and `day` in sequence. The data file consists of only one column that accommodates date and time values in `yyyy-mm-dd hh:mm:ss` format. In this case, you need to specify `column_list` as `(tmp_time)` and specify `(year = year(tmp_time), month=month(tmp_time), day=day(tmp_time))` in the SET clause to implement data conversion.
+
+- `WHERE`
+
+  Specifies the conditions based on which you want to filter the source data. StarRocks loads only the source data that meets the filter conditions specified in the WHERE clause.
+
+### WITH BROKER
+
+In v2.3 and earlier, input `WITH BROKER "<broker_name>"` to specify the broker you want to use. From v2.5 onwards, you no longer need to specify a broker, but you still need to retain the `WITH BROKER` keyword.
+
+### StorageCredentialParams
+
+The authentication information used by StarRocks to access your storage system.
+
+#### HDFS
+
+Open-source HDFS supports two authentication methods: simple authentication and Kerberos authentication. Broker Load uses simple authentication by default. Open-source HDFS also supports configuring an HA mechanism for the NameNode. If you choose open-source HDFS as your storage system, you can specify the authentication configuration and HA configuration as follows:
+
+- Authentication configuration
+
+  - If you use simple authentication, configure `StorageCredentialParams` as follows:
+
+    ```Plain
+    "hadoop.security.authentication" = "simple",
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+    ```
+
+    The following table describes the parameters in `StorageCredentialParams`.
+
+    | Parameter                       | Description                                                  |
+    | ------------------------------- | ------------------------------------------------------------ |
+    | hadoop.security.authentication  | The authentication method. Valid values: `simple` and `kerberos`. Default value: `simple`. `simple` represents simple authentication, meaning no authentication, and `kerberos` represents Kerberos authentication. |
+    | username                        | The username of the account that you want to use to access the NameNode of the HDFS cluster. |
+    | password                        | The password of the account that you want to use to access the NameNode of the HDFS cluster. |
+
+  - If you use Kerberos authentication, configure `StorageCredentialParams` as follows:
+
+    ```Plain
+    "hadoop.security.authentication" = "kerberos",
+    "kerberos_principal" = "nn/zelda1@ZELDA.COM",
+    "kerberos_keytab" = "/keytab/hive.keytab",
+    "kerberos_keytab_content" = "YWFhYWFh"
+    ```
+
+    The following table describes the parameters in `StorageCredentialParams`.
+
+    | Parameter                       | Description                                                  |
+    | ------------------------------- | ------------------------------------------------------------ |
+    | hadoop.security.authentication  | The authentication method. Valid values: `simple` and `kerberos`. Default value: `simple`. `simple` represents simple authentication, meaning no authentication, and `kerberos` represents Kerberos authentication. |
+    | kerberos_principal              | The Kerberos principal to be authenticated. Each principal consists of the following three parts to ensure that it is unique across the HDFS cluster:<ul><li>`username` or `servicename`: The name of the principal.</li><li>`instance`: the name of the server that hosts the node to be authenticated in the HDFS cluster. The server name helps ensure that the principal is unique, for example, when the HDFS cluster consists of multiple DataNodes that each are independently authenticated.</li><li>`realm`: The name of the realm. The realm name must be capitalized.</li></ul>Example: `nn/zelda1@ZELDA.COM`. |
+    | kerberos_keytab                 | The save path of the Kerberos keytab file. |
+    | kerberos_keytab_content         | The Base64-encoded content of the the Kerberos keytab file. You can choose to specify either `kerberos_keytab` or `kerberos_keytab_content`. |
+
+- HA configuration
+
+  You can configure an HA mechanism for the NameNode of the HDFS cluster. This way, if the NameNode is switched over to another node, StarRocks can automatically identify the new node that serves as the NameNode. This includes the following scenarios:
+
+  - If you load data from a single HDFS cluster that has one Kerberos user configured, both broker-based loading and broker-free loading are supported.
+  
+    - To perform broker-based loading, make sure that at least one independent broker group is deployed, and place the `hdfs-site.xml` file to the `{deploy}/conf` path on the broker node that serves the HDFS cluster. StarRocks will add the `{deploy}/conf` path to the environment variable `CLASSPATH` upon broker startup, allowing the brokers to read information about the HDFS cluster nodes.
+  
+    - To perform broker-free loading, place the `hdfs-site.xml` file to the `{deploy}/conf` paths of each FE node and each BE or CN node.
+  
+  - If you load data from a single HDFS cluster that has multiple Kerberos users configured, only broker-based loading is supported. Make sure that at least one independent broker group is deployed, and place the `hdfs-site.xml` file to the `{deploy}/conf` path on the broker node that serves the HDFS cluster. StarRocks will add the `{deploy}/conf` path to the environment variable `CLASSPATH` upon broker startup, allowing the brokers to read information about the HDFS cluster nodes.
+
+  - If you load data from multiple HDFS clusters (regardless of whether one or multiple Kerberos users are configured), only broker-based loading is supported. Make sure that at least one independent broker group is deployed for each of these HDFS clusters, and take one of the following actions to enable the brokers to read information about the HDFS cluster nodes:
+
+    - Place the `hdfs-site.xml` file to the `{deploy}/conf` path on the broker node that serves each HDFS cluster. StarRocks will add the `{deploy}/conf` path to the environment variable `CLASSPATH` upon broker startup, allowing the brokers to read information about the nodes in that HDFS cluster.
+
+    - Add the following HA configuration at job creation:
+
+      ```Plain
+      "dfs.nameservices" = "ha_cluster",
+      "dfs.ha.namenodes.ha_cluster" = "ha_n1,ha_n2",
+      "dfs.namenode.rpc-address.ha_cluster.ha_n1" = "<hdfs_host>:<hdfs_port>",
+      "dfs.namenode.rpc-address.ha_cluster.ha_n2" = "<hdfs_host>:<hdfs_port>",
+      "dfs.client.failover.proxy.provider" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
+      ```
+
+      The following table describes the parameters in the HA configuration.
+
+      | Parameter                          | Description                                                  |
+      | ---------------------------------- | ------------------------------------------------------------ |
+      | dfs.nameservices                   | The name of the HDFS cluster.                                |
+      | dfs.ha.namenodes.XXX               | The name of the NameNode in the HDFS cluster. If you specify multiple NameNode names, separate them with commas (`,`). `xxx` is the HDFS cluster name that you have specified in `dfs.nameservices`. |
+      | dfs.namenode.rpc-address.XXX.NN    | The RPC address of the NameNode in the HDFS cluster. `NN` is the NameNode name that you have specified in `dfs.ha.namenodes.XXX`. |
+      | dfs.client.failover.proxy.provider | The provider of the NameNode to which the client will connect. Default value: `org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider`. |
+
+  > **NOTE**
+  >
+  > You can use the [SHOW BROKER](../cluster-management/nodes_processes/SHOW_BROKER.md) statement to check for brokers that are deployed in your StarRocks cluster.
+
+#### AWS S3
+
+If you choose AWS S3 as your storage system, take one of the following actions:
+
+- To choose the instance profile-based authentication method, configure `StorageCredentialParams` as follows:
+
+  ```SQL
+  "aws.s3.use_instance_profile" = "true",
+  "aws.s3.region" = "<aws_s3_region>"
+  ```
+
+- To choose the assumed role-based authentication method, configure `StorageCredentialParams` as follows:
+
+  ```SQL
+  "aws.s3.use_instance_profile" = "true",
+  "aws.s3.iam_role_arn" = "<iam_role_arn>",
+  "aws.s3.region" = "<aws_s3_region>"
+  ```
+
+- To choose the IAM user-based authentication method, configure `StorageCredentialParams` as follows:
+
+  ```SQL
+  "aws.s3.use_instance_profile" = "false",
+  "aws.s3.access_key" = "<iam_user_access_key>",
+  "aws.s3.secret_key" = "<iam_user_secret_key>",
+  "aws.s3.region" = "<aws_s3_region>"
+  ```
+
+The following table describes the parameters you need to configure in `StorageCredentialParams`.
+
+| Parameter                   | Required | Description                                                  |
+| --------------------------- | -------- | ------------------------------------------------------------ |
+| aws.s3.use_instance_profile | Yes      | Specifies whether to enable the credential methods instance profile and assumed role. Valid values: `true` and `false`. Default value: `false`. |
+| aws.s3.iam_role_arn         | No       | The ARN of the IAM role that has privileges on your AWS S3 bucket. If you choose assumed role as the credential method for accessing AWS S3, you must specify this parameter. |
+| aws.s3.region               | Yes      | The region in which your AWS S3 bucket resides. Example: `us-west-1`. |
+| aws.s3.access_key           | No       | The access key of your IAM user. If you choose IAM user as the credential method for accessing AWS S3, you must specify this parameter. |
+| aws.s3.secret_key           | No       | The secret key of your IAM user. If you choose IAM user as the credential method for accessing AWS S3, you must specify this parameter. |
+
+For information about how to choose an authentication method for accessing AWS S3 and how to configure an access control policy in AWS IAM Console, see [Authentication parameters for accessing AWS S3](../../../integrations/authenticate_to_aws_resources.md#authentication-parameters-for-accessing-aws-s3).
+
+#### Google GCS
+
+If you choose Google GCS as your storage system, take one of the following actions:
+
+- To choose the VM-based authentication method, configure `StorageCredentialParams` as follows:
+
+  ```SQL
+  "gcp.gcs.use_compute_engine_service_account" = "true"
+  ```
+
+  The following table describes the parameters you need to configure in `StorageCredentialParams`.
+
+  | **Parameter**                              | **Default value** | **Value** **example** | **Description**                                              |
+  | ------------------------------------------ | ----------------- | --------------------- | ------------------------------------------------------------ |
+  | gcp.gcs.use_compute_engine_service_account | false             | true                  | Specifies whether to directly use the service account that is bound to your Compute Engine. |
+
+- To choose the service account-based authentication method, configure `StorageCredentialParams` as follows:
+
+  ```SQL
+  "gcp.gcs.service_account_email" = "<google_service_account_email>",
+  "gcp.gcs.service_account_private_key_id" = "<google_service_private_key_id>",
+  "gcp.gcs.service_account_private_key" = "<google_service_private_key>"
+  ```
+
+  The following table describes the parameters you need to configure in `StorageCredentialParams`.
+
+  | **Parameter**                          | **Default value** | **Value** **example**                                        | **Description**                                              |
+  | -------------------------------------- | ----------------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
+  | gcp.gcs.service_account_email          | ""                | `"user@hello.iam.gserviceaccount.com"` | The email address in the JSON file generated at the creation of the service account. |
+  | gcp.gcs.service_account_private_key_id | ""                | "61d257bd8479547cb3e04f0b9b6b9ca07af3b7ea"                   | The private key ID in the JSON file generated at the creation of the service account. |
+  | gcp.gcs.service_account_private_key    | ""                | "-----BEGIN PRIVATE KEY----xxxx-----END PRIVATE KEY-----\n"  | The private key in the JSON file generated at the creation of the service account. |
+
+- To choose the impersonation-based authentication method, configure `StorageCredentialParams` as follows:
+
+  - Make a VM instance impersonate a service account:
+
+    ```SQL
+    "gcp.gcs.use_compute_engine_service_account" = "true",
+    "gcp.gcs.impersonation_service_account" = "<assumed_google_service_account_email>"
+    ```
+
+    The following table describes the parameters you need to configure in `StorageCredentialParams`.
+
+    | **Parameter**                              | **Default value** | **Value** **example** | **Description**                                              |
+    | ------------------------------------------ | ----------------- | --------------------- | ------------------------------------------------------------ |
+    | gcp.gcs.use_compute_engine_service_account | false             | true                  | Specifies whether to directly use the service account that is bound to your Compute Engine. |
+    | gcp.gcs.impersonation_service_account      | ""                | "hello"               | The service account that you want to impersonate.            |
+
+  - Make a service account (named as meta service account) impersonate another service account (named as data service account):
+
+    ```SQL
+    "gcp.gcs.service_account_email" = "<google_service_account_email>",
+    "gcp.gcs.service_account_private_key_id" = "<meta_google_service_account_email>",
+    "gcp.gcs.service_account_private_key" = "<meta_google_service_account_email>",
+    "gcp.gcs.impersonation_service_account" = "<data_google_service_account_email>"
+    ```
+
+    The following table describes the parameters you need to configure in `StorageCredentialParams`.
+
+    | **Parameter**                          | **Default value** | **Value** **example**                                        | **Description**                                              |
+    | -------------------------------------- | ----------------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
+    | gcp.gcs.service_account_email          | ""                | `"user@hello.iam.gserviceaccount.com"` | The email address in the JSON file generated at the creation of the meta service account. |
+    | gcp.gcs.service_account_private_key_id | ""                | "61d257bd8479547cb3e04f0b9b6b9ca07af3b7ea"                   | The private key ID in the JSON file generated at the creation of the meta service account. |
+    | gcp.gcs.service_account_private_key    | ""                | "-----BEGIN PRIVATE KEY----xxxx-----END PRIVATE KEY-----\n"  | The private key in the JSON file generated at the creation of the meta service account. |
+    | gcp.gcs.impersonation_service_account  | ""                | "hello"                                                      | The data service account that you want to impersonate.       |
+
+#### Other S3-compatible storage system
+
+If you choose other S3-compatible storage system, such as MinIO, configure `StorageCredentialParams` as follows:
+
+```SQL
+"aws.s3.enable_ssl" = "false",
+"aws.s3.enable_path_style_access" = "true",
+"aws.s3.endpoint" = "<s3_endpoint>",
+"aws.s3.access_key" = "<iam_user_access_key>",
+"aws.s3.secret_key" = "<iam_user_secret_key>"
+```
+
+The following table describes the parameters you need to configure in `StorageCredentialParams`.
+
+| Parameter                        | Required | Description                                                  |
+| -------------------------------- | -------- | ------------------------------------------------------------ |
+| aws.s3.enable_ssl                | Yes      | Specifies whether to enable SSL connection. Valid values: `true` and `false`. Default value: `true`. |
+| aws.s3.enable_path_style_access  | Yes      | Specifies whether to enable path-style URL access. Valid values: `true` and `false`. Default value: `false`. For MinIO, you must set the value to `true`. |
+| aws.s3.endpoint                  | Yes      | The endpoint that is used to connect to your S3-compatible storage system instead of AWS S3. |
+| aws.s3.access_key                | Yes      | The access key of your IAM user. |
+| aws.s3.secret_key                | Yes      | The secret key of your IAM user. |
+
+#### Microsoft Azure Storage
+
+##### Azure Blob Storage
+
+If you choose Blob Storage as your storage system, take one of the following actions:
+
+- To choose the Shared Key authentication method, configure `StorageCredentialParams` as follows:
+
+  ```SQL
+  "azure.blob.storage_account" = "<storage_account_name>",
+  "azure.blob.shared_key" = "<storage_account_shared_key>"
+  ```
+
+  The following table describes the parameters you need to configure in `StorageCredentialParams`.
+
+  | **Parameter**              | **Required** | **Description**                              |
+  | -------------------------- | ------------ | -------------------------------------------- |
+  | azure.blob.storage_account | Yes          | The username of your Blob Storage account.   |
+  | azure.blob.shared_key      | Yes          | The shared key of your Blob Storage account. |
+
+- To choose the SAS Token authentication method, configure `StorageCredentialParams` as follows:
+
+  ```SQL
+  "azure.blob.storage_account" = "<storage_account_name>",
+  "azure.blob.container" = "<container_name>",
+  "azure.blob.sas_token" = "<storage_account_SAS_token>"
+  ```
+
+  The following table describes the parameters you need to configure in `StorageCredentialParams`.
+
+  | **Parameter**             | **Required** | **Description**                                              |
+  | ------------------------- | ------------ | ------------------------------------------------------------ |
+  | azure.blob.storage_account| Yes          | The username of your Blob Storage account.                   |
+  | azure.blob.container      | Yes          | The name of the blob container that stores your data.        |
+  | azure.blob.sas_token      | Yes          | The SAS token that is used to access your Blob Storage account. |
+
+##### Azure Data Lake Storage Gen2
+
+If you choose Data Lake Storage Gen2 as your storage system, take one of the following actions:
+
+- To choose the Managed Identity authentication method, configure `StorageCredentialParams` as follows:
+
+  ```SQL
+  "azure.adls2.oauth2_use_managed_identity" = "true",
+  "azure.adls2.oauth2_tenant_id" = "<service_principal_tenant_id>",
+  "azure.adls2.oauth2_client_id" = "<service_client_id>"
+  ```
+
+  The following table describes the parameters you need to configure in `StorageCredentialParams`.
+
+  | **Parameter**                           | **Required** | **Description**                                              |
+  | --------------------------------------- | ------------ | ------------------------------------------------------------ |
+  | azure.adls2.oauth2_use_managed_identity | Yes          | Specifies whether to enable the Managed Identity authentication method. Set the value to `true`. |
+  | azure.adls2.oauth2_tenant_id            | Yes          | The ID of the tenant whose data you want to access.          |
+  | azure.adls2.oauth2_client_id            | Yes          | The client (application) ID of the managed identity.         |
+
+- To choose the Shared Key authentication method, configure `StorageCredentialParams` as follows:
+
+  ```SQL
+  "azure.adls2.storage_account" = "<storage_account_name>",
+  "azure.adls2.shared_key" = "<storage_account_shared_key>"
+  ```
+
+  The following table describes the parameters you need to configure in `StorageCredentialParams`.
+
+  | **Parameter**               | **Required** | **Description**                                              |
+  | --------------------------- | ------------ | ------------------------------------------------------------ |
+  | azure.adls2.storage_account | Yes          | The username of your Data Lake Storage Gen2 storage account. |
+  | azure.adls2.shared_key      | Yes          | The shared key of your Data Lake Storage Gen2 storage account. |
+
+- To choose the Service Principal authentication method, configure `StorageCredentialParams` as follows:
+
+  ```SQL
+  "azure.adls2.oauth2_client_id" = "<service_client_id>",
+  "azure.adls2.oauth2_client_secret" = "<service_principal_client_secret>",
+  "azure.adls2.oauth2_client_endpoint" = "<service_principal_client_endpoint>"
+  ```
+
+  The following table describes the parameters you need to configure `in StorageCredentialParams`.
+
+  | **Parameter**                      | **Required** | **Description**                                              |
+  | ---------------------------------- | ------------ | ------------------------------------------------------------ |
+  | azure.adls2.oauth2_client_id       | Yes          | The client (application) ID of the service principal.        |
+  | azure.adls2.oauth2_client_secret   | Yes          | The value of the new client (application) secret created.    |
+  | azure.adls2.oauth2_client_endpoint | Yes          | The OAuth 2.0 token endpoint (v1) of the service principal or application. |
+
+##### Azure Data Lake Storage Gen1
+
+If you choose Data Lake Storage Gen1 as your storage system, take one of the following actions:
+
+- To choose the Managed Service Identity authentication method, configure `StorageCredentialParams` as follows:
+
+  ```SQL
+  "azure.adls1.use_managed_service_identity" = "true"
+  ```
+
+  The following table describes the parameters you need to configure in `StorageCredentialParams`.
+
+  | **Parameter**                            | **Required** | **Description**                                              |
+  | ---------------------------------------- | ------------ | ------------------------------------------------------------ |
+  | azure.adls1.use_managed_service_identity | Yes          | Specifies whether to enable the Managed Service Identity authentication method. Set the value to `true`. |
+
+- To choose the Service Principal authentication method, configure `StorageCredentialParams` as follows:
+
+  ```SQL
+  "azure.adls1.oauth2_client_id" = "<application_client_id>",
+  "azure.adls1.oauth2_credential" = "<application_client_credential>",
+  "azure.adls1.oauth2_endpoint" = "<OAuth_2.0_authorization_endpoint_v2>"
+  ```
+
+  The following table describes the parameters you need to configure in `StorageCredentialParams`.
+
+  | **Parameter**                 | **Required** | **Description**                                              |
+  | ----------------------------- | ------------ | ------------------------------------------------------------ |
+  | azure.adls1.oauth2_client_id  | Yes          | The client (application) ID of the .                         |
+  | azure.adls1.oauth2_credential | Yes          | The value of the new client (application) secret created.    |
+  | azure.adls1.oauth2_endpoint   | Yes          | The OAuth 2.0 token endpoint (v1) of the service principal or application. |
+
+### opt_properties
+
+Specifies some optional parameters whose settings are applied to the entire load job. Syntax:
+
+```Plain
+PROPERTIES ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
+```
+
+The following parameters are supported:
+
+- `timeout`
+
+  Specifies the timeout period of the load job. Unit: second. The default timeout period is 4 hours. We recommend that you specify a timeout period shorter than 6 hours. If the load job does not finish within the timeout period, StarRocks cancels the load job and the status of the load job becomes **CANCELLED**.
+
+  > **NOTE**
+  >
+  > In most cases, you do not need to set the timeout period. We recommend that you set the timeout period only when the load job cannot finish within the default timeout period.
+
+  Use the following formula to infer the timeout period:
+
+  **Timeout period > (Total size of the data files to be loaded x Total number of the data files to be loaded and the materialized views created on the data files)/Average load speed**
+
+  > **NOTE**
+  >
+  > "Average load speed" is the average load speed for your entire StarRocks cluster. The average load speed varies for each cluster depending on the server configuration and the maximum number of concurrent query tasks allowed for the cluster. You can infer the average load speed based on the load speeds of historical load jobs.
+
+  Suppose that you want to load a 1-GB data file on which two materialized views are created into a StarRocks cluster whose average load speed is 10 MB/s. The amount of time required for the data load is approximately 102 seconds.
+
+  (1 x 1024 x 3)/10 = 307.2 (second)
+
+  For this example, we recommend that you set the timeout period to a value greater than 308 seconds.
+
+- `max_filter_ratio`
+
+  Specifies the maximum error tolerance of the load job. The maximum error tolerance is the maximum percentage of rows that can be filtered out as a result of inadequate data quality. Valid values: `0`~`1`. Default value: `0`.
+
+  - If you set this parameter to `0`, StarRocks does not ignore unqualified rows during loading. As such, if the source data contains unqualified rows, the load job fails. This helps ensure the correctness of the data loaded into StarRocks.
+
+  - If you set this parameter to a value greater than `0`, StarRocks can ignore unqualified rows during loading. As such, the load job can succeed even if the source data contains unqualified rows.
+
+    > **NOTE**
+    >
+    > Rows that are filtered out due to inadequate data quality do not include rows that are filtered out by the WHERE clause.
+
+  If the load job fails because the maximum error tolerance is set to `0`, you can use [SHOW LOAD](SHOW_LOAD.md) to view the job result. Then, determine whether unqualified rows can be filtered out. If unqualified rows can be filtered out, calculate the maximum error tolerance based on the values returned for `dpp.abnorm.ALL` and `dpp.norm.ALL` in the job result, adjust the maximum error tolerance, and submit the load job again. The formula for calculating the maximum error tolerance is as follows:
+
+  `max_filter_ratio` = [`dpp.abnorm.ALL`/(`dpp.abnorm.ALL` + `dpp.norm.ALL`)]
+
+  The sum of the values returned for `dpp.abnorm.ALL` and `dpp.norm.ALL` is the total number of rows to be loaded.
+
+- `log_rejected_record_num`
+
+  Specifies the maximum number of unqualified data rows that can be logged. This parameter is supported from v3.1 onwards. Valid values: `0`, `-1`, and any non-zero positive integer. Default value: `0`.
+  
+  - The value `0` specifies that data rows that are filtered out will not be logged.
+  - The value `-1` specifies that all data rows that are filtered out will be logged.
+  - A non-zero positive integer such as `n` specifies that up to `n` data rows that are filtered out can be logged on each BE.
+
+- `load_mem_limit`
+
+  Specifies the maximum amount of memory that can be provided to the load job. The value of this parameter cannot exceed the upper memory limit supported by each BE or CN node. Unit: bytes: The default memory limit is 2 GB.
+
+- `strict_mode`
+
+  Specifies whether to enable the [strict mode](../../../loading/load_concept/strict_mode.md). Valid values: `true` and `false`. Default value: `false`. `true` specifies to enable the strict mode, and `false` specifies to disable the strict mode.
+
+- `timezone`
+
+  Specifies the time zone of the load job. Default value: `Asia/Shanghai`. The time zone setting affects the results returned by functions such as strftime, alignment_timestamp, and from_unixtime. For more information, see [Configure a time zone](../../../administration/management/timezone.md). The time zone specified in the `timezone` parameter is a session-level time zone.
+
+- `priority`
+
+  Specifies the priority of the load job. Valid values: `LOWEST`, `LOW`, `NORMAL`, `HIGH`, and `HIGHEST`. Default value: `NORMAL`. Broker Load provides the [FE parameter](../../../administration/management/FE_configuration.md) `max_broker_load_job_concurrency`, determines the maximum number of Broker Load jobs that can be concurrently run within your StarRocks cluster. If the number of Broker Load jobs that are submitted within the specified time period exceeds the maximum number, excessive jobs will be waiting to be scheduled based on their priorities.
+
+  You can use the [ALTER LOAD](ALTER_LOAD.md) statement to change the priority of an existing load job that is in the `QUEUEING` or `LOADING` state.
+
+  StarRocks allows setting the `priority` parameter for a Broker Load job since v2.5.
+
+- `partial_update`
+
+  Whether to use partial updates. Valid values: `TRUE` and `FALSE`. Default value: `FALSE`, indicating to disable this feature.
+
+- `partial_update_mode`
+
+  Specifies the mode for partial updates. Valid values: `row` and `column`. <ul><li> The value `row` (default) means partial updates in row mode, which is more suitable for real-time updates with many columns and small batches.</li><li>The value `column` means partial updates in column mode, which is more suitable for batch updates with few columns and many rows. In such scenarios, enabling the column mode offers faster update speeds. For example, in a table with 100 columns, if only 10 columns (10% of the total) are updated for all rows, the update speed of the column mode is 10 times faster.</li></ul>
+
+- `merge_condition`
+
+  Specifies the name of the column you want to use as the condition to determine whether updates can take effect. The update from a source record to a destination record takes effect only when the source data record has a greater or equal value than the destination data record in the specified column.
+  
+  Broker Load supports conditional updates since v3.1. For more information, see [Change data through loading](../../../loading/Load_to_Primary_Key_tables.md#conditional-updates).
+  
+  > **NOTE**
+  >
+  > The column that you specify cannot be a primary key column. Additionally, only tables that use the Primary Key table support conditional updates.
+
+StarRocks supports loading JSON data from v3.2.3 onwards. The parameters are as follows:
+
+- jsonpaths
+
+  The names of the keys that you want to load from the JSON data file. You need to specify this parameter only when you load JSON data by using the matched mode. The value of this parameter is in JSON format. See [Configure column mapping for JSON data loading](#configure-column-mapping-for-json-data-loading).
+
+- strip_outer_array
+
+  Specifies whether to strip the outermost array structure. Valid values: `true` and `false`. Default value: `false`.
+  
+  In real-world business scenarios, the JSON data may have an outermost array structure as indicated by a pair of square brackets `[]`. In this situation, we recommend that you set this parameter to `true`, so StarRocks removes the outermost square brackets `[]` and loads each inner array as a separate data record. If you set this parameter to `false`, StarRocks parses the entire JSON data file into one array and loads the array as a single data record. For example, the JSON data is `[ {"category" : 1, "author" : 2}, {"category" : 3, "author" : 4} ]`. If you set this parameter to `true`,  `{"category" : 1, "author" : 2}` and `{"category" : 3, "author" : 4}` are parsed into separate data records that are loaded into separate StarRocks table rows.
+
+- json_root
+
+  The root element of the JSON data that you want to load from the JSON data file. You need to specify this parameter only when you load JSON data by using the matched mode. The value of this parameter is a valid JsonPath string. By default, the value of this parameter is empty, indicating that all data of the JSON data file will be loaded. For more information, see the "[Load JSON data using matched mode with root element specified](#load-json-data-using-matched-mode-with-root-element-specified)" section of this topic.
+
+<!-- - ignore_json_size
+
+  Specifies whether to check the size of the JSON body in the HTTP request.
+  
+  > **NOTE**
+  >
+  > By default, the size of the JSON body in an HTTP request cannot exceed 100 MB. If the JSON body exceeds 100 MB in size, an error "The size of this batch exceed the max size [104857600] of json type data data [8617627793]. Set ignore_json_size to skip check, although it may lead huge memory consuming." is reported. To prevent this error, you can add `"ignore_json_size:true"` in the HTTP request header to instruct StarRocks not to check the JSON body size.
+-->
+When you load JSON data, also note that the size per JSON object cannot exceed 4 GB. If an individual JSON object in the JSON data file exceeds 4 GB in size, an error "This parser can't support a document that big." is reported.
+
+## Column mapping
+
+### Configure column mapping for CSV data loading
+
+If the columns of the data file can be mapped one on one in sequence to the columns of the StarRocks table, you do not need to configure the column mapping between the data file and the StarRocks table.
+
+If the columns of the data file cannot be mapped one on one in sequence to the columns of the StarRocks table, you need to use the `columns` parameter to configure the column mapping between the data file and the StarRocks table. This includes the following two use cases:
+
+- **Same number of columns but different column sequence.** **Also, the data from the data file does not need to be computed by functions before it is loaded into the matching StarRocks table columns.**
+
+  In the `columns` parameter, you need to specify the names of the StarRocks table columns in the same sequence as how the data file columns are arranged.
+
+  For example, the StarRocks table consists of three columns, which are `col1`, `col2`, and `col3` in sequence, and the data file also consists of three columns, which can be mapped to the StarRocks table columns `col3`, `col2`, and `col1` in sequence. In this case, you need to specify `"columns: col3, col2, col1"`.
+
+- **Different number of columns and different column sequence. Also, the data from the data file needs to be computed by functions before it is loaded into the matching StarRocks table columns.**
+
+  In the `columns` parameter, you need to specify the names of the StarRocks table columns in the same sequence as how the data file columns are arranged and specify the functions you want to use to compute the data. Two examples are as follows:
+
+  - The StarRocks table consists of three columns, which are `col1`, `col2`, and `col3` in sequence. The data file consists of four columns, among which the first three columns can be mapped in sequence to the StarRocks table columns `col1`, `col2`, and `col3` and the fourth column cannot be mapped to any of the StarRocks table columns. In this case, you need to temporarily specify a name for the fourth column of the data file, and the temporary name must be different from any of the StarRocks table column names. For example, you can specify `"columns: col1, col2, col3, temp"`, in which the fourth column of the data file is temporarily named `temp`.
+  - The StarRocks table consists of three columns, which are `year`, `month`, and `day` in sequence. The data file consists of only one column that accommodates date and time values in `yyyy-mm-dd hh:mm:ss` format. In this case, you can specify `"columns: col, year = year(col), month=month(col), day=day(col)"`, in which `col` is the temporary name of the data file column and the functions `year = year(col)`, `month=month(col)`, and `day=day(col)` are used to extract data from the data file column `col` and loads the data into the mapping StarRocks table columns. For example, `year = year(col)` is used to extract the `yyyy` data from the data file column `col` and loads the data into the StarRocks table column `year`.
+
+For detailed examples, see [Configure column mapping](#configure-column-mapping).
+
+### Configure column mapping for JSON data loading
+
+If the keys of the JSON document have the same names as the columns of the StarRocks table, you can load the JSON-formatted data by using the simple mode. In simple mode, you do not need to specify the `jsonpaths` parameter. This mode requires that the JSON-formatted data must be an object as indicated by curly brackets `{}`, such as `{"category": 1, "author": 2, "price": "3"}`. In this example, `category`, `author`, and `price` are key names, and these keys can be mapped one on one by name to the columns `category`, `author`, and `price` of the StarRocks table.
+
+If the keys of the JSON document have different names than the columns of the StarRocks table, you can load the JSON-formatted data by using the matched mode. In matched mode, you need to use the `jsonpaths` and `COLUMNS` parameters to specify the column mapping between the JSON document and the StarRocks table:
+
+- In the `jsonpaths` parameter, specify the JSON keys in the sequence as how they are arranged in the JSON document.
+- In the `COLUMNS` parameter, specify the mapping between the JSON keys and the StarRocks table columns:
+  - The column names specified in the `COLUMNS` parameter are mapped one on one in sequence to the JSON keys.
+  - The column names specified in the `COLUMNS` parameter are mapped one on one by name to the StarRocks table columns.
+
+For examples about loading JSON-formatted data by using the matched mode, see [Load JSON data using matched mode](#load-json-data-using-matched-mode).
+
+## Related configuration items
+
+The [FE configuration item](../../../administration/management/FE_configuration.md) `max_broker_load_job_concurrency` specifies the maximum number of Broker Load jobs that can be concurrently run within your StarRocks cluster.
+
+In StarRocks v2.4 and earlier, if the total number of Broker Load jobs that are submitted within a specific period of time exceeds the maximum number, excessive jobs will be queued and scheduled based on their submission time.
+
+Since StarRocks v2.5, if the total number of Broker Load jobs that are submitted within a specific period of time exceeds the maximum number, excessive jobs are queued and scheduled based on their priorities. You can specify a priority for a job by using the `priority` parameter described above. You can use [ALTER LOAD](ALTER_LOAD.md) to modify the priority of an existing job that is in the **QUEUEING** or **LOADING** state.
+
+## Job splitting and concurrent running
+
+A Broker Load job can be split into one or more tasks that concurrently run. The tasks within a load job are run within a single transaction. They must all succeed or fail. StarRocks splits each load job based on how you declare `data_desc` in the `LOAD` statement:
+
+- If you declare multiple `data_desc` parameters, each of which specifies a distinct table, a task is generated to load the data of each table.
+
+- If you declare multiple `data_desc` parameters, each of which specifies a distinct partition for the same table, a task is generated to load the data of each partition.
+
+Additionally, each task can be further split into one or more instances, which are evenly distributed to and concurrently run on the BEs or CNs of your StarRocks cluster. StarRocks splits each task based on the FE parameter [`min_bytes_per_broker_scanner`](../../../administration/management/FE_configuration.md) and the number of BE or CN nodes. You can use the following formula to calculate the number of instances in an individual task:
+
+**Number of instances in an individual task = min(Amount of data to be loaded by an individual task/`min_bytes_per_broker_scanner`, Number of BE/CN nodes)**
+
+In most cases, only one `data_desc` is declared for each load job, each load job is split into only one task, and the task is split into the same number of instances as the number of BE or CN nodes.
+
+## Examples
+
+This section uses HDFS as an example to describe various load configurations.
+
+### Load CSV data
+
+This section uses CSV as an example to explain the various parameter configurations that you can use to meet your diverse load requirements.
+
+#### Set timeout period
+
+Your StarRocks database `test_db` contains a table named `table1`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example1.csv` also consists of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table1`.
+
+If you want to load all data from `example1.csv` into `table1` within up to 3600 seconds, run the following command:
+
+```SQL
+LOAD LABEL test_db.label1
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example1.csv")
+    INTO TABLE table1
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+)
+PROPERTIES
+(
+    "timeout" = "3600"
+);
+```
+
+#### Set maximum error tolerance
+
+Your StarRocks database `test_db` contains a table named `table2`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example2.csv` also consists of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table2`.
+
+If you want to load all data from `example2.csv` into `table2` with a maximum error tolerance of `0.1`, run the following command:
+
+```SQL
+LOAD LABEL test_db.label2
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example2.csv")
+    INTO TABLE table2
+
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+)
+PROPERTIES
+(
+    "max_filter_ratio" = "0.1"
+);
+```
+
+#### Load all data files from a file path
+
+Your StarRocks database `test_db` contains a table named `table3`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+All data files stored in the `/user/starrocks/data/input/` path of your HDFS cluster also each consist of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table3`. The column separator used in these data files is `\x01`.
+
+If you want to load data from all these data files stored in the `hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/` path into `table3`, run the following command:
+
+```SQL
+LOAD LABEL test_db.label3
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/*")
+    INTO TABLE table3
+    COLUMNS TERMINATED BY "\\x01"
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+#### Set NameNode HA mechanism
+
+Your StarRocks database `test_db` contains a table named `table4`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example4.csv` also consists of three columns, which are mapped onto `col1`, `col2`, and `col3` of `table4`.
+
+If you want to load all data from `example4.csv` into `table4` with an HA mechanism configured for the NameNode, run the following command:
+
+```SQL
+LOAD LABEL test_db.label4
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example4.csv")
+    INTO TABLE table4
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>",
+    "dfs.nameservices" = "my_ha",
+    "dfs.ha.namenodes.my_ha" = "my_namenode1, my_namenode2","dfs.namenode.rpc-address.my_ha.my_namenode1" = "nn1_host:rpc_port",
+    "dfs.namenode.rpc-address.my_ha.my_namenode2" = "nn2_host:rpc_port",
+    "dfs.client.failover.proxy.provider" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
+);
+```
+
+#### Set Kerberos authentication
+
+Your StarRocks database `test_db` contains a table named `table5`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example5.csv` also consists of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table5`.
+
+If you want to load all data from `example5.csv` into `table5` with Kerberos authentication configured and the keytab file path specified, run the following command:
+
+```SQL
+LOAD LABEL test_db.label5
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example5.csv")
+    INTO TABLE table5
+    COLUMNS TERMINATED BY "\t"
+)
+WITH BROKER
+(
+    "hadoop.security.authentication" = "kerberos",
+    "kerberos_principal" = "starrocks@YOUR.COM",
+    "kerberos_keytab" = "/home/starRocks/starRocks.keytab"
+);
+```
+
+#### Revoke data loading
+
+Your StarRocks database `test_db` contains a table named `table6`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example6.csv` also consists of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table6`.
+
+You have loaded all data from `example6.csv` into `table6` by running a Broker Load job.
+
+If you want to revoke the data you have loaded, run the following command:
+
+```SQL
+LOAD LABEL test_db.label6
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example6.csv")
+    NEGATIVE
+    INTO TABLE table6
+    COLUMNS TERMINATED BY "\t"
+)
+WITH BROKER
+(
+    "hadoop.security.authentication" = "kerberos",
+    "kerberos_principal" = "starrocks@YOUR.COM",
+    "kerberos_keytab" = "/home/starRocks/starRocks.keytab"
+);
+```
+
+#### Specify destination partitions
+
+Your StarRocks database `test_db` contains a table named `table7`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example7.csv` also consists of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table7`.
+
+If you want to load all data from `example7.csv` into two partitions, `p1` and `p2`, of `table7`, run the following command:
+
+```SQL
+LOAD LABEL test_db.label7
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example7.csv")
+    INTO TABLE table7
+    PARTITION (p1, p2)
+    COLUMNS TERMINATED BY ","
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+#### Configure column mapping
+
+Your StarRocks database `test_db` contains a table named `table8`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example8.csv` also consists of three columns, which are mapped in sequence onto `col2`, `col1`, and `col3` of `table8`.
+
+If you want to load all data from `example8.csv` into `table8`, run the following command:
+
+```SQL
+LOAD LABEL test_db.label8
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example8.csv")
+    INTO TABLE table8
+    COLUMNS TERMINATED BY ","
+    (col2, col1, col3)
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+> **NOTE**
+>
+> In the preceding example, the columns of `example8.csv` cannot be mapped onto the columns of `table8` in the same sequence as how these columns are arranged in `table8`. Therefore, you need to use `column_list` to configure the column mapping between `example8.csv` and `table8`.
+
+#### Set filter conditions
+
+Your StarRocks database `test_db` contains a table named `table9`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example9.csv` also consists of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table9`.
+
+If you want to load only the data records whose values in the first column are greater than `20180601` from `example9.csv` into `table9`, run the following command:
+
+```SQL
+LOAD LABEL test_db.label9
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example9.csv")
+    INTO TABLE table9
+    (col1, col2, col3)
+    where col1 > 20180601
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+> **NOTE**
+>
+> In the preceding example, the columns of `example9.csv` can be mapped onto the columns of `table9` in the same sequence as how these columns are arranged in `table9`, but you need to use the WHERE clause to specify column-based filter conditions. Therefore, you need to use `column_list` to configure the column mapping between `example9.csv` and `table9`.
+
+#### Load data into tables containing HLL-type columns
+
+Your StarRocks database `test_db` contains a table named `table10`. The table consists of four columns, which are `id`, `col1`, `col2`, and `col3` in sequence. `col1` and `col2` are defined as HLL-type columns.
+
+Your data file `example10.csv` consists of three columns, among which the first column is mapped onto `id` of `table10` and the second and third columns are mapped in sequence onto `col1` and `col2` of `table10`. The values in the second and third columns of `example10.csv` can be converted into HLL-type data by using functions before they are loaded into `col1` and `col2` of `table10`.
+
+If you want to load all data from `example10.csv` into `table10`, run the following command:
+
+```SQL
+LOAD LABEL test_db.label10
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example10.csv")
+    INTO TABLE table10
+    COLUMNS TERMINATED BY ","
+    (id, temp1, temp2)
+    SET
+    (
+        col1 = hll_hash(temp1),
+        col2 = hll_hash(temp2),
+        col3 = empty_hll()
+     )
+ )
+ WITH BROKER
+ (
+     "username" = "<hdfs_username>",
+     "password" = "<hdfs_password>"
+ );
+```
+
+> **NOTE**
+>
+> In the preceding example, the three columns of `example10.csv` are named `id`, `temp1`, and `temp2` in sequence by using `column_list`. Then, functions are used to convert data as follows:
+>
+> - The `hll_hash` function is used to convert the values in `temp1` and `temp2` of `example10.csv` into HLL-type data and map `temp1` and `temp2` of `example10.csv` onto `col1` and `col2` of `table10`.
+>
+> - The `hll_empty` function is used to fill the specified default value into `col3` of `table10`.
+
+For usage of the functions `hll_hash` and `hll_empty`, see [hll_hash](../../sql-functions/scalar-functions/hll_hash.md) and [hll_empty](../../sql-functions/scalar-functions/hll_empty.md).
+
+#### Extract partition field values from file path
+
+Broker Load supports parsing the values of specific partition fields contained in a file path based on the column definitions of the destination StarRocks table. This feature of StarRocks is similar to the Partition Discovery feature of Apache Spark™.
+
+Your StarRocks database `test_db` contains a table named `table11`. The table consists of five columns, which are `col1`, `col2`, `col3`, `city`, and `utc_date` in sequence.
+
+The file path `/user/starrocks/data/input/dir/city=beijing` of your HDFS cluster contains the following data files:
+
+- `/user/starrocks/data/input/dir/city=beijing/utc_date=2019-06-26/0000.csv`
+
+- `/user/starrocks/data/input/dir/city=beijing/utc_date=2019-06-26/0001.csv`
+
+These data files each consist of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table11`.
+
+If you want to load data from all data files from the file path `/user/starrocks/data/input/dir/city=beijing/utc_date=*/*` into `table11` and, at the same time, you want to extract the values of the partition fields `city` and `utc_date` contained in the file path and load the extracted values into `city` and `utc_date` of `table11`, run the following command:
+
+```SQL
+LOAD LABEL test_db.label11
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/dir/city=beijing/*/*")
+    INTO TABLE table11
+    FORMAT AS "csv"
+    (col1, col2, col3)
+    COLUMNS FROM PATH AS (city, utc_date)
+    SET (uniq_id = md5sum(k1, city))
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+#### Extract partition field values from `%3A`-included file path
+
+In HDFS, file paths cannot contain colons (:). All colons (:) will be converted into `%3A`.
+
+Your StarRocks database `test_db` contains a table named `table12`. The table consists of three columns, which are `data_time`, `col1`, and `col2` in sequence. The table schema is as follows:
+
+```SQL
+data_time DATETIME,
+col1        INT,
+col2        INT
+```
+
+The file path `/user/starrocks/data` of your HDFS cluster contains the following data files:
+
+- `/user/starrocks/data/data_time=2020-02-17 00%3A00%3A00/example12.csv`
+
+- `/user/starrocks/data/data_time=2020-02-18 00%3A00%3A00/example12.csv`
+
+If you want to load all data from `example12.csv` into `table12` and, at the same time, you want to extract the values of the partition field `data_time` from the file path and load the extracted values into `data_time` of `table12`, run the following command:
+
+```SQL
+LOAD LABEL test_db.label12
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/*/example12.csv")
+    INTO TABLE table12
+    COLUMNS TERMINATED BY ","
+    FORMAT AS "csv"
+    (col1,col2)
+    COLUMNS FROM PATH AS (data_time)
+    SET (data_time = str_to_date(data_time, '%Y-%m-%d %H%%3A%i%%3A%s'))
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+> **NOTE**
+>
+> In the preceding example, the values extracted from the partition field `data_time` are strings that contain `%3A`, such as `2020-02-17 00%3A00%3A00`. Therefore, you need to use the `str_to_date` function to convert the strings into DATETIME-type data before they are loaded into `data_time` of `table8`.
+
+#### Setting `format_type_options`
+
+Your StarRocks database `test_db` contains a table named `table13`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example13.csv` also consists of three columns, which are mapped in sequence onto `col2`, `col1`, and `col3` of `table13`.
+
+If you want to load all data from `example13.csv` into `table13`, with the intention of skipping the first two rows of `example13.csv`, removing the spaces preceding and following column separators, and setting `enclose` to `\` and `escape` to `\`, run the following command:
+
+```SQL
+LOAD LABEL test_db.label13
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/*/example13.csv")
+    INTO TABLE table13
+    COLUMNS TERMINATED BY ","
+    FORMAT AS "CSV"
+    (
+        skip_header = 2
+        trim_space = TRUE
+        enclose = "\""
+        escape = "\\"
+    )
+    (col2, col1, col3)
+)
+WITH BROKER
+(
+    "username" = "hdfs_username",
+    "password" = "hdfs_password"
+)
+PROPERTIES
+(
+    "timeout" = "3600"
+);
+```
+
+### Load Parquet data
+
+This section describes some parameters settings you need to take note of when you load Parquet data.
+
+Your StarRocks database `test_db` contains a table named `table13`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example13.parquet` also consists of three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table13`.
+
+If you want to load all data from `example13.parquet` into `table13`, run the following command:
+
+```SQL
+LOAD LABEL test_db.label13
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example13.parquet")
+    INTO TABLE table13
+    FORMAT AS "parquet"
+    (col1, col2, col3)
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+> **NOTE**
+>
+> By default, when you load Parquet data, StarRocks determines the data file format based on whether the filename contains the extension **.parquet**. If the filename does not contain the extension **.parquet**, you must use `FORMAT AS` to specify the data file format as `Parquet`.
+
+### Load ORC data
+
+This section describes some parameters settings you need to take note of when you load ORC data.
+
+Your StarRocks database `test_db` contains a table named `table14`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example14.orc` also contains three columns, which are mapped in sequence onto `col1`, `col2`, and `col3` of `table14`.
+
+If you want to load all data from `example14.orc` into `table14`, run the following command:
+
+```SQL
+LOAD LABEL test_db.label14
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example14.orc")
+    INTO TABLE table14
+    FORMAT AS "orc"
+    (col1, col2, col3)
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+> **NOTE**
+>
+> - By default, when you load ORC data, StarRocks determines the data file format based on whether the filename contains the extension **.orc**. If the filename does not contain the extension **.orc**, you must use `FORMAT AS` to specify the data file format as `ORC`.
+>
+> - In StarRocks v2.3 and earlier, if the data file contains ARRAY-type columns, you must make sure that the columns of the ORC data file have the same names as their mapping columns in the StarRocks table and the columns cannot be specified in the SET clause.
+
+### Load JSON data
+
+This section describes the parameter settings that you need to take note of when you load JSON data.
+
+Your StarRocks database `test_db` contains a table named `tbl1`, whose schema is as follows:
+
+```SQL
+`category` varchar(512) NULL COMMENT "",
+`author` varchar(512) NULL COMMENT "",
+`title` varchar(512) NULL COMMENT "",
+`price` double NULL COMMENT ""
+```
+
+#### Load JSON data using simple mode
+
+Suppose that your data file `example1.json` consists of the following data:
+
+```JSON
+{"category":"C++","author":"avc","title":"C++ primer","price":895}
+```
+
+To load all data from `example1.json` into `tbl1`, run the following command:
+
+```SQL
+LOAD LABEL test_db.label15
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example1.csv")
+    INTO TABLE tbl1
+    FORMAT AS "json"
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+> **NOTE**
+>
+> In the preceding example, the parameters `columns` and `jsonpaths` are not specified. Therefore, the keys in `example1.json` are mapped by name onto the columns of `tbl1`.
+
+#### Load JSON data using matched mode
+
+StarRocks performs the following steps to match and process JSON data:
+
+1. (Optional) Strips the outermost array structure as instructed by the `strip_outer_array` parameter setting.
+
+   > **NOTE**
+   >
+   > This step is performed only when the outermost layer of the JSON data is an array structure as indicated by a pair of square brackets `[]`. You need to set `strip_outer_array` to `true`.
+
+2. (Optional) Matches the root element of the JSON data as instructed by the `json_root` parameter setting.
+
+   > **NOTE**
+   >
+   > This step is performed only when the JSON data has a root element. You need to specify the root element by using the `json_root` parameter.
+
+3. Extracts the specified JSON data as instructed by the `jsonpaths` parameter setting.
+
+##### Load JSON data using matched mode without root element specified
+
+Suppose that your data file `example2.json` consists of the following data:
+
+```JSON
+[
+    {"category":"xuxb111","author":"1avc","title":"SayingsoftheCentury","price":895},
+    {"category":"xuxb222","author":"2avc","title":"SayingsoftheCentury","price":895},
+    {"category":"xuxb333","author":"3avc","title":"SayingsoftheCentury","price":895}
+]
+```
+
+To load only `category`, `author`, and `price` from `example2.json`, run the following command:
+
+```SQL
+LOAD LABEL test_db.label16
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example2.csv")
+    INTO TABLE tbl1
+    FORMAT AS "json"
+    (category, price, author)
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+)
+PROPERTIES
+(
+    "strip_outer_array" = "true",
+    "jsonpaths" = "[\"$.category\",\"$.price\",\"$.author\"]"
+);
+```
+
+> **NOTE**
+>
+> In the preceding example, the outermost layer of the JSON data is an array structure as indicated by a pair of square brackets `[]`. The array structure consists of multiple JSON objects that each represent a data record. Therefore, you need to set `strip_outer_array` to `true` to strip the outermost array structure. The key **title** that you do not want to load is ignored during loading.
+
+##### Load JSON data using matched mode with root element specified
+
+Suppose your data file `example3.json` consists of the following data:
+
+```JSON
+{
+    "id": 10001,
+    "RECORDS":[
+        {"category":"11","title":"SayingsoftheCentury","price":895,"timestamp":1589191587},
+        {"category":"22","author":"2avc","price":895,"timestamp":1589191487},
+        {"category":"33","author":"3avc","title":"SayingsoftheCentury","timestamp":1589191387}
+    ],
+    "comments": ["3 records", "there will be 3 rows"]
+}
+```
+
+To load only `category`, `author`, and `price` from `example3.json`, run the following command:
+
+```SQL
+LOAD LABEL test_db.label17
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example3.csv")
+    INTO TABLE tbl1
+    FORMAT AS "json"
+    (category, price, author)
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+)
+PROPERTIES
+(
+    "json_root"="$.RECORDS",
+    "strip_outer_array" = "true",
+    "jsonpaths" = "[\"$.category\",\"$.price\",\"$.author\"]"
+);
+```
+
+> **NOTE**
+>
+> In the preceding example, the outermost layer of the JSON data is an array structure as indicated by a pair of square brackets `[]`. The array structure consists of multiple JSON objects that each represent a data record. Therefore, you need to set `strip_outer_array` to `true` to strip the outermost array structure. The keys `title` and `timestamp` that you do not want to load are ignored during loading. Additionally, the `json_root` parameter is used to specify the root element, which is an array, of the JSON data.
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/CANCEL_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/CANCEL_LOAD.md
new file mode 100644
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+++ b/docs/en/sql-reference/sql-statements/loading_unloading/CANCEL_LOAD.md
@@ -0,0 +1,43 @@
+---
+displayed_sidebar: docs
+---
+
+# CANCEL LOAD
+
+## Description
+
+Cancels a given load job: [Broker Load](BROKER_LOAD.md), [Spark Load](SPARK_LOAD.md), or [INSERT](INSERT.md). A load job in the `PREPARED`, `CANCELLED` or `FINISHED` state cannot be canceled.
+
+Canceling a load job is an asynchronous process. You can use the [SHOW LOAD](SHOW_LOAD.md) statement to check whether a load job is successfully canceled. The load job is successfully canceled if the value of `State` is `CANCELLED` and the value of `type` (displayed in `ErrorMsg`) is `USER_CANCEL`.
+
+## Syntax
+
+```SQL
+CANCEL LOAD
+[FROM db_name]
+WHERE LABEL = "label_name"
+```
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                              |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| db_name       | No           | The name of the database to which the load job belongs. If this parameter is not specified, a load job in your current database is canceled by default. |
+| label_name    | Yes          | The label of the load job.                                   |
+
+## Examples
+
+Example 1: Cancel the load job whose label is `example_label` in the current database.
+
+```SQL
+CANCEL LOAD
+WHERE LABEL = "example_label";
+```
+
+Example 2: Cancel the load job whose label is `example_label` in the `example_db` database.
+
+```SQL
+CANCEL LOAD
+FROM example_db
+WHERE LABEL = "example_label";
+```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/ETL/DROP_TASK.md b/docs/en/sql-reference/sql-statements/loading_unloading/ETL/DROP_TASK.md
new file mode 100644
index 00000000000000..2e07a605d2f7bc
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/ETL/DROP_TASK.md
@@ -0,0 +1,61 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP TASK
+
+## Description
+
+Drops an asynchronous ETL task submitted using [SUBMIT TASK](SUBMIT_TASK.md). This feature has been supported since StarRocks v2.5.7.
+
+> **NOTE**
+>
+> Dropping a task with DROP TASK simultaneously cancels the corresponding TaskRun.
+
+## Syntax
+
+```SQL
+DROP TASK `<task_name>` [FORCE]
+```
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**               |
+| ------------- | ------------ | ----------------------------- |
+| task_name     | Yes          | The name of the task to drop. Please wrap the task name with backticks (`) to prevent any parse failure. |
+| FORCE         | No           | Forces to drop the task. |
+
+## Usage notes
+
+You can check the information of asynchronous tasks by querying the metadata views `tasks` and `task_runs` in Information Schema.
+
+```SQL
+SELECT * FROM INFORMATION_SCHEMA.tasks;
+SELECT * FROM information_schema.tasks WHERE task_name = '<task_name>';
+SELECT * FROM information_schema.task_runs;
+SELECT * FROM information_schema.task_runs WHERE task_name = '<task_name>';
+```
+
+You can obtain the `task_name` of materialized view refresh tasks by using the SHOW MATERIALIZED VIEWS statement.
+
+```SQL
+SHOW MATERIALIZED VIEWS;
+SHOW MATERIALIZED VIEWS WHERE name = '<mv_name>';
+```
+
+## Examples
+
+```Plain
+MySQL > SUBMIT /*+set_var(query_timeout=100000)*/ TASK `ctas` AS
+    -> CREATE TABLE insert_wiki_edit_new
+    -> AS SELECT * FROM source_wiki_edit;
++----------+-----------+
+| TaskName | Status    |
++----------+-----------+
+| ctas     | SUBMITTED |
++----------+-----------+
+1 row in set (1.19 sec)
+
+MySQL > DROP TASK `ctas`;
+Query OK, 0 rows affected (0.35 sec)
+```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/ETL/SUBMIT_TASK.md b/docs/en/sql-reference/sql-statements/loading_unloading/ETL/SUBMIT_TASK.md
new file mode 100644
index 00000000000000..1f66f6d354311c
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/ETL/SUBMIT_TASK.md
@@ -0,0 +1,119 @@
+---
+displayed_sidebar: docs
+---
+
+# SUBMIT TASK
+
+## Description
+
+Submits an ETL statement as an asynchronous task.
+
+You can use this statement to:
+
+- execute long-running tasks in the background (supported from v2.5 onwards)
+- schedule a task at a regular interval (supported from v3.3 onwards)
+
+Supported statements include:
+
+- [CREATE TABLE AS SELECT](../../table_bucket_part_index/CREATE_TABLE_AS_SELECT.md) (from v3.0 onwards)
+- [INSERT](../INSERT.md) (from v3.0 onwards)
+- [CACHE SELECT](../../../../data_source/data_cache_warmup.md) (from v3.3 onwards)
+
+You can view the list of tasks by querying `INFORMATION_SCHEMA.tasks`, or view the execution history of tasks by querying `INFORMATION_SCHEMA.task_runs`. For more information, see [Usage Notes](#usage-notes).
+
+You can drop an asynchronous task using [DROP TASK](DROP_TASK.md).
+
+## Syntax
+
+```SQL
+SUBMIT TASK <task_name> 
+[SCHEDULE [START(<schedule_start>)] EVERY(INTERVAL <schedule_interval>) ]
+[PROPERTIES(<"key" = "value"[, ...]>)]
+AS <etl_statement>
+```
+
+## Parameters
+
+| **Parameter**      | **Required** | **Description**                                                                                     |
+| -------------      | ------------ | ---------------------------------------------------------------------------------------------------- |
+| task_name          | Yes     | The name of the task.                                                                               |
+| schedule_start     | No      | The start time for the scheduled task.                                                                 |
+| schedule_interval  | No      | The interval at which the scheduled task is executed, with a minimum interval of 10 seconds.          |
+| etl_statement      | Yes     | The ETL statement that you want to submit as an asynchronous task. StarRocks currently supports submitting asynchronous tasks for [CREATE TABLE AS SELECT](../../table_bucket_part_index/CREATE_TABLE_AS_SELECT.md) and [INSERT](../../loading_unloading/INSERT.md). |
+
+## Usage notes
+
+This statement creates a Task, which is a template for storing a task that executes the ETL statement. You can check the information of the Task by querying the metadata view [`tasks` in Information Schema](../../../information_schema/tasks.md).
+
+```SQL
+SELECT * FROM INFORMATION_SCHEMA.tasks;
+SELECT * FROM information_schema.tasks WHERE task_name = '<task_name>';
+```
+
+After you run the Task, a TaskRun is generated accordingly. A TaskRun indicates a task that executes the ETL statement. A TaskRun has the following states:
+
+- `PENDING`: The task waits to be run.
+- `RUNNING`: The task is running.
+- `FAILED`: The task failed.
+- `SUCCESS`: The task runs successfully.
+
+You can check the state of a TaskRun by querying the metadata view [`task_runs` in Information Schema](../../../information_schema/task_runs.md).
+
+```SQL
+SELECT * FROM INFORMATION_SCHEMA.task_runs;
+SELECT * FROM information_schema.task_runs WHERE task_name = '<task_name>';
+```
+
+## Configure via FE configuration items
+
+You can configure asynchronous ETL tasks using the following FE configuration items:
+
+| **Parameter**                | **Default value** | **Description**                                              |
+| ---------------------------- | ----------------- | ------------------------------------------------------------ |
+| task_ttl_second              | 86400             | The period during which a Task is valid. Unit: seconds. Tasks that exceed the validity period are deleted. |
+| task_check_interval_second   | 3600              | The time interval to delete invalid Tasks. Unit: seconds.    |
+| task_runs_ttl_second         | 86400             | The period during which a TaskRun is valid. Unit: seconds. TaskRuns that exceed the validity period are deleted automatically. Additionally, TaskRuns in the `FAILED` and `SUCCESS` states are also deleted automatically. |
+| task_runs_concurrency        | 4                 | The maximum number of TaskRuns that can be run in parallel.  |
+| task_runs_queue_length       | 500               | The maximum number of TaskRuns that are pending for running. If the number exceeds the default value, the incoming tasks will be suspended. |
+| task_runs_max_history_number | 10000             | The maximum number of TaskRun records to retain. |
+| task_min_schedule_interval_s | 10                | The minimum interval for Task execution. Unit: seconds. |
+
+## Examples
+
+Example 1: Submit an asynchronous task for `CREATE TABLE tbl1 AS SELECT * FROM src_tbl`, and specify the task name as `etl0`:
+
+```SQL
+SUBMIT TASK etl0 AS CREATE TABLE tbl1 AS SELECT * FROM src_tbl;
+```
+
+Example 2: Submit an asynchronous task for `INSERT INTO tbl2 SELECT * FROM src_tbl`, and specify the task name as `etl1`:
+
+```SQL
+SUBMIT TASK etl1 AS INSERT INTO tbl2 SELECT * FROM src_tbl;
+```
+
+Example 3: Submit an asynchronous task for `INSERT OVERWRITE tbl3 SELECT * FROM src_tbl`:
+
+```SQL
+SUBMIT TASK AS INSERT OVERWRITE tbl3 SELECT * FROM src_tbl;
+```
+
+Example 4: Submit an asynchronous task for `INSERT OVERWRITE insert_wiki_edit SELECT * FROM source_wiki_edit` without specifying the task name, and extend the query timeout to `100000` seconds using the hint:
+
+```SQL
+SUBMIT /*+set_var(query_timeout=100000)*/ TASK AS
+INSERT OVERWRITE insert_wiki_edit
+SELECT * FROM source_wiki_edit;
+```
+
+Example 5: Create an asynchronous task for an INSERT OVERWRITE statement. The task will be regularly executed at an interval of 1 minute.
+
+```SQL
+SUBMIT TASK
+SCHEDULE EVERY(INTERVAL 1 MINUTE)
+AS
+INSERT OVERWRITE insert_wiki_edit
+    SELECT dt, user_id, count(*) 
+    FROM source_wiki_edit 
+    GROUP BY dt, user_id;
+```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/INSERT.md b/docs/en/sql-reference/sql-statements/loading_unloading/INSERT.md
new file mode 100644
index 00000000000000..1133b054ecfcfd
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/INSERT.md
@@ -0,0 +1,130 @@
+---
+displayed_sidebar: docs
+---
+
+# INSERT
+
+## Description
+
+Inserts data into a specific table or overwrites a specific table with data. For detailed information about the application scenarios, see [Load data with INSERT](../../../loading/InsertInto.md). From v3.2.0 onwards, INSERT supports writing data into files in remote storage. You can [use INSERT INTO FILES() to unload data from StarRocks to remote storage](../../../unloading/unload_using_insert_into_files.md).
+
+You can submit an asynchronous INSERT task using [SUBMIT TASK](ETL/SUBMIT_TASK.md).
+
+## Syntax
+
+- **Data loading**:
+
+  ```sql
+  INSERT { INTO | OVERWRITE } [db_name.]<table_name>
+  [ PARTITION (<partition_name> [, ...] ) ]
+  [ TEMPORARY PARTITION (<temporary_partition_name> [, ...] ) ]
+  [ WITH LABEL <label>]
+  [ (<column_name>[, ...]) ]
+  { VALUES ( { <expression> | DEFAULT } [, ...] ) | <query> }
+  ```
+
+- **Data unloading**:
+
+  ```sql
+  INSERT INTO FILES()
+  [ WITH LABEL <label> ]
+  { VALUES ( { <expression> | DEFAULT } [, ...] ) | <query> }
+  ```
+
+## Parameters
+
+| **Parameter** | Description                                                  |
+| ------------- | ------------------------------------------------------------ |
+| INTO          | To append data to the table.                                 |
+| OVERWRITE     | To overwrite the table with data.                            |
+| table_name    | The name of the table into which you want to load data. It can be specified with the database the table resides as `db_name.table_name`. |
+| PARTITION    |  The partitions into which you want to load the data. You can specify multiple partitions, which must be separated by commas (,). It must be set to partitions that exist in the destination table. If you specify this parameter, the data will be inserted only into the specified partitions. If you do not specify this parameter, the data will be inserted into all partitions. |
+| TEMPORARY PARTITION |The name of the [temporary partition](../../../table_design/Temporary_partition.md) into which you want to load data. You can specify multiple temporary partitions, which must be separated by commas (,).|
+| label         | The unique identification label for each data load transaction within the database. If it is not specified, the system automatically generates one for the transaction. We recommend you specify the label for the transaction. Otherwise, you cannot check the transaction status if a connection error occurs and no result is returned. You can check the transaction status via `SHOW LOAD WHERE label="label"` statement. For the naming conventions of labels, see [System Limits](../../System_limit.md). |
+| column_name   | The name of the destination column(s) to load data in. It must be set as columns that exist in the destination table. The destination columns you specify are mapped one on one in sequence to the columns of the source table, regardless of what the destination column names are. If no destination column is specified, the default value is all columns in the destination table. If the specified column in the source table does not exist in the destination column, the default value will be written to this column, and the transaction will fail if the specified column does not have a default value. If the column type of the source table is inconsistent with that of the destination table, the system will perform an implicit conversion on the mismatched column. If the conversion fails, a syntax parsing error will be returned.<br />**NOTE**<br />From v3.3.1, specifying a column list in the INSERT INTO statement on a Primary Key table will perform Partial Updates (instead of Full Upsert in earlier versions). If the column list is not specified, the system will perform Full Upsert. |
+| expression    | Expression that assigns values to the column.                |
+| DEFAULT       | Assigns default value to the column.                         |
+| query         | Query statement whose result will be loaded into the destination table. It can be any SQL statement supported by StarRocks. |
+| FILES()       | Table function [FILES()](../../sql-functions/table-functions/files.md). You can use this function to unload data into remote storage. For more information, see [Use INSERT INTO FILES() to unload data to remote storage](../../../unloading/unload_using_insert_into_files.md). |
+
+## Return
+
+```Plain
+Query OK, 5 rows affected, 2 warnings (0.05 sec)
+{'label':'insert_load_test', 'status':'VISIBLE', 'txnId':'1008'}
+```
+
+| Return        | Description                                                  |
+| ------------- | ------------------------------------------------------------ |
+| rows affected | Indicates how many rows are loaded. `warnings` indicates the rows that are filtered out. |
+| label         | The unique identification label for each data load transaction within the database. It can be assigned by user or automatically by the system. |
+| status        | Indicates if the loaded data is visible. `VISIBLE`: the data is successfully loaded and visible. `COMMITTED`: the data is successfully loaded but invisible for now. |
+| txnId         | The ID number corresponding to each INSERT transaction.      |
+
+## Usage notes
+
+- As for the current version, when StarRocks executes the INSERT INTO statement, if any row of data mismatches the destination table format (for example, the string is too long), the INSERT transaction fails by default. You can set the session variable `enable_insert_strict` to `false` so that the system filters out the data that mismatches the destination table format and continues to execute the transaction.
+
+- After INSERT OVERWRITE statement is executed, StarRocks creates temporary partitions for the partitions that store the original data, inserts data into the temporary partitions, and swaps the original partitions with the temporary partitions. All these operations are executed in the Leader FE node. Therefore, if the Leader FE node crashes while executing INSERT OVERWRITE statement, the whole load transaction fails, and the temporary partitions are deleted.
+
+## Example
+
+The following examples are based on table `test`, which contains two columns `c1` and `c2`. The `c2` column has a default value of DEFAULT.
+
+- Import a row of data into the `test` table.
+
+```SQL
+INSERT INTO test VALUES (1, 2);
+INSERT INTO test (c1, c2) VALUES (1, 2);
+INSERT INTO test (c1, c2) VALUES (1, DEFAULT);
+INSERT INTO test (c1) VALUES (1);
+```
+
+When no destination column is specified, the columns are loaded in sequence into the destination table by default. Therefore, in the above example, the outcomes of the first and second SQL statements are the same.
+
+If a destination column (with or without data inserted) uses DEFAULT as the value, the column will use the default value as the loaded data. Therefore, in the above example, the outputs of the third and fourth statements are the same.
+
+- Load multiple rows of data into the `test` table at one time.
+
+```SQL
+INSERT INTO test VALUES (1, 2), (3, 2 + 2);
+INSERT INTO test (c1, c2) VALUES (1, 2), (3, 2 * 2);
+INSERT INTO test (c1, c2) VALUES (1, DEFAULT), (3, DEFAULT);
+INSERT INTO test (c1) VALUES (1), (3);
+```
+
+Because the results of expressions are equivalent, the outcomes of the first and second statements are the same. The outcomes of the third and fourth statements are the same because they both use default value.
+
+- Import a query statement result into the `test` table.
+
+```SQL
+INSERT INTO test SELECT * FROM test2;
+INSERT INTO test (c1, c2) SELECT * from test2;
+```
+
+- Import a query result into the `test` table, and specify partition and label.
+
+```SQL
+INSERT INTO test PARTITION(p1, p2) WITH LABEL `label1` SELECT * FROM test2;
+INSERT INTO test WITH LABEL `label1` (c1, c2) SELECT * from test2;
+```
+
+- Overwrite the `test` table with a query result, and specify partition and label.
+
+```SQL
+INSERT OVERWRITE test PARTITION(p1, p2) WITH LABEL `label1` SELECT * FROM test3;
+INSERT OVERWRITE test WITH LABEL `label1` (c1, c2) SELECT * from test3;
+```
+
+The following example inserts data rows from the Parquet file **parquet/insert_wiki_edit_append.parquet** within the AWS S3 bucket `inserttest` into the table `insert_wiki_edit`:
+
+```Plain
+INSERT INTO insert_wiki_edit
+    SELECT * FROM FILES(
+        "path" = "s3://inserttest/parquet/insert_wiki_edit_append.parquet",
+        "format" = "parquet",
+        "aws.s3.access_key" = "XXXXXXXXXX",
+        "aws.s3.secret_key" = "YYYYYYYYYY",
+        "aws.s3.region" = "ap-southeast-1"
+);
+```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md
new file mode 100644
index 00000000000000..f7f7eeb2fa3074
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md
@@ -0,0 +1,176 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW LOAD
+
+## Description
+
+Displays information of all load jobs or given load jobs in a database. This statement can only display load jobs that are created by using [Broker Load](BROKER_LOAD.md), [INSERT](../data-mSPARK_LOAD.mdLoad](../loading_unloading/SPARK_LOAD.md). You can also view information of load jobs via the `curl` command. From v3.1 onwards, we recommend that you use the [SELECT](../table_bucket_part_index/SELECT.md) statement to query the results of Broker Load or Insert jobs from the [`loads`](../../information_schema/loads.md) table in the `information_schema` database. For more information, see [Load data from HDFS](../../../loading/hdfs_load.md), [Load data from cloud storage](../../../loading/cloud_storage_load.md), [Load data using INSERT](../../../loading/InsertInto.md), and [Bulk load using Apache Spark™](../../../loading/SparkLoad.md).
+
+In addition to the preceding loading methods, StarRocks supports using Stream Load and Routine Load to load data. Stream Load is a synchronous operation and will directly return information of Stream Load jobs. Routine Load is an asynchronous operation where you can use the [SHOW ROUTINE LOAD](routine_load/SHOW_ROUTINE_LOAD.md) statement to display information of Routine Load jobs.
+
+## Syntax
+
+```SQL
+SHOW LOAD [ FROM db_name ]
+[
+   WHERE [ LABEL { = "label_name" | LIKE "label_matcher" } ]
+         [ [AND] STATE = { "PENDING" | "ETL" | "LOADING" | "FINISHED" | "CANCELLED" } ]
+]
+[ ORDER BY field_name [ ASC | DESC ] ]
+[ LIMIT { [offset, ] limit | limit OFFSET offset } ]
+```
+
+> **Note**
+>
+> You can add the `\G` option to the statement (such as `SHOW LOAD WHERE LABEL = "label1"\G;`) to vertically display output rather than in the usual horizontal table format. For more information, see [Example 1](#examples).
+
+## Parameters
+
+| **Parameter**                     | **Required** | **Description**                                              |
+| --------------------------------- | ------------ | ------------------------------------------------------------ |
+| db_name                           | No           | The database name. If this parameter is not specified, your current database is used by default. |
+| LABEL = "label_name"              | No           | The labels of load jobs.                                     |
+| LABEL LIKE "label_matcher"        | No           | If this parameter is specified, the information of load jobs whose labels contain `label_matcher` is returned. |
+| AND                               | No           | <ul><li>If you specify only one filter condition in the WHERE clause, do not specify this keyword. Example: `WHERE STATE = "PENDING"`.</li><li>If you specify two or three filter conditions in the WHERE clause, you must specify this keyword. Example: `WHERE LABEL = "label_name" AND STATE = "PENDING"`. </li></ul>|
+| STATE                             | No           | The states of load jobs. The states vary based on loading methods.<ul><li>Broker Load<ul><li>`PENDING`: The load job is created.</li><li>`QUEUEING`: The load job is in the queue waiting to be scheduled.</li><li>`LOADING`: The load job is running.</li><li>`PREPARED`: The transaction has been committed.</li><li>`FINISHED`: The load job succeeded.</li><li>`CANCELLED`: The load job failed.</li></ul></li><li>Spark Load<ul><li>`PENDING`: Your StarRocks cluster is preparing configurations related to ETL and then submits an ETL job to your Apache Spark™ cluster.</li><li>`ETL`: Your Spark cluster is executing the ETL job and then writes the data into the corresponding HDFS cluster.</li><li>`LOADING`: The data in the HDFS cluster is being loaded to your StarRocks cluster, which means the load job is running.</li><li>`PREPARED`: The transaction has been committed.</li><li>`FINISHED`: The load job succeeded.</li><li>`CANCELLED`: The load job failed.</li></ul></li><li>INSERT<ul><li>`FINISHED`: The load job succeeded.</li><li>`CANCELLED`: The load job failed.</li></ul></li></ul>If the `STATE` parameter is not specified, the information of load jobs in all states is returned by default. If the `STATE` parameter is specified, only the information of load jobs in the given state is returned. For example, `STATE = "PENDING"` returns the information of load jobs in the `PENDING` state. |
+| ORDER BY field_name [ASC \| DESC] | No           | If this parameter is specified, the output is sorted in ascending or descending order based on a field. The following fields are supported: `JobId`, `Label`, `State`, `Progress`, `Type`, `EtlInfo`, `TaskInfo`, `ErrorMsg`, `CreateTime`, `EtlStartTime`, `EtlFinishTime`, `LoadStartTime`, `LoadFinishTime`, `URL`, and `JobDetails`.<ul><li>To sort the output in ascending order, specify `ORDER BY field_name ASC`.</li><li>To sort the output in descending order, specify `ORDER BY field_name DESC`.</li></ul>If you do not specify the field and the sort order, the output is sorted in ascending order of `JobId` by default. |
+| LIMIT limit                       | No           | The number of load jobs that are allowed to display. If this parameter is not specified, the information of all load jobs that match the filter conditions are displayed. If this parameter is specified, for example, `LIMIT 10`, only the information of 10 load jobs that match filter conditions are returned. |
+| OFFSET offset                     | No           | The `offset` parameter defines the number of load jobs to be skipped. For example, `OFFSET 5` skips the first five load jobs and returns the rest. The value of the `offset` parameter defaults to `0`. |
+
+## Output
+
+```SQL
++-------+-------+-------+----------+------+---------+----------+----------+------------+--------------+---------------+---------------+----------------+-----+------------+
+| JobId | Label | State | Progress | Type | Priority | EtlInfo | TaskInfo | ErrorMsg | CreateTime | EtlStartTime | EtlFinishTime | LoadStartTime | LoadFinishTime | URL | JobDetails |
++-------+-------+-------+----------+------+---------+----------+----------+------------+--------------+---------------+---------------+----------------+-----+------------+
+```
+
+The output of this statement varies based on loading methods.
+
+| **Field**      | **Broker Load**                                              | **Spark Load**                                               | **INSERT**                                                   |
+| -------------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
+| JobId          | The unique ID assigned by StarRocks to identify the load job in your StarRocks cluster. | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The field has the same meaning in a INSERT job as it does in a Broker Load job. |
+| Label          | The label of the load job. The label of a load job is unique within a database but can be duplicate across different databases. | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The field has the same meaning in a INSERT job as it does in a Broker Load job. |
+| State          | The state of the load job.<ul><li>`PENDING`: The load job is created.</li><li>`QUEUEING`: The load job is in the queue waiting to be scheduled.</li><li>`LOADING`: The load job is running.</li><li>`PREPARED`: The transaction has been committed.</li><li>`FINISHED`: The load job succeeded.</li><li>`CANCELLED`: The load job failed.</li></ul> | The state of the load job.<ul><li>`PENDING`: Your StarRocks cluster is preparing configurations related to ETL and then submits an ETL job to your Spark cluster.</li><li>`ETL`: Your Spark cluster is executing the ETL job and then writes the data into the corresponding HDFS cluster.</li><li>`LOADING`: The data in the HDFS cluster is being loaded to your StarRocks cluster, which means the load job is running.</li><li>`PREPARED`: The transaction has been committed.</li><li>`FINISHED`: The load job succeeded.</li><li>`CANCELLED`: The load job failed.</li></ul> | The state of the load job.<ul><li>`FINISHED`: The load job succeeded.</li><li>`CANCELLED`: The load job failed.</li></ul> |
+| Progress       | The stage of the load job. A Broker Load job only has the `LOAD` stage, which ranges from 0% to 100% to describe the progress of the stage. When the load job enters the `LOAD` stage, `LOADING` is returned for the `State` parameter. A Broker Load job does not have the `ETL` stage. The `ETL` parameter is valid only for a Spark Load job.<br />**Note**<ul><li>The formula to calculate the progress of the `LOAD` stage: Number of StarRocks tables that complete data loading/Number of StarRocks tables that you plan to load data into * 100%.</li><li>When all data is loaded into StarRocks, `99%` is returned for the `LOAD` parameter. Then, loaded data starts taking effect in StarRocks. After the data takes effect, `100%` is returned for the `LOAD` parameter.</li><li>The progress of the `LOAD` stage is not linear. Therefore, the value of the `LOAD` parameter may not change over a period of time even if data loading is still ongoing.</li></ul> | The stage of the load job. A Spark Load job has two stages:<ul><li>`ETL`: ranges from 0% to 100% to describe the progress of the `ETL` stage.</li><li>`LOAD`: ranges from 0% to 100% to describe the progress of the `Load` stage. </li></ul>When the load job enters the `ETL` stage, `ETL` is returned for the `State` parameter. When the load job moves to the `LOAD` stage, `LOADING` is returned for the `State` parameter. <br />The **Note** is the same as those for Broker Load. | The stage of the load job. An INSERT job only has the `LOAD` stage, which ranges from 0% to 100% to describe the progress of the stage. When the load job enters the `LOAD` stage, `LOADING` is returned for the `State` parameter. An INSERT job does not have the `ETL` stage. The `ETL` parameter is valid only for a Spark Load job.<br />The **Note** is the same as those for Broker Load. |
+| Type           | The method of the load job. The value of this parameter defaults to `BROKER`. | The method of the load job. The value of this parameter defaults to `SPARK`. | The method of the load job. The value of this parameter defaults to `INSERT`. |
+| Priority       | The priority of the load job. Valid values: LOWEST, LOW, NORMAL, HIGH, and HIGHEST. | - | - |
+| EtlInfo        | The metrics related to ETL.<ul><li>`unselected.rows`: The number of rows that are filtered out by the WHERE clause.</li><li>`dpp.abnorm.ALL`: The number of rows that are filtered out due to data quality issues, which refers to mismatches between source tables and StarRocks tables in, for example, the data type and the number of columns.</li><li>`dpp.norm.ALL`: The number of rows that are loaded into your StarRocks cluster.</li></ul>The sum of the preceding metrics is the total number of rows of raw data. You can use the following formula to calculate whether the percentage of unqualified data exceeds the value of the `max-filter-ratio` parameter:`dpp.abnorm.ALL`/(`unselected.rows` + `dpp.abnorm.ALL` + `dpp.norm.ALL`). | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The metrics related to ETL. An INSERT job does not have the `ETL` stage. Therefore, `NULL` is returned. |
+| TaskInfo       | The parameters that are specified when you create the load job.<ul><li>`resource`: This parameter is valid only in a Spark Load job.</li><li>`timeout`: The time period that a load job is allowed to run. Unit: seconds.</li><li>`max-filter-ratio`: The largest percentage of rows that are filtered out due to data quality issues.</li></ul>For more information, see [BROKER LOAD](BROKER_LOAD.md). | The parameters that are specified when you create the load job.<ul><li>`resource`: The resource name.</li><li>`timeout`: The time period that a load job is allowed to run. Unit: seconds.</li><li>`max-filter-ratio`: The largest percentage of rows that are filtered out due to data quality issues.</li></ul>For more information, see [SPARK LOAD](SPARK_LOAD.md). | The parameters that are specified when you create the load job.<ul><li>`resource`: This parameter is valid only in a Spark Load job.</li><li>`timeout`: The time period that a load job is allowed to run. Unit: seconds.</li><li>`max-filter-ratio`: The largest percentage of rows that are filtered out due to data quality issues.</li></ul>For more information, see [INSERT](./INSERT.md). |../data-manipulation/INSERT.md
+| ErrorMsg       | The error message returned when the load job fails. When the state of the loading job is `PENDING`, `LOADING`, or `FINISHED`, `NULL` is returned for the `ErrorMsg` field. When the state of the loading job is `CANCELLED`, the value returned for the `ErrorMsg` field consists of two parts: `type` and `msg`.<ul><li>The `type` part can be any of the following values:<ul><li>`USER_CANCEL`: The load job was manually canceled.</li><li>`ETL_SUBMIT_FAIL`: The load job failed to be submitted.</li><li>`ETL-QUALITY-UNSATISFIED`: The load job failed because the percentage of unqualified data exceeds the value of the `max-filter-ratio` parameter.</li><li>`LOAD-RUN-FAIL`: The load job failed in the `LOAD` stage.</li><li>`TIMEOUT`: The load job failed to finish within the specified timeout period.</li><li>`UNKNOWN`: The load job failed due to an unknown error.</li></ul></li><li>The `msg` part provides the detailed cause of the load failure.</li></ul> | The error message returned when the load job fails. When the state of the loading job is `PENDING`, `LOADING`, or `FINISHED`, `NULL` is returned for the `ErrorMsg` field. When the state of the loading job is `CANCELLED`, the value returned for the `ErrorMsg` field consists of two parts: `type` and `msg`.<ul><li>The `type` part can be any of the following values:<ul><li>`USER_CANCEL`: The load job was manually canceled.</li><li>`ETL_SUBMIT_FAIL`: StarRocks failed to submit an ETL job to Spark.</li><li>`ETL-RUN-FAIL`: Spark failed to execute the ETL job. </li><li>`ETL-QUALITY-UNSATISFIED`: The load job failed because the percentage of unqualified data exceeds the value of the `max-filter-ratio` parameter.</li><li>`LOAD-RUN-FAIL`: The load job failed in the `LOAD` stage.</li><li>`TIMEOUT`: The load job failed to finish within the specified timeout period.</li><li>`UNKNOWN`: The load job failed due to an unknown error.</li></ul></li><li>The `msg` part provides the detailed cause of the load failure.</li></ul> | The error message returned when the load job fails. When the state of the loading job is `FINISHED`, `NULL` is returned for the `ErrorMsg` field. When the state of the loading job is `CANCELLED`, the value returned for the `ErrorMsg` field consists of two parts: `type` and `msg`.<ul><li>The `type` part can be any of the following values:<ul><li>`USER_CANCEL`: The load job was manually canceled.</li><li>`ETL_SUBMIT_FAIL`: The load job failed to be submitted.</li><li>`ETL_RUN_FAIL`: The load job failed to run.</li><li>`ETL_QUALITY_UNSATISFIED`: The load job failed due to quality issues of raw data.</li><li>`LOAD-RUN-FAIL`: The load job failed in the `LOAD` stage.</li><li>`TIMEOUT`: The load job failed to finish within the specified timeout period.</li><li>`UNKNOWN`: The load job failed due to an unknown error.</li><li>`TXN_UNKNOWN`: The load job failed because the state of the transaction of the load job is unknown.</li></ul></li><li>The `msg` part provides the detailed cause of the load failure.</li></ul> |
+| CreateTime     | The time at which the load job was created.                  | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The field has the same meaning in a INSERT job as it does in a Broker Load job. |
+| EtlStartTime   | A Broker Load job does not have the `ETL` stage. Therefore, the value of this field is the same as the value of the `LoadStartTime` field. | The time at which the `ETL` stage starts.                    | An INSERT job does not have the `ETL` stage. Therefore, the value of this field is the same as the value of the `LoadStartTime` field. |
+| EtlFinishTime  | A Broker Load job does not have the `ETL` stage. Therefore, the value of this field is the same as the value of the `LoadStartTime` field. | The time at which the `ETL` stage finishes.                  | An INSERT job does not have the `ETL` stage. Therefore, the value of this field is the same as the value of the `LoadStartTime` field. |
+| LoadStartTime  | The time at which the `LOAD` stage starts.                   | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The field has the same meaning in a INSERT job as it does in a Broker Load job. |
+| LoadFinishTime | The time at which the load job finishes.                     | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The field has the same meaning in a INSERT job as it does in a Broker Load job. |
+| URL            | The URL that is used to access the unqualified data detected in the load job. You can use the `curl` or `wget` command to access the URL and obtain the unqualified data. If no unqualified data is detected, `NULL` is returned. | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The field has the same meaning in a INSERT job as it does in a Broker Load job. |
+| JobDetails     | Other information related to the load job.<ul><li>`Unfinished backends`: The ID of the BE that does not complete data loading.</li><li>`ScannedRows`: The total number of rows that are loaded into StarRocks and the number of rows that are filtered out.</li><li>`TaskNumber`: A load job can be split into one or more tasks that concurrently run. This field indicates the number of load tasks.</li><li>`All backends`: The ID of the BE that is executing data loading.</li><li>`FileNumber`: The number of source data files.</li><li>`FileSize`: The data volume of source data files. Unit: bytes.</li></ul> | The field has the same meaning in a Spark Load job as it does in a Broker Load job. | The field has the same meaning in a INSERT job as it does in a Broker Load job. |
+
+## Usage notes
+
+- The information returned by the SHOW LOAD statement is valid for 3 days from `LoadFinishTime` of a load job. After 3 days, the information cannot be displayed. You can use the `label_keep_max_second` parameter to modify the default validity period.
+
+    ```SQL
+    ADMIN SET FRONTEND CONFIG ("label_keep_max_second" = "value");
+    ```
+
+- If the value of the `LoadStartTime` field is `N/A` for a long time, it means that load jobs heavily pile up. We recommended that you reduce the frequency of creating load jobs.
+- Total time period consumed by a load job = `LoadFinishTime` - `CreateTime`.
+- Total time period a load job consumed in the `LOAD` stage = `LoadFinishTime` - `LoadStartTime`.
+
+## Examples
+
+Example 1: Vertically display all load jobs in your current database.
+
+```plaintext
+SHOW LOAD\G
+*************************** 1. row ***************************
+         JobId: 976331
+         Label: duplicate_table_with_null
+         State: FINISHED
+      Progress: ETL:100%; LOAD:100%
+          Type: BROKER
+      Priority: NORMAL
+       EtlInfo: unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546
+      TaskInfo: resource:N/A; timeout(s):300; max_filter_ratio:0.0
+      ErrorMsg: NULL
+    CreateTime: 2022-10-17 19:35:00
+  EtlStartTime: 2022-10-17 19:35:04
+ EtlFinishTime: 2022-10-17 19:35:04
+ LoadStartTime: 2022-10-17 19:35:04
+LoadFinishTime: 2022-10-17 19:35:06
+           URL: NULL
+    JobDetails: {"Unfinished backends":{"b90a703c-6e5a-4fcb-a8e1-94eca5be0b8f":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"b90a703c-6e5a-4fcb-a8e1-94eca5be0b8f":[10004]},"FileNumber":1,"FileSize":548622}
+```
+
+Example 2: Display two load jobs whose labels contain the string `null` in your current database.
+
+```plaintext
+SHOW LOAD 
+WHERE LABEL LIKE "null" 
+LIMIT 2;
+
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| JobId | Label                     | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                                                                                | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL                                                                            | JobDetails                                                                                                                                                                                              |
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| 10082 | duplicate_table_with_null | FINISHED | ETL:100%; LOAD:100% | BROKER | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:N/A; timeout(s):300; max_filter_ratio:0.0                                                      | NULL     | 2022-08-02 14:53:27 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:31 | NULL                                                                           | {"Unfinished backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[10002]},"FileNumber":1,"FileSize":548622} |
+| 10103 | unique_table_with_null    | FINISHED | ETL:100%; LOAD:100% | SPARK  | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:test_spark_resource_07af473a_1230_11ed_b483_00163e0e550b; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:56:06 | 2022-08-02 14:56:19 | 2022-08-02 14:56:41 | 2022-08-02 14:56:41 | 2022-08-02 14:56:44 | http://emr-header-1.cluster-49091:20888/proxy/application_1655710334658_26391/ | {"Unfinished backends":{"00000000-0000-0000-0000-000000000000":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"00000000-0000-0000-0000-000000000000":[-1]},"FileNumber":1,"FileSize":8790855}   |
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
+
+Example 3: Display the load jobs whose labels contain the string `table` in `example_db`. In addition, the load jobs returned are displayed in descending order of the `LoadStartTime` field.
+
+```plaintext
+SHOW LOAD FROM example_db 
+WHERE LABEL Like "table" 
+ORDER BY LoadStartTime DESC;
+
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| JobId | Label                     | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                                                                                | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL                                                                            | JobDetails                                                                                                                                                                                              |
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| 10103 | unique_table_with_null    | FINISHED | ETL:100%; LOAD:100% | SPARK  | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:test_spark_resource_07af473a_1230_11ed_b483_00163e0e550b; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:56:06 | 2022-08-02 14:56:19 | 2022-08-02 14:56:41 | 2022-08-02 14:56:41 | 2022-08-02 14:56:44 | http://emr-header-1.cluster-49091:20888/proxy/application_1655710334658_26391/ | {"Unfinished backends":{"00000000-0000-0000-0000-000000000000":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"00000000-0000-0000-0000-000000000000":[-1]},"FileNumber":1,"FileSize":8790855}   |
+| 10082 | duplicate_table_with_null | FINISHED | ETL:100%; LOAD:100% | BROKER | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:N/A; timeout(s):300; max_filter_ratio:0.0                                                      | NULL     | 2022-08-02 14:53:27 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:31 | NULL                                                                           | {"Unfinished backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[10002]},"FileNumber":1,"FileSize":548622} |
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
+
+Example 4: Display the load job whose label is `duplicate_table_with_null` and state is `FINISHED` in `example_db`.
+
+```plaintext
+SHOW LOAD FROM example_db 
+WHERE LABEL = "duplicate_table_with_null" AND STATE = "FINISHED";
+
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+----------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| JobId | Label                     | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                           | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL  | JobDetails                                                                                                                                                                                              |
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+----------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| 10082 | duplicate_table_with_null | FINISHED | ETL:100%; LOAD:100% | BROKER | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:N/A; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:53:27 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:31 | NULL | {"Unfinished backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[10002]},"FileNumber":1,"FileSize":548622} |
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+----------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
+
+Example 5: Skip the first load job and display the next two load jobs. In addition, these two load jobs are sorted in ascending order.
+
+```plaintext
+SHOW LOAD FROM example_db 
+ORDER BY CreateTime ASC 
+LIMIT 2 OFFSET 1;
+```
+
+Or
+
+```plaintext
+SHOW LOAD FROM example_db 
+ORDER BY CreateTime ASC 
+LIMIT 1,2;
+```
+
+The output of the preceding statements is as follows.
+
+```plaintext
++-------+---------------------------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| JobId | Label                                       | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                                                                                | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL                                                                            | JobDetails                                                                                                                                                                                            |
++-------+---------------------------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| 10103 | unique_table_with_null                      | FINISHED | ETL:100%; LOAD:100% | SPARK  | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:test_spark_resource_07af473a_1230_11ed_b483_00163e0e550b; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:56:06 | 2022-08-02 14:56:19 | 2022-08-02 14:56:41 | 2022-08-02 14:56:41 | 2022-08-02 14:56:44 | http://emr-header-1.cluster-49091:20888/proxy/application_1655710334658_26391/ | {"Unfinished backends":{"00000000-0000-0000-0000-000000000000":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"00000000-0000-0000-0000-000000000000":[-1]},"FileNumber":1,"FileSize":8790855} |
+| 10120 | insert_3a57b595-1230-11ed-b075-00163e14c85e | FINISHED | ETL:100%; LOAD:100% | INSERT | NULL                                                    | resource:N/A; timeout(s):3600; max_filter_ratio:0.0                                                     | NULL     | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 |                                                                                | {"Unfinished backends":{},"ScannedRows":0,"TaskNumber":0,"All backends":{},"FileNumber":0,"FileSize":0}                                                                                               |
++-------+---------------------------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/SHOW_TRANSACTION.md b/docs/en/sql-reference/sql-statements/loading_unloading/SHOW_TRANSACTION.md
new file mode 100644
index 00000000000000..c9436c7b756900
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/SHOW_TRANSACTION.md
@@ -0,0 +1,65 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW TRANSACTION
+
+## Description
+
+This syntax is used to view the transaction details of the specified transaction id.
+
+Syntax:
+
+```sql
+SHOW TRANSACTION
+[FROM <db_name>]
+WHERE id = transaction_id
+```
+
+Examples of returned results:
+
+```plain text
+TransactionId: 4005
+Label: insert_8d807d5d-bcdd-46eb-be6d-3fa87aa4952d
+Coordinator: FE: 10.74.167.16
+TransactionStatus: VISIBLE
+LoadJobSourceType: INSERT_STREAMING
+PrepareTime: 2020-01-09 14:59:07
+CommitTime: 2020-01-09 14:59:09
+FinishTime: 2020-01-09 14:59:09
+Reason:
+ErrorReplicasCount: 0
+ListenerId: -1
+TimeoutMs: 300000
+```
+
+* TransactionId: transaction id
+* Label: import the label corresponding to the task
+* Coordinator: the node responsible for transaction coordination
+* TransactionStatus: transaction status
+* PREPARE: preparation stage
+* COMMITTED: the transaction succeeded, but the data is not visible
+* VISIBLE: the transaction is successful and the data is visible
+* ABORTED: transaction failed
+* LoadJobSourceType: type of import task.
+* PrepareTime: transaction start time
+* CommitTime: the time when the transaction is successfully committed
+* FinishTime: the time when the data is visible
+* Reason: error message
+* ErrorReplicasCount: number of replicas with errors
+* ListenerId: id of the related import job
+* TimeoutMs: transaction timeout, in milliseconds
+
+## Examples
+
+1. To view a transaction with id 4005:
+
+    ```sql
+    SHOW TRANSACTION WHERE ID=4005;
+    ```
+
+2. In the specified dB, view the transaction with id 4005:
+
+    ```sql
+    SHOW TRANSACTION FROM db WHERE ID=4005;
+    ```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md
new file mode 100644
index 00000000000000..93d10a22f32944
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md
@@ -0,0 +1,276 @@
+---
+displayed_sidebar: docs
+---
+
+# SPARK LOAD
+
+## Description
+
+Spark load preprocesses the imported data through external spark resources, improves the import performance of a large amount of StarRocks data, and saves the computing resources of StarRocks cluster. It is mainly used in the scenario of initial migration and large amount of data import into StarRocks.
+
+Spark load is an asynchronous import method. Users need to create Spark type import tasks through MySQL protocol and view the import results through`SHOW LOAD`.
+
+> **NOTICE**
+>
+> - You can load data into StarRocks tables only as a user who has the INSERT privilege on those StarRocks tables. If you do not have the INSERT privilege, follow the instructions provided in [GRANT](../account-management/GRANT.md) to grant the INSERT privilege to the user that you use to connect to your StarRocks cluster.
+> - When Spark Load is used to load data into a StarRocks table, the bucketing column of the StarRocks table cannot be of DATE, DATETIME, or DECIMAL type.
+
+Syntax
+
+```sql
+LOAD LABEL load_label
+(
+data_desc1[, data_desc2, ...]
+)
+WITH RESOURCE resource_name
+[resource_properties]
+[opt_properties]
+```
+
+1.load_label
+
+Label of the currently imported batch. Unique within a database.
+
+Syntax:
+
+```sql
+[database_name.]your_label
+```
+
+2.data_desc
+
+Used to describe a batch of imported data.
+
+Syntax:
+
+```sql
+DATA INFILE
+(
+"file_path1"[, file_path2, ...]
+)
+[NEGATIVE]
+INTO TABLE `table_name`
+[PARTITION (p1, p2)]
+[COLUMNS TERMINATED BY "column_separator"]
+[FORMAT AS "file_type"]
+[(column_list)]
+[COLUMNS FROM PATH AS (col2, ...)]
+[SET (k1 = func(k2))]
+[WHERE predicate]
+
+DATA FROM TABLE hive_external_tbl
+[NEGATIVE]
+INTO TABLE tbl_name
+[PARTITION (p1, p2)]
+[SET (k1=f1(xx), k2=f2(xx))]
+[WHERE predicate]
+```
+
+Note
+
+```plain text
+file_path:
+
+The file path can be specified to one file, or the * wildcard can be used to specify all files in a directory. Wildcards must match files, not directories.
+
+hive_external_tbl:
+
+hive external table name.
+It is required that the columns in the imported starrocks table must exist in the hive external table.
+Each load task only supports loading from one Hive external table.
+Cannot be used with file_ path mode at the same time.
+
+PARTITION:
+
+If this parameter is specified, only the specified partition will be imported, and the data outside the imported partition will be filtered out.
+If not specified, all partitions of table will be imported by default.
+
+NEGATIVE:
+
+If this parameter is specified, it is equivalent to loading a batch of "negative" data. Used to offset the same batch of previously imported data.
+This parameter is only applicable when the value column exists and the aggregation type of the value column is SUM only.
+
+column_separator:
+
+Specifies the column separator in the import file. Default is \ t
+If it is an invisible character, you need to prefix it with \ \ x and use hexadecimal to represent the separator.
+For example, the separator of hive file \ x01 is specified as "\ \ x01"
+
+file_type:
+
+Used to specify the type of imported file. Currently, supported file types are csv, orc, and parquet.
+
+column_list:
+
+Used to specify the correspondence between the columns in the import file and the columns in the table.
+When you need to skip a column in the import file, specify the column as a column name that does not exist in the table.
+
+Syntax:
+(col_name1, col_name2, ...)
+
+SET:
+
+If specify this parameter, you can convert a column of the source file according to the function, and then import the converted results into table. Syntax is column_name = expression.
+Only Spark SQL build_in functions are supported. Please refer to https://spark.apache.org/docs/2.4.6/api/sql/index.html.
+Give a few examples to help understand.
+Example 1: there are three columns "c1, c2, c3" in the table, and the first two columns in the source file correspond to (c1, c2), and the sum of the last two columns corresponds to C3; then columns (c1, c2, tmp_c3, tmp_c4) set (c3 = tmp_c3 + tmp_c4) needs to be specified;
+Example 2: there are three columns "year, month and day" in the table, and there is only one time column in the source file in the format of "2018-06-01 01:02:03".
+Then you can specify columns (tmp_time) set (year = year (tmp_time), month = month (tmp_time), day = day (tmp_time)) to complete the import.
+
+WHERE:
+
+Filter the transformed data, and only the data that meets the where condition can be imported. Only the column names in the table can be referenced in the WHERE statement
+```
+
+3.resource_name
+
+The name of the spark resource used can be viewed through `SHOW RESOURCES` command.
+
+4.resource_properties
+
+When you have a temporary need, such as modifying the Spark and HDFS configurations, you can set the parameters here, which takes effect only in this specific spark loading job and not to affect the existing configurations in the StarRocks cluster.
+
+5.opt_properties
+
+Used to specify some special parameters.
+
+Syntax:
+
+```sql
+[PROPERTIES ("key"="value", ...)]
+```
+
+You can specify the following parameters:
+timeout:         specifies the timeout of the import operation. The default timeout is 4 hours. In seconds.
+max_filter_ratio:the maximum allowable data proportion that can be filtered (for reasons such as non-standard data). The default is zero tolerance.
+strict mode:     whether to strictly restrict the data. The default is false.
+timezone:         specifies the time zone of some functions affected by the time zone, such as strftime / alignment_timestamp/from_unixtime, etc. Please refer to the [time zone] document for details. If not specified, the "Asia / Shanghai" time zone is used.
+
+6.Import data format example
+
+int (TINYINT/SMALLINT/INT/BIGINT/LARGEINT): 1, 1000, 1234
+float (FLOAT/DOUBLE/DECIMAL): 1.1, 0.23, .356
+date (DATE/DATETIME) :2017-10-03, 2017-06-13 12:34:03.
+(Note: for other date formats, you can use strftime or time_format function to convert in the Import command) string class (CHAR/VARCHAR): "I am a student", "a"
+
+NULL value: \ N
+
+## Examples
+
+1. Import a batch of data from HDFS, and specify the timeout time and filtering ratio. Use the name my_ spark resources for spark.
+
+    ```sql
+    LOAD LABEL example_db.label1
+    (
+    DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/file")
+    INTO TABLE `my_table`
+    )
+    WITH RESOURCE 'my_spark'
+    PROPERTIES
+    (
+        "timeout" = "3600",
+        "max_filter_ratio" = "0.1"
+    );
+    ```
+
+    Where hdfs_host is the host of namenode, hdfs_port is fs.defaultfs port (default 9000)
+
+2. Import a batch of "negative" data from HDFS, specify the separator as comma, use the wildcard * to specify all files in the directory, and specify the temporary parameters of spark resources.
+
+    ```sql
+    LOAD LABEL example_db.label3
+    (
+    DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/*")
+    NEGATIVE
+    INTO TABLE `my_table`
+    COLUMNS TERMINATED BY ","
+    )
+    WITH RESOURCE 'my_spark'
+    (
+        "spark.executor.memory" = "3g",
+        "broker.username" = "hdfs_user",
+        "broker.password" = "hdfs_passwd"
+    );
+    ```
+
+3. Import a batch of data from HDFS, specify the partition, and do some conversion on the columns of the imported file, as follows:
+
+    ```plain text
+    The table structure is:
+    k1 varchar(20)
+    k2 int
+    
+    Assume that the data file has only one line of data:
+    
+    Adele,1,1
+    
+    Each column in the data file corresponds to each column specified in the import statement:
+    k1,tmp_k2,tmp_k3
+    
+    The conversion is as follows:
+    
+    1. k1: no conversion
+    2. k2:is the sum of tmp_ k2 and tmp_k3
+    
+    LOAD LABEL example_db.label6
+    (
+    DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/file")
+    INTO TABLE `my_table`
+    PARTITION (p1, p2)
+    COLUMNS TERMINATED BY ","
+    (k1, tmp_k2, tmp_k3)
+    SET (
+    k2 = tmp_k2 + tmp_k3
+    )
+    )
+    WITH RESOURCE 'my_spark';
+    ```
+
+4. Extract the partition field in the file path
+
+    If necessary, the partitioned fields in the file path will be resolved according to the field types defined in the table, similar to the function of Partition Discovery in Spark
+
+    ```sql
+    LOAD LABEL example_db.label10
+    (
+    DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/dir/city=beijing/*/*")
+    INTO TABLE `my_table`
+    (k1, k2, k3)
+    COLUMNS FROM PATH AS (city, utc_date)
+    SET (uniq_id = md5sum(k1, city))
+    )
+    WITH RESOURCE 'my_spark';
+    ```
+
+    `hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/dir/city=beijing`  The directory includes the following files:
+
+    `[hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/dir/city=beijing/utc_date=2019-06-26/0000.csv, hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/dir/city=beijing/utc_date=2019-06-26/0001.csv, ...]`
+
+    The city and utc_date field in the file path are extracted
+
+5. Filter the data to be imported. Only columns with k1 value greater than 10 can be imported.
+
+    ```sql
+    LOAD LABEL example_db.label10
+    (
+    DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/file")
+    INTO TABLE `my_table`
+    WHERE k1 > 10
+    )
+    WITH RESOURCE 'my_spark';
+    ```
+
+6. Import from the hive external table and convert the uuid column in the source table to the bitmap type through the global dictionary.
+
+    ```sql
+    LOAD LABEL db1.label1
+    (
+    DATA FROM TABLE hive_t1
+    INTO TABLE tbl1
+    SET
+    (
+    uuid=bitmap_dict(uuid)
+    )
+    )
+    WITH RESOURCE 'my_spark';
+    ```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md
new file mode 100644
index 00000000000000..9982519dc00e0a
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md
@@ -0,0 +1,555 @@
+---
+displayed_sidebar: docs
+toc_max_heading_level: 4
+---
+
+# STREAM LOAD
+
+:::tip
+The [StarRocks in Docker](../../../quick_start/shared-nothing.md) quick start features Stream Load. Give it a try for hands-on experience and a detailed explanation of a realistic ETL flow.
+:::
+
+## Description
+
+StarRocks provides the loading method HTTP-based Stream Load to help you load data from a local file system or a streaming data source. After you submit a load job, StarRocks synchronously runs the job, and returns the result of the job after the job finishes. You can determine whether the job is successful based on the job result. For information about the application scenarios, limits, principles, and supported data file formats of Stream Load, see [Loading from a local file system via Stream Load](../../../loading/StreamLoad.md#loading-from-a-local-file-system-via-stream-load).
+
+Since v3.2.7, Stream Load supports compressing JSON data during transmission, reducing network bandwidth overhead. Users can specify different compression algorithms using parameters `compression` and `Content-Encoding`. Supported compression algorithms including GZIP, BZIP2, LZ4_FRAME, and ZSTD. For more information, see [data_desc](#data_desc).
+
+> **NOTICE**
+>
+> - After you load data into a StarRocks table by using Stream Load, the data of the materialized views that are created on that table is also updated.
+> - You can load data into StarRocks tables only as a user who has the INSERT privilege on those StarRocks tables. If you do not have the INSERT privilege, follow the instructions provided in [GRANT](../account-management/GRANT.md) to grant the INSERT privilege to the user that you use to connect to your StarRocks cluster.
+
+## Syntax
+
+```Bash
+curl --location-trusted -u <username>:<password> -XPUT <url>
+(
+    data_desc
+)
+[opt_properties]        
+```
+
+This topic uses curl as an example to describe how to load data by using Stream Load. In addition to curl, you can also use other HTTP-compatible tools or languages to perform Stream Load. Load-related parameters are included in HTTP request header fields. When you input these parameters, take note of the following points:
+
+- You can use chunked transfer encoding, as demonstrated in this topic. If you do not choose chunked transfer encoding, you must input a `Content-Length` header field to indicate the length of content to be transferred, thereby ensuring data integrity.
+
+  > **NOTE**
+  >
+  > If you use curl to perform Stream Load, StarRocks automatically adds a `Content-Length` header field and you do not need manually input it.
+
+- You must add an `Expect` header field and specify its value as `100-continue`, as in `"Expect:100-continue"`. This helps prevent unnecessary data transfers and reduce resource overheads in case your job request is denied.
+
+Note that in StarRocks some literals are used as reserved keywords by the SQL language. Do not directly use these keywords in SQL statements. If you want to use such a keyword in an SQL statement, enclose it in a pair of backticks (`). See [Keywords](../keywords.md).
+
+## Parameters
+
+### username and password
+
+Specify the username and password of the account that you use to connect to your StarRocks cluster. This is a required parameter. If you use an account for which no password is set, you need to input only `<username>:`.
+
+### XPUT
+
+Specifies the HTTP request method. This is a required parameter. Stream Load supports only the PUT method.
+
+### url
+
+Specifies the URL of the StarRocks table. Syntax:
+
+```Plain
+http://<fe_host>:<fe_http_port>/api/<database_name>/<table_name>/_stream_load
+```
+
+The following table describes the parameters in the URL.
+
+| Parameter     | Required | Description                                                  |
+| ------------- | -------- | ------------------------------------------------------------ |
+| fe_host       | Yes      | The IP address of the FE node in your StarRocks cluster.<br/>**NOTE**<br/>If you submit the load job to a specific BE or CN node, you must input the IP address of the BE or CN node. |
+| fe_http_port  | Yes      | The HTTP port number of the FE node in your StarRocks cluster. The default port number is `8030`.<br/>**NOTE**<br/>If you submit the load job to a specific BE or CN node, you must input the HTTP port number of the BE or CN node. The default port number is `8030`. |
+| database_name | Yes      | The name of the database to which the StarRocks table belongs. |
+| table_name    | Yes      | The name of the StarRocks table.                             |
+
+> **NOTE**
+>
+> You can use [SHOW FRONTENDS](../cluster-management/nodes_processes/SHOW_FRONTENDS.md) to view the IP address and HTTP port of the FE node.
+
+### data_desc
+
+Describes the data file that you want to load. The `data_desc` descriptor can include the data file's name, format, column separator, row separator, destination partitions, and column mapping against the StarRocks table. Syntax:
+
+```Bash
+-T <file_path>
+-H "format: CSV | JSON"
+-H "column_separator: <column_separator>"
+-H "row_delimiter: <row_delimiter>"
+-H "columns: <column1_name>[, <column2_name>, ... ]"
+-H "partitions: <partition1_name>[, <partition2_name>, ...]"
+-H "temporary_partitions: <temporary_partition1_name>[, <temporary_partition2_name>, ...]"
+-H "jsonpaths: [ \"<json_path1>\"[, \"<json_path2>\", ...] ]"
+-H "strip_outer_array: true | false"
+-H "json_root: <json_path>"
+-H "ignore_json_size: true | false"
+-H "compression: <compression_algorithm> | Content-Encoding: <compression_algorithm>"
+```
+
+The parameters in the `data_desc` descriptor can be divided into three types: common parameters, CSV parameters, and JSON parameters.
+
+#### Common parameters
+
+| Parameter  | Required | Description                                                  |
+| ---------- | -------- | ------------------------------------------------------------ |
+| file_path  | Yes      | The save path of the data file. You can optionally include the extension of the file name. |
+| format     | No       | The format of the data file. Valid values: `CSV` and `JSON`. Default value: `CSV`. |
+| partitions | No       | The partitions into which you want to load the data file. By default, if you do not specify this parameter, StarRocks loads the data file into all partitions of the StarRocks table. |
+| temporary_partitions|  No       | The name of the [temporary partition](../../../table_design/Temporary_partition.md) into which you want to load data file. You can specify multiple temporary partitions, which must be separated by commas (,).|
+| columns    | No       | The column mapping between the data file and the StarRocks table.<br/>If the fields in the data file can be mapped in sequence onto the columns in the StarRocks table, you do not need to specify this parameter. Instead, you can use this parameter to implement data conversions. For example, if you load a CSV data file and the file consists of two columns that can be mapped in sequence onto the two columns, `id` and `city`, of the StarRocks table, you can specify `"columns: city,tmp_id, id = tmp_id * 100"`. For more information, see the "[Column mapping](#column-mapping)" section in this topic. |
+
+#### CSV parameters
+
+| Parameter        | Required | Description                                                  |
+| ---------------- | -------- | ------------------------------------------------------------ |
+| column_separator | No       | The characters that are used in the data file to separate fields. If you do not specify this parameter, this parameter defaults to `\t`, which indicates tab.<br/>Make sure that the column separator you specify by using this parameter is the same as the column separator used in the data file.<br/>**NOTE**<br/>For CSV data, you can use a UTF-8 string, such as a comma (,), tab, or pipe (\|), whose length does not exceed 50 bytes as a text delimiter. |
+| row_delimiter    | No       | The characters that are used in the data file to separate rows. If you do not specify this parameter, this parameter defaults to `\n`. |
+| skip_header      | No       | Specifies whether to skip the first few rows of the data file when the data file is in CSV format. Type: INTEGER. Default value: `0`.<br />In some CSV-formatted data files, the first few rows at the beginning are used to define metadata such as column names and column data types. By setting the `skip_header` parameter, you can enable StarRocks to skip the first few rows of the data file during data loading. For example, if you set this parameter to `1`, StarRocks skips the first row of the data file during data loading.<br />The first few rows at the beginning in the data file must be separated by using the row separator that you specify in the load command. |
+| trim_space       | No       | Specifies whether to remove spaces preceding and following column separators from the data file when the data file is in CSV format. Type: BOOLEAN. Default value: `false`.<br />For some databases, spaces are added to column separators when you export data as a CSV-formatted data file. Such spaces are called leading spaces or trailing spaces depending on their locations. By setting the `trim_space` parameter, you can enable StarRocks to remove such unnecessary spaces during data loading.<br />Note that StarRocks does not remove the spaces (including leading spaces and trailing spaces) within a field wrapped in a pair of `enclose`-specified characters. For example, the following field values use pipe (<code class="language-text">&#124;</code>) as the column separator and double quotation marks (`"`) as the `enclose`-specified character:<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124; "Love StarRocks" &#124;</code> <br />If you set `trim_space` to `true`, StarRocks processes the preceding field values as follows:<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> |
+| enclose          | No       | Specifies the character that is used to wrap the field values in the data file according to [RFC4180](https://www.rfc-editor.org/rfc/rfc4180) when the data file is in CSV format. Type: single-byte character. Default value: `NONE`. The most prevalent characters are single quotation mark (`'`) and double quotation mark (`"`).<br />All special characters (including row separators and column separators) wrapped by using the `enclose`-specified character are considered normal symbols. StarRocks can do more than RFC4180 as it allows you to specify any single-byte character as the `enclose`-specified character.<br />If a field value contains an `enclose`-specified character, you can use the same character to escape that `enclose`-specified character. For example, you set `enclose` to `"`, and a field value is `a "quoted" c`. In this case, you can enter the field value as `"a ""quoted"" c"` into the data file. |
+| escape           | No       | Specifies the character that is used to escape various special characters, such as row separators, column separators, escape characters, and `enclose`-specified characters, which are then considered by StarRocks to be common characters and are parsed as part of the field values in which they reside. Type: single-byte character. Default value: `NONE`. The most prevalent character is slash (`\`), which must be written as double slashes (`\\`) in SQL statements.<br />**NOTE**<br />The character specified by `escape` is applied to both inside and outside of each pair of `enclose`-specified characters.<br />Two examples are as follows:<ul><li>When you set `enclose` to `"` and `escape` to `\`, StarRocks parses `"say \"Hello world\""` into `say "Hello world"`.</li><li>Assume that the column separator is comma (`,`). When you set `escape` to `\`, StarRocks parses `a, b\, c` into two separate field values: `a` and `b, c`.</li></ul> |
+
+> **NOTE**
+>
+> - For CSV data, you can use a UTF-8 string, such as a comma (,), tab, or pipe (|), whose length does not exceed 50 bytes as a text delimiter.
+> - Null values are denoted by using `\N`. For example, a data file consists of three columns, and a record from that data file holds data in the first and third columns but no data in the second column. In this situation, you need to use `\N` in the second column to denote a null value. This means the record must be compiled as `a,\N,b` instead of `a,,b`. `a,,b` denotes that the second column of the record holds an empty string.
+> - The format options, including `skip_header`, `trim_space`, `enclose`, and `escape`, are supported in v3.0 and later.
+
+#### JSON parameters
+
+| Parameter         | Required | Description                                                  |
+| ----------------- | -------- | ------------------------------------------------------------ |
+| jsonpaths         | No       | The names of the keys that you want to load from the JSON data file. You need to specify this parameter only when you load JSON data by using the matched mode. The value of this parameter is in JSON format. See [Configure column mapping for JSON data loading](#configure-column-mapping-for-json-data-loading).           |
+| strip_outer_array | No       | Specifies whether to strip the outermost array structure. Valid values: `true` and `false`. Default value: `false`.<br/>In real-world business scenarios, the JSON data may have an outermost array structure as indicated by a pair of square brackets `[]`. In this situation, we recommend that you set this parameter to `true`, so StarRocks removes the outermost square brackets `[]` and loads each inner array as a separate data record. If you set this parameter to `false`, StarRocks parses the entire JSON data file into one array and loads the array as a single data record.<br/>For example, the JSON data is `[ {"category" : 1, "author" : 2}, {"category" : 3, "author" : 4} ]`. If you set this parameter to `true`,  `{"category" : 1, "author" : 2}` and `{"category" : 3, "author" : 4}` are parsed into separate data records that are loaded into separate StarRocks table rows. |
+| json_root         | No       | The root element of the JSON data that you want to load from the JSON data file. You need to specify this parameter only when you load JSON data by using the matched mode. The value of this parameter is a valid JsonPath string. By default, the value of this parameter is empty, indicating that all data of the JSON data file will be loaded. For more information, see the "[Load JSON data using matched mode with root element specified](#load-json-data-using-matched-mode-with-root-element-specified)" section of this topic. |
+| ignore_json_size  | No       | Specifies whether to check the size of the JSON body in the HTTP request.<br/>**NOTE**<br/>By default, the size of the JSON body in an HTTP request cannot exceed 100 MB. If the JSON body exceeds 100 MB in size, an error "The size of this batch exceed the max size [104857600] of json type data data [8617627793]. Set ignore_json_size to skip check, although it may lead huge memory consuming." is reported. To prevent this error, you can add `"ignore_json_size:true"` in the HTTP request header to instruct StarRocks not to check the JSON body size. |
+| compression, Content-Encoding | NO | The encoding algorithm that is applied to the data during transmission. Supported algorithms include GZIP, BZIP2, LZ4_FRAME, and ZSTD. Example: `curl --location-trusted -u root:  -v 'http://127.0.0.1:18030/api/db0/tbl_simple/_stream_load' \-X PUT  -H "expect:100-continue" \-H 'format: json' -H 'compression: lz4_frame'   -T ./b.json.lz4`. |
+
+When you load JSON data, also note that the size per JSON object cannot exceed 4 GB. If an individual JSON object in the JSON data file exceeds 4 GB in size, an error "This parser can't support a document that big." is reported.
+
+### opt_properties
+
+Specifies some optional parameters, which are applied to the entire load job. Syntax:
+
+```Bash
+-H "label: <label_name>"
+-H "where: <condition1>[, <condition2>, ...]"
+-H "max_filter_ratio: <num>"
+-H "timeout: <num>"
+-H "strict_mode: true | false"
+-H "timezone: <string>"
+-H "load_mem_limit: <num>"
+-H "partial_update: true | false"
+-H "partial_update_mode: row | column"
+-H "merge_condition: <column_name>"
+```
+
+The following table describes the optional parameters.
+
+| Parameter        | Required | Description                                                  |
+| ---------------- | -------- | ------------------------------------------------------------ |
+| label            | No       | The label of the load job. If you do not specify this parameter, StarRocks automatically generates a label for the load job.<br/>StarRocks does not allow you to use one label to load a data batch multiple times. As such, StarRocks prevents the same data from being repeatedly loaded. For label naming conventions, see [System limits](../../System_limit.md).<br/>By default, StarRocks retains the labels of load jobs that were successfully completed over the most recent three days. You can use the [FE parameter](../../../administration/management/FE_configuration.md) `label_keep_max_second` to change the label retention period. |
+| where            | No       | The conditions based on which StarRocks filters the pre-processed data. StarRocks loads only the pre-processed data that meets the filter conditions specified in the WHERE clause. |
+| max_filter_ratio | No       | The maximum error tolerance of the load job. The error tolerance is the maximum percentage of data records that can be filtered out due to inadequate data quality in all data records requested by the load job. Valid values: `0` to `1`. Default value: `0`.<br/>We recommend that you retain the default value `0`. This way, if unqualified data records are detected, the load job fails, thereby ensuring data correctness.<br/>If you want to ignore unqualified data records, you can set this parameter to a value greater than `0`. This way, the load job can succeed even if the data file contains unqualified data records.<br/>**NOTE**<br/>Unqualified data records do not include data records that are filtered out by the WHERE clause. |
+| log_rejected_record_num | No           | Specifies the maximum number of unqualified data rows that can be logged. This parameter is supported from v3.1 onwards. Valid values: `0`, `-1`, and any non-zero positive integer. Default value: `0`.<ul><li>The value `0` specifies that data rows that are filtered out will not be logged.</li><li>The value `-1` specifies that all data rows that are filtered out will be logged.</li><li>A non-zero positive integer such as `n` specifies that up to `n` data rows that are filtered out can be logged on each BE or CN.</li></ul> |
+| timeout          | No       | The timeout period of the load job. Valid values: `1` to `259200`. Unit: second. Default value: `600`.<br/>**NOTE**In addition to the `timeout` parameter, you can also use the [FE parameter](../../../administration/management/FE_configuration.md) `stream_load_default_timeout_second` to centrally control the timeout period for all Stream Load jobs in your StarRocks cluster. If you specify the `timeout` parameter, the timeout period specified by the `timeout` parameter prevails. If you do not specify the `timeout` parameter, the timeout period specified by the `stream_load_default_timeout_second` parameter prevails. |
+| strict_mode      | No       | Specifies whether to enable the [strict mode](../../../loading/load_concept/strict_mode.md). Valid values: `true` and `false`. Default value: `false`.  The value `true` specifies to enable the strict mode, and the value `false` specifies to disable the strict mode. |
+| timezone         | No       | The time zone used by the load job. Default value: `Asia/Shanghai`. The value of this parameter affects the results returned by functions such as strftime, alignment_timestamp, and from_unixtime. The time zone specified by this parameter is a session-level time zone. For more information, see [Configure a time zone](../../../administration/management/timezone.md). |
+| load_mem_limit   | No       | The maximum amount of memory that can be provisioned to the load job. Unit: bytes. By default, the maximum memory size for a load job is 2 GB. The value of this parameter cannot exceed the maximum amount of memory that can be provisioned to each BE or CN. |
+| partial_update | No | Whether to use partial updates. Valid values: `TRUE` and `FALSE`. Default value: `FALSE`, indicating to disable this feature. |
+| partial_update_mode | No | Specifies the mode for partial updates. Valid values: `row` and `column`. <ul><li> The value `row` (default) means partial updates in row mode, which is more suitable for real-time updates with many columns and small batches.</li><li>The value `column` means partial updates in column mode, which is more suitable for batch updates with few columns and many rows. In such scenarios, enabling the column mode offers faster update speeds. For example, in a table with 100 columns, if only 10 columns (10% of the total) are updated for all rows, the update speed of the column mode is 10 times faster.</li></ul> |
+| merge_condition  | No       | Specifies the name of the column you want to use as the condition to determine whether updates can take effect. The update from a source record to a destination record takes effect only when the source data record has a greater or equal value than the destination data record in the specified column. StarRocks supports conditional updates since v2.5. For more information, see [Change data through loading](../../../loading/Load_to_Primary_Key_tables.md). <br/>**NOTE**<br/>The column that you specify cannot be a primary key column. Additionally, only tables that use the Primary Key table support conditional updates. |
+
+## Column mapping
+
+### Configure column mapping for CSV data loading
+
+If the columns of the data file can be mapped one on one in sequence to the columns of the StarRocks table, you do not need to configure the column mapping between the data file and the StarRocks table.
+
+If the columns of the data file cannot be mapped one on one in sequence to the columns of the StarRocks table, you need to use the `columns` parameter to configure the column mapping between the data file and the StarRocks table. This includes the following two use cases:
+
+- **Same number of columns but different column sequence.** **Also, the data from the data file does not need to be computed by functions before it is loaded into the matching StarRocks table columns.**
+
+  In the `columns` parameter, you need to specify the names of the StarRocks table columns in the same sequence as how the data file columns are arranged.
+
+  For example, the StarRocks table consists of three columns, which are `col1`, `col2`, and `col3` in sequence, and the data file also consists of three columns, which can be mapped to the StarRocks table columns `col3`, `col2`, and `col1` in sequence. In this case, you need to specify `"columns: col3, col2, col1"`.
+
+- **Different number of columns and different column sequence. Also, the data from the data file needs to be computed by functions before it is loaded into the matching StarRocks table columns.**
+
+  In the `columns` parameter, you need to specify the names of the StarRocks table columns in the same sequence as how the data file columns are arranged and specify the functions you want to use to compute the data. Two examples are as follows:
+
+  - The StarRocks table consists of three columns, which are `col1`, `col2`, and `col3` in sequence. The data file consists of four columns, among which the first three columns can be mapped in sequence to the StarRocks table columns `col1`, `col2`, and `col3` and the fourth column cannot be mapped to any of the StarRocks table columns. In this case, you need to temporarily specify a name for the fourth column of the data file, and the temporary name must be different from any of the StarRocks table column names. For example, you can specify `"columns: col1, col2, col3, temp"`, in which the fourth column of the data file is temporarily named `temp`.
+  - The StarRocks table consists of three columns, which are `year`, `month`, and `day` in sequence. The data file consists of only one column that accommodates date and time values in `yyyy-mm-dd hh:mm:ss` format. In this case, you can specify `"columns: col, year = year(col), month=month(col), day=day(col)"`, in which `col` is the temporary name of the data file column and the functions `year = year(col)`, `month=month(col)`, and `day=day(col)` are used to extract data from the data file column `col` and loads the data into the mapping StarRocks table columns. For example, `year = year(col)` is used to extract the `yyyy` data from the data file column `col` and loads the data into the StarRocks table column `year`.
+
+For detailed examples, see [Configure column mapping](#configure-column-mapping).
+
+### Configure column mapping for JSON data loading
+
+If the keys of the JSON document have the same names as the columns of the StarRocks table, you can load the JSON-formatted data by using the simple mode. In simple mode, you do not need to specify the `jsonpaths` parameter. This mode requires that the JSON-formatted data must be an object as indicated by curly brackets `{}`, such as `{"category": 1, "author": 2, "price": "3"}`. In this example, `category`, `author`, and `price` are key names, and these keys can be mapped one on one by name to the columns `category`, `author`, and `price` of the StarRocks table.
+
+If the keys of the JSON document have different names than the columns of the StarRocks table, you can load the JSON-formatted data by using the matched mode. In matched mode, you need to use the `jsonpaths` and `COLUMNS` parameters to specify the column mapping between the JSON document and the StarRocks table:
+
+- In the `jsonpaths` parameter, specify the JSON keys in the sequence as how they are arranged in the JSON document.
+- In the `COLUMNS` parameter, specify the mapping between the JSON keys and the StarRocks table columns:
+  - The column names specified in the `COLUMNS` parameter are mapped one on one in sequence to the JSON keys.
+  - The column names specified in the `COLUMNS` parameter are mapped one on one by name to the StarRocks table columns.
+
+For examples about loading JSON-formatted data by using the matched mode, see [Load JSON data using matched mode](#load-json-data-using-matched-mode).
+
+## Return value
+
+After the load job finishes, StarRocks returns the job result in JSON format. Example:
+
+```JSON
+{
+    "TxnId": 1003,
+    "Label": "label123",
+    "Status": "Success",
+    "Message": "OK",
+    "NumberTotalRows": 1000000,
+    "NumberLoadedRows": 999999,
+    "NumberFilteredRows": 1,
+    "NumberUnselectedRows": 0,
+    "LoadBytes": 40888898,
+    "LoadTimeMs": 2144,
+    "BeginTxnTimeMs": 0,
+    "StreamLoadPlanTimeMs": 1,
+    "ReadDataTimeMs": 0,
+    "WriteDataTimeMs": 11,
+    "CommitAndPublishTimeMs": 16,
+}
+```
+
+The following table describes the parameters in the returned job result.
+
+| Parameter              | Description                                                  |
+| ---------------------- | ------------------------------------------------------------ |
+| TxnId                  | The transaction ID of the load job.                          |
+| Label                  | The label of the load job.                                   |
+| Status                 | The final status of the data loaded.<ul><li>`Success`: The data is successfully loaded and can be queried.</li><li>`Publish Timeout`: The load job is successfully submitted, but the data still cannot be queried. You do not need to retry to load the data.</li><li>`Label Already Exists`: The label of the load job has been used for another load job. The data may have been successfully loaded or is being loaded.</li><li>`Fail`: The data failed to be loaded. You can retry the load job.</li></ul> |
+| Message                | The status of the load job. If the load job fails, the detailed failure cause is returned. |
+| NumberTotalRows        | The total number of data records that are read.              |
+| NumberLoadedRows       | The total number of data records that are successfully loaded. This parameter is valid only when the value returned for `Status` is `Success`. |
+| NumberFilteredRows     | The number of data records that are filtered out due to inadequate data quality. |
+| NumberUnselectedRows   | The number of data records that are filtered out by the WHERE clause. |
+| LoadBytes              | The amount of data that is loaded. Unit: bytes.              |
+| LoadTimeMs             | The amount of time that is taken by the load job. Unit: ms.  |
+| BeginTxnTimeMs         | The amount of time that is taken to run a transaction for the load job. |
+| StreamLoadPlanTimeMs   | The amount of time that is taken to generate a execution plan for the load job. |
+| ReadDataTimeMs         | The amount of time that is taken to read data for the load job. |
+| WriteDataTimeMs        | The amount of time that is taken to write data for the load job. |
+| CommitAndPublishTimeMs | The amount of time that is taken to commit and publish data for the load job. |
+
+If the load job fails, StarRocks also returns `ErrorURL`. Example:
+
+```JSON
+{"ErrorURL": "http://172.26.195.68:8045/api/_load_error_log?file=error_log_3a4eb8421f0878a6_9a54df29fd9206be"}
+```
+
+`ErrorURL` provides a URL from which you can obtain details about unqualified data records that have been filtered out. You can specify the maximum number of unqualified data rows that can be logged by using the optional parameter `log_rejected_record_num`, which is set when you submit a load job.
+
+You can run `curl "url"` to directly view details about the filtered-out, unqualified data records. You can also run `wget "url"` to export the details about these data records:
+
+```Bash
+wget http://172.26.195.68:8045/api/_load_error_log?file=error_log_3a4eb8421f0878a6_9a54df29fd9206be
+```
+
+The exported data record details are saved to a local file with a name similar to `_load_error_log?file=error_log_3a4eb8421f0878a6_9a54df29fd9206be`. You can use the `cat` command to view the file.
+
+Then, you can adjust the configuration of the load job, and submit the load job again.
+
+## Examples
+
+### Load CSV data
+
+This section CSV data as an example to describe how you can employ various parameter settings and combinations to meet your diverse loading requirements.
+
+#### Set timeout period
+
+Your StarRocks database `test_db` contains a table named `table1`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example1.csv` also consists of three columns, which can be mapped in sequence onto `col1`, `col2`, and `col3` of `table1`.
+
+If you want to load all data from `example1.csv` into `table1` within up to 100 seconds, run the following command:
+
+```Bash
+curl --location-trusted -u <username>:<password> -H "label:label1" \
+    -H "Expect:100-continue" \
+    -H "timeout:100" \
+    -H "max_filter_ratio:0.2" \
+    -T example1.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table1/_stream_load
+```
+
+#### Set error tolerance
+
+Your StarRocks database `test_db` contains a table named `table2`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example2.csv` also consists of three columns, which can be mapped in sequence onto `col1`, `col2`, and `col3` of `table2`.
+
+If you want to load all data from `example2.csv` into `table2` with a maximum error tolerance of `0.2`, run the following command:
+
+```Bash
+curl --location-trusted -u <username>:<password> -H "label:label2" \
+    -H "Expect:100-continue" \
+    -H "max_filter_ratio:0.2" \
+    -T example2.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table2/_stream_load
+```
+
+#### Configure column mapping
+
+Your StarRocks database `test_db` contains a table named `table3`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example3.csv` also consists of three columns, which can be mapped in sequence onto `col2`, `col1`, and `col3` of `table3`.
+
+If you want to load all data from `example3.csv` into `table3`, run the following command:
+
+```Bash
+curl --location-trusted -u <username>:<password>  -H "label:label3" \
+    -H "Expect:100-continue" \
+    -H "columns: col2, col1, col3" \
+    -T example3.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table3/_stream_load
+```
+
+> **NOTE**
+>
+> In the preceding example, the columns of `example3.csv` cannot be mapped onto the columns of `table3` in the same sequence as how these columns are arranged in `table3`. Therefore, you need to use the `columns` parameter to configure the column mapping between `example3.csv` and `table3`.
+
+#### Set filter conditions
+
+Your StarRocks database `test_db` contains a table named `table4`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example4.csv` also consists of three columns, which can be mapped in sequence onto `col1`, `col2`, and `col3` of `table4`.
+
+If you want to load only the data records whose values in the first column of `example4.csv` are equal to `20180601` into `table4`, run the following command:
+
+```Bash
+curl --location-trusted -u <username>:<password> -H "label:label4" \
+    -H "Expect:100-continue" \
+    -H "columns: col1, col2, col3]"\
+    -H "where: col1 = 20180601" \
+    -T example4.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table4/_stream_load
+```
+
+> **NOTE**
+>
+> In the preceding example, `example4.csv` and `table4` have the same number of columns that can be mapped in sequence, but you need to use the WHERE clause to specify column-based filter conditions. Therefore, you need to use the `columns` parameter to define temporary names for the columns of `example4.csv`.
+
+#### Set destination partitions
+
+Your StarRocks database `test_db` contains a table named `table5`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example5.csv` also consists of three columns, which can be mapped in sequence onto `col1`, `col2`, and `col3` of `table5`.
+
+If you want to load all data from `example5.csv` into partitions `p1` and `p2` of `table5`, run the following command:
+
+```Bash
+curl --location-trusted -u <username>:<password>  -H "label:label5" \
+    -H "Expect:100-continue" \
+    -H "partitions: p1, p2" \
+    -T example5.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table5/_stream_load
+```
+
+#### Set strict mode and time zone
+
+Your StarRocks database `test_db` contains a table named `table6`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example6.csv` also consists of three columns, which can be mapped in sequence onto `col1`, `col2`, and `col3` of `table6`.
+
+If you want to load all data from `example6.csv` into `table6` by using the strict mode and the time zone `Africa/Abidjan`, run the following command:
+
+```Bash
+curl --location-trusted -u <username>:<password> \
+    -H "Expect:100-continue" \
+    -H "strict_mode: true" \
+    -H "timezone: Africa/Abidjan" \
+    -T example6.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table6/_stream_load
+```
+
+#### Load data into tables containing HLL-type columns
+
+Your StarRocks database `test_db` contains a table named `table7`. The table consists of two HLL-type columns, which are `col1` and `col2` in sequence.
+
+Your data file `example7.csv` also consists of two columns, among which the first column can be mapped onto `col1` of `table7` and the second column cannot be mapped onto any column of `table7`. The values in the first column of `example7.csv` can be converted into HLL-type data by using functions before they are loaded into `col1` of `table7`.
+
+If you want to load data from `example7.csv` into `table7`, run the following command:
+
+```Bash
+curl --location-trusted -u <username>:<password> \
+    -H "Expect:100-continue" \
+    -H "columns: temp1, temp2, col1=hll_hash(temp1), col2=hll_empty()" \
+    -T example7.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table7/_stream_load
+```
+
+> **NOTE**
+>
+> In the preceding example, the two columns of `example7.csv` are named `temp1` and `temp2` in sequence by using the `columns` parameter. Then, functions are used to convert data as follows:
+>
+> - The `hll_hash` function is used to convert the values in `temp1` of `example7.csv` into HLL-type data and map `temp1` of `example7.csv` onto `col1` of `table7`.
+>
+> - The `hll_empty` function is used to fill the specified default value into `col2` of `table7`.
+
+For usage of the functions `hll_hash` and `hll_empty`, see [hll_hash](../../sql-functions/scalar-functions/hll_hash.md) and [hll_empty](../../sql-functions/scalar-functions/hll_empty.md).
+
+#### Load data into tables containing BITMAP-type columns
+
+Your StarRocks database `test_db` contains a table named `table8`. The table consists of two BITMAP-type columns, which are `col1` and `col2`, in sequence.
+
+Your data file `example8.csv` also consists of two columns, among which the first column can be mapped onto `col1` of `table8` and the second column cannot be mapped onto any column of `table8`. The values in the first column of `example8.csv` can be converted by using functions before they are loaded into `col1` of `table8`.
+
+If you want to load data from `example8.csv` into `table8`, run the following command:
+
+```Bash
+curl --location-trusted -u <username>:<password> \
+    -H "Expect:100-continue" \
+    -H "columns: temp1, temp2, col1=to_bitmap(temp1), col2=bitmap_empty()" \
+    -T example8.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table8/_stream_load
+```
+
+> **NOTE**
+>
+> In the preceding example, the two columns of `example8.csv` are named `temp1` and `temp2` in sequence by using the `columns` parameter. Then, functions are used to convert data as follows:
+>
+> - The `to_bitmap` function is used to convert the values in `temp1` of `example8.csv` into BITMAP-type data and map `temp1` of `example8.csv` onto `col1` of `table8`.
+>
+> - The `bitmap_empty` function is used to fill the specified default value into `col2` of `table8`.
+
+For usage of the functions `to_bitmap` and `bitmap_empty`, see [to_bitmap](../../sql-functions/bitmap-functions/to_bitmap.md) and [bitmap_empty](../../sql-functions/bitmap-functions/bitmap_empty.md).
+
+#### Setting `skip_header`, `trim_space`, `enclose`, and `escape`
+
+Your StarRocks database `test_db` contains a table named `table9`. The table consists of three columns, which are `col1`, `col2`, and `col3` in sequence.
+
+Your data file `example9.csv` also consists of three columns, which are mapped in sequence onto `col2`, `col1`, and `col3` of `table13`.
+
+If you want to load all data from `example9.csv` into `table9`, with the intention of skipping the first five rows of `example9.csv`, removing the spaces preceding and following column separators, and setting `enclose` to `\` and `escape` to `\`, run the following command:
+
+```Bash
+curl --location-trusted -u <username>:<password> -H "label:3875" \
+    -H "Expect:100-continue" \
+    -H "trim_space: true" -H "skip_header: 5" \
+    -H "column_separator:," -H "enclose:\"" -H "escape:\\" \
+    -H "columns: col2, col1, col3" \
+    -T example9.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/tbl9/_stream_load
+```
+
+### Load JSON data
+
+This section describes the parameter settings that you need to take note of when you load JSON data.
+
+Your StarRocks database `test_db` contains a table named `tbl1`, whose schema is as follows:
+
+```SQL
+`category` varchar(512) NULL COMMENT "",`author` varchar(512) NULL COMMENT "",`title` varchar(512) NULL COMMENT "",`price` double NULL COMMENT ""
+```
+
+#### Load JSON data using simple mode
+
+Suppose that your data file `example1.json` consists of the following data:
+
+```JSON
+{"category":"C++","author":"avc","title":"C++ primer","price":895}
+```
+
+To load all data from `example1.json` into `tbl1`, run the following command:
+
+```Bash
+curl --location-trusted -u <username>:<password> -H "label:label6" \
+    -H "Expect:100-continue" \
+    -H "format: json" \
+    -T example1.json -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/tbl1/_stream_load
+```
+
+> **NOTE**
+>
+> In the preceding example, the parameters `columns` and `jsonpaths` are not specified. Therefore, the keys in `example1.json` are mapped by name onto the columns of `tbl1`.
+
+To increase throughput, Stream Load supports loading multiple data records all at once. Example:
+
+```JSON
+[{"category":"C++","author":"avc","title":"C++ primer","price":89.5},{"category":"Java","author":"avc","title":"Effective Java","price":95},{"category":"Linux","author":"avc","title":"Linux kernel","price":195}]
+```
+
+#### Load JSON data using matched mode
+
+StarRocks performs the following steps to match and process JSON data:
+
+1. (Optional) Strips the outermost array structure as instructed by the `strip_outer_array` parameter setting.
+
+   > **NOTE**
+   >
+   > This step is performed only when the outermost layer of the JSON data is an array structure as indicated by a pair of square brackets `[]`. You need to set `strip_outer_array` to `true`.
+
+2. (Optional) Matches the root element of the JSON data as instructed by the `json_root` parameter setting.
+
+   > **NOTE**
+   >
+   > This step is performed only when the JSON data has a root element. You need to specify the root element by using the `json_root` parameter.
+
+3. Extracts the specified JSON data as instructed by the `jsonpaths` parameter setting.
+
+##### Load JSON data using matched mode without root element specified
+
+Suppose that your data file `example2.json` consists of the following data:
+
+```JSON
+[{"category":"xuxb111","author":"1avc","title":"SayingsoftheCentury","price":895},{"category":"xuxb222","author":"2avc","title":"SayingsoftheCentury","price":895},{"category":"xuxb333","author":"3avc","title":"SayingsoftheCentury","price":895}]
+```
+
+To load only `category`, `author`, and `price` from `example2.json`, run the following command:
+
+```Bash
+curl --location-trusted -u <username>:<password> -H "label:label7" \
+    -H "Expect:100-continue" \
+    -H "format: json" \
+    -H "strip_outer_array: true" \
+    -H "jsonpaths: [\"$.category\",\"$.price\",\"$.author\"]" \
+    -H "columns: category, price, author" \
+    -T example2.json -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/tbl1/_stream_load
+```
+
+> **NOTE**
+>
+> In the preceding example, the outermost layer of the JSON data is an array structure as indicated by a pair of square brackets `[]`. The array structure consists of multiple JSON objects that each represent a data record. Therefore, you need to set `strip_outer_array` to `true` to strip the outermost array structure. The key **title** that you do not want to load is ignored during loading.
+
+##### Load JSON data using matched mode with root element specified
+
+Suppose your data file `example3.json` consists of the following data:
+
+```JSON
+{"id": 10001,"RECORDS":[{"category":"11","title":"SayingsoftheCentury","price":895,"timestamp":1589191587},{"category":"22","author":"2avc","price":895,"timestamp":1589191487},{"category":"33","author":"3avc","title":"SayingsoftheCentury","timestamp":1589191387}],"comments": ["3 records", "there will be 3 rows"]}
+```
+
+To load only `category`, `author`, and `price` from `example3.json`, run the following command:
+
+```Bash
+curl --location-trusted -u <username>:<password> \
+    -H "Expect:100-continue" \
+    -H "format: json" \
+    -H "json_root: $.RECORDS" \
+    -H "strip_outer_array: true" \
+    -H "jsonpaths: [\"$.category\",\"$.price\",\"$.author\"]" \
+    -H "columns: category, price, author" -H "label:label8" \
+    -T example3.json -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/tbl1/_stream_load
+```
+
+> **NOTE**
+>
+> In the preceding example, the outermost layer of the JSON data is an array structure as indicated by a pair of square brackets `[]`. The array structure consists of multiple JSON objects that each represent a data record. Therefore, you need to set `strip_outer_array` to `true` to strip the outermost array structure. The keys `title` and `timestamp` that you do not want to load are ignored during loading. Additionally, the `json_root` parameter is used to specify the root element, which is an array, of the JSON data.
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/_category_.yml b/docs/en/sql-reference/sql-statements/loading_unloading/_category_.yml
new file mode 100644
index 00000000000000..b57df2adbc0120
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/_category_.yml
@@ -0,0 +1,6 @@
+position: 40 # float position is supported
+label: 'Loading and unloading'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/pipe/ALTER_PIPE.md b/docs/en/sql-reference/sql-statements/loading_unloading/pipe/ALTER_PIPE.md
new file mode 100644
index 00000000000000..499758d7818ed7
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/pipe/ALTER_PIPE.md
@@ -0,0 +1,54 @@
+---
+displayed_sidebar: docs
+---
+
+# ALTER PIPE
+
+## Description
+
+Alters the settings of the properties of a pipe. This command is supported from v3.2 onwards.
+
+## Syntax
+
+```SQL
+ALTER PIPE [db_name.]<pipe_name> 
+SET PROPERTY
+(
+    "<key>" = <value>[, "<key>" = "<value>" ...]
+) 
+```
+
+## Parameters
+
+### db_name
+
+The name of the database to which the pipe belongs.
+
+### pipe_name
+
+The name of the pipe.
+
+### PROPERTIES
+
+The properties whose settings you want to alter for the pipe. Format: `"key" = "value"`. For more information about the properties supported, see [CREATE PIPE](CREATE_PIPE.md).
+
+## Examples
+
+Change the setting of the `AUTO_INGEST` property to `FALSE` for the pipe named `user_behavior_replica` in the database named `mydatabase`:
+
+```SQL
+USE mydatabase;
+ALTER PIPE user_behavior_replica
+SET
+(
+    "AUTO_INGEST" = "FALSE"
+);
+```
+
+## References
+
+- [CREATE PIPE](CREATE_PIPE.md)
+- [DROP PIPE](DROP_PIPE.md)
+- [SHOW PIPES](SHOW_PIPES.md)
+- [SUSPEND or RESUME PIPE](SUSPEND_or_RESUME_PIPE.md)
+- [RETRY FILE](RETRY_FILE.md)
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md b/docs/en/sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md
new file mode 100644
index 00000000000000..423d33a0cb15f6
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md
@@ -0,0 +1,86 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE PIPE
+
+## Description
+
+Creates a new pipe for defining the INSERT INTO SELECT FROM FILES statement used by the system to load data from a specified source data file to a destination table. This command is supported from v3.2 onwards.
+
+## Syntax
+
+```SQL
+CREATE [OR REPLACE] PIPE [db_name.]<pipe_name> 
+[PROPERTIES ("<key>" = "<value>"[, "<key> = <value>" ...])]
+AS <INSERT_SQL>
+```
+
+StarRocks supports CREATE [OR REPLACE] PIPE from v3.2.3 onwards. When you use CREATE [OR REPLACE] PIPE to create a pipe and the pipe name specified in `pipe_name` is the same as the name of an existing pipe in the current database, the existing database is replaced by the new pipe.
+
+## Parameters
+
+### db_name
+
+The unique name of the database to which the pipe belongs.
+
+> **NOTICE**
+>
+> Each pipe belongs to a specific database. If you drop the database to which a pipe belongs, the pipe is deleted along with the database, and cannot be recovered even if the database is recovered.
+
+### pipe_name
+
+The name of the pipe. The pipe name must be unique within the database in which the pipe is created. For the naming conventions, see [System limits](../../../System_limit.md).
+
+### INSERT_SQL
+
+The INSERT INTO SELECT FROM FILES statement that is used to load data from the specified source data file to the destination table.
+
+For more information about the FILES() table function, see [FILES](../../../sql-functions/table-functions/files.md).
+
+### PROPERTIES
+
+A set of optional parameters that specify how to execute the pipe. Format: `"key" = "value"`.
+
+| Property      | Default value | Description                                                  |
+| :------------ | :------------ | :----------------------------------------------------------- |
+| AUTO_INGEST   | `TRUE`        | Whether to enable automatic incremental data loads. Valid values: `TRUE` and `FALSE`. If you set this parameter to `TRUE`, automatic incremental data loads are enabled. If you set this parameter to `FALSE`, the system loads only the source data file content specified at job creation and subsequent new or updated file content will not be loaded. For a bulk load, you can set this parameter to `FALSE`. |
+| POLL_INTERVAL | `300` second | The polling interval for automatic incremental data loads.   |
+| BATCH_SIZE    | `1GB`         | The size of data to be loaded as a batch. If you do not include a unit in the parameter value, the default unit byte is used. |
+| BATCH_FILES   | `256`         | The number of source data files to be loaded as a batch.     |
+
+## Examples
+
+Create a pipe named `user_behavior_replica` in the current database to load the data of the sample dataset `s3://starrocks-examples/user_behavior_ten_million_rows.parquet` to the `user_behavior_replica` table:
+
+```SQL
+CREATE PIPE user_behavior_replica
+PROPERTIES
+(
+    "AUTO_INGEST" = "TRUE"
+)
+AS
+INSERT INTO user_behavior_replica
+SELECT * FROM FILES
+(
+    "path" = "s3://starrocks-examples/user_behavior_ten_million_rows.parquet",
+    "format" = "parquet",
+    "aws.s3.region" = "us-east-1",
+    "aws.s3.access_key" = "AAAAAAAAAAAAAAAAAAAA",
+    "aws.s3.secret_key" = "BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB"
+); 
+```
+
+> **NOTE**
+>
+> Substitute your credentials for `AAA` and `BBB` in the above command. Any valid `aws.s3.access_key` and `aws.s3.secret_key` can be used, as the object is readable by any AWS authenticated user.
+
+This example uses the IAM user-based authentication method and a Parquet file that has the same schema as the StarRocks table. For more information about the other authentication methods and the CREATE PIPE usage, see [Authenticate to AWS resources](../../../../integrations/authenticate_to_aws_resources.md) and [FILES](../../../sql-functions/table-functions/files.md).
+
+## References
+
+- [ALTER PIPE](ALTER_PIPE.md)
+- [DROP PIPE](DROP_PIPE.md)
+- [SHOW PIPES](SHOW_PIPES.md)
+- [SUSPEND or RESUME PIPE](SUSPEND_or_RESUME_PIPE.md)
+- [RETRY FILE](RETRY_FILE.md)
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/pipe/DROP_PIPE.md b/docs/en/sql-reference/sql-statements/loading_unloading/pipe/DROP_PIPE.md
new file mode 100644
index 00000000000000..4d9040d03505b2
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/pipe/DROP_PIPE.md
@@ -0,0 +1,42 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP PIPE
+
+## Description
+
+Drops a pipe and the related jobs and metadata. Executing this statement on a pipe does not revoke the data that has been loaded via this pipe. This command is supported from v3.2 onwards.
+
+## Syntax
+
+```SQL
+DROP PIPE [IF EXISTS] [db_name.]<pipe_name>
+```
+
+## Parameters
+
+### db_name
+
+The name of the database to which the pipe belongs.
+
+### pipe_name
+
+The name of the pipe.
+
+## Examples
+
+Drop the pipe named `user_behavior_replica` in the database named `mydatabase`:
+
+```SQL
+USE mydatabase;
+DROP PIPE user_behavior_replica;
+```
+
+## References
+
+- [CREATE PIPE](CREATE_PIPE.md)
+- [ALTER PIPE](ALTER_PIPE.md)
+- [SHOW PIPES](SHOW_PIPES.md)
+- [SUSPEND or RESUME PIPE](SUSPEND_or_RESUME_PIPE.md)
+- [RETRY FILE](RETRY_FILE.md)
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/pipe/RETRY_FILE.md b/docs/en/sql-reference/sql-statements/loading_unloading/pipe/RETRY_FILE.md
new file mode 100644
index 00000000000000..3332657257fa7a
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/pipe/RETRY_FILE.md
@@ -0,0 +1,43 @@
+# RETRY FILE
+
+## Description
+
+Retries to load all data files or a specific data file in a pipe. This command is supported from v3.2 onwards.
+
+## Syntax
+
+```SQL
+ALTER PIPE [ IF EXISTS ] <pipe_name> { RETRY ALL | RETRY FILE '<file_name>' }
+```
+
+## Parameters
+
+### pipe_name
+
+The name of the pipe.
+
+### file_name
+
+The storage path of the data file that you want to retry to load. Note that you must specify the full storage path of the file. If the file you specify does not belong to the pipe you specify in `pipe_name`, an error is returned.
+
+## Examples
+
+The following example retries to load all data files in a pipe named `user_behavior_replica`:
+
+```SQL
+ALTER PIPE [ IF EXISTS ] user_behavior_replica RETRY ALL;
+```
+
+The following example retries to load the data file `s3://starrocks-examples/user_behavior_ten_million_rows.parquet` in a pipe named `user_behavior_replica`:
+
+```SQL
+ALTER PIPE [ IF EXISTS ] user_behavior_replica RETRY FILE 's3://starrocks-examples/user_behavior_ten_million_rows.parquet';
+```
+
+## References
+
+- [CREATE PIPE](CREATE_PIPE.md)
+- [ALTER PIPE](ALTER_PIPE.md)
+- [DROP PIPE](DROP_PIPE.md)
+- [SHOW PIPES](SHOW_PIPES.md)
+- [SUSPEND or RESUME PIPE](SUSPEND_or_RESUME_PIPE.md)
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md b/docs/en/sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md
new file mode 100644
index 00000000000000..0000c5c4f108a4
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md
@@ -0,0 +1,82 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW PIPES
+
+## Description
+
+Lists the pipes stored in a specified database or in the current database in use. This command is supported from v3.2 onwards.
+
+## Syntax
+
+```SQL
+SHOW PIPES [FROM <db_name>]
+[
+   WHERE [ NAME { = "<pipe_name>" | LIKE "pipe_matcher" } ]
+         [ [AND] STATE = { "SUSPENDED" | "RUNNING" | "ERROR" } ]
+]
+[ ORDER BY <field_name> [ ASC | DESC ] ]
+[ LIMIT { [offset, ] limit | limit OFFSET offset } ]
+```
+
+## Parameters
+
+### FROM `<db_name>`
+
+The name of the database for which you want to query pipes. If you do not specify this parameter, the system returns the pipes for the current database in use.
+
+### WHERE
+
+The criteria based on which to query pipes.
+
+### ORDER BY `<field_name>`
+
+The field by which you want to sort the records returned.
+
+### LIMIT
+
+The maximum number of records you want the system to return.
+
+## Return result
+
+The command output consists of the following fields.
+
+| **Field**     | **Description**                                              |
+| ------------- | ------------------------------------------------------------ |
+| DATABASE_NAME | The name of the database in which the pipe is stored.        |
+| PIPE_ID       | The unique ID of the pipe.                                   |
+| PIPE_NAME     | The name of the pipe.                                        |
+| TABLE_NAME    | The name of the destination StarRocks table.                 |
+| STATE         | The status of the pipe. Valid values: `RUNNING`, `FINISHED`, `SUSPENDED`, and `ERROR`. |
+| LOAD_STATUS   | The overall status of the data files to be loaded via the pipe, including the following sub-fields:<ul><li>`loadedFiles`: the number of data files that have been loaded.</li><li>`loadedBytes`: the volume of data that has been loaded, measured in bytes.</li><li>`LastLoadedTime`: the date and time when the last data file was loaded. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`.</li></ul> |
+| LAST_ERROR    | The details about the last error that occurred during the pipe execution. Default value: `NULL`. |
+| CREATED_TIME  | The date and time when the pipe was created. Format: `yyyy-MM-dd HH:mm:ss`. Example: `2023-07-24 14:58:58`. |
+
+## Examples
+
+### Query all pipes
+
+Switch to the database named `mydatabase` and show all the pipes in it:
+
+```SQL
+USE mydatabase;
+SHOW PIPES \G
+```
+
+### Query a specified pipe
+
+Switch to the database named `mydatabase` and show the pipe named `user_behavior_replica` in it:
+
+```SQL
+USE mydatabase;
+SHOW PIPES WHERE NAME = 'user_behavior_replica' \G
+```
+
+## References
+
+- [CREATE PIPE](CREATE_PIPE.md)
+- [ALTER PIPE](ALTER_PIPE.md)
+- [DROP PIPE](DROP_PIPE.md)
+- [SUSPEND or RESUME PIPE](SUSPEND_or_RESUME_PIPE.md)
+- [RETRY FILE](RETRY_FILE.md)
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/pipe/SUSPEND_or_RESUME_PIPE.md b/docs/en/sql-reference/sql-statements/loading_unloading/pipe/SUSPEND_or_RESUME_PIPE.md
new file mode 100644
index 00000000000000..f65fdf4fabfb38
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/pipe/SUSPEND_or_RESUME_PIPE.md
@@ -0,0 +1,58 @@
+---
+displayed_sidebar: docs
+---
+
+# SUSPEND or RESUME PIPE
+
+## Description
+
+Suspends or resumes a pipe:
+
+- When a load job is in progress (namely, in the `RUNNING` state), suspending (`SUSPEND`) the pipe for the job interrupts the job.
+- When a load job encounters errors, resuming (`RESUME`) the pipe for the job will continue to run the erroneous job.
+
+This command is supported from v3.2 onwards.
+
+## Syntax
+
+```SQL
+ALTER PIPE [ IF EXISTS ] <pipe_name> { SUSPEND | RESUME [ IF SUSPENDED ] }
+```
+
+## Parameters
+
+### pipe_name
+
+The name of the pipe.
+
+## Examples
+
+### Suspend a pipe
+
+Suspend the pipe named `user_behavior_replica` (which is in the `RUNNING` state) in the database named `mydatabase`:
+
+```SQL
+USE mydatabase;
+ALTER PIPE user_behavior_replica SUSPEND;
+```
+
+If you use [SHOW PIPES](SHOW_PIPES.md) to query the pipe, you can see that its state has changed to `SUSPEND`.
+
+### Resume a pipe
+
+Resume the pipe named `user_behavior_replica` in the database named `mydatabase`:
+
+```SQL
+USE mydatabase;
+ALTER PIPE user_behavior_replica RESUME;
+```
+
+If you use [SHOW PIPES](SHOW_PIPES.md) to query the pipe, you can see that its state has changed to `RUNNING`.
+
+## References
+
+- [CREATE PIPE](CREATE_PIPE.md)
+- [ALTER PIPE](ALTER_PIPE.md)
+- [DROP PIPE](DROP_PIPE.md)
+- [SHOW PIPES](SHOW_PIPES.md)
+- [RETRY FILE](RETRY_FILE.md)
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md
new file mode 100644
index 00000000000000..959aa1f39176a7
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md
@@ -0,0 +1,128 @@
+---
+displayed_sidebar: docs
+---
+
+# ALTER ROUTINE LOAD
+
+import RoutineLoadPrivNote from '../../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
+
+## Description
+
+Alters a Routine Load job that is in the `PAUSED` state. You can execute PAUSE ROUTINE LOAD to pause a Routine Load job.
+
+After successfully altering a Routine Load job, you can:
+
+- Check the modifications made to the Routine Load job by using [SHOW ROUTINE LOAD](SHOW_ROUTINE_LOAD.md).
+- Resume the Routine Load job by using [RESUME ROUTINE LOAD](RESUME_ROUTINE_LOAD.md).
+
+<RoutineLoadPrivNote />
+
+## Syntax
+
+```SQL
+ALTER ROUTINE LOAD FOR [<db_name>.]<job_name>
+[load_properties]
+[job_properties]
+FROM data_source
+[data_source_properties]
+```
+
+## Parameters
+
+- **`[<db_name>.]<job_name>`**
+  - **`db_name`**: Optional. The name of the StarRocks database.
+  - **`job_name`:** Required. The name of the Routine Load job to be altered.
+- **`load_properties`**
+
+   The properties of the source data to be loaded. The syntax is as follows:
+
+   ```SQL
+   [COLUMNS TERMINATED BY '<column_separator>'],
+   [ROWS TERMINATED BY '<row_separator>'],
+   [COLUMNS ([<column_name> [, ...] ] [, column_assignment [, ...] ] )],
+   [WHERE <expr>],
+   [PARTITION ([ <partition_name> [, ...] ])]
+   [TEMPORARY PARTITION (<temporary_partition1_name>[,<temporary_partition2_name>,...])]
+   ```
+
+   For detailed parameter descriptions, see [CREATE ROUTINE LOAD](CREATE_ROUTINE_LOAD.md#load_properties).
+
+- **`job_properties`**
+
+  The properties of the load job. The syntax is as follows:
+
+  ```SQL
+  PROPERTIES ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
+  ```
+
+  Only the following parameters can be altered:
+
+  - `desired_concurrent_number`
+
+  - `max_error_number`
+
+  - `max_batch_interval`
+
+  - `max_batch_rows`
+
+  - `max_batch_size`
+
+  - `jsonpaths`
+
+  - `json_root`
+
+  - `strip_outer_array`
+
+  - `strict_mode`
+
+  - `timezone`
+
+  For detailed parameter descriptions, see [CREATE ROUTINE LOAD](CREATE_ROUTINE_LOAD.md#job_properties).
+
+- **`data_source`** **and** **`data_source_properties`**
+
+  - **`data_source`**
+
+    Required. The source of the data you want to load. Valid value: `KAFKA`.
+
+  - **`data_source_properties`**
+
+    The properties of the data source. Currently, only the following properties can be altered:
+    - `kafka_partitions` and `kafka_offsets`: Note that StarRocks only supports modifying the offset of Kafka partitions that have already been consumed but does not support adding new Kafka partitions.
+    - `property.*`: Custom parameters for the data source Kafka, such as `property.kafka_default_offsets`.
+
+## Examples
+
+1. The following example increases the value of the property `desired_concurrent_number` of the load job to `5` in order to increase the parallelism of load tasks. For details on task parallelism, see [how to improve load performance](../../../../faq/loading/Routine_load_faq.md#how-can-i-improve-loading-performance).
+
+   ```SQL
+   ALTER ROUTINE LOAD FOR example_tbl_ordertest
+   PROPERTIES
+   (
+   "desired_concurrent_number" = "5"
+   );
+   ```
+
+2. The following example alters the load job's properties and data source information at the same time.
+
+   ```SQL
+   ALTER ROUTINE LOAD FOR example_tbl_ordertest
+   PROPERTIES
+   (
+   "desired_concurrent_number" = "5"
+   )
+   FROM KAFKA
+   (
+   "kafka_partitions" = "0, 1, 2",
+   "kafka_offsets" = "100, 200, 100",
+   "property.group.id" = "new_group"
+   );
+   ```
+
+3. The following example alters the filtering condition and the StarRocks partitions that data is loaded into at the same time.
+
+   ```SQL
+   ALTER ROUTINE LOAD FOR example_tbl_ordertest
+   WHERE pay_dt < 2023-06-31
+   PARTITION (p202306);
+   ```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md
new file mode 100644
index 00000000000000..75eea2d86f8e0f
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md
@@ -0,0 +1,968 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE ROUTINE LOAD
+
+:::tip
+Try Routine Load out in this [Quick Start](../../../../quick_start/routine-load.md)
+:::
+
+Routine Load can continuously consume messages from Apache Kafka® and load data into StarRocks. Routine Load can consume CSV, JSON, and Avro (supported since v3.0.1) data from a Kafka cluster and access Kafka via multiple security protocols, including `plaintext`, `ssl`, `sasl_plaintext`, and `sasl_ssl`.
+
+This topic describes the syntax, parameters, and examples of the CREATE ROUTINE LOAD statement.
+
+> **NOTE**
+>
+> - For information about the application scenarios, principles, and basic operations of Routine Load, see [Load data using Routine Load](../../../../loading/RoutineLoad.md).
+> - You can load data into StarRocks tables only as a user who has the INSERT privilege on those StarRocks tables. If you do not have the INSERT privilege, follow the instructions provided in [GRANT](../../account-management/GRANT.md) to grant the INSERT privilege to the user that you use to connect to your StarRocks cluster.
+
+## Syntax
+
+```SQL
+CREATE ROUTINE LOAD <database_name>.<job_name> ON <table_name>
+[load_properties]
+[job_properties]
+FROM data_source
+[data_source_properties]
+```
+
+## Parameters
+
+### `database_name`, `job_name`, `table_name`
+
+`database_name`
+
+Optional. The name of the StarRocks database.
+
+`job_name`
+
+Required. The name of the Routine Load job. A table may receive data from multiple Routine Load jobs.  We recommend that you set a meaningful Routine Load job name by using identifiable information, for example, Kafka topic name and the approximate job creation time, to distinguish multiple Routine Load jobs. The name of the Routine Load job must be unique within the same database.
+
+`table_name`
+
+Required. The name of the StarRocks table to which data is loaded.
+
+### `load_properties`
+
+Optional. The properties of the data. Syntax:
+
+```SQL
+[COLUMNS TERMINATED BY '<column_separator>'],
+[ROWS TERMINATED BY '<row_separator>'],
+[COLUMNS (<column1_name>[, <column2_name>, <column_assignment>, ... ])],
+[WHERE <expr>],
+[PARTITION (<partition1_name>[, <partition2_name>, ...])]
+[TEMPORARY PARTITION (<temporary_partition1_name>[, <temporary_partition2_name>, ...])]
+```
+
+`COLUMNS TERMINATED BY`
+
+The column separator for CSV-formatted data. The default column separator is `\t` (Tab). For example, you can use `COLUMNS TERMINATED BY ","` to specify the column separator as a comma.
+
+> **Note**
+>
+> - Ensure that the column separator specified here is the same as the column separator in the data to be ingested.
+> - You can use a UTF-8 string, such as a comma (,), tab, or pipe (|), whose length does not exceed 50 bytes as a text delimiter.
+> - Null values are denoted by using `\N`. For example, a data record consists of three columns, and the data record holds data in the first and third columns but does not hold data in the second column. In this situation, you need to use `\N` in the second column to denote a null value. This means the record must be compiled as `a,\N,b` instead of `a,,b`. `a,,b` denotes that the second column of the record holds an empty string.
+
+`ROWS TERMINATED BY`
+
+The row separator for CSV-formatted data. The default row separator is `\n`.
+
+`COLUMNS`
+
+The mapping between the columns in the source data and the columns in the StarRocks table. For more information, see [Column mapping](#column-mapping) in this topic.
+
+- `column_name`: If a column of the source data can be mapped to a column of the StarRocks table without any computation, you only need to specify the column name. These columns can be referred to as mapped columns.
+- `column_assignment`: If a column of the source data cannot be directly mapped to a column of the StarRocks table, and the column's values must be computed by using functions before data loading, you must specify the computation function in `expr`. These columns can be referred to as derived columns.
+  It is recommended to place derived columns after mapped columns because StarRocks first parses mapped columns.
+
+`WHERE`
+
+The filter condition. Only data that meets the filter condition can be loaded into StarRocks. For example, if you only want to ingest rows whose `col1` value is greater than `100` and `col2` value is equal to `1000`, you can use `WHERE col1 > 100 and col2 = 1000`.
+
+> **NOTE**
+>
+> The columns specified in the filter condition can be source columns or derived columns.
+
+`PARTITION`
+
+If a StarRocks table is distributed on partitions p0, p1, p2 and p3, and you want to load the data only to p1, p2, and p3 in StarRocks and filter out the data that will be stored in p0, then you can specify `PARTITION(p1, p2, p3)` as a filter condition. By default, if you do not specify this parameter, the data will be loaded into all the partitions. Example:
+
+```SQL
+PARTITION (p1, p2, p3)
+```
+
+`TEMPORARY PARTITION`
+
+The name of the [temporary partition](../../../../table_design/Temporary_partition.md) into which you want to load data. You can specify multiple temporary partitions, which must be separated by commas (,).
+
+### `job_properties`
+
+Required. The properties of the load job. Syntax:
+
+```SQL
+PROPERTIES ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
+```
+
+| **Property**              | **Required** | **Description**                                              |
+| ------------------------- | ------------ | ------------------------------------------------------------ |
+| desired_concurrent_number | No           | The expected task parallelism of a single Routine Load job. Default value: `3`. The actual task parallelism is determined by the minimum value of the multiple parameters: `min(alive_be_number, partition_number, desired_concurrent_number, max_routine_load_task_concurrent_num)`. <ul><li>`alive_be_number`: the number of alive BE nodes.</li><li>`partition_number`: the number of partitions to be consumed.</li><li>`desired_concurrent_number`: the expected task parallelism of a single Routine Load  job. Default value: `3`.</li><li>`max_routine_load_task_concurrent_num`: the default maximum task parallelism of a Routine Load job, which is `5`. See [FE dynamic parameter](../../../../administration/management/FE_configuration.md#configure-fe-dynamic-parameters).</li></ul>The maximum actual task parallelism is determined by either the number of alive BE nodes or the number of partitions to be consumed.|
+| max_batch_interval        | No           | The scheduling interval for a task, that is, how often a task is executed. Unit: seconds. Value range: `5` ~ `60`. Default value: `10`. It is recommended to set a value larger than `10`. If the scheduling is shorter than 10 seconds, too many tablet versions are generated due to an excessively high loading frequency. |
+| max_batch_rows            | No           | This property is only used to define the window of error detection. The window is the number of rows of data consumed by a single Routine Load task. The value is `10 * max_batch_rows`. The default value is `10 * 200000 = 2000000`. The Routine Load task detects error data in the error detection window. Error data refers to data that StarRocks cannot parse, such as invalid JSON-formatted data. |
+| max_error_number          | No           | The maximum number of error data rows allowed within an error detection window. If the number of error data rows exceeds this value, the load job will pause. You can execute [SHOW ROUTINE LOAD](SHOW_ROUTINE_LOAD.md)  and view the error logs by using `ErrorLogUrls`. After that, you can correct the error in Kafka according to the error logs. The default value is `0`, which means error rows are not allowed. <br />**NOTE** <br /> <ul><li>The last batch of tasks will **succeed** before the load job pauses when there are too many error data rows. That is, the qualified data will be loaded, and the unqualified data will be filtered. If you don't want to filter too many unqualified data rows, set parameter `max_filter_ratio`. </li><li>Error data rows do not include data rows that are filtered out by the WHERE clause.</li><li>This parameter, along with the next parameter `max_filter_ratio`, controls the maximum number of error data records. When `max_filter_ratio` is not set, the value of this parameter takes effect. When `max_filter_ratio` is set, the load job pauses as soon as the number of error data record reaches either the threshold set by this parameter or the `max_filter_ratio` parameter.</li></ul>|
+|max_filter_ratio|No|The maximum error tolerance of the load job. The error tolerance is the maximum percentage of data records that can be filtered out due to inadequate data quality in all data records requested by the load job. Valid values: `0` to `1`. Default value: `1` (That means it won't actually take effect).<br/>We recommend that you set it to `0`. This way, if unqualified data records are detected, the load job pauses, thereby ensuring data correctness.<br/>If you want to ignore unqualified data records, you can set this parameter to a value greater than `0`. This way, the load job can succeed even if the data file contains unqualified data records.  <br/>**NOTE**<br/><ul><li>The last batch of tasks will **fail** when there are too many error data rows larger than `max_filter_ratio`. It's a bit **different** with the effect of `max_error_number`.</li><li>Unqualified data records do not include data records that are filtered out by the WHERE clause.</li><li>This parameter, along with the last parameter `max_error_number`, controls the maximum number of error data records. When this parameter is not set (It works the same as setting `max_filter_ratio = 1`), the value of the `max_error_number` parameter takes effect. When this parameter is set, the load job pauses as soon as the number of error data records reaches either the threshold set by this parameter or the `max_error_number` parameter.</li></ul>|
+| strict_mode               | No           | Specifies whether to enable the [strict mode](../../../../loading/load_concept/strict_mode.md). Valid values: `true` and `false`. Default value: `false`. When the strict mode is enabled, if the value for a column in the loaded data is `NULL` but the target table does not allow a `NULL` value for this column, the data row will be filtered out. |
+| log_rejected_record_num | No | Specifies the maximum number of unqualified data rows that can be logged. This parameter is supported from v3.1 onwards. Valid values: `0`, `-1`, and any non-zero positive integer. Default value: `0`.<ul><li>The value `0` specifies that data rows that are filtered out will not be logged.</li><li>The value `-1` specifies that all data rows that are filtered out will be logged.</li><li>A non-zero positive integer such as `n` specifies that up to `n` data rows that are filtered out can be logged on each BE.</li></ul> |
+| timezone                  | No           | The time zone used by the load job. Default value: `Asia/Shanghai`. The value of this parameter affects the results returned by functions such as strftime(), alignment_timestamp(), and from_unixtime(). The time zone specified by this parameter is a session-level time zone. For more information, see [Configure a time zone](../../../../administration/management/timezone.md). |
+| partial_update | No | Whether to use partial updates. Valid values: `TRUE` and `FALSE`. Default value: `FALSE`, indicating to disable this feature. |
+| merge_condition           | No           | Specifies the name of the column you want to use as the condition to determine whether to update data. Data will be updated only when the value of the data to be loaded into this column is greater than or equal to the current value of this column. For more information, see [Change data through loading](../../../../loading/Load_to_Primary_Key_tables.md).<br />**NOTE**<br />Only Primary Key tables support conditional updates. The column that you specify cannot be a primary key column. |
+| format                    | No           | The format of the data to be loaded. Valid values: `CSV`, `JSON`, and `Avro` (supported since v3.0.1). Default value: `CSV`. |
+| trim_space                | No           | Specifies whether to remove spaces preceding and following column separators from the data file when the data file is in CSV format. Type: BOOLEAN. Default value: `false`.<br />For some databases, spaces are added to column separators when you export data as a CSV-formatted data file. Such spaces are called leading spaces or trailing spaces depending on their locations. By setting the `trim_space` parameter, you can enable StarRocks to remove such unnecessary spaces during data loading.<br />Note that StarRocks does not remove the spaces (including leading spaces and trailing spaces) within a field wrapped in a pair of `enclose`-specified characters. For example, the following field values use pipe (<code class="language-text">&#124;</code>) as the column separator and double quotation marks (`"`) as the `enclose`-specified character: <code class="language-text">&#124; "Love StarRocks" &#124;</code>. If you set `trim_space` to `true`, StarRocks processes the preceding field values as <code class="language-text">&#124;"Love StarRocks"&#124;</code>. |
+| enclose                   | No           | Specifies the character that is used to wrap the field values in the data file according to [RFC4180](https://www.rfc-editor.org/rfc/rfc4180) when the data file is in CSV format. Type: single-byte character. Default value: `NONE`. The most prevalent characters are single quotation mark (`'`) and double quotation mark (`"`).<br />All special characters (including row separators and column separators) wrapped by using the `enclose`-specified character are considered normal symbols. StarRocks can do more than RFC4180 as it allows you to specify any single-byte character as the `enclose`-specified character.<br />If a field value contains an `enclose`-specified character, you can use the same character to escape that `enclose`-specified character. For example, you set `enclose` to `"`, and a field value is `a "quoted" c`. In this case, you can enter the field value as `"a ""quoted"" c"` into the data file. |
+| escape                    | No           | Specifies the character that is used to escape various special characters, such as row separators, column separators, escape characters, and `enclose`-specified characters, which are then considered by StarRocks to be common characters and are parsed as part of the field values in which they reside. Type: single-byte character. Default value: `NONE`. The most prevalent character is slash (`\`), which must be written as double slashes (`\\`) in SQL statements.<br />**NOTE**<br />The character specified by `escape` is applied to both inside and outside of each pair of `enclose`-specified characters.<br />Two examples are as follows:<br /><ul><li>When you set `enclose` to `"` and `escape` to `\`, StarRocks parses `"say \"Hello world\""` into `say "Hello world"`.</li><li>Assume that the column separator is comma (`,`). When you set `escape` to `\`, StarRocks parses `a, b\, c` into two separate field values: `a` and `b, c`.</li></ul> |
+| strip_outer_array         | No           | Specifies whether to strip the outermost array structure of the JSON-formatted data. Valid values: `true` and `false`. Default value: `false`. In real-world business scenarios, JSON-formatted data may have an outermost array structure as indicated by a pair of square brackets `[]`. In this situation, we recommend that you set this parameter to `true`, so StarRocks removes the outermost square brackets `[]` and loads each inner array as a separate data record. If you set this parameter to `false`, StarRocks parses the entire JSON-formatted data into one array and loads the array as a single data record. Use the JSON-formatted data `[{"category" : 1, "author" : 2}, {"category" : 3, "author" : 4} ]` as an example. If you set this parameter to `true`, `{"category" : 1, "author" : 2}` and `{"category" : 3, "author" : 4}` are parsed as two separate data records and are loaded into two StarRocks data rows. |
+| jsonpaths                 | No           | The names of the fields that you want to load from JSON-formatted data. The value of this parameter is a valid JsonPath expression. For more information, see [StarRocks table contains derived columns whose values are generated by using expressions](#starrocks-table-contains-derived-columns-whose-values-are-generated-by-using-expressions)) in this topic. |
+| json_root                 | No           | The root element of the JSON-formatted data to load. StarRocks extracts the elements of the root node through `json_root` for parsing. By default, the value of this parameter is empty, indicating that all JSON-formatted data will be loaded. For more information, see [Specify the root element of the JSON-formatted data to be loaded](#specify-the-root-element-of-the-json-formatted-data-to-be-loaded) in this topic. |
+| task_consume_second | No | The maximum time for each Routine Load task within the specified Routine Load job to consume data. Unit: second. Unlike the [FE dynamic parameters](../../../../administration/management/FE_configuration.md) `routine_load_task_consume_second` (which applies to all Routine Load jobs within the cluster), this parameter is specific to an individual Routine Load job, which is more flexible. This parameter is supported since v3.1.0.<ul> <li>When `task_consume_second` and `task_timeout_second` are not configured, StarRocks uses the FE dynamic parameters `routine_load_task_consume_second` and `routine_load_task_timeout_second` to control the load behavior.</li> <li>When only `task_consume_second` is configured, the default value for `task_timeout_second` is calculated as `task_consume_second` * 4.</li> <li>When only `task_timeout_second` is configured, the default value for `task_consume_second` is calculated as `task_timeout_second`/4.</li> </ul> |
+|task_timeout_second|No|The timeout duration for each Routine Load task within the specified Routine Load job. Unit: second. Unlike the [FE dynamic parameter](../../../../administration/management/FE_configuration.md) `routine_load_task_timeout_second` (which applies to all Routine Load jobs within the cluster), this parameter is specific to an individual Routine Load job, which is more flexible. This parameter is supported since v3.1.0. <ul> <li>When `task_consume_second` and `task_timeout_second` are not configured, StarRocks uses the FE dynamic parameters `routine_load_task_consume_second` and `routine_load_task_timeout_second` to control the load behavior.</li> <li>When only `task_timeout_second` is configured, the default value for `task_consume_second` is calculated as `task_timeout_second`/4.</li> <li>When only `task_consume_second` is configured, the default value for `task_timeout_second` is calculated as `task_consume_second` * 4.</li> </ul>|
+
+### `data_source`, `data_source_properties`
+
+Required. The data source and relevant properties.
+
+```sql
+FROM <data_source>
+ ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
+```
+
+`data_source`
+
+Required. The source of the data you want to load. Valid value: `KAFKA`.
+
+`data_source_properties`
+
+The properties of the data source.
+
+| Property          | Required | Description                                                  |
+| ----------------- | -------- | ------------------------------------------------------------ |
+| kafka_broker_list | Yes      | Kafka's broker connection information. The format is `<kafka_broker_ip>:<broker_ port>`. Multiple brokers are separated by commas (,). The default port used by Kafka brokers is `9092`. Example:`"kafka_broker_list" = ""xxx.xx.xxx.xx:9092,xxx.xx.xxx.xx:9092"`. |
+| kafka_topic       | Yes      | The  Kafka topic to be consumed. A Routine Load job can only consume messages from one topic. |
+| kafka_partitions  | No       | The Kafka partitions to be consumed, for example, `"kafka_partitions" = "0, 1, 2, 3"`. If this property is not specified, all partitions are consumed by default. |
+| kafka_offsets     | No       | The starting offset from which to consume data in a Kafka partition as specified in `kafka_partitions`. If this property is not specified, the Routine Load job consumes data starting from the latest offsets in `kafka_partitions`. Valid values:<ul><li>A specific offset: consumes data starting from a specific offset.</li><li>`OFFSET_BEGINNING`: consumes data starting from the earliest offset possible.</li><li>`OFFSET_END`: consumes data starting from the latest offset.</li></ul> Multiple starting offsets are separated by commas (,), for example, `"kafka_offsets" = "1000, OFFSET_BEGINNING, OFFSET_END, 2000"`.|
+| property.kafka_default_offsets| No| The default starting offset for all consumer partitions. The supported values for this property are same as those for the `kafka_offsets` property.|
+| confluent.schema.registry.url|No |The URL of the Schema Registry where the Avro schema is registered. StarRocks retrieves the Avro schema by using this URL. The format is as follows:<br />`confluent.schema.registry.url = http[s]://[<schema-registry-api-key>:<schema-registry-api-secret>@]<hostname or ip address>[:<port>]`|
+
+#### More data source-related properties
+
+You can specify additional data source (Kafka) related properties, which are equivalent to using the Kafka command line `--property`. For more supported properties, see the properties for a Kafka consumer client in [librdkafka configuration properties](https://github.com/confluentinc/librdkafka/blob/master/CONFIGURATION.md).
+
+> **NOTE**
+>
+> If the value of a property is a file name, add the keyword `FILE:` preceding the file name. For information about how to create a file, see [CREATE FILE](../../cluster-management/file/CREATE_FILE.md).
+
+- **Specify the default initial offset for all the partitions to be consumed**
+
+```SQL
+"property.kafka_default_offsets" = "OFFSET_BEGINNING"
+```
+
+- **Specify the ID of the consumer group used by the Routine Load job**
+
+```SQL
+"property.group.id" = "group_id_0"
+```
+
+If `property.group.id` is not specified, StarRocks generates a random value based on the name of the Routine Load job, in the format of `{job_name}_{random uuid}`, such as `simple_job_0a64fe25-3983-44b2-a4d8-f52d3af4c3e8`.
+
+- **Specify the security protocol and relevant parameters used by BE to access Kafka**
+
+  The security protocol can be specified as `plaintext` (default), `ssl`, `sasl_plaintext`, or `sasl_ssl`. And you need to configure the related parameters according to the specified security protocol.
+
+  When the security protocol is set to `sasl_plaintext` or `sasl_ssl`, the following SASL authentication mechanisms are supported:
+
+  - PLAIN
+  - SCRAM-SHA-256 and SCRAM-SHA-512
+  - OAUTHBEARER
+  - GSSAPI (Kerberos)
+
+  **Examples:**
+
+  - Access Kafka using the SSL security protocol:
+
+    ```SQL
+    "property.security.protocol" = "ssl", -- Specify the security protocol as SSL.
+    "property.ssl.ca.location" = "FILE:ca-cert", -- File or directory path to CA certificate(s) for verifying the kafka broker's key.
+    -- If the Kafka server enables client authentication, the following three parameters are also required:
+    "property.ssl.certificate.location" = "FILE:client.pem", -- Path to the client's public key used for authentication.
+    "property.ssl.key.location" = "FILE:client.key", -- Path to the client's private key used for authentication.
+    "property.ssl.key.password" = "xxxxxx" -- Password for the client's private key.
+    ```
+
+  - Access Kafka using the SASL_PLAINTEXT security protocol and SASL/PLAIN authentication mechanism:
+
+    ```SQL
+    "property.security.protocol" = "SASL_PLAINTEXT", -- Specify the security protocol as SASL_PLAINTEXT.
+    "property.sasl.mechanism" = "PLAIN", -- Specify the SASL mechanism as PLAIN which is a simple username/password authentication mechanism.
+    "property.sasl.username" = "admin",  -- SASL username.
+    "property.sasl.password" = "xxxxxx"  -- SASL password.
+    ```
+
+  - Access Kafka using the SASL_PLAINTEXT security protocol and SASL/GSSAPI (Kerberos) authentication mechanism:
+
+    ```sql
+    "property.security.protocol" = "SASL_PLAINTEXT", -- Specify the security protocol as SASL_PLAINTEXT.
+    "property.sasl.mechanism" = "GSSAPI", -- Specify the SASL authentication mechanism as GSSAPI. Default value is GSSAPI.
+    "property.sasl.kerberos.service.name" = "kafka", -- The broker service name. Default value is kafka.
+    "property.sasl.kerberos.keytab" = "/home/starrocks/starrocks.keytab", -- The client keytab location.
+    "property.sasl.kerberos.principal" = "starrocks@YOUR.COM" -- The Kerberos principal.
+    ```
+
+    :::note
+
+    - Since StarRocks v3.1.4, SASL/GSSAPI (Kerberos) authentication is supported.
+    - SASL related modules need to be installed on the BE machine.
+
+        ```bash
+        # Debian/Ubuntu:
+        sudo apt-get install libsasl2-modules-gssapi-mit libsasl2-dev
+        # CentOS/Redhat:
+        sudo yum install cyrus-sasl-gssapi cyrus-sasl-devel
+        ```
+
+    :::
+
+### FE and BE configuration items
+
+For FE and BE configuration items related to Routine Load, see [configuration items](../../../../administration/management/FE_configuration.md).
+
+## Column mapping
+
+### Configure column mapping for loading CSV-formatted data
+
+If the columns of the  CSV-formatted data can be mapped one on one in sequence to the columns of the StarRocks table, you do not need to configure the column mapping between the data and the StarRocks table.
+
+If the columns of the CSV-formatted data cannot be mapped one on one in sequence to the columns of the StarRocks table, you need to use the `columns` parameter to configure the column mapping between the data file and the StarRocks table. This includes the following two use cases:
+
+- **Same number of columns but different column sequence. Also, the data from the data file does not need to be computed by functions before it is loaded into the matching StarRocks table columns.**
+
+  - In the `columns` parameter, you need to specify the names of the StarRocks table columns in the same sequence as how the data file columns are arranged.
+
+  - For example, the StarRocks table consists of three columns, which are `col1`, `col2`, and `col3` in sequence, and the data file also consists of three columns, which can be mapped to the StarRocks table columns `col3`, `col2`, and `col1` in sequence. In this case, you need to specify `"columns: col3, col2, col1"`.
+
+- **Different number of columns and different column sequence. Also, the data from the data file needs to be computed by functions before it is loaded into the matching StarRocks table columns.**
+
+  In the `columns` parameter, you need to specify the names of the StarRocks table columns in the same sequence as how the data file columns are arranged and specify the functions you want to use to compute the data. Two examples are as follows:
+
+  - The StarRocks table consists of three columns, which are `col1`, `col2`, and `col3` in sequence. The data file consists of four columns, among which the first three columns can be mapped in sequence to the StarRocks table columns `col1`, `col2`, and `col3` and the fourth column cannot be mapped to any of the StarRocks table columns. In this case, you need to temporarily specify a name for the fourth column of the data file, and the temporary name must be different from any of the StarRocks table column names. For example, you can specify `"columns: col1, col2, col3, temp"`, in which the fourth column of the data file is temporarily named `temp`.
+  - The StarRocks table consists of three columns, which are `year`, `month`, and `day` in sequence. The data file consists of only one column that accommodates date and time values in `yyyy-mm-dd hh:mm:ss` format. In this case, you can specify `"columns: col, year = year(col), month=month(col), day=day(col)"`, in which `col` is the temporary name of the data file column and the functions `year = year(col)`, `month=month(col)`, and `day=day(col)` are used to extract data from the data file column `col` and loads the data into the mapping StarRocks table columns. For example, `year = year(col)` is used to extract the `yyyy` data from the data file column `col` and loads the data into the StarRocks table column `year`.
+
+For more examples, see [Configure column mapping](#configure-column-mapping).
+
+### Configure column mapping for loading JSON-formatted or Avro-formatted data
+
+> **NOTE**
+>
+> Since v3.0.1, StarRocks supports loading Avro data by using Routine Load. When you load JSON or Avro data, the configuration for column mapping and transformation is the same. Therefore, in this section, JSON data is used as an example to introduce the configuration.
+
+If the keys of the JSON-formatted data have the same names as the columns of the StarRocks table, you can load the JSON-formatted data by using the simple mode. In simple mode, you do not need to specify the `jsonpaths` parameter. This mode requires that the JSON-formatted data must be an object as indicated by curly brackets `{}`, such as `{"category": 1, "author": 2, "price": "3"}`. In this example, `category`, `author`, and `price` are key names, and these keys can be mapped one on one by name to the columns `category`, `author`, and `price` of the StarRocks table. For examples, please see [simple mode](#starrocks-table-column-names-consistent-with-json-key-names).
+
+If the keys of the JSON-formatted data have different names than the columns of the StarRocks table, you can load the JSON-formatted data by using the matched mode. In matched mode, you need to use the `jsonpaths` and `COLUMNS` parameters to specify the column mapping between the JSON-formatted data and the StarRocks table:
+
+- In the `jsonpaths` parameter, specify the JSON keys in the sequence as how they are arranged in the JSON-formatted data.
+- In the `COLUMNS` parameter, specify the mapping between the JSON keys and the StarRocks table columns:
+  - The column names specified in the `COLUMNS` parameter are mapped one on one in sequence to the JSON-formatted data.
+  - The column names specified in the `COLUMNS` parameter are mapped one on one by name to the StarRocks table columns.
+
+For examples, see [StarRocks table contains derived columns whose values are generated by using expressions](#starrocks-table-contains-derived-columns-whose-values-are-generated-by-using-expressions).
+
+## Examples
+
+### Load  CSV-formatted data
+
+This section uses  CSV-formatted data as an example to describe how you can employ various parameter settings and combinations to meet your diverse loading requirements.
+
+**Prepare a dataset**
+
+Suppose you want to load CSV-formatted data from a Kafka topic named `ordertest1`.Every message in the dataset includes six columns: order ID, payment date, customer name, nationality, gender, and price.
+
+```plaintext
+2020050802,2020-05-08,Johann Georg Faust,Deutschland,male,895
+2020050802,2020-05-08,Julien Sorel,France,male,893
+2020050803,2020-05-08,Dorian Grey,UK,male,1262
+2020050901,2020-05-09,Anna Karenina,Russia,female,175
+2020051001,2020-05-10,Tess Durbeyfield,US,female,986
+2020051101,2020-05-11,Edogawa Conan,japan,male,8924
+```
+
+**Create a table**
+
+According to the columns of CSV-formatted data, create a table named `example_tbl1` in the database `example_db`.
+
+```SQL
+CREATE TABLE example_db.example_tbl1 ( 
+    `order_id` bigint NOT NULL COMMENT "Order ID",
+    `pay_dt` date NOT NULL COMMENT "Payment date", 
+    `customer_name` varchar(26) NULL COMMENT "Customer name", 
+    `nationality` varchar(26) NULL COMMENT "Nationality", 
+    `gender` varchar(26) NULL COMMENT "Gender", 
+    `price` double NULL COMMENT "Price") 
+DUPLICATE KEY (order_id,pay_dt) 
+DISTRIBUTED BY HASH(`order_id`); 
+```
+
+#### Consume data starting from specified offsets for specified partitions
+
+If the Routine Load job needs to consume data starting from specified partitions and offsets, you need to configure the parameters `kafka_partitions` and `kafka_offsets`.
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest1",
+    "kafka_partitions" ="0,1,2,3,4", -- partitions to be consumed
+    "kafka_offsets" = "1000, OFFSET_BEGINNING, OFFSET_END, 2000" -- corresponding initial offsets
+);
+```
+
+#### Improve loading performance by increasing task parallelism
+
+To improve loading performance and avoid accumulative consumption, you can increase task parallelism by increasing the `desired_concurrent_number` value when you create the Routine Load job. Task parallelism allows splitting one Routine Load job into as many parallel tasks as possible.
+
+> **Note**
+>
+> For more ways to improve loading performance, see [Routine Load FAQ](../../../../faq/loading/Routine_load_faq.md).
+
+Note that the actual task parallelism is determined by the minimum value among the following multiple parameters:
+
+```SQL
+min(alive_be_number, partition_number, desired_concurrent_number, max_routine_load_task_concurrent_num)
+```
+
+> **Note**
+>
+> The maximum actual task parallelism is either the number of alive BE nodes or the number of partitions to be consumed.
+
+Therefore, when the number of alive BE nodes and the number of partitions to be consumed are greater than the values of the other two parameters `max_routine_load_task_concurrent_num` and `desired_concurrent_number`, you can increase the values of the other two parameters to increase the actual task parallelism.
+
+Assume that the number of partitions to be consumed is 7, the number of alive BE nodes is 5, and `max_routine_load_task_concurrent_num` is the default value `5`. If you want to increase the actual task parallelism, you can set `desired_concurrent_number` to `5` (the default value is `3`). In this case, the actual task parallelism `min(5,7,5,5)` is configured at `5`.
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
+PROPERTIES
+(
+"desired_concurrent_number" = "5" -- set the value of desired_concurrent_number to 5
+)
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest1"
+);
+```
+
+#### Configure column mapping
+
+If the sequence of columns in the CSV-formatted data is inconsistent with the columns in the target table, assuming that the fifth column in the CSV-formatted data does not need to be imported to the target table, you need to specify the column mapping between the CSV-formatted data and the target table through the `COLUMNS` parameter.
+
+**Target database and table**
+
+Create the target table `example_tbl2` in the target database `example_db` according to the columns in the CSV-formatted data. In this scenario, you need to create five columns corresponding to the five columns in the CSV-formatted data, except for the fifth column that stores gender.
+
+```SQL
+CREATE TABLE example_db.example_tbl2 ( 
+    `order_id` bigint NOT NULL COMMENT "Order ID",
+    `pay_dt` date NOT NULL COMMENT "Payment date", 
+    `customer_name` varchar(26) NULL COMMENT "Customer name", 
+    `nationality` varchar(26) NULL COMMENT "Nationality", 
+    `price` double NULL COMMENT "Price"
+) 
+DUPLICATE KEY (order_id,pay_dt) 
+DISTRIBUTED BY HASH(order_id); 
+```
+
+**Routine Load job**
+
+In this example, since the fifth column in the CSV-formatted data does not need to be loaded to the target table, the fifth column is temporarily named `temp_gender` in `COLUMNS`, and the other columns are directly mapped to the table `example_tbl2`.
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl2_ordertest1 ON example_tbl2
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, temp_gender, price)
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest1"
+);
+```
+
+#### Set filter conditions
+
+If you want to load only data that meets certain conditions, you can set filter conditions in the `WHERE` clause, for example, `price > 100.`
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl2_ordertest1 ON example_tbl2
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price),
+WHERE price > 100 -- set the filter condition
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest1"
+);
+```
+
+#### Enable strict mode to filter out rows with NULL values
+
+In `PROPERTIES`, you can set `"strict_mode" = "true"`, which means that the Routine Load job is in strict mode.  If there is a `NULL` value in a source column, but the destination StarRocks table column does not allow NULL values, the row that holds a NULL value in the source column is filtered out.
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
+PROPERTIES
+(
+"strict_mode" = "true" -- enable the strict mode
+)
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest1"
+);
+```
+
+#### Set error tolerance
+
+If your business scenario has low tolerance for unqualified data, you need to set the error detection window and the maximum number of error data rows by configuring the parameters `max_batch_rows` and `max_error_number`. When the number of error data rows within an error detection window exceeds the value of `max_error_number`, the Routine Load job pauses.
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
+PROPERTIES
+(
+"max_batch_rows" = "100000",-- The value of max_batch_rows multiplied by 10 equals the error detection window.
+"max_error_number" = "100" -- The maximum number of error data rows allowed within an error detection window.
+)
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest1"
+);
+```
+
+#### Specify the security protocol as SSL and configure the related parameters
+
+If you need to specify the security protocol as SSL used by BE to access Kafka, you need to configure `"property.security.protocol" = "ssl"` and related parameters.
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
+PROPERTIES
+(
+-- Specify the security protocol as SSL.
+"property.security.protocol" = "ssl",
+-- The location of the CA certificate.
+"property.ssl.ca.location" = "FILE:ca-cert",
+-- If authentication is enabled for Kafka clients, you need to configure the following properties:
+-- The location of the Kafka client's public key.
+"property.ssl.certificate.location" = "FILE:client.pem",
+-- The location of the Kafka client's private key.
+"property.ssl.key.location" = "FILE:client.key",
+-- The password to the Kafka client's private key.
+"property.ssl.key.password" = "abcdefg"
+)
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest1"
+);
+```
+
+#### Setting trim_space, enclose, and escape
+
+Suppose you want to load CSV-formatted data from a Kafka topic named `test_csv`. Every message in the dataset includes six columns: order ID, payment date, customer name, nationality, gender, and price.
+
+```Plaintext
+ "2020050802" , "2020-05-08" , "Johann Georg Faust" , "Deutschland" , "male" , "895"
+ "2020050802" , "2020-05-08" , "Julien Sorel" , "France" , "male" , "893"
+ "2020050803" , "2020-05-08" , "Dorian Grey\,Lord Henry" , "UK" , "male" , "1262"
+ "2020050901" , "2020-05-09" , "Anna Karenina" , "Russia" , "female" , "175"
+ "2020051001" , "2020-05-10" , "Tess Durbeyfield" , "US" , "female" , "986"
+ "2020051101" , "2020-05-11" , "Edogawa Conan" , "japan" , "male" , "8924"
+```
+
+If you want to load all data from the Kafka topic `test_csv` into `example_tbl1`, with the intention of removing the spaces preceding and following column separators and setting `enclose` to `"` and `escape` to `\`, run the following command:
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl1_test_csv ON example_tbl1
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
+PROPERTIES
+(
+    "trim_space"="true",
+    "enclose"="\"",
+    "escape"="\\",
+)
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic"="test_csv",
+    "property.kafka_default_offsets"="OFFSET_BEGINNING"
+);
+```
+
+### Load  JSON-formatted data
+
+#### StarRocks table column names consistent with JSON key names
+
+**Prepare a dataset**
+
+For example, the following JSON-formatted data exists in the Kafka topic `ordertest2`.
+
+```SQL
+{"commodity_id": "1", "customer_name": "Mark Twain", "country": "US","pay_time": 1589191487,"price": 875}
+{"commodity_id": "2", "customer_name": "Oscar Wilde", "country": "UK","pay_time": 1589191487,"price": 895}
+{"commodity_id": "3", "customer_name": "Antoine de Saint-Exupéry","country": "France","pay_time": 1589191487,"price": 895}
+```
+
+> **Note** Each JSON object must be in one Kafka message. Otherwise, an error that indicates a failure in parsing JSON-formatted data occurs.
+
+**Target database and table**
+
+Create table `example_tbl3` in the target database `example_db` in the StarRocks cluster. The column names are consistent with the keys names in the JSON-formatted data.
+
+```SQL
+CREATE TABLE example_db.example_tbl3 ( 
+    commodity_id varchar(26) NULL, 
+    customer_name varchar(26) NULL, 
+    country varchar(26) NULL, 
+    pay_time bigint(20) NULL, 
+    price double SUM NULL COMMENT "Price") 
+AGGREGATE KEY(commodity_id,customer_name,country,pay_time)
+DISTRIBUTED BY HASH(commodity_id); 
+```
+
+**Routine Load job**
+
+You can use the simple mode for the Routine Load job. That is, you do not need to specify `jsonpaths` and `COLUMNS` parameters when creating the Routine Load job. StarRocks extracts the keys of JSON-formatted data in the topic `ordertest2` of the Kafka cluster according to the column names of the target table `example_tbl3` and loads the JSON-formatted data into the target table.
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl3_ordertest2 ON example_tbl3
+PROPERTIES
+(
+    "format" = "json"
+ )
+FROM KAFKA
+(
+    "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest2"
+);
+```
+
+> **Note**
+>
+> - If the outermost layer of the JSON-formatted data is an array structure, you need to set `"strip_outer_array"="true"` in `PROPERTIES` to strip the outermost array structure. Additionally, when you need to specify `jsonpaths`, the root element of the entire JSON-formatted data is the flattened JSON object because the outermost array structure of the JSON-formatted data is stripped.
+> - You can use `json_root` to specify the root element of the JSON-formatted data.
+
+#### StarRocks table contains derived columns whose values are generated by using expressions
+
+**Prepare a dataset**
+
+For example, the following JSON-formatted data exists in the topic `ordertest2` of the Kafka cluster.
+
+```SQL
+{"commodity_id": "1", "customer_name": "Mark Twain", "country": "US","pay_time": 1589191487,"price": 875}
+{"commodity_id": "2", "customer_name": "Oscar Wilde", "country": "UK","pay_time": 1589191487,"price": 895}
+{"commodity_id": "3", "customer_name": "Antoine de Saint-Exupéry","country": "France","pay_time": 1589191487,"price": 895}
+```
+
+**Target database and table**
+
+Create a table named `example_tbl4` in the database `example_db` in the StarRocks cluster. The column `pay_dt` is a derived column whose values are generated by computing values of the key `pay_time` in the JSON-formatted data.
+
+```SQL
+CREATE TABLE example_db.example_tbl4 ( 
+    `commodity_id` varchar(26) NULL, 
+    `customer_name` varchar(26) NULL, 
+    `country` varchar(26) NULL,
+    `pay_time` bigint(20) NULL,  
+    `pay_dt` date NULL, 
+    `price` double SUM NULL) 
+AGGREGATE KEY(`commodity_id`,`customer_name`,`country`,`pay_time`,`pay_dt`) 
+DISTRIBUTED BY HASH(`commodity_id`); 
+```
+
+**Routine Load job**
+
+You can use the matched mode for the Routine Load job. That is, you need to specify `jsonpaths` and `COLUMNS` parameters when creating the Routine Load job.
+
+You need to specify the keys of the JSON-formatted data and arrange them in sequence in the `jsonpaths` parameter.
+
+And since the values in the key `pay_time` of the JSON-formatted data need to be converted to the DATE type before the values are stored in the `pay_dt` column of the `example_tbl4` table, you need to specify the computation by using `pay_dt=from_unixtime(pay_time,'%Y%m%d')` in `COLUMNS`. The values of other keys in the JSON-formatted data can be directly mapped to the `example_tbl4` table.
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl4_ordertest2 ON example_tbl4
+COLUMNS(commodity_id, customer_name, country, pay_time, pay_dt=from_unixtime(pay_time, '%Y%m%d'), price)
+PROPERTIES
+(
+    "format" = "json",
+    "jsonpaths" = "[\"$.commodity_id\",\"$.customer_name\",\"$.country\",\"$.pay_time\",\"$.price\"]"
+ )
+FROM KAFKA
+(
+    "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest2"
+);
+```
+
+> **Note**
+>
+> - If the outermost layer of the JSON data is an array structure, you need to set `"strip_outer_array"="true"` in the `PROPERTIES` to strip the outermost array structure. Additionally, when you need to specify `jsonpaths`, the root element of the entire JSON data is the flattened JSON object because the outermost array structure of the JSON data is stripped.
+> - You can use `json_root` to specify the root element of the JSON-formatted data.
+
+#### StarRocks table contains derived column whose values are generated by using CASE expression
+
+**Prepare a dataset**
+
+For example, the following JSON-formatted data exists in the Kafka topic `topic-expr-test`.
+
+```JSON
+{"key1":1, "key2": 21}
+{"key1":12, "key2": 22}
+{"key1":13, "key2": 23}
+{"key1":14, "key2": 24}
+```
+
+**Target database and table**
+
+Create a table named `tbl_expr_test` in the database `example_db` in the StarRocks cluster. The target table `tbl_expr_test` contains two columns, where the values of the `col2` column need to be computed by using case expression on JSON data.
+
+```SQL
+CREATE TABLE tbl_expr_test (
+    col1 string, col2 string)
+DISTRIBUTED BY HASH (col1);
+```
+
+**Routine Load job**
+
+Because the values in the `col2` column in the target table are generated using a CASE expression, you need to specify the corresponding expression in the `COLUMNS` parameter for the Routine load job.
+
+```SQL
+CREATE ROUTINE LOAD rl_expr_test ON tbl_expr_test
+COLUMNS (
+      key1,
+      key2,
+      col1 = key1,
+      col2 = CASE WHEN key1 = "1" THEN "key1=1" 
+                  WHEN key1 = "12" THEN "key1=12"
+                  ELSE "nothing" END) 
+PROPERTIES ("format" = "json")
+FROM KAFKA
+(
+    "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "topic-expr-test"
+);
+```
+
+**Query StarRocks table**
+
+Query the StarRocks table. The result shows that the values in the `col2` column are the output of the CASE expression.
+
+```SQL
+MySQL [example_db]> SELECT * FROM tbl_expr_test;
++------+---------+
+| col1 | col2    |
++------+---------+
+| 1    | key1=1  |
+| 12   | key1=12 |
+| 13   | nothing |
+| 14   | nothing |
++------+---------+
+4 rows in set (0.015 sec)
+```
+
+#### Specify the root element of the JSON-formatted data to be loaded
+
+You need to use `json_root` to specify the root element of the JSON-formatted data to be loaded and the value must be a valid JsonPath expression.
+
+**Prepare a dataset**
+
+For example, the following JSON-formatted data exists in the topic `ordertest3` of the Kafka cluster. And the root element of the JSON-formatted data to be loaded is `$.RECORDS`.
+
+```SQL
+{"RECORDS":[{"commodity_id": "1", "customer_name": "Mark Twain", "country": "US","pay_time": 1589191487,"price": 875},{"commodity_id": "2", "customer_name": "Oscar Wilde", "country": "UK","pay_time": 1589191487,"price": 895},{"commodity_id": "3", "customer_name": "Antoine de Saint-Exupéry","country": "France","pay_time": 1589191487,"price": 895}]}
+```
+
+**Target database and table**
+
+Create a table named `example_tbl3` in the database `example_db` in the StarRocks cluster.
+
+```SQL
+CREATE TABLE example_db.example_tbl3 ( 
+    commodity_id varchar(26) NULL, 
+    customer_name varchar(26) NULL, 
+    country varchar(26) NULL, 
+    pay_time bigint(20) NULL, 
+    price double SUM NULL) 
+AGGREGATE KEY(commodity_id,customer_name,country,pay_time) 
+ENGINE=OLAP
+DISTRIBUTED BY HASH(commodity_id); 
+```
+
+**Routine Load job**
+
+You can set `"json_root" = "$.RECORDS"` in `PROPERTIES` to specify the root element of the JSON-formatted data to be loaded. Also, since the JSON-formatted data to be loaded is in an array structure, you must also set `"strip_outer_array" = "true"` to strip the outermost array structure.
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl3_ordertest3 ON example_tbl3
+PROPERTIES
+(
+    "format" = "json",
+    "json_root" = "$.RECORDS",
+    "strip_outer_array" = "true"
+ )
+FROM KAFKA
+(
+    "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest2"
+);
+```
+
+### Load Avro-formatted data
+
+Since v3.0.1, StarRocks supports loading Avro data by using Routine Load.
+
+#### Avro schema is simple
+
+Suppose the Avro schema is relatively simple, and you need to load all fields of the Avro data.
+
+**Prepare a dataset**
+
+- **Avro schema**
+
+    1. Create the following Avro schema file `avro_schema1.avsc`:
+
+        ```json
+        {
+            "type": "record",
+            "name": "sensor_log",
+            "fields" : [
+                {"name": "id", "type": "long"},
+                {"name": "name", "type": "string"},
+                {"name": "checked", "type" : "boolean"},
+                {"name": "data", "type": "double"},
+                {"name": "sensor_type", "type": {"type": "enum", "name": "sensor_type_enum", "symbols" : ["TEMPERATURE", "HUMIDITY", "AIR-PRESSURE"]}}  
+            ]
+        }
+        ```
+
+    2. Register the Avro schema in the [Schema Registry](https://docs.confluent.io/platform/current/schema-registry/index.html).
+
+- **Avro data**
+
+Prepare the Avro data and send it to the Kafka topic `topic_1`.
+
+**Target database and table**
+
+According to the fields of Avro data, create a table `sensor_log1` in the target database `sensor` in the StarRocks cluster. The column names of the table must match the field names in the Avro data. For the data types mapping when Avro data is loaded into StarRocks, see [Data types mapping](#Data types mapping).
+
+```SQL
+CREATE TABLE sensor.sensor_log1 ( 
+    `id` bigint NOT NULL COMMENT "sensor id",
+    `name` varchar(26) NOT NULL COMMENT "sensor name", 
+    `checked` boolean NOT NULL COMMENT "checked", 
+    `data` double NULL COMMENT "sensor data", 
+    `sensor_type` varchar(26) NOT NULL COMMENT "sensor type"
+) 
+ENGINE=OLAP 
+DUPLICATE KEY (id) 
+DISTRIBUTED BY HASH(`id`); 
+```
+
+**Routine Load job**
+
+You can use the simple mode for the Routine Load job. That is, you do not need to specify the parameter `jsonpaths` when creating the Routine Load job. Execute the following statement to submit a Routine Load job named `sensor_log_load_job1` to consume the Avro messages in the Kafka topic `topic_1` and load the data into the table `sensor_log1` in the database `sensor`.
+
+```sql
+CREATE ROUTINE LOAD sensor.sensor_log_load_job1 ON sensor_log1  
+PROPERTIES  
+(  
+  "format" = "avro"  
+)  
+FROM KAFKA  
+(  
+  "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>,...",
+  "confluent.schema.registry.url" = "http://172.xx.xxx.xxx:8081",  
+  "kafka_topic"= "topic_1",  
+  "kafka_partitions" = "0,1,2,3,4,5",  
+  "property.kafka_default_offsets" = "OFFSET_BEGINNING"  
+);
+```
+
+#### Avro schema contains a nested record-type field
+
+Suppose the Avro schema contains a nested record-type field, and you need to load the subfield in a nested record-type field into StarRocks.
+
+**Prepare a dataset**
+
+- **Avro schema**
+
+    1. Create the following Avro schema file `avro_schema2.avsc`. The outer Avro record includes five fields which are `id`, `name`, `checked`, `sensor_type`, and `data` in sequence. And the field `data` has a nested record `data_record`.
+
+        ```JSON
+        {
+            "type": "record",
+            "name": "sensor_log",
+            "fields" : [
+                {"name": "id", "type": "long"},
+                {"name": "name", "type": "string"},
+                {"name": "checked", "type" : "boolean"},
+                {"name": "sensor_type", "type": {"type": "enum", "name": "sensor_type_enum", "symbols" : ["TEMPERATURE", "HUMIDITY", "AIR-PRESSURE"]}},
+                {"name": "data", "type": 
+                    {
+                        "type": "record",
+                        "name": "data_record",
+                        "fields" : [
+                            {"name": "data_x", "type" : "boolean"},
+                            {"name": "data_y", "type": "long"}
+                        ]
+                    }
+                }
+            ]
+        }
+        ```
+
+    2. Register the Avro schema in the [Schema Registry](https://docs.confluent.io/platform/current/schema-registry/index.html).
+
+- **Avro data**
+
+Prepare the Avro data and send it to the Kafka topic `topic_2`.
+
+**Target database and table**
+
+According to the fields of Avro data, create a table `sensor_log2` in the target database `sensor` in the StarRocks cluster.
+
+Suppose that in addition to loading the fields `id`, `name`, `checked`, and `sensor_type` of the outer Record, you also need to load the subfield `data_y` in the nested Record `data_record`.
+
+```sql
+CREATE TABLE sensor.sensor_log2 ( 
+    `id` bigint NOT NULL COMMENT "sensor id",
+    `name` varchar(26) NOT NULL COMMENT "sensor name", 
+    `checked` boolean NOT NULL COMMENT "checked", 
+    `sensor_type` varchar(26) NOT NULL COMMENT "sensor type",
+    `data_y` long NULL COMMENT "sensor data" 
+) 
+ENGINE=OLAP 
+DUPLICATE KEY (id) 
+DISTRIBUTED BY HASH(`id`); 
+```
+
+**Routine Load job**
+
+Submit the load job, use `jsonpaths` to specify the fields of the Avro data that need to be loaded. Note that for the subfield `data_y` in the nested Record, you need to specify its `jsonpath` as `"$.data.data_y"`.
+
+```sql
+CREATE ROUTINE LOAD sensor.sensor_log_load_job2 ON sensor_log2  
+PROPERTIES  
+(  
+  "format" = "avro",
+  "jsonpaths" = "[\"$.id\",\"$.name\",\"$.checked\",\"$.sensor_type\",\"$.data.data_y\"]"
+)  
+FROM KAFKA  
+(  
+  "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>,...",
+  "confluent.schema.registry.url" = "http://172.xx.xxx.xxx:8081",  
+  "kafka_topic" = "topic_1",  
+  "kafka_partitions" = "0,1,2,3,4,5",  
+  "property.kafka_default_offsets" = "OFFSET_BEGINNING"  
+);
+```
+
+#### Avro schema contains a Union field
+
+**Prepare a dataset**
+
+Suppose the Avro schema contains a Union field, and you need to load the Union field into StarRocks.
+
+- **Avro schema**
+
+    1. Create the following Avro schema file `avro_schema3.avsc`. The outer Avro record includes five fields which are `id`, `name`, `checked`, `sensor_type`, and `data` in sequence. And the field `data` is of Union type and includes two elements, `null` and a nested record `data_record`.
+
+        ```JSON
+        {
+            "type": "record",
+            "name": "sensor_log",
+            "fields" : [
+                {"name": "id", "type": "long"},
+                {"name": "name", "type": "string"},
+                {"name": "checked", "type" : "boolean"},
+                {"name": "sensor_type", "type": {"type": "enum", "name": "sensor_type_enum", "symbols" : ["TEMPERATURE", "HUMIDITY", "AIR-PRESSURE"]}},
+                {"name": "data", "type": [null,
+                        {
+                            "type": "record",
+                            "name": "data_record",
+                            "fields" : [
+                                {"name": "data_x", "type" : "boolean"},
+                                {"name": "data_y", "type": "long"}
+                            ]
+                        }
+                    ]
+                }
+            ]
+        }
+        ```
+
+    2. Register the Avro schema in the [Schema Registry](https://docs.confluent.io/platform/current/schema-registry/index.html).
+
+- **Avro data**
+
+Prepare the Avro data and send it to the Kafka topic `topic_3`.
+
+**Target database and table**
+
+According to the fields of Avro data, create a table `sensor_log3` in the target database `sensor` in the StarRocks cluster.
+
+Suppose that in addition to loading the fields `id`, `name`, `checked`, and `sensor_type` of the outer Record, you also need to load the field `data_y` of the element `data_record` in the Union type field `data`.
+
+```sql
+CREATE TABLE sensor.sensor_log3 ( 
+    `id` bigint NOT NULL COMMENT "sensor id",
+    `name` varchar(26) NOT NULL COMMENT "sensor name", 
+    `checked` boolean NOT NULL COMMENT "checked", 
+    `sensor_type` varchar(26) NOT NULL COMMENT "sensor type",
+    `data_y` long NULL COMMENT "sensor data" 
+) 
+ENGINE=OLAP 
+DUPLICATE KEY (id) 
+DISTRIBUTED BY HASH(`id`); 
+```
+
+**Routine Load job**
+
+Submit the load job, use `jsonpaths` to specify the fields that need to be loaded in the Avro data. Note that for the field `data_y`, you need to specify its `jsonpath` as `"$.data.data_y"`.
+
+```sql
+CREATE ROUTINE LOAD sensor.sensor_log_load_job3 ON sensor_log3  
+PROPERTIES  
+(  
+  "format" = "avro",
+  "jsonpaths" = "[\"$.id\",\"$.name\",\"$.checked\",\"$.sensor_type\",\"$.data.data_y\"]"
+)  
+FROM KAFKA  
+(  
+  "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>,...",
+  "confluent.schema.registry.url" = "http://172.xx.xxx.xxx:8081",  
+  "kafka_topic" = "topic_1",  
+  "kafka_partitions" = "0,1,2,3,4,5",  
+  "property.kafka_default_offsets" = "OFFSET_BEGINNING"  
+);
+```
+
+When the value for the Union type field `data` is `null`, the value loaded into the column `data_y` in the StarRocks table is `null`. When the value for the Union type field `data` is a data record, the value loaded into the column `data_y` is of Long type.
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/PAUSE_ROUTINE_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/PAUSE_ROUTINE_LOAD.md
new file mode 100644
index 00000000000000..2221563dbbbdc4
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/PAUSE_ROUTINE_LOAD.md
@@ -0,0 +1,34 @@
+---
+displayed_sidebar: docs
+---
+
+# PAUSE ROUTINE LOAD
+
+import RoutineLoadPrivNote from '../../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
+
+## Description
+
+Pauses a Routine Load job but does not terminate this job. You can execute [RESUME ROUTINE LOAD](RESUME_ROUTINE_LOAD.md) to resume it. After the load job is paused, you can execute [SHOW ROUTINE LOAD](SHOW_ROUTINE_LOAD.md) and [ALTER ROUTINE LOAD](./ALTER_ROUTINE_LOAD.md) to view and modify information ../../data-manipulation/ALTER_ROUTINE_LOAD.mdob.
+
+<RoutineLoadPrivNote />
+
+## Syntax
+
+```SQL
+PAUSE ROUTINE LOAD FOR [db_name.]<job_name>;
+```
+
+## Parameters
+
+| Parameter | Required | Description                                                  |
+| --------- | -------- | ------------------------------------------------------------ |
+| db_name   |          | The name of the database to which the Routine Load job belongs. |
+| job_name  | ✅        | The name of the Routine Load job. A table may have multiple Routine Load jobs, it is recommended to set a meaningful Routine Load job name by using identifiable information, for example, Kafka topic name or time when you create the load job, to distinguish multiple routine load jobs.  The name of the Routine Load job must be unique within the same database |
+
+## Examples
+
+Pause the Routine Load job `example_tbl1_ordertest1` in the database `example_db`.
+
+```sql
+PAUSE ROUTINE LOAD FOR example_db.example_tbl1_ordertest1;
+```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md
new file mode 100644
index 00000000000000..507dcf963bb1a2
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md
@@ -0,0 +1,34 @@
+---
+displayed_sidebar: docs
+---
+
+# RESUME ROUTINE LOAD
+
+import RoutineLoadPrivNote from '../../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
+
+## Description
+
+Resumes a Routine load job. The job will temporarily enter **NEED_SCHEDULE** state because the job is being re-scheduled. And after some time, the job will be resumed to **RUNNING** state, continuing consuming messages from the data source and loading data. You can check the job's information using the [SHOW ROUTINE LOAD](SHOW_ROUTINE_LOAD.md) statement.
+
+<RoutineLoadPrivNote />
+
+## Syntax
+
+```SQL
+RESUME ROUTINE LOAD FOR [db_name.]<job_name>
+```
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                              |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| db_name       |              | The name of the database to which the Routine Load job belongs. |
+| job_name      | ✅            | The name of the Routine Load job.                            |
+
+## Examples
+
+Resume the Routine Load job `example_tbl1_ordertest1` in the database `example_db`.
+
+```SQL
+RESUME ROUTINE LOAD FOR example_db.example_tbl1_ordertest1;
+```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md
new file mode 100644
index 00000000000000..776f3a4308c816
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md
@@ -0,0 +1,126 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW ROUTINE LOAD
+
+import RoutineLoadPrivNote from '../../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
+
+## Description
+
+Shows the execution information of Routine Load jobs.
+
+<RoutineLoadPrivNote />
+
+## Syntax
+
+```SQL
+SHOW [ALL] ROUTINE LOAD [ FOR [<db_name>.]<job_name> | FROM <db_name> ]
+[ WHERE [ STATE = { "NEED_SCHEDULE" | "RUNNING" | "PAUSED" | "UNSTABLE" | "STOPPED" | "CANCELLED"  } ] ]
+[ ORDER BY field_name [ ASC | DESC ] ]
+[ LIMIT { [offset, ] limit | limit OFFSET offset } ]
+```
+
+:::tip
+
+You can add the `\G` option to the statement (such as `SHOW ROUTINE LOAD FOR <job_name>\G`) to vertically display the return result rather than in the usual horizontal table format.
+
+:::
+
+## Parameters
+
+| **Parameter**                     | **Required** | **Description**                                              |
+| --------------------------------- | ------------ | ------------------------------------------------------------ |
+| db_name                           | No           | The name of the database to which the load job belongs. Note that this parameter is required if the `FROM` clause is used. |
+| job_name                          | No           | The name of the load job. Note that this parameter is required if the `FOR` clause is used.         |
+| ALL                               | No           | Displays all load jobs, including those in the `STOPPED` or  `CANCELLED` states. |
+| STATE                             | No           |  The status of the load job.                                       |
+| ORDER BY field_name [ASC \| DESC] | No           | Sorts the return result in ascending or descending order based on the specified field. The following fields are supported: `Id`, `Name`, `CreateTime`, `PauseTime`, `EndTime`, `TableName`, `State`, and `CurrentTaskNum`.<ul><li>To sort the return result in ascending order, specify `ORDER BY field_name ASC`.</li><li>To sort the return result in descending order, specify `ORDER BY field_name DESC`.</li></ul>If you do not specify the field or the sort order, the return result is sorted in ascending order of `Id` by default. |
+| LIMIT limit                       | No           | The number of load jobs that will be returned. For example, if `LIMIT 10` is specified, only the information of 10 load jobs that match filter conditions will be returned. If this parameter is not specified, the information of all load jobs that match the filter conditions are displayed.  |
+| OFFSET offset                     | No           | The `offset` parameter defines the number of load jobs to be skipped. For example, `OFFSET 5` skips the first five load jobs and returns the rest. The value of the `offset` parameter defaults to `0`. |
+
+## Output
+
+| **Parameter**        | **Description**                                              |
+| -------------------- | ------------------------------------------------------------ |
+| Id                   | The globally unique ID of the load job, generated automatically by StarRocks. |
+| Name                 | The name of the load job.                                        |
+| CreateTime           | The date and time when the load job was created.             |
+| PauseTime            | The date and time when the load job entered `PAUSED` state.  |
+| EndTime              | The date and time when the load job entered `STOPPED` state. |
+| DbName               | The database to which the target table of the load job belongs.  |
+| TableName            | The target table of the load job.                                |
+| State                | The status of the load job, including:<ul><li>`NEED_SCHEDULE`: The load job is waiting to be scheduled. After you use CREATE ROUTINE LOAD or RESUME ROUTINE LOAD to create or resume a Routine Load job, the load job first enters the `NEED_SCHEDULE` state.</li><li>`RUNNING`: The load job is running. You can view the consumption progress of the Routine Load job through `Statistic` and `Progress`.</li><li>`PAUSED`: The load job is paused. You can refer to `ReasonOfStateChanged` and `ErrorLogUrls` for troubleshooting. After fixing the error, you can use RESUME ROUTINE LOAD to resume the Routine Load job.</li><li>`CANCELLED`: The load job is cancelled. You can refer to `ReasonOfStateChanged` and `ErrorLogUrls` for troubleshooting. However, after fixing the error, you cannot recover the load job in this state.</li><li>`STOPPED`: The load job is stopped. You cannot recover the load job in this state.</li><li>`UNSTABLE`: The load job is unstable. A Routine Load job is set in the `UNSTABLE` state if any task within the Routine Load job lags (namely, the difference between the timestamp of the message being consumed and the current time exceeds this FE parameter [`routine_load_unstable_threshold_second`](../../../../administration/management/FE_configuration.md#routine_load_unstable_threshold_second), and unconsumed messages exist in the data source.)</li></ul> |
+| DataSourceType       | The type of the data source. Fixed value: `KAFKA`.           |
+| CurrentTaskNum       | The current number of tasks in the load job.                     |
+| JobProperties        | The properties of the load job, such as partitions to be consumed and column mapping. |
+| DataSourceProperties | The properties of the data source, such as Topic and the list of addresses and ports of brokers in the Kafka cluster. |
+| CustomProperties     | The additional data source-related properties defined in the load job. |
+| Statistic            | The statistic of loading data, such as successfully loaded rows, total rows, and received data volume. |
+| Progress             | The progress (measured in the offset) of consuming messages in partitions of the topic. |
+| TimestampProgress    | The progress (measured in the timestamp) of consuming messages in partitions of the topic. |
+| ReasonOfStateChanged | The reasons for the load job being in CANCELLED or PAUSED state. |
+| ErrorLogUrls         | The URL of error logs. You can use the `curl` or `wget` command to  access the URL. |
+| TrackingSQL          | The SQL command that you can directly run to query the error log information recorded in the `information_schema` database. |
+| OtherMsg             | The information about all failed load tasks of the Routine Load job. |
+| LatestSourcePosition | The position of latest message in each partition of the topic, which helps check the latencies of data loading. |
+
+## Examples
+
+If a load job is successfully started and stays in the RUNNING state, the returned result might be as follows:
+
+```SQL
+MySQL [example_db]> SHOW ROUTINE LOAD FOR example_tbl_ordertest1\G
+*************************** 1. row ***************************
+                  Id: 10204
+                Name: example_tbl_ordertest1
+          CreateTime: 2023-12-21 21:01:31
+           PauseTime: NULL
+             EndTime: NULL
+              DbName: example_db
+           TableName: example_tbl
+               State: RUNNING
+      DataSourceType: KAFKA
+      CurrentTaskNum: 1
+       JobProperties: {"partitions":"*","rowDelimiter":"\t","partial_update":"false","columnToColumnExpr":"order_id,pay_dt,customer_name,nationality,temp_gender,price","maxBatchIntervalS":"10","partial_update_mode":"null","whereExpr":"*","timezone":"Asia/Shanghai","format":"csv","columnSeparator":"','","log_rejected_record_num":"0","taskTimeoutSecond":"60","json_root":"","maxFilterRatio":"1.0","strict_mode":"false","jsonpaths":"","taskConsumeSecond":"15","desireTaskConcurrentNum":"5","maxErrorNum":"0","strip_outer_array":"false","currentTaskConcurrentNum":"1","maxBatchRows":"200000"}
+DataSourceProperties: {"topic":"lilyliuyitest4csv","currentKafkaPartitions":"0","brokerList":"xxx.xx.xx.xxx:9092"}
+    CustomProperties: {"kafka_default_offsets":"OFFSET_BEGINNING","group.id":"example_tbl_ordertest1_b05da08f-9b9d-4fe1-b1f2-25d7116d617c"}
+           Statistic: {"receivedBytes":313,"errorRows":0,"committedTaskNum":1,"loadedRows":6,"loadRowsRate":0,"abortedTaskNum":0,"totalRows":6,"unselectedRows":0,"receivedBytesRate":0,"taskExecuteTimeMs":699}
+            Progress: {"0":"5"}
+   TimestampProgress: {"0":"1686143856061"}
+ReasonOfStateChanged: 
+        ErrorLogUrls: 
+         TrackingSQL: 
+            OtherMsg: 
+LatestSourcePosition: {"0":"6"}
+1 row in set (0.01 sec)
+```
+
+If a load job is in the `PAUSED` or `CANCELLED` state due to exceptions, you can troubleshoot based on the `ReasonOfStateChanged`, `ErrorLogUrls`, `TrackingSQL`, and `OtherMsg` fields in the return result.
+
+```SQL
+MySQL [example_db]> SHOW ROUTINE LOAD FOR example_tbl_ordertest2\G
+*************************** 1. row ***************************
+                  Id: 10204
+                Name: example_tbl_ordertest2
+          CreateTime: 2023-12-22 12:13:18
+           PauseTime: 2023-12-22 12:13:38
+             EndTime: NULL
+              DbName: example_db
+           TableName: example_tbl
+               State: PAUSED
+      DataSourceType: KAFKA
+      CurrentTaskNum: 0
+       JobProperties: {"partitions":"*","rowDelimiter":"\t","partial_update":"false","columnToColumnExpr":"order_id,pay_dt,customer_name,nationality,temp_gender,price","maxBatchIntervalS":"10","partial_update_mode":"null","whereExpr":"*","timezone":"Asia/Shanghai","format":"csv","columnSeparator":"','","log_rejected_record_num":"0","taskTimeoutSecond":"60","json_root":"","maxFilterRatio":"1.0","strict_mode":"false","jsonpaths":"","taskConsumeSecond":"15","desireTaskConcurrentNum":"5","maxErrorNum":"0","strip_outer_array":"false","currentTaskConcurrentNum":"1","maxBatchRows":"200000"}
+DataSourceProperties: {"topic":"mytest","currentKafkaPartitions":"0","brokerList":"xxx.xx.xx.xxx:9092"}
+    CustomProperties: {"kafka_default_offsets":"OFFSET_BEGINNING","group.id":"example_tbl_ordertest2_b3fada0f-6721-4ad1-920d-e4bf6d6ea7f7"}
+           Statistic: {"receivedBytes":541,"errorRows":10,"committedTaskNum":1,"loadedRows":6,"loadRowsRate":0,"abortedTaskNum":0,"totalRows":16,"unselectedRows":0,"receivedBytesRate":0,"taskExecuteTimeMs":646}
+            Progress: {"0":"19"}
+   TimestampProgress: {"0":"1702623900871"}
+ReasonOfStateChanged: ErrorReason{errCode = 102, msg='current error rows is more than max error num'}
+        ErrorLogUrls: http://xxx.xx.xx.xxx:8040/api/_load_error_log?file=error_log_b25dcc7e642344b2_b0b342b9de0567db
+         TrackingSQL: select tracking_log from information_schema.load_tracking_logs where job_id=10204
+            OtherMsg: 
+LatestSourcePosition: {"0":"20"}
+1 row in set (0.00 sec)
+```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD_TASK.md b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD_TASK.md
new file mode 100644
index 00000000000000..c462a644ab264e
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD_TASK.md
@@ -0,0 +1,70 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW ROUTINE LOAD TASK
+
+import RoutineLoadPrivNote from '../../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
+
+## Description
+
+Shows the execution information of load tasks within a Routine Load job.
+
+:::note
+
+- <RoutineLoadPrivNote />
+
+- For the relationship between a Routine Load job and the load tasks in it, see [Load data using Routine Load](../../../../loading/RoutineLoad.md#basic-concepts)
+
+:::
+
+## Syntax
+
+```SQL
+SHOW ROUTINE LOAD TASK
+[  FROM <db_name>]
+[  WHERE JobName = <job_name> ]
+```
+
+:::note
+
+You can add the `\G` option to the statement (such as `SHOW ROUTINE LOAD TASK WHERE JobName = <job_name>\G`) to vertically display the return result rather than in the usual horizontal table format.
+
+:::
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                             |
+| ------------- | ------------ | ----------------------------------------------------------- |
+| db_name       | No           | The name of the database to which the Routine Load job belongs. |
+| JobName       | No           | The name of the Routine Load job.                               |
+
+## Output
+
+| **Parameter**        | **Description**                                              |
+| -------------------- | ------------------------------------------------------------ |
+| TaskId               | The globally unique ID of the load task, automatically generated by StarRocks. |
+| TxnId                | The ID of the transaction to which the load task belongs.        |
+| TxnStatus            | The status of the transaction to which the load task belongs. `UNKNOWN` indicates that the transaction is not started yet, possibly because the load task is not dispatched or executed. |
+| JobId                | The ID of the load job.                                          |
+| CreateTime           | The date and time when the load task was created.            |
+| LastScheduledTime    | The date and time when the load task was last scheduled.     |
+| ExecuteStartTime     | The date and time when the load task was executed.           |
+| Timeout              | The timeout period for the load task, controlled by the FE parameter [`routine_load_task_timeout_second`](../../../../administration/management/FE_configuration.md#routine_load_task_timeout_second) and the `task_timeout_second` parameter in [job_properties](./CREATE_ROUTINE_LO../../data-manipulation/CREATE_ROUTINE_LOAD.mdr the Routine Load job. |
+| BeId                 | The ID of the BE that executes the load task.                    |
+| DataSourceProperties | The load task's progress (measured in the offset) of consuming messages in partitions of the topic. |
+| Message              | The information returned for the load task, including task error information. |
+
+## Examples
+
+View all load tasks in the Routine Load job `example_tbl_ordertest`.
+
+```SQL
+MySQL [example_db]> SHOW ROUTINE LOAD TASK WHERE JobName = "example_tbl_ordertest";  
++--------------------------------------+-------+-----------+-------+---------------------+---------------------+------------------+---------+------+------------------------------------+-----------------------------------------------------------------------------+
+| TaskId                               | TxnId | TxnStatus | JobId | CreateTime          | LastScheduledTime   | ExecuteStartTime | Timeout | BeId | DataSourceProperties               | Message                                                                     |
++--------------------------------------+-------+-----------+-------+---------------------+---------------------+------------------+---------+------+------------------------------------+-----------------------------------------------------------------------------+
+| abde6998-c19a-43d6-b48c-6ca7e14144a3 | -1    | UNKNOWN   | 10208 | 2023-12-22 12:46:10 | 2023-12-22 12:47:00 | NULL             | 60      | -1   | Progress:{"0":6},LatestOffset:null | there is no new data in kafka/pulsar, wait for 10 seconds to schedule again |
++--------------------------------------+-------+-----------+-------+---------------------+---------------------+------------------+---------+------+------------------------------------+-----------------------------------------------------------------------------+
+1 row in set (0.00 sec)
+```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/STOP_ROUTINE_LOAD.md b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/STOP_ROUTINE_LOAD.md
new file mode 100644
index 00000000000000..1899701eea4877
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/routine_load/STOP_ROUTINE_LOAD.md
@@ -0,0 +1,41 @@
+---
+displayed_sidebar: docs
+---
+
+# STOP ROUTINE LOAD
+
+import RoutineLoadPrivNote from '../../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
+
+## Description
+
+Stops a Routine Load job.
+
+<RoutineLoadPrivNote />
+
+::: warning
+
+- A stopped Routine Load job cannot be resumed. Therefore, please proceed with caution when executing this statement.
+- If you only need to pause the Routine Load job, you can execute [PAUSE ROUTINE LOAD](PAUSE_ROUTINE_LOAD.md).
+
+:::
+
+## Syntax
+
+```SQL
+STOP ROUTINE LOAD FOR [db_name.]<job_name>
+```
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                              |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| db_name       |              | The name of the database to which the Routine Load job belongs. |
+| job_name      | ✅            | The name of the Routine Load job.                            |
+
+## Examples
+
+Stop the Routine Load job `example_tbl1_ordertest1` in the database `example_db`.
+
+```SQL
+STOP ROUTINE LOAD FOR example_db.example_tbl1_ordertest1;
+```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/unloading/CANCEL_EXPORT.md b/docs/en/sql-reference/sql-statements/loading_unloading/unloading/CANCEL_EXPORT.md
new file mode 100644
index 00000000000000..6040f0974491f9
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/unloading/CANCEL_EXPORT.md
@@ -0,0 +1,43 @@
+---
+displayed_sidebar: docs
+---
+
+# CANCEL EXPORT
+
+## Description
+
+Cancels a given data unloading job. Unloading jobs with the state `CANCELLED` or `FINISHED` cannot be canceled. Canceling an unloading job is an asynchronous process. You can use the [SHOW EXPORT](SHOW_EXPORT.md) statement to check whether an unloading job is successfully canceled. The unloading job is successfully canceled if the value of `State` is `CANCELLED`.
+
+The CANCEL EXPORT statement requires that you have at least one of the following privileges on the database to which the given unloading job belongs: `SELECT_PRIV`, `LOAD_PRIV`, `ALTER_PRIV`, `CREATE_PRIV`, `DROP_PRIV`, and `USAGE_PRIV`. For more information about privilege descriptions, see [GRANT](../../account-management/GRANT.md).
+
+## Syntax
+
+```SQL
+CANCEL EXPORT
+[FROM db_name]
+WHERE QUERYID = "query_id"
+```
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                              |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| db_name       | No           | The name of the databases to which the unloading job belongs. If this parameter is not specified, an unloading job in your current database is canceled. |
+| query_id      | Yes          | The query ID of the unloading job. You can obtain the ID by using the [LAST_QUERY_ID()](../../../sql-functions/utility-functions/last_query_id.md) function. Note that this function only returns the latest query ID. |
+
+## Examples
+
+Example 1: Cancel an unloading job whose query ID is `921d8f80-7c9d-11eb-9342-acde48001121` in the current database.
+
+```SQL
+CANCEL EXPORT
+WHERE queryid = "921d8f80-7c9d-11eb-9342-acde48001121";
+```
+
+Example 2: Cancel an unloading job whose query ID is `921d8f80-7c9d-11eb-9342-acde48001121` in the `example_db` database.
+
+```SQL
+CANCEL EXPORT 
+FROM example_db 
+WHERE queryid = "921d8f80-7c9d-11eb-9342-acde48001122";
+```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/unloading/EXPORT.md b/docs/en/sql-reference/sql-statements/loading_unloading/unloading/EXPORT.md
new file mode 100644
index 00000000000000..10c4774556e523
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/unloading/EXPORT.md
@@ -0,0 +1,157 @@
+---
+displayed_sidebar: docs
+---
+
+# EXPORT
+
+## Description
+
+Exports the data of a table to a specified location.
+
+This is an asynchronous operation. The export result is returned after you submit the export task. You can use [SHOW EXPORT](SHOW_EXPORT.md) to view the progress of the export task.
+
+> **NOTICE**
+>
+> You can export data out of StarRocks tables only as a user who has the EXPORT privilege on those StarRocks tables. If you do not have the EXPORT privilege, follow the instructions provided in [GRANT](../../account-management/GRANT.md) to grant the EXPORT privilege to the user that you use to connect to your StarRocks cluster.
+
+## Syntax
+
+```SQL
+EXPORT TABLE <table_name>
+[PARTITION (<partition_name>[, ...])]
+[(<column_name>[, ...])]
+TO <export_path>
+[opt_properties]
+WITH BROKER
+[broker_properties]
+```
+
+## Parameters
+
+- `table_name`
+
+  The name of the table. StarRocks supports exporting the data of tables whose `engine` is `olap` or `mysql`.
+
+- `partition_name`
+
+  The partitions from which you want to export data. By default, if you do not specify this parameter, StarRocks exports the data from all partitions of the table.
+
+- `column_name`
+
+  The columns from which you want to export data. The sequence of columns that you specify by using this parameter can differ from the schema of the table. By default, if you do not specify this parameter, StarRocks exports the data from all columns of the table.
+
+- `export_path`
+
+  The location to which you want to export the data of the table. If the location contains a path, make sure that the path ends with a slash (/). Otherwise, the part following the last slash (/) in the path will be used as the prefix to the name of the exported file. By default, `data_` is used as the file name prefix if no file name prefix is specified.
+
+- `opt_properties`
+
+  Optional properties that you can configure for the export task.
+
+  Syntax:
+
+  ```SQL
+  [PROPERTIES ("<key>"="<value>", ...)]
+  ```
+
+  | **Property**     | **Description**                                              |
+  | ---------------- | ------------------------------------------------------------ |
+  | column_separator | The column separator that you want to use in the exported file. Default value: `\t`. |
+  | line_delimiter   | The row separator that you want to use in the exported file. Default value: `\n`. |
+  | load_mem_limit   | The maximum memory that is allowed for the export task on each individual BE. Unit: bytes. The default maximum memory is 2 GB. |
+  | timeout          | The amount of time after which the export task times out. Unit: second. Default value: `86400`, meaning 1 day. |
+  | include_query_id | Specifies whether the name of the exported file contains `query_id`. Valid values: `true` and `false`. The value `true` specifies that the file name contains `query_id`, and the value `false` specifies that the file name does not contain `query_id`. |
+
+- `WITH BROKER`
+
+  In v2.4 and earlier, input `WITH BROKER "<broker_name>"` to specify the broker you want to use. From v2.5 onwards, you no longer need to specify a broker, but you still need to retain the `WITH BROKER` keyword. For more information, see [Export data using EXPORT > Background information](../../../../unloading/Export.md#background-information).
+
+- `broker_properties`
+
+  The information that is used to authenticate the source data. The authentication information varies depending on the data source. For more information, see [BROKER LOAD](../BROKER_LOAD.md).
+
+## Examples
+
+### Export all data of a table to HDFS
+
+The following example exports all data of the `testTbl` table to the `hdfs://<hdfs_host>:<hdfs_port>/a/b/c/` path of an HDFS cluster:
+
+```SQL
+EXPORT TABLE testTbl 
+TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
+WITH BROKER
+(
+        "username"="xxx",
+        "password"="yyy"
+);
+```
+
+### Export the data of specified partitions of a table to HDFS
+
+The following example exports the data of two partitions, `p1` and `p2`, of the `testTbl` table to the `hdfs://<hdfs_host>:<hdfs_port>/a/b/c/` path of an HDFS cluster:
+
+```SQL
+EXPORT TABLE testTbl
+PARTITION (p1,p2) 
+TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
+WITH BROKER
+(
+        "username"="xxx",
+        "password"="yyy"
+);
+```
+
+### Export all data of a table to HDFS with column separator specified
+
+The following example exports all data of the `testTbl` table to the `hdfs://<hdfs_host>:<hdfs_port>/a/b/c/` path of an HDFS cluster and specifies that commas (`,`) is used as the column separator:
+
+```SQL
+EXPORT TABLE testTbl 
+TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
+PROPERTIES
+(
+    "column_separator"=","
+) 
+WITH BROKER
+(
+    "username"="xxx",
+    "password"="yyy"
+);
+```
+
+The following example exports all data of the `testTbl` table to the `hdfs://<hdfs_host>:<hdfs_port>/a/b/c/` path of an HDFS cluster and specifies that `\x01` (the default column separator supported by Hive) is used as the column separator:
+
+```SQL
+EXPORT TABLE testTbl 
+TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
+PROPERTIES
+(
+    "column_separator"="\\x01"
+) 
+WITH BROKER;
+```
+
+### Export all data of a table to HDFS with file name prefix specified
+
+The following example exports all data of the `testTbl` table to the `hdfs://<hdfs_host>:<hdfs_port>/a/b/c/` path of an HDFS cluster and specifies that `testTbl_` is used as the prefix to the name of the exported file:
+
+```SQL
+EXPORT TABLE testTbl 
+TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/testTbl_" 
+WITH BROKER;
+```
+
+### Export data to AWS S3
+
+The following example exports all data of the `testTbl` table to the `s3-package/export/` path of an AWS S3 bucket:
+
+```SQL
+EXPORT TABLE testTbl 
+TO "s3a://s3-package/export/"
+WITH BROKER
+(
+    "aws.s3.access_key" = "xxx",
+    "aws.s3.secret_key" = "yyy",
+    "aws.s3.region" = "zzz"
+);
+```
diff --git a/docs/en/sql-reference/sql-statements/loading_unloading/unloading/SHOW_EXPORT.md b/docs/en/sql-reference/sql-statements/loading_unloading/unloading/SHOW_EXPORT.md
new file mode 100644
index 00000000000000..6dccbe804bbb36
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/loading_unloading/unloading/SHOW_EXPORT.md
@@ -0,0 +1,138 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW EXPORT
+
+## Description
+
+Queries the execution information of export jobs that meet the specified conditions.
+
+## Syntax
+
+```SQL
+SHOW EXPORT
+[ FROM <db_name> ]
+[
+WHERE
+    [ QUERYID = <query_id> ]
+    [ STATE = { "PENDING" | "EXPORTING" | "FINISHED" | "CANCELLED" } ]
+]
+[ ORDER BY <field_name> [ ASC | DESC ] [, ... ] ]
+[ LIMIT <count> ]
+```
+
+## Parameters
+
+This statement can contain the following optional clauses:
+
+- FROM
+
+  Specifies the name of the database that you want to query. If you do not specify a FROM clause, StarRocks queries the current database.
+
+- WHERE
+
+  Specifies the conditions based on which you want to filter export jobs. Only the export jobs that meet the specified conditions are returned in the result set of the query.
+
+  | **Parameter** | **Required** | **Description**                                              |
+  | ------------- | ------------ | ------------------------------------------------------------ |
+  | QUERYID       | No           | The ID of the export job that you want to query. This parameter is used to query the execution information of a single export job. |
+  | STATE         | No           | The status of the export jobs that you want to query. Valid values:<ul><li>`PENDING`: specifies to query export jobs that are waiting to be scheduled.</li><li>`EXPORTING`: specifies to query export jobs that are being executed.</li><li>`FINISHED`: specifies to query export jobs that have been successfully completed.</li><li>`CANCELLED`: specifies to query export jobs that have failed.</li></ul> |
+
+- ORDER BY
+
+  Specifies the name of the field based on which you want to sort the export job records in the result set of the query. You can specify multiple fields, which must be separated with commas (`,`). Additionally, you can use the `ASC` or `DESC` keyword to specify that the export job records are sorted in ascending or descending order based on the specified field.
+
+- LIMIT
+
+  Restricts the result set of the query to a specified maximum number of rows. Valid values: positive integer. If you do not specify a LIMIT clause, StarRocks returns all export jobs that meet the specified conditions.
+
+## Return result
+
+For example, query the execution information of an export job whose ID is `edee47f0-abe1-11ec-b9d1-00163e1e238f`:
+
+```SQL
+SHOW EXPORT
+WHERE QUERYID = "edee47f0-abe1-11ec-b9d1-00163e1e238f";
+```
+
+The following execution information is returned:
+
+```SQL
+     JobId: 14008
+   QueryId: edee47f0-abe1-11ec-b9d1-00163e1e238f
+     State: FINISHED
+  Progress: 100%
+  TaskInfo: {"partitions":["*"],"column separator":"\t","columns":["*"],"tablet num":10,"broker":"","coord num":1,"db":"db0","tbl":"tbl_simple","row delimiter":"\n","mem limit":2147483648}
+      Path: hdfs://127.0.0.1:9000/users/230320/
+CreateTime: 2023-03-20 11:16:14
+ StartTime: 2023-03-20 11:16:17
+FinishTime: 2023-03-20 11:16:26
+   Timeout: 7200
+```
+
+The parameters in the return result are described as follows:
+
+- `JobId`: the ID of the export job.
+- `QueryId`: the ID of the query.
+- `State`: the status of the export job.
+
+  Valid values:
+
+  - `PENDING`: The export job is waiting to be scheduled.
+  - `EXPORTING`: The export job is being executed.
+  - `FINISHED`: The export job has been successfully completed.
+  - `CANCELLED`: The export job has failed.
+
+- `Progress`: the progress of the export job. The progress is measured in the unit of query plans. Suppose that the export job is divided into 10 query plans and three of them have finished. In this case, the progress of the export job is 30%. For more information, see ["Export data using EXPORT > Workflow"](../../../../unloading/Export.md#workflow).
+- `TaskInfo`: the information of the export job.
+
+  The information is a JSON object that consists of the following keys:
+
+  - `partitions`: the partitions on which the exported data resides. If a wildcard (`*`) is returned as a value for this key, the export job is run to export data from all partitions.
+  - `column separator`: the column separator used in the exported data file.
+  - `columns`: the names of the columns whose data is exported.
+  - `tablet num`: the total number of tablets that are exported.
+  - `broker`: In v2.4 and earlier, this field is used to return the name of the broker that is used by the export job. From v2.5 onwards, this field returns an empty string. For more information, see ["Export data using EXPORT > Background information"](../../../../unloading/Export.md#background-information).
+  - `coord num`: the number of query plans into which the export job is divided.
+  - `db`: the name of the database to which the exported data belongs.
+  - `tbl`: the name of the table to which the exported data belongs
+  - `row delimiter`: the row separator used in the exported data file.
+  - `mem limit`: the maximum amount of memory allowed for the export job. Unit: bytes.
+
+- `Path`: the path to which the exported data is stored on the remote storage.
+- `CreateTime`: the time when the export job was created.
+- `StartTime`: the time when the export job started to be scheduled.
+- `FinishTime`: the time when the export job was finished.
+- `Timeout`: the amount of time that the export job took than expected. Unit: seconds. The time is counted from `CreateTime`.
+- `ErrorMsg`: the reason why the export job throws an error. This field is returned only when the export job encounters an error.
+
+## Examples
+
+- Query all export jobs in the current database:
+
+  ```SQL
+  SHOW EXPORT;
+  ```
+
+- Query the export job whose ID is `921d8f80-7c9d-11eb-9342-acde48001122` in the database `example_db`:
+
+  ```SQL
+  SHOW EXPORT FROM example_db
+  WHERE queryid = "921d8f80-7c9d-11eb-9342-acde48001122";
+  ```
+
+- Query export jobs that are in the `EXPORTING` state in the database `example_db` and specify to sort the export job records in the result set by `StartTime` in ascending order:
+
+  ```SQL
+  SHOW EXPORT FROM example_db
+  WHERE STATE = "exporting"
+  ORDER BY StartTime ASC;
+  ```
+
+- Query all export jobs in the database `example_db` and specify to sort the export job records in the result set by `StartTime` in descending order:
+
+  ```SQL
+  SHOW EXPORT FROM example_db
+  ORDER BY StartTime DESC;
+  ```
diff --git a/docs/en/sql-reference/sql-statements/materialized_view/ALTER_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/materialized_view/ALTER_MATERIALIZED_VIEW.md
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+---
+displayed_sidebar: docs
+---
+
+# ALTER MATERIALIZED VIEW
+
+## Description
+
+This SQL statement can:
+
+- Alter the name of an asynchronous materialized view.
+- Alter the refresh strategy of an asynchronous materialized view.
+- Alter the status of an asynchronous materialized view to active or inactive.
+- Perform an atomic swap between two asynchronous materialized views.
+- Alter the properties of an asynchronous materialized view.
+
+  You can use this SQL statement to alter the following properties:
+
+  - `partition_ttl_number`
+  - `partition_refresh_number`
+  - `resource_group`
+  - `auto_refresh_partitions_limit`
+  - `excluded_trigger_tables`
+  - `mv_rewrite_staleness_second`
+  - `unique_constraints`
+  - `foreign_key_constraints`
+  - `colocate_with`
+  - All session variable-related properties. For information on session variables, see [System variables](../../System_variable.md).
+
+:::tip
+
+- This operation requires the ALTER privilege on the target materialized view. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
+- ALTER MATERIALIZED VIEW does not support directly modifying the query statement used to build the materialized view. You can build a new materialized view and swap it with the original one using ALTER MATERIALIZED VIEW SWAP WITH.
+
+:::
+
+## Syntax
+
+```SQL
+ALTER MATERIALIZED VIEW [db_name.]<mv_name> 
+    { RENAME [db_name.]<new_mv_name> 
+    | REFRESH <new_refresh_scheme_desc> 
+    | ACTIVE | INACTIVE 
+    | SWAP WITH [db_name.]<mv2_name>
+    | SET ( "<key>" = "<value>"[,...]) }
+```
+
+## Parameters
+
+| **Parameter**           | **Required** | **Description**                                              |
+| ----------------------- | ------------ | ------------------------------------------------------------ |
+| mv_name                 | yes          | The name of the materialized view to alter.                  |
+| new_refresh_scheme_desc | no           | New refresh strategy, see [SQL Reference - CREATE MATERIALIZED VIEW - Parameters](CREATE_MATERIALIZED_VIEW.md#parameters) for details. |
+| new_mv_name             | no           | New name for the materialized view.                          |
+| ACTIVE                  | no           |Set the status of the materialized view to active. StarRocks automatically sets a materialized view to inactive if any of its base tables is changed, for example, dropped and re-created, to prevent the situation that original metadata mismatches the changed base table. Inactive materialized views cannot be used for query acceleration or query rewrite. You can use this SQL to activate the materialized view after changing the base tables. |
+| INACTIVE                | no           | Set the status of the materialized view to inactive. An inactive asynchronous materialized view cannot be refreshed. But you can still query it as a table. |
+| SWAP WITH               | no           | Perform an atomic exchange with another asynchronous materialized view after necessary consistency checks. |
+| key                     | no           | The name of the property to alter, see [SQL Reference - CREATE MATERIALIZED VIEW - Parameters](CREATE_MATERIALIZED_VIEW.md#parameters) for details.<br />**NOTE**<br />If you want to alter a session variable-related property of the materialized view, you must add a `session.` prefix to the property, for example, `session.query_timeout`. You do not need to specify the prefix for non-session properties, for example, `mv_rewrite_staleness_second`. |
+| value                   | no           | The value of the property to alter.                         |
+
+## Example
+
+Example 1: Alter the name of the materialized view.
+
+```SQL
+ALTER MATERIALIZED VIEW lo_mv1 RENAME lo_mv1_new_name;
+```
+
+Example 2: Alter the refresh interval of the materialized view.
+
+```SQL
+ALTER MATERIALIZED VIEW lo_mv2 REFRESH ASYNC EVERY(INTERVAL 1 DAY);
+```
+
+Example 3: Alter the timeout duration for the materialized view refresh tasks to 1 hour (default).
+
+```SQL
+ALTER MATERIALIZED VIEW mv1 SET ("session.query_timeout" = "3600");
+```
+
+Example 4: Alter the materialized view's status to active.
+
+```SQL
+ALTER MATERIALIZED VIEW order_mv ACTIVE;
+```
+
+Example 5: Perform an atomic exchange between materialized views `order_mv` and `order_mv1`.
+
+```SQL
+ALTER MATERIALIZED VIEW order_mv SWAP WITH order_mv1;
+```
+
+Example 6: Enable profile for the materialized view refresh process. This feature is enabled by default.
+
+```SQL
+ALTER MATERIALIZED VIEW mv1 SET ("session.enable_profile" = "true");
+```
+
+Example 7: Enable intermediate result spilling for the materialized view refresh process, and set the mode of spilling to `force`. Intermediate result spilling is enabled by default since v3.1.
+
+```SQL
+-- Enable spilling during materialized view refresh.
+ALTER MATERIALIZED VIEW mv1 SET ("session.enable_spill" = "true");
+-- Set spill_mode to force (the default value is auto).
+ALTER MATERIALIZED VIEW mv1 SET ("session.spill_mode" = "force");
+```
+
+Example 8: Alter the optimizer timeout duration for materialized view to 30 seconds (default since v3.3) if its query statement contains external tables or multiple joins.
+
+```SQL
+ALTER MATERIALIZED VIEW mv1 SET ("session.new_planner_optimize_timeout" = "30000");
+```
+
+Example 9: Alter the query rewrite staleness time for the materialized view to 600 seconds.
+
+```SQL
+ALTER MATERIALIZED VIEW mv1 SET ("mv_rewrite_staleness_second" = "600");
+```
diff --git a/docs/en/sql-reference/sql-statements/materialized_view/CANCEL_REFRESH_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/materialized_view/CANCEL_REFRESH_MATERIALIZED_VIEW.md
new file mode 100644
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+++ b/docs/en/sql-reference/sql-statements/materialized_view/CANCEL_REFRESH_MATERIALIZED_VIEW.md
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+---
+displayed_sidebar: docs
+---
+
+# CANCEL REFRESH MATERIALIZED VIEW
+
+## Description
+
+Cancels a refresh task for an asynchronous materialized view.
+
+:::tip
+
+This operation requires the REFRESH privilege on the target materialized view.
+
+:::
+
+## Syntax
+
+```SQL
+CANCEL REFRESH MATERIALIZED VIEW [<database_name>.]<materialized_view_name> [FORCE]
+```
+
+## Parameters
+
+| **Parameter**          | **Required** | **Description**                                              |
+| ---------------------- | ------------ | ------------------------------------------------------------ |
+| database_name          | No           | Name of the database where the materialized view resides. If this parameter is not specified, the current database is used. |
+| materialized_view_name | Yes          | Name of the materialized view.                               |
+| FORCE                  | NO           | Forces to cancel the running materialized view refresh task. |
+
+## Examples
+
+Example 1: Cancel the refresh task for the ASYNC refresh materialized view `lo_mv1`.
+
+```SQL
+CANCEL REFRESH MATERIALIZED VIEW lo_mv1;
+CANCEL REFRESH MATERIALIZED VIEW lo_mv1 FORCE;
+```
diff --git a/docs/en/sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md
new file mode 100644
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+++ b/docs/en/sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md
@@ -0,0 +1,868 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE MATERIALIZED VIEW
+
+## Description
+
+Creates a materialized view. For usage information about materialized views, see [Synchronous materialized view](../../../using_starrocks/Materialized_view-single_table.md) and [Asynchronous materialized view](../../../using_starrocks/Materialized_view.md).
+
+> **CAUTION**
+>
+> Only users with the CREATE MATERIALIZED VIEW privilege in the database where the base table resides can create a materialized view.
+
+Creating a materialized view is an asynchronous operation. Running this command successfully indicates that the task of creating the materialized view is submitted successfully. You can view the building status of a synchronous materialized view in a database via [SHOW ALTER MATERIALIZED VIEW](SHOW_ALTER_MATERIALIZED_VIEW.md) command, and view that of an asynchronous materialized view by querying the metadata views [`tasks`](../../information_schema/tasks.md) and [`task_runs`](../../information_schema/task_runs.md) in [Information Schema](../../information_schema/information_schema.md).
+
+StarRocks supports asynchronous materialized views from v2.4. The major differences between asynchronous materialized views and synchronous materialized views in previous versions are as follows:
+
+|                       | **Single-table aggregation** | **Multi-table join** | **Query rewrite** | **Refresh strategy** | **Base table** |
+| --------------------- | ---------------------------- | -------------------- | ----------------- | -------------------- | -------------- |
+| **ASYNC MV** | Yes | Yes | Yes | <ul><li>Asynchronous refresh</li><li>Manual refresh</li></ul> | Multiple tables from:<ul><li>Default catalog</li><li>External catalogs (v2.5)</li><li>Existing materialized views (v2.5)</li><li>Existing views (v3.1)</li></ul> |
+| **SYNC MV (Rollup)**  | Limited choices of aggregate functions | No | Yes | Synchronous refresh during data loading | Single table in the default catalog |
+
+## Synchronous materialized view
+
+### Syntax
+
+```SQL
+CREATE MATERIALIZED VIEW [IF NOT EXISTS] [database.]<mv_name>
+[COMMENT ""]
+[PROPERTIES ("key"="value", ...)]
+AS 
+<query_statement>
+```
+
+Parameters in brackets [] are optional.
+
+### Parameters
+
+**mv_name** (required)
+
+The name of the materialized view. The naming requirements are as follows:
+
+- The name must consist of letters (a-z or A-Z), digits (0-9), or underscores (\_), and it can only start with a letter.
+- The length of the name cannot exceed 64 characters.
+- The name is case-sensitive.
+
+**COMMENT** (optional)
+
+Comment on the materialized view. Note that `COMMENT` must be placed after `mv_name`. Otherwise, the materialized view cannot be created.
+
+**query_statement** (required)
+
+The query statement to create the materialized view. Its result is the data in the materialized view. The syntax is as follows:
+
+```SQL
+SELECT select_expr[, select_expr ...]
+[WHERE where_expr]
+[GROUP BY column_name[, column_name ...]]
+[ORDER BY column_name[, column_name ...]]
+```
+
+- select_expr (required)
+
+  All columns in the query statement, that is, all columns in the materialized view schema. This parameter supports the following values:
+
+  - Simple columns or aggregate columns such as `SELECT a, abs(b), min(c) FROM table_a`, where `a`, `b`, and `c` are the names of columns in the base table. If you do not specify column names for the materialized view, StarRocks automatically assigns names to the columns.
+  - Expressions such as `SELECT a+1 AS x, b+2 AS y, c*c AS z FROM table_a`, where `a+1`, `b+2` and `c*c` are the expressions that reference the columns in the base tables, and `x`, `y` and `z` are the aliases assigned to the columns in the materialized view.
+
+  > **NOTE**
+  >
+  > - You must specify at least one column in `select_expr`.
+  > - When creating a synchronous materialized view with an aggregate function, you must specify the GROUP BY clause, and specify at least one GROUP BY column in `select_expr`.
+  > - Synchronous materialized views do not support clauses such as JOIN and the HAVING clause of GROUP BY.
+  > - From v3.1 onwards, each synchronous materialized view can support more than one aggregate function for each column of the base table, for example, query statements such as `select b, sum(a), min(a) from table group by b`.
+  > - From v3.1 onwards, synchronous materialized views support complex expressions for SELECT and aggregate functions, for example, query statements such as `select b, sum(a + 1) as sum_a1, min(cast (a as bigint)) as min_a from table group by b` or `select abs(b) as col1, a + 1 as col2, cast(a as bigint) as col3 from table`. The following restrictions are imposed on the complex expression used for synchronous materialized views:
+  >   - Each complex expression must have an alias and different aliases must be assigned to different complex expressions among all the synchronous materialized views of a base table. For example, query statements `select b, sum(a + 1) as sum_a from table group by b` and `select b, sum(a) as sum_a from table group by b` cannot be used to create synchronous materialized views for a same base table. You can set different aliases for a complex expression.
+  >   - You can check whether your queries are rewritten by the synchronous materialized views created with complex expressions by executing `EXPLAIN <sql_statement>`. For more information, see [Query analysis](../../../administration/Query_planning.md).
+
+- WHERE (optional)
+
+  From v3.1.8 onwards, synchronous materialized views support the WHERE clause which can filter rows used for the materialized view.
+
+- GROUP BY (optional)
+
+  The GROUP BY column of the query. If this parameter is not specified, the data will not be grouped by default.
+
+- ORDER BY (optional)
+
+  The ORDER BY column of the query.
+
+  - Columns in the ORDER BY clause must be declared in the same order as the columns in `select_expr`.
+  - If the query statement contains a GROUP BY clause, the ORDER BY columns must be identical to the GROUP BY columns.
+  - If this parameter is not specified, the system will automatically supplement the ORDER BY column according to the following rules:
+    - If the materialized view is the AGGREGATE type, all GROUP BY columns are automatically used as sort keys.
+    - If the materialized view is not the AGGREGATE type, StarRocks automatically selects sort keys based on the prefix columns.
+
+### Query a synchronous materialized view
+
+Because a synchronous materialized view is essentially an index of the base table rather than a physical table, you can only query a synchronous materialized view using the hint `[_SYNC_MV_]`:
+
+```SQL
+-- Do not omit the brackets [] in the hint.
+SELECT * FROM <mv_name> [_SYNC_MV_];
+```
+
+> **CAUTION**
+>
+> Currently, StarRocks automatically generates names for columns in a synchronous materialized view even if you have specified aliases for them.
+
+### Automatic query rewrite with synchronous materialized view
+
+When a query that follows the pattern of a synchronous materialized view is executed, the original query statement is automatically rewritten and the intermediate results stored in the materialized view are used.
+
+The following table shows the correspondence between the aggregate function in the original query and the aggregate function used to construct the materialized view. You can select the corresponding aggregate function to build a materialized view according to your business scenario.
+
+| **aggregate function in the original query**           | **aggregate function of the materialized view** |
+| ------------------------------------------------------ | ----------------------------------------------- |
+| sum                                                    | sum                                             |
+| min                                                    | min                                             |
+| max                                                    | max                                             |
+| count                                                  | count                                           |
+| bitmap_union, bitmap_union_count, count(distinct)      | bitmap_union                                    |
+| hll_raw_agg, hll_union_agg, ndv, approx_count_distinct | hll_union                                       |
+| percentile_approx, percentile_union                    | percentile_union                                |
+
+## Asynchronous materialized view
+
+### Syntax
+
+```SQL
+CREATE MATERIALIZED VIEW [IF NOT EXISTS] [database.]<mv_name>
+[COMMENT ""]
+-- You must specify either `distribution_desc` or `refresh_scheme`, or both.
+-- distribution_desc
+[DISTRIBUTED BY HASH(<bucket_key>[,<bucket_key2> ...]) [BUCKETS <bucket_number>]]
+-- refresh_desc
+[REFRESH 
+-- refresh_moment
+    [IMMEDIATE | DEFERRED]
+-- refresh_scheme
+    [ASYNC | ASYNC [START (<start_time>)] EVERY (INTERVAL <refresh_interval>) | MANUAL]
+]
+-- partition_expression
+[PARTITION BY 
+    {<date_column> | date_trunc(fmt, <date_column>)}
+]
+-- order_by_expression
+[ORDER BY (<sort_key>)]
+[PROPERTIES ("key"="value", ...)]
+AS 
+<query_statement>
+```
+
+Parameters in brackets [] are optional.
+
+### Parameters
+
+**mv_name** (required)
+
+The name of the materialized view. The naming requirements are as follows:
+
+- The name must consist of letters (a-z or A-Z), digits (0-9), or underscores (\_), and it can only start with a letter.
+- The length of the name cannot exceed 64 characters.
+- The name is case-sensitive.
+
+> **CAUTION**
+>
+> Multiple materialized views can be created on the same base table, but the names of the materialized views in the same database cannot be duplicated.
+
+**COMMENT** (optional)
+
+Comment on the materialized view. Note that `COMMENT` must be placed after `mv_name`. Otherwise, the materialized view cannot be created.
+
+**distribution_desc** (optional)
+
+The bucketing strategy of the asynchronous materialized view. StarRocks supports hash bucketing and random bucketing (from v3.1 onwards). If you do not specify this parameter, StarRocks uses the random bucketing strategy and automatically sets the number of buckets.
+
+> **NOTE**
+>
+> While creating an asynchronous materialized view, you must specify either `distribution_desc` or `refresh_scheme`, or both.
+
+- **Hash bucketing**:
+
+  Syntax
+
+  ```SQL
+  DISTRIBUTED BY HASH (<bucket_key1>[,<bucket_key2> ...]) [BUCKETS <bucket_number>]
+  ```
+
+  For more information, see [Data distribution](../../../table_design/Data_distribution.md#data-distribution).
+
+  > **NOTE**
+  >
+  > Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../../../table_design/Data_distribution.md#set-the-number-of-buckets).
+
+- **Random bucketing**:
+
+  If you choose the random bucketing strategy and allow StarRocks to set the number of buckets automatically, you do not need to specify `distribution_desc`. However, if you want to set the number of buckets manually, you can refer to the following syntax:
+
+  ```SQL
+  DISTRIBUTED BY RANDOM BUCKETS <bucket_number>
+  ```
+
+  > **CAUTION**
+  >
+  > Asynchronous materialized views with a random bucketing strategy cannot be assigned to a colocation group.
+
+  For more information, see [Random bucketing](../../../table_design/Data_distribution.md#random-bucketing-since-v31)
+
+**refresh_moment** (optional)
+
+The refresh moment of the materialized view. Default value: `IMMEDIATE`. Valid values:
+
+- `IMMEDIATE`: Refresh the asynchronous materialized view immediately after it is created.
+- `DEFERRED`: The asynchronous materialized view is not refreshed after it is created. You can manually refresh the materialized view or schedule regular refresh tasks.
+
+**refresh_scheme** (optional)
+
+> **NOTE**
+>
+> While creating an asynchronous materialized view, you must specify either `distribution_desc` or `refresh_scheme`, or both.
+
+The refresh strategy of the asynchronous materialized view. Valid values:
+
+- `ASYNC`: Automatic refresh mode. Each time the base table data changes, the materialized view is automatically refreshed.
+- `ASYNC [START (<start_time>)] EVERY(INTERVAL <interval>)`: Regular refresh mode. The materialized view is refreshed regularly at the interval defined. You can specify the interval as `EVERY (interval n day/hour/minute/second)` using the following units: `DAY`, `HOUR`, `MINUTE`, and `SECOND`. The default value is `10 MINUTE`. You can further specify the refresh start time as `START('yyyy-MM-dd hh:mm:ss')`. If the start time is not specified, the current time is used. Example: `ASYNC START ('2023-09-12 16:30:25') EVERY (INTERVAL 5 MINUTE)`.
+- `MANUAL`: Manual refresh mode. The materialized view will not be refreshed unless you trigger a refresh task manually.
+
+If this parameter is not specified, the default value `MANUAL` is used.
+
+**partition_expression** (optional)
+
+The partitioning strategy of the asynchronous materialized view. As for the current version of StarRocks, only one partition expression is supported when creating an asynchronous materialized view.
+
+> **CAUTION**
+>
+> Currently, asynchronous materialized views do not support the list partitioning strategy.
+
+Valid values:
+
+- `column_name`: The name of the column used for partitioning. The expression `PARTITION BY dt` means to partition the materialized view according to the `dt` column.
+- `date_trunc` function: The function used to truncate the time unit. `PARTITION BY date_trunc("MONTH", dt)` means that the `dt` column is truncated to month as the unit for partitioning. The `date_trunc` function supports truncating time to units including `YEAR`, `MONTH`, `DAY`, `HOUR`, and `MINUTE`.
+- `str2date` function: The function used to partition string type parititions of base table into materialized view's partition. `PARTITION BY str2date(dt, "%Y%m%d")` means that the `dt` column is a string date type whose date format is `"%Y%m%d"`. The `str2date` function supports a lot of date formats, you can refer to [str2date](../../sql-functions/date-time-functions/str2date.md) for more information. Supported from v3.1.4.
+- `time_slice` function: From v3.1 onwards, you can further use these functions to convert the given time into the beginning or end of a time interval based on the specified time granularity, for example, `PARTITION BY date_trunc("MONTH", time_slice(dt, INTERVAL 7 DAY))` where time_slice must have a finer granularity than date_trunc. You can use them to specify a GROUP BY column with a finer granularity than that of the partitioning key, for example, `GROUP BY time_slice(dt, INTERVAL 1 MINUTE) PARTITION BY date_trunc('DAY', ts)`.
+
+If this parameter is not specified, no partitioning strategy is adopted by default.
+
+**order_by_expression** (optional)
+
+The sort key of the asynchronous materialized view. If you do not specify the sort key, StarRocks chooses some of the prefix columns from SELECT columns as the sort keys. For example, in `select a, b, c, d`, sort keys can be `a` and `b`. This parameter is supported from StarRocks v3.0 onwards.
+
+**PROPERTIES** (optional)
+
+Properties of the asynchronous materialized view. You can modify the properties of an existing materialized view using [ALTER MATERIALIZED VIEW](ALTER_MATERIALIZED_VIEW.md).
+
+- `session.`: If you want to alter a session variable-related property of the materialized view, you must add a `session.` prefix to the property, for example, `session.query_timeout`. You do not need to specify the prefix for non-session properties, for example, `mv_rewrite_staleness_second`.
+- `replication_num`: The number of materialized view replicas to create.
+- `storage_medium`: Storage medium type. Valid values: `HDD` and `SSD`.
+- `storage_cooldown_time`: the storage cooldown time for a partition. If both HDD and SSD storage mediums are used, data in the SSD storage is moved to the HDD storage after the time specified by this property. Format: "yyyy-MM-dd HH:mm:ss". The specified time must be later than the current time. If this property is not explicitly specified, the storage cooldown is not performed by default.
+- `partition_ttl`: The time-to-live (TTL) for partitions. Partitions whose data is within the specified time range are retained. Expired partitions are deleted automatically. Unit: `YEAR`, `MONTH`, `DAY`, `HOUR`, and `MINUTE`. For example, you can specify this property as `2 MONTH`. This property is recommended over `partition_ttl_number`. It is supported from v3.1.5 onwards.
+- `partition_ttl_number`: The number of most recent materialized view partitions to retain. For the partitions with a start time earlier than the current time, after the number of these partitions exceeds this value, less recent partitions will be deleted. StarRocks will periodically check materialized view partitions according to the time interval specified in the FE configuration item `dynamic_partition_check_interval_seconds`, and automatically delete expired partitions. If you enabled the [dynamic partitioning](../../../table_design/dynamic_partitioning.md) strategy, the partitions created in advance are not counted in. When the value is `-1`, all partitions of the materialized view will be preserved. Default: `-1`.
+- `partition_refresh_number`: In a single refresh, the maximum number of partitions to refresh. If the number of partitions to be refreshed exceeds this value, StarRocks will split the refresh task and complete it in batches. Only when the previous batch of partitions is refreshed successfully, StarRocks will continue to refresh the next batch of partitions until all partitions are refreshed. If any of the partitions fail to be refreshed, no subsequent refresh tasks will be generated. When the value is `-1`, the refresh task will not be split. The default value is changed from `-1` to `1` since v3.3, meaning StarRocks refeshes partitions one by one.
+- `excluded_trigger_tables`: If a base table of the materialized view is listed here, the automatic refresh task will not be triggered when the data in the base table is changed. This parameter only applies to load-triggered refresh strategy, and is usually used together with the property `auto_refresh_partitions_limit`. Format: `[db_name.]table_name`. When the value is an empty string, any data change in all base tables triggers the refresh of the corresponding materialized view. The default value is an empty string.
+- `auto_refresh_partitions_limit`: The number of most recent materialized view partitions that need to be refreshed when a materialized view refresh is triggered. You can use this property to limit the refresh range and reduce the refresh cost. However, because not all the partitions are refreshed, the data in the materialized view may not be consistent with the base table. Default: `-1`. When the value is `-1`, all partitions will be refreshed. When the value is a positive integer N, StarRocks sorts the existing partitions in chronological order, and refreshes the current partition and N-1 most recent partitions. If the number of partitions is less than N, StarRocks refreshes all existing partitions. If there are dynamic partitions created in advance in your materialized view, StarRocks refreshes all pre-created partitions.
+- `mv_rewrite_staleness_second`: If the materialized view's last refresh is within the time interval specified in this property, this materialized view can be used directly for query rewrite, regardless of whether the data in the base tables changes. If the last refresh is before this time interval, StarRocks checks whether the base tables have been updated to determine whether the materialized view can be used for query rewrite. Unit: Second. This property is supported from v3.0.
+- `colocate_with`: The colocation group of the asynchronous materialized view. See [Colocate Join](../../../using_starrocks/Colocate_join.md) for further information. This property is supported from v3.0.
+- `unique_constraints` and `foreign_key_constraints`: The Unique Key constraints and Foreign Key constraints when you create an asynchronous materialized view for query rewrite in the View Delta Join scenario. See [Asynchronous materialized view - Rewrite queries in View Delta Join scenario](../../../using_starrocks/query_rewrite_with_materialized_views.md) for further information. This property is supported from v3.0.
+
+  > **CAUTION**
+  >
+  > The Unique Key constraints and Foreign Key constraints are only used for query rewrite. The Foreign Key constraint checks are not guaranteed when data is loaded into the table. You must ensure the data loaded into the table meets the constraints.
+
+- `resource_group`: The resource group to which the refresh tasks of the materialized view belong. The default value of this property is `default_mv_wg`, which is a system-defined resource group specifically used for materialized view refresh. The `cpu_core_limit` of `default_mv_wg` is `1`, `mem_limit` is `0.8`. For more about resource groups, see [Resource group](../../../administration/management/resource_management/resource_group.md).
+- `query_rewrite_consistency`: The query rewrite rule for the asynchronous materialized views. This property is supported from v3.2. Valid values:
+  - `disable`: Disable automatic query rewrite of the asynchronous materialized view.
+  - `checked` (Default value): Enable automatic query rewrite only when the materialized view meets the timeliness requirement, which means:
+    - If `mv_rewrite_staleness_second` is not specified, the materialized view can be used for query rewrite only when its data is consistent with the data in all base tables.
+    - If `mv_rewrite_staleness_second` is specified, the materialized view can be used for query rewrite when its last refresh is within the staleness time interval.
+  - `loose`: Enable automatic query rewrite directly, and no consistency check is required.
+- `storage_volume`: The name of the storage volume used to store the asynchronous materialized view you want to create if you are using a shared-data cluster. This property is supported from v3.1 onwards. If this property is not specified, the default storage volume is used. Example: `"storage_volume" = "def_volume"`.
+- `force_external_table_query_rewrite`: Whether to enable query rewrite for external catalog-based materialized views. This property is supported from v3.2. Valid values:
+  - `true`(Default value since v3.3): Enable query rewrite for external catalog-based materialized views.
+  - `false`: Disable query rewrite for external catalog-based materialized views.
+
+  Because strong data consistency is not guaranteed between base tables and external catalog-based materialized views, this feature is set to `false` by default. When this feature is enabled, the materialized view is used for query rewrite in accordance with the rule specified in `query_rewrite_consistency`.
+- `enable_query_rewrite`: Whether to use the materialized view for query rewrite. When there are many materialized views, query rewrite based on materialized views can impact the optimizer's time consumption. With this property, you can control whether the materialized view can be used for query rewrite. This feature is supported from v3.3.0 onwards. Valid values:
+  - `default` (Default): The system will not perform semantic checks on the materialized view, but only the SPJG-type materialized views can be used for query rewrite. Note that if the text-based query rewrite is enabled, non-SPJG-type materialized views can also be used for query rewrite.
+  - `true`: The system will perform semantic checks when creating or modifying the materialized view. If the materialized view is not eligible for query rewrite (that is, the definition of the materialized view is not an SPJG-type query), a failure will be returned.
+  - `false`: The materialized view will not be used for query rewrite.
+- [Preview] `transparent_mv_rewrite_mode`: Specifies the transparent rewrite mode for **queries directly against the materialized view**. This feature is supported from v3.3.0 onwards. Valid values:
+  - `false` (Default, compatible with the behavior in earlier versions): Queries directly against the materialized view will not be rewritten, and are only returned with the existing data in the materialized view. Their query results may be different from those of queries based on the definition of the materialized view according to the refresh status (data consistency) of the materialized view.
+  - `true`: Queries directly against the materialized view will be rewritten and returned with the most updated data, which is consistent with the result of the materialized view definition query. Please note that when the materialized view is inactive or does not support transparent query rewrite, these queries will be executed as the materialized view definition query.
+  - `transparent_or_error`: Queries directly against the materialized view will be rewritten whenever they are eligible. If the materialized view is inactive or does not support transparent query rewrite, these queries will be returned with an error.
+  - `transparent_or_default` Queries directly against the materialized view will be rewritten whenever they are eligible. If the materialized view is inactive or does not support transparent query rewrite, these queries will be returned with the existing data in the materialized view.
+
+**query_statement** (required)
+
+The query statement to create the asynchronous materialized view. From v3.1.6 onwards, StarRocks supports creating asynchronous materialized views with Common Table Expression (CTE).
+
+> **CAUTION**
+>
+> Currently, StarRocks does not support creating asynchronous materialized views with base tables created with the list partitioning strategy.
+
+### Query an asynchronous materialized view
+
+An asynchronous materialized view is a physical table. You can operate it as any regular table **except that you cannot directly load data into an asynchronous materialized view**.
+
+### Automatic query rewrite with asynchronous materialized view
+
+StarRocks v2.5 supports automatic and transparent query rewrite based on the SPJG-type asynchronous materialized views. The SPJG-type materialized views refer to materialized views whose plan only includes Scan, Filter, Project, and Aggregate types of operators. The SPJG-type materialized views query rewrite includes single table query rewrite, Join query rewrite, aggregation query rewrite, Union query rewrite and query rewrite based on nested materialized views.
+
+See [Asynchronous materialized view -  Rewrite queries with the asynchronous materialized view](../../../using_starrocks/query_rewrite_with_materialized_views.md) for further information.
+
+### Supported data types
+
+- Asynchronous materialized views created based on the StarRocks default catalog support the following data types:
+
+  - **Date**: DATE, DATETIME
+  - **String**: CHAR, VARCHAR
+  - **Numeric**: BOOLEAN, TINYINT, SMALLINT, INT, BIGINT, LARGEINT, FLOAT, DOUBLE, DECIMAL, PERCENTILE
+  - **Semi-structured**: ARRAY, JSON, MAP (from v3.1 onwards), STRUCT (from v3.1 onwards)
+  - **Other**: BITMAP, HLL
+
+> **NOTE**
+>
+> BITMAP, HLL, and PERCENTILE have been supported since v2.4.5.
+
+- Asynchronous materialized views created based on the StarRocks external catalogs support the following data types:
+
+  - Hive Catalog
+
+    - **Numeric**: INT/INTEGER, BIGINT, DOUBLE, FLOAT, DECIMAL
+    - **Date**: TIMESTAMP
+    - **String**: STRING, VARCHAR, CHAR
+    - **Semi-structured**: ARRAY
+
+  - Hudi Catalog
+
+    - **Numeric**: BOOLEAN, INT, LONG, FLOAT, DOUBLE, DECIMAL
+    - **Date**: DATE, TimeMillis/TimeMicros, TimestampMillis/TimestampMicros
+    - **String**: STRING
+    - **Semi-structured**: ARRAY
+
+  - Iceberg Catalog
+
+    - **Numeric**: BOOLEAN, INT, LONG, FLOAT, DOUBLE, DECIMAL(P, S)
+    - **Date**: DATE, TIME, TIMESTAMP
+    - **String**: STRING, UUID, FIXED(L), BINARY
+    - **Semi-structured**: LIST
+
+## Usage notes
+
+- The current version of StarRocks does not support creating multiple materialized views at the same time. A new materialized view can only be created when the one before is completed.
+
+- About synchronous materialized views:
+
+  - Synchronous materialized views only support aggregate functions on a single column. Query statements in the form of `sum(a+b)` are not supported.
+  - Synchronous materialized views support only one aggregate function for each column of the base table. Query statements such as `select sum(a), min(a) from table` are not supported.
+  - When creating a synchronous materialized view with an aggregate function, you must specify the GROUP BY clause, and specify at least one GROUP BY column in SELECT.
+  - Synchronous materialized views do not support clauses such as JOIN, and the HAVING clause of GROUP BY.
+  - When using ALTER TABLE DROP COLUMN to drop a specific column in a base table, you must ensure that all synchronous materialized views of the base table do not contain the dropped column, otherwise, the drop operation will fail. Before you drop the column, you must first drop all synchronous materialized views that contain the column.
+  - Creating too many synchronous materialized views for a table will affect the data load efficiency. When data is being loaded to the base table, the data in the synchronous materialized view and the base table will be updated synchronously. If a base table contains `n` synchronous materialized views, the efficiency of loading data into the base table is about the same as the efficiency of loading data into `n` tables.
+
+- About nested asynchronous materialized views:
+
+  - The refresh strategy for each materialized view only applies to the corresponding materialized view.
+  - Currently, StarRocks does not limit the number of nesting levels. In a production environment, we recommend that the number of nesting layers not exceed THREE.
+
+- About external catalog asynchronous materialized views:
+
+  - External catalog materialized view only support async fixed-interval refresh and manual refresh.
+  - Strict consistency is not guaranteed between the materialized view and the base tables in the external catalog.
+  - Currently, building materialized views based on external resources is not supported.
+  - Currently, StarRocks cannot perceive if the base table data in the external catalog has changed, so all partitions will be refreshed by default every time the base table is refreshed. You can manually refresh only some of partitions using [REFRESH MATERIALIZED VIEW](REFRESH_MATERIALIZED_VIEW.md).
+
+## Examples
+
+### Examples of synchronous materialized views
+
+The schema of the base table is as follows:
+
+```Plain Text
+mysql> desc duplicate_table;
++-------+--------+------+------+---------+-------+
+| Field | Type   | Null | Key  | Default | Extra |
++-------+--------+------+------+---------+-------+
+| k1    | INT    | Yes  | true | N/A     |       |
+| k2    | INT    | Yes  | true | N/A     |       |
+| k3    | BIGINT | Yes  | true | N/A     |       |
+| k4    | BIGINT | Yes  | true | N/A     |       |
++-------+--------+------+------+---------+-------+
+```
+
+Example 1: Create a synchronous materialized view that only contains the columns of the original table (k1, k2).
+
+```sql
+create materialized view k1_k2 as
+select k1, k2 from duplicate_table;
+```
+
+The materialized view contains only two columns k1 and k2 without any aggregation.
+
+```plain text
++-----------------+-------+--------+------+------+---------+-------+
+| IndexName       | Field | Type   | Null | Key  | Default | Extra |
++-----------------+-------+--------+------+------+---------+-------+
+| k1_k2           | k1    | INT    | Yes  | true | N/A     |       |
+|                 | k2    | INT    | Yes  | true | N/A     |       |
++-----------------+-------+--------+------+------+---------+-------+
+```
+
+Example 2: Create a synchronous materialized view sorted by k2.
+
+```sql
+create materialized view k2_order as
+select k2, k1 from duplicate_table order by k2;
+```
+
+The materialized view's schema is shown below. The materialized view contains only two columns k2 and k1, where column k2 is a sort column without any aggregation.
+
+```plain text
++-----------------+-------+--------+------+-------+---------+-------+
+| IndexName       | Field | Type   | Null | Key   | Default | Extra |
++-----------------+-------+--------+------+-------+---------+-------+
+| k2_order        | k2    | INT    | Yes  | true  | N/A     |       |
+|                 | k1    | INT    | Yes  | false | N/A     | NONE  |
++-----------------+-------+--------+------+-------+---------+-------+
+```
+
+Example 3: Create a synchronous materialized view grouped by k1 and k2, and a SUM aggregation on k3.
+
+```sql
+create materialized view k1_k2_sumk3 as
+select k1, k2, sum(k3) from duplicate_table group by k1, k2;
+```
+
+The materialized view's schema is shown below. The materialized view contains three columns k1, k2 and sum (k3), where k1, k2 are grouped columns, and sum (k3) is the sum of the k3 columns grouped according to k1 and k2.
+
+```plain text
++-----------------+-------+--------+------+-------+---------+-------+
+| IndexName       | Field | Type   | Null | Key   | Default | Extra |
++-----------------+-------+--------+------+-------+---------+-------+
+| k1_k2_sumk3     | k1    | INT    | Yes  | true  | N/A     |       |
+|                 | k2    | INT    | Yes  | true  | N/A     |       |
+|                 | k3    | BIGINT | Yes  | false | N/A     | SUM   |
++-----------------+-------+--------+------+-------+---------+-------+
+```
+
+Because the materialized view does not declare a sort column, and it adopts an aggregation function, StarRocks supplements the grouped columns k1 and k2 by default.
+
+Example 4: Create a synchronous materialized view to remove duplicate rows.
+
+```sql
+create materialized view deduplicate as
+select k1, k2, k3, k4 from duplicate_table group by k1, k2, k3, k4;
+```
+
+The materialized view's schema is shown below. The materialized view contains k1, k2, k3, and k4 columns, and there are no duplicate rows.
+
+```plain text
++-----------------+-------+--------+------+-------+---------+-------+
+| IndexName       | Field | Type   | Null | Key   | Default | Extra |
++-----------------+-------+--------+------+-------+---------+-------+
+| deduplicate     | k1    | INT    | Yes  | true  | N/A     |       |
+|                 | k2    | INT    | Yes  | true  | N/A     |       |
+|                 | k3    | BIGINT | Yes  | true  | N/A     |       |
+|                 | k4    | BIGINT | Yes  | true  | N/A     |       |
++-----------------+-------+--------+------+-------+---------+-------+
+```
+
+Example 5: Create a non-aggregated synchronous materialized view that does not declare a sort column.
+
+The schema of the base table is shown below:
+
+```plain text
++-------+--------------+------+-------+---------+-------+
+| Field | Type         | Null | Key   | Default | Extra |
++-------+--------------+------+-------+---------+-------+
+| k1    | TINYINT      | Yes  | true  | N/A     |       |
+| k2    | SMALLINT     | Yes  | true  | N/A     |       |
+| k3    | INT          | Yes  | true  | N/A     |       |
+| k4    | BIGINT       | Yes  | true  | N/A     |       |
+| k5    | DECIMAL(9,0) | Yes  | true  | N/A     |       |
+| k6    | DOUBLE       | Yes  | false | N/A     | NONE  |
+| k7    | VARCHAR(20)  | Yes  | false | N/A     | NONE  |
++-------+--------------+------+-------+---------+-------+
+```
+
+The materialized view contains k3, k4, k5, k6, and k7 columns, and no sort column is declared. Create the materialized view with the following statement:
+
+```sql
+create materialized view mv_1 as
+select k3, k4, k5, k6, k7 from all_type_table;
+```
+
+StarRocks automatically uses k3, k4, and k5 as the sort columns by default. The sum of the bytes occupied by these three column types is 4 (INT) + 8 (BIGINT) + 16 (DECIMAL) = 28 < 36. So these three columns are added as sort columns.
+
+The materialized view's schema is as follows.
+
+```plain text
++----------------+-------+--------------+------+-------+---------+-------+
+| IndexName      | Field | Type         | Null | Key   | Default | Extra |
++----------------+-------+--------------+------+-------+---------+-------+
+| mv_1           | k3    | INT          | Yes  | true  | N/A     |       |
+|                | k4    | BIGINT       | Yes  | true  | N/A     |       |
+|                | k5    | DECIMAL(9,0) | Yes  | true  | N/A     |       |
+|                | k6    | DOUBLE       | Yes  | false | N/A     | NONE  |
+|                | k7    | VARCHAR(20)  | Yes  | false | N/A     | NONE  |
++----------------+-------+--------------+------+-------+---------+-------+
+```
+
+It can be observed that the `key` field of the k3, k4, and k5 columns is `true`, which indicates that they are the sort keys. The key field of the k6, and k7 columns is `false`, which indicates that they are not the sort keys.
+
+Example 6: Create a synchronous materialized view that contains the WHERE clause and complex expressions.
+
+```SQL
+-- Create the base table: user_event
+CREATE TABLE user_event (
+      ds date   NOT NULL,
+      id  varchar(256)    NOT NULL,
+      user_id int DEFAULT NULL,
+      user_id1    varchar(256)    DEFAULT NULL,
+      user_id2    varchar(256)    DEFAULT NULL,
+      column_01   int DEFAULT NULL,
+      column_02   int DEFAULT NULL,
+      column_03   int DEFAULT NULL,
+      column_04   int DEFAULT NULL,
+      column_05   int DEFAULT NULL,
+      column_06   DECIMAL(12,2)   DEFAULT NULL,
+      column_07   DECIMAL(12,3)   DEFAULT NULL,
+      column_08   JSON   DEFAULT NULL,
+      column_09   DATETIME    DEFAULT NULL,
+      column_10   DATETIME    DEFAULT NULL,
+      column_11   DATE    DEFAULT NULL,
+      column_12   varchar(256)    DEFAULT NULL,
+      column_13   varchar(256)    DEFAULT NULL,
+      column_14   varchar(256)    DEFAULT NULL,
+      column_15   varchar(256)    DEFAULT NULL,
+      column_16   varchar(256)    DEFAULT NULL,
+      column_17   varchar(256)    DEFAULT NULL,
+      column_18   varchar(256)    DEFAULT NULL,
+      column_19   varchar(256)    DEFAULT NULL,
+      column_20   varchar(256)    DEFAULT NULL,
+      column_21   varchar(256)    DEFAULT NULL,
+      column_22   varchar(256)    DEFAULT NULL,
+      column_23   varchar(256)    DEFAULT NULL,
+      column_24   varchar(256)    DEFAULT NULL,
+      column_25   varchar(256)    DEFAULT NULL,
+      column_26   varchar(256)    DEFAULT NULL,
+      column_27   varchar(256)    DEFAULT NULL,
+      column_28   varchar(256)    DEFAULT NULL,
+      column_29   varchar(256)    DEFAULT NULL,
+      column_30   varchar(256)    DEFAULT NULL,
+      column_31   varchar(256)    DEFAULT NULL,
+      column_32   varchar(256)    DEFAULT NULL,
+      column_33   varchar(256)    DEFAULT NULL,
+      column_34   varchar(256)    DEFAULT NULL,
+      column_35   varchar(256)    DEFAULT NULL,
+      column_36   varchar(256)    DEFAULT NULL,
+      column_37   varchar(256)    DEFAULT NULL
+  )
+  PARTITION BY date_trunc("day", ds)
+  DISTRIBUTED BY hash(id);
+
+  -- Create the materialized view with the WHERE clause and complex expresssions.
+  CREATE MATERIALIZED VIEW test_mv1
+  AS 
+  SELECT
+  ds,
+  column_19,
+  column_36,
+  sum(column_01) as column_01_sum,
+  bitmap_union(to_bitmap( user_id)) as user_id_dist_cnt,
+  bitmap_union(to_bitmap(case when column_01 > 1 and column_34 IN ('1','34')   then user_id2 else null end)) as filter_dist_cnt_1,
+  bitmap_union(to_bitmap( case when column_02 > 60 and column_35 IN ('11','13') then  user_id2 else null end)) as filter_dist_cnt_2,
+  bitmap_union(to_bitmap(case when column_03 > 70 and column_36 IN ('21','23') then  user_id2 else null end)) as filter_dist_cnt_3,
+  bitmap_union(to_bitmap(case when column_04 > 20 and column_27 IN ('31','27') then  user_id2 else null end)) as filter_dist_cnt_4,
+  bitmap_union(to_bitmap( case when column_05 > 90 and column_28 IN ('41','43') then  user_id2 else null end)) as filter_dist_cnt_5
+  FROM user_event
+  WHERE ds >= '2023-11-02'
+  GROUP BY
+  ds,
+  column_19,
+  column_36;
+ ```
+
+### Examples of asynchronous materialized views
+
+The following examples are based on the base tables below:
+
+```SQL
+CREATE TABLE `lineorder` (
+  `lo_orderkey` int(11) NOT NULL COMMENT "",
+  `lo_linenumber` int(11) NOT NULL COMMENT "",
+  `lo_custkey` int(11) NOT NULL COMMENT "",
+  `lo_partkey` int(11) NOT NULL COMMENT "",
+  `lo_suppkey` int(11) NOT NULL COMMENT "",
+  `lo_orderdate` int(11) NOT NULL COMMENT "",
+  `lo_orderpriority` varchar(16) NOT NULL COMMENT "",
+  `lo_shippriority` int(11) NOT NULL COMMENT "",
+  `lo_quantity` int(11) NOT NULL COMMENT "",
+  `lo_extendedprice` int(11) NOT NULL COMMENT "",
+  `lo_ordtotalprice` int(11) NOT NULL COMMENT "",
+  `lo_discount` int(11) NOT NULL COMMENT "",
+  `lo_revenue` int(11) NOT NULL COMMENT "",
+  `lo_supplycost` int(11) NOT NULL COMMENT "",
+  `lo_tax` int(11) NOT NULL COMMENT "",
+  `lo_commitdate` int(11) NOT NULL COMMENT "",
+  `lo_shipmode` varchar(11) NOT NULL COMMENT ""
+) ENGINE=OLAP
+DUPLICATE KEY(`lo_orderkey`)
+COMMENT "OLAP"
+PARTITION BY RANGE(`lo_orderdate`)
+(PARTITION p1 VALUES [("-2147483648"), ("19930101")),
+PARTITION p2 VALUES [("19930101"), ("19940101")),
+PARTITION p3 VALUES [("19940101"), ("19950101")),
+PARTITION p4 VALUES [("19950101"), ("19960101")),
+PARTITION p5 VALUES [("19960101"), ("19970101")),
+PARTITION p6 VALUES [("19970101"), ("19980101")),
+PARTITION p7 VALUES [("19980101"), ("19990101")))
+DISTRIBUTED BY HASH(`lo_orderkey`);
+
+CREATE TABLE IF NOT EXISTS `customer` (
+  `c_custkey` int(11) NOT NULL COMMENT "",
+  `c_name` varchar(26) NOT NULL COMMENT "",
+  `c_address` varchar(41) NOT NULL COMMENT "",
+  `c_city` varchar(11) NOT NULL COMMENT "",
+  `c_nation` varchar(16) NOT NULL COMMENT "",
+  `c_region` varchar(13) NOT NULL COMMENT "",
+  `c_phone` varchar(16) NOT NULL COMMENT "",
+  `c_mktsegment` varchar(11) NOT NULL COMMENT ""
+) ENGINE=OLAP
+DUPLICATE KEY(`c_custkey`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`c_custkey`);
+
+CREATE TABLE IF NOT EXISTS `dates` (
+  `d_datekey` int(11) NOT NULL COMMENT "",
+  `d_date` varchar(20) NOT NULL COMMENT "",
+  `d_dayofweek` varchar(10) NOT NULL COMMENT "",
+  `d_month` varchar(11) NOT NULL COMMENT "",
+  `d_year` int(11) NOT NULL COMMENT "",
+  `d_yearmonthnum` int(11) NOT NULL COMMENT "",
+  `d_yearmonth` varchar(9) NOT NULL COMMENT "",
+  `d_daynuminweek` int(11) NOT NULL COMMENT "",
+  `d_daynuminmonth` int(11) NOT NULL COMMENT "",
+  `d_daynuminyear` int(11) NOT NULL COMMENT "",
+  `d_monthnuminyear` int(11) NOT NULL COMMENT "",
+  `d_weeknuminyear` int(11) NOT NULL COMMENT "",
+  `d_sellingseason` varchar(14) NOT NULL COMMENT "",
+  `d_lastdayinweekfl` int(11) NOT NULL COMMENT "",
+  `d_lastdayinmonthfl` int(11) NOT NULL COMMENT "",
+  `d_holidayfl` int(11) NOT NULL COMMENT "",
+  `d_weekdayfl` int(11) NOT NULL COMMENT ""
+) ENGINE=OLAP
+DUPLICATE KEY(`d_datekey`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`d_datekey`);
+
+CREATE TABLE IF NOT EXISTS `supplier` (
+  `s_suppkey` int(11) NOT NULL COMMENT "",
+  `s_name` varchar(26) NOT NULL COMMENT "",
+  `s_address` varchar(26) NOT NULL COMMENT "",
+  `s_city` varchar(11) NOT NULL COMMENT "",
+  `s_nation` varchar(16) NOT NULL COMMENT "",
+  `s_region` varchar(13) NOT NULL COMMENT "",
+  `s_phone` varchar(16) NOT NULL COMMENT ""
+) ENGINE=OLAP
+DUPLICATE KEY(`s_suppkey`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`s_suppkey`);
+
+CREATE TABLE IF NOT EXISTS `part` (
+  `p_partkey` int(11) NOT NULL COMMENT "",
+  `p_name` varchar(23) NOT NULL COMMENT "",
+  `p_mfgr` varchar(7) NOT NULL COMMENT "",
+  `p_category` varchar(8) NOT NULL COMMENT "",
+  `p_brand` varchar(10) NOT NULL COMMENT "",
+  `p_color` varchar(12) NOT NULL COMMENT "",
+  `p_type` varchar(26) NOT NULL COMMENT "",
+  `p_size` int(11) NOT NULL COMMENT "",
+  `p_container` varchar(11) NOT NULL COMMENT ""
+) ENGINE=OLAP
+DUPLICATE KEY(`p_partkey`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`p_partkey`);
+
+create table orders ( 
+    dt date NOT NULL, 
+    order_id bigint NOT NULL, 
+    user_id int NOT NULL, 
+    merchant_id int NOT NULL, 
+    good_id int NOT NULL, 
+    good_name string NOT NULL, 
+    price int NOT NULL, 
+    cnt int NOT NULL, 
+    revenue int NOT NULL, 
+    state tinyint NOT NULL 
+) 
+PRIMARY KEY (dt, order_id) 
+PARTITION BY RANGE(`dt`) 
+( PARTITION p20210820 VALUES [('2021-08-20'), ('2021-08-21')), 
+PARTITION p20210821 VALUES [('2021-08-21'), ('2021-08-22')) ) 
+DISTRIBUTED BY HASH(order_id)
+PROPERTIES (
+    "replication_num" = "3", 
+    "enable_persistent_index" = "true"
+);
+```
+
+Example 1: Create a non-partitioned materialized view.
+
+```SQL
+CREATE MATERIALIZED VIEW lo_mv1
+DISTRIBUTED BY HASH(`lo_orderkey`)
+REFRESH ASYNC
+AS
+select
+    lo_orderkey, 
+    lo_custkey, 
+    sum(lo_quantity) as total_quantity, 
+    sum(lo_revenue) as total_revenue, 
+    count(lo_shipmode) as shipmode_count
+from lineorder 
+group by lo_orderkey, lo_custkey 
+order by lo_orderkey;
+```
+
+Example 2: Create a partitioned materialized view.
+
+```SQL
+CREATE MATERIALIZED VIEW lo_mv2
+PARTITION BY `lo_orderdate`
+DISTRIBUTED BY HASH(`lo_orderkey`)
+REFRESH ASYNC START('2023-07-01 10:00:00') EVERY (interval 1 day)
+AS
+select
+    lo_orderkey,
+    lo_orderdate,
+    lo_custkey, 
+    sum(lo_quantity) as total_quantity, 
+    sum(lo_revenue) as total_revenue, 
+    count(lo_shipmode) as shipmode_count
+from lineorder 
+group by lo_orderkey, lo_orderdate, lo_custkey
+order by lo_orderkey;
+
+-- Use the date_trunc() function to partition the materialized view by month.
+CREATE MATERIALIZED VIEW order_mv1
+PARTITION BY date_trunc('month', `dt`)
+DISTRIBUTED BY HASH(`order_id`)
+REFRESH ASYNC START('2023-07-01 10:00:00') EVERY (interval 1 day)
+AS
+select
+    dt,
+    order_id,
+    user_id,
+    sum(cnt) as total_cnt,
+    sum(revenue) as total_revenue, 
+    count(state) as state_count
+from orders
+group by dt, order_id, user_id;
+```
+
+Example 3: Create an asynchronous materialized view.
+
+```SQL
+CREATE MATERIALIZED VIEW flat_lineorder
+DISTRIBUTED BY HASH(`lo_orderkey`)
+REFRESH MANUAL
+AS
+SELECT
+    l.LO_ORDERKEY AS LO_ORDERKEY,
+    l.LO_LINENUMBER AS LO_LINENUMBER,
+    l.LO_CUSTKEY AS LO_CUSTKEY,
+    l.LO_PARTKEY AS LO_PARTKEY,
+    l.LO_SUPPKEY AS LO_SUPPKEY,
+    l.LO_ORDERDATE AS LO_ORDERDATE,
+    l.LO_ORDERPRIORITY AS LO_ORDERPRIORITY,
+    l.LO_SHIPPRIORITY AS LO_SHIPPRIORITY,
+    l.LO_QUANTITY AS LO_QUANTITY,
+    l.LO_EXTENDEDPRICE AS LO_EXTENDEDPRICE,
+    l.LO_ORDTOTALPRICE AS LO_ORDTOTALPRICE,
+    l.LO_DISCOUNT AS LO_DISCOUNT,
+    l.LO_REVENUE AS LO_REVENUE,
+    l.LO_SUPPLYCOST AS LO_SUPPLYCOST,
+    l.LO_TAX AS LO_TAX,
+    l.LO_COMMITDATE AS LO_COMMITDATE,
+    l.LO_SHIPMODE AS LO_SHIPMODE,
+    c.C_NAME AS C_NAME,
+    c.C_ADDRESS AS C_ADDRESS,
+    c.C_CITY AS C_CITY,
+    c.C_NATION AS C_NATION,
+    c.C_REGION AS C_REGION,
+    c.C_PHONE AS C_PHONE,
+    c.C_MKTSEGMENT AS C_MKTSEGMENT,
+    s.S_NAME AS S_NAME,
+    s.S_ADDRESS AS S_ADDRESS,
+    s.S_CITY AS S_CITY,
+    s.S_NATION AS S_NATION,
+    s.S_REGION AS S_REGION,
+    s.S_PHONE AS S_PHONE,
+    p.P_NAME AS P_NAME,
+    p.P_MFGR AS P_MFGR,
+    p.P_CATEGORY AS P_CATEGORY,
+    p.P_BRAND AS P_BRAND,
+    p.P_COLOR AS P_COLOR,
+    p.P_TYPE AS P_TYPE,
+    p.P_SIZE AS P_SIZE,
+    p.P_CONTAINER AS P_CONTAINER FROM lineorder AS l 
+INNER JOIN customer AS c ON c.C_CUSTKEY = l.LO_CUSTKEY
+INNER JOIN supplier AS s ON s.S_SUPPKEY = l.LO_SUPPKEY
+INNER JOIN part AS p ON p.P_PARTKEY = l.LO_PARTKEY;
+```
+
+Example 4: Create a partitioned materialized view and use `str2date` to transform the STRING type partition key of the base table into the date type as for the materialized view.
+
+``` SQL
+
+-- Hive Table with string partition column.
+CREATE TABLE `part_dates` (
+  `d_date` varchar(20) DEFAULT NULL,
+  `d_dayofweek` varchar(10) DEFAULT NULL,
+  `d_month` varchar(11) DEFAULT NULL,
+  `d_year` int(11) DEFAULT NULL,
+  `d_yearmonthnum` int(11) DEFAULT NULL,
+  `d_yearmonth` varchar(9) DEFAULT NULL,
+  `d_daynuminweek` int(11) DEFAULT NULL,
+  `d_daynuminmonth` int(11) DEFAULT NULL,
+  `d_daynuminyear` int(11) DEFAULT NULL,
+  `d_monthnuminyear` int(11) DEFAULT NULL,
+  `d_weeknuminyear` int(11) DEFAULT NULL,
+  `d_sellingseason` varchar(14) DEFAULT NULL,
+  `d_lastdayinweekfl` int(11) DEFAULT NULL,
+  `d_lastdayinmonthfl` int(11) DEFAULT NULL,
+  `d_holidayfl` int(11) DEFAULT NULL,
+  `d_weekdayfl` int(11) DEFAULT NULL,
+  `d_datekey` varchar(11) DEFAULT NULL
+) partition by (d_datekey);
+
+
+-- Create the materialied view  with `str2date`.
+CREATE MATERIALIZED VIEW IF NOT EXISTS `test_mv` 
+PARTITION BY str2date(`d_datekey`,'%Y%m%d')
+DISTRIBUTED BY HASH(`d_date`, `d_month`, `d_month`) 
+REFRESH MANUAL 
+AS
+SELECT
+`d_date` ,
+  `d_dayofweek`,
+  `d_month` ,
+  `d_yearmonthnum` ,
+  `d_yearmonth` ,
+  `d_daynuminweek`,
+  `d_daynuminmonth`,
+  `d_daynuminyear` ,
+  `d_monthnuminyear` ,
+  `d_weeknuminyear` ,
+  `d_sellingseason`,
+  `d_lastdayinweekfl`,
+  `d_lastdayinmonthfl`,
+  `d_holidayfl` ,
+  `d_weekdayfl`,
+   `d_datekey`
+FROM
+ `hive_catalog`.`ssb_1g_orc`.`part_dates` ;
+```
diff --git a/docs/en/sql-reference/sql-statements/materialized_view/DROP_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/materialized_view/DROP_MATERIALIZED_VIEW.md
new file mode 100644
index 00000000000000..bf80a28b41e10b
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/materialized_view/DROP_MATERIALIZED_VIEW.md
@@ -0,0 +1,78 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP MATERIALIZED VIEW
+
+## Description
+
+Drops a materialized view.
+
+You cannot drop a synchronous materialized view that is being created in process with this command. To drop a synchronous materialized view that is being created in process, see [Synchronous materialized View - Drop an unfinished materialized view](../../../using_starrocks/Materialized_view-single_table.md#drop-an-unfinished-synchronous-materialized-view) for further instructions.
+
+:::tip
+
+This operation requires the DROP privilege on the target materialized view.
+
+:::
+
+## Syntax
+
+```SQL
+DROP MATERIALIZED VIEW [IF EXISTS] [database.]mv_name
+```
+
+Parameters in brackets [] is optional.
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                              |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| IF EXISTS     | no           | If this parameter is specified, StarRocks will not throw an exception when deleting a materialized view that does not exist. If this parameter is not specified, the system will throw an exception when deleting a materialized view that does not exist. |
+| mv_name       | yes          | The name of the materialized view to delete.                 |
+
+## Examples
+
+Example 1: Drop an existing materialized view
+
+1. View all existing materialized views in the database.
+
+  ```Plain
+  MySQL > SHOW MATERIALIZED VIEWS\G
+  *************************** 1. row ***************************
+              id: 470740
+          name: order_mv1
+  database_name: default_cluster:sr_hub
+        text: SELECT `sr_hub`.`orders`.`dt` AS `dt`, `sr_hub`.`orders`.`order_id` AS `order_id`, `sr_hub`.`orders`.`user_id` AS `user_id`, sum(`sr_hub`.`orders`.`cnt`) AS `total_cnt`, sum(`sr_hub`.`orders`.`revenue`) AS `total_revenue`, count(`sr_hub`.`orders`.`state`) AS `state_count` FROM `sr_hub`.`orders` GROUP BY `sr_hub`.`orders`.`dt`, `sr_hub`.`orders`.`order_id`, `sr_hub`.`orders`.`user_id`
+          rows: 0
+  1 rows in set (0.00 sec)
+  ```
+
+2. Drop the materialized view `order_mv1`.
+
+  ```SQL
+  DROP MATERIALIZED VIEW order_mv1;
+  ```
+
+3. Check if the dropped materialized view exists.
+
+  ```Plain
+  MySQL > SHOW MATERIALIZED VIEWS;
+  Empty set (0.01 sec)
+  ```
+
+Example 2: Drop a non-existing materialized view
+
+- If the parameter `IF EXISTS` is specified, StarRocks will not throw an exception when deleting a materialized view that does not exist.
+
+```Plain
+MySQL > DROP MATERIALIZED VIEW IF EXISTS k1_k2;
+Query OK, 0 rows affected (0.00 sec)
+```
+
+- If the parameter `IF EXISTS` is not specified, the system will throw an exception when deleting a materialized view that does not exist.
+
+```Plain
+MySQL > DROP MATERIALIZED VIEW k1_k2;
+ERROR 1064 (HY000): Materialized view k1_k2 is not find
+```
diff --git a/docs/en/sql-reference/sql-statements/materialized_view/REFRESH_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/materialized_view/REFRESH_MATERIALIZED_VIEW.md
new file mode 100644
index 00000000000000..46c5cdc4c21a6e
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/materialized_view/REFRESH_MATERIALIZED_VIEW.md
@@ -0,0 +1,68 @@
+---
+displayed_sidebar: docs
+---
+
+# REFRESH MATERIALIZED VIEW
+
+## Description
+
+Manually refresh a specific asynchronous materialized view or partitions within.
+
+> **CAUTION**
+>
+> You can only manually refresh materialized views that adopt ASYNC or MANUAL refresh strategy. You can check the refresh strategy of an asynchronous materialized view using [SHOW MATERIALIZED VIEWS](SHOW_MATERIALIZED_VIEW.md).
+> This operation requires the REFRESH privilege on the target materialized view.
+
+## Syntax
+
+```SQL
+REFRESH MATERIALIZED VIEW [database.]mv_name
+[PARTITION START ("<partition_start_date>") END ("<partition_end_date>")]
+[FORCE]
+[WITH { SYNC | ASYNC } MODE]
+```
+
+## Parameters
+
+| **Parameter**             | **Required** | **Description**                                        |
+| ------------------------- | ------------ | ------------------------------------------------------ |
+| mv_name                   | yes          | The name of the materialized view to refresh manually. |
+| PARTITION START () END () | no           | Manually refresh partitions within a certain time interval. |
+| partition_start_date      | no           | The start date of the partitions to refresh manually.  |
+| partition_end_date        | no           | The end date of the partitions to refresh manually.    |
+| FORCE                     | no           | If you specify this parameter, StarRocks forcibly refreshes the corresponding materialized view or partitions. If you do not specify this parameter, StarRocks automatically judges if the data is updated and refreshes the partition only when needed.  |
+| WITH ... MODE             | no           | Make a synchronous or asynchronous call of the refresh task. `SYNC` indicates making a synchronous call of the refresh task, and StarRocks returns the task result only when the task succeeds or fails. `ASYNC` indicates making an asynchronous call of the refresh task, and StarRocks returns success right after the task is submitted, leaving the task to be executed asynchronously in the background. You can check the refresh task status of an asynchronous materialized view by querying the `tasks` and `task_runs` metadata views in StarRocks' Information Schema. For more information, see [Check the execution status of asynchronous materialized view](../../../using_starrocks/Materialized_view.md#check-the-execution-status-of-asynchronous-materialized-view). Default: `ASYNC`. Supported from v2.5.8 and v3.1.0 onwards. |
+
+> **CAUTION**
+>
+> When refreshing materialized views created based on the external catalogs, StarRocks refreshes all partitions in the materialized views.
+
+## Examples
+
+Example 1: Manually refresh a specific materialized view via an asynchronous call.
+
+```Plain
+REFRESH MATERIALIZED VIEW lo_mv1;
+
+REFRESH MATERIALIZED VIEW lo_mv1 WITH ASYNC MODE;
+```
+
+Example 2: Manually refresh certain partitions of a specific materialized view.
+
+```Plain
+REFRESH MATERIALIZED VIEW lo_mv1 
+PARTITION START ("2020-02-01") END ("2020-03-01");
+```
+
+Example 3: Forcibly refresh certain partitions of a specific materialized view.
+
+```Plain
+REFRESH MATERIALIZED VIEW lo_mv1
+PARTITION START ("2020-02-01") END ("2020-03-01") FORCE;
+```
+
+Example 4: Manually refresh a materialized view via a synchronous call.
+
+```Plain
+REFRESH MATERIALIZED VIEW lo_mv1 WITH SYNC MODE;
+```
diff --git a/docs/en/sql-reference/sql-statements/materialized_view/SHOW_ALTER_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/materialized_view/SHOW_ALTER_MATERIALIZED_VIEW.md
new file mode 100644
index 00000000000000..fccef6cd2ec0c7
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/materialized_view/SHOW_ALTER_MATERIALIZED_VIEW.md
@@ -0,0 +1,81 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW ALTER MATERIALIZED VIEW
+
+## Description
+
+Shows the building status of synchronous materialized views.
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```SQL
+SHOW ALTER MATERIALIZED VIEW [ { FROM | IN } db_name]
+```
+
+Parameters in brackets [] is optional.
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                              |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| db_name       | no           | The name of the database to which the materialized view resides. If this parameter is not specified, the current database is used by default. |
+
+## Returns
+
+| **Return**      | **Description**                                  |
+| --------------- | ------------------------------------------------ |
+| JobId           | The ID of refresh job.                           |
+| TableName       | The name of the table.                           |
+| CreateTime      | The time when refresh job is created.            |
+| FinishedTime    | The time when refresh job is finished.           |
+| BaseIndexName   | The name of the base table.                      |
+| RollupIndexName | The name of the materialized view.               |
+| RollupId        | The ID of the materialized view rollup.          |
+| TransactionId   | The ID of transaction that waits to be executed. |
+| State           | The state of the job.                            |
+| Msg             | Error message.                                   |
+| Progress        | Progress of the refresh job.                     |
+| Timeout         | Timeout for the refresh job.                     |
+
+## Examples
+
+Example 1: building status of synchronous materialized views
+
+```Plain
+MySQL > SHOW ALTER MATERIALIZED VIEW\G
+*************************** 1. row ***************************
+          JobId: 475991
+      TableName: lineorder
+     CreateTime: 2022-08-24 19:46:53
+   FinishedTime: 2022-08-24 19:47:15
+  BaseIndexName: lineorder
+RollupIndexName: lo_mv_sync_1
+       RollupId: 475992
+  TransactionId: 33067
+          State: FINISHED
+            Msg: 
+       Progress: NULL
+        Timeout: 86400
+*************************** 2. row ***************************
+          JobId: 477337
+      TableName: lineorder
+     CreateTime: 2022-08-24 19:47:25
+   FinishedTime: 2022-08-24 19:47:45
+  BaseIndexName: lineorder
+RollupIndexName: lo_mv_sync_2
+       RollupId: 477338
+  TransactionId: 33068
+          State: FINISHED
+            Msg: 
+       Progress: NULL
+        Timeout: 86400
+2 rows in set (0.00 sec)
+```
diff --git a/docs/en/sql-reference/sql-statements/materialized_view/SHOW_CREATE_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/materialized_view/SHOW_CREATE_MATERIALIZED_VIEW.md
new file mode 100644
index 00000000000000..c617de316cc036
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/materialized_view/SHOW_CREATE_MATERIALIZED_VIEW.md
@@ -0,0 +1,56 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW CREATE MATERIALIZED VIEW
+
+## Description
+
+Shows the definition of a specific asynchronous materialized view.
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```SQL
+SHOW CREATE MATERIALIZED VIEW [database.]<mv_name>
+```
+
+Parameters in brackets [] is optional.
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                            |
+| ------------- | ------------ | ------------------------------------------ |
+| mv_name       | yes          | The name of the materialized view to show. |
+
+## Returns
+
+| **Return**               | **Description**                          |
+| ------------------------ | ---------------------------------------- |
+| Materialized View        | The name of the materialized view.       |
+| Create Materialized View | The definition of the materialized view. |
+
+## Examples
+
+Example 1: Show the definition of a specific materialized view
+
+```Plain
+MySQL > SHOW CREATE MATERIALIZED VIEW lo_mv1\G
+*************************** 1. row ***************************
+       Materialized View: lo_mv1
+Create Materialized View: CREATE MATERIALIZED VIEW `lo_mv1`
+COMMENT "MATERIALIZED_VIEW"
+DISTRIBUTED BY HASH(`lo_orderkey`) 
+REFRESH ASYNC
+PROPERTIES (
+"replication_num" = "3",
+"storage_medium" = "HDD"
+)
+AS SELECT `wlc_test`.`lineorder`.`lo_orderkey` AS `lo_orderkey`, `wlc_test`.`lineorder`.`lo_custkey` AS `lo_custkey`, sum(`wlc_test`.`lineorder`.`lo_quantity`) AS `total_quantity`, sum(`wlc_test`.`lineorder`.`lo_revenue`) AS `total_revenue`, count(`wlc_test`.`lineorder`.`lo_shipmode`) AS `shipmode_count` FROM `wlc_test`.`lineorder` GROUP BY `wlc_test`.`lineorder`.`lo_orderkey`, `wlc_test`.`lineorder`.`lo_custkey` ORDER BY `wlc_test`.`lineorder`.`lo_orderkey` ASC ;
+1 row in set (0.01 sec)
+```
diff --git a/docs/en/sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md b/docs/en/sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md
new file mode 100644
index 00000000000000..ce495dc7c0c5c3
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md
@@ -0,0 +1,170 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW MATERIALIZED VIEWS
+
+## Description
+
+Shows all or one specific asynchronous materialized view.
+
+Since v3.0, the name of this statement is changed from SHOW MATERIALIZED VIEW to SHOW MATERIALIZED VIEWS.
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```SQL
+SHOW MATERIALIZED VIEWS
+[FROM db_name]
+[
+WHERE NAME { = "mv_name" | LIKE "mv_name_matcher"}
+]
+```
+
+:::note
+
+Since v3.3, `SHOW MATERIALIZED VIEWS` command will track the state of all task_runs if a refresh task consists of multiple partitions/task_runs to refresh. Only when all task_runs are success, `last_refresh_state` will return `SUCCESS`.
+
+:::
+
+## Parameters
+
+| **Parameter**   | **Required** | **Description**                                              |
+| --------------- | ------------ | ------------------------------------------------------------ |
+| db_name         | no           | The name of the database to which the materialized view resides. If this parameter is not specified, the current database is used by default. |
+| mv_name         | no           | The name of the materialized view to show.                   |
+| mv_name_matcher | no           | The matcher used to filter materialized views.               |
+
+## Returns
+
+| **Return**                 | **Description**                                              |
+| -------------------------- | ------------------------------------------------------------ |
+| id                         | The ID of the materialized view.                             |
+| database_name              | The name of the database in which the materialized view resides. |
+| name                       | The name of the materialized view.                           |
+| refresh_type               | The refresh type of the materialized view, including ROLLUP, MANUAL, ASYNC, and INCREMENTAL. |
+| is_active                  | Whether the materialized view state is active. Valid Value: `true` and `false`. |
+| partition_type             | The partition type of the materialized view, including RANGE and UNPARTITIONED.                |
+| task_id                    | ID of the materialized view refresh task.                  |
+| task_name                  | Name of the materialized view refresh task.                |
+| last_refresh_start_time    | The start time of the last refresh of the materialized view. |
+| last_refresh_finished_time | The end time of the last refresh of the materialized view.   |
+| last_refresh_duration      | The time taken by the last refresh. Unit: seconds.           |
+| last_refresh_state         | The status of the last refresh, including PENDING, RUNNING, FAILED, and SUCCESS. |
+| last_refresh_force_refresh | Whether the last refresh is a FORCE refresh.                 |
+| last_refresh_start_partition | The start partition of the last refresh in the materialized view. |
+| last_refresh_end_partition | The end partition of the last refresh in the materialized view. |
+| last_refresh_base_refresh_partitions | The base table partitions that were refreshed in the last refresh. |
+| last_refresh_mv_refresh_partitions | The materialized view partitions that were refreshed in the last refresh. |
+| last_refresh_error_code    | The error code for the last failed refresh of the materialized view (if the materialized view state is not active). |
+| last_refresh_error_message | The reason why the last refresh failed (if the materialized view state is not active). |
+| rows                       | The number of data rows in the materialized view.            |
+| text                       | The statement used to create the materialized view.          |
+
+## Examples
+
+The following examples is based on this business scenario:
+
+```Plain
+-- Create Table: customer
+CREATE TABLE customer ( C_CUSTKEY     INTEGER NOT NULL,
+                        C_NAME        VARCHAR(25) NOT NULL,
+                        C_ADDRESS     VARCHAR(40) NOT NULL,
+                        C_NATIONKEY   INTEGER NOT NULL,
+                        C_PHONE       CHAR(15) NOT NULL,
+                        C_ACCTBAL     double   NOT NULL,
+                        C_MKTSEGMENT  CHAR(10) NOT NULL,
+                        C_COMMENT     VARCHAR(117) NOT NULL,
+                        PAD char(1) NOT NULL)
+    ENGINE=OLAP
+DUPLICATE KEY(`c_custkey`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`c_custkey`)
+PROPERTIES (
+"replication_num" = "3",
+"storage_format" = "DEFAULT"
+);
+
+-- Create MV: customer_mv
+CREATE MATERIALIZED VIEW customer_mv
+DISTRIBUTED BY HASH(c_custkey)
+REFRESH MANUAL
+PROPERTIES (
+    "replication_num" = "3"
+)
+AS SELECT
+              c_custkey, c_phone, c_acctbal, count(1) as c_count, sum(c_acctbal) as c_sum
+   FROM
+              customer
+   GROUP BY c_custkey, c_phone, c_acctbal;
+
+-- Refresh the MV
+REFRESH MATERIALIZED VIEW customer_mv;
+```
+
+Example 1: Show a specific materialized view.
+
+```Plain
+mysql> SHOW MATERIALIZED VIEWS WHERE NAME='customer_mv'\G
+*************************** 1. row ***************************
+                        id: 10142
+                      name: customer_mv
+             database_name: test
+              refresh_type: MANUAL
+                 is_active: true
+   last_refresh_start_time: 2023-02-17 10:27:33
+last_refresh_finished_time: 2023-02-17 10:27:33
+     last_refresh_duration: 0
+        last_refresh_state: SUCCESS
+             inactive_code: 0
+           inactive_reason:
+                      text: CREATE MATERIALIZED VIEW `customer_mv`
+COMMENT "MATERIALIZED_VIEW"
+DISTRIBUTED BY HASH(`c_custkey`)
+REFRESH MANUAL
+PROPERTIES (
+"replication_num" = "3",
+"storage_medium" = "HDD"
+)
+AS SELECT `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`, count(1) AS `c_count`, sum(`customer`.`c_acctbal`) AS `c_sum`
+FROM `test`.`customer`
+GROUP BY `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`;
+                      rows: 0
+1 row in set (0.11 sec)
+```
+
+Example 2: Show materialized views by matching the name.
+
+```Plain
+mysql> SHOW MATERIALIZED VIEWS WHERE NAME LIKE 'customer_mv'\G
+*************************** 1. row ***************************
+                        id: 10142
+                      name: customer_mv
+             database_name: test
+              refresh_type: MANUAL
+                 is_active: true
+   last_refresh_start_time: 2023-02-17 10:27:33
+last_refresh_finished_time: 2023-02-17 10:27:33
+     last_refresh_duration: 0
+        last_refresh_state: SUCCESS
+             inactive_code: 0
+           inactive_reason:
+                      text: CREATE MATERIALIZED VIEW `customer_mv`
+COMMENT "MATERIALIZED_VIEW"
+DISTRIBUTED BY HASH(`c_custkey`)
+REFRESH MANUAL
+PROPERTIES (
+"replication_num" = "3",
+"storage_medium" = "HDD"
+)
+AS SELECT `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`, count(1) AS `c_count`, sum(`customer`.`c_acctbal`) AS `c_sum`
+FROM `test`.`customer`
+GROUP BY `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`;
+                      rows: 0
+1 row in set (0.12 sec)
+```
diff --git a/docs/en/sql-reference/sql-statements/materialized_view/_category_.yml b/docs/en/sql-reference/sql-statements/materialized_view/_category_.yml
new file mode 100644
index 00000000000000..0d1bae9518ed0a
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/materialized_view/_category_.yml
@@ -0,0 +1,6 @@
+position: 100 # float position is supported
+label: 'Materialized View'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-statements/prepared_statement.md b/docs/en/sql-reference/sql-statements/prepared_statement.md
index 9d962eeb7afed5..bf90a5c78f49bc 100644
--- a/docs/en/sql-reference/sql-statements/prepared_statement.md
+++ b/docs/en/sql-reference/sql-statements/prepared_statement.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Prepared statements
@@ -71,7 +71,7 @@ SET @var_name = expr [, ...];
 SET @id1 = 1, @id2 = 2;
 ```
 
-For more information, see [user-defined variables](../../reference/user_defined_variables.md).
+For more information, see [user-defined variables](../user_defined_variables.md).
 
 ### EXECUTE
 
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md
new file mode 100644
index 00000000000000..92914e852169bb
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md
@@ -0,0 +1,1239 @@
+---
+displayed_sidebar: docs
+---
+
+# ALTER TABLE
+
+## Description
+
+Modifies an existing table, including:
+
+- [Rename table, partition, index, or column](#rename)
+- [Modify table comment](#alter-table-comment-from-v31)
+- [Modify partitions (add/delete partitions and modify partition attributes)](#modify-partition)
+- [Modify the bucketing method and number of buckets](#modify-the-bucketing-method-and-number-of-buckets-from-v32)
+- [Modify columns (add/delete columns and change the order of columns)](#modify-columns-adddelete-columns-change-the-order-of-columns)
+- [Create/delete rollup index](#modify-rollup-index)
+- [Modify bitmap index](#modify-bitmap-indexes)
+- [Modify table properties](#modify-table-properties)
+- [Atomic swap](#swap)
+- [Manual data version compaction](#manual-compaction-from-31)
+
+:::tip
+This operation requires the ALTER privilege on the destination table.
+:::
+
+## Syntax
+
+```SQL
+ALTER TABLE [<db_name>.]<tbl_name>
+alter_clause1[, alter_clause2, ...]
+```
+
+`alter_clause` can held the following operations: rename, comment, partition, bucket, column, rollup index, bitmap index, table property, swap, and compaction.
+
+- rename: renames a table, rollup index, partition, or column (supported from **v3.3.2 onwards**).
+- comment: modifies the table comment (supported from **v3.1 onwards**).
+- partition: modifies partition properties, drops a partition, or adds a partition.
+- bucket: modifies the bucketing method and number of buckets.
+- column: adds, drops, or reorders columns, or modifies column type.
+- rollup index: creates or drops a rollup index.
+- bitmap index: modifies index (only Bitmap index can be modified).
+- swap: atomic exchange of two tables.
+- compaction: performs manual compaction to merge versions of loaded data (supported from **v3.1 onwards**).
+
+## Limits and usage notes
+
+- Operations on partition, column, and rollup index cannot be performed in one ALTER TABLE statement.
+- Column comments cannot be modified.
+- One table can have only one ongoing schema change operation at a time. You cannot run two schema change commands on a table at the same time.
+- Operations on bucket, column and rollup index are asynchronous operations. A success message is return immediately after the task is submitted. You can run the [SHOW ALTER TABLE](SHOW_ALTER.md) command to check the progress, and run the [CANCEL ALTER TABLE](CANCEL_ALTER_TABLE.md) command to cancel the operation.
+- Operations on rename, comment, partition, bitmap index and swap are synchronous operations, and a command return indicates that the execution is finished.
+
+### Rename
+
+Rename supports modification of table name, rollup index, and partition name.
+
+#### Rename a table
+
+```sql
+ALTER TABLE <tbl_name> RENAME <new_tbl_name>
+```
+
+#### Rename a rollup index
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+RENAME ROLLUP <old_rollup_name> <new_rollup_name>
+```
+
+#### Rename a partition
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+RENAME PARTITION <old_partition_name> <new_partition_name>
+```
+
+#### Rename a column
+
+From v3.3.2 onwards, StarRocks supports renaming columns.
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+RENAME COLUMN <old_col_name> [ TO ] <new_col_name>
+```
+
+:::note
+
+- After renaming a column from A to B, adding a new column named A is not supported.
+- Materialized views built on a renamed column will not take effect. You must rebuild them upon the column with the new name.
+
+:::
+
+### Alter table comment (from v3.1)
+
+Syntax:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name> COMMENT = "<new table comment>";
+```
+
+:::tip
+Currently, column comments cannot be modified.
+:::
+
+### Modify partition
+
+#### ADD PARTITION(S)
+
+You can choose to add range partitions or list partitions.
+
+Syntax：
+
+- Range partitions
+
+    ```SQL
+    ALTER TABLE
+        ADD { single_range_partition | multi_range_partitions } [distribution_desc] ["key"="value"];
+
+    single_range_partition ::=
+        PARTITION [IF NOT EXISTS] <partition_name> VALUES partition_key_desc
+
+    partition_key_desc ::=
+        { LESS THAN { MAXVALUE | value_list }
+        | [ value_list , value_list ) } -- Note that [ represents a left-closed interval.
+
+    value_list ::=
+        ( <value> [, ...] )
+
+    multi_range_partitions ::=
+        { PARTITIONS START ("<start_date_value>") END ("<end_date_value>") EVERY ( INTERVAL <N> <time_unit> )
+        | PARTITIONS START ("<start_integer_value>") END ("<end_integer_value>") EVERY ( <granularity> ) } -- The partition column values still need to be enclosed in double quotes even if the partition column values specified by START and END are integers. However, the interval values in the EVERY clause do not need to be enclosed in double quotes.
+    ```
+
+- List partitions
+
+    ```SQL
+    ALTER TABLE
+        ADD PARTITION <partition_name> VALUES IN (value_list) [distribution_desc] ["key"="value"];
+
+    value_list ::=
+        value_item [, ...]
+
+    value_item ::=
+        { <value> | ( <value> [, ...] ) }
+    ```
+
+Parameters:
+
+- Partition-related parameters:
+
+  - For range partitions, you can add a single range partition (`single_range_partition`) or multiple range partitions in batch (`multi_range_partitions`).
+  - For list partitions, you can only add a single list partition.
+
+- `distribution_desc`:
+
+   You can set the number of buckets for the new partition separately, but you cannot set the bucketing method separately.
+
+- `"key"="value"`:
+
+   You can set properties for the new partition. For details, see [CREATE TABLE](CREATE_TABLE.md#properties).
+
+Examples:
+
+- Range partitions
+
+  - If the partition column is specified as `event_day` at table creation, for example `PARTITION BY RANGE(event_day)`, and a new partition needs to be added after table creation, you can execute:
+
+    ```sql
+    ALTER TABLE site_access ADD PARTITION p4 VALUES LESS THAN ("2020-04-30");
+    ```
+
+  - If the partition column is specified as `datekey` at table creation, for example `PARTITION BY RANGE (datekey)`, and multiple partitions need to be added in batch after table creation, you can execute:
+
+    ```sql
+    ALTER TABLE site_access
+        ADD PARTITIONS START ("2021-01-05") END ("2021-01-10") EVERY (INTERVAL 1 DAY);
+    ```
+
+- List partitions
+
+  - If a single partition column is specified at table creation, for example `PARTITION BY LIST (city)`, and a new partition needs to be added after table creation, you can execute:
+
+    ```sql
+    ALTER TABLE t_recharge_detail2
+    ADD PARTITION pCalifornia VALUES IN ("Los Angeles","San Francisco","San Diego");
+    ```
+
+  - If multiple partition columns are specified at table creation, for example `PARTITION BY LIST (dt,city)`, and a new partition needs to be added after table creation, you can execute:
+
+    ```sql
+    ALTER TABLE t_recharge_detail4 
+    ADD PARTITION p202204_California VALUES IN
+    (
+        ("2022-04-01", "Los Angeles"),
+        ("2022-04-01", "San Francisco"),
+        ("2022-04-02", "Los Angeles"),
+        ("2022-04-02", "San Francisco")
+    );
+    ```
+
+#### DROP PARTITION(S)
+
+- Drop a single partition:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+DROP PARTITION [ IF EXISTS ] <partition_name> [ FORCE ]
+```
+
+- Drop partitions in batch (Supported from v3.3.1):
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+DROP PARTITIONS [ IF EXISTS ]  { partition_name_list | multi_range_partitions } [ FORCE ]
+
+partion_name_list ::= ( <partition_name> [, ... ] )
+
+multi_range_partitions ::=
+    { START ("<start_date_value>") END ("<end_date_value>") EVERY ( INTERVAL <N> <time_unit> )
+    | START ("<start_integer_value>") END ("<end_integer_value>") EVERY ( <granularity> ) } -- The partition column values still need to be enclosed in double quotes even if the partition column values are integers. However, the interval values in the EVERY clause do not need to be enclosed in double quotes.
+```
+
+Notes for `multi_range_partitions`:
+
+- It only appiles to Range Partitioning.
+- The parameters involved is consistent with those in [ADD PARTITION(S)](#add-partitions).
+- It only supports partitions with a single Partition Key.
+
+:::note
+
+- Keep at least one partition for partitioned tables.
+- If FORCE is not specified, you can recover the dropped partitions by using the [RECOVER](../backup_restore/RECOVER.md) command within a specified period (1 day by default).
+- If FORCE is specified, the partitions will be deleted directly regardless of whether there are any unfinished operations on the partitions, and they cannot be recovered. Thus, generally, this operation is not recommended.
+
+:::
+
+#### Add a temporary partition
+
+Syntax:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name> 
+ADD TEMPORARY PARTITION [IF NOT EXISTS] <partition_name>
+partition_desc ["key"="value"]
+[DISTRIBUTED BY HASH (k1[,k2 ...]) [BUCKETS num]]
+```
+
+#### Use a temporary partition to replace the current partition
+
+Syntax:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+REPLACE PARTITION <partition_name>
+partition_desc ["key"="value"]
+WITH TEMPORARY PARTITION
+partition_desc ["key"="value"]
+[PROPERTIES ("key"="value", ...)]
+```
+
+#### Drop a temporary partition
+
+Syntax:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+DROP TEMPORARY PARTITION <partition_name>
+```
+
+#### Modify partition properties
+
+**Syntax**
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+MODIFY PARTITION { <partition_name> | ( <partition1_name> [, <partition2_name> ...] ) | (*) }
+SET ("key" = "value", ...);
+```
+
+**Usages**
+
+- The following properties of a partition can be modified:
+
+  - storage_medium
+  - storage_cooldown_ttl or storage_cooldown_time
+  - replication_num
+
+- For the table that has only one partition, the partition name is the same as the table name. If the table is divided into multiple partitions, you can use `(*)`to modify the properties of all partitions, which is more convenient.
+
+- Execute `SHOW PARTITIONS FROM <tbl_name>` to view the partition properties after modification.
+
+### Modify the bucketing method and number of buckets (from v3.2)
+
+Syntax:
+
+```SQL
+ALTER TABLE [<db_name>.]<table_name>
+[ partition_names ]
+[ distribution_desc ]
+
+partition_names ::= 
+    (PARTITION | PARTITIONS) ( <partition_name> [, <partition_name> ...] )
+
+distribution_desc ::=
+    DISTRIBUTED BY RANDOM [ BUCKETS <num> ] |
+    DISTRIBUTED BY HASH ( <column_name> [, <column_name> ...] ) [ BUCKETS <num> ]
+```
+
+Example:
+
+For example, the original table is a Duplicate Key table where hash bucketing is used and the number of buckets is automatically set by StarRocks.
+
+```SQL
+CREATE TABLE IF NOT EXISTS details (
+    event_time DATETIME NOT NULL COMMENT "datetime of event",
+    event_type INT NOT NULL COMMENT "type of event",
+    user_id INT COMMENT "id of user",
+    device_code INT COMMENT "device code",
+    channel INT COMMENT ""
+)
+DUPLICATE KEY(event_time, event_type)
+PARTITION BY date_trunc('day', event_time)
+DISTRIBUTED BY HASH(user_id);
+
+-- Insert data of several days
+INSERT INTO details (event_time, event_type, user_id, device_code, channel) VALUES
+-- Data of November 26th
+('2023-11-26 08:00:00', 1, 101, 12345, 2),
+('2023-11-26 09:15:00', 2, 102, 54321, 3),
+('2023-11-26 10:30:00', 1, 103, 98765, 1),
+-- Data of November 27th
+('2023-11-27 08:30:00', 1, 104, 11111, 2),
+('2023-11-27 09:45:00', 2, 105, 22222, 3),
+('2023-11-27 11:00:00', 1, 106, 33333, 1),
+-- Data of November 28th
+('2023-11-28 08:00:00', 1, 107, 44444, 2),
+('2023-11-28 09:15:00', 2, 108, 55555, 3),
+('2023-11-28 10:30:00', 1, 109, 66666, 1);
+```
+
+#### Modify the bucketing method only
+
+> **NOTICE**
+>
+> - The modification is applied to all partitions in the table and cannot be applied to specific partitions only.
+> - Although only the bucketing method needs to be modified, the number of buckets still needs to be specified in the command using `BUCKETS <num>`. If `BUCKETS <num>` is not specified, it means that the number of buckets is automatically determined by StarRocks.
+
+- The bucketing method is modified to random bucketing from hash bucketing and the number of buckets remains automatically set by StarRocks.
+
+  ```SQL
+  ALTER TABLE details DISTRIBUTED BY RANDOM;
+  ```
+
+- The keys for hash bucketing are modified to `user_id, event_time` from `event_time, event_type`. And the number of buckets remains automatically set by StarRocks.
+
+  ```SQL
+  ALTER TABLE details DISTRIBUTED BY HASH(user_id, event_time);
+  ```
+
+#### Modify the number of buckets only
+
+> **NOTICE**
+>
+> Although only the number of buckets needs to be modified, the bucketing method still needs to be specified in the command, for example, `HASH(user_id)`.
+
+- Modify the number of buckets for all partitions to 10 from being automatically set by StarRocks.
+
+  ```SQL
+  ALTER TABLE details DISTRIBUTED BY HASH(user_id) BUCKETS 10;
+  ```
+
+- Modify the number of buckets for specified partitions to 15 from being automatically set by StarRocks.
+
+  ```SQL
+  ALTER TABLE details PARTITIONS (p20231127, p20231128) DISTRIBUTED BY HASH(user_id) BUCKETS 15 ;
+  ```
+
+  > **NOTE**
+  >
+  > Partition names can be viewed by executing `SHOW PARTITIONS FROM <table_name>;`.
+
+#### Modify both the bucketing method and the number of buckets
+
+> **NOTICE**
+>
+> The modification is applied to all partitions in the table and cannot be applied to specific partitions only.
+
+- Modify the bucketing method from hash bucketing to random bucketing, and change the number of buckets to 10 from being automatically set by StarRocks.
+
+   ```SQL
+   ALTER TABLE details DISTRIBUTED BY RANDOM BUCKETS 10;
+   ```
+
+- Modify the key for hash bucketing, and change the number of buckets to 10 from being automatically set by StarRocks. The key used for hashing bucketing is modified to `user_id, event_time` from the original `event_time, event_type`. The number of buckets is modified to 10 from automatically set by StarRocks.
+
+  ```SQL
+  ALTER TABLE details DISTRIBUTED BY HASH(user_id, event_time) BUCKETS 10;
+  ``
+
+### Modify columns (add/delete columns, change the order of columns)
+
+#### Add a column to the specified location of the specified index
+
+Syntax:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+ADD COLUMN column_name column_type [KEY | agg_type] [DEFAULT "default_value"]
+[AFTER column_name|FIRST]
+[TO rollup_index_name]
+[PROPERTIES ("key"="value", ...)]
+```
+
+Note:
+
+1. If you add a value column to an Aggregate table, you need to specify agg_type.
+2. If you add a key column to a non-Aggregate table (such as a Duplicate Key table), you need to specify the KEY keyword.
+3. You cannot add a column that already exists in the base index to the rollup index. (You can recreate a rollup index if needed.)
+
+#### Add multiple columns to specified index
+
+Syntax:
+
+- Add multiple columns
+
+  ```sql
+  ALTER TABLE [<db_name>.]<tbl_name>
+  ADD COLUMN (column_name1 column_type [KEY | agg_type] DEFAULT "default_value", ...)
+  [TO rollup_index_name]
+  [PROPERTIES ("key"="value", ...)]
+  ```
+
+- Add multiple columns and use AFTER to specify locations of the added columns
+
+  ```sql
+  ALTER TABLE [<db_name>.]<tbl_name>
+  ADD COLUMN column_name1 column_type [KEY | agg_type] DEFAULT "default_value" AFTER column_name,
+  ADD COLUMN column_name2 column_type [KEY | agg_type] DEFAULT "default_value" AFTER column_name
+  [, ...]
+  [TO rollup_index_name]
+  [PROPERTIES ("key"="value", ...)]
+  ```
+
+Note:
+
+1. If you add a value column to an Aggregate table, you need to specify `agg_type`.
+
+2. If you add a key column to a non-Aggregate table, you need to specify the KEY keyword.
+
+3. You cannot add a column that already exists in the base index to the rollup index. (You can create another rollup index if needed.)
+
+#### Add a generated column (from v3.1)
+
+Syntax:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+ADD COLUMN col_name data_type [NULL] AS generation_expr [COMMENT 'string']
+```
+
+You can add a generated column and specify its expression. [The generated column](../generated_columns.md) can be used to precompute and store the results of expressions, which significantly accelerates queries with the same complex expressions. Since v3.1, StarRocks supports generated columns.
+
+#### Drop a column from specified index
+
+Syntax:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+DROP COLUMN column_name
+[FROM rollup_index_name];
+```
+
+Note:
+
+1. You cannot drop partition column.
+2. If the column is dropped from the base index, it will also be dropped if it is included in the rollup index.
+
+#### Modify the column type and column position of specified index
+
+Syntax:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+MODIFY COLUMN column_name column_type [KEY | agg_type] [NULL | NOT NULL] [DEFAULT "default_value"]
+[AFTER column_name|FIRST]
+[FROM rollup_index_name]
+[PROPERTIES ("key"="value", ...)]
+```
+
+Note:
+
+1. If you modify the value column in aggregation models, you need to specify agg_type.
+2. If you modify the key column in non-aggregation models, you need to specify the KEY keyword.
+3. Only the type of column can be modified. The other properties of the column remain as they are currently. (i.e. other properties need to be explicitly written in the statement according to the original property, see example 8 in the [column](#column) part).
+4. The partition column cannot be modified.
+5. The following types of conversions are currently supported (accuracy loss is guaranteed by the user).
+
+   - Convert TINYINT/SMALLINT/INT/BIGINT to TINYINT/SMALLINT/INT/BIGINT/DOUBLE.
+   - Convert TINYINT/SMALLINT/INT/BIGINT/LARGEINT/FLOAT/DOUBLE/DECIMAL to VARCHAR. VARCHAR supports modification of maximum length.
+   - Convert VARCHAR to TINYINT/SMALLINT/INT/BIGINT/LARGEINT/FLOAT/DOUBLE.
+   - Convert VARCHAR to DATE (currently support six formats: "%Y-%m-%d", "%y-%m-%d", "%Y%m%d", "%y%m%d", "%Y/%m/%d, "%y/%m/%d")
+   - Convert DATETIME to DATE(only year-month-day information is retained, i.e.  `2019-12-09 21:47:05` `<-->` `2019-12-09`)
+   - Convert DATE to DATETIME (set hour, minute, second to zero, For example: `2019-12-09` `<-->` `2019-12-09 00:00:00`)
+   - Convert FLOAT to DOUBLE
+   - Convert INT to DATE (If the INT data fails to convert, the original data remains the same)
+
+6. Conversion from NULL to NOT NULL is not supported.
+
+#### Reorder the columns of specified index
+
+Syntax:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+ORDER BY (column_name1, column_name2, ...)
+[FROM rollup_index_name]
+[PROPERTIES ("key"="value", ...)]
+```
+
+Note:
+
+- All columns in the index must be written.
+- The value column is listed after the key column.
+
+#### Modify the sort key
+
+Since v3.0, the sort keys for the Primary Key tables can be modified. v3.3 extends this support to Duplicate Key tables, Aggregate tables, and Unique Key tables.
+
+The sort keys in Duplicate Key tables and Primary Key tables can be combination of any sort columns. The sort keys in Aggregate tables and Unique Key tables must include all key columns, but the order of the columns does not need to be same as the key columns.
+
+Syntax:
+
+```SQL
+ALTER TABLE [<db_name>.]<table_name>
+[ order_desc ]
+
+order_desc ::=
+    ORDER BY <column_name> [, <column_name> ...]
+```
+
+Example: modify the sort keys in Primary Key tables.
+
+For example, the original table is a Primary Key table where the sort key and the primary key are coupled, which is `dt, order_id`.
+
+```SQL
+create table orders (
+    dt date NOT NULL,
+    order_id bigint NOT NULL,
+    user_id int NOT NULL,
+    merchant_id int NOT NULL,
+    good_id int NOT NULL,
+    good_name string NOT NULL,
+    price int NOT NULL,
+    cnt int NOT NULL,
+    revenue int NOT NULL,
+    state tinyint NOT NULL
+) PRIMARY KEY (dt, order_id)
+PARTITION BY date_trunc('day', dt)
+DISTRIBUTED BY HASH(order_id);
+```
+
+Decouple the sort key from the primary key, and modify the sort key to `dt, revenue, state`.
+
+```SQL
+ALTER TABLE orders ORDER BY (dt, revenue, state);
+```
+
+#### Modify a STRUCT column to add or drop a field
+
+From v3.2.10 and v3.3.2 onwards, StarRocks supports modifying a STRUCT column to add or drop a field, which can be nested or within an ARRAY type.
+
+Syntax:
+
+```sql
+-- Add a field
+ALTER TABLE [<db_name>.]<tbl_name>
+MODIFY COLUMN <column_name> ADD FIELD <field_name> <field_type> [AFTER <prior_field_name> |FIRST]
+
+-- Drop a field
+ALTER TABLE [<db_name>.]<tbl_name>
+MODIFY COLUMN <column_name> DROP FIELD <field_name>
+```
+
+Parameters:
+
+- `field_name`: The name of the field to be added or removed. This can be a simple field name, indicating a top-dimension field, for example, `new_field_name`, or a Column Access Path, representing a nested field, for example, `lv1_k1.lv2_k2.new_field_name`.
+- `prior_field_name`: The field preceding the newly added field. Used in conjunction with the AFTER keyword to specify the order of the new field. You do not need to specify this parameter if the FIRST keyword is used, indicating the new field should be the first field. The dimension of `prior_field_name` is determined by `field_name` and does not need to be specified explicitly.
+
+For more usage instructions, see [Example - Column -14](#column).
+
+:::note
+
+- Currently, this feature is only supported in shared-nothing clusters.
+- The table must have the `fast_schema_evolution` property enabled.
+- Adding or dropping fields in the STRUCT type within a MAP type is not supported.
+- Newly added fields cannot have default values or attributes such as Nullable specified. They default to being Nullable, with a default value of null.
+- After this feature is used, downgrading the cluster directly to a version that does not support this feature is not allowed.
+
+:::
+
+
+### Modify rollup index
+
+#### Create a rollup index
+
+Syntax:
+
+```SQL
+ALTER TABLE [<db_name>.]<tbl_name> 
+ADD ROLLUP rollup_name (column_name1, column_name2, ...)
+[FROM from_index_name]
+[PROPERTIES ("key"="value", ...)]
+```
+
+PROPERTIES: Support setting timeout time and the default timeout time is one day.
+
+Example:
+
+```SQL
+ALTER TABLE [<db_name>.]<tbl_name> 
+ADD ROLLUP r1(col1,col2) from r0;
+```
+
+#### Create rollup indexes in batches
+
+Syntax:
+
+```SQL
+ALTER TABLE [<db_name>.]<tbl_name>
+ADD ROLLUP [rollup_name (column_name1, column_name2, ...)
+[FROM from_index_name]
+[PROPERTIES ("key"="value", ...)],...];
+```
+
+Example:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+ADD ROLLUP r1(col1,col2) from r0, r2(col3,col4) from r0;
+```
+
+Note:
+
+1. If from_index_name is not specified, then create from base index by default.
+2. The columns in the rollup table must be existing columns in from_index.
+3. In properties, user can specify the storage format. See CREATE TABLE for details.
+
+#### Drop a rollup index
+
+Syntax:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+DROP ROLLUP rollup_name [PROPERTIES ("key"="value", ...)];
+```
+
+Example:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name> DROP ROLLUP r1;
+```
+
+#### Batch drop rollup indexes
+
+Syntax:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+DROP ROLLUP [rollup_name [PROPERTIES ("key"="value", ...)],...];
+```
+
+Example:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name> DROP ROLLUP r1, r2;
+```
+
+Note: You cannot drop the base index.
+
+### Modify bitmap indexes
+
+Bitmap index supports the following modifications:
+
+#### Create a bitmap index
+
+Syntax:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+ADD INDEX index_name (column [, ...],) [USING BITMAP] [COMMENT 'balabala'];
+```
+
+Note:
+
+```plain text
+1. Bitmap index is only supported for the current version.
+2. A BITMAP index is created only in a single column.
+```
+
+#### Drop an bitmap index
+
+Syntax:
+
+```sql
+DROP INDEX index_name;
+```
+
+### Modify table properties
+
+Syntax:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+SET ("key" = "value",...)
+```
+
+Currently, StarRocks supports modifying the following table properties:
+
+- `replication_num`
+- `default.replication_num`
+- `storage_cooldown_ttl`
+- `storage_cooldown_time`
+- Dynamic partitioning related properties
+- `enable_persistent_index`
+- `bloom_filter_columns`
+- `colocate_with`
+- `bucket_size` (supported since 3.2)
+
+Note:
+You can also modify the properties by merging into the above operation on column. See the [following examples](#examples).
+
+### Swap
+
+Swap supports atomic exchange of two tables.
+
+Syntax:
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+SWAP WITH <tbl_name>;
+```
+
+### Manual compaction (from 3.1)
+
+StarRocks uses a compaction mechanism to merge different versions of loaded data. This feature can combine small files into large files, which effectively improves query performance.
+
+Before v3.1, compaction is performed in two ways:
+
+- Automatic compaction by system: Compaction is performed at the BE level in the background. Users cannot specify database or table for compaction.
+- Users can perform compaction by calling an HTTP interface.
+
+Starting from v3.1, StarRocks offers a SQL interface for users to manually perform compaction by running SQL commands. They can choose a specific table or partition for compaction. This provides more flexibility and control over the compaction process.
+
+Shared-data clusters support this feature from v3.3.0 onwards.
+
+Syntax:
+
+```SQL
+ALTER TABLE <tbl_name> [ BASE | CUMULATIVE ] COMPACT [ <partition_name> | ( <partition1_name> [, <partition2_name> ...] ) ]
+```
+
+That is:
+
+```SQL
+-- Perform compaction on the entire table.
+ALTER TABLE <tbl_name> COMPACT
+
+-- Perform compaction on a single partition.
+ALTER TABLE <tbl_name> COMPACT <partition_name>
+
+-- Perform compaction on multiple partitions.
+ALTER TABLE <tbl_name> COMPACT (<partition1_name>[,<partition2_name>,...])
+
+-- Perform cumulative compaction.
+ALTER TABLE <tbl_name> CUMULATIVE COMPACT (<partition1_name>[,<partition2_name>,...])
+
+-- Perform base compaction.
+ALTER TABLE <tbl_name> BASE COMPACT (<partition1_name>[,<partition2_name>,...])
+```
+
+The `be_compactions` table in the `information_schema` database records compaction results. You can run `SELECT * FROM information_schema.be_compactions;` to query data versions after compaction.
+
+## Examples
+
+### Table
+
+1. Modify the default number of replicas of the table, which is used as the default number of replicas for newly added partitions.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    SET ("default.replication_num" = "2");
+    ```
+
+2. Modify the actual number of replicas of a single-partition table.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    SET ("replication_num" = "3");
+    ```
+
+3. Modify data writing and replication mode among replicas.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    SET ("replicated_storage" = "false");
+    ```
+
+   This example sets the data writing and replication mode among replicas to "leaderless replication", which means data is written to multiple replicas at the same time without differentiating primary and secondary replicas. For more information, see the `replicated_storage` parameter in [CREATE TABLE](CREATE_TABLE.md).
+
+### Partition
+
+1. Add a partition and use the default bucketing mode. The existing partition is [MIN, 2013-01-01). The added partition is [2013-01-01, 2014-01-01).
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD PARTITION p1 VALUES LESS THAN ("2014-01-01");
+    ```
+
+2. Add a partition and use the new number of buckets.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD PARTITION p1 VALUES LESS THAN ("2015-01-01")
+    DISTRIBUTED BY HASH(k1);
+    ```
+
+3. Add a partition and use the new number of replicas.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD PARTITION p1 VALUES LESS THAN ("2015-01-01")
+    ("replication_num"="1");
+    ```
+
+4. Alter the number of replicas for a partition.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    MODIFY PARTITION p1 SET("replication_num"="1");
+    ```
+
+5. Batch alter the number of replicas for specified partitions.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    MODIFY PARTITION (p1, p2, p4) SET("replication_num"="1");
+    ```
+
+6. Batch alter the storage medium of all partitions.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    MODIFY PARTITION (*) SET("storage_medium"="HDD");
+    ```
+
+7. Drop a partition.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    DROP PARTITION p1;
+    ```
+
+8. Add a partition that has upper and lower boundaries.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD PARTITION p1 VALUES [("2014-01-01"), ("2014-02-01"));
+    ```
+
+### Rollup index
+
+1. Create an rollup index `example_rollup_index` based on the base index (k1,k2,k3,v1,v2). Column-based storage is used.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD ROLLUP example_rollup_index(k1, k3, v1, v2)
+    PROPERTIES("storage_type"="column");
+    ```
+
+2. Create an index `example_rollup_index2` based on `example_rollup_index(k1,k3,v1,v2)`.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD ROLLUP example_rollup_index2 (k1, v1)
+    FROM example_rollup_index;
+    ```
+
+3. Create an index `example_rollup_index3` based on the base index (k1, k2, k3, v1). The rollup timeout time is set to one hour.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD ROLLUP example_rollup_index3(k1, k3, v1)
+    PROPERTIES("storage_type"="column", "timeout" = "3600");
+    ```
+
+4. Drop an index `example_rollup_index2`.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    DROP ROLLUP example_rollup_index2;
+    ```
+
+### Column
+
+1. Add a key column `new_col` (non-aggregate column) after the `col1` column of `example_rollup_index`.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD COLUMN new_col INT KEY DEFAULT "0" AFTER col1
+    TO example_rollup_index;
+    ```
+
+2. Add a value column `new_col` (non-aggregate column) after the `col1` column of `example_rollup_index`.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD COLUMN new_col INT DEFAULT "0" AFTER col1
+    TO example_rollup_index;
+    ```
+
+3. Add a key column `new_col` (aggregate column) after the `col1` column of `example_rollup_index`.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD COLUMN new_col INT DEFAULT "0" AFTER col1
+    TO example_rollup_index;
+    ```
+
+4. Add a value column `new_col SUM` (aggregate column) after the `col1` column of `example_rollup_index`.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD COLUMN new_col INT SUM DEFAULT "0" AFTER col1
+    TO example_rollup_index;
+    ```
+
+5. Add multiple columns to `example_rollup_index` (aggregate).
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD COLUMN (col1 INT DEFAULT "1", col2 FLOAT SUM DEFAULT "2.3")
+    TO example_rollup_index;
+    ```
+
+6. Add multiple columns to `example_rollup_index` (aggregate) and specify the locations of the added columns using `AFTER`.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD COLUMN col1 INT DEFAULT "1" AFTER `k1`,
+    ADD COLUMN col2 FLOAT SUM AFTER `v2`,
+    TO example_rollup_index;
+    ```
+
+7. Drop a column from `example_rollup_index`.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    DROP COLUMN col2
+    FROM example_rollup_index;
+    ```
+
+8. Modify the column type of col1 of the base index to BIGINT and put it after `col2`.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    MODIFY COLUMN col1 BIGINT DEFAULT "1" AFTER col2;
+    ```
+
+9. Modify the maximum length of the `val1` column of the base index to 64. The original length is 32.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    MODIFY COLUMN val1 VARCHAR(64) REPLACE DEFAULT "abc";
+    ```
+
+10. Reorder the columns in `example_rollup_index`. The original column order is k1, k2, k3, v1, v2.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ORDER BY (k3,k1,k2,v2,v1)
+    FROM example_rollup_index;
+    ```
+
+11. Perform two operations (ADD COLUMN and ORDER BY) at one time.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD COLUMN v2 INT MAX DEFAULT "0" AFTER k2 TO example_rollup_index,
+    ORDER BY (k3,k1,k2,v2,v1) FROM example_rollup_index;
+    ```
+
+12. Alter the bloomfilter columns of the table.
+
+     ```sql
+     ALTER TABLE example_db.my_table
+     SET ("bloom_filter_columns"="k1,k2,k3");
+     ```
+
+     This operation can also be merged into the above column operation (note that the syntax of multiple clauses is slightly different).
+
+     ```sql
+     ALTER TABLE example_db.my_table
+     DROP COLUMN col2
+     PROPERTIES ("bloom_filter_columns"="k1,k2,k3");
+     ```
+
+13. Modify the data type of multiple columns in a single statement.
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    MODIFY COLUMN k1 VARCHAR(100) KEY NOT NULL,
+    MODIFY COLUMN v2 DOUBLE DEFAULT "1" AFTER v1;
+    ```
+
+14. Add and drop fields in STRUCT-type data.
+
+    **Prerequisites**: Create a table and insert a row of data.
+
+    ```sql
+    CREATE TABLE struct_test(
+        c0 INT,
+        c1 STRUCT<v1 INT, v2 STRUCT<v4 INT, v5 INT>, v3 INT>,
+        c2 STRUCT<v1 INT, v2 ARRAY<STRUCT<v3 INT, v4 STRUCT<v5 INT, v6 INT>>>>
+    )
+    DUPLICATE KEY(c0)
+    DISTRIBUTED BY HASH(`c0`) BUCKETS 1
+    PROPERTIES (
+        "fast_schema_evolution" = "true"
+    );
+    INSERT INTO struct_test VALUES (
+        1, 
+        ROW(1, ROW(2, 3), 4), 
+        ROW(5, [ROW(6, ROW(7, 8)), ROW(9, ROW(10, 11))])
+    );
+    ```
+
+    ```plain
+    mysql> SELECT * FROM struct_test\G
+    *************************** 1. row ***************************
+    c0: 1
+    c1: {"v1":1,"v2":{"v4":2,"v5":3},"v3":4}
+    c2: {"v1":5,"v2":[{"v3":6,"v4":{"v5":7,"v6":8}},{"v3":9,"v4":{"v5":10,"v6":11}}]}
+    ```
+
+    - Add a new field to a STRUCT-type column.
+
+    ```sql
+    ALTER TABLE struct_test MODIFY COLUMN c1 ADD FIELD v4 INT AFTER v2;
+    ```
+
+    ```plain
+    mysql> SELECT * FROM struct_test\G
+    *************************** 1. row ***************************
+    c0: 1
+    c1: {"v1":1,"v2":{"v4":2,"v5":3},"v4":null,"v3":4}
+    c2: {"v1":5,"v2":[{"v3":6,"v4":{"v5":7,"v6":8}},{"v3":9,"v4":{"v5":10,"v6":11}}]}
+    ```
+
+    - Add a new field to a nested STRUCT type.
+
+    ```sql
+    ALTER TABLE struct_test MODIFY COLUMN c1 ADD FIELD v2.v6 INT FIRST;
+    ```
+
+    ```plain
+    mysql> SELECT * FROM struct_test\G
+    *************************** 1. row ***************************
+    c0: 1
+    c1: {"v1":1,"v2":{"v6":null,"v4":2,"v5":3},"v4":null,"v3":4}
+    c2: {"v1":5,"v2":[{"v3":6,"v4":{"v5":7,"v6":8}},{"v3":9,"v4":{"v5":10,"v6":11}}]}
+    ```
+
+    - Add a new field to a STRUCT type in an array.
+
+    ```sql
+    ALTER TABLE struct_test MODIFY COLUMN c2 ADD FIELD v2.[*].v7 INT AFTER v3;
+    ```
+
+    ```plain
+    mysql> SELECT * FROM struct_test\G
+    *************************** 1. row ***************************
+    c0: 1
+    c1: {"v1":1,"v2":{"v6":null,"v4":2,"v5":3},"v4":null,"v3":4}
+    c2: {"v1":5,"v2":[{"v3":6,"v7":null,"v4":{"v5":7,"v6":8}},{"v3":9,"v7":null,"v4":{"v5":10,"v6":11}}]}
+    ```
+
+    - Drop a field from a STRUCT-type column.
+
+    ```sql
+    ALTER TABLE struct_test MODIFY COLUMN c1 DROP FIELD v3;
+    ```
+
+    ```plain
+    mysql> SELECT * FROM struct_test\G
+    *************************** 1. row ***************************
+    c0: 1
+    c1: {"v1":1,"v2":{"v6":null,"v4":2,"v5":3},"v4":null}
+    c2: {"v1":5,"v2":[{"v3":6,"v7":null,"v4":{"v5":7,"v6":8}},{"v3":9,"v7":null,"v4":{"v5":10,"v6":11}}]}
+    ```
+
+    - Drop a field from a nested STRUCT type.
+
+    ```sql
+    ALTER TABLE struct_test MODIFY COLUMN c1 DROP FIELD v2.v4;
+    ```
+
+    ```plain
+    mysql> SELECT * FROM struct_test\G
+    *************************** 1. row ***************************
+    c0: 1
+    c1: {"v1":1,"v2":{"v6":null,"v5":3},"v4":null}
+    c2: {"v1":5,"v2":[{"v3":6,"v7":null,"v4":{"v5":7,"v6":8}},{"v3":9,"v7":null,"v4":{"v5":10,"v6":11}}]}
+    ```
+
+    - Drop a field from a STRUCT type in an array.
+
+    ```sql
+    ALTER TABLE struct_test MODIFY COLUMN c2 DROP FIELD v2.[*].v3;
+    ```
+
+    ```plain
+    mysql> SELECT * FROM struct_test\G
+    *************************** 1. row ***************************
+    c0: 1
+    c1: {"v1":1,"v2":{"v6":null,"v5":3},"v4":null}
+    c2: {"v1":5,"v2":[{"v7":null,"v4":{"v5":7,"v6":8}},{"v7":null,"v4":{"v5":10,"v6":11}}]}
+    ```
+
+### Table property
+
+1. Alter the Colocate property of the table.
+
+     ```sql
+     ALTER TABLE example_db.my_table
+     SET ("colocate_with" = "t1");
+     ```
+
+2. Alter the dynamic partition property of the table.
+
+     ```sql
+     ALTER TABLE example_db.my_table
+     SET ("dynamic_partition.enable" = "false");
+     ```
+
+     If you need to add dynamic partition properties to a table with no dynamic partition properties configured, you need to specify all the dynamic partition properties.
+
+     ```sql
+     ALTER TABLE example_db.my_table
+     SET (
+         "dynamic_partition.enable" = "true",
+         "dynamic_partition.time_unit" = "DAY",
+         "dynamic_partition.end" = "3",
+         "dynamic_partition.prefix" = "p",
+         "dynamic_partition.buckets" = "32"
+         );
+     ```
+
+### Rename
+
+1. Rename `table1` to `table2`.
+
+    ```sql
+    ALTER TABLE table1 RENAME table2;
+    ```
+
+2. Rename rollup index `rollup1` of `example_table` to `rollup2`.
+
+    ```sql
+    ALTER TABLE example_table RENAME ROLLUP rollup1 rollup2;
+    ```
+
+3. Rename partition `p1` of `example_table` to `p2`.
+
+    ```sql
+    ALTER TABLE example_table RENAME PARTITION p1 p2;
+    ```
+
+### Bitmap index
+
+1. Create a bitmap index for column `siteid` in `table1`.
+
+    ```sql
+    ALTER TABLE table1
+    ADD INDEX index_1 (siteid) [USING BITMAP] COMMENT 'balabala';
+    ```
+
+2. Drop the bitmap index of column `siteid` in `table1`.
+
+    ```sql
+    ALTER TABLE table1
+    DROP INDEX index_1;
+    ```
+
+### Swap
+
+Atomic swap between `table1` and `table2`.
+
+```sql
+ALTER TABLE table1 SWAP WITH table2
+```
+
+### Manual compaction
+
+```sql
+CREATE TABLE compaction_test( 
+    event_day DATE,
+    pv BIGINT)
+DUPLICATE KEY(event_day)
+PARTITION BY date_trunc('month', event_day)
+DISTRIBUTED BY HASH(event_day) BUCKETS 8
+PROPERTIES("replication_num" = "3");
+
+INSERT INTO compaction_test VALUES
+('2023-02-14', 2),
+('2033-03-01',2);
+{'label':'insert_734648fa-c878-11ed-90d6-00163e0dcbfc', 'status':'VISIBLE', 'txnId':'5008'}
+
+INSERT INTO compaction_test VALUES
+('2023-02-14', 2),('2033-03-01',2);
+{'label':'insert_85c95c1b-c878-11ed-90d6-00163e0dcbfc', 'status':'VISIBLE', 'txnId':'5009'}
+
+ALTER TABLE compaction_test COMPACT;
+
+ALTER TABLE compaction_test COMPACT p203303;
+
+ALTER TABLE compaction_test COMPACT (p202302,p203303);
+
+ALTER TABLE compaction_test CUMULATIVE COMPACT (p202302,p203303);
+
+ALTER TABLE compaction_test BASE COMPACT (p202302,p203303);
+```
+
+## References
+
+- [CREATE TABLE](CREATE_TABLE.md)
+- [SHOW CREATE TABLE](SHOW_CREATE_TABLE.md)
+- [SHOW TABLES](SHOW_TABLES.md)
+- [SHOW ALTER TABLE](SHOW_ALTER.md)
+- [DROP TABLE](DROP_TABLE.md)
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/CANCEL_ALTER_TABLE.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/CANCEL_ALTER_TABLE.md
new file mode 100644
index 00000000000000..d8f2191ad463c1
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/CANCEL_ALTER_TABLE.md
@@ -0,0 +1,56 @@
+---
+displayed_sidebar: docs
+---
+
+# CANCEL ALTER TABLE
+
+## Description
+
+Cancels the execution of the ongoing ALTER TABLE operation, including:
+
+- Modify columns.
+- Optimize table schema (from v3.2), including modifying the bucketing method and the number of buckets.
+- Create and delete the rollup index.
+
+> **NOTICE**
+>
+> - This statement is a synchronous operation.
+> - This statement requires you to have the `ALTER_PRIV` privilege on the table.
+> - This statement only supports canceling asynchronous operations using ALTER TABLE (as mentioned above) and does not support canceling synchronous operations using ALTER TABLE, such as rename.
+
+## Syntax
+
+   ```SQL
+   CANCEL ALTER TABLE { COLUMN | OPTIMIZE | ROLLUP } FROM [db_name.]table_name
+   ```
+
+## Parameters
+
+- `{COLUMN ｜ OPTIMIZE | ROLLUP}`
+
+  - If `COLUMN` is specified, this statement cancels operations of modifying columns.
+  - If `OPTIMIZE` is specified, this statement cancels operations of optimizing table schema.
+  - If `ROLLUP` is specified, this statement cancels operations of adding or deleting the rollup index.
+
+- `db_name`: optional. The name of the database to which the table belongs. If this parameter is not specified, your current database is used by default.
+- `table_name`: required. The table name.
+
+## Examples
+
+1. Cancel the operation of modifying columns for `example_table` in the database `example_db`.
+
+   ```SQL
+   CANCEL ALTER TABLE COLUMN FROM example_db.example_table;
+   ```
+
+2. Cancel the operation of optimizing table schema for `example_table` in the database `example_db`.
+
+   ```SQL
+   CANCEL ALTER TABLE OPTIMIZE FROM example_db.example_table;
+   ```
+
+3. Cancel the operation of adding or deleting the rollup index for `example_table` in the current database.
+
+   ```SQL
+   CANCEL ALTER TABLE ROLLUP FROM example_table;
+   ```
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_INDEX.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_INDEX.md
new file mode 100644
index 00000000000000..91f4f7fcb167d7
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_INDEX.md
@@ -0,0 +1,34 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE INDEX
+
+## Description
+
+This statement is used to create indexes. You can use this statement to create only Bitmap indexes. For usage notes and scenarios of Bitmap indexes, see [Bitmap index](../../../table_design/indexes/Bitmap_index.md).
+
+:::tip
+
+This operation requires the ALTER privilege on the target table. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+## Syntax
+
+```sql
+CREATE INDEX index_name ON table_name (column [, ...],) [USING BITMAP] [COMMENT 'balabala']
+```
+
+Note:
+
+1. For the naming conventions of indexes, see [System limits](../../System_limit.md).
+2. One column can have only one BITMAP index. If a column already has an index, you cannot create one more index on it.
+
+## Examples
+
+1. Create bitmap index for `siteid` on `table1`.
+
+    ```sql
+    CREATE INDEX index_name ON table1 (siteid) USING BITMAP COMMENT 'balabala';
+    ```
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md
new file mode 100644
index 00000000000000..a32d5bb753d7d4
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md
@@ -0,0 +1,1048 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE TABLE
+
+Create a new table in StarRocks.
+
+:::tip
+This operation requires the CREATE TABLE privilege on the destination database.
+:::
+
+## Syntax
+
+```SQL
+CREATE [EXTERNAL] [TEMPORARY] TABLE [IF NOT EXISTS] [database.]table_name
+(column_definition1[, column_definition2, ...]
+[, index_definition1[, index_definition12,]])
+[ENGINE = [olap|mysql|elasticsearch|hive|hudi|iceberg|jdbc]]
+[key_desc]
+[COMMENT "table comment"]
+[partition_desc]
+[distribution_desc]
+[rollup_index]
+[ORDER BY (column_definition1,...)]
+[PROPERTIES ("key"="value", ...)]
+[BROKER PROPERTIES ("key"="value", ...)]
+```
+
+## Parameters
+
+:::tip
+
+- The table name, partition name, column name, and index name you create must follow the naming conventions in [System limits](../../System_limit.md).
+- When you specify database name, table name, column name, or partition name, note that some literals are used as reserved keywords in StarRocks. Do not directly use these keywords in SQL statements. If you want to use such a keyword in an SQL statement, enclose it in a pair of backticks (`). See [Keywords](../keywords.md) for these reserved keywords.
+
+:::
+
+### column_definition
+
+Syntax:
+
+```SQL
+col_name col_type [agg_type] [NULL | NOT NULL] [DEFAULT "default_value"] [AUTO_INCREMENT] [AS generation_expr]
+```
+
+**col_name**: column name.
+
+Note that normally you cannot create a column whose name is initiated with `__op` or `__row` because these name formats are reserved for special purposes in StarRocks and creating such columns may result in undefined behavior. If you do need to create such column, set the FE dynamic parameter [`allow_system_reserved_names`](../../../administration/management/FE_configuration.md#allow_system_reserved_names) to `TRUE`.
+
+**col_type**: Column type. Specific column information, such as types and ranges:
+
+- TINYINT (1 byte): Ranges from -2^7 + 1 to 2^7 - 1.
+- SMALLINT (2 bytes): Ranges from -2^15 + 1 to 2^15 - 1.
+- INT (4 bytes): Ranges from -2^31 + 1 to 2^31 - 1.
+- BIGINT (8 bytes): Ranges from -2^63 + 1 to 2^63 - 1.
+- LARGEINT (16 bytes): Ranges from -2^127 + 1 to 2^127 - 1.
+- FLOAT (4 bytes): Supports scientific notation.
+- DOUBLE (8 bytes): Supports scientific notation.
+- DECIMAL[(precision, scale)] (16 bytes)
+
+  - Default value: DECIMAL(10, 0)
+  - precision: 1 ~ 38
+  - scale: 0 ~ precision
+  - Integer part: precision - scale
+
+    Scientific notation is not supported.
+
+- DATE (3 bytes): Ranges from 0000-01-01 to 9999-12-31.
+- DATETIME (8 bytes): Ranges from 0000-01-01 00:00:00 to 9999-12-31 23:59:59.
+- CHAR[(length)]: Fixed length string. Range: 1 ~ 255. Default value: 1.
+- VARCHAR[(length)]: A variable-length string. The default value is 1. Unit: bytes. In versions earlier than StarRocks 2.1, the value range of `length` is 1–65533. [Preview] In StarRocks 2.1 and later versions, the value range of `length` is 1–1048576.
+- HLL (1~16385 bytes): For HLL type, there's no need to specify length or default value. The length will be controlled within the system according to data aggregation. HLL column can only be queried or used by [hll_union_agg](../../sql-functions/aggregate-functions/hll_union_agg.md), [Hll_cardinality](../../sql-functions/scalar-functions/hll_cardinality.md), and [hll_hash](../../sql-functions/scalar-functions/hll_hash.md).
+- BITMAP: Bitmap type does not require specified length or default value. It represents a set of unsigned bigint numbers. The largest element could be up to 2^64 - 1.
+
+**agg_type**: aggregation type. If not specified, this column is key column.
+If specified, it is value column. The aggregation types supported are as follows:
+
+- SUM, MAX, MIN, REPLACE
+- HLL_UNION (only for HLL type)
+- BITMAP_UNION(only for BITMAP)
+- REPLACE_IF_NOT_NULL: This means the imported data will only be replaced when it is of non-null value. If it is of null value, StarRocks will retain the original value.
+
+> NOTE
+>
+> - When the column of aggregation type BITMAP_UNION is imported, its original data types must be TINYINT, SMALLINT, INT, and BIGINT.
+> - If NOT NULL is specified by REPLACE_IF_NOT_NULL column when the table was created, StarRocks will still convert the data to NULL without sending an error report to the user. With this, the user can import selected columns.
+
+This aggregation type applies ONLY to the Aggregate table whose key_desc type is AGGREGATE KEY. Since v3.1.9, `REPLACE_IF_NOT_NULL` newly supports the columns of the BITMAP type.
+
+**NULL | NOT NULL**: Whether the column is allowed to be `NULL`. By default, `NULL` is specified for all columns in a table that uses the Duplicate Key, Aggregate, or Unique Key table. In a table that uses the Primary Key table, by default, value columns are specified with `NULL`, whereas key columns are specified with `NOT NULL`. If `NULL` values are included in the raw data, present them with `\N`. StarRocks treats `\N` as `NULL` during data loading.
+
+**DEFAULT "default_value"**: the default value of a column. When you load data into StarRocks, if the source field mapped onto the column is empty, StarRocks automatically fills the default value in the column. You can specify a default value in one of the following ways:
+
+- **DEFAULT current_timestamp**: Use the current time as the default value. For more information, see [current_timestamp()](../../sql-functions/date-time-functions/current_timestamp.md).
+- **DEFAULT `<default_value>`**: Use a given value of the column data type as the default value. For example, if the data type of the column is VARCHAR, you can specify a VARCHAR string, such as beijing, as the default value, as presented in `DEFAULT "beijing"`. Note that default values cannot be any of the following types: ARRAY, BITMAP, JSON, HLL, and BOOLEAN.
+- **DEFAULT (\<expr\>)**: Use the result returned by a given function as the default value. Only the [uuid()](../../sql-functions/utility-functions/uuid.md) and [uuid_numeric()](../../sql-functions/utility-functions/uuid_numeric.md) expressions are supported.
+
+**AUTO_INCREMENT**: specifies an `AUTO_INCREMENT` column. The data types of `AUTO_INCREMENT` columns must be BIGINT. Auto-incremented IDs start from 1 and increase at a step of 1. For more information about `AUTO_INCREMENT` columns, see [AUTO_INCREMENT](auto_increment.md). Since v3.0, StarRocks supports `AUTO_INCREMENT` columns.
+
+**AS generation_expr**: specifies the generated column and its expression. [The generated column](../generated_columns.md) can be used to precompute and store the results of expressions, which significantly accelerates queries with the same complex expressions. Since v3.1, StarRocks supports generated columns.
+
+### index_definition
+
+```SQL
+INDEX index_name (col_name[, col_name, ...]) [USING BITMAP] COMMENT 'xxxxxx'
+```
+
+For more information about parameter descriptions and usage notes, see [Bitmap indexing](../../../table_design/indexes/Bitmap_index.md#create-an-index).
+
+### ENGINE type
+
+Default value: `olap`. If this parameter is not specified, an OLAP table (StarRocks native table) is created by default.
+
+Optional value: `mysql`, `elasticsearch`, `hive`, `jdbc` (2.3 and later), `iceberg`, and `hudi` (2.2 and later). If you want to create an external table to query external data sources, specify `CREATE EXTERNAL TABLE` and set `ENGINE` to any of these values. You can refer to [External table](../../../data_source/External_table.md) for more information.
+
+**From v3.0 onwards, we recommend that you use catalogs to query data from Hive, Iceberg, Hudi, and JDBC data sources. External tables are deprecated. For more information, see [Hive catalog](../../../data_source/catalog/hive_catalog.md), [Iceberg catalog](../../../data_source/catalog/iceberg_catalog.md), [Hudi catalog](../../../data_source/catalog/hudi_catalog.md), and [JDBC catalog](../../../data_source/catalog/jdbc_catalog.md).**
+
+**From v3.1 onwards, StarRocks supports creating Parquet-formatted tables in Iceberg catalogs, and you can insert data to these Parquet-formatted Iceberg tables by using [INSERT INTO](../loading_unloading/INSERT.md). See [Create an Iceberg table](../../../data_source/catalog/iceberg_catalog.md#create-an-iceberg-table).**
+
+**From v3.2 onwards, StarRocks supports creating Parquet-formatted tables in Hive catalogs, and supports sinking data to these Parquet-formatted Hive tables by using [INSERT INTO](../loading_unloading/INSERT.md). From v3.3 onwards, StarRocks supports creating ORC- and Textfile-formatted tables in Hive catalogs, and supports sinking data to these ORC- and Textfile-formatted Hive tables by using [INSERT INTO](../loading_unloading/INSERT.md). For more information, see [Create a Hive table](../../../data_source/catalog/hive_catalog.md#create-a-hive-table) and [Sink data to a Hive table](../../../data_source/catalog/hive_catalog.md#sink-data-to-a-hive-table).**
+
+- For MySQL, specify the following properties:
+
+    ```plaintext
+    PROPERTIES (
+        "host" = "mysql_server_host",
+        "port" = "mysql_server_port",
+        "user" = "your_user_name",
+        "password" = "your_password",
+        "database" = "database_name",
+        "table" = "table_name"
+    )
+    ```
+
+    Note:
+
+    "table_name" in MySQL should indicate the real table name. In contrast, "table_name" in CREATE TABLE statement indicates the name of this mysql table on StarRocks. They can either be different or the same.
+
+    The aim of creating MySQL tables in StarRocks is to access MySQL database. StarRocks itself does not maintain or store any MySQL data.
+
+- For Elasticsearch, specify the following properties:
+
+    ```plaintext
+    PROPERTIES (
+
+    "hosts" = "http://192.168.0.1:8200,http://192.168.0.2:8200",
+    "user" = "root",
+    "password" = "root",
+    "index" = "tindex",
+    "type" = "doc"
+    )
+    ```
+
+  - `hosts`: the URL that is used to connect your Elasticsearch cluster. You can specify one or more URLs.
+  - `user`: the account of the root user that is used to log in to your Elasticsearch cluster for which basic authentication is enabled.
+  - `password`: the password of the preceding root account.
+  - `index`: the index of the StarRocks table in your Elasticsearch cluster. The index name is the same as the StarRocks table name. You can set this parameter to the alias of the StarRocks table.
+  - `type`: the type of index. The default value is `doc`.
+
+- For Hive, specify the following properties:
+
+    ```plaintext
+    PROPERTIES (
+
+        "database" = "hive_db_name",
+        "table" = "hive_table_name",
+        "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083"
+    )
+    ```
+
+    Here, database is the name of the corresponding database in Hive table. Table is the name of Hive table. `hive.metastore.uris` is the server address.
+
+- For JDBC, specify the following properties:
+
+    ```plaintext
+    PROPERTIES (
+    "resource"="jdbc0",
+    "table"="dest_tbl"
+    )
+    ```
+
+    `resource` is the JDBC resource name and `table` is the destination table.
+
+- For Iceberg, specify the following properties:
+
+   ```plaintext
+    PROPERTIES (
+    "resource" = "iceberg0", 
+    "database" = "iceberg", 
+    "table" = "iceberg_table"
+    )
+    ```
+
+    `resource` is the Iceberg resource name. `database` is the Iceberg database. `table` is the Iceberg table.
+
+- For Hudi, specify the following properties:
+
+  ```plaintext
+    PROPERTIES (
+    "resource" = "hudi0", 
+    "database" = "hudi", 
+    "table" = "hudi_table" 
+    )
+    ```
+
+### key_desc
+
+Syntax:
+
+```SQL
+key_type(k1[,k2 ...])
+```
+
+Data is sequenced in specified key columns and has different attributes for different key types:
+
+- AGGREGATE KEY: Identical content in key columns will be aggregated into value columns according to the specified aggregation type. It usually applies to business scenarios such as financial statements and multi-dimensional analysis.
+- UNIQUE KEY/PRIMARY KEY: Identical content in key columns will be replaced in value columns according to the import sequence. It can be applied to make addition, deletion, modification and query on key columns.
+- DUPLICATE KEY: Identical content in key columns, which also exists in StarRocks at the same time. It can be used to store detailed data or data with no aggregation attributes. **DUPLICATE KEY is the default type. Data will be sequenced according to key columns.**
+
+> **NOTE**
+>
+> Value columns do not need to specify aggregation types when other key_type is used to create tables with the exception of AGGREGATE KEY.
+
+### COMMENT
+
+You can add a table comment when you create a table, optional. Note that COMMENT must be placed after `key_desc`. Otherwise, the table cannot be created.
+
+From v3.1 onwards, you can modify the table comment suing `ALTER TABLE <table_name> COMMENT = "new table comment"`.
+
+### partition_desc
+
+Partition description can be used in the following ways:
+
+#### Create partitions dynamically
+
+[Dynamic partitioning](../../../table_design/dynamic_partitioning.md) provides a time-to-live (TTL) management for partitions. StarRocks automatically creates new partitions in advance and removes expired partitions to ensure data freshness. To enable this feature, you can configure Dynamic partitioning related properties at table creation.
+
+#### Create partitions one by one
+
+**Specify only the upper bound for a partition**
+
+Syntax:
+
+```sql
+PARTITION BY RANGE ( <partitioning_column1> [, <partitioning_column2>, ... ] )
+  PARTITION <partition1_name> VALUES LESS THAN ("<upper_bound_for_partitioning_column1>" [ , "<upper_bound_for_partitioning_column2>", ... ] )
+  [ ,
+  PARTITION <partition2_name> VALUES LESS THAN ("<upper_bound_for_partitioning_column1>" [ , "<upper_bound_for_partitioning_column2>", ... ] )
+  , ... ] 
+)
+```
+
+Note:
+
+Please use specified key columns and specified value ranges for partitioning.
+
+- For the naming conventions of partitions, see [System limits](../../System_limit.md).
+- Before v3.3.0, columns for the range partitioning only support the following types: TINYINT, SMALLINT, INT, BIGINT, LARGEINT, DATE, and DATETIME. Since v3.3.0, three specific time functions can be used as columns for the range partitioning. For detailed usage, see [Data distribution](../../../table_design/Data_distribution.md#manually-create-partitions).
+- Partitions are left closed and right open. The left boundary of the first partition is of minimum value.
+- NULL value is stored only in partitions that contain minimum values. When the partition containing the minimum value is deleted, NULL values can no longer be imported.
+- Partition columns can either be single columns or multiple columns. The partition values are the default minimum values.
+- When only one column is specified as the partitioning column, you can set `MAXVALUE` as the upper bound for the partitioning column of the most recent partition.
+
+  ```SQL
+  PARTITION BY RANGE (pay_dt) (
+    PARTITION p1 VALUES LESS THAN ("20210102"),
+    PARTITION p2 VALUES LESS THAN ("20210103"),
+    PARTITION p3 VALUES LESS THAN MAXVALUE
+  )
+  ```
+
+Please note:
+
+- Partitions are often used for managing data related to time.
+- When data backtracking is needed, you may want to consider emptying the first partition for adding partitions later when necessary.
+
+**Specify both the lower and upper bounds for a partition**
+
+Syntax:
+
+```SQL
+PARTITION BY RANGE ( <partitioning_column1> [, <partitioning_column2>, ... ] )
+(
+    PARTITION <partition_name1> VALUES [( "<lower_bound_for_partitioning_column1>" [ , "<lower_bound_for_partitioning_column2>", ... ] ), ( "<upper_bound_for_partitioning_column1?" [ , "<upper_bound_for_partitioning_column2>", ... ] ) ) 
+    [,
+    PARTITION <partition_name2> VALUES [( "<lower_bound_for_partitioning_column1>" [ , "<lower_bound_for_partitioning_column2>", ... ] ), ( "<upper_bound_for_partitioning_column1>" [ , "<upper_bound_for_partitioning_column2>", ... ] ) ) 
+    , ...]
+)
+```
+
+Note:
+
+- Fixed Range is more flexible than LESS THAN. You can customize the left and right partitions.
+- Fixed Range is the same as LESS THAN in the other aspects.
+- When only one column is specified as the partitioning column, you can set `MAXVALUE` as the upper bound for the partitioning column of the most recent partition.
+
+  ```SQL
+  PARTITION BY RANGE (pay_dt) (
+    PARTITION p202101 VALUES [("20210101"), ("20210201")),
+    PARTITION p202102 VALUES [("20210201"), ("20210301")),
+    PARTITION p202103 VALUES [("20210301"), (MAXVALUE))
+  )
+  ```
+
+#### Create multiple partitions in a batch
+
+Syntax
+
+- If the partitioning column is of a date type.
+
+    ```sql
+    PARTITION BY RANGE (<partitioning_column>) (
+        START ("<start_date>") END ("<end_date>") EVERY (INTERVAL <N> <time_unit>)
+    )
+    ```
+
+- If the partitioning column is of an integer type.
+
+    ```sql
+    PARTITION BY RANGE (<partitioning_column>) (
+        START ("<start_integer>") END ("<end_integer>") EVERY (<partitioning_granularity>)
+    )
+    ```
+
+Description
+
+You can specify the start and end values in `START()` and `END()` and the time unit or partitioning granularity in `EVERY()` to create multiple partitions in a batch.
+
+- Before v3.3.0, columns for the range partitioning only support the following types: TINYINT, SMALLINT, INT, BIGINT, LARGEINT, DATE, and DATETIME. Since v3.3.0, three specific time functions can be used as columns for the range partitioning. For detailed usage, see [Data distribution](../../../table_design/Data_distribution.md#manually-create-partitions).
+- If the partitioning column is of a date type, you need to use the `INTERVAL` keyword to specify the time interval. You can specify the time unit as hour (since v3.0), day, week, month, or year. The naming conventions of partitions are the same as those for dynamic partitions.
+
+For more information, see [Data distribution](../../../table_design/Data_distribution.md).
+
+### distribution_desc
+
+StarRocks supports hash bucketing and random bucketing. If you do not configure bucketing, StarRocks uses random bucketing and automatically sets the number of buckets by default.
+
+- Random bucketing (since v3.1)
+
+  For data in a partition, StarRocks distributes the data randomly across all buckets, which is not based on specific column values. And if you want StarRocks to automatically set the number of buckets, you do not need to specify any bucketing configurations. If you choose to manually specify the number of buckets, the syntax is as follows:
+
+  ```SQL
+  DISTRIBUTED BY RANDOM BUCKETS <num>
+  ```
+  
+  However, note that the query performance provided by random bucketing may not be ideal when you query massive amounts of data and frequently use certain columns as conditional columns. In this scenario, it is recommended to use hash bucketing. Because only a small number of buckets need to be scanned and computed, significantly improving query performance.
+
+  **Precautions**
+  - You can only use random bucketing to create Duplicate Key tables.
+  - You can not specify a [Colocation Group](../../../using_starrocks/Colocate_join.md) for a table bucketed randomly.
+  - [Spark Load](../../../loading/SparkLoad.md) cannot be used to load data into tables bucketed randomly.
+  - Since StarRocks v2.5.7, you do not need to set the number of buckets when you create a table. StarRocks automatically sets the number of buckets. If you want to set this parameter, see [Set the number of buckets](../../../table_design/Data_distribution.md#set-the-number-of-buckets).
+
+  For more information, see [Random bucketing](../../../table_design/Data_distribution.md#random-bucketing-since-v31).
+
+- Hash bucketing
+
+  Syntax:
+
+  ```SQL
+  DISTRIBUTED BY HASH (k1[,k2 ...]) [BUCKETS num]
+  ```
+
+  Data in partitions can be subdivided into buckets based on the hash values of the bucketing columns and the number of buckets. We recommend that you choose the column that meets the following two requirements as the bucketing column.
+
+  - High cardinality column such as ID
+  - Column that is often used as a filter in queries
+
+  If such a column does not exist, you can determine the bucketing column according to the complexity of queries.
+
+  - If the query is complex, we recommend that you select a high cardinality column as the bucketing column to ensure balanced data distribution among buckets and improve cluster resource utilization.
+  - If the query is relatively simple, we recommend that you select the column that is often used as the query condition as the bucketing column to improve query efficiency.
+
+  If partition data cannot be evenly distributed into each bucket by using one bucketing column, you can choose multiple bucketing columns (at most three). For more information, see [Choose bucketing columns](../../../table_design/Data_distribution.md#hash-bucketing).
+
+  **Precautions**:
+
+  - **When you create a table, you must specify its bucketing columns**.
+  - The values of bucketing columns cannot be updated.
+  - Bucketing columns cannot be modified after they are specified.
+  - Since StarRocks v2.5.7, you do not need to set the number of buckets when you create a table. StarRocks automatically sets the number of buckets. If you want to set this parameter, see [Set the number of buckets](../../../table_design/Data_distribution.md#set-the-number-of-buckets).
+
+### ORDER BY
+
+Since v3.0, Primary Key tables support defining sort keys using `ORDER BY`. Since v3.3, Duplicate Key tables, Aggregate tables, and Unique Key tables support defining sort keys using `ORDER BY`.
+
+For more descriptions of sort keys, see [Sort keys and prefix indexes](../../../table_design/indexes/Prefix_index_sort_key.md).
+
+### TEMPORARY
+
+Creates a temporary table. From v3.3.1, StarRocks supports creating temporary tables in the Default Catalog. For more information, see [Temporary Table](../../../table_design/StarRocks_table_design.md#temporary-table).
+
+:::note
+When creating a temporary table, you must set `ENGINE` to `olap`.
+:::
+
+### PROPERTIES
+
+#### Specify initial storage medium, automatic storage cooldown time, replica number
+
+If the engine type is `OLAP`, you can specify initial storage medium (`storage_medium`), automatic storage cooldown time (`storage_cooldown_time`) or time interval (`storage_cooldown_ttl`), and replica number (`replication_num`) when you create a table.
+
+The scope where the properties take effect: If the table has only one partition, the properties belong to the table. If the table is divided into multiple partitions, the properties belong to each partition. And when you need to configure different properties for specified partitions, you can execute [ALTER TABLE ... ADD PARTITION or ALTER TABLE ... MODIFY PARTITION](ALTER_TABLE.md) after table creation.
+
+**Set initial storage medium and automatic storage cooldown time**
+
+```sql
+PROPERTIES (
+    "storage_medium" = "[SSD|HDD]",
+    { "storage_cooldown_ttl" = "<num> { YEAR | MONTH | DAY | HOUR } "
+    | "storage_cooldown_time" = "yyyy-MM-dd HH:mm:ss" }
+)
+```
+
+- `storage_medium`: the initial storage medium, which can be set to `SSD` or `HDD`. Make sure that the type of storage medium you explicitly specified is consistent with the BE disk types for your StarRocks cluster specified in the BE static parameter `storage_root_path`.<br />
+
+    If the FE configuration item `enable_strict_storage_medium_check` is set to `true`, the system strictly checks BE disk type when you create a table. If the storage medium you specified in CREATE TABLE is inconsistent with BE disk type, an error "Failed to find enough host in all backends with storage medium is SSD|HDD." is returned and table creation fails. If `enable_strict_storage_medium_check` is set to `false`, the system ignores this error and forcibly creates the table. However, cluster disk space may be unevenly distributed after data is loaded.<br />
+
+    From v2.3.6, v2.4.2, v2.5.1, and v3.0 onwards, the system automatically infers storage medium based on BE disk type if `storage_medium` is not explicitly specified.<br />
+
+  - The system automatically sets this parameter to SSD in the following scenarios:
+
+    - The disk types reported by BEs (`storage_root_path`) contain only SSD.
+    - The disk types reported by BEs (`storage_root_path`) contain both SSD and HDD. Note that from v2.3.10, v2.4.5, v2.5.4, and v3.0 onwards, the system sets `storage_medium` to SSD when `storage_root_path` reported by BEs contain both SSD and HDD and the property `storage_cooldown_time` is specified.
+
+  - The system automatically sets this parameter to HDD in the following scenarios:
+
+    - The disk types reported by BEs (`storage_root_path`) contain only HDD.
+    - From 2.3.10, 2.4.5, 2.5.4, and 3.0 onwards,  the system sets `storage_medium` to HDD when `storage_root_path` reported by BEs contain both SSD and HDD and the property `storage_cooldown_time` is not specified.
+
+- `storage_cooldown_ttl` or `storage_cooldown_time`: the automatic storage cooldown time or time interval. Automatic storage cooldown refers to automatically migrate data from SSD to HDD. This feature is only effective when the initial storage medium is SSD.
+
+  **Parameter**
+
+  - `storage_cooldown_ttl`: the **time interval** of automatic storage cooldown for the partitions in this table. If you need to retain the most recent partitions on SSD and automatically cool down older partitions to HDD after a certain time interval, you can use this parameter. The automatic storage cooldown time for each partition is calculated using the value of this parameter plus the upper time bound of the partition.
+
+  The supported values are `<num> YEAR`, `<num> MONTH`, `<num> DAY`, and `<num> HOUR`. `<num>` is a non-negative integer. The default value is null, indicating that storage cooldown is not automatically performed.
+
+  For example, you specify the value as `"storage_cooldown_ttl"="1 DAY"` when creating the table, and the partition `p20230801` with a range of `[2023-08-01 00:00:00,2023-08-02 00:00:00)` exists. The automatic storage cooldown time for this partition is `2023-08-03 00:00:00`, which is `2023-08-02 00:00:00 + 1 DAY`. If you specify the value as `"storage_cooldown_ttl"="0 DAY"` when creating the table, the automatic storage cooldown time for this partition is `2023-08-02 00:00:00`.
+
+  - `storage_cooldown_time`: the automatic storage cooldown time (**absolute time**) when the table is cooled down from SSD to HDD. The specified time needs to be later than the current time. Format: "yyyy-MM-dd HH:mm:ss". When you need to configure different properties for specified partitions, you can execute [ALTER TABLE ... ADD PARTITION or ALTER TABLE ... MODIFY PARTITION](ALTER_TABLE.md).
+
+**Usages**
+
+- The comparison between the parameters related to automatic storage cooldown is as follows:
+  - `storage_cooldown_ttl`: A table property that specifies the time interval of automatic storage cooldown for partitions in the table. The system automatically cools down a partition at the time `the value of this parameter plus the upper time bound of the partition`. So automatic storage cooldown is performed at the partition granularity, which is more flexible.
+  - `storage_cooldown_time`: A table property that specifies the automatic storage cooldown time (**absolute time**) for this table. Also, you can configure different properties for specified partitions after table creation.
+  - `storage_cooldown_second`: A static FE parameter that specifies the automatic storage cooldown latency for all tables within the cluster.
+
+- The table property `storage_cooldown_ttl` or `storage_cooldown_time` takes precedence over the FE static parameter `storage_cooldown_second`.
+- When configuring these parameters, you need to specify `"storage_medium = "SSD"`.
+- If you do not configure these parameters, automatic storage cooldown is not be automatically performed.
+- Execute `SHOW PARTITIONS FROM <table_name>` to view the automatic storage cooldown time for each partition.
+
+**Limit**
+
+- Expression and List partitioning are not supported.
+- The partition column need to be of date type.
+- Multiple partition columns are not supported.
+- Primary Key tables are not supported.
+
+**Set the number of replicas for each tablet in partitions**
+
+`replication_num`: number of replicas for each table in the partitions. Default number: `3`.
+
+```sql
+PROPERTIES (
+    "replication_num" = "<num>"
+)
+```
+
+#### Add bloom filter index for a column
+
+If the Engine type is olap, you can specify a column to adopt bloom filter indexes.
+
+The following limits apply when you use bloom filter index:
+
+- You can create bloom filter indexes for all columns of a Duplicate Key or Primary Key table. For an Aggregate table or Unique Key table, you can only create bloom filter indexes for key columns.
+- TINYINT, FLOAT, DOUBLE, and DECIMAL columns do not support creating bloom filter indexes.
+- Bloom filter indexes can only improve the performance of queries that contain the `in` and `=` operators, such as `Select xxx from table where x in {}` and `Select xxx from table where column = xxx`. More discrete values in this column will result in more precise queries.
+
+For more information, see [Bloom filter indexing](../../../table_design/indexes/Bloomfilter_index.md)
+
+```SQL
+PROPERTIES (
+    "bloom_filter_columns"="k1,k2,k3"
+)
+```
+
+#### Use Colocate Join
+
+If you want to use Colocate Join attributes, specify it in `properties`.
+
+```SQL
+PROPERTIES (
+    "colocate_with"="table1"
+)
+```
+
+#### Configure dynamic partitions
+
+If you want to use dynamic partition attributes, please specify it in properties.
+
+```SQL
+PROPERTIES (
+
+    "dynamic_partition.enable" = "true|false",
+    "dynamic_partition.time_unit" = "DAY|WEEK|MONTH",
+    "dynamic_partition.start" = "${integer_value}",
+    "dynamic_partition.end" = "${integer_value}",
+    "dynamic_partition.prefix" = "${string_value}",
+    "dynamic_partition.buckets" = "${integer_value}"
+```
+
+**`PROPERTIES`**
+
+| Parameter                   | Required | Description                                                  |
+| --------------------------- | -------- | ------------------------------------------------------------ |
+| dynamic_partition.enable    | No       | Whether to enable dynamic partitioning. Valid values: `TRUE` and `FALSE`. Default value: `TRUE`. |
+| dynamic_partition.time_unit | Yes      | The time granularity for dynamically created  partitions. It is a required parameter. Valid values: `DAY`, `WEEK`, and `MONTH`. The time granularity determines the suffix format for dynamically created partitions.<br/>  - If the value is `DAY`, the suffix format for dynamically created partitions is `yyyyMMdd`. An example partition name suffix is `20200321`.<br/>  - If the value is `WEEK`, the suffix format for dynamically created partitions is `yyyy_ww`, for example `2020_13` for the 13th week of 2020.<br/>  - If the value is `MONTH`, the suffix format for dynamically created partitions is `yyyyMM`, for example `202003`. |
+| dynamic_partition.start     | No       | The starting offset of dynamic partitioning. The value of this parameter must be a negative integer. The partitions before this offset will be deleted based on the current day, week, or month which is determined by `dynamic_partition.time_unit`. The default value is `Integer.MIN_VALUE`, namely, -2147483648, which means that historical partitions will not be deleted. |
+| dynamic_partition.end       | Yes      | The end offset of dynamic partitioning. The value of this parameter must be a positive integer. The partitions from the current day, week, or month to the end offset will be created in advance. |
+| dynamic_partition.prefix    | No       | The prefix added to the names of dynamic partitions. Default value: `p`. |
+| dynamic_partition.buckets   | No       | The number of buckets per dynamic partition. The default value is the same as the number of buckets determined by the reserved word `BUCKETS` or automatically set by StarRocks. |
+
+#### Specify the bucket size (`bucket_size`) for tables configured with random bucketing
+
+Since v3.2, for tables configured with random bucketing, you can specify the bucket size by using the `bucket_size` parameter in `PROPERTIES` at table creation to enable the on-demand and dynamic increase of the number of buckets. Unit: B.
+
+```sql
+PROPERTIES (
+    "bucket_size" = "1073741824"
+)
+```
+
+#### Set data compression algorithm
+
+You can specify a data compression algorithm for a table by adding property `compression` when you create a table.
+
+The valid values of `compression` are:
+
+- `LZ4`: the LZ4 algorithm.
+- `ZSTD`: the Zstandard algorithm.
+- `ZLIB`: the zlib algorithm.
+- `SNAPPY`: the Snappy algorithm.
+
+From v3.3.2 onwards, StarRocks supports specifying the compression level for zstd compression format during table creation.
+
+Syntax:
+
+```sql
+PROPERTIES ("compression" = "zstd(<compression_level>)")
+```
+
+`compression_level`: the compression level for ZSTD compression format. Type: Integer. Range: [1,22]. Default: `3` (Recommended). The greater the number, the higher the compression ratio. The higher the compression level, the more time consumption for compression and decompression.
+
+Example:
+
+```sql
+PROPERTIES ("compression" = "zstd(3)")
+```
+
+For more information about how to choose a suitable data compression algorithm, see [Data compression](../../../table_design/data_compression.md).
+
+#### Set write quorum for data loading
+
+If your StarRocks cluster has multiple data replicas, you can set different write quorum for tables, that is, how many replicas are required to return loading success before StarRocks can determine the loading task is successful. You can specify write quorum by adding the property `write_quorum` when you create a table. This property is supported from v2.5.
+
+The valid values of `write_quorum` are:
+
+- `MAJORITY`: Default value. When the **majority** of data replicas return loading success, StarRocks returns loading task success. Otherwise, StarRocks returns loading task failed.
+- `ONE`: When **one** of the data replicas returns loading success, StarRocks returns loading task success. Otherwise, StarRocks returns loading task failed.
+- `ALL`: When **all** of the data replicas return loading success, StarRocks returns loading task success. Otherwise, StarRocks returns loading task failed.
+
+> **CAUTION**
+>
+> - Setting a low write quorum for loading increases the risk of data inaccessibility and even loss. For example, you load data into a table with one write quorum in a StarRocks cluster of two replicas, and the data was successfully loaded into only one replica. Despite that StarRocks determines the loading task succeeded, there is only one surviving replica of the data. If the server which stores the tablets of loaded data goes down, the data in these tablets becomes inaccessible. And if the disk of the server is damaged, the data is lost.
+> - StarRocks returns the loading task status only after all data replicas have returned the status. StarRocks will not return the loading task status when there are replicas whose loading status is unknown. In a replica, loading timeout is also considered as loading failed.
+
+#### Specify data writing and replication mode among replicas
+
+If your StarRocks cluster has multiple data replicas, you can specify the `replicated_storage` parameter in `PROPERTIES` to configure the data writing and replication mode among replicas.
+
+- `true` (default in v3.0 and later) indicates "single leader replication", which means data is written only to the primary replica. Other replicas synchronize data from the primary replica. This mode significantly reduces CPU cost caused by data writing to multiple replicas. It is supported from v2.5.
+- `false` (default in v2.5) indicates "leaderless replication", which means data is directly written to multiple replicas, without differentiating primary and secondary replicas. The CPU cost is multiplied by the number of replicas.
+
+In most cases, using the default value gains better data writing performance. If you want to change the data writing and replication mode among replicas, run the ALTER TABLE command. Example:
+
+```sql
+    ALTER TABLE example_db.my_table
+    SET ("replicated_storage" = "false");
+```
+
+#### Create rollup in bulk
+
+You can create rollup in bulk when you create a table.
+
+Syntax:
+
+```SQL
+ROLLUP (rollup_name (column_name1, column_name2, ...)
+[FROM from_index_name]
+[PROPERTIES ("key"="value", ...)],...)
+```
+
+#### Define Unique Key constraints and Foreign Key constraints for View Delta Join query rewrite
+
+To enable query rewrite in the View Delta Join scenario, you must define the Unique Key constraints `unique_constraints` and Foreign Key constraints `foreign_key_constraints` for the table to be joined in the Delta Join. See [Asynchronous materialized view - Rewrite queries in View Delta Join scenario](../../../using_starrocks/query_rewrite_with_materialized_views.md#query-delta-join-rewrite) for further information.
+
+```SQL
+PROPERTIES (
+    "unique_constraints" = "<unique_key>[, ...]",
+    "foreign_key_constraints" = "
+    (<child_column>[, ...]) 
+    REFERENCES 
+    [catalog_name].[database_name].<parent_table_name>(<parent_column>[, ...])
+    [;...]
+    "
+)
+```
+
+- `child_column`: the Foreign Key of the table. You can define multiple `child_column`.
+- `catalog_name`: the name of the catalog where the table to join resides. The default catalog is used if this parameter is not specified.
+- `database_name`: the name of the database where the table to join resides. The current database is used if this parameter is not specified.
+- `parent_table_name`: the name of the table to join.
+- `parent_column`: the column to be joined. They must be the Primary Keys or Unique Keys of the corresponding tables.
+
+> **CAUTION**
+>
+> - `unique_constraints` and `foreign_key_constraints` are only used for query rewrite. Foreign Key constraints checks are not guaranteed when data is loaded into the table. You must ensure the data loaded into the table meets the constraints.
+> - The primary keys of a Primary Key table or the unique keys of a Unique Key table are, by default, the corresponding `unique_constraints`. You do not need to set it manually.
+> - The `child_column` in a table's `foreign_key_constraints` must be referenced to a `unique_key` in another table's `unique_constraints`.
+> - The number of `child_column` and `parent_column` must agree.
+> - The data types of the `child_column` and the corresponding `parent_column` must match.
+
+#### Create cloud-native tables for StarRocks Shared-data cluster
+
+To use your StarRocks Shared-data cluster, you must create cloud-native tables with the following properties:
+
+```SQL
+PROPERTIES (
+    "storage_volume" = "<storage_volume_name>",
+    "datacache.enable" = "{ true | false }",
+    "datacache.partition_duration" = "<string_value>",
+    "enable_async_write_back" = "{ true | false }"
+)
+```
+
+- `storage_volume`: The name of the storage volume used to store the cloud-native table you want to create. If this property is not specified, the default storage volume is used. This property is supported from v3.1 onwards.
+
+- `datacache.enable`: Whether to enable the local disk cache. Default: `true`.
+
+  - When this property is set to `true`, the data to be loaded is simultaneously written into the object storage and the local disk (as the cache for query acceleration).
+  - When this property is set to `false`, the data is loaded only into the object storage.
+
+  > **NOTE**
+  >
+  > To enable the local disk cache, you must specify the directory of the disk in the BE configuration item `storage_root_path`. For more information, see [BE Configuration items](../../../administration/management/BE_configuration.md).
+
+- `datacache.partition_duration`: The validity duration of the hot data. When the local disk cache is enabled, all data is loaded into the cache. When the cache is full, StarRocks deletes the less recently used data from the cache. When a query needs to scan the deleted data, StarRocks checks if the data is within the duration of validity. If the data is within the duration, StarRocks loads the data into the cache again. If the data is not within the duration, StarRocks does not load it into the cache. This property is a string value that can be specified with the following units: `YEAR`, `MONTH`, `DAY`, and `HOUR`, for example, `7 DAY` and `12 HOUR`. If it is not specified, all data is cached as the hot data.
+
+  > **NOTE**
+  >
+  > This property is available only when `datacache.enable` is set to `true`.
+
+- `enable_async_write_back`: Whether to allow data to be written into object storage asynchronously. Default: `false`.
+
+  - When this property is set to `true`, the load task returns success as soon as the data is written into the local disk cache, and the data is written into the object storage asynchronously. This allows better loading performance, but it also risks data reliability under potential system failures.
+  - When this property is set to `false`, the load task returns success only after the data is written into both object storage and the local disk cache. This guarantees higher availability but leads to lower loading performance.
+
+#### Set fast schema evolution
+
+`fast_schema_evolution`: Whether to enable fast schema evolution for the table. Valid values are `TRUE` or `FALSE` (default). Enabling fast schema evolution can increase the speed of schema changes and reduce resource usage when columns are added or dropped. Currently, this property can only be enabled at table creation, and it cannot be modified using [ALTER TABLE](ALTER_TABLE.md) after table creation.
+  > **NOTE**
+  >
+  > - This parameter is supported for shared-nothing clusters since v3.2.0, and shared-data clusters since v3.3.0.
+  > - If you need to configure fast schema evolution at the cluster level, such as disabling fast schema evolution within the StarRocks cluster, you can set the FE dynamic parameter [`enable_fast_schema_evolution`](../../../administration/management/FE_configuration.md#enable_fast_schema_evolution).
+
+## Examples
+
+### Create an Aggregate table that uses Hash bucketing and columnar storage
+
+```SQL
+CREATE TABLE example_db.table_hash
+(
+    k1 TINYINT,
+    k2 DECIMAL(10, 2) DEFAULT "10.5",
+    v1 CHAR(10) REPLACE,
+    v2 INT SUM
+)
+ENGINE=olap
+AGGREGATE KEY(k1, k2)
+COMMENT "my first starrocks table"
+DISTRIBUTED BY HASH(k1)
+PROPERTIES ("storage_type"="column");
+```
+
+### Create an Aggregate table and set the storage medium and cooldown time
+
+```SQL
+CREATE TABLE example_db.table_hash
+(
+    k1 BIGINT,
+    k2 LARGEINT,
+    v1 VARCHAR(2048) REPLACE,
+    v2 SMALLINT SUM DEFAULT "10"
+)
+ENGINE=olap
+UNIQUE KEY(k1, k2)
+DISTRIBUTED BY HASH (k1, k2)
+PROPERTIES(
+    "storage_type"="column",
+    "storage_medium" = "SSD",
+    "storage_cooldown_time" = "2015-06-04 00:00:00"
+);
+```
+
+Or
+
+```SQL
+CREATE TABLE example_db.table_hash
+(
+    k1 BIGINT,
+    k2 LARGEINT,
+    v1 VARCHAR(2048) REPLACE,
+    v2 SMALLINT SUM DEFAULT "10"
+)
+ENGINE=olap
+PRIMARY KEY(k1, k2)
+DISTRIBUTED BY HASH (k1, k2)
+PROPERTIES(
+    "storage_type"="column",
+    "storage_medium" = "SSD",
+    "storage_cooldown_time" = "2015-06-04 00:00:00"
+);
+```
+
+### Create a Duplicate Key table that uses Range partition, Hash bucketing, and column-based storage, and set the storage medium and cooldown time
+
+LESS THAN
+
+```SQL
+CREATE TABLE example_db.table_range
+(
+    k1 DATE,
+    k2 INT,
+    k3 SMALLINT,
+    v1 VARCHAR(2048),
+    v2 DATETIME DEFAULT "2014-02-04 15:36:00"
+)
+ENGINE=olap
+DUPLICATE KEY(k1, k2, k3)
+PARTITION BY RANGE (k1)
+(
+    PARTITION p1 VALUES LESS THAN ("2014-01-01"),
+    PARTITION p2 VALUES LESS THAN ("2014-06-01"),
+    PARTITION p3 VALUES LESS THAN ("2014-12-01")
+)
+DISTRIBUTED BY HASH(k2)
+PROPERTIES(
+    "storage_medium" = "SSD", 
+    "storage_cooldown_time" = "2015-06-04 00:00:00"
+);
+```
+
+Note:
+
+This statement will create three data partitions:
+
+```SQL
+( {    MIN     },   {"2014-01-01"} )
+[ {"2014-01-01"},   {"2014-06-01"} )
+[ {"2014-06-01"},   {"2014-12-01"} )
+```
+
+Data outside these ranges will be not be loaded.
+
+Fixed Range
+
+```SQL
+CREATE TABLE table_range
+(
+    k1 DATE,
+    k2 INT,
+    k3 SMALLINT,
+    v1 VARCHAR(2048),
+    v2 DATETIME DEFAULT "2014-02-04 15:36:00"
+)
+ENGINE=olap
+DUPLICATE KEY(k1, k2, k3)
+PARTITION BY RANGE (k1, k2, k3)
+(
+    PARTITION p1 VALUES [("2014-01-01", "10", "200"), ("2014-01-01", "20", "300")),
+    PARTITION p2 VALUES [("2014-06-01", "100", "200"), ("2014-07-01", "100", "300"))
+)
+DISTRIBUTED BY HASH(k2)
+PROPERTIES(
+    "storage_medium" = "SSD"
+);
+```
+
+### Create a MySQL external table
+
+```SQL
+CREATE EXTERNAL TABLE example_db.table_mysql
+(
+    k1 DATE,
+    k2 INT,
+    k3 SMALLINT,
+    k4 VARCHAR(2048),
+    k5 DATETIME
+)
+ENGINE=mysql
+PROPERTIES
+(
+    "host" = "127.0.0.1",
+    "port" = "8239",
+    "user" = "mysql_user",
+    "password" = "mysql_passwd",
+    "database" = "mysql_db_test",
+    "table" = "mysql_table_test"
+)
+```
+
+### Create a table that contains HLL columns
+
+```SQL
+CREATE TABLE example_db.example_table
+(
+    k1 TINYINT,
+    k2 DECIMAL(10, 2) DEFAULT "10.5",
+    v1 HLL HLL_UNION,
+    v2 HLL HLL_UNION
+)
+ENGINE=olap
+AGGREGATE KEY(k1, k2)
+DISTRIBUTED BY HASH(k1)
+PROPERTIES ("storage_type"="column");
+```
+
+### Create a table containing BITMAP_UNION aggregation type
+
+The original data type of `v1` and `v2` columns must be TINYINT, SMALLINT, or INT.
+
+```SQL
+CREATE TABLE example_db.example_table
+(
+    k1 TINYINT,
+    k2 DECIMAL(10, 2) DEFAULT "10.5",
+    v1 BITMAP BITMAP_UNION,
+    v2 BITMAP BITMAP_UNION
+)
+ENGINE=olap
+AGGREGATE KEY(k1, k2)
+DISTRIBUTED BY HASH(k1)
+PROPERTIES ("storage_type"="column");
+```
+
+### Create two tables that support Colocate Join
+
+```SQL
+CREATE TABLE `t1` 
+(
+     `id` int(11) COMMENT "",
+    `value` varchar(8) COMMENT ""
+) 
+ENGINE=OLAP
+DUPLICATE KEY(`id`)
+DISTRIBUTED BY HASH(`id`)
+PROPERTIES 
+(
+    "colocate_with" = "t1"
+);
+
+CREATE TABLE `t2` 
+(
+    `id` int(11) COMMENT "",
+    `value` varchar(8) COMMENT ""
+) 
+ENGINE=OLAP
+DUPLICATE KEY(`id`)
+DISTRIBUTED BY HASH(`id`)
+PROPERTIES 
+(
+    "colocate_with" = "t1"
+);
+```
+
+### Create a table with bitmap index
+
+```SQL
+CREATE TABLE example_db.table_hash
+(
+    k1 TINYINT,
+    k2 DECIMAL(10, 2) DEFAULT "10.5",
+    v1 CHAR(10) REPLACE,
+    v2 INT SUM,
+    INDEX k1_idx (k1) USING BITMAP COMMENT 'xxxxxx'
+)
+ENGINE=olap
+AGGREGATE KEY(k1, k2)
+COMMENT "my first starrocks table"
+DISTRIBUTED BY HASH(k1)
+PROPERTIES ("storage_type"="column");
+```
+
+### Create a dynamic partition table
+
+The dynamic partitioning function must be enabled ("dynamic_partition.enable" = "true") in FE configuration. For more information, see [Configure dynamic partitions](#configure-dynamic-partitions).
+
+This example creates partitions for the next three days and deletes partitions created three days ago. For example, if today is 2020-01-08, partitions with the following names will be created: p20200108, p20200109, p20200110, p20200111, and their ranges are:
+
+```plaintext
+[types: [DATE]; keys: [2020-01-08]; ‥types: [DATE]; keys: [2020-01-09]; )
+[types: [DATE]; keys: [2020-01-09]; ‥types: [DATE]; keys: [2020-01-10]; )
+[types: [DATE]; keys: [2020-01-10]; ‥types: [DATE]; keys: [2020-01-11]; )
+[types: [DATE]; keys: [2020-01-11]; ‥types: [DATE]; keys: [2020-01-12]; )
+```
+
+```SQL
+CREATE TABLE example_db.dynamic_partition
+(
+    k1 DATE,
+    k2 INT,
+    k3 SMALLINT,
+    v1 VARCHAR(2048),
+    v2 DATETIME DEFAULT "2014-02-04 15:36:00"
+)
+ENGINE=olap
+DUPLICATE KEY(k1, k2, k3)
+PARTITION BY RANGE (k1)
+(
+    PARTITION p1 VALUES LESS THAN ("2014-01-01"),
+    PARTITION p2 VALUES LESS THAN ("2014-06-01"),
+    PARTITION p3 VALUES LESS THAN ("2014-12-01")
+)
+DISTRIBUTED BY HASH(k2)
+PROPERTIES(
+    "storage_medium" = "SSD",
+    "dynamic_partition.enable" = "true",
+    "dynamic_partition.time_unit" = "DAY",
+    "dynamic_partition.start" = "-3",
+    "dynamic_partition.end" = "3",
+    "dynamic_partition.prefix" = "p",
+    "dynamic_partition.buckets" = "10"
+);
+```
+
+### Create a table where multiple partitions are created in a batch, and an integer type column is specified as partitioning column
+
+  In the following example, the partitioning column `datekey` is of the INT type. All the partitions are created by only one simple partition clause  `START ("1") END ("5") EVERY (1)`. The range of all the partitions starts from `1` and ends at `5`, with a partition granularity of `1`:
+  > **NOTE**
+  >
+  > The partitioning column values in **START()** and **END()** need to be wrapped in quotation marks, while the partition granularity in the **EVERY()** does not need to be wrapped in quotation marks.
+
+  ```SQL
+  CREATE TABLE site_access (
+      datekey INT,
+      site_id INT,
+      city_code SMALLINT,
+      user_name VARCHAR(32),
+      pv BIGINT DEFAULT '0'
+  )
+  ENGINE=olap
+  DUPLICATE KEY(datekey, site_id, city_code, user_name)
+  PARTITION BY RANGE (datekey) (START ("1") END ("5") EVERY (1)
+  )
+  DISTRIBUTED BY HASH(site_id)
+  PROPERTIES ("replication_num" = "3");
+  ```
+
+### Create a Hive external table
+
+Before you create a Hive external table, you must have created a Hive resource and database. For more information, see [External table](../../../data_source/External_table.md#deprecated-hive-external-table).
+
+```SQL
+CREATE EXTERNAL TABLE example_db.table_hive
+(
+    k1 TINYINT,
+    k2 VARCHAR(50),
+    v INT
+)
+ENGINE=hive
+PROPERTIES
+(
+    "resource" = "hive0",
+    "database" = "hive_db_name",
+    "table" = "hive_table_name"
+);
+```
+
+### Create a Primary Key table and specify the sort key
+
+Suppose that you need to analyze user behavior in real time from dimensions such as users' address and last active time. When you create a table, you can define the `user_id` column as the primary key and define the combination of the `address` and `last_active` columns as the sort key.
+
+```SQL
+create table users (
+    user_id bigint NOT NULL,
+    name string NOT NULL,
+    email string NULL,
+    address string NULL,
+    age tinyint NULL,
+    sex tinyint NULL,
+    last_active datetime,
+    property0 tinyint NOT NULL,
+    property1 tinyint NOT NULL,
+    property2 tinyint NOT NULL,
+    property3 tinyint NOT NULL
+) 
+PRIMARY KEY (`user_id`)
+DISTRIBUTED BY HASH(`user_id`)
+ORDER BY(`address`,`last_active`)
+PROPERTIES(
+    "replication_num" = "3",
+    "enable_persistent_index" = "true"
+);
+```
+
+### Create a partitioned temporary table
+
+```SQL
+CREATE TEMPORARY TABLE example_db.temp_table
+(
+    k1 DATE,
+    k2 INT,
+    k3 SMALLINT,
+    v1 VARCHAR(2048),
+    v2 DATETIME DEFAULT "2014-02-04 15:36:00"
+)
+ENGINE=olap
+DUPLICATE KEY(k1, k2, k3)
+PARTITION BY RANGE (k1)
+(
+    PARTITION p1 VALUES LESS THAN ("2014-01-01"),
+    PARTITION p2 VALUES LESS THAN ("2014-06-01"),
+    PARTITION p3 VALUES LESS THAN ("2014-12-01")
+)
+DISTRIBUTED BY HASH(k2);
+```
+
+## References
+
+- [SHOW CREATE TABLE](SHOW_CREATE_TABLE.md)
+- [SHOW TABLES](SHOW_TABLES.md)
+- [USE](../Database/USE.md)
+- [ALTER TABLE](ALTER_TABLE.md)
+- [DROP TABLE](DROP_TABLE.md)
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md
new file mode 100644
index 00000000000000..aea454c28a8135
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md
@@ -0,0 +1,261 @@
+---
+displayed_sidebar: docs
+keywords: ['CTAS']
+---
+
+# CREATE TABLE AS SELECT
+
+## Description
+
+You can use the CREATE TABLE AS SELECT (CTAS) statement to synchronously or asynchronously query a table and create a new table based on the query result, and then insert the query result into the new table.
+
+You can submit an asynchronous CTAS task using [SUBMIT TASK](../loading_unloading/ETL/SUBMIT_TASK.md).
+
+## Syntax
+
+- Synchronously query a table and create a new table based on the query result, and then insert the query result into the new table.
+
+  ```SQL
+  CREATE [TEMPORARY] TABLE [IF NOT EXISTS] [database.]table_name
+  [column_name1 [, column_name2, ...]]
+  [index_definition1 [, index_definition2, ...]]
+  [key_desc]
+  [COMMENT "table comment"]
+  [partition_desc]
+  [distribution_desc]
+  [ORDER BY (column_name1 [, column_name2, ...])]
+  [PROPERTIES ("key"="value", ...)]
+  AS SELECT query
+  [ ... ]
+  ```
+
+- Asynchronously query a table and create a new table based on the query result, and then insert the query result into the new table.
+
+  ```SQL
+  SUBMIT [/*+ SET_VAR(key=value) */] TASK [[database.]<task_name>]AS
+  CREATE TABLE [IF NOT EXISTS] [database.]table_name
+  [column_name1 [, column_name2, ...]]
+  [index_definition1 [, index_definition2, ...]]
+  [key_desc]
+  [COMMENT "table comment"]
+  [partition_desc]
+  [distribution_desc]
+  [ORDER BY (column_name1 [, column_name2, ...])]
+  [PROPERTIES ("key"="value", ...)] AS SELECT query
+  [ ... ]
+  ```
+
+## Parameters
+
+| **Parameter**     | **Required** | **Description**                                              |
+| ----------------- | ------------ | ------------------------------------------------------------ |
+| TEMPORARY         | No           | Creates a temporary table. From v3.3.1, StarRocks supports creating temporary tables in the Default Catalog. For more information, see [Temporary Table](../../../table_design/StarRocks_table_design.md#temporary-table). Currently, StarRocks does not support creating temporary tables with asynchronous tasks by using SUBMIT TASK. |
+| column_name       | No          | The name of a column in the new table. You do not need to specify the data type for the column. StarRocks automatically specifies an appropriate data type for the column. StarRocks converts FLOAT and DOUBLE data into DECIMAL(38,9) data. StarRocks also converts CHAR, VARCHAR, and STRING data into VARCHAR(65533) data. |
+| index_definition| No          | Since v3.1.8, a bitmap index can be created for the new table. The syntax is `INDEX index_name (col_name[, col_name, ...]) [USING BITMAP] COMMENT 'xxxxxx'`. For more information about parameter descriptions and usage notes, see [Bitmap indexes](../../../table_design/indexes/Bitmap_index.md). |
+| key_desc          | No           | The syntax is `key_type ( <col_name1> [, <col_name2> , ...])`.<br />**Parameters**:<ul><li>`key_type`: [the key type of the new table](../../../table_design/table_types/table_types.md). Valid values: `DUPLICATE KEY` and `PRIMARY KEY`. Default value: `DUPLICATE KEY`.</li><li> `col_name`: the column to form the key.</li></ul> |
+| COMMENT           | No           | The comment of the new table.                                |
+| partition_desc    | No           | The partitioning method of the new table. By default, if you do not specify this parameter, the new table has no partition. For more information about partitioning, see [CREATE TABLE](./CREATE_TABLE.md#partition_desc). |
+| distribution_desc | No           | The bucketing method of the new table. If you do not specify this parameter, the bucket column defaults to the column with the highest cardinality collected by the cost-based optimizer (CBO). The number of buckets defaults to 10. If the CBO does not collect information about the cardinality, the bucket column defaults to the first column in the new table. For more information about bucketing, see [CREATE TABLE](./CREATE_TABLE.md#distribution_desc). |
+| ORDER BY | No | Since v3.1.8, a sort key can be specified for the new table if the new table is a Primary Key table. The sort key can be a combination of any columns. A Primary Key table is a table for which `PRIMARY KEY (xxx)` is specified at table creation.|
+| Properties        | No           | The properties of the new table.                             |
+| AS SELECT query   | Yes          | The query result.  You can specify columns in `... AS SELECT query`, for example, `... AS SELECT a, b, c FROM table_a;`. In this example, `a`, `b`, and `c` indicates the column names of the table that is queried. If you do not specify the column names of the new table, the column names of the new table are also `a`, `b`, and `c`. You can specify expressions in `... AS SELECT query`, for example, `... AS SELECT a+1 AS x, b+2 AS y, c*c AS z FROM table_a;`. In this example, `a+1`, `b+2`, and `c*c` indicates the column names of the table that is queried, and `x`, `y`, and `z` indicates the column names of the new table. Note:  The number of columns in the new table need to be the same as the number of the columns specified in the SELECT statement . We recommend that you use column names that are easy to identify. |
+
+## Usage notes
+
+- The CTAS statement can only create a new table that meets the following requirements:
+  - `ENGINE` is `OLAP`.
+
+  - The table is a Duplicate Key table by default. You can also specify it as a Primary Key table in `key_desc`.
+
+  - The sort keys are the first three columns, and the storage space of the data types of these three columns does not exceed 36 bytes.
+
+- The CTAS statement does not support setting indexes for a newly created table.
+
+- If the CTAS statement fails to execute due to reasons, such as an FE restart, one of the following issues may occur:
+  - A new table is created successfully but does not contain data.
+
+  - A new table fails to be created.
+
+- After a new table is created, if multiple methods (such as INSERT INTO) are used to insert data into the new table, the method that completes the INSERT operation first will insert its data into the new table.
+
+- After a new table is created, you need to manually grant permissions on this table to users.
+
+- If you do not specify a name for a Task when you asynchronously query a table and create a new table based on the query result, StarRocks automatically generates a name for the Task.
+
+## Examples
+
+Example 1: Synchronously query a table `order` and create a new table `order_new` based on the query result, and then insert the query result into the new table.
+
+```SQL
+CREATE TABLE order_new
+AS SELECT * FROM order;
+```
+
+Example 2: Synchronously query the `k1`, `k2`, and `k3` columns in the table `order` and create a new table `order_new` based on the query result, and then insert the query result into the new table. Additionally, set the column names of the new table to `a`, `b`, and `c`.
+
+```SQL
+CREATE TABLE order_new (a, b, c)
+AS SELECT k1, k2, k3 FROM order;
+```
+
+or
+
+```SQL
+CREATE TABLE order_new
+AS SELECT k1 AS a, k2 AS b, k3 AS c FROM order;
+```
+
+Example 3: Synchronously query the largest value of the `salary` column in the table `employee` and create a new table `employee_new` based on the query result, and then insert the query result into the new table. Additionally, set the column name of the new table to `salary_max`.
+
+```SQL
+CREATE TABLE employee_new
+AS SELECT MAX(salary) AS salary_max FROM employee;
+```
+
+After data is inserted, query the new table.
+
+```SQL
+SELECT * FROM employee_new;
+
++------------+
+| salary_max |
++------------+
+|   10000    |
++------------+
+```
+
+Example 4: Synchronously query the `customer_id` and `first_name` columns in the table `customers` and create a new table `customers_new` based on the query result, and then insert the query result into the new table. Additionally, set the column names of the new table to `customer_id_new` and `first_name_new`. Also, build a bitmap index for the column `customer_id_new` in the new table.
+
+```SQL
+CREATE TABLE customers_new 
+(   customer_id_new,
+    first_name_new,
+    INDEX idx_bitmap_customer_id (customer_id_new) USING BITMAP
+) 
+AS SELECT customer_id,first_name FROM customers;
+```
+
+Example 5: Synchronously query a table `customers` and create a new table `customers_new` based on the query result, and then insert the query result into the new table. Additionally, specify the new table as a Primary Key table, and specify its sort key as `first_name` and `last_name`.
+
+```SQL
+CREATE TABLE customers_pk
+PRIMARY KEY (customer_id)
+ORDER BY (first_name,last_name)
+AS SELECT  * FROM customers;
+```
+
+Example 6: Use CTAS to create a Primary Key table. Note that the number of data rows in the Primary Key table may be less than that in the query result. It is because the [Primary Key](../../../table_design/table_types/primary_key_table.md) table only stores the most recent data row among a group of rows that have the same primary key.
+
+```SQL
+CREATE TABLE employee_new
+PRIMARY KEY(order_id)
+AS SELECT
+    order_list.order_id,
+    sum(goods.price) as total
+FROM order_list INNER JOIN goods ON goods.item_id1 = order_list.item_id2
+GROUP BY order_id;
+```
+
+Example 7: Synchronously query four tables, including `lineorder`, `customer`, `supplier`, and `part` and create a new table `lineorder_flat` based on the query result, and then insert the query result to the new table. Additionally, specify the partitioning method and bucketing method for the new table.
+
+```SQL
+CREATE TABLE lineorder_flat
+PARTITION BY RANGE(`LO_ORDERDATE`)
+(
+    START ("1993-01-01") END ("1999-01-01") EVERY (INTERVAL 1 YEAR)
+)
+DISTRIBUTED BY HASH(`LO_ORDERKEY`) AS SELECT
+    l.LO_ORDERKEY AS LO_ORDERKEY,
+    l.LO_LINENUMBER AS LO_LINENUMBER,
+    l.LO_CUSTKEY AS LO_CUSTKEY,
+    l.LO_PARTKEY AS LO_PARTKEY,
+    l.LO_SUPPKEY AS LO_SUPPKEY,
+    l.LO_ORDERDATE AS LO_ORDERDATE,
+    l.LO_ORDERPRIORITY AS LO_ORDERPRIORITY,
+    l.LO_SHIPPRIORITY AS LO_SHIPPRIORITY,
+    l.LO_QUANTITY AS LO_QUANTITY,
+    l.LO_EXTENDEDPRICE AS LO_EXTENDEDPRICE,
+    l.LO_ORDTOTALPRICE AS LO_ORDTOTALPRICE,
+    l.LO_DISCOUNT AS LO_DISCOUNT,
+    l.LO_REVENUE AS LO_REVENUE,
+    l.LO_SUPPLYCOST AS LO_SUPPLYCOST,
+    l.LO_TAX AS LO_TAX,
+    l.LO_COMMITDATE AS LO_COMMITDATE,
+    l.LO_SHIPMODE AS LO_SHIPMODE,
+    c.C_NAME AS C_NAME,
+    c.C_ADDRESS AS C_ADDRESS,
+    c.C_CITY AS C_CITY,
+    c.C_NATION AS C_NATION,
+    c.C_REGION AS C_REGION,
+    c.C_PHONE AS C_PHONE,
+    c.C_MKTSEGMENT AS C_MKTSEGMENT,
+    s.S_NAME AS S_NAME,
+    s.S_ADDRESS AS S_ADDRESS,
+    s.S_CITY AS S_CITY,
+    s.S_NATION AS S_NATION,
+    s.S_REGION AS S_REGION,
+    s.S_PHONE AS S_PHONE,
+    p.P_NAME AS P_NAME,
+    p.P_MFGR AS P_MFGR,
+    p.P_CATEGORY AS P_CATEGORY,
+    p.P_BRAND AS P_BRAND,
+    p.P_COLOR AS P_COLOR,
+    p.P_TYPE AS P_TYPE,
+    p.P_SIZE AS P_SIZE,
+    p.P_CONTAINER AS P_CONTAINER FROM lineorder AS l
+INNER JOIN customer AS c ON c.C_CUSTKEY = l.LO_CUSTKEY
+INNER JOIN supplier AS s ON s.S_SUPPKEY = l.LO_SUPPKEY
+INNER JOIN part AS p ON p.P_PARTKEY = l.LO_PARTKEY;
+```
+
+Example 8: Asynchronously query the table `order_detail` and create a new table `order_statistics` based on the query result, and then insert the query result into the new table.
+
+```plaintext
+SUBMIT TASK AS CREATE TABLE order_statistics AS SELECT COUNT(*) as count FROM order_detail;
+
++-------------------------------------------+-----------+
+| TaskName                                  | Status    |
++-------------------------------------------+-----------+
+| ctas-df6f7930-e7c9-11ec-abac-bab8ee315bf2 | SUBMITTED |
++-------------------------------------------+-----------+
+```
+
+Check information of the Task.
+
+```SQL
+SELECT * FROM INFORMATION_SCHEMA.tasks;
+
+-- Information of the Task
+
+TASK_NAME: ctas-df6f7930-e7c9-11ec-abac-bab8ee315bf2
+CREATE_TIME: 2022-06-14 14:07:06
+SCHEDULE: MANUAL
+DATABASE: default_cluster:test
+DEFINITION: CREATE TABLE order_statistics AS SELECT COUNT(*) as cnt FROM order_detail
+EXPIRE_TIME: 2022-06-17 14:07:06
+```
+
+Check the state of the TaskRun.
+
+```SQL
+SELECT * FROM INFORMATION_SCHEMA.task_runs;
+
+-- State of the TaskRun
+
+QUERY_ID: 37bd2b63-eba8-11ec-8d41-bab8ee315bf2
+TASK_NAME: ctas-df6f7930-e7c9-11ec-abac-bab8ee315bf2
+CREATE_TIME: 2022-06-14 14:07:06
+FINISH_TIME: 2022-06-14 14:07:07
+STATE: SUCCESS
+DATABASE: 
+DEFINITION: CREATE TABLE order_statistics AS SELECT COUNT(*) as cnt FROM order_detail
+EXPIRE_TIME: 2022-06-17 14:07:06
+ERROR_CODE: 0
+ERROR_MESSAGE: NULL
+```
+
+Query the new table when the state of the TaskRun is `SUCCESS`.
+
+```SQL
+SELECT * FROM order_statistics;
+```
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_LIKE.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_LIKE.md
new file mode 100644
index 00000000000000..c1d2d800be8d55
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_LIKE.md
@@ -0,0 +1,156 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE TABLE LIKE
+
+## Description
+
+Creates an identical empty table based on the definition of another table. The definition includes column definition, partitions, and table properties. You can copy an external table such as MySQL.
+
+v3.2 allows you to specify a different partitioning method, bucketing method, and properties for the new table than the source table.
+
+:::tip
+This operation requires the CREATE TABLE privilege on the database in which you want to create a table, and the `SELECT` privilege on the source table based on which to create a table.
+:::
+
+## Syntax
+
+- Syntax supported in versions earlier than v3.2.
+
+```sql
+CREATE [EXTERNAL] TABLE [IF NOT EXISTS] [database.]<table_name>
+LIKE [database.]<source_table_name>
+```
+
+- v3.2 supports specifying properties for the new table.
+
+```sql
+CREATE [TEMPORARY] [EXTERNAL] TABLE [IF NOT EXISTS] [database.]<table_name>
+[partition_desc]
+[distribution_desc]
+[PROPERTIES ("key" = "value",...)]
+LIKE [database.]<source_table_name>
+```
+
+## Parameters
+
+- `TEMPORARY`: Creates a temporary table. From v3.3.1, StarRocks supports creating temporary tables in the Default Catalog. For more information, see [Temporary Table](../../../table_design/StarRocks_table_design.md#temporary-table).
+- `database`: the database.
+- `table_name`: the name of the table you want to create. For the naming conventions, see [System limits](../../System_limit.md).
+- `source_table_name`: the name of the source table you want to copy.
+- - `partition_desc`: the partitioning method. For more information, see [CREATE TABLE](./CREATE_TABLE.md#partition_desc).
+- `distribution_desc`: the bucketing method. For more information, see [CREATE TABLE](./CREATE_TABLE.md#distribution_desc).
+- `PROPERTIES`: the properties of the table. All the table properties are supported. For more information, see [ALTER TABLE](ALTER_TABLE.md#modify-table-properties).
+
+## Examples
+
+Suppose there is a table `orders` in database `test1`.
+
+```sql
+create table orders (
+    dt date NOT NULL,
+    order_id bigint NOT NULL,
+    user_id int NOT NULL,
+    merchant_id int NOT NULL,
+    good_id int NOT NULL,
+    good_name string NOT NULL,
+    price int NOT NULL,
+    cnt int NOT NULL,
+    revenue int NOT NULL,
+    state tinyint NOT NULL
+) PRIMARY KEY (dt, order_id)
+PARTITION BY RANGE(`dt`) (
+    PARTITION p20210820 VALUES [('2021-08-20'), ('2021-08-21')),
+    PARTITION p20210821 VALUES [('2021-08-21'), ('2021-08-22')),
+    PARTITION p20210929 VALUES [('2021-09-29'), ('2021-09-30')),
+    PARTITION p20210930 VALUES [('2021-09-30'), ('2021-10-01'))
+) DISTRIBUTED BY HASH(order_id)
+PROPERTIES (
+    "replication_num" = "3",
+    "enable_persistent_index" = "true"
+);
+```
+
+Example 1: In database `test1`, create an empty table `order_1` that has the same table structure as `orders`.
+
+ ```sql
+CREATE TABLE test1.order_1 LIKE test1.orders;
+```
+
+```plaintext
+show create table order_1\G
+*************************** 1. row ***************************
+       Table: order_1
+Create Table: CREATE TABLE `order_1` (
+  `dt` date NOT NULL COMMENT "",
+  `order_id` bigint(20) NOT NULL COMMENT "",
+  `user_id` int(11) NOT NULL COMMENT "",
+  `merchant_id` int(11) NOT NULL COMMENT "",
+  `good_id` int(11) NOT NULL COMMENT "",
+  `good_name` varchar(65533) NOT NULL COMMENT "",
+  `price` int(11) NOT NULL COMMENT "",
+  `cnt` int(11) NOT NULL COMMENT "",
+  `revenue` int(11) NOT NULL COMMENT "",
+  `state` tinyint(4) NOT NULL COMMENT ""
+) ENGINE=OLAP 
+PRIMARY KEY(`dt`, `order_id`)
+PARTITION BY RANGE(`dt`)
+(PARTITION p20210820 VALUES [("2021-08-20"), ("2021-08-21")),
+PARTITION p20210821 VALUES [("2021-08-21"), ("2021-08-22")),
+PARTITION p20210929 VALUES [("2021-09-29"), ("2021-09-30")),
+PARTITION p20210930 VALUES [("2021-09-30"), ("2021-10-01")))
+DISTRIBUTED BY HASH(`order_id`)
+PROPERTIES (
+"replication_num" = "3",
+"in_memory" = "false",
+"enable_persistent_index" = "true",
+"replicated_storage" = "true",
+"compression" = "LZ4"
+);
+```
+
+Example 2: Create an empty table `order_2` based on `orders` and specify properties for `order_2`.
+
+```sql
+CREATE TABLE order_2
+PARTITION BY date_trunc('day',dt)
+DISTRIBUTED BY hash(dt)
+PROPERTIES ("replication_num" = "1")
+LIKE orders;
+```
+
+```plaintext
+show create table order_2\G
+*************************** 1. row ***************************
+       Table: order_2
+Create Table: CREATE TABLE `order_2` (
+  `dt` date NOT NULL COMMENT "",
+  `order_id` bigint(20) NOT NULL COMMENT "",
+  `user_id` int(11) NOT NULL COMMENT "",
+  `merchant_id` int(11) NOT NULL COMMENT "",
+  `good_id` int(11) NOT NULL COMMENT "",
+  `good_name` varchar(65533) NOT NULL COMMENT "",
+  `price` int(11) NOT NULL COMMENT "",
+  `cnt` int(11) NOT NULL COMMENT "",
+  `revenue` int(11) NOT NULL COMMENT "",
+  `state` tinyint(4) NOT NULL COMMENT ""
+) ENGINE=OLAP 
+PRIMARY KEY(`dt`, `order_id`)
+PARTITION BY RANGE(date_trunc('day', dt))
+()
+DISTRIBUTED BY HASH(`dt`)
+PROPERTIES (
+"replication_num" = "1",
+"in_memory" = "false",
+"enable_persistent_index" = "true",
+"replicated_storage" = "true",
+"compression" = "LZ4"
+);
+```
+
+Example 3: Create an empty table `table2` that has the same table structure as MySQL external table `table1`.
+
+```sql
+CREATE TABLE test1.table2 LIKE test1.table1
+```
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/DELETE.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/DELETE.md
new file mode 100644
index 00000000000000..22a39e642887f0
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/DELETE.md
@@ -0,0 +1,394 @@
+---
+displayed_sidebar: docs
+---
+
+# DELETE
+
+Deletes data rows from a table based on the specified conditions. The table can be a partitioned or non-partitioned table.
+
+For Duplicate Key tables, Aggregate tables, and Unique Key tables, you can delete data from specified partitions. From v2.3, Primary Key tables support complete `DELETE...WHERE` semantics, which allows you to delete data rows based on the primary key, any column, or the results of a subquery. From v3.0, StarRocks enriches the `DELETE...WHERE` semantics with multi-table joins and common table expressions (CTEs). If you need to join Primary Key tables with other tables in the database, you can reference these other tables in the USING clause or CTE.
+
+## Usage notes
+
+- You must have privileges on the table and database you want to perform DELETE.
+- Frequent DELETE operations are not recommended. If needed, perform such operations during off-peak hours.
+- The DELETE operation only deletes data in the table. The table remains. To drop the table, run [DROP TABLE](DROP_TABLE.md).
+- To prevent misoperations from deleting data in the entire table, you must specify the WHERE clause in the DELETE statement.
+- The deleted rows are not immediately cleaned. They are marked as "deleted" and will be temporarily saved in Segment. Physically, the rows are removed only after data version merge (compaction) is completed.
+- This operation also deletes data of the materialized views that reference this table.
+
+## Duplicate Key tables, Aggregate tables, and Unique Key tables
+
+### Syntax
+
+```SQL
+DELETE FROM  [<db_name>.]<table_name> [PARTITION <partition_name>]
+WHERE
+column_name1 op { value | value_list } [ AND column_name2 op { value | value_list } ...]
+```
+
+### Parameters
+
+| **Parameter**         | **Required** | **Description**                                                     |
+| :--------------- | :------- | :----------------------------------------------------------- |
+| `db_name`        | No       | The database to which the destination table belongs. If this parameter is not specified, the current database is used by default.      |
+| `table_name`     | Yes      | The table from which you want to delete data.   |
+| `partition_name` | No       | The partition from which you want to delete data.  |
+| `column_name`    | Yes      | The column you want to use as the DELETE condition. You can specify one or more columns.   |
+| `op`             | Yes      | The operator used in the DELETE condition. The supported operators are `=`, `>`, `<`, `>=`, `<=`, `!=`, `IN`, and `NOT IN`. |
+
+### Limits and usage notes
+
+- For Duplicate Key tables, you can use **any column** as the DELETE condition. For Aggregate tables and Unique Key tables, only **key columns** can be used as the DELETE condition.
+
+- The conditions that you specify must be in the AND relation. If you want to specify conditions in OR relation, you must specify the conditions in separate DELETE statements.
+
+- For Duplicate Key tables, Aggregate tables, and Unique Key tables, the DELETE statement does not support using subquery results as conditions.
+
+### Impacts
+
+After you execute the DELETE statement, the query performance of your cluster may deteriorate for a period of time (before compaction is completed). The degree of deterioration varies based on the number of conditions that you specify. A larger number of conditions indicates a higher degree of deterioration.
+
+### Examples
+
+#### Create a table and insert data
+
+The following example creates a partitioned Duplicate Key table.
+
+```SQL
+CREATE TABLE `my_table` (
+    `date` date NOT NULL,
+    `k1` int(11) NOT NULL COMMENT "",
+    `k2` varchar(65533) NULL DEFAULT "" COMMENT "")
+DUPLICATE KEY(`date`)
+PARTITION BY RANGE(`date`)
+(
+    PARTITION p1 VALUES [('2022-03-11'), ('2022-03-12')),
+    PARTITION p2 VALUES [('2022-03-12'), ('2022-03-13'))
+)
+DISTRIBUTED BY HASH(`date`)
+PROPERTIES
+("replication_num" = "3");
+
+INSERT INTO `my_table` VALUES
+('2022-03-11', 3, 'abc'),
+('2022-03-11', 2, 'acb'),
+('2022-03-11', 4, 'abc'),
+('2022-03-12', 2, 'bca'),
+('2022-03-12', 4, 'cba'),
+('2022-03-12', 5, 'cba');
+```
+
+#### Query data
+
+```plain
+select * from my_table order by date;
++------------+------+------+
+| date       | k1   | k2   |
++------------+------+------+
+| 2022-03-11 |    3 | abc  |
+| 2022-03-11 |    2 | acb  |
+| 2022-03-11 |    4 | abc  |
+| 2022-03-12 |    2 | bca  |
+| 2022-03-12 |    4 | cba  |
+| 2022-03-12 |    5 | cba  |
++------------+------+------+
+```
+
+#### Delete data
+
+##### Delete data from a specified partition
+
+Delete rows whose `k1` values are `3` from the `p1` partition.
+
+```plain
+DELETE FROM my_table PARTITION p1
+WHERE k1 = 3;
+
+-- The query result shows rows whose `k1` values are `3` are deleted.
+
+select * from my_table partition (p1);
++------------+------+------+
+| date       | k1   | k2   |
++------------+------+------+
+| 2022-03-11 |    2 | acb  |
+| 2022-03-11 |    4 | abc  |
++------------+------+------+
+```
+
+##### Delete data from a specified partition using AND
+
+Delete rows whose `k1` values are greater than or equal to `3` and whose `k2` values are `"abc"` from the `p1` partition.
+
+```plain
+DELETE FROM my_table PARTITION p1
+WHERE k1 >= 3 AND k2 = "abc";
+
+select * from my_table partition (p1);
++------------+------+------+
+| date       | k1   | k2   |
++------------+------+------+
+| 2022-03-11 |    2 | acb  |
++------------+------+------+
+```
+
+##### Delete data from all partitions
+
+Delete rows whose `k2` values are `"abc"` or `"cba"` from all partitions.
+
+```plain
+DELETE FROM my_table
+WHERE  k2 in ("abc", "cba");
+
+select * from my_table order by date;
++------------+------+------+
+| date       | k1   | k2   |
++------------+------+------+
+| 2022-03-11 |    2 | acb  |
+| 2022-03-12 |    2 | bca  |
++------------+------+------+
+```
+
+## Primary Key tables
+
+From v2.3, Primary Key tables support complete `DELETE...WHERE` semantics, which allows you to delete data rows based on the primary key, any column, or a subquery.
+
+### Syntax
+
+```SQL
+[ WITH <with_query> [, ...] ]
+DELETE FROM <table_name>
+[ USING <from_item> [, ...] ]
+[ WHERE <where_condition> ]
+```
+
+### Parameters
+
+|   **Parameter**   | **Required** | **Description**                                              |
+| :---------------: | :----------- | :----------------------------------------------------------- |
+|   `with_query`    | No           | One or more CTEs that can be referenced by name in a DELETE statement. CTEs are temporary result sets that can improve the readability of complex statements. |
+|   `table_name`    | Yes          | The table from which you want to delete data.                |
+|    `from_item`    | No           | One or more other tables in the database. These tables can be joined with the table being operated based on the condition specified in the WHERE clause. Based on the result set of the join query, StarRocks deletes the matched rows from the table being operated. For example, if the USING clause is `USING t1 WHERE t0.pk = t1.pk;`, StarRocks converts the table expression in the USING clause to `t0 JOIN t1 ON t0.pk=t1.pk;` when executing the DELETE statement. |
+| `where_condition` | Yes          | The condition based on which you want to delete rows. Only rows that meet the WHERE condition can be deleted. This parameter is required, because it helps prevent you from accidentally deleting the entire table. If you want to delete the entire table, you can use 'WHERE true'. |
+
+### Limits and usage notes
+
+- Primary Key tables do not support deleting data from a specified partition, for example, `DELETE FROM <table_name> PARTITION <partition_id> WHERE <where_condition>`.
+- The following comparison operators are supported: `=`, `>`, `<`, `>=`, `<=`, `!=`, `IN`, `NOT IN`.
+- The following logical operators are supported: `AND` and `OR`.
+- You cannot use the DELETE statement to run concurrent DELETE operations or to delete data at data loading. If you perform such operations, the atomicity, consistency, isolation, and durability (ACID) of transactions may not be ensured.
+
+### Examples
+
+#### Create a table and insert data
+
+Create a Primary Key table named `score_board`:
+
+```sql
+CREATE TABLE `score_board` (
+  `id` int(11) NOT NULL COMMENT "",
+  `name` varchar(65533) NULL DEFAULT "" COMMENT "",
+  `score` int(11) NOT NULL DEFAULT "0" COMMENT ""
+) ENGINE=OLAP
+PRIMARY KEY(`id`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`id`)
+PROPERTIES (
+"replication_num" = "3",
+"storage_format" = "DEFAULT",
+"enable_persistent_index" = "false"
+);
+
+INSERT INTO score_board VALUES
+(0, 'Jack', 21),
+(1, 'Bob', 21),
+(2, 'Stan', 21),
+(3, 'Sam', 22);
+```
+
+#### Query data
+
+Execute the following statement to insert data into the `score_board` table:
+
+```Plain
+select * from score_board;
++------+------+------+
+| id   | name | score|
++------+------+------+
+|    0 | Jack |   21 |
+|    1 | Bob  |   21 |
+|    2 | Stan |   21 |
+|    3 | Sam  |   22 |
++------+------+------+
+4 rows in set (0.00 sec)
+```
+
+#### Delete data
+
+##### Delete data by primary key
+
+You can specify the primary key in the DELETE statement, so StarRocks does not need to scan the entire table.
+
+Delete rows whose `id` values are `0` from the `score_board` table.
+
+```Plain
+DELETE FROM score_board WHERE id = 0;
+
+select * from score_board;
++------+------+------+
+| id   | name | score|
++------+------+------+
+|    1 | Bob  |   21 |
+|    2 | Stan |   21 |
+|    3 | Sam  |   22 |
++------+------+------+
+```
+
+##### Delete data by condition
+
+Example 1: Delete rows whose `score` values are `22` from the `score_board` table.
+
+```Plain
+DELETE FROM score_board WHERE score = 22;
+
+select * from score_board;
++------+------+------+
+| id   | name | score|
++------+------+------+
+|    0 | Jack |   21 |
+|    1 | Bob  |   21 |
+|    2 | Stan |   21 |
++------+------+------+
+```
+
+Example 2: Delete rows whose `score` values are less than `22` from the `score_board` table.
+
+```Plain
+DELETE FROM score_board WHERE score < 22;
+
+select * from score_board;
++------+------+------+
+| id   | name | score|
++------+------+------+
+|    3 | Sam  |   22 |
++------+------+------+
+```
+
+Example 3: Delete rows whose `score` values are less than `22` and whose `name` values are not `Bob` from the `score_board` table.
+
+```Plain
+DELETE FROM score_board WHERE score < 22 and name != "Bob";
+
+select * from score_board;
++------+------+------+
+| id   | name | score|
++------+------+------+
+|    1 | Bob  |   21 |
+|    3 | Sam  |   22 |
++------+------+------+
+2 rows in set (0.00 sec)
+```
+
+##### Delete data by subquery result
+
+You can nest one or more subqueries in the `DELETE` statement and use the subquery results as conditions.
+
+Before you delete data, execute the following statement to create another table named `users`:
+
+```SQL
+CREATE TABLE `users` (
+  `uid` int(11) NOT NULL COMMENT "",
+  `name` varchar(65533) NOT NULL COMMENT "",
+  `country` varchar(65533) NULL COMMENT ""
+) ENGINE=OLAP
+PRIMARY KEY(`uid`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`uid`)
+PROPERTIES (
+"replication_num" = "3",
+"storage_format" = "DEFAULT",
+"enable_persistent_index" = "false"
+);
+```
+
+Insert data into the `users` table:
+
+```SQL
+INSERT INTO users VALUES
+(0, "Jack", "China"),
+(2, "Stan", "USA"),
+(1, "Bob", "China"),
+(3, "Sam", "USA");
+```
+
+```plain
+select * from users;
++------+------+---------+
+| uid  | name | country |
++------+------+---------+
+|    0 | Jack | China   |
+|    1 | Bob  | China   |
+|    2 | Stan | USA     |
+|    3 | Sam  | USA     |
++------+------+---------+
+4 rows in set (0.00 sec)
+```
+
+Nest a subquery to find the rows whose `country` values are `China` from the `users` table, and delete the rows, which have the same `name` values as the rows returned from the subquery, from the `score_board` table. You can use one of the following methods to fulfill the purpose:
+
+- Method 1
+
+```plain
+DELETE FROM score_board
+WHERE name IN (select name from users where country = "China");
+    
+select * from score_board;
++------+------+------+
+| id   | name | score|
++------+------+------+
+|    2 | Stan |   21 |
+|    3 | Sam  |   22 |
++------+------+------+
+```
+
+- Method 2
+
+```plain
+DELETE FROM score_board
+WHERE EXISTS (select name from users
+              where score_board.name = users.name and country = "China");
+    
+select * from score_board;
++------+------+-------+
+| id   | name | score |
++------+------+-------+
+|    2 | Stan |    21 |
+|    3 | Sam  |    22 |
++------+------+-------+
+2 rows in set (0.00 sec)
+```
+
+##### Delete data by using multi-table join or CTE
+
+To delete all movies produced by the producer "foo", you can execute the following statement:
+
+```SQL
+DELETE FROM films USING producers
+WHERE producer_id = producers.id
+    AND producers.name = 'foo';
+```
+
+You can also use a CTE to rewrite the above statement to improve readability.
+
+```SQL
+WITH foo_producers as (
+    SELECT * from producers
+    where producers.name = 'foo'
+)
+DELETE FROM films USING foo_producers
+WHERE producer_id = foo_producers.id;
+```
+
+## References
+
+[SHOW DELETE](SHOW_DELETE.md): queries historical DELETE operations that were successfully performed on Duplicate Key tables, Aggregate tables, and Unique Key tables.
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md
new file mode 100644
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--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md
@@ -0,0 +1,118 @@
+---
+displayed_sidebar: docs
+---
+
+# DESC
+
+## Description
+
+You can use the statement to perform the following operations:
+
+- View the schema of a table stored in your StarRocks cluster, along with the type of the [sort key](../../../table_design/indexes/Prefix_index_sort_key.md) and [materialized view](../../../using_starrocks/Materialized_view.md) of the table.
+- View the schema of a table stored in the following external data sources, such as Apache Hive™. Note that you can perform this operation only in StarRocks 2.4 and later versions.
+
+## Syntax
+
+```SQL
+DESC[RIBE] [catalog_name.][db_name.]table_name [ALL];
+```
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                              |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| catalog_name  | No           | The name of the internal catalog or an external catalog. <ul><li>If you set the value of the parameter to the name of the internal catalog, which is `default_catalog`, you can view the schema of the table stored in your StarRocks cluster. </li><li>If you set the value of the parameter to the name of an external catalog, you can view the schema of the table stored in the external data source.</li></ul> |
+| db_name       | No           | The database name.                                           |
+| table_name    | Yes          | The table name.                                              |
+| ALL           | No           | <ul><li>If this keyword is specified, you can view the type of the sort key, materialized view, and schema of a table stored in your StarRocks cluster. If this keyword is not specified, you only view the table schema. </li><li>Do not specify this keyword when you view the schema of a table stored in an external data source.</li></ul> |
+
+## Output
+
+```Plain
++-----------+---------------+-------+------+------+-----+---------+-------+
+| IndexName | IndexKeysType | Field | Type | Null | Key | Default | Extra |
++-----------+---------------+-------+------+------+-----+---------+-------+
+```
+
+The following table describes the parameters returned by this statement.
+
+| **Parameter** | **Description**                                              |
+| ------------- | ------------------------------------------------------------ |
+| IndexName     | The table name. If you view the schema of a table stored in an external data source, this parameter is not returned. |
+| IndexKeysType | The type of the sort key of the table. If you view the schema of a table stored in an external data source, this parameter is not returned. |
+| Field         | The column name.                                             |
+| Type          | The data type of the column.                                 |
+| Null          | Whether the column values can be NULL. <ul><li>`yes`: indicates the values can be NULL. </li><li>`no`: indicates the values cannot be NULL. </li></ul>|
+| Key           | Whether the column is used as the sort key. <ul><li>`true`: indicates the column is used as the sort key. </li><li>`false`: indicates the column is not used as the sort key. </li></ul>|
+| Default       | The default value for the data type of the column. If the data type does not have a default value, a NULL is returned. |
+| Extra         | <ul><li>If you see the schema of a table stored in your StarRocks cluster, this field displays the following information about the column: <ul><li>The aggregate function used by the column, such as `SUM` and `MIN`. </li><li>Whether a bloom filter index is created on the column. If so, the value of `Extra` is `BLOOM_FILTER`. </li></ul></li><li>If you see the schema of a table stored in external data sources, this field displays whether the column is the partition column. If the column is the partition column, the value of `Extra` is `partition key`. </li></ul>|
+
+> Note: For information about how a materialized view is displayed in the output, see Example 2.
+
+## Examples
+
+Example 1: View the schema of `example_table` stored in your StarRocks cluster.
+
+```SQL
+DESC example_table;
+```
+
+Or
+
+```SQL
+DESC default_catalog.example_db.example_table;
+```
+
+The output of the preceding statements is as follows.
+
+```Plain
++-------+---------------+------+-------+---------+-------+
+| Field | Type          | Null | Key   | Default | Extra |
++-------+---------------+------+-------+---------+-------+
+| k1    | TINYINT       | Yes  | true  | NULL    |       |
+| k2    | DECIMAL(10,2) | Yes  | true  | 10.5    |       |
+| k3    | CHAR(10)      | Yes  | false | NULL    |       |
+| v1    | INT           | Yes  | false | NULL    |       |
++-------+---------------+------+-------+---------+-------+
+```
+
+Example 2: View the schema, type of the sort key, and materialized view of `sales_records` stored in your StarRocks cluster. In the following example, one materialized view `store_amt` is created based on `sales_records`.
+
+```Plain
+DESC db1.sales_records ALL;
+
++---------------+---------------+-----------+--------+------+-------+---------+-------+
+| IndexName     | IndexKeysType | Field     | Type   | Null | Key   | Default | Extra |
++---------------+---------------+-----------+--------+------+-------+---------+-------+
+| sales_records | DUP_KEYS      | record_id | INT    | Yes  | true  | NULL    |       |
+|               |               | seller_id | INT    | Yes  | true  | NULL    |       |
+|               |               | store_id  | INT    | Yes  | true  | NULL    |       |
+|               |               | sale_date | DATE   | Yes  | false | NULL    | NONE  |
+|               |               | sale_amt  | BIGINT | Yes  | false | NULL    | NONE  |
+|               |               |           |        |      |       |         |       |
+| store_amt     | AGG_KEYS      | store_id  | INT    | Yes  | true  | NULL    |       |
+|               |               | sale_amt  | BIGINT | Yes  | false | NULL    | SUM   |
++---------------+---------------+-----------+--------+------+-------+---------+-------+
+```
+
+Example 3: View the schema of `hive_table` stored in your Hive cluster.
+
+```Plain
+DESC hive_catalog.hive_db.hive_table;
+
++-------+----------------+------+-------+---------+---------------+ 
+| Field | Type           | Null | Key   | Default | Extra         | 
++-------+----------------+------+-------+---------+---------------+ 
+| id    | INT            | Yes  | false | NULL    |               | 
+| name  | VARCHAR(65533) | Yes  | false | NULL    |               | 
+| date  | DATE           | Yes  | false | NULL    | partition key | 
++-------+----------------+------+-------+---------+---------------+
+```
+
+## References
+
+- [CREATE DATABASE](../Database/CREATE_DATABASE.md)
+- [SHOW CREATE DATABASE](../Database/SHOW_CREATE_DATABASE.md)
+- [USE](../Database/USE.md)
+- [SHOW DATABASES](../Database/SHOW_DATABASES.md)
+- [DROP DATABASE](../Database/DROP_DATABASE.md)
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/DROP_INDEX.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/DROP_INDEX.md
new file mode 100644
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+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/DROP_INDEX.md
@@ -0,0 +1,21 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP INDEX
+
+## Description
+
+This statement is used to drop a specified index on a table. Currently, only bitmap index is supported in this version.
+
+:::tip
+
+This operation requires the ALTER privilege on the target table. You can follow the instructions in [GRANT](../account-management/GRANT.md) to grant this privilege.
+
+:::
+
+Syntax:
+
+```sql
+DROP INDEX index_name ON [db_name.]table_name
+```
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md
new file mode 100644
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+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md
@@ -0,0 +1,49 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP TABLE
+
+## Description
+
+This statement is used to delete a table.
+
+## Syntax
+
+```sql
+DROP [TEMPORARY] TABLE [IF EXISTS] [db_name.]table_name [FORCE]
+```
+
+Note:
+
+- After a table is dropped, you can use the [RECOVER](../backup_restore/RECOVER.md) statement to restore the table within a specified period (1 day by default).
+- If DROP Table FORCE is executed, the table will be deleted directly and cannot be recovered without checking whether there are unfinished activities in the database. Generally, this operation is not recommended.
+- Once dropped, temporary tables cannot be restored using RECOVER.
+
+## Examples
+
+1. Drop a table.
+
+    ```sql
+    DROP TABLE my_table;
+    ```
+
+2. If it exists, then drop the table on the specified database.
+
+    ```sql
+    DROP TABLE IF EXISTS example_db.my_table;
+    ```
+
+3. Force to drop the table and clear its data on disk.
+
+    ```sql
+    DROP TABLE my_table FORCE;
+    ```
+
+## References
+
+- [CREATE TABLE](CREATE_TABLE.md)
+- [SHOW TABLES](SHOW_TABLES.md)
+- [SHOW CREATE TABLE](SHOW_CREATE_TABLE.md)
+- [ALTER TABLE](ALTER_TABLE.md)
+- [SHOW ALTER TABLE](SHOW_ALTER.md)
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/REFRESH_EXTERNAL_TABLE.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/REFRESH_EXTERNAL_TABLE.md
new file mode 100644
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+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/REFRESH_EXTERNAL_TABLE.md
@@ -0,0 +1,101 @@
+---
+displayed_sidebar: docs
+---
+
+# REFRESH EXTERNAL TABLE
+
+## Description
+
+Updates metadata cached in StarRocks. The metadata is from tables in data lakes. This statement is used in the following scenarios:
+
+- **External table**: When using a Hive external table or Hudi external table to query data in Apache Hive™ or Apache Hudi, you can execute this statement to update the metadata of a Hive table or Hudi table cached in StarRocks.
+- **External catalog**: When using a [Hive catalog](../../../data_source/catalog/hive_catalog.md), [Hudi catalog](../../../data_source/catalog/hudi_catalog.md), [Delta Lake catalog](../../../data_source/catalog/deltalake_catalog.md), or [MaxCompute Catalog](../../../data_source/catalog/maxcompute_catalog.md) (since v3.3) to query data in the corresponding data source, you can execute this statement to update the metadata cached in StarRocks.
+
+## Basic concepts
+
+- **Hive external table**: is created and stored in StarRocks. You can use it to query Hive data.
+- **Hudi external table**: is created and stored in StarRocks. You can use it to query Hudi data.
+- **Hive table**: is created and stored in Hive.
+- **Hudi table**: is created and stored in Hudi.
+
+## Syntaxes and parameters
+
+The following describes the syntaxes and parameters based on different cases:
+
+- External table
+
+    ```SQL
+    REFRESH EXTERNAL TABLE table_name 
+    [PARTITION ('partition_name', ...)]
+    ```
+
+    | **Parameter**  | **Required** | **Description**                                              |
+    | -------------- | ------------ | ------------------------------------------------------------ |
+    | table_name     | Yes          | The name of a Hive external table or Hudi external table.    |
+    | partition_name | No           | The names of the partitions of a Hive table or Hudi table. Specifying this parameter updates the metadata of the partitions of the Hive table and Hudi table cached in StarRocks. |
+
+- External catalog
+
+    ```SQL
+    REFRESH EXTERNAL TABLE [external_catalog.][db_name.]table_name
+    [PARTITION ('partition_name', ...)]
+    ```
+
+    | **Parameter**    | **Required** | **Description**                                              |
+    | ---------------- | ------------ | ------------------------------------------------------------ |
+    | external_catalog | No           | The name of the external catalog, which supports Hive, Hudi, Delta Lake, and MaxCompute (since v3.3) catalogs.                  |
+    | db_name          | No           | The name of the database where the destination table resides. |
+    | table_name       | Yes          | The name of the table.                    |
+    | partition_name   | No           | The names of the partitions. Specifying this parameter updates the metadata of the partitions of the destination table cached in StarRocks. |
+
+## Usage notes
+
+Only users who have the `ALTER_PRIV` privilege can execute this statement to update the metadata of Hive tables and Hudi tables cached in StarRocks.
+
+## Examples
+
+Usage examples in different cases are as follows:
+
+### External table
+
+Example 1: Update the cached metadata of the corresponding Hive table in StarRocks by specifying the external table `hive1`.
+
+```SQL
+REFRESH EXTERNAL TABLE hive1;
+```
+
+Example 2: Update the cached metadata of the partitions of the corresponding Hudi table in StarRocks by specifying the external table `hudi1` and the partitions in that table.
+
+```SQL
+REFRESH EXTERNAL TABLE hudi1
+PARTITION ('date=2022-12-20', 'date=2022-12-21');
+```
+
+### External catalog
+
+Example 1: Update the metadata of `hive_table` cached in StarRocks.
+
+```SQL
+REFRESH EXTERNAL TABLE hive_catalog.hive_db.hive_table;
+```
+
+Or
+
+```SQL
+USE hive_catalog.hive_db;
+REFRESH EXTERNAL TABLE hive_table;
+```
+
+Example 2: Update the metadata of the second-level partition `p2` in `hive_table` cached in StarRocks.
+
+```SQL
+USE hive_catalog.hive_db;
+REFRESH EXTERNAL TABLE hive_table PARTITION ('p1=${date}/p2=${hour}');
+```
+
+Example 3: Update the metadata of the partitions of `hudi_table` cached in StarRocks.
+
+```SQL
+REFRESH EXTERNAL TABLE hudi_catalog.hudi_db.hudi_table
+PARTITION ('date=2022-12-20', 'date=2022-12-21');
+```
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/SELECT.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SELECT.md
new file mode 100644
index 00000000000000..599da086ddd6e8
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SELECT.md
@@ -0,0 +1,1138 @@
+---
+displayed_sidebar: docs
+---
+
+# SELECT
+
+## Description
+
+Queries data from one or more tables, views, or materialized views. The SELECT statement generally consists of the following clauses:
+
+- [WITH](#with)
+- [WHERE and operators](#where-and-operators)
+- [GROUP BY](#group-by)
+- [HAVING](#having)
+- [UNION](#union)
+- [INTERSECT](#intersect)
+- [EXCEPT/MINUS](#exceptminus)
+- [ORDER BY](#order-by)
+- [LIMIT](#limit)
+- [OFFSET](#offset)
+- [Joins](#join)
+- [Subqueries](#subquery)
+- [DISTINCT](#distinct)
+- [Alias](#alias)
+
+SELECT can work as an independent statement or a clause nested in other statements. The output of the SELECT clause can be used as the input of other statements.
+
+StarRocks' query statement basically conforms to the SQL92 standard. Here is a brief description of the supported SELECT usage.
+
+> **NOTE**
+>
+> To query data from tables, views, or materialized views in a StarRocks internal table, you must have the SELECT privilege on these objects. To query data from tables, views, or materialized views in an external data source, you must have the USAGE privilege on the corresponding external catalog.
+
+### WITH
+
+A clause that can be added before a SELECT statement to define an alias for a complex expression that is referenced multiple times inside SELECT.
+
+Similar to CRATE VIEW, but the table and column names defined in the clause do not persist after the query ends and do not conflict with names in the actual table or VIEW.
+
+The benefits of using a WITH clause are:
+
+Convenient and easy to maintain, reducing duplication within queries.
+
+ It is easier to read and understand SQL code by abstracting the most complex parts of a query into separate blocks.
+
+Examples:
+
+```sql
+-- Define one subquery at the outer level, and another at the inner level as part of the
+-- initial stage of the UNION ALL query.
+
+with t1 as (select 1),t2 as (select 2)
+select * from t1 union all select * from t2;
+```
+
+### Join
+
+Join operations combine data from two or more tables and then return a result set of some columns from some of them.
+
+StarRocks supports self joins, cross joins, inner joins, outer joins, semi joins, and anti joins. Outer joins include left joins, right joins, and full joins.
+
+Syntax:
+
+```sql
+SELECT select_list FROM
+table_or_subquery1 [INNER] JOIN table_or_subquery2 |
+table_or_subquery1 {LEFT [OUTER] | RIGHT [OUTER] | FULL [OUTER]} JOIN table_or_subquery2 |
+table_or_subquery1 {LEFT | RIGHT} SEMI JOIN table_or_subquery2 |
+table_or_subquery1 {LEFT | RIGHT} ANTI JOIN table_or_subquery2 |
+[ ON col1 = col2 [AND col3 = col4 ...] |
+USING (col1 [, col2 ...]) ]
+[other_join_clause ...]
+[ WHERE where_clauses ]
+```
+
+```sql
+SELECT select_list FROM
+table_or_subquery1, table_or_subquery2 [, table_or_subquery3 ...]
+[other_join_clause ...]
+WHERE
+col1 = col2 [AND col3 = col4 ...]
+```
+
+```sql
+SELECT select_list FROM
+table_or_subquery1 CROSS JOIN table_or_subquery2
+[other_join_clause ...]
+[ WHERE where_clauses ]
+```
+
+#### Self Join
+
+StarRocks supports self-joins, which are self-joins and self-joins. For example, different columns of the same table are joined.
+
+There is actually no special syntax to identify self-join. The conditions on both sides of a join in a self-join come from the same table.
+
+We need to assign them different aliases.
+
+Examples:
+
+```sql
+SELECT lhs.id, rhs.parent, lhs.c1, rhs.c2 FROM tree_data lhs, tree_data rhs WHERE lhs.id = rhs.parent;
+```
+
+#### Cross Join
+
+Cross join can produce a lot of results, so cross join should be used with caution.
+
+Even if you need to use cross join, you need to use filter conditions and ensure that fewer results are returned. Example:
+
+```sql
+SELECT * FROM t1, t2;
+
+SELECT * FROM t1 CROSS JOIN t2;
+```
+
+#### Inner Join
+
+Inner join is the most well-known and commonly used join. Returns results from columns requested by two similar tables, joined if the columns of both tables contain the same value.
+
+If a column name of both tables is the same, we need to use the full name (in the form of table_name.column_name) or alias the column name.
+
+Examples:
+
+The following three queries are equivalent.
+
+```sql
+SELECT t1.id, c1, c2 FROM t1, t2 WHERE t1.id = t2.id;
+
+SELECT t1.id, c1, c2 FROM t1 JOIN t2 ON t1.id = t2.id;
+
+SELECT t1.id, c1, c2 FROM t1 INNER JOIN t2 ON t1.id = t2.id;
+```
+
+#### Outer Join
+
+Outer join returns the left or right table or all rows of both. If there is no matching data in another table, set it to NULL. Example:
+
+```sql
+SELECT * FROM t1 LEFT OUTER JOIN t2 ON t1.id = t2.id;
+
+SELECT * FROM t1 RIGHT OUTER JOIN t2 ON t1.id = t2.id;
+
+SELECT * FROM t1 FULL OUTER JOIN t2 ON t1.id = t2.id;
+```
+
+#### Equivalent and unequal join
+
+Usually, users use the most equal join, which requires the operator of the join condition to be an equal sign.
+
+Unequal join can be used on join conditions!=, Equal sign. Unequal joins produce a large number of results and may exceed the memory limit during calculation.
+
+Use with caution. Unequal join only supports inner join. Example:
+
+```sql
+SELECT t1.id, c1, c2 FROM t1 INNER JOIN t2 ON t1.id = t2.id;
+
+SELECT t1.id, c1, c2 FROM t1 INNER JOIN t2 ON t1.id > t2.id;
+```
+
+#### Semi Join
+
+Left semi join returns only the rows in the left table that match the data in the right table, regardless of how many rows match the data in the right table.
+
+This row of the left table is returned at most once. Right semi join works similarly, except that the data returned is a right table.
+
+Examples:
+
+```sql
+SELECT t1.c1, t1.c2, t1.c2 FROM t1 LEFT SEMI JOIN t2 ON t1.id = t2.id;
+```
+
+#### Anti Join
+
+Left anti join only returns rows from the left table that do not match the right table.
+
+Right anti join reverses this comparison, returning only rows from the right table that do not match the left table. Example:
+
+```sql
+SELECT t1.c1, t1.c2, t1.c2 FROM t1 LEFT ANTI JOIN t2 ON t1.id = t2.id;
+```
+
+#### Equi-join and Non-equi-join
+
+The various joins supported by StarRocks can be classified as equi-joins and non-equi-joins depending on the join conditions specified in the joins.
+
+| **Equi-joins**         | Self joins, cross joins, inner joins, outer joins, semi joins, and anti joins |
+| -------------------------- | ------------------------------------------------------------ |
+| **Non-equi-joins** | cross joins, inner joins, left semi joins, left anti joins, and outer joins   |
+
+- Equi-joins
+  
+  An equi-join uses a join condition in which two join items are combined by the `=` operator. Example: `a JOIN b ON a.id = b.id`.
+
+- Non-equi-joins
+  
+  A non-equi-join uses a join condition in which two join items are combined by a comparison operator such as `<`, `<=`, `>`, `>=`, or `<>`. Example: `a JOIN b ON a.id < b.id`. Non-equi-joins run slower than equi-joins. We recommend that you exercise caution when you use non-equi-joins.
+
+  The following two examples show how to run non-equi-joins:
+
+  ```SQL
+  SELECT t1.id, c1, c2 
+  FROM t1 
+  INNER JOIN t2 ON t1.id < t2.id;
+    
+  SELECT t1.id, c1, c2 
+  FROM t1 
+  LEFT JOIN t2 ON t1.id > t2.id;
+  ```
+
+### ORDER BY
+
+The ORDER BY clause of a SELECT statement sorts the result set by comparing the values from one or more columns.
+
+ORDER BY is a time- and resource-consuming operation because all the results must be sent to one node for merging before the results can be sorted. Sorting consumes more memory resources than a query without ORDER BY.
+
+Therefore, if you only need the first `N` results from the sorted result set, you can use the LIMIT clause, which reduces memory usage and network overhead. If the LIMIT clause is not specified, the first 65535 results are returned by default.
+
+Syntax:
+
+```sql
+ORDER BY <column_name> 
+    [ASC | DESC]
+    [NULLS FIRST | NULLS LAST]
+```
+
+`ASC` specifies that the results should be returned in ascending order. `DESC` specifies that the results should be returned in descending order. If the order is not specified, ASC (ascending) is the default. Example:
+
+```sql
+select * from big_table order by tiny_column, short_column desc;
+```
+
+Sort order for NULL values: `NULLS FIRST` indicates that NULL values should be returned before non-NULL values. `NULLS LAST` indicates that NULL values should be returned after non-NULL values.
+
+Examples:
+
+```sql
+select  *  from  sales_record  order by  employee_id  nulls first;
+```
+
+### GROUP BY
+
+The GROUP BY clause is often used with aggregate functions such as COUNT(), SUM(), AVG(), MIN(), and MAX().
+
+The column specified by GROUP BY will not participate in the aggregation operation. The GROUP BY clause can be added with the Having clause to filter the results produced by the aggregate function.
+
+Examples:
+
+```sql
+select tiny_column, sum(short_column)
+from small_table 
+group by tiny_column;
+```
+
+```plain text
++-------------+---------------------+
+| tiny_column |  sum('short_column')|
++-------------+---------------------+
+|      1      |        2            |
+|      2      |        1            |
++-------------+---------------------+
+```
+
+#### Syntax
+
+  ```sql
+  SELECT ...
+  FROM ...
+  [ ... ]
+  GROUP BY [
+      , ... |
+      GROUPING SETS [, ...] (  groupSet [ , groupSet [ , ... ] ] ) |
+      ROLLUP(expr  [ , expr [ , ... ] ]) |
+      CUBE(expr  [ , expr [ , ... ] ])
+      ]
+  [ ... ]
+  ```
+
+#### Parameters
+
+  `groupSet` represents a set composed of columns, aliases or expressions in the select list.  `groupSet ::= { ( expr  [ , expr [ , ... ] ] )}`
+
+  `expr`  indicates the column, alias or expression in the select list.
+
+#### Note
+
+StarRocks supports syntax like PostgreSQL. The syntax examples are as follows:
+
+  ```sql
+  SELECT a, b, SUM( c ) FROM tab1 GROUP BY GROUPING SETS ( (a, b), (a), (b), ( ) );
+  SELECT a, b,c, SUM( d ) FROM tab1 GROUP BY ROLLUP(a,b,c)
+  SELECT a, b,c, SUM( d ) FROM tab1 GROUP BY CUBE(a,b,c)
+  ```
+
+  `ROLLUP(a,b,c)` is equivalent to the following`GROUPING SETS` statement:
+
+  ```sql
+  GROUPING SETS (
+  (a,b,c),
+  ( a, b ),
+  ( a),
+  ( )
+  )
+  ```
+
+  `CUBE ( a, b, c )`  is equivalent to the following`GROUPING SETS` statement:
+
+  ```sql
+  GROUPING SETS (
+  ( a, b, c ),
+  ( a, b ),
+  ( a,    c ),
+  ( a       ),
+  (    b, c ),
+  (    b    ),
+  (       c ),
+  (         )
+  )
+  ```
+
+#### Examples
+
+  The following is an example of actual data:
+
+  ```plain text
+  SELECT * FROM t;
+  +------+------+------+
+  | k1   | k2   | k3   |
+  +------+------+------+
+  | a    | A    |    1 |
+  | a    | A    |    2 |
+  | a    | B    |    1 |
+  | a    | B    |    3 |
+  | b    | A    |    1 |
+  | b    | A    |    4 |
+  | b    | B    |    1 |
+  | b    | B    |    5 |
+  +------+------+------+
+  8 rows in set (0.01 sec)
+
+  SELECT k1, k2, SUM(k3) FROM t GROUP BY GROUPING SETS ( (k1, k2), (k2), (k1), ( ) );
+  +------+------+-----------+
+  | k1   | k2   | sum(`k3`) |
+  +------+------+-----------+
+  | b    | B    |         6 |
+  | a    | B    |         4 |
+  | a    | A    |         3 |
+  | b    | A    |         5 |
+  | NULL | B    |        10 |
+  | NULL | A    |         8 |
+  | a    | NULL |         7 |
+  | b    | NULL |        11 |
+  | NULL | NULL |        18 |
+  +------+------+-----------+
+  9 rows in set (0.06 sec)
+
+  > SELECT k1, k2, GROUPING_ID(k1,k2), SUM(k3) FROM t GROUP BY GROUPING SETS ((k1, k2), (k1), (k2), ());
+  +------+------+---------------+----------------+
+  | k1   | k2   | grouping_id(k1,k2) | sum(`k3`) |
+  +------+------+---------------+----------------+
+  | a    | A    |             0 |              3 |
+  | a    | B    |             0 |              4 |
+  | a    | NULL |             1 |              7 |
+  | b    | A    |             0 |              5 |
+  | b    | B    |             0 |              6 |
+  | b    | NULL |             1 |             11 |
+  | NULL | A    |             2 |              8 |
+  | NULL | B    |             2 |             10 |
+  | NULL | NULL |             3 |             18 |
+  +------+------+---------------+----------------+
+  9 rows in set (0.02 sec)
+  ```
+
+GROUP BY `GROUPING SETS` ｜ `CUBE` ｜ `ROLLUP` is an extension of the GROUP BY clause. It can realize the aggregation of groups of multiple sets in a GROUP BY clause. The result is equivalent to the UNION operation of multiple corresponding GROUP BY clauses.
+
+GROUP BY clause is a special case of GROUP BY GROUPING SETS containing only one element. For example, the GROUPING SETS statement:
+
+  ```sql
+  SELECT a, b, SUM( c ) FROM tab1 GROUP BY GROUPING SETS ( (a, b), (a), (b), ( ) );
+  ```
+
+  The query result is equivalent to:
+
+  ```sql
+  SELECT a, b, SUM( c ) FROM tab1 GROUP BY a, b
+  UNION
+  SELECT a, null, SUM( c ) FROM tab1 GROUP BY a
+  UNION
+  SELECT null, b, SUM( c ) FROM tab1 GROUP BY b
+  UNION
+  SELECT null, null, SUM( c ) FROM tab1
+  ```
+
+  `GROUPING(expr)` indicates whether a column is an aggregate column. If it is an aggregate column, it is 0, otherwise it is 1.
+
+  `GROUPING_ID(expr  [ , expr [ , ... ] ])` is similar to GROUPING. GROUPING_ ID calculates the bitmap value of a column list according to the specified column order, and each bit is the value of GROUPING.
+  
+  GROUPING_ID() function returns the decimal value of the bit vector.
+
+### HAVING
+
+The HAVING clause does not filter row data in a table, but filters the results of aggregate functions.
+
+Generally speaking, HAVING is used with aggregate functions (such as COUNT(), SUM(), AVG(), MIN(), MAX()) and GROUP BY clauses.
+
+Examples:
+
+```sql
+select tiny_column, sum(short_column) 
+from small_table 
+group by tiny_column 
+having sum(short_column) = 1;
+```
+
+```plain text
++-------------+---------------------+
+|tiny_column  | sum('short_column') |
++-------------+---------------------+
+|         2   |        1            |
++-------------+---------------------+
+
+1 row in set (0.07 sec)
+```
+
+```sql
+select tiny_column, sum(short_column) 
+from small_table 
+group by tiny_column 
+having tiny_column > 1;
+```
+
+```plain text
++-------------+---------------------+
+|tiny_column  | sum('short_column') |
++-------------+---------------------+
+|      2      |          1          |
++-------------+---------------------+
+
+1 row in set (0.07 sec)
+```
+
+### LIMIT
+
+LIMIT clauses are used to limit the maximum number of rows returned. Setting the maximum number of rows returned can help StarRocks optimize memory usage.
+
+This clause is mainly used in the following scenarios:
+
+Returns the result of the top-N query.
+
+Think about what's included in the table below.
+
+The size of the query result set needs to be limited because of the large amount of data in the table or because the where clause does not filter too much data.
+
+Instructions for use: The value of the LIMIT clause must be a numeric literal constant.
+
+Examples:
+
+```plain text
+mysql> select tiny_column from small_table limit 1;
+
++-------------+
+|tiny_column  |
++-------------+
+|     1       |
++-------------+
+
+1 row in set (0.02 sec)
+```
+
+```plain text
+mysql> select tiny_column from small_table limit 10000;
+
++-------------+
+|tiny_column  |
++-------------+
+|      1      |
+|      2      |
++-------------+
+
+2 rows in set (0.01 sec)
+```
+
+### OFFSET
+
+The OFFSET clause causes the result set to skip the first few rows and return the following results directly.
+
+The result set defaults to start at line 0, so offset 0 and no offset return the same results.
+
+Generally speaking, OFFSET clauses need to be used with ORDER BY and LIMIT clauses to be valid.
+
+Examples:
+
+```plain text
+mysql> select varchar_column from big_table order by varchar_column limit 3;
+
++----------------+
+| varchar_column | 
++----------------+
+|    beijing     | 
+|    chongqing   | 
+|    tianjin     | 
++----------------+
+
+3 rows in set (0.02 sec)
+```
+
+```plain text
+mysql> select varchar_column from big_table order by varchar_column limit 1 offset 0;
+
++----------------+
+|varchar_column  |
++----------------+
+|     beijing    |
++----------------+
+
+1 row in set (0.01 sec)
+```
+
+```plain text
+mysql> select varchar_column from big_table order by varchar_column limit 1 offset 1;
+
++----------------+
+|varchar_column  |
++----------------+
+|    chongqing   | 
++----------------+
+
+1 row in set (0.01 sec)
+```
+
+```plain text
+mysql> select varchar_column from big_table order by varchar_column limit 1 offset 2;
+
++----------------+
+|varchar_column  |
++----------------+
+|     tianjin    |     
++----------------+
+
+1 row in set (0.02 sec)
+```
+
+Note: It is allowed to use offset syntax without order by, but offset does not make sense at this time.
+
+In this case, only the limit value is taken, and the offset value is ignored. So without order by.
+
+Offset exceeds the maximum number of rows in the result set and is still a result. It is recommended that users use offset with order by.
+
+### UNION
+
+Combines the result of multiple queries.
+
+**Syntax:**
+
+```sql
+query_1 UNION [DISTINCT | ALL] query_2
+```
+
+- DISTINCT (default) returns only unique rows. UNION is equivalent to UNION DISTINCT.
+- ALL combines all rows, including duplicates. Since de-duplication is memory intensive, queries using UNION ALL are faster and less memory-consuming. For better performance, use UNION ALL.
+
+> **NOTE**
+>
+> Each query statement must return the same number of columns and the columns must have compatible data types.
+
+**Examples:**
+
+Create tables `select1` and `select2`.
+
+```SQL
+CREATE TABLE select1(
+    id          INT,
+    price       INT
+    )
+DISTRIBUTED BY HASH(id);
+
+INSERT INTO select1 VALUES
+    (1,2),
+    (1,2),
+    (2,3),
+    (5,6),
+    (5,6);
+
+CREATE TABLE select2(
+    id          INT,
+    price       INT
+    )
+DISTRIBUTED BY HASH(id);
+
+INSERT INTO select2 VALUES
+    (2,3),
+    (3,4),
+    (5,6),
+    (7,8);
+```
+
+Example 1: Return all IDs in the two tables, including duplicates.
+
+```Plaintext
+mysql> (select id from select1) union all (select id from select2) order by id;
+
++------+
+| id   |
++------+
+|    1 |
+|    1 |
+|    2 |
+|    2 |
+|    3 |
+|    5 |
+|    5 |
+|    5 |
+|    7 |
++------+
+11 rows in set (0.02 sec)
+```
+
+Example 2: Return all the unique IDs in the two tables. The following two statements are equivalent.
+
+```Plaintext
+mysql> (select id from select1) union (select id from select2) order by id;
+
++------+
+| id   |
++------+
+|    1 |
+|    2 |
+|    3 |
+|    5 |
+|    7 |
++------+
+6 rows in set (0.01 sec)
+
+mysql> (select id from select1) union distinct (select id from select2) order by id;
++------+
+| id   |
++------+
+|    1 |
+|    2 |
+|    3 |
+|    5 |
+|    7 |
++------+
+5 rows in set (0.02 sec)
+```
+
+Example 3: Return the first three IDs among all the unique IDs in the two tables. The following two statements are equivalent.
+
+```SQL
+mysql> (select id from select1) union distinct (select id from select2)
+order by id
+limit 3;
+++------+
+| id   |
++------+
+|    1 |
+|    2 |
+|    3 |
++------+
+4 rows in set (0.11 sec)
+
+mysql> select * from (select id from select1 union distinct select id from select2) as t1
+order by id
+limit 3;
++------+
+| id   |
++------+
+|    1 |
+|    2 |
+|    3 |
++------+
+3 rows in set (0.01 sec)
+```
+
+### **INTERSECT**
+
+Calculates the intersection of the results of multiple queries, that is, the results that appear in all the result sets. This clause returns only unique rows among the result sets. The ALL keyword is not supported.
+
+**Syntax:**
+
+```SQL
+query_1 INTERSECT [DISTINCT] query_2
+```
+
+> **NOTE**
+>
+> - INTERSECT is equivalent to INTERSECT DISTINCT.
+> - Each query statement must return the same number of columns and the columns must have compatible data types.
+
+**Examples:**
+
+The two tables in UNION  are used.
+
+Return distinct `(id, price)` combinations that are common to both tables. The following two statements are equivalent.
+
+```Plaintext
+mysql> (select id, price from select1) intersect (select id, price from select2)
+order by id;
+
++------+-------+
+| id   | price |
++------+-------+
+|    2 |     3 |
+|    5 |     6 |
++------+-------+
+
+mysql> (select id, price from select1) intersect distinct (select id, price from select2)
+order by id;
+
++------+-------+
+| id   | price |
++------+-------+
+|    2 |     3 |
+|    5 |     6 |
++------+-------+
+```
+
+### **EXCEPT/MINUS**
+
+Returns distinct results of the left-hand query that do not exist in the right-hand query. EXCEPT is equivalent to MINUS.
+
+**Syntax:**
+
+```SQL
+query_1 {EXCEPT | MINUS} [DISTINCT] query_2
+```
+
+> **NOTE**
+>
+> - EXCEPT is equivalent to EXCEPT DISTINCT. The ALL keyword is not supported.
+> - Each query statement must return the same number of columns and the columns must have compatible data types.
+
+**Examples:**
+
+The two tables in UNION  are used.
+
+Return distinct `(id, price)` combinations in `select1` that cannot be found in `select2`.
+
+```Plaintext
+mysql> (select id, price from select1) except (select id, price from select2)
+order by id;
++------+-------+
+| id   | price |
++------+-------+
+|    1 |     2 |
++------+-------+
+
+mysql> (select id, price from select1) minus (select id, price from select2)
+order by id;
++------+-------+
+| id   | price |
++------+-------+
+|    1 |     2 |
++------+-------+
+```
+
+### DISTINCT
+
+The DISTINCT keyword deduplicates the result set. Example:
+
+```SQL
+-- Returns the unique values from one column.
+select distinct tiny_column from big_table limit 2;
+
+-- Returns the unique combinations of values from multiple columns.
+select distinct tiny_column, int_column from big_table limit 2;
+```
+
+DISTINCT can be used with aggregate functions (usually count functions), and count (distinct) is used to calculate how many different combinations are contained on one or more columns.
+
+```SQL
+-- Counts the unique values from one column.
+select count(distinct tiny_column) from small_table;
+```
+
+```plain text
++-------------------------------+
+| count(DISTINCT 'tiny_column') |
++-------------------------------+
+|             2                 |
++-------------------------------+
+1 row in set (0.06 sec)
+```
+
+```SQL
+-- Counts the unique combinations of values from multiple columns.
+select count(distinct tiny_column, int_column) from big_table limit 2;
+```
+
+StarRocks supports multiple aggregate functions using distinct at the same time.
+
+```SQL
+-- Count the unique value from multiple aggregation function separately.
+select count(distinct tiny_column, int_column), count(distinct varchar_column) from big_table;
+```
+
+### Subquery
+
+Subqueries are categorized into two types in terms of relevance:
+
+- A noncorrelated subquery obtains its results independently of its outer query.
+- A correlated subquery requires values from its outer query.
+
+#### Noncorrelated subquery
+
+Noncorrelated subqueries support [NOT] IN and EXISTS.
+
+Example:
+
+```sql
+SELECT x FROM t1 WHERE x [NOT] IN (SELECT y FROM t2);
+
+SELECT * FROM t1 WHERE (x,y) [NOT] IN (SELECT x,y FROM t2 LIMIT 2);
+
+SELECT x FROM t1 WHERE EXISTS (SELECT y FROM t2 WHERE y = 1);
+```
+
+From v3.0 onwards, you can specify multiple fields in the WHERE clause of `SELECT... FROM... WHERE... [NOT] IN`, for example, `WHERE (x,y)` in the second SELECT statement.
+
+#### Correlated subquery
+
+Related subqueries support [NOT] IN and [NOT] EXISTS.
+
+Example:
+
+```sql
+SELECT * FROM t1 WHERE x [NOT] IN (SELECT a FROM t2 WHERE t1.y = t2.b);
+
+SELECT * FROM t1 WHERE [NOT] EXISTS (SELECT a FROM t2 WHERE t1.y = t2.b);
+```
+
+Subqueries also support scalar quantum queries. It can be divided into irrelevant scalar quantum query, related scalar quantum query and scalar quantum query as parameters of the general function.
+
+Examples:
+
+1. Uncorrelated scalar quantum query with predicate = sign. For example, output information about the person with the highest wage.
+
+    ```sql
+    SELECT name FROM table WHERE salary = (SELECT MAX(salary) FROM table);
+    ```
+
+2. Uncorrelated scalar quantum queries with predicates `>`, `<` etc. For example, output information about people who are paid more than average.
+
+    ```sql
+    SELECT name FROM table WHERE salary > (SELECT AVG(salary) FROM table);
+    ```
+
+3. Related scalar quantum queries. For example, output the highest salary information for each department.
+
+    ```sql
+    SELECT name FROM table a WHERE salary = (SELECT MAX(salary) FROM table b WHERE b.Department= a.Department);
+    ```
+
+4. Scalar quantum queries are used as parameters of ordinary functions.
+
+    ```sql
+    SELECT name FROM table WHERE salary = abs((SELECT MAX(salary) FROM table));
+    ```
+
+### Where and Operators
+
+SQL operators are a series of functions used for comparison and are widely used in where clauses of select statements.
+
+#### Arithmetic operator
+
+Arithmetic operators usually appear in expressions that contain left, right, and most often left operands
+
+**+and-**: can be used as a unit or as a 2-ary operator. When used as a unit operator, such as +1, -2.5 or -col_ name, which means the value is multiplied by +1 or -1.
+
+So the cell operator + returns an unchanged value, and the cell operator - changes the symbol bits of that value.
+
+Users can overlay two cell operators, such as +5 (returning a positive value), -+2 or +2 (returning a negative value), but users cannot use two consecutive - signs.
+
+Because--is interpreted as a comment in the following statement (when a user can use two-signs, a space or parenthesis is required between the two-signs, such as-(-2) or - -2, which actually results in + 2).
+
+When + or - is a binary operator, such as 2+2, 3+1.5, or col1+col2, it means that the left value is added or subtracted from the right value. Both left and right values must be numeric types.
+
+**and/**: represent multiplication and division, respectively. The operands on both sides must be data types. When two numbers are multiplied.
+
+Smaller operands may be promoted if needed (e.g., SMALLINT to INT or BIGINT), and the result of the expression will be promoted to the next larger type.
+
+For example, TINYINT multiplied by INT will produce a BIGINT type of result. When two numbers are multiplied, both operands and expression results are interpreted as DOUBLE types to avoid loss of precision.
+
+If the user wants to convert the result of the expression to another type, it needs to be converted using the CAST function.
+
+**%**: Modulation operator. Returns the remainder of the left operand divided by the right operand. Both left and right operands must be integers.
+
+**&, |and ^**: The bitwise operator returns the result of bitwise AND, bitwise OR, bitwise XOR operations on two operands. Both operands require an integer type.
+
+If the types of the two operands of a bitwise operator are inconsistent, the operands of a smaller type are promoted to the operands of a larger type, and the corresponding bitwise operations are performed.
+
+Multiple arithmetic operators can appear in an expression, and the user can enclose the corresponding arithmetic expression in parentheses. Arithmetic operators usually do not have corresponding mathematical functions to express the same functions as arithmetic operators.
+
+For example, we don't have the MOD() function to represent the% operator. Conversely, mathematical functions do not have corresponding arithmetic operators. For example, the power function POW() does not have a corresponding ** exponentiation operator.
+
+ Users can find out which arithmetic functions we support through the Mathematical Functions section.
+
+#### Between Operator
+
+In a where clause, expressions may be compared with both upper and lower bounds. If the expression is greater than or equal to the lower bound and less than or equal to the upper bound, the result of the comparison is true.
+
+Syntax:
+
+```sql
+expression BETWEEN lower_bound AND upper_bound
+```
+
+Data type: Usually an expression evaluates to a numeric type, which also supports other data types. If you must ensure that both the lower and upper bounds are comparable characters, you can use the cast() function.
+
+ Instructions for use: If the operand is of type string, note that a long string starting with an upper bound will not match the upper bound, which is larger than the upper bound. For example, "between'A'and'M' will not match 'MJ'.
+
+ If you need to make sure the expression works correctly, you can use functions such as upper(), lower(), substr(), trim().
+
+Example:
+
+```sql
+select c1 from t1 where month between 1 and 6;
+```
+
+#### Comparison operators
+
+Comparison operators are used to compare two values. `=`, `!=`, `>=` apply to all data types.
+
+The `<>` and `!=` operators are equivalent, which indicate that two values are not equal.
+
+#### In Operator
+
+The In operator compares to the VALUE collection and returns TRUE if it can match any of the elements in the collection.
+
+Parameters and VALUE collections must be comparable. All expressions using the IN operator can be written as equivalent comparisons connected with OR, but the syntax of IN is simpler, more precise, and easier for StarRocks to optimize.
+
+Examples:
+
+```sql
+select * from small_table where tiny_column in (1,2);
+```
+
+#### Like Operator
+
+This operator is used to compare to a string. ''matches a single character,'%' matches multiple characters. The parameter must match the complete string. Typically, placing'%'at the end of a string is more practical.
+
+Examples:
+
+```plain text
+mysql> select varchar_column from small_table where varchar_column like 'm%';
+
++----------------+
+|varchar_column  |
++----------------+
+|     milan      |
++----------------+
+
+1 row in set (0.02 sec)
+```
+
+```plain
+mysql> select varchar_column from small_table where varchar_column like 'm____';
+
++----------------+
+| varchar_column | 
++----------------+
+|    milan       | 
++----------------+
+
+1 row in set (0.01 sec)
+```
+
+#### Logical Operator
+
+Logical operators return a BOOL value, including unit and multiple operators, each of which handles parameters that are expressions that return BOOL values. Supported operators are:
+
+AND: 2-ary operator, the AND operator returns TRUE if the parameters on the left and right are both calculated as TRUE.
+
+OR: 2-ary operator that returns TRUE if one of the parameters on the left and right is calculated as TRUE. If both parameters are FALSE, the OR operator returns FALSE.
+
+NOT: Unit operator, the result of inverting an expression. If the parameter is TRUE, the operator returns FALSE; If the parameter is FALSE, the operator returns TRUE.
+
+Examples:
+
+```plain text
+mysql> select true and true;
+
++-------------------+
+| (TRUE) AND (TRUE) | 
++-------------------+
+|         1         | 
++-------------------+
+
+1 row in set (0.00 sec)
+```
+
+```plain text
+mysql> select true and false;
+
++--------------------+
+| (TRUE) AND (FALSE) | 
++--------------------+
+|         0          | 
++--------------------+
+
+1 row in set (0.01 sec)
+```
+
+```plain text
+mysql> select true or false;
+
++-------------------+
+| (TRUE) OR (FALSE) | 
++-------------------+
+|        1          | 
++-------------------+
+
+1 row in set (0.01 sec)
+```
+
+```plain text
+mysql> select not true;
+
++----------+
+| NOT TRUE | 
++----------+
+|     0    | 
++----------+
+
+1 row in set (0.01 sec)
+```
+
+#### Regular Expression Operator
+
+Determines whether the regular expression is matched. Using POSIX standard regular expressions,'^'matches the first part of the string,'$' matches the end of the string.
+
+"." matches any single character, "*" matches zero or more options, "+" matches one or more options, "?" means greedy representation, and so on. Regular expressions need to match complete values, not just parts of strings.
+
+If you want to match the middle part, the front part of the regular expression can be written as'^. 'or'.'. '^'and'$' are usually omitted. The RLIKE operator and the REGEXP operator are synonyms.
+
+The'|'operator is an optional operator. Regular expressions on either side of'|' only need to satisfy one side condition. The'|'operator and regular expressions on both sides usually need to be enclosed in ().
+
+Examples:
+
+```plain text
+mysql> select varchar_column from small_table where varchar_column regexp '(mi|MI).*';
+
++----------------+
+| varchar_column | 
++----------------+
+|     milan      |       
++----------------+
+
+1 row in set (0.01 sec)
+```
+
+```plain text
+mysql> select varchar_column from small_table where varchar_column regexp 'm.*';
+
++----------------+
+| varchar_column | 
++----------------+
+|     milan      |  
++----------------+
+
+1 row in set (0.01 sec)
+```
+
+### Alias
+
+When you write the names of tables, columns, or expressions that contain columns in a query, you can assign them an alias. Aliases are usually shorter and better to remember than original names.
+
+When an alias is needed, you can simply add an AS clause after the table, column, and expression names in the select list or from list. The AS keyword is optional. You can also specify aliases directly after the original name without using AS.
+
+If an alias or other identifier has the same name as an internal [StarRocks keyword](../keywords.md), you need to enclose the name in a pair of backticks, for example, `rank`.
+
+Aliases are case-sensitive, but column aliases and expression aliases are not case-sensitive.
+
+Examples:
+
+```sql
+select tiny_column as name, int_column as sex from big_table;
+
+select sum(tiny_column) as total_count from big_table;
+
+select one.tiny_column, two.int_column from small_table one, <br/> big_table two where one.tiny_column = two.tiny_column;
+```
+
+### PIVOT
+
+The PIVOT operation is an advanced feature in SQL that allows you to transform rows into columns in a table, which is particularly useful for creating pivot tables. This comes in handy when dealing with database reports or analytics, especially when you need to summarize or categorize data for presentation.
+
+Actually, the PIVOT is a syntax sugar, which can simplify the writing of the query statement like `sum(case when ... then ... end)`.
+
+#### Syntax
+
+```sql
+pivot:
+SELECT ...
+FROM ...
+PIVOT (
+  aggregate_function(<expr>) [[AS] alias] [, aggregate_function(<expr>) [[AS] alias] ...]
+  FOR <pivot_column>
+  IN (<pivot_value>)
+)
+
+pivot_column:
+<column_name> 
+| (<column_name> [, <column_name> ...])
+
+pivot_value:
+<literal> [, <literal> ...]
+| (<literal>, <literal> ...) [, (<literal>, <literal> ...)]
+```
+
+#### Parameters
+
+In a PIVOT operation, you need to specify several key components:
+
+- aggregate_function(): An aggregate function such as SUM, AVG, COUNT, etc., used to summarize the data.
+- alias: An alias for the aggregated result, making the outcome more understandable.
+- FOR pivot_column: Specifies the column name on which the row-to-column transformation will be performed.
+- IN (pivot_value): Specifies the specific values of the pivot_column that will be transformed into columns.
+
+#### Examples
+
+```sql
+create table t1 (c0 int, c1 int, c2 int, c3 int);
+SELECT * FROM t1 PIVOT (SUM(c1) AS sum_c1, AVG(c2) AS avg_c2 FOR c3 IN (1, 2, 3, 4, 5));
+-- The result is equivalent to the following query:
+SELECT SUM(CASE WHEN c3 = 1 THEN c1 ELSE NULL END) AS sum_c1_1,
+       AVG(CASE WHEN c3 = 1 THEN c2 ELSE NULL END) AS avg_c2_1,
+       SUM(CASE WHEN c3 = 2 THEN c1 ELSE NULL END) AS sum_c1_2,
+       AVG(CASE WHEN c3 = 2 THEN c2 ELSE NULL END) AS avg_c2_2,
+       SUM(CASE WHEN c3 = 3 THEN c1 ELSE NULL END) AS sum_c1_3,
+       AVG(CASE WHEN c3 = 3 THEN c2 ELSE NULL END) AS avg_c2_3,
+       SUM(CASE WHEN c3 = 4 THEN c1 ELSE NULL END) AS sum_c1_4,
+       AVG(CASE WHEN c3 = 4 THEN c2 ELSE NULL END) AS avg_c2_4,
+       SUM(CASE WHEN c3 = 5 THEN c1 ELSE NULL END) AS sum_c1_5,
+       AVG(CASE WHEN c3 = 5 THEN c2 ELSE NULL END) AS avg_c2_5
+FROM t1
+GROUP BY c0;
+```
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_ALTER.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_ALTER.md
new file mode 100644
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--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_ALTER.md
@@ -0,0 +1,69 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW ALTER TABLE
+
+## Description
+
+Shows the execution of the ongoing ALTER TABLE operations, including:
+
+- Modify columns.
+- Optimize table schema (from v3.2), including modifying the bucketing method and the number of buckets.
+- Create and delete the rollup index.
+
+## Syntax
+
+- Show the execution of operations of modifying columns or optimizing table schema.
+
+    ```sql
+    SHOW ALTER TABLE { COLUMN | OPTIMIZE } [FROM db_name] [WHERE TableName|CreateTime|FinishTime|State] [ORDER BY] [LIMIT]
+    ```
+
+- Show the execution of operations of adding or deleting the rollup index.
+
+    ```sql
+    SHOW ALTER TABLE ROLLUP [FROM db_name]
+    ```
+
+## Parameters
+
+- `{COLUMN ｜ OPTIMIZE | ROLLUP}`:
+
+  - If `COLUMN` is specified, this statement shows operations of modifying columns.
+  - If `OPTIMIZE` is specified, this statement shows operations of optimizing table structure.
+  - If `ROLLUP` is specified, this statement shows operations of adding or deleting the rollup index.
+
+- `db_name`: optional. If `db_name` is not specified, the current database is used by default.
+
+## Examples
+
+1. Show the execution of operations of modifying columns, optimizing table schema, and creating or deleting the rollup index in the current database.
+
+    ```sql
+    SHOW ALTER TABLE COLUMN;
+    SHOW ALTER TABLE OPTIMIZE;
+    SHOW ALTER TABLE ROLLUP;
+    ```
+
+2. Show the execution of operations related to modifying columns, optimizing table schema, and creating or deleting the rollup index in a specified database.
+
+    ```sql
+    SHOW ALTER TABLE COLUMN FROM example_db;
+    SHOW ALTER TABLE OPTIMIZE FROM example_db;
+    SHOW ALTER TABLE ROLLUP FROM example_db;
+    ```
+
+3. Show the execution of the most recent operation of modifying columns or optimizing table schema in a specified table.
+
+    ```sql
+    SHOW ALTER TABLE COLUMN WHERE TableName = "table1" ORDER BY CreateTime DESC LIMIT 1;
+    SHOW ALTER TABLE OPTIMIZE WHERE TableName = "table1" ORDER BY CreateTime DESC LIMIT 1; 
+    ```
+
+## References
+
+- [CREATE TABLE](CREATE_TABLE.md)
+- [ALTER TABLE](ALTER_TABLE.md)
+- [SHOW TABLES](SHOW_TABLES.md)
+- [SHOW CREATE TABLE](SHOW_CREATE_TABLE.md)
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md
new file mode 100644
index 00000000000000..6199821e5a72a8
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md
@@ -0,0 +1,141 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW CREATE TABLE
+
+Returns the CREATE TABLE statement that was used to create a given table.
+
+> **NOTE**
+>
+> In versions earlier than v3.0, the SHOW CREATE TABLE statement requires you to have the `SELECT_PRIV` privilege on the table. Since v3.0, the SHOW CREATE TABLE statement requires you to have the `SELECT` privilege on the table.
+
+Since v3.0, you can use the SHOW CREATE TABLE statement to view the CREATE TABLE statements of the tables that are managed by an external catalog and are stored in Apache Hive™, Apache Iceberg, Apache Hudi, or Delta Lake.
+
+Since v2.5.7, StarRocks can automatically set the number of buckets (BUCKETS) when you create a table or add a partition. You no longer need to manually set the number of buckets. For detailed information, see [set the number of buckets](../../../table_design/Data_distribution.md#set-the-number-of-buckets).
+
+- If you specified the number of buckets when creating a table, the output of SHOW CREATE TABLE will display the number of buckets.
+- If you did not specify the number of buckets when creating a table, the output of SHOW CREATE TABLE will not display the number of buckets. You can run [SHOW PARTITIONS](SHOW_PARTITIONS.md) to view the number of buckets for each partition.
+
+In versions earlier than v2.5.7, you are required to set the number of buckets when creating a table. Therefore, SHOW CREATE TABLE displays the number of buckets by default.
+
+## Syntax
+
+```SQL
+SHOW CREATE TABLE [db_name.]table_name
+```
+
+## Parameters
+
+| **Parameter** | **Required** | **Description**                                              |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| db_name       | No           | The database name. If this parameter is not specified, the CREATE TABLE statement of a given table in your current database is returned by default. |
+| table_name    | Yes          | The table name.                                              |
+
+## Output
+
+```Plain
++-----------+----------------+
+| Table     | Create Table   |                                               
++-----------+----------------+
+```
+
+The following table describes the parameters returned by this statement.
+
+| **Parameter** | **Description**                          |
+| ------------- | ---------------------------------------- |
+| Table         | The table name.                          |
+| Create Table  | The CREATE TABLE statement of the table. |
+
+## Examples
+
+### Bucket number is not specified
+
+Create a table named `example_table` with no bucket number specified in DISTRIBUTED BY.
+
+```SQL
+CREATE TABLE example_table
+(
+    k1 TINYINT,
+    k2 DECIMAL(10, 2) DEFAULT "10.5",
+    v1 CHAR(10) REPLACE,
+    v2 INT SUM
+)
+ENGINE = olap
+AGGREGATE KEY(k1, k2)
+COMMENT "my first starrocks table"
+DISTRIBUTED BY HASH(k1);
+```
+
+Run SHOW CREATE TABLE to display the CREATE TABLE statement of `example_table`. No bucket number is displayed in DISTRIBUTED BY. Note that if you did not specify PROPERTIES when you create the table, the default properties are displayed in the output of SHOW CREATE TABLE.
+
+```Plain
+SHOW CREATE TABLE example_table\G
+*************************** 1. row ***************************
+       Table: example_table
+Create Table: CREATE TABLE `example_table` (
+  `k1` tinyint(4) NULL COMMENT "",
+  `k2` decimal64(10, 2) NULL DEFAULT "10.5" COMMENT "",
+  `v1` char(10) REPLACE NULL COMMENT "",
+  `v2` int(11) SUM NULL COMMENT ""
+) ENGINE=OLAP 
+AGGREGATE KEY(`k1`, `k2`)
+COMMENT "my first starrocks table"
+DISTRIBUTED BY HASH(`k1`)
+PROPERTIES (
+"replication_num" = "3",
+"in_memory" = "false",
+"enable_persistent_index" = "false",
+"replicated_storage" = "true",
+"compression" = "LZ4"
+);
+```
+
+### Bucket number is specified
+
+Create a table named `example_table1` with bucket number set to 10 in DISTRIBUTED BY.
+
+```SQL
+CREATE TABLE example_table1
+(
+    k1 TINYINT,
+    k2 DECIMAL(10, 2) DEFAULT "10.5",
+    v1 CHAR(10) REPLACE,
+    v2 INT SUM
+)
+ENGINE = olap
+AGGREGATE KEY(k1, k2)
+COMMENT "my first starrocks table"
+DISTRIBUTED BY HASH(k1) BUCKETS 10;
+```
+
+Run SHOW CREATE TABLE to display the CREATE TABLE statement of `example_table`. The bucket number (`BUCKETS 10`) is displayed in DISTRIBUTED BY. Note that if you did not specify PROPERTIES when you create the table, the default properties are displayed in the output of SHOW CREATE TABLE.
+
+```plain
+SHOW CREATE TABLE example_table1\G
+*************************** 1. row ***************************
+       Table: example_table1
+Create Table: CREATE TABLE `example_table1` (
+  `k1` tinyint(4) NULL COMMENT "",
+  `k2` decimal64(10, 2) NULL DEFAULT "10.5" COMMENT "",
+  `v1` char(10) REPLACE NULL COMMENT "",
+  `v2` int(11) SUM NULL COMMENT ""
+) ENGINE=OLAP 
+AGGREGATE KEY(`k1`, `k2`)
+COMMENT "my first starrocks table"
+DISTRIBUTED BY HASH(`k1`) BUCKETS 10 
+PROPERTIES (
+"replication_num" = "3",
+"in_memory" = "false",
+"enable_persistent_index" = "false",
+"replicated_storage" = "true",
+"compression" = "LZ4"
+);
+```
+
+## References
+
+- [CREATE TABLE](CREATE_TABLE.md)
+- [SHOW TABLES](SHOW_TABLES.md)
+- [ALTER TABLE](ALTER_TABLE.md)
+- [DROP TABLE](DROP_TABLE.md)
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_DELETE.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_DELETE.md
new file mode 100644
index 00000000000000..77d71229ff1128
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_DELETE.md
@@ -0,0 +1,41 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW DELETE
+
+## Description
+
+Queries historical DELETE operations that were successfully performed on Duplicate Key, Unique Key, and Aggregate tables in a specified database. For more information about data deletion, see [DELETE](DELETE.md).
+
+Note that this command cannot be used to query DELETE operations that were performed on Primary Key tables.
+
+## Syntax
+
+```sql
+SHOW DELETE [FROM <db_name>]
+```
+
+`db_name`: the database name, optional. If this parameter is not specified, the current database is used by default.
+
+Return fields:
+
+- `TableName`: the table from which data is deleted.
+- `PartitionName`: the partition from which data is deleted. If the table is a non-partitioned table, `*` is displayed.
+- `CreateTime`: the time when the DELETE task was created.
+- `DeleteCondition`: the specified DELETE condition.
+- `State`: the status of the DELETE task.
+
+## Examples
+
+Show all historical DELETE operations of `database`.
+
+```sql
+SHOW DELETE FROM database;
+
++------------+---------------+---------------------+-----------------+----------+
+| TableName  | PartitionName | CreateTime          | DeleteCondition | State    |
++------------+---------------+---------------------+-----------------+----------+
+| mail_merge | *             | 2023-03-14 10:39:03 | name EQ "Peter" | FINISHED |
++------------+---------------+---------------------+-----------------+----------+
+```
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_DYNAMIC_PARTITION_TABLES.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_DYNAMIC_PARTITION_TABLES.md
new file mode 100644
index 00000000000000..dbc46319bfa2c4
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_DYNAMIC_PARTITION_TABLES.md
@@ -0,0 +1,40 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW DYNAMIC PARTITION TABLES
+
+## Description
+
+This statement is used to display the status of all the partitioned tables for which dynamic partitioning properties are configured in a database.
+
+## Syntax
+
+```sql
+SHOW DYNAMIC PARTITION TABLES FROM <db_name>
+```
+
+This statement returns the following fields:
+
+- TableName: the name of the table.
+- Enable: whether dynamic partitioning is enabled.
+- TimeUnit: the time granularity for the partitions.
+- Start: the starting offset of dynamic partitioning.
+- End: the end offset of dynamic partitioning.
+- Prefix: the prefix of the partition name.
+- Buckets: the number of buckets per partition.
+- ReplicationNum: the number of replicas for the table.
+- StartOf
+- LastUpdateTime: the time when the table was last updated.
+- LastSchedulerTime: the time when data in the table was last scheduled.
+- State: the status of the table.
+- LastCreatePartitionMsg: the message for the latest partition creation operation.
+- LastDropPartitionMsg: the message for the latest partition dropping operation.
+
+## Examples
+
+Display the status of all the partitioned tables for which dynamic partitioning properties are configured in `db_test`.
+
+```sql
+SHOW DYNAMIC PARTITION TABLES FROM db_test;
+```
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_FULL_COLUMNS.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_FULL_COLUMNS.md
new file mode 100644
index 00000000000000..b7ac419d42759a
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_FULL_COLUMNS.md
@@ -0,0 +1,29 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW FULL COLUMNS
+
+## Description
+
+This statement is used to show content in columns from specified tables.
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```sql
+SHOW FULL COLUMNS FROM <tbl_name>
+```
+
+## Examples
+
+1. View column content from specified tables.  
+
+    ```sql
+    SHOW FULL COLUMNS FROM tbl;
+    ```
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_INDEX.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_INDEX.md
new file mode 100644
index 00000000000000..e7f032d084b930
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_INDEX.md
@@ -0,0 +1,31 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW INDEX
+
+## Description
+
+This statement is used to show information related to index in a table. It currently only supports bitmap index.
+
+:::tip
+
+This operation does not require privileges.
+
+:::
+
+## Syntax
+
+```sql
+SHOW INDEX[ES] FROM [db_name.]table_name [FROM database]
+Or
+SHOW KEY[S] FROM [db_name.]table_name [FROM database]
+```
+
+## Examples
+
+1. Show all indexes under the specified table_name:
+
+    ```sql
+    SHOW INDEX FROM example_db.table_name;
+    ```
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md
new file mode 100644
index 00000000000000..eca9ada42bbb47
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md
@@ -0,0 +1,100 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW PARTITIONS
+
+## Description
+
+Displays partition information, including common partitions and [temporary partitions](../../../table_design/Temporary_partition.md).
+
+## Syntax
+
+```sql
+SHOW [TEMPORARY] PARTITIONS FROM [db_name.]table_name [WHERE] [ORDER BY] [LIMIT]
+```
+
+> NOTE
+>
+> This syntax only supports StarRocks tables (`"ENGINE" = "OLAP"`).
+> Since v3.0, this operation requires the SELECT privilege on the specified table. For v2.5 and earlier versions, this operation requires the SELECT__PRIV privilege on the specified table.
+
+## Description of return fields
+
+```plaintext
++-------------+---------------+----------------+---------------------+--------------------+--------+--------------+-------+--------------------+---------+----------------+---------------+---------------------+--------------------------+----------+------------+----------+
+| PartitionId | PartitionName | VisibleVersion | VisibleVersionTime  | VisibleVersionHash | State  | PartitionKey | Range | DistributionKey    | Buckets | ReplicationNum | StorageMedium | CooldownTime        | LastConsistencyCheckTime | DataSize | IsInMemory | RowCount |
++-------------+---------------+----------------+---------------------+--------------------+--------+--------------+-------+--------------------+---------+----------------+---------------+---------------------+--------------------------+----------+------------+----------+
+```
+
+| **Field**                | **Description**                                              |
+| ------------------------ | ------------------------------------------------------------ |
+| PartitionId              | The ID of the partition.                                |
+| PartitionName            | The name of the partition.                                   |
+| VisibleVersion           | The version number of the last successful load transaction. The version number increases by 1 with each successful load transaction. |
+| VisibleVersionTime       | The timestamp of the last successful load transaction.       |
+| VisibleVersionHash       | The hash value for the version number of the last successful load transaction. |
+| State                    | The status of the partition. Fixed value: `Normal`.           |
+| PartitionKey             | The partition key that consists of one or more partition columns. |
+| Range                    | The range of the partition, which is a right half-open interval. |
+| DistributionKey          | The bucket key of hash bucketing.                            |
+| Buckets                  | The number of buckets for the partition.                     |
+| ReplicationNum           | The number of replicas per tablet in the partition.        |
+| StorageMedium            | The storage medium to store the data in the partition. The value `HHD` indicates hard disk drives, and the value `SSD` indicates solid-state drives. |
+| CooldownTime             | The cooldown time for data in the partition. If the initial storage medium is SSD, the storage medium is switched from SSD to HDD after the time specified by this parameter. Format: "yyyy-MM-dd HH:mm:ss". |
+| LastConsistencyCheckTime | The time of the last consistency check. `NULL` indicates no consistency check was performed. |
+| DataSize                 | The size of data in the partition.                          |
+| IsInMemory               | Whether all data in the partition is stored in memory.          |
+| RowCount                 | The number of data rows of the partition.                    |
+| MaxCS                    | The maximum Compaction Score of the partition. For shared-data clusters only.                    |
+
+## Examples
+
+1. Display information of all regular partitions from the specified table `site_access` under the specified database `test`.
+
+    ```SQL
+    MySQL > show partitions from test.site_access\G
+    *************************** 1. row ***************************
+                PartitionId: 20990
+            PartitionName: p2019 
+            VisibleVersion: 1
+        VisibleVersionTime: 2023-08-08 15:45:13
+        VisibleVersionHash: 0
+                    State: NORMAL
+                PartitionKey: datekey
+                    Range: [types: [DATE]; keys: [2019-01-01]; ..types: [DATE]; keys: [2020-01-01]; )
+            DistributionKey: site_id
+                    Buckets: 6
+            ReplicationNum: 3
+            StorageMedium: HDD
+                CooldownTime: 9999-12-31 23:59:59
+    LastConsistencyCheckTime: NULL
+                    DataSize:  4KB   
+                IsInMemory: false
+                    RowCount: 3 
+    1 row in set (0.00 sec)
+    ```
+
+2. Display information of all temporary partitions from the specified table `site_access` under the specified database `test`.
+
+    ```sql
+    SHOW TEMPORARY PARTITIONS FROM test.site_access;
+    ```
+
+3. Display the information of the specified partition `p1` of the specified table `site_access` under the specified database `test`.
+
+    ```sql
+    -- Regular partition
+    SHOW PARTITIONS FROM test.site_access WHERE PartitionName = "p1";
+    -- Temporary partition
+    SHOW TEMPORARY PARTITIONS FROM test.site_access WHERE PartitionName = "p1";
+    ```
+
+4. Display the latest partition information of the specified table `site_access` under the specified database `test`.
+
+    ```sql
+    -- Regular partition
+    SHOW PARTITIONS FROM test.site_access ORDER BY PartitionId DESC LIMIT 1;
+    -- Temporary partition
+    SHOW TEMPORARY PARTITIONS FROM test.site_access ORDER BY PartitionId DESC LIMIT 1;
+    ```
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_TABLES.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_TABLES.md
new file mode 100644
index 00000000000000..547c4d2748ea6f
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_TABLES.md
@@ -0,0 +1,86 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW TABLES
+
+## Description
+
+Displays all tables in a StarRocks database or a database in an external data source, for example, Hive, Iceberg, Hudi, or Delta Lake.
+
+> **NOTE**
+>
+> To view tables in an external data source, you must have the USAGE privilege on the external catalog that corresponds to that data source.
+
+## Syntax
+
+```sql
+SHOW TABLES [FROM <catalog_name>.<db_name>]
+```
+
+## Parameters
+
+| **Parameter**          | **Required** | **Description**                                                     |
+| ----------------- | -------- | ------------------------------------------------------------ |
+| catalog_name | No       | The name of the internal catalog or an external catalog.<ul><li>If you do not specify this parameter or set it to `default_catalog`, tables in StarRocks databases are returned.</li><li>If you set this parameter to the name of an external catalog, tables in databases of an external data source are returned.</li></ul> You can run [SHOW CATALOGS](../Catalog/SHOW_CATALOGS.md) to view internal and external catalogs.|
+| db_name | No       | The database name. If not specified, the current database is used by default. |
+
+## Examples
+
+Example 1: View tables in database `example_db` of the `default_catalog` after connecting to the StarRocks cluster. The following two statements are equivalent.
+
+```plain
+show tables from example_db;
++----------------------------+
+| Tables_in_example_db       |
++----------------------------+
+| depts                      |
+| depts_par                  |
+| emps                       |
+| emps2                      |
++----------------------------+
+
+show tables from default_catalog.example_db;
++----------------------------+
+| Tables_in_example_db       |
++----------------------------+
+| depts                      |
+| depts_par                  |
+| emps                       |
+| emps2                      |
++----------------------------+
+```
+
+Example 2: View tables in the current database `example_db` after connecting to this database.
+
+```plain
+show tables;
++----------------------------+
+| Tables_in_example_db       |
++----------------------------+
+| depts                      |
+| depts_par                  |
+| emps                       |
+| emps2                      |
++----------------------------+
+```
+
+Example 2: View tables in database `hudi_db` of the external catalog `hudi_catalog`.
+
+```plain
+show tables from hudi_catalog.hudi_db;
++----------------------------+
+| Tables_in_hudi_db          |
++----------------------------+
+| hudi_sync_mor              |
+| hudi_table1                |
++----------------------------+
+```
+
+Alternatively, you can run SET CATALOG to switch to the external catalog `hudi_catalog` and then run `SHOW TABLES FROM hudi_db;`.
+
+## References
+
+- [SHOW CATALOGS](../Catalog/SHOW_CATALOGS.md): Views all catalogs in a StarRocks cluster.
+- [SHOW DATABASES](../Database/SHOW_DATABASES.md): Views all databases in the internal catalog or an external catalog.
+- [SET CATALOG](../Catalog/SET_CATALOG.md): Switches between catalogs.
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_TABLET.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_TABLET.md
new file mode 100644
index 00000000000000..c30ec0052394fa
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/SHOW_TABLET.md
@@ -0,0 +1,226 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW TABLET
+
+## Description
+
+Displays tablet related information.
+
+> **NOTE**
+>
+> For v3.0 and later, this operation requires the SYSTEM-level OPERATE privilege and TABLE-level SELECT privilege. For v2.5 and earlier, this operation requires the ADMIN_PRIV privilege.
+
+## Syntax
+
+### Query information of tablets in a table or a partition
+
+```sql
+SHOW TABLET
+FROM [<db_name>.]<table_name>
+[PARTITION(<partition_name>, ...)]
+[
+WHERE [version = <version_number>] 
+    [[AND] backendid = <backend_id>] 
+    [[AND] STATE = "NORMAL"|"ALTER"|"CLONE"|"DECOMMISSION"]
+]
+[ORDER BY <field_name> [ASC | DESC]]
+[LIMIT [<offset>,]<limit>]
+```
+
+| **Parameter**       | **Required** | **Description**                                                     |
+| -------------- | -------- | ------------------------------------------------------------ |
+| db_name        | No       | The database name. If you do not specify this parameter, the current database is used by default.                     |
+| table_name     | Yes       | The name of the table from which you want to query tablet information. You must specify this parameter. Otherwise, an error is returned.                                                     |
+| partition_name | No       | The name of the partition from which you want to query tablet information.                                                     |
+| version_number | No       | The data version number.                                                   |
+| backend_id     | No       | The ID of the BE where the replica of the tablet is located.                                 |
+| STATE          | No       | The status of tablet replicas. <ul><li>`NORMAL`: The replica is normal.</li><li>`ALTER`: A Rollup or schema change is being performed on the replica.</li><li>`CLONE`: The replica is being cloned. (Replicas in this state are not available for use). </li><li>`DECOMMISSION`: The replica is being decommissioned. </li></ul> |
+| field_name     | No       | The field by which the results are sorted. All the fields returned by `SHOW TABLET FROM <table_name>` are sortable.<ul><li>If you want to display results in ascending order, use `ORDER BY field_name ASC`. </li><li>If you want to display results in descending order, use `ORDER BY field_name DESC`.</li></ul> |
+| offset         | No       | The number of tablets to skip from the results. For example, `OFFSET 5` means to skip the first five tablets. Default value: 0. |
+| limit          | No       | The number of tablets to return. For example, `LIMIT 10` means to return only 10 tablets. If this parameter is not specified, all the tablets that meet the filter conditions are returned. |
+
+### Query information of a single tablet
+
+After obtaining all tablet IDs using `SHOW TABLET FROM <table_name>`, you can query the information of a single tablet.
+
+```sql
+SHOW TABLET <tablet_id>
+```
+
+| **Parameter**  | **Required** | **Description**       |
+| --------- | -------- | -------------- |
+| tablet_id | Yes       | Tablet ID |
+
+## Description of return fields
+
+### Query information of tablets in a table or a partition
+
+```plain
++----------+-----------+-----------+------------+---------+-------------+-------------------+-----------------------+------------------+----------------------+---------------+----------+----------+--------+-------------------------+--------------+------------------+--------------+----------+----------+-------------------+
+| TabletId | ReplicaId | BackendId | SchemaHash | Version | VersionHash | LstSuccessVersion | LstSuccessVersionHash | LstFailedVersion | LstFailedVersionHash | LstFailedTime | DataSize | RowCount | State  | LstConsistencyCheckTime | CheckVersion | CheckVersionHash | VersionCount | PathHash | MetaUrl  | CompactionStatus  |
++----------+-----------+-----------+------------+---------+-------------+-------------------+-----------------------+------------------+----------------------+---------------+----------+----------+--------+-------------------------+--------------+------------------+--------------+----------+----------+-------------------+
+```
+
+| **Field**                | **Description**                        |
+| ----------------------- | ------------------------------- |
+| TabletId                | Table ID.                   |
+| ReplicaId               | Replica ID.                      |
+| BackendId               | The ID of the BE where the replica is located.  |
+| SchemaHash              | Schema hash (randomly generated).        |
+| Version                 | Data version number.                     |
+| VersionHash             | Hash of data version number.              |
+| LstSuccessVersion       | The last successfully loaded version.        |
+| LstSuccessVersionHash   | The hash of the last successfully loaded version. |
+| LstFailedVersion        | The version of the last failed loading. `-1` indicates no version failed to be loaded. |
+| LstFailedVersionHash    | The hash of the last failed version. |
+| LstFailedTime           | The time of the last failed loading. `NULL` indicates there is no load failure.       |
+| DataSize                | Data size of the tablet.          |
+| RowCount                | The number of data rows of the tablet.            |
+| State                   | Replica status of the tablet.           |
+| LstConsistencyCheckTime | The time of the last consistency check. `NULL` indicates no consistency check was performed. |
+| CheckVersion            | The data version on which consistency check was performed. `-1` indicates no version was checked.    |
+| CheckVersionHash        | The hash of the version on which consistency check was performed.         |
+| VersionCount            | The total number of data versions.                      |
+| PathHash                | The hash of the directory in which the tablet is stored.        |
+| MetaUrl                 | The URL used to query more meta information.     |
+| CompactionStatus        | The URL used to query data version compaction status.    |
+
+### Query information of a specific tablet
+
+```Plain
++--------+-----------+---------------+-----------+------+---------+-------------+---------+--------+-----------+
+| DbName | TableName | PartitionName | IndexName | DbId | TableId | PartitionId | IndexId | IsSync | DetailCmd |
++--------+-----------+---------------+-----------+------+---------+-------------+---------+--------+-----------+
+```
+
+| **Field**      | **Description**                                                     |
+| ------------- | ------------------------------------------------------------ |
+| DbName        | The name of the database to which the tablet belongs.      |
+| TableName     | The name of the table to which the tablet belongs.         |
+| PartitionName | The name of the partition to which the tablet belongs.     |
+| IndexName     | The index name.                                            |
+| DbId          | The database ID.                                           |
+| TableId       | The table ID.                                              |
+| PartitionId   | The partition ID.                                          |
+| IndexId       | The index ID.                                              |
+| IsSync        | Whether data on the tablet is consistent with table meta. `true` indicates data is consistent and the tablet is normal. `false` indicates data is missing on the tablet. |
+| DetailCmd     | The URL used to query more information.                    |
+
+## Examples
+
+Create table `test_show_tablet` in the database `example_db`.
+
+```sql
+CREATE TABLE `test_show_tablet` (
+  `k1` date NULL COMMENT "",
+  `k2` datetime NULL COMMENT "",
+  `k3` char(20) NULL COMMENT "",
+  `k4` varchar(20) NULL COMMENT "",
+  `k5` boolean NULL COMMENT "",
+  `k6` tinyint(4) NULL COMMENT "",
+  `k7` smallint(6) NULL COMMENT "",
+  `k8` int(11) NULL COMMENT "",
+  `k9` bigint(20) NULL COMMENT "",
+  `k10` largeint(40) NULL COMMENT "",
+  `k11` float NULL COMMENT "",
+  `k12` double NULL COMMENT "",
+  `k13` decimal128(27, 9) NULL COMMENT ""
+) ENGINE=OLAP 
+DUPLICATE KEY(`k1`, `k2`, `k3`, `k4`, `k5`)
+COMMENT "OLAP"
+PARTITION BY RANGE(`k1`)
+(PARTITION p20210101 VALUES [("2021-01-01"), ("2021-01-02")),
+PARTITION p20210102 VALUES [("2021-01-02"), ("2021-01-03")),
+PARTITION p20210103 VALUES [("2021-01-03"), ("2021-01-04")),
+PARTITION p20210104 VALUES [("2021-01-04"), ("2021-01-05")),
+PARTITION p20210105 VALUES [("2021-01-05"), ("2021-01-06")),
+PARTITION p20210106 VALUES [("2021-01-06"), ("2021-01-07")),
+PARTITION p20210107 VALUES [("2021-01-07"), ("2021-01-08")),
+PARTITION p20210108 VALUES [("2021-01-08"), ("2021-01-09")),
+PARTITION p20210109 VALUES [("2021-01-09"), ("2021-01-10")))
+DISTRIBUTED BY HASH(`k1`, `k2`, `k3`);
+```
+
+- Example 1: Query information of all the tablets in the specified table. The following example excerpts information of only one tablet from the return information.
+
+    ```plain
+        mysql> show tablet from example_db.test_show_tablet\G
+        *************************** 1. row ***************************
+                TabletId: 9588955
+                ReplicaId: 9588956
+                BackendId: 10004
+                SchemaHash: 0
+                    Version: 1
+                VersionHash: 0
+          LstSuccessVersion: 1
+      LstSuccessVersionHash: 0
+           LstFailedVersion: -1
+       LstFailedVersionHash: 0
+            LstFailedTime: NULL
+                DataSize: 0B
+                RowCount: 0
+                    State: NORMAL
+    LstConsistencyCheckTime: NULL
+            CheckVersion: -1
+        CheckVersionHash: 0
+            VersionCount: 1
+                PathHash: 0
+                 MetaUrl: http://172.26.92.141:8038/api/meta/header/9588955
+        CompactionStatus: http://172.26.92.141:8038/api/compaction/show?tablet_id=9588955
+    ```
+
+- Example 2: Query information of tablet 9588955.
+
+    ```plain
+        mysql> show tablet 9588955\G
+        *************************** 1. row ***************************
+        DbName: example_db
+        TableName: test_show_tablet
+        PartitionName: p20210103
+        IndexName: test_show_tablet
+            DbId: 11145
+        TableId: 9588953
+    PartitionId: 9588946
+        IndexId: 9588954
+        IsSync: true
+        DetailCmd: SHOW PROC '/dbs/11145/9588953/partitions/9588946/9588954/9588955';
+    ```
+
+- Example 3: Query information of tablets in partition `p20210103`.
+
+    ```sql
+    SHOW TABLET FROM test_show_tablet partition(p20210103);
+    ```
+
+- Example 4: Return information of 10 tablets.
+
+    ```sql
+        SHOW TABLET FROM test_show_tablet limit 10;
+    ```
+
+- Example 5: Return information of 10 tablets with an offset 5.
+
+    ```sql
+    SHOW TABLET FROM test_show_tablet limit 5,10;
+    ```
+
+- Example 6: Filter tablets by `backendid`, `version`, and `state`.
+
+    ```sql
+        SHOW TABLET FROM test_show_tablet
+        WHERE backendid = 10004 and version = 1 and state = "NORMAL";
+    ```
+
+- Example 7: Sort tablets by `version`.
+
+    ```sql
+        SHOW TABLET FROM table_name where backendid = 10004 order by version;
+    ```
+
+- Example 8: Return information of tablets whose index name is `test_show_tablet`.
+
+    ```sql
+    SHOW TABLET FROM test_show_tablet where indexname = "test_show_tablet";
+    ```
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/TRUNCATE_TABLE.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/TRUNCATE_TABLE.md
new file mode 100644
index 00000000000000..c41a61486b7523
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/TRUNCATE_TABLE.md
@@ -0,0 +1,37 @@
+---
+displayed_sidebar: docs
+---
+
+# TRUNCATE TABLE
+
+## Description
+
+This statement is used to truncate the specified table and partition data.
+
+Syntax:
+
+```sql
+TRUNCATE TABLE [db.]tbl[ PARTITION(p1, p2, ...)]
+```
+
+Note:
+
+1. This statement is used to truncate data while retaining tables or partitions.
+2. Unlike DELETE, this statement can only empty the specified tables or partitions as a whole, and filtering conditions cannot be added.
+3. Unlike DELETE, using this method to clear data will not affect query performance.
+4. This statement directly deletes data. The deleted data cannot be recovered.
+5. The table on which you perform this operation must be in the NORMAL state. For example, you cannot perform TRUNCATE TABLE on a table with SCHEMA CHANGE going on.
+
+## Examples
+
+1. Truncate table `tbl` under `example_db`.
+
+    ```sql
+    TRUNCATE TABLE example_db.tbl;
+    ```
+
+2. Truncate partitions `p1` and `p2` in table `tbl`.
+
+    ```sql
+    TRUNCATE TABLE tbl PARTITION(p1, p2);
+    ```
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/UPDATE.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/UPDATE.md
new file mode 100644
index 00000000000000..44e7bc77049eae
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/UPDATE.md
@@ -0,0 +1,176 @@
+---
+displayed_sidebar: docs
+---
+
+# UPDATE
+
+Updates rows in a Primary Key table.
+
+StarRocks supports the UPDATE statement since v2.3, which only supports single-table UPDATE and does not support common table expressions (CTEs). Starting from version 3.0, StarRocks enriches the syntax to support multi-table joins and CTEs. If you need to join the table to be updated with other tables in the database, you can reference these other tables in the FROM clause or CTE. Since version 3.1, the UPDATE statement supports the partial updates in column mode, which is suitable for scenarios involving a small number of columns but a large number of rows, resulting in faster update speeds.
+
+This command requires the UPDATE privilege on the table you want to update.
+
+## Usage notes
+
+When executing the UPDATE statement involving multiple tables, StarRocks converts the table expression in the FROM clause of the UPDATE statement into an equivalent JOIN query statement. Therefore, make sure that the table expression that you specify in the FROM clause of the UPDATE statement supports this conversion. For example, the UPDATE statement is 'UPDATE t0 SET v1=t1.v1 FROM t1 WHERE t0.pk = t1.pk;'. The table expression in the FROM clause can be converted to 't0 JOIN t1 ON t0.pk=t1.pk;'. StarRocks matches the data rows to be updated based on the result set of the JOIN query. It is possible that multiple rows in the result set match a certain row in the table to be updated. In this scenario, that row is updated based on the value of a random row among these multiple rows.
+
+## Syntax
+
+### Single-table UPDATE
+
+If the data rows of the table to be updated meet the WHERE condition, the specified columns of these data rows are assigned new values.
+
+```SQL
+[ WITH <with_query> [, ...] ]
+UPDATE <table_name>
+    SET <column_name> = <expression> [, ...]
+    WHERE <where_condition>
+```
+
+### Multi-table UPDATE
+
+The result set from the multi-table join is matched against the table to be updated. If the data rows of the table to be updated match the result set and meet the WHERE condition, the specified columns of these data rows are assigned new values.
+
+```SQL
+[ WITH <with_query> [, ...] ]
+UPDATE <table_name>
+    SET <column_name> = <expression> [, ...]
+    [ FROM <from_item> [, ...] ]
+    WHERE <where_condition>
+```
+
+## Parameters
+
+`with_query`
+
+One or more CTEs that can be referenced by name in an UPDATE statement. CTEs are temporary result sets that can improve the readability of complex statements.
+
+`table_name`
+
+The name of the table to be updated.
+
+`column_name`
+
+The name of the column to be updated. It cannot include the table name. For example, 'UPDATE t1 SET col = 1' is not valid.
+
+`expression`
+
+The expression that assigns new values to the column.
+
+`from_item`
+
+One or more other tables in the database. These tables can be joined with the table to be updated based on the condition specified in the WHERE clause. The values of the rows in the result set are used to update the values for the specified columns in the matched rows in the table to be updated. For example, if the FROM clause is `FROM t1 WHERE t0.pk = t1.pk`, StarRocks converts the table expression in the FROM clause to `t0 JOIN t1 ON t0.pk=t1.pk` when executing the UPDATE statement.
+
+`where_condition`
+
+The condition based on which you want to update rows. Only rows that meet the WHERE condition can be updated. This parameter is required, because it helps prevent you from accidentally updating the entire table. If you want to update the entire table, you can use 'WHERE true'. However, this parameter is not required for [partial updates in column mode](#partial-updates-in-column-mode-since-v31).
+
+## Partial updates in column mode (since v3.1)
+
+Partial updates in column mode are suitable for scenarios where only a small number of columns, but a large number of rows need to be updated. In such scenarios, enabling the column mode offers faster update speeds. For example, in a table with 100 columns, if only 10 columns (10% of the total) are updated for all rows, the update speed of the column mode is 10 times faster.
+
+The system variable `partial_update_mode` controls the mode of partial updates and supports the following values:
+
+- `auto` (default): The system automatically determines the mode of partial updates by analyzing the UPDATE statement and the columns involved. If the following criteria are met, the system automatically uses the column mode:
+  - The percentage of updated columns compared to the total number of columns is less than 30%, and the number of updated columns is fewer than 4.
+  - The update statement does not use a WHERE condition.
+
+  Otherwise, the system does not use the column mode.
+- `column`: The column mode is used for the partial updates, which is particularly suitable for the partial updates which involve a small number of columns and a large number of rows.
+
+You can use `EXPLAIN UPDATE xxx` to view the mode of partial updates.
+
+## Examples
+
+### Single-table UPDATE
+
+Create a table `Employees` to record employee information and insert five data rows into the table.
+
+```SQL
+CREATE TABLE Employees (
+    EmployeeID INT,
+    Name VARCHAR(50),
+    Salary DECIMAL(10, 2)
+)
+PRIMARY KEY (EmployeeID) 
+DISTRIBUTED BY HASH (EmployeeID)
+PROPERTIES ("replication_num" = "3");
+
+INSERT INTO Employees VALUES
+    (1, 'John Doe', 5000),
+    (2, 'Jane Smith', 6000),
+    (3, 'Robert Johnson', 5500),
+    (4, 'Emily Williams', 4500),
+    (5, 'Michael Brown', 7000);
+```
+
+If you need to give a 10% raise to all employees, you can execute the following statement:
+
+```SQL
+UPDATE Employees
+SET Salary = Salary * 1.1  -- Increase the salary by 10%.
+WHERE true;
+```
+
+If you need to give a 10% raise to employees with salaries lower than the average salary, you can execute the following statement:
+
+```SQL
+UPDATE Employees
+SET Salary = Salary * 1.1   -- Increase the salary by 10%.
+WHERE Salary < (SELECT AVG(Salary) FROM Employees);
+```
+
+You can also use a CTE to rewrite the above statement to improve readability.
+
+```SQL
+WITH AvgSalary AS (
+    SELECT AVG(Salary) AS AverageSalary
+    FROM Employees
+)
+UPDATE Employees
+SET Salary = Salary * 1.1   -- Increase the salary by 10%.
+FROM AvgSalary
+WHERE Employees.Salary < AvgSalary.AverageSalary;
+```
+
+### Multi-table UPDATE
+
+Create a table `Accounts` to record account information and insert three data rows into the table.
+
+```SQL
+CREATE TABLE Accounts (
+    Accounts_id BIGINT NOT NULL,
+    Name VARCHAR(26) NOT NULL,
+    Sales_person VARCHAR(50) NOT NULL
+) 
+PRIMARY KEY (Accounts_id)
+DISTRIBUTED BY HASH (Accounts_id)
+PROPERTIES ("replication_num" = "3");
+
+INSERT INTO Accounts VALUES
+    (1,'Acme Corporation','John Doe'),
+    (2,'Acme Corporation','Robert Johnson'),
+    (3,'Acme Corporation','Lily Swift');
+```
+
+If you need to give a 10% raise to employees in the table `Employees` who manage accounts for Acme Corporation, you can execute the following statement:
+
+```SQL
+UPDATE Employees
+SET Salary = Salary * 1.1  -- Increase the salary by 10%.
+FROM Accounts
+WHERE Accounts.name = 'Acme Corporation'
+    AND Employees.Name = Accounts.Sales_person;
+```
+
+You can also use a CTE to rewrite the above statement to improve readability.
+
+```SQL
+WITH Acme_Accounts as (
+    SELECT * from Accounts
+    WHERE Accounts.name = 'Acme Corporation'
+)
+UPDATE Employees SET Salary = Salary * 1.1 -- Increase the salary by 10%.
+FROM Acme_Accounts
+WHERE Employees.Name = Acme_Accounts.Sales_person;
+```
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/_category_.yml b/docs/en/sql-reference/sql-statements/table_bucket_part_index/_category_.yml
new file mode 100644
index 00000000000000..fad8ac4e6a457d
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/_category_.yml
@@ -0,0 +1,6 @@
+position: 80 # float position is supported
+label: 'Table, bucket, partition, and index'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/en/sql-reference/sql-statements/table_bucket_part_index/auto_increment.md b/docs/en/sql-reference/sql-statements/table_bucket_part_index/auto_increment.md
new file mode 100644
index 00000000000000..d75e0074eb0154
--- /dev/null
+++ b/docs/en/sql-reference/sql-statements/table_bucket_part_index/auto_increment.md
@@ -0,0 +1,399 @@
+---
+displayed_sidebar: docs
+---
+
+# AUTO_INCREMENT
+
+Since version 3.0, StarRocks supports the `AUTO_INCREMENT` column attribute, which can simplify data management. This topic introduces the application scenarios, usage and features of the `AUTO_INCREMENT` column attribute.
+
+## Introduction
+
+When a new data row is loaded into a table and values are not specified for the `AUTO_INCREMENT` column, StarRocks automatically assigns an integer value for the row's `AUTO_INCREMENT` column as its unique ID across the table. The subsequent values for the `AUTO_INCREMENT` column automatically increase at a specific step starting from the ID of the row. An `AUTO_INCREMENT` column can be used to simplify data management and speed up some queries. Here are some application scenarios of an `AUTO_INCREMENT` column:
+
+- Serve as primary keys: An `AUTO_INCREMENT` column can be used as the primary key to ensure that each row has a unique ID and make it easy to query and manage data.
+- Join tables: When multiple tables are joined, an `AUTO_INCREMENT` column can be used as the Join Key, which can expedite queries compared to using a column whose data type is STRING, for example, UUID.
+- Count the number of distinct values in a high-cardinality column: An `AUTO_INCREMENT` column can be used to represent the unique value column in a dictionary. Compared to directly counting distinct STRING values, counting distinct integer values of the `AUTO_INCREMENT` column can sometimes improve the query speed by several times or even tens of times.
+
+You need to specify an `AUTO_INCREMENT` column in the CREATE TABLE statement. The data types of an `AUTO_INCREMENT` column must be BIGINT. The value for an AUTO_INCREMENT column can be [implicitly assigned or explicitly specified](#assign-values-for-auto_increment-column). It starts from 1, and increments by 1 for each new row.
+
+## Basic operations
+
+### Specify `AUTO_INCREMENT` column at table creation
+
+Create a table named `test_tbl1` with two columns, `id` and `number`. Specify the column `number` as the `AUTO_INCREMENT` column.
+
+```SQL
+CREATE TABLE test_tbl1
+(
+    id BIGINT NOT NULL, 
+    number BIGINT NOT NULL AUTO_INCREMENT
+) 
+PRIMARY KEY (id) 
+DISTRIBUTED BY HASH(id)
+PROPERTIES("replicated_storage" = "true");
+```
+
+### Assign values for `AUTO_INCREMENT` column
+
+#### Assign values implicitly
+
+When you load data into a StarRocks table, you do not need to specify the values for the `AUTO_INCREMENT` column. StarRocks automatically assigns unique integer values for that column and inserts them into the table.
+
+```SQL
+INSERT INTO test_tbl1 (id) VALUES (1);
+INSERT INTO test_tbl1 (id) VALUES (2);
+INSERT INTO test_tbl1 (id) VALUES (3),(4),(5);
+```
+
+View data in the table.
+
+```SQL
+mysql > SELECT * FROM test_tbl1 ORDER BY id;
++------+--------+
+| id   | number |
++------+--------+
+|    1 |      1 |
+|    2 |      2 |
+|    3 |      3 |
+|    4 |      4 |
+|    5 |      5 |
++------+--------+
+5 rows in set (0.02 sec)
+```
+
+When you load data into a StarRocks table, you can also specify the values as `DEFAULT` for the `AUTO_INCREMENT` column. StarRocks automatically assigns unique integer values for that column and inserts them into the table.
+
+```SQL
+INSERT INTO test_tbl1 (id, number) VALUES (6, DEFAULT);
+```
+
+View data in the table.
+
+```SQL
+mysql > SELECT * FROM test_tbl1 ORDER BY id;
++------+--------+
+| id   | number |
++------+--------+
+|    1 |      1 |
+|    2 |      2 |
+|    3 |      3 |
+|    4 |      4 |
+|    5 |      5 |
+|    6 |      6 |
++------+--------+
+6 rows in set (0.02 sec)
+```
+
+In actual usage, the following result may be returned when you view the data in the table. This is because StarRocks cannot guarantee that the values for the `AUTO_INCREMENT` column are strictly monotonic. But StarRocks can guarantee that the values roughly increase in chronological order. For more information, see [Monotonicity](#monotonicity).
+
+```SQL
+mysql > SELECT * FROM test_tbl1 ORDER BY id;
++------+--------+
+| id   | number |
++------+--------+
+|    1 |      1 |
+|    2 | 100001 |
+|    3 | 200001 |
+|    4 | 200002 |
+|    5 | 200003 |
+|    6 | 200004 |
++------+--------+
+6 rows in set (0.01 sec)
+```
+
+#### Specify values explicitly
+
+You can also explicitly specify the values for the `AUTO_INCREMENT` column and insert them into the table.
+
+```SQL
+INSERT INTO test_tbl1 (id, number) VALUES (7, 100);
+
+-- view data in the table.
+
+mysql > SELECT * FROM test_tbl1 ORDER BY id;
++------+--------+
+| id   | number |
++------+--------+
+|    1 |      1 |
+|    2 | 100001 |
+|    3 | 200001 |
+|    4 | 200002 |
+|    5 | 200003 |
+|    6 | 200004 |
+|    7 |    100 |
++------+--------+
+7 rows in set (0.01 sec)
+```
+
+Moreover, explicitly specifying values does not affect the subsequent values generated by StarRocks for newly inserted data rows.
+
+```SQL
+INSERT INTO test_tbl1 (id) VALUES (8);
+
+-- view data in the table.
+
+mysql > SELECT * FROM test_tbl1 ORDER BY id;
++------+--------+
+| id   | number |
++------+--------+
+|    1 |      1 |
+|    2 | 100001 |
+|    3 | 200001 |
+|    4 | 200002 |
+|    5 | 200003 |
+|    6 | 200004 |
+|    7 |    100 |
+|    8 |      2 |
++------+--------+
+8 rows in set (0.01 sec)
+```
+
+**NOTICE**
+
+We recommend that you do not use implicitly assigned values and explicitly specified values for the `AUTO_INCREMENT` column at the same time. Because the specified values may be the same as the values generated by StarRocks, breaking the [global uniqueness of auto-incremented IDs](#uniqueness).
+
+## Basic features
+
+### Uniqueness
+
+In general, StarRocks guarantees that the values for a `AUTO_INCREMENT` column are globally unique across a table. We recommend that you do not implicitly assign and explicitly specify the values for the `AUTO_INCREMENT` column at the same time. If you do so, it may break the global uniqueness of auto-incremented IDs. Here is a simple example: Create a table named `test_tbl2` with two columns, `id` and `number`. Specify the column `number` as the `AUTO_INCREMENT` column.
+
+```SQL
+CREATE TABLE test_tbl2
+(
+    id BIGINT NOT NULL,
+    number BIGINT NOT NULL AUTO_INCREMENT
+ ) 
+PRIMARY KEY (id) 
+DISTRIBUTED BY HASH(id)
+PROPERTIES("replicated_storage" = "true");
+```
+
+Implicitly assign and explicitly specify the values for the `AUTO_INCREMENT` column `number` in the table `test_tbl2`.
+
+```SQL
+INSERT INTO test_tbl2 (id, number) VALUES (1, DEFAULT);
+INSERT INTO test_tbl2 (id, number) VALUES (2, 2);
+INSERT INTO test_tbl2 (id) VALUES (3);
+```
+
+Query the table `test_tbl2`.
+
+```SQL
+mysql > SELECT * FROM test_tbl2 ORDER BY id;
++------+--------+
+| id   | number |
++------+--------+
+|    1 |      1 |
+|    2 |      2 |
+|    3 | 100001 |
++------+--------+
+3 rows in set (0.08 sec)
+```
+
+### Monotonicity
+
+In order to improve the performance of allocating auto-incremented IDs, BEs cache some auto-incremented IDs locally. In this situation, StarRocks cannot guarantee that the values for the `AUTO_INCREMENT` column are strictly monotonic. It can only be ensured that the values roughly increase in chronological order.
+
+> **NOTE**
+>
+> The number of auto-incremented IDs cached by the BEs is determined by the FE dynamic parameter `auto_increment_cache_size`, which defaults to `100,000`. You can modify the value by using `ADMIN SET FRONTEND CONFIG ("auto_increment_cache_size" = "xxx");`
+
+For example, a StarRocks cluster has one FE node and two BE nodes. Create a table named `test_tbl3` and insert five rows of data as follows:
+
+```SQL
+CREATE TABLE test_tbl3
+(
+    id BIGINT NOT NULL,
+    number BIGINT NOT NULL AUTO_INCREMENT
+) 
+PRIMARY KEY (id)
+DISTRIBUTED BY HASH(id)
+PROPERTIES("replicated_storage" = "true");
+
+INSERT INTO test_tbl3 VALUES (1, DEFAULT);
+INSERT INTO test_tbl3 VALUES (2, DEFAULT);
+INSERT INTO test_tbl3 VALUES (3, DEFAULT);
+INSERT INTO test_tbl3 VALUES (4, DEFAULT);
+INSERT INTO test_tbl3 VALUES (5, DEFAULT);
+```
+
+The auto-incremented IDs in the table `test_tbl3` do not monotonically increase, because the two BE nodes cache auto-incremented IDs, [1, 100000] and [100001, 200000], respectively. When data is loaded by using multiple INSERT statements, the data is sent to different BE nodes which allocate auto-incremented IDs independently. Therefore, it cannot be guaranteed that auto-incremented IDs are strictly monotonic.
+
+```SQL
+mysql > SELECT * FROM test_tbl3 ORDER BY id;
++------+--------+
+| id   | number |
++------+--------+
+|    1 |      1 |
+|    2 | 100001 |
+|    3 | 200001 |
+|    4 |      2 |
+|    5 | 100002 |
++------+--------+
+5 rows in set (0.07 sec)
+```
+
+## Partial updates and `AUTO_INCREMENT` column
+
+This section explains how to update only a few specified columns in a table that contains an `AUTO_INCREMENT` column.
+
+> **NOTE**
+>
+> Currently, only Primary Key tables support partial updates.
+
+### `AUTO_INCREMENT` column is primary key
+
+You need to specify the primary key during partial updates. Therefore, if the `AUTO_INCREMENT` column is the primary key or part of the primary key, the user behavior for partial updates is exactly the same as when the `AUTO_INCREMENT` column is not defined.
+
+1. Create a table `test_tbl4` in the database `example_db` and insert one data row.
+
+    ```SQL
+    -- Create a table.
+    CREATE TABLE test_tbl4
+    (
+        id BIGINT AUTO_INCREMENT,
+        name BIGINT NOT NULL,
+        job1 BIGINT NOT NULL,
+        job2 BIGINT NOT NULL
+    ) 
+    PRIMARY KEY (id, name)
+    DISTRIBUTED BY HASH(id)
+    PROPERTIES("replicated_storage" = "true");
+
+    -- Prepared data.
+    mysql > INSERT INTO test_tbl4 (id, name, job1, job2) VALUES (0, 0, 1, 1);
+    Query OK, 1 row affected (0.04 sec)
+    {'label':'insert_6af28e77-7d2b-11ed-af6e-02424283676b', 'status':'VISIBLE', 'txnId':'152'}
+
+    -- Query the table.
+    mysql > SELECT * FROM test_tbl4 ORDER BY id;
+    +------+------+------+------+
+    | id   | name | job1 | job2 |
+    +------+------+------+------+
+    |    0 |    0 |    1 |    1 |
+    +------+------+------+------+
+    1 row in set (0.01 sec)
+    ```
+
+2. Prepare the CSV file **my_data4.csv** to update table `test_tbl4`. The CSV file includes values for the `AUTO_INCREMENT` column and does not include values for the column `job1`. The primary key of the first row already exists in table `test_tbl4`, while the primary key of the second row does not exist in the table.
+
+    ```Plaintext
+    0,0,99
+    1,1,99
+    ```
+
+3. Run a [Stream Load](../loading_unloading/STREAM_LOAD.md) job and use the CSV file to update table `test_tbl4`.
+
+    ```Bash
+    curl --location-trusted -u <username>:<password> -H "label:1" \
+        -H "column_separator:," \
+        -H "partial_update:true" \
+        -H "columns:id,name,job2" \
+        -T my_data4.csv -XPUT \
+        http://<fe_host>:<fe_http_port>/api/example_db/test_tbl4/_stream_load
+    ```
+
+4. Query the updated table. The first row of data already exists in table `test_tbl4`, and the value for the column `job1` remains unchanged. The second row of data is newly inserted, and because the default value for the column `job1` is not specified, the partial update framework directly sets the value for this column to `0`.
+
+    ```SQL
+    mysql > SELECT * FROM test_tbl4 ORDER BY id;
+    +------+------+------+------+
+    | id   | name | job1 | job2 |
+    +------+------+------+------+
+    |    0 |    0 |    1 |   99 |
+    |    1 |    1 |    0 |   99 |
+    +------+------+------+------+
+    2 rows in set (0.01 sec)
+    ```
+
+### `AUTO_INCREMENT` column is not primary key
+
+If the `AUTO_INCREMENT` column is not a primary key or a part of the primary key, and auto-incremented IDs are not provided in a Stream Load job, the following situations occur:
+
+- If the row already exists in the table, StarRocks does not update the auto-incremented ID.
+- If the row is newly loaded into the table, StarRocks generates a new auto-incremented ID.
+
+This feature can be used to build a dictionary table for quickly computing distinct STRING values.
+
+1. In the database `example_db`, create a table `test_tbl5` and specify the column `job1` as the `AUTO_INCREMENT` column and insert a data row into the table `test_tbl5`.
+
+    ```SQL
+    -- Create a table.
+    CREATE TABLE test_tbl5
+    (
+        id BIGINT NOT NULL,
+        name BIGINT NOT NULL,
+        job1 BIGINT NOT NULL AUTO_INCREMENT,
+        job2 BIGINT NOT NULL
+    )
+    PRIMARY KEY (id, name)
+    DISTRIBUTED BY HASH(id)
+    PROPERTIES("replicated_storage" = "true");
+
+    -- Prepare data.
+    mysql > INSERT INTO test_tbl5 VALUES (0, 0, -1, -1);
+    Query OK, 1 row affected (0.04 sec)
+    {'label':'insert_458d9487-80f6-11ed-ae56-aa528ccd0ebf', 'status':'VISIBLE', 'txnId':'94'}
+
+    -- Query the table.
+    mysql > SELECT * FROM test_tbl5 ORDER BY id;
+    +------+------+------+------+
+    | id   | name | job1 | job2 |
+    +------+------+------+------+
+    |    0 |    0 |   -1 |   -1 |
+    +------+------+------+------+
+    1 row in set (0.01 sec)
+    ```
+
+2. Prepare a CSV file **my_data5.csv** to update table `test_tbl5`. The CSV file does not contain values for the `AUTO_INCREMENT` column `job1`. The primary key of the first row already exists in the table while the primary keys of the second and third rows do not.
+
+    ```Plaintext
+    0,0,99
+    1,1,99
+    2,2,99
+    ```
+
+3. Run a [Stream Load](../loading_unloading/STREAM_LOAD.md) job to load data from the CSV file into table `test_tbl5`.
+
+    ```Bash
+    curl --location-trusted -u <username>:<password> -H "label:2" \
+        -H "column_separator:," \
+        -H "partial_update:true" \
+        -H "columns: id,name,job2" \
+        -T my_data5.csv -XPUT \
+        http://<fe_host>:<fe_http_port>/api/example_db/test_tbl5/_stream_load
+    ```
+
+4. Query the updated table. The first row of data already exists in table `test_tbl5`, so the `AUTO_INCREMENT` column `job1` retains its original value. The second and third rows of data are newly inserted, so StarRocks generate new values for the `AUTO_INCREMENT` column `job1`.
+
+    ```SQL
+    mysql > SELECT * FROM test_tbl5 ORDER BY id;
+    +------+------+--------+------+
+    | id   | name | job1   | job2 |
+    +------+------+--------+------+
+    |    0 |    0 |     -1 |   99 |
+    |    1 |    1 |      1 |   99 |
+    |    2 |    2 | 100001 |   99 |
+    +------+------+--------+------+
+    3 rows in set (0.01 sec)
+    ```
+
+## Limits
+
+- When a table with an `AUTO_INCREMENT` column is created, `'replicated_storage' = 'true'` must be set to ensure that all replicas have the same auto-incremented IDs.
+- Each table can have only one `AUTO_INCREMENT` column.
+- The data type of the `AUTO_INCREMENT` column must be BIGINT.
+- The `AUTO_INCREMENT` column must be `NOT NULL` and does not have a default value.
+- You can delete data from a Primary Key table with an `AUTO_INCREMENT` column. However, if the `AUTO_INCREMENT` column is not the primary key or part of the primary key, you need to note the following limits when you delete data in the following scenarios:
+
+  - During the DELETE operation, there is also a load job for partial updates, which only contains UPSERT operations. If both the UPSERT and DELETE operations hit the same data row and the UPSERT operation is executed after the DELETE operation, the UPSERT operation may not take effect.
+  - There is a load job for partial updates, which includes multiple UPSERT and DELETE operations on the same data row. If a certain UPSERT operation is executed after the DELETE operation, the UPSERT operation may not take effect.
+
+- Adding the `AUTO_INCREMENT` attribute by using ALTER TABLE is not supported.
+- Since version 3.1, StarRocks's shared-data mode supports the `AUTO_INCREMENT` attribute.
+- StarRocks does not support specifying the starting value and step size for the `AUTO_INCREMENT` column.
+
+## Keywords
+
+AUTO_INCREMENT, AUTO INCREMENT
diff --git a/docs/en/sql-reference/sys/grants_to_roles.md b/docs/en/sql-reference/sys/grants_to_roles.md
new file mode 100644
index 00000000000000..4bf0add6d1abaf
--- /dev/null
+++ b/docs/en/sql-reference/sys/grants_to_roles.md
@@ -0,0 +1,63 @@
+---
+displayed_sidebar: docs
+---
+
+# grants_to_roles
+
+You can view the privileges granted to user-defined roles by querying the view `grants_to_roles`.
+
+:::note
+
+By default, only users or roles with the `user_admin` role can access this view. You can grant other users the SELECT privilege on this view using [GRANT](../../sql-reference/sql-statements/account-management/GRANT.md).
+
+:::
+
+The following fields are provided in `grants_to_roles`:
+
+| **Field**       | **Description**                                              |
+| --------------- | ------------------------------------------------------------ |
+| GRANTEE         | The role to whom this privilege is granted. Only user-defined roles will be listed in this view, and system-defined ones will not. |
+| OBJECT_CATALOG  | The catalog to which the object belongs. `NULL` is returned if the privilege is a SYSTEM, RESOURCE GROUP, RESOURCE, USER, or GLOBAL FUNCTION level privilege. |
+| OBJECT_DATABASE | The database to which the object belongs. `NULL` is returned if the privilege is a SYSTEM, RESOURCE GROUP, RESOURCE, USER, GLOBAL FUNCTION, or CATALOG level privilege. |
+| OBJECT_NAME     | The table to which the object belongs. `NULL` is returned if the privilege is a SYSTEM, RESOURCE GROUP, RESOURCE, USER, GLOBAL FUNCTION, CATALOG, or DATABASE level privilege. |
+| OBJECT_TYPE     | The type of the object.                                      |
+| PRIVILEGE_TYPE  | The type of the privilege. Different privileges on the same object will be merged and returned in a single row. As shown in the following example, `role_test` has the SELECT and ALTER privileges on `default_catalog.db_test.tbl1`. |
+| IS_GRANTABLE    | Whether the grantee has the grant option.                    |
+
+Example:
+
+```Plain
+MySQL > SELECT * FROM sys.grants_to_roles LIMIT 5\G
+*************************** 1. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: db_test
+    OBJECT_NAME: tbl1
+    OBJECT_TYPE: TABLE
+ PRIVILEGE_TYPE: SELECT, ALTER
+   IS_GRANTABLE: NO
+*************************** 2. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: db_test
+    OBJECT_NAME: tbl2
+    OBJECT_TYPE: TABLE
+ PRIVILEGE_TYPE: SELECT
+   IS_GRANTABLE: YES
+*************************** 3. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: db_test
+    OBJECT_NAME: mv_test
+    OBJECT_TYPE: MATERIALIZED VIEW
+ PRIVILEGE_TYPE: SELECT
+   IS_GRANTABLE: YES
+*************************** 4. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: NULL
+OBJECT_DATABASE: NULL
+    OBJECT_NAME: NULL
+    OBJECT_TYPE: SYSTEM
+ PRIVILEGE_TYPE: CREATE RESOURCE GROUP
+   IS_GRANTABLE: NO
+```
diff --git a/docs/en/sql-reference/sys/grants_to_users.md b/docs/en/sql-reference/sys/grants_to_users.md
new file mode 100644
index 00000000000000..53f04d8fcbd697
--- /dev/null
+++ b/docs/en/sql-reference/sys/grants_to_users.md
@@ -0,0 +1,48 @@
+---
+displayed_sidebar: docs
+---
+
+# grants_to_users
+
+You can view the privileges granted to users by querying the view `grants_to_users`.
+
+:::note
+
+By default, only users or roles with the `user_admin` role can access this view. You can grant other users the SELECT privilege on this view using [GRANT](../../sql-reference/sql-statements/account-management/GRANT.md).
+
+:::
+
+The following fields are provided in `grants_to_users`:
+
+| **Field**       | **Description**                                              |
+| --------------- | ------------------------------------------------------------ |
+| GRANTEE         | The user to whom this privilege is granted.                  |
+| OBJECT_CATALOG  | The catalog to which the object belongs. `NULL` is returned if the privilege is a SYSTEM, RESOURCE GROUP, RESOURCE, USER, or GLOBAL FUNCTION level privilege. |
+| OBJECT_DATABASE | The database to which the object belongs. `NULL` is returned if the privilege is a SYSTEM, RESOURCE GROUP, RESOURCE, USER, GLOBAL FUNCTION, or CATALOG level privilege. |
+| OBJECT_NAME     | The table to which the object belongs. `NULL` is returned if the privilege is a SYSTEM, RESOURCE GROUP, RESOURCE, USER, GLOBAL FUNCTION, CATALOG, or DATABASE level privilege. |
+| OBJECT_TYPE     | The type of the object.                                      |
+| PRIVILEGE_TYPE  | The type of the privilege. Different privileges on the same object will be merged and returned in a single row. As shown in the following example, `'user1'@'%'` has the SELECT and DROP privileges on `default_catalog.db_test.view_test`. |
+| IS_GRANTABLE    | Whether the grantee has the grant option.                    |
+
+Example:
+
+```Plain
+MySQL > SELECT * FROM sys.grants_to_users LIMIT 5\G
+*************************** 1. row ***************************
+        GRANTEE: 'user1'@'%'
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: db_test
+    OBJECT_NAME: view_test
+    OBJECT_TYPE: VIEW
+ PRIVILEGE_TYPE: SELECT, DROP
+   IS_GRANTABLE: NO
+*************************** 2. row ***************************
+        GRANTEE: 'user2'@'%'
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: simo
+    OBJECT_NAME: view_test
+    OBJECT_TYPE: VIEW
+ PRIVILEGE_TYPE: SELECT
+   IS_GRANTABLE: NO
+```
+
diff --git a/docs/en/sql-reference/sys/object_dependencies.md b/docs/en/sql-reference/sys/object_dependencies.md
new file mode 100644
index 00000000000000..85b810477b0fdd
--- /dev/null
+++ b/docs/en/sql-reference/sys/object_dependencies.md
@@ -0,0 +1,52 @@
+---
+displayed_sidebar: docs
+---
+
+# object_dependencies
+
+You can view the dependency relationship of asynchronous materialized views by querying the view `object_dependencies`.
+
+The following fields are provided in `object_dependencies`:
+
+| **Field**           | **Description**                                              |
+| ------------------- | ------------------------------------------------------------ |
+| object_id           | ID of the object.                                            |
+| object_name         | The name of the object.                                      |
+| object_database     | The Database where the object is located.                    |
+| object_catalog      | The catalog where the object is located. This field is always `default_catalog`. |
+| object_type         | The type of the object. This field is always `MATERIALIZED_VIEW`. |
+| ref_object_id       | ID of the referenced object.                                 |
+| ref_object_name     | The name of the referenced object.                           |
+| ref_object_database | The database where the referenced object is located.         |
+| ref_object_catalog  | The catalog where the referenced object is located.          |
+| ref_object_type     | The type of the referenced object.                           |
+
+Example:
+
+```Plain
+MySQL > SELECT * FROM sys.object_dependencies\G
+*************************** 1. row ***************************
+          object_id: 11115
+        object_name: mv2
+    object_database: test_db
+     object_catalog: default_catalog
+        object_type: MATERIALIZED_VIEW
+      ref_object_id: 11092
+    ref_object_name: mv1
+ref_object_database: test_db
+ ref_object_catalog: default_catalog
+    ref_object_type: MATERIALIZED_VIEW
+*************************** 2. row ***************************
+          object_id: 11092
+        object_name: mv1
+    object_database: test_db
+     object_catalog: default_catalog
+        object_type: MATERIALIZED_VIEW
+      ref_object_id: 11074
+    ref_object_name: test_tbl
+ref_object_database: test_db
+ ref_object_catalog: default_catalog
+    ref_object_type: OLAP
+```
+
+The above example indicates that the materialized view `mv1` is created based on the StarRocks internal table `test_tbl`, and the materialized view `mv2` is created based on the materialized view `mv1`.
diff --git a/docs/en/sql-reference/sys/role_edges.md b/docs/en/sql-reference/sys/role_edges.md
new file mode 100644
index 00000000000000..c4e40b045caec9
--- /dev/null
+++ b/docs/en/sql-reference/sys/role_edges.md
@@ -0,0 +1,42 @@
+---
+displayed_sidebar: docs
+---
+
+# role_edges
+
+You can view the grantees of roles by querying the view `role_edges`.
+
+:::note
+
+By default, only users or roles with the `user_admin` role can access this view. You can grant other users the SELECT privilege on this view using [GRANT](../../sql-reference/sql-statements/account-management/GRANT.md).
+
+:::
+
+The following fields are provided in `role_edges`:
+
+| **Field** | **Description**                                              |
+| --------- | ------------------------------------------------------------ |
+| FROM_ROLE | The role that is granted. Multiple records with the same `FROM_ROLE` can be returned because a role can be granted to multiple roles and users. |
+| TO_ROLE   | The role to whom the current `FROM_ROLE` is granted. `NULL` is returned if the current `FROM_ROLE` is granted to a user. |
+| TO_USER   | The user to whom the current `FROM_ROLE` is granted. `NULL` is returned if the current `FROM_ROLE` is granted to a role. |
+
+Example:
+
+```Plain
+MySQL > SELECT * FROM sys.role_edges;
++------------+------------+---------------+
+| FROM_ROLE  | TO_ROLE    | TO_USER       |
++------------+------------+---------------+
+| dba_leader | director   | NULL          |
+| dba        | dba_leader | NULL          |
+| dba        | NULL       | 'aneesh'@'%'  |
+| dba        | NULL       | 'chelsea'@'%' |
+| dba_leader | NULL       | 'albert'@'%'  |
+| director   | NULL       | 'stan'@'%'    |
+| root       | NULL       | 'root'@'%'    |
++------------+------------+---------------+
+```
+
+The following diagram illustrates the nesting relation of the granted roles in the preceding example:
+
+![role_edges](../../_assets/role_edges.png)
\ No newline at end of file
diff --git a/docs/en/sql-reference/sys/sys.md b/docs/en/sql-reference/sys/sys.md
new file mode 100644
index 00000000000000..4017c338060e27
--- /dev/null
+++ b/docs/en/sql-reference/sys/sys.md
@@ -0,0 +1,69 @@
+---
+displayed_sidebar: docs
+---
+
+# System metadatabase
+
+This topic describes how to view the exclusive metadata of your StarRocks cluster via system-defined views.
+
+Each StarRocks cluster maintains a database `sys`, which contains several read-only, system-defined views. These metadata views provide a unified, easy-to-use interface that allows you to have an overall insight into the privilege structure, object dependencies, and other information within your StarRocks cluster.
+
+## View metadata information via `sys`
+
+You can view the exclusive metadata information within a StarRocks instance by querying the content of views in `sys`.
+
+The following example checks the privileges granted to user-defined roles by querying the view `grants_to_roles`.
+
+```Plain
+MySQL > SELECT * FROM sys.grants_to_roles LIMIT 5\G
+*************************** 1. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: db_test
+    OBJECT_NAME: tbl1
+    OBJECT_TYPE: TABLE
+ PRIVILEGE_TYPE: SELECT, ALTER
+   IS_GRANTABLE: NO
+*************************** 2. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: db_test
+    OBJECT_NAME: tbl2
+    OBJECT_TYPE: TABLE
+ PRIVILEGE_TYPE: SELECT
+   IS_GRANTABLE: YES
+*************************** 3. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: db_test
+    OBJECT_NAME: mv_test
+    OBJECT_TYPE: MATERIALIZED VIEW
+ PRIVILEGE_TYPE: SELECT
+   IS_GRANTABLE: YES
+*************************** 4. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: NULL
+OBJECT_DATABASE: NULL
+    OBJECT_NAME: NULL
+    OBJECT_TYPE: SYSTEM
+ PRIVILEGE_TYPE: CREATE RESOURCE GROUP
+   IS_GRANTABLE: NO
+```
+
+## Views in `sys`
+
+`sys` contains the following metadata views:
+
+| **View**             | **Description**                                                               |
+| -------------------- | ----------------------------------------------------------------------------- |
+| [grants_to_roles](../sys/grants_to_roles.md)         | Records the information of privileges that are granted to user-defined roles. |
+| [grants_to_users](../sys/grants_to_users.md)         | Records the information of privileges that are granted to users.              |
+| [role_edges](../sys/role_edges.md)                   | Records the grantees of roles.                                                |
+| [object_dependencies](../sys/object_dependencies.md) | Records the dependency relationship of asynchronous materialized views.       |
+
+:::note
+
+As per their scenarios of applications, views in `sys` are only accessible to some `admin` roles by default. Depending on your specific needs, you can grant other users the SELECT privilege on these views.
+
+:::
+
diff --git a/docs/en/sql-reference/template_for_config.md b/docs/en/sql-reference/template_for_config.md
index fe994e4eae0e73..a1c1e8356a4a21 100644
--- a/docs/en/sql-reference/template_for_config.md
+++ b/docs/en/sql-reference/template_for_config.md
@@ -1,5 +1,6 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
+unlisted: true
 ---
 
 # Template for writing FE/BE parameters and variables
diff --git a/docs/en/sql-reference/user_defined_variables.md b/docs/en/sql-reference/user_defined_variables.md
new file mode 100644
index 00000000000000..d54d2d29ed506b
--- /dev/null
+++ b/docs/en/sql-reference/user_defined_variables.md
@@ -0,0 +1,74 @@
+---
+displayed_sidebar: docs
+---
+
+# User-defined variables
+
+This topic describes how to declare and use user-defined variables.
+
+StarRocks 2.5 and later versions support user-defined variables. These variables are used to store specific values that are referenced in later SQL statements, thereby simplifying the writing of SQL statements and avoiding duplicate computation.
+
+## Usage notes
+
+- User-defined variables are variables, which can be created by the user and exist in the session. This means that no one can access user-defined variables that have been declared by another user, and when the session is closed these variables expire.
+- StarRocks does not support using the SHOW statement to display existing user-defined variables.
+- The following types of values cannot be declared as user-defined variables: BITMAP, HLL, and PERCENTILE. User-defined variables of the JSON type are converted to the STRING type for storage.
+- From v3.2.7 onwards, StarRocks supports the ARRAY type as a user-defined variable.
+
+## Declare user-defined variables
+
+### Syntax
+
+```Plain
+SET @var_name = expr [, ...];
+```
+
+> **NOTE**
+>
+> - All variables must be preceded by a single at sign (@).
+> - Multiple variables can be declared in the same SET statement and need to be separated with commas (`,`).
+> - You can declare the same variable multiple times. The newly declared value overwrites the original value.
+> - If an undeclared variable is used, the value of the variable is `NULL` by default, and the NULL type is STRING.
+
+### Parameters
+
+| **Parameter** | **Required** | **Description**                                              |
+| ------------- | ------------ | ------------------------------------------------------------ |
+| var_name      | Yes          | The name of the user-defined variable. The naming conventions are as follows:<ul><li>The name can contain letters, digits (0-9), and underscores (\_). </li><li>The name cannot exceed 64 characters in length.</li></ul>You can declare a string as a user-defined variable, such as @'my-var', @"my-var", and @\`my-var\`. User-defined variables of the STRING type can contain characters other than letters, digits, and underscores (_), such as periods (.). |
+| expr          | Yes          | The value of the user-defined variable. You can specify a number (such as 43) or a complex expression (such as the value returned by a SELECT statement) for this parameter. The data type of the variable is the same as the data type of the result returned by the expression. |
+
+### Examples
+
+Example 1: Declare a number as a user-defined variable.
+
+```SQL
+SET @var = 43;
+```
+
+Example 2: Declare the value returned by a SELECT query as a user-defined variable.
+
+```SQL
+SET @var = (SELECT SUM(v1) FROM test);
+```
+
+Example 3: Declare multiple user-defined variables in the same SET statement.
+
+```SQL
+SET @v1=1, @v2=2;
+```
+
+## Use user-defined variables in SQL
+
+- Simplifies the writing of SQL statements. For example, when you execute the following SELECT statement, StarRocks parses `@var` as `1`.
+
+  ```Plain
+  SET @var = 1;
+  SELECT @var, v1 from test;
+  ```
+
+- Avoids duplicate computation. For example, when you execute the following SELECT statement, StarRocks parses `@var` as the result returned by the `select sum(c1) from tbl` command.
+
+  ```Plain
+  SET @var = (select sum(c1) from tbl);
+  SELECT @var, v1 from test;
+  ```
diff --git a/docs/en/table_design/Data_distribution.md b/docs/en/table_design/Data_distribution.md
index 68a712e459ac4c..93e800ec08f7d0 100644
--- a/docs/en/table_design/Data_distribution.md
+++ b/docs/en/table_design/Data_distribution.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 description: Partition and bucket data
 ---
@@ -549,7 +549,7 @@ The following statement deletes partition `p1` from table `site_access`.
 
 > **NOTE**
 >
-> This operation does not immediately delete data in a partition. Data is retained in the Trash for a period of time (one day by default). If a partition is mistakenly deleted, you can use the [RECOVER](../sql-reference/sql-statements/data-definition/backup_restore/RECOVER.md) command to restore the partition and its data.
+> This operation does not immediately delete data in a partition. Data is retained in the Trash for a period of time (one day by default). If a partition is mistakenly deleted, you can use the [RECOVER](../sql-reference/sql-statements/backup_restore/RECOVER.md) command to restore the partition and its data.
 
 ```SQL
 ALTER TABLE site_access
@@ -733,7 +733,7 @@ Buckets reflect how data files are actually organized in StarRocks.
   :::warning
 
   - To enable the on-demand and dynamic increase of the number of buckets, you need to set the table property `PROPERTIES("bucket_size"="xxx")` to specify the size of a single bucket. If the data volume in a partition is small, you can set the `bucket_size` to 1 GB. Otherwise, you can set the `bucket_size` to 4 GB.
-  - Once the on-demand and dynamic increase of the number of buckets is enabled, and you need to rollback to version 3.1, you have to first delete the table which enables the dynamic increase in the number of buckets. Then you need to manually execute a metadata checkpoint using [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/Administration/ALTER_SYSTEM.md) before rolling back.
+  - Once the on-demand and dynamic increase of the number of buckets is enabled, and you need to rollback to version 3.1, you have to first delete the table which enables the dynamic increase in the number of buckets. Then you need to manually execute a metadata checkpoint using [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) before rolling back.
 
   :::
 
@@ -846,7 +846,7 @@ Buckets reflect how data files are actually organized in StarRocks.
   :::warning
 
   - To enable the on-demand and dynamic increase of the number of buckets, you need to set the table property `PROPERTIES("bucket_size"="xxx")` to specify the size of a single bucket. If the data volume in a partition is small, you can set the `bucket_size` to 1 GB. Otherwise, you can set the `bucket_size` to 4 GB.
-  - Once the on-demand and dynamic increase of the number of buckets is enabled, and you need to rollback to version 3.1, you have to first delete the table which enables the dynamic increase in the number of buckets. Then you need to manually execute a metadata checkpoint using [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/Administration/ALTER_SYSTEM.md) before rolling back.
+  - Once the on-demand and dynamic increase of the number of buckets is enabled, and you need to rollback to version 3.1, you have to first delete the table which enables the dynamic increase in the number of buckets. Then you need to manually execute a metadata checkpoint using [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) before rolling back.
 
   :::
 
@@ -918,7 +918,7 @@ Buckets reflect how data files are actually organized in StarRocks.
 
 #### View the number of buckets
 
-After creating a table, you can execute [SHOW PARTITIONS](../sql-reference/sql-statements/data-manipulation/SHOW_PARTITIONS.md) to view the number of buckets set by StarRocks for each partition. Tables configured with hash bucketing have a fixed number of buckets per partition.
+After creating a table, you can execute [SHOW PARTITIONS](../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md) to view the number of buckets set by StarRocks for each partition. Tables configured with hash bucketing have a fixed number of buckets per partition.
 
 :::info
 
@@ -957,4 +957,4 @@ As query patterns and data volume evolve in business scenarios, the configuratio
   ALTER TABLE t ORDER BY k2, k1;
   ```
 
-For more information, see [ALTER TABLE](../sql-reference/sql-statements/data-definition/ALTER_TABLE.md).
+For more information, see [ALTER TABLE](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md).
diff --git a/docs/en/table_design/StarRocks_table_design.md b/docs/en/table_design/StarRocks_table_design.md
index af22a1a5c65091..057d86bed95866 100644
--- a/docs/en/table_design/StarRocks_table_design.md
+++ b/docs/en/table_design/StarRocks_table_design.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Table overview
@@ -41,7 +41,7 @@ Since v3.3.0, the Duplicate Key table supports specifying the sort key using `OR
 
 <Replicanum />
 
-Execute [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md) to view the table schema.
+Execute [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md) to view the table schema.
 
 ```SQL
 MySQL [test]> DESCRIBE user_access;
@@ -58,7 +58,7 @@ MySQL [test]> DESCRIBE user_access;
 6 rows in set (0.00 sec)
 ```
 
-Execute [SHOW CREATE TABLE](../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE.md) to view the CREATE TABLE statement.
+Execute [SHOW CREATE TABLE](../sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md) to view the CREATE TABLE statement.
 
 ```SQL
 MySQL [example_db]> SHOW CREATE TABLE user_access\G
@@ -119,7 +119,7 @@ StarRocks provides two bucketing methods:
 - Hash bucketing: Data is distributed into buckets based on the hash values of the bucketing key. You can select columns frequently used as condition columns in queries as bucketing columns, which helps improve query efficiency.
 - Random bucketing: Data is randomly distributed to buckets. This bucketing method is more simple and ease to use.
 
-### [Data types](../sql-reference/data-types/data-type-list.md)
+### [Data types](../sql-reference/data-types/README.md)
 
 In addition to basic data types such as NUMERIC, DATE, and STRING, StarRocks supports complex semi-structured data types, including ARRAY, JSON, MAP, and STRUCT.
 
@@ -143,10 +143,10 @@ To address this issue, StarRocks introduces temporary tables in v3.3.1. Temporar
 
 You can use the `TEMPORARY` keyword in the following SQL statements to create and drop temporary tables:
 
-- [CREATE TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md)
-- [CREATE TABLE AS SELECT](../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md)
-- [CREATE TABLE LIKE](../sql-reference/sql-statements/data-definition/CREATE_TABLE_LIKE.md)
-- [DROP TABLE](../sql-reference/sql-statements/data-definition/DROP_TABLE.md)
+- [CREATE TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md)
+- [CREATE TABLE AS SELECT](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md)
+- [CREATE TABLE LIKE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_LIKE.md)
+- [DROP TABLE](../sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md)
 
 :::note
 
@@ -171,4 +171,4 @@ While the usage of temporary tables is similar to that of native tables, there a
 
 ### More features
 
-Apart from the above features, you can adopt more features based on your business requirements to design a more robust table structure. For example, using Bitmap and HLL columns to accelerate distinct counting, specifying generated columns or auto-increment columns to speed up some queries, configuring flexible and automatic storage cooldown methods to reduce maintenance costs, and configuring Colocate Join to speed up multi-table JOIN queries. For more details, see [CREATE TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md).
+Apart from the above features, you can adopt more features based on your business requirements to design a more robust table structure. For example, using Bitmap and HLL columns to accelerate distinct counting, specifying generated columns or auto-increment columns to speed up some queries, configuring flexible and automatic storage cooldown methods to reduce maintenance costs, and configuring Colocate Join to speed up multi-table JOIN queries. For more details, see [CREATE TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md).
diff --git a/docs/en/table_design/Table_design.md b/docs/en/table_design/Table_design.md
index c4d2ec9fc427f3..a5eae18cef61dc 100644
--- a/docs/en/table_design/Table_design.md
+++ b/docs/en/table_design/Table_design.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Introduction
diff --git a/docs/en/table_design/Temporary_partition.md b/docs/en/table_design/Temporary_partition.md
index 6e39da849ee924..57c3a6084eb199 100644
--- a/docs/en/table_design/Temporary_partition.md
+++ b/docs/en/table_design/Temporary_partition.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Temporary partition
@@ -12,7 +12,7 @@ You can use the temporary partition feature in the following scenarios:
 
 - Atomic overwrite operation
   
-  If you need to rewrite the data in a partition while ensuring that the data can be queried during the rewriting process, you can first create a temporary partition based on the original formal partition, and load the new data into the temporary partition. Then you can use the replace operation to atomically replace the original formal partition with the temporary partition. For atomic overwrite operations on non-partitioned tables, see [ALTER TABLE - SWAP](../sql-reference/sql-statements/data-definition/ALTER_TABLE.md#swap).
+  If you need to rewrite the data in a partition while ensuring that the data can be queried during the rewriting process, you can first create a temporary partition based on the original formal partition, and load the new data into the temporary partition. Then you can use the replace operation to atomically replace the original formal partition with the temporary partition. For atomic overwrite operations on non-partitioned tables, see [ALTER TABLE - SWAP](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md#swap).
 
 - Adjust partition data query concurrency
 
@@ -24,7 +24,7 @@ You can use the temporary partition feature in the following scenarios:
 
 ## Create temporary partitions
 
-You can create one or more partitions at a time by using the [ALTER TABLE](../sql-reference/sql-statements/data-definition/ALTER_TABLE.md) command.
+You can create one or more partitions at a time by using the [ALTER TABLE](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) command.
 
 ### Syntax
 
@@ -94,7 +94,7 @@ ADD TEMPORARY PARTITIONS START ("2020-04-01") END ("2021-01-01") EVERY (INTERVAL
 
 ## Show temporary partitions
 
-You can view the temporary partitions by using the [SHOW TEMPORARY PARTITIONS](../sql-reference/sql-statements/data-manipulation/SHOW_PARTITIONS.md) command.
+You can view the temporary partitions by using the [SHOW TEMPORARY PARTITIONS](../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md) command.
 
 ```SQL
 SHOW TEMPORARY PARTITIONS FROM [db_name.]table_name [WHERE] [ORDER BY] [LIMIT]
@@ -114,7 +114,7 @@ INSERT INTO site_access TEMPORARY PARTITION (tp2) SELECT * FROM site_access_copy
 INSERT INTO site_access TEMPORARY PARTITION (tp3, tp4,...) SELECT * FROM site_access_copy PARTITION (p3, p4,...);
 ```
 
-For detailed syntax and parameter descriptions, see [INSERT INTO](../sql-reference/sql-statements/data-manipulation/INSERT.md).
+For detailed syntax and parameter descriptions, see [INSERT INTO](../sql-reference/sql-statements/loading_unloading/INSERT.md).
 
 ### Load data by using STREAM LOAD
 
@@ -125,7 +125,7 @@ curl --location-trusted -u root: -H "label:123" -H "Expect:100-continue" -H "tem
     http://host:port/api/example_db/site_access/_stream_load    
 ```
 
-For detailed syntax and parameter descriptions, see [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md).
+For detailed syntax and parameter descriptions, see [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md).
 
 ### Load data by using BROKER LOAD
 
@@ -145,7 +145,7 @@ WITH BROKER
 );
 ```
 
-Note that `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For detailed syntax and parameter descriptions, see [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md).
+Note that `StorageCredentialParams` represents a group of authentication parameters which vary depending on the authentication method you choose. For detailed syntax and parameter descriptions, see [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md).
 
 ### Load data by using ROUTINE LOAD
 
@@ -162,11 +162,11 @@ FROM KAFKA
 );
 ```
 
-For detailed syntax and parameter descriptions, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md).
+For detailed syntax and parameter descriptions, see [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md).
 
 ## Query data in temporary partitions
 
-You can use the [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) statement to query data in specified temporary partitions.
+You can use the [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) statement to query data in specified temporary partitions.
 
 ```SQL
 SELECT * FROM
@@ -191,7 +191,7 @@ ON site_access.site_id=site_access1.site_id and site_access.event_day=site_acces
 
 ## Replace original formal partitions with temporary partitions
 
-You can use the [ALTER TABLE](../sql-reference/sql-statements/data-definition/ALTER_TABLE.md) statement to replace the original formal partition with a temporary partition, thereby creating a new formal partition.
+You can use the [ALTER TABLE](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) statement to replace the original formal partition with a temporary partition, thereby creating a new formal partition.
 
 > **NOTE**
 >
diff --git a/docs/en/table_design/catalog_db_tbl.md b/docs/en/table_design/catalog_db_tbl.md
index 7d1ad89fd82034..d83c93e40c5e91 100644
--- a/docs/en/table_design/catalog_db_tbl.md
+++ b/docs/en/table_design/catalog_db_tbl.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Catalogs, databases, and tables
@@ -44,7 +44,7 @@ External tables are maintained in external catalogs. The data of external tables
 
 Materialized views are special physical tables that hold precomputed query results from one or more base tables. Materialized views are categorized as synchronous and asynchronous materialized views. Asynchronous materialized views are more powerful because they can store precomputed results from multiple base tables (internal and external tables) and support various aggregation operators. When complex queries are executed on base tables, StarRocks can automatically reuse precomputed results stored in materialized views, to achieve transparent query acceleration, accelerate queries in data lakes and establish data modeling.
 
-## [Views](../sql-reference/sql-statements/data-definition/CREATE_VIEW.md)
+## [Views](../sql-reference/sql-statements/View/CREATE_VIEW.md)
 
 Views, or logical views, are virtual tables that do not hold any data. Views only display data that is the results of queries against other existing physical tables. The query that defines a view is run every time the view is referenced in a query.
 
diff --git a/docs/en/table_design/data_compression.md b/docs/en/table_design/data_compression.md
index 464f47f7c07f1b..4331d4824a3c69 100644
--- a/docs/en/table_design/data_compression.md
+++ b/docs/en/table_design/data_compression.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Data compression
@@ -18,7 +18,7 @@ StarRocks supports four data compression algorithms: LZ4, Zstandard (or zstd), z
 
 You can specify a data compression algorithm for a table only when creating the table, and you cannot change it afterwards.
 
-The following example creates a table `data_compression` with the Zstandard algorithm. For detailed instructions, see [CREATE TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md).
+The following example creates a table `data_compression` with the Zstandard algorithm. For detailed instructions, see [CREATE TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md).
 
 ```SQL
 CREATE TABLE `data_compression` (
@@ -38,4 +38,4 @@ PROPERTIES (
 >
 > If no data compression algorithm is specified, StarRocks uses LZ4 by default.
 
-You can view the compression algorithm of a table using [SHOW CREATE TABLE](../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE.md).
+You can view the compression algorithm of a table using [SHOW CREATE TABLE](../sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md).
diff --git a/docs/en/table_design/dynamic_partitioning.md b/docs/en/table_design/dynamic_partitioning.md
index 414bc185be86a0..f8fb2b6e33896a 100644
--- a/docs/en/table_design/dynamic_partitioning.md
+++ b/docs/en/table_design/dynamic_partitioning.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Dynamic partitioning
@@ -8,7 +8,7 @@ StarRocks supports dynamic partitioning, which can automatically manage the time
 
 ## Enable dynamic partitioning
 
-Take table `site_access` as an example. To enable dynamic partitioning, you need to configure the PROPERTIES parameter. For information about the configuration items, see [CREATE TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md).
+Take table `site_access` as an example. To enable dynamic partitioning, you need to configure the PROPERTIES parameter. For information about the configuration items, see [CREATE TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md).
 
 ```SQL
 CREATE TABLE site_access(
@@ -75,7 +75,7 @@ SHOW PARTITIONS FROM site_access;
 
 ## Modify properties of dynamic partitioning
 
-You can use the [ALTER TABLE](../sql-reference/sql-statements/data-definition/ALTER_TABLE.md) statement to modify properties of dynamic partitioning, such as disabling dynamic partitioning. Take the following statement as an example.
+You can use the [ALTER TABLE](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) statement to modify properties of dynamic partitioning, such as disabling dynamic partitioning. Take the following statement as an example.
 
 ```SQL
 ALTER TABLE site_access 
@@ -84,5 +84,5 @@ SET("dynamic_partition.enable"="false");
 
 > Note:
 >
-> - To check the properties of dynamic partitioning of a table, execute the [SHOW CREATE TABLE](../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE.md) statement.
+> - To check the properties of dynamic partitioning of a table, execute the [SHOW CREATE TABLE](../sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md) statement.
 > - You can also use the ALTER TABLE statement to modify other properties of a table.
diff --git a/docs/en/table_design/expression_partitioning.md b/docs/en/table_design/expression_partitioning.md
index 5774cf83ee7a2c..2a9add05bc820a 100644
--- a/docs/en/table_design/expression_partitioning.md
+++ b/docs/en/table_design/expression_partitioning.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 description: Partition data in StarRocks
 ---
 
diff --git a/docs/en/table_design/feature-support-data-distribution.md b/docs/en/table_design/feature-support-data-distribution.md
index 04bbfe25dd2ce2..a4101ae724cb38 100644
--- a/docs/en/table_design/feature-support-data-distribution.md
+++ b/docs/en/table_design/feature-support-data-distribution.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_label: "Feature Support"
 ---
 
diff --git a/docs/en/table_design/hybrid_table.md b/docs/en/table_design/hybrid_table.md
index 81d26e8a4f10f0..54d7d07231b8f6 100644
--- a/docs/en/table_design/hybrid_table.md
+++ b/docs/en/table_design/hybrid_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # [Preview] Hybrid row-column storage
@@ -111,7 +111,7 @@ MySQL [example_db]> SELECT * FROM users ORDER BY id;
    SHOW VARIABLES LIKE '%enable_short_circuit%';
    ```
 
-   If the short circuiting for queries is not enabled, run the `SET enable_short_circuit = true;` command to set the variable [`enable_short_circuit`](../reference/System_variable.md) to `true`.
+   If the short circuiting for queries is not enabled, run the `SET enable_short_circuit = true;` command to set the variable [`enable_short_circuit`](../sql-reference/System_variable.md) to `true`.
 
 2. Query data. If the query meets the criteria that conditional columns in the WHERE clause include all primary key columns, and the operators in the WHERE clause are `=` or `IN`, the query takes the shortcut.
 
@@ -172,7 +172,7 @@ EXECUTE select_by_id_stmt USING @id2;
 ## Limits
 
 - Currently, StarRocks shared-data clusters do not support hybrid row-column storage.
-- Since v3.2.4, the table with hybrid row-column storage can be altered by using [ALTER TABLE](../sql-reference/sql-statements/data-definition/ALTER_TABLE.md).
+- Since v3.2.4, the table with hybrid row-column storage can be altered by using [ALTER TABLE](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md).
 - The short circuiting for queries is currently only suitable for queries that happen after scheduled batch data loading. Because mutual exclusion of indexes may be incurred when the short circuiting for queries happens at the apply stage of the data writing process, data writing may block short circuiting for queries, affecting the response time of point queries during data writing.
 - Hybrid row-column storage may significantly increase storage consumption. This is because data is stored in both row and column formats, and the data compression ratio of row storage may not be as high as that of column storage.
 - Hybrid row-column storage can increase the time and resource consumption during data loading.
diff --git a/docs/en/table_design/indexes/Bitmap_index.md b/docs/en/table_design/indexes/Bitmap_index.md
index 738227135b312f..86c6ff0829476b 100644
--- a/docs/en/table_design/indexes/Bitmap_index.md
+++ b/docs/en/table_design/indexes/Bitmap_index.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Bitmap indexes
@@ -87,18 +87,18 @@ Bitmap indexes can be created on all columns in primary key and duplicate key ta
     DISTRIBUTED BY HASH(`lo_orderkey`) BUCKETS 1;
     ```
 
-    In this example, a bitmap index named `lo_orderdate_index` is created on the `lo_orderdate` column. Naming requirements for bitmap indexes can be found in [System Limits](../../reference/System_limit.md). Identical bitmap indexes cannot be created within the same table.
+    In this example, a bitmap index named `lo_orderdate_index` is created on the `lo_orderdate` column. Naming requirements for bitmap indexes can be found in [System Limits](../../sql-reference/System_limit.md). Identical bitmap indexes cannot be created within the same table.
 
     Multiple bitmap indexes can be created for multiple columns, separated by commas (,).
 
     :::note
 
 
-    For more parameters of table creation, refer to [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md).
+    For more parameters of table creation, refer to [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md).
 
     :::
 
-- `CREATE INDEX` can be used to create a bitmap index after table creation. For detailed parameter descriptions and examples, refer to [CREATE INDEX](../../sql-reference/sql-statements/data-definition/CREATE_INDEX.md).
+- `CREATE INDEX` can be used to create a bitmap index after table creation. For detailed parameter descriptions and examples, refer to [CREATE INDEX](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_INDEX.md).
 
     ```SQL
     CREATE INDEX lo_quantity_index (lo_quantity) USING BITMAP;
@@ -106,7 +106,7 @@ Bitmap indexes can be created on all columns in primary key and duplicate key ta
 
 ### Progress of creating an index
 
-Creating a bitmap index is an asynchronous process. After executing the index creation statement, you can check the index creation progress using the [SHOW ALTER TABLE](../../sql-reference/sql-statements/data-manipulation/SHOW_ALTER.md) command. When the `State` field in the returned value shows `FINISHED`, the index is successfully created.
+Creating a bitmap index is an asynchronous process. After executing the index creation statement, you can check the index creation progress using the [SHOW ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_ALTER.md) command. When the `State` field in the returned value shows `FINISHED`, the index is successfully created.
 
 ```SQL
 SHOW ALTER TABLE COLUMN;
@@ -120,7 +120,7 @@ Each table can only have one ongoing Schema Change task at a time. You cannot cr
 
 ### View an index
 
-View all bitmap indexes for a specified table. For detailed parameters and returned results, refer to [SHOW INDEX](../../sql-reference/sql-statements/data-manipulation//SHOW_INDEX.md).
+View all bitmap indexes for a specified table. For detailed parameters and returned results, refer to [SHOW INDEX](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_INDEX.md).
 
 ```SQL
 SHOW INDEXES FROM lineorder_partial;
@@ -134,7 +134,7 @@ Creating a bitmap index is an asynchronous process. Using the above statement, y
 
 ### Delete an index
 
-Delete a bitmap index for a specified table. For detailed parameters and examples, refer to [DROP INDEX](../../sql-reference/sql-statements/data-definition/DROP_INDEX.md).
+Delete a bitmap index for a specified table. For detailed parameters and examples, refer to [DROP INDEX](../../sql-reference/sql-statements/table_bucket_part_index/DROP_INDEX.md).
 
 ```SQL
 DROP INDEX lo_orderdate_index ON lineorder_partial;
diff --git a/docs/en/table_design/indexes/Bloomfilter_index.md b/docs/en/table_design/indexes/Bloomfilter_index.md
index ef5d886c902430..38f5291761fae9 100644
--- a/docs/en/table_design/indexes/Bloomfilter_index.md
+++ b/docs/en/table_design/indexes/Bloomfilter_index.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Bloom filter indexes
@@ -45,11 +45,11 @@ DISTRIBUTED BY HASH (k1, k2)
 PROPERTIES("bloom_filter_columns" = "k1,k2");
 ```
 
-You can create bloom filter indexes for multiple columns at a time by specifying these column names. Note that you need to separate these column names with commas (`,`). For other parameter descriptions of the CREATE TABLE statement, see [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md).
+You can create bloom filter indexes for multiple columns at a time by specifying these column names. Note that you need to separate these column names with commas (`,`). For other parameter descriptions of the CREATE TABLE statement, see [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md).
 
 ## Display bloom filter indexes
 
-For example, the following statement displays bloom filter indexes of `table1`. For the output description, see [SHOW CREATE TABLE](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE.md).
+For example, the following statement displays bloom filter indexes of `table1`. For the output description, see [SHOW CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md).
 
 ```SQL
 SHOW CREATE TABLE table1;
@@ -57,7 +57,7 @@ SHOW CREATE TABLE table1;
 
 ## Modify bloom filter indexes
 
-You can add, reduce, and delete bloom filter indexes by using the [ALTER TABLE](../../sql-reference/sql-statements/data-definition/ALTER_TABLE.md) statement.
+You can add, reduce, and delete bloom filter indexes by using the [ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) statement.
 
 - The following statement adds a bloom filter index on the `v1` column.
 
@@ -77,4 +77,4 @@ You can add, reduce, and delete bloom filter indexes by using the [ALTER TABLE](
     ALTER TABLE table1 SET ("bloom_filter_columns" = "");
     ```
 
-> Note: Altering an index is an asynchronous operation. You can view the progress of this operation by executing [SHOW ALTER TABLE](../../sql-reference/sql-statements/data-manipulation/SHOW_ALTER.md). You can run only one alter index task on a table each time.
+> Note: Altering an index is an asynchronous operation. You can view the progress of this operation by executing [SHOW ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_ALTER.md). You can run only one alter index task on a table each time.
diff --git a/docs/en/table_design/indexes/Ngram_Bloom_Filter_Index.md b/docs/en/table_design/indexes/Ngram_Bloom_Filter_Index.md
index 2b031d31744e4c..b9135e9eb6f096 100644
--- a/docs/en/table_design/indexes/Ngram_Bloom_Filter_Index.md
+++ b/docs/en/table_design/indexes/Ngram_Bloom_Filter_Index.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 
 ---
 
@@ -52,7 +52,7 @@ N-gram bloom filter index-related parameters:
 | `case_sensitive`   |  No          | Whether this index is case-sensitive or not. Default value is `true`. |
 | `COMMENT`          | No           | Index comment. |
 
-For explanations of other parameters related to table creation, see [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md).
+For explanations of other parameters related to table creation, see [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md).
 
 ### View N-gram bloom filter index 
 
@@ -65,7 +65,7 @@ SHOW INDEX FROM table1;
 
 ### Modify N-gram bloom filter index
 
-You can add and delete the N-gram bloom filter index by using the [ALTER TABLE](../../sql-reference/sql-statements/data-definition/ALTER_TABLE.md) statement.
+You can add and delete the N-gram bloom filter index by using the [ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) statement.
 
 - Execute the following statement to add a new N-gram bloom filter index `new_index_name` for the column `k1` to the table `table1`.
 
@@ -83,7 +83,7 @@ You can add and delete the N-gram bloom filter index by using the [ALTER TABLE](
 
 :::note
 
-Altering an index is an asynchronous operation. You can view the progress of this operation by executing [SHOW ALTER TABLE](../../sql-reference/sql-statements/data-manipulation/SHOW_ALTER.md). You can run only one task to alter the index in a table each time.
+Altering an index is an asynchronous operation. You can view the progress of this operation by executing [SHOW ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_ALTER.md). You can run only one task to alter the index in a table each time.
 
 :::
 
diff --git a/docs/en/table_design/indexes/Prefix_index_sort_key.md b/docs/en/table_design/indexes/Prefix_index_sort_key.md
index c6f022512b8b01..2471ef4f19d751 100644
--- a/docs/en/table_design/indexes/Prefix_index_sort_key.md
+++ b/docs/en/table_design/indexes/Prefix_index_sort_key.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Prefix indexes
diff --git a/docs/en/table_design/indexes/indexes_overview.md b/docs/en/table_design/indexes/indexes_overview.md
index 8db89326648f55..cf5d24c517c539 100644
--- a/docs/en/table_design/indexes/indexes_overview.md
+++ b/docs/en/table_design/indexes/indexes_overview.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Indexes
diff --git a/docs/en/table_design/indexes/inverted_index.md b/docs/en/table_design/indexes/inverted_index.md
index c1d52163fc45cc..2c3340cb52f875 100644
--- a/docs/en/table_design/indexes/inverted_index.md
+++ b/docs/en/table_design/indexes/inverted_index.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 ---
 
diff --git a/docs/en/table_design/list_partitioning.md b/docs/en/table_design/list_partitioning.md
index 2babd161d193f1..8d8a0f7490573b 100644
--- a/docs/en/table_design/list_partitioning.md
+++ b/docs/en/table_design/list_partitioning.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # List partitioning
diff --git a/docs/en/table_design/table_types/aggregate_table.md b/docs/en/table_design/table_types/aggregate_table.md
index 02227a3953724b..e6d5c5dc94edca 100644
--- a/docs/en/table_design/table_types/aggregate_table.md
+++ b/docs/en/table_design/table_types/aggregate_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Aggregate table
@@ -84,7 +84,7 @@ DISTRIBUTED BY HASH(site_id);
 
 - **Value column**: Define a column as the value column by specifying an aggregate function after the column name. This column generally holds data that needs to be aggregated.
 
-- **Aggregate function**: The aggregate function used for the value column. For supported aggregate functions for the Aggregate tables, see [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md).
+- **Aggregate function**: The aggregate function used for the value column. For supported aggregate functions for the Aggregate tables, see [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md).
 
 - **Sort key**
 
diff --git a/docs/en/table_design/table_types/duplicate_key_table.md b/docs/en/table_design/table_types/duplicate_key_table.md
index 612847be3f2865..8aa2a08a128aa2 100644
--- a/docs/en/table_design/table_types/duplicate_key_table.md
+++ b/docs/en/table_design/table_types/duplicate_key_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Duplicate Key table
diff --git a/docs/en/table_design/table_types/primary_key_table.md b/docs/en/table_design/table_types/primary_key_table.md
index 57176803b79cdd..7b56378244b94c 100644
--- a/docs/en/table_design/table_types/primary_key_table.md
+++ b/docs/en/table_design/table_types/primary_key_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 # Primary Key table
 
@@ -209,7 +209,7 @@ During data loading, the data is stored after being sorted according to the sort
 ## What's more
 
 - To load data into the table created, you can refer to [Loading overview](../../loading/loading_introduction/Loading_intro.md) to choose an appropriate load options.
-- If you need to change data in the Primary Key table, you can refer to [change data through loading](../../loading/Load_to_Primary_Key_tables.md) or use DML ([INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md), [UPDATE](../../sql-reference/sql-statements/data-manipulation/UPDATE.md), and [DELETE](../../sql-reference/sql-statements/data-manipulation/DELETE.md)).
+- If you need to change data in the Primary Key table, you can refer to [change data through loading](../../loading/Load_to_Primary_Key_tables.md) or use DML ([INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md), [UPDATE](../../sql-reference/sql-statements/table_bucket_part_index/UPDATE.md), and [DELETE](../../sql-reference/sql-statements/table_bucket_part_index/DELETE.md)).
 - If you want to further accelerate queries, you can refer to [Query Acceleration](../../cover_pages/query_acceleration.mdx).
-- If you need to modify the table schema, you can refer to [ALTER TABLE](../../sql-reference/sql-statements/data-definition/ALTER_RESOURCE.md).
+- If you need to modify the table schema, you can refer to [ALTER TABLE](../../sql-reference/sql-statements/Resource/ALTER_RESOURCE.md).
 - An [AUTO_INCREMENT](../../sql-reference/sql-statements/generated_columns.md) column can be used as the Primary Key.
diff --git a/docs/en/table_design/table_types/table_capabilities.md b/docs/en/table_design/table_types/table_capabilities.md
index a33c12f54326ca..83c5514b30cf9e 100644
--- a/docs/en/table_design/table_types/table_capabilities.md
+++ b/docs/en/table_design/table_types/table_capabilities.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Capabilities of different table types
@@ -35,7 +35,7 @@ On the other hand, the value columns support basic data types, including numeric
 <thead>
 <tr><th> </th><th><strong>Primary Key</strong> <strong>Table</strong></th><th><strong>Duplicate Key table</strong></th><th><strong>Aggregate table</strong></th><th><strong>Unique Key table</strong></th></tr>
 </thead>
-<tbody><tr><td><strong>INSERT through data loading</strong> </td><td  rowspan="2">Supported. [Configure <code>__op=0</code> in the load job to achieve INSERT](../../loading/Load_to_Primary_Key_tables.md). <br /> In the internal implementation, StarRocks considers both INSERT and UPDATE operations as UPSERT operations.</td><td>Supported</td><td>Supported (Data rows with the same aggregate Key value will be aggregated.)</td><td>Supported (Data rows with the same unique key value will be updated.) </td></tr><tr><td><strong>UPDATE through data loading</strong> </td><td>Not supported </td><td>Supported (This can be achieved by using replace as the aggregate function.) </td><td>Supported (The Unique Key table itself can be considered as an Aggregate table using the replace aggregate function.) </td></tr><tr><td><strong>DELETE through data loading</strong> </td><td>Supported. [Configure <code>__op=1</code> in the load job to achieve DELETE](../../loading/Load_to_Primary_Key_tables.md). </td><td colspan="3">Not supported </td></tr><tr><td><strong>Integrity of data column values to be loaded</strong> </td><td>By default, all column values need to be loaded. However, if partial column update (<code>partial_update</code>) is enabled, or a column has a default value, not all column values need to be loaded.</td><td>By default, all column values need to be loaded. However, if a column has a default value, not all column values need to be loaded. </td><td>By default, all column values need to be loaded. However, Aggregate tables can achieve partial column update by specifying the aggregate functions for value columns as REPLACE_IF_NOT_NULL. For details, see [aggr_type](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md#column_definition). Also, if a column has a default value, not all column values need to be loaded.</td><td>By default, all column values need to be loaded. However, if a column has a default value, not all column values need to be loaded.</td></tr><tr><td><strong>[DML INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md)</strong></td><td colspan="4">Supported</td></tr><tr><td><strong>[DML UPDATE](../../sql-reference/sql-statements/data-manipulation/UPDATE.md)</strong> </td><td><ul><li>Key columns as filter conditions: Supported</li><li>Value columns as filter conditions: Supported </li></ul></td><td colspan="3">Not supported</td></tr><tr><td><strong>[DML DELETE](../../sql-reference/sql-statements/data-manipulation/DELETE.md)</strong></td><td><ul><li>Key columns as filter conditions: Supported</li><li>Value columns as filter conditions: Supported</li></ul></td><td><ul><li>Key columns as filter conditions: Supported</li><li>Value columns as filter conditions: Supported</li></ul>Note that only simple filter conditions based on key or value columns themselves are supported, such as =, &lt;, &gt;. Complex filter conditions, such as functions or subqueries, are not supported.</td><td colspan="2"><ul><li>Key columns as filter conditions: Supported. Note that only simple filter conditions based on key columns themselves are supported, such as =, &lt;, &gt;. Complex filter conditions, such as functions or subqueries, are not supported.</li><li>Value columns as filter conditions: Not supported.</li></ul> </td></tr></tbody>
+<tbody><tr><td><strong>INSERT through data loading</strong> </td><td  rowspan="2">Supported. [Configure <code>__op=0</code> in the load job to achieve INSERT](../../loading/Load_to_Primary_Key_tables.md). <br /> In the internal implementation, StarRocks considers both INSERT and UPDATE operations as UPSERT operations.</td><td>Supported</td><td>Supported (Data rows with the same aggregate Key value will be aggregated.)</td><td>Supported (Data rows with the same unique key value will be updated.) </td></tr><tr><td><strong>UPDATE through data loading</strong> </td><td>Not supported </td><td>Supported (This can be achieved by using replace as the aggregate function.) </td><td>Supported (The Unique Key table itself can be considered as an Aggregate table using the replace aggregate function.) </td></tr><tr><td><strong>DELETE through data loading</strong> </td><td>Supported. [Configure <code>__op=1</code> in the load job to achieve DELETE](../../loading/Load_to_Primary_Key_tables.md). </td><td colspan="3">Not supported </td></tr><tr><td><strong>Integrity of data column values to be loaded</strong> </td><td>By default, all column values need to be loaded. However, if partial column update (<code>partial_update</code>) is enabled, or a column has a default value, not all column values need to be loaded.</td><td>By default, all column values need to be loaded. However, if a column has a default value, not all column values need to be loaded. </td><td>By default, all column values need to be loaded. However, Aggregate tables can achieve partial column update by specifying the aggregate functions for value columns as REPLACE_IF_NOT_NULL. For details, see [aggr_type](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md#column_definition). Also, if a column has a default value, not all column values need to be loaded.</td><td>By default, all column values need to be loaded. However, if a column has a default value, not all column values need to be loaded.</td></tr><tr><td><strong>[DML INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md)</strong></td><td colspan="4">Supported</td></tr><tr><td><strong>[DML UPDATE](../../sql-reference/sql-statements/table_bucket_part_index/UPDATE.md)</strong> </td><td><ul><li>Key columns as filter conditions: Supported</li><li>Value columns as filter conditions: Supported </li></ul></td><td colspan="3">Not supported</td></tr><tr><td><strong>[DML DELETE](../../sql-reference/sql-statements/table_bucket_part_index/DELETE.md)</strong></td><td><ul><li>Key columns as filter conditions: Supported</li><li>Value columns as filter conditions: Supported</li></ul></td><td><ul><li>Key columns as filter conditions: Supported</li><li>Value columns as filter conditions: Supported</li></ul>Note that only simple filter conditions based on key or value columns themselves are supported, such as =, &lt;, &gt;. Complex filter conditions, such as functions or subqueries, are not supported.</td><td colspan="2"><ul><li>Key columns as filter conditions: Supported. Note that only simple filter conditions based on key columns themselves are supported, such as =, &lt;, &gt;. Complex filter conditions, such as functions or subqueries, are not supported.</li><li>Value columns as filter conditions: Not supported.</li></ul> </td></tr></tbody>
 </table>
 
 ## Compatibility with other features
diff --git a/docs/en/table_design/table_types/table_types.md b/docs/en/table_design/table_types/table_types.md
index 67ffb6c34b4672..62b3e1463d3dea 100644
--- a/docs/en/table_design/table_types/table_types.md
+++ b/docs/en/table_design/table_types/table_types.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Overview of table types
diff --git a/docs/en/table_design/table_types/unique_key_table.md b/docs/en/table_design/table_types/unique_key_table.md
index 38e65f67c2566a..4c5070a7d830ac 100644
--- a/docs/en/table_design/table_types/unique_key_table.md
+++ b/docs/en/table_design/table_types/unique_key_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Unique Key table
diff --git a/docs/en/unloading/Export.md b/docs/en/unloading/Export.md
index 26f57117edc8b1..19d3d58f37b166 100644
--- a/docs/en/unloading/Export.md
+++ b/docs/en/unloading/Export.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Export data using EXPORT
@@ -34,7 +34,7 @@ When your data is stored in HDFS, however, broker-free unloading may not work an
 
 - If the FEs in your StarRocks cluster restart or a new leader FE is elected when an export job is running, the export job fails. In this situation, you must submit the export job again.
 
-- If the FEs in your StarRocks cluster restart or a new leader FE is elected after an export job finishes, some of the job information returned by the [SHOW EXPORT](../sql-reference/sql-statements/data-manipulation/SHOW_EXPORT.md) statement may be lost.
+- If the FEs in your StarRocks cluster restart or a new leader FE is elected after an export job finishes, some of the job information returned by the [SHOW EXPORT](../sql-reference/sql-statements/loading_unloading/unloading/SHOW_EXPORT.md) statement may be lost.
 
 - StarRocks exports only the data of base tables. StarRocks does not export the data of materialized views created on base tables.
 
@@ -100,7 +100,7 @@ WITH BROKER
 );
 ```
 
-For detailed syntax and parameter descriptions as well as the command examples of exporting data to AWS S3, see [EXPORT](../sql-reference/sql-statements/data-manipulation/EXPORT.md).
+For detailed syntax and parameter descriptions as well as the command examples of exporting data to AWS S3, see [EXPORT](../sql-reference/sql-statements/loading_unloading/unloading/EXPORT.md).
 
 ### Obtain the query ID of an export job
 
@@ -135,7 +135,7 @@ Timeout: 3600
 ErrorMsg: N/A
 ```
 
-For detailed syntax and parameter descriptions, see [SHOW EXPORT](../sql-reference/sql-statements/data-manipulation/SHOW_EXPORT.md).
+For detailed syntax and parameter descriptions, see [SHOW EXPORT](../sql-reference/sql-statements/loading_unloading/unloading/SHOW_EXPORT.md).
 
 ### Cancel an export job
 
@@ -149,7 +149,7 @@ CANCEL EXPORT WHERE queryid = "921d8f80-7c9d-11eb-9342-acde48001122";
 >
 > In the preceding example, `queryid` is the query ID of the export job.
 
-For detailed syntax and parameter descriptions, see [CANCEL EXPORT](../sql-reference/sql-statements/data-manipulation/CANCEL_EXPORT.md).
+For detailed syntax and parameter descriptions, see [CANCEL EXPORT](../sql-reference/sql-statements/loading_unloading/unloading/CANCEL_EXPORT.md).
 
 ## Best practices
 
diff --git a/docs/en/unloading/Flink_connector.md b/docs/en/unloading/Flink_connector.md
index d00fad217980e9..e2eb39ef1dbaa3 100644
--- a/docs/en/unloading/Flink_connector.md
+++ b/docs/en/unloading/Flink_connector.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Read data from StarRocks using Flink connector
diff --git a/docs/en/unloading/Spark_connector.md b/docs/en/unloading/Spark_connector.md
index 5c973d0938f80f..8da2bbb9580271 100644
--- a/docs/en/unloading/Spark_connector.md
+++ b/docs/en/unloading/Spark_connector.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Read data from StarRocks using Spark connector
diff --git a/docs/en/unloading/feature-support-loading-and-unloading.mdx b/docs/en/unloading/feature-support-loading-and-unloading.mdx
index 3cc55cd3e35e90..3bf7cc29a6f477 100644
--- a/docs/en/unloading/feature-support-loading-and-unloading.mdx
+++ b/docs/en/unloading/feature-support-loading-and-unloading.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_label: "Feature Support"
 title: "Feature Support: Data Loading and Unloading"
 ---
diff --git a/docs/en/unloading/unload_using_insert_into_files.md b/docs/en/unloading/unload_using_insert_into_files.md
index 26af43f91a1ad2..4e343b3b7115a8 100644
--- a/docs/en/unloading/unload_using_insert_into_files.md
+++ b/docs/en/unloading/unload_using_insert_into_files.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Unload data using INSERT INTO FILES
@@ -203,5 +203,5 @@ SELECT * FROM sales_records;
 
 ## See also
 
-- For more instructions on the usage of INSERT, see [SQL reference - INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md).
+- For more instructions on the usage of INSERT, see [SQL reference - INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md).
 - For more instructions on the usage of FILES(), see [SQL reference - FILES()](../sql-reference/sql-functions/table-functions/files.md).
diff --git a/docs/en/unloading/unloading.mdx b/docs/en/unloading/unloading.mdx
index 23cd9267e81e6b..58bb11e502370d 100644
--- a/docs/en/unloading/unloading.mdx
+++ b/docs/en/unloading/unloading.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Data Unloading
diff --git a/docs/en/using_starrocks/Colocate_join.md b/docs/en/using_starrocks/Colocate_join.md
index c1255e732ddba0..ab5eac764f98f4 100644
--- a/docs/en/using_starrocks/Colocate_join.md
+++ b/docs/en/using_starrocks/Colocate_join.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Colocate Join
diff --git a/docs/en/using_starrocks/Cost_based_optimizer.md b/docs/en/using_starrocks/Cost_based_optimizer.md
index 0db4f97aa40d1f..c1b6ecf6919fc1 100644
--- a/docs/en/using_starrocks/Cost_based_optimizer.md
+++ b/docs/en/using_starrocks/Cost_based_optimizer.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Gather statistics for CBO
@@ -690,6 +690,6 @@ DROP STATS tbl_name
 
 ## References
 
-- To query FE configuration items, run [ADMIN SHOW CONFIG](../sql-reference/sql-statements/Administration/ADMIN_SHOW_CONFIG.md).
+- To query FE configuration items, run [ADMIN SHOW CONFIG](../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SHOW_CONFIG.md).
 
-- To modify FE configuration items, run [ADMIN SET CONFIG](../sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md).
+- To modify FE configuration items, run [ADMIN SET CONFIG](../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md).
diff --git a/docs/en/using_starrocks/Flat_json.md b/docs/en/using_starrocks/Flat_json.md
index d4cf184659f5d5..abedec574c49cd 100644
--- a/docs/en/using_starrocks/Flat_json.md
+++ b/docs/en/using_starrocks/Flat_json.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # [Preview] Flat JSON
diff --git a/docs/en/using_starrocks/Lateral_join.md b/docs/en/using_starrocks/Lateral_join.md
index 5f304f174a2ad6..0339ee18bdcfb2 100644
--- a/docs/en/using_starrocks/Lateral_join.md
+++ b/docs/en/using_starrocks/Lateral_join.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 keywords: ['explode']
 ---
 
diff --git a/docs/en/using_starrocks/Materialized_view-single_table.md b/docs/en/using_starrocks/Materialized_view-single_table.md
index 81ceb89c58997c..e92e2bf8a40a99 100644
--- a/docs/en/using_starrocks/Materialized_view-single_table.md
+++ b/docs/en/using_starrocks/Materialized_view-single_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Synchronous materialized view
@@ -141,7 +141,7 @@ It can be observed that the query takes about 0.02 seconds, and no synchronous m
 
 ## Create a synchronous materialized view
 
-You can create a synchronous materialized view based on a specific query statement using [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md).
+You can create a synchronous materialized view based on a specific query statement using [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md).
 
 Based on the table `sales_records` and the query statement mentioned above, the following example creates the synchronous materialized view `store_amt` to analyze the sum of sales amount in each store.
 
@@ -164,7 +164,7 @@ GROUP BY store_id;
 
 ## Check the building status of a synchronous materialized view
 
-Creating a synchronous materialized view is an asynchronous operation. Executing CREATE MATERIALIZED VIEW successfully indicates that the task of creating the materialized view is submitted successfully. You can view the building status of the synchronous materialized view in a database via [SHOW ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW.md).
+Creating a synchronous materialized view is an asynchronous operation. Executing CREATE MATERIALIZED VIEW successfully indicates that the task of creating the materialized view is submitted successfully. You can view the building status of the synchronous materialized view in a database via [SHOW ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/SHOW_ALTER_MATERIALIZED_VIEW.md).
 
 ```Plain
 MySQL > SHOW ALTER MATERIALIZED VIEW\G
@@ -328,7 +328,7 @@ CANCEL ALTER TABLE ROLLUP FROM sales_records (12090);
 
 ### Drop an existing synchronous materialized view
 
-You can drop an existing synchronous materialized view with the [DROP MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW.md) command.
+You can drop an existing synchronous materialized view with the [DROP MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/DROP_MATERIALIZED_VIEW.md) command.
 
 ```SQL
 DROP MATERIALIZED VIEW store_amt;
diff --git a/docs/en/using_starrocks/Materialized_view.md b/docs/en/using_starrocks/Materialized_view.md
index 7e24aefa3b2863..84b617235bf438 100644
--- a/docs/en/using_starrocks/Materialized_view.md
+++ b/docs/en/using_starrocks/Materialized_view.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Asynchronous materialized views
@@ -153,7 +153,7 @@ GROUP BY order_id;
 
 ### Create the materialized view
 
-You can create a materialized view based on a specific query statement using [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md).
+You can create a materialized view based on a specific query statement using [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md).
 
 Based on the table `goods`, `order_list`, and the query statement mentioned above, the following example creates the materialized view `order_mv` to analyze the total of each order. The materialized view is set to refresh itself at an interval of one day.
 
@@ -175,7 +175,7 @@ GROUP BY order_id;
 > - Asynchronous materialized views support a dynamic partitioning strategy in a longer span. For example, if the base table is partitioned at an interval of one day, you can set the materialized view to be partitioned at an interval of one month.
 > - Currently, StarRocks does not support creating asynchronous materialized views with the list partitioning strategy or based on tables that are created with the list partitioning strategy.
 > - The query statement used to create a materialized view does not support random functions, including rand(), random(), uuid(), and sleep().
-> - Asynchronous materialized views support a variety of data types. For more information, see [CREATE MATERIALIZED VIEW - Supported data types](../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md#supported-data-types).
+> - Asynchronous materialized views support a variety of data types. For more information, see [CREATE MATERIALIZED VIEW - Supported data types](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md#supported-data-types).
 > - By default, executing a CREATE MATERIALIZED VIEW statement immediately triggers the refresh task, which can consume a certain proportion of the system resources. If you want to defer the refresh task, you can add the REFRESH DEFERRED parameter to your CREATE MATERIALIZED VIEW statement.
 
 - **About refresh mechanisms of asynchronous materialized views**
@@ -190,7 +190,7 @@ GROUP BY order_id;
   - You can specify the base tables where data changes will not automatically trigger a refresh of the corresponding materialized view.
   - You can assign a resource group to the refresh task.
 
-  For more information, see the **PROPERTIES** section in [CREATE MATERIALIZED VIEW - Parameters](../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md#parameters). You can also modify the mechanisms of an existing asynchronous materialized view using [ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md).
+  For more information, see the **PROPERTIES** section in [CREATE MATERIALIZED VIEW - Parameters](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md#parameters). You can also modify the mechanisms of an existing asynchronous materialized view using [ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/ALTER_MATERIALIZED_VIEW.md).
 
   > **CAUTION**
   >
@@ -206,7 +206,7 @@ GROUP BY order_id;
 
 ## Manually refresh an asynchronous materialized view
 
-You can refresh an asynchronous materialized view regardless of its refreshing strategy via [REFRESH MATERIALIZED VIEW](../sql-reference/sql-statements/data-manipulation/REFRESH_MATERIALIZED_VIEW.md). StarRocks v2.5 supports refreshing specific partitions of an asynchronous materialized view by specifying partition names. StarRocks v3.1 supports making a synchronous call of the refresh task, and the SQL statement is returned only when the task succeeds or fails.
+You can refresh an asynchronous materialized view regardless of its refreshing strategy via [REFRESH MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/REFRESH_MATERIALIZED_VIEW.md). StarRocks v2.5 supports refreshing specific partitions of an asynchronous materialized view by specifying partition names. StarRocks v3.1 supports making a synchronous call of the refresh task, and the SQL statement is returned only when the task succeeds or fails.
 
 ```SQL
 -- Refresh the materialized view via an asynchronous call (default).
@@ -215,7 +215,7 @@ REFRESH MATERIALIZED VIEW order_mv;
 REFRESH MATERIALIZED VIEW order_mv WITH SYNC MODE;
 ```
 
-You can cancel a refresh task submitted via an asynchronous call using [CANCEL REFRESH MATERIALIZED VIEW](../sql-reference/sql-statements/data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW.md).
+You can cancel a refresh task submitted via an asynchronous call using [CANCEL REFRESH MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/CANCEL_REFRESH_MATERIALIZED_VIEW.md).
 
 ## Query the asynchronous materialized view directly
 
@@ -251,7 +251,7 @@ Currently, StarRocks supports rewriting queries on asynchronous materialized vie
 
 ### Alter an asynchronous materialized view
 
-You can alter the property of an asynchronous materialized view using [ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md).
+You can alter the property of an asynchronous materialized view using [ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/ALTER_MATERIALIZED_VIEW.md).
 
 - Enable an inactive materialized view.
 
@@ -273,7 +273,7 @@ You can alter the property of an asynchronous materialized view using [ALTER MAT
 
 ### Show asynchronous materialized views
 
-You can view the asynchronous materialized views in your database by using [SHOW MATERIALIZED VIEWS](../sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md) or querying the system metadata view in Information Schema.
+You can view the asynchronous materialized views in your database by using [SHOW MATERIALIZED VIEWS](../sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md) or querying the system metadata view in Information Schema.
 
 - Check all asynchronous materialized views in your database.
 
@@ -293,7 +293,7 @@ You can view the asynchronous materialized views in your database by using [SHOW
   SHOW MATERIALIZED VIEWS WHERE NAME LIKE "order%";
   ```
 
-- Check all asynchronous materialized views by querying the metadata view `materialized_views` in Information Schema. For more information, please refer to [information_schema.materialized_views](../reference/information_schema/materialized_views.md).
+- Check all asynchronous materialized views by querying the metadata view `materialized_views` in Information Schema. For more information, please refer to [information_schema.materialized_views](../sql-reference/information_schema/materialized_views.md).
 
   ```SQL
   SELECT * FROM information_schema.materialized_views;
@@ -301,7 +301,7 @@ You can view the asynchronous materialized views in your database by using [SHOW
 
 ### Check the definition of asynchronous materialized view
 
-You can check the query used to create an asynchronous materialized view via [SHOW CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_MATERIALIZED_VIEW.md).
+You can check the query used to create an asynchronous materialized view via [SHOW CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/SHOW_CREATE_MATERIALIZED_VIEW.md).
 
 ```SQL
 SHOW CREATE MATERIALIZED VIEW order_mv;
@@ -309,7 +309,7 @@ SHOW CREATE MATERIALIZED VIEW order_mv;
 
 ### Check the execution status of asynchronous materialized view
 
-You can check the execution (building or refreshing) status of an asynchronous materialized view by querying the [`tasks`](../reference/information_schema/tasks.md) and [`task_runs`](../reference/information_schema/task_runs.md) in [Information Schema](../reference/overview-pages/information_schema.md).
+You can check the execution (building or refreshing) status of an asynchronous materialized view by querying the [`tasks`](../sql-reference/information_schema/tasks.md) and [`task_runs`](../sql-reference/information_schema/task_runs.md) in [Information Schema](../sql-reference/information_schema/information_schema.md).
 
 The following example checks the execution status of the materialized view that was created most recently:
 
@@ -352,7 +352,7 @@ The following example checks the execution status of the materialized view that
 
 ### Drop an asynchronous materialized view
 
-You can drop an asynchronous materialized view via [DROP MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW.md).
+You can drop an asynchronous materialized view via [DROP MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/DROP_MATERIALIZED_VIEW.md).
 
 ```Plain
 DROP MATERIALIZED VIEW order_mv;
diff --git a/docs/en/using_starrocks/Using_HLL.md b/docs/en/using_starrocks/Using_HLL.md
index 99d9b3ba7acf8f..4c2adb8618d8a1 100644
--- a/docs/en/using_starrocks/Using_HLL.md
+++ b/docs/en/using_starrocks/Using_HLL.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Use HLL for approximate count distinct
@@ -77,7 +77,7 @@ DISTRIBUTED BY HASH(ID);
 
 > * Note: When the data volume is large, it is better to create a corresponding rollup table for high frequency HLL queries
 
-Load data using [Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md):
+Load data using [Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md):
 
 ~~~bash
 curl --location-trusted -u <username>:<password> -H "label:label_1600997542287" \
diff --git a/docs/en/using_starrocks/Using_bitmap.md b/docs/en/using_starrocks/Using_bitmap.md
index 9443a8cb293820..84667c03014009 100644
--- a/docs/en/using_starrocks/Using_bitmap.md
+++ b/docs/en/using_starrocks/Using_bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Use Bitmap for exact Count Distinct
diff --git a/docs/en/using_starrocks/block_cache.md b/docs/en/using_starrocks/block_cache.md
index 525c19566d8807..bd0a698d6e3e5d 100644
--- a/docs/en/using_starrocks/block_cache.md
+++ b/docs/en/using_starrocks/block_cache.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 toc_max_heading_level: 2
 ---
 
diff --git a/docs/en/using_starrocks/create_partitioned_materialized_view.md b/docs/en/using_starrocks/create_partitioned_materialized_view.md
index df31414a72e1c9..d1d3eb3e4472ce 100644
--- a/docs/en/using_starrocks/create_partitioned_materialized_view.md
+++ b/docs/en/using_starrocks/create_partitioned_materialized_view.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Create a partitioned materialized view
@@ -197,17 +197,17 @@ You can create a materialized view whose partitioning granularity is larger than
 
 ### Align partitions at a customized time granularity
 
-The partition rollup method mentioned above only allows partitioning the materialized view based on specific time granularities and does not permit customizing the partition time range. If your business scenario requires partitioning using a customized time granularity, you can create a materialized view and define the time granularity for its partitions by using the date_trunc function with the [time_slice](../sql-reference/sql-functions/date-time-functions/time_slice.md) or [date_slice](../sql-reference/sql-functions/date-time-functions/date_slice.md) function, which can convert a given time into the beginning or end of a time interval based on the specified time granularity.
+The partition rollup method mentioned above only allows partitioning the materialized view based on specific time granularities and does not permit customizing the partition time range. If your business scenario requires partitioning using a customized time granularity, you can create a materialized view and define the time granularity for its partitions by using the date_trunc function with the [time_slice](../sql-reference/sql-functions/date-time-functions/time_slice.md)  function, which can convert a given time into the beginning or end of a time interval based on the specified time granularity.
 
-You need to define the new time granularity (interval) by using the time_slice or date_slice function on the Partitioning Key of the base table in the SELECT list, set an alias for it, and use it in the date_trunc function to specify the Partitioning Key of the materialized view.
+You need to define the new time granularity (interval) by using the time_slice function on the Partitioning Key of the base table in the SELECT list, set an alias for it, and use it in the date_trunc function to specify the Partitioning Key of the materialized view.
 
 ```SQL
 PARTITION BY
 date_trunc(<format>, <mv_partitioning_column>)
 AS
 SELECT 
-  -- You can use time_slice or date_slice.
-  date_slice(<base_table_partitioning_column>, <interval>) AS <mv_partitioning_column>
+  -- You can use time_slice.
+  time_slice(<base_table_partitioning_column>, <interval>) AS <mv_partitioning_column>
 ```
 
 Example:
diff --git a/docs/en/using_starrocks/data_lake_query_acceleration_with_materialized_views.md b/docs/en/using_starrocks/data_lake_query_acceleration_with_materialized_views.md
index 44f04655ae4e06..fc748865fad7e9 100644
--- a/docs/en/using_starrocks/data_lake_query_acceleration_with_materialized_views.md
+++ b/docs/en/using_starrocks/data_lake_query_acceleration_with_materialized_views.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Data lake query acceleration with materialized views
@@ -100,7 +100,7 @@ For Hive Catalog, Iceberg Catalog (starting from v3.1.4), JDBC catalog (starting
 
 :::tip
 
-You can still choose to tolerate a certain level of data inconsistency by setting the property `mv_rewrite_staleness_second` when creating the materialized view. For more information, see [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md).
+You can still choose to tolerate a certain level of data inconsistency by setting the property `mv_rewrite_staleness_second` when creating the materialized view. For more information, see [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md).
 
 :::
 
@@ -136,7 +136,7 @@ FROM `iceberg`.`test`.`iceberg_sample_datetime_day`;
 
 For Hive catalogs, you can enable the Hive metadata cache refresh feature to allow StarRocks to detect data changes at the partition level. When this feature is enabled, StarRocks periodically accesses the Hive Metastore Service (HMS) or AWS Glue to check the metadata information of recently queried hot data.
 
-To enable the Hive metadata cache refresh feature, you can set the following FE dynamic configuration item using [ADMIN SET FRONTEND CONFIG](../sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md):
+To enable the Hive metadata cache refresh feature, you can set the following FE dynamic configuration item using [ADMIN SET FRONTEND CONFIG](../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md):
 
 ### Configuration items
 
diff --git a/docs/en/using_starrocks/data_modeling_with_materialized_views.md b/docs/en/using_starrocks/data_modeling_with_materialized_views.md
index 8107fa93f7b5cd..4af25cd1119c40 100644
--- a/docs/en/using_starrocks/data_modeling_with_materialized_views.md
+++ b/docs/en/using_starrocks/data_modeling_with_materialized_views.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Data modeling with materialized views
@@ -179,7 +179,7 @@ Several parameters can be used to control refresh behavior:
 - `excluded_trigger_tables`: the table whose data changes can be ignored to avoid triggering the automatic refresh.
 - `auto_refresh_partitions_limit`: the number of partitions to refresh in each automatic refresh operation.
 
-For more information, see [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md).
+For more information, see [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md).
 
 Currently, partitioned materialized views have the following limitations:
 
diff --git a/docs/en/using_starrocks/feature-support-asynchronous-materialized-views.md b/docs/en/using_starrocks/feature-support-asynchronous-materialized-views.md
index 2af90b2467e9fb..52f6a2462dc1cd 100644
--- a/docs/en/using_starrocks/feature-support-asynchronous-materialized-views.md
+++ b/docs/en/using_starrocks/feature-support-asynchronous-materialized-views.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 sidebar_label: "Feature Support"
 ---
 
diff --git a/docs/en/using_starrocks/mv_ref.md b/docs/en/using_starrocks/mv_ref.md
new file mode 100644
index 00000000000000..4e5da8e8f40721
--- /dev/null
+++ b/docs/en/using_starrocks/mv_ref.md
@@ -0,0 +1,11 @@
+---
+displayed_sidebar: docs
+---
+
+# Asynch Materialized view reference
+
+- [CREATE](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md)
+- [ALTER](../sql-reference/sql-statements/materialized_view/ALTER_MATERIALIZED_VIEW.md)
+- [DROP](../sql-reference/sql-statements/materialized_view/DROP_MATERIALIZED_VIEW.md)
+- [SHOW](../sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md)
+- [Information schema](../sql-reference/information_schema/materialized_views.md)
diff --git a/docs/en/using_starrocks/query_acceleration_with_auto_increment.md b/docs/en/using_starrocks/query_acceleration_with_auto_increment.md
index 604abefd609872..1646750590f83c 100644
--- a/docs/en/using_starrocks/query_acceleration_with_auto_increment.md
+++ b/docs/en/using_starrocks/query_acceleration_with_auto_increment.md
@@ -1,7 +1,240 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
-# Query acceleration with auto increment
+# Accelerate COUNT(DISTINCT) and Joins with AUTO INCREMENT and Global Dictionary
 
-Currently not available in English.
+This topic describes how to accelerate COUNT(DISTINCT) calculation and Joins using AUTO INCREMENT columns and Global Dictionary.
+
+## Use Cases
+
+- **Scenario one**: Suppose you need to perform exact deduplication on massive data (such as retail or delivery orders). However, the column for deduplication is of STRING type, which may lead to suboptimal performance during counting. For instance, in the `orders` table, the `order_uuid` column representing order ID is of STRING type, typically 32 to 36 bytes in size, generated by `UUID()` or similar functions. In this case, COUNT(DISTINCT) on the STRING column `order_uuid` with a query like `SELECT count(DISTINCT order_uuid) FROM orders WHERE create_date >= CURDATE();` might not deliver satisfactory performance. Using an INTEGER column for exact deduplication would significantly enhance performance.
+
+- **Scenario two**: Suppose you want to [accelerate exact deduplication in multi-dimensional analysis using bitmap functions](../using_starrocks/Using_bitmap.md). The `bitmap_count()` function requires INTEGER input, but if the column to be deduplicated is of STRING type, you need to use the `bitmap_hash()` function. This may result in approximate, slightly lower deduplication counts and could also reduce query performance and increase storage requirements, as the INTEGER values generated by bitmap_hash() are more dispersed compared to sequentially assigned INTEGER values.
+
+- **Scenario three**: Suppose you need to query the number of orders with a short time span between placing and paying for the order, where the order placement and payment times might be stored in different tables maintained by different business teams. You might need to join these tables based on the order ID and then deduplicate the orders. For example:
+
+  ```SQL
+  SELECT count(distinct order_uuid)
+  FROM orders_t1 as t1 JOIN orders_t2 as t2
+      ON t1.order_uuid = t2.order_uuid
+  WHERE t2.payment_time - t1.create_time <= 3600
+      AND create_date >= CURDATE();
+  ```
+
+  However, using a STRING type `order_uuid` column for joins is less efficient than using an INTEGER column.
+
+## Optimization Approach
+
+To address the the issues in the above scenarios, the optimization approach involves loading order data into a target table and establishing a mapping between STRING and INTEGER values. Subsequent query analysis will be based on the INTEGER column. This approach can be divided into the following stages:
+
+1. Stage 1: Create a global dictionary and establish a mapping between STRING and INTEGER values. In this dictionary, the key column is of STRING type, and the value column is an AUTO INCREMENT INTEGER type. When data is loaded, the system automatically generates a unique ID for each STRING value, creating a mapping between STRING and INTEGER values.
+
+2. Stage 2: Load the mapping relationship between order data and the global dictionary into the target table.
+
+3. Stage 3: Use the INTEGER column from the target table for exact deduplication or joins during subsequent query analysis, which can significantly improve performance.
+
+4. Stage 4: For further performance optimization, you can use bitmap functions on the INTEGER column to accelerate exact deduplication.
+
+## Solution
+
+Before v3.2.5, Stage 2 could be implemented through two methods:
+
+- Using an external table or an internal table as intermediate table to join with the dictionary table to obtain the corresponding dictionary ID before loading.
+- Using a Primary Key table for data loading, and then using an UPDATE statement with a JOIN operation to update the dictionary ID. However, this data loading process can be inconvenient and comes with many constraints.
+
+From v3.2.5 onwards, StarRocks introduced the `dict_mapping()` function, allowing you to define the dictionary ID column in the target table as a generated column using the `dict_mapping()` expression. Subsequent data loading tasks are handled like regular data loading, without needing UPDATE statements with JOIN operations to write dictionary IDs. During data loading, the system automatically associates the original table with the dictionary table and inserts the corresponding dictionary ID, greatly simplifying the data loading process with a global dictionary table, regardless of table types and supporting various loading methods.
+
+### Business Scenario
+
+The following example uses two example CSV files, `batch1.csv` and `batch2.csv`, each containing two columns: `id` and `order_uuid`.
+
+- `batch1.csv`
+
+  ```csv
+  1, a1
+  2, a2
+  3, a3
+  11, a1
+  11, a2
+  12, a1
+  ```
+
+- `batch2.csv`
+
+  ```csv
+  1, a2
+  2, a2
+  3, a2
+  11, a2
+  12, a101
+  12, a102
+  13, a102
+  ```
+
+### Process
+
+#### Stage one
+
+Create a global dictionary table and load the order ID column values from the CSV files to establish a mapping between STRING and INTEGER values.
+
+1. Create a Primary Key table to serve as the global dictionary. Define the Primary Key, `order_uuid` (of STRING type), and the value column, `order_id_int` (of AUTO INCREMENT INTEGER type).
+
+    :::info
+
+    The `dict_mapping` function requires the global dictionary table to be a Primary Key table.
+
+    :::
+
+    ```SQL
+    CREATE TABLE dict (
+        order_uuid STRING,
+        order_id_int BIGINT AUTO_INCREMENT  -- Automatically assign an ID to each order_uuid value.
+    )
+    PRIMARY KEY (order_uuid)
+    DISTRIBUTED BY HASH (order_uuid)
+    PROPERTIES("replicated_storage" = "true");
+    ```
+
+2. Use Stream Load to batch load the `order_uuid` column from the two CSV files into the `order_uuid` column of the dictionary table `dict`. Make sure you have used the Partial Update in column mode.
+
+    ```Bash
+    curl --location-trusted -u root: \
+        -H "partial_update: true" \
+        -H "format: CSV" -H "column_separator:," -H "columns: id, order_uuid" \
+        -T batch1.csv \
+        -XPUT http://<fe_host>:<fe_http_port>/api/example_db/dict/_stream_load
+        
+    curl --location-trusted -u root: \
+        -H "partial_update: true" \
+        -H "format: CSV" -H "column_separator:," -H "columns: id, order_uuid" \
+        -T batch2.csv \
+        -XPUT http://<fe_host>:<fe_http_port>/api/example_db/dict/_stream_load
+    ```
+
+> **NOTE**
+>
+> If new data is added to the data source before proceeding to the next stage, all new data must be loaded into the dictionary table to ensure the mapping exists.
+
+#### Stage two
+
+Create a target table that includes a dictionary ID column with the `dict_mapping` attribute. When order data is loaded into the target table, the system will automatically associate it with the dictionary table and insert the corresponding dictionary ID.
+
+1. Create a table `dest_table` that includes all columns from the CSV files. You also need to define an INTEGER column `order_id_int` (typically BIGINT) to map with the STRING type `order_uuid` column and has the `dict_mapping` column attribute. Future query analysis will be based on this `order_id_int` column.
+
+    ```SQL
+    -- In the target table, define a BIGINT dict_mapping column `order_id_int` to map with the STRING-type column `order_uuid`.
+    CREATE TABLE dest_table (
+        id BIGINT,
+        order_uuid STRING, -- This column records STRING-type Order ID.
+        batch INT comment 'Used to distinguish different batch loading',
+        order_id_int BIGINT AS dict_mapping('dict', order_uuid) -- Dictionary ID dict_mapping column corresponds to `order_uuid`.
+    )
+    DUPLICATE KEY (id, order_uuid)
+    DISTRIBUTED BY HASH(id);
+    ```
+
+2. Load data into the target table with Stream Load or any other available methods. Since the `order_id_int` column has the `dict_mapping` attribute, the system will automatically fetch the dictionary ID from `dict` during loading.
+
+    ```Bash
+    curl --location-trusted -u root: \
+        -H "format: CSV" -H "column_separator:," -H "columns: id, order_uuid, batch=1" \
+        -T batch1.csv \
+        -XPUT http://<fe_host>:<fe_http_port>/api/example_db/dest_table/_stream_load
+        
+    curl --location-trusted -u root: \
+        -H "format: CSV" -H "column_separator:," -H "columns: id, order_uuid, batch=2" \
+        -T batch2.csv \
+        -XPUT http://<fe_host>:<fe_http_port>/api/example_db/dest_table/_stream_load
+    ```
+
+#### Stage three
+
+During query analysis, you can perform exact deduplication or joins on the INTEGER column `order_id_int`, significantly enhancing performance compared to using the STRING column `order_uuid`.
+
+```SQL
+-- Exact deduplication based on BIGINT-type order_id_int.
+SELECT id, COUNT(DISTINCT order_id_int) FROM dest_table GROUP BY id ORDER BY id;
+-- Exact deduplication based on STRING-type order_uuid .
+SELECT id, COUNT(DISTINCT order_uuid) FROM dest_table GROUP BY id ORDER BY id;
+```
+
+You can also [use bitmap functions to accelerate exact deduplication](#use-bitmap-functions-to-accelerate-exact-deduplication).
+
+### Use bitmap functions to accelerate exact deduplication
+
+To further accelerate the calculation, you can insert the INTEGER column values of the dictionary table directly into a bitmap column after creating a global dictionary. Subsequently, you can use bitmap functions on this bitmap column for exact deduplication.
+
+#### Method one
+
+If you have built a global dictionary and already imported the order data into `dest_table`, follow these steps:
+
+1. Create an Aggregate table `dest_table_bitmap` with two columns: a BITMAP type `order_id_bitmap` column for aggregation using the `bitmap_union()` function, and an INTEGER type column `id`. This table does not include the original STRING column, otherwise, each bitmap would contain only one value, negating the acceleration benefit.
+
+    ```SQL
+    CREATE TABLE dest_table_bitmap (
+        id BIGINT,
+        order_id_bitmap BITMAP BITMAP_UNION
+    )
+    AGGREGATE KEY (id)
+    DISTRIBUTED BY HASH(id) BUCKETS 6;
+    ```
+
+2. Insert data into `dest_table_bitmap`. Insert the data from the `id` column of `dest_table` into the `id` column, and insert the INTEGER column `order_id_int` data from the dictionary table `dict` (processed with the `to_bitmap()` function) into the `order_id_bitmap` column.
+
+    ```SQL
+    INSERT INTO dest_table_bitmap (id, order_id_bitmap)
+    SELECT id,  to_bitmap(dict_mapping('dict', order_uuid))
+    FROM dest_table
+    WHERE dest_table.batch = 1; -- Indicates different batches.
+        
+    INSERT INTO dest_table_bitmap (id, order_id_bitmap)
+    SELECT id, to_bitmap(dict_mapping('dict', order_uuid))
+    FROM dest_table
+    WHERE dest_table.batch = 2;
+    ```
+
+3. Use the `BITMAP_UNION_COUNT()` function on the BITMAP column for exact deduplication.
+
+    ```SQL
+    SELECT id, BITMAP_UNION_COUNT(order_id_bitmap) FROM dest_table_bitmap
+    GROUP BY id ORDER BY id;
+    ```
+
+#### Method two
+
+If you do not need to retain specific order data after creating a global dictionary, and you want to load data directly into the `dest_table_bitmap` table, follow these steps:
+
+1. Create an Aggregate table `dest_table_bitmap` with two columns: a BITMAP type `order_id_bitmap` column for aggregation using the `bitmap_union()` function, and an INTEGER type column `id`. This table does not include the original STRING column, otherwise, each bitmap would contain only one value, negating the acceleration benefit.
+
+    ```SQL
+    CREATE TABLE dest_table_bitmap (
+        id BIGINT,
+        order_id_bitmap BITMAP BITMAP_UNION
+    )
+    AGGREGATE KEY (id)
+    DISTRIBUTED BY HASH(id) BUCKETS 6;
+    ```
+
+2. Insert data into the Aggregate table. Insert the data from the `id` column of the CSV files into the `id` column and the INTEGER column `order_id_int` data from the dictionary table `dict` (processed with the `to_bitmap()` function) into the `order_id_bitmap` column.
+
+    ```bash
+    curl --location-trusted -u root: \
+        -H "format: CSV" -H "column_separator:," \
+        -H "columns: id, order_uuid,  order_id_bitmap=to_bitmap(dict_mapping('dict', order_uuid))" \
+        -T batch1.csv \
+        -XPUT http://<fe_host>:<fe_http_port>/api/example_db/dest_table_bitmap/_stream_load
+    
+    curl --location-trusted -u root: \
+        -H "format: CSV" -H "column_separator:," \
+        -H "columns: id, order_uuid, order_id_bitmap=to_bitmap(dict_mapping('dict', order_uuid))" \
+        -T batch2.csv \
+        -XPUT http:///<fe_host>:<fe_http_port>/api/example_db/dest_table_bitmap/_stream_load
+    ```
+
+3. Use the `BITMAP_UNION_COUNT()` function on the BITMAP column for exact deduplication.
+
+    ```SQL
+    SELECT id, BITMAP_UNION_COUNT(order_id_bitmap) FROM dest_table_bitmap
+    GROUP BY id ORDER BY id;
+    ```
diff --git a/docs/en/using_starrocks/query_cache.md b/docs/en/using_starrocks/query_cache.md
index b9a773a0973bf4..8502f9c96ee67a 100644
--- a/docs/en/using_starrocks/query_cache.md
+++ b/docs/en/using_starrocks/query_cache.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Query Cache
diff --git a/docs/en/using_starrocks/query_rewrite_with_materialized_views.md b/docs/en/using_starrocks/query_rewrite_with_materialized_views.md
index 22ceb6140ad864..3abd84372e0cfa 100644
--- a/docs/en/using_starrocks/query_rewrite_with_materialized_views.md
+++ b/docs/en/using_starrocks/query_rewrite_with_materialized_views.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Query rewrite with materialized views
@@ -1094,7 +1094,7 @@ The FE configuration item `enable_materialized_view_text_based_rewrite` controls
 
 The variable `materialized_view_subuqery_text_match_max_count` controls the maximum number of times to compare the abstract syntax trees of the materialized view and the sub-queries. The default value is `4`. Increasing this value will also increase the time consumption of the optimizer.
 
-Please note that, only when the materialized view meets the timeliness (data consistency) requirement can it be used for text-based query rewrite. You can manually set the consistency check rule using the property `query_rewrite_consistency` when creating the materialized view. For more information, see [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md).
+Please note that, only when the materialized view meets the timeliness (data consistency) requirement can it be used for text-based query rewrite. You can manually set the consistency check rule using the property `query_rewrite_consistency` when creating the materialized view. For more information, see [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md).
 
 ### Use cases
 
@@ -1236,7 +1236,7 @@ mysql> EXPLAIN SELECT
 
 By default, StarRocks enables query rewrite for asynchronous materialized views created based on the default catalog. You can disable this feature by setting the session variable `enable_materialized_view_rewrite` to `false`.
 
-For asynchronous materialized views created based on an external catalog, you can disable this feature by setting the materialized view property `force_external_table_query_rewrite` to `false` using [ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md).
+For asynchronous materialized views created based on an external catalog, you can disable this feature by setting the materialized view property `force_external_table_query_rewrite` to `false` using [ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/ALTER_MATERIALIZED_VIEW.md).
 
 ## Limitations
 
diff --git a/docs/en/using_starrocks/sorted_aggregate.md b/docs/en/using_starrocks/sorted_aggregate.md
index f710d512e81313..251b1c61ef848a 100644
--- a/docs/en/using_starrocks/sorted_aggregate.md
+++ b/docs/en/using_starrocks/sorted_aggregate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Sorted streaming aggregate
diff --git a/docs/en/using_starrocks/troubleshooting_asynchronous_materialized_views.md b/docs/en/using_starrocks/troubleshooting_asynchronous_materialized_views.md
index dc62371c606a1d..d693d9b937dd64 100644
--- a/docs/en/using_starrocks/troubleshooting_asynchronous_materialized_views.md
+++ b/docs/en/using_starrocks/troubleshooting_asynchronous_materialized_views.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "English"
+displayed_sidebar: docs
 ---
 
 # Troubleshooting asynchronous materialized views
@@ -16,14 +16,14 @@ To get a whole picture of asynchronous materialized views that you are working w
 
 ### Check the working state of an asynchronous materialized view
 
-You can check the working state of an asynchronous materialized view using [SHOW MATERIALIZED VIEWS](../sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md). Among all the information returned, you can focus on the following fields:
+You can check the working state of an asynchronous materialized view using [SHOW MATERIALIZED VIEWS](../sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md). Among all the information returned, you can focus on the following fields:
 
 - `is_active`: Whether the state of the materialized view is active. Only an active materialized view can be used for query acceleration and rewrite.
 - `last_refresh_state`: The state of the last refresh, including PENDING, RUNNING, FAILED, and SUCCESS.
 - `last_refresh_error_message`: The reason why the last refresh failed (if the materialized view state is not active).
 - `rows`: The number of data rows in the materialized view. Please note that this value can be different from the actual row count of the materialized view because the updates can be deferred.
 
-For detailed information on other fields returned, see [SHOW MATERIALIZED VIEWS - Returns](../sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md#returns).
+For detailed information on other fields returned, see [SHOW MATERIALIZED VIEWS - Returns](../sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md#returns).
 
 Example:
 
@@ -113,7 +113,7 @@ You can monitor and analyze the resource consumed by an asynchronous materialize
 
 #### Monitor resource consumption during refresh
 
-During a refresh task, you can monitor its real-time resource consumption using [SHOW PROC '/current_queries'](../sql-reference/sql-statements/Administration/SHOW_PROC.md).
+During a refresh task, you can monitor its real-time resource consumption using [SHOW PROC '/current_queries'](../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROC.md).
 
 Among all the information returned, you can focus on the following fields:
 
@@ -158,7 +158,7 @@ For detailed information on how to check the query profile and understand other
 
 ### Verify whether queries are rewritten by an asynchronous materialized view
 
-You can check whether a query can be rewritten with an asynchronous materialized view from its query plan using [EXPLAIN](../sql-reference/sql-statements/Administration/EXPLAIN.md).
+You can check whether a query can be rewritten with an asynchronous materialized view from its query plan using [EXPLAIN](../sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN.md).
 
 If the metric `SCAN` in the query plan shows the name of the corresponding materialized view, the query has been rewritten by the materialized view.
 
@@ -304,7 +304,7 @@ Large materialized views may fail to refresh because the refresh task exceeds th
   - Obtain the `query_id` corresponding to the refresh task by querying `information_schema.task_runs`.
   - Analyze the query profile of the refresh task using the following statements:
     - [GET_QUERY_PROFILE](../sql-reference/sql-functions/utility-functions/get_query_profile.md): Retrive the original query profile based on `query_id`.
-    - [ANALYZE PROFILE](../sql-reference/sql-statements/Administration/ANALYZE_PROFILE.md): Analyze the query profile on a per-fragment basis, and display it in a tree structure.
+    - [ANALYZE PROFILE](../sql-reference/sql-statements/cluster-management/plan_profile/ANALYZE_PROFILE.md): Analyze the query profile on a per-fragment basis, and display it in a tree structure.
 
 ### Materialized view state is not active
 
@@ -340,7 +340,7 @@ To stop a refresh task that occupies too many resources, you can:
   ALTER MATERIALIZED VIEW mv1 INACTIVE;
   ```
 
-- Terminate the running refresh task using [CANCEL REFRESH MATERIALIZED VIEW](../sql-reference/sql-statements/data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW.md):
+- Terminate the running refresh task using [CANCEL REFRESH MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/CANCEL_REFRESH_MATERIALIZED_VIEW.md):
 
   ```SQL
   CANCEL REFRESH MATERIALIZED VIEW mv1;
diff --git a/docs/en/using_starrocks/usage/alter.mdx b/docs/en/using_starrocks/usage/alter.mdx
deleted file mode 100644
index 6fe09963d95e74..00000000000000
--- a/docs/en/using_starrocks/usage/alter.mdx
+++ /dev/null
@@ -1,13 +0,0 @@
----
-displayed_sidebar: "English"
-sidebar_position: 1
-sidebar_label: ALTER
-title: ALTER MATERIALIZED VIEW
----
-<head>
-  <link rel="canonical" href="https://docs.starrocks.io/sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW/" />
-</head>
-
-import Content from '../../sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md';
-
-<Content />
diff --git a/docs/en/using_starrocks/usage/create.mdx b/docs/en/using_starrocks/usage/create.mdx
deleted file mode 100644
index 135098b44e5c64..00000000000000
--- a/docs/en/using_starrocks/usage/create.mdx
+++ /dev/null
@@ -1,13 +0,0 @@
----
-displayed_sidebar: "English"
-sidebar_position: 0
-sidebar_label: CREATE
-title: CREATE MATERIALIZED VIEW
----
-<head>
-  <link rel="canonical" href="https://docs.starrocks.io/sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW/" />
-</head>
-
-import Content from '../../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md';
-
-<Content />
diff --git a/docs/en/using_starrocks/usage/drop.mdx b/docs/en/using_starrocks/usage/drop.mdx
deleted file mode 100644
index 969efcd27e4a85..00000000000000
--- a/docs/en/using_starrocks/usage/drop.mdx
+++ /dev/null
@@ -1,13 +0,0 @@
----
-displayed_sidebar: "English"
-sidebar_position: 2
-sidebar_label: DROP
-title: DROP MATERIALIZED VIEW
----
-<head>
-  <link rel="canonical" href="https://docs.starrocks.io/sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW/" />
-</head>
-
-import Content from '../../sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW.md';
-
-<Content />
diff --git a/docs/en/using_starrocks/usage/information_schema-materialized_views.mdx b/docs/en/using_starrocks/usage/information_schema-materialized_views.mdx
deleted file mode 100644
index 776420106c7b6e..00000000000000
--- a/docs/en/using_starrocks/usage/information_schema-materialized_views.mdx
+++ /dev/null
@@ -1,13 +0,0 @@
----
-displayed_sidebar: "English"
-sidebar_position: 4
-sidebar_label: materialized_views
-title: materialized_views
----
-<head>
-  <link rel="canonical" href="https://docs.starrocks.io/docs/reference/information_schema/materialized_views/" />
-</head>
-
-import Content from '../../reference/information_schema/materialized_views.md';
-
-<Content />
diff --git a/docs/en/using_starrocks/usage/intro.mdx b/docs/en/using_starrocks/usage/intro.mdx
deleted file mode 100644
index 143c90f9f327e1..00000000000000
--- a/docs/en/using_starrocks/usage/intro.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "English"
----
-
-# Usage
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/en/using_starrocks/usage/show.mdx b/docs/en/using_starrocks/usage/show.mdx
deleted file mode 100644
index b6318061f59527..00000000000000
--- a/docs/en/using_starrocks/usage/show.mdx
+++ /dev/null
@@ -1,13 +0,0 @@
----
-displayed_sidebar: "English"
-sidebar_position: 3
-sidebar_label: SHOW
-title: SHOW MATERIALIZED VIEW
----
-<head>
-  <link rel="canonical" href="https://docs.starrocks.io/sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW/" />
-</head>
-
-import Content from '../../sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md';
-
-<Content />
diff --git a/docs/zh/README.md b/docs/zh/README.md
index 0db7133b6354c0..2bcb6e0b94e83a 100644
--- a/docs/zh/README.md
+++ b/docs/zh/README.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # StarRocks 文档
diff --git a/docs/zh/_assets/commonMarkdown/FE_config_method.md b/docs/zh/_assets/commonMarkdown/FE_config_method.md
index db8f710c9fdc59..a2558410f289e2 100644
--- a/docs/zh/_assets/commonMarkdown/FE_config_method.md
+++ b/docs/zh/_assets/commonMarkdown/FE_config_method.md
@@ -4,6 +4,6 @@ FE 参数分为动态参数和静态参数。
 
 - 静态参数必须在 FE 配置文件 **fe.conf** 中进行配置和调整。**调整完成后，需要重启 FE 使变更生效。**
 
-参数是否为动态参数可通过 [ADMIN SHOW CONFIG](../../sql-reference/sql-statements/Administration/ADMIN_SHOW_CONFIG.md) 返回结果中的 `IsMutable` 列查看。`TRUE` 表示动态参数。
+参数是否为动态参数可通过 [ADMIN SHOW CONFIG](../../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SHOW_CONFIG.md) 返回结果中的 `IsMutable` 列查看。`TRUE` 表示动态参数。
 
 静态和动态参数均可通过 **fe.conf** 文件进行修改。
diff --git a/docs/zh/_assets/commonMarkdown/loadMethodIntro.md b/docs/zh/_assets/commonMarkdown/loadMethodIntro.md
index 2506a566916ace..3f91c20925e10a 100644
--- a/docs/zh/_assets/commonMarkdown/loadMethodIntro.md
+++ b/docs/zh/_assets/commonMarkdown/loadMethodIntro.md
@@ -1,7 +1,7 @@
 
-- 使用 [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md)+[`FILES()`](../../sql-reference/sql-functions/table-functions/files.md) 进行同步导入。
-- 使用 [Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 进行异步导入。
-- 使用 [Pipe](../../sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md) 进行持续的异步导入。
+- 使用 [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md)+[`FILES()`](../../sql-reference/sql-functions/table-functions/files.md) 进行同步导入。
+- 使用 [Broker Load](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 进行异步导入。
+- 使用 [Pipe](../../sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md) 进行持续的异步导入。
 
 三种导入方式各有优势，具体将在下面分章节详细阐述。
 
diff --git a/docs/zh/_assets/commonMarkdown/sharedDataUse.md b/docs/zh/_assets/commonMarkdown/sharedDataUse.md
index 63acc9cabca95e..e72d29948e8385 100644
--- a/docs/zh/_assets/commonMarkdown/sharedDataUse.md
+++ b/docs/zh/_assets/commonMarkdown/sharedDataUse.md
@@ -1,5 +1,5 @@
 
-有关如何为其他远程存储创建存储卷和设置默认存储卷的更多信息，请参阅 [CREATE STORAGE VOLUME](../../sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md) 和 [SET DEFAULT STORAGE VOLUME](../../sql-reference/sql-statements/Administration/SET_DEFAULT_STORAGE_VOLUME.md)。
+有关如何为其他远程存储创建存储卷和设置默认存储卷的更多信息，请参阅 [CREATE STORAGE VOLUME](../../sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md) 和 [SET DEFAU../../sql-reference/sql-statements/cluster_management/storage_volume/SET_DEFAULT_STORAGE_VOLUME.mdT_STORAGE_VOLUME.md)。
 
 ### 创建数据库和云原生表
 
@@ -68,7 +68,7 @@ PROPERTIES (
 
 ### 查看表信息
 
-您可以通过 `SHOW PROC "/dbs/<db_id>"` 查看特定数据库中的表的信息。详细信息，请参阅 [SHOW PROC](../../sql-reference/sql-statements/Administration/SHOW_PROC.md)。
+您可以通过 `SHOW PROC "/dbs/<db_id>"` 查看特定数据库中的表的信息。详细信息，请参阅 [SHOW PROC](../../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROC.md)。
 
 示例：
 
@@ -89,7 +89,7 @@ StarRocks 存算分离集群支持 StarRocks 提供的所有导入方式。详
 
 ### 在 StarRocks 存算分离集群查询
 
-StarRocks 存算分离集群支持 StarRocks 提供的所有查询方式。详细信息，请参阅 [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md)。
+StarRocks 存算分离集群支持 StarRocks 提供的所有查询方式。详细信息，请参阅 [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md)。
 
 > **说明**
 >
diff --git a/docs/zh/administration/AWS_cloudformation.md b/docs/zh/administration/AWS_cloudformation.md
index da6413aa6d0ccd..3423ce20984dab 100644
--- a/docs/zh/administration/AWS_cloudformation.md
+++ b/docs/zh/administration/AWS_cloudformation.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 在 AWS 上使用 AWS CloudFormation 部署 StarRocks 集群
diff --git a/docs/zh/administration/Data_recovery.md b/docs/zh/administration/Data_recovery.md
index 90cc7c9891ae24..1813fd4ab716f2 100644
--- a/docs/zh/administration/Data_recovery.md
+++ b/docs/zh/administration/Data_recovery.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 恢复数据
diff --git a/docs/zh/administration/Meta_recovery.md b/docs/zh/administration/Meta_recovery.md
index cf029005b97fd7..149d8d4fba292b 100644
--- a/docs/zh/administration/Meta_recovery.md
+++ b/docs/zh/administration/Meta_recovery.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 恢复元数据
diff --git a/docs/zh/administration/Profiling.md b/docs/zh/administration/Profiling.md
index d31ab773aa6e8c..f174fda982fb06 100644
--- a/docs/zh/administration/Profiling.md
+++ b/docs/zh/administration/Profiling.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 优化性能
diff --git a/docs/zh/administration/Query_planning.md b/docs/zh/administration/Query_planning.md
index 67aa4089bb0e77..e0e85dda0d9434 100644
--- a/docs/zh/administration/Query_planning.md
+++ b/docs/zh/administration/Query_planning.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 分析查询
@@ -43,7 +43,7 @@ order by count(*) limit 100;
 
 Query Plan 可以分为逻辑执行计划（Logical Query Plan），和物理执行计划（Physical Query Plan），本章节所讲述的 Query Plan 默认指代的都是逻辑执行计划。
 
-通过 [EXPLAIN](../sql-reference/sql-statements/Administration/EXPLAIN.md) 命令查看 Query Plan。
+通过 [EXPLAIN](../sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN.md) 命令查看 Query Plan。
 
 ```sql
 EXPLAIN sql_statement;
@@ -332,9 +332,9 @@ Query hint 是一种指令或注释，显式地向查询优化器建议如何执
 
 ### 系统变量 hint
 
-在 SELECT、SUBMIT TASK 语句中使用 `SET_VAR` hint 设置一个或多个[系统变量](../reference/System_variable.md) ，然后执行该语句。其他语句中如果包含 SELECT 子句（如 CREATE MATERIALIZED VIEW AS SELECT，CREATE VIEW AS SELECT），则您也可以在该 SELECT 子句中使用 `SET_VAR` hint。注意如果在 CTE 中的 SELECT 子句中使用 `SET_VAR` hint 设置系统变量，即使语句执行成功，但是该 `SET_VAR` hint 不会生效。
+在 SELECT、SUBMIT TASK 语句中使用 `SET_VAR` hint 设置一个或多个[系统变量](../sql-reference/System_variable.md) ，然后执行该语句。其他语句中如果包含 SELECT 子句（如 CREATE MATERIALIZED VIEW AS SELECT，CREATE VIEW AS SELECT），则您也可以在该 SELECT 子句中使用 `SET_VAR` hint。注意如果在 CTE 中的 SELECT 子句中使用 `SET_VAR` hint 设置系统变量，即使语句执行成功，但是该 `SET_VAR` hint 不会生效。
 
-相比于[系统变量的一般用法](../reference/System_variable.md)是会话级别生效的，`SET_VAR` hint 是语句级别生效，不会影响整个会话。
+相比于[系统变量的一般用法](../sql-reference/System_variable.md)是会话级别生效的，`SET_VAR` hint 是语句级别生效，不会影响整个会话。
 
 #### 语法
 
@@ -371,9 +371,9 @@ CREATE MATERIALIZED VIEW mv
 
 ### 用户自定义变量 hint
 
-在 SELECT 或者 INSERT 语句中使用 `SET_USER_VARIABLE` hint 设置一个或多个[用户自定义变量](../reference/user_defined_variables.md) ，然后执行该语句。如果其他语句中包含 SELECT 子句（如 SELECT 语句和 INSERT 语句，不包括 CREATE MATERIALIZED VIEW AS SELECT，CREATE VIEW AS SELECT），则您也可以在该 SELECT 子句中使用 `SET_USER_VARIABLE` hint。注意如果在 CTE 中的 SELECT 子句中使用 `SET_USER_VARIABLE` hint 设置系统变量，即使语句执行成功，但是该 `SET_USER_VARIABLE` hint 不会生效。自 3.2.4 起，StarRocks 支持用户自定义变量 hint。
+在 SELECT 或者 INSERT 语句中使用 `SET_USER_VARIABLE` hint 设置一个或多个[用户自定义变量](../sql-reference/user_defined_variables.md) ，然后执行该语句。如果其他语句中包含 SELECT 子句（如 SELECT 语句和 INSERT 语句，不包括 CREATE MATERIALIZED VIEW AS SELECT，CREATE VIEW AS SELECT），则您也可以在该 SELECT 子句中使用 `SET_USER_VARIABLE` hint。注意如果在 CTE 中的 SELECT 子句中使用 `SET_USER_VARIABLE` hint 设置系统变量，即使语句执行成功，但是该 `SET_USER_VARIABLE` hint 不会生效。自 3.2.4 起，StarRocks 支持用户自定义变量 hint。
 
-相比于[用户自定义变量的一般用法](../reference/user_defined_variables.md)是会话级别生效的，`SET_USER_VARIABLE` hint 是语句级别生效，不会影响整个会话。
+相比于[用户自定义变量的一般用法](../sql-reference/user_defined_variables.md)是会话级别生效的，`SET_USER_VARIABLE` hint 是语句级别生效，不会影响整个会话。
 
 #### 语法
 
diff --git a/docs/zh/administration/administration.mdx b/docs/zh/administration/administration.mdx
index befba9138e6485..71cf1e16ce01d7 100644
--- a/docs/zh/administration/administration.mdx
+++ b/docs/zh/administration/administration.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 管理手册
diff --git a/docs/zh/administration/data_migration_tool.md b/docs/zh/administration/data_migration_tool.md
index f65588f519ffbe..9d85833d6ee3dc 100644
--- a/docs/zh/administration/data_migration_tool.md
+++ b/docs/zh/administration/data_migration_tool.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 跨集群数据迁移工具
diff --git a/docs/zh/administration/http_interface.md b/docs/zh/administration/http_interface.md
index 81ba1b6b0cbccf..88cc869072d8ab 100644
--- a/docs/zh/administration/http_interface.md
+++ b/docs/zh/administration/http_interface.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # HTTP 接口
diff --git a/docs/zh/administration/management/BE_blacklist.md b/docs/zh/administration/management/BE_blacklist.md
index a60daca2a75f38..c6641c5bfbad3e 100644
--- a/docs/zh/administration/management/BE_blacklist.md
+++ b/docs/zh/administration/management/BE_blacklist.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 管理 BE 黑名单
@@ -19,7 +19,7 @@ displayed_sidebar: "Chinese"
 
 ## 添加 BE 节点至黑名单
 
-您可以使用 [ADD BACKEND BLACKLIST](../../sql-reference/sql-statements/Administration/ADD_BACKEND_BLACKLIST.md) 语句手动将一个 BE 节点添加到 BE 黑名单中。您需要在此语句中指定该 BE 节点的 ID。您可以通过执行 [SHOW BACKENDS](../../sql-reference/sql-statements/Administration/SHOW_BACKENDS.md) 语句来获取 BE 节点的 ID。
+您可以使用 [ADD BACKEND BLACKLIST](../../sql-reference/sql-statements/cluster-management/nodes_processes/ADD_BACKEND_BLACKLIST.md) 语句手动将一个 BE 节点添加到 BE 黑名单中。您需要在此语句中指定该 BE 节点的 ID。您可以通过执行 [SHOW BACKENDS](../../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKENDS.md) 语句来获取 BE 节点的 ID。
 
 示例：
 
@@ -36,7 +36,7 @@ ADD BACKEND BLACKLIST 10001;
 
 ## 从黑名单中移除 BE 节点
 
-您可以使用 [DELETE BACKEND BLACKLIST](../../sql-reference/sql-statements/Administration/DELETE_BACKEND_BLACKLIST.md) 语句手动将一个 BE 节点从 BE 黑名单中移除。您同样需要在此语句中指定 BE 节点的 ID。
+您可以使用 [DELETE BACKEND BLACKLIST](../../sql-reference/sql-statements/cluster-management/nodes_processes/DELETE_BACKEND_BLACKLIST.md) 语句手动将一个 BE 节点从 BE 黑名单中移除。您同样需要在此语句中指定 BE 节点的 ID。
 
 示例：
 
@@ -46,7 +46,7 @@ DELETE BACKEND BLACKLIST 10001;
 
 ## 查看 BE 黑名单
 
-您可以使用 [SHOW BACKEND BLACKLIST](../../sql-reference/sql-statements/Administration/SHOW_BACKEND_BLACKLIST.md) 语句查看 BE 黑名单中的节点。
+您可以使用 [SHOW BACKEND BLACKLIST](../../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKEND_BLACKLIST.md) 语句查看 BE 黑名单中的节点。
 
 示例：
 
diff --git a/docs/zh/administration/management/BE_configuration.md b/docs/zh/administration/management/BE_configuration.md
index a63652ca17132e..46e9bf737b3920 100644
--- a/docs/zh/administration/management/BE_configuration.md
+++ b/docs/zh/administration/management/BE_configuration.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['Canshu']
 ---
 
@@ -4417,7 +4417,7 @@ curl http://<BE_IP>:<BE_HTTP_PORT>/varz
 <!--
 ##### get_txn_status_internal_sec
 
-- 默认值：30
+- 默认值：10
 - 类型：Int
 - 单位：Seconds
 - 是否动态：是
diff --git a/docs/zh/administration/management/Backup_and_restore.md b/docs/zh/administration/management/Backup_and_restore.md
index 0245425121bd6a..b1ccffcc609e97 100644
--- a/docs/zh/administration/management/Backup_and_restore.md
+++ b/docs/zh/administration/management/Backup_and_restore.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 备份与恢复
@@ -29,7 +29,7 @@ StarRocks 支持以数据库、表、或分区为粒度全量备份数据。
 
 ### 创建仓库
 
-仓库用于在远端存储系统中存储备份文件。备份数据前，您需要基于远端存储系统路径在 StarRocks 中创建仓库。您可以在同一集群中创建多个仓库。详细使用方法参阅 [CREATE REPOSITORY](../../sql-reference/sql-statements/data-definition/backup_restore/CREATE_REPOSITORY.md)。
+仓库用于在远端存储系统中存储备份文件。备份数据前，您需要基于远端存储系统路径在 StarRocks 中创建仓库。您可以在同一集群中创建多个仓库。详细使用方法参阅 [CREATE REPOSITORY](../../sql-reference/sql-statements/backup_restore/CREATE_REPOSITORY.md)。
 
 - 在 HDFS 集群中创建仓库
 
@@ -140,11 +140,11 @@ PROPERTIES(
 );
 ```
 
-仓库创建完成后，您可以通过 [SHOW REPOSITORIES](../../sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_REPOSITORIES.md) 查看已创建的仓库。完成数据恢复后，您可以通过 [DROP REPOSITORY](../../sql-reference/sql-statements/data-definition/backup_restore/DROP_REPOSITORY.md) 语句删除 StarRocks 中的仓库。但备份在远端存储系统中的快照数据目前无法通过 StarRocks 直接删除，您需要手动删除备份在远端存储系统的快照路径。
+仓库创建完成后，您可以通过 [SHOW REPOSITORIES](../../sql-reference/sql-statements/backup_restore/SHOW_REPOSITORIES.md) 查看已创建的仓库。完成数据恢复后，您可以通过 [DROP REPOSITORY](../../sql-reference/sql-statements/backup_restore/DROP_REPOSITORY.md) 语句删除 StarRocks 中的仓库。但备份在远端存储系统中的快照数据目前无法通过 StarRocks 直接删除，您需要手动删除备份在远端存储系统的快照路径。
 
 ### 备份数据快照
 
-创建数据仓库后，您可以通过 [BACKUP](../../sql-reference/sql-statements/data-definition/backup_restore/BACKUP.md) 命令创建数据快照并将其备份至远端仓库。
+创建数据仓库后，您可以通过 [BACKUP](../../sql-reference/sql-statements/backup_restore/BACKUP.md) 命令创建数据快照并将其备份至远端仓库。
 
 以下示例在数据库 `sr_hub` 中为表 `sr_member` 创建数据快照 `sr_member_backup` 并备份至仓库 `test_repo` 中。
 
@@ -161,7 +161,7 @@ StarRocks 支持以下粒度的备份还原操作：
 - 数据库级：您无需指定 ON 子句。此举将备份或还原整个数据库。
 :::
 
-数据备份为异步操作。您可以通过 [SHOW BACKUP](../../sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_BACKUP.md) 语句查看备份作业状态，或通过 [CANCEL BACKUP](../../sql-reference/sql-statements/data-definition/backup_restore/CANCEL_BACKUP.md) 语句取消备份作业。
+数据备份为异步操作。您可以通过 [SHOW BACKUP](../../sql-reference/sql-statements/backup_restore/SHOW_BACKUP.md) 语句查看备份作业状态，或通过 [CANCEL BACKUP](../../sql-reference/sql-statements/backup_restore/CANCEL_BACKUP.md) 语句取消备份作业。
 
 ## 恢复或迁移数据
 
@@ -173,7 +173,7 @@ StarRocks 支持以下粒度的备份还原操作：
 
 ### 查看数据库快照
 
-开始恢复或迁移前，您可以通过 [SHOW SNAPSHOT](../../sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_SNAPSHOT.md) 查看特定仓库对应的数据快照信息。
+开始恢复或迁移前，您可以通过 [SHOW SNAPSHOT](../../sql-reference/sql-statements/backup_restore/SHOW_SNAPSHOT.md) 查看特定仓库对应的数据快照信息。
 
 以下示例查看仓库 `test_repo` 中的数据快照信息。
 
@@ -189,7 +189,7 @@ mysql> SHOW SNAPSHOT ON test_repo;
 
 ### 恢复数据快照
 
-通过 [RESTORE](../../sql-reference/sql-statements/data-definition/backup_restore/RESTORE.md) 语句将远端仓库中的数据快照恢复至当前或其他 StarRocks 集群以恢复或迁移数据。
+通过 [RESTORE](../../sql-reference/sql-statements/backup_restore/RESTORE.md) 语句将远端仓库中的数据快照恢复至当前或其他 StarRocks 集群以恢复或迁移数据。
 
 以下示例将仓库 `test_repo` 中的数据快照 `sr_member_backup`恢复为表 `sr_member`，仅恢复一个数据副本。
 
@@ -210,7 +210,7 @@ StarRocks 支持以下粒度的备份还原操作：
 - 数据库级：您无需指定 ON 子句。此举将备份或还原整个数据库。
 :::
 
-数据恢复为异步操作。您可以通过 [SHOW RESTORE](../../sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_RESTORE.md) 语句查看恢复作业状态，或通过 [CANCEL RESTORE](../../sql-reference/sql-statements/data-definition/backup_restore/CANCEL_RESTORE.md) 语句取消恢复作业。
+数据恢复为异步操作。您可以通过 [SHOW RESTORE](../../sql-reference/sql-statements/backup_restore/SHOW_RESTORE.md) 语句查看恢复作业状态，或通过 [CANCEL RESTORE](../../sql-reference/sql-statements/backup_restore/CANCEL_RESTORE.md) 语句取消恢复作业。
 
 ## 配置相关参数
 
@@ -245,10 +245,10 @@ StarRocks 支持以下粒度的备份还原操作：
 
 在整个还原过程中遇到的任何错误都不会阻塞该过程。
 
-还原后，您可以使用[SHOW MATERIALIZED VIEWS](../../sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md) 检查物化视图的状态。
+还原后，您可以使用[SHOW MATERIALIZED VIEWS](../../sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md) 检查物化视图的状态。
 
 - 如果物化视图处于 Active 状态，则可以直接使用。
-- 如果物化视图处于 Inactive 状态，可能是因为其基表尚未还原。在还原所有基表后，您可以使用[ALTER MATERIALIZED VIEW](../../sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md) 重新激活物化视图。
+- 如果物化视图处于 Inactive 状态，可能是因为其基表尚未还原。在还原所有基表后，您可以使用[ALTER MATERIALIZED VIEW](../../sql-reference/sql-statements/materialized_view/ALTER_MATERIALIZED_VIEW.md) 重新激活物化视图。
 
 ## 注意事项
 
diff --git a/docs/zh/administration/management/FE_configuration.md b/docs/zh/administration/management/FE_configuration.md
index 4bb2fc2816dcb5..00f8b6e9ab17d7 100644
--- a/docs/zh/administration/management/FE_configuration.md
+++ b/docs/zh/administration/management/FE_configuration.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['Canshu']
 ---
 
@@ -21,7 +21,7 @@ FE 启动后，您可以在 MySQL 客户端执行 ADMIN SHOW FRONTEND CONFIG 命
  ADMIN SHOW FRONTEND CONFIG [LIKE "pattern"];
  ```
 
-详细的命令返回字段解释，参见 [ADMIN SHOW CONFIG](../../sql-reference/sql-statements/Administration/ADMIN_SHOW_CONFIG.md)。
+详细的命令返回字段解释，参见 [ADMIN SHOW CONFIG](../../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SHOW_CONFIG.md)。
 
 :::note
 只有拥有 `cluster_admin` 角色的用户才可以执行集群管理相关命令。
@@ -31,7 +31,7 @@ FE 启动后，您可以在 MySQL 客户端执行 ADMIN SHOW FRONTEND CONFIG 命
 
 ### 配置 FE 动态参数
 
-您可以通过 [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md) 命令在线修改 FE 动态参数。
+您可以通过 [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md) 命令在线修改 FE 动态参数。
 
 ```sql
 ADMIN SET FRONTEND CONFIG ("key" = "value");
@@ -2134,7 +2134,7 @@ ADMIN SET FRONTEND CONFIG ("key" = "value");
 - 类型：Long
 - 单位：Seconds
 - 是否动态：是
-- 描述：集群内每个 Routine Load 导入任务消费数据的最大时间。自 v3.1.0 起，Routine Load 导入作业 [job_properties](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md#job_properties) 新增参数 `task_consume_second`，作用于单个 Routine Load 导入作业内的导入任务，更加灵活。
+- 描述：集群内每个 Routine Load 导入任务消费数据的最大时间。自 v3.1.0 起，Routine Load 导入作业 [job_properties](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md#job_properties) 新增参数 `task_consume_second`，作用于单个 Routine Load 导入作业内的导入任务，更加灵活。
 - 引入版本：-
 
 ##### routine_load_task_timeout_second
@@ -2143,7 +2143,7 @@ ADMIN SET FRONTEND CONFIG ("key" = "value");
 - 类型：Long
 - 单位：Seconds
 - 是否动态：是
-- 描述：集群内每个 Routine Load 导入任务超时时间，自 v3.1.0 起，Routine Load 导入作业 [job_properties](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md#job_properties) 新增参数 `task_timeout_second`，作用于单个 Routine Load 导入作业内的任务，更加灵活。
+- 描述：集群内每个 Routine Load 导入任务超时时间，自 v3.1.0 起，Routine Load 导入作业 [job_properties](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md#job_properties) 新增参数 `task_timeout_second`，作用于单个 Routine Load 导入作业内的任务，更加灵活。
 - 引入版本：-
 
 <!--
@@ -2381,7 +2381,7 @@ ADMIN SET FRONTEND CONFIG ("key" = "value");
 - 类型：Long
 - 单位：Seconds
 - 是否动态：是
-- 描述：删除表/数据库之后，元数据在回收站中保留的时长，超过这个时长，数据就不可以通过[RECOVER](../../sql-reference/sql-statements/data-definition/backup_restore/RECOVER.md) 语句恢复。
+- 描述：删除表/数据库之后，元数据在回收站中保留的时长，超过这个时长，数据就不可以通过[RECOVER](../../sql-reference/sql-statements/backup_restore/RECOVER.md) 语句恢复。
 - 引入版本：-
 
 ##### enable_auto_tablet_distribution
@@ -2475,7 +2475,7 @@ ADMIN SET FRONTEND CONFIG ("key" = "value");
 > **说明**
 >
 > - StarRocks 存算分离集群自 v3.3.0 起支持该参数。
-> - 如果您需要为某张表设置该配置，例如关闭该表的 fast schema evolution，则可以在建表时设置表属性 [`fast_schema_evolution`](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md#设置-fast-schema-evolution)。
+> - 如果您需要为某张表设置该配置，例如关闭该表的 fast schema evolution，则可以在建表时设置表属性 [`fast_schema_evolution`](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md#设置-fast-schema-evolution)。
 
 ##### recover_with_empty_tablet
 
@@ -3015,7 +3015,7 @@ ADMIN SET FRONTEND CONFIG ("key" = "value");
 - 描述：存算分离集群下，触发 Compaction 操作的 Compaction Score 阈值。当一个表分区的 Compaction Score 大于或等于该值时，系统会对该分区执行 Compaction 操作。
 - 引入版本：v3.1.0
 
-Compaction Score 代表了一个表分区是否值得进行 Compaction 的评分，您可以通过 [SHOW PARTITIONS](../../sql-reference/sql-statements/data-manipulation/SHOW_PARTITIONS.md) 语句返回中的 `MaxCS` 一列的值来查看某个分区的 Compaction Score。Compaction Score 和分区中的文件数量有关系。文件数量过多将影响查询性能，因此系统后台会定期执行 Compaction 操作来合并小文件，减少文件数量。
+Compaction Score 代表了一个表分区是否值得进行 Compaction 的评分，您可以通过 [SHOW PARTITIONS](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md) 语句返回中的 `MaxCS` 一列的值来查看某个分区的 Compaction Score。Compaction Score 和分区中的文件数量有关系。文件数量过多将影响查询性能，因此系统后台会定期执行 Compaction 操作来合并小文件，减少文件数量。
 
 ##### lake_compaction_max_tasks
 
@@ -4583,6 +4583,15 @@ Compaction Score 代表了一个表分区是否值得进行 Compaction 的评分
 - 描述：单次 RESTORE 操作下，系统向单个 BE 节点下发的最大下载任务数。设置为小于或等于 0 时表示不限制任务数。
 - 引入版本：v3.1.0
 
+##### enable_colocate_restore
+
+- 默认值：false
+- 类型：Boolean
+- 单位：-
+- 是否动态：是
+- 描述：是否为 Colocate 表启用备份恢复。`true` 表示启用 Colocate 表备份恢复，`false` 表示禁用。
+- 引入版本：v3.2.10、v3.3.3
+
 <!--
 ##### enable_persistent_index_by_default
 
diff --git a/docs/zh/administration/management/Scale_up_down.md b/docs/zh/administration/management/Scale_up_down.md
index d27464b9437b2b..073eeab6c298ee 100644
--- a/docs/zh/administration/management/Scale_up_down.md
+++ b/docs/zh/administration/management/Scale_up_down.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 扩容缩容 StarRocks
diff --git a/docs/zh/administration/management/audit_loader.md b/docs/zh/administration/management/audit_loader.md
index 0bbcd082b759fc..9a8b5b22b7e9ce 100644
--- a/docs/zh/administration/management/audit_loader.md
+++ b/docs/zh/administration/management/audit_loader.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 通过 AuditLoader 管理 StarRocks 中的审计日志
@@ -10,7 +10,7 @@ displayed_sidebar: "Chinese"
 
 ## 创建审计日志库表
 
-在 StarRocks 集群中为审计日志创建数据库和表。详细操作说明参阅 [CREATE DATABASE](../../sql-reference/sql-statements/data-definition/CREATE_DATABASE.md) 和 [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md)。
+在 StarRocks 集群中为审计日志创建数据库和表。详细操作说明参阅 [CREATE DATABASE](../../sql-reference/sql-statements/Database/CREATE_DATABASE.md) 和 [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md)。
 
 > **注意**
 >
@@ -109,11 +109,11 @@ SHOW PARTITIONS FROM starrocks_audit_db__.starrocks_audit_tbl__;
 INSTALL PLUGIN FROM "<absolute_path_to_package>";
 ```
 
-详细操作说明参阅 [INSTALL PLUGIN](../../sql-reference/sql-statements/Administration/INSTALL_PLUGIN.md)。
+详细操作说明参阅 [INSTALL PLUGIN](../../sql-reference/sql-statements/cluster-management/plugin/INSTALL_PLUGIN.md)。
 
 ## 验证安装并查询审计日志
 
-1. 您可以通过 [SHOW PLUGINS](../../sql-reference/sql-statements/Administration/SHOW_PLUGINS.md) 语句检查插件是否安装成功。
+1. 您可以通过 [SHOW PLUGINS](../../sql-reference/sql-statements/cluster-management/plugin/SHOW_PLUGINS.md) 语句检查插件是否安装成功。
 
     以下示例中，插件 `AuditLoader` 的 `Status` 为 `INSTALLED`，即代表安装成功。
 
diff --git a/docs/zh/administration/management/configuration.mdx b/docs/zh/administration/management/configuration.mdx
index fade997d3fcc59..33c6690629c54c 100644
--- a/docs/zh/administration/management/configuration.mdx
+++ b/docs/zh/administration/management/configuration.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 配置项
diff --git a/docs/zh/administration/management/enable_fqdn.md b/docs/zh/administration/management/enable_fqdn.md
index 0a8b0e4b17fc14..48ab02bc032359 100644
--- a/docs/zh/administration/management/enable_fqdn.md
+++ b/docs/zh/administration/management/enable_fqdn.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 启用 FQDN 访问
diff --git a/docs/zh/administration/management/management.mdx b/docs/zh/administration/management/management.mdx
index 5369a6db518b39..3906b1bb4e4fd4 100644
--- a/docs/zh/administration/management/management.mdx
+++ b/docs/zh/administration/management/management.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/zh/administration/management/monitor_manage_big_queries.md b/docs/zh/administration/management/monitor_manage_big_queries.md
index b9e6ee3ad715ff..bd200f0666865e 100644
--- a/docs/zh/administration/management/monitor_manage_big_queries.md
+++ b/docs/zh/administration/management/monitor_manage_big_queries.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 监控管理大查询
@@ -107,7 +107,7 @@ SET GLOBAL enable_query_queue_select = true;
   SET GLOBAL query_queue_pending_timeout_second = 480;
   ```
 
-您可以使用 [SHOW PROCESSLIST](../../sql-reference/sql-statements/Administration/SHOW_PROCESSLIST.md) 查看查询是否为待处理（Pending）状态。
+您可以使用 [SHOW PROCESSLIST](../../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROCESSLIST.md) 查看查询是否为待处理（Pending）状态。
 
 ```Plain
 mysql> SHOW PROCESSLIST;
@@ -126,7 +126,7 @@ mysql> SHOW PROCESSLIST;
 
 ### 通过 MySQL 客户端监控
 
-1. 您可以使用 [SHOW PROC](../../sql-reference/sql-statements/Administration/SHOW_PROC.md) 查看当前正在处理的查询 `current_queries`。
+1. 您可以使用 [SHOW PROC](../../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROC.md) 查看当前正在处理的查询 `current_queries`。
 
    ```SQL
    SHOW PROC '/current_queries';
@@ -187,7 +187,7 @@ mysql> SHOW PROCESSLIST;
 
 ### 手动终止大查询
 
-如果有大查询绕过了您设置的预防措施并威胁到系统可用性，您可以通过在 [KILL](../../sql-reference/sql-statements/Administration/KILL.md) 语句中使用该查询对应的连接 ID 手动终止该查询：
+如果有大查询绕过了您设置的预防措施并威胁到系统可用性，您可以通过在 [KILL](../../sql-reference/sql-statements/cluster-management/nodes_processes/KILL.md) 语句中使用该查询对应的连接 ID 手动终止该查询：
 
 ```SQL
 KILL QUERY <ConnectionId>;
@@ -247,7 +247,7 @@ SET GLOBAL enable_big_query_log = true;
 ADMIN SET FRONTEND CONFIG ("enable_sql_blacklist" = "true");
 ```
 
-然后，您可以使用 [ADD SQLBLACKLIST](../../sql-reference/sql-statements/Administration/ADD_SQLBLACKLIST.md) 语句将代表这种 SQL 模式的正则表达式添加到 SQL 黑名单。
+然后，您可以使用 [ADD SQLBLACKLIST](../../sql-reference/sql-statements/cluster-management/sql_blacklist/ADD_SQLBLACKLIST.md) 语句将代表这种 SQL 模式的正则表达式添加到 SQL 黑名单。
 
 以下示例将 `COUNT(DISTINCT)` 添加到 SQL 黑名单：
 
diff --git a/docs/zh/administration/management/monitoring/Monitor_and_Alert.md b/docs/zh/administration/management/monitoring/Monitor_and_Alert.md
index 0f575d4eef9ded..2d9ee653680719 100644
--- a/docs/zh/administration/management/monitoring/Monitor_and_Alert.md
+++ b/docs/zh/administration/management/monitoring/Monitor_and_Alert.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 Prometheus 和 Grafana 监控报警
diff --git a/docs/zh/administration/management/monitoring/metrics-materialized_view.md b/docs/zh/administration/management/monitoring/metrics-materialized_view.md
index ea58cd374859fc..79aee65f82bbb0 100644
--- a/docs/zh/administration/management/monitoring/metrics-materialized_view.md
+++ b/docs/zh/administration/management/monitoring/metrics-materialized_view.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 异步物化视图监控指标
diff --git a/docs/zh/administration/management/monitoring/metrics-shared-data.md b/docs/zh/administration/management/monitoring/metrics-shared-data.md
index e6049770daa7db..9cbae2d348d950 100644
--- a/docs/zh/administration/management/monitoring/metrics-shared-data.md
+++ b/docs/zh/administration/management/monitoring/metrics-shared-data.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 存算分离集群监控指标
diff --git a/docs/zh/administration/management/monitoring/metrics.md b/docs/zh/administration/management/monitoring/metrics.md
index 09d93bcf75dfd4..cad91f65d3380f 100644
--- a/docs/zh/administration/management/monitoring/metrics.md
+++ b/docs/zh/administration/management/monitoring/metrics.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 通用监控指标
diff --git a/docs/zh/administration/management/resource_management/Blacklist.md b/docs/zh/administration/management/resource_management/Blacklist.md
index 73b93622c560e5..50689fe3cd71ee 100644
--- a/docs/zh/administration/management/resource_management/Blacklist.md
+++ b/docs/zh/administration/management/resource_management/Blacklist.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 管理黑名单
diff --git a/docs/zh/administration/management/resource_management/Load_balance.md b/docs/zh/administration/management/resource_management/Load_balance.md
index 106d4716ed7658..aa7c86ae317c40 100644
--- a/docs/zh/administration/management/resource_management/Load_balance.md
+++ b/docs/zh/administration/management/resource_management/Load_balance.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 负载均衡
diff --git a/docs/zh/administration/management/resource_management/Memory_management.md b/docs/zh/administration/management/resource_management/Memory_management.md
index 037c2dd5150304..578151911c77f0 100644
--- a/docs/zh/administration/management/resource_management/Memory_management.md
+++ b/docs/zh/administration/management/resource_management/Memory_management.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 管理内存
diff --git a/docs/zh/administration/management/resource_management/Query_management.md b/docs/zh/administration/management/resource_management/Query_management.md
index 69a0097e494209..23217c720fb86f 100644
--- a/docs/zh/administration/management/resource_management/Query_management.md
+++ b/docs/zh/administration/management/resource_management/Query_management.md
@@ -1,138 +1,138 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
-# 管理查询
-
-本文介绍如何管理查询。
-
-## 管理用户连接数
-
-Property 指针对用户粒度的属性的设置项。设置用户的属性，包括分配给用户的资源等。此处的用户属性，是指针对 user，而非 user_identity 的属性。
-
-您可以通过以下命令管理特定用户的客户端到 FE 最大连接数。
-
-```sql
-SET PROPERTY [FOR 'user'] 'key' = 'value'[, ...];
-```
-
-以下示例修改用户 jack 的最大连接数为 1000。
-
-```sql
-SET PROPERTY FOR 'jack' 'max_user_connections' = '1000';
-```
-
-您可以通过以下命令查看特定用户的连接数限制。
-
-```sql
-SHOW PROPERTY FOR 'user';
-```
-
-## 设置查询相关的 Session 变量
-
-您可以设置查询相关的 Session 级别变量，以调整当前 Session 中查询的并发度，内存等。
-
-### 调整查询并发度
-
-如需调整查询并发度，推荐您修改 Pipeline 执行引擎相关变量。
-
-> **说明**
->
-> - 自 2.2 版本起，正式发布 Pipeline 引擎。
-> - 自 3.0 版本起，支持根据查询并发度自适应调节 `pipeline_dop`。
-
-```sql
-SET enable_pipeline_engine = true;
-SET pipeline_dop = 0;
-```
-
-| 参数                                 | 说明                                                         |
-| ----------------------------------- | ------------------------------------------------------------ |
-| enable_pipeline_engine              | 是否启用 Pipeline 执行引擎。true：启用（默认），false：不启用。 |
-| pipeline_dop                        | 一个 Pipeline 实例的并行数量。建议设为默认值 0，即系统自适应调整每个 pipeline 的并行度。您也可以设置为大于 0 的数值，通常为 BE 节点 CPU 物理核数的一半。 |
-
-您也可通过设置实例的并行数量调整查询并发度。
-
-```sql
-SET GLOBAL parallel_fragment_exec_instance_num = INT;
-```
-
-`parallel_fragment_exec_instance_num`：一个 Fragment 实例的并行数量。一个 Fragment 实例占用 BE 节点的一个 CPU，所以一个查询的并行度为一个 Fragment 实例的并行数量。如果您希望提升一个查询的并行度，则可以设置该参数为 BE 的 CPU 核数的一半。
-
-> 注意：
->
-> - 实际场景中，一个 Fragment 实例的并行数量存在上限，为一张表在一个 BE 中的 Tablet 数量。例如，一张表的 3 个分区，32 个分桶，分布在 4 个 BE 节点上，则一个 BE 节点的 Tablet 数量为 32 * 3 / 4 = 24，因此该 BE 节点上一个 Fragment 实例的并行数上限为 24，此时即使设置该参数为 `32`，实际使用时并行数仍为 24。
-> - 在高并发场景下，CPU 资源往往已充分利用，因此建议设置 Fragment 实例的并行数量为 `1`，以减少不同查询间资源竞争，从而提高整体查询效率。
-
-### 调整查询内存上限
-
-您可以通过以下命令调整查询内存上限。
-
-```sql
-SET query_mem_limit = INT;
-```
-
-`query_mem_limit`：单个查询的内存限制，单位是 Byte。建议设置为 17179869184（16GB）以上。
-
-## 调整数据库存储容量 Quota
-
-默认设置下，每个数据库的存储容量无限制。您可以通过以下命令调整。
-
-```sql
-ALTER DATABASE db_name SET DATA QUOTA quota;
-```
-
-> 说明：`quota` 单位为 `B`，`K`，`KB`，`M`，`MB`，`G`，`GB`，`T`，`TB`，`P`，或 `PB`。
-
-示例：
-
-```sql
-ALTER DATABASE example_db SET DATA QUOTA 10T;
-```
-
-详细内容，参考 [ALTER DATABASE](../../../sql-reference/sql-statements/data-definition/ALTER_DATABASE.md)
-
-## 停止查询
-
-您可以通过以下命令停止某一个连接上的查询。
-
-```sql
-KILL connection_id;
-```
-
-`connection_id`：特定连接的 ID。您可以通过 `SHOW processlist;` 或者 `select connection_id();` 查看。
-
-示例：
-
-```plain text
-mysql> show processlist;
-+------+--------------+---------------------+-----------------+-------------------+---------+------+-------+------+
-| Id   | User         | Host                | Cluster         | Db                | Command | Time | State | Info |
-+------+--------------+---------------------+-----------------+-------------------+---------+------+-------+------+
-|    1 | starrocksmgr | 172.26.34.147:56208 | default_cluster | starrocks_monitor | Sleep   |    8 |       |      |
-|  129 | root         | 172.26.92.139:54818 | default_cluster |                   | Query   |    0 |       |      |
-|  114 | test         | 172.26.34.147:57974 | default_cluster | ssb_100g          | Query   |    3 |       |      |
-|    3 | starrocksmgr | 172.26.34.147:57268 | default_cluster | starrocks_monitor | Sleep   |    8 |       |      |
-|  100 | root         | 172.26.34.147:58472 | default_cluster | ssb_100           | Sleep   |  637 |       |      |
-|  117 | starrocksmgr | 172.26.34.147:33790 | default_cluster | starrocks_monitor | Sleep   |    8 |       |      |
-|    6 | starrocksmgr | 172.26.34.147:57632 | default_cluster | starrocks_monitor | Sleep   |    8 |       |      |
-|  119 | starrocksmgr | 172.26.34.147:33804 | default_cluster | starrocks_monitor | Sleep   |    8 |       |      |
-|  111 | root         | 172.26.92.139:55472 | default_cluster |                   | Sleep   | 2758 |       |      |
-+------+--------------+---------------------+-----------------+-------------------+---------+------+-------+------+
-9 rows in set (0.00 sec)
-
-mysql> select connection_id();
-+-----------------+
-| CONNECTION_ID() |
-+-----------------+
-|              98 |
-+-----------------+
-
-
-mysql> kill 114;
-Query OK, 0 rows affected (0.02 sec)
-```
-
-> 说明
->
-> `Info` 列中展示对应的 SQL 语句。如果因为 SQL 语句较长而导致被截断，您可以使用 `SHOW FULL processlist;` 来查看完整的 SQL 语句。
+# 管理查询
+
+本文介绍如何管理查询。
+
+## 管理用户连接数
+
+Property 指针对用户粒度的属性的设置项。设置用户的属性，包括分配给用户的资源等。此处的用户属性，是指针对 user，而非 user_identity 的属性。
+
+您可以通过以下命令管理特定用户的客户端到 FE 最大连接数。
+
+```sql
+SET PROPERTY [FOR 'user'] 'key' = 'value'[, ...];
+```
+
+以下示例修改用户 jack 的最大连接数为 1000。
+
+```sql
+SET PROPERTY FOR 'jack' 'max_user_connections' = '1000';
+```
+
+您可以通过以下命令查看特定用户的连接数限制。
+
+```sql
+SHOW PROPERTY FOR 'user';
+```
+
+## 设置查询相关的 Session 变量
+
+您可以设置查询相关的 Session 级别变量，以调整当前 Session 中查询的并发度，内存等。
+
+### 调整查询并发度
+
+如需调整查询并发度，推荐您修改 Pipeline 执行引擎相关变量。
+
+> **说明**
+>
+> - 自 2.2 版本起，正式发布 Pipeline 引擎。
+> - 自 3.0 版本起，支持根据查询并发度自适应调节 `pipeline_dop`。
+
+```sql
+SET enable_pipeline_engine = true;
+SET pipeline_dop = 0;
+```
+
+| 参数                                 | 说明                                                         |
+| ----------------------------------- | ------------------------------------------------------------ |
+| enable_pipeline_engine              | 是否启用 Pipeline 执行引擎。true：启用（默认），false：不启用。 |
+| pipeline_dop                        | 一个 Pipeline 实例的并行数量。建议设为默认值 0，即系统自适应调整每个 pipeline 的并行度。您也可以设置为大于 0 的数值，通常为 BE 节点 CPU 物理核数的一半。 |
+
+您也可通过设置实例的并行数量调整查询并发度。
+
+```sql
+SET GLOBAL parallel_fragment_exec_instance_num = INT;
+```
+
+`parallel_fragment_exec_instance_num`：一个 Fragment 实例的并行数量。一个 Fragment 实例占用 BE 节点的一个 CPU，所以一个查询的并行度为一个 Fragment 实例的并行数量。如果您希望提升一个查询的并行度，则可以设置该参数为 BE 的 CPU 核数的一半。
+
+> 注意：
+>
+> - 实际场景中，一个 Fragment 实例的并行数量存在上限，为一张表在一个 BE 中的 Tablet 数量。例如，一张表的 3 个分区，32 个分桶，分布在 4 个 BE 节点上，则一个 BE 节点的 Tablet 数量为 32 * 3 / 4 = 24，因此该 BE 节点上一个 Fragment 实例的并行数上限为 24，此时即使设置该参数为 `32`，实际使用时并行数仍为 24。
+> - 在高并发场景下，CPU 资源往往已充分利用，因此建议设置 Fragment 实例的并行数量为 `1`，以减少不同查询间资源竞争，从而提高整体查询效率。
+
+### 调整查询内存上限
+
+您可以通过以下命令调整查询内存上限。
+
+```sql
+SET query_mem_limit = INT;
+```
+
+`query_mem_limit`：单个查询的内存限制，单位是 Byte。建议设置为 17179869184（16GB）以上。
+
+## 调整数据库存储容量 Quota
+
+默认设置下，每个数据库的存储容量无限制。您可以通过以下命令调整。
+
+```sql
+ALTER DATABASE db_name SET DATA QUOTA quota;
+```
+
+> 说明：`quota` 单位为 `B`，`K`，`KB`，`M`，`MB`，`G`，`GB`，`T`，`TB`，`P`，或 `PB`。
+
+示例：
+
+```sql
+ALTER DATABASE example_db SET DATA QUOTA 10T;
+```
+
+详细内容，参考 [ALTER DATABASE](../../../sql-reference/sql-statements/Database/ALTER_DATABASE.md)
+
+## 停止查询
+
+您可以通过以下命令停止某一个连接上的查询。
+
+```sql
+KILL connection_id;
+```
+
+`connection_id`：特定连接的 ID。您可以通过 `SHOW processlist;` 或者 `select connection_id();` 查看。
+
+示例：
+
+```plain text
+mysql> show processlist;
++------+--------------+---------------------+-----------------+-------------------+---------+------+-------+------+
+| Id   | User         | Host                | Cluster         | Db                | Command | Time | State | Info |
++------+--------------+---------------------+-----------------+-------------------+---------+------+-------+------+
+|    1 | starrocksmgr | 172.26.34.147:56208 | default_cluster | starrocks_monitor | Sleep   |    8 |       |      |
+|  129 | root         | 172.26.92.139:54818 | default_cluster |                   | Query   |    0 |       |      |
+|  114 | test         | 172.26.34.147:57974 | default_cluster | ssb_100g          | Query   |    3 |       |      |
+|    3 | starrocksmgr | 172.26.34.147:57268 | default_cluster | starrocks_monitor | Sleep   |    8 |       |      |
+|  100 | root         | 172.26.34.147:58472 | default_cluster | ssb_100           | Sleep   |  637 |       |      |
+|  117 | starrocksmgr | 172.26.34.147:33790 | default_cluster | starrocks_monitor | Sleep   |    8 |       |      |
+|    6 | starrocksmgr | 172.26.34.147:57632 | default_cluster | starrocks_monitor | Sleep   |    8 |       |      |
+|  119 | starrocksmgr | 172.26.34.147:33804 | default_cluster | starrocks_monitor | Sleep   |    8 |       |      |
+|  111 | root         | 172.26.92.139:55472 | default_cluster |                   | Sleep   | 2758 |       |      |
++------+--------------+---------------------+-----------------+-------------------+---------+------+-------+------+
+9 rows in set (0.00 sec)
+
+mysql> select connection_id();
++-----------------+
+| CONNECTION_ID() |
++-----------------+
+|              98 |
++-----------------+
+
+
+mysql> kill 114;
+Query OK, 0 rows affected (0.02 sec)
+```
+
+> 说明
+>
+> `Info` 列中展示对应的 SQL 语句。如果因为 SQL 语句较长而导致被截断，您可以使用 `SHOW FULL processlist;` 来查看完整的 SQL 语句。
diff --git a/docs/zh/administration/management/resource_management/Replica.md b/docs/zh/administration/management/resource_management/Replica.md
index 0f86a1efd90e2d..9417bed074273a 100644
--- a/docs/zh/administration/management/resource_management/Replica.md
+++ b/docs/zh/administration/management/resource_management/Replica.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['Fuben']
 ---
 
@@ -90,7 +90,7 @@ TabletChecker 作为常驻的后台进程，会定期检查所有分片的状态
     +----------+-----------+-----------+---------+-------------------+--------------------+------------------+------------+------------+-------+--------+--------+
     ```
 
-    结果展示所有副本的状态。其中 `IsBad` 列为 `true` 则表示副本已经损坏。而 `Status` 列则会显示另外的其他状态。更多信息，请参考 [ADMIN SHOW REPLICA STATUS](../../../sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_STATUS.md)。
+    结果展示所有副本的状态。其中 `IsBad` 列为 `true` 则表示副本已经损坏。而 `Status` 列则会显示另外的其他状态。更多信息，请参考 [ADMIN SHOW REPLICA STATUS](../../../sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SHOW_REPLICA_STATUS.md)。
 
     您还可以通过以下命令查看指定表中副本的一些额外信息。
 
diff --git a/docs/zh/administration/management/resource_management/be_label.md b/docs/zh/administration/management/resource_management/be_label.md
index ae209935a83b3d..589481ccb00282 100644
--- a/docs/zh/administration/management/resource_management/be_label.md
+++ b/docs/zh/administration/management/resource_management/be_label.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用标签管理 BE 节点
diff --git a/docs/zh/administration/management/resource_management/filemanager.md b/docs/zh/administration/management/resource_management/filemanager.md
index d5da2ee4c3283a..a90a2c2a12f7ae 100644
--- a/docs/zh/administration/management/resource_management/filemanager.md
+++ b/docs/zh/administration/management/resource_management/filemanager.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 文件管理器
@@ -18,7 +18,7 @@ displayed_sidebar: "Chinese"
 
 - FE 配置
   - `small_file_dir`：用于存放上传文件的目录。默认路径为 FE 运行目录的 small_files/ 目录。您需要在 **fe.conf** 文件中修改该配置项，然后重启 FE 后生效。
-  - `max_small_file_size_bytes`：单个文件大小限制。单位为字节，默认为 1 MB。大于该参数值的文件无法创建。您可以通过 [ADMIN SET CONFIG](../../../sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md) 语句在线修改该配置项。
+  - `max_small_file_size_bytes`：单个文件大小限制。单位为字节，默认为 1 MB。大于该参数值的文件无法创建。您可以通过 [ADMIN SET CONFIG](../../../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md) 语句在线修改该配置项。
   - `max_small_file_number`：一个 StarRocks 集群支持的总文件数量。默认为 100。当创建的文件数量超过该参数值，后续的创建将会被拒绝。您可以通过 ADMIN SET CONFIG 语句在线修改该配置项。
 
 > 说明：文件数量和大小的增加会导致 FE 内存使用量增加，非必要不推荐增大 `max_small_file_size_bytes` 和 `max_small_file_number` 的参数值。
@@ -27,15 +27,15 @@ displayed_sidebar: "Chinese"
 
 ## 创建文件
 
-使用 CREATE FILE 语句创建文件。具体的语法和参数等信息，参见 [CREATE FILE](../../../sql-reference/sql-statements/Administration/CREATE_FILE.md)。文件创建后会自动上传并持久化在 StarRocks 集群中。
+使用 CREATE FILE 语句创建文件。具体的语法和参数等信息，参见 [CREATE FILE](../../../sql-reference/sql-statements/cluster-management/file/CREATE_FILE.md)。文件创建后会自动上传并持久化在 StarRocks 集群中。
 
 ## 查看文件
 
-使用 SHOW FILE 语句查看保存在数据库中的文件的信息。具体的语法和参数等信息，参见 [SHOW FILE](../../../sql-reference/sql-statements/Administration/SHOW_FILE.md)。
+使用 SHOW FILE 语句查看保存在数据库中的文件的信息。具体的语法和参数等信息，参见 [SHOW FILE](../../../sql-reference/sql-statements/cluster-management/file/SHOW_FILE.md)。
 
 ## 删除文件
 
-使用 DROP FILE 语句删除文件。具体的语法和参数等信息，参见 [DROP FILE](../../../sql-reference/sql-statements/Administration/DROP_FILE.md)。
+使用 DROP FILE 语句删除文件。具体的语法和参数等信息，参见 [DROP FILE](../../../sql-reference/sql-statements/cluster-management/file/DROP_FILE.md)。
 
 ## 使用文件
 
diff --git a/docs/zh/administration/management/resource_management/query_queues.md b/docs/zh/administration/management/resource_management/query_queues.md
index 773b7757d50691..088e8aac8b6860 100644
--- a/docs/zh/administration/management/resource_management/query_queues.md
+++ b/docs/zh/administration/management/resource_management/query_queues.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 查询队列
@@ -119,7 +119,7 @@ SET GLOBAL enable_group_level_query_queue = true;
 
 ### SHOW PROC
 
-通过 [SHOW PROC](../../../sql-reference/sql-statements/Administration/SHOW_PROC.md) 查看 BE 节点运行查询的数量、内存和 CPU 使用情况：
+通过 [SHOW PROC](../../../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROC.md) 查看 BE 节点运行查询的数量、内存和 CPU 使用情况：
 
 ```Plain
 mysql> SHOW PROC '/backends'\G
@@ -132,7 +132,7 @@ mysql> SHOW PROC '/backends'\G
 
 ### SHOW PROCESSLIST
 
-通过 [SHOW PROCESSLIST](../../../sql-reference/sql-statements/Administration/SHOW_PROCESSLIST.md) 查看查询是否在队列中（即 `IsPending` 为 `true` 时）：
+通过 [SHOW PROCESSLIST](../../../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROCESSLIST.md) 查看查询是否在队列中（即 `IsPending` 为 `true` 时）：
 
 ```Plain
 MySQL [(none)]> SHOW PROCESSLIST;
diff --git a/docs/zh/administration/management/resource_management/resource_group.md b/docs/zh/administration/management/resource_management/resource_group.md
index 732369effecab9..1abbb13a1422b9 100644
--- a/docs/zh/administration/management/resource_management/resource_group.md
+++ b/docs/zh/administration/management/resource_management/resource_group.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 资源隔离
@@ -350,7 +350,7 @@ FE 节点 **fe.audit.log** 的 `ResourceGroup` 列和 `EXPLAIN VERBOSE <query>`
 
 ### 查看资源组的使用信息
 
-从 v3.1.4 版本开始，StarRocks 支持 SQL 语句 [SHOW USAGE RESOURCE GROUPS](../../../sql-reference/sql-statements/Administration/SHOW_RUNNING_QUERIES.md)，用以展示每个资源组在各个 BE 上的使用信息。各个字段的含义如下：
+从 v3.1.4 版本开始，StarRocks 支持 SQL 语句 [SHOW USAGE RESOURCE GROUPS](../../../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_RUNNING_QUERIES.md)，用以展示每个资源组在各个 BE 上的使用信息。各个字段的含义如下：
 
 - `Name`：资源组的名称。
 - `Id`：资源组的 ID。
diff --git a/docs/zh/administration/management/resource_management/resource_management.mdx b/docs/zh/administration/management/resource_management/resource_management.mdx
index 5369a6db518b39..3906b1bb4e4fd4 100644
--- a/docs/zh/administration/management/resource_management/resource_management.mdx
+++ b/docs/zh/administration/management/resource_management/resource_management.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/zh/administration/management/resource_management/spill_to_disk.md b/docs/zh/administration/management/resource_management/spill_to_disk.md
index 17bdfacce43ce5..b03ad9cbf922ea 100644
--- a/docs/zh/administration/management/resource_management/spill_to_disk.md
+++ b/docs/zh/administration/management/resource_management/spill_to_disk.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 中间结果落盘
@@ -61,7 +61,7 @@ displayed_sidebar: "Chinese"
 自 v3.3.0 起，StarRocks 支持将中间结果落盘至对象存储。
 
 :::tip
-在启用将对象存储落盘功能之前，您必须创建一个存储卷来指定您想要使用的对象存储。有关创建存储卷的详细说明，请参阅 [CREATE STORAGE VOLUME](../../../sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md)。
+在启用将对象存储落盘功能之前，您必须创建一个存储卷来指定您想要使用的对象存储。有关创建存储卷的详细说明，请参阅 [CREATE STORAGE VOLUME](../../../sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md)。
 :::
 
 在上一步中开启落盘之后，您可以进一步设置以下系统变量，以允许将中间结果落盘至对象存储：
diff --git a/docs/zh/administration/management/timezone.md b/docs/zh/administration/management/timezone.md
index d552e2cd088fcf..696e17aa67da84 100644
--- a/docs/zh/administration/management/timezone.md
+++ b/docs/zh/administration/management/timezone.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 设置时区
diff --git a/docs/zh/administration/query_profile_details.md b/docs/zh/administration/query_profile_details.md
index 9e5924ca1b940c..15dd3f449c8135 100644
--- a/docs/zh/administration/query_profile_details.md
+++ b/docs/zh/administration/query_profile_details.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Query Profile 结构与详细指标
diff --git a/docs/zh/administration/query_profile_overview.md b/docs/zh/administration/query_profile_overview.md
index 4ec0b7dfb83306..3b82c4c734076d 100644
--- a/docs/zh/administration/query_profile_overview.md
+++ b/docs/zh/administration/query_profile_overview.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Query Profile 概述
diff --git a/docs/zh/administration/query_profile_text_based_analysis.md b/docs/zh/administration/query_profile_text_based_analysis.md
index bfeee05d421bce..c2008faa35ad77 100644
--- a/docs/zh/administration/query_profile_text_based_analysis.md
+++ b/docs/zh/administration/query_profile_text_based_analysis.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 文本可视化 Query Profile
diff --git a/docs/zh/administration/stargo.md b/docs/zh/administration/stargo.md
index 82205f523bec9c..7c7e5b3961f7d4 100644
--- a/docs/zh/administration/stargo.md
+++ b/docs/zh/administration/stargo.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 StarGo 部署管理 StarRocks
diff --git a/docs/zh/administration/user_privs/Authentication.md b/docs/zh/administration/user_privs/Authentication.md
index 4c210711db4c97..62aeaff1f16842 100644
--- a/docs/zh/administration/user_privs/Authentication.md
+++ b/docs/zh/administration/user_privs/Authentication.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 设置用户认证
diff --git a/docs/zh/administration/user_privs/User_privilege.md b/docs/zh/administration/user_privs/User_privilege.md
index e0d51e2b670de2..fd2191c73d1869 100644
--- a/docs/zh/administration/user_privs/User_privilege.md
+++ b/docs/zh/administration/user_privs/User_privilege.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 管理用户权限
diff --git a/docs/zh/administration/user_privs/privilege_faq.md b/docs/zh/administration/user_privs/privilege_faq.md
index 03e936a7078908..05483eac4e1263 100644
--- a/docs/zh/administration/user_privs/privilege_faq.md
+++ b/docs/zh/administration/user_privs/privilege_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 权限系统 FAQ
diff --git a/docs/zh/administration/user_privs/privilege_item.md b/docs/zh/administration/user_privs/privilege_item.md
index 5b7773009ec765..6fb206b9bf2aa7 100644
--- a/docs/zh/administration/user_privs/privilege_item.md
+++ b/docs/zh/administration/user_privs/privilege_item.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 权限项
diff --git a/docs/zh/administration/user_privs/privilege_overview.md b/docs/zh/administration/user_privs/privilege_overview.md
index 3c6a597ddee5d5..80fe4027a4c4da 100644
--- a/docs/zh/administration/user_privs/privilege_overview.md
+++ b/docs/zh/administration/user_privs/privilege_overview.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 权限系统总览
diff --git a/docs/zh/administration/user_privs/ranger_plugin.md b/docs/zh/administration/user_privs/ranger_plugin.md
index 4361c7d2753177..ff30a344650f66 100644
--- a/docs/zh/administration/user_privs/ranger_plugin.md
+++ b/docs/zh/administration/user_privs/ranger_plugin.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 Apache Ranger 管理权限
diff --git a/docs/zh/benchmarking/SSB_Benchmarking.md b/docs/zh/benchmarking/SSB_Benchmarking.md
index 739b0b51d101e1..d0ef6a5da84b72 100644
--- a/docs/zh/benchmarking/SSB_Benchmarking.md
+++ b/docs/zh/benchmarking/SSB_Benchmarking.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # SSB Flat Table 性能测试
diff --git a/docs/zh/benchmarking/TPC-H_Benchmarking.md b/docs/zh/benchmarking/TPC-H_Benchmarking.md
index f90740211e1b95..e0546002b6e562 100644
--- a/docs/zh/benchmarking/TPC-H_Benchmarking.md
+++ b/docs/zh/benchmarking/TPC-H_Benchmarking.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # TPC-H 基准测试
diff --git a/docs/zh/benchmarking/TPC_DS_Benchmark.md b/docs/zh/benchmarking/TPC_DS_Benchmark.md
index 64f9f59cfc48fd..13e34de0a7b38a 100644
--- a/docs/zh/benchmarking/TPC_DS_Benchmark.md
+++ b/docs/zh/benchmarking/TPC_DS_Benchmark.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # TPC-DS 性能测试
diff --git a/docs/zh/benchmarking/benchmarking.mdx b/docs/zh/benchmarking/benchmarking.mdx
index de469fbc7dbabc..4b28ed3eb34b95 100644
--- a/docs/zh/benchmarking/benchmarking.mdx
+++ b/docs/zh/benchmarking/benchmarking.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 性能测试
diff --git a/docs/zh/benchmarking/tpc_ds_99_sql.md b/docs/zh/benchmarking/tpc_ds_99_sql.md
index e0aaba7a781c65..d2c588bff736d5 100644
--- a/docs/zh/benchmarking/tpc_ds_99_sql.md
+++ b/docs/zh/benchmarking/tpc_ds_99_sql.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # TPC-DS test SQL
diff --git a/docs/zh/cover_pages/batch_loading_integration.mdx b/docs/zh/cover_pages/batch_loading_integration.mdx
index 5369a6db518b39..3906b1bb4e4fd4 100644
--- a/docs/zh/cover_pages/batch_loading_integration.mdx
+++ b/docs/zh/cover_pages/batch_loading_integration.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/zh/cover_pages/bi_tools.mdx b/docs/zh/cover_pages/bi_tools.mdx
index 6761cca7fe86fa..29a723a33f44e9 100644
--- a/docs/zh/cover_pages/bi_tools.mdx
+++ b/docs/zh/cover_pages/bi_tools.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # BI 工具
diff --git a/docs/zh/cover_pages/csp_auth.mdx b/docs/zh/cover_pages/csp_auth.mdx
index 7d45b48d9958ec..368b7d03b628da 100644
--- a/docs/zh/cover_pages/csp_auth.mdx
+++ b/docs/zh/cover_pages/csp_auth.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # CSP 认证鉴权
diff --git a/docs/zh/cover_pages/data_cache.mdx b/docs/zh/cover_pages/data_cache.mdx
index abf114103d1006..8e94dc650320d8 100644
--- a/docs/zh/cover_pages/data_cache.mdx
+++ b/docs/zh/cover_pages/data_cache.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Data Cache
diff --git a/docs/zh/cover_pages/deployment_preparation.mdx b/docs/zh/cover_pages/deployment_preparation.mdx
index 5369a6db518b39..3906b1bb4e4fd4 100644
--- a/docs/zh/cover_pages/deployment_preparation.mdx
+++ b/docs/zh/cover_pages/deployment_preparation.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/zh/cover_pages/developers.mdx b/docs/zh/cover_pages/developers.mdx
index 5369a6db518b39..3906b1bb4e4fd4 100644
--- a/docs/zh/cover_pages/developers.mdx
+++ b/docs/zh/cover_pages/developers.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/zh/cover_pages/distinct_values.mdx b/docs/zh/cover_pages/distinct_values.mdx
index 5369a6db518b39..3906b1bb4e4fd4 100644
--- a/docs/zh/cover_pages/distinct_values.mdx
+++ b/docs/zh/cover_pages/distinct_values.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/zh/cover_pages/functions_binary.mdx b/docs/zh/cover_pages/functions_binary.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/cover_pages/functions_binary.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/cover_pages/functions_conditional.mdx b/docs/zh/cover_pages/functions_conditional.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/cover_pages/functions_conditional.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/cover_pages/functions_crypto.mdx b/docs/zh/cover_pages/functions_crypto.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/cover_pages/functions_crypto.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/cover_pages/functions_date.mdx b/docs/zh/cover_pages/functions_date.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/cover_pages/functions_date.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/cover_pages/functions_geo.mdx b/docs/zh/cover_pages/functions_geo.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/cover_pages/functions_geo.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/cover_pages/functions_json_constructor.mdx b/docs/zh/cover_pages/functions_json_constructor.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/cover_pages/functions_json_constructor.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/cover_pages/functions_json_query.mdx b/docs/zh/cover_pages/functions_json_query.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/cover_pages/functions_json_query.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/cover_pages/functions_like.mdx b/docs/zh/cover_pages/functions_like.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/cover_pages/functions_like.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/cover_pages/functions_math.mdx b/docs/zh/cover_pages/functions_math.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/cover_pages/functions_math.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/cover_pages/functions_percentile.mdx b/docs/zh/cover_pages/functions_percentile.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/cover_pages/functions_percentile.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/cover_pages/functions_scalar.mdx b/docs/zh/cover_pages/functions_scalar.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/cover_pages/functions_scalar.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/cover_pages/functions_string.mdx b/docs/zh/cover_pages/functions_string.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/cover_pages/functions_string.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/cover_pages/functions_struct.mdx b/docs/zh/cover_pages/functions_struct.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/cover_pages/functions_struct.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/cover_pages/functions_table.mdx b/docs/zh/cover_pages/functions_table.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/cover_pages/functions_table.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/cover_pages/functions_utility.mdx b/docs/zh/cover_pages/functions_utility.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/cover_pages/functions_utility.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/cover_pages/ide_tools.mdx b/docs/zh/cover_pages/ide_tools.mdx
index 5369a6db518b39..3906b1bb4e4fd4 100644
--- a/docs/zh/cover_pages/ide_tools.mdx
+++ b/docs/zh/cover_pages/ide_tools.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/zh/cover_pages/loading_kafka.mdx b/docs/zh/cover_pages/loading_kafka.mdx
index 5369a6db518b39..3906b1bb4e4fd4 100644
--- a/docs/zh/cover_pages/loading_kafka.mdx
+++ b/docs/zh/cover_pages/loading_kafka.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/zh/cover_pages/loading_spark.mdx b/docs/zh/cover_pages/loading_spark.mdx
index 5369a6db518b39..3906b1bb4e4fd4 100644
--- a/docs/zh/cover_pages/loading_spark.mdx
+++ b/docs/zh/cover_pages/loading_spark.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/zh/cover_pages/manage_deployment.mdx b/docs/zh/cover_pages/manage_deployment.mdx
index 5369a6db518b39..3906b1bb4e4fd4 100644
--- a/docs/zh/cover_pages/manage_deployment.mdx
+++ b/docs/zh/cover_pages/manage_deployment.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/zh/cover_pages/mv_use_cases.mdx b/docs/zh/cover_pages/mv_use_cases.mdx
index 5369a6db518b39..3906b1bb4e4fd4 100644
--- a/docs/zh/cover_pages/mv_use_cases.mdx
+++ b/docs/zh/cover_pages/mv_use_cases.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/zh/cover_pages/performance_tuning.mdx b/docs/zh/cover_pages/performance_tuning.mdx
index 5369a6db518b39..3906b1bb4e4fd4 100644
--- a/docs/zh/cover_pages/performance_tuning.mdx
+++ b/docs/zh/cover_pages/performance_tuning.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/zh/cover_pages/query_acceleration.mdx b/docs/zh/cover_pages/query_acceleration.mdx
index 932fe0ea9a0db5..d36a54d317e932 100644
--- a/docs/zh/cover_pages/query_acceleration.mdx
+++ b/docs/zh/cover_pages/query_acceleration.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['shitu'] 
 ---
 
diff --git a/docs/zh/cover_pages/shared_data_deployment.mdx b/docs/zh/cover_pages/shared_data_deployment.mdx
index dd38e1c88d595f..ee3d3ca73e7601 100644
--- a/docs/zh/cover_pages/shared_data_deployment.mdx
+++ b/docs/zh/cover_pages/shared_data_deployment.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 #
diff --git a/docs/zh/cover_pages/shared_nothing_deployment.mdx b/docs/zh/cover_pages/shared_nothing_deployment.mdx
index 5369a6db518b39..3906b1bb4e4fd4 100644
--- a/docs/zh/cover_pages/shared_nothing_deployment.mdx
+++ b/docs/zh/cover_pages/shared_nothing_deployment.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 
diff --git a/docs/zh/data_source/External_table.md b/docs/zh/data_source/External_table.md
index c401d3ba7a3008..7617be826a5c81 100644
--- a/docs/zh/data_source/External_table.md
+++ b/docs/zh/data_source/External_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 外部表
@@ -594,7 +594,7 @@ SHOW RESOURCES;
 DROP RESOURCE "hive0";
 ~~~
 
-StarRocks 2.3 及以上版本支持修改 Hive 资源的 `hive.metastore.uris`。更多信息，参见 [ALTER RESOURCE](../sql-reference/sql-statements/data-definition/ALTER_RESOURCE.md).
+StarRocks 2.3 及以上版本支持修改 Hive 资源的 `hive.metastore.uris`。更多信息，参见 [ALTER RESOURCE](../sql-reference/sql-statements/Resource/ALTER_RESOURCE.md).
 
 ### 创建数据库
 
@@ -933,7 +933,7 @@ PROPERTIES (
 | iceberg.catalog.type | Iceberg 的 catalog 类型。目前支持 Hive catalog 和 custom catalog。 如要使用 Hive catalog， 需指定该参数值为 `HIVE`。 如要使用 custom catalog，需指定该参数值为 `CUSTOM`。 |
 | iceberg.catalog-impl   | 开发的 custom catalog 的全限定类名。FE 会根据该类名查找开发的 custom catalog。如果 custom catalog 中包含自定义的配置项，需要在创建 Iceberg 外部表时将其以键值对的形式添加到 SQL 语句的 `PROPERTIES` 中。 |
 
-StarRocks 2.3 及以上版本支持修改 Iceberg 资源的 `hive.metastore.uris` 和 `iceberg.catalog-impl`。更多信息，参见 [ALTER RESOURCE](../sql-reference/sql-statements/data-definition/ALTER_RESOURCE.md).
+StarRocks 2.3 及以上版本支持修改 Iceberg 资源的 `hive.metastore.uris` 和 `iceberg.catalog-impl`。更多信息，参见 [ALTER RESOURCE](../sql-reference/sql-statements/Resource/ALTER_RESOURCE.md).
 
 **查看 Iceberg 资源**
 
@@ -1076,7 +1076,7 @@ PROPERTIES (
 | type  | 资源类型，固定取值为 **hudi**。 |
 | hive.metastore.uris | Hive Metastore 的 thrift URI。<br /> Hudi 通过连接 Hive Metastore，以创建并管理表。您需要传入该 Hive Metastore 的 thrift URI。格式为 **`thrift://<Hudi元数据的IP地址>:<端口号>`**，端口号默认为 9083。 |
 
-StarRocks 2.3 及以上版本支持修改 Hudi 资源的 `hive.metastore.uris`。更多信息，参见 [ALTER RESOURCE](../sql-reference/sql-statements/data-definition/ALTER_RESOURCE.md).
+StarRocks 2.3 及以上版本支持修改 Hudi 资源的 `hive.metastore.uris`。更多信息，参见 [ALTER RESOURCE](../sql-reference/sql-statements/Resource/ALTER_RESOURCE.md).
 
 执行如下命令，查看 StarRocks 中的所有 Hudi 资源。
 
diff --git a/docs/zh/data_source/catalog/catalog_intro.mdx b/docs/zh/data_source/catalog/catalog_intro.mdx
index 9834ba88a46bd1..6e089fb79c05b1 100644
--- a/docs/zh/data_source/catalog/catalog_intro.mdx
+++ b/docs/zh/data_source/catalog/catalog_intro.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['catalog']
 ---
 
diff --git a/docs/zh/data_source/catalog/catalog_overview.md b/docs/zh/data_source/catalog/catalog_overview.md
index b3891bd82b7b58..abd4b9d041bf76 100644
--- a/docs/zh/data_source/catalog/catalog_overview.md
+++ b/docs/zh/data_source/catalog/catalog_overview.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 概述
@@ -37,7 +37,7 @@ StarRocks 自 2.3 版本起支持 Catalog（数据目录）功能，实现在一
 
 ## 访问 Catalog
 
-您可以使用 [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) 切换当前会话里生效的 Catalog，然后通过该 Catalog 查询数据。
+您可以使用 [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) 切换当前会话里生效的 Catalog，然后通过该 Catalog 查询数据。
 
 ## 查询数据
 
diff --git a/docs/zh/data_source/catalog/default_catalog.md b/docs/zh/data_source/catalog/default_catalog.md
index c349e9d4e9bc30..6ac7bc52b01d5e 100644
--- a/docs/zh/data_source/catalog/default_catalog.md
+++ b/docs/zh/data_source/catalog/default_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Default catalog
@@ -13,7 +13,7 @@ StarRocks 2.3 及以上版本提供了 Internal Catalog（内部数据目录）
 1. 连接 StarRocks。
    - 如从 MySQL 客户端连接到 StarRocks。连接后，默认进入到 `default_catalog`。
    - 如使用 JDBC 连接到 StarRocks，连接时即可通过 `default_catalog.db_name` 的方式指定要连接的数据库。
-2. （可选）通过 [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) 查看数据库：
+2. （可选）通过 [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) 查看数据库：
 
    ```SQL
    SHOW DATABASES;
@@ -25,25 +25,25 @@ StarRocks 2.3 及以上版本提供了 Internal Catalog（内部数据目录）
    SHOW DATABASES FROM default_catalog;
    ```
 
-3. （可选）通过 [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) 切换当前会话生效的 Catalog：
+3. （可选）通过 [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) 切换当前会话生效的 Catalog：
 
    ```SQL
    SET CATALOG <catalog_name>;
    ```
 
-   再通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 指定当前会话生效的数据库：
+   再通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 指定当前会话生效的数据库：
 
    ```SQL
    USE <db_name>;
    ```
 
-   或者，也可以通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 直接将会话切换到目标 Catalog 下的指定数据库：
+   或者，也可以通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 直接将会话切换到目标 Catalog 下的指定数据库：
 
    ```SQL
    USE <catalog_name>.<db_name>;
    ```
 
-4. 通过 [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) 查询内部数据：
+4. 通过 [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 查询内部数据：
 
    ```SQL
    SELECT * FROM <table_name>;
diff --git a/docs/zh/data_source/catalog/deltalake_catalog.md b/docs/zh/data_source/catalog/deltalake_catalog.md
index f6c33a32978863..a78f0a3a4195ea 100644
--- a/docs/zh/data_source/catalog/deltalake_catalog.md
+++ b/docs/zh/data_source/catalog/deltalake_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 5
 ---
 
@@ -7,7 +7,7 @@ toc_max_heading_level: 5
 
 Delta Lake Catalog 是一种 External Catalog。通过 Delta Lake Catalog，您不需要执行数据导入就可以直接查询 Delta Lake 里的数据。
 
-此外，您还可以基于 Delta Lake Catalog，结合 [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 能力来实现数据转换和导入。StarRocks 从 2.5 版本开始支持 Delta Lake Catalog。
+此外，您还可以基于 Delta Lake Catalog，结合 [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 能力来实现数据转换和导入。StarRocks 从 2.5 版本开始支持 Delta Lake Catalog。
 
 为保证正常访问 Delta Lake 内的数据，StarRocks 集群必须能够访问 Delta Lake 集群的存储系统和元数据服务。目前 StarRocks 支持以下存储系统和元数据服务：
 
@@ -769,13 +769,13 @@ PROPERTIES
 
 ## 查看 Delta Lake Catalog
 
-您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
+您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 Delta Lake Catalog `deltalake_catalog_glue` 的创建语句：
+您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 Delta Lake Catalog `deltalake_catalog_glue` 的创建语句：
 
 ```SQL
 SHOW CREATE CATALOG deltalake_catalog_glue;
@@ -785,7 +785,7 @@ SHOW CREATE CATALOG deltalake_catalog_glue;
 
 您可以通过如下方法切换至目标 Delta Lake Catalog 和数据库：
 
-- 先通过 [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) 指定当前会话生效的 Delta Lake Catalog，然后再通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 指定数据库：
+- 先通过 [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) 指定当前会话生效的 Delta Lake Catalog，然后再通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 指定数据库：
 
   ```SQL
   -- 切换当前会话生效的 Catalog：
@@ -794,7 +794,7 @@ SHOW CREATE CATALOG deltalake_catalog_glue;
   USE <db_name>
   ```
 
-- 通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 直接将会话切换到目标 Delta Lake Catalog 下的指定数据库：
+- 通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 直接将会话切换到目标 Delta Lake Catalog 下的指定数据库：
 
   ```SQL
   USE <catalog_name>.<db_name>
@@ -802,7 +802,7 @@ SHOW CREATE CATALOG deltalake_catalog_glue;
 
 ## 删除 Delta Lake Catalog
 
-您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) 删除某个 External Catalog。
+您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) 删除某个 External Catalog。
 
 例如，通过如下命令删除 Delta Lake Catalog `deltalake_catalog_glue`：
 
@@ -828,7 +828,7 @@ DROP Catalog deltalake_catalog_glue;
 
 ## 查询 Delta Lake 表数据
 
-1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) 查看指定 Catalog 所属的 Delta Lake 集群中的数据库：
+1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) 查看指定 Catalog 所属的 Delta Lake 集群中的数据库：
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>
@@ -836,7 +836,7 @@ DROP Catalog deltalake_catalog_glue;
 
 2. [切换至目标 Delta Lake Catalog 和数据库](#切换-delta-lake-catalog-和数据库)。
 
-3. 通过 [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) 查询目标数据库中的目标表：
+3. 通过 [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 查询目标数据库中的目标表：
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10
diff --git a/docs/zh/data_source/catalog/elasticsearch_catalog.md b/docs/zh/data_source/catalog/elasticsearch_catalog.md
index 6e146e2cdb173f..e6d1baebf2a6fb 100644
--- a/docs/zh/data_source/catalog/elasticsearch_catalog.md
+++ b/docs/zh/data_source/catalog/elasticsearch_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 ---
 
diff --git a/docs/zh/data_source/catalog/hive_catalog.md b/docs/zh/data_source/catalog/hive_catalog.md
index 6b3d5ed500cb9e..4f8cfc15a44115 100644
--- a/docs/zh/data_source/catalog/hive_catalog.md
+++ b/docs/zh/data_source/catalog/hive_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 5
 ---
 
@@ -8,8 +8,8 @@ toc_max_heading_level: 5
 Hive Catalog 是一种 External Catalog，自 2.3 版本开始支持。通过 Hive Catalog，您可以：
 
 - 无需手动建表，通过 Hive Catalog 直接查询 Hive 内的数据。
-- 通过 [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 或异步物化视图（3.1 版本及以上）将 Hive 内的数据进行加工建模，并导入至 StarRocks。
-- 在 StarRocks 侧创建或删除 Hive 库表，或通过 [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 把 StarRocks 表数据写入到 Parquet 格式（3.2 版本及以上）、以及 ORC 或 Textfile 格式（3.3 版本及以上）的 Hive 表中。
+- 通过 [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 或异步物化视图（3.1 版本及以上）将 Hive 内的数据进行加工建模，并导入至 StarRocks。
+- 在 StarRocks 侧创建或删除 Hive 库表，或通过 [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 把 StarRocks 表数据写入到 Parquet 格式（3.2 版本及以上）、以及 ORC 或 Textfile 格式（3.3 版本及以上）的 Hive 表中。
 
 为保证正常访问 Hive 内的数据，StarRocks 集群必须能够访问 Hive 集群的存储系统和元数据服务。目前 StarRocks 支持以下存储系统和元数据服务：
 
@@ -38,7 +38,7 @@ Hive Catalog 是一种 External Catalog，自 2.3 版本开始支持。通过 Hi
   - Parquet 和 ORC 文件支持 NO_COMPRESSION、SNAPPY、LZ4、ZSTD 和 GZIP 压缩格式。
   - Textfile 文件支持 NO_COMPRESSION 压缩格式。
 
-  您可以通过系统变量 [`connector_sink_compression_codec`](../../reference/System_variable.md#connector_sink_compression_codec) 来设置写入到 Hive 表时的压缩算法。
+  您可以通过系统变量 [`connector_sink_compression_codec`](../../sql-reference/System_variable.md#connector_sink_compression_codec) 来设置写入到 Hive 表时的压缩算法。
 
 ## 准备工作
 
@@ -801,13 +801,13 @@ PROPERTIES
 
 ## 查看 Hive Catalog
 
-您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
+您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 Hive Catalog `hive_catalog_glue` 的创建语句：
+您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 Hive Catalog `hive_catalog_glue` 的创建语句：
 
 ```SQL
 SHOW CREATE CATALOG hive_catalog_glue;
@@ -817,7 +817,7 @@ SHOW CREATE CATALOG hive_catalog_glue;
 
 您可以通过如下方法切换至目标 Hive Catalog 和数据库：
 
-- 先通过 [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) 指定当前会话生效的 Hive Catalog，然后再通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 指定数据库：
+- 先通过 [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) 指定当前会话生效的 Hive Catalog，然后再通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 指定数据库：
 
   ```SQL
   -- 切换当前会话生效的 Catalog：
@@ -826,7 +826,7 @@ SHOW CREATE CATALOG hive_catalog_glue;
   USE <db_name>
   ```
 
-- 通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 直接将会话切换到目标 Hive Catalog 下的指定数据库：
+- 通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 直接将会话切换到目标 Hive Catalog 下的指定数据库：
 
   ```SQL
   USE <catalog_name>.<db_name>
@@ -834,7 +834,7 @@ SHOW CREATE CATALOG hive_catalog_glue;
 
 ## 删除 Hive Catalog
 
-您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) 删除某个 External Catalog。
+您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) 删除某个 External Catalog。
 
 例如，通过如下命令删除 Hive Catalog `hive_catalog_glue`：
 
@@ -860,7 +860,7 @@ DROP Catalog hive_catalog_glue;
 
 ## 查询 Hive 表数据
 
-1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) 查看指定 Catalog 所属的 Hive 集群中的数据库：
+1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) 查看指定 Catalog 所属的 Hive 集群中的数据库：
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>
@@ -868,7 +868,7 @@ DROP Catalog hive_catalog_glue;
 
 2. [切换至目标 Hive Catalog 和数据库](#切换-hive-catalog-和数据库)。
 
-3. 通过 [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) 查询目标数据库中的目标表：
+3. 通过 [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 查询目标数据库中的目标表：
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10
@@ -905,7 +905,7 @@ GRANT SELECT ON ALL TABLES IN ALL DATABASES TO ROLE hive_role_table;
 
 ## 创建 Hive 数据库
 
-同 StarRocks 内部数据目录 (Internal Catalog) 一致，如果您拥有 Hive Catalog 的 [CREATE DATABASE](../../administration/user_privs/privilege_item.md#数据目录权限-catalog) 权限，那么您可以使用 [CREATE DATABASE](../../sql-reference/sql-statements/data-definition/CREATE_DATABASE.md) 在该 Hive Catalog 内创建数据库。本功能自 3.2 版本起开始支持。
+同 StarRocks 内部数据目录 (Internal Catalog) 一致，如果您拥有 Hive Catalog 的 [CREATE DATABASE](../../administration/user_privs/privilege_item.md#数据目录权限-catalog) 权限，那么您可以使用 [CREATE DATABASE](../../sql-reference/sql-statements/Database/CREATE_DATABASE.md) 在该 Hive Catalog 内创建数据库。本功能自 3.2 版本起开始支持。
 
 :::note
 
@@ -941,7 +941,7 @@ CREATE DATABASE <database_name>
 
 ## 删除 Hive 数据库
 
-同 StarRocks 内部数据库一致，如果您拥有 Hive 数据库的 [DROP](../../administration/user_privs/privilege_item.md#数据库权限-database) 权限，那么您可以使用 [DROP DATABASE](../../sql-reference/sql-statements/data-definition/DROP_DATABASE.md) 来删除该 Hive 数据库。本功能自 3.2 版本起开始支持。仅支持删除空数据库。
+同 StarRocks 内部数据库一致，如果您拥有 Hive 数据库的 [DROP](../../administration/user_privs/privilege_item.md#数据库权限-database) 权限，那么您可以使用 [DROP DATABASE](../../sql-reference/sql-statements/Database/DROP_DATABASE.md) 来删除该 Hive 数据库。本功能自 3.2 版本起开始支持。仅支持删除空数据库。
 
 :::note
 
@@ -959,7 +959,7 @@ DROP DATABASE <database_name>
 
 ## 创建 Hive 表
 
-同 StarRocks 内部数据库一致，如果您拥有 Hive 数据库的 [CREATE TABLE](../../administration/user_privs/privilege_item.md#数据库权限-database) 权限，那么您可以使用 [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md)、[CREATE TABLE AS SELECT (CTAS)](../../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md)、或 [CREATE TABLE LIKE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE_LIKE.md) 在该 Hive 数据库下创建 Managed Table。
+同 StarRocks 内部数据库一致，如果您拥有 Hive 数据库的 [CREATE TABLE](../../administration/user_privs/privilege_item.md#数据库权限-database) 权限，那么您可以使用 [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md)、[CREATE TABLE AS SELECT (CTAS)](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md)、或 [CREATE TABL../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_LIKE.md_LIKE.md) 在该 Hive 数据库下创建 Managed Table。
 
 本功能自 3.2 版本起开始支持，彼时只支持创建 Parquet 格式的 Hive 表。自 3.3 版本起，该功能还支持创建 ORC 及 Textfile 格式的 Hive 表。
 
@@ -1029,7 +1029,7 @@ PARTITION BY (par_col1[, par_col2...])
 | ----------------- | ------------------------------------------------------------ |
 | location          | Managed Table 所在的文件路径。使用 HMS 作为元数据服务时，您无需指定 `location` 参数。使用 AWS Glue 作为元数据服务时：<ul><li>如果在创建当前数据库时指定了 `location` 参数，那么在当前数据库下建表时不需要再指定 `location` 参数，StarRocks 默认把表建在当前数据库所在的文件路径下。</li><li>如果在创建当前数据库时没有指定 `location` 参数，那么在当前数据库建表时必须指定 `location` 参数。</li></ul> |
 | file_format       | Managed Table 的文件格式。当前支持 Parquet、ORC、Textfile 文件格式，其中 ORC 和 Textfile 文件格式自 3.3 版本起支持。取值范围：`parquet`、`orc`、`textfile`。默认值：`parquet`。 |
-| compression_codec | Managed Table 的压缩格式。该属性自 3.2.3 版本起弃用，此后写入 Hive 表时的压缩算法统一由会话变量 [connector_sink_compression_codec](../../reference/System_variable.md#connector_sink_compression_codec) 控制。 |
+| compression_codec | Managed Table 的压缩格式。该属性自 3.2.3 版本起弃用，此后写入 Hive 表时的压缩算法统一由会话变量 [connector_sink_compression_codec](../../sql-reference/System_variable.md#connector_sink_compression_codec) 控制。 |
 
 ### 示例
 
@@ -1067,16 +1067,16 @@ PARTITION BY (par_col1[, par_col2...])
 
 ## 向 Hive 表中插入数据
 
-同 StarRocks 内表一致，如果您拥有 Hive 表（Managed Table 或 External Table）的 [INSERT](../../administration/user_privs/privilege_item.md#表权限-table) 权限，那么您可以使用 [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 将 StarRocks 表数据写入到该 Hive 表中。
+同 StarRocks 内表一致，如果您拥有 Hive 表（Managed Table 或 External Table）的 [INSERT](../../administration/user_privs/privilege_item.md#表权限-table) 权限，那么您可以使用 [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 将 StarRocks 表数据写入到该 Hive 表中。
 
 本功能自 3.2 版本起开始支持，彼时只支持写入到 Parquet 格式的 Hive 表。自 3.3 版本起，该功能还支持写入到 ORC 及 Textfile 格式的 Hive 表。
 
-需要注意的是，写数据到 External Table 的功能默认是关闭的，您需要通过[系统变量 ENABLE_WRITE_HIVE_EXTERNAL_TABLE](../../reference/System_variable.md) 打开。
+需要注意的是，写数据到 External Table 的功能默认是关闭的，您需要通过[系统变量 ENABLE_WRITE_HIVE_EXTERNAL_TABLE](../../sql-reference/System_variable.md) 打开。
 
 :::note
 
 - 您可以通过 [GRANT](../../sql-reference/sql-statements/account-management/GRANT.md) 和 [REVOKE](../../sql-reference/sql-statements/account-management/REVOKE.md) 操作对用户和角色进行权限的赋予和收回。
-- 您可以通过会话变量 [connector_sink_compression_codec](../../reference/System_variable.md#connector_sink_compression_codec) 来指定写入 Hive 表时的压缩算法。
+- 您可以通过会话变量 [connector_sink_compression_codec](../../sql-reference/System_variable.md#connector_sink_compression_codec) 来指定写入 Hive 表时的压缩算法。
 
 :::
 
@@ -1165,7 +1165,7 @@ PARTITION (par_col1=<value> [, par_col2=<value>...])
 
 ## 删除 Hive 表
 
-同 StarRocks 内表一致，如果您拥有 Hive 表的 [DROP](../../administration/user_privs/privilege_item.md#表权限-table) 权限，那么您可以使用 [DROP TABLE](../../sql-reference/sql-statements/data-definition/DROP_TABLE.md) 来删除该 Hive 表。本功能自 3.2 版本起开始支持。注意当前只支持删除 Hive 的 Managed Table。
+同 StarRocks 内表一致，如果您拥有 Hive 表的 [DROP](../../administration/user_privs/privilege_item.md#表权限-table) 权限，那么您可以使用 [DROP TABLE](../../sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md) 来删除该 Hive 表。本功能自 3.2 版本起开始支持。注意当前只支持删除 Hive 的 Managed Table。
 
 :::note
 
@@ -1185,7 +1185,7 @@ DROP TABLE <table_name> FORCE
 
 ### 手动更新
 
-默认情况下，StarRocks 会缓存 Hive 的元数据、并以异步模式自动更新缓存的元数据，从而提高查询性能。此外，在对 Hive 表做了表结构变更或其他表更新后，您也可以使用 [REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE.md) 手动更新该表的元数据，从而确保 StarRocks 第一时间生成合理的查询计划：
+默认情况下，StarRocks 会缓存 Hive 的元数据、并以异步模式自动更新缓存的元数据，从而提高查询性能。此外，在对 Hive 表做了表结构变更或其他表更新后，您也可以使用 [REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/table_bucket_part_index/REFRESH_EXTERNAL_TABLE.md) 手动更新该表的元数据，从而确保 StarRocks 第一时间生成合理的查询计划：
 
 ```SQL
 REFRESH EXTERNAL TABLE <table_name> [PARTITION ('partition_name', ...)]
@@ -1284,9 +1284,9 @@ HMS 2.x 和 3.x 版本均支持配置事件侦听器。这里以配套 HMS 3.1.2
 
 | 配置名称                                                      | 默认值                        | 说明                                  |
 | ------------------------------------------------------------ | ---------------------------- | ------------------------------------ |
-| enable_background_refresh_connector_metadata                 | v3.0 为 true，v2.5 为 false   | 是否开启 Hive 元数据缓存周期性刷新。开启后，StarRocks 会轮询 Hive 集群的元数据服务（HMS 或 AWS Glue），并刷新经常访问的 Hive 外部数据目录的元数据缓存，以感知数据更新。`true` 代表开启，`false` 代表关闭。[FE 动态参数](../../administration/management/FE_configuration.md)，可以通过 [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md) 命令设置。 |
-| background_refresh_metadata_interval_millis                  | 600000（10 分钟）             | 接连两次 Hive 元数据缓存刷新之间的间隔。单位：毫秒。[FE 动态参数](../../administration/management/FE_configuration.md)，可以通过 [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md) 命令设置。 |
-| background_refresh_metadata_time_secs_since_last_access_secs | 86400（24 小时）              | Hive 元数据缓存刷新任务过期时间。对于已被访问过的 Hive Catalog，如果超过该时间没有被访问，则停止刷新其元数据缓存。对于未被访问过的 Hive Catalog，StarRocks 不会刷新其元数据缓存。单位：秒。[FE 动态参数](../../administration/management/FE_configuration.md)，可以通过 [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md) 命令设置。 |
+| enable_background_refresh_connector_metadata                 | v3.0 为 true，v2.5 为 false   | 是否开启 Hive 元数据缓存周期性刷新。开启后，StarRocks 会轮询 Hive 集群的元数据服务（HMS 或 AWS Glue），并刷新经常访问的 Hive 外部数据目录的元数据缓存，以感知数据更新。`true` 代表开启，`false` 代表关闭。[FE 动态参数](../../administration/management/FE_configuration.md)，可以通过 [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md) 命令设置。 |
+| background_refresh_metadata_interval_millis                  | 600000（10 分钟）             | 接连两次 Hive 元数据缓存刷新之间的间隔。单位：毫秒。[FE 动态参数](../../administration/management/FE_configuration.md)，可以通过 [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md) 命令设置。 |
+| background_refresh_metadata_time_secs_since_last_access_secs | 86400（24 小时）              | Hive 元数据缓存刷新任务过期时间。对于已被访问过的 Hive Catalog，如果超过该时间没有被访问，则停止刷新其元数据缓存。对于未被访问过的 Hive Catalog，StarRocks 不会刷新其元数据缓存。单位：秒。[FE 动态参数](../../administration/management/FE_configuration.md)，可以通过 [ADMIN SET FRONTEND CONFIG](../../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md) 命令设置。 |
 
 元数据缓存周期性刷新与元数据自动异步更新策略配合使用，可以进一步加快数据访问速度，降低从外部数据源读取数据的压力，提升查询性能。
 
diff --git a/docs/zh/data_source/catalog/hudi_catalog.md b/docs/zh/data_source/catalog/hudi_catalog.md
index c07fd90e6e04eb..a6e54d3e4c3704 100644
--- a/docs/zh/data_source/catalog/hudi_catalog.md
+++ b/docs/zh/data_source/catalog/hudi_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 5
 ---
 
@@ -7,7 +7,7 @@ toc_max_heading_level: 5
 
 Hudi Catalog 是一种 External Catalog。通过 Hudi Catalog，您不需要执行数据导入就可以直接查询 Apache Hudi 里的数据。
 
-此外，您还可以基于 Hudi Catalog ，结合 [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 能力来实现数据转换和导入。StarRocks 从 2.4 版本开始支持 Hudi Catalog。
+此外，您还可以基于 Hudi Catalog ，结合 [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 能力来实现数据转换和导入。StarRocks 从 2.4 版本开始支持 Hudi Catalog。
 
 为保证正常访问 Hudi 内的数据，StarRocks 集群必须能够访问 Hudi 集群的存储系统和元数据服务。目前 StarRocks 支持以下存储系统和元数据服务：
 
@@ -769,13 +769,13 @@ PROPERTIES
 
 ## 查看 Hudi Catalog
 
-您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
+您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 Hudi Catalog `hudi_catalog_glue` 的创建语句：
+您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 Hudi Catalog `hudi_catalog_glue` 的创建语句：
 
 ```SQL
 SHOW CREATE CATALOG hudi_catalog_glue;
@@ -785,7 +785,7 @@ SHOW CREATE CATALOG hudi_catalog_glue;
 
 您可以通过如下方法切换至目标 Hudi Catalog 和数据库：
 
-- 先通过 [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) 指定当前会话生效的 Hudi Catalog，然后再通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 指定数据库：
+- 先通过 [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) 指定当前会话生效的 Hudi Catalog，然后再通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 指定数据库：
 
   ```SQL
   -- 切换当前会话生效的 Catalog：
@@ -794,7 +794,7 @@ SHOW CREATE CATALOG hudi_catalog_glue;
   USE <db_name>
   ```
 
-- 通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 直接将会话切换到目标 Hudi Catalog 下的指定数据库：
+- 通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 直接将会话切换到目标 Hudi Catalog 下的指定数据库：
 
   ```SQL
   USE <catalog_name>.<db_name>
@@ -802,7 +802,7 @@ SHOW CREATE CATALOG hudi_catalog_glue;
 
 ## 删除 Hudi Catalog
 
-您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) 删除某个 External Catalog。
+您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) 删除某个 External Catalog。
 
 例如，通过如下命令删除 Hudi Catalog `hudi_catalog_glue`：
 
@@ -828,7 +828,7 @@ DROP Catalog hudi_catalog_glue;
 
 ## 查询 Hudi 表数据
 
-1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) 查看指定 Catalog 所属的 Hudi 集群中的数据库：
+1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) 查看指定 Catalog 所属的 Hudi 集群中的数据库：
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>
@@ -836,7 +836,7 @@ DROP Catalog hudi_catalog_glue;
 
 2. [切换至目标 Hudi Catalog 和数据库](#切换-hudi-catalog-和数据库)。
 
-3. 通过 [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) 查询目标数据库中的目标表：
+3. 通过 [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 查询目标数据库中的目标表：
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10
@@ -854,7 +854,7 @@ INSERT INTO default_catalog.olap_db.olap_tbl SELECT * FROM hudi_table
 
 ### 手动更新
 
-默认情况下，StarRocks 会缓存 Hudi 的元数据、并以异步模式自动更新缓存的元数据，从而提高查询性能。此外，在对 Hudi 表做了表结构变更或其他表更新后，您也可以使用 [REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE.md) 手动更新该表的元数据，从而确保 StarRocks 第一时间生成合理的查询计划：
+默认情况下，StarRocks 会缓存 Hudi 的元数据、并以异步模式自动更新缓存的元数据，从而提高查询性能。此外，在对 Hudi 表做了表结构变更或其他表更新后，您也可以使用 [REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/table_bucket_part_index/REFRESH_EXTERNAL_TABLE.md) 手动更新该表的元数据，从而确保 StarRocks 第一时间生成合理的查询计划：
 
 ```SQL
 REFRESH EXTERNAL TABLE <table_name> [PARTITION ('partition_name', ...)]
diff --git a/docs/zh/data_source/catalog/iceberg_catalog.md b/docs/zh/data_source/catalog/iceberg_catalog.md
index 468f0b265f744e..35804e878d7975 100644
--- a/docs/zh/data_source/catalog/iceberg_catalog.md
+++ b/docs/zh/data_source/catalog/iceberg_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 5
 ---
 
@@ -8,8 +8,8 @@ toc_max_heading_level: 5
 Iceberg Catalog 是一种 External Catalog。StarRocks 从 2.4 版本开始支持 Iceberg Catalog。您可以：
 
 - 无需手动建表，通过 Iceberg Catalog 直接查询 Iceberg 内的数据。
-- 通过 [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 或异步物化视图（2.5 版本及以上）将 Iceberg 内的数据进行加工建模，并导入至 StarRocks。
-- 在 StarRocks 侧创建或删除 Iceberg 库表，或通过 [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 把 StarRocks 表数据写入到 Parquet 格式的 Iceberg 表中（3.1 版本及以上）。
+- 通过 [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 或异步物化视图（2.5 版本及以上）将 Iceberg 内的数据进行加工建模，并导入至 StarRocks。
+- 在 StarRocks 侧创建或删除 Iceberg 库表，或通过 [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 把 StarRocks 表数据写入到 Parquet 格式的 Iceberg 表中（3.1 版本及以上）。
 
 为保证正常访问 Iceberg 内的数据，StarRocks 集群必须能够访问 Iceberg 集群的存储系统和元数据服务。目前 StarRocks 支持以下存储系统和元数据服务：
 
@@ -805,13 +805,13 @@ PROPERTIES
 
 ## 查看 Iceberg Catalog
 
-您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
+您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 Iceberg Catalog `iceberg_catalog_glue` 的创建语句：
+您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 Iceberg Catalog `iceberg_catalog_glue` 的创建语句：
 
 ```SQL
 SHOW CREATE CATALOG iceberg_catalog_glue;
@@ -821,7 +821,7 @@ SHOW CREATE CATALOG iceberg_catalog_glue;
 
 您可以通过如下方法切换至目标 Iceberg Catalog 和数据库：
 
-- 先通过 [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) 指定当前会话生效的 Iceberg Catalog，然后再通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 指定数据库：
+- 先通过 [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) 指定当前会话生效的 Iceberg Catalog，然后再通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 指定数据库：
 
   ```SQL
   -- 切换当前会话生效的 Catalog：
@@ -830,7 +830,7 @@ SHOW CREATE CATALOG iceberg_catalog_glue;
   USE <db_name>
   ```
 
-- 通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 直接将会话切换到目标 Iceberg Catalog 下的指定数据库：
+- 通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 直接将会话切换到目标 Iceberg Catalog 下的指定数据库：
 
   ```SQL
   USE <catalog_name>.<db_name>
@@ -838,7 +838,7 @@ SHOW CREATE CATALOG iceberg_catalog_glue;
 
 ## 删除 Iceberg Catalog
 
-您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) 删除某个 External Catalog。
+您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) 删除某个 External Catalog。
 
 例如，通过如下命令删除 Iceberg Catalog `iceberg_catalog_glue`：
 
@@ -864,7 +864,7 @@ DROP Catalog iceberg_catalog_glue;
 
 ## 查询 Iceberg 表数据
 
-1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) 查看指定 Catalog 所属的 Iceberg 集群中的数据库：
+1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) 查看指定 Catalog 所属的 Iceberg 集群中的数据库：
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>
@@ -872,7 +872,7 @@ DROP Catalog iceberg_catalog_glue;
 
 2. [切换至目标 Iceberg Catalog 和数据库](#切换-iceberg-catalog-和数据库)。
 
-3. 通过 [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) 查询目标数据库中的目标表：
+3. 通过 [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 查询目标数据库中的目标表：
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10
@@ -880,7 +880,7 @@ DROP Catalog iceberg_catalog_glue;
 
 ## 创建 Iceberg 数据库
 
-同 StarRocks 内部数据目录 (Internal Catalog) 一致，如果您拥有 Iceberg Catalog 的 [CREATE DATABASE](../../administration/user_privs/privilege_item.md#数据目录权限-catalog) 权限，那么您可以使用 [CREATE DATABASE](../../sql-reference/sql-statements/data-definition/CREATE_DATABASE.md) 在该 Iceberg Catalog 内创建数据库。本功能自 3.1 版本起开始支持。
+同 StarRocks 内部数据目录 (Internal Catalog) 一致，如果您拥有 Iceberg Catalog 的 [CREATE DATABASE](../../administration/user_privs/privilege_item.md#数据目录权限-catalog) 权限，那么您可以使用 [CREATE DATABASE](../../sql-reference/sql-statements/Database/CREATE_DATABASE.md) 在该 Iceberg Catalog 内创建数据库。本功能自 3.1 版本起开始支持。
 
 > **说明**
 >
@@ -911,7 +911,7 @@ CREATE DATABASE <database_name>
 
 ## 删除 Iceberg 数据库
 
-同 StarRocks 内部数据库一致，如果您拥有 Iceberg 数据库的 [DROP](../../administration/user_privs/privilege_item.md#数据库权限-database) 权限，那么您可以使用 [DROP DATABASE](../../sql-reference/sql-statements/data-definition/DROP_DATABASE.md) 来删除该 Iceberg 数据库。本功能自 3.1 版本起开始支持。仅支持删除空数据库。
+同 StarRocks 内部数据库一致，如果您拥有 Iceberg 数据库的 [DROP](../../administration/user_privs/privilege_item.md#数据库权限-database) 权限，那么您可以使用 [DROP DATABASE](../../sql-reference/sql-statements/Database/DROP_DATABASE.md) 来删除该 Iceberg 数据库。本功能自 3.1 版本起开始支持。仅支持删除空数据库。
 
 > **说明**
 >
@@ -927,7 +927,7 @@ DROP DATABASE <database_name>;
 
 ## 创建 Iceberg 表
 
-同 StarRocks 内部数据库一致，如果您拥有 Iceberg 数据库的 [CREATE TABLE](../../administration/user_privs/privilege_item.md#数据库权限-database) 权限，那么您可以使用 [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) 或 [CREATE TABLE AS SELECT (CTAS)](../../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md) 在该 Iceberg 数据库下创建表。本功能自 3.1 版本起开始支持。
+同 StarRocks 内部数据库一致，如果您拥有 Iceberg 数据库的 [CREATE TABLE](../../administration/user_privs/privilege_item.md#数据库权限-database) 权限，那么您可以使用 [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) 或 [CREATE TABLE AS SELECT (CTAS)](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md) 在该 Iceberg 数据库下创建表。本功能自 3.1 版本起开始支持。
 
 > **说明**
 >
@@ -991,7 +991,7 @@ PARTITION BY (par_col1[, par_col2...])
 | ----------------- | ------------------------------------------------------------ |
 | location          | Iceberg 表所在的文件路径。使用 HMS 作为元数据服务时，您无需指定 `location` 参数。使用 AWS Glue 作为元数据服务时：<ul><li>如果在创建当前数据库时指定了 `location` 参数，那么在当前数据库下建表时不需要再指定 `location` 参数，StarRocks 默认把表建在当前数据库所在的文件路径下。</li><li>如果在创建当前数据库时没有指定 `location` 参数，那么在当前数据库建表时必须指定 `location` 参数。</li></ul> |
 | file_format       | Iceberg 表的文件格式。当前仅支持 Parquet 格式。默认值：`parquet`。 |
-| compression_codec | Iceberg 表的压缩格式。当前支持 SNAPPY、GZIP、ZSTD 和 LZ4。默认值：`gzip`。该属性自 3.2.3 版本起弃用，此后写入 Iceberg 表时的压缩算法统一由会话变量 [connector_sink_compression_codec](../../reference/System_variable.md#connector_sink_compression_codec) 控制。 |
+| compression_codec | Iceberg 表的压缩格式。当前支持 SNAPPY、GZIP、ZSTD 和 LZ4。默认值：`gzip`。该属性自 3.2.3 版本起弃用，此后写入 Iceberg 表时的压缩算法统一由会话变量 [connector_sink_compression_codec](../../sql-reference/System_variable.md#connector_sink_compression_codec) 控制。 |
 
 ### 示例
 
@@ -1027,7 +1027,7 @@ PARTITION BY (par_col1[, par_col2...])
 
 ## 向 Iceberg 表中插入数据
 
-同 StarRocks 内表一致，如果您拥有 Iceberg 表的 [INSERT](../../administration/user_privs/privilege_item.md#表权限-table) 权限，那么您可以使用 [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 将 StarRocks 表数据写入到该 Iceberg 表中（当前仅支持写入到 Parquet 格式的 Iceberg 表）。本功能自 3.1 版本起开始支持。
+同 StarRocks 内表一致，如果您拥有 Iceberg 表的 [INSERT](../../administration/user_privs/privilege_item.md#表权限-table) 权限，那么您可以使用 [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 将 StarRocks 表数据写入到该 Iceberg 表中（当前仅支持写入到 Parquet 格式的 Iceberg 表）。本功能自 3.1 版本起开始支持。
 
 > **说明**
 >
@@ -1116,7 +1116,7 @@ PARTITION (par_col1=<value> [, par_col2=<value>...])
 
 ## 删除 Iceberg 表
 
-同 StarRocks 内表一致，在拥有 Iceberg 表的 [DROP](../../administration/user_privs/privilege_item.md#表权限-table) 权限的情况下，您可以使用 [DROP TABLE](../../sql-reference/sql-statements/data-definition/DROP_TABLE.md) 来删除该 Iceberg 表。本功能自 3.1 版本起开始支持。
+同 StarRocks 内表一致，在拥有 Iceberg 表的 [DROP](../../administration/user_privs/privilege_item.md#表权限-table) 权限的情况下，您可以使用 [DROP TABLE](../../sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md) 来删除该 Iceberg 表。本功能自 3.1 版本起开始支持。
 
 > **说明**
 >
diff --git a/docs/zh/data_source/catalog/jdbc_catalog.md b/docs/zh/data_source/catalog/jdbc_catalog.md
index 746529ee6c31ed..8eaf96cb645663 100644
--- a/docs/zh/data_source/catalog/jdbc_catalog.md
+++ b/docs/zh/data_source/catalog/jdbc_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 ---
 
@@ -9,7 +9,7 @@ StarRocks 从 3.0 版本开始支持 JDBC Catalog。
 
 JDBC Catalog 是一种 External Catalog。通过 JDBC Catalog，您不需要执行数据导入就可以直接查询 JDBC 数据源里的数据。
 
-此外，您还可以基于 JDBC Catalog ，结合 [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 能力对 JDBC 数据源的数据实现转换和导入。
+此外，您还可以基于 JDBC Catalog ，结合 [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 能力对 JDBC 数据源的数据实现转换和导入。
 
 JDBC Catalog 自 3.0 版本开始支持 MySQL、PostgreSQL，自 3.2.9、3.3.1 版本开始支持 Oracle 和 SQLServer。
 
@@ -112,13 +112,13 @@ PROPERTIES
 
 ## 查看 JDBC Catalog
 
-您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
+您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 JDBC Catalog `jdbc0` 的创建语句：
+您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 JDBC Catalog `jdbc0` 的创建语句：
 
 ```SQL
 SHOW CREATE CATALOG jdbc0;
@@ -126,7 +126,7 @@ SHOW CREATE CATALOG jdbc0;
 
 ## 删除 JDBC Catalog
 
-您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) 删除一个 JDBC Catalog。
+您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) 删除一个 JDBC Catalog。
 
 例如，通过如下命令删除 JDBC Catalog `jdbc0`：
 
@@ -136,31 +136,31 @@ DROP Catalog jdbc0;
 
 ## 查询 JDBC Catalog 中的表数据
 
-1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) 查看指定 Catalog 所属的集群中的数据库：
+1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) 查看指定 Catalog 所属的集群中的数据库：
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>;
    ```
 
-2. 通过 [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) 切换当前会话生效的 Catalog：
+2. 通过 [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) 切换当前会话生效的 Catalog：
 
     ```SQL
     SET CATALOG <catalog_name>;
     ```
 
-    再通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 指定当前会话生效的数据库：
+    再通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 指定当前会话生效的数据库：
 
     ```SQL
     USE <db_name>;
     ```
 
-    或者，也可以通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 直接将会话切换到目标 Catalog 下的指定数据库：
+    或者，也可以通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 直接将会话切换到目标 Catalog 下的指定数据库：
 
     ```SQL
     USE <catalog_name>.<db_name>;
     ```
 
-3. 通过 [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) 查询目标数据库中的目标表：
+3. 通过 [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 查询目标数据库中的目标表：
 
    ```SQL
    SELECT * FROM <table_name>;
diff --git a/docs/zh/data_source/catalog/kudu_catalog.md b/docs/zh/data_source/catalog/kudu_catalog.md
index 540ed910940d5d..4836551e13bd55 100644
--- a/docs/zh/data_source/catalog/kudu_catalog.md
+++ b/docs/zh/data_source/catalog/kudu_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # [Experimental] Kudu catalog
@@ -8,7 +8,7 @@ StarRocks 从 3.3 版本开始支持 Kudu Catalog。
 
 Kudu Catalog 是一种 External Catalog。通过 Kudu Catalog，您不需要执行数据导入就可以直接查询 Apache Kudu 里的数据。
 
-此外，您还可以基于 Kudu Catalog ，结合 [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 能力来实现数据转换和导入。
+此外，您还可以基于 Kudu Catalog ，结合 [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 能力来实现数据转换和导入。
 
 为保证正常访问 Kudu 内的数据，StarRocks 集群必须集成以下关键组件：
 
@@ -116,13 +116,13 @@ StarRocks 访问 Kudu 集群元数据的相关参数配置。
 
 ## 查看 Kudu Catalog
 
-您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
+您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 Kudu Catalog `kudu_catalog` 的创建语句：
+您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 Kudu Catalog `kudu_catalog` 的创建语句：
 
 ```SQL
 SHOW CREATE CATALOG kudu_catalog;
@@ -130,7 +130,7 @@ SHOW CREATE CATALOG kudu_catalog;
 
 ## 删除 Kudu Catalog
 
-您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) 删除某个 External Catalog。
+您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) 删除某个 External Catalog。
 
 例如，通过如下命令删除 Kudu Catalog `kudu_catalog`：
 
@@ -156,31 +156,31 @@ DROP Catalog kudu_catalog;
 
 ## 查询 Kudu 表数据
 
-1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) 查看指定 Catalog 所属的 Kudu Catalog 中的数据库：
+1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) 查看指定 Catalog 所属的 Kudu Catalog 中的数据库：
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>;
    ```
 
-2. 通过 [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) 切换当前会话生效的 Catalog：
+2. 通过 [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) 切换当前会话生效的 Catalog：
 
    ```SQL
    SET CATALOG <catalog_name>;
    ```
 
-   再通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 指定当前会话生效的数据库：
+   再通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 指定当前会话生效的数据库：
 
    ```SQL
    USE <db_name>;
    ```
 
-   或者，也可以通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 直接将会话切换到目标 Catalog 下的指定数据库：
+   或者，也可以通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 直接将会话切换到目标 Catalog 下的指定数据库：
 
    ```SQL
    USE <catalog_name>.<db_name>;
    ```
 
-3. 通过 [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) 查询目标数据库中的目标表：
+3. 通过 [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 查询目标数据库中的目标表：
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10;
diff --git a/docs/zh/data_source/catalog/maxcompute_catalog.md b/docs/zh/data_source/catalog/maxcompute_catalog.md
index 2d13a9c7e0a54e..ce0d1be911f7ab 100644
--- a/docs/zh/data_source/catalog/maxcompute_catalog.md
+++ b/docs/zh/data_source/catalog/maxcompute_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 ---
 
@@ -9,7 +9,7 @@ StarRocks 从 3.3 版本开始支持 Alibaba Cloud MaxCompute (即以前的 ODPS
 
 MaxCompute Catalog 是一种 External Catalog。通过 MaxCompute Catalog，您不需要执行数据导入就可以直接查询 MaxCompute 里的数据。
 
-此外，您还可以基于 MaxCompute Catalog，结合 [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 能力来实现数据转换和导入。
+此外，您还可以基于 MaxCompute Catalog，结合 [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 能力来实现数据转换和导入。
 
 ## 使用说明
 
@@ -113,13 +113,13 @@ PROPERTIES
 
 ## 查看 MaxCompute Catalog
 
-您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
+您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 MaxCompute Catalog `odps_catalog` 的创建语句：
+您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 MaxCompute Catalog `odps_catalog` 的创建语句：
 
 ```SQL
 SHOW CREATE CATALOG odps_catalog;
@@ -127,7 +127,7 @@ SHOW CREATE CATALOG odps_catalog;
 
 ## 删除 MaxCompute Catalog
 
-您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) 删除某个 External Catalog。
+您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) 删除某个 External Catalog。
 
 例如，通过如下命令删除 MaxCompute Catalog `odps_catalog`：
 
@@ -153,31 +153,31 @@ DROP CATALOG odps_catalog;
 
 ## 查询 MaxCompute 表数据
 
-1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) 查看指定 Catalog 所属的 MaxCompute Catalog 中的数据库：
+1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) 查看指定 Catalog 所属的 MaxCompute Catalog 中的数据库：
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>;
    ```
 
-2. 通过 [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) 切换当前会话生效的 Catalog：
+2. 通过 [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) 切换当前会话生效的 Catalog：
 
    ```SQL
    SET CATALOG <catalog_name>;
    ```
 
-   再通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 指定当前会话生效的数据库：
+   再通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 指定当前会话生效的数据库：
 
    ```SQL
    USE <db_name>;
    ```
 
-   或者，也可以通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 直接将会话切换到目标 Catalog 下的指定数据库：
+   或者，也可以通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 直接将会话切换到目标 Catalog 下的指定数据库：
 
    ```SQL
    USE <catalog_name>.<db_name>;
    ```
 
-3. 通过 [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) 查询目标数据库中的目标表：
+3. 通过 [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 查询目标数据库中的目标表：
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10;
@@ -227,7 +227,7 @@ TIMESTAMP 类型在 StarRocks 中由于类型转换，会损失精度。
 
 由于 MaxCompute Catalog 在当前版本还无法自动采集 MaxCompute 表的 CBO 统计信息，导致某些情况下优化器无法做出最优的查询计划。在这种情况下，手动扫描 MaxCompute 表的 CBO 统计信息，并导入到 StarRocks 中，可以有效优化查询时间。
 
-假设有一个 MaxCompute 表，表名为 `mc_table`, 您可以通过 [ANALYZE TABLE](../../sql-reference/sql-statements/data-definition/ANALYZE_TABLE.md) 创建手动采集任务，进行 CBO 统计信息采集：
+假设有一个 MaxCompute 表，表名为 `mc_table`, 您可以通过 [ANALYZE TABLE](../../sql-reference/sql-statements/cbo_stats/ANALYZE_TABLE.md) 创建手动采集任务，进行 CBO 统计信息采集：
 
 ```SQL
 ANALYZE TABLE mc_table;
@@ -235,7 +235,7 @@ ANALYZE TABLE mc_table;
 
 ## 手动更新元数据缓存
 
-默认情况下，StarRocks 会缓存 MaxCompute 的元数据，从而提高查询性能。因此，当对 MaxCompute 表做了表结构变更或其他表更新后，您可以使用 [REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE.md) 手动更新该表的元数据，从而确保 StarRocks 第一时间获取到新的元数据信息：
+默认情况下，StarRocks 会缓存 MaxCompute 的元数据，从而提高查询性能。因此，当对 MaxCompute 表做了表结构变更或其他表更新后，您可以使用 [REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/table_bucket_part_index/REFRESH_EXTERNAL_TABLE.md) 手动更新该表的元数据，从而确保 StarRocks 第一时间获取到新的元数据信息：
 
 ```SQL
 REFRESH EXTERNAL TABLE <table_name> [PARTITION ('partition_name', ...)]
diff --git a/docs/zh/data_source/catalog/paimon_catalog.md b/docs/zh/data_source/catalog/paimon_catalog.md
index 31288b17b1ae63..3287e7d97f3c42 100644
--- a/docs/zh/data_source/catalog/paimon_catalog.md
+++ b/docs/zh/data_source/catalog/paimon_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 5
 ---
 
@@ -9,7 +9,7 @@ StarRocks 从 3.1 版本开始支持 Paimon Catalog。
 
 Paimon Catalog 是一种 External Catalog。通过 Paimon Catalog，您不需要执行数据导入就可以直接查询 Apache Paimon 里的数据。
 
-此外，您还可以基于 Paimon Catalog ，结合 [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 能力来实现数据转换和导入。
+此外，您还可以基于 Paimon Catalog ，结合 [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 能力来实现数据转换和导入。
 
 为保证正常访问 Paimon 内的数据，StarRocks 集群必须能够访问 Paimon 集群的存储系统和元数据服务。目前 StarRocks 支持以下存储系统和元数据服务：
 
@@ -634,13 +634,13 @@ PROPERTIES
 
 ## 查看 Paimon Catalog
 
-您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
+您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 Paimon Catalog `paimon_catalog_fs` 的创建语句：
+您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 Paimon Catalog `paimon_catalog_fs` 的创建语句：
 
 ```SQL
 SHOW CREATE CATALOG paimon_catalog_fs;
@@ -648,7 +648,7 @@ SHOW CREATE CATALOG paimon_catalog_fs;
 
 ## 删除 Paimon Catalog
 
-您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) 删除某个 External Catalog。
+您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) 删除某个 External Catalog。
 
 例如，通过如下命令删除 Paimon Catalog `paimon_catalog_fs`：
 
@@ -674,31 +674,31 @@ DROP Catalog paimon_catalog_fs;
 
 ## 查询 Paimon 表数据
 
-1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) 查看指定 Catalog 所属的 Paimon Catalog 中的数据库：
+1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) 查看指定 Catalog 所属的 Paimon Catalog 中的数据库：
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>;
    ```
 
-2. 通过 [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) 切换当前会话生效的 Catalog：
+2. 通过 [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) 切换当前会话生效的 Catalog：
 
    ```SQL
    SET CATALOG <catalog_name>;
    ```
 
-   再通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 指定当前会话生效的数据库：
+   再通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 指定当前会话生效的数据库：
 
    ```SQL
    USE <db_name>;
    ```
 
-   或者，也可以通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 直接将会话切换到目标 Catalog 下的指定数据库：
+   或者，也可以通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 直接将会话切换到目标 Catalog 下的指定数据库：
 
    ```SQL
    USE <catalog_name>.<db_name>;
    ```
 
-3. 通过 [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) 查询目标数据库中的目标表：
+3. 通过 [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 查询目标数据库中的目标表：
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10;
diff --git a/docs/zh/data_source/catalog/query_external_data.md b/docs/zh/data_source/catalog/query_external_data.md
index f8b86b034cee0f..6434e9dbec8b2a 100644
--- a/docs/zh/data_source/catalog/query_external_data.md
+++ b/docs/zh/data_source/catalog/query_external_data.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 查询外部数据
@@ -16,25 +16,25 @@ displayed_sidebar: "Chinese"
    - 如从 MySQL 客户端连接到 StarRocks。连接后，默认进入到 `default_catalog`。
    - 如使用 JDBC 连接到 StarRocks，连接时即可通过 `default_catalog.db_name` 的方式指定要连接的数据库。
 
-2. （可选）执行以下语句查看当前 StarRocks 集群中的所有 Catalog 并找到指定的 External Catalog。有关返回值说明，请参见 [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md)。
+2. （可选）执行以下语句查看当前 StarRocks 集群中的所有 Catalog 并找到指定的 External Catalog。有关返回值说明，请参见 [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md)。
 
     ```SQL
     SHOW CATALOGS;
     ```
 
-3. （可选）执行以下语句查看指定 external catalog 中的数据库。有关参数和返回值说明，请参见 [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md)。
+3. （可选）执行以下语句查看指定 external catalog 中的数据库。有关参数和返回值说明，请参见 [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md)。
 
     ```SQL
     SHOW DATABASES FROM catalog_name;
     ```
 
-4. （可选）执行以下语句将当前会话切换到指定 external catalog 的指定数据库。有关参数说明和示例，请参见 [USE](../../sql-reference/sql-statements/data-definition/USE.md)。
+4. （可选）执行以下语句将当前会话切换到指定 external catalog 的指定数据库。有关参数说明和示例，请参见 [USE](../../sql-reference/sql-statements/Database/USE.md)。
 
     ```SQL
     USE catalog_name.db_name;
     ```
 
-5. 查询外部数据。更多 SELECT 的使用方法，请参见 [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md)。
+5. 查询外部数据。更多 SELECT 的使用方法，请参见 [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md)。
 
     ```SQL
     SELECT * FROM table_name;
diff --git a/docs/zh/data_source/catalog/unified_catalog.md b/docs/zh/data_source/catalog/unified_catalog.md
index 63a43634033e35..9f392dfb362b44 100644
--- a/docs/zh/data_source/catalog/unified_catalog.md
+++ b/docs/zh/data_source/catalog/unified_catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 5
 ---
 
@@ -8,7 +8,7 @@ toc_max_heading_level: 5
 Unified Catalog 是一种 External Catalog，自 3.2 版本起支持。通过 Unified Catalog，您可以把 Apache Hive™、Apache Iceberg、Apache Hudi、 Delta Lake 和 Apache Kudu 数据源作为一个融合的数据源，不需要执行导入就可以直接操作其中的表数据，包括：
 
 - 无需手动建表，通过 Unified Catalog 直接查询 Hive、Iceberg、Hudi、Delta Lake 和 Kudu 数据源里的数据。
-- 通过 [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 或异步物化视图（2.5 版本及以上）将 Hive、Iceberg、Hudi、Delta Lake 和 Kudu 数据源里的数据进行加工建模，并导入至 StarRocks。
+- 通过 [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 或异步物化视图（2.5 版本及以上）将 Hive、Iceberg、Hudi、Delta Lake 和 Kudu 数据源里的数据进行加工建模，并导入至 StarRocks。
 - 在 StarRocks 侧创建或删除 Hive、Iceberg 库表。
 
 为保证正常访问融合数据源内的数据，StarRocks 集群必须能够访问融合数据源的存储系统和元数据服务。目前 StarRocks 支持以下存储系统和元数据服务：
@@ -29,9 +29,9 @@ Unified Catalog 是一种 External Catalog，自 3.2 版本起支持。通过 Un
 
 - 有关 Unified Catalog 支持的文件格式和数据类型，请参见 [Hive catalog](../catalog/hive_catalog.md)、[Iceberg catalog](../catalog/iceberg_catalog.md)、[Hudi catalog](../catalog/hudi_catalog.md)、[Delta Lake catalog](../catalog/deltalake_catalog.md) 和 [Kudu catalog](../catalog/kudu_catalog.md) 文档中“使用说明”部分。
 
-- 部分操作只能用于特定的表格式。例如，[CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) 和 [DROP TABLE](../../sql-reference/sql-statements/data-definition/DROP_TABLE.md) 当前只支持 Hive 和 Iceberg 表，[REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE.md) 只支持 Hive 和 Hudi 表。
+- 部分操作只能用于特定的表格式。例如，[CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) 和 [DROP TABLE](../../sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md) 当前只支持 Hive 和 Iceberg 表，[REFRESH EXTERNAL TABLE](../../sql-reference/sql-statements/table_bucket_part_index/REFRESH_EXTERNAL_TABLE.md) 只支持 Hive 和 Hudi 表。
 
-  当您通过 [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) 在 Unified Catalog 中创建表时，必须通过 `ENGINE` 参数来指定表格式（Hive 或 Iceberg）。
+  当您通过 [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) 在 Unified Catalog 中创建表时，必须通过 `ENGINE` 参数来指定表格式（Hive 或 Iceberg）。
 
 ## 准备工作
 
@@ -778,13 +778,13 @@ PROPERTIES
 
 ## 查看 Unified Catalog
 
-您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
+您可以通过 [SHOW CATALOGS](../../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) 查询当前所在 StarRocks 集群里所有 Catalog：
 
 ```SQL
 SHOW CATALOGS;
 ```
 
-您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 Unified Catalog `unified_catalog_glue` 的创建语句：
+您也可以通过 [SHOW CREATE CATALOG](../../sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md) 查询某个 External Catalog 的创建语句。例如，通过如下命令查询 Unified Catalog `unified_catalog_glue` 的创建语句：
 
 ```SQL
 SHOW CREATE CATALOG unified_catalog_glue;
@@ -794,7 +794,7 @@ SHOW CREATE CATALOG unified_catalog_glue;
 
 您可以通过如下方法切换至目标 Unified Catalog 和数据库：
 
-- 先通过 [SET CATALOG](../../sql-reference/sql-statements/data-definition/SET_CATALOG.md) 指定当前会话生效的 Unified Catalog，然后再通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 指定数据库：
+- 先通过 [SET CATALOG](../../sql-reference/sql-statements/Catalog/SET_CATALOG.md) 指定当前会话生效的 Unified Catalog，然后再通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 指定数据库：
 
   ```SQL
   -- 切换当前会话生效的 Catalog：
@@ -803,7 +803,7 @@ SHOW CREATE CATALOG unified_catalog_glue;
   USE <db_name>
   ```
 
-- 通过 [USE](../../sql-reference/sql-statements/data-definition/USE.md) 直接将会话切换到目标 Unified Catalog 下的指定数据库：
+- 通过 [USE](../../sql-reference/sql-statements/Database/USE.md) 直接将会话切换到目标 Unified Catalog 下的指定数据库：
 
   ```SQL
   USE <catalog_name>.<db_name>
@@ -811,7 +811,7 @@ SHOW CREATE CATALOG unified_catalog_glue;
 
 ## 删除 Unified Catalog
 
-您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md) 删除某个 External Catalog。
+您可以通过 [DROP CATALOG](../../sql-reference/sql-statements/Catalog/DROP_CATALOG.md) 删除某个 External Catalog。
 
 例如，通过如下命令删除 Unified Catalog `unified_catalog_glue`：
 
@@ -839,7 +839,7 @@ DROP CATALOG unified_catalog_glue;
 
  您可以通过如下操作查询 Unified Catalog 内的数据：
 
-1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) 查看指定 Unified Catalog 所属的数据源中的数据库：
+1. 通过 [SHOW DATABASES](../../sql-reference/sql-statements/Database/SHOW_DATABASES.md) 查看指定 Unified Catalog 所属的数据源中的数据库：
 
    ```SQL
    SHOW DATABASES FROM <catalog_name>
@@ -847,7 +847,7 @@ DROP CATALOG unified_catalog_glue;
 
 2. [切换至目标 Unified Catalog 和数据库](#切换-unified-catalog-和数据库)。
 
-3. 通过 [SELECT](../../sql-reference/sql-statements/data-manipulation/SELECT.md) 查询目标数据库中的目标表：
+3. 通过 [SELECT](../../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 查询目标数据库中的目标表：
 
    ```SQL
    SELECT count(*) FROM <table_name> LIMIT 10
@@ -855,7 +855,7 @@ DROP CATALOG unified_catalog_glue;
 
 ## 从 Hive、Iceberg、Hudi、Delta Lake 或 Kudu 导入数据
 
-您可以通过 [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 将 Hive、Iceberg、Hudi、Delta Lake 或 Kudu 表中的数据导入 StarRocks 中 Unified Catalog 下的表。
+您可以通过 [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 将 Hive、Iceberg、Hudi、Delta Lake 或 Kudu 表中的数据导入 StarRocks 中 Unified Catalog 下的表。
 
 例如，通过如下命令将 Hive 表 `hive_table` 的数据导入到 StarRocks 中 Unified Catalog `unified_catalog` 下数据库`test_database` 里的表 `test_table`：
 
@@ -865,7 +865,7 @@ INSERT INTO unified_catalog.test_database.test_table SELECT * FROM hive_table
 
 ## 在 Unified Catalog 内创建数据库
 
-同 StarRocks 内部数据目录 (Internal Catalog) 一致，如果您拥有 Unified Catalog 的 [CREATE DATABASE](../../administration/user_privs/privilege_item.md#数据目录权限-catalog) 权限，那么您可以使用 [CREATE DATABASE](../../sql-reference/sql-statements/data-definition/CREATE_DATABASE.md) 在该 Unified Catalog 内创建数据库。
+同 StarRocks 内部数据目录 (Internal Catalog) 一致，如果您拥有 Unified Catalog 的 [CREATE DATABASE](../../administration/user_privs/privilege_item.md#数据目录权限-catalog) 权限，那么您可以使用 [CREATE DATABASE](../../sql-reference/sql-statements/Database/CREATE_DATABASE.md) 在该 Unified Catalog 内创建数据库。
 
 > **说明**
 >
@@ -901,7 +901,7 @@ CREATE DATABASE <database_name>
 
 ## 从 Unified Catalog 内删除数据库
 
-同 StarRocks 内部数据库一致，如果您拥有 Unified Catalog 内数据库的 [DROP](../../administration/user_privs/privilege_item.md#数据库权限-database) 权限，那么您可以使用 [DROP DATABASE](../../sql-reference/sql-statements/data-definition/DROP_DATABASE.md) 来删除该数据库。仅支持删除空数据库。
+同 StarRocks 内部数据库一致，如果您拥有 Unified Catalog 内数据库的 [DROP](../../administration/user_privs/privilege_item.md#数据库权限-database) 权限，那么您可以使用 [DROP DATABASE](../../sql-reference/sql-statements/Database/DROP_DATABASE.md) 来删除该数据库。仅支持删除空数据库。
 
 > **说明**
 >
@@ -919,7 +919,7 @@ DROP DATABASE <database_name>
 
 ## 在 Unified Catalog 内创建表
 
-同 StarRocks 内部数据库一致，如果您拥有 Unified Catalog 内数据库的 [CREATE TABLE](../../administration/user_privs/privilege_item.md#数据库权限-database) 权限，那么您可以使用 [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) 或 [CREATE TABLE AS SELECT (CTAS)](../../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md) 在该数据库下创建表。
+同 StarRocks 内部数据库一致，如果您拥有 Unified Catalog 内数据库的 [CREATE TABLE](../../administration/user_privs/privilege_item.md#数据库权限-database) 权限，那么您可以使用 [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) 或 [CREATE TABLE AS SELECT (CTAS)](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md) 在该数据库下创建表。
 
 > **说明**
 >
@@ -927,7 +927,7 @@ DROP DATABASE <database_name>
 
 注意当前仅支持创建 Hive 表和 Iceberg 表。
 
-[切换至目标 Unified Catalog 和数据库](#切换-unified-catalog-和数据库)，然后通过 [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) 创建 Hive 表或 Iceberg 表：
+[切换至目标 Unified Catalog 和数据库](#切换-unified-catalog-和数据库)，然后通过 [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) 创建 Hive 表或 Iceberg 表：
 
 ```SQL
 CREATE TABLE <table_name>
@@ -953,7 +953,7 @@ PARTITION BY (id,dt);
 
 ## 向 Unified Catalog 内的表中插入数据
 
-同 StarRocks 内表一致，如果您拥有 Unified Catalog 内表的 [INSERT](../../administration/user_privs/privilege_item.md#表权限-table) 权限，那么您可以使用 [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 将 StarRocks 表数据写入到该表（当前仅支持写入到 Parquet 格式的 Unified Catalog 表）。
+同 StarRocks 内表一致，如果您拥有 Unified Catalog 内表的 [INSERT](../../administration/user_privs/privilege_item.md#表权限-table) 权限，那么您可以使用 [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 将 StarRocks 表数据写入到该表（当前仅支持写入到 Parquet 格式的 Unified Catalog 表）。
 
 > **说明**
 >
@@ -961,7 +961,7 @@ PARTITION BY (id,dt);
 
 注意当前仅支持向 Hive 表和 Iceberg 表中插入数据。
 
-[切换至目标 Unified Catalog 和数据库](#切换-unified-catalog-和数据库)，然后通过 [INSERT INTO](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 向 Hive 表或 Iceberg 表中插入数据：
+[切换至目标 Unified Catalog 和数据库](#切换-unified-catalog-和数据库)，然后通过 [INSERT INTO](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 向 Hive 表或 Iceberg 表中插入数据：
 
 ```SQL
 INSERT {INTO | OVERWRITE} <table_name>
@@ -988,7 +988,7 @@ VALUES
 
 ## 从 Unified Catalog 内删除表
 
-同 StarRocks 内表一致，如果您拥有 Unified Catalog 内表的 [DROP](../../administration/user_privs/privilege_item.md#表权限-table) 权限，那么您可以使用 [DROP TABLE](../../sql-reference/sql-statements/data-definition/DROP_TABLE.md) 来删除该表。
+同 StarRocks 内表一致，如果您拥有 Unified Catalog 内表的 [DROP](../../administration/user_privs/privilege_item.md#表权限-table) 权限，那么您可以使用 [DROP TABLE](../../sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md) 来删除该表。
 
 > **说明**
 >
@@ -996,7 +996,7 @@ VALUES
 
 注意当前仅支持删除 Hive 表和 Iceberg 表。
 
-[切换至目标 Unified Catalog 和数据库](#切换-unified-catalog-和数据库)，然后通过 [DROP TABLE](../../sql-reference/sql-statements/data-definition/DROP_TABLE.md) 删除 Hive 表或 Iceberg 表。
+[切换至目标 Unified Catalog 和数据库](#切换-unified-catalog-和数据库)，然后通过 [DROP TABLE](../../sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md) 删除 Hive 表或 Iceberg 表。
 
 ```SQL
 DROP TABLE <table_name>
diff --git a/docs/zh/data_source/data_cache.md b/docs/zh/data_source/data_cache.md
index ade7e487818b2e..dea84374973797 100644
--- a/docs/zh/data_source/data_cache.md
+++ b/docs/zh/data_source/data_cache.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Data Cache
@@ -94,7 +94,7 @@ mysql> explain verbose select col1 from hudi_table;
 
 其中 `dataCacheOptions={populate: false}` 即表明不填充 Data Cache，因为该查询会扫描全部分区。
 
-您还可以通过 Session Variable [populdate_datacache_mode](../reference/System_variable.md#populate_datacache_mode) 进一步精细化管理该行为。
+您还可以通过 Session Variable [populdate_datacache_mode](../sql-reference/System_variable.md#populate_datacache_mode) 进一步精细化管理该行为。
 
 ### 填充方式
 
@@ -108,7 +108,7 @@ Data Cache 支持以同步或异步的方式进行缓存填充。
 
   使用异步填充方式时，系统会尝试在尽可能不影响读取性能的前提下在后台对访问到的数据进行缓存。异步方式能够减少缓存填充对首次读取性能的影响，但填充效率较低。通常单次查询不能保证将访问到的所以数据都缓存到本地，往往需要多次。
 
-自 v3.3.0 起，系统默认以异步方式进行缓存，您可以通过修改 Session 变量 [enable_datacache_async_populate_mode](../reference/System_variable.md) 来修改填充方式。
+自 v3.3.0 起，系统默认以异步方式进行缓存，您可以通过修改 Session 变量 [enable_datacache_async_populate_mode](../sql-reference/System_variable.md) 来修改填充方式。
 
 ## Footer Cache
 
@@ -244,10 +244,10 @@ datacache_auto_adjust_enable=true
 
 ### 系统变量
 
-- [populdate_datacache_mode](../reference/System_variable.md#populate_datacache_mode)
-- [enable_datacache_io_adaptor](../reference/System_variable.md#enable_datacache_io_adaptor)
-- [enable_file_metacache](../reference/System_variable.md#enable_file_metacache)
-- [enable_datacache_async_populate_mode](../reference/System_variable.md)
+- [populdate_datacache_mode](../sql-reference/System_variable.md#populate_datacache_mode)
+- [enable_datacache_io_adaptor](../sql-reference/System_variable.md#enable_datacache_io_adaptor)
+- [enable_file_metacache](../sql-reference/System_variable.md#enable_file_metacache)
+- [enable_datacache_async_populate_mode](../sql-reference/System_variable.md)
 
 ### BE 参数
 
diff --git a/docs/zh/data_source/data_cache_observe.md b/docs/zh/data_source/data_cache_observe.md
index 7c56db6ef9f655..cd5f0d8410c17a 100644
--- a/docs/zh/data_source/data_cache_observe.md
+++ b/docs/zh/data_source/data_cache_observe.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Data Cache 可观测性
diff --git a/docs/zh/data_source/data_cache_warmup.md b/docs/zh/data_source/data_cache_warmup.md
index 64601b879fa283..1527ae76e1a6ff 100644
--- a/docs/zh/data_source/data_cache_warmup.md
+++ b/docs/zh/data_source/data_cache_warmup.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Data Cache 预热
@@ -114,7 +114,7 @@ mysql> cache select * from hive_catalog.test_db.lineitem properties("verbose"="t
 
 ## CACHE SELECT 定时调度
 
-CACHE SELECT 可以和 [SUBMIT TASK](../sql-reference/sql-statements/data-manipulation/SUBMIT_TASK.md) 结合，实现周期性的预热。
+CACHE SELECT 可以和 [SUBMIT TASK](../sql-reference/sql-statements/loading_unloading/ETL/SUBMIT_TASK.md) 结合，实现周期性的预热。
 
 每隔 5 分钟对 `lineitem` 表进行一次预热：
 
diff --git a/docs/zh/data_source/data_lakes.mdx b/docs/zh/data_source/data_lakes.mdx
index 98b80f6e0019f7..da097224fbe2f6 100644
--- a/docs/zh/data_source/data_lakes.mdx
+++ b/docs/zh/data_source/data_lakes.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 import DataLakeIntro from '../_assets/commonMarkdown/datalakeIntro.md'
diff --git a/docs/zh/data_source/datalake_faq.md b/docs/zh/data_source/datalake_faq.md
index 1cec2b5b9365c9..dee457a96eb71e 100644
--- a/docs/zh/data_source/datalake_faq.md
+++ b/docs/zh/data_source/datalake_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 数据湖相关 FAQ
diff --git a/docs/zh/data_source/feature-support-data-lake-analytics.md b/docs/zh/data_source/feature-support-data-lake-analytics.md
index 8be0bebf0b05e2..c77cc458de7ee7 100644
--- a/docs/zh/data_source/feature-support-data-lake-analytics.md
+++ b/docs/zh/data_source/feature-support-data-lake-analytics.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: "能力边界"
 ---
 
diff --git a/docs/zh/data_source/file_external_table.md b/docs/zh/data_source/file_external_table.md
index d3a3ec3840c361..488fbffc4776dd 100644
--- a/docs/zh/data_source/file_external_table.md
+++ b/docs/zh/data_source/file_external_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 文件外部表
@@ -14,7 +14,7 @@ displayed_sidebar: "Chinese"
 
 ## 使用限制
 
-- 当前仅支持在 [default_catalog](../data_source/catalog/default_catalog.md) 下的数据库内创建文件外部表，不支持 external catalog。您可以通过 [SHOW CATALOGS](../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md) 来查询集群下的 catalog。
+- 当前仅支持在 [default_catalog](../data_source/catalog/default_catalog.md) 下的数据库内创建文件外部表，不支持 external catalog。您可以通过 [SHOW CATALOGS](../sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md) 来查询集群下的 catalog。
 - 仅支持查询 Parquet、ORC、Avro、RCFile、或 SequenceFile 格式的数据文件。
 - 目前**仅支持读取**目标数据文件中的数据，不支持例如 INSERT、DELETE、DROP 等**写入**操作。
 
@@ -24,7 +24,7 @@ displayed_sidebar: "Chinese"
 
 ## 创建数据库 （可选）
 
-连接到 StarRocks 集群后，您可以在当前已有的数据库下创建文件外部表；也可以创建一个新的数据库来管理文件外部表。您可以使用 [SHOW DATABASES](../sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md) 来查询集群中的数据库，然后执行 `USE <db_name>` 切换到目标数据库。
+连接到 StarRocks 集群后，您可以在当前已有的数据库下创建文件外部表；也可以创建一个新的数据库来管理文件外部表。您可以使用 [SHOW DATABASES](../sql-reference/sql-statements/Database/SHOW_DATABASES.md) 来查询集群中的数据库，然后执行 `USE <db_name>` 切换到目标数据库。
 
 创建数据库的语法如下。
 
@@ -288,4 +288,4 @@ SELECT * FROM t0;
 
 ## 管理文件外部表
 
-您可以执行 [DESC](../sql-reference/sql-statements/Utility/DESCRIBE.md) 来查询文件外部表的信息和表结构，或者通过 [DROP TABLE](../sql-reference/sql-statements/data-definition/DROP_TABLE.md) 来删除文件外部表。
+您可以执行 [DESC](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md) 来查询文件外部表的信息和表结构，或者通过 [DROP TABLE](../sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md) 来删除文件外部表。
diff --git a/docs/zh/data_source/icebergtutorial.mdx b/docs/zh/data_source/icebergtutorial.mdx
index f4af2fcf7195de..4a9145d8d7946d 100644
--- a/docs/zh/data_source/icebergtutorial.mdx
+++ b/docs/zh/data_source/icebergtutorial.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: Chinese
+displayed_sidebar: docs
 sidebar_label: 基于 Apache Iceberg 的数据湖分析
 title: 基于 Apache Iceberg 的数据湖分析
 description: 基于 Docker 创建的 Iceberg 数据湖分析
diff --git a/docs/zh/deployment/deploy_manually.md b/docs/zh/deployment/deploy_manually.md
index 53dbb2e316a8f3..ca9930ce984043 100644
--- a/docs/zh/deployment/deploy_manually.md
+++ b/docs/zh/deployment/deploy_manually.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 手动部署 StarRocks
@@ -377,7 +377,7 @@ Compute Node（CN）是一种无状态的计算服务，本身不存储数据。
    如果字段 `Alive` 为 `true`，说明该 CN 节点正常启动并加入集群。
 
    如果执行查询时需要使用 CN 节点扩展算力，则需要设置系统变量 `SET
-prefer_compute_node = true;` 和 `SET use_compute_nodes = -1;`。系统变量的更多信息，请参见[系统变量](../reference/System_variable.md#支持的变量)。
+prefer_compute_node = true;` 和 `SET use_compute_nodes = -1;`。系统变量的更多信息，请参见[系统变量](../sql-reference/System_variable.md#支持的变量)。
 
 ## 第五步：（可选）部署高可用 FE 集群
 
@@ -402,7 +402,7 @@ prefer_compute_node = true;` 和 `SET use_compute_nodes = -1;`。系统变量的
    > **说明**
    >
    > - 您只能通过一条 SQL 添加一个 Follower FE 节点。
-   > - 如需添加更多的 Observer FE 节点，请执行 `ALTER SYSTEM ADD OBSERVER "<fe_address>:<edit_log_port>"`。有关详细说明，请参考 [ALTER SYSTEM - FE](../sql-reference/sql-statements/Administration/ALTER_SYSTEM.md)。
+   > - 如需添加更多的 Observer FE 节点，请执行 `ALTER SYSTEM ADD OBSERVER "<fe_address>:<edit_log_port>"`。有关详细说明，请参考 [ALTER SYSTEM - FE](../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md)。
 
 3. 在新的 FE 示例上启动终端，创建元数据存储路径，进入 StarRocks 部署目录，并修改 FE 配置文件 **fe/conf/fe.conf**。详细信息，请参考 [第一步：启动 Leader FE 节点](#第一步启动-leader-fe-节点)。
 
diff --git a/docs/zh/deployment/deployment_overview.md b/docs/zh/deployment/deployment_overview.md
index 313c6dda2c7d55..4d341e33f2c3e0 100644
--- a/docs/zh/deployment/deployment_overview.md
+++ b/docs/zh/deployment/deployment_overview.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 部署总览
diff --git a/docs/zh/deployment/deployment_prerequisites.md b/docs/zh/deployment/deployment_prerequisites.md
index 5d7a32317f3ee2..6676e01c54dcb1 100644
--- a/docs/zh/deployment/deployment_prerequisites.md
+++ b/docs/zh/deployment/deployment_prerequisites.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 部署前提条件
diff --git a/docs/zh/deployment/downgrade.md b/docs/zh/deployment/downgrade.md
index 6005605b3a13ac..f5a68b71398377 100644
--- a/docs/zh/deployment/downgrade.md
+++ b/docs/zh/deployment/downgrade.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 降级 StarRocks
@@ -99,7 +99,7 @@ ADMIN SET FRONTEND CONFIG ("disable_colocate_balance"="false");
 
 1. 生成新的元数据快照。
 
-   a. 执行 [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/Administration/ALTER_SYSTEM.md) 创建新的元数据快照文件。
+   a. 执行 [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) 创建新的元数据快照文件。
 
    b. 通过查看 Leader FE 节点的日志文件 **fe.log** 确认元数据快照文件是否推送完成。如果日志打印以下内容，则说明快照文件推送完成：
 
diff --git a/docs/zh/deployment/environment_configurations.md b/docs/zh/deployment/environment_configurations.md
index afe4803fd1ce3c..99195b92848eae 100644
--- a/docs/zh/deployment/environment_configurations.md
+++ b/docs/zh/deployment/environment_configurations.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 检查环境配置
diff --git a/docs/zh/deployment/helm.md b/docs/zh/deployment/helm.md
index 25f371a51d2ffc..fe658c5190389a 100644
--- a/docs/zh/deployment/helm.md
+++ b/docs/zh/deployment/helm.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 Helm 部署 StarRocks 集群
diff --git a/docs/zh/deployment/plan_cluster.md b/docs/zh/deployment/plan_cluster.md
index cd293a66fba5e7..1dc88c301e0d2c 100644
--- a/docs/zh/deployment/plan_cluster.md
+++ b/docs/zh/deployment/plan_cluster.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 规划 StarRocks 集群
diff --git a/docs/zh/deployment/post_deployment_setup.md b/docs/zh/deployment/post_deployment_setup.md
index ef44b9c59479c6..891219e60a8866 100644
--- a/docs/zh/deployment/post_deployment_setup.md
+++ b/docs/zh/deployment/post_deployment_setup.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 部署后设置
@@ -74,7 +74,7 @@ displayed_sidebar: "Chinese"
   SET GLOBAL pipeline_dop = 0;
   ```
 
-有关系统变量的更多信息，请参阅 [系统变量](../reference/System_variable.md)。
+有关系统变量的更多信息，请参阅 [系统变量](../sql-reference/System_variable.md)。
 
 ## 设置用户属性
 
diff --git a/docs/zh/deployment/prepare_deployment_files.md b/docs/zh/deployment/prepare_deployment_files.md
index a746309a8cdf4f..f8d7707e9b7bde 100644
--- a/docs/zh/deployment/prepare_deployment_files.md
+++ b/docs/zh/deployment/prepare_deployment_files.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 准备部署文件
diff --git a/docs/zh/deployment/shared_data/azure.md b/docs/zh/deployment/shared_data/azure.md
index 4ee46f3b339464..fb9c127a0ef3d7 100644
--- a/docs/zh/deployment/shared_data/azure.md
+++ b/docs/zh/deployment/shared_data/azure.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 基于 Azure Blob 部署
diff --git a/docs/zh/deployment/shared_data/feature-support-shared-data.md b/docs/zh/deployment/shared_data/feature-support-shared-data.md
index 6b05bc66aa146c..2c5093e28bdb42 100644
--- a/docs/zh/deployment/shared_data/feature-support-shared-data.md
+++ b/docs/zh/deployment/shared_data/feature-support-shared-data.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: "能力边界"
 ---
 
@@ -182,7 +182,7 @@ CANCEL COMPACTION WHERE TXN_ID = 123;
 
 ### 手动 Compaction
 
-从 v3.1 开始，StarRocks 支持通过 SQL 语句手动 Compaction。可以指定表或分区进行 Compaction。有关详细信息，请参阅 [手动 Compaction](../../sql-reference/sql-statements/data-definition/ALTER_TABLE.md#手动-compaction)。
+从 v3.1 开始，StarRocks 支持通过 SQL 语句手动 Compaction。可以指定表或分区进行 Compaction。有关详细信息，请参阅 [手动 Compaction](../../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md#手动-compaction)。
 
 ## 主键表
 
diff --git a/docs/zh/deployment/shared_data/gcs.md b/docs/zh/deployment/shared_data/gcs.md
index 71e71c662d8999..df6495e51b0e65 100644
--- a/docs/zh/deployment/shared_data/gcs.md
+++ b/docs/zh/deployment/shared_data/gcs.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 基于 GCS 部署
@@ -132,7 +132,7 @@ StarRocks 集群的运行模式。有效值：
 
 <SharedDataUseIntro />
 
-以下示例使用 HMAC Access Key 以及 Secret Key 认证为 GCS 存储空间 `defaultbucket` 创建存储卷 `def_volume`，激活[分区前缀](../../sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md#分区前缀)功能，并将其设置为默认存储卷：
+以下示例使用 HMAC Access Key 以及 Secret Key 认证为 GCS 存储空间 `defaultbucket` 创建存储卷 `def_volume`，激活[分区前缀](../../sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md#分区前缀)功能，并将其设置为默认存储卷：
 
 ```SQL
 CREATE STORAGE VOLUME def_volume
diff --git a/docs/zh/deployment/shared_data/hdfs.md b/docs/zh/deployment/shared_data/hdfs.md
index bbf2b19ee5a507..b55bf44d3a04c9 100644
--- a/docs/zh/deployment/shared_data/hdfs.md
+++ b/docs/zh/deployment/shared_data/hdfs.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 基于 HDFS 部署
diff --git a/docs/zh/deployment/shared_data/minio.md b/docs/zh/deployment/shared_data/minio.md
index 0623cfebdaafdc..6c9ec707743dc5 100644
--- a/docs/zh/deployment/shared_data/minio.md
+++ b/docs/zh/deployment/shared_data/minio.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 基于 MinIO 部署
@@ -133,7 +133,7 @@ StarRocks 集群的运行模式。有效值：
 
 <SharedDataUseIntro />
 
-以下示例使用 Access Key 以及 Secret Key 认证为 MinIO 存储空间 `defaultbucket` 创建存储卷 `def_volume`，激活[分区前缀](../../sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md#分区前缀)功能，并将其设置为默认存储卷：
+以下示例使用 Access Key 以及 Secret Key 认证为 MinIO 存储空间 `defaultbucket` 创建存储卷 `def_volume`，激活[分区前缀](../../sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md#分区前缀)功能，并将其设置为默认存储卷：
 
 ```SQL
 CREATE STORAGE VOLUME def_volume
diff --git a/docs/zh/deployment/shared_data/other.md b/docs/zh/deployment/shared_data/other.md
index 0f70a25519f5c4..664645fa3b343c 100644
--- a/docs/zh/deployment/shared_data/other.md
+++ b/docs/zh/deployment/shared_data/other.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 基于其他云存储部署
@@ -232,7 +232,7 @@ StarRocks 集群的运行模式。有效值：
 
 <SharedDataUseIntro />
 
-以下示例使用 Access Key 以及 Secret Key 认证为 OSS 存储空间 `defaultbucket` 创建存储卷 `def_volume`，激活[分区前缀](../../sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md#分区前缀)功能，并将其设置为默认存储卷：
+以下示例使用 Access Key 以及 Secret Key 认证为 OSS 存储空间 `defaultbucket` 创建存储卷 `def_volume`，激活[分区前缀](../../sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md#分区前缀)功能，并将其设置为默认存储卷：
 
 ```SQL
 CREATE STORAGE VOLUME def_volume
diff --git a/docs/zh/deployment/shared_data/s3.md b/docs/zh/deployment/shared_data/s3.md
index 3d6e58799d7f1a..8fd2d42dce4094 100644
--- a/docs/zh/deployment/shared_data/s3.md
+++ b/docs/zh/deployment/shared_data/s3.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 基于 AWS S3 部署
@@ -258,7 +258,7 @@ StarRocks 集群的运行模式。有效值：
 
 <SharedDataUseIntro />
 
-以下示例使用 IAM User 认证为 AWS S3 存储空间 `defaultbucket` 创建存储卷 `def_volume`，激活[分区前缀](../../sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md#分区前缀)功能，并将其设置为默认存储卷：
+以下示例使用 IAM User 认证为 AWS S3 存储空间 `defaultbucket` 创建存储卷 `def_volume`，激活[分区前缀](../../sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md#分区前缀)功能，并将其设置为默认存储卷：
 
 ```SQL
 CREATE STORAGE VOLUME def_volume
diff --git a/docs/zh/deployment/shared_data/shared_data.mdx b/docs/zh/deployment/shared_data/shared_data.mdx
index dd38e1c88d595f..ee3d3ca73e7601 100644
--- a/docs/zh/deployment/shared_data/shared_data.mdx
+++ b/docs/zh/deployment/shared_data/shared_data.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 #
diff --git a/docs/zh/deployment/sr_operator.md b/docs/zh/deployment/sr_operator.md
index da729d8105bbf5..489d8d35b77d5d 100644
--- a/docs/zh/deployment/sr_operator.md
+++ b/docs/zh/deployment/sr_operator.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 Operator 部署 StarRocks 集群
diff --git a/docs/zh/deployment/upgrade.md b/docs/zh/deployment/upgrade.md
index d55a1906cfdcc3..1cceee241e28b1 100644
--- a/docs/zh/deployment/upgrade.md
+++ b/docs/zh/deployment/upgrade.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['shengji']
 ---
 
@@ -38,7 +38,7 @@ StarRocks 的版本号由三个数字表示，格式为 **Major.Minor.Patch**，
 >
 > 如果您需要进行连续的大版本升级，比如从 2.4->2.5->3.0->3.1->3.2，或者在升级之后进行了降级，之后再次执行升级，比如 2.5->3.0->2.5->3.0。为了避免部分 FE 节点元数据升级失败，需要在相邻的两次升级之间或降级后升级前执行如下操作：
 >
-> 1. 执行 [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/Administration/ALTER_SYSTEM.md) 创建新的元数据快照文件。
+> 1. 执行 [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) 创建新的元数据快照文件。
 > 2. 等待元数据快照文件同步至其他 FE 节点。
 >
 > 您可以通过查看 Leader FE 节点的日志文件 **fe.log** 确认元数据快照文件是否推送完成。如果日志打印以下内容，则说明快照文件推送完成："push image.xxx from subdir [] to other nodes. totally xx nodes, push succeeded xx nodes"。
diff --git a/docs/zh/developers/build-starrocks/Build_in_docker.md b/docs/zh/developers/build-starrocks/Build_in_docker.md
index da844133650d3e..275e2e42776f91 100644
--- a/docs/zh/developers/build-starrocks/Build_in_docker.md
+++ b/docs/zh/developers/build-starrocks/Build_in_docker.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 Docker 编译 StarRocks
diff --git a/docs/zh/developers/build-starrocks/build_starrocks_on_ubuntu.md b/docs/zh/developers/build-starrocks/build_starrocks_on_ubuntu.md
index f956d5747b86a2..779f72cd6899b7 100644
--- a/docs/zh/developers/build-starrocks/build_starrocks_on_ubuntu.md
+++ b/docs/zh/developers/build-starrocks/build_starrocks_on_ubuntu.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 基于 Ubuntu 编译 StarRocks
diff --git a/docs/zh/developers/debuginfo.md b/docs/zh/developers/debuginfo.md
index 7801bb432bfb20..5c11baefae8d4e 100644
--- a/docs/zh/developers/debuginfo.md
+++ b/docs/zh/developers/debuginfo.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 debuginfo 文件进行调试
diff --git a/docs/zh/developers/trace-tools/query_trace_profile.md b/docs/zh/developers/trace-tools/query_trace_profile.md
index 314dc052eaa274..f923c6899d5227 100644
--- a/docs/zh/developers/trace-tools/query_trace_profile.md
+++ b/docs/zh/developers/trace-tools/query_trace_profile.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Query Trace Profile
diff --git a/docs/zh/ecosystem_release/flink_connector.md b/docs/zh/ecosystem_release/flink_connector.md
index 3c1f77fbed4160..dd0685d41a060c 100644
--- a/docs/zh/ecosystem_release/flink_connector.md
+++ b/docs/zh/ecosystem_release/flink_connector.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Flink connector 版本发布
diff --git a/docs/zh/ecosystem_release/kafka_connector.md b/docs/zh/ecosystem_release/kafka_connector.md
index 71accf46cb78fc..17bb47c898ea16 100644
--- a/docs/zh/ecosystem_release/kafka_connector.md
+++ b/docs/zh/ecosystem_release/kafka_connector.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Kafka connector 版本发布
diff --git a/docs/zh/ecosystem_release/spark_connector.md b/docs/zh/ecosystem_release/spark_connector.md
index dc6ad19dbed55f..edf0827bd59ac5 100644
--- a/docs/zh/ecosystem_release/spark_connector.md
+++ b/docs/zh/ecosystem_release/spark_connector.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Spark connector 版本发布
diff --git a/docs/zh/ecosystem_release/starrocks-kubernetes-operator.md b/docs/zh/ecosystem_release/starrocks-kubernetes-operator.md
index 4a2a13c50ed873..a9b311fd3f8e39 100644
--- a/docs/zh/ecosystem_release/starrocks-kubernetes-operator.md
+++ b/docs/zh/ecosystem_release/starrocks-kubernetes-operator.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Kubernetes Operator 版本发布
diff --git a/docs/zh/faq/Deploy_faq.md b/docs/zh/faq/Deploy_faq.md
index 2edbb70377421e..4f780b83646db7 100644
--- a/docs/zh/faq/Deploy_faq.md
+++ b/docs/zh/faq/Deploy_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 部署常见问题
diff --git a/docs/zh/faq/Dump_query.md b/docs/zh/faq/Dump_query.md
index d5bc79d4f0f492..3a5024957e8e6e 100644
--- a/docs/zh/faq/Dump_query.md
+++ b/docs/zh/faq/Dump_query.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # query_dump 接口
diff --git a/docs/zh/faq/Exporting_faq.md b/docs/zh/faq/Exporting_faq.md
index 22df349f8e865b..b8ae9f78ae4035 100644
--- a/docs/zh/faq/Exporting_faq.md
+++ b/docs/zh/faq/Exporting_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 导出
diff --git a/docs/zh/faq/Others.md b/docs/zh/faq/Others.md
index 98261d0f4565cb..3a54e5c35f4204 100644
--- a/docs/zh/faq/Others.md
+++ b/docs/zh/faq/Others.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 其他问题
diff --git a/docs/zh/faq/Sql_faq.md b/docs/zh/faq/Sql_faq.md
index fab5b3533783d9..fb60c9ec7d02dd 100644
--- a/docs/zh/faq/Sql_faq.md
+++ b/docs/zh/faq/Sql_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 查询常见问题
@@ -178,7 +178,7 @@ StarRocks 使用 keyword 数据类型对该查询语句进行转换。因为该
 
 ## 如何快速统计 StarRocks 库、表的大小，所占的磁盘资源？
 
-查看库、表的存储大小可以用 [SHOW DATA](../sql-reference/sql-statements/data-manipulation/SHOW_DATA.md) 命令查看。
+查看库、表的存储大小可以用 [SHOW DATA](../sql-reference/sql-statements/Database/SHOW_DATA.md) 命令查看。
 
 `SHOW DATA;` 可以展示当前数据库下所有表的数据量和副本数。
 
diff --git a/docs/zh/faq/Video.md b/docs/zh/faq/Video.md
index f08b1edc2f4a3f..9e36e49cfb06b1 100644
--- a/docs/zh/faq/Video.md
+++ b/docs/zh/faq/Video.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 视频资源
diff --git a/docs/zh/faq/datalake.mdx b/docs/zh/faq/datalake.mdx
index e25d87e92e283a..ea6f69ab3ddc2a 100644
--- a/docs/zh/faq/datalake.mdx
+++ b/docs/zh/faq/datalake.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: 数据湖相关 FAQ
 title: 数据湖相关 FAQ
 ---
diff --git a/docs/zh/faq/faq.mdx b/docs/zh/faq/faq.mdx
index fe6093a5afbe6f..a919e460a76e60 100644
--- a/docs/zh/faq/faq.mdx
+++ b/docs/zh/faq/faq.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 常见问题解答
diff --git a/docs/zh/faq/loading/Broker_load_faq.md b/docs/zh/faq/loading/Broker_load_faq.md
index 476e336f2fd7c3..6f3b7199b46604 100644
--- a/docs/zh/faq/loading/Broker_load_faq.md
+++ b/docs/zh/faq/loading/Broker_load_faq.md
@@ -1,12 +1,12 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Broker Load 导入常见问题
 
 ## 1. Broker Load 是否支持再次执行已经执行成功、处于 FINISHED 状态的导入作业？
 
-Broker Load 不支持再次执行已经执行成功、处于 FINISHED 状态的导入作业。而且，为了保证数据不丢不重，每个执行成功的导入作业的标签 (Label) 均不可复用。可以使用 [SHOW LOAD](../../sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md) 语句查看历史的导入记录，找到想要再次执行的导入作业，复制作业信息，并修改作业标签后，重新创建一个导入作业并执行。
+Broker Load 不支持再次执行已经执行成功、处于 FINISHED 状态的导入作业。而且，为了保证数据不丢不重，每个执行成功的导入作业的标签 (Label) 均不可复用。可以使用 [SHOW LOAD](../../sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md) 语句查看历史的导入记录，找到想要再次执行的导入作业，复制作业信息，并修改作业标签后，重新创建一个导入作业并执行。
 
 ## 2. 通过 Broker Load 导入 HDFS 数据时，为什么数据的导入日期字段会出现异常，比正确的日期时间多加了 8 小时？这种情况应该怎么处理？
 
@@ -18,11 +18,11 @@ StarRocks 表在建表时设置的 `timezone` 为中国时区，创建 Broker Lo
 
 ## 4. 为什么 Broker Load 导入作业没报错，但是却查询不到数据？
 
-Broker Load 是一种异步的导入方式，创建导入作业的语句没报错，不代表导入作业成功了。可以通过 [SHOW LOAD](../../sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md) 语句来查看导入作业的结果状态和 `errmsg` 信息，然后修改导入作业的参数配置后，再重试导入作业。
+Broker Load 是一种异步的导入方式，创建导入作业的语句没报错，不代表导入作业成功了。可以通过 [SHOW LOAD](../../sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md) 语句来查看导入作业的结果状态和 `errmsg` 信息，然后修改导入作业的参数配置后，再重试导入作业。
 
 ## 5. 导入报 "failed to send batch" 或 "TabletWriter add batch with unknown id" 错误应该如何处理？
 
-该错误由数据写入超时而引起。需要修改[系统变量](../../reference/System_variable.md) `query_timeout` 和 [BE 配置项](../../administration/management/BE_configuration.md) `streaming_load_rpc_max_alive_time_sec` 的配置。
+该错误由数据写入超时而引起。需要修改[系统变量](../../sql-reference/System_variable.md) `query_timeout` 和 [BE 配置项](../../administration/management/BE_configuration.md) `streaming_load_rpc_max_alive_time_sec` 的配置。
 
 ## 6. 导入报 "LOAD-RUN-FAIL; msg:OrcScannerAdapter::init_include_columns. col name = xxx not found" 错误应该如何处理？
 
@@ -37,7 +37,7 @@ SET
 )
 ```
 
-上述示例，表示将 Parquet 或 ORC 文件中以 `tmp_c1` 和 `tmp_c2` 为列名的列，分别映射到 StarRocks 表中的 `name` 和 `id` 列。如果没有使用 `SET` 子句，则以 `column_list` 参数中指定的列作为映射。具体请参见 [BROKER LOAD](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+上述示例，表示将 Parquet 或 ORC 文件中以 `tmp_c1` 和 `tmp_c2` 为列名的列，分别映射到 StarRocks 表中的 `name` 和 `id` 列。如果没有使用 `SET` 子句，则以 `column_list` 参数中指定的列作为映射。具体请参见 [BROKER LOAD](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 > **注意**
 >
diff --git a/docs/zh/faq/loading/CloudCanal_load_faq.md b/docs/zh/faq/loading/CloudCanal_load_faq.md
index c82e99f513dabe..e27a9f6eac6896 100644
--- a/docs/zh/faq/loading/CloudCanal_load_faq.md
+++ b/docs/zh/faq/loading/CloudCanal_load_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # CloudCanal 导入常见问题
diff --git a/docs/zh/faq/loading/DataX_faq.md b/docs/zh/faq/loading/DataX_faq.md
index b161c4b78b16a5..eaf7b2aabe279e 100644
--- a/docs/zh/faq/loading/DataX_faq.md
+++ b/docs/zh/faq/loading/DataX_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # DataX 导入常见问题
diff --git a/docs/zh/faq/loading/Flink_connector_faq.md b/docs/zh/faq/loading/Flink_connector_faq.md
index 187f9877e46358..2ddd105f928ccb 100644
--- a/docs/zh/faq/loading/Flink_connector_faq.md
+++ b/docs/zh/faq/loading/Flink_connector_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Flink Connector 导入常见问题
diff --git a/docs/zh/faq/loading/Insert_into_faq.md b/docs/zh/faq/loading/Insert_into_faq.md
index 0c87e038c3cf84..1fc0012973760a 100644
--- a/docs/zh/faq/loading/Insert_into_faq.md
+++ b/docs/zh/faq/loading/Insert_into_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # INSERT INTO 导入常见问题
diff --git a/docs/zh/faq/loading/Loading_faq.md b/docs/zh/faq/loading/Loading_faq.md
index c17f4cdd8d248b..be8e8133fe5f0f 100644
--- a/docs/zh/faq/loading/Loading_faq.md
+++ b/docs/zh/faq/loading/Loading_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 导入通用问题
@@ -48,7 +48,7 @@ StarRocks 集群中同一个数据库内已经有一个具有相同标签的导
 
 ## 3. 发生数据质量错误 "ETL_QUALITY_UNSATISFIED; msg:quality not good enough to cancel" 应该如何处理？
 
-运行 [SHOW LOAD](../../sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md) 语句。在语句返回的信息中，找到 URL，然后查看错误数据。
+运行 [SHOW LOAD](../../sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md) 语句。在语句返回的信息中，找到 URL，然后查看错误数据。
 
 常见的数据质量错误有：
 
diff --git a/docs/zh/faq/loading/Routine_load_faq.md b/docs/zh/faq/loading/Routine_load_faq.md
index 06308d48b70908..77b9597381b5e2 100644
--- a/docs/zh/faq/loading/Routine_load_faq.md
+++ b/docs/zh/faq/loading/Routine_load_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Routine Load 导入常见问题
@@ -25,8 +25,8 @@ min(alive_be_number, partition_number, desired_concurrent_number, max_routine_lo
 - `partition_number`：消费分区数量。
 
 - `desired_concurrent_number`：Routine Load 导入作业时为单个导入作业设置较高的期望任务并行度，默认值为 3。
-  - 如果还未创建导入作业，则需要在执行 [CREATE ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md) 创建导入作业时，设置该参数。
-  - 如果已经创建导入作业，则需要执行 [ALTER ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD.md)，修改该参数。
+  - 如果还未创建导入作业，则需要在执行 [CREATE ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md) 创建导入作业时，设置该参数。
+  - 如果已经创建导入作业，则需要执行 [ALTER ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md)，修改该参数。
 
 - `max_routine_load_task_concurrent_num`：Routine Load 导入作业的默认最大任务并行度的 ，默认值为 `5`。该参数为 FE 动态参数，更多说明和设置方式，请参见 [配置参数](../../administration/management/FE_configuration.md#导入导出)。
 
@@ -34,7 +34,7 @@ min(alive_be_number, partition_number, desired_concurrent_number, max_routine_lo
 
 假设消费分区数量为 `7`，存活 BE 数量为 `5`，`max_routine_load_task_concurrent_num` 为默认值 `5`。此时如果需要增加实际任务并发度至上限，则需要将 `desired_concurrent_number` 设置为 `5`（默认值为 `3`），则计算实际任务并行度 `min(5,7,5,5)` 为 `5`。
 
-更多参数说明，请参见 [CREATE ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md#示例)。
+更多参数说明，请参见 [CREATE ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md#示例)。
 
 **方式二**：**增大单个导入任务消费分区的数据量**。
 
@@ -71,10 +71,10 @@ I0325 20:27:50.410579 15259 data_consumer_group.cpp:131] consumer group done: 41
 
   **解决方式**：您可以根据 `ReasonOfStateChanged`, `ErrorLogUrls`报错进行排查。
 
-  - 如果是数据源的数据格式问题，则需要检查数据源数据格式，并进行修复。修复后您可以使用 [RESUME ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md)，恢复 **PAUSED** 状态的导入作业。
+  - 如果是数据源的数据格式问题，则需要检查数据源数据格式，并进行修复。修复后您可以使用 [RESUME ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md)，恢复 **PAUSED** 状态的导入作业。
 
   - 如果是数据源的数据格式无法被 StarRocks 解析，则需要调整错误行数阈值`max_error_number`。
-  您可以先执行 [SHOW ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md)，查看错误行数阈值 `max_error_number`，然后执行 [ALTER ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD.md)，适当提高错误行数阈值 `max_error_number`。修改阈值后您可以使用 [RESUME ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md)，恢复 **PAUSED** 状态的导入作业。
+  您可以先执行 [SHOW ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md)，查看错误行数阈值 `max_error_number`，然后执行 [ALTER ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md)，适当提高错误行数阈值 `max_error_number`。修改阈值后您可以使用 [RESUME ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md)，恢复 **PAUSED** 状态的导入作业。
 
 - **报错提示**：如果导入作业变成为 **CANCELLED** 状态。
 
diff --git a/docs/zh/faq/loading/Stream_load_faq.md b/docs/zh/faq/loading/Stream_load_faq.md
index cb28d0a1074c3e..e69e86a94c795b 100644
--- a/docs/zh/faq/loading/Stream_load_faq.md
+++ b/docs/zh/faq/loading/Stream_load_faq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Stream Load 导入常见问题
@@ -18,7 +18,7 @@ Stream Load 不支持识别 CSV 格式文件开头前几行的列名，列名对
 
 - 在Stream Load 执行命令或语句中加入 `-H "max_filter_ratio:0.01"`，这样可以给导入作业设置一个 1% 或者更小、但能容错数行的容错率，从而将前几行的错误忽视掉。设置容错率后，返回结果的 `ErrorURL` 依旧会提示有错误，但导入作业整体会成功。容错率不宜设置过大，避免漏掉其他数据问题。
 
-从 3.0 版本起，Stream Load 支持 `skip_header` 参数，用于指定跳过 CSV 文件开头的前几行数据。参见 [CSV 适用参数](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md#csv-适用参数)。
+从 3.0 版本起，Stream Load 支持 `skip_header` 参数，用于指定跳过 CSV 文件开头的前几行数据。参见 [CSV 适用参数](../../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md#csv-适用参数)。
 
 ## 2. 当前业务的分区键对应的数据不是标准的 DATE 和 INT 类型，比如是 202106.00 的格式，如果需要使用 Stream Load 把这些数据导入到 StarRocks 中，需要如何转换？
 
diff --git a/docs/zh/faq/loading/synchronize_mysql_into_sr.md b/docs/zh/faq/loading/synchronize_mysql_into_sr.md
index 0ed57e29ce3365..f6a271944fa737 100644
--- a/docs/zh/faq/loading/synchronize_mysql_into_sr.md
+++ b/docs/zh/faq/loading/synchronize_mysql_into_sr.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # MySQL 实时同步至 StarRocks 常见问题
diff --git a/docs/zh/feedback-and-contribute.md b/docs/zh/feedback-and-contribute.md
index 844b1a4ac49002..0e26c7852a2f64 100644
--- a/docs/zh/feedback-and-contribute.md
+++ b/docs/zh/feedback-and-contribute.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # How to feedback and contribute
diff --git a/docs/zh/integrations/BI_integrations/FineBI.md b/docs/zh/integrations/BI_integrations/FineBI.md
index a5b73ab14e5472..75539fed589247 100644
--- a/docs/zh/integrations/BI_integrations/FineBI.md
+++ b/docs/zh/integrations/BI_integrations/FineBI.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 
diff --git a/docs/zh/integrations/BI_integrations/Hex.md b/docs/zh/integrations/BI_integrations/Hex.md
index 153c0bc51780f2..344387b67ec0b3 100644
--- a/docs/zh/integrations/BI_integrations/Hex.md
+++ b/docs/zh/integrations/BI_integrations/Hex.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Hex
diff --git a/docs/zh/integrations/BI_integrations/Metabase.md b/docs/zh/integrations/BI_integrations/Metabase.md
index 7a5f67a182d7aa..d47b9744b58fbf 100644
--- a/docs/zh/integrations/BI_integrations/Metabase.md
+++ b/docs/zh/integrations/BI_integrations/Metabase.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Metabase
diff --git a/docs/zh/integrations/BI_integrations/Querybook.md b/docs/zh/integrations/BI_integrations/Querybook.md
index d116630674b32c..65f169d34c9bee 100644
--- a/docs/zh/integrations/BI_integrations/Querybook.md
+++ b/docs/zh/integrations/BI_integrations/Querybook.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Querybook
diff --git a/docs/zh/integrations/BI_integrations/QuickBI.md b/docs/zh/integrations/BI_integrations/QuickBI.md
index e08a03896aeebc..951f3c914ceedb 100644
--- a/docs/zh/integrations/BI_integrations/QuickBI.md
+++ b/docs/zh/integrations/BI_integrations/QuickBI.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # QuickBI
diff --git a/docs/zh/integrations/BI_integrations/Superset.md b/docs/zh/integrations/BI_integrations/Superset.md
index 17a9763ac2e057..a6e69dc69d6dc5 100644
--- a/docs/zh/integrations/BI_integrations/Superset.md
+++ b/docs/zh/integrations/BI_integrations/Superset.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Apache Superset
diff --git a/docs/zh/integrations/BI_integrations/Tableau_Desktop.md b/docs/zh/integrations/BI_integrations/Tableau_Desktop.md
index 0b307239c8c3e2..41bde108150533 100644
--- a/docs/zh/integrations/BI_integrations/Tableau_Desktop.md
+++ b/docs/zh/integrations/BI_integrations/Tableau_Desktop.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Tableau Desktop
diff --git a/docs/zh/integrations/IDE_integrations/DBeaver.md b/docs/zh/integrations/IDE_integrations/DBeaver.md
index 2cee2d3b264b4a..a04fcacdd64149 100644
--- a/docs/zh/integrations/IDE_integrations/DBeaver.md
+++ b/docs/zh/integrations/IDE_integrations/DBeaver.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # DBeaver
diff --git a/docs/zh/integrations/IDE_integrations/DataGrip.md b/docs/zh/integrations/IDE_integrations/DataGrip.md
index 00d3a9ae3b20db..834e641dbc8aa2 100644
--- a/docs/zh/integrations/IDE_integrations/DataGrip.md
+++ b/docs/zh/integrations/IDE_integrations/DataGrip.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # DataGrip
diff --git a/docs/zh/integrations/IDE_integrations/Dataphin.md b/docs/zh/integrations/IDE_integrations/Dataphin.md
index 904948ede57147..dd296429c38e6a 100644
--- a/docs/zh/integrations/IDE_integrations/Dataphin.md
+++ b/docs/zh/integrations/IDE_integrations/Dataphin.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Dataphin
diff --git a/docs/zh/integrations/IDE_integrations/jupysql.md b/docs/zh/integrations/IDE_integrations/jupysql.md
index e609635c39c12d..a1b212f691f339 100644
--- a/docs/zh/integrations/IDE_integrations/jupysql.md
+++ b/docs/zh/integrations/IDE_integrations/jupysql.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Jupyter
diff --git a/docs/zh/integrations/authenticate_to_aws_resources.md b/docs/zh/integrations/authenticate_to_aws_resources.md
index a92234e97a7686..6a6bb461a03760 100644
--- a/docs/zh/integrations/authenticate_to_aws_resources.md
+++ b/docs/zh/integrations/authenticate_to_aws_resources.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: AWS
 description: "本文介绍如何认证 AWS 资源"
 ---
@@ -38,19 +38,19 @@ IAM User 支持通过 AWS IAM User 来实现对外部数据源的访问认证和
 
 关于访问特定 AWS 资源所需要创建的 IAM 策略，见如下内容：
 
-- [从 AWS S3 批量导入数据](../reference/aws_iam_policies.md#从-aws-s3-批量导入数据)
-- [从 AWS S3 读写数据](../reference/aws_iam_policies.md#从-aws-s3-读写数据)
-- [对接 AWS Glue](../reference/aws_iam_policies.md#对接-aws-glue)
+- [从 AWS S3 批量导入数据](../sql-reference/aws_iam_policies.md#从-aws-s3-批量导入数据)
+- [从 AWS S3 读写数据](../sql-reference/aws_iam_policies.md#从-aws-s3-读写数据)
+- [对接 AWS Glue](../sql-reference/aws_iam_policies.md#对接-aws-glue)
 
 ### 基于 Instance Profile 认证鉴权
 
-把声明了访问特定 AWS 资源的 [IAM 策略](../reference/aws_iam_policies.md) 添加到 EC2 实例关联角色。
+把声明了访问特定 AWS 资源的 [IAM 策略](../sql-reference/aws_iam_policies.md) 添加到 EC2 实例关联角色。
 
 ### 基于 Assumed Role 认证鉴权
 
 #### 创建 IAM 角色并添加策略
 
-您可以根据需要访问的 AWS 资源选择创建一个或多个 IAM 角色。具体操作请参见 AWS 官网文档 [Creating IAM roles](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_create.html)。然后，把声明了访问特定 AWS 资源的 [IAM 策略](../reference/aws_iam_policies.md) 添加到您所创建的 IAM 角色。
+您可以根据需要访问的 AWS 资源选择创建一个或多个 IAM 角色。具体操作请参见 AWS 官网文档 [Creating IAM roles](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_create.html)。然后，把声明了访问特定 AWS 资源的 [IAM 策略](../sql-reference/aws_iam_policies.md) 添加到您所创建的 IAM 角色。
 
 这里假设您的操作场景需要 StarRocks 集群访问 AWS S3 和 AWS Glue。在这种情况下，您可以选择创建一个 IAM 角色（如 `s3_assumed_role`），然后把赋权访问 AWS S3 的策略和赋权访问 AWS Glue 的策略都添加到该角色。您也可以选择创建两个不同的 IAM 角色（如 `s3_assumed_role` 和 `glue_assumed_role`），然后把这些不同的策略分别添加到这两个角色（即，把赋权访问 AWS S3 的策略添加到 `s3_assumed_role`， 把赋权访问 AWS Glue 的策略添加到 `glue_assumed_role`）。
 
@@ -116,7 +116,7 @@ StarRocks 集群的 EC2 实例关联角色通过承担您所创建和配置的 I
 
 创建一个 IAM 用户。具体操作请参见 AWS 官网文档 [Creating an IAM user in your AWS account](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_users_create.html)。
 
-然后，把声明了访问特定 AWS 资源的 [IAM 策略](../reference/aws_iam_policies.md) 添加到创建好的 IAM 用户。
+然后，把声明了访问特定 AWS 资源的 [IAM 策略](../sql-reference/aws_iam_policies.md) 添加到创建好的 IAM 用户。
 
 ## 原理图
 
@@ -346,7 +346,7 @@ PROPERTIES
 
 ### 数据导入
 
-您可以从 AWS S3 导入数据。 以下示例将存储在 `s3a://test-bucket/test_brokerload_ingestion` 路径下的所有 Parquet 格式数据文件都导入到了现有数据库 `test_s3_db` 中一个名为 `test_ingestion_2` 的表中。有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+您可以从 AWS S3 导入数据。 以下示例将存储在 `s3a://test-bucket/test_brokerload_ingestion` 路径下的所有 Parquet 格式数据文件都导入到了现有数据库 `test_s3_db` 中一个名为 `test_ingestion_2` 的表中。有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 #### 基于 Instance Profile 鉴权认证
 
diff --git a/docs/zh/integrations/authenticate_to_azure_storage.md b/docs/zh/integrations/authenticate_to_azure_storage.md
index e8447334989c84..106b91a828da33 100644
--- a/docs/zh/integrations/authenticate_to_azure_storage.md
+++ b/docs/zh/integrations/authenticate_to_azure_storage.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: Microsoft Azure Storage
 description: "本文介绍如何认证 Azure 资源"
 ---
@@ -19,7 +19,7 @@ StarRocks 支持通过以下类型的 Azure 存储账号来访问 Azure Storage
 - Azure Data Lake Storage Gen1
 - Azure Data Lake Storage Gen2
 
-本文档以 Hive catalog、文件外部表和 Broker Load 为例，介绍 StarRocks 在各应用场景下如何通过不同类型的存储账号来访问 Azure Storage。有关下面示例中出现的参数详解，参见 [Hive catalog](../data_source/catalog/hive_catalog.md)、[文件外部表](../data_source/file_external_table.md)和 [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+本文档以 Hive catalog、文件外部表和 Broker Load 为例，介绍 StarRocks 在各应用场景下如何通过不同类型的存储账号来访问 Azure Storage。有关下面示例中出现的参数详解，参见 [Hive catalog](../data_source/catalog/hive_catalog.md)、[文件外部表](../data_source/file_external_table.md)和 [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 ## Blob Storage
 
@@ -39,7 +39,7 @@ StarRocks 支持通过以下认证方式来访问 Blob Storage：
 
 #### External Catalog
 
-在 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) 语句中，按如下配置 `azure.blob.storage_account` 和 `azure.blob.shared_key`：
+在 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) 语句中，按如下配置 `azure.blob.storage_account` 和 `azure.blob.shared_key`：
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_azure
@@ -54,7 +54,7 @@ PROPERTIES
 
 #### 文件外部表
 
-在 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) 语句中，按如下配置 `azure.blob.storage_account`、`azure.blob.shared_key` 和文件路径 (`path`)：
+在 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) 语句中，按如下配置 `azure.blob.storage_account`、`azure.blob.shared_key` 和文件路径 (`path`)：
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_azure
@@ -74,7 +74,7 @@ PROPERTIES
 
 #### Broker Load
 
-在 [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 语句中，按如下配置  `azure.blob.storage_account`、`azure.blob.shared_key` 和文件路径 (`DATA INFILE`)：
+在 [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 语句中，按如下配置  `azure.blob.storage_account`、`azure.blob.shared_key` 和文件路径 (`DATA INFILE`)：
 
 ```SQL
 LOAD LABEL test_db.label000
@@ -94,7 +94,7 @@ WITH BROKER
 
 #### External Catalog
 
-在 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) 语句中，按如下配置 `azure.blob.storage_account`、`azure.blob.container` 和 `azure.blob.sas_token`：
+在 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) 语句中，按如下配置 `azure.blob.storage_account`、`azure.blob.container` 和 `azure.blob.sas_token`：
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_azure
@@ -110,7 +110,7 @@ PROPERTIES
 
 #### 文件外部表
 
-在 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) 语句中，按如下配置 `azure.blob.storage_account`、`azure.blob.container`、`azure.blob.sas_token` 和文件路径 (`path`)：
+在 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) 语句中，按如下配置 `azure.blob.storage_account`、`azure.blob.container`、`azure.blob.sas_token` 和文件路径 (`path`)：
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_azure
@@ -131,7 +131,7 @@ PROPERTIES
 
 #### Broker load
 
-在 [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 语句中，按如下配置 `azure.blob.storage_account`、`azure.blob.container`、`azure.blob.sas_token` 和文件路径 (`DATA INFILE`)：
+在 [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 语句中，按如下配置 `azure.blob.storage_account`、`azure.blob.container`、`azure.blob.sas_token` 和文件路径 (`DATA INFILE`)：
 
 ```SQL
 LOAD LABEL test_db.label000
@@ -163,7 +163,7 @@ StarRocks 支持通过以下认证方式来访问 Data Lake Storage Gen1：
 
 #### External Catalog
 
-在 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) 语句中，按如下配置 `azure.adls1.use_managed_service_identity`：
+在 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) 语句中，按如下配置 `azure.adls1.use_managed_service_identity`：
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_azure
@@ -177,7 +177,7 @@ PROPERTIES
 
 #### 文件外部表
 
-在 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) 语句中，按如下配置 `azure.adls1.use_managed_service_identity` 和文件路径 (`path`)：
+在 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) 语句中，按如下配置 `azure.adls1.use_managed_service_identity` 和文件路径 (`path`)：
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_azure
@@ -196,7 +196,7 @@ PROPERTIES
 
 #### Broker Load
 
-在 [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 语句中，按如下配置 `azure.adls1.use_managed_service_identity` 和文件路径 (`DATA INFILE`)：
+在 [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 语句中，按如下配置 `azure.adls1.use_managed_service_identity` 和文件路径 (`DATA INFILE`)：
 
 ```SQL
 LOAD LABEL test_db.label000
@@ -215,7 +215,7 @@ WITH BROKER
 
 #### External Catalog
 
-在 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) 语句中，按如下配置 `azure.adls1.oauth2_client_id`、`azure.adls1.oauth2_credential` 和 `azure.adls1.oauth2_endpoint`：
+在 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) 语句中，按如下配置 `azure.adls1.oauth2_client_id`、`azure.adls1.oauth2_credential` 和 `azure.adls1.oauth2_endpoint`：
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_azure
@@ -231,7 +231,7 @@ PROPERTIES
 
 #### 文件外部表
 
-在 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) 语句中，按如下配置 `azure.adls1.oauth2_client_id`、`azure.adls1.oauth2_credential`、`azure.adls1.oauth2_endpoint` 和文件路径 (`path`)：
+在 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) 语句中，按如下配置 `azure.adls1.oauth2_client_id`、`azure.adls1.oauth2_credential`、`azure.adls1.oauth2_endpoint` 和文件路径 (`path`)：
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_azure
@@ -252,7 +252,7 @@ PROPERTIES
 
 #### Broker Load
 
-在 [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 语句中，按如下配置 `azure.adls1.oauth2_client_id`、`azure.adls1.oauth2_credential`、`azure.adls1.oauth2_endpoint` 和文件路径 (`DATA INFILE`)：
+在 [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 语句中，按如下配置 `azure.adls1.oauth2_client_id`、`azure.adls1.oauth2_credential`、`azure.adls1.oauth2_endpoint` 和文件路径 (`DATA INFILE`)：
 
 ```SQL
 LOAD LABEL test_db.label000
@@ -294,7 +294,7 @@ StarRocks 支持通过以下认证方式来访问 Data Lake Storage Gen2：
 
 #### External Catalog
 
-在 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) 语句中，按如下配置 `azure.adls2.oauth2_use_managed_identity`、`azure.adls2.oauth2_tenant_id` 和 `azure.adls2.oauth2_client_id`：
+在 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) 语句中，按如下配置 `azure.adls2.oauth2_use_managed_identity`、`azure.adls2.oauth2_tenant_id` 和 `azure.adls2.oauth2_client_id`：
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_azure
@@ -310,7 +310,7 @@ PROPERTIES
 
 #### 文件外部表
 
-在 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) 语句中，按如下配置 `azure.adls2.oauth2_use_managed_identity`、`azure.adls2.oauth2_tenant_id`、`azure.adls2.oauth2_client_id` 和文件路径 (`path`)：
+在 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) 语句中，按如下配置 `azure.adls2.oauth2_use_managed_identity`、`azure.adls2.oauth2_tenant_id`、`azure.adls2.oauth2_client_id` 和文件路径 (`path`)：
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_azure
@@ -331,7 +331,7 @@ PROPERTIES
 
 #### Broker Load
 
-在 [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 语句中，按如下配置 `azure.adls2.oauth2_use_managed_identity`、`azure.adls2.oauth2_tenant_id`、`azure.adls2.oauth2_client_id` 和文件路径 (`DATA INFILE`)：
+在 [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 语句中，按如下配置 `azure.adls2.oauth2_use_managed_identity`、`azure.adls2.oauth2_tenant_id`、`azure.adls2.oauth2_client_id` 和文件路径 (`DATA INFILE`)：
 
 ```SQL
 LOAD LABEL test_db.label000
@@ -352,7 +352,7 @@ WITH BROKER
 
 #### External Catalog
 
-在 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) 语句中，按如下配置 `azure.adls2.storage_account` 和 `azure.adls2.shared_key`：
+在 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) 语句中，按如下配置 `azure.adls2.storage_account` 和 `azure.adls2.shared_key`：
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_azure
@@ -367,7 +367,7 @@ PROPERTIES
 
 #### 文件外部表
 
-在 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) 语句中，按如下配置 `azure.adls2.storage_account`、`azure.adls2.shared_key` 和文件路径 (`path`)：
+在 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) 语句中，按如下配置 `azure.adls2.storage_account`、`azure.adls2.shared_key` 和文件路径 (`path`)：
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_azure
@@ -387,7 +387,7 @@ PROPERTIES
 
 #### Broker Load
 
-在 [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 语句中，按如下配置 `azure.adls2.storage_account`、`azure.adls2.shared_key` 和文件路径 (`DATA INFILE`)：
+在 [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 语句中，按如下配置 `azure.adls2.storage_account`、`azure.adls2.shared_key` 和文件路径 (`DATA INFILE`)：
 
 ```SQL
 LOAD LABEL test_db.label000
@@ -409,7 +409,7 @@ WITH BROKER
 
 #### External Catalog
 
-在 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) 语句中，按如下配置 `azure.adls2.oauth2_client_id`、`azure.adls2.oauth2_client_secret` 和 `azure.adls2.oauth2_client_endpoint`：
+在 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) 语句中，按如下配置 `azure.adls2.oauth2_client_id`、`azure.adls2.oauth2_client_secret` 和 `azure.adls2.oauth2_client_endpoint`：
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_azure
@@ -425,7 +425,7 @@ PROPERTIES
 
 #### 文件外部表
 
-在 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) 语句中，按如下配置 `azure.adls2.oauth2_client_id`、`azure.adls2.oauth2_client_secret`、`azure.adls2.oauth2_client_endpoint` 和文件路径 (`path`)：
+在 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) 语句中，按如下配置 `azure.adls2.oauth2_client_id`、`azure.adls2.oauth2_client_secret`、`azure.adls2.oauth2_client_endpoint` 和文件路径 (`path`)：
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_azure
@@ -446,7 +446,7 @@ PROPERTIES
 
 #### Broker Load
 
-在 [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 语句中，按如下配置 `azure.adls2.oauth2_client_id`、`azure.adls2.oauth2_client_secret`、`azure.adls2.oauth2_client_endpoint` 和文件路径 (`DATA INFILE`)：
+在 [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 语句中，按如下配置 `azure.adls2.oauth2_client_id`、`azure.adls2.oauth2_client_secret`、`azure.adls2.oauth2_client_endpoint` 和文件路径 (`DATA INFILE`)：
 
 ```SQL
 LOAD LABEL test_db.label000
diff --git a/docs/zh/integrations/authenticate_to_gcs.md b/docs/zh/integrations/authenticate_to_gcs.md
index 9206b2abb8dbec..048c6ae4a2b0d1 100644
--- a/docs/zh/integrations/authenticate_to_gcs.md
+++ b/docs/zh/integrations/authenticate_to_gcs.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: Google Cloud Storage (GCS)
 description: "本文介绍如何认证 GCS 资源"
 ---
@@ -31,7 +31,7 @@ StarRocks 支持在以下场景中集成 GCS：
 - 查询 GCS 中的 Parquet 或 ORC 格式的数据文件。
 - 查询 GCS 中的 [Hive](../data_source/catalog/hive_catalog.md)、[Iceberg](../data_source/catalog/iceberg_catalog.md)、[Hudi](../data_source/catalog/hudi_catalog.md)、或 [Delta Lake](../data_source/catalog/deltalake_catalog.md) 表。
 
-本文档以 [Hive catalog](../data_source/catalog/hive_catalog.md)、[文件外部表](../data_source/file_external_table.md) 和 [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 为例，介绍 StarRocks 在各应用场景下如何集成 GCS。有关下面示例中出现的 `StorageCredentialParams` 详解，参见本文档“[参数配置](../integrations/authenticate_to_gcs.md#参数配置)”小节。
+本文档以 [Hive catalog](../data_source/catalog/hive_catalog.md)、[文件外部表](../data_source/file_external_table.md) 和 [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 为例，介绍 StarRocks 在各应用场景下如何集成 GCS。有关下面示例中出现的 `StorageCredentialParams` 详解，参见本文档“[参数配置](../integrations/authenticate_to_gcs.md#参数配置)”小节。
 
 > **说明**
 >
@@ -39,7 +39,7 @@ StarRocks 支持在以下场景中集成 GCS：
 
 ### External Catalog
 
-通过 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md) 语句创建一个 Hive Catalog `hive_catalog_gcs`，用以查询 GCS 中的数据文件：
+通过 [CREATE EXTERNAL CATALOG](../sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md) 语句创建一个 Hive Catalog `hive_catalog_gcs`，用以查询 GCS 中的数据文件：
 
 ```SQL
 CREATE EXTERNAL CATALOG hive_catalog_gcs
@@ -53,7 +53,7 @@ PROPERTIES
 
 ### 文件外部表
 
-通过 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) 语句创建一个文件外部表 `external_table_gcs`，用以查询 GCS 中的数据文件 `test_file_external_tbl`（GCS 未配置元数据服务）：
+通过 [CREATE EXTERNAL TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) 语句创建一个文件外部表 `external_table_gcs`，用以查询 GCS 中的数据文件 `test_file_external_tbl`（GCS 未配置元数据服务）：
 
 ```SQL
 CREATE EXTERNAL TABLE external_table_gcs
@@ -72,7 +72,7 @@ PROPERTIES
 
 ### Broker load
 
-通过 [LOAD LABEL](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 语句创建一个 Broker Load 作业，作业标签为 `test_db.label000`，用以把 GCS 中的数据批量导入 StarRocks 表 `target_table`：
+通过 [LOAD LABEL](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 语句创建一个 Broker Load 作业，作业标签为 `test_db.label000`，用以把 GCS 中的数据批量导入 StarRocks 表 `target_table`：
 
 ```SQL
 LOAD LABEL test_db.label000
diff --git a/docs/zh/integrations/batch/Spark-connector-starrocks.mdx b/docs/zh/integrations/batch/Spark-connector-starrocks.mdx
index 7ab835f47837b9..41071778ddf638 100644
--- a/docs/zh/integrations/batch/Spark-connector-starrocks.mdx
+++ b/docs/zh/integrations/batch/Spark-connector-starrocks.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_position: 2
 sidebar_label: StarRocks Spark Connector
 description: "借助 Spark DataFrames 或 Spark SQL 导入数据"
diff --git a/docs/zh/integrations/batch/SparkLoad.mdx b/docs/zh/integrations/batch/SparkLoad.mdx
index 146fab0ebd7fcb..20c2c508f51bc4 100644
--- a/docs/zh/integrations/batch/SparkLoad.mdx
+++ b/docs/zh/integrations/batch/SparkLoad.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_position: 2
 sidebar_label: Apache Spark Load
 description: "通过 Spark Load 批量导入数据"
diff --git a/docs/zh/integrations/data_lakes.mdx b/docs/zh/integrations/data_lakes.mdx
index 23ce0e67d4252c..331cda45ed761a 100644
--- a/docs/zh/integrations/data_lakes.mdx
+++ b/docs/zh/integrations/data_lakes.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 import DataLakeIntro from '../_assets/commonMarkdown/datalakeIntro.md'
 
diff --git a/docs/zh/integrations/hive_bitmap_udf.md b/docs/zh/integrations/hive_bitmap_udf.md
deleted file mode 100644
index a5bb19a8f95c04..00000000000000
--- a/docs/zh/integrations/hive_bitmap_udf.md
+++ /dev/null
@@ -1,213 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# Hive Bitmap UDF
-
-Hive Bitmap UDF 提供了可以直接在 Hive 里使用的 UDF，可用于生成 Bitmap 和执行 Bitmap 运算。
-
-UDF 定义的 Bitmap 格式与 StarRocks 里格式一致，可直接用于导入导出。
-
-适用场景:
-
-- 原始数据量比较大，直接导入 StarRocks 计算会对 StarRocks 集群产生较大压力。所以希望在 Hive 里计算完生成 Bitmap 后，再导入 StarRocks。
-- 将 StarRocks 里生成的 Bitmap，导出到 Hive，方便其它系统使用。
-
-导入导出格式:
-
-- 3.1 及以上版本支持 String，Base64，和 Binary 三种格式导入导出。
-- 2.5 和 3.0 版本只支持 String 和 Base64 两种格式导入导出。
-
-## 支持生成的 Hive Bitmap UDF 函数
-
-- com.starrocks.hive.udf.UDAFBitmapAgg
-
-  将一列中的多行非 NULL 数值合并成一行 BITMAP 值，等同于 StarRocks 的内置聚合函数 [bitmap_agg](../sql-reference/sql-functions/bitmap-functions/bitmap_agg.md)。
-
-- com.starrocks.hive.udf.UDAFBitmapUnion
-
-  输入一组 Bitmap 值，求这一组 Bitmap 值的并集，等同于 StarRocks 的内置聚合函数 [bitmap_union](../sql-reference/sql-functions/bitmap-functions/bitmap_union.md)。
-
-- com.starrocks.hive.udf.UDFBase64ToBitmap
-
-  将 Base64 编码的字符串转化为 Bitmap，等同于 StarRocks 的内置函数 [base64_to_bitmap](../sql-reference/sql-functions/bitmap-functions/base64_to_bitmap.md)。
-
-- com.starrocks.hive.udf.UDFBitmapAnd
-
-  计算两个 Bitmap 的交集，等同于 StarRocks 的内置函数 [bitmap_and](../sql-reference/sql-functions/bitmap-functions/bitmap_and.md)。
-
-- com.starrocks.hive.udf.UDFBitmapCount
-
-  统计 Bitmap 中值的个数，等同于 StarRocks 的内置函数 [bitmap_count](../sql-reference/sql-functions/bitmap-functions/bitmap_count.md)。
-
-- com.starrocks.hive.udf.UDFBitmapFromString
-
-  将一个逗号分隔的字符串转化为一个 Bitmap，等同于 StarRocks 的内置函数 [bitmap_from_string](../sql-reference/sql-functions/bitmap-functions/bitmap_from_string.md)。
-
-- com.starrocks.hive.udf.UDFBitmapOr
-
-  计算两个 Bitmap 的并集，等同于 StarRocks 的内置函数 [bitmap_or](../sql-reference/sql-functions/bitmap-functions/bitmap_or.md)。
-
-- com.starrocks.hive.udf.UDFBitmapToBase64
-
-  将 Bitmap 转换为 Base64 字符串，等同于 StarRocks 的内置函数 [bitmap_to_base64](../sql-reference/sql-functions/bitmap-functions/bitmap_to_base64.md)。
-
-- com.starrocks.hive.udf.UDFBitmapToString
-
-  将 Bitmap 转换为逗号分隔的字符串，等同于 StarRocks 的内置函数 [bitmap_to_string](../sql-reference/sql-functions/bitmap-functions/bitmap_to_string.md)。
-
-- com.starrocks.hive.udf.UDFBitmapXor
-
-  计算两个 Bitmap 中不重复元素所构成的集合，等同于 StarRocks 的内置函数 [bitmap_xor](../sql-reference/sql-functions/bitmap-functions/bitmap_xor.md)。
-
-## 使用方法
-
-1. 在 FE 上编译生成 Hive UDF。
-
-   ```bash
-   ./build.sh --hive-udf
-   ```
-
-   会在 `fe/hive-udf/` 目录下生成一个 JAR 包 `hive-udf-1.0.0.jar`。
-
-2. 将 JAR 包上传到 HDFS。
-
-   ```bash
-   hadoop  fs -put -f ./hive-udf-1.0.0.jar hdfs://<hdfs_ip>:<hdfs_port>/hive-udf-1.0.0.jar
-   ```
-
-3. Hive 里加载 JAR 包。
-
-   ```bash
-   hive> add jar hdfs://<hdfs_ip>:<hdfs_port>/hive-udf-1.0.0.jar;
-   ```
-
-4. 加载 UDF 函数。
-
-   ```sql
-   hive> create temporary function bitmap_agg as 'com.starrocks.hive.udf.UDAFBitmapAgg';
-   hive> create temporary function bitmap_union as 'com.starrocks.hive.udf.UDAFBitmapUnion';
-   hive> create temporary function base64_to_bitmap as 'com.starrocks.hive.udf.UDFBase64ToBitmap';
-   hive> create temporary function bitmap_and as 'com.starrocks.hive.udf.UDFBitmapAnd';
-   hive> create temporary function bitmap_count as 'com.starrocks.hive.udf.UDFBitmapCount';
-   hive> create temporary function bitmap_from_string as 'com.starrocks.hive.udf.UDFBitmapFromString';
-   hive> create temporary function bitmap_or as 'com.starrocks.hive.udf.UDFBitmapOr';
-   hive> create temporary function bitmap_to_base64 as 'com.starrocks.hive.udf.UDFBitmapToBase64';
-   hive> create temporary function bitmap_to_string as 'com.starrocks.hive.udf.UDFBitmapToString';
-   hive> create temporary function bitmap_xor as 'com.starrocks.hive.udf.UDFBitmapXor';
-   ```
-
-## 使用示例
-
-### 在 Hive 里生成 Bitmap 并通过 Binary 格式导入到 StarRocks
-
-1. 创建 Hive 源数据表。
-
-    ```sql
-    hive> create table t_src(c1 bigint, c2 bigint) stored as parquet;
-    
-    hive> insert into t_src values (1,1), (1,2), (1,3), (2,4), (2,5);
-    
-    hive> select * from t_src;
-    1       1
-    1       2
-    1       3
-    2       4
-    2       5
-    ```
-
-2. 创建 Hive Bitmap 表。
-
-    ```sql
-    hive> create table t_bitmap(c1 bigint, c2 binary) stored as parquet;
-    ```
-
-    Hive 通过 UDFBitmapAgg 生成 Bitmap，并写入 Bitmap 表。
-
-    ```sql
-    hive> insert into t_bitmap select c1, bitmap_agg(c2) from t_src group by c1;
-    ```
-
-3. 创建 StarRocks Bitmap 表。
-
-    ```sql
-    mysql> create table t1(c1 int, c2 bitmap bitmap_union) aggregate key(c1)  distributed by hash(c1);
-    ```
-
-4. 通过不同方式导入到 StarRocks。
-
-   - 通过 [files](../sql-reference/sql-functions/table-functions/files.md) 函数导入。
-
-    ```sql
-    mysql> insert into t1 select c1, bitmap_from_binary(c2) from files (
-        "path" = "hdfs://<hdfs_ip>:<hdfs_port>/<hdfs_db>/t_bitmap/*",
-        "format"="parquet",
-        "compression" = "uncompressed"
-        );
-    ```
-
-   - 通过 [Hive Catalog](../data_source/catalog/hive_catalog.md) 导入。
-
-    ```sql
-    mysql> insert into t1 select c1, bitmap_from_binary(c2) from hive_catalog_hms.xxx_db.t_bitmap;
-    ```
-
-5. 查看结果。
-
-    ```plain
-    mysql> select c1, bitmap_to_string(c2) from t1;                                                                                                                                                                                                                                   
-    +------+----------------------+                                                                                                                                                                                                                                                   
-    | c1   | bitmap_to_string(c2) |
-    +------+----------------------+
-    |    1 | 1,2,3                |
-    |    2 | 4,5                  |
-    +------+----------------------+
-    ```
-
-### 将 StarRocks 里的 Bitmap 导出到 Hive
-
-1. 在 StarRocks 里创建 Bitmap 表，并写入数据。
-
-    ```sql
-    mysql> create table t1(c1 int, c2 bitmap bitmap_union) aggregate key(c1) buckets 3 distributed by hash(c1);
-    
-    mysql> select c1, bitmap_to_string(c2) from t1;                                                                                                                                                                                                                                   
-    +------+----------------------+                                                                                                                                                                                                                                                   
-    | c1   | bitmap_to_string(c2) |
-    +------+----------------------+
-    |    1 | 1,2,3                |
-    |    2 | 4,5                  |
-    +------+----------------------+
-    ```
-
-2. 在 Hive 里创建 Bitmap 表。
-
-    ```sql
-    hive> create table t_bitmap(c1 bigint, c2 binary) stored as parquet;
-    ```
-
-3. 通过不同方式导出。
-
-   - 通过 INSERT INTO FILES 导出（binary 格式）。
-
-    ```sql
-    mysql> insert into files (
-        "path" = "hdfs://<hdfs_ip>:<hdfs_port>/<hdfs_db>/t_bitmap/",
-        "format"="parquet",
-        "compression" = "uncompressed"
-    ) select c1, bitmap_to_binary(c2) as c2 from t1;
-    ```
-
-   - 通过 [Hive Catalog](../data_source/catalog/hive_catalog.md) 方式导出（binary 格式）。
-
-    ```sql
-    mysql> insert into hive_catalog_hms.<hdfs_db>.t_bitmap select c1, bitmap_to_binary(c2) from t1;
-    ```
-
-4. 在 Hive 里查看结果。
-
-    ```sql
-    hive> select c1, bitmap_to_string(c2) from t_bitmap;
-    1       1,2,3
-    2       4,5
-    ```
diff --git a/docs/zh/integrations/integrations.mdx b/docs/zh/integrations/integrations.mdx
index 11f9a983821238..006e70d62bbf51 100644
--- a/docs/zh/integrations/integrations.mdx
+++ b/docs/zh/integrations/integrations.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 外部系统集成
diff --git a/docs/zh/integrations/loading_tools/CloudCanal.md b/docs/zh/integrations/loading_tools/CloudCanal.md
index 241665381d07dc..b6ad82d314c085 100644
--- a/docs/zh/integrations/loading_tools/CloudCanal.md
+++ b/docs/zh/integrations/loading_tools/CloudCanal.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 CloudCanal 导入
diff --git a/docs/zh/integrations/loading_tools/DataX-starrocks-writer.md b/docs/zh/integrations/loading_tools/DataX-starrocks-writer.md
index 07f60e47ab638b..8c7d0c554bd39a 100644
--- a/docs/zh/integrations/loading_tools/DataX-starrocks-writer.md
+++ b/docs/zh/integrations/loading_tools/DataX-starrocks-writer.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 DataX 导入
@@ -104,7 +104,7 @@ tar -xzvf starrockswriter.tar.gz
 | maxBatchRows  | 单次 Stream Load 导入的最大行数。导入大量数据时，StarRocks Writer 将根据 `maxBatchRows` 或 `maxBatchSize` 将数据分为多个 Stream Load 作业分批导入。 | 否       | 500000     |
 | maxBatchSize  | 单次 Stream Load 导入的最大字节数，单位为 Byte。导入大量数据时，StarRocks Writer 将根据 `maxBatchRows` 或 `maxBatchSize` 将数据分为多个 Stream Load 作业分批导入。 | 否       | 104857600  |
 | flushInterval | 上一次 Stream Load 结束至下一次开始的时间间隔，单位为 ms。   | 否       | 300000     |
-| loadProps     | Stream Load 的导入参数，详情参考 [STREAM LOAD](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)。 | 否       | 无         |
+| loadProps     | Stream Load 的导入参数，详情参考 [STREAM LOAD](../../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。 | 否       | 无         |
 
 > 注意
 >
@@ -179,7 +179,7 @@ python datax/bin/datax.py --jvm="-Xms6G -Xmx6G" --loglevel=debug datax/job/job.j
 
 由于 DataX 导入是基于封装的 Stream Load 实现，您可以在 `datax/log/$date/` 目录下搜索对应的导入作业日志，日志文件名字中包含导入使用的 JSON 文件名和任务启动时间（小时、分钟、秒），例如：**t_datax_job_job_json-20_52_19.196.log**。
 
-- 如果日志中有 "http://fe_ip:fe_http_port/api/db_name/tbl_name/_stream_load" 记录生成，则表示 Stream Load 作业已成功触发。作业成功触发后，您可参考 [Stream Load 返回值](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md#返回值) 查看任务情况。
+- 如果日志中有 "http://fe_ip:fe_http_port/api/db_name/tbl_name/_stream_load" 记录生成，则表示 Stream Load 作业已成功触发。作业成功触发后，您可参考 [Stream Load 返回值](../../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md#返回值) 查看任务情况。
 - 日志中如果没有上述信息，请根据报错信息排查问题，或者在 [DataX 社区问题](https://github.com/alibaba/DataX/issues)中寻找解决方案。
 
 > 注意
diff --git a/docs/zh/integrations/loading_tools/SMT.md b/docs/zh/integrations/loading_tools/SMT.md
index 187f2f7e5fa389..4165afcf1e52a5 100644
--- a/docs/zh/integrations/loading_tools/SMT.md
+++ b/docs/zh/integrations/loading_tools/SMT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # StarRocks migration tool（SMT）
diff --git a/docs/zh/integrations/loading_tools/loading_tools_integration.mdx b/docs/zh/integrations/loading_tools/loading_tools_integration.mdx
index 2104a7ccebc283..64964fb8a1233c 100644
--- a/docs/zh/integrations/loading_tools/loading_tools_integration.mdx
+++ b/docs/zh/integrations/loading_tools/loading_tools_integration.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 # 
 
diff --git a/docs/zh/integrations/other_integrations/datadog_support.md b/docs/zh/integrations/other_integrations/datadog_support.md
index bd5fc8ec1be28d..4bf7a627e59ca3 100644
--- a/docs/zh/integrations/other_integrations/datadog_support.md
+++ b/docs/zh/integrations/other_integrations/datadog_support.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: Datadog
 ---
 
diff --git a/docs/zh/integrations/streaming.mdx b/docs/zh/integrations/streaming.mdx
index 466056b3d3358e..6d889a3f204b34 100644
--- a/docs/zh/integrations/streaming.mdx
+++ b/docs/zh/integrations/streaming.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Streaming data
diff --git a/docs/zh/integrations/streaming/apache_kafka.mdx b/docs/zh/integrations/streaming/apache_kafka.mdx
index 100d80a8845bf0..2e9af4a5bd8c97 100644
--- a/docs/zh/integrations/streaming/apache_kafka.mdx
+++ b/docs/zh/integrations/streaming/apache_kafka.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: Apache Kafka
 description: "从 Apache Kafka 持续导入数据"
 title: Apache Kafka
diff --git a/docs/zh/integrations/streaming/flink.mdx b/docs/zh/integrations/streaming/flink.mdx
index e33e7b90c3a122..5aa10df4dc8447 100644
--- a/docs/zh/integrations/streaming/flink.mdx
+++ b/docs/zh/integrations/streaming/flink.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_position: 1
 sidebar_label: Apache Flink
 description: "从 Apache Flink 持续导入数据"
diff --git a/docs/zh/integrations/streaming/kafka/Kafka-connector-starrocks.mdx b/docs/zh/integrations/streaming/kafka/Kafka-connector-starrocks.mdx
index 671f516bba41f5..a2862d98f55e14 100644
--- a/docs/zh/integrations/streaming/kafka/Kafka-connector-starrocks.mdx
+++ b/docs/zh/integrations/streaming/kafka/Kafka-connector-starrocks.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_position: 2
 sidebar_label: Kafka connector
 description: "从 Apache Kafka 持续导入数据流"
diff --git a/docs/zh/integrations/streaming/kafka/RoutineLoad.mdx b/docs/zh/integrations/streaming/kafka/RoutineLoad.mdx
index 995ebc99b53061..6789d003a6fba9 100644
--- a/docs/zh/integrations/streaming/kafka/RoutineLoad.mdx
+++ b/docs/zh/integrations/streaming/kafka/RoutineLoad.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_position: 2
 sidebar_label: Routine Load
 description: "从 Apache Kafka 导入 CSV、JSON、或 Avro 格式的数据"
diff --git a/docs/zh/integrations/streaming/pipe.mdx b/docs/zh/integrations/streaming/pipe.mdx
index 492b86db70a5c1..f9f63415b86894 100644
--- a/docs/zh/integrations/streaming/pipe.mdx
+++ b/docs/zh/integrations/streaming/pipe.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Stream with StarRocks Pipe
diff --git a/docs/zh/integrations/streaming/pipe/hdfs.mdx b/docs/zh/integrations/streaming/pipe/hdfs.mdx
index a23d1ebf3cb0a6..c56dfaedc4947b 100644
--- a/docs/zh/integrations/streaming/pipe/hdfs.mdx
+++ b/docs/zh/integrations/streaming/pipe/hdfs.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_position: 2
 sidebar_label: HDFS
 description: "借助 Pipe 从 HDFS 导入数据"
diff --git a/docs/zh/integrations/streaming/pipe/s3.mdx b/docs/zh/integrations/streaming/pipe/s3.mdx
index 876c36c3d1b825..d27951ab7dd9db 100644
--- a/docs/zh/integrations/streaming/pipe/s3.mdx
+++ b/docs/zh/integrations/streaming/pipe/s3.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_position: 2
 sidebar_label: S3
 description: "借助 Pipe 从 S3 导入数据"
diff --git a/docs/zh/integrations/streaming/rising_wave.md b/docs/zh/integrations/streaming/rising_wave.md
index 8a2df4fc525022..44582020f316c2 100644
--- a/docs/zh/integrations/streaming/rising_wave.md
+++ b/docs/zh/integrations/streaming/rising_wave.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 从 RisingWave 持续导入
diff --git a/docs/zh/integrations/superset_support.md b/docs/zh/integrations/superset_support.md
index f4478925095aec..83fa3467dcc7cf 100644
--- a/docs/zh/integrations/superset_support.md
+++ b/docs/zh/integrations/superset_support.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 支持 Superset
diff --git a/docs/zh/introduction/Architecture.md b/docs/zh/introduction/Architecture.md
index 7becbbf5a83e63..cc9302a7052319 100644
--- a/docs/zh/introduction/Architecture.md
+++ b/docs/zh/introduction/Architecture.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: Chinese
+displayed_sidebar: docs
 ---
 
 # 架构
diff --git a/docs/zh/introduction/Features.md b/docs/zh/introduction/Features.md
index 294a2a14c85d9d..5b0b2428454a81 100644
--- a/docs/zh/introduction/Features.md
+++ b/docs/zh/introduction/Features.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 产品特性
diff --git a/docs/zh/introduction/StarRocks_intro.md b/docs/zh/introduction/StarRocks_intro.md
index eea37d2d1ad107..a8401ef0902f2c 100644
--- a/docs/zh/introduction/StarRocks_intro.md
+++ b/docs/zh/introduction/StarRocks_intro.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # StarRocks
diff --git a/docs/zh/introduction/introduction.mdx b/docs/zh/introduction/introduction.mdx
index d6021652ff3ae6..33230722251bc8 100644
--- a/docs/zh/introduction/introduction.mdx
+++ b/docs/zh/introduction/introduction.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 产品简介
diff --git a/docs/zh/introduction/what_is_starrocks.md b/docs/zh/introduction/what_is_starrocks.md
index 38a61a8b8ddbfd..1dd64923ad7924 100644
--- a/docs/zh/introduction/what_is_starrocks.md
+++ b/docs/zh/introduction/what_is_starrocks.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 什么是 StarRocks
diff --git a/docs/zh/loading/BrokerLoad.md b/docs/zh/loading/BrokerLoad.md
index 9f847528df48d0..753823950cf3df 100644
--- a/docs/zh/loading/BrokerLoad.md
+++ b/docs/zh/loading/BrokerLoad.md
@@ -1,12 +1,12 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 从 HDFS 或外部云存储系统导入数据
 
 StarRocks 提供基于 MySQL 协议的 Broker Load 导入方式，帮助您从 HDFS 或外部云存储系统导入大批量数据。
 
-Broker Load 是一种异步的导入方式。您提交导入作业以后，StarRocks 会异步地执行导入作业。您需要通过 [SHOW LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md) 语句或者 curl 命令来查看导入作业的结果。
+Broker Load 是一种异步的导入方式。您提交导入作业以后，StarRocks 会异步地执行导入作业。您需要通过 [SHOW LOAD](../sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md) 语句或者 curl 命令来查看导入作业的结果。
 
 Broker Load 支持单表导入 (Single-Table Load) 和多表导入 (Multi-Table Load)。您可以通过单次导入操作，把一个或多个数据文件导入单张或多张目标表。而且 Broker Load 能够保证单次导入事务的原子性，即单次导入的多个数据文件都成功或者都失败，而不会出现部分导入成功、部分导入失败的情况。
 
@@ -22,7 +22,7 @@ Broker Load 支持在导入过程中做数据转换、以及通过 UPSERT 和 DE
 
 自 v2.5 起，StarRocks 在执行 Broker Load 时不需要借助 Broker 即可访问外部存储系统，称为“无 Broker 的导入”。导入语句中也不再需要指定 `broker_name`，但继续保留 `WITH BROKER` 关键字。
 
-需要注意的是，无 Broker 的导入在数据源为 HDFS 的某些场景下会受限，例如，在多 HDFS 集群或者多 Kerberos 用户的场景。在这些场景下，可以继续采用有 Broker 的导入，需要确保至少部署了一组独立的 Broker。有关各种场景下如何指定认证方式和 HA 配置，参见 [HDFS](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md##hdfs)。
+需要注意的是，无 Broker 的导入在数据源为 HDFS 的某些场景下会受限，例如，在多 HDFS 集群或者多 Kerberos 用户的场景。在这些场景下，可以继续采用有 Broker 的导入，需要确保至少部署了一组独立的 Broker。有关各种场景下如何指定认证方式和 HA 配置，参见 [HDFS](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md##hdfs)。
 
 
 ## 支持的数据文件格式
@@ -74,7 +74,7 @@ Broker Load 支持从如下外部存储系统导入数据：
 
 ### 创建多表导入 (Multi-Table Load) 作业
 
-这里以 CSV 格式的数据为例，介绍如何导入多个数据文件至多张目标表。有关如何导入其他格式的数据、以及 Broker Load 的详细语法和参数说明，请参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+这里以 CSV 格式的数据为例，介绍如何导入多个数据文件至多张目标表。有关如何导入其他格式的数据、以及 Broker Load 的详细语法和参数说明，请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 注意在 StarRocks 中，部分文字是 SQL 语言的保留关键字，不能直接用于 SQL 语句。如果想在 SQL 语句中使用这些保留关键字，必须用反引号 (`) 包裹起来。参见[关键字](../sql-reference/sql-statements/keywords.md)。
 
@@ -159,7 +159,7 @@ PROPERTIES
 );
 ```
 
-以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#hdfs)。
+以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#hdfs)。
 
 从 3.1 版本起，StarRocks 支持使用 INSERT 语句和 TABLE 关键字直接从 HDFS 导入 Parquet 或 ORC 格式的数据文件，避免了需事先创建外部表的麻烦。参见 [通过 INSERT 语句导入数据 > 通过 TABLE 关键字直接导入外部数据文件](../loading/InsertInto.md#通过-insert-into-select-以及表函数-files-导入外部数据文件)。
 
@@ -190,7 +190,7 @@ WITH BROKER
 >
 > 由于 Broker Load 只支持通过 S3A 协议访问 AWS S3，因此当从 AWS S3 导入数据时，`DATA INFILE` 中传入的目标文件的 S3 URI，前缀必须将 `s3://` 修改为 `s3a://`。
 
-以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#aws-s3)。
+以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#aws-s3)。
 
 从 3.1 版本起，StarRocks 支持使用 INSERT 语句和 TABLE 关键字直接从 AWS S3 导入 Parquet 或 ORC 格式的数据文件，避免了需事先创建外部表的麻烦。参见 [通过 INSERT 语句导入数据 > 通过 TABLE 关键字直接导入外部数据文件](../loading/InsertInto.md#通过-insert-into-select-以及表函数-files-导入外部数据文件)。
 
@@ -221,7 +221,7 @@ WITH BROKER
 >
 > 由于 Broker Load 只支持通过 gs 协议访问 Google GCS，因此当从 Google GCS 导入数据时，必须确保文件路径传入的目标文件的 GCS URI 使用 `gs://` 为前缀。
 
-以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#google-gcs)。
+以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#google-gcs)。
 
 #### 从 阿里云 OSS 导入
 
@@ -246,7 +246,7 @@ WITH BROKER
 );
 ```
 
-以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#阿里云-oss)。
+以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#阿里云-oss)。
 
 #### 从腾讯云 COS 导入
 
@@ -271,7 +271,7 @@ WITH BROKER
 );
 ```
 
-以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#腾讯云-cos)。
+以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#腾讯云-cos)。
 
 #### 从华为云 OBS 导入
 
@@ -300,7 +300,7 @@ WITH BROKER
 >
 > 从华为云 OBS 导入数据时，需要先下载[依赖库](https://github.com/huaweicloud/obsa-hdfs/releases/download/v45/hadoop-huaweicloud-2.8.3-hw-45.jar)添加到 **$BROKER_HOME/lib/** 路径下并重启 Broker。
 
-以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#华为云-obs)。
+以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#华为云-obs)。
 
 #### 从其他兼容 S3 协议的对象存储导入
 
@@ -325,7 +325,7 @@ WITH BROKER
 );
 ```
 
-以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#其他兼容-s3-协议的对象存储)。
+以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#其他兼容-s3-协议的对象存储)。
 
 #### 从 Microsoft Azure Storage 导入
 
@@ -362,7 +362,7 @@ WITH BROKER
   >   - 如果使用 HTTP 协议进行访问，请使用 `abfs://` 作为前缀，例如，`abfs://<container>@<storage_account>.dfs.core.windows.net/<file_name>`。
   >   - 如果使用 HTTPS 协议进行访问，请使用 `abfss://` 作为前缀，例如，`abfss://<container>@<storage_account>.dfs.core.windows.net/<file_name>`。
 
-以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#microsoft-azure-storage)。
+以上示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#microsoft-azure-storage)。
 
 #### 查询数据
 
@@ -431,7 +431,7 @@ WITH BROKER
 )；
 ```
 
-以上两个示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#aws-s3)。
+以上两个示例中，`StorageCredentialParams` 代表一组认证参数，具体包含哪些参数，需要根据您所使用的认证方式来确定，详情请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#aws-s3)。
 
 ### 查看导入作业
 
@@ -439,7 +439,7 @@ Broker Load 支持通过 SHOW LOAD 语句和 curl 命令两种方式来查看导
 
 #### 使用 SHOW LOAD 语句
 
-请参见 [SHOW LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md)。
+请参见 [SHOW LOAD](../sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md)。
 
 #### 使用 curl 命令
 
@@ -482,7 +482,7 @@ curl --location-trusted -u <username>:<password> \
 
 ### 取消导入作业
 
-当导入作业状态不为 **CANCELLED** 或 **FINISHED** 时，可以通过 [CANCEL LOAD](../sql-reference/sql-statements/data-manipulation/CANCEL_LOAD.md) 语句来取消该导入作业。
+当导入作业状态不为 **CANCELLED** 或 **FINISHED** 时，可以通过 [CANCEL LOAD](../sql-reference/sql-statements/loading_unloading/CANCEL_LOAD.md) 语句来取消该导入作业。
 
 例如，可以通过以下语句，撤销 `db1` 数据库中标签为 `label1` 的导入作业：
 
@@ -518,7 +518,7 @@ WHERE LABEL = "label";
 
 StarRocks v2.4 及以前版本中，如果某一时间段内提交的 Broker Load 作业总数超过最大数量，则超出作业会按照各自的提交时间放到队列中排队等待调度。
 
-StarRocks v2.5 版本中，如果某一时间段内提交的 Broker Load 作业总数超过最大数量，则超出的作业会按照作业创建时指定的优先级被放到队列中排队等待调度。参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#opt_properties) 文档中的可选参数 `priority`。您可以使用 [ALTER LOAD](../sql-reference/sql-statements/data-manipulation/ALTER_LOAD.md) 语句修改处于 **QUEUEING** 状态或者 **LOADING** 状态的 Broker Load 作业的优先级。
+StarRocks v2.5 版本中，如果某一时间段内提交的 Broker Load 作业总数超过最大数量，则超出的作业会按照作业创建时指定的优先级被放到队列中排队等待调度。参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#opt_properties) 文档中的可选参数 `priority`。您可以使用 [ALTER LOAD](../sql-reference/sql-statements/loading_unloading/ALTER_LOAD.md) 语句修改处于 **QUEUEING** 状态或者 **LOADING** 状态的 Broker Load 作业的优先级。
 
 ## 常见问题
 
diff --git a/docs/zh/loading/Etl_in_loading.md b/docs/zh/loading/Etl_in_loading.md
index 20b6ba12628944..777893b32593c3 100644
--- a/docs/zh/loading/Etl_in_loading.md
+++ b/docs/zh/loading/Etl_in_loading.md
@@ -1,12 +1,12 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 导入过程中实现数据转换
 
 StarRocks 支持在导入数据的过程中实现数据转换。
 
-目前支持的导入方式有 [Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)、[Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 和 [Routine Load](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md)。暂不支持 [Spark Load](../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md) 导入方式。
+目前支持的导入方式有 [Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)、[Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 和 [Routine Load](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md)。暂不支持 [Spark Load](../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md) 导入方式。
 
 > **注意**
 >
@@ -147,7 +147,7 @@ curl --location-trusted -u <username>:<password> \
 >
 > `columns` 参数用于对数据文件中的列进行临时命名，从而映射到 StarRocks 表的列。
 
-有关详细的语法和参数介绍，请参见 [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)。
+有关详细的语法和参数介绍，请参见 [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。
 
 #### 从 HDFS 导入
 
@@ -169,7 +169,7 @@ WITH BROKER;
 >
 > `column_list` 参数用于对数据文件中的列进行临时命名，从而映射到 StarRocks 表的列。
 
-有关详细的语法和参数介绍，请参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+有关详细的语法和参数介绍，请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 #### 从 Kafka 导入
 
@@ -191,7 +191,7 @@ FROM KAFKA
 >
 > `COLUMNS` 参数用于对数据中的列进行临时命名，从而映射到 StarRocks 表的列。
 
-有关详细的语法和参数介绍，请参见 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md)。
+有关详细的语法和参数介绍，请参见 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md)。
 
 ### 查询数据
 
@@ -243,7 +243,7 @@ curl --location-trusted -u <username>:<password> \
     http://<fe_host>:<fe_http_port>/api/test_db/table1/_stream_load
 ```
 
-有关详细的语法和参数介绍，请参见 [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)。
+有关详细的语法和参数介绍，请参见 [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。
 
 #### 从 HDFS 导入
 
@@ -262,7 +262,7 @@ LOAD LABEL test_db.label2
 WITH BROKER;
 ```
 
-有关详细的语法和参数介绍，请参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+有关详细的语法和参数介绍，请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 #### 从 Kafka 导入
 
@@ -281,7 +281,7 @@ FROM KAFKA
 );
 ```
 
-有关详细的语法和参数介绍，请参见 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md)。
+有关详细的语法和参数介绍，请参见 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md)。
 
 ### 查询数据
 
@@ -336,7 +336,7 @@ curl --location-trusted -u <username>:<password> \
 >
 > - 不支持 `column_name = function(column_name)` 的形式，需要时可以重命名衍生列之前的列，比如为 `column_name = func(``tempcolumn_name``)`。
 
-有关详细的语法和参数介绍，请参见 [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)。
+有关详细的语法和参数介绍，请参见 [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。
 
 #### 从 HDFS 导入
 
@@ -359,7 +359,7 @@ WITH BROKER;
 >
 > 必须先通过 `column_list` 参数声明源数据文件中包含的所有列，然后再通过 SET 子句声明衍生列。如上述示例中，先通过 `column_list` 参数声明 `file2.csv` 文件中包含的仅有的一列临时命名为 `date`，然后再通过 SET 子句声明需要调用函数经过转化才能生成的衍生列：`year=year(date)`、`month=month(date)` 和 `day=day(date)`。
 
-有关详细的语法和参数介绍，请参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+有关详细的语法和参数介绍，请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 #### 从 Kafka 导入
 
@@ -381,7 +381,7 @@ FROM KAFKA
 >
 > 必须通过 `COLUMNS` 参数先声明源数据文件中包含的所有列，然后再声明衍生列。如上述示例中，`COLUMNS` 参数中先声明 `file2.csv` 文件中包含的仅有的一列临时命名为 `date`，然后再声明需要调用函数经过转化才能生成的衍生列：`year=year(date)`、`month=month(date)` 和 `day=day(date)`。
 
-有关详细的语法和参数介绍，请参见 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md)。
+有关详细的语法和参数介绍，请参见 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md)。
 
 ### 查询数据
 
@@ -439,7 +439,7 @@ WITH BROKER;
 >
 > 上述示例中，指定的文件路径中的分区字段 `date` 对应 `table1` 表中的 `event_date` 列，因此需要通过 SET 子句完成 `date` 到 `event_date` 的映射。如果指定的文件路径中的分区字段与其对应的 StarRocks 表中的列名称一样，则不需要通过 SET 子句来指定映射关系。
 
-有关详细的语法和参数介绍，请参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+有关详细的语法和参数介绍，请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 ### 查询数据
 
diff --git a/docs/zh/loading/Flink-connector-starrocks.md b/docs/zh/loading/Flink-connector-starrocks.md
index 08d9fd84a9bf51..5c34cc05ef3d99 100644
--- a/docs/zh/loading/Flink-connector-starrocks.md
+++ b/docs/zh/loading/Flink-connector-starrocks.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 从 Apache Flink® 持续导入
@@ -112,11 +112,11 @@ Flink connector JAR 文件的命名格式如下：
 | sink.wait-for-continue.timeout-ms | No       | 10000         | 此参数自 Flink connector 1.2.7 开始支持。等待 FE HTTP 100-continue 应答的超时时间。取值范围：[3000, 60000]。 |
 | sink.ignore.update-before         | No       | TRUE          | 此参数自 Flink connector 1.2.8 开始支持。将数据导入到主键表时，是否忽略来自 Flink 的 UPDATE_BEFORE 记录。如果将此参数设置为 false，则将该记录在主键表中视为 DELETE 操作。 |
 | sink.parallelism                  | No       | NONE          | 写入的并行度。仅适用于 Flink SQL。如果未设置， Flink planner 将决定并行度。**在多并行度的场景中，用户需要确保数据按正确顺序写入。** |
-| sink.properties.*                 | No       | NONE          | Stream Load 的参数，控制 Stream Load 导入行为。例如 参数 sink.properties.format 表示 Stream Load 所导入的数据格式，如 CSV 或者 JSON。全部参数和解释，请参见 [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)。 |
+| sink.properties.*                 | No       | NONE          | Stream Load 的参数，控制 Stream Load 导入行为。例如 参数 sink.properties.format 表示 Stream Load 所导入的数据格式，如 CSV 或者 JSON。全部参数和解释，请参见 [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。 |
 | sink.properties.format            | No       | csv           | Stream Load 导入时的数据格式。Flink connector 会将内存的数据转换为对应格式，然后通过 Stream Load 导入至 StarRocks。取值为 CSV 或者 JSON。 |
 | sink.properties.column_separator  | No       | \t            | CSV 数据的列分隔符。                                         |
 | sink.properties.row_delimiter     | No       | \n            | CSV 数据的行分隔符。                                         |
-| sink.properties.max_filter_ratio  | No       | 0             | 导入作业的最大容错率，即导入作业能够容忍的因数据质量不合格而过滤掉的数据行所占的最大比例。取值范围：0~1。默认值：0 。详细信息，请参见  [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)。 |
+| sink.properties.max_filter_ratio  | No       | 0             | 导入作业的最大容错率，即导入作业能够容忍的因数据质量不合格而过滤掉的数据行所占的最大比例。取值范围：0~1。默认值：0 。详细信息，请参见  [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。 |
 | sink.properties.partial_update      | 否      | `FALSE` | 是否使用部分更新。取值包括 `TRUE` 和 `FALSE`。默认值：`FALSE`。                                                                                                                                                                                             |
 | sink.properties.partial_update_mode | 否      | `row` | 指定部分更新的模式，取值包括 `row` 和 `column`。<ul><li>`row`（默认值），指定使用行模式执行部分更新，比较适用于较多列且小批量的实时更新场景。</li><li>`column`，指定使用列模式执行部分更新，比较适用于少数列并且大量行的批处理更新场景。在该场景，开启列模式，更新速度更快。例如，在一个包含 100 列的表中，每次更新 10 列（占比 10%）并更新所有行，则开启列模式，更新性能将提高 10 倍。</li></ul>  |
 
@@ -433,7 +433,7 @@ DISTRIBUTED BY HASH(id);
 
 快速上手教程可以参考[从 MySQL 到 StarRocks 的流式 ELT 管道](https://nightlies.apache.org/flink/flink-cdc-docs-stable/docs/get-started/quickstart/mysql-to-starrocks)。
 
-建议您使用 StarRocks v3.2.1 及以后的版本，以开启 [fast_schema_evolution](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md#设置-fast-schema-evolution)，来提高加减列的速度并降低资源使用。
+建议您使用 StarRocks v3.2.1 及以后的版本，以开启 [fast_schema_evolution](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md#设置-fast-schema-evolution)，来提高加减列的速度并降低资源使用。
 
 ## 最佳实践
 
diff --git a/docs/zh/loading/Flink_cdc_load.md b/docs/zh/loading/Flink_cdc_load.md
index 24cc6ab5b70f2c..fc17e9e18ddc7f 100644
--- a/docs/zh/loading/Flink_cdc_load.md
+++ b/docs/zh/loading/Flink_cdc_load.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 从 MySQL 实时同步
diff --git a/docs/zh/loading/InsertInto.md b/docs/zh/loading/InsertInto.md
index 8a94a980b42314..6cd7914627a034 100644
--- a/docs/zh/loading/InsertInto.md
+++ b/docs/zh/loading/InsertInto.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 通过 INSERT 语句导入数据
@@ -21,10 +21,10 @@ import InsertPrivNote from '../_assets/commonMarkdown/insertPrivNote.md'
 ## 注意事项
 
 - 您只能在 MySQL 客户端通过 `Ctrl` + `C` 按键强制取消同步 INSERT 导入任务。
-- 您可以通过 [SUBMIT TASK](../sql-reference/sql-statements/data-manipulation/SUBMIT_TASK.md) 创建异步 INSERT 导入任务。
+- 您可以通过 [SUBMIT TASK](../sql-reference/sql-statements/loading_unloading/ETL/SUBMIT_TASK.md) 创建异步 INSERT 导入任务。
 - 当前版本中，StarRocks 在执行 INSERT 语句时，如果有数据不符合目标表格式（例如字符串超长等情况），INSERT 操作默认执行失败。您可以通过设置会话变量 `enable_insert_strict` 为 `false` 以确保 INSERT 操作过滤不符合目标表格式的数据，并继续执行。
 - 频繁使用 INSERT 语句导入小批量数据会产生过多的数据版本，从而影响查询性能，因此不建议您频繁使用 INSERT 语句导入数据或将其作为生产环境的日常例行导入作业。如果您的业务场景需要流式导入或者小批量多次导入数据，建议使用 Apache Kafka® 作为数据源并通过 [Routine Load](../loading/RoutineLoad.md) 方式进行导入作业。
-- 执行 INSERT OVERWRITE 语句后，系统将为目标分区创建相应的临时分区，并将数据写入临时分区，最后使用临时分区[原子替换](../sql-reference/sql-statements/data-definition/ALTER_TABLE.md#使用临时分区替换原分区)目标分区来实现覆盖写入。其所有过程均在 Leader FE 节点执行。因此，如果 Leader FE 节点在覆盖写入过程中发生宕机，将会导致该次 INSERT OVERWRITE 导入失败，其过程中所创建的临时分区也会被删除。
+- 执行 INSERT OVERWRITE 语句后，系统将为目标分区创建相应的临时分区，并将数据写入临时分区，最后使用临时分区[原子替换](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md#使用临时分区替换原分区)目标分区来实现覆盖写入。其所有过程均在 Leader FE 节点执行。因此，如果 Leader FE 节点在覆盖写入过程中发生宕机，将会导致该次 INSERT OVERWRITE 导入失败，其过程中所创建的临时分区也会被删除。
 
 ## 准备工作
 
@@ -113,7 +113,7 @@ DISTRIBUTED BY HASH(user);
 
 ## 通过 INSERT INTO VALUES 语句导入数据
 
-您可以通过 INSERT INTO VALUES 语句向指定的表中直接导入数据。此导入方式中，多条数据用逗号（,）分隔。详细使用方式，参考 [SQL 参考 - INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md)。详细参数信息，参考 [INSERT 参数说明](../sql-reference/sql-statements/data-manipulation/INSERT.md#参数说明)。
+您可以通过 INSERT INTO VALUES 语句向指定的表中直接导入数据。此导入方式中，多条数据用逗号（,）分隔。详细使用方式，参考 [SQL 参考 - INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md)。详细参数信息，参考 [INSERT 参数说明](../sql-reference/sql-statements/loading_unloading/INSERT.md#参数说明)。
 
 > **注意**
 >
@@ -137,7 +137,7 @@ VALUES
 
 ## 通过 INSERT INTO SELECT 语句导入数据
 
-您可以通过 INSERT INTO SELECT 语句将源表中的数据导入至目标表中。INSERT INTO SELECT 将源表中的数据进行 ETL 转换之后，导入到 StarRocks 内表中。源表可以是一张或多张内部表或者外部表，甚至云存储或 HDFS 中的数据文件。目标表必须是 StarRocks 的内表。执行该语句之后，系统将 SELECT 语句结果导入目标表。详细使用方式，参考 [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md)。详细参数信息，参考 [INSERT 参数](../sql-reference/sql-statements/data-manipulation/INSERT.md#参数说明)。
+您可以通过 INSERT INTO SELECT 语句将源表中的数据导入至目标表中。INSERT INTO SELECT 将源表中的数据进行 ETL 转换之后，导入到 StarRocks 内表中。源表可以是一张或多张内部表或者外部表，甚至云存储或 HDFS 中的数据文件。目标表必须是 StarRocks 的内表。执行该语句之后，系统将 SELECT 语句结果导入目标表。详细使用方式，参考 [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md)。详细参数信息，参考 [INSERT 参数](../sql-reference/sql-statements/loading_unloading/INSERT.md#参数说明)。
 
 ### 通过 INSERT INTO SELECT 将内外表数据导入内表
 
@@ -223,7 +223,7 @@ INSERT INTO insert_wiki_edit
 
 ## 通过 INSERT OVERWRITE VALUES 语句覆盖写入数据
 
-您可以通过 INSERT OVERWRITE VALUES 语句向指定的表中覆盖写入数据。此导入方式中，多条数据用逗号（,）分隔。详细使用方式，参考 [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md)。详细参数信息，参考 [INSERT 参数说明](../sql-reference/sql-statements/data-manipulation/INSERT.md#参数说明)。
+您可以通过 INSERT OVERWRITE VALUES 语句向指定的表中覆盖写入数据。此导入方式中，多条数据用逗号（,）分隔。详细使用方式，参考 [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md)。详细参数信息，参考 [INSERT 参数说明](../sql-reference/sql-statements/loading_unloading/INSERT.md#参数说明)。
 
 > **注意**
 >
@@ -263,7 +263,7 @@ VALUES
 
 ## 通过 INSERT OVERWRITE SELECT 语句覆盖写入数据
 
-您可以通过 INSERT OVERWRITE SELECT 语句将源表中的数据覆盖写入至目标表中。INSERT OVERWRITE SELECT 将源表中的数据进行 ETL 转换之后，覆盖写入到 StarRocks 内表中。源表可以是一张或多张内部表或者外部表。目标表必须是 StarRocks 的内表。执行该语句之后，系统使用 SELECT 语句结果覆盖目标表的数据。详细使用方式，参考 [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md)。详细参数信息，参考 [INSERT 参数](../sql-reference/sql-statements/data-manipulation/INSERT.md#参数说明)。
+您可以通过 INSERT OVERWRITE SELECT 语句将源表中的数据覆盖写入至目标表中。INSERT OVERWRITE SELECT 将源表中的数据进行 ETL 转换之后，覆盖写入到 StarRocks 内表中。源表可以是一张或多张内部表或者外部表。目标表必须是 StarRocks 的内表。执行该语句之后，系统使用 SELECT 语句结果覆盖目标表的数据。详细使用方式，参考 [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md)。详细参数信息，参考 [INSERT 参数](../sql-reference/sql-statements/loading_unloading/INSERT.md#参数说明)。
 
 > 说明
 >
@@ -381,7 +381,7 @@ mysql> SELECT * FROM insert_generated_columns;
 
 ## 通过 INSERT 语句异步导入数据
 
-使用 INSERT 语句创建的同步导入任务，可能会因为会话中断或超时而失败。您可以使用 [SUBMIT TASK](../sql-reference/sql-statements/data-manipulation/SUBMIT_TASK.md) 语句提交异步 INSERT 任务。此功能自 StarRocks v2.5 起支持。
+使用 INSERT 语句创建的同步导入任务，可能会因为会话中断或超时而失败。您可以使用 [SUBMIT TASK](../sql-reference/sql-statements/loading_unloading/ETL/SUBMIT_TASK.md) 语句提交异步 INSERT 任务。此功能自 StarRocks v2.5 起支持。
 
 - 以下示例将源表中的数据异步导入至目标表中。
 
@@ -453,7 +453,7 @@ ERROR 1064 (HY000): Insert has filtered data in strict mode, tracking_url=http:/
 
 ### 通过 Information Schema 查看
 
-您可以通过 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句从 `information_schema` 数据库中的 `loads` 表来查看 INSERT INTO 作业的结果。该功能自 3.1 版本起支持。
+您可以通过 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句从 `information_schema` 数据库中的 `loads` 表来查看 INSERT INTO 作业的结果。该功能自 3.1 版本起支持。
 
 示例一：查看 `load_test` 数据库中导入作业的执行情况，同时指定查询结果根据作业创建时间 (`CREATE_TIME`) 按降序排列，并且最多显示一条结果数据：
 
@@ -501,7 +501,7 @@ REJECTED_RECORD_PATH: NULL
 1 row in set (0.01 sec)
 ```
 
-有关返回字段的说明，参见 [`information_schema.loads`](../reference/information_schema/loads.md)。
+有关返回字段的说明，参见 [`information_schema.loads`](../sql-reference/information_schema/loads.md)。
 
 ## 相关配置项
 
diff --git a/docs/zh/loading/Kafka-connector-starrocks.md b/docs/zh/loading/Kafka-connector-starrocks.md
index 043db2302917d5..1de814fa5834b2 100644
--- a/docs/zh/loading/Kafka-connector-starrocks.md
+++ b/docs/zh/loading/Kafka-connector-starrocks.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 Kafka connector 导入数据
@@ -210,8 +210,8 @@ MySQL [example_db]> select * from test_tbl;
 | bufferflush.maxbytes                | 否       | 94371840(90M)                                                | 数据攒批的大小，达到该阈值后将数据通过 Stream Load 批量写入 StarRocks。取值范围：[64MB, 10GB]。 Stream Load SDK buffer可能会启动多个 Stream Load 来缓冲数据，因此这里的阈值是指总数据量大小。 |
 | bufferflush.intervalms              | 否       | 300000                                                       | 数据攒批发送的间隔，用于控制数据写入 StarRocks 的延迟，取值范围：[1000, 3600000]。 |
 | connect.timeoutms                   | 否       | 1000                                                         | 连接 http-url 的超时时间。取值范围：[100, 60000]。           |
-| sink.properties.*                   |          |                                                              | 指定 Stream Load 的参数，用于控制导入行为，例如使用 `sink.properties.format` 指定导入数据的格式为 CSV 或者 JSON。更多参数和说明，请参见 [Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)。 |
-| sink.properties.format              | 否       | json                                                         | Stream Load 导入时的数据格式。取值为 CSV 或者 JSON。默认为JSON。更多参数说明，参见 [CSV 适用参数](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md#csv-适用参数)和 [JSON 适用参数](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md#json-适用参数)。 |
+| sink.properties.*                   |          |                                                              | 指定 Stream Load 的参数，用于控制导入行为，例如使用 `sink.properties.format` 指定导入数据的格式为 CSV 或者 JSON。更多参数和说明，请参见 [Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。 |
+| sink.properties.format              | 否       | json                                                         | Stream Load 导入时的数据格式。取值为 CSV 或者 JSON。默认为JSON。更多参数说明，参见 [CSV 适用参数](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md#csv-适用参数)和 [JSON 适用参数](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md#json-适用参数)。 |
 | sink.properties.partial_update      | 否      | `FALSE` | 是否使用部分更新。取值包括 `TRUE` 和 `FALSE`。默认值：`FALSE`。                                                                                                                                                                                             |
 | sink.properties.partial_update_mode | 否      | `row` | 指定部分更新的模式，取值包括 `row` 和 `column`。<ul><li>`row`（默认值），指定使用行模式执行部分更新，比较适用于较多列且小批量的实时更新场景。</li><li>`column`，指定使用列模式执行部分更新，比较适用于少数列并且大量行的批处理更新场景。在该场景，开启列模式，更新速度更快。例如，在一个包含 100 列的表中，每次更新 10 列（占比 10%）并更新所有行，则开启列模式，更新性能将提高 10 倍。</li></ul>  |
 
diff --git a/docs/zh/loading/Load_to_Primary_Key_tables.md b/docs/zh/loading/Load_to_Primary_Key_tables.md
index 4cd1cdf5803a15..8591381c298768 100644
--- a/docs/zh/loading/Load_to_Primary_Key_tables.md
+++ b/docs/zh/loading/Load_to_Primary_Key_tables.md
@@ -1,11 +1,11 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['zhujian']
 ---
 
 # 通过导入实现数据变更
 
-StarRocks 的[主键表](../table_design/table_types/primary_key_table.md)支持通过 [Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)、[Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 或 [Routine Load](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md) 导入作业，对 StarRocks 表进行数据变更，包括插入、更新和删除数据。不支持通过 [Spark Load](../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md) 导入作业或 [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md) 语句对 StarRocks 表进行数据变更。
+StarRocks 的[主键表](../table_design/table_types/primary_key_table.md)支持通过 [Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)、[Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 或 [Routine Load](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md) 导入作业，对 StarRocks 表进行数据变更，包括插入、更新和删除数据。不支持通过 [Spark Load](../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md) 导入作业或 [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md) 语句对 StarRocks 表进行数据变更。
 
 StarRocks 还支持部分更新 (Partial Update) 和条件更新 (Conditional Update)。
 
@@ -63,7 +63,7 @@ StarRocks 的主键表目前支持 UPSERT 和 DELETE 操作，不支持区分 IN
 
 ## 基本操作
 
-下面通过几个示例来展示具体的导入操作。有关使用 Stream Load、Broker Load 和 Routine Load 导入数据的详细语法和参数介绍，请参见 [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)、[BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 和 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md)。
+下面通过几个示例来展示具体的导入操作。有关使用 Stream Load、Broker Load 和 Routine Load 导入数据的详细语法和参数介绍，请参见 [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)、[BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 和 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md)。
 
 ### UPSERT
 
diff --git a/docs/zh/loading/Loading_data_template.md b/docs/zh/loading/Loading_data_template.md
index 59bec657867be8..ea54595392ee17 100644
--- a/docs/zh/loading/Loading_data_template.md
+++ b/docs/zh/loading/Loading_data_template.md
@@ -1,4 +1,4 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 unlisted: true
 ---
diff --git a/docs/zh/loading/RoutineLoad.md b/docs/zh/loading/RoutineLoad.md
index 1e0190a8a0f0ce..42a7d9607c409d 100644
--- a/docs/zh/loading/RoutineLoad.md
+++ b/docs/zh/loading/RoutineLoad.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 Routine Load 导入数据
@@ -62,13 +62,13 @@ Routine Load 目前支持从 Kakfa 集群中消费 CSV、JSON、Avro (自 v3.0.1
 
 3. **多个导入任务并行进行，消费 Kafka 多个分区的消息，导入至 StarRocks**
 
-    1. **调度和提交导入任务**：FE 定时调度任务执行队列中的导入任务，分配给选定的 Coordinator BE。调度导入任务的时间间隔由 `max_batch_interval` 参数，并且 FE 会尽可能均匀地向所有 BE 分配导入任务。有关 `max_batch_interval` 参数的详细介绍，请参见  [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md#job_properties)。
+    1. **调度和提交导入任务**：FE 定时调度任务执行队列中的导入任务，分配给选定的 Coordinator BE。调度导入任务的时间间隔由 `max_batch_interval` 参数，并且 FE 会尽可能均匀地向所有 BE 分配导入任务。有关 `max_batch_interval` 参数的详细介绍，请参见  [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md#job_properties)。
 
     2. **执行导入任务**：Coordinator BE 执行导入任务，消费分区的消息，解析并过滤数据。导入任务需要消费足够多的消息，或者消费足够长时间。消费时间和消费的数据量由 FE 配置项 `max_routine_load_batch_size`、`routine_load_task_consume_second`决定，有关该配置项的更多说明，请参见 [配置参数](../administration/management/FE_configuration.md#导入导出)。然后，Coordinator BE 将消息分发至相关 Executor BE 节点， Executor BE 节点将消息写入磁盘。
 
       > **说明**
       >
-      > StarRocks 支持通过安全协议，包括 SASL_SSL、SAS_PLAINTEXT、SSL，或者 PLAINTEXT 来连接 Kafka。本文以 PLAINTEXT 方式连接 Kafka 为例进行演示，如果您需要通过其他安全协议连接 Kafka，请参见[CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md)。
+      > StarRocks 支持通过安全协议，包括 SASL_SSL、SAS_PLAINTEXT、SSL，或者 PLAINTEXT 来连接 Kafka。本文以 PLAINTEXT 方式连接 Kafka 为例进行演示，如果您需要通过其他安全协议连接 Kafka，请参见[CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md)。
 
 4. **持续生成新的导入任务，不间断地导入数据**
 
@@ -82,7 +82,7 @@ Routine Load 目前支持从 Kakfa 集群中消费 CSV、JSON、Avro (自 v3.0.1
 
 ## 创建导入作业
 
-这里通过三个简单的示例，介绍如何通过 Routine Load 持续消费 Kafka 中 CSV、JSON 和 Avro 格式的数据，并导入至 StarRocks 中。有关创建 Routine Load 的详细语法和参数说明，请参见 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md)。
+这里通过三个简单的示例，介绍如何通过 Routine Load 持续消费 Kafka 中 CSV、JSON 和 Avro 格式的数据，并导入至 StarRocks 中。有关创建 Routine Load 的详细语法和参数说明，请参见 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md)。
 
 ### 导入 CSV 数据
 
@@ -143,7 +143,7 @@ FROM KAFKA
 );
 ```
 
-提交导入作业后，您可以执行  [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md)，查看导入作业执行情况。
+提交导入作业后，您可以执行  [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md)，查看导入作业执行情况。
 
 - **导入作业的名称**
 
@@ -169,7 +169,7 @@ FROM KAFKA
     "property.kafka_default_offsets" = "OFFSET_BEGINNING"
   ```
 
-  更多参数说明，请参见 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md#data_sourcedata_source_properties)。
+  更多参数说明，请参见 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md#data_sourcedata_source_properties)。
 
 - **数据转换**
 
@@ -257,7 +257,7 @@ FROM KAFKA
 );
 ```
 
-提交导入作业后，您可以执行  [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md)，查看导入作业执行情况。
+提交导入作业后，您可以执行  [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md)，查看导入作业执行情况。
 
 - **数据格式**
 
@@ -368,7 +368,7 @@ FROM KAFKA
   >
   > 如果一条 Avro record 中字段的名称和数量（顺序不需要对应）都能对应目标表中列，则无需配置 `COLUMNS` 。
 
-提交导入作业后，您可以执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md)，查看导入作业执行情况。
+提交导入作业后，您可以执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md)，查看导入作业执行情况。
 
 #### 数据类型映射
 
@@ -408,9 +408,9 @@ StarRocks 支持导入所有类型的 Avro 数据。导入 Avro 数据至 StarRo
 
 ### 查看导入作业
 
-执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md)，查看名称为  `example_tbl2_ordertest2` 的导入作业的信息，比如导入作业状态`State`，导入作业的统计信息`Statistic`（消费的总数据行数、已导入的行数等），消费的分区及进度`Progress`等。
+执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md)，查看名称为  `example_tbl2_ordertest2` 的导入作业的信息，比如导入作业状态`State`，导入作业的统计信息`Statistic`（消费的总数据行数、已导入的行数等），消费的分区及进度`Progress`等。
 
-如果导入作业状态自动变为 **PAUSED**，则可能为导入任务错误行数超过阈值。错误行数阈值的设置方式，请参考 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md#job_properties)。您可以参考`ReasonOfStateChanged`、`ErrorLogUrls`报错进行排查和修复。修复后您可以使用 [RESUME ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md)，恢复 **PAUSED** 状态的导入作业。
+如果导入作业状态自动变为 **PAUSED**，则可能为导入任务错误行数超过阈值。错误行数阈值的设置方式，请参考 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md#job_properties)。您可以参考`ReasonOfStateChanged`、`ErrorLogUrls`报错进行排查和修复。修复后您可以使用 [RESUME ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md)，恢复 **PAUSED** 状态的导入作业。
 
 如果导入作业状态为 **CANCELLED**，则可能为导入任务执行遇到异常（如表被删除）。您可以参考`ReasonOfStateChanged`、`ErrorLogUrls`报错进行排查和修复。但是修复后，您无法恢复 **CANCELLED** 状态的导入作业。
 
@@ -443,7 +443,7 @@ ReasonOfStateChanged:
 
 ### 查看导入任务
 
-执行 [SHOW ROUTINE LOAD TASK](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD_TASK.md)，查看导入作业`example_tbl2_ordertest2` 中一个或多个导入任务的信息。比如当前有多少任务正在运行，消费分区及进度`DataSourceProperties`，以及对应的 Coordinator BE 节点 `BeId`。
+执行 [SHOW ROUTINE LOAD TASK](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD_TASK.md)，查看导入作业`example_tbl2_ordertest2` 中一个或多个导入任务的信息。比如当前有多少任务正在运行，消费分区及进度`DataSourceProperties`，以及对应的 Coordinator BE 节点 `BeId`。
 
 ```SQL
 MySQL [example_db]> SHOW ROUTINE LOAD TASK WHERE JobName = "example_tbl2_ordertest2" \G
@@ -487,7 +487,7 @@ DataSourceProperties: {"0":2,"3":0}
 
 ## 暂停导入作业
 
-执行 [PAUSE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/PAUSE_ROUTINE_LOAD.md) 语句后，会暂停导入作业。导入作业会进入 **PAUSED** 状态，但是导入作业未结束，您可以执行 [RESUME ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md) 语句重启该导入作业。您也可以执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) 语句查看已暂停的导入作业的状态。
+执行 [PAUSE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/PAUSE_ROUTINE_LOAD.md) 语句后，会暂停导入作业。导入作业会进入 **PAUSED** 状态，但是导入作业未结束，您可以执行 [RESUME R../sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.mdUTINE_LOAD.md) 语句重启该导入作业。您也可以执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) 语句查看已暂停的导入作业的状态。
 
 例如，可以通过以下语句，暂停导入作业`example_tbl2_ordertest2`：
 
@@ -497,7 +497,7 @@ PAUSE ROUTINE LOAD FOR example_tbl2_ordertest2;
 
 ## 恢复导入作业
 
-执行 [RESUME ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md)，恢复导入作业。导入作业会先短暂地进入 **NEED_SCHEDULE** 状态，表示正在重新调度导入作业，一段时间后会恢复至 **RUNNING** 状态，继续消费 Kafka 消息并且导入数据。您可以执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) 语句查看已恢复的导入作业。
+执行 [RESUME ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md)，恢复导入作业。导入作业会先短暂地进入 **NEED_SCHEDULE** 状态，表示正在重新调度导入作业，一段时间后会恢复至 **RUNNING** 状态，继续消费 Kafka 消息并且导入数据。您可以执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) 语句查看已恢复的导入作业。
 
 例如，可以通过以下语句，恢复导入作业`example_tbl2_ordertest2`：
 
@@ -507,7 +507,7 @@ RESUME ROUTINE LOAD FOR example_tbl2_ordertest2;
 
 ## 修改导入作业
 
-修改前，您需要先执行 PAUSE ROUTINE LOAD 暂停导入作业。然后执行 [ALTER ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD.md) 语句，修改导入作业的参数配置。修改成功后，您需要执行 [RESUME ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md)，恢复导入作业。然后执行  [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) 语句查看修改后的导入作业。
+修改前，您需要先执行 PAUSE ROUTINE LOAD 暂停导入作业。然后执行 [ALTER ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md) 语句，修改导入作业的参数配置。修改成功后，您需要执行 [RESUME ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md)，恢复导入作业。然后执行  [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) 语句查看修改后的导入作业。
 
 例如，当存活 BE 节点数增至 6 个，待消费分区为`"0,1,2,3,4,5,6,7"`时，如果您希望提高实际的导入并行度，则可以通过以下语句，将期望任务并行度`desired_concurrent_number` 增加至 `6`（大于等于存活 BE 节点数），并且调整待消费分区和起始消费位点。
 
@@ -530,7 +530,7 @@ FROM kafka
 
 ## 停止导入作业
 
-执行  [STOP ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/STOP_ROUTINE_LOAD.md)，可以停止导入作业。导入作业会进入 **STOPPED** 状态，代表此导入作业已经结束，且无法恢复。再次执行 SHOW ROUTINE LOAD 语句，将无法看到已经停止的导入作业。
+执行  [STOP ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/STOP_ROUTINE_LOAD.md)，可以停止导入作业。导入作业会进入 **STOPPED** 状态，代表此导入作业已经结束，且无法恢复。再次执行 SHOW ROUTINE LOAD 语句，将无法看到已经停止的导入作业。
 
 例如，可以通过以下语句，停止导入作业`example_tbl2_ordertest2`：
 
diff --git a/docs/zh/loading/Spark-connector-starrocks.md b/docs/zh/loading/Spark-connector-starrocks.md
index d850459951d270..bdeade1fef9d83 100644
--- a/docs/zh/loading/Spark-connector-starrocks.md
+++ b/docs/zh/loading/Spark-connector-starrocks.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 Spark connector 导入数据（推荐）
@@ -108,7 +108,7 @@ connector jar包的命名格式如下
 | starrocks.write.max.retries                    | 否       | 3             | 自 1.1.1 版本起支持。如果一批数据导入失败，Spark connector 导入该批数据的重试次数上线。<br/> **注意：**由于 Stream Load 事务接口不支持重试。如果此参数为正数，则 Spark connector 始终使用 Stream Load 接口，并忽略 `starrocks.write.enable.transaction-stream-load` 的值。|
 | starrocks.write.retry.interval.ms              | 否       | 10000         | 自 1.1.1 版本起支持。如果一批数据导入失败，Spark connector 尝试再次导入该批数据的时间间隔。|
 | starrocks.columns                              | 否      | 无 | 支持向 StarRocks 表中写入部分列，通过该参数指定列名，多个列名之间使用逗号 (,) 分隔，例如"c0,c1,c2"。                                                                                                                                                       |
-| starrocks.write.properties.*                   | 否      | 无 | 指定 Stream Load 的参数，用于控制导入行为，例如使用 `starrocks.write.properties.format` 指定导入数据的格式为 CSV 或者 JSON。更多参数和说明，请参见 [Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)。 |
+| starrocks.write.properties.*                   | 否      | 无 | 指定 Stream Load 的参数，用于控制导入行为，例如使用 `starrocks.write.properties.format` 指定导入数据的格式为 CSV 或者 JSON。更多参数和说明，请参见 [Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。 |
 | starrocks.write.properties.format              | 否      | CSV | 指定导入数据的格式，取值为 CSV 和 JSON。connector 会将每批数据转换成相应的格式发送给 StarRocks。                                                                                                                                             |
 | starrocks.write.properties.row_delimiter       | 否      | \n | 使用CSV格式导入时，用于指定行分隔符。                                                                                                                                                                                                  |
 | starrocks.write.properties.column_separator    | 否      | \t | 使用CSV格式导入时，用于指定列分隔符。                                                                                                                                                                                                  |
diff --git a/docs/zh/loading/SparkLoad.md b/docs/zh/loading/SparkLoad.md
index 7929fbf498ebcd..c8a338a3ade2ca 100644
--- a/docs/zh/loading/SparkLoad.md
+++ b/docs/zh/loading/SparkLoad.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 Spark Load 批量导入数据
@@ -125,7 +125,7 @@ PROPERTIES
 `spark0`、`spark1` 和 `spark2` 为 StarRocks 中配置的 Spark 资源的名字。
 
 PROPERTIES 是 Spark 资源相关参数，以下对重要参数进行说明：
-> Spark 资源的全部参数和说明，请参见 [CREATE RESOURCE](../sql-reference/sql-statements/data-definition/CREATE_RESOURCE.md#spark-资源)。
+> Spark 资源的全部参数和说明，请参见 [CREATE RESOURCE](../sql-reference/sql-statements/Resource/CREATE_RESOURCE.md#spark-资源)。
 
 * Spark 集群相关参数
   * `type`：必填，资源类型，取值为 `spark`。
@@ -141,7 +141,7 @@ PROPERTIES 是 Spark 资源相关参数，以下对重要参数进行说明：
       * `spark.hadoop.yarn.resourcemanager.address.rm-id`: 对于每个 rm-id，指定 `host:port` 以供客户端提交作业。
 * Broker 相关参数
   * `broker`: Broker 组的名称。需要使用 `ALTER SYSTEM ADD BROKER` 命令提前完成配置。
-  * `broker.property_key`: Broker 读取 ETL 生成的中间文件时需要指定的认证信息等，详细可参考 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+  * `broker.property_key`: Broker 读取 ETL 生成的中间文件时需要指定的认证信息等，详细可参考 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 * 其他参数
   * `working_dir`: 必填，一个 HDFS 文件路径，用于存放 ETL 作业生成的文件。例如`hdfs://host: port/tmp/starrocks`。
 
@@ -150,7 +150,7 @@ PROPERTIES 是 Spark 资源相关参数，以下对重要参数进行说明：
 以上为通过 Broker 进程执行导入时的参数说明，如果使用无 Broker 进程的方式导入，则需要注意如下事项：
 
 * 无需传入 `broker`。
-* 如果您需要配置用户身份认证、NameNode 节点的 HA，则需要在 HDFS 集群中的 **hdfs-site.xml** 文件中配置参数，具体参数和说明，请参见 [broker_properties](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md#hdfs)。并且将 **hdfs-site.xml** 文件放到每一个 FE 的 **$FE_HOME/conf** 下以及每个 BE 的 **$BE_HOME/conf** 下。
+* 如果您需要配置用户身份认证、NameNode 节点的 HA，则需要在 HDFS 集群中的 **hdfs-site.xml** 文件中配置参数，具体参数和说明，请参见 [broker_properties](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md#hdfs)。并且将 **hdfs-site.xml** 文件放到每一个 FE 的 **$FE_HOME/conf** 下以及每个 BE 的 **$BE_HOME/conf** 下。
 
     > **说明**
     >
@@ -319,7 +319,7 @@ PROPERTIES
     );
     ~~~
 
-创建导入的详细语法请参考 [SPARK LOAD](../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md)。这里主要介绍 Spark load 的创建导入语法中参数意义和注意事项。
+创建导入的详细语法请参考 [SPARK LOAD](../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md)。这里主要介绍 Spark load 的创建导入语法中参数意义和注意事项。
 
 * **Label**
   
@@ -356,7 +356,7 @@ WITH RESOURCE 'spark0'
 
 ### 查看导入任务
 
-Spark Load 导入方式同 Broker Load 一样都是异步的，用户必须将创建导入的 Label 记录下来，并且在 `SHOW LOAD` 命令中使用 Label 来查看导入结果。查看导入的命令在所有导入方式中是通用的，具体语法可参考 [SHOW LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md)。示例如下：
+Spark Load 导入方式同 Broker Load 一样都是异步的，用户必须将创建导入的 Label 记录下来，并且在 `SHOW LOAD` 命令中使用 Label 来查看导入结果。查看导入的命令在所有导入方式中是通用的，具体语法可参考 [SHOW LOAD](../sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md)。示例如下：
 
 ~~~sql
 mysql > show load where label="label1"\G
@@ -378,11 +378,11 @@ LoadFinishTime: 2019-07-27 11:50:16
     JobDetails: {"ScannedRows":28133395, "TaskNumber":1, "FileNumber":1,"FileSize":200000}
 ~~~
 
-返回结果集中参数的意义可参考 [查看导入状态](../sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md#返回结果说明)。
+返回结果集中参数的意义可参考 [查看导入状态](../sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md#返回结果说明)。
 
 ### 取消导入
 
-当 Spark load 作业状态不为 CANCELLED 或 FINISHED 时，可以被用户手动取消。取消时需要指定待取消导入任务的 Label 。取消导入命令语法可参考 [CANCEL LOAD](../sql-reference/sql-statements/data-manipulation/CANCEL_LOAD.md) 。示例如下：
+当 Spark load 作业状态不为 CANCELLED 或 FINISHED 时，可以被用户手动取消。取消时需要指定待取消导入任务的 Label 。取消导入命令语法可参考 [CANCEL LOAD](../sql-reference/sql-statements/loading_unloading/CANCEL_LOAD.md) 。示例如下：
 
 ~~~sql
 CANCEL LOAD FROM db1 WHERE LABEL = "label1";
diff --git a/docs/zh/loading/StreamLoad.md b/docs/zh/loading/StreamLoad.md
index be7de62d05947b..6bf2512b125080 100644
--- a/docs/zh/loading/StreamLoad.md
+++ b/docs/zh/loading/StreamLoad.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['Stream Load']
 ---
 
@@ -9,8 +9,8 @@ import InsertPrivNote from '../_assets/commonMarkdown/insertPrivNote.md'
 
 StarRocks 提供两种导入方式帮助您从本地文件系统导入数据：
 
-- 使用 [Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md) 进行同步导入。
-- 使用 [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 进行异步导入。
+- 使用 [Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md) 进行同步导入。
+- 使用 [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 进行异步导入。
 
 两种导入方式各有优势：
 
@@ -64,7 +64,7 @@ Stream Load 当前不支持导入某一列为 JSON 的 CSV 文件的数据。
 
 ### 操作示例
 
-本文以 curl 工具为例，介绍如何使用 Stream Load 从本地文件系统导入 CSV 或 JSON 格式的数据。有关创建导入作业的详细语法和参数说明，请参见 [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)。
+本文以 curl 工具为例，介绍如何使用 Stream Load 从本地文件系统导入 CSV 或 JSON 格式的数据。有关创建导入作业的详细语法和参数说明，请参见 [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。
 
 注意在 StarRocks 中，部分文字是 SQL 语言的保留关键字，不能直接用于 SQL 语句。如果想在 SQL 语句中使用这些保留关键字，必须用反引号 (`) 包裹起来。参见[关键字](../sql-reference/sql-statements/keywords.md)。
 
@@ -126,7 +126,7 @@ curl --location-trusted -u <username>:<password> -H "label:123" \
 :::note
 
 - 如果账号没有设置密码，这里只需要传入 `<username>:`。
-- 您可以通过 [SHOW FRONTENDS](../sql-reference/sql-statements/Administration/SHOW_FRONTENDS.md) 命令查看 FE 节点的 IP 地址和 HTTP 端口号。
+- 您可以通过 [SHOW FRONTENDS](../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_FRONTENDS.md) 命令查看 FE 节点的 IP 地址和 HTTP 端口号。
 
 :::
 
@@ -151,7 +151,7 @@ SELECT * FROM table1;
 
 #### 导入 JSON 格式的数据
 
-从 3.2.7 版本起，STREAM LOAD 支持在传输过程中对 JSON 数据进行压缩，减少网络带宽开销。用户可以通过 `compression` 或 `Content-Encoding` 参数指定不同的压缩方式，支持 GZIP、BZIP2、LZ4_FRAME、ZSTD 压缩算法。语法参见[STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)。
+从 3.2.7 版本起，STREAM LOAD 支持在传输过程中对 JSON 数据进行压缩，减少网络带宽开销。用户可以通过 `compression` 或 `Content-Encoding` 参数指定不同的压缩方式，支持 GZIP、BZIP2、LZ4_FRAME、ZSTD 压缩算法。语法参见[STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。
 
 ##### 数据样例
 
@@ -205,7 +205,7 @@ curl -v --location-trusted -u <username>:<password> -H "strict_mode: true" \
 :::note
 
 - 如果账号没有设置密码，这里只需要传入 `<username>:`。
-- 您可以通过 [SHOW FRONTENDS](../sql-reference/sql-statements/Administration/SHOW_FRONTENDS.md) 命令查看 FE 节点的 IP 地址和 HTTP 端口号。
+- 您可以通过 [SHOW FRONTENDS](../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_FRONTENDS.md) 命令查看 FE 节点的 IP 地址和 HTTP 端口号。
 
 :::
 
@@ -225,7 +225,7 @@ curl -v --location-trusted -u <username>:<password> -H "strict_mode: true" \
 
 :::
 
-有关导入 JSON 数据时 `jsonpaths`、`columns` 和 StarRocks 表中的字段之间的对应关系，请参见 STREAM LOAD 文档中“[列映射](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md#列映射)”章节。
+有关导入 JSON 数据时 `jsonpaths`、`columns` 和 StarRocks 表中的字段之间的对应关系，请参见 STREAM LOAD 文档中“[列映射](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md#列映射)”章节。
 
 导入完成后，您可以查询 `table2` 表，验证数据导入是否成功，如下所示：
 
@@ -241,7 +241,7 @@ SELECT * FROM table2;
 
 #### 查看 Stream Load 导入进度
 
-导入作业结束后，StarRocks 会以 JSON 格式返回本次导入作业的结果信息，具体请参见 STREAM LOAD 文档中“[返回值](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md#返回值)”章节。
+导入作业结束后，StarRocks 会以 JSON 格式返回本次导入作业的结果信息，具体请参见 STREAM LOAD 文档中“[返回值](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md#返回值)”章节。
 
 Stream Load 不支持通过 SHOW LOAD 语句查看导入作业执行情况。
 
@@ -282,7 +282,7 @@ Stream Load 不支持手动取消导入作业。如果导入作业发生超时
 
   :::
 
-  Stream Load 还提供 `timeout` 参数来设置当前导入作业的超时时间。具体请参见 [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)。
+  Stream Load 还提供 `timeout` 参数来设置当前导入作业的超时时间。具体请参见 [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。
 
 ### 使用说明
 
@@ -381,13 +381,13 @@ PROPERTIES
 - `BROKER`：Broker 的名称。
 - `PROPERTIES`：用于指定超时时间等可选的作业属性。
 
-有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 #### 查看 Broker Load 导入进度
 
-在 v3.0 及以前版本，您需要通过 [SHOW LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md) 语句或者 curl 命令来查看导入作业的进度。
+在 v3.0 及以前版本，您需要通过 [SHOW LOAD](../sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md) 语句或者 curl 命令来查看导入作业的进度。
 
-在 v3.1 及以后版本，您可以通过 [`information_schema.loads`](../reference/information_schema/loads.md) 视图来查看 Broker Load 作业的进度：
+在 v3.1 及以后版本，您可以通过 [`information_schema.loads`](../sql-reference/information_schema/loads.md) 视图来查看 Broker Load 作业的进度：
 
 ```SQL
 SELECT * FROM information_schema.loads;
@@ -420,7 +420,7 @@ SELECT * FROM mytable;
 
 #### 取消 Broker Load 作业
 
-当导入作业状态不为 **CANCELLED** 或 **FINISHED** 时，可以通过 [CANCEL LOAD](../sql-reference/sql-statements/data-manipulation/CANCEL_LOAD.md) 语句来取消该导入作业。
+当导入作业状态不为 **CANCELLED** 或 **FINISHED** 时，可以通过 [CANCEL LOAD](../sql-reference/sql-statements/loading_unloading/CANCEL_LOAD.md) 语句来取消该导入作业。
 
 例如，可以通过以下语句，撤销 `mydatabase` 数据库中标签为 `label_local` 的导入作业：
 
@@ -464,6 +464,6 @@ WHERE LABEL = "label_local";
    - `BROKER`：无需指定。
    - `PROPERTIES`：用于指定超时时间等可选的作业属性。
 
-   有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+   有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 提交导入作业后，您可以查看导入进度、或者取消导入作业。具体操作参见本文“[查看 Broker Load 导入进度](#查看-broker-load-导入进度)”和“[取消 Broker Load 作业](#取消-broker-load-作业)中的介绍。
diff --git a/docs/zh/loading/Stream_Load_transaction_interface.md b/docs/zh/loading/Stream_Load_transaction_interface.md
index 881615abb8b8d6..9e6f91d83b596a 100644
--- a/docs/zh/loading/Stream_Load_transaction_interface.md
+++ b/docs/zh/loading/Stream_Load_transaction_interface.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['Stream Load']
 ---
 
@@ -500,4 +500,4 @@ curl --location-trusted -u <jack>:<123456> -H "label:streamload_txn_example1_tab
 
 有关 Stream Load 适用的业务场景、支持的数据文件格式、基本原理等信息，参见[使用 Stream Load 从本地导入](../loading/StreamLoad.md#使用-stream-load-从本地导入)。
 
-有关创建 Stream Load 作业的语法和参数，参见[STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)。
+有关创建 Stream Load 作业的语法和参数，参见[STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。
diff --git a/docs/zh/loading/azure.md b/docs/zh/loading/azure.md
index d89f1e4706526a..62190a114540a7 100644
--- a/docs/zh/loading/azure.md
+++ b/docs/zh/loading/azure.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 keywords: ['Broker Load']
 ---
@@ -10,8 +10,8 @@ import InsertPrivNote from '../_assets/commonMarkdown/insertPrivNote.md'
 
 StarRocks 支持通过以下方式从 Azure 导入数据：
 
-- 使用 [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md)+[`FILES()`](../sql-reference/sql-functions/table-functions/files.md) 进行同步导入。
-- 使用 [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 进行异步导入。
+- 使用 [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md)+[`FILES()`](../sql-reference/sql-functions/table-functions/files.md) 进行同步导入。
+- 使用 [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 进行异步导入。
 
 两种导入方式各有优势，具体将在下面分章节详细阐述。
 
@@ -52,9 +52,9 @@ StarRocks 支持通过以下方式从 Azure 导入数据：
 
 通过 `FILES()`，您可以：
 
-- 使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句直接从 Azure 查询数据。
-- 通过 [CREATE TABLE AS SELECT](../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md)（简称 CTAS）语句实现自动建表和导入数据。
-- 手动建表，然后通过 [INSERT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 导入数据。
+- 使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句直接从 Azure 查询数据。
+- 通过 [CREATE TABLE AS SELECT](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md)（简称 CTAS）语句实现自动建表和导入数据。
+- 手动建表，然后通过 [INSERT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 导入数据。
 
 ### 操作示例
 
@@ -127,7 +127,7 @@ SELECT * FROM FILES
 );
 ```
 
-建表完成后，您可以通过 [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md) 查看新建表的表结构：
+建表完成后，您可以通过 [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md) 查看新建表的表结构：
 
 ```SQL
 DESCRIBE user_behavior_inferred;
@@ -206,7 +206,7 @@ DUPLICATE KEY(UserID)
 DISTRIBUTED BY HASH(UserID);
 ```
 
-通过 [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md) 查看新建表的表结构：
+通过 [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md) 查看新建表的表结构：
 
 ```sql
 DESCRIBE user_behavior_declared;
@@ -270,13 +270,13 @@ SELECT * from user_behavior_declared LIMIT 3;
 
 #### 查看导入进度
 
-通过 StarRocks Information Schema 库中的 [`loads`](../reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。例如：
+通过 StarRocks Information Schema 库中的 [`loads`](../sql-reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。例如：
 
 ```SQL
 SELECT * FROM information_schema.loads ORDER BY JOB_ID DESC;
 ```
 
-有关 `loads` 视图提供的字段详情，参见 [`loads`](../reference/information_schema/loads.md)。
+有关 `loads` 视图提供的字段详情，参见 [`loads`](../sql-reference/information_schema/loads.md)。
 
 如果您提交了多个导入作业，您可以通过 `LABEL` 过滤出想要查看的作业。例如：
 
@@ -395,17 +395,17 @@ PROPERTIES
 - `BROKER`：连接数据源的认证信息配置。
 - `PROPERTIES`：用于指定超时时间等可选的作业属性。
 
-有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 #### 查看导入进度
 
-通过 StarRocks Information Schema 库中的 [`loads`](../reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。
+通过 StarRocks Information Schema 库中的 [`loads`](../sql-reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。
 
 ```SQL
 SELECT * FROM information_schema.loads \G
 ```
 
-有关 `loads` 视图提供的字段详情，参见 [`loads`](../reference/information_schema/loads.md)。
+有关 `loads` 视图提供的字段详情，参见 [`loads`](../sql-reference/information_schema/loads.md)。
 
 如果您提交了多个导入作业，您可以通过 `LABEL` 过滤出想要查看的作业。例如：
 
diff --git a/docs/zh/loading/cloud_storage_load.md b/docs/zh/loading/cloud_storage_load.md
index 1f274488a6f531..f788c884fdabe9 100644
--- a/docs/zh/loading/cloud_storage_load.md
+++ b/docs/zh/loading/cloud_storage_load.md
@@ -1,10 +1,10 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 从云存储导入
 
-StarRocks 支持通过两种方式从云存储系统导入大批量数据：[Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 和 [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md)。
+StarRocks 支持通过两种方式从云存储系统导入大批量数据：[Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 和 [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md)。
 
 在 3.0 及以前版本，StarRocks 只支持 Broker Load 导入方式。Broker Load 是一种异步导入方式，即您提交导入作业以后，StarRocks 会异步地执行导入作业。您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
@@ -18,7 +18,7 @@ Broker Load 能够保证单次导入事务的原子性，即单次导入的多
 
 从 3.1 版本起，StarRocks 新增支持使用 INSERT 语句和 `FILES` 关键字直接从 AWS S3 导入特定格式的数据文件，避免了需事先创建外部表的麻烦。参见 [INSERT > 通过 FILES 关键字直接导入外部数据文件](../loading/InsertInto.md#通过-insert-into-select-以及表函数-files-导入外部数据文件)。
 
-本文主要介绍如何使用 [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 从云存储系统导入数据。
+本文主要介绍如何使用 [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 从云存储系统导入数据。
 
 ## 支持的数据文件格式
 
@@ -99,7 +99,7 @@ Broker Load 支持如下数据文件格式：
 
 注意，Broker Load 支持通过 S3 或 S3A 协议访问 AWS S3，因此从 AWS S3 导入数据时，您在文件路径 (`DATA INFILE`) 中传入的目标文件的 S3 URI 可以使用 `s3://` 或 `s3a://` 作为前缀。
 
-另外注意，下述命令以 CSV 格式和基于 Instance Profile 的认证方式为例。有关如何导入其他格式的数据、以及使用其他认证方式时需要配置的参数，参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+另外注意，下述命令以 CSV 格式和基于 Instance Profile 的认证方式为例。有关如何导入其他格式的数据、以及使用其他认证方式时需要配置的参数，参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 ### 导入单个数据文件到单表
 
@@ -130,7 +130,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
 
 ```SQL
 SELECT * FROM table1;
@@ -174,7 +174,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
 
 ```SQL
 SELECT * FROM table1;
@@ -227,7 +227,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 和 `table2` 中的数据：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 和 `table2` 中的数据：
 
 1. 查询 `table1` 的数据，如下所示：
 
@@ -263,7 +263,7 @@ PROPERTIES
 
 注意，由于 Broker Load 只支持通过 gs 协议访问 Google GCS，因此从 Google GCS 导入数据时，必须确保您在文件路径 (`DATA INFILE`) 中传入的目标文件的 GCS URI 使用 `gs://` 作为前缀。
 
-另外注意，下述命令以 CSV 格式和基于 VM 的认证方式为例。有关如何导入其他格式的数据、以及使用其他认证方式时需要配置的参数，参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+另外注意，下述命令以 CSV 格式和基于 VM 的认证方式为例。有关如何导入其他格式的数据、以及使用其他认证方式时需要配置的参数，参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 ### 导入单个数据文件到单表
 
@@ -293,7 +293,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
 
 ```SQL
 SELECT * FROM table1;
@@ -336,7 +336,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
 
 ```SQL
 SELECT * FROM table1;
@@ -388,7 +388,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 和 `table2` 中的数据：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 和 `table2` 中的数据：
 
 1. 查询 `table1` 的数据，如下所示：
 
@@ -432,7 +432,7 @@ PROPERTIES
   - 如果使用 HTTP 协议进行访问，请使用 `abfs://` 作为前缀，例如，`abfs://<container>@<storage_account>.dfs.core.windows.net/<file_name>`。
   - 如果使用 HTTPS 协议进行访问，请使用 `abfss://` 作为前缀，例如，`abfss://<container>@<storage_account>.dfs.core.windows.net/<file_name>`。
 
-另外注意，下述命令以 CSV 格式、Azure Blob Storage 和基于 Shared Key 的认证方式为例。有关如何导入其他格式的数据、以及使用其他 Azure 对象存储服务和其他认证方式时需要配置的参数，参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+另外注意，下述命令以 CSV 格式、Azure Blob Storage 和基于 Shared Key 的认证方式为例。有关如何导入其他格式的数据、以及使用其他 Azure 对象存储服务和其他认证方式时需要配置的参数，参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 ### 导入单个数据文件到单表
 
@@ -463,7 +463,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
 
 ```SQL
 SELECT * FROM table1;
@@ -507,7 +507,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
 
 ```SQL
 SELECT * FROM table1;
@@ -560,7 +560,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 和 `table2` 中的数据：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 和 `table2` 中的数据：
 
 1. 查询 `table1` 的数据，如下所示：
 
@@ -594,7 +594,7 @@ PROPERTIES
 
 ## 从阿里云 OSS 导入
 
-下述命令以 CSV 格式为例。有关如何导入其他格式的数据，参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+下述命令以 CSV 格式为例。有关如何导入其他格式的数据，参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 ### 导入单个数据文件到单表
 
@@ -626,7 +626,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
 
 ```SQL
 SELECT * FROM table1;
@@ -671,7 +671,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
 
 ```SQL
 SELECT * FROM table1;
@@ -725,7 +725,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 和 `table2` 中的数据：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 和 `table2` 中的数据：
 
 1. 查询 `table1` 的数据，如下所示：
 
@@ -759,7 +759,7 @@ PROPERTIES
 
 ## 从腾讯云 COS 导入
 
-下述命令以 CSV 格式为例。有关如何导入其他格式的数据，参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+下述命令以 CSV 格式为例。有关如何导入其他格式的数据，参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 ### 导入单个数据文件到单表
 
@@ -791,7 +791,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
 
 ```SQL
 SELECT * FROM table1;
@@ -836,7 +836,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
 
 ```SQL
 SELECT * FROM table1;
@@ -890,7 +890,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 和 `table2` 中的数据：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 和 `table2` 中的数据：
 
 1. 查询 `table1` 的数据，如下所示：
 
@@ -924,7 +924,7 @@ PROPERTIES
 
 ## 从华为云 OBS 导入
 
-下述命令以 CSV 格式为例。有关如何导入其他格式的数据，参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+下述命令以 CSV 格式为例。有关如何导入其他格式的数据，参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 ### 导入单个数据文件到单表
 
@@ -956,7 +956,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
 
 ```SQL
 SELECT * FROM table1;
@@ -1001,7 +1001,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
 
 ```SQL
 SELECT * FROM table1;
@@ -1055,7 +1055,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 和 `table2` 中的数据：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 和 `table2` 中的数据：
 
 1. 查询 `table1` 的数据，如下所示：
 
@@ -1089,7 +1089,7 @@ PROPERTIES
 
 ## 从其他兼容 S3 协议的对象存储导入
 
-下述命令以 CSV 格式和 MinIO 存储为例。有关如何导入其他格式的数据，参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+下述命令以 CSV 格式和 MinIO 存储为例。有关如何导入其他格式的数据，参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 ### 导入单个数据文件到单表
 
@@ -1123,7 +1123,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
 
 ```SQL
 SELECT * FROM table1;
@@ -1170,7 +1170,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 的数据，如下所示：
 
 ```SQL
 SELECT * FROM table1;
@@ -1226,7 +1226,7 @@ PROPERTIES
 
 提交导入作业以后，您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持，具体请参见本文“[查看导入作业](#查看导入作业)”小节。
 
-确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句来查询 `table1` 和 `table2` 中的数据：
+确认导入作业成功以后，您可以使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句来查询 `table1` 和 `table2` 中的数据：
 
 1. 查询 `table1` 的数据，如下所示：
 
@@ -1260,7 +1260,7 @@ PROPERTIES
 
 ## 查看导入作业
 
-通过 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句从 `information_schema` 数据库中的 `loads` 表来查看 Broker Load 作业的结果。该功能自 3.1 版本起支持。
+通过 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句从 `information_schema` 数据库中的 `loads` 表来查看 Broker Load 作业的结果。该功能自 3.1 版本起支持。
 
 示例一：通过如下命令查看 `test_db` 数据库中导入作业的执行情况，同时指定查询结果根据作业创建时间 (`CREATE_TIME`) 按降序排列，并且最多显示两条结果数据：
 
@@ -1360,11 +1360,11 @@ WHERE database_name = 'test_db' and label = 'label_brokerload_unqualifiedtest_82
 REJECTED_RECORD_PATH: 172.26.95.92:/home/disk1/sr/be/storage/rejected_record/test_db/label_brokerload_unqualifiedtest_0728/6/404a20b1e4db4d27_8aa9af1e8d6d8bdc
 ```
 
-有关返回字段的说明，参见 [`information_schema.loads`](../reference/information_schema/loads.md)。
+有关返回字段的说明，参见 [`information_schema.loads`](../sql-reference/information_schema/loads.md)。
 
 ## 取消导入作业
 
-当导入作业状态不为 **CANCELLED** 或 **FINISHED** 时，可以通过 [CANCEL LOAD](../sql-reference/sql-statements/data-manipulation/CANCEL_LOAD.md) 语句来取消该导入作业。
+当导入作业状态不为 **CANCELLED** 或 **FINISHED** 时，可以通过 [CANCEL LOAD](../sql-reference/sql-statements/loading_unloading/CANCEL_LOAD.md) 语句来取消该导入作业。
 
 例如，可以通过以下语句，撤销 `test_db` 数据库中标签为 `label1` 的导入作业：
 
diff --git a/docs/zh/loading/gcs.md b/docs/zh/loading/gcs.md
index 1de6ba72b467a8..cc3f7f91dcac01 100644
--- a/docs/zh/loading/gcs.md
+++ b/docs/zh/loading/gcs.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 keywords: ['Broker Load']
 ---
@@ -10,8 +10,8 @@ import InsertPrivNote from '../_assets/commonMarkdown/insertPrivNote.md'
 
 StarRocks 支持通过以下方式从 GCS 导入数据：
 
-- 使用 [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md)+[`FILES()`](../sql-reference/sql-functions/table-functions/files.md) 进行同步导入。
-- 使用 [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 进行异步导入。
+- 使用 [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md)+[`FILES()`](../sql-reference/sql-functions/table-functions/files.md) 进行同步导入。
+- 使用 [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 进行异步导入。
 
 两种导入方式各有优势，具体将在下面分章节详细阐述。
 
@@ -52,9 +52,9 @@ StarRocks 支持通过以下方式从 GCS 导入数据：
 
 通过 `FILES()`，您可以：
 
-- 使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句直接从 GCS 查询数据。
-- 通过 [CREATE TABLE AS SELECT](../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md)（简称 CTAS）语句实现自动建表和导入数据。
-- 手动建表，然后通过 [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md) 导入数据。
+- 使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句直接从 GCS 查询数据。
+- 通过 [CREATE TABLE AS SELECT](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md)（简称 CTAS）语句实现自动建表和导入数据。
+- 手动建表，然后通过 [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md) 导入数据。
 
 ### 操作示例
 
@@ -137,7 +137,7 @@ SELECT * FROM FILES
 >
 > 把上面命令示例中的访问凭证替换成您自己的访问凭证。由于这里使用的数据对象对所有合法的 GCP 用户开放，因此您填入任何真实有效的 Service Account 的 Email、Private Key ID 和 Private Key 都可以。
 
-建表完成后，您可以通过 [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md) 查看新建表的表结构：
+建表完成后，您可以通过 [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md) 查看新建表的表结构：
 
 ```SQL
 DESCRIBE user_behavior_inferred;
@@ -216,7 +216,7 @@ DUPLICATE KEY(UserID)
 DISTRIBUTED BY HASH(UserID);
 ```
 
-通过 [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md) 查看新建表的表结构：
+通过 [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md) 查看新建表的表结构：
 
 ```sql
 DESCRIBE user_behavior_declared;
@@ -285,13 +285,13 @@ SELECT * from user_behavior_declared LIMIT 3;
 
 #### 查看导入进度
 
-通过 StarRocks Information Schema 库中的 [`loads`](../reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。例如：
+通过 StarRocks Information Schema 库中的 [`loads`](../sql-reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。例如：
 
 ```SQL
 SELECT * FROM information_schema.loads ORDER BY JOB_ID DESC;
 ```
 
-有关 `loads` 视图提供的字段详情，参见 [`loads`](../reference/information_schema/loads.md)。
+有关 `loads` 视图提供的字段详情，参见 [`loads`](../sql-reference/information_schema/loads.md)。
 
 如果您提交了多个导入作业，您可以通过 `LABEL` 过滤出想要查看的作业。例如：
 
@@ -417,17 +417,17 @@ PROPERTIES
 - `BROKER`：连接数据源的认证信息配置。
 - `PROPERTIES`：用于指定超时时间等可选的作业属性。
 
-有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 #### 查看导入进度
 
-通过 StarRocks Information Schema 库中的 [`loads`](../reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。
+通过 StarRocks Information Schema 库中的 [`loads`](../sql-reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。
 
 ```SQL
 SELECT * FROM information_schema.loads;
 ```
 
-有关 `loads` 视图提供的字段详情，参见 [`loads`](../reference/information_schema/loads.md)。
+有关 `loads` 视图提供的字段详情，参见 [`loads`](../sql-reference/information_schema/loads.md)。
 
 如果您提交了多个导入作业，您可以通过 `LABEL` 过滤出想要查看的作业。例如：
 
diff --git a/docs/zh/loading/hdfs_load.md b/docs/zh/loading/hdfs_load.md
index 1f7127d6e4b5ff..d8722f290a7a46 100644
--- a/docs/zh/loading/hdfs_load.md
+++ b/docs/zh/loading/hdfs_load.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 keywords: ['Broker Load']
 ---
@@ -38,9 +38,9 @@ StarRocks 支持通过以下方式从 HDFS 导入数据：
 
 通过 `FILES()`，您可以：
 
-- 使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句直接从 HDFS 查询数据。
-- 通过 [CREATE TABLE AS SELECT](../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md)（简称 CTAS）语句实现自动建表和导入数据。
-- 手动建表，然后通过 [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md) 导入数据。
+- 使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句直接从 HDFS 查询数据。
+- 通过 [CREATE TABLE AS SELECT](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md)（简称 CTAS）语句实现自动建表和导入数据。
+- 手动建表，然后通过 [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md) 导入数据。
 
 ### 操作示例
 
@@ -115,7 +115,7 @@ SELECT * FROM FILES
 );
 ```
 
-建表完成后，您可以通过 [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md) 查看新建表的表结构：
+建表完成后，您可以通过 [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md) 查看新建表的表结构：
 
 ```SQL
 DESCRIBE user_behavior_inferred;
@@ -194,7 +194,7 @@ DUPLICATE KEY(UserID)
 DISTRIBUTED BY HASH(UserID);
 ```
 
-通过 [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md) 查看新建表的表结构：
+通过 [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md) 查看新建表的表结构：
 
 ```sql
 DESCRIBE user_behavior_declared;
@@ -265,7 +265,7 @@ SELECT * from user_behavior_declared LIMIT 3;
 SELECT * FROM information_schema.loads ORDER BY JOB_ID DESC;
 ```
 
-有关 `loads` 视图提供的字段详情，参见 [`loads`](../reference/information_schema/loads.md)。
+有关 `loads` 视图提供的字段详情，参见 [`loads`](../sql-reference/information_schema/loads.md)。
 
 如果您提交了多个导入作业，您可以通过 `LABEL` 过滤出想要查看的作业。例如：
 
@@ -385,17 +385,17 @@ PROPERTIES
 - `BROKER`：连接数据源的认证信息配置。
 - `PROPERTIES`：用于指定超时时间等可选的作业属性。
 
-有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 #### 查看导入进度
 
-通过 StarRocks Information Schema 库中的 [`loads`](../reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。
+通过 StarRocks Information Schema 库中的 [`loads`](../sql-reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。
 
 ```SQL
 SELECT * FROM information_schema.loads;
 ```
 
-有关 `loads` 视图提供的字段详情，参见 [`loads`](../reference/information_schema/loads.md)。
+有关 `loads` 视图提供的字段详情，参见 [`loads`](../sql-reference/information_schema/loads.md)。
 
 如果您提交了多个导入作业，您可以通过 `LABEL` 过滤出想要查看的作业。例如：
 
@@ -520,11 +520,11 @@ SELECT * FROM FILES
 - `INSERT_SQL`：INSERT INTO SELECT FROM FILES 语句，用于从指定的源数据文件导入数据到目标表。
 - `PROPERTIES`：用于控制 Pipe 执行的一些参数，例如 `AUTO_INGEST`、`POLL_INTERVAL`、`BATCH_SIZE` 和 `BATCH_FILES`，格式为 `"key" = "value"`。
 
-有关详细的语法和参数说明，参见 [CREATE PIPE](../sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md)。
+有关详细的语法和参数说明，参见 [CREATE PIPE](../sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md)。
 
 #### 查看导入进度
 
-- 通过 [SHOW PIPES](../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md) 查看当前数据库中的导入作业。
+- 通过 [SHOW PIPES](../sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md) 查看当前数据库中的导入作业。
 
   ```SQL
   SHOW PIPES;
@@ -546,7 +546,7 @@ SELECT * FROM FILES
   1 row in set (0.00 sec)
   ```
 
-- 通过 StarRocks Information Schema 库中的 [`pipes`](../reference/information_schema/pipes.md) 视图查看当前数据库中的导入作业。
+- 通过 StarRocks Information Schema 库中的 [`pipes`](../sql-reference/information_schema/pipes.md) 视图查看当前数据库中的导入作业。
 
   ```SQL
   SELECT * FROM information_schema.pipes;
@@ -570,7 +570,7 @@ SELECT * FROM FILES
 
 #### 查看导入的文件信息
 
-您可以通过 StarRocks Information Schema 库中的 [`pipe_files`](../reference/information_schema/pipe_files.md) 视图查看导入的文件信息。
+您可以通过 StarRocks Information Schema 库中的 [`pipe_files`](../sql-reference/information_schema/pipe_files.md) 视图查看导入的文件信息。
 
 ```SQL
 SELECT * FROM information_schema.pipe_files;
@@ -598,4 +598,4 @@ FINISH_LOAD_TIME: 2023-11-17 16:13:22
 
 #### 管理导入作业
 
-创建 Pipe 导入作业以后，您可以根据需要对这些作业进行修改、暂停或重新启动、删除、查询、以及尝试重新导入等操作。详情参见 [ALTER PIPE](../sql-reference/sql-statements/data-manipulation/ALTER_PIPE.md)、[SUSPEND or RESUME PIPE](../sql-reference/sql-statements/data-manipulation/SUSPEND_or_RESUME_PIPE.md)、[DROP PIPE](../sql-reference/sql-statements/data-manipulation/DROP_PIPE.md)、[SHOW PIPES](../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md)、[RETRY FILE](../sql-reference/sql-statements/data-manipulation/RETRY_FILE.md)。
+创建 Pipe 导入作业以后，您可以根据需要对这些作业进行修改、暂停或重新启动、删除、查询、以及尝试重新导入等操作。详情参见 [ALTER PIPE](../sql-reference/sql-statements/loading_unloading/pipe/ALTER_PIPE.md)、[SUSPEND or RESUME PIPE](../sql-reference/sql-statements/loading_unloading/pipe/SUSPEND_or_RESUME_PIPE.md)、[DROP PIPE](../sql-reference/sql-statements/loading_unloading/pipe/DROP_PIPE.md)、[SHOW PIPES](../sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md)、[RETRY FILE](../sql-reference/sql-statements/loading_unloading/pipe/RETRY_FILE.md)。
diff --git a/docs/zh/loading/load_concept/strict_mode.md b/docs/zh/loading/load_concept/strict_mode.md
index 752c21a73fabcf..cf888f9fb4fcaa 100644
--- a/docs/zh/loading/load_concept/strict_mode.md
+++ b/docs/zh/loading/load_concept/strict_mode.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 严格模式
@@ -22,7 +22,7 @@ displayed_sidebar: "Chinese"
 
 - 实际导入过程中，正确的数据行和错误的数据行都有可能存在 `NULL` 值。如果目标列不允许 `NULL` 值，则 StarRocks 会报错，并把这些包含 `NULL` 值的数据行过滤掉。
 
-- 对于 [Stream Load](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)、[Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)、[Routine Load](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md) 和 [Spark Load](../../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md)，导入作业能够容忍的因数据质量不合格而过滤掉的错误数据行所占的最大比例，由作业的可选参数 `max_filter_ratio` 控制。[INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 导入方式当前不支持 `max_filter_ratio` 参数。
+- 对于 [Stream Load](../../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)、[Broker Load](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)、[Routine Load](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md) 和 [Spark Load](../../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md)，导入作业能够容忍的因数据质量不合格而过滤掉的错误数据行所占的最大比例，由作业的可选参数 `max_filter_ratio` 控制。[INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 导入方式当前不支持 `max_filter_ratio` 参数。
 
 下面以 CSV 格式的数据文件为例来说明严格模式的效果。假设目标列数据类型为 TINYINT [-128, 127]。以 `\N`（表示空值 null）、`abc`、`2000` 和 `1` 四个原始列值为例：
 
@@ -60,7 +60,7 @@ displayed_sidebar: "Chinese"
 
 ## 设置严格模式
 
-使用 [Stream Load](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)、[Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)、[Routine Load](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md) 和 [Spark Load](../../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md) 执行数据导入时，需要通过参数 `strict_mode` 来设置严格模式。参数取值范围：`true` 和 `false`。默认值：`false`。`true` 表示开启，`false` 表示关闭。
+使用 [Stream Load](../../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)、[Broker Load](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)、[Routine Load](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md) 和 [Spark Load](../../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md) 执行数据导入时，需要通过参数 `strict_mode` 来设置严格模式。参数取值范围：`true` 和 `false`。默认值：`false`。`true` 表示开启，`false` 表示关闭。
 
 使用 [INSERT](../../loading/InsertInto.md) 执行数据导入时，需要通过会话变量 `enable_insert_strict` 来设置严格模式。变量取值范围：`true` 和 `false`。默认值：`true`。`true` 表示开启，`false` 表示关闭。
 
@@ -75,7 +75,7 @@ curl --location-trusted -u <username>:<password> \
     http://<fe_host>:<fe_http_port>/api/<database_name>/<table_name>/_stream_load
 ```
 
-有关 Stream Load 的语法和参数说明，请参见 [STREAM LOAD](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)。
+有关 Stream Load 的语法和参数说明，请参见 [STREAM LOAD](../../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。
 
 ### Broker Load
 
@@ -96,7 +96,7 @@ PROPERTIES
 )
 ```
 
-这里以 HDFS 数据源为例。有关 Broker Load 的语法和参数说明，请参见 [BROKER LOAD](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+这里以 HDFS 数据源为例。有关 Broker Load 的语法和参数说明，请参见 [BROKER LOAD](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 ### Routine Load
 
@@ -113,7 +113,7 @@ FROM KAFKA
 )
 ```
 
-这里以 Apache Kafka® 数据源为例。有关 Routine Load 的语法和参数说明，请参见 [CREATE ROUTINE LOAD](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md)。
+这里以 Apache Kafka® 数据源为例。有关 Routine Load 的语法和参数说明，请参见 [CREATE ROUTINE LOAD](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md)。
 
 ### Spark Load
 
@@ -135,7 +135,7 @@ PROPERTIES
 )
 ```
 
-这里以 HDFS 数据源为例。有关 Spark Load 的语法和参数说明，请参见 [SPARK LOAD](../../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md)。
+这里以 HDFS 数据源为例。有关 Spark Load 的语法和参数说明，请参见 [SPARK LOAD](../../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md)。
 
 ### INSERT
 
@@ -144,4 +144,4 @@ SET enable_insert_strict = {true | false};
 INSERT INTO <table_name> ...
 ```
 
-有关 INSERT 的语法和参数说明，请参见 [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md)。
+有关 INSERT 的语法和参数说明，请参见 [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md)。
diff --git a/docs/zh/loading/load_from_pulsar.md b/docs/zh/loading/load_from_pulsar.md
index 8a441de37aec30..09191c69472ddf 100644
--- a/docs/zh/loading/load_from_pulsar.md
+++ b/docs/zh/loading/load_from_pulsar.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 【公测中】从 Apache® Pulsar™ 持续导入
@@ -46,7 +46,7 @@ Topic 负责存储和发布消息。Producer 往 Topic 中写消息，Consumer 
 
 ## 创建导入作业
 
-通过 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md) 语句，向StarRocks 提交一个 Routine Load 导入作业 `routine_wiki_edit_1`，持续消费 Pulsar 集群中 Topic `ordertest1`  的消息， 并且使用 Subscription  `load-test`，指定消费分区为 `load-partition-0`，`load-partition-1`，分区对应的消费起始 Position 分别为 Partition 有数据的位置开始消费、Partition 末尾开始消费。并导入至数据库 `load_test` 的表 `routine_wiki_edit` 中。
+通过 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md) 语句，向StarRocks 提交一个 Routine Load 导入作业 `routine_wiki_edit_1`，持续消费 Pulsar 集群中 Topic `ordertest1`  的消息， 并且使用 Subscription  `load-test`，指定消费分区为 `load-partition-0`，`load-partition-1`，分区对应的消费起始 Position 分别为 Partition 有数据的位置开始消费、Partition 末尾开始消费。并导入至数据库 `load_test` 的表 `routine_wiki_edit` 中。
 
 ```SQL
 CREATE ROUTINE LOAD load_test.routine_wiki_edit_1 ON routine_wiki_edit
@@ -93,7 +93,7 @@ Routine Load 还支持自定义 Pulsar 参数，如下表所述。
 
 ### 查看导入作业
 
-提交 Routine Load 导入作业以后，您可以执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) 语句来查看导入作业的信息。例如，您可以通过如下命令查看一个名为 `routine_wiki_edit_1` 的导入作业的信息：
+提交 Routine Load 导入作业以后，您可以执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) 语句来查看导入作业的信息。例如，您可以通过如下命令查看一个名为 `routine_wiki_edit_1` 的导入作业的信息：
 
 ```Plaintext
 MySQL [load_test] > SHOW ROUTINE LOAD for routine_wiki_edit_1 \G
@@ -123,7 +123,7 @@ ReasonOfStateChanged:
 
 ### 查看导入任务
 
-提交 Routine Load 导入作业以后，您可以执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md)，查看导入作业中一个或多个导入任务的信息。例如，您可以通过如下命令查看一个名为 `routine_wiki_edit_1`的导入作业中一个或多个导入任务的信息。比如当前有多少任务正在运行，消费分区及进度`DataSourceProperties`，以及对应的 Coordinator BE 节点 `BeId`。
+提交 Routine Load 导入作业以后，您可以执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md)，查看导入作业中一个或多个导入任务的信息。例如，您可以通过如下命令查看一个名为 `routine_wiki_edit_1`的导入作业中一个或多个导入任务的信息。比如当前有多少任务正在运行，消费分区及进度`DataSourceProperties`，以及对应的 Coordinator BE 节点 `BeId`。
 
 ```SQL
 MySQL [example_db]> SHOW ROUTINE LOAD TASK WHERE JobName = "routine_wiki_edit_1" \G
@@ -133,11 +133,11 @@ MySQL [example_db]> SHOW ROUTINE LOAD TASK WHERE JobName = "routine_wiki_edit_1"
 
 ## 修改导入作业
 
-修改前，您需要先执行 [PAUSE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/PAUSE_ROUTINE_LOAD.md) 暂停导入作业。然后执行 [ALTER ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD.md) 语句，修改导入作业的参数配置。修改成功后，您需要执行 [RESUME ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md)，恢复导入作业。然后执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) 语句查看修改后的导入作业。
+修改前，您需要先执行 [PAUSE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/PAUSE_ROUTINE_LOAD.md) 暂停导入作业。然后执行 [ALTER ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md) 语句，修改导入作业的参数配置。修改成功后，您需要执行 [RESUME R../sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.mdUTINE_LOAD.md)，恢复导入作业。然后执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) 语句查看修改后的导入作业。
 
 消费 Pulsar 集群中的数据，除了 `data_source_properties` 外的参数修改方式与[消费 Kafka](./RoutineLoad.md#修改导入作业)  时相同。
 
-修改前，您需要先执行 [PAUSE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/PAUSE_ROUTINE_LOAD.md) 暂停导入作业。然后执行 [ALTER ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD.md) 语句，修改导入作业的参数配置。修改成功后，您需要执行 [RESUME ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md)，恢复导入作业。然后执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md) 语句查看修改后的导入作业。
+修改前，您需要先执行 [PAUSE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/PAUSE_ROUTINE_LOAD.md) 暂停导入作业。然后执行 [ALTER ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md) 语句，修改导入作业的参数配置。修改成功后，您需要执行 [RESUME R../sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.mdUTINE_LOAD.md)，恢复导入作业。然后执行 [SHOW ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md) 语句查看修改后的导入作业。
 
 消费 Pulsar 集群中的数据，除了 `data_source_properties` 外的参数修改方式与[消费 Kafka](./RoutineLoad.md#修改导入作业)  时相同。
 
diff --git a/docs/zh/loading/loading.mdx b/docs/zh/loading/loading.mdx
index ec983e6ca11d30..373d3aabf363c7 100644
--- a/docs/zh/loading/loading.mdx
+++ b/docs/zh/loading/loading.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Data loading
diff --git a/docs/zh/loading/loading_introduction/Loading_intro.md b/docs/zh/loading/loading_introduction/Loading_intro.md
index 751509fae83ec8..12ea57af351f5e 100644
--- a/docs/zh/loading/loading_introduction/Loading_intro.md
+++ b/docs/zh/loading/loading_introduction/Loading_intro.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 3
 ---
 
@@ -55,7 +55,7 @@ StarRocks 提供以下各种导入方案供您选择：
 
 **单次导入数据量限制：** 根据内存大小的不同而不同
 
-### [Stream Load](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)
+### [Stream Load](../../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)
 
 **适用场景：** 从本地文件系统批量导入数据。
 
@@ -63,7 +63,7 @@ StarRocks 提供以下各种导入方案供您选择：
 
 **单次导入数据量限制：** 10 GB 以内
 
-### [Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)
+### [Broker Load](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)
 
 **适用场景：**
 
@@ -74,7 +74,7 @@ StarRocks 提供以下各种导入方案供您选择：
 
 **单次导入数据量限制：** 数十到数百 GB
 
-### [Pipe](../../sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md)
+### [Pipe](../../sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md)
 
 **适用场景：** 从 HDFS 或 AWS S3 批量或实时导入数据。
 
@@ -88,7 +88,7 @@ StarRocks 提供以下各种导入方案供您选择：
 
 **单次导入数据量限制：** 100 GB 到 TB 级别
 
-### [Routine Load](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md)
+### [Routine Load](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md)
 
 **适用场景：** 从 Kafka 实时导入数据。
 
@@ -96,7 +96,7 @@ StarRocks 提供以下各种导入方案供您选择：
 
 **单次导入数据量限制：** 微批导入 MB 到 GB 级别
 
-### [Spark Load](../../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md)
+### [Spark Load](../../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md)
 
 **适用场景：** 通过 Spark 集群从 HDFS 批量导入 Apache Hive™ 表的数据。
 
diff --git a/docs/zh/loading/loading_introduction/feature-support-loading-and-unloading.md b/docs/zh/loading/loading_introduction/feature-support-loading-and-unloading.md
index e0d333af3386a0..f007a7e6c8668e 100644
--- a/docs/zh/loading/loading_introduction/feature-support-loading-and-unloading.md
+++ b/docs/zh/loading/loading_introduction/feature-support-loading-and-unloading.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: "能力边界"
 ---
 
diff --git a/docs/zh/loading/loading_introduction/loading_concepts.md b/docs/zh/loading/loading_introduction/loading_concepts.md
index fe70eb80e25b7d..dc811e6a9abf4b 100644
--- a/docs/zh/loading/loading_introduction/loading_concepts.md
+++ b/docs/zh/loading/loading_introduction/loading_concepts.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 ---
 
@@ -27,7 +27,7 @@ StarRocks 支持通过以下两种访问协议来提交导入作业：MySQL 和
 
 ## 支持的数据类型
 
-StarRocks 支持导入所有数据类型。个别数据类型的导入可能会存在一些限制，具体请参见[数据类型](../../sql-reference/data-types/data-type-list.md)。
+StarRocks 支持导入所有数据类型。个别数据类型的导入可能会存在一些限制，具体请参见[数据类型](../../sql-reference/data-types/README.md)。
 
 ## 严格模式
 
@@ -66,11 +66,11 @@ StarRocks 支持两种导入模式：同步导入和异步导入。
 
 :::tip
 
-如果您的 StarRocks 集群有多数据副本，您可以根据业务需求为表设置不同导入数据安全等级，即设置需要多少数据副本导入成功后 StarRocks 可返回导入成功。您可在 [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md) 时通过增加属性（PROPERTIES） `write_quorum` 指定导入数据安全等级，或通过 [ALTER TABLE](../../sql-reference/sql-statements/data-definition/ALTER_TABLE.md) 语句为已有 Table 添加该属性。该属性从 2.5 版本开始支持。
+如果您的 StarRocks 集群有多数据副本，您可以根据业务需求为表设置不同导入数据安全等级，即设置需要多少数据副本导入成功后 StarRocks 可返回导入成功。您可在 [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md) 时通过增加属性（PROPERTIES） `write_quorum` 指定导入数据安全等级，或通过 [ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) 语句为已有 Table 添加该属性。该属性从 2.5 版本开始支持。
 
 :::
 
-支持异步模式的导入方式有 [Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)、[Pipe](../../sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md)、[Routine Load](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md) 和 [Spark Load](../../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md)。
+支持异步模式的导入方式有 [Broker Load](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)、[Pipe](../../sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md)、[Routine Load](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md) 和 [Spark Load](../../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md)。
 
 用户操作过程如下：
 
diff --git a/docs/zh/loading/loading_introduction/loading_considerations.md b/docs/zh/loading/loading_introduction/loading_considerations.md
index 5b2df89fb6bad7..5e1df72e92f9eb 100644
--- a/docs/zh/loading/loading_introduction/loading_considerations.md
+++ b/docs/zh/loading/loading_introduction/loading_considerations.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 ---
 
@@ -11,7 +11,7 @@ toc_max_heading_level: 4
 
 您可以通过设置参数来限制单个导入作业的内存使用，以防止导入作业占用过多内存，特别是在导入并发较高的情况下。同时，您也需要注意避免设置过小的内存使用上限，因为内存使用上限过小，导入过程中可能会因为内存使用量达到上限而频繁地将内存中的数据刷出到磁盘，进而可能影响导入效率。建议您根据具体的业务场景要求，合理地设置内存使用上限。
 
-不同的导入方式限制内存的方式略有不同，具体请参见 [Stream Load](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)、[Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)、[Routine Load](../../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md)、[Spark Load](../../sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md) 和 [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md)。需要注意的是，一个导入作业通常都会分布在多个 BE（或 CN）上执行，这些内存参数限制的是一个导入作业在单个 BE（或 CN）上的内存使用，而不是在整个集群上的内存使用总和。
+不同的导入方式限制内存的方式略有不同，具体请参见 [Stream Load](../../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)、[Broker Load](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)、[Routine Load](../../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md)、[Spark Load](../../sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md) 和 [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md)。需要注意的是，一个导入作业通常都会分布在多个 BE（或 CN）上执行，这些内存参数限制的是一个导入作业在单个 BE（或 CN）上的内存使用，而不是在整个集群上的内存使用总和。
 
 您还可以通过设置一些参数来限制在单个 BE（或 CN）上运行的所有导入作业的总的内存使用上限。可参考下面的“[系统配置](#系统配置)”章节。
 
@@ -68,7 +68,7 @@ toc_max_heading_level: 4
 
 ### 会话变量
 
-您可以设置如下[会话变量](../../reference/System_variable.md)：
+您可以设置如下[会话变量](../../sql-reference/System_variable.md)：
 
 - `query_timeout`
 
diff --git a/docs/zh/loading/loading_introduction/loading_overview.mdx b/docs/zh/loading/loading_introduction/loading_overview.mdx
index cd81101560e264..4e74a5677e8b4f 100644
--- a/docs/zh/loading/loading_introduction/loading_overview.mdx
+++ b/docs/zh/loading/loading_introduction/loading_overview.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 导入概览
diff --git a/docs/zh/loading/minio.md b/docs/zh/loading/minio.md
index 60c3a76bb15141..2f3fa8b500b444 100644
--- a/docs/zh/loading/minio.md
+++ b/docs/zh/loading/minio.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 ---
 
@@ -9,8 +9,8 @@ import InsertPrivNote from '../_assets/commonMarkdown/insertPrivNote.md'
 
 StarRocks 支持通过以下方式从 MinIO 导入数据：
 
-- 使用 [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md)+[`FILES()`](../sql-reference/sql-functions/table-functions/files.md) 进行同步导入。
-- 使用 [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 进行异步导入。
+- 使用 [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md)+[`FILES()`](../sql-reference/sql-functions/table-functions/files.md) 进行同步导入。
+- 使用 [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 进行异步导入。
 
 两种导入方式各有优势，具体将在下面分章节详细阐述。
 
@@ -57,9 +57,9 @@ curl -O https://starrocks-examples.s3.amazonaws.com/user_behavior_ten_million_ro
 
 通过 `FILES()`，您可以：
 
-- 使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句直接从 MinIO 查询数据。
-- 通过 [CREATE TABLE AS SELECT](../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md)（简称 CTAS）语句实现自动建表和导入数据。
-- 手动建表，然后通过 [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md) 导入数据。
+- 使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句直接从 MinIO 查询数据。
+- 通过 [CREATE TABLE AS SELECT](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md)（简称 CTAS）语句实现自动建表和导入数据。
+- 手动建表，然后通过 [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md) 导入数据。
 
 ### 操作示例
 
@@ -261,7 +261,7 @@ PROPERTIES
 );
 ```
 
-通过 [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md) 查看新建表的表结构：
+通过 [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md) 查看新建表的表结构：
 
 ```SQL
 DESCRIBE user_behavior_declared;
@@ -341,13 +341,13 @@ SELECT * from user_behavior_declared LIMIT 3;
 
 #### 查看导入进度
 
-通过 StarRocks Information Schema 库中的 [`loads`](../reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。例如：
+通过 StarRocks Information Schema 库中的 [`loads`](../sql-reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。例如：
 
 ```SQL
 SELECT * FROM information_schema.loads ORDER BY JOB_ID DESC;
 ```
 
-有关 `loads` 视图提供的字段详情，参见 [`loads`](../reference/information_schema/loads.md)。
+有关 `loads` 视图提供的字段详情，参见 [`loads`](../sql-reference/information_schema/loads.md)。
 
 如果您提交了多个导入作业，您可以通过 `LABEL` 过滤出想要查看的作业。例如：
 
@@ -514,17 +514,17 @@ PROPERTIES
 - `BROKER`：连接数据源的认证信息配置。
 - `PROPERTIES`：用于指定超时时间等可选的作业属性。
 
-有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 #### 查看导入进度
 
-通过 StarRocks Information Schema 库中的 [`loads`](../reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。例如：
+通过 StarRocks Information Schema 库中的 [`loads`](../sql-reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。例如：
 
 ```SQL
 SELECT * FROM information_schema.loads;
 ```
 
-有关 `loads` 视图提供的字段详情，参见 [`loads`](../reference/information_schema/loads.md)。
+有关 `loads` 视图提供的字段详情，参见 [`loads`](../sql-reference/information_schema/loads.md)。
 
 如果您提交了多个导入作业，您可以通过 `LABEL` 过滤出想要查看的作业。例如：
 
diff --git a/docs/zh/loading/objectstorage.mdx b/docs/zh/loading/objectstorage.mdx
index ccfa55e0cf61b6..a3d0ceb1637cb3 100644
--- a/docs/zh/loading/objectstorage.mdx
+++ b/docs/zh/loading/objectstorage.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 description: "Load from S3, GCS, Azure, and MinIO"
 ---
 
diff --git a/docs/zh/loading/s3.md b/docs/zh/loading/s3.md
index 370858d76ab745..afc04826acfd56 100644
--- a/docs/zh/loading/s3.md
+++ b/docs/zh/loading/s3.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 keywords: ['Broker Load']
 ---
@@ -28,7 +28,7 @@ StarRocks 支持通过以下方式从 AWS S3 导入数据：
 
 ### 获取资源访问配置
 
-本文的示例均使用基于 IAM User 的认证方式。为确保您能够顺利访问存储在 AWS S3 中的数据，建议您根据“[基于 IAM User 认证鉴权](../integrations/authenticate_to_aws_resources.md)中介绍的准备工作，创建 IAM User、并配置 [IAM 策略](../reference/aws_iam_policies.md)。
+本文的示例均使用基于 IAM User 的认证方式。为确保您能够顺利访问存储在 AWS S3 中的数据，建议您根据“[基于 IAM User 认证鉴权](../integrations/authenticate_to_aws_resources.md)中介绍的准备工作，创建 IAM User、并配置 [IAM 策略](../sql-reference/aws_iam_policies.md)。
 
 概括来说，如果选择使用基于 IAM User 的认证方式，您需要提前获取以下 AWS 资源信息：
 
@@ -49,9 +49,9 @@ StarRocks 支持通过以下方式从 AWS S3 导入数据：
 
 通过 `FILES()`，您可以：
 
-- 使用 [SELECT](../sql-reference/sql-statements/data-manipulation/SELECT.md) 语句直接从 AWS S3 查询数据。
-- 通过 [CREATE TABLE AS SELECT](../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md)（简称 CTAS）语句实现自动建表和导入数据。
-- 手动建表，然后通过 [INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md) 导入数据。
+- 使用 [SELECT](../sql-reference/sql-statements/table_bucket_part_index/SELECT.md) 语句直接从 AWS S3 查询数据。
+- 通过 [CREATE TABLE AS SELECT](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md)（简称 CTAS）语句实现自动建表和导入数据。
+- 手动建表，然后通过 [INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md) 导入数据。
 
 ### 操作示例
 
@@ -134,7 +134,7 @@ SELECT * FROM FILES
 >
 > 把上面命令示例中的 `AAA` 和 `BBB` 替换成真实有效的 Access Key 和 Secret Key 作为访问凭证。由于这里使用的数据对象对所有合法的 AWS 用户开放，因此您填入任何真实有效的 Access Key 和 Secret Key 都可以。
 
-建表完成后，您可以通过 [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md) 查看新建表的表结构：
+建表完成后，您可以通过 [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md) 查看新建表的表结构：
 
 ```SQL
 DESCRIBE user_behavior_inferred;
@@ -213,7 +213,7 @@ DUPLICATE KEY(UserID)
 DISTRIBUTED BY HASH(UserID);
 ```
 
-通过 [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md) 查看新建表的表结构：
+通过 [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md) 查看新建表的表结构：
 
 ```sql
 DESCRIBE user_behavior_declared;
@@ -282,13 +282,13 @@ SELECT * from user_behavior_declared LIMIT 3;
 
 #### 查看导入进度
 
-通过 StarRocks Information Schema 库中的 [`loads`](../reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。例如：
+通过 StarRocks Information Schema 库中的 [`loads`](../sql-reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。例如：
 
 ```SQL
 SELECT * FROM information_schema.loads ORDER BY JOB_ID DESC;
 ```
 
-有关 `loads` 视图提供的字段详情，参见 [`loads`](../reference/information_schema/loads.md)。
+有关 `loads` 视图提供的字段详情，参见 [`loads`](../sql-reference/information_schema/loads.md)。
 
 如果您提交了多个导入作业，您可以通过 `LABEL` 过滤出想要查看的作业。例如：
 
@@ -414,17 +414,17 @@ PROPERTIES
 - `BROKER`：连接数据源的认证信息配置。
 - `PROPERTIES`：用于指定超时时间等可选的作业属性。
 
-有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+有关详细的语法和参数说明，参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 #### 查看导入进度
 
-通过 StarRocks Information Schema 库中的 [`loads`](../reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。
+通过 StarRocks Information Schema 库中的 [`loads`](../sql-reference/information_schema/loads.md) 视图查看导入作业的进度。该功能自 3.1 版本起支持。
 
 ```SQL
 SELECT * FROM information_schema.loads WHERE LABEL = 'user_behavior';
 ```
 
-有关 `loads` 视图提供的字段详情，参见 [`loads`](../reference/information_schema/loads.md)。
+有关 `loads` 视图提供的字段详情，参见 [`loads`](../sql-reference/information_schema/loads.md)。
 
 系统返回如下结果，作业状态为 `LOADING`，进度为 39%。您可以重复执行上面命令，直到作业状态显示为 `FINISHED`。
 
@@ -566,11 +566,11 @@ SELECT * FROM FILES
 - `INSERT_SQL`：INSERT INTO SELECT FROM FILES 语句，用于从指定的源数据文件导入数据到目标表。
 - `PROPERTIES`：用于控制 Pipe 执行的一些参数，例如 `AUTO_INGEST`、`POLL_INTERVAL`、`BATCH_SIZE` 和 `BATCH_FILES`，格式为 `"key" = "value"`。
 
-有关详细的语法和参数说明，参见 [CREATE PIPE](../sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md)。
+有关详细的语法和参数说明，参见 [CREATE PIPE](../sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md)。
 
 #### 查看导入进度
 
-- 在当前数据库中通过 [SHOW PIPES](../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md) 查看导入作业。
+- 在当前数据库中通过 [SHOW PIPES](../sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md) 查看导入作业。
 
   ```SQL
   SHOW PIPES WHERE NAME = 'user_behavior_pipe' \G
@@ -597,7 +597,7 @@ SELECT * FROM FILES
   1 row in set (0.02 sec)
   ```
 
-- 通过 StarRocks Information Schema 库中的 [`pipes`](../reference/information_schema/pipes.md) 视图查看当前数据库中的导入作业。
+- 通过 StarRocks Information Schema 库中的 [`pipes`](../sql-reference/information_schema/pipes.md) 视图查看当前数据库中的导入作业。
 
   ```SQL
   SELECT * FROM information_schema.pipes WHERE pipe_name = 'uuser_behavior_pipe' \G
@@ -624,7 +624,7 @@ SELECT * FROM FILES
 
 #### 查看导入的文件信息
 
-您可以通过 StarRocks Information Schema 库中的 [`pipe_files`](../reference/information_schema/pipe_files.md) 视图查看导入的文件信息。
+您可以通过 StarRocks Information Schema 库中的 [`pipe_files`](../sql-reference/information_schema/pipe_files.md) 视图查看导入的文件信息。
 
 ```SQL
 SELECT * FROM information_schema.pipe_files WHERE pipe_name = 'user_behavior_replica' \G
@@ -651,4 +651,4 @@ FINISH_LOAD_TIME: 2023-11-09 15:35:42
 
 #### 管理导入作业
 
-创建 Pipe 导入作业以后，您可以根据需要对这些作业进行修改、暂停或重新启动、删除、查询、以及尝试重新导入等操作。详情参见 [ALTER PIPE](../sql-reference/sql-statements/data-manipulation/ALTER_PIPE.md)、[SUSPEND or RESUME PIPE](../sql-reference/sql-statements/data-manipulation/SUSPEND_or_RESUME_PIPE.md)、[DROP PIPE](../sql-reference/sql-statements/data-manipulation/DROP_PIPE.md)、[SHOW PIPES](../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md)、[RETRY FILE](../sql-reference/sql-statements/data-manipulation/RETRY_FILE.md)。
+创建 Pipe 导入作业以后，您可以根据需要对这些作业进行修改、暂停或重新启动、删除、查询、以及尝试重新导入等操作。详情参见 [ALTER PIPE](../sql-reference/sql-statements/loading_unloading/pipe/ALTER_PIPE.md)、[SUSPEND or RESUME PIPE](../sql-reference/sql-statements/loading_unloading/pipe/SUSPEND_or_RESUME_PIPE.md)、[DROP PIPE](../sql-reference/sql-statements/loading_unloading/pipe/DROP_PIPE.md)、[SHOW PIPES](../sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md)、[RETRY FILE](../sql-reference/sql-statements/loading_unloading/pipe/RETRY_FILE.md)。
diff --git a/docs/zh/project_help/project_help.mdx b/docs/zh/project_help/project_help.mdx
index 60fe0f0cb458ed..cc8f8d604ee303 100644
--- a/docs/zh/project_help/project_help.mdx
+++ b/docs/zh/project_help/project_help.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 技术支持
diff --git a/docs/zh/project_help/slack.md b/docs/zh/project_help/slack.md
index 43d82333815179..68be1bc13e78b6 100644
--- a/docs/zh/project_help/slack.md
+++ b/docs/zh/project_help/slack.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: "支持渠道"
 description: "与社区互动"
 ---
diff --git a/docs/zh/quick_start/helm.md b/docs/zh/quick_start/helm.md
index b880ff79b162cc..9f5b3e7b773c27 100644
--- a/docs/zh/quick_start/helm.md
+++ b/docs/zh/quick_start/helm.md
@@ -1,6 +1,6 @@
 ---
 description: 使用 Helm 部署 StarRocks
-displayed_sidebar: Chinese
+displayed_sidebar: docs
 ---
 
 import Tabs from '@theme/Tabs';
@@ -601,7 +601,7 @@ helm delete starrocks
 
 默认 [`values.yaml`](https://github.com/StarRocks/starrocks-kubernetes-operator/blob/main/helm-charts/charts/kube-starrocks/values.yaml)
 
-[Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)
+[Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)
 
 [Motor Vehicle Collisions - Crashes](https://data.cityofnewyork.us/Public-Safety/Motor-Vehicle-Collisions-Crashes/h9gi-nx95) 数据集由纽约市提供，受以下 [使用条款](https://www.nyc.gov/home/terms-of-use.page) 和 [隐私政策](https://www.nyc.gov/home/privacy-policy.page) 约束。
 
diff --git a/docs/zh/quick_start/hudi.md b/docs/zh/quick_start/hudi.md
index 08ea1d2a4ca26f..96e6f003d307bb 100644
--- a/docs/zh/quick_start/hudi.md
+++ b/docs/zh/quick_start/hudi.md
@@ -1,4 +1,4 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 unlisted: true
 ---
\ No newline at end of file
diff --git a/docs/zh/quick_start/iceberg.md b/docs/zh/quick_start/iceberg.md
index a780a6edd5ef5c..a1171a1b67cc6d 100644
--- a/docs/zh/quick_start/iceberg.md
+++ b/docs/zh/quick_start/iceberg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_position: 3
 description: "湖仓分析"
 toc_max_heading_level: 2
diff --git a/docs/zh/quick_start/quick_start.mdx b/docs/zh/quick_start/quick_start.mdx
index fd8fb34380ff67..967181d9a9d11d 100644
--- a/docs/zh/quick_start/quick_start.mdx
+++ b/docs/zh/quick_start/quick_start.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 快速入门信息
diff --git a/docs/zh/quick_start/routine-load.md b/docs/zh/quick_start/routine-load.md
index 08ea1d2a4ca26f..96e6f003d307bb 100644
--- a/docs/zh/quick_start/routine-load.md
+++ b/docs/zh/quick_start/routine-load.md
@@ -1,4 +1,4 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 unlisted: true
 ---
\ No newline at end of file
diff --git a/docs/zh/quick_start/shared-data.md b/docs/zh/quick_start/shared-data.md
index 12268e018e2342..26c820060ca7c2 100644
--- a/docs/zh/quick_start/shared-data.md
+++ b/docs/zh/quick_start/shared-data.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_position: 2
 description: "存算分离"
 keywords: ['cunsuan']
@@ -468,6 +468,6 @@ MinIO 端点，包括端口号。
 
 - [StarRocks 表设计](../table_design/StarRocks_table_design.md)
 - [物化视图](../cover_pages/mv_use_cases.mdx)
-- [Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)
+- [Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)
 - [纽约市交通事故数据](https://data.cityofnewyork.us/Public-Safety/Motor-Vehicle-Collisions-Crashes/h9gi-nx95) 数据集由纽约市提供，受到以下[使用条款](https://www.nyc.gov/home/terms-of-use.page)和[隐私政策](https://www.nyc.gov/home/privacy-policy.page)的约束。
 - [气象数据](https://www.ncdc.noaa.gov/cdo-web/datatools/lcd)(LCD)由 NOAA 提供，附带[免责声明](https://www.noaa.gov/disclaimer)和[隐私政策](https://www.noaa.gov/protecting-your-privacy)。
diff --git a/docs/zh/quick_start/shared-nothing.md b/docs/zh/quick_start/shared-nothing.md
index 5d0e42de25fd29..77b616e77142eb 100644
--- a/docs/zh/quick_start/shared-nothing.md
+++ b/docs/zh/quick_start/shared-nothing.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_position: 1
 description: "存算一体"
 ---
@@ -222,6 +222,6 @@ curl --location-trusted -u root             \
 
 - [StarRocks 表设计](../table_design/StarRocks_table_design.md)
 - [物化视图](../cover_pages/mv_use_cases.mdx)
-- [Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)
+- [Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)
 - [纽约市交通事故数据](https://data.cityofnewyork.us/Public-Safety/Motor-Vehicle-Collisions-Crashes/h9gi-nx95) 数据集由纽约市提供，受到以下[使用条款](https://www.nyc.gov/home/terms-of-use.page)和[隐私政策](https://www.nyc.gov/home/privacy-policy.page)的约束。
 - [气象数据](https://www.ncdc.noaa.gov/cdo-web/datatools/lcd)(LCD)由 NOAA 提供，附带以下[免责声明](https://www.noaa.gov/disclaimer)和[隐私政策](https://www.noaa.gov/protecting-your-privacy)。
diff --git a/docs/zh/reference/Error_code.md b/docs/zh/reference/Error_code.md
deleted file mode 100644
index 65563c00cb4d56..00000000000000
--- a/docs/zh/reference/Error_code.md
+++ /dev/null
@@ -1,149 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 错误码
-
-本节描述查询请求常见的错误码。
-
-|错误码|错误信息|
-| --- | --- |
-|1005|创建表格失败，并给出具体原因。|
-|1007|不能创建同名的数据库。|
-|1008|不能删除不存在的数据库。|
-|1044|不能访问未授权的数据库。|
-|1045|用户名及密码不匹配，不能访问系统。|
-|1046|没有指定要查询的目标数据库。|
-|1047|指定了无效的指令。|
-|1049|指定了无效的数据库。|
-|1050|已存在同名的数据表。|
-|1051|指定了无效的数据表。|
-|1052|指定的列名有歧义，不能唯一确定对应列。|
-|1053|为 Semi-Join/Anti-Join 查询指定了非法的数据列。|
-|1054|表中不存在指定的列。|
-|1058|查询语句中选择的列数目与查询结果的列数目不一致。|
-|1060|列名重复。|
-|1064|无存活的 BE 节点。|
-|1066|查询语句中出现重复的表别名。|
-|1094|线程 ID 无效。|
-|1095|非线程的拥有者不能终止线程的运行。|
-|1096|查询语句没有指定要查询或操作的数据表。|
-|1102|数据库名不正确。|
-|1104|数据表名不正确。|
-|1105|其它错误。|
-|1110|子查询中指定了重复的列。|
-|1111|在 Where 子句中非法使用聚合函数。|
-|1113|新建表的列集合不能为空。|
-|1115|使用了不支持的字符集。|
-|1130|客户端使用了未被授权的 IP 地址来访问系统。|
-|1132|没有权限修改用户密码。|
-|1141|撤销用户权限时指定了用户不具备的权限条目。|
-|1142|执行了未被授权的操作。|
-|1166|数据列名字不正确。|
-|1193|使用了无效的系统变量名字。|
-|1203|使用的活跃连接数目超过了限制。|
-|1211|不允许创建新用户。|
-|1227|执行了越权操作。|
-|1228|会话变量不能通过 SET GLOBAL 指令来修改。|
-|1229|全局变量应通过 SET GLOBAL 指令来修改。|
-|1230|相关的系统变量无缺省值。|
-|1231|给某系统变量设置了无效值。|
-|1232|给某系统变量设置了错误数据类型的值。|
-|1248|没有给内联视图设置别名。|
-|1251|客户端不支持服务器要求的用户认证协议。|
-|1286|配置的存储引擎不正确。|
-|1298|配置的时区不正确。|
-|1347|对象与期望的类型不匹配。|
-|1353|视图的 SELECT 子句中指定的列数目与其定义的列数目不相等。|
-|1364|没有给不允许 NULL 值的列设置缺省值。|
-|1372|密码长度不够。|
-|1396|用户执行的某操作运行失败。|
-|1471|指定的表不允许插入数据。|
-|1507|删除不存在的分区，且没有指定如果存在才删除的条件。|
-|1508|应该通过删除表的操作来删除所有分区。|
-|1517|出现了重复的分区名。|
-|1524|指定的插件尚未被加载。|
-|1567|分区名不正确。|
-|1621|指定的系统变量是只读的。|
-|1735|表中不存在指定的分区名。|
-|1748|不能向没有分区的表中插入数据。|
-|1749|不存在指定的分区。|
-|5000|指定的表不是 OLAP 表。|
-|5001|指定的存储过程路径无效。|
-|5002|应显示指定列名。|
-|5003|维度列应排在指标列之前。|
-|5004|表至少应包含1个维度列。|
-|5005|集群 ID 无效。|
-|5006|无效的查询规划提示。|
-|5007|冲突的查询规划提示。|
-|5008|数据插入提示仅适用于有分区的数据表。|
-|5009|PARTITION 子句不适用于向不分区的表插入数据。|
-|5010|待创建表的列数目与 SELECT 子句中的列数目不相等。|
-|5011|无法解析表引用。|
-|5012|指定的值不是一个有效数字。|
-|5013|不支持该时间单位。|
-|5014|表状态不正常。|
-|5015|分区状态不正常。|
-|5016|分区上存在数据导入任务。|
-|5017|指定列不是维度列。|
-|5018|值的格式无效。|
-|5019|数据副本与版本不匹配。|
-|5021|BE 节点已离线。|
-|5022|非分区表的分区数不为1。|
-|5023|修改表或数据的语句中没有指定任何操作。|
-|5024|任务执行超时。|
-|5025|数据插入操作失败。|
-|5026|通过 SELECT 语句创建表时使用了不支持的数据类型。|
-|5027|没有设置指定的参数。|
-|5028|没有找到指定的集群。|
-|5030|某用户没有访问集群的权限。|
-|5031|没有指定参数或参数无效。|
-|5032|没有指定集群实例数目。|
-|5034|已存在同名的集群。|
-|5035|集群实例数目配置错误。|
-|5036|集群中 BE 节点不足。|
-|5037|删除集群前应先删除所有数据库。|
-|5037|集群中不存在指定 ID 的 BE 节点。|
-|5040|不存在同名的集群。|
-|5042|没有权限。|
-|5043|实例数目应大于0。|
-|5046|源集群不存在。|
-|5047|目标集群不存在。|
-|5048|源数据库不存在。|
-|5049|目标数据库不存在。|
-|5050|没有选择集群。|
-|5051|应先将源数据库关联至目标数据库。|
-|5052|集群内部错误：BE 节点信息错误。|
-|5053|没有从源数据库到目标数据库的迁移任务。|
-|5054|指定数据库已经被关联至目标数据库，或正在迁移数据。|
-|5055|数据库关联或数据迁移不能在同一集群内执行。|
-|5056|不能删除数据库：被关联至其它数据库或正在迁移数据。|
-|5056|不能重命名数据库：被关联至其它数据库或正在迁移数据。|
-|5056|集群中 BE 节点不足。|
-|5056|集群内已存在指定数目的 BE 节点。|
-|5059|集群中存在处于下线状态的 BE 节点。|
-|5063|类型名不正确。|
-|5064|通用错误提示。|
-|5063|Colocate 功能已被管理员禁用。|
-|5063|不存在同名的 Colocate 数据表。|
-|5063|Colocate 表必须是 OLAP 表。|
-|5063|Colocate 表应该具有同样的副本数目。|
-|5063|Colocate 表应该具有同样的分桶数目。|
-|5063|Colocate 表的分区列数目应该一致。|
-|5063|Colocate 表的分区列的数据类型应该一致。|
-|5064|指定表不是 Colocate 表。|
-|5065|指定的操作无效。|
-|5065|指定的时间单位非法，正确的单位包括：DAY、WEEK、MONTH。|
-|5066|动态分区起始值应该小于0。|
-|5066|动态分区起始值不是有效的数字。|
-|5066|动态分区结束值应该大于0。|
-|5066|动态分区结束值不是有效的数字。|
-|5066|动态分区结束值为空。|
-|5067|动态分区分桶数应该大于0。|
-|5067|动态分区分桶值不是有效的数字。|
-|5066|动态分区分桶值为空。|
-|5068|是否允许动态分区的值不是有效的布尔值：true 或者 false。|
-|5069|指定的动态分区名前缀非法。|
-|5070|指定的操作被禁止了。|
-|5071|动态分区副本数应该大于0。|
-|5072|动态分区副本值不是有效的数字。|
diff --git a/docs/zh/reference/HTTP_API/SQL.md b/docs/zh/reference/HTTP_API/SQL.md
deleted file mode 100644
index 9ac17795924870..00000000000000
--- a/docs/zh/reference/HTTP_API/SQL.md
+++ /dev/null
@@ -1,207 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# HTTP SQL API
-
-## 功能
-
-StarRocks 3.2.0 版本提供了 HTTP SQL API，方便用户通过 HTTP 协议使用 StarRocks 的查询功能，当前支持 SELECT、SHOW、EXPLAIN、KILL 语句。
-
-使用 curl 命令的一个语法示例：
-
-```shell
-curl -X POST 'http://<fe_ip>:<fe_http_port>/api/v1/catalogs/<catalog_name>/databases/<database_name>/sql' \
-   -u '<username>:<password>'  -d '{"query": "<sql_query>;", "sessionVariables":{"<var_name>":<var_value>}}' \
-   --header "Content-Type: application/json"
-```
-
-## 请求报文
-
-### Request line
-
-```shell
-POST 'http://<fe_ip>:<fe_http_port>/api/v1/catalogs/<catalog_name>/databases/<database_name>/sql'
-```
-
-| Field                    | Description                                                  |
-| ------------------------ | :----------------------------------------------------------- |
-|  fe_ip                   | FE 节点 IP。                                                  |
-|  fe_http_port            | FE 节点 HTTP Port。                                           |
-|  catalog_name            | 数据目录名称。3.2.0 版本仅支持查询 StarRocks 内部表，即 `<catalog_name>` 仅支持为 `default_catalog`。从 3.2.1 版本开始，支持查询[外部 Catalog](../../data_source/catalog/catalog_overview.md) 下的表。|
-|  database_name           | 数据库名称。如果未指定数据库名称，那么在 SQL query 语句中出现的表名前面需要加上 database 名，比如 `database_name.table_name`。 |
-
-- 指定 catalog，跨 database 查询。SQL 语句中出现的表前面需要加上 database 名。
-
-   ```shell
-   POST /api/v1/catalogs/<catalog_name>/sql
-   ```
-
-- 指定 catalog 和 database 查询。
-
-   ```shell
-   POST /api/v1/catalogs/<catalog_name>/databases/<database_name>/sql
-   ```
-
-### 认证方式
-
-```SQL
-Authorization: Basic <credentials>
-```
-
-使用 Basic authentication 进行认证，即 `credentials` 里填写用户名和密码 (`-u '<username>:<password>'`)。注意如果账号没有设置密码，只需传入 `<username>:`，密码留空。举例，如果 root 账号没有设置密码，则写作 `-u 'root:'`。
-
-### Request body
-
-```shell
--d '{"query": "<sql_query>;", "sessionVariables":{"<var_name>":<var_value>}}'
-```
-
-| Field                    | Description                                                  |
-| ------------------------ | :----------------------------------------------------------- |
-| query                    | SQL 语句，STRING 格式。当前支持 SELECT、SHOW、EXPLAIN、KILL 语句。一次 HTTP 请求只允许执行一条 SQL。 |
-| sessionVariables         | 指定的 session 变量，JSON 格式。可选，默认为空。设置的 session 变量在同一连接中始终有效，连接断开后 session 变量失效。 |
-
-### Request header
-
-```shell
---header "Content-Type: application/json"
-```
-
-表示发送的请求体是 JSON 字符串。
-
-## 响应报文
-
-### Status code
-
-- 200：HTTP 请求成功，且在发送数据给客户端之前服务器未出现异常。
-- 4xx：HTTP 请求错误，表示客户端出错。
-- `500 Internal Server Error`：HTTP 请求成功，但是在发送数据给客户端之前出现异常。
-- 503：HTTP 请求成功，但是 FE 当前无法提供服务。
-
-### Response header
-
-content-type 表示 response body 的格式。这里使用 Newline delimited JSON 格式，即 response body 由若干 JSON object 组成，JSON object 之间以 `\n` 隔开。
-
-|                      | Description                                                  |
-| -------------------- | :----------------------------------------------------------- |
-| content-type         | 格式为 Newline delimited JSON。默认为 "application/x-ndjson charset=UTF-8"。 |
-| X-StarRocks-Query-Id | Query ID。                                                          |
-
-### Response body
-
-#### 在结果发出之前执行失败
-
-客户端的请求出错或者服务端在将数据发送给客户端之前出现异常，此时 response body 格式如下。其中 `msg` 为对应的错误异常信息。
-
-```json
-{
-   "status":"FAILED",
-   "msg":"xxx"
-}
-```
-
-#### 在结果发出部分后执行失败
-
-此时结果已经部分发出，HTTP 状态码为 200，因此选择不再继续发送数据，并关闭连接，记录错误日志。
-
-#### 执行成功
-
-返回结果中每行是一个 JSON object，JSON object 之间以换行符 `\n` 隔开，从而便于客户端解析。
-
-- 对于 SELECT 语句，会返回以下 JSON object。
-
-| Object       | Description                                                  |
-| ------------ | :----------------------------------------------------------- |
-| `connectionId` | 该连接对应的 ID，可通过 KILL `<connectionId>` 来取消某个执行时间过长的 query。 |
-| `meta`        | 用来描述每个列。Key 为 meta, Value 为一个 JSON array。array 中的每个 object 表示一个 column。 |
-| `data`         | 代表一行数据。Key 为 data, Value 为一个 JSON  array，array 中包含一条数据。 |
-| `statistics`   | 本次执行结果的统计信息。                                       |
-
-- 对于 SHOW，会返回 `meta`，`data`，`statistics`。
-- 对于 EXPLAIN，会返回一个 `explain` 对象，展示这条查询详细的执行计划。
-
-样例：这里换行以 `\n` 表示。发送时 StarRocks 使用 HTTP chunked 方式传输数据，FE 每获取一批数据，就将该批数据流式转发给客户端。客户端可以按行解析 StarRocks 发送的数据，而不需要缓存现有结果直到所有数据发送完毕再进行解析。这可以降低客户端的内存消耗。
-
-```json
-{"connectionId": 7}\n
-{"meta": [
-    {
-      "name": "stock_symbol",
-      "type": "varchar"
-    },
-    {
-      "name": "closing_price",
-      "type": "decimal64(8, 2)"
-    },
-    {
-      "name": "closing_date",
-      "type": "datetime"
-    }
-  ]}\n
-{"data": ["JDR", 12.86, "2014-10-02 00:00:00"]}\n
-{"data": ["JDR",14.8, "2014-10-10 00:00:00"]}\n
-...
-{"statistics": {"scanRows": 0,"scanBytes": 0,"returnRows": 9}}
-```
-
-## 接口调用示例
-
-### 发起查询
-
-- 查询 StarRocks 内部表，即 `<catalog_name>` 为 `default_catalog`。
-
-  ```shell
-  curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:' -d '{"query": "select * from agg;"}' --header "Content-Type: application/json"
-  ```
-
-  返回结果：
-
-  ```json
-  {"connectionId":49}
-  {"meta":[{"name":"no","type":"int(11)"},{"name":"k","type":"decimal64(10, 2)"},{"name":"v","type":"decimal64(10, 2)"}]}
-  {"data":[1,"10.00",null]}
-  {"data":[2,"10.00","11.00"]}
-  {"data":[2,"20.00","22.00"]}
-  {"data":[2,"25.00",null]}
-  {"data":[2,"30.00","35.00"]}
-  {"statistics":{"scanRows":0,"scanBytes":0,"returnRows":5}}
-  ```
-
-- 查询 Iceberg Catalog 下的表。
-
-  ```shell
-  curl -X POST 'http://172.26.93.145:8030/api/v1/catalogs/iceberg_catalog/databases/ywb/sql' -u 'root:' -d '{"query": "select * from iceberg_analyze;"}' --header "Content-Type: application/json"
-  ```
-
-  返回结果：
-
-  ```json
-  {"connectionId":13}
-  {"meta":[{"name":"k1","type":"int(11)"},{"name":"k2","type":"int(11)"}]}
-  {"data":[1,2]}
-  {"data":[1,1]}
-  {"statistics":{"scanRows":0,"scanBytes":0,"returnRows":2}}
-  ```
-
-### 取消查询
-
-想要取消一个耗时过长的查询时，可以直接断开连接。当检测到连接已断开，StarRocks 会自动取消该查询。
-
-此外，也可以通过发送 KILL `connectionId` 的方式取消该查询。举例：
-
-```shell
-curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:' -d '{"query": "kill 17;"}' --header "Content-Type: application/json"
-```
-
-`connectionId` 除了在 Response body 中会返回，也可以通过 SHOW PROCESSLIST 命令获得。举例：
-
-```shell
-curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:' -d '{"query": "show processlist;"}' --header "Content-Type: application/json"
-```
-
-### 发起查询的同时设置 session 变量
-
-```shell
-curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:'  -d '{"query": "SHOW VARIABLES;", "sessionVariables":{"broadcast_row_limit":14000000}}'  --header "Content-Type: application/json"
-```
diff --git a/docs/zh/reference/System_limit.md b/docs/zh/reference/System_limit.md
deleted file mode 100644
index 17a11f4c744d3b..00000000000000
--- a/docs/zh/reference/System_limit.md
+++ /dev/null
@@ -1,35 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 系统限制
-
-本文介绍使用 StarRocks 系统时需要注意的事项。
-
-- StarRocks 采用 MySQL 协议进行通信，用户可通过 MySQL Client 或者 JDBC 连接到 StarRocks 集群。选择 MySQL Client 版本时建议采用 5.1 及之后的版本，5.1 之前版本不支持长度超过 16 个字符的用户名。
-
-- 对名称的要求，包括数据目录名 (catalog)、数据库名、表名、视图名、分区名、列名、索引名、用户名、角色名、仓库名 (repository)、资源名 (resource)、存储卷名 (Storage Volume)、Pipe 名等：
-  - 只能由数字 (0-9)、字母 (a-z或A-Z)，以及下划线 (\_) 组成。**用户名 (username) 可以使用纯数字命名。**
-  - 可以以字母或下划线开头。
-  - 长度不能超过 64 个字符。**几个特殊情况：**
-    - 数据库名不能超过 256 个字符。
-    - 表名和列名不能超过 1024 个字符。
-    - 用户名 (username) 不能超过 128 个字符。
-  - 列名（包括列别名）、分区名、索引名大小写**不敏感**，其他名称大小写**敏感**。
-
-- 对标签（Label）名的要求：
-  导入数据时可指定任务的标签（Label）。标签名可由数字 (0-9)、字母（a-z或A-Z），以及下划线(\_)组成，且长度不能超过 128 个字符。标签名对起始字符无要求。
-
-- 建表时，Key 列不能使用 FLOAT 或者 DOUBLE 类型，可用 DECIMAL 类型表示小数。
-
-- VARCHAR 最大长度：
-  - 对于 StarRocks 2.1 之前的版本，长度范围为 1~65533 字节。
-  - 【公测中】自 StarRocks 2.1 版本开始，长度范围为 1~1048576 字节。1048578（行最大值）- 2（长度标识位，记录实际数据长度）= 1048576。
-
-- StarRocks 仅支持 UTF8 编码，不支持 GBK 等编码。
-
-- 建表后，表类型不支持修改（比如不能将已有的明细表修改为主键表）。如果需要修改表类型，请重新建表。
-
-- StarRocks 不支持修改表的列名。
-
-- 一个查询中子查询的最大个数默认为 10000，可以通过 FE 参数 `expr_children_limit` 设置。
diff --git a/docs/zh/reference/System_variable.md b/docs/zh/reference/System_variable.md
deleted file mode 100644
index b7467e998f2fac..00000000000000
--- a/docs/zh/reference/System_variable.md
+++ /dev/null
@@ -1,1059 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['session','variable']
----
-
-# 系统变量
-
-StarRocks 提供多个系统变量（system variables），方便您根据业务情况进行调整。本文介绍 StarRocks 支持的变量。您可以在 MySQL 客户端通过命令 [SHOW VARIABLES](../sql-reference/sql-statements/Administration/SHOW_VARIABLES.md) 查看当前变量。也可以通过 [SET](../sql-reference/sql-statements/Administration/SET.md) 命令动态设置或者修改变量。您可以设置变量在系统全局 (global) 范围内生效、仅在当前会话 (session) 中生效、或者仅在单个查询语句中生效。
-
-StarRocks 中的变量参考 MySQL 中的变量设置，但**部分变量仅用于兼容 MySQL 客户端协议，并不产生其在 MySQL 数据库中的实际意义**。
-
-> **说明**
->
-> 任何用户都有权限通过 SHOW VARIABLES 查看变量。任何用户都有权限设置变量在 Session 级别生效。只有拥有 System 级 OPERATE 权限的用户才可以设置变量为全局生效。设置全局生效后，后续所有新的会话都会使用新配置，当前会话仍然使用老的配置。
-
-## 查看变量
-
-可以通过 `SHOW VARIABLES [LIKE 'xxx'];` 查看所有或指定的变量。例如：
-
-```SQL
-
--- 查看系统中所有变量。
-SHOW VARIABLES;
-
--- 查看符合匹配规则的变量。
-SHOW VARIABLES LIKE '%time_zone%';
-```
-
-## 变量层级和类型
-
-StarRocks 支持三种类型（层级）的变量：全局变量、Session 变量和 `SET_VAR` Hint。它们的层级关系如下：
-
-* 全局变量在全局级别生效，可以被 Session 变量和 `SET_VAR` Hint 覆盖。
-* Session 变量仅在当前会话中生效，可以被 `SET_VAR` Hint 覆盖。
-* `SET_VAR` Hint 仅在当前查询语句中生效。
-
-## 设置变量
-
-### 设置变量全局生效或在会话中生效
-
-变量一般可以设置为**全局**生效或**仅当前会话**生效。设置为全局生效后，**后续所有新的会话**连接中会使用新设置的值，当前会话还会继续使用之前设置的值；设置为仅当前会话生效时，变量仅对当前会话产生作用。
-
-通过 `SET <var_name> = xxx;` 语句设置的变量仅在当前会话生效。如：
-
-```SQL
-SET query_mem_limit = 137438953472;
-
-SET forward_to_master = true;
-
-SET time_zone = "Asia/Shanghai";
-```
-
-通过 `SET GLOBAL <var_name> = xxx;` 语句设置的变量全局生效。如：
-
- ```SQL
-SET GLOBAL query_mem_limit = 137438953472;
- ```
-
-以下变量仅支持全局生效，不支持设置为会话级别生效。您必须使用 `SET GLOBAL <var_name> = xxx;`，不能使用 `SET <var_name> = xxx;`，否则返回错误。
-
-* activate_all_roles_on_login
-* character_set_database
-* default_rowset_type
-* enable_query_queue_select
-* enable_query_queue_statistic
-* enable_query_queue_load
-* init_connect
-* lower_case_table_names
-* license
-* language
-* query_cache_size
-* query_queue_fresh_resource_usage_interval_ms
-* query_queue_concurrency_limit
-* query_queue_mem_used_pct_limit
-* query_queue_cpu_used_permille_limit
-* query_queue_pending_timeout_second
-* query_queue_max_queued_queries
-* system_time_zone
-* version_comment
-* version
-
-Session 级变量既可以设置全局生效也可以设置 session 级生效。
-
-此外，变量设置也支持常量表达式，如：
-
-```SQL
-SET query_mem_limit = 10 * 1024 * 1024 * 1024;
-```
-
-```SQL
-SET forward_to_master = concat('tr', 'u', 'e');
-```
-
-### 设置变量在单个查询语句中生效
-
-在一些场景中，可能需要对某些查询专门设置变量。可以使用 SET_VAR 提示 (Hint) 在查询中设置仅在单个语句内生效的会话变量。
-
-当前，StarRocks 支持在以下语句中使用 `SET_VAR` Hint：
-
-- SELECT
-- INSERT（自 v3.1.12 和 v3.2.0 起支持）
-- UPDATE（自 v3.1.12 和 v3.2.0 起支持）
-- DELETE（自 v3.1.12 和 v3.2.0 起支持）
-
-`SET_VAR` 只能跟在以上关键字之后，必须以 `/*+` 开头，以 `*/` 结束。
-
-举例：
-
-```sql
-SELECT /*+ SET_VAR(query_mem_limit = 8589934592) */ name FROM people ORDER BY name;
-
-SELECT /*+ SET_VAR(query_timeout = 1) */ sleep(3);
-
-UPDATE /*+ SET_VAR(query_timeout=100) */ tbl SET c1 = 2 WHERE c1 = 1;
-
-DELETE /*+ SET_VAR(query_mem_limit = 8589934592) */
-FROM my_table PARTITION p1
-WHERE k1 = 3;
-
-INSERT /*+ SET_VAR(query_timeout = 10000000) */
-INTO insert_wiki_edit
-    SELECT * FROM FILES(
-        "path" = "s3://inserttest/parquet/insert_wiki_edit_append.parquet",
-        "format" = "parquet",
-        "aws.s3.access_key" = "XXXXXXXXXX",
-        "aws.s3.secret_key" = "YYYYYYYYYY",
-        "aws.s3.region" = "us-west-2"
-);
-```
-
-StarRocks 同时支持在单个语句中设置多个变量，参考如下示例：
-
-```sql
-SELECT /*+ SET_VAR
-  (
-  exec_mem_limit = 515396075520,
-  query_timeout=10000000,
-  batch_size=4096,
-  parallel_fragment_exec_instance_num=32
-  )
-  */ * FROM TABLE;
-```
-
-## 支持的变量
-
-本节以字母顺序对变量进行解释。带 `global` 标记的变量为全局变量，仅支持全局生效。其余变量既可以设置全局生效，也可设置会话级别生效。
-
-### activate_all_roles_on_login (global)
-
-* 描述：用于控制是否在用户登录时默认激活所有角色（包括默认角色和授予的角色）。
-  * 开启后，在用户登录时默认激活所有角色，优先级高于通过 [SET DEFAULT ROLE](../sql-reference/sql-statements/account-management/SET_DEFAULT_ROLE.md) 设置的角色。
-  * 如果不开启，则会默认激活 SET DEFAULT ROLE 中设置的角色。
-* 默认值：false，表示不开启。
-* 引入版本：v3.0
-
-如果要在当前会话中激活一个角色，可以使用 [SET ROLE](../sql-reference/sql-statements/account-management/SET_ROLE.md)。
-
-### auto_increment_increment
-
-* 描述：用于兼容 MySQL 客户端。无实际作用。
-* 默认值：1
-* 类型：Int
-
-### autocommit
-
-* 描述：用于兼容 MySQL 客户端。无实际作用。
-* 默认值：true
-
-### chunk_size
-
-用于指定在查询执行过程中，各个节点传输的单个数据包的行数。默认一个数据包的行数为 4096 行，即源端节点每产生 4096 行数据后，打包发给目的节点。较大的行数，会在扫描大数据量场景下提升查询的吞吐率，但可能会在小查询场景下增加查询延迟。同时，也会增加查询的内存开销。建议设置范围 1024 至 4096。
-
-### big_query_profile_threshold
-
-* 描述：用于设定大查询的阈值。当会话变量 `enable_profile` 设置为 `false` 且查询时间超过 `big_query_profile_threshold` 设定的阈值时，则会生成 Profile。
-
-  NOTE：在 v3.1.5 至 v3.1.7 以及 v3.2.0 至 v3.2.2 中，引入了 `big_query_profile_second_threshold` 参数，用于设定大查询的阈值。而在 v3.1.8、v3.2.3 及后续版本中，此参数被 `big_query_profile_threshold` 替代，以便提供更加灵活的配置选项。
-* 默认值：0
-* 单位：秒
-* 类型：String
-* 引入版本：v3.1
-
-### catalog（3.2.4 及以后）
-
-* 描述：用于指定当前会话所在的 Catalog。
-* 默认值：default_catalog
-* 类型：String
-* 引入版本：v3.2.4
-
-### cbo_decimal_cast_string_strict
-
-* 描述：用于优化器控制 DECIMAL 类型转为 STRING 类型的行为。取值为 `true` 时，使用 v2.5.x及之后版本的处理逻辑，执行严格转换（按 Scale 截断补 `0`）；取值为 `false`时，保留 v2.5.x 之前版本的处理逻辑（按有效数字处理）。默认值是 `true`。
-* 默认值：true
-* 引入版本：v2.5.14
-
-### cbo_enable_low_cardinality_optimize
-
-* 描述：是否开启低基数全局字典优化。开启后，查询 STRING 列时查询速度会有 3 倍左右提升。
-* 默认值：true
-
-### cbo_eq_base_type
-
-* 描述：用来指定 DECIMAL 类型和 STRING 类型的数据比较时的强制类型，默认按照 `VARCHAR` 类型进行比较，可选 `DECIMAL`（按数值进行比较）。**该变量仅在进行 `=` 和 `!=` 比较时生效。**
-* 类型：String
-* 引入版本：v2.5.14
-
-### cbo_materialized_view_rewrite_related_mvs_limit
-
-* 描述：用于指定查询在 Plan 阶段最多拥有的候选物化视图个数。
-* 默认值：64
-* 类型：Int
-* 引入版本：v3.1.9, v3.2.5
-
-### cbo_prune_subfield
-
-* 描述：是否开启 JSON 子列裁剪。需要配合 BE 动态参数 `enable_json_flat` 一起使用，单独使用可能会导致 JSON 性能变慢。
-* 默认值：false
-* 引入版本：v3.3.0
-
-### enable_sync_materialized_view_rewrite
-
-* 描述：是否启用基于同步物化视图的查询改写。
-* 默认值：true
-* 引入版本：v3.1.11，v3.2.5
-
-### enable_datacache_async_populate_mode
-
-* 描述：是否使用异步方式进行 Data Cache 填充。系统默认使用同步方式进行填充，即在查询数据时同步填充进行缓存填充。
-* 默认值：false
-* 引入版本：v3.2.7
-
-### query_including_mv_names
-
-* 描述：指定需要在查询执行过程中包含的异步物化视图的名称。您可以使用此变量来限制候选物化视图的数量，并提高优化器中的查询改写性能。此项优先于 `query_excluding_mv_names` 生效。
-* 默认值：空字符串
-* 类型：String
-* 引入版本：v3.1.11，v3.2.5
-
-### query_excluding_mv_names
-
-* 描述：指定需要在查询执行过程中排除的异步物化视图的名称。您可以使用此变量来限制候选物化视图的数量，并提高优化器中的查询改写性能。`query_including_mv_names` 优先于此项生效。
-* 默认值：空字符串
-* 类型：String
-* 引入版本：v3.1.11，v3.2.5
-
-### optimizer_materialized_view_timelimit
-
-* 描述：指定一个物化视图改写规则可消耗的最大时间。当达到阈值时，将不再使用该规则进行查询改写。
-* 默认值：1000
-* 单位：毫秒
-* 类型：Long
-
-### enable_materialized_view_agg_pushdown_rewrite
-
-* 描述：是否为物化视图查询改写启用聚合函数下推。如果设置为 `true`，聚合函数将在查询执行期间下推至 Scan Operator，并在执行 Join Operator 之前被物化视图改写。此举可以缓解 Join 操作导致的数据膨胀，从而提高查询性能。有关此功能的具体场景和限制的详细信息，请参见 [聚合函数下推](../using_starrocks/query_rewrite_with_materialized_views.md#聚合下推)。
-* 默认值：false
-* 引入版本：v3.3.0
-
-### enable_materialized_view_text_match_rewrite
-
-* 描述：是否启用基于文本的物化视图改写。当此项设置为 `true` 时，优化器将查询与现有的物化视图进行比较。如果物化视图定义的抽象语法树与查询或其子查询的抽象语法树匹配，则会对查询进行改写。
-* 默认值：true
-* 引入版本：v3.2.5，v3.3.0
-
-### materialized_view_subuqery_text_match_max_count
-
-* 描述：指定系统比对查询的子查询是否与物化视图定义匹配的最大次数。
-* 默认值：4
-* 引入版本：v3.2.5，v3.3.0
-
-### enable_force_rule_based_mv_rewrite
-
-* 描述：在优化器的 RBO（rule-based optimization）阶段是否针对多表查询启用查询改写。启用此功能将提高查询改写的鲁棒性。但如果查询未命中物化视图，则会增加优化耗时。
-* 默认值：true
-* 引入版本：v3.3
-
-### enable_view_based_mv_rewrite
-
-* 描述：是否为基于逻辑视图创建的物化视图启用查询改写。如果此项设置为 `true`，则逻辑视图被用作统一节点进行查询改写，从而获得更好的性能。如果此项设置为 `false`，则系统将针对逻辑视图的查询展开变为针对物理表或物化视图的查询，然后进行改写。
-* 默认值：false
-* 引入版本：v3.1.9，v3.2.5，v3.3.0
-
-### enable_materialized_view_union_rewrite
-
-* 描述：是否启用物化视图 UNION 改写。如果此项设置为 true，则系统在物化视图的谓词不能满足查询的谓词时，会尝试使用 UNION ALL 来补偿谓词。
-* 默认值：true
-* 引入版本：v2.5.20，v3.1.9，v3.2.7，v3.3.0
-
-### enable_materialized_view_plan_cache
-
-* 描述：是否开启物化视图查询计划缓存，用于提高物化视图查询改写性能。默认值是 `true`，即开启物化视图查询计划缓存。
-* 默认值：true
-* 引入版本：v2.5.13，v3.0.7，v3.1.4，v3.2.0，v3.3.0
-
-### follower_query_forward_mode
-
-* 描述：用于指定将查询语句路由到 Leader FE 或 Follower FE 节点。
-
-  有效值:
-  * `default`: 将查询语句路由到 Leader FE 或 Follower FE 节点，取决于 Follower FE 节点的回放进度。如果 Follower FE 节点未完成回放，查询将会被路由至 Leader FE 节点。反之，查询会被优先路由至 Follower FE 节点。
-  * `leader`: 将查询语句路由到 Leader FE 节点。
-  * `follower`: 将查询语句路由到 Follower FE 节点。
-* 默认值：default
-* 类型：String
-* 引入版本：v2.5.20，v3.1.9，v3.2.7，v3.3.0
-
-### character_set_database（global）
-
-* 描述：StarRocks 数据库支持的字符集，当前仅支持 UTF8 编码（`utf8`）。
-* 默认值：utf8
-* 类型：String
-
-### connector_io_tasks_per_scan_operator
-
-* 描述：外表查询时每个 Scan 算子能同时下发的 I/O 任务的最大数量。目前外表查询时会使用自适应算法来调整并发 I/O 任务的数量，通过 `enable_connector_adaptive_io_tasks` 开关来控制，默认打开。
-* 默认值：16
-* 类型：Int
-* 引入版本：v2.5
-
-### connector_sink_compression_codec
-
-* 描述：用于指定写入 Hive 表或 Iceberg 表时以及使用 Files() 导出数据时的压缩算法。有效值：`uncompressed`、`snappy`、`lz4`、`zstd`、`gzip`。
-* 默认值：uncompressed
-* 类型：String
-* 引入版本：v3.2.3
-
-### connector_sink_target_max_file_size
-
-* 描述: 指定将数据写入 Hive 表或 Iceberg 表或使用 Files() 导出数据时目标文件的最大大小。该限制并不一定精确，只作为尽可能的保证。
-* 单位：Bytes
-* 默认值: 1073741824
-* 类型: Long
-* 引入版本: v3.3.0
-
-### count_distinct_column_buckets
-
-* 描述：group-by-count-distinct 查询中为 count distinct 列设置的分桶数。该变量只有在 `enable_distinct_column_bucketization` 设置为 `true` 时才会生效。
-* 默认值：1024
-* 引入版本：v2.5
-
-### default_rowset_type (global)
-
-全局变量，仅支持全局生效。用于设置计算节点存储引擎默认的存储格式。当前支持的存储格式包括：alpha/beta。
-
-### default_table_compression
-
-* 描述：存储表格数据时使用的默认压缩算法，支持 LZ4、Zstandard（或 zstd）、zlib 和 Snappy。如果您建表时在 PROPERTIES 设置了 `compression`，则 `compression` 指定的压缩算法生效。
-* 默认值：lz4_frame
-* 类型：String
-* 引入版本：v3.0
-
-### disable_colocate_join
-
-* 描述：控制是否启用 Colocate Join 功能。默认值为 false，表示启用该功能。true 表示禁用该功能。当该功能被禁用后，查询规划将不会尝试执行 Colocate Join。
-* 默认值：false
-
-### disable_streaming_preaggregations (已弃用)
-
-控制是否开启流式预聚合。默认为 `false`，即开启。3.1 版本已弃用。
-
-### div_precision_increment
-
-* 描述：用于兼容 MySQL 客户端，无实际作用。
-* 默认值：4
-* 类型：Int
-<!--
-### enable_collect_table_level_scan_stats (Invisible to users)
-
-解决升级中的兼容问题，用户不可见。
-
-默认值：`true`。
--->
-
-### enable_connector_adaptive_io_tasks
-
-* 描述：外表查询时是否使用自适应策略来调整 I/O 任务的并发数。默认打开。如果未开启自适应策略，可以通过 `connector_io_tasks_per_scan_operator` 变量来手动设置外表查询时的 I/O 任务并发数。
-* 默认值：true
-* 引入版本：v2.5
-
-### enable_distinct_column_bucketization
-
-* 描述：是否在 group-by-count-distinct 查询中开启对 count distinct 列的分桶优化。在类似 `select a, count(distinct b) from t group by a;` 的查询中，如果 group by 列 a 为低基数列，count distinct 列 b 为高基数列且发生严重数据倾斜时，会引发查询性能瓶颈。可以通过对 count distinct 列进行分桶来平衡数据，规避数据倾斜。
-
-  该变量需要与 `count_distinct_column_buckets` 配合使用。
-
-  您也可以通过添加 `skew` hint 来开启 count distinct 列的分桶优化，例如 `select a,count(distinct [skew] b) from t group by a;`。
-* 默认值：false，表示不开启。
-* 引入版本：v2.5
-
-### enable_gin_filter
-
-* 描述：查询时是否使用[全文倒排索引](../table_design/indexes/inverted_index.md)。
-* 默认值：true
-* 引入版本：v3.3.0
-
-### enable_group_level_query_queue (global)
-
-* 描述：是否开启资源组粒度的[查询队列](../administration/management/resource_management/query_queues.md)。
-* 默认值：false，表示不开启。
-* 引入版本：v3.1.4
-
-### enable_iceberg_metadata_cache
-
-* 描述：是否缓存 Iceberg 表指针和分区名相关的数据。在 3.2.1 到 3.2.3 版本，该参数默认值统一为 `true`。自 3.2.4 版本起，如果 Iceberg 集群的元数据服务为 AWS Glue，该参数默认值仍为 `true`，如果 Iceberg 集群的元数据服务为 Hive Metastore（简称 HMS）或其他，则该参数默认值变更为 `false`。
-* 引入版本：v3.2.1
-
-### enable_insert_strict
-
-* 描述：用于设置通过 INSERT 语句进行数据导入时，是否开启严格模式 (Strict Mode)。
-默认值为 `true`，即开启严格模式。关于该模式的介绍，可以参阅[严格模式](../loading/load_concept/strict_mode.md)。
-* 默认值：true
-
-### enable_materialized_view_for_insert
-
-* 描述：是否允许 StarRocks 改写 INSERT INTO SELECT 语句中的查询。
-* 默认值：false，即默认关闭该场景下的物化视图查询改写。
-* 引入版本：v2.5.18, v3.0.9, v3.1.7, v3.2.2
-
-### enable_rule_based_materialized_view_rewrite
-
-* 描述：是否开启基于规则的物化视图查询改写功能，主要用于处理单表查询改写。
-* 默认值：true
-* 引入版本：v2.5
-
-### enable_short_circuit
-
-* 描述：是否启用短路径查询。默认值：`false`。如果将其设置为 `true`，当[查询满足条件](../table_design/hybrid_table.md#查询数据)（用于评估是否为点查）：WHERE 子句的条件列必须包含所有主键列，并且运算符为 `=` 或者 `IN`，则该查询才会走短路径。
-* 默认值：false
-* 引入版本：v3.2.3
-
-### enable_spill
-
-* 描述：是否启用中间结果落盘。默认值：`false`。如果将其设置为 `true`，StarRocks 会将中间结果落盘，以减少在查询中处理聚合、排序或连接算子时的内存使用量。
-* 默认值：false
-* 引入版本：v3.0
-
-### enable_spill_to_remote_storage
-
-* 描述：是否启用将中间结果落盘至对象存储。如果设置为 `true`，当本地磁盘的用量达到上限后，StarRocks 将中间结果落盘至 `spill_storage_volume` 中指定的存储卷中。有关更多信息，请参阅 [将中间结果落盘至对象存储](../administration/management/resource_management/spill_to_disk.md#将中间结果落盘至对象存储)。
-* 默认值：false
-* 引入版本：v3.3.0
-
-### enable_strict_order_by
-
-* 描述：是否校验 ORDER BY 引用列是否有歧义。设置为默认值 `TRUE` 时，如果查询中的输出列存在不同的表达式使用重复别名的情况，且按照该别名进行排序，查询会报错，例如 `select distinct t1.* from tbl1 t1 order by t1.k1;`。该行为和 2.3 及之前版本的逻辑一致。如果取值为 `FALSE`，采用宽松的去重机制，把这类查询作为有效 SQL 处理。
-* 默认值：true
-* 引入版本：v2.5.18，v3.1.7
-
-### enable_profile
-
-用于设置是否需要查看查询的 profile。默认为 `false`，即不需要查看 profile。2.5 版本之前，该变量名称为 `is_report_success`，2.5 版本之后更名为 `enable_profile`。
-
-默认情况下，只有在查询发生错误时，BE 才会发送 profile 给 FE，用于查看错误。正常结束的查询不会发送 profile。发送 profile 会产生一定的网络开销，对高并发查询场景不利。当用户希望对一个查询的 profile 进行分析时，可以将这个变量设为 `true` 后，发送查询。查询结束后，可以通过在当前连接的 FE 的 web 页面（地址：fe_host:fe_http_port/query）查看 profile。该页面会显示最近 100 条开启了 `enable_profile` 的查询的 profile。
-
-### enable_query_queue_load (global)
-
-* 描述：用于控制是否为导入任务启用查询队列。
-* 默认值：false
-* 类型：Boolean
-
-### enable_query_queue_select (global)
-
-* 描述：用于控制是否为 SELECT 查询启用查询队列。
-* 默认值：false
-* 类型：Boolean
-
-### enable_query_queue_statistic (global)
-
-* 描述：用于控制是否为统计信息查询启用查询队列。
-* 默认值：false
-* 类型：Boolean
-
-### enable_query_tablet_affinity
-
-* 描述：用于控制在多次查询同一个 tablet 时是否倾向于选择固定的同一个副本。
-
-  如果待查询的表中存在大量 tablet，开启该特性会对性能有提升，因为会更快的将 tablet 的元信息以及数据缓存在内存中。但是，如果查询存在一些热点 tablet，开启该特性可能会导致性能有所退化，因为该特性倾向于将一个热点 tablet 的查询调度到相同的 BE 上，在高并发的场景下无法充分利用多台 BE 的资源。
-* 默认值：`false`，表示使用原来的机制，即每次查询会从多个副本中选择一个。
-* 类型：Boolean
-* 引入版本：v2.5.6、v3.0.8、v3.1.4、v3.2.0
-
-### enable_lake_tablet_internal_parallel
-
-* 描述：是否开启存算分离集群内云原生表的 Tablet 并行 Scan.
-* 默认值：false
-* 类型：Boolean
-* 引入版本：v3.3.0
-
-### tablet_internal_parallel_mode
-
-* 描述：Tablet 内部并行 Scan 策略。有效值:
-  * `auto`: 在 BE 或 CN 节点需要扫描的 Tablet 数小于 DOP 时，系统根据预估的 Tablet 大小自动判断是否需要并行 Scan。
-  * `force_split`: 强制对 Tablet 进行拆分和并行扫描。
-* 默认值：auto
-* 类型：String
-* 引入版本：v2.5.0
-
-### enable_scan_datacache
-
-* 描述：是否开启 Data Cache 特性。该特性开启之后，StarRocks 通过将外部存储系统中的热数据缓存成多个 block，加速数据查询和分析。更多信息，参见 [Data Cache](../data_source/data_cache.md)。该特性从 2.5 版本开始支持。在 3.2 之前各版本中，对应变量为 `enable_scan_block_cache`。
-* 默认值：false
-* 引入版本：v2.5
-
-### populate_datacache_mode
-
-* 描述：StarRocks 从外部存储系统读取数据时，控制数据缓存填充行为。有效值包括：
-  * `auto`（默认）：系统自动根据查询的特点，选择性进行缓存。
-  * `always`：总是缓存数据。 
-  * `never` 永不缓存数据。
-* 默认值：auto
-* 引入版本：v3.3.2
-
-### enable_datacache_io_adaptor
-
-* 描述：是否开启 Data Cache I/O 自适应开关。`true` 表示开启。开启后，系统会根据当前磁盘 I/O 负载自动将一部分缓存请求路由到远端存储来减少磁盘压力。
-* 默认值：true
-* 引入版本：v3.3.0
-
-### enable_file_metacache
-
-* 描述：是否启用远端文件元数据缓存（Footer Cache）。`true` 表示开启。Footer Cache 通过将解析后生成 Footer 对象直接缓存在内存中，在后续访问相同文件 Footer 时，可以直接从缓存中获得该对象句柄进行使用，避免进行重复解析。该功能依赖 Data Cache 的内存缓存，因此需要保证 BE 参数 `datacache_enable` 为 `true` 且为 `datacache_mem_size` 配置一个合理值后才会生效。
-* 默认值：true
-* 引入版本：v3.3.0
-
-### enable_tablet_internal_parallel
-
-* 描述：是否开启自适应 Tablet 并行扫描，使用多个线程并行分段扫描一个 Tablet，可以减少 Tablet 数量对查询能力的限制。
-* 默认值：true
-* 引入版本：v2.3
-
-### enable_query_cache
-
-* 描述：是否开启 Query Cache。取值范围：true 和 false。true 表示开启，false 表示关闭（默认值）。开启该功能后，只有当查询满足[Query Cache](../using_starrocks/query_cache.md#应用场景) 所述条件时，才会启用 Query Cache。
-* 默认值：false
-* 引入版本：v2.5
-
-### enable_adaptive_sink_dop
-
-* 描述：是否开启导入自适应并行度。开启后 INSERT INTO 和 Broker Load 自动设置导入并行度，保持和 `pipeline_dop` 一致。新部署的 2.5 版本默认值为 `true`，从 2.4 版本升级上来为 `false`。
-* 默认值：false
-* 引入版本：v2.5
-
-### enable_pipeline_engine
-
-* 描述：是否启用 Pipeline 执行引擎。`true`：启用（默认），`false`：不启用。
-* 默认值：true
-
-### enable_sort_aggregate
-
-* 描述：是否开启 sorted streaming 聚合。`true` 表示开启 sorted streaming 聚合功能，对流中的数据进行排序。
-* 默认值：false
-* 引入版本：v2.5
-
-### enable_global_runtime_filter
-
-* 描述：Global runtime filter 开关。Runtime Filter（简称 RF）在运行时对数据进行过滤，过滤通常发生在 Join 阶段。当多表进行 Join 时，往往伴随着谓词下推等优化手段进行数据过滤，以减少 Join 表的数据扫描以及 shuffle 等阶段产生的 IO，从而提升查询性能。StarRocks 中有两种 RF，分别是 Local RF 和 Global RF。Local RF 应用于 Broadcast Hash Join 场景。Global RF 应用于 Shuffle Join 场景。
-* 默认值 `true`，表示打开 global runtime filter 开关。关闭该开关后, 不生成 Global RF, 但是依然会生成 Local RF。
-
-### enable_multicolumn_global_runtime_filter
-
-* 描述：多列 Global runtime filter 开关。默认值为 false，表示关闭该开关。
-
-  对于 Broadcast 和 Replicated Join 类型之外的其他 Join，当 Join 的等值条件有多个的情况下：
-  * 如果该选项关闭: 则只会产生 Local RF。
-  * 如果该选项打开, 则会生成 multi-part GRF, 并且该 GRF 需要携带 multi-column 作为 partition-by 表达式.
-
-* 默认值：false
-
-### enable_strict_type
-
-* 描述：是否对所有复合谓词以及 WHERE 子句中的表达式进行隐式转换。
-* 默认值：false
-* 引入版本：v3.1
-
-### enable_write_hive_external_table
-
-* 描述：是否开启往 Hive 的 External Table 写数据的功能。
-* 默认值：false
-* 引入版本：v3.2
-
-### event_scheduler
-
-* 描述：用于兼容 MySQL 客户端。无实际作用。
-* 默认值：OFF
-* 类型：String
-
-### force_streaming_aggregate（已弃用）
-
-用于控制聚合节点是否启用流式聚合计算策略。默认为 false，表示不启用该策略。
-
-### forward_to_leader
-
-用于设置是否将一些命令转发到 Leader FE 节点执行。默认为 `false`，即不转发。StarRocks 中存在多个 FE 节点，其中一个为 Leader 节点。通常用户可以连接任意 FE 节点进行全功能操作。但部分信息查看指令只有从 Leader FE 节点才能获取详细信息。别名 `forward_to_master`。
-
-如 `SHOW BACKENDS;` 命令，如果不转发到 Leader FE 节点，则仅能看到节点是否存活等一些基本信息，而转发到 Leader FE 则可以获取包括节点启动时间、最后一次心跳时间等更详细的信息。
-
-当前受该参数影响的命令如下：
-
-* SHOW FRONTENDS;
-
-  转发到 Leader 可以查看最后一次心跳信息。
-
-* SHOW BACKENDS;
-
-  转发到 Leader 可以查看启动时间、最后一次心跳信息、磁盘容量信息。
-
-* SHOW BROKER;
-
-  转发到 Leader 可以查看启动时间、最后一次心跳信息。
-
-* SHOW TABLET;
-* ADMIN SHOW REPLICA DISTRIBUTION;
-* ADMIN SHOW REPLICA STATUS;
-
-  转发到 Leader 可以查看 Leader FE 元数据中存储的 tablet 信息。正常情况下，不同 FE 元数据中 tablet 信息应该是一致的。当出现问题时，可以通过这个方法比较当前 FE 和 Leader FE 元数据的差异。
-
-* SHOW PROC;
-
-  转发到 Leader 可以查看 Leader FE 元数据中存储的相关 PROC 的信息。主要用于元数据比对。
-
-### group_concat_max_len
-
-* 描述：[group_concat](../sql-reference/sql-functions/string-functions/group_concat.md) 函数返回的字符串的最大长度，单位为字符。
-* 默认值：1024
-* 最小值：4
-* 类型：Long
-
-### hash_join_push_down_right_table
-
-* 描述：用于控制在 Join 查询中是否可以使用针对右表的过滤条件来过滤左表的数据，可以减少 Join 过程中需要处理的左表的数据量。取值为 `true` 时表示允许该操作，系统将根据实际情况决定是否能对左表进行过滤；取值为 `false` 表示禁用该操作。
-* 默认值：true
-
-### init_connect (global)
-
-用于兼容 MySQL 客户端。无实际作用。
-
-### interactive_timeout
-
-* 描述：用于兼容 MySQL 客户端。无实际作用。
-* 默认值：1024
-* 单位：秒
-* 类型：Int
-
-### io_tasks_per_scan_operator
-
-* 每个 Scan 算子能同时下发的 I/0 任务的数量。如果使用远端存储系统（比如 HDFS 或 S3）且时延较长，可以增加该值。但是值过大会增加内存消耗。
-* 默认值：4
-* 类型：Int
-* 引入版本：v2.5
-
-### language (global)
-
-用于兼容 MySQL 客户端。无实际作用。
-
-### license (global)
-
-* 描述：显示 StarRocks 的 license。无其他作用。
-* 默认值：Apache License 2.0
-* 类型：String
-
-### load_mem_limit
-
-* 描述：用于指定导入操作的内存限制，单位为 Byte。默认值为 0，即表示不使用该变量，而采用 `query_mem_limit` 作为导入操作的内存限制。
-
-  这个变量仅用于 INSERT 操作。因为 INSERT 操作涉及查询和导入两个部分，如果用户不设置此变量，则查询和导入操作各自的内存限制均为 `query_mem_limit`。否则，INSERT 的查询部分内存限制为 `query_mem_limit`，而导入部分限制为 `load_mem_limit`。
-
-  其他导入方式，如 Broker Load，STREAM LOAD 的内存限制依然使用 `query_mem_limit`。
-
-* 默认值：0
-* 单位：Byte
-
-### log_rejected_record_num（3.1 及以后）
-
-* 描述：指定最多允许记录多少条因数据质量不合格而过滤掉的数据行数。取值范围：`0`、`-1`、大于 0 的正整数。
-* 取值为 `0` 表示不记录过滤掉的数据行。
-* 取值为 `-1` 表示记录所有过滤掉的数据行。
-* 取值为大于 0 的正整数（比如 `n`）表示每个 BE 节点上最多可以记录 `n` 条过滤掉的数据行。
-
-### lower_case_table_names (global)
-
-用于兼容 MySQL 客户端，无实际作用。StarRocks 中的表名是大小写敏感的。
-
-### materialized_view_rewrite_mode（3.2 及以后）
-
-指定异步物化视图的查询改写模式。有效值：
-
-* `disable`：禁用异步物化视图的自动查询改写。
-* `default`（默认值）：启用异步物化视图的自动查询改写，并允许优化器根据 Cost 决定是否可以使用物化视图改写查询。如果查询无法改写，则直接查询基表中的数据。
-* `default_or_error`：启用异步物化视图的自动查询改写，并允许优化器根据 Cost 决定是否可以使用物化视图改写查询。如果查询无法改写，将返回错误。
-* `force`：启用异步物化视图的自动查询改写，并且优化器优先使用物化视图改写查询。如果查询无法改写，则直接查询基表中的数据。
-* `force_or_error`：启用异步物化视图的自动查询改写，并且优化器优先使用物化视图改写查询。如果查询无法改写，将返回错误。
-
-### max_allowed_packet
-
-* 描述：用于兼容 JDBC 连接池 C3P0。该变量值决定了服务端发送给客户端或客户端发送给服务端的最大 packet 大小。当客户端报 `PacketTooBigException` 异常时，可以考虑调大该值。
-* 默认值：33554432 (32 MB)
-* 单位：Byte
-* 类型：Int
-
-### max_pushdown_conditions_per_column
-
-* 描述：该变量的具体含义请参阅 [BE 配置项](../administration/management/BE_configuration.md)中 `max_pushdown_conditions_per_column` 的说明。
-* 默认值：`-1`，表示使用 `be.conf` 中的配置值。如果设置大于 0，则忽略 `be.conf` 中的配置值。
-* 类型：Int
-
-### max_scan_key_num
-
-* 描述：该变量的具体含义请参阅 [BE 配置项](../administration/management/BE_configuration.md)中 `max_scan_key_num` 的说明。
-* 默认值：`-1`，表示使用 `be.conf` 中的配置值。如果设置大于 0，则忽略 `be.conf` 中的配置值。
-
-### nested_mv_rewrite_max_level
-
-* 描述：可用于查询改写的嵌套物化视图的最大层数。
-* 取值范围：[1, +∞)。取值为 `1` 表示只可使用基于基表创建的物化视图用于查询改写。
-* 默认值：`3`
-* 类型：Int
-
-### net_buffer_length
-
-* 描述：用于兼容 MySQL 客户端。无实际作用。
-* 默认值：16384
-* 类型：Int
-
-### net_read_timeout
-
-* 描述：用于兼容 MySQL 客户端。无实际作用。
-* 默认值：60
-* 单位：秒
-* 类型：Int
-
-### net_write_timeout
-
-* 描述：用于兼容 MySQL 客户端。无实际作用。
-* 默认值：60
-* 单位：秒
-* 类型：Int
-
-### new_planner_optimize_timeout
-
-* 描述：查询优化器的超时时间。一般查询中 Join 过多时容易出现超时。超时后会报错并停止查询，影响查询性能。您可以根据查询的具体情况调大该参数配置，也可以将问题上报给 StarRocks 技术支持进行排查。
-* 默认值：3000
-* 单位：毫秒
-
-### parallel_exchange_instance_num
-
-用于设置执行计划中，一个上层节点接收下层节点数据所使用的 exchange node 数量。默认为 -1，即表示 exchange node 数量等于下层节点执行实例的个数（默认行为）。当设置大于 0，并且小于下层节点执行实例的个数，则 exchange node 数量等于设置值。
-
-在一个分布式的查询执行计划中，上层节点通常有一个或多个 exchange node 用于接收来自下层节点在不同 BE 上的执行实例的数据。通常 exchange node 数量等于下层节点执行实例数量。
-
-在一些聚合查询场景下，如果底层需要扫描的数据量较大，但聚合之后的数据量很小，则可以尝试修改此变量为一个较小的值，可以降低此类查询的资源开销。如在 DUPLICATE KEY 明细表上进行聚合查询的场景。
-
-### parallel_fragment_exec_instance_num
-
-针对扫描节点，设置其在每个 BE 节点上执行实例的个数。默认为 1。
-
-一个查询计划通常会产生一组 scan range，即需要扫描的数据范围。这些数据分布在多个 BE 节点上。一个 BE 节点会有一个或多个 scan range。默认情况下，每个 BE 节点的一组 scan range 只由一个执行实例处理。当机器资源比较充裕时，可以将增加该变量，让更多的执行实例同时处理一组 scan range，从而提升查询效率。
-
-而 scan 实例的数量决定了上层其他执行节点，如聚合节点，join 节点的数量。因此相当于增加了整个查询计划执行的并发度。修改该参数会对大查询效率提升有帮助，但较大数值会消耗更多的机器资源，如CPU、内存、磁盘I/O。
-
-### partial_update_mode
-
-* 描述：控制部分更新的模式，有效值为：
-
-  * `auto`（默认值），表示由系统通过分析更新语句以及其涉及的列，自动判断执行部分更新时使用的模式。
-  * `column`，指定使用列模式执行部分更新，比较适用于涉及少数列并且大量行的部分列更新场景。
-
-  详细信息，请参见[UPDATE](../sql-reference/sql-statements/data-manipulation/UPDATE.md#列模式的部分更新自-31)。
-* 默认值：auto
-* 引入版本：v3.1
-
-### performance_schema (global)
-
-用于兼容 8.0.16 及以上版本的 MySQL JDBC。无实际作用。
-
-### pipeline_dop
-
-* 描述：一个 Pipeline 实例的并行数量。可通过设置实例的并行数量调整查询并发度。默认值为 0，即系统自适应调整每个 pipeline 的并行度。您也可以设置为大于 0 的数值，通常为 BE 节点 CPU 物理核数的一半。从 3.0 版本开始，支持根据查询并发度自适应调节 `pipeline_dop`。
-* 默认值：0
-* 类型：Int
-
-### pipeline_profile_level
-
-* 描述：用于控制 profile 的等级。一个 profile 通常有 5 个层级：Fragment、FragmentInstance、Pipeline、PipelineDriver、Operator。不同等级下，profile 的详细程度有所区别：
-  * 0：在此等级下，StarRocks 会合并 profile，只显示几个核心指标。
-  * 1：默认值。在此等级下，StarRocks 会对 profile 进行简化处理，将同一个 pipeline 的指标做合并来缩减层级。
-  * 2：在此等级下，StarRocks 会保留 Profile 所有的层级，不做简化。该设置下 profile 的体积会非常大，特别是 SQL 较复杂时，因此不推荐该设置。
-* 默认值：1
-* 类型：Int
-
-### prefer_compute_node
-
-* 描述：将部分执行计划调度到 CN 节点执行。
-* 默认值：false
-* 引入版本：v2.4
-
-### query_cache_size (global)
-
-用于兼容 MySQL 客户端。无实际作用。
-
-### query_cache_type
-
- 用于兼容 JDBC 连接池 C3P0。无实际作用。
-
-### query_cache_entry_max_bytes
-
-* 描述：Cache 项的字节数上限，触发 Passthrough 模式的阈值。当一个 Tablet 上产生的计算结果的字节数或者行数超过 `query_cache_entry_max_bytes` 或 `query_cache_entry_max_rows` 指定的阈值时，则查询采用 Passthrough 模式执行。当 `query_cache_entry_max_bytes` 或 `query_cache_entry_max_rows` 取值为 0 时, 即便 Tablet 产生结果为空，也采用 Passthrough 模式。
-* 取值范围：0 ~ 9223372036854775807
-* 默认值：4194304
-* 单位：字节
-* 类型：Long
-* 引入版本：v2.5
-
-### query_cache_entry_max_rows
-
-* 描述：Cache 项的行数上限，见 `query_cache_entry_max_bytes` 描述。
-* 默认值：409600
-* 类型：Long
-* 引入版本：v2.5
-
-### query_cache_agg_cardinality_limit
-
-* 描述：GROUP BY 聚合的高基数上限。GROUP BY 聚合的输出预估超过该行数, 则不启用 cache。
-* 默认值：5000000
-* 类型：Long
-* 引入版本：v2.5
-
-### query_mem_limit
-
-* 描述：用于设置每个 BE 节点上单个查询的内存限制。该项仅在启用 Pipeline Engine 后生效。
-* 单位：字节
-* 默认值：`0`，表示没有限制。
-
-### query_queue_concurrency_limit (global)
-
-* 描述：单个 BE 节点中并发查询上限。仅在设置为大于 `0` 后生效。
-* 默认值：`0`
-* 单位：-
-* 类型：Int
-
-### query_queue_cpu_used_permille_limit (global)
-
-* 描述：单个 BE 节点中内存使用千分比上限（即 CPU 使用率）。仅在设置为大于 `0` 后生效。
-* 默认值：0。
-* 取值范围：[0, 1000]
-
-### query_queue_max_queued_queries (global)
-
-* 描述：队列中查询数量的上限。当达到此阈值时，新增查询将被拒绝执行。仅在设置为大于 `0` 后生效。
-* 默认值：1024。
-
-### query_queue_mem_used_pct_limit (global)
-
-* 描述：单个 BE 节点中内存使用百分比上限。仅在设置为大于 `0` 后生效。
-* 默认值：`0`
-* 取值范围：[0, 1]
-
-### query_queue_pending_timeout_second (global)
-
-* 描述：队列中单个查询的最大超时时间。当达到此阈值时，该查询将被拒绝执行。
-* 默认值：300
-* 单位：秒
-
-### query_timeout
-
-* 描述：用于设置查询超时时间，单位为秒。该变量会作用于当前连接中所有的查询语句，以及 INSERT 语句。
-* 默认值：300 （5 分钟）
-* 单位：秒
-* 类型：Int
-* 取值范围：1 ~ 259200
-
-### range_pruner_max_predicate
-
-* 描述：设置进行 Range 分区裁剪时，最多能使用的 IN 谓词的个数，默认值：100。如果超过该值，会扫描全部 tablet，降低查询性能。
-* 默认值：100
-* 引入版本：v3.0
-
-### resource_group
-
-暂不使用。
-
-### rewrite_count_distinct_to_bitmap_hll (已弃用)
-
-是否将 Bitmap 和 HLL 类型的 count distinct 查询改写为 bitmap_union_count 和 hll_union_agg。
-
-### runtime_filter_on_exchange_node
-
-* 描述：GRF 成功下推跨过 Exchange 算子后，是否在 Exchange Node 上放置 GRF。当一个 GRF 下推跨越 Exchange 算子，最终安装在 Exchange 算子更下层的算子上时，Exchange 算子本身是不放置 GRF 的，这样可以避免重复性使用 GRF 过滤数据而增加计算时间。但是 GRF 的投递本身是 try-best 模式，如果 query 执行时，Exchange 下层的算子接收 GRF 失败，而 Exchange 本身又没有安装 GRF，数据无法被过滤，会造成性能衰退.
-
-  该选项打开（设置为 `true`）时，GRF 即使下推跨过了 Exchange 算子, 依然会在 Exchange 算子上放置 GRF 并生效。
-* 默认值：false
-
-### runtime_join_filter_push_down_limit
-
-* 描述：生成 Bloomfilter 类型的 Local RF 的 Hash Table 的行数阈值。超过该阈值, 则不产生 Local RF。该变量避免产生过大 Local RF。取值为整数，表示行数。
-* 默认值：1024000
-* 类型：Long
-
-### runtime_profile_report_interval
-
-* 描述：Runtime Profile 的上报间隔。
-* 默认值：10
-* 单位：秒
-* 类型：Int
-* 引入版本：v3.1.0
-
-### spill_mode (3.0 及以后)
-
-中间结果落盘的执行方式。默认值：`auto`。有效值包括：
-
-* `auto`：达到内存使用阈值时，会自动触发落盘。
-* `force`：无论内存使用情况如何，StarRocks 都会强制落盘所有相关算子的中间结果。
-
-此变量仅在变量 `enable_spill` 设置为 `true` 时生效。
-
-### spill_storage_volume
-
-* 描述：用于存储触发落盘的查询的中间结果的存储卷。有关更多信息，请参阅 [将中间结果落盘至对象存储](../administration/management/resource_management/spill_to_disk.md#将中间结果落盘至对象存储)。
-* 默认值：空字符串
-* 引入版本：v3.3.0
-
-### SQL_AUTO_IS_NULL
-
-用于兼容 JDBC 连接池 C3P0，无实际作用。默认值：false。
-
-### sql_dialect
-
-* 描述：设置生效的 SQL 语法。例如，执行 `set sql_dialect = 'trino';` 命令可以切换为 Trino 语法，这样您就可以在查询中使用 Trino 特有的 SQL 语法和函数。
-
-  > **注意**
-  >
-  > 设置使用 Trino 语法后，查询默认对大小写不敏感。因此，您在 StarRocks 内建库、表时必须使用小写的库、表名称，否则查询会失败。
-* 默认值：StarRocks
-* 类型：String
-* 引入版本：v3.0
-
-### sql_mode
-
-用于指定 SQL 模式，以适应某些 SQL 方言。有效值包括：
-
-* `PIPES_AS_CONCAT`：管道符号 `|` 用于连接字符串。例如：`select 'hello ' || 'world'`。
-* `ONLY_FULL_GROUP_BY` (默认值)：SELECT LIST 中只能包含 GROUP BY 列或者聚合函数。
-* `ALLOW_THROW_EXCEPTION`：类型转换报错而不是返回 NULL。
-* `FORBID_INVALID_DATE`：禁止非法的日期。
-* `MODE_DOUBLE_LITERAL`：将浮点类型解释为 DOUBLE 而非 DECIMAL。
-* `SORT_NULLS_LAST`：排序后，将 NULL 值放到最后。
-* `ERROR_IF_OVERFLOW`：运算溢出时，报错而不是返回 NULL，目前仅 DECIMAL 支持这一行为。
-* `GROUP_CONCAT_LEGACY`：使用 2.5 及以前的 `group_concat` 的语法。该选项从 3.0.9，3.1.6 开始支持。
-
-不同模式之间可以独立设置，您可以单独开启某一个模式，例如：
-
-```SQL
-set sql_mode = 'PIPES_AS_CONCAT';
-```
-
-或者，您也可以同时设置多个模式，例如：
-
-```SQL
-set sql_mode = 'PIPES_AS_CONCAT,ERROR_IF_OVERFLOW,GROUP_CONCAT_LEGACY';
-```
-
-### sql_safe_updates
-
-用于兼容 MySQL 客户端。无实际作用。
-
-### sql_select_limit
-
-用于兼容 MySQL 客户端。无实际作用。
-
-### statistic_collect_parallel
-
-* 描述：用于调整 BE 上能并发执行的统计信息收集任务的个数，默认值为 1，可以调大该数值来加快采集任务的执行速度。
-* 默认值：1
-* 类型：Int
-
-### storage_engine
-
-指定系统使用的存储引擎。StarRocks 支持的引擎类型包括：
-
-* olap (默认值)：StarRocks 系统自有引擎。
-* mysql：使用 MySQL 外部表。
-* broker：通过 Broker 程序访问外部表。
-* ELASTICSEARCH 或者 es：使用 Elasticsearch 外部表。
-* HIVE：使用 Hive 外部表。
-* ICEBERG：使用 Iceberg 外部表。从 2.1 版本开始支持。
-* HUDI: 使用 Hudi 外部表。从 2.2 版本开始支持。
-* jdbc: 使用 JDBC 外部表。从2.3 版本开始支持。
-
-### streaming_preaggregation_mode
-
-用于设置多阶段聚合时，group-by 第一阶段的预聚合方式。如果第一阶段本地预聚合效果不好，则可以关闭预聚合，走流式方式，把数据简单序列化之后发出去。取值含义如下：
-
-* `auto`（默认值）：先探索本地预聚合，如果预聚合效果好，则进行本地预聚合；否则切换成流式。默认值，建议保留。
-* `force_preaggregation`: 不进行探索，直接进行本地预聚合。
-* `force_streaming`: 不进行探索，直接做流式。
-
-### system_time_zone (global)
-
-显示当前系统时区。不可更改。
-
-### time_zone
-
-用于设置当前会话的时区。时区会对某些时间函数的结果产生影响。
-
-### trace_log_mode
-
-* 描述：用于控制 Query Trace Profile 的 Logs 的输出位置。有效值包括：
-  * `command`：在执行 TRACE LOGS 后作为 **Explain String** 返回。
-  * `file`：在 FE 日志文件 **fe.log** 中以 `FileLogTracer` 为类名返回。
-
-  有关 Query Trace Profile 的更多信息，请参阅 [Query Trace Profile](../developers/trace-tools/query_trace_profile.md)。
-
-* 默认值：`command`
-* 类型：String
-* 引入版本：v3.2.0
-
-### transaction_read_only
-
-* 描述：用于兼容 MySQL 5.8 以上客户端，无实际作用。别名 `tx_read_only`。该变量用于指定事务访问模式。取值 `ON` 表示只读。取值 `OFF` 表示可读可写。
-* 默认值：OFF
-* 引入版本：v2.5.18, v3.0.9, v3.1.7
-
-### tx_isolation
-
-用于兼容 MySQL 客户端，无实际作用。别名 `transaction_isolation`。
-
-### use_compute_nodes
-
-* 描述：用于设置使用 CN 节点的数量上限。该设置只会在 `prefer_compute_node=true` 时才会生效。`-1`，表示使用所有 CN 节点。`0` 表示不使用 CN 节点。
-* 默认值：-1
-* 类型：Int
-* 引入版本：v2.4
-
-### use_v2_rollup
-
-用于控制查询使用 segment v2 存储格式的 Rollup 索引获取数据。该变量用于上线 segment v2 的时进行验证使用。其他情况不建议使用。
-
-### vectorized_engine_enable (2.4 版本开始弃用)
-
-用于控制是否使用向量化引擎执行查询。值为 true 时表示使用向量化引擎，否则使用非向量化引擎。默认值为 true。2.4 版本开始默认打开，所以弃用该变量。
-
-### version (global)
-
-MySQL 服务器的版本，取值等于 FE 参数 `mysql_server_version`。
-
-### version_comment (global)
-
-用于显示 StarRocks 的版本，不可更改。
-
-### wait_timeout
-
-* 描述：用于设置客户端与 StarRocks 数据库交互时的最大空闲时长。如果一个空闲连接在该时长内与 StarRocks 数据库没有任何交互，StarRocks 会主动断开这个连接。
-* 默认值：28800（即 8 小时）
-* 单位：秒
-* 类型：Int
-
-### orc_use_column_names
-
-* 描述：设置通过 Hive Catalog 读取 ORC 文件时，列的对应方式。默认值是 `false`，即按照 Hive 表中列的顺序对应。如果设置为 `true`，则按照列名称对应。
-* 引入版本：v3.1.10
diff --git a/docs/zh/reference/aws_iam_policies.md b/docs/zh/reference/aws_iam_policies.md
deleted file mode 100644
index 576af7c84ba3e7..00000000000000
--- a/docs/zh/reference/aws_iam_policies.md
+++ /dev/null
@@ -1,128 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# AWS IAM 策略
-
-IAM 策略用于声明特定 AWS 资源的一组访问权限。创建 IAM 策略后，您需要将创建好的策略添加到某个 IAM 用户或角色，从而使该 IAM 用户或角色拥有该策略中所声明的访问特定 AWS 资源的权限。
-
-在 StarRocks 中，不同的操作涉及的 AWS 资源也不同。因此，您需要根据要访问的 AWS 资源来创建 IAM 策略。
-
-本文介绍在不同场景下选择 [Instance Profile、Assumed Role、及 IAM User 鉴权方式](../integrations/authenticate_to_aws_resources.md#准备工作)时，为确保 StarRocks 能够正确访问所涉及的 AWS 资源需要配置哪些 IAM 策略。
-
-## 从 AWS S3 批量导入数据
-
-如果您需要从 S3 Bucket 批量导入数据，请按如下配置 IAM 策略：
-
-> **注意**
->
-> 您需要将下面策略中的 `<bucket_name>` 替换为数据所在的 S3 Bucket 的名称。
-
-```SQL
-{
-  "Version": "2012-10-17",
-  "Statement": [
-      {
-          "Sid": "s3",
-          "Effect": "Allow",
-          "Action": [
-              "s3:GetObject"
-          ],
-          "Resource": [
-              "arn:aws:s3:::<bucket_name>/*"
-          ]
-      },
-      {
-          "Sid": "s3list",
-          "Effect": "Allow",
-          "Action": [
-              "s3:ListBucket"
-          ],
-          "Resource": [
-              "arn:aws:s3:::<bucket_name>"
-          ]
-      }
-  ]
-}
-```
-
-## 从 AWS S3 读写数据
-
-如果您需要从 S3 Bucket 查询数据，请按如下配置 IAM 策略：
-
-> **注意**
->
-> 您需要将下面策略中的 `<bucket_name>` 替换为数据所在的 S3 Bucket 的名称。
-
-```SQL
-{
-  "Version": "2012-10-17",
-  "Statement": [
-      {
-          "Sid": "s3",
-          "Effect": "Allow",
-          "Action": [
-              "s3:GetObject", 
-              "s3:PutObject",
-              "s3:DeleteObject"
-          ],
-          "Resource": [
-              "arn:aws:s3:::<bucket_name>/*"
-          ]
-      },
-      {
-          "Sid": "s3list",
-          "Effect": "Allow",
-          "Action": [
-              "s3:ListBucket"
-          ],
-          "Resource": [
-              "arn:aws:s3:::<bucket_name>"
-          ]
-      }
-  ]
-}
-```
-
-## 对接 AWS Glue
-
-如果您需要对接 AWS Glue，完成数据糊的查询与写入，请按如下配置 IAM 策略：
-
-```SQL
-{
-    "Version": "2012-10-17",
-    "Statement": [
-      {
-          "Effect": "Allow",
-          "Action": [
-                "glue:BatchCreatePartition",
-                "glue:UpdateDatabase",
-                "glue:GetConnections",
-                "glue:CreateTable",
-                "glue:DeleteDatabase",
-                "glue:BatchUpdatePartition",
-                "glue:GetTables",
-                "glue:GetTableVersions",
-                "glue:GetPartitions",
-                "glue:UpdateTable",
-                "glue:BatchGetPartition",
-                "glue:DeleteTable",
-                "glue:GetDatabases",
-                "glue:GetDevEndpoint",
-                "glue:GetTable",
-                "glue:GetDatabase",
-                "glue:GetPartition",
-                "glue:GetDevEndpoints",
-                "glue:GetConnection",
-                "glue:CreateDatabase",
-                "glue:CreatePartition",
-                "glue:DeletePartition",
-                "glue:UpdatePartition"
-          ],
-          "Resource": [
-              "*"
-            ]
-        }
-    ]
-}
-```
diff --git a/docs/zh/reference/information_schema/be_bvars.md b/docs/zh/reference/information_schema/be_bvars.md
deleted file mode 100644
index b2f6631d74205a..00000000000000
--- a/docs/zh/reference/information_schema/be_bvars.md
+++ /dev/null
@@ -1,15 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# be_bvars
-
-`be_bvars` 提供有关 bRPC 的统计信息。您可以查看 RPC 延迟、QPS 和某些 StarRocks 组件的统计信息。
-
-`be_bvars` 提供以下字段：
-
-| **字段** | **描述**                          |
-| -------- | --------------------------------- |
-| BE_ID    | bvar 所在的 BE 的 ID。             |
-| NAME     | bvar 名称。                       |
-| DESC     | bvar 描述，其中包括统计信息的值。 |
diff --git a/docs/zh/reference/information_schema/be_cloud_native_compactions.md b/docs/zh/reference/information_schema/be_cloud_native_compactions.md
deleted file mode 100644
index 0d890ea46e8a73..00000000000000
--- a/docs/zh/reference/information_schema/be_cloud_native_compactions.md
+++ /dev/null
@@ -1,23 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# be_cloud_native_compactions
-
-`be_cloud_native_compactions` 提供有关存算一体集群的 CN（或 v3.0 中的 BE）上运行的 Compaction 事务的信息。每个 Compaction 任务会以 Tablet 为粒度，拆分为多个子任务，视图中每一行对应的是一个 Tablet 的 Compaction 子任务。
-
-`be_cloud_native_compactions` 提供以下字段：
-
-| **字段**    | **描述**                                                     |
-| ----------- | ------------------------------------------------------------ |
-| BE_ID       | CN（BE）的 ID。                                              |
-| TXN_ID      | Compaction 任务对应的事务 ID。同一个 Compaction 事务可能会有多个子任务，所以可能存在 TXN_ID 相同的情况。 |
-| TABLET_ID   | Compaction 任务对应的 Tablet ID。                            |
-| VERSION     | Compaction 任务的输入数据的版本。                            |
-| SKIPPED     | 任务是否跳过执行。                                           |
-| RUNS        | 任务运行次数，大于 1 表示发生过重试。                        |
-| START_TIME  | 开始执行的时间。                                             |
-| FINISH_TIME | 结束执行的时间。如果任务还在执行中，值为 NULL。              |
-| PROGRESS    | 进度的百分比，范围是 0 到 100。                              |
-| STATUS      | 任务运行状态。                                               |
-
diff --git a/docs/zh/reference/information_schema/be_compactions.md b/docs/zh/reference/information_schema/be_compactions.md
deleted file mode 100644
index 5ead670c70c0e5..00000000000000
--- a/docs/zh/reference/information_schema/be_compactions.md
+++ /dev/null
@@ -1,20 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# be_compactions
-
-`be_compactions` 提供有关 Compaction 任务的统计信息。
-
-`be_compactions` 提供以下字段：
-
-| **字段**                          | **描述**                                      |
-| --------------------------------- | --------------------------------------------- |
-| BE_ID                             | BE 的 ID。                                    |
-| CANDIDATES_NUM                    | 当前等待执行的 Compaction 任务数。            |
-| BASE_COMPACTION_CONCURRENCY       | 当前正在执行的 Base Compaction 任务数。       |
-| CUMULATIVE_COMPACTION_CONCURRENCY | 当前正在执行的 Cumulative Compaction 任务数。 |
-| LATEST_COMPACTION_SCORE           | 上次 Compaction 任务的 Compaction Score。     |
-| CANDIDATE_MAX_SCORE               | 等待执行的任务的最大 Compaction Score。       |
-| MANUAL_COMPACTION_CONCURRENCY     | 当前正在执行的手动 Compaction 任务数。        |
-| MANUAL_COMPACTION_CANDIDATES_NUM  | 当前等待执行的手动 Compaction 任务数。        |
diff --git a/docs/zh/reference/information_schema/character_sets.md b/docs/zh/reference/information_schema/character_sets.md
deleted file mode 100644
index 63fc5dbbfc7893..00000000000000
--- a/docs/zh/reference/information_schema/character_sets.md
+++ /dev/null
@@ -1,16 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# character_sets
-
-`character_sets` 用于识别可用的字符集。
-
-`character_sets` 提供以下字段：
-
-| **字段**             | **描述**                       |
-| -------------------- | ------------------------------ |
-| CHARACTER_SET_NAME   | 字符集名称。                   |
-| DEFAULT_COLLATE_NAME | 字符集的默认排序规则。         |
-| DESCRIPTION          | 字符集的描述。                 |
-| MAXLEN               | 存储一个字符所需的最大字节数。 |
diff --git a/docs/zh/reference/information_schema/collations.md b/docs/zh/reference/information_schema/collations.md
deleted file mode 100644
index d50f681c55eb34..00000000000000
--- a/docs/zh/reference/information_schema/collations.md
+++ /dev/null
@@ -1,18 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# collations
-
-`collations` 包含可用的排序规则。
-
-`collations` 提供以下字段：
-
-| **字段**           | **描述**                                       |
-| ------------------ | ---------------------------------------------- |
-| COLLATION_NAME     | 排序规则名称。                                 |
-| CHARACTER_SET_NAME | 与排序规则相关联的字符集的名称。               |
-| ID                 | 排序规则的 ID。                                |
-| IS_DEFAULT         | 排序规则是否为其字符集的默认值。               |
-| IS_COMPILED        | 字符集是否已编译到服务器中。                   |
-| SORTLEN            | 与在字符集中表达的字符串排序所需的内存量有关。 |
diff --git a/docs/zh/reference/information_schema/column_privileges.md b/docs/zh/reference/information_schema/column_privileges.md
deleted file mode 100644
index 9eef54556fdc2d..00000000000000
--- a/docs/zh/reference/information_schema/column_privileges.md
+++ /dev/null
@@ -1,25 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# column_privileges
-
-:::note
-
-该视图不适用于 StarRocks 当前支持的功能。
-
-:::
-
-`column_privileges` 用于识别当前启用的角色被授予的或由当前启用的角色授予的所有列权限。
-
-`column_privileges` 提供以下字段：
-
-| 字段           | 描述                                                         |
-| -------------- | ------------------------------------------------------------ |
-| GRANTEE        | 被授予权限的用户的名称。                                     |
-| TABLE_CATALOG  | 包含列的表所属的目录的名称。该值始终为 `def`。               |
-| TABLE_SCHEMA   | 包含列的表所属的模式（数据库）的名称。                       |
-| TABLE_NAME     | 包含列的表的名称。                                           |
-| COLUMN_NAME    | 列的名称。                                                   |
-| PRIVILEGE_TYPE | 被授予的权限。该值可以是在列级别授予的任何权限。每一行列出一个权限，因此对于被授予者拥有的每个列权限，都有一行。 |
-| IS_GRANTABLE   | 如果用户具有 `GRANT OPTION` 权限，则为 `YES`，否则为 `NO`。输出不将 `GRANT OPTION` 列为单独的行，其 `PRIVILEGE_TYPE` 为 `'GRANT OPTION'`。 |
diff --git a/docs/zh/reference/information_schema/columns.md b/docs/zh/reference/information_schema/columns.md
deleted file mode 100644
index d36364ea0ff93b..00000000000000
--- a/docs/zh/reference/information_schema/columns.md
+++ /dev/null
@@ -1,40 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# columns
-
-`columns` 包含有关所有表（或视图）中列的信息。
-
-:::note
-[同步物化视图](../../using_starrocks/Materialized_view-single_table.md) 的元数据并未在 `columns` 中记录。您可以通过执行 `SHOW PROC '/dbs/db/table/index_schema'` 查看同步物化视图的元数据。
-:::
-
-`columns` 提供以下字段：
-
-| 字段                     | 描述                                                         |
-| ------------------------ | ------------------------------------------------------------ |
-| TABLE_CATALOG            | 包含列的表所属的目录的名称。该值始终为 NULL。                |
-| TABLE_SCHEMA             | 包含列的表所属的模式（数据库）的名称。                       |
-| TABLE_NAME               | 包含列的表的名称。                                           |
-| COLUMN_NAME              | 列的名称。                                                   |
-| ORDINAL_POSITION         | 列在表内的顺序位置。                                         |
-| COLUMN_DEFAULT           | 列的默认值。如果列具有显式的 NULL 默认值，或者列定义中不包含 DEFAULT 子句，则为 NULL。 |
-| IS_NULLABLE              | 列是否可为 NULL。如果可以在列中存储 NULL 值，则值为 `YES`，否则为 `NO`。 |
-| DATA_TYPE                | 列的数据类型。<br />`DATA_TYPE` 值仅为类型名称，不包含其他信息。`COLUMN_TYPE` 值包含类型名称，可能还包含其他信息，如精度或长度。 |
-| CHARACTER_MAXIMUM_LENGTH | 对于字符串列，字符的最大长度。                               |
-| CHARACTER_OCTET_LENGTH   | 对于字符串列，字节的最大长度。                               |
-| NUMERIC_PRECISION        | 对于数值列，数值的精度。                                     |
-| NUMERIC_SCALE            | 对于数值列，数值的刻度。                                     |
-| DATETIME_PRECISION       | 对于时间列，小数秒的精度。                                   |
-| CHARACTER_SET_NAME       | 对于字符字符串列，字符集的名称。                             |
-| COLLATION_NAME           | 对于字符字符串列，排序规则的名称。                           |
-| COLUMN_TYPE              | 列的数据类型。<br />`DATA_TYPE` 值仅为类型名称，不包含其他信息。`COLUMN_TYPE` 值包含类型名称，可能还包含其他信息，如精度或长度。 |
-| COLUMN_KEY               | 列是否已建立索引：<br />如果 `COLUMN_KEY` 为空，则该列未建立索引，或仅作为多列非唯一索引中的次要列建立索引。<br />如果 `COLUMN_KEY` 为 `PRI`，则该列是主键，或是多列主键中的一列。<br />如果 `COLUMN_KEY` 为 `UNI`，则该列是唯一索引的第一列。<br />如果 `COLUMN_KEY` 为 `DUP`，则该列是允许在列内有多个相同值的非唯一索引的第一列。<br />如果给定表的列的多个 `COLUMN_KEY` 值都适用，则 `COLUMN_KEY` 会显示具有最高优先级的值，按照 `PRI`、`UNI`、`DUP` 的顺序。<br />如果 UNIQUE 索引不允许包含 NULL 值，并且表中没有主键，则唯一索引可能显示为 `PRI`。如果多个列形成复合唯一索引，则尽管这些列的组合是唯一的，每个列仍然可以包含多个相同值，因此可能显示为 `MUL`。 |
-| EXTRA                    | 关于给定列的任何其他信息。                                   |
-| PRIVILEGES               | 您对该列拥有的权限。                                         |
-| COLUMN_COMMENT           | 列定义中包含的任何注释。                                     |
-| COLUMN_SIZE              |                                                              |
-| DECIMAL_DIGITS           |                                                              |
-| GENERATION_EXPRESSION    | 对于生成的列，显示用于计算列值的表达式。非生成列为空。       |
-| SRS_ID                   | 此值适用于空间列。它包含列 SRID 值，指示存储在列中的值的空间参考系统。 |
diff --git a/docs/zh/reference/information_schema/engines.md b/docs/zh/reference/information_schema/engines.md
deleted file mode 100644
index 17a80faf65647d..00000000000000
--- a/docs/zh/reference/information_schema/engines.md
+++ /dev/null
@@ -1,25 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# engines
-
-:::note
-
-该视图不适用于 StarRocks 当前支持的功能。
-
-:::
-
-`engines` 提供有关存储引擎的信息。
-
-`engines` 提供以下字段：
-
-| 字段         | 描述                                                         |
-| ------------ | ------------------------------------------------------------ |
-| ENGINE       | 存储引擎的名称。                                             |
-| SUPPORT      | 服务器对存储引擎的支持水平。有效值：<br />`YES`：引擎受支持且处于活动状态。<br />`DEFAULT`：类似于 YES，此外还是默认引擎。<br />`NO`：引擎不受支持。<br />`DISABLED`：引擎受支持但已被禁用。 |
-| COMMENT      | 存储引擎的简要描述。                                         |
-| TRANSACTIONS | 存储引擎是否支持事务。                                       |
-| XA           | 存储引擎是否支持 XA 事务。                                   |
-| SAVEPOINTS   | 存储引擎是否支持保存点。                                     |
-
diff --git a/docs/zh/reference/information_schema/events.md b/docs/zh/reference/information_schema/events.md
deleted file mode 100644
index 200b16325f8f30..00000000000000
--- a/docs/zh/reference/information_schema/events.md
+++ /dev/null
@@ -1,42 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# events
-
-:::note
-
-该视图不适用于 StarRocks 当前支持的功能。
-
-:::
-
-`events` 提供有关 Event Manager 事件的信息。
-
-`events` 提供以下字段：
-
-| 字段                 | 描述                                                         |
-| -------------------- | ------------------------------------------------------------ |
-| EVENT_CATALOG        | 事件所属的目录的名称。该值始终为 def。                       |
-| EVENT_SCHEMA         | 事件所属的模式（数据库）的名称。                             |
-| EVENT_NAME           | 事件的名称。                                                 |
-| DEFINER              | DEFINER 子句中指定的用户（通常是创建事件的用户）。           |
-| TIME_ZONE            | 事件的时区，用于调度事件并在事件执行时生效。默认值为 SYSTEM。 |
-| EVENT_BODY           | 事件的 DO 子句中语句所使用的语言。该值始终为 SQL。           |
-| EVENT_DEFINITION     | 事件的 DO 子句组成的 SQL 语句的文本；换句话说，此事件执行的语句。 |
-| EVENT_TYPE           | 事件的重复类型，可以是 ONE TIME（一次性）或 RECURRING（重复）。 |
-| EXECUTE_AT           | 对于一次性事件，这是在创建事件的 CREATE EVENT 语句的 AT 子句中指定的 DATETIME 值，或者在最后一个修改事件的 ALTER EVENT 语句中指定的 DATETIME 值。此列中显示的值反映了事件的 AT 子句中包含的任何 INTERVAL 值的加法或减法。例如，如果使用 ON SCHEDULE AT CURRENT_DATETIME + '1:6' DAY_HOUR 创建事件，并且事件在 2018-02-09 14:05:30 创建，则此列中显示的值将为 '2018-02-10 20:05:30'。如果事件的时间是由 EVERY 子句而不是 AT 子句确定的（即事件是重复的），则此列的值为 NULL。 |
-| INTERVAL_VALUE       | 对于重复事件，事件执行之间等待的间隔数。对于一次性事件，该值始终为 NULL。 |
-| INTERVAL_FIELD       | 重复事件等待重复之前使用的间隔的时间单位。对于一次性事件，该值始终为 NULL。 |
-| SQL_MODE             | 事件创建或更改时有效的 SQL 模式，以及事件执行时使用的 SQL 模式。 |
-| STARTS               | 重复事件的开始日期和时间。显示为 DATETIME 值，如果未为事件定义开始日期和时间，则为 NULL。对于一次性事件，此列始终为 NULL。对于定义包含 STARTS 子句的重复事件，此列包含相应的 DATETIME 值。与 EXECUTE_AT 列一样，此值解析了任何使用的表达式。如果没有 STARTS 子句影响事件的时间，此列为 NULL。 |
-| ENDS                 | 对于定义包含 ENDS 子句的重复事件，此列包含相应的 DATETIME 值。与 EXECUTE_AT 列一样，此值解析了任何使用的表达式。如果没有 ENDS 子句影响事件的时间，此列为 NULL。 |
-| STATUS               | 事件的状态。ENABLED、DISABLED 或 SLAVESIDE_DISABLED 中的一个。SLAVESIDE_DISABLED 表示事件的创建发生在充当复制源的另一台 MySQL 服务器上，并且复制到充当副本的当前 MySQL 服务器，但事件当前未在副本上执行。 |
-| ON_COMPLETION        | 有效值：PRESERVE 和 NOT PRESERVE。                           |
-| CREATED              | 事件创建的日期和时间。这是一个 DATETIME 值。                 |
-| LAST_ALTERED         | 事件上次修改的日期和时间。这是一个 DATETIME 值。如果事件自创建以来未被修改，则此值与 CREATED 值相同。 |
-| LAST_EXECUTED        | 事件上次执行的日期和时间。这是一个 DATETIME 值。如果事件从未执行过，则此列为 NULL。LAST_EXECUTED 指示事件何时开始执行。因此，ENDS 列永远不会小于 LAST_EXECUTED。 |
-| EVENT_COMMENT        | 事件的注释文本，如果事件有注释。如果没有，则此值为空。       |
-| ORIGINATOR           | 事件创建时所在的 MySQL 服务器的服务器 ID；用于复制。如果在复制源上执行，则 ALTER EVENT 可更新此值为该语句发生的服务器的服务器 ID。默认值为 0。 |
-| CHARACTER_SET_CLIENT | 创建事件时 character_set_client 系统变量的会话值。           |
-| COLLATION_CONNECTION | 创建事件时 collation_connection 系统变量的会话值。           |
-| DATABASE_COLLATION   | 与事件关联的数据库的排序规则。                               |
diff --git a/docs/zh/reference/information_schema/global_variables.md b/docs/zh/reference/information_schema/global_variables.md
deleted file mode 100644
index acfb7b51a0902e..00000000000000
--- a/docs/zh/reference/information_schema/global_variables.md
+++ /dev/null
@@ -1,15 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# global_variables
-
-`global_variables` 提供有关全局变量的信息。
-
-`global_variables` 提供以下字段：
-
-| **字段**       | **描述**       |
-| -------------- | -------------- |
-| VARIABLE_NAME  | 全局变量的名称 |
-| VARIABLE_VALUE | 全局变量的值   |
-
diff --git a/docs/zh/reference/information_schema/key_column_usage.md b/docs/zh/reference/information_schema/key_column_usage.md
deleted file mode 100644
index 442ec739fe380f..00000000000000
--- a/docs/zh/reference/information_schema/key_column_usage.md
+++ /dev/null
@@ -1,30 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# key_column_usage
-
-:::note
-
-该视图不适用于 StarRocks 当前支持的功能。
-
-:::
-
-`key_column_usage` 用于识别受某些唯一、主键或外键约束限制的所有列。
-
-`key_column_usage` 提供以下字段：
-
-| 字段                          | 描述                                                         |
-| ----------------------------- | ------------------------------------------------------------ |
-| CONSTRAINT_CATALOG            | 约束所属的目录的名称。该值始终为 def。                       |
-| CONSTRAINT_SCHEMA             | 约束所属的数据库的名称。                                     |
-| CONSTRAINT_NAME               | 约束的名称。                                                 |
-| TABLE_CATALOG                 | 表所属的目录的名称。该值始终为 def。                         |
-| TABLE_SCHEMA                  | 表所属的数据库的名称。                                       |
-| TABLE_NAME                    | 具有约束的表的名称。                                         |
-| COLUMN_NAME                   | 具有约束的列的名称。如果约束是外键，则这是外键的列，而不是外键引用的列。 |
-| ORDINAL_POSITION              | 列在约束内的位置，而不是列在表内的位置。列位置从 1 开始编号。 |
-| POSITION_IN_UNIQUE_CONSTRAINT | 对于唯一和主键约束，为 NULL。对于外键约束，此列是被引用的表中 key 的序数位置。 |
-| REFERENCED_TABLE_SCHEMA       | 约束引用的模式的名称。                                       |
-| REFERENCED_TABLE_NAME         | 约束引用的表的名称。                                         |
-| REFERENCED_COLUMN_NAME        | 约束引用的列的名称。                                         |
diff --git a/docs/zh/reference/information_schema/load_tracking_logs.md b/docs/zh/reference/information_schema/load_tracking_logs.md
deleted file mode 100644
index 8cbff9ad4110f0..00000000000000
--- a/docs/zh/reference/information_schema/load_tracking_logs.md
+++ /dev/null
@@ -1,36 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# load_tracking_logs
-
-提供导入作业相关的错误信息。此视图自 StarRocks v3.0 起支持。
-
-`load_tracking_logs` 提供以下字段：
-
-| **字段**      | **描述**                         |
-| ------------- | ------------------------------- |
-| ID            | 导入ID。                  |
-| JOB_ID        | 导入作业的 ID（已废弃）。           |
-| LABEL         | 导入作业的 Label。               |
-| DATABASE_NAME | 导入作业所属的数据库名称。       |
-| TRACKING_LOG  | 导入作业的错误日志信息（如有）。 |
-
-:::tip
-查询 `load_tracking_logs` 视图时，您需要根据 `JOB_ID` 或 `LABEL` 进行过滤。
-
-您可以通过 `information_schema.loads` 视图查询已有的 `JOB_ID` 和 `LABEL` 。
-
-示例：
-
-```sql
-SELECT * from information_schema.load_tracking_logs WHERE label ='user_behavior'\G
-*************************** 1. row ***************************
-       JOB_ID: 10141
-        LABEL: user_behavior
-DATABASE_NAME: mydatabase
- TRACKING_LOG: NULL
-         TYPE: BROKER
-1 row in set (0.02 sec)
-```
-:::
diff --git a/docs/zh/reference/information_schema/loads.md b/docs/zh/reference/information_schema/loads.md
deleted file mode 100644
index e29881bb11e4a9..00000000000000
--- a/docs/zh/reference/information_schema/loads.md
+++ /dev/null
@@ -1,35 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# loads
-
-提供导入作业的结果信息。此视图自 StarRocks v3.1 版本起支持。当前仅支持查看 [Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 和 [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 导入作业的结果信息。
-
-`loads` 提供以下字段：
-
-| **字段**             | **说明**                                                     |
-| -------------------- | ------------------------------------------------------------ |
-| JOB_ID               | 导入作业的 ID，由 StarRocks 自动生成。                       |
-| LABEL                | 导入作业的标签。                                             |
-| DATABASE_NAME        | 目标 StarRocks 表所在的数据库的名称。                        |
-| STATE                | 导入作业的状态，包括：<ul><li>`PENDING`：导入作业已创建。</li><li>`QUEUEING`：导入作业正在等待执行中。</li><li>`LOADING`：导入作业正在执行中。</li><li>`PREPARED`：事务已提交。</li><li>`FINISHED`：导入作业成功。</li><li>`CANCELLED`：导入作业失败。</li></ul>请参见[异步导入](../../loading/loading_introduction/loading_concepts.md#异步导入)。 |
-| PROGRESS             | 导入作业 ETL 阶段和 LOADING 阶段的进度。                     |
-| TYPE                 | 导入作业的类型。如果是 Broker Load 导入，则返回 `BROKER`。如果是 INSERT 导入，则返回 `INSERT`。 |
-| PRIORITY             | 导入作业的优先级。取值范围：`HIGHEST`、`HIGH`、`NORMAL`、`LOW`、`LOWEST`。 |
-| SCAN_ROWS            | 扫描的数据行总数。                                           |
-| FILTERED_ROWS        | 因数据质量不合格而过滤掉的错误数据行总数。                   |
-| UNSELECTED_ROWS      | 根据 WHERE 子句中指定的条件过滤掉的数据行总数。              |
-| SINK_ROWS            | 完成导入的数据行总数。                                       |
-| ETL_INFO             | ETL 详情。该字段只对 Spark Load 作业有效。如果是其他类型的导入作业，则返回结果为空。 |
-| TASK_INFO            | 导入作业的详情，比如导入作业的超时时长 (`timeout`) 和最大容忍率 (`max_filter_ratio`) 等。 |
-| CREATE_TIME          | 导入作业的创建时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
-| ETL_START_TIME       | ETL 阶段的开始时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
-| ETL_FINISH_TIME      | ETL 阶段的结束时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
-| LOAD_START_TIME      | LOADING 阶段的开始时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
-| LOAD_FINISH_TIME     | LOADING 阶段的结束时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
-| JOB_DETAILS          | 导入数据的详情，包括导入的数据大小（按字节数计）、文件个数等。 |
-| ERROR_MSG            | 导入作业的错误信息。如果没有错误，则返回 `NULL`。            |
-| TRACKING_URL         | 导入作业中质量不合格数据采样的访问地址。可以使用 `curl` 命令或 `wget` 命令访问该地址。如果导入作业中不存在质量不合格的数据，则返回 `NULL`。 |
-| TRACKING_SQL         | 导入作业跟踪日志的查询语句。仅在导入作业包含不合格数据时才会返回查询语句。如果导入作业未包含不合格数据，则返回 `NULL`。 |
-| REJECTED_RECORD_PATH | 导入作业中质量不合格数据的访问地址。返回的不合格数据结果条数，由导入作业中 `log_rejected_record_num` 参数的设置决定。您可以使用 `wget` 命令访问该地址。如果导入作业中不存在质量不合格的数据，则返回 `NULL`。 |
diff --git a/docs/zh/reference/information_schema/materialized_views.md b/docs/zh/reference/information_schema/materialized_views.md
deleted file mode 100644
index 394d5b136f1cf3..00000000000000
--- a/docs/zh/reference/information_schema/materialized_views.md
+++ /dev/null
@@ -1,34 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# materialized_views
-
-`materialized_views` 提供有关所有物化视图的信息。
-
-`materialized_views` 提供以下字段：
-
-| **字段**                             | **描述**                                         |
-| ------------------------------------ | ------------------------------------------------ |
-| MATERIALIZED_VIEW_ID                 | 物化视图 ID。                                    |
-| TABLE_SCHEMA                         | 物化视图所在的数据库名称。                       |
-| TABLE_NAME                           | 物化视图名称。                                   |
-| REFRESH_TYPE                         | 物化视图（刷新）类型，包括 `ROLLUP`（同步物化视图）、`ASYNC`（异步刷新物化视图）以及 `MANUAL`（手动刷新物化视图）。当此值为 `ROLLUP` 时，以下生效状态和刷新相关的字段为空。 |
-| IS_ACTIVE                            | 是否生效，失效的物化视图不会被刷新和查询改写。   |
-| INACTIVE_REASON                      | 失效的原因。                                     |
-| PARTITION_TYPE                       | 物化视图分区类型。                               |
-| TASK_ID                              | 物化视图刷新任务的 ID。                          |
-| TASK_NAME                            | 物化视图刷新任务的名称。                         |
-| LAST_REFRESH_START_TIME              | 最近一次刷新任务的开始时间。                     |
-| LAST_REFRESH_FINISHED_TIME           | 最近一次刷新任务的结束时间。                     |
-| LAST_REFRESH_DURATION                | 最近一次刷新任务的持续时间。                     |
-| LAST_REFRESH_STATE                   | 最近一次刷新任务的状态。                         |
-| LAST_REFRESH_FORCE_REFRESH           | 最近一次刷新任务是否强制刷新。                   |
-| LAST_REFRESH_START_PARTITION         | 最近一次刷新任务的开始分区。                     |
-| LAST_REFRESH_END_PARTITION           | 最近一次刷新任务的结束分区。                     |
-| LAST_REFRESH_BASE_REFRESH_PARTITIONS | 最近一次刷新任务的基表分区。                     |
-| LAST_REFRESH_MV_REFRESH_PARTITIONS   | 最近一次刷新任务刷新的分区。                   |
-| LAST_REFRESH_ERROR_CODE              | 最近一次刷新任务的错误码。                       |
-| LAST_REFRESH_ERROR_MESSAGE           | 最近一次刷新任务的错误信息。                     |
-| TABLE_ROWS                           | 物化视图的数据行数，后台统计的近似值。           |
-| MATERIALIZED_VIEW_DEFINITION         | 物化视图的 SQL 定义。                            |
diff --git a/docs/zh/reference/information_schema/partitions.md b/docs/zh/reference/information_schema/partitions.md
deleted file mode 100644
index 819775882400a5..00000000000000
--- a/docs/zh/reference/information_schema/partitions.md
+++ /dev/null
@@ -1,42 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# partitions
-
-:::note
-
-该视图不适用于 StarRocks 当前支持的功能。
-
-:::
-
-`partitions` 提供有关表分区的信息。
-
-`partitions` 提供以下字段：
-
-| 字段                       | 描述                                                         |
-| -------------------------- | ------------------------------------------------------------ |
-| TABLE_CATALOG              | 表所属的目录的名称。该值始终为 def。                         |
-| TABLE_SCHEMA               | 表所属的数据库的名称。                                       |
-| TABLE_NAME                 | 包含分区的表的名称。                                         |
-| PARTITION_NAME             | 分区的名称。                                                 |
-| SUBPARTITION_NAME          | 如果 PARTITIONS 表行表示子分区，则为子分区的名称；否则为 NULL。对于 NDB：该值始终为 NULL。 |
-| PARTITION_ORDINAL_POSITION | 所有分区按照定义的顺序进行索引，其中 1 是分配给第一个分区的数字。随着添加、删除和重新组织分区，索引可能会发生变化；此列中显示的数字反映了当前的顺序，考虑到任何索引更改。 |
-| PARTITION_METHOD           | 有效值：RANGE、LIST、HASH、LINEAR HASH、KEY 或 LINEAR KEY。  |
-| SUBPARTITION_METHOD        | 有效值：HASH、LINEAR HASH、KEY 或 LINEAR KEY。               |
-| PARTITION_EXPRESSION       | 用于 CREATE TABLE 或 ALTER TABLE 语句中创建表的当前分区方案的分区函数的表达式。 |
-| SUBPARTITION_EXPRESSION    | 对于子分区表达式，其功能与 PARTITION_EXPRESSION 对于定义表分区的分区表达式相同。如果表没有子分区，则此列为 NULL。 |
-| PARTITION_DESCRIPTION      | 此列用于 RANGE 和 LIST 分区。对于 RANGE 分区，它包含在分区的 VALUES LESS THAN 子句中设置的值，可以是整数或 MAXVALUE。对于 LIST 分区，此列包含在分区的 VALUES IN 子句中定义的值，这是一个逗号分隔的整数值列表。对于 PARTITION_METHOD 不是 RANGE 或 LIST 的分区，此列始终为 NULL。 |
-| TABLE_ROWS                 | 分区中的表行数。                                             |
-| AVG_ROW_LENGTH             | 存储在此分区或子分区中的行的平均长度，以字节为单位。这与 DATA_LENGTH 除以 TABLE_ROWS 相同。 |
-| DATA_LENGTH                | 存储在此分区或子分区中的所有行的总长度，以字节为单位；即存储在分区或子分区中的字节总数。 |
-| MAX_DATA_LENGTH            | 可以存储在此分区或子分区中的最大字节数。                     |
-| INDEX_LENGTH               | 此分区或子分区的索引文件长度，以字节为单位。                 |
-| DATA_FREE                  | 为分区或子分区分配但未使用的字节数。                         |
-| CREATE_TIME                | 创建分区或子分区的时间。                                     |
-| UPDATE_TIME                | 上次修改分区或子分区的时间。                                 |
-| CHECK_TIME                 | 检查属于此分区或子分区的表的最后一次时间。                   |
-| CHECKSUM                   | 校验和值，如果有的话；否则为 NULL。                          |
-| PARTITION_COMMENT          | 分区的注释文本，如果有的话。如果没有，则此值为空。           |
-| NODEGROUP                  | 分区所属的节点组。                                           |
-| TABLESPACE_NAME            | 分区所属的表空间的名称。                                     |
diff --git a/docs/zh/reference/information_schema/pipe_files.md b/docs/zh/reference/information_schema/pipe_files.md
deleted file mode 100644
index ee6eb5419b9120..00000000000000
--- a/docs/zh/reference/information_schema/pipe_files.md
+++ /dev/null
@@ -1,24 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# pipe_files
-
-`pipe_files` 提供指定 Pipe 下数据文件的导入状态。此视图自 StarRocks v3.2 版本起支持。
-
-`pipe_files` 提供以下字段：
-
-| **字段**         | **描述**                                                     |
-| ---------------- | ------------------------------------------------------------ |
-| DATABASE_NAME    | Pipe 所属数据库的名称。                                      |
-| PIPE_ID          | Pipe 的唯一 ID。                                             |
-| PIPE_NAME        | Pipe 的名称。                                                |
-| FILE_NAME        | 数据文件的名称。                                             |
-| FILE_VERSION     | 数据文件的内容摘要值。                                       |
-| FILE_SIZE        | 数据文件的大小。单位：字节。                                 |
-| LAST_MODIFIED    | 数据文件的最后修改时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
-| LOAD_STATE       | 数据文件的导入状态，包括 `UNLOADED`、`LOADING`、`FINISHED`、`ERROR`。 |
-| STAGED_TIME      | 数据文件被 Pipe 首次记录的时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
-| START_LOAD_TIME  | 数据文件导入开始的时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
-| FINISH_LOAD_TIME | 数据文件导入结束的时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
-| ERROR_MSG        | 数据文件的导入错误信息。                                     |
diff --git a/docs/zh/reference/information_schema/pipes.md b/docs/zh/reference/information_schema/pipes.md
deleted file mode 100644
index a5da4019d71bc9..00000000000000
--- a/docs/zh/reference/information_schema/pipes.md
+++ /dev/null
@@ -1,26 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# pipes
-
-`pipes` 提供当前数据库或指定数据库下所有 Pipe 的详细信息。此视图自 StarRocks v3.2 版本起支持。
-
-:::note
-
-您可以通过 [SHOW PIPES](../../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md) 命令查看当前数据库或指定数据库下 Pipe。该命令也是从 3.2 版本开始支持。
-
-:::
-
-`pipes` 提供以下字段：
-
-| **字段**      | **描述**                                                     |
-| ------------- | ------------------------------------------------------------ |
-| DATABASE_NAME | Pipe 所属数据库的名称。                                      |
-| PIPE_ID       | Pipe 的唯一 ID。                                             |
-| PIPE_NAME     | Pipe 的名称。                                                |
-| TABLE_NAME    | StarRocks 目标表的名称。格式：`<database_name>.<table_name>`。 |
-| STATE         | Pipe 的状态，包括 `RUNNING`、`FINISHED`、`SUSPENDED`、`ERROR`。 |
-| LOAD_STATUS   | Pipe 下待导入数据文件的整体状态，包括如下字段：<br />`loadedFiles`：已导入的数据文件总个数。<br />`loadedBytes`：已导入的数据总量，单位为字节。<br />`loadingFiles`：正在导入的数据文件总个数。 |
-| LAST_ERROR    | Pipe 执行过程中最近一次错误的详细信息。默认值为 `NULL`。     |
-| CREATED_TIME  | Pipe 的创建时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
diff --git a/docs/zh/reference/information_schema/referential_constraints.md b/docs/zh/reference/information_schema/referential_constraints.md
deleted file mode 100644
index 6b8ad478c5d1a2..00000000000000
--- a/docs/zh/reference/information_schema/referential_constraints.md
+++ /dev/null
@@ -1,29 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# referential_constraints
-
-:::note
-
-该视图不适用于 StarRocks 当前支持的功能。
-
-:::
-
-`referential_constraints` 包含所有参照（外键）约束。
-
-`referential_constraints` 提供以下字段：
-
-| 字段                      | 描述                                                         |
-| ------------------------- | ------------------------------------------------------------ |
-| CONSTRAINT_CATALOG        | 约束所属的目录的名称。该值始终为 def。                       |
-| CONSTRAINT_SCHEMA         | 约束所属的数据库的名称。                                     |
-| CONSTRAINT_NAME           | 约束的名称。                                                 |
-| UNIQUE_CONSTRAINT_CATALOG | 包含约束引用的唯一约束的目录的名称。该值始终为 def。         |
-| UNIQUE_CONSTRAINT_SCHEMA  | 包含约束引用的唯一约束的模式的名称。                         |
-| UNIQUE_CONSTRAINT_NAME    | 约束引用的唯一约束的名称。                                   |
-| MATCH_OPTION              | 约束 MATCH 属性的值。目前唯一有效的值是 NONE。               |
-| UPDATE_RULE               | 约束 ON UPDATE 属性的值。有效值：CASCADE、SET NULL、SET DEFAULT、RESTRICT 和 NO ACTION。 |
-| DELETE_RULE               | 约束 ON DELETE 属性的值。有效值：CASCADE、SET NULL、SET DEFAULT、RESTRICT 和 NO ACTION。 |
-| TABLE_NAME                | 表的名称。此值与 TABLE_CONSTRAINTS 表中的相同。              |
-| REFERENCED_TABLE_NAME     | 约束引用的表的名称。                                         |
diff --git a/docs/zh/reference/information_schema/routines.md b/docs/zh/reference/information_schema/routines.md
deleted file mode 100644
index b70d337079751e..00000000000000
--- a/docs/zh/reference/information_schema/routines.md
+++ /dev/null
@@ -1,42 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# routines
-
-:::note
-
-该视图不适用于 StarRocks 当前支持的功能。
-
-:::
-
-`routines` 包含所有存储的过程（Routine），包括流程和函数。
-
-`routine` 提供以下字段：
-
-| 字段                 | 描述                                                         |
-| -------------------- | ------------------------------------------------------------ |
-| SPECIFIC_NAME        | 过程的名称。                                                 |
-| ROUTINE_CATALOG      | 过程所属的目录的名称。该值始终为 def。                       |
-| ROUTINE_SCHEMA       | 过程所属的数据库的名称。                                     |
-| ROUTINE_NAME         | 过程的名称。                                                 |
-| ROUTINE_TYPE         | 存储过程的类型为 PROCEDURE，存储函数的类型为 FUNCTION。      |
-| DTD_IDENTIFIER       | 如果过程是存储函数，则为返回值的数据类型。如果过程是存储过程，则此值为空。 |
-| ROUTINE_BODY         | 用于过程定义的语言。此值始终为 SQL。                         |
-| ROUTINE_DEFINITION   | 过程执行的 SQL 语句的文本。                                  |
-| EXTERNAL_NAME        | 此值始终为 NULL。                                            |
-| EXTERNAL_LANGUAGE    | 存储过程的语言。                                             |
-| PARAMETER_STYLE      | 此值始终为 SQL。                                             |
-| IS_DETERMINISTIC     | 取决于是否使用 DETERMINISTIC 特性定义了过程。可以是 YES 或 NO。 |
-| SQL_DATA_ACCESS      | 过程的数据访问特性。该值是 CONTAINS SQL、NO SQL、READS SQL DATA 或 MODIFIES SQL DATA 中的一个。 |
-| SQL_PATH             | 此值始终为 NULL。                                            |
-| SECURITY_TYPE        | 过程的 SQL SECURITY 特性。该值是 DEFINER 或 INVOKER 中的一个。 |
-| CREATED              | 过程创建的日期和时间。这是一个 DATETIME 值。                 |
-| LAST_ALTERED         | 过程上次修改的日期和时间。这是一个 DATETIME 值。如果自创建以来过程未被修改，则此值与 CREATED 值相同。 |
-| SQL_MODE             | 过程创建或修改时生效的 SQL 模式，并在其中运行过程。          |
-| ROUTINE_COMMENT      | 过程的注释文本，如果有的话。如果没有，则此值为空。           |
-| DEFINER              | 在 DEFINER 子句中指定的用户（通常是创建过程的用户）。        |
-| CHARACTER_SET_CLIENT |                                                              |
-| COLLATION_CONNECTION |                                                              |
-| DATABASE_COLLATION   | 过程关联的数据库的排序规则。                                 |
-
diff --git a/docs/zh/reference/information_schema/schema_privileges.md b/docs/zh/reference/information_schema/schema_privileges.md
deleted file mode 100644
index 4a69aa51aa70af..00000000000000
--- a/docs/zh/reference/information_schema/schema_privileges.md
+++ /dev/null
@@ -1,23 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# schema_privileges
-
-:::note
-
-该视图不适用于 StarRocks 当前支持的功能。
-
-:::
-
-`schema_privileges` 提供有关数据库权限的信息。
-
-`schema_privileges` 提供以下字段：
-
-| 字段           | 描述                                                         |
-| -------------- | ------------------------------------------------------------ |
-| GRANTEE        | 授予权限的用户的名称。                                       |
-| TABLE_CATALOG  | 模式所属的目录的名称。该值始终为 def。                       |
-| TABLE_SCHEMA   | 模式的名称。                                                 |
-| PRIVILEGE_TYPE | 所授予的权限。每一行列出一个权限，因此每个由授予权限的用户拥有的模式权限都有一行。 |
-| IS_GRANTABLE   | 如果用户具有 GRANT OPTION 权限，则为 YES；否则为 NO。输出不会将 GRANT OPTION 作为单独的行列出，而是使用 PRIVILEGE_TYPE='GRANT OPTION'。 |
diff --git a/docs/zh/reference/information_schema/schemata.md b/docs/zh/reference/information_schema/schemata.md
deleted file mode 100644
index 03b223351cb63f..00000000000000
--- a/docs/zh/reference/information_schema/schemata.md
+++ /dev/null
@@ -1,17 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# schemata
-
-`schemata` 提供有关数据库的信息。
-
-`schemata` 提供以下字段：
-
-| 字段                       | 描述                                    |
-| -------------------------- | --------------------------------------- |
-| CATALOG_NAME               | 模式所属的目录的名称。该值始终为 NULL。 |
-| SCHEMA_NAME                | 模式的名称。                            |
-| DEFAULT_CHARACTER_SET_NAME | 模式的默认字符集。                      |
-| DEFAULT_COLLATION_NAME     | 模式的默认排序规则。                    |
-| SQL_PATH                   | 此值始终为 NULL。                       |
diff --git a/docs/zh/reference/information_schema/session_variables.md b/docs/zh/reference/information_schema/session_variables.md
deleted file mode 100644
index e0cedad44b9b5d..00000000000000
--- a/docs/zh/reference/information_schema/session_variables.md
+++ /dev/null
@@ -1,14 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# session_variables
-
-`session_variables` 提供有关 Session 变量的信息。
-
-`session_variables` 提供以下字段：
-
-| **字段**       | **描述**             |
-| -------------- | -------------------- |
-| VARIABLE_NAME  | Session 变量的名称。 |
-| VARIABLE_VALUE | Session 变量的值。   |
diff --git a/docs/zh/reference/information_schema/statistics.md b/docs/zh/reference/information_schema/statistics.md
deleted file mode 100644
index 2c83ecaa810c4b..00000000000000
--- a/docs/zh/reference/information_schema/statistics.md
+++ /dev/null
@@ -1,34 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# statistics
-
-:::note
-
-该视图不适用于 StarRocks 当前支持的功能。
-
-:::
-
-`statistics` 提供有关表索引的信息。
-
-`statistics` 提供以下字段：
-
-| 字段          | 描述                                                         |
-| ------------- | ------------------------------------------------------------ |
-| TABLE_CATALOG | 包含索引的表所属的目录的名称。该值始终为 def。               |
-| TABLE_SCHEMA  | 包含索引的表所属的数据库的名称。                             |
-| TABLE_NAME    | 包含索引的表的名称。                                         |
-| NON_UNIQUE    | 如果索引不能包含重复值，则为 0；如果可以，则为 1。           |
-| INDEX_SCHEMA  | 索引所属的数据库的名称。                                     |
-| INDEX_NAME    | 索引的名称。如果索引是主键，则名称始终为 PRIMARY。           |
-| SEQ_IN_INDEX  | 索引中的列序号，从 1 开始。                                  |
-| COLUMN_NAME   | 列名。有关 EXPRESSION 列的描述，请参见下文。                 |
-| COLLATION     | 列在索引中的排序方式。可以有值 A（升序）、D（降序）或 NULL（未排序）。 |
-| CARDINALITY   | 索引中唯一值的估计数量。                                     |
-| SUB_PART      | 索引前缀。即，如果只对列的一部分进行索引，则为索引的字符数，如果整个列都被索引，则为 NULL。 |
-| PACKED        | 指示键如何被打包。如果没有打包，则为 NULL。                  |
-| NULLABLE      | 如果列可能包含 NULL 值，则为 YES，如果不可能，则为''。       |
-| INDEX_TYPE    | 使用的索引方法（BTREE、FULLTEXT、HASH、RTREE）。             |
-| COMMENT       | 有关索引的信息，未在其自己的列中描述，例如，如果索引已禁用，则为 disabled。 |
-| INDEX_COMMENT | 在创建索引时使用 COMMENT 属性为索引提供的任何注释。          |
diff --git a/docs/zh/reference/information_schema/table_constraints.md b/docs/zh/reference/information_schema/table_constraints.md
deleted file mode 100644
index e327862d95d995..00000000000000
--- a/docs/zh/reference/information_schema/table_constraints.md
+++ /dev/null
@@ -1,24 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# table_constraints
-
-:::note
-
-该视图不适用于 StarRocks 当前支持的功能。
-
-:::
-
-`table_constraints` 描述具有约束的表。
-
-`table_constraints` 提供以下字段：
-
-| 字段               | 描述                                   |
-| ------------------ | -------------------------------------- |
-| CONSTRAINT_CATALOG | 约束所属的目录的名称。该值始终为 def。 |
-| CONSTRAINT_SCHEMA  | 约束所属的数据库的名称。               |
-| CONSTRAINT_NAME    | 约束的名称。                           |
-| TABLE_SCHEMA       | 表所属的数据库的名称。                 |
-| TABLE_NAME         | 表的名称。                             |
-| CONSTRAINT_TYPE    | 约束的类型。                           |
diff --git a/docs/zh/reference/information_schema/table_privileges.md b/docs/zh/reference/information_schema/table_privileges.md
deleted file mode 100644
index 13ef9683edc32d..00000000000000
--- a/docs/zh/reference/information_schema/table_privileges.md
+++ /dev/null
@@ -1,25 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# table_privileges
-
-:::note
-
-该视图不适用于 StarRocks 当前支持的功能。
-
-:::
-
-`table_privileges` 提供有关表权限的信息。
-
-`table_privileges` 提供以下字段：
-
-| 字段           | 描述                                                         |
-| -------------- | ------------------------------------------------------------ |
-| GRANTEE        | 授予权限的用户的名称。                                       |
-| TABLE_CATALOG  | 表所属的目录的名称。该值始终为 def。                         |
-| TABLE_SCHEMA   | 表所属的数据库的名称。                                       |
-| TABLE_NAME     | 表的名称。                                                   |
-| PRIVILEGE_TYPE | 所授予的权限。该值可以是可在表级别授予的任何权限。           |
-| IS_GRANTABLE   | 如果用户具有 GRANT OPTION 权限，则为 YES；否则为 NO。输出不会将 GRANT OPTION 作为单独的行列出，而是使用 PRIVILEGE_TYPE='GRANT OPTION'。 |
-
diff --git a/docs/zh/reference/information_schema/tables.md b/docs/zh/reference/information_schema/tables.md
deleted file mode 100644
index 4aafe2494b8efc..00000000000000
--- a/docs/zh/reference/information_schema/tables.md
+++ /dev/null
@@ -1,33 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# tables
-
-`tables` 提供有关表的信息。
-
-`tables` 提供以下字段：
-
-| **字段**        | **描述**                                                     |
-| --------------- | ------------------------------------------------------------ |
-| TABLE_CATALOG   | 表所属的 Catalog 名称。                                      |
-| TABLE_SCHEMA    | 表所属的数据库名称。                                         |
-| TABLE_NAME      | 表名。                                                       |
-| TABLE_TYPE      | 表的类型。有效值：`BASE TABLE` 和 `VIEW`。                  |
-| ENGINE          | 表的引擎类型。有效值：`StarRocks`、`MySQL`、`MEMORY` 和空字符串。 |
-| VERSION         | 该字段暂不可用。                                             |
-| ROW_FORMAT      | 该字段暂不可用。                                             |
-| TABLE_ROWS      | 表的行数。                                                   |
-| AVG_ROW_LENGTH  | 表的平均行长度（大小），等于 `DATA_LENGTH`/`TABLE_ROWS`。单位：Byte。 |
-| DATA_LENGTH     | 数据长度（大小）。单位：Byte。                              |
-| MAX_DATA_LENGTH | 该字段暂不可用。                                             |
-| INDEX_LENGTH    | 该字段暂不可用。                                             |
-| DATA_FREE       | 该字段暂不可用。                                             |
-| AUTO_INCREMENT  | 该字段暂不可用。                                             |
-| CREATE_TIME     | 创建表的时间。                                               |
-| UPDATE_TIME     | 最后一次更新表的时间。                                       |
-| CHECK_TIME      | 最后一次对表进行一致性检查的时间。                           |
-| TABLE_COLLATION | 表的默认 Collation。                                         |
-| CHECKSUM        | 该字段暂不可用。                                             |
-| CREATE_OPTIONS  | 该字段暂不可用。                                             |
-| TABLE_COMMENT   | 表的 Comment。                                               |
diff --git a/docs/zh/reference/information_schema/tables_config.md b/docs/zh/reference/information_schema/tables_config.md
deleted file mode 100644
index acc87d92402c85..00000000000000
--- a/docs/zh/reference/information_schema/tables_config.md
+++ /dev/null
@@ -1,24 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# tables_config
-
-`tables_config` 提供有关表配置的信息。
-
-`tables_config` 提供以下字段：
-
-| **字段**         | **描述**                                                     |
-| ---------------- | ------------------------------------------------------------ |
-| TABLE_SCHEMA     | 表所属的数据库名称。                                         |
-| TABLE_NAME       | 表名。                                                       |
-| TABLE_ENGINE     | 表的引擎类型。                                               |
-| TABLE_MODEL      | 表的类型。 有效值：`DUP_KEYS`、`AGG_KEYS`、`UNQ_KEYS` 和 `PRI_KEYS`。 |
-| PRIMARY_KEY      | 主键表或更新表的唯一约束键。如果该表不是主键表或更新表，则返回空字符串。 |
-| PARTITION_KEY    | 表的分区键。                                                 |
-| DISTRIBUTE_KEY   | 表的分桶键。                                                 |
-| DISTRIBUTE_TYPE  | 表的分桶方式。                                               |
-| DISTRUBTE_BUCKET | 表的分桶数。                                                 |
-| SORT_KEY         | 表的排序键。                                                 |
-| PROPERTIES       | 表的属性。                                                   |
-| TABLE_ID         | 表的 ID。                                                    |
diff --git a/docs/zh/reference/information_schema/task_runs.md b/docs/zh/reference/information_schema/task_runs.md
deleted file mode 100644
index 1c797c2e5fb518..00000000000000
--- a/docs/zh/reference/information_schema/task_runs.md
+++ /dev/null
@@ -1,24 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# task_runs
-
-`task_runs` 提供有关异步任务执行的信息。
-
-`task_runs` 提供以下字段：
-
-| 字段          | 描述                                                         |
-| ------------- | ------------------------------------------------------------ |
-| QUERY_ID      | 查询的 ID。                                                  |
-| TASK_NAME     | 任务的名称。                                                 |
-| CREATE_TIME   | 任务创建的时间。                                             |
-| FINISH_TIME   | 任务完成的时间。                                             |
-| STATE         | 任务的状态，包括 `PENDING`（待处理）、`RUNNING`（运行中）、`FAILED`（失败）和 `SUCCESS`（成功）。从 v3.1.12 开始，新增了一个专门用于物化视图刷新任务的状态 `MERGED`。当提交新的刷新任务时，如果旧任务仍在 PENDING 队列中，这些任务将被合并，并保持其优先级属性。 |
-| DATABASE      | 任务所属的数据库。                                           |
-| DEFINITION    | 任务的 SQL 定义。                                            |
-| EXPIRE_TIME   | 任务过期的时间。                                             |
-| ERROR_CODE    | 任务的错误代码。                                             |
-| ERROR_MESSAGE | 任务的错误消息。                                             |
-| PROGRESS      | 任务的进度。                                                 |
-| EXTRA_MESSAGE | 任务的额外消息，例如在异步物化视图创建任务中的分区信息。     |
diff --git a/docs/zh/reference/information_schema/tasks.md b/docs/zh/reference/information_schema/tasks.md
deleted file mode 100644
index 6013fa53e1d3e6..00000000000000
--- a/docs/zh/reference/information_schema/tasks.md
+++ /dev/null
@@ -1,18 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# tasks
-
-`tasks` 提供有关异步任务的信息。
-
-`tasks` 提供以下字段：
-
-| **字段**    | **描述**                                                     |
-| ----------- | ------------------------------------------------------------ |
-| TASK_NAME   | 任务的名称。                                                 |
-| CREATE_TIME | 任务创建的时间。                                             |
-| SCHEDULE    | 任务调度。如果任务为周期运行，会显示 `START xxx EVERY xxx`。 |
-| DATABASE    | 任务所属的数据库。                                           |
-| DEFINITION  | 任务的 SQL 定义。                                            |
-| EXPIRE_TIME | 任务过期的时间。                                             |
diff --git a/docs/zh/reference/information_schema/triggers.md b/docs/zh/reference/information_schema/triggers.md
deleted file mode 100644
index e1cde5b899c958..00000000000000
--- a/docs/zh/reference/information_schema/triggers.md
+++ /dev/null
@@ -1,40 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# triggers
-
-:::note
-
-该视图不适用于 StarRocks 当前支持的功能。
-
-:::
-
-`triggers` 提供有关触发器的信息。
-
-`triggers` 提供以下字段：
-
-| 字段                       | 描述                                                         |
-| -------------------------- | ------------------------------------------------------------ |
-| TRIGGER_CATALOG            | 触发器所属的目录的名称。该值始终为 def。                     |
-| TRIGGER_SCHEMA             | 触发器所属的数据库的名称。                                   |
-| TRIGGER_NAME               | 触发器的名称。                                               |
-| EVENT_MANIPULATION         | 触发器事件。这是触发器激活的相关表上的操作类型。该值可以是 INSERT（插入了一行）、DELETE（删除了一行）或 UPDATE（修改了一行）。 |
-| EVENT_OBJECT_CATALOG       | 每个触发器与确切的一张表关联。这张表所在的目录。             |
-| EVENT_OBJECT_SCHEMA        | 每个触发器与确切的一张表关联。这张表所在的数据库。           |
-| EVENT_OBJECT_TABLE         | 触发器关联的表的名称。                                       |
-| ACTION_ORDER               | 触发器动作在与相同 EVENT_MANIPULATION 和 ACTION_TIMING 值的同一张表上的触发器列表中的顺序位置。 |
-| ACTION_CONDITION           | 该值始终为 NULL。                                            |
-| ACTION_STATEMENT           | 触发器体；也就是触发器激活时执行的语句。此文本使用 UTF-8 编码。 |
-| ACTION_ORIENTATION         | 该值始终为 ROW。                                             |
-| ACTION_TIMING              | 触发器是在触发事件之前还是之后激活。该值为 BEFORE 或 AFTER。 |
-| ACTION_REFERENCE_OLD_TABLE | 该值始终为 NULL。                                            |
-| ACTION_REFERENCE_NEW_TABLE | 该值始终为 NULL。                                            |
-| ACTION_REFERENCE_OLD_ROW   | 旧列标识符。该值始终为 OLD。                                 |
-| ACTION_REFERENCE_NEW_ROW   | 新列标识符。该值始终为 NEW。                                 |
-| CREATED                    | 触发器创建的日期和时间。对于触发器，这是一个 DATETIME(2) 值（百分之一秒的小数部分）。 |
-| SQL_MODE                   | 触发器创建时有效的 SQL 模式，以及触发器执行的 SQL 模式。     |
-| DEFINER                    | 在 DEFINER 子句中命名的用户（通常是创建触发器的用户）。      |
-| CHARACTER_SET_CLIENT       |                                                              |
-| COLLATION_CONNECTION       |                                                              |
-| DATABASE_COLLATION         | 与触发器关联的数据库的排序规则。                             |
diff --git a/docs/zh/reference/information_schema/user_privileges.md b/docs/zh/reference/information_schema/user_privileges.md
deleted file mode 100644
index ffd0b4d1ab4d6c..00000000000000
--- a/docs/zh/reference/information_schema/user_privileges.md
+++ /dev/null
@@ -1,22 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# user_privileges
-
-:::note
-
-该视图不适用于 StarRocks 当前支持的功能。
-
-:::
-
-`user_privileges` 提供有关用户权限的信息。
-
-`user_privileges` 提供以下字段：
-
-| 字段           | 描述                                                         |
-| -------------- | ------------------------------------------------------------ |
-| GRANTEE        | 被授予权限的用户的名称。                                     |
-| TABLE_CATALOG  | 目录的名称。该值始终为 def。                                 |
-| PRIVILEGE_TYPE | 授予的权限。该值可以是可在全局级别授予的任何权限。           |
-| IS_GRANTABLE   | 如果用户具有 GRANT OPTION 权限，则为 YES，否则为 NO。输出不会将 GRANT OPTION 作为 PRIVILEGE_TYPE='GRANT OPTION' 的单独行列出。 |
diff --git a/docs/zh/reference/information_schema/views.md b/docs/zh/reference/information_schema/views.md
deleted file mode 100644
index 27ca6be8e96f4c..00000000000000
--- a/docs/zh/reference/information_schema/views.md
+++ /dev/null
@@ -1,22 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# views
-
-`views` 提供有关所有用户定义视图的信息。
-
-`views` 提供以下字段：
-
-| 字段                 | 描述                                                         |
-| -------------------- | ------------------------------------------------------------ |
-| TABLE_CATALOG        | 视图所属的目录名称。此值始终为 def。                         |
-| TABLE_SCHEMA         | 视图所属的数据库名称。                                       |
-| TABLE_NAME           | 视图的名称。                                                 |
-| VIEW_DEFINITION      | 提供视图定义的SELECT语句。                                   |
-| CHECK_OPTION         | CHECK_OPTION 属性的值。该值是 NONE、CASCADE 或 LOCAL 中的一个。 |
-| IS_UPDATABLE         | 视图是否可更新。如果对视图的 UPDATE 和 DELETE（以及类似的操作）是合法的，则设置标志为 YES（true）。否则，标志设置为 NO（false）。如果视图不可更新，诸如 UPDATE、DELETE 和 INSERT 等语句是非法的，会被拒绝。 |
-| DEFINER              | 创建视图的用户。                                             |
-| SECURITY_TYPE        | 视图的 SQL SECURITY 特性。该值是 DEFINER 或 INVOKER 中的一个。 |
-| CHARACTER_SET_CLIENT |                                                              |
-| COLLATION_CONNECTION |                                                              |
diff --git a/docs/zh/reference/overview-pages/http_api.mdx b/docs/zh/reference/overview-pages/http_api.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/reference/overview-pages/http_api.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/reference/overview-pages/information_schema.md b/docs/zh/reference/overview-pages/information_schema.md
deleted file mode 100644
index 6be5eac5f3d4f2..00000000000000
--- a/docs/zh/reference/overview-pages/information_schema.md
+++ /dev/null
@@ -1,82 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['Yuanshuju']
----
-
-# Information Schema
-
-Information Schema 是 StarRocks 实例中的一个数据库。该数据库包含数张由系统定义的视图，这些视图中存储了关于 StarRocks 实例中所有对象的大量元数据信息。
-
-自 v3.2.0 起，Information Schema 支持管理 External Catalog 中的元数据信息。
-
-## 通过 Information Schema 查看元数据信息
-
-您可以通过查询 Information Schema 中的视图来查看 StarRocks 实例中的元数据信息。
-
-以下示例通过查询视图 `tables` 查看 StarRocks 中名为 `table1` 的表相关的元数据信息。
-
-```Plain
-MySQL > SELECT * FROM information_schema.tables WHERE TABLE_NAME like 'table1'\G
-*************************** 1. row ***************************
-  TABLE_CATALOG: def
-   TABLE_SCHEMA: test_db
-     TABLE_NAME: table1
-     TABLE_TYPE: BASE TABLE
-         ENGINE: StarRocks
-        VERSION: NULL
-     ROW_FORMAT: 
-     TABLE_ROWS: 4
- AVG_ROW_LENGTH: 1657
-    DATA_LENGTH: 6630
-MAX_DATA_LENGTH: NULL
-   INDEX_LENGTH: NULL
-      DATA_FREE: NULL
- AUTO_INCREMENT: NULL
-    CREATE_TIME: 2023-06-13 11:37:00
-    UPDATE_TIME: 2023-06-13 11:38:06
-     CHECK_TIME: NULL
-TABLE_COLLATION: utf8_general_ci
-       CHECKSUM: NULL
- CREATE_OPTIONS: 
-  TABLE_COMMENT: 
-1 row in set (0.01 sec)
-```
-
-## Information Schema 中的视图
-
-StarRocks Information Schema 中包含以下视图：
-
-| **视图名**                                                  | **描述**                                                     |
-| ----------------------------------------------------------- | ------------------------------------------------------------ |
-| [be_bvars](../information_schema/be_bvars.md)                                       | `be_bvars` 提供有关 bRPC 的统计信息。                        |
-| [be_cloud_native_compactions](../information_schema/be_cloud_native_compactions.md) | `be_cloud_native_compactions` 提供有关存算一体集群的 CN（或 v3.0 中的 BE）上运行的 Compaction 事务的信息。 |
-| [be_compactions](../information_schema/be_compactions.md)                           | `be_compactions` 提供有关 Compaction 任务的统计信息。        |
-| [character_sets](../information_schema/character_sets.md)                           | `character_sets` 用于识别可用的字符集。                      |
-| [collations](../information_schema/collations.md)                                   | `collations` 包含可用的排序规则。                            |
-| [column_privileges](../information_schema/column_privileges.md)                     | `column_privileges` 用于识别当前启用的角色被授予的或由当前启用的角色授予的所有列权限。 |
-| [columns](../information_schema/columns.md)                                         | `columns` 包含有关所有表（或视图）中列的信息。               |
-| [engines](../information_schema/engines.md)                                         | `engines` 提供有关存储引擎的信息。                           |
-| [events](../information_schema/events.md)                                           | `events` 提供有关 Event Manager 事件的信息。                 |
-| [global_variables](../information_schema/global_variables.md)                       | `global_variables` 提供有关全局变量的信息。                  |
-| [key_column_usage](../information_schema/key_column_usage.md)                       | `key_column_usage` 用于识别受某些唯一、主键或外键约束限制的所有列。 |
-| [load_tracking_logs](../information_schema/load_tracking_logs.md)                   | 提供导入作业相关的错误信息。                                 |
-| [loads](../information_schema/loads.md)                                             | 提供导入作业的结果信息。当前仅支持查看 [Broker Load](../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 和 [INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md) 导入作业的结果信息。 |
-| [materialized_views](../information_schema/materialized_views.md)                   | `materialized_views` 提供有关所有异步物化视图的信息。        |
-| [partitions](../information_schema/partitions.md)                                   | `partitions` 提供有关表分区的信息。                          |
-| [pipe_files](../information_schema/pipe_files.md)                                   | `pipe_files` 提供指定 Pipe 下数据文件的导入状态。            |
-| [pipes](../information_schema/pipes.md)                                             | `pipes` 提供当前数据库或指定数据库下所有 Pipe 的详细信息。   |
-| [referential_constraints](../information_schema/referential_constraints.md)         | `referential_constraints` 包含所有参照（外键）约束。         |
-| [routines](../information_schema/routines.md)                                       | `routines` 包含所有存储的过程（Routine），包括流程和函数。   |
-| [schema_privileges](../information_schema/schema_privileges.md)                     | `schema_privileges` 提供有关数据库权限的信息。               |
-| [schemata](../information_schema/schemata.md)                                       | `schemata` 提供有关数据库的信息。                            |
-| [session_variables](../information_schema/session_variables.md)                     | `session_variables` 提供有关 Session 变量的信息。            |
-| [statistics](../information_schema/statistics.md)                                   | `statistics` 提供有关表索引的信息。                          |
-| [table_constraints](../information_schema/table_constraints.md)                     | `table_constraints` 描述具有约束的表。                       |
-| [table_privileges](../information_schema/table_privileges.md)                       | `table_privileges` 提供有关表权限的信息。                    |
-| [tables](../information_schema/tables.md)                                           | `tables` 提供有关表的信息。                                  |
-| [tables_config](../information_schema/tables_config.md)                             | `tables_config` 提供有关表配置的信息。                       |
-| [task_runs](../information_schema/task_runs.md)                                     | `task_runs` 提供有关异步任务执行的信息。                     |
-| [tasks](../information_schema/tasks.md)                                             | `tasks` 提供有关异步任务的信息。                             |
-| [triggers](../information_schema/triggers.md)                                       | `triggers` 提供有关触发器的信息。                            |
-| [user_privileges](../information_schema/user_privileges.md)                         | `user_privileges` 提供有关用户权限的信息。                   |
-| [views](../information_schema/views.md)                                             | `views` 提供有关所有用户定义视图的信息。                     |
diff --git a/docs/zh/reference/overview-pages/sys.md b/docs/zh/reference/overview-pages/sys.md
deleted file mode 100644
index 86b2decd43a09f..00000000000000
--- a/docs/zh/reference/overview-pages/sys.md
+++ /dev/null
@@ -1,68 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 系统元数据库
-
-本文介绍如何通过系统定义的视图查看 StarRocks 集群中独有的的元数据。
-
-每个 StarRocks 集群维护一个数据库 `sys`，其中包含数张由系统定义的视图。这些视图提供了一个统一且易于使用的接口，使您可以全面了解 StarRocks 集群中的权限结构和对象依赖关系等信息。
-
-## 通过 `sys` 查看元数据信息
-
-您可以通过查询 `sys` 中的视图来查看 StarRocks 实例中的元数据信息。
-
-以下示例通过查询 `grants_to_roles` 视图查看用户自定义角色的权限。
-
-```Plain
-MySQL > SELECT * FROM sys.grants_to_roles LIMIT 5\G
-*************************** 1. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: db_test
-    OBJECT_NAME: tbl1
-    OBJECT_TYPE: TABLE
- PRIVILEGE_TYPE: SELECT, ALTER
-   IS_GRANTABLE: NO
-*************************** 2. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: db_test
-    OBJECT_NAME: tbl2
-    OBJECT_TYPE: TABLE
- PRIVILEGE_TYPE: SELECT
-   IS_GRANTABLE: YES
-*************************** 3. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: db_test
-    OBJECT_NAME: mv_test
-    OBJECT_TYPE: MATERIALIZED VIEW
- PRIVILEGE_TYPE: SELECT
-   IS_GRANTABLE: YES
-*************************** 4. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: NULL
-OBJECT_DATABASE: NULL
-    OBJECT_NAME: NULL
-    OBJECT_TYPE: SYSTEM
- PRIVILEGE_TYPE: CREATE RESOURCE GROUP
-   IS_GRANTABLE: NO
-```
-
-## `sys` 中的视图
-
-`sys` 中包含以下视图：
-
-| **视图名**               | **描述**                                                       |
-| ----------------------- | ------------------------------------------------------------- |
-| [grants_to_roles](../sys/grants_to_roles.md)     | 记录了授予用户自定义角色的权限信息。       |
-| [grants_to_users](../sys/grants_to_users.md)     | 记录了授予用户的权限信息。               |
-| [role_edges](../sys/role_edges.md)          | 记录了角色的授予关系。                        |
-| [object_dependencies](../sys/object_dependencies.md) | 记录了异步物化视图的依赖关系。        |
-
-:::note
-
-`sys` 库中的视图根据使用场景，默认只有一些管理员角色拥有查询权限。您也可以根据实际情况使用对应管理员角色将系统视图的查询权限赋予给其他用户。
-
-:::
diff --git a/docs/zh/reference/reference.mdx b/docs/zh/reference/reference.mdx
deleted file mode 100644
index 8f8c58dad84097..00000000000000
--- a/docs/zh/reference/reference.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 参考手册
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/reference/sys/grants_to_roles.md b/docs/zh/reference/sys/grants_to_roles.md
deleted file mode 100644
index c1f29eee6aea5a..00000000000000
--- a/docs/zh/reference/sys/grants_to_roles.md
+++ /dev/null
@@ -1,63 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# grants_to_roles
-
-您可以通过查询 `grants_to_roles` 视图查看用户自定义角色的权限。
-
-:::note
-
-默认仅拥有 `user_admin` 角色的用户或角色可以查询此视图，或通过 [GRANT](../../sql-reference/sql-statements/account-management/GRANT.md) 语句将此视图的权限赋予给其他用户。
-
-:::
-
-`grants_to_roles` 提供以下字段：
-
-| **字段**        | **描述**                                                     |
-| --------------- | ------------------------------------------------------------ |
-| GRANTEE         | 被授予此权限的角色。只有用户自定义角色会出现在此视图中，系统预制角色不会出现在此视图中。 |
-| OBJECT_CATALOG  | 权限对象所属的 Catalog。如果权限为 SYSTEM、RESOURCE GROUP、RESOURCE、USER 或 GLOBAL FUNCTION 级别权限，则返回 `NULL`。 |
-| OBJECT_DATABASE | 权限对象所属的数据库。如果权限为 SYSTEM、RESOURCE GROUP、RESOURCE、USER、GLOBAL FUNCTION 或 CATALOG 级别权限，则返回 `NULL`。 |
-| OBJECT_NAME     | 权限对象所属的表。如果权限为 SYSTEM、RESOURCE GROUP、RESOURCE、USER、GLOBAL FUNCTION、CATALOG 或 DATABASE 级别权限，则返回 `NULL`。 |
-| OBJECT_TYPE     | 权限对象的类型。                                             |
-| PRIVILEGE_TYPE  | 权限的类型。同一个对象上的不同权限会进行合并展示。如示例中，`role_test` 同时拥有 `default_catalog.db_test.tbl1`的`SELECT`和`ALTER`权限，则会合并展示。 |
-| IS_GRANTABLE    | 被授予角色是否拥有该权限的 GRANT 权限。                      |
-
-示例：
-
-```Plain
-MySQL > SELECT * FROM sys.grants_to_roles LIMIT 5\G
-*************************** 1. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: db_test
-    OBJECT_NAME: tbl1
-    OBJECT_TYPE: TABLE
- PRIVILEGE_TYPE: SELECT, ALTER
-   IS_GRANTABLE: NO
-*************************** 2. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: db_test
-    OBJECT_NAME: tbl2
-    OBJECT_TYPE: TABLE
- PRIVILEGE_TYPE: SELECT
-   IS_GRANTABLE: YES
-*************************** 3. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: db_test
-    OBJECT_NAME: mv_test
-    OBJECT_TYPE: MATERIALIZED VIEW
- PRIVILEGE_TYPE: SELECT
-   IS_GRANTABLE: YES
-*************************** 4. row ***************************
-        GRANTEE: role_test
- OBJECT_CATALOG: NULL
-OBJECT_DATABASE: NULL
-    OBJECT_NAME: NULL
-    OBJECT_TYPE: SYSTEM
- PRIVILEGE_TYPE: CREATE RESOURCE GROUP
-   IS_GRANTABLE: NO
-```
diff --git a/docs/zh/reference/sys/grants_to_users.md b/docs/zh/reference/sys/grants_to_users.md
deleted file mode 100644
index 3001d9d6aa00c3..00000000000000
--- a/docs/zh/reference/sys/grants_to_users.md
+++ /dev/null
@@ -1,47 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# grants_to_users
-
-您可以通过查询 `grants_to_users` 视图查看授予用户的权限。
-
-:::note
-
-默认仅拥有 `user_admin` 角色的用户或角色可以查询此视图，或通过 [GRANT](../../sql-reference/sql-statements/account-management/GRANT.md) 语句将此视图的权限赋予给其他用户。
-
-:::
-
-`grants_to_users` 提供以下字段：
-
-| **字段**        | **描述**                                                     |
-| --------------- | ------------------------------------------------------------ |
-| GRANTEE         | 被授予此权限的用户。                                         |
-| OBJECT_CATALOG  | 权限对象所属的 Catalog。如果权限为 SYSTEM、RESOURCE GROUP、RESOURCE、USER 或 GLOBAL FUNCTION 级别权限，则返回 `NULL`。 |
-| OBJECT_DATABASE | 权限对象所属的数据库。如果权限为 SYSTEM、RESOURCE GROUP、RESOURCE、USER、GLOBAL FUNCTION 或 CATALOG 级别权限，则返回 `NULL`。 |
-| OBJECT_NAME     | 权限对象所属的表。如果权限为 SYSTEM、RESOURCE GROUP、RESOURCE、USER、GLOBAL FUNCTION、CATALOG 或 DATABASE 级别权限，则返回 `NULL`。 |
-| OBJECT_TYPE     | 权限对象的类型。                                             |
-| PRIVILEGE_TYPE  | 权限的类型。同一个对象上的不同权限会进行合并展示。如示例中，`'user1'@'%'` 同时拥有 `default_catalog.db_test.view_test`的 SELECT 和 DROP 权限，则会合并展示。 |
-| IS_GRANTABLE    | 被授予用户是否拥有该权限的 GRANT 权限。                      |
-
-示例：
-
-```Plain
-MySQL > SELECT * FROM sys.grants_to_users LIMIT 5\G
-*************************** 1. row ***************************
-        GRANTEE: 'user1'@'%'
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: db_test
-    OBJECT_NAME: view_test
-    OBJECT_TYPE: VIEW
- PRIVILEGE_TYPE: SELECT, DROP
-   IS_GRANTABLE: NO
-*************************** 2. row ***************************
-        GRANTEE: 'user2'@'%'
- OBJECT_CATALOG: default_catalog
-OBJECT_DATABASE: simo
-    OBJECT_NAME: view_test
-    OBJECT_TYPE: VIEW
- PRIVILEGE_TYPE: SELECT
-   IS_GRANTABLE: NO
-```
diff --git a/docs/zh/reference/sys/object_dependencies.md b/docs/zh/reference/sys/object_dependencies.md
deleted file mode 100644
index c9f5ab08f96c70..00000000000000
--- a/docs/zh/reference/sys/object_dependencies.md
+++ /dev/null
@@ -1,52 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# object_dependencies
-
-您可以通过查询 `object_dependencies` 视图查看异步物化视图的依赖关系。
-
-`object_dependencies` 提供以下字段：
-
-| **字段**            | **描述**                                           |
-| ------------------- | -------------------------------------------------- |
-| object_id           | 对象的 ID。                                        |
-| object_name         | 对象的名称。                                       |
-| object_database     | 对象所在的数据库。                                 |
-| object_catalog      | 对象所在的 Catalog。该字段常为 `default_catalog`。 |
-| object_type         | 对象的类型。该字段常为 `MATERIALIZED_VIEW`。       |
-| ref_object_id       | 依赖对象的 ID。                                    |
-| ref_object_name     | 依赖对象的名称。                                   |
-| ref_object_database | 依赖对象所在的数据库。                             |
-| ref_object_catalog  | 依赖的对象所在的 Catalog。                         |
-| ref_object_type     | 依赖的对象的类型。                                 |
-
-示例：
-
-```Plain
-MySQL > SELECT * FROM sys.object_dependencies\G
-*************************** 1. row ***************************
-          object_id: 11115
-        object_name: mv2
-    object_database: test_db
-     object_catalog: default_catalog
-        object_type: MATERIALIZED_VIEW
-      ref_object_id: 11092
-    ref_object_name: mv1
-ref_object_database: test_db
- ref_object_catalog: default_catalog
-    ref_object_type: MATERIALIZED_VIEW
-*************************** 2. row ***************************
-          object_id: 11092
-        object_name: mv1
-    object_database: test_db
-     object_catalog: default_catalog
-        object_type: MATERIALIZED_VIEW
-      ref_object_id: 11074
-    ref_object_name: test_tbl
-ref_object_database: test_db
- ref_object_catalog: default_catalog
-    ref_object_type: OLAP
-```
-
-上述示例表明，物化视图 `mv1` 是基于 StarRocks 内表 `test_tbl` 创建的，物化视图 `mv2` 是基于物化视图 `mv1` 创建的。
diff --git a/docs/zh/reference/sys/role_edges.md b/docs/zh/reference/sys/role_edges.md
deleted file mode 100644
index 7c91aa448852cb..00000000000000
--- a/docs/zh/reference/sys/role_edges.md
+++ /dev/null
@@ -1,42 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# role_edges
-
-您可以通过查询 `role_edges` 视图查看角色的授予关系。
-
-:::note
-
-默认仅拥有 `user_admin` 角色的用户或角色可以查询此视图，或通过 [GRANT](../../sql-reference/sql-statements/account-management/GRANT.md) 语句将此视图的权限赋予给其他用户。
-
-:::
-
-`role_edges` 提供以下字段：
-
-| **字段**  | **描述**                                                     |
-| --------- | ------------------------------------------------------------ |
-| FROM_ROLE | 授予的角色。因为一个角色可以授予多个角色和用户，所以 `role_edges` 视图可以返回多条具有相同 `FROM_ROLE` 的记录。 |
-| TO_ROLE   | 当前 `FROM_ROLE` 被授予的角色。如果当前 `FROM_ROLE` 被授予用户，则返回 `NULL`。 |
-| TO_USER   | 当前 `FROM_ROLE` 被授予的用户。如果当前 `FROM_ROLE` 被授予角色，则返回 `NULL`。 |
-
-示例：
-
-```Plain
-MySQL > SELECT * FROM sys.role_edges;
-+------------+------------+---------------+
-| FROM_ROLE  | TO_ROLE    | TO_USER       |
-+------------+------------+---------------+
-| dba_leader | director   | NULL          |
-| dba        | dba_leader | NULL          |
-| dba        | NULL       | 'aneesh'@'%'  |
-| dba        | NULL       | 'chelsea'@'%' |
-| dba_leader | NULL       | 'albert'@'%'  |
-| director   | NULL       | 'stan'@'%'    |
-| root       | NULL       | 'root'@'%'    |
-+------------+------------+---------------+
-```
-
-下图说明了以上示例中角色授予的嵌套关系：
-
-![role_edges](../../_assets/role_edges.png)
\ No newline at end of file
diff --git a/docs/zh/reference/user_defined_variables.md b/docs/zh/reference/user_defined_variables.md
deleted file mode 100644
index 30121017bfcf51..00000000000000
--- a/docs/zh/reference/user_defined_variables.md
+++ /dev/null
@@ -1,74 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 用户自定义变量
-
-本文介绍如何声明和使用用户自定义变量。
-
-自 2.5 版本起， StarRocks 支持用户声明自定义变量 (user-defined variables)。自定义变量用于存储特定的值，后续引用在 SQL 语句中，简化 SQL 语句的编写和避免重复计算。
-
-## 使用说明
-
-- 当前仅支持声明会话级别的自定义变量，即用户只能使用自己声明的自定义变量，且如客户端断开，那么当前会话中所有自定义变量将失效。
-- StarRocks 暂不支持使用 SHOW 语句查看已有的自定义变量。
-- 不支持声明 BITMAP、HLL 和 PERCENTILE 类型的自定义变量，JSON 类型的自定义变量会转换为 STRING 类型进行存储。
-- 自 v3.2.7 起，StarRocks 支持声明 ARRAY 类型的自定义变量。
-
-## 声明自定义变量
-
-### 语法
-
-```Plain
-SET @var_name = expr [, ...];
-```
-
-> **说明**
->
-> - 声明自定义变量时，必须加前缀 `@`。
-> - 可同时声明多个自定义变量，多个变量之间用逗号 (,) 隔开。
-> - 支持多次声明同一自定义变量，新声明的值会覆盖原有值。
-> - 如在一个 SQL 语句中引用了没有声明过的变量，该变量值默认为 `NULL` 且为 STRING 类型。
-
-### 参数说明
-
-| **参数** | **必填** | **说明**                                                     |
-| -------- | -------- | ------------------------------------------------------------ |
-| var_name | 是       | 自定义变量名称，命名规则如下：<ul><li>必须由字母 (a-z 或 A-Z)、数字 (0-9) 或下划线 (\_) 组成。</li><li>总长度不能超过 64 个字符。</li></ul> 例如，@'my-var'、@"my-var" 和 @\`my-var\`。字符串类型的变量名称可以包含除字母、数字和下划线 (_) 以外的其他字符，例如句点 (.)。 |
-| expr     | 是       | 自定义变量存储的值。支持简单值，例如 `43`；也支持复杂表达式，如 SELECT 查询返回的值。表达式计算结果的数据类型即为变量的数据类型。 |
-
-### 示例
-
-示例一：声明一个数值为自定义变量。
-
-```SQL
-SET @var = 43;
-```
-
-示例二：声明 SELECT 语句返回的值为自定义变量。
-
-```SQL
-SET @var = (SELECT SUM(v1) FROM test);
-```
-
-示例三：一次性声明多个变量。
-
-```SQL
-SET @v1=1, @v2=2;
-```
-
-## **使用场景**
-
-- 简化 SQL 语句的编写。示例如下，执行 SELECT 语句时，`@var` 会被 `1` 替换。
-
-  ```Plain
-  SET @var = 1;
-  SELECT @var, v1 from test;
-  ```
-
-- 避免重复计算。示例如下，执行 SELECT 语句时，`@var` 会被 `select sum(c1) from tbl` 命令的计算结果替换。
-
-  ```Plain
-  SET @var = (select sum(c1) from tbl);
-  SELECT @var, v1 from test;
-  ```
diff --git a/docs/zh/release_notes/release-1.19.md b/docs/zh/release_notes/release-1.19.md
index 4bcdb7ce543593..dfaa9050c86d58 100644
--- a/docs/zh/release_notes/release-1.19.md
+++ b/docs/zh/release_notes/release-1.19.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 1.19
diff --git a/docs/zh/release_notes/release-2.0.md b/docs/zh/release_notes/release-2.0.md
index d4357b541d3275..653813d4988f26 100644
--- a/docs/zh/release_notes/release-2.0.md
+++ b/docs/zh/release_notes/release-2.0.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 2.0
diff --git a/docs/zh/release_notes/release-2.1.md b/docs/zh/release_notes/release-2.1.md
index 4bbc5cf14f27ba..a372fa9e237af6 100644
--- a/docs/zh/release_notes/release-2.1.md
+++ b/docs/zh/release_notes/release-2.1.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 2.1
diff --git a/docs/zh/release_notes/release-2.2.md b/docs/zh/release_notes/release-2.2.md
index e411da23f8d005..e7c12a7d8baf9e 100644
--- a/docs/zh/release_notes/release-2.2.md
+++ b/docs/zh/release_notes/release-2.2.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 2.2
diff --git a/docs/zh/release_notes/release-2.3.md b/docs/zh/release_notes/release-2.3.md
index 6d4896db3969ef..9a4fb7054d7d5a 100644
--- a/docs/zh/release_notes/release-2.3.md
+++ b/docs/zh/release_notes/release-2.3.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 2.3
diff --git a/docs/zh/release_notes/release-2.4.md b/docs/zh/release_notes/release-2.4.md
index 295f095de89e67..b3c7a18585be6c 100644
--- a/docs/zh/release_notes/release-2.4.md
+++ b/docs/zh/release_notes/release-2.4.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 2.4
diff --git a/docs/zh/release_notes/release-2.5.md b/docs/zh/release_notes/release-2.5.md
index 6804163701a83f..1da274b2e6a692 100644
--- a/docs/zh/release_notes/release-2.5.md
+++ b/docs/zh/release_notes/release-2.5.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 2.5
diff --git a/docs/zh/release_notes/release-3.0.md b/docs/zh/release_notes/release-3.0.md
index 1e8b7f5d4ae8bc..860358f3f22268 100644
--- a/docs/zh/release_notes/release-3.0.md
+++ b/docs/zh/release_notes/release-3.0.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 3.0
diff --git a/docs/zh/release_notes/release-3.1.md b/docs/zh/release_notes/release-3.1.md
index 0a2a44703b91d3..c53ee07004f39a 100644
--- a/docs/zh/release_notes/release-3.1.md
+++ b/docs/zh/release_notes/release-3.1.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 3.1
diff --git a/docs/zh/release_notes/release-3.2.md b/docs/zh/release_notes/release-3.2.md
index a37fc721dd4df1..a6806b34563476 100644
--- a/docs/zh/release_notes/release-3.2.md
+++ b/docs/zh/release_notes/release-3.2.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 3.2
diff --git a/docs/zh/release_notes/release-3.3.md b/docs/zh/release_notes/release-3.3.md
index d9bc0aa2616534..45d1d3dbfcf74c 100644
--- a/docs/zh/release_notes/release-3.3.md
+++ b/docs/zh/release_notes/release-3.3.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # StarRocks version 3.3
diff --git a/docs/zh/sql-reference/Error_code.md b/docs/zh/sql-reference/Error_code.md
new file mode 100644
index 00000000000000..aea200013a9acb
--- /dev/null
+++ b/docs/zh/sql-reference/Error_code.md
@@ -0,0 +1,149 @@
+---
+displayed_sidebar: docs
+---
+
+# 错误码
+
+本节描述查询请求常见的错误码。
+
+|错误码|错误信息|
+| --- | --- |
+|1005|创建表格失败，并给出具体原因。|
+|1007|不能创建同名的数据库。|
+|1008|不能删除不存在的数据库。|
+|1044|不能访问未授权的数据库。|
+|1045|用户名及密码不匹配，不能访问系统。|
+|1046|没有指定要查询的目标数据库。|
+|1047|指定了无效的指令。|
+|1049|指定了无效的数据库。|
+|1050|已存在同名的数据表。|
+|1051|指定了无效的数据表。|
+|1052|指定的列名有歧义，不能唯一确定对应列。|
+|1053|为 Semi-Join/Anti-Join 查询指定了非法的数据列。|
+|1054|表中不存在指定的列。|
+|1058|查询语句中选择的列数目与查询结果的列数目不一致。|
+|1060|列名重复。|
+|1064|无存活的 BE 节点。|
+|1066|查询语句中出现重复的表别名。|
+|1094|线程 ID 无效。|
+|1095|非线程的拥有者不能终止线程的运行。|
+|1096|查询语句没有指定要查询或操作的数据表。|
+|1102|数据库名不正确。|
+|1104|数据表名不正确。|
+|1105|其它错误。|
+|1110|子查询中指定了重复的列。|
+|1111|在 Where 子句中非法使用聚合函数。|
+|1113|新建表的列集合不能为空。|
+|1115|使用了不支持的字符集。|
+|1130|客户端使用了未被授权的 IP 地址来访问系统。|
+|1132|没有权限修改用户密码。|
+|1141|撤销用户权限时指定了用户不具备的权限条目。|
+|1142|执行了未被授权的操作。|
+|1166|数据列名字不正确。|
+|1193|使用了无效的系统变量名字。|
+|1203|使用的活跃连接数目超过了限制。|
+|1211|不允许创建新用户。|
+|1227|执行了越权操作。|
+|1228|会话变量不能通过 SET GLOBAL 指令来修改。|
+|1229|全局变量应通过 SET GLOBAL 指令来修改。|
+|1230|相关的系统变量无缺省值。|
+|1231|给某系统变量设置了无效值。|
+|1232|给某系统变量设置了错误数据类型的值。|
+|1248|没有给内联视图设置别名。|
+|1251|客户端不支持服务器要求的用户认证协议。|
+|1286|配置的存储引擎不正确。|
+|1298|配置的时区不正确。|
+|1347|对象与期望的类型不匹配。|
+|1353|视图的 SELECT 子句中指定的列数目与其定义的列数目不相等。|
+|1364|没有给不允许 NULL 值的列设置缺省值。|
+|1372|密码长度不够。|
+|1396|用户执行的某操作运行失败。|
+|1471|指定的表不允许插入数据。|
+|1507|删除不存在的分区，且没有指定如果存在才删除的条件。|
+|1508|应该通过删除表的操作来删除所有分区。|
+|1517|出现了重复的分区名。|
+|1524|指定的插件尚未被加载。|
+|1567|分区名不正确。|
+|1621|指定的系统变量是只读的。|
+|1735|表中不存在指定的分区名。|
+|1748|不能向没有分区的表中插入数据。|
+|1749|不存在指定的分区。|
+|5000|指定的表不是 OLAP 表。|
+|5001|指定的存储过程路径无效。|
+|5002|应显示指定列名。|
+|5003|维度列应排在指标列之前。|
+|5004|表至少应包含1个维度列。|
+|5005|集群 ID 无效。|
+|5006|无效的查询规划提示。|
+|5007|冲突的查询规划提示。|
+|5008|数据插入提示仅适用于有分区的数据表。|
+|5009|PARTITION 子句不适用于向不分区的表插入数据。|
+|5010|待创建表的列数目与 SELECT 子句中的列数目不相等。|
+|5011|无法解析表引用。|
+|5012|指定的值不是一个有效数字。|
+|5013|不支持该时间单位。|
+|5014|表状态不正常。|
+|5015|分区状态不正常。|
+|5016|分区上存在数据导入任务。|
+|5017|指定列不是维度列。|
+|5018|值的格式无效。|
+|5019|数据副本与版本不匹配。|
+|5021|BE 节点已离线。|
+|5022|非分区表的分区数不为1。|
+|5023|修改表或数据的语句中没有指定任何操作。|
+|5024|任务执行超时。|
+|5025|数据插入操作失败。|
+|5026|通过 SELECT 语句创建表时使用了不支持的数据类型。|
+|5027|没有设置指定的参数。|
+|5028|没有找到指定的集群。|
+|5030|某用户没有访问集群的权限。|
+|5031|没有指定参数或参数无效。|
+|5032|没有指定集群实例数目。|
+|5034|已存在同名的集群。|
+|5035|集群实例数目配置错误。|
+|5036|集群中 BE 节点不足。|
+|5037|删除集群前应先删除所有数据库。|
+|5037|集群中不存在指定 ID 的 BE 节点。|
+|5040|不存在同名的集群。|
+|5042|没有权限。|
+|5043|实例数目应大于0。|
+|5046|源集群不存在。|
+|5047|目标集群不存在。|
+|5048|源数据库不存在。|
+|5049|目标数据库不存在。|
+|5050|没有选择集群。|
+|5051|应先将源数据库关联至目标数据库。|
+|5052|集群内部错误：BE 节点信息错误。|
+|5053|没有从源数据库到目标数据库的迁移任务。|
+|5054|指定数据库已经被关联至目标数据库，或正在迁移数据。|
+|5055|数据库关联或数据迁移不能在同一集群内执行。|
+|5056|不能删除数据库：被关联至其它数据库或正在迁移数据。|
+|5056|不能重命名数据库：被关联至其它数据库或正在迁移数据。|
+|5056|集群中 BE 节点不足。|
+|5056|集群内已存在指定数目的 BE 节点。|
+|5059|集群中存在处于下线状态的 BE 节点。|
+|5063|类型名不正确。|
+|5064|通用错误提示。|
+|5063|Colocate 功能已被管理员禁用。|
+|5063|不存在同名的 Colocate 数据表。|
+|5063|Colocate 表必须是 OLAP 表。|
+|5063|Colocate 表应该具有同样的副本数目。|
+|5063|Colocate 表应该具有同样的分桶数目。|
+|5063|Colocate 表的分区列数目应该一致。|
+|5063|Colocate 表的分区列的数据类型应该一致。|
+|5064|指定表不是 Colocate 表。|
+|5065|指定的操作无效。|
+|5065|指定的时间单位非法，正确的单位包括：DAY、WEEK、MONTH。|
+|5066|动态分区起始值应该小于0。|
+|5066|动态分区起始值不是有效的数字。|
+|5066|动态分区结束值应该大于0。|
+|5066|动态分区结束值不是有效的数字。|
+|5066|动态分区结束值为空。|
+|5067|动态分区分桶数应该大于0。|
+|5067|动态分区分桶值不是有效的数字。|
+|5066|动态分区分桶值为空。|
+|5068|是否允许动态分区的值不是有效的布尔值：true 或者 false。|
+|5069|指定的动态分区名前缀非法。|
+|5070|指定的操作被禁止了。|
+|5071|动态分区副本数应该大于0。|
+|5072|动态分区副本值不是有效的数字。|
diff --git a/docs/zh/sql-reference/How_to_Write_Functions_Documentation.md b/docs/zh/sql-reference/How_to_Write_Functions_Documentation.md
index 59583284620608..0697a420c8c7db 100644
--- a/docs/zh/sql-reference/How_to_Write_Functions_Documentation.md
+++ b/docs/zh/sql-reference/How_to_Write_Functions_Documentation.md
@@ -1,5 +1,6 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
+unlisted: true
 ---
 
 # CONVERT_TZ
diff --git a/docs/zh/sql-reference/How_to_write_SQL_command_doc.md b/docs/zh/sql-reference/How_to_write_SQL_command_doc.md
index 60a19c1dec219b..2cbc92f89f4746 100644
--- a/docs/zh/sql-reference/How_to_write_SQL_command_doc.md
+++ b/docs/zh/sql-reference/How_to_write_SQL_command_doc.md
@@ -1,5 +1,6 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
+unlisted: true
 ---
 
 # SQL 命令模板
diff --git a/docs/zh/sql-reference/System_limit.md b/docs/zh/sql-reference/System_limit.md
new file mode 100644
index 00000000000000..9e8cd47c1ce161
--- /dev/null
+++ b/docs/zh/sql-reference/System_limit.md
@@ -0,0 +1,35 @@
+---
+displayed_sidebar: docs
+---
+
+# 系统限制
+
+本文介绍使用 StarRocks 系统时需要注意的事项。
+
+- StarRocks 采用 MySQL 协议进行通信，用户可通过 MySQL Client 或者 JDBC 连接到 StarRocks 集群。选择 MySQL Client 版本时建议采用 5.1 及之后的版本，5.1 之前版本不支持长度超过 16 个字符的用户名。
+
+- 对名称的要求，包括数据目录名 (catalog)、数据库名、表名、视图名、分区名、列名、索引名、用户名、角色名、仓库名 (repository)、资源名 (resource)、存储卷名 (Storage Volume)、Pipe 名等：
+  - 只能由数字 (0-9)、字母 (a-z或A-Z)，以及下划线 (\_) 组成。**用户名 (username) 可以使用纯数字命名。**
+  - 可以以字母或下划线开头。
+  - 长度不能超过 64 个字符。**几个特殊情况：**
+    - 数据库名不能超过 256 个字符。
+    - 表名和列名不能超过 1024 个字符。
+    - 用户名 (username) 不能超过 128 个字符。
+  - 列名（包括列别名）、分区名、索引名大小写**不敏感**，其他名称大小写**敏感**。
+
+- 对标签（Label）名的要求：
+  导入数据时可指定任务的标签（Label）。标签名可由数字 (0-9)、字母（a-z或A-Z），以及下划线(\_)组成，且长度不能超过 128 个字符。标签名对起始字符无要求。
+
+- 建表时，Key 列不能使用 FLOAT 或者 DOUBLE 类型，可用 DECIMAL 类型表示小数。
+
+- VARCHAR 最大长度：
+  - 对于 StarRocks 2.1 之前的版本，长度范围为 1~65533 字节。
+  - 【公测中】自 StarRocks 2.1 版本开始，长度范围为 1~1048576 字节。1048578（行最大值）- 2（长度标识位，记录实际数据长度）= 1048576。
+
+- StarRocks 仅支持 UTF8 编码，不支持 GBK 等编码。
+
+- 建表后，表类型不支持修改（比如不能将已有的明细表修改为主键表）。如果需要修改表类型，请重新建表。
+
+- StarRocks 不支持修改表的列名。
+
+- 一个查询中子查询的最大个数默认为 10000，可以通过 FE 参数 `expr_children_limit` 设置。
diff --git a/docs/zh/sql-reference/System_variable.md b/docs/zh/sql-reference/System_variable.md
new file mode 100644
index 00000000000000..1177a858ed8e22
--- /dev/null
+++ b/docs/zh/sql-reference/System_variable.md
@@ -0,0 +1,1059 @@
+---
+displayed_sidebar: docs
+keywords: ['session','variable']
+---
+
+# 系统变量
+
+StarRocks 提供多个系统变量（system variables），方便您根据业务情况进行调整。本文介绍 StarRocks 支持的变量。您可以在 MySQL 客户端通过命令 [SHOW VARIABLES](sql-statements/cluster-management/config_vars/SHOW_VARIABLES.md) 查看当前变量。也可以通过 [SET](sql-statements/cluster-management/config_vars/SET.md) 命令动态设置或者修改变量。您可以设置变量在系统全局 (global) 范围内生效、仅在当前会话 (session) 中生效、或者仅在单个查询语句中生效。
+
+StarRocks 中的变量参考 MySQL 中的变量设置，但**部分变量仅用于兼容 MySQL 客户端协议，并不产生其在 MySQL 数据库中的实际意义**。
+
+> **说明**
+>
+> 任何用户都有权限通过 SHOW VARIABLES 查看变量。任何用户都有权限设置变量在 Session 级别生效。只有拥有 System 级 OPERATE 权限的用户才可以设置变量为全局生效。设置全局生效后，后续所有新的会话都会使用新配置，当前会话仍然使用老的配置。
+
+## 查看变量
+
+可以通过 `SHOW VARIABLES [LIKE 'xxx'];` 查看所有或指定的变量。例如：
+
+```SQL
+
+-- 查看系统中所有变量。
+SHOW VARIABLES;
+
+-- 查看符合匹配规则的变量。
+SHOW VARIABLES LIKE '%time_zone%';
+```
+
+## 变量层级和类型
+
+StarRocks 支持三种类型（层级）的变量：全局变量、Session 变量和 `SET_VAR` Hint。它们的层级关系如下：
+
+* 全局变量在全局级别生效，可以被 Session 变量和 `SET_VAR` Hint 覆盖。
+* Session 变量仅在当前会话中生效，可以被 `SET_VAR` Hint 覆盖。
+* `SET_VAR` Hint 仅在当前查询语句中生效。
+
+## 设置变量
+
+### 设置变量全局生效或在会话中生效
+
+变量一般可以设置为**全局**生效或**仅当前会话**生效。设置为全局生效后，**后续所有新的会话**连接中会使用新设置的值，当前会话还会继续使用之前设置的值；设置为仅当前会话生效时，变量仅对当前会话产生作用。
+
+通过 `SET <var_name> = xxx;` 语句设置的变量仅在当前会话生效。如：
+
+```SQL
+SET query_mem_limit = 137438953472;
+
+SET forward_to_master = true;
+
+SET time_zone = "Asia/Shanghai";
+```
+
+通过 `SET GLOBAL <var_name> = xxx;` 语句设置的变量全局生效。如：
+
+ ```SQL
+SET GLOBAL query_mem_limit = 137438953472;
+ ```
+
+以下变量仅支持全局生效，不支持设置为会话级别生效。您必须使用 `SET GLOBAL <var_name> = xxx;`，不能使用 `SET <var_name> = xxx;`，否则返回错误。
+
+* activate_all_roles_on_login
+* character_set_database
+* default_rowset_type
+* enable_query_queue_select
+* enable_query_queue_statistic
+* enable_query_queue_load
+* init_connect
+* lower_case_table_names
+* license
+* language
+* query_cache_size
+* query_queue_fresh_resource_usage_interval_ms
+* query_queue_concurrency_limit
+* query_queue_mem_used_pct_limit
+* query_queue_cpu_used_permille_limit
+* query_queue_pending_timeout_second
+* query_queue_max_queued_queries
+* system_time_zone
+* version_comment
+* version
+
+Session 级变量既可以设置全局生效也可以设置 session 级生效。
+
+此外，变量设置也支持常量表达式，如：
+
+```SQL
+SET query_mem_limit = 10 * 1024 * 1024 * 1024;
+```
+
+```SQL
+SET forward_to_master = concat('tr', 'u', 'e');
+```
+
+### 设置变量在单个查询语句中生效
+
+在一些场景中，可能需要对某些查询专门设置变量。可以使用 SET_VAR 提示 (Hint) 在查询中设置仅在单个语句内生效的会话变量。
+
+当前，StarRocks 支持在以下语句中使用 `SET_VAR` Hint：
+
+- SELECT
+- INSERT（自 v3.1.12 和 v3.2.0 起支持）
+- UPDATE（自 v3.1.12 和 v3.2.0 起支持）
+- DELETE（自 v3.1.12 和 v3.2.0 起支持）
+
+`SET_VAR` 只能跟在以上关键字之后，必须以 `/*+` 开头，以 `*/` 结束。
+
+举例：
+
+```sql
+SELECT /*+ SET_VAR(query_mem_limit = 8589934592) */ name FROM people ORDER BY name;
+
+SELECT /*+ SET_VAR(query_timeout = 1) */ sleep(3);
+
+UPDATE /*+ SET_VAR(query_timeout=100) */ tbl SET c1 = 2 WHERE c1 = 1;
+
+DELETE /*+ SET_VAR(query_mem_limit = 8589934592) */
+FROM my_table PARTITION p1
+WHERE k1 = 3;
+
+INSERT /*+ SET_VAR(query_timeout = 10000000) */
+INTO insert_wiki_edit
+    SELECT * FROM FILES(
+        "path" = "s3://inserttest/parquet/insert_wiki_edit_append.parquet",
+        "format" = "parquet",
+        "aws.s3.access_key" = "XXXXXXXXXX",
+        "aws.s3.secret_key" = "YYYYYYYYYY",
+        "aws.s3.region" = "us-west-2"
+);
+```
+
+StarRocks 同时支持在单个语句中设置多个变量，参考如下示例：
+
+```sql
+SELECT /*+ SET_VAR
+  (
+  exec_mem_limit = 515396075520,
+  query_timeout=10000000,
+  batch_size=4096,
+  parallel_fragment_exec_instance_num=32
+  )
+  */ * FROM TABLE;
+```
+
+## 支持的变量
+
+本节以字母顺序对变量进行解释。带 `global` 标记的变量为全局变量，仅支持全局生效。其余变量既可以设置全局生效，也可设置会话级别生效。
+
+### activate_all_roles_on_login (global)
+
+* 描述：用于控制是否在用户登录时默认激活所有角色（包括默认角色和授予的角色）。
+  * 开启后，在用户登录时默认激活所有角色，优先级高于通过 [SET DEFAULT ROLE](sql-statements/account-management/SET_DEFAULT_ROLE.md) 设置的角色。
+  * 如果不开启，则会默认激活 SET DEFAULT ROLE 中设置的角色。
+* 默认值：false，表示不开启。
+* 引入版本：v3.0
+
+如果要在当前会话中激活一个角色，可以使用 [SET ROLE](sql-statements/account-management/SET_ROLE.md)。
+
+### auto_increment_increment
+
+* 描述：用于兼容 MySQL 客户端。无实际作用。
+* 默认值：1
+* 类型：Int
+
+### autocommit
+
+* 描述：用于兼容 MySQL 客户端。无实际作用。
+* 默认值：true
+
+### chunk_size
+
+用于指定在查询执行过程中，各个节点传输的单个数据包的行数。默认一个数据包的行数为 4096 行，即源端节点每产生 4096 行数据后，打包发给目的节点。较大的行数，会在扫描大数据量场景下提升查询的吞吐率，但可能会在小查询场景下增加查询延迟。同时，也会增加查询的内存开销。建议设置范围 1024 至 4096。
+
+### big_query_profile_threshold
+
+* 描述：用于设定大查询的阈值。当会话变量 `enable_profile` 设置为 `false` 且查询时间超过 `big_query_profile_threshold` 设定的阈值时，则会生成 Profile。
+
+  NOTE：在 v3.1.5 至 v3.1.7 以及 v3.2.0 至 v3.2.2 中，引入了 `big_query_profile_second_threshold` 参数，用于设定大查询的阈值。而在 v3.1.8、v3.2.3 及后续版本中，此参数被 `big_query_profile_threshold` 替代，以便提供更加灵活的配置选项。
+* 默认值：0
+* 单位：秒
+* 类型：String
+* 引入版本：v3.1
+
+### catalog（3.2.4 及以后）
+
+* 描述：用于指定当前会话所在的 Catalog。
+* 默认值：default_catalog
+* 类型：String
+* 引入版本：v3.2.4
+
+### cbo_decimal_cast_string_strict
+
+* 描述：用于优化器控制 DECIMAL 类型转为 STRING 类型的行为。取值为 `true` 时，使用 v2.5.x及之后版本的处理逻辑，执行严格转换（按 Scale 截断补 `0`）；取值为 `false`时，保留 v2.5.x 之前版本的处理逻辑（按有效数字处理）。默认值是 `true`。
+* 默认值：true
+* 引入版本：v2.5.14
+
+### cbo_enable_low_cardinality_optimize
+
+* 描述：是否开启低基数全局字典优化。开启后，查询 STRING 列时查询速度会有 3 倍左右提升。
+* 默认值：true
+
+### cbo_eq_base_type
+
+* 描述：用来指定 DECIMAL 类型和 STRING 类型的数据比较时的强制类型，默认按照 `VARCHAR` 类型进行比较，可选 `DECIMAL`（按数值进行比较）。**该变量仅在进行 `=` 和 `!=` 比较时生效。**
+* 类型：String
+* 引入版本：v2.5.14
+
+### cbo_materialized_view_rewrite_related_mvs_limit
+
+* 描述：用于指定查询在 Plan 阶段最多拥有的候选物化视图个数。
+* 默认值：64
+* 类型：Int
+* 引入版本：v3.1.9, v3.2.5
+
+### cbo_prune_subfield
+
+* 描述：是否开启 JSON 子列裁剪。需要配合 BE 动态参数 `enable_json_flat` 一起使用，单独使用可能会导致 JSON 性能变慢。
+* 默认值：false
+* 引入版本：v3.3.0
+
+### enable_sync_materialized_view_rewrite
+
+* 描述：是否启用基于同步物化视图的查询改写。
+* 默认值：true
+* 引入版本：v3.1.11，v3.2.5
+
+### enable_datacache_async_populate_mode
+
+* 描述：是否使用异步方式进行 Data Cache 填充。系统默认使用同步方式进行填充，即在查询数据时同步填充进行缓存填充。
+* 默认值：false
+* 引入版本：v3.2.7
+
+### query_including_mv_names
+
+* 描述：指定需要在查询执行过程中包含的异步物化视图的名称。您可以使用此变量来限制候选物化视图的数量，并提高优化器中的查询改写性能。此项优先于 `query_excluding_mv_names` 生效。
+* 默认值：空字符串
+* 类型：String
+* 引入版本：v3.1.11，v3.2.5
+
+### query_excluding_mv_names
+
+* 描述：指定需要在查询执行过程中排除的异步物化视图的名称。您可以使用此变量来限制候选物化视图的数量，并提高优化器中的查询改写性能。`query_including_mv_names` 优先于此项生效。
+* 默认值：空字符串
+* 类型：String
+* 引入版本：v3.1.11，v3.2.5
+
+### optimizer_materialized_view_timelimit
+
+* 描述：指定一个物化视图改写规则可消耗的最大时间。当达到阈值时，将不再使用该规则进行查询改写。
+* 默认值：1000
+* 单位：毫秒
+* 类型：Long
+
+### enable_materialized_view_agg_pushdown_rewrite
+
+* 描述：是否为物化视图查询改写启用聚合函数下推。如果设置为 `true`，聚合函数将在查询执行期间下推至 Scan Operator，并在执行 Join Operator 之前被物化视图改写。此举可以缓解 Join 操作导致的数据膨胀，从而提高查询性能。有关此功能的具体场景和限制的详细信息，请参见 [聚合函数下推](../using_starrocks/query_rewrite_with_materialized_views.md#聚合下推)。
+* 默认值：false
+* 引入版本：v3.3.0
+
+### enable_materialized_view_text_match_rewrite
+
+* 描述：是否启用基于文本的物化视图改写。当此项设置为 `true` 时，优化器将查询与现有的物化视图进行比较。如果物化视图定义的抽象语法树与查询或其子查询的抽象语法树匹配，则会对查询进行改写。
+* 默认值：true
+* 引入版本：v3.2.5，v3.3.0
+
+### materialized_view_subuqery_text_match_max_count
+
+* 描述：指定系统比对查询的子查询是否与物化视图定义匹配的最大次数。
+* 默认值：4
+* 引入版本：v3.2.5，v3.3.0
+
+### enable_force_rule_based_mv_rewrite
+
+* 描述：在优化器的 RBO（rule-based optimization）阶段是否针对多表查询启用查询改写。启用此功能将提高查询改写的鲁棒性。但如果查询未命中物化视图，则会增加优化耗时。
+* 默认值：true
+* 引入版本：v3.3
+
+### enable_view_based_mv_rewrite
+
+* 描述：是否为基于逻辑视图创建的物化视图启用查询改写。如果此项设置为 `true`，则逻辑视图被用作统一节点进行查询改写，从而获得更好的性能。如果此项设置为 `false`，则系统将针对逻辑视图的查询展开变为针对物理表或物化视图的查询，然后进行改写。
+* 默认值：false
+* 引入版本：v3.1.9，v3.2.5，v3.3.0
+
+### enable_materialized_view_union_rewrite
+
+* 描述：是否启用物化视图 UNION 改写。如果此项设置为 true，则系统在物化视图的谓词不能满足查询的谓词时，会尝试使用 UNION ALL 来补偿谓词。
+* 默认值：true
+* 引入版本：v2.5.20，v3.1.9，v3.2.7，v3.3.0
+
+### enable_materialized_view_plan_cache
+
+* 描述：是否开启物化视图查询计划缓存，用于提高物化视图查询改写性能。默认值是 `true`，即开启物化视图查询计划缓存。
+* 默认值：true
+* 引入版本：v2.5.13，v3.0.7，v3.1.4，v3.2.0，v3.3.0
+
+### follower_query_forward_mode
+
+* 描述：用于指定将查询语句路由到 Leader FE 或 Follower FE 节点。
+
+  有效值:
+  * `default`: 将查询语句路由到 Leader FE 或 Follower FE 节点，取决于 Follower FE 节点的回放进度。如果 Follower FE 节点未完成回放，查询将会被路由至 Leader FE 节点。反之，查询会被优先路由至 Follower FE 节点。
+  * `leader`: 将查询语句路由到 Leader FE 节点。
+  * `follower`: 将查询语句路由到 Follower FE 节点。
+* 默认值：default
+* 类型：String
+* 引入版本：v2.5.20，v3.1.9，v3.2.7，v3.3.0
+
+### character_set_database（global）
+
+* 描述：StarRocks 数据库支持的字符集，当前仅支持 UTF8 编码（`utf8`）。
+* 默认值：utf8
+* 类型：String
+
+### connector_io_tasks_per_scan_operator
+
+* 描述：外表查询时每个 Scan 算子能同时下发的 I/O 任务的最大数量。目前外表查询时会使用自适应算法来调整并发 I/O 任务的数量，通过 `enable_connector_adaptive_io_tasks` 开关来控制，默认打开。
+* 默认值：16
+* 类型：Int
+* 引入版本：v2.5
+
+### connector_sink_compression_codec
+
+* 描述：用于指定写入 Hive 表或 Iceberg 表时以及使用 Files() 导出数据时的压缩算法。有效值：`uncompressed`、`snappy`、`lz4`、`zstd`、`gzip`。
+* 默认值：uncompressed
+* 类型：String
+* 引入版本：v3.2.3
+
+### connector_sink_target_max_file_size
+
+* 描述: 指定将数据写入 Hive 表或 Iceberg 表或使用 Files() 导出数据时目标文件的最大大小。该限制并不一定精确，只作为尽可能的保证。
+* 单位：Bytes
+* 默认值: 1073741824
+* 类型: Long
+* 引入版本: v3.3.0
+
+### count_distinct_column_buckets
+
+* 描述：group-by-count-distinct 查询中为 count distinct 列设置的分桶数。该变量只有在 `enable_distinct_column_bucketization` 设置为 `true` 时才会生效。
+* 默认值：1024
+* 引入版本：v2.5
+
+### default_rowset_type (global)
+
+全局变量，仅支持全局生效。用于设置计算节点存储引擎默认的存储格式。当前支持的存储格式包括：alpha/beta。
+
+### default_table_compression
+
+* 描述：存储表格数据时使用的默认压缩算法，支持 LZ4、Zstandard（或 zstd）、zlib 和 Snappy。如果您建表时在 PROPERTIES 设置了 `compression`，则 `compression` 指定的压缩算法生效。
+* 默认值：lz4_frame
+* 类型：String
+* 引入版本：v3.0
+
+### disable_colocate_join
+
+* 描述：控制是否启用 Colocate Join 功能。默认值为 false，表示启用该功能。true 表示禁用该功能。当该功能被禁用后，查询规划将不会尝试执行 Colocate Join。
+* 默认值：false
+
+### disable_streaming_preaggregations (已弃用)
+
+控制是否开启流式预聚合。默认为 `false`，即开启。3.1 版本已弃用。
+
+### div_precision_increment
+
+* 描述：用于兼容 MySQL 客户端，无实际作用。
+* 默认值：4
+* 类型：Int
+<!--
+### enable_collect_table_level_scan_stats (Invisible to users)
+
+解决升级中的兼容问题，用户不可见。
+
+默认值：`true`。
+-->
+
+### enable_connector_adaptive_io_tasks
+
+* 描述：外表查询时是否使用自适应策略来调整 I/O 任务的并发数。默认打开。如果未开启自适应策略，可以通过 `connector_io_tasks_per_scan_operator` 变量来手动设置外表查询时的 I/O 任务并发数。
+* 默认值：true
+* 引入版本：v2.5
+
+### enable_distinct_column_bucketization
+
+* 描述：是否在 group-by-count-distinct 查询中开启对 count distinct 列的分桶优化。在类似 `select a, count(distinct b) from t group by a;` 的查询中，如果 group by 列 a 为低基数列，count distinct 列 b 为高基数列且发生严重数据倾斜时，会引发查询性能瓶颈。可以通过对 count distinct 列进行分桶来平衡数据，规避数据倾斜。
+
+  该变量需要与 `count_distinct_column_buckets` 配合使用。
+
+  您也可以通过添加 `skew` hint 来开启 count distinct 列的分桶优化，例如 `select a,count(distinct [skew] b) from t group by a;`。
+* 默认值：false，表示不开启。
+* 引入版本：v2.5
+
+### enable_gin_filter
+
+* 描述：查询时是否使用[全文倒排索引](../table_design/indexes/inverted_index.md)。
+* 默认值：true
+* 引入版本：v3.3.0
+
+### enable_group_level_query_queue (global)
+
+* 描述：是否开启资源组粒度的[查询队列](../administration/management/resource_management/query_queues.md)。
+* 默认值：false，表示不开启。
+* 引入版本：v3.1.4
+
+### enable_iceberg_metadata_cache
+
+* 描述：是否缓存 Iceberg 表指针和分区名相关的数据。在 3.2.1 到 3.2.3 版本，该参数默认值统一为 `true`。自 3.2.4 版本起，如果 Iceberg 集群的元数据服务为 AWS Glue，该参数默认值仍为 `true`，如果 Iceberg 集群的元数据服务为 Hive Metastore（简称 HMS）或其他，则该参数默认值变更为 `false`。
+* 引入版本：v3.2.1
+
+### enable_insert_strict
+
+* 描述：用于设置通过 INSERT 语句进行数据导入时，是否开启严格模式 (Strict Mode)。
+默认值为 `true`，即开启严格模式。关于该模式的介绍，可以参阅[严格模式](../loading/load_concept/strict_mode.md)。
+* 默认值：true
+
+### enable_materialized_view_for_insert
+
+* 描述：是否允许 StarRocks 改写 INSERT INTO SELECT 语句中的查询。
+* 默认值：false，即默认关闭该场景下的物化视图查询改写。
+* 引入版本：v2.5.18, v3.0.9, v3.1.7, v3.2.2
+
+### enable_rule_based_materialized_view_rewrite
+
+* 描述：是否开启基于规则的物化视图查询改写功能，主要用于处理单表查询改写。
+* 默认值：true
+* 引入版本：v2.5
+
+### enable_short_circuit
+
+* 描述：是否启用短路径查询。默认值：`false`。如果将其设置为 `true`，当[查询满足条件](../table_design/hybrid_table.md#查询数据)（用于评估是否为点查）：WHERE 子句的条件列必须包含所有主键列，并且运算符为 `=` 或者 `IN`，则该查询才会走短路径。
+* 默认值：false
+* 引入版本：v3.2.3
+
+### enable_spill
+
+* 描述：是否启用中间结果落盘。默认值：`false`。如果将其设置为 `true`，StarRocks 会将中间结果落盘，以减少在查询中处理聚合、排序或连接算子时的内存使用量。
+* 默认值：false
+* 引入版本：v3.0
+
+### enable_spill_to_remote_storage
+
+* 描述：是否启用将中间结果落盘至对象存储。如果设置为 `true`，当本地磁盘的用量达到上限后，StarRocks 将中间结果落盘至 `spill_storage_volume` 中指定的存储卷中。有关更多信息，请参阅 [将中间结果落盘至对象存储](../administration/management/resource_management/spill_to_disk.md#将中间结果落盘至对象存储)。
+* 默认值：false
+* 引入版本：v3.3.0
+
+### enable_strict_order_by
+
+* 描述：是否校验 ORDER BY 引用列是否有歧义。设置为默认值 `TRUE` 时，如果查询中的输出列存在不同的表达式使用重复别名的情况，且按照该别名进行排序，查询会报错，例如 `select distinct t1.* from tbl1 t1 order by t1.k1;`。该行为和 2.3 及之前版本的逻辑一致。如果取值为 `FALSE`，采用宽松的去重机制，把这类查询作为有效 SQL 处理。
+* 默认值：true
+* 引入版本：v2.5.18，v3.1.7
+
+### enable_profile
+
+用于设置是否需要查看查询的 profile。默认为 `false`，即不需要查看 profile。2.5 版本之前，该变量名称为 `is_report_success`，2.5 版本之后更名为 `enable_profile`。
+
+默认情况下，只有在查询发生错误时，BE 才会发送 profile 给 FE，用于查看错误。正常结束的查询不会发送 profile。发送 profile 会产生一定的网络开销，对高并发查询场景不利。当用户希望对一个查询的 profile 进行分析时，可以将这个变量设为 `true` 后，发送查询。查询结束后，可以通过在当前连接的 FE 的 web 页面（地址：fe_host:fe_http_port/query）查看 profile。该页面会显示最近 100 条开启了 `enable_profile` 的查询的 profile。
+
+### enable_query_queue_load (global)
+
+* 描述：用于控制是否为导入任务启用查询队列。
+* 默认值：false
+* 类型：Boolean
+
+### enable_query_queue_select (global)
+
+* 描述：用于控制是否为 SELECT 查询启用查询队列。
+* 默认值：false
+* 类型：Boolean
+
+### enable_query_queue_statistic (global)
+
+* 描述：用于控制是否为统计信息查询启用查询队列。
+* 默认值：false
+* 类型：Boolean
+
+### enable_query_tablet_affinity
+
+* 描述：用于控制在多次查询同一个 tablet 时是否倾向于选择固定的同一个副本。
+
+  如果待查询的表中存在大量 tablet，开启该特性会对性能有提升，因为会更快的将 tablet 的元信息以及数据缓存在内存中。但是，如果查询存在一些热点 tablet，开启该特性可能会导致性能有所退化，因为该特性倾向于将一个热点 tablet 的查询调度到相同的 BE 上，在高并发的场景下无法充分利用多台 BE 的资源。
+* 默认值：`false`，表示使用原来的机制，即每次查询会从多个副本中选择一个。
+* 类型：Boolean
+* 引入版本：v2.5.6、v3.0.8、v3.1.4、v3.2.0
+
+### enable_lake_tablet_internal_parallel
+
+* 描述：是否开启存算分离集群内云原生表的 Tablet 并行 Scan.
+* 默认值：false
+* 类型：Boolean
+* 引入版本：v3.3.0
+
+### tablet_internal_parallel_mode
+
+* 描述：Tablet 内部并行 Scan 策略。有效值:
+  * `auto`: 在 BE 或 CN 节点需要扫描的 Tablet 数小于 DOP 时，系统根据预估的 Tablet 大小自动判断是否需要并行 Scan。
+  * `force_split`: 强制对 Tablet 进行拆分和并行扫描。
+* 默认值：auto
+* 类型：String
+* 引入版本：v2.5.0
+
+### enable_scan_datacache
+
+* 描述：是否开启 Data Cache 特性。该特性开启之后，StarRocks 通过将外部存储系统中的热数据缓存成多个 block，加速数据查询和分析。更多信息，参见 [Data Cache](../data_source/data_cache.md)。该特性从 2.5 版本开始支持。在 3.2 之前各版本中，对应变量为 `enable_scan_block_cache`。
+* 默认值：false
+* 引入版本：v2.5
+
+### populate_datacache_mode
+
+* 描述：StarRocks 从外部存储系统读取数据时，控制数据缓存填充行为。有效值包括：
+  * `auto`（默认）：系统自动根据查询的特点，选择性进行缓存。
+  * `always`：总是缓存数据。 
+  * `never` 永不缓存数据。
+* 默认值：auto
+* 引入版本：v3.3.2
+
+### enable_datacache_io_adaptor
+
+* 描述：是否开启 Data Cache I/O 自适应开关。`true` 表示开启。开启后，系统会根据当前磁盘 I/O 负载自动将一部分缓存请求路由到远端存储来减少磁盘压力。
+* 默认值：true
+* 引入版本：v3.3.0
+
+### enable_file_metacache
+
+* 描述：是否启用远端文件元数据缓存（Footer Cache）。`true` 表示开启。Footer Cache 通过将解析后生成 Footer 对象直接缓存在内存中，在后续访问相同文件 Footer 时，可以直接从缓存中获得该对象句柄进行使用，避免进行重复解析。该功能依赖 Data Cache 的内存缓存，因此需要保证 BE 参数 `datacache_enable` 为 `true` 且为 `datacache_mem_size` 配置一个合理值后才会生效。
+* 默认值：true
+* 引入版本：v3.3.0
+
+### enable_tablet_internal_parallel
+
+* 描述：是否开启自适应 Tablet 并行扫描，使用多个线程并行分段扫描一个 Tablet，可以减少 Tablet 数量对查询能力的限制。
+* 默认值：true
+* 引入版本：v2.3
+
+### enable_query_cache
+
+* 描述：是否开启 Query Cache。取值范围：true 和 false。true 表示开启，false 表示关闭（默认值）。开启该功能后，只有当查询满足[Query Cache](../using_starrocks/query_cache.md#应用场景) 所述条件时，才会启用 Query Cache。
+* 默认值：false
+* 引入版本：v2.5
+
+### enable_adaptive_sink_dop
+
+* 描述：是否开启导入自适应并行度。开启后 INSERT INTO 和 Broker Load 自动设置导入并行度，保持和 `pipeline_dop` 一致。新部署的 2.5 版本默认值为 `true`，从 2.4 版本升级上来为 `false`。
+* 默认值：false
+* 引入版本：v2.5
+
+### enable_pipeline_engine
+
+* 描述：是否启用 Pipeline 执行引擎。`true`：启用（默认），`false`：不启用。
+* 默认值：true
+
+### enable_sort_aggregate
+
+* 描述：是否开启 sorted streaming 聚合。`true` 表示开启 sorted streaming 聚合功能，对流中的数据进行排序。
+* 默认值：false
+* 引入版本：v2.5
+
+### enable_global_runtime_filter
+
+* 描述：Global runtime filter 开关。Runtime Filter（简称 RF）在运行时对数据进行过滤，过滤通常发生在 Join 阶段。当多表进行 Join 时，往往伴随着谓词下推等优化手段进行数据过滤，以减少 Join 表的数据扫描以及 shuffle 等阶段产生的 IO，从而提升查询性能。StarRocks 中有两种 RF，分别是 Local RF 和 Global RF。Local RF 应用于 Broadcast Hash Join 场景。Global RF 应用于 Shuffle Join 场景。
+* 默认值 `true`，表示打开 global runtime filter 开关。关闭该开关后, 不生成 Global RF, 但是依然会生成 Local RF。
+
+### enable_multicolumn_global_runtime_filter
+
+* 描述：多列 Global runtime filter 开关。默认值为 false，表示关闭该开关。
+
+  对于 Broadcast 和 Replicated Join 类型之外的其他 Join，当 Join 的等值条件有多个的情况下：
+  * 如果该选项关闭: 则只会产生 Local RF。
+  * 如果该选项打开, 则会生成 multi-part GRF, 并且该 GRF 需要携带 multi-column 作为 partition-by 表达式.
+
+* 默认值：false
+
+### enable_strict_type
+
+* 描述：是否对所有复合谓词以及 WHERE 子句中的表达式进行隐式转换。
+* 默认值：false
+* 引入版本：v3.1
+
+### enable_write_hive_external_table
+
+* 描述：是否开启往 Hive 的 External Table 写数据的功能。
+* 默认值：false
+* 引入版本：v3.2
+
+### event_scheduler
+
+* 描述：用于兼容 MySQL 客户端。无实际作用。
+* 默认值：OFF
+* 类型：String
+
+### force_streaming_aggregate（已弃用）
+
+用于控制聚合节点是否启用流式聚合计算策略。默认为 false，表示不启用该策略。
+
+### forward_to_leader
+
+用于设置是否将一些命令转发到 Leader FE 节点执行。默认为 `false`，即不转发。StarRocks 中存在多个 FE 节点，其中一个为 Leader 节点。通常用户可以连接任意 FE 节点进行全功能操作。但部分信息查看指令只有从 Leader FE 节点才能获取详细信息。别名 `forward_to_master`。
+
+如 `SHOW BACKENDS;` 命令，如果不转发到 Leader FE 节点，则仅能看到节点是否存活等一些基本信息，而转发到 Leader FE 则可以获取包括节点启动时间、最后一次心跳时间等更详细的信息。
+
+当前受该参数影响的命令如下：
+
+* SHOW FRONTENDS;
+
+  转发到 Leader 可以查看最后一次心跳信息。
+
+* SHOW BACKENDS;
+
+  转发到 Leader 可以查看启动时间、最后一次心跳信息、磁盘容量信息。
+
+* SHOW BROKER;
+
+  转发到 Leader 可以查看启动时间、最后一次心跳信息。
+
+* SHOW TABLET;
+* ADMIN SHOW REPLICA DISTRIBUTION;
+* ADMIN SHOW REPLICA STATUS;
+
+  转发到 Leader 可以查看 Leader FE 元数据中存储的 tablet 信息。正常情况下，不同 FE 元数据中 tablet 信息应该是一致的。当出现问题时，可以通过这个方法比较当前 FE 和 Leader FE 元数据的差异。
+
+* SHOW PROC;
+
+  转发到 Leader 可以查看 Leader FE 元数据中存储的相关 PROC 的信息。主要用于元数据比对。
+
+### group_concat_max_len
+
+* 描述：[group_concat](sql-functions/string-functions/group_concat.md) 函数返回的字符串的最大长度，单位为字符。
+* 默认值：1024
+* 最小值：4
+* 类型：Long
+
+### hash_join_push_down_right_table
+
+* 描述：用于控制在 Join 查询中是否可以使用针对右表的过滤条件来过滤左表的数据，可以减少 Join 过程中需要处理的左表的数据量。取值为 `true` 时表示允许该操作，系统将根据实际情况决定是否能对左表进行过滤；取值为 `false` 表示禁用该操作。
+* 默认值：true
+
+### init_connect (global)
+
+用于兼容 MySQL 客户端。无实际作用。
+
+### interactive_timeout
+
+* 描述：用于兼容 MySQL 客户端。无实际作用。
+* 默认值：1024
+* 单位：秒
+* 类型：Int
+
+### io_tasks_per_scan_operator
+
+* 每个 Scan 算子能同时下发的 I/0 任务的数量。如果使用远端存储系统（比如 HDFS 或 S3）且时延较长，可以增加该值。但是值过大会增加内存消耗。
+* 默认值：4
+* 类型：Int
+* 引入版本：v2.5
+
+### language (global)
+
+用于兼容 MySQL 客户端。无实际作用。
+
+### license (global)
+
+* 描述：显示 StarRocks 的 license。无其他作用。
+* 默认值：Apache License 2.0
+* 类型：String
+
+### load_mem_limit
+
+* 描述：用于指定导入操作的内存限制，单位为 Byte。默认值为 0，即表示不使用该变量，而采用 `query_mem_limit` 作为导入操作的内存限制。
+
+  这个变量仅用于 INSERT 操作。因为 INSERT 操作涉及查询和导入两个部分，如果用户不设置此变量，则查询和导入操作各自的内存限制均为 `query_mem_limit`。否则，INSERT 的查询部分内存限制为 `query_mem_limit`，而导入部分限制为 `load_mem_limit`。
+
+  其他导入方式，如 Broker Load，STREAM LOAD 的内存限制依然使用 `query_mem_limit`。
+
+* 默认值：0
+* 单位：Byte
+
+### log_rejected_record_num（3.1 及以后）
+
+* 描述：指定最多允许记录多少条因数据质量不合格而过滤掉的数据行数。取值范围：`0`、`-1`、大于 0 的正整数。
+* 取值为 `0` 表示不记录过滤掉的数据行。
+* 取值为 `-1` 表示记录所有过滤掉的数据行。
+* 取值为大于 0 的正整数（比如 `n`）表示每个 BE 节点上最多可以记录 `n` 条过滤掉的数据行。
+
+### lower_case_table_names (global)
+
+用于兼容 MySQL 客户端，无实际作用。StarRocks 中的表名是大小写敏感的。
+
+### materialized_view_rewrite_mode（3.2 及以后）
+
+指定异步物化视图的查询改写模式。有效值：
+
+* `disable`：禁用异步物化视图的自动查询改写。
+* `default`（默认值）：启用异步物化视图的自动查询改写，并允许优化器根据 Cost 决定是否可以使用物化视图改写查询。如果查询无法改写，则直接查询基表中的数据。
+* `default_or_error`：启用异步物化视图的自动查询改写，并允许优化器根据 Cost 决定是否可以使用物化视图改写查询。如果查询无法改写，将返回错误。
+* `force`：启用异步物化视图的自动查询改写，并且优化器优先使用物化视图改写查询。如果查询无法改写，则直接查询基表中的数据。
+* `force_or_error`：启用异步物化视图的自动查询改写，并且优化器优先使用物化视图改写查询。如果查询无法改写，将返回错误。
+
+### max_allowed_packet
+
+* 描述：用于兼容 JDBC 连接池 C3P0。该变量值决定了服务端发送给客户端或客户端发送给服务端的最大 packet 大小。当客户端报 `PacketTooBigException` 异常时，可以考虑调大该值。
+* 默认值：33554432 (32 MB)
+* 单位：Byte
+* 类型：Int
+
+### max_pushdown_conditions_per_column
+
+* 描述：该变量的具体含义请参阅 [BE 配置项](../administration/management/BE_configuration.md)中 `max_pushdown_conditions_per_column` 的说明。
+* 默认值：`-1`，表示使用 `be.conf` 中的配置值。如果设置大于 0，则忽略 `be.conf` 中的配置值。
+* 类型：Int
+
+### max_scan_key_num
+
+* 描述：该变量的具体含义请参阅 [BE 配置项](../administration/management/BE_configuration.md)中 `max_scan_key_num` 的说明。
+* 默认值：`-1`，表示使用 `be.conf` 中的配置值。如果设置大于 0，则忽略 `be.conf` 中的配置值。
+
+### nested_mv_rewrite_max_level
+
+* 描述：可用于查询改写的嵌套物化视图的最大层数。
+* 取值范围：[1, +∞)。取值为 `1` 表示只可使用基于基表创建的物化视图用于查询改写。
+* 默认值：`3`
+* 类型：Int
+
+### net_buffer_length
+
+* 描述：用于兼容 MySQL 客户端。无实际作用。
+* 默认值：16384
+* 类型：Int
+
+### net_read_timeout
+
+* 描述：用于兼容 MySQL 客户端。无实际作用。
+* 默认值：60
+* 单位：秒
+* 类型：Int
+
+### net_write_timeout
+
+* 描述：用于兼容 MySQL 客户端。无实际作用。
+* 默认值：60
+* 单位：秒
+* 类型：Int
+
+### new_planner_optimize_timeout
+
+* 描述：查询优化器的超时时间。一般查询中 Join 过多时容易出现超时。超时后会报错并停止查询，影响查询性能。您可以根据查询的具体情况调大该参数配置，也可以将问题上报给 StarRocks 技术支持进行排查。
+* 默认值：3000
+* 单位：毫秒
+
+### parallel_exchange_instance_num
+
+用于设置执行计划中，一个上层节点接收下层节点数据所使用的 exchange node 数量。默认为 -1，即表示 exchange node 数量等于下层节点执行实例的个数（默认行为）。当设置大于 0，并且小于下层节点执行实例的个数，则 exchange node 数量等于设置值。
+
+在一个分布式的查询执行计划中，上层节点通常有一个或多个 exchange node 用于接收来自下层节点在不同 BE 上的执行实例的数据。通常 exchange node 数量等于下层节点执行实例数量。
+
+在一些聚合查询场景下，如果底层需要扫描的数据量较大，但聚合之后的数据量很小，则可以尝试修改此变量为一个较小的值，可以降低此类查询的资源开销。如在 DUPLICATE KEY 明细表上进行聚合查询的场景。
+
+### parallel_fragment_exec_instance_num
+
+针对扫描节点，设置其在每个 BE 节点上执行实例的个数。默认为 1。
+
+一个查询计划通常会产生一组 scan range，即需要扫描的数据范围。这些数据分布在多个 BE 节点上。一个 BE 节点会有一个或多个 scan range。默认情况下，每个 BE 节点的一组 scan range 只由一个执行实例处理。当机器资源比较充裕时，可以将增加该变量，让更多的执行实例同时处理一组 scan range，从而提升查询效率。
+
+而 scan 实例的数量决定了上层其他执行节点，如聚合节点，join 节点的数量。因此相当于增加了整个查询计划执行的并发度。修改该参数会对大查询效率提升有帮助，但较大数值会消耗更多的机器资源，如CPU、内存、磁盘I/O。
+
+### partial_update_mode
+
+* 描述：控制部分更新的模式，有效值为：
+
+  * `auto`（默认值），表示由系统通过分析更新语句以及其涉及的列，自动判断执行部分更新时使用的模式。
+  * `column`，指定使用列模式执行部分更新，比较适用于涉及少数列并且大量行的部分列更新场景。
+
+  详细信息，请参见[UPDATE](sql-statements/table_bucket_part_index/UPDATE.md#列模式的部分更新自-31)。
+* 默认值：auto
+* 引入版本：v3.1
+
+### performance_schema (global)
+
+用于兼容 8.0.16 及以上版本的 MySQL JDBC。无实际作用。
+
+### pipeline_dop
+
+* 描述：一个 Pipeline 实例的并行数量。可通过设置实例的并行数量调整查询并发度。默认值为 0，即系统自适应调整每个 pipeline 的并行度。您也可以设置为大于 0 的数值，通常为 BE 节点 CPU 物理核数的一半。从 3.0 版本开始，支持根据查询并发度自适应调节 `pipeline_dop`。
+* 默认值：0
+* 类型：Int
+
+### pipeline_profile_level
+
+* 描述：用于控制 profile 的等级。一个 profile 通常有 5 个层级：Fragment、FragmentInstance、Pipeline、PipelineDriver、Operator。不同等级下，profile 的详细程度有所区别：
+  * 0：在此等级下，StarRocks 会合并 profile，只显示几个核心指标。
+  * 1：默认值。在此等级下，StarRocks 会对 profile 进行简化处理，将同一个 pipeline 的指标做合并来缩减层级。
+  * 2：在此等级下，StarRocks 会保留 Profile 所有的层级，不做简化。该设置下 profile 的体积会非常大，特别是 SQL 较复杂时，因此不推荐该设置。
+* 默认值：1
+* 类型：Int
+
+### prefer_compute_node
+
+* 描述：将部分执行计划调度到 CN 节点执行。
+* 默认值：false
+* 引入版本：v2.4
+
+### query_cache_size (global)
+
+用于兼容 MySQL 客户端。无实际作用。
+
+### query_cache_type
+
+ 用于兼容 JDBC 连接池 C3P0。无实际作用。
+
+### query_cache_entry_max_bytes
+
+* 描述：Cache 项的字节数上限，触发 Passthrough 模式的阈值。当一个 Tablet 上产生的计算结果的字节数或者行数超过 `query_cache_entry_max_bytes` 或 `query_cache_entry_max_rows` 指定的阈值时，则查询采用 Passthrough 模式执行。当 `query_cache_entry_max_bytes` 或 `query_cache_entry_max_rows` 取值为 0 时, 即便 Tablet 产生结果为空，也采用 Passthrough 模式。
+* 取值范围：0 ~ 9223372036854775807
+* 默认值：4194304
+* 单位：字节
+* 类型：Long
+* 引入版本：v2.5
+
+### query_cache_entry_max_rows
+
+* 描述：Cache 项的行数上限，见 `query_cache_entry_max_bytes` 描述。
+* 默认值：409600
+* 类型：Long
+* 引入版本：v2.5
+
+### query_cache_agg_cardinality_limit
+
+* 描述：GROUP BY 聚合的高基数上限。GROUP BY 聚合的输出预估超过该行数, 则不启用 cache。
+* 默认值：5000000
+* 类型：Long
+* 引入版本：v2.5
+
+### query_mem_limit
+
+* 描述：用于设置每个 BE 节点上单个查询的内存限制。该项仅在启用 Pipeline Engine 后生效。
+* 单位：字节
+* 默认值：`0`，表示没有限制。
+
+### query_queue_concurrency_limit (global)
+
+* 描述：单个 BE 节点中并发查询上限。仅在设置为大于 `0` 后生效。
+* 默认值：`0`
+* 单位：-
+* 类型：Int
+
+### query_queue_cpu_used_permille_limit (global)
+
+* 描述：单个 BE 节点中内存使用千分比上限（即 CPU 使用率）。仅在设置为大于 `0` 后生效。
+* 默认值：0。
+* 取值范围：[0, 1000]
+
+### query_queue_max_queued_queries (global)
+
+* 描述：队列中查询数量的上限。当达到此阈值时，新增查询将被拒绝执行。仅在设置为大于 `0` 后生效。
+* 默认值：1024。
+
+### query_queue_mem_used_pct_limit (global)
+
+* 描述：单个 BE 节点中内存使用百分比上限。仅在设置为大于 `0` 后生效。
+* 默认值：`0`
+* 取值范围：[0, 1]
+
+### query_queue_pending_timeout_second (global)
+
+* 描述：队列中单个查询的最大超时时间。当达到此阈值时，该查询将被拒绝执行。
+* 默认值：300
+* 单位：秒
+
+### query_timeout
+
+* 描述：用于设置查询超时时间，单位为秒。该变量会作用于当前连接中所有的查询语句，以及 INSERT 语句。
+* 默认值：300 （5 分钟）
+* 单位：秒
+* 类型：Int
+* 取值范围：1 ~ 259200
+
+### range_pruner_max_predicate
+
+* 描述：设置进行 Range 分区裁剪时，最多能使用的 IN 谓词的个数，默认值：100。如果超过该值，会扫描全部 tablet，降低查询性能。
+* 默认值：100
+* 引入版本：v3.0
+
+### resource_group
+
+暂不使用。
+
+### rewrite_count_distinct_to_bitmap_hll (已弃用)
+
+是否将 Bitmap 和 HLL 类型的 count distinct 查询改写为 bitmap_union_count 和 hll_union_agg。
+
+### runtime_filter_on_exchange_node
+
+* 描述：GRF 成功下推跨过 Exchange 算子后，是否在 Exchange Node 上放置 GRF。当一个 GRF 下推跨越 Exchange 算子，最终安装在 Exchange 算子更下层的算子上时，Exchange 算子本身是不放置 GRF 的，这样可以避免重复性使用 GRF 过滤数据而增加计算时间。但是 GRF 的投递本身是 try-best 模式，如果 query 执行时，Exchange 下层的算子接收 GRF 失败，而 Exchange 本身又没有安装 GRF，数据无法被过滤，会造成性能衰退.
+
+  该选项打开（设置为 `true`）时，GRF 即使下推跨过了 Exchange 算子, 依然会在 Exchange 算子上放置 GRF 并生效。
+* 默认值：false
+
+### runtime_join_filter_push_down_limit
+
+* 描述：生成 Bloomfilter 类型的 Local RF 的 Hash Table 的行数阈值。超过该阈值, 则不产生 Local RF。该变量避免产生过大 Local RF。取值为整数，表示行数。
+* 默认值：1024000
+* 类型：Long
+
+### runtime_profile_report_interval
+
+* 描述：Runtime Profile 的上报间隔。
+* 默认值：10
+* 单位：秒
+* 类型：Int
+* 引入版本：v3.1.0
+
+### spill_mode (3.0 及以后)
+
+中间结果落盘的执行方式。默认值：`auto`。有效值包括：
+
+* `auto`：达到内存使用阈值时，会自动触发落盘。
+* `force`：无论内存使用情况如何，StarRocks 都会强制落盘所有相关算子的中间结果。
+
+此变量仅在变量 `enable_spill` 设置为 `true` 时生效。
+
+### spill_storage_volume
+
+* 描述：用于存储触发落盘的查询的中间结果的存储卷。有关更多信息，请参阅 [将中间结果落盘至对象存储](../administration/management/resource_management/spill_to_disk.md#将中间结果落盘至对象存储)。
+* 默认值：空字符串
+* 引入版本：v3.3.0
+
+### SQL_AUTO_IS_NULL
+
+用于兼容 JDBC 连接池 C3P0，无实际作用。默认值：false。
+
+### sql_dialect
+
+* 描述：设置生效的 SQL 语法。例如，执行 `set sql_dialect = 'trino';` 命令可以切换为 Trino 语法，这样您就可以在查询中使用 Trino 特有的 SQL 语法和函数。
+
+  > **注意**
+  >
+  > 设置使用 Trino 语法后，查询默认对大小写不敏感。因此，您在 StarRocks 内建库、表时必须使用小写的库、表名称，否则查询会失败。
+* 默认值：StarRocks
+* 类型：String
+* 引入版本：v3.0
+
+### sql_mode
+
+用于指定 SQL 模式，以适应某些 SQL 方言。有效值包括：
+
+* `PIPES_AS_CONCAT`：管道符号 `|` 用于连接字符串。例如：`select 'hello ' || 'world'`。
+* `ONLY_FULL_GROUP_BY` (默认值)：SELECT LIST 中只能包含 GROUP BY 列或者聚合函数。
+* `ALLOW_THROW_EXCEPTION`：类型转换报错而不是返回 NULL。
+* `FORBID_INVALID_DATE`：禁止非法的日期。
+* `MODE_DOUBLE_LITERAL`：将浮点类型解释为 DOUBLE 而非 DECIMAL。
+* `SORT_NULLS_LAST`：排序后，将 NULL 值放到最后。
+* `ERROR_IF_OVERFLOW`：运算溢出时，报错而不是返回 NULL，目前仅 DECIMAL 支持这一行为。
+* `GROUP_CONCAT_LEGACY`：使用 2.5 及以前的 `group_concat` 的语法。该选项从 3.0.9，3.1.6 开始支持。
+
+不同模式之间可以独立设置，您可以单独开启某一个模式，例如：
+
+```SQL
+set sql_mode = 'PIPES_AS_CONCAT';
+```
+
+或者，您也可以同时设置多个模式，例如：
+
+```SQL
+set sql_mode = 'PIPES_AS_CONCAT,ERROR_IF_OVERFLOW,GROUP_CONCAT_LEGACY';
+```
+
+### sql_safe_updates
+
+用于兼容 MySQL 客户端。无实际作用。
+
+### sql_select_limit
+
+用于兼容 MySQL 客户端。无实际作用。
+
+### statistic_collect_parallel
+
+* 描述：用于调整 BE 上能并发执行的统计信息收集任务的个数，默认值为 1，可以调大该数值来加快采集任务的执行速度。
+* 默认值：1
+* 类型：Int
+
+### storage_engine
+
+指定系统使用的存储引擎。StarRocks 支持的引擎类型包括：
+
+* olap (默认值)：StarRocks 系统自有引擎。
+* mysql：使用 MySQL 外部表。
+* broker：通过 Broker 程序访问外部表。
+* ELASTICSEARCH 或者 es：使用 Elasticsearch 外部表。
+* HIVE：使用 Hive 外部表。
+* ICEBERG：使用 Iceberg 外部表。从 2.1 版本开始支持。
+* HUDI: 使用 Hudi 外部表。从 2.2 版本开始支持。
+* jdbc: 使用 JDBC 外部表。从2.3 版本开始支持。
+
+### streaming_preaggregation_mode
+
+用于设置多阶段聚合时，group-by 第一阶段的预聚合方式。如果第一阶段本地预聚合效果不好，则可以关闭预聚合，走流式方式，把数据简单序列化之后发出去。取值含义如下：
+
+* `auto`（默认值）：先探索本地预聚合，如果预聚合效果好，则进行本地预聚合；否则切换成流式。默认值，建议保留。
+* `force_preaggregation`: 不进行探索，直接进行本地预聚合。
+* `force_streaming`: 不进行探索，直接做流式。
+
+### system_time_zone (global)
+
+显示当前系统时区。不可更改。
+
+### time_zone
+
+用于设置当前会话的时区。时区会对某些时间函数的结果产生影响。
+
+### trace_log_mode
+
+* 描述：用于控制 Query Trace Profile 的 Logs 的输出位置。有效值包括：
+  * `command`：在执行 TRACE LOGS 后作为 **Explain String** 返回。
+  * `file`：在 FE 日志文件 **fe.log** 中以 `FileLogTracer` 为类名返回。
+
+  有关 Query Trace Profile 的更多信息，请参阅 [Query Trace Profile](../developers/trace-tools/query_trace_profile.md)。
+
+* 默认值：`command`
+* 类型：String
+* 引入版本：v3.2.0
+
+### transaction_read_only
+
+* 描述：用于兼容 MySQL 5.8 以上客户端，无实际作用。别名 `tx_read_only`。该变量用于指定事务访问模式。取值 `ON` 表示只读。取值 `OFF` 表示可读可写。
+* 默认值：OFF
+* 引入版本：v2.5.18, v3.0.9, v3.1.7
+
+### tx_isolation
+
+用于兼容 MySQL 客户端，无实际作用。别名 `transaction_isolation`。
+
+### use_compute_nodes
+
+* 描述：用于设置使用 CN 节点的数量上限。该设置只会在 `prefer_compute_node=true` 时才会生效。`-1`，表示使用所有 CN 节点。`0` 表示不使用 CN 节点。
+* 默认值：-1
+* 类型：Int
+* 引入版本：v2.4
+
+### use_v2_rollup
+
+用于控制查询使用 segment v2 存储格式的 Rollup 索引获取数据。该变量用于上线 segment v2 的时进行验证使用。其他情况不建议使用。
+
+### vectorized_engine_enable (2.4 版本开始弃用)
+
+用于控制是否使用向量化引擎执行查询。值为 true 时表示使用向量化引擎，否则使用非向量化引擎。默认值为 true。2.4 版本开始默认打开，所以弃用该变量。
+
+### version (global)
+
+MySQL 服务器的版本，取值等于 FE 参数 `mysql_server_version`。
+
+### version_comment (global)
+
+用于显示 StarRocks 的版本，不可更改。
+
+### wait_timeout
+
+* 描述：用于设置客户端与 StarRocks 数据库交互时的最大空闲时长。如果一个空闲连接在该时长内与 StarRocks 数据库没有任何交互，StarRocks 会主动断开这个连接。
+* 默认值：28800（即 8 小时）
+* 单位：秒
+* 类型：Int
+
+### orc_use_column_names
+
+* 描述：设置通过 Hive Catalog 读取 ORC 文件时，列的对应方式。默认值是 `false`，即按照 Hive 表中列的顺序对应。如果设置为 `true`，则按照列名称对应。
+* 引入版本：v3.1.10
diff --git a/docs/zh/sql-reference/aws_iam_policies.md b/docs/zh/sql-reference/aws_iam_policies.md
new file mode 100644
index 00000000000000..4920ca08b656f4
--- /dev/null
+++ b/docs/zh/sql-reference/aws_iam_policies.md
@@ -0,0 +1,128 @@
+---
+displayed_sidebar: docs
+---
+
+# AWS IAM 策略
+
+IAM 策略用于声明特定 AWS 资源的一组访问权限。创建 IAM 策略后，您需要将创建好的策略添加到某个 IAM 用户或角色，从而使该 IAM 用户或角色拥有该策略中所声明的访问特定 AWS 资源的权限。
+
+在 StarRocks 中，不同的操作涉及的 AWS 资源也不同。因此，您需要根据要访问的 AWS 资源来创建 IAM 策略。
+
+本文介绍在不同场景下选择 [Instance Profile、Assumed Role、及 IAM User 鉴权方式](../integrations/authenticate_to_aws_resources.md#准备工作)时，为确保 StarRocks 能够正确访问所涉及的 AWS 资源需要配置哪些 IAM 策略。
+
+## 从 AWS S3 批量导入数据
+
+如果您需要从 S3 Bucket 批量导入数据，请按如下配置 IAM 策略：
+
+> **注意**
+>
+> 您需要将下面策略中的 `<bucket_name>` 替换为数据所在的 S3 Bucket 的名称。
+
+```SQL
+{
+  "Version": "2012-10-17",
+  "Statement": [
+      {
+          "Sid": "s3",
+          "Effect": "Allow",
+          "Action": [
+              "s3:GetObject"
+          ],
+          "Resource": [
+              "arn:aws:s3:::<bucket_name>/*"
+          ]
+      },
+      {
+          "Sid": "s3list",
+          "Effect": "Allow",
+          "Action": [
+              "s3:ListBucket"
+          ],
+          "Resource": [
+              "arn:aws:s3:::<bucket_name>"
+          ]
+      }
+  ]
+}
+```
+
+## 从 AWS S3 读写数据
+
+如果您需要从 S3 Bucket 查询数据，请按如下配置 IAM 策略：
+
+> **注意**
+>
+> 您需要将下面策略中的 `<bucket_name>` 替换为数据所在的 S3 Bucket 的名称。
+
+```SQL
+{
+  "Version": "2012-10-17",
+  "Statement": [
+      {
+          "Sid": "s3",
+          "Effect": "Allow",
+          "Action": [
+              "s3:GetObject", 
+              "s3:PutObject",
+              "s3:DeleteObject"
+          ],
+          "Resource": [
+              "arn:aws:s3:::<bucket_name>/*"
+          ]
+      },
+      {
+          "Sid": "s3list",
+          "Effect": "Allow",
+          "Action": [
+              "s3:ListBucket"
+          ],
+          "Resource": [
+              "arn:aws:s3:::<bucket_name>"
+          ]
+      }
+  ]
+}
+```
+
+## 对接 AWS Glue
+
+如果您需要对接 AWS Glue，完成数据糊的查询与写入，请按如下配置 IAM 策略：
+
+```SQL
+{
+    "Version": "2012-10-17",
+    "Statement": [
+      {
+          "Effect": "Allow",
+          "Action": [
+                "glue:BatchCreatePartition",
+                "glue:UpdateDatabase",
+                "glue:GetConnections",
+                "glue:CreateTable",
+                "glue:DeleteDatabase",
+                "glue:BatchUpdatePartition",
+                "glue:GetTables",
+                "glue:GetTableVersions",
+                "glue:GetPartitions",
+                "glue:UpdateTable",
+                "glue:BatchGetPartition",
+                "glue:DeleteTable",
+                "glue:GetDatabases",
+                "glue:GetDevEndpoint",
+                "glue:GetTable",
+                "glue:GetDatabase",
+                "glue:GetPartition",
+                "glue:GetDevEndpoints",
+                "glue:GetConnection",
+                "glue:CreateDatabase",
+                "glue:CreatePartition",
+                "glue:DeletePartition",
+                "glue:UpdatePartition"
+          ],
+          "Resource": [
+              "*"
+            ]
+        }
+    ]
+}
+```
diff --git a/docs/zh/sql-reference/data-types/README.md b/docs/zh/sql-reference/data-types/README.md
new file mode 100644
index 00000000000000..d7467f8799612e
--- /dev/null
+++ b/docs/zh/sql-reference/data-types/README.md
@@ -0,0 +1,12 @@
+---
+sidebar_position: 1
+displayed_sidebar: docs
+---
+
+# Data type overview
+
+import DocCardList from '@theme/DocCardList';
+
+StarRocks supports the following data types: [Numeric](#numeric), [String](#string), [Date](#date), [Semi-structured](#semi-structured), and [Others](#others). You can define columns of these types when you create a table.
+
+<DocCardList />
diff --git a/docs/zh/sql-reference/data-types/_category_.yml b/docs/zh/sql-reference/data-types/_category_.yml
new file mode 100644
index 00000000000000..9e37077d1bb42d
--- /dev/null
+++ b/docs/zh/sql-reference/data-types/_category_.yml
@@ -0,0 +1,7 @@
+position: 10 # float position is supported
+label: 'Data types'
+collapsible: true
+collapsed: true
+link:
+  type: doc
+  id: README
diff --git a/docs/zh/sql-reference/data-types/data-type-list.md b/docs/zh/sql-reference/data-types/data-type-list.md
deleted file mode 100644
index da97aff1803893..00000000000000
--- a/docs/zh/sql-reference/data-types/data-type-list.md
+++ /dev/null
@@ -1,44 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 数据类型概述
-
-StarRocks 支持以下数据类型：[数值类型](#数值类型)、[字符串类型](#字符串类型)、[日期类型](#日期类型)、[半结构化类型](#半结构化类型)、[其他类型](#其他类型)。您在建表时可以指定以下类型的列，向表中导入该类型的数据并查询数据。
-
-## 数值类型
-
-- [TINYINT](./numeric/TINYINT.md)
-- [SMALLINT](./numeric/SMALLINT.md)
-- [INT](./numeric/INT.md)
-- [BIGINT](./numeric/BIGINT.md)
-- [LARGEINT](./numeric/LARGEINT.md)
-- [DECIMAL](./numeric/DECIMAL.md)
-- [DOUBLE](./numeric/DOUBLE.md)
-- [FLOAT](./numeric/FLOAT.md)
-- [BOOLEAN](./numeric/BOOLEAN.md)
-- PERCENTILE
-
-## 字符串类型
-
-- [CHAR](./string-type/CHAR.md)
-- [STRING](./string-type/STRING.md)
-- [VARCHAR](./string-type/VARCHAR.md)
-- [BINARY](./string-type/BINARY.md)
-
-## 日期类型
-
-- [DATE](./date-types/DATE.md)
-- [DATETIME](./date-types/DATETIME.md)
-
-## 半结构化类型
-
-- [ARRAY](./semi_structured/Array.md)
-- [JSON](./semi_structured/JSON.md)
-- [MAP](./semi_structured/Map.md)
-- [STRUCT](./semi_structured/STRUCT.md)
-
-## 其他类型
-
-- [BITMAP](./other-data-types/BITMAP.md)
-- [HLL](./other-data-types/HLL.md)
diff --git a/docs/zh/sql-reference/data-types/date-types/DATE.md b/docs/zh/sql-reference/data-types/date-types/DATE.md
index 472026f0dd99a5..9759042e761ec1 100644
--- a/docs/zh/sql-reference/data-types/date-types/DATE.md
+++ b/docs/zh/sql-reference/data-types/date-types/DATE.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # DATE
diff --git a/docs/zh/sql-reference/data-types/date-types/DATETIME.md b/docs/zh/sql-reference/data-types/date-types/DATETIME.md
index 0f7678e842183a..d9782967b97ade 100644
--- a/docs/zh/sql-reference/data-types/date-types/DATETIME.md
+++ b/docs/zh/sql-reference/data-types/date-types/DATETIME.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # DATETIME
diff --git a/docs/zh/sql-reference/data-types/date-types/_category_.yml b/docs/zh/sql-reference/data-types/date-types/_category_.yml
new file mode 100644
index 00000000000000..825c31d54e82ef
--- /dev/null
+++ b/docs/zh/sql-reference/data-types/date-types/_category_.yml
@@ -0,0 +1,6 @@
+position: 30 # float position is supported
+label: '日期类型'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/data-types/date-types/date-types.mdx b/docs/zh/sql-reference/data-types/date-types/date-types.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/sql-reference/data-types/date-types/date-types.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/sql-reference/data-types/numeric/BIGINT.md b/docs/zh/sql-reference/data-types/numeric/BIGINT.md
index 65f8c510a1e2b2..f3c8b9a0518bca 100644
--- a/docs/zh/sql-reference/data-types/numeric/BIGINT.md
+++ b/docs/zh/sql-reference/data-types/numeric/BIGINT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # BIGINT
diff --git a/docs/zh/sql-reference/data-types/numeric/BOOLEAN.md b/docs/zh/sql-reference/data-types/numeric/BOOLEAN.md
index 66c665820cdf3b..d2fe4ef3c1df31 100644
--- a/docs/zh/sql-reference/data-types/numeric/BOOLEAN.md
+++ b/docs/zh/sql-reference/data-types/numeric/BOOLEAN.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # BOOLEAN
diff --git a/docs/zh/sql-reference/data-types/numeric/DECIMAL.md b/docs/zh/sql-reference/data-types/numeric/DECIMAL.md
index a6b4f3212d5053..fbcefead0b9e56 100644
--- a/docs/zh/sql-reference/data-types/numeric/DECIMAL.md
+++ b/docs/zh/sql-reference/data-types/numeric/DECIMAL.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # DECIMAL
diff --git a/docs/zh/sql-reference/data-types/numeric/DOUBLE.md b/docs/zh/sql-reference/data-types/numeric/DOUBLE.md
index 43efc97cec4ef6..c8f47347328be2 100644
--- a/docs/zh/sql-reference/data-types/numeric/DOUBLE.md
+++ b/docs/zh/sql-reference/data-types/numeric/DOUBLE.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # DOUBLE
diff --git a/docs/zh/sql-reference/data-types/numeric/FLOAT.md b/docs/zh/sql-reference/data-types/numeric/FLOAT.md
index 2f4f7788d4f087..e98bd09c1065a5 100644
--- a/docs/zh/sql-reference/data-types/numeric/FLOAT.md
+++ b/docs/zh/sql-reference/data-types/numeric/FLOAT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # FLOAT
diff --git a/docs/zh/sql-reference/data-types/numeric/INT.md b/docs/zh/sql-reference/data-types/numeric/INT.md
index 609c7e0d1f670d..691a172896f7e0 100644
--- a/docs/zh/sql-reference/data-types/numeric/INT.md
+++ b/docs/zh/sql-reference/data-types/numeric/INT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # INT
diff --git a/docs/zh/sql-reference/data-types/numeric/LARGEINT.md b/docs/zh/sql-reference/data-types/numeric/LARGEINT.md
index cc4e3f281fca85..98d5b5e6984944 100644
--- a/docs/zh/sql-reference/data-types/numeric/LARGEINT.md
+++ b/docs/zh/sql-reference/data-types/numeric/LARGEINT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # LARGEINT
diff --git a/docs/zh/sql-reference/data-types/numeric/SMALLINT.md b/docs/zh/sql-reference/data-types/numeric/SMALLINT.md
index 00ea1666e46245..2ce19399271dc3 100644
--- a/docs/zh/sql-reference/data-types/numeric/SMALLINT.md
+++ b/docs/zh/sql-reference/data-types/numeric/SMALLINT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # SMALLINT
diff --git a/docs/zh/sql-reference/data-types/numeric/TINYINT.md b/docs/zh/sql-reference/data-types/numeric/TINYINT.md
index fc59fba03e5764..34fdb407ca25aa 100644
--- a/docs/zh/sql-reference/data-types/numeric/TINYINT.md
+++ b/docs/zh/sql-reference/data-types/numeric/TINYINT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # TINYINT
diff --git a/docs/zh/sql-reference/data-types/numeric/_category_.yml b/docs/zh/sql-reference/data-types/numeric/_category_.yml
new file mode 100644
index 00000000000000..a0af3b0b3a131d
--- /dev/null
+++ b/docs/zh/sql-reference/data-types/numeric/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: '数值类型'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/data-types/numeric/numeric.mdx b/docs/zh/sql-reference/data-types/numeric/numeric.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/sql-reference/data-types/numeric/numeric.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/sql-reference/data-types/other-data-types/BITMAP.md b/docs/zh/sql-reference/data-types/other-data-types/BITMAP.md
index b81522641d95d7..0e05fe7128a5b7 100644
--- a/docs/zh/sql-reference/data-types/other-data-types/BITMAP.md
+++ b/docs/zh/sql-reference/data-types/other-data-types/BITMAP.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # BITMAP
diff --git a/docs/zh/sql-reference/data-types/other-data-types/HLL.md b/docs/zh/sql-reference/data-types/other-data-types/HLL.md
index de9786aa03164f..2a42bd54b267b9 100644
--- a/docs/zh/sql-reference/data-types/other-data-types/HLL.md
+++ b/docs/zh/sql-reference/data-types/other-data-types/HLL.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # HLL (HyperLogLog)
@@ -55,7 +55,7 @@ create table test(
 distributed by hash(id);
 ```
 
-### 通过 [Stream load](../../sql-statements/data-manipulation/STREAM_LOAD.md) 导入数据
+### 通过 [Stream load](../../sql-statements/loading_unloading/STREAM_LOAD.md) 导入数据
 
 ```bash
 a. 使用表中的列生成 HLL 列。
diff --git a/docs/zh/sql-reference/data-types/other-data-types/_category_.yml b/docs/zh/sql-reference/data-types/other-data-types/_category_.yml
new file mode 100644
index 00000000000000..e3d588757d4186
--- /dev/null
+++ b/docs/zh/sql-reference/data-types/other-data-types/_category_.yml
@@ -0,0 +1,6 @@
+position: 50 # float position is supported
+label: '其他类型'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/data-types/other-data-types/other-data-types.mdx b/docs/zh/sql-reference/data-types/other-data-types/other-data-types.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/sql-reference/data-types/other-data-types/other-data-types.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/sql-reference/data-types/semi_structured/Array.md b/docs/zh/sql-reference/data-types/semi_structured/Array.md
index 7175520d755c7f..e382114706573b 100644
--- a/docs/zh/sql-reference/data-types/semi_structured/Array.md
+++ b/docs/zh/sql-reference/data-types/semi_structured/Array.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ARRAY
@@ -200,7 +200,7 @@ INSERT INTO t0 VALUES(1, [1,2,3]);
 
 ### 通过 Broker Load 批量导入 ORC 或 Parquet 文件中的数组
 
-StarRocks 中的数组类型，与 ORC 或 Parquet 格式中的 List 结构相对应，所以无需额外指定。具体导入方法请参考 [Broker load](../../sql-statements/data-manipulation/BROKER_LOAD.md)。
+StarRocks 中的数组类型，与 ORC 或 Parquet 格式中的 List 结构相对应，所以无需额外指定。具体导入方法请参考 [Broker load](../../sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 当前 StarRocks 支持直接导入 ORC 文件的 List 结构。Parquet 格式导入正在开发中。
 
diff --git a/docs/zh/sql-reference/data-types/semi_structured/JSON.md b/docs/zh/sql-reference/data-types/semi_structured/JSON.md
index 4350dc2f12fcb2..692d05c8c0bc70 100644
--- a/docs/zh/sql-reference/data-types/semi_structured/JSON.md
+++ b/docs/zh/sql-reference/data-types/semi_structured/JSON.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # JSON
@@ -53,7 +53,7 @@ INSERT INTO tj (id, j) VALUES (4, json_object('a', 4, 'b', false));
   - 如果需要将 JSON 文件中根节点的 JSON 对象导入并存储为 JSON 类型，可设置 `jsonpaths` 为 `$`。
   - 如果需要将 JSON 文件中一个 JSON 对象的值 (value) 导入并存储为 JSON 类型，可设置 `jsonpaths` 为 `$.a`（a 代表 key）。更多 JSON 路径表达式，参见 [JSON path](../../sql-functions/json-functions/overview-of-json-functions-and-operators.md#json-path)。
   
-- 方式三：通过 Broker Load 的方式导入 Parquet 文件并存储为 JSON 类型。导入方式，请参见 [Broker Load](../../sql-statements/data-manipulation/BROKER_LOAD.md)。
+- 方式三：通过 Broker Load 的方式导入 Parquet 文件并存储为 JSON 类型。导入方式，请参见 [Broker Load](../../sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 导入时支持数据类型转换如下：
 
diff --git a/docs/zh/sql-reference/data-types/semi_structured/Map.md b/docs/zh/sql-reference/data-types/semi_structured/Map.md
index dd4028a7f7d569..7122e61d12b7d7 100644
--- a/docs/zh/sql-reference/data-types/semi_structured/Map.md
+++ b/docs/zh/sql-reference/data-types/semi_structured/Map.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # MAP
@@ -105,7 +105,7 @@ select map() as empty_map; -- 返回 {}。
 
 ## 导入 MAP 类型数据
 
-可以使用两种方式导入 MAP 数据到 StarRocks：[INSERT INTO](../../sql-statements/data-manipulation/INSERT.md) 和 [ORC/Parquet 文件导入](../../sql-statements/data-manipulation/BROKER_LOAD.md)。
+可以使用两种方式导入 MAP 数据到 StarRocks：[INSERT INTO](../../sql-statements/loading_unloading/INSERT.md) 和 [ORC/Parquet 文件导入](../../sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 导入过程中 StarRocks 会对重复的 Key 值进行删除。
 
@@ -123,7 +123,7 @@ select map() as empty_map; -- 返回 {}。
 
 ### 从 ORC 和 Parquet 文件导入
 
-StarRocks 的 MAP 类型对应 ORC 和 Parquet 格式中的 MAP，无需您做额外的转换或定义。具体导入操作，参考 [Broker Load 文档](../../sql-statements/data-manipulation/BROKER_LOAD.md)。
+StarRocks 的 MAP 类型对应 ORC 和 Parquet 格式中的 MAP，无需您做额外的转换或定义。具体导入操作，参考 [Broker Load 文档](../../sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 ## 查询 MAP 数据
 
diff --git a/docs/zh/sql-reference/data-types/semi_structured/STRUCT.md b/docs/zh/sql-reference/data-types/semi_structured/STRUCT.md
index 1b3b933b36e10e..2d0a120639d4a2 100644
--- a/docs/zh/sql-reference/data-types/semi_structured/STRUCT.md
+++ b/docs/zh/sql-reference/data-types/semi_structured/STRUCT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # STRUCT
@@ -80,7 +80,7 @@ select named_struct('a', 1, 'b', 2, 'c', 3, 'd', 4) as numbers; -- 返回 {"a":1
 
 ## 导入 STRUCT 类型数据
 
-可以使用两种方式导入 STRUCT 数据到 StarRocks：[INSERT INTO](../../sql-statements/data-manipulation/INSERT.md) 和 [ORC/Parquet 文件导入](../../sql-statements/data-manipulation/BROKER_LOAD.md)。
+可以使用两种方式导入 STRUCT 数据到 StarRocks：[INSERT INTO](../../sql-statements/loading_unloading/INSERT.md) 和 [ORC/Parquet 文件导入](../../sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 导入过程中 StarRocks 会对重复的 Key 值进行删除。
 
@@ -105,7 +105,7 @@ SELECT * FROM t0;
 
 ### 从 ORC 和 Parquet 文件导入
 
-StarRocks 的 STRUCT 类型对应 ORC 和 Parquet 格式中的嵌套列 (nested columns structure)，无需您做额外的转换或定义。具体导入操作，参考 [Broker Load 文档](../../sql-statements/data-manipulation/BROKER_LOAD.md)。
+StarRocks 的 STRUCT 类型对应 ORC 和 Parquet 格式中的嵌套列 (nested columns structure)，无需您做额外的转换或定义。具体导入操作，参考 [Broker Load 文档](../../sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 ## 查询 STRUCT 数据
 
diff --git a/docs/zh/sql-reference/data-types/semi_structured/_category_.yml b/docs/zh/sql-reference/data-types/semi_structured/_category_.yml
new file mode 100644
index 00000000000000..a9fbbe8a3a6f71
--- /dev/null
+++ b/docs/zh/sql-reference/data-types/semi_structured/_category_.yml
@@ -0,0 +1,6 @@
+position: 40 # float position is supported
+label: '半结构化类型'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/data-types/semi_structured/semi_structured.mdx b/docs/zh/sql-reference/data-types/semi_structured/semi_structured.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/sql-reference/data-types/semi_structured/semi_structured.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/sql-reference/data-types/string-type/BINARY.md b/docs/zh/sql-reference/data-types/string-type/BINARY.md
index 23bb181b92fe54..28069671279593 100644
--- a/docs/zh/sql-reference/data-types/string-type/BINARY.md
+++ b/docs/zh/sql-reference/data-types/string-type/BINARY.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # BINARY/VARBINARY
diff --git a/docs/zh/sql-reference/data-types/string-type/CHAR.md b/docs/zh/sql-reference/data-types/string-type/CHAR.md
index c79d588fec674e..bc8465d0e17a31 100644
--- a/docs/zh/sql-reference/data-types/string-type/CHAR.md
+++ b/docs/zh/sql-reference/data-types/string-type/CHAR.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # CHAR
diff --git a/docs/zh/sql-reference/data-types/string-type/STRING.md b/docs/zh/sql-reference/data-types/string-type/STRING.md
index a8ee711252f4bd..730778226fdd4d 100644
--- a/docs/zh/sql-reference/data-types/string-type/STRING.md
+++ b/docs/zh/sql-reference/data-types/string-type/STRING.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # STRING
diff --git a/docs/zh/sql-reference/data-types/string-type/VARCHAR.md b/docs/zh/sql-reference/data-types/string-type/VARCHAR.md
index b4c5c09593f03d..d3233165ffa477 100644
--- a/docs/zh/sql-reference/data-types/string-type/VARCHAR.md
+++ b/docs/zh/sql-reference/data-types/string-type/VARCHAR.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # VARCHAR
diff --git a/docs/zh/sql-reference/data-types/string-type/_category_.yml b/docs/zh/sql-reference/data-types/string-type/_category_.yml
new file mode 100644
index 00000000000000..36ab6f303cdc1b
--- /dev/null
+++ b/docs/zh/sql-reference/data-types/string-type/_category_.yml
@@ -0,0 +1,6 @@
+position: 20 # float position is supported
+label: '字符串类型'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/data-types/string-type/string-type.mdx b/docs/zh/sql-reference/data-types/string-type/string-type.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/sql-reference/data-types/string-type/string-type.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/sql-reference/http_sql_api.md b/docs/zh/sql-reference/http_sql_api.md
new file mode 100644
index 00000000000000..e258bd7b9b6feb
--- /dev/null
+++ b/docs/zh/sql-reference/http_sql_api.md
@@ -0,0 +1,207 @@
+---
+displayed_sidebar: docs
+---
+
+# HTTP SQL API
+
+## 功能
+
+StarRocks 3.2.0 版本提供了 HTTP SQL API，方便用户通过 HTTP 协议使用 StarRocks 的查询功能，当前支持 SELECT、SHOW、EXPLAIN、KILL 语句。
+
+使用 curl 命令的一个语法示例：
+
+```shell
+curl -X POST 'http://<fe_ip>:<fe_http_port>/api/v1/catalogs/<catalog_name>/databases/<database_name>/sql' \
+   -u '<username>:<password>'  -d '{"query": "<sql_query>;", "sessionVariables":{"<var_name>":<var_value>}}' \
+   --header "Content-Type: application/json"
+```
+
+## 请求报文
+
+### Request line
+
+```shell
+POST 'http://<fe_ip>:<fe_http_port>/api/v1/catalogs/<catalog_name>/databases/<database_name>/sql'
+```
+
+| Field                    | Description                                                  |
+| ------------------------ | :----------------------------------------------------------- |
+|  fe_ip                   | FE 节点 IP。                                                  |
+|  fe_http_port            | FE 节点 HTTP Port。                                           |
+|  catalog_name            | 数据目录名称。3.2.0 版本仅支持查询 StarRocks 内部表，即 `<catalog_name>` 仅支持为 `default_catalog`。从 3.2.1 版本开始，支持查询[外部 Catalog](../data_source/catalog/catalog_overview.md) 下的表。|
+|  database_name           | 数据库名称。如果未指定数据库名称，那么在 SQL query 语句中出现的表名前面需要加上 database 名，比如 `database_name.table_name`。 |
+
+- 指定 catalog，跨 database 查询。SQL 语句中出现的表前面需要加上 database 名。
+
+   ```shell
+   POST /api/v1/catalogs/<catalog_name>/sql
+   ```
+
+- 指定 catalog 和 database 查询。
+
+   ```shell
+   POST /api/v1/catalogs/<catalog_name>/databases/<database_name>/sql
+   ```
+
+### 认证方式
+
+```SQL
+Authorization: Basic <credentials>
+```
+
+使用 Basic authentication 进行认证，即 `credentials` 里填写用户名和密码 (`-u '<username>:<password>'`)。注意如果账号没有设置密码，只需传入 `<username>:`，密码留空。举例，如果 root 账号没有设置密码，则写作 `-u 'root:'`。
+
+### Request body
+
+```shell
+-d '{"query": "<sql_query>;", "sessionVariables":{"<var_name>":<var_value>}}'
+```
+
+| Field                    | Description                                                  |
+| ------------------------ | :----------------------------------------------------------- |
+| query                    | SQL 语句，STRING 格式。当前支持 SELECT、SHOW、EXPLAIN、KILL 语句。一次 HTTP 请求只允许执行一条 SQL。 |
+| sessionVariables         | 指定的 session 变量，JSON 格式。可选，默认为空。设置的 session 变量在同一连接中始终有效，连接断开后 session 变量失效。 |
+
+### Request header
+
+```shell
+--header "Content-Type: application/json"
+```
+
+表示发送的请求体是 JSON 字符串。
+
+## 响应报文
+
+### Status code
+
+- 200：HTTP 请求成功，且在发送数据给客户端之前服务器未出现异常。
+- 4xx：HTTP 请求错误，表示客户端出错。
+- `500 Internal Server Error`：HTTP 请求成功，但是在发送数据给客户端之前出现异常。
+- 503：HTTP 请求成功，但是 FE 当前无法提供服务。
+
+### Response header
+
+content-type 表示 response body 的格式。这里使用 Newline delimited JSON 格式，即 response body 由若干 JSON object 组成，JSON object 之间以 `\n` 隔开。
+
+|                      | Description                                                  |
+| -------------------- | :----------------------------------------------------------- |
+| content-type         | 格式为 Newline delimited JSON。默认为 "application/x-ndjson charset=UTF-8"。 |
+| X-StarRocks-Query-Id | Query ID。                                                          |
+
+### Response body
+
+#### 在结果发出之前执行失败
+
+客户端的请求出错或者服务端在将数据发送给客户端之前出现异常，此时 response body 格式如下。其中 `msg` 为对应的错误异常信息。
+
+```json
+{
+   "status":"FAILED",
+   "msg":"xxx"
+}
+```
+
+#### 在结果发出部分后执行失败
+
+此时结果已经部分发出，HTTP 状态码为 200，因此选择不再继续发送数据，并关闭连接，记录错误日志。
+
+#### 执行成功
+
+返回结果中每行是一个 JSON object，JSON object 之间以换行符 `\n` 隔开，从而便于客户端解析。
+
+- 对于 SELECT 语句，会返回以下 JSON object。
+
+| Object       | Description                                                  |
+| ------------ | :----------------------------------------------------------- |
+| `connectionId` | 该连接对应的 ID，可通过 KILL `<connectionId>` 来取消某个执行时间过长的 query。 |
+| `meta`        | 用来描述每个列。Key 为 meta, Value 为一个 JSON array。array 中的每个 object 表示一个 column。 |
+| `data`         | 代表一行数据。Key 为 data, Value 为一个 JSON  array，array 中包含一条数据。 |
+| `statistics`   | 本次执行结果的统计信息。                                       |
+
+- 对于 SHOW，会返回 `meta`，`data`，`statistics`。
+- 对于 EXPLAIN，会返回一个 `explain` 对象，展示这条查询详细的执行计划。
+
+样例：这里换行以 `\n` 表示。发送时 StarRocks 使用 HTTP chunked 方式传输数据，FE 每获取一批数据，就将该批数据流式转发给客户端。客户端可以按行解析 StarRocks 发送的数据，而不需要缓存现有结果直到所有数据发送完毕再进行解析。这可以降低客户端的内存消耗。
+
+```json
+{"connectionId": 7}\n
+{"meta": [
+    {
+      "name": "stock_symbol",
+      "type": "varchar"
+    },
+    {
+      "name": "closing_price",
+      "type": "decimal64(8, 2)"
+    },
+    {
+      "name": "closing_date",
+      "type": "datetime"
+    }
+  ]}\n
+{"data": ["JDR", 12.86, "2014-10-02 00:00:00"]}\n
+{"data": ["JDR",14.8, "2014-10-10 00:00:00"]}\n
+...
+{"statistics": {"scanRows": 0,"scanBytes": 0,"returnRows": 9}}
+```
+
+## 接口调用示例
+
+### 发起查询
+
+- 查询 StarRocks 内部表，即 `<catalog_name>` 为 `default_catalog`。
+
+  ```shell
+  curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:' -d '{"query": "select * from agg;"}' --header "Content-Type: application/json"
+  ```
+
+  返回结果：
+
+  ```json
+  {"connectionId":49}
+  {"meta":[{"name":"no","type":"int(11)"},{"name":"k","type":"decimal64(10, 2)"},{"name":"v","type":"decimal64(10, 2)"}]}
+  {"data":[1,"10.00",null]}
+  {"data":[2,"10.00","11.00"]}
+  {"data":[2,"20.00","22.00"]}
+  {"data":[2,"25.00",null]}
+  {"data":[2,"30.00","35.00"]}
+  {"statistics":{"scanRows":0,"scanBytes":0,"returnRows":5}}
+  ```
+
+- 查询 Iceberg Catalog 下的表。
+
+  ```shell
+  curl -X POST 'http://172.26.93.145:8030/api/v1/catalogs/iceberg_catalog/databases/ywb/sql' -u 'root:' -d '{"query": "select * from iceberg_analyze;"}' --header "Content-Type: application/json"
+  ```
+
+  返回结果：
+
+  ```json
+  {"connectionId":13}
+  {"meta":[{"name":"k1","type":"int(11)"},{"name":"k2","type":"int(11)"}]}
+  {"data":[1,2]}
+  {"data":[1,1]}
+  {"statistics":{"scanRows":0,"scanBytes":0,"returnRows":2}}
+  ```
+
+### 取消查询
+
+想要取消一个耗时过长的查询时，可以直接断开连接。当检测到连接已断开，StarRocks 会自动取消该查询。
+
+此外，也可以通过发送 KILL `connectionId` 的方式取消该查询。举例：
+
+```shell
+curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:' -d '{"query": "kill 17;"}' --header "Content-Type: application/json"
+```
+
+`connectionId` 除了在 Response body 中会返回，也可以通过 SHOW PROCESSLIST 命令获得。举例：
+
+```shell
+curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:' -d '{"query": "show processlist;"}' --header "Content-Type: application/json"
+```
+
+### 发起查询的同时设置 session 变量
+
+```shell
+curl -X POST 'http://127.0.0.1:8030/api/v1/catalogs/default_catalog/databases/test/sql' -u 'root:'  -d '{"query": "SHOW VARIABLES;", "sessionVariables":{"broadcast_row_limit":14000000}}'  --header "Content-Type: application/json"
+```
diff --git a/docs/zh/sql-reference/information_schema/be_bvars.md b/docs/zh/sql-reference/information_schema/be_bvars.md
new file mode 100644
index 00000000000000..4a7d43f10ade86
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/be_bvars.md
@@ -0,0 +1,15 @@
+---
+displayed_sidebar: docs
+---
+
+# be_bvars
+
+`be_bvars` 提供有关 bRPC 的统计信息。您可以查看 RPC 延迟、QPS 和某些 StarRocks 组件的统计信息。
+
+`be_bvars` 提供以下字段：
+
+| **字段** | **描述**                          |
+| -------- | --------------------------------- |
+| BE_ID    | bvar 所在的 BE 的 ID。             |
+| NAME     | bvar 名称。                       |
+| DESC     | bvar 描述，其中包括统计信息的值。 |
diff --git a/docs/zh/sql-reference/information_schema/be_cloud_native_compactions.md b/docs/zh/sql-reference/information_schema/be_cloud_native_compactions.md
new file mode 100644
index 00000000000000..a97e2b558c34b5
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/be_cloud_native_compactions.md
@@ -0,0 +1,23 @@
+---
+displayed_sidebar: docs
+---
+
+# be_cloud_native_compactions
+
+`be_cloud_native_compactions` 提供有关存算一体集群的 CN（或 v3.0 中的 BE）上运行的 Compaction 事务的信息。每个 Compaction 任务会以 Tablet 为粒度，拆分为多个子任务，视图中每一行对应的是一个 Tablet 的 Compaction 子任务。
+
+`be_cloud_native_compactions` 提供以下字段：
+
+| **字段**    | **描述**                                                     |
+| ----------- | ------------------------------------------------------------ |
+| BE_ID       | CN（BE）的 ID。                                              |
+| TXN_ID      | Compaction 任务对应的事务 ID。同一个 Compaction 事务可能会有多个子任务，所以可能存在 TXN_ID 相同的情况。 |
+| TABLET_ID   | Compaction 任务对应的 Tablet ID。                            |
+| VERSION     | Compaction 任务的输入数据的版本。                            |
+| SKIPPED     | 任务是否跳过执行。                                           |
+| RUNS        | 任务运行次数，大于 1 表示发生过重试。                        |
+| START_TIME  | 开始执行的时间。                                             |
+| FINISH_TIME | 结束执行的时间。如果任务还在执行中，值为 NULL。              |
+| PROGRESS    | 进度的百分比，范围是 0 到 100。                              |
+| STATUS      | 任务运行状态。                                               |
+
diff --git a/docs/zh/sql-reference/information_schema/be_compactions.md b/docs/zh/sql-reference/information_schema/be_compactions.md
new file mode 100644
index 00000000000000..5cd69bd54cae98
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/be_compactions.md
@@ -0,0 +1,20 @@
+---
+displayed_sidebar: docs
+---
+
+# be_compactions
+
+`be_compactions` 提供有关 Compaction 任务的统计信息。
+
+`be_compactions` 提供以下字段：
+
+| **字段**                          | **描述**                                      |
+| --------------------------------- | --------------------------------------------- |
+| BE_ID                             | BE 的 ID。                                    |
+| CANDIDATES_NUM                    | 当前等待执行的 Compaction 任务数。            |
+| BASE_COMPACTION_CONCURRENCY       | 当前正在执行的 Base Compaction 任务数。       |
+| CUMULATIVE_COMPACTION_CONCURRENCY | 当前正在执行的 Cumulative Compaction 任务数。 |
+| LATEST_COMPACTION_SCORE           | 上次 Compaction 任务的 Compaction Score。     |
+| CANDIDATE_MAX_SCORE               | 等待执行的任务的最大 Compaction Score。       |
+| MANUAL_COMPACTION_CONCURRENCY     | 当前正在执行的手动 Compaction 任务数。        |
+| MANUAL_COMPACTION_CANDIDATES_NUM  | 当前等待执行的手动 Compaction 任务数。        |
diff --git a/docs/zh/sql-reference/information_schema/character_sets.md b/docs/zh/sql-reference/information_schema/character_sets.md
new file mode 100644
index 00000000000000..cc17595ed2f09c
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/character_sets.md
@@ -0,0 +1,16 @@
+---
+displayed_sidebar: docs
+---
+
+# character_sets
+
+`character_sets` 用于识别可用的字符集。
+
+`character_sets` 提供以下字段：
+
+| **字段**             | **描述**                       |
+| -------------------- | ------------------------------ |
+| CHARACTER_SET_NAME   | 字符集名称。                   |
+| DEFAULT_COLLATE_NAME | 字符集的默认排序规则。         |
+| DESCRIPTION          | 字符集的描述。                 |
+| MAXLEN               | 存储一个字符所需的最大字节数。 |
diff --git a/docs/zh/sql-reference/information_schema/collations.md b/docs/zh/sql-reference/information_schema/collations.md
new file mode 100644
index 00000000000000..f3eaf06e0503ea
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/collations.md
@@ -0,0 +1,18 @@
+---
+displayed_sidebar: docs
+---
+
+# collations
+
+`collations` 包含可用的排序规则。
+
+`collations` 提供以下字段：
+
+| **字段**           | **描述**                                       |
+| ------------------ | ---------------------------------------------- |
+| COLLATION_NAME     | 排序规则名称。                                 |
+| CHARACTER_SET_NAME | 与排序规则相关联的字符集的名称。               |
+| ID                 | 排序规则的 ID。                                |
+| IS_DEFAULT         | 排序规则是否为其字符集的默认值。               |
+| IS_COMPILED        | 字符集是否已编译到服务器中。                   |
+| SORTLEN            | 与在字符集中表达的字符串排序所需的内存量有关。 |
diff --git a/docs/zh/sql-reference/information_schema/column_privileges.md b/docs/zh/sql-reference/information_schema/column_privileges.md
new file mode 100644
index 00000000000000..5588220d6bb5cb
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/column_privileges.md
@@ -0,0 +1,25 @@
+---
+displayed_sidebar: docs
+---
+
+# column_privileges
+
+:::note
+
+该视图不适用于 StarRocks 当前支持的功能。
+
+:::
+
+`column_privileges` 用于识别当前启用的角色被授予的或由当前启用的角色授予的所有列权限。
+
+`column_privileges` 提供以下字段：
+
+| 字段           | 描述                                                         |
+| -------------- | ------------------------------------------------------------ |
+| GRANTEE        | 被授予权限的用户的名称。                                     |
+| TABLE_CATALOG  | 包含列的表所属的目录的名称。该值始终为 `def`。               |
+| TABLE_SCHEMA   | 包含列的表所属的模式（数据库）的名称。                       |
+| TABLE_NAME     | 包含列的表的名称。                                           |
+| COLUMN_NAME    | 列的名称。                                                   |
+| PRIVILEGE_TYPE | 被授予的权限。该值可以是在列级别授予的任何权限。每一行列出一个权限，因此对于被授予者拥有的每个列权限，都有一行。 |
+| IS_GRANTABLE   | 如果用户具有 `GRANT OPTION` 权限，则为 `YES`，否则为 `NO`。输出不将 `GRANT OPTION` 列为单独的行，其 `PRIVILEGE_TYPE` 为 `'GRANT OPTION'`。 |
diff --git a/docs/zh/sql-reference/information_schema/columns.md b/docs/zh/sql-reference/information_schema/columns.md
new file mode 100644
index 00000000000000..ab11d0586950b1
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/columns.md
@@ -0,0 +1,40 @@
+---
+displayed_sidebar: docs
+---
+
+# columns
+
+`columns` 包含有关所有表（或视图）中列的信息。
+
+:::note
+[同步物化视图](../../using_starrocks/Materialized_view-single_table.md) 的元数据并未在 `columns` 中记录。您可以通过执行 `SHOW PROC '/dbs/db/table/index_schema'` 查看同步物化视图的元数据。
+:::
+
+`columns` 提供以下字段：
+
+| 字段                     | 描述                                                         |
+| ------------------------ | ------------------------------------------------------------ |
+| TABLE_CATALOG            | 包含列的表所属的目录的名称。该值始终为 NULL。                |
+| TABLE_SCHEMA             | 包含列的表所属的模式（数据库）的名称。                       |
+| TABLE_NAME               | 包含列的表的名称。                                           |
+| COLUMN_NAME              | 列的名称。                                                   |
+| ORDINAL_POSITION         | 列在表内的顺序位置。                                         |
+| COLUMN_DEFAULT           | 列的默认值。如果列具有显式的 NULL 默认值，或者列定义中不包含 DEFAULT 子句，则为 NULL。 |
+| IS_NULLABLE              | 列是否可为 NULL。如果可以在列中存储 NULL 值，则值为 `YES`，否则为 `NO`。 |
+| DATA_TYPE                | 列的数据类型。<br />`DATA_TYPE` 值仅为类型名称，不包含其他信息。`COLUMN_TYPE` 值包含类型名称，可能还包含其他信息，如精度或长度。 |
+| CHARACTER_MAXIMUM_LENGTH | 对于字符串列，字符的最大长度。                               |
+| CHARACTER_OCTET_LENGTH   | 对于字符串列，字节的最大长度。                               |
+| NUMERIC_PRECISION        | 对于数值列，数值的精度。                                     |
+| NUMERIC_SCALE            | 对于数值列，数值的刻度。                                     |
+| DATETIME_PRECISION       | 对于时间列，小数秒的精度。                                   |
+| CHARACTER_SET_NAME       | 对于字符字符串列，字符集的名称。                             |
+| COLLATION_NAME           | 对于字符字符串列，排序规则的名称。                           |
+| COLUMN_TYPE              | 列的数据类型。<br />`DATA_TYPE` 值仅为类型名称，不包含其他信息。`COLUMN_TYPE` 值包含类型名称，可能还包含其他信息，如精度或长度。 |
+| COLUMN_KEY               | 列是否已建立索引：<br />如果 `COLUMN_KEY` 为空，则该列未建立索引，或仅作为多列非唯一索引中的次要列建立索引。<br />如果 `COLUMN_KEY` 为 `PRI`，则该列是主键，或是多列主键中的一列。<br />如果 `COLUMN_KEY` 为 `UNI`，则该列是唯一索引的第一列。<br />如果 `COLUMN_KEY` 为 `DUP`，则该列是允许在列内有多个相同值的非唯一索引的第一列。<br />如果给定表的列的多个 `COLUMN_KEY` 值都适用，则 `COLUMN_KEY` 会显示具有最高优先级的值，按照 `PRI`、`UNI`、`DUP` 的顺序。<br />如果 UNIQUE 索引不允许包含 NULL 值，并且表中没有主键，则唯一索引可能显示为 `PRI`。如果多个列形成复合唯一索引，则尽管这些列的组合是唯一的，每个列仍然可以包含多个相同值，因此可能显示为 `MUL`。 |
+| EXTRA                    | 关于给定列的任何其他信息。                                   |
+| PRIVILEGES               | 您对该列拥有的权限。                                         |
+| COLUMN_COMMENT           | 列定义中包含的任何注释。                                     |
+| COLUMN_SIZE              |                                                              |
+| DECIMAL_DIGITS           |                                                              |
+| GENERATION_EXPRESSION    | 对于生成的列，显示用于计算列值的表达式。非生成列为空。       |
+| SRS_ID                   | 此值适用于空间列。它包含列 SRID 值，指示存储在列中的值的空间参考系统。 |
diff --git a/docs/zh/sql-reference/information_schema/engines.md b/docs/zh/sql-reference/information_schema/engines.md
new file mode 100644
index 00000000000000..89fc1961ca1a8e
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/engines.md
@@ -0,0 +1,25 @@
+---
+displayed_sidebar: docs
+---
+
+# engines
+
+:::note
+
+该视图不适用于 StarRocks 当前支持的功能。
+
+:::
+
+`engines` 提供有关存储引擎的信息。
+
+`engines` 提供以下字段：
+
+| 字段         | 描述                                                         |
+| ------------ | ------------------------------------------------------------ |
+| ENGINE       | 存储引擎的名称。                                             |
+| SUPPORT      | 服务器对存储引擎的支持水平。有效值：<br />`YES`：引擎受支持且处于活动状态。<br />`DEFAULT`：类似于 YES，此外还是默认引擎。<br />`NO`：引擎不受支持。<br />`DISABLED`：引擎受支持但已被禁用。 |
+| COMMENT      | 存储引擎的简要描述。                                         |
+| TRANSACTIONS | 存储引擎是否支持事务。                                       |
+| XA           | 存储引擎是否支持 XA 事务。                                   |
+| SAVEPOINTS   | 存储引擎是否支持保存点。                                     |
+
diff --git a/docs/zh/sql-reference/information_schema/events.md b/docs/zh/sql-reference/information_schema/events.md
new file mode 100644
index 00000000000000..95401971c31564
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/events.md
@@ -0,0 +1,42 @@
+---
+displayed_sidebar: docs
+---
+
+# events
+
+:::note
+
+该视图不适用于 StarRocks 当前支持的功能。
+
+:::
+
+`events` 提供有关 Event Manager 事件的信息。
+
+`events` 提供以下字段：
+
+| 字段                 | 描述                                                         |
+| -------------------- | ------------------------------------------------------------ |
+| EVENT_CATALOG        | 事件所属的目录的名称。该值始终为 def。                       |
+| EVENT_SCHEMA         | 事件所属的模式（数据库）的名称。                             |
+| EVENT_NAME           | 事件的名称。                                                 |
+| DEFINER              | DEFINER 子句中指定的用户（通常是创建事件的用户）。           |
+| TIME_ZONE            | 事件的时区，用于调度事件并在事件执行时生效。默认值为 SYSTEM。 |
+| EVENT_BODY           | 事件的 DO 子句中语句所使用的语言。该值始终为 SQL。           |
+| EVENT_DEFINITION     | 事件的 DO 子句组成的 SQL 语句的文本；换句话说，此事件执行的语句。 |
+| EVENT_TYPE           | 事件的重复类型，可以是 ONE TIME（一次性）或 RECURRING（重复）。 |
+| EXECUTE_AT           | 对于一次性事件，这是在创建事件的 CREATE EVENT 语句的 AT 子句中指定的 DATETIME 值，或者在最后一个修改事件的 ALTER EVENT 语句中指定的 DATETIME 值。此列中显示的值反映了事件的 AT 子句中包含的任何 INTERVAL 值的加法或减法。例如，如果使用 ON SCHEDULE AT CURRENT_DATETIME + '1:6' DAY_HOUR 创建事件，并且事件在 2018-02-09 14:05:30 创建，则此列中显示的值将为 '2018-02-10 20:05:30'。如果事件的时间是由 EVERY 子句而不是 AT 子句确定的（即事件是重复的），则此列的值为 NULL。 |
+| INTERVAL_VALUE       | 对于重复事件，事件执行之间等待的间隔数。对于一次性事件，该值始终为 NULL。 |
+| INTERVAL_FIELD       | 重复事件等待重复之前使用的间隔的时间单位。对于一次性事件，该值始终为 NULL。 |
+| SQL_MODE             | 事件创建或更改时有效的 SQL 模式，以及事件执行时使用的 SQL 模式。 |
+| STARTS               | 重复事件的开始日期和时间。显示为 DATETIME 值，如果未为事件定义开始日期和时间，则为 NULL。对于一次性事件，此列始终为 NULL。对于定义包含 STARTS 子句的重复事件，此列包含相应的 DATETIME 值。与 EXECUTE_AT 列一样，此值解析了任何使用的表达式。如果没有 STARTS 子句影响事件的时间，此列为 NULL。 |
+| ENDS                 | 对于定义包含 ENDS 子句的重复事件，此列包含相应的 DATETIME 值。与 EXECUTE_AT 列一样，此值解析了任何使用的表达式。如果没有 ENDS 子句影响事件的时间，此列为 NULL。 |
+| STATUS               | 事件的状态。ENABLED、DISABLED 或 SLAVESIDE_DISABLED 中的一个。SLAVESIDE_DISABLED 表示事件的创建发生在充当复制源的另一台 MySQL 服务器上，并且复制到充当副本的当前 MySQL 服务器，但事件当前未在副本上执行。 |
+| ON_COMPLETION        | 有效值：PRESERVE 和 NOT PRESERVE。                           |
+| CREATED              | 事件创建的日期和时间。这是一个 DATETIME 值。                 |
+| LAST_ALTERED         | 事件上次修改的日期和时间。这是一个 DATETIME 值。如果事件自创建以来未被修改，则此值与 CREATED 值相同。 |
+| LAST_EXECUTED        | 事件上次执行的日期和时间。这是一个 DATETIME 值。如果事件从未执行过，则此列为 NULL。LAST_EXECUTED 指示事件何时开始执行。因此，ENDS 列永远不会小于 LAST_EXECUTED。 |
+| EVENT_COMMENT        | 事件的注释文本，如果事件有注释。如果没有，则此值为空。       |
+| ORIGINATOR           | 事件创建时所在的 MySQL 服务器的服务器 ID；用于复制。如果在复制源上执行，则 ALTER EVENT 可更新此值为该语句发生的服务器的服务器 ID。默认值为 0。 |
+| CHARACTER_SET_CLIENT | 创建事件时 character_set_client 系统变量的会话值。           |
+| COLLATION_CONNECTION | 创建事件时 collation_connection 系统变量的会话值。           |
+| DATABASE_COLLATION   | 与事件关联的数据库的排序规则。                               |
diff --git a/docs/zh/sql-reference/information_schema/global_variables.md b/docs/zh/sql-reference/information_schema/global_variables.md
new file mode 100644
index 00000000000000..a9da1ab10dd246
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/global_variables.md
@@ -0,0 +1,15 @@
+---
+displayed_sidebar: docs
+---
+
+# global_variables
+
+`global_variables` 提供有关全局变量的信息。
+
+`global_variables` 提供以下字段：
+
+| **字段**       | **描述**       |
+| -------------- | -------------- |
+| VARIABLE_NAME  | 全局变量的名称 |
+| VARIABLE_VALUE | 全局变量的值   |
+
diff --git a/docs/zh/sql-reference/information_schema/information_schema.md b/docs/zh/sql-reference/information_schema/information_schema.md
new file mode 100644
index 00000000000000..4056fdbdb5cdf2
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/information_schema.md
@@ -0,0 +1,51 @@
+---
+displayed_sidebar: docs
+keywords: ['Yuanshuju']
+---
+
+# Information Schema
+
+import DocCardList from '@theme/DocCardList';
+
+Information Schema 是 StarRocks 实例中的一个数据库。该数据库包含数张由系统定义的视图，这些视图中存储了关于 StarRocks 实例中所有对象的大量元数据信息。
+
+自 v3.2.0 起，Information Schema 支持管理 External Catalog 中的元数据信息。
+
+## 通过 Information Schema 查看元数据信息
+
+您可以通过查询 Information Schema 中的视图来查看 StarRocks 实例中的元数据信息。
+
+以下示例通过查询视图 `tables` 查看 StarRocks 中名为 `table1` 的表相关的元数据信息。
+
+```Plain
+MySQL > SELECT * FROM information_schema.tables WHERE TABLE_NAME like 'table1'\G
+*************************** 1. row ***************************
+  TABLE_CATALOG: def
+   TABLE_SCHEMA: test_db
+     TABLE_NAME: table1
+     TABLE_TYPE: BASE TABLE
+         ENGINE: StarRocks
+        VERSION: NULL
+     ROW_FORMAT: 
+     TABLE_ROWS: 4
+ AVG_ROW_LENGTH: 1657
+    DATA_LENGTH: 6630
+MAX_DATA_LENGTH: NULL
+   INDEX_LENGTH: NULL
+      DATA_FREE: NULL
+ AUTO_INCREMENT: NULL
+    CREATE_TIME: 2023-06-13 11:37:00
+    UPDATE_TIME: 2023-06-13 11:38:06
+     CHECK_TIME: NULL
+TABLE_COLLATION: utf8_general_ci
+       CHECKSUM: NULL
+ CREATE_OPTIONS: 
+  TABLE_COMMENT: 
+1 row in set (0.01 sec)
+```
+
+## Information Schema 中的视图
+
+StarRocks Information Schema 中包含以下视图：
+
+<DocCardList />
diff --git a/docs/zh/sql-reference/information_schema/key_column_usage.md b/docs/zh/sql-reference/information_schema/key_column_usage.md
new file mode 100644
index 00000000000000..1b9804983d674f
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/key_column_usage.md
@@ -0,0 +1,30 @@
+---
+displayed_sidebar: docs
+---
+
+# key_column_usage
+
+:::note
+
+该视图不适用于 StarRocks 当前支持的功能。
+
+:::
+
+`key_column_usage` 用于识别受某些唯一、主键或外键约束限制的所有列。
+
+`key_column_usage` 提供以下字段：
+
+| 字段                          | 描述                                                         |
+| ----------------------------- | ------------------------------------------------------------ |
+| CONSTRAINT_CATALOG            | 约束所属的目录的名称。该值始终为 def。                       |
+| CONSTRAINT_SCHEMA             | 约束所属的数据库的名称。                                     |
+| CONSTRAINT_NAME               | 约束的名称。                                                 |
+| TABLE_CATALOG                 | 表所属的目录的名称。该值始终为 def。                         |
+| TABLE_SCHEMA                  | 表所属的数据库的名称。                                       |
+| TABLE_NAME                    | 具有约束的表的名称。                                         |
+| COLUMN_NAME                   | 具有约束的列的名称。如果约束是外键，则这是外键的列，而不是外键引用的列。 |
+| ORDINAL_POSITION              | 列在约束内的位置，而不是列在表内的位置。列位置从 1 开始编号。 |
+| POSITION_IN_UNIQUE_CONSTRAINT | 对于唯一和主键约束，为 NULL。对于外键约束，此列是被引用的表中 key 的序数位置。 |
+| REFERENCED_TABLE_SCHEMA       | 约束引用的模式的名称。                                       |
+| REFERENCED_TABLE_NAME         | 约束引用的表的名称。                                         |
+| REFERENCED_COLUMN_NAME        | 约束引用的列的名称。                                         |
diff --git a/docs/zh/sql-reference/information_schema/load_tracking_logs.md b/docs/zh/sql-reference/information_schema/load_tracking_logs.md
new file mode 100644
index 00000000000000..ab2e12a70ab364
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/load_tracking_logs.md
@@ -0,0 +1,36 @@
+---
+displayed_sidebar: docs
+---
+
+# load_tracking_logs
+
+提供导入作业相关的错误信息。此视图自 StarRocks v3.0 起支持。
+
+`load_tracking_logs` 提供以下字段：
+
+| **字段**      | **描述**                         |
+| ------------- | ------------------------------- |
+| ID            | 导入ID。                  |
+| JOB_ID        | 导入作业的 ID（已废弃）。           |
+| LABEL         | 导入作业的 Label。               |
+| DATABASE_NAME | 导入作业所属的数据库名称。       |
+| TRACKING_LOG  | 导入作业的错误日志信息（如有）。 |
+
+:::tip
+查询 `load_tracking_logs` 视图时，您需要根据 `JOB_ID` 或 `LABEL` 进行过滤。
+
+您可以通过 `information_schema.loads` 视图查询已有的 `JOB_ID` 和 `LABEL` 。
+
+示例：
+
+```sql
+SELECT * from information_schema.load_tracking_logs WHERE label ='user_behavior'\G
+*************************** 1. row ***************************
+       JOB_ID: 10141
+        LABEL: user_behavior
+DATABASE_NAME: mydatabase
+ TRACKING_LOG: NULL
+         TYPE: BROKER
+1 row in set (0.02 sec)
+```
+:::
diff --git a/docs/zh/sql-reference/information_schema/loads.md b/docs/zh/sql-reference/information_schema/loads.md
new file mode 100644
index 00000000000000..3afdc2f0d11120
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/loads.md
@@ -0,0 +1,35 @@
+---
+displayed_sidebar: docs
+---
+
+# loads
+
+提供导入作业的结果信息。此视图自 StarRocks v3.1 版本起支持。当前仅支持查看 [Broker Load](../../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 和 [INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md) 导入作业的结果信息。
+
+`loads` 提供以下字段：
+
+| **字段**             | **说明**                                                     |
+| -------------------- | ------------------------------------------------------------ |
+| JOB_ID               | 导入作业的 ID，由 StarRocks 自动生成。                       |
+| LABEL                | 导入作业的标签。                                             |
+| DATABASE_NAME        | 目标 StarRocks 表所在的数据库的名称。                        |
+| STATE                | 导入作业的状态，包括：<ul><li>`PENDING`：导入作业已创建。</li><li>`QUEUEING`：导入作业正在等待执行中。</li><li>`LOADING`：导入作业正在执行中。</li><li>`PREPARED`：事务已提交。</li><li>`FINISHED`：导入作业成功。</li><li>`CANCELLED`：导入作业失败。</li></ul>请参见[异步导入](../../loading/loading_introduction/loading_concepts.md#异步导入)。 |
+| PROGRESS             | 导入作业 ETL 阶段和 LOADING 阶段的进度。                     |
+| TYPE                 | 导入作业的类型。如果是 Broker Load 导入，则返回 `BROKER`。如果是 INSERT 导入，则返回 `INSERT`。 |
+| PRIORITY             | 导入作业的优先级。取值范围：`HIGHEST`、`HIGH`、`NORMAL`、`LOW`、`LOWEST`。 |
+| SCAN_ROWS            | 扫描的数据行总数。                                           |
+| FILTERED_ROWS        | 因数据质量不合格而过滤掉的错误数据行总数。                   |
+| UNSELECTED_ROWS      | 根据 WHERE 子句中指定的条件过滤掉的数据行总数。              |
+| SINK_ROWS            | 完成导入的数据行总数。                                       |
+| ETL_INFO             | ETL 详情。该字段只对 Spark Load 作业有效。如果是其他类型的导入作业，则返回结果为空。 |
+| TASK_INFO            | 导入作业的详情，比如导入作业的超时时长 (`timeout`) 和最大容忍率 (`max_filter_ratio`) 等。 |
+| CREATE_TIME          | 导入作业的创建时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
+| ETL_START_TIME       | ETL 阶段的开始时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
+| ETL_FINISH_TIME      | ETL 阶段的结束时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
+| LOAD_START_TIME      | LOADING 阶段的开始时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
+| LOAD_FINISH_TIME     | LOADING 阶段的结束时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
+| JOB_DETAILS          | 导入数据的详情，包括导入的数据大小（按字节数计）、文件个数等。 |
+| ERROR_MSG            | 导入作业的错误信息。如果没有错误，则返回 `NULL`。            |
+| TRACKING_URL         | 导入作业中质量不合格数据采样的访问地址。可以使用 `curl` 命令或 `wget` 命令访问该地址。如果导入作业中不存在质量不合格的数据，则返回 `NULL`。 |
+| TRACKING_SQL         | 导入作业跟踪日志的查询语句。仅在导入作业包含不合格数据时才会返回查询语句。如果导入作业未包含不合格数据，则返回 `NULL`。 |
+| REJECTED_RECORD_PATH | 导入作业中质量不合格数据的访问地址。返回的不合格数据结果条数，由导入作业中 `log_rejected_record_num` 参数的设置决定。您可以使用 `wget` 命令访问该地址。如果导入作业中不存在质量不合格的数据，则返回 `NULL`。 |
diff --git a/docs/zh/sql-reference/information_schema/materialized_views.md b/docs/zh/sql-reference/information_schema/materialized_views.md
new file mode 100644
index 00000000000000..d5c319d4fb9b12
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/materialized_views.md
@@ -0,0 +1,34 @@
+---
+displayed_sidebar: docs
+---
+
+# materialized_views
+
+`materialized_views` 提供有关所有物化视图的信息。
+
+`materialized_views` 提供以下字段：
+
+| **字段**                             | **描述**                                         |
+| ------------------------------------ | ------------------------------------------------ |
+| MATERIALIZED_VIEW_ID                 | 物化视图 ID。                                    |
+| TABLE_SCHEMA                         | 物化视图所在的数据库名称。                       |
+| TABLE_NAME                           | 物化视图名称。                                   |
+| REFRESH_TYPE                         | 物化视图（刷新）类型，包括 `ROLLUP`（同步物化视图）、`ASYNC`（异步刷新物化视图）以及 `MANUAL`（手动刷新物化视图）。当此值为 `ROLLUP` 时，以下生效状态和刷新相关的字段为空。 |
+| IS_ACTIVE                            | 是否生效，失效的物化视图不会被刷新和查询改写。   |
+| INACTIVE_REASON                      | 失效的原因。                                     |
+| PARTITION_TYPE                       | 物化视图分区类型。                               |
+| TASK_ID                              | 物化视图刷新任务的 ID。                          |
+| TASK_NAME                            | 物化视图刷新任务的名称。                         |
+| LAST_REFRESH_START_TIME              | 最近一次刷新任务的开始时间。                     |
+| LAST_REFRESH_FINISHED_TIME           | 最近一次刷新任务的结束时间。                     |
+| LAST_REFRESH_DURATION                | 最近一次刷新任务的持续时间。                     |
+| LAST_REFRESH_STATE                   | 最近一次刷新任务的状态。                         |
+| LAST_REFRESH_FORCE_REFRESH           | 最近一次刷新任务是否强制刷新。                   |
+| LAST_REFRESH_START_PARTITION         | 最近一次刷新任务的开始分区。                     |
+| LAST_REFRESH_END_PARTITION           | 最近一次刷新任务的结束分区。                     |
+| LAST_REFRESH_BASE_REFRESH_PARTITIONS | 最近一次刷新任务的基表分区。                     |
+| LAST_REFRESH_MV_REFRESH_PARTITIONS   | 最近一次刷新任务刷新的分区。                   |
+| LAST_REFRESH_ERROR_CODE              | 最近一次刷新任务的错误码。                       |
+| LAST_REFRESH_ERROR_MESSAGE           | 最近一次刷新任务的错误信息。                     |
+| TABLE_ROWS                           | 物化视图的数据行数，后台统计的近似值。           |
+| MATERIALIZED_VIEW_DEFINITION         | 物化视图的 SQL 定义。                            |
diff --git a/docs/zh/sql-reference/information_schema/partitions.md b/docs/zh/sql-reference/information_schema/partitions.md
new file mode 100644
index 00000000000000..1820d6dd75435c
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/partitions.md
@@ -0,0 +1,42 @@
+---
+displayed_sidebar: docs
+---
+
+# partitions
+
+:::note
+
+该视图不适用于 StarRocks 当前支持的功能。
+
+:::
+
+`partitions` 提供有关表分区的信息。
+
+`partitions` 提供以下字段：
+
+| 字段                       | 描述                                                         |
+| -------------------------- | ------------------------------------------------------------ |
+| TABLE_CATALOG              | 表所属的目录的名称。该值始终为 def。                         |
+| TABLE_SCHEMA               | 表所属的数据库的名称。                                       |
+| TABLE_NAME                 | 包含分区的表的名称。                                         |
+| PARTITION_NAME             | 分区的名称。                                                 |
+| SUBPARTITION_NAME          | 如果 PARTITIONS 表行表示子分区，则为子分区的名称；否则为 NULL。对于 NDB：该值始终为 NULL。 |
+| PARTITION_ORDINAL_POSITION | 所有分区按照定义的顺序进行索引，其中 1 是分配给第一个分区的数字。随着添加、删除和重新组织分区，索引可能会发生变化；此列中显示的数字反映了当前的顺序，考虑到任何索引更改。 |
+| PARTITION_METHOD           | 有效值：RANGE、LIST、HASH、LINEAR HASH、KEY 或 LINEAR KEY。  |
+| SUBPARTITION_METHOD        | 有效值：HASH、LINEAR HASH、KEY 或 LINEAR KEY。               |
+| PARTITION_EXPRESSION       | 用于 CREATE TABLE 或 ALTER TABLE 语句中创建表的当前分区方案的分区函数的表达式。 |
+| SUBPARTITION_EXPRESSION    | 对于子分区表达式，其功能与 PARTITION_EXPRESSION 对于定义表分区的分区表达式相同。如果表没有子分区，则此列为 NULL。 |
+| PARTITION_DESCRIPTION      | 此列用于 RANGE 和 LIST 分区。对于 RANGE 分区，它包含在分区的 VALUES LESS THAN 子句中设置的值，可以是整数或 MAXVALUE。对于 LIST 分区，此列包含在分区的 VALUES IN 子句中定义的值，这是一个逗号分隔的整数值列表。对于 PARTITION_METHOD 不是 RANGE 或 LIST 的分区，此列始终为 NULL。 |
+| TABLE_ROWS                 | 分区中的表行数。                                             |
+| AVG_ROW_LENGTH             | 存储在此分区或子分区中的行的平均长度，以字节为单位。这与 DATA_LENGTH 除以 TABLE_ROWS 相同。 |
+| DATA_LENGTH                | 存储在此分区或子分区中的所有行的总长度，以字节为单位；即存储在分区或子分区中的字节总数。 |
+| MAX_DATA_LENGTH            | 可以存储在此分区或子分区中的最大字节数。                     |
+| INDEX_LENGTH               | 此分区或子分区的索引文件长度，以字节为单位。                 |
+| DATA_FREE                  | 为分区或子分区分配但未使用的字节数。                         |
+| CREATE_TIME                | 创建分区或子分区的时间。                                     |
+| UPDATE_TIME                | 上次修改分区或子分区的时间。                                 |
+| CHECK_TIME                 | 检查属于此分区或子分区的表的最后一次时间。                   |
+| CHECKSUM                   | 校验和值，如果有的话；否则为 NULL。                          |
+| PARTITION_COMMENT          | 分区的注释文本，如果有的话。如果没有，则此值为空。           |
+| NODEGROUP                  | 分区所属的节点组。                                           |
+| TABLESPACE_NAME            | 分区所属的表空间的名称。                                     |
diff --git a/docs/zh/sql-reference/information_schema/pipe_files.md b/docs/zh/sql-reference/information_schema/pipe_files.md
new file mode 100644
index 00000000000000..ff7bff856d8203
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/pipe_files.md
@@ -0,0 +1,24 @@
+---
+displayed_sidebar: docs
+---
+
+# pipe_files
+
+`pipe_files` 提供指定 Pipe 下数据文件的导入状态。此视图自 StarRocks v3.2 版本起支持。
+
+`pipe_files` 提供以下字段：
+
+| **字段**         | **描述**                                                     |
+| ---------------- | ------------------------------------------------------------ |
+| DATABASE_NAME    | Pipe 所属数据库的名称。                                      |
+| PIPE_ID          | Pipe 的唯一 ID。                                             |
+| PIPE_NAME        | Pipe 的名称。                                                |
+| FILE_NAME        | 数据文件的名称。                                             |
+| FILE_VERSION     | 数据文件的内容摘要值。                                       |
+| FILE_SIZE        | 数据文件的大小。单位：字节。                                 |
+| LAST_MODIFIED    | 数据文件的最后修改时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
+| LOAD_STATE       | 数据文件的导入状态，包括 `UNLOADED`、`LOADING`、`FINISHED`、`ERROR`。 |
+| STAGED_TIME      | 数据文件被 Pipe 首次记录的时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
+| START_LOAD_TIME  | 数据文件导入开始的时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
+| FINISH_LOAD_TIME | 数据文件导入结束的时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
+| ERROR_MSG        | 数据文件的导入错误信息。                                     |
diff --git a/docs/zh/sql-reference/information_schema/pipes.md b/docs/zh/sql-reference/information_schema/pipes.md
new file mode 100644
index 00000000000000..5089e5db84b3e7
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/pipes.md
@@ -0,0 +1,26 @@
+---
+displayed_sidebar: docs
+---
+
+# pipes
+
+`pipes` 提供当前数据库或指定数据库下所有 Pipe 的详细信息。此视图自 StarRocks v3.2 版本起支持。
+
+:::note
+
+您可以通过 [SHOW PIPES](../../sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md) 命令查看当前数据库或指定数据库下 Pipe。该命令也是从 3.2 版本开始支持。
+
+:::
+
+`pipes` 提供以下字段：
+
+| **字段**      | **描述**                                                     |
+| ------------- | ------------------------------------------------------------ |
+| DATABASE_NAME | Pipe 所属数据库的名称。                                      |
+| PIPE_ID       | Pipe 的唯一 ID。                                             |
+| PIPE_NAME     | Pipe 的名称。                                                |
+| TABLE_NAME    | StarRocks 目标表的名称。格式：`<database_name>.<table_name>`。 |
+| STATE         | Pipe 的状态，包括 `RUNNING`、`FINISHED`、`SUSPENDED`、`ERROR`。 |
+| LOAD_STATUS   | Pipe 下待导入数据文件的整体状态，包括如下字段：<br />`loadedFiles`：已导入的数据文件总个数。<br />`loadedBytes`：已导入的数据总量，单位为字节。<br />`loadingFiles`：正在导入的数据文件总个数。 |
+| LAST_ERROR    | Pipe 执行过程中最近一次错误的详细信息。默认值为 `NULL`。     |
+| CREATED_TIME  | Pipe 的创建时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。 |
diff --git a/docs/zh/sql-reference/information_schema/referential_constraints.md b/docs/zh/sql-reference/information_schema/referential_constraints.md
new file mode 100644
index 00000000000000..a0ec918c475ea2
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+++ b/docs/zh/sql-reference/information_schema/referential_constraints.md
@@ -0,0 +1,29 @@
+---
+displayed_sidebar: docs
+---
+
+# referential_constraints
+
+:::note
+
+该视图不适用于 StarRocks 当前支持的功能。
+
+:::
+
+`referential_constraints` 包含所有参照（外键）约束。
+
+`referential_constraints` 提供以下字段：
+
+| 字段                      | 描述                                                         |
+| ------------------------- | ------------------------------------------------------------ |
+| CONSTRAINT_CATALOG        | 约束所属的目录的名称。该值始终为 def。                       |
+| CONSTRAINT_SCHEMA         | 约束所属的数据库的名称。                                     |
+| CONSTRAINT_NAME           | 约束的名称。                                                 |
+| UNIQUE_CONSTRAINT_CATALOG | 包含约束引用的唯一约束的目录的名称。该值始终为 def。         |
+| UNIQUE_CONSTRAINT_SCHEMA  | 包含约束引用的唯一约束的模式的名称。                         |
+| UNIQUE_CONSTRAINT_NAME    | 约束引用的唯一约束的名称。                                   |
+| MATCH_OPTION              | 约束 MATCH 属性的值。目前唯一有效的值是 NONE。               |
+| UPDATE_RULE               | 约束 ON UPDATE 属性的值。有效值：CASCADE、SET NULL、SET DEFAULT、RESTRICT 和 NO ACTION。 |
+| DELETE_RULE               | 约束 ON DELETE 属性的值。有效值：CASCADE、SET NULL、SET DEFAULT、RESTRICT 和 NO ACTION。 |
+| TABLE_NAME                | 表的名称。此值与 TABLE_CONSTRAINTS 表中的相同。              |
+| REFERENCED_TABLE_NAME     | 约束引用的表的名称。                                         |
diff --git a/docs/zh/sql-reference/information_schema/routines.md b/docs/zh/sql-reference/information_schema/routines.md
new file mode 100644
index 00000000000000..51ade0cfd3a5e5
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/routines.md
@@ -0,0 +1,42 @@
+---
+displayed_sidebar: docs
+---
+
+# routines
+
+:::note
+
+该视图不适用于 StarRocks 当前支持的功能。
+
+:::
+
+`routines` 包含所有存储的过程（Routine），包括流程和函数。
+
+`routine` 提供以下字段：
+
+| 字段                 | 描述                                                         |
+| -------------------- | ------------------------------------------------------------ |
+| SPECIFIC_NAME        | 过程的名称。                                                 |
+| ROUTINE_CATALOG      | 过程所属的目录的名称。该值始终为 def。                       |
+| ROUTINE_SCHEMA       | 过程所属的数据库的名称。                                     |
+| ROUTINE_NAME         | 过程的名称。                                                 |
+| ROUTINE_TYPE         | 存储过程的类型为 PROCEDURE，存储函数的类型为 FUNCTION。      |
+| DTD_IDENTIFIER       | 如果过程是存储函数，则为返回值的数据类型。如果过程是存储过程，则此值为空。 |
+| ROUTINE_BODY         | 用于过程定义的语言。此值始终为 SQL。                         |
+| ROUTINE_DEFINITION   | 过程执行的 SQL 语句的文本。                                  |
+| EXTERNAL_NAME        | 此值始终为 NULL。                                            |
+| EXTERNAL_LANGUAGE    | 存储过程的语言。                                             |
+| PARAMETER_STYLE      | 此值始终为 SQL。                                             |
+| IS_DETERMINISTIC     | 取决于是否使用 DETERMINISTIC 特性定义了过程。可以是 YES 或 NO。 |
+| SQL_DATA_ACCESS      | 过程的数据访问特性。该值是 CONTAINS SQL、NO SQL、READS SQL DATA 或 MODIFIES SQL DATA 中的一个。 |
+| SQL_PATH             | 此值始终为 NULL。                                            |
+| SECURITY_TYPE        | 过程的 SQL SECURITY 特性。该值是 DEFINER 或 INVOKER 中的一个。 |
+| CREATED              | 过程创建的日期和时间。这是一个 DATETIME 值。                 |
+| LAST_ALTERED         | 过程上次修改的日期和时间。这是一个 DATETIME 值。如果自创建以来过程未被修改，则此值与 CREATED 值相同。 |
+| SQL_MODE             | 过程创建或修改时生效的 SQL 模式，并在其中运行过程。          |
+| ROUTINE_COMMENT      | 过程的注释文本，如果有的话。如果没有，则此值为空。           |
+| DEFINER              | 在 DEFINER 子句中指定的用户（通常是创建过程的用户）。        |
+| CHARACTER_SET_CLIENT |                                                              |
+| COLLATION_CONNECTION |                                                              |
+| DATABASE_COLLATION   | 过程关联的数据库的排序规则。                                 |
+
diff --git a/docs/zh/sql-reference/information_schema/schema_privileges.md b/docs/zh/sql-reference/information_schema/schema_privileges.md
new file mode 100644
index 00000000000000..472b4313cc0f01
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/schema_privileges.md
@@ -0,0 +1,23 @@
+---
+displayed_sidebar: docs
+---
+
+# schema_privileges
+
+:::note
+
+该视图不适用于 StarRocks 当前支持的功能。
+
+:::
+
+`schema_privileges` 提供有关数据库权限的信息。
+
+`schema_privileges` 提供以下字段：
+
+| 字段           | 描述                                                         |
+| -------------- | ------------------------------------------------------------ |
+| GRANTEE        | 授予权限的用户的名称。                                       |
+| TABLE_CATALOG  | 模式所属的目录的名称。该值始终为 def。                       |
+| TABLE_SCHEMA   | 模式的名称。                                                 |
+| PRIVILEGE_TYPE | 所授予的权限。每一行列出一个权限，因此每个由授予权限的用户拥有的模式权限都有一行。 |
+| IS_GRANTABLE   | 如果用户具有 GRANT OPTION 权限，则为 YES；否则为 NO。输出不会将 GRANT OPTION 作为单独的行列出，而是使用 PRIVILEGE_TYPE='GRANT OPTION'。 |
diff --git a/docs/zh/sql-reference/information_schema/schemata.md b/docs/zh/sql-reference/information_schema/schemata.md
new file mode 100644
index 00000000000000..50429a57c8c261
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/schemata.md
@@ -0,0 +1,17 @@
+---
+displayed_sidebar: docs
+---
+
+# schemata
+
+`schemata` 提供有关数据库的信息。
+
+`schemata` 提供以下字段：
+
+| 字段                       | 描述                                    |
+| -------------------------- | --------------------------------------- |
+| CATALOG_NAME               | 模式所属的目录的名称。该值始终为 NULL。 |
+| SCHEMA_NAME                | 模式的名称。                            |
+| DEFAULT_CHARACTER_SET_NAME | 模式的默认字符集。                      |
+| DEFAULT_COLLATION_NAME     | 模式的默认排序规则。                    |
+| SQL_PATH                   | 此值始终为 NULL。                       |
diff --git a/docs/zh/sql-reference/information_schema/session_variables.md b/docs/zh/sql-reference/information_schema/session_variables.md
new file mode 100644
index 00000000000000..ada3095219e724
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/session_variables.md
@@ -0,0 +1,14 @@
+---
+displayed_sidebar: docs
+---
+
+# session_variables
+
+`session_variables` 提供有关 Session 变量的信息。
+
+`session_variables` 提供以下字段：
+
+| **字段**       | **描述**             |
+| -------------- | -------------------- |
+| VARIABLE_NAME  | Session 变量的名称。 |
+| VARIABLE_VALUE | Session 变量的值。   |
diff --git a/docs/zh/sql-reference/information_schema/statistics.md b/docs/zh/sql-reference/information_schema/statistics.md
new file mode 100644
index 00000000000000..e4052adb80d0f1
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/statistics.md
@@ -0,0 +1,34 @@
+---
+displayed_sidebar: docs
+---
+
+# statistics
+
+:::note
+
+该视图不适用于 StarRocks 当前支持的功能。
+
+:::
+
+`statistics` 提供有关表索引的信息。
+
+`statistics` 提供以下字段：
+
+| 字段          | 描述                                                         |
+| ------------- | ------------------------------------------------------------ |
+| TABLE_CATALOG | 包含索引的表所属的目录的名称。该值始终为 def。               |
+| TABLE_SCHEMA  | 包含索引的表所属的数据库的名称。                             |
+| TABLE_NAME    | 包含索引的表的名称。                                         |
+| NON_UNIQUE    | 如果索引不能包含重复值，则为 0；如果可以，则为 1。           |
+| INDEX_SCHEMA  | 索引所属的数据库的名称。                                     |
+| INDEX_NAME    | 索引的名称。如果索引是主键，则名称始终为 PRIMARY。           |
+| SEQ_IN_INDEX  | 索引中的列序号，从 1 开始。                                  |
+| COLUMN_NAME   | 列名。有关 EXPRESSION 列的描述，请参见下文。                 |
+| COLLATION     | 列在索引中的排序方式。可以有值 A（升序）、D（降序）或 NULL（未排序）。 |
+| CARDINALITY   | 索引中唯一值的估计数量。                                     |
+| SUB_PART      | 索引前缀。即，如果只对列的一部分进行索引，则为索引的字符数，如果整个列都被索引，则为 NULL。 |
+| PACKED        | 指示键如何被打包。如果没有打包，则为 NULL。                  |
+| NULLABLE      | 如果列可能包含 NULL 值，则为 YES，如果不可能，则为''。       |
+| INDEX_TYPE    | 使用的索引方法（BTREE、FULLTEXT、HASH、RTREE）。             |
+| COMMENT       | 有关索引的信息，未在其自己的列中描述，例如，如果索引已禁用，则为 disabled。 |
+| INDEX_COMMENT | 在创建索引时使用 COMMENT 属性为索引提供的任何注释。          |
diff --git a/docs/zh/sql-reference/information_schema/table_constraints.md b/docs/zh/sql-reference/information_schema/table_constraints.md
new file mode 100644
index 00000000000000..7544b785bcef68
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/table_constraints.md
@@ -0,0 +1,24 @@
+---
+displayed_sidebar: docs
+---
+
+# table_constraints
+
+:::note
+
+该视图不适用于 StarRocks 当前支持的功能。
+
+:::
+
+`table_constraints` 描述具有约束的表。
+
+`table_constraints` 提供以下字段：
+
+| 字段               | 描述                                   |
+| ------------------ | -------------------------------------- |
+| CONSTRAINT_CATALOG | 约束所属的目录的名称。该值始终为 def。 |
+| CONSTRAINT_SCHEMA  | 约束所属的数据库的名称。               |
+| CONSTRAINT_NAME    | 约束的名称。                           |
+| TABLE_SCHEMA       | 表所属的数据库的名称。                 |
+| TABLE_NAME         | 表的名称。                             |
+| CONSTRAINT_TYPE    | 约束的类型。                           |
diff --git a/docs/zh/sql-reference/information_schema/table_privileges.md b/docs/zh/sql-reference/information_schema/table_privileges.md
new file mode 100644
index 00000000000000..99250702a92040
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/table_privileges.md
@@ -0,0 +1,25 @@
+---
+displayed_sidebar: docs
+---
+
+# table_privileges
+
+:::note
+
+该视图不适用于 StarRocks 当前支持的功能。
+
+:::
+
+`table_privileges` 提供有关表权限的信息。
+
+`table_privileges` 提供以下字段：
+
+| 字段           | 描述                                                         |
+| -------------- | ------------------------------------------------------------ |
+| GRANTEE        | 授予权限的用户的名称。                                       |
+| TABLE_CATALOG  | 表所属的目录的名称。该值始终为 def。                         |
+| TABLE_SCHEMA   | 表所属的数据库的名称。                                       |
+| TABLE_NAME     | 表的名称。                                                   |
+| PRIVILEGE_TYPE | 所授予的权限。该值可以是可在表级别授予的任何权限。           |
+| IS_GRANTABLE   | 如果用户具有 GRANT OPTION 权限，则为 YES；否则为 NO。输出不会将 GRANT OPTION 作为单独的行列出，而是使用 PRIVILEGE_TYPE='GRANT OPTION'。 |
+
diff --git a/docs/zh/sql-reference/information_schema/tables.md b/docs/zh/sql-reference/information_schema/tables.md
new file mode 100644
index 00000000000000..755bb3094f3ab7
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/tables.md
@@ -0,0 +1,33 @@
+---
+displayed_sidebar: docs
+---
+
+# tables
+
+`tables` 提供有关表的信息。
+
+`tables` 提供以下字段：
+
+| **字段**        | **描述**                                                     |
+| --------------- | ------------------------------------------------------------ |
+| TABLE_CATALOG   | 表所属的 Catalog 名称。                                      |
+| TABLE_SCHEMA    | 表所属的数据库名称。                                         |
+| TABLE_NAME      | 表名。                                                       |
+| TABLE_TYPE      | 表的类型。有效值：`BASE TABLE` 和 `VIEW`。                  |
+| ENGINE          | 表的引擎类型。有效值：`StarRocks`、`MySQL`、`MEMORY` 和空字符串。 |
+| VERSION         | 该字段暂不可用。                                             |
+| ROW_FORMAT      | 该字段暂不可用。                                             |
+| TABLE_ROWS      | 表的行数。                                                   |
+| AVG_ROW_LENGTH  | 表的平均行长度（大小），等于 `DATA_LENGTH`/`TABLE_ROWS`。单位：Byte。 |
+| DATA_LENGTH     | 数据长度（大小）。单位：Byte。                              |
+| MAX_DATA_LENGTH | 该字段暂不可用。                                             |
+| INDEX_LENGTH    | 该字段暂不可用。                                             |
+| DATA_FREE       | 该字段暂不可用。                                             |
+| AUTO_INCREMENT  | 该字段暂不可用。                                             |
+| CREATE_TIME     | 创建表的时间。                                               |
+| UPDATE_TIME     | 最后一次更新表的时间。                                       |
+| CHECK_TIME      | 最后一次对表进行一致性检查的时间。                           |
+| TABLE_COLLATION | 表的默认 Collation。                                         |
+| CHECKSUM        | 该字段暂不可用。                                             |
+| CREATE_OPTIONS  | 该字段暂不可用。                                             |
+| TABLE_COMMENT   | 表的 Comment。                                               |
diff --git a/docs/zh/sql-reference/information_schema/tables_config.md b/docs/zh/sql-reference/information_schema/tables_config.md
new file mode 100644
index 00000000000000..6640fac6e5784c
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/tables_config.md
@@ -0,0 +1,24 @@
+---
+displayed_sidebar: docs
+---
+
+# tables_config
+
+`tables_config` 提供有关表配置的信息。
+
+`tables_config` 提供以下字段：
+
+| **字段**         | **描述**                                                     |
+| ---------------- | ------------------------------------------------------------ |
+| TABLE_SCHEMA     | 表所属的数据库名称。                                         |
+| TABLE_NAME       | 表名。                                                       |
+| TABLE_ENGINE     | 表的引擎类型。                                               |
+| TABLE_MODEL      | 表的类型。 有效值：`DUP_KEYS`、`AGG_KEYS`、`UNQ_KEYS` 和 `PRI_KEYS`。 |
+| PRIMARY_KEY      | 主键表或更新表的唯一约束键。如果该表不是主键表或更新表，则返回空字符串。 |
+| PARTITION_KEY    | 表的分区键。                                                 |
+| DISTRIBUTE_KEY   | 表的分桶键。                                                 |
+| DISTRIBUTE_TYPE  | 表的分桶方式。                                               |
+| DISTRUBTE_BUCKET | 表的分桶数。                                                 |
+| SORT_KEY         | 表的排序键。                                                 |
+| PROPERTIES       | 表的属性。                                                   |
+| TABLE_ID         | 表的 ID。                                                    |
diff --git a/docs/zh/sql-reference/information_schema/task_runs.md b/docs/zh/sql-reference/information_schema/task_runs.md
new file mode 100644
index 00000000000000..f054376f39e5c7
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/task_runs.md
@@ -0,0 +1,24 @@
+---
+displayed_sidebar: docs
+---
+
+# task_runs
+
+`task_runs` 提供有关异步任务执行的信息。
+
+`task_runs` 提供以下字段：
+
+| 字段          | 描述                                                         |
+| ------------- | ------------------------------------------------------------ |
+| QUERY_ID      | 查询的 ID。                                                  |
+| TASK_NAME     | 任务的名称。                                                 |
+| CREATE_TIME   | 任务创建的时间。                                             |
+| FINISH_TIME   | 任务完成的时间。                                             |
+| STATE         | 任务的状态，包括 `PENDING`（待处理）、`RUNNING`（运行中）、`FAILED`（失败）和 `SUCCESS`（成功）。从 v3.1.12 开始，新增了一个专门用于物化视图刷新任务的状态 `MERGED`。当提交新的刷新任务时，如果旧任务仍在 PENDING 队列中，这些任务将被合并，并保持其优先级属性。 |
+| DATABASE      | 任务所属的数据库。                                           |
+| DEFINITION    | 任务的 SQL 定义。                                            |
+| EXPIRE_TIME   | 任务过期的时间。                                             |
+| ERROR_CODE    | 任务的错误代码。                                             |
+| ERROR_MESSAGE | 任务的错误消息。                                             |
+| PROGRESS      | 任务的进度。                                                 |
+| EXTRA_MESSAGE | 任务的额外消息，例如在异步物化视图创建任务中的分区信息。     |
diff --git a/docs/zh/sql-reference/information_schema/tasks.md b/docs/zh/sql-reference/information_schema/tasks.md
new file mode 100644
index 00000000000000..76c6c3ec5094e9
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/tasks.md
@@ -0,0 +1,18 @@
+---
+displayed_sidebar: docs
+---
+
+# tasks
+
+`tasks` 提供有关异步任务的信息。
+
+`tasks` 提供以下字段：
+
+| **字段**    | **描述**                                                     |
+| ----------- | ------------------------------------------------------------ |
+| TASK_NAME   | 任务的名称。                                                 |
+| CREATE_TIME | 任务创建的时间。                                             |
+| SCHEDULE    | 任务调度。如果任务为周期运行，会显示 `START xxx EVERY xxx`。 |
+| DATABASE    | 任务所属的数据库。                                           |
+| DEFINITION  | 任务的 SQL 定义。                                            |
+| EXPIRE_TIME | 任务过期的时间。                                             |
diff --git a/docs/zh/sql-reference/information_schema/triggers.md b/docs/zh/sql-reference/information_schema/triggers.md
new file mode 100644
index 00000000000000..3ebba07308ea47
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/triggers.md
@@ -0,0 +1,40 @@
+---
+displayed_sidebar: docs
+---
+
+# triggers
+
+:::note
+
+该视图不适用于 StarRocks 当前支持的功能。
+
+:::
+
+`triggers` 提供有关触发器的信息。
+
+`triggers` 提供以下字段：
+
+| 字段                       | 描述                                                         |
+| -------------------------- | ------------------------------------------------------------ |
+| TRIGGER_CATALOG            | 触发器所属的目录的名称。该值始终为 def。                     |
+| TRIGGER_SCHEMA             | 触发器所属的数据库的名称。                                   |
+| TRIGGER_NAME               | 触发器的名称。                                               |
+| EVENT_MANIPULATION         | 触发器事件。这是触发器激活的相关表上的操作类型。该值可以是 INSERT（插入了一行）、DELETE（删除了一行）或 UPDATE（修改了一行）。 |
+| EVENT_OBJECT_CATALOG       | 每个触发器与确切的一张表关联。这张表所在的目录。             |
+| EVENT_OBJECT_SCHEMA        | 每个触发器与确切的一张表关联。这张表所在的数据库。           |
+| EVENT_OBJECT_TABLE         | 触发器关联的表的名称。                                       |
+| ACTION_ORDER               | 触发器动作在与相同 EVENT_MANIPULATION 和 ACTION_TIMING 值的同一张表上的触发器列表中的顺序位置。 |
+| ACTION_CONDITION           | 该值始终为 NULL。                                            |
+| ACTION_STATEMENT           | 触发器体；也就是触发器激活时执行的语句。此文本使用 UTF-8 编码。 |
+| ACTION_ORIENTATION         | 该值始终为 ROW。                                             |
+| ACTION_TIMING              | 触发器是在触发事件之前还是之后激活。该值为 BEFORE 或 AFTER。 |
+| ACTION_REFERENCE_OLD_TABLE | 该值始终为 NULL。                                            |
+| ACTION_REFERENCE_NEW_TABLE | 该值始终为 NULL。                                            |
+| ACTION_REFERENCE_OLD_ROW   | 旧列标识符。该值始终为 OLD。                                 |
+| ACTION_REFERENCE_NEW_ROW   | 新列标识符。该值始终为 NEW。                                 |
+| CREATED                    | 触发器创建的日期和时间。对于触发器，这是一个 DATETIME(2) 值（百分之一秒的小数部分）。 |
+| SQL_MODE                   | 触发器创建时有效的 SQL 模式，以及触发器执行的 SQL 模式。     |
+| DEFINER                    | 在 DEFINER 子句中命名的用户（通常是创建触发器的用户）。      |
+| CHARACTER_SET_CLIENT       |                                                              |
+| COLLATION_CONNECTION       |                                                              |
+| DATABASE_COLLATION         | 与触发器关联的数据库的排序规则。                             |
diff --git a/docs/zh/sql-reference/information_schema/user_privileges.md b/docs/zh/sql-reference/information_schema/user_privileges.md
new file mode 100644
index 00000000000000..d0bfa0d195415e
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/user_privileges.md
@@ -0,0 +1,22 @@
+---
+displayed_sidebar: docs
+---
+
+# user_privileges
+
+:::note
+
+该视图不适用于 StarRocks 当前支持的功能。
+
+:::
+
+`user_privileges` 提供有关用户权限的信息。
+
+`user_privileges` 提供以下字段：
+
+| 字段           | 描述                                                         |
+| -------------- | ------------------------------------------------------------ |
+| GRANTEE        | 被授予权限的用户的名称。                                     |
+| TABLE_CATALOG  | 目录的名称。该值始终为 def。                                 |
+| PRIVILEGE_TYPE | 授予的权限。该值可以是可在全局级别授予的任何权限。           |
+| IS_GRANTABLE   | 如果用户具有 GRANT OPTION 权限，则为 YES，否则为 NO。输出不会将 GRANT OPTION 作为 PRIVILEGE_TYPE='GRANT OPTION' 的单独行列出。 |
diff --git a/docs/zh/sql-reference/information_schema/views.md b/docs/zh/sql-reference/information_schema/views.md
new file mode 100644
index 00000000000000..a26d4370c0c32d
--- /dev/null
+++ b/docs/zh/sql-reference/information_schema/views.md
@@ -0,0 +1,22 @@
+---
+displayed_sidebar: docs
+---
+
+# views
+
+`views` 提供有关所有用户定义视图的信息。
+
+`views` 提供以下字段：
+
+| 字段                 | 描述                                                         |
+| -------------------- | ------------------------------------------------------------ |
+| TABLE_CATALOG        | 视图所属的目录名称。此值始终为 def。                         |
+| TABLE_SCHEMA         | 视图所属的数据库名称。                                       |
+| TABLE_NAME           | 视图的名称。                                                 |
+| VIEW_DEFINITION      | 提供视图定义的SELECT语句。                                   |
+| CHECK_OPTION         | CHECK_OPTION 属性的值。该值是 NONE、CASCADE 或 LOCAL 中的一个。 |
+| IS_UPDATABLE         | 视图是否可更新。如果对视图的 UPDATE 和 DELETE（以及类似的操作）是合法的，则设置标志为 YES（true）。否则，标志设置为 NO（false）。如果视图不可更新，诸如 UPDATE、DELETE 和 INSERT 等语句是非法的，会被拒绝。 |
+| DEFINER              | 创建视图的用户。                                             |
+| SECURITY_TYPE        | 视图的 SQL SECURITY 特性。该值是 DEFINER 或 INVOKER 中的一个。 |
+| CHARACTER_SET_CLIENT |                                                              |
+| COLLATION_CONNECTION |                                                              |
diff --git a/docs/zh/sql-reference/overview-pages/map-functions.mdx b/docs/zh/sql-reference/overview-pages/map-functions.mdx
deleted file mode 100644
index 5369a6db518b39..00000000000000
--- a/docs/zh/sql-reference/overview-pages/map-functions.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# 
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/sql-reference/sql-functions/JAVA_UDF.md b/docs/zh/sql-reference/sql-functions/JAVA_UDF.md
index 3430c34353bf1e..0afc8de6442129 100644
--- a/docs/zh/sql-reference/sql-functions/JAVA_UDF.md
+++ b/docs/zh/sql-reference/sql-functions/JAVA_UDF.md
@@ -1,5 +1,6 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
+sidebar_position: 0.9
 ---
 
 # Java UDF
@@ -527,7 +528,7 @@ SELECT t1.a,t1.b, MY_UDF_SPLIT FROM t1, MY_UDF_SPLIT(t1.c1);
 SHOW [GLOBAL] FUNCTIONS;
 ```
 
-更多信息，请参见[SHOW FUNCTIONS](../sql-statements/data-definition/SHOW_FUNCTIONS.md)。
+更多信息，请参见[SHOW FUNCTIONS](../sql-statements/Function/SHOW_FUNCTIONS.md)。
 
 ## 删除 UDF
 
@@ -537,7 +538,7 @@ SHOW [GLOBAL] FUNCTIONS;
 DROP [GLOBAL] FUNCTION <function_name>(arg_type [, ...]);
 ```
 
-更多信息，请参见[DROP FUNCTION](../sql-statements/data-definition/DROP_FUNCTION.md)。
+更多信息，请参见[DROP FUNCTION](../sql-statements/Function/DROP_FUNCTION.md)。
 
 ## 类型映射关系
 
diff --git a/docs/zh/sql-reference/sql-functions/Lambda_expression.md b/docs/zh/sql-reference/sql-functions/Lambda_expression.md
index 898aa3313d7f53..74c107c0824eb4 100644
--- a/docs/zh/sql-reference/sql-functions/Lambda_expression.md
+++ b/docs/zh/sql-reference/sql-functions/Lambda_expression.md
@@ -1,5 +1,6 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
+sidebar_position: 0.9
 ---
 
 # Lambda 表达式
diff --git a/docs/zh/sql-reference/sql-functions/Python_UDF.md b/docs/zh/sql-reference/sql-functions/Python_UDF.md
index 48a70fe1441ad0..60feb7e2f2b9ff 100644
--- a/docs/zh/sql-reference/sql-functions/Python_UDF.md
+++ b/docs/zh/sql-reference/sql-functions/Python_UDF.md
@@ -1,5 +1,6 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
+sidebar_position: 0.9
 ---
 
 # Python UDF
diff --git a/docs/zh/sql-reference/sql-functions/README.md b/docs/zh/sql-reference/sql-functions/README.md
new file mode 100644
index 00000000000000..a484dc9b0e2ffa
--- /dev/null
+++ b/docs/zh/sql-reference/sql-functions/README.md
@@ -0,0 +1,12 @@
+---
+displayed_sidebar: docs
+sidebar_position: 0.5
+---
+
+# 函数
+
+import DocCardList from '@theme/DocCardList';
+
+StarRocks 提供了丰富的函数，方便您在日常数据查询和分析时使用。除了常见的函数分类，StarRocks 也支持 ARRAY、JSON、MAP、STRUCT 等半结构化函数，支持 [Lambda 高阶函数](Lambda_expression.md)。如果以上函数都不符合您的需求，您还可以自行编写 [Java UDF](JAVA_UDF.md) 来满足业务需求。StarRocks 还提供 [Hive Bitmap UDF](hive_bitmap_udf.md) 功能，您可以在 Hive 里计算生成 Bitmap 后，再导入 StarRocks；将 StarRocks 里生成的 Bitmap，导出到 Hive，方便其它系统使用。
+
+<DocCardList />
diff --git a/docs/zh/sql-reference/sql-functions/Window_function.md b/docs/zh/sql-reference/sql-functions/Window_function.md
index 63851af69fe989..b0796e0068e5ef 100644
--- a/docs/zh/sql-reference/sql-functions/Window_function.md
+++ b/docs/zh/sql-reference/sql-functions/Window_function.md
@@ -1,6 +1,7 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['analytic']
+sidebar_position: 0.9
 ---
 
 # 使用窗口函数组织过滤数据
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/any_value.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/any_value.md
index 088769c09dbc9f..22c1606bf7516e 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/any_value.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/any_value.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # any_value
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/approx_count_distinct.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/approx_count_distinct.md
index 8068cfc47e08fe..0c70285f6a2fbf 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/approx_count_distinct.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/approx_count_distinct.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # approx_count_distinct
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/approx_top_k.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/approx_top_k.md
index 5de09a2bb24ab5..cebee17f843132 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/approx_top_k.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/approx_top_k.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # approx_top_k
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/avg.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/avg.md
index 78933f852ef679..4e00ba56583244 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/avg.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/avg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # avg
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/bitmap.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/bitmap.md
index 3d09a36fe05f4b..2bdc07d96ae98b 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/bitmap.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/corr.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/corr.md
index d68f026ae7a399..0941e4f7433fcb 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/corr.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/corr.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # corr
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/count.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/count.md
index fbfb0a8de269c6..d4983a5e7581d5 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/count.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/count.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/count_if.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/count_if.md
index 79c9052f6c9817..14ab261b7ca41c 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/count_if.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/count_if.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # count_if
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/covar_pop.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/covar_pop.md
index aef6f65983bcca..686aa02ba973c3 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/covar_pop.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/covar_pop.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # covar_pop
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/covar_samp.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/covar_samp.md
index d00af0e5b655e3..02df250ae22a74 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/covar_samp.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/covar_samp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # covar_samp
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/group_concat.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/group_concat.md
index fee71f7e7993ad..cc5fc8a599d8cd 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/group_concat.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/group_concat.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # group_concat
@@ -33,7 +33,7 @@ VARCHAR GROUP_CONCAT([DISTINCT] expr [,expr ...]
 
 返回值的数据类型为 VARCHAR。如果没有非 NULL 值，则返回 NULL。
 
-您可以使用系统变量 [group_concat_max_len](../../../reference/System_variable.md#group_concat_max_len) 来控制可以返回的最大字符长度。默认值：1024。最小值：4。单位：字符。
+您可以使用系统变量 [group_concat_max_len](../../System_variable.md#group_concat_max_len) 来控制可以返回的最大字符长度。默认值：1024。最小值：4。单位：字符。
 
 变量的设置方法：
 
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/grouping.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/grouping.md
index 0ebacd37194d23..ee619bb1c50675 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/grouping.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/grouping.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # grouping
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/grouping_id.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/grouping_id.md
index 9064d3f6c53d72..06a86df8e6c99d 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/grouping_id.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/grouping_id.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/hll_raw_agg.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/hll_raw_agg.md
index 70a27d5e97822d..3eae5ae6769933 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/hll_raw_agg.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/hll_raw_agg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # hll_raw_agg
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/hll_union.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/hll_union.md
index ecf9b520267200..3481382ac888e4 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/hll_union.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/hll_union.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/hll_union_agg.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/hll_union_agg.md
index f8221a44531b08..119f2b146d3ccd 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/hll_union_agg.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/hll_union_agg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # hll_union_agg
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/mann_whitney_u_test.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/mann_whitney_u_test.md
new file mode 100644
index 00000000000000..f5c682a5cdd892
--- /dev/null
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/mann_whitney_u_test.md
@@ -0,0 +1,129 @@
+---
+displayed_sidebar: "docs"
+---
+
+# mann_whitney_u_test
+
+## 功能
+
+对来自两个总体的样本执行Mann-Whitney检验。Mann-Whitney U检验是一种非参数检验，可以用来确定两个总体是否来自相同的分布。
+
+
+## 语法
+
+```Haskell
+MANN_WHITNEY_U_TEST (sample_data, sample_treatment[, alternative[, continuity_correction]])
+```
+
+## 参数说明
+
+- `sample_data`: 样本数据的值。必须为数值数据类型。
+
+- `sample_treatment`: 样本数据的索引。每个元素表示对应样本所属的处理组。值应为布尔类型，`false`表示第一组，`true`表示第二组。
+
+- `alternative` (可选): 一个常量String，指定备择假设的类型。可以是以下之一：
+
+- - 'two-sided': 默认值。检验两个总体的均值是否不同。
+
+- - 'less': 检验第一个总体的均值是否小于第二个总体的均值。
+
+- - 'greater': 检验第一个总体的均值是否大于第二个总体的均值。
+
+- `continuity_correction` (可选): 一个常量布尔值，表示是否应用连续性修正。连续性修正将U统计量向U分布的均值调整`0.5`，从而可以提高小样本大小时检验的准确性。默认值为`true`。
+
+## 返回值说明
+
+该函数返回一个包含以下两个元素的json数组：
+
+Mann-Whitney U统计量和与检验相关的p值。
+
+## 使用说明
+
+此函数忽略NULL值。
+
+## 示例
+
+假设有一个名为testing_data的表，其中包含以下数据。
+
+```sql
+create table testing_data (
+    id int, 
+    score int, 
+    treatment boolean
+)
+properties(
+    "replication_num" = "1"
+);
+
+insert into testing_data values 
+    (1, 80, false), 
+    (2, 100, false), 
+    (3, NULL, false), 
+    (4, 60, true), 
+    (5, 70, true), 
+    (6, 85, true);
+```
+
+
+```Plain
+select * from testing_data;
++------+-------+-----------+
+| id   | score | treatment |
++------+-------+-----------+
+|    1 |    80 |         0 |
+|    2 |   100 |         0 |
+|    3 |  NULL |         0 |
+|    4 |    60 |         1 |
+|    5 |    70 |         1 |
+|    6 |    85 |         1 |
++------+-------+-----------+
+```
+
+Query:
+
+```SQL
+SELECT MANN_WHITNEY_U_TEST(score, treatment) FROM testing_data;
+```
+
+Result:
+
+```Plain
++---------------------------------------+
+| mann_whitney_u_test(score, treatment) |
++---------------------------------------+
+| [5, 0.38647623077123283]              |
++---------------------------------------+
+```
+
+Query:
+
+```SQL
+SELECT MANN_WHITNEY_U_TEST(score, treatment, 'less') FROM testing_data;
+```
+
+Result:
+
+```Plain
++-----------------------------------------------+
+| mann_whitney_u_test(score, treatment, 'less') |
++-----------------------------------------------+
+| [5, 0.9255426634106172]                       |
++-----------------------------------------------+
+```
+
+
+Query:
+
+```SQL
+SELECT MANN_WHITNEY_U_TEST(score, treatment, 'two-sided', 0) FROM testing_data;
+```
+
+Result:
+
+```Plain
++-------------------------------------------------------+
+| mann_whitney_u_test(score, treatment, 'two-sided', 0) |
++-------------------------------------------------------+
+| [5, 0.2482130789899235]                               |
++-------------------------------------------------------+
+```
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/max.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/max.md
index 1dc9a96157aa24..8e55e77f2537a9 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/max.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/max.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # max
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/max_by.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/max_by.md
index 71177bc0556967..81e5ed117492ce 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/max_by.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/max_by.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # max_by
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/min.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/min.md
index 0ab1b1ea2c0e19..114f3cdaa3f8cc 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/min.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/min.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # min
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/min_by.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/min_by.md
index 3f4a33abc297f8..97e0de91107af6 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/min_by.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/min_by.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # min_by
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/multi_distinct_count.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/multi_distinct_count.md
index 773cb7cd34146a..0d19ddc973502a 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/multi_distinct_count.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/multi_distinct_count.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # multi_distinct_count
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/multi_distinct_sum.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/multi_distinct_sum.md
index 1fe29c3a71cd39..9dcdc5add2d800 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/multi_distinct_sum.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/multi_distinct_sum.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # multi_distinct_sum
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_approx.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_approx.md
index 8d78358110972e..4df9d83151ff7f 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_approx.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_approx.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # percentile_approx
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_cont.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_cont.md
index 6801a8a59fb195..edeccae43596d6 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_cont.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_cont.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # percentile_cont
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_disc.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_disc.md
index 00353f1bcf70b0..3e414729e4059a 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_disc.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_disc.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # percentile_disc
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_disc_lc.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_disc_lc.md
index 41821448385af8..ce698570847683 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_disc_lc.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/percentile_disc_lc.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # percentile_disc_lc
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/retention.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/retention.md
index f606396f5c9eb4..5ef116554ff411 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/retention.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/retention.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # retention
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/std.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/std.md
index b896421201738c..54df6bd637edc3 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/std.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/std.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # std
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/stddev.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/stddev.md
index 3c7cbca8164db9..5aafe146780b66 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/stddev.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/stddev.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/stddev_samp.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/stddev_samp.md
index dfd147cc8edc62..89fb7a8bdea9bb 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/stddev_samp.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/stddev_samp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # stddev_samp
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/sum.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/sum.md
index 6365072d8690b3..b35d6053a2ab48 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/sum.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/sum.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/var_samp.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/var_samp.md
index e163bcf0203fc1..7366ca853b08cb 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/var_samp.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/var_samp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/variance.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/variance.md
index e52193ab204b0a..3ef1d8821a0412 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/variance.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/variance.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # variance, var_pop, variance_pop
diff --git a/docs/zh/sql-reference/sql-functions/aggregate-functions/window_funnel.md b/docs/zh/sql-reference/sql-functions/aggregate-functions/window_funnel.md
index 7ef8ee1b3d8845..ae819ecd8a8983 100644
--- a/docs/zh/sql-reference/sql-functions/aggregate-functions/window_funnel.md
+++ b/docs/zh/sql-reference/sql-functions/aggregate-functions/window_funnel.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # window_funnel
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/all_match.md b/docs/zh/sql-reference/sql-functions/array-functions/all_match.md
index 147b1b9db825b7..fb961d09e32f16 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/all_match.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/all_match.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # all_match
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/any_match.md b/docs/zh/sql-reference/sql-functions/array-functions/any_match.md
index 0e8cff9fd4cd29..b4f33a8ca43727 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/any_match.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/any_match.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # any_match
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_agg.md b/docs/zh/sql-reference/sql-functions/array-functions/array_agg.md
index 17ff133eaaddc7..3a037223d395cf 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_agg.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_agg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_agg
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_append.md b/docs/zh/sql-reference/sql-functions/array-functions/array_append.md
index a7d6bcc7106e2a..b9459210e125e7 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_append.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_append.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_append
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_avg.md b/docs/zh/sql-reference/sql-functions/array-functions/array_avg.md
index e55ec6668fe0c1..6b3a3bcecb037d 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_avg.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_avg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_avg
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_concat.md b/docs/zh/sql-reference/sql-functions/array-functions/array_concat.md
index 04254b6caa6d6b..0df92c524a2bc8 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_concat.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_concat.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_concat
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_contains.md b/docs/zh/sql-reference/sql-functions/array-functions/array_contains.md
index 4a3e28d3a8d9f5..78ad90ab3c7499 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_contains.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_contains.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_contains
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_contains_all.md b/docs/zh/sql-reference/sql-functions/array-functions/array_contains_all.md
index e9f8a8f84da0e5..110a4e6fc97175 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_contains_all.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_contains_all.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_contains_all
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_contains_seq.md b/docs/zh/sql-reference/sql-functions/array-functions/array_contains_seq.md
index 0fcf875fa50bba..4c7813230de886 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_contains_seq.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_contains_seq.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_contains_seq
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_cum_sum.md b/docs/zh/sql-reference/sql-functions/array-functions/array_cum_sum.md
index ae8140218a1725..e35eb2e0c66db1 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_cum_sum.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_cum_sum.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_cum_sum
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_difference.md b/docs/zh/sql-reference/sql-functions/array-functions/array_difference.md
index f13c31c2f46c0d..e98e409e07ee93 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_difference.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_difference.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_difference
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_distinct.md b/docs/zh/sql-reference/sql-functions/array-functions/array_distinct.md
index 46a324ade1f68c..0240414896c39b 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_distinct.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_distinct.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_distinct
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_filter.md b/docs/zh/sql-reference/sql-functions/array-functions/array_filter.md
index 58a206683d02e1..e8da45d6b5d67e 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_filter.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_filter.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_filter
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_generate.md b/docs/zh/sql-reference/sql-functions/array-functions/array_generate.md
index 3482c9a2392317..a7ccb72792db1d 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_generate.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_generate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_generate
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_intersect.md b/docs/zh/sql-reference/sql-functions/array-functions/array_intersect.md
index 7dd170e5038d10..3f727543411339 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_intersect.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_intersect.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_intersect
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_join.md b/docs/zh/sql-reference/sql-functions/array-functions/array_join.md
index f48dae7781b530..6fac8b6b533863 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_join.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_join.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_join
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_length.md b/docs/zh/sql-reference/sql-functions/array-functions/array_length.md
index 8e9ea828f80982..fd2a579e9e2bdf 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_length.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_length.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_length
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_map.md b/docs/zh/sql-reference/sql-functions/array-functions/array_map.md
index 6c5647b1ffef62..727644ada77c8a 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_map.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_map.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_map
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_max.md b/docs/zh/sql-reference/sql-functions/array-functions/array_max.md
index fafdc2cc795a62..ca91d8e3232dfc 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_max.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_max.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_max
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_min.md b/docs/zh/sql-reference/sql-functions/array-functions/array_min.md
index 3e955a3ca4f600..7c0f516a1b98ce 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_min.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_min.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_min
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_position.md b/docs/zh/sql-reference/sql-functions/array-functions/array_position.md
index 170d2ab3fb5f31..b9f2564a2e22e9 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_position.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_position.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_position
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_remove.md b/docs/zh/sql-reference/sql-functions/array-functions/array_remove.md
index 71f75b71e54fbf..dfb8568a9ad842 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_remove.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_remove.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_remove
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_repeat.md b/docs/zh/sql-reference/sql-functions/array-functions/array_repeat.md
index 51d09d710b74b8..5d493d68d2f4ca 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_repeat.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_repeat.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_repeat
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_slice.md b/docs/zh/sql-reference/sql-functions/array-functions/array_slice.md
index 9fcf3cd823d488..6b9d1ce0f9da37 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_slice.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_slice.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_slice
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_sort.md b/docs/zh/sql-reference/sql-functions/array-functions/array_sort.md
index 5c181ab4401791..a0dace6fb8898e 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_sort.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_sort.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_sort
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_sortby.md b/docs/zh/sql-reference/sql-functions/array-functions/array_sortby.md
index e6b42482507860..01bfa1c805e9f0 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_sortby.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_sortby.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_sortby
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_sum.md b/docs/zh/sql-reference/sql-functions/array-functions/array_sum.md
index bcf938ea4d304e..f20d8f8a21f3ca 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_sum.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_sum.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_sum
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_to_bitmap.md b/docs/zh/sql-reference/sql-functions/array-functions/array_to_bitmap.md
index f532a3c2a74b4d..190e996803ec35 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_to_bitmap.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_to_bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_to_bitmap
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/array_unique_agg.md b/docs/zh/sql-reference/sql-functions/array-functions/array_unique_agg.md
index fa9aa7b6193b0a..ef339e1061f313 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/array_unique_agg.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/array_unique_agg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # array_unique_agg
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/arrays_overlap.md b/docs/zh/sql-reference/sql-functions/array-functions/arrays_overlap.md
index 90f6f3d26a765a..f258ad707ddffb 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/arrays_overlap.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/arrays_overlap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # arrays_overlap
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/cardinality.md b/docs/zh/sql-reference/sql-functions/array-functions/cardinality.md
index db27101b79e4c3..223ddce9ab3d27 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/cardinality.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/cardinality.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # cardinality
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/element_at.md b/docs/zh/sql-reference/sql-functions/array-functions/element_at.md
index ea55b2817780a9..57807f6eb0269d 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/element_at.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/element_at.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # element_at
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/reverse.md b/docs/zh/sql-reference/sql-functions/array-functions/reverse.md
index c54012d08275bb..bd168f5fc2681a 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/reverse.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/reverse.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # reverse
diff --git a/docs/zh/sql-reference/sql-functions/array-functions/unnest.md b/docs/zh/sql-reference/sql-functions/array-functions/unnest.md
index bfb73275350da9..9c3880c94abaa8 100644
--- a/docs/zh/sql-reference/sql-functions/array-functions/unnest.md
+++ b/docs/zh/sql-reference/sql-functions/array-functions/unnest.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # unnest
diff --git a/docs/zh/sql-reference/sql-functions/binary-functions/from_binary.md b/docs/zh/sql-reference/sql-functions/binary-functions/from_binary.md
index d83b7d46c6db90..f8ea0080d577af 100644
--- a/docs/zh/sql-reference/sql-functions/binary-functions/from_binary.md
+++ b/docs/zh/sql-reference/sql-functions/binary-functions/from_binary.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # from_binary
diff --git a/docs/zh/sql-reference/sql-functions/binary-functions/to_binary.md b/docs/zh/sql-reference/sql-functions/binary-functions/to_binary.md
index 5af235c488a74b..a59d9b0e7e5e3f 100644
--- a/docs/zh/sql-reference/sql-functions/binary-functions/to_binary.md
+++ b/docs/zh/sql-reference/sql-functions/binary-functions/to_binary.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # to_binary
diff --git a/docs/zh/sql-reference/sql-functions/bit-functions/bit_shift_left.md b/docs/zh/sql-reference/sql-functions/bit-functions/bit_shift_left.md
index 5e45714bc47594..4512f0a0db0915 100644
--- a/docs/zh/sql-reference/sql-functions/bit-functions/bit_shift_left.md
+++ b/docs/zh/sql-reference/sql-functions/bit-functions/bit_shift_left.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bit_shift_left
diff --git a/docs/zh/sql-reference/sql-functions/bit-functions/bit_shift_right.md b/docs/zh/sql-reference/sql-functions/bit-functions/bit_shift_right.md
index 023be6d793d017..5aaaa4e82f6e46 100644
--- a/docs/zh/sql-reference/sql-functions/bit-functions/bit_shift_right.md
+++ b/docs/zh/sql-reference/sql-functions/bit-functions/bit_shift_right.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bit_shift_right
diff --git a/docs/zh/sql-reference/sql-functions/bit-functions/bit_shift_right_logical.md b/docs/zh/sql-reference/sql-functions/bit-functions/bit_shift_right_logical.md
index a4fe1cadbf4948..d88cb765552b0d 100644
--- a/docs/zh/sql-reference/sql-functions/bit-functions/bit_shift_right_logical.md
+++ b/docs/zh/sql-reference/sql-functions/bit-functions/bit_shift_right_logical.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bit_shift_right_logical
diff --git a/docs/zh/sql-reference/sql-functions/bit-functions/bitand.md b/docs/zh/sql-reference/sql-functions/bit-functions/bitand.md
index f77a58de769982..7d26f31996996c 100644
--- a/docs/zh/sql-reference/sql-functions/bit-functions/bitand.md
+++ b/docs/zh/sql-reference/sql-functions/bit-functions/bitand.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitand
diff --git a/docs/zh/sql-reference/sql-functions/bit-functions/bitnot.md b/docs/zh/sql-reference/sql-functions/bit-functions/bitnot.md
index bbaef296ec60dc..02a29eb0c8d938 100644
--- a/docs/zh/sql-reference/sql-functions/bit-functions/bitnot.md
+++ b/docs/zh/sql-reference/sql-functions/bit-functions/bitnot.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitnot
diff --git a/docs/zh/sql-reference/sql-functions/bit-functions/bitor.md b/docs/zh/sql-reference/sql-functions/bit-functions/bitor.md
index 36139eb0c1a830..c7088558c6d68b 100644
--- a/docs/zh/sql-reference/sql-functions/bit-functions/bitor.md
+++ b/docs/zh/sql-reference/sql-functions/bit-functions/bitor.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitor
diff --git a/docs/zh/sql-reference/sql-functions/bit-functions/bitxor.md b/docs/zh/sql-reference/sql-functions/bit-functions/bitxor.md
index a6a7f498430713..2c5bf719d1d830 100644
--- a/docs/zh/sql-reference/sql-functions/bit-functions/bitxor.md
+++ b/docs/zh/sql-reference/sql-functions/bit-functions/bitxor.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitxor
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/base64_to_bitmap.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/base64_to_bitmap.md
index f574e5be5e8603..2412d5b025ad25 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/base64_to_bitmap.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/base64_to_bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # base64_to_bitmap
@@ -48,7 +48,7 @@ BITMAP base64_to_bitmap(VARCHAR bitmap)
     );
     ```
 
-2. 使用 [Stream Load](../../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md) 将 JSON 格式数据导入到 `bitmap_table` 中。
+2. 使用 [Stream Load](../../sql-statements/loading_unloading/STREAM_LOAD.md) 将 JSON 格式数据导入到 `bitmap_table` 中。
 
     假设有 JSON 格式文件**simpledata**, 内容如下，`userid`为 Base64 编码后的字符串:
 
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_agg.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_agg.md
index 8de3f50d268e00..c4e6a3f3db8fd0 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_agg.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_agg.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_agg
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_and.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_and.md
index fe37447e6e9adf..6de73f2d026ad5 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_and.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_and.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_and
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_andnot.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_andnot.md
index d2f7cc2234e68a..ffea17e1427064 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_andnot.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_andnot.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_andnot
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_contains.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_contains.md
index 892be2185838e3..4de5a58dbd86fe 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_contains.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_contains.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_contains
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_count.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_count.md
index 18bf2dba9077e0..af1498b837bf96 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_count.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_count.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_count
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_empty.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_empty.md
index a027fe225ee675..a1ec05c2a92269 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_empty.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_empty.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_empty
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_from_binary.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_from_binary.md
index 339176ec301e81..d540cdc6cfea1f 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_from_binary.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_from_binary.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_from_binary
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_from_string.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_from_string.md
index c7873c57d9bbda..dc8bfe6a491919 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_from_string.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_from_string.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_from_string
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_has_any.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_has_any.md
index 7f088e924ca421..bcf0beb15c0865 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_has_any.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_has_any.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_has_any
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_hash.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_hash.md
index e583b3b33b9ba9..ae5ac718951569 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_hash.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_hash.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_hash
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_intersect.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_intersect.md
index 082bb523c863e0..dcbc6830d8d082 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_intersect.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_intersect.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_intersect
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_max.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_max.md
index c1f68decee73be..bd78f168e0e6e5 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_max.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_max.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_max
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_min.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_min.md
index 934c85e9b5de91..f651d632f90a33 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_min.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_min.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_min
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_or.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_or.md
index adff27be9ee29c..2874958fc18721 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_or.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_or.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_or
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_remove.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_remove.md
index a207a35a157652..a77c49c8f08bb3 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_remove.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_remove.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_remove
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_subset_in_range.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_subset_in_range.md
index 5d955713604f94..21f43209f9fa6e 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_subset_in_range.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_subset_in_range.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_subset_in_range
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_subset_limit.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_subset_limit.md
index 83b550f52ae5b8..bff434c9513dac 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_subset_limit.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_subset_limit.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_subset_limit
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_array.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_array.md
index cd8215498fccfa..a978b99176721d 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_array.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_array.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_to_array
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_base64.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_base64.md
index 7803cde56d6026..0d1f99b0ddc3e5 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_base64.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_base64.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_to_base64
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_binary.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_binary.md
index 107b9813fcbdeb..4d2a0589f35399 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_binary.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_binary.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_to_binary
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_string.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_string.md
index 67064e77d6bf0e..08c0507ab84fd5 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_string.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_to_string.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_to_string
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_union.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_union.md
index 383318079a8ad4..28c86f011d6f6b 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_union.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_union.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_union
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_union_count.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_union_count.md
index 16f60997dd2097..ec15a3123183cf 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_union_count.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_union_count.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_union_count
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_union_int.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_union_int.md
index cfff0dec25dcd5..7cdb4c4b7a782a 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_union_int.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_union_int.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_union_int
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_xor.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_xor.md
index 60b12d7b383920..b6e52ce3399426 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_xor.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/bitmap_xor.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bitmap_xor
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/intersect_count.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/intersect_count.md
index 7f16afbeb0ed5d..659964230751c7 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/intersect_count.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/intersect_count.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # intersect_count
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/sub_bitmap.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/sub_bitmap.md
index 9ce53cc5ad4fa0..3f1113990e99a0 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/sub_bitmap.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/sub_bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # sub_bitmap
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/subdivide_bitmap.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/subdivide_bitmap.md
index df5ed39d08d23f..d9724c6e6db473 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/subdivide_bitmap.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/subdivide_bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # subdivide_bitmap
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/to_bitmap.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/to_bitmap.md
index 92465996debc79..d76af3d0cc4591 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/to_bitmap.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/to_bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # to_bitmap
diff --git a/docs/zh/sql-reference/sql-functions/bitmap-functions/unnest_bitmap.md b/docs/zh/sql-reference/sql-functions/bitmap-functions/unnest_bitmap.md
index 8db7ea49d786ef..16a47a45cbdb8d 100644
--- a/docs/zh/sql-reference/sql-functions/bitmap-functions/unnest_bitmap.md
+++ b/docs/zh/sql-reference/sql-functions/bitmap-functions/unnest_bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # unnest_bitmap
diff --git a/docs/zh/sql-reference/sql-functions/cast.md b/docs/zh/sql-reference/sql-functions/cast.md
index dd9b4cd633f099..15726935c40065 100644
--- a/docs/zh/sql-reference/sql-functions/cast.md
+++ b/docs/zh/sql-reference/sql-functions/cast.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # CAST
diff --git a/docs/zh/sql-reference/sql-functions/condition-functions/case_when.md b/docs/zh/sql-reference/sql-functions/condition-functions/case_when.md
index 2c491b49eeeaa1..eaf0d29eda81eb 100644
--- a/docs/zh/sql-reference/sql-functions/condition-functions/case_when.md
+++ b/docs/zh/sql-reference/sql-functions/condition-functions/case_when.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # case
diff --git a/docs/zh/sql-reference/sql-functions/condition-functions/coalesce.md b/docs/zh/sql-reference/sql-functions/condition-functions/coalesce.md
index a84d30035b29b2..0909116311d63e 100644
--- a/docs/zh/sql-reference/sql-functions/condition-functions/coalesce.md
+++ b/docs/zh/sql-reference/sql-functions/condition-functions/coalesce.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # coalesce
diff --git a/docs/zh/sql-reference/sql-functions/condition-functions/if.md b/docs/zh/sql-reference/sql-functions/condition-functions/if.md
index e4bc13d04edabf..9df81a7b6bc7ae 100644
--- a/docs/zh/sql-reference/sql-functions/condition-functions/if.md
+++ b/docs/zh/sql-reference/sql-functions/condition-functions/if.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # if
diff --git a/docs/zh/sql-reference/sql-functions/condition-functions/ifnull.md b/docs/zh/sql-reference/sql-functions/condition-functions/ifnull.md
index 43753bb49d0ce4..8cdaee6450e043 100644
--- a/docs/zh/sql-reference/sql-functions/condition-functions/ifnull.md
+++ b/docs/zh/sql-reference/sql-functions/condition-functions/ifnull.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ifnull
diff --git a/docs/zh/sql-reference/sql-functions/condition-functions/nullif.md b/docs/zh/sql-reference/sql-functions/condition-functions/nullif.md
index 43f2facad1cd42..ac6bbc26c32e73 100644
--- a/docs/zh/sql-reference/sql-functions/condition-functions/nullif.md
+++ b/docs/zh/sql-reference/sql-functions/condition-functions/nullif.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # nullif
diff --git a/docs/zh/sql-reference/sql-functions/crytographic-functions/aes_decrypt.md b/docs/zh/sql-reference/sql-functions/crytographic-functions/aes_decrypt.md
index b4109d2cbc3ec2..a9d58774355f51 100644
--- a/docs/zh/sql-reference/sql-functions/crytographic-functions/aes_decrypt.md
+++ b/docs/zh/sql-reference/sql-functions/crytographic-functions/aes_decrypt.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # aes_decrypt
diff --git a/docs/zh/sql-reference/sql-functions/crytographic-functions/aes_encrypt.md b/docs/zh/sql-reference/sql-functions/crytographic-functions/aes_encrypt.md
index f69ce02d503698..c5aeeabd40dbaf 100644
--- a/docs/zh/sql-reference/sql-functions/crytographic-functions/aes_encrypt.md
+++ b/docs/zh/sql-reference/sql-functions/crytographic-functions/aes_encrypt.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # aes_encrypt
diff --git a/docs/zh/sql-reference/sql-functions/crytographic-functions/base64_decode_binary.md b/docs/zh/sql-reference/sql-functions/crytographic-functions/base64_decode_binary.md
index 307cb90c815d49..b7530fa944d73f 100644
--- a/docs/zh/sql-reference/sql-functions/crytographic-functions/base64_decode_binary.md
+++ b/docs/zh/sql-reference/sql-functions/crytographic-functions/base64_decode_binary.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # base64_decode_binary
diff --git a/docs/zh/sql-reference/sql-functions/crytographic-functions/base64_decode_string.md b/docs/zh/sql-reference/sql-functions/crytographic-functions/base64_decode_string.md
index 90324e40df4a99..77dc05c4ed9d8b 100644
--- a/docs/zh/sql-reference/sql-functions/crytographic-functions/base64_decode_string.md
+++ b/docs/zh/sql-reference/sql-functions/crytographic-functions/base64_decode_string.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # base64_decode_string
diff --git a/docs/zh/sql-reference/sql-functions/crytographic-functions/from_base64.md b/docs/zh/sql-reference/sql-functions/crytographic-functions/from_base64.md
index 42a9235ddd95be..527202cce2656d 100644
--- a/docs/zh/sql-reference/sql-functions/crytographic-functions/from_base64.md
+++ b/docs/zh/sql-reference/sql-functions/crytographic-functions/from_base64.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # from_base64
diff --git a/docs/zh/sql-reference/sql-functions/crytographic-functions/md5.md b/docs/zh/sql-reference/sql-functions/crytographic-functions/md5.md
index afddd032113a1d..9020fdd402eb42 100644
--- a/docs/zh/sql-reference/sql-functions/crytographic-functions/md5.md
+++ b/docs/zh/sql-reference/sql-functions/crytographic-functions/md5.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # md5
diff --git a/docs/zh/sql-reference/sql-functions/crytographic-functions/md5sum.md b/docs/zh/sql-reference/sql-functions/crytographic-functions/md5sum.md
index 3c738dc261d6ec..ee5a6adcf3e4e2 100644
--- a/docs/zh/sql-reference/sql-functions/crytographic-functions/md5sum.md
+++ b/docs/zh/sql-reference/sql-functions/crytographic-functions/md5sum.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # md5sum
diff --git a/docs/zh/sql-reference/sql-functions/crytographic-functions/md5sum_numeric.md b/docs/zh/sql-reference/sql-functions/crytographic-functions/md5sum_numeric.md
index 171b2b7558655a..468f58c783bdec 100644
--- a/docs/zh/sql-reference/sql-functions/crytographic-functions/md5sum_numeric.md
+++ b/docs/zh/sql-reference/sql-functions/crytographic-functions/md5sum_numeric.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # md5sum_numeric
diff --git a/docs/zh/sql-reference/sql-functions/crytographic-functions/sha2.md b/docs/zh/sql-reference/sql-functions/crytographic-functions/sha2.md
index 42467634d07517..976c1bb0c7a525 100644
--- a/docs/zh/sql-reference/sql-functions/crytographic-functions/sha2.md
+++ b/docs/zh/sql-reference/sql-functions/crytographic-functions/sha2.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # sha2
diff --git a/docs/zh/sql-reference/sql-functions/crytographic-functions/sm3.md b/docs/zh/sql-reference/sql-functions/crytographic-functions/sm3.md
index 93a5c480437edb..05b3a026b908ff 100644
--- a/docs/zh/sql-reference/sql-functions/crytographic-functions/sm3.md
+++ b/docs/zh/sql-reference/sql-functions/crytographic-functions/sm3.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # sm3
diff --git a/docs/zh/sql-reference/sql-functions/crytographic-functions/to_base64.md b/docs/zh/sql-reference/sql-functions/crytographic-functions/to_base64.md
index a2d4c3ec4d02ba..36c4b6d6f54f9f 100644
--- a/docs/zh/sql-reference/sql-functions/crytographic-functions/to_base64.md
+++ b/docs/zh/sql-reference/sql-functions/crytographic-functions/to_base64.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # to_base64
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/add_months.md b/docs/zh/sql-reference/sql-functions/date-time-functions/add_months.md
index d6a0da3f6f4372..a67b6cbf47eba1 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/add_months.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/add_months.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # add_months
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/adddate.md b/docs/zh/sql-reference/sql-functions/date-time-functions/adddate.md
index d80ce029664e7a..d5464995695f34 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/adddate.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/adddate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # adddate,date_add
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/convert_tz.md b/docs/zh/sql-reference/sql-functions/date-time-functions/convert_tz.md
index 3c685e69b3665f..98b17a78537f97 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/convert_tz.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/convert_tz.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # convert_tz
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/curdate.md b/docs/zh/sql-reference/sql-functions/date-time-functions/curdate.md
index e12a5a6f26eff0..145b0126b083fa 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/curdate.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/curdate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # curdate,current_date
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/current_timestamp.md b/docs/zh/sql-reference/sql-functions/date-time-functions/current_timestamp.md
index 3ab4a0358fc3fd..78c951cf8675be 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/current_timestamp.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/current_timestamp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # current_timestamp
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/curtime.md b/docs/zh/sql-reference/sql-functions/date-time-functions/curtime.md
index a5f51ee4a23194..acad8edd3c3bae 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/curtime.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/curtime.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # curtime,current_time
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/date.md b/docs/zh/sql-reference/sql-functions/date-time-functions/date.md
index 2d44c3b302c07f..0f5ed68b7310a2 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/date.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/date.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # date
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/date_add.md b/docs/zh/sql-reference/sql-functions/date-time-functions/date_add.md
index 2db91de0f5e1fe..b8976c94c0ddc3 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/date_add.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/date_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # date_add,adddate
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/date_diff.md b/docs/zh/sql-reference/sql-functions/date-time-functions/date_diff.md
index 131c2ffd8f9540..7d3ead6d61b1b6 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/date_diff.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/date_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # date_diff
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/date_format.md b/docs/zh/sql-reference/sql-functions/date-time-functions/date_format.md
index 8a2fb8ac5de4b6..ea5b39c02d530e 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/date_format.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/date_format.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # date_format
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/date_slice.md b/docs/zh/sql-reference/sql-functions/date-time-functions/date_slice.md
index b7f5176fdd6dd2..8f5e055564c7b9 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/date_slice.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/date_slice.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # date_slice
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/date_sub.md b/docs/zh/sql-reference/sql-functions/date-time-functions/date_sub.md
index ef2ca32f3b1293..6df9e8c52ad0bc 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/date_sub.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/date_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # date_sub,subdate
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/date_trunc.md b/docs/zh/sql-reference/sql-functions/date-time-functions/date_trunc.md
index 5a43b48a0ecef4..a69d8a9727c48a 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/date_trunc.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/date_trunc.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # date_trunc
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/datediff.md b/docs/zh/sql-reference/sql-functions/date-time-functions/datediff.md
index 2c3f9f932d316f..6bd3db4b39bd63 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/datediff.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/datediff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # datediff
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/day.md b/docs/zh/sql-reference/sql-functions/date-time-functions/day.md
index cfd2a7573a2b80..80bc0561fdf7a1 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/day.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/day.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # day
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/day_of_week_iso.md b/docs/zh/sql-reference/sql-functions/date-time-functions/day_of_week_iso.md
index 174e56045d01e4..b4c56c0a5dc49f 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/day_of_week_iso.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/day_of_week_iso.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # dayofweek_iso
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/dayname.md b/docs/zh/sql-reference/sql-functions/date-time-functions/dayname.md
index d5203b8d4a1a3d..4d6276bb598fc7 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/dayname.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/dayname.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # dayname
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/dayofmonth.md b/docs/zh/sql-reference/sql-functions/date-time-functions/dayofmonth.md
index f6af2ba7931592..4629b25a1ce6dc 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/dayofmonth.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/dayofmonth.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # dayofmonth
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/dayofweek.md b/docs/zh/sql-reference/sql-functions/date-time-functions/dayofweek.md
index 4ec02ca40959a9..16c4903a410ea5 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/dayofweek.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/dayofweek.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # dayofweek
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/dayofyear.md b/docs/zh/sql-reference/sql-functions/date-time-functions/dayofyear.md
index 4953c7966d3d05..8533dcba9256a4 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/dayofyear.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/dayofyear.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # dayofyear
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/days_add.md b/docs/zh/sql-reference/sql-functions/date-time-functions/days_add.md
index 88614e17a40a9d..11ca3180e8aecf 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/days_add.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/days_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # days_add
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/days_diff.md b/docs/zh/sql-reference/sql-functions/date-time-functions/days_diff.md
index 97aa589b39993a..33c4d5f4b3c00b 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/days_diff.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/days_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # days_diff
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/days_sub.md b/docs/zh/sql-reference/sql-functions/date-time-functions/days_sub.md
index 12aea71b21548c..7a04617f3be97b 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/days_sub.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/days_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # days_sub
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/from_days.md b/docs/zh/sql-reference/sql-functions/date-time-functions/from_days.md
index a189655d1f4a12..e7592c48fdcc8a 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/from_days.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/from_days.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # from_days
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/from_unixtime.md b/docs/zh/sql-reference/sql-functions/date-time-functions/from_unixtime.md
index caabd184dfe3a7..2d0369b5f8c2ec 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/from_unixtime.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/from_unixtime.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # from_unixtime
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/hour.md b/docs/zh/sql-reference/sql-functions/date-time-functions/hour.md
index faaf4000b0dc31..4f19d70a5c16d5 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/hour.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/hour.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # hour
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/hours_add.md b/docs/zh/sql-reference/sql-functions/date-time-functions/hours_add.md
index 00c446d73c3bcc..4c2ea289711111 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/hours_add.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/hours_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # hours_add
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/hours_diff.md b/docs/zh/sql-reference/sql-functions/date-time-functions/hours_diff.md
index dd166587d504c2..99b3b983ab1ad6 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/hours_diff.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/hours_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # hours_diff
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/hours_sub.md b/docs/zh/sql-reference/sql-functions/date-time-functions/hours_sub.md
index 0a2b89b106b404..385d77d22cac37 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/hours_sub.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/hours_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # hours_sub
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/jodatime_format.md b/docs/zh/sql-reference/sql-functions/date-time-functions/jodatime_format.md
index e5accf520dbcf1..995b54b403a74a 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/jodatime_format.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/jodatime_format.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # jodatime_format
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/last_day.md b/docs/zh/sql-reference/sql-functions/date-time-functions/last_day.md
index e94194cf3415e3..a7b822e10e35f6 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/last_day.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/last_day.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # last_day
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/makedate.md b/docs/zh/sql-reference/sql-functions/date-time-functions/makedate.md
index b0c45742f71472..196837312c7755 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/makedate.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/makedate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # makedate
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/microseconds_add.md b/docs/zh/sql-reference/sql-functions/date-time-functions/microseconds_add.md
index 304121b807263a..0fd8795c64a2d1 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/microseconds_add.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/microseconds_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # microseconds_add
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/microseconds_sub.md b/docs/zh/sql-reference/sql-functions/date-time-functions/microseconds_sub.md
index 78c97a3bd79e6c..f53b92b494abe1 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/microseconds_sub.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/microseconds_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # microseconds_sub
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/milliseconds_diff.md b/docs/zh/sql-reference/sql-functions/date-time-functions/milliseconds_diff.md
index 401b2b71a83fc4..5a5cbd5e112142 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/milliseconds_diff.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/milliseconds_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # milliseconds_diff
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/minute.md b/docs/zh/sql-reference/sql-functions/date-time-functions/minute.md
index 3f1868d770d2a6..0f9e508645e79c 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/minute.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/minute.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # minute
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/minutes_add.md b/docs/zh/sql-reference/sql-functions/date-time-functions/minutes_add.md
index f048ea7a1bbaf1..599529b31626da 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/minutes_add.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/minutes_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # minutes_add
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/minutes_diff.md b/docs/zh/sql-reference/sql-functions/date-time-functions/minutes_diff.md
index 3a344f6be81ce2..19526dd686c576 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/minutes_diff.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/minutes_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # minutes_diff
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/minutes_sub.md b/docs/zh/sql-reference/sql-functions/date-time-functions/minutes_sub.md
index 9d5cd19e590ac5..865071a1675468 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/minutes_sub.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/minutes_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # minutes_sub
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/month.md b/docs/zh/sql-reference/sql-functions/date-time-functions/month.md
index 76eaf0e2970d25..509f591f2670bb 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/month.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/month.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # month
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/monthname.md b/docs/zh/sql-reference/sql-functions/date-time-functions/monthname.md
index d11364c5c7efb3..c8c816dd464ef0 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/monthname.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/monthname.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # monthname
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/months_add.md b/docs/zh/sql-reference/sql-functions/date-time-functions/months_add.md
index 8ed0613e81fb23..6e6763c3298777 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/months_add.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/months_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # months_add
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/months_diff.md b/docs/zh/sql-reference/sql-functions/date-time-functions/months_diff.md
index e3000cd2e13923..35aa51642d5762 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/months_diff.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/months_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # months_diff
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/months_sub.md b/docs/zh/sql-reference/sql-functions/date-time-functions/months_sub.md
index a3e6fb793ba8a0..085ba99134cf24 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/months_sub.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/months_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # months_sub
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/next_day.md b/docs/zh/sql-reference/sql-functions/date-time-functions/next_day.md
index 5e2b47c53bed7f..26202da87d841e 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/next_day.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/next_day.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # next_day
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/now.md b/docs/zh/sql-reference/sql-functions/date-time-functions/now.md
index 7163661edfd12d..ac9c6adb2fca35 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/now.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/now.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # now, current_timestamp, localtime, localtimestamp
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/previous_day.md b/docs/zh/sql-reference/sql-functions/date-time-functions/previous_day.md
index adb34df198a864..e88b83558f68b3 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/previous_day.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/previous_day.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # previous_day
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/quarter.md b/docs/zh/sql-reference/sql-functions/date-time-functions/quarter.md
index dc721ba0d77f0d..7006af1969fb20 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/quarter.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/quarter.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # quarter
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/second.md b/docs/zh/sql-reference/sql-functions/date-time-functions/second.md
index 65df01e299be81..99bf80530c9107 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/second.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/second.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # second
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/seconds_add.md b/docs/zh/sql-reference/sql-functions/date-time-functions/seconds_add.md
index 71074839e3a8c6..7056b1707f8662 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/seconds_add.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/seconds_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # seconds_add
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/seconds_diff.md b/docs/zh/sql-reference/sql-functions/date-time-functions/seconds_diff.md
index eb6e5d3074f54f..c9fa0cc61d4e88 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/seconds_diff.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/seconds_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # seconds_diff
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/seconds_sub.md b/docs/zh/sql-reference/sql-functions/date-time-functions/seconds_sub.md
index 0f086238be3489..d90839b7ecc7e2 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/seconds_sub.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/seconds_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # seconds_sub
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/str2date.md b/docs/zh/sql-reference/sql-functions/date-time-functions/str2date.md
index 5e1154fd4a755b..109ba02167ae60 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/str2date.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/str2date.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # str2date
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/str_to_date.md b/docs/zh/sql-reference/sql-functions/date-time-functions/str_to_date.md
index a58a9cb3e9a1c3..2461a93d9e52c0 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/str_to_date.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/str_to_date.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # str_to_date
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/str_to_jodatime.md b/docs/zh/sql-reference/sql-functions/date-time-functions/str_to_jodatime.md
index cbec47ffe43cca..14a937caf9c60f 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/str_to_jodatime.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/str_to_jodatime.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # str_to_jodatime
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/time_slice.md b/docs/zh/sql-reference/sql-functions/date-time-functions/time_slice.md
index 604f978e3b4887..359ce15a8940d3 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/time_slice.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/time_slice.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # time_slice
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/time_to_sec.md b/docs/zh/sql-reference/sql-functions/date-time-functions/time_to_sec.md
index f74c89b9d9e2c9..ca1c294ddedad4 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/time_to_sec.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/time_to_sec.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # time_to_sec
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/timediff.md b/docs/zh/sql-reference/sql-functions/date-time-functions/timediff.md
index ca5a7a0eea11ca..75de64ae7546b8 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/timediff.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/timediff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # timediff
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/timestamp.md b/docs/zh/sql-reference/sql-functions/date-time-functions/timestamp.md
index 0708040f0eaacd..0e52faa628d6cb 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/timestamp.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/timestamp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # timestamp
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/timestampadd.md b/docs/zh/sql-reference/sql-functions/date-time-functions/timestampadd.md
index 550c5f11757b24..2f2239b6e8266a 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/timestampadd.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/timestampadd.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # timestampadd
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/timestampdiff.md b/docs/zh/sql-reference/sql-functions/date-time-functions/timestampdiff.md
index a7c89933fc3a90..6e502f879deb6f 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/timestampdiff.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/timestampdiff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # timestampdiff
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/to_date.md b/docs/zh/sql-reference/sql-functions/date-time-functions/to_date.md
index 7c5f7e69a935cf..6f0fbb8106e319 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/to_date.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/to_date.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # to_date
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/to_days.md b/docs/zh/sql-reference/sql-functions/date-time-functions/to_days.md
index 52614b87cfd5eb..f5b598991607f2 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/to_days.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/to_days.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # to_days
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/to_iso8601.md b/docs/zh/sql-reference/sql-functions/date-time-functions/to_iso8601.md
index df7d0bcb2059c3..2cd8c225694e74 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/to_iso8601.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/to_iso8601.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # to_iso8601
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/to_tera_date.md b/docs/zh/sql-reference/sql-functions/date-time-functions/to_tera_date.md
index a2ca4844b223d1..0d9e6b6bfd26ae 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/to_tera_date.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/to_tera_date.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # to_tera_date
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/to_tera_timestamp.md b/docs/zh/sql-reference/sql-functions/date-time-functions/to_tera_timestamp.md
index 91713820f6a8d0..ea018e5584f5c9 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/to_tera_timestamp.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/to_tera_timestamp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # to_tera_timestamp
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/unix_timestamp.md b/docs/zh/sql-reference/sql-functions/date-time-functions/unix_timestamp.md
index 4d139c24bbb43e..77fa2d4db8f5ec 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/unix_timestamp.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/unix_timestamp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # unix_timestamp
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/utc_timestamp.md b/docs/zh/sql-reference/sql-functions/date-time-functions/utc_timestamp.md
index 83baf3a93ea454..d3366915ea190e 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/utc_timestamp.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/utc_timestamp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # utc_timestamp
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/week.md b/docs/zh/sql-reference/sql-functions/date-time-functions/week.md
index ebdb75412ce2e0..dc1b949f02f128 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/week.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/week.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # week
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/week_iso.md b/docs/zh/sql-reference/sql-functions/date-time-functions/week_iso.md
index ed239b778afeb8..4c22b677d6df29 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/week_iso.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/week_iso.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # week_iso
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/weekofyear.md b/docs/zh/sql-reference/sql-functions/date-time-functions/weekofyear.md
index ac2de437aeb749..d32ffbcb5f79aa 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/weekofyear.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/weekofyear.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # weekofyear
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/weeks_add.md b/docs/zh/sql-reference/sql-functions/date-time-functions/weeks_add.md
index 2fc4ee8e9f4ef1..c9818825c2e112 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/weeks_add.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/weeks_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # weeks_add
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/weeks_diff.md b/docs/zh/sql-reference/sql-functions/date-time-functions/weeks_diff.md
index 4a40366f0479de..80928a0dc6cb5e 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/weeks_diff.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/weeks_diff.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # weeks_diff
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/weeks_sub.md b/docs/zh/sql-reference/sql-functions/date-time-functions/weeks_sub.md
index 8f5d3d7d5d662e..a86764eb5c798d 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/weeks_sub.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/weeks_sub.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # weeks_sub
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/year.md b/docs/zh/sql-reference/sql-functions/date-time-functions/year.md
index 660adfa29ca755..4d1dbe27999505 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/year.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/year.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # year
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/years_add.md b/docs/zh/sql-reference/sql-functions/date-time-functions/years_add.md
index e023026491a652..760c8faaabbeef 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/years_add.md
+++ b/docs/zh/sql-reference/sql-functions/date-time-functions/years_add.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # years_add
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/years_diff.md b/docs/zh/sql-reference/sql-functions/date-time-functions/years_diff.md
index c555f2825474c2..edeaa64bfc7ab3 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/years_diff.md
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 # years_diff
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/years_sub.md b/docs/zh/sql-reference/sql-functions/date-time-functions/years_sub.md
index f019429113864a..f70d97a0a51dfe 100644
--- a/docs/zh/sql-reference/sql-functions/date-time-functions/years_sub.md
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 # years_sub
diff --git a/docs/zh/sql-reference/sql-functions/date-time-functions/yearweek.md b/docs/zh/sql-reference/sql-functions/date-time-functions/yearweek.md
index 1ecfac0f376242..4613dbb1760e61 100644
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 # yearweek
diff --git a/docs/zh/sql-reference/sql-functions/dict-functions/dict_mapping.md b/docs/zh/sql-reference/sql-functions/dict-functions/dict_mapping.md
index 716032b0b28641..17393075726d59 100644
--- a/docs/zh/sql-reference/sql-functions/dict-functions/dict_mapping.md
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 # dict_mapping
diff --git a/docs/zh/sql-reference/sql-functions/function-list.md b/docs/zh/sql-reference/sql-functions/function-list.md
deleted file mode 100644
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----
-
-# 函数列表
-
-StarRocks 提供了丰富的函数，方便您在日常数据查询和分析时使用。除了常见的函数分类，StarRocks 也支持 ARRAY、JSON、MAP、STRUCT 等半结构化函数，支持 [Lambda 高阶函数](Lambda_expression.md)。如果以上函数都不符合您的需求，您还可以自行编写 [Java UDF](JAVA_UDF.md) 来满足业务需求。StarRocks 还提供 [Hive Bitmap UDF](../../integrations/hive_bitmap_udf.md) 功能，您可以在 Hive 里计算生成 Bitmap 后，再导入 StarRocks；将 StarRocks 里生成的 Bitmap，导出到 Hive，方便其它系统使用。
-
-您可以按照以下分类来查找目标函数。
-
-- [函数列表](#函数列表)
-  - [时间日期函数](#时间日期函数)
-  - [字符串函数](#字符串函数)
-  - [聚合函数](#聚合函数)
-  - [数学函数](#数学函数)
-  - [Array 函数](#array-函数)
-  - [Bitmap 函数](#bitmap-函数)
-  - [JSON 函数](#json-函数)
-  - [Map 函数](#map-函数)
-  - [Struct 函数](#struct-函数)
-  - [表函数](#表函数)
-  - [Bit 函数](#bit-函数)
-  - [Binary 函数](#binary-函数)
-  - [加密函数](#加密函数)
-  - [模糊/正则匹配函数](#模糊正则匹配函数)
-  - [条件函数](#条件函数)
-  - [百分位函数](#百分位函数)
-  - [标量函数](#标量函数)
-  - [工具函数](#工具函数)
-  - [地理位置函数](#地理位置函数)
-  - [Hash 函数](#hash-函数)
-  - [字典函数](#字典函数)
-
-## 时间日期函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-| [add_months](./date-time-functions/add_months.md)  |   在给定的日期（DATE、DATETIME）上增加一个整数月。     |
-| [adddate](./date-time-functions/adddate.md)          |  向日期添加指定的时间间隔。        |
-| [convert_tz](./date-time-functions/convert_tz.md)          |   将给定的时间转化为另一个时区的时间。  |
-| [current_date，curdate](./date-time-functions/curdate.md)          |   获取当前的日期，以 DATE 类型返回。  |
-| [current_time，curtime](./date-time-functions/curtime.md)      |  获取当前的时间，以 TIME 类型返回。  |
-| [current_timestamp](./date-time-functions/current_timestamp.md)      |  获取当前时间，以 DATETIME 类型返回。   |
-| [date](./date-time-functions/date.md)      |  从日期或时间日期表达式中截取日期部分。  |
-| [date_add，adddate](./date-time-functions/date_add.md)      |  向日期添加指定的时间间隔。    |
-| [date_diff](./date-time-functions/date_diff.md)| 根据指定的时间单位返回两个日期的差值。 |
-| [date_format](./date-time-functions/date_format.md)      |  按照 format 指定的格式来显示日期/时间数据。   |
-| [date_slice](./date-time-functions/date_slice.md)      |  根据指定的时间粒度周期，将给定的时间转化到其所在的时间粒度周期的起始或结束时刻。  |
-| [date_sub，subdate](./date-time-functions/date_sub.md)    |    从日期中减去指定的时间间隔。   |
-| [date_trunc](./date-time-functions/date_trunc.md)     |    根据指定的精度级别，将一个日期时间截断。  |
-| [datediff](./date-time-functions/datediff.md)   |  计算两个日期的差值，结果精确到天。        |
-| [day](./date-time-functions/day.md) | 返回指定日期中的天信息。|
-| [dayname](./date-time-functions/dayname.md)| 返回指定日期对应的星期名称。|
-| [dayofmonth](./date-time-functions/dayofmonth.md)| 返回日期中的天信息，返回值范围 1~31。  |
-| [dayofweek](./date-time-functions/dayofweek.md)| 返回指定日期的工作日索引值。  |
-| [dayofweek_iso](./date-time-functions/day_of_week_iso.md)| 根据 ISO 标准，计算某一个日期对应的是一周内的星期几。  |
-| [dayofyear](./date-time-functions/dayofyear.md)|  计算指定日期为对应年中的哪一天。   |
-| [days_add](./date-time-functions/days_add.md)| 向日期添加指定的天数。  |
-| [days_diff](./date-time-functions/days_diff.md)|  计算开始时间和结束时间相差几天。 |
-| [days_sub](./date-time-functions/days_sub.md)| 从给定日期或者日期时间中减去指定的天数，获得新的 DATETIME 结果。  |
-| [from_days](./date-time-functions/from_days.md)|  通过计算当前时间距离 0000-01-01 的天数，计算出当前是时间哪一天。 |
-| [from_unixtime](./date-time-functions/from_unixtime.md)|  将 UNIX 时间戳转化为对应的时间格式。 |
-| [hour](./date-time-functions/hour.md)| 获得指定日期中的小时信息。  |
-| [hours_add](./date-time-functions/hours_add.md)| 给指定的日期时间增加指定的小时数。  |
-| [hours_diff](./date-time-functions/hours_diff.md)|  计算开始时间和结束时间相差多少个小时。 |
-| [hours_sub](./date-time-functions/hours_sub.md)| 从指定的日期时间中减少指定的小时数。  |
-| [jodatime_format](./date-time-functions/jodatime_format.md)| 将某一个日期转换成指定的 Joda DateTimeFormat 格式的字符串。  |
-| [last_day](./date-time-functions/last_day.md)| 根据指定的时间单位，返回输入的日期对应的最后一天。|
-| [makedate](./date-time-functions/makedate.md)| 根据给定的年份和天数值，构造一个日期值。 |
-| [microseconds_add](./date-time-functions/microseconds_add.md)| 向一个日期时间添加指定的时间间隔，单位为微秒。  |
-| [microseconds_sub](./date-time-functions/microseconds_sub.md)| 从一个日期时间中减去指定的时间间隔，单位为微秒。  |
-| [milliseconds_diff](./date-time-functions/milliseconds_diff.md)| 计算开始时间和结束时间相差多少毫秒。  |
-| [minute](./date-time-functions/minute.md)| 获得日期中的分钟的信息，返回值范围为 0~59。  |
-| [minutes_add](./date-time-functions/minutes_add.md)| 给指定的日期时间或日期增加指定的分钟数。|
-| [minutes_diff](./date-time-functions/minutes_diff.md)| 计算开始时间和结束时间相差多少分钟。  |
-| [minutes_sub](./date-time-functions/minutes_sub.md)| 从指定的日期时间或日期中减去指定的分钟数。  |
-| [month](./date-time-functions/month.md)|  返回指定日期中的月份。 |
-| [monthname](./date-time-functions/monthname.md)|  返回指定日期对应的月份。 |
-| [months_add](./date-time-functions/months_add.md)| 给日期添加指定的月数。  |
-| [months_diff](./date-time-functions/months_diff.md)| 计算开始时间和结束时间相差几个月。  |
-| [months_sub](./date-time-functions/months_sub.md)|  从日期中减去指定的月数。 |
-|[next_day](./date-time-functions/next_day.md)|根据输入的日期值，返回它之后的那个星期几所对应的日期。 |
-| [now](./date-time-functions/now.md)| 获取当前的时间，以 DATETIME 类型返回。  |
-| [previous_day](./date-time-functions/previous_day.md) | 根据输入的日期值，返回它之前的那个星期几所对应的日期。 |
-| [quarter](./date-time-functions/quarter.md)| 返回给定的日期值对应的季度，范围 1~4。  |
-| [second](./date-time-functions/second.md)|  获得日期中的秒的信息，返回值范围 0~59。 |
-| [seconds_add](./date-time-functions/seconds_add.md)| 向一个日期时间添加指定的时间间隔，单位为秒。  |
-| [seconds_diff](./date-time-functions/seconds_diff.md)| 计算开始时间和结束时间相差多少秒。  |
-| [seconds_sub](./date-time-functions/seconds_sub.md)|  给指定的日期时间或日期减去指定的秒数。 |
-| [str2date](./date-time-functions/str2date.md)| 按照 format 指定的格式将 str 转换为 DATE 类型的值。  |
-| [str_to_date](./date-time-functions/str_to_date.md)| 按照 format 指定的格式将 str 转换为 DATETIME 类型的值。  |
-| [str_to_jodatime](./date-time-functions/str_to_jodatime.md)| 将某一个 Joda 格式的字符串转换为指定的 Joda DateTime 格式的 DATETIME 值。  |
-| [time_slice](./date-time-functions/time_slice.md)| 根据指定的时间粒度周期，将给定的时间转化为其所在的时间粒度周期的起始或结束时刻。  |
-| [time_to_sec](./date-time-functions/time_to_sec.md)| 将 time 时间值转换为秒数。  |
-| [timediff](./date-time-functions/timediff.md)| 返回两个 DATETIME 类型值之间的差值，返回 TIME 类型。  |
-| [timestamp](./date-time-functions/timestamp.md)|  将时间表达式转换为 DATETIME 值。 |
-| [timestampadd](./date-time-functions/timestampadd.md)| 将整数表达式间隔添加到日期或日期时间表达式中。  |
-| [timestampdiff](./date-time-functions/timestampdiff.md)|  返回两个日期或日期时间表达式的差值。 |
-| [to_date](./date-time-functions/to_date.md)| 返回 DATETIME 类型值中的日期部分。  |
-| [to_days](./date-time-functions/to_days.md)| 返回指定日期距离 0000-01-01 的天数。  |
-| [to_iso8601](./date-time-functions/to_iso8601.md)| 将某一个日期转换为 ISO 8601 标准格式的字符串。  |
-| [to_tera_date](./date-time-functions/to_tera_date.md)| 将某一个 VARCHAR 类型的值转换成指定格式的日期。  |
-| [to_tera_timestamp](./date-time-functions/to_tera_timestamp.md)| 将某一个 VARCHAR 类型的值按指定的格式转换成 DATETIME 类型的值。  |
-| [unix_timestamp](./date-time-functions/unix_timestamp.md)| 将 DATE 或 DATETIME 类型的值转化为 UNIX 时间戳。  |
-| [utc_timestamp](./date-time-functions/utc_timestamp.md)| 返回当前 UTC 日期时间。  |
-| [week](./date-time-functions/week.md)| 根据指定的周数计算逻辑，计算指定的日期时间属于一年中的第几周。  |
-| [week_iso](./date-time-functions/week_iso.md)| 根据 ISO 标准，计算某一个日期对应的是一年内的第几个周。  |
-| [weekofyear](./date-time-functions/weekofyear.md)| 计算指定的日期时间属于一年中的第几周。 |
-| [weeks_add](./date-time-functions/weeks_add.md)|  向原始的日期时间加上指定周数。 |
-| [weeks_diff](./date-time-functions/weeks_diff.md)|  计算开始时间和结束时间相差几周。 |
-| [weeks_sub](./date-time-functions/weeks_sub.md)| 从原始的日期中减去若干周数。  |
-| [year](./date-time-functions/year.md)|  返回指定日期时间中的年份。 |
-| [yearweek](./date-time-functions/yearweek.md)| 返回给定日期对应的年份和周数。 |
-| [years_add](./date-time-functions/years_add.md)| 向原始的日期时间添加指定的年数。  |
-| [years_diff](./date-time-functions/years_diff.md)|  计算开始时间和结束时间相差几年。 |
-| [years_sub](./date-time-functions/years_sub.md)  |  从指定的日期时间中减去指定年数。     |
-
-## 字符串函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-| [append_trailing_char_if_absent](./string-functions/append_trailing_char_if_absent.md)   | 如果字符串非空并且末尾不包含 trailing_char 字符，则将 trailing_char 字符附加到末尾。  |
-| [ascii](./string-functions/ascii.md) | 返回字符串第一个字符对应的 ASCII 码。  |
-| [char](./string-functions/char.md)| 根据输入的 ASCII 值返回对应的字符。  |
-| [char_length，character_length](./string-functions/char_length.md) | 返回字符串的长度。  |
-| [concat](./string-functions/concat.md) |  将多个字符串连接起来。 |
-| [concat_ws](./string-functions/concat_ws.md) | 使用分隔符将两个或以上的字符串拼接成一个新的字符串。  |
-| [crc32](./string-functions/crc32.md) | 返回字符串的 32 位循环冗余校验值。 |
-| [ends_with](./string-functions/ends_with.md) | 如果字符串以指定后缀结尾，返回 true，否则返回 false。  |
-| [find_in_set](./string-functions/find_in_set.md) | 返回指定的字符串在一系列字符串列表中第一次出现的位置。  |
-| [group_concat](./string-functions/group_concat.md) | 将结果集中的多行结果连接成一个字符串。  |
-| [hex_decode_binary](./string-functions/hex_decode_binary.md) |  将一个十六进制编码的字符串解码为 VARBINARY 类型的值。 |
-| [hex_decode_string](./string-functions/hex_decode_string.md) | 将输入字符串中每一对十六进制数字解析为一个数字，并将解析得到的数字转换为表示该数字的字节，然后返回一个二进制字符串。  |
-| [hex](./string-functions/hex.md) | 对于输入的数字或字符，返回十六进制的字符串表示形式。  |
-| [instr](./string-functions/instr.md) |  返回子字符串在指定的字符串中第一次出现的位置。 |
-| [left](./string-functions/left.md) | 从字符串左边部分返回指定长度的字符。  |
-| [length](./string-functions/length.md) | 返回字符串的字节长度。  |
-| [locate](./string-functions/locate.md) | 从 pos 下标开始的字符串处开始查找子字符串在某个字符串中第一次出现的位置。  |
-| [lower](./string-functions/lower.md) | 将参数中所有的字符串转换成小写。  |
-| [lpad](./string-functions/lpad.md) |根据指定的长度在字符串前面（左侧）追加字符。  |
-| [ltrim](./string-functions/ltrim.md) |  从字符串的左侧（开始部分）移除连续出现的空格或指定字符。 |
-| [money_format](./string-functions/money_format.md) |  将数字按照货币格式输出，整数部分每隔 3 位用逗号分隔，小数部分保留 2 位。  |
-| [ngram_search](./string-functions/ngram_search.md) |  计算两个字符串的 ngram 相似度。|
-| [null_or_empty](./string-functions/null_or_empty.md) | 如果字符串为空字符串或者 NULL 则返回 true，否则返回 false。 |
-| [parse_url](./string-functions/parse_url.md) |  从目标 URL 中提取一部分信息。 |
-| [repeat](./string-functions/repeat.md) | 将字符串重复 count 次输出，count 小于 1 时返回空字符串。  |
-| [replace](./string-functions/replace.md) | 将字符串中符合指定模式的字符全部替换成其他字符。  |
-| [reverse](./string-functions/reverse.md) | 将字符串或数组反转，返回的字符串或数组的顺序和源字符串或数组的顺序相反。  |
-| [right](./string-functions/right.md) | 从字符串右边部分返回指定长度的字符。  |
-| [rpad](./string-functions/rpad.md) |  根据指定的长度在字符串后面（右侧）追加字符。 |
-| [rtrim](./string-functions/rtrim.md) | 从字符串的右侧（结尾部分）移除连续出现的空格或指定字符。  |
-| [space](./string-functions/space.md) | 返回由指定数量的空格组成的字符串。|
-| [split](./string-functions/split.md) | 根据分隔符拆分字符串，将拆分后的所有字符串以 ARRAY 的格式返回。  |
-| [split_part](./string-functions/split_part.md) | 根据分割符拆分字符串，返回指定的分割部分。  |
-| [starts_with](./string-functions/starts_with.md) | 如果字符串以指定前缀开头返回 1，否则返回 0。  |
-| [str_to_map](./string-functions/str_to_map.md) | 将给定的字符串分割成键值对 (Key-Value pair)，返回包含这些键值对的 Map。  |
-| [strleft](./string-functions/strleft.md) | 从字符串左边部分返回指定长度的字符。  |
-| [strright](./string-functions/strright.md) | 从字符串右边部分返回指定长度的字符。  |
-| [substr, substring](./string-functions/substring.md) | 返回字符串中从位置 pos 开始的指定长度的子字符串。  |
-| [substring_index](./string-functions/substring_index.md) | 从给定字符串中截取第 `count` 个分隔符之前或之后的字符串。  |
-| [translate](./string-functions/translate.md) | 将给定字符串 `source` 中出现在 `from_string` 中的字符替换为对应位置的 `to_string` 中的字符。 |
-| [trim](./string-functions/trim.md) | 从字符串的左侧和右侧移除连续出现的空格或指定的字符。  |
-| [ucase](./string-functions/ucase.md) | 该函数与 upper 一致，将字符串转换为大写形式。  |
-| [unhex](./string-functions/unhex.md) | 将输入的字符串中的两个字符为一组转化为 16 进制的字符，然后拼接成字符串输出。  |
-| [upper](./string-functions/upper.md) | 将字符串转换为大写形式。  |
-| [url_decode](./string-functions/url_decode.md) | 将字符串从 [application/x-www-form-urlencoded](https://www.w3.org/TR/html4/interact/forms.html#h-17.13.4.1) 格式转换回来。 |
-| [url_encode](./string-functions/url_encode.md)  | 将字符串根据 [application/x-www-form-urlencoded](https://www.w3.org/TR/html4/interact/forms.html#h-17.13.4.1) 格式进行编码。  |
-| [url_extract_host](./string-functions/url_extract_host.md)| 从一个 URL 中截取 host 部分。|
-| [url_extract_parameter](./string-functions/url_extract_parameter.md)   | 从一个 URL 的 query 部分，获取指定参数（`name`）的取值。  |
-
-## 聚合函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-|  [any_value](./aggregate-functions/any_value.md)| 在包含 GROUP BY 的聚合查询中，该函数用于从每个聚合分组中**随机**选择一行返回。 |
-|  [approx_count_distinct](./aggregate-functions/approx_count_distinct.md)| 返回类似于 COUNT(DISTINCT col) 结果的近似值。 |
-|  [approx_top_k](./aggregate-functions/approx_top_k.md)| 返回表达式 `expr` 中最常出现的 `k` 个项目以及每个项目出现的近似次数。 |
-|  [array_agg](./array-functions/array_agg.md) | 将一列中的值（包括空值 null）串联成一个数组（多行转一行）。  |
-|  [avg](./aggregate-functions/avg.md)| 用于返回选中字段的平均值。 |
-|  [bitmap](./aggregate-functions/bitmap.md)| 通过 bitmap 函数实现聚合。 |
-|  [bitmap_agg](./bitmap-functions/bitmap_agg.md)| 将一列中的多行非 NULL 数值合并成一行 BITMAP 值，即多行转一行。 |
-|  [corr](./aggregate-functions/corr.md) | 返回两个随机变量的皮尔逊相关系数. |
-|  [covar_pop](./aggregate-functions/covar_pop.md)| 返回两个随机变量的总体协方差。 |
-|  [covar_samp](./aggregate-functions/covar_samp.md)| 返回两个随机变量的样本协方差。 |
-|  [count](./aggregate-functions/count.md)| 计算总行数。 |
-|  [count_if](./aggregate-functions/count_if.md)| 计算满足指定条件的记录数。 |
-|  [group_concat](./string-functions/group_concat.md)| 将结果集中的多行结果连接成一个字符串。|
-|  [grouping](./aggregate-functions/grouping.md)| 判断一个列是否为聚合列，如果是聚合列则返回 0，否则返回 1。|
-|  [grouping_id](./aggregate-functions/grouping_id.md)| 用于区分相同分组标准的分组统计结果。 |
-|  [hll_raw_agg](./aggregate-functions/hll_raw_agg.md)| 用于聚合 HLL 类型的字段，返回 HLL 类型。 |
-|  [hll_union](./aggregate-functions/hll_union.md)| 返回一组 HLL 值的并集。 |
-|  [hll_union_agg](./aggregate-functions/hll_union_agg.md)| 将多个 HLL 类型数据合并成一个 HLL。 |
-|  [max](./aggregate-functions/max.md)| 返回表达式中的最大值。 |
-|  [max_by](./aggregate-functions/max_by.md)| 返回与 y 的最大值相关联的 x 值。 |
-|  [min](./aggregate-functions/min.md)| 返回表达式中的最小值。 |
-|  [min_by](./aggregate-functions/min_by.md) | 返回与 y 的最小值关联的 x 值。 |
-|  [multi_distinct_count](./aggregate-functions/multi_distinct_count.md)| 返回表达式去除重复值后的行数，功能等同于 COUNT(DISTINCT expr)。 |
-|  [multi_distinct_sum](./aggregate-functions/multi_distinct_sum.md)| 返回表达式去除重复值后的总和，功能等同于 sum(distinct expr)。 |
-|  [percentile_approx](./aggregate-functions/percentile_approx.md)| 返回第 p 个百分位点的近似值。 |
-|  [percentile_cont](./aggregate-functions/percentile_cont.md)| 计算精确百分位数。 |
-|  [percentile_disc](./aggregate-functions/percentile_disc.md)| 计算百分位数。 |
-|  [retention](./aggregate-functions/retention.md)| 用于计算一段时间内的用户留存情况。  |
-|  [sum](./aggregate-functions/sum.md)| 返回指定列所有值的总和。 |
-|  [std](./aggregate-functions/std.md)| 返回指定列的标准差。 |
-|  [stddev，stddev_pop](./aggregate-functions/stddev.md)| 返回表达式的总体标准差。 |
-|  [stddev_samp](./aggregate-functions/stddev_samp.md)| 返回表达式的样本标准差。 |
-|  [variance, variance_pop, var_pop](./aggregate-functions/variance.md)| 返回表达式的方差。 |
-|  [var_samp](./aggregate-functions/var_samp.md)| 返回表达式的样本方差。 |
-|  [window_funnel](./aggregate-functions/window_funnel.md)| 搜索滑动时间窗口内的事件列表，计算条件匹配的事件链里的最大连续事件数。 |
-
-## 数学函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-|  [abs](./math-functions/abs.md)| 计算绝对值。 |
-|  [acos](./math-functions/acos.md)| 计算反余弦值（单位为弧度）。 |
-|  [asin](./math-functions/asin.md)| 计算反正弦值（单位为弧度）。 |
-|  [atan](./math-functions/atan.md)| 计算反正切值（单位为弧度）。 |
-|  [atan2](./math-functions/atan2.md)| 通过使用两个参数的符号确定象限，计算 x/y 的反正切的主值，返回值在 [-π, π] 范围内。 |
-|  [bin](./math-functions/bin.md)| 将输入的参数转成二进制。 |
-|  [cbrt](./math-functions/cbrt.md)  | 计算参数的立方根。|
-|  [ceil, dceil](./math-functions/ceil.md)| 返回大于或等于 x 的最小整数。 |
-|  [ceiling](./math-functions/ceiling.md)| 返回大于或等于 x 的最小整数。 |
-|  [conv](./math-functions/conv.md)| 对输入的参数进行进制转换。 |
-|  [cos](./math-functions/cos.md)| 计算余弦值。 |
-|  [cosh](./math-functions/cosh.md)| 计算输入数值的双曲余弦值。 |
-|  [cosine_similarity](./math-functions/cos_similarity.md)| 计算两个向量的余弦夹角来评估向量之间的相似度。 |
-|  [cosine_similarity_norm](./math-functions/cos_similarity_norm.md)| 计算两个归一化向量的余弦夹角来评估向量之间的相似度。|
-|  [cot](./math-functions/cot.md)| 计算余切值（单位为弧度）。 |
-| [cbrt](./math-functions/cbrt.md)||
-|  [degrees](./math-functions/degrees.md)| 将参数 x 转成角度，x 是弧度。 |
-|  [divide](./math-functions/divide.md)| 除法函数，返回 x 除以 y 的结果， |
-|  [e](./math-functions/e.md)| 返回自然对数函数的底数。 |
-|  [exp, dexp](./math-functions/exp.md)| 返回 e 的 x 次幂。 |
-|  [floor, dfloor](./math-functions/floor.md)| 返回不大于 x 的最大整数值。 |
-|  [fmod](./math-functions/fmod.md)| 取模函数，返回两个数相除之后的浮点余数。 |
-|  [greatest](./math-functions/greatest.md)| 返回多个输入参数中的最大值。 |
-|  [least](./math-functions/least.md)| 返回多个输入参数中的最小值。 |
-|  [ln, dlog1, log](./math-functions/ln.md)| 返回参数 x 的自然对数，以 e 为底数。 |
-|  [log](./math-functions/log.md)| 返回以 base 为底数的 x 的对数。如果未指定 base，则该函数等同于 ln()。 |
-|  [log2](./math-functions/log2.md)| 返回以 2 为底数的 x 的对数。 |
-|  [log10, dlog10](./math-functions/log10.md)| 返回以 10 为底数的 x 的对数。 |
-|  [mod](./math-functions/mod.md)| 取模函数，返回两个数相除之后的余数。 |
-|  [multiply](./math-functions/multiply.md)| 计算两个参数的乘积。 |
-|  [negative](./math-functions/negative.md)| 返回参数的负数。 |
-|  [pi](./math-functions/pi.md)| 返回圆周率。 |
-|  [pmod](./math-functions/pmod.md)| 取模函数，返回两个数相除之后的正余数。 |
-|  [positive](./math-functions/positive.md)| 返回表达式的结果。 |
-|  [pow, power, dpow, fpow](./math-functions/pow.md)| 返回参数 x 的 y 次方。 |
-|  [radians](./math-functions/radians.md)| 将参数 x 转为弧度，x 是角度。 |
-|  [rand, random](./math-functions/rand.md)| 返回一个 0 (包含) 到 1（不包含）之间的随机浮点数。 |
-|  [round, dround](./math-functions/round.md)| 按照指定的小数位数对数值进行四舍五入。 |
-|  [sign](./math-functions/sign.md)| 返回参数 x 的符号。 |
-|  [sin](./math-functions/sin.md)| 计算参数 x 的正弦，x 为弧度值。 |
-|  [sinh](./math-functions/sinh.md)| 计算输入数值的双曲正弦值。 |
-|  [sqrt, dsqrt](./math-functions/sqrt.md)| 计算参数的平方根。 |
-|  [square](./math-functions/square.md)| 计算参数的平方。 |
-|  [tan](./math-functions/tan.md)| 计算参数 x 的正切，x 为弧度值。 |
-|  [tanh](./math-functions/tanh.md)| 计算输入数值的双曲正切值。 |
-|  [truncate](./math-functions/truncate.md)| 返回数值 x 保留到小数点后 y 位的值。 |
-
-## Array 函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-|  [all_match](./array-functions/all_match.md)| 判断数组中的所有元素是否都匹配谓词中指定的条件。 |
-|  [any_match](./array-functions/any_match.md)| 判断数组中是否有元素匹配谓词中指定的条件。 |
-|  [array_agg](./array-functions/array_agg.md)| 将一列中的值（包括空值 null）串联成一个数组（多行转一行）。 |
-|  [array_append](./array-functions/array_append.md)| 在数组末尾添加一个新的元素。 |
-|  [array_avg](./array-functions/array_avg.md)| 求取一个 ARRAY 中的所有数据的平均数。 |
-|  [array_concat](./array-functions/array_concat.md)| 将多个数组拼接成一个数组。 |
-|  [array_contains](./array-functions/array_contains.md)| 检查数组中是否包含某个元素，是的话返回 1，否则返回 0。 |
-|  [array_contains_all](./array-functions/array_contains_all.md)| 检查数组 `arr1` 是否包含数组 `arr2` 中的所有元素。 |
-|  [array_contains_seq](./array-functions/array_contains_seq.md) | 检查数组 `arr2` 的所有元素是否以完全相同的顺序出现在数组 `arr1` 中 |
-|  [array_cum_sum](./array-functions/array_cum_sum.md)| 对数组中的元素进行向前累加。 |
-|  [array_difference](./array-functions/array_difference.md)| 对于数值型数组，返回相邻两个元素的差(从后者中减去前者)构成的数组。 |
-|  [array_distinct](./array-functions/array_distinct.md)| 数组元素去重。 |
-|  [array_filter](./array-functions/array_filter.md)| 根据设定的过滤条件返回数组中匹配的元素。 |
-|  [array_generate](./array-functions/array_generate.md)| 生成一个包含数值元素的数组，数值范围在 start 和 end 之间，步长为 step。 |
-|  [array_intersect](./array-functions/array_intersect.md)| 对于多个同类型数组，返回交集。 |
-|  [array_join](./array-functions/array_join.md)| 将数组中的所有元素连接生成一个字符串。 |
-|  [array_length](./array-functions/array_length.md)| 计算数组中的元素个数。 |
-|  [array_map](./array-functions/array_map.md)| 用于将输入的 arr1，arr2 等数组按照 lambda_function 进行转换，输出一个新的数组。 |
-|  [array_max](./array-functions/array_max.md)| 求取一个ARRAY中的所有数据中的最大值。 |
-|  [array_min](./array-functions/array_min.md)| 求取一个ARRAY中的所有数据中的最小值。 |
-|  [arrays_overlap](./array-functions/arrays_overlap.md)| 判断两个相同类型的数组中是否包含相同的元素。 |
-|  [array_position](./array-functions/array_position.md)| 获取数组中某个元素位置，是的话返回位置，否则返回 0. |
-|  [array_remove](./array-functions/array_remove.md)| 从数组中移除指定元素。 |
-|  [array_slice](./array-functions/array_slice.md)| 返回数组的一个数组片段。 |
-|  [array_sort](./array-functions/array_sort.md)| 对数组中的元素进行升序排列。 |
-|  [array_sortby](./array-functions/array_sortby.md)| 对数组中的元素根据另外一个键值数组元素或者 Lambda 函数生成的键值数组元素进行升序排列。 |
-|  [array_sum](./array-functions/array_sum.md)| 对数组中的所有元素求和。 |
-|  [array_to_bitmap](./array-functions/array_to_bitmap.md)| 将 array 类型转化为 bitmap 类型。 |
-|  [array_unique_agg](./array-functions/array_unique_agg.md) | 将一列中的 distinct 值（包括空值 null）串联成一个数组（多行转一行）。  |
-|  [cardinality](./array-functions/cardinality.md)| 计算数组中的元素个数， |
-|  [element_at](./array-functions/element_at.md)| 获取 Array 数组中指定位置的元素。 |
-|  [reverse](./string-functions/reverse.md)| 将字符串或数组反转，返回的字符串或数组的顺序和源字符串或数组的顺序相反。 |
-|  [unnest](./array-functions/unnest.md)| 表函数，用于将一个数组展开成多行。 |
-|  [array_repeat](./array-functions/array_repeat.md)| 将一个给定的元素重复指定的次数，返回一个数组。 |
-
-## Bitmap 函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-|  [bitmap_agg](./bitmap-functions/bitmap_agg.md)| 将一列中的多行非 NULL 数值合并成一行 BITMAP 值，即多行转一行。 |
-|  [bitmap_and](./bitmap-functions/bitmap_and.md)| 计算两个 bitmap 的交集，返回新的 bitmap。|
-|  [bitmap_andnot](./bitmap-functions/bitmap_andnot.md)| 计算两个输入的 bitmap 的差集。|
-|  [bitmap_contains](./bitmap-functions/bitmap_contains.md)| 计算输入值是否在 Bitmap 列中。 |
-|  [bitmap_count](./bitmap-functions/bitmap_count.md)| 统计 bitmap 中不重复值的个数。 |
-|  [bitmap_empty](./bitmap-functions/bitmap_empty.md)| 返回一个空 bitmap，主要用于 insert 或 stream load 时填充默认值。|
-|  [bitmap_from_binary](./bitmap-functions/bitmap_from_binary.md)| 将一个特定格式的二进制字符串转化为一个 bitmap。|
-|  [bitmap_from_string](./bitmap-functions/bitmap_from_string.md)| 将一个字符串转化为一个 bitmap，字符串由逗号分隔的一组 UInt32 数字组成。|
-|  [bitmap_hash](./bitmap-functions/bitmap_hash.md)| 对任意类型的输入计算 32 位的哈希值，返回包含该哈希值的 bitmap。|
-|  [bitmap_has_any](./bitmap-functions/bitmap_has_any.md)| 计算两个 Bitmap 列是否存在相交元素。|
-|  [bitmap_intersect](./bitmap-functions/bitmap_intersect.md)| 求一组 bitmap 值的交集。|
-|  [bitmap_max](./bitmap-functions/bitmap_max.md)| 获取 Bitmap 中的最大值。|
-|  [bitmap_min](./bitmap-functions/bitmap_min.md)| 获取 Bitmap 中的最小值。|
-|  [bitmap_or](./bitmap-functions/bitmap_or.md)| 计算两个 bitmap 的并集，返回新的 bitmap。|
-|  [bitmap_remove](./bitmap-functions/bitmap_remove.md)| 从 Bitmap 中删除指定的数值。 |
-|  [bitmap_subset_in_range](./bitmap-functions/bitmap_subset_in_range.md)| 从 Bitmap 中返回取值在指定范围内的元素。|
-|  [bitmap_subset_limit](./bitmap-functions/bitmap_subset_limit.md)| 根据指定的起始值，从 BITMAP 中截取指定个数的元素。|
-|  [bitmap_to_array](./bitmap-functions/bitmap_to_array.md)| 将 BITMAP 中的所有值组合成 BIGINT 类型的数组。|
-|  [bitmap_to_base64](./bitmap-functions/bitmap_to_base64.md)| 将 bitmap 转换为 Base64 字符串。|
-|  [bitmap_to_binary](./bitmap-functions/bitmap_to_binary.md)| 将 bitmap 转换为特定格式的 binary 字符串。|
-|  [base64_to_bitmap](./bitmap-functions/base64_to_bitmap.md)|将 Base64 编码的字符串转化为 Bitmap。 |
-|  [bitmap_to_string](./bitmap-functions/bitmap_to_string.md)| 将一个 bitmap 转化成一个逗号分隔的字符串。|
-|  [bitmap_union](./bitmap-functions/bitmap_union.md)| 求一组 bitmap 值的并集。 |
-|  [bitmap_union_count](./bitmap-functions/bitmap_union_count.md)| 计算一组 bitmap 值的并集，并返回并集的基数。|
-|  [bitmap_union_int](./bitmap-functions/bitmap_union_int.md)| 计算 TINYINT，SMALLINT 和 INT 类型的列中不重复值的个数。|
-|  [bitmap_xor](./bitmap-functions/bitmap_xor.md)| 计算两个 Bitmap 中不重复元素所构成的集合。|
-|  [intersect_count](./bitmap-functions/intersect_count.md)| 求 bitmap 交集大小。|
-|  [subdivide_bitmap](./bitmap-functions/subdivide_bitmap.md)| 将大 bitmap 拆成多个子 bitmap。|
-|  [sub_bitmap](./bitmap-functions/sub_bitmap.md)| 计算两个 bitmap 之间相同元素的个数。|
-|  [to_bitmap](./bitmap-functions/to_bitmap.md)| 将输入值转换为 bitmap。 |
-|  [unnest_bitmap](./bitmap-functions/unnest_bitmap.md)| 将 bitmap 展开成多行。|
-
-## JSON 函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-|  [json_array](./json-functions/json-constructor-functions/json_array.md)| 接收 SQL 数组并返回一个 JSON 类型的数组。|
-|  [json_object](./json-functions/json-constructor-functions/json_object.md)| 接收键值集合，返回一个包含这些键值对的 JSON 类型的对象。|
-|  [parse_json](./json-functions/json-constructor-functions/parse_json.md)|将字符串类型的数据构造为 JSON 类型的数据。|
-|  [箭头函数](./json-functions/json-query-and-processing-functions/arrow-function.md)| 箭头函数可以查询 JSON 对象中指定路径的值。|
-|  [cast](./json-functions/json-query-and-processing-functions/cast.md)| 实现 JSON 类型数据与 SQL 类型间的相互转换。|
-|  [get_json_bool](./json-functions/json-query-and-processing-functions/get_json_bool.md)| 解析并获取 `json_str` 内指定 `json_path` 下的布尔内容。|
-|  [get_json_double](./json-functions/json-query-and-processing-functions/get_json_double.md)| 解析并获取 JSON 字符串内指定路径中的浮点型内容。|
-|  [get_json_int](./json-functions/json-query-and-processing-functions/get_json_int.md)| 解析并获取 JSON 字符串内指定路径中的整型内容。|
-|  [get_json_string, get_json_object](./json-functions/json-query-and-processing-functions/get_json_string.md)| 解析并获取 JSON 字符串内指定路径中的字符串。|
-|  [json_each](./json-functions/json-query-and-processing-functions/json_each.md)| 将 JSON 对象的最外层按照键和值展开为两列，返回一行或多行数据的集合。|
-|  [json_exists](./json-functions/json-query-and-processing-functions/json_exists.md)| 查询 JSON 对象中指定路径是否存在满足特定条件的值。|
-|  [json_keys](./json-functions/json-query-and-processing-functions/json_keys.md)| 返回 JSON 对象中所有最上层成员 (key) 组成的数组。|
-|  [json_length](./json-functions/json-query-and-processing-functions/json_length.md)| 计算 JSON 字符串的长度。|
-|  [json_query](./json-functions/json-query-and-processing-functions/json_query.md)| 查询 JSON 对象中指定路径（json_path）的值，并输出 JSON 类型的结果。 |
-|  [json_string](./json-functions/json-query-and-processing-functions/json_string.md)| 将 JSON 类型转化为 JSON 字符串。|
-|  [to_json](./json-functions/json-query-and-processing-functions/to_json.md)| 将 Map 或 Struct 类型的数据转换成 JSON 数据。 |
-
-## Map 函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-|  [cardinality](./map-functions/cardinality.md)| 计算 Map 中元素的个数。 |
-|  [distinct_map_keys](./map-functions/distinct_map_keys.md)| 删除 Map 中重复的 Key。 |
-|  [element_at](./map-functions/element_at.md)| 获取 Map 中指定键 (Key) 对应的值 (Value)。 |
-|  [map_apply](./map-functions/map_apply.md)| 返回 Map 中所有 Key 或 Value 进行 Lambda 函数运算后的 Map 值。 |
-|  [map_concat](./map-functions/map_concat.md)| 将多个 Map 合并成一个 Map。 |
-|  [map_filter](./map-functions/map_filter.md)| 根据设定的过滤函数返回 MAP 中匹配的 Key-value 对。 |
-|  [map_from_arrays](./map-functions/map_from_arrays.md)| 将两个 ARRAY 数组作为 Key 和 Value 组合成一个 MAP 对象。 |
-|  [map_keys](./map-functions/map_keys.md)| 返回 Map 中所有 key 组成的数组。 |
-|  [map_size](./map-functions/map_size.md)| 计算 Map 中元素的个数。 |
-|  [map_values](./map-functions/map_values.md)| 返回 Map 中所有 Value 组成的数组。 |
-|  [transform_keys](./map-functions/transform_keys.md)| 对 Map 中的 key 进行 Lambda 转换。 |
-|  [transform_values](./map-functions/transform_values.md)| 对 Map 中的 value 进行 lambda 转换。 |
-
-## Struct 函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-|  [named_struct](./struct-functions/named_struct.md)| 根据给定的字段名和字段值来构建 STRUCT。 |
-|  [row](./struct-functions/row.md)| 根据给定的一个或多个值来构建 STRUCT。 |
-
-## 表函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-| [files](./table-functions/files.md) | 从云存储或 HDFS 读取数据文件。|
-| [generate_series](./table-functions/generate_series.md) | 生成一系列从 start 到 end 的数值，步长为 step。 |
-| [json_each](./json-functions/json-query-and-processing-functions/json_each.md) | 将 JSON 对象的最外层按照键和值展开为两列，返回一行或多行数据的集合。 |
-| [subdivide_bitmap](./bitmap-functions/subdivide_bitmap.md)| 将大 bitmap 拆成多个子 bitmap。|
-| [unnest](./array-functions/unnest.md) | 用于将一个数组展开成多行。|
-| [unnest_bitmap](./bitmap-functions/unnest_bitmap.md) | 用于将一个 bitmap 展开成多行。|
-
-## Bit 函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-|  [bitand](./bit-functions/bitand.md)| 返回两个数值在按位进行 AND 运算后的结果。 |
-|  [bitnot](./bit-functions/bitnot.md)| 返回参数 `x` 进行取反运算后的结果。 |
-|  [bitor](./bit-functions/bitor.md)| 返回两个数值在按位进行 OR 运算后的结果。  |
-|  [bitxor](./bit-functions/bitxor.md)| 返回两个数值在按位 XOR 运算后的结果。 |
-|  [bit_shift_left](./bit-functions/bit_shift_left.md)| 将一个数值或数值表达式的二进制表示向左移动指定的位数。该函数执行算术左移。 |
-|  [bit_shift_right](./bit-functions/bit_shift_right.md)| 将一个数值或者数值表达式的二进制表示向右移动指定的位数。该函数执行算术右移。 |
-|  [bit_shift_right_logical](./bit-functions/bit_shift_right_logical.md)| 将一个数值或者数值表达式的二进制表示向右移动指定的位数。该函数执行逻辑右移。 |
-
-## Binary 函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-|  [from_binary](./binary-functions/from_binary.md)| 根据指定的格式，将二进制数据转化为 VARCHAR 类型的字符串。 |
-|  [to_binary](./binary-functions/to_binary.md)| 根据指定的二进制格式 (binary_type)，将 VARCHAR 字符串转换为二进制类型。|
-
-## 加密函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-|  [aes_decrypt](./crytographic-functions/aes_decrypt.md)| 使用 AES_128_ECB 算法将字符串解密并返回一个二进制字符串。 |
-|  [aes_encrypt](./crytographic-functions/aes_encrypt.md)| 使用 AES_128_ECB 算法对字符串进行加密并返回一个二进制字符串。 |
-|  [base64_decode_binary](./crytographic-functions/base64_decode_binary.md)| 解码某个 Base64 编码的字符串，并返回一个 VARBINARY 类型的值。 |
-|  [base64_decode_string](./crytographic-functions/base64_decode_string.md)| 用于解码某个 Base64 编码的字符串，是 to_base64() 函数的反向函数。 |
-|  [from_base64](./crytographic-functions/from_base64.md)| 将 Base64 编码过的字符串 str 进行解码。反向函数为 to_base64。 |
-|  [md5](./crytographic-functions/md5.md)| 使用 MD5 加密算法将给定字符串进行加密，输出一个 128-bit 的校验和 (checksum)，以 32 字符的十六进制字符串表示。 |
-|  [md5sum](./crytographic-functions/md5sum.md)| 计算多个输入参数的 MD5 128-bit 校验和 (checksum)，以 32 字符的十六进制字符串表示。 |
-|  [sha2](./crytographic-functions/sha2.md)| 计算 SHA-2 系列哈希函数 (SHA-224/SHA-256/SHA-384/SHA-512)。 |
-|  [sm3](./crytographic-functions/sm3.md)| 使用 SM3 摘要算法，将字符串加密为 256-bit 的 十六进制字符串，每 32 位用空格分隔。 |
-|  [to_base64](./crytographic-functions/to_base64.md)| 将字符串 str 进行 Base64 编码。反向函数为 from_base64。 |
-
-## 模糊/正则匹配函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-|  [like](./like-predicate-functions/like.md) | 判断字符串是否**模糊匹配**给定的模式 `pattern`。 |
-|  [regexp](./like-predicate-functions/regexp.md) | 判断字符串是否匹配给定的正则表达式 `pattern`。 |
-|  [regexp_extract](./like-predicate-functions/regexp_extract.md) | 对字符串进行正则匹配，抽取符合 pattern 的第 pos 个匹配部分，需要 pattern 完全匹配 str 中的某部分，才能返回 pattern 部分中需匹配部分，如果没有匹配就返回空字符串。 |
-|  [regexp_extract_all](./like-predicate-functions/regexp_extract_all.md) | 从 `str` 中提取与正则表达式 `pattern` 相匹配的子字符串并返回一个字符串数组。字符串必须匹配 `pos` 指定的正则分组。 |
-|  [regexp_replace](./like-predicate-functions/regexp_replace.md) | 对字符串进行正则匹配，将命中 pattern 的部分使用 repl 来进行替换。 |
-
-## 条件函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-|  [case](./condition-functions/case_when.md)| 将表达式与一个值比较。如果能找到匹配项，则返回 THEN 中的结果。如果未找到匹配项，则返回 ELSE 中的结果。 |
-|  [coalesce](./condition-functions/coalesce.md)| 从左向右返回参数中的第一个非 NULL 表达式。 |
-|  [if](./condition-functions/if.md)| 若参数 expr1 成立，返回结果 expr2；否则返回结果 expr3。 |
-|  [ifnull](./condition-functions/ifnull.md)| 若 expr1 不为 NULL，返回 expr1。若 expr1 为 NULL，返回 expr2。 |
-|  [nullif](./condition-functions/nullif.md)| 若参数 expr1 与 expr2 相等，则返回 NULL，否则返回 expr1 的值。 |
-
-## 百分位函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-|  [percentile_approx](./aggregate-functions/percentile_approx.md)| 返回第 p 个百分位点的近似值。 |
-|  [percentile_approx_raw](./percentile-functions/percentile_approx_raw.md)| 计算给定参数 x 的百分位数。 |
-|  [percentile_cont](./aggregate-functions/percentile_cont.md)| 计算精确百分位数。 |
-|  [percentile_disc](./aggregate-functions/percentile_disc.md)| 计算百分位数。 |
-|  [percentile_empty](./percentile-functions/percentile_empty.md)| 构造一个 percentile 类型的数值，主要用于 INSERT 或 Stream Load 导入时填充默认值。 |
-|  [percentile_hash](./percentile-functions/percentile_hash.md)| 将 double 类型数值构造成 percentile 类型数值。 |
-|  [percentile_union](./percentile-functions/percentile_union.md)| 用于对分组结果进行聚合。 |
-
-## 标量函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-| [hll_cardinality](./scalar-functions/hll_cardinality.md) |  用于计算 HLL 类型值的基数。  |
-| [hll_empty](./scalar-functions/hll_empty.md)| 生成空 HLL 列，用于 INSERT 或导入数据时补充默认值。 |
-| [hll_hash](./scalar-functions/hll_hash.md)| 将一个数值转换为 HLL 类型。通常用于导入中，将源数据中的数值映射到 StarRocks 表中的 HLL 列类型。 |
-
-## 工具函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-| [catalog](./utility-functions/catalog.md)| 查询当前会话所在的 Catalog。 |
-|  [current_role](./utility-functions/current_role.md)| 获取当前用户激活的角色。  |
-|  [current_version](./utility-functions/current_version.md)| 获取当前 StarRocks 的版本 |
-| [database](./utility-functions/database.md)| 查询当前会话所在的数据库。 |
-| [get_query_profile](./utility-functions/get_query_profile.md)| 获取指定查询的 Profile。|
-|  [host_name](./utility-functions/host_name.md)| 获取计算所在节点的主机名。|
-|  [isnull](./utility-functions/isnull.md)| 判断输入值是否为 NULL。|
-| [is_role_in_session](./utility-functions/is_role_in_session.md) | 检查指定的角色（包括嵌套角色）在当前会话下是否已经激活。 |
-|  [last_query_id](./utility-functions/last_query_id.md)| 返回最近一次执行的查询的 ID。|
-|  [sleep](./utility-functions/sleep.md)| 将当前正在执行的线程休眠 x 秒。|
-|  [uuid](./utility-functions/uuid.md)| 以 VARCHAR 形式返回一个随机的 UUID 值。长度为36个字符，包含32个十六进制字符，由4个连字符进行连接，形式为8-4-4-4-12。|
-|  [uuid_numeric](./utility-functions/uuid_numeric.md)|返回一个数值类型的随机 UUID 值。 |
-|  [version](./utility-functions/version.md)|返回当前 MySQL 数据库的版本。  |
-
-## 地理位置函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-|  [ST_AsText, ST_AsWKT](./spatial-functions/st_astext.md)| 将一个几何图形转化为 WKT（Well Known Text）的表示形式。 |
-|  [st_circle](./spatial-functions/st_circle.md)| 将一个 WKT (Well Known Text) 转化为地球球面上的一个圆。 |
-|  [st_contains](./spatial-functions/st_contains.md)| 判断几何图形 shape1 是否完全能够包含几何图形 shape2。 |
-|  [st_distance_sphere](./spatial-functions/st_distance_sphere.md)| 计算地球两点之间的球面距离，单位是米。 |
-|  [st_geometryfromtext](./spatial-functions/st_geometryfromtext.md)| 将一个 WKT（Well Known Text）转化为对应的内存的几何形式。 |
-|  [st_linefromtext, ST_LineStringFromText](./spatial-functions/st_linefromtext.md)| 将一个 WKT（Well Known Text）转化为一个 Line 形式的内存表现形式。 |
-|  [st_point](./spatial-functions/st_point.md)| 通过给定的 X 坐标值、Y 坐标值返回对应的 Point。 |
-|  [st_polygon](./spatial-functions/st_polygon.md)| 将一个 WKT（Well Known Text）转化为对应的多边形内存形式。 |
-|  [st_x](./spatial-functions/st_x.md)| 当 point 是一个合法的 POINT 类型时，返回对应的 X 坐标值。 |
-|  [st_y](./spatial-functions/st_y.md)| 当 point 是一个合法的 POINT 类型时，返回对应的 Y 坐标值。 |
-
-## Hash 函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-| [murmur_hash3_32](./hash-functions/murmur_hash3_32.md) | 返回输入字符串的 32 位 murmur3 hash 值。 |
-| [xx_hash3_64](./hash-functions/xx_hash3_64.md) | 返回输入字符串的 64 位 xxhash3 值。 |
-
-## 字典函数
-
-| 函数                |                 功能      |
-|  :-:                |                :-:       |
-|  [dict_mapping](./dict-functions/dict_mapping.md)| 通过指定字典表和 key，返回该 key 所映射的 value。 |
diff --git a/docs/zh/sql-reference/sql-functions/hash-functions/murmur_hash3_32.md b/docs/zh/sql-reference/sql-functions/hash-functions/murmur_hash3_32.md
index 213bcd04b7f765..2852de73152921 100644
--- a/docs/zh/sql-reference/sql-functions/hash-functions/murmur_hash3_32.md
+++ b/docs/zh/sql-reference/sql-functions/hash-functions/murmur_hash3_32.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # murmur_hash3_32
diff --git a/docs/zh/sql-reference/sql-functions/hash-functions/xx_hash3_128.md b/docs/zh/sql-reference/sql-functions/hash-functions/xx_hash3_128.md
index 1ea77f60349c57..658520516e218d 100644
--- a/docs/zh/sql-reference/sql-functions/hash-functions/xx_hash3_128.md
+++ b/docs/zh/sql-reference/sql-functions/hash-functions/xx_hash3_128.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # xx_hash3_128
diff --git a/docs/zh/sql-reference/sql-functions/hash-functions/xx_hash3_64.md b/docs/zh/sql-reference/sql-functions/hash-functions/xx_hash3_64.md
index f283d93b547d2d..21c455d79ece08 100644
--- a/docs/zh/sql-reference/sql-functions/hash-functions/xx_hash3_64.md
+++ b/docs/zh/sql-reference/sql-functions/hash-functions/xx_hash3_64.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # xx_hash3_64
diff --git a/docs/zh/sql-reference/sql-functions/hive_bitmap_udf.md b/docs/zh/sql-reference/sql-functions/hive_bitmap_udf.md
new file mode 100644
index 00000000000000..070334d28b8b26
--- /dev/null
+++ b/docs/zh/sql-reference/sql-functions/hive_bitmap_udf.md
@@ -0,0 +1,214 @@
+---
+displayed_sidebar: docs
+sidebar_position: 0.9
+---
+
+# Hive Bitmap UDF
+
+Hive Bitmap UDF 提供了可以直接在 Hive 里使用的 UDF，可用于生成 Bitmap 和执行 Bitmap 运算。
+
+UDF 定义的 Bitmap 格式与 StarRocks 里格式一致，可直接用于导入导出。
+
+适用场景:
+
+- 原始数据量比较大，直接导入 StarRocks 计算会对 StarRocks 集群产生较大压力。所以希望在 Hive 里计算完生成 Bitmap 后，再导入 StarRocks。
+- 将 StarRocks 里生成的 Bitmap，导出到 Hive，方便其它系统使用。
+
+导入导出格式:
+
+- 3.1 及以上版本支持 String，Base64，和 Binary 三种格式导入导出。
+- 2.5 和 3.0 版本只支持 String 和 Base64 两种格式导入导出。
+
+## 支持生成的 Hive Bitmap UDF 函数
+
+- com.starrocks.hive.udf.UDAFBitmapAgg
+
+  将一列中的多行非 NULL 数值合并成一行 BITMAP 值，等同于 StarRocks 的内置聚合函数 [bitmap_agg](bitmap-functions/bitmap_agg.md)。
+
+- com.starrocks.hive.udf.UDAFBitmapUnion
+
+  输入一组 Bitmap 值，求这一组 Bitmap 值的并集，等同于 StarRocks 的内置聚合函数 [bitmap_union](bitmap-functions/bitmap_union.md)。
+
+- com.starrocks.hive.udf.UDFBase64ToBitmap
+
+  将 Base64 编码的字符串转化为 Bitmap，等同于 StarRocks 的内置函数 [base64_to_bitmap](bitmap-functions/base64_to_bitmap.md)。
+
+- com.starrocks.hive.udf.UDFBitmapAnd
+
+  计算两个 Bitmap 的交集，等同于 StarRocks 的内置函数 [bitmap_and](bitmap-functions/bitmap_and.md)。
+
+- com.starrocks.hive.udf.UDFBitmapCount
+
+  统计 Bitmap 中值的个数，等同于 StarRocks 的内置函数 [bitmap_count](bitmap-functions/bitmap_count.md)。
+
+- com.starrocks.hive.udf.UDFBitmapFromString
+
+  将一个逗号分隔的字符串转化为一个 Bitmap，等同于 StarRocks 的内置函数 [bitmap_from_string](bitmap-functions/bitmap_from_string.md)。
+
+- com.starrocks.hive.udf.UDFBitmapOr
+
+  计算两个 Bitmap 的并集，等同于 StarRocks 的内置函数 [bitmap_or](bitmap-functions/bitmap_or.md)。
+
+- com.starrocks.hive.udf.UDFBitmapToBase64
+
+  将 Bitmap 转换为 Base64 字符串，等同于 StarRocks 的内置函数 [bitmap_to_base64](bitmap-functions/bitmap_to_base64.md)。
+
+- com.starrocks.hive.udf.UDFBitmapToString
+
+  将 Bitmap 转换为逗号分隔的字符串，等同于 StarRocks 的内置函数 [bitmap_to_string](bitmap-functions/bitmap_to_string.md)。
+
+- com.starrocks.hive.udf.UDFBitmapXor
+
+  计算两个 Bitmap 中不重复元素所构成的集合，等同于 StarRocks 的内置函数 [bitmap_xor](bitmap-functions/bitmap_xor.md)。
+
+## 使用方法
+
+1. 在 FE 上编译生成 Hive UDF。
+
+   ```bash
+   ./build.sh --hive-udf
+   ```
+
+   会在 `fe/hive-udf/` 目录下生成一个 JAR 包 `hive-udf-1.0.0.jar`。
+
+2. 将 JAR 包上传到 HDFS。
+
+   ```bash
+   hadoop  fs -put -f ./hive-udf-1.0.0.jar hdfs://<hdfs_ip>:<hdfs_port>/hive-udf-1.0.0.jar
+   ```
+
+3. Hive 里加载 JAR 包。
+
+   ```bash
+   hive> add jar hdfs://<hdfs_ip>:<hdfs_port>/hive-udf-1.0.0.jar;
+   ```
+
+4. 加载 UDF 函数。
+
+   ```sql
+   hive> create temporary function bitmap_agg as 'com.starrocks.hive.udf.UDAFBitmapAgg';
+   hive> create temporary function bitmap_union as 'com.starrocks.hive.udf.UDAFBitmapUnion';
+   hive> create temporary function base64_to_bitmap as 'com.starrocks.hive.udf.UDFBase64ToBitmap';
+   hive> create temporary function bitmap_and as 'com.starrocks.hive.udf.UDFBitmapAnd';
+   hive> create temporary function bitmap_count as 'com.starrocks.hive.udf.UDFBitmapCount';
+   hive> create temporary function bitmap_from_string as 'com.starrocks.hive.udf.UDFBitmapFromString';
+   hive> create temporary function bitmap_or as 'com.starrocks.hive.udf.UDFBitmapOr';
+   hive> create temporary function bitmap_to_base64 as 'com.starrocks.hive.udf.UDFBitmapToBase64';
+   hive> create temporary function bitmap_to_string as 'com.starrocks.hive.udf.UDFBitmapToString';
+   hive> create temporary function bitmap_xor as 'com.starrocks.hive.udf.UDFBitmapXor';
+   ```
+
+## 使用示例
+
+### 在 Hive 里生成 Bitmap 并通过 Binary 格式导入到 StarRocks
+
+1. 创建 Hive 源数据表。
+
+    ```sql
+    hive> create table t_src(c1 bigint, c2 bigint) stored as parquet;
+    
+    hive> insert into t_src values (1,1), (1,2), (1,3), (2,4), (2,5);
+    
+    hive> select * from t_src;
+    1       1
+    1       2
+    1       3
+    2       4
+    2       5
+    ```
+
+2. 创建 Hive Bitmap 表。
+
+    ```sql
+    hive> create table t_bitmap(c1 bigint, c2 binary) stored as parquet;
+    ```
+
+    Hive 通过 UDFBitmapAgg 生成 Bitmap，并写入 Bitmap 表。
+
+    ```sql
+    hive> insert into t_bitmap select c1, bitmap_agg(c2) from t_src group by c1;
+    ```
+
+3. 创建 StarRocks Bitmap 表。
+
+    ```sql
+    mysql> create table t1(c1 int, c2 bitmap bitmap_union) aggregate key(c1)  distributed by hash(c1);
+    ```
+
+4. 通过不同方式导入到 StarRocks。
+
+   - 通过 [files](table-functions/files.md) 函数导入。
+
+    ```sql
+    mysql> insert into t1 select c1, bitmap_from_binary(c2) from files (
+        "path" = "hdfs://<hdfs_ip>:<hdfs_port>/<hdfs_db>/t_bitmap/*",
+        "format"="parquet",
+        "compression" = "uncompressed"
+        );
+    ```
+
+   - 通过 [Hive Catalog](../../data_source/catalog/hive_catalog.md) 导入。
+
+    ```sql
+    mysql> insert into t1 select c1, bitmap_from_binary(c2) from hive_catalog_hms.xxx_db.t_bitmap;
+    ```
+
+5. 查看结果。
+
+    ```plain
+    mysql> select c1, bitmap_to_string(c2) from t1;                                                                                                                                                                                                                                   
+    +------+----------------------+                                                                                                                                                                                                                                                   
+    | c1   | bitmap_to_string(c2) |
+    +------+----------------------+
+    |    1 | 1,2,3                |
+    |    2 | 4,5                  |
+    +------+----------------------+
+    ```
+
+### 将 StarRocks 里的 Bitmap 导出到 Hive
+
+1. 在 StarRocks 里创建 Bitmap 表，并写入数据。
+
+    ```sql
+    mysql> create table t1(c1 int, c2 bitmap bitmap_union) aggregate key(c1) buckets 3 distributed by hash(c1);
+    
+    mysql> select c1, bitmap_to_string(c2) from t1;                                                                                                                                                                                                                                   
+    +------+----------------------+                                                                                                                                                                                                                                                   
+    | c1   | bitmap_to_string(c2) |
+    +------+----------------------+
+    |    1 | 1,2,3                |
+    |    2 | 4,5                  |
+    +------+----------------------+
+    ```
+
+2. 在 Hive 里创建 Bitmap 表。
+
+    ```sql
+    hive> create table t_bitmap(c1 bigint, c2 binary) stored as parquet;
+    ```
+
+3. 通过不同方式导出。
+
+   - 通过 INSERT INTO FILES 导出（binary 格式）。
+
+    ```sql
+    mysql> insert into files (
+        "path" = "hdfs://<hdfs_ip>:<hdfs_port>/<hdfs_db>/t_bitmap/",
+        "format"="parquet",
+        "compression" = "uncompressed"
+    ) select c1, bitmap_to_binary(c2) as c2 from t1;
+    ```
+
+   - 通过 [Hive Catalog](../../data_source/catalog/hive_catalog.md) 方式导出（binary 格式）。
+
+    ```sql
+    mysql> insert into hive_catalog_hms.<hdfs_db>.t_bitmap select c1, bitmap_to_binary(c2) from t1;
+    ```
+
+4. 在 Hive 里查看结果。
+
+    ```sql
+    hive> select c1, bitmap_to_string(c2) from t_bitmap;
+    1       1,2,3
+    2       4,5
+    ```
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-constructor-functions/json_array.md b/docs/zh/sql-reference/sql-functions/json-functions/json-constructor-functions/json_array.md
index cd36a2ced08f9e..f95360c56f5d46 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-constructor-functions/json_array.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-constructor-functions/json_array.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # json_array
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-constructor-functions/json_object.md b/docs/zh/sql-reference/sql-functions/json-functions/json-constructor-functions/json_object.md
index 90025f880348e0..28f1bcbd2bd2af 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-constructor-functions/json_object.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-constructor-functions/json_object.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # json_object
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-constructor-functions/parse_json.md b/docs/zh/sql-reference/sql-functions/json-functions/json-constructor-functions/parse_json.md
index e82b43541dd645..a659b7a50f1f14 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-constructor-functions/parse_json.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-constructor-functions/parse_json.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # parse_json
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-operators.md b/docs/zh/sql-reference/sql-functions/json-functions/json-operators.md
index e2875a41a57a3f..21108d41fa5a9b 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-operators.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-operators.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # JSON 运算符
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/arrow-function.md b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/arrow-function.md
index 34434d9c9c254b..8a6440470b7332 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/arrow-function.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/arrow-function.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 箭头函数
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/cast.md b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/cast.md
index c1b66bea5221cb..4c87ff384e56ad 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/cast.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/cast.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # cast
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_bool.md b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_bool.md
index 010da283bef419..8c8b7ae0d1858d 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_bool.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_bool.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # get_json_bool
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_double.md b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_double.md
index a34f934b81e0c4..d566ced1255b3d 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_double.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_double.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # get_json_double
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_int.md b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_int.md
index 2d2e6b54d5b836..df54451c410b79 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_int.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_int.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # get_json_int
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_string.md b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_string.md
index f0e79c7a1a9bc8..a3878bd6cde913 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_string.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/get_json_string.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # get_json_string,get_json_object
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_each.md b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_each.md
index ef587f7fef2473..08c9c3df391d62 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_each.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_each.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # json_each
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_exists.md b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_exists.md
index 93640809044cdb..8f3924c04e57c4 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_exists.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_exists.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # json_exists
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_keys.md b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_keys.md
index d40620dfcd6b13..391dfdc4ceeb01 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_keys.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_keys.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # json_keys
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_length.md b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_length.md
index babb2421e09103..5007cc811175b8 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_length.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_length.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # json_length
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_query.md b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_query.md
index a3641652564e14..aab7caace153b7 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_query.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_query.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # json_query
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_string.md b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_string.md
index 86a3de7f735e3d..d5b8c1c9a19faf 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_string.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/json_string.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # json_string
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/to_json.md b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/to_json.md
index e84d6d71c1444c..57fd5f6b046b42 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/to_json.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/json-query-and-processing-functions/to_json.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # to_json
@@ -67,5 +67,5 @@ select to_json(named_struct("k1", cast(null as string), "k2", "v2"));
 
 - [Map 数据类型](../../../data-types/semi_structured/Map.md)
 - [Struct 数据类型](../../../data-types/semi_structured/STRUCT.md)
-- [Map 函数](../../function-list.md#map-函数)
-- [Struct 函数](../../function-list.md#struct-函数)
+- [Map 函数](../../README.md#map-函数)
+- [Struct 函数](../../README.md#struct-函数)
diff --git a/docs/zh/sql-reference/sql-functions/json-functions/overview-of-json-functions-and-operators.md b/docs/zh/sql-reference/sql-functions/json-functions/overview-of-json-functions-and-operators.md
index 18466bedae1feb..1e67592947fe26 100644
--- a/docs/zh/sql-reference/sql-functions/json-functions/overview-of-json-functions-and-operators.md
+++ b/docs/zh/sql-reference/sql-functions/json-functions/overview-of-json-functions-and-operators.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # JSON 函数概述
diff --git a/docs/zh/sql-reference/sql-functions/like-predicate-functions/like.md b/docs/zh/sql-reference/sql-functions/like-predicate-functions/like.md
index 5dc5586d587d1d..ebc2945d1ccb86 100644
--- a/docs/zh/sql-reference/sql-functions/like-predicate-functions/like.md
+++ b/docs/zh/sql-reference/sql-functions/like-predicate-functions/like.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # like
diff --git a/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp.md b/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp.md
index fda756b8870a0b..b3829531d161f1 100644
--- a/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp.md
+++ b/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # regexp
diff --git a/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp_extract.md b/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp_extract.md
index ee464e3fc7ddc8..09bab89d058723 100644
--- a/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp_extract.md
+++ b/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp_extract.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # regexp_extract
diff --git a/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp_extract_all.md b/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp_extract_all.md
index 1d4fff6a1e0414..0b2ecbb3adacb2 100644
--- a/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp_extract_all.md
+++ b/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp_extract_all.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # regexp_extract_all
diff --git a/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp_replace.md b/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp_replace.md
index cb398552a7f9ea..2b05cc1bc48e01 100644
--- a/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp_replace.md
+++ b/docs/zh/sql-reference/sql-functions/like-predicate-functions/regexp_replace.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # regexp_replace
diff --git a/docs/zh/sql-reference/sql-functions/map-functions/cardinality.md b/docs/zh/sql-reference/sql-functions/map-functions/cardinality.md
index eaa5482c0134cb..62f22e379010ba 100644
--- a/docs/zh/sql-reference/sql-functions/map-functions/cardinality.md
+++ b/docs/zh/sql-reference/sql-functions/map-functions/cardinality.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # cardinality
diff --git a/docs/zh/sql-reference/sql-functions/map-functions/distinct_map_keys.md b/docs/zh/sql-reference/sql-functions/map-functions/distinct_map_keys.md
index 60bb6465ca5ff2..a072e338337365 100644
--- a/docs/zh/sql-reference/sql-functions/map-functions/distinct_map_keys.md
+++ b/docs/zh/sql-reference/sql-functions/map-functions/distinct_map_keys.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # distinct_map_keys
diff --git a/docs/zh/sql-reference/sql-functions/map-functions/element_at.md b/docs/zh/sql-reference/sql-functions/map-functions/element_at.md
index a0a36a700ba7ce..2bca471c4befc4 100644
--- a/docs/zh/sql-reference/sql-functions/map-functions/element_at.md
+++ b/docs/zh/sql-reference/sql-functions/map-functions/element_at.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # element_at
diff --git a/docs/zh/sql-reference/sql-functions/map-functions/map_apply.md b/docs/zh/sql-reference/sql-functions/map-functions/map_apply.md
index 21d111060d8c28..f7cdf756d2a8cf 100644
--- a/docs/zh/sql-reference/sql-functions/map-functions/map_apply.md
+++ b/docs/zh/sql-reference/sql-functions/map-functions/map_apply.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # map_apply
diff --git a/docs/zh/sql-reference/sql-functions/map-functions/map_concat.md b/docs/zh/sql-reference/sql-functions/map-functions/map_concat.md
index e415f5ddf7b2af..7dd449c5444ab7 100644
--- a/docs/zh/sql-reference/sql-functions/map-functions/map_concat.md
+++ b/docs/zh/sql-reference/sql-functions/map-functions/map_concat.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # map_concat
diff --git a/docs/zh/sql-reference/sql-functions/map-functions/map_filter.md b/docs/zh/sql-reference/sql-functions/map-functions/map_filter.md
index 1fad09992d5d50..ef1891bd21966f 100644
--- a/docs/zh/sql-reference/sql-functions/map-functions/map_filter.md
+++ b/docs/zh/sql-reference/sql-functions/map-functions/map_filter.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # map_filter
diff --git a/docs/zh/sql-reference/sql-functions/map-functions/map_from_arrays.md b/docs/zh/sql-reference/sql-functions/map-functions/map_from_arrays.md
index 32a1d4d79eed27..d1852bc2e7936b 100644
--- a/docs/zh/sql-reference/sql-functions/map-functions/map_from_arrays.md
+++ b/docs/zh/sql-reference/sql-functions/map-functions/map_from_arrays.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # map_from_arrays
diff --git a/docs/zh/sql-reference/sql-functions/map-functions/map_keys.md b/docs/zh/sql-reference/sql-functions/map-functions/map_keys.md
index 5da2822baf2c41..5b4a16b1793f77 100644
--- a/docs/zh/sql-reference/sql-functions/map-functions/map_keys.md
+++ b/docs/zh/sql-reference/sql-functions/map-functions/map_keys.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # map_keys
diff --git a/docs/zh/sql-reference/sql-functions/map-functions/map_size.md b/docs/zh/sql-reference/sql-functions/map-functions/map_size.md
index 13eec819690aba..94c04b4c809377 100644
--- a/docs/zh/sql-reference/sql-functions/map-functions/map_size.md
+++ b/docs/zh/sql-reference/sql-functions/map-functions/map_size.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # map_size
diff --git a/docs/zh/sql-reference/sql-functions/map-functions/map_values.md b/docs/zh/sql-reference/sql-functions/map-functions/map_values.md
index 00cb7635b5d95a..7d14b5939405ea 100644
--- a/docs/zh/sql-reference/sql-functions/map-functions/map_values.md
+++ b/docs/zh/sql-reference/sql-functions/map-functions/map_values.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # map_values
diff --git a/docs/zh/sql-reference/sql-functions/map-functions/transform_keys.md b/docs/zh/sql-reference/sql-functions/map-functions/transform_keys.md
index e25cd735cdc721..6df919561848e6 100644
--- a/docs/zh/sql-reference/sql-functions/map-functions/transform_keys.md
+++ b/docs/zh/sql-reference/sql-functions/map-functions/transform_keys.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # transform_keys
diff --git a/docs/zh/sql-reference/sql-functions/map-functions/transform_values.md b/docs/zh/sql-reference/sql-functions/map-functions/transform_values.md
index d484661a1e67c0..c5dae9229e4a0f 100644
--- a/docs/zh/sql-reference/sql-functions/map-functions/transform_values.md
+++ b/docs/zh/sql-reference/sql-functions/map-functions/transform_values.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # transform_values
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/abs.md b/docs/zh/sql-reference/sql-functions/math-functions/abs.md
index 74719722636961..b93de227767657 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/abs.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/abs.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # abs
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/acos.md b/docs/zh/sql-reference/sql-functions/math-functions/acos.md
index f33d6b109cc371..b2d773b5ca25a0 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/acos.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/acos.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # acos
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/asin.md b/docs/zh/sql-reference/sql-functions/math-functions/asin.md
index 399e3d8b0c763b..4c378e576bb1fc 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/asin.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/asin.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # asin
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/atan.md b/docs/zh/sql-reference/sql-functions/math-functions/atan.md
index d3618d57e868e0..f899526abbb034 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/atan.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/atan.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # atan
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/atan2.md b/docs/zh/sql-reference/sql-functions/math-functions/atan2.md
index 8f268fe064f2d0..3d66b22d9b9b60 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/atan2.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/atan2.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # atan2
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/bin.md b/docs/zh/sql-reference/sql-functions/math-functions/bin.md
index a41acc023457a2..906cd4b4135e3c 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/bin.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/bin.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # bin
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/cbrt.md b/docs/zh/sql-reference/sql-functions/math-functions/cbrt.md
index cb033c28af220e..3ba6cb01e9e541 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/cbrt.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/cbrt.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # cbrt
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/ceil.md b/docs/zh/sql-reference/sql-functions/math-functions/ceil.md
index df1a34178c88c0..2f88f990570be4 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/ceil.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/ceil.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ceil, dceil
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/ceiling.md b/docs/zh/sql-reference/sql-functions/math-functions/ceiling.md
index 338f23ad3d0979..330e238d63665e 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/ceiling.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/ceiling.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ceiling
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/conv.md b/docs/zh/sql-reference/sql-functions/math-functions/conv.md
index a96ee5c2253ab9..5c12cc9c3e75c8 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/conv.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/conv.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # conv
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/cos.md b/docs/zh/sql-reference/sql-functions/math-functions/cos.md
index 7cae32e8bd47c9..02a26aff8127ef 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/cos.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/cos.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # cos
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/cos_similarity.md b/docs/zh/sql-reference/sql-functions/math-functions/cos_similarity.md
index 0cdacf1ee0ee36..f917422c486757 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/cos_similarity.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/cos_similarity.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # cosine_similarity
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/cos_similarity_norm.md b/docs/zh/sql-reference/sql-functions/math-functions/cos_similarity_norm.md
index f8aa6c5b52c928..56509c119e0372 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/cos_similarity_norm.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/cos_similarity_norm.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # cosine_similarity_norm
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/cosh.md b/docs/zh/sql-reference/sql-functions/math-functions/cosh.md
index 48d42c4be17803..ec00025c55561a 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/cosh.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/cosh.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # cosh
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/cot.md b/docs/zh/sql-reference/sql-functions/math-functions/cot.md
index b138470b4471d3..3991c94fbeed55 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/cot.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/cot.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # cot
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/degrees.md b/docs/zh/sql-reference/sql-functions/math-functions/degrees.md
index 7ba8cf96650867..4a9080dd4dba6e 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/degrees.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/degrees.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # degrees
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/divide.md b/docs/zh/sql-reference/sql-functions/math-functions/divide.md
index bfc3c1c941fe46..bd2a43399a62cd 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/divide.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/divide.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # divide
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/e.md b/docs/zh/sql-reference/sql-functions/math-functions/e.md
index 620877617e2b2c..fa4925deef2ad6 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/e.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/e.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # e
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/exp.md b/docs/zh/sql-reference/sql-functions/math-functions/exp.md
index 5c5b30fb1043e9..1362b7f3c71c80 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/exp.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/exp.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # exp, dexp
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/floor.md b/docs/zh/sql-reference/sql-functions/math-functions/floor.md
index 499e59b26b59c4..d1db247252b84c 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/floor.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/floor.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # floor, dfloor
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/fmod.md b/docs/zh/sql-reference/sql-functions/math-functions/fmod.md
index c5748a9316d8e9..528bad25247b72 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/fmod.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/fmod.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # fmod
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/greatest.md b/docs/zh/sql-reference/sql-functions/math-functions/greatest.md
index b9ee4e2d8a7709..512fe5af64a0e7 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/greatest.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/greatest.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # greatest
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/least.md b/docs/zh/sql-reference/sql-functions/math-functions/least.md
index 2d36f1f1e1471f..2d0b02a958d89d 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/least.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/least.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # least
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/ln.md b/docs/zh/sql-reference/sql-functions/math-functions/ln.md
index d851e26c79a56c..db5f78be6ceeba 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/ln.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/ln.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ln, dlog1, log
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/log.md b/docs/zh/sql-reference/sql-functions/math-functions/log.md
index 6e3813c05df004..bd903e0f05cb33 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/log.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/log.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # log
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/log10.md b/docs/zh/sql-reference/sql-functions/math-functions/log10.md
index dcab85d2cf7b2e..dafc2ff1ddbfe6 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/log10.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/log10.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # log10, dlog10
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/log2.md b/docs/zh/sql-reference/sql-functions/math-functions/log2.md
index 95378ef8e92894..a92b5fbec1e72d 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/log2.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/log2.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # log2
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/mod.md b/docs/zh/sql-reference/sql-functions/math-functions/mod.md
index c879b6720b8f34..7aaab59b63d368 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/mod.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/mod.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # mod
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/multiply.md b/docs/zh/sql-reference/sql-functions/math-functions/multiply.md
index 57ac35bacb9d90..443904a18b0705 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/multiply.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/multiply.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # multiply
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/negative.md b/docs/zh/sql-reference/sql-functions/math-functions/negative.md
index 48de133243272d..bc18060d0f86d5 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/negative.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/negative.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # negative
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/pi.md b/docs/zh/sql-reference/sql-functions/math-functions/pi.md
index e584f8c339ae8d..a102de618be60b 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/pi.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/pi.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # pi
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/pmod.md b/docs/zh/sql-reference/sql-functions/math-functions/pmod.md
index 5273def14ffdbc..747d94c19c3c56 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/pmod.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/pmod.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # pmod
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/positive.md b/docs/zh/sql-reference/sql-functions/math-functions/positive.md
index bbe47c9b1d0f5d..8c2fbd0259fdbb 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/positive.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/positive.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # positive
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/pow.md b/docs/zh/sql-reference/sql-functions/math-functions/pow.md
index 1c1f6d3cd0ae75..f1213088434e91 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/pow.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/pow.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # pow, power, dpow, fpow
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/radians.md b/docs/zh/sql-reference/sql-functions/math-functions/radians.md
index 7e9735016e9bee..4e8e485ae707a5 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/radians.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/radians.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # radians
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/rand.md b/docs/zh/sql-reference/sql-functions/math-functions/rand.md
index 958f5b6a73db67..76e361296e153e 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/rand.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/rand.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # rand, random
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/round.md b/docs/zh/sql-reference/sql-functions/math-functions/round.md
index 253dcb71e6e990..41612db63254cb 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/round.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/round.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # round, dround
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/sign.md b/docs/zh/sql-reference/sql-functions/math-functions/sign.md
index e4a6e05bad86f2..0f7a984106b453 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/sign.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/sign.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # sign
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/sin.md b/docs/zh/sql-reference/sql-functions/math-functions/sin.md
index a0164e20c8b5a2..75672c5d725d72 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/sin.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/sin.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # sin
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/sinh.md b/docs/zh/sql-reference/sql-functions/math-functions/sinh.md
index d5a09d2638973a..8620f36f22b587 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/sinh.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/sinh.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # sinh
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/sqrt.md b/docs/zh/sql-reference/sql-functions/math-functions/sqrt.md
index 7380dc99f16c3b..fdec6e8439b29c 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/sqrt.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/sqrt.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # sqrt, dsqrt
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/square.md b/docs/zh/sql-reference/sql-functions/math-functions/square.md
index a010ab3eac72dc..c2ba91050796e7 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/square.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/square.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # SQUARE
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/tan.md b/docs/zh/sql-reference/sql-functions/math-functions/tan.md
index c136d0c9aa02cf..fbc01168835ecd 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/tan.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/tan.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # tan
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/tanh.md b/docs/zh/sql-reference/sql-functions/math-functions/tanh.md
index bb196ae889e4f0..7a96b0c16fe9cc 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/tanh.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/tanh.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # tanh
diff --git a/docs/zh/sql-reference/sql-functions/math-functions/truncate.md b/docs/zh/sql-reference/sql-functions/math-functions/truncate.md
index 5a439ffbbc46e8..daff56a465439a 100644
--- a/docs/zh/sql-reference/sql-functions/math-functions/truncate.md
+++ b/docs/zh/sql-reference/sql-functions/math-functions/truncate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # truncate
diff --git a/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_approx.mdx b/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_approx.mdx
index e095334a0bcac4..a2913df6e66eab 100644
--- a/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_approx.mdx
+++ b/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_approx.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: percentile_approx
 title: percentile_approx
 ---
diff --git a/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_approx_raw.md b/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_approx_raw.md
index 99cd2cc763985e..bba166290a361b 100644
--- a/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_approx_raw.md
+++ b/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_approx_raw.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # percentile_approx_raw
diff --git a/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_cont.mdx b/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_cont.mdx
index cd8a32edcd9e4d..1ed34cbdc5cc6e 100644
--- a/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_cont.mdx
+++ b/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_cont.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: percentile_cont
 title: percentile_cont
 ---
diff --git a/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_disc.mdx b/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_disc.mdx
index d18a86c09258fe..7a4385ac31fe02 100644
--- a/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_disc.mdx
+++ b/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_disc.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: percentile_disc
 title: percentile_disc
 ---
diff --git a/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_empty.md b/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_empty.md
index b5f5b71ad51834..1990cf14011c7c 100644
--- a/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_empty.md
+++ b/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_empty.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # percentile_empty
diff --git a/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_hash.md b/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_hash.md
index d3396fc2c0d47d..0a29e935df6af2 100644
--- a/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_hash.md
+++ b/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_hash.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # percentile_hash
diff --git a/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_union.md b/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_union.md
index 484a34de1b6421..a39927878ade73 100644
--- a/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_union.md
+++ b/docs/zh/sql-reference/sql-functions/percentile-functions/percentile_union.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # percentile_union
diff --git a/docs/zh/sql-reference/sql-functions/scalar-functions/hll_cardinality.md b/docs/zh/sql-reference/sql-functions/scalar-functions/hll_cardinality.md
index da335070a29b7b..90ea2f80759239 100644
--- a/docs/zh/sql-reference/sql-functions/scalar-functions/hll_cardinality.md
+++ b/docs/zh/sql-reference/sql-functions/scalar-functions/hll_cardinality.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # hll_cardinality
diff --git a/docs/zh/sql-reference/sql-functions/scalar-functions/hll_empty.md b/docs/zh/sql-reference/sql-functions/scalar-functions/hll_empty.md
index bc2043e4705f68..ac51ce348e6621 100644
--- a/docs/zh/sql-reference/sql-functions/scalar-functions/hll_empty.md
+++ b/docs/zh/sql-reference/sql-functions/scalar-functions/hll_empty.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # hll_empty
diff --git a/docs/zh/sql-reference/sql-functions/scalar-functions/hll_hash.md b/docs/zh/sql-reference/sql-functions/scalar-functions/hll_hash.md
index a9e5e2fb6643bf..d4ec66f5a27304 100644
--- a/docs/zh/sql-reference/sql-functions/scalar-functions/hll_hash.md
+++ b/docs/zh/sql-reference/sql-functions/scalar-functions/hll_hash.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # hll_hash
diff --git a/docs/zh/sql-reference/sql-functions/spatial-functions/st_astext.md b/docs/zh/sql-reference/sql-functions/spatial-functions/st_astext.md
index 8084882b315c66..7c5f2ae5c4fe87 100644
--- a/docs/zh/sql-reference/sql-functions/spatial-functions/st_astext.md
+++ b/docs/zh/sql-reference/sql-functions/spatial-functions/st_astext.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ST_AsText, ST_AsWKT
diff --git a/docs/zh/sql-reference/sql-functions/spatial-functions/st_circle.md b/docs/zh/sql-reference/sql-functions/spatial-functions/st_circle.md
index df7946d2933965..a78734a18b0115 100644
--- a/docs/zh/sql-reference/sql-functions/spatial-functions/st_circle.md
+++ b/docs/zh/sql-reference/sql-functions/spatial-functions/st_circle.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ST_Circle
diff --git a/docs/zh/sql-reference/sql-functions/spatial-functions/st_contains.md b/docs/zh/sql-reference/sql-functions/spatial-functions/st_contains.md
index 52af6de55d83c3..86e0641c66dca7 100644
--- a/docs/zh/sql-reference/sql-functions/spatial-functions/st_contains.md
+++ b/docs/zh/sql-reference/sql-functions/spatial-functions/st_contains.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ST_Contains
diff --git a/docs/zh/sql-reference/sql-functions/spatial-functions/st_distance_sphere.md b/docs/zh/sql-reference/sql-functions/spatial-functions/st_distance_sphere.md
index ed463bb40f1aa9..cdec95cceafef1 100644
--- a/docs/zh/sql-reference/sql-functions/spatial-functions/st_distance_sphere.md
+++ b/docs/zh/sql-reference/sql-functions/spatial-functions/st_distance_sphere.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ST_Distance_Sphere
diff --git a/docs/zh/sql-reference/sql-functions/spatial-functions/st_geometryfromtext.md b/docs/zh/sql-reference/sql-functions/spatial-functions/st_geometryfromtext.md
index f037ef1e89728e..6add215694fa73 100644
--- a/docs/zh/sql-reference/sql-functions/spatial-functions/st_geometryfromtext.md
+++ b/docs/zh/sql-reference/sql-functions/spatial-functions/st_geometryfromtext.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ST_GeometryFromText, ST_GeomFromText
diff --git a/docs/zh/sql-reference/sql-functions/spatial-functions/st_linefromtext.md b/docs/zh/sql-reference/sql-functions/spatial-functions/st_linefromtext.md
index 778ddd13e2c3c4..4c3a5adec4a5e6 100644
--- a/docs/zh/sql-reference/sql-functions/spatial-functions/st_linefromtext.md
+++ b/docs/zh/sql-reference/sql-functions/spatial-functions/st_linefromtext.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ST_LineFromText, ST_LineStringFromText
diff --git a/docs/zh/sql-reference/sql-functions/spatial-functions/st_point.md b/docs/zh/sql-reference/sql-functions/spatial-functions/st_point.md
index e2813833da8ce2..c78298d1079eee 100644
--- a/docs/zh/sql-reference/sql-functions/spatial-functions/st_point.md
+++ b/docs/zh/sql-reference/sql-functions/spatial-functions/st_point.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ST_Point
diff --git a/docs/zh/sql-reference/sql-functions/spatial-functions/st_polygon.md b/docs/zh/sql-reference/sql-functions/spatial-functions/st_polygon.md
index 336b4ec47d93cd..2567f90ef254c3 100644
--- a/docs/zh/sql-reference/sql-functions/spatial-functions/st_polygon.md
+++ b/docs/zh/sql-reference/sql-functions/spatial-functions/st_polygon.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ST_Polygon, ST_PolyFromText, ST_PolygonFromText
diff --git a/docs/zh/sql-reference/sql-functions/spatial-functions/st_x.md b/docs/zh/sql-reference/sql-functions/spatial-functions/st_x.md
index 6feb6e08cd2aea..81fa6c66626c9a 100644
--- a/docs/zh/sql-reference/sql-functions/spatial-functions/st_x.md
+++ b/docs/zh/sql-reference/sql-functions/spatial-functions/st_x.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ST_X
diff --git a/docs/zh/sql-reference/sql-functions/spatial-functions/st_y.md b/docs/zh/sql-reference/sql-functions/spatial-functions/st_y.md
index 8872669eb6decc..2d86d82a62dc11 100644
--- a/docs/zh/sql-reference/sql-functions/spatial-functions/st_y.md
+++ b/docs/zh/sql-reference/sql-functions/spatial-functions/st_y.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ST_Y
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/append_trailing_char_if_absent.md b/docs/zh/sql-reference/sql-functions/string-functions/append_trailing_char_if_absent.md
index 00544efdd6eec1..c370ad53810c54 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/append_trailing_char_if_absent.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/append_trailing_char_if_absent.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # append_trailing_char_if_absent
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/ascii.md b/docs/zh/sql-reference/sql-functions/string-functions/ascii.md
index a9fddab913c274..23b357800a3f8d 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/ascii.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/ascii.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ascii
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/char.md b/docs/zh/sql-reference/sql-functions/string-functions/char.md
index 4064d0eac3e94e..857eb693fa6721 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/char.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/char.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # char
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/char_length.md b/docs/zh/sql-reference/sql-functions/string-functions/char_length.md
index 3c39478219df63..ab943eb34c865b 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/char_length.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/char_length.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # char_length
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/character_length.md b/docs/zh/sql-reference/sql-functions/string-functions/character_length.md
index a442288f970e2f..8622c2791e414e 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/character_length.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/character_length.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # character_length
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/concat.md b/docs/zh/sql-reference/sql-functions/string-functions/concat.md
index 3ed1e516871acc..eb453749c8ecc7 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/concat.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/concat.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # concat
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/concat_ws.md b/docs/zh/sql-reference/sql-functions/string-functions/concat_ws.md
index 8cb4c4e5a427cc..6b2f5a493f1ec0 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/concat_ws.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/concat_ws.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # concat_ws
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/crc32.md b/docs/zh/sql-reference/sql-functions/string-functions/crc32.md
index bd73060d0e2402..459bcd9f858cad 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/crc32.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/crc32.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # crc32
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/ends_with.md b/docs/zh/sql-reference/sql-functions/string-functions/ends_with.md
index c38d68b114cd9e..853fa3d7255522 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/ends_with.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/ends_with.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ends_with
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/find_in_set.md b/docs/zh/sql-reference/sql-functions/string-functions/find_in_set.md
index 6d70c17afdee99..7e7fdcb475d9ea 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/find_in_set.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/find_in_set.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # find_in_set
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/group_concat.md b/docs/zh/sql-reference/sql-functions/string-functions/group_concat.md
index d9c24da8cd0e5e..23fd0a765021bd 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/group_concat.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/group_concat.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # group_concat
@@ -33,7 +33,7 @@ VARCHAR GROUP_CONCAT([DISTINCT] expr [,expr ...]
 
 返回值的数据类型为 VARCHAR。如果没有非 NULL 值，则返回 NULL。
 
-您可以使用系统变量 [group_concat_max_len](../../../reference/System_variable.md#group_concat_max_len) 来控制可以返回的最大字符长度。默认值：1024。最小值：4。单位：字符。
+您可以使用系统变量 [group_concat_max_len](../../System_variable.md#group_concat_max_len) 来控制可以返回的最大字符长度。默认值：1024。最小值：4。单位：字符。
 
 变量的设置方法：
 
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/hex.md b/docs/zh/sql-reference/sql-functions/string-functions/hex.md
index 72708b683c1c1f..f37455068ca11e 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/hex.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/hex.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # hex
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/hex_decode_binary.md b/docs/zh/sql-reference/sql-functions/string-functions/hex_decode_binary.md
index 1d686138060c48..995b1c14d5008f 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/hex_decode_binary.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/hex_decode_binary.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # hex_decode_binary
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/hex_decode_string.md b/docs/zh/sql-reference/sql-functions/string-functions/hex_decode_string.md
index 981b17dbbecfe2..281f846f3c1b4c 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/hex_decode_string.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/hex_decode_string.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # hex_decode_string
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/instr.md b/docs/zh/sql-reference/sql-functions/string-functions/instr.md
index db3595cfe4441b..f44f367cc6e396 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/instr.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/instr.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # instr
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/lcase.md b/docs/zh/sql-reference/sql-functions/string-functions/lcase.md
index 2423f33812b0d5..4be72f47a82da7 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/lcase.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/lcase.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # lcase
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/left.md b/docs/zh/sql-reference/sql-functions/string-functions/left.md
index 2d1f15c3451d5b..f712c0f84e209a 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/left.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/left.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # left
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/length.md b/docs/zh/sql-reference/sql-functions/string-functions/length.md
index 04a0413b547e91..a686a231fcb452 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/length.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/length.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # length
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/locate.md b/docs/zh/sql-reference/sql-functions/string-functions/locate.md
index 7a87a34b325169..558e2b53ff56a9 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/locate.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/locate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # locate
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/lower.md b/docs/zh/sql-reference/sql-functions/string-functions/lower.md
index d8257543e0a3de..94ac0d1f1ca335 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/lower.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/lower.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # lower
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/lpad.md b/docs/zh/sql-reference/sql-functions/string-functions/lpad.md
index 8354453b1b0bff..a35b07178b0441 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/lpad.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/lpad.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # lpad
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/ltrim.md b/docs/zh/sql-reference/sql-functions/string-functions/ltrim.md
index e26ab430578dc1..69bef33450ad58 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/ltrim.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/ltrim.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ltrim
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/money_format.md b/docs/zh/sql-reference/sql-functions/string-functions/money_format.md
index 7ae95825dc39bc..21d0f3d20f3459 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/money_format.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/money_format.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # money_format
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/ngram_search.md b/docs/zh/sql-reference/sql-functions/string-functions/ngram_search.md
index 60dedaf5c055ab..9cd57893ba4faf 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/ngram_search.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/ngram_search.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ngram_search
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/null_or_empty.md b/docs/zh/sql-reference/sql-functions/string-functions/null_or_empty.md
index 818f466e157441..72de0fcbe060cd 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/null_or_empty.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/null_or_empty.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # null_or_empty
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/parse_url.md b/docs/zh/sql-reference/sql-functions/string-functions/parse_url.md
index 3f7d2529b95cb2..8c6c480f60c1d0 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/parse_url.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/parse_url.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # parse_url
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/regexp_split.md b/docs/zh/sql-reference/sql-functions/string-functions/regexp_split.md
index df0ecc22f0f427..c4c9dff7703277 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/regexp_split.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/regexp_split.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # regexp_split
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/repeat.md b/docs/zh/sql-reference/sql-functions/string-functions/repeat.md
index 752bc8b9b74fcc..f5f7f50a1a6c5b 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/repeat.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/repeat.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # repeat
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/replace.md b/docs/zh/sql-reference/sql-functions/string-functions/replace.md
index 0f3aed205b5d29..6cb88f171f0838 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/replace.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/replace.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # replace
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/reverse.md b/docs/zh/sql-reference/sql-functions/string-functions/reverse.md
index c54012d08275bb..bd168f5fc2681a 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/reverse.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/reverse.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # reverse
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/right.md b/docs/zh/sql-reference/sql-functions/string-functions/right.md
index 9049091dbff4c6..968e7111bb299f 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/right.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/right.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # right
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/rpad.md b/docs/zh/sql-reference/sql-functions/string-functions/rpad.md
index 0f5b09175c0057..396b434c4cfd5f 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/rpad.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/rpad.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # rpad
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/rtrim.md b/docs/zh/sql-reference/sql-functions/string-functions/rtrim.md
index 4dc22e986d995c..57f394b6453fb4 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/rtrim.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/rtrim.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # rtrim
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/space.md b/docs/zh/sql-reference/sql-functions/string-functions/space.md
index ea02d6d5129ef7..d71ec80bd17247 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/space.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/space.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # space
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/split.md b/docs/zh/sql-reference/sql-functions/string-functions/split.md
index 136814b5b6b626..f0591f8e5b103a 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/split.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/split.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # split
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/split_part.md b/docs/zh/sql-reference/sql-functions/string-functions/split_part.md
index a8b17c04d4f9a2..1ac5fbf43a4752 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/split_part.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/split_part.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # split_part
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/starts_with.md b/docs/zh/sql-reference/sql-functions/string-functions/starts_with.md
index fb03db800640a6..1cd08415c881bf 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/starts_with.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/starts_with.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # starts_with
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/str_to_map.md b/docs/zh/sql-reference/sql-functions/string-functions/str_to_map.md
index f690dfe0a301e9..3b0a9194dc36c8 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/str_to_map.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/str_to_map.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # str_to_map
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/strleft.md b/docs/zh/sql-reference/sql-functions/string-functions/strleft.md
index 03799f5588c34b..4a39804e81b965 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/strleft.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/strleft.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # strleft
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/strright.md b/docs/zh/sql-reference/sql-functions/string-functions/strright.md
index 67b3197b96eddd..5a6faa5fa4e924 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/strright.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/strright.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # strright
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/substring.md b/docs/zh/sql-reference/sql-functions/string-functions/substring.md
index 824ae06be879f5..efc9691778b525 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/substring.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/substring.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # substr, substring
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/substring_index.md b/docs/zh/sql-reference/sql-functions/string-functions/substring_index.md
index 5dea1cbac6db18..d0731f497541b5 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/substring_index.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/substring_index.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # substring_index
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/translate.md b/docs/zh/sql-reference/sql-functions/string-functions/translate.md
index 09d417a6a04b86..9a8f3c33e1d43f 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/translate.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/translate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # translate
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/trim.md b/docs/zh/sql-reference/sql-functions/string-functions/trim.md
index 6e70f6ede9c829..1a3e59f83ce3e7 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/trim.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/trim.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # trim
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/ucase.md b/docs/zh/sql-reference/sql-functions/string-functions/ucase.md
index e63a79b597a1a3..a9fc6152a948f9 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/ucase.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/ucase.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ucase
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/unhex.md b/docs/zh/sql-reference/sql-functions/string-functions/unhex.md
index 4f3d5a68ba618b..54895389770733 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/unhex.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/unhex.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # unhex
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/upper.md b/docs/zh/sql-reference/sql-functions/string-functions/upper.md
index ff71c9da7b2a82..af824265d2e2b0 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/upper.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/upper.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # upper
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/url_decode.md b/docs/zh/sql-reference/sql-functions/string-functions/url_decode.md
index 0238fe9fe7998a..269544e64d1cfe 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/url_decode.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/url_decode.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # url_decode
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/url_encode.md b/docs/zh/sql-reference/sql-functions/string-functions/url_encode.md
index 214f2a8e1014dc..68394ba99df90d 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/url_encode.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/url_encode.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # url_encode
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/url_extract_host.md b/docs/zh/sql-reference/sql-functions/string-functions/url_extract_host.md
index 0ee5a972acf9f7..736dd51ae2f590 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/url_extract_host.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/url_extract_host.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # url_extract_host
diff --git a/docs/zh/sql-reference/sql-functions/string-functions/url_extract_parameter.md b/docs/zh/sql-reference/sql-functions/string-functions/url_extract_parameter.md
index cd12621cc7fa4d..611a453ef05c36 100644
--- a/docs/zh/sql-reference/sql-functions/string-functions/url_extract_parameter.md
+++ b/docs/zh/sql-reference/sql-functions/string-functions/url_extract_parameter.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # url_extract_parameter
diff --git a/docs/zh/sql-reference/sql-functions/struct-functions/named_struct.md b/docs/zh/sql-reference/sql-functions/struct-functions/named_struct.md
index 3653fc44aa672c..cff03cd39e23e3 100644
--- a/docs/zh/sql-reference/sql-functions/struct-functions/named_struct.md
+++ b/docs/zh/sql-reference/sql-functions/struct-functions/named_struct.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # named_struct
diff --git a/docs/zh/sql-reference/sql-functions/struct-functions/row.md b/docs/zh/sql-reference/sql-functions/struct-functions/row.md
index bd11913904efb8..efce8da91ccddd 100644
--- a/docs/zh/sql-reference/sql-functions/struct-functions/row.md
+++ b/docs/zh/sql-reference/sql-functions/struct-functions/row.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # row
diff --git a/docs/zh/sql-reference/sql-functions/table-functions/files.md b/docs/zh/sql-reference/sql-functions/table-functions/files.md
index 0830d893c9d6c5..052e7982e69e54 100644
--- a/docs/zh/sql-reference/sql-functions/table-functions/files.md
+++ b/docs/zh/sql-reference/sql-functions/table-functions/files.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # FILES
@@ -8,7 +8,7 @@ displayed_sidebar: "Chinese"
 
 定义远程存储中的数据文件。
 
-从 v3.1.0 版本开始，StarRocks 支持使用表函数 FILES() 在远程存储中定义只读文件。该函数根据给定的数据路径等参数读取数据，并自动根据数据文件的格式、列信息等推断出 Table Schema，最终以数据行形式返回文件中的数据。您可以通过 [SELECT](../../sql-statements/data-manipulation/SELECT.md) 直接直接查询该数据，通过 [INSERT](../../sql-statements/data-manipulation/INSERT.md) 导入数据，或通过 [CREATE TABLE AS SELECT](../../sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md) 建表并导入数据。
+从 v3.1.0 版本开始，StarRocks 支持使用表函数 FILES() 在远程存储中定义只读文件。该函数根据给定的数据路径等参数读取数据，并自动根据数据文件的格式、列信息等推断出 Table Schema，最终以数据行形式返回文件中的数据。您可以通过 [SELECT](../../sql-statements/table_bucket_part_index/SELECT.md) 直接直接查询该数据，通过 [INSERT](../../sql-statements/loading_unloading/INSERT.md) 导入数据，或通过 [CREATE TABLE AS SELECT](../../sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md) 建表并导入数据。
 
 从 v3.2.0 版本开始，FILES() 写入数据至远程存储。您可以[使用 INSERT INTO FILES() 将数据从 StarRocks 导出到远程存储](../../../unloading/unload_using_insert_into_files.md)。
 
diff --git a/docs/zh/sql-reference/sql-functions/table-functions/generate_series.md b/docs/zh/sql-reference/sql-functions/table-functions/generate_series.md
index e7a8f619d42d37..b669ecf1fbfa25 100644
--- a/docs/zh/sql-reference/sql-functions/table-functions/generate_series.md
+++ b/docs/zh/sql-reference/sql-functions/table-functions/generate_series.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # generate_series
diff --git a/docs/zh/sql-reference/sql-functions/utility-functions/catalog.md b/docs/zh/sql-reference/sql-functions/utility-functions/catalog.md
index 53680689e5c70e..d08e0156df5cbf 100644
--- a/docs/zh/sql-reference/sql-functions/utility-functions/catalog.md
+++ b/docs/zh/sql-reference/sql-functions/utility-functions/catalog.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # catalog
@@ -55,4 +55,4 @@ select catalog();
 
 ## 相关 SQL
 
-[SET CATALOG](../../sql-statements/data-definition/SET_CATALOG.md)：切换到指定 Catalog。
+[SET CATALOG](../../sql-statements/Catalog/SET_CATALOG.md)：切换到指定 Catalog。
diff --git a/docs/zh/sql-reference/sql-functions/utility-functions/current_role.md b/docs/zh/sql-reference/sql-functions/utility-functions/current_role.md
index 68763506616565..903a5d98b9a880 100644
--- a/docs/zh/sql-reference/sql-functions/utility-functions/current_role.md
+++ b/docs/zh/sql-reference/sql-functions/utility-functions/current_role.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # current_role
diff --git a/docs/zh/sql-reference/sql-functions/utility-functions/current_version.md b/docs/zh/sql-reference/sql-functions/utility-functions/current_version.md
index 246032203f04d5..366f7c1cdd7f14 100644
--- a/docs/zh/sql-reference/sql-functions/utility-functions/current_version.md
+++ b/docs/zh/sql-reference/sql-functions/utility-functions/current_version.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # current_version
diff --git a/docs/zh/sql-reference/sql-functions/utility-functions/database.md b/docs/zh/sql-reference/sql-functions/utility-functions/database.md
index a8d26682c60576..e6fe72f3b01127 100644
--- a/docs/zh/sql-reference/sql-functions/utility-functions/database.md
+++ b/docs/zh/sql-reference/sql-functions/utility-functions/database.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # database
@@ -39,4 +39,4 @@ select database();
 
 ## 相关 SQL
 
-[USE](../../sql-statements/data-definition/USE.md)：切换到指定数据库。
+[USE](../../sql-statements/Database/USE.md)：切换到指定数据库。
diff --git a/docs/zh/sql-reference/sql-functions/utility-functions/get_query_profile.md b/docs/zh/sql-reference/sql-functions/utility-functions/get_query_profile.md
index 3580e10a0509ad..a37b0bd17eb3a7 100644
--- a/docs/zh/sql-reference/sql-functions/utility-functions/get_query_profile.md
+++ b/docs/zh/sql-reference/sql-functions/utility-functions/get_query_profile.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # get_query_profile
diff --git a/docs/zh/sql-reference/sql-functions/utility-functions/host_name.md b/docs/zh/sql-reference/sql-functions/utility-functions/host_name.md
index f2284bf2d7e282..8cdcaf26692722 100644
--- a/docs/zh/sql-reference/sql-functions/utility-functions/host_name.md
+++ b/docs/zh/sql-reference/sql-functions/utility-functions/host_name.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # host_name
diff --git a/docs/zh/sql-reference/sql-functions/utility-functions/is_role_in_session.md b/docs/zh/sql-reference/sql-functions/utility-functions/is_role_in_session.md
index b5ce51154f1efa..10d56d359e7902 100644
--- a/docs/zh/sql-reference/sql-functions/utility-functions/is_role_in_session.md
+++ b/docs/zh/sql-reference/sql-functions/utility-functions/is_role_in_session.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # is_role_in_session
diff --git a/docs/zh/sql-reference/sql-functions/utility-functions/isnotnull.md b/docs/zh/sql-reference/sql-functions/utility-functions/isnotnull.md
index 8ff4d2ee5e7560..9ee65bfa9babd1 100644
--- a/docs/zh/sql-reference/sql-functions/utility-functions/isnotnull.md
+++ b/docs/zh/sql-reference/sql-functions/utility-functions/isnotnull.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # isnotnull
diff --git a/docs/zh/sql-reference/sql-functions/utility-functions/isnull.md b/docs/zh/sql-reference/sql-functions/utility-functions/isnull.md
index ba68fd712a14c2..77298c0e3c980f 100644
--- a/docs/zh/sql-reference/sql-functions/utility-functions/isnull.md
+++ b/docs/zh/sql-reference/sql-functions/utility-functions/isnull.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # isnull
diff --git a/docs/zh/sql-reference/sql-functions/utility-functions/last_query_id.md b/docs/zh/sql-reference/sql-functions/utility-functions/last_query_id.md
index a93b041e55f079..8021774ed35483 100644
--- a/docs/zh/sql-reference/sql-functions/utility-functions/last_query_id.md
+++ b/docs/zh/sql-reference/sql-functions/utility-functions/last_query_id.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # last_query_id
diff --git a/docs/zh/sql-reference/sql-functions/utility-functions/sleep.md b/docs/zh/sql-reference/sql-functions/utility-functions/sleep.md
index b640b4391bde4e..aafbf444f4f558 100644
--- a/docs/zh/sql-reference/sql-functions/utility-functions/sleep.md
+++ b/docs/zh/sql-reference/sql-functions/utility-functions/sleep.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # sleep
diff --git a/docs/zh/sql-reference/sql-functions/utility-functions/uuid.md b/docs/zh/sql-reference/sql-functions/utility-functions/uuid.md
index a49093222d2be4..89e597f689d0b3 100644
--- a/docs/zh/sql-reference/sql-functions/utility-functions/uuid.md
+++ b/docs/zh/sql-reference/sql-functions/utility-functions/uuid.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # uuid
diff --git a/docs/zh/sql-reference/sql-functions/utility-functions/uuid_numeric.md b/docs/zh/sql-reference/sql-functions/utility-functions/uuid_numeric.md
index 8d6462a1546263..6b74fb40730c6c 100644
--- a/docs/zh/sql-reference/sql-functions/utility-functions/uuid_numeric.md
+++ b/docs/zh/sql-reference/sql-functions/utility-functions/uuid_numeric.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # uuid_numeric
diff --git a/docs/zh/sql-reference/sql-functions/utility-functions/version.md b/docs/zh/sql-reference/sql-functions/utility-functions/version.md
index a5c56b91b59eb6..53b3313a47c7aa 100644
--- a/docs/zh/sql-reference/sql-functions/utility-functions/version.md
+++ b/docs/zh/sql-reference/sql-functions/utility-functions/version.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # version
diff --git a/docs/zh/sql-reference/sql-statements/Administration/ADD_BACKEND_BLACKLIST.md b/docs/zh/sql-reference/sql-statements/Administration/ADD_BACKEND_BLACKLIST.md
deleted file mode 100644
index 0e9c8c646edca6..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/ADD_BACKEND_BLACKLIST.md
+++ /dev/null
@@ -1,49 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# ADD BACKEND BLACKLIST
-
-## 功能
-
-将一个 BE 节点添加到 BE 黑名单中。您可以手动将 BE 节点添加到黑名单中，禁止在查询执行中使用该节点，从而避免由于节点断连而引起的查询超时失败或其他意外行为。
-
-此功能自 v3.3.0 起支持。更多信息，参考[管理 BE 黑名单](../../../administration/management/BE_blacklist.md)。
-
-:::note
-
-该操作需要有 SYSTEM 级 BLACKLIST 权限。
-
-:::
-
-默认情况下，StarRocks 可以自动管理 BE 黑名单，将断连的 BE 节点添加到黑名单中，并在重新连接成功时将其从黑名单中移除。但 StarRocks 不会主动将用户手动加入黑名单的节点移除。
-
-## 语法
-
-```SQL
-ADD BACKEND BLACKLIST <be_id>[, ...]
-```
-
-## 参数说明
-
-`be_id`：要添加到黑名单中的 BE 节点的 ID。您可以通过执行 [SHOW BACKENDS](./SHOW_BACKENDS.md) 语句来获取 BE 节点的 ID。
-
-## 示例
-
-```SQL
--- 获取 BE ID。
-SHOW BACKENDS\G
-*************************** 1. row ***************************
-            BackendId: 10001
-                   IP: xxx.xx.xx.xxx
-                   ...
--- 添加 BE 节点至黑名单。
-ADD BACKEND BLACKLIST 10001;
-```
-
-## 相关 SQL
-
-- [DELETE BACKEND BLACKLIST](./DELETE_BACKEND_BLACKLIST.md)
-- [SHOW BACKEND BLACKLIST](./SHOW_BACKEND_BLACKLIST.md)
-- [SHOW BACKENDS](./SHOW_BACKENDS.md)
-
diff --git a/docs/zh/sql-reference/sql-statements/Administration/ADD_SQLBLACKLIST.md b/docs/zh/sql-reference/sql-statements/Administration/ADD_SQLBLACKLIST.md
deleted file mode 100644
index c539f2267ce115..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/ADD_SQLBLACKLIST.md
+++ /dev/null
@@ -1,63 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# ADD SQLBLACKLIST
-
-## 功能
-
-将一个 SQL 正则表达式添加至 SQL 黑名单。启用 SQL 黑名单功能后，StarRocks 会将所有需要执行的 SQL 语句与黑名单中的 SQL 正则表达式进行比较。StarRocks 不会执行与黑名单中任何正则表达式相匹配的 SQL，并返回错误。
-
-有关 SQL 黑名单的更多信息，请参阅 [管理 SQL 黑名单](../../../administration/management/resource_management/Blacklist.md)。
-
-:::tip
-
-- 该操作需要 SYSTEM 级的 BLACKLIST 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-- 当前 StarRocks 支持将 SELECT 语句加入 SQL 黑名单。
-:::
-
-## 语法
-
-```SQL
-ADD SQLBLACKLIST "<sql_reg_expr>"
-```
-
-## 参数说明
-
-`sql_reg_expr`：用于指定 SQL 语句的正则表达式。为了区分 SQL 语句中的特殊字符和正则表达式中的特殊字符，您需要使用转义符（\）作为 SQL 语句中特殊字符的前缀，如 `(`、`)` 以及 `+`。由于 `(` 和 `)` 在 SQL 语句中经常被使用，StarRocks 可以直接识别 SQL 语句中的 `(` 和 `)`。所以您无需为 `(` 和 `)` 添加转义符。
-
-## 示例
-
-示例一：将 `count(\*)` 添加到 SQL 黑名单。
-
-```Plain
-mysql> ADD SQLBLACKLIST "select count(\\*) from .+";
-```
-
-示例二：将 `count(distinct )` 添加到 SQL 黑名单。
-
-```Plain
-mysql> ADD SQLBLACKLIST "select count(distinct .+) from .+";
-```
-
-示例三：将 `order by limit x, y，1 <= x <=7, 5 <=y <=7` 加入SQL黑名单。
-
-```Plain
-mysql> ADD SQLBLACKLIST "select id_int from test_all_type_select1 
-    order by id_int 
-    limit [1-7], [5-7]";
-```
-
-示例四：将复杂的 SQL 正则表达式添加到 SQL 黑名单中。该示例是为了演示如何使用转义符来表示 SQL 语句中的 `*` 和 `-`。
-
-```Plain
-mysql> ADD SQLBLACKLIST 
-    "select id_int \\* 4, id_tinyint, id_varchar 
-        from test_all_type_nullable 
-    except select id_int, id_tinyint, id_varchar 
-        from test_basic 
-    except select (id_int \\* 9 \\- 8) \\/ 2, id_tinyint, id_varchar 
-        from test_all_type_nullable2 
-    except select id_int, id_tinyint, id_varchar 
-        from test_basic_nullable";
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_CANCEL_REPAIR.md b/docs/zh/sql-reference/sql-statements/Administration/ADMIN_CANCEL_REPAIR.md
deleted file mode 100644
index 617207e748c45b..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_CANCEL_REPAIR.md
+++ /dev/null
@@ -1,31 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# ADMIN CANCEL REPAIR
-
-## 功能
-
-该语句用于取消以高优先级修复指定表或分区。
-
-:::tip
-
-该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```sql
-ADMIN CANCEL REPAIR TABLE table_name[ PARTITION (p1,...)]
-```
-
-说明：该语句仅表示系统不再以高优先级修复指定表或分区的分片副本。系统仍会以默认调度方式修复副本。
-
-## 示例
-
-取消高优先级修复。
-
-```sql
-ADMIN CANCEL REPAIR TABLE tbl PARTITION(p1);
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_CHECK_TABLET.md b/docs/zh/sql-reference/sql-statements/Administration/ADMIN_CHECK_TABLET.md
deleted file mode 100644
index b2552465fdec38..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_CHECK_TABLET.md
+++ /dev/null
@@ -1,38 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# ADMIN CHECK TABLET
-
-## 功能
-
-该语句用于对一组 tablet 执行指定的检查操作。
-
-:::tip
-
-该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```sql
-ADMIN CHECK TABLET (tablet_id1, tablet_id2, ...)
-PROPERTIES("type" = "...")
-```
-
-说明：
-
-1. 必须指定 tablet id 列表以及 PROPERTIES 中的 type 属性。
-2. 目前 type 仅支持：
-
-     **consistency**: 对 tablet 的副本数据一致性进行检查。该命令为异步命令，发送后，StarRocks 会开始执行对应 tablet 的一致性检查作业。最终的结果，将体现在 `SHOW PROC "/statistic";` 结果中的 InconsistentTabletNum 列。
-
-## 示例
-
-1. 对指定的一组 tablet 进行副本数据一致性检查
-
-    ```sql
-    ADMIN CHECK TABLET (10000, 10001)
-    PROPERTIES("type" = "consistency");
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_REPAIR.md b/docs/zh/sql-reference/sql-statements/Administration/ADMIN_REPAIR.md
deleted file mode 100644
index fc839a73e45c26..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_REPAIR.md
+++ /dev/null
@@ -1,40 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# ADMIN REPAIR
-
-## 功能
-
-该语句用于尝试优先修复指定的表或分区。
-
-:::tip
-
-该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```sql
-ADMIN REPAIR TABLE table_name[ PARTITION (p1,...)]
-```
-
-说明：
-
-1. 该语句仅表示让系统尝试以高优先级修复指定表或分区的分片副本，并不保证能够修复成功。用户可以通过 `ADMIN SHOW REPLICA STATUS;` 命令查看修复情况。
-2. 默认的 timeout 是 14400 秒(4 小时)。超时意味着系统将不再以高优先级修复指定表或分区的分片副本。需要重新使用该命令设置。
-
-## 示例
-
-1. 尝试修复指定表
-
-    ```sql
-    ADMIN REPAIR TABLE tbl1;
-    ```
-
-2. 尝试修复指定分区
-
-    ```sql
-    ADMIN REPAIR TABLE tbl1 PARTITION (p1, p2);
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md b/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md
deleted file mode 100644
index 90309c0e48d410..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md
+++ /dev/null
@@ -1,33 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# ADMIN SET CONFIG
-
-## 功能
-
-该语句用于设置集群的配置项（当前仅支持设置 FE 的配置项）。
-
-可设置的配置项，可以通过 [ADMIN SHOW FRONTEND CONFIG](ADMIN_SHOW_CONFIG.md) 命令查看。
-
-设置后的配置项，在 FE 重启之后会恢复成 **fe.conf** 文件中的配置或者默认值。如果需要让配置长期生效，建议设置完之后同时修改 **fe.conf** 文件，防止重启后修改失效。
-
-:::tip
-
-该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```sql
-ADMIN SET FRONTEND CONFIG ("key" = "value")
-```
-
-## 示例
-
-设置 `tablet_sched_disable_balance` 为 `true`。
-
-```sql
- ADMIN SET FRONTEND CONFIG ("tablet_sched_disable_balance" = "true");
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SET_PARTITION_VERSION.md b/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SET_PARTITION_VERSION.md
deleted file mode 100644
index 8a5a89cd3065c4..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SET_PARTITION_VERSION.md
+++ /dev/null
@@ -1,51 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# ADMIN SET PARTITION VERSION
-
-## 功能
-
-手动设置分区的版本。
-
-请注意，手动设置分区版本是一项危险操作，仅建议在集群元数据出现问题时才使用该方式。在正常情况下，分区的版本会自动与其内部的 Tablet 保持一致。
-
-:::tip
-
-该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```sql
-ADMIN SET TABLE <table_name> PARTITION ( <partition_name> | <partition_id> ) 
-TO VERSION <version>
-```
-
-## 参数说明
-
-- `table_name`: 分区所属表的名称。
-- `partition_name`: 分区的名称。您需要使用 `partition_name` 或 `partition_id` 来指定分区。对于非分区表，`partition_name` 与表名相同。
-- `partition_id`: 分区的 ID。您需要使用 `partition_name` 或 `partition_id` 来指定分区。对于采用随机分桶策略的表，您必须使用 `partition_id` 来指定分区。
-- `version`: 要设置的分区版本。
-
-## 示例
-
-1. 将非分区表 `t1` 的版本设置为 `10`。
-
-    ```sql
-    ADMIN SET TABLE t1 PARTITION(t1) TO VERSION 10;
-    ```
-
-2. 将表 `t2` 中分区 `p1` 的版本设置为 `10`。
-
-    ```sql
-    ADMIN SET TABLE t2 PARTITION(p1) TO VERSION 10;
-    ```
-
-3. 将 ID 为 `123456` 的分区的版本设置为 `10`。`t3` 为采用随机分桶策略的表。
-
-    ```sql
-    ADMIN SET TABLE t3 PARTITION('123456') TO VERSION 10;
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SET_REPLICA_STATUS.md b/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SET_REPLICA_STATUS.md
deleted file mode 100644
index 52cd1c1d90c120..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SET_REPLICA_STATUS.md
+++ /dev/null
@@ -1,51 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# ADMIN SET REPLICA STATUS
-
-## 功能
-
-该语句用于设置指定副本的状态。
-
-该命令目前仅用于手动将某些副本状态设置为 bad 或 ok，从而使得系统能够自动修复这些副本。
-
-:::tip
-
-该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```sql
-ADMIN SET REPLICA STATUS
-PROPERTIES ("key" = "value", ...)
-```
-
-目前支持如下属性：
-
-**tablet_id**：必需。指定一个 Tablet Id。
-
-**backend_id**：必需。指定 Backend Id。
-
-**status**：必需。指定状态。当前仅支持 "bad" 或 "ok"。
-
-如果指定的副本不存在，或状态已经是 bad，则会被忽略。
-
-**注意：**
-设置为 bad 状态的副本可能立刻被删除，请谨慎操作。
-
-## 示例
-
-1. 设置 tablet 10003 在 BE 10001 上的副本状态为 bad。
-
-    ```sql
-    ADMIN SET REPLICA STATUS PROPERTIES("tablet_id" = "10003", "backend_id" = "10001", "status" = "bad");
-    ```
-
-2. 设置 tablet 10003 在 BE 10001 上的副本状态为 ok。
-
-    ```sql
-    ADMIN SET REPLICA STATUS PROPERTIES("tablet_id" = "10003", "backend_id" = "10001", "status" = "ok");
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SHOW_CONFIG.md b/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SHOW_CONFIG.md
deleted file mode 100644
index 91a237aa825a83..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SHOW_CONFIG.md
+++ /dev/null
@@ -1,59 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# ADMIN SHOW CONFIG
-
-## 功能
-
-该语句用于展示当前集群的配置（当前仅支持展示 FE 的配置项）。
-
-关于每个配置项的含义，参见[FE 配置项](../../../administration/management/FE_configuration.md)。
-
-如果要动态设置或修改集群的配置项，参见 [ADMIN SET CONFIG](ADMIN_SET_CONFIG.md)。
-
-:::tip
-
-该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```sql
-ADMIN SHOW FRONTEND CONFIG [LIKE "pattern"]
-```
-
-说明：
-
-结果中的各列含义如下：
-
-```plain text
-1. Key         配置项名称
-2. AliasNames  配置项别名
-2. Value       配置项取值
-3. Type        配置项数据类型
-4. IsMutable   是否可以通过 ADMIN SET CONFIG 命令动态设置
-5. Comment     配置项说明
-```
-
-## 示例
-
-1. 查看当前 FE 节点的配置。
-
-    ```sql
-    ADMIN SHOW FRONTEND CONFIG;
-    ```
-
-2. 使用 like 谓词搜索当前 FE 节点的配置。
-
-    ```plain text
-    mysql> ADMIN SHOW FRONTEND CONFIG LIKE '%check_java_version%';
-    +--------------------+------------+-------+---------+-----------+---------+
-    | Key                | AliasNames | Value | Type    | IsMutable | Comment |
-    +--------------------+------------+-------+---------+-----------+---------+
-    | check_java_version | []         | true  | boolean | false     |         |
-    +--------------------+------------+-------+---------+-----------+---------+
-    1 row in set (0.00 sec)
-
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_DISTRIBUTION.md b/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_DISTRIBUTION.md
deleted file mode 100644
index 80c8298841fef4..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_DISTRIBUTION.md
+++ /dev/null
@@ -1,39 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# ADMIN SHOW REPLICA DISTRIBUTION
-
-## 功能
-
-该语句用于展示一个表或分区副本分布状态。
-
-:::tip
-
-该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```sql
-ADMIN SHOW REPLICA DISTRIBUTION FROM [db_name.]tbl_name [PARTITION (p1, ...)]
-```
-
-说明：
-
-结果中的 Graph 列以图形的形式展示副本分布比例。
-
-## 示例
-
-1. 查看表的副本分布
-
-    ```sql
-    ADMIN SHOW REPLICA DISTRIBUTION FROM tbl1;
-    ```
-
-2. 查看表的分区的副本分布
-
-    ```sql
-    ADMIN SHOW REPLICA DISTRIBUTION FROM db1.tbl1 PARTITION(p1, p2);
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_STATUS.md b/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_STATUS.md
deleted file mode 100644
index 687e7f9d58d547..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/ADMIN_SHOW_REPLICA_STATUS.md
+++ /dev/null
@@ -1,55 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# ADMIN SHOW REPLICA STATUS
-
-## 功能
-
-该语句用于展示一个表或分区的副本状态信息。
-
-:::tip
-
-该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```sql
-ADMIN SHOW REPLICA STATUS FROM [db_name.]tbl_name [PARTITION (p1, ...)]
-[WHERE STATUS [!]= "replica_status"]
-```
-
-说明：
-
-```plain text
-replica_status:
-OK:             replica 处于健康状态
-DEAD:           replica 所在 Backend 不可用
-VERSION_ERROR:  replica 数据版本有缺失
-SCHEMA_ERROR:   replica 的 schema hash 不正确
-MISSING:        replica 不存在
-```
-
-## 示例
-
-1. 查看表全部的副本状态。
-
-    ```sql
-    ADMIN SHOW REPLICA STATUS FROM db1.tbl1;
-    ```
-
-2. 查看表某个分区状态为 VERSION_ERROR 的副本。
-
-    ```sql
-    ADMIN SHOW REPLICA STATUS FROM tbl1 PARTITION (p1, p2)
-    WHERE STATUS = "VERSION_ERROR";
-    ```
-
-3. 查看表所有状态不健康的副本。
-
-    ```sql
-    ADMIN SHOW REPLICA STATUS FROM tbl1
-    WHERE STATUS != "OK";
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/ALTER_RESOURCE_GROUP.md b/docs/zh/sql-reference/sql-statements/Administration/ALTER_RESOURCE_GROUP.md
deleted file mode 100644
index ad54b743e80f10..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/ALTER_RESOURCE_GROUP.md
+++ /dev/null
@@ -1,65 +0,0 @@
----
-keywords: ['xiugai'] 
-displayed_sidebar: "Chinese"
----
-
-# ALTER RESOURCE GROUP
-
-## 功能
-
-修改资源组设置。
-
-:::tip
-
-该操作需要对应 Resource Group 的 ALTER 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```SQL
-ALTER RESOURCE GROUP <resource_group_name>
-{  ADD CLASSIFIER1, CLASSIFIER2, ...
- | DROP (CLASSIFIER_ID_1, CLASSIFIER_ID_2, ...)
- | DROP ALL
- | WITH resource_limit 
-}
-```
-
-## 参数说明
-
-| **参数**            | **说明**                                                     |
-| ------------------- | ------------------------------------------------------------ |
-| resource_group_name | 待修改的资源组名。                                           |
-| ADD                 | 为资源组添加分类器。关于分类器参数具体信息，请见 [CREATE RESOURCE GROUP - 参数说明](../../../sql-reference/sql-statements/Administration/CREATE_RESOURCE_GROUP.md)。 |
-| DROP                | 通过分类器 ID 为资源组删除对应分类器。您可以通过 [SHOW RESOURCE GROUP](../../../sql-reference/sql-statements/Administration/SHOW_RESOURCE_GROUP.md) 语句查看分类器 ID。 |
-| DROP ALL            | 为资源组删除所有分类器。                                     |
-| WITH                | 为资源组修改资源限制。关于资源限制参数具体信息，请见 [CREATE RESOURCE GROUP - 参数说明](../../../sql-reference/sql-statements/Administration/CREATE_RESOURCE_GROUP.md)。 |
-
-## 示例
-
-示例一：为资源组 `rg1` 添加新的分类器。
-
-```SQL
-ALTER RESOURCE GROUP rg1 ADD (user='root', query_type in ('select'));
-```
-
-示例二：为资源组 `rg1` 删除 ID 为 `300040`，`300041` 以及 `300041` 的分类器。
-
-```SQL
-ALTER RESOURCE GROUP rg1 DROP (300040, 300041, 300041);
-```
-
-示例三：为资源组 `rg1` 删除所有分类器。
-
-```SQL
-ALTER RESOURCE GROUP rg1 DROP ALL;
-```
-
-示例四：修改资源组 `rg1` 的资源限制。
-
-```SQL
-ALTER RESOURCE GROUP rg1 WITH (
-    'cpu_core_limit' = '20'
-);
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/ALTER_STORAGE_VOLUME.md b/docs/zh/sql-reference/sql-statements/Administration/ALTER_STORAGE_VOLUME.md
deleted file mode 100644
index b1eec67cb26bf8..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/ALTER_STORAGE_VOLUME.md
+++ /dev/null
@@ -1,61 +0,0 @@
----
-keywords: ['xiugai'] 
-displayed_sidebar: "Chinese"
----
-
-# ALTER STORAGE VOLUME
-
-## 功能
-
-更改存储卷的认证属性、注释或状态（`enabled`）。关于存储卷的属性，请参见[CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)。该功能自 v3.1 起支持。
-
-> **注意**
->
-> - 仅拥有特定存储卷 ALTER 权限的用户可以执行该操作。
-> - 已有存储卷的 `TYPE` 、`LOCATIONS` 和其他存储路径相关的参数无法更改，仅能更改认证属性。如果您更改了存储路径相关的配置项，则在此之前创建的数据库和表将变为只读，您无法向其中导入数据。
-> - `enabled` 为 `false` 的存储卷无法被引用。
-
-## 语法
-
-```SQL
-ALTER STORAGE VOLUME [ IF EXISTS ] <storage_volume_name>
-{ COMMENT '<comment_string>'
-| SET ("key" = "value"[,...]) }
-```
-
-## 参数说明
-
-| **参数**            | **说明**                         |
-| ------------------- | -------------------------------- |
-| storage_volume_name | 待更改或新增属性的存储卷的名称。 |
-| COMMENT             | 存储卷的注释。                   |
-
-有关可更改或新增 PROPERTIES 的详细信息，请参阅 [CREATE STORAGE VOLUME - PROPERTIES](./CREATE_STORAGE_VOLUME.md#properties)。
-
-## 示例
-
-示例一：禁用存储卷 `my_s3_volume`。
-
-```Plain
-MySQL > ALTER STORAGE VOLUME my_s3_volume
-    -> SET ("enabled" = "false");
-Query OK, 0 rows affected (0.01 sec)
-```
-
-示例二：修改存储卷 `my_s3_volume` 的认证信息。
-
-```Plain
-MySQL > ALTER STORAGE VOLUME my_s3_volume
-    -> SET (
-    ->     "aws.s3.use_instance_profile" = "true"
-    -> );
-Query OK, 0 rows affected (0.00 sec)
-```
-
-## 相关 SQL
-
-- [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)
-- [DROP STORAGE VOLUME](./DROP_STORAGE_VOLUME.md)
-- [SET DEFAULT STORAGE VOLUME](./SET_DEFAULT_STORAGE_VOLUME.md)
-- [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md)
-- [SHOW STORAGE VOLUMES](./SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/zh/sql-reference/sql-statements/Administration/ALTER_SYSTEM.md b/docs/zh/sql-reference/sql-statements/Administration/ALTER_SYSTEM.md
deleted file mode 100644
index 7d51529f2e1b0f..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/ALTER_SYSTEM.md
+++ /dev/null
@@ -1,193 +0,0 @@
----
-keywords: ['xiugai'] 
-displayed_sidebar: "Chinese"
----
-
-# ALTER SYSTEM
-
-## 功能
-
-管理 StarRocks 集群中的 FE、BE、CN 和 Broker。
-
-> **注意**
->
-> 只有拥有 `cluster_admin` 角色的用户才可以执行集群管理相关操作。
-
-## 语法和参数说明
-
-### FE
-
-- 添加 Follower FE。添加后，可使用 `SHOW PROC '/frontends'\G` 命令查看新增FE 的状态。
-
-   ```SQL
-    ALTER SYSTEM ADD FOLLOWER "host:edit_log_port"[, ...]
-    ```
-
-- 删除 Follower FE。
-
-    ```SQL
-    ALTER SYSTEM DROP FOLLOWER "host:edit_log_port"[, ...]
-    ```
-
-- 添加 Observer FE。添加后，可通过 `SHOW PROC '/frontends'\G` 命令查看新增FE 的状态。
-
-    ```SQL
-    ALTER SYSTEM ADD OBSERVER "host:edit_log_port"[, ...]
-    ```
-
-- 删除 Observer FE。
-
-    ```SQL
-    ALTER SYSTEM DROP OBSERVER "host:edit_log_port"[, ...]
-    ```
-
-     参数说明如下：
-
-    | **参数**           | **必选** | **说明**                                                     |
-    | ------------------ | -------- | ------------------------------------------------------------ |
-    | host:edit_log_port | 是       | <ul><li>`host`：FE 机器的 FQDN 或 IP 地址。如果机器存在多个 IP 地址，则该参数取值应为 `priority_networks` 配置项下设定的唯一通信 IP 地址。</li><li>`edit_log_port`：FE 上的 BDBJE 通信端口，默认为 `9010`。</li></ul> |
-
-- 创建 image。
-
-    ```SQL
-    ALTER SYSTEM CREATE IMAGE
-    ```
-
-    执行该语句会主动触发 Leader FE 创建新的 Image（元数据快照）文件。该操作异步执行，您可以通过查看 FE 日志文件 **fe.log** 确认操作何时开始执行及结束。`triggering a new checkpoint manually...` 表明操作开始执行，`finished save image...` 则表明 Image 创建完成。
-
-### BE
-
-- 添加 BE。 添加后，可通过 [SHOW BACKENDS](../Administration/SHOW_BACKENDS.md) 查看新增 BE 的状态。
-
-    ```SQL
-    ALTER SYSTEM ADD BACKEND "host:heartbeat_service_port"[, ...]
-    ```
-
-- 删除 BE。如果有表是单副本且该表的部分 tablet 分布在要删除的 BE 上，则不允许删除该 BE。
-
-    ```SQL
-    ALTER SYSTEM DROP BACKEND "host:heartbeat_service_port"[, ...]
-    ```
-
-- 下线 BE。
-
-    ```SQL
-    ALTER SYSTEM DECOMMISSION BACKEND "host:heartbeat_service_port"[, ...]
-    ```
-
-    下线前，该 BE 上的数据会迁移到其他 BE 上，过程中不影响数据导入和查询。下线 BE 为异步操作，可通过 [SHOW BACKENDS](../Administration/SHOW_BACKENDS.md) 语句查看是否下线成功，如下线成功，该 BE 不会在 SHOW BACKENDS 返回的信息中显示。您可以手动撤销下线操作，详情参见 [CANCEL DECOMMISSION](../Administration/CANCEL_DECOMMISSION.md)。
-
-    参数说明如下：
-
-    | **参数**                    | **必选** | **说明**                                                     |
-    | --------------------------- | -------- | ------------------------------------------------------------ |
-    | host:heartbeat_service_port | 是       |<ul><li> `host`：BE 机器的 FQDN 或 IP 地址。如果机器存在多个 IP 地址，则该参数取值应为 `priority_networks` 配置项下设定的唯一通信 IP 地址。</li><li>`heartbeat_service_port`：BE 的心跳端口，用于接收来自 FE 的心跳，默认为 `9050`。</li></ul> |
-
-### CN
-
-- 添加 CN。 添加后，可通过 `SHOW PROC '/compute_nodes'\G` 查看新增 CN 的状态。
-
-    ```SQL
-    ALTER SYSTEM ADD COMPUTE NODE "host:heartbeat_service_port"[, ...]
-    ```
-
-- 删除 CN。
-
-    ```SQL
-    ALTER SYSTEM DROP COMPUTE NODE "host:heartbeat_service_port"[, ...]
-    ```
-
-> **说明**
->
-> CN 暂不支持通过 `ALTER SYSTEM DECOMMISSION` 命令下线。
-
-    参数说明如下：
-
-    | **参数**                    | **必选** | **说明**                                                     |
-    | --------------------------- | -------- | ------------------------------------------------------------ |
-    | host:heartbeat_service_port | 是       |<ul><li> `host`：CN 机器的 FQDN 或 IP 地址。如果机器存在多个 IP 地址，则该参数取值应为 `priority_networks` 配置项下设定的唯一通信 IP 地址。</li><li>`heartbeat_service_port`：CN 的心跳端口，用于接收来自 FE 的心跳，默认为 `9050`。</li></ul> |
-
-### Broker
-
-- 添加 Broker。添加后，您可以使用 Broker Load 将 HDFS 或外部云存储系统中的数据导入到 StarRocks 中。详情参见[从 HDFS 导入](../../../loading/hdfs_load.md)或[从云存储导入](../../../loading/cloud_storage_load.md)。
-
-    ```SQL
-    ALTER SYSTEM ADD BROKER broker_name "host:port"[, ...]
-    ```
-
-    在一条 SQL 语句中，如同时添加多个 Broker（一个`host:port`为一个 Broker），那么这些 Broker 共用同一个 `broker_name`。添加后，可通过 [SHOW BROKER](../Administration/SHOW_BROKER.md) 语句查看 Broker 的详细信息。
-
-- 删除 Broker。注意如一个 Broker 上有正在执行的导入任务，那么删除该 Broker 会导致该任务中断。
-
-  - 删除 `broker_name` 下的一个或多个 Broker。
-
-      ```SQL
-      ALTER SYSTEM DROP BROKER broker_name "host:broker_ipc_port"[, ...]
-      ```
-
-  - 删除所有名为 `broker_name` 下的 Broker。
-
-      ```SQL
-      ALTER SYSTEM DROP ALL BROKER broker_name
-      ```
-
-     参数说明如下：
-
-    | **参数**             | **必选** | **说明**                                                     |
-    | -------------------- | -------- | ------------------------------------------------------------ |
-    | broker_name          | 是       | 一个 Broker 的名称或多个 Broker 共用的名称。                 |
-    | host:broker_ipc_port | 是       | <ul><li>`host`：Broker 机器的 FQDN 或 IP 地址。</li><li>`broker_ipc_port`：Broker 上的 thrift server 端口，用于接受 FE 或 BE 的请求，默认为 `8000`。</li></ul> |
-
-## 使用说明
-
-添加和删除 FE、添加和删除 BE 以及添加和删除 Broker 均为同步操作。执行删除语句后，FE、BE 或 Broker 会直接删除，不可手动撤销该操作。
-
-## 示例
-
-示例一：添加一个 Follower FE。
-
-```SQL
-ALTER SYSTEM ADD FOLLOWER "x.x.x.x:9010";
-```
-
-示例二：同时删除两个 Observer FE。
-
-```SQL
-ALTER SYSTEM DROP OBSERVER "x.x.x.x:9010","x.x.x.x:9010";
-```
-
-示例三：添加一个 BE。
-
-```SQL
-ALTER SYSTEM ADD BACKEND "x.x.x.x:9050";
-```
-
-示例四：同时删除两个 BE。
-
-```SQL
-ALTER SYSTEM DROP BACKEND "x.x.x.x:9050", "x.x.x.x:9050";
-```
-
-示例五：同时下线两个 BE。
-
-```SQL
-ALTER SYSTEM DECOMMISSION BACKEND "x.x.x.x:9050", "x.x.x.x:9050";
-```
-
-示例六：同时添加两个名为 `hdfs` 的 Broker。
-
-```SQL
-ALTER SYSTEM ADD BROKER hdfs "x.x.x.x:8000", "x.x.x.x:8000";
-```
-
-示例七：删除 `amazon_s3` 下的两个 Broker。
-
-```SQL
-ALTER SYSTEM DROP BROKER amazon_s3 "x.x.x.x:8000", "x.x.x.x:8000";
-```
-
-示例八：删除 `amazon_s3` 下的所有 Broker。
-
-```SQL
-ALTER SYSTEM DROP ALL BROKER amazon_s3;
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/ANALYZE_PROFILE.md b/docs/zh/sql-reference/sql-statements/Administration/ANALYZE_PROFILE.md
deleted file mode 100644
index 9e35748161d46e..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/ANALYZE_PROFILE.md
+++ /dev/null
@@ -1,44 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# ANALYZE PROFILE
-
-## 功能
-
-以 Fragment 为单位分析指定 Query Profile，并以树形结构展示。更多信息，参考 [Query Profile 概述](../../../administration/query_profile_overview.md)。
-
-此功能自 v3.1 起支持。
-
-> **注意**
->
-> 该操作需要有指定表的 SELECT 权限。
-
-## 语法
-
-```SQL
-ANALYZE PROFILE FROM '<query_id>', [<plan_node_id>[, ...] ]
-```
-
-## 参数说明
-
-| **参数**     | **说明**                                                     |
-| ------------ | ------------------------------------------------------------ |
-| query_id     | 查询 ID。您可以通过 [SHOW PROFILELIST](./SHOW_PROFILELIST.md) 获得。              |
-| plan_node_id | Query Profile 中的计划节点 ID。您可以指定此参数以查看相应计划节点的详细指标。如果未指定此参数，则仅显示所有计划节点的摘要指标。 |
-
-## 示例
-
-示例一：查询 Query Profile，不指定节点 ID。
-
-![img](../../../_assets/Profile/text_based_profile_without_node_id.jpeg)
-
-示例二：查询 Query Profile，并指定节点 ID 为 `0`。StarRocks 会返回 Node ID 为 `0` 的节点的所有详细指标，并且高亮显示使用占比较高的指标，便于定位问题。
-
-![img](../../../_assets/Profile/text_based_profile_with_node_id.jpeg)
-
-## 相关 SQL
-
-- [SHOW PROFILELIST](./SHOW_PROFILELIST.md)
-- [EXPLAIN ANALYZE](./EXPLAIN_ANALYZE.md)
-
diff --git a/docs/zh/sql-reference/sql-statements/Administration/CANCEL_DECOMMISSION.md b/docs/zh/sql-reference/sql-statements/Administration/CANCEL_DECOMMISSION.md
deleted file mode 100644
index ef0faad699aab6..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/CANCEL_DECOMMISSION.md
+++ /dev/null
@@ -1,27 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CANCEL DECOMMISSION
-
-## 功能
-
-该语句用于撤销一个节点下线操作。
-
-> **注意**
->
-> 只有拥有 `cluster_admin` 角色的用户才可以执行集群管理相关操作。
-
-## 语法
-
-```sql
-CANCEL DECOMMISSION BACKEND "host:heartbeat_port"[,"host:heartbeat_port"...]
-```
-
-## 示例
-
-取消两个节点的下线操作:
-
-```sql
-CANCEL DECOMMISSION BACKEND "host1:port", "host2:port";
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/CREATE_FILE.md b/docs/zh/sql-reference/sql-statements/Administration/CREATE_FILE.md
deleted file mode 100644
index 2d179cf0d3a775..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/CREATE_FILE.md
+++ /dev/null
@@ -1,66 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CREATE FILE
-
-CREATE FILE 语句用于创建文件。文件创建后会自动上传并持久化在 StarRocks 集群中。
-
-:::tip
-
-该操作需要 SYSTEM 级 FILE 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。当一个文件归属于一个数据库时，对该数据库拥有访问权限的用户都可以使用该文件。
-
-:::
-
-## 基本概念
-
-**文件**：是指创建并保存在 StarRocks 中的文件。每个文件都有一个全局唯一的标识符 (`FileId`)。一个文件由数据库名称 (`database`)、类别 (`catalog`) 和文件名 (`file_name`) 共同定位。
-
-## 语法
-
-```SQL
-CREATE FILE "file_name" [IN database]
-[properties]
-```
-
-## 参数说明
-
-| **参数**   | **必填** | **描述**                                                     |
-| ---------- | -------- | ------------------------------------------------------------ |
-| file_name  | 是       | 文件名，可根据需求自定义。                                   |
-| database   | 否       | 文件所属的数据库。如果没有指定该参数，则使用当前会话的数据库。 |
-| properties | 是       | 文件属性，具体配置项见下表：`properties` 配置项。            |
-
-**properties 配置项**
-
-| **配置项** | **必填** | **描述**                                                     |
-| ---------- | -------- | ------------------------------------------------------------ |
-| url        | 是       | 文件的下载路径。当前仅支持无认证的 HTTP 下载路径。语句执行成功后，文件会被下载并持久化保存在 StarRocks 中。 |
-| catalog    | 是       | 文件所属类别，可根据需求自定义。在某些命令中，会查找指定类别下的文件。比如在例行导入中，当数据源为 StarRocks 会查找 Apache Kafka® 类别下的文件。 |
-| md5        | 否       | 消息摘要算法。如果指定该参数，StarRocks 会对下载后的文件进行校验。 |
-
-## 示例
-
-- 创建一个名为 **test.pem** 的文件，所属类别为 kafka。
-
-```SQL
-CREATE FILE "test.pem"
-PROPERTIES
-(
-    "url" = "http://starrocks-public.oss-cn-xxxx.aliyuncs.com/key/test.pem",
-    "catalog" = "kafka"
-);
-```
-
-- 创建一个名为 **client.key** 的文件，所属类别为 my_catalog。
-
-```SQL
-CREATE FILE "client.key"
-IN my_database
-PROPERTIES
-(
-    "url" = "http://test.bj.bcebos.com/kafka-key/client.key",
-    "catalog" = "my_catalog",
-    "md5" = "b5bb901bf10f99205b39a46ac3557dd9"
-);
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/CREATE_RESOURCE_GROUP.md b/docs/zh/sql-reference/sql-statements/Administration/CREATE_RESOURCE_GROUP.md
deleted file mode 100644
index c0f9d8495dd411..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/CREATE_RESOURCE_GROUP.md
+++ /dev/null
@@ -1,77 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CREATE RESOURCE GROUP
-
-## 功能
-
-创建资源组。关于资源组的更多信息，参见[资源隔离](../../../administration/management/resource_management/resource_group.md)。
-
-:::tip
-
-该操作需要 SYSTEM 级 CREATE RESOURCE GROUP 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```SQL
-CREATE RESOURCE GROUP resource_group_name
-TO CLASSIFIER1, CLASSIFIER2, ...
-WITH resource_limit
-```
-
-## 参数说明
-
-- `resource_group_name`：需要创建的资源组名称。
-
-- `CLASSIFIER`：用于区分需要被施加资源限制的查询的分类器，采用 `"key"="value"` 对形式。您可以为同一个资源组设置多个分类器。
-
-  - 分类器可以包含以下参数：
-
-    | **参数**   | **必选** | **说明**                                            |
-    | ---------- | -------- | --------------------------------------------------- |
-    | user       | 否       | 用户名。                                            |
-    | role       | 否       | 用户所属角色名。                                    |
-    | query_type | 否       | 需要被施加资源限制的查询类型，目前支持 `SELECT` 与 `INSERT` (2.5 及以后)。当 `query_type` 为 `insert` 的资源组有导入任务正在运行时，当前 BE 节点会为其预留相应的计算资源。 |
-    | source_ip  | 否       | 发起查询的 IP 地址，类型为 CIDR。                   |
-    | db         | 否       | 查询所访问的数据库，可以为逗号（,）分割的字符串。   |
-    | plan_cpu_cost_range | 否     | 估计的查询 CPU 开销范围。该值与 **fe.audit.log** 中的 `PlanCpuCost` 字段含义相同，无单位。格式为 `[DOUBLE, DOUBLE)`。默认为 NULL，表示没有该限制。自 v3.1.4 起支持。                   |
-    | plan_mem_cost_range | 否     | 估计的查询内存开销范围。该值与 **fe.audit.log** 中的 `PlanMemCost` 字段含义相同，无单位。格式为 `[DOUBLE, DOUBLE)`。默认为 NULL，表示没有该限制。自 v3.1.4 起支持。                |
-
-- `resource_limit`：为当前资源组设置的资源限制，采用 `"key"="value"` 对形式。您可以为同一个资源组设置多个资源限制。
-
-  - 资源限制可以包含以下参数：
-
-    | **参数**                   | **必选** | **说明**                                                     |
-    | -------------------------- | -------- | ------------------------------------------------------------ |
-    | cpu_core_limit             | 否       | 该资源组在当前 BE 节点可使用的 CPU 核数软上限，实际使用的 CPU 核数会根据节点资源空闲程度按比例弹性伸缩。取值为正整数。 |
-    | mem_limit                  | 否       | 该资源组在当前 BE 节点可使用于查询的内存（query_pool）占总内存的百分比（%）。取值范围为 (0,1)。 |
-    | concurrency_limit          | 否       | 资源组中并发查询数的上限，用以防止并发查询提交过多而导致的过载。 |
-    | max_cpu_cores              | 否       | 资源组在单个 BE 节点中使用的 CPU 核数上限。仅在设置为大于 `0` 后生效。取值范围：[0, `avg_be_cpu_cores`]，其中 `avg_be_cpu_cores` 表示所有 BE 的 CPU 核数的平均值。默认值为 0。自 v3.1.4 起支持。 |
-    | big_query_cpu_second_limit | 否       | 大查询任务可以使用 CPU 的时间上限，其中的并行任务将累加 CPU 使用时间。单位为秒。 |
-    | big_query_scan_rows_limit  | 否       | 大查询任务可以扫描的行数上限。                               |
-    | big_query_mem_limit        | 否       | 大查询任务可以使用的内存上限。单位为 Byte。                  |
-    | type                       | 否       | 资源组类型。有效取值包括：<br />`short_query`：当 `short_query` 资源组有查询正在运行时，当前 BE 节点会为其预留 `short_query.cpu_core_limit` 的 CPU 资源，所有 `normal` 资源组的总 CPU 核数使用上限会被硬限制为 BE 节点核数减 `short_query.cpu_core_limit`。<br />`normal`：当 `short_query` 资源组没有查询正在运行时，所有 `normal` 资源组的 CPU 核数没有硬限制。<br />注意：同一集群中，您最多只能创建一个 `short_query` 资源组。 |
-
-## 示例
-
-示例一：基于多个分类器创建资源组 `rg1`。
-
-```SQL
-CREATE RESOURCE GROUP rg1
-TO 
-    (user='rg1_user1', role='rg1_role1', query_type in ('select'), source_ip='192.168.x.x/24'),
-    (user='rg1_user2', query_type in ('select'), source_ip='192.168.x.x/24'),
-    (user='rg1_user3', source_ip='192.168.x.x/24'),
-    (user='rg1_user4'),
-    (db='db1')
-WITH ('cpu_core_limit' = '10',
-      'mem_limit' = '20%',
-      'type' = 'normal',
-      'big_query_cpu_second_limit' = '100',
-      'big_query_scan_rows_limit' = '100000',
-      'big_query_mem_limit' = '1073741824'
-);
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md b/docs/zh/sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md
deleted file mode 100644
index a46936b09a4a0c..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/CREATE_STORAGE_VOLUME.md
+++ /dev/null
@@ -1,465 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CREATE STORAGE VOLUME
-
-## 功能
-
-为远程存储系统创建存储卷。该功能自 v3.1 起支持。
-
-存储卷由远程存储系统的属性和认证信息组成。您可以在 [StarRocks 存算分离集群](../../../deployment/shared_data/shared_data.mdx)中创建数据库和云原生表时引用存储卷。
-
-> **注意**
->
-> - 仅拥有 SYSTEM 级 CREATE STORAGE VOLUME 权限的用户可以执行该操作。
-> - 如果您需要基于 HDFS 创建存储卷，建议您不要随意修改 **HADOOP_CONF** 和 **core-site.xml/hdfs-site.xml**。如果以上文件中的参数与创建 Storage Volume 的参数存在差异，可能导致系统发生未知行为。
-
-## 语法
-
-```SQL
-CREATE STORAGE VOLUME [IF NOT EXISTS] <storage_volume_name>
-TYPE = { S3 | HDFS | AZBLOB }
-LOCATIONS = ('<remote_storage_path>')
-[ COMMENT '<comment_string>' ]
-PROPERTIES
-("key" = "value",...)
-```
-
-## 参数说明
-
-| **参数**            | **说明**                                                     |
-| ------------------- | ------------------------------------------------------------ |
-| storage_volume_name | 存储卷的名称。请注意，您无法创建名为 `builtin_storage_volume` 的存储卷，因为该名称被用于创建内置存储卷。有关 storage volume 的命名要求，参见[系统限制](../../../reference/System_limit.md)。 |
-| TYPE                | 远程存储系统的类型。有效值：`S3` 、`AZBLOB` 和 `HDFS`。`S3` 代表AWS S3 或与 S3 协议兼容的存储系统。`AZBLOB` 代表 Azure Blob Storage（自 v3.1.1 起支持）。`HDFS` 代表 HDFS 集群。 |
-| LOCATIONS           | 远程存储系统的位置。格式如下：<ul><li>AWS S3 或与 S3 协议兼容的存储系统：`s3://<s3_path>`。`<s3_path>` 必须为绝对路径，如 `s3://testbucket/subpath`。请注意，如果要为存储卷启用 [分区前缀](#分区前缀) 功能，您只能指定存储桶名称，不允许指定子路径。</li><li>Azure Blob Storage: `azblob://<azblob_path>`。`<azblob_path>` 必须为绝对路径，如 `azblob://testcontainer/subpath`。</li><li>HDFS：`hdfs://<host>:<port>/<hdfs_path>`。`<hdfs_path>` 必须为绝对路径，如 `hdfs://127.0.0.1:9000/user/xxx/starrocks`。</li><li>WebHDFS：`webhdfs://<host>:<http_port>/<hdfs_path>`，其中 `<http_port>` 为 NameNode 的 HTTP 端口。`<hdfs_path>` 必须为绝对路径，如 `webhdfs://127.0.0.1:50070/user/xxx/starrocks`。</li><li>ViewFS：`viewfs://<ViewFS_cluster>/<viewfs_path>`，其中 `<ViewFS_cluster>` 为 ViewFS 集群名。`<viewfs_path>` 必须为绝对路径，如 `viewfs://myviewfscluster/user/xxx/starrocks`。</li></ul> |
-| COMMENT             | 存储卷的注释。                                               |
-| PROPERTIES          | `"key" = "value"` 形式的参数对，用以指定访问远程存储系统的属性和认证信息。有关详细信息，请参阅 [PROPERTIES](#properties)。 |
-
-### PROPERTIES
-
-下表列出了存储卷所有可用的属性。这些属性的使用说明在列表后提供，从 [认证信息](#认证信息) 和 [特性](#特性) 两个方面，基于不同场景进行分类。
-
-| **属性**                            | **描述**                                                     |
-| ----------------------------------- | ------------------------------------------------------------ |
-| enabled                             | 是否启用当前存储卷。默认值：`false`。已禁用的存储卷无法被引用。 |
-| aws.s3.region                       | 需访问的 S3 存储空间的地区，如 `us-west-2`。                 |
-| aws.s3.endpoint                     | 访问 S3 存储空间的连接地址，如 `https://s3.us-west-2.amazonaws.com`。[Preview] 自 v3.3.0 起，支持 Amazon S3 Express One Zone Storage，如 `https://s3express.us-west-2.amazonaws.com`。 |
-| aws.s3.use_aws_sdk_default_behavior | 是否使用 AWS SDK 默认的认证凭证。有效值：`true` 和 `false` (默认)。 |
-| aws.s3.use_instance_profile         | 是否使用 Instance Profile 或 Assumed Role 作为安全凭证访问 S3。有效值：`true` 和 `false` (默认)。<ul><li>如果您使用 IAM 用户凭证（Access Key 和 Secret Key）访问 S3，则需要将此项设为 `false`，并指定 `aws.s3.access_key` 和 `aws.s3.secret_key`。</li><li>如果您使用 Instance Profile 访问 S3，则需要将此项设为 `true`。</li><li>如果您使用 Assumed Role 访问 S3，则需要将此项设为 `true`，并指定 `aws.s3.iam_role_arn`。</li><li>如果您使用外部 AWS 账户通过 Assumed Role 认证访问 S3，则需要将此项设为 `true`，并额外指定 `aws.s3.iam_role_arn` 和 `aws.s3.external_id`。</li></ul> |
-| aws.s3.access_key                   | 访问 S3 存储空间的 Access Key。                              |
-| aws.s3.secret_key                   | 访问 S3 存储空间的 Secret Key。                              |
-| aws.s3.iam_role_arn                 | 有访问 S3 存储空间权限 IAM Role 的 ARN。                     |
-| aws.s3.external_id                  | 用于跨 AWS 账户访问 S3 存储空间的外部 ID。                   |
-| azure.blob.endpoint   | Azure Blob Storage 的链接地址，如 `https://test.blob.core.windows.net`。 |
-| azure.blob.shared_key | 访问 Azure Blob Storage 的共享密钥（Shared Key）。           |
-| azure.blob.sas_token  | 访问 Azure Blob Storage 的共享访问签名（SAS）。              |
-| hadoop.security.authentication                        | 指定认证方式。有效值：`simple`（默认） 和 `kerberos`。`simple` 表示简单认证，即 Username。`kerberos` 表示 Kerberos 认证。 |
-| username                                              | 用于访问 HDFS 集群中 NameNode 节点的用户名。                      |
-| hadoop.security.kerberos.ticket.cache.path            | 用于指定 kinit 生成的 Ticket Cache 文件的路径。                   |
-| dfs.nameservices                                      | 自定义 HDFS 集群的名称。                                        |
-| dfs.ha.namenodes.`<ha_cluster_name\>`                   | 自定义 NameNode 的名称，多个名称以逗号 (,) 分隔，双引号内不允许出现空格。其中 `<ha_cluster_name>` 为 `dfs.nameservices` 中自定义的 HDFS 服务的名称。 |
-| dfs.namenode.rpc-address.`<ha_cluster_name\>`.`<NameNode\>` | 指定 NameNode 的 RPC 地址信息。 其中 `<NameNode>` 表示 `dfs.ha.namenodes.<ha_cluster_name>` 中自定义 NameNode 的名称。 |
-| dfs.client.failover.proxy.provider                    | 指定客户端连接的 NameNode 的提供者，默认为 `org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider`。 |
-| fs.viewfs.mounttable.`<ViewFS_cluster\>`.link./`<viewfs_path\>` | 需要挂载的 ViewFS 集群路径，多个路径以逗号 (,) 分隔。其中 `<ViewFS_cluster>` 为 `LOCATIONS` 中自定义的 ViewFS 集群名。 |
-| aws.s3.enable_partitioned_prefix    | 是否启用存储卷的分区前缀功能。默认值：`false`。有关此功能的更多信息，请参阅 [分区前缀](#分区前缀)。 |
-| aws.s3.num_partitioned_prefix       | 要为该存储卷创建的前缀数量。默认值：`256`。有效范围：[4, 1024]。|
-
-#### 认证信息
-
-##### AWS S3
-
-- 如果您使用 AWS SDK 默认的认证凭证，请设置以下属性：
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "aws.s3.region" = "<region>",
-  "aws.s3.endpoint" = "<endpoint_url>",
-  "aws.s3.use_aws_sdk_default_behavior" = "true"
-  ```
-
-- 如果您使用 IAM user-based 认证，请设置以下属性：
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "aws.s3.region" = "<region>",
-  "aws.s3.endpoint" = "<endpoint_url>",
-  "aws.s3.use_aws_sdk_default_behavior" = "false",
-  "aws.s3.use_instance_profile" = "false",
-  "aws.s3.access_key" = "<access_key>",
-  "aws.s3.secret_key" = "<secrete_key>"
-  ```
-
-- 如果您使用 Instance Profile 认证，请设置以下属性：
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "aws.s3.region" = "<region>",
-  "aws.s3.endpoint" = "<endpoint_url>",
-  "aws.s3.use_aws_sdk_default_behavior" = "false",
-  "aws.s3.use_instance_profile" = "true"
-  ```
-
-- 如果您使用 Assumed Role 认证，请设置以下属性：
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "aws.s3.region" = "<region>",
-  "aws.s3.endpoint" = "<endpoint_url>",
-  "aws.s3.use_aws_sdk_default_behavior" = "false",
-  "aws.s3.use_instance_profile" = "true",
-  "aws.s3.iam_role_arn" = "<role_arn>"
-  ```
-
-- 如果您使用外部 AWS 账户通过 Assumed Role 认证，请设置以下属性：
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "aws.s3.region" = "<region>",
-  "aws.s3.endpoint" = "<endpoint_url>",
-  "aws.s3.use_aws_sdk_default_behavior" = "false",
-  "aws.s3.use_instance_profile" = "true",
-  "aws.s3.iam_role_arn" = "<role_arn>",
-  "aws.s3.external_id" = "<external_id>"
-  ```
-
-##### GCS
-
-如果您使用 GCP Cloud Storage，请设置以下属性：
-
-```SQL
-"enabled" = "{ true | false }",
-
--- 例如：us-east-1
-"aws.s3.region" = "<region>",
-
--- 例如：https://storage.googleapis.com
-"aws.s3.endpoint" = "<endpoint_url>",
-
-"aws.s3.access_key" = "<access_key>",
-"aws.s3.secret_key" = "<secrete_key>"
-```
-
-##### 阿里云 OSS
-
-如果您使用阿里云 OSS，请设置以下属性：
-
-```SQL
-"enabled" = "{ true | false }",
-
--- 例如：cn-zhangjiakou
-"aws.s3.region" = "<region>",
-
--- 例如：https://oss-cn-zhangjiakou-internal.aliyuncs.com
-"aws.s3.endpoint" = "<endpoint_url>",
-
-"aws.s3.access_key" = "<access_key>",
-"aws.s3.secret_key" = "<secrete_key>"
-```
-
-##### 华为云 OBS
-
-如果您使用华为云 OBS，请设置以下属性：
-
-```SQL
-"enabled" = "{ true | false }",
-
--- 例如：cn-north-4
-"aws.s3.region" = "<region>",
-
--- 例如：https://obs.cn-north-4.myhuaweicloud.com
-"aws.s3.endpoint" = "<endpoint_url>",
-
-"aws.s3.access_key" = "<access_key>",
-"aws.s3.secret_key" = "<secrete_key>"
-```
-
-##### 腾讯云 COS
-
-如果您使用腾讯云 COS，请设置以下属性：
-
-```SQL
-"enabled" = "{ true | false }",
-
--- 例如：ap-beijing
-"aws.s3.region" = "<region>",
-
--- 例如：https://cos.ap-beijing.myqcloud.com
-"aws.s3.endpoint" = "<endpoint_url>",
-
-"aws.s3.access_key" = "<access_key>",
-"aws.s3.secret_key" = "<secrete_key>"
-```
-
-##### 火山引擎 TOS
-
-如果您使用火山引擎 TOS，请设置以下属性：
-
-```SQL
-"enabled" = "{ true | false }",
-
--- 例如：cn-beijing
-"aws.s3.region" = "<region>",
-
--- 例如：https://tos-s3-cn-beijing.ivolces.com
-"aws.s3.endpoint" = "<endpoint_url>",
-
-"aws.s3.access_key" = "<access_key>",
-"aws.s3.secret_key" = "<secrete_key>"
-```
-
-##### 金山云
-
-如果您使用金山云，请设置以下属性：
-
-```SQL
-"enabled" = "{ true | false }",
-
--- 例如：BEIJING
-"aws.s3.region" = "<region>",
-
--- 注意请使用三级域名, 金山云不支持二级域名
--- 例如：jeff-test.ks3-cn-beijing.ksyuncs.com
-"aws.s3.endpoint" = "<endpoint_url>",
-
-"aws.s3.access_key" = "<access_key>",
-"aws.s3.secret_key" = "<secrete_key>"
-```
-
-##### MinIO
-
-如果您使用 MinIO，请设置以下属性：
-
-```SQL
-"enabled" = "{ true | false }",
-
--- 例如：us-east-1
-"aws.s3.region" = "<region>",
-
--- 例如：http://172.26.xx.xxx:39000
-"aws.s3.endpoint" = "<endpoint_url>",
-
-"aws.s3.access_key" = "<access_key>",
-"aws.s3.secret_key" = "<secrete_key>"
-```
-
-##### Ceph S3
-
-如果您使用 Ceph S3，请设置以下属性：
-
-```SQL
-"enabled" = "{ true | false }",
-
--- 例如：http://172.26.xx.xxx:7480
-"aws.s3.endpoint" = "<endpoint_url>",
-
-"aws.s3.access_key" = "<access_key>",
-"aws.s3.secret_key" = "<secrete_key>"
-```
-
-##### Azure Blob Storage
-
-StarRocks 自 v3.1.1 起支持基于 Azure Blob Storage 创建存储卷。
-
-- 如果您使用共享密钥（Shared Key）认证，请设置以下 PROPERTIES：
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "azure.blob.endpoint" = "<endpoint_url>",
-  "azure.blob.shared_key" = "<shared_key>"
-  ```
-
-- 如果您使用共享访问签名（SAS）认证，请设置以下 PROPERTIES：
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "azure.blob.endpoint" = "<endpoint_url>",
-  "azure.blob.sas_token" = "<sas_token>"
-  ```
-
-> **注意**
->
-> 创建 Azure Blob Storage Account 时必须禁用分层命名空间。
-
-##### HDFS
-
-- 如果您不使用认证接入 HDFS，请设置以下属性：
-
-  ```SQL
-  "enabled" = "{ true | false }"
-  ```
-
-- 如果您使用简单认证 (Username) 接入 HDFS（自 v3.2 起支持），请设置以下属性：
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "hadoop.security.authentication" = "simple",
-  "username" = "<hdfs_username>"
-  ```
-
-- 如果您使用 Kerberos Ticket Cache 认证接入 HDFS（自 v3.2 起支持），请设置以下属性：
-
-  ```SQL
-  "enabled" = "{ true | false }",
-  "hadoop.security.authentication" = "kerberos",
-  "hadoop.security.kerberos.ticket.cache.path" = "<ticket_cache_path>"
-  ```
-
-  > **注意**
-  >
-  > - 该设置仅为强制系统使用 KeyTab 通过 Kerberos 访问 HDFS。请确保每个 BE 或 CN 节点都能够访问 KeyTab 文件。同时，还需要确保正确设置 **/etc/krb5.conf** 文件。
-  > - Ticket cache 由外部的 kinit 工具生成，请确保有 crontab 或类似的定期任务来刷新 Ticket。
-
-- 如果您的 HDFS 集群启用了 NameNode HA 配置（自 v3.2 起支持），请额外设置以下属性：
-
-  ```SQL
-  "dfs.nameservices" = "<ha_cluster_name>",
-  "dfs.ha.namenodes.<ha_cluster_name>" = "<NameNode1>,<NameNode2> [, ...]",
-  "dfs.namenode.rpc-address.<ha_cluster_name>.<NameNode1>" = "<hdfs_host>:<hdfs_port>",
-  "dfs.namenode.rpc-address.<ha_cluster_name>.<NameNode2>" = "<hdfs_host>:<hdfs_port>",
-  [...]
-  "dfs.client.failover.proxy.provider.<ha_cluster_name>" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
-  ```
-
-  更多信息，请参考 [HDFS HA 文档](https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HDFSHighAvailabilityWithNFS.html)。
-
-  - 如果您使用 WebHDFS（自 v3.2 起支持），请设置以下属性：
-
-  ```SQL
-  "enabled" = "{ true | false }"
-  ```
-
-  更多信息，请参考 [WebHDFS 文档](https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/WebHDFS.html)。
-
-- 如果您使用 Hadoop ViewFS（自 v3.2 起支持），请设置以下属性：
-
-  ```SQL
-  -- 请将 <ViewFS_cluster> 替换为 ViewFS 集群名。
-  "fs.viewfs.mounttable.<ViewFS_cluster>.link./<viewfs_path_1>" = "hdfs://<hdfs_host_1>:<hdfs_port_1>/<hdfs_path_1>",
-  "fs.viewfs.mounttable.<ViewFS_cluster>.link./<viewfs_path_2>" = "hdfs://<hdfs_host_2>:<hdfs_port_2>/<hdfs_path_2>",
-  [, ...]
-  ```
-
-  更多信息，请参考 [ViewFS 文档](https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/ViewFs.html)。
-
-#### 特性
-
-##### 分区前缀
-
-自 v3.2.4 起，StarRocks 支持基于兼容 S3 的对象存储系统创建带有分区前缀功能的存储卷。当启用此功能时，StarRocks 会将数据存储在存储桶下多个使用统一前缀的分区（子路径）中。由于存储桶的 QPS 或吞吐量限制是基于单个分区设置的，此举可以轻松提高 StarRocks 对存储桶中数据文件的读写性能。
-
-如需启用此功能，除了上述与凭证相关的参数之外，您还需要设置以下属性：
-
-```SQL
-"aws.s3.enable_partitioned_prefix" = "{ true | false }",
-"aws.s3.num_partitioned_prefix" = "<INT>"
-```
-
-:::note
-- 分区前缀功能仅支持兼容 S3 对象存储系统，即存储卷的 `TYPE` 必须为 `S3`。
-- 存储卷的 `LOCATIONS` 只能包含存储桶名称，例如，`s3://testbucket`。不允许在存储桶名称后指定子路径。
-- 存储卷创建成功后，以上两个属性均无法修改。
-- 使用 FE 配置文件 **fe.conf** 创建存储卷无法启用此功能。
-:::
-
-## 示例
-
-示例一：为 AWS S3 存储空间 `defaultbucket` 创建存储卷 `my_s3_volume`，使用 IAM user-based 认证，并启用该存储卷。
-
-```SQL
-CREATE STORAGE VOLUME my_s3_volume
-TYPE = S3
-LOCATIONS = ("s3://defaultbucket/test/")
-PROPERTIES
-(
-    "aws.s3.region" = "us-west-2",
-    "aws.s3.endpoint" = "https://s3.us-west-2.amazonaws.com",
-    "aws.s3.use_aws_sdk_default_behavior" = "false",
-    "aws.s3.use_instance_profile" = "false",
-    "aws.s3.access_key" = "xxxxxxxxxx",
-    "aws.s3.secret_key" = "yyyyyyyyyy"
-);
-```
-
-示例二：为 HDFS 创建存储卷 `my_hdfs_volume`，并启用该存储卷。
-
-```SQL
-CREATE STORAGE VOLUME my_hdfs_volume
-TYPE = HDFS
-LOCATIONS = ("hdfs://127.0.0.1:9000/sr/test/")
-PROPERTIES
-(
-    "enabled" = "true"
-);
-```
-
-示例三：使用简单验证为 HDFS 创建存储卷 `hdfsvolumehadoop`。
-
-```sql
-CREATE STORAGE VOLUME hdfsvolumehadoop
-TYPE = HDFS
-LOCATIONS = ("hdfs://127.0.0.1:9000/sr/test/")
-PROPERTIES(
-    "hadoop.security.authentication" = "simple",
-    "username" = "starrocks"
-);
-```
-
-示例四：使用 Kerberos Ticket Cache 认证接入 HDFS 并创建存储卷 `hdfsvolkerberos`。
-
-```sql
-CREATE STORAGE VOLUME hdfsvolkerberos
-TYPE = HDFS
-LOCATIONS = ("hdfs://127.0.0.1:9000/sr/test/")
-PROPERTIES(
-    "hadoop.security.authentication" = "kerberos",
-    "hadoop.security.kerberos.ticket.cache.path" = "/path/to/ticket/cache/path"
-);
-```
-
-示例五：为启用了 NameNode HA 配置的 HDFS 集群创建存储卷 `hdfsvolha`。
-
-```sql
-CREATE STORAGE VOLUME hdfsvolha
-TYPE = HDFS
-LOCATIONS = ("hdfs://myhacluster/data/sr")
-PROPERTIES(
-    "dfs.nameservices" = "myhacluster",
-    "dfs.ha.namenodes.myhacluster" = "nn1,nn2,nn3",
-    "dfs.namenode.rpc-address.myhacluster.nn1" = "machine1.example.com:8020",
-    "dfs.namenode.rpc-address.myhacluster.nn2" = "machine2.example.com:8020",
-    "dfs.namenode.rpc-address.myhacluster.nn3" = "machine3.example.com:8020",
-    "dfs.namenode.http-address.myhacluster.nn1" = "machine1.example.com:9870",
-    "dfs.namenode.http-address.myhacluster.nn2" = "machine2.example.com:9870",
-    "dfs.namenode.http-address.myhacluster.nn3" = "machine3.example.com:9870",
-    "dfs.client.failover.proxy.provider.myhacluster" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
-);
-```
-
-示例六：为 WebHDFS 创建存储卷 `webhdfsvol`。
-
-```sql
-CREATE STORAGE VOLUME webhdfsvol
-TYPE = HDFS
-LOCATIONS = ("webhdfs://namenode:9870/data/sr");
-```
-
-示例七：使用 Hadoop ViewFS 创建存储卷 `viewfsvol`。
-
-```sql
-CREATE STORAGE VOLUME viewfsvol
-TYPE = HDFS
-LOCATIONS = ("viewfs://clusterX/data/sr")
-PROPERTIES(
-    "fs.viewfs.mounttable.clusterX.link./data" = "hdfs://nn1-clusterx.example.com:8020/data",
-    "fs.viewfs.mounttable.clusterX.link./project" = "hdfs://nn2-clusterx.example.com:8020/project"
-);
-```
-
-## 相关 SQL
-
-- [ALTER STORAGE VOLUME](./ALTER_STORAGE_VOLUME.md)
-- [DROP STORAGE VOLUME](./DROP_STORAGE_VOLUME.md)
-- [SET DEFAULT STORAGE VOLUME](./SET_DEFAULT_STORAGE_VOLUME.md)
-- [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md)
-- [SHOW STORAGE VOLUMES](./SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/zh/sql-reference/sql-statements/Administration/DELETE_BACKEND_BLACKLIST.md b/docs/zh/sql-reference/sql-statements/Administration/DELETE_BACKEND_BLACKLIST.md
deleted file mode 100644
index 6200a65d9cb860..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/DELETE_BACKEND_BLACKLIST.md
+++ /dev/null
@@ -1,40 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DELETE BACKEND BLACKLIST
-
-## 功能
-
-从 BE 黑名单中移除 BE 节点。请注意，StarRocks 不会主动将用户手动加入黑名单的节点移除。
-
-此功能自 v3.3.0 起支持。更多信息，参考[管理 BE 黑名单](../../../administration/management/BE_blacklist.md)。
-
-:::note
-
-该操作需要有 SYSTEM 级 BLACKLIST 权限。
-
-:::
-
-## 语法
-
-```SQL
-DELETE BACKEND BLACKLIST <be_id>[, ...]
-```
-
-## 参数说明
-
-`be_id`：要从黑名单中移除的 BE 节点的 ID。您可以通过执行 [SHOW BACKEND BLACKLIST](./SHOW_BACKEND_BLACKLIST.md) 语句获取被列入黑名单的 BE 的 ID。
-
-## 示例
-
-```SQL
-DELETE BACKEND BLACKLIST 10001;
-```
-
-## 相关 SQL
-
-- [ADD BACKEND BLACKLIST](./ADD_BACKEND_BLACKLIST.md)
-- [SHOW BACKEND BLACKLIST](./SHOW_BACKEND_BLACKLIST.md)
-- [SHOW BACKENDS](./SHOW_BACKENDS.md)
-
diff --git a/docs/zh/sql-reference/sql-statements/Administration/DELETE_SQLBLACKLIST.md b/docs/zh/sql-reference/sql-statements/Administration/DELETE_SQLBLACKLIST.md
deleted file mode 100644
index 7d3e21096d80a2..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/DELETE_SQLBLACKLIST.md
+++ /dev/null
@@ -1,41 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DELETE SQLBLACKLIST
-
-## 功能
-
-从 SQL 黑名单中删除一个 SQL 正则表达式。
-
-有关 SQL 黑名单的更多信息，请参阅 [管理 SQL 黑名单](../../../administration/management/resource_management/Blacklist.md)。
-
-:::tip
-
-该操作需要 SYSTEM 级 BLACKLIST 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```SQL
-DELETE SQLBLACKLIST <sql_index_number>
-```
-
-## 参数说明
-
-`sql_index_number`：SQL 正则表达式在黑名单中的序号。用逗号（,）和一个空格分隔多个序号。您可以使用 [SHOW SQLBLACKLIST](../Administration/SHOW_SQLBLACKLIST.md) 查询相应索引号。
-
-## 示例
-
-```Plain
-mysql> DELETE SQLBLACKLIST 3, 4;
-
-mysql> SHOW SQLBLACKLIST;
-+-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| Index | Forbidden SQL                                                                                                                                                                                                                                                                                          |
-+-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| 1     | select count\(\*\) from .+                                                                                                                                                                                                                                                                             |
-| 2     | select id_int \* 4, id_tinyint, id_varchar from test_all_type_nullable except select id_int, id_tinyint, id_varchar from test_basic except select \(id_int \* 9 \- 8\) \/ 2, id_tinyint, id_varchar from test_all_type_nullable2 except select id_int, id_tinyint, id_varchar from test_basic_nullable |
-+-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/DESC_STORAGE_VOLUME.md b/docs/zh/sql-reference/sql-statements/Administration/DESC_STORAGE_VOLUME.md
deleted file mode 100644
index 27b6e9b36c1c74..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/DESC_STORAGE_VOLUME.md
+++ /dev/null
@@ -1,62 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DESC STORAGE VOLUME
-
-## 功能
-
-查看指定存储卷的信息。该功能自 v3.1 起支持。
-
-> **注意**
->
-> 仅拥有指定存储卷 USAGE 权限的用户可以执行该操作。
-
-## 语法
-
-```SQL
-DESC[RIBE] STORAGE VOLUME <storage_volume_name>
-```
-
-## 参数说明
-
-| **参数**            | **说明**               |
-| ------------------- | ---------------------- |
-| storage_volume_name | 待查看的存储卷的名称。 |
-
-## 返回
-
-| **返回**  | **说明**                                                |
-| --------- | ------------------------------------------------------- |
-| Name      | 存储卷的名称。                                          |
-| Type      | 远程存储系统的类型。有效值：`S3`、`AZBLOB` 和 `HDFS`。 |
-| IsDefault | 该存储卷是否为默认存储卷。                              |
-| Location  | 远程存储系统的位置。                                    |
-| Params    | 用于连接远程存储系统的认证信息。                        |
-| Enabled   | 该存储卷是否已被启用。                                  |
-| Comment   | 存储卷的注释。                                          |
-
-## 示例
-
-示例一：查看存储卷 `my_s3_volume` 的信息。
-
-```Plain
-MySQL > DESCRIBE STORAGE VOLUME my_s3_volume\G
-*************************** 1. row ***************************
-     Name: my_s3_volume
-     Type: S3
-IsDefault: false
- Location: s3://defaultbucket/test/
-   Params: {"aws.s3.access_key":"xxxxxxxxxx","aws.s3.secret_key":"yyyyyyyyyy","aws.s3.endpoint":"https://s3.us-west-2.amazonaws.com","aws.s3.region":"us-west-2","aws.s3.use_instance_profile":"true","aws.s3.use_aws_sdk_default_behavior":"false"}
-  Enabled: false
-  Comment: 
-1 row in set (0.00 sec)
-```
-
-## 相关 SQL
-
-- [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)
-- [ALTER STORAGE VOLUME](./ALTER_STORAGE_VOLUME.md)
-- [DROP STORAGE VOLUME](./DROP_STORAGE_VOLUME.md)
-- [SET DEFAULT STORAGE VOLUME](./SET_DEFAULT_STORAGE_VOLUME.md)
-- [SHOW STORAGE VOLUMES](./SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/zh/sql-reference/sql-statements/Administration/DROP_FILE.md b/docs/zh/sql-reference/sql-statements/Administration/DROP_FILE.md
deleted file mode 100644
index 515cc07a684de3..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/DROP_FILE.md
+++ /dev/null
@@ -1,43 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DROP FILE
-
-DROP FILE 语句用于删除保存在数据库中的文件。使用该语句删除一个文件，那么该文件在 FE 内存和 BDBJE 中均会被删除。
-
-:::tip
-
-该操作需要 SYSTEM 级 FILE 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。当一个文件归属于一个数据库时，对该数据库拥有访问权限的用户都可以使用该文件。
-
-:::
-
-## 语法
-
-```SQL
-DROP FILE "file_name" [FROM database]
-
-[properties]
-```
-
-## 参数说明
-
-| **参数**   | **必填** | **描述**                                         |
-| ---------- | -------- | ------------------------------------------------ |
-| file_name  | 是       | 文件名。                                           |
-| database   | 否       | 文件所属的数据库。                                 |
-| properties | 是       | 文件属性，具体配置项见下表：`properties`配置项。     |
-
-`properties` 配置项
-
-| **配置项** | **必填** | **描述**     |
-| ---------- | -------- | ------------ |
-| catalog    | 是       | 文件所属类别。 |
-
-## 示例
-
-删除文件 `ca.pem`。
-
-```SQL
-DROP FILE "ca.pem" properties("catalog" = "kafka");
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/DROP_RESOURCE_GROUP.md b/docs/zh/sql-reference/sql-statements/Administration/DROP_RESOURCE_GROUP.md
deleted file mode 100644
index 350d515569e555..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/DROP_RESOURCE_GROUP.md
+++ /dev/null
@@ -1,35 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DROP RESOURCE GROUP
-
-## 功能
-
-删除指定资源组。
-
-:::tip
-
-该操作需要对应 Resource Group 的 DROP 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```SQL
-DROP RESOURCE GROUP <resource_group_name>
-```
-
-## 参数说明
-
-| **参数**            | **说明**         |
-| ------------------- | ---------------- |
-| resource_group_name | 待删除资源组名。 |
-
-## 示例
-
-示例一：删除资源组 `rg1`。
-
-```SQL
-DROP RESOURCE GROUP rg1;
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/DROP_STORAGE_VOLUME.md b/docs/zh/sql-reference/sql-statements/Administration/DROP_STORAGE_VOLUME.md
deleted file mode 100644
index ae6cf3b3f9567f..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/DROP_STORAGE_VOLUME.md
+++ /dev/null
@@ -1,44 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DROP STORAGE VOLUME
-
-## 功能
-
-删除指定存储卷。已删除的存储卷无法被引用。该功能自 v3.1 起支持。
-
-> **注意**
->
-> - 仅拥有指定存储卷 DROP 权限的用户可以执行该操作。
-> - 默认存储卷以及内置存储卷 `builtin_storage_volume` 无法删除。您可以通过 [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md) 查看存储卷是否为默认存储卷。
-> - 被已有数据库或云原生表引用的存储卷无法删除。
-
-## 语法
-
-```SQL
-DROP STORAGE VOLUME [ IF EXISTS ] <storage_volume_name>
-```
-
-## 参数说明
-
-| **参数**            | **说明**               |
-| ------------------- | ---------------------- |
-| storage_volume_name | 待删除的存储卷的名称。 |
-
-## 示例
-
-示例一：删除存储卷 `my_s3_volume`。
-
-```Plain
-MySQL > DROP STORAGE VOLUME my_s3_volume;
-Query OK, 0 rows affected (0.01 sec)
-```
-
-## 相关 SQL
-
-- [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)
-- [ALTER STORAGE VOLUME](./ALTER_STORAGE_VOLUME.md)
-- [SET DEFAULT STORAGE VOLUME](./SET_DEFAULT_STORAGE_VOLUME.md)
-- [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md)
-- [SHOW STORAGE VOLUMES](./SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/zh/sql-reference/sql-statements/Administration/EXPLAIN.md b/docs/zh/sql-reference/sql-statements/Administration/EXPLAIN.md
deleted file mode 100644
index daa2cd9c5d028c..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/EXPLAIN.md
+++ /dev/null
@@ -1,437 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# EXPLAIN
-
-## 功能
-
-显示输入查询语句的逻辑或物理执行计划。关于如何分析查询计划，请参考 [分析 Query Plan](../../../administration/Query_planning.md#分析-query-plan)。
-
-:::tip
-
-该操作不需要权限。
-
-:::
-
-## 语法
-
-```SQL
-EXPLAIN [ LOGICAL | VERBOSE | COSTS ] <query>
-```
-
-:::tip
-
-执行计划详细程度：EXPLAIN LOGICAL < EXPLAIN < EXPLAIN VERBOSE < EXPLAIN COSTS。
-
-通常情况下使用 EXPLAIN 即可，EXPLAIN VERBOSE 和 EXPLAIN COSTS 会打印大量冗余信息，主要用于调试计划。
-
-:::
-
-## 参数说明
-
-| **参数** | **说明**                                                   |
-| -------- | ---------------------------------------------------------- |
-| LOGICAL  | 显示简要的逻辑执行计划。                  |
-| VERBOSE  | 显示详细的逻辑执行计划，包括数据类型，nullable 信息，优化策略等。 |
-| COSTS    | 显示详细的逻辑执行计划，包括统计信息。 |
-| query    | 需要查看执行计划的查询语句。                                  |
-
-## 返回
-
-返回输入查询语句的执行计划。
-
-| **返回**       | **说明**                           |
-| -------------- |----------------------------------|
-| avgRowSize     | 扫描数据行的平均大小。                      |
-| cardinality    | 扫描表的数据总行数。                       |
-| colocate       | 是否为 Colocate 表。                  |
-| numNodes       | 待扫描的节点数。                         |
-| rollup         | 使用的同步物化视图。                       |
-| preaggregation | 预聚合的状态。                          |
-| predicates     | 查询中使用的谓词。                        |
-| column statistics | 列统计信息，依次为MIN,MAX, NULL个数，平均大小，基数 |
-## 示例
-
-### EXPLAIN
-
-```Plain
-MySQL tpcds> explain select 
-    sr_customer_sk as ctr_customer_sk, 
-    sr_store_sk as ctr_store_sk, 
-    sum(SR_RETURN_AMT) as ctr_total_return 
-  from 
-    store_returns, 
-    date_dim 
-  where 
-    sr_returned_date_sk = d_date_sk and d_year = 2000 
-  group by 
-    sr_customer_sk, 
-    sr_store_sk
-+-----------------------------------------------------------------------------+
-| Explain String                                                              |
-+-----------------------------------------------------------------------------+
-| PLAN FRAGMENT 0                                                             |
-|  OUTPUT EXPRS:5: sr_customer_sk | 9: sr_store_sk | 49: sum                  |
-|   PARTITION: UNPARTITIONED                                                  |
-|                                                                             |
-|   RESULT SINK                                                               |
-|                                                                             |
-|   9:EXCHANGE                                                                |
-|                                                                             |
-| PLAN FRAGMENT 1                                                             |
-|  OUTPUT EXPRS:                                                              |
-|   PARTITION: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk            |
-|                                                                             |
-|   STREAM DATA SINK                                                          |
-|     EXCHANGE ID: 09                                                         |
-|     UNPARTITIONED                                                           |
-|                                                                             |
-|   8:AGGREGATE (merge finalize)                                              |
-|   |  output: sum(49: sum)                                                   |
-|   |  group by: 5: sr_customer_sk, 9: sr_store_sk                            |
-|   |                                                                         |
-|   7:EXCHANGE                                                                |
-|                                                                             |
-| PLAN FRAGMENT 2                                                             |
-|  OUTPUT EXPRS:                                                              |
-|   PARTITION: RANDOM                                                         |
-|                                                                             |
-|   STREAM DATA SINK                                                          |
-|     EXCHANGE ID: 07                                                         |
-|     HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                     |
-|                                                                             |
-|   6:AGGREGATE (update serialize)                                            |
-|   |  STREAMING                                                              |
-|   |  output: sum(12: sr_return_amt)                                         |
-|   |  group by: 5: sr_customer_sk, 9: sr_store_sk                            |
-|   |                                                                         |
-|   5:Project                                                                 |
-|   |  <slot 5> : 5: sr_customer_sk                                           |
-|   |  <slot 9> : 9: sr_store_sk                                              |
-|   |  <slot 12> : 12: sr_return_amt                                          |
-|   |                                                                         |
-|   4:HASH JOIN                                                               |
-|   |  join op: INNER JOIN (BROADCAST)                                        |
-|   |  colocate: false, reason:                                               |
-|   |  equal join conjunct: 3: sr_returned_date_sk = 21: d_date_sk            |
-|   |                                                                         |
-|   |----3:EXCHANGE                                                           |
-|   |                                                                         |
-|   0:OlapScanNode                                                            |
-|      TABLE: store_returns                                                   |
-|      PREAGGREGATION: ON                                                     |
-|      PREDICATES: 3: sr_returned_date_sk IS NOT NULL                         |
-|      partitions=1/1                                                         |
-|      rollup: store_returns                                                  |
-|      tabletRatio=10/10                                                      |
-|      tabletList=10241,10243,10245,10247,10249,10251,10253,10255,10257,10259 |
-|      cardinality=277502                                                     |
-|      avgRowSize=20.0                                                        |
-|                                                                             |
-| PLAN FRAGMENT 3                                                             |
-|  OUTPUT EXPRS:                                                              |
-|   PARTITION: RANDOM                                                         |
-|                                                                             |
-|   STREAM DATA SINK                                                          |
-|     EXCHANGE ID: 03                                                         |
-|     UNPARTITIONED                                                           |
-|                                                                             |
-|   2:Project                                                                 |
-|   |  <slot 21> : 21: d_date_sk                                              |
-|   |                                                                         |
-|   1:OlapScanNode                                                            |
-|      TABLE: date_dim                                                        |
-|      PREAGGREGATION: ON                                                     |
-|      PREDICATES: 27: d_year = 2000                                          |
-|      partitions=1/1                                                         |
-|      rollup: date_dim                                                       |
-|      tabletRatio=5/5                                                        |
-|      tabletList=11543,11545,11547,11549,11551                               |
-|      cardinality=362                                                        |
-|      avgRowSize=8.0                                                         |
-+-----------------------------------------------------------------------------+
-79 rows in set
-```
-
-### EXPLAIN LOGICAL
-
-```Plain
-MySQL tpcds> explain logical select 
-    sr_customer_sk as ctr_customer_sk, 
-    sr_store_sk as ctr_store_sk, 
-    sum(SR_RETURN_AMT) as ctr_total_return 
-  from 
-    store_returns, 
-    date_dim 
-  where 
-    sr_returned_date_sk = d_date_sk and d_year = 2000 
-  group by 
-    sr_customer_sk, 
-    sr_store_sk
- 
-+---------------------------------------------------------------------------------------------------------------------------------+
-| Explain String                                                                                                                  |
-+---------------------------------------------------------------------------------------------------------------------------------+
-| - Output => [5:sr_customer_sk, 9:sr_store_sk, 49:sum]                                                                           |
-|     - AGGREGATE(GLOBAL) [5:sr_customer_sk, 9:sr_store_sk]                                                                       |
-|             Estimates: {row: 49728, cpu: 795660.58, memory: 795660.58, network: 0.00, cost: 8405375.45}                         |
-|             49:sum := sum(49:sum)                                                                                               |
-|         - EXCHANGE(SHUFFLE) [5, 9]                                                                                              |
-|                 Estimates: {row: 49728, cpu: 79566.06, memory: 0.00, network: 0.00, cost: 6416223.99}                           |
-|             - AGGREGATE(LOCAL) [5:sr_customer_sk, 9:sr_store_sk]                                                                |
-|                     Estimates: {row: 49728, cpu: 119349.09, memory: 79566.06, network: 0.00, cost: 6376440.96}                  |
-|                     49:sum := sum(12:sr_return_amt)                                                                             |
-|                 - HASH/INNER JOIN [3:sr_returned_date_sk = 21:d_date_sk] => [5:sr_customer_sk, 9:sr_store_sk, 12:sr_return_amt] |
-|                         Estimates: {row: 49728, cpu: 6744977.39, memory: 1446.51, network: 0.00, cost: 6157634.30}              |
-|                     - SCAN [store_returns] => [3:sr_returned_date_sk, 5:sr_customer_sk, 9:sr_store_sk, 12:sr_return_amt]        |
-|                             Estimates: {row: 277502, cpu: 5550040.00, memory: 0.00, network: 0.00, cost: 2775020.00}            |
-|                             partitionRatio: 1/1, tabletRatio: 10/10                                                             |
-|                             predicate: 3:sr_returned_date_sk IS NOT NULL                                                        |
-|                     - EXCHANGE(BROADCAST)                                                                                       |
-|                             Estimates: {row: 361, cpu: 1446.51, memory: 1446.51, network: 1446.51, cost: 7232.57}               |
-|                         - SCAN [date_dim] => [21:d_date_sk]                                                                     |
-|                                 Estimates: {row: 361, cpu: 2893.03, memory: 0.00, network: 0.00, cost: 1446.51}                 |
-|                                 partitionRatio: 1/1, tabletRatio: 5/5                                                           |
-|                                 predicate: 27:d_year = 2000                                                                     |
-+---------------------------------------------------------------------------------------------------------------------------------+
-21 rows in set
-```
-
-### EXPLAIN VERBOSE
-
-```Plain
-MySQL tpcds> explain verbose select 
-    sr_customer_sk as ctr_customer_sk, 
-    sr_store_sk as ctr_store_sk, 
-    sum(SR_RETURN_AMT) as ctr_total_return 
-  from 
-    store_returns, 
-    date_dim 
-  where 
-    sr_returned_date_sk = d_date_sk and d_year = 2000 
-  group by 
-    sr_customer_sk, 
-    sr_store_sk
- 
-+---------------------------------------------------------------------------------------------------------------------------------------------------------+
-| Explain String                                                                                                                                          |
-+---------------------------------------------------------------------------------------------------------------------------------------------------------+
-| RESOURCE GROUP: default_wg                                                                                                                              |
-|                                                                                                                                                         |
-| PLAN FRAGMENT 0(F04)                                                                                                                                    |
-|   Fragment Cost: 0.0                                                                                                                                    |
-|   Output Exprs:5: sr_customer_sk | 9: sr_store_sk | 49: sum                                                                                             |
-|   Input Partition: UNPARTITIONED                                                                                                                        |
-|   RESULT SINK                                                                                                                                           |
-|                                                                                                                                                         |
-|   9:EXCHANGE                                                                                                                                            |
-|      cardinality: 49729                                                                                                                                 |
-|                                                                                                                                                         |
-| PLAN FRAGMENT 1(F03)                                                                                                                                    |
-|   Fragment Cost: 2028934.4876271961                                                                                                                     |
-|                                                                                                                                                         |
-|   Input Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                  |
-|   OutPut Partition: UNPARTITIONED                                                                                                                       |
-|   OutPut Exchange Id: 09                                                                                                                                |
-|                                                                                                                                                         |
-|   8:AGGREGATE (merge finalize)                                                                                                                          |
-|   |  aggregate: sum[([49: sum, DECIMAL128(38,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true]         |
-|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |                                                                                                                                                     |
-|   7:EXCHANGE                                                                                                                                            |
-|      distribution type: SHUFFLE                                                                                                                         |
-|      partition exprs: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                       |
-|      cardinality: 49729                                                                                                                                 |
-|                                                                                                                                                         |
-| PLAN FRAGMENT 2(F00)                                                                                                                                    |
-|   Fragment Cost: 6376440.959353934                                                                                                                      |
-|                                                                                                                                                         |
-|   Input Partition: RANDOM                                                                                                                               |
-|   OutPut Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                 |
-|   OutPut Exchange Id: 07                                                                                                                                |
-|                                                                                                                                                         |
-|   6:AGGREGATE (update serialize)                                                                                                                        |
-|   |  STREAMING                                                                                                                                          |
-|   |  aggregate: sum[([12: sr_return_amt, DECIMAL64(7,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true] |
-|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |                                                                                                                                                     |
-|   5:Project                                                                                                                                             |
-|   |  output columns:                                                                                                                                    |
-|   |  5 <-> [5: sr_customer_sk, INT, true]                                                                                                               |
-|   |  9 <-> [9: sr_store_sk, INT, true]                                                                                                                  |
-|   |  12 <-> [12: sr_return_amt, DECIMAL64(7,2), true]                                                                                                   |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |                                                                                                                                                     |
-|   4:HASH JOIN                                                                                                                                           |
-|   |  join op: INNER JOIN (BROADCAST)                                                                                                                    |
-|   |  equal join conjunct: [3: sr_returned_date_sk, INT, true] = [21: d_date_sk, INT, false]                                                             |
-|   |  build runtime filters:                                                                                                                             |
-|   |  - filter_id = 0, build_expr = (21: d_date_sk), remote = false                                                                                      |
-|   |  output columns: 5, 9, 12                                                                                                                           |
-|   |  can local shuffle: true                                                                                                                            |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |                                                                                                                                                     |
-|   |----3:EXCHANGE                                                                                                                                       |
-|   |       distribution type: BROADCAST                                                                                                                  |
-|   |       cardinality: 362                                                                                                                              |
-|   |                                                                                                                                                     |
-|   0:OlapScanNode                                                                                                                                        |
-|      table: store_returns, rollup: store_returns                                                                                                        |
-|      preAggregation: on                                                                                                                                 |
-|      Predicates: 3: sr_returned_date_sk IS NOT NULL                                                                                                     |
-|      partitionsRatio=1/1, tabletsRatio=10/10                                                                                                            |
-|      tabletList=10241,10243,10245,10247,10249,10251,10253,10255,10257,10259                                                                             |
-|      actualRows=287514, avgRowSize=20.0                                                                                                                 |
-|      cardinality: 277502                                                                                                                                |
-|      probe runtime filters:                                                                                                                             |
-|      - filter_id = 0, probe_expr = (3: sr_returned_date_sk)                                                                                             |
-|                                                                                                                                                         |
-| PLAN FRAGMENT 3(F01)                                                                                                                                    |
-|   Fragment Cost: 1446.5148514851485                                                                                                                     |
-|                                                                                                                                                         |
-|   Input Partition: RANDOM                                                                                                                               |
-|   OutPut Partition: UNPARTITIONED                                                                                                                       |
-|   OutPut Exchange Id: 03                                                                                                                                |
-|                                                                                                                                                         |
-|   2:Project                                                                                                                                             |
-|   |  output columns:                                                                                                                                    |
-|   |  21 <-> [21: d_date_sk, INT, false]                                                                                                                 |
-|   |  cardinality: 362                                                                                                                                   |
-|   |                                                                                                                                                     |
-|   1:OlapScanNode                                                                                                                                        |
-|      table: date_dim, rollup: date_dim                                                                                                                  |
-|      preAggregation: on                                                                                                                                 |
-|      Predicates: [27: d_year, INT, false] = 2000                                                                                                        |
-|      partitionsRatio=1/1, tabletsRatio=5/5                                                                                                              |
-|      tabletList=11543,11545,11547,11549,11551                                                                                                           |
-|      actualRows=73049, avgRowSize=8.0                                                                                                                   |
-|      cardinality: 362                                                                                                                                   |
-+---------------------------------------------------------------------------------------------------------------------------------------------------------+
-```
-
-### EXPLAIN COSTS
-
-```Plain
-+---------------------------------------------------------------------------------------------------------------------------------------------------------+
-| Explain String                                                                                                                                          |
-+---------------------------------------------------------------------------------------------------------------------------------------------------------+
-| PLAN FRAGMENT 0(F04)                                                                                                                                    |
-|   Output Exprs:5: sr_customer_sk | 9: sr_store_sk | 49: sum                                                                                             |
-|   Input Partition: UNPARTITIONED                                                                                                                        |
-|   RESULT SINK                                                                                                                                           |
-|                                                                                                                                                         |
-|   9:EXCHANGE                                                                                                                                            |
-|      cardinality: 49729                                                                                                                                 |
-|                                                                                                                                                         |
-| PLAN FRAGMENT 1(F03)                                                                                                                                    |
-|                                                                                                                                                         |
-|   Input Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                  |
-|   OutPut Partition: UNPARTITIONED                                                                                                                       |
-|   OutPut Exchange Id: 09                                                                                                                                |
-|                                                                                                                                                         |
-|   8:AGGREGATE (merge finalize)                                                                                                                          |
-|   |  aggregate: sum[([49: sum, DECIMAL128(38,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true]         |
-|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |  column statistics:                                                                                                                                 |
-|   |  * sr_customer_sk-->[1.0, 100000.0, 2.010867271218169E-5, 4.0, 49728.786461450894] ESTIMATE                                                         |
-|   |  * sr_store_sk-->[1.0, 10.0, 0.14285714285714285, 4.0, 6.0] ESTIMATE                                                                                |
-|   |  * sum-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                                    |
-|   |                                                                                                                                                     |
-|   7:EXCHANGE                                                                                                                                            |
-|      distribution type: SHUFFLE                                                                                                                         |
-|      partition exprs: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                       |
-|      cardinality: 49729                                                                                                                                 |
-|                                                                                                                                                         |
-| PLAN FRAGMENT 2(F00)                                                                                                                                    |
-|                                                                                                                                                         |
-|   Input Partition: RANDOM                                                                                                                               |
-|   OutPut Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                 |
-|   OutPut Exchange Id: 07                                                                                                                                |
-|                                                                                                                                                         |
-|   6:AGGREGATE (update serialize)                                                                                                                        |
-|   |  STREAMING                                                                                                                                          |
-|   |  aggregate: sum[([12: sr_return_amt, DECIMAL64(7,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true] |
-|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |  column statistics:                                                                                                                                 |
-|   |  * sr_customer_sk-->[1.0, 100000.0, 2.010867271218169E-5, 4.0, 49728.786461450894] ESTIMATE                                                         |
-|   |  * sr_store_sk-->[1.0, 10.0, 0.14285714285714285, 4.0, 6.0] ESTIMATE                                                                                |
-|   |  * sum-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                                    |
-|   |                                                                                                                                                     |
-|   5:Project                                                                                                                                             |
-|   |  output columns:                                                                                                                                    |
-|   |  5 <-> [5: sr_customer_sk, INT, true]                                                                                                               |
-|   |  9 <-> [9: sr_store_sk, INT, true]                                                                                                                  |
-|   |  12 <-> [12: sr_return_amt, DECIMAL64(7,2), true]                                                                                                   |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |  column statistics:                                                                                                                                 |
-|   |  * sr_customer_sk-->[1.0, 100000.0, 0.034836564480338346, 4.0, 49728.786461450894] ESTIMATE                                                         |
-|   |  * sr_store_sk-->[1.0, 10.0, 0.034996556689413386, 4.0, 6.0] ESTIMATE                                                                               |
-|   |  * sr_return_amt-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                          |
-|   |                                                                                                                                                     |
-|   4:HASH JOIN                                                                                                                                           |
-|   |  join op: INNER JOIN (BROADCAST)                                                                                                                    |
-|   |  equal join conjunct: [3: sr_returned_date_sk, INT, true] = [21: d_date_sk, INT, false]                                                             |
-|   |  build runtime filters:                                                                                                                             |
-|   |  - filter_id = 0, build_expr = (21: d_date_sk), remote = false                                                                                      |
-|   |  output columns: 5, 9, 12                                                                                                                           |
-|   |  can local shuffle: true                                                                                                                            |
-|   |  cardinality: 49729                                                                                                                                 |
-|   |  column statistics:                                                                                                                                 |
-|   |  * sr_returned_date_sk-->[2450820.0, 2452822.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                               |
-|   |  * sr_customer_sk-->[1.0, 100000.0, 0.034836564480338346, 4.0, 49728.786461450894] ESTIMATE                                                         |
-|   |  * sr_store_sk-->[1.0, 10.0, 0.034996556689413386, 4.0, 6.0] ESTIMATE                                                                               |
-|   |  * sr_return_amt-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                          |
-|   |  * d_date_sk-->[2450820.0, 2452822.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                                         |
-|   |                                                                                                                                                     |
-|   |----3:EXCHANGE                                                                                                                                       |
-|   |       distribution type: BROADCAST                                                                                                                  |
-|   |       cardinality: 362                                                                                                                              |
-|   |                                                                                                                                                     |
-|   0:OlapScanNode                                                                                                                                        |
-|      table: store_returns, rollup: store_returns                                                                                                        |
-|      preAggregation: on                                                                                                                                 |
-|      Predicates: 3: sr_returned_date_sk IS NOT NULL                                                                                                     |
-|      partitionsRatio=1/1, tabletsRatio=10/10                                                                                                            |
-|      tabletList=10241,10243,10245,10247,10249,10251,10253,10255,10257,10259                                                                             |
-|      actualRows=287514, avgRowSize=20.0                                                                                                                 |
-|      cardinality: 277502                                                                                                                                |
-|      probe runtime filters:                                                                                                                             |
-|      - filter_id = 0, probe_expr = (3: sr_returned_date_sk)                                                                                             |
-|      column statistics:                                                                                                                                 |
-|      * sr_returned_date_sk-->[2450820.0, 2452822.0, 0.0, 4.0, 2018.0] ESTIMATE                                                                          |
-|      * sr_customer_sk-->[1.0, 100000.0, 0.034836564480338346, 4.0, 86524.0] ESTIMATE                                                                    |
-|      * sr_store_sk-->[1.0, 10.0, 0.034996556689413386, 4.0, 6.0] ESTIMATE                                                                               |
-|      * sr_return_amt-->[0.0, 16917.12, 0.034878301578357924, 8.0, 113968.0] ESTIMATE                                                                    |
-|                                                                                                                                                         |
-| PLAN FRAGMENT 3(F01)                                                                                                                                    |
-|                                                                                                                                                         |
-|   Input Partition: RANDOM                                                                                                                               |
-|   OutPut Partition: UNPARTITIONED                                                                                                                       |
-|   OutPut Exchange Id: 03                                                                                                                                |
-|                                                                                                                                                         |
-|   2:Project                                                                                                                                             |
-|   |  output columns:                                                                                                                                    |
-|   |  21 <-> [21: d_date_sk, INT, false]                                                                                                                 |
-|   |  cardinality: 362                                                                                                                                   |
-|   |  column statistics:                                                                                                                                 |
-|   |  * d_date_sk-->[2415022.0, 2488070.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                                         |
-|   |                                                                                                                                                     |
-|   1:OlapScanNode                                                                                                                                        |
-|      table: date_dim, rollup: date_dim                                                                                                                  |
-|      preAggregation: on                                                                                                                                 |
-|      Predicates: [27: d_year, INT, false] = 2000                                                                                                        |
-|      partitionsRatio=1/1, tabletsRatio=5/5                                                                                                              |
-|      tabletList=11543,11545,11547,11549,11551                                                                                                           |
-|      actualRows=73049, avgRowSize=8.0                                                                                                                   |
-|      cardinality: 362                                                                                                                                   |
-|      column statistics:                                                                                                                                 |
-|      * d_date_sk-->[2415022.0, 2488070.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                                         |
-|      * d_year-->[2000.0, 2000.0, 0.0, 4.0, 202.0] ESTIMATE                                                                                              |
-+---------------------------------------------------------------------------------------------------------------------------------------------------------+
-114 rows in set
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/EXPLAIN_ANALYZE.md b/docs/zh/sql-reference/sql-statements/Administration/EXPLAIN_ANALYZE.md
deleted file mode 100644
index 47c1a8e87b429c..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/EXPLAIN_ANALYZE.md
+++ /dev/null
@@ -1,44 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# EXPLAIN ANALYZE
-
-## 功能
-
-执行指定 SQL，并显示相应的 Query Profile 文件。更多信息，参考 [Query Profile 概述](../../../administration/query_profile_overview.md)。
-
-此功能自 v3.1 起支持。
-
-> **注意**
->
-> 该操作需要有指定表的 SELECT 或 INSERT 权限。
-
-## 语法
-
-```SQL
-EXPLAIN ANALYZE <statement>
-```
-
-## 参数说明
-
-`statement`：需要查询 Query Profile 的 SQL 语句。支持 [SELECT](../data-manipulation/SELECT.md) 和 [INSERT INTO](../data-manipulation/INSERT.md)。
-
-## 使用说明
-
-请注意，当您模拟并分析 INSERT INTO 语句的 Query Profile 时，实际上不会导入任何数据。默认情况下，导入事务会被强制回滚，以确保在分析过程中不会对数据进行意外更改。
-
-## 示例
-
-示例一：模拟分析 SELECT 语句，查询返回结果会被丢弃。
-
-![img](../../../_assets/Profile/text_based_explain_analyze_select.jpeg)
-
-示例二：模拟分析 INSERT INTO 语句。执行结束后，导入事务会被强制回滚，数据不会被实际导入。
-
-![img](../../../_assets/Profile/text_based_explain_analyze_insert.jpeg)
-
-## 相关 SQL
-
-- [SHOW PROFILELIST](./SHOW_PROFILELIST.md)
-- [ANALYZE PROFILE](./EXPLAIN_ANALYZE.md)
diff --git a/docs/zh/sql-reference/sql-statements/Administration/INSTALL_PLUGIN.md b/docs/zh/sql-reference/sql-statements/Administration/INSTALL_PLUGIN.md
deleted file mode 100644
index e86d3422645782..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/INSTALL_PLUGIN.md
+++ /dev/null
@@ -1,59 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# INSTALL PLUGIN
-
-## 功能
-
-该语句用于安装一个插件。
-
-:::tip
-
-该操作需要 SYSTEM 级 PLUGIN 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```sql
-INSTALL PLUGIN FROM [source] [PROPERTIES ("key"="value", ...)]
-```
-
-**source 支持三种类型：**
-
-```plain text
-1. 指向一个 zip 文件的绝对路径。
-2. 指向一个插件目录的绝对路径。
-3. 指向一个 http 或 https 协议的 zip 文件下载路径。
-```
-
-**PROPERTIES：**
-
-支持设置插件的一些配置，如设置 zip 文件的 md5sum 的值等。
-
-## 示例
-
-1. 安装一个本地 zip 文件插件：
-
-    ```sql
-    INSTALL PLUGIN FROM "/home/users/starrocks/auditdemo.zip";
-    ```
-
-2. 安装一个本地目录中的插件：
-
-    ```sql
-    INSTALL PLUGIN FROM "/home/users/starrocks/auditdemo/";
-    ```
-
-3. 下载并安装一个插件：
-
-    ```sql
-    INSTALL PLUGIN FROM "http://mywebsite.com/plugin.zip";
-    ```
-
-4. 下载并安装一个插件，同时设置了 zip 文件的 md5sum 的值：
-
-    ```sql
-    INSTALL PLUGIN FROM "http://mywebsite.com/plugin.zip" PROPERTIES("md5sum" = "73877f6029216f4314d712086a146570");
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/KILL.md b/docs/zh/sql-reference/sql-statements/Administration/KILL.md
deleted file mode 100644
index 2008ec7771d4f9..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/KILL.md
+++ /dev/null
@@ -1,43 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# KILL
-
-## 功能
-
-终止当前集群内的正在执行的指定连接或者查询。
-
-:::tip
-
-该操作不需要权限。
-
-:::
-
-## 语法
-
-```SQL
-KILL [ CONNECTION | QUERY ] <processlist_id>
-```
-
-## 参数说明
-
-| **参数**                | **说明**                                                     |
-| ----------------------- | ------------------------------------------------------------ |
-| 修饰符：<ul><li>CONNECTION</li><li>QUERY</li></ul> | <ul><li>使用 `CONNECTION` 修饰符，KILL 语句首先终止与 `processlist_id` 关联的连接下正在执行的语句，然后终止该连接。</li><li>使用 `QUERY` 修饰符，KILL 语句仅终止与 `processlist_id` 关联的连接下正在执行的语句，不会终止该连接。</li><li>如不指定修饰符，默认值为 `CONNECTION`。</li></ul> |
-| processlist_id          | 需要终止的线程的 ID。 您可以通过 [SHOW PROCESSLIST](../Administration/SHOW_PROCESSLIST.md) 获取正在执行的线程的 ID。 |
-
-## 示例
-
-```Plain
-mysql> SHOW FULL PROCESSLIST;
-+------+------+---------------------+--------+---------+---------------------+------+-------+-----------------------+-----------+
-| Id   | User | Host                | Db     | Command | ConnectionStartTime | Time | State | Info                  | IsPending |
-+------+------+---------------------+--------+---------+---------------------+------+-------+-----------------------+-----------+
-|   20 | root | xxx.xx.xxx.xx:xxxxx | sr_hub | Query   | 2023-01-05 16:30:19 |    0 | OK    | show full processlist | false     |
-+------+------+---------------------+--------+---------+---------------------+------+-------+-----------------------+-----------+
-1 row in set (0.01 sec)
-
-mysql> KILL 20;
-Query OK, 0 rows affected (0.00 sec)
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SET.md b/docs/zh/sql-reference/sql-statements/Administration/SET.md
deleted file mode 100644
index a567b5b3445759..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SET.md
+++ /dev/null
@@ -1,54 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SET
-
-## 功能
-
-为 StarRocks 设置指定的系统变量或用户自定义变量。您可以通过 [SHOW VARIABLES](../Administration/SHOW_VARIABLES.md) 查看 StarRocks 的系统变量。有关系统变量的详细信息，请参阅[系统变量](../../../reference/System_variable.md)。有关用户自定义变量的详细信息，请参阅[用户自定义变量](../../../reference/user_defined_variables.md)。
-
-:::tip
-
-该操作不需要权限。
-
-:::
-
-## 语法
-
-```SQL
-SET [ GLOBAL | SESSION ] <variable_name> = <value> [, <variable_name> = <value>] ...
-```
-
-## 参数说明
-
-| **参数**              | **说明**                                                     |
-| --------------------- | ------------------------------------------------------------ |
-| 修饰符：<ul><li>GLOBAL</li><li>SESSION</li></ul> | <ul><li>使用 `GLOBAL` 修饰符，该语句设置该变量值为全局变量值。</li><li>使用 `SESSION` 修饰符，该语句设置该变量值对当前连接有效。您可以使用 `LOCAL` 替代 `SESSION`。</li><li>如不指定修饰符，默认值为 `SESSION`。</li></ul>有关全局变量和会话变量的详细信息，请参阅 [系统变量](../../../reference/System_variable.md)。<br/>**说明**<br/>仅拥有 System 级 OPERATE 权限的用户才能设置全局变量。 |
-| variable_name         | 变量名。                                                     |
-| value                 | 变量值。                                                     |
-
-## 示例
-
-示例一：在当前会话内设置 `time_zone` 为 `Asia/Shanghai`。
-
-```Plain
-mysql> SET time_zone = "Asia/Shanghai";
-Query OK, 0 rows affected (0.00 sec)
-```
-
-示例二：全局设置 `exec_mem_limit` 为 `2147483648`。
-
-```Plain
-mysql> SET GLOBAL exec_mem_limit = 2147483648;
-Query OK, 0 rows affected (0.00 sec)
-```
-
-示例三：同时设置多个全局变量。需要在所有变量名前添加 `GLOBAL` 关键字。
-
-```Plain
-mysql> SET 
-       GLOBAL exec_mem_limit = 2147483648,
-       GLOBAL time_zone = "Asia/Shanghai";
-Query OK, 0 rows affected (0.00 sec)
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SET_DEFAULT_STORAGE_VOLUME.md b/docs/zh/sql-reference/sql-statements/Administration/SET_DEFAULT_STORAGE_VOLUME.md
deleted file mode 100644
index df332e7f7081bd..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SET_DEFAULT_STORAGE_VOLUME.md
+++ /dev/null
@@ -1,44 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SET DEFAULT STORAGE VOLUME
-
-## 功能
-
-设置指定存储卷为默认存储卷。为远程存储系统创建了存储卷之后，您可以设置该存储卷为集群的默认存储卷。该功能自 v3.1 起支持。
-
-> **注意**
->
-> - 仅拥有指定存储卷 USAGE 权限的用户可以执行该操作。
-> - 默认存储卷无法删除或禁用。
-> - 您必须为 StarRocks 存算分离集群设置默认存储卷，因为 StarRocks 会将系统统计信息存储在默认存储卷中。
-
-## 语法
-
-```SQL
-SET <storage_volume_name> AS DEFAULT STORAGE VOLUME
-```
-
-## 参数说明
-
-| **参数**            | **说明**               |
-| ------------------- | ---------------------- |
-| storage_volume_name | 待设置的存储卷的名称。 |
-
-## 示例
-
-示例一：设置存储卷 `my_s3_volume` 为默认存储卷。
-
-```SQL
-MySQL > SET my_s3_volume AS DEFAULT STORAGE VOLUME;
-Query OK, 0 rows affected (0.01 sec)
-```
-
-## 相关 SQL
-
-- [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)
-- [ALTER STORAGE VOLUME](./ALTER_STORAGE_VOLUME.md)
-- [DROP STORAGE VOLUME](./DROP_STORAGE_VOLUME.md)
-- [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md)
-- [SHOW STORAGE VOLUMES](./SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_BACKENDS.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_BACKENDS.md
deleted file mode 100644
index 8d1063336e4211..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_BACKENDS.md
+++ /dev/null
@@ -1,76 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW BACKENDS
-
-## 功能
-
-查看当前集群中所有 BE 节点的相关信息。
-
-> **注意**
->
-> 该操作需要 SYSTEM 级 OPERATE 权限或 `cluster_admin` 角色。
-
-## 语法
-
-```SQL
-SHOW BACKENDS
-```
-
-## 返回信息说明
-
-```SQL
-+-----------+-----------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+--------------------+--------------------------------------------------------+-------------------+-------------+----------+-------------------+------------+------------+------------------+----------+
-| BackendId | IP        | HeartbeatPort | BePort | HttpPort | BrpcPort | LastStartTime       | LastHeartbeat       | Alive | SystemDecommissioned | ClusterDecommissioned | TabletNum | DataUsedCapacity | AvailCapacity | TotalCapacity | UsedPct | MaxDiskUsedPct | ErrMsg | Version            | Status                                                 | DataTotalCapacity | DataUsedPct | CpuCores | NumRunningQueries | MemUsedPct | CpuUsedPct | DataCacheMetrics | Location |
-+-----------+-----------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+--------------------+--------------------------------------------------------+-------------------+-------------+----------+-------------------+------------+------------+------------------+----------+
-```
-
-返回信息中的参数说明如下：
-
-| **参数**               | **说明**                                                     |
-| --------------------- | ------------------------------------------------------------ |
-| BackendId             | BE 的 ID。                                                   |
-| IP                    | BE 的 IP 地址。                                              |
-| HeartbeatPort         | BE 上的心跳端口，用于接收来自 FE 的心跳。                    |
-| BePort                | BE 上的 Thrift server 端口， 用于接收来自 FE 的请求。        |
-| HttpPort              | BE 上的 HTTP server 端口，用于网页访问 BE。                  |
-| BrpcPort              | BE 上的 bRPC 端口，用于 BE 之间通讯。                        |
-| LastStartTime         | BE 最后一次启动的时间。                                      |
-| LastHeartbeat         | FE 最后一次发心跳给 BE，且 BE 成功回复的时间。               |
-| Alive                 | BE 是否存活。<ul><li>`true`：表示存活。</li><li>`false`：表示没有存活。 </li></ul>      |
-| SystemDecommissioned  | BE 是否已下线。下线前，该 BE 节点的数据会迁移到其他 BE 节点上，期间不影响数据导入和查询。<ul><li>`true`：表示集群已经标记该 BE 下线（数据可能已经完成迁移，或还在迁移中）。</li><li>`false`：表示集群正常使用该 BE（未执行下线操作）。</li></ul> |
-| ClusterDecommissioned | 该参数用于系统兼容。                                         |
-| TabletNum             | BE 上 tablet 的数量。                                        |
-| DataUsedCapacity      | 数据文件占用的磁盘空间。                                     |
-| AvailCapacity         | 可使用的磁盘空间。                                           |
-| TotalCapacity         | 总磁盘空间，即为 `DataUsedCapacity` + `AvailCapacity` + 非数据文件占用的空间。 |
-| UsedPct               | 磁盘使用量百分比。                                           |
-| MaxDiskUsedPct        | 一个 BE 节点如果有多个存储数据的路径，该参数为存储数据最多的路径占用磁盘的百分比。 |
-| ErrMsg                | 接收 FE 心跳失败时的错误信息。                               |
-| Version               | 当前集群的版本。                                             |
-| Status                | BE 最后一次向 FE 报告 tablet 数量的时间，以 JSON 格式显示 。 |
-| DataTotalCapacity     | `DataUsedCapacity` + `AvailCapacity`，即数据文件所占用的磁盘空间 + 可使用的磁盘空间。 |
-| DataUsedPct           | `DataUsedCapacity`/`DataTotalCapacity`，即数据文件所占用的磁盘空间/（数据文件所占用的磁盘空间 + 可使用的磁盘空间）。 |
-| CpuCores              | BE 机器的 CPU 核数。                                         |
-| NumRunningQueries     | BE 上正在运行的查询数量。                                      |
-| MemUsedPct            | 内存使用量百分比。                                            |
-| CpuUsedPct            | CPU 使用量百分比。                                           |
-| DataCacheMetrics      | Data Cache 状态：<ul><li>`Disabled`：未开启。</li><li>`Normal`：正常。 </li><li>`Abnormal`：异常。 </li><li>`Updating`：正在执行变更操作，例如扩缩容等。 </li></ul>                      |
-| Location              | BE 节点的标签。更多信息，参考[使用标签管理 BE 节点](../../../administration/management/resource_management/be_label.md)。                      |
-
-## 示例
-
-查看当前集群中的所有 BE 节点的相关信息。
-
-```Plain
-SHOW BACKENDS;
-
-+-----------+---------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+----------------------+--------------------------------------------------------+-------------------+-------------+----------+
-| BackendId | IP      | HeartbeatPort | BePort | HttpPort | BrpcPort | LastStartTime       | LastHeartbeat       | Alive | SystemDecommissioned | ClusterDecommissioned | TabletNum | DataUsedCapacity | AvailCapacity | TotalCapacity | UsedPct | MaxDiskUsedPct | ErrMsg | Version              | Status                                                 | DataTotalCapacity | DataUsedPct | CpuCores |
-+-----------+---------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+----------------------+--------------------------------------------------------+-------------------+-------------+----------+
-| 10002     | x.x.x.x | 9254          | 9260   | 8238     | 8260     | 2022-09-08 14:37:10 | 2022-09-08 15:14:21 | true  | false                | false                 | 21753     | 25.122 GB        | 1.088 TB      | 1.968 TB      | 44.72 % | 44.72 %        |        | MAIN-RELEASE-d094052 | {"lastSuccessReportTabletsTime":"2022-09-08 15:14:13"} | 1.113 TB          | 2.20 %      | 16       |
-| 10003     | x.x.x.x | 9254          | 9260   | 8238     | 8260     | 2022-09-08 14:37:20 | 2022-09-08 15:14:21 | true  | false                | false                 | 21754     | 25.121 GB        | 1.169 TB      | 1.968 TB      | 40.61 % | 40.61 %        |        | MAIN-RELEASE-d094052 | {"lastSuccessReportTabletsTime":"2022-09-08 15:14:22"} | 1.194 TB          | 2.06 %      | 16       |
-| 10004     | x.x.x.x | 9254          | 9260   | 8238     | 8260     | 2022-09-08 14:37:39 | 2022-09-08 15:14:21 | true  | false                | false                 | 21754     | 25.112 GB        | 1.172 TB      | 1.968 TB      | 40.46 % | 40.46 %        |        | MAIN-RELEASE-d094052 | {"lastSuccessReportTabletsTime":"2022-09-08 15:13:42"} | 1.197 TB          | 2.05 %      | 16       |
-+-----------+---------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+----------------------+--------------------------------------------------------+-------------------+-------------+----------+
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_BACKEND_BLACKLIST.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_BACKEND_BLACKLIST.md
deleted file mode 100644
index 74653127540daa..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_BACKEND_BLACKLIST.md
+++ /dev/null
@@ -1,50 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW BACKEND BLACKLIST
-
-## 功能
-
-查看 BE 黑名单中的节点。
-
-此功能自 v3.3.0 起支持。更多信息，参考[管理 BE 黑名单](../../../administration/management/BE_blacklist.md)。
-
-:::note
-
-该操作需要有 SYSTEM 级 BLACKLIST 权限。
-
-:::
-
-## 语法
-
-```SQL
-SHOW BACKEND BLACKLIST
-```
-
-## 返回
-
-| **返回**                     | **说明**                                                     |
-| ---------------------------- | ------------------------------------------------------------ |
-| AddBlackListType             | BE 节点被添加到黑名单的方式。`MANUAL` 表示由用户手动添加到黑名单。`AUTO` 表示由 StarRocks 自动添加到黑名单。 |
-| LostConnectionTime           | 对于 `MANUAL` 类型，表示 BE 节点被手动添加到黑名单的时间。<br />对于 `AUTO` 类型，表示最后一次成功建立连接的时间。 |
-| LostConnectionNumberInPeriod | 在 `CheckTimePeriod(s)` 内检测到的断连次数。                 |
-| CheckTimePeriod(s)           | StarRocks 检查黑名单中 BE 节点连接状态的间隔。其值等于您在 FE 配置项 `black_host_history_sec` 中指定的值。单位：秒。 |
-
-## 示例
-
-```SQL
-SHOW BACKEND BLACKLIST;
-+-----------+------------------+---------------------+------------------------------+--------------------+
-| BackendId | AddBlackListType | LostConnectionTime  | LostConnectionNumberInPeriod | CheckTimePeriod(s) |
-+-----------+------------------+---------------------+------------------------------+--------------------+
-| 10001     | MANUAL           | 2024-04-28 11:52:09 | 0                            | 5                  |
-+-----------+------------------+---------------------+------------------------------+--------------------+
-```
-
-## 相关 SQL
-
-- [ADD BACKEND BLACKLIST](./ADD_BACKEND_BLACKLIST.md)
-- [DELETE BACKEND BLACKLIST](./DELETE_BACKEND_BLACKLIST.md)
-- [SHOW BACKENDS](./SHOW_BACKENDS.md)
-
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_BROKER.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_BROKER.md
deleted file mode 100644
index aa7f42f854637e..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_BROKER.md
+++ /dev/null
@@ -1,26 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW BROKER
-
-## 功能
-
-该语句用于查看当前存在的 broker。
-
-> **注意**
->
-> 该操作需要 SYSTEM 级 OPERATE 权限或 cluster_admin 角色。
-
-## 语法
-
-```sql
-SHOW BROKER
-```
-
-命令返回结果说明：
-
-1. LastStartTime 表示最近一次 BE 启动时间。
-2. LastHeartbeat 表示最近一次心跳。
-3. Alive 表示节点是否存活。
-4. ErrMsg 用于显示心跳失败时的错误信息。
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_COMPUTE_NODES.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_COMPUTE_NODES.md
deleted file mode 100644
index 447c581dab1b5f..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_COMPUTE_NODES.md
+++ /dev/null
@@ -1,86 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW COMPUTE NODES
-
-## 功能
-
-查看当前集群中所有 CN 节点的相关信息。
-
-> **注意**
->
-> 该操作需要 SYSTEM 级 OPERATE 权限或 `cluster_admin` 角色。
-
-## 语法
-
-```sql
-SHOW COMPUTE NODES
-```
-
-## 返回信息说明
-
-```SQL
-+---------------+--------------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+--------+--------------------+----------+-------------------+------------+------------+----------------+-------------+----------+-------------------+-----------+
-| ComputeNodeId | IP           | HeartbeatPort | BePort | HttpPort | BrpcPort | LastStartTime       | LastHeartbeat       | Alive | SystemDecommissioned | ClusterDecommissioned | ErrMsg | Version            | CpuCores | NumRunningQueries | MemUsedPct | CpuUsedPct | HasStoragePath | StarletPort | WorkerId | WarehouseName     | TabletNum |
-+---------------+--------------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+--------+--------------------+----------+-------------------+------------+------------+----------------+-------------+----------+-------------------+-----------+
-```
-
-返回信息中的参数说明如下：
-
-| **参数**              | **说明**                                                          |
-| -------------------- | ----------------------------------------------------------------- |
-| ComputeNodeId        | CN 的 ID。                                                         |
-| IP                   | CN 的 IP 地址。                                                    |
-| HeartbeatPort        | CN 上的心跳端口，用于接收来自 FE 的心跳。                               |
-| BePort               | CN 上的 Thrift server 端口， 用于接收来自 FE 的请求。                  |
-| HttpPort             | CN 上的 HTTP server 端口，用于网页访问 BE。                           |
-| BrpcPort             | CN 上的 bRPC 端口，用于 CN 之间通讯。                                 |
-| LastStartTime        | CN 最后一次启动的时间。                                              |
-| LastHeartbeat        | FE 最后一次发心跳给 BE，且 CN 成功回复的时间。                          |
-| Alive                | CN 是否存活。<ul><li>`true`：表示存活。</li><li>`false`：表示没有存活。 </li></ul> |
-| SystemDecommissioned | CN 是否已下线。`true`：表示集群已经标记该 CN 下线。                     |
-| ClusterDecommissioned | 该参数用于系统兼容。                                                |
-| ErrMsg               | 接收 FE 心跳失败时的错误信息。                                        |
-| Version              | CN 的 StarRocks 版本。                                             |
-| CpuCores             | CN 机器的 CPU 核数。                                                |
-| NumRunningQueries    | CN 上正在运行的查询数量。                                             |
-| MemUsedPct           | 内存使用量百分比。                                                   |
-| CpuUsedPct           | CPU 使用量百分比。                                                  |
-| HasStoragePath       | CN 是否配置有存储路径。                                               |
-| StarletPort          | CN 的 `starlet_port`。该端口为额外 Agent 服务端口。                   |
-| WorkerId             | CN 的内部调度 ID。                                                  |
-| WarehouseName        | CN 所属的 Warehouse 名。该值恒为 `default_warehouse`。               |
-| TabletNum            | CN 上 Tablet 的数量（仅针对 Cache 中的数据）。                         |
-
-## 示例
-
-查看当前集群中的所有 CN 节点的相关信息。
-
-```Plain
-MySQL > SHOW COMPUTE NODES\G
-*************************** 1. row ***************************
-        ComputeNodeId: 10001
-                   IP: x.x.x.x
-        HeartbeatPort: 9050
-               BePort: 9060
-             HttpPort: 8040
-             BrpcPort: 8060
-        LastStartTime: 2024-05-14 15:45:34
-        LastHeartbeat: 2024-05-14 15:47:59
-                Alive: true
- SystemDecommissioned: false
-ClusterDecommissioned: false
-               ErrMsg: 
-              Version: 3.3.0-rc01-3b8cb0c
-             CpuCores: 4
-    NumRunningQueries: 0
-           MemUsedPct: 1.95 %
-           CpuUsedPct: 0.0 %
-       HasStoragePath: true
-          StarletPort: 8167
-             WorkerId: 1
-        WarehouseName: default_warehouse
-            TabletNum: 58
-1 row in set (0.00 sec)
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_FILE.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_FILE.md
deleted file mode 100644
index a145dfcd2c2cb2..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_FILE.md
+++ /dev/null
@@ -1,36 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW FILE
-
-SHOW FILE 语句用于查看保存在数据库中的文件的信息。
-
-:::tip
-
-该操作需要用户有 File 所属数据库上的任意权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。当一个文件归属于一个数据库时，对该数据库拥有访问权限的用户都可以使用该文件。
-
-:::
-
-## 语法
-
-```SQL
-SHOW FILE [FROM database]
-```
-
-语句返回的信息如下：
-
-- `FileId`: 文件ID，全局唯一。
-- `DbName`: 所属数据库。
-- `Catalog`: 自定义类别。
-- `FileName`: 文件名。
-- `FileSize`: 文件大小，单位字节。
-- `MD5`: 消息摘要算法，用于检查文件。
-
-## 示例
-
-查看保存在数据库 `my_database` 中的文件。
-
-```SQL
-SHOW FILE FROM my_database;
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_FRONTENDS.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_FRONTENDS.md
deleted file mode 100644
index ab21448589074f..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_FRONTENDS.md
+++ /dev/null
@@ -1,29 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW FRONTENDS
-
-## 功能
-
-该语句用于查看 FE 节点。FE 节点添加方式及高可用部署请参考 [集群部署](../../../deployment/deploy_manually.md) 章节。
-
-> **注意**
->
-> 该操作需要 SYSTEM 级 OPERATE 权限或 cluster_admin 角色。
-
-## 语法
-
-```sql
-SHOW FRONTENDS
-```
-
-命令返回结果说明：
-
-1. name 表示该 FE 节点在 bdbje 中的名称。
-2. Join 为 true 表示该节点曾经加入过集群。但不代表当前还在集群内（可能已失联）
-3. Alive 表示节点是否存活。
-4. ReplayedJournalId 表示该节点当前已经回放的最大元数据日志 id。
-5. LastHeartbeat 是最近一次心跳。
-6. IsHelper 表示该节点是否是 bdbje 中的 helper 节点。
-7. ErrMsg 用于显示心跳失败时的错误信息。
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_PLUGINS.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_PLUGINS.md
deleted file mode 100644
index e9b536b36ddf54..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_PLUGINS.md
+++ /dev/null
@@ -1,31 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW PLUGINS
-
-## 功能
-
-该语句用于展示已安装的插件。
-
-:::tip
-
-该操作需要 SYSTEM 级 PLUGIN 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```sql
-SHOW PLUGINS
-```
-
-该命令会展示所有用户安装的和系统内置的插件。
-
-## 示例
-
-1. 展示已安装的插件：
-
-    ```sql
-    SHOW PLUGINS;
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_PROC.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_PROC.md
deleted file mode 100644
index 49903e0be22020..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_PROC.md
+++ /dev/null
@@ -1,442 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW PROC
-
-## 功能
-
-查看当前集群中的特定指标。
-
-> **注意**
->
-> 该操作需要 SYSTEM 级 OPERATE 权限。
-
-## 语法
-
-```SQL
-SHOW PROC { '/backends' | '/compute_nodes' | '/dbs' 
-          | '/jobs' | '/statistic' | '/tasks' | '/frontends' 
-          | '/brokers' | '/resources' | '/load_error_hub' 
-          | '/transactions' | '/monitor' | '/current_queries' 
-          | '/current_backend_instances' | '/cluster_balance' 
-          | '/routine_loads' | '/colocation_group' | '/catalog' }
-```
-
-## 参数说明
-
-| **参数**                     | **说明**                                                     |
-| ---------------------------- | ------------------------------------------------------------ |
-| '/backends'                  | 查看当前集群的 BE 节点信息。                                 |
-| '/compute_nodes'             | 查看当前集群的 CN 节点信息。                                 |
-| '/dbs'                       | 查看当前集群的数据库信息。                                   |
-| '/jobs'                      | 查看当前集群的作业信息。                                     |
-| '/statistic'                 | 查看当前集群各数据库的统计信息。                             |
-| '/tasks'                     | 查看当前集群各种任务类型的总数和失败总数。                   |
-| '/frontends'                 | 查看当前集群的 FE 节点信息。                                 |
-| '/brokers'                   | 查看当前集群的 Broker 节点信息。                             |
-| '/resources'                 | 查看当前集群的资源信息。                                     |
-| '/load_error_hub'            | 查看当前集群的 Error Hub 的配置信息。Error Hub 用于管理导入作业产生的错误信息。 |
-| '/transactions'              | 查看当前集群的事务信息。                                     |
-| '/monitor'                   | 查看当前集群的监控信息。                                     |
-| '/current_queries'           | 查看当前连接的FE节点正在执行的查询信息。                       |
-| '/current_backend_instances' | 查看当前集群正在执行作业的 BE 节点。                         |
-| '/cluster_balance'           | 查看当前集群的负载信息。                                     |
-| '/routine_loads'             | 查看当前集群的 Routine Load 导入信息。                       |
-| '/colocation_group'          | 查看当前集群的 Colocate Join Group 信息。                    |
-| '/catalog'                   | 查看当前集群的 Catalog 信息。                                |
-
-## 示例
-
-示例一：查看当前集群的 BE 节点信息。
-
-```Plain
-mysql> SHOW PROC '/backends'\G
-*************************** 1. row ***************************
-            BackendId: 10004
-                   IP: xxx.xx.92.200
-        HeartbeatPort: 9354
-               BePort: 9360
-             HttpPort: 8338
-             BrpcPort: 8360
-        LastStartTime: 2023-04-21 09:56:10
-        LastHeartbeat: 2023-04-21 09:56:10
-                Alive: true
- SystemDecommissioned: false
-ClusterDecommissioned: false
-            TabletNum: 2199
-     DataUsedCapacity: 0.000 
-        AvailCapacity: 584.578 GB
-        TotalCapacity: 1.968 TB
-              UsedPct: 71.00 %
-       MaxDiskUsedPct: 71.00 %
-               ErrMsg: 
-              Version: BRANCH-3.0-RELEASE-8eb8705
-               Status: {"lastSuccessReportTabletsTime":"N/A"}
-    DataTotalCapacity: 584.578 GB
-          DataUsedPct: 0.00 %
-             CpuCores: 16
-    NumRunningQueries: 0
-           MemUsedPct: 0.52 %
-           CpuUsedPct: 0.0 %
-```
-
-| **返回**              | **说明**                                                     |
-| --------------------- | ------------------------------------------------------------ |
-| BackendId             | BE 节点 ID。                                                 |
-| IP                    | BE 节点 IP 地址。                                            |
-| HeartbeatPort         | BE 节点心跳服务端口。                                        |
-| BePort                | BE 节点 Thrift Server 端口。                                 |
-| HttpPort              | BE 节点 HTTP Server 端口。                                   |
-| BrpcPort              | BE 节点 bRPC 端口。                                          |
-| LastStartTime         | BE 节点上一次启动时间。                                      |
-| LastHeartbeat         | BE 节点上一次接受 FE 心跳时间。                              |
-| Alive                 | BE 节点存活状态。                                            |
-| SystemDecommissioned  | BE 节点是否正在下线。                                        |
-| ClusterDecommissioned | BE 节点是否正在集群中下线。                                  |
-| TabletNum             | BE 节点 Tablet 数量。                                        |
-| DataUsedCapacity      | BE 节点被占用的存储空间。                                    |
-| AvailCapacity         | BE 节点剩余存储空间。                                        |
-| TotalCapacity         | BE 节点总存储空间。                                          |
-| UsedPct               | BE 节点当前存储空间占用比例。                                |
-| MaxDiskUsedPct        | BE 节点最大存储空间占用比例。                                |
-| ErrMsg                | BE 节点错误信息。                                            |
-| Version               | BE 节点 StarRocks 版本。                                     |
-| Status                | BE节点状态信息，包含最近一次 BE 汇报 Tablet 的时间信息。     |
-| DataTotalCapacity     | 数据文件所占用的磁盘空间 + 可用磁盘空间，即 DataUsedCapacity + AvailCapacity。 |
-| DataUsedPct           | 数据文件占用磁盘的比例，即 DataUsedCapacity/DataTotalCapacity。 |
-| CpuCores              | BE 节点 CPU 核数。                                           |
-| NumRunningQueries     | 当前运行中的查询数量。                                            |
-| MemUsedPct            | 当前内存使用占比。                                            |
-| CpuUsedPct            | 当前 CPU 使用占比。                                          |
-
-示例二：查看当前集群的数据库信息。
-
-```Plain
-mysql> SHOW PROC '/dbs';
-+---------+------------------------+----------+----------------+--------------------------+---------------------+
-| DbId    | DbName                 | TableNum | Quota          | LastConsistencyCheckTime | ReplicaQuota        |
-+---------+------------------------+----------+----------------+--------------------------+---------------------+
-| 1       | information_schema     | 22       | 8388608.000 TB | NULL                     | 9223372036854775807 |
-| 840997  | tpcds_100g             | 25       | 1024.000 GB    | NULL                     | 1073741824          |
-| 1275196 | _statistics_           | 3        | 8388608.000 TB | 2022-09-06 23:00:58      | 9223372036854775807 |
-| 1286207 | tpcds_n                | 24       | 8388608.000 TB | NULL                     | 9223372036854775807 |
-| 1381289 | test                   | 6        | 8388608.000 TB | 2022-01-14 23:10:18      | 9223372036854775807 |
-| 6186781 | test_stddev            | 1        | 8388608.000 TB | 2022-09-06 23:00:58      | 9223372036854775807 |
-+---------+------------------------+----------+----------------+--------------------------+---------------------+
-```
-
-| **返回**                 | **说明**                     |
-| ------------------------ | ---------------------------- |
-| DbId                     | 数据库 ID。                  |
-| DbName                   | 数据库名称。                 |
-| TableNum                 | 数据库包含表数量。           |
-| Quota                    | 数据库设置的存储配额。       |
-| LastConsistencyCheckTime | 数据库上一次一致性检查时间。 |
-| ReplicaQuota             | 数据库的副本配额。           |
-
-示例三：查看当前集群的作业信息。您可以通过对应的 `DbId` 进一步查询该数据库中的详细作业信息。
-
-```Plain
-mysql> SHOW PROC '/jobs';
-+-------+--------------------------------------+
-| DbId  | DbName                               |
-+-------+--------------------------------------+
-| 10005 | default_cluster:_statistics_         |
-| 0     | default_cluster:information_schema   |
-| 12711 | default_cluster:starrocks_audit_db__ |
-+-------+--------------------------------------+
-3 rows in set (0.00 sec)
-
-mysql> SHOW PROC '/jobs/10005';
-+---------------+---------+---------+----------+-----------+-------+
-| JobType       | Pending | Running | Finished | Cancelled | Total |
-+---------------+---------+---------+----------+-----------+-------+
-| load          | 0       | 0       | 3        | 0         | 3     |
-| rollup        | 0       | 0       | 0        | 0         | 0     |
-| schema_change | 0       | 0       | 0        | 0         | 0     |
-| export        | 0       | 0       | 0        | 0         | 0     |
-+---------------+---------+---------+----------+-----------+-------+
-4 rows in set (0.00 sec)
-```
-
-| **返回**  | **说明**         |
-| --------- | ---------------- |
-| DbId      | 数据库 ID。      |
-| DbName    | 数据库名称。     |
-| JobType   | 作业类型。       |
-| Pending   | 待执行作业数。   |
-| Running   | 正在执行作业数。 |
-| Finished  | 已完成作业数。   |
-| Cancelled | 已取消作业数。   |
-| Total     | 总作业数。       |
-
-示例四：查看当前集群各数据库的统计信息。
-
-```Plain
-mysql> SHOW PROC '/statistic';
-+--------+----------------------------------------------------------+----------+--------------+----------+-----------+------------+--------------------+-----------------------+------------------+---------------------+
-| DbId   | DbName                                                   | TableNum | PartitionNum | IndexNum | TabletNum | ReplicaNum | UnhealthyTabletNum | InconsistentTabletNum | CloningTabletNum | ErrorStateTabletNum |
-+--------+----------------------------------------------------------+----------+--------------+----------+-----------+------------+--------------------+-----------------------+------------------+---------------------+
-| 10004  | _statistics_                                             | 3        | 3            | 3        | 30        | 60         | 0                  | 0                     | 0                | 0                   |
-| 1      | information_schema                                       | 0        | 0            | 0        | 0         | 0          | 0                  | 0                     | 0                | 0                   |
-| 92498  | stream_load_test_db_03afc714_b1cb_11ed_a82c_00163e237e98 | 0        | 0            | 0        | 0         | 0          | 0                  | 0                     | 0                | 0                   |
-| 92542  | stream_load_test_db_79876e92_b1da_11ed_b50e_00163e237e98 | 1        | 1            | 1        | 3         | 3          | 0                  | 0                     | 0                | 0                   |
-| 115476 | testdb                                                   | 0        | 0            | 0        | 0         | 0          | 0                  | 0                     | 0                | 0                   |
-| 10002  | zq_test                                                  | 8        | 8            | 8        | 5043      | 7063       | 0                  | 0                     | 0                | 2                   |
-| Total  | 6                                                        | 12       | 12           | 12       | 5076      | 7126       | 0                  | 0                     | 0                | 2                   |
-+--------+----------------------------------------------------------+----------+--------------+----------+-----------+------------+--------------------+-----------------------+------------------+---------------------+
-7 rows in set (0.01 sec)
-
-mysql> show proc '/statistic/10002';
-+------------------+---------------------+----------------+-------------------+
-| UnhealthyTablets | InconsistentTablets | CloningTablets | ErrorStateTablets |
-+------------------+---------------------+----------------+-------------------+
-| []               | []                  | []             | [116703, 116706]  |
-+------------------+---------------------+----------------+-------------------+
-```
-
-| **返回**              | **说明**                                    |
-| --------------------- | ------------------------------------------- |
-| DbId                  | 数据库 ID。                                 |
-| DbName                | 数据库名称。                                |
-| TableNum              | 数据库中表的数量。                          |
-| PartitionNum          | 数据库中分区的数量。                        |
-| IndexNum              | 数据库中索引的数量。                        |
-| TabletNum             | 数据库中 Tablet 的数量。                    |
-| ReplicaNum            | 数据库中副本的数量。                        |
-| UnhealthyTabletNum    | 数据重分布过程中还未完成的 Tablet 数量。      |
-| InconsistentTabletNum | 数据库中不一致的 Tablet 数量。              |
-| CloningTabletNum      | 数据库中正在进行 Clone 操作的 Tablet 数量。   |
-| ErrorStateTabletNum   | 主键表中错误状态的 Tablet 数量。          |
-| ErrorStateTablets     | 主键表中错误状态的 Tablet 的 ID。         |
-
-示例五：查看当前集群各种任务类型的总数和失败总数。
-
-```Plain
-mysql> SHOW PROC '/tasks';
-+-------------------------+-----------+----------+
-| TaskType                | FailedNum | TotalNum |
-+-------------------------+-----------+----------+
-| CREATE                  | 0         | 0        |
-| DROP                    | 0         | 0        |
-| PUSH                    | 0         | 0        |
-| CLONE                   | 0         | 0        |
-| STORAGE_MEDIUM_MIGRATE  | 0         | 0        |
-| ROLLUP                  | 0         | 0        |
-| SCHEMA_CHANGE           | 0         | 0        |
-| CANCEL_DELETE           | 0         | 0        |
-| MAKE_SNAPSHOT           | 0         | 0        |
-| RELEASE_SNAPSHOT        | 0         | 0        |
-| CHECK_CONSISTENCY       | 0         | 0        |
-| UPLOAD                  | 0         | 0        |
-| DOWNLOAD                | 0         | 0        |
-| CLEAR_REMOTE_FILE       | 0         | 0        |
-| MOVE                    | 0         | 0        |
-| REALTIME_PUSH           | 0         | 0        |
-| PUBLISH_VERSION         | 0         | 0        |
-| CLEAR_ALTER_TASK        | 0         | 0        |
-| CLEAR_TRANSACTION_TASK  | 0         | 0        |
-| RECOVER_TABLET          | 0         | 0        |
-| STREAM_LOAD             | 0         | 0        |
-| UPDATE_TABLET_META_INFO | 0         | 0        |
-| ALTER                   | 0         | 0        |
-| INSTALL_PLUGIN          | 0         | 0        |
-| UNINSTALL_PLUGIN        | 0         | 0        |
-| NUM_TASK_TYPE           | 0         | 0        |
-| Total                   | 0         | 0        |
-+-------------------------+-----------+----------+
-```
-
-| **返回**  | **说明**     |
-| --------- | ------------ |
-| TaskType  | 任务类型。   |
-| FailedNum | 失败任务数。 |
-| TotalNum  | 总任务数。   |
-
-示例六：查看当前集群的 FE 节点信息。
-
-```Plain
-mysql> SHOW PROC '/frontends';
-+----------------------------------+---------------+-------------+----------+-----------+---------+----------+------------+-------+-------+-------------------+---------------+----------+---------------+-----------+---------+
-| Name                             | IP            | EditLogPort | HttpPort | QueryPort | RpcPort | Role     | ClusterId  | Join  | Alive | ReplayedJournalId | LastHeartbeat | IsHelper | ErrMsg        | StartTime | Version |
-+----------------------------------+---------------+-------------+----------+-----------+---------+----------+------------+-------+-------+-------------------+---------------+----------+---------------+-----------+---------+
-| xxx.xx.xx.xxx_9009_1600088918395 | xxx.xx.xx.xxx | 9009        | 7390     | 0         | 0       | FOLLOWER | 1747363037 | false | false | 0                 | NULL          | true     | got exception | NULL      | NULL    |
-+----------------------------------+---------------+-------------+----------+-----------+---------+----------+------------+-------+-------+-------------------+---------------+----------+---------------+-----------+---------+
-```
-
-| **返回**          | **说明**                                      |
-| ----------------- | --------------------------------------------- |
-| Name              | FE 节点名称。                                 |
-| IP                | FE 节点 IP 地址。                             |
-| EditLogPort       | FE 节点之间的通信端口。                       |
-| HttpPort          | FE 节点 HTTP Server 端口。                    |
-| QueryPort         | FE 节点 MySQL Server 端口。                   |
-| RpcPort           | FE 节点 RPC 端口。                            |
-| Role              | FE 节点角色（Leader、Follower 或 Observer）。 |
-| ClusterId         | 集群 ID。                                     |
-| Join              | FE 节点是否曾加入过集群。                     |
-| Alive             | FE 节点存活状态。                             |
-| ReplayedJournalId | FE 节点已回放过的最大元数据日志 ID。          |
-| LastHeartbeat     | FE 节点上一次发送心跳时间。                   |
-| IsHelper          | FE 节点是否为 BDBJE 的 Helper 节点。          |
-| ErrMsg            | FE 节点错误信息。                             |
-| StartTime         | FE 节点启动时间。                             |
-| Version           | FE 节点 StarRocks 版本。                      |
-
-示例七：查看当前集群的 Broker 节点信息。
-
-```Plain
-mysql> SHOW PROC '/brokers';
-+-------------+---------------+------+-------+---------------+---------------------+--------+
-| Name        | IP            | Port | Alive | LastStartTime | LastUpdateTime      | ErrMsg |
-+-------------+---------------+------+-------+---------------+---------------------+--------+
-| hdfs_broker | xxx.xx.xx.xxx | 8500 | true  | NULL          | 2022-10-10 16:37:59 |        |
-| hdfs_broker | xxx.xx.xx.xxx | 8500 | true  | NULL          | 2022-10-10 16:37:59 |        |
-| hdfs_broker | xxx.xx.xx.xxx | 8500 | true  | NULL          | 2022-10-10 16:37:59 |        |
-+-------------+---------------+------+-------+---------------+---------------------+--------+
-```
-
-| **返回**       | **说明**                                         |
-| -------------- | ------------------------------------------------ |
-| Name           | Broker 节点名称。                                |
-| IP             | Broker 节点 IP 地址。                            |
-| Port           | Broker 节点的 Thrift Server 端口，用于接收请求。 |
-| Alive          | Broker 节点存活状态。                            |
-| LastStartTime  | Broker 节点上一次启动时间。                      |
-| LastUpdateTime | Broker 节点上一次更新时间。                      |
-| ErrMsg         | Broker 节点错误信息。                            |
-
-示例八：查看当前集群的资源信息。
-
-```Plain
-mysql> SHOW PROC '/resources';
-+-------------------------+--------------+---------------------+------------------------------+
-| Name                    | ResourceType | Key                 | Value                        |
-+-------------------------+--------------+---------------------+------------------------------+
-| hive_resource_stability | hive         | hive.metastore.uris | thrift://xxx.xx.xxx.xxx:9083 |
-| hive2                   | hive         | hive.metastore.uris | thrift://xxx.xx.xx.xxx:9083  |
-+-------------------------+--------------+---------------------+------------------------------+
-```
-
-| **返回**     | **说明**     |
-| ------------ | ------------ |
-| Name         | 资源名称。   |
-| ResourceType | 资源类型。   |
-| Key          | 资源关键字。 |
-| Value        | 资源值。     |
-
-示例九：查看当前集群的事务信息。您可以通过对应的 `DbId` 进一步查询该数据库中的详细事务信息。
-
-```Plain
-mysql> SHOW PROC '/transactions';
-+-------+--------------------------------------+
-| DbId  | DbName                               |
-+-------+--------------------------------------+
-| 10005 | default_cluster:_statistics_         |
-| 12711 | default_cluster:starrocks_audit_db__ |
-+-------+--------------------------------------+
-2 rows in set (0.00 sec)
-
-mysql> SHOW PROC '/transactions/10005';
-+----------+--------+
-| State    | Number |
-+----------+--------+
-| running  | 0      |
-| finished | 4      |
-+----------+--------+
-2 rows in set (0.00 sec)
-```
-
-| **返回** | **说明**     |
-| -------- | ------------ |
-| DbId     | 数据库 ID。  |
-| DbName   | 数据库名称。 |
-| State    | 事务状态。   |
-| Number   | 事务数量。   |
-
-示例十：查看当前集群的监控信息。
-
-```Plain
-mysql> SHOW PROC '/monitor';
-+------+------+
-| Name | Info |
-+------+------+
-| jvm  |      |
-+------+------+
-```
-
-| **返回** | **说明**   |
-| -------- | ---------- |
-| Name     | JVM 名称。 |
-| Info     | JVM 信息。 |
-
-示例十一：查看当前集群的负载信息。
-
-```Plain
-mysql> SHOW PROC '/cluster_balance';
-+-------------------+--------+
-| Item              | Number |
-+-------------------+--------+
-| cluster_load_stat | 1      |
-| working_slots     | 3      |
-| sched_stat        | 1      |
-| priority_repair   | 0      |
-| pending_tablets   | 2001   |
-| running_tablets   | 0      |
-| history_tablets   | 1000   |
-+-------------------+--------+
-```
-
-| **返回** | **说明**                                     |
-| -------- | -------------------------------------------- |
-| Item     | cluster_balance 中的子命令。<ul><li>cluster_load_stat: 集群当前的负载状态。</li><li>working_slots: 当前可用的工作插槽数。</li><li>sched_stat: 调度系统的当前状态。</li><li>priority_repair: 当前需要优先处理的 Tablet 修复任务数。</li><li>pending_tablets: 当前等待处理的 Tablet 数量。</li><li>running_tablets: 当前正在修复的 Tablet 数量。</li><li>history_tablets: 历史上修复过的 Tablet 数量。</li></ul>                 |
-| Number   | cluster_balance 中每个子命令正在执行的个数。 |
-
-示例十二：查看当前集群的 Colocate Join Group 信息。
-
-```Plain
-mysql> SHOW PROC '/colocation_group';
-+-----------------+----------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------+------------+----------------+-------------+----------+
-| GroupId         | GroupName                  | TableIds                                                                                                                                          | BucketsNum | ReplicationNum | DistCols    | IsStable |
-+-----------------+----------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------+------------+----------------+-------------+----------+
-| 24010.177354    | 24010_lineitem_str_g1      | 177672                                                                                                                                            | 12         | 1              | varchar(-1) | true     |
-| 24010.182146    | 24010_lineitem_str_g2      | 182144                                                                                                                                            | 192        | 1              | varchar(-1) | true     |
-| 1439318.1735496 | 1439318_group_agent_uid    | 1735677, 1738390                                                                                                                                  | 12         | 2              | bigint(20)  | true     |
-| 24010.37804     | 24010_gsdaf2449s9e         | 37802                                                                                                                                             | 192        | 1              | int(11)     | true     |
-| 174844.175370   | 174844_groupa4             | 175368, 591307, 591362, 591389, 591416                                                                                                            | 12         | 1              | int(11)     | true     |
-| 24010.30587     | 24010_group2               | 30585, 30669                                                                                                                                      | 12         | 1              | int(11)     | true     |
-| 10005.181366    | 10005_lineorder_str_normal | 181364                                                                                                                                            | 192        | 1              | varchar(-1) | true     |
-| 1904968.5973175 | 1904968_groupa2            | 5973173                                                                                                                                           | 12         | 1              | int(11)     | true     |
-| 24010.182535    | 24010_lineitem_str_g3      | 182533                                                                                                                                            | 192        | 1              | varchar(-1) | true     |
-+-----------------+----------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------+------------+----------------+-------------+----------+
-```
-
-| **返回**       | **说明**                              |
-| -------------- | ------------------------------------- |
-| GroupId        | Colocate Join Group 的 ID。           |
-| GroupName      | Colocate Join Group 的名称。          |
-| TableIds       | Colocate Join Group 所包含的表的 ID。 |
-| BucketsNum     | Colocate Join Group 的分桶数。        |
-| ReplicationNum | Colocate Join Group 的副本数。        |
-| DistCols       | Colocate Join Group 的分桶列类型。    |
-| IsStable       | Colocate Join Group 是否稳定。        |
-
-示例十三：查看当前集群的 Catalog 信息。
-
-```Plain
-mysql> SHOW PROC '/catalog';
-+--------------------------------------------------------------+----------+----------------------+
-| Catalog                                                      | Type     | Comment              |
-+--------------------------------------------------------------+----------+----------------------+
-| resource_mapping_inside_catalog_hive_hive2                   | hive     | mapping hive catalog |
-| resource_mapping_inside_catalog_hive_hive_resource_stability | hive     | mapping hive catalog |
-| default_catalog                                              | Internal | Internal Catalog     |
-+--------------------------------------------------------------+----------+----------------------+
-```
-
-| **返回** | **说明**       |
-| -------- | -------------- |
-| Catalog  | Catalog 名称。 |
-| Type     | Catalog 类型。 |
-| Comment  | Catalog 描述。 |
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_PROCESSLIST.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_PROCESSLIST.md
deleted file mode 100644
index 9aba79d0f82257..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_PROCESSLIST.md
+++ /dev/null
@@ -1,59 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW PROCESSLIST
-
-## 功能
-
-展示当前服务器内运行线程执行的操作。当前版本仅支持展示查询任务。
-
-:::tip
-
-该操作不需要权限。
-
-:::
-
-## 语法
-
-```SQL
-SHOW [FULL] PROCESSLIST
-```
-
-## 参数说明
-
-| 参数 | 必选 | 说明                                          |
-| ---- | ---- |---------------------------------------------|
-| FULL | 否   | 如果不指定该参数，则列出 SQL 语句的前 100 个字符。如果指定该参数，则列出完整 SQL 语句。 |
-
-## 返回
-
-| 返回                | 说明                           |
-| ------------------- | ------------------------------ |
-| Id                  | 连接ID                         |
-| User                | 线程所属用户名                 |
-| Host                | 发出语句的客户端的主机名       |
-| Db                  | 线程所属数据库名               |
-| Command             | 线程执行的命令类型             |
-| ConnectionStartTime | 连接开始时间                   |
-| Time                | 线程处于其当前状态的时间（单位：秒） |
-| State               | 线程运行状态                   |
-| Info                | 线程正在执行的语句             |
-
-## 注意事项
-
-如果当前用户为 `root`，则列出所有用户正在运行的线程；否则，仅列出当前用户运行的线程。
-
-## 示例
-
-示例一：通过 `root` 用户查看正在运行的线程。
-
-```Plain
-SHOW PROCESSLIST;
-
-+------+------+---------------------+-------+---------+---------------------+------+-------+------------------+
-| Id   | User | Host                | Db    | Command | ConnectionStartTime | Time | State | Info             |
-+------+------+---------------------+-------+---------+---------------------+------+-------+------------------+
-|  0   | root | x.x.x.x:xxxx        | tpcds | Query   | 2022-10-09 19:58:25 |    0 | OK    | SHOW PROCESSLIST |
-+------+------+---------------------+-------+---------+---------------------+------+-------+------------------+
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_PROFILELIST.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_PROFILELIST.md
deleted file mode 100644
index 14eeadf066bce6..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_PROFILELIST.md
+++ /dev/null
@@ -1,47 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW PROFILELIST
-
-## 功能
-
-列出 StarRocks 集群中缓存的 Query Profile 记录。更多信息，参考 [Query Profile 概述](../../../administration/query_profile_overview.md)。
-
-此功能自 v3.1 起支持。
-
-该操作无需任何权限。
-
-## 语法
-
-```SQL
-SHOW PROFILELIST [LIMIT n]
-```
-
-## 参数说明
-
-`LIMIT n`：列出最新 n 条记录。
-
-## 返回
-
-| **返回**  | **说明**                                                     |
-| --------- | ------------------------------------------------------------ |
-| QueryId   | 查询 ID。                                                    |
-| StartTime | 查询开始时间。                                               |
-| Time      | 查询时长。                                                   |
-| State     | 查询状态，其中包括`Error`：查询异常。`Finished`：查询执行结束。`Running`：查询正在执行。 |
-| Statement | 查询对应 SQL。                                               |
-
-## 示例
-
-示例一：列出最新 5 条 Query Profile 记录。
-
-```SQL
-SHOW PROFILELIST LIMIT 5;
-```
-
-## 相关 SQL
-
-- [ANALYZE PROFILE](./ANALYZE_PROFILE.md)
-- [EXPLAIN ANALYZE](./EXPLAIN_ANALYZE.md)
-
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_RESOURCE_GROUP.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_RESOURCE_GROUP.md
deleted file mode 100644
index 6058078b02482c..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_RESOURCE_GROUP.md
+++ /dev/null
@@ -1,56 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW RESOURCE GROUP
-
-## 功能
-
-查看资源组信息。
-
-## 语法
-
-```SQL
-SHOW { RESOURCE GROUPS [ALL] | RESOURCE GROUP resource_group_name }
-```
-
-## 参数说明
-
-| **参数**            | **说明**                                   |
-| ------------------- | ------------------------------------------ |
-| RESOURCE GROUPS     | 查看与当前用户匹配的资源组。               |
-| ALL                 | 如果表明此参数，则查看当前集群所有资源组。 |
-| RESOURCE GROUP      | 查看指定资源组信息。                       |
-| resource_group_name | 待查看资源组名。                           |
-
-## 返回
-
-| **返回**                   | **说明**                                                     |
-| -------------------------- | ------------------------------------------------------------ |
-| name                       | 资源组名。                                                   |
-| id                         | 资源组 ID。                                                  |
-| cpu_core_limit             | 资源组 CPU 核数上限。                                        |
-| mem_limit                  | 资源组内存资源上限。                                         |
-| big_query_cpu_second_limit | 大查询任务可以使用 CPU 的时间上限。                          |
-| big_query_scan_rows_limit  | 大查询任务可以扫描的行数上限。                               |
-| big_query_mem_limit        | 大查询任务可以使用的内存上限。                               |
-| concurrency_limit          | 资源组中并发查询数的上限。                                   |
-| type                       | 资源组类型。                                                 |
-| classifiers                | 资源组关联的分类器信息。其中，`id` 为分类器 ID，`weight` 为分类器匹配度。 |
-
-## 示例
-
-示例一：查看当前集群内所有资源组的信息。
-
-```Plain
-mysql> SHOW RESOURCE GROUPS ALL;
-+-------+--------+----------------+-----------+----------------------------+---------------------------+---------------------+-------------------+--------+------------------------------------------------------------------------------------------------------------------+
-| name  | id     | cpu_core_limit | mem_limit | big_query_cpu_second_limit | big_query_scan_rows_limit | big_query_mem_limit | concurrency_limit | type   | classifiers                                                                                                      |
-+-------+--------+----------------+-----------+----------------------------+---------------------------+---------------------+-------------------+--------+------------------------------------------------------------------------------------------------------------------+
-| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625127, weight=4.459375, user=rg1_user1, role=rg1_role1, query_type in (SELECT), source_ip=172.26.xxx.xx/24) |
-| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625128, weight=3.459375, user=rg1_user2, query_type in (SELECT), source_ip=172.26.xxx.xx/24)                 |
-| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625129, weight=2.359375, user=rg1_user3, source_ip=172.26.xxx.xx/24)                                         |
-| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625130, weight=1.0, user=rg1_user4)                                                                          |
-| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625131, weight=10.0, db='db1')                                                                                |
-+-------+--------+----------------+-----------+----------------------------+---------------------------+---------------------+-------------------+--------+------------------------------------------------------------------------------------------------------------------+
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_RUNNING_QUERIES.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_RUNNING_QUERIES.md
deleted file mode 100644
index 209d6fc35a1d99..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_RUNNING_QUERIES.md
+++ /dev/null
@@ -1,46 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW RUNNING QUERIES
-
-## 功能
-
-显示所有正在运行或在查询队列中等待执行的查询的信息。此功能从 v3.1.4 开始支持。
-
-:::tip
-
-该操作不需要权限。
-
-:::
-
-## 语法
-
-```SQL
-SHOW RUNNING QUERIES
-```
-
-## 返回
-
-- `QuerId`：该查询的 Query ID。
-- `ResourceGroupId`：该查询命中的资源组 ID。当没有命中用户定义的资源组时，会显示为 “-”。
-- `StartTime`：该查询开始时间。
-- `PendingTimeout`：PENDING 状态下查询在队列中超时的时间。
-- `QueryTimeout`：该查询超时的时间。
-- `State`：该查询的排队状态。其中，PENDING 表示在队列中；RUNNING 表示正在执行。
-- `Slots`：该查询申请的逻辑资源数量，目前固定为 `1`。
-- `Frontend`：发起该查询的 FE 节点。
-- `FeStartTime`：发起该查询的 FE 节点的启动时间。
-
-## 示例
-
-```Plain
-MySQL [(none)]> SHOW RUNNING QUERIES;
-+--------------------------------------+-----------------+---------------------+---------------------+---------------------+-----------+-------+---------------------------------+---------------------+
-| QueryId                              | ResourceGroupId | StartTime           | PendingTimeout      | QueryTimeout        |   State   | Slots | Frontend                        | FeStartTime         |
-+--------------------------------------+-----------------+---------------------+---------------------+---------------------+-----------+-------+---------------------------------+---------------------+
-| a46f68c6-3b49-11ee-8b43-00163e10863a | -               | 2023-08-15 16:56:37 | 2023-08-15 17:01:37 | 2023-08-15 17:01:37 |  RUNNING  | 1     | 127.00.00.01_9010_1692069711535 | 2023-08-15 16:37:03 |
-| a6935989-3b49-11ee-935a-00163e13bca3 | 12003           | 2023-08-15 16:56:40 | 2023-08-15 17:01:40 | 2023-08-15 17:01:40 |  RUNNING  | 1     | 127.00.00.02_9010_1692069658426 | 2023-08-15 16:37:03 |
-| a7b5e137-3b49-11ee-8b43-00163e10863a | 12003           | 2023-08-15 16:56:42 | 2023-08-15 17:01:42 | 2023-08-15 17:01:42 |  PENDING  | 1     | 127.00.00.03_9010_1692069711535 | 2023-08-15 16:37:03 |
-+--------------------------------------+-----------------+---------------------+---------------------+---------------------+-----------+-------+---------------------------------+---------------------+
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_SQLBLACKLIST.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_SQLBLACKLIST.md
deleted file mode 100644
index 5850aee6489b8c..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_SQLBLACKLIST.md
+++ /dev/null
@@ -1,44 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW SQLBLACKLIST
-
-## 功能
-
-显示 SQL 黑名单中的 SQL 正则表达式。
-
-有关 SQL 黑名单的更多信息，请参阅 [管理 SQL 黑名单](../../../administration/management/resource_management/Blacklist.md)。
-
-:::tip
-
-该操作需要 SYSTEM 级 BLACKLIST 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```SQL
-SHOW SQLBLACKLIST
-```
-
-## 返回
-
-| **返回**      | **说明**                              |
-| ------------- | ------------------------------------- |
-| Index         | 已加入黑名单的 SQL 正则表达式的序号。 |
-| Forbidden SQL | 已加入黑名单的 SQL 正则表达式。       |
-
-## 示例
-
-```Plain
-mysql> SHOW SQLBLACKLIST;
-+-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| Index | Forbidden SQL                                                                                                                                                                                                                                                                                          |
-+-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| 1     | select count\(\*\) from .+                                                                                                                                                                                                                                                                             |
-| 2     | select id_int \* 4, id_tinyint, id_varchar from test_all_type_nullable except select id_int, id_tinyint, id_varchar from test_basic except select \(id_int \* 9 \- 8\) \/ 2, id_tinyint, id_varchar from test_all_type_nullable2 except select id_int, id_tinyint, id_varchar from test_basic_nullable |
-| 3     | select id_int from test_all_type_select1 order by id_int limit [1-7], [5-7]                                                                                                                                                                                                                            |
-| 4     | select count\(distinct .+\) from .+                                                                                                                                                                                                                                                                    |
-+-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_STORAGE_VOLUMES.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_STORAGE_VOLUMES.md
deleted file mode 100644
index 2643ffb3fa337c..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_STORAGE_VOLUMES.md
+++ /dev/null
@@ -1,55 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW STORAGE VOLUMES
-
-## 功能
-
-显示当前 StarRocks 集群中的存储卷。该功能自 v3.1 起支持。
-
-:::tip
-
-该操作不需要权限。
-
-:::
-
-## 语法
-
-```SQL
-SHOW STORAGE VOLUMES [ LIKE '<pattern>' ]
-```
-
-## 参数说明
-
-| **参数** | **说明**               |
-| -------- | ---------------------- |
-| pattern  | 用于匹配存储卷的模式。 |
-
-## 返回
-
-| **返回**       | **说明**       |
-| -------------- | -------------- |
-| Storage Volume | 存储卷的名称。 |
-
-## 示例
-
-示例一：显示当前 StarRocks 集群中所有的存储卷。
-
-```SQL
-MySQL > SHOW STORAGE VOLUMES;
-+----------------+
-| Storage Volume |
-+----------------+
-| my_s3_volume   |
-+----------------+
-1 row in set (0.01 sec)
-```
-
-## 相关 SQL
-
-- [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)
-- [ALTER STORAGE VOLUME](./ALTER_STORAGE_VOLUME.md)
-- [DROP STORAGE VOLUME](./DROP_STORAGE_VOLUME.md)
-- [SET DEFAULT STORAGE VOLUME](./SET_DEFAULT_STORAGE_VOLUME.md)
-- [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md)
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_TABLE_STATUS.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_TABLE_STATUS.md
deleted file mode 100644
index 52a38d3d1c1aba..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_TABLE_STATUS.md
+++ /dev/null
@@ -1,40 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW TABLE STATUS
-
-## 功能
-
-该语句用于查看 Table 的一些信息。
-
-:::tip
-
-该操作不需要权限。
-
-:::
-
-## 语法
-
-```sql
-SHOW TABLE STATUS
-[FROM db] [LIKE "pattern"]
-```
-
-> **说明**
->
-> 该语句主要用于兼容 MySQL 语法，目前仅显示 Comment 等少量信息。
-
-## 示例
-
-1. 查看当前数据库下所有表的信息
-
-    ```SQL
-    SHOW TABLE STATUS;
-    ```
-
-2. 查看指定数据库下，名称包含 example 的表的信息
-
-    ```SQL
-    SHOW TABLE STATUS FROM db LIKE "%example%";
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_USAGE_RESOURCE_GROUPS.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_USAGE_RESOURCE_GROUPS.md
deleted file mode 100644
index 2defd6d5b5965a..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_USAGE_RESOURCE_GROUPS.md
+++ /dev/null
@@ -1,52 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW USAGE RESOURCE GROUPS
-
-## 功能
-
-展示所有资源组在各 BE 上的使用信息。此功能从 v3.1.4 开始支持。
-
-:::tip
-
-该操作不需要权限。
-
-:::
-
-## 语法
-
-```SQL
-SHOW USAGE RESOURCE GROUPS
-```
-
-## 返回
-
-- `Name`：资源组的名称。
-- `Id`：资源组的 ID。
-- `Backend`：BE 的 IP 或 FQDN。
-- `BEInUseCpuCores`：该资源组在该 BE 上正在使用的 CPU 核数，该值为一个估计近似值。
-- `BEInUseMemBytes`：该资源组在该 BE 上正在使用的内存字节数。
-- `BERunningQueries`：该资源组在该 BE 上还未结束的查询数量。
-
-## 使用说明
-
-- 这些资源使用信息由 BE 周期性汇报给 Leader FE，汇报周期为 `report_resource_usage_interval_ms`，默认 1s。
-- 结果中只会展示 BEInUseCpuCores/BEInUseMemBytes/BERunningQueries 至少一个为正数的行，即只有一个资源组在一个 BE 上使用了某种资源时，才会在结果中进行展示。
-
-## 示例
-
-```Plain
-MySQL [(none)]> SHOW USAGE RESOURCE GROUPS;
-+------------+----+-----------+-----------------+-----------------+------------------+
-| Name       | Id | Backend   | BEInUseCpuCores | BEInUseMemBytes | BERunningQueries |
-+------------+----+-----------+-----------------+-----------------+------------------+
-| default_wg | 0  | 127.0.0.1 | 0.100           | 1               | 5                |
-+------------+----+-----------+-----------------+-----------------+------------------+
-| default_wg | 0  | 127.0.0.2 | 0.200           | 2               | 6                |
-+------------+----+-----------+-----------------+-----------------+------------------+
-| wg1        | 0  | 127.0.0.1 | 0.300           | 3               | 7                |
-+------------+----+-----------+-----------------+-----------------+------------------+
-| wg2        | 0  | 127.0.0.1 | 0.400           | 4               | 8                |
-+------------+----+-----------+-----------------+-----------------+------------------+
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SHOW_VARIABLES.md b/docs/zh/sql-reference/sql-statements/Administration/SHOW_VARIABLES.md
deleted file mode 100644
index 389751d60c0668..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SHOW_VARIABLES.md
+++ /dev/null
@@ -1,94 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW VARIABLES
-
-## 功能
-
-查看当前集群的系统变量信息。
-
-:::tip
-
-该操作不需要权限。
-
-:::
-
-## 语法
-
-```SQL
-SHOW [ GLOBAL | SESSION ] VARIABLES
-    [ LIKE <pattern> | WHERE <expr> ]
-```
-
-## 参数说明
-
-| **参数**              | **说明**                                                     |
-| --------------------- | ------------------------------------------------------------ |
-| 修饰符：<ul><li>GLOBAL</li><li>SESSION</li></ul> | <ul><li>使用 `GLOBAL` 修饰符，该语句显示全局系统变量值。在生成新连接时，StarRocks 自动初始化所有变量的会话值作为全局值。如果变量没有全局值，则不显示任何值。</li><li>使用 `SESSION` 修饰符，该语句显示对当前连接有效的系统变量值。如果变量没有会话值，则显示全局值。您可以使用 `LOCAL` 替代 `SESSION`。</li><li>如不指定修饰符，默认值为 `SESSION`。</li></ul> |
-| pattern               | 用于匹配变量名的 LIKE 子句模式。您可以在当前参数中使用 % 通配符。 |
-| expr                  | 用于匹配变量名 `variable_name` 或变量值 `value` 的 WHERE 子句匹配表达式。 |
-
-## 返回
-
-| **返回**      | **说明** |
-| ------------- | -------- |
-| Variable_name | 变量名。 |
-| Value         | 变量值。 |
-
-## 示例
-
-示例一：通过 LIKE 子句精确匹配变量名显示变量信息。
-
-```Plain
-mysql> SHOW VARIABLES LIKE 'wait_timeout';
-+---------------+-------+
-| Variable_name | Value |
-+---------------+-------+
-| wait_timeout  | 28800 |
-+---------------+-------+
-1 row in set (0.01 sec)
-```
-
-示例二：通过 LIKE 子句与 % 通配符模糊匹配变量名显示变量信息。
-
-```Plain
-mysql> SHOW VARIABLES LIKE '%imeou%';
-+------------------------------------+-------+
-| Variable_name                      | Value |
-+------------------------------------+-------+
-| interactive_timeout                | 3600  |
-| net_read_timeout                   | 60    |
-| net_write_timeout                  | 60    |
-| new_planner_optimize_timeout       | 3000  |
-| query_delivery_timeout             | 300   |
-| query_queue_pending_timeout_second | 300   |
-| query_timeout                      | 300   |
-| wait_timeout                       | 28800 |
-+------------------------------------+-------+
-9 rows in set (0.00 sec)
-```
-
-示例三：通过 WHERE 子句精确匹配变量名显示变量信息。
-
-```Plain
-mysql> show variables where variable_name = 'wait_timeout';
-+---------------+-------+
-| Variable_name | Value |
-+---------------+-------+
-| wait_timeout  | 28800 |
-+---------------+-------+
-1 row in set (0.17 sec)
-```
-
-示例四：通过 WHERE 子句精确匹配变量值显示变量信息。
-
-```Plain
-mysql> show variables where value = '28800';
-+---------------+-------+
-| Variable_name | Value |
-+---------------+-------+
-| wait_timeout  | 28800 |
-+---------------+-------+
-1 row in set (0.70 sec)
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/SYNC.md b/docs/zh/sql-reference/sql-statements/Administration/SYNC.md
deleted file mode 100644
index 511cb360148c50..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/SYNC.md
+++ /dev/null
@@ -1,28 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SYNC
-
-同步不同 Session 之间的数据一致性。
-
-目前，StarRocks 只能保证同一 Session 内的一致性，也就是说，只有发起数据写入操作的 Session 才能在操作成功后立即读取最新数据。如果想立即从其他 Session 读取最新数据，必须使用 SYNC 语句同步数据一致性。如果不执行该语句，Session 之间通常会有毫秒级的延迟。
-
-:::tip
-
-该操作不需要权限。
-
-:::
-
-## 语法
-
-```SQL
-SYNC
-```
-
-## 示例
-
-```Plain
-mysql> SYNC;
-Query OK, 0 rows affected (0.01 sec)
-```
diff --git a/docs/zh/sql-reference/sql-statements/Administration/UNINSTALL_PLUGIN.md b/docs/zh/sql-reference/sql-statements/Administration/UNINSTALL_PLUGIN.md
deleted file mode 100644
index fcf3403261d36d..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Administration/UNINSTALL_PLUGIN.md
+++ /dev/null
@@ -1,33 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# UNINSTALL PLUGIN
-
-## 功能
-
-该语句用于卸载一个插件。
-
-:::tip
-
-该操作需要 SYSTEM 级 PLUGIN 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```SQL
-UNINSTALL PLUGIN plugin_name
-```
-
-plugin_name 可以通过 `SHOW PLUGINS;` 命令查看。
-
-只能卸载非 builtin 的插件。
-
-## 示例
-
-1. 卸载一个插件：
-
-    ```SQL
-    UNINSTALL PLUGIN auditdemo;
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md b/docs/zh/sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md
new file mode 100644
index 00000000000000..d0c3626316dbe9
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Catalog/CREATE_EXTERNAL_CATALOG.md
@@ -0,0 +1,140 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE EXTERNAL CATALOG
+
+## 功能
+
+该语句用于创建 External Catalog。创建后，无需数据导入或创建外部表即可查询外部数据。当前支持创建如下 External Catalog：
+
+- [Hive catalog](../../../data_source/catalog/hive_catalog.md)：用于查询 Apache Hive™ 集群中的数据。
+- [Iceberg catalog](../../../data_source/catalog/iceberg_catalog.md)：用于查询 Apache Iceberg 集群中的数据。
+- [Hudi catalog](../../../data_source/catalog/hudi_catalog.md)：用于查询 Apache Hudi 集群中的数据。
+- [Delta Lake catalog](../../../data_source/catalog/deltalake_catalog.md)：用于查询 Delta Lake 中的数据。
+- [JDBC catalog](../../../data_source/catalog/jdbc_catalog.md)：用于查询 JDBC 数据源中的数据。
+- [Elasticsearch catalog](../../../data_source/catalog/elasticsearch_catalog.md)：用于查询 Elasticsearch 中的数据。该特性自 3.1 版本起支持。
+- [Paimon catalog](../../../data_source/catalog/paimon_catalog.md)：用于查询 Apache Paimon 中的数据。该特性自 3.1 版本起支持。
+- [Unified catalog](../../../data_source/catalog/unified_catalog.md)：把 Hive、Iceberg、Hudi 和 Delta Lake 作为一个融合的数据源，从中查询数据。该特性自 3.2 版本起支持。
+
+> **注意**
+>
+> - 在 3.0 及以后版本，使用该语句需要有 System 级 CREATE EXTERNAL CATALOG 权限。
+> - 在创建 External Catalog 前，需要根据数据源的存储系统（如 AWS S3）、元数据服务（如 Hive metastore）和认证方式（如 Kerberos）在 StarRocks 中做相应的配置。详细信息，请参见以上各个 External Catalog 文档中的「前提条件」小节。
+
+## 语法
+
+```SQL
+CREATE EXTERNAL CATALOG [IF NOT EXISTS] <catalog_name>
+[COMMENT <comment>]
+PROPERTIES ("key"="value", ...)
+```
+
+## 参数说明
+
+| 参数         | 必选 | 说明                                                         |
+| ------------ | ---- | ------------------------------------------------------------ |
+| catalog_name | 是   | External catalog 的名称，命名要求参见[系统限制](../../System_limit.md)。 |
+| comment      | 否   | External catalog 的描述。 |
+| PROPERTIES   | 是   | External catalog 的属性，不同的 external catalog 需要设置不同属性。详细配置信息，请参见 [Hive catalog](../../../data_source/catalog/hive_catalog.md)、[Iceberg catalog](../../../data_source/catalog/iceberg_catalog.md)、[Hudi catalog](../../../data_source/catalog/hudi_catalog.md)、[Delta Lake catalog](../../../data_source/catalog/deltalake_catalog.md) 和 [JDBC Catalog](../../../data_source/catalog/jdbc_catalog.md)。 |
+
+## 示例
+
+示例一：创建名为 `hive_metastore_catalog` 的 Hive catalog。其对应的 Hive 集群使用 Hive metastore 作为元数据服务。
+
+```SQL
+CREATE EXTERNAL CATALOG hive_metastore_catalog
+PROPERTIES(
+   "type"="hive", 
+   "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
+);
+```
+
+示例二：创建名为 `hive_glue_catalog` 的 Hive catalog。其对应的 Hive 集群使用 AWS Glue 作为元数据服务。
+
+```SQL
+CREATE EXTERNAL CATALOG hive_glue_catalog
+PROPERTIES(
+    "type"="hive", 
+    "hive.metastore.type"="glue",
+    "aws.hive.metastore.glue.aws-access-key"="xxxxxx",
+    "aws.hive.metastore.glue.aws-secret-key"="xxxxxxxxxxxx",
+    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
+);
+```
+
+示例三：创建名为 `iceberg_metastore_catalog` 的 Iceberg catalog。其对应的 Iceberg 集群使用 Hive metastore 作为元数据服务。
+
+```SQL
+CREATE EXTERNAL CATALOG iceberg_metastore_catalog
+PROPERTIES(
+    "type"="iceberg",
+    "iceberg.catalog.type"="hive",
+    "iceberg.catalog.hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
+);
+```
+
+示例四：创建名为 `iceberg_glue_catalog` 的 Iceberg catalog。其对应的 Iceberg 集群使用  AWS Glue 作为元数据服务。
+
+```SQL
+CREATE EXTERNAL CATALOG iceberg_glue_catalog
+PROPERTIES(
+    "type"="iceberg", 
+    "iceberg.catalog.type"="glue",
+    "aws.hive.metastore.glue.aws-access-key"="xxxxx",
+    "aws.hive.metastore.glue.aws-secret-key"="xxx",
+    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
+);
+```
+
+示例五：创建名为 `hudi_metastore_catalog` 的 Hudi catalog。其对应的 Hudi 集群使用 Hive metastore 作为元数据服务。
+
+```SQL
+CREATE EXTERNAL CATALOG hudi_metastore_catalog
+PROPERTIES(
+    "type"="hudi",
+    "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
+);
+```
+
+示例六：创建名为 `hudi_glue_catalog` 的 Hudi catalog。其对应的 Hudi 集群使用 AWS Glue 作为元数据服务。
+
+```SQL
+CREATE EXTERNAL CATALOG hudi_glue_catalog
+PROPERTIES(
+    "type"="hudi", 
+    "hive.metastore.type"="glue",
+    "aws.hive.metastore.glue.aws-access-key"="xxxxxx",
+    "aws.hive.metastore.glue.aws-secret-key"="xxxxxxxxxxxx",
+    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
+);
+```
+
+示例七：创建名为 `delta_metastore_catalog` 的 Delta Lake catalog。其对应的 Delta Lake 使用 Hive metastore 作为元数据服务。
+
+```SQL
+CREATE EXTERNAL CATALOG delta_metastore_catalog
+PROPERTIES(
+    "type"="deltalake",
+    "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
+);
+```
+
+示例八：创建名为 `delta_glue_catalog` 的 Delta Lake catalog。其对应的 Delta Lake 使用 AWS Glue 作为元数据服务。
+
+```SQL
+CREATE EXTERNAL CATALOG delta_glue_catalog
+PROPERTIES(
+    "type"="deltalake", 
+    "hive.metastore.type"="glue",
+    "aws.hive.metastore.glue.aws-access-key"="xxxxxx",
+    "aws.hive.metastore.glue.aws-secret-key"="xxxxxxxxxxxx",
+    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
+);
+```
+
+## 相关操作
+
+- 如要查看所有 Catalog，参见 [SHOW CATALOGS](SHOW_CATALOGS.md)。
+- 如要查看某个 External Catalog 的创建语句，参见 [SHOW CREATE CATALOG](SHOW_CREATE_CATALOG.md)。
+- 如要删除 External Catalog，参见 [DROP CATALOG](DROP_CATALOG.md)。
diff --git a/docs/zh/sql-reference/sql-statements/Catalog/DROP_CATALOG.md b/docs/zh/sql-reference/sql-statements/Catalog/DROP_CATALOG.md
new file mode 100644
index 00000000000000..6ce29d9fe61ded
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Catalog/DROP_CATALOG.md
@@ -0,0 +1,37 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP CATALOG
+
+## 功能
+
+删除指定的 external catalog。注意目前不支持删除 internal catalog。一个 StarRocks 集群中只有一个默认的 internal catalog，名为 `default_catalog`。
+
+## 语法
+
+```SQL
+DROP CATALOG [IF EXISTS] catalog_name
+```
+
+## 参数说明
+
+`catalog_name`：external catalog 名称，必选参数。
+
+## 示例
+
+创建名为`hive1`的 Hive catalog。
+
+```SQL
+CREATE EXTERNAL CATALOG hive1
+PROPERTIES(
+  "type"="hive", 
+  "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
+);
+```
+
+删除`hive1`。
+
+```SQL
+DROP CATALOG hive1;
+```
diff --git a/docs/zh/sql-reference/sql-statements/Catalog/SET_CATALOG.md b/docs/zh/sql-reference/sql-statements/Catalog/SET_CATALOG.md
new file mode 100644
index 00000000000000..dde5ab3d2c1414
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Catalog/SET_CATALOG.md
@@ -0,0 +1,37 @@
+---
+displayed_sidebar: docs
+---
+
+# SET CATALOG
+
+## 功能
+
+切换到指定的 Catalog。该命令自 3.0 版本起支持。
+
+> **注意**
+>
+> 如果是新部署的 3.1 集群，用户需要有目标 Catalog 的 USAGE 权限才可以执行该操作。如果是从低版本升级上来的集群，则不需要重新赋权。您可以使用 [GRANT](../account-management/GRANT.md) 命令进行授权操作。
+
+## 语法
+
+```SQL
+SET CATALOG <catalog_name>
+```
+
+## 参数
+
+`catalog_name`：当前会话里生效的 Catalog，支持 Internal Catalog 和 External Catalog。如果指定的 Catalog 不存在，则会引发异常。
+
+## 示例
+
+通过如下命令，切换当前会话里生效的 Catalog 为 Hive Catalog `hive_metastore`：
+
+```SQL
+SET CATALOG hive_metastore;
+```
+
+通过如下命令，切换当前会话里生效的 Catalog 为 Internal Catalog `default_catalog`：
+
+```SQL
+SET CATALOG default_catalog;
+```
diff --git a/docs/zh/sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md b/docs/zh/sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md
new file mode 100644
index 00000000000000..896e6807d0563b
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Catalog/SHOW_CATALOGS.md
@@ -0,0 +1,55 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW CATALOGS
+
+## 功能
+
+查看当前集群中的所有 Catalog，包括 Internal Catalog 和 External Catalog。
+
+> **注意**
+>
+> 只有拥有 External Catalog USAGE 权限的用户才能查看到该 Catalog。如果没有该权限，仅返回 default_catalog。您可以使用 [GRANT](../account-management/GRANT.md) 命令进行授权操作。
+
+## 语法
+
+```SQL
+SHOW CATALOGS
+```
+
+## 返回结果说明
+
+```SQL
++----------+--------+----------+
+| Catalog  | Type   | Comment  |
++----------+--------+----------+
+```
+
+返回结果中的字段说明如下：
+
+| **字段** | **说明**                                                     |
+| -------- | ------------------------------------------------------------ |
+| Catalog  | Catalog 名称。                                               |
+| Type     | Catalog 类型。如果是 `default_catalog`，则返回 `Internal`。如果是 external catalog，则返回 external catalog 的类型，例如 `Hive`, `Hudi`, `Iceberg`。          |
+| Comment  | Catalog 的备注。<ul><li>在创建 external catalog 时不支持为 external catalog 添加备注，所以如果是 external catalog，则返回的 `Comment` 为 `NULL`。</li><li>如果是 `default_catalog`，则默认返回的 `Comment` 为 `An internal catalog contains this cluster's self-managed tables.`。`default_catalog` 是 StarRocks 集群中唯一的 internal catalog，不允许删除。</li></ul> |
+
+## 示例
+
+查看当前集群中的所有 catalog。
+
+```SQL
+SHOW CATALOGS\G
+*************************** 1. row ***************************
+Catalog: default_catalog
+   Type: Internal
+Comment: An internal catalog contains this cluster's self-managed tables.
+*************************** 2. row ***************************
+Catalog: hudi_catalog
+   Type: Hudi
+Comment: NULL
+*************************** 3. row ***************************
+Catalog: iceberg_catalog
+   Type: Iceberg
+Comment: NULL
+```
diff --git a/docs/zh/sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md b/docs/zh/sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md
new file mode 100644
index 00000000000000..1c025d8f31c389
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Catalog/SHOW_CREATE_CATALOG.md
@@ -0,0 +1,72 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW CREATE CATALOG
+
+## 功能
+
+查看某个 External Catalog 的创建语句。
+
+当前支持查看如下 External Catalog:
+
+- [Hive Catalog](../../../data_source/catalog/hive_catalog.md)
+- [Iceberg Catalog](../../../data_source/catalog/iceberg_catalog.md)
+- [Hudi Catalog](../../../data_source/catalog/hudi_catalog.md)
+- [Delta Lake Catalog](../../../data_source/catalog/deltalake_catalog.md)
+- [JDBC catalog](../../../data_source/catalog/jdbc_catalog.md) (自 3.0 版本起)
+- [Unified Catalog](../../../data_source/catalog/unified_catalog.md) (自 3.2 版本起)
+- [MaxCompute Catalog](../../../data_source/catalog/maxcompute_catalog.md) (自 3.3 版本起)
+
+其中认证相关的密钥信息会进行脱敏展示，无法查看。
+
+该命令自 3.0 版本起支持。
+
+## 语法
+
+```SQL
+SHOW CREATE CATALOG <catalog_name>;
+```
+
+## 参数说明
+
+| **参数**     | **是否必选** | **说明**                  |
+| ------------ | ------------ | ------------------------- |
+| catalog_name | 是           | 待查看的 Catalog 的名称。 |
+
+## 返回结果说明
+
+```Plain
++------------+-----------------+
+| Catalog    | Create Catalog  |
++------------+-----------------+
+```
+
+| **字段**       | **说明**             |
+| -------------- | -------------------- |
+| Catalog        | Catalog 的名称。     |
+| Create Catalog | Catalog 的创建语句。 |
+
+## 示例
+
+以一个名为 `hive_catalog_glue` 的 Hive Catalog 为例，查询该 Catalog 的创建语句：
+
+```SQL
+SHOW CREATE CATALOG hive_catalog_glue;
+```
+
+返回如下信息：
+
+```SQL
+CREATE EXTERNAL CATALOG `hive_catalog_hms`
+PROPERTIES ("aws.s3.access_key"  =  "AK******M4",
+"hive.metastore.type"  =  "glue",
+"aws.s3.secret_key"  =  "iV******iD",
+"aws.glue.secret_key"  =  "iV******iD",
+"aws.s3.use_instance_profile"  =  "false",
+"aws.s3.region"  =  "us-west-1",
+"aws.glue.region"  =  "us-west-1",
+"type"  =  "hive",
+"aws.glue.access_key"  =  "AK******M4"
+)
+```
diff --git a/docs/zh/sql-reference/sql-statements/Catalog/_category_.yml b/docs/zh/sql-reference/sql-statements/Catalog/_category_.yml
new file mode 100644
index 00000000000000..30eb2b13100262
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Catalog/_category_.yml
@@ -0,0 +1,6 @@
+position: 50 # float position is supported
+label: '数据目录'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/Database/ALTER_DATABASE.md b/docs/zh/sql-reference/sql-statements/Database/ALTER_DATABASE.md
new file mode 100644
index 00000000000000..57132cb34b846c
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Database/ALTER_DATABASE.md
@@ -0,0 +1,77 @@
+---
+keywords: ['xiugai'] 
+displayed_sidebar: docs
+---
+
+# ALTER DATABASE
+
+## 功能
+
+该语句用于设置指定数据库的属性。
+
+:::tip
+
+该操作需要对应数据库的 ALTER 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+### 设置数据库数据量配额
+
+单位为 B/K/KB/M/MB/G/GB/T/TB/P/PB。
+
+```sql
+ALTER DATABASE <db_name> SET DATA QUOTA <quota>
+```
+
+### 重命名数据库
+
+```sql
+ALTER DATABASE <db_name> RENAME <new_db_name>
+```
+
+### 设置数据库的副本数量配额
+
+```sql
+ALTER DATABASE <db_name> SET REPLICA QUOTA <quota>
+```
+
+说明：
+
+```plain text
+重命名数据库后，如需要，请使用 REVOKE 和 GRANT 命令修改相应的用户权限。
+数据库的默认数据量配额和默认副本数量配额均为 2^63 - 1。
+```
+
+## 示例
+
+1. 设置指定数据库数据量配额。
+
+    ```SQL
+    ALTER DATABASE example_db SET DATA QUOTA 10995116277760B;
+    -- 上述单位为字节，等价于下面的语句
+    ALTER DATABASE example_db SET DATA QUOTA 10T;
+    ALTER DATABASE example_db SET DATA QUOTA 100G;
+    ALTER DATABASE example_db SET DATA QUOTA 200M;
+    ```
+
+2. 将数据库 `example_db` 重命名为 `example_db2`。
+
+    ```SQL
+    ALTER DATABASE example_db RENAME example_db2;
+    ```
+
+3. 设定指定数据库副本数量配额。
+
+    ```SQL
+    ALTER DATABASE example_db SET REPLICA QUOTA 102400;
+    ```
+
+## 相关参考
+
+- [CREATE DATABASE](CREATE_DATABASE.md)
+- [USE](USE.md)
+- [SHOW DATABASES](SHOW_DATABASES.md)
+- [DESC](../table_bucket_part_index/DESCRIBE.md)
+- [DROP DATABASE](DROP_DATABASE.md)
diff --git a/docs/zh/sql-reference/sql-statements/Database/CREATE_DATABASE.md b/docs/zh/sql-reference/sql-statements/Database/CREATE_DATABASE.md
new file mode 100644
index 00000000000000..d203b0cf86d04b
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Database/CREATE_DATABASE.md
@@ -0,0 +1,53 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE DATABASE
+
+## 功能
+
+该语句用于创建数据库 (database)。
+
+:::tip
+
+该操作需要对应 Catalog 下的 CREATE DATABASE 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```sql
+CREATE DATABASE [IF NOT EXISTS] <db_name>
+[PROPERTIES ("key"="value", ...)]
+```
+
+## 参数说明
+
+`db_name`：数据库名称。有关数据库的命名要求，参见[系统限制](../../System_limit.md)。
+
+**PROPERTIES（选填）**
+
+`storage_volume`: 存算分离集群中，用于存储当前数据库中数据的存储卷。如未指定，则使用默认存储卷。
+
+## 示例
+
+1. 新建数据库 `db_test`。
+
+   ```sql
+   CREATE DATABASE db_test;
+   ```
+
+2. 基于存储卷 `s3_storage_volume` 新建云原生数据 `cloud_db`。
+
+   ```sql
+   CREATE DATABASE cloud_db
+   PROPERTIES ("storage_volume"="s3_storage_volume");
+   ```
+
+## 相关参考
+
+- [SHOW CREATE DATABASE](SHOW_CREATE_DATABASE.md)
+- [USE](USE.md)
+- [SHOW DATABASES](SHOW_DATABASES.md)
+- [DESC](../table_bucket_part_index/DESCRIBE.md)
+- [DROP DATABASE](DROP_DATABASE.md)
diff --git a/docs/zh/sql-reference/sql-statements/Database/DROP_DATABASE.md b/docs/zh/sql-reference/sql-statements/Database/DROP_DATABASE.md
new file mode 100644
index 00000000000000..710d0b85e44ff6
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Database/DROP_DATABASE.md
@@ -0,0 +1,44 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP DATABASE
+
+## 功能
+
+该语句用于删除数据库（database）。
+
+> **注意**
+>
+> 该操作需要有对应数据库的 DROP 权限。
+
+## 语法
+
+```sql
+-- 2.0 之前版本
+DROP DATABASE [IF EXISTS] [FORCE] db_name
+-- 2.0 及以后版本
+DROP DATABASE [IF EXISTS] db_name [FORCE]
+```
+
+注意以下几点：
+
+- 执行 DROP DATABASE 一段时间内（默认 1 天），可以通过 [RECOVER](../backup_restore/RECOVER.md) 语句恢复被删除的数据库，但是该数据库下已经随数据库删除的 Pipe 导入作业（自 3.2 版本起支持）无法恢复。
+- 如果执行 `DROP DATABASE FORCE`，则系统不会检查该数据库是否存在未完成的事务，数据库将直接被删除并且 **不能被恢复**，一般不建议执行此操作。
+- 删除数据库后，所有从属于该数据库的 Pipe 导入作业（自 3.2 版本起支持）也将随之删除。
+
+## 示例
+
+1. 删除数据库 db_test。
+
+    ```sql
+    DROP DATABASE db_test;
+    ```
+
+## 相关参考
+
+- [CREATE DATABASE](CREATE_DATABASE.md)
+- [SHOW CREATE DATABASE](SHOW_CREATE_DATABASE.md)
+- [USE](USE.md)
+- [DESC](../table_bucket_part_index/DESCRIBE.md)
+- [SHOW DATABASES](SHOW_DATABASES.md)
diff --git a/docs/zh/sql-reference/sql-statements/Database/SHOW_CREATE_DATABASE.md b/docs/zh/sql-reference/sql-statements/Database/SHOW_CREATE_DATABASE.md
new file mode 100644
index 00000000000000..981230d8eee42c
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Database/SHOW_CREATE_DATABASE.md
@@ -0,0 +1,44 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW CREATE DATABASE
+
+查看指定数据库的创建语句。
+
+## 语法
+
+```sql
+SHOW CREATE DATABASE <db_name>
+```
+
+## 参数说明
+
+`db_name`：数据库的名称，必填。
+
+## 返回结果说明
+
+返回两个字段：
+
+- Database：数据库名称
+
+- Create Database：数据库的创建语句
+
+## 示例
+
+```sql
+mysql > show create database zj_test;
++----------+---------------------------+
+| Database | Create Database           |
++----------+---------------------------+
+| zj_test  | CREATE DATABASE `zj_test` |
++----------+---------------------------+
+```
+
+## 相关参考
+
+- [CREATE DATABASE](CREATE_DATABASE.md)
+- [SHOW DATABASES](SHOW_DATABASES.md)
+- [USE](USE.md)
+- [DESC](../table_bucket_part_index/DESCRIBE.md)
+- [DROP DATABASE](DROP_DATABASE.md)
diff --git a/docs/zh/sql-reference/sql-statements/Database/SHOW_DATA.md b/docs/zh/sql-reference/sql-statements/Database/SHOW_DATA.md
new file mode 100644
index 00000000000000..0e281be27b9636
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Database/SHOW_DATA.md
@@ -0,0 +1,64 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW DATA
+
+## 功能
+
+用于查看指定数据库或指定表的数据量、副本数量以及统计行数。
+
+## 语法
+
+```sql
+SHOW DATA [FROM <db_name>[.<table_name>]]
+```
+
+说明：
+
+1. 如果不指定 FROM 子句，则展示当前 db 下细分到各个 table 的数据量和副本数量。其中数据量为所有副本的总数据量。而副本数量为表的所有分区以及所有物化视图的副本数量。
+
+2. 如果指定 FROM 子句，则展示 table 下细分到各个物化视图的数据量、副本数量和统计行数。其中数据量为所有副本的总数据量。副本数量为对应物化视图的所有分区的副本数量。统计行数为对应物化视图的所有分区统计行数。
+
+3. 统计行数时，以多个副本中，行数最大的那个副本为准。
+
+4. 结果集中的 `Total` 行表示汇总行。`Quota` 行表示当前数据库设置的配额。`Left` 行表示剩余配额。
+
+5. 如果想查看各个 Partition 的大小，请参阅 [show partitions](../table_bucket_part_index/SHOW_PARTITIONS.md)。
+
+## 示例
+
+### 查看数据库下表的总数据量
+
+查看当前数据库下各个 table 的数据量，副本数量，汇总数据量和汇总副本数量。
+
+```sql
+SHOW DATA;
+
++-----------+-------------+--------------+
+| TableName | Size        | ReplicaCount |
++-----------+-------------+--------------+
+| tbl1      | 900.000 B   | 6            |
+| tbl2      | 500.000 B   | 3            |
+| Total     | 1.400 KB    | 9            |
+| Quota     | 1024.000 GB | 1073741824   |
+| Left      | 1021.921 GB | 1073741815   |
++-----------+-------------+--------------+
+```
+
+### 查看某个表的数据量
+
+查看指定数据库下指定表的细分数据量、副本数量和统计行数。
+
+```sql
+SHOW DATA FROM example_db.test;
+
++-----------+-----------+-----------+--------------+----------+
+| TableName | IndexName | Size      | ReplicaCount | RowCount |
++-----------+-----------+-----------+--------------+----------+
+| test      | r1        | 10.000MB  | 30           | 10000    |
+|           | r2        | 20.000MB  | 30           | 20000    |
+|           | test2     | 50.000MB  | 30           | 50000    |
+|           | Total     | 80.000    | 90           |          |
++-----------+-----------+-----------+--------------+----------+
+```
diff --git a/docs/zh/sql-reference/sql-statements/Database/SHOW_DATABASES.md b/docs/zh/sql-reference/sql-statements/Database/SHOW_DATABASES.md
new file mode 100644
index 00000000000000..4ef7efd2539526
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Database/SHOW_DATABASES.md
@@ -0,0 +1,69 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW DATABASES
+
+## 功能
+
+查看当前 StarRocks 集群或外部数据源中的数据库。
+
+## 语法
+
+```SQL
+SHOW DATABASES [FROM <catalog_name>]
+```
+
+## 参数说明
+
+| **参数**          | **必选** | **说明**                                                     |
+| ----------------- | -------- | ------------------------------------------------------------ |
+| catalog_name | 否       | Internal catalog 或 external catalog 的名称。<ul><li>如不指定或指定为 internal catalog 名称，即 `default_catalog`，则查看当前 StarRocks 集群中的数据库。</li><li>如指定 external catalog 名称，则查看外部数据源中的数据库。您可以使用 [SHOW CATALOGS](../Catalog/SHOW_CATALOGS.md) 命令查看当前集群的内外部 catalog。</li></ul> |
+
+## 示例
+
+示例一：查看当前 StarRocks 集群中的数据库。
+
+```SQL
+SHOW DATABASES;
+```
+
+或
+
+```SQL
+SHOW DATABASES FROM default_catalog;
+```
+
+返回信息如下：
+
+```SQL
++----------+
+| Database |
++----------+
+| db1      |
+| db2      |
+| db3      |
++----------+
+```
+
+示例二：通过 external catalog `hive1` 查看 Apache Hive™ 中的数据库。
+
+```SQL
+SHOW DATABASES FROM hive1;
+
++-----------+
+| Database  |
++-----------+
+| hive_db1  |
+| hive_db2  |
+| hive_db3  |
++-----------+
+```
+
+## 相关参考
+
+- [CREATE DATABASE](CREATE_DATABASE.md)
+- [SHOW CREATE DATABASE](SHOW_CREATE_DATABASE.md)
+- [USE](USE.md)
+- [DESC](../table_bucket_part_index/DESCRIBE.md)
+- [DROP DATABASE](DROP_DATABASE.md)
diff --git a/docs/zh/sql-reference/sql-statements/Database/USE.md b/docs/zh/sql-reference/sql-statements/Database/USE.md
new file mode 100644
index 00000000000000..a8f7de5f2d25fe
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Database/USE.md
@@ -0,0 +1,48 @@
+---
+displayed_sidebar: docs
+---
+
+# USE
+
+## 功能
+
+指定会话使用的数据库。指定数据库后，即可以进行后续的建表或者查询等操作。
+
+## 语法
+
+```SQL
+USE [<catalog_name>.]<db_name>
+```
+
+## 参数说明
+
+| **参数**     | **必选** | **说明**                                                     |
+| ------------ | -------- | ------------------------------------------------------------ |
+| catalog_name | 否       | Catalog 名称。<ul><li>如不指定该参数，则默认使用 `default_catalog` 下的数据库。</li><li>如要使用 external catalog 下的数据库，则必须指定该参数，具体见「示例二」。</li><li>如从一个 catalog 下的数据库切换到另一个 catalog 下的数据库，则必须指定该参数，具体见「示例三」。</li></ul>更多有关 catalog 的信息，请参见[概述](../../../data_source/catalog/catalog_overview.md)。 |
+| db_name      | 是       | 数据库名称。该数据库必须存在。                               |
+
+## 示例
+
+示例一：使用 `default_catalog` 下的 `example_db` 作为会话的数据库。
+
+```SQL
+USE default_catalog.example_db;
+```
+
+或
+
+```SQL
+USE example_db;
+```
+
+示例二：使用 `hive_catalog` 下的 `example_db` 作为会话的数据库。
+
+```SQL
+USE hive_catalog.example_db;
+```
+
+示例三：将会话使用的数据库 `hive_catalog.example_table1` 切换到  `iceberg_catalog.example_table2`。
+
+```SQL
+USE iceberg_catalog.example_table2;
+```
diff --git a/docs/zh/sql-reference/sql-statements/Database/_category_.yml b/docs/zh/sql-reference/sql-statements/Database/_category_.yml
new file mode 100644
index 00000000000000..880f366cbf8695
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Database/_category_.yml
@@ -0,0 +1,6 @@
+position: 60 # float position is supported
+label: 'Database'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
\ No newline at end of file
diff --git a/docs/zh/sql-reference/sql-statements/Function/CREATE_FUNCTION.md b/docs/zh/sql-reference/sql-statements/Function/CREATE_FUNCTION.md
new file mode 100644
index 00000000000000..c262a7b508ddd5
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Function/CREATE_FUNCTION.md
@@ -0,0 +1,43 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE FUNCTION
+
+## 功能
+
+创建 UDF（用户自定义函数）。当前仅支持创建 Java UDF，即 Java 语言编写的自定义函数，具体包括：
+
+- Scalar UDF：自定义标量函数。
+- UDAF：自定义聚合函数。
+- UDWF：自定义窗口函数。
+- UDTF：自定义表值函数。
+
+**更多创建和使用 UDF 的信息，推荐参考 [Java UDF](../../sql-functions/JAVA_UDF.md)。**
+
+> **注意**
+>
+> - 要创建全局 UDF，需要拥有 SYSTEM 级 CREATE GLOBAL FUNCTION 权限。
+> - 要创建数据库级别的 UDF，需要拥有 DATABASE 级 CREATE FUNCTION 权限。
+
+## 语法
+
+```SQL
+CREATE [OR REPLACE] [GLOBAL] [AGGREGATE | TABLE] FUNCTION function_name
+(arg_type [, ...])
+RETURNS return_type
+[PROPERTIES ("key" = "value" [, ...]) ]
+```
+
+## 参数说明
+
+| **参数**      | **必选** | **说明**                                                     |
+| ------------- | -------- | ------------------------------------------------------------ |
+| OR REPLACE    | 否       | 如已存在有同样签名（Function Signature）的函数，则替换该函数。从 3.4 版本开始支持。              |
+| GLOBAL        | 否       | 如需创建全局 UDF，需指定该关键字。从 3.0 版本开始支持。              |
+| AGGREGATE     | 否       | 如要创建 UDAF 和 UDWF，需指定该关键字。                         |
+| TABLE         | 否       | 如要创建 UDTF，需指定该关键字。                              |
+| function_name | 是       | 函数名，可以包含数据库名称，比如，`db1.my_func`。如果 `function_name` 中包含了数据库名称，那么该 UDF 会创建在对应的数据库中，否则该 UDF 会创建在当前数据库。新函数名和参数不能与目标数据库中已有的函数相同，否则会创建失败；如只有函数名相同，参数不同，则可以创建成功。 |
+| arg_type      | 是       | 函数的参数类型。具体支持的数据类型，请参见 [Java UDF](../../sql-functions/JAVA_UDF.md#类型映射关系)。 |
+| return_type   | 是       | 函数的返回值类型。具体支持的数据类型，请参见 [Java UDF](../../sql-functions/JAVA_UDF.md#类型映射关系)。 |
+| properties    | 是       | 函数相关属性。创建不同类型的 UDF 需配置不同的属性，详情和示例请参考 [Java UDF](../../sql-functions/JAVA_UDF.md#步骤六在-starrocks-中创建-udf)。 |
diff --git a/docs/zh/sql-reference/sql-statements/Function/DROP_FUNCTION.md b/docs/zh/sql-reference/sql-statements/Function/DROP_FUNCTION.md
new file mode 100644
index 00000000000000..0f8a9d2003a34a
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Function/DROP_FUNCTION.md
@@ -0,0 +1,36 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP FUNCTION
+
+## 功能
+
+删除一个自定义函数。函数的名称、参数类型完全一致才能够被删除。
+
+要执行该命令的用户必须是函数的拥有者。
+
+## 语法
+
+```sql
+DROP [GLOBAL] FUNCTION <function_name>(arg_type [, ...])
+```
+
+## 参数说明
+
+- `GLOBAL`：表示删除全局函数。StarRocks 从 3.0 版本开始支持创建 [Global UDF](../../sql-functions/JAVA_UDF.md)。
+- `function_name`: 待删除函数的名字，必填。
+- `arg_type`: 待删除函数的参数类型，必填。
+
+## 示例
+
+删除一个函数。
+
+```sql
+DROP FUNCTION my_add(INT, INT)
+```
+
+## 相关 SQL
+
+- [SHOW FUNCTIONS](SHOW_FUNCTIONS.md)
+- [Java UDF](../../sql-functions/JAVA_UDF.md)
diff --git a/docs/zh/sql-reference/sql-statements/Function/SHOW_FUNCTIONS.md b/docs/zh/sql-reference/sql-statements/Function/SHOW_FUNCTIONS.md
new file mode 100644
index 00000000000000..d068addccc8150
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Function/SHOW_FUNCTIONS.md
@@ -0,0 +1,60 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW FUNCTIONS
+
+## 功能
+
+查看数据库下所有的自定义(系统提供)函数。如果未指定数据库，则直接查询当前会话所在数据库。
+
+## 语法
+
+```sql
+SHOW [FULL] [BUILTIN] [GLOBAL] FUNCTIONS [IN|FROM <db_name>] [LIKE 'function_pattern']
+```
+
+## 参数说明
+
+* `FULL`: 表示显示函数的详细信息。
+* `BUILTIN`: 表示显示系统提供的函数。
+* `GLOBAL`: 表示显示全局函数。StarRocks 从 3.0 版本开始支持创建 [Global UDF](../../sql-functions/JAVA_UDF.md)。
+* `db_name`: 要查询的数据库名称。
+* `function_pattern`: 用于过滤函数名称。
+
+## 示例
+
+```sql
+-- \G表示将查询结果进行按列打印
+mysql> show full functions in testDb\G
+*************************** 1. row ***************************
+        Signature: my_add(INT,INT)
+      Return Type: INT
+    Function Type: Scalar
+Intermediate Type: NULL
+       Properties: {"symbol":"_ZN9starrocks_udf6AddUdfEPNS_15FunctionContextERKNS_6IntValES4_","object_file":"http://host:port/libudfsample.so","md5":"cfe7a362d10f3aaf6c49974ee0f1f878"}
+*************************** 2. row ***************************
+        Signature: my_count(BIGINT)
+      Return Type: BIGINT
+    Function Type: Aggregate
+Intermediate Type: NULL
+       Properties: {"object_file":"http://host:port/libudasample.so","finalize_fn":"_ZN9starrocks_udf13CountFinalizeEPNS_15FunctionContextERKNS_9BigIntValE","init_fn":"_ZN9starrocks_udf9CountInitEPNS_15FunctionContextEPNS_9BigIntValE","merge_fn":"_ZN9starrocks_udf10CountMergeEPNS_15FunctionContextERKNS_9BigIntValEPS2_","md5":"37d185f80f95569e2676da3d5b5b9d2f","update_fn":"_ZN9starrocks_udf11CountUpdateEPNS_15FunctionContextERKNS_6IntValEPNS_9BigIntValE"}
+
+2 rows in set (0.00 sec)
+
+mysql> show builtin functions in testDb like 'year%';
++---------------+
+| Function Name |
++---------------+
+| year          |
+| years_add     |
+| years_diff    |
+| years_sub     |
++---------------+
+2 rows in set (0.00 sec)
+```
+
+## 相关 SQL
+
+* [DROP FUNCTION](DROP_FUNCTION.md)
+* [Java UDF](../../sql-functions/JAVA_UDF.md)
diff --git a/docs/zh/sql-reference/sql-statements/Function/_category_.yml b/docs/zh/sql-reference/sql-statements/Function/_category_.yml
new file mode 100644
index 00000000000000..e5d207af87bb2f
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Function/_category_.yml
@@ -0,0 +1,6 @@
+position: 110 # float position is supported
+label: '函数'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/Resource/ALTER_RESOURCE.md b/docs/zh/sql-reference/sql-statements/Resource/ALTER_RESOURCE.md
new file mode 100644
index 00000000000000..3dd91d47e83914
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Resource/ALTER_RESOURCE.md
@@ -0,0 +1,37 @@
+---
+keywords: ['xiugai'] 
+displayed_sidebar: docs
+---
+
+# ALTER RESOURCE
+
+## 功能
+
+修改资源的属性。仅 StarRocks 2.3 及以上版本支持修改资源属性。
+
+## 语法
+
+```SQL
+ALTER RESOURCE 'resource_name' SET PROPERTIES ("key"="value", ...)
+```
+
+## 参数说明
+
+- `resource_name`：待修改的资源名称。
+- `PROPERTIES ("key"="value", ...)`：资源属性。不同类型的资源支持修改不同的属性，当前支持修改以下资源的 Hive metastore 地址。
+  - Apache Iceberg 资源支持修改以下属性：
+    - `iceberg.catalog-impl`：[custom catalog](../../../data_source/External_table.md#步骤一创建-iceberg-资源) 的全限定类名。
+    - `iceberg.catalog.hive.metastore.uris`：Hive metastore 地址。
+  - Apache Hive™ 和 Apache Hudi 资源支持修改 `hive.metastore.uris`，即 Hive metastore 地址。
+
+## 注意事项
+
+引用一个资源创建外部表后，如果修改了该资源的 Hive metastore 地址会导致该外部表不可用。若仍想使用该外部表查询数据，需保证新 Hive metastore 中存在与原 Hive metastore 中名称和表结构相同的数据表。
+
+## 示例
+
+修改 Apache Hive™ 资源 `hive0` 的 Hive metastore 地址。
+
+```SQL
+ALTER RESOURCE 'hive0' SET PROPERTIES ("hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083")
+```
diff --git a/docs/zh/sql-reference/sql-statements/Resource/CREATE_RESOURCE.md b/docs/zh/sql-reference/sql-statements/Resource/CREATE_RESOURCE.md
new file mode 100644
index 00000000000000..0e504ed441932d
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Resource/CREATE_RESOURCE.md
@@ -0,0 +1,257 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE RESOURCE
+
+## 功能
+
+创建资源。StarRocks 支持创建以下资源：Apache Spark™、Apache Hive™、Apache Iceberg、 Apache Hudi 和 JDBC。其中 Spark 资源用于 [Spark Load](../../../loading/SparkLoad.md)，负责管理数据导入的相关信息，比如 YARN 配置，中间数据存储的路径以及 Broker 配置等；Hive、Iceberg、Hudi 和 JDBC 资源用于在查询[外部表](../../../data_source/External_table.md)是管理数据源的访问信息。
+
+> 说明：
+>
+> - 只有拥有 System 级 CREATE RESOURCE 权限的用户才可以创建资源。
+> - StarRocks 2.3 及以上版本支持创建 JDBC 资源。
+
+## 语法
+
+```SQL
+CREATE EXTERNAL RESOURCE "resource_name"
+PROPERTIES ("key"="value"[, ...])
+```
+
+## 参数说明
+
+### resource_name
+
+资源名称。命名要求参见[系统限制](../../System_limit.md)。
+
+### PROPERTIES
+
+资源配置项，不同类型的资源可设置不同配置项。
+
+#### Spark 资源
+
+Spark 集群配置不同，资源需要添加的配置项也不同。当前 Spark Load 仅支持 Spark 的 cluster manager 为 YARN 且数据存储系统为 HDFS，且 YARN 和 HDFS 均支持 HA（高可用）。具体可分为以下几种情况：
+
+- 如果选择使用Broker 进程的方式导入
+
+  - 如果 Spark 的 cluster manager 为 YARN，数据存储系统为 HDFS，则需添加如下配置项：
+
+    | **配置项**                                | **必选** | **说明**                                                     |
+    | ----------------------------------------- | -------- | ------------------------------------------------------------ |
+    | type                                      | 是       | 资源类型，取值为 `spark`。                                   |
+    | spark.master                              | 是       | Spark 的 cluster manager。当前仅支持 YARN，所以取值为 `yarn`。 |
+    | spark.submit.deployMode                   | 是       | Spark driver 的部署模式。取值包括`cluster`和`client`。关于取值说明，参考 [Launching Spark on YARN](https://spark.apache.org/docs/3.3.0/running-on-yarn.html#launching-spark-on-yarn)。 |
+    | spark.executor.memory                     | 否       | Spark executor 占用的内存量，单位为 KB、MB、GB 或 TB。       |
+    | spark.yarn.queue                          | 否       | YARN 队列名称。                                              |
+    | spark.hadoop.yarn.resourcemanager.address | 是       | YARN ResourceManager 地址。                                  |
+    | spark.hadoop.fs.defaultFS                 | 是       | HDFS 中 NameNode 的地址。格式为：`hdfs://namenode_host:port`。 |
+    | working_dir                               | 是       | 一个 HDFS 文件路径，用于存放 ETL 作业生成的文件。例如：`hdfs://host: port/tmp/starrocks`。 |
+    | broker                                    | 是       | Broker 名称。您可以使用 [SHOW BROKER](../cluster-management/nodes_processes/SHOW_BROKER.md) 语句查看当前所有 Broker 的名称。如未添加过 Broker，可使用 [ALTER SYSTEM](../cluster-management/nodes_processes/ALTER_SYSTEM.md) 语句添加 Broker。 |
+    | broker.username                           | 否       | 通过指定的 HDFS 用户去访问HDFS中的文件。如果 HDFS 文件只能由特定用户访问，则需要传入该参数，如果该文件是所有用户都可以访问的话，则不需要传入该参数。 |
+    | broker.password                           | 否       | HDFS 用户密码。                                              |
+
+  - 如果 Spark 的 cluster manager 为 YARN，并且为 YARN ResourceManager HA，数据存储系统为 HDFS，则需添加如下配置项：
+
+    | **配置项**                                       | **必选** | **说明**                                                     |
+    | ------------------------------------------------ | -------- | ------------------------------------------------------------ |
+    | type                                             | 是       | 资源类型，取值为`spark`。                                    |
+    | spark.master                                     | 是       | Spark 的 cluster manager。当前仅支持 YARN，所以取值为`yarn`。 |
+    | spark.submit.deployMode                          | 是       | Spark 驱动程序的部署模式。取值包括`cluster`和`client`。关于取值说明，参考 [Launching Spark on YARN](https://spark.apache.org/docs/3.3.0/running-on-yarn.html#launching-spark-on-yarn)。 |
+    | spark.hadoop.yarn.resourcemanager.ha.enabled     | 是       | YARN ResourceManager 是否启用 HA。需设置该参数为`true`，即启用 HA。 |
+    | spark.hadoop.yarn.resourcemanager.ha.rm-ids      | 是       | YARN ResourceManager 的逻辑 ID 列表。多个逻辑 ID 之间用逗号 (`,`) 隔开。 |
+    | spark.hadoop.yarn.resourcemanager.hostname.rm-id | 是       | 对于每个 rm-id，需指定 ResourceManager 对应的主机名。如已添加该配置项，则不需要再添加`spark.hadoop.yarn.resourcemanager.address.rm-id`。 |
+    | spark.hadoop.yarn.resourcemanager.address.rm-id  | 是       | 对于每个rm-id，需指定 ResourceManager 对应 `host:port`。如已添加该配置项，则不需要再添加`spark.hadoop.yarn.resourcemanager.hostname.rm-id`。 |
+    | spark.hadoop.fs.defaultFS                        | 是       | Spark 使用的 HDFS 中 NameNode 节点地址。格式为：`hdfs://namenode_host:port`。 |
+    | working_dir                                      | 是       | ETL 作业目录，用于存放 ETL 作业生成的中间数据。例如：`hdfs://host: port/tmp/starrocks`。 |
+    | broker                                           | 是       | Broker 名称。您可以使用 [SHOW BROKER](../cluster-management/nodes_processes/SHOW_BROKER.md) 语句查看当前所有 Broker 的名称。如未添加过 Broker，可使用 [ALTER SYSTEM](../cluster-management/nodes_processes/ALTER_SYSTEM.md) 语句添加 Broker。 |
+    | broker.username                           | 否       | 通过指定的 HDFS 用户去访问HDFS中的文件。如果 HDFS 文件只能由特定用户访问，则需要传入该参数，如果该文件是所有用户都可以访问的话，则不需要传入该参数。 |
+    | broker.password                           | 否       | HDFS 用户密码。                                              |
+
+  - 如果 Spark 的 cluster manager 为 YARN，数据存储系统为 HDFS HA，则需添加如下配置项：
+
+    | **配置项**                                                   | **必选** | **说明**                                                     |
+    | ------------------------------------------------------------ | -------- | ------------------------------------------------------------ |
+    | type                                                         | 是       | 资源类型，取值为`spark`。                                    |
+    | spark.master                                                 | 是       | Spark 的 cluster manager。当前仅支持 YARN，所以取值为 `yarn`。 |
+    | spark.hadoop.yarn.resourcemanager.address                    | 是       | YARN ResourceManager 地址。                                  |
+    | spark.hadoop.fs.defaultFS                                    | 是       | Spark 使用的 HDFS 中 NameNode 节点地址。格式为：`hdfs://namenode_host:port`。 |
+    | spark.hadoop.dfs.nameservices                                | 是       | HDFS nameservice 的 ID。该配置项供 Spark 使用。              |
+    | spark.hadoop.dfs.ha.namenodes.[nameservice ID]               | 是       | HDFS NameNode 的 ID。您可配置多个 NameNode ID。多个 NameNode ID 之间要用逗号 (`,`) 隔开。该配置项供 Spark 使用。 |
+    | spark.hadoop.dfs.namenode.rpc-address.[nameservice ID].[name node ID] | 是       | 每个 HDFS NameNode 监听的 RPC 地址。注意需配置完全限定的 RPC 地址。该配置项供 Spark 使用。 |
+    | spark.hadoop.dfs.client.failover.proxy.provider              | 是       | HDFS 的 Java 类，其用来联系 Active 状态的 NameNode。该配置项供 Spark 使用。 |
+    | working_dir                                                  | 是       | ETL 作业目录，用于存放 ETL 作业生成的中间数据。例如：`hdfs://host: port/tmp/starrocks`。 |
+    | broker                                                       | 是       | Broker 名称。您可以使用 [SHOW BROKER](../cluster-management/nodes_processes/SHOW_BROKER.md) 语句查看当前所有 Broker 的名称。如未添加过 Broker，可使用 [ALTER SYSTEM](../cluster-management/nodes_processes/ALTER_SYSTEM.md) 语句添加 Broker。 |
+    | broker.username                           | 否       | 通过指定的 HDFS 用户去访问HDFS中的文件。如果 HDFS 文件只能由特定用户访问，则需要传入该参数，如果该文件是所有用户都可以访问，则不需要传入该参数。 |
+    | broker.password                           | 否       | HDFS 用户密码。                                              |
+    | broker.dfs.nameservices                                      | 是       | HDFS nameservice 的 ID。该配置项供 Broker 使用。             |
+    | broker.dfs.ha.namenodes. [nameservice ID]                    | 是       | HDFS NameNode 的 ID。您可配置多个 NameNode ID。多个 NameNode ID 之间要用逗号 (`,`) 隔开。该配置项供 Broker 使用。 |
+    | broker.dfs.namenode.rpc-address. [nameservice ID].[name node ID] | 是       | 每个 HDFS NameNode 监听的 RPC 地址。注意需配置完全限定的 RPC 地址。该配置项供 Broker 使用。 |
+    | broker.dfs.client.failover.proxy.provider                    | 是       | HDFS 的 Java 类，其用来联系 Active 状态的 NameNode。该配置项供 Broker 使用。 |
+
+- 如果使用无 Broker 进程的方式导入，则在创建资源时参数设置与使用Broker 进程的方式导入稍有差异，具体差异如下：
+
+  - 无需传入 `broker`。
+  - 如果您需要配置用户身份认证、NameNode 节点的 HA，则需要在 HDFS 集群中的 **hdfs-site.xml** 文件中配置参数，具体参数和说明，请参见 [broker_properties](../loading_unloading/BROKER_LOAD.md#hdfs)。并且将 **hdfs-site.xml** 文件放到每一个 FE 的 **$FE_HOME/conf** 下以及每个 BE 的 **$BE_HOME/conf** 下。
+
+> **说明**
+>
+> - 使用无 Broker 进程的方式导入时，如果 HDFS 文件只能由特定用户访问，则您仍然需要传入 HDFS 用户名 `broker.name`和 HDFS 用户密码`broker.password`。
+> - 在以上几种情况中，如要添加除表格以外的配置项，可参考 [Spark Configuration](https://spark.apache.org/docs/latest/configuration.html) 和 [Running Spark on YARN](https://spark.apache.org/docs/latest/running-on-yarn.html)。
+
+#### Hive 资源
+
+如创建一个 Hive 资源，需添加如下配置项：
+
+| **配置项**          | **必选** | **说明**                  |
+| ------------------- | -------- | ------------------------- |
+| type                | 是       | 资源类型，取值为 `hive`。 |
+| hive.metastore.uris | 是       | Hive metastore 的 URI。   |
+
+#### Iceberg 资源
+
+如创建一个 Iceberg 资源，需添加如下配置项：
+
+| **配置项**                          | **必选** | **说明**                                                     |
+| ----------------------------------- | -------- | ------------------------------------------------------------ |
+| type                                | 是       | 资源类型，取值为 `iceberg`。                                 |
+| starrocks.catalog-type              | 是       | Iceberg 的 catalog 类型。StarRocks 2.3 以下版本仅支持 Hive catalog；StarRocks 2.3 及以上版本支持 Hive catalog 和 custom catalog。 如要使用 Hive catalog， 设置该参数为 `HIVE`。 如要使用 custom catalog，设置该参数为 `CUSTOM`。详细信息参见[创建 Iceberg 资源](../../../data_source/External_table.md#步骤一创建-iceberg-资源)。 |
+| iceberg.catalog.hive.metastore.uris | 是       | Hive metastore 的URI。                                       |
+
+#### Hudi 资源
+
+如创建一个 Hudi 资源，需添加如下配置项：
+
+| **配置项**          | **必选** | **说明**                  |
+| ------------------- | -------- | ------------------------- |
+| type                | 是       | 资源类型，取值为 `hudi`。 |
+| hive.metastore.uris | 是       | Hive metastore 的 URI。   |
+
+#### JDBC 资源
+
+如创建一个 JDBC 资源，需添加如下配置项：
+
+| **配置项**   | **必选** | **说明**                                                     |
+| ------------ | -------- | ------------------------------------------------------------ |
+| type         | 是       | 资源类型，取值为 `jdbc`。                                    |
+| user         | 是       | 登录到支持的 JDBC 数据库 （以下简称“目标数据库”）的用户名。  |
+| password     | 是       | 目标数据库的登录密码。                                       |
+| jdbc_uri     | 是       | 用于连接目标数据库的JDBC URI，需要满足目标数据库 URI 的语法。常见的目标数据库 URI，请参见 [MySQL](https://dev.mysql.com/doc/connector-j/en/connector-j-reference-jdbc-url-format.html)、[Oracle](https://docs.oracle.com/en/database/oracle/oracle-database/21/jjdbc/data-sources-and-URLs.html#GUID-6D8EFA50-AB0F-4A2B-88A0-45B4A67C361E)、[PostgreSQL](https://jdbc.postgresql.org/documentation/head/connect.html)、[SQL Server](https://docs.microsoft.com/en-us/sql/connect/jdbc/building-the-connection-url?view=sql-server-ver16) 官网文档。 |
+| driver_url   | 是       | 用于下载 JDBC 驱动程序 JAR 包的 URL，支持使用 HTTP 协议 或者 file 协议。例如 `https://repo1.maven.org/maven2/org/postgresql/postgresql/42.3.3/postgresql-42.3.3.jar`， `file:///home/disk1/postgresql-42.3.3.jar`。 |
+| driver_class | 是       | 目标数据库使用的 JDBC 驱动程序的类名称。常见的类名称如下： <ul><li>MySQL：com.mysql.jdbc.Driver（MySQL 5.x 及以下版本）和com.mysql.cj.jdbc.Driver （MySQL 6.x 及以上版本）</li><li>SQL Server：com.microsoft.sqlserver.jdbc.SQLServerDriver </li><li>Oracle： oracle.jdbc.driver.OracleDriver </li><li>PostgreSQL：org.postgresql.Driver</li></ul> |
+
+## 示例
+
+示例一： 当使用 YARN 作为 Spark 的 cluster manager，HDFS 来存储数据时，创建一个名为`spark0`的 Spark 资源，语句如下：
+
+```SQL
+CREATE EXTERNAL RESOURCE "spark0"
+PROPERTIES (
+    "type" = "spark",
+    "spark.master" = "yarn",
+    "spark.submit.deployMode" = "cluster",
+    "spark.executor.memory" = "1g",
+    "spark.yarn.queue" = "queue0",
+    "spark.hadoop.yarn.resourcemanager.address" = "resourcemanager_host:8032",
+    "spark.hadoop.fs.defaultFS" = "hdfs://namenode_host:9000",
+    "working_dir" = "hdfs://namenode_host:9000/tmp/starrocks",
+    "broker" = "broker0",
+    "broker.username" = "user0",
+    "broker.password" = "password0"
+);
+```
+
+示例二：当使用 YARN HA 作为 Spark 的 cluster manager，HDFS 来存储数据时，创建一个名为`spark1`的 Spark 资源，语句如下：
+
+```SQL
+CREATE EXTERNAL RESOURCE "spark1"
+PROPERTIES (
+    "type" = "spark",
+    "spark.master" = "yarn",
+    "spark.submit.deployMode" = "cluster",
+    "spark.hadoop.yarn.resourcemanager.ha.enabled" = "true",
+    "spark.hadoop.yarn.resourcemanager.ha.rm-ids" = "rm1,rm2",
+    "spark.hadoop.yarn.resourcemanager.hostname.rm1" = "host1",
+    "spark.hadoop.yarn.resourcemanager.hostname.rm2" = "host2",
+    "spark.hadoop.fs.defaultFS" = "hdfs://namenode_host:9000",
+    "working_dir" = "hdfs://namenode_host:9000/tmp/starrocks",
+    "broker" = "broker1"
+);
+```
+
+示例三：当使用 YARN 作为 Spark 的 cluster manager，HDFS HA 来存储数据时，创建一个名为`spark2`的 Spark 资源，语句如下：
+
+```SQL
+CREATE EXTERNAL RESOURCE "spark2"
+PROPERTIES (
+    "type" = "spark", 
+    "spark.master" = "yarn",
+    "spark.hadoop.yarn.resourcemanager.address" = "resourcemanager_host:8032",
+    "spark.hadoop.fs.defaultFS" = "hdfs://myha",
+    "spark.hadoop.dfs.nameservices" = "myha",
+    "spark.hadoop.dfs.ha.namenodes.myha" = "mynamenode1,mynamenode2",
+    "spark.hadoop.dfs.namenode.rpc-address.myha.mynamenode1" = "nn1_host:rpc_port",
+    "spark.hadoop.dfs.namenode.rpc-address.myha.mynamenode2" = "nn2_host:rpc_port",
+    "spark.hadoop.dfs.client.failover.proxy.provider" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider",
+    "working_dir" = "hdfs://myha/tmp/starrocks",
+    "broker" = "broker2",
+    "broker.dfs.nameservices" = "myha",
+    "broker.dfs.ha.namenodes.myha" = "mynamenode1,mynamenode2",
+    "broker.dfs.namenode.rpc-address.myha.mynamenode1" = "nn1_host:rpc_port",
+    "broker.dfs.namenode.rpc-address.myha.mynamenode2" = "nn2_host:rpc_port",
+    "broker.dfs.client.failover.proxy.provider" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
+);
+```
+
+示例四：创建一个名为`hive0`的 Hive 资源。
+
+```SQL
+CREATE EXTERNAL RESOURCE "hive0"
+PROPERTIES (
+  "type" = "hive",
+  "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083"
+);
+```
+
+示例五：创建一个名为`iceberg0`的 Iceberg 资源。
+
+```SQL
+CREATE EXTERNAL RESOURCE "iceberg0" 
+PROPERTIES ( 
+   "type" = "iceberg", 
+   "starrocks.catalog-type"="HIVE", 
+   "iceberg.catalog.hive.metastore.uris"="thrift://xx.xx.xx.xx:9083" 
+);
+```
+
+示例六：创建一个名为`hudi0`的 Hudi 资源。
+
+```SQL
+CREATE EXTERNAL RESOURCE "hudi0" 
+PROPERTIES ( 
+    "type" = "hudi", 
+    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083"
+);
+```
+
+示例七：创建一个名为`jdbc0`的 JDBC 资源。
+
+```SQL
+CREATE EXTERNAL RESOURCE jdbc0
+PROPERTIES (
+    "type"="jdbc",
+    "user"="postgres",
+    "password"="changeme",
+    "jdbc_uri"="jdbc:postgresql://127.0.0.1:5432/jdbc_test",
+    "driver_url"="https://repo1.maven.org/maven2/org/postgresql/postgresql/42.3.3/postgresql-42.3.3.jar",
+    "driver_class"="org.postgresql.Driver"
+);
+```
+
+## 相关操作
+
+- 如要修改资源属性，参见 [ALTER RESOURCE](ALTER_RESOURCE.md)。
+- 如要删除资源，参见 [DROP RESOURCE](DROP_RESOURCE.md)。
+- 如要使用 Spark 资源进行 Spark Load，参见 [Spark Load](../../../loading/SparkLoad.md)。
+- 如要引用 Hive、Iceberg、Hudi 和 JDBC 资源创建外部表，参见[外部表](../../../data_source/External_table.md)。
diff --git a/docs/zh/sql-reference/sql-statements/Resource/DROP_RESOURCE.md b/docs/zh/sql-reference/sql-statements/Resource/DROP_RESOURCE.md
new file mode 100644
index 00000000000000..029ce179d03c3c
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Resource/DROP_RESOURCE.md
@@ -0,0 +1,31 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP RESOURCE
+
+## 功能
+
+该语句用于删除一个已有的资源。需要拥有资源的 DROP 权限才可以删除资源。
+
+创建 RESOURCE 操作请参考 [CREATE RESOURCE](CREATE_RESOURCE.md) 章节。
+
+## 语法
+
+```sql
+DROP RESOURCE 'resource_name'
+```
+
+## 示例
+
+1. 删除名为 spark0 的 Spark 资源。
+
+    ```SQL
+    DROP RESOURCE 'spark0';
+    ```
+
+2. 删除名为 hive0 的 Hive 资源。
+
+    ```SQL
+    DROP RESOURCE 'hive0';
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/Resource/SHOW_RESOURCES.md b/docs/zh/sql-reference/sql-statements/Resource/SHOW_RESOURCES.md
new file mode 100644
index 00000000000000..05bd3196d3d6a6
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Resource/SHOW_RESOURCES.md
@@ -0,0 +1,42 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW RESOURCES
+
+## 功能
+
+用于展示用户有使用权限 (USAGE) 的资源。
+
+> **注意**
+>
+> 普通用户可以看到自己有 USAGE 权限的资源，`db_admin` 角色可以看到全局资源。
+
+## 语法
+
+```sql
+SHOW RESOURCES
+```
+
+返回字段
+
+| 字段     | 说明                                              |
+| -------- | ----------------------------------|
+| Name    | 资源名称。                                          |
+| ResourceType    | 资源类型，比如 spark。                       |
+| Key     |  创建资源时在 PROPERTIES 里指定的 key。               |
+| Value   |    key 对应的 value。                               |
+
+## 示例
+
+```plain
+MySQL [(none)]> show resources;
++-------------------+--------------+---------------------+-----------------------+
+| Name              | ResourceType | Key                 | Value                 |
++-------------------+--------------+---------------------+-----------------------+
+| spark_resource_16ce91e4_e20a_11ed_a756_00163e0e489a | spark | spark.master | yarn |
+```
+
+## Keywords
+
+show resource, show resources
diff --git a/docs/zh/sql-reference/sql-statements/Resource/_category_.yml b/docs/zh/sql-reference/sql-statements/Resource/_category_.yml
new file mode 100644
index 00000000000000..79f3e6be74c47b
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/Resource/_category_.yml
@@ -0,0 +1,6 @@
+position: 70 # float position is supported
+label: '资源组'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/Utility/DESCRIBE.md b/docs/zh/sql-reference/sql-statements/Utility/DESCRIBE.md
deleted file mode 100644
index aa6107a467e5d3..00000000000000
--- a/docs/zh/sql-reference/sql-statements/Utility/DESCRIBE.md
+++ /dev/null
@@ -1,118 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DESC
-
-## 功能
-
-您可以使用该语句进行如下操作：
-
-- 查看 StarRocks 表结构、[排序键](../../../table_design/indexes/Prefix_index_sort_key.md) (Sort Key) 类型和[物化视图](../../../using_starrocks/Materialized_view.md)。
-- 查看外部数据源（如 Apache Hive™）中的表结构。仅 StarRocks 2.4 及以上版本支持该操作。
-
-## 语法
-
-```SQL
-DESC[RIBE] [catalog_name.][db_name.]table_name [ALL];
-```
-
-## 参数说明
-
-| **参数**     | **必选** | **说明**                                                     |
-| ------------ | -------- | ------------------------------------------------------------ |
-| catalog_name | 否       | Internal catalog 或 external catalog 的名称。<ul><li>如指定 internal catalog 名称，即 `default_catalog`，则查看当前 StarRocks 集群的指定表结构。</li><li>如指定 external catalog 名称，则查看外部数据源的指定表结构。</li></ul> |
-| db_name      | 否       | 数据库名称。                                                 |
-| table_name   | 是       | 表名称。                                                     |
-| ALL          | 否       | <ul><li>如要查看 StarRocks 表的排序键类型和物化视图，则指定该关键字；如只查看 StarRocks 表结构，则可以不指定。</li><li>如查看外部数据源表结构，不能指定该关键词。</li></ul> |
-
-## 返回信息说明
-
-```Plain
-+-----------+---------------+-------+------+------+-----+---------+-------+
-| IndexName | IndexKeysType | Field | Type | Null | Key | Default | Extra |
-+-----------+---------------+-------+------+------+-----+---------+-------+
-```
-
-返回信息中的参数说明：
-
-| **参数**      | **说明**                                                     |
-| ------------- | ------------------------------------------------------------ |
-| IndexName     | 表名。如查看外部数据源表结构，则不返回该参数。               |
-| IndexKeysType | 表的排序键类型。如查看外部数据源表结构，则不返回该参数。     |
-| Field         | 列名。                                                       |
-| Type          | 列的数据型。                                               |
-| Null          | 是否允许为 NULL。<ul><li>`yes`: 表示允许为 NULL。</li><li>`no`：表示不允许为 NULL。</li></ul> |
-| Key           | 是否为排序键。<ul><li>`true`: 表示为排序键。</li><li>`false`：表示不为排序键。</li></ul> |
-| Default       | 数据类型的默认值。如该数据类型没有默认值，则返回 NULL。      |
-| Extra         | <ul><li>如果是查看 StarRocks 表结构，该参数会根据情况返回以下信息：<ul><li>该列使用了哪种聚合函数，如 SUM 和 MIN。</li><li>该列是否创建了 bloom filter 索引。如创建，则追加显示 `BLOOM_FILTER`。</li></ul></li><li>如果是查看外部数据源表结构，该参数会显示该列是否为分区键 (partition column)。如是，则显示 `partition key`。</li></ul> |
-
-> 说明：有关物化视图的展示，请参见示例二。
-
-## 示例
-
-示例一：查看 StarRocks 的 `example_table` 表结构信息。
-
-```SQL
-DESC example_table;
-```
-
-或
-
-```SQL
-DESC default_catalog.example_db.example_table;
-```
-
-返回信息如下：
-
-```Plain
-+-------+---------------+------+-------+---------+-------+
-| Field | Type          | Null | Key   | Default | Extra |
-+-------+---------------+------+-------+---------+-------+
-| k1    | TINYINT       | Yes  | true  | NULL    |       |
-| k2    | DECIMAL(10,2) | Yes  | true  | 10.5    |       |
-| k3    | CHAR(10)      | Yes  | false | NULL    |       |
-| v1    | INT           | Yes  | false | NULL    |       |
-+-------+---------------+------+-------+---------+-------+
-```
-
-示例二：查看 StarRocks 的 `sales_records` 表结构、排序键类型和物化视图。如下所示， `sales_records` 表只有一张物化视图 `store_amt`。
-
-```Plain
-DESC db1.sales_records ALL;
-
-+---------------+---------------+-----------+--------+------+-------+---------+-------+
-| IndexName     | IndexKeysType | Field     | Type   | Null | Key   | Default | Extra |
-+---------------+---------------+-----------+--------+------+-------+---------+-------+
-| sales_records | DUP_KEYS      | record_id | INT    | Yes  | true  | NULL    |       |
-|               |               | seller_id | INT    | Yes  | true  | NULL    |       |
-|               |               | store_id  | INT    | Yes  | true  | NULL    |       |
-|               |               | sale_date | DATE   | Yes  | false | NULL    | NONE  |
-|               |               | sale_amt  | BIGINT | Yes  | false | NULL    | NONE  |
-|               |               |           |        |      |       |         |       |
-| store_amt     | AGG_KEYS      | store_id  | INT    | Yes  | true  | NULL    |       |
-|               |               | sale_amt  | BIGINT | Yes  | false | NULL    | SUM   |
-+---------------+---------------+-----------+--------+------+-------+---------+-------+
-```
-
-示例三：查看 Hive 中 `hive_table` 表结构。
-
-```SQL
-DESC hive_catalog.hive_db.hive_table;
-
-+-------+----------------+------+-------+---------+---------------+ 
-| Field | Type           | Null | Key   | Default | Extra         | 
-+-------+----------------+------+-------+---------+---------------+ 
-| id    | INT            | Yes  | false | NULL    |               | 
-| name  | VARCHAR(65533) | Yes  | false | NULL    |               | 
-| date  | DATE           | Yes  | false | NULL    | partition key | 
-+-------+----------------+------+-------+---------+---------------+
-```
-
-## 相关文档
-
-- [CREATE DATABASE](../data-definition/CREATE_DATABASE.md)
-- [SHOW CREATE DATABASE](../data-manipulation/SHOW_CREATE_DATABASE.md)
-- [USE](../data-definition/USE.md)
-- [SHOW DATABASES](../data-manipulation/SHOW_DATABASES.md)
-- [DROP DATABASE](../data-definition/DROP_DATABASE.md)
diff --git a/docs/zh/sql-reference/sql-statements/View/ALTER_VIEW.md b/docs/zh/sql-reference/sql-statements/View/ALTER_VIEW.md
new file mode 100644
index 00000000000000..291d1317c63179
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/View/ALTER_VIEW.md
@@ -0,0 +1,40 @@
+---
+keywords: ['xiugai', 'shitu'] 
+displayed_sidebar: docs
+---
+
+# ALTER VIEW
+
+## 功能
+
+该语句用于修改一个逻辑视图的定义。
+
+## 语法
+
+```sql
+ALTER VIEW
+[db_name.]view_name
+(column1[ COMMENT "col comment"][, column2, ...])
+AS query_stmt
+```
+
+说明：
+
+1. 逻辑视图中的数据不会存储在物理介质上，在查询时，逻辑视图将作为语句中的子查询，因此，修改逻辑视图的定义等价于修改 query_stmt。
+2. query_stmt 为任意支持的 SQL。
+
+## 示例
+
+1. 修改example_db上的逻辑视图example_view。
+
+    ```sql
+    ALTER VIEW example_db.example_view
+    (
+        c1 COMMENT "column 1",
+        c2 COMMENT "column 2",
+        c3 COMMENT "column 3"
+    )
+    AS SELECT k1, k2, SUM(v1) 
+    FROM example_table
+    GROUP BY k1, k2;
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/View/CREATE_VIEW.md b/docs/zh/sql-reference/sql-statements/View/CREATE_VIEW.md
new file mode 100644
index 00000000000000..8fb98f78f2effa
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/View/CREATE_VIEW.md
@@ -0,0 +1,80 @@
+---
+displayed_sidebar: docs
+keywords: ['shitu']
+---
+
+# CREATE VIEW
+
+## 功能
+
+创建一个视图。
+
+视图（或逻辑视图）是一种虚拟表，其中的数据来自于对其他现有实体表的查询结果。因此，视图无需占用物理存储空间。所有针对视图的查询相当于该视图对应查询语句之上的子查询。
+
+关于 StarRocks 支持的物化视图，请参阅[同步物化视图](../../../using_starrocks/Materialized_view-single_table.md)和[异步物化视图](../../../using_starrocks/Materialized_view.md)。
+
+> **注意**
+>
+> 该操作需要有指定数据库的 CREATE VIEW 权限。
+
+## 语法
+
+```SQL
+CREATE [OR REPLACE] VIEW [IF NOT EXISTS]
+[<database>.]<view_name>
+(
+    <column_name>[ COMMENT 'column comment']
+    [, <column_name>[ COMMENT 'column comment'], ...]
+)
+[COMMENT 'view comment']
+AS <query_statement>
+```
+
+## 参数说明
+
+| **参数**        | **说明**                                                     |
+| --------------- | ------------------------------------------------------------ |
+| OR REPLACE      | 替换已有视图。                                               |
+| database        | 视图所属的数据库名。                                         |
+| view_name       | 视图名。命名要求参见[系统限制](../../System_limit.md)。                                                     |
+| column_name     | 视图中的列名。请注意，视图中的列和 `query_statement` 中查询的列的数量必须一致。 |
+| COMMENT         | 视图中的列或视图本身的注释。                                 |
+| query_statement | 用于创建视图的查询语句。可以为 StarRocks 支持的任意查询语句。 |
+
+## 使用说明
+
+- 查询视图需要该视图的 SELECT 权限和其对应基表的 SELECT 权限。
+- 如果基表变更导致创建视图的查询语句无法执行，则查询该视图时报错。
+
+## 示例
+
+示例一：通过基于表 `example_table` 的聚合查询在数据库 `example_db` 中创建名为 `example_view` 的视图。
+
+```SQL
+CREATE VIEW example_db.example_view (k1, k2, k3, v1)
+AS
+SELECT c1 as k1, k2, k3, SUM(v1) FROM example_table
+WHERE k1 = 20160112 GROUP BY k1,k2,k3;
+```
+
+示例二：通过基于表 `example_table` 的聚合查询在数据库 `example_db` 中创建名为 `example_view` 的视图，并为视图和其中的列设置注释。
+
+```SQL
+CREATE VIEW example_db.example_view
+(
+    k1 COMMENT 'first key',
+    k2 COMMENT 'second key',
+    k3 COMMENT 'third key',
+    v1 COMMENT 'first value'
+)
+COMMENT 'my first view'
+AS
+SELECT c1 as k1, k2, k3, SUM(v1) FROM example_table
+WHERE k1 = 20160112 GROUP BY k1,k2,k3;
+```
+
+## 相关 SQL
+
+- [SHOW CREATE VIEW](SHOW_CREATE_VIEW.md)
+- [ALTER VIEW](ALTER_VIEW.md)
+- [DROP VIEW](DROP_VIEW.md)
diff --git a/docs/zh/sql-reference/sql-statements/View/DROP_VIEW.md b/docs/zh/sql-reference/sql-statements/View/DROP_VIEW.md
new file mode 100644
index 00000000000000..401128f0bc932e
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/View/DROP_VIEW.md
@@ -0,0 +1,28 @@
+---
+displayed_sidebar: docs
+keywords: ['shitu']
+---
+
+# DROP VIEW
+
+## 功能
+
+该语句用于删除一个逻辑视图。
+
+## 语法
+
+```sql
+DROP VIEW [IF EXISTS] [db_name.]view_name
+```
+
+## 示例
+
+1. 如果存在，删除 example_db 上的逻辑视图 example_view。
+
+    ```sql
+    DROP VIEW IF EXISTS example_db.example_view;
+    ```
+
+## 相关操作
+
+如要创建逻辑视图，请参考 [CREATE VIEW](CREATE_VIEW.md)。
diff --git a/docs/zh/sql-reference/sql-statements/View/SHOW_CREATE_VIEW.md b/docs/zh/sql-reference/sql-statements/View/SHOW_CREATE_VIEW.md
new file mode 100644
index 00000000000000..924aea1bedbea1
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/View/SHOW_CREATE_VIEW.md
@@ -0,0 +1,108 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW CREATE VIEW
+
+## 功能
+
+查看指定逻辑视图的创建语句 CREATE VIEW。视图创建语句可以帮助您理解视图定义，作为后续修改视图或重建视图的参考。
+
+> **注意**
+>
+> 只有拥有该视图和视图对应基表的 SELECT 权限的用户才可以查看。
+
+从 2.5.4 版本开始，为了兼容 MySQL 标准语法，支持使用 SHOW CREATE VIEW 来查看异步物化视图的创建语句。该语句将物化视图当做普通视图来处理。
+
+## 语法
+
+```SQL
+SHOW CREATE VIEW [<db_name>.]<view_name>
+```
+
+## 参数说明
+
+| **参数**  | **必选** | **说明**                                                     |
+| --------- | -------- | ------------------------------------------------------------ |
+| db_name   | 否       | 数据库名称。如不指定，则默认查看当前数据库中指定视图的创建语句。 |
+| view_name | 是       | 视图名称。                                                   |
+
+## 返回结果说明
+
+```plain
++---------+--------------+----------------------+----------------------+
+| View    | Create View  | character_set_client | collation_connection |
++---------+--------------+----------------------+----------------------+
+```
+
+返回结果中的参数说明如下：
+
+| **参数**             | **说明**                                  |
+| -------------------- | ----------------------------------------- |
+| View                 | 视图名称。                                |
+| Create View          | 视图的创建语句。                          |
+| character_set_client | 客户端连接 StarRocks 服务端使用的字符集。 |
+| collation_connection | 字符集的校对规则。                        |
+
+## 示例
+
+### 查看逻辑视图创建语句
+
+创建表 `base`。
+
+```SQL
+CREATE TABLE base (
+    k1 date,
+    k2 int,
+    v1 int sum)
+PARTITION BY RANGE(k1)
+(
+    PARTITION p1 values less than('2020-02-01'),
+    PARTITION p2 values less than('2020-03-01')
+)
+DISTRIBUTED BY HASH(k2)
+PROPERTIES( "replication_num"  = "3");
+```
+
+在表 `base` 上创建视图 `example_view`。
+
+```SQL
+CREATE VIEW example_view (k1, k2, v1)
+AS SELECT k1, k2, v1 FROM base;
+```
+
+查看视图 `example_view` 的创建语句。
+
+```Plain
+SHOW CREATE VIEW example_view;
+
+MySQL [yn_db]> SHOW CREATE VIEW example_view;
++--------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+----------------------+----------------------+
+| View         | Create View                                                                                                                                         | character_set_client | collation_connection |
++--------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+----------------------+----------------------+
+| example_view | CREATE VIEW `example_view` (k1, k2, v1) COMMENT "VIEW" AS SELECT `yn_db`.`base`.`k1`, `yn_db`.`base`.`k2`, `yn_db`.`base`.`v1`
+FROM `yn_db`.`base`; | utf8                 | utf8_general_ci      |
++--------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+----------------------+----------------------+
+
+```
+
+### 查看物化视图创建语句
+
+在表 `base` 上创建物化视图 `example_mv`。
+
+```SQL
+CREATE MATERIALIZED VIEW example_mv distributed by hash(k1)
+AS SELECT k1 FROM base;
+```
+
+查看物化视图 `example_mv` 的创建语句。
+
+```Plain
+SHOW CREATE VIEW example_mv;
++------------+----------------------------------------------------------------------------+----------------------+----------------------+
+| View       | Create View                                                                | character_set_client | collation_connection |
++------------+----------------------------------------------------------------------------+----------------------+----------------------+
+| example_mv | CREATE VIEW `example_mv` AS SELECT `yn_db`.`base`.`k1`
+FROM `yn_db`.`base` | utf8                 | utf8_general_ci      |
++------------+------------------------------------------------
+```
diff --git a/docs/zh/sql-reference/sql-statements/View/_category_.yml b/docs/zh/sql-reference/sql-statements/View/_category_.yml
new file mode 100644
index 00000000000000..cca3dff0db85c3
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/View/_category_.yml
@@ -0,0 +1,6 @@
+position: 90 # float position is supported
+label: '视图'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/_category_.yml b/docs/zh/sql-reference/sql-statements/_category_.yml
new file mode 100644
index 00000000000000..64815c66a56e07
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/_category_.yml
@@ -0,0 +1,6 @@
+position: 50 # float position is supported
+label: 'SQL 参考手册'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/account-management/ALTER_USER.md b/docs/zh/sql-reference/sql-statements/account-management/ALTER_USER.md
index 58218a5462ee01..c05bca617a339f 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/ALTER_USER.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/ALTER_USER.md
@@ -1,6 +1,6 @@
 ---
 keywords: ['xiugai'] 
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # ALTER USER
diff --git a/docs/zh/sql-reference/sql-statements/account-management/CREATE_ROLE.md b/docs/zh/sql-reference/sql-statements/account-management/CREATE_ROLE.md
index 670bc7d7aafdec..17d8ce1acb7b46 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/CREATE_ROLE.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/CREATE_ROLE.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # CREATE ROLE
@@ -20,7 +20,7 @@ CREATE ROLE <role_name>
 
 ## 参数说明
 
-`role_name`：角色名称，命名要求参见[系统限制](../../../reference/System_limit.md)。
+`role_name`：角色名称，命名要求参见[系统限制](../../System_limit.md)。
 
 > 注意：角色名称不能与 StarRocks 的系统预置角色 `root`，`cluster_admin`，`db_admin`，`user_admin`，`public` 重复。
 
diff --git a/docs/zh/sql-reference/sql-statements/account-management/CREATE_USER.md b/docs/zh/sql-reference/sql-statements/account-management/CREATE_USER.md
index 4cca6037990757..0c679c8f593939 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/CREATE_USER.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/CREATE_USER.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # CREATE USER
@@ -22,7 +22,7 @@ CREATE USER [IF NOT EXISTS] <user_identity> [auth_option] [DEFAULT ROLE <role_na
 
 - `user_identity`：用户标识。由登录IP（userhost）和用户名（username）组成，写作：`username@'userhost'` 。其中，`userhost` 的部分可以使用 `%` 来进行模糊匹配。如果不指定 `userhost`，默认为 `%`，即表示创建一个可以从任意 host 使用 `username` 链接到 StarRocks 的用户。
 
-  有关用户名 (username) 的命名要求，参见[系统限制](../../../reference/System_limit.md)。
+  有关用户名 (username) 的命名要求，参见[系统限制](../../System_limit.md)。
 
 - `auth_option`：用户的认证方式。目前，StarRocks 支持原生密码、mysql_native_password 和 LDAP 三种认证方式，其中，原生密码与 mysql_native_password 认证方式的内在逻辑相同，仅在具体设置语法上有轻微差别。同一个 user identity 只能使用一种认证方式。
 
diff --git a/docs/zh/sql-reference/sql-statements/account-management/DROP_ROLE.md b/docs/zh/sql-reference/sql-statements/account-management/DROP_ROLE.md
index c9fdd41f121501..319b93733e83f4 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/DROP_ROLE.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/DROP_ROLE.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # DROP ROLE
diff --git a/docs/zh/sql-reference/sql-statements/account-management/DROP_USER.md b/docs/zh/sql-reference/sql-statements/account-management/DROP_USER.md
index fadff97a3702a7..b5fd1aaa3d108f 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/DROP_USER.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/DROP_USER.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # DROP USER
diff --git a/docs/zh/sql-reference/sql-statements/account-management/EXECUTE_AS.md b/docs/zh/sql-reference/sql-statements/account-management/EXECUTE_AS.md
index 3806c2cfcf333a..a686f1f00a9aff 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/EXECUTE_AS.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/EXECUTE_AS.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # EXECUTE AS
diff --git a/docs/zh/sql-reference/sql-statements/account-management/GRANT.md b/docs/zh/sql-reference/sql-statements/account-management/GRANT.md
index 84998cb970324a..e1517b5fd16ffd 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/GRANT.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/GRANT.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 4
 ---
 
diff --git a/docs/zh/sql-reference/sql-statements/account-management/REVOKE.md b/docs/zh/sql-reference/sql-statements/account-management/REVOKE.md
index f54f677b5d4a74..e4c357e885088a 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/REVOKE.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/REVOKE.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # REVOKE
diff --git a/docs/zh/sql-reference/sql-statements/account-management/SET_DEFAULT_ROLE.md b/docs/zh/sql-reference/sql-statements/account-management/SET_DEFAULT_ROLE.md
index 598d3b342116ac..7af260240f7793 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/SET_DEFAULT_ROLE.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/SET_DEFAULT_ROLE.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # SET DEFAULT ROLE
diff --git a/docs/zh/sql-reference/sql-statements/account-management/SET_PASSWORD.md b/docs/zh/sql-reference/sql-statements/account-management/SET_PASSWORD.md
index 54eae543f875f3..fad37fdfea5f0b 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/SET_PASSWORD.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/SET_PASSWORD.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # SET PASSWORD
diff --git a/docs/zh/sql-reference/sql-statements/account-management/SET_PROPERTY.md b/docs/zh/sql-reference/sql-statements/account-management/SET_PROPERTY.md
index aee4d42e040844..507d279b0354a8 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/SET_PROPERTY.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/SET_PROPERTY.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # SET PROPERTY
diff --git a/docs/zh/sql-reference/sql-statements/account-management/SET_ROLE.md b/docs/zh/sql-reference/sql-statements/account-management/SET_ROLE.md
index 4af7b10fdd469d..fa9b161c1c61ff 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/SET_ROLE.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/SET_ROLE.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # SET ROLE
diff --git a/docs/zh/sql-reference/sql-statements/account-management/SHOW_AUTHENTICATION.md b/docs/zh/sql-reference/sql-statements/account-management/SHOW_AUTHENTICATION.md
index e160c86b00110d..202b0898cd2b67 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/SHOW_AUTHENTICATION.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/SHOW_AUTHENTICATION.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # SHOW AUTHENTICATION
diff --git a/docs/zh/sql-reference/sql-statements/account-management/SHOW_GRANTS.md b/docs/zh/sql-reference/sql-statements/account-management/SHOW_GRANTS.md
index 45cf9c14859df6..8dc906ec78bb1b 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/SHOW_GRANTS.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/SHOW_GRANTS.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # SHOW GRANTS
diff --git a/docs/zh/sql-reference/sql-statements/account-management/SHOW_PROPERTY.md b/docs/zh/sql-reference/sql-statements/account-management/SHOW_PROPERTY.md
index b01f0fd1c64297..a6bbbb5e482ad1 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/SHOW_PROPERTY.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/SHOW_PROPERTY.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 
diff --git a/docs/zh/sql-reference/sql-statements/account-management/SHOW_ROLES.md b/docs/zh/sql-reference/sql-statements/account-management/SHOW_ROLES.md
index 1f6edf6a195039..b0441727934139 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/SHOW_ROLES.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/SHOW_ROLES.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # SHOW ROLES
diff --git a/docs/zh/sql-reference/sql-statements/account-management/SHOW_USERS.md b/docs/zh/sql-reference/sql-statements/account-management/SHOW_USERS.md
index 81cb70603ac04c..3248da862be2ff 100644
--- a/docs/zh/sql-reference/sql-statements/account-management/SHOW_USERS.md
+++ b/docs/zh/sql-reference/sql-statements/account-management/SHOW_USERS.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # SHOW USERS
diff --git a/docs/zh/sql-reference/sql-statements/account-management/_category_.yml b/docs/zh/sql-reference/sql-statements/account-management/_category_.yml
new file mode 100644
index 00000000000000..10711b709875b9
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/account-management/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: '用户账户管理'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/all-commands.md b/docs/zh/sql-reference/sql-statements/all-commands.md
deleted file mode 100644
index cb7369112044ef..00000000000000
--- a/docs/zh/sql-reference/sql-statements/all-commands.md
+++ /dev/null
@@ -1,291 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# All commands
-
-本文罗列了所有 StarRocks 支持的 SQL 命令，并按照命令的功能进行了分类。
-
-- [All commands](#all-commands)
-  - [用户账户管理](#用户账户管理)
-  - [集群管理](#集群管理)
-    - [节点和进程](#节点和进程)
-    - [资源组](#资源组)
-    - [存储卷](#存储卷)
-    - [表，tablet，副本检查与修复](#表tablet副本检查与修复)
-    - [系统配置、变量](#系统配置变量)
-    - [文件](#文件)
-    - [SQL 黑名单](#sql-黑名单)
-    - [插件](#插件)
-    - [执行计划和 Profile](#执行计划和-profile)
-  - [导入，导出](#导入导出)
-    - [Routine load](#routine-load)
-    - [其他导入](#其他导入)
-    - [Pipe](#pipe)
-    - [导出](#导出)
-    - [ETL 任务](#etl-任务)
-  - [数据目录 (Catalog)，数据库，资源](#数据目录-catalog数据库资源)
-    - [Catalog](#catalog)
-    - [数据库](#数据库)
-    - [资源](#资源)
-  - [表，分区，分桶，索引](#表分区分桶索引)
-  - [视图，物化视图](#视图物化视图)
-    - [视图](#视图)
-    - [物化视图](#物化视图)
-  - [函数，SELECT](#函数select)
-  - [CBO 统计信息](#cbo-统计信息)
-  - [备份与恢复](#备份与恢复)
-  - [工具辅助语句](#工具辅助语句)
-
-## 用户账户管理
-
-管理用户、角色、和权限。
-
-- [ALTER USER](./account-management/ALTER_USER.md)
-- [CREATE ROLE](./account-management/CREATE_ROLE.md)
-- [CREATE USER](./account-management/CREATE_USER.md)
-- [DROP ROLE](./account-management/DROP_ROLE.md)
-- [DROP USER](./account-management/DROP_USER.md)
-- [EXECUTE AS](./account-management/EXECUTE_AS.md)
-- [GRANT](./account-management/GRANT.md)
-- [REVOKE](./account-management/REVOKE.md)
-- [SET DEFAULT ROLE](./account-management/SET_DEFAULT_ROLE.md)
-- [SET PASSWORD](./account-management/SET_PASSWORD.md)
-- [SET PROPERTY](./account-management/SET_PROPERTY.md)
-- [SET ROLE](./account-management/SET_ROLE.md)
-- [SHOW AUTHENTICATION](./account-management/SHOW_AUTHENTICATION.md)
-- [SHOW GRANTS](./account-management/SHOW_GRANTS.md)
-- [SHOW PROPERTY](./account-management/SHOW_PROPERTY.md)
-- [SHOW ROLES](./account-management/SHOW_ROLES.md)
-- [SHOW USERS](./account-management/SHOW_USERS.md)
-
-## 集群管理
-
-管理集群，包括 FE、BE、Compute Node (CN) 节点、资源组 (Resource Group)、存储卷（Storage Volume）、表、Tablet、副本 (Replica)、文件、变量（Variable）、插件（Plugin）、SQL Blacklist 等。
-
-### 节点和进程
-
-- [ALTER SYSTEM](./Administration/ALTER_SYSTEM.md)
-- [CANCEL DECOMMISSION](./Administration/CANCEL_DECOMMISSION.md)
-- [KILL](./Administration/KILL.md)
-- [SHOW BACKENDS](./Administration/SHOW_BACKENDS.md)
-- [SHOW BROKER](./Administration/SHOW_BROKER.md)
-- [SHOW COMPUTE NODES](./Administration/SHOW_COMPUTE_NODES.md)
-- [SHOW FRONTENDS](./Administration/SHOW_FRONTENDS.md)
-- [SHOW PROC](./Administration/SHOW_PROC.md)
-- [SHOW PROCESSLIST](./Administration/SHOW_PROCESSLIST.md)
-- [SHOW RUNNING QUERIES](./Administration/SHOW_RUNNING_QUERIES.md)
-- [ADD BACKEND BLACKLIST](./Administration/ADD_BACKEND_BLACKLIST.md)
-- [DELETE BACKEND BLACKLIST](./Administration/DELETE_BACKEND_BLACKLIST.md)
-- [SHOW BACKEND BLACKLIST](./Administration/SHOW_BACKEND_BLACKLIST.md)
-- [SYNC](./Administration/SYNC.md)
-
-### 资源组
-
-- [ALTER RESOURCE GROUP](./Administration/ALTER_RESOURCE_GROUP.md)
-- [CREATE RESOURCE GROUP](./Administration/CREATE_RESOURCE_GROUP.md)
-- [DROP RESOURCE GROUP](./Administration/DROP_RESOURCE_GROUP.md)
-- [SHOW RESOURCE GROUP](./Administration/SHOW_RESOURCE_GROUP.md)
-- [SHOW USAGE RESOURCE GROUPS](./Administration/SHOW_USAGE_RESOURCE_GROUPS.md)
-
-### 存储卷
-
-- [ALTER STORAGE VOLUME](./Administration/ALTER_STORAGE_VOLUME.md)
-- [CREATE STORAGE VOLUME](./Administration/CREATE_STORAGE_VOLUME.md)
-- [DESC STORAGE VOLUME](./Administration/DESC_STORAGE_VOLUME.md)
-- [DROP STORAGE VOLUME](./Administration/DROP_STORAGE_VOLUME.md)
-- [SET DEFAULT STORAGE VOLUME](./Administration/SET_DEFAULT_STORAGE_VOLUME.md)
-- [SHOW STORAGE VOLUMES](./Administration/SHOW_STORAGE_VOLUMES.md)
-
-### 表，tablet，副本检查与修复
-
-- [ADMIN CANCEL REPAIR TABLE](./Administration/ADMIN_CANCEL_REPAIR.md)
-- [ADMIN CHECK TABLET](./Administration/ADMIN_CHECK_TABLET.md)
-- [ADMIN REPAIR TABLE](./Administration/ADMIN_REPAIR.md)
-- [ADMIN SET REPLICA STATUS](./Administration/ADMIN_SET_REPLICA_STATUS.md)
-- [ADMIN SET PARTITION VERSION](./Administration/ADMIN_SET_PARTITION_VERSION.md)
-- [ADMIN SHOW REPLICA DISTRIBUTION](./Administration/ADMIN_SHOW_REPLICA_DISTRIBUTION.md)
-- [ADMIN SHOW REPLICA STATUS](./Administration/ADMIN_SHOW_REPLICA_STATUS.md)
-- [SHOW TABLE STATUS](./Administration/SHOW_TABLE_STATUS.md)
-
-### 系统配置、变量
-
-- [ADMIN SET CONFIG](./Administration/ADMIN_SET_CONFIG.md)
-- [ADMIN SHOW CONFIG](./Administration/ADMIN_SHOW_CONFIG.md)
-- [SET (variable)](./Administration/SET.md)
-- [SHOW VARIABLES](./Administration/SHOW_VARIABLES.md)
-
-### 文件
-
-- [CREATE FILE](./Administration/CREATE_FILE.md)
-- [DROP FILE](./Administration/DROP_FILE.md)
-- [SHOW FILE](./Administration/SHOW_FILE.md)
-
-### SQL 黑名单
-
-- [ADD SQLBLACKLIST](./Administration/ADD_SQLBLACKLIST.md)
-- [DELETE SQLBLACKLIST](./Administration/DELETE_SQLBLACKLIST.md)
-- [SHOW SQLBLACKLIST](./Administration/SHOW_SQLBLACKLIST.md)
-
-### 插件
-
-- [INSTALL PLUGIN](./Administration/INSTALL_PLUGIN.md)
-- [SHOW PLUGINS](./Administration/SHOW_PLUGINS.md)
-- [UNINSTALL PLUGIN](./Administration/UNINSTALL_PLUGIN.md)
-
-### 执行计划和 Profile
-
-- [ANALYZE PROFILE](./Administration/ANALYZE_PROFILE.md)
-- [EXPLAIN](./Administration/EXPLAIN.md)
-- [EXPLAIN ANALYZE](./Administration/EXPLAIN_ANALYZE.md)
-- [SHOW PROFILELIST](./Administration/SHOW_PROFILELIST.md)
-
-## 导入，导出
-
-### Routine load
-
-- [ALTER ROUTINE LOAD](./data-manipulation/ALTER_ROUTINE_LOAD.md)
-- [CREATE ROUTINE LOAD](./data-manipulation/CREATE_ROUTINE_LOAD.md)
-- [PAUSE ROUTINE LOAD](./data-manipulation/PAUSE_ROUTINE_LOAD.md)
-- [RESUME ROUTINE LOAD](./data-manipulation/RESUME_ROUTINE_LOAD.md)
-- [SHOW ROUTINE LOAD](./data-manipulation/SHOW_ROUTINE_LOAD.md)
-- [SHOW ROUTINE LOAD TASK](./data-manipulation/SHOW_ROUTINE_LOAD_TASK.md)
-- [STOP ROUTINE LOAD](./data-manipulation/STOP_ROUTINE_LOAD.md)
-
-### 其他导入
-
-- [ALTER LOAD](./data-manipulation/ALTER_LOAD.md)
-- [BROKER LOAD](./data-manipulation/BROKER_LOAD.md)
-- [CANCEL LOAD](./data-manipulation/CANCEL_LOAD.md)
-- [INSERT](./data-manipulation/INSERT.md)
-- [SHOW LOAD](./data-manipulation/SHOW_LOAD.md)
-- [SHOW TRANSACTION](./data-manipulation/SHOW_TRANSACTION.md)
-- [SPARK LOAD](./data-manipulation/SPARK_LOAD.md)
-- [STREAM LOAD](./data-manipulation/STREAM_LOAD.md)
-
-### Pipe
-
-- [ALTER PIPE](./data-manipulation/ALTER_PIPE.md)
-- [CREATE PIPE](./data-manipulation/CREATE_PIPE.md)
-- [DROP PIPE](./data-manipulation/DROP_PIPE.md)
-- [RETRY FILE](./data-manipulation/RETRY_FILE.md)
-- [SHOW PIPES](./data-manipulation/SHOW_PIPES.md)
-- [SUSPEND or RESUME PIPE](./data-manipulation/SUSPEND_or_RESUME_PIPE.md)
-
-### 导出
-
-- [EXPORT](./data-manipulation/EXPORT.md)
-- [CANCEL EXPORT](./data-manipulation/CANCEL_EXPORT.md)
-- [SHOW EXPORT](./data-manipulation/SHOW_EXPORT.md)
-
-### ETL 任务
-
-- [DROP TASK](./data-manipulation/DROP_TASK.md)
-- [SUBMIT TASK](./data-manipulation/SUBMIT_TASK.md)
-
-## 数据目录 (Catalog)，数据库，资源
-
-### Catalog
-
-- [CREATE EXTERNAL CATALOG](./data-definition/CREATE_EXTERNAL_CATALOG.md)
-- [DROP CATALOG](./data-definition/DROP_CATALOG.md)
-- [SET CATALOG](./data-definition/SET_CATALOG.md)
-- [SHOW CATALOGS](./data-manipulation/SHOW_CATALOGS.md)
-- [SHOW CREATE CATALOG](./data-manipulation/SHOW_CREATE_CATALOG.md)
-
-### 数据库
-
-- [ALTER DATABASE](./data-definition/ALTER_DATABASE.md)
-- [CREATE DATABASE](./data-definition/CREATE_DATABASE.md)
-- [DROP DATABASE](./data-definition/DROP_DATABASE.md)
-- [SHOW CREATE DATABASE](./data-manipulation/SHOW_CREATE_DATABASE.md)
-- [SHOW DATA](./data-manipulation/SHOW_DATA.md)
-- [SHOW DATABASES](./data-manipulation/SHOW_DATABASES.md)
-
-### 资源
-
-- [ALTER RESOURCE](./data-definition/ALTER_RESOURCE.md)
-- [CREATE RESOURCE](./data-definition/CREATE_RESOURCE.md)
-- [DROP RESOURCE](./data-definition/DROP_RESOURCE.md)
-- [SHOW RESOURCES](./data-definition/SHOW_RESOURCES.md)
-
-## 表，分区，分桶，索引
-
-- [ALTER TABLE](./data-definition/ALTER_TABLE.md)
-- [CANCEL ALTER TABLE](./data-definition/CANCEL_ALTER_TABLE.md)
-- [CREATE INDEX](./data-definition/CREATE_INDEX.md)
-- [CREATE TABLE](./data-definition/CREATE_TABLE.md)
-- [CREATE TABLE AS SELECT](./data-definition/CREATE_TABLE_AS_SELECT.md)
-- [CREATE TABLE LIKE](./data-definition/CREATE_TABLE_LIKE.md)
-- [DELETE](./data-manipulation/DELETE.md)
-- [DROP INDEX](./data-definition/DROP_INDEX.md)
-- [DROP TABLE](./data-definition/DROP_TABLE.md)
-- [REFRESH EXTERNAL TABLE](./data-definition/REFRESH_EXTERNAL_TABLE.md)
-- [SELECT](./data-manipulation/SELECT.md)
-- [SHOW ALTER TABLE](./data-manipulation/SHOW_ALTER.md)
-- [SHOW CREATE TABLE](./data-manipulation/SHOW_CREATE_TABLE.md)
-- [SHOW DELETE](./data-manipulation/SHOW_DELETE.md)
-- [SHOW DYNAMIC PARTITION TABLES](./data-manipulation/SHOW_DYNAMIC_PARTITION_TABLES.md)
-- [SHOW PARTITIONS](./data-manipulation/SHOW_PARTITIONS.md)
-- [SHOW FULL COLUMNS](./data-manipulation/SHOW_FULL_COLUMNS.md)
-- [SHOW INDEX](./data-manipulation/SHOW_INDEX.md)
-- [SHOW TABLES](./data-manipulation/SHOW_TABLES.md)
-- [SHOW TABLET](./data-manipulation/SHOW_TABLET.md)
-- [TRUNCATE TABLE](./data-definition/TRUNCATE_TABLE.md)
-- [UPDATE](./data-manipulation/UPDATE.md)
-
-## 视图，物化视图
-
-### 视图
-
-- [ALTER VIEW](./data-definition/ALTER_VIEW.md)
-- [CREATE VIEW](./data-definition/CREATE_VIEW.md)
-- [DROP VIEW](./data-definition/DROP_VIEW.md)
-- [SHOW CREATE VIEW](./data-manipulation/SHOW_CREATE_VIEW.md)
-
-### 物化视图
-
-- [ALTER MATERIALIZED VIEW](./data-definition/ALTER_MATERIALIZED_VIEW.md)
-- [CANCEL REFRESH MATERIALIZED VIEW](./data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW.md)
-- [CREATE MATERIALIZED VIEW](./data-definition/CREATE_MATERIALIZED_VIEW.md)
-- [DROP MATERIALIZED VIEW](./data-definition/DROP_MATERIALIZED_VIEW.md)
-- [REFRESH MATERIALIZED VIEW](./data-manipulation/REFRESH_MATERIALIZED_VIEW.md)
-- [SHOW ALTER MATERIALIZED VIEW](./data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW.md)
-- [SHOW CREATE MATERIALIZED VIEW](./data-manipulation/SHOW_CREATE_MATERIALIZED_VIEW.md)
-- [SHOW MATERIALIZED VIEWS](./data-manipulation/SHOW_MATERIALIZED_VIEW.md)
-
-## 函数，SELECT
-
-- [CREATE FUNCTION](./data-definition/CREATE_FUNCTION.md)
-- [DROP FUNCTION](./data-definition/DROP_FUNCTION.md)
-- [SHOW FUNCTIONS](./data-definition/SHOW_FUNCTIONS.md)
-
-## CBO 统计信息
-
-- [ANALYZE TABLE](./data-definition/ANALYZE_TABLE.md)
-- [CREATE ANALYZE](./data-definition/CREATE_ANALYZE.md)
-- [DROP ANALYZE](./data-definition/DROP_ANALYZE.md)
-- [DROP STATS](./data-definition/DROP_STATS.md)
-- [KILL ANALYZE](./data-definition/KILL_ANALYZE.md)
-- [SHOW ANALYZE JOB](./data-definition/SHOW_ANALYZE_JOB.md)
-- [SHOW ANALYZE STATUS](./data-definition/SHOW_ANALYZE_STATUS.md)
-- [SHOW META](./data-definition/SHOW_META.md)
-
-## 备份与恢复
-
-- [BACKUP](./data-definition/backup_restore/BACKUP.md)
-- [CANCEL BACKUP](./data-definition/backup_restore/CANCEL_BACKUP.md)
-- [CANCEL RESTORE](./data-definition/backup_restore/CANCEL_RESTORE.md)
-- [CREATE REPOSITORY](./data-definition/backup_restore/CREATE_REPOSITORY.md)
-- [DROP REPOSITORY](./data-definition/backup_restore/DROP_REPOSITORY.md)
-- [RECOVER](./data-definition/backup_restore/RECOVER.md)
-- [RESTORE](./data-definition/backup_restore/RESTORE.md)
-- [SHOW BACKUP](./data-manipulation/backup_restore/SHOW_BACKUP.md)
-- [SHOW REPOSITORIES](./data-manipulation/backup_restore/SHOW_REPOSITORIES.md)
-- [SHOW RESTORE](./data-manipulation/backup_restore/SHOW_RESTORE.md)
-- [SHOW SNAPSHOT](./data-manipulation/backup_restore/SHOW_SNAPSHOT.md)
-
-## 工具辅助语句
-
-- [DESC](./Utility/DESCRIBE.md)
-- [USE](./data-definition/USE.md)
diff --git a/docs/zh/sql-reference/sql-statements/auto_increment.md b/docs/zh/sql-reference/sql-statements/auto_increment.md
deleted file mode 100644
index f3be461945e17f..00000000000000
--- a/docs/zh/sql-reference/sql-statements/auto_increment.md
+++ /dev/null
@@ -1,396 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# AUTO_INCREMENT
-
-StarRocks 自 3.0 版本起支持 `AUTO_INCREMENT` 列属性，可以简化数据管理。本文介绍 `AUTO_INCREMENT` 列属性的应用场景、用法和特性。
-
-## 功能介绍
-
-当插入一条新的记录时，StarRocks 会自动为该记录的自增列分配一个表内全局唯一的整数值作为自增 ID，并且后续值会自动增加。自增列可以简化数据管理，同时可以加速一些查询场景。以下是一些自增列的应用场景：
-
-- 主键：自增列可用于生成主键，确保每条记录都有一个唯一的标识符，方便查询和管理数据。
-- 关联表：在多个表之间进行关联时，可以使用自增列作为 Join Key，相比使用如 UUID 等字符串类型的列能够提高查询速度。
-- 高基数列的精确去重计数：将自增列的 ID 值作为字典唯一值列，相比用字符串直接精确去重计数，查询速度能提升数倍甚至十数倍。
-
-您需要在 CREATE TABLE 语句中通过 `AUTO_INCREMENT` 属性指定自增列。自增列的数据类型只支持 BIGINT，从 1 开始增加，自增步长为 1。 并且 StarRocks 支持[隐式分配自增列的值和显式指定自增 ID](#分配自增列的值)。
-
-## 基本用法
-
-### 建表指定自增列
-
-创建表 `test_tbl1`，包含两列，分别为 `id` 和 `number`，如下所示，建表时指定 `number` 列为自增列：
-
-```SQL
-CREATE TABLE test_tbl1
-(
-    id BIGINT NOT NULL, 
-    number BIGINT NOT NULL AUTO_INCREMENT
-) 
-PRIMARY KEY (id) 
-DISTRIBUTED BY HASH(id)
-PROPERTIES("replicated_storage" = "true");
-```
-
-### 分配自增列的值
-
-**隐式分配自增列的值**
-
-导入时，您无需指定自增列的值，StarRocks 会自动为该自增列分配唯一的整数值，并插入到表中。
-
-```SQL
-INSERT INTO test_tbl1 (id) VALUES (1);
-INSERT INTO test_tbl1 (id) VALUES (2);
-INSERT INTO test_tbl1 (id) VALUES (3),(4),(5);
-```
-
-查看表的数据。
-
-```SQL
-mysql > SELECT * FROM test_tbl1 ORDER BY id;
-+------+--------+
-| id   | number |
-+------+--------+
-|    1 |      1 |
-|    2 |      2 |
-|    3 |      3 |
-|    4 |      4 |
-|    5 |      5 |
-+------+--------+
-5 rows in set (0.02 sec)
-```
-
-您也可以指定自增列的值为 `DEFAULT`，StarRocks 会自动为该自增列分配唯一的整数值，并插入到表中。
-
-```SQL
-INSERT INTO test_tbl1 (id, number) VALUES (6, DEFAULT);
-```
-
-查看表的数据。
-
-```SQL
-mysql > SELECT * FROM test_tbl1 ORDER BY id;
-+------+--------+
-| id   | number |
-+------+--------+
-|    1 |      1 |
-|    2 |      2 |
-|    3 |      3 |
-|    4 |      4 |
-|    5 |      5 |
-|    6 |      6 |
-+------+--------+
-6 rows in set (0.02 sec)
-```
-
-在实际使用中，您查看表的数据时可能会返回如下结果。这是因为 StarRocks 无法保证自增列的值按照时间顺序严格递增，但是能保证自增列的值大致上是递增的。更多介绍，请参见[单调性保证](#单调性保证)。
-
-```SQL
-mysql > SELECT * FROM test_tbl1 ORDER BY id;
-+------+--------+
-| id   | number |
-+------+--------+
-|    1 |      1 |
-|    2 | 100001 |
-|    3 | 200001 |
-|    4 | 200002 |
-|    5 | 200003 |
-|    6 | 200004 |
-+------+--------+
-6 rows in set (0.01 sec)
-```
-
-**显式指定自增列的值**
-
-您也可以显式地指定自增列的值，并插入到表中。
-
-```SQL
-INSERT INTO test_tbl1 (id, number) VALUES (7, 100);
-
--- 查看表的数据
-mysql > SELECT * FROM test_tbl1 ORDER BY id;
-+------+--------+
-| id   | number |
-+------+--------+
-|    1 |      1 |
-|    2 | 100001 |
-|    3 | 200001 |
-|    4 | 200002 |
-|    5 | 200003 |
-|    6 | 200004 |
-|    7 |    100 |
-+------+--------+
-7 rows in set (0.01 sec)
-```
-
-并且，后续插入新数据时不会影响 StarRocks 新生成的自增列的值。
-
-```SQL
-INSERT INTO test_tbl1 (id) VALUES (8);
-
--- 查看表的数据
-mysql > SELECT * FROM test_tbl1 ORDER BY id;
-+------+--------+
-| id   | number |
-+------+--------+
-|    1 |      1 |
-|    2 | 100001 |
-|    3 | 200001 |
-|    4 | 200002 |
-|    5 | 200003 |
-|    6 | 200004 |
-|    7 |    100 |
-|    8 |      2 |
-+------+--------+
-8 rows in set (0.01 sec)
-```
-
-**注意事项**
-
-因为同时隐式分配和显式指定自增 ID 可能会破坏自增 ID 的[全局唯一性](#唯一性保证)，建议您不要混用。
-
-## 基本特性
-
-### 唯一性保证
-
-在一般情况下，StarRocks 保证自增 ID 在一张表内是全局唯一的。
-
-但是，如果您混用隐式分配和显式指定自增 ID，则可能会破坏自增 ID 的全局唯一性。因此建议您不要同时隐式分配和显式指定自增 ID。以下是一个简单的示例：
-
-创建表 `test_tbl2`，其中列 `number` 为自增列。
-
-```SQL
-CREATE TABLE test_tbl2
-(
-    id BIGINT NOT NULL,
-    number BIGINT NOT NULL AUTO_INCREMENT
- ) 
-PRIMARY KEY (id) 
-DISTRIBUTED BY HASH(id)
-PROPERTIES("replicated_storage" = "true");
-```
-
-往表 `test_tbl2` 中同时隐式分配和显式指定自增 ID。
-
-```SQL
-INSERT INTO test_tbl2 (id, number) VALUES (1, DEFAULT);
-INSERT INTO test_tbl2 (id, number) VALUES (2, 2);
-INSERT INTO test_tbl2 (id) VALUES (3);
-```
-
-查询表 `test_tbl2` 的数据。
-
-```SQL
-mysql > SELECT * FROM test_tbl2 ORDER BY id;
-+------+--------+
-| id   | number |
-+------+--------+
-|    1 |      1 |
-|    2 |      2 |
-|    3 | 100001 |
-+------+--------+
-3 rows in set (0.08 sec)
-```
-
-### 单调性保证
-
-为了提升分配自增 ID 的性能，BE 会本地缓存部分自增 ID。在这种情况下，StarRocks 无法保证自增 ID 按照时间顺序严格递增，只能保证自增 ID 大致上是递增的。
-> **说明**
->
-> BE 缓存的自增 ID 数量由 FE 动态参数 `auto_increment_cache_size` 决定，默认是 `100000`。您可以使用 `ADMIN SET FRONTEND CONFIG ("auto_increment_cache_size" = "xxx");` 进行修改 。
-假设 StarRocks 集群具有一个 FE 节点和两个 BE 节点。创建表 `test_tbl3` 并且插入五行数据，如下所示：
-
-```SQL
-CREATE TABLE test_tbl3
-(
-    id BIGINT NOT NULL,
-    number BIGINT NOT NULL AUTO_INCREMENT
-) 
-PRIMARY KEY (id)
-DISTRIBUTED BY HASH(id)
-PROPERTIES("replicated_storage" = "true");
-
-INSERT INTO test_tbl3 VALUES (1, DEFAULT);
-INSERT INTO test_tbl3 VALUES (2, DEFAULT);
-INSERT INTO test_tbl3 VALUES (3, DEFAULT);
-INSERT INTO test_tbl3 VALUES (4, DEFAULT);
-INSERT INTO test_tbl3 VALUES (5, DEFAULT);
-```
-
-表 test_tbl3` 中自增 ID 不是单调递增的。这是因为两个 BE 节点分别缓存了 [1, 100000] 和 [100001, 200000] 范围内的自增 ID，使用多个 INSERT 语句导入数据时，会发送给不同的 BE，由不同 BE 分配自增 ID，因此无法保证自增 ID 的严格单调性。
-
-```SQL
-mysql > SELECT * FROM test_tbl3 ORDER BY id;
-+------+--------+
-| id   | number |
-+------+--------+
-|    1 |      1 |
-|    2 | 100001 |
-|    3 | 200001 |
-|    4 |      2 |
-|    5 | 100002 |
-+------+--------+
-5 rows in set (0.07 sec)
-```
-
-## 部分列更新与自增列
-
-本小节介绍具有自增列的表如何实现部分列更新。
-
-> **说明**
->
-> 目前仅主键表支持部分列更新。
-
-### 自增列为主键
-
-如果自增列为主键或主键的一部分，由于部分列更新时您需要指定主键，因此部分列更新的用户行为和没有定义自增列完全一样。
-
-1. 在数据库 `example_db` 中创建表 `test_tbl4`，并且插入一条数据。
-
-    ```SQL
-    -- 建表
-    CREATE TABLE test_tbl4
-    (
-        id BIGINT AUTO_INCREMENT,
-        name BIGINT NOT NULL,
-        job1 BIGINT NOT NULL,
-        job2 BIGINT NOT NULL
-    ) 
-    PRIMARY KEY (id, name)
-    DISTRIBUTED BY HASH(id)
-    PROPERTIES("replicated_storage" = "true");
-
-    -- 准备数据
-    mysql > INSERT INTO test_tbl4 (id, name, job1, job2) VALUES (0, 0, 1, 1);
-    Query OK, 1 row affected (0.04 sec)
-    {'label':'insert_6af28e77-7d2b-11ed-af6e-02424283676b', 'status':'VISIBLE', 'txnId':'152'}
-
-    -- 查询数据
-    mysql > SELECT * FROM test_tbl4 ORDER BY id;
-    +------+------+------+------+
-    | id   | name | job1 | job2 |
-    +------+------+------+------+
-    |    0 |    0 |    1 |    1 |
-    +------+------+------+------+
-    1 row in set (0.01 sec)
-    ```
-
-2. 准备 CSV 文件 **my_data4.csv**，用于更新表 `test_tbl4`。 CSV 文件包括自增列的 ID 值，不包含列 `job1` 的值，并且第一行数据的主键存在表 `test_tbl4` 中，第二行的主键不存在。
-
-    ```Plaintext
-    0,0,99
-    1,1,99
-    ```
-
-3. 通过 [Stream Load](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md) 将 CSV 文件数据更新至表 `test_tbl4`。
-
-    ```Bash
-    curl --location-trusted -u <username>:<password> -H "label:1" \
-        -H "column_separator:," \
-        -H "partial_update:true" \
-        -H "columns:id,name,job2" \
-        -T my_data4.csv -XPUT \
-        http://<fe_host>:<fe_http_port>/api/example_db/test_tbl4/_stream_load
-    ```
-
-4. 查询更新后的表。第一条数据原先已经存在表 `test_tbl4` 中，并且列 `job1` 保持原先的值。第二条数据是新插入的数据，由于列 `job1` 没有定义默认值，因此部分列更新框架会直接将此列的值设置为 `0`。
-
-    ```SQL
-    mysql > SELECT * FROM test_tbl4 ORDER BY id;
-    +------+------+------+------+
-    | id   | name | job1 | job2 |
-    +------+------+------+------+
-    |    0 |    0 |    1 |   99 |
-    |    1 |    1 |    0 |   99 |
-    +------+------+------+------+
-    2 rows in set (0.01 sec)
-    ```
-
-### 自增列不为主键
-
-如果自增列不是主键或者主键的一部分，并且 Stream Load 中未给出自增 ID，则会发生以下情况：
-
-- 如果表中已经存在该行，则 StarRocks 不会更新自增ID。
-- 如果表中不存在该行，则 StarRocks 会自动生成新的自增 ID。
-
-该特性可以构建字典表的值，用于加速字符串的精确去重计数。
-
-1. 在数据库 `example_db` 中创建表 `test_tbl5`，指定 `job1` 为自增列，并且插入一条数据。
-
-    ```SQL
-    -- 建表
-    CREATE TABLE test_tbl5
-    (
-        id BIGINT NOT NULL,
-        name BIGINT NOT NULL,
-        job1 BIGINT NOT NULL AUTO_INCREMENT,
-        job2 BIGINT NOT NULL
-    )
-    PRIMARY KEY (id, name)
-    DISTRIBUTED BY HASH(id)
-    PROPERTIES("replicated_storage" = "true");
-
-    -- 准备数据
-    mysql > INSERT INTO test_tbl5 VALUES (0, 0, -1, -1);
-    Query OK, 1 row affected (0.04 sec)
-    {'label':'insert_458d9487-80f6-11ed-ae56-aa528ccd0ebf', 'status':'VISIBLE', 'txnId':'94'}
-
-    mysql > SELECT * FROM test_tbl5 ORDER BY id;
-    +------+------+------+------+
-    | id   | name | job1 | job2 |
-    +------+------+------+------+
-    |    0 |    0 |   -1 |   -1 |
-    +------+------+------+------+
-    1 row in set (0.01 sec)
-    ```
-
-2. 准备 CSV 文件 **my_data5.csv**，用于更新表 `test_tbl5`。CSV 文件不包含自增列 `job1` 的值，并且第一行数据的主键存在于表中，第二、三行数据的主键不存在。
-
-    ```Plaintext
-    0,0,99
-    1,1,99
-    2,2,99
-    ```
-
-3. 通过 [Stream Load](../../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md) 将 CSV 文件数据导入至表 `test_tbl5`。
-
-    ```Bash
-    curl --location-trusted -u <username>:<password> -H "label:2" \
-        -H "column_separator:," \
-        -H "partial_update:true" \
-        -H "columns: id,name,job2" \
-        -T my_data5.csv -XPUT \
-        http://<fe_host>:<fe_http_port>/api/example_db/test_tbl5/_stream_load
-    ```
-
-4. 查询更新后的表。第一条数据已经存在表 `test_tbl5` 中，自增列 `job1` 保持原先的 ID 值。第二、三条数据是新插入的数据，自增列 `job1` 的 ID 值由 StarRocks 自动生成。
-
-    ```SQL
-    mysql > SELECT * FROM test_tbl5 ORDER BY id;
-    +------+------+--------+------+
-    | id   | name | job1   | job2 |
-    +------+------+--------+------+
-    |    0 |    0 |     -1 |   99 |
-    |    1 |    1 |      1 |   99 |
-    |    2 |    2 | 100001 |   99 |
-    +------+------+--------+------+
-    3 rows in set (0.01 sec)
-    ```
-
-## 使用限制
-
-- 创建具有自增列的表时，必须设置 `'replicated_storage' = 'true'`，以确保所有副本具有相同的自增 ID。
-- 每个表最多只能有一个自增列。
-- 自增列必须是 BIGINT 类型。
-- 自增列必须为 `NOT NULL`，并且不支持指定默认值。
-- 您可以从具有自增列的主键表中删除数据。但是如果自增列不为 Primary Key，则您在删除数据时，需要注意以下两个场景中的限制：
-  - DELETE 操作的同时，还存在一个部分列更新的导入任务，其中只包含 UPSERT 操作。如果 UPSERT 操作和 DELETE 操作命中了同一行数据，并且 UPSERT 操作在 DELETE 操作后执行，则该 UPSERT 操作可能会失效。
-  - 存在一个部分列更新的导入任务，其中包含若干个对同一行数据的 UPSERT、DELETE 操作。如果某个 UPSERT 操作在 DELETE 操作后执行，则该 UPSERT 操作可能会失效。
-- 不支持使用 ALTER TABLE 添加 `AUTO_INCREMENT` 属性。
-- 自 3.1 版本起存算分离模式支持该功能。
-- 不支持设置自增列的起始值和自增步长。
-
-## Keywords
-
-AUTO_INCREMENT, AUTO INCREMENT
diff --git a/docs/zh/sql-reference/sql-statements/backup_restore/BACKUP.md b/docs/zh/sql-reference/sql-statements/backup_restore/BACKUP.md
new file mode 100644
index 00000000000000..c2cf4b29738606
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/backup_restore/BACKUP.md
@@ -0,0 +1,108 @@
+---
+displayed_sidebar: docs
+keywords: ['beifen']
+---
+
+# BACKUP
+
+## 功能
+
+备份指定数据库、表或分区的数据。当前 StarRocks 仅支持备份 OLAP 类型表。更多信息，请见 备份和恢复。
+
+数据备份为异步操作。您可以通过 [SHOW BACKUP](./SHOW_BACKUP.md) 语句查看备份作业状态，或通过 [CANCEL BACKUP](./CANCEL_BACKUP.md) 语句取消备份作业。作业成功后，您可以通过 [SHOW SNAPSHOT](./SHOW_SNAPSHOT.md) 查看特定仓库对应的数据快照信息。
+
+> **注意**
+>
+> - 单一数据库内，仅可同时执行一个备份或恢复作业，否则系统报错。
+> - 目前 StarRocks 不支持在备份数据时使用压缩算法。
+
+## 权限要求
+
+3.0 之前的版本中，拥有 admin_priv 权限才可执行此操作。3.0 及之后的版本中，如需备份指定数据表或整个数据库，需要拥有 System 级的 REPOSITORY 权限，以及对应表或对应数据库下所有表的 EXPORT 权限。例如：
+
+- 授予角色从指定的表中导出数据的权限。
+
+    ```SQL
+    GRANT REPOSITORY ON SYSTEM TO ROLE backup_tbl;
+    GRANT EXPORT ON TABLE <table_name> TO ROLE backup_tbl;
+    ```
+
+- 授予角色从指定数据下所有表中导出数据的权限。
+
+    ```SQL
+    GRANT REPOSITORY ON SYSTEM TO ROLE backup_db;
+    GRANT EXPORT ON ALL TABLES IN DATABASE <database_name> TO ROLE backup_db;
+    ```
+
+- 授予角色从所有数据库的所有表中导出数据的权限。
+
+    ```SQL
+    GRANT REPOSITORY ON SYSTEM TO ROLE backup;
+    GRANT EXPORT ON ALL TABLES IN ALL DATABASES TO ROLE backup;
+    ```
+
+## 语法
+
+```SQL
+BACKUP SNAPSHOT <db_name>.<snapshot_name>
+TO <repository_name>
+[ ON ( <table_name> [ PARTITION ( <partition_name> [, ...] ) ]
+       [, ...] ) ]
+[ PROPERTIES ("key"="value" [, ...] ) ]
+```
+
+## 参数说明
+
+| **参数**        | **说明**                                                     |
+| --------------- | ------------------------------------------------------------ |
+| db_name         | 需要备份的数据所属的数据库名。                                   |
+| snapshot_name   | 指定数据快照名。全局范围内，快照名不可重复。                      |
+| repository_name | 仓库名。您可以通过 [CREATE REPOSITORY](./CREATE_REPOSITORY.md) 创建仓库。 |
+| ON              | 需要备份的表名。如不指定则备份整个数据库。                         |
+| PARTITION       | 需要备份的分区名。如不指定则备份对应表的所有分区。                   |
+| PROPERTIES      | 数据快照属性。现支持以下属性：`type`：备份类型。当前仅支持 `FULL`，即全量备份。默认：`FULL`。`timeout`：任务超时时间。单位：秒。默认：`86400`。 |
+
+## 示例
+
+示例一：全量备份 `example_db` 数据库到仓库 `example_repo` 中。
+
+```SQL
+BACKUP SNAPSHOT example_db.snapshot_label1
+TO example_repo
+PROPERTIES ("type" = "full");
+```
+
+示例二：全量备份 `example_db` 数据库下的表 `example_tbl` 到仓库 `example_repo` 中。
+
+```SQL
+BACKUP SNAPSHOT example_db.snapshot_label2
+TO example_repo
+ON (example_tbl);
+```
+
+示例三：全量备份 `example_db` 数据库中表 `example_tbl` 的 `p1`、`p2` 分区和表 `example_tbl2` 到仓库 `example_repo` 中。
+
+```SQL
+BACKUP SNAPSHOT example_db.snapshot_label3
+TO example_repo
+ON(
+    example_tbl PARTITION (p1, p2),
+    example_tbl2
+);
+```
+
+## 注意事项
+
+- 执行全局、数据库级、表级以及分区级备份恢复需要不同权限。
+- 单一数据库内，仅可同时执行一个备份或恢复作业。否则，StarRocks 返回错误。
+- 因为备份与恢复操作会占用一定系统资源，建议您在集群业务低峰期进行该操作。
+- 目前 StarRocks 不支持在备份数据时使用压缩算法。
+- 因为数据备份是通过快照的形式完成的，所以在当前数据快照生成之后导入的数据不会被备份。因此，在快照生成至恢复（迁移）作业完成这段期间导入的数据，需要重新导入至集群。建议您在迁移完成后，对新旧两个集群并行导入一段时间，完成数据和业务正确性校验后，再将业务迁移到新的集群。
+- 在恢复作业完成前，被恢复表无法被操作。
+- Primary Key 表无法被恢复至 v2.5 之前版本的 StarRocks 集群中。
+- 您无需在恢复作业前在新集群中创建需要被恢复表。恢复作业将自动创建该表。
+- 如果被恢复表与已有表重名，StarRocks 会首先识别已有表的 Schema。如果 Schema 相同，StarRocks 会覆盖写入已有表。如果 Schema 不同，恢复作业失败。您可以通过 `AS` 关键字重新命名被恢复表，或者删除已有表后重新发起恢复作业。
+- 如果恢复作业是一次覆盖操作（指定恢复数据到已经存在的表或分区中），那么从恢复作业的 COMMIT 阶段开始，当前集群上被覆盖的数据有可能不能再被还原。此时如果恢复作业失败或被取消，有可能造成之前的数据损坏且无法访问。这种情况下，只能通过再次执行恢复操作，并等待作业完成。因此，我们建议您，如无必要，不要使用覆盖的方式恢复数据，除非确认当前数据已不再使用。覆盖操作会检查快照和已存在的表或分区的元数据是否相同，包括 Schema 和 Rollup 等信息，如果不同则无法执行恢复操作。
+- 目前 StarRocks 暂不支持备份恢复逻辑视图。
+- 目前 StarRocks 暂不支持备份恢复用户、权限以及资源组配置相关数据。
+- StarRocks 不支持备份恢复表之间的 Colocate Join 关系。
diff --git a/docs/zh/sql-reference/sql-statements/backup_restore/CANCEL_BACKUP.md b/docs/zh/sql-reference/sql-statements/backup_restore/CANCEL_BACKUP.md
new file mode 100644
index 00000000000000..967ffff1b7ce2f
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/backup_restore/CANCEL_BACKUP.md
@@ -0,0 +1,30 @@
+---
+displayed_sidebar: docs
+keywords: ['beifen']
+---
+
+# CANCEL BACKUP
+
+## 功能
+
+取消指定数据库中一个正在进行的备份任务。更多信息，请见 备份和恢复。
+
+## 语法
+
+```SQL
+CANCEL BACKUP FROM <db_name>
+```
+
+## 参数说明
+
+| **参数** | **说明**               |
+| -------- | ---------------------- |
+| db_name  | 备份任务所属数据库名。 |
+
+## 示例
+
+示例一：取消 `example_db` 数据库下的备份任务。
+
+```SQL
+CANCEL BACKUP FROM example_db;
+```
diff --git a/docs/zh/sql-reference/sql-statements/backup_restore/CANCEL_RESTORE.md b/docs/zh/sql-reference/sql-statements/backup_restore/CANCEL_RESTORE.md
new file mode 100644
index 00000000000000..a7bfaed4480d41
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/backup_restore/CANCEL_RESTORE.md
@@ -0,0 +1,34 @@
+---
+displayed_sidebar: docs
+keywords: ['beifen']
+---
+
+# CANCEL RESTORE
+
+## 功能
+
+取消指定数据库中一个正在进行的恢复任务。更多信息，请见 备份和恢复。
+
+> **注意**
+>
+> 如果恢复作业在 COMMIT 阶段被取消，已恢复的数据将会损坏且无法访问。这种情况下，只能通过再次执行恢复操作，并等待作业完成。
+
+## 语法
+
+```SQL
+CANCEL RESTORE FROM <db_name>
+```
+
+## 参数说明
+
+| **参数** | **说明**               |
+| -------- | ---------------------- |
+| db_name  | 恢复任务所属数据库名。 |
+
+## 示例
+
+示例一：取消 `example_db` 数据库下的恢复任务。
+
+```SQL
+CANCEL RESTORE FROM example_db;
+```
diff --git a/docs/zh/sql-reference/sql-statements/backup_restore/CREATE_REPOSITORY.md b/docs/zh/sql-reference/sql-statements/backup_restore/CREATE_REPOSITORY.md
new file mode 100644
index 00000000000000..7e36432a9425ef
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/backup_restore/CREATE_REPOSITORY.md
@@ -0,0 +1,118 @@
+---
+displayed_sidebar: docs
+keywords: ['beifen']
+---
+
+# CREATE REPOSITORY
+
+## 功能
+
+基于远端存储系统创建用于存储数据快照的仓库。仓库用于 备份和恢复 数据库数据。
+
+> **注意**
+>
+> 只有拥有 System 级 REPOSITORY 权限的用户才可以创建仓库。
+
+删除仓库操作请参考 [DROP REPOSITORY](./DROP_REPOSITORY.md) 章节。
+
+## 语法
+
+```SQL
+CREATE [READ ONLY] REPOSITORY <repository_name>
+WITH BROKER
+ON LOCATION "<repository_location>"
+PROPERTIES ("key"="value", ...)
+```
+
+## 参数说明
+
+| **参数**            | **说明**                                                     |
+| ------------------- | ------------------------------------------------------------ |
+| READ ONLY           | 创建只读仓库。请注意只读仓库只可进行恢复操作。当为两个集群创建相同仓库，用以迁移数据时，可以为新集群创建只读仓库，仅赋予其恢复的权限。|
+| repository_name     | 仓库名。命名要求参见[系统限制](../../System_limit.md)。  |
+| repository_location | 远端存储系统路径。                                           |
+| PROPERTIES          | 访问远端存储系统的节点及密钥或用户名及密码。具体使用方式见以下说明。 |
+
+**PROPERTIES**：
+
+StarRocks 支持在 HDFS、AWS S3、Google GCS、阿里云 OSS 以及腾讯云 COS 中创建仓库。
+
+- HDFS：
+  - "username"：用于访问 HDFS 集群中 NameNode 节点的用户名。
+  - "password"：用于访问 HDFS 集群中 NameNode 节点的密码。
+
+- S3：
+  - "aws.s3.use_instance_profile"：是否使用 Instance Profile 或 Assumed Role 作为安全凭证访问 AWS S3。默认值：`false`。
+
+    - 如果您使用 IAM 用户凭证（Access Key 和 Secret Key）访问 AWS S3，则无需指定该参数，并指定 "aws.s3.access_key"、"aws.s3.secret_key" 以及 "aws.s3.endpoint"。
+    - 如果您使用 Instance Profile 访问 AWS S3，则需将该参数设置为 `true`，并指定 "aws.s3.region"。
+    - 如果您使用 Assumed Role 访问 AWS S3，则需将该参数设置为 `true`，并指定 "aws.s3.iam_role_arn" 和 "aws.s3.region"。
+
+  - "aws.s3.access_key"：访问 AWS S3 存储空间的 Access Key。
+  - "aws.s3.secret_key"：访问 AWS S3 存储空间的 Secret Key。
+  - "aws.s3.endpoint"：访问 AWS S3 存储空间的连接地址。
+  - "aws.s3.iam_role_arn"：有访问 AWS S3 存储空间权限 IAM Role 的 ARN。如使用 Instance Profile 或 Assumed Role 作为安全凭证访问 AWS S3，则必须指定该参数。
+  - "aws.s3.region"：需访问的 AWS S3 存储空间的地区，如 `us-west-1`。
+
+> **说明**
+>
+> StarRocks 仅支持通过 S3A 协议在 AWS S3 中创建仓库。因此，当您在 AWS S3 中创建仓库时，必须在 `ON LOCATION` 参数下将 S3 URI 中的 `s3://` 替换为 `s3a://`。
+
+- GCS：
+  - "fs.s3a.access.key"：访问 Google GCS 存储空间的 Access Key。
+  - "fs.s3a.secret.key"：访问 Google GCS 存储空间的 Secret Key。
+  - "fs.s3a.endpoint"：访问 Google GCS 存储空间的连接地址。
+
+> **说明**
+>
+> StarRocks 仅支持通过 S3A 协议在 Google GCS 中创建仓库。 因此，当您在 Google GCS 中创建仓库时，必须在 `ON LOCATION` 参数下将 GCS URI 的前缀替换为 `s3a://`。
+
+- OSS：
+  - "fs.oss.accessKeyId"：访问阿里云 OSS 存储空间的 AccessKey ID，用于标识用户。
+  - "fs.oss.accessKeySecret"：访问阿里云 OSS 存储空间的 AccessKey Secret，是用于加密签名字符串和 OSS 用来验证签名字符串的密钥。
+  - "fs.oss.endpoint"：访问阿里云 OSS 存储空间的连接地址。
+
+- COS：
+  - "fs.cosn.userinfo.secretId"：访问腾讯云 COS 存储空间的 SecretId，用于标识 API 调用者的身份。
+  - "fs.cosn.userinfo.secretKey"：访问腾讯云 COS 存储空间的 SecretKey，是用于加密签名字符串和服务端验证签名字符串的密钥。
+  - "fs.cosn.bucket.endpoint_suffix"：访问腾讯云 COS 存储空间的连接地址。
+
+## 示例
+
+示例一：在 Apache™ Hadoop® 集群中创建名为 `hdfs_repo` 的仓库。
+
+```SQL
+CREATE REPOSITORY hdfs_repo
+WITH BROKER
+ON LOCATION "hdfs://x.x.x.x:yyyy/repo_dir/backup"
+PROPERTIES(
+    "username" = "xxxxxxxx",
+    "password" = "yyyyyyyy"
+);
+```
+
+示例二：在 Amazon S3 存储桶 `bucket_s3` 中创建名为 `s3_repo` 的只读仓库。
+
+```SQL
+CREATE READ ONLY REPOSITORY s3_repo
+WITH BROKER
+ON LOCATION "s3a://bucket_s3/backup"
+PROPERTIES(
+    "aws.s3.access_key" = "XXXXXXXXXXXXXXXXX",
+    "aws.s3.secret_key" = "yyyyyyyyyyyyyyyyy",
+    "aws.s3.endpoint" = "s3.us-east-1.amazonaws.com"
+);
+```
+
+示例三：在 Google GCS 存储桶 `bucket_gcs` 中创建一个名为 `gcs_repo` 的仓库。
+
+```SQL
+CREATE REPOSITORY gcs_repo
+WITH BROKER
+ON LOCATION "s3a://bucket_gcs/backup"
+PROPERTIES(
+    "fs.s3a.access.key" = "xxxxxxxxxxxxxxxxxxxx",
+    "fs.s3a.secret.key" = "yyyyyyyyyyyyyyyyyyyy",
+    "fs.s3a.endpoint" = "storage.googleapis.com"
+);
+```
diff --git a/docs/zh/sql-reference/sql-statements/backup_restore/DROP_REPOSITORY.md b/docs/zh/sql-reference/sql-statements/backup_restore/DROP_REPOSITORY.md
new file mode 100644
index 00000000000000..cf8b9a4aa35923
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/backup_restore/DROP_REPOSITORY.md
@@ -0,0 +1,35 @@
+---
+displayed_sidebar: docs
+keywords: ['beifen']
+---
+
+# DROP REPOSITORY
+
+## 功能
+
+删除一个仓库。仓库用于 备份和恢复 数据库数据。
+
+> **注意**
+>
+> - 只有拥有 System 级 REPOSITORY 权限的用户才可以删除仓库。
+> - 该操作仅删除仓库在 StarRocks 中的映射，不会删除实际的仓库数据。如需删除备份数据，您需要手动删除备份在远端存储系统的快照路径。删除后，您可以再次通过指定相同的远端存储系统路径映射到该仓库。
+
+## 语法
+
+```SQL
+DROP REPOSITORY <repository_name>
+```
+
+## 参数说明
+
+| **参数**        | **说明**         |
+| --------------- | ---------------- |
+| repository_name | 要删除的仓库名。 |
+
+## 示例
+
+示例一：删除名为 `oss_repo` 的仓库。
+
+```SQL
+DROP REPOSITORY `oss_repo`;
+```
diff --git a/docs/zh/sql-reference/sql-statements/backup_restore/RECOVER.md b/docs/zh/sql-reference/sql-statements/backup_restore/RECOVER.md
new file mode 100644
index 00000000000000..8fb572c2aa7742
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/backup_restore/RECOVER.md
@@ -0,0 +1,62 @@
+---
+displayed_sidebar: docs
+keywords: ['beifen']
+---
+
+# RECOVER
+
+## 功能
+
+恢复之前通过 DROP 操作删除的 database、table 或者 partition。DROP 操作后只有在指定的时间内才能通过 RECOVER 恢复数据，超过这个时间无法恢复。该时间由 FE 动态参数 `catalog_trash_expire_second` 控制，默认 1 天。
+
+通过 [TRUNCATE TABLE](../table_bucket_part_index/TRUNCATE_TABLE.md) 命令删除的数据无法恢复。
+
+> **注意**
+>
+> 只有拥有 default_catalog 的 CREATE DATABASE 权限才可以恢复数据库；同时需要拥有对应数据库的 CREATE TABLE 和对应表的 DROP 权限。
+
+## 语法
+
+### 恢复 database
+
+```sql
+RECOVER DATABASE <db_name>
+```
+
+### 恢复 table
+
+```sql
+RECOVER TABLE [db_name.]table_name;
+```
+
+### 恢复 partition
+
+```sql
+RECOVER PARTITION partition_name FROM [db_name.]table_name;
+```
+
+说明：
+
+1. 该操作仅能恢复之前一段时间内删除的元信息，默认为 1 天。（可通过 `fe.conf` 中 `catalog_trash_expire_second` 参数配置。）
+
+2. 如果删除元信息后新建了同名同类型的元信息，则之前删除的元信息不能被恢复。
+
+## 示例
+
+1. 恢复名为 `example_db` 的 database。
+
+    ```sql
+    RECOVER DATABASE example_db;
+    ```
+
+2. 恢复名为 `example_tbl` 的 table。
+
+    ```sql
+    RECOVER TABLE example_db.example_tbl;
+    ```
+
+3. 恢复表 `example_tbl` 中名为 `p1` 的 partition。
+
+    ```sql
+    RECOVER PARTITION p1 FROM example_tbl;
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/backup_restore/RESTORE.md b/docs/zh/sql-reference/sql-statements/backup_restore/RESTORE.md
new file mode 100644
index 00000000000000..733e2d38e8cfd1
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/backup_restore/RESTORE.md
@@ -0,0 +1,108 @@
+---
+displayed_sidebar: docs
+keywords: ['beifen']
+---
+
+# RESTORE
+
+## 功能
+
+恢复指定数据库、表或分区的数据。当前 StarRocks 仅支持恢复 OLAP 类型表。更多信息，请见 备份和恢复。
+
+数据恢复为异步操作。您可以通过 [SHOW RESTORE](./SHOW_RESTORE.md) 语句查看恢复作业状态，或通过 [CANCEL RESTORE](./CANCEL_RESTORE.md) 语句取消恢复作业。
+
+> **注意**
+>
+> 单一数据库内，仅可同时执行一个备份或恢复作业，否则系统报错。
+
+## 权限要求
+
+3.0 之前的版本中，拥有 admin_priv 权限才可执行此操作。3.0 及之后的版本中，如需恢复整个数据库，需要拥有 System 级的 REPOSITORY 权限，以及创建数据库、创建表、导入数据的权限；如需恢复特定表，则需要拥有 System 级的 REPOSITORY 权限，以及对特定表的导入权限（INSERT）。例如：
+
+- 授予角色恢复指定表中数据的权限。
+
+    ```SQL
+    GRANT REPOSITORY ON SYSTEM TO ROLE recover_tbl;
+    GRANT INSERT ON TABLE <table_name> TO ROLE recover_tbl;
+    ```
+
+- 授予角色恢复指定数据库下所有数据的权限。
+
+    ```SQL
+    GRANT REPOSITORY ON SYSTEM TO ROLE recover_db;
+    GRANT INSERT ON ALL TABLES ALL DATABASES TO ROLE recover_db;
+    ```
+
+- 授予角色恢复 default_catalog 下全部数据库中数据的权限。
+
+    ```SQL
+    GRANT REPOSITORY ON SYSTEM TO ROLE recover_db;
+    GRANT CREATE DATABASE ON CATALOG default_catalog TO ROLE recover_db;
+    ```
+
+## 语法
+
+```SQL
+RESTORE SNAPSHOT <db_name>.<snapshot_name>
+FROM <repository_name>
+[ ON ( <table_name> [ PARTITION ( <partition_name> [, ...] ) ]
+    [ AS <table_alias>] [, ...] ) ]
+PROPERTIES ("key"="value", ...)
+```
+
+## 参数说明
+
+| **参数**        | **说明**                                                     |
+| --------------- | ------------------------------------------------------------ |
+| db_name         | 恢复数据至该数据库。                                           |
+| snapshot_name   | 数据快照名。                                                 |
+| repository_name | 仓库名。                                                    |
+| ON              | 需要恢复的表名。如不指定则恢复整个数据库。                   |
+| PARTITION       | 需要恢复的分区名。如不指定则恢复对应表的所有分区。您可以通过 [SHOW PARTITIONS](../table_bucket_part_index/SHOW_PARTITIONS.md) 语句查看分区名。 |
+| PROPERTIES      | 恢复操作属性。现支持以下属性：<ul><li>`backup_timestamp`：备份时间戳，**必填**。您可以通过 [SHOW SNAPSHOT](./SHOW_SNAPSHOT.md) 查看备份时间戳。</li><li>`replication_num`：指定恢复的表或分区的副本数。默认：`3`。</li><li>`meta_version`：该参数作为临时方案，仅用于恢复旧版本 StarRocks 备份的数据。最新版本的备份数据中已经包含 `meta version`，无需再指定。</li><li>`timeout`：任务超时时间。单位：秒。默认：`86400`。</li></ul> |
+
+## 示例
+
+示例一：从 `example_repo` 仓库中恢复备份 `snapshot_label1` 中的表 `backup_tbl` 至数据库 `example_db`，备份时间戳为 `2018-05-04-16-45-08`。恢复为一个副本。
+
+```SQL
+RESTORE SNAPSHOT example_db.snapshot_label1
+FROM example_repo
+ON ( backup_tbl )
+PROPERTIES
+(
+    "backup_timestamp"="2018-05-04-16-45-08",
+    "replication_num" = "1"
+);
+```
+
+示例二：从 `example_repo` 仓库中恢复备份 `snapshot_label2` 中的表 `backup_tbl` 的分区 `p1` 及 `p2`，以及表 `backup_tbl2` 到数据库 `example_db`，并重命名为 `new_tbl`，备份时间戳为 `2018-05-04-17-11-01`。默认恢复三个副本。
+
+```SQL
+RESTORE SNAPSHOT example_db.snapshot_label2
+FROM example_repo
+ON(
+    backup_tbl PARTITION (p1, p2),
+    backup_tbl2 AS new_tbl
+)
+PROPERTIES
+(
+    "backup_timestamp"="2018-05-04-17-11-01"
+);
+```
+
+## 注意事项
+
+- 执行全局、数据库级、表级以及分区级备份恢复需要不同权限。
+- 单一数据库内，仅可同时执行一个备份或恢复作业。否则，StarRocks 返回错误。
+- 因为备份与恢复操作会占用一定系统资源，建议您在集群业务低峰期进行该操作。
+- 目前 StarRocks 不支持在备份数据时使用压缩算法。
+- 因为数据备份是通过快照的形式完成的，所以在当前数据快照生成之后导入的数据不会被备份。因此，在快照生成至恢复（迁移）作业完成这段期间导入的数据，需要重新导入至集群。建议您在迁移完成后，对新旧两个集群并行导入一段时间，完成数据和业务正确性校验后，再将业务迁移到新的集群。
+- 在恢复作业完成前，被恢复表无法被操作。
+- Primary Key 表无法被恢复至 v2.5 之前版本的 StarRocks 集群中。
+- 您无需在恢复作业前在新集群中创建需要被恢复表。恢复作业将自动创建该表。
+- 如果被恢复表与已有表重名，StarRocks 会首先识别已有表的 Schema。如果 Schema 相同，StarRocks 会覆盖写入已有表。如果 Schema 不同，恢复作业失败。您可以通过 `AS` 关键字重新命名被恢复表，或者删除已有表后重新发起恢复作业。
+- 如果恢复作业是一次覆盖操作（指定恢复数据到已经存在的表或分区中），那么从恢复作业的 COMMIT 阶段开始，当前集群上被覆盖的数据有可能不能再被还原。此时如果恢复作业失败或被取消，有可能造成之前的数据损坏且无法访问。这种情况下，只能通过再次执行恢复操作，并等待作业完成。因此，我们建议您，如无必要，不要使用覆盖的方式恢复数据，除非确认当前数据已不再使用。覆盖操作会检查快照和已存在的表或分区的元数据是否相同，包括 Schema 和 Rollup 等信息，如果不同则无法执行恢复操作。
+- 目前 StarRocks 暂不支持备份恢复逻辑视图。
+- 目前 StarRocks 暂不支持备份恢复用户、权限以及资源组配置相关数据。
+- StarRocks 不支持备份恢复表之间的 Colocate Join 关系。
diff --git a/docs/zh/sql-reference/sql-statements/backup_restore/SHOW_BACKUP.md b/docs/zh/sql-reference/sql-statements/backup_restore/SHOW_BACKUP.md
new file mode 100644
index 00000000000000..d104635ec14ad4
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/backup_restore/SHOW_BACKUP.md
@@ -0,0 +1,52 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW BACKUP
+
+## 功能
+
+查看指定数据库中的备份任务。更多信息，请见 备份和恢复。
+
+> **说明**
+>
+> StarRocks 中仅保存最近一次备份任务信息。
+
+## 语法
+
+```SQL
+SHOW BACKUP [FROM <db_name>]
+```
+
+## 参数说明
+
+| **参数** | **说明**               |
+| -------- | ---------------------- |
+| db_name  | 备份任务所属数据库名。 |
+
+## 返回
+
+| **返回**             | **说明**                                                     |
+| -------------------- | ------------------------------------------------------------ |
+| JobId                | 本次备份作业的 ID。                                          |
+| SnapshotName         | 用户指定的本次备份作业的名称。                               |
+| DbName               | 备份作业对应的数据库。                                       |
+| State                | 备份作业当前所在阶段：<ul><li>PENDING：作业初始状态。</li><li>SNAPSHOTING：正在进行快照操作。</li><li>UPLOAD_SNAPSHOT：快照结束，准备上传。</li><li>UPLOADING：正在上传快照。</li><li>SAVE_META：正在本地生成元数据文件。</li><li>UPLOAD_INFO：上传元数据文件和本次备份作业的信息。</li><li>FINISHED：备份完成。</li><li>CANCELLED：备份失败或被取消。</li></ul> |
+| BackupObjs           | 本次备份涉及的对象。                                         |
+| CreateTime           | 作业创建时间。                                               |
+| SnapshotFinishedTime | 快照完成时间。                                               |
+| UploadFinishedTime   | 快照上传完成时间。                                           |
+| FinishedTime         | 本次作业完成时间。                                           |
+| UnfinishedTasks      | 在 SNAPSHOTTING，UPLOADING 等阶段，会有多个子任务在同时进行，这里展示的当前段，未完成子任务的 Task ID。 |
+| Progress             | 快照上传任务进展。|
+| TaskErrMsg           | 如果有子任务执行出错，这里会显示对应子任务的错误信息。       |
+| Status               | 用于记录在整个作业过程中，可能出现的一些状态信息。           |
+| Timeout              | 作业的超时时间，单位为秒。                                   |
+
+## 示例
+
+示例一：查看数据库 `example_db` 下最后一次备份任务。
+
+```SQL
+SHOW BACKUP FROM example_db;
+```
diff --git a/docs/zh/sql-reference/sql-statements/backup_restore/SHOW_REPOSITORIES.md b/docs/zh/sql-reference/sql-statements/backup_restore/SHOW_REPOSITORIES.md
new file mode 100644
index 00000000000000..89b4d18f0002fc
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/backup_restore/SHOW_REPOSITORIES.md
@@ -0,0 +1,35 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW REPOSITORIES
+
+## 功能
+
+查看当前已创建的仓库。
+
+## 语法
+
+```SQL
+SHOW REPOSITORIES
+```
+
+## 返回
+
+| **返回**   | **说明**                |
+| ---------- | ----------------------- |
+| RepoId     | 仓库 ID。               |
+| RepoName   | 仓库名。                |
+| CreateTime | 仓库创建时间。          |
+| IsReadOnly | 是否为只读仓库。        |
+| Location   | 远端存储系统路径。      |
+| Broker     | 用于创建仓库的 Broker。 |
+| ErrMsg     | 仓库连接错误信息。      |
+
+## 示例
+
+示例一：查看已创建的仓库。
+
+```SQL
+SHOW REPOSITORIES;
+```
diff --git a/docs/zh/sql-reference/sql-statements/backup_restore/SHOW_RESTORE.md b/docs/zh/sql-reference/sql-statements/backup_restore/SHOW_RESTORE.md
new file mode 100644
index 00000000000000..28f7d943d184a9
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/backup_restore/SHOW_RESTORE.md
@@ -0,0 +1,56 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW RESTORE
+
+## 功能
+
+查看指定数据库中的恢复任务。更多信息，请见 备份和恢复。
+
+> **说明**
+>
+> StarRocks 中仅保存最近一次恢复任务信息。
+
+## 语法
+
+```SQL
+SHOW RESTORE [FROM <db_name>]
+```
+
+## 参数说明
+
+| **参数** | **说明**               |
+| -------- | ---------------------- |
+| db_name  | 恢复任务所属数据库名。 |
+
+## 返回
+
+| **返回**             | **说明**                                                     |
+| -------------------- | ------------------------------------------------------------ |
+| JobId                | 本次恢复作业的 ID。                                          |
+| Label                | 要恢复的备份名称。                                           |
+| Timestamp            | 备份时间戳。                                                 |
+| DbName               | 恢复作业对应的数据库。                                       |
+| State                | 恢复作业当前所在阶段：<ul><li>PENDING：作业初始状态。</li><li>SNAPSHOTING：正在进行本地新建表的快照操作。</li><li>DOWNLOAD：正在发送下载快照任务。</li><li>DOWNLOADING：快照正在下载。</li><li>COMMIT：准备生效已下载的快照。</li><li>COMMITTING：正在生效已下载的快照。</li><li>FINISHED：恢复完成。</li><li>CANCELLED：恢复失败或被取消。</li></ul> |
+| AllowLoad            | 恢复期间是否允许导入。                                       |
+| ReplicationNum       | 恢复指定的副本数。                                           |
+| RestoreObjs          | 被恢复的对象（表和分区）。                                   |
+| CreateTime           | 作业创建时间。                                               |
+| MetaPreparedTime     | 本地元数据生成完成时间。                                     |
+| SnapshotFinishedTime | 快照完成时间。                                               |
+| DownloadFinishedTime | 远端快照下载完成时间。                                       |
+| FinishedTime         | 本次作业完成时间。                                           |
+| UnfinishedTasks      | 在 SNAPSHOTTING、DOWNLOADING、COMMITTING 等阶段，会有多个子任务在同时进行，这里展示的当前段，未完成子任务的 Task ID。 |
+| Progress             | 快照下载任务进展。                                          |
+| TaskErrMsg           | 如果有子任务执行出错，这里会显示对应子任务的错误信息。       |
+| Status               | 用于记录在整个作业过程中，可能出现的一些状态信息。           |
+| Timeout              | 作业的超时时间，单位为秒。                                   |
+
+## 示例
+
+示例一：查看数据库 `example_db` 下最后一次恢复任务。
+
+```SQL
+SHOW RESTORE FROM example_db;
+```
diff --git a/docs/zh/sql-reference/sql-statements/backup_restore/SHOW_SNAPSHOT.md b/docs/zh/sql-reference/sql-statements/backup_restore/SHOW_SNAPSHOT.md
new file mode 100644
index 00000000000000..8b3f5a7de5c49d
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/backup_restore/SHOW_SNAPSHOT.md
@@ -0,0 +1,56 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW SNAPSHOT
+
+## 功能
+
+查看指定仓库中的备份。更多信息，请见 [备份和恢复](../../../administration/management/Backup_and_restore.md)。
+
+## 语法
+
+```SQL
+SHOW SNAPSHOT ON <repo_name>
+[WHERE SNAPSHOT = <snapshot_name> [AND TIMESTAMP = <backup_timestamp>]]
+```
+
+## 参数说明
+
+| **参数**         | **说明**         |
+| ---------------- | ---------------- |
+| repo_name        | 备份所属仓库名。 |
+| snapshot_nam     | 备份名。         |
+| backup_timestamp | 备份时间戳。     |
+
+## 返回
+
+| **返回**  | **说明**                                    |
+| --------- | ------------------------------------------- |
+| Snapshot  | 备份名。                                    |
+| Timestamp | 备份时间戳。                                |
+| Status    | 如果备份正常，则显示 OK，否则显示错误信息。 |
+| Database  | 备份所属数据库名。                          |
+| Details   | 备份的数据目录及文件结构。JSON 格式。       |
+
+## 示例
+
+示例一：查看仓库 `example_repo` 中已有的备份。
+
+```SQL
+SHOW SNAPSHOT ON example_repo;
+```
+
+示例二：查看仓库 `example_repo` 中名为 `backup1` 的备份。
+
+```SQL
+SHOW SNAPSHOT ON example_repo
+WHERE SNAPSHOT = "backup1";
+```
+
+示例三：查看仓库 `example_repo` 中名为 `backup1` 、时间戳为 `2018-05-05-15-34-26` 的备份。
+
+```SQL
+SHOW SNAPSHOT ON example_repo 
+WHERE SNAPSHOT = "backup1" AND TIMESTAMP = "2018-05-05-15-34-26";
+```
diff --git a/docs/zh/sql-reference/sql-statements/backup_restore/_category_.yml b/docs/zh/sql-reference/sql-statements/backup_restore/_category_.yml
new file mode 100644
index 00000000000000..d2330d87d1d505
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/backup_restore/_category_.yml
@@ -0,0 +1,6 @@
+position: 130 # float position is supported
+label: '备份与恢复'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/backup_restore/backup_restore.mdx b/docs/zh/sql-reference/sql-statements/backup_restore/backup_restore.mdx
new file mode 100644
index 00000000000000..45c23861b46352
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/backup_restore/backup_restore.mdx
@@ -0,0 +1,9 @@
+---
+displayed_sidebar: docs
+keywords: ['beifen']
+---
+
+# 备份与恢复
+
+import DocCardList from '@theme/DocCardList';
+
diff --git a/docs/zh/sql-reference/sql-statements/cbo_stats/ANALYZE_TABLE.md b/docs/zh/sql-reference/sql-statements/cbo_stats/ANALYZE_TABLE.md
new file mode 100644
index 00000000000000..665ecf8632bc26
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cbo_stats/ANALYZE_TABLE.md
@@ -0,0 +1,121 @@
+---
+displayed_sidebar: docs
+---
+
+# ANALYZE TABLE
+
+## 功能
+
+创建手动采集任务，进行 CBO 统计信息采集。**手动采集默认为同步操作。您也可以将手动任务设置为异步，执行命令后，会立即返回命令的状态，但是统计信息采集任务会在后台运行，运行的状态可以使用 SHOW ANALYZE STATUS 查看。手动任务创建后仅会执行一次，无需手动删除。**
+
+### 手动采集基础统计信息
+
+关于基础统计信息，请参见[CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md#统计信息数据类型)。
+
+#### 语法
+
+```SQL
+ANALYZE [FULL|SAMPLE] TABLE tbl_name (col_name [,col_name])
+[WITH SYNC | ASYNC MODE]
+PROPERTIES (property [,property])
+```
+
+#### 参数说明
+
+- 采集类型
+  - FULL：全量采集。
+  - SAMPLE：抽样采集。
+  - 如果不指定采集类型，默认为全量采集。
+
+- `WITH SYNC | ASYNC MODE`: 如果不指定，默认为同步操作。
+
+- `col_name`: 要采集统计信息的列，多列使用逗号分隔。如果不指定，表示采集整张表的信息。
+
+- PROPERTIES: 采集任务的自定义参数。如果不配置，则采用`fe.conf`中的默认配置。任务实际执行中使用的 PROPERTIES，可以通过 SHOW ANALYZE STATUS 返回结果中的 `Properties` 列查看。
+
+| **PROPERTIES**                | **类型** | **默认值** | **说明**                                                     |
+| ----------------------------- | -------- | ---------- | ------------------------------------------------------------ |
+| statistic_sample_collect_rows | INT      | 200000     | 最小采样行数。如果参数取值超过了实际的表行数，默认进行全量采集。 |
+
+#### 示例
+
+示例1：手动全量采集
+
+```SQL
+-- 手动全量采集指定表的统计信息，使用默认配置。
+ANALYZE TABLE tbl_name;
+
+-- 手动全量采集指定表的统计信息，使用默认配置。
+ANALYZE FULL TABLE tbl_name;
+
+-- 手动全量采集指定表指定列的统计信息，使用默认配置。
+ANALYZE TABLE tbl_name(c1, c2, c3);
+```
+
+示例2：手动抽样采集
+
+```SQL
+-- 手动抽样采集指定表的统计信息，使用默认配置。
+ANALYZE SAMPLE TABLE tbl_name;
+
+-- 手动抽样采集指定表指定列的统计信息，设置抽样行数。
+ANALYZE SAMPLE TABLE tbl_name (v1, v2, v3) PROPERTIES(
+    "statistic_sample_collect_rows" = "1000000"
+);
+```
+
+### 手动采集直方图统计信息
+
+关于直方图的说明，请参见[CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md#统计信息数据类型)。
+
+#### 语法
+
+```SQL
+ANALYZE TABLE tbl_name UPDATE HISTOGRAM ON col_name [, col_name]
+[WITH SYNC | ASYNC MODE]
+[WITH N BUCKETS]
+PROPERTIES (property [,property]);
+```
+
+#### 参数说明
+
+- `col_name`: 要采集统计信息的列，多列使用逗号分隔。该参数必填。
+
+- `WITH SYNC | ASYNC MODE`: 如果不指定，默认为同步采集。
+
+- `WITH ``N`` BUCKETS`: `N`为直方图的分桶数。如果不指定，则使用`fe.conf`中的默认值。
+
+- PROPERTIES: 采集任务的自定义参数。如果不指定，则使用`fe.conf`中的默认配置。
+
+| **PROPERTIES**                 | **类型** | **默认值** | **说明**                                                     |
+| ------------------------------ | -------- | ---------- | ------------------------------------------------------------ |
+| statistic_sample_collect_rows  | INT      | 200000     | 最小采样行数。如果参数取值超过了实际的表行数，默认进行全量采集。 |
+| histogram_mcv_size             | INT      | 100        | 直方图 most common value (MCV) 的数量。                      |
+| histogram_sample_ratio         | FLOAT    | 0.1        | 直方图采样比例。                                             |
+| histogram_max_sample_row_count | LONG     | 10000000   | 直方图最大采样行数。                                         |
+
+直方图的采样行数由多个参数共同控制，采样行数取 `statistic_sample_collect_rows` 和表总行数 `histogram_sample_ratio` 两者中的最大值。最多不超过 `histogram_max_sample_row_count` 指定的行数。如果超过，则按照该参数定义的上限行数进行采集。
+
+直方图任务实际执行中使用的**PROPERTIES**，可以通过 SHOW ANALYZE STATUS 返回结果中的**PROPERTIES**列查看。
+
+#### 示例
+
+```SQL
+-- 手动采集v1列的直方图信息，使用默认配置。
+ANALYZE TABLE tbl_name UPDATE HISTOGRAM ON v1;
+
+-- 手动采集 v1 列的直方图信息，指定 32 个分桶，MCV 指定为 32 个，采样比例为 50%。
+ANALYZE TABLE tbl_name UPDATE HISTOGRAM ON v1,v2 WITH 32 BUCKETS 
+PROPERTIES(
+   "histogram_mcv_size" = "32",
+   "histogram_sample_ratio" = "0.5"
+);
+```
+
+## 相关文档
+
+[SHOW ANALYZE STATUS](SHOW_ANALYZE_STATUS.md)：查看当前所有**手动采集任务**的状态。
+
+[KILL ANALYZE](KILL_ANALYZE.md)：取消**正在运行中（Running）**的统计信息收集任务。
+
+想了解更多 CBO 统计信息采集的内容，参见[CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
diff --git a/docs/zh/sql-reference/sql-statements/cbo_stats/CREATE_ANALYZE.md b/docs/zh/sql-reference/sql-statements/cbo_stats/CREATE_ANALYZE.md
new file mode 100644
index 00000000000000..fbde9168c43ed7
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cbo_stats/CREATE_ANALYZE.md
@@ -0,0 +1,84 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE ANALYZE
+
+## 功能
+
+创建自定义自动采集任务，进行 CBO 统计信息采集。
+
+默认情况下，StarRocks 会周期性自动采集表的全量统计信息。默认检查更新时间为 5 分钟一次，如果发现有数据更新，会自动触发采集。如果您不希望使用自动全量采集，可以设置 FE 配置项 `enable_collect_full_statistic` 为 `false`，系统会停止自动全量采集，根据您创建的自定义任务进行定制化采集。
+
+创建自定义自动采集任务之前，需要先关闭自动全量采集 `enable_collect_full_statistic=false`，否则自定义采集任务不生效。
+
+## 语法
+
+```SQL
+-- 定期采集所有数据库的统计信息。
+CREATE ANALYZE [FULL|SAMPLE] ALL PROPERTIES (property [,property])
+
+-- 定期采集指定数据库下所有表的统计信息。
+CREATE ANALYZE [FULL|SAMPLE] DATABASE db_name PROPERTIES (property [,property])
+
+-- 定期采集指定表、列的统计信息。
+CREATE ANALYZE [FULL|SAMPLE] TABLE tbl_name (col_name [,col_name]) PROPERTIES (property [,property])
+```
+
+## 参数说明
+
+- 采集类型
+  - FULL：全量采集。
+  - SAMPLE：抽样采集。
+  - 如果不指定采集类型，默认为抽样采集。
+
+- `col_name`: 要采集统计信息的列，多列使用逗号 (,)分隔。如果不指定，表示采集整张表的信息。
+
+- PROPERTIES: 采集任务的自定义参数。如果不配置，则采用 `fe.conf` 中的默认配置。任务实际执行中使用的 PROPERTIES，可以通过 [SHOW ANALYZE JOB](SHOW_ANALYZE_JOB.md) 中的 `Properties` 列查看。
+
+| **PROPERTIES**                        | **类型** | **默认值** | **说明**                                                     |
+| ------------------------------------- | -------- | ---------- | ------------------------------------------------------------ |
+| statistic_auto_collect_ratio          | FLOAT    | 0.8        | 自动统计信息的健康度阈值。如果统计信息的健康度小于该阈值，则触发自动采集。 |
+| statistics_max_full_collect_data_size | INT      | 100        | 自动统计信息采集的最大分区的大小。单位: GB。如果某个分区超过该值，则放弃全量统计信息采集，转为对该表进行抽样统计信息采集。 |
+| statistic_sample_collect_rows         | INT      | 200000     | 抽样采集的采样行数。如果该参数取值超过了实际的表行数，则进行全量采集。 |
+
+## 示例
+
+示例 1：自动全量采集
+
+```SQL
+-- 定期全量采集所有数据库的统计信息。
+CREATE ANALYZE ALL;
+
+-- 定期全量采集指定数据库下所有表的统计信息。
+CREATE ANALYZE DATABASE db_name;
+
+-- 定期全量采集指定数据库下所有表的统计信息。
+CREATE ANALYZE FULL DATABASE db_name;
+
+-- 定期全量采集指定表、列的统计信息。
+CREATE ANALYZE TABLE tbl_name(c1, c2, c3); 
+```
+
+示例 2：自动抽样采集
+
+```SQL
+-- 定期抽样采集指定数据库下所有表的统计信息，使用默认配置。
+CREATE ANALYZE SAMPLE DATABASE db_name;
+
+-- 定期抽样采集指定表、列的统计信息，设置采样行数和健康度阈值。
+CREATE ANALYZE SAMPLE TABLE tbl_name(c1, c2, c3) PROPERTIES(
+   "statistic_auto_collect_ratio" = "0.5",
+   "statistic_sample_collect_rows" = "1000000"
+);
+```
+
+## 相关文档
+
+[SHOW ANALYZE JOB](SHOW_ANALYZE_JOB.md)：查看创建的自定义自动采集任务。
+
+[DROP ANALYZE](DROP_ANALYZE.md)：删除自动采集任务。
+
+[KILL ANALYZE](KILL_ANALYZE.md)：取消正在运行中（Running）的统计信息收集任务。
+
+想了解更多 CBO 统计信息采集的内容，参见 [CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
diff --git a/docs/zh/sql-reference/sql-statements/cbo_stats/DROP_ANALYZE.md b/docs/zh/sql-reference/sql-statements/cbo_stats/DROP_ANALYZE.md
new file mode 100644
index 00000000000000..7b2b9e3134baa7
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cbo_stats/DROP_ANALYZE.md
@@ -0,0 +1,35 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP ANALYZE
+
+## 功能
+
+删除自定义自动采集任务。自定义自动采集任务用于采集 CBO 统计信息。
+
+默认情况下，StarRocks 会周期性自动采集表的全量统计信息。默认检查更新时间为 5 分钟一次，如果发现有数据更新，会自动触发采集。如果您不希望使用自动全量采集，可以设置 FE 配置项 `enable_collect_full_statistic` 为 `false`，系统会停止自动全量采集，根据您创建的自定义任务进行定制化采集。
+
+## 语法
+
+```SQL
+DROP ANALYZE <ID>
+```
+
+可以通过 SHOW ANALYZE JOB 查看任务的 ID。
+
+## 示例
+
+```SQL
+DROP ANALYZE 266030;
+```
+
+## 相关文档
+
+[CREATE ANALYZE](CREATE_ANALYZE.md)：创建自定义自动采集任务。
+
+[SHOW ANALYZE JOB](SHOW_ANALYZE_JOB.md)：查看自定义自动采集任务。
+
+[KILL ANALYZE](KILL_ANALYZE.md)：取消正在运行中（Running）的统计信息收集任务。
+
+想了解更多 CBO 统计信息采集的内容，参见[CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
diff --git a/docs/zh/sql-reference/sql-statements/cbo_stats/DROP_STATS.md b/docs/zh/sql-reference/sql-statements/cbo_stats/DROP_STATS.md
new file mode 100644
index 00000000000000..f2a9ee730e0864
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cbo_stats/DROP_STATS.md
@@ -0,0 +1,33 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP STATS
+
+## 功能
+
+删除 CBO 统计信息。
+
+StarRocks 支持手动删除统计信息。手动删除统计信息时，会删除统计信息数据和统计信息元数据，并且会删除过期内存中的统计信息缓存。需要注意的是，如果当前存在自动采集任务，可能会重新采集之前已删除的统计信息。您可以使用`SHOW ANALYZE STATUS`查看统计信息采集历史记录。该语句从 2.4 版本开始支持。
+
+您可以使用 DROP STATS 删除基础统计信息，使用 ANALYZE TABLE DROP HISTOGRAM 删除直方图统计信息。
+
+### 删除基础统计信息
+
+#### 语法
+
+```SQL
+DROP STATS <tbl_name>
+```
+
+### 删除直方图统计信息
+
+#### 语法
+
+```SQL
+ANALYZE TABLE tbl_name DROP HISTOGRAM ON <col_name> [, <col_name>]
+```
+
+## 相关文档
+
+想了解更多 CBO 统计信息采集的内容，参见[CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
diff --git a/docs/zh/sql-reference/sql-statements/cbo_stats/KILL_ANALYZE.md b/docs/zh/sql-reference/sql-statements/cbo_stats/KILL_ANALYZE.md
new file mode 100644
index 00000000000000..564b0dd0a319d3
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cbo_stats/KILL_ANALYZE.md
@@ -0,0 +1,23 @@
+---
+displayed_sidebar: docs
+---
+
+# KILL ANALYZE
+
+## 功能
+
+取消正在运行中（Running）的统计信息收集任务，包括手动采集任务和自定义自动采集任务。该语句从 2.4 版本开始支持。
+
+## 语法
+
+```SQL
+KILL ANALYZE <ID>
+```
+
+手动采集任务的任务 ID 可以在 SHOW ANALYZE STATUS 中查看。自定义自动采集任务的任务 ID 可以在 SHOW ANALYZE JOB 中查看。
+
+## 相关文档
+
+[SHOW ANALYZE STATUS](SHOW_ANALYZE_STATUS.md)
+
+[SHOW ANALYZE JOB](SHOW_ANALYZE_JOB.md)
diff --git a/docs/zh/sql-reference/sql-statements/cbo_stats/SHOW_ANALYZE_JOB.md b/docs/zh/sql-reference/sql-statements/cbo_stats/SHOW_ANALYZE_JOB.md
new file mode 100644
index 00000000000000..bd78631d9fbe73
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cbo_stats/SHOW_ANALYZE_JOB.md
@@ -0,0 +1,52 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW ANALYZE JOB
+
+## 功能
+
+查看自定义自动采集任务的信息和状态。自定义自动采集任务用于采集 CBO 统计信息。该语句从 2.4 版本开始支持。
+
+默认情况下，StarRocks 会周期性自动采集表的全量统计信息。默认检查更新时间为 5 分钟一次，如果发现有数据更新，会自动触发采集。如果您不希望使用自动全量采集，可以设置 FE 配置项 `enable_collect_full_statistic` 为 `false`，系统会停止自动全量采集，根据您创建的自定义任务进行定制化采集。
+
+## 语法
+
+```SQL
+SHOW ANALYZE JOB [WHERE predicate]
+```
+
+您可以使用 WHERE 子句设定筛选条件，进行返回结果筛选。该语句会返回如下列。
+
+| **列名**     | **说明**                                                     |
+| ------------ | ------------------------------------------------------------ |
+| Id           | 采集任务的 ID。                                               |
+| Database     | 数据库名。                                                   |
+| Table        | 表名。                                                       |
+| Columns      | 列名列表。                                                   |
+| Type         | 统计信息的类型。取值： FULL，SAMPLE。                        |
+| Schedule     | 调度的类型。自动采集任务固定为 `SCHEDULE`。                   |
+| Properties   | 自定义参数信息。                                             |
+| Status       | 任务状态，包括 PENDING（等待）、RUNNING（正在执行）、SUCCESS（执行成功）和 FAILED（执行失败）。 |
+| LastWorkTime | 最近一次采集时间。                                           |
+| Reason       | 任务失败的原因。如果执行成功则为 `NULL`。                    |
+
+## 示例
+
+```SQL
+-- 查看集群全部自定义采集任务。
+SHOW ANALYZE JOB
+
+-- 查看数据库 `test` 下的自定义采集任务。
+SHOW ANALYZE JOB where `database` = 'test';
+```
+
+## 相关文档
+
+[CREATE ANALYZE](CREATE_ANALYZE.md)：创建自定义自动采集任务。
+
+[DROP ANALYZE](DROP_ANALYZE.md)：删除自动采集任务。
+
+[KILL ANALYZE](KILL_ANALYZE.md)：取消正在运行中（Running）的统计信息收集任务。
+
+想了解更多 CBO 统计信息采集的内容，参见 [CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
diff --git a/docs/zh/sql-reference/sql-statements/cbo_stats/SHOW_ANALYZE_STATUS.md b/docs/zh/sql-reference/sql-statements/cbo_stats/SHOW_ANALYZE_STATUS.md
new file mode 100644
index 00000000000000..6c413c7734b7c3
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cbo_stats/SHOW_ANALYZE_STATUS.md
@@ -0,0 +1,41 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW ANALYZE STATUS
+
+## 功能
+
+查看当前所有采集任务的状态。**该语句不支持查看自定义采集任务的状态，如要查看，请使用 SHOW ANALYZE JOB;**。该语句从 2.4 版本开始支持。
+
+## 语法
+
+```SQL
+SHOW ANALYZE STATUS [LIKE | WHERE predicate]
+```
+
+您可以使用 `Like 或 Where` 来筛选需要返回的信息。
+
+目前 `SHOW ANALYZE STATUS` 会返回如下列。
+
+| **列名**   | **说明**                                                     |
+| ---------- | ------------------------------------------------------------ |
+| Id         | 采集任务的 ID。                                               |
+| Database   | 数据库名。                                                   |
+| Table      | 表名。                                                       |
+| Columns    | 列名列表。                                                   |
+| Type       | 统计信息的类型，包括 FULL，SAMPLE，HISTOGRAM。               |
+| Schedule   | 调度的类型。`ONCE` 表示手动，`SCHEDULE` 表示自动。             |
+| Status     | 任务状态，包括 RUNNING（正在执行）、SUCCESS（执行成功）和 FAILED（执行失败）。 |
+| StartTime  | 任务开始执行的时间。                                         |
+| EndTime    | 任务结束执行的时间。                                         |
+| Properties | 自定义参数信息。                                             |
+| Reason     | 任务失败的原因。如果执行成功则为 NULL。                      |
+
+## 相关文档
+
+[ANALYZE TABLE](ANALYZE_TABLE.md)：创建手动采集任务。
+
+[KILL ANALYZE](KILL_ANALYZE.md)：取消正在运行中（Running）的统计信息收集任务。
+
+想了解更多 CBO 统计信息采集的内容，参见 [CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
diff --git a/docs/zh/sql-reference/sql-statements/cbo_stats/SHOW_META.md b/docs/zh/sql-reference/sql-statements/cbo_stats/SHOW_META.md
new file mode 100644
index 00000000000000..3ae93da6c67a28
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cbo_stats/SHOW_META.md
@@ -0,0 +1,54 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW META
+
+## 功能
+
+查看统计信息元数据。该命令支持查看基础统计信息和直方图统计信息的元数据。该语句从 2.4 版本开始支持。
+
+更多 CBO 统计信息采集的内容，参见 [CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
+
+### 基础统计信息元数据
+
+#### 语法
+
+```SQL
+SHOW STATS META [WHERE predicate]
+```
+
+该语句返回如下列。
+
+| **列名**   | **说明**                                            |
+| ---------- | --------------------------------------------------- |
+| Database   | 数据库名。                                          |
+| Table      | 表名。                                              |
+| Columns    | 列名。                                              |
+| Type       | 统计信息的类型，`FULL` 表示全量，`SAMPLE` 表示抽样。 |
+| UpdateTime | 当前表的最新统计信息更新时间。                      |
+| Properties | 自定义参数信息。                                    |
+| Healthy    | 统计信息健康度。                                    |
+
+### 直方图统计信息元数据
+
+#### 语法
+
+```SQL
+SHOW HISTOGRAM META [WHERE predicate];
+```
+
+该语句返回如下列。
+
+| **列名**   | **说明**                                  |
+| ---------- | ----------------------------------------- |
+| Database   | 数据库名。                                |
+| Table      | 表名。                                    |
+| Column     | 列名。                                    |
+| Type       | 统计信息的类型，直方图固定为 `HISTOGRAM`。 |
+| UpdateTime | 当前表的最新统计信息更新时间。            |
+| Properties | 自定义参数信息。                          |
+
+## 相关文档
+
+想了解更多 CBO 统计信息采集的内容，参见 [CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
diff --git a/docs/zh/sql-reference/sql-statements/cbo_stats/_category_.yml b/docs/zh/sql-reference/sql-statements/cbo_stats/_category_.yml
new file mode 100644
index 00000000000000..08c8f03bf45546
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cbo_stats/_category_.yml
@@ -0,0 +1,6 @@
+position: 120 # float position is supported
+label: 'CBO 统计信息'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/_category_.yml b/docs/zh/sql-reference/sql-statements/cluster-management/_category_.yml
new file mode 100644
index 00000000000000..1f0ebc85979ebe
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/_category_.yml
@@ -0,0 +1,6 @@
+position: 20 # float position is supported
+label: '集群管理'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md b/docs/zh/sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md
new file mode 100644
index 00000000000000..a1f4202123c135
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md
@@ -0,0 +1,33 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN SET CONFIG
+
+## 功能
+
+该语句用于设置集群的配置项（当前仅支持设置 FE 的配置项）。
+
+可设置的配置项，可以通过 [ADMIN SHOW FRONTEND CONFIG](ADMIN_SHOW_CONFIG.md) 命令查看。
+
+设置后的配置项，在 FE 重启之后会恢复成 **fe.conf** 文件中的配置或者默认值。如果需要让配置长期生效，建议设置完之后同时修改 **fe.conf** 文件，防止重启后修改失效。
+
+:::tip
+
+该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```sql
+ADMIN SET FRONTEND CONFIG ("key" = "value")
+```
+
+## 示例
+
+设置 `tablet_sched_disable_balance` 为 `true`。
+
+```sql
+ ADMIN SET FRONTEND CONFIG ("tablet_sched_disable_balance" = "true");
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SHOW_CONFIG.md b/docs/zh/sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SHOW_CONFIG.md
new file mode 100644
index 00000000000000..12fd8c62294bf5
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SHOW_CONFIG.md
@@ -0,0 +1,59 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN SHOW CONFIG
+
+## 功能
+
+该语句用于展示当前集群的配置（当前仅支持展示 FE 的配置项）。
+
+关于每个配置项的含义，参见[FE 配置项](../../../../administration/management/FE_configuration.md)。
+
+如果要动态设置或修改集群的配置项，参见 [ADMIN SET CONFIG](ADMIN_SET_CONFIG.md)。
+
+:::tip
+
+该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```sql
+ADMIN SHOW FRONTEND CONFIG [LIKE "pattern"]
+```
+
+说明：
+
+结果中的各列含义如下：
+
+```plain text
+1. Key         配置项名称
+2. AliasNames  配置项别名
+2. Value       配置项取值
+3. Type        配置项数据类型
+4. IsMutable   是否可以通过 ADMIN SET CONFIG 命令动态设置
+5. Comment     配置项说明
+```
+
+## 示例
+
+1. 查看当前 FE 节点的配置。
+
+    ```sql
+    ADMIN SHOW FRONTEND CONFIG;
+    ```
+
+2. 使用 like 谓词搜索当前 FE 节点的配置。
+
+    ```plain text
+    mysql> ADMIN SHOW FRONTEND CONFIG LIKE '%check_java_version%';
+    +--------------------+------------+-------+---------+-----------+---------+
+    | Key                | AliasNames | Value | Type    | IsMutable | Comment |
+    +--------------------+------------+-------+---------+-----------+---------+
+    | check_java_version | []         | true  | boolean | false     |         |
+    +--------------------+------------+-------+---------+-----------+---------+
+    1 row in set (0.00 sec)
+
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/config_vars/SET.md b/docs/zh/sql-reference/sql-statements/cluster-management/config_vars/SET.md
new file mode 100644
index 00000000000000..5d8d309a0c1461
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/config_vars/SET.md
@@ -0,0 +1,54 @@
+---
+displayed_sidebar: docs
+---
+
+# SET
+
+## 功能
+
+为 StarRocks 设置指定的系统变量或用户自定义变量。您可以通过 [SHOW VARIABLES](SHOW_VARIABLES.md) 查看 StarRocks 的系统变量。有关系统变量的详细信息，请参阅[系统变量](../../../System_variable.md)。有关用户自定义变量的详细信息，请参阅[用户自定义变量](../../../../r../../../user_defined_variables.md
+
+:::tip
+
+该操作不需要权限。
+
+:::
+
+## 语法
+
+```SQL
+SET [ GLOBAL | SESSION ] <variable_name> = <value> [, <variable_name> = <value>] ...
+```
+
+## 参数说明
+
+| **参数**              | **说明**                                                     |
+| --------------------- | ------------------------------------------------------------ |
+| 修饰符：<ul><li>GLOBAL</li><li>SESSION</li></ul> | <ul><li>使用 `GLOBAL` 修饰符，该语句设置该变量值为全局变量值。</li><li>使用 `SESSION` 修饰符，该语句设置该变量值对当前连接有效。您可以使用 `LOCAL` 替代 `SESSION`。</li><li>如不指定修饰符，默认值为 `SESSION`。</li></ul>有关全局变量和会话变量的详细信息，请参阅 [系统变量](../../../System_variable.md)。<br/>**说明**<br/>仅拥有 System 级 OPERATE 权限的用户才能设置全局变量。 |
+| variable_name         | 变量名。                                                     |
+| value                 | 变量值。                                                     |
+
+## 示例
+
+示例一：在当前会话内设置 `time_zone` 为 `Asia/Shanghai`。
+
+```Plain
+mysql> SET time_zone = "Asia/Shanghai";
+Query OK, 0 rows affected (0.00 sec)
+```
+
+示例二：全局设置 `exec_mem_limit` 为 `2147483648`。
+
+```Plain
+mysql> SET GLOBAL exec_mem_limit = 2147483648;
+Query OK, 0 rows affected (0.00 sec)
+```
+
+示例三：同时设置多个全局变量。需要在所有变量名前添加 `GLOBAL` 关键字。
+
+```Plain
+mysql> SET 
+       GLOBAL exec_mem_limit = 2147483648,
+       GLOBAL time_zone = "Asia/Shanghai";
+Query OK, 0 rows affected (0.00 sec)
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/config_vars/SHOW_VARIABLES.md b/docs/zh/sql-reference/sql-statements/cluster-management/config_vars/SHOW_VARIABLES.md
new file mode 100644
index 00000000000000..1dbffaa25e095a
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/config_vars/SHOW_VARIABLES.md
@@ -0,0 +1,94 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW VARIABLES
+
+## 功能
+
+查看当前集群的系统变量信息。
+
+:::tip
+
+该操作不需要权限。
+
+:::
+
+## 语法
+
+```SQL
+SHOW [ GLOBAL | SESSION ] VARIABLES
+    [ LIKE <pattern> | WHERE <expr> ]
+```
+
+## 参数说明
+
+| **参数**              | **说明**                                                     |
+| --------------------- | ------------------------------------------------------------ |
+| 修饰符：<ul><li>GLOBAL</li><li>SESSION</li></ul> | <ul><li>使用 `GLOBAL` 修饰符，该语句显示全局系统变量值。在生成新连接时，StarRocks 自动初始化所有变量的会话值作为全局值。如果变量没有全局值，则不显示任何值。</li><li>使用 `SESSION` 修饰符，该语句显示对当前连接有效的系统变量值。如果变量没有会话值，则显示全局值。您可以使用 `LOCAL` 替代 `SESSION`。</li><li>如不指定修饰符，默认值为 `SESSION`。</li></ul> |
+| pattern               | 用于匹配变量名的 LIKE 子句模式。您可以在当前参数中使用 % 通配符。 |
+| expr                  | 用于匹配变量名 `variable_name` 或变量值 `value` 的 WHERE 子句匹配表达式。 |
+
+## 返回
+
+| **返回**      | **说明** |
+| ------------- | -------- |
+| Variable_name | 变量名。 |
+| Value         | 变量值。 |
+
+## 示例
+
+示例一：通过 LIKE 子句精确匹配变量名显示变量信息。
+
+```Plain
+mysql> SHOW VARIABLES LIKE 'wait_timeout';
++---------------+-------+
+| Variable_name | Value |
++---------------+-------+
+| wait_timeout  | 28800 |
++---------------+-------+
+1 row in set (0.01 sec)
+```
+
+示例二：通过 LIKE 子句与 % 通配符模糊匹配变量名显示变量信息。
+
+```Plain
+mysql> SHOW VARIABLES LIKE '%imeou%';
++------------------------------------+-------+
+| Variable_name                      | Value |
++------------------------------------+-------+
+| interactive_timeout                | 3600  |
+| net_read_timeout                   | 60    |
+| net_write_timeout                  | 60    |
+| new_planner_optimize_timeout       | 3000  |
+| query_delivery_timeout             | 300   |
+| query_queue_pending_timeout_second | 300   |
+| query_timeout                      | 300   |
+| wait_timeout                       | 28800 |
++------------------------------------+-------+
+9 rows in set (0.00 sec)
+```
+
+示例三：通过 WHERE 子句精确匹配变量名显示变量信息。
+
+```Plain
+mysql> show variables where variable_name = 'wait_timeout';
++---------------+-------+
+| Variable_name | Value |
++---------------+-------+
+| wait_timeout  | 28800 |
++---------------+-------+
+1 row in set (0.17 sec)
+```
+
+示例四：通过 WHERE 子句精确匹配变量值显示变量信息。
+
+```Plain
+mysql> show variables where value = '28800';
++---------------+-------+
+| Variable_name | Value |
++---------------+-------+
+| wait_timeout  | 28800 |
++---------------+-------+
+1 row in set (0.70 sec)
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/config_vars/_category_.yml b/docs/zh/sql-reference/sql-statements/cluster-management/config_vars/_category_.yml
new file mode 100644
index 00000000000000..7b8928e1b9ab89
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/config_vars/_category_.yml
@@ -0,0 +1,6 @@
+position: 50 # float position is supported
+label: '系统配置和变量'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/file/CREATE_FILE.md b/docs/zh/sql-reference/sql-statements/cluster-management/file/CREATE_FILE.md
new file mode 100644
index 00000000000000..95351ee9160b57
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/file/CREATE_FILE.md
@@ -0,0 +1,66 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE FILE
+
+CREATE FILE 语句用于创建文件。文件创建后会自动上传并持久化在 StarRocks 集群中。
+
+:::tip
+
+该操作需要 SYSTEM 级 FILE 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。当一个文件归属于一个数据库时，对该数据库拥有访问权限的用户都可以使用该文件。
+
+:::
+
+## 基本概念
+
+**文件**：是指创建并保存在 StarRocks 中的文件。每个文件都有一个全局唯一的标识符 (`FileId`)。一个文件由数据库名称 (`database`)、类别 (`catalog`) 和文件名 (`file_name`) 共同定位。
+
+## 语法
+
+```SQL
+CREATE FILE "file_name" [IN database]
+[properties]
+```
+
+## 参数说明
+
+| **参数**   | **必填** | **描述**                                                     |
+| ---------- | -------- | ------------------------------------------------------------ |
+| file_name  | 是       | 文件名，可根据需求自定义。                                   |
+| database   | 否       | 文件所属的数据库。如果没有指定该参数，则使用当前会话的数据库。 |
+| properties | 是       | 文件属性，具体配置项见下表：`properties` 配置项。            |
+
+**properties 配置项**
+
+| **配置项** | **必填** | **描述**                                                     |
+| ---------- | -------- | ------------------------------------------------------------ |
+| url        | 是       | 文件的下载路径。当前仅支持无认证的 HTTP 下载路径。语句执行成功后，文件会被下载并持久化保存在 StarRocks 中。 |
+| catalog    | 是       | 文件所属类别，可根据需求自定义。在某些命令中，会查找指定类别下的文件。比如在例行导入中，当数据源为 StarRocks 会查找 Apache Kafka® 类别下的文件。 |
+| md5        | 否       | 消息摘要算法。如果指定该参数，StarRocks 会对下载后的文件进行校验。 |
+
+## 示例
+
+- 创建一个名为 **test.pem** 的文件，所属类别为 kafka。
+
+```SQL
+CREATE FILE "test.pem"
+PROPERTIES
+(
+    "url" = "http://starrocks-public.oss-cn-xxxx.aliyuncs.com/key/test.pem",
+    "catalog" = "kafka"
+);
+```
+
+- 创建一个名为 **client.key** 的文件，所属类别为 my_catalog。
+
+```SQL
+CREATE FILE "client.key"
+IN my_database
+PROPERTIES
+(
+    "url" = "http://test.bj.bcebos.com/kafka-key/client.key",
+    "catalog" = "my_catalog",
+    "md5" = "b5bb901bf10f99205b39a46ac3557dd9"
+);
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/file/DROP_FILE.md b/docs/zh/sql-reference/sql-statements/cluster-management/file/DROP_FILE.md
new file mode 100644
index 00000000000000..b8922e9c5d5431
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/file/DROP_FILE.md
@@ -0,0 +1,43 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP FILE
+
+DROP FILE 语句用于删除保存在数据库中的文件。使用该语句删除一个文件，那么该文件在 FE 内存和 BDBJE 中均会被删除。
+
+:::tip
+
+该操作需要 SYSTEM 级 FILE 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。当一个文件归属于一个数据库时，对该数据库拥有访问权限的用户都可以使用该文件。
+
+:::
+
+## 语法
+
+```SQL
+DROP FILE "file_name" [FROM database]
+
+[properties]
+```
+
+## 参数说明
+
+| **参数**   | **必填** | **描述**                                         |
+| ---------- | -------- | ------------------------------------------------ |
+| file_name  | 是       | 文件名。                                           |
+| database   | 否       | 文件所属的数据库。                                 |
+| properties | 是       | 文件属性，具体配置项见下表：`properties`配置项。     |
+
+`properties` 配置项
+
+| **配置项** | **必填** | **描述**     |
+| ---------- | -------- | ------------ |
+| catalog    | 是       | 文件所属类别。 |
+
+## 示例
+
+删除文件 `ca.pem`。
+
+```SQL
+DROP FILE "ca.pem" properties("catalog" = "kafka");
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/file/SHOW_FILE.md b/docs/zh/sql-reference/sql-statements/cluster-management/file/SHOW_FILE.md
new file mode 100644
index 00000000000000..7bb1bb43685722
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/file/SHOW_FILE.md
@@ -0,0 +1,36 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW FILE
+
+SHOW FILE 语句用于查看保存在数据库中的文件的信息。
+
+:::tip
+
+该操作需要用户有 File 所属数据库上的任意权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。当一个文件归属于一个数据库时，对该数据库拥有访问权限的用户都可以使用该文件。
+
+:::
+
+## 语法
+
+```SQL
+SHOW FILE [FROM database]
+```
+
+语句返回的信息如下：
+
+- `FileId`: 文件ID，全局唯一。
+- `DbName`: 所属数据库。
+- `Catalog`: 自定义类别。
+- `FileName`: 文件名。
+- `FileSize`: 文件大小，单位字节。
+- `MD5`: 消息摘要算法，用于检查文件。
+
+## 示例
+
+查看保存在数据库 `my_database` 中的文件。
+
+```SQL
+SHOW FILE FROM my_database;
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/file/_category_.yml b/docs/zh/sql-reference/sql-statements/cluster-management/file/_category_.yml
new file mode 100644
index 00000000000000..a3a8aed7f63639
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/file/_category_.yml
@@ -0,0 +1,6 @@
+position: 60 # float position is supported
+label: '文件'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/ADD_BACKEND_BLACKLIST.md b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/ADD_BACKEND_BLACKLIST.md
new file mode 100644
index 00000000000000..e58e857b3b16d7
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/ADD_BACKEND_BLACKLIST.md
@@ -0,0 +1,49 @@
+---
+displayed_sidebar: docs
+---
+
+# ADD BACKEND BLACKLIST
+
+## 功能
+
+将一个 BE 节点添加到 BE 黑名单中。您可以手动将 BE 节点添加到黑名单中，禁止在查询执行中使用该节点，从而避免由于节点断连而引起的查询超时失败或其他意外行为。
+
+此功能自 v3.3.0 起支持。更多信息，参考[管理 BE 黑名单](../../../../administration/management/BE_blacklist.md)。
+
+:::note
+
+该操作需要有 SYSTEM 级 BLACKLIST 权限。
+
+:::
+
+默认情况下，StarRocks 可以自动管理 BE 黑名单，将断连的 BE 节点添加到黑名单中，并在重新连接成功时将其从黑名单中移除。但 StarRocks 不会主动将用户手动加入黑名单的节点移除。
+
+## 语法
+
+```SQL
+ADD BACKEND BLACKLIST <be_id>[, ...]
+```
+
+## 参数说明
+
+`be_id`：要添加到黑名单中的 BE 节点的 ID。您可以通过执行 [SHOW BACKENDS](SHOW_BACKENDS.md) 语句来获取 BE 节点的 ID。
+
+## 示例
+
+```SQL
+-- 获取 BE ID。
+SHOW BACKENDS\G
+*************************** 1. row ***************************
+            BackendId: 10001
+                   IP: xxx.xx.xx.xxx
+                   ...
+-- 添加 BE 节点至黑名单。
+ADD BACKEND BLACKLIST 10001;
+```
+
+## 相关 SQL
+
+- [DELETE BACKEND BLACKLIST](DELETE_BACKEND_BLACKLIST.md)
+- [SHOW BACKEND BLACKLIST](SHOW_BACKEND_BLACKLIST.md)
+- [SHOW BACKENDS](SHOW_BACKENDS.md)
+
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md
new file mode 100644
index 00000000000000..a5e4fd87e5fbe5
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md
@@ -0,0 +1,193 @@
+---
+keywords: ['xiugai'] 
+displayed_sidebar: docs
+---
+
+# ALTER SYSTEM
+
+## 功能
+
+管理 StarRocks 集群中的 FE、BE、CN 和 Broker。
+
+> **注意**
+>
+> 只有拥有 `cluster_admin` 角色的用户才可以执行集群管理相关操作。
+
+## 语法和参数说明
+
+### FE
+
+- 添加 Follower FE。添加后，可使用 `SHOW PROC '/frontends'\G` 命令查看新增FE 的状态。
+
+   ```SQL
+    ALTER SYSTEM ADD FOLLOWER "host:edit_log_port"[, ...]
+    ```
+
+- 删除 Follower FE。
+
+    ```SQL
+    ALTER SYSTEM DROP FOLLOWER "host:edit_log_port"[, ...]
+    ```
+
+- 添加 Observer FE。添加后，可通过 `SHOW PROC '/frontends'\G` 命令查看新增FE 的状态。
+
+    ```SQL
+    ALTER SYSTEM ADD OBSERVER "host:edit_log_port"[, ...]
+    ```
+
+- 删除 Observer FE。
+
+    ```SQL
+    ALTER SYSTEM DROP OBSERVER "host:edit_log_port"[, ...]
+    ```
+
+     参数说明如下：
+
+    | **参数**           | **必选** | **说明**                                                     |
+    | ------------------ | -------- | ------------------------------------------------------------ |
+    | host:edit_log_port | 是       | <ul><li>`host`：FE 机器的 FQDN 或 IP 地址。如果机器存在多个 IP 地址，则该参数取值应为 `priority_networks` 配置项下设定的唯一通信 IP 地址。</li><li>`edit_log_port`：FE 上的 BDBJE 通信端口，默认为 `9010`。</li></ul> |
+
+- 创建 image。
+
+    ```SQL
+    ALTER SYSTEM CREATE IMAGE
+    ```
+
+    执行该语句会主动触发 Leader FE 创建新的 Image（元数据快照）文件。该操作异步执行，您可以通过查看 FE 日志文件 **fe.log** 确认操作何时开始执行及结束。`triggering a new checkpoint manually...` 表明操作开始执行，`finished save image...` 则表明 Image 创建完成。
+
+### BE
+
+- 添加 BE。 添加后，可通过 [SHOW BACKENDS](SHOW_BACKENDS.md) 查看新增 BE 的状态。
+
+    ```SQL
+    ALTER SYSTEM ADD BACKEND "host:heartbeat_service_port"[, ...]
+    ```
+
+- 删除 BE。如果有表是单副本且该表的部分 tablet 分布在要删除的 BE 上，则不允许删除该 BE。
+
+    ```SQL
+    ALTER SYSTEM DROP BACKEND "host:heartbeat_service_port"[, ...]
+    ```
+
+- 下线 BE。
+
+    ```SQL
+    ALTER SYSTEM DECOMMISSION BACKEND "host:heartbeat_service_port"[, ...]
+    ```
+
+    下线前，该 BE 上的数据会迁移到其他 BE 上，过程中不影响数据导入和查询。下线 BE 为异步操作，可通过 [SHOW BACKENDS](SHOW_BACKENDS.md) 语句查看是否下线成功，如下线成功，该 BE 不会在 SHOW BACKENDS 返回的信息中显示。您可以手动撤销下线操作，详情参见 [CANCEL DECOMMISSION](CANCEL_DECOMMISSION.md)。
+
+    参数说明如下：
+
+    | **参数**                    | **必选** | **说明**                                                     |
+    | --------------------------- | -------- | ------------------------------------------------------------ |
+    | host:heartbeat_service_port | 是       |<ul><li> `host`：BE 机器的 FQDN 或 IP 地址。如果机器存在多个 IP 地址，则该参数取值应为 `priority_networks` 配置项下设定的唯一通信 IP 地址。</li><li>`heartbeat_service_port`：BE 的心跳端口，用于接收来自 FE 的心跳，默认为 `9050`。</li></ul> |
+
+### CN
+
+- 添加 CN。 添加后，可通过 `SHOW PROC '/compute_nodes'\G` 查看新增 CN 的状态。
+
+    ```SQL
+    ALTER SYSTEM ADD COMPUTE NODE "host:heartbeat_service_port"[, ...]
+    ```
+
+- 删除 CN。
+
+    ```SQL
+    ALTER SYSTEM DROP COMPUTE NODE "host:heartbeat_service_port"[, ...]
+    ```
+
+> **说明**
+>
+> CN 暂不支持通过 `ALTER SYSTEM DECOMMISSION` 命令下线。
+
+    参数说明如下：
+
+    | **参数**                    | **必选** | **说明**                                                     |
+    | --------------------------- | -------- | ------------------------------------------------------------ |
+    | host:heartbeat_service_port | 是       |<ul><li> `host`：CN 机器的 FQDN 或 IP 地址。如果机器存在多个 IP 地址，则该参数取值应为 `priority_networks` 配置项下设定的唯一通信 IP 地址。</li><li>`heartbeat_service_port`：CN 的心跳端口，用于接收来自 FE 的心跳，默认为 `9050`。</li></ul> |
+
+### Broker
+
+- 添加 Broker。添加后，您可以使用 Broker Load 将 HDFS 或外部云存储系统中的数据导入到 StarRocks 中。详情参见[从 HDFS 导入](../../../../loading/hdfs_load.md)或[从云存储导入](../../../../loading/cloud_storage_load.md)。
+
+    ```SQL
+    ALTER SYSTEM ADD BROKER broker_name "host:port"[, ...]
+    ```
+
+    在一条 SQL 语句中，如同时添加多个 Broker（一个`host:port`为一个 Broker），那么这些 Broker 共用同一个 `broker_name`。添加后，可通过 [SHOW BROKER](SHOW_BROKER.md) 语句查看 Broker 的详细信息。
+
+- 删除 Broker。注意如一个 Broker 上有正在执行的导入任务，那么删除该 Broker 会导致该任务中断。
+
+  - 删除 `broker_name` 下的一个或多个 Broker。
+
+      ```SQL
+      ALTER SYSTEM DROP BROKER broker_name "host:broker_ipc_port"[, ...]
+      ```
+
+  - 删除所有名为 `broker_name` 下的 Broker。
+
+      ```SQL
+      ALTER SYSTEM DROP ALL BROKER broker_name
+      ```
+
+     参数说明如下：
+
+    | **参数**             | **必选** | **说明**                                                     |
+    | -------------------- | -------- | ------------------------------------------------------------ |
+    | broker_name          | 是       | 一个 Broker 的名称或多个 Broker 共用的名称。                 |
+    | host:broker_ipc_port | 是       | <ul><li>`host`：Broker 机器的 FQDN 或 IP 地址。</li><li>`broker_ipc_port`：Broker 上的 thrift server 端口，用于接受 FE 或 BE 的请求，默认为 `8000`。</li></ul> |
+
+## 使用说明
+
+添加和删除 FE、添加和删除 BE 以及添加和删除 Broker 均为同步操作。执行删除语句后，FE、BE 或 Broker 会直接删除，不可手动撤销该操作。
+
+## 示例
+
+示例一：添加一个 Follower FE。
+
+```SQL
+ALTER SYSTEM ADD FOLLOWER "x.x.x.x:9010";
+```
+
+示例二：同时删除两个 Observer FE。
+
+```SQL
+ALTER SYSTEM DROP OBSERVER "x.x.x.x:9010","x.x.x.x:9010";
+```
+
+示例三：添加一个 BE。
+
+```SQL
+ALTER SYSTEM ADD BACKEND "x.x.x.x:9050";
+```
+
+示例四：同时删除两个 BE。
+
+```SQL
+ALTER SYSTEM DROP BACKEND "x.x.x.x:9050", "x.x.x.x:9050";
+```
+
+示例五：同时下线两个 BE。
+
+```SQL
+ALTER SYSTEM DECOMMISSION BACKEND "x.x.x.x:9050", "x.x.x.x:9050";
+```
+
+示例六：同时添加两个名为 `hdfs` 的 Broker。
+
+```SQL
+ALTER SYSTEM ADD BROKER hdfs "x.x.x.x:8000", "x.x.x.x:8000";
+```
+
+示例七：删除 `amazon_s3` 下的两个 Broker。
+
+```SQL
+ALTER SYSTEM DROP BROKER amazon_s3 "x.x.x.x:8000", "x.x.x.x:8000";
+```
+
+示例八：删除 `amazon_s3` 下的所有 Broker。
+
+```SQL
+ALTER SYSTEM DROP ALL BROKER amazon_s3;
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/CANCEL_DECOMMISSION.md b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/CANCEL_DECOMMISSION.md
new file mode 100644
index 00000000000000..648211c6952983
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/CANCEL_DECOMMISSION.md
@@ -0,0 +1,27 @@
+---
+displayed_sidebar: docs
+---
+
+# CANCEL DECOMMISSION
+
+## 功能
+
+该语句用于撤销一个节点下线操作。
+
+> **注意**
+>
+> 只有拥有 `cluster_admin` 角色的用户才可以执行集群管理相关操作。
+
+## 语法
+
+```sql
+CANCEL DECOMMISSION BACKEND "host:heartbeat_port"[,"host:heartbeat_port"...]
+```
+
+## 示例
+
+取消两个节点的下线操作:
+
+```sql
+CANCEL DECOMMISSION BACKEND "host1:port", "host2:port";
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/DELETE_BACKEND_BLACKLIST.md b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/DELETE_BACKEND_BLACKLIST.md
new file mode 100644
index 00000000000000..13396a731a6df3
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/DELETE_BACKEND_BLACKLIST.md
@@ -0,0 +1,40 @@
+---
+displayed_sidebar: docs
+---
+
+# DELETE BACKEND BLACKLIST
+
+## 功能
+
+从 BE 黑名单中移除 BE 节点。请注意，StarRocks 不会主动将用户手动加入黑名单的节点移除。
+
+此功能自 v3.3.0 起支持。更多信息，参考[管理 BE 黑名单](../../../../administration/management/BE_blacklist.md)。
+
+:::note
+
+该操作需要有 SYSTEM 级 BLACKLIST 权限。
+
+:::
+
+## 语法
+
+```SQL
+DELETE BACKEND BLACKLIST <be_id>[, ...]
+```
+
+## 参数说明
+
+`be_id`：要从黑名单中移除的 BE 节点的 ID。您可以通过执行 [SHOW BACKEND BLACKLIST](SHOW_BACKEND_BLACKLIST.md) 语句获取被列入黑名单的 BE 的 ID。
+
+## 示例
+
+```SQL
+DELETE BACKEND BLACKLIST 10001;
+```
+
+## 相关 SQL
+
+- [ADD BACKEND BLACKLIST](ADD_BACKEND_BLACKLIST.md)
+- [SHOW BACKEND BLACKLIST](SHOW_BACKEND_BLACKLIST.md)
+- [SHOW BACKENDS](SHOW_BACKENDS.md)
+
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/KILL.md b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/KILL.md
new file mode 100644
index 00000000000000..5aca36f767422d
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/KILL.md
@@ -0,0 +1,43 @@
+---
+displayed_sidebar: docs
+---
+
+# KILL
+
+## 功能
+
+终止当前集群内的正在执行的指定连接或者查询。
+
+:::tip
+
+该操作不需要权限。
+
+:::
+
+## 语法
+
+```SQL
+KILL [ CONNECTION | QUERY ] <processlist_id>
+```
+
+## 参数说明
+
+| **参数**                | **说明**                                                     |
+| ----------------------- | ------------------------------------------------------------ |
+| 修饰符：<ul><li>CONNECTION</li><li>QUERY</li></ul> | <ul><li>使用 `CONNECTION` 修饰符，KILL 语句首先终止与 `processlist_id` 关联的连接下正在执行的语句，然后终止该连接。</li><li>使用 `QUERY` 修饰符，KILL 语句仅终止与 `processlist_id` 关联的连接下正在执行的语句，不会终止该连接。</li><li>如不指定修饰符，默认值为 `CONNECTION`。</li></ul> |
+| processlist_id          | 需要终止的线程的 ID。 您可以通过 [SHOW PROCESSLIST](SHOW_PROCESSLIST.md) 获取正在执行的线程的 ID。 |
+
+## 示例
+
+```Plain
+mysql> SHOW FULL PROCESSLIST;
++------+------+---------------------+--------+---------+---------------------+------+-------+-----------------------+-----------+
+| Id   | User | Host                | Db     | Command | ConnectionStartTime | Time | State | Info                  | IsPending |
++------+------+---------------------+--------+---------+---------------------+------+-------+-----------------------+-----------+
+|   20 | root | xxx.xx.xxx.xx:xxxxx | sr_hub | Query   | 2023-01-05 16:30:19 |    0 | OK    | show full processlist | false     |
++------+------+---------------------+--------+---------+---------------------+------+-------+-----------------------+-----------+
+1 row in set (0.01 sec)
+
+mysql> KILL 20;
+Query OK, 0 rows affected (0.00 sec)
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKENDS.md b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKENDS.md
new file mode 100644
index 00000000000000..7e947990566f1e
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKENDS.md
@@ -0,0 +1,76 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW BACKENDS
+
+## 功能
+
+查看当前集群中所有 BE 节点的相关信息。
+
+> **注意**
+>
+> 该操作需要 SYSTEM 级 OPERATE 权限或 `cluster_admin` 角色。
+
+## 语法
+
+```SQL
+SHOW BACKENDS
+```
+
+## 返回信息说明
+
+```SQL
++-----------+-----------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+--------------------+--------------------------------------------------------+-------------------+-------------+----------+-------------------+------------+------------+------------------+----------+
+| BackendId | IP        | HeartbeatPort | BePort | HttpPort | BrpcPort | LastStartTime       | LastHeartbeat       | Alive | SystemDecommissioned | ClusterDecommissioned | TabletNum | DataUsedCapacity | AvailCapacity | TotalCapacity | UsedPct | MaxDiskUsedPct | ErrMsg | Version            | Status                                                 | DataTotalCapacity | DataUsedPct | CpuCores | NumRunningQueries | MemUsedPct | CpuUsedPct | DataCacheMetrics | Location |
++-----------+-----------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+--------------------+--------------------------------------------------------+-------------------+-------------+----------+-------------------+------------+------------+------------------+----------+
+```
+
+返回信息中的参数说明如下：
+
+| **参数**               | **说明**                                                     |
+| --------------------- | ------------------------------------------------------------ |
+| BackendId             | BE 的 ID。                                                   |
+| IP                    | BE 的 IP 地址。                                              |
+| HeartbeatPort         | BE 上的心跳端口，用于接收来自 FE 的心跳。                    |
+| BePort                | BE 上的 Thrift server 端口， 用于接收来自 FE 的请求。        |
+| HttpPort              | BE 上的 HTTP server 端口，用于网页访问 BE。                  |
+| BrpcPort              | BE 上的 bRPC 端口，用于 BE 之间通讯。                        |
+| LastStartTime         | BE 最后一次启动的时间。                                      |
+| LastHeartbeat         | FE 最后一次发心跳给 BE，且 BE 成功回复的时间。               |
+| Alive                 | BE 是否存活。<ul><li>`true`：表示存活。</li><li>`false`：表示没有存活。 </li></ul>      |
+| SystemDecommissioned  | BE 是否已下线。下线前，该 BE 节点的数据会迁移到其他 BE 节点上，期间不影响数据导入和查询。<ul><li>`true`：表示集群已经标记该 BE 下线（数据可能已经完成迁移，或还在迁移中）。</li><li>`false`：表示集群正常使用该 BE（未执行下线操作）。</li></ul> |
+| ClusterDecommissioned | 该参数用于系统兼容。                                         |
+| TabletNum             | BE 上 tablet 的数量。                                        |
+| DataUsedCapacity      | 数据文件占用的磁盘空间。                                     |
+| AvailCapacity         | 可使用的磁盘空间。                                           |
+| TotalCapacity         | 总磁盘空间，即为 `DataUsedCapacity` + `AvailCapacity` + 非数据文件占用的空间。 |
+| UsedPct               | 磁盘使用量百分比。                                           |
+| MaxDiskUsedPct        | 一个 BE 节点如果有多个存储数据的路径，该参数为存储数据最多的路径占用磁盘的百分比。 |
+| ErrMsg                | 接收 FE 心跳失败时的错误信息。                               |
+| Version               | 当前集群的版本。                                             |
+| Status                | BE 最后一次向 FE 报告 tablet 数量的时间，以 JSON 格式显示 。 |
+| DataTotalCapacity     | `DataUsedCapacity` + `AvailCapacity`，即数据文件所占用的磁盘空间 + 可使用的磁盘空间。 |
+| DataUsedPct           | `DataUsedCapacity`/`DataTotalCapacity`，即数据文件所占用的磁盘空间/（数据文件所占用的磁盘空间 + 可使用的磁盘空间）。 |
+| CpuCores              | BE 机器的 CPU 核数。                                         |
+| NumRunningQueries     | BE 上正在运行的查询数量。                                      |
+| MemUsedPct            | 内存使用量百分比。                                            |
+| CpuUsedPct            | CPU 使用量百分比。                                           |
+| DataCacheMetrics      | Data Cache 状态：<ul><li>`Disabled`：未开启。</li><li>`Normal`：正常。 </li><li>`Abnormal`：异常。 </li><li>`Updating`：正在执行变更操作，例如扩缩容等。 </li></ul>                      |
+| Location              | BE 节点的标签。更多信息，参考[使用标签管理 BE 节点](../../../../administration/management/resource_management/be_label.md)。                      |
+
+## 示例
+
+查看当前集群中的所有 BE 节点的相关信息。
+
+```Plain
+SHOW BACKENDS;
+
++-----------+---------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+----------------------+--------------------------------------------------------+-------------------+-------------+----------+
+| BackendId | IP      | HeartbeatPort | BePort | HttpPort | BrpcPort | LastStartTime       | LastHeartbeat       | Alive | SystemDecommissioned | ClusterDecommissioned | TabletNum | DataUsedCapacity | AvailCapacity | TotalCapacity | UsedPct | MaxDiskUsedPct | ErrMsg | Version              | Status                                                 | DataTotalCapacity | DataUsedPct | CpuCores |
++-----------+---------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+----------------------+--------------------------------------------------------+-------------------+-------------+----------+
+| 10002     | x.x.x.x | 9254          | 9260   | 8238     | 8260     | 2022-09-08 14:37:10 | 2022-09-08 15:14:21 | true  | false                | false                 | 21753     | 25.122 GB        | 1.088 TB      | 1.968 TB      | 44.72 % | 44.72 %        |        | MAIN-RELEASE-d094052 | {"lastSuccessReportTabletsTime":"2022-09-08 15:14:13"} | 1.113 TB          | 2.20 %      | 16       |
+| 10003     | x.x.x.x | 9254          | 9260   | 8238     | 8260     | 2022-09-08 14:37:20 | 2022-09-08 15:14:21 | true  | false                | false                 | 21754     | 25.121 GB        | 1.169 TB      | 1.968 TB      | 40.61 % | 40.61 %        |        | MAIN-RELEASE-d094052 | {"lastSuccessReportTabletsTime":"2022-09-08 15:14:22"} | 1.194 TB          | 2.06 %      | 16       |
+| 10004     | x.x.x.x | 9254          | 9260   | 8238     | 8260     | 2022-09-08 14:37:39 | 2022-09-08 15:14:21 | true  | false                | false                 | 21754     | 25.112 GB        | 1.172 TB      | 1.968 TB      | 40.46 % | 40.46 %        |        | MAIN-RELEASE-d094052 | {"lastSuccessReportTabletsTime":"2022-09-08 15:13:42"} | 1.197 TB          | 2.05 %      | 16       |
++-----------+---------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+----------------------+--------------------------------------------------------+-------------------+-------------+----------+
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKEND_BLACKLIST.md b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKEND_BLACKLIST.md
new file mode 100644
index 00000000000000..2069e4f9583f20
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BACKEND_BLACKLIST.md
@@ -0,0 +1,50 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW BACKEND BLACKLIST
+
+## 功能
+
+查看 BE 黑名单中的节点。
+
+此功能自 v3.3.0 起支持。更多信息，参考[管理 BE 黑名单](../../../../administration/management/BE_blacklist.md)。
+
+:::note
+
+该操作需要有 SYSTEM 级 BLACKLIST 权限。
+
+:::
+
+## 语法
+
+```SQL
+SHOW BACKEND BLACKLIST
+```
+
+## 返回
+
+| **返回**                     | **说明**                                                     |
+| ---------------------------- | ------------------------------------------------------------ |
+| AddBlackListType             | BE 节点被添加到黑名单的方式。`MANUAL` 表示由用户手动添加到黑名单。`AUTO` 表示由 StarRocks 自动添加到黑名单。 |
+| LostConnectionTime           | 对于 `MANUAL` 类型，表示 BE 节点被手动添加到黑名单的时间。<br />对于 `AUTO` 类型，表示最后一次成功建立连接的时间。 |
+| LostConnectionNumberInPeriod | 在 `CheckTimePeriod(s)` 内检测到的断连次数。                 |
+| CheckTimePeriod(s)           | StarRocks 检查黑名单中 BE 节点连接状态的间隔。其值等于您在 FE 配置项 `black_host_history_sec` 中指定的值。单位：秒。 |
+
+## 示例
+
+```SQL
+SHOW BACKEND BLACKLIST;
++-----------+------------------+---------------------+------------------------------+--------------------+
+| BackendId | AddBlackListType | LostConnectionTime  | LostConnectionNumberInPeriod | CheckTimePeriod(s) |
++-----------+------------------+---------------------+------------------------------+--------------------+
+| 10001     | MANUAL           | 2024-04-28 11:52:09 | 0                            | 5                  |
++-----------+------------------+---------------------+------------------------------+--------------------+
+```
+
+## 相关 SQL
+
+- [ADD BACKEND BLACKLIST](ADD_BACKEND_BLACKLIST.md)
+- [DELETE BACKEND BLACKLIST](DELETE_BACKEND_BLACKLIST.md)
+- [SHOW BACKENDS](./SHOW_BACKENDS.md)
+
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BROKER.md b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BROKER.md
new file mode 100644
index 00000000000000..f7fd1db997dcd2
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_BROKER.md
@@ -0,0 +1,26 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW BROKER
+
+## 功能
+
+该语句用于查看当前存在的 broker。
+
+> **注意**
+>
+> 该操作需要 SYSTEM 级 OPERATE 权限或 cluster_admin 角色。
+
+## 语法
+
+```sql
+SHOW BROKER
+```
+
+命令返回结果说明：
+
+1. LastStartTime 表示最近一次 BE 启动时间。
+2. LastHeartbeat 表示最近一次心跳。
+3. Alive 表示节点是否存活。
+4. ErrMsg 用于显示心跳失败时的错误信息。
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_COMPUTE_NODES.md b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_COMPUTE_NODES.md
new file mode 100644
index 00000000000000..b8f828c8d3efe8
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_COMPUTE_NODES.md
@@ -0,0 +1,86 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW COMPUTE NODES
+
+## 功能
+
+查看当前集群中所有 CN 节点的相关信息。
+
+> **注意**
+>
+> 该操作需要 SYSTEM 级 OPERATE 权限或 `cluster_admin` 角色。
+
+## 语法
+
+```sql
+SHOW COMPUTE NODES
+```
+
+## 返回信息说明
+
+```SQL
++---------------+--------------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+--------+--------------------+----------+-------------------+------------+------------+----------------+-------------+----------+-------------------+-----------+
+| ComputeNodeId | IP           | HeartbeatPort | BePort | HttpPort | BrpcPort | LastStartTime       | LastHeartbeat       | Alive | SystemDecommissioned | ClusterDecommissioned | ErrMsg | Version            | CpuCores | NumRunningQueries | MemUsedPct | CpuUsedPct | HasStoragePath | StarletPort | WorkerId | WarehouseName     | TabletNum |
++---------------+--------------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+--------+--------------------+----------+-------------------+------------+------------+----------------+-------------+----------+-------------------+-----------+
+```
+
+返回信息中的参数说明如下：
+
+| **参数**              | **说明**                                                          |
+| -------------------- | ----------------------------------------------------------------- |
+| ComputeNodeId        | CN 的 ID。                                                         |
+| IP                   | CN 的 IP 地址。                                                    |
+| HeartbeatPort        | CN 上的心跳端口，用于接收来自 FE 的心跳。                               |
+| BePort               | CN 上的 Thrift server 端口， 用于接收来自 FE 的请求。                  |
+| HttpPort             | CN 上的 HTTP server 端口，用于网页访问 BE。                           |
+| BrpcPort             | CN 上的 bRPC 端口，用于 CN 之间通讯。                                 |
+| LastStartTime        | CN 最后一次启动的时间。                                              |
+| LastHeartbeat        | FE 最后一次发心跳给 BE，且 CN 成功回复的时间。                          |
+| Alive                | CN 是否存活。<ul><li>`true`：表示存活。</li><li>`false`：表示没有存活。 </li></ul> |
+| SystemDecommissioned | CN 是否已下线。`true`：表示集群已经标记该 CN 下线。                     |
+| ClusterDecommissioned | 该参数用于系统兼容。                                                |
+| ErrMsg               | 接收 FE 心跳失败时的错误信息。                                        |
+| Version              | CN 的 StarRocks 版本。                                             |
+| CpuCores             | CN 机器的 CPU 核数。                                                |
+| NumRunningQueries    | CN 上正在运行的查询数量。                                             |
+| MemUsedPct           | 内存使用量百分比。                                                   |
+| CpuUsedPct           | CPU 使用量百分比。                                                  |
+| HasStoragePath       | CN 是否配置有存储路径。                                               |
+| StarletPort          | CN 的 `starlet_port`。该端口为额外 Agent 服务端口。                   |
+| WorkerId             | CN 的内部调度 ID。                                                  |
+| WarehouseName        | CN 所属的 Warehouse 名。该值恒为 `default_warehouse`。               |
+| TabletNum            | CN 上 Tablet 的数量（仅针对 Cache 中的数据）。                         |
+
+## 示例
+
+查看当前集群中的所有 CN 节点的相关信息。
+
+```Plain
+MySQL > SHOW COMPUTE NODES\G
+*************************** 1. row ***************************
+        ComputeNodeId: 10001
+                   IP: x.x.x.x
+        HeartbeatPort: 9050
+               BePort: 9060
+             HttpPort: 8040
+             BrpcPort: 8060
+        LastStartTime: 2024-05-14 15:45:34
+        LastHeartbeat: 2024-05-14 15:47:59
+                Alive: true
+ SystemDecommissioned: false
+ClusterDecommissioned: false
+               ErrMsg: 
+              Version: 3.3.0-rc01-3b8cb0c
+             CpuCores: 4
+    NumRunningQueries: 0
+           MemUsedPct: 1.95 %
+           CpuUsedPct: 0.0 %
+       HasStoragePath: true
+          StarletPort: 8167
+             WorkerId: 1
+        WarehouseName: default_warehouse
+            TabletNum: 58
+1 row in set (0.00 sec)
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_FRONTENDS.md b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_FRONTENDS.md
new file mode 100644
index 00000000000000..d2a494bc86b0fb
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_FRONTENDS.md
@@ -0,0 +1,29 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW FRONTENDS
+
+## 功能
+
+该语句用于查看 FE 节点。FE 节点添加方式及高可用部署请参考 [集群部署](../../../../deployment/deploy_manually.md) 章节。
+
+> **注意**
+>
+> 该操作需要 SYSTEM 级 OPERATE 权限或 cluster_admin 角色。
+
+## 语法
+
+```sql
+SHOW FRONTENDS
+```
+
+命令返回结果说明：
+
+1. name 表示该 FE 节点在 bdbje 中的名称。
+2. Join 为 true 表示该节点曾经加入过集群。但不代表当前还在集群内（可能已失联）
+3. Alive 表示节点是否存活。
+4. ReplayedJournalId 表示该节点当前已经回放的最大元数据日志 id。
+5. LastHeartbeat 是最近一次心跳。
+6. IsHelper 表示该节点是否是 bdbje 中的 helper 节点。
+7. ErrMsg 用于显示心跳失败时的错误信息。
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROC.md b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROC.md
new file mode 100644
index 00000000000000..dc909be0a64367
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROC.md
@@ -0,0 +1,442 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW PROC
+
+## 功能
+
+查看当前集群中的特定指标。
+
+> **注意**
+>
+> 该操作需要 SYSTEM 级 OPERATE 权限。
+
+## 语法
+
+```SQL
+SHOW PROC { '/backends' | '/compute_nodes' | '/dbs' 
+          | '/jobs' | '/statistic' | '/tasks' | '/frontends' 
+          | '/brokers' | '/resources' | '/load_error_hub' 
+          | '/transactions' | '/monitor' | '/current_queries' 
+          | '/current_backend_instances' | '/cluster_balance' 
+          | '/routine_loads' | '/colocation_group' | '/catalog' }
+```
+
+## 参数说明
+
+| **参数**                     | **说明**                                                     |
+| ---------------------------- | ------------------------------------------------------------ |
+| '/backends'                  | 查看当前集群的 BE 节点信息。                                 |
+| '/compute_nodes'             | 查看当前集群的 CN 节点信息。                                 |
+| '/dbs'                       | 查看当前集群的数据库信息。                                   |
+| '/jobs'                      | 查看当前集群的作业信息。                                     |
+| '/statistic'                 | 查看当前集群各数据库的统计信息。                             |
+| '/tasks'                     | 查看当前集群各种任务类型的总数和失败总数。                   |
+| '/frontends'                 | 查看当前集群的 FE 节点信息。                                 |
+| '/brokers'                   | 查看当前集群的 Broker 节点信息。                             |
+| '/resources'                 | 查看当前集群的资源信息。                                     |
+| '/load_error_hub'            | 查看当前集群的 Error Hub 的配置信息。Error Hub 用于管理导入作业产生的错误信息。 |
+| '/transactions'              | 查看当前集群的事务信息。                                     |
+| '/monitor'                   | 查看当前集群的监控信息。                                     |
+| '/current_queries'           | 查看当前连接的FE节点正在执行的查询信息。                       |
+| '/current_backend_instances' | 查看当前集群正在执行作业的 BE 节点。                         |
+| '/cluster_balance'           | 查看当前集群的负载信息。                                     |
+| '/routine_loads'             | 查看当前集群的 Routine Load 导入信息。                       |
+| '/colocation_group'          | 查看当前集群的 Colocate Join Group 信息。                    |
+| '/catalog'                   | 查看当前集群的 Catalog 信息。                                |
+
+## 示例
+
+示例一：查看当前集群的 BE 节点信息。
+
+```Plain
+mysql> SHOW PROC '/backends'\G
+*************************** 1. row ***************************
+            BackendId: 10004
+                   IP: xxx.xx.92.200
+        HeartbeatPort: 9354
+               BePort: 9360
+             HttpPort: 8338
+             BrpcPort: 8360
+        LastStartTime: 2023-04-21 09:56:10
+        LastHeartbeat: 2023-04-21 09:56:10
+                Alive: true
+ SystemDecommissioned: false
+ClusterDecommissioned: false
+            TabletNum: 2199
+     DataUsedCapacity: 0.000 
+        AvailCapacity: 584.578 GB
+        TotalCapacity: 1.968 TB
+              UsedPct: 71.00 %
+       MaxDiskUsedPct: 71.00 %
+               ErrMsg: 
+              Version: BRANCH-3.0-RELEASE-8eb8705
+               Status: {"lastSuccessReportTabletsTime":"N/A"}
+    DataTotalCapacity: 584.578 GB
+          DataUsedPct: 0.00 %
+             CpuCores: 16
+    NumRunningQueries: 0
+           MemUsedPct: 0.52 %
+           CpuUsedPct: 0.0 %
+```
+
+| **返回**              | **说明**                                                     |
+| --------------------- | ------------------------------------------------------------ |
+| BackendId             | BE 节点 ID。                                                 |
+| IP                    | BE 节点 IP 地址。                                            |
+| HeartbeatPort         | BE 节点心跳服务端口。                                        |
+| BePort                | BE 节点 Thrift Server 端口。                                 |
+| HttpPort              | BE 节点 HTTP Server 端口。                                   |
+| BrpcPort              | BE 节点 bRPC 端口。                                          |
+| LastStartTime         | BE 节点上一次启动时间。                                      |
+| LastHeartbeat         | BE 节点上一次接受 FE 心跳时间。                              |
+| Alive                 | BE 节点存活状态。                                            |
+| SystemDecommissioned  | BE 节点是否正在下线。                                        |
+| ClusterDecommissioned | BE 节点是否正在集群中下线。                                  |
+| TabletNum             | BE 节点 Tablet 数量。                                        |
+| DataUsedCapacity      | BE 节点被占用的存储空间。                                    |
+| AvailCapacity         | BE 节点剩余存储空间。                                        |
+| TotalCapacity         | BE 节点总存储空间。                                          |
+| UsedPct               | BE 节点当前存储空间占用比例。                                |
+| MaxDiskUsedPct        | BE 节点最大存储空间占用比例。                                |
+| ErrMsg                | BE 节点错误信息。                                            |
+| Version               | BE 节点 StarRocks 版本。                                     |
+| Status                | BE节点状态信息，包含最近一次 BE 汇报 Tablet 的时间信息。     |
+| DataTotalCapacity     | 数据文件所占用的磁盘空间 + 可用磁盘空间，即 DataUsedCapacity + AvailCapacity。 |
+| DataUsedPct           | 数据文件占用磁盘的比例，即 DataUsedCapacity/DataTotalCapacity。 |
+| CpuCores              | BE 节点 CPU 核数。                                           |
+| NumRunningQueries     | 当前运行中的查询数量。                                            |
+| MemUsedPct            | 当前内存使用占比。                                            |
+| CpuUsedPct            | 当前 CPU 使用占比。                                          |
+
+示例二：查看当前集群的数据库信息。
+
+```Plain
+mysql> SHOW PROC '/dbs';
++---------+------------------------+----------+----------------+--------------------------+---------------------+
+| DbId    | DbName                 | TableNum | Quota          | LastConsistencyCheckTime | ReplicaQuota        |
++---------+------------------------+----------+----------------+--------------------------+---------------------+
+| 1       | information_schema     | 22       | 8388608.000 TB | NULL                     | 9223372036854775807 |
+| 840997  | tpcds_100g             | 25       | 1024.000 GB    | NULL                     | 1073741824          |
+| 1275196 | _statistics_           | 3        | 8388608.000 TB | 2022-09-06 23:00:58      | 9223372036854775807 |
+| 1286207 | tpcds_n                | 24       | 8388608.000 TB | NULL                     | 9223372036854775807 |
+| 1381289 | test                   | 6        | 8388608.000 TB | 2022-01-14 23:10:18      | 9223372036854775807 |
+| 6186781 | test_stddev            | 1        | 8388608.000 TB | 2022-09-06 23:00:58      | 9223372036854775807 |
++---------+------------------------+----------+----------------+--------------------------+---------------------+
+```
+
+| **返回**                 | **说明**                     |
+| ------------------------ | ---------------------------- |
+| DbId                     | 数据库 ID。                  |
+| DbName                   | 数据库名称。                 |
+| TableNum                 | 数据库包含表数量。           |
+| Quota                    | 数据库设置的存储配额。       |
+| LastConsistencyCheckTime | 数据库上一次一致性检查时间。 |
+| ReplicaQuota             | 数据库的副本配额。           |
+
+示例三：查看当前集群的作业信息。您可以通过对应的 `DbId` 进一步查询该数据库中的详细作业信息。
+
+```Plain
+mysql> SHOW PROC '/jobs';
++-------+--------------------------------------+
+| DbId  | DbName                               |
++-------+--------------------------------------+
+| 10005 | default_cluster:_statistics_         |
+| 0     | default_cluster:information_schema   |
+| 12711 | default_cluster:starrocks_audit_db__ |
++-------+--------------------------------------+
+3 rows in set (0.00 sec)
+
+mysql> SHOW PROC '/jobs/10005';
++---------------+---------+---------+----------+-----------+-------+
+| JobType       | Pending | Running | Finished | Cancelled | Total |
++---------------+---------+---------+----------+-----------+-------+
+| load          | 0       | 0       | 3        | 0         | 3     |
+| rollup        | 0       | 0       | 0        | 0         | 0     |
+| schema_change | 0       | 0       | 0        | 0         | 0     |
+| export        | 0       | 0       | 0        | 0         | 0     |
++---------------+---------+---------+----------+-----------+-------+
+4 rows in set (0.00 sec)
+```
+
+| **返回**  | **说明**         |
+| --------- | ---------------- |
+| DbId      | 数据库 ID。      |
+| DbName    | 数据库名称。     |
+| JobType   | 作业类型。       |
+| Pending   | 待执行作业数。   |
+| Running   | 正在执行作业数。 |
+| Finished  | 已完成作业数。   |
+| Cancelled | 已取消作业数。   |
+| Total     | 总作业数。       |
+
+示例四：查看当前集群各数据库的统计信息。
+
+```Plain
+mysql> SHOW PROC '/statistic';
++--------+----------------------------------------------------------+----------+--------------+----------+-----------+------------+--------------------+-----------------------+------------------+---------------------+
+| DbId   | DbName                                                   | TableNum | PartitionNum | IndexNum | TabletNum | ReplicaNum | UnhealthyTabletNum | InconsistentTabletNum | CloningTabletNum | ErrorStateTabletNum |
++--------+----------------------------------------------------------+----------+--------------+----------+-----------+------------+--------------------+-----------------------+------------------+---------------------+
+| 10004  | _statistics_                                             | 3        | 3            | 3        | 30        | 60         | 0                  | 0                     | 0                | 0                   |
+| 1      | information_schema                                       | 0        | 0            | 0        | 0         | 0          | 0                  | 0                     | 0                | 0                   |
+| 92498  | stream_load_test_db_03afc714_b1cb_11ed_a82c_00163e237e98 | 0        | 0            | 0        | 0         | 0          | 0                  | 0                     | 0                | 0                   |
+| 92542  | stream_load_test_db_79876e92_b1da_11ed_b50e_00163e237e98 | 1        | 1            | 1        | 3         | 3          | 0                  | 0                     | 0                | 0                   |
+| 115476 | testdb                                                   | 0        | 0            | 0        | 0         | 0          | 0                  | 0                     | 0                | 0                   |
+| 10002  | zq_test                                                  | 8        | 8            | 8        | 5043      | 7063       | 0                  | 0                     | 0                | 2                   |
+| Total  | 6                                                        | 12       | 12           | 12       | 5076      | 7126       | 0                  | 0                     | 0                | 2                   |
++--------+----------------------------------------------------------+----------+--------------+----------+-----------+------------+--------------------+-----------------------+------------------+---------------------+
+7 rows in set (0.01 sec)
+
+mysql> show proc '/statistic/10002';
++------------------+---------------------+----------------+-------------------+
+| UnhealthyTablets | InconsistentTablets | CloningTablets | ErrorStateTablets |
++------------------+---------------------+----------------+-------------------+
+| []               | []                  | []             | [116703, 116706]  |
++------------------+---------------------+----------------+-------------------+
+```
+
+| **返回**              | **说明**                                    |
+| --------------------- | ------------------------------------------- |
+| DbId                  | 数据库 ID。                                 |
+| DbName                | 数据库名称。                                |
+| TableNum              | 数据库中表的数量。                          |
+| PartitionNum          | 数据库中分区的数量。                        |
+| IndexNum              | 数据库中索引的数量。                        |
+| TabletNum             | 数据库中 Tablet 的数量。                    |
+| ReplicaNum            | 数据库中副本的数量。                        |
+| UnhealthyTabletNum    | 数据重分布过程中还未完成的 Tablet 数量。      |
+| InconsistentTabletNum | 数据库中不一致的 Tablet 数量。              |
+| CloningTabletNum      | 数据库中正在进行 Clone 操作的 Tablet 数量。   |
+| ErrorStateTabletNum   | 主键表中错误状态的 Tablet 数量。          |
+| ErrorStateTablets     | 主键表中错误状态的 Tablet 的 ID。         |
+
+示例五：查看当前集群各种任务类型的总数和失败总数。
+
+```Plain
+mysql> SHOW PROC '/tasks';
++-------------------------+-----------+----------+
+| TaskType                | FailedNum | TotalNum |
++-------------------------+-----------+----------+
+| CREATE                  | 0         | 0        |
+| DROP                    | 0         | 0        |
+| PUSH                    | 0         | 0        |
+| CLONE                   | 0         | 0        |
+| STORAGE_MEDIUM_MIGRATE  | 0         | 0        |
+| ROLLUP                  | 0         | 0        |
+| SCHEMA_CHANGE           | 0         | 0        |
+| CANCEL_DELETE           | 0         | 0        |
+| MAKE_SNAPSHOT           | 0         | 0        |
+| RELEASE_SNAPSHOT        | 0         | 0        |
+| CHECK_CONSISTENCY       | 0         | 0        |
+| UPLOAD                  | 0         | 0        |
+| DOWNLOAD                | 0         | 0        |
+| CLEAR_REMOTE_FILE       | 0         | 0        |
+| MOVE                    | 0         | 0        |
+| REALTIME_PUSH           | 0         | 0        |
+| PUBLISH_VERSION         | 0         | 0        |
+| CLEAR_ALTER_TASK        | 0         | 0        |
+| CLEAR_TRANSACTION_TASK  | 0         | 0        |
+| RECOVER_TABLET          | 0         | 0        |
+| STREAM_LOAD             | 0         | 0        |
+| UPDATE_TABLET_META_INFO | 0         | 0        |
+| ALTER                   | 0         | 0        |
+| INSTALL_PLUGIN          | 0         | 0        |
+| UNINSTALL_PLUGIN        | 0         | 0        |
+| NUM_TASK_TYPE           | 0         | 0        |
+| Total                   | 0         | 0        |
++-------------------------+-----------+----------+
+```
+
+| **返回**  | **说明**     |
+| --------- | ------------ |
+| TaskType  | 任务类型。   |
+| FailedNum | 失败任务数。 |
+| TotalNum  | 总任务数。   |
+
+示例六：查看当前集群的 FE 节点信息。
+
+```Plain
+mysql> SHOW PROC '/frontends';
++----------------------------------+---------------+-------------+----------+-----------+---------+----------+------------+-------+-------+-------------------+---------------+----------+---------------+-----------+---------+
+| Name                             | IP            | EditLogPort | HttpPort | QueryPort | RpcPort | Role     | ClusterId  | Join  | Alive | ReplayedJournalId | LastHeartbeat | IsHelper | ErrMsg        | StartTime | Version |
++----------------------------------+---------------+-------------+----------+-----------+---------+----------+------------+-------+-------+-------------------+---------------+----------+---------------+-----------+---------+
+| xxx.xx.xx.xxx_9009_1600088918395 | xxx.xx.xx.xxx | 9009        | 7390     | 0         | 0       | FOLLOWER | 1747363037 | false | false | 0                 | NULL          | true     | got exception | NULL      | NULL    |
++----------------------------------+---------------+-------------+----------+-----------+---------+----------+------------+-------+-------+-------------------+---------------+----------+---------------+-----------+---------+
+```
+
+| **返回**          | **说明**                                      |
+| ----------------- | --------------------------------------------- |
+| Name              | FE 节点名称。                                 |
+| IP                | FE 节点 IP 地址。                             |
+| EditLogPort       | FE 节点之间的通信端口。                       |
+| HttpPort          | FE 节点 HTTP Server 端口。                    |
+| QueryPort         | FE 节点 MySQL Server 端口。                   |
+| RpcPort           | FE 节点 RPC 端口。                            |
+| Role              | FE 节点角色（Leader、Follower 或 Observer）。 |
+| ClusterId         | 集群 ID。                                     |
+| Join              | FE 节点是否曾加入过集群。                     |
+| Alive             | FE 节点存活状态。                             |
+| ReplayedJournalId | FE 节点已回放过的最大元数据日志 ID。          |
+| LastHeartbeat     | FE 节点上一次发送心跳时间。                   |
+| IsHelper          | FE 节点是否为 BDBJE 的 Helper 节点。          |
+| ErrMsg            | FE 节点错误信息。                             |
+| StartTime         | FE 节点启动时间。                             |
+| Version           | FE 节点 StarRocks 版本。                      |
+
+示例七：查看当前集群的 Broker 节点信息。
+
+```Plain
+mysql> SHOW PROC '/brokers';
++-------------+---------------+------+-------+---------------+---------------------+--------+
+| Name        | IP            | Port | Alive | LastStartTime | LastUpdateTime      | ErrMsg |
++-------------+---------------+------+-------+---------------+---------------------+--------+
+| hdfs_broker | xxx.xx.xx.xxx | 8500 | true  | NULL          | 2022-10-10 16:37:59 |        |
+| hdfs_broker | xxx.xx.xx.xxx | 8500 | true  | NULL          | 2022-10-10 16:37:59 |        |
+| hdfs_broker | xxx.xx.xx.xxx | 8500 | true  | NULL          | 2022-10-10 16:37:59 |        |
++-------------+---------------+------+-------+---------------+---------------------+--------+
+```
+
+| **返回**       | **说明**                                         |
+| -------------- | ------------------------------------------------ |
+| Name           | Broker 节点名称。                                |
+| IP             | Broker 节点 IP 地址。                            |
+| Port           | Broker 节点的 Thrift Server 端口，用于接收请求。 |
+| Alive          | Broker 节点存活状态。                            |
+| LastStartTime  | Broker 节点上一次启动时间。                      |
+| LastUpdateTime | Broker 节点上一次更新时间。                      |
+| ErrMsg         | Broker 节点错误信息。                            |
+
+示例八：查看当前集群的资源信息。
+
+```Plain
+mysql> SHOW PROC '/resources';
++-------------------------+--------------+---------------------+------------------------------+
+| Name                    | ResourceType | Key                 | Value                        |
++-------------------------+--------------+---------------------+------------------------------+
+| hive_resource_stability | hive         | hive.metastore.uris | thrift://xxx.xx.xxx.xxx:9083 |
+| hive2                   | hive         | hive.metastore.uris | thrift://xxx.xx.xx.xxx:9083  |
++-------------------------+--------------+---------------------+------------------------------+
+```
+
+| **返回**     | **说明**     |
+| ------------ | ------------ |
+| Name         | 资源名称。   |
+| ResourceType | 资源类型。   |
+| Key          | 资源关键字。 |
+| Value        | 资源值。     |
+
+示例九：查看当前集群的事务信息。您可以通过对应的 `DbId` 进一步查询该数据库中的详细事务信息。
+
+```Plain
+mysql> SHOW PROC '/transactions';
++-------+--------------------------------------+
+| DbId  | DbName                               |
++-------+--------------------------------------+
+| 10005 | default_cluster:_statistics_         |
+| 12711 | default_cluster:starrocks_audit_db__ |
++-------+--------------------------------------+
+2 rows in set (0.00 sec)
+
+mysql> SHOW PROC '/transactions/10005';
++----------+--------+
+| State    | Number |
++----------+--------+
+| running  | 0      |
+| finished | 4      |
++----------+--------+
+2 rows in set (0.00 sec)
+```
+
+| **返回** | **说明**     |
+| -------- | ------------ |
+| DbId     | 数据库 ID。  |
+| DbName   | 数据库名称。 |
+| State    | 事务状态。   |
+| Number   | 事务数量。   |
+
+示例十：查看当前集群的监控信息。
+
+```Plain
+mysql> SHOW PROC '/monitor';
++------+------+
+| Name | Info |
++------+------+
+| jvm  |      |
++------+------+
+```
+
+| **返回** | **说明**   |
+| -------- | ---------- |
+| Name     | JVM 名称。 |
+| Info     | JVM 信息。 |
+
+示例十一：查看当前集群的负载信息。
+
+```Plain
+mysql> SHOW PROC '/cluster_balance';
++-------------------+--------+
+| Item              | Number |
++-------------------+--------+
+| cluster_load_stat | 1      |
+| working_slots     | 3      |
+| sched_stat        | 1      |
+| priority_repair   | 0      |
+| pending_tablets   | 2001   |
+| running_tablets   | 0      |
+| history_tablets   | 1000   |
++-------------------+--------+
+```
+
+| **返回** | **说明**                                     |
+| -------- | -------------------------------------------- |
+| Item     | cluster_balance 中的子命令。<ul><li>cluster_load_stat: 集群当前的负载状态。</li><li>working_slots: 当前可用的工作插槽数。</li><li>sched_stat: 调度系统的当前状态。</li><li>priority_repair: 当前需要优先处理的 Tablet 修复任务数。</li><li>pending_tablets: 当前等待处理的 Tablet 数量。</li><li>running_tablets: 当前正在修复的 Tablet 数量。</li><li>history_tablets: 历史上修复过的 Tablet 数量。</li></ul>                 |
+| Number   | cluster_balance 中每个子命令正在执行的个数。 |
+
+示例十二：查看当前集群的 Colocate Join Group 信息。
+
+```Plain
+mysql> SHOW PROC '/colocation_group';
++-----------------+----------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------+------------+----------------+-------------+----------+
+| GroupId         | GroupName                  | TableIds                                                                                                                                          | BucketsNum | ReplicationNum | DistCols    | IsStable |
++-----------------+----------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------+------------+----------------+-------------+----------+
+| 24010.177354    | 24010_lineitem_str_g1      | 177672                                                                                                                                            | 12         | 1              | varchar(-1) | true     |
+| 24010.182146    | 24010_lineitem_str_g2      | 182144                                                                                                                                            | 192        | 1              | varchar(-1) | true     |
+| 1439318.1735496 | 1439318_group_agent_uid    | 1735677, 1738390                                                                                                                                  | 12         | 2              | bigint(20)  | true     |
+| 24010.37804     | 24010_gsdaf2449s9e         | 37802                                                                                                                                             | 192        | 1              | int(11)     | true     |
+| 174844.175370   | 174844_groupa4             | 175368, 591307, 591362, 591389, 591416                                                                                                            | 12         | 1              | int(11)     | true     |
+| 24010.30587     | 24010_group2               | 30585, 30669                                                                                                                                      | 12         | 1              | int(11)     | true     |
+| 10005.181366    | 10005_lineorder_str_normal | 181364                                                                                                                                            | 192        | 1              | varchar(-1) | true     |
+| 1904968.5973175 | 1904968_groupa2            | 5973173                                                                                                                                           | 12         | 1              | int(11)     | true     |
+| 24010.182535    | 24010_lineitem_str_g3      | 182533                                                                                                                                            | 192        | 1              | varchar(-1) | true     |
++-----------------+----------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------+------------+----------------+-------------+----------+
+```
+
+| **返回**       | **说明**                              |
+| -------------- | ------------------------------------- |
+| GroupId        | Colocate Join Group 的 ID。           |
+| GroupName      | Colocate Join Group 的名称。          |
+| TableIds       | Colocate Join Group 所包含的表的 ID。 |
+| BucketsNum     | Colocate Join Group 的分桶数。        |
+| ReplicationNum | Colocate Join Group 的副本数。        |
+| DistCols       | Colocate Join Group 的分桶列类型。    |
+| IsStable       | Colocate Join Group 是否稳定。        |
+
+示例十三：查看当前集群的 Catalog 信息。
+
+```Plain
+mysql> SHOW PROC '/catalog';
++--------------------------------------------------------------+----------+----------------------+
+| Catalog                                                      | Type     | Comment              |
++--------------------------------------------------------------+----------+----------------------+
+| resource_mapping_inside_catalog_hive_hive2                   | hive     | mapping hive catalog |
+| resource_mapping_inside_catalog_hive_hive_resource_stability | hive     | mapping hive catalog |
+| default_catalog                                              | Internal | Internal Catalog     |
++--------------------------------------------------------------+----------+----------------------+
+```
+
+| **返回** | **说明**       |
+| -------- | -------------- |
+| Catalog  | Catalog 名称。 |
+| Type     | Catalog 类型。 |
+| Comment  | Catalog 描述。 |
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROCESSLIST.md b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROCESSLIST.md
new file mode 100644
index 00000000000000..9e7bcbdc65f61a
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROCESSLIST.md
@@ -0,0 +1,59 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW PROCESSLIST
+
+## 功能
+
+展示当前服务器内运行线程执行的操作。当前版本仅支持展示查询任务。
+
+:::tip
+
+该操作不需要权限。
+
+:::
+
+## 语法
+
+```SQL
+SHOW [FULL] PROCESSLIST
+```
+
+## 参数说明
+
+| 参数 | 必选 | 说明                                          |
+| ---- | ---- |---------------------------------------------|
+| FULL | 否   | 如果不指定该参数，则列出 SQL 语句的前 100 个字符。如果指定该参数，则列出完整 SQL 语句。 |
+
+## 返回
+
+| 返回                | 说明                           |
+| ------------------- | ------------------------------ |
+| Id                  | 连接ID                         |
+| User                | 线程所属用户名                 |
+| Host                | 发出语句的客户端的主机名       |
+| Db                  | 线程所属数据库名               |
+| Command             | 线程执行的命令类型             |
+| ConnectionStartTime | 连接开始时间                   |
+| Time                | 线程处于其当前状态的时间（单位：秒） |
+| State               | 线程运行状态                   |
+| Info                | 线程正在执行的语句             |
+
+## 注意事项
+
+如果当前用户为 `root`，则列出所有用户正在运行的线程；否则，仅列出当前用户运行的线程。
+
+## 示例
+
+示例一：通过 `root` 用户查看正在运行的线程。
+
+```Plain
+SHOW PROCESSLIST;
+
++------+------+---------------------+-------+---------+---------------------+------+-------+------------------+
+| Id   | User | Host                | Db    | Command | ConnectionStartTime | Time | State | Info             |
++------+------+---------------------+-------+---------+---------------------+------+-------+------------------+
+|  0   | root | x.x.x.x:xxxx        | tpcds | Query   | 2022-10-09 19:58:25 |    0 | OK    | SHOW PROCESSLIST |
++------+------+---------------------+-------+---------+---------------------+------+-------+------------------+
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_RUNNING_QUERIES.md b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_RUNNING_QUERIES.md
new file mode 100644
index 00000000000000..ca208ca17364e1
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_RUNNING_QUERIES.md
@@ -0,0 +1,46 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW RUNNING QUERIES
+
+## 功能
+
+显示所有正在运行或在查询队列中等待执行的查询的信息。此功能从 v3.1.4 开始支持。
+
+:::tip
+
+该操作不需要权限。
+
+:::
+
+## 语法
+
+```SQL
+SHOW RUNNING QUERIES
+```
+
+## 返回
+
+- `QuerId`：该查询的 Query ID。
+- `ResourceGroupId`：该查询命中的资源组 ID。当没有命中用户定义的资源组时，会显示为 “-”。
+- `StartTime`：该查询开始时间。
+- `PendingTimeout`：PENDING 状态下查询在队列中超时的时间。
+- `QueryTimeout`：该查询超时的时间。
+- `State`：该查询的排队状态。其中，PENDING 表示在队列中；RUNNING 表示正在执行。
+- `Slots`：该查询申请的逻辑资源数量，目前固定为 `1`。
+- `Frontend`：发起该查询的 FE 节点。
+- `FeStartTime`：发起该查询的 FE 节点的启动时间。
+
+## 示例
+
+```Plain
+MySQL [(none)]> SHOW RUNNING QUERIES;
++--------------------------------------+-----------------+---------------------+---------------------+---------------------+-----------+-------+---------------------------------+---------------------+
+| QueryId                              | ResourceGroupId | StartTime           | PendingTimeout      | QueryTimeout        |   State   | Slots | Frontend                        | FeStartTime         |
++--------------------------------------+-----------------+---------------------+---------------------+---------------------+-----------+-------+---------------------------------+---------------------+
+| a46f68c6-3b49-11ee-8b43-00163e10863a | -               | 2023-08-15 16:56:37 | 2023-08-15 17:01:37 | 2023-08-15 17:01:37 |  RUNNING  | 1     | 127.00.00.01_9010_1692069711535 | 2023-08-15 16:37:03 |
+| a6935989-3b49-11ee-935a-00163e13bca3 | 12003           | 2023-08-15 16:56:40 | 2023-08-15 17:01:40 | 2023-08-15 17:01:40 |  RUNNING  | 1     | 127.00.00.02_9010_1692069658426 | 2023-08-15 16:37:03 |
+| a7b5e137-3b49-11ee-8b43-00163e10863a | 12003           | 2023-08-15 16:56:42 | 2023-08-15 17:01:42 | 2023-08-15 17:01:42 |  PENDING  | 1     | 127.00.00.03_9010_1692069711535 | 2023-08-15 16:37:03 |
++--------------------------------------+-----------------+---------------------+---------------------+---------------------+-----------+-------+---------------------------------+---------------------+
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SYNC.md b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SYNC.md
new file mode 100644
index 00000000000000..af4905a1fc089b
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/SYNC.md
@@ -0,0 +1,28 @@
+---
+displayed_sidebar: docs
+---
+
+# SYNC
+
+同步不同 Session 之间的数据一致性。
+
+目前，StarRocks 只能保证同一 Session 内的一致性，也就是说，只有发起数据写入操作的 Session 才能在操作成功后立即读取最新数据。如果想立即从其他 Session 读取最新数据，必须使用 SYNC 语句同步数据一致性。如果不执行该语句，Session 之间通常会有毫秒级的延迟。
+
+:::tip
+
+该操作不需要权限。
+
+:::
+
+## 语法
+
+```SQL
+SYNC
+```
+
+## 示例
+
+```Plain
+mysql> SYNC;
+Query OK, 0 rows affected (0.01 sec)
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/_category_.yml b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/_category_.yml
new file mode 100644
index 00000000000000..026aa7910430db
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/nodes_processes/_category_.yml
@@ -0,0 +1,6 @@
+position: 10 # float position is supported
+label: '节点和进程'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/plan_profile/ANALYZE_PROFILE.md b/docs/zh/sql-reference/sql-statements/cluster-management/plan_profile/ANALYZE_PROFILE.md
new file mode 100644
index 00000000000000..795987aea5ab95
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/plan_profile/ANALYZE_PROFILE.md
@@ -0,0 +1,44 @@
+---
+displayed_sidebar: docs
+---
+
+# ANALYZE PROFILE
+
+## 功能
+
+以 Fragment 为单位分析指定 Query Profile，并以树形结构展示。更多信息，参考 [Query Profile 概述](../../../../administration/query_profile_overview.md)。
+
+此功能自 v3.1 起支持。
+
+> **注意**
+>
+> 该操作需要有指定表的 SELECT 权限。
+
+## 语法
+
+```SQL
+ANALYZE PROFILE FROM '<query_id>', [<plan_node_id>[, ...] ]
+```
+
+## 参数说明
+
+| **参数**     | **说明**                                                     |
+| ------------ | ------------------------------------------------------------ |
+| query_id     | 查询 ID。您可以通过 [SHOW PROFILELIST](SHOW_PROFILELIST.md) 获得。              |
+| plan_node_id | Query Profile 中的计划节点 ID。您可以指定此参数以查看相应计划节点的详细指标。如果未指定此参数，则仅显示所有计划节点的摘要指标。 |
+
+## 示例
+
+示例一：查询 Query Profile，不指定节点 ID。
+
+![img](../../../../_assets/Profile/text_based_profile_without_node_id.jpeg)
+
+示例二：查询 Query Profile，并指定节点 ID 为 `0`。StarRocks 会返回 Node ID 为 `0` 的节点的所有详细指标，并且高亮显示使用占比较高的指标，便于定位问题。
+
+![img](../../../../_assets/Profile/text_based_profile_with_node_id.jpeg)
+
+## 相关 SQL
+
+- [SHOW PROFILELIST](SHOW_PROFILELIST.md)
+- [EXPLAIN ANALYZE](EXPLAIN_ANALYZE.md)
+
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN.md b/docs/zh/sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN.md
new file mode 100644
index 00000000000000..74c1a6ae64ba0b
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN.md
@@ -0,0 +1,437 @@
+---
+displayed_sidebar: docs
+---
+
+# EXPLAIN
+
+## 功能
+
+显示输入查询语句的逻辑或物理执行计划。关于如何分析查询计划，请参考 [分析 Query Plan](../../../../administration/Query_planning.md#分析-query-plan)。
+
+:::tip
+
+该操作不需要权限。
+
+:::
+
+## 语法
+
+```SQL
+EXPLAIN [ LOGICAL | VERBOSE | COSTS ] <query>
+```
+
+:::tip
+
+执行计划详细程度：EXPLAIN LOGICAL < EXPLAIN < EXPLAIN VERBOSE < EXPLAIN COSTS。
+
+通常情况下使用 EXPLAIN 即可，EXPLAIN VERBOSE 和 EXPLAIN COSTS 会打印大量冗余信息，主要用于调试计划。
+
+:::
+
+## 参数说明
+
+| **参数** | **说明**                                                   |
+| -------- | ---------------------------------------------------------- |
+| LOGICAL  | 显示简要的逻辑执行计划。                  |
+| VERBOSE  | 显示详细的逻辑执行计划，包括数据类型，nullable 信息，优化策略等。 |
+| COSTS    | 显示详细的逻辑执行计划，包括统计信息。 |
+| query    | 需要查看执行计划的查询语句。                                  |
+
+## 返回
+
+返回输入查询语句的执行计划。
+
+| **返回**       | **说明**                           |
+| -------------- |----------------------------------|
+| avgRowSize     | 扫描数据行的平均大小。                      |
+| cardinality    | 扫描表的数据总行数。                       |
+| colocate       | 是否为 Colocate 表。                  |
+| numNodes       | 待扫描的节点数。                         |
+| rollup         | 使用的同步物化视图。                       |
+| preaggregation | 预聚合的状态。                          |
+| predicates     | 查询中使用的谓词。                        |
+| column statistics | 列统计信息，依次为MIN,MAX, NULL个数，平均大小，基数 |
+## 示例
+
+### EXPLAIN
+
+```Plain
+MySQL tpcds> explain select 
+    sr_customer_sk as ctr_customer_sk, 
+    sr_store_sk as ctr_store_sk, 
+    sum(SR_RETURN_AMT) as ctr_total_return 
+  from 
+    store_returns, 
+    date_dim 
+  where 
+    sr_returned_date_sk = d_date_sk and d_year = 2000 
+  group by 
+    sr_customer_sk, 
+    sr_store_sk
++-----------------------------------------------------------------------------+
+| Explain String                                                              |
++-----------------------------------------------------------------------------+
+| PLAN FRAGMENT 0                                                             |
+|  OUTPUT EXPRS:5: sr_customer_sk | 9: sr_store_sk | 49: sum                  |
+|   PARTITION: UNPARTITIONED                                                  |
+|                                                                             |
+|   RESULT SINK                                                               |
+|                                                                             |
+|   9:EXCHANGE                                                                |
+|                                                                             |
+| PLAN FRAGMENT 1                                                             |
+|  OUTPUT EXPRS:                                                              |
+|   PARTITION: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk            |
+|                                                                             |
+|   STREAM DATA SINK                                                          |
+|     EXCHANGE ID: 09                                                         |
+|     UNPARTITIONED                                                           |
+|                                                                             |
+|   8:AGGREGATE (merge finalize)                                              |
+|   |  output: sum(49: sum)                                                   |
+|   |  group by: 5: sr_customer_sk, 9: sr_store_sk                            |
+|   |                                                                         |
+|   7:EXCHANGE                                                                |
+|                                                                             |
+| PLAN FRAGMENT 2                                                             |
+|  OUTPUT EXPRS:                                                              |
+|   PARTITION: RANDOM                                                         |
+|                                                                             |
+|   STREAM DATA SINK                                                          |
+|     EXCHANGE ID: 07                                                         |
+|     HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                     |
+|                                                                             |
+|   6:AGGREGATE (update serialize)                                            |
+|   |  STREAMING                                                              |
+|   |  output: sum(12: sr_return_amt)                                         |
+|   |  group by: 5: sr_customer_sk, 9: sr_store_sk                            |
+|   |                                                                         |
+|   5:Project                                                                 |
+|   |  <slot 5> : 5: sr_customer_sk                                           |
+|   |  <slot 9> : 9: sr_store_sk                                              |
+|   |  <slot 12> : 12: sr_return_amt                                          |
+|   |                                                                         |
+|   4:HASH JOIN                                                               |
+|   |  join op: INNER JOIN (BROADCAST)                                        |
+|   |  colocate: false, reason:                                               |
+|   |  equal join conjunct: 3: sr_returned_date_sk = 21: d_date_sk            |
+|   |                                                                         |
+|   |----3:EXCHANGE                                                           |
+|   |                                                                         |
+|   0:OlapScanNode                                                            |
+|      TABLE: store_returns                                                   |
+|      PREAGGREGATION: ON                                                     |
+|      PREDICATES: 3: sr_returned_date_sk IS NOT NULL                         |
+|      partitions=1/1                                                         |
+|      rollup: store_returns                                                  |
+|      tabletRatio=10/10                                                      |
+|      tabletList=10241,10243,10245,10247,10249,10251,10253,10255,10257,10259 |
+|      cardinality=277502                                                     |
+|      avgRowSize=20.0                                                        |
+|                                                                             |
+| PLAN FRAGMENT 3                                                             |
+|  OUTPUT EXPRS:                                                              |
+|   PARTITION: RANDOM                                                         |
+|                                                                             |
+|   STREAM DATA SINK                                                          |
+|     EXCHANGE ID: 03                                                         |
+|     UNPARTITIONED                                                           |
+|                                                                             |
+|   2:Project                                                                 |
+|   |  <slot 21> : 21: d_date_sk                                              |
+|   |                                                                         |
+|   1:OlapScanNode                                                            |
+|      TABLE: date_dim                                                        |
+|      PREAGGREGATION: ON                                                     |
+|      PREDICATES: 27: d_year = 2000                                          |
+|      partitions=1/1                                                         |
+|      rollup: date_dim                                                       |
+|      tabletRatio=5/5                                                        |
+|      tabletList=11543,11545,11547,11549,11551                               |
+|      cardinality=362                                                        |
+|      avgRowSize=8.0                                                         |
++-----------------------------------------------------------------------------+
+79 rows in set
+```
+
+### EXPLAIN LOGICAL
+
+```Plain
+MySQL tpcds> explain logical select 
+    sr_customer_sk as ctr_customer_sk, 
+    sr_store_sk as ctr_store_sk, 
+    sum(SR_RETURN_AMT) as ctr_total_return 
+  from 
+    store_returns, 
+    date_dim 
+  where 
+    sr_returned_date_sk = d_date_sk and d_year = 2000 
+  group by 
+    sr_customer_sk, 
+    sr_store_sk
+ 
++---------------------------------------------------------------------------------------------------------------------------------+
+| Explain String                                                                                                                  |
++---------------------------------------------------------------------------------------------------------------------------------+
+| - Output => [5:sr_customer_sk, 9:sr_store_sk, 49:sum]                                                                           |
+|     - AGGREGATE(GLOBAL) [5:sr_customer_sk, 9:sr_store_sk]                                                                       |
+|             Estimates: {row: 49728, cpu: 795660.58, memory: 795660.58, network: 0.00, cost: 8405375.45}                         |
+|             49:sum := sum(49:sum)                                                                                               |
+|         - EXCHANGE(SHUFFLE) [5, 9]                                                                                              |
+|                 Estimates: {row: 49728, cpu: 79566.06, memory: 0.00, network: 0.00, cost: 6416223.99}                           |
+|             - AGGREGATE(LOCAL) [5:sr_customer_sk, 9:sr_store_sk]                                                                |
+|                     Estimates: {row: 49728, cpu: 119349.09, memory: 79566.06, network: 0.00, cost: 6376440.96}                  |
+|                     49:sum := sum(12:sr_return_amt)                                                                             |
+|                 - HASH/INNER JOIN [3:sr_returned_date_sk = 21:d_date_sk] => [5:sr_customer_sk, 9:sr_store_sk, 12:sr_return_amt] |
+|                         Estimates: {row: 49728, cpu: 6744977.39, memory: 1446.51, network: 0.00, cost: 6157634.30}              |
+|                     - SCAN [store_returns] => [3:sr_returned_date_sk, 5:sr_customer_sk, 9:sr_store_sk, 12:sr_return_amt]        |
+|                             Estimates: {row: 277502, cpu: 5550040.00, memory: 0.00, network: 0.00, cost: 2775020.00}            |
+|                             partitionRatio: 1/1, tabletRatio: 10/10                                                             |
+|                             predicate: 3:sr_returned_date_sk IS NOT NULL                                                        |
+|                     - EXCHANGE(BROADCAST)                                                                                       |
+|                             Estimates: {row: 361, cpu: 1446.51, memory: 1446.51, network: 1446.51, cost: 7232.57}               |
+|                         - SCAN [date_dim] => [21:d_date_sk]                                                                     |
+|                                 Estimates: {row: 361, cpu: 2893.03, memory: 0.00, network: 0.00, cost: 1446.51}                 |
+|                                 partitionRatio: 1/1, tabletRatio: 5/5                                                           |
+|                                 predicate: 27:d_year = 2000                                                                     |
++---------------------------------------------------------------------------------------------------------------------------------+
+21 rows in set
+```
+
+### EXPLAIN VERBOSE
+
+```Plain
+MySQL tpcds> explain verbose select 
+    sr_customer_sk as ctr_customer_sk, 
+    sr_store_sk as ctr_store_sk, 
+    sum(SR_RETURN_AMT) as ctr_total_return 
+  from 
+    store_returns, 
+    date_dim 
+  where 
+    sr_returned_date_sk = d_date_sk and d_year = 2000 
+  group by 
+    sr_customer_sk, 
+    sr_store_sk
+ 
++---------------------------------------------------------------------------------------------------------------------------------------------------------+
+| Explain String                                                                                                                                          |
++---------------------------------------------------------------------------------------------------------------------------------------------------------+
+| RESOURCE GROUP: default_wg                                                                                                                              |
+|                                                                                                                                                         |
+| PLAN FRAGMENT 0(F04)                                                                                                                                    |
+|   Fragment Cost: 0.0                                                                                                                                    |
+|   Output Exprs:5: sr_customer_sk | 9: sr_store_sk | 49: sum                                                                                             |
+|   Input Partition: UNPARTITIONED                                                                                                                        |
+|   RESULT SINK                                                                                                                                           |
+|                                                                                                                                                         |
+|   9:EXCHANGE                                                                                                                                            |
+|      cardinality: 49729                                                                                                                                 |
+|                                                                                                                                                         |
+| PLAN FRAGMENT 1(F03)                                                                                                                                    |
+|   Fragment Cost: 2028934.4876271961                                                                                                                     |
+|                                                                                                                                                         |
+|   Input Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                  |
+|   OutPut Partition: UNPARTITIONED                                                                                                                       |
+|   OutPut Exchange Id: 09                                                                                                                                |
+|                                                                                                                                                         |
+|   8:AGGREGATE (merge finalize)                                                                                                                          |
+|   |  aggregate: sum[([49: sum, DECIMAL128(38,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true]         |
+|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |                                                                                                                                                     |
+|   7:EXCHANGE                                                                                                                                            |
+|      distribution type: SHUFFLE                                                                                                                         |
+|      partition exprs: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                       |
+|      cardinality: 49729                                                                                                                                 |
+|                                                                                                                                                         |
+| PLAN FRAGMENT 2(F00)                                                                                                                                    |
+|   Fragment Cost: 6376440.959353934                                                                                                                      |
+|                                                                                                                                                         |
+|   Input Partition: RANDOM                                                                                                                               |
+|   OutPut Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                 |
+|   OutPut Exchange Id: 07                                                                                                                                |
+|                                                                                                                                                         |
+|   6:AGGREGATE (update serialize)                                                                                                                        |
+|   |  STREAMING                                                                                                                                          |
+|   |  aggregate: sum[([12: sr_return_amt, DECIMAL64(7,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true] |
+|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |                                                                                                                                                     |
+|   5:Project                                                                                                                                             |
+|   |  output columns:                                                                                                                                    |
+|   |  5 <-> [5: sr_customer_sk, INT, true]                                                                                                               |
+|   |  9 <-> [9: sr_store_sk, INT, true]                                                                                                                  |
+|   |  12 <-> [12: sr_return_amt, DECIMAL64(7,2), true]                                                                                                   |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |                                                                                                                                                     |
+|   4:HASH JOIN                                                                                                                                           |
+|   |  join op: INNER JOIN (BROADCAST)                                                                                                                    |
+|   |  equal join conjunct: [3: sr_returned_date_sk, INT, true] = [21: d_date_sk, INT, false]                                                             |
+|   |  build runtime filters:                                                                                                                             |
+|   |  - filter_id = 0, build_expr = (21: d_date_sk), remote = false                                                                                      |
+|   |  output columns: 5, 9, 12                                                                                                                           |
+|   |  can local shuffle: true                                                                                                                            |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |                                                                                                                                                     |
+|   |----3:EXCHANGE                                                                                                                                       |
+|   |       distribution type: BROADCAST                                                                                                                  |
+|   |       cardinality: 362                                                                                                                              |
+|   |                                                                                                                                                     |
+|   0:OlapScanNode                                                                                                                                        |
+|      table: store_returns, rollup: store_returns                                                                                                        |
+|      preAggregation: on                                                                                                                                 |
+|      Predicates: 3: sr_returned_date_sk IS NOT NULL                                                                                                     |
+|      partitionsRatio=1/1, tabletsRatio=10/10                                                                                                            |
+|      tabletList=10241,10243,10245,10247,10249,10251,10253,10255,10257,10259                                                                             |
+|      actualRows=287514, avgRowSize=20.0                                                                                                                 |
+|      cardinality: 277502                                                                                                                                |
+|      probe runtime filters:                                                                                                                             |
+|      - filter_id = 0, probe_expr = (3: sr_returned_date_sk)                                                                                             |
+|                                                                                                                                                         |
+| PLAN FRAGMENT 3(F01)                                                                                                                                    |
+|   Fragment Cost: 1446.5148514851485                                                                                                                     |
+|                                                                                                                                                         |
+|   Input Partition: RANDOM                                                                                                                               |
+|   OutPut Partition: UNPARTITIONED                                                                                                                       |
+|   OutPut Exchange Id: 03                                                                                                                                |
+|                                                                                                                                                         |
+|   2:Project                                                                                                                                             |
+|   |  output columns:                                                                                                                                    |
+|   |  21 <-> [21: d_date_sk, INT, false]                                                                                                                 |
+|   |  cardinality: 362                                                                                                                                   |
+|   |                                                                                                                                                     |
+|   1:OlapScanNode                                                                                                                                        |
+|      table: date_dim, rollup: date_dim                                                                                                                  |
+|      preAggregation: on                                                                                                                                 |
+|      Predicates: [27: d_year, INT, false] = 2000                                                                                                        |
+|      partitionsRatio=1/1, tabletsRatio=5/5                                                                                                              |
+|      tabletList=11543,11545,11547,11549,11551                                                                                                           |
+|      actualRows=73049, avgRowSize=8.0                                                                                                                   |
+|      cardinality: 362                                                                                                                                   |
++---------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
+
+### EXPLAIN COSTS
+
+```Plain
++---------------------------------------------------------------------------------------------------------------------------------------------------------+
+| Explain String                                                                                                                                          |
++---------------------------------------------------------------------------------------------------------------------------------------------------------+
+| PLAN FRAGMENT 0(F04)                                                                                                                                    |
+|   Output Exprs:5: sr_customer_sk | 9: sr_store_sk | 49: sum                                                                                             |
+|   Input Partition: UNPARTITIONED                                                                                                                        |
+|   RESULT SINK                                                                                                                                           |
+|                                                                                                                                                         |
+|   9:EXCHANGE                                                                                                                                            |
+|      cardinality: 49729                                                                                                                                 |
+|                                                                                                                                                         |
+| PLAN FRAGMENT 1(F03)                                                                                                                                    |
+|                                                                                                                                                         |
+|   Input Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                  |
+|   OutPut Partition: UNPARTITIONED                                                                                                                       |
+|   OutPut Exchange Id: 09                                                                                                                                |
+|                                                                                                                                                         |
+|   8:AGGREGATE (merge finalize)                                                                                                                          |
+|   |  aggregate: sum[([49: sum, DECIMAL128(38,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true]         |
+|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |  column statistics:                                                                                                                                 |
+|   |  * sr_customer_sk-->[1.0, 100000.0, 2.010867271218169E-5, 4.0, 49728.786461450894] ESTIMATE                                                         |
+|   |  * sr_store_sk-->[1.0, 10.0, 0.14285714285714285, 4.0, 6.0] ESTIMATE                                                                                |
+|   |  * sum-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                                    |
+|   |                                                                                                                                                     |
+|   7:EXCHANGE                                                                                                                                            |
+|      distribution type: SHUFFLE                                                                                                                         |
+|      partition exprs: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                       |
+|      cardinality: 49729                                                                                                                                 |
+|                                                                                                                                                         |
+| PLAN FRAGMENT 2(F00)                                                                                                                                    |
+|                                                                                                                                                         |
+|   Input Partition: RANDOM                                                                                                                               |
+|   OutPut Partition: HASH_PARTITIONED: 5: sr_customer_sk, 9: sr_store_sk                                                                                 |
+|   OutPut Exchange Id: 07                                                                                                                                |
+|                                                                                                                                                         |
+|   6:AGGREGATE (update serialize)                                                                                                                        |
+|   |  STREAMING                                                                                                                                          |
+|   |  aggregate: sum[([12: sr_return_amt, DECIMAL64(7,2), true]); args: DECIMAL64; result: DECIMAL128(38,2); args nullable: true; result nullable: true] |
+|   |  group by: [5: sr_customer_sk, INT, true], [9: sr_store_sk, INT, true]                                                                              |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |  column statistics:                                                                                                                                 |
+|   |  * sr_customer_sk-->[1.0, 100000.0, 2.010867271218169E-5, 4.0, 49728.786461450894] ESTIMATE                                                         |
+|   |  * sr_store_sk-->[1.0, 10.0, 0.14285714285714285, 4.0, 6.0] ESTIMATE                                                                                |
+|   |  * sum-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                                    |
+|   |                                                                                                                                                     |
+|   5:Project                                                                                                                                             |
+|   |  output columns:                                                                                                                                    |
+|   |  5 <-> [5: sr_customer_sk, INT, true]                                                                                                               |
+|   |  9 <-> [9: sr_store_sk, INT, true]                                                                                                                  |
+|   |  12 <-> [12: sr_return_amt, DECIMAL64(7,2), true]                                                                                                   |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |  column statistics:                                                                                                                                 |
+|   |  * sr_customer_sk-->[1.0, 100000.0, 0.034836564480338346, 4.0, 49728.786461450894] ESTIMATE                                                         |
+|   |  * sr_store_sk-->[1.0, 10.0, 0.034996556689413386, 4.0, 6.0] ESTIMATE                                                                               |
+|   |  * sr_return_amt-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                          |
+|   |                                                                                                                                                     |
+|   4:HASH JOIN                                                                                                                                           |
+|   |  join op: INNER JOIN (BROADCAST)                                                                                                                    |
+|   |  equal join conjunct: [3: sr_returned_date_sk, INT, true] = [21: d_date_sk, INT, false]                                                             |
+|   |  build runtime filters:                                                                                                                             |
+|   |  - filter_id = 0, build_expr = (21: d_date_sk), remote = false                                                                                      |
+|   |  output columns: 5, 9, 12                                                                                                                           |
+|   |  can local shuffle: true                                                                                                                            |
+|   |  cardinality: 49729                                                                                                                                 |
+|   |  column statistics:                                                                                                                                 |
+|   |  * sr_returned_date_sk-->[2450820.0, 2452822.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                               |
+|   |  * sr_customer_sk-->[1.0, 100000.0, 0.034836564480338346, 4.0, 49728.786461450894] ESTIMATE                                                         |
+|   |  * sr_store_sk-->[1.0, 10.0, 0.034996556689413386, 4.0, 6.0] ESTIMATE                                                                               |
+|   |  * sr_return_amt-->[0.0, 16917.12, 0.034878301578357924, 8.0, 49728.786461450894] ESTIMATE                                                          |
+|   |  * d_date_sk-->[2450820.0, 2452822.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                                         |
+|   |                                                                                                                                                     |
+|   |----3:EXCHANGE                                                                                                                                       |
+|   |       distribution type: BROADCAST                                                                                                                  |
+|   |       cardinality: 362                                                                                                                              |
+|   |                                                                                                                                                     |
+|   0:OlapScanNode                                                                                                                                        |
+|      table: store_returns, rollup: store_returns                                                                                                        |
+|      preAggregation: on                                                                                                                                 |
+|      Predicates: 3: sr_returned_date_sk IS NOT NULL                                                                                                     |
+|      partitionsRatio=1/1, tabletsRatio=10/10                                                                                                            |
+|      tabletList=10241,10243,10245,10247,10249,10251,10253,10255,10257,10259                                                                             |
+|      actualRows=287514, avgRowSize=20.0                                                                                                                 |
+|      cardinality: 277502                                                                                                                                |
+|      probe runtime filters:                                                                                                                             |
+|      - filter_id = 0, probe_expr = (3: sr_returned_date_sk)                                                                                             |
+|      column statistics:                                                                                                                                 |
+|      * sr_returned_date_sk-->[2450820.0, 2452822.0, 0.0, 4.0, 2018.0] ESTIMATE                                                                          |
+|      * sr_customer_sk-->[1.0, 100000.0, 0.034836564480338346, 4.0, 86524.0] ESTIMATE                                                                    |
+|      * sr_store_sk-->[1.0, 10.0, 0.034996556689413386, 4.0, 6.0] ESTIMATE                                                                               |
+|      * sr_return_amt-->[0.0, 16917.12, 0.034878301578357924, 8.0, 113968.0] ESTIMATE                                                                    |
+|                                                                                                                                                         |
+| PLAN FRAGMENT 3(F01)                                                                                                                                    |
+|                                                                                                                                                         |
+|   Input Partition: RANDOM                                                                                                                               |
+|   OutPut Partition: UNPARTITIONED                                                                                                                       |
+|   OutPut Exchange Id: 03                                                                                                                                |
+|                                                                                                                                                         |
+|   2:Project                                                                                                                                             |
+|   |  output columns:                                                                                                                                    |
+|   |  21 <-> [21: d_date_sk, INT, false]                                                                                                                 |
+|   |  cardinality: 362                                                                                                                                   |
+|   |  column statistics:                                                                                                                                 |
+|   |  * d_date_sk-->[2415022.0, 2488070.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                                         |
+|   |                                                                                                                                                     |
+|   1:OlapScanNode                                                                                                                                        |
+|      table: date_dim, rollup: date_dim                                                                                                                  |
+|      preAggregation: on                                                                                                                                 |
+|      Predicates: [27: d_year, INT, false] = 2000                                                                                                        |
+|      partitionsRatio=1/1, tabletsRatio=5/5                                                                                                              |
+|      tabletList=11543,11545,11547,11549,11551                                                                                                           |
+|      actualRows=73049, avgRowSize=8.0                                                                                                                   |
+|      cardinality: 362                                                                                                                                   |
+|      column statistics:                                                                                                                                 |
+|      * d_date_sk-->[2415022.0, 2488070.0, 0.0, 4.0, 361.6287128712871] ESTIMATE                                                                         |
+|      * d_year-->[2000.0, 2000.0, 0.0, 4.0, 202.0] ESTIMATE                                                                                              |
++---------------------------------------------------------------------------------------------------------------------------------------------------------+
+114 rows in set
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN_ANALYZE.md b/docs/zh/sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN_ANALYZE.md
new file mode 100644
index 00000000000000..8eabba2a0d620b
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN_ANALYZE.md
@@ -0,0 +1,44 @@
+---
+displayed_sidebar: docs
+---
+
+# EXPLAIN ANALYZE
+
+## 功能
+
+执行指定 SQL，并显示相应的 Query Profile 文件。更多信息，参考 [Query Profile 概述](../../../../administration/query_profile_overview.md)。
+
+此功能自 v3.1 起支持。
+
+> **注意**
+>
+> 该操作需要有指定表的 SELECT 或 INSERT 权限。
+
+## 语法
+
+```SQL
+EXPLAIN ANALYZE <statement>
+```
+
+## 参数说明
+
+`statement`：需要查询 Query Profile 的 SQL 语句。支持 [SELECT](../../table_bucket_part_index/SELECT.md) 和 [INSERT INTO](../../loading_unloading/INSERT.md)。
+
+## 使用说明
+
+请注意，当您模拟并分析 INSERT INTO 语句的 Query Profile 时，实际上不会导入任何数据。默认情况下，导入事务会被强制回滚，以确保在分析过程中不会对数据进行意外更改。
+
+## 示例
+
+示例一：模拟分析 SELECT 语句，查询返回结果会被丢弃。
+
+![img](../../../../_assets/Profile/text_based_explain_analyze_select.jpeg)
+
+示例二：模拟分析 INSERT INTO 语句。执行结束后，导入事务会被强制回滚，数据不会被实际导入。
+
+![img](../../../../_assets/Profile/text_based_explain_analyze_insert.jpeg)
+
+## 相关 SQL
+
+- [SHOW PROFILELIST](SHOW_PROFILELIST.md)
+- [ANALYZE PROFILE](./EXPLAIN_ANALYZE.md)
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/plan_profile/SHOW_PROFILELIST.md b/docs/zh/sql-reference/sql-statements/cluster-management/plan_profile/SHOW_PROFILELIST.md
new file mode 100644
index 00000000000000..6f1b0131f43077
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/plan_profile/SHOW_PROFILELIST.md
@@ -0,0 +1,47 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW PROFILELIST
+
+## 功能
+
+列出 StarRocks 集群中缓存的 Query Profile 记录。更多信息，参考 [Query Profile 概述](../../../../administration/query_profile_overview.md)。
+
+此功能自 v3.1 起支持。
+
+该操作无需任何权限。
+
+## 语法
+
+```SQL
+SHOW PROFILELIST [LIMIT n]
+```
+
+## 参数说明
+
+`LIMIT n`：列出最新 n 条记录。
+
+## 返回
+
+| **返回**  | **说明**                                                     |
+| --------- | ------------------------------------------------------------ |
+| QueryId   | 查询 ID。                                                    |
+| StartTime | 查询开始时间。                                               |
+| Time      | 查询时长。                                                   |
+| State     | 查询状态，其中包括`Error`：查询异常。`Finished`：查询执行结束。`Running`：查询正在执行。 |
+| Statement | 查询对应 SQL。                                               |
+
+## 示例
+
+示例一：列出最新 5 条 Query Profile 记录。
+
+```SQL
+SHOW PROFILELIST LIMIT 5;
+```
+
+## 相关 SQL
+
+- [ANALYZE PROFILE](ANALYZE_PROFILE.md)
+- [EXPLAIN ANALYZE](EXPLAIN_ANALYZE.md)
+
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/plan_profile/_category_.yml b/docs/zh/sql-reference/sql-statements/cluster-management/plan_profile/_category_.yml
new file mode 100644
index 00000000000000..209b1a2ca296f2
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/plan_profile/_category_.yml
@@ -0,0 +1,6 @@
+position: 90 # float position is supported
+label: '执行计划和 Profile'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/plugin/INSTALL_PLUGIN.md b/docs/zh/sql-reference/sql-statements/cluster-management/plugin/INSTALL_PLUGIN.md
new file mode 100644
index 00000000000000..73897e8ab25047
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/plugin/INSTALL_PLUGIN.md
@@ -0,0 +1,59 @@
+---
+displayed_sidebar: docs
+---
+
+# INSTALL PLUGIN
+
+## 功能
+
+该语句用于安装一个插件。
+
+:::tip
+
+该操作需要 SYSTEM 级 PLUGIN 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```sql
+INSTALL PLUGIN FROM [source] [PROPERTIES ("key"="value", ...)]
+```
+
+**source 支持三种类型：**
+
+```plain text
+1. 指向一个 zip 文件的绝对路径。
+2. 指向一个插件目录的绝对路径。
+3. 指向一个 http 或 https 协议的 zip 文件下载路径。
+```
+
+**PROPERTIES：**
+
+支持设置插件的一些配置，如设置 zip 文件的 md5sum 的值等。
+
+## 示例
+
+1. 安装一个本地 zip 文件插件：
+
+    ```sql
+    INSTALL PLUGIN FROM "/home/users/starrocks/auditdemo.zip";
+    ```
+
+2. 安装一个本地目录中的插件：
+
+    ```sql
+    INSTALL PLUGIN FROM "/home/users/starrocks/auditdemo/";
+    ```
+
+3. 下载并安装一个插件：
+
+    ```sql
+    INSTALL PLUGIN FROM "http://mywebsite.com/plugin.zip";
+    ```
+
+4. 下载并安装一个插件，同时设置了 zip 文件的 md5sum 的值：
+
+    ```sql
+    INSTALL PLUGIN FROM "http://mywebsite.com/plugin.zip" PROPERTIES("md5sum" = "73877f6029216f4314d712086a146570");
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/plugin/SHOW_PLUGINS.md b/docs/zh/sql-reference/sql-statements/cluster-management/plugin/SHOW_PLUGINS.md
new file mode 100644
index 00000000000000..8dd10cb73069b8
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/plugin/SHOW_PLUGINS.md
@@ -0,0 +1,31 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW PLUGINS
+
+## 功能
+
+该语句用于展示已安装的插件。
+
+:::tip
+
+该操作需要 SYSTEM 级 PLUGIN 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```sql
+SHOW PLUGINS
+```
+
+该命令会展示所有用户安装的和系统内置的插件。
+
+## 示例
+
+1. 展示已安装的插件：
+
+    ```sql
+    SHOW PLUGINS;
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/plugin/UNINSTALL_PLUGIN.md b/docs/zh/sql-reference/sql-statements/cluster-management/plugin/UNINSTALL_PLUGIN.md
new file mode 100644
index 00000000000000..ca0d2dc907c8c3
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/plugin/UNINSTALL_PLUGIN.md
@@ -0,0 +1,33 @@
+---
+displayed_sidebar: docs
+---
+
+# UNINSTALL PLUGIN
+
+## 功能
+
+该语句用于卸载一个插件。
+
+:::tip
+
+该操作需要 SYSTEM 级 PLUGIN 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```SQL
+UNINSTALL PLUGIN plugin_name
+```
+
+plugin_name 可以通过 `SHOW PLUGINS;` 命令查看。
+
+只能卸载非 builtin 的插件。
+
+## 示例
+
+1. 卸载一个插件：
+
+    ```SQL
+    UNINSTALL PLUGIN auditdemo;
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/plugin/_category_.yml b/docs/zh/sql-reference/sql-statements/cluster-management/plugin/_category_.yml
new file mode 100644
index 00000000000000..238c4a9ef904ba
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/plugin/_category_.yml
@@ -0,0 +1,6 @@
+position: 80 # float position is supported
+label: '插件'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/ALTER_RESOURCE_GROUP.md b/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/ALTER_RESOURCE_GROUP.md
new file mode 100644
index 00000000000000..a91f3f8e3caff8
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/ALTER_RESOURCE_GROUP.md
@@ -0,0 +1,65 @@
+---
+keywords: ['xiugai'] 
+displayed_sidebar: docs
+---
+
+# ALTER RESOURCE GROUP
+
+## 功能
+
+修改资源组设置。
+
+:::tip
+
+该操作需要对应 Resource Group 的 ALTER 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```SQL
+ALTER RESOURCE GROUP <resource_group_name>
+{  ADD CLASSIFIER1, CLASSIFIER2, ...
+ | DROP (CLASSIFIER_ID_1, CLASSIFIER_ID_2, ...)
+ | DROP ALL
+ | WITH resource_limit 
+}
+```
+
+## 参数说明
+
+| **参数**            | **说明**                                                     |
+| ------------------- | ------------------------------------------------------------ |
+| resource_group_name | 待修改的资源组名。                                           |
+| ADD                 | 为资源组添加分类器。关于分类器参数具体信息，请见 [CREATE RESOURCE GROUP - 参数说明](CREATE_RESOURCE_GROUP.md)。 |
+| DROP                | 通过分类器 ID 为资源组删除对应分类器。您可以通过 [SHOW RESOURCE GROUP](SHOW_RESOURCE_GROUP.md) 语句查看分类器 ID。 |
+| DROP ALL            | 为资源组删除所有分类器。                                     |
+| WITH                | 为资源组修改资源限制。关于资源限制参数具体信息，请见 [CREATE RESOURCE GROUP - 参数说明](CREATE_RESOURCE_GROUP.md)。 |
+
+## 示例
+
+示例一：为资源组 `rg1` 添加新的分类器。
+
+```SQL
+ALTER RESOURCE GROUP rg1 ADD (user='root', query_type in ('select'));
+```
+
+示例二：为资源组 `rg1` 删除 ID 为 `300040`，`300041` 以及 `300041` 的分类器。
+
+```SQL
+ALTER RESOURCE GROUP rg1 DROP (300040, 300041, 300041);
+```
+
+示例三：为资源组 `rg1` 删除所有分类器。
+
+```SQL
+ALTER RESOURCE GROUP rg1 DROP ALL;
+```
+
+示例四：修改资源组 `rg1` 的资源限制。
+
+```SQL
+ALTER RESOURCE GROUP rg1 WITH (
+    'cpu_core_limit' = '20'
+);
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/CREATE_RESOURCE_GROUP.md b/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/CREATE_RESOURCE_GROUP.md
new file mode 100644
index 00000000000000..1f2a6887c38254
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/CREATE_RESOURCE_GROUP.md
@@ -0,0 +1,77 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE RESOURCE GROUP
+
+## 功能
+
+创建资源组。关于资源组的更多信息，参见[资源隔离](../../../../administration/management/resource_management/resource_group.md)。
+
+:::tip
+
+该操作需要 SYSTEM 级 CREATE RESOURCE GROUP 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```SQL
+CREATE RESOURCE GROUP resource_group_name
+TO CLASSIFIER1, CLASSIFIER2, ...
+WITH resource_limit
+```
+
+## 参数说明
+
+- `resource_group_name`：需要创建的资源组名称。
+
+- `CLASSIFIER`：用于区分需要被施加资源限制的查询的分类器，采用 `"key"="value"` 对形式。您可以为同一个资源组设置多个分类器。
+
+  - 分类器可以包含以下参数：
+
+    | **参数**   | **必选** | **说明**                                            |
+    | ---------- | -------- | --------------------------------------------------- |
+    | user       | 否       | 用户名。                                            |
+    | role       | 否       | 用户所属角色名。                                    |
+    | query_type | 否       | 需要被施加资源限制的查询类型，目前支持 `SELECT` 与 `INSERT` (2.5 及以后)。当 `query_type` 为 `insert` 的资源组有导入任务正在运行时，当前 BE 节点会为其预留相应的计算资源。 |
+    | source_ip  | 否       | 发起查询的 IP 地址，类型为 CIDR。                   |
+    | db         | 否       | 查询所访问的数据库，可以为逗号（,）分割的字符串。   |
+    | plan_cpu_cost_range | 否     | 估计的查询 CPU 开销范围。该值与 **fe.audit.log** 中的 `PlanCpuCost` 字段含义相同，无单位。格式为 `[DOUBLE, DOUBLE)`。默认为 NULL，表示没有该限制。自 v3.1.4 起支持。                   |
+    | plan_mem_cost_range | 否     | 估计的查询内存开销范围。该值与 **fe.audit.log** 中的 `PlanMemCost` 字段含义相同，无单位。格式为 `[DOUBLE, DOUBLE)`。默认为 NULL，表示没有该限制。自 v3.1.4 起支持。                |
+
+- `resource_limit`：为当前资源组设置的资源限制，采用 `"key"="value"` 对形式。您可以为同一个资源组设置多个资源限制。
+
+  - 资源限制可以包含以下参数：
+
+    | **参数**                   | **必选** | **说明**                                                     |
+    | -------------------------- | -------- | ------------------------------------------------------------ |
+    | cpu_core_limit             | 否       | 该资源组在当前 BE 节点可使用的 CPU 核数软上限，实际使用的 CPU 核数会根据节点资源空闲程度按比例弹性伸缩。取值为正整数。 |
+    | mem_limit                  | 否       | 该资源组在当前 BE 节点可使用于查询的内存（query_pool）占总内存的百分比（%）。取值范围为 (0,1)。 |
+    | concurrency_limit          | 否       | 资源组中并发查询数的上限，用以防止并发查询提交过多而导致的过载。 |
+    | max_cpu_cores              | 否       | 资源组在单个 BE 节点中使用的 CPU 核数上限。仅在设置为大于 `0` 后生效。取值范围：[0, `avg_be_cpu_cores`]，其中 `avg_be_cpu_cores` 表示所有 BE 的 CPU 核数的平均值。默认值为 0。自 v3.1.4 起支持。 |
+    | big_query_cpu_second_limit | 否       | 大查询任务可以使用 CPU 的时间上限，其中的并行任务将累加 CPU 使用时间。单位为秒。 |
+    | big_query_scan_rows_limit  | 否       | 大查询任务可以扫描的行数上限。                               |
+    | big_query_mem_limit        | 否       | 大查询任务可以使用的内存上限。单位为 Byte。                  |
+    | type                       | 否       | 资源组类型。有效取值包括：<br />`short_query`：当 `short_query` 资源组有查询正在运行时，当前 BE 节点会为其预留 `short_query.cpu_core_limit` 的 CPU 资源，所有 `normal` 资源组的总 CPU 核数使用上限会被硬限制为 BE 节点核数减 `short_query.cpu_core_limit`。<br />`normal`：当 `short_query` 资源组没有查询正在运行时，所有 `normal` 资源组的 CPU 核数没有硬限制。<br />注意：同一集群中，您最多只能创建一个 `short_query` 资源组。 |
+
+## 示例
+
+示例一：基于多个分类器创建资源组 `rg1`。
+
+```SQL
+CREATE RESOURCE GROUP rg1
+TO 
+    (user='rg1_user1', role='rg1_role1', query_type in ('select'), source_ip='192.168.x.x/24'),
+    (user='rg1_user2', query_type in ('select'), source_ip='192.168.x.x/24'),
+    (user='rg1_user3', source_ip='192.168.x.x/24'),
+    (user='rg1_user4'),
+    (db='db1')
+WITH ('cpu_core_limit' = '10',
+      'mem_limit' = '20%',
+      'type' = 'normal',
+      'big_query_cpu_second_limit' = '100',
+      'big_query_scan_rows_limit' = '100000',
+      'big_query_mem_limit' = '1073741824'
+);
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/DROP_RESOURCE_GROUP.md b/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/DROP_RESOURCE_GROUP.md
new file mode 100644
index 00000000000000..399fb38ee17c2d
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/DROP_RESOURCE_GROUP.md
@@ -0,0 +1,35 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP RESOURCE GROUP
+
+## 功能
+
+删除指定资源组。
+
+:::tip
+
+该操作需要对应 Resource Group 的 DROP 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```SQL
+DROP RESOURCE GROUP <resource_group_name>
+```
+
+## 参数说明
+
+| **参数**            | **说明**         |
+| ------------------- | ---------------- |
+| resource_group_name | 待删除资源组名。 |
+
+## 示例
+
+示例一：删除资源组 `rg1`。
+
+```SQL
+DROP RESOURCE GROUP rg1;
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/SHOW_RESOURCE_GROUP.md b/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/SHOW_RESOURCE_GROUP.md
new file mode 100644
index 00000000000000..07fdc83614b2b8
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/SHOW_RESOURCE_GROUP.md
@@ -0,0 +1,56 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW RESOURCE GROUP
+
+## 功能
+
+查看资源组信息。
+
+## 语法
+
+```SQL
+SHOW { RESOURCE GROUPS [ALL] | RESOURCE GROUP resource_group_name }
+```
+
+## 参数说明
+
+| **参数**            | **说明**                                   |
+| ------------------- | ------------------------------------------ |
+| RESOURCE GROUPS     | 查看与当前用户匹配的资源组。               |
+| ALL                 | 如果表明此参数，则查看当前集群所有资源组。 |
+| RESOURCE GROUP      | 查看指定资源组信息。                       |
+| resource_group_name | 待查看资源组名。                           |
+
+## 返回
+
+| **返回**                   | **说明**                                                     |
+| -------------------------- | ------------------------------------------------------------ |
+| name                       | 资源组名。                                                   |
+| id                         | 资源组 ID。                                                  |
+| cpu_core_limit             | 资源组 CPU 核数上限。                                        |
+| mem_limit                  | 资源组内存资源上限。                                         |
+| big_query_cpu_second_limit | 大查询任务可以使用 CPU 的时间上限。                          |
+| big_query_scan_rows_limit  | 大查询任务可以扫描的行数上限。                               |
+| big_query_mem_limit        | 大查询任务可以使用的内存上限。                               |
+| concurrency_limit          | 资源组中并发查询数的上限。                                   |
+| type                       | 资源组类型。                                                 |
+| classifiers                | 资源组关联的分类器信息。其中，`id` 为分类器 ID，`weight` 为分类器匹配度。 |
+
+## 示例
+
+示例一：查看当前集群内所有资源组的信息。
+
+```Plain
+mysql> SHOW RESOURCE GROUPS ALL;
++-------+--------+----------------+-----------+----------------------------+---------------------------+---------------------+-------------------+--------+------------------------------------------------------------------------------------------------------------------+
+| name  | id     | cpu_core_limit | mem_limit | big_query_cpu_second_limit | big_query_scan_rows_limit | big_query_mem_limit | concurrency_limit | type   | classifiers                                                                                                      |
++-------+--------+----------------+-----------+----------------------------+---------------------------+---------------------+-------------------+--------+------------------------------------------------------------------------------------------------------------------+
+| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625127, weight=4.459375, user=rg1_user1, role=rg1_role1, query_type in (SELECT), source_ip=172.26.xxx.xx/24) |
+| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625128, weight=3.459375, user=rg1_user2, query_type in (SELECT), source_ip=172.26.xxx.xx/24)                 |
+| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625129, weight=2.359375, user=rg1_user3, source_ip=172.26.xxx.xx/24)                                         |
+| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625130, weight=1.0, user=rg1_user4)                                                                          |
+| rg1   | 625126 | 10             | 20.0%     | 100                        | 100000                    | 1073741824          | null              | NORMAL | (id=625131, weight=10.0, db='db1')                                                                                |
++-------+--------+----------------+-----------+----------------------------+---------------------------+---------------------+-------------------+--------+------------------------------------------------------------------------------------------------------------------+
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/SHOW_USAGE_RESOURCE_GROUPS.md b/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/SHOW_USAGE_RESOURCE_GROUPS.md
new file mode 100644
index 00000000000000..79f54822edee6b
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/SHOW_USAGE_RESOURCE_GROUPS.md
@@ -0,0 +1,52 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW USAGE RESOURCE GROUPS
+
+## 功能
+
+展示所有资源组在各 BE 上的使用信息。此功能从 v3.1.4 开始支持。
+
+:::tip
+
+该操作不需要权限。
+
+:::
+
+## 语法
+
+```SQL
+SHOW USAGE RESOURCE GROUPS
+```
+
+## 返回
+
+- `Name`：资源组的名称。
+- `Id`：资源组的 ID。
+- `Backend`：BE 的 IP 或 FQDN。
+- `BEInUseCpuCores`：该资源组在该 BE 上正在使用的 CPU 核数，该值为一个估计近似值。
+- `BEInUseMemBytes`：该资源组在该 BE 上正在使用的内存字节数。
+- `BERunningQueries`：该资源组在该 BE 上还未结束的查询数量。
+
+## 使用说明
+
+- 这些资源使用信息由 BE 周期性汇报给 Leader FE，汇报周期为 `report_resource_usage_interval_ms`，默认 1s。
+- 结果中只会展示 BEInUseCpuCores/BEInUseMemBytes/BERunningQueries 至少一个为正数的行，即只有一个资源组在一个 BE 上使用了某种资源时，才会在结果中进行展示。
+
+## 示例
+
+```Plain
+MySQL [(none)]> SHOW USAGE RESOURCE GROUPS;
++------------+----+-----------+-----------------+-----------------+------------------+
+| Name       | Id | Backend   | BEInUseCpuCores | BEInUseMemBytes | BERunningQueries |
++------------+----+-----------+-----------------+-----------------+------------------+
+| default_wg | 0  | 127.0.0.1 | 0.100           | 1               | 5                |
++------------+----+-----------+-----------------+-----------------+------------------+
+| default_wg | 0  | 127.0.0.2 | 0.200           | 2               | 6                |
++------------+----+-----------+-----------------+-----------------+------------------+
+| wg1        | 0  | 127.0.0.1 | 0.300           | 3               | 7                |
++------------+----+-----------+-----------------+-----------------+------------------+
+| wg2        | 0  | 127.0.0.1 | 0.400           | 4               | 8                |
++------------+----+-----------+-----------------+-----------------+------------------+
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/_category_.yml b/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/_category_.yml
new file mode 100644
index 00000000000000..ae0cad158643ea
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/resource_group/_category_.yml
@@ -0,0 +1,6 @@
+position: 30 # float position is supported
+label: '资源组'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/sql_blacklist/ADD_SQLBLACKLIST.md b/docs/zh/sql-reference/sql-statements/cluster-management/sql_blacklist/ADD_SQLBLACKLIST.md
new file mode 100644
index 00000000000000..fa58f75aab8790
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/sql_blacklist/ADD_SQLBLACKLIST.md
@@ -0,0 +1,63 @@
+---
+displayed_sidebar: docs
+---
+
+# ADD SQLBLACKLIST
+
+## 功能
+
+将一个 SQL 正则表达式添加至 SQL 黑名单。启用 SQL 黑名单功能后，StarRocks 会将所有需要执行的 SQL 语句与黑名单中的 SQL 正则表达式进行比较。StarRocks 不会执行与黑名单中任何正则表达式相匹配的 SQL，并返回错误。
+
+有关 SQL 黑名单的更多信息，请参阅 [管理 SQL 黑名单](../../../../administration/management/resource_management/Blacklist.md)。
+
+:::tip
+
+- 该操作需要 SYSTEM 级的 BLACKLIST 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+- 当前 StarRocks 支持将 SELECT 语句加入 SQL 黑名单。
+:::
+
+## 语法
+
+```SQL
+ADD SQLBLACKLIST "<sql_reg_expr>"
+```
+
+## 参数说明
+
+`sql_reg_expr`：用于指定 SQL 语句的正则表达式。为了区分 SQL 语句中的特殊字符和正则表达式中的特殊字符，您需要使用转义符（\）作为 SQL 语句中特殊字符的前缀，如 `(`、`)` 以及 `+`。由于 `(` 和 `)` 在 SQL 语句中经常被使用，StarRocks 可以直接识别 SQL 语句中的 `(` 和 `)`。所以您无需为 `(` 和 `)` 添加转义符。
+
+## 示例
+
+示例一：将 `count(\*)` 添加到 SQL 黑名单。
+
+```Plain
+mysql> ADD SQLBLACKLIST "select count(\\*) from .+";
+```
+
+示例二：将 `count(distinct )` 添加到 SQL 黑名单。
+
+```Plain
+mysql> ADD SQLBLACKLIST "select count(distinct .+) from .+";
+```
+
+示例三：将 `order by limit x, y，1 <= x <=7, 5 <=y <=7` 加入SQL黑名单。
+
+```Plain
+mysql> ADD SQLBLACKLIST "select id_int from test_all_type_select1 
+    order by id_int 
+    limit [1-7], [5-7]";
+```
+
+示例四：将复杂的 SQL 正则表达式添加到 SQL 黑名单中。该示例是为了演示如何使用转义符来表示 SQL 语句中的 `*` 和 `-`。
+
+```Plain
+mysql> ADD SQLBLACKLIST 
+    "select id_int \\* 4, id_tinyint, id_varchar 
+        from test_all_type_nullable 
+    except select id_int, id_tinyint, id_varchar 
+        from test_basic 
+    except select (id_int \\* 9 \\- 8) \\/ 2, id_tinyint, id_varchar 
+        from test_all_type_nullable2 
+    except select id_int, id_tinyint, id_varchar 
+        from test_basic_nullable";
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/sql_blacklist/DELETE_SQLBLACKLIST.md b/docs/zh/sql-reference/sql-statements/cluster-management/sql_blacklist/DELETE_SQLBLACKLIST.md
new file mode 100644
index 00000000000000..526c2d175d0a19
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/sql_blacklist/DELETE_SQLBLACKLIST.md
@@ -0,0 +1,41 @@
+---
+displayed_sidebar: docs
+---
+
+# DELETE SQLBLACKLIST
+
+## 功能
+
+从 SQL 黑名单中删除一个 SQL 正则表达式。
+
+有关 SQL 黑名单的更多信息，请参阅 [管理 SQL 黑名单](../../../../administration/management/resource_management/Blacklist.md)。
+
+:::tip
+
+该操作需要 SYSTEM 级 BLACKLIST 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```SQL
+DELETE SQLBLACKLIST <sql_index_number>
+```
+
+## 参数说明
+
+`sql_index_number`：SQL 正则表达式在黑名单中的序号。用逗号（,）和一个空格分隔多个序号。您可以使用 [SHOW SQLBLACKLIST](SHOW_SQLBLACKLIST.md) 查询相应索引号。
+
+## 示例
+
+```Plain
+mysql> DELETE SQLBLACKLIST 3, 4;
+
+mysql> SHOW SQLBLACKLIST;
++-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| Index | Forbidden SQL                                                                                                                                                                                                                                                                                          |
++-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| 1     | select count\(\*\) from .+                                                                                                                                                                                                                                                                             |
+| 2     | select id_int \* 4, id_tinyint, id_varchar from test_all_type_nullable except select id_int, id_tinyint, id_varchar from test_basic except select \(id_int \* 9 \- 8\) \/ 2, id_tinyint, id_varchar from test_all_type_nullable2 except select id_int, id_tinyint, id_varchar from test_basic_nullable |
++-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/sql_blacklist/SHOW_SQLBLACKLIST.md b/docs/zh/sql-reference/sql-statements/cluster-management/sql_blacklist/SHOW_SQLBLACKLIST.md
new file mode 100644
index 00000000000000..ec5214ae3d8c55
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/sql_blacklist/SHOW_SQLBLACKLIST.md
@@ -0,0 +1,44 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW SQLBLACKLIST
+
+## 功能
+
+显示 SQL 黑名单中的 SQL 正则表达式。
+
+有关 SQL 黑名单的更多信息，请参阅 [管理 SQL 黑名单](../../../../administration/management/resource_management/Blacklist.md)。
+
+:::tip
+
+该操作需要 SYSTEM 级 BLACKLIST 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```SQL
+SHOW SQLBLACKLIST
+```
+
+## 返回
+
+| **返回**      | **说明**                              |
+| ------------- | ------------------------------------- |
+| Index         | 已加入黑名单的 SQL 正则表达式的序号。 |
+| Forbidden SQL | 已加入黑名单的 SQL 正则表达式。       |
+
+## 示例
+
+```Plain
+mysql> SHOW SQLBLACKLIST;
++-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| Index | Forbidden SQL                                                                                                                                                                                                                                                                                          |
++-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| 1     | select count\(\*\) from .+                                                                                                                                                                                                                                                                             |
+| 2     | select id_int \* 4, id_tinyint, id_varchar from test_all_type_nullable except select id_int, id_tinyint, id_varchar from test_basic except select \(id_int \* 9 \- 8\) \/ 2, id_tinyint, id_varchar from test_all_type_nullable2 except select id_int, id_tinyint, id_varchar from test_basic_nullable |
+| 3     | select id_int from test_all_type_select1 order by id_int limit [1-7], [5-7]                                                                                                                                                                                                                            |
+| 4     | select count\(distinct .+\) from .+                                                                                                                                                                                                                                                                    |
++-------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/sql_blacklist/_category_.yml b/docs/zh/sql-reference/sql-statements/cluster-management/sql_blacklist/_category_.yml
new file mode 100644
index 00000000000000..e46beea6d570f6
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/sql_blacklist/_category_.yml
@@ -0,0 +1,6 @@
+position: 70 # float position is supported
+label: 'SQL 黑名单'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/ALTER_STORAGE_VOLUME.md b/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/ALTER_STORAGE_VOLUME.md
new file mode 100644
index 00000000000000..d85f0931781cf5
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/ALTER_STORAGE_VOLUME.md
@@ -0,0 +1,61 @@
+---
+keywords: ['xiugai'] 
+displayed_sidebar: docs
+---
+
+# ALTER STORAGE VOLUME
+
+## 功能
+
+更改存储卷的认证属性、注释或状态（`enabled`）。关于存储卷的属性，请参见[CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)。该功能自 v3.1 起支持。
+
+> **注意**
+>
+> - 仅拥有特定存储卷 ALTER 权限的用户可以执行该操作。
+> - 已有存储卷的 `TYPE` 、`LOCATIONS` 和其他存储路径相关的参数无法更改，仅能更改认证属性。如果您更改了存储路径相关的配置项，则在此之前创建的数据库和表将变为只读，您无法向其中导入数据。
+> - `enabled` 为 `false` 的存储卷无法被引用。
+
+## 语法
+
+```SQL
+ALTER STORAGE VOLUME [ IF EXISTS ] <storage_volume_name>
+{ COMMENT '<comment_string>'
+| SET ("key" = "value"[,...]) }
+```
+
+## 参数说明
+
+| **参数**            | **说明**                         |
+| ------------------- | -------------------------------- |
+| storage_volume_name | 待更改或新增属性的存储卷的名称。 |
+| COMMENT             | 存储卷的注释。                   |
+
+有关可更改或新增 PROPERTIES 的详细信息，请参阅 [CREATE STORAGE VOLUME - PROPERTIES](./CREATE_STORAGE_VOLUME.md#properties)。
+
+## 示例
+
+示例一：禁用存储卷 `my_s3_volume`。
+
+```Plain
+MySQL > ALTER STORAGE VOLUME my_s3_volume
+    -> SET ("enabled" = "false");
+Query OK, 0 rows affected (0.01 sec)
+```
+
+示例二：修改存储卷 `my_s3_volume` 的认证信息。
+
+```Plain
+MySQL > ALTER STORAGE VOLUME my_s3_volume
+    -> SET (
+    ->     "aws.s3.use_instance_profile" = "true"
+    -> );
+Query OK, 0 rows affected (0.00 sec)
+```
+
+## 相关 SQL
+
+- [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)
+- [DROP STORAGE VOLUME](./DROP_STORAGE_VOLUME.md)
+- [SET DEFAULT STORAGE VOLUME](./SET_DEFAULT_STORAGE_VOLUME.md)
+- [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md)
+- [SHOW STORAGE VOLUMES](./SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md b/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md
new file mode 100644
index 00000000000000..a020a69720a198
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/CREATE_STORAGE_VOLUME.md
@@ -0,0 +1,465 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE STORAGE VOLUME
+
+## 功能
+
+为远程存储系统创建存储卷。该功能自 v3.1 起支持。
+
+存储卷由远程存储系统的属性和认证信息组成。您可以在 [StarRocks 存算分离集群](../../../../deployment/shared_data/shared_data.mdx)中创建数据库和云原生表时引用存储卷。
+
+> **注意**
+>
+> - 仅拥有 SYSTEM 级 CREATE STORAGE VOLUME 权限的用户可以执行该操作。
+> - 如果您需要基于 HDFS 创建存储卷，建议您不要随意修改 **HADOOP_CONF** 和 **core-site.xml/hdfs-site.xml**。如果以上文件中的参数与创建 Storage Volume 的参数存在差异，可能导致系统发生未知行为。
+
+## 语法
+
+```SQL
+CREATE STORAGE VOLUME [IF NOT EXISTS] <storage_volume_name>
+TYPE = { S3 | HDFS | AZBLOB }
+LOCATIONS = ('<remote_storage_path>')
+[ COMMENT '<comment_string>' ]
+PROPERTIES
+("key" = "value",...)
+```
+
+## 参数说明
+
+| **参数**            | **说明**                                                     |
+| ------------------- | ------------------------------------------------------------ |
+| storage_volume_name | 存储卷的名称。请注意，您无法创建名为 `builtin_storage_volume` 的存储卷，因为该名称被用于创建内置存储卷。有关 storage volume 的命名要求，参见[系统限制](../../../System_limit.md)。 |
+| TYPE                | 远程存储系统的类型。有效值：`S3` 、`AZBLOB` 和 `HDFS`。`S3` 代表AWS S3 或与 S3 协议兼容的存储系统。`AZBLOB` 代表 Azure Blob Storage（自 v3.1.1 起支持）。`HDFS` 代表 HDFS 集群。 |
+| LOCATIONS           | 远程存储系统的位置。格式如下：<ul><li>AWS S3 或与 S3 协议兼容的存储系统：`s3://<s3_path>`。`<s3_path>` 必须为绝对路径，如 `s3://testbucket/subpath`。请注意，如果要为存储卷启用 [分区前缀](#分区前缀) 功能，您只能指定存储桶名称，不允许指定子路径。</li><li>Azure Blob Storage: `azblob://<azblob_path>`。`<azblob_path>` 必须为绝对路径，如 `azblob://testcontainer/subpath`。</li><li>HDFS：`hdfs://<host>:<port>/<hdfs_path>`。`<hdfs_path>` 必须为绝对路径，如 `hdfs://127.0.0.1:9000/user/xxx/starrocks`。</li><li>WebHDFS：`webhdfs://<host>:<http_port>/<hdfs_path>`，其中 `<http_port>` 为 NameNode 的 HTTP 端口。`<hdfs_path>` 必须为绝对路径，如 `webhdfs://127.0.0.1:50070/user/xxx/starrocks`。</li><li>ViewFS：`viewfs://<ViewFS_cluster>/<viewfs_path>`，其中 `<ViewFS_cluster>` 为 ViewFS 集群名。`<viewfs_path>` 必须为绝对路径，如 `viewfs://myviewfscluster/user/xxx/starrocks`。</li></ul> |
+| COMMENT             | 存储卷的注释。                                               |
+| PROPERTIES          | `"key" = "value"` 形式的参数对，用以指定访问远程存储系统的属性和认证信息。有关详细信息，请参阅 [PROPERTIES](#properties)。 |
+
+### PROPERTIES
+
+下表列出了存储卷所有可用的属性。这些属性的使用说明在列表后提供，从 [认证信息](#认证信息) 和 [特性](#特性) 两个方面，基于不同场景进行分类。
+
+| **属性**                            | **描述**                                                     |
+| ----------------------------------- | ------------------------------------------------------------ |
+| enabled                             | 是否启用当前存储卷。默认值：`false`。已禁用的存储卷无法被引用。 |
+| aws.s3.region                       | 需访问的 S3 存储空间的地区，如 `us-west-2`。                 |
+| aws.s3.endpoint                     | 访问 S3 存储空间的连接地址，如 `https://s3.us-west-2.amazonaws.com`。[Preview] 自 v3.3.0 起，支持 Amazon S3 Express One Zone Storage，如 `https://s3express.us-west-2.amazonaws.com`。 |
+| aws.s3.use_aws_sdk_default_behavior | 是否使用 AWS SDK 默认的认证凭证。有效值：`true` 和 `false` (默认)。 |
+| aws.s3.use_instance_profile         | 是否使用 Instance Profile 或 Assumed Role 作为安全凭证访问 S3。有效值：`true` 和 `false` (默认)。<ul><li>如果您使用 IAM 用户凭证（Access Key 和 Secret Key）访问 S3，则需要将此项设为 `false`，并指定 `aws.s3.access_key` 和 `aws.s3.secret_key`。</li><li>如果您使用 Instance Profile 访问 S3，则需要将此项设为 `true`。</li><li>如果您使用 Assumed Role 访问 S3，则需要将此项设为 `true`，并指定 `aws.s3.iam_role_arn`。</li><li>如果您使用外部 AWS 账户通过 Assumed Role 认证访问 S3，则需要将此项设为 `true`，并额外指定 `aws.s3.iam_role_arn` 和 `aws.s3.external_id`。</li></ul> |
+| aws.s3.access_key                   | 访问 S3 存储空间的 Access Key。                              |
+| aws.s3.secret_key                   | 访问 S3 存储空间的 Secret Key。                              |
+| aws.s3.iam_role_arn                 | 有访问 S3 存储空间权限 IAM Role 的 ARN。                     |
+| aws.s3.external_id                  | 用于跨 AWS 账户访问 S3 存储空间的外部 ID。                   |
+| azure.blob.endpoint   | Azure Blob Storage 的链接地址，如 `https://test.blob.core.windows.net`。 |
+| azure.blob.shared_key | 访问 Azure Blob Storage 的共享密钥（Shared Key）。           |
+| azure.blob.sas_token  | 访问 Azure Blob Storage 的共享访问签名（SAS）。              |
+| hadoop.security.authentication                        | 指定认证方式。有效值：`simple`（默认） 和 `kerberos`。`simple` 表示简单认证，即 Username。`kerberos` 表示 Kerberos 认证。 |
+| username                                              | 用于访问 HDFS 集群中 NameNode 节点的用户名。                      |
+| hadoop.security.kerberos.ticket.cache.path            | 用于指定 kinit 生成的 Ticket Cache 文件的路径。                   |
+| dfs.nameservices                                      | 自定义 HDFS 集群的名称。                                        |
+| dfs.ha.namenodes.`<ha_cluster_name\>`                   | 自定义 NameNode 的名称，多个名称以逗号 (,) 分隔，双引号内不允许出现空格。其中 `<ha_cluster_name>` 为 `dfs.nameservices` 中自定义的 HDFS 服务的名称。 |
+| dfs.namenode.rpc-address.`<ha_cluster_name\>`.`<NameNode\>` | 指定 NameNode 的 RPC 地址信息。 其中 `<NameNode>` 表示 `dfs.ha.namenodes.<ha_cluster_name>` 中自定义 NameNode 的名称。 |
+| dfs.client.failover.proxy.provider                    | 指定客户端连接的 NameNode 的提供者，默认为 `org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider`。 |
+| fs.viewfs.mounttable.`<ViewFS_cluster\>`.link./`<viewfs_path\>` | 需要挂载的 ViewFS 集群路径，多个路径以逗号 (,) 分隔。其中 `<ViewFS_cluster>` 为 `LOCATIONS` 中自定义的 ViewFS 集群名。 |
+| aws.s3.enable_partitioned_prefix    | 是否启用存储卷的分区前缀功能。默认值：`false`。有关此功能的更多信息，请参阅 [分区前缀](#分区前缀)。 |
+| aws.s3.num_partitioned_prefix       | 要为该存储卷创建的前缀数量。默认值：`256`。有效范围：[4, 1024]。|
+
+#### 认证信息
+
+##### AWS S3
+
+- 如果您使用 AWS SDK 默认的认证凭证，请设置以下属性：
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "aws.s3.region" = "<region>",
+  "aws.s3.endpoint" = "<endpoint_url>",
+  "aws.s3.use_aws_sdk_default_behavior" = "true"
+  ```
+
+- 如果您使用 IAM user-based 认证，请设置以下属性：
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "aws.s3.region" = "<region>",
+  "aws.s3.endpoint" = "<endpoint_url>",
+  "aws.s3.use_aws_sdk_default_behavior" = "false",
+  "aws.s3.use_instance_profile" = "false",
+  "aws.s3.access_key" = "<access_key>",
+  "aws.s3.secret_key" = "<secrete_key>"
+  ```
+
+- 如果您使用 Instance Profile 认证，请设置以下属性：
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "aws.s3.region" = "<region>",
+  "aws.s3.endpoint" = "<endpoint_url>",
+  "aws.s3.use_aws_sdk_default_behavior" = "false",
+  "aws.s3.use_instance_profile" = "true"
+  ```
+
+- 如果您使用 Assumed Role 认证，请设置以下属性：
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "aws.s3.region" = "<region>",
+  "aws.s3.endpoint" = "<endpoint_url>",
+  "aws.s3.use_aws_sdk_default_behavior" = "false",
+  "aws.s3.use_instance_profile" = "true",
+  "aws.s3.iam_role_arn" = "<role_arn>"
+  ```
+
+- 如果您使用外部 AWS 账户通过 Assumed Role 认证，请设置以下属性：
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "aws.s3.region" = "<region>",
+  "aws.s3.endpoint" = "<endpoint_url>",
+  "aws.s3.use_aws_sdk_default_behavior" = "false",
+  "aws.s3.use_instance_profile" = "true",
+  "aws.s3.iam_role_arn" = "<role_arn>",
+  "aws.s3.external_id" = "<external_id>"
+  ```
+
+##### GCS
+
+如果您使用 GCP Cloud Storage，请设置以下属性：
+
+```SQL
+"enabled" = "{ true | false }",
+
+-- 例如：us-east-1
+"aws.s3.region" = "<region>",
+
+-- 例如：https://storage.googleapis.com
+"aws.s3.endpoint" = "<endpoint_url>",
+
+"aws.s3.access_key" = "<access_key>",
+"aws.s3.secret_key" = "<secrete_key>"
+```
+
+##### 阿里云 OSS
+
+如果您使用阿里云 OSS，请设置以下属性：
+
+```SQL
+"enabled" = "{ true | false }",
+
+-- 例如：cn-zhangjiakou
+"aws.s3.region" = "<region>",
+
+-- 例如：https://oss-cn-zhangjiakou-internal.aliyuncs.com
+"aws.s3.endpoint" = "<endpoint_url>",
+
+"aws.s3.access_key" = "<access_key>",
+"aws.s3.secret_key" = "<secrete_key>"
+```
+
+##### 华为云 OBS
+
+如果您使用华为云 OBS，请设置以下属性：
+
+```SQL
+"enabled" = "{ true | false }",
+
+-- 例如：cn-north-4
+"aws.s3.region" = "<region>",
+
+-- 例如：https://obs.cn-north-4.myhuaweicloud.com
+"aws.s3.endpoint" = "<endpoint_url>",
+
+"aws.s3.access_key" = "<access_key>",
+"aws.s3.secret_key" = "<secrete_key>"
+```
+
+##### 腾讯云 COS
+
+如果您使用腾讯云 COS，请设置以下属性：
+
+```SQL
+"enabled" = "{ true | false }",
+
+-- 例如：ap-beijing
+"aws.s3.region" = "<region>",
+
+-- 例如：https://cos.ap-beijing.myqcloud.com
+"aws.s3.endpoint" = "<endpoint_url>",
+
+"aws.s3.access_key" = "<access_key>",
+"aws.s3.secret_key" = "<secrete_key>"
+```
+
+##### 火山引擎 TOS
+
+如果您使用火山引擎 TOS，请设置以下属性：
+
+```SQL
+"enabled" = "{ true | false }",
+
+-- 例如：cn-beijing
+"aws.s3.region" = "<region>",
+
+-- 例如：https://tos-s3-cn-beijing.ivolces.com
+"aws.s3.endpoint" = "<endpoint_url>",
+
+"aws.s3.access_key" = "<access_key>",
+"aws.s3.secret_key" = "<secrete_key>"
+```
+
+##### 金山云
+
+如果您使用金山云，请设置以下属性：
+
+```SQL
+"enabled" = "{ true | false }",
+
+-- 例如：BEIJING
+"aws.s3.region" = "<region>",
+
+-- 注意请使用三级域名, 金山云不支持二级域名
+-- 例如：jeff-test.ks3-cn-beijing.ksyuncs.com
+"aws.s3.endpoint" = "<endpoint_url>",
+
+"aws.s3.access_key" = "<access_key>",
+"aws.s3.secret_key" = "<secrete_key>"
+```
+
+##### MinIO
+
+如果您使用 MinIO，请设置以下属性：
+
+```SQL
+"enabled" = "{ true | false }",
+
+-- 例如：us-east-1
+"aws.s3.region" = "<region>",
+
+-- 例如：http://172.26.xx.xxx:39000
+"aws.s3.endpoint" = "<endpoint_url>",
+
+"aws.s3.access_key" = "<access_key>",
+"aws.s3.secret_key" = "<secrete_key>"
+```
+
+##### Ceph S3
+
+如果您使用 Ceph S3，请设置以下属性：
+
+```SQL
+"enabled" = "{ true | false }",
+
+-- 例如：http://172.26.xx.xxx:7480
+"aws.s3.endpoint" = "<endpoint_url>",
+
+"aws.s3.access_key" = "<access_key>",
+"aws.s3.secret_key" = "<secrete_key>"
+```
+
+##### Azure Blob Storage
+
+StarRocks 自 v3.1.1 起支持基于 Azure Blob Storage 创建存储卷。
+
+- 如果您使用共享密钥（Shared Key）认证，请设置以下 PROPERTIES：
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "azure.blob.endpoint" = "<endpoint_url>",
+  "azure.blob.shared_key" = "<shared_key>"
+  ```
+
+- 如果您使用共享访问签名（SAS）认证，请设置以下 PROPERTIES：
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "azure.blob.endpoint" = "<endpoint_url>",
+  "azure.blob.sas_token" = "<sas_token>"
+  ```
+
+> **注意**
+>
+> 创建 Azure Blob Storage Account 时必须禁用分层命名空间。
+
+##### HDFS
+
+- 如果您不使用认证接入 HDFS，请设置以下属性：
+
+  ```SQL
+  "enabled" = "{ true | false }"
+  ```
+
+- 如果您使用简单认证 (Username) 接入 HDFS（自 v3.2 起支持），请设置以下属性：
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "hadoop.security.authentication" = "simple",
+  "username" = "<hdfs_username>"
+  ```
+
+- 如果您使用 Kerberos Ticket Cache 认证接入 HDFS（自 v3.2 起支持），请设置以下属性：
+
+  ```SQL
+  "enabled" = "{ true | false }",
+  "hadoop.security.authentication" = "kerberos",
+  "hadoop.security.kerberos.ticket.cache.path" = "<ticket_cache_path>"
+  ```
+
+  > **注意**
+  >
+  > - 该设置仅为强制系统使用 KeyTab 通过 Kerberos 访问 HDFS。请确保每个 BE 或 CN 节点都能够访问 KeyTab 文件。同时，还需要确保正确设置 **/etc/krb5.conf** 文件。
+  > - Ticket cache 由外部的 kinit 工具生成，请确保有 crontab 或类似的定期任务来刷新 Ticket。
+
+- 如果您的 HDFS 集群启用了 NameNode HA 配置（自 v3.2 起支持），请额外设置以下属性：
+
+  ```SQL
+  "dfs.nameservices" = "<ha_cluster_name>",
+  "dfs.ha.namenodes.<ha_cluster_name>" = "<NameNode1>,<NameNode2> [, ...]",
+  "dfs.namenode.rpc-address.<ha_cluster_name>.<NameNode1>" = "<hdfs_host>:<hdfs_port>",
+  "dfs.namenode.rpc-address.<ha_cluster_name>.<NameNode2>" = "<hdfs_host>:<hdfs_port>",
+  [...]
+  "dfs.client.failover.proxy.provider.<ha_cluster_name>" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
+  ```
+
+  更多信息，请参考 [HDFS HA 文档](https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HDFSHighAvailabilityWithNFS.html)。
+
+  - 如果您使用 WebHDFS（自 v3.2 起支持），请设置以下属性：
+
+  ```SQL
+  "enabled" = "{ true | false }"
+  ```
+
+  更多信息，请参考 [WebHDFS 文档](https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/WebHDFS.html)。
+
+- 如果您使用 Hadoop ViewFS（自 v3.2 起支持），请设置以下属性：
+
+  ```SQL
+  -- 请将 <ViewFS_cluster> 替换为 ViewFS 集群名。
+  "fs.viewfs.mounttable.<ViewFS_cluster>.link./<viewfs_path_1>" = "hdfs://<hdfs_host_1>:<hdfs_port_1>/<hdfs_path_1>",
+  "fs.viewfs.mounttable.<ViewFS_cluster>.link./<viewfs_path_2>" = "hdfs://<hdfs_host_2>:<hdfs_port_2>/<hdfs_path_2>",
+  [, ...]
+  ```
+
+  更多信息，请参考 [ViewFS 文档](https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/ViewFs.html)。
+
+#### 特性
+
+##### 分区前缀
+
+自 v3.2.4 起，StarRocks 支持基于兼容 S3 的对象存储系统创建带有分区前缀功能的存储卷。当启用此功能时，StarRocks 会将数据存储在存储桶下多个使用统一前缀的分区（子路径）中。由于存储桶的 QPS 或吞吐量限制是基于单个分区设置的，此举可以轻松提高 StarRocks 对存储桶中数据文件的读写性能。
+
+如需启用此功能，除了上述与凭证相关的参数之外，您还需要设置以下属性：
+
+```SQL
+"aws.s3.enable_partitioned_prefix" = "{ true | false }",
+"aws.s3.num_partitioned_prefix" = "<INT>"
+```
+
+:::note
+- 分区前缀功能仅支持兼容 S3 对象存储系统，即存储卷的 `TYPE` 必须为 `S3`。
+- 存储卷的 `LOCATIONS` 只能包含存储桶名称，例如，`s3://testbucket`。不允许在存储桶名称后指定子路径。
+- 存储卷创建成功后，以上两个属性均无法修改。
+- 使用 FE 配置文件 **fe.conf** 创建存储卷无法启用此功能。
+:::
+
+## 示例
+
+示例一：为 AWS S3 存储空间 `defaultbucket` 创建存储卷 `my_s3_volume`，使用 IAM user-based 认证，并启用该存储卷。
+
+```SQL
+CREATE STORAGE VOLUME my_s3_volume
+TYPE = S3
+LOCATIONS = ("s3://defaultbucket/test/")
+PROPERTIES
+(
+    "aws.s3.region" = "us-west-2",
+    "aws.s3.endpoint" = "https://s3.us-west-2.amazonaws.com",
+    "aws.s3.use_aws_sdk_default_behavior" = "false",
+    "aws.s3.use_instance_profile" = "false",
+    "aws.s3.access_key" = "xxxxxxxxxx",
+    "aws.s3.secret_key" = "yyyyyyyyyy"
+);
+```
+
+示例二：为 HDFS 创建存储卷 `my_hdfs_volume`，并启用该存储卷。
+
+```SQL
+CREATE STORAGE VOLUME my_hdfs_volume
+TYPE = HDFS
+LOCATIONS = ("hdfs://127.0.0.1:9000/sr/test/")
+PROPERTIES
+(
+    "enabled" = "true"
+);
+```
+
+示例三：使用简单验证为 HDFS 创建存储卷 `hdfsvolumehadoop`。
+
+```sql
+CREATE STORAGE VOLUME hdfsvolumehadoop
+TYPE = HDFS
+LOCATIONS = ("hdfs://127.0.0.1:9000/sr/test/")
+PROPERTIES(
+    "hadoop.security.authentication" = "simple",
+    "username" = "starrocks"
+);
+```
+
+示例四：使用 Kerberos Ticket Cache 认证接入 HDFS 并创建存储卷 `hdfsvolkerberos`。
+
+```sql
+CREATE STORAGE VOLUME hdfsvolkerberos
+TYPE = HDFS
+LOCATIONS = ("hdfs://127.0.0.1:9000/sr/test/")
+PROPERTIES(
+    "hadoop.security.authentication" = "kerberos",
+    "hadoop.security.kerberos.ticket.cache.path" = "/path/to/ticket/cache/path"
+);
+```
+
+示例五：为启用了 NameNode HA 配置的 HDFS 集群创建存储卷 `hdfsvolha`。
+
+```sql
+CREATE STORAGE VOLUME hdfsvolha
+TYPE = HDFS
+LOCATIONS = ("hdfs://myhacluster/data/sr")
+PROPERTIES(
+    "dfs.nameservices" = "myhacluster",
+    "dfs.ha.namenodes.myhacluster" = "nn1,nn2,nn3",
+    "dfs.namenode.rpc-address.myhacluster.nn1" = "machine1.example.com:8020",
+    "dfs.namenode.rpc-address.myhacluster.nn2" = "machine2.example.com:8020",
+    "dfs.namenode.rpc-address.myhacluster.nn3" = "machine3.example.com:8020",
+    "dfs.namenode.http-address.myhacluster.nn1" = "machine1.example.com:9870",
+    "dfs.namenode.http-address.myhacluster.nn2" = "machine2.example.com:9870",
+    "dfs.namenode.http-address.myhacluster.nn3" = "machine3.example.com:9870",
+    "dfs.client.failover.proxy.provider.myhacluster" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
+);
+```
+
+示例六：为 WebHDFS 创建存储卷 `webhdfsvol`。
+
+```sql
+CREATE STORAGE VOLUME webhdfsvol
+TYPE = HDFS
+LOCATIONS = ("webhdfs://namenode:9870/data/sr");
+```
+
+示例七：使用 Hadoop ViewFS 创建存储卷 `viewfsvol`。
+
+```sql
+CREATE STORAGE VOLUME viewfsvol
+TYPE = HDFS
+LOCATIONS = ("viewfs://clusterX/data/sr")
+PROPERTIES(
+    "fs.viewfs.mounttable.clusterX.link./data" = "hdfs://nn1-clusterx.example.com:8020/data",
+    "fs.viewfs.mounttable.clusterX.link./project" = "hdfs://nn2-clusterx.example.com:8020/project"
+);
+```
+
+## 相关 SQL
+
+- [ALTER STORAGE VOLUME](./ALTER_STORAGE_VOLUME.md)
+- [DROP STORAGE VOLUME](./DROP_STORAGE_VOLUME.md)
+- [SET DEFAULT STORAGE VOLUME](./SET_DEFAULT_STORAGE_VOLUME.md)
+- [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md)
+- [SHOW STORAGE VOLUMES](./SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/DESC_STORAGE_VOLUME.md b/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/DESC_STORAGE_VOLUME.md
new file mode 100644
index 00000000000000..5fa2c3dec93f04
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/DESC_STORAGE_VOLUME.md
@@ -0,0 +1,62 @@
+---
+displayed_sidebar: docs
+---
+
+# DESC STORAGE VOLUME
+
+## 功能
+
+查看指定存储卷的信息。该功能自 v3.1 起支持。
+
+> **注意**
+>
+> 仅拥有指定存储卷 USAGE 权限的用户可以执行该操作。
+
+## 语法
+
+```SQL
+DESC[RIBE] STORAGE VOLUME <storage_volume_name>
+```
+
+## 参数说明
+
+| **参数**            | **说明**               |
+| ------------------- | ---------------------- |
+| storage_volume_name | 待查看的存储卷的名称。 |
+
+## 返回
+
+| **返回**  | **说明**                                                |
+| --------- | ------------------------------------------------------- |
+| Name      | 存储卷的名称。                                          |
+| Type      | 远程存储系统的类型。有效值：`S3`、`AZBLOB` 和 `HDFS`。 |
+| IsDefault | 该存储卷是否为默认存储卷。                              |
+| Location  | 远程存储系统的位置。                                    |
+| Params    | 用于连接远程存储系统的认证信息。                        |
+| Enabled   | 该存储卷是否已被启用。                                  |
+| Comment   | 存储卷的注释。                                          |
+
+## 示例
+
+示例一：查看存储卷 `my_s3_volume` 的信息。
+
+```Plain
+MySQL > DESCRIBE STORAGE VOLUME my_s3_volume\G
+*************************** 1. row ***************************
+     Name: my_s3_volume
+     Type: S3
+IsDefault: false
+ Location: s3://defaultbucket/test/
+   Params: {"aws.s3.access_key":"xxxxxxxxxx","aws.s3.secret_key":"yyyyyyyyyy","aws.s3.endpoint":"https://s3.us-west-2.amazonaws.com","aws.s3.region":"us-west-2","aws.s3.use_instance_profile":"true","aws.s3.use_aws_sdk_default_behavior":"false"}
+  Enabled: false
+  Comment: 
+1 row in set (0.00 sec)
+```
+
+## 相关 SQL
+
+- [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)
+- [ALTER STORAGE VOLUME](./ALTER_STORAGE_VOLUME.md)
+- [DROP STORAGE VOLUME](./DROP_STORAGE_VOLUME.md)
+- [SET DEFAULT STORAGE VOLUME](./SET_DEFAULT_STORAGE_VOLUME.md)
+- [SHOW STORAGE VOLUMES](./SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/DROP_STORAGE_VOLUME.md b/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/DROP_STORAGE_VOLUME.md
new file mode 100644
index 00000000000000..420f5604c9eef3
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/DROP_STORAGE_VOLUME.md
@@ -0,0 +1,44 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP STORAGE VOLUME
+
+## 功能
+
+删除指定存储卷。已删除的存储卷无法被引用。该功能自 v3.1 起支持。
+
+> **注意**
+>
+> - 仅拥有指定存储卷 DROP 权限的用户可以执行该操作。
+> - 默认存储卷以及内置存储卷 `builtin_storage_volume` 无法删除。您可以通过 [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md) 查看存储卷是否为默认存储卷。
+> - 被已有数据库或云原生表引用的存储卷无法删除。
+
+## 语法
+
+```SQL
+DROP STORAGE VOLUME [ IF EXISTS ] <storage_volume_name>
+```
+
+## 参数说明
+
+| **参数**            | **说明**               |
+| ------------------- | ---------------------- |
+| storage_volume_name | 待删除的存储卷的名称。 |
+
+## 示例
+
+示例一：删除存储卷 `my_s3_volume`。
+
+```Plain
+MySQL > DROP STORAGE VOLUME my_s3_volume;
+Query OK, 0 rows affected (0.01 sec)
+```
+
+## 相关 SQL
+
+- [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)
+- [ALTER STORAGE VOLUME](./ALTER_STORAGE_VOLUME.md)
+- [SET DEFAULT STORAGE VOLUME](./SET_DEFAULT_STORAGE_VOLUME.md)
+- [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md)
+- [SHOW STORAGE VOLUMES](./SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/SET_DEFAULT_STORAGE_VOLUME.md b/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/SET_DEFAULT_STORAGE_VOLUME.md
new file mode 100644
index 00000000000000..4984477f409aea
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/SET_DEFAULT_STORAGE_VOLUME.md
@@ -0,0 +1,44 @@
+---
+displayed_sidebar: docs
+---
+
+# SET DEFAULT STORAGE VOLUME
+
+## 功能
+
+设置指定存储卷为默认存储卷。为远程存储系统创建了存储卷之后，您可以设置该存储卷为集群的默认存储卷。该功能自 v3.1 起支持。
+
+> **注意**
+>
+> - 仅拥有指定存储卷 USAGE 权限的用户可以执行该操作。
+> - 默认存储卷无法删除或禁用。
+> - 您必须为 StarRocks 存算分离集群设置默认存储卷，因为 StarRocks 会将系统统计信息存储在默认存储卷中。
+
+## 语法
+
+```SQL
+SET <storage_volume_name> AS DEFAULT STORAGE VOLUME
+```
+
+## 参数说明
+
+| **参数**            | **说明**               |
+| ------------------- | ---------------------- |
+| storage_volume_name | 待设置的存储卷的名称。 |
+
+## 示例
+
+示例一：设置存储卷 `my_s3_volume` 为默认存储卷。
+
+```SQL
+MySQL > SET my_s3_volume AS DEFAULT STORAGE VOLUME;
+Query OK, 0 rows affected (0.01 sec)
+```
+
+## 相关 SQL
+
+- [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)
+- [ALTER STORAGE VOLUME](./ALTER_STORAGE_VOLUME.md)
+- [DROP STORAGE VOLUME](./DROP_STORAGE_VOLUME.md)
+- [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md)
+- [SHOW STORAGE VOLUMES](./SHOW_STORAGE_VOLUMES.md)
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/SHOW_STORAGE_VOLUMES.md b/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/SHOW_STORAGE_VOLUMES.md
new file mode 100644
index 00000000000000..5eb35cb8ef0525
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/SHOW_STORAGE_VOLUMES.md
@@ -0,0 +1,55 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW STORAGE VOLUMES
+
+## 功能
+
+显示当前 StarRocks 集群中的存储卷。该功能自 v3.1 起支持。
+
+:::tip
+
+该操作不需要权限。
+
+:::
+
+## 语法
+
+```SQL
+SHOW STORAGE VOLUMES [ LIKE '<pattern>' ]
+```
+
+## 参数说明
+
+| **参数** | **说明**               |
+| -------- | ---------------------- |
+| pattern  | 用于匹配存储卷的模式。 |
+
+## 返回
+
+| **返回**       | **说明**       |
+| -------------- | -------------- |
+| Storage Volume | 存储卷的名称。 |
+
+## 示例
+
+示例一：显示当前 StarRocks 集群中所有的存储卷。
+
+```SQL
+MySQL > SHOW STORAGE VOLUMES;
++----------------+
+| Storage Volume |
++----------------+
+| my_s3_volume   |
++----------------+
+1 row in set (0.01 sec)
+```
+
+## 相关 SQL
+
+- [CREATE STORAGE VOLUME](./CREATE_STORAGE_VOLUME.md)
+- [ALTER STORAGE VOLUME](./ALTER_STORAGE_VOLUME.md)
+- [DROP STORAGE VOLUME](./DROP_STORAGE_VOLUME.md)
+- [SET DEFAULT STORAGE VOLUME](./SET_DEFAULT_STORAGE_VOLUME.md)
+- [DESC STORAGE VOLUME](./DESC_STORAGE_VOLUME.md)
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/_category_.yml b/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/_category_.yml
new file mode 100644
index 00000000000000..c802bdfa61f3b7
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/storage_volume/_category_.yml
@@ -0,0 +1,6 @@
+position: 30 # float position is supported
+label: '存储卷'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_CANCEL_REPAIR.md b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_CANCEL_REPAIR.md
new file mode 100644
index 00000000000000..369a7416753442
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_CANCEL_REPAIR.md
@@ -0,0 +1,31 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN CANCEL REPAIR
+
+## 功能
+
+该语句用于取消以高优先级修复指定表或分区。
+
+:::tip
+
+该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```sql
+ADMIN CANCEL REPAIR TABLE table_name[ PARTITION (p1,...)]
+```
+
+说明：该语句仅表示系统不再以高优先级修复指定表或分区的分片副本。系统仍会以默认调度方式修复副本。
+
+## 示例
+
+取消高优先级修复。
+
+```sql
+ADMIN CANCEL REPAIR TABLE tbl PARTITION(p1);
+```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_CHECK_TABLET.md b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_CHECK_TABLET.md
new file mode 100644
index 00000000000000..fd02064fce329a
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_CHECK_TABLET.md
@@ -0,0 +1,38 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN CHECK TABLET
+
+## 功能
+
+该语句用于对一组 tablet 执行指定的检查操作。
+
+:::tip
+
+该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```sql
+ADMIN CHECK TABLET (tablet_id1, tablet_id2, ...)
+PROPERTIES("type" = "...")
+```
+
+说明：
+
+1. 必须指定 tablet id 列表以及 PROPERTIES 中的 type 属性。
+2. 目前 type 仅支持：
+
+     **consistency**: 对 tablet 的副本数据一致性进行检查。该命令为异步命令，发送后，StarRocks 会开始执行对应 tablet 的一致性检查作业。最终的结果，将体现在 `SHOW PROC "/statistic";` 结果中的 InconsistentTabletNum 列。
+
+## 示例
+
+1. 对指定的一组 tablet 进行副本数据一致性检查
+
+    ```sql
+    ADMIN CHECK TABLET (10000, 10001)
+    PROPERTIES("type" = "consistency");
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_REPAIR.md b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_REPAIR.md
new file mode 100644
index 00000000000000..491ed9d580c45f
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_REPAIR.md
@@ -0,0 +1,40 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN REPAIR
+
+## 功能
+
+该语句用于尝试优先修复指定的表或分区。
+
+:::tip
+
+该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```sql
+ADMIN REPAIR TABLE table_name[ PARTITION (p1,...)]
+```
+
+说明：
+
+1. 该语句仅表示让系统尝试以高优先级修复指定表或分区的分片副本，并不保证能够修复成功。用户可以通过 `ADMIN SHOW REPLICA STATUS;` 命令查看修复情况。
+2. 默认的 timeout 是 14400 秒(4 小时)。超时意味着系统将不再以高优先级修复指定表或分区的分片副本。需要重新使用该命令设置。
+
+## 示例
+
+1. 尝试修复指定表
+
+    ```sql
+    ADMIN REPAIR TABLE tbl1;
+    ```
+
+2. 尝试修复指定分区
+
+    ```sql
+    ADMIN REPAIR TABLE tbl1 PARTITION (p1, p2);
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SET_PARTITION_VERSION.md b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SET_PARTITION_VERSION.md
new file mode 100644
index 00000000000000..cdf4eef7075910
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SET_PARTITION_VERSION.md
@@ -0,0 +1,51 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN SET PARTITION VERSION
+
+## 功能
+
+手动设置分区的版本。
+
+请注意，手动设置分区版本是一项危险操作，仅建议在集群元数据出现问题时才使用该方式。在正常情况下，分区的版本会自动与其内部的 Tablet 保持一致。
+
+:::tip
+
+该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```sql
+ADMIN SET TABLE <table_name> PARTITION ( <partition_name> | <partition_id> ) 
+TO VERSION <version>
+```
+
+## 参数说明
+
+- `table_name`: 分区所属表的名称。
+- `partition_name`: 分区的名称。您需要使用 `partition_name` 或 `partition_id` 来指定分区。对于非分区表，`partition_name` 与表名相同。
+- `partition_id`: 分区的 ID。您需要使用 `partition_name` 或 `partition_id` 来指定分区。对于采用随机分桶策略的表，您必须使用 `partition_id` 来指定分区。
+- `version`: 要设置的分区版本。
+
+## 示例
+
+1. 将非分区表 `t1` 的版本设置为 `10`。
+
+    ```sql
+    ADMIN SET TABLE t1 PARTITION(t1) TO VERSION 10;
+    ```
+
+2. 将表 `t2` 中分区 `p1` 的版本设置为 `10`。
+
+    ```sql
+    ADMIN SET TABLE t2 PARTITION(p1) TO VERSION 10;
+    ```
+
+3. 将 ID 为 `123456` 的分区的版本设置为 `10`。`t3` 为采用随机分桶策略的表。
+
+    ```sql
+    ADMIN SET TABLE t3 PARTITION('123456') TO VERSION 10;
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SET_REPLICA_STATUS.md b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SET_REPLICA_STATUS.md
new file mode 100644
index 00000000000000..64bfb59ff06827
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SET_REPLICA_STATUS.md
@@ -0,0 +1,51 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN SET REPLICA STATUS
+
+## 功能
+
+该语句用于设置指定副本的状态。
+
+该命令目前仅用于手动将某些副本状态设置为 bad 或 ok，从而使得系统能够自动修复这些副本。
+
+:::tip
+
+该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```sql
+ADMIN SET REPLICA STATUS
+PROPERTIES ("key" = "value", ...)
+```
+
+目前支持如下属性：
+
+**tablet_id**：必需。指定一个 Tablet Id。
+
+**backend_id**：必需。指定 Backend Id。
+
+**status**：必需。指定状态。当前仅支持 "bad" 或 "ok"。
+
+如果指定的副本不存在，或状态已经是 bad，则会被忽略。
+
+**注意：**
+设置为 bad 状态的副本可能立刻被删除，请谨慎操作。
+
+## 示例
+
+1. 设置 tablet 10003 在 BE 10001 上的副本状态为 bad。
+
+    ```sql
+    ADMIN SET REPLICA STATUS PROPERTIES("tablet_id" = "10003", "backend_id" = "10001", "status" = "bad");
+    ```
+
+2. 设置 tablet 10003 在 BE 10001 上的副本状态为 ok。
+
+    ```sql
+    ADMIN SET REPLICA STATUS PROPERTIES("tablet_id" = "10003", "backend_id" = "10001", "status" = "ok");
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SHOW_REPLICA_DISTRIBUTION.md b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SHOW_REPLICA_DISTRIBUTION.md
new file mode 100644
index 00000000000000..fccc5285bc9ff4
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SHOW_REPLICA_DISTRIBUTION.md
@@ -0,0 +1,39 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN SHOW REPLICA DISTRIBUTION
+
+## 功能
+
+该语句用于展示一个表或分区副本分布状态。
+
+:::tip
+
+该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```sql
+ADMIN SHOW REPLICA DISTRIBUTION FROM [db_name.]tbl_name [PARTITION (p1, ...)]
+```
+
+说明：
+
+结果中的 Graph 列以图形的形式展示副本分布比例。
+
+## 示例
+
+1. 查看表的副本分布
+
+    ```sql
+    ADMIN SHOW REPLICA DISTRIBUTION FROM tbl1;
+    ```
+
+2. 查看表的分区的副本分布
+
+    ```sql
+    ADMIN SHOW REPLICA DISTRIBUTION FROM db1.tbl1 PARTITION(p1, p2);
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SHOW_REPLICA_STATUS.md b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SHOW_REPLICA_STATUS.md
new file mode 100644
index 00000000000000..ce7e7dae0f7201
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/ADMIN_SHOW_REPLICA_STATUS.md
@@ -0,0 +1,55 @@
+---
+displayed_sidebar: docs
+---
+
+# ADMIN SHOW REPLICA STATUS
+
+## 功能
+
+该语句用于展示一个表或分区的副本状态信息。
+
+:::tip
+
+该操作需要 SYSTEM 级 OPERATE 权限。请参考 [GRANT](../../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```sql
+ADMIN SHOW REPLICA STATUS FROM [db_name.]tbl_name [PARTITION (p1, ...)]
+[WHERE STATUS [!]= "replica_status"]
+```
+
+说明：
+
+```plain text
+replica_status:
+OK:             replica 处于健康状态
+DEAD:           replica 所在 Backend 不可用
+VERSION_ERROR:  replica 数据版本有缺失
+SCHEMA_ERROR:   replica 的 schema hash 不正确
+MISSING:        replica 不存在
+```
+
+## 示例
+
+1. 查看表全部的副本状态。
+
+    ```sql
+    ADMIN SHOW REPLICA STATUS FROM db1.tbl1;
+    ```
+
+2. 查看表某个分区状态为 VERSION_ERROR 的副本。
+
+    ```sql
+    ADMIN SHOW REPLICA STATUS FROM tbl1 PARTITION (p1, p2)
+    WHERE STATUS = "VERSION_ERROR";
+    ```
+
+3. 查看表所有状态不健康的副本。
+
+    ```sql
+    ADMIN SHOW REPLICA STATUS FROM tbl1
+    WHERE STATUS != "OK";
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/SHOW_TABLE_STATUS.md b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/SHOW_TABLE_STATUS.md
new file mode 100644
index 00000000000000..9aa0b953834b4c
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/SHOW_TABLE_STATUS.md
@@ -0,0 +1,40 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW TABLE STATUS
+
+## 功能
+
+该语句用于查看 Table 的一些信息。
+
+:::tip
+
+该操作不需要权限。
+
+:::
+
+## 语法
+
+```sql
+SHOW TABLE STATUS
+[FROM db] [LIKE "pattern"]
+```
+
+> **说明**
+>
+> 该语句主要用于兼容 MySQL 语法，目前仅显示 Comment 等少量信息。
+
+## 示例
+
+1. 查看当前数据库下所有表的信息
+
+    ```SQL
+    SHOW TABLE STATUS;
+    ```
+
+2. 查看指定数据库下，名称包含 example 的表的信息
+
+    ```SQL
+    SHOW TABLE STATUS FROM db LIKE "%example%";
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/_category_.yml b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/_category_.yml
new file mode 100644
index 00000000000000..657c29ab60637d
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/cluster-management/tablet_replica/_category_.yml
@@ -0,0 +1,6 @@
+position: 40 # float position is supported
+label: 'Tablet，Replica 检查修复'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/ALTER_DATABASE.md b/docs/zh/sql-reference/sql-statements/data-definition/ALTER_DATABASE.md
deleted file mode 100644
index 38280e9fb634a3..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/ALTER_DATABASE.md
+++ /dev/null
@@ -1,77 +0,0 @@
----
-keywords: ['xiugai'] 
-displayed_sidebar: "Chinese"
----
-
-# ALTER DATABASE
-
-## 功能
-
-该语句用于设置指定数据库的属性。
-
-:::tip
-
-该操作需要对应数据库的 ALTER 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-### 设置数据库数据量配额
-
-单位为 B/K/KB/M/MB/G/GB/T/TB/P/PB。
-
-```sql
-ALTER DATABASE <db_name> SET DATA QUOTA <quota>
-```
-
-### 重命名数据库
-
-```sql
-ALTER DATABASE <db_name> RENAME <new_db_name>
-```
-
-### 设置数据库的副本数量配额
-
-```sql
-ALTER DATABASE <db_name> SET REPLICA QUOTA <quota>
-```
-
-说明：
-
-```plain text
-重命名数据库后，如需要，请使用 REVOKE 和 GRANT 命令修改相应的用户权限。
-数据库的默认数据量配额和默认副本数量配额均为 2^63 - 1。
-```
-
-## 示例
-
-1. 设置指定数据库数据量配额。
-
-    ```SQL
-    ALTER DATABASE example_db SET DATA QUOTA 10995116277760B;
-    -- 上述单位为字节，等价于下面的语句
-    ALTER DATABASE example_db SET DATA QUOTA 10T;
-    ALTER DATABASE example_db SET DATA QUOTA 100G;
-    ALTER DATABASE example_db SET DATA QUOTA 200M;
-    ```
-
-2. 将数据库 `example_db` 重命名为 `example_db2`。
-
-    ```SQL
-    ALTER DATABASE example_db RENAME example_db2;
-    ```
-
-3. 设定指定数据库副本数量配额。
-
-    ```SQL
-    ALTER DATABASE example_db SET REPLICA QUOTA 102400;
-    ```
-
-## 相关参考
-
-- [CREATE DATABASE](CREATE_DATABASE.md)
-- [USE](../data-definition/USE.md)
-- [SHOW DATABASES](../data-manipulation/SHOW_DATABASES.md)
-- [DESC](../Utility/DESCRIBE.md)
-- [DROP DATABASE](../data-definition/DROP_DATABASE.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md
deleted file mode 100644
index ef35969e5d505b..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md
+++ /dev/null
@@ -1,117 +0,0 @@
----
-keywords: ['xiugai'] 
-displayed_sidebar: "Chinese"
----
-
-# ALTER MATERIALIZED VIEW
-
-## 功能
-
-此 SQL 语句可以：
-
-- 变更异步物化视图的名称
-- 变更异步物化视图的刷新策略
-- 变更异步物化视图的状态为 Active 或 Inactive
-- 原子替换异步物化视图
-- 变更异步物化视图的属性
-
-  您可以使用此 SQL 语句变更异步物化视图的以下属性：
-
-  - `partition_ttl_number`
-  - `partition_refresh_number`
-  - `resource_group`
-  - `auto_refresh_partitions_limit`
-  - `excluded_trigger_tables`
-  - `mv_rewrite_staleness_second`
-  - `unique_constraints`
-  - `foreign_key_constraints`
-  - `colocate_with`
-  - 所有 Session 变量属性。有关 Session 变量，详细信息请见 [系统变量](../../../reference/System_variable.md)。
-
-:::tip
-- 该操作需要对应物化视图的 ALTER 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-- ALTER MATERIALIZED VIEW 不支持直接修改构建物化视图的查询语句。您可以重新构建物化视图，并通过 ALTER MATERIALIZED VIEW SWAP WITH 将其与原始物化视图替换。
-:::
-
-## 语法
-
-```SQL
-ALTER MATERIALIZED VIEW [db_name.]<mv_name> 
-    { RENAME [db_name.]<new_mv_name> 
-    | REFRESH <new_refresh_scheme_desc> 
-    | ACTIVE | INACTIVE 
-    | SWAP WITH <mv2_name>
-    | SET ( "<key>" = "<value>"[,...]) }
-```
-
-## 参数
-
-| **参数**                | **必选** | **说明**                                                     |
-| ----------------------- | -------- | ---------------------------------------------------------- |
-| mv_name                 | 是       | 待变更的物化视图的名称。                                       |
-| new_refresh_scheme_desc | 否       | 新的刷新机制，详细信息请见 [SQL 参考 - CREATE MATERIALIZED VIEW - 参数](../data-definition/CREATE_MATERIALIZED_VIEW.md#参数)。 |
-| new_mv_name             | 否       | 新的物化视图的名称。                                           |
-| ACTIVE                  | 否       | 将物化视图的状态设置为 Active。如果物化视图的基表发生更改，例如被删除后重新创建，StarRocks 会自动将该物化视图的状态设置为 Inactive，以避免原始元数据与更改后的基表不匹配的情况。状态为 Inactive 的物化视图无法用于查询加速或改写。更改基表后，您可以使用此 SQL 将该物化视图的状态设置为 Active。 |
-| INACTIVE                | 否       | 将物化视图的状态设置为 Inactive。Inactive 状态的物化视图无法被刷新，但您仍然可以将其作为表直接查询。 |
-| SWAP WITH               | 否       | 同另一物化视图进行原子替换。替换前，StarRocks 会进行必要的一致性检查。|
-| key                     | 否       | 待变更的属性的名称，详细信息请见 [SQL 参考 - CREATE MATERIALIZED VIEW - 参数](../data-definition/CREATE_MATERIALIZED_VIEW.md#参数)。<br />**说明**<br />如需更改物化视图的 Session 变量属性，则必须为 Session 属性添加 `session.` 前缀，例如，`session.query_timeout`。您无需为非 Session 属性指定前缀，例如，`mv_rewrite_staleness_second`。 |
-| value                   | 否       | 待变更的属性的值。                                             |
-
-## 示例
-
-示例一：修改物化视图名称
-
-```SQL
-ALTER MATERIALIZED VIEW lo_mv1 RENAME lo_mv1_new_name;
-```
-
-示例二：修改物化视图刷新间隔
-
-```SQL
-ALTER MATERIALIZED VIEW lo_mv2 REFRESH ASYNC EVERY(INTERVAL 1 DAY);
-```
-
-示例三：修改物化视图属性，调整物化视图刷新 Timeout 为一小时（默认）。
-
-```SQL
-ALTER MATERIALIZED VIEW mv1 SET ("session.query_timeout" = "3600");
-```
-
-示例四：修改物化视图状态为 Active。
-
-```SQL
-ALTER MATERIALIZED VIEW order_mv ACTIVE;
-```
-
-示例五：原子替换物化视图 `order_mv` 和 `order_mv1`。
-
-```SQL
-ALTER MATERIALIZED VIEW order_mv SWAP WITH order_mv1;
-```
-
-示例六：为物化视图刷新开启 Profile（默认开启）。
-
-```SQL
-ALTER MATERIALIZED VIEW mv1 SET ("session.enable_profile" = "true");
-```
-
-示例七：为物化视图刷新开启中间结果落盘（自 v3.1 起默认开启），并设置落盘模式为 `force`。
-
-```SQL
--- 为物化视图刷新开启中间结果落盘。
-ALTER MATERIALIZED VIEW mv1 SET ("session.enable_spill" = "true");
--- 设置落盘模式为 `force`。
-ALTER MATERIALIZED VIEW mv1 SET ("session.spill_mode" = "force");
-```
-
-示例八：调整 Optimizer Timeout 为 30 秒（自 v3.3 起为默认值），适用于物化视图查询包含外表或多个 Join。
-
-```SQL
-ALTER MATERIALIZED VIEW mv1 SET ("session.new_planner_optimize_timeout" = "30000");
-```
-
-示例九：调整物化视图查询改写 Staleness 时间为 600 秒。
-
-```SQL
-ALTER MATERIALIZED VIEW mv1 SET ("mv_rewrite_staleness_second" = "600");
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/ALTER_RESOURCE.md b/docs/zh/sql-reference/sql-statements/data-definition/ALTER_RESOURCE.md
deleted file mode 100644
index d4c0254b3b2452..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/ALTER_RESOURCE.md
+++ /dev/null
@@ -1,37 +0,0 @@
----
-keywords: ['xiugai'] 
-displayed_sidebar: "Chinese"
----
-
-# ALTER RESOURCE
-
-## 功能
-
-修改资源的属性。仅 StarRocks 2.3 及以上版本支持修改资源属性。
-
-## 语法
-
-```SQL
-ALTER RESOURCE 'resource_name' SET PROPERTIES ("key"="value", ...)
-```
-
-## 参数说明
-
-- `resource_name`：待修改的资源名称。
-- `PROPERTIES ("key"="value", ...)`：资源属性。不同类型的资源支持修改不同的属性，当前支持修改以下资源的 Hive metastore 地址。
-  - Apache Iceberg 资源支持修改以下属性：
-    - `iceberg.catalog-impl`：[custom catalog](../../../data_source/External_table.md#步骤一创建-iceberg-资源) 的全限定类名。
-    - `iceberg.catalog.hive.metastore.uris`：Hive metastore 地址。
-  - Apache Hive™ 和 Apache Hudi 资源支持修改 `hive.metastore.uris`，即 Hive metastore 地址。
-
-## 注意事项
-
-引用一个资源创建外部表后，如果修改了该资源的 Hive metastore 地址会导致该外部表不可用。若仍想使用该外部表查询数据，需保证新 Hive metastore 中存在与原 Hive metastore 中名称和表结构相同的数据表。
-
-## 示例
-
-修改 Apache Hive™ 资源 `hive0` 的 Hive metastore 地址。
-
-```SQL
-ALTER RESOURCE 'hive0' SET PROPERTIES ("hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083")
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/ALTER_TABLE.md b/docs/zh/sql-reference/sql-statements/data-definition/ALTER_TABLE.md
deleted file mode 100644
index dba70c4237c2b1..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/ALTER_TABLE.md
+++ /dev/null
@@ -1,1224 +0,0 @@
----
-keywords: ['xiugai'] 
-displayed_sidebar: "Chinese"
----
-
-# ALTER TABLE
-
-## 功能
-
-该语句用于修改已有表，包括：
-
-- [修改表名、分区名、索引名、列名](#rename-对名称进行修改)
-- [修改表注释](#修改表的注释31-版本起)
-- [修改分区（增删分区和修改分区属性）](#操作-partition-相关语法)
-- [修改分桶方式和分桶数量](#修改分桶方式和分桶数量自-32-版本起)
-- [修改列（增删列和修改列顺序）](#修改列增删列和修改列顺序)
-- [创建或删除 rollup index](#操作-rollup-index-语法)
-- [修改 bitmap index](#bitmap-index-修改)
-- [修改表的属性](#修改表的属性)
-- [对表进行原子替换](#swap-将两个表原子替换)
-- [手动执行 compaction 合并表数据](#手动-compaction31-版本起)
-
-:::tip
-该操作需要有对应表的 ALTER 权限。
-:::
-
-## 语法
-
-ALTER TABLE 语法格式如下：
-
-```SQL
-ALTER TABLE [<db_name>.]<tbl_name>
-alter_clause1[, alter_clause2, ...]
-```
-
-其中 **alter_clause** 分为 rename、comment、partition、bucket、column、rollup index、bitmap index、table property、swap、compaction 相关修改操作：
-
-- rename: 修改表名、rollup index 名、partition 名或列名（从 3.3.2 版本开始支持）。
-- comment: 修改表的注释。**从 3.1 版本开始支持。**
-- partition: 修改分区属性，删除分区，增加分区。
-- bucket：修改分桶方式和分桶数量。
-- column: 增加列，删除列，调整列顺序，修改列类型。*
-- rollup index: 创建或删除 rollup index。
-- bitmap index: 修改 bitmap index。
-- swap: 原子替换两张表。
-- compaction: 对指定表或分区手动执行 Compaction（数据版本合并）。**从 3.1 版本开始支持。**
-
-## 使用限制和注意事项
-
-- partition、column 和 rollup index <!--是否包含compaction，bucket和column/rollupindex可以在一起吗-->这些操作不能同时出现在一条 `ALTER TABLE` 语句中。
-- 当前还不支持修改列注释。
-- 每张表仅支持一个进行中的 Schema Change 操作。不能对同一张表同时执行两条 Schema Change 命令。
-- bucket、column、rollup index <!--是否包含compaction和fast schema evolution-->是异步操作，命令提交成功后会立即返回一个成功消息，您可以使用 [SHOW ALTER TABLE](../data-manipulation/SHOW_ALTER.md) 语句查看操作的进度。如果需要取消正在进行的操作，则您可以使用 [CANCEL ALTER TABLE](../data-manipulation/SHOW_ALTER.md)。
-- rename、comment、partition、bitmap index 和 swap 是同步操作，命令返回表示执行完毕。
-
-### Rename 对名称进行修改
-
-#### 修改表名
-
-语法：
-
-```sql
-ALTER TABLE <tbl_name> RENAME <new_tbl_name>;
-```
-
-#### 修改 rollup index 名称 (RENAME ROLLUP)
-
-语法：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-RENAME ROLLUP old_rollup_name new_rollup_name;
-```
-
-#### 修改 partition 名称 (RENAME PARTITION)
-
-语法：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-RENAME PARTITION <old_partition_name> <new_partition_name>;
-```
-
-#### 修改列名（RENAME COLUMN）
-
-自 v3.3.2 起，StarRocks 支持修改列名。
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-RENAME COLUMN <old_col_name> [ TO ] <new_col_name>
-```
-
-:::note
-
-- 在将某列由 A 重命名为 B 后，不支持继续增加 A 列。
-- 在列名变更后，基于该列创建的物化视图将不再生效，您需要根据新的列名重新创建。
-
-:::
-
-### 修改表的注释（3.1 版本起）
-
-语法：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name> COMMENT = "<new table comment>";
-```
-
-:::tip
-当前还不支持修改列注释。
-:::
-
-### 操作 partition 相关语法
-
-#### 增加分区 (ADD PARTITION(S))
-
-增加分区时支持使用 Range 分区和 List 分区。
-
-语法：
-
-- Range 分区
-
-    ```SQL
-    ALTER TABLE
-        ADD { single_range_partition | multi_range_partitions } [distribution_desc] ["key"="value"];
-    
-    single_range_partition ::=
-        PARTITION [IF NOT EXISTS] <partition_name> VALUES partition_key_desc
-
-    partition_key_desc ::=
-        { LESS THAN { MAXVALUE | value_list }
-        | [ value_list , value_list ) } -- 注意此处的 [ 代表左闭合区间
-
-    value_list ::=
-        ( <value> [, ...] )
-
-    multi_range_partitions ::=
-        { PARTITIONS START ("<start_date_value>") END ("<end_date_value>") EVERY ( INTERVAL <N> <time_unit> )
-        | PARTITIONS START ("<start_integer_value>") END ("<end_integer_value>") EVERY ( <granularity> ) } -- 即使 START、END 所指定的分区列值为整数，也需要使用英文引号包裹，而 EVERY 子句中的分区增量值不用英文引号包裹。
-    ```
-
-- List 分区
-
-    ```SQL
-    ALTER TABLE
-        ADD PARTITION <partition_name> VALUES IN (value_list) [distribution_desc] ["key"="value"];
-
-    value_list ::=
-        value_item [, ...]
-
-    value_item ::=
-        { <value> | ( <value> [, ...] ) }
-    ```
-
-参数：
-
-- 分区相关参数
-
-  - Range 分区支持新增单个分区 `single_range_partition` 或者批量创建分区 `multi_range_partition`。
-  - List 分区仅支持新增单个分区。
-
-- `distribution_desc`：
-
-   可以为新的分区单独设置分桶数量，但是不支持单独设置分桶方式。
-
-- `"key"="value"`：
-
-   可以为新的分区设置属性，具体说明见 [CREATE TABLE](./CREATE_TABLE.md#properties)。
-
-示例：
-
-- Range 分区
-
-  - 如果建表时指定分区列为 `event_day`，例如 `PARTITION BY RANGE(event_day)`，并且建表后需要新增一个分区，则可以执行：
-
-    ```sql
-    ALTER TABLE site_access ADD PARTITION p4 VALUES LESS THAN ("2020-04-30");
-    ```
-
-  - 如果建表时指定分区列为 `datekey`，例如 `PARTITION BY RANGE (datekey)`，并且建表后需要批量新增多个分区，则可以执行：
-
-    ```sql
-    ALTER TABLE site_access
-        ADD PARTITIONS START ("2021-01-05") END ("2021-01-10") EVERY (INTERVAL 1 DAY);
-    ```
-
-- List 分区
-
-  - 如果建表时指定单个分区列，例如 `PARTITION BY LIST (city)`，并且建表后需要新增一个分区，则可以执行：
-
-    ```sql
-    ALTER TABLE t_recharge_detail2
-    ADD PARTITION pCalifornia VALUES IN ("Los Angeles","San Francisco","San Diego");
-    ```
-
-  - 如果建表时指定多个分区列，例如 `PARTITION BY LIST (dt,city)`，并且建表后需要新增一个分区，则可以执行：
-
-    ```sql
-    ALTER TABLE t_recharge_detail4 
-    ADD PARTITION p202204_California VALUES IN
-    (
-        ("2022-04-01", "Los Angeles"),
-        ("2022-04-01", "San Francisco"),
-        ("2022-04-02", "Los Angeles"),
-        ("2022-04-02", "San Francisco")
-    );
-    ```
-
-#### 删除分区 (DROP PARTITION(S))
-
-删除单个分区：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-DROP PARTITION [ IF EXISTS ] <partition_name> [ FORCE ]
-```
-
-批量删除分区（自 v3.3.1 起支持）：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-DROP [ TEMPORARY ] PARTITIONS [ IF EXISTS ]  { partition_name_list | multi_range_partitions } [ FORCE ] 
-
-partion_name_list ::= ( <partition_name> [, ... ] )
-
-multi_range_partitions ::=
-    { START ("<start_date_value>") END ("<end_date_value>") EVERY ( INTERVAL <N> <time_unit> )
-    | START ("<start_integer_value>") END ("<end_integer_value>") EVERY ( <granularity> ) } -- 即使 START、END 所指定的分区列值为整数，也需要使用英文引号包裹，而 EVERY 子句中的分区增量值不用英文引号包裹。
-```
-
-关于 `multi_range_partitions` 的说明：
-
-- `multi_range_partitions` 仅适用于 Range 分区。
-- 其中涉及的参数与 [增加分区 ADD PARTITION(S)](#增加分区-add-partitions) 中的相同。
-- 仅支持基于单个分区键的分区。
-
-:::note
-
-- 分区表需要至少要保留一个分区。
-- 如果未指定 FORCE 关键字，您可以通过 [RECOVER](../data-definition/backup_restore/RECOVER.md) 语句恢复一定时间范围内（默认 1 天）删除的分区。
-- 如果指定了 FORCE 关键字，则系统不会检查该分区是否存在未完成的事务，分区将直接被删除并且不能被恢复，一般不建议执行此操作。
-
-:::
-
-#### 增加临时分区 (ADD TEMPORARY PARTITION)
-
-详细使用信息，请查阅[临时分区](../../../table_design/Temporary_partition.md)。
-
-语法：
-
-```SQL
-ALTER TABLE [<db_name>.]<tbl_name>
-ADD TEMPORARY PARTITION [IF NOT EXISTS] <partition_name>
-partition_desc ["key"="value"]
-[DISTRIBUTED BY HASH (k1[,k2 ...]) [BUCKETS num]];
-```
-
-#### 使用临时分区替换原分区
-
-语法：
-
-```SQL
-ALTER TABLE [<db_name>.]<tbl_name>
-REPLACE PARTITION <partition_name> 
-partition_desc ["key"="value"]
-WITH TEMPORARY PARTITION
-partition_desc ["key"="value"]
-[PROPERTIES ("key"="value", ...)]
-```
-
-#### 删除临时分区 (DROP TEMPORARY PARTITION)
-
-语法：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-DROP TEMPORARY PARTITION <partition_name>;
-```
-
-#### 修改分区属性 (MODIFY PARTITION)
-
-**语法：**
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-    MODIFY PARTITION { <partition_name> | partition_name_list | (*) }
-        SET ("key" = "value", ...);
-```
-
-**使用说明：**
-
-- 当前支持修改分区的下列属性：
-  - storage_medium
-  - storage_cooldown_ttl 或 storage_cooldown_time
-  - replication_num
-
-- 对于单分区表，分区名同表名。对于多分区表，如果需要修改所有分区的属性，则使用 `(*)` 更加方便。
-- 执行 `SHOW PARTITIONS FROM <tbl_name>` 查看修改后分区属性。
-
-### 修改分桶方式和分桶数量（自 3.2 版本起）
-
-语法：
-
-```SQL
-ALTER TABLE [<db_name>.]<table_name>
-[ partition_names ]
-[ distribution_desc ]
-
-partition_names ::= 
-    (PARTITION | PARTITIONS) ( <partition_name> [, <partition_name> ...] )
-
-distribution_desc ::=
-    DISTRIBUTED BY RANDOM [ BUCKETS <num> ] |
-    DISTRIBUTED BY HASH ( <column_name> [, <column_name> ...] ) [ BUCKETS <num> ]
-```
-
-示例：
-
-假设原表为明细表，分桶方式为 Hash 分桶，分桶数量为自动设置。
-
-```SQL
-CREATE TABLE IF NOT EXISTS details (
-    event_time DATETIME NOT NULL COMMENT "datetime of event",
-    event_type INT NOT NULL COMMENT "type of event",
-    user_id INT COMMENT "id of user",
-    device_code INT COMMENT "device code",
-    channel INT COMMENT ""
-)
-DUPLICATE KEY(event_time, event_type)
-PARTITION BY date_trunc('day', event_time)
-DISTRIBUTED BY HASH(user_id);
-
--- 插入多天的数据
-INSERT INTO details (event_time, event_type, user_id, device_code, channel) VALUES
--- 11 月 26 日的数据
-('2023-11-26 08:00:00', 1, 101, 12345, 2),
-('2023-11-26 09:15:00', 2, 102, 54321, 3),
-('2023-11-26 10:30:00', 1, 103, 98765, 1),
--- 11 月 27 日的数据
-('2023-11-27 08:30:00', 1, 104, 11111, 2),
-('2023-11-27 09:45:00', 2, 105, 22222, 3),
-('2023-11-27 11:00:00', 1, 106, 33333, 1),
--- 11 月 28 日的数据
-('2023-11-28 08:00:00', 1, 107, 44444, 2),
-('2023-11-28 09:15:00', 2, 108, 55555, 3),
-('2023-11-28 10:30:00', 1, 109, 66666, 1);
-```
-
-#### 仅修改分桶方式
-
-> **注意**
->
-> - 修改分桶方式针对整个表的所有分区生效，不能仅仅针对某个分区生效。
-> - 虽然仅修改分桶方式，没有修改分桶数量，但是您仍然需要在语句中说明分桶数量 `BUCKETS <num>`，如果不指定，则表示由 StarRocks 自动设置分桶数量。
-
-- 将原先的 Hash 分桶修改为 Random 分桶，并且分桶数量仍然由 StarRocks 自动设置。
-
-  ```SQL
-  ALTER TABLE details DISTRIBUTED BY RANDOM;
-  ```
-
-- 将 Hash 分桶时所使用的分桶键从原先的 `event_time, event_type` 修改为 `user_id, event_time`。并且分桶数量仍然由 StarRocks 自动设置。
-
-  ```SQL
-  ALTER TABLE details DISTRIBUTED BY HASH(user_id, event_time);
-  ```
-
-#### 仅修改分桶数量
-
-> **注意**
->
-> 虽然仅修改分桶数量，没有修改分桶方式，但是您仍然需要在语句中说明分桶方式，例如示例中的 `HASH(user_id)`。
-
-- 将所有分区的分桶数量从原先的由 StarRocks 自动设置修改为 10。
-
-  ```SQL
-  ALTER TABLE details DISTRIBUTED BY HASH(user_id) BUCKETS 10;
-  ```
-
-- 将指定分区的分桶数量从原先的由 StarRocks 自动设置修改为 15。
-
-  ```SQL
-  ALTER TABLE details PARTITIONS (p20231127, p20231128) DISTRIBUTED BY HASH(user_id) BUCKETS 15;
-  ```
-
-  > **说明**
-  >
-  > 分区名称可以执行 `SHOW PARTITIONS FROM <table_name>;` 进行查看。
-
-#### 同时修改分桶方式和分桶数量
-
-> **注意**
->
-> 同时修改分桶方式和分桶数量针对整个表的所有分区生效，不能仅仅针对某个分区生效。
-
-- 分桶方式从原先的 Hash 分桶修改为 Random 分桶，并且分桶数量从原先的由 StarRocks 自动设置修改为 10。
-
-   ```SQL
-   ALTER TABLE details DISTRIBUTED BY RANDOM BUCKETS 10;
-   ```
-
-- 将 Hash 分桶时所使用的分桶键从原先的 `event_time, event_type` 修改为 `user_id, event_time`，并且分桶数量从原先的由 StarRocks 自动设置修改为 10。
-
-  ```SQL
-  ALTER TABLE details DISTRIBUTED BY HASH(user_id, event_time) BUCKETS 10;
-  ```
-
-### 修改列（增删列和修改列顺序）
-
-下文中的 index 为物化索引。建表成功后表为 base 表 (base index)，基于 base 表可 [创建 rollup index](#创建-rollup-index-add-rollup)。
-
-base index 和 rollup index 都是物化索引。下方语句在编写时如果没有指定 `rollup_index_name`，默认操作基表。
-
-#### 向指定 index 的指定位置添加一列 (ADD COLUMN)
-
-语法：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-ADD COLUMN column_name column_type [KEY | agg_type] [DEFAULT "default_value"]
-[AFTER column_name|FIRST]
-[TO rollup_index_name]
-[PROPERTIES ("key"="value", ...)]
-```
-
-使用说明：
-
-- 聚合表如果增加 value 列，需要指定 agg_type。
-- 非聚合表（如 DUPLICATE KEY）如果增加 key 列，需要指定 KEY 关键字。
-- 不能在 rollup index 中增加 base index 中已经存在的列，如有需要，可以重新创建一个 rollup index。
-
-#### 向指定 index 添加多列
-
-语法：
-
-- 添加多列:
-
-  ```sql
-  ALTER TABLE [<db_name>.]<tbl_name>
-  ADD COLUMN (column_name1 column_type [KEY | agg_type] DEFAULT "default_value", ...)
-  [TO rollup_index_name]
-  [PROPERTIES ("key"="value", ...)]
-  ```
-
-- 添加多列的同时通过 `AFTER` 指定列的添加位置：
-
-  ```sql
-  ALTER TABLE [<db_name>.]<tbl_name>
-  ADD COLUMN column_name1 column_type [KEY | agg_type] DEFAULT "default_value" AFTER column_name,
-  ADD COLUMN column_name2 column_type [KEY | agg_type] DEFAULT "default_value" AFTER column_name
-  [, ...]
-  [TO rollup_index_name]
-  [PROPERTIES ("key"="value", ...)]
-  ```
-
-注意：
-
-1. 聚合表如果增加 value 列，需要指定 agg_type。
-2. 非聚合表如果增加 key 列，需要指定 KEY 关键字。
-3. 不能在 rollup index 中增加 base index 中已经存在的列，如有需要，可以重新创建一个 rollup index。
-
-#### 增加生成列
-
-语法：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-ADD COLUMN col_name data_type [NULL] AS generation_expr [COMMENT 'string']
-```
-
-增加生成列并且指定其使用的表达式。[生成列](../generated_columns.md)用于预先计算并存储表达式的结果，可以加速包含复杂表达式的查询。自 v3.1，StarRocks 支持该功能。
-
-#### 从指定 index 中删除一列 (DROP COLUMN)
-
-语法：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-DROP COLUMN column_name
-[FROM rollup_index_name];
-```
-
-注意：
-
-1. 不能删除分区列。
-2. 如果是从 base index 中删除列，则如果 rollup index 中包含该列，也会被删除。
-
-#### 修改指定 index 的列类型以及列位置 (MODIFY COLUMN)
-
-语法：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-MODIFY COLUMN column_name column_type [KEY | agg_type] [NULL | NOT NULL] [DEFAULT "default_value"]
-[AFTER column_name|FIRST]
-[FROM rollup_index_name]
-[PROPERTIES ("key"="value", ...)]
-```
-
-注意：
-
-1. 聚合表如果修改 value 列，需要指定 agg_type。
-2. 非聚合类型如果修改 key 列，需要指定 KEY 关键字。
-3. 只能修改列的类型，列的其他属性维持原样（即其他属性需在语句中按照原属性显式的写出，参见示例中 [column](#column) 部分第 8 个例子）。
-4. 分区列不能做任何修改。
-5. 目前支持以下类型的转换（精度损失由用户保证）：
-
-    - TINYINT/SMALLINT/INT/BIGINT 转换成 TINYINT/SMALLINT/INT/BIGINT/DOUBLE。
-    - TINYINT/SMALLINT/INT/BIGINT/LARGEINT/FLOAT/DOUBLE/DECIMAL 转换成 VARCHAR。
-    - VARCHAR 支持修改最大长度。
-    - VARCHAR 转换成 TINYINT/SMALLINT/INT/BIGINT/LARGEINT/FLOAT/DOUBLE。
-    - VARCHAR 转换成 DATE (目前支持 "%Y-%m-%d"，"%y-%m-%d"， "%Y%m%d"，"%y%m%d"，"%Y/%m/%d，"%y/%m/%d " 六种格式化格式)
-    DATETIME 转换成 DATE(仅保留年-月-日信息，例如: `2019-12-09 21:47:05` &lt;--&gt; `2019-12-09`)
-    DATE 转换成 DATETIME(时分秒自动补零，例如: `2019-12-09` &lt;--&gt; `2019-12-09 00:00:00`)
-    - FLOAT 转换成 DOUBLE。
-    - INT 转换成 DATE (如果 INT 类型数据不合法则转换失败，原始数据不变。)
-
-#### 修改排序键
-
-自 3.0 版本起，支持修改主键表的排序键。自 3.3 版本起，支持修改明细表、聚合表和更新表的排序键。
-
-明细表和主键表中排序键可以为任意列的排序组合，聚合表和更新表中排序键必须包含所有 key 列，但是列的顺序无需与 key 列保持一致。
-
-语法：
-
-```SQL
-ALTER TABLE [<db_name>.]<table_name>
-[ order_desc ]
-
-order_desc ::=
-    ORDER BY <column_name> [, <column_name> ...]
-```
-
-示例：修改主键表中的排序键
-
-假设原表为主键表，排序键与主键耦合 `dt,order_id`。
-
-```SQL
-create table orders (
-    dt date NOT NULL,
-    order_id bigint NOT NULL,
-    user_id int NOT NULL,
-    merchant_id int NOT NULL,
-    good_id int NOT NULL,
-    good_name string NOT NULL,
-    price int NOT NULL,
-    cnt int NOT NULL,
-    revenue int NOT NULL,
-    state tinyint NOT NULL
-) PRIMARY KEY (dt, order_id)
-PARTITION BY date_trunc('day', dt)
-DISTRIBUTED BY HASH(order_id);
-```
-
-解耦排序键和主键，修改排序键为 `dt,revenue,state`。
-
-```SQL
-ALTER TABLE orders ORDER BY (dt,revenue,state);
-```
-
-#### STRUCT 类型列增删字段（MODIFY COLUMN ADD/DROP FIELD）
-
-自 v3.2.10 及 v3.3.2 起，StarRocks 支持向 STRUCT 类型列增删字段。该字段可以为嵌套 STRUCT 类型或存在于 ARRAY 类型中。
-
-语法：
-
-```sql
--- 增加字段
-ALTER TABLE [<db_name>.]<tbl_name>
-MODIFY COLUMN <column_name> ADD FIELD <field_name>  <field_type> [AFTER <prior_field_name> |FIRST]
-
--- 删除字段
-ALTER TABLE [<db_name>.]<tbl_name>
-MODIFY COLUMN <column_name> DROP FIELD <field_name>
-```
-
-参数：
-
-- `field_name`：需要增加或删除字段的名称。可以是单独的字段名，表示第一层级的字段，例如 `new_field_name`。也可以是 Column Access Path，用以表示嵌套层级的字段，例如 `lv1_k1.lv2_k2.new_field_name`。
-- `prior_field_name`：新增字段的前一个字段。与 AFTER 关键字合用，可以表示新加字段的顺序。如果指定 FIRST 关键字，表示新增第一个字段，则无需指定该参数。`prior_field_name` 的层级由 `field_name` 决定，无需手动指定。
-
-有关示例，参考 [示例 - Column -14](#column)。
-
-:::note
-
-- 目前仅支持存算一体集群。
-- 对应表必须开启 `fast_schema_evolution`。
-- 不支持向 MAP 类型中的 STRUCT 增删字段。
-- 新增字段不支持指定默认值，Nullable 等属性。默认为 Nullable，默认值为 null。
-- 使用该功能后，不支持直接将集群降级至不具备该功能的版本。
-
-:::
-
-### 操作 rollup index 语法
-
-#### 创建 rollup index (ADD ROLLUP)
-
-**RollUp 表索引**: shortkey index 可加速数据查找，但 shortkey index 依赖维度列排列次序。如果使用非前缀的维度列构造查找谓词，用户可以为数据表创建若干 RollUp 表索引。 RollUp 表索引的数据组织和存储和数据表相同，但 RollUp 表拥有自身的 shortkey index。用户创建 RollUp 表索引时，可选择聚合的粒度，列的数量，维度列的次序。使频繁使用的查询条件能够命中相应的 RollUp 表索引。
-
-语法：
-
-```SQL
-ALTER TABLE [<db_name>.]<tbl_name> 
-ADD ROLLUP rollup_name (column_name1, column_name2, ...)
-[FROM from_index_name]
-[PROPERTIES ("key"="value", ...)];
-```
-
-PROPERTIES: 支持设置超时时间，默认超时时间为 1 天。
-
-例子：
-
-```SQL
-ALTER TABLE [<db_name>.]<tbl_name> 
-ADD ROLLUP r1(col1,col2) from r0;
-```
-
-#### 批量创建 rollup index
-
-语法：
-
-```SQL
-ALTER TABLE [<db_name>.]<tbl_name>
-ADD ROLLUP [rollup_name (column_name1, column_name2, ...)
-[FROM from_index_name]
-[PROPERTIES ("key"="value", ...)],...];
-```
-
-例子：
-
-```SQL
-ALTER TABLE [<db_name>.]<tbl_name>
-ADD ROLLUP r1(col1,col2) from r0, r2(col3,col4) from r0;
-```
-
-> 注意
->
-1. 如果没有指定 from_index_name，则默认从 base index 创建。
-2. rollup 表中的列必须是 from_index 中已有的列。
-3. 在 properties 中，可以指定存储格式。具体请参阅 [CREATE TABLE](../data-definition/CREATE_TABLE.md) 章节。
-
-#### 删除 rollup index (DROP ROLLUP)
-
-语法：
-
-```SQL
-ALTER TABLE [<db_name>.]<tbl_name>
-DROP ROLLUP rollup_name [PROPERTIES ("key"="value", ...)];
-```
-
-例子：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name> DROP ROLLUP r1;
-```
-
-#### 批量删除 rollup index
-
-语法：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-DROP ROLLUP [rollup_name [PROPERTIES ("key"="value", ...)],...];
-```
-
-例子：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name> DROP ROLLUP r1, r2;
-```
-
-注意：
-
-不能删除 base index。
-
-### bitmap index 修改
-
-#### 创建 bitmap index (ADD INDEX)
-
-语法：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-ADD INDEX index_name (column [, ...],) [USING BITMAP] [COMMENT 'balabala'];
-```
-
-注意：
-
-1. 目前仅支持修改 bitmap index。
-2. bitmap index 仅在单列上创建。
-
-#### 删除 bitmap index (DROP INDEX)
-
-语法：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-DROP INDEX index_name;
-```
-
-### 修改表的属性
-
-语法：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-SET ("key" = "value",...)
-```
-
-参数说明：
-
-- `key` 表示表属性的名称，`value` 表示该表属性的配置。
-
-- 支持修改如下表属性：
-  - `replication_num`
-  - `default.replication_num`
-  - `storage_cooldown_ttl`
-  - `storage_cooldown_time`
-  - [动态分区相关属性 properties](../../../table_design/dynamic_partitioning.md)，比如 `dynamic_partition.enable`
-  - `enable_persistent_index`
-  - `bloom_filter_columns`
-  - `colocate_with`
-  - `bucket_size`（自 3.2 版本支持）
-
-注意：修改表的属性也可以合并到 schema change <!--这个 schema change 除了column相关的alter table还包括啥--> 操作中来修改，见[示例](#示例)部分。
-
-### Swap 将两个表原子替换
-
-语法：
-
-```sql
-ALTER TABLE [<db_name>.]<tbl_name>
-SWAP WITH <tbl_name>;
-```
-
-### 手动 Compaction（3.1 版本起）
-
-StarRocks 通过 Compaction 机制将导入的不同数据版本进行合并，将小文件合并成大文件，有效提升了查询性能。
-
-3.1 版本之前，支持通过两种方式来做 Compaction：
-
-- 系统自动在后台执行 Compaction。Compaction 的粒度是 BE 级，由后台自动执行，用户无法控制具体的数据库或者表。
-- 用户通过 HTTP 接口指定 Tablet 来执行 Compaction。
-
-3.1 版本之后，增加了一个 SQL 接口，用户可以通过执行 SQL 命令来手动进行 Compaction，可以指定表、单个或多个分区进行 Compaction。
-
-存算分离集群自 v3.3.0 起支持该功能。
-
-语法：
-
-```sql
--- 对整张表做 compaction。
-ALTER TABLE <tbl_name> COMPACT
-
--- 指定一个分区进行 compaction。
-ALTER TABLE <tbl_name> COMPACT <partition_name>
-
--- 指定多个分区进行 compaction。
-ALTER TABLE <tbl_name> COMPACT (<partition1_name>[,<partition2_name>,...])
-
--- 对多个分区进行 cumulative compaction。
-ALTER TABLE <tbl_name> CUMULATIVE COMPACT (<partition1_name>[,<partition2_name>,...])
-
--- 对多个分区进行 base compaction。
-ALTER TABLE <tbl_name> BASE COMPACT (<partition1_name>[,<partition2_name>,...])
-```
-
-执行完 Compaction 后，您可以通过查询 `information_schema` 数据库下的 `be_compactions` 表来查看 Compaction 后的数据版本变化 （`SELECT * FROM information_schema.be_compactions;`）。
-
-## 示例
-
-### Table
-
-1. 修改表的默认副本数量，新建分区副本数量默认使用此值。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    SET ("default.replication_num" = "2");
-    ```
-
-2. 修改单分区表的实际副本数量(只限单分区表)。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    SET ("replication_num" = "3");
-    ```
-
-3. 修改数据在多副本间的写入和同步方式。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    SET ("replicated_storage" = "false");
-    ```
-
-    以上示例表示将多副本的写入和同步方式设置为 leaderless replication，即数据同时写入到多个副本，不区分主从副本。更多信息，参见 [CREATE TABLE](CREATE_TABLE.md) 的 `replicated_storage` 参数描述。
-
-### Partition
-
-1. 增加分区，现有分区 [MIN, 2013-01-01)，增加分区 [2013-01-01, 2014-01-01)，使用默认分桶方式。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD PARTITION p1 VALUES LESS THAN ("2014-01-01");
-    ```
-
-2. 增加分区，使用新的分桶数。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD PARTITION p1 VALUES LESS THAN ("2015-01-01")
-    DISTRIBUTED BY HASH(k1) BUCKETS 20;
-    ```
-
-3. 增加分区，使用新的副本数。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD PARTITION p1 VALUES LESS THAN ("2015-01-01")
-    ("replication_num"="1");
-    ```
-
-4. 修改分区副本数。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    MODIFY PARTITION p1 SET("replication_num"="1");
-    ```
-
-5. 批量修改指定分区。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    MODIFY PARTITION (p1, p2, p4) SET("replication_num"="1");
-    ```
-
-6. 批量修改所有分区。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    MODIFY PARTITION (*) SET("storage_medium"="HDD");
-    ```
-
-7. 删除分区。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    DROP PARTITION p1;
-    ```
-
-8. 增加一个指定上下界的分区。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD PARTITION p1 VALUES [("2014-01-01"), ("2014-02-01"));
-    ```
-
-### Rollup index
-
-1. 创建 index `example_rollup_index`，基于 base index（k1, k2, k3, v1, v2），列式存储。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD ROLLUP example_rollup_index(k1, k3, v1, v2)
-    PROPERTIES("storage_type"="column");
-    ```
-
-2. 创建 index `example_rollup_index2`，基于 example_rollup_index（k1, k3, v1, v2）。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD ROLLUP example_rollup_index2 (k1, v1)
-    FROM example_rollup_index;
-    ```
-
-3. 创建 index `example_rollup_index3`，基于 base index (k1, k2, k3, v1), 自定义 rollup 超时时间一小时。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD ROLLUP example_rollup_index3(k1, k3, v1)
-    PROPERTIES("storage_type"="column", "timeout" = "3600");
-    ```
-
-4. 删除 index `example_rollup_index2`。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    DROP ROLLUP example_rollup_index2;
-    ```
-
-### Column
-
-1. 向 `example_rollup_index` 的 `col1` 后添加一个 key 列 `new_col`（非聚合表）。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD COLUMN new_col INT KEY DEFAULT "0" AFTER col1
-    TO example_rollup_index;
-    ```
-
-2. 向 `example_rollup_index` 的 `col1` 后添加一个 value 列 `new_col`（非聚合表）。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD COLUMN new_col INT DEFAULT "0" AFTER col1
-    TO example_rollup_index;
-    ```
-
-3. 向 `example_rollup_index` 的 `col1` 后添加一个 key 列 `new_col`（聚合表）。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD COLUMN new_col INT DEFAULT "0" AFTER col1
-    TO example_rollup_index;
-    ```
-
-4. 向 `example_rollup_index` 的 `col1` 后添加一个 value 列 `new_col`（SUM 聚合类型）（聚合表）。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD COLUMN new_col INT SUM DEFAULT "0" AFTER col1
-    TO example_rollup_index;
-    ```
-
-5. 向 `example_rollup_index` 添加多列（聚合表）。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD COLUMN (col1 INT DEFAULT "1", col2 FLOAT SUM DEFAULT "2.3")
-    TO example_rollup_index;
-    ```
-
-6. 向 `example_rollup_index` 添加多列并通过 `AFTER` 指定列的添加位置。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD COLUMN col1 INT DEFAULT "1" AFTER `k1`,
-    ADD COLUMN col2 FLOAT SUM AFTER `v2`,
-    TO example_rollup_index;
-    ```
-
-7. 从 `example_rollup_index` 删除一列。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    DROP COLUMN col2
-    FROM example_rollup_index;
-    ```
-
-8. 修改 base index 的 `col1` 列的类型为 BIGINT，并移动到 `col2` 列后面。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    MODIFY COLUMN col1 BIGINT DEFAULT "1" AFTER col2;
-    ```
-
-9. 修改 base index 的 `val1` 列最大长度。原 `val1` 为 (`val1 VARCHAR(32) REPLACE DEFAULT "abc"`)。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    MODIFY COLUMN val1 VARCHAR(64) REPLACE DEFAULT "abc";
-    ```
-
-10. 重新排序 `example_rollup_index` 中的列（设原列顺序为：k1, k2, k3, v1, v2）。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ORDER BY (k3,k1,k2,v2,v1)
-    FROM example_rollup_index;
-    ```
-
-11. 同时执行两种操作。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    ADD COLUMN v2 INT MAX DEFAULT "0" AFTER k2 TO example_rollup_index,
-    ORDER BY (k3,k1,k2,v2,v1) FROM example_rollup_index;
-    ```
-
-12. 修改表的 bloom filter 列。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    SET ("bloom_filter_columns"="k1,k2,k3");
-    ```
-
-    也可以合并到上面的修改列操作中（注意多子句的语法有少许区别）
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    DROP COLUMN col2
-    PROPERTIES ("bloom_filter_columns"="k1,k2,k3");
-    ```
-
-13. 批量修改字段数据类型。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    MODIFY COLUMN k1 VARCHAR(100) KEY NOT NULL,
-    MODIFY COLUMN v2 DOUBLE DEFAULT "1" AFTER v1;
-    ```
-
-14. STRUCT 类型增删字段。
-
-    **准备工作**：建表并导入数据
-
-    ```sql
-    CREATE TABLE struct_test(
-        c0 INT,
-        c1 STRUCT<v1 INT, v2 STRUCT<v4 INT, v5 INT>, v3 INT>,
-        c2 STRUCT<v1 INT, v2 ARRAY<STRUCT<v3 INT, v4 STRUCT<v5 INT, v6 INT>>>>
-    )
-    DUPLICATE KEY(c0)
-    DISTRIBUTED BY HASH(`c0`) BUCKETS 1
-    PROPERTIES (
-        "fast_schema_evolution" = "true"
-    );
-    INSERT INTO struct_test VALUES (
-        1, 
-        ROW(1, ROW(2, 3), 4), 
-        ROW(5, [ROW(6, ROW(7, 8)), ROW(9, ROW(10, 11))])
-    );
-    ```
-
-    ```plain
-    mysql> SELECT * FROM struct_test\G
-    *************************** 1. row ***************************
-    c0: 1
-    c1: {"v1":1,"v2":{"v4":2,"v5":3},"v3":4}
-    c2: {"v1":5,"v2":[{"v3":6,"v4":{"v5":7,"v6":8}},{"v3":9,"v4":{"v5":10,"v6":11}}]}
-    ```
-
-    - 向 STRUCT 类型列添加新字段。
-
-    ```sql
-    ALTER TABLE struct_test MODIFY COLUMN c1 ADD FIELD v4 INT AFTER v2;
-    ```
-
-    ```plain
-    mysql> SELECT * FROM struct_test\G
-    *************************** 1. row ***************************
-    c0: 1
-    c1: {"v1":1,"v2":{"v4":2,"v5":3},"v4":null,"v3":4}
-    c2: {"v1":5,"v2":[{"v3":6,"v4":{"v5":7,"v6":8}},{"v3":9,"v4":{"v5":10,"v6":11}}]}
-    ```
-
-    - 向嵌套 STRUCT 类型添加字段。
-
-    ```sql
-    ALTER TABLE struct_test MODIFY COLUMN c1 ADD FIELD v2.v6 INT FIRST;
-    ```
-
-    ```plain
-    mysql> SELECT * FROM struct_test\G
-    *************************** 1. row ***************************
-    c0: 1
-    c1: {"v1":1,"v2":{"v6":null,"v4":2,"v5":3},"v4":null,"v3":4}
-    c2: {"v1":5,"v2":[{"v3":6,"v4":{"v5":7,"v6":8}},{"v3":9,"v4":{"v5":10,"v6":11}}]}
-    ```
-
-    - 向 Array 类型中的 STRUCT 类型添加字段。
-
-    ```sql
-    ALTER TABLE struct_test MODIFY COLUMN c2 ADD FIELD v2.[*].v7 INT AFTER v3;
-    ```
-
-    ```plain
-    mysql> SELECT * FROM struct_test\G
-    *************************** 1. row ***************************
-    c0: 1
-    c1: {"v1":1,"v2":{"v6":null,"v4":2,"v5":3},"v4":null,"v3":4}
-    c2: {"v1":5,"v2":[{"v3":6,"v7":null,"v4":{"v5":7,"v6":8}},{"v3":9,"v7":null,"v4":{"v5":10,"v6":11}}]}
-    ```
-
-    - 删除 STRUCT 类型列中的字段。
-
-    ```sql
-    ALTER TABLE struct_test MODIFY COLUMN c1 DROP FIELD v3;
-    ```
-
-    ```plain
-    mysql> SELECT * FROM struct_test\G
-    *************************** 1. row ***************************
-    c0: 1
-    c1: {"v1":1,"v2":{"v6":null,"v4":2,"v5":3},"v4":null}
-    c2: {"v1":5,"v2":[{"v3":6,"v7":null,"v4":{"v5":7,"v6":8}},{"v3":9,"v7":null,"v4":{"v5":10,"v6":11}}]}
-    ```
-
-    - 删除嵌套 STRUCT 类型中的字段。
-
-    ```sql
-    ALTER TABLE struct_test MODIFY COLUMN c1 DROP FIELD v2.v4;
-    ```
-
-    ```plain
-    mysql> SELECT * FROM struct_test\G
-    *************************** 1. row ***************************
-    c0: 1
-    c1: {"v1":1,"v2":{"v6":null,"v5":3},"v4":null}
-    c2: {"v1":5,"v2":[{"v3":6,"v7":null,"v4":{"v5":7,"v6":8}},{"v3":9,"v7":null,"v4":{"v5":10,"v6":11}}]}
-    ```
-
-    - 删除 Array 类型中的 STRUCT 类型的字段。
-
-    ```sql
-    ALTER TABLE struct_test MODIFY COLUMN c2 DROP FIELD v2.[*].v3;
-    ```
-
-    ```plain
-    mysql> SELECT * FROM struct_test\G
-    *************************** 1. row ***************************
-    c0: 1
-    c1: {"v1":1,"v2":{"v6":null,"v5":3},"v4":null}
-    c2: {"v1":5,"v2":[{"v7":null,"v4":{"v5":7,"v6":8}},{"v7":null,"v4":{"v5":10,"v6":11}}]}
-    ```
-
-### Table property
-
-1. 修改表的 Colocate 属性。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    SET ("colocate_with" = "t1");
-    ```
-
-2. 修改表的动态分区属性(支持未添加动态分区属性的表添加动态分区属性)。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    SET ("dynamic_partition.enable" = "false");
-    ```
-
-    如果需要在未添加动态分区属性的表中添加动态分区属性，则需要指定所有的动态分区属性。
-
-    ```sql
-    ALTER TABLE example_db.my_table
-    SET (
-        "dynamic_partition.enable" = "true",
-        "dynamic_partition.time_unit" = "DAY",
-        "dynamic_partition.end" = "3",
-        "dynamic_partition.prefix" = "p",
-        "dynamic_partition.buckets" = "32"
-        );
-    ```
-
-### Rename
-
-1. 将表 `table1` 的名称修改为 `table2`。
-
-    ```sql
-    ALTER TABLE table1 RENAME table2;
-    ```
-
-2. 将表 `example_table` 中名为 `rollup1` 的 rollup index 修改为 `rollup2`。
-
-    ```sql
-    ALTER TABLE example_table RENAME ROLLUP rollup1 rollup2;
-    ```
-
-3. 将表 `example_table` 中名为 `p1` 的 partition 修改为 `p2`。
-
-    ```sql
-    ALTER TABLE example_table RENAME PARTITION p1 p2;
-    ```
-
-### Bitmap index
-
-1. 在 `table1` 上为 `siteid` 创建 bitmap index。
-
-    ```sql
-    ALTER TABLE table1
-    ADD INDEX index_name (siteid) [USING BITMAP] COMMENT 'balabala';
-    ```
-
-2. 删除 `table1` 上的 `siteid` 列的 bitmap index。
-
-    ```sql
-    ALTER TABLE table1 DROP INDEX index_name;
-    ```
-
-### Swap
-
-将 `table1` 与 `table2` 原子替换。
-
-```sql
-ALTER TABLE table1 SWAP WITH table2;
-```
-
-### 手动 Compaction
-
-```sql
-CREATE TABLE compaction_test( 
-    event_day DATE,
-    pv BIGINT)
-DUPLICATE KEY(event_day)
-PARTITION BY date_trunc('month', event_day)
-DISTRIBUTED BY HASH(event_day) BUCKETS 8
-PROPERTIES("replication_num" = "3");
-
-INSERT INTO compaction_test VALUES
-('2023-02-14', 2),
-('2033-03-01',2);
-{'label':'insert_734648fa-c878-11ed-90d6-00163e0dcbfc', 'status':'VISIBLE', 'txnId':'5008'}
-
-INSERT INTO compaction_test VALUES
-('2023-02-14', 2),('2033-03-01',2);
-{'label':'insert_85c95c1b-c878-11ed-90d6-00163e0dcbfc', 'status':'VISIBLE', 'txnId':'5009'}
-
-ALTER TABLE compaction_test COMPACT;
-
-ALTER TABLE compaction_test COMPACT p203303;
-
-ALTER TABLE compaction_test COMPACT (p202302,p203303);
-
-ALTER TABLE compaction_test CUMULATIVE COMPACT (p202302,p203303);
-
-ALTER TABLE compaction_test BASE COMPACT (p202302,p203303);
-```
-
-## 相关参考
-
-- [CREATE TABLE](./CREATE_TABLE.md)
-- [SHOW CREATE TABLE](../data-manipulation/SHOW_CREATE_TABLE.md)
-- [SHOW TABLES](../data-manipulation/SHOW_TABLES.md)
-- [SHOW ALTER TABLE](../data-manipulation/SHOW_ALTER.md)
-- [DROP TABLE](./DROP_TABLE.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/ALTER_VIEW.md b/docs/zh/sql-reference/sql-statements/data-definition/ALTER_VIEW.md
deleted file mode 100644
index c3f02c1e841b2c..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/ALTER_VIEW.md
+++ /dev/null
@@ -1,40 +0,0 @@
----
-keywords: ['xiugai', 'shitu'] 
-displayed_sidebar: "Chinese"
----
-
-# ALTER VIEW
-
-## 功能
-
-该语句用于修改一个逻辑视图的定义。
-
-## 语法
-
-```sql
-ALTER VIEW
-[db_name.]view_name
-(column1[ COMMENT "col comment"][, column2, ...])
-AS query_stmt
-```
-
-说明：
-
-1. 逻辑视图中的数据不会存储在物理介质上，在查询时，逻辑视图将作为语句中的子查询，因此，修改逻辑视图的定义等价于修改 query_stmt。
-2. query_stmt 为任意支持的 SQL。
-
-## 示例
-
-1. 修改example_db上的逻辑视图example_view。
-
-    ```sql
-    ALTER VIEW example_db.example_view
-    (
-        c1 COMMENT "column 1",
-        c2 COMMENT "column 2",
-        c3 COMMENT "column 3"
-    )
-    AS SELECT k1, k2, SUM(v1) 
-    FROM example_table
-    GROUP BY k1, k2;
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/ANALYZE_TABLE.md b/docs/zh/sql-reference/sql-statements/data-definition/ANALYZE_TABLE.md
deleted file mode 100644
index b903b371cdf1b1..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/ANALYZE_TABLE.md
+++ /dev/null
@@ -1,121 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# ANALYZE TABLE
-
-## 功能
-
-创建手动采集任务，进行 CBO 统计信息采集。**手动采集默认为同步操作。您也可以将手动任务设置为异步，执行命令后，会立即返回命令的状态，但是统计信息采集任务会在后台运行，运行的状态可以使用 SHOW ANALYZE STATUS 查看。手动任务创建后仅会执行一次，无需手动删除。**
-
-### 手动采集基础统计信息
-
-关于基础统计信息，请参见[CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md#统计信息数据类型)。
-
-#### 语法
-
-```SQL
-ANALYZE [FULL|SAMPLE] TABLE tbl_name (col_name [,col_name])
-[WITH SYNC | ASYNC MODE]
-PROPERTIES (property [,property])
-```
-
-#### 参数说明
-
-- 采集类型
-  - FULL：全量采集。
-  - SAMPLE：抽样采集。
-  - 如果不指定采集类型，默认为全量采集。
-
-- `WITH SYNC | ASYNC MODE`: 如果不指定，默认为同步操作。
-
-- `col_name`: 要采集统计信息的列，多列使用逗号分隔。如果不指定，表示采集整张表的信息。
-
-- PROPERTIES: 采集任务的自定义参数。如果不配置，则采用`fe.conf`中的默认配置。任务实际执行中使用的 PROPERTIES，可以通过 SHOW ANALYZE STATUS 返回结果中的 `Properties` 列查看。
-
-| **PROPERTIES**                | **类型** | **默认值** | **说明**                                                     |
-| ----------------------------- | -------- | ---------- | ------------------------------------------------------------ |
-| statistic_sample_collect_rows | INT      | 200000     | 最小采样行数。如果参数取值超过了实际的表行数，默认进行全量采集。 |
-
-#### 示例
-
-示例1：手动全量采集
-
-```SQL
--- 手动全量采集指定表的统计信息，使用默认配置。
-ANALYZE TABLE tbl_name;
-
--- 手动全量采集指定表的统计信息，使用默认配置。
-ANALYZE FULL TABLE tbl_name;
-
--- 手动全量采集指定表指定列的统计信息，使用默认配置。
-ANALYZE TABLE tbl_name(c1, c2, c3);
-```
-
-示例2：手动抽样采集
-
-```SQL
--- 手动抽样采集指定表的统计信息，使用默认配置。
-ANALYZE SAMPLE TABLE tbl_name;
-
--- 手动抽样采集指定表指定列的统计信息，设置抽样行数。
-ANALYZE SAMPLE TABLE tbl_name (v1, v2, v3) PROPERTIES(
-    "statistic_sample_collect_rows" = "1000000"
-);
-```
-
-### 手动采集直方图统计信息
-
-关于直方图的说明，请参见[CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md#统计信息数据类型)。
-
-#### 语法
-
-```SQL
-ANALYZE TABLE tbl_name UPDATE HISTOGRAM ON col_name [, col_name]
-[WITH SYNC | ASYNC MODE]
-[WITH N BUCKETS]
-PROPERTIES (property [,property]);
-```
-
-#### 参数说明
-
-- `col_name`: 要采集统计信息的列，多列使用逗号分隔。该参数必填。
-
-- `WITH SYNC | ASYNC MODE`: 如果不指定，默认为同步采集。
-
-- `WITH ``N`` BUCKETS`: `N`为直方图的分桶数。如果不指定，则使用`fe.conf`中的默认值。
-
-- PROPERTIES: 采集任务的自定义参数。如果不指定，则使用`fe.conf`中的默认配置。
-
-| **PROPERTIES**                 | **类型** | **默认值** | **说明**                                                     |
-| ------------------------------ | -------- | ---------- | ------------------------------------------------------------ |
-| statistic_sample_collect_rows  | INT      | 200000     | 最小采样行数。如果参数取值超过了实际的表行数，默认进行全量采集。 |
-| histogram_mcv_size             | INT      | 100        | 直方图 most common value (MCV) 的数量。                      |
-| histogram_sample_ratio         | FLOAT    | 0.1        | 直方图采样比例。                                             |
-| histogram_max_sample_row_count | LONG     | 10000000   | 直方图最大采样行数。                                         |
-
-直方图的采样行数由多个参数共同控制，采样行数取 `statistic_sample_collect_rows` 和表总行数 `histogram_sample_ratio` 两者中的最大值。最多不超过 `histogram_max_sample_row_count` 指定的行数。如果超过，则按照该参数定义的上限行数进行采集。
-
-直方图任务实际执行中使用的**PROPERTIES**，可以通过 SHOW ANALYZE STATUS 返回结果中的**PROPERTIES**列查看。
-
-#### 示例
-
-```SQL
--- 手动采集v1列的直方图信息，使用默认配置。
-ANALYZE TABLE tbl_name UPDATE HISTOGRAM ON v1;
-
--- 手动采集 v1 列的直方图信息，指定 32 个分桶，MCV 指定为 32 个，采样比例为 50%。
-ANALYZE TABLE tbl_name UPDATE HISTOGRAM ON v1,v2 WITH 32 BUCKETS 
-PROPERTIES(
-   "histogram_mcv_size" = "32",
-   "histogram_sample_ratio" = "0.5"
-);
-```
-
-## 相关文档
-
-[SHOW ANALYZE STATUS](../data-definition/SHOW_ANALYZE_STATUS.md)：查看当前所有**手动采集任务**的状态。
-
-[KILL ANALYZE](../data-definition/KILL_ANALYZE.md)：取消**正在运行中（Running）**的统计信息收集任务。
-
-想了解更多 CBO 统计信息采集的内容，参见[CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/CANCEL_ALTER_TABLE.md b/docs/zh/sql-reference/sql-statements/data-definition/CANCEL_ALTER_TABLE.md
deleted file mode 100644
index c952d6e9059f2e..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/CANCEL_ALTER_TABLE.md
+++ /dev/null
@@ -1,55 +0,0 @@
----
-keywords: ['xiugai'] 
-displayed_sidebar: "Chinese"
----
-
-# CANCEL ALTER TABLE
-
-## 功能
-
-取消正在进行的 ALTER TABLE 操作，包括：
-
-- 修改列。
-- 优化表结构（自 3.2 版本起），包括修改分桶方式和分桶数量。
-- 创建和删除 rollup index。
-
-> **注意**
->
-> - 该语句为同步操作。
-> - 只有拥有对应表 ALTER 权限的用户才可以执行语句。
-> - 该语句仅支持取消使用 ALTER TABLE 执行的异步操作（如上），不支持取消使用 ALTER TABLE 执行同步操作，比如 rename。
-
-## 语法
-
-   ```SQL
-   CANCEL ALTER TABLE { COLUMN | OPTIMIZE | ROLLUP } FROM [<db_name>.]<table_name>
-   ```
-
-## 参数说明
-
-- `{COLUMN ｜ OPTIMIZE | ROLLUP}`：从 `COLUMN`、`OPTIMIZE` 和 `ROLLUP` 中必选其中一个。
-  - 如果指定了 `COLUMN`，该语句用于取消修改列的操作。
-  - 如果指定了 `OPTIMIZE`，该语句用于取消优化表结构的操作（修改分桶方式和分桶数量）。
-  - 如果指定了 `ROLLUP`，该语句用于取消创建或删除 rollup index 的操作。
-- `db_name`：可选。表所在的数据库名称。如不指定，默认为当前数据库。
-- `table_name`：必选。表名。
-
-## 示例
-
-1. 取消数据库 `example_db` 中表 `example_table` 的修改列操作。
-
-   ```SQL
-   CANCEL ALTER TABLE COLUMN FROM example_db.example_table;
-   ```
-
-2. 取消数据库 `example_db` 中表 `example_table` 的优化表结构操作。
-
-   ```SQL
-   CANCEL ALTER TABLE OPTIMIZE FROM example_db.example_table;
-   ```
-
-3. 取消当前数据库中，`example_table` 的创建和删除 rollup index 的操作。
-
-    ```SQL
-    CANCEL ALTER TABLE ROLLUP FROM example_table;
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_ANALYZE.md b/docs/zh/sql-reference/sql-statements/data-definition/CREATE_ANALYZE.md
deleted file mode 100644
index 7e5d8ec094685c..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_ANALYZE.md
+++ /dev/null
@@ -1,84 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CREATE ANALYZE
-
-## 功能
-
-创建自定义自动采集任务，进行 CBO 统计信息采集。
-
-默认情况下，StarRocks 会周期性自动采集表的全量统计信息。默认检查更新时间为 5 分钟一次，如果发现有数据更新，会自动触发采集。如果您不希望使用自动全量采集，可以设置 FE 配置项 `enable_collect_full_statistic` 为 `false`，系统会停止自动全量采集，根据您创建的自定义任务进行定制化采集。
-
-创建自定义自动采集任务之前，需要先关闭自动全量采集 `enable_collect_full_statistic=false`，否则自定义采集任务不生效。
-
-## 语法
-
-```SQL
--- 定期采集所有数据库的统计信息。
-CREATE ANALYZE [FULL|SAMPLE] ALL PROPERTIES (property [,property])
-
--- 定期采集指定数据库下所有表的统计信息。
-CREATE ANALYZE [FULL|SAMPLE] DATABASE db_name PROPERTIES (property [,property])
-
--- 定期采集指定表、列的统计信息。
-CREATE ANALYZE [FULL|SAMPLE] TABLE tbl_name (col_name [,col_name]) PROPERTIES (property [,property])
-```
-
-## 参数说明
-
-- 采集类型
-  - FULL：全量采集。
-  - SAMPLE：抽样采集。
-  - 如果不指定采集类型，默认为抽样采集。
-
-- `col_name`: 要采集统计信息的列，多列使用逗号 (,)分隔。如果不指定，表示采集整张表的信息。
-
-- PROPERTIES: 采集任务的自定义参数。如果不配置，则采用 `fe.conf` 中的默认配置。任务实际执行中使用的 PROPERTIES，可以通过 [SHOW ANALYZE JOB](../data-definition/SHOW_ANALYZE_JOB.md) 中的 `Properties` 列查看。
-
-| **PROPERTIES**                        | **类型** | **默认值** | **说明**                                                     |
-| ------------------------------------- | -------- | ---------- | ------------------------------------------------------------ |
-| statistic_auto_collect_ratio          | FLOAT    | 0.8        | 自动统计信息的健康度阈值。如果统计信息的健康度小于该阈值，则触发自动采集。 |
-| statistics_max_full_collect_data_size | INT      | 100        | 自动统计信息采集的最大分区的大小。单位: GB。如果某个分区超过该值，则放弃全量统计信息采集，转为对该表进行抽样统计信息采集。 |
-| statistic_sample_collect_rows         | INT      | 200000     | 抽样采集的采样行数。如果该参数取值超过了实际的表行数，则进行全量采集。 |
-
-## 示例
-
-示例 1：自动全量采集
-
-```SQL
--- 定期全量采集所有数据库的统计信息。
-CREATE ANALYZE ALL;
-
--- 定期全量采集指定数据库下所有表的统计信息。
-CREATE ANALYZE DATABASE db_name;
-
--- 定期全量采集指定数据库下所有表的统计信息。
-CREATE ANALYZE FULL DATABASE db_name;
-
--- 定期全量采集指定表、列的统计信息。
-CREATE ANALYZE TABLE tbl_name(c1, c2, c3); 
-```
-
-示例 2：自动抽样采集
-
-```SQL
--- 定期抽样采集指定数据库下所有表的统计信息，使用默认配置。
-CREATE ANALYZE SAMPLE DATABASE db_name;
-
--- 定期抽样采集指定表、列的统计信息，设置采样行数和健康度阈值。
-CREATE ANALYZE SAMPLE TABLE tbl_name(c1, c2, c3) PROPERTIES(
-   "statistic_auto_collect_ratio" = "0.5",
-   "statistic_sample_collect_rows" = "1000000"
-);
-```
-
-## 相关文档
-
-[SHOW ANALYZE JOB](../data-definition/SHOW_ANALYZE_JOB.md)：查看创建的自定义自动采集任务。
-
-[DROP ANALYZE](../data-definition/DROP_ANALYZE.md)：删除自动采集任务。
-
-[KILL ANALYZE](../data-definition/KILL_ANALYZE.md)：取消正在运行中（Running）的统计信息收集任务。
-
-想了解更多 CBO 统计信息采集的内容，参见 [CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_DATABASE.md b/docs/zh/sql-reference/sql-statements/data-definition/CREATE_DATABASE.md
deleted file mode 100644
index b72396ac2c43b2..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_DATABASE.md
+++ /dev/null
@@ -1,53 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CREATE DATABASE
-
-## 功能
-
-该语句用于创建数据库 (database)。
-
-:::tip
-
-该操作需要对应 Catalog 下的 CREATE DATABASE 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```sql
-CREATE DATABASE [IF NOT EXISTS] <db_name>
-[PROPERTIES ("key"="value", ...)]
-```
-
-## 参数说明
-
-`db_name`：数据库名称。有关数据库的命名要求，参见[系统限制](../../../reference/System_limit.md)。
-
-**PROPERTIES（选填）**
-
-`storage_volume`: 存算分离集群中，用于存储当前数据库中数据的存储卷。如未指定，则使用默认存储卷。
-
-## 示例
-
-1. 新建数据库 `db_test`。
-
-   ```sql
-   CREATE DATABASE db_test;
-   ```
-
-2. 基于存储卷 `s3_storage_volume` 新建云原生数据 `cloud_db`。
-
-   ```sql
-   CREATE DATABASE cloud_db
-   PROPERTIES ("storage_volume"="s3_storage_volume");
-   ```
-
-## 相关参考
-
-- [SHOW CREATE DATABASE](../data-manipulation/SHOW_CREATE_DATABASE.md)
-- [USE](../data-definition/USE.md)
-- [SHOW DATABASES](../data-manipulation/SHOW_DATABASES.md)
-- [DESC](../Utility/DESCRIBE.md)
-- [DROP DATABASE](../data-definition/DROP_DATABASE.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md b/docs/zh/sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md
deleted file mode 100644
index 7ff9b968c0d6a6..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_EXTERNAL_CATALOG.md
+++ /dev/null
@@ -1,140 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CREATE EXTERNAL CATALOG
-
-## 功能
-
-该语句用于创建 External Catalog。创建后，无需数据导入或创建外部表即可查询外部数据。当前支持创建如下 External Catalog：
-
-- [Hive catalog](../../../data_source/catalog/hive_catalog.md)：用于查询 Apache Hive™ 集群中的数据。
-- [Iceberg catalog](../../../data_source/catalog/iceberg_catalog.md)：用于查询 Apache Iceberg 集群中的数据。
-- [Hudi catalog](../../../data_source/catalog/hudi_catalog.md)：用于查询 Apache Hudi 集群中的数据。
-- [Delta Lake catalog](../../../data_source/catalog/deltalake_catalog.md)：用于查询 Delta Lake 中的数据。
-- [JDBC catalog](../../../data_source/catalog/jdbc_catalog.md)：用于查询 JDBC 数据源中的数据。
-- [Elasticsearch catalog](../../../data_source/catalog/elasticsearch_catalog.md)：用于查询 Elasticsearch 中的数据。该特性自 3.1 版本起支持。
-- [Paimon catalog](../../../data_source/catalog/paimon_catalog.md)：用于查询 Apache Paimon 中的数据。该特性自 3.1 版本起支持。
-- [Unified catalog](../../../data_source/catalog/unified_catalog.md)：把 Hive、Iceberg、Hudi 和 Delta Lake 作为一个融合的数据源，从中查询数据。该特性自 3.2 版本起支持。
-
-> **注意**
->
-> - 在 3.0 及以后版本，使用该语句需要有 System 级 CREATE EXTERNAL CATALOG 权限。
-> - 在创建 External Catalog 前，需要根据数据源的存储系统（如 AWS S3）、元数据服务（如 Hive metastore）和认证方式（如 Kerberos）在 StarRocks 中做相应的配置。详细信息，请参见以上各个 External Catalog 文档中的「前提条件」小节。
-
-## 语法
-
-```SQL
-CREATE EXTERNAL CATALOG [IF NOT EXISTS] <catalog_name>
-[COMMENT <comment>]
-PROPERTIES ("key"="value", ...)
-```
-
-## 参数说明
-
-| 参数         | 必选 | 说明                                                         |
-| ------------ | ---- | ------------------------------------------------------------ |
-| catalog_name | 是   | External catalog 的名称，命名要求参见[系统限制](../../../reference/System_limit.md)。 |
-| comment      | 否   | External catalog 的描述。 |
-| PROPERTIES   | 是   | External catalog 的属性，不同的 external catalog 需要设置不同属性。详细配置信息，请参见 [Hive catalog](../../../data_source/catalog/hive_catalog.md)、[Iceberg catalog](../../../data_source/catalog/iceberg_catalog.md)、[Hudi catalog](../../../data_source/catalog/hudi_catalog.md)、[Delta Lake catalog](../../../data_source/catalog/deltalake_catalog.md) 和 [JDBC Catalog](../../../data_source/catalog/jdbc_catalog.md)。 |
-
-## 示例
-
-示例一：创建名为 `hive_metastore_catalog` 的 Hive catalog。其对应的 Hive 集群使用 Hive metastore 作为元数据服务。
-
-```SQL
-CREATE EXTERNAL CATALOG hive_metastore_catalog
-PROPERTIES(
-   "type"="hive", 
-   "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
-);
-```
-
-示例二：创建名为 `hive_glue_catalog` 的 Hive catalog。其对应的 Hive 集群使用 AWS Glue 作为元数据服务。
-
-```SQL
-CREATE EXTERNAL CATALOG hive_glue_catalog
-PROPERTIES(
-    "type"="hive", 
-    "hive.metastore.type"="glue",
-    "aws.hive.metastore.glue.aws-access-key"="xxxxxx",
-    "aws.hive.metastore.glue.aws-secret-key"="xxxxxxxxxxxx",
-    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
-);
-```
-
-示例三：创建名为 `iceberg_metastore_catalog` 的 Iceberg catalog。其对应的 Iceberg 集群使用 Hive metastore 作为元数据服务。
-
-```SQL
-CREATE EXTERNAL CATALOG iceberg_metastore_catalog
-PROPERTIES(
-    "type"="iceberg",
-    "iceberg.catalog.type"="hive",
-    "iceberg.catalog.hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
-);
-```
-
-示例四：创建名为 `iceberg_glue_catalog` 的 Iceberg catalog。其对应的 Iceberg 集群使用  AWS Glue 作为元数据服务。
-
-```SQL
-CREATE EXTERNAL CATALOG iceberg_glue_catalog
-PROPERTIES(
-    "type"="iceberg", 
-    "iceberg.catalog.type"="glue",
-    "aws.hive.metastore.glue.aws-access-key"="xxxxx",
-    "aws.hive.metastore.glue.aws-secret-key"="xxx",
-    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
-);
-```
-
-示例五：创建名为 `hudi_metastore_catalog` 的 Hudi catalog。其对应的 Hudi 集群使用 Hive metastore 作为元数据服务。
-
-```SQL
-CREATE EXTERNAL CATALOG hudi_metastore_catalog
-PROPERTIES(
-    "type"="hudi",
-    "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
-);
-```
-
-示例六：创建名为 `hudi_glue_catalog` 的 Hudi catalog。其对应的 Hudi 集群使用 AWS Glue 作为元数据服务。
-
-```SQL
-CREATE EXTERNAL CATALOG hudi_glue_catalog
-PROPERTIES(
-    "type"="hudi", 
-    "hive.metastore.type"="glue",
-    "aws.hive.metastore.glue.aws-access-key"="xxxxxx",
-    "aws.hive.metastore.glue.aws-secret-key"="xxxxxxxxxxxx",
-    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
-);
-```
-
-示例七：创建名为 `delta_metastore_catalog` 的 Delta Lake catalog。其对应的 Delta Lake 使用 Hive metastore 作为元数据服务。
-
-```SQL
-CREATE EXTERNAL CATALOG delta_metastore_catalog
-PROPERTIES(
-    "type"="deltalake",
-    "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
-);
-```
-
-示例八：创建名为 `delta_glue_catalog` 的 Delta Lake catalog。其对应的 Delta Lake 使用 AWS Glue 作为元数据服务。
-
-```SQL
-CREATE EXTERNAL CATALOG delta_glue_catalog
-PROPERTIES(
-    "type"="deltalake", 
-    "hive.metastore.type"="glue",
-    "aws.hive.metastore.glue.aws-access-key"="xxxxxx",
-    "aws.hive.metastore.glue.aws-secret-key"="xxxxxxxxxxxx",
-    "aws.hive.metastore.glue.endpoint"="https://glue.x-x-x.amazonaws.com"
-);
-```
-
-## 相关操作
-
-- 如要查看所有 Catalog，参见 [SHOW CATALOGS](../../../sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md)。
-- 如要查看某个 External Catalog 的创建语句，参见 [SHOW CREATE CATALOG](../../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md)。
-- 如要删除 External Catalog，参见 [DROP CATALOG](../../../sql-reference/sql-statements/data-definition/DROP_CATALOG.md)。
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_FUNCTION.md b/docs/zh/sql-reference/sql-statements/data-definition/CREATE_FUNCTION.md
deleted file mode 100644
index 455fdff59da498..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_FUNCTION.md
+++ /dev/null
@@ -1,43 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CREATE FUNCTION
-
-## 功能
-
-创建 UDF（用户自定义函数）。当前仅支持创建 Java UDF，即 Java 语言编写的自定义函数，具体包括：
-
-- Scalar UDF：自定义标量函数。
-- UDAF：自定义聚合函数。
-- UDWF：自定义窗口函数。
-- UDTF：自定义表值函数。
-
-**更多创建和使用 UDF 的信息，推荐参考 [Java UDF](../../sql-functions/JAVA_UDF.md)。**
-
-> **注意**
->
-> - 要创建全局 UDF，需要拥有 SYSTEM 级 CREATE GLOBAL FUNCTION 权限。
-> - 要创建数据库级别的 UDF，需要拥有 DATABASE 级 CREATE FUNCTION 权限。
-
-## 语法
-
-```SQL
-CREATE [OR REPLACE] [GLOBAL] [AGGREGATE | TABLE] FUNCTION function_name
-(arg_type [, ...])
-RETURNS return_type
-[PROPERTIES ("key" = "value" [, ...]) ]
-```
-
-## 参数说明
-
-| **参数**      | **必选** | **说明**                                                     |
-| ------------- | -------- | ------------------------------------------------------------ |
-| OR REPLACE    | 否       | 如已存在有同样签名（Function Signature）的函数，则替换该函数。从 3.4 版本开始支持。              |
-| GLOBAL        | 否       | 如需创建全局 UDF，需指定该关键字。从 3.0 版本开始支持。              |
-| AGGREGATE     | 否       | 如要创建 UDAF 和 UDWF，需指定该关键字。                         |
-| TABLE         | 否       | 如要创建 UDTF，需指定该关键字。                              |
-| function_name | 是       | 函数名，可以包含数据库名称，比如，`db1.my_func`。如果 `function_name` 中包含了数据库名称，那么该 UDF 会创建在对应的数据库中，否则该 UDF 会创建在当前数据库。新函数名和参数不能与目标数据库中已有的函数相同，否则会创建失败；如只有函数名相同，参数不同，则可以创建成功。 |
-| arg_type      | 是       | 函数的参数类型。具体支持的数据类型，请参见 [Java UDF](../../sql-functions/JAVA_UDF.md#类型映射关系)。 |
-| return_type   | 是       | 函数的返回值类型。具体支持的数据类型，请参见 [Java UDF](../../sql-functions/JAVA_UDF.md#类型映射关系)。 |
-| properties    | 是       | 函数相关属性。创建不同类型的 UDF 需配置不同的属性，详情和示例请参考 [Java UDF](../../sql-functions/JAVA_UDF.md#步骤六在-starrocks-中创建-udf)。 |
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_INDEX.md b/docs/zh/sql-reference/sql-statements/data-definition/CREATE_INDEX.md
deleted file mode 100644
index 1a46626523cd2a..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_INDEX.md
+++ /dev/null
@@ -1,66 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['suoyin']
----
-
-# CREATE INDEX
-
-## 功能
-
-创建索引。仅支持使用该语句创建 Bitmap 索引，有关 Bitmap 索引的使用说明和适用场景，参见 [Bitmap 索引](../../../table_design/indexes/Bitmap_index.md)。
-
-:::tip
-
-- 该操作需要对应表的 ALTER 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-- 一列只能创建一个 Bitmap index。如果某列已有 index，再次创建会返回失败。
-
-:::
-
-## 语法
-
-```SQL
-CREATE INDEX index_name ON table_name (column_name) [USING BITMAP] [COMMENT'']
-```
-
-## 参数说明
-
-| **参数**    | **必选** | **说明**                                                     |
-| ----------- | -------- | ------------------------------------------------------------ |
-| index_name  | 是       | 索引名称，命名要求参见[系统限制](../../../reference/System_limit.md)。在同一张表中不能创建名称相同的索引。 |
-| table_name  | 是       | 表名。                                                       |
-| column_name | 是       | 创建索引的列名。执行一次该语句只能为某一列创建索引，且同一列只能创建一个索引。 |
-| COMMENT     | 否       | 索引备注。                                                   |
-
-## 示例
-
-例如有一张表 `sales_records`，其建表语句如下：
-
-```SQL
-CREATE TABLE sales_records
-(
-    record_id int,
-    seller_id int,
-    item_id int
-)
-DISTRIBUTED BY hash(record_id)
-PROPERTIES (
-    "replication_num" = "3"
-);
-```
-
-为表 `sales_records` 中的 `item_id` 列创建 bitmap 索引，索引名称为 `index3`。
-
-```SQL
-CREATE INDEX index3 ON sales_records (item_id) USING BITMAP COMMENT '';
-```
-
-或
-
-```SQL
-CREATE INDEX index3 ON sales_records (item_id);
-```
-
-## 相关操作
-
-- 如要查看索引，参见 [SHOW INDEX](../data-manipulation//SHOW_INDEX.md)。
-- 如要删除索引，参见 [DROP INDEX](../data-definition/DROP_INDEX.md)。
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md
deleted file mode 100644
index fcc19984c6eb32..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md
+++ /dev/null
@@ -1,858 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CREATE MATERIALIZED VIEW
-
-## 功能
-
-创建物化视图。关于物化视图适用的场景请参考[同步物化视图](../../../using_starrocks/Materialized_view-single_table.md)和[异步物化视图](../../../using_starrocks/Materialized_view.md)。
-
-创建物化视图是一个异步的操作。该命令执行成功即代表创建物化视图的任务提交成功。您可以通过 [SHOW ALTER MATERIALIZED VIEW](../data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW.md) 命令查看当前数据库中同步物化视图的构建状态，或通过查询 [Information Schema](../../../reference/overview-pages/information_schema.md) 中的 [`tasks`](../../../reference/information_schema/tasks.md) 和 [`task_runs`](../../../reference/information_schema/task_runs.md) 来查看异步物化视图的构建状态。
-
-> **注意**
->
-> 只有拥有基表所在数据库的 CREATE MATERIALIZED VIEW 权限的用户才可以创建物化视图。
-
-StarRocks 自 v2.4 起支持异步物化视图。异步物化视图与先前版本中的同步物化视图区别主要体现在以下方面：
-
-|                              | **单表聚合** | **多表关联** | **查询改写** | **刷新策略** | **基表** |
-| ---------------------------- | ----------- | ---------- | ----------- | ---------- | -------- |
-| **异步物化视图** | 是 | 是 | 是 | <ul><li>异步刷新</li><li>手动刷新</li></ul> | 支持多表构建。基表可以来自：<ul><li>Default Catalog</li><li>External Catalog（v2.5）</li><li>已有异步物化视图（v2.5）</li><li>已有视图（v3.1）</li></ul> |
-| **同步物化视图（Rollup）** | 仅部分聚合函数 | 否 | 是 | 导入同步刷新 | 仅支持基于 Default Catalog 的单表构建 |
-
-## 同步物化视图
-
-### 语法
-
-```SQL
-CREATE MATERIALIZED VIEW [IF NOT EXISTS] [database.]<mv_name>
-[COMMENT ""]
-[PROPERTIES ("key"="value", ...)]
-AS 
-<query_statement>
-```
-
-### 参数
-
-**mv_name**（必填）
-
-物化视图的名称。命名要求如下：
-
-- 必须由字母（a-z 或 A-Z）、数字（0-9）或下划线（_）组成，且只能以字母开头。
-- 总长度不能超过 64 个字符。
-- 视图名大小写敏感。
-
-**COMMENT**（选填）
-
-物化视图的注释。注意建立物化视图时 `COMMENT` 必须在 `mv_name` 之后，否则创建失败。
-
-**query_statement**（必填）
-
-创建物化视图的查询语句，其结果即为物化视图中的数据。语法如下：
-
-```SQL
-SELECT select_expr[, select_expr ...]
-[WHERE where_expr]
-[GROUP BY column_name[, column_name ...]]
-[ORDER BY column_name[, column_name ...]]
-```
-
-- select_expr（必填）
-
-  构建同步物化视图的查询语句。
-
-  - 单列或聚合列：形如 `SELECT a, b, c FROM table_a`，其中 `a`、`b` 和 `c` 为基表的列名。如果您没有为物化视图指定列名，那么 StarRocks 自动为这些列命名。
-  - 表达式：形如 `SELECT a+1 AS x, b+2 AS y, c*c AS z FROM table_a`，其中 `a+1`、`b+2` 和 `c*c` 为包含基表列名的表达式，`x`、`y` 和 `z` 为物化视图的列名。
-
-  > **说明**
-  >
-  > - 该参数至少需包含一个单列。
-  > - 使用聚合函数创建同步物化视图时，必须指定 GROUP BY 子句，并在 `select_expr` 中指定至少一个 GROUP BY 列。
-  > - 同步物化视图不支持 JOIN、以及 GROUP BY 的 HAVING 子句。
-  > - 从 v3.1 开始，每个同步物化视图支持为基表的每一列使用多个聚合函数，支持形如 `select b, sum(a), min(a) from table group by b` 形式的查询语句。
-  > - 从 v3.1 开始，同步物化视图支持 SELECT 和聚合函数的复杂表达式，即形如 `select b, sum(a + 1) as sum_a1, min(cast (a as bigint)) as min_a from table group by b` 或 `select abs(b) as col1, a + 1 as col2, cast(a as bigint) as col3 from table` 的查询语句。同步物化视图的复杂表达式有以下限制：
-  >   - 每个复杂表达式必须有一个列名，并且基表所有同步物化视图中的不同复杂表达式的别名必须不同。例如，查询语句 `select b, sum(a + 1) as sum_a from table group by b` 和`select b, sum(a) as sum_a from table group by b` 不能同时用于为相同的基表创建同步物化视图，你可以为同一复杂表达式设置多个不同别名。
-  >   - 您可以通过执行 `EXPLAIN <sql_statement>` 来查看您的查询是否被使用复杂表达式创建的同步物化视图改写。更多信息请参见[查询分析](../../../administration/Query_planning.md)。
-
-- WHERE （选填）
-
-  自 v3.1.8 起，同步物化视图支持通过 WHERE 子句筛选数据。
-
-- GROUP BY（选填）
-
-  构建物化视图查询语句的分组列。如不指定该参数，则默认不对数据进行分组。
-
-- ORDER BY（选填）
-
-  构建物化视图查询语句的排序列。
-
-  - 排序列的声明顺序必须和 `select_expr` 中列声明顺序一致。
-  - 如果查询语句中包含分组列，则排序列必须和分组列一致。
-  - 如果不指定排序列，则系统根据以下规则自动补充排序列：
-  
-    - 如果物化视图是聚合类型，则所有的分组列自动补充为排序列。
-    - 如果物化视图是非聚合类型，则系统根据前缀列自动选择排序列。
-
-### 查询同步物化视图
-
-因为同步物化视图本质上是基表的索引而不是物理表，所以您只能使用 Hint `[_SYNC_MV_]` 查询同步物化视图：
-
-```SQL
--- 请勿省略 Hint 中的括号[]。
-SELECT * FROM <mv_name> [_SYNC_MV_];
-```
-
-> **注意**
->
-> 目前，StarRocks 会自动为同步物化视图中的列生成名称。您为同步物化视图中的列指定的 Alias 将无法生效。
-
-### 同步物化视图查询自动改写
-
-使用同步物化视图查询时，原始查询语句将会被自动改写并用于查询物化视图中保存的中间结果。
-
-下表展示了原始查询聚合函数和构建同步物化视图用到的聚合函数的匹配关系。您可以根据业务场景选择对应的聚合函数构建同步物化视图。
-
-| **原始查询聚合函数**                                   | **物化视图构建聚合函数** |
-| ------------------------------------------------------ | ------------------------ |
-| sum                                                    | sum                      |
-| min                                                    | min                      |
-| max                                                    | max                      |
-| count                                                  | count                    |
-| bitmap_union, bitmap_union_count, count(distinct)      | bitmap_union             |
-| hll_raw_agg, hll_union_agg, ndv, approx_count_distinct | hll_union                |
-
-## 异步物化视图
-
-### 语法
-
-```SQL
-CREATE MATERIALIZED VIEW [IF NOT EXISTS] [database.]<mv_name>
-[COMMENT ""]
--- distribution_desc
-[DISTRIBUTED BY HASH(<bucket_key>[,<bucket_key2> ...]) [BUCKETS <bucket_number>]]
--- refresh_desc
-[REFRESH 
--- refresh_moment
-    [IMMEDIATE | DEFERRED]
--- refresh_scheme
-    [ASYNC | ASYNC [START (<start_time>)] EVERY (INTERVAL <refresh_interval>) | MANUAL]
-]
--- partition_expression
-[PARTITION BY 
-    {<date_column> | date_trunc(fmt, <date_column>)}
-]
--- order_by_expression
-[ORDER BY (<sort_key>)]
-[PROPERTIES ("key"="value", ...)]
-AS 
-<query_statement>
-```
-
-### 参数
-
-**mv_name**（必填）
-
-物化视图的名称。命名要求如下：
-
-- 必须由字母（a-z 或 A-Z）、数字（0-9）或下划线（_）组成，且只能以字母开头。
-- 总长度不能超过 64 个字符。
-- 视图名大小写敏感。
-
-> **注意**
->
-> 同一张基表可以创建多个异步物化视图，但同一数据库内的异步物化视图名称不可重复。
-
-**COMMENT**（选填）
-
-物化视图的注释。注意建立物化视图时 `COMMENT` 必须在 `mv_name` 之后，否则创建失败。
-
-**distribution_desc**（选填）
-
-异步物化视图的分桶方式，包括哈希分桶和随机分桶（自 3.1 版本起）。如不指定该参数，StarRocks 使用随机分桶方式，并自动设置分桶数量。
-
-> **说明**
->
-> 创建异步物化视图时必须至少指定 `distribution_desc` 和 `refresh_scheme` 其中之一。
-
-- **哈希分桶**：
-
-  语法
-
-  ```SQL
-  DISTRIBUTED BY HASH (<bucket_key1>[,<bucket_key2> ...]) [BUCKETS <bucket_number>]
-  ```
-
-  更多信息，请参见 [分桶](../../../table_design/Data_distribution.md#分桶)。
-
-  > **说明**
-  >
-  > 自 2.5.7 版本起，StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS)，您无需手动设置分桶数量。更多信息，请参见 [设置分桶数量](../../../table_design/Data_distribution.md#设置分桶数量)。
-
-- **随机分桶**：
-
-  如果您选择随机分桶方式，并且自动设置分桶数量，则无需指定 `distribution_desc`。如果您需要手动设置分桶数，请使用以下语法：
-
-  ```SQL
-  DISTRIBUTED BY RANDOM BUCKETS <bucket_number>
-  ```
-
-  > **注意**
-  >
-  > 采用随机分桶方式的异步物化视图不支持设置 Colocation Group。
-
-  更多信息，请参见 [随机分桶](../../../table_design/Data_distribution.md#随机分桶自-v31)。
-
-**refresh_moment**（选填）
-
-物化视图的刷新时刻。默认值：`IMMEDIATE`。有效值：
-
-- `IMMEDIATE`：异步物化视图创建成功后立即刷新。
-- `DEFERRED`：异步物化视图创建成功后不进行刷新。您可以通过手动调用或创建定时任务触发刷新。
-
-**refresh_scheme**（选填）
-
-> **说明**
->
-> 创建异步物化视图时必须至少指定 `distribution_desc` 和 `refresh_scheme` 其中之一。
-
-物化视图的刷新方式。该参数支持如下值：
-
-- `ASYNC`: 自动刷新模式。每当基表数据发生变化时，物化视图会自动刷新。
-- `ASYNC [START (<start_time>)] EVERY(INTERVAL <interval>)`: 定时刷新模式。物化视图将按照定义的间隔定时刷新。您可以使用 `DAY`（天）、`HOUR`（小时）、`MINUTE`（分钟）和 `SECOND`（秒）作为单位指定间隔，格式为 `EVERY (interval n day/hour/minute/second)`。默认值为 `10 MINUTE`（10 分钟）。您还可以进一步指定刷新起始时间，格式为 `START('yyyy-MM-dd hh:mm:ss')`。如未指定起始时间，默认使用当前时间。示例：`ASYNC START ('2023-09-12 16:30:25') EVERY (INTERVAL 5 MINUTE)`。
-- `MANUAL`: 手动刷新模式。除非手动触发刷新任务，否则物化视图不会刷新。
-
-如果不指定该参数，则默认使用 MANUAL 方式。
-
-**partition_expression**（选填）
-
-异步物化视图的分区表达式。目前仅支持在创建异步物化视图时使用一个分区表达式。
-
-> **注意**
->
-> 异步物化视图暂不支持使用 List 分区策略。
-
-该参数支持如下值：
-
-- `date_column`：用于分区的列的名称。形如 `PARTITION BY dt`，表示按照 `dt` 列进行分区。
-- `date_trunc` 函数：形如 `PARTITION BY date_trunc("MONTH", dt)`，表示将 `dt` 列截断至以月为单位进行分区。date_trunc 函数支持截断的单位包括 `YEAR`、`MONTH`、`DAY`、`HOUR` 以及 `MINUTE`。
-- `str2date` 函数：用于将基表的 STRING 类型分区键转化为物化视图的分区键所需的日期类型。`PARTITION BY str2date(dt, "%Y%m%d")` 表示 `dt` 列是一个 STRING 类型日期，其日期格式为 `"%Y%m%d"`。`str2date` 函数支持多种日期格式。更多信息，参考[str2date](../../sql-functions/date-time-functions/str2date.md)。自 v3.1.4 起支持。
-- `time_slice` 或 `date_slice` 函数：从 v3.1 开始，您可以进一步使用 time_slice 或 date_slice 函数根据指定的时间粒度周期，将给定的时间转化到其所在的时间粒度周期的起始或结束时刻，例如 `PARTITION BY date_trunc("MONTH", time_slice(dt, INTERVAL 7 DAY))`，其中 time_slice 或 date_slice 的时间粒度必须比 `date_trunc` 的时间粒度更细。你可以使用它们来指定一个比分区键更细时间粒度的 GROUP BY 列，例如，`GROUP BY time_slice(dt, INTERVAL 1 MINUTE) PARTITION BY date_trunc('DAY', ts)`。
-
-如不指定该参数，则默认物化视图为无分区。
-
-**order_by_expression**（选填）
-
-异步物化视图的排序键。如不指定该参数，StarRocks 从 SELECT 列中选择部分前缀作为排序键，例如：`select a, b, c, d` 中, 排序列可能为 `a` 和 `b`。此参数自 StarRocks 3.0 起支持。
-
-**PROPERTIES**（选填）
-
-异步物化视图的属性。您可以使用 [ALTER MATERIALIZED VIEW](./ALTER_MATERIALIZED_VIEW.md) 修改已有异步物化视图的属性。
-
-- `session.`: 如果您想要更改与物化视图相关的 Session 变量属性，必须在属性前添加 `session.` 前缀，例如，`session.query_timeout`。对于非 Session 属性，例如，`mv_rewrite_staleness_second`，则无需指定前缀。
-- `replication_num`：创建物化视图副本数量。
-- `storage_medium`：存储介质类型。有效值：`HDD` 和 `SSD`。
-- `storage_cooldown_time`: 当设置存储介质为 SSD 时，指定该分区在该时间点之后从 SSD 降冷到 HDD，设置的时间必须大于当前时间。如不指定该属性，默认不进行自动降冷。取值格式为："yyyy-MM-dd HH:mm:ss"。
-- `partition_ttl`: 物化视图分区的生存时间 (TTL)。数据在指定的时间范围内的分区将被保留，过期的分区将被自动删除。单位：`YEAR`、`MONTH`、`DAY`、`HOUR` 和 `MINUTE`。例如，您可以将此属性设置为 `2 MONTH`（2个月）。建议您使用此属性，不推荐使用 `partition_ttl_number`。该属性自 v3.1.5 起支持。
-- `partition_ttl_number`：需要保留的最近的物化视图分区数量。对于分区开始时间小于当前时间的分区，当数量超过该值之后，多余的分区将会被删除。StarRocks 将根据 FE 配置项 `dynamic_partition_check_interval_seconds` 中的时间间隔定期检查物化视图分区，并自动删除过期分区。在[动态分区](../../../table_design/dynamic_partitioning.md)场景下，提前创建的未来分区将不会被纳入 TTL 考虑。默认值：`-1`。当值为 `-1` 时，将保留物化视图所有分区。
-- `partition_refresh_number`：单次刷新中，最多刷新的分区数量。如果需要刷新的分区数量超过该值，StarRocks 将拆分这次刷新任务，并分批完成。仅当前一批分区刷新成功时，StarRocks 会继续刷新下一批分区，直至所有分区刷新完成。如果其中有分区刷新失败，将不会产生后续的刷新任务。当值为 `-1` 时，将不会拆分刷新任务。自 v3.3 起，默认值由 `-1` 变为 `1`，表示 StarRocks 每次只刷新一个分区。
-- `excluded_trigger_tables`：在此项属性中列出的基表，其数据产生变化时不会触发对应物化视图自动刷新。该参数仅针对导入触发式刷新，通常需要与属性 `auto_refresh_partitions_limit` 搭配使用。形式：`[db_name.]table_name`。默认值为空字符串。当值为空字符串时，任意的基表数据变化都将触发对应物化视图刷新。
-- `auto_refresh_partitions_limit`：当触发物化视图刷新时，需要刷新的最近的物化视图分区数量。您可以通过该属性限制刷新的范围，降低刷新代价，但因为仅有部分分区刷新，有可能导致物化视图数据与基表无法保持一致。默认值：`-1`。当参数值为 `-1` 时，StarRocks 将刷新所有分区。当参数值为正整数 N 时，StarRocks 会将已存在的分区按时间先后排序，并刷新当前分区和 N-1 个历史分区。如果分区数不足 N，则刷新所有已存在的分区。如果物化视图存在提前创建的未来分区，将会刷新所有提前创建的分区。
-- `mv_rewrite_staleness_second`：如果当前物化视图的上一次刷新在此属性指定的时间间隔内，则此物化视图可直接用于查询改写，无论基表数据是否更新。如果上一次刷新时间早于此属性指定的时间间隔，StarRocks 通过检查基表数据是否变更决定该物化视图能否用于查询改写。单位：秒。该属性自 v3.0 起支持。
-- `colocate_with`：异步物化视图的 Colocation Group。更多信息请参阅 [Colocate Join](../../../using_starrocks/Colocate_join.md)。该属性自 v3.0 起支持。
-- `unique_constraints` 和 `foreign_key_constraints`：创建 View Delta Join 查询改写的异步物化视图时的 Unique Key 约束和外键约束。更多信息请参阅 [异步物化视图 - 基于 View Delta Join 场景改写查询](../../../using_starrocks/query_rewrite_with_materialized_views.md#view-delta-join-改写)。该属性自 v3.0 起支持。
-
-  > **注意**
-  >
-  > Unique Key 约束和外键约束仅用于查询改写。导入数据时，不保证进行外键约束校验。您必须确保导入的数据满足约束条件。
-
-- `resource_group`: 为物化视图刷新任务设置资源组。默认值为 `default_mv_wg`，即一个系统定义的，专门用于物化视图刷新的资源组。该资源组的 `cpu_core_limit` 为 `1`，`mem_limit` 为 `0.8`。更多关于资源组信息，请参考[资源隔离](../../../administration/management/resource_management/resource_group.md)。
-- `query_rewrite_consistency`: 指定当前异步物化视图的查询改写规则。该属性自 v3.2 起支持。有效值：
-  - `disable`：禁用基于该异步物化视图进行自动查询改写。
-  - `checked`（默认值）：仅在物化视图满足时效性要求时启用自动查询改写，即：
-    - 如果未指定 `mv_rewrite_staleness_second`，则只有当物化视图的数据与所有基表中的数据一致时，才可以将其用于查询改写。
-    - 如果指定了 `mv_rewrite_staleness_second`，则只有在其最后刷新在 staleness 时间间隔内时，才可以将物化视图用于查询改写。
-  - `loose`：直接启用自动查询改写，无需进行一致性检查。
-- `storage_volume`：[如果您使用存算分离集群](../../../deployment/shared_data/shared_data.mdx)，则需要指定创建物化视图的 Storage Volume 名称。该属性自 v3.1 版本起支持。如果未指定该属性，则使用默认 Storage Volume。示例：`"storage_volume" = "def_volume"`。
-- `force_external_table_query_rewrite`: 是否启用基于 External Catalog 的物化视图的查询改写。该属性自 v3.2 起支持。有效值：
-  - `true`（自 v3.3 变为默认值）：启用基于 External Catalog 的物化视图的查询改写。
-  - `false`：禁用基于 External Catalog 的物化视图的查询改写。
-
-  由于无法保证基表和基于 External Catalog 的物化视图之间的数据强一致，因此默认情况下禁用此功能。启用此功能时，物化视图将根据 `query_rewrite_consistency` 中指定的规则改写查询。
-- `enable_query_rewrite`：是否使用物化视图进行查询改写。当存在大量物化视图时，基于物化视图的查询改写可能会影响优化器的耗时。通过此属性，您可以控制是否允许使用物化视图进行查询改写。该功能自 v3.3.0 起支持。有效值：
-  - `default`（默认）：系统将不会针对物化视图执行语义检查，但只有 SPJG 类型的物化视图可以用于查询改写。请注意，如果启用了基于文本的查询改写，非 SPJG 类型的物化视图也可以用于查询改写。
-  - `true`：系统将在创建或修改物化视图时执行语义检查。如果物化视图不符合查询改写的条件（即，物化视图的定义不是 SPJG 类型的查询），则会返回失败信息。
-  - `false`：物化视图将不会用于查询改写。
-- [Preview] `transparent_mv_rewrite_mode`：为 **直接针对物化视图的查询** 指定透明改写模式。此功能从 v3.3.0 版本开始支持。有效值如下：
-  - `false`（默认，与早期版本行为兼容）：直接针对物化视图的查询不会被改写，仅返回物化视图中现有的数据。根据物化视图的刷新状态（数据一致性），其结果可能与直接执行物化视图定义查询的结果不同。
-  - `true`：直接针对物化视图的查询将被改写，并返回最新数据，结果与物化视图定义查询的一致。请注意，当物化视图处于失效（Inactive）状态或不支持透明查询改写时，这些查询将路由至物化视图定义查询执行。
-  - `transparent_or_error`：直接针对物化视图的查询将在符合条件时可以被改写。如果物化视图处于失效（Inactive）状态或不支持透明查询改写，将返回错误。
-  - `transparent_or_default`：直接针对物化视图的查询将在符合条件时可以被改写。如果物化视图处于失效（Inactive）状态或不支持透明查询改写，将返回物化视图中现有的数据。
-
-**query_statement**（必填）
-
-创建异步物化视图的查询语句，其结果即为异步物化视图中的数据。从 v3.1.6 版本开始，StarRocks 支持使用 Common Table Expression (CTE) 创建异步物化视图。
-
-> **注意**
->
-> 异步物化视图暂不支持基于使用 List 分区的基表创建。
-
-### 查询异步物化视图
-
-异步物化视图本质是一张实体表。您可以将其作为普通表进行任何**除直接导入数据**以外的操作。
-
-### 支持数据类型
-
-- 基于 StarRocks 内部数据目录（Default Catalog）创建的异步物化视图支持以下数据类型：
-
-  - **日期类型**：DATE、DATETIME
-  - **字符串类型**：CHAR、VARCHAR
-  - **数值类型**：BOOLEAN、TINYINT、SMALLINT、INT、BIGINT、LARGEINT、FLOAT、DOUBLE、DECIMAL、PERCENTILE
-  - **半结构化类型**：ARRAY、JSON、MAP（自 v3.1 起）、STRUCT（自 v3.1 起）
-  - **其他类型**：BITMAP、HLL
-
-> **说明**
->
-> 自 v2.4.5 起支持 BITMAP、HLL 以及 PERCENTILE。
-
-- 基于 StarRocks 外部数据目录（External Catalog）创建的异步物化视图支持以下数据类型：
-
-  - Hive Catalog
-
-    - **数值类型**：INT/INTEGER、BIGINT、DOUBLE、FLOAT、DECIMAL
-    - **日期类型**：TIMESTAMP
-    - **字符串类型**：STRING、VARCHAR、CHAR
-    - **半结构化类型**：ARRAY
-
-  - Hudi Catalog
-
-    - **数值类型**：BOOLEAN、INT、LONG、FLOAT、DOUBLE、DECIMAL
-    - **日期类型**：DATE、TimeMillis/TimeMicros、TimestampMillis/TimestampMicros
-    - **字符串类型**：STRING
-    - **半结构化类型**：ARRAY
-
-  - Iceberg Catalog
-
-    - **数值类型**：BOOLEAN、INT、LONG、FLOAT、DOUBLE、DECIMAL(P, S)
-    - **日期类型**：DATE、TIME、TIMESTAMP
-    - **字符串类型**：STRING、UUID、FIXED(L)、BINARY
-    - **半结构化类型**：LIST
-
-## 注意事项
-
-- 当前版本暂时不支持同时创建多个物化视图。仅当当前创建任务完成时，方可执行下一个创建任务。
-
-- 关于同步物化视图：
-
-  - 同步物化视图仅支持单列聚合函数，不支持形如 `sum(a+b)` 的查询语句。
-  - 同步物化视图仅支持对同一列数据使用一种聚合函数，不支持形如 `select sum(a), min(a) from table` 的查询语句。
-  - 同步物化视图中使用聚合函数需要与 GROUP BY 语句一起使用，且 SELECT 的列中至少包含一个分组列。
-  - 同步物化视图创建语句不支持 JOIN 以及 GROUP BY 的 HAVING 子句。
-  - 使用 ALTER TABLE DROP COLUMN 删除基表中特定列时，需要保证该基表所有同步物化视图中不包含被删除列，否则无法进行删除操作。如果必须删除该列，则需要将所有包含该列的同步物化视图删除，然后进行删除列操作。
-  - 为一张表创建过多的同步物化视图会影响导入的效率。导入数据时，同步物化视图和基表数据将同步更新，如果一张基表包含 n 个物化视图，向基表导入数据时，其导入效率大约等同于导入 n 张表，数据导入的速度会变慢。
-
-- 关于嵌套异步物化视图：
-
-  - 每个异步物化视图的刷新方式仅影响当前物化视图。
-  - 当前 StarRocks 不对嵌套层数进行限制。生产环境中建议嵌套层数不超过三层。
-
-- 关于外部数据目录异步物化视图：
-
-  - 外部数据目录物化视图仅支持异步定时刷新和手动刷新。
-  - 物化视图中的数据不保证与外部数据目录的数据强一致。
-  - 目前暂不支持基于资源（Resource）构建物化视图。
-  - StarRocks 目前无法感知外部数据目录基表数据是否发生变动，所以每次刷新会默认刷新所有分区。您可以通过手动刷新方式指定刷新部分分区。
-
-## 示例
-
-### 同步物化视图示例
-
-基表结构为：
-
-```sql
-mysql> desc duplicate_table;
-+-------+--------+------+------+---------+-------+
-| Field | Type   | Null | Key  | Default | Extra |
-+-------+--------+------+------+---------+-------+
-| k1    | INT    | Yes  | true | N/A     |       |
-| k2    | INT    | Yes  | true | N/A     |       |
-| k3    | BIGINT | Yes  | true | N/A     |       |
-| k4    | BIGINT | Yes  | true | N/A     |       |
-+-------+--------+------+------+---------+-------+
-```
-
-1. 创建一个仅包含原始表 （k1，k2）列的物化视图。
-
-    ```sql
-    create materialized view k1_k2 as
-    select k1, k2 from duplicate_table;
-    ```
-
-    物化视图的 schema 如下图，物化视图仅包含两列 k1、k2 且不带任何聚合。
-
-    ```sql
-    +-----------------+-------+--------+------+------+---------+-------+
-    | IndexName       | Field | Type   | Null | Key  | Default | Extra |
-    +-----------------+-------+--------+------+------+---------+-------+
-    | k1_k2           | k1    | INT    | Yes  | true | N/A     |       |
-    |                 | k2    | INT    | Yes  | true | N/A     |       |
-    +-----------------+-------+--------+------+------+---------+-------+
-    ```
-
-2. 创建一个以 k2 为排序列的物化视图。
-
-    ```sql
-    create materialized view k2_order as
-    select k2, k1 from duplicate_table order by k2;
-    ```
-
-    物化视图的 schema 如下图，物化视图仅包含两列 k2、k1，其中 k2 列为排序列，不带任何聚合。
-
-    ```sql
-    +-----------------+-------+--------+------+-------+---------+-------+
-    | IndexName       | Field | Type   | Null | Key   | Default | Extra |
-    +-----------------+-------+--------+------+-------+---------+-------+
-    | k2_order        | k2    | INT    | Yes  | true  | N/A     |       |
-    |                 | k1    | INT    | Yes  | false | N/A     | NONE  |
-    +-----------------+-------+--------+------+-------+---------+-------+
-    ```
-
-3. 创建一个以 k1，k2 分组，k3 列为 SUM 聚合的物化视图。
-
-    ```sql
-    create materialized view k1_k2_sumk3 as
-    select k1, k2, sum(k3) from duplicate_table group by k1, k2;
-    ```
-
-    物化视图的 schema 如下图，物化视图包含两列 k1、k2，sum(k3) 其中 k1、k2 为分组列，sum(k3) 为根据 k1、k2 分组后的 k3 列的求和值。
-
-    由于物化视图没有声明排序列，且物化视图带聚合数据，系统默认补充分组列 k1、k2 为排序列。
-
-    ```sql
-    +-----------------+-------+--------+------+-------+---------+-------+
-    | IndexName       | Field | Type   | Null | Key   | Default | Extra |
-    +-----------------+-------+--------+------+-------+---------+-------+
-    | k1_k2_sumk3     | k1    | INT    | Yes  | true  | N/A     |       |
-    |                 | k2    | INT    | Yes  | true  | N/A     |       |
-    |                 | k3    | BIGINT | Yes  | false | N/A     | SUM   |
-    +-----------------+-------+--------+------+-------+---------+-------+
-    ```
-
-4. 创建一个去除重复行的物化视图。
-
-    ```sql
-    create materialized view deduplicate as
-    select k1, k2, k3, k4 from duplicate_table group by k1, k2, k3, k4;
-    ```
-
-    物化视图 schema 如下图，物化视图包含 k1、k2、k3、k4 列，且不存在重复行。
-
-    ```sql
-    +-----------------+-------+--------+------+-------+---------+-------+
-    | IndexName       | Field | Type   | Null | Key   | Default | Extra |
-    +-----------------+-------+--------+------+-------+---------+-------+
-    | deduplicate     | k1    | INT    | Yes  | true  | N/A     |       |
-    |                 | k2    | INT    | Yes  | true  | N/A     |       |
-    |                 | k3    | BIGINT | Yes  | true  | N/A     |       |
-    |                 | k4    | BIGINT | Yes  | true  | N/A     |       |
-    +-----------------+-------+--------+------+-------+---------+-------+
-
-    ```
-
-5. 创建一个不声明排序列的非聚合型物化视图。
-
-    all_type_table 的 schema 如下：
-
-    ```sql
-    +-------+--------------+------+-------+---------+-------+
-    | Field | Type         | Null | Key   | Default | Extra |
-    +-------+--------------+------+-------+---------+-------+
-    | k1    | TINYINT      | Yes  | true  | N/A     |       |
-    | k2    | SMALLINT     | Yes  | true  | N/A     |       |
-    | k3    | INT          | Yes  | true  | N/A     |       |
-    | k4    | BIGINT       | Yes  | true  | N/A     |       |
-    | k5    | DECIMAL(9,0) | Yes  | true  | N/A     |       |
-    | k6    | DOUBLE       | Yes  | false | N/A     | NONE  |
-    | k7    | VARCHAR(20)  | Yes  | false | N/A     | NONE  |
-    +-------+--------------+------+-------+---------+-------+
-    ```
-
-    物化视图包含 k3、k4、k5、k6、k7 列，且不声明排序列，则创建语句如下：
-
-    ```sql
-    create materialized view mv_1 as
-    select k3, k4, k5, k6, k7 from all_type_table;
-    ```
-
-    系统默认补充的排序列为 k3、k4、k5 三列。这三列类型的字节数之和为 4(INT) + 8(BIGINT) + 16(DECIMAL) = 28 < 36。所以补充的是这三列作为排序列。
-    物化视图的 schema 如下，可以看到其中 k3、k4、k5 列的 key 字段为 true，也就是排序列。k6、k7 列的 key 字段为 false，也就是非排序列。
-
-    ```sql
-    +----------------+-------+--------------+------+-------+---------+-------+
-    | IndexName      | Field | Type         | Null | Key   | Default | Extra |
-    +----------------+-------+--------------+------+-------+---------+-------+
-    | mv_1           | k3    | INT          | Yes  | true  | N/A     |       |
-    |                | k4    | BIGINT       | Yes  | true  | N/A     |       |
-    |                | k5    | DECIMAL(9,0) | Yes  | true  | N/A     |       |
-    |                | k6    | DOUBLE       | Yes  | false | N/A     | NONE  |
-    |                | k7    | VARCHAR(20)  | Yes  | false | N/A     | NONE  |
-    +----------------+-------+--------------+------+-------+---------+-------+
-    ```
-
-6. 使用 WHERE 子句和复杂表达式创建同步物化视图。
-
-  ```sql
-  -- 创建基表 user_event
-  CREATE TABLE user_event (
-      ds date   NOT NULL,
-      id  varchar(256)    NOT NULL,
-      user_id int DEFAULT NULL,
-      user_id1    varchar(256)    DEFAULT NULL,
-      user_id2    varchar(256)    DEFAULT NULL,
-      column_01   int DEFAULT NULL,
-      column_02   int DEFAULT NULL,
-      column_03   int DEFAULT NULL,
-      column_04   int DEFAULT NULL,
-      column_05   int DEFAULT NULL,
-      column_06   DECIMAL(12,2)   DEFAULT NULL,
-      column_07   DECIMAL(12,3)   DEFAULT NULL,
-      column_08   JSON   DEFAULT NULL,
-      column_09   DATETIME    DEFAULT NULL,
-      column_10   DATETIME    DEFAULT NULL,
-      column_11   DATE    DEFAULT NULL,
-      column_12   varchar(256)    DEFAULT NULL,
-      column_13   varchar(256)    DEFAULT NULL,
-      column_14   varchar(256)    DEFAULT NULL,
-      column_15   varchar(256)    DEFAULT NULL,
-      column_16   varchar(256)    DEFAULT NULL,
-      column_17   varchar(256)    DEFAULT NULL,
-      column_18   varchar(256)    DEFAULT NULL,
-      column_19   varchar(256)    DEFAULT NULL,
-      column_20   varchar(256)    DEFAULT NULL,
-      column_21   varchar(256)    DEFAULT NULL,
-      column_22   varchar(256)    DEFAULT NULL,
-      column_23   varchar(256)    DEFAULT NULL,
-      column_24   varchar(256)    DEFAULT NULL,
-      column_25   varchar(256)    DEFAULT NULL,
-      column_26   varchar(256)    DEFAULT NULL,
-      column_27   varchar(256)    DEFAULT NULL,
-      column_28   varchar(256)    DEFAULT NULL,
-      column_29   varchar(256)    DEFAULT NULL,
-      column_30   varchar(256)    DEFAULT NULL,
-      column_31   varchar(256)    DEFAULT NULL,
-      column_32   varchar(256)    DEFAULT NULL,
-      column_33   varchar(256)    DEFAULT NULL,
-      column_34   varchar(256)    DEFAULT NULL,
-      column_35   varchar(256)    DEFAULT NULL,
-      column_36   varchar(256)    DEFAULT NULL,
-      column_37   varchar(256)    DEFAULT NULL
-  )
-  PARTITION BY date_trunc("day", ds)
-  DISTRIBUTED BY hash(id);
-  
-  -- 使用 WHERE 子句和复杂表达式创建同步物化视图
-  CREATE MATERIALIZED VIEW test_mv1
-  AS 
-  SELECT
-  ds,
-  column_19,
-  column_36,
-  sum(column_01) as column_01_sum,
-  bitmap_union(to_bitmap( user_id)) as user_id_dist_cnt,
-  bitmap_union(to_bitmap(case when column_01 > 1 and column_34 IN ('1','34')   then user_id2 else null end)) as filter_dist_cnt_1,
-  bitmap_union(to_bitmap( case when column_02 > 60 and column_35 IN ('11','13') then  user_id2 else null end)) as filter_dist_cnt_2,
-  bitmap_union(to_bitmap(case when column_03 > 70 and column_36 IN ('21','23') then  user_id2 else null end)) as filter_dist_cnt_3,
-  bitmap_union(to_bitmap(case when column_04 > 20 and column_27 IN ('31','27') then  user_id2 else null end)) as filter_dist_cnt_4,
-  bitmap_union(to_bitmap( case when column_05 > 90 and column_28 IN ('41','43') then  user_id2 else null end)) as filter_dist_cnt_5
-  FROM user_event
-  WHERE ds >= '2023-11-02'
-  GROUP BY
-  ds,
-  column_19,
-  column_36;
-  ```
-
-### 异步物化视图示例
-
-以下示例基于下列基表。
-
-```SQL
-CREATE TABLE `lineorder` (
-  `lo_orderkey` int(11) NOT NULL COMMENT "",
-  `lo_linenumber` int(11) NOT NULL COMMENT "",
-  `lo_custkey` int(11) NOT NULL COMMENT "",
-  `lo_partkey` int(11) NOT NULL COMMENT "",
-  `lo_suppkey` int(11) NOT NULL COMMENT "",
-  `lo_orderdate` int(11) NOT NULL COMMENT "",
-  `lo_orderpriority` varchar(16) NOT NULL COMMENT "",
-  `lo_shippriority` int(11) NOT NULL COMMENT "",
-  `lo_quantity` int(11) NOT NULL COMMENT "",
-  `lo_extendedprice` int(11) NOT NULL COMMENT "",
-  `lo_ordtotalprice` int(11) NOT NULL COMMENT "",
-  `lo_discount` int(11) NOT NULL COMMENT "",
-  `lo_revenue` int(11) NOT NULL COMMENT "",
-  `lo_supplycost` int(11) NOT NULL COMMENT "",
-  `lo_tax` int(11) NOT NULL COMMENT "",
-  `lo_commitdate` int(11) NOT NULL COMMENT "",
-  `lo_shipmode` varchar(11) NOT NULL COMMENT ""
-) ENGINE=OLAP
-DUPLICATE KEY(`lo_orderkey`)
-COMMENT "OLAP"
-PARTITION BY RANGE(`lo_orderdate`)
-(PARTITION p1 VALUES [("-2147483648"), ("19930101")),
-PARTITION p2 VALUES [("19930101"), ("19940101")),
-PARTITION p3 VALUES [("19940101"), ("19950101")),
-PARTITION p4 VALUES [("19950101"), ("19960101")),
-PARTITION p5 VALUES [("19960101"), ("19970101")),
-PARTITION p6 VALUES [("19970101"), ("19980101")),
-PARTITION p7 VALUES [("19980101"), ("19990101")))
-DISTRIBUTED BY HASH(`lo_orderkey`);
-
-CREATE TABLE IF NOT EXISTS `customer` (
-  `c_custkey` int(11) NOT NULL COMMENT "",
-  `c_name` varchar(26) NOT NULL COMMENT "",
-  `c_address` varchar(41) NOT NULL COMMENT "",
-  `c_city` varchar(11) NOT NULL COMMENT "",
-  `c_nation` varchar(16) NOT NULL COMMENT "",
-  `c_region` varchar(13) NOT NULL COMMENT "",
-  `c_phone` varchar(16) NOT NULL COMMENT "",
-  `c_mktsegment` varchar(11) NOT NULL COMMENT ""
-) ENGINE=OLAP
-DUPLICATE KEY(`c_custkey`)
-COMMENT "OLAP"
-DISTRIBUTED BY HASH(`c_custkey`);
-
-CREATE TABLE IF NOT EXISTS `dates` (
-  `d_datekey` int(11) NOT NULL COMMENT "",
-  `d_date` varchar(20) NOT NULL COMMENT "",
-  `d_dayofweek` varchar(10) NOT NULL COMMENT "",
-  `d_month` varchar(11) NOT NULL COMMENT "",
-  `d_year` int(11) NOT NULL COMMENT "",
-  `d_yearmonthnum` int(11) NOT NULL COMMENT "",
-  `d_yearmonth` varchar(9) NOT NULL COMMENT "",
-  `d_daynuminweek` int(11) NOT NULL COMMENT "",
-  `d_daynuminmonth` int(11) NOT NULL COMMENT "",
-  `d_daynuminyear` int(11) NOT NULL COMMENT "",
-  `d_monthnuminyear` int(11) NOT NULL COMMENT "",
-  `d_weeknuminyear` int(11) NOT NULL COMMENT "",
-  `d_sellingseason` varchar(14) NOT NULL COMMENT "",
-  `d_lastdayinweekfl` int(11) NOT NULL COMMENT "",
-  `d_lastdayinmonthfl` int(11) NOT NULL COMMENT "",
-  `d_holidayfl` int(11) NOT NULL COMMENT "",
-  `d_weekdayfl` int(11) NOT NULL COMMENT ""
-) ENGINE=OLAP
-DUPLICATE KEY(`d_datekey`)
-COMMENT "OLAP"
-DISTRIBUTED BY HASH(`d_datekey`);
-
-CREATE TABLE IF NOT EXISTS `supplier` (
-  `s_suppkey` int(11) NOT NULL COMMENT "",
-  `s_name` varchar(26) NOT NULL COMMENT "",
-  `s_address` varchar(26) NOT NULL COMMENT "",
-  `s_city` varchar(11) NOT NULL COMMENT "",
-  `s_nation` varchar(16) NOT NULL COMMENT "",
-  `s_region` varchar(13) NOT NULL COMMENT "",
-  `s_phone` varchar(16) NOT NULL COMMENT ""
-) ENGINE=OLAP
-DUPLICATE KEY(`s_suppkey`)
-COMMENT "OLAP"
-DISTRIBUTED BY HASH(`s_suppkey`);
-
-CREATE TABLE IF NOT EXISTS `part` (
-  `p_partkey` int(11) NOT NULL COMMENT "",
-  `p_name` varchar(23) NOT NULL COMMENT "",
-  `p_mfgr` varchar(7) NOT NULL COMMENT "",
-  `p_category` varchar(8) NOT NULL COMMENT "",
-  `p_brand` varchar(10) NOT NULL COMMENT "",
-  `p_color` varchar(12) NOT NULL COMMENT "",
-  `p_type` varchar(26) NOT NULL COMMENT "",
-  `p_size` int(11) NOT NULL COMMENT "",
-  `p_container` varchar(11) NOT NULL COMMENT ""
-) ENGINE=OLAP
-DUPLICATE KEY(`p_partkey`)
-COMMENT "OLAP"
-DISTRIBUTED BY HASH(`p_partkey`);
-
-create table orders ( 
-    dt date NOT NULL, 
-    order_id bigint NOT NULL, 
-    user_id int NOT NULL, 
-    merchant_id int NOT NULL, 
-    good_id int NOT NULL, 
-    good_name string NOT NULL, 
-    price int NOT NULL, 
-    cnt int NOT NULL, 
-    revenue int NOT NULL, 
-    state tinyint NOT NULL 
-) 
-PRIMARY KEY (dt, order_id) 
-PARTITION BY RANGE(`dt`) 
-( PARTITION p20210820 VALUES [('2021-08-20'), ('2021-08-21')), 
-PARTITION p20210821 VALUES [('2021-08-21'), ('2021-08-22')) ) 
-DISTRIBUTED BY HASH(order_id)
-PROPERTIES (
-    "replication_num" = "3", 
-    "enable_persistent_index" = "true"
-);
-```
-
-示例一：从源表创建非分区物化视图
-
-```SQL
-CREATE MATERIALIZED VIEW lo_mv1
-DISTRIBUTED BY HASH(`lo_orderkey`)
-REFRESH ASYNC
-AS
-select
-    lo_orderkey, 
-    lo_custkey, 
-    sum(lo_quantity) as total_quantity, 
-    sum(lo_revenue) as total_revenue, 
-    count(lo_shipmode) as shipmode_count
-from lineorder 
-group by lo_orderkey, lo_custkey 
-order by lo_orderkey;
-```
-
-示例二：从源表创建分区物化视图
-
-```SQL
-CREATE MATERIALIZED VIEW lo_mv2
-PARTITION BY `lo_orderdate`
-DISTRIBUTED BY HASH(`lo_orderkey`)
-REFRESH ASYNC START('2023-07-01 10:00:00') EVERY (interval 1 day)
-AS
-select
-    lo_orderkey,
-    lo_orderdate,
-    lo_custkey, 
-    sum(lo_quantity) as total_quantity, 
-    sum(lo_revenue) as total_revenue, 
-    count(lo_shipmode) as shipmode_count
-from lineorder 
-group by lo_orderkey, lo_orderdate, lo_custkey
-order by lo_orderkey;
-
-# 使用 date_trunc 函数将 `dt` 列截断至以月为单位进行分区。
-CREATE MATERIALIZED VIEW order_mv1
-PARTITION BY date_trunc('month', `dt`)
-DISTRIBUTED BY HASH(`order_id`)
-REFRESH ASYNC START('2023-07-01 10:00:00') EVERY (interval 1 day)
-AS
-select
-    dt,
-    order_id,
-    user_id,
-    sum(cnt) as total_cnt,
-    sum(revenue) as total_revenue, 
-    count(state) as state_count
-from orders
-group by dt, order_id, user_id;
-```
-
-示例三：创建异步物化视图
-
-```SQL
-CREATE MATERIALIZED VIEW flat_lineorder
-DISTRIBUTED BY HASH(`lo_orderkey`)
-REFRESH MANUAL
-AS
-SELECT
-    l.LO_ORDERKEY AS LO_ORDERKEY,
-    l.LO_LINENUMBER AS LO_LINENUMBER,
-    l.LO_CUSTKEY AS LO_CUSTKEY,
-    l.LO_PARTKEY AS LO_PARTKEY,
-    l.LO_SUPPKEY AS LO_SUPPKEY,
-    l.LO_ORDERDATE AS LO_ORDERDATE,
-    l.LO_ORDERPRIORITY AS LO_ORDERPRIORITY,
-    l.LO_SHIPPRIORITY AS LO_SHIPPRIORITY,
-    l.LO_QUANTITY AS LO_QUANTITY,
-    l.LO_EXTENDEDPRICE AS LO_EXTENDEDPRICE,
-    l.LO_ORDTOTALPRICE AS LO_ORDTOTALPRICE,
-    l.LO_DISCOUNT AS LO_DISCOUNT,
-    l.LO_REVENUE AS LO_REVENUE,
-    l.LO_SUPPLYCOST AS LO_SUPPLYCOST,
-    l.LO_TAX AS LO_TAX,
-    l.LO_COMMITDATE AS LO_COMMITDATE,
-    l.LO_SHIPMODE AS LO_SHIPMODE,
-    c.C_NAME AS C_NAME,
-    c.C_ADDRESS AS C_ADDRESS,
-    c.C_CITY AS C_CITY,
-    c.C_NATION AS C_NATION,
-    c.C_REGION AS C_REGION,
-    c.C_PHONE AS C_PHONE,
-    c.C_MKTSEGMENT AS C_MKTSEGMENT,
-    s.S_NAME AS S_NAME,
-    s.S_ADDRESS AS S_ADDRESS,
-    s.S_CITY AS S_CITY,
-    s.S_NATION AS S_NATION,
-    s.S_REGION AS S_REGION,
-    s.S_PHONE AS S_PHONE,
-    p.P_NAME AS P_NAME,
-    p.P_MFGR AS P_MFGR,
-    p.P_CATEGORY AS P_CATEGORY,
-    p.P_BRAND AS P_BRAND,
-    p.P_COLOR AS P_COLOR,
-    p.P_TYPE AS P_TYPE,
-    p.P_SIZE AS P_SIZE,
-    p.P_CONTAINER AS P_CONTAINER FROM lineorder AS l 
-INNER JOIN customer AS c ON c.C_CUSTKEY = l.LO_CUSTKEY
-INNER JOIN supplier AS s ON s.S_SUPPKEY = l.LO_SUPPKEY
-INNER JOIN part AS p ON p.P_PARTKEY = l.LO_PARTKEY;
-```
-
-示例四：创建分区物化视图，并将基表 STRING 类型分区键转化为日期类型作为异步物化视图分区键。
-
-```sql
--- 创建分区键为 STRING 类型的基表。
-CREATE TABLE `part_dates` (
-  `d_date` varchar(20) DEFAULT NULL,
-  `d_dayofweek` varchar(10) DEFAULT NULL,
-  `d_month` varchar(11) DEFAULT NULL,
-  `d_year` int(11) DEFAULT NULL,
-  `d_yearmonthnum` int(11) DEFAULT NULL,
-  `d_yearmonth` varchar(9) DEFAULT NULL,
-  `d_daynuminweek` int(11) DEFAULT NULL,
-  `d_daynuminmonth` int(11) DEFAULT NULL,
-  `d_daynuminyear` int(11) DEFAULT NULL,
-  `d_monthnuminyear` int(11) DEFAULT NULL,
-  `d_weeknuminyear` int(11) DEFAULT NULL,
-  `d_sellingseason` varchar(14) DEFAULT NULL,
-  `d_lastdayinweekfl` int(11) DEFAULT NULL,
-  `d_lastdayinmonthfl` int(11) DEFAULT NULL,
-  `d_holidayfl` int(11) DEFAULT NULL,
-  `d_weekdayfl` int(11) DEFAULT NULL,
-  `d_datekey` varchar(11) DEFAULT NULL
-) partition by (d_datekey);
-
-
--- 使用 `str2date` 函数创建分区物化视图。
-CREATE MATERIALIZED VIEW IF NOT EXISTS `test_mv` 
-PARTITION BY str2date(`d_datekey`,'%Y%m%d')
-DISTRIBUTED BY HASH(`d_date`, `d_month`, `d_month`) 
-REFRESH MANUAL 
-AS
-SELECT
-  `d_date` ,
-  `d_dayofweek`,
-  `d_month` ,
-  `d_yearmonthnum` ,
-  `d_yearmonth` ,
-  `d_daynuminweek`,
-  `d_daynuminmonth`,
-  `d_daynuminyear` ,
-  `d_monthnuminyear` ,
-  `d_weeknuminyear` ,
-  `d_sellingseason`,
-  `d_lastdayinweekfl`,
-  `d_lastdayinmonthfl`,
-  `d_holidayfl` ,
-  `d_weekdayfl`,
-  `d_datekey`
-FROM
-`hive_catalog`.`ssb_1g_orc`.`part_dates` ;
-```
-
-## 更多操作
-
-如要创建逻辑视图，请参见 [CREATE VIEW](./CREATE_VIEW.md)。
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_RESOURCE.md b/docs/zh/sql-reference/sql-statements/data-definition/CREATE_RESOURCE.md
deleted file mode 100644
index dcd22a4de929fc..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_RESOURCE.md
+++ /dev/null
@@ -1,257 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CREATE RESOURCE
-
-## 功能
-
-创建资源。StarRocks 支持创建以下资源：Apache Spark™、Apache Hive™、Apache Iceberg、 Apache Hudi 和 JDBC。其中 Spark 资源用于 [Spark Load](../../../loading/SparkLoad.md)，负责管理数据导入的相关信息，比如 YARN 配置，中间数据存储的路径以及 Broker 配置等；Hive、Iceberg、Hudi 和 JDBC 资源用于在查询[外部表](../../../data_source/External_table.md)是管理数据源的访问信息。
-
-> 说明：
->
-> - 只有拥有 System 级 CREATE RESOURCE 权限的用户才可以创建资源。
-> - StarRocks 2.3 及以上版本支持创建 JDBC 资源。
-
-## 语法
-
-```SQL
-CREATE EXTERNAL RESOURCE "resource_name"
-PROPERTIES ("key"="value"[, ...])
-```
-
-## 参数说明
-
-### resource_name
-
-资源名称。命名要求参见[系统限制](../../../reference/System_limit.md)。
-
-### PROPERTIES
-
-资源配置项，不同类型的资源可设置不同配置项。
-
-#### Spark 资源
-
-Spark 集群配置不同，资源需要添加的配置项也不同。当前 Spark Load 仅支持 Spark 的 cluster manager 为 YARN 且数据存储系统为 HDFS，且 YARN 和 HDFS 均支持 HA（高可用）。具体可分为以下几种情况：
-
-- 如果选择使用Broker 进程的方式导入
-
-  - 如果 Spark 的 cluster manager 为 YARN，数据存储系统为 HDFS，则需添加如下配置项：
-
-    | **配置项**                                | **必选** | **说明**                                                     |
-    | ----------------------------------------- | -------- | ------------------------------------------------------------ |
-    | type                                      | 是       | 资源类型，取值为 `spark`。                                   |
-    | spark.master                              | 是       | Spark 的 cluster manager。当前仅支持 YARN，所以取值为 `yarn`。 |
-    | spark.submit.deployMode                   | 是       | Spark driver 的部署模式。取值包括`cluster`和`client`。关于取值说明，参考 [Launching Spark on YARN](https://spark.apache.org/docs/3.3.0/running-on-yarn.html#launching-spark-on-yarn)。 |
-    | spark.executor.memory                     | 否       | Spark executor 占用的内存量，单位为 KB、MB、GB 或 TB。       |
-    | spark.yarn.queue                          | 否       | YARN 队列名称。                                              |
-    | spark.hadoop.yarn.resourcemanager.address | 是       | YARN ResourceManager 地址。                                  |
-    | spark.hadoop.fs.defaultFS                 | 是       | HDFS 中 NameNode 的地址。格式为：`hdfs://namenode_host:port`。 |
-    | working_dir                               | 是       | 一个 HDFS 文件路径，用于存放 ETL 作业生成的文件。例如：`hdfs://host: port/tmp/starrocks`。 |
-    | broker                                    | 是       | Broker 名称。您可以使用 [SHOW BROKER](../Administration/SHOW_BROKER.md) 语句查看当前所有 Broker 的名称。如未添加过 Broker，可使用 [ALTER SYSTEM](../Administration/ALTER_SYSTEM.md) 语句添加 Broker。 |
-    | broker.username                           | 否       | 通过指定的 HDFS 用户去访问HDFS中的文件。如果 HDFS 文件只能由特定用户访问，则需要传入该参数，如果该文件是所有用户都可以访问的话，则不需要传入该参数。 |
-    | broker.password                           | 否       | HDFS 用户密码。                                              |
-
-  - 如果 Spark 的 cluster manager 为 YARN，并且为 YARN ResourceManager HA，数据存储系统为 HDFS，则需添加如下配置项：
-
-    | **配置项**                                       | **必选** | **说明**                                                     |
-    | ------------------------------------------------ | -------- | ------------------------------------------------------------ |
-    | type                                             | 是       | 资源类型，取值为`spark`。                                    |
-    | spark.master                                     | 是       | Spark 的 cluster manager。当前仅支持 YARN，所以取值为`yarn`。 |
-    | spark.submit.deployMode                          | 是       | Spark 驱动程序的部署模式。取值包括`cluster`和`client`。关于取值说明，参考 [Launching Spark on YARN](https://spark.apache.org/docs/3.3.0/running-on-yarn.html#launching-spark-on-yarn)。 |
-    | spark.hadoop.yarn.resourcemanager.ha.enabled     | 是       | YARN ResourceManager 是否启用 HA。需设置该参数为`true`，即启用 HA。 |
-    | spark.hadoop.yarn.resourcemanager.ha.rm-ids      | 是       | YARN ResourceManager 的逻辑 ID 列表。多个逻辑 ID 之间用逗号 (`,`) 隔开。 |
-    | spark.hadoop.yarn.resourcemanager.hostname.rm-id | 是       | 对于每个 rm-id，需指定 ResourceManager 对应的主机名。如已添加该配置项，则不需要再添加`spark.hadoop.yarn.resourcemanager.address.rm-id`。 |
-    | spark.hadoop.yarn.resourcemanager.address.rm-id  | 是       | 对于每个rm-id，需指定 ResourceManager 对应 `host:port`。如已添加该配置项，则不需要再添加`spark.hadoop.yarn.resourcemanager.hostname.rm-id`。 |
-    | spark.hadoop.fs.defaultFS                        | 是       | Spark 使用的 HDFS 中 NameNode 节点地址。格式为：`hdfs://namenode_host:port`。 |
-    | working_dir                                      | 是       | ETL 作业目录，用于存放 ETL 作业生成的中间数据。例如：`hdfs://host: port/tmp/starrocks`。 |
-    | broker                                           | 是       | Broker 名称。您可以使用 [SHOW BROKER](../Administration/SHOW_BROKER.md) 语句查看当前所有 Broker 的名称。如未添加过 Broker，可使用 [ALTER SYSTEM](../Administration/ALTER_SYSTEM.md) 语句添加 Broker。 |
-    | broker.username                           | 否       | 通过指定的 HDFS 用户去访问HDFS中的文件。如果 HDFS 文件只能由特定用户访问，则需要传入该参数，如果该文件是所有用户都可以访问的话，则不需要传入该参数。 |
-    | broker.password                           | 否       | HDFS 用户密码。                                              |
-
-  - 如果 Spark 的 cluster manager 为 YARN，数据存储系统为 HDFS HA，则需添加如下配置项：
-
-    | **配置项**                                                   | **必选** | **说明**                                                     |
-    | ------------------------------------------------------------ | -------- | ------------------------------------------------------------ |
-    | type                                                         | 是       | 资源类型，取值为`spark`。                                    |
-    | spark.master                                                 | 是       | Spark 的 cluster manager。当前仅支持 YARN，所以取值为 `yarn`。 |
-    | spark.hadoop.yarn.resourcemanager.address                    | 是       | YARN ResourceManager 地址。                                  |
-    | spark.hadoop.fs.defaultFS                                    | 是       | Spark 使用的 HDFS 中 NameNode 节点地址。格式为：`hdfs://namenode_host:port`。 |
-    | spark.hadoop.dfs.nameservices                                | 是       | HDFS nameservice 的 ID。该配置项供 Spark 使用。              |
-    | spark.hadoop.dfs.ha.namenodes.[nameservice ID]               | 是       | HDFS NameNode 的 ID。您可配置多个 NameNode ID。多个 NameNode ID 之间要用逗号 (`,`) 隔开。该配置项供 Spark 使用。 |
-    | spark.hadoop.dfs.namenode.rpc-address.[nameservice ID].[name node ID] | 是       | 每个 HDFS NameNode 监听的 RPC 地址。注意需配置完全限定的 RPC 地址。该配置项供 Spark 使用。 |
-    | spark.hadoop.dfs.client.failover.proxy.provider              | 是       | HDFS 的 Java 类，其用来联系 Active 状态的 NameNode。该配置项供 Spark 使用。 |
-    | working_dir                                                  | 是       | ETL 作业目录，用于存放 ETL 作业生成的中间数据。例如：`hdfs://host: port/tmp/starrocks`。 |
-    | broker                                                       | 是       | Broker 名称。您可以使用 [SHOW BROKER](../Administration/SHOW_BROKER.md) 语句查看当前所有 Broker 的名称。如未添加过 Broker，可使用 [ALTER SYSTEM](../Administration/ALTER_SYSTEM.md) 语句添加 Broker。 |
-    | broker.username                           | 否       | 通过指定的 HDFS 用户去访问HDFS中的文件。如果 HDFS 文件只能由特定用户访问，则需要传入该参数，如果该文件是所有用户都可以访问，则不需要传入该参数。 |
-    | broker.password                           | 否       | HDFS 用户密码。                                              |
-    | broker.dfs.nameservices                                      | 是       | HDFS nameservice 的 ID。该配置项供 Broker 使用。             |
-    | broker.dfs.ha.namenodes. [nameservice ID]                    | 是       | HDFS NameNode 的 ID。您可配置多个 NameNode ID。多个 NameNode ID 之间要用逗号 (`,`) 隔开。该配置项供 Broker 使用。 |
-    | broker.dfs.namenode.rpc-address. [nameservice ID].[name node ID] | 是       | 每个 HDFS NameNode 监听的 RPC 地址。注意需配置完全限定的 RPC 地址。该配置项供 Broker 使用。 |
-    | broker.dfs.client.failover.proxy.provider                    | 是       | HDFS 的 Java 类，其用来联系 Active 状态的 NameNode。该配置项供 Broker 使用。 |
-
-- 如果使用无 Broker 进程的方式导入，则在创建资源时参数设置与使用Broker 进程的方式导入稍有差异，具体差异如下：
-
-  - 无需传入 `broker`。
-  - 如果您需要配置用户身份认证、NameNode 节点的 HA，则需要在 HDFS 集群中的 **hdfs-site.xml** 文件中配置参数，具体参数和说明，请参见 [broker_properties](../data-manipulation/BROKER_LOAD.md#hdfs)。并且将 **hdfs-site.xml** 文件放到每一个 FE 的 **$FE_HOME/conf** 下以及每个 BE 的 **$BE_HOME/conf** 下。
-
-> **说明**
->
-> - 使用无 Broker 进程的方式导入时，如果 HDFS 文件只能由特定用户访问，则您仍然需要传入 HDFS 用户名 `broker.name`和 HDFS 用户密码`broker.password`。
-> - 在以上几种情况中，如要添加除表格以外的配置项，可参考 [Spark Configuration](https://spark.apache.org/docs/latest/configuration.html) 和 [Running Spark on YARN](https://spark.apache.org/docs/latest/running-on-yarn.html)。
-
-#### Hive 资源
-
-如创建一个 Hive 资源，需添加如下配置项：
-
-| **配置项**          | **必选** | **说明**                  |
-| ------------------- | -------- | ------------------------- |
-| type                | 是       | 资源类型，取值为 `hive`。 |
-| hive.metastore.uris | 是       | Hive metastore 的 URI。   |
-
-#### Iceberg 资源
-
-如创建一个 Iceberg 资源，需添加如下配置项：
-
-| **配置项**                          | **必选** | **说明**                                                     |
-| ----------------------------------- | -------- | ------------------------------------------------------------ |
-| type                                | 是       | 资源类型，取值为 `iceberg`。                                 |
-| starrocks.catalog-type              | 是       | Iceberg 的 catalog 类型。StarRocks 2.3 以下版本仅支持 Hive catalog；StarRocks 2.3 及以上版本支持 Hive catalog 和 custom catalog。 如要使用 Hive catalog， 设置该参数为 `HIVE`。 如要使用 custom catalog，设置该参数为 `CUSTOM`。详细信息参见[创建 Iceberg 资源](../../../data_source/External_table.md#步骤一创建-iceberg-资源)。 |
-| iceberg.catalog.hive.metastore.uris | 是       | Hive metastore 的URI。                                       |
-
-#### Hudi 资源
-
-如创建一个 Hudi 资源，需添加如下配置项：
-
-| **配置项**          | **必选** | **说明**                  |
-| ------------------- | -------- | ------------------------- |
-| type                | 是       | 资源类型，取值为 `hudi`。 |
-| hive.metastore.uris | 是       | Hive metastore 的 URI。   |
-
-#### JDBC 资源
-
-如创建一个 JDBC 资源，需添加如下配置项：
-
-| **配置项**   | **必选** | **说明**                                                     |
-| ------------ | -------- | ------------------------------------------------------------ |
-| type         | 是       | 资源类型，取值为 `jdbc`。                                    |
-| user         | 是       | 登录到支持的 JDBC 数据库 （以下简称“目标数据库”）的用户名。  |
-| password     | 是       | 目标数据库的登录密码。                                       |
-| jdbc_uri     | 是       | 用于连接目标数据库的JDBC URI，需要满足目标数据库 URI 的语法。常见的目标数据库 URI，请参见 [MySQL](https://dev.mysql.com/doc/connector-j/en/connector-j-reference-jdbc-url-format.html)、[Oracle](https://docs.oracle.com/en/database/oracle/oracle-database/21/jjdbc/data-sources-and-URLs.html#GUID-6D8EFA50-AB0F-4A2B-88A0-45B4A67C361E)、[PostgreSQL](https://jdbc.postgresql.org/documentation/head/connect.html)、[SQL Server](https://docs.microsoft.com/en-us/sql/connect/jdbc/building-the-connection-url?view=sql-server-ver16) 官网文档。 |
-| driver_url   | 是       | 用于下载 JDBC 驱动程序 JAR 包的 URL，支持使用 HTTP 协议 或者 file 协议。例如 `https://repo1.maven.org/maven2/org/postgresql/postgresql/42.3.3/postgresql-42.3.3.jar`， `file:///home/disk1/postgresql-42.3.3.jar`。 |
-| driver_class | 是       | 目标数据库使用的 JDBC 驱动程序的类名称。常见的类名称如下： <ul><li>MySQL：com.mysql.jdbc.Driver（MySQL 5.x 及以下版本）和com.mysql.cj.jdbc.Driver （MySQL 6.x 及以上版本）</li><li>SQL Server：com.microsoft.sqlserver.jdbc.SQLServerDriver </li><li>Oracle： oracle.jdbc.driver.OracleDriver </li><li>PostgreSQL：org.postgresql.Driver</li></ul> |
-
-## 示例
-
-示例一： 当使用 YARN 作为 Spark 的 cluster manager，HDFS 来存储数据时，创建一个名为`spark0`的 Spark 资源，语句如下：
-
-```SQL
-CREATE EXTERNAL RESOURCE "spark0"
-PROPERTIES (
-    "type" = "spark",
-    "spark.master" = "yarn",
-    "spark.submit.deployMode" = "cluster",
-    "spark.executor.memory" = "1g",
-    "spark.yarn.queue" = "queue0",
-    "spark.hadoop.yarn.resourcemanager.address" = "resourcemanager_host:8032",
-    "spark.hadoop.fs.defaultFS" = "hdfs://namenode_host:9000",
-    "working_dir" = "hdfs://namenode_host:9000/tmp/starrocks",
-    "broker" = "broker0",
-    "broker.username" = "user0",
-    "broker.password" = "password0"
-);
-```
-
-示例二：当使用 YARN HA 作为 Spark 的 cluster manager，HDFS 来存储数据时，创建一个名为`spark1`的 Spark 资源，语句如下：
-
-```SQL
-CREATE EXTERNAL RESOURCE "spark1"
-PROPERTIES (
-    "type" = "spark",
-    "spark.master" = "yarn",
-    "spark.submit.deployMode" = "cluster",
-    "spark.hadoop.yarn.resourcemanager.ha.enabled" = "true",
-    "spark.hadoop.yarn.resourcemanager.ha.rm-ids" = "rm1,rm2",
-    "spark.hadoop.yarn.resourcemanager.hostname.rm1" = "host1",
-    "spark.hadoop.yarn.resourcemanager.hostname.rm2" = "host2",
-    "spark.hadoop.fs.defaultFS" = "hdfs://namenode_host:9000",
-    "working_dir" = "hdfs://namenode_host:9000/tmp/starrocks",
-    "broker" = "broker1"
-);
-```
-
-示例三：当使用 YARN 作为 Spark 的 cluster manager，HDFS HA 来存储数据时，创建一个名为`spark2`的 Spark 资源，语句如下：
-
-```SQL
-CREATE EXTERNAL RESOURCE "spark2"
-PROPERTIES (
-    "type" = "spark", 
-    "spark.master" = "yarn",
-    "spark.hadoop.yarn.resourcemanager.address" = "resourcemanager_host:8032",
-    "spark.hadoop.fs.defaultFS" = "hdfs://myha",
-    "spark.hadoop.dfs.nameservices" = "myha",
-    "spark.hadoop.dfs.ha.namenodes.myha" = "mynamenode1,mynamenode2",
-    "spark.hadoop.dfs.namenode.rpc-address.myha.mynamenode1" = "nn1_host:rpc_port",
-    "spark.hadoop.dfs.namenode.rpc-address.myha.mynamenode2" = "nn2_host:rpc_port",
-    "spark.hadoop.dfs.client.failover.proxy.provider" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider",
-    "working_dir" = "hdfs://myha/tmp/starrocks",
-    "broker" = "broker2",
-    "broker.dfs.nameservices" = "myha",
-    "broker.dfs.ha.namenodes.myha" = "mynamenode1,mynamenode2",
-    "broker.dfs.namenode.rpc-address.myha.mynamenode1" = "nn1_host:rpc_port",
-    "broker.dfs.namenode.rpc-address.myha.mynamenode2" = "nn2_host:rpc_port",
-    "broker.dfs.client.failover.proxy.provider" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
-);
-```
-
-示例四：创建一个名为`hive0`的 Hive 资源。
-
-```SQL
-CREATE EXTERNAL RESOURCE "hive0"
-PROPERTIES (
-  "type" = "hive",
-  "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083"
-);
-```
-
-示例五：创建一个名为`iceberg0`的 Iceberg 资源。
-
-```SQL
-CREATE EXTERNAL RESOURCE "iceberg0" 
-PROPERTIES ( 
-   "type" = "iceberg", 
-   "starrocks.catalog-type"="HIVE", 
-   "iceberg.catalog.hive.metastore.uris"="thrift://xx.xx.xx.xx:9083" 
-);
-```
-
-示例六：创建一个名为`hudi0`的 Hudi 资源。
-
-```SQL
-CREATE EXTERNAL RESOURCE "hudi0" 
-PROPERTIES ( 
-    "type" = "hudi", 
-    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083"
-);
-```
-
-示例七：创建一个名为`jdbc0`的 JDBC 资源。
-
-```SQL
-CREATE EXTERNAL RESOURCE jdbc0
-PROPERTIES (
-    "type"="jdbc",
-    "user"="postgres",
-    "password"="changeme",
-    "jdbc_uri"="jdbc:postgresql://127.0.0.1:5432/jdbc_test",
-    "driver_url"="https://repo1.maven.org/maven2/org/postgresql/postgresql/42.3.3/postgresql-42.3.3.jar",
-    "driver_class"="org.postgresql.Driver"
-);
-```
-
-## 相关操作
-
-- 如要修改资源属性，参见 [ALTER RESOURCE](../data-definition/ALTER_RESOURCE.md)。
-- 如要删除资源，参见 [DROP RESOURCE](../data-definition/DROP_RESOURCE.md)。
-- 如要使用 Spark 资源进行 Spark Load，参见 [Spark Load](../../../loading/SparkLoad.md)。
-- 如要引用 Hive、Iceberg、Hudi 和 JDBC 资源创建外部表，参见[外部表](../../../data_source/External_table.md)。
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_TABLE.md b/docs/zh/sql-reference/sql-statements/data-definition/CREATE_TABLE.md
deleted file mode 100644
index c5b03fec778e69..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_TABLE.md
+++ /dev/null
@@ -1,1109 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CREATE TABLE
-
-## 功能
-
-该语句用于创建表。
-
-:::tip
-该操作需要有在对应数据库内的建表权限 (CREATE TABLE)。
-:::
-
-## 语法
-
-```sql
-CREATE [TEMPORARY] [EXTERNAL] TABLE [IF NOT EXISTS] [database.]table_name
-(column_definition1[, column_definition2, ...]
-[, index_definition1[, index_definition2, ...]])
-[ENGINE = [olap|mysql|elasticsearch|hive|iceberg|hudi|jdbc]]
-[key_desc]
-[COMMENT "table comment"]
-[partition_desc]
-[distribution_desc]
-[rollup_index]
-[ORDER BY (column_definition1,...)]
-[PROPERTIES ("key"="value", ...)]
-[BROKER PROPERTIES ("key"="value", ...)]
-```
-
-## 参数说明
-
-:::tip
-
-- 关于建表时对于表名、列名、分区名、索引名的命名要求，参见[系统限制](../../../reference/System_limit.md)。
-
-- 在指定数据库名、表名和列名等变量时，如果使用了保留关键字，必须使用反引号 (`) 包裹，否则可能会产生报错。有关 StarRocks 的保留关键字列表，请参见[关键字](../keywords.md#保留关键字)。
-
-:::
-
-### column_definition
-
-语法：
-
-```sql
-col_name col_type [agg_type] [NULL | NOT NULL] [DEFAULT "default_value"] [AUTO_INCREMENT] [AS generation_expr]
-```
-
-说明：
-
-**col_name**：列名称。
-
-注意，在一般情况下，不能直接创建以以 `__op` 或 `__row` 开头命名的列，因为此类列名被 StarRocks 保留用于特殊目的，创建这样的列可能导致未知行为。如需创建这样的列，必须将 FE 动态参数 [`allow_system_reserved_names`](../../../administration/management/FE_configuration.md#allow_system_reserved_names) 设置为 `TRUE`。
-
-**col_type**：列数据类型
-
-支持的列类型以及取值范围等信息如下：
-
-- TINYINT（1字节）
-  范围：-2^7 + 1 ~ 2^7 - 1
-
-- SMALLINT（2字节）
-  范围：-2^15 + 1 ~ 2^15 - 1
-
-- INT（4字节）
-  范围：-2^31 + 1 ~ 2^31 - 1
-
-- BIGINT（8字节）
-  范围：-2^63 + 1 ~ 2^63 - 1
-
-- LARGEINT（16字节）
-  范围：-2^127 + 1 ~ 2^127 - 1
-
-- FLOAT（4字节）
-  支持科学计数法。
-
-- DOUBLE（8字节）
-  支持科学计数法。
-
-- DECIMAL[(precision, scale)] (16字节)
-  保证精度的小数类型。默认是 DECIMAL(10, 0)
-    precision: 1 ~ 38
-    scale: 0 ~ precision
-  其中整数部分为：precision - scale
-  不支持科学计数法。
-
-- DATE（3字节）
-  范围：0000-01-01 ~ 9999-12-31
-
-- DATETIME（8字节）
-  范围：0000-01-01 00:00:00 ~ 9999-12-31 23:59:59
-
-- CHAR[(length)]
-
-  定长字符串。长度范围：1 ~ 255。默认为 1。
-
-- VARCHAR[(length)]
-
-  变长字符串。单位：字节，默认取值为 `1`。
-  - StarRocks 2.1.0 之前的版本，`length` 的取值范围为 1~65533。
-  - 【公测中】自 StarRocks 2.1.0 版本开始，`length` 的取值范围为 1~1048576。
-
-- HLL (1~16385个字节)
-
-  HLL 列类型，不需要指定长度和默认值，长度根据数据的聚合程度系统内控制，并且 HLL 列只能通过配套的 [hll_union_agg](../../sql-functions/aggregate-functions/hll_union_agg.md)、[hll_cardinality](../../sql-functions/scalar-functions/hll_cardinality.md)、[hll_hash](../../sql-functions/scalar-functions/hll_hash.md)进行查询或使用。
-
-- BITMAP
-  BITMAP 列类型，不需要指定长度和默认值。表示整型的集合，元素个数最大支持到 2^64 - 1。
-
-- ARRAY
-  支持在一个数组中嵌套子数组，最多可嵌套 14 层。您必须使用尖括号（ < 和 > ）来声明 ARRAY 的元素类型，如 ARRAY < INT >。目前不支持将数组中的元素声明为 [Fast Decimal](../../data-types/numeric/DECIMAL.md) 类型。
-
-**agg_type**：聚合类型，如果不指定，则该列为 key 列。否则，该列为 value 列。
-
-```plain
-支持的聚合类型如下：
-
-- SUM、MAX、MIN、REPLACE
-
-- HLL_UNION（仅用于 HLL列，为 HLL 独有的聚合方式)。
-
-- BITMAP_UNION（仅用于 BITMAP 列，为 BITMAP 独有的聚合方式)。
-
-- REPLACE_IF_NOT_NULL：这个聚合类型的含义是当且仅当新导入数据是非 NULL 值时会发生替换行为。如果新导入的数据是 NULL，那么 StarRocks 仍然会保留原值。
-```
-
-注意：
-
-1. BITMAP_UNION 聚合类型列在导入时的原始数据类型必须是 `TINYINT, SMALLINT, INT, BIGINT`。
-2. 如果在建表时 `REPLACE_IF_NOT_NULL` 列指定了 NOT NULL，那么 StarRocks 仍然会将其转化 NULL，不会向用户报错。用户可以借助这个类型完成「部分列导入」的功能。
-  该类型只对聚合表有用 (`key_desc` 的 `type` 为 `AGGREGATE KEY`)。自 3.1.9 起，`REPLACE_IF_NOT_NULL` 新增支持 BITMAP 类型的列。
-
-**NULL | NOT NULL**：列数据是否允许为 `NULL`。其中明细表、聚合表和更新表中所有列都默认指定 `NULL`。主键表的指标列默认指定 `NULL`，维度列默认指定 `NOT NULL`。如源数据文件中存在 `NULL` 值，可以用 `\N` 来表示，导入时 StarRocks 会将其解析为 `NULL`。
-
-**DEFAULT "default_value"**：列数据的默认值。导入数据时，如果该列对应的源数据文件中的字段为空，则自动填充 `DEFAULT` 关键字中指定的默认值。支持以下三种指定方式：
-
-- **DEFAULT current_timestamp**：默认值为当前时间。参见 [current_timestamp()](../../sql-functions/date-time-functions/current_timestamp.md) 。
-- **DEFAULT `<默认值>`**：默认值为指定类型的值。例如，列类型为 VARCHAR，即可指定默认值为 `DEFAULT "beijing"`。当前不支持指定 ARRAY、BITMAP、JSON、HLL 和 BOOLEAN 类型为默认值。
-- **DEFAULT (`<表达式>`)**：默认值为指定函数返回的结果。目前仅支持 [uuid()](../../sql-functions/utility-functions/uuid.md) 和 [uuid_numeric()](../../sql-functions/utility-functions/uuid_numeric.md) 表达式。
-
-**AUTO_INCREMENT**：指定自增列。自增列的数据类型只支持 BIGINT，自增 ID 从 1 开始增加，自增步长为 1。有关自增列的详细说明，请参见 [AUTO_INCREMENT](../auto_increment.md)。自 v3.0，StarRocks 支持该功能。
-
-**AS generation_expr**：指定生成列和其使用的表达式。[生成列](../generated_columns.md)用于预先计算并存储表达式的结果，可以加速包含复杂表达式的查询。自 v3.1，StarRocks 支持该功能。
-
-### index_definition
-
-创建 bitmap 索引的语法如下。有关参数说明和使用限制，请参见 [Bitmap 索引](../../../table_design/indexes/Bitmap_index.md#创建索引)。
-
-```sql
-INDEX index_name (col_name[, col_name, ...]) [USING BITMAP] [COMMENT '']
-```
-
-### ENGINE 类型
-
-默认为 `olap`，表示创建的是 StarRocks 内部表。
-
-可选值：`mysql`、`elasticsearch`、`hive`、`jdbc` (2.3 及以后)、`iceberg`、`hudi`（2.2 及以后）。如果指定了可选值，则创建的是对应类型的外部表 (external table)，在建表时需要使用 CREATE EXTERNAL TABLE。更多信息，参见[外部表](../../../data_source/External_table.md)。
-
-**从 3.0 版本起，对于查询 Hive、Iceberg、Hudi 和 JDBC 数据源的场景，推荐使用 Catalog 直接查询，不再推荐外部表的方式。具体参见 [Hive catalog](../../../data_source/catalog/hive_catalog.md)、[Iceberg catalog](../../../data_source/catalog/iceberg_catalog.md)、[Hudi catalog](../../../data_source/catalog/hudi_catalog.md) 和 [JDBC catalog](../../../data_source/catalog/jdbc_catalog.md)。**
-
-**从 3.1 版本起，支持直接在 Iceberg catalog 内创建表（当前仅支持 Parquet 格式的表），您可以通过 [INSERT INTO](../data-manipulation/INSERT.md) 把数据插入到 Iceberg 表中。参见 [创建 Iceberg 表](../../../data_source/catalog/iceberg_catalog.md#创建-iceberg-表)。**
-
-**从 3.2 版本起，支持直接在 Hive Catalog 内创建 Parquet 格式的表，并支持通过 [INSERT INTO](../data-manipulation/INSERT.md) 把数据插入到 Parquet 格式的 Hive 表中。从 3.3 版本起，支持直接在 Hive Catalog 中创建 ORC 及 Textfile 格式的表，并支持通过 [INSERT INTO](../data-manipulation/INSERT.md) 把数据插入到 ORC 及 Textfile 格式的 Hive 表中。参见[创建 Hive 表](../../../data_source/catalog/hive_catalog.md#创建-hive-表)和[向 Hive 表中插入数据](../../../data_source/catalog/hive_catalog.md#向-hive-表中插入数据)。**
-
-1. 如果是 mysql，则需要在 properties 提供以下信息：
-
-    ```sql
-    PROPERTIES (
-        "host" = "mysql_server_host",
-        "port" = "mysql_server_port",
-        "user" = "your_user_name",
-        "password" = "your_password",
-        "database" = "database_name",
-        "table" = "table_name"
-    )
-    ```
-
-    注意：
-    "table" 条目中的 "table_name" 是 MySQL 中的真实表名。
-    而 CREATE TABLE 语句中的 table_name 是该 MySQL 表在 StarRocks 中的名字，可以不同。
-
-    在 StarRocks 创建 MySQL 表的目的是可以通过 StarRocks 访问 MySQL 数据库。
-    而 StarRocks 本身并不维护、存储任何 MySQL 数据。
-
-2. 如果是 elasticsearch，则需要在 properties 提供以下信息：
-
-    ```sql
-    PROPERTIES (
-        "hosts" = "http://192.168.0.1:8200,http://192.168.0.2:8200",
-        "user" = "root",
-        "password" = "root",
-        "index" = "tindex",
-        "type" = "doc"
-    )
-    ```
-
-    其中 `hosts` 为 Elasticsearch 集群连接地址，可指定一个或者多个，`user 和 password` 为开启 basic 认证的 Elasticsearch 集群的用户名/密码，`index` 是 StarRocks 中的表对应的 Elasticsearch 的 index 名字，可以是 alias，`type` 指定 index 的类型，默认是 `doc`。
-
-3. 如果是 hive，则需要在 properties 提供以下信息：
-
-    ```sql
-    PROPERTIES (
-        "database" = "hive_db_name",
-        "table" = "hive_table_name",
-        "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083"
-    )
-    ```
-
-    其中 `database` 是 Hive 表对应的库名字，`table` 是 hive 表的名字，`hive.metastore.uris` 是 Hive metastore 服务地址。
-
-4. 如果是 jdbc，则需要在 properties 提供以下信息：
-
-    ```sql
-    PROPERTIES (
-        "resource"="jdbc0",
-        "table"="dest_tbl"
-    )
-    ```
-
-    其中 `resource` 是所使用 JDBC 资源的名称。`table` 是目标数据库表名。
-
-5. 如果是 iceberg，则需要在 properties 提供以下信息：
-
-    ```sql
-    PROPERTIES (
-        "resource" = "iceberg0", 
-        "database" = "iceberg", 
-        "table" = "iceberg_table"
-    )
-    ```
-
-    其中 `resource` 是引用的 Iceberg 资源的名称。`database` 是 Iceberg 表所属的数据库名称。`table` Iceberg 表名称。
-6. 如果是 hudi，则需要在 properties 提供以下信息：
-
-    ```sql
-    PROPERTIES (
-        "resource" = "hudi0", 
-        "database" = "hudi", 
-        "table" = "hudi_table" 
-    )
-    ```
-
-    其中 `resource` 是 Hudi 资源的名称。`database` 是 Hudi 表所属的数据库名称。`table` Hudi 表名称。
-
-### key_desc
-
-语法：
-
-```sql
-`key_type(k1[,k2 ...])`
-```
-
-> 说明
->
-数据按照指定的 key 列进行排序，且根据不同的 `key_type` 具有不同特性。
-`key_type` 支持以下类型：
-
-- AGGREGATE KEY: key 列相同的记录，value 列按照指定的聚合类型进行聚合，适合报表、多维分析等业务场景。
-- UNIQUE KEY/PRIMARY KEY: key 列相同的记录，value 列按导入顺序进行覆盖，适合按 key 列进行增删改查的点查询 (point query) 业务。
-- DUPLICATE KEY: key 列相同的记录，同时存在于 StarRocks 中，适合存储明细数据或者数据无聚合特性的业务场景。
-
-默认为 DUPLICATE KEY，数据按 key 列做排序。
-
-除 AGGREGATE KEY 外，其他 `key_type` 在建表时，`value` 列不需要指定聚合类型 (agg_type)。
-
-### COMMENT
-
-表的注释，可选。注意建表时 COMMENT 必须在 `key_desc` 之后，否则建表失败。
-
-如果后续想修改表的注释，可以使用 `ALTER TABLE <table_name> COMMENT = "new table comment"`（3.1 版本开始支持）。
-
-### partition_desc
-
-支持三种分区方式，[表达式分区](../../../table_design/expression_partitioning.md)（推荐）、[Range 分区](../../../table_design/Data_distribution.md#range-分区) 和 [List 分区](../../../table_design/list_partitioning.md)。
-
-使用 Range 分区时，提供三种创建方式，其语法、说明和示例如下：
-
-- **动态创建分区**
-
-    [动态分区](../../../table_design/dynamic_partitioning.md)提供了分区生命周期管理（TTL）。StarRocks 会自动提前创建新的分区，并删除过期的分区，以确保数据时效性。要启用这个功能，您可以在创建表时配置与动态分区相关的属性。
-
-- **手动创建分区**
-
-  - 仅指定各个分区的上界
-
-    语法：
-
-    ```sql
-    PARTITION BY RANGE ( <partitioning_column1> [, <partitioning_column2>, ... ] )
-    PARTITION <partition1_name> VALUES LESS THAN ("<upper_bound_for_partitioning_column1>" [ , "<upper_bound_for_partitioning_column2>", ... ] )
-    [ ,
-    PARTITION <partition2_name> VALUES LESS THAN ("<upper_bound_for_partitioning_column1>" [ , "<upper_bound_for_partitioning_column2>", ... ] )
-    , ... ] 
-    )
-    ```
-
-    说明：
-
-    使用指定的 key 列和指定的数值范围进行分区。
-
-    - 分区名称的命名要求，参见[系统限制](../../../reference/System_limit.md)。
-    - 3.3.0 之前，仅支持以下类型的列作为 Range 分区列：`TINYINT, SMALLINT, INT, BIGINT, LARGEINT, DATE, DATETIME`。自 3.3.0 起，支持三个特定时间函数为 Range 分区列。具体使用方式，参见[数据分布](../../../table_design/Data_distribution.md#手动创建分区)。
-    - 分区为左闭右开区间，首个分区的左边界为最小值。
-    - NULL 值只会存放在包含 **最小值** 的分区中。当包含最小值的分区被删除后，NULL 值将无法导入。
-    - 可以指定一列或多列作为分区列。如果分区值缺省，则会默认填充最小值。
-    - 当只指定一个列作为分区列时，您可以设置最后一个分区的分区列的上界为 MAXVALUE。
-
-    注意：
-
-    1. 分区一般用于时间维度的数据管理。
-    2. 有数据回溯需求的，可以考虑首个分区为空分区，以便后续增加分区。
-
-    示例：
-
-    1. 分区列 `pay_dt` 为 DATE 类型，并且按天分区。
-
-        ```sql
-        PARTITION BY RANGE(pay_dt)
-        (
-            PARTITION p1 VALUES LESS THAN ("2021-01-02"),
-            PARTITION p2 VALUES LESS THAN ("2021-01-03"),
-            PARTITION p3 VALUES LESS THAN ("2021-01-04")
-        )
-        ```
-
-    2. 分区列 `pay_dt` 为 INT 类型，并且按天分区。
-
-        ```sql
-        PARTITION BY RANGE(pay_dt)
-        (
-            PARTITION p1 VALUES LESS THAN ("20210102"),
-            PARTITION p2 VALUES LESS THAN ("20210103"),
-            PARTITION p3 VALUES LESS THAN ("20210104")
-        )
-        ```
-
-    3. 分区列 `pay_dt` 为 INT 类型，并且按天分区，最后一个分区没有上界。
-
-        ```sql
-        PARTITION BY RANGE(pay_dt)
-        (
-            PARTITION p1 VALUES LESS THAN ("20210102"),
-            PARTITION p2 VALUES LESS THAN ("20210103"),
-            PARTITION p3 VALUES LESS THAN MAXVALUE
-        )
-        ```
-
-  - 指定各个分区的上界和下界
-
-    语法：
-
-    ```sql
-    PARTITION BY RANGE ( <partitioning_column1> [, <partitioning_column2>, ... ] )
-    (
-        PARTITION <partition_name1> VALUES [( "<lower_bound_for_partitioning_column1>" [ , "<lower_bound_for_partitioning_column2>", ... ] ), ( "<upper_bound_for_partitioning_column1>" [ , "<upper_bound_for_partitioning_column2>", ... ] ) ) 
-        [,
-        PARTITION <partition_name2> VALUES [( "<lower_bound_for_partitioning_column1>" [ , "<lower_bound_for_partitioning_column2>", ... ] ), ( "<upper_bound_for_partitioning_column1>" [ , "<upper_bound_for_partitioning_column2>", ... ] ) ) 
-        , ...]
-    )
-    ```
-
-    说明：
-
-    - 与仅指定分区下界相比，指定各个分区的上界和下界相对灵活，并且您可以自定义左右区间。
-    - 其他与 LESS THAN 保持同步。
-    - 当只指定一个列作为分区列时，您可以设置最后一个分区的分区列的上界为 MAXVALUE。
-
-    示例：
-
-    1. 分区列 `pay_dt` 为 DATE 类型，并且按月分区。
-
-        ```sql
-        PARTITION BY RANGE (pay_dt)
-        (
-            PARTITION p202101 VALUES [("2021-01-01"), ("2021-02-01")),
-            PARTITION p202102 VALUES [("2021-02-01"), ("2021-03-01")),
-            PARTITION p202103 VALUES [("2021-03-01"), ("2021-04-01"))
-        )
-        ```
-
-    2. 分区列 `pay_dt` 为 INT 类型，并且按月分区。
-
-        ```sql
-        PARTITION BY RANGE (pay_dt)
-        (
-            PARTITION p202101 VALUES [("20210101"), ("20210201")),
-            PARTITION p202102 VALUES [("20210201"), ("20210301")),
-            PARTITION p202103 VALUES [("20210301"), ("20210401"))
-        )
-        ```
-
-    3. 分区列 `pay_dt` 为 INT 类型，并且按月分区，最后一个分区没有上界。
-
-        ```sql
-        PARTITION BY RANGE (pay_dt)
-        (
-            PARTITION p202101 VALUES [("20210101"), ("20210201")),
-            PARTITION p202102 VALUES [("20210201"), ("20210301")),
-            PARTITION p202103 VALUES [("20210301"), (MAXVALUE))
-        )
-        ```
-
-- **批量创建分区**
-
-  语法：
-
-  - 如果分区列为时间类型
-
-    ```sql
-    PARTITION BY RANGE (<partitioning_column>) (
-        START ("<start_date>") END ("<end_date>") EVERY (INTERVAL <N> <time_unit>)
-    )
-    ```
-
-    - 如果分区列为整数类型
-
-    ```sql
-    PARTITION BY RANGE (<partitioning_column>) (
-        START ("<start_integer>") END ("<end_integer>") EVERY (<partitioning_granularity>)
-    )
-    ```
-
-    说明：
-    用户可以通过给出一个 START 值、一个 END 值以及一个定义分区增量值的 EVERY 子句批量产生分区。
-
-    - 3.3.0 之前，仅支持以下类型的列作为 Range 分区列：`TINYINT, SMALLINT, INT, BIGINT, LARGEINT, DATE, DATETIME`。自 3.3.0 起，支持三个特定时间函数为 Range 分区列。具体使用方式，参见[数据分布](../../../table_design/Data_distribution.md#手动创建分区)。
-    - 当分区列为日期类型时，需要指定 `INTERVAL` 关键字来表示日期间隔。目前日期间隔支持 hour (v3.0）、day、week、month、year，分区的命名规则同动态分区一样。
-    - 当分区列为整数类型时，START 值、END 值仍需要用双引号包裹。
-    - 仅支持指定一列作为分区列。
-
-    更多信息，请参见[批量创建分区](../../../table_design/Data_distribution.md#range-分区)。
-
-    示例：
-
-    1. 分区列 `pay_dt` 为 DATE 类型，并且按年分区。
-
-        ```sql
-        PARTITION BY RANGE (pay_dt) (
-            START ("2018-01-01") END ("2023-01-01") EVERY (INTERVAL 1 YEAR)
-        )
-        ```
-
-    2. 分区列 `pay_dt` 为 INT 类型，并且按年分区。
-
-        ```sql
-        PARTITION BY RANGE (pay_dt) (
-            START ("2018") END ("2023") EVERY (1)
-        )
-        ```
-
-### distribution_desc
-
-支持随机分桶（Random bucketing）和哈希分桶（Hash bucketing）。如果不指定分桶信息，则 StarRocks 默认使用随机分桶且自动设置分桶数量。
-
-- 随机分桶（自 v3.1）
-
-  对每个分区的数据，StarRocks 将数据随机地分布在所有分桶中，而不受到特定列值的影响。并且如果选择由系统设置分桶数量，则您无需设置分桶信息。如果选择手动指定分桶数量，则语法如下：
-
-  ```SQL
-  DISTRIBUTED BY RANDOM BUCKETS <num>
-  ```
-
-  不过值得注意的是，如果查询海量数据且查询时经常使用一些列会作为条件列，随机分桶提供的查询性能可能不够理想。在该场景下建议您使用哈希分桶，当查询时经常使用这些列作为条件列时，只需要扫描和计算查询命中的少量分桶，则可以显著提高查询性能。
-
-  **注意事项**
-
-  - 不支持主键表、更新表和聚合表。
-  - 不支持指定 [Colocation Group](../../../using_starrocks/Colocate_join.md)。
-  - 不支持 [Spark Load](../../../loading/SparkLoad.md)。
-  - 自 2.5.7 版本起，建表时**无需手动指定分桶数量**，StarRocks 自动设置分桶数量。如果您需要手动设置分桶数量，请参见[设置分桶数量](../../../table_design/Data_distribution.md#设置分桶数量)。
-
-  更多随机分桶的信息，请参见[随机分桶](../../../table_design/Data_distribution.md#随机分桶自-v31)。
-
-- 哈希分桶
-
-  语法：
-
-  ```SQL
-  DISTRIBUTED BY HASH (k1[,k2 ...]) [BUCKETS num]
-  ```
-
-  对每个分区的数据，StarRocks 会根据分桶键和分桶数量进行哈希分桶。
-
-  对于分桶键的选择，如果列是高基数且经常作为查询条件，则优先选择其为分桶键，进行哈希分桶。
-  如果不存在同时满足两个条件的列，则需要根据查询进行判断。
-  - 如果查询比较复杂，则建议选择高基数的列为分桶键，保证数据在各个分桶中尽量均衡，提高集群资源利用率。
-  - 如果查询比较简单，则建议选择经常作为查询条件的列为分桶键，提高查询效率。
-  并且，如果数据倾斜情况严重，您还可以使用多个列作为数据的分桶键，但是建议不超过 3 个列。
-  更多选择分桶键的信息，请参见[选择分桶键](../../../table_design/Data_distribution.md#哈希分桶).
-
-  **注意事项**
-
-  - **建表时，必须指定分桶键**。
-  - 作为分桶键的列，该列的值不支持更新。
-  - 分桶键指定后不支持修改。
-  - 自 2.5.7 版本起，建表时**无需手动指定分桶数量**，StarRocks 自动设置分桶数量。如果您需要手动设置分桶数量，请参见[设置分桶数量](../../../table_design/Data_distribution.md#设置分桶数量)。
-
-### ORDER BY
-
-自 3.0 版本起，主键表支持使用 `ORDER BY` 定义排序键，自 3.3 版本起，明细表、聚合表和更新表支持使用 `ORDER BY` 定义排序键。
-
-排序键的更多说明，请参见[排序键和前缀索引](../../../table_design/indexes/Prefix_index_sort_key.md)。
-
-### TEMPORARY
-
-创建临时表。从 v3.3.1 版本开始，StarRocks 支持在 Default Catalog 中创建临时表。更多信息，请参见 [临时表](../../../table_design/StarRocks_table_design.md#临时表)。
-
-:::note
-创建临时表时，必须将 `ENGINE` 设置为 `olap`。
-:::
-
-### PROPERTIES
-
-#### 设置数据的初始存储介质、自动降冷时间和副本数
-
-如果 ENGINE 类型为 OLAP，可以在属性 `properties` 中设置该表数据的初始存储介质（storage_medium）、自动降冷时间（storage_cooldown_time）或者时间间隔（storage_cooldown_ttl）和副本数（replication_num）。
-
-属性生效范围：当表为单分区表时，以上属性为表的属性。当表划分成多个分区时，以上属性属于每一个分区。并且如果希望不同分区有不同属性，则建表后可以执行 [ALTER TABLE ... ADD PARTITION 或 ALTER TABLE ... MODIFY PARTITION](../data-definition/ALTER_TABLE.md)。
-
-**设置数据的初始存储介质、自动降冷时间**
-
-```sql
-PROPERTIES (
-    "storage_medium" = "[SSD|HDD]",
-    { "storage_cooldown_ttl" = "<num> { YEAR | MONTH | DAY | HOUR } "
-    | "storage_cooldown_time" = "yyyy-MM-dd HH:mm:ss" }
-)
-```
-
-- `storage_medium`：数据初始存储介质，取值为 `SSD` 或 `HDD`。显式指定该参数时，请确保该值与 BE 静态参数 `storage_root_path` 中指定的集群存储介质相匹配。
-  
-  当 FE 配置项 `enable_strict_storage_medium_check` 为 `true` 时，表示在建表时会严格校验 BE 上的存储介质。如果建表语句中的存储介质和 BE 的存储类型不一致，建表语句会报错 `Failed to find enough hosts with storage medium [SSD|HDD] at all backends...`。当 `enable_strict_storage_medium_check` 为 `false` 时，可以忽略该报错强行建表，但是后续可能会导致集群磁盘空间分布出现不均衡。
-
-  从 2.3.6，2.4.2，2.5.1，3.0 及以上版本开始，支持在未显式指定该参数的情况下，由系统自动推导存储介质。
-
-  - 在以下场景中，系统推导该参数为 SSD：
-    - BE 上报的存储路径 (`storage_root_path`) 都是 SSD。
-    - BE 上报的存储路径包含 SSD 和 HDD。并且从 2.3.10，2.4.5，2.5.4，3.0 及以上版本开始，如果 BE 上报的存储路径两者都有且 FE 配置文件中设置了 `storage_cooldown_second`。
-  - 在以下场景中，系统推导该参数为 HDD：
-    - BE 上报的存储路径都是 HDD。
-    - 从 2.3.10，2.4.5，2.5.4，3.0 及以上版本开始，如果 BE 上报的存储路径两者都有且 FE 配置文件中未设置 `storage_cooldown_second`。
-
-- `storage_cooldown_ttl` 或 `storage_cooldown_time`：数据自动降冷的时间间隔或者时间点。数据自动降冷，即数据自动从 SSD 介质迁移到 HDD 介质。只在数据初始存储介质为 SSD 时生效。
-
-  **参数说明**
-
-  - `storage_cooldown_ttl`：该表分区自动降冷**时间间隔**。如果您需要保留最近几个分区在 SSD，其它较早的分区经过一定时间间隔自动降冷至 HDD，则您可以使用该参数，各个分区的自动降冷时间点为该参数值 + 该分区的时间上界。
-  
-      取值为 `<num> YEAR`，`<num> MONTH`，`<num> DAY` 或 `<num> HOUR`。`<num>` 为非负整数。默认值为空，表示该表分区不进行自动降冷。
-  
-      例如建表时指定 `"storage_cooldown_ttl"="1 DAY"`，建表后存在分区 `p20230801` ，其范围为 `[2023-08-01 00:00:00,2023-08-02 00:00:00)`，则该分区的自动降冷时间点是 `2023-08-03 00:00:00`，即 `2023-08-02 00:00:00 + 1 DAY`。如果建表时指定 `"storage_cooldown_ttl"="0 DAY"`，则该分区自动降冷时间点是 `2023-08-02 00:00:00`。
-
-  - `storage_cooldown_time`：该表自动降冷**时间点**（绝对时间）。数据在该时间点之后数据从 SSD 自动降冷到 HDD，设置的时间必须大于当前时间。取值格式为："yyyy-MM-dd HH:mm:ss"。如果需要不同分区具有不同自动降冷时间点，则需要执行 [ALTER TABLE ... ADD PARTITION 或 ALTER TABLE ... MODIFY PARTITION](../data-definition/ALTER_TABLE.md) 手动指定。
-
-  **使用说明**
-
-  - 目前 StarRocks 提供如下数据自动降冷的相关参数，对比如下：
-    - `storage_cooldown_ttl`：表的属性，指定该表中分区自动降冷时间间隔，由系统自动降冷表中到达时间点（时间间隔+分区时间上界）的分区。并且表按照分区粒度自动降冷，更加灵活。
-    - `storage_cooldown_time`：表的属性，指定该表的自动降冷时间点（绝对时间）。建表后也可以为不同分区配置不同时间点。
-    - `storage_cooldown_second`：FE 静态参数，指定集群范围内所有表的自动降冷时延。
-  - 表属性 `storage_cooldown_ttl` 或 `storage_cooldown_time` 比 FE 静态参数 `storage_cooldown_second` 优先级高。
-  - 配置以上参数时，必须指定 `"storage_medium = "SSD"`。
-  - 不配置以上参数时，则不进行自动降冷。
-  - 执行 `SHOW PARTITIONS FROM <table_name>` 查看各个分区的自动降冷时间点。
-
-  **限制**
-  - 不支持表达式分区和 List 分区。
-  - 不支持分区列为非日期类型。
-  - 不支持多个分区列。
-  - 不支持主键表。
-
-**设置分区 Tablet 副本数**
-
-`replication_num`：分区 Tablet 副本数。默认为 3。
-
-```sql
-PROPERTIES (
-    "replication_num" = "<num>"
-)
-```
-
-#### 创建表时为列添加 bloom filter 索引
-
-如果 Engine 类型为 olap, 可以指定某列使用 bloom filter 索引。bloom filter 索引使用时有如下限制：
-
-- 主键表和明细表中所有列都可以创建 Bloom filter 索引；聚合表和更新表中，只有维度列（即 Key 列）支持创建 Bloom filter 索引。
-- 不支持为 TINYINT、FLOAT、DOUBLE 和 DECIMAL 类型的列创建 Bloom filter 索引。
-- Bloom filter 索引只能提高查询条件为 `in` 和 `=` 的查询效率，值越分散效果越好。
-
-更多信息，参见 [Bloom filter 索引](../../../table_design/indexes/Bloomfilter_index.md)。
-
-```sql
-PROPERTIES (
-    "bloom_filter_columns" = "k1, k2, k3"
-)
-```
-
-#### 添加属性支持 Colocate Join
-
-如果希望使用 Colocate Join 特性，需要在 properties 中指定:
-
-``` sql
-PROPERTIES (
-    "colocate_with" = "table1"
-)
-```
-
-详细的 Colocate Join 使用方法及应用场景请参考 [Colocate Join](../../../using_starrocks/Colocate_join.md) 章节。
-
-#### 设置动态分区
-
-如果希望使用动态分区特性，需要在 properties 中指定如下参数：
-
-``` sql
-PROPERTIES (
-    "dynamic_partition.enable" = "true|false",
-    "dynamic_partition.time_unit" = "DAY|WEEK|MONTH",
-    "dynamic_partition.start" = "${integer_value}",
-    "dynamic_partition.end" = "${integer_value}",
-    "dynamic_partition.prefix" = "${string_value}",
-    "dynamic_partition.buckets" = "${integer_value}"
-)
-```
-
-| 参数                          | 是否必填 | 说明                                                         |
-| ----------------------------- | -------- | ------------------------------------------------------------ |
-| `dynamic_partition.enable`    | 否       | 开启动态分区特性，取值为 `TRUE`（默认）或 `FALSE`。       |
-| `dynamic_partition.time_unit` | 是       | 动态分区的时间粒度，取值为 `DAY`、`WEEK` 或 `MONTH`。时间粒度会决定动态创建的分区名后缀格式。  <br />取值为 `DAY` 时，动态创建的分区名后缀格式为 yyyyMMdd，例如 `20200321`。<br />取值为 `WEEK` 时，动态创建的分区名后缀格式为 `yyyy_ww`，例如 `2020_13` 代表 2020 年第 13 周。<br />取值为 `MONTH` 时，动态创建的分区名后缀格式为 yyyyMM，例如 `202003`。 |
-| `dynamic_partition.start`：   | 否       | 保留的动态分区的起始偏移，取值范围为负整数。根据 `dynamic_partition.time_unit` 属性的不同，以当天（周/月）为基准，分区范围在此偏移之前的分区将会被删除。比如设置为`-3`，并且`dynamic_partition.time_unit`为`day`，则表示 3 天前的分区会被删掉。<br />如果不填写，则默认为 `Integer.MIN_VALUE`，即 `-2147483648`，表示不删除历史分区。 |
-| `dynamic_partition.end`       | 是       | 提前创建的分区数量，取值范围为正整数。根据 `dynamic_partition.time_unit` 属性的不同，以当天（周/月）为基准，提前创建对应范围的分区。 |
-| `dynamic_partition.prefix`    | 否       | 动态分区的前缀名，默认值为 `p`。                             |
-| dynamic_partition.buckets     | 否       | 动态分区的分桶数量。默认与 BUCKETS 保留字指定的分桶数量、或者 StarRocks 自动设置的分桶数量保持一致。 |
-
-#### 设置随机分桶表中分桶大小 (`bucket_size`)
-
-自 3.2 版本起，对于随机分桶的表，您可以在建表时在 `PROPERTIES` 中设置 `bucket_size` 参数来指定分桶大小，启用按需动态增加分桶数量。单位为 B。
-
-``` sql
-PROPERTIES (
-    "bucket_size" = "1073741824"
-)
-```
-
-#### 设置数据压缩算法
-
-您可以在建表时通过增加属性 `compression` 为该表指定数据压缩算法。
-
-`compression` 有效值包括：
-
-- `LZ4`：LZ4 算法。
-- `ZSTD`：Zstandard 算法。
-- `ZLIB`：zlib 算法。
-- `SNAPPY`：Snappy 算法。
-
-如不指定数据压缩算法，StarRocks 默认使用 LZ4。
-
-自 v3.3.2 起，StarRocks 支持在建表时指定 ZSTD 压缩格式的压缩级别。
-
-语法：
-
-```sql
-PROPERTIES ("compression" = "zstd(<compression_level>)")
-```
-
-`compression_level`：ZSTD 压缩格式的压缩级别。类型：Integer。范围：[1,22]。默认值：`3`（推荐）。数字越大，压缩率越高。压缩级别越高，压缩和解压的耗时越大。
-
-示例：
-
-```sql
-PROPERTIES ("compression" = "zstd(3)")
-```
-
-关于如何选择合适的数据压缩算法，请参阅[数据压缩](../../../table_design/data_compression.md)。
-
-#### 设置数据导入安全等级
-
-如果您的 StarRocks 集群有多数据副本，可以在建表时在 `PROPERTIES` 中设置 `write_quorum` 参数来指定数据导入安全等级，即设置需要多少数据副本导入成功后 StarRocks 可返回导入成功。该属性从 2.5 版本开始支持。
-
-`write_quorum` 的取值及其对应描述如下：
-
-- `MAJORITY`：默认值。当**多数**数据副本导入成功时，StarRocks 返回导入成功，否则返回失败。
-- `ONE`：当**一个**数据副本导入成功时，StarRocks 返回导入成功，否则返回失败。
-- `ALL`：当**所有**数据副本导入成功时，StarRocks 返回导入成功，否则返回失败。
-
-> **注意**
->
-> - 设置较低的导入数据安全等级会增加数据不可访问甚至丢失的风险。例如，在 StarRocks 集群有两个数据副本的情况下设置 `write_quorum` 为 `ONE`，如果某个 Tablet 实际只成功导入了一个副本，而此副本所在机器后续下线，则会导致该 Tablet 中的数据因为没有存活副本而无法访问。如果服务器磁盘受损，则会导致该 Tablet 中的数据丢失。
-> - 仅当所有数据副本返回导入状态后，StarRocks 才会返回导入任务状态。当有副本导入状态未知时，StarRocks 不会返回导入任务状态。导入超时的副本亦会被标记为失败。
-
-#### 指定数据在多副本间的写入和同步方式
-
-如果您的 StarRocks 集群有多数据副本，可以在建表时在 `PROPERTIES` 中设置 `replicated_storage` 参数来指定数据在多副本间的写入和同步方式。
-
-- 设置为 `true`（3.0 及后续版本的默认值）表示 single leader replication，即数据只写入到主副本 (primary replica)，由主副本同步数据到从副本 (secondary replica)。该模式能有效降低多副本写入带来的 CPU 成本。该模式从 2.5 版本开始支持。
-- 设置为 `false`（2.5 版本的默认值）表示 leaderless replication，即数据直接写入到多个副本，不区分主从副本。该模式 CPU 成本比较高。
-
-默认配置在绝大部分场景下能获得更好的写入性能，如果要修改已有表的多副本写入和同步方式，可执行 ALTER TABLE 命令，举例：
-
-```sql
-ALTER TABLE example_db.my_table
-SET ("replicated_storage" = "true");
-```
-
-#### 建表时批量创建多个 Rollup
-
-语法：
-
-```sql
-ROLLUP (rollup_name (column_name1, column_name2, ...)
-[FROM from_index_name]
-[PROPERTIES ("key" = "value", ...)],...)
-```
-
-#### 为 View Delta Join 查询改写定义 Unique Key 和外键约束
-
-要在 View Delta Join 场景中启用查询重写，您必须为 Delta Join 中的表定义 Unique Key 约束 `unique_constraints` 和外键约束 `foreign_key_constraints`。详细信息，请参阅 [异步物化视图 - 基于 View Delta Join 场景改写查询](../../../using_starrocks/query_rewrite_with_materialized_views.md#view-delta-join-改写)。
-
-```SQL
-PROPERTIES (
-    "unique_constraints" = "<unique_key>[, ...]",
-    "foreign_key_constraints" = "
-    (<child_column>[, ...]) 
-    REFERENCES 
-    [catalog_name].[database_name].<parent_table_name>(<parent_column>[, ...])
-    [;...]
-    "
-)
-```
-
-- `child_column`：当前表中的外键列。 您可以定义多个 `child_column`。
-- `catalog_name`：待 Join 表所在的数据目录名。未指定此参数时使用默认目录。
-- `database_name`：待 Join 表所在的数据库名。未指定此参数时使用当前数据库。
-- `parent_table_name`：待 Join 表名。
-- `parent_column`：待 Join 列名，必须为相应表的 Primary Key 或 Unique Key。
-
-> **注意**
->
-> - `unique_constraints` 约束和 `foreign_key_constraints` 约束仅用于查询重写。导入数据时，不保证进行外键约束校验。您必须确保导入的数据满足约束条件。
-> - 主键表的 Primary Key 或更新表的 Unique Key 默认是其 `unique_constraints`，您无需手动设置。
-> - `foreign_key_constraints` 中的 `child_column` 必须对应另一个表的 `unique_constraints` 中的 `unique_key`。
-> - `child_column` 和 `parent_column` 的数量必须一致。
-> - `child_column` 和对应的 `parent_column` 的数据类型必须匹配。
-
-#### 为 StarRocks 存算分离集群创建云原生表
-
-为了[使用 StarRocks 存算分离集群](../../../deployment/shared_data/shared_data.mdx)，您需要通过以下 PROPERTIES 创建云原生表：
-
-```SQL
-PROPERTIES (
-    "storage_volume" = "<storage_volume_name>",
-    "datacache.enable" = "{ true | false }",
-    "datacache.partition_duration" = "<string_value>",
-    "enable_async_write_back" = "{ true | false }"
-)
-```
-
-- `storage_volume`：建表使用的 Storage Volume 名称。该属性自 v3.1 版本起支持。如果未指定该属性，则使用默认 Storage Volume。示例：`"storage_volume" = "def_volume"`。
-
-- `datacache.enable`：是否启用本地磁盘缓存。默认值：`true`。
-
-  - 当该属性设置为 `true` 时，数据会同时导入对象存储（或 HDFS）和本地磁盘（作为查询加速的缓存）。
-  - 当该属性设置为 `false` 时，数据仅导入到对象存储中。
-
-  > **说明**
-  >
-  > 如需启用本地磁盘缓存，必须在 BE 配置项 `storage_root_path` 中指定磁盘目录。更多信息，请参见 [BE 配置项](../../../administration/management/BE_configuration.md)。
-
-- `datacache.partition_duration`：热数据的有效期。当启用本地磁盘缓存时，所有数据都会导入至本地磁盘缓存中。当缓存满时，StarRocks 会从缓存中删除最近较少使用（Less recently used）的数据。当有查询需要扫描已删除的数据时，StarRocks 会检查该数据是否在有效期内。如果数据在有效期内，StarRocks 会再次将数据导入至缓存中。如果数据不在有效期内，StarRocks 不会将其导入至缓存中。该属性为字符串，您可以使用以下单位指定：`YEAR`、`MONTH`、`DAY` 和 `HOUR`，例如，`7 DAY` 和 `12 HOUR`。如果不指定，StarRocks 将所有数据都作为热数据进行缓存。
-
-  > **说明**
-  >
-  > 仅当 `datacache.enable` 设置为 `true` 时，此属性可用。
-
-- `enable_async_write_back`：是否允许数据异步写入对象存储。默认值：`false`。
-
-  - 当该属性设置为 `true` 时，导入任务在数据写入本地磁盘缓存后立即返回成功，数据将异步写入对象存储。允许数据异步写入可以提升导入性能，但如果系统发生故障，可能会存在一定的数据可靠性风险。
-  - 当该属性设置为 `false` 时，只有在数据同时写入对象存储和本地磁盘缓存后，导入任务才会返回成功。禁用数据异步写入保证了更高的可用性，但会导致较低的导入性能。
-
-#### 设置 fast schema evolution
-
-`fast_schema_evolution`: 是否开启该表的 fast schema evolution，取值：`TRUE` 或 `FALSE`（默认）。开启后增删列时可以提高 schema change 速度并降低资源使用。目前仅支持在建表时开启该属性，建表后不支持通过 [ALTER TABLE](../data-definition/ALTER_TABLE.md) 修改该属性。
-
-> **NOTE**
->
-> - StarRocks 存算一体集群自 v3.2.0 版本起支持该参数，存算分离集群自 v3.3.0 起支持该参数。
-> - 如果您需要在集群范围内设置该配置，例如集群范围内关闭 fast schema evolution，则可以设置 FE 动态参数 [`enable_fast_schema_evolution`](../../../administration/management/FE_configuration.md#enable_fast_schema_evolution)。
-
-## 示例
-
-### 创建 Hash 分桶表并根据 key 列对数据进行聚合
-
-创建一个 olap 表，使用 Hash 分桶，使用列存，相同 key 的记录进行聚合。
-
-``` sql
-CREATE TABLE example_db.table_hash
-(
-    k1 TINYINT,
-    k2 DECIMAL(10, 2) DEFAULT "10.5",
-    v1 CHAR(10) REPLACE,
-    v2 INT SUM
-)
-ENGINE = olap
-AGGREGATE KEY(k1, k2)
-COMMENT "my first starrocks table"
-DISTRIBUTED BY HASH(k1)
-PROPERTIES ("storage_type" = "column");
-```
-
-### 创建表并设置存储介质和数据自动降冷时间
-
-创建一个 olap 表，使用 Hash 分桶，使用列存，相同 key 的记录进行覆盖，设置初始存储介质和冷却时间。
-
-``` sql
-CREATE TABLE example_db.table_hash
-(
-    k1 BIGINT,
-    k2 LARGEINT,
-    v1 VARCHAR(2048) REPLACE,
-    v2 SMALLINT DEFAULT "10"
-)
-ENGINE = olap
-UNIQUE KEY(k1, k2)
-DISTRIBUTED BY HASH (k1, k2)
-PROPERTIES(
-    "storage_type" = "column",
-    "storage_medium" = "SSD",
-    "storage_cooldown_time" = "2025-06-04 00:00:00"
-);
-```
-
-或
-
-``` sql
-CREATE TABLE example_db.table_hash
-(
-    k1 BIGINT,
-    k2 LARGEINT,
-    v1 VARCHAR(2048) REPLACE,
-    v2 SMALLINT DEFAULT "10"
-)
-ENGINE = olap
-PRIMARY KEY(k1, k2)
-DISTRIBUTED BY HASH (k1, k2)
-PROPERTIES(
-    "storage_type" = "column",
-    "storage_medium" = "SSD",
-    "storage_cooldown_time" = "2025-06-04 00:00:00"
-);
-```
-
-### 创建分区表
-
-创建一个 olap 表，使用 Range 分区，使用 Hash 分桶，默认使用列存，相同 key 的记录同时存在，设置初始存储介质和冷却时间。
-
-使用 LESS THAN 方式按照范围划分分区：
-
-``` sql
-CREATE TABLE example_db.table_range
-(
-    k1 DATE,
-    k2 INT,
-    k3 SMALLINT,
-    v1 VARCHAR(2048),
-    v2 DATETIME DEFAULT "2014-02-04 15:36:00"
-)
-ENGINE = olap
-DUPLICATE KEY(k1, k2, k3)
-PARTITION BY RANGE (k1)
-(
-    PARTITION p1 VALUES LESS THAN ("2014-01-01"),
-    PARTITION p2 VALUES LESS THAN ("2014-06-01"),
-    PARTITION p3 VALUES LESS THAN ("2014-12-01")
-)
-DISTRIBUTED BY HASH(k2)
-PROPERTIES(
-    "storage_medium" = "SSD",
-    "storage_cooldown_time" = "2025-06-04 00:00:00"
-);
-```
-
-说明：
-这个语句会将数据划分成如下 3 个分区：
-
-``` sql
-( {    MIN     },   {"2014-01-01"} )
-[ {"2014-01-01"},   {"2014-06-01"} )
-[ {"2014-06-01"},   {"2014-12-01"} )
-```
-
-不在这些分区范围内的数据将视为非法数据被过滤。
-
-使用 Fixed Range 方式创建分区：
-
-``` sql
-CREATE TABLE table_range
-(
-    k1 DATE,
-    k2 INT,
-    k3 SMALLINT,
-    v1 VARCHAR(2048),
-    v2 DATETIME DEFAULT "2014-02-04 15:36:00"
-)
-ENGINE = olap
-DUPLICATE KEY(k1, k2, k3)
-PARTITION BY RANGE (k1, k2, k3)
-(
-    PARTITION p1 VALUES [("2014-01-01", "10", "200"), ("2014-01-01", "20", "300")),
-    PARTITION p2 VALUES [("2014-06-01", "100", "200"), ("2014-07-01", "100", "300"))
-)
-DISTRIBUTED BY HASH(k2)
-PROPERTIES(
-    "storage_medium" = "SSD"
-);
-```
-
-### 创建一个 MySQL 外表
-
-``` sql
-CREATE EXTERNAL TABLE example_db.table_mysql
-(
-    k1 DATE,
-    k2 INT,
-    k3 SMALLINT,
-    k4 VARCHAR(2048),
-    k5 DATETIME
-)
-ENGINE = mysql
-PROPERTIES
-(
-    "host" = "127.0.0.1",
-    "port" = "8239",
-    "user" = "mysql_user",
-    "password" = "mysql_passwd",
-    "database" = "mysql_db_test",
-    "table" = "mysql_table_test"
-);
-```
-
-### 创建一张含有 HLL 列的表
-
-``` sql
-CREATE TABLE example_db.example_table
-(
-    k1 TINYINT,
-    k2 DECIMAL(10, 2) DEFAULT "10.5",
-    v1 HLL HLL_UNION,
-    v2 HLL HLL_UNION
-)
-ENGINE = olap
-AGGREGATE KEY(k1, k2)
-DISTRIBUTED BY HASH(k1)
-PROPERTIES ("storage_type" = "column");
-```
-
-### 创建一张含有 `BITMAP_UNION` 聚合类型的表
-
-v1 和 v2 列的原始数据类型必须是 `TINYINT, SMALLINT, INT`。
-
-``` sql
-CREATE TABLE example_db.example_table
-(
-    k1 TINYINT,
-    k2 DECIMAL(10, 2) DEFAULT "10.5",
-    v1 BITMAP BITMAP_UNION,
-    v2 BITMAP BITMAP_UNION
-)
-ENGINE = olap
-AGGREGATE KEY(k1, k2)
-DISTRIBUTED BY HASH(k1)
-PROPERTIES ("storage_type" = "column");
-```
-
-### 创建两张支持 Colocate Join 的表
-
-创建 t1 和 t2 两个表，两表可进行 Colocate Join。两表属性中的 `colocate_with` 属性的值需保持一致。
-
-``` sql
-CREATE TABLE `t1` (
-    `id` int(11) COMMENT "",
-    `value` varchar(8) COMMENT ""
-) ENGINE = OLAP
-DUPLICATE KEY(`id`)
-DISTRIBUTED BY HASH(`id`)
-PROPERTIES (
-    "colocate_with" = "t1"
-);
-
-CREATE TABLE `t2` (
-    `id` int(11) COMMENT "",
-    `value` varchar(8) COMMENT ""
-) ENGINE = OLAP
-DUPLICATE KEY(`id`)
-DISTRIBUTED BY HASH(`id`)
-PROPERTIES (
-    "colocate_with" = "t1"
-);
-```
-
-### 创建一个带有 bitmap 索引的表
-
-``` sql
-CREATE TABLE example_db.table_hash
-(
-    k1 TINYINT,
-    k2 DECIMAL(10, 2) DEFAULT "10.5",
-    v1 CHAR(10) REPLACE,
-    v2 INT SUM,
-    INDEX k1_idx (k1) USING BITMAP COMMENT 'xxxxxx'
-)
-ENGINE = olap
-AGGREGATE KEY(k1, k2)
-COMMENT "my first starrocks table"
-DISTRIBUTED BY HASH(k1)
-PROPERTIES ("storage_type" = "column");
-```
-
-### 创建动态分区表
-
- 创建动态分区表需要在 FE 配置中开启 **动态分区** 功能（`"dynamic_partition.enable" = "true"`），参数可参见本文[设置动态分区](#设置动态分区)。
-
- 该表每天提前创建 3 天的分区，并删除 3 天前的分区。例如今天为 `2020-01-08`，则会创建分区名为 `p20200108`，`p20200109`，`p20200110`，`p20200111` 的分区. 分区范围分别为:
-
-```plain text
-[types: [DATE]; keys: [2020-01-08]; ‥types: [DATE]; keys: [2020-01-09]; )
-[types: [DATE]; keys: [2020-01-09]; ‥types: [DATE]; keys: [2020-01-10]; )
-[types: [DATE]; keys: [2020-01-10]; ‥types: [DATE]; keys: [2020-01-11]; )
-[types: [DATE]; keys: [2020-01-11]; ‥types: [DATE]; keys: [2020-01-12]; )
-```
-
-```sql
-CREATE TABLE example_db.dynamic_partition
-(
-    k1 DATE,
-    k2 INT,
-    k3 SMALLINT,
-    v1 VARCHAR(2048),
-    v2 DATETIME DEFAULT "2014-02-04 15:36:00"
-)
-ENGINE = olap
-DUPLICATE KEY(k1, k2, k3)
-PARTITION BY RANGE (k1)
-(
-    PARTITION p1 VALUES LESS THAN ("2014-01-01"),
-    PARTITION p2 VALUES LESS THAN ("2014-06-01"),
-    PARTITION p3 VALUES LESS THAN ("2014-12-01")
-)
-DISTRIBUTED BY HASH(k2)
-PROPERTIES(
-    "storage_medium" = "SSD",
-    "dynamic_partition.time_unit" = "DAY",
-    "dynamic_partition.start" = "-3",
-    "dynamic_partition.end" = "3",
-    "dynamic_partition.prefix" = "p"
-);
-```
-
-### 创建一个 Hive 外部表
-
-``` SQL
-CREATE EXTERNAL TABLE example_db.table_hive
-(
-    k1 TINYINT,
-    k2 VARCHAR(50),
-    v INT
-)
-ENGINE = hive
-PROPERTIES
-(
-    "resource" = "hive0",
-    "database" = "hive_db_name",
-    "table" = "hive_table_name"
-);
-```
-
-### 创建一张主键表并且指定排序键
-
-假设需要按地域、最近活跃时间实时分析用户情况，则可以将表示用户 ID 的 `user_id` 列作为主键，表示地域的 `address` 列和表示最近活跃时间的 `last_active` 列作为排序键。建表语句如下：
-
-```SQL
-create table users (
-    user_id bigint NOT NULL,
-    name string NOT NULL,
-    email string NULL,
-    address string NULL,
-    age tinyint NULL,
-    sex tinyint NULL,
-    last_active datetime,
-    property0 tinyint NOT NULL,
-    property1 tinyint NOT NULL,
-    property2 tinyint NOT NULL,
-    property3 tinyint NOT NULL
-) 
-PRIMARY KEY (`user_id`)
-DISTRIBUTED BY HASH(`user_id`)
-ORDER BY(`address`,`last_active`)
-PROPERTIES(
-    "replication_num" = "3",
-    "enable_persistent_index" = "true"
-);
-```
-
-## References
-
-- [SHOW CREATE TABLE](../data-manipulation/SHOW_CREATE_TABLE.md)
-- [SHOW TABLES](../data-manipulation/SHOW_TABLES.md)
-- [USE](USE.md)
-- [ALTER TABLE](ALTER_TABLE.md)
-- [DROP TABLE](DROP_TABLE.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md b/docs/zh/sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md
deleted file mode 100644
index cae102ab1deca4..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md
+++ /dev/null
@@ -1,259 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['CTAS']
----
-
-# CREATE TABLE AS SELECT
-
-## 功能
-
-CREATE TABLE AS SELECT（简称 CTAS）语句可用于同步或异步查询原表并基于查询结果创建新表，然后将查询结果插入到新表中。
-
-您可以通过 [SUBMIT TASK](../data-manipulation/SUBMIT_TASK.md) 创建异步 CTAS 任务。
-
-## 语法
-
-- 同步查询原表并基于查询结果创建新表，然后将查询结果插入到新表中。
-
-  ```SQL
-  CREATE [TEMPORARY] TABLE [IF NOT EXISTS] [database.]table_name
-  [column_name1 [, column_name2, ...]]
-  [index_definition1 [, index_definition2, ...]]
-  [key_desc]
-  [COMMENT "table comment"]
-  [partition_desc]
-  [distribution_desc]
-  [ORDER BY (column_name1 [, column_name2, ...])]
-  [PROPERTIES ("key"="value", ...)]AS SELECT query
-  [ ... ]
-  ```
-
-- 异步查询原表并基于查询结果创建新表，然后将查询结果插入到新表中。
-
-  ```SQL
-  SUBMIT [/*+ SET_VAR(key=value) */] TASK [[database.]<task_name>]AS
-  CREATE TABLE [IF NOT EXISTS] [database.]table_name
-  [column_name1 [, column_name2, ...]]
-  [index_definition1 [, index_definition2, ...]]
-  [key_desc]
-  [COMMENT "table comment"]
-  [partition_desc]
-  [distribution_desc]
-  [ORDER BY (column_name1 [, column_name2, ...])]
-  [PROPERTIES ("key"="value", ...)] AS SELECT query
-  [ ... ]
-  ```
-
-## 参数说明
-
-| **参数**          | **必填** | **描述**                                                     |
-| ----------------- | -------- | ------------------------------------------------------------ |
-| TEMPORARY         | 否       | 创建临时表。从 v3.3.1 版本开始，StarRocks 支持在 Default Catalog 中创建临时表。更多信息，请参见 [临时表](../../../table_design/StarRocks_table_design.md#临时表)。目前，StarRocks 不支持通过 SUBMIT TASK 发起异步任务创建临时表。 |
-| column_name       | 否       | 新表的列名。您无需指定列类型。StarRocks 会自动选择合适的列类型，并将 FLOAT 和 DOUBLE 转换为 DECIMAL(38,9)；将 CHAR、VARCHAR 和 STRING 转换为 VARCHAR(65533)。 |
-| index_definition  | 否       | 自 3.1.8 开始支持为新表创建 Bitmap 索引，语法是 `INDEX index_name (col_name[, col_name, ...]) [USING BITMAP] [COMMENT '']`。有关参数说明和使用限制，请参见 [Bitmap 索引](../../../table_design/indexes/Bitmap_index.md)。|
-| key_desc          | 否       | 语法是 `key_type (<col_name1> [, <col_name2>, ...])`。<br />**参数**：<ul><li>`key_type`：新表的 Key 类型。有效值：`DUPLICATE KEY` 和 `PRIMARY KEY`。默认值：`DUPLICATE KEY`。</li><li> `col_name`：组成 Key 的列。</li></ul>|
-| COMMENT           | 否       | 新表注释。                                                   |
-| partition_desc    | 否       | 新表的分区方式。如不指定该参数，则默认新表为无分区。更多有关分区的设置，参见 [CREATE TABLE](./CREATE_TABLE.md#partition_desc)。 |
-| distribution_desc | 否       | 新表的分桶方式。如不指定该参数，则默认新表的分桶列为使用 CBO 优化器采集的统计信息中基数最高的列，且分桶数量默认为 10。如果 CBO 优化器没有采集基数信息，则默认新表的第一列为分桶列。更多有关分桶的设置，参见 [CREATE TABLE](./CREATE_TABLE.md#distribution_desc)。 |
-| ORDER BY| 否       |自 v3.1.8 版本以来，如果新表是主键表，则可以为新表指定排序键。排序键可以是任意列的组合。主键表是指在创建表时指定了 `PRIMARY KEY (xxx)` 的表。| 
-| Properties        | 否       | 新表的属性。                                                 |
-| AS SELECT query   | 是       | 查询结果。该参数支持如下值： 列。比如 `... AS SELECT a, b, c FROM table_a;`，其中 `a`、`b` 和 `c` 为原表的列名。如果您没有为新表指定列名，那么新表的列名也为 `a`、`b` 和 `c`。 表达式。比如 `... AS SELECT a+1 AS x, b+2 AS y, c*c AS z FROM table_a;`，其中 `a+1`、`b+2` 和 `c*c` 为原表的列名，`x`、`y` 和 `z` 为新表的列名。 说明： 新表的列数需要与 `AS SELECT query` 中指定的列数保持一致。 建议您为新表的列设置具有业务意义的列名，便于后续识别使用。 |
-
-## 注意事项
-
-- 使用 CTAS 语句创建的新表需满足如下条件：
-  - `ENGINE` 类型为 `OLAP`。
-
-  - 表类型默认为明细表，您也可以在 `key_desc` 中指定为主键表。
-
-  - 排序列为前三列且这三列类型的存储空间不能超过 36 个字节。
-
-- CTAS 语句不支持为新表设置索引。
-
-- 如果 CTAS 语句由于 FE 重启或其他原因执行失败，可能会发生如下情况：
-  - 新表创建成功，但表中没有数据。
-
-  - 新表创建失败。
-
-- 新表创建后，如果存在多种方式（比如 Insert Into）将数据插入到新表中，那么最先执行完插入操作的即最先将数据插入到新表中。
-
-- 新表创建成功后，您需要手动授予用户对该表的权限。参见 [表权限](../../../administration/user_privs/privilege_item.md#表权限-table) 和 [GRANT](../account-management/GRANT.md)。
-- 当异步查询原表并基于查询结果创建新表时，如果不指定 Task 名称，那么 StarRocks 会自动生成一个 Task 名称。
-
-## 示例
-
-示例一：同步查询原表 `order` 并根据查询结果创建新表 `order_new`，然后将查询结果插入到新表中。
-
-```SQL
-CREATE TABLE order_new
-AS SELECT * FROM order;
-```
-
-示例二：同步查询原表 `order`中的 `k1`、`k2` 和 `k3` 列并根据查询结果创建新表 `order_new`，然后将查询结果插入到新表中，并指定新表中列的名称为 `a`、`b` 和 `c`。
-
-```SQL
-CREATE TABLE order_new (a, b, c)
-AS SELECT k1, k2, k3 FROM order;
-```
-
-或
-
-```SQL
-CREATE TABLE order_new
-AS SELECT k1 AS a, k2 AS b, k3 AS c FROM order;
-```
-
-示例三：同步查询原表 `employee`中 `salary` 列的最大值并根据查询结果创建新表 `employee_new` ，然后将查询结果插入到新表中，并指定新表中列名为 `salary_new`。
-
-```SQL
-CREATE TABLE employee_new
-AS SELECT MAX(salary) AS salary_max FROM employee;
-```
-
-插入完成后，查询新表 `employee_new`。
-
-```SQL
-SELECT * FROM employee_new;
-
-+------------+
-| salary_max |
-+------------+
-|   10000    |
-+------------+
-```
-
-示例四：同步查询原表 `customers` 中的 `customer_id` 和 `first_name` 列并根据查询结果创建新表 `customers_new`，然后将查询结果插入到新表中，并指定新表中列的名称为 `customer_id_new` 和 `first_name_new`。同时在新表中基于列 `customer_id_new` 构建 Bitmap 索引。
-
-```SQL
-CREATE TABLE customers_new 
-(   customer_id_new,
-    first_name_new,
-    INDEX idx_bitmap_customer_id (customer_id_new) USING BITMAP
-) 
-AS SELECT customer_id,first_name FROM customers;
-```
-
-示例五：同步查询原表 `customers` 并根据查询结果创建新表 `customers_new`，然后将查询结果插入到新表中。 并且指定新表为主键表并且指定其排序键为 `first_name` 和 `last_name`。
-
-```SQL
-CREATE TABLE customers_pk
-PRIMARY KEY (customer_id)
-ORDER BY (first_name,last_name)
-AS SELECT  * FROM customers;
-```
-
-示例六：使用 CTAS 创建一张主键表。需要注意的是，主键表中的数据行数可能会比查询结果中的数据行数少。这是因为主键表只存储具有相同主键的一组数据行中最新的一条数据行。
-
-```SQL
-CREATE TABLE employee_new
-PRIMARY KEY(order_id)
-AS SELECT
-    order_list.order_id,
-    sum(goods.price) as total
-FROM order_list INNER JOIN goods ON goods.item_id1 = order_list.item_id2
-GROUP BY order_id;
-```
-
-示例七：同步查询四张原表 `lineorder`、`customer`、`supplier` 和 `part` 并根据查询结果创建新表 `lineorder_flat`，然后将查询结果插入到新表中，并指定新表的分区和分桶方式。
-
-```SQL
-CREATE TABLE lineorder_flat
-PARTITION BY RANGE (`LO_ORDERDATE`)
-(
-    START ("1993-01-01") END ("1999-01-01") EVERY (INTERVAL 1 YEAR)
-)
-DISTRIBUTED BY HASH (`LO_ORDERKEY`) AS SELECT
-    l.LO_ORDERKEY AS LO_ORDERKEY,
-    l.LO_LINENUMBER AS LO_LINENUMBER,
-    l.LO_CUSTKEY AS LO_CUSTKEY,
-    l.LO_PARTKEY AS LO_PARTKEY,
-    l.LO_SUPPKEY AS LO_SUPPKEY,
-    l.LO_ORDERDATE AS LO_ORDERDATE,
-    l.LO_ORDERPRIORITY AS LO_ORDERPRIORITY,
-    l.LO_SHIPPRIORITY AS LO_SHIPPRIORITY,
-    l.LO_QUANTITY AS LO_QUANTITY,
-    l.LO_EXTENDEDPRICE AS LO_EXTENDEDPRICE,
-    l.LO_ORDTOTALPRICE AS LO_ORDTOTALPRICE,
-    l.LO_DISCOUNT AS LO_DISCOUNT,
-    l.LO_REVENUE AS LO_REVENUE,
-    l.LO_SUPPLYCOST AS LO_SUPPLYCOST,
-    l.LO_TAX AS LO_TAX,
-    l.LO_COMMITDATE AS LO_COMMITDATE,
-    l.LO_SHIPMODE AS LO_SHIPMODE,
-    c.C_NAME AS C_NAME,
-    c.C_ADDRESS AS C_ADDRESS,
-    c.C_CITY AS C_CITY,
-    c.C_NATION AS C_NATION,
-    c.C_REGION AS C_REGION,
-    c.C_PHONE AS C_PHONE,
-    c.C_MKTSEGMENT AS C_MKTSEGMENT,
-    s.S_NAME AS S_NAME,
-    s.S_ADDRESS AS S_ADDRESS,
-    s.S_CITY AS S_CITY,
-    s.S_NATION AS S_NATION,
-    s.S_REGION AS S_REGION,
-    s.S_PHONE AS S_PHONE,
-    p.P_NAME AS P_NAME,
-    p.P_MFGR AS P_MFGR,
-    p.P_CATEGORY AS P_CATEGORY,
-    p.P_BRAND AS P_BRAND,
-    p.P_COLOR AS P_COLOR,
-    p.P_TYPE AS P_TYPE,
-    p.P_SIZE AS P_SIZE,
-    p.P_CONTAINER AS P_CONTAINER FROM lineorder AS l 
-INNER JOIN customer AS c ON c.C_CUSTKEY = l.LO_CUSTKEY
-INNER JOIN supplier AS s ON s.S_SUPPKEY = l.LO_SUPPKEY
-INNER JOIN part AS p ON p.P_PARTKEY = l.LO_PARTKEY;
-```
-
-示例八：异步查询原表 `order_detail` 并根据查询结果创建新表 `order_statistics`，然后将查询结果插入到新表中。
-
-```Plain_Text
-SUBMIT TASK AS CREATE TABLE order_statistics AS SELECT COUNT(*) as count FROM order_detail;
-
-+-------------------------------------------+-----------+
-| TaskName                                  | Status    |
-+-------------------------------------------+-----------+
-| ctas-df6f7930-e7c9-11ec-abac-bab8ee315bf2 | SUBMITTED |
-+-------------------------------------------+-----------+
-```
-
-查询 Task 的信息。
-
-```SQL
-SELECT * FROM INFORMATION_SCHEMA.tasks;
-
--- Task 信息如下
-
-TASK_NAME: ctas-df6f7930-e7c9-11ec-abac-bab8ee315bf2
-CREATE_TIME: 2022-06-14 14:07:06
-SCHEDULE: MANUAL
-DATABASE: default_cluster:test
-DEFINITION: CREATE TABLE order_statistics AS SELECT COUNT(*) as cnt FROM order_detail
-EXPIRE_TIME: 2022-06-17 14:07:06
-```
-
-查询 TaskRun 的状态。
-
-```SQL
-SELECT * FROM INFORMATION_SCHEMA.task_runs;
-
---TaskRun 的状态如下
-
-QUERY_ID: 37bd2b63-eba8-11ec-8d41-bab8ee315bf2
-TASK_NAME: ctas-df6f7930-e7c9-11ec-abac-bab8ee315bf2
-CREATE_TIME: 2022-06-14 14:07:06
-FINISH_TIME: 2022-06-14 14:07:07
-STATE: SUCCESS
-DATABASE: 
-DEFINITION: CREATE TABLE order_statistics AS SELECT COUNT(*) as cnt FROM order_detail
-EXPIRE_TIME: 2022-06-17 14:07:06
-ERROR_CODE: 0
-ERROR_MESSAGE: NULL
-```
-
-当 TaskRun 的状态为 `SUCCESS` 时即可查询新表。
-
-```SQL
-SELECT * FROM order_statistics;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_TABLE_LIKE.md b/docs/zh/sql-reference/sql-statements/data-definition/CREATE_TABLE_LIKE.md
deleted file mode 100644
index 84e08f3d62ec88..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_TABLE_LIKE.md
+++ /dev/null
@@ -1,158 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CREATE TABLE LIKE
-
-## 功能
-
-该语句用于创建一个表结构和另一张表完全相同的空表。复制的表结构包括 Column Definition、Partitions、Table Properties 等。支持复制 MySQL 等外表。
-
-自 3.2 版本起支持为新表指定不同的分区方式、分桶方式、或属性。
-
-:::tip
-该操作需要有在目标数据库下 CREATE TABLE 的权限，对要复制的原表有 `SELECT` 权限。权限控制请参考 [GRANT](../account-management/GRANT.md) 章节。
-:::
-
-## 语法
-
-- 3.2 版本之前支持的语法
-
-```sql
-CREATE [EXTERNAL] TABLE [IF NOT EXISTS] [database.]<table_name>
-LIKE [database.]<source_table_name>
-```
-
-- 3.2 版本起支持为新表指定分区方式、分桶方式、属性
-
-```sql
-CREATE [TEMPORARY] [EXTERNAL] TABLE [IF NOT EXISTS] [database.]<table_name>
-[partition_desc]
-[distribution_desc]
-[PROPERTIES ("key" = "value",...)]
-LIKE [database.]<source_table_name>
-```
-
-## 参数说明
-
-- `TEMPORARY`：创建临时表。从 v3.3.1 版本开始，StarRocks 支持在 Default Catalog 中创建临时表。更多信息，请参见 [临时表](../../../table_design/StarRocks_table_design.md#临时表)。
-- `database`：数据库。
-- `table_name`：要创建的表的名称。有关表名的命令要求，参见[系统限制](../../../reference/System_limit.md)。
-- `source_table_name`：要拷贝的表的名称。
-- `partition_desc`：分区方式。更多信息，参见 [CREATE TABLE](./CREATE_TABLE.md#partition_desc)。
-- `distribution_desc`：分桶方式。更多信息，参见 [CREATE TABLE](./CREATE_TABLE.md#distribution_desc)。
-- `PROPERTIES`：表的属性。支持所有表属性。更多信息，参见 [ALTER TABLE](./ALTER_TABLE.md#修改表的属性)。
-
-## 示例
-
-假设数据库 `test1` 下有表 `orders`。
-
-```sql
-create table orders (
-    dt date NOT NULL,
-    order_id bigint NOT NULL,
-    user_id int NOT NULL,
-    merchant_id int NOT NULL,
-    good_id int NOT NULL,
-    good_name string NOT NULL,
-    price int NOT NULL,
-    cnt int NOT NULL,
-    revenue int NOT NULL,
-    state tinyint NOT NULL
-) PRIMARY KEY (dt, order_id)
-PARTITION BY RANGE(`dt`) (
-    PARTITION p20210820 VALUES [('2021-08-20'), ('2021-08-21')),
-    PARTITION p20210821 VALUES [('2021-08-21'), ('2021-08-22')),
-    PARTITION p20210929 VALUES [('2021-09-29'), ('2021-09-30')),
-    PARTITION p20210930 VALUES [('2021-09-30'), ('2021-10-01'))
-) DISTRIBUTED BY HASH(order_id)
-PROPERTIES (
-    "replication_num" = "3",
-    "enable_persistent_index" = "true"
-);
-```
-
-示例一：在 `test1` 库下创建一张表结构和 `orders` 完全相同的空表，表名为 `order_1`。
-
-```sql
-CREATE TABLE test1.order_1 LIKE test1.orders;
-```
-
-可以看到 `order_1` 和 `orders` 表结构完全相同。
-
-```plaintext
-show create table order_1\G
-*************************** 1. row ***************************
-       Table: order_1
-Create Table: CREATE TABLE `order_1` (
-  `dt` date NOT NULL COMMENT "",
-  `order_id` bigint(20) NOT NULL COMMENT "",
-  `user_id` int(11) NOT NULL COMMENT "",
-  `merchant_id` int(11) NOT NULL COMMENT "",
-  `good_id` int(11) NOT NULL COMMENT "",
-  `good_name` varchar(65533) NOT NULL COMMENT "",
-  `price` int(11) NOT NULL COMMENT "",
-  `cnt` int(11) NOT NULL COMMENT "",
-  `revenue` int(11) NOT NULL COMMENT "",
-  `state` tinyint(4) NOT NULL COMMENT ""
-) ENGINE=OLAP 
-PRIMARY KEY(`dt`, `order_id`)
-PARTITION BY RANGE(`dt`)
-(PARTITION p20210820 VALUES [("2021-08-20"), ("2021-08-21")),
-PARTITION p20210821 VALUES [("2021-08-21"), ("2021-08-22")),
-PARTITION p20210929 VALUES [("2021-09-29"), ("2021-09-30")),
-PARTITION p20210930 VALUES [("2021-09-30"), ("2021-10-01")))
-DISTRIBUTED BY HASH(`order_id`)
-PROPERTIES (
-"replication_num" = "3",
-"in_memory" = "false",
-"enable_persistent_index" = "true",
-"replicated_storage" = "true",
-"compression" = "LZ4"
-);
-```
-
-示例二：建表时指定新表的分区方式、分桶方式和属性。
-
-```sql
-CREATE TABLE order_2
-PARTITION BY date_trunc('day',dt)
-DISTRIBUTED BY hash(dt)
-PROPERTIES ("replication_num" = "1")
-LIKE orders;
-```
-
-```plaintext
-show create table order_2\G
-*************************** 1. row ***************************
-       Table: order_2
-Create Table: CREATE TABLE `order_2` (
-  `dt` date NOT NULL COMMENT "",
-  `order_id` bigint(20) NOT NULL COMMENT "",
-  `user_id` int(11) NOT NULL COMMENT "",
-  `merchant_id` int(11) NOT NULL COMMENT "",
-  `good_id` int(11) NOT NULL COMMENT "",
-  `good_name` varchar(65533) NOT NULL COMMENT "",
-  `price` int(11) NOT NULL COMMENT "",
-  `cnt` int(11) NOT NULL COMMENT "",
-  `revenue` int(11) NOT NULL COMMENT "",
-  `state` tinyint(4) NOT NULL COMMENT ""
-) ENGINE=OLAP 
-PRIMARY KEY(`dt`, `order_id`)
-PARTITION BY RANGE(date_trunc('day', dt))
-()
-DISTRIBUTED BY HASH(`dt`)
-PROPERTIES (
-"replication_num" = "1",
-"in_memory" = "false",
-"enable_persistent_index" = "true",
-"replicated_storage" = "true",
-"compression" = "LZ4"
-);
-```
-
-示例三：在 `test1` 库下创建一张表结构和 MySQL 外表 `table1` 相同的空表，表名为 `table2`。
-
-```sql
-CREATE TABLE test1.table2 LIKE test1.table1;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_VIEW.md b/docs/zh/sql-reference/sql-statements/data-definition/CREATE_VIEW.md
deleted file mode 100644
index 9b2c548fd4e337..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/CREATE_VIEW.md
+++ /dev/null
@@ -1,80 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['shitu']
----
-
-# CREATE VIEW
-
-## 功能
-
-创建一个视图。
-
-视图（或逻辑视图）是一种虚拟表，其中的数据来自于对其他现有实体表的查询结果。因此，视图无需占用物理存储空间。所有针对视图的查询相当于该视图对应查询语句之上的子查询。
-
-关于 StarRocks 支持的物化视图，请参阅[同步物化视图](../../../using_starrocks/Materialized_view-single_table.md)和[异步物化视图](../../../using_starrocks/Materialized_view.md)。
-
-> **注意**
->
-> 该操作需要有指定数据库的 CREATE VIEW 权限。
-
-## 语法
-
-```SQL
-CREATE [OR REPLACE] VIEW [IF NOT EXISTS]
-[<database>.]<view_name>
-(
-    <column_name>[ COMMENT 'column comment']
-    [, <column_name>[ COMMENT 'column comment'], ...]
-)
-[COMMENT 'view comment']
-AS <query_statement>
-```
-
-## 参数说明
-
-| **参数**        | **说明**                                                     |
-| --------------- | ------------------------------------------------------------ |
-| OR REPLACE      | 替换已有视图。                                               |
-| database        | 视图所属的数据库名。                                         |
-| view_name       | 视图名。命名要求参见[系统限制](../../../reference/System_limit.md)。                                                     |
-| column_name     | 视图中的列名。请注意，视图中的列和 `query_statement` 中查询的列的数量必须一致。 |
-| COMMENT         | 视图中的列或视图本身的注释。                                 |
-| query_statement | 用于创建视图的查询语句。可以为 StarRocks 支持的任意查询语句。 |
-
-## 使用说明
-
-- 查询视图需要该视图的 SELECT 权限和其对应基表的 SELECT 权限。
-- 如果基表变更导致创建视图的查询语句无法执行，则查询该视图时报错。
-
-## 示例
-
-示例一：通过基于表 `example_table` 的聚合查询在数据库 `example_db` 中创建名为 `example_view` 的视图。
-
-```SQL
-CREATE VIEW example_db.example_view (k1, k2, k3, v1)
-AS
-SELECT c1 as k1, k2, k3, SUM(v1) FROM example_table
-WHERE k1 = 20160112 GROUP BY k1,k2,k3;
-```
-
-示例二：通过基于表 `example_table` 的聚合查询在数据库 `example_db` 中创建名为 `example_view` 的视图，并为视图和其中的列设置注释。
-
-```SQL
-CREATE VIEW example_db.example_view
-(
-    k1 COMMENT 'first key',
-    k2 COMMENT 'second key',
-    k3 COMMENT 'third key',
-    v1 COMMENT 'first value'
-)
-COMMENT 'my first view'
-AS
-SELECT c1 as k1, k2, k3, SUM(v1) FROM example_table
-WHERE k1 = 20160112 GROUP BY k1,k2,k3;
-```
-
-## 相关 SQL
-
-- [SHOW CREATE VIEW](../data-manipulation/SHOW_CREATE_VIEW.md)
-- [ALTER VIEW](./ALTER_VIEW.md)
-- [DROP VIEW](./DROP_VIEW.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/DROP_ANALYZE.md b/docs/zh/sql-reference/sql-statements/data-definition/DROP_ANALYZE.md
deleted file mode 100644
index 0bf9692e9fcba4..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/DROP_ANALYZE.md
+++ /dev/null
@@ -1,35 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DROP ANALYZE
-
-## 功能
-
-删除自定义自动采集任务。自定义自动采集任务用于采集 CBO 统计信息。
-
-默认情况下，StarRocks 会周期性自动采集表的全量统计信息。默认检查更新时间为 5 分钟一次，如果发现有数据更新，会自动触发采集。如果您不希望使用自动全量采集，可以设置 FE 配置项 `enable_collect_full_statistic` 为 `false`，系统会停止自动全量采集，根据您创建的自定义任务进行定制化采集。
-
-## 语法
-
-```SQL
-DROP ANALYZE <ID>
-```
-
-可以通过 SHOW ANALYZE JOB 查看任务的 ID。
-
-## 示例
-
-```SQL
-DROP ANALYZE 266030;
-```
-
-## 相关文档
-
-[CREATE ANALYZE](../data-definition/CREATE_ANALYZE.md)：创建自定义自动采集任务。
-
-[SHOW ANALYZE JOB](../data-definition/SHOW_ANALYZE_JOB.md)：查看自定义自动采集任务。
-
-[KILL ANALYZE](../data-definition/KILL_ANALYZE.md)：取消正在运行中（Running）的统计信息收集任务。
-
-想了解更多 CBO 统计信息采集的内容，参见[CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/DROP_CATALOG.md b/docs/zh/sql-reference/sql-statements/data-definition/DROP_CATALOG.md
deleted file mode 100644
index 2135e07f08194c..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/DROP_CATALOG.md
+++ /dev/null
@@ -1,37 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DROP CATALOG
-
-## 功能
-
-删除指定的 external catalog。注意目前不支持删除 internal catalog。一个 StarRocks 集群中只有一个默认的 internal catalog，名为 `default_catalog`。
-
-## 语法
-
-```SQL
-DROP CATALOG [IF EXISTS] catalog_name
-```
-
-## 参数说明
-
-`catalog_name`：external catalog 名称，必选参数。
-
-## 示例
-
-创建名为`hive1`的 Hive catalog。
-
-```SQL
-CREATE EXTERNAL CATALOG hive1
-PROPERTIES(
-  "type"="hive", 
-  "hive.metastore.uris"="thrift://xx.xx.xx.xx:9083"
-);
-```
-
-删除`hive1`。
-
-```SQL
-DROP CATALOG hive1;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/DROP_DATABASE.md b/docs/zh/sql-reference/sql-statements/data-definition/DROP_DATABASE.md
deleted file mode 100644
index 0647c0eda2963b..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/DROP_DATABASE.md
+++ /dev/null
@@ -1,44 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DROP DATABASE
-
-## 功能
-
-该语句用于删除数据库（database）。
-
-> **注意**
->
-> 该操作需要有对应数据库的 DROP 权限。
-
-## 语法
-
-```sql
--- 2.0 之前版本
-DROP DATABASE [IF EXISTS] [FORCE] db_name
--- 2.0 及以后版本
-DROP DATABASE [IF EXISTS] db_name [FORCE]
-```
-
-注意以下几点：
-
-- 执行 DROP DATABASE 一段时间内（默认 1 天），可以通过 [RECOVER](../data-definition/backup_restore/RECOVER.md) 语句恢复被删除的数据库，但是该数据库下已经随数据库删除的 Pipe 导入作业（自 3.2 版本起支持）无法恢复。
-- 如果执行 `DROP DATABASE FORCE`，则系统不会检查该数据库是否存在未完成的事务，数据库将直接被删除并且 **不能被恢复**，一般不建议执行此操作。
-- 删除数据库后，所有从属于该数据库的 Pipe 导入作业（自 3.2 版本起支持）也将随之删除。
-
-## 示例
-
-1. 删除数据库 db_test。
-
-    ```sql
-    DROP DATABASE db_test;
-    ```
-
-## 相关参考
-
-- [CREATE DATABASE](../data-definition/CREATE_DATABASE.md)
-- [SHOW CREATE DATABASE](../data-manipulation/SHOW_CREATE_DATABASE.md)
-- [USE](../data-definition/USE.md)
-- [DESC](../Utility/DESCRIBE.md)
-- [SHOW DATABASES](../data-manipulation/SHOW_DATABASES.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/DROP_FUNCTION.md b/docs/zh/sql-reference/sql-statements/data-definition/DROP_FUNCTION.md
deleted file mode 100644
index a0f00005020c56..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/DROP_FUNCTION.md
+++ /dev/null
@@ -1,36 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DROP FUNCTION
-
-## 功能
-
-删除一个自定义函数。函数的名称、参数类型完全一致才能够被删除。
-
-要执行该命令的用户必须是函数的拥有者。
-
-## 语法
-
-```sql
-DROP [GLOBAL] FUNCTION <function_name>(arg_type [, ...])
-```
-
-## 参数说明
-
-- `GLOBAL`：表示删除全局函数。StarRocks 从 3.0 版本开始支持创建 [Global UDF](../../sql-functions/JAVA_UDF.md)。
-- `function_name`: 待删除函数的名字，必填。
-- `arg_type`: 待删除函数的参数类型，必填。
-
-## 示例
-
-删除一个函数。
-
-```sql
-DROP FUNCTION my_add(INT, INT)
-```
-
-## 相关 SQL
-
-- [SHOW FUNCTIONS](./SHOW_FUNCTIONS.md)
-- [Java UDF](../../sql-functions/JAVA_UDF.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/DROP_INDEX.md b/docs/zh/sql-reference/sql-statements/data-definition/DROP_INDEX.md
deleted file mode 100644
index c9d9a609278485..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/DROP_INDEX.md
+++ /dev/null
@@ -1,44 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['suoyin']
----
-
-# DROP INDEX
-
-## 功能
-
-删除指定表的某个 bitmap 索引。创建 bitmap 索引会占用额外的存储空间，所以不用的索引建议删除。删除索引后，存储空间会立即释放。
-
-:::tip
-
-该操作需要对应表的 ALTER 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
-
-:::
-
-## 语法
-
-```SQL
-DROP INDEX index_name ON [db_name.]table_name
-```
-
-## 参数说明
-
-| **参数**   | **必选** | **说明**           |
-| ---------- | -------- | ------------------ |
-| index_name | 是       | 要删除的索引名称。 |
-| table_name | 是       | 创建索引的表。     |
-| db_name    | 否       | 表所属的数据库。   |
-
-## 示例
-
-例如为表 `sales_records` 中的 `item_id` 列创建位图索引，索引名称为 `index3`。
-
-```SQL
-CREATE INDEX index3 ON sales_records (item_id);
-```
-
-删除表`sales_records`中的索引`index3`。
-
-```SQL
-DROP INDEX index3 ON sales_records;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW.md
deleted file mode 100644
index d8c234a4e32497..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW.md
+++ /dev/null
@@ -1,74 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DROP MATERIALIZED VIEW
-
-## 功能
-
-删除物化视图。
-
-此命令无法用于删除正在创建中的同步物化视图。如要删除创建中的同步物化视图，请参考 [同步物化视图 - 删除物化视图](../../../using_starrocks/Materialized_view-single_table.md#删除正在创建的同步物化视图)。
-
-> **注意**
->
-> 只有拥有对应物化视图 DROP 权限的用户才可以删除物化视图。
-
-## 语法
-
-```SQL
-DROP MATERIALIZED VIEW [IF EXISTS] [database.]mv_name
-```
-
-## 参数
-
-| **参数**  | **必选** | **说明**                                                     |
-| --------- | -------- | ------------------------------------------------------------ |
-| IF EXISTS | 否       | 如果声明该参数，删除不存在的物化视图系统不会报错。如果不声明该参数，删除不存在的物化视图系统会报错。 |
-| mv_name   | 是       | 待删除的物化视图的名称。                                     |
-
-## 示例
-
-示例一：删除存在的物化视图
-
-1. 查看当前数据库中存在的物化视图。
-
-    ```Plain
-    MySQL > SHOW MATERIALIZED VIEWS\G
-    *************************** 1. row ***************************
-              id: 470740
-            name: order_mv1
-    database_name: default_cluster:sr_hub
-            text: SELECT `sr_hub`.`orders`.`dt` AS `dt`, `sr_hub`.`orders`.`order_id` AS `order_id`, `sr_hub`.`orders`.`user_id` AS `user_id`, sum(`sr_hub`.`orders`.`cnt`) AS `total_cnt`, sum(`sr_hub`.`orders`.`revenue`) AS `total_revenue`, count(`sr_hub`.`orders`.`state`) AS `state_count` FROM `sr_hub`.`orders` GROUP BY `sr_hub`.`orders`.`dt`, `sr_hub`.`orders`.`order_id`, `sr_hub`.`orders`.`user_id`
-            rows: 0
-    1 rows in set (0.00 sec)
-    ```
-
-2. 删除物化视图 `order_mv1`。
-
-    ```Plain
-    DROP MATERIALIZED VIEW order_mv1;
-    ```
-
-3. 删除后重新查看当前数据库中存在的物化视图将不会显示该物化视图。
-
-    ```Plain
-    MySQL > SHOW MATERIALIZED VIEWS;
-    Empty set (0.01 sec)
-    ```
-
-示例二：删除不存在的物化视图
-
-- 当未声明 `IF EXISTS` 参数时，删除一个不属于当前数据库的物化视图 `k1_k2` 会报错。
-
-```Plain
-MySQL > DROP MATERIALIZED VIEW k1_k2;
-ERROR 1064 (HY000): Materialized view k1_k2 is not found
-```
-
-- 当声明 `IF EXISTS` 参数时，删除一个不属于当前数据库的物化视图 `k1_k2` 不会报错。
-
-```Plain
-MySQL > DROP MATERIALIZED VIEW IF EXISTS k1_k2;
-Query OK, 0 rows affected (0.00 sec)
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/DROP_RESOURCE.md b/docs/zh/sql-reference/sql-statements/data-definition/DROP_RESOURCE.md
deleted file mode 100644
index 54dafd44070e01..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/DROP_RESOURCE.md
+++ /dev/null
@@ -1,31 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DROP RESOURCE
-
-## 功能
-
-该语句用于删除一个已有的资源。需要拥有资源的 DROP 权限才可以删除资源。
-
-创建 RESOURCE 操作请参考 [CREATE RESOURCE](../data-definition/CREATE_RESOURCE.md) 章节。
-
-## 语法
-
-```sql
-DROP RESOURCE 'resource_name'
-```
-
-## 示例
-
-1. 删除名为 spark0 的 Spark 资源。
-
-    ```SQL
-    DROP RESOURCE 'spark0';
-    ```
-
-2. 删除名为 hive0 的 Hive 资源。
-
-    ```SQL
-    DROP RESOURCE 'hive0';
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/DROP_STATS.md b/docs/zh/sql-reference/sql-statements/data-definition/DROP_STATS.md
deleted file mode 100644
index f7104c9e27bd50..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/DROP_STATS.md
+++ /dev/null
@@ -1,33 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DROP STATS
-
-## 功能
-
-删除 CBO 统计信息。
-
-StarRocks 支持手动删除统计信息。手动删除统计信息时，会删除统计信息数据和统计信息元数据，并且会删除过期内存中的统计信息缓存。需要注意的是，如果当前存在自动采集任务，可能会重新采集之前已删除的统计信息。您可以使用`SHOW ANALYZE STATUS`查看统计信息采集历史记录。该语句从 2.4 版本开始支持。
-
-您可以使用 DROP STATS 删除基础统计信息，使用 ANALYZE TABLE DROP HISTOGRAM 删除直方图统计信息。
-
-### 删除基础统计信息
-
-#### 语法
-
-```SQL
-DROP STATS <tbl_name>
-```
-
-### 删除直方图统计信息
-
-#### 语法
-
-```SQL
-ANALYZE TABLE tbl_name DROP HISTOGRAM ON <col_name> [, <col_name>]
-```
-
-## 相关文档
-
-想了解更多 CBO 统计信息采集的内容，参见[CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/DROP_TABLE.md b/docs/zh/sql-reference/sql-statements/data-definition/DROP_TABLE.md
deleted file mode 100644
index 4862debc6d56b5..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/DROP_TABLE.md
+++ /dev/null
@@ -1,49 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DROP TABLE
-
-## 功能
-
-该语句用于删除表。
-
-## 语法
-
-```sql
-DROP [TEMPORARY] TABLE [IF EXISTS] [db_name.]table_name [FORCE]
-```
-
-说明：
-
-- 执行 DROP TABLE 后一段时间内（默认 1 天），可以通过 [RECOVER](../data-definition/backup_restore/RECOVER.md) 语句恢复被删除的表。
-- 如果执行 `DROP TABLE FORCE`，则系统不会检查该表是否存在未完成的事务，表将直接被删除并且不能被恢复，一般不建议执行此操作。
-- 临时表删除后不可以通过 RECOVER 语句恢复。
-
-## 示例
-
-1. 删除一个 table。
-
-    ```sql
-    DROP TABLE my_table;
-    ```
-
-2. 如果存在，删除指定 database 的 table。
-
-    ```sql
-    DROP TABLE IF EXISTS example_db.my_table;
-    ```
-
-3. 强制删除表，并清理磁盘文件。
-
-    ```sql
-    DROP TABLE my_table FORCE;
-    ```
-
-## References
-
-* [CREATE TABLE](CREATE_TABLE.md)
-* [SHOW TABLES](../data-manipulation/SHOW_TABLES.md)
-* [SHOW CREATE TABLE](../data-manipulation/SHOW_CREATE_TABLE.md)
-* [ALTER TABLE](ALTER_TABLE.md)
-* [SHOW ALTER TABLE](../data-manipulation/SHOW_ALTER.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/DROP_VIEW.md b/docs/zh/sql-reference/sql-statements/data-definition/DROP_VIEW.md
deleted file mode 100644
index 9657330b031be5..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/DROP_VIEW.md
+++ /dev/null
@@ -1,28 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['shitu']
----
-
-# DROP VIEW
-
-## 功能
-
-该语句用于删除一个逻辑视图。
-
-## 语法
-
-```sql
-DROP VIEW [IF EXISTS] [db_name.]view_name
-```
-
-## 示例
-
-1. 如果存在，删除 example_db 上的逻辑视图 example_view。
-
-    ```sql
-    DROP VIEW IF EXISTS example_db.example_view;
-    ```
-
-## 相关操作
-
-如要创建逻辑视图，请参考 [CREATE VIEW](../data-definition/CREATE_VIEW.md)。
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/KILL_ANALYZE.md b/docs/zh/sql-reference/sql-statements/data-definition/KILL_ANALYZE.md
deleted file mode 100644
index b013f0cd2bd54a..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/KILL_ANALYZE.md
+++ /dev/null
@@ -1,23 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# KILL ANALYZE
-
-## 功能
-
-取消正在运行中（Running）的统计信息收集任务，包括手动采集任务和自定义自动采集任务。该语句从 2.4 版本开始支持。
-
-## 语法
-
-```SQL
-KILL ANALYZE <ID>
-```
-
-手动采集任务的任务 ID 可以在 SHOW ANALYZE STATUS 中查看。自定义自动采集任务的任务 ID 可以在 SHOW ANALYZE JOB 中查看。
-
-## 相关文档
-
-[SHOW ANALYZE STATUS](../data-definition/SHOW_ANALYZE_STATUS.md)
-
-[SHOW ANALYZE JOB](../data-definition/SHOW_ANALYZE_JOB.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE.md b/docs/zh/sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE.md
deleted file mode 100644
index 9fa7b30617cb5f..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/REFRESH_EXTERNAL_TABLE.md
+++ /dev/null
@@ -1,101 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# REFRESH EXTERNAL TABLE
-
-## 功能
-
-该语句用于更新缓存在 StarRocks 中的数据湖上的元数据，主要有以下两个使用场景：
-
-- **外部表**：使用 Hive 外部表和 Hudi 外部表查询 Hive 和 Hudi 数据时， 可使用该语句更新缓存的 Hive 和 Hudi 元数据。
-- **External catalog**：使用 [Hive catalog](../../../data_source/catalog/hive_catalog.md)、[Hudi catalog](../../../data_source/catalog/hudi_catalog.md)、[Delta Lake catalog](../../../data_source/catalog/deltalake_catalog.md)、[MaxCompute Catalog](../../../data_source/catalog/maxcompute_catalog.md)（自 3.3 起）查询对应数据源数据时，可使用该语句更新缓存的元数据。
-
-> **注意**
->
-> 只有拥有对应外表 ALTER 权限的用户才可以执行该操作。
-
-## 基本概念
-
-- **Hive 外部表**：在 StarRocks 中创建并保存的表，用于查询 Hive 集群中的数据。
-- **Hudi 外部表**：在 StarRocks 中创建并保存的表，用于查询 Hudi 集群中的数据。
-- **Hive 表**：在 Hive 中创建并保存的表。
-- **Hudi 表**：在 Hudi 中创建并保存的表。
-
-## 语法和参数说明
-
-在不同的使用场景下，对应语法和参数说明如下：
-
-- 外部表
-
-    ```SQL
-    REFRESH EXTERNAL TABLE <table_name>
-    [PARTITION ('partition_name', ...)]
-    ```
-
-    | **参数**       | **必选** | **说明**                                                     |
-    | -------------- | -------- | ------------------------------------------------------------ |
-    | table_name     | 是       | Hive 外部表或 Hudi 外部表名。                                |
-    | partition_name | 否       | Hive 表或 Hudi 表中的分区名。如指定，则更新缓存的 Hive 表或 Hudi 表指定分区的元数据。 |
-
-- External catalog
-
-    ```SQL
-    REFRESH EXTERNAL TABLE [external_catalog.][db_name.]<table_name>
-    [PARTITION ('partition_name', ...)]
-    ```
-
-    | **参数**         | **必选** | **说明**                                                     |
-    | ---------------- | -------- | ------------------------------------------------------------ |
-    | external_catalog | 否       | 外部数据目录名称，支持 Hive、Hudi、Delta Lake、MaxCompute catalog （自 3.3 起）。                          |
-    | db_name          | 否       | 表所在的数据库名。                            |
-    | table_name       | 是       | 表名名。                                        |
-    | partition_name   | 否       | 表中的分区名。如指定，则更新缓存的表中指定分区的元数据。 |
-
-## 示例
-
-在不同使用场景下， 对应的示例如下。
-
-### 外部表
-
-示例一：更新外部表 `hive1` 对应的 Hive 表元数据。
-
-```SQL
-REFRESH EXTERNAL TABLE hive1;
-```
-
-示例二：更新外部表 `hudi1` 对应的 Hudi 表 `p1` 和 `p2` 分区元数据。
-
-```SQL
-REFRESH EXTERNAL TABLE hudi1
-PARTITION ('p1', 'p2');
-```
-
-### External catalog
-
-示例一：更新缓存的 `hive_table` 表的元数据。
-
-```SQL
-REFRESH EXTERNAL TABLE hive_catalog.hive_db.hive_table;
-```
-
-或
-
-```SQL
-USE hive_catalog.hive_db;
-REFRESH EXTERNAL TABLE hive_table;
-```
-
-示例二：更新缓存的 `hive_table` 表的二级分区 `p2` 的元数据。
-
-```SQL
-USE hive_catalog.hive_db;
-REFRESH EXTERNAL TABLE hive_table PARTITION ('p1=${date}/p2=${hour}');
-```
-
-示例三：更新缓存的 `hudi_table` 表的分区 `p1` 和 `p2` 的元数据。
-
-```SQL
-REFRESH EXTERNAL TABLE hudi_catalog.hudi_db.hudi_table
-PARTITION ('p1', 'p2');
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/SET_CATALOG.md b/docs/zh/sql-reference/sql-statements/data-definition/SET_CATALOG.md
deleted file mode 100644
index b469153bbbf4e1..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/SET_CATALOG.md
+++ /dev/null
@@ -1,37 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SET CATALOG
-
-## 功能
-
-切换到指定的 Catalog。该命令自 3.0 版本起支持。
-
-> **注意**
->
-> 如果是新部署的 3.1 集群，用户需要有目标 Catalog 的 USAGE 权限才可以执行该操作。如果是从低版本升级上来的集群，则不需要重新赋权。您可以使用 [GRANT](../account-management/GRANT.md) 命令进行授权操作。
-
-## 语法
-
-```SQL
-SET CATALOG <catalog_name>
-```
-
-## 参数
-
-`catalog_name`：当前会话里生效的 Catalog，支持 Internal Catalog 和 External Catalog。如果指定的 Catalog 不存在，则会引发异常。
-
-## 示例
-
-通过如下命令，切换当前会话里生效的 Catalog 为 Hive Catalog `hive_metastore`：
-
-```SQL
-SET CATALOG hive_metastore;
-```
-
-通过如下命令，切换当前会话里生效的 Catalog 为 Internal Catalog `default_catalog`：
-
-```SQL
-SET CATALOG default_catalog;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/SHOW_ANALYZE_JOB.md b/docs/zh/sql-reference/sql-statements/data-definition/SHOW_ANALYZE_JOB.md
deleted file mode 100644
index 6c714071e94160..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/SHOW_ANALYZE_JOB.md
+++ /dev/null
@@ -1,52 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW ANALYZE JOB
-
-## 功能
-
-查看自定义自动采集任务的信息和状态。自定义自动采集任务用于采集 CBO 统计信息。该语句从 2.4 版本开始支持。
-
-默认情况下，StarRocks 会周期性自动采集表的全量统计信息。默认检查更新时间为 5 分钟一次，如果发现有数据更新，会自动触发采集。如果您不希望使用自动全量采集，可以设置 FE 配置项 `enable_collect_full_statistic` 为 `false`，系统会停止自动全量采集，根据您创建的自定义任务进行定制化采集。
-
-## 语法
-
-```SQL
-SHOW ANALYZE JOB [WHERE predicate]
-```
-
-您可以使用 WHERE 子句设定筛选条件，进行返回结果筛选。该语句会返回如下列。
-
-| **列名**     | **说明**                                                     |
-| ------------ | ------------------------------------------------------------ |
-| Id           | 采集任务的 ID。                                               |
-| Database     | 数据库名。                                                   |
-| Table        | 表名。                                                       |
-| Columns      | 列名列表。                                                   |
-| Type         | 统计信息的类型。取值： FULL，SAMPLE。                        |
-| Schedule     | 调度的类型。自动采集任务固定为 `SCHEDULE`。                   |
-| Properties   | 自定义参数信息。                                             |
-| Status       | 任务状态，包括 PENDING（等待）、RUNNING（正在执行）、SUCCESS（执行成功）和 FAILED（执行失败）。 |
-| LastWorkTime | 最近一次采集时间。                                           |
-| Reason       | 任务失败的原因。如果执行成功则为 `NULL`。                    |
-
-## 示例
-
-```SQL
--- 查看集群全部自定义采集任务。
-SHOW ANALYZE JOB
-
--- 查看数据库 `test` 下的自定义采集任务。
-SHOW ANALYZE JOB where `database` = 'test';
-```
-
-## 相关文档
-
-[CREATE ANALYZE](../data-definition/CREATE_ANALYZE.md)：创建自定义自动采集任务。
-
-[DROP ANALYZE](../data-definition/DROP_ANALYZE.md)：删除自动采集任务。
-
-[KILL ANALYZE](../data-definition/KILL_ANALYZE.md)：取消正在运行中（Running）的统计信息收集任务。
-
-想了解更多 CBO 统计信息采集的内容，参见 [CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/SHOW_ANALYZE_STATUS.md b/docs/zh/sql-reference/sql-statements/data-definition/SHOW_ANALYZE_STATUS.md
deleted file mode 100644
index 8462a5c1c131ce..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/SHOW_ANALYZE_STATUS.md
+++ /dev/null
@@ -1,41 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW ANALYZE STATUS
-
-## 功能
-
-查看当前所有采集任务的状态。**该语句不支持查看自定义采集任务的状态，如要查看，请使用 SHOW ANALYZE JOB;**。该语句从 2.4 版本开始支持。
-
-## 语法
-
-```SQL
-SHOW ANALYZE STATUS [LIKE | WHERE predicate]
-```
-
-您可以使用 `Like 或 Where` 来筛选需要返回的信息。
-
-目前 `SHOW ANALYZE STATUS` 会返回如下列。
-
-| **列名**   | **说明**                                                     |
-| ---------- | ------------------------------------------------------------ |
-| Id         | 采集任务的 ID。                                               |
-| Database   | 数据库名。                                                   |
-| Table      | 表名。                                                       |
-| Columns    | 列名列表。                                                   |
-| Type       | 统计信息的类型，包括 FULL，SAMPLE，HISTOGRAM。               |
-| Schedule   | 调度的类型。`ONCE` 表示手动，`SCHEDULE` 表示自动。             |
-| Status     | 任务状态，包括 RUNNING（正在执行）、SUCCESS（执行成功）和 FAILED（执行失败）。 |
-| StartTime  | 任务开始执行的时间。                                         |
-| EndTime    | 任务结束执行的时间。                                         |
-| Properties | 自定义参数信息。                                             |
-| Reason     | 任务失败的原因。如果执行成功则为 NULL。                      |
-
-## 相关文档
-
-[ANALYZE TABLE](../data-definition/ANALYZE_TABLE.md)：创建手动采集任务。
-
-[KILL ANALYZE](../data-definition/KILL_ANALYZE.md)：取消正在运行中（Running）的统计信息收集任务。
-
-想了解更多 CBO 统计信息采集的内容，参见 [CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/SHOW_FUNCTIONS.md b/docs/zh/sql-reference/sql-statements/data-definition/SHOW_FUNCTIONS.md
deleted file mode 100644
index ee057566e6a1a5..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/SHOW_FUNCTIONS.md
+++ /dev/null
@@ -1,60 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW FUNCTIONS
-
-## 功能
-
-查看数据库下所有的自定义(系统提供)函数。如果未指定数据库，则直接查询当前会话所在数据库。
-
-## 语法
-
-```sql
-SHOW [FULL] [BUILTIN] [GLOBAL] FUNCTIONS [IN|FROM <db_name>] [LIKE 'function_pattern']
-```
-
-## 参数说明
-
-* `FULL`: 表示显示函数的详细信息。
-* `BUILTIN`: 表示显示系统提供的函数。
-* `GLOBAL`: 表示显示全局函数。StarRocks 从 3.0 版本开始支持创建 [Global UDF](../../sql-functions/JAVA_UDF.md)。
-* `db_name`: 要查询的数据库名称。
-* `function_pattern`: 用于过滤函数名称。
-
-## 示例
-
-```sql
--- \G表示将查询结果进行按列打印
-mysql> show full functions in testDb\G
-*************************** 1. row ***************************
-        Signature: my_add(INT,INT)
-      Return Type: INT
-    Function Type: Scalar
-Intermediate Type: NULL
-       Properties: {"symbol":"_ZN9starrocks_udf6AddUdfEPNS_15FunctionContextERKNS_6IntValES4_","object_file":"http://host:port/libudfsample.so","md5":"cfe7a362d10f3aaf6c49974ee0f1f878"}
-*************************** 2. row ***************************
-        Signature: my_count(BIGINT)
-      Return Type: BIGINT
-    Function Type: Aggregate
-Intermediate Type: NULL
-       Properties: {"object_file":"http://host:port/libudasample.so","finalize_fn":"_ZN9starrocks_udf13CountFinalizeEPNS_15FunctionContextERKNS_9BigIntValE","init_fn":"_ZN9starrocks_udf9CountInitEPNS_15FunctionContextEPNS_9BigIntValE","merge_fn":"_ZN9starrocks_udf10CountMergeEPNS_15FunctionContextERKNS_9BigIntValEPS2_","md5":"37d185f80f95569e2676da3d5b5b9d2f","update_fn":"_ZN9starrocks_udf11CountUpdateEPNS_15FunctionContextERKNS_6IntValEPNS_9BigIntValE"}
-
-2 rows in set (0.00 sec)
-
-mysql> show builtin functions in testDb like 'year%';
-+---------------+
-| Function Name |
-+---------------+
-| year          |
-| years_add     |
-| years_diff    |
-| years_sub     |
-+---------------+
-2 rows in set (0.00 sec)
-```
-
-## 相关 SQL
-
-* [DROP FUNCTION](./DROP_FUNCTION.md)
-* [Java UDF](../../sql-functions/JAVA_UDF.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/SHOW_META.md b/docs/zh/sql-reference/sql-statements/data-definition/SHOW_META.md
deleted file mode 100644
index c40f1d624d4037..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/SHOW_META.md
+++ /dev/null
@@ -1,54 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW META
-
-## 功能
-
-查看统计信息元数据。该命令支持查看基础统计信息和直方图统计信息的元数据。该语句从 2.4 版本开始支持。
-
-更多 CBO 统计信息采集的内容，参见 [CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
-
-### 基础统计信息元数据
-
-#### 语法
-
-```SQL
-SHOW STATS META [WHERE predicate]
-```
-
-该语句返回如下列。
-
-| **列名**   | **说明**                                            |
-| ---------- | --------------------------------------------------- |
-| Database   | 数据库名。                                          |
-| Table      | 表名。                                              |
-| Columns    | 列名。                                              |
-| Type       | 统计信息的类型，`FULL` 表示全量，`SAMPLE` 表示抽样。 |
-| UpdateTime | 当前表的最新统计信息更新时间。                      |
-| Properties | 自定义参数信息。                                    |
-| Healthy    | 统计信息健康度。                                    |
-
-### 直方图统计信息元数据
-
-#### 语法
-
-```SQL
-SHOW HISTOGRAM META [WHERE predicate];
-```
-
-该语句返回如下列。
-
-| **列名**   | **说明**                                  |
-| ---------- | ----------------------------------------- |
-| Database   | 数据库名。                                |
-| Table      | 表名。                                    |
-| Column     | 列名。                                    |
-| Type       | 统计信息的类型，直方图固定为 `HISTOGRAM`。 |
-| UpdateTime | 当前表的最新统计信息更新时间。            |
-| Properties | 自定义参数信息。                          |
-
-## 相关文档
-
-想了解更多 CBO 统计信息采集的内容，参见 [CBO 统计信息](../../../using_starrocks/Cost_based_optimizer.md)。
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/SHOW_RESOURCES.md b/docs/zh/sql-reference/sql-statements/data-definition/SHOW_RESOURCES.md
deleted file mode 100644
index 26c0d68c14916e..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/SHOW_RESOURCES.md
+++ /dev/null
@@ -1,42 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW RESOURCES
-
-## 功能
-
-用于展示用户有使用权限 (USAGE) 的资源。
-
-> **注意**
->
-> 普通用户可以看到自己有 USAGE 权限的资源，`db_admin` 角色可以看到全局资源。
-
-## 语法
-
-```sql
-SHOW RESOURCES
-```
-
-返回字段
-
-| 字段     | 说明                                              |
-| -------- | ----------------------------------|
-| Name    | 资源名称。                                          |
-| ResourceType    | 资源类型，比如 spark。                       |
-| Key     |  创建资源时在 PROPERTIES 里指定的 key。               |
-| Value   |    key 对应的 value。                               |
-
-## 示例
-
-```plain
-MySQL [(none)]> show resources;
-+-------------------+--------------+---------------------+-----------------------+
-| Name              | ResourceType | Key                 | Value                 |
-+-------------------+--------------+---------------------+-----------------------+
-| spark_resource_16ce91e4_e20a_11ed_a756_00163e0e489a | spark | spark.master | yarn |
-```
-
-## Keywords
-
-show resource, show resources
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/TRUNCATE_TABLE.md b/docs/zh/sql-reference/sql-statements/data-definition/TRUNCATE_TABLE.md
deleted file mode 100644
index c0cbcb9acee345..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/TRUNCATE_TABLE.md
+++ /dev/null
@@ -1,37 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# TRUNCATE TABLE
-
-## 功能
-
-该语句用于清空指定表和分区的数据。
-
-## 语法
-
-```sql
-TRUNCATE TABLE [db.]tbl[ PARTITION(p1, p2, ...)]
-```
-
-说明：
-
-1. 该语句清空数据，但保留表或分区。
-2. 不同于 DELETE，该语句只能整体清空指定的表或分区，不能添加过滤条件。
-3. 不同于 DELETE，使用该方式清空数据**不会对查询性能造成影响**。
-4. 该操作会直接删除数据，删除掉的数据**不可恢复**。
-5. 使用该命令时，表状态需为 NORMAL，即不允许正在进行 SCHEMA CHANGE 等操作。
-
-## 示例
-
-1. 清空 example_db 下的表 tbl。
-
-    ```sql
-    TRUNCATE TABLE example_db.tbl;
-    ```
-
-2. 清空表 tbl 的 p1 和 p2 分区。
-
-    ```sql
-    TRUNCATE TABLE tbl PARTITION(p1, p2);
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/USE.md b/docs/zh/sql-reference/sql-statements/data-definition/USE.md
deleted file mode 100644
index 11ac6d5cdf456e..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/USE.md
+++ /dev/null
@@ -1,48 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# USE
-
-## 功能
-
-指定会话使用的数据库。指定数据库后，即可以进行后续的建表或者查询等操作。
-
-## 语法
-
-```SQL
-USE [<catalog_name>.]<db_name>
-```
-
-## 参数说明
-
-| **参数**     | **必选** | **说明**                                                     |
-| ------------ | -------- | ------------------------------------------------------------ |
-| catalog_name | 否       | Catalog 名称。<ul><li>如不指定该参数，则默认使用 `default_catalog` 下的数据库。</li><li>如要使用 external catalog 下的数据库，则必须指定该参数，具体见「示例二」。</li><li>如从一个 catalog 下的数据库切换到另一个 catalog 下的数据库，则必须指定该参数，具体见「示例三」。</li></ul>更多有关 catalog 的信息，请参见[概述](../../../data_source/catalog/catalog_overview.md)。 |
-| db_name      | 是       | 数据库名称。该数据库必须存在。                               |
-
-## 示例
-
-示例一：使用 `default_catalog` 下的 `example_db` 作为会话的数据库。
-
-```SQL
-USE default_catalog.example_db;
-```
-
-或
-
-```SQL
-USE example_db;
-```
-
-示例二：使用 `hive_catalog` 下的 `example_db` 作为会话的数据库。
-
-```SQL
-USE hive_catalog.example_db;
-```
-
-示例三：将会话使用的数据库 `hive_catalog.example_table1` 切换到  `iceberg_catalog.example_table2`。
-
-```SQL
-USE iceberg_catalog.example_table2;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/BACKUP.md b/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/BACKUP.md
deleted file mode 100644
index 60524088f21bca..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/BACKUP.md
+++ /dev/null
@@ -1,108 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['beifen']
----
-
-# BACKUP
-
-## 功能
-
-备份指定数据库、表或分区的数据。当前 StarRocks 仅支持备份 OLAP 类型表。更多信息，请见 备份和恢复。
-
-数据备份为异步操作。您可以通过 [SHOW BACKUP](../../data-manipulation/backup_restore/SHOW_BACKUP.md) 语句查看备份作业状态，或通过 [CANCEL BACKUP](../../data-definition/backup_restore/CANCEL_BACKUP.md) 语句取消备份作业。作业成功后，您可以通过 [SHOW SNAPSHOT](../../data-manipulation/backup_restore/SHOW_SNAPSHOT.md) 查看特定仓库对应的数据快照信息。
-
-> **注意**
->
-> - 单一数据库内，仅可同时执行一个备份或恢复作业，否则系统报错。
-> - 目前 StarRocks 不支持在备份数据时使用压缩算法。
-
-## 权限要求
-
-3.0 之前的版本中，拥有 admin_priv 权限才可执行此操作。3.0 及之后的版本中，如需备份指定数据表或整个数据库，需要拥有 System 级的 REPOSITORY 权限，以及对应表或对应数据库下所有表的 EXPORT 权限。例如：
-
-- 授予角色从指定的表中导出数据的权限。
-
-    ```SQL
-    GRANT REPOSITORY ON SYSTEM TO ROLE backup_tbl;
-    GRANT EXPORT ON TABLE <table_name> TO ROLE backup_tbl;
-    ```
-
-- 授予角色从指定数据下所有表中导出数据的权限。
-
-    ```SQL
-    GRANT REPOSITORY ON SYSTEM TO ROLE backup_db;
-    GRANT EXPORT ON ALL TABLES IN DATABASE <database_name> TO ROLE backup_db;
-    ```
-
-- 授予角色从所有数据库的所有表中导出数据的权限。
-
-    ```SQL
-    GRANT REPOSITORY ON SYSTEM TO ROLE backup;
-    GRANT EXPORT ON ALL TABLES IN ALL DATABASES TO ROLE backup;
-    ```
-
-## 语法
-
-```SQL
-BACKUP SNAPSHOT <db_name>.<snapshot_name>
-TO <repository_name>
-[ ON ( <table_name> [ PARTITION ( <partition_name> [, ...] ) ]
-       [, ...] ) ]
-[ PROPERTIES ("key"="value" [, ...] ) ]
-```
-
-## 参数说明
-
-| **参数**        | **说明**                                                     |
-| --------------- | ------------------------------------------------------------ |
-| db_name         | 需要备份的数据所属的数据库名。                                   |
-| snapshot_name   | 指定数据快照名。全局范围内，快照名不可重复。                      |
-| repository_name | 仓库名。您可以通过 [CREATE REPOSITORY](../../data-definition/backup_restore/CREATE_REPOSITORY.md) 创建仓库。 |
-| ON              | 需要备份的表名。如不指定则备份整个数据库。                         |
-| PARTITION       | 需要备份的分区名。如不指定则备份对应表的所有分区。                   |
-| PROPERTIES      | 数据快照属性。现支持以下属性：`type`：备份类型。当前仅支持 `FULL`，即全量备份。默认：`FULL`。`timeout`：任务超时时间。单位：秒。默认：`86400`。 |
-
-## 示例
-
-示例一：全量备份 `example_db` 数据库到仓库 `example_repo` 中。
-
-```SQL
-BACKUP SNAPSHOT example_db.snapshot_label1
-TO example_repo
-PROPERTIES ("type" = "full");
-```
-
-示例二：全量备份 `example_db` 数据库下的表 `example_tbl` 到仓库 `example_repo` 中。
-
-```SQL
-BACKUP SNAPSHOT example_db.snapshot_label2
-TO example_repo
-ON (example_tbl);
-```
-
-示例三：全量备份 `example_db` 数据库中表 `example_tbl` 的 `p1`、`p2` 分区和表 `example_tbl2` 到仓库 `example_repo` 中。
-
-```SQL
-BACKUP SNAPSHOT example_db.snapshot_label3
-TO example_repo
-ON(
-    example_tbl PARTITION (p1, p2),
-    example_tbl2
-);
-```
-
-## 注意事项
-
-- 执行全局、数据库级、表级以及分区级备份恢复需要不同权限。
-- 单一数据库内，仅可同时执行一个备份或恢复作业。否则，StarRocks 返回错误。
-- 因为备份与恢复操作会占用一定系统资源，建议您在集群业务低峰期进行该操作。
-- 目前 StarRocks 不支持在备份数据时使用压缩算法。
-- 因为数据备份是通过快照的形式完成的，所以在当前数据快照生成之后导入的数据不会被备份。因此，在快照生成至恢复（迁移）作业完成这段期间导入的数据，需要重新导入至集群。建议您在迁移完成后，对新旧两个集群并行导入一段时间，完成数据和业务正确性校验后，再将业务迁移到新的集群。
-- 在恢复作业完成前，被恢复表无法被操作。
-- Primary Key 表无法被恢复至 v2.5 之前版本的 StarRocks 集群中。
-- 您无需在恢复作业前在新集群中创建需要被恢复表。恢复作业将自动创建该表。
-- 如果被恢复表与已有表重名，StarRocks 会首先识别已有表的 Schema。如果 Schema 相同，StarRocks 会覆盖写入已有表。如果 Schema 不同，恢复作业失败。您可以通过 `AS` 关键字重新命名被恢复表，或者删除已有表后重新发起恢复作业。
-- 如果恢复作业是一次覆盖操作（指定恢复数据到已经存在的表或分区中），那么从恢复作业的 COMMIT 阶段开始，当前集群上被覆盖的数据有可能不能再被还原。此时如果恢复作业失败或被取消，有可能造成之前的数据损坏且无法访问。这种情况下，只能通过再次执行恢复操作，并等待作业完成。因此，我们建议您，如无必要，不要使用覆盖的方式恢复数据，除非确认当前数据已不再使用。覆盖操作会检查快照和已存在的表或分区的元数据是否相同，包括 Schema 和 Rollup 等信息，如果不同则无法执行恢复操作。
-- 目前 StarRocks 暂不支持备份恢复逻辑视图。
-- 目前 StarRocks 暂不支持备份恢复用户、权限以及资源组配置相关数据。
-- StarRocks 不支持备份恢复表之间的 Colocate Join 关系。
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/CANCEL_BACKUP.md b/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/CANCEL_BACKUP.md
deleted file mode 100644
index 1b739789d1f5a1..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/CANCEL_BACKUP.md
+++ /dev/null
@@ -1,30 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['beifen']
----
-
-# CANCEL BACKUP
-
-## 功能
-
-取消指定数据库中一个正在进行的备份任务。更多信息，请见 备份和恢复。
-
-## 语法
-
-```SQL
-CANCEL BACKUP FROM <db_name>
-```
-
-## 参数说明
-
-| **参数** | **说明**               |
-| -------- | ---------------------- |
-| db_name  | 备份任务所属数据库名。 |
-
-## 示例
-
-示例一：取消 `example_db` 数据库下的备份任务。
-
-```SQL
-CANCEL BACKUP FROM example_db;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/CANCEL_RESTORE.md b/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/CANCEL_RESTORE.md
deleted file mode 100644
index 06df2244178882..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/CANCEL_RESTORE.md
+++ /dev/null
@@ -1,34 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['beifen']
----
-
-# CANCEL RESTORE
-
-## 功能
-
-取消指定数据库中一个正在进行的恢复任务。更多信息，请见 备份和恢复。
-
-> **注意**
->
-> 如果恢复作业在 COMMIT 阶段被取消，已恢复的数据将会损坏且无法访问。这种情况下，只能通过再次执行恢复操作，并等待作业完成。
-
-## 语法
-
-```SQL
-CANCEL RESTORE FROM <db_name>
-```
-
-## 参数说明
-
-| **参数** | **说明**               |
-| -------- | ---------------------- |
-| db_name  | 恢复任务所属数据库名。 |
-
-## 示例
-
-示例一：取消 `example_db` 数据库下的恢复任务。
-
-```SQL
-CANCEL RESTORE FROM example_db;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/CREATE_REPOSITORY.md b/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/CREATE_REPOSITORY.md
deleted file mode 100644
index ecde8a9dbb3cea..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/CREATE_REPOSITORY.md
+++ /dev/null
@@ -1,118 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['beifen']
----
-
-# CREATE REPOSITORY
-
-## 功能
-
-基于远端存储系统创建用于存储数据快照的仓库。仓库用于 备份和恢复 数据库数据。
-
-> **注意**
->
-> 只有拥有 System 级 REPOSITORY 权限的用户才可以创建仓库。
-
-删除仓库操作请参考 [DROP REPOSITORY](../../data-definition/backup_restore/DROP_REPOSITORY.md) 章节。
-
-## 语法
-
-```SQL
-CREATE [READ ONLY] REPOSITORY <repository_name>
-WITH BROKER
-ON LOCATION "<repository_location>"
-PROPERTIES ("key"="value", ...)
-```
-
-## 参数说明
-
-| **参数**            | **说明**                                                     |
-| ------------------- | ------------------------------------------------------------ |
-| READ ONLY           | 创建只读仓库。请注意只读仓库只可进行恢复操作。当为两个集群创建相同仓库，用以迁移数据时，可以为新集群创建只读仓库，仅赋予其恢复的权限。|
-| repository_name     | 仓库名。命名要求参见[系统限制](../../../../reference/System_limit.md)。  |
-| repository_location | 远端存储系统路径。                                           |
-| PROPERTIES          | 访问远端存储系统的节点及密钥或用户名及密码。具体使用方式见以下说明。 |
-
-**PROPERTIES**：
-
-StarRocks 支持在 HDFS、AWS S3、Google GCS、阿里云 OSS 以及腾讯云 COS 中创建仓库。
-
-- HDFS：
-  - "username"：用于访问 HDFS 集群中 NameNode 节点的用户名。
-  - "password"：用于访问 HDFS 集群中 NameNode 节点的密码。
-
-- S3：
-  - "aws.s3.use_instance_profile"：是否使用 Instance Profile 或 Assumed Role 作为安全凭证访问 AWS S3。默认值：`false`。
-
-    - 如果您使用 IAM 用户凭证（Access Key 和 Secret Key）访问 AWS S3，则无需指定该参数，并指定 "aws.s3.access_key"、"aws.s3.secret_key" 以及 "aws.s3.endpoint"。
-    - 如果您使用 Instance Profile 访问 AWS S3，则需将该参数设置为 `true`，并指定 "aws.s3.region"。
-    - 如果您使用 Assumed Role 访问 AWS S3，则需将该参数设置为 `true`，并指定 "aws.s3.iam_role_arn" 和 "aws.s3.region"。
-
-  - "aws.s3.access_key"：访问 AWS S3 存储空间的 Access Key。
-  - "aws.s3.secret_key"：访问 AWS S3 存储空间的 Secret Key。
-  - "aws.s3.endpoint"：访问 AWS S3 存储空间的连接地址。
-  - "aws.s3.iam_role_arn"：有访问 AWS S3 存储空间权限 IAM Role 的 ARN。如使用 Instance Profile 或 Assumed Role 作为安全凭证访问 AWS S3，则必须指定该参数。
-  - "aws.s3.region"：需访问的 AWS S3 存储空间的地区，如 `us-west-1`。
-
-> **说明**
->
-> StarRocks 仅支持通过 S3A 协议在 AWS S3 中创建仓库。因此，当您在 AWS S3 中创建仓库时，必须在 `ON LOCATION` 参数下将 S3 URI 中的 `s3://` 替换为 `s3a://`。
-
-- GCS：
-  - "fs.s3a.access.key"：访问 Google GCS 存储空间的 Access Key。
-  - "fs.s3a.secret.key"：访问 Google GCS 存储空间的 Secret Key。
-  - "fs.s3a.endpoint"：访问 Google GCS 存储空间的连接地址。
-
-> **说明**
->
-> StarRocks 仅支持通过 S3A 协议在 Google GCS 中创建仓库。 因此，当您在 Google GCS 中创建仓库时，必须在 `ON LOCATION` 参数下将 GCS URI 的前缀替换为 `s3a://`。
-
-- OSS：
-  - "fs.oss.accessKeyId"：访问阿里云 OSS 存储空间的 AccessKey ID，用于标识用户。
-  - "fs.oss.accessKeySecret"：访问阿里云 OSS 存储空间的 AccessKey Secret，是用于加密签名字符串和 OSS 用来验证签名字符串的密钥。
-  - "fs.oss.endpoint"：访问阿里云 OSS 存储空间的连接地址。
-
-- COS：
-  - "fs.cosn.userinfo.secretId"：访问腾讯云 COS 存储空间的 SecretId，用于标识 API 调用者的身份。
-  - "fs.cosn.userinfo.secretKey"：访问腾讯云 COS 存储空间的 SecretKey，是用于加密签名字符串和服务端验证签名字符串的密钥。
-  - "fs.cosn.bucket.endpoint_suffix"：访问腾讯云 COS 存储空间的连接地址。
-
-## 示例
-
-示例一：在 Apache™ Hadoop® 集群中创建名为 `hdfs_repo` 的仓库。
-
-```SQL
-CREATE REPOSITORY hdfs_repo
-WITH BROKER
-ON LOCATION "hdfs://x.x.x.x:yyyy/repo_dir/backup"
-PROPERTIES(
-    "username" = "xxxxxxxx",
-    "password" = "yyyyyyyy"
-);
-```
-
-示例二：在 Amazon S3 存储桶 `bucket_s3` 中创建名为 `s3_repo` 的只读仓库。
-
-```SQL
-CREATE READ ONLY REPOSITORY s3_repo
-WITH BROKER
-ON LOCATION "s3a://bucket_s3/backup"
-PROPERTIES(
-    "aws.s3.access_key" = "XXXXXXXXXXXXXXXXX",
-    "aws.s3.secret_key" = "yyyyyyyyyyyyyyyyy",
-    "aws.s3.endpoint" = "s3.us-east-1.amazonaws.com"
-);
-```
-
-示例三：在 Google GCS 存储桶 `bucket_gcs` 中创建一个名为 `gcs_repo` 的仓库。
-
-```SQL
-CREATE REPOSITORY gcs_repo
-WITH BROKER
-ON LOCATION "s3a://bucket_gcs/backup"
-PROPERTIES(
-    "fs.s3a.access.key" = "xxxxxxxxxxxxxxxxxxxx",
-    "fs.s3a.secret.key" = "yyyyyyyyyyyyyyyyyyyy",
-    "fs.s3a.endpoint" = "storage.googleapis.com"
-);
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/DROP_REPOSITORY.md b/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/DROP_REPOSITORY.md
deleted file mode 100644
index 03132ccdfe0a85..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/DROP_REPOSITORY.md
+++ /dev/null
@@ -1,35 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['beifen']
----
-
-# DROP REPOSITORY
-
-## 功能
-
-删除一个仓库。仓库用于 备份和恢复 数据库数据。
-
-> **注意**
->
-> - 只有拥有 System 级 REPOSITORY 权限的用户才可以删除仓库。
-> - 该操作仅删除仓库在 StarRocks 中的映射，不会删除实际的仓库数据。如需删除备份数据，您需要手动删除备份在远端存储系统的快照路径。删除后，您可以再次通过指定相同的远端存储系统路径映射到该仓库。
-
-## 语法
-
-```SQL
-DROP REPOSITORY <repository_name>
-```
-
-## 参数说明
-
-| **参数**        | **说明**         |
-| --------------- | ---------------- |
-| repository_name | 要删除的仓库名。 |
-
-## 示例
-
-示例一：删除名为 `oss_repo` 的仓库。
-
-```SQL
-DROP REPOSITORY `oss_repo`;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/RECOVER.md b/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/RECOVER.md
deleted file mode 100644
index 3a06543dce4982..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/RECOVER.md
+++ /dev/null
@@ -1,62 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['beifen']
----
-
-# RECOVER
-
-## 功能
-
-恢复之前通过 DROP 操作删除的 database、table 或者 partition。DROP 操作后只有在指定的时间内才能通过 RECOVER 恢复数据，超过这个时间无法恢复。该时间由 FE 动态参数 `catalog_trash_expire_second` 控制，默认 1 天。
-
-通过 [TRUNCATE TABLE](../TRUNCATE_TABLE.md) 命令删除的数据无法恢复。
-
-> **注意**
->
-> 只有拥有 default_catalog 的 CREATE DATABASE 权限才可以恢复数据库；同时需要拥有对应数据库的 CREATE TABLE 和对应表的 DROP 权限。
-
-## 语法
-
-### 恢复 database
-
-```sql
-RECOVER DATABASE <db_name>
-```
-
-### 恢复 table
-
-```sql
-RECOVER TABLE [db_name.]table_name;
-```
-
-### 恢复 partition
-
-```sql
-RECOVER PARTITION partition_name FROM [db_name.]table_name;
-```
-
-说明：
-
-1. 该操作仅能恢复之前一段时间内删除的元信息，默认为 1 天。（可通过 `fe.conf` 中 `catalog_trash_expire_second` 参数配置。）
-
-2. 如果删除元信息后新建了同名同类型的元信息，则之前删除的元信息不能被恢复。
-
-## 示例
-
-1. 恢复名为 `example_db` 的 database。
-
-    ```sql
-    RECOVER DATABASE example_db;
-    ```
-
-2. 恢复名为 `example_tbl` 的 table。
-
-    ```sql
-    RECOVER TABLE example_db.example_tbl;
-    ```
-
-3. 恢复表 `example_tbl` 中名为 `p1` 的 partition。
-
-    ```sql
-    RECOVER PARTITION p1 FROM example_tbl;
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/RESTORE.md b/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/RESTORE.md
deleted file mode 100644
index 55f7ce523d3772..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/RESTORE.md
+++ /dev/null
@@ -1,108 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['beifen']
----
-
-# RESTORE
-
-## 功能
-
-恢复指定数据库、表或分区的数据。当前 StarRocks 仅支持恢复 OLAP 类型表。更多信息，请见 备份和恢复。
-
-数据恢复为异步操作。您可以通过 [SHOW RESTORE](../../data-manipulation/backup_restore/SHOW_RESTORE.md) 语句查看恢复作业状态，或通过 [CANCEL RESTORE](../../data-definition/backup_restore/CANCEL_RESTORE.md) 语句取消恢复作业。
-
-> **注意**
->
-> 单一数据库内，仅可同时执行一个备份或恢复作业，否则系统报错。
-
-## 权限要求
-
-3.0 之前的版本中，拥有 admin_priv 权限才可执行此操作。3.0 及之后的版本中，如需恢复整个数据库，需要拥有 System 级的 REPOSITORY 权限，以及创建数据库、创建表、导入数据的权限；如需恢复特定表，则需要拥有 System 级的 REPOSITORY 权限，以及对特定表的导入权限（INSERT）。例如：
-
-- 授予角色恢复指定表中数据的权限。
-
-    ```SQL
-    GRANT REPOSITORY ON SYSTEM TO ROLE recover_tbl;
-    GRANT INSERT ON TABLE <table_name> TO ROLE recover_tbl;
-    ```
-
-- 授予角色恢复指定数据库下所有数据的权限。
-
-    ```SQL
-    GRANT REPOSITORY ON SYSTEM TO ROLE recover_db;
-    GRANT INSERT ON ALL TABLES ALL DATABASES TO ROLE recover_db;
-    ```
-
-- 授予角色恢复 default_catalog 下全部数据库中数据的权限。
-
-    ```SQL
-    GRANT REPOSITORY ON SYSTEM TO ROLE recover_db;
-    GRANT CREATE DATABASE ON CATALOG default_catalog TO ROLE recover_db;
-    ```
-
-## 语法
-
-```SQL
-RESTORE SNAPSHOT <db_name>.<snapshot_name>
-FROM <repository_name>
-[ ON ( <table_name> [ PARTITION ( <partition_name> [, ...] ) ]
-    [ AS <table_alias>] [, ...] ) ]
-PROPERTIES ("key"="value", ...)
-```
-
-## 参数说明
-
-| **参数**        | **说明**                                                     |
-| --------------- | ------------------------------------------------------------ |
-| db_name         | 恢复数据至该数据库。                                           |
-| snapshot_name   | 数据快照名。                                                 |
-| repository_name | 仓库名。                                                    |
-| ON              | 需要恢复的表名。如不指定则恢复整个数据库。                   |
-| PARTITION       | 需要恢复的分区名。如不指定则恢复对应表的所有分区。您可以通过 [SHOW PARTITIONS](../../data-manipulation/SHOW_PARTITIONS.md) 语句查看分区名。 |
-| PROPERTIES      | 恢复操作属性。现支持以下属性：<ul><li>`backup_timestamp`：备份时间戳，**必填**。您可以通过 [SHOW SNAPSHOT](../../data-manipulation/backup_restore/SHOW_SNAPSHOT.md) 查看备份时间戳。</li><li>`replication_num`：指定恢复的表或分区的副本数。默认：`3`。</li><li>`meta_version`：该参数作为临时方案，仅用于恢复旧版本 StarRocks 备份的数据。最新版本的备份数据中已经包含 `meta version`，无需再指定。</li><li>`timeout`：任务超时时间。单位：秒。默认：`86400`。</li></ul> |
-
-## 示例
-
-示例一：从 `example_repo` 仓库中恢复备份 `snapshot_label1` 中的表 `backup_tbl` 至数据库 `example_db`，备份时间戳为 `2018-05-04-16-45-08`。恢复为一个副本。
-
-```SQL
-RESTORE SNAPSHOT example_db.snapshot_label1
-FROM example_repo
-ON ( backup_tbl )
-PROPERTIES
-(
-    "backup_timestamp"="2018-05-04-16-45-08",
-    "replication_num" = "1"
-);
-```
-
-示例二：从 `example_repo` 仓库中恢复备份 `snapshot_label2` 中的表 `backup_tbl` 的分区 `p1` 及 `p2`，以及表 `backup_tbl2` 到数据库 `example_db`，并重命名为 `new_tbl`，备份时间戳为 `2018-05-04-17-11-01`。默认恢复三个副本。
-
-```SQL
-RESTORE SNAPSHOT example_db.snapshot_label2
-FROM example_repo
-ON(
-    backup_tbl PARTITION (p1, p2),
-    backup_tbl2 AS new_tbl
-)
-PROPERTIES
-(
-    "backup_timestamp"="2018-05-04-17-11-01"
-);
-```
-
-## 注意事项
-
-- 执行全局、数据库级、表级以及分区级备份恢复需要不同权限。
-- 单一数据库内，仅可同时执行一个备份或恢复作业。否则，StarRocks 返回错误。
-- 因为备份与恢复操作会占用一定系统资源，建议您在集群业务低峰期进行该操作。
-- 目前 StarRocks 不支持在备份数据时使用压缩算法。
-- 因为数据备份是通过快照的形式完成的，所以在当前数据快照生成之后导入的数据不会被备份。因此，在快照生成至恢复（迁移）作业完成这段期间导入的数据，需要重新导入至集群。建议您在迁移完成后，对新旧两个集群并行导入一段时间，完成数据和业务正确性校验后，再将业务迁移到新的集群。
-- 在恢复作业完成前，被恢复表无法被操作。
-- Primary Key 表无法被恢复至 v2.5 之前版本的 StarRocks 集群中。
-- 您无需在恢复作业前在新集群中创建需要被恢复表。恢复作业将自动创建该表。
-- 如果被恢复表与已有表重名，StarRocks 会首先识别已有表的 Schema。如果 Schema 相同，StarRocks 会覆盖写入已有表。如果 Schema 不同，恢复作业失败。您可以通过 `AS` 关键字重新命名被恢复表，或者删除已有表后重新发起恢复作业。
-- 如果恢复作业是一次覆盖操作（指定恢复数据到已经存在的表或分区中），那么从恢复作业的 COMMIT 阶段开始，当前集群上被覆盖的数据有可能不能再被还原。此时如果恢复作业失败或被取消，有可能造成之前的数据损坏且无法访问。这种情况下，只能通过再次执行恢复操作，并等待作业完成。因此，我们建议您，如无必要，不要使用覆盖的方式恢复数据，除非确认当前数据已不再使用。覆盖操作会检查快照和已存在的表或分区的元数据是否相同，包括 Schema 和 Rollup 等信息，如果不同则无法执行恢复操作。
-- 目前 StarRocks 暂不支持备份恢复逻辑视图。
-- 目前 StarRocks 暂不支持备份恢复用户、权限以及资源组配置相关数据。
-- StarRocks 不支持备份恢复表之间的 Colocate Join 关系。
diff --git a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/backup_restore.mdx b/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/backup_restore.mdx
deleted file mode 100644
index d62f8cd8f4d421..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-definition/backup_restore/backup_restore.mdx
+++ /dev/null
@@ -1,10 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['beifen']
----
-
-# 备份与恢复
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/ALTER_LOAD.md b/docs/zh/sql-reference/sql-statements/data-manipulation/ALTER_LOAD.md
deleted file mode 100644
index a2e670e30a8315..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/ALTER_LOAD.md
+++ /dev/null
@@ -1,43 +0,0 @@
----
-keywords: ['xiugai'] 
-displayed_sidebar: "Chinese"
----
-
-# ALTER LOAD
-
-## 功能
-
-修改 **QUEUEING** 或者 **LOADING** 状态的 Broker Load 作业的优先级。StarRocks 自 v2.5 版本起支持该命令。
-
-> **说明**
->
-> 修改处于 **LOADING** 状态的 Broker Load 作业的优先级不会对作业产生任何影响。
-
-## 语法
-
-```SQL
-ALTER LOAD FOR <label_name>
-PROPERTIES
-(
-    'priority'='{LOWEST | LOW | NORMAL | HIGH | HIGHEST}'
-)
-```
-
-## 参数说明
-
-| **参数**   | **是否必选** | **说明**                                                     |
-| ---------- | ------------ | ------------------------------------------------------------ |
-| label_name | 是           | 指定导入作业的标签。格式：`[<database_name>.]<label_name>`。参见 [BROKER LOAD](../data-manipulation/BROKER_LOAD.md#database_name-和-label_name)。 |
-| priority   | 是           | 指定导入作业的优先级。取值范围：`LOWEST`、`LOW`、`NORMAL`、`HIGH` 和 `HIGHEST`。参见 [BROKER LOAD](../data-manipulation/BROKER_LOAD.md#opt_properties)。 |
-
-## 示例
-
-假设您有一个标签为 `test_db.label1` 的 Broker Load 作业，且作业当前处于 **QUEUEING** 状态或者 **LOADING** 状态。如果您想尽快执行该作业，可以通过如下命令，把该作业的优先级改为 `HIGHEST`：
-
-```SQL
-ALTER LOAD FOR test_db.label1
-PROPERTIES
-(
-    'priority'='HIGHEST'
-);
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/ALTER_PIPE.md b/docs/zh/sql-reference/sql-statements/data-manipulation/ALTER_PIPE.md
deleted file mode 100644
index 86dbd5e2069f25..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/ALTER_PIPE.md
+++ /dev/null
@@ -1,55 +0,0 @@
----
-keywords: ['xiugai'] 
-displayed_sidebar: "Chinese"
----
-
-# ALTER PIPE
-
-## 功能
-
-修改 Pipe 的执行参数。该命令自 3.2 版本起支持。
-
-## 语法
-
-```SQL
-ALTER PIPE [db_name.]<pipe_name> 
-SET
-(
-    "<key>" = <value>[, "<key>" = "<value>" ...]
-) 
-```
-
-## 参数说明
-
-### db_name
-
-Pipe 所属的数据库的名称。
-
-### pipe_name
-
-Pipe 的名称。
-
-### **PROPERTIES**
-
-要修改的执行参数设置。格式：`"key" = "value"`。有关支持的执行参数，参见 [CREATE PIPE](../../../sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md)。
-
-## 示例
-
-修改数据库 `mydatabase` 下名为 `user_behavior_replica` 的 Pipe 的 `AUTO_INGEST` 属性为 `FALSE`：
-
-```SQL
-USE mydatabase;
-ALTER PIPE user_behavior_replica
-SET
-(
-    "AUTO_INGEST" = "FALSE"
-);
-```
-
-## 相关文档
-
-- [CREATE PIPE](../data-manipulation/CREATE_PIPE.md)
-- [DROP PIPE](../data-manipulation/DROP_PIPE.md)
-- [SHOW PIPES](../data-manipulation/SHOW_PIPES.md)
-- [SUSPEND or RESUME PIPE](../data-manipulation/SUSPEND_or_RESUME_PIPE.md)
-- [RETRY FILE](../data-manipulation/RETRY_FILE.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD.md b/docs/zh/sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD.md
deleted file mode 100644
index a8ffff70052549..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/ALTER_ROUTINE_LOAD.md
+++ /dev/null
@@ -1,131 +0,0 @@
----
-keywords: ['xiugai'] 
-displayed_sidebar: "Chinese"
----
-
-# ALTER ROUTINE LOAD
-
-import RoutineLoadPrivNote from '../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
-
-## 功能
-
-该语法用于修改 Routine Load 导入作业。注意，只能修改处于 `PAUSED` 状态的作业。您可以通过 [PAUSE ROUTINE LOAD](./PAUSE_ROUTINE_LOAD.md) 暂停 Routine Load 导入作业。
-
-修改成功后，您可以：
-
-- 通过 [SHOW ROUTINE LOAD](./SHOW_ROUTINE_LOAD.md) 检查修改后的作业详情。
-- 通过 [RESUME ROUTINE LOAD](./RESUME_ROUTINE_LOAD.md) 重启该导入作业。
-
-<RoutineLoadPrivNote />
-
-## **语法**
-
-```SQL
-ALTER ROUTINE LOAD FOR [db_name.]<job_name>
-[load_properties]
-[job_properties]
-FROM data_source
-[data_source_properties]
-```
-
-## 参数说明
-
-- **`[<db_name>.]<job_name>`**
-
-    指定要修改的作业名称。
-
-- **`load_properties`**
-
-    待导入的源数据信息。语法如下：
-
-    ```SQL
-    [COLUMNS TERMINATED BY '<column_separator>'],
-    [ROWS TERMINATED BY '<row_separator>'],
-    [COLUMNS ([<column_name> [, ...] ] [, column_assignment [, ...] ] )],
-    [WHERE <expr>],
-    [PARTITION ([ <partition_name> [, ...] ])]
-    [TEMPORARY PARTITION (<temporary_partition1_name>[,<temporary_partition2_name>,...])]
-    ```
-
-    详细的参数介绍，请参见 [CREATE ROUTINE LOAD](./CREATE_ROUTINE_LOAD.md#load_properties)。
-
-- **`job_properties`**
-
-  导入作业的属性。语法如下：
-
-  ```SQL
-  PROPERTIES ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
-  ```
-
-  目前仅支持修改如下属性：
-
-  - `desired_concurrent_number`
-
-  - `max_error_number`
-
-  - `max_batch_interval`
-
-  - `max_batch_rows`
-
-  - `max_batch_size`
-
-  - `jsonpaths`
-
-  - `json_root`
-
-  - `strip_outer_array`
-
-  - `strict_mode`
-
-  - `timezone`
-
-  详细的属性介绍，请参见 [CREATE ROUTINE LOAD](./CREATE_ROUTINE_LOAD.md#job_properties)。
-
-- **`data_source`** 和 **`data_source_properties`**
-
-  - **`data_source`**
-
-    必填，指定数据源，目前仅支持取值为 `KAFKA`。
-
-  - **`data_source_properties`**
-
-    数据源的相关属性。目前支持修改：
-
-    - `kafka_partitions` 和 `kafka_offsets`：需要注意的是，仅支持修改当前已经消费的 Kafka partition 的 offset，不支持新增 Kafka partition。
-    - `property.*`： 自定义的数据源 Kafka 相关参数，例如 `property.kafka_default_offsets`。
-
-## 示例
-
-1. 将导入作业的属性 `desired_concurrent_number` 调大至 `5`，以提高导入任务的并行度。任务的并行度的详细说明，参见[如何提高导入性能](../../../faq/loading/Routine_load_faq.md#1-如何提高导入性能)。
-
-    ```SQL
-    ALTER ROUTINE LOAD FOR example_tbl_ordertest
-    PROPERTIES
-    (
-        "desired_concurrent_number" = "5"
-    );
-    ```
-
-2. 同时修改导入作业的属性和数据源信息。
-
-    ```SQL
-    ALTER ROUTINE LOAD FOR example_tbl_ordertest
-    PROPERTIES
-    (
-        "desired_concurrent_number" = "5"
-    )
-    FROM KAFKA
-    (
-        "kafka_partitions" = "0, 1, 2",
-        "kafka_offsets" = "100, 200, 100",
-        "property.group.id" = "new_group"
-    );
-    ```
-
-3. 同时修改过滤条件和导入的目标 StarRocks 分区。
-
-    ```SQL
-    ALTER ROUTINE LOAD FOR example_tbl_ordertest
-    WHERE pay_dt < 2023-06-31
-    PARTITION (p202306);
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md b/docs/zh/sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md
deleted file mode 100644
index 1eee855e4621bd..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md
+++ /dev/null
@@ -1,1346 +0,0 @@
----
-displayed_sidebar: "Chinese"
-toc_max_heading_level: 5
----
-
-# BROKER LOAD
-
-## 功能
-
-Broker Load 是一种基于 MySQL 协议的异步导入方式。您提交导入作业以后，StarRocks 会异步地执行导入作业。您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持。有关 Broker Load 的背景信息、基本原理、支持的数据文件格式、如何执行单表导入 (Single-Table Load) 和多表导入 (Multi-Table Load) 操作、以及如何查看导入作业的结果等信息，请参见[从 HDFS 导入](../../../loading/hdfs_load.md)和[从云存储导入](../../../loading/cloud_storage_load.md)。
-
-> **注意**
->
-> Broker Load 操作需要目标表的 INSERT 权限。如果您的用户账号没有 INSERT 权限，请参考 [GRANT](../account-management/GRANT.md) 给用户赋权。
-
-## 语法
-
-```SQL
-LOAD LABEL [<database_name>.]<label_name>
-(
-    data_desc[, data_desc ...]
-)
-WITH BROKER
-(
-    StorageCredentialParams
-)
-[PROPERTIES
-(
-    opt_properties
-)
-]
-```
-
-注意在 StarRocks 中，部分文字是 SQL 语言的保留关键字，不能直接用于 SQL 语句。如果想在 SQL 语句中使用这些保留关键字，必须用反引号 (`) 包裹起来。参见[关键字](../keywords.md)。
-
-## 参数说明
-
-### database_name 和 label_name
-
-`label_name` 指定导入作业的标签。命名要求参见[系统限制](../../../reference/System_limit.md)。
-
-`database_name` 为可选，指定目标 StarRocks 表所在的数据库。
-
-每个导入作业都对应一个在该数据库内唯一的标签。通过标签，可以查看对应导入作业的执行情况，并防止导入相同的数据。导入作业的状态为 **FINISHED** 时，其标签不可再复用给其他导入作业。导入作业的状态为 **CANCELLED** 时，其标签可以复用给其他导入作业，但通常都是用来重试同一个导入作业（即使用同一个标签导入相同的数据）以实现数据“精确一次 (Exactly-Once)”语义。
-
-### data_desc
-
-用于描述一批次待导入的数据。每个 `data_desc` 声明了本批次待导入数据所属的数据源地址、ETL 函数、StarRocks 表和分区等信息。
-
-Broker Load 支持一次导入多个数据文件。在一个导入作业中，您可以使用多个 `data_desc` 来声明导入多个数据文件，也可以使用一个 `data_desc` 来声明导入一个路径下的所有数据文件。Broker Load 还支持保证单次导入事务的原子性，即单次导入的多个数据文件都成功或者都失败，而不会出现部分导入成功、部分导入失败的情况。
-
-`data_desc` 语法如下：
-
-```SQL
-DATA INFILE ("<file_path>"[, "<file_path>" ...])
-[NEGATIVE]
-INTO TABLE <table_name>
-[PARTITION (<partition1_name>[, <partition2_name> ...])]
-[TEMPORARY PARTITION (<temporary_partition1_name>[, <temporary_partition2_name> ...])]
-[COLUMNS TERMINATED BY "<column_separator>"]
-[ROWS TERMINATED BY "<row_separator>"]
-[FORMAT AS "CSV | Parquet | ORC"]
-[(format_type_options)]
-[(column_list)]
-[COLUMNS FROM PATH AS (<partition_field_name>[, <partition_field_name> ...])]
-[SET <k1=f1(v1)>[, <k2=f2(v2)> ...]]
-[WHERE predicate]
-```
-
-`data_desc` 中的必选参数如下：
-
-- `file_path`
-
-  用于指定源数据文件所在的路径。
-
-  您可以指定导入一个具体的数据文件。例如，通过指定 `"hdfs://<hdfs_host>:<hdfs_port>/user/data/tablename/20210411"` 可以匹配 HDFS 服务器上 `/user/data/tablename` 目录下名为 `20210411` 的数据文件。
-
-  您也可以用通配符指定导入某个路径下所有的数据文件。Broker Load 支持如下通配符：`?`、`*`、`[]`、`{}` 和 `^`。具体请参见[通配符使用规则参考](https://hadoop.apache.org/docs/stable/api/org/apache/hadoop/fs/FileSystem.html#globStatus-org.apache.hadoop.fs.Path-)。例如， 通过指定 `"hdfs://<hdfs_host>:<hdfs_port>/user/data/tablename/*/*"` 路径可以匹配 HDFS 服务器上 `/user/data/tablename` 目录下所有分区内的数据文件，通过 `"hdfs://<hdfs_host>:<hdfs_port>/user/data/tablename/dt=202104*/*"` 路径可以匹配 HDFS 服务器上 `/user/data/tablename` 目录下所有 `202104` 分区内的数据文件。
-
-  > **说明**
-  >
-  > 中间的目录也可以使用通配符匹配。
-
-  以 HDFS 数据源为例，文件路径中的 `hdfs_host` 和 `hdfs_port` 参数说明如下：
-
-  - `hdfs_host`：HDFS 集群中 NameNode 所在主机的 IP 地址。
-  - `hdfs_port`：HDFS 集群中 NameNode 所在主机的 FS 端口。默认端口号为 `9000`。
-
-  > **注意**
-  >
-  > - Broker Load 支持通过 S3 或 S3A 协议访问 AWS S3，因此从 AWS S3 导入数据时，您在文件路径中传入的目标文件的 S3 URI 可以使用 `s3://` 或 `s3a://` 作为前缀。
-  > - 由于 Broker Load 只支持通过 gs 协议访问 Google GCS，因此当从 Google GCS 导入数据时，必须确保文件路径传入的目标文件的 GCS URI 使用 `gs://` 为前缀。
-  > - 从 Blob Storage 导入数据时，需要使用 wasb 或 wasbs 作为文件协议访问目标数据：
-  >   - 如果您的存储账号支持通过 HTTP 协议进行访问，请使用 wasb 文件协议，文件路径格式为 `wasb://<container_name>@<storage_account_name>.blob.core.windows.net/<path>/<file_name>/*`。
-  >   - 如果您的存储账号支持通过 HTTPS 协议进行访问，请使用 wasbs 文件协议，文件路径格式为 `wasbs://<container_name>@<storage_account_name>.blob.core.windows.net/<path>/<file_name>/*`。
-  > - 从 Data Lake Storage Gen2 导入数据时，需要使用 abfs 或 abfss 作为文件协议访问目标数据：
-  >   - 如果您的存储账号支持通过 HTTP 协议进行访问，请使用 abfs 文件协议，文件路径格式为 `abfs://<container_name>@<storage_account_name>.dfs.core.windows.net/<file_name>`。
-  >   - 如果您的存储账号支持通过 HTTPS 协议进行访问，请使用 abfss 文件协议，文件路径格式为 `abfss://<container_name>@<storage_account_name>.dfs.core.windows.net/<file_name>`。
-  > - 从 Azure Data Lake Storage Gen1 导入数据时，需要使用 adl 作为文件协议访问目标数据，文件路径格式为 `adl://<data_lake_storage_gen1_name>.azuredatalakestore.net/<path>/<file_name>`。
-  
-- `INTO TABLE`
-
-  用于指定目标 StarRocks 表的名称。
-
-`data_desc` 中的可选参数如下：
-
-- `NEGATIVE`
-
-  用于撤销某一批已经成功导入的数据。如果想要撤销某一批已经成功导入的数据，可以通过指定 `NEGATIVE` 关键字来导入同一批数据。
-
-  > **说明**
-  >
-  > 该参数仅适用于目标 StarRocks 表使用聚合表、并且所有 Value 列的聚合函数均为 `sum` 的情况。
-
-- `PARTITION`
-
-  指定要把数据导入哪些分区。如果不指定该参数，则默认导入到 StarRocks 表所在的所有分区中。
-
-- `TEMPORARY_PARTITION`
-
-  指定要把数据导入哪些[临时分区](../../../table_design/Temporary_partition.md)。
-
-- `COLUMNS TERMINATED BY`
-
-  用于指定源数据文件中的列分隔符。如果不指定该参数，则默认列分隔符为 `\t`，即 Tab。必须确保这里指定的列分隔符与源数据文件中的列分隔符一致；否则，导入作业会因数据质量错误而失败，作业状态 (`State`) 会显示为 `CANCELLED`。
-
-  需要注意的是，Broker Load 通过 MySQL 协议提交导入请求，除了 StarRocks 会做转义处理以外，MySQL 协议也会做转义处理。因此，如果列分隔符是 Tab 等不可见字符，则需要在列分隔字符前面多加一个反斜线 (\\)。例如，如果列分隔符是 `\t`，这里必须输入 `\\t`；如果列分隔符是 `\n`，这里必须输入 `\\n`。Apache Hive™ 文件的列分隔符为 `\x01`，因此，如果源数据文件是 Hive 文件，这里必须传入 `\\x01`。
-
-  > **说明**
-  >
-  > - StarRocks 支持设置长度最大不超过 50 个字节的 UTF-8 编码字符串作为列分隔符，包括常见的逗号 (,)、Tab 和 Pipe (|)。
-  > - 空值 (null) 用 `\N` 表示。比如，数据文件一共有三列，其中某行数据的第一列、第三列数据分别为 `a` 和 `b`，第二列没有数据，则第二列需要用 `\N` 来表示空值，写作 `a,\N,b`，而不是 `a,,b`。`a,,b` 表示第二列是一个空字符串。
-
-- `ROWS TERMINATED BY`
-
-  用于指定源数据文件中的行分隔符。如果不指定该参数，则默认行分隔符为 `\n`，即换行符。必须确保这里指定的行分隔符与源数据文件中的行分隔符一致；否则，导入作业会因数据质量错误而失败，作业状态 (`State`) 会显示为 `CANCELLED`。该参数从 2.5.4 版本开始支持。
-
-  其他注意事项和使用条件与上文通过 `COLUMNS TERMINATED BY` 指定列分隔符相同。
-
-- `FORMAT AS`
-
-  用于指定源数据文件的格式。取值包括 `CSV`、`Parquet` 和 `ORC`。如果不指定该参数，则默认通过 `file_path` 参数中指定的文件扩展名（**.csv**、**.parquet**、和 **.orc**）来判断文件格式。
-
-- `format_type_options`
-
-  `FORMAT AS` 设置为 `CSV` 时用于指定 CSV 格式选项。语法如下：
-
-  ```JSON
-  (
-      key = value
-      key = value
-      ...
-  )
-  ```
-  
-  > **说明**
-  >
-  > `format_type_options` 在 3.0 及以后版本支持。
-
-  选项说明见下表。
-  
-  | **参数**    | **说明**                                                     |
-  | ----------- | ------------------------------------------------------------ |
-  | skip_header | 用于指定跳过 CSV 文件最开头的几行数据。取值类型：INTEGER。默认值：`0`。<br />在某些 CSV 文件里，最开头的几行数据会用来定义列名、列类型等元数据信息。通过设置该参数，可以使 StarRocks 在导入数据时忽略 CSV 文件的前面几行。例如，如果设置该参数为 `1`，则 StarRocks 会在导入数据时忽略 CSV 文件的第一行。<br />这里的行所使用的分隔符须与您在导入语句中所设定的行分隔符一致。 |
-  | trim_space  | 用于指定是否去除 CSV 文件中列分隔符前后的空格。取值类型：BOOLEAN。默认值：`false`。<br />有些数据库在导出数据为 CSV 文件时，会在列分隔符的前后添加一些空格。根据位置的不同，这些空格可以称为“前导空格”或者“尾随空格”。通过设置该参数，可以使 StarRocks 在导入数据时删除这些不必要的空格。<br />需要注意的是，StarRocks 不会去除被 `enclose` 指定字符括起来的字段内的空格（包括字段的前导空格和尾随空格）。例如，列分隔符是竖线 (<code class="language-text">&#124;</code>)，`enclose` 指定的字符是双引号 (`"`)：<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124; "Love StarRocks" &#124;</code> <br />如果设置 `trim_space` 为 `true`，则 StarRocks 处理后的结果数据如下：<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> |
-  | enclose     | 根据 [RFC4180](https://www.rfc-editor.org/rfc/rfc4180)，用于指定把 CSV 文件中的字段括起来的字符。取值类型：单字节字符。默认值：`NONE`。最常用 `enclose` 字符为单引号 (`'`) 或双引号 (`"`)。<br />被 `enclose` 指定字符括起来的字段内的所有特殊字符（包括行分隔符、列分隔符等）均看做是普通符号。比 RFC4180 标准更进一步的是，StarRocks 提供的 `enclose` 属性支持设置任意单个字节的字符。<br />如果一个字段内包含了 `enclose` 指定字符，则可以使用同样的字符对 `enclose` 指定字符进行转义。例如，在设置了`enclose` 为双引号 (`"`) 时，字段值 `a "quoted" c` 在 CSV 文件中应该写作 `"a ""quoted"" c"`。 |
-  | escape      | 指定用于转义的字符。用来转义各种特殊字符，比如行分隔符、列分隔符、转义符、`enclose` 指定字符等，使 StarRocks 把这些特殊字符当做普通字符而解析成字段值的一部分。取值类型：单字节字符。默认值：`NONE`。最常用的 `escape` 字符为斜杠 (`\`)，在 SQL 语句中应该写作双斜杠 (`\\`)。<br />**说明**<br />`escape` 指定字符同时作用于 `enclose` 指定字符的内部和外部。<br />以下为两个示例：<ul><li>当设置 `enclose` 为双引号 (`"`) 、`escape` 为斜杠 (`\`) 时，StarRocks 会把 `"say \"Hello world\""` 解析成一个字段值 `say "Hello world"`。</li><li>假设列分隔符为逗号 (`,`) ，当设置 `escape` 为斜杠 (`\`) ，StarRocks 会把 `a, b\, c` 解析成 `a` 和 `b, c` 两个字段值。</li></ul> |
-
-- `column_list`
-
-  用于指定源数据文件和 StarRocks 表之间的列对应关系。语法如下：`(<column_name>[, <column_name> ...])`。`column_list` 中声明的列与 StarRocks 表中的列按名称一一对应。
-
-  > **说明**
-  >
-  > 如果源数据文件的列和 StarRocks 表中的列按顺序一一对应，则不需要指定 `column_list` 参数。
-
-  如果要跳过源数据文件中的某一列，只需要在 `column_list` 参数中将该列命名为 StarRocks 表中不存在的列名即可。具体请参见[导入过程中实现数据转换](../../../loading/Etl_in_loading.md)。
-
-- `COLUMNS FROM PATH AS`
-
-  用于从指定的文件路径中提取一个或多个分区字段的信息。该参数仅当指定的文件路径中存在分区字段时有效。
-
-  例如，源数据文件所在的路径为 `/path/col_name=col_value/file1`，其中 `col_name` 可以对应到 StarRocks 表中的列。这时候，您可以设置参数为 `col_name`。导入时，StarRocks 会将 `col_value` 落入 `col_name` 对应的列中。
-
-  > **说明**
-  >
-  > 该参数只有在从 HDFS 导入数据时可用。
-
-- `SET`
-
-  用于将源数据文件的某一列按照指定的函数进行转化，然后将转化后的结果落入 StarRocks 表中。语法如下：`column_name = expression`。以下为两个示例：
-
-  - StarRocks 表中有三列，按顺序依次为 `col1`、`col2` 和 `col3`；源数据文件中有四列，前两列按顺序依次对应 StarRocks 表中的 `col1`、`col2` 列，后两列之和对应 StarRocks 表中的 `col3` 列。这种情况下，需要通过 `column_list` 参数声明 `(col1,col2,tmp_col3,tmp_col4)`，并使用 SET 子句指定 `SET (col3=tmp_col3+tmp_col4)` 来实现数据转换。
-  - StarRocks 表中有三列，按顺序依次为 `year`、`month` 和 `day`；源数据文件中只有一个包含时间数据的列，格式为 `yyyy-mm-dd hh:mm:ss`。这种情况下，需要通过 `column_list` 参数声明 `(tmp_time)`、并使用 SET 子句指定 `SET (year = year(tmp_time), month=month(tmp_time), day=day(tmp_time))` 来实现数据转换。
-
-- `WHERE`
-
-  用于指定过滤条件，对做完转换的数据进行过滤。只有符合 WHERE 子句中指定的过滤条件的数据才会导入到 StarRocks 表中。
-
-### WITH BROKER
-
-自 v2.5 起，您不再需要指定 `broker_name`，但继续保留 `WITH BROKER` 关键字。
-
-### StorageCredentialParams
-
-StarRocks 访问存储系统的认证配置。
-
-#### HDFS
-
-社区版 HDFS 支持简单认证和 Kerberos 认证两种认证方式（Broker Load 默认使用简单认证），并且支持 NameNode 节点的 HA 配置。如果存储系统为社区版 HDFS，您可以按如下指定认证方式和 HA 配置：
-
-- 认证方式
-
-  - 如果使用简单认证，请按如下配置 `StorageCredentialParams`：
-
-    ```Plain
-    "hadoop.security.authentication" = "simple",
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-    ```
-
-    `StorageCredentialParams` 包含如下参数。
-
-    | **参数名称**                     | **参数说明**                                 |
-    | ------------------------------- | -------------------------------------------- |
-    | hadoop.security.authentication  | 指定认证方式。取值范围：`simple` 和 `kerberos`。默认值：`simple`。`simple` 表示简单认证，即无认证。`kerberos` 表示 Kerberos 认证。 |
-    | username                        | 用于访问 HDFS 集群中 NameNode 节点的用户名。 |
-    | password                        | 用于访问 HDFS 集群中 NameNode 节点的密码。   |
-
-  - 如果使用 Kerberos 认证，请按如下配置 `StorageCredentialParams`：
-
-    ```Plain
-    "hadoop.security.authentication" = "kerberos",
-    "kerberos_principal" = "nn/zelda1@ZELDA.COM",
-    "kerberos_keytab" = "/keytab/hive.keytab",
-    "kerberos_keytab_content" = "YWFhYWFh"
-    ```
-
-    `StorageCredentialParams` 包含如下参数。
-
-    | **参数名称**                     | **参数说明**                                                 |
-    | ------------------------------- | ------------------------------------------------------------ |
-    | hadoop.security.authentication  | 指定认证方式。取值范围：`simple` 和 `kerberos`。默认值：`simple`。`simple` 表示简单认证，即无认证。`kerberos` 表示 Kerberos 认证。 |
-    | kerberos_principal              | 用于指定 Kerberos 的用户或服务 (Principal)。每个 Principal 在 HDFS 集群内唯一，由如下三部分组成：<ul><li>`username` 或 `servicename`：HDFS 集群中用户或服务的名称。</li><li>`instance`：HDFS 集群要认证的节点所在服务器的名称，用来保证用户或服务全局唯一。比如，HDFS 集群中有多个 DataNode 节点，各节点需要各自独立认证。</li><li>`realm`：域，必须全大写。</li></ul>举例：`nn/zelda1@ZELDA.COM`。 |
-    | kerberos_keytab                 | 用于指定 Kerberos 的 Key Table（简称为“keytab”）文件的路径。 |
-    | kerberos_keytab_content         | 用于指定 Kerberos 中 keytab 文件的内容经过 Base64 编码之后的内容。该参数跟 `kerberos_keytab` 参数二选一配置。 |
-
-- HA 配置
-
-  可以为 HDFS 集群中的 NameNode 节点配置 HA 机制，从而确保发生 NameNode 节点切换时，StarRocks 能够自动识别新切换到的 NameNode 节点，包括如下几种场景：
-
-  - 在单 HDFS 集群、并且配置了单 Kerberos 用户的场景下，可以采用有 Broker 的导入，也可以采用无 Broker 的导入。
-  
-    - 如果采用有 Broker 的导入，您需要确保至少部署了一组独立的 Broker，并将 `hdfs-site.xml` 文件放在 HDFS 集群对应的 Broker 节点的 `{deploy}/conf` 目录下。Broker 进程重启时，会将 `{deploy}/conf` 目录添加到 `CLASSPATH` 环境变量，使 Broker 能够读取 HDFS 集群中各节点的信息。
-  
-    - 如果采用无 Broker 的导入，您需要将 `hdfs-site.xml` 文件放在每个 FE 节点和每个 BE（或 CN）节点的 `{deploy}/conf` 目录下。
-
-  - 在单 HDFS 集群、并且配置了多 Kerberos 用户的场景下，只支持有 Broker 的导入。您需要确保至少部署了一组独立的 Broker，并将 `hdfs-site.xml` 文件放在 HDFS 集群对应的 Broker 节点的 `{deploy}/conf` 目录下。Broker 进程重启时，会将 `{deploy}/conf` 目录添加到 `CLASSPATH` 环境变量，使 Broker 能够读取 HDFS 集群中各节点的信息。
-
-  - 在多 HDFS 集群场景下（不管是单 Kerberos 用户、还是多 Kerberos 用户），只支持有 Broker 的导入。您需要确保至少部署了一组独立的 Broker，并且采取如下方法之一来配置 Broker 读取 HDFS 集群中各节点的信息：
-  
-    - 将 `hdfs-site.xml` 文件放在每个 HDFS 集群对应的 Broker 节点的 `{deploy}/conf` 目录下。Broker 进程重启时，会将 `{deploy}/conf` 目录添加到 `CLASSPATH` 环境变量，使 Broker 能够读取 HDFS 集群中各节点的信息。
-    - 在创建 Broker Load 作业时增加如下 HA 配置：
-
-      ```Plain
-      "dfs.nameservices" = "ha_cluster",
-      "dfs.ha.namenodes.ha_cluster" = "ha_n1,ha_n2",
-      "dfs.namenode.rpc-address.ha_cluster.ha_n1" = "<hdfs_host>:<hdfs_port>",
-      "dfs.namenode.rpc-address.ha_cluster.ha_n2" = "<hdfs_host>:<hdfs_port>",
-      "dfs.client.failover.proxy.provider" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
-      ```
-
-      上述配置中的参数说明如下表所述：
-
-      | **参数名称**                         | **参数说明**                                                 |
-      | ------------------------------------------------------- | --------------------------- |
-      | dfs.nameservices                  | 自定义 HDFS 集群的名称。                                     |
-      | dfs.ha.namenodes.XXX              | 自定义 NameNode 的名称，多个名称以逗号 (,) 分隔，双引号内不允许出现空格。  <br />其中 `xxx` 为 `dfs.nameservices` 中自定义的HDFS 服务的名称。 |
-      | dfs.namenode.rpc-address.XXX.NN    | 指定 NameNode 的 RPC 地址信息。  <br />其中 `NN` 表示 `dfs.ha.namenodes.XXX` 中自定义 NameNode 的名称。 |
-      | dfs.client.failover.proxy.provider | 指定客户端连接的 NameNode 的提供者，默认为 `org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider`。 |
-
-  > **说明**
-  >
-  > 您可以通过 [SHOW BROKER](../Administration/SHOW_BROKER.md) 语句来查看 StarRocks 集群中已经部署的 Broker。
-
-#### AWS S3
-
-如果存储系统为 AWS S3，请按如下配置 `StorageCredentialParams`：
-
-- 基于 Instance Profile 进行认证和鉴权
-
-  ```SQL
-  "aws.s3.use_instance_profile" = "true",
-  "aws.s3.region" = "<aws_s3_region>"
-  ```
-
-- 基于 Assumed Role 进行认证和鉴权
-
-  ```SQL
-  "aws.s3.use_instance_profile" = "true",
-  "aws.s3.iam_role_arn" = "<iam_role_arn>",
-  "aws.s3.region" = "<aws_s3_region>"
-  ```
-
-- 基于 IAM User 进行认证和鉴权
-
-  ```SQL
-  "aws.s3.use_instance_profile" = "false",
-  "aws.s3.access_key" = "<iam_user_access_key>",
-  "aws.s3.secret_key" = "<iam_user_secret_key>",
-  "aws.s3.region" = "<aws_s3_region>"
-  ```
-
-`StorageCredentialParams` 包含如下参数。
-
-| 参数                        | 是否必须   | 说明                                                         |
-| --------------------------- | -------- | ------------------------------------------------------------ |
-| aws.s3.use_instance_profile | 是       | 指定是否开启 Instance Profile 和 Assumed Role 两种鉴权方式。取值范围：`true` 和 `false`。默认值：`false`。 |
-| aws.s3.iam_role_arn         | 否       | 有权限访问 AWS S3 Bucket 的 IAM Role 的 ARN。采用 Assumed Role 鉴权方式访问 AWS S3 时，必须指定此参数。 |
-| aws.s3.region               | 是       | AWS S3 Bucket 所在的地域。示例：`us-west-1`。                |
-| aws.s3.access_key           | 否       | IAM User 的 Access Key。采用 IAM User 鉴权方式访问 AWS S3 时，必须指定此参数。 |
-| aws.s3.secret_key           | 否       | IAM User 的 Secret Key。采用 IAM User 鉴权方式访问 AWS S3 时，必须指定此参数。 |
-
-有关如何选择用于访问 AWS S3 的鉴权方式、以及如何在 AWS IAM 控制台配置访问控制策略，参见[访问 AWS S3 的认证参数](../../../integrations/authenticate_to_aws_resources.md#访问-aws-s3-的认证参数)。
-
-#### Google GCS
-
-如果存储系统为 Google GCS，请按如下配置 `StorageCredentialParams`：
-
-- 基于 VM 进行认证和鉴权
-
-  ```SQL
-  "gcp.gcs.use_compute_engine_service_account" = "true"
-  ```
-
-  `StorageCredentialParams` 包含如下参数。
-
-  | **参数**                                   | **默认值** | **取值样例** | **说明**                                                 |
-  | ------------------------------------------ | ---------- | ------------ | -------------------------------------------------------- |
-  | gcp.gcs.use_compute_engine_service_account | false      | true         | 是否直接使用 Compute Engine 上面绑定的 Service Account。 |
-
-- 基于 Service Account 号进行认证和鉴权
-
-  ```SQL
-  "gcp.gcs.service_account_email" = "<google_service_account_email>",
-  "gcp.gcs.service_account_private_key_id" = "<google_service_private_key_id>",
-  "gcp.gcs.service_account_private_key" = "<google_service_private_key>"
-  ```
-
-  `StorageCredentialParams` 包含如下参数。
-
-  | **参数**                               | **默认值** | **取值样例**                                                 | **说明**                                                     |
-  | -------------------------------------- | ---------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
-  | gcp.gcs.service_account_email          | ""         | `"user@hello.iam.gserviceaccount.com"` | 创建 Service Account 时生成的 JSON 文件中的 Email。          |
-  | gcp.gcs.service_account_private_key_id | ""         | "61d257bd8479547cb3e04f0b9b6b9ca07af3b7ea"                   | 创建 Service Account 时生成的 JSON 文件中的 Private Key ID。 |
-  | gcp.gcs.service_account_private_key    | ""         | "-----BEGIN PRIVATE KEY----xxxx-----END PRIVATE KEY-----\n"  | 创建 Service Account 时生成的 JSON 文件中的 Private Key。    |
-
-- 基于 Impersonation 进行认证和鉴权
-
-  - 使用 VM 实例模拟 Service Account
-
-    ```SQL
-    "gcp.gcs.use_compute_engine_service_account" = "true",
-    "gcp.gcs.impersonation_service_account" = "<assumed_google_service_account_email>"
-    ```
-
-    `StorageCredentialParams` 包含如下参数。
-
-    | **参数**                                   | **默认值** | **取值样例** | **说明**                                                     |
-    | ------------------------------------------ | ---------- | ------------ | ------------------------------------------------------------ |
-    | gcp.gcs.use_compute_engine_service_account | false      | true         | 是否直接使用 Compute Engine 上面绑定的 Service Account。     |
-    | gcp.gcs.impersonation_service_account      | ""         | "hello"      | 需要模拟的目标 Service Account。 |
-
-  - 使用一个 Service Account（即“Meta Service Account”）模拟另一个 Service Account（即“Data Service Account”）
-
-    ```SQL
-    "gcp.gcs.service_account_email" = "<google_service_account_email>",
-    "gcp.gcs.service_account_private_key_id" = "<meta_google_service_account_email>",
-    "gcp.gcs.service_account_private_key" = "<meta_google_service_account_email>",
-    "gcp.gcs.impersonation_service_account" = "<data_google_service_account_email>"
-    ```
-
-    `StorageCredentialParams` 包含如下参数。
-
-    | **参数**                               | **默认值** | **取值样例**                                                 | **说明**                                                     |
-    | -------------------------------------- | ---------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
-    | gcp.gcs.service_account_email          | ""         | `"user@hello.iam.gserviceaccount.com"` | 创建 Meta Service Account 时生成的 JSON 文件中的 Email。     |
-    | gcp.gcs.service_account_private_key_id | ""         | "61d257bd8479547cb3e04f0b9b6b9ca07af3b7ea"                   | 创建 Meta Service Account 时生成的 JSON 文件中的 Private Key ID。 |
-    | gcp.gcs.service_account_private_key    | ""         | "-----BEGIN PRIVATE KEY----xxxx-----END PRIVATE KEY-----\n"  | 创建 Meta Service Account 时生成的 JSON 文件中的 Private Key。 |
-    | gcp.gcs.impersonation_service_account  | ""         | "hello"                                                      | 需要模拟的目标 Data Service Account。 |
-
-#### 阿里云 OSS
-
-如果存储系统为阿里云 OSS，请按如下配置 `StorageCredentialParams`：
-
-```SQL
-"fs.oss.accessKeyId" = "<oss_access_key>",
-"fs.oss.accessKeySecret" = "<oss_secret_key>",
-"fs.oss.endpoint" = "<oss_endpoint>"
-```
-
-`StorageCredentialParams` 包含如下参数。
-
-| **参数名称**           | **参数说明**                                                 |
-| ---------------------- | ------------------------------------------------------------ |
-| fs.oss.accessKeyId     | 访问阿里云 OSS 存储空间的 AccessKey ID，用于标识用户。           |
-| fs.oss.accessKeySecret | 访问阿里云 OSS 存储空间的 AccessKey Secret，是用于加密签名字符串和 OSS 用来验证签名字符串的密钥。 |
-| fs.oss.endpoint        | 访问阿里云 OSS 存储空间的连接地址。                              |
-
-请参见阿里云官方文档[用户签名验证](https://help.aliyun.com/document_detail/31950.html)。
-
-#### 腾讯云 COS
-
-如果存储系统为腾讯云 COS，请按如下配置 `StorageCredentialParams`：
-
-```SQL
-"fs.cosn.userinfo.secretId" = "<cos_access_key>",
-"fs.cosn.userinfo.secretKey" = "<cos_secret_key>",
-"fs.cosn.bucket.endpoint_suffix" = "<cos_endpoint>"
-```
-
-`StorageCredentialParams` 包含如下参数。
-
-| **参数名称**                   | **参数说明**                                                 |
-| ------------------------------ | ------------------------------------------------------------ |
-| fs.cosn.userinfo.secretId      | 访问腾讯云 COS 存储空间的 SecretId，用于标识 API 调用者的身份。  |
-| fs.cosn.userinfo.secretKey     | 访问腾讯云 COS 存储空间的 SecretKey，是用于加密签名字符串和服务端验证签名字符串的密钥。 |
-| fs.cosn.bucket.endpoint_suffix | 访问腾讯云 COS 存储空间的连接地址。                              |
-
-请参见腾讯云官方文档[使用永久密钥访问 COS](https://cloud.tencent.com/document/product/436/68282)。
-
-#### 华为云 OBS
-
-如果存储系统为华为云 OBS，请按如下配置 `StorageCredentialParams`：
-
-```SQL
-"fs.obs.access.key" = "<obs_access_key>",
-"fs.obs.secret.key" = "<obs_secret_key>",
-"fs.obs.endpoint" = "<obs_endpoint>"
-```
-
-`StorageCredentialParams` 包含如下参数。
-
-| **参数名称**           | **参数说明**                                                 |
-| ---------------------- | ------------------------------------------------------------ |
-| fs.obs.access.key      | 访问华为云 OBS 存储空间的 Access Key ID，与私有访问密钥关联的唯一标识符。|
-| fs.obs.secret.key      | 访问华为云 OBS 存储空间的 Secret Access Key，对请求进行加密签名，可标识发送方，并防止请求被修改。 |
-| fs.obs.endpoint        | 访问华为云 OBS 存储空间的连接地址。                              |
-
-请参见华为云官方文档[通过永久访问密钥访问 OBS](https://support.huaweicloud.com/perms-cfg-obs/obs_40_0007.html)。
-
-> **说明**
->
-> 使用 Broker Load 从华为云 OBS 导入数据时，需要先下载[依赖库](https://github.com/huaweicloud/obsa-hdfs/releases/download/v45/hadoop-huaweicloud-2.8.3-hw-45.jar)添加到 **$BROKER_HOME/lib/** 路径下并重启 Broker。
-
-#### 其他兼容 S3 协议的对象存储
-
-如果存储系统为其他兼容 S3 协议的对象存储（如 MinIO），请按如下配置 `StorageCredentialParams`：
-
-```SQL
-"aws.s3.enable_ssl" = "false",
-"aws.s3.enable_path_style_access" = "true",
-"aws.s3.endpoint" = "<s3_endpoint>",
-"aws.s3.access_key" = "<iam_user_access_key>",
-"aws.s3.secret_key" = "<iam_user_secret_key>"
-```
-
-`StorageCredentialParams` 包含如下参数。
-
-| 参数                            | 是否必须 | 描述                                                         |
-| ------------------------------- | -------- | ------------------------------------------------------------ |
-| aws.s3.enable_ssl               | 是       | 是否开启 SSL 连接。取值范围：`true` 和 `false`。默认值：`true`。对于 MinIO，必须设置为 `true`。 |
-| aws.s3.enable_path_style_access | 是       | 是否开启路径类型 URL 访问 (Path-Style URL Access)。取值范围：`true` 和 `false`。默认值：`false`。 |
-| aws.s3.endpoint                 | 是       | 用于访问兼容 S3 协议的对象存储的 Endpoint。                         |
-| aws.s3.access_key               | 是       | IAM User 的 Access Key。                                     |
-| aws.s3.secret_key               | 是       | IAM User 的 Secret Key。                                     |
-
-#### Microsoft Azure Storage
-
-##### Azure Blob Storage
-
-如果存储系统为 Blob Storage，请按如下配置 `StorageCredentialParams`：
-
-- 基于 Shared Key 进行认证和鉴权
-
-  ```SQL
-  "azure.blob.storage_account" = "<storage_account_name>",
-  "azure.blob.shared_key" = "<storage_account_shared_key>"
-  ```
-
-  `StorageCredentialParams` 包含如下参数。
-
-  | **参数**                   | **是否必须** | **说明**                         |
-  | -------------------------- | ------------ | -------------------------------- |
-  | azure.blob.storage_account | 是           | Blob Storage 账号的用户名。      |
-  | azure.blob.shared_key      | 是           | Blob Storage 账号的 Shared Key。 |
-
-- 基于 SAS Token 进行认证和鉴权
-
-  ```SQL
-  "azure.blob.storage_account" = "<storage_account_name>",
-  "azure.blob.container" = "<container_name>",
-  "azure.blob.sas_token" = "<storage_account_SAS_token>"
-  ```
-
-  `StorageCredentialParams` 包含如下参数。
-
-  | **参数**                  | **是否必须** | **说明**                                 |
-  | ------------------------- | ------------ | ---------------------------------------- |
-  | azure.blob.storage_account| 是           | Blob Storage 账号的用户名。              |
-  | azure.blob.container      | 是           | 用于存储数据的 Blob 容器的名称。         |
-  | azure.blob.sas_token      | 是           | 用于访问 Blob Storage 账号的 SAS Token。 |
-
-##### Azure Data Lake Storage Gen2
-
-如果存储系统为 Data Lake Storage Gen2，请按如下配置 `StorageCredentialParams`：
-
-- 基于 Managed Identity 进行认证和鉴权
-
-  ```SQL
-  "azure.adls2.oauth2_use_managed_identity" = "true",
-  "azure.adls2.oauth2_tenant_id" = "<service_principal_tenant_id>",
-  "azure.adls2.oauth2_client_id" = "<service_client_id>"
-  ```
-
-  `StorageCredentialParams` 包含如下参数。
-
-  | **参数**                                | **是否必须** | **说明**                                                |
-  | --------------------------------------- | ------------ | ------------------------------------------------------- |
-  | azure.adls2.oauth2_use_managed_identity | 是           | 指定是否开启 Managed Identity 鉴权方式。设置为 `true`。 |
-  | azure.adls2.oauth2_tenant_id            | 是           | 数据所属的 Tenant 的 ID。                               |
-  | azure.adls2.oauth2_client_id            | 是           | Managed Identity 的 Client (Application) ID。           |
-
-- 基于 Shared Key 进行认证和鉴权
-
-  ```SQL
-  "azure.adls2.storage_account" = "<storage_account_name>",
-  "azure.adls2.shared_key" = "<storage_account_shared_key>"
-  ```
-
-  `StorageCredentialParams` 包含如下参数。
-
-  | **参数**                    | **是否必须** | **说明**                                   |
-  | --------------------------- | ------------ | ------------------------------------------ |
-  | azure.adls2.storage_account | 是           | Data Lake Storage Gen2 账号的用户名。      |
-  | azure.adls2.shared_key      | 是           | Data Lake Storage Gen2 账号的 Shared Key。 |
-
-- 基于 Service Principal 进行认证和鉴权
-
-  ```SQL
-  "azure.adls2.oauth2_client_id" = "<service_client_id>",
-  "azure.adls2.oauth2_client_secret" = "<service_principal_client_secret>",
-  "azure.adls2.oauth2_client_endpoint" = "<service_principal_client_endpoint>"
-  ```
-
-  `StorageCredentialParams` 包含如下参数。
-
-  | **参数**                           | **是否必须** | **说明**                                                     |
-  | ---------------------------------- | ------------ | ------------------------------------------------------------ |
-  | azure.adls2.oauth2_client_id       | 是           | Service Principal 的 Client (Application) ID。               |
-  | azure.adls2.oauth2_client_secret   | 是           | 新建 Client (Application) Secret。                           |
-  | azure.adls2.oauth2_client_endpoint | 是           | Service Principal 或 Application 的 OAuth 2.0 Token Endpoint (v1)。 |
-
-##### Azure Data Lake Storage Gen1
-
-如果存储系统为 Data Lake Storage Gen1，请按如下配置 `StorageCredentialParams`：
-
-- 基于 Managed Service Identity 进行认证和鉴权
-
-  ```SQL
-  "azure.adls1.use_managed_service_identity" = "true"
-  ```
-
-  `StorageCredentialParams` 包含如下参数。
-
-  | **参数**                                 | **是否必须** | **说明**                                                     |
-  | ---------------------------------------- | ------------ | ------------------------------------------------------------ |
-  | azure.adls1.use_managed_service_identity | 是           | 指定是否开启 Managed Service Identity 鉴权方式。设置为 `true`。 |
-
-- 基于 Service Principal 进行认证和鉴权
-
-  ```SQL
-  "azure.adls1.oauth2_client_id" = "<application_client_id>",
-  "azure.adls1.oauth2_credential" = "<application_client_credential>",
-  "azure.adls1.oauth2_endpoint" = "<OAuth_2.0_authorization_endpoint_v2>"
-  ```
-
-  `StorageCredentialParams` 包含如下参数。
-
-  | **参数**                      | **是否必须** | **说明**                                                     |
-  | ----------------------------- | ------------ | ------------------------------------------------------------ |
-  | azure.adls1.oauth2_client_id  | 是           | Service Principal 的 Client (Application) ID。               |
-  | azure.adls1.oauth2_credential | 是           | 新建 Client (Application) Secret。                           |
-  | azure.adls1.oauth2_endpoint   | 是           | Service Principal 或 Application 的 OAuth 2.0 Token Endpoint (v1)。 |
-
-### opt_properties
-
-用于指定一些导入相关的可选参数，指定的参数设置作用于整个导入作业。语法如下：
-
-```Plain
-PROPERTIES ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
-```
-
-参数说明如下：
-
-- `timeout`
-
-  导入作业的超时时间。单位：秒。默认超时时间为 4 小时。建议超时时间小于 6 小时。如果导入作业在设定的时限内未完成，会自动取消，变成 **CANCELLED** 状态。
-
-  > **说明**
-  >
-  > 通常情况下，您不需要手动设置导入作业的超时时间。只有当导入作业无法在默认的超时时间内完成时，才推荐您手动设置导入作业的超时时间。
-
-  推荐超时时间大于下面公式的计算值：
-
-  **超时时间 > (源数据文件的总大小 x 源数据文件及相关物化视图的个数)/平均导入速度**
-
-    > **说明**
-    >
-    > “平均导入速度”是指目前 StarRocks 集群的平均导入速度。由于每个 StarRocks 集群的机器环境不同、且集群允许的并发查询任务数也不同，因此，StarRocks 集群的平均导入速度需要根据历史导入速度进行推测。
-
-   例如，要导入一个 1 GB 的数据文件，该数据文件包含 2 个物化视图，当前 StarRocks 集群的平均导入速度为 10 MB/s。在这种情况下，根据公式计算出来时长为 102 秒：
-
-   **(1 x 1024 x 3)/10 = 307.2（秒）**
-
-   因此，建议导入作业的超时时间大于 308 秒。
-
-- `max_filter_ratio`
-
-  导入作业的最大容忍率，即导入作业能够容忍的因数据质量不合格而过滤掉的数据行所占的最大比例。取值范围：`0`~`1`。默认值：`0` 。
-
-  - 如果设置最大容忍率为 `0`，则 StarRocks 在导入过程中不会忽略错误的数据行。当导入的数据行中有错误时，导入作业会失败，从而保证数据的正确性。
-  - 如果设置最大容忍率大于 `0`，则 StarRocks 在导入过程中会忽略错误的数据行。这样，即使导入的数据行中有错误，导入作业也能成功。
-    > **说明**
-    >
-    > 这里因数据质量不合格而过滤掉的数据行，不包括通过 WHERE 子句过滤掉的数据行。
-
-  如果因为设置最大容忍率为 `0` 而导致作业失败，可以通过 [SHOW LOAD](../data-manipulation/SHOW_LOAD.md) 语句来查看导入作业的结果信息。然后，判断错误的数据行是否可以被过滤掉。如果可以被过滤掉，则可以根据结果信息中的 `dpp.abnorm.ALL` 和 `dpp.norm.ALL` 来计算导入作业的最大容忍率，然后调整后重新提交导入作业。计算公式如下：
-
-  **`max_filter_ratio` = [`dpp.abnorm.ALL`/(`dpp.abnorm.ALL` + `dpp.norm.ALL`)]**
-
-  `dpp.abnorm.ALL` 和 `dpp.norm.ALL` 的总和就等于待导入的总行数。
-
-- `log_rejected_record_num`
-
-  指定最多允许记录多少条因数据质量不合格而过滤掉的数据行数。该参数自 3.1 版本起支持。取值范围：`0`、`-1`、大于 0 的正整数。默认值：`0`。
-  
-  - 取值为 `0` 表示不记录过滤掉的数据行。
-  - 取值为 `-1` 表示记录所有过滤掉的数据行。
-  - 取值为大于 0 的正整数（比如 `n`）表示每个 BE（或 CN）节点上最多可以记录 `n` 条过滤掉的数据行。
-
-- `load_mem_limit`
-
-  导入作业的内存限制，最大不超过 BE（或 CN）的内存限制。单位：字节。默认内存限制为 2 GB。
-
-- `strict_mode`
-
-  是否开启严格模式。取值范围：`true` 和 `false`。默认值：`false`。`true` 表示开启，`false` 表示关闭。<br />关于该模式的介绍，参见[严格模式](../../../loading/load_concept/strict_mode.md)。
-
-- `timezone`
-
-  指定导入作业所使用的时区。默认为 `Asia/Shanghai` 时区。该参数会影响所有导入涉及的、跟时区设置有关的函数所返回的结果。受时区影响的函数有 strftime、alignment_timestamp 和 from_unixtime 等，具体请参见[设置时区](../../../administration/management/timezone.md)。导入参数 `timezone` 设置的时区对应“[设置时区](../../../administration/management/timezone.md)”中所述的会话级时区。
-
-- `priority`
-
-   指定导入作业的优先级。取值范围：`LOWEST`、`LOW`、`NORMAL`、`HIGH` 和 `HIGHEST`。默认值：`NORMAL`。Broker Load 通过 [FE 配置项](../../../administration/management/FE_configuration.md) `max_broker_load_job_concurrency` 指定 StarRocks 集群中可以并行执行的 Broker Load 作业的最大数量。如果某一时间段内提交的 Broker Load 作业总数超过最大数量，则超出的作业会按照优先级在队列中排队等待调度。
-
-   已经创建成功的导入作业，如果处于 **QUEUEING** 状态或者 **LOADING** 状态，那么您可以使用 [ALTER LOAD](../data-manipulation/ALTER_LOAD.md) 语句修改该作业的优先级。
-
-   StarRocks 自 v2.5 版本起支持为导入作业设置 `priority` 参数。
-
-- `partial_update`
-  
-   是否使用部分列更新。取值包括 `TRUE` 和 `FALSE`。默认值：`FALSE`。
-
-- `partial_update_mode`
-
-  指定部分更新的模式，取值包括 `row` 和 `column`。<ul><li>`row`（默认值），指定使用行模式执行部分更新，比较适用于较多列且小批量的实时更新场景。</li><li>`column`，指定使用列模式执行部分更新，比较适用于少数列并且大量行的批处理更新场景。在该场景，开启列模式，更新速度更快。例如，在一个包含 100 列的表中，每次更新 10 列（占比 10%）并更新所有行，则开启列模式，更新性能将提高 10 倍。</li></ul>
-
-- `merge_condition`
-
-  用于指定作为更新生效条件的列名。这样只有当导入的数据中该列的值大于等于当前值的时候，更新才会生效。
-  
-  Broker Load 自 3.1 版本起支持条件更新。参见[通过导入实现数据变更](../../../loading/Load_to_Primary_Key_tables.md#条件更新)。
-  
-  > **说明**
-  >
-  > 指定的列必须为非主键列，且仅主键表支持条件更新。
-
-StarRocks 自 3.2.3 版本起支持导入 JSON 格式的数据，相关参数如下：
-
-- jsonpaths
-
-  用于指定待导入的字段的名称。仅在使用匹配模式导入 JSON 数据时需要指定该参数。参数取值为 JSON 格式。参见[导入 JSON 数据时配置列映射关系](#导入-json-数据时配置列映射关系)。
-
-- strip_outer_array
-
-  用于指定是否裁剪最外层的数组结构。取值范围：`true` 和 `false`。默认值：`false`。
-  
-  真实业务场景中，待导入的 JSON 数据可能在最外层有一对表示数组结构的中括号 `[]`。这种情况下，一般建议您指定该参数取值为 `true`，这样 StarRocks 会剪裁掉外层的中括号 `[]`，并把中括号 `[]` 里的每个内层数组都作为一行单独的数据导入。如果您指定该参数取值为 `false`，则 StarRocks 会把整个 JSON 数据文件解析成一个数组，并作为一行数据导入。例如，待导入的 JSON 数据为 `[ {"category" : 1, "author" : 2}, {"category" : 3, "author" : 4} ]`，如果指定该参数取值为 `true`，则 StarRocks 会把 `{"category" : 1, "author" : 2}` 和 `{"category" : 3, "author" : 4}` 解析成两行数据，并导入到目标 StarRocks 表中对应的数据行。
-
-- json_root
-
-  用于指定待导入 JSON 数据的根元素。仅在使用匹配模式导入 JSON 数据时需要指定该参数。参数取值为合法的 JsonPath 字符串。默认值为空，表示会导入整个 JSON 数据文件的数据。具体请参见本文提供的示例“[导入数据并指定 JSON 根节点](#指定-json-根节点使用匹配模式导入数据)”。
-
-<!-- - ignore_json_size
-
-  用于指定是否检查 HTTP 请求中 JSON Body 的大小。
-  
-  > **说明**
-  >
-  > HTTP 请求中 JSON Body 的大小默认不能超过 100 MB。如果 JSON Body 的大小超过 100 MB，会提示 "The size of this batch exceed the max size [104857600] of json type data data [8617627793]. Set ignore_json_size to skip check, although it may lead huge memory consuming." 错误。为避免该报错，可以在 HTTP 请求头中添加 `"ignore_json_size:true"` 设置，忽略对 JSON Body 大小的检查。
--->
-另外，导入 JSON 格式的数据时，需要注意单个 JSON 对象的大小不能超过 4 GB。如果 JSON 文件中单个 JSON 对象的大小超过 4 GB，会提示 "This parser can't support a document that big." 错误。
-
-## 列映射
-
-### 导入 CSV 数据时配置列映射关系
-
-如果源数据文件中的列与目标表中的列按顺序一一对应，您不需要指定列映射和转换关系。
-
-如果源数据文件中的列与目标表中的列不能按顺序一一对应，包括数量或顺序不一致，则必须通过 `COLUMNS` 参数来指定列映射和转换关系。一般包括如下两种场景：
-
-- **列数量一致、但是顺序不一致，并且数据不需要通过函数计算、可以直接落入目标表中对应的列。** 这种场景下，您需要在 `COLUMNS` 参数中按照源数据文件中的列顺序、使用目标表中对应的列名来配置列映射和转换关系。
-
-  例如，目标表中有三列，按顺序依次为 `col1`、`col2` 和 `col3`；源数据文件中也有三列，按顺序依次对应目标表中的 `col3`、`col2` 和 `col1`。这种情况下，需要指定 `COLUMNS(col3, col2, col1)`。
-
-- **列数量、顺序都不一致，并且某些列的数据需要通过函数计算以后才能落入目标表中对应的列。** 这种场景下，您不仅需要在 `COLUMNS` 参数中按照源数据文件中的列顺序、使用目标表中对应的列名来配置列映射关系，还需要指定参与数据计算的函数。以下为两个示例：
-
-  - 目标表中有三列，按顺序依次为 `col1`、`col2` 和 `col3` ；源数据文件中有四列，前三列按顺序依次对应目标表中的 `col1`、`col2` 和 `col3`，第四列在目标表中无对应的列。这种情况下，需要指定 `COLUMNS(col1, col2, col3, temp)`，其中，最后一列可随意指定一个名称（如 `temp`）用于占位即可。
-  - 目标表中有三列，按顺序依次为 `year`、`month` 和 `day`。源数据文件中只有一个包含时间数据的列，格式为 `yyyy-mm-dd hh:mm:ss`。这种情况下，可以指定 `COLUMNS (col, year = year(col), month=month(col), day=day(col))`。其中，`col` 是源数据文件中所包含的列的临时命名，`year = year(col)`、`month=month(col)` 和 `day=day(col)` 用于指定从 `col` 列提取对应的数据并落入目标表中对应的列，如 `year = year(col)` 表示通过 `year` 函数提取源数据文件中 `col` 列的 `yyyy` 部分的数据并落入目标表中的 `year` 列。
-
-有关操作示例，参见[设置列映射关系](#设置列映射关系)。
-
-### 导入 JSON 数据时配置列映射关系
-
-如果 JSON 文件中的 Key 名与目标表中的列名一致，您可以使用简单模式来导入数据。简单模式下，不需要设置 `jsonpaths` 参数，这种模式要求 JSON 数据是大括号 {} 表示的对象类型，例如 `{"category": 1, "author": 2, "price": "3"}` 中，`category`、`author`、`price` 是 Key 的名称，按名称直接对应目标 表中的 `category`、`author`、`price` 三列。
-
-如果 JSON 文件中的 Key 名与目标表中的列名不一致，则需要使用匹配模式来导入数据。匹配模式下，需要通过 `jsonpaths` 和 `COLUMNS` 两个参数来指定 JSON 文件中的 Key 和目标表中的列之间的映射和转换关系：
-
-- `jsonpaths` 参数中按照 JSON 文件中 Key 的顺序一一指定待导入的 Key。
-- `COLUMNS` 参数中指定 JSON 文件中的 Key 与目标表中的列之间的映射关系和数据转换关系。
-  - `COLUMNS` 参数中指定的列名与 `jsonpaths` 参数中指定的 Key 按顺序保持一一对应。
-  - `COLUMNS` 参数中指定的列名与目标表中的列按名称保持一一对应。
-
-有关使用匹配模式导入 JSON 数据的示例，参见[使用匹配模式导入数据](#使用匹配模式导入数据)。
-
-## 相关配置项
-
-[FE 配置项](../../../administration/management/FE_configuration.md) `max_broker_load_job_concurrency` 指定了 StarRocks 集群中可以并行执行的 Broker Load 作业的最大数量。
-
-StarRocks v2.4 及以前版本中，如果某一时间段内提交的 Broker Load 作业总数超过最大数量，则超出作业会按照各自的提交时间放到队列中排队等待调度。
-
-自 StarRocks v2.5 版本起，如果某一时间段内提交的 Broker Load 作业总数超过最大数量，则超出的作业会按照作业创建时指定的优先级被放到队列中排队等待调度。参见上面介绍的可选参数 `priority`。您可以使用 [ALTER LOAD](../data-manipulation/ALTER_LOAD.md) 语句修改处于 **QUEUEING** 状态或者 **LOADING** 状态的 Broker Load 作业的优先级。
-
-## 作业拆分与并行执行
-
-一个 Broker Load 作业会拆分成一个或者多个子任务并行处理，一个作业的所有子任务作为一个事务整体成功或失败。作业的拆分通过 `LOAD LABEL` 语句中的 `data_desc` 参数来指定：
-
-- 如果声明多个 `data_desc` 参数对应导入多张不同的表，则每张表数据的导入会拆分成一个子任务。
-
-- 如果声明多个 `data_desc` 参数对应导入同一张表的不同分区，则每个分区数据的导入会拆分成一个子任务。
-
-每个子任务还会拆分成一个或者多个实例，然后这些实例会均匀地被分配到 BE（或 CN）上并行执行。实例的拆分由 FE 配置参数 [`min_bytes_per_broker_scanner`](../../../administration/management/FE_configuration.md) 和 BE（或 CN）节点数量决定，可以使用如下公式计算单个子任务的实例总数：
-
-单个子任务的实例总数 = min（单个子任务待导入数据量的总大小/`min_bytes_per_broker_scanner`, BE/CN 节点数量）
-
-一般情况下，一个导入作业只有一个 `data_desc`，只会拆分成一个子任务，子任务会拆分成与 BE（或 CN）节点数量相等的实例。
-
-## 示例
-
-本文以 HDFS 数据源为例，介绍各种导入配置。
-
-### 导入 CSV 格式的数据
-
-本小节以 CSV 格式的数据为例，重点阐述在创建导入作业的时候，如何运用各种参数配置来满足不同业务场景下的各种导入要求。
-
-#### 设置超时时间
-
-StarRocks 数据库 `test_db` 里的表 `table1` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example1.csv` 也包含三列，按顺序一一对应 `table1` 中的三列。
-
-如果要把 `example1.csv` 中所有的数据都导入到 `table1` 中，并且要求超时时间最大不超过 3600 秒，可以执行如下语句：
-
-```SQL
-LOAD LABEL test_db.label1
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example1.csv")
-    INTO TABLE table1
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-)
-PROPERTIES
-(
-    "timeout" = "3600"
-);
-```
-
-#### 设置最大容错率
-
-StarRocks 数据库 `test_db` 里的表 `table2` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example2.csv` 也包含三列，按顺序一一对应 `table2` 中的三列。
-
-如果要把 `example2.csv` 中所有的数据都导入到 `table2` 中，并且要求容错率最大不超过 `0.1`，可以执行如下语句：
-
-```SQL
-LOAD LABEL test_db.label2
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example2.csv")
-    INTO TABLE table2
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-)
-PROPERTIES
-(
-    "max_filter_ratio" = "0.1"
-);
-```
-
-#### 导入指定路径下所有数据文件
-
-StarRocks 数据库 `test_db` 里的表 `table3` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-HDFS 集群的 `/user/starrocks/data/input/` 路径下所有数据文件也包含三列，按顺序一一对应 `table3` 中的三列，并且列分隔符为 Hive 文件的默认列分隔符 `\x01`。
-
-如果要把 `hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/` 路径下所有数据文件的数据都导入到 `table3` 中，可以执行如下语句：
-
-```SQL
-LOAD LABEL test_db.label3
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/*")
-    INTO TABLE table3
-    COLUMNS TERMINATED BY "\\x01"
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-#### 设置 NameNode HA 机制
-
-StarRocks 数据库 `test_db` 里的表 `table4` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example4.csv` 也包含三列，按顺序一一对应 `table4` 中的三列。
-
-如果要把 `example4.csv` 中所有的数据都导入到 `table4` 中，并且要求使用 NameNode HA 机制，可以执行如下语句：
-
-```SQL
-LOAD LABEL test_db.label4
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example4.csv")
-    INTO TABLE table4
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>",
-    "dfs.nameservices" = "my_ha",
-    "dfs.ha.namenodes.my_ha" = "my_namenode1, my_namenode2",
-    "dfs.namenode.rpc-address.my_ha.my_namenode1" = "nn1_host:rpc_port",
-    "dfs.namenode.rpc-address.my_ha.my_namenode2" = "nn2_host:rpc_port",
-    "dfs.client.failover.proxy.provider" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
-);
-```
-
-#### 设置 Kerberos 认证方式
-
-StarRocks 数据库 `test_db` 里的表 `table5` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example5.csv` 也包含三列，按顺序一一对应 `table5` 中的三列。
-
-如果要把 `example5.csv` 中所有的数据都导入到 `table5` 中，并且要求使用 Kerberos 认证方式、提供 keytab 文件的路径，可以执行如下语句：
-
-```SQL
-LOAD LABEL test_db.label5
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example5.csv")
-    INTO TABLE table5
-    COLUMNS TERMINATED BY "\t"
-)
-WITH BROKER
-(
-    "hadoop.security.authentication" = "kerberos",
-    "kerberos_principal" = "starrocks@YOUR.COM",
-    "kerberos_keytab" = "/home/starRocks/starRocks.keytab"
-);
-```
-
-#### 撤销已导入的数据
-
-StarRocks 数据库 `test_db` 里的表 `table6` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example6.csv` 也包含三列，按顺序一一对应 `table6` 中的三列。
-
-并且，您已经通过 Broker Load 把 `example6.csv` 中所有的数据都导入到了 `table6` 中。
-
-如果您想撤销已导入的数据，可以执行如下语句：
-
-```SQL
-LOAD LABEL test_db.label6
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example6.csv")
-    NEGATIVE
-    INTO TABLE table6
-    COLUMNS TERMINATED BY "\t"
-)
-WITH BROKER
-(
-    "hadoop.security.authentication" = "kerberos",
-    "kerberos_principal" = "starrocks@YOUR.COM",
-    "kerberos_keytab" = "/home/starRocks/starRocks.keytab"
-);
-```
-
-#### 设置目标分区
-
-StarRocks 数据库 `test_db` 里的表 `table7` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example7.csv` 也包含三列，按顺序一一对应 `table7` 中的三列。
-
-如果要把 `example7.csv` 中所有的数据都导入到 `table7` 所在的分区 `p1` 和 `p2`，可以执行如下语句：
-
-```SQL
-LOAD LABEL test_db.label7
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example7.csv")
-    INTO TABLE table7
-    PARTITION (p1, p2)
-    COLUMNS TERMINATED BY ","
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-#### 设置列映射关系
-
-StarRocks 数据库 `test_db` 里的表 `table8` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example8.csv` 也包含三列，按顺序依次对应 `table8` 中 `col2`、`col1`、`col3`。
-
-如果要把 `example8.csv` 中所有的数据都导入到 `table8` 中，可以执行如下语句：
-
-```SQL
-LOAD LABEL test_db.label8
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example8.csv")
-    INTO TABLE table8
-    COLUMNS TERMINATED BY ","
-    (col2, col1, col3)
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-> **说明**
->
-> 上述示例中，因为 `example8.csv` 和 `table8` 所包含的列不能按顺序依次对应，因此需要通过 `column_list` 参数来设置 `example8.csv` 和 `table8` 之间的列映射关系。
-
-#### 设置筛选条件
-
-StarRocks 数据库 `test_db` 里的表 `table9` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example9.csv` 也包含三列，按顺序一一对应 `table9` 中的三列。
-
-如果只想把 `example9.csv` 中第一列的值大于 `20180601` 的数据行导入到 `table9` 中，可以执行如下语句：
-
-```SQL
-LOAD LABEL test_db.label9
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example9.csv")
-    INTO TABLE table9
-    (col1, col2, col3)
-    where col1 > 20180601
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-> **说明**
->
-> 上述示例中，虽然 `example9.csv` 和 `table9` 所包含的列数目相同、并且按顺序一一对应，但是因为需要通过 WHERE 子句指定基于列的过滤条件，因此需要通过 `column_list` 参数对 `example9.csv` 中的列进行临时命名。
-
-#### 导入数据到含有 HLL 类型列的表
-
-StarRocks 数据库 `test_db` 里的表 `table10` 包含四列，按顺序依次为 `id`、`col1`、`col2`、`col3`，其中 `col1` 和 `col2` 是 HLL 类型的列。
-
-数据文件 `example10.csv` 包含三列，第一列对应 `table10` 中的 `id` 列；第二列和第三列分别对应 `table10` 中 HLL 类型的列 `col1` 和 `col2`，可以通过函数转换成 HLL 类型的数据并分别落入 `col1`、`col2` 列。
-
-如果要把 `example10.csv` 中所有的数据都导入到 `table10` 中，可以执行如下语句：
-
-```SQL
-LOAD LABEL test_db.label10
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example10.csv")
-    INTO TABLE table10
-    COLUMNS TERMINATED BY ","
-    (id, temp1, temp2)
-    SET
-    (
-        col1 = hll_hash(temp1),
-        col2 = hll_hash(temp2),
-        col3 = empty_hll()
-    )
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-> **说明**
->
-> 上述示例中，通过 `column_list` 参数，把 `example10.csv` 中的三列按顺序依次临时命名为 `id`、`temp1`、`temp2`，然后使用函数指定数据转换规则，包括：
->
-> - 使用 `hll_hash` 函数把 `example10.csv` 中的 `temp1`、`temp2` 列转换成 HLL 类型的数据，并分别落入 `table10`中的 `col1`、`col2` 列。
->
-> - 使用 `hll_empty` 函数给导入的数据行在 `table10` 中的第四列补充默认值。
-
-有关 `hll_hash` 函数和 `hll_empty` 函数的用法，请参见 [hll_hash](../../sql-functions/scalar-functions/hll_hash.md)和[hll_empty](../../sql-functions/scalar-functions/hll_empty.md)。
-
-#### 提取文件路径中的分区字段
-
-Broker Load 支持根据 StarRocks 表中定义的字段类型来解析待导入文件路径中的分区字段，类似 Apache Spark™ 中的分区发现 (Partition Discovery) 功能。
-
-StarRocks 数据库 `test_db` 里的表 `table11` 包含五列，按顺序依次为 `col1`、`col2`、`col3`、`city`、`utc_date`。
-
-HDFS 集群的 `/user/starrocks/data/input/dir/city=beijing` 路径下包含如下数据文件：
-
-- `/user/starrocks/data/input/dir/city=beijing/utc_date=2019-06-26/0000.csv`
-
-- `/user/starrocks/data/input/dir/city=beijing/utc_date=2019-06-26/0001.csv`
-
-这些数据文件都包含三列，按顺序分别对应 `table11` 中 `col1`、`col2`、`col3` 三列。
-
-如果要把 `/user/starrocks/data/input/dir/city=beijing/utc_date=*/*` 路径下所有数据文件的数据都导入到 `table11` 中，并且要求提取路径中分区字段 `city` 和 `utc_date` 的信息落入 `table11` 中对应的 `city`、`utc_date` 列，可以执行如下语句：
-
-```SQL
-LOAD LABEL test_db.label11
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/dir/city=beijing/*/*")
-    INTO TABLE table11
-    FORMAT AS "csv"
-    (col1, col2, col3)
-    COLUMNS FROM PATH AS (city, utc_date)
-    SET (uniq_id = md5sum(k1, city))
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-#### 提取文件路径中包含 `%3A` 的时间分区字段
-
-在 HDFS 的文件路径中，不允许有冒号 (:)，所有冒号 (:) 都会自动替换成 `%3A`。
-
-StarRocks 数据库 `test_db` 里的表 `table12` 包含三列，按顺序依次为 `data_time`、`col1`、`col2`，表结构如下：
-
-```SQL
-data_time DATETIME,
-col1        INT,
-col2        INT
-```
-
-HDFS 集群的 `/user/starrocks/data` 路径下有如下数据文件：
-
-- `/user/starrocks/data/data_time=2020-02-17 00%3A00%3A00/example12.csv`
-
-- `/user/starrocks/data/data_time=2020-02-18 00%3A00%3A00/example12.csv`
-
-如果要把 `example12.csv` 中所有的数据都导入到 `table12` 中，并且要求提取指定路径中分区字段 `data_time` 的信息落入到 `table12` 中的 `data_time` 列，可以执行如下语句：
-
-```SQL
-LOAD LABEL test_db.label12
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/*/example12.csv")
-    INTO TABLE table12
-    COLUMNS TERMINATED BY ","
-    FORMAT AS "csv"
-    (col1,col2)
-    COLUMNS FROM PATH AS (data_time)
-    SET (data_time = str_to_date(data_time, '%Y-%m-%d %H%%3A%i%%3A%s'))
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-上述示例中，因为直接提取后的分区字段 `data_time` 是包含 `%3A` 的字符串（如 `2020-02-17 00%3A00%3A00`），因此需要再通过 `str_to_date` 函数把字符串转换为 DATETIME 类型的数据以后才能落入 `table8` 中的 `data_time` 列。
-
-#### 设置 `format_type_options`
-
-StarRocks 数据库 `test_db` 里的表 `table13` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example13.csv` 也包含三列，按顺序依次对应 `table13` 中 `col2`、`col1`、`col3`。
-
-如果要把 `example13.csv` 中所有的数据都导入到 `table13` 中，并且希望跳过 `example13.csv` 中最开头的两行数据、去除列分隔符前后的空格、 指定 `enclose` 字符为斜杠 (`\`)、并且指定 `escape` 字符为斜杠 (`\`)，可以执行如下语句：
-
-```SQL
-LOAD LABEL test_db.label13
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/*/example13.csv")
-    INTO TABLE table13
-    COLUMNS TERMINATED BY ","
-    FORMAT AS "CSV"
-    (
-        skip_header = 2
-        trim_space = TRUE
-        enclose = "\""
-        escape = "\\"
-    )
-    (col2, col1, col3)
-)
-WITH BROKER
-(
-    "username" = "hdfs_username",
-    "password" = "hdfs_password"
-)
-PROPERTIES
-(
-    "timeout" = "3600"
-);
-```
-
-### 导入 Parquet 格式的数据
-
-本小节主要描述导入 Parquet 格式的数据时，需要关注的一些参数配置。
-
-StarRocks 数据库 `test_db` 里的表 `table13` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example13.parquet` 也包含三列，按顺序一一对应 `table13` 中的三列。
-
-如果要把 `example13.parquet` 中所有的数据都导入到 `table13` 中，可以执行如下语句：
-
-```SQL
-LOAD LABEL test_db.label13
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example13.parquet")
-    INTO TABLE table13
-    FORMAT AS "parquet"
-    (col1, col2, col3)
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-> **说明**
->
-> 导入 Parquet 格式的数据时，默认通过文件扩展名 (**.parquet**) 判断数据文件的格式。如果文件名称中没有包含扩展名，则必须通过 `FORMAT AS` 参数指定数据文件格式为 `Parquet`。
-
-### 导入 ORC 格式的数据
-
-本小节主要描述导入 ORC 格式的数据时，需要关注的一些参数配置。
-
-StarRocks 数据库 `test_db` 里的表 `table14` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example14.orc` 也包含三列，按顺序一一对应 `table14` 中的三列。
-
-如果要把 `example14.orc` 中所有的数据都导入到 `table14` 中，可以执行如下语句：
-
-```SQL
-LOAD LABEL test_db.label14
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example14.orc")
-    INTO TABLE table14
-    FORMAT AS "orc"
-    (col1, col2, col3)
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-> **说明**
->
-> - 导入 ORC 格式的数据时，默认通过文件扩展名 (**.orc**) 判断数据文件的格式。如果文件名称中没有包含扩展名，则必须通过 `FORMAT AS` 参数指定数据文件格式为 `ORC`。
->
-> - StarRocks v2.3 及之前版本，当数据文件中包含 ARRAY 类型的列时，必须确保数据文件和 StarRocks 表中对应的列同名，并且不能写在 SET 子句里。
-
-### 导入 JSON 格式的数据
-
-本小节主要描述导入 JSON 格式的数据时，需要关注的一些参数配置。
-
-StarRocks 数据库 `test_db` 里的表 `tbl1` 拥有如下表结构：
-
-```SQL
-`category` varchar(512) NULL COMMENT "",
-`author` varchar(512) NULL COMMENT "",
-`title` varchar(512) NULL COMMENT "",
-`price` double NULL COMMENT ""
-```
-
-#### 使用简单模式导入数据
-
-假设数据文件 `example1.json` 包含如下数据：
-
-```JSON
-{"category":"C++","author":"avc","title":"C++ primer","price":895}
-```
-
-您可以通过如下命令将 `example1.json` 中的数据导入到 `tbl1` 中：
-
-```SQL
-LOAD LABEL test_db.label15
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example1.csv")
-    INTO TABLE tbl1
-    FORMAT AS "json"
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-);
-```
-
-> **说明**
->
-> 如上述示例所示，在没有指定 `columns` 和 `jsonpaths` 参数的情况下，则会按照 StarRocks 表中的列名称去对应 JSON 数据文件中的字段。
-
-#### 使用匹配模式导入数据
-
-StarRocks 按照如下顺序对数据进行匹配和处理：
-
-1. （可选）根据 `strip_outer_array` 参数裁剪最外层的数组结构。
-
-    > **说明**
-    >
-    > 仅在 JSON 数据的最外层是一个通过中括号 `[]` 表示的数组结构时涉及，需要设置 `strip_outer_array` 为 `true`。
-
-2. （可选）根据 `json_root` 参数匹配 JSON 数据的根节点。
-
-    > **说明**
-    >
-    > 仅在 JSON 数据存在根节点时涉及，需要通过 `json_root` 参数来指定根节点。
-
-3. 根据 `jsonpaths` 参数提取待导入的 JSON 数据。
-
-##### 不指定 JSON 根节点、使用匹配模式导入数据
-
-假设数据文件 `example2.json` 包含如下数据：
-
-```JSON
-[
-    {"category":"xuxb111","author":"1avc","title":"SayingsoftheCentury","price":895},
-    {"category":"xuxb222","author":"2avc","title":"SayingsoftheCentury","price":895},
-    {"category":"xuxb333","author":"3avc","title":"SayingsoftheCentury","price":895}
-]
-```
-
-您可以通过指定 `jsonpaths` 参数进行精准导入，例如只导入 `category`、`author`、`price` 三个字段的数据：
-
-```SQL
-LOAD LABEL test_db.label16
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example2.csv")
-    INTO TABLE tbl1
-    FORMAT AS "json"
-    (category, price, author)
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-)
-PROPERTIES
-(
-    "strip_outer_array" = "true",
-    "jsonpaths" = "[\"$.category\",\"$.price\",\"$.author\"]"
-);
-```
-
-> **说明**
->
-> 上述示例中，JSON 数据的最外层是一个通过中括号 [] 表示的数组结构，并且数组结构中的每个 JSON 对象都表示一条数据记录。因此，需要设置 `strip_outer_array` 为 `true`来裁剪最外层的数组结构。导入过程中，未指定的字段 `title` 会被忽略掉。
-
-##### 指定 JSON 根节点、使用匹配模式导入数据
-
-假设数据文件 `example3.json` 包含如下数据：
-
-```JSON
-{
-    "id": 10001,
-    "RECORDS":[
-        {"category":"11","title":"SayingsoftheCentury","price":895,"timestamp":1589191587},
-        {"category":"22","author":"2avc","price":895,"timestamp":1589191487},
-        {"category":"33","author":"3avc","title":"SayingsoftheCentury","timestamp":1589191387}
-    ],
-    "comments": ["3 records", "there will be 3 rows"]
-}
-```
-
-您可以通过指定 `jsonpaths` 进行精准导入，例如只导入 `category`、`author`、`price` 三个字段的数据：
-
-```SQL
-LOAD LABEL test_db.label17
-(
-    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example3.csv")
-    INTO TABLE tbl1
-    FORMAT AS "json"
-    (category, price, author)
-)
-WITH BROKER
-(
-    "username" = "<hdfs_username>",
-    "password" = "<hdfs_password>"
-)
-PROPERTIES
-(
-    "json_root"="$.RECORDS",
-    "strip_outer_array" = "true",
-    "jsonpaths" = "[\"$.category\",\"$.price\",\"$.author\"]"
-);
-```
-
-> **说明**
->
-> 上述示例中，JSON 数据的最外层是一个通过中括号 [] 表示的数组结构，并且数组结构中的每个 JSON 对象都表示一条数据记录。因此，需要设置 `strip_outer_array` 为 `true`来裁剪最外层的数组结构。导入过程中，未指定的字段 `title` 和 `timestamp` 会被忽略掉。另外，示例中还通过 `json_root` 参数指定了需要真正导入的数据为 `RECORDS` 字段对应的值，即一个 JSON 数组。
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/CANCEL_EXPORT.md b/docs/zh/sql-reference/sql-statements/data-manipulation/CANCEL_EXPORT.md
deleted file mode 100644
index 55bead13f58065..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/CANCEL_EXPORT.md
+++ /dev/null
@@ -1,45 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CANCEL EXPORT
-
-## 功能
-
-取消指定的数据导出作业，状态为 `CANCELLED` 或 `FINISHED` 的导出作业不能取消。CANCEL EXPORT 是一个异步操作，执行后可使用 [SHOW EXPORT](./SHOW_EXPORT.md) 语句查看是否取消成功。当状态 (`State`) 为 `CANCELLED` 时，代表成功取消了导入作业。
-
-> **注意**
->
-> 要执行该操作，需要有对应表的 EXPORT 权限。
-
-## 语法
-
-```SQL
-CANCEL EXPORT
-[FROM db_name]
-WHERE QUERYID = "query_id"
-```
-
-## 参数说明
-
-| **参数** | **必选** | **说明**                                                     |
-| -------- | -------- | ------------------------------------------------------------ |
-| db_name  | 否       | 数据库名称。如不指定，则默认取消当前数据库中的指定导出作业。 |
-| query_id | 是       | 导出作业的查询 ID，可使用 [LAST_QUERY_ID()](../../sql-functions/utility-functions/last_query_id.md) 函数获取。注意使用该函数只能获取到最近一次的查询 ID。 |
-
-## 示例
-
-示例一：取消当前数据库中，查询 ID 为 `921d8f80-7c9d-11eb-9342-acde48001121` 的导出作业。
-
-```SQL
-CANCEL EXPORT
-WHERE queryid = "921d8f80-7c9d-11eb-9342-acde48001121";
-```
-
-示例二：取消数据库 `example_db` 中，查询 ID 为 `921d8f80-7c9d-11eb-9342-acde48001122` 的导出作业。
-
-```SQL
-CANCEL EXPORT 
-FROM example_db 
-WHERE queryid = "921d8f80-7c9d-11eb-9342-acde48001122";
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/CANCEL_LOAD.md b/docs/zh/sql-reference/sql-statements/data-manipulation/CANCEL_LOAD.md
deleted file mode 100644
index fc1f9a1dec0510..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/CANCEL_LOAD.md
+++ /dev/null
@@ -1,43 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CANCEL LOAD
-
-## 功能
-
-取消指定的 [Broker Load](../data-manipulation/BROKER_LOAD.md)、[Spark Load](../data-manipulation/SPARK_LOAD.md) 或 [INSERT](./INSERT.md) 导入作业，状态为 PREPARED、CANCELLED 或 FINISHED 的导入作业不能取消。
-
-CANCEL LOAD 是一个异步操作，执行后可使用 [SHOW LOAD](../data-manipulation/SHOW_LOAD.md) 语句查看是否取消成功。当状态 (`State`) 为 `CANCELLED` 且导入作业失败原因 (`ErrorMsg`) 中的失败类型 (`type`) 为 `USER_CANCEL` 时，代表成功取消了导入作业。
-
-## 语法
-
-```SQL
-CANCEL LOAD
-[FROM db_name]
-WHERE LABEL = "label_name"
-```
-
-## 参数说明
-
-| **参数**   | **必选** | **说明**                                       |
-| ---------- | -------- | ---------------------------------------------- |
-| db_name    | 否       | 导入作业所在的数据库的名称。默认为当前数据库。 |
-| label_name | 是       | 导入作业的标签。                               |
-
-## 示例
-
-示例一：取消当前数据库中标签为`example_label`的导入作业。
-
-```SQL
-CANCEL LOAD
-WHERE LABEL = "example_label";
-```
-
-示例二：取消数据库`example_db`中标签为`example_label`的导入作业。
-
-```SQL
-CANCEL LOAD
-FROM example_db
-WHERE LABEL = "example_label";
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW.md
deleted file mode 100644
index 91063bba85de45..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW.md
+++ /dev/null
@@ -1,38 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CANCEL REFRESH MATERIALIZED VIEW
-
-## 功能
-
-取消异步物化视图的刷新任务。
-
-:::tip
-
-该操作需要对应物化视图的 REFRESH 权限。
-
-:::
-
-## 语法
-
-```SQL
-CANCEL REFRESH MATERIALIZED VIEW [database_name.]materialized_view_name [FORCE]
-```
-
-## 参数说明
-
-| **参数**               | **必选** | **说明**                                                     |
-| ---------------------- | -------- | ------------------------------------------------------------ |
-| database_name          | 否       | 待取消刷新的物化视图所属数据库名称。如果不指定该参数，则默认使用当前数据库。 |
-| materialized_view_name | 是       | 待取消刷新的物化视图名称。                                   |
-| FORCE                  | 否       | 强制取消物化视图刷新任务。                                   |
-
-## 示例
-
-示例一：取消异步物化视图 `lo_mv1` 的刷新任务。
-
-```SQL
-CANCEL REFRESH MATERIALIZED VIEW lo_mv1;
-CANCEL REFRESH MATERIALIZED VIEW lo_mv1 FORCE;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md b/docs/zh/sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md
deleted file mode 100644
index 3facd47aa1411b..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/CREATE_PIPE.md
+++ /dev/null
@@ -1,86 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CREATE PIPE
-
-## 功能
-
-创建一个 Pipe，用于定义一个实现数据导入的 INSERT INTO SELECT FROM FILES 语句。该命令自 3.2 版本起支持。
-
-## 语法
-
-```SQL
-CREATE [OR REPLACE] PIPE [db_name.]<pipe_name> 
-[PROPERTIES ("<key>" = "<value>"[, "<key> = <value>" ...])]
-AS <INSERT_SQL>
-```
-
-StarRocks 自 3.2.3 版本起支持 CREATE [OR REPLACE] PIPE。使用 CREATE [OR REPLACE] PIPE 时，如果指定的 `pipe_name` 与当前数据库里的某个已有的 Pipe 名称相同，则新建的 Pipe 会取代已有的 Pipe。
-
-## 参数说明
-
-### db_name
-
-Pipe 所属的数据库的名称。
-
-### pipe_name
-
-Pipe 的名称。该名称在 Pipe 所在的数据库内必须唯一。命名要求参见[系统限制](../../../reference/System_limit.md)。
-
-> **NOTICE**
->
-> 每个 Pipe 从属于一个数据库。删除 Pipe 所在的数据库后，该 Pipe 也会随之删除，并且该 Pipe 不会随数据库的恢复而恢复。
-
-### INSERT_SQL
-
-INSERT INTO SELECT FROM FILES 语句，用于从指定的源数据文件导入数据到目标表。
-
-有关如何使用表函数 FILES()，参见 [FILES](../../../sql-reference/sql-functions/table-functions/files.md)。
-
-### PROPERTIES
-
-用于控制 Pipe 执行的一些参数。格式：`"key" = "value"`。
-
-| 参数          | 默认值        | 参数描述                                                     |
-| :------------ | :------------ | :----------------------------------------------------------- |
-| AUTO_INGEST   | `TRUE`        | 是否启用自动增量导入。取值范围：`TRUE` 和 `FALSE`。`TRUE` 表示开启自动增量导入。`FALSE` 表示只导入作业启动时指定的数据文件内容，后续新增或修改的文件内容不导入。对于批量导入来说，可以将其设置为 `FALSE`。 |
-| POLL_INTERVAL | `300` (second) | 自动增量导入的轮询间隔。                                     |
-| BATCH_SIZE    | `1 GB`       | 导入批次大小。如果参数取值中不指定单位，则使用默认单位 Byte。 |
-| BATCH_FILES   | `256`         | 导入批次文件数量。                                           |
-
-## 示例
-
-在当前数据库下，创建一个名为 `user_behavior_replica` 的 Pipe，用于把 `s3://starrocks-examples/user_behavior_ten_million_rows.parquet` 中的数据导入到表 `user_behavior_replica` 中：
-
-```SQL
-CREATE PIPE user_behavior_replica
-PROPERTIES
-(
-    "AUTO_INGEST" = "TRUE"
-)
-AS
-INSERT INTO user_behavior_replica
-SELECT * FROM FILES
-(
-    "path" = "s3://starrocks-examples/user_behavior_ten_million_rows.parquet",
-    "format" = "parquet",
-    "aws.s3.region" = "us-east-1",
-    "aws.s3.access_key" = "AAAAAAAAAAAAAAAAAAAA",
-    "aws.s3.secret_key" = "BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB"
-); 
-```
-
-> **说明**
->
-> 把上面命令示例中的 `AAA` 和 `BBB` 替换成真实有效的 Access Key 和 Secret Key 作为访问凭证。由于这里使用的数据对象对所有合法的 AWS 用户开放，因此您填入任何真实有效的 Access Key 和 Secret Key 都可以。
-
-该示例以基于 IAM User 的认证鉴权方式为例，并假设 Parquet 源文件与 StarRocks 目标表的结构相同。有关认证方式和语句详情，参见[配置 AWS 认证信息](../../../integrations/authenticate_to_aws_resources.md)和 [FILES](../../../sql-reference/sql-functions/table-functions/files.md)。
-
-## 相关文档
-
-- [ALTER PIPE](../data-manipulation/ALTER_PIPE.md)
-- [DROP PIPE](../data-manipulation/DROP_PIPE.md)
-- [SHOW PIPES](../data-manipulation/SHOW_PIPES.md)
-- [SUSPEND or RESUME PIPE](../data-manipulation/SUSPEND_or_RESUME_PIPE.md)
-- [RETRY FILE](../data-manipulation/RETRY_FILE.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md b/docs/zh/sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md
deleted file mode 100644
index 28b220d826dd0a..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md
+++ /dev/null
@@ -1,963 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# CREATE ROUTINE LOAD
-
-## 功能
-
-Routine Load 支持持续消费 Apache Kafka® 的消息并导入至 StarRocks 中。Routine Load 支持 Kafka 中消息的格式为 CSV、JSON、Avro (自 v3.0.1)，并且访问 Kafka 时，支持多种安全协议，包括 `plaintext`、`ssl`、`sasl_plaintext` 和 `sasl_ssl`。
-
-本文介绍 CREATE ROUTINE LOAD 的语法、参数说明和示例。
-
-> **说明**
->
-> - Routine Load 的应用场景、基本原理和基本操作，请参见 [使用 Routine Load 导入数据](../../../loading/RoutineLoad.md)。
-> - Routine Load 操作需要目标表的 INSERT 权限。如果您的用户账号没有 INSERT 权限，请参考 [GRANT](../account-management/GRANT.md) 给用户赋权。
-
-## 语法
-
-```SQL
-CREATE ROUTINE LOAD <database_name>.<job_name> ON <table_name>
-[load_properties]
-[job_properties]
-FROM data_source
-[data_source_properties]
-```
-
-## 参数说明
-
-### `database_name`、`job_name`、`table_name`
-
-`database_name`
-
-选填，目标数据库的名称。
-
-`job_name`
-
-必填，导入作业的名称。一张表可能有多个导入作业，建议您利用具有辨识度的信息（例如 Kafka Topic 名称、创建导入作业的大致时间等）来设置具有意义的导入作业名称，用于区分多个导入作业。同一数据库内，导入作业的名称必须唯一。
-
-`table_name`
-
-必填，目标表的名称。
-
-### `load_properties`
-
-选填。源数据的属性。语法：
-
-```SQL
-[COLUMNS TERMINATED BY '<column_separator>'],
-[ROWS TERMINATED BY '<row_separator>'],
-[COLUMNS (<column1_name>[,<column2_name>,<column_assignment>,... ])],
-[WHERE <expr>],
-[PARTITION (<partition1_name>[,<partition2_name>,...])]
-[TEMPORARY PARTITION (<temporary_partition1_name>[,<temporary_partition2_name>,...])]
-```
-
-如果导入 CSV 格式的数据，则可以指定列分隔符，默认为`\t`，即 Tab。例如可以输入 `COLUMNS TERMINATED BY ","`。指定列分隔符为逗号(,)。
-
-> **说明**
->
-> - 必须确保这里指定的列分隔符与源数据中的列分隔符一致。
-> - StarRocks 支持设置长度最大不超过 50 个字节的 UTF-8 编码字符串作为列分隔符，包括常见的逗号 (,)、Tab 和 Pipe (|)。
-> - 空值 (null) 用 `\N` 表示。比如，源数据一共有三列，其中某行数据的第一列、第三列数据分别为 `a` 和 `b`，第二列没有数据，则第二列需要用 `\N` 来表示空值，写作 `a,\N,b`，而不是 `a,,b`。`a,,b` 表示第二列是一个空字符串。
-
-`ROWS TERMINATED BY`
-
-用于指定源数据中的行分隔符。如果不指定该参数，则默认为 `\n`。
-
-`COLUMNS`
-
-源数据和目标表之间的列映射和转换关系。详细说明，请参见[列映射和转换关系](#列映射和转换关系)。
-
-- `column_name`：映射列，源数据中这类列的值可以直接落入目标表的列中，不需要进行计算。
-- `column_assignment`：衍生列，格式为 `column_name = expr`，源数据中这类列的值需要基于表达式 `expr` 进行计算后，才能落入目标表的列中。 建议将衍生列排在映射列之后，因为 StarRocks 先解析映射列，再解析衍生列。
-
-> **说明**
->
-> 以下情况不需要设置 `COLUMNS` 参数：
->
-> - 待导入 CSV 数据中的列与目标表中列的数量和顺序一致。
-> - 待导入 JSON 数据中的 Key 名与目标表中的列名一致。
-
-`WHERE`
-
-设置过滤条件，只有满足过滤条件的数据才会导入到 StarRocks 中。例如只希望导入 `col1` 大于 `100` 并且 `col2` 等于 `1000` 的数据行，则可以输入 `WHERE col1 > 100 and col2 = 1000`。
-
-> **说明**
->
-> 过滤条件中指定的列可以是源数据中本来就存在的列，也可以是基于源数据的列生成的衍生列。
-
-`PARTITION`
-
-将数据导入至目标表的指定分区中。如果不指定分区，则会将数据自动导入至其对应的分区中。 示例：
-
-```SQL
-PARTITION(p1, p2, p3)
-```
-
-### `job_properties`
-
-必填。导入作业的属性。语法：
-
-```SQL
-PROPERTIES ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
-```
-
-参数说明如下：
-
-| **参数**                  | **是否必选** | **说明**                                                     |
-| ------------------------- | ------------ | ------------------------------------------------------------ |
-| desired_concurrent_number | 否           | 单个 Routine Load 导入作业的**期望**任务并发度，表示期望一个导入作业最多被分成多少个任务并行执行。默认值为 `3`。 但是**实际**任务并行度由如下多个参数组成的公式决定，并且实际任务并行度的上限为 BE 节点的数量或者消费分区的数量。`min(alive_be_number, partition_number, desired_concurrent_number, max_routine_load_task_concurrent_num)`。<ul> <li>`alive_be_number`：存活的 BE 节点数量。</li><li>`partition_number`：消费分区数量。</li><li>`desired_concurrent_number`：单个Routine Load 导入作业的期望任务并发度。默认值为 `3`。</li><li>`max_routine_load_task_concurrent_num`：Routine Load 导入作业的默认最大任务并行度，默认值为 `5`。该参数为 [FE 动态参数](../../../administration/management/FE_configuration.md)。</li></ul> |
-| max_batch_interval        | 否           | 任务的调度间隔，即任务多久执行一次。单位：秒。取值范围：`5`～`60`。默认值：`10`。建议取值为导入间隔 10s 以上，否则会因为导入频率过高可能会报错版本数过多。 |
-| max_batch_rows            | 否           | 该参数只用于定义错误检测窗口范围，错误检测窗口范围为单个 Routine Load 导入任务所消费的 `10 * max-batch-rows` 行数据，默认为 `10 * 200000 = 2000000`。导入任务时会检测窗口中数据是否存在错误。错误数据是指 StarRocks 无法解析的数据，比如非法的 JSON。 |
-| max_error_number          | 否           | 错误检测窗口范围内允许的数据行数的上限。当错误数据行数超过该值时，导入作业会暂停，此时您需要执行 [SHOW ROUTINE LOAD](../data-manipulation/SHOW_ROUTINE_LOAD.md)，根据 `ErrorLogUrls`，检查 Kafka 中的消息并且更正错误。默认为 `0`，表示不允许有错误行。<br />**注意**<br /><ul><li>错误行不包括通过 WHERE 子句过滤掉的数据。</li><li>该参数与下个参数 `max_filter_ratio` 都用于控制错误行数阈值。如果没有设置 `max_filter_ratio` 时，则本参数生效，如果设置了 `max_filter_ratio`，则错误行数只要达到本参数或 `max_filter_ratio` 参数其中任何一个阈值，则导入作业暂停。</li></ul> |
-| max_filter_ratio         | 否           |  用于指定导入作业的最大容错率，即导入作业能够容忍的因数据质量不合格而过滤掉的数据行所占的最大比例。取值范围：`0`~`1`。默认值：`0` 。<br />建议您保留默认值 `0`。这样的话，当导入的数据行中有错误时，导入作业会暂停，从而保证数据的正确性。<br />如果希望忽略错误的数据行，可以设置该参数的取值大于 `0`。这样的话，即使导入的数据行中有错误，导入作业也能成功。<br />**注意**<br /><ul><li>这里因数据质量不合格而过滤掉的数据行，不包括通过 WHERE 子句过滤掉的数据行。</li><li>该参数与上个参数 `max_error_number` 都用于控制错误行数阈值。当该参数保持默认值 `0` 时，`max_error_number` 生效，如果设置了本参数，则错误行数只要达到本参数或 `max_error_number` 参数其中任何一个阈值，则导入作业暂停。</li></ul> |
-| strict_mode               | 否           | 是否开启严格模式。取值范围：`TRUE` 或者 `FALSE`。默认值：`FALSE`。开启后，如果源数据某列的值为 `NULL`，但是目标表中该列不允许为 `NULL`，则该行数据会被过滤掉。<br />关于该模式的介绍，参见[严格模式](../../../loading/load_concept/strict_mode.md)。|
-| log_rejected_record_num | 否 | 指定最多允许记录多少条因数据质量不合格而过滤掉的数据行数。该参数自 3.1 版本起支持。取值范围：`0`、`-1`、大于 0 的正整数。默认值：`0`。<ul><li>取值为 `0` 表示不记录过滤掉的数据行。</li><li>取值为 `-1` 表示记录所有过滤掉的数据行。</li><li>取值为大于 0 的正整数（比如 `n`）表示每个 BE 节点上最多可以记录 `n` 条过滤掉的数据行。</li></ul> |
-| timezone                  | 否           | 该参数的取值会影响所有导入涉及的、跟时区设置有关的函数所返回的结果。受时区影响的函数有 strftime、alignment_timestamp 和 from_unixtime 等，具体请参见[设置时区](../../../administration/management/timezone.md)。导入参数 `timezone` 设置的时区对应[设置时区](../../../administration/management/timezone.md)中所述的会话级时区。 |
-| partial_update | 否 |是否使用部分列更新。取值包括 `TRUE` 和 `FALSE`。默认值：`FALSE`。|
-| merge_condition           | 否           | 用于指定作为更新生效条件的列名。这样只有当导入的数据中该列的值大于等于当前值的时候，更新才会生效。参见[通过导入实现数据变更](../../../loading/Load_to_Primary_Key_tables.md)。指定的列必须为非主键列，且仅主键表支持条件更新。 |
-| format                    | 否           | 源数据的格式，取值范围：`CSV`、`JSON` 或者 `Avro`（自 v3.0.1）。默认值：`CSV`。|
-| trim_space                | 否           | 用于指定是否去除 CSV 文件中列分隔符前后的空格。取值类型：BOOLEAN。默认值：`false`。<br />有些数据库在导出数据为 CSV 文件时，会在列分隔符的前后添加一些空格。根据位置的不同，这些空格可以称为“前导空格”或者“尾随空格”。通过设置该参数，可以使 StarRocks 在导入数据时删除这些不必要的空格。<br />需要注意的是，StarRocks 不会去除被 `enclose` 指定字符括起来的字段内的空格（包括字段的前导空格和尾随空格）。例如，列分隔符是竖线 (<code class="language-text">&#124;</code>)，`enclose` 指定的字符是双引号 (`"`)：<code class="language-text">&#124; "Love StarRocks" &#124;</code>。如果设置 trim_space 为 true，则 StarRocks 处理后的结果数据为 <code class="language-text">&#124;"Love StarRocks"&#124;</code>。|
-| enclose                   | 否           | 根据 [RFC4180](https://www.rfc-editor.org/rfc/rfc4180)，用于指定把 CSV 文件中的字段括起来的字符。取值类型：单字节字符。默认值：`NONE`。最常用 `enclose` 字符为单引号 (`'`) 或双引号 (`"`)。<br />被 `enclose` 指定字符括起来的字段内的所有特殊字符（包括行分隔符、列分隔符等）均看做是普通符号。比 RFC4180 标准更进一步的是，StarRocks 提供的 `enclose` 属性支持设置任意单个字节的字符。<br />如果一个字段内包含了 `enclose` 指定字符，则可以使用同样的字符对 `enclose` 指定字符进行转义。例如，在设置了`enclose` 为双引号 (`"`) 时，字段值 `a "quoted" c` 在 CSV 文件中应该写作 `"a ""quoted"" c"`。 |
-| escape                    | 否           | 指定用于转义的字符。用来转义各种特殊字符，比如行分隔符、列分隔符、转义符、`enclose` 指定字符等，使 StarRocks 把这些特殊字符当做普通字符而解析成字段值的一部分。取值类型：单字节字符。默认值：`NONE`。最常用的 `escape` 字符为斜杠 (`\`)，在 SQL 语句中应该写作双斜杠 (`\\`)。<br />`escape` 指定字符同时作用于 `enclose` 指定字符的内部和外部。<br />以下为两个示例：<br /><ul><li>当设置 `enclose` 为双引号 (`"`) 、`escape` 为斜杠 (`\`) 时，StarRocks 会把 `"say \"Hello world\""` 解析成一个字段值 `say "Hello world"`。</li><li>假设列分隔符为逗号 (`,`) ，当设置 `escape` 为斜杠 (`\`) ，StarRocks 会把 `a, b\, c` 解析成 `a` 和 `b, c` 两个字段值。</li></ul> |
-| strip_outer_array         | 否           | 是否裁剪 JSON 数据最外层的数组结构。取值范围：`TRUE` 或者 `FALSE`。默认值：`FALSE`。真实业务场景中，待导入的 JSON 数据可能在最外层有一对表示数组结构的中括号 `[]`。这种情况下，一般建议您指定该参数取值为 `true`，这样 StarRocks 会剪裁掉外层的中括号 `[]`，并把中括号 `[]` 里的每个内层数组都作为一行单独的数据导入。如果您指定该参数取值为 `false`，则 StarRocks 会把整个 JSON 数据解析成一个数组，并作为一行数据导入。例如，待导入的 JSON 数据为 `[ {"category" : 1, "author" : 2}, {"category" : 3, "author" : 4} ]`，如果指定该参数取值为 `true`，则 StarRocks 会把 `{"category" : 1, "author" : 2}` 和 `{"category" : 3, "author" : 4}` 解析成两行数据，并导入到目标表中对应的数据行。 |
-| jsonpaths                 | 否           | 用于指定待导入的字段的名称。仅在使用匹配模式导入 JSON 数据时需要指定该参数。参数取值为 JSON 格式。参见[目标表存在衍生列，其列值通过表达式计算生成](#目标表存在衍生列其列值通过表达式计算生成)。|
-| json_root                 | 否           | 如果不需要导入整个 JSON 数据，则指定实际待导入 JSON 数据的根节点。参数取值为合法的 JsonPath。默认值为空，表示会导入整个 JSON 数据。具体请参见本文提供的示例[指定实际待导入 JSON 数据的根节点](#指定实际待导入-json-数据的根节点)。 |
-| task_consume_second                 | 否           |单个 Routine Load 导入作业中每个 Routine Load 导入任务消费数据的最大时长，单位为秒。相较于[FE 动态参数](../../../administration/management/FE_configuration.md) `routine_load_task_consume_second`（作用于集群内部所有 Routine Load 导入作业），该参数仅针对单个 Routine Load 导入作业，更加灵活。该参数自 v3.1.0 起新增。 <ul><li>当未配置 `task_consume_second` 和 `task_timeout_second` 时，StarRocks 则使用 FE 动态参数 `routine_load_task_consume_second` 和`routine_load_task_timeout_second` 来控制导入行为。</li><li>当只配置 `task_consume_second` 时，默认 `task_timeout_second` = `task_consume_second` * 4。</li><li>当只配置 `task_timeout_second` 时，默认 `task_consume_second` = `task_timeout_second` /4。</li></ul>|
-| task_timeout_second                 | 否           | Routine Load 导入作业中每个 Routine Load 导入任务超时时间，单位为秒。相较于[FE 动态参数](../../../administration/management/FE_configuration.md) `routine_load_task_timeout_second`（作用于集群内部所有 Routine Load 导入作业），该参数仅针对单个 Routine Load 导入作业，更加灵活。该参数自 v3.1.0 起新增。<ul><li>当未配置 `task_consume_second` 和 `task_timeout_second` 时，StarRocks 则使用 FE 动态参数 `routine_load_task_consume_second` 和 `routine_load_task_timeout_second` 来控制导入行为。</li><li>当只配置 `task_timeout_second` 时，默认 `task_consume_second` = `task_timeout_second` /4。</li><li>当只配置 `task_consume_second` 时，默认 `task_timeout_second` = `task_consume_second` * 4。</li></ul>|
-
-### `data_source`、`data_source_properties`
-
-数据源和数据源属性。语法:
-
-```Bash
-FROM <data_source>
- ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
-```
-
-`data_source`
-
-必填。指定数据源，目前仅支持取值为 `KAFKA`。
-
-`data_source_properties`
-
-必填。数据源属性，参数以及说明如下：
-
-| **参数**          | **说明**                                                     |
-| ----------------- | ------------------------------------------------------------ |
-| kafka_broker_list | Kafka 的 Broker 连接信息。格式为 `<kafka_broker_ip>:<kafka port>`，多个 Broker 之间以英文逗号 (,) 分隔。 Kafka Broker 默认端口号为 `9092`。示例：`"kafka_broker_list" = "xxx.xx.xxx.xx:9092,xxx.xx.xxx.xx:9092"` |
-| kafka_topic       | Kafka Topic 名称。一个导入作业仅支持消费一个 Topic 的消息。  |
-| kafka_partitions  | 待消费的分区。示例：`"kafka_partitions" = "0, 1, 2, 3"`。如果不配置该参数，则默认消费所有分区。 |
-| kafka_offsets     | 待消费分区的起始消费位点，必须一一对应 `kafka_partitions` 中指定的每个分区。如果不配置该参数，则默认为从分区的末尾开始消费。支持取值为<ul><li> 具体消费位点：从分区中该消费位点的数据开始消费。</li><li>`OFFSET_BEGINNING`：从分区中有数据的位置开始消费。</li><li>`OFFSET_END`：从分区的末尾开始消费。</li></ul>多个起始消费位点之间用英文逗号（, ）分隔。<br />示例： `"kafka_offsets" = "1000, OFFSET_BEGINNING, OFFSET_END, 2000"`。|
-| property.kafka_default_offsets | 所有待消费分区的默认起始消费位点。支持的取值与 `kafka_offsets` 一致。 |
-| confluent.schema.registry.url| 注册该 Avro schema 的 Schema Registry 的 URL，StarRocks 会从该 URL 获取 Avro schema。格式为 `confluent.schema.registry.url = http[s]://[<schema-registry-api-key>:<schema-registry-api-secret>@]<hostname or ip address>[:<port>]`。|
-
-**更多数据源相关参数**
-
-支持设置更多数据源 Kafka 相关参数，功能等同于 Kafka 命令行 `--property`， 支持参数，请参见 [librdkafka 配置项文档](https://github.com/edenhill/librdkafka/blob/master/CONFIGURATION.md)中适用于客户端的配置项。
-
-> **说明**
->
-> 当参数的取值是文件时，则值前加上关键词 `FILE:`。关于如何创建文件，请参见 [CREATE FILE](../Administration/CREATE_FILE.md) 命令文档。
-
-**指定所有待消费分区的默认起始消费位点。**
-
-```Plaintext
-"property.kafka_default_offsets" = "OFFSET_BEGINNING"
-```
-
-`property.kafka_default_offsets` 的取值为具体的消费位点，或者：
-
-- `OFFSET_BEGINNING`：从分区中有数据的位置开始消费。
-- `OFFSET_END`：从分区的末尾开始消费。
-
-**指定导入任务消费 Kafka 时所基于 Consumer Group 的 `group.id`**
-
-```Plaintext
-"property.group.id" = "group_id_0"
-```
-
-如果没有指定 `group.id`，StarRocks 会根据 Routine Load 的导入作业名称生成一个随机值，具体格式为`{job_name}_{random uuid}`，如 `simple_job_0a64fe25-3983-44b2-a4d8-f52d3af4c3e8`。
-
-**指定 BE 访问 Kafka 时的安全协议并配置相关参数**
-
-支持安全协议为 `plaintext`（默认）、`ssl`、`sasl_plaintext` 和 `sasl_ssl`，并且需要根据安全协议配置相关参数。
-
-当安全协议为 `sasl_plaintext` 或 `sasl_ssl` 时，支持如下 SASL 认证机制：
-
-- PLAIN
-- SCRAM-SHA-256 和 SCRAM-SHA-512
-- OAUTHBEARER
-- GSSAPI (Kerberos)
-
-示例：
-
-- 访问 Kafka 时，使用安全协议 SSL
-
-    ```sql
-    "property.security.protocol" = "ssl", -- 指定安全协议为 SSL
-    "property.ssl.ca.location" = "FILE:ca-cert", -- CA 证书的位置
-    --如果 Kafka server 端开启了 client 认证，则还需设置如下三个参数：
-    "property.ssl.certificate.location" = "FILE:client.pem", -- Client 的 public key 的位置
-    "property.ssl.key.location" = "FILE:client.key", -- Client 的 private key 的位置
-    "property.ssl.key.password" = "abcdefg" -- Client 的 private key 的密码
-    ```
-
-- 访问 Kafka 时，使用 SASL_PLAINTEXT 安全协议和 SASL/PLAIN 认证机制
-
-    ```sql
-    "property.security.protocol" = "SASL_PLAINTEXT", -- 指定安全协议为 SASL_PLAINTEXT
-    "property.sasl.mechanism" = "PLAIN", -- 指定 SASL 认证机制为 PLAIN
-    "property.sasl.username" = "admin", -- SASL 的用户名
-    "property.sasl.password" = "admin" -- SASL 的密码
-    ```
-
-- 访问 Kafka 时，使用 SASL_PLAINTEXT 安全协议和 SASL/GSSAPI (Kerberos) 认证机制
-
-  ```sql
-  "property.security.protocol" = "SASL_PLAINTEXT", -- 指定安全协议为 SASL_PLAINTEXT
-  "property.sasl.mechanism" = "GSSAPI", -- 指定 SASL 认证机制为 GSSAPI, 默认是 GSSAPI
-  "property.sasl.kerberos.service.name" = "kafka", -- 指定 broker service name，默认是 Kafka
-  "property.sasl.kerberos.keytab" = "/home/starrocks/starrocks.keytab", -- 指定 client keytab 的位置
-  "property.sasl.kerberos.principal" = "starrocks@YOUR.COM" -- 指定 kerberos principal
-  ```
-
-  :::note
-
-  - 自 StarRocks 3.1.4 版本起，支持 SASL/GSSAPI (Kerberos) 认证。
-  - 需要在 BE 机器上安装 SASL 相关模块。
-
-    ```bash
-    # Debian/Ubuntu:
-    sudo apt-get install libsasl2-modules-gssapi-mit libsasl2-dev
-    # CentOS/Redhat:
-    sudo yum install cyrus-sasl-gssapi cyrus-sasl-devel
-    ```
-
-  :::
-
-### FE 和 BE 配置项
-
-Routine Load 相关配置项，请参见[配置参数](../../../administration/management/FE_configuration.md)。
-
-## 列映射和转换关系
-
-### 导入 CSV 数据
-
-**如果 CSV 格式的数据中的列与目标表中的列的数量或顺序不一致**，则需要通过 `COLUMNS` 参数来指定源数据和目标表之间的列映射和转换关系。一般包括如下两种场景：
-
-- **源数据中的列与目标表中的列数量一致，但是顺序不一致**。并且数据不需要通过函数计算、可以直接落入目标表中对应的列。
-  您需要在 `COLUMNS` 参数中按照源数据中的列顺序、使用目标表中对应的列名来配置列映射和转换关系。
-
-  例如，目标表中有三列，按顺序依次为 `col1`、`col2` 和 `col3`；源数据中也有三列，按顺序依次对应目标表中的 `col3`、`col2` 和 `col1`。这种情况下，需要指定 `COLUMNS(col3, col2, col1)`。
-- **源数据中的列与目标表中的列数量不一致，甚至某些列的数据需要通过转换（函数计算以后）才能落入目标表中对应的列。**
-  您不仅需要在 `COLUMNS` 参数中按照源数据中的列顺序、使用目标表中对应的列名来配置列映射关系，还需要指定参与数据计算的函数。以下为两个示例：
-
-  - **源数据比目标表多列**。
-    比如目标表中有三列，按顺序依次为 `col1`、`col2` 和 `col3` ；源数据中有四列，前三列按顺序依次对应目标表中的 `col1`、`col2` 和 `col3`，第四列在目标表中无对应的列。这种情况下，需要指定 `COLUMNS(col1, col2, col3, temp)`，其中，最后一列可随意指定一个名称（如 `temp`）用于占位即可。
-  - **目标表存在基于源数据的列进行计算后生成的衍生列**。
-    例如源数据中只有一个包含时间数据的列，格式为 `yyyy-mm-dd hh:mm:ss`。目标表中有三列，按顺序依次为 `year`、`month` 和 `day`，均是基于源数据中包含时间数据的列进行计算后生成的衍生列。这种情况下，可以指定 `COLUMNS(col, year = year(col), month=month(col), day=day(col)`。其中，`col` 是源数据中所包含的列的临时命名，`year = year(col)`、`month=month(col)` 和 `day=day(col)` 用于指定从源数据中的 `col` 列提取对应的数据并落入目标表中对应的衍生列，如 `year = year(col)` 表示通过 `year` 函数提取源数据中 `col` 列的 `yyyy` 部分的数据并落入目标表中的 `year` 列。
-
-  有关操作示例，请参见[设置列的映射和转换关系](#设置列的映射和转换关系)。
-
-### 导入 JSON 或 Avro 数据
-
-> **说明**
->
-> 自 3.0.1 版本开始，StarRocks 支持使用 Routine Load 导入 Avro 数据。导入 JSON 或者 Avro 数据时，列映射和转换关系的配置方式相同。因此本小节以导入 Avro 数据为例进行说明。
-
-**如果 JSON 格式的数据中的 Key 名与目标表中的列名不一致**，则需要使用匹配模式导入 JSON 数据，即通过 `jsonpaths` 和 `COLUMNS` 两个参数来指定源数据和目标表之间的列映射和转换关系：
-
-- `jsonpaths` 参数指定待导入 JSON 数据的 Key，并进行排序（就像新生成了 CSV 数据）。
-- `COLUMNS`参数指定待导入 JSON 数据的 Key 与目标表的列的映射关系和数据转换关系。
-  - 与 `jsonpaths`中指定的 Key 按顺序保持一一对应。
-  - 与目标表中的列按名称保持一一对应。
-
-详细示例，请参见[目标表存在衍生列，其列值通过表达式计算生成](#目标表存在衍生列其列值通过表达式计算生成)。
-
-> **说明**
->
-> 如果待导入 JSON 数据中 Key 名（Key的顺序和数量不需要对应）都能对应目标表中列名，则可以使用简单模式导入 JSON 数据，无需配置 `jsonpaths` 和 `COLUMNS`。
-
-## 示例
-
-### 导入 CSV 数据
-
-本小节以 CSV 格式的数据为例，重点阐述在创建导入作业的时候，如何运用各种参数配置来满足不同业务场景下的各种导入要求。
-
-**数据集**
-
-假设 Kafka 集群的 Topic `ordertest1` 存在如下 CSV 格式的数据，其中 CSV 数据中列的含义依次是订单编号、支付日期、顾客姓名、国籍、性别、支付金额。
-
-```Plaintext
-2020050802,2020-05-08,Johann Georg Faust,Deutschland,male,895
-2020050802,2020-05-08,Julien Sorel,France,male,893
-2020050803,2020-05-08,Dorian Grey,UK,male,1262
-2020050901,2020-05-09,Anna Karenina,Russia,female,175
-2020051001,2020-05-10,Tess Durbeyfield,US,female,986
-2020051101,2020-05-11,Edogawa Conan,japan,male,8924
-```
-
-**目标数据库和表**
-
-根据 CSV 数据中需要导入的列， 在 StarRocks 集群的目标数据库 `example_db` 中创建表 `example_tbl1`，建表语句如下：
-
-```SQL
-CREATE TABLE example_db.example_tbl1 ( 
-    `order_id` bigint NOT NULL COMMENT "订单编号",
-    `pay_dt` date NOT NULL COMMENT "支付日期", 
-    `customer_name` varchar(26) NULL COMMENT "顾客姓名", 
-    `nationality` varchar(26) NULL COMMENT "国籍", 
-    `gender` varchar(26) NULL COMMENT "性别", 
-    `price` double NULL COMMENT "支付金额") 
-DUPLICATE KEY (order_id,pay_dt) 
-DISTRIBUTED BY HASH(`order_id`);
-```
-
-#### 从 Topic 指定分区和起始位点开始消费
-
-如果需要指定分区，以及各个分区对应的起始位点，则需要配置参数 `kafka_partitions`、`kafka_offsets`。
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest1",
-    "kafka_partitions" ="0,1,2,3", -- 指定分区
-    "kafka_offsets" = "1000, OFFSET_BEGINNING, OFFSET_END, 2000" -- 指定起始位点
-);
-```
-
-#### 调整导入性能
-
-如果需要提高导入性能，避免出现消费积压等情况，则可以通过设置单个 Routine Load 导入作业的期望任务并发度`desired_concurrent_number`，增加实际任务并行度，将一个导入作业拆分成尽可能多的导入任务并行执行。
-
-> 更多提升导入性能的方式，请参见 [Routine Load常见问题](../../../faq/loading/Routine_load_faq.md)。
-
-请注意，实际任务并行度由如下多个参数组成的公式决定，上限为 BE 节点的数量或者消费分区的数量。
-
-```SQL
-min(alive_be_number, partition_number, desired_concurrent_number, max_routine_load_task_concurrent_num)
-```
-
-因此当消费分区和 BE 节点数量较多，并且大于其余两个参数时，如果您需要增加实际任务并行度，则可以提高`max_routine_load_task_concurrent_num`、 `desired_concurrent_number` 的值。
-
-假设消费分区数量为 `7`，存活 BE 数量为 `5`，`max_routine_load_task_concurrent_num` 为默认值 `5`。此时如果需要增加实际任务并发度至上限，则需要将 `desired_concurrent_number` 设置为 `5`（默认值为 `3`），则计算实际任务并行度 `min(5,7,5,5)` 为 `5`。
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
-PROPERTIES
-(
-"desired_concurrent_number" = "5" -- 设置单个 Routine Load 导入作业的期望任务并发度
-)
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest1"
-);
-```
-
-#### 设置列的映射和转换关系
-
-如果 CSV 格式的数据中的列与目标表中的列的数量或顺序不一致，假设无需导入 CSV 数据的第五列至目标表，则需要通过 `COLUMNS` 参数来指定源数据和目标表之间的列映射和转换关系。
-
-**目标数据库和表**
-
-根据 CSV 数据中需要导入的几列（例如除第五列性别外的其余五列需要导入至 StarRocks）， 在 StarRocks 集群的目标数据库 `example_db` 中创建表 `example_tbl2`。
-
-```SQL
-CREATE TABLE example_db.example_tbl2 ( 
-    `order_id` bigint NOT NULL COMMENT "订单编号",
-    `pay_dt` date NOT NULL COMMENT "支付日期", 
-    `customer_name` varchar(26) NULL COMMENT "顾客姓名", 
-    `nationality` varchar(26) NULL COMMENT "国籍", 
-    `price` double NULL COMMENT "支付金额"
-) 
-DUPLICATE KEY (order_id,pay_dt) 
-DISTRIBUTED BY HASH(`order_id`);
-```
-
-**导入作业**
-
-本示例中，由于无需导入 CSV 数据的第五列至目标表，因此`COLUMNS`中把第五列临时命名为 `temp_gender` 用于占位，其他列都直接映射至表 `example_tbl2` 中。
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl2_ordertest1 ON example_tbl2
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, temp_gender, price)
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest1"
-);
-```
-
-#### 设置过滤条件 筛选待导入的数据
-
-如果仅导入满足条件的数据，则可以在 WHERE 子句中设置过滤条件，例如`price > 100`。
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price),
-WHERE price > 100
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest1"
-);
-```
-
-#### 设置导入任务为严格模式
-
-在`PROPERTIES`中设置`"strict_mode" = "true"`，表示导入作业为严格模式。如果源数据某列的值为 NULL，但是目标表中该列不允许为 NULL，则该行数据会被过滤掉。
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
-PROPERTIES
-(
-"strict_mode" = "true" -- 设置导入作业为严格模式
-)
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest1"
-);
-```
-
-#### 设置导入任务的容错率
-
-如果业务场景对数据质量的有要求，则需要设置参数`max_batch_rows`和`max_error_number`设置错误检测窗口的范围和允许的错误数据行数的上限，当错误数据行数超过该值时，导入作业会暂停。
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
-PROPERTIES
-(
-"max_batch_rows" = "100000", -- 错误检测窗口范围为单个 Routine Load 导入任务所消费的 10 * max-batch-rows 行数。
-"max_error_number" = "100" -- 错误检测窗口范围内允许的错误数据行数的上限
-)
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest1"
-);
-```
-
-#### 指定安全协议为 SSL 并配置相关参数
-
-如果需要指定 BE 访问 Kafka 时使用的安全协议为 SSL，则需要配置 `"property.security.protocol" = "ssl"` 等参数。
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
-PROPERTIES
-(
-"desired_concurrent_number" = "5"
-)
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest1",
-    "property.security.protocol" = "ssl", -- 使用 SSL 加密
-    "property.ssl.ca.location" = "FILE:ca-cert", -- CA 证书的位置
-    -- 如果 Kafka Server 端开启了 Client 身份认证，则还需设置如下三个参数：
-    "property.ssl.certificate.location" = "FILE:client.pem", -- Client 的 Public Key 的位置
-    "property.ssl.key.location" = "FILE:client.key", -- Client 的 Private Key 的位置
-    "property.ssl.key.password" = "abcdefg" -- Client 的 Private Key 的密码
-);
-```
-
-#### 设置 `trim_space`、`enclose` 和 `escape`
-
-假设 Kafka 集群的 Topic `test_csv` 存在如下 CSV 格式的数据，其中 CSV 数据中列的含义依次是订单编号、支付日期、顾客姓名、国籍、性别、支付金额。
-
-```Plain
- "2020050802" , "2020-05-08" , "Johann Georg Faust" , "Deutschland" , "male" , "895"
- "2020050802" , "2020-05-08" , "Julien Sorel" , "France" , "male" , "893"
- "2020050803" , "2020-05-08" , "Dorian Grey\,Lord Henry" , "UK" , "male" , "1262"
- "2020050901" , "2020-05-09" , "Anna Karenina" , "Russia" , "female" , "175"
- "2020051001" , "2020-05-10" , "Tess Durbeyfield" , "US" , "female" , "986"
- "2020051101" , "2020-05-11" , "Edogawa Conan" , "japan" , "male" , "8924"
-```
-
-如果要把 Topic `test_csv` 中所有的数据都导入到 `example_tbl1` 中，并且希望去除被 `enclose` 指定字符括起来的字段前后的空格、 指定 `enclose` 字符为双引号 (")、并且指定 `escape` 字符为斜杠 (`\`)，可以执行如下语句：
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl1_test_csv ON example_tbl1
-COLUMNS TERMINATED BY ",",
-COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
-PROPERTIES
-(
-    "trim_space"="true",
-    "enclose"="\"",
-    "escape"="\\"
-)
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic"="test_csv",
-    "property.kafka_default_offsets"="OFFSET_BEGINNING"
-);
-```
-
-### 导入 JSON 格式数据
-
-#### 目标表的列名与 JSON 数据的 Key 一致
-
-可以使用简单模式导入数据，即创建导入作业时无需使用 `jsonpaths` 和 `COLUMNS` 参数。StarRocks 会按照目标表的列名去对应 JSON 数据的 Key。
-
-**数据集**
-
-假设 Kafka 集群的 Topic `ordertest2` 中存在如下 JSON 数据。
-
-```JSON
-{"commodity_id": "1", "customer_name": "Mark Twain", "country": "US","pay_time": 1589191487,"price": 875}
-{"commodity_id": "2", "customer_name": "Oscar Wilde", "country": "UK","pay_time": 1589191487,"price": 895}
-{"commodity_id": "3", "customer_name": "Antoine de Saint-Exupéry","country": "France","pay_time": 1589191487,"price": 895}
-```
-
-> 注意
->
-> 这里每行一个 JSON 对象必须在一个 Kafka 消息中，否则会出现“JSON 解析错误”的问题。
-
-**目标数据库和表**
-
-在 StarRocks 集群的目标数据库 `example_db` 中创建表 `example_tbl3` ，并且列名与 JSON 数据中需要导入的 Key 一致。
-
-```SQL
-CREATE TABLE example_db.example_tbl3 ( 
-    `commodity_id` varchar(26) NULL COMMENT "品类ID", 
-    `customer_name` varchar(26) NULL COMMENT "顾客姓名", 
-    `country` varchar(26) NULL COMMENT "顾客国籍", 
-    `pay_time` bigint(20) NULL COMMENT "支付时间", 
-    `price` double SUM NULL COMMENT "支付金额") 
-AGGREGATE KEY(`commodity_id`,`customer_name`,`country`,`pay_time`) 
-DISTRIBUTED BY HASH(`commodity_id`);
-```
-
-**导入作业**
-
-提交导入作业时使用简单模式，即无需使用`jsonpaths` 和 `COLUMNS` 参数，就可以将 Kafka 集群的 Topic `ordertest2` 中的 JSON 数据导入至目标表 `example_tbl3` 中。
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl3_ordertest2 ON example_tbl3
-PROPERTIES
-(
-    "format" = "json"
- )
-FROM KAFKA
-(
-    "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest2"
-);
-```
-
-> **说明**
->
-> - 如果 JSON 数据最外层是数组结构，则需要在`PROPERTIES`设置`"strip_outer_array"="true"`，表示裁剪最外层的数组结构。并且需要注意在设置 `jsonpaths` 时，整个 JSON 数据的根节点是裁剪最外层的数组结构后**展平的 JSON 对象**。
-> - 如果不需要导入整个 JSON 数据，则需要使用 `json_root` 指定实际所需导入的 JSON 数据根节点。
-
-#### 目标表存在衍生列，其列值通过表达式计算生成
-
-需要使用匹配模式导入数据，即需要使用 `jsonpaths` 和 `COLUMNS` 参数，`jsonpaths`指定待导入 JSON 数据的 Key，`COLUMNS` 参数指定待导入 JSON 数据的 Key 与目标表的列的映射关系和数据转换关系。
-
-**数据集**
-
-假设 Kafka 集群的 Topic `ordertest2` 中存在如下 JSON 格式的数据。
-
-```JSON
-{"commodity_id": "1", "customer_name": "Mark Twain", "country": "US","pay_time": 1589191487,"price": 875}
-{"commodity_id": "2", "customer_name": "Oscar Wilde", "country": "UK","pay_time": 1589191487,"price": 895}
-{"commodity_id": "3", "customer_name": "Antoine de Saint-Exupéry","country": "France","pay_time": 1589191487,"price": 895}
-```
-
-**目标数据库和表**
-
-假设在 StarRocks 集群的目标数据库 `example_db` 中存在目标表 `example_tbl4` 其中有一列衍生列 `pay_dt`，是基于 JSON 数据的Key `pay_time` 进行计算后的数据。其建表语句如下：
-
-```SQL
-CREATE TABLE example_db.example_tbl4 ( 
-    `commodity_id` varchar(26) NULL COMMENT "品类ID", 
-    `customer_name` varchar(26) NULL COMMENT "顾客姓名", 
-    `country` varchar(26) NULL COMMENT "顾客国籍",
-    `pay_time` bigint(20) NULL COMMENT "支付时间",  
-    `pay_dt` date NULL COMMENT "支付日期", 
-    `price`double SUM NULL COMMENT "支付金额") 
-AGGREGATE KEY(`commodity_id`,`customer_name`,`country`,`pay_time`,`pay_dt`) 
-DISTRIBUTED BY HASH(`commodity_id`);
-```
-
-**导入作业**
-
-提交导入作业时使用匹配模式。使用 `jsonpaths` 指定待导入 JSON 数据的 Key。并且由于 JSON 数据中 key `pay_time` 需要转换为 DATE 类型，才能导入到目标表的列 `pay_dt`，因此 `COLUMNS` 中需要使用函数`from_unixtime`进行转换。JSON 数据的其他 key 都能直接映射至表 `example_tbl4` 中。
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl4_ordertest2 ON example_tbl4
-COLUMNS(commodity_id, customer_name, country, pay_time, pay_dt=from_unixtime(pay_time, '%Y%m%d'), price)
-PROPERTIES
-(
-    "format" = "json",
-    "jsonpaths" = "[\"$.commodity_id\",\"$.customer_name\",\"$.country\",\"$.pay_time\",\"$.price\"]"
- )
-FROM KAFKA
-(
-    "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest2"
-);
-```
-
-> **说明**
->
-> - 如果 JSON 数据最外层是数组结构，则需要在`PROPERTIES`设置`"strip_outer_array"="true"`，表示裁剪最外层的数组结构。并且需要注意在设置 `jsonpaths` 时，整个 JSON 数据的根节点是裁剪最外层的数组结构后**展平的 JSON 对象**。
-> - 如果不需要导入整个 JSON 数据，则需要使用 `json_root` 指定实际所需导入的 JSON 数据根节点。
-
-#### 目标表存在衍生列，其列值通过 CASE 表达式计算生成
-
-**数据集**
-
-假设 Kafka 集群的 Topic `topic-expr-test` 中存在如下 JSON 格式的数据。
-
-```JSON
-{"key1":1, "key2": 21}
-{"key1":12, "key2": 22}
-{"key1":13, "key2": 23}
-{"key1":14, "key2": 24}
-```
-
-**目标数据库和表**
-
-假设在 StarRocks 集群的目标数据库 `example_db` 中存在目标表 `tbl_expr_test` 包含两列，其中列 `col2` 的值基于 JSON 数据进行 CASE 表达式计算得出。其建表语句如下：
-
-```SQL
-CREATE TABLE tbl_expr_test (
-    col1 string, col2 string)
-DISTRIBUTED BY HASH (col1);
-```
-
-**导入作业**
-
-目标表中列 `col2` 的值需要基于 JSON 数据进行 CASE 表达式计算后得出，因此您需要在导入作业中的 `COLUMNS` 参数配置对应的 CASE 表达式。
-
-```SQL
-CREATE ROUTINE LOAD rl_expr_test ON tbl_expr_test
-COLUMNS (
-      key1,
-      key2,
-      col1 = key1,
-      col2 = CASE WHEN key1 = "1" THEN "key1=1" 
-                  WHEN key1 = "12" THEN "key1=12"
-                  ELSE "nothing" END) 
-PROPERTIES ("format" = "json")
-FROM KAFKA
-(
-    "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "topic-expr-test"
-);
-```
-
-**查询数据**
-
-查询目标表中的数据，返回结果显示列 `col2` 的值是使用 CASE 表达式计算后输出的值。
-
-```SQL
-MySQL [example_db]> SELECT * FROM tbl_expr_test;
-+------+---------+
-| col1 | col2    |
-+------+---------+
-| 1    | key1=1  |
-| 12   | key1=12 |
-| 13   | nothing |
-| 14   | nothing |
-+------+---------+
-4 rows in set (0.015 sec)
-```
-
-#### 指定实际待导入 JSON 数据的根节点
-
-如果不需要导入整个 JSON 数据，则需要使用 `json_root` 指定实际上所需导入的 JSON 数据的根对象，参数取值为合法的 JsonPath。
-
-**数据集**
-
-假设 Kafka 集群的 Topic `ordertest3` 中存在如下 JSON 格式的数据，实际导入时仅需要导入 key `RECORDS`的值。
-
-```JSON
-{"RECORDS":[{"commodity_id": "1", "customer_name": "Mark Twain", "country": "US","pay_time": 1589191487,"price": 875},{"commodity_id": "2", "customer_name": "Oscar Wilde", "country": "UK","pay_time": 1589191487,"price": 895},{"commodity_id": "3", "customer_name": "Antoine de Saint-Exupéry","country": "France","pay_time": 1589191487,"price": 895}]}
-```
-
-**目标数据库和表**
-
-假设在 StarRocks 集群的目标数据库 `example_db` 中存在目标表`example_tbl3` ，其建表语句如下：
-
-```SQL
-CREATE TABLE example_db.example_tbl3 ( 
-    `commodity_id` varchar(26) NULL COMMENT "品类ID", 
-    `customer_name` varchar(26) NULL COMMENT "顾客姓名", 
-    `country` varchar(26) NULL COMMENT "顾客国籍", 
-    `pay_time` bigint(20) NULL COMMENT "支付时间", 
-    `price`double SUM NULL COMMENT "支付金额") 
-AGGREGATE KEY(`commodity_id`,`customer_name`,`country`,`pay_time`) 
-DISTRIBUTED BY HASH(`commodity_id`);
-```
-
-**导入作业**
-
-提交导入作业，设置`"json_root" = "$.RECORDS"`指定实际待导入的 JSON 数据的根节点。并且由于实际待导入的 JSON 数据是数组结构，因此还需要设置`"strip_outer_array" = "true"`，裁剪外层的数组结构。
-
-```SQL
-CREATE ROUTINE LOAD example_db.example_tbl3_ordertest3 ON example_tbl3
-PROPERTIES
-(
-    "format" = "json",
-    "strip_outer_array" = "true",
-    "json_root" = "$.RECORDS"
- )
-FROM KAFKA
-(
-    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
-    "kafka_topic" = "ordertest2"
-);
-```
-
-### 导入 Avro 数据
-
-自 3.0.1 版本开始，StarRocks 支持使用 Routine Load 导入 Avro 数据。
-
-#### Avro schema 只包含简单数据类型
-
-假设 Avro schema 只包含简单数据类型，并且您需要导入 Avro 数据中的所有字段。
-
-**数据集**
-
-**Avro schema**
-
-1. 创建如下 Avro schema 文件 `avro_schema1.avsc`：
-
-      ```json
-      {
-          "type": "record",
-          "name": "sensor_log",
-          "fields" : [
-              {"name": "id", "type": "long"},
-              {"name": "name", "type": "string"},
-              {"name": "checked", "type" : "boolean"},
-              {"name": "data", "type": "double"},
-              {"name": "sensor_type", "type": {"type": "enum", "name": "sensor_type_enum", "symbols" : ["TEMPERATURE", "HUMIDITY", "AIR-PRESSURE"]}}  
-          ]
-      }
-      ```
-
-2. 注册该 Avro schema 至 [Schema Registry](https://docs.confluent.io/platform/current/schema-registry/index.html)。
-
-**Avro 数据**
-
-构建 Avro 数据并且发送至 Kafka 集群的 topic `topic_1`。
-
-**目标数据库和表**
-
-根据 Avro 数据中需要导入的字段，在 StarRocks 集群的目标数据库 `sensor` 中创建表 `sensor_log1`。表的列名与 Avro 数据的字段名保持一致。两者的数据类型映射关系，请参见xxx。
-
-```SQL
-CREATE TABLE sensor.sensor_log1 ( 
-    `id` bigint NOT NULL COMMENT "sensor id",
-    `name` varchar(26) NOT NULL COMMENT "sensor name", 
-    `checked` boolean NOT NULL COMMENT "checked", 
-    `data` double NULL COMMENT "sensor data", 
-    `sensor_type` varchar(26) NOT NULL COMMENT "sensor type"
-) 
-ENGINE=OLAP 
-DUPLICATE KEY (id) 
-DISTRIBUTED BY HASH(`id`);
-```
-
-**导入作业**
-
-提交导入作业时使用简单模式，即无需使用 `jsonpaths` 参数，就可以将 Kafka 集群的 Topic `topic_1` 中的 Avro 数据导入至数据库 `sensor` 中的表 `sensor_log1`。
-
-```sql
-CREATE ROUTINE LOAD sensor.sensor_log_load_job1 ON sensor_log1  
-PROPERTIES  
-(  
-  "format" = "avro"  
-)  
-FROM KAFKA  
-(  
-  "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>,...",
-  "confluent.schema.registry.url" = "http://172.xx.xxx.xxx:8081",  
-  "kafka_topic" = "topic_1",  
-  "kafka_partitions" = "0,1,2,3,4,5",  
-  "property.kafka_default_offsets" = "OFFSET_BEGINNING"  
-);
-```
-
-#### Avro schema 嵌套 Record 类型的字段
-
-假设 Avro schema 嵌套 Record 类型的字段，并且您需要导入嵌套 Record 字段中的子字段。
-
-**数据集**
-
-**Avro schema**
-
-1. 创建如下 Avro schema 文件 `avro_schema2.avsc`。其中最外层 Record 的字段依次是 `id`、 `name`、`checked`、`sensor_type` 和 `data`。并且字段 `data` 包含嵌套 Record `data_record`。
-
-      ```JSON
-      {
-          "type": "record",
-          "name": "sensor_log",
-          "fields" : [
-              {"name": "id", "type": "long"},
-              {"name": "name", "type": "string"},
-              {"name": "checked", "type" : "boolean"},
-              {"name": "sensor_type", "type": {"type": "enum", "name": "sensor_type_enum", "symbols" : ["TEMPERATURE", "HUMIDITY", "AIR-PRESSURE"]}},
-              {"name": "data", "type": 
-                  {
-                      "type": "record",
-                      "name": "data_record",
-                      "fields" : [
-                          {"name": "data_x", "type" : "boolean"},
-                          {"name": "data_y", "type": "long"}
-                      ]
-                  }
-              }
-          ]
-      }
-      ```
-
-2. 注册该 Avro schema 至 [Schema Registry](https://docs.confluent.io/platform/current/schema-registry/index.html)。
-
-**Avro 数据**
-
-构建 Avro 数据并且发送至 Kafka 集群的 topic `topic_2`。
-
-**目标数据库和表**
-
-根据 Avro 数据中需要导入的字段，在 StarRocks 集群的目标数据库 `sensor` 中创建表 `sensor_log2`。
-
-假设您除了需要导入最外层 Record 的 `id`、`name`、`checked`、`sensor_type` 字段之外，还需要导入嵌套 Record 中的字段 `data_y`。
-
-```sql
-CREATE TABLE sensor.sensor_log2 ( 
-    `id` bigint NOT NULL COMMENT "sensor id",
-    `name` varchar(26) NOT NULL COMMENT "sensor name", 
-    `checked` boolean NOT NULL COMMENT "checked", 
-    `sensor_type` varchar(26) NOT NULL COMMENT "sensor type",
-    `data_y` long NULL COMMENT "sensor data" 
-) 
-ENGINE=OLAP 
-DUPLICATE KEY (id) 
-DISTRIBUTED BY HASH(`id`);
-```
-
-**导入作业**
-
-提交导入作业，使用 `jsonpaths` 指定实际待导入的 Avro 数据的字段。其中对于嵌套 Record 中的字段 `data_y`，您需要指定 `jsonpaths` 为 `"$.data.data_y"`。
-
-```sql
-CREATE ROUTINE LOAD sensor.sensor_log_load_job2 ON sensor_log2  
-PROPERTIES  
-(  
-  "format" = "avro",
-  "jsonpaths" = "[\"$.id\",\"$.name\",\"$.checked\",\"$.sensor_type\",\"$.data.data_y\"]"
-)  
-FROM KAFKA  
-(  
-  "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>,...",
-  "confluent.schema.registry.url" = "http://172.xx.xxx.xxx:8081",  
-  "kafka_topic" = "topic_1",  
-  "kafka_partitions" = "0,1,2,3,4,5",  
-  "property.kafka_default_offsets" = "OFFSET_BEGINNING"  
-);
-```
-
-#### Avro schema 包含 Union 类型的字段
-
-**数据集**
-
-假设 Avro 数据包含 Union 类型的字段，并且您需要导入该 Union 字段。
-
-**Avro schema**
-
-1. 创建如下 Avro schema 文件 `avro_schema3.avsc`。其中最外层 Record 的字段依次是`id`、`name`、 `checked`、 `sensor_type` 和 `data`。并且字段 `data`为 Union 类型，包含两个元素，分别是 `null` 和嵌套 Record `data_record` 。
-
-      ```JSON
-      {
-          "type": "record",
-          "name": "sensor_log",
-          "fields" : [
-              {"name": "id", "type": "long"},
-              {"name": "name", "type": "string"},
-              {"name": "checked", "type" : "boolean"},
-              {"name": "sensor_type", "type": {"type": "enum", "name": "sensor_type_enum", "symbols" : ["TEMPERATURE", "HUMIDITY", "AIR-PRESSURE"]}},
-              {"name": "data", "type": [null,
-                    {
-                        "type": "record",
-                        "name": "data_record",
-                        "fields" : [
-                            {"name": "data_x", "type" : "boolean"},
-                            {"name": "data_y", "type": "long"}
-                        ]
-                    }
-                  ]
-              }
-          ]
-      }
-      ```
-
-2. 注册该 Avro schema 至 [Schema Registry](https://docs.confluent.io/platform/current/schema-registry/index.html)。
-
-**Avro 数据**
-
-构建 Avro 数据并且发送至 Kafka 集群的 topic `topic_3`。
-
-**目标数据库和表**
-
-根据 Avro 数据中需要导入的字段，在 StarRocks 集群的目标数据库 `sensor` 中创建表 `sensor_log3` 。
-
-假设您除了需要导入最外层 Record 的 `id`、`name`、`checked`、`sensor_type` 字段之外，还需要导入 Union 类型的字段 `data` 中元素 `data_record` 包含的字段 `data_y`。
-
-```sql
-CREATE TABLE sensor.sensor_log3 ( 
-    `id` bigint NOT NULL COMMENT "sensor id",
-    `name` varchar(26) NOT NULL COMMENT "sensor name", 
-    `checked` boolean NOT NULL COMMENT "checked", 
-    `sensor_type` varchar(26) NOT NULL COMMENT "sensor type",
-    `data_y` long NULL COMMENT "sensor data" 
-) 
-ENGINE=OLAP 
-DUPLICATE KEY (id) 
-DISTRIBUTED BY HASH(`id`);
-```
-
-**导入作业**
-
-提交导入作业，使用 `jsonpaths` 指定实际待导入的 Avro 数据的字段。其中您需要指定字段 `data_y`的`jsonpaths` 为 `"$.data.data_y"`。
-
-```sql
-CREATE ROUTINE LOAD sensor.sensor_log_load_job3 ON sensor_log3  
-PROPERTIES  
-(  
-  "format" = "avro",
-  "jsonpaths" = "[\"$.id\",\"$.name\",\"$.checked\",\"$.sensor_type\",\"$.data.data_y\"]"
-)  
-FROM KAFKA  
-(  
-  "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>,...",
-  "confluent.schema.registry.url" = "http://172.xx.xxx.xxx:8081",  
-  "kafka_topic" = "topic_1",  
-  "kafka_partitions" = "0,1,2,3,4,5",  
-  "property.kafka_default_offsets" = "OFFSET_BEGINNING"  
-);
-```
-
-当 Union 类型的字段 `data` 的值为 `null` 时，则导入 `data_y` 列的值为 `null`。当 `data` 的值为一条 data record 时，则导入  `data_y` 列的值 Long 类型。
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/DELETE.md b/docs/zh/sql-reference/sql-statements/data-manipulation/DELETE.md
deleted file mode 100644
index a96e595b03a973..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/DELETE.md
+++ /dev/null
@@ -1,391 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DELETE
-
-该语句用于从表中删除数据行。表可以是分区表或者非分区表。
-
-对于明细表、聚合表，以及更新表，支持删除表中**指定分区**的数据。从 2.3 版本开始，主键表支持完整的 DELETE...WHERE 语义，即支持按主键、任意列、以及子查询结果删除数据。从 3.0 版本开始，主键类型表丰富了 DELETE...WHERE 语义，支持使用多表关联和公用表表达式（CTE）。
-
-## 注意事项
-
-- 执行 DELETE 操作需要有对应表的 DELETE 权限。
-- 不建议您执行高频的 DELETE 操作。如需要，请在业务低峰期进行。
-- DELETE 删除的是表中数据，表依然存在。如果要删除表，参见 [DROP TABLE](../data-definition/DROP_TABLE.md)。
-- 为防止误删整表，必须在 DELETE 语句中指定 WHERE 子句。
-- 删除的数据会标记为“Deleted”，暂时保留在 Segment 中，不会立即进行物理删除。Compaction（数据版本合并）完成之后会被回收。
-- 该操作会同时删除和表相关的物化视图的数据。
-
-## DELETE 与明细类型、聚合类型和更新类型表
-
-### 语法
-
-```SQL
-DELETE FROM [<db_name>.]<table_name> [PARTITION <partition_name>]
-WHERE
-column_name1 op { value | value_list } [ AND column_name2 op { value | value_list } ...]
-```
-
-### 参数说明
-
-| **参数**         | **必选** | **描述**                                                     |
-| ---------------- | -------- | ------------------------------------------------------------ |
-| `db_name`        | No       | 要操作的表所在的数据库。如果不指定，默认为当前数据库。       |
-| `table_name`     | Yes      | 要操作的表名。                                               |
-| `partition_name` | No       | 要操作的分区名。                                             |
-| `column_name`    | Yes      | 作为删除条件的列，可以指定一个或多个列。                     |
-| `op`             | Yes      | 指定的算子。支持 `=`、`>`、`<`、`>=`、`<=`、`!=`、`IN` 和 `NOT IN`。 |
-
-### 使用限制
-
-- 聚合类型和更新类型表**仅支持 Key 列**作为删除条件。明细类型表支持**任意列**作为删除条件。
-- 条件之间只能是“AND”关系。若希望达成“OR”的关系，需要将条件分别写在两个 DELETE 语句中。
-- 明细类型、聚合类型和更新表类型下，DELETE 语句目前不支持以子查询结果作为删除条件。
-
-### 影响
-
-执行 DELETE 语句后，可能会导致接下来一段时间内（Compaction 完成之前）的查询效率降低。影响程度取决于语句中指定的删除条件的数量。指定的条件越多，影响越大。
-
-### 示例
-
-#### 创建表并插入数据
-
-以下示例创建一张明细类型的分区表。
-
-```SQL
-CREATE TABLE `my_table` (
-    `date` date NOT NULL,
-    `k1` int(11) NOT NULL COMMENT "",
-    `k2` varchar(65533) NULL DEFAULT "" COMMENT "")
-DUPLICATE KEY(`date`)
-PARTITION BY RANGE(`date`)
-(
-    PARTITION p1 VALUES [('2022-03-11'), ('2022-03-12')),
-    PARTITION p2 VALUES [('2022-03-12'), ('2022-03-13'))
-)
-DISTRIBUTED BY HASH(`date`)
-PROPERTIES
-("replication_num" = "3");
-
-INSERT INTO `my_table` VALUES
-('2022-03-11', 3, 'abc'),
-('2022-03-11', 2, 'acb'),
-('2022-03-11', 4, 'abc'),
-('2022-03-12', 2, 'bca'),
-('2022-03-12', 4, 'cba'),
-('2022-03-12', 5, 'cba');
-```
-
-#### 查询表数据
-
-```SQL
-select * from my_table order by date; 
-+------------+------+------+
-| date       | k1   | k2   |
-+------------+------+------+
-| 2022-03-11 |    3 | abc  |
-| 2022-03-11 |    2 | acb  |
-| 2022-03-11 |    4 | abc  |
-| 2022-03-12 |    2 | bca  |
-| 2022-03-12 |    4 | cba  |
-| 2022-03-12 |    5 | cba  |
-+------------+------+------+
-```
-
-#### 删除数据
-
-**删除指定分区中的行**
-
-删除 `my_table` 表 `p1` 分区中 `k1` 列值为 `3` 的数据行。
-
-```SQL
-DELETE FROM my_table PARTITION p1
-WHERE k1 = 3;
-
--- 可以看到 p1 分区中 k1 为 3 的那行数据被删除。
-select * from my_table partition (p1);
-+------------+------+------+
-| date       | k1   | k2   |
-+------------+------+------+
-| 2022-03-11 |    2 | acb  |
-| 2022-03-11 |    4 | abc  |
-+------------+------+------+
-```
-
-**删除指定分区中满足 AND 条件的行**
-
-删除 `my_table` 表 `p1` 分区中 `k1` 列值大于等于 `3` 且 `k2` 列值为 `"abc"` 的数据行。
-
-```SQL
-DELETE FROM my_table PARTITION p1
-WHERE k1 >= 3 AND k2 = "abc";
-
-select * from my_table partition (p1);
-+------------+------+------+
-| date       | k1   | k2   |
-+------------+------+------+
-| 2022-03-11 |    2 | acb  |
-+------------+------+------+
-```
-
-**删除所有分区中满足条件的行**
-
-删除 `my_table` 表所有分区中 `k2` 列值为 `"abc"` 或 `"cba"` 的数据行。
-
-```SQL
-DELETE FROM my_table
-WHERE k2 in ("abc", "cba");
-
-select * from my_table order by date;
-+------------+------+------+
-| date       | k1   | k2   |
-+------------+------+------+
-| 2022-03-11 |    2 | acb  |
-| 2022-03-12 |    2 | bca  |
-+------------+------+------+
-```
-
-## DELETE 与主键类型表
-
-从 2.3 版本开始，主键类型表支持完整的 DELETE...WHERE 语义。支持按主键、任意列、以及子查询结果删除数据。从 3.0 版本开始，StarRocks 丰富了 DELETE...WHERE 语义，支持使用多表关联和公用表表达式（CTE）。如果需要将待操作的表与数据库中其他表关联，则可以在 USING 子句或 CTE 中引用其他的表。
-
-### 语法
-
-```SQL
-[ WITH <with_query> [, ...] ]
-DELETE FROM <table_name>
-[ USING <from_item> [, ...] ]
-[ WHERE <where_condition> ]
-```
-
-### 参数说明
-
-| 参数            | 是否必选 | 描述                                                         |
-| --------------- | -------- | ------------------------------------------------------------ |
-| with_query      | No       | 一个或多个可以在 DELETE 语句中通过名字引用的 CTE。CTE 是一个临时结果集，可以提高复杂语句的易读性。 |
-| table_name      | Yes      | 要操作的表名。                                               |
-| from_item       | No       | 引用数据库中一个或者多个其他的表。该表与待操作的表进行连接，WHERE 子句指定连接条件，最终 StarRocks 基于连接查询的结果集删除待操作表中的匹配行。 例如 USING 子句为 `USING t1 WHERE t0.pk = t1.pk;`，StarRocks 实际执行 DELETE 语句时会将该 USING 子句的表表达式会转换为 `t0 JOIN t1 ON t0.pk=t1.pk;`。 |
-| where_condition | No       | 只有满足 WHERE 条件的行才会被删除。该参数为必选，防止误删整张表。如需删除表中的所有行，请使用 `WHERE true`。 |
-
-### 注意事项
-
-- 主键类型表目前**还不支持**删除指定分区中的数据，例如 `DELETE FROM <table_name> PARTITION <partition_id> WHERE <where_condition>`。
-- 支持如下比较运算符：`=`、`>`、`<`、`>=`、`<=`、`!=`、`IN` 和 `NOT IN`。
-- 支持如下逻辑运算符：`AND` 和 `OR`。
-- 不支持并发删除或导入数据时删除，因为可能无法保证导入的事务性。
-
-### 示例
-
-#### 创建表并插入数据
-
-在数据库 `test` 中创建一张名为 `score_board` 的主键类型表：
-
-```SQL
-CREATE TABLE `score_board` (
-    `id` int(11) NOT NULL COMMENT "",
-    `name` varchar(65533) NULL DEFAULT "" COMMENT "",
-    `score` int(11) NOT NULL DEFAULT "0" COMMENT "")
-ENGINE=OLAP
-PRIMARY KEY(`id`)
-COMMENT "OLAP"
-DISTRIBUTED BY HASH(`id`)
-PROPERTIES
-(
-    "replication_num" = "3",
-    "storage_format" = "DEFAULT",
-    "enable_persistent_index" = "false"
-);
-
-INSERT INTO score_board VALUES
-(0, 'Jack', 21),
-(1, 'Bob', 21),
-(2, 'Stan', 21),
-(3, 'Sam', 22);
-```
-
-#### 查询表数据
-
-```Plain
-select * from score_board;
-+------+------+------+
-| id   | name | score|
-+------+------+------+
-|    0 | Jack |   21 |
-|    1 | Bob  |   21 |
-|    2 | Stan |   21 |
-|    3 | Sam  |   22 |
-+------+------+------+
-4 rows in set (0.00 sec)
-```
-
-#### 删除数据
-
-**按主键删除数据**
-
-通过指定主键，可以避免全表扫描。
-
-删除 `score_board` 表中 `id` 列值为 `0` 的数据行。
-
-```SQL
-DELETE FROM score_board WHERE id = 0;
-
-select * from score_board;
-+------+------+------+
-| id   | name | score|
-+------+------+------+
-|    1 | Bob  |   21 |
-|    2 | Stan |   21 |
-|    3 | Sam  |   22 |
-+------+------+------+
-3 rows in set (0.01 sec)
-```
-
-**按条件删除数据**
-
-条件中的列，可以为任意列。
-
-示例一：删除 `score_board` 表中 `score` 列值等于 `22` 的所有数据行。
-
-```SQL
-DELETE FROM score_board WHERE score = 22;
-
-select * from score_board;
-+------+------+------+
-| id   | name | score|
-+------+------+------+
-|    0 | Jack |   21 |
-|    1 | Bob  |   21 |
-|    2 | Stan |   21 |
-+------+------+------+
-3 rows in set (0.01 sec)
-```
-
-示例二：删除 `score_board` 表中 `score` 列值小于 `22` 的所有数据行。
-
-```SQL
-DELETE FROM score_board WHERE score < 22;
-
-select * from score_board;
-+------+------+------+
-| id   | name | score|
-+------+------+------+
-|    3 | Sam  |   22 |
-+------+------+------+
-1 row in set (0.01 sec)
-```
-
-示例三：删除 `score_board` 表中 `score` 列值小于 `22`、且 `name` 列值不为 `Bob` 的所有数据行。
-
-```SQL
-DELETE FROM score_board WHERE score < 22 and name != "Bob";
-
-select * from score_board;
-+------+------+------+
-| id   | name | score|
-+------+------+------+
-|    1 | Bob  |   21 |
-|    3 | Sam  |   22 |
-+------+------+------+
-2 rows in set (0.00 sec)
-```
-
-**按子查询结果删除数据**
-
-可以在 `DELETE` 语句中嵌套一个或多个子查询，并使用子查询结果作为删除条件。
-
-开始删除操作之前，先在数据库 `test` 中再创建一张名为 `users` 的主键类型表：
-
-```SQL
-CREATE TABLE
-    `users` (`uid` int(11) NOT NULL COMMENT "",
-    `name` varchar(65533) NOT NULL COMMENT "",
-    `country` varchar(65533) NULL COMMENT "")
-ENGINE=OLAP
-PRIMARY KEY(`uid`)COMMENT "OLAP"
-DISTRIBUTED BY HASH(`uid`)
-PROPERTIES
-(
-    "replication_num" = "3",
-    "storage_format" = "DEFAULT",
-    "enable_persistent_index" = "false"
-);
-```
-
-向 `users` 表中插入数据：
-
-```SQL
-INSERT INTO users VALUES
-(0, "Jack", "China"),
-(2, "Stan", "USA"),
-(1, "Bob", "China"),
-(3, "Sam", "USA");
-select * from users;
-+------+------+---------+
-| uid  | name | country |
-+------+------+---------+
-|    0 | Jack | China   |
-|    1 | Bob  | China   |
-|    2 | Stan | USA     |
-|    3 | Sam  | USA     |
-+------+------+---------+
-4 rows in set (0.00 sec)
-```
-
-查询 `users` 表中 `country` 列值为 `China` 的数据行，然后删除 `score_board` 表中与 `users` 表中查询到的数据行具有相同 `name` 列值的所有数据行。有两种实现方法：
-
-- 方法 1
-
-```SQL
-DELETE FROM score_board
-WHERE name IN (select name from users where country = "China");
-select * from score_board;
-+------+------+------+
-| id   | name | score|
-+------+------+------+
-|    2 | Stan |   21 |
-|    3 | Sam  |   22 |
-+------+------+------+
-2 rows in set (0.00 sec)
-```
-
-- 方法 2
-
-```SQL
-DELETE FROM score_board
-WHERE EXISTS (select name from users
-              where score_board.name = users.name and country = "China");
-select * from score_board;
-+------+------+-------+
-| id   | name | score |
-+------+------+-------+
-|    2 | Stan |    21 |
-|    3 | Sam  |    22 |
-+------+------+-------+
-2 rows in set (0.00 sec)
-```
-
-**按多表关联或者 CTE 的结果集删除数据**
-
-删除制片人 foo 制作的所有电影，则可以执行以下语句：
-
-```SQL
-DELETE FROM films USING producers
-WHERE producer_id = producers.id
-    AND producers.name = 'foo';
-```
-
-您也可以使用 CTE 改写上述语句，增加易读性。
-
-```SQL
-WITH foo_producers as (
-    SELECT * from producers
-    where producers.name = 'foo'
-)
-DELETE FROM films USING foo_producers
-WHERE producer_id = foo_producers.id;
-```
-
-## 相关 SQL
-
-[SHOW DELETE](./SHOW_DELETE.md)：用于查询在指定数据库下，所有在明细表、聚合表、更新表上成功执行的历史删除 (DELETE) 任务。
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/DROP_PIPE.md b/docs/zh/sql-reference/sql-statements/data-manipulation/DROP_PIPE.md
deleted file mode 100644
index 1e1ed9e002628d..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/DROP_PIPE.md
+++ /dev/null
@@ -1,42 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DROP PIPE
-
-## 功能
-
-删除 Pipe，并删除相关的作业和元数据。该操作不会删除已经导入的数据。该命令自 3.2 版本起支持。
-
-## 语法
-
-```SQL
-DROP PIPE [IF EXISTS] [db_name.]<pipe_name>
-```
-
-## 参数说明
-
-### db_name
-
-Pipe 所属的数据库的名称。
-
-### pipe_name
-
-Pipe 的名称。
-
-## 示例
-
-删除数据库 `mydatabase` 下名为 `user_behavior_replica` 的 Pipe：
-
-```SQL
-USE mydatabase;
-DROP PIPE user_behavior_replica;
-```
-
-## 相关文档
-
-- [CREATE PIPE](../data-manipulation/CREATE_PIPE.md)
-- [ALTER PIPE](../data-manipulation/ALTER_PIPE.md)
-- [SHOW PIPES](../data-manipulation/SHOW_PIPES.md)
-- [SUSPEND or RESUME PIPE](../data-manipulation/SUSPEND_or_RESUME_PIPE.md)
-- [RETRY FILE](../data-manipulation/RETRY_FILE.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/DROP_TASK.md b/docs/zh/sql-reference/sql-statements/data-manipulation/DROP_TASK.md
deleted file mode 100644
index 18ab18c6821672..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/DROP_TASK.md
+++ /dev/null
@@ -1,61 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DROP TASK
-
-## 功能
-
-删除通过 [SUBMIT TASK](./SUBMIT_TASK.md) 语句提交的异步 ETL 任务。此功能从 StarRocks v2.5.7 起支持。
-
-> **说明**
->
-> 通过 DROP TASK 删除任务将同时取消该任务对应的 TaskRun。
-
-## 语法
-
-```SQL
-DROP TASK `<task_name>` [FORCE]
-```
-
-## 参数说明
-
-| **参数**  | **必须** | **说明**       |
-| --------- | ------- | -------------- |
-| task_name | 是      | 待删除任务名。为避免解析失败，请使用反括号（`）包裹任务名。 |
-| FORCE     | 否      | 强制删除任务。   |
-
-## 使用说明
-
-您可以通过查询 Information Schema 中的元数据视图 `tasks` 和 `task_runs` 来查看异步任务的信息。
-
-```SQL
-SELECT * FROM INFORMATION_SCHEMA.tasks;
-SELECT * FROM information_schema.tasks WHERE task_name = '<task_name>';
-SELECT * FROM information_schema.task_runs;
-SELECT * FROM information_schema.task_runs WHERE task_name = '<task_name>';
-```
-
-您可以通过 SHOW MATERIALIZED VIEWS 语句获取物化视图刷新任务的 `task_name`。
-
-```SQL
-SHOW MATERIALIZED VIEWS;
-SHOW MATERIALIZED VIEWS WHERE name = '<mv_name>';
-```
-
-## 示例
-
-```Plain
-MySQL > SUBMIT /*+set_var(query_timeout=100000)*/ TASK `ctas` AS
-    -> CREATE TABLE insert_wiki_edit_new
-    -> AS SELECT * FROM source_wiki_edit;
-+----------+-----------+
-| TaskName | Status    |
-+----------+-----------+
-| ctas     | SUBMITTED |
-+----------+-----------+
-1 row in set (1.19 sec)
-
-MySQL > DROP TASK `ctas`;
-Query OK, 0 rows affected (0.35 sec)
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/EXPORT.md b/docs/zh/sql-reference/sql-statements/data-manipulation/EXPORT.md
deleted file mode 100644
index 05d708004b4720..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/EXPORT.md
+++ /dev/null
@@ -1,208 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# EXPORT
-
-## 功能
-
-该语句用于将指定表的数据导出到指定位置。
-
-这是一个异步操作，任务提交成功后返回结果。执行后可使用 [SHOW EXPORT](../../../sql-reference/sql-statements/data-manipulation/SHOW_EXPORT.md) 命令查看进度。
-
-> **注意**
->
-> 导出操作需要目标表的 EXPORT 权限。如果您的用户账号没有 EXPORT 权限，请参考 [GRANT](../account-management/GRANT.md) 给用户赋权。
-
-## 语法
-
-```sql
-EXPORT TABLE <table_name>
-[PARTITION (<partition_name>[, ...])]
-[(<column_name>[, ...])]
-TO <export_path>
-[opt_properties]
-WITH BROKER
-[broker_properties]
-```
-
-## 参数说明
-
-- `table_name`
-
-  待导出数据所在的表。目前支持导出 `engine` 为 `olap` 或 `mysql` 的表。
-
-- `partition_name`
-
-  要导出的分区。如不指定则默认导出表中所有分区的数据。
-
-- `column_name`
-
-  要导出的列。列的导出顺序可以和源表结构 (Schema) 不同。如不指定则默认导出表中所有列的数据。
-
-- `export_path`
-
-  导出的目标路径。如果是目录，需要以斜杠 (/) 结尾。否则最后一个斜杠后面的部分会作为导出文件的前缀。如不指定文件名前缀，则默认文件名前缀为 `data_`。
-
-- `opt_properties`
-
-  导出相关的属性配置。
-
-  语法：
-
-  ```sql
-  [PROPERTIES ("<key>"="<value>", ...)]
-  ```
-
-  配置项：
-
-  | **配置项**         | **描述**                                                     |
-  | ---------------- | ------------------------------------------------------------ |
-  | column_separator | 指定导出文件的列分隔符。默认值：`\t`。                       |
-  | line_delimiter   | 指定导出文件的行分隔符。默认值：`\n`。                       |
-  | load_mem_limit   | 指定导出任务在单个 BE 节点上的内存使用上限。单位：字节。默认内存使用上限为 2 GB。 |
-  | timeout          | 指定导出任务的超时时间。单位：秒。默认值：`86400`（1 天）。  |
-  | include_query_id | 指定导出文件名中是否包含 `query_id`。取值范围：`true` 和 `false`。默认值：`true`。`true` 表示包含，`false` 表示不包含。 |
-
-- `WITH BROKER`
-
-  在 v2.4 及以前版本，您需要在导出语句中通过 `WITH BROKER "<broker_name>"` 来指定使用哪个 Broker。自 v2.5 起，您不再需要指定 `broker_name`，但继续保留 `WITH BROKER` 关键字。参见[从 使用 EXPORT 导出数据 > 背景信息](../../../unloading/Export.md#背景信息)。
-
-- `broker_properties`
-
-  用于提供访问数据源的鉴权信息。数据源不同，需要提供的鉴权信息也不同，参考 [BROKER LOAD](../../../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
-
-## 示例
-
-### 将表中所有数据导出到 HDFS
-
-将 `testTbl` 表中的所有数据导出到 HDFS 集群的指定路径下。
-
-```sql
-EXPORT TABLE testTbl 
-TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
-WITH BROKER
-(
-    "username"="xxx",
-    "password"="yyy"
-);
-```
-
-### 将表中部分分区的数据导出到 HDFS
-
-将 `testTbl` 表中 `p1` 和 `p2` 分区的数据导出到 HDFS 集群的指定路径下。
-
-```sql
-EXPORT TABLE testTbl
-PARTITION (p1,p2) 
-TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
-WITH BROKER
-(
-    "username"="xxx",
-    "password"="yyy"
-);
-```
-
-### 指定分隔符
-
-将 `testTbl` 表中的所有数据导出到 HDFS 集群的指定路径下，以 `,` 作为导出文件的列分隔符。
-
-```sql
-EXPORT TABLE testTbl 
-TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
-PROPERTIES
-(
-    "column_separator"=","
-) 
-WITH BROKER
-(
-    "username"="xxx",
-    "password"="yyy"
-);
-```
-
-将 `testTbl` 表中的所有数据导出到 HDFS 集群的指定路径下，以 Hive 默认分隔符 `\x01` 作为导出文件的列分隔符。
-
-```sql
-EXPORT TABLE testTbl 
-TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
-PROPERTIES
-(
-    "column_separator"="\\x01"
-) 
-WITH BROKER;
-```
-
-### 指定导出文件名前缀
-
-将 `testTbl` 表中的所有数据导出到 HDFS 集群的指定路径下，以 `testTbl_` 作为导出文件的文件名前缀。
-
-```sql
-EXPORT TABLE testTbl 
-TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/testTbl_" 
-WITH BROKER;
-```
-
-### 导出数据到 Alibaba Cloud OSS
-
-将 `testTbl` 表中的所有数据导出到 Alibaba Cloud OSS 存储桶的指定路径下。
-
-```sql
-EXPORT TABLE testTbl 
-TO "oss://oss-package/export/"
-WITH BROKER
-(
-    "fs.oss.accessKeyId" = "xxx",
-    "fs.oss.accessKeySecret" = "yyy",
-    "fs.oss.endpoint" = "oss-cn-zhangjiakou-internal.aliyuncs.com"
-);
-```
-
-### 导出数据到 Tencent Cloud COS
-
-将 `testTbl` 表中的所有数据导出到 Tencent Cloud COS 存储桶的指定路径下。
-
-```sql
-EXPORT TABLE testTbl 
-TO "cosn://cos-package/export/"
-WITH BROKER
-(
-    "fs.cosn.userinfo.secretId" = "xxx",
-    "fs.cosn.userinfo.secretKey" = "yyy",
-    "fs.cosn.bucket.endpoint_suffix" = "cos.ap-beijing.myqcloud.com"
-);
-```
-
-### 导出数据到 AWS S3
-
-将 `testTbl` 表中的所有数据导出到 AWS S3 存储桶的指定路径下。
-
-```sql
-EXPORT TABLE testTbl 
-TO "s3a://s3-package/export/"
-WITH BROKER
-(
-    "aws.s3.access_key" = "xxx",
-    "aws.s3.secret_key" = "yyy",
-    "aws.s3.region" = "zzz"
-);
-```
-
-### 导出数据到 Huawei Cloud OBS 上
-
-将 `testTbl` 表中的所有数据导出到 Huawei Cloud OBS 存储桶的指定路径下。
-
-```sql
-EXPORT TABLE testTbl 
-TO "obs://obs-package/export/"
-WITH BROKER
-(
-    "fs.obs.access.key" = "xxx",
-    "fs.obs.secret.key" = "yyy",
-    "fs.obs.endpoint" = "obs.cn-east-3.myhuaweicloud.com"
-);
-```
-
-> **说明**
->
-> 导出数据至华为云 OBS 时，需要先下载[依赖库](https://github.com/huaweicloud/obsa-hdfs/releases/download/v45/hadoop-huaweicloud-2.8.3-hw-45.jar)添加到 **$BROKER_HOME/lib/** 路径中并重启 Broker。
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/INSERT.md b/docs/zh/sql-reference/sql-statements/data-manipulation/INSERT.md
deleted file mode 100644
index 5e802a272ade7d..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/INSERT.md
+++ /dev/null
@@ -1,118 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# INSERT
-
-## 功能
-
-向 StarRocks 表中插入或覆盖写入数据。关于该种导入数据方式适用的场景请参考 [INSERT INTO 导入](../../../loading/InsertInto.md)。
-
-您可以通过 [SUBMIT TASK](./SUBMIT_TASK.md) 创建异步 INSERT 任务。
-
-## 语法
-
-- **导入**:
-
-  ```sql
-  INSERT { INTO | OVERWRITE } [db_name.]<table_name>
-  [ PARTITION (<partition_name> [, ...] ) ]
-  [ TEMPORARY PARTITION (<temporary_partition_name> [, ...] ) ]
-  [ WITH LABEL <label>]
-  [ (<column_name>[, ...]) ]
-  { VALUES ( { <expression> | DEFAULT } [, ...] ) | <query> }
-  ```
-
-- **导出**:
-
-  ```sql
-  INSERT INTO FILES()
-  [ WITH LABEL <label> ]
-  { VALUES ( { <expression> | DEFAULT } [, ...] ) | <query> }
-  ```
-
-## 参数说明
-
-| **参数**    | **说明**                                                     |
-| ----------- | ------------------------------------------------------------ |
-| INTO        | 将数据追加写入目标表。                                       |
-| OVERWRITE   | 将数据覆盖写入目标表。                                       |
-| table_name  | 导入数据的目标表。可以为 `db_name.table_name` 形式。         |
-| PARTITION  | 导入的目标分区。此参数必须是目标表中存在的分区，多个分区名称用逗号（,）分隔。如果指定该参数，数据只会被导入相应分区内。如果未指定，则默认将数据导入至目标表的所有分区。 |
-| TEMPORARY PARTITION | 指定要把数据导入哪些[临时分区](../../../table_design/Temporary_partition.md)。|
-| label       | 导入作业的标识，数据库内唯一。如果未指定，StarRocks 会自动为作业生成一个 Label。建议您指定 Label。否则，如果当前导入作业因网络错误无法返回结果，您将无法得知该导入操作是否成功。如果指定了 Label，可以通过 SQL 命令 `SHOW LOAD WHERE label="label";` 查看任务结果。关于 Label 命名要求，参见[系统限制](../../../reference/System_limit.md)。 |
-| column_name | 导入的目标列，必须是目标表中存在的列。该参数的对应关系与列名无关，但与其顺序一一对应。如果不指定目标列，默认为目标表中的所有列。如果源表中的某个列在目标列不存在，则写入默认值。如果当前列没有默认值，导入作业会失败。如果查询语句的结果列类型与目标列的类型不一致，会进行隐式转化，如果不能进行转化，那么 INSERT INTO 语句会报语法解析错误。<br />**说明**<br />自 v3.3.1 起，INSERT INTO 导入主键表时指定 Column List 会执行部分列更新（而在先前版本中，指定 Column List 仍然导致 Full Upsert）。如不指定 Column List，系统执行 Full Upsert。 |
-| expression  | 表达式，用以为对应列赋值。                                   |
-| DEFAULT     | 为对应列赋予默认值。                                         |
-| query       | 查询语句，查询的结果会导入至目标表中。查询语句支持任意 StarRocks 支持的 SQL 查询语法。 |
-| FILES()       | 表函数 [FILES()](../../sql-functions/table-functions/files.md)。您可以通过该函数将数据导出至远端存储。更多信息，请参考 [使用 INSERT INTO FILES() 导出数据](../../../unloading/unload_using_insert_into_files.md). |
-
-## 注意事项
-
-- 当前版本中，StarRocks 在执行 INSERT 语句时，如果有数据不符合目标表格式的数据（例如字符串超长等情况），INSERT 操作默认执行失败。您可以通过设置会话变量 `enable_insert_strict` 为 `false` 以确保 INSERT 操作过滤不符合目标表格式的数据，并继续执行。
-
-- 执行 INSERT OVERWRITE 语句后，系统将为目标分区创建相应的临时分区，并将数据写入临时分区，最后使用临时分区原子替换目标分区来实现覆盖写入。其所有过程均在在 Leader FE 节点执行。因此，如果 Leader FE 节点在覆盖写入过程中发生宕机，将会导致该次 INSERT OVERWRITE 导入失败，其过程中所创建的临时分区也会被删除。
-
-## 示例
-
-以下示例基于表 `test`，其中包含两个列 `c1` 和 `c2`。`c2` 列有默认值 DEFAULT。
-
-### 示例一：向 test 表中导入一行数据
-
-```SQL
-INSERT INTO test VALUES (1, 2);
-INSERT INTO test (c1, c2) VALUES (1, 2);
-INSERT INTO test (c1, c2) VALUES (1, DEFAULT);
-INSERT INTO test (c1) VALUES (1);
-```
-
-- 在不指定目标列时，使用表中的列顺序来作为默认的目标列导入顺序。因此以上示例中，第一条、第二条 SQL 语句导入效果相同。
-- 如果有目标列未插入数据或使用 DEFAULT 作为值插入数据，该列将使用默认值作为导入数据。因此以上示例中，第三条、第四条语句导入效果相同。
-
-### 示例二：向 test 表中一次性导入多行数据
-
-```SQL
-INSERT INTO test VALUES (1, 2), (3, 2 + 2);
-INSERT INTO test (c1, c2) VALUES (1, 2), (3, 2 * 2);
-INSERT INTO test (c1) VALUES (1), (3);
-INSERT INTO test (c1, c2) VALUES (1, DEFAULT), (3, DEFAULT);
-```
-
-- 因表达式结果相同，以上示例中，第一条、第二条 SQL 语句导入效果相同。
-- 第三条、第四条语句使用 DEFAULT 作为值插入数据，因此导入效果相同。
-
-### 示例三：向 test 表中导入一个查询语句结果
-
-```SQL
-INSERT INTO test SELECT * FROM test2;
-INSERT INTO test (c1, c2) SELECT * from test2;
-```
-
-### 示例四：向 test 表中导入一个查询语句结果，并指定分区和 Label
-
-```SQL
-INSERT INTO test PARTITION(p1, p2) WITH LABEL `label1` SELECT * FROM test2;
-INSERT INTO test WITH LABEL `label1` (c1, c2) SELECT * from test2;
-```
-
-### 示例五：向 test 表中覆盖写入一个查询语句结果，并指定分区和 Label
-
-```SQL
-INSERT OVERWRITE test PARTITION(p1, p2) WITH LABEL `label1` SELECT * FROM test3;
-INSERT OVERWRITE test WITH LABEL `label1` (c1, c2) SELECT * from test3;
-```
-
-### 示例六：从 AWS S3 中导入 Parquet 数据文件
-
-以下示例将 AWS S3 存储桶 `inserttest` 内 Parquet 文件 **parquet/insert_wiki_edit_append.parquet** 中的数据插入至表 `insert_wiki_edit` 中：
-
-```Plain
-INSERT INTO insert_wiki_edit
-    SELECT * FROM TABLE(
-        "path" = "s3://inserttest/parquet/insert_wiki_edit_append.parquet",
-        "format" = "parquet",
-        "aws.s3.access_key" = "xxxxxxxxxx",
-        "aws.s3.secret_key" = "yyyyyyyyyy",
-        "aws.s3.region" = "aa-bbbb-c"
-);
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/PAUSE_ROUTINE_LOAD.md b/docs/zh/sql-reference/sql-statements/data-manipulation/PAUSE_ROUTINE_LOAD.md
deleted file mode 100644
index cc365c7020f64d..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/PAUSE_ROUTINE_LOAD.md
+++ /dev/null
@@ -1,36 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# PAUSE ROUTINE LOAD
-
-import RoutineLoadPrivNote from '../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
-
-## 功能
-
-暂停 Routine Load 导入作业，导入作业会进入 PAUSED 状态，但是未结束，您可以执行 [RESUME ROUTINE LOAD](./RESUME_ROUTINE_LOAD.md) 语句重启导入作业。
-
-Routine Load 导入作业暂停后，您可以执行 [SHOW ROUTINE LOAD](./SHOW_ROUTINE_LOAD.md) 、[ALTER ROUTINE LOAD](./ALTER_ROUTINE_LOAD.md) 语句查看和修改已暂停的导入作业的信息。
-
-<RoutineLoadPrivNote />
-
-## 语法
-
-```SQL
-PAUSE ROUTINE LOAD FOR [db_name.]<job_name>
-```
-
-## 参数说明
-
-| 参数名称 | 是否必填 | 说明                                                         |
-| -------- | -------- | ------------------------------------------------------------ |
-| db_name  |          | Routine Load 导入作业所属数据库名称。                                           |
-| job_name | ✅        | Routine Load 导入作业名称。|
-
-## 示例
-
-暂停 `example_db` 数据库中名称为 `example_tbl1_ordertest1` 的 Routine Load 导入作业。
-
-```SQL
-PAUSE ROUTINE LOAD FOR example_db.example_tbl1_ordertest1;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/REFRESH_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/data-manipulation/REFRESH_MATERIALIZED_VIEW.md
deleted file mode 100644
index 678073843fed2a..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/REFRESH_MATERIALIZED_VIEW.md
+++ /dev/null
@@ -1,68 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# REFRESH MATERIALIZED VIEW
-
-## 功能
-
-手动刷新指定异步物化视图或其中部分分区。
-
-> **注意**
->
-> 您只能通过该命令手动刷新刷新方式为 ASYNC 或 MANUAL 的异步物化视图。您可以通过 [SHOW MATERIALIZED VIEWS](../data-manipulation/SHOW_MATERIALIZED_VIEW.md) 查看物化视图的刷新方式。
-> 该操作需要对应物化视图的 REFRESH 权限。
-
-## 语法
-
-```SQL
-REFRESH MATERIALIZED VIEW [database.]mv_name
-[PARTITION START ("<partition_start_date>") END ("<partition_end_date>")]
-[FORCE]
-[WITH { SYNC | ASYNC } MODE]
-```
-
-## 参数
-
-| **参数**                   | **必选**     | **说明**                     |
-| ------------------------- | ------------ | ---------------------------- |
-| mv_name                   | 是           | 待手动刷新的异步物化视图名称。    |
-| PARTITION START () END () | 否           | 手动刷新该时间区间内的分区。      |
-| partition_start_date      | 否           | 待手动刷新的分区开始时间。       |
-| partition_end_date        | 否           | 待手动刷新的分区结束时间。       |
-| FORCE                     | 否           | 如果指定该参数，StarRocks 将强制刷新相应的物化视图或分区。如果不指定该参数，StarRocks 会自动判断数据是否被更新过，只在需要时刷新分区。|
-| WITH ... MODE             | 否           | 同步或异步调用刷新任务。`SYNC` 指同步调用刷新任务，执行 SQL 语句后，StarRocks 将在刷新任务成功或失败后返回结果。`ASYNC` 指异步调用刷新任务，执行 SQL 语句后，StarRocks 将在刷新任务提交后立即返回成功，实际刷新任务会异步在后台运行。您可以通过查询 StarRocks 的 Information Schema 中的 `tasks` 和 `task_runs` 元数据视图来查看异步物化视图的刷新状态。详细信息，请参考[查看异步物化视图的执行状态](../../../using_starrocks/Materialized_view.md#查看异步物化视图的执行状态)。默认值：`ASYNC`。自 v2.5.8 和 v3.1.0 起支持。 |
-
-> **注意**
->
-> 刷新基于外部数据目录（External Catalog）创建的异步物化视图时，StarRocks 会刷新所有分区。
-
-## 示例
-
-示例一：异步调用任务手动刷新指定物化视图。
-
-```SQL
-REFRESH MATERIALIZED VIEW lo_mv1;
-
-REFRESH MATERIALIZED VIEW lo_mv1 WITH ASYNC MODE;
-```
-
-示例二：手动刷新物化视图指定分区。
-
-```SQL
-REFRESH MATERIALIZED VIEW lo_mv1 
-PARTITION START ("2020-02-01") END ("2020-03-01");
-```
-
-示例三：强制手动刷新物化视图指定分区。
-
-```SQL
-REFRESH MATERIALIZED VIEW lo_mv1 
-PARTITION START ("2020-02-01") END ("2020-03-01") FORCE;
-```
-
-示例四：同步调用任务手动刷新指定物化视图。
-
-```SQL
-REFRESH MATERIALIZED VIEW lo_mv1 WITH SYNC MODE;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md b/docs/zh/sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md
deleted file mode 100644
index 6974ab9138b580..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD.md
+++ /dev/null
@@ -1,34 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# RESUME ROUTINE LOAD
-
-import RoutineLoadPrivNote from '../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
-
-## 功能
-
-恢复 Routine Load 导入作业。导入作业会先短暂地进入 **NEED_SCHEDULE** 状态，表示正在重新调度导入作业，一段时间后会恢复至 **RUNNING** 状态，继续消费数据源的消息并且导入数据。您可以执行 [SHOW ROUTINE LOAD](./SHOW_ROUTINE_LOAD.md) 语句查看已恢复的导入作业。
-
-<RoutineLoadPrivNote />
-
-## 语法
-
-```SQL
-RESUME ROUTINE LOAD FOR [db_name.]<job_name>
-```
-
-## 参数说明
-
-| 参数名称 | 是否必填 | 说明                        |
-| -------- | -------- | --------------------------- |
-| db_name  |          | Routine Load 导入作业所属数据库名称。         |
-| job_name | ✅        | Routine Load 导入作业名称。 |
-
-## 示例
-
-恢复 `example_db` 数据库中名称为 `example_tbl1_ordertest1` 的 Routine Load 导入作业。
-
-```SQL
-RESUME ROUTINE LOAD FOR example_db.example_tbl1_ordertest1;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/RETRY_FILE.md b/docs/zh/sql-reference/sql-statements/data-manipulation/RETRY_FILE.md
deleted file mode 100644
index 805c7a5ce278d5..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/RETRY_FILE.md
+++ /dev/null
@@ -1,43 +0,0 @@
-# RETRY FILE
-
-## 功能
-
-重新尝试导入指定 Pipe 中所有数据文件或某个数据文件。该命令自 3.2 版本起支持。
-
-## 语法
-
-```SQL
-ALTER PIPE [ IF EXISTS ] <pipe_name> { RETRY ALL | RETRY FILE '<file_name>' }
-```
-
-## 参数说明
-
-### pipe_name
-
-Pipe 的名称。
-
-### file_name
-
-要重试的数据文件的存储路径。注意这里需要指定完整的路径。如果指定的文件不属于当前指定的 Pipe，则返回报错。
-
-## 示例
-
-重试导入名为 `user_behavior_replica` 的 Pipe 中所有数据文件：
-
-```SQL
-ALTER PIPE [ IF EXISTS ] user_behavior_replica RETRY ALL;
-```
-
-重试导入名为 `user_behavior_replica` 的 Pipe 中的数据文件 `s3://starrocks-examples/user_behavior_ten_million_rows.parquet`：
-
-```SQL
-ALTER PIPE [ IF EXISTS ] user_behavior_replica RETRY FILE 's3://starrocks-examples/user_behavior_ten_million_rows.parquet';
-```
-
-## 相关文档
-
-- [CREATE PIPE](../data-manipulation/CREATE_PIPE.md)
-- [ALTER PIPE](../data-manipulation/ALTER_PIPE.md)
-- [DROP PIPE](../data-manipulation/DROP_PIPE.md)
-- [SHOW PIPES](../data-manipulation/SHOW_PIPES.md)
-- [SUSPEND or RESUME PIPE](../data-manipulation/SUSPEND_or_RESUME_PIPE.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SELECT.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SELECT.md
deleted file mode 100644
index 7c083e4f7ba56c..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SELECT.md
+++ /dev/null
@@ -1,1135 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SELECT
-
-## 功能
-
-SELECT 语句用于从单个或多个表，视图，物化视图中读取数据。SELECT 语句一般由以下子句组成：
-
-- [SELECT](#select)
-  - [功能](#功能)
-    - [WITH](#with)
-    - [连接 (Join)](#连接-join)
-      - [Self Join](#self-join)
-      - [笛卡尔积 (Cross Join)](#笛卡尔积-cross-join)
-      - [Inner Join](#inner-join)
-      - [Outer Join](#outer-join)
-      - [Semi Join](#semi-join)
-      - [Anti Join](#anti-join)
-      - [等值 Join 和非等值 Join](#等值-join-和非等值-join)
-    - [ORDER BY](#order-by)
-    - [GROUP BY](#group-by)
-  - [语法](#语法)
-    - [Parameters](#parameters)
-    - [Note](#note)
-  - [示例](#示例)
-    - [HAVING](#having)
-    - [LIMIT](#limit)
-      - [OFFSET](#offset)
-    - [**UNION**](#union)
-    - [**INTERSECT**](#intersect)
-    - [**EXCEPT/MINUS**](#exceptminus)
-    - [DISTINCT](#distinct)
-    - [子查询](#子查询)
-      - [不相关子查询](#不相关子查询)
-      - [相关子查询](#相关子查询)
-    - [WHERE 与操作符](#where-与操作符)
-      - [算数操作符](#算数操作符)
-      - [BETWEEN 操作符](#between-操作符)
-      - [比较操作符](#比较操作符)
-      - [In 操作符](#in-操作符)
-      - [Like 操作符](#like-操作符)
-      - [逻辑操作符](#逻辑操作符)
-      - [正则表达式操作符](#正则表达式操作符)
-    - [别名 (alias)](#别名-alias)
-    - [PIVOT](#pivot)
-      - [语法](#语法-1)
-      - [参数](#参数)
-      - [示例](#示例-1)
-
-SELECT 可以作为独立的语句也可以作为其他语句的子句，其查询结果可以作为另一个语句的输入值。
-
-StarRocks 的查询语句基本符合 SQL-92 标准。下面介绍支持的 SELECT 用法。
-
-> **说明**
->
-> 如果要查询 StarRocks 表、视图、或物化视图内的数据，需要有对应对象的 SELECT 权限。如果要查询 External Catalog 里的数据，需要有对应 Catalog 的 USAGE 权限。
-
-### WITH
-
-可以在 SELECT 语句之前添加的子句，用于定义在 SELECT 内部多次引用的复杂表达式的别名。
-
-与 CREATE VIEW 类似，但在子句中定义的表和列名在查询结束后不会持久，也不会与实际表或 VIEW 中的名称冲突。
-
-使用 WITH 子句的好处：
-
-- 方便和易于维护，减少查询内部的重复。
-
-- 通过将查询中最复杂的部分抽象成单独的块，更易于阅读和理解 SQL 代码。
-
-示例：
-
-```sql
--- Define one subquery at the outer level, and another at the inner level as part of the
--- initial stage of the UNION ALL query.
-
-with t1 as (select 1),t2 as (select 2)
-select * from t1 union all select * from t2;
-```
-
-### 连接 (Join)
-
-连接操作合并 2 个或多个表的数据，然后返回某些表中某些列的结果集。
-
-目前 StarRocks 支持 Self Join、Cross Join、Inner Join、Outer Join、Semi Join 和 Anti Join。其中，Outer Join 包括 Left Join、Right Join 和 Full Join。
-
-Join 的语法定义如下：
-
-```sql
-SELECT select_list FROM
-table_or_subquery1 [INNER] JOIN table_or_subquery2 |
-table_or_subquery1 {LEFT [OUTER] | RIGHT [OUTER] | FULL [OUTER]} JOIN table_or_subquery2 |
-table_or_subquery1 {LEFT | RIGHT} SEMI JOIN table_or_subquery2 |
-table_or_subquery1 {LEFT | RIGHT} ANTI JOIN table_or_subquery2 |
-[ ON col1 = col2 [AND col3 = col4 ...] |
-USING (col1 [, col2 ...]) ]
-[other_join_clause ...]
-[ WHERE where_clauses ]
-```
-
-```sql
-SELECT select_list FROM
-table_or_subquery1, table_or_subquery2 [, table_or_subquery3 ...]
-[other_join_clause ...]
-WHERE
-col1 = col2 [AND col3 = col4 ...]
-```
-
-```sql
-SELECT select_list FROM
-table_or_subquery1 CROSS JOIN table_or_subquery2
-[other_join_clause ...]
-[ WHERE where_clauses ]
-```
-
-#### Self Join
-
-StarRocks 支持 Self Join，即自己和自己 Join。例如同一张表的不同列进行 Join。
-
-实际上没有特殊的语法标识 Self Join。Self Join 中 Join 两边的条件都来自同一张表，
-
-您需要给他们分配不同的别名。
-
-例如：
-
-```sql
-SELECT lhs.id, rhs.parent, lhs.c1, rhs.c2 FROM tree_data lhs, tree_data rhs WHERE lhs.id = rhs.parent;
-```
-
-#### 笛卡尔积 (Cross Join)
-
-Cross join 会产生大量的结果，须慎用 cross join。
-
-即使需要使用 Cross Join 时也需要使用过滤条件并且确保返回结果数较少。例如：
-
-```sql
-SELECT * FROM t1, t2;
-
-SELECT * FROM t1 CROSS JOIN t2;
-```
-
-#### Inner Join
-
-Inner Inner Join 是大家最熟知，最常用的 Join。返回的结果来自相近的两张表所请求的列，Join 的条件为两个表的列包含有相同的值。
-
-如果两个表的某个列名相同，我们需要使用全名（table_name.column_name 形式）或者给列名起别名。
-
-例如：
-
-下列 3 个查询是等价的。
-
-```sql
-SELECT t1.id, c1, c2 FROM t1, t2 WHERE t1.id = t2.id;
-
-SELECT t1.id, c1, c2 FROM t1 JOIN t2 ON t1.id = t2.id;
-
-SELECT t1.id, c1, c2 FROM t1 INNER JOIN t2 ON t1.id = t2.id;
-```
-
-#### Outer Join
-
-Outer Join 返回左表或者右表或者两者所有的行。如果在另一张表中没有匹配的数据，则将其设置为 `NULL`。例如：
-
-```sql
-SELECT * FROM t1 LEFT OUTER JOIN t2 ON t1.id = t2.id;
-
-SELECT * FROM t1 RIGHT OUTER JOIN t2 ON t1.id = t2.id;
-
-SELECT * FROM t1 FULL OUTER JOIN t2 ON t1.id = t2.id;
-```
-
-#### Semi Join
-
-Left Semi Join 只返回左表中能匹配右表数据的行，不管能匹配右表多少行数据，
-
-左表的该行最多只返回一次。Right Semi Join 原理相似，只是返回的数据是右表的。
-
-例如：
-
-```sql
-SELECT t1.c1, t1.c2, t1.c2 FROM t1 LEFT SEMI JOIN t2 ON t1.id = t2.id;
-```
-
-#### Anti Join
-
-Left Anti Join 只返回左表中不能匹配右表的行。
-
-Right Anti Join 反转了这个比较，只返回右表中不能匹配左表的行。例如：
-
-```sql
-SELECT t1.c1, t1.c2, t1.c2 FROM t1 LEFT ANTI JOIN t2 ON t1.id = t2.id;
-```
-
-#### 等值 Join 和非等值 Join
-
-根据 Join 条件的不同，StarRocks 支持的上述各种类型的 Join 可以分为等值 Join 和非等值 Join，如下表所示：
-
-| **等值 Join**   | Self Join、Cross Join、Inner Join、Outer Join、Semi Join 和 Anti Join |
-| --------------- | ------------------------------------------------------------ |
-| **非等值 Join** | Cross Join、Inner Join，LEFT SEMI JOIN， LEFT ANTI JOIN 和 Outer Join  |
-
-- 等值 Join
-  
-  等值 Join 使用等值条件作为连接条件，例如 `a JOIN b ON a.id = b.id`。
-
-- 非等值 Join
-  
-  非等值 Join 不使用等值条件，使用 `<`、`<=`、`>`、`>=`、`<>` 等比较操作符，例如 `a JOIN b ON a.id < b.id`。与等值 Join 相比，非等值 Join 目前效率较低，建议您谨慎使用。
-
-  以下为非等值 Join 的两个使用示例：
-
-  ```SQL
-  SELECT t1.id, c1, c2 
-  FROM t1 
-  INNER JOIN t2 ON t1.id < t2.id;
-    
-  SELECT t1.id, c1, c2 
-  FROM t1 
-  LEFT JOIN t2 ON t1.id > t2.id;
-  ```
-
-### ORDER BY
-
-ORDER BY 通过比较一列或者多列的大小来对结果集进行排序。
-
-ORDER BY 是比较耗时耗资源的操作，因为所有数据都需要发送到 1 个节点后才能排序，需要更多的内存。
-
-如果需要返回前 N 个排序结果，需要使用 LIMIT 子句；为了限制内存的使用，如果您没有指定 LIMIT 子句，则默认返回前 65535 个排序结果。
-
-ORDER BY 语法定义如下：
-
-```sql
-ORDER BY col [ASC | DESC]
-[ NULLS FIRST | NULLS LAST ]
-```
-
-默认排序顺序是 ASC（升序）。示例：
-
-```sql
-select * from big_table order by tiny_column, short_column desc;
-```
-
-StarRocks 支持在 ORDER BY 后声明 null 值排在最前面还是最后面，语法为 `order by <> [ NULLS FIRST | NULLS LAST ]`。`NULLS FIRST` 表示 null 值的记录将排在最前面，`NULLS LAST` 表示 null 值的记录将排在最后面。
-
-示例：将 null 值始终排在最前面。
-
-```sql
-select  *  from  sales_record  order by  employee_id  nulls first;
-```
-
-### GROUP BY
-
-GROUP BY 子句通常和聚合函数（例如 COUNT(), SUM(), AVG(), MIN()和 MAX()）一起使用。
-
-GROUP BY 指定的列不会参加聚合操作。GROUP BY 子句可以加入 HAVING 子句来过滤聚合函数产出的结果。例如：
-
-```sql
-select tiny_column, sum(short_column)
-from small_table 
-group by tiny_column;
-```
-
-```sql
-+-------------+---------------------+
-| tiny_column |  sum('short_column')|
-+-------------+---------------------+
-|      1      |        2            |
-|      2      |        1            |
-+-------------+---------------------+
-```
-
-## 语法
-
-  ```sql
-  SELECT ...
-  FROM ...
-  [ ... ]
-  GROUP BY [
-      , ... |
-      GROUPING SETS [, ...] (  groupSet [ , groupSet [ , ... ] ] ) |
-      ROLLUP(expr  [ , expr [ , ... ] ]) |
-      CUBE(expr  [ , expr [ , ... ] ])
-      ]
-  [ ... ]
-  ```
-
-### Parameters
-
-- `groupSet` 表示 select list 中的列，别名或者表达式组成的集合 `groupSet ::= { ( expr  [ , expr [ , ... ] ] )}`。
-
-- `expr`  表示 select list 中的列，别名或者表达式。
-
-### Note
-
-StarRocks 支持类似 PostgreSQL 语法，语法实例如下：
-
-  ```sql
-  SELECT a, b, SUM( c ) FROM tab1 GROUP BY GROUPING SETS ( (a, b), (a), (b), ( ) );
-  SELECT a, b,c, SUM( d ) FROM tab1 GROUP BY ROLLUP(a,b,c)
-  SELECT a, b,c, SUM( d ) FROM tab1 GROUP BY CUBE(a,b,c)
-  ```
-
-`ROLLUP(a,b,c)` 等价于如下 `GROUPING SETS` 语句。
-
-  ```sql
-  GROUPING SETS (
-  (a,b,c),
-  (a,b  ),
-  (a    ),
-  (     )
-  )
-  ```
-
-`CUBE (a, b, c)` 等价于如下 `GROUPING SETS` 语句。
-
-  ```sql
-  GROUPING SETS (
-  ( a, b, c ),
-  ( a, b    ),
-  ( a,    c ),
-  ( a       ),
-  (    b, c ),
-  (    b    ),
-  (       c ),
-  (         )
-  )
-  ```
-
-## 示例
-
-下面是一个实际数据的例子:
-
-  ```sql
-  SELECT * FROM t;
-  +------+------+------+
-  | k1   | k2   | k3   |
-  +------+------+------+
-  | a    | A    |    1 |
-  | a    | A    |    2 |
-  | a    | B    |    1 |
-  | a    | B    |    3 |
-  | b    | A    |    1 |
-  | b    | A    |    4 |
-  | b    | B    |    1 |
-  | b    | B    |    5 |
-  +------+------+------+
-  8 rows in set (0.01 sec)
-
-  SELECT k1, k2, SUM(k3) FROM t
-  GROUP BY GROUPING SETS ( (k1, k2), (k2), (k1), ( ) );
-  +------+------+-----------+
-  | k1   | k2   | sum(`k3`) |
-  +------+------+-----------+
-  | b    | B    |         6 |
-  | a    | B    |         4 |
-  | a    | A    |         3 |
-  | b    | A    |         5 |
-  | NULL | B    |        10 |
-  | NULL | A    |         8 |
-  | a    | NULL |         7 |
-  | b    | NULL |        11 |
-  | NULL | NULL |        18 |
-  +------+------+-----------+
-  9 rows in set (0.06 sec)
-
-  SELECT k1, k2, GROUPING_ID(k1,k2), SUM(k3) FROM t
-  GROUP BY GROUPING SETS ((k1, k2), (k1), (k2), ());
-  +------+------+---------------+----------------+
-  | k1   | k2   | grouping_id(k1,k2) | sum(`k3`) |
-  +------+------+---------------+----------------+
-  | a    | A    |             0 |              3 |
-  | a    | B    |             0 |              4 |
-  | a    | NULL |             1 |              7 |
-  | b    | A    |             0 |              5 |
-  | b    | B    |             0 |              6 |
-  | b    | NULL |             1 |             11 |
-  | NULL | A    |             2 |              8 |
-  | NULL | B    |             2 |             10 |
-  | NULL | NULL |             3 |             18 |
-  +------+------+---------------+----------------+
-  9 rows in set (0.02 sec)
-  ```
-
-GROUP BY `GROUPING SETS` ｜ `CUBE` ｜ `ROLLUP` 是对 GROUP BY 子句的扩展，它能够在一个 GROUP BY 子句中实现多个集合的分组的聚合。其结果等价于将多个相应 GROUP BY 子句进行 UNION 操作。
-
-  GROUP BY 子句是只含有一个元素的 GROUP BY GROUPING SETS 的特例。
-  例如，GROUPING SETS 语句：
-
-  ```sql
-  SELECT a, b, SUM( c ) FROM tab1 GROUP BY GROUPING SETS ( (a, b), (a), (b), ( ) );
-  ```
-
-  其查询结果等价于：
-
-  ```sql
-  SELECT a, b, SUM( c ) FROM tab1 GROUP BY a, b
-  UNION
-  SELECT a, null, SUM( c ) FROM tab1 GROUP BY a
-  UNION
-  SELECT null, b, SUM( c ) FROM tab1 GROUP BY b
-  UNION
-  SELECT null, null, SUM( c ) FROM tab1
-  ```
-
-  `GROUPING(expr)` 指示一个列是否为聚合列，如果是聚合列为 0，否则为 1。
-
-  `GROUPING_ID(expr  [ , expr [ , ... ] ])` 与 GROUPING 类似，GROUPING_ID 根据指定的 column 顺序，计算出一个列列表的 bitmap 值，每一位为 GROUPING 的值. GROUPING_ID()函数返回位向量的十进制值。
-
-### HAVING
-
-HAVING 子句不过滤表中的行数据，而是过滤聚合函数产出的结果。
-
-通常来说 HAVING 要和聚合函数（例如 COUNT(), SUM(), AVG(), MIN(), MAX()）以及 group by 子句一起使用。
-
-示例：
-
-```sql
-select tiny_column, sum(short_column) 
-from small_table 
-group by tiny_column 
-having sum(short_column) = 1;
-```
-
-```sql
-+-------------+---------------------+
-|tiny_column  | sum('short_column') |
-+-------------+---------------------+
-|         2   |        1            |
-+-------------+---------------------+
-
-1 row in set (0.07 sec)
-```
-
-```sql
-select tiny_column, sum(short_column) 
-from small_table 
-group by tiny_column 
-having tiny_column > 1;
-```
-
-```sql
-+-------------+---------------------+
-|tiny_column  | sum('short_column') |
-+-------------+---------------------+
-|      2      |          1          |
-+-------------+---------------------+
-
-1 row in set (0.07 sec)
-```
-
-### LIMIT
-
-LIMIT 子句用于限制返回结果的最大行数。设置返回结果的最大行数可以帮助 StarRocks 优化内存的使用。
-
-该子句主要应用如下场景：
-
-1. 返回 top-N 的查询结果。
-
-2. 简单查看表中包含的内容。
-
-3. 表中数据量大，或者 where 子句没有过滤太多的数据，需要限制查询结果集的大小。
-
-使用说明：LIMMIT 子句的值必须是数字型字面常量。
-
-示例：
-
-```sql
-mysql> select tiny_column from small_table limit 1;
-
-+-------------+
-|tiny_column  |
-+-------------+
-|     1       |
-+-------------+
-
-1 row in set (0.02 sec)
-```
-
-```sql
-mysql> select tiny_column from small_table limit 10000;
-
-+-------------+
-|tiny_column  |
-+-------------+
-|      1      |
-|      2      |
-+-------------+
-
-2 rows in set (0.01 sec)
-```
-
-#### OFFSET
-
-OFFSET 子句用于跳过结果集的前若干行结果，直接返回后续的结果。
-
-默认从第 0 行开始，因此 OFFSET 0 和不带 OFFSET 返回相同的结果。
-
-通常来说，OFFSET 子句需要与 ORDER BY 子句和 LIMIT 子句一起使用才有效。
-
-示例：
-
-```sql
-mysql> select varchar_column from big_table order by varchar_column limit 3;
-
-+----------------+
-| varchar_column | 
-+----------------+
-|    beijing     | 
-|    chongqing   | 
-|    tianjin     | 
-+----------------+
-
-3 rows in set (0.02 sec)
-```
-
-```sql
-mysql> select varchar_column from big_table order by varchar_column limit 1 offset 0;
-
-+----------------+
-|varchar_column  |
-+----------------+
-|     beijing    |
-+----------------+
-
-1 row in set (0.01 sec)
-```
-
-```sql
-mysql> select varchar_column from big_table order by varchar_column limit 1 offset 1;
-
-+----------------+
-|varchar_column  |
-+----------------+
-|    chongqing   | 
-+----------------+
-
-1 row in set (0.01 sec)
-```
-
-```sql
-mysql> select varchar_column from big_table order by varchar_column limit 1 offset 2;
-
-+----------------+
-|varchar_column  |
-+----------------+
-|     tianjin    |     
-+----------------+
-
-1 row in set (0.02 sec)
-```
-
-> **注意**
->
-> 在没有 ORDER BY 的情况下使用 OFFSET 语法是允许的，但是此时 OFFSET 无意义。这种情况只取 LIMIT 的值，忽略 OFFSET 的值。因此在没有 ORDER BY 的情况下，OFFSET 超过结果集的最大行数依然是有结果的。**建议使用 OFFSET 时一定带上 ORDER BY。**
-
-### **UNION**
-
-UNION 子句用于合并多个查询的结果，即获取并集。
-
-**语法如下：**
-
-```SQL
-query_1 UNION [DISTINCT | ALL] query_2
-```
-
-- DISTINCT：默认值，返回不重复的结果。UNION 和 UNION DISTINCT 效果相同（见第二个示例）。
-- ALL: 返回所有结果的集合，不进行去重。由于去重工作比较耗费内存，因此使用 UNION ALL 查询速度会快一些，内存消耗也会少一些（见第一个示例）。
-
-> **说明**
->
-> 每条 SELECT 查询返回的列数必须相同，且列类型必须能够兼容。
-
-**示例：**
-
-以表 `select1` 和 `select2` 示例说明。
-
-```SQL
-CREATE TABLE select1(
-    id          INT,
-    price       INT
-    )
-DISTRIBUTED BY HASH(id);
-
-INSERT INTO select1 VALUES
-    (1,2),
-    (1,2),
-    (2,3),
-    (5,6),
-    (5,6);
-
-CREATE TABLE select2(
-    id          INT,
-    price       INT
-    )
-DISTRIBUTED BY HASH(id);
-
-INSERT INTO select2 VALUES
-    (2,3),
-    (3,4),
-    (5,6),
-    (7,8);
-```
-
-示例一：返回两张表中所有 `id` 的并集，不进行去重。
-
-```Plaintext
-mysql> (select id from select1) union all (select id from select2) order by id;
-
-+------+
-| id   |
-+------+
-|    1 |
-|    1 |
-|    2 |
-|    2 |
-|    3 |
-|    5 |
-|    5 |
-|    5 |
-|    7 |
-+------+
-11 rows in set (0.02 sec)
-```
-
-示例二：返回两张表中 `id` 的并集，进行去重。下面两条查询在功能上对等。
-
-```Plaintext
-mysql> (select id from select1) union (select id from select2) order by id;
-
-+------+
-| id   |
-+------+
-|    1 |
-|    2 |
-|    3 |
-|    5 |
-|    7 |
-+------+
-6 rows in set (0.01 sec)
-
-mysql> (select id from select1) union distinct (select id from select2) order by id;
-+------+
-| id   |
-+------+
-|    1 |
-|    2 |
-|    3 |
-|    5 |
-|    7 |
-+------+
-5 rows in set (0.02 sec)
-```
-
-示例三：返回两张表中所有 `id` 的并集，进行去重，只返回 3 行结果。下面两条查询在功能上对等。
-
-```SQL
-mysql> (select id from select1) union distinct (select id from select2)
-order by id
-limit 3;
-++------+
-| id   |
-+------+
-|    1 |
-|    2 |
-|    3 |
-+------+
-4 rows in set (0.11 sec)
-
-mysql> select * from (select id from select1 union distinct select id from select2) as t1
-order by id
-limit 3;
-+------+
-| id   |
-+------+
-|    1 |
-|    2 |
-|    3 |
-+------+
-3 rows in set (0.01 sec)
-```
-
-### **INTERSECT**
-
-INTERSECT 子句用于返回多个查询结果之间的交集，即每个结果中都有的数据，并对结果集进行去重。
-
-**语法如下：**
-
-```SQL
-query_1 INTERSECT [DISTINCT] query_2
-```
-
-> **说明**
->
-> - INTERSECT 效果等同于 INTERSECT DISTINCT。不支持 ALL 关键字。
-> - 每条 SELECT 查询返回的列数必须相同，且列类型能够兼容。
-
-**示例：**
-
-继续使用 UNION 子句里的两张表。返回两张表中 `id` 和 `price` 组合的交集。下面两条查询在功能上对等。
-
-```Plaintext
-mysql> (select id, price from select1) intersect (select id, price from select2)
-order by id;
-
-+------+-------+
-| id   | price |
-+------+-------+
-|    2 |     3 |
-|    5 |     6 |
-+------+-------+
-
-mysql> (select id, price from select1) intersect distinct (select id, price from select2)
-order by id;
-
-+------+-------+
-| id   | price |
-+------+-------+
-|    2 |     3 |
-|    5 |     6 |
-+------+-------+
-```
-
-### **EXCEPT/MINUS**
-
-EXCEPT/MINUS 子句用于返回多个查询结果之间的补集，即返回左侧查询中在右侧查询中不存在的数据，并对结果集去重。EXCEPT 和 MINUS 功能对等。
-
-**语法如下：**
-
-```SQL
-query_1 {EXCEPT | MINUS} [DISTINCT] query_2
-```
-
-> **说明**
->
-> - EXCEPT 效果等同于 EXCEPT DISTINCT。不支持 ALL 关键字。
-> - 每条 SELECT 查询返回的列数必须相同，且列类型能够兼容。
-
-**示例：**
-
-继续使用 UNION 子句里的两张表。返回表 `select1` 中不存在于表 `select2` 的 `(id,price)` 组合。
-
-可以看到在结果中对组合 `(1,2)` 进行了去重。
-
-```Plaintext
-mysql> (select id, price from select1) except (select id, price from select2)
-order by id;
-+------+-------+
-| id   | price |
-+------+-------+
-|    1 |     2 |
-+------+-------+
-
-mysql> (select id, price from select1) minus (select id, price from select2)
-order by id;
-+------+-------+
-| id   | price |
-+------+-------+
-|    1 |     2 |
-+------+-------+
-```
-
-### DISTINCT
-
-DISTINCT 关键字对结果集进行去重。示例：
-
-```SQL
--- 返回一列中去重后的值。
-select distinct tiny_column from big_table limit 2;
-
--- 返回多列中去重后的组合。
-select distinct tiny_column, int_column from big_table limit 2;
-```
-
-DISTINCT 可以和聚合函数 (通常是 count) 一同使用，count(distinct) 用于计算出一个列或多个列上包含多少不同的组合。
-
-```SQL
--- 计算一列中不重复值的个数。
-select count(distinct tiny_column) from small_table;
-```
-
-```sql
-+-------------------------------+
-| count(DISTINCT 'tiny_column') |
-+-------------------------------+
-|             2                 |
-+-------------------------------+
-1 row in set (0.06 sec)
-```
-
-```SQL
--- 计算多列中不重复组合的个数。
-select count(distinct tiny_column, int_column) from big_table limit 2;
-```
-
-StarRocks 支持多个聚合函数同时使用 distinct。
-
-```SQL
--- 单独返回多个聚合函数去重后的个数。
-
-select count(distinct tiny_column, int_column), count(distinct varchar_column) from big_table;
-```
-
-### 子查询
-
-子查询按相关性可以分为不相关子查询和相关子查询。
-
-- 不相关子查询（简单查询）不依赖外层查询的结果。
-- 相关子查询需要依赖外层查询的结果才能执行。
-
-#### 不相关子查询
-
-不相关子查询支持 [NOT] IN 和 EXISTS。
-
-示例：
-
-```sql
-SELECT x FROM t1 WHERE x [NOT] IN (SELECT y FROM t2);
-
-SELECT * FROM t1 WHERE (x,y) [NOT] IN (SELECT x,y FROM t2 LIMIT 2);
-
-SELECT x FROM t1 WHERE EXISTS (SELECT y FROM t2 WHERE y = 1);
-```
-
-从 3.0 版本开始，`SELECT... FROM... WHERE... [NOT] IN` 支持在 WHERE 中指定多个字段进行比较，即上面第二个示例中的 `WHERE (x,y)` 用法。
-
-#### 相关子查询
-
-相关子查询支持 [NOT] IN 和 [NOT] EXISTS。
-
-示例：
-
-```sql
-SELECT * FROM t1 WHERE x [NOT] IN (SELECT a FROM t2 WHERE t1.y = t2.b);
-
-SELECT * FROM t1 WHERE [NOT] EXISTS (SELECT a FROM t2 WHERE t1.y = t2.b);
-```
-
-子查询还支持标量子查询。分为不相关标量子查询、相关标量子查询和标量子查询作为普通函数的参数。
-
-示例：
-
-1. 不相关标量子查询，谓词为 = 号。例如输出最高工资的人的信息。
-
-    ```sql
-    SELECT name FROM table WHERE salary = (SELECT MAX(salary) FROM table);
-    ```
-
-2. 不相关标量子查询，谓词为 >,< 等。例如输出比平均工资高的人的信息。
-
-    ```sql
-    SELECT name FROM table WHERE salary > (SELECT AVG(salary) FROM table);
-    ```
-
-3. 相关标量子查询。例如输出各个部门工资最高的信息。
-
-    ```sql
-    SELECT name FROM table a WHERE salary = （SELECT MAX(salary) FROM table b WHERE b.部门= a.部门）;
-    ```
-
-4. 标量子查询作为普通函数的参数。
-
-    ```sql
-    SELECT name FROM table WHERE salary = abs((SELECT MAX(salary) FROM table));
-    ```
-
-### WHERE 与操作符
-
-SQL 操作符是一系列用于比较的函数，这些操作符广泛地用于 SELECT 语句的 WHERE 子句中。
-
-#### 算数操作符
-
-算术操作符通常出现在包含左操作数，操作符和右操作数（大部分情况下）组成的表达式中。
-
-**+和-**：分别代表着加法和减法，可以作为单元或 2 元操作符。当其作为单元操作符时，如+1, -2.5 或者-col_name，表达的意思是该值乘以+1 或者-1。
-
-因此单元操作符+返回的是未发生变化的值，单元操作符-改变了该值的符号位。
-
-用户可以将两个单元操作符叠加起来，比如++5(返回的是正值)，-+2 或者+-2（这两种情况返回的是负值），但是用户不能使用连续的两个-号。
-
-因为--被解释为后面的语句是注释（用户也是可以使用两个-号的，此时需要在两个-号之间加上空格或圆括号，如-(-2)或者- -2，这两种写法实际表达的结果都是+2）。
-
-+或者-作为 2 元操作符时，例如 2+2，3-1.5 或者 col1 + col2，表达的含义是左值加或者减去右值。左值和右值必须都是数字类型。
-
-***和/**：分别代表着乘法和除法操作符。两侧的操作数必须都是数据类型。
-
-当两个数相乘时，类型较小的操作数在需要的情况下类型可能会提升（比如 SMALLINT 提升到 INT 或者 BIGINT 等），表达式的结果被提升到下一个较大的类型，
-
-比如 TINYINT 乘以 INT 产生的结果的类型会是 BIGINT）。当两个数相乘时，为了避免精度丢失，操作数和表达式结果都会被解释成 DOUBLE 类型。
-
-如果用户想把表达式结果转换成其他类型，需要用 CAST 函数转换。
-
-**%**：取模操作符。返回左操作数除以右操作数的余数。左操作数和右操作数都必须是整型。
-
-**&，|和^**：按位操作符返回对两个操作数进行按位与，按位或，按位异或操作的结果。两个操作数都要求是一种整型类型。
-
-如果按位操作符的两个操作数的类型不一致，则类型小的操作数会被提升到类型较大的操作数，然后再做相应的按位操作。
-
-在 1 个表达式中可以出现多个算术操作符，用户可以用小括号将相应的算术表达式括起来。算术操作符通常没有对应的数学函数来表达和算术操作符相同的功能。
-
-比如我们没有 MOD()函数来表示%操作符的功能。反过来，数学函数也没有对应的算术操作符。比如幂函数 POW()并没有相应的 **求幂操作符。
-
-#### BETWEEN 操作符
-
-在 where 子句中，表达式可能同时与上界和下界比较。如果表达式大于等于下界，同时小于等于上界，比较的结果是 true。语法定义如下：
-
-```sql
-expression BETWEEN lower_bound AND upper_bound
-```
-
-数据类型：通常表达式（expression）的计算结果都是数字类型，该操作符也支持其他数据类型。如果必须要确保下界和上界都是可比较的字符，可以使用 cast()函数。
-
-使用说明：如果操作数是 string 类型应注意，起始部分为上界的长字符串将不会匹配上界，该字符串比上界要大。例如：‘MJ’比‘M’大，所以 `between 'A' and 'M'` 不会匹配‘MJ’。
-
-如果需要确保表达式能够正常工作，可以使用一些函数，如 upper(), lower(), substr(), trim()。
-
-示例：
-
-```sql
-select c1 from t1 where month between 1 and 6;
-```
-
-#### 比较操作符
-
-比较操作符用来判断列和列是否相等或者对列进行排序。`=`, `!=`, `<=`, `>=` 可以适用所有数据类型。
-
-其中 `<>` 符号是不等于的意思，与 `!=` 的功能一致。IN 和 BETWEEN 操作符提供更简短的表达来描述相等、小于、大于等关系的比较。
-
-#### In 操作符
-
-In 操作符会和 VALUE 集合进行比较，如果可以匹配该集合中任何一元素，则返回 TRUE。
-
-参数和 VALUE 集合必须是可比较的。所有使用 IN 操作符的表达式都可以写成用 OR 连接的等值比较，但是 IN 的语法更简单，更精准，更容易让 StarRocks 进行优化。
-
-示例：
-
-```sql
-select * from small_table where tiny_column in (1,2);
-```
-
-#### Like 操作符
-
-该操作符用于和字符串进行比较。"_"用来匹配单个字符，"%"用来匹配多个字符。参数必须要匹配完整的字符串。通常，把"%" 放在字符串的尾部更加符合实际用法。
-
-示例：
-
-```sql
-mysql> select varchar_column from small_table where varchar_column like 'm%';
-
-+----------------+
-|varchar_column  |
-+----------------+
-|     milan      |
-+----------------+
-
-1 row in set (0.02 sec)
-```
-
-```sql
-mysql> select varchar_column from small_table where varchar_column like 'm____';
-
-+----------------+
-| varchar_column | 
-+----------------+
-|    milan       | 
-+----------------+
-
-1 row in set (0.01 sec)
-```
-
-#### 逻辑操作符
-
-逻辑操作符返回一个 BOOL 值，逻辑操作符包括单元操作符和多元操作符，每个操作符处理的参数都是返回值为 BOOL 值的表达式。支持的操作符有：
-
-AND: 2 元操作符，如果左侧和右侧的参数的计算结果都是 TRUE，则 AND 操作符返回 TRUE。
-
-OR: 2 元操作符，如果左侧和右侧的参数的计算结果有一个为 TRUE，则 OR 操作符返回 TRUE。如果两个参数都是 FALSE，则 OR 操作符返回 FALSE。
-
-NOT: 单元操作符，反转表达式的结果。如果参数为 TRUE，则该操作符返回 FALSE；如果参数为 FALSE，则该操作符返回 TRUE。
-
-示例：
-
-```sql
-mysql> select true and true;
-
-+-------------------+
-| (TRUE) AND (TRUE) | 
-+-------------------+
-|         1         | 
-+-------------------+
-
-1 row in set (0.00 sec)
-```
-
-```sql
-mysql> select true and false;
-
-+--------------------+
-| (TRUE) AND (FALSE) | 
-+--------------------+
-|         0          | 
-+--------------------+
-
-1 row in set (0.01 sec)
-```
-
-```sql
-mysql> select true or false;
-
-+-------------------+
-| (TRUE) OR (FALSE) | 
-+-------------------+
-|        1          | 
-+-------------------+
-
-1 row in set (0.01 sec)
-```
-
-```sql
-mysql> select not true;
-
-+----------+
-| NOT TRUE | 
-+----------+
-|     0    | 
-+----------+
-
-1 row in set (0.01 sec)
-```
-
-#### 正则表达式操作符
-
-判断是否匹配正则表达式，使用 POSIX 标准的正则表达式。
-
-"^" 用来匹配字符串的首部，"$" 用来匹配字符串的尾部，"." 匹配任何一个单字符，"*"匹配 0 个或多个选项，"+"匹配 1 个多个选项，"?" 表示分贪婪表示等等。正则表达式需要匹配完整的值，并不是仅仅匹配字符串的部分内容。
-
-如果想匹配中间的部分，正则表达式的前面部分可以写成 "^.*" 或者".*"。"^" 和 "$" 通常是可以省略的。RLIKE 操作符和 REGEXP 操作符是同义词。
-
-"|" 操作符是个可选操作符，"|" 两侧的正则表达式只需满足 1 侧条件即可，"|" 操作符和两侧的正则表达式通常需要用()括起来。
-
-示例：
-
-```sql
-mysql> select varchar_column from small_table where varchar_column regexp '(mi|MI).*';
-
-+----------------+
-| varchar_column | 
-+----------------+
-|     milan      |       
-+----------------+
-
-1 row in set (0.01 sec)
-```
-
-```sql
-mysql> select varchar_column from small_table where varchar_column regexp 'm.*';
-
-+----------------+
-| varchar_column | 
-+----------------+
-|     milan      |  
-+----------------+
-
-1 row in set (0.01 sec)
-```
-
-### 别名 (alias)
-
-在查询中书写表名、列名，或者包含列的表达式的名字时，可以通过 AS 给它们分配一个别名。
-
-当需要使用表名、列名时，可以使用别名来访问。别名通常相对原名来说更简短更容易记忆。当需要新建一个别名时，只需在 select list 或者 from list 中的表、列、表达式名称后面加上 AS alias 子句即可。AS 关键词是可选的，用户可以直接在原名后面指定别名。如果别名或者其他标志符和 [StarRocks 内部保留关键字](../keywords.md)同名时，需要在该名称加上反引号，比如 `rank`。**别名对大小写敏感，但是列别名和表达式别名对大小写不敏感**。
-
-示例：
-
-```sql
-select tiny_column as name, int_column as sex from big_table;
-
-select sum(tiny_column) as total_count from big_table;
-
-select one.tiny_column, two.int_column from small_table one, big_table two where one.tiny_column = two.tiny_column;
-```
-
-### PIVOT
-
-PIVOT操作符是SQL中的一个高级特性，它允许你将表中的行转换为列，通常用于数据透视表的创建。这在处理数据库报表或分析时非常有用，特别是当你需要对数据进行汇总或分类展示时。
-
-实际上，PIVOT 是一种语法糖，它可以简化像 sum(case when ... then ... end) 这样的查询语句的编写。
-
-#### 语法
-  
-```sql
-pivot:
-SELECT ...
-FROM ...
-PIVOT (
-  aggregate_function(<expr>) [[AS] alias] [, aggregate_function(<expr>) [[AS] alias] ...]
-  FOR <pivot_column>
-  IN (<pivot_value>)
-)
-
-pivot_column:
-<column_name> 
-| (<column_name> [, <column_name> ...])
-
-pivot_value:
-<literal> [, <literal> ...]
-| (<literal>, <literal> ...) [, (<literal>, <literal> ...)]
-```
-
-#### 参数
-在PIVOT操作中，你需要指定以下几个关键部分：
-- aggregate_function()：聚合函数，如SUM、AVG、COUNT等，用于对数据进行汇总。
-- alias：为聚合结果指定的别名，使得结果更易于理解。
-- FOR pivot_column：指定要进行行转列操作的列名。
-- IN (pivot_value)：指定pivot_column列中要转换为列的具体值。
-
-#### 示例
-
-```sql
-create table t1 (c0 int, c1 int, c2 int, c3 int);
-SELECT * FROM t1 PIVOT (SUM(c1) AS sum_c1, AVG(c2) AS avg_c2 FOR c3 IN (1, 2, 3, 4, 5));
--- 结果等同于以下查询：
-SELECT SUM(CASE WHEN c3 = 1 THEN c1 ELSE NULL END) AS sum_c1_1,
-       AVG(CASE WHEN c3 = 1 THEN c2 ELSE NULL END) AS avg_c2_1,
-       SUM(CASE WHEN c3 = 2 THEN c1 ELSE NULL END) AS sum_c1_2,
-       AVG(CASE WHEN c3 = 2 THEN c2 ELSE NULL END) AS avg_c2_2,
-       SUM(CASE WHEN c3 = 3 THEN c1 ELSE NULL END) AS sum_c1_3,
-       AVG(CASE WHEN c3 = 3 THEN c2 ELSE NULL END) AS avg_c2_3,
-       SUM(CASE WHEN c3 = 4 THEN c1 ELSE NULL END) AS sum_c1_4,
-       AVG(CASE WHEN c3 = 4 THEN c2 ELSE NULL END) AS avg_c2_4,
-       SUM(CASE WHEN c3 = 5 THEN c1 ELSE NULL END) AS sum_c1_5,
-       AVG(CASE WHEN c3 = 5 THEN c2 ELSE NULL END) AS avg_c2_5
-FROM t1
-GROUP BY c0;
-```
\ No newline at end of file
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_ALTER.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_ALTER.md
deleted file mode 100644
index 1e4df04c69f228..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_ALTER.md
+++ /dev/null
@@ -1,73 +0,0 @@
----
-keywords: ['xiugai'] 
-displayed_sidebar: "Chinese"
----
-
-# SHOW ALTER TABLE
-
-## 功能
-
-查询正在进行的 Alter table 操作的执行情况，包括：
-
-- 修改列。
-- 优化表结构（自 3.2 版本起），包括修改分桶方式和分桶数量。
-- 创建和删除 rollup index。
-
-## 语法
-
-- 查询修改列或者优化表结构的操作执行情况。
-
-    ```sql
-    SHOW ALTER TABLE { COLUMN | OPTIMIZE } [FROM <db_name>]
-    [WHERE <where_condition> ] [ORDER BY <col_name> [ASC | DESC]] [LIMIT <num>]
-    ```
-
-- 查询创建和删除 rollup index 的操作执行情况。
-
-    ```sql
-    SHOW ALTER TABLE ROLLUP [FROM <db_name>]
-    ```
-
-## 参数说明
-
-- `{COLUMN ｜ OPTIMIZE | ROLLUP}`：从 `COLUMN`、`OPTIMIZE` 和 `ROLLUP` 中必选其中一个。
-  - 如果指定了 `COLUMN`，该语句用于查询修改列的操作。
-  - 如果指定了 `OPTIMIZE`，该语句用于查询优化表结构操作（修改分桶方式和分桶数量）。
-  - 如果指定了 `ROLLUP`，该语句用于查询创建或删除 rollup index 的操作。
-- 当指定了 `COLUMN` 或者 `OPTIMIZE` 查询修改列或者优化表结构操作时，支持使用如下子句：
-  - `WHERE <where_condition>`：根据操作的 `TableName`、`CreateTime`、`FinishTime` 和 `State` 过滤出满足条件的操作。
-  - `ORDER BY <col_name> [ASC | DESC]`：根据操作的 `TableName`、`CreateTime`、`FinishTime` 和 `State` 对返回结果中的操作进行排序。
-  - `LIMIT <num>`：返回指定个数的操作。
-- `db_name`：可选。如果不指定，则默认使用当前数据库。
-
-## 示例
-
-1. 查询当前数据库中所有修改列操作和优化表结构操作，以及创建或删除 rollup index 操作的执行情况。
-
-    ```sql
-    SHOW ALTER TABLE COLUMN;
-    SHOW ALTER TABLE OPTIMIZE;
-    SHOW ALTER TABLE ROLLUP;
-    ```
-
-2. 查询指定数据库中修改列操作和优化表结构操作，以及创建或删除 rollup index 操作的执行情况。
-
-    ```sql
-    SHOW ALTER TABLE COLUMN FROM example_db;
-    SHOW ALTER TABLE OPTIMIZE FROM example_db;
-    SHOW ALTER TABLE ROLLUP FROM example_db;
-    ````
-
-3. 查询指定表中最近一次修改列操作或者优化表结构操作的执行情况。
-
-    ```sql
-    SHOW ALTER TABLE COLUMN WHERE TableName = "table1" ORDER BY CreateTime DESC LIMIT 1;
-    SHOW ALTER TABLE OPTIMIZE WHERE TableName = "table1" ORDER BY CreateTime DESC LIMIT 1; 
-    ```
-
-## 相关参考
-
-- [CREATE TABLE](../data-definition/CREATE_TABLE.md)
-- [ALTER TABLE](../data-definition/ALTER_TABLE.md)
-- [SHOW TABLES](../data-manipulation/SHOW_TABLES.md)
-- [SHOW CREATE TABLE](../data-manipulation/SHOW_CREATE_TABLE.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW.md
deleted file mode 100644
index 16377bdf8d1356..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW.md
+++ /dev/null
@@ -1,80 +0,0 @@
----
-keywords: ['xiugai'] 
-displayed_sidebar: "Chinese"
----
-
-# SHOW ALTER MATERIALIZED VIEW
-
-## 功能
-
-查看同步物化视图构建状态。
-
-:::tip
-
-该操作不需要权限。
-
-:::
-
-## 语法
-
-```SQL
-SHOW ALTER MATERIALIZED VIEW [ { FROM | IN } db_name]
-```
-
-## 参数
-
-| **参数** | **必选** | **说明**                                                     |
-| -------- | -------- | ------------------------------------------------------------ |
-| db_name  | 否       | 待查看的数据库名称。如果不指定该参数，则默认使用当前数据库。 |
-
-## 返回
-
-| **返回**        | **说明**             |
-| --------------- | -------------------- |
-| JobId           | 作业 ID。            |
-| TableName       | 表名。               |
-| CreateTime      | 作业创建时间。       |
-| FinishedTime    | 作业结束时间。       |
-| BaseIndexName   | 基表名称。           |
-| RollupIndexName | 物化视图名称。       |
-| RollupId        | 物化视图 Rollup ID。 |
-| TransactionId   | 等待的事务 ID。      |
-| State           | 创建任务状态。       |
-| Msg             | 错误信息。           |
-| Progress        | 创建任务进度。       |
-| Timeout         | 超时时间长度。       |
-
-## 示例
-
-### 示例一：查看同步物化视图刷新任务
-
-```Plain
-MySQL > SHOW ALTER MATERIALIZED VIEW\G
-*************************** 1. row ***************************
-          JobId: 475991
-      TableName: lineorder
-     CreateTime: 2022-08-24 19:46:53
-   FinishedTime: 2022-08-24 19:47:15
-  BaseIndexName: lineorder
-RollupIndexName: lo_mv_sync_1
-       RollupId: 475992
-  TransactionId: 33067
-          State: FINISHED
-            Msg: 
-       Progress: NULL
-        Timeout: 86400
-*************************** 2. row ***************************
-          JobId: 477337
-      TableName: lineorder
-     CreateTime: 2022-08-24 19:47:25
-   FinishedTime: 2022-08-24 19:47:45
-  BaseIndexName: lineorder
-RollupIndexName: lo_mv_sync_2
-       RollupId: 477338
-  TransactionId: 33068
-          State: FINISHED
-            Msg: 
-       Progress: NULL
-        Timeout: 86400
-2 rows in set (0.00 sec)
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md
deleted file mode 100644
index 190540820426d0..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CATALOGS.md
+++ /dev/null
@@ -1,55 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW CATALOGS
-
-## 功能
-
-查看当前集群中的所有 Catalog，包括 Internal Catalog 和 External Catalog。
-
-> **注意**
->
-> 只有拥有 External Catalog USAGE 权限的用户才能查看到该 Catalog。如果没有该权限，仅返回 default_catalog。您可以使用 [GRANT](../account-management/GRANT.md) 命令进行授权操作。
-
-## 语法
-
-```SQL
-SHOW CATALOGS
-```
-
-## 返回结果说明
-
-```SQL
-+----------+--------+----------+
-| Catalog  | Type   | Comment  |
-+----------+--------+----------+
-```
-
-返回结果中的字段说明如下：
-
-| **字段** | **说明**                                                     |
-| -------- | ------------------------------------------------------------ |
-| Catalog  | Catalog 名称。                                               |
-| Type     | Catalog 类型。如果是 `default_catalog`，则返回 `Internal`。如果是 external catalog，则返回 external catalog 的类型，例如 `Hive`, `Hudi`, `Iceberg`。          |
-| Comment  | Catalog 的备注。<ul><li>在创建 external catalog 时不支持为 external catalog 添加备注，所以如果是 external catalog，则返回的 `Comment` 为 `NULL`。</li><li>如果是 `default_catalog`，则默认返回的 `Comment` 为 `An internal catalog contains this cluster's self-managed tables.`。`default_catalog` 是 StarRocks 集群中唯一的 internal catalog，不允许删除。</li></ul> |
-
-## 示例
-
-查看当前集群中的所有 catalog。
-
-```SQL
-SHOW CATALOGS\G
-*************************** 1. row ***************************
-Catalog: default_catalog
-   Type: Internal
-Comment: An internal catalog contains this cluster's self-managed tables.
-*************************** 2. row ***************************
-Catalog: hudi_catalog
-   Type: Hudi
-Comment: NULL
-*************************** 3. row ***************************
-Catalog: iceberg_catalog
-   Type: Iceberg
-Comment: NULL
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md
deleted file mode 100644
index 0e101179477b4c..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_CATALOG.md
+++ /dev/null
@@ -1,72 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW CREATE CATALOG
-
-## 功能
-
-查看某个 External Catalog 的创建语句。
-
-当前支持查看如下 External Catalog:
-
-- [Hive Catalog](../../../data_source/catalog/hive_catalog.md)
-- [Iceberg Catalog](../../../data_source/catalog/iceberg_catalog.md)
-- [Hudi Catalog](../../../data_source/catalog/hudi_catalog.md)
-- [Delta Lake Catalog](../../../data_source/catalog/deltalake_catalog.md)
-- [JDBC catalog](../../../data_source/catalog/jdbc_catalog.md) (自 3.0 版本起)
-- [Unified Catalog](../../../data_source/catalog/unified_catalog.md) (自 3.2 版本起)
-- [MaxCompute Catalog](../../../data_source/catalog/maxcompute_catalog.md) (自 3.3 版本起)
-
-其中认证相关的密钥信息会进行脱敏展示，无法查看。
-
-该命令自 3.0 版本起支持。
-
-## 语法
-
-```SQL
-SHOW CREATE CATALOG <catalog_name>;
-```
-
-## 参数说明
-
-| **参数**     | **是否必选** | **说明**                  |
-| ------------ | ------------ | ------------------------- |
-| catalog_name | 是           | 待查看的 Catalog 的名称。 |
-
-## 返回结果说明
-
-```Plain
-+------------+-----------------+
-| Catalog    | Create Catalog  |
-+------------+-----------------+
-```
-
-| **字段**       | **说明**             |
-| -------------- | -------------------- |
-| Catalog        | Catalog 的名称。     |
-| Create Catalog | Catalog 的创建语句。 |
-
-## 示例
-
-以一个名为 `hive_catalog_glue` 的 Hive Catalog 为例，查询该 Catalog 的创建语句：
-
-```SQL
-SHOW CREATE CATALOG hive_catalog_glue;
-```
-
-返回如下信息：
-
-```SQL
-CREATE EXTERNAL CATALOG `hive_catalog_hms`
-PROPERTIES ("aws.s3.access_key"  =  "AK******M4",
-"hive.metastore.type"  =  "glue",
-"aws.s3.secret_key"  =  "iV******iD",
-"aws.glue.secret_key"  =  "iV******iD",
-"aws.s3.use_instance_profile"  =  "false",
-"aws.s3.region"  =  "us-west-1",
-"aws.glue.region"  =  "us-west-1",
-"type"  =  "hive",
-"aws.glue.access_key"  =  "AK******M4"
-)
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_DATABASE.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_DATABASE.md
deleted file mode 100644
index 8bb8994ceca899..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_DATABASE.md
+++ /dev/null
@@ -1,44 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW CREATE DATABASE
-
-查看指定数据库的创建语句。
-
-## 语法
-
-```sql
-SHOW CREATE DATABASE <db_name>
-```
-
-## 参数说明
-
-`db_name`：数据库的名称，必填。
-
-## 返回结果说明
-
-返回两个字段：
-
-- Database：数据库名称
-
-- Create Database：数据库的创建语句
-
-## 示例
-
-```sql
-mysql > show create database zj_test;
-+----------+---------------------------+
-| Database | Create Database           |
-+----------+---------------------------+
-| zj_test  | CREATE DATABASE `zj_test` |
-+----------+---------------------------+
-```
-
-## 相关参考
-
-- [CREATE DATABASE](../data-definition/CREATE_DATABASE.md)
-- [SHOW DATABASES](SHOW_DATABASES.md)
-- [USE](../data-definition/USE.md)
-- [DESC](../Utility/DESCRIBE.md)
-- [DROP DATABASE](../data-definition/DROP_DATABASE.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_MATERIALIZED_VIEW.md
deleted file mode 100644
index 02390e7864db44..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_MATERIALIZED_VIEW.md
+++ /dev/null
@@ -1,55 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW CREATE MATERIALIZED VIEW
-
-## 功能
-
-查看指定[异步物化视图](../../../using_starrocks/Materialized_view.md)的定义。
-
-:::tip
-
-该操作不需要权限。
-
-:::
-
-## 语法
-
-```SQL
-SHOW CREATE MATERIALIZED VIEW [db_name.]mv_name
-```
-
-## 参数
-
-| **参数** | **必选** | **说明**                     |
-| -------- | -------- | ---------------------------- |
-| db_name   | 否       | 数据库名称。如不指定，则默认查看当前数据库中指定物化视图的定义。 |
-| mv_name  | 是       | 待查看定义的物化视图的名称。 |
-
-## 返回
-
-| **返回**                 | **说明**         |
-| ------------------------ | ---------------- |
-| Materialized View        | 物化视图的名称。 |
-| Create Materialized View | 物化视图的定义。 |
-
-## 示例
-
-### 示例一：查看指定物化视图定义
-
-```Plain
-MySQL > SHOW CREATE MATERIALIZED VIEW lo_mv1\G
-*************************** 1. row ***************************
-       Materialized View: lo_mv1
-Create Materialized View: CREATE MATERIALIZED VIEW `lo_mv1`
-COMMENT "MATERIALIZED_VIEW"
-DISTRIBUTED BY HASH(`lo_orderkey`) BUCKETS 10 
-REFRESH ASYNC
-PROPERTIES (
-"replication_num" = "3",
-"storage_medium" = "HDD"
-)
-AS SELECT `wlc_test`.`lineorder`.`lo_orderkey` AS `lo_orderkey`, `wlc_test`.`lineorder`.`lo_custkey` AS `lo_custkey`, sum(`wlc_test`.`lineorder`.`lo_quantity`) AS `total_quantity`, sum(`wlc_test`.`lineorder`.`lo_revenue`) AS `total_revenue`, count(`wlc_test`.`lineorder`.`lo_shipmode`) AS `shipmode_count` FROM `wlc_test`.`lineorder` GROUP BY `wlc_test`.`lineorder`.`lo_orderkey`, `wlc_test`.`lineorder`.`lo_custkey` ORDER BY `wlc_test`.`lineorder`.`lo_orderkey` ASC ;
-1 row in set (0.01 sec)
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE.md
deleted file mode 100644
index 321eb01d985e86..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE.md
+++ /dev/null
@@ -1,138 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW CREATE TABLE
-
-## 功能
-
-查看指定表的建表语句。
-
-自 3.0 版本起支持使用该语句查看 External Catalog 下的表，包括 Apache Hive™ 、Apache Iceberg、Apache Hudi、Delta Lake 表。
-
-自 2.5.7 版本起，StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS)，您无需手动设置分桶数量。更多信息，请参见 [设置分桶数量](../../../table_design/Data_distribution.md#设置分桶数量)。
-
-- 如果您在建表时指定了分桶数，SHOW CREATE TABLE 会显示分桶数。
-
-- 如果您在建表时没有指定分桶数，SHOW CREATE TABLE 不会显示分桶数，您可以通过 [SHOW PARTITIONS](SHOW_PARTITIONS.md) 查看分区的分桶数。
-
-2.5.7 之前的版本在建表时必须设置分桶数，因此 SHOW CREATE TABLE 会显示分桶数。
-
-> **注意**
->
-> - 3.0 版本之前，只有拥有该表 SELECT_PRIV 权限的用户才可以查看。
-> - 自 3.0 版本起，只有拥有该表 SELECT 权限的用户才可以查看。
-
-## 语法
-
-```SQL
-SHOW CREATE TABLE [db_name.]table_name
-```
-
-## 参数说明
-
-| **参数**    | **必选** | **说明**                                        |
-| ---------- | -------- | ---------------------------------------------- |
-| db_name    | 否       | 数据库名称。如指定，则查看指定数据库中某张表的建表语句。 |
-| table_name | 是       | 表名。                                          |
-
-## 返回结果说明
-
-```Plain
-+-----------+----------------+
-| Table     | Create Table   |       
-+-----------+----------------+
-```
-
-返回结果中的参数说明如下：
-
-| **参数**     | **说明**   |
-| ------------ | ---------- |
-| Table        | 表名。     |
-| Create Table | 建表语句。 |
-
-## 示例
-
-### 建表时未指定分桶数
-
-创建一个表 `example_table`，DISTRIBUTED BY 中未指定分桶数。
-
-```SQL
-CREATE TABLE example_table
-(
-    k1 TINYINT,
-    k2 DECIMAL(10, 2) DEFAULT "10.5",
-    v1 CHAR(10) REPLACE,
-    v2 INT SUM
-)
-ENGINE = olap
-AGGREGATE KEY(k1, k2)
-COMMENT "my first starrocks table"
-DISTRIBUTED BY HASH(k1);
-```
-
-查看表 `example_table` 的建表语句，结果中不显示分桶数。注意建表时如果未指定 PROPERTIES，SHOW CREATE TABLE 语句会显示默认的 PROPERTIES。
-
-```Plain
-SHOW CREATE TABLE example_table\G
-*************************** 1. row ***************************
-       Table: example_table
-Create Table: CREATE TABLE `example_table` (
-  `k1` tinyint(4) NULL COMMENT "",
-  `k2` decimal64(10, 2) NULL DEFAULT "10.5" COMMENT "",
-  `v1` char(10) REPLACE NULL COMMENT "",
-  `v2` int(11) SUM NULL COMMENT ""
-) ENGINE=OLAP 
-AGGREGATE KEY(`k1`, `k2`)
-COMMENT "my first starrocks table"
-DISTRIBUTED BY HASH(`k1`)
-PROPERTIES (
-"replication_num" = "3",
-"in_memory" = "false",
-"enable_persistent_index" = "false",
-"replicated_storage" = "true",
-"compression" = "LZ4"
-);
-```
-
-### 建表时指定了分桶数
-
-创建一个表 `example_table1`，DISTRIBUTED BY 中指定分桶数为 10。
-
-```SQL
-CREATE TABLE example_table1
-(
-    k1 TINYINT,
-    k2 DECIMAL(10, 2) DEFAULT "10.5",
-    v1 CHAR(10) REPLACE,
-    v2 INT SUM
-)
-ENGINE = olap
-AGGREGATE KEY(k1, k2)
-COMMENT "my first starrocks table"
-DISTRIBUTED BY HASH(k1) BUCKETS 10;
-```
-
-查看表 `example_table` 的建表语句，结果中显示分桶数。注意建表时如果未指定 PROPERTIES，SHOW CREATE TABLE 语句会显示默认的 PROPERTIES。
-
-```plain
-SHOW CREATE TABLE example_table1\G
-*************************** 1. row ***************************
-       Table: example_table1
-Create Table: CREATE TABLE `example_table1` (
-  `k1` tinyint(4) NULL COMMENT "",
-  `k2` decimal64(10, 2) NULL DEFAULT "10.5" COMMENT "",
-  `v1` char(10) REPLACE NULL COMMENT "",
-  `v2` int(11) SUM NULL COMMENT ""
-) ENGINE=OLAP 
-AGGREGATE KEY(`k1`, `k2`)
-COMMENT "my first starrocks table"
-DISTRIBUTED BY HASH(`k1`) BUCKETS 10 
-PROPERTIES (
-"replication_num" = "3",
-"in_memory" = "false",
-"enable_persistent_index" = "false",
-"replicated_storage" = "true",
-"compression" = "LZ4"
-);
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_VIEW.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_VIEW.md
deleted file mode 100644
index e563c4768bb741..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_CREATE_VIEW.md
+++ /dev/null
@@ -1,108 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW CREATE VIEW
-
-## 功能
-
-查看指定逻辑视图的创建语句 CREATE VIEW。视图创建语句可以帮助您理解视图定义，作为后续修改视图或重建视图的参考。
-
-> **注意**
->
-> 只有拥有该视图和视图对应基表的 SELECT 权限的用户才可以查看。
-
-从 2.5.4 版本开始，为了兼容 MySQL 标准语法，支持使用 SHOW CREATE VIEW 来查看异步物化视图的创建语句。该语句将物化视图当做普通视图来处理。
-
-## 语法
-
-```SQL
-SHOW CREATE VIEW [<db_name>.]<view_name>
-```
-
-## 参数说明
-
-| **参数**  | **必选** | **说明**                                                     |
-| --------- | -------- | ------------------------------------------------------------ |
-| db_name   | 否       | 数据库名称。如不指定，则默认查看当前数据库中指定视图的创建语句。 |
-| view_name | 是       | 视图名称。                                                   |
-
-## 返回结果说明
-
-```plain
-+---------+--------------+----------------------+----------------------+
-| View    | Create View  | character_set_client | collation_connection |
-+---------+--------------+----------------------+----------------------+
-```
-
-返回结果中的参数说明如下：
-
-| **参数**             | **说明**                                  |
-| -------------------- | ----------------------------------------- |
-| View                 | 视图名称。                                |
-| Create View          | 视图的创建语句。                          |
-| character_set_client | 客户端连接 StarRocks 服务端使用的字符集。 |
-| collation_connection | 字符集的校对规则。                        |
-
-## 示例
-
-### 查看逻辑视图创建语句
-
-创建表 `base`。
-
-```SQL
-CREATE TABLE base (
-    k1 date,
-    k2 int,
-    v1 int sum)
-PARTITION BY RANGE(k1)
-(
-    PARTITION p1 values less than('2020-02-01'),
-    PARTITION p2 values less than('2020-03-01')
-)
-DISTRIBUTED BY HASH(k2)
-PROPERTIES( "replication_num"  = "3");
-```
-
-在表 `base` 上创建视图 `example_view`。
-
-```SQL
-CREATE VIEW example_view (k1, k2, v1)
-AS SELECT k1, k2, v1 FROM base;
-```
-
-查看视图 `example_view` 的创建语句。
-
-```Plain
-SHOW CREATE VIEW example_view;
-
-MySQL [yn_db]> SHOW CREATE VIEW example_view;
-+--------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+----------------------+----------------------+
-| View         | Create View                                                                                                                                         | character_set_client | collation_connection |
-+--------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+----------------------+----------------------+
-| example_view | CREATE VIEW `example_view` (k1, k2, v1) COMMENT "VIEW" AS SELECT `yn_db`.`base`.`k1`, `yn_db`.`base`.`k2`, `yn_db`.`base`.`v1`
-FROM `yn_db`.`base`; | utf8                 | utf8_general_ci      |
-+--------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+----------------------+----------------------+
-
-```
-
-### 查看物化视图创建语句
-
-在表 `base` 上创建物化视图 `example_mv`。
-
-```SQL
-CREATE MATERIALIZED VIEW example_mv distributed by hash(k1)
-AS SELECT k1 FROM base;
-```
-
-查看物化视图 `example_mv` 的创建语句。
-
-```Plain
-SHOW CREATE VIEW example_mv;
-+------------+----------------------------------------------------------------------------+----------------------+----------------------+
-| View       | Create View                                                                | character_set_client | collation_connection |
-+------------+----------------------------------------------------------------------------+----------------------+----------------------+
-| example_mv | CREATE VIEW `example_mv` AS SELECT `yn_db`.`base`.`k1`
-FROM `yn_db`.`base` | utf8                 | utf8_general_ci      |
-+------------+------------------------------------------------
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_DATA.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_DATA.md
deleted file mode 100644
index ec3364f599f552..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_DATA.md
+++ /dev/null
@@ -1,64 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW DATA
-
-## 功能
-
-用于查看指定数据库或指定表的数据量、副本数量以及统计行数。
-
-## 语法
-
-```sql
-SHOW DATA [FROM <db_name>[.<table_name>]]
-```
-
-说明：
-
-1. 如果不指定 FROM 子句，则展示当前 db 下细分到各个 table 的数据量和副本数量。其中数据量为所有副本的总数据量。而副本数量为表的所有分区以及所有物化视图的副本数量。
-
-2. 如果指定 FROM 子句，则展示 table 下细分到各个物化视图的数据量、副本数量和统计行数。其中数据量为所有副本的总数据量。副本数量为对应物化视图的所有分区的副本数量。统计行数为对应物化视图的所有分区统计行数。
-
-3. 统计行数时，以多个副本中，行数最大的那个副本为准。
-
-4. 结果集中的 `Total` 行表示汇总行。`Quota` 行表示当前数据库设置的配额。`Left` 行表示剩余配额。
-
-5. 如果想查看各个 Partition 的大小，请参阅 [show partitions](../data-manipulation/SHOW_PARTITIONS.md)。
-
-## 示例
-
-### 查看数据库下表的总数据量
-
-查看当前数据库下各个 table 的数据量，副本数量，汇总数据量和汇总副本数量。
-
-```sql
-SHOW DATA;
-
-+-----------+-------------+--------------+
-| TableName | Size        | ReplicaCount |
-+-----------+-------------+--------------+
-| tbl1      | 900.000 B   | 6            |
-| tbl2      | 500.000 B   | 3            |
-| Total     | 1.400 KB    | 9            |
-| Quota     | 1024.000 GB | 1073741824   |
-| Left      | 1021.921 GB | 1073741815   |
-+-----------+-------------+--------------+
-```
-
-### 查看某个表的数据量
-
-查看指定数据库下指定表的细分数据量、副本数量和统计行数。
-
-```sql
-SHOW DATA FROM example_db.test;
-
-+-----------+-----------+-----------+--------------+----------+
-| TableName | IndexName | Size      | ReplicaCount | RowCount |
-+-----------+-----------+-----------+--------------+----------+
-| test      | r1        | 10.000MB  | 30           | 10000    |
-|           | r2        | 20.000MB  | 30           | 20000    |
-|           | test2     | 50.000MB  | 30           | 50000    |
-|           | Total     | 80.000    | 90           |          |
-+-----------+-----------+-----------+--------------+----------+
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md
deleted file mode 100644
index ba38b638589675..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_DATABASES.md
+++ /dev/null
@@ -1,69 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW DATABASES
-
-## 功能
-
-查看当前 StarRocks 集群或外部数据源中的数据库。
-
-## 语法
-
-```SQL
-SHOW DATABASES [FROM <catalog_name>]
-```
-
-## 参数说明
-
-| **参数**          | **必选** | **说明**                                                     |
-| ----------------- | -------- | ------------------------------------------------------------ |
-| catalog_name | 否       | Internal catalog 或 external catalog 的名称。<ul><li>如不指定或指定为 internal catalog 名称，即 `default_catalog`，则查看当前 StarRocks 集群中的数据库。</li><li>如指定 external catalog 名称，则查看外部数据源中的数据库。您可以使用 [SHOW CATALOGS](SHOW_CATALOGS.md) 命令查看当前集群的内外部 catalog。</li></ul> |
-
-## 示例
-
-示例一：查看当前 StarRocks 集群中的数据库。
-
-```SQL
-SHOW DATABASES;
-```
-
-或
-
-```SQL
-SHOW DATABASES FROM default_catalog;
-```
-
-返回信息如下：
-
-```SQL
-+----------+
-| Database |
-+----------+
-| db1      |
-| db2      |
-| db3      |
-+----------+
-```
-
-示例二：通过 external catalog `hive1` 查看 Apache Hive™ 中的数据库。
-
-```SQL
-SHOW DATABASES FROM hive1;
-
-+-----------+
-| Database  |
-+-----------+
-| hive_db1  |
-| hive_db2  |
-| hive_db3  |
-+-----------+
-```
-
-## 相关参考
-
-- [CREATE DATABASE](../data-definition/CREATE_DATABASE.md)
-- [SHOW CREATE DATABASE](SHOW_CREATE_DATABASE.md)
-- [USE](../data-definition/USE.md)
-- [DESC](../Utility/DESCRIBE.md)
-- [DROP DATABASE](../data-definition/DROP_DATABASE.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_DELETE.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_DELETE.md
deleted file mode 100644
index 8db8526aca99a7..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_DELETE.md
+++ /dev/null
@@ -1,43 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW DELETE
-
-## 功能
-
-用于展示在指定数据库下，所有在明细表、聚合表、更新表上成功执行的历史删除 (DELETE) 任务。
-
-有关删除操作的更多信息，参见 [DELETE](DELETE.md)。
-
-注意该语句不能用于查询在主键表上执行的 DELETE 操作。
-
-## 语法
-
-```sql
-SHOW DELETE [FROM <db_name>]
-```
-
-`db_name`: 数据库名称，可选。如果不指定，默认为当前数据库。
-
-命令返回字段：
-
-- `TableName`: 表名称，即从哪些表中删除了数据。
-- `PartitionName`：表的分区名称，即从哪些分区中删除了数据。如果表是**非分区表**，则显示为 `*`。
-- `CreateTime`: DELETE 任务的创建时间。
-- `DeleteCondition`: 指定的删除条件。
-- `State`: DELETE 任务的状态。
-
-## 示例
-
-展示数据库 `database` 下的所有历史 DELETE 任务。
-
-```sql
-SHOW DELETE FROM database;
-
-+------------+---------------+---------------------+-----------------+----------+
-| TableName  | PartitionName | CreateTime          | DeleteCondition | State    |
-+------------+---------------+---------------------+-----------------+----------+
-| mail_merge | *             | 2023-03-14 10:39:03 | name EQ "Peter" | FINISHED |
-+------------+---------------+---------------------+-----------------+----------+
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_DYNAMIC_PARTITION_TABLES.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_DYNAMIC_PARTITION_TABLES.md
deleted file mode 100644
index 22f19015cd04cb..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_DYNAMIC_PARTITION_TABLES.md
+++ /dev/null
@@ -1,24 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['fenqu']
----
-
-# SHOW DYNAMIC PARTITION TABLES
-
-## 功能
-
-该语句用于展示当前数据库 db 下所有设置过动态分区属性的分区表状态。
-
-## 语法
-
-```sql
-SHOW DYNAMIC PARTITION TABLES [FROM <db_name>]
-```
-
-## 示例
-
-1. 展示数据库 database 的所有设置过动态分区属性的分区表状态。
-
-```sql
-SHOW DYNAMIC PARTITION TABLES FROM database;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_EXPORT.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_EXPORT.md
deleted file mode 100644
index 42d2de3626e859..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_EXPORT.md
+++ /dev/null
@@ -1,130 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW EXPORT
-
-## 功能
-
-查询符合指定条件的导出作业的执行情况。
-
-## 语法
-
-```SQL
-SHOW EXPORT
-[ FROM <db_name> ]
-[
-WHERE
-    [ QUERYID = <query_id> ]
-    [ STATE = { "PENDING" | "EXPORTING" | "FINISHED" | "CANCELLED" } ]
-]
-[ ORDER BY <field_name> [ ASC | DESC ] [, ... ] ]
-[ LIMIT <count> ]
-```
-
-## 参数说明
-
-该语句包含四个可选子句：
-
-- FROM
-
-  指定要查询的数据库的名称。如果不指定该子句，则默认查询当前数据库。
-
-- WHERE
-
-  指定过滤条件。只有符合过滤条件的导入作业记录才会作为查询结果返回。
-
-  | **参数** | **是否必选** | **说明**                                                     |
-  | -------- | ------------ | ------------------------------------------------------------ |
-  | QUERYID  | 否           | 导出作业的 ID。该参数用于查询单个导出作业的执行情况。        |
-  | STATE    | 否           | 导出作业的状态。取值范围：<br /><ul><li>`PENDING`：表示查询待调度的导出作业。</li><li>`EXPORTING`：表示查询正在执行中的导出作业。</li><li>`FINISHED`：表示查询成功完成的导出作业。</li><li>`CANCELLED`：表示查询失败的导出作业。</li></ul> |
-
-- ORDER BY
-
-  指定用于对返回的导出作业记录进行排序的字段的名称。支持指定多个字段，多个字段之间必须用逗号 (,) 分隔。另外，您还可以在字段后通过添加 `ASC` 或 `DESC` 关键字来指定按该字段对返回的导出作业记录进行升序或降序排序。
-
-- LIMIT
-
-  指定允许返回的导出作业记录最大数量。取值范围：正整数。如果不指定该子句，则默认返回符合指定条件的所有导出作业。
-
-## 返回结果说明
-
-例如查看一个 ID 为 `edee47f0-abe1-11ec-b9d1-00163e1e238f` 的导出作业的执行情况：
-
-```SQL
-SHOW EXPORT
-WHERE QUERYID = "edee47f0-abe1-11ec-b9d1-00163e1e238f";
-```
-
-返回结果如下：
-
-```SQL
-     JobId: 14008
-   QueryId: edee47f0-abe1-11ec-b9d1-00163e1e238f
-     State: FINISHED
-  Progress: 100%
-  TaskInfo: {"partitions":["*"],"column separator":"\t","columns":["*"],"tablet num":10,"broker":"","coord num":1,"db":"db0","tbl":"tbl_simple","row delimiter":"\n","mem limit":2147483648}
-      Path: hdfs://127.0.0.1:9000/users/230320/
-CreateTime: 2023-03-20 11:16:14
- StartTime: 2023-03-20 11:16:17
-FinishTime: 2023-03-20 11:16:26
-   Timeout: 7200
-```
-
-返回结果中的参数说明如下：
-
-- `JobId`：导出作业的 ID。
-- `QueryId`：当前查询的 ID。
-- `State`：导出作业的状态，包括：
-  - `PENDING`：导出作业待调度。
-  - `EXPORTING`：导出作业正在执行中。
-  - `FINISHED`：导出作业成功。
-  - `CANCELLED`：导出作业失败。
-- `Progress`：导出作业的进度。该进度以查询计划为单位。假设导出作业一共分为 10 个查询计划，当前已完成 3 个，则进度为 30%。有关查询计划的原理，参见[“使用 EXPORT 导出数据 > 导出流程”](../../../unloading/Export.md#导出流程)。
-- `TaskInfo`：导出作业的信息，格式为 JSON，包括：
-  - `partitions`：导出数据所在的分区。通配符 (`*`) 表示导出了所有分区的数据。
-  - `column separator`：导出文件的列分隔符。
-  - `columns`：导出的列的名称。
-  - `tablet num`：导出的 Tablet 总数量。
-  - `broker`：在 v2.4 及以前版本，该字段用于返回导出作业使用的 Broker 的名称。自 v2.5 起，该字段返回一个空字符串。具体原因请参见[“使用 EXPORT 导出数据 > 背景信息”](../../../unloading/Export.md#背景信息)。
-  - `coord num`：导出作业拆分的查询计划的个数。
-  - `db`：导出数据所在的数据库的名称。
-  - `tbl`：导出数据所在的表的名称。
-  - `row delimiter`：导出文件的行分隔符。
-  - `mem limit`：导出作业的内存使用限制。单位是字节。
-- `Path`：远端存储上的导出路径。
-- `CreateTime`：导出作业的创建时间。
-- `StartTime`：导出作业开始调度的时间。
-- `FinishTime`：导出作业的结束时间。
-- `Timeout`：导出作业的超时时间。单位是秒。该时间从 `CreateTime` 开始计算。
-- `ErrorMsg`：导出作业的错误原因。该字段仅当导出作业出现错误时才会返回。
-
-## 示例
-
-- 查询当前数据库下所有导出作业：
-
-  ```SQL
-  SHOW EXPORT;
-  ```
-
-- 查询指定数据库 `example_db` 下 ID 为 `921d8f80-7c9d-11eb-9342-acde48001122` 的导出作业：
-
-  ```SQL
-  SHOW EXPORT FROM example_db
-  WHERE queryid = "921d8f80-7c9d-11eb-9342-acde48001122";
-  ```
-
-- 查询指定数据库 `example_db` 下状态为 `EXPORTING` 的导出作业，并按 `StartTime` 对返回的导出作业记录进行升序排序：
-
-  ```SQL
-  SHOW EXPORT FROM example_db
-  WHERE STATE = "exporting"
-  ORDER BY StartTime ASC;
-  ```
-
-- 查询指定数据库 `example_db` 下所有导出作业，并按 `StartTime` 对返回的导出作业记录进行降序排序：
-
-  ```SQL
-  SHOW EXPORT FROM example_db
-  ORDER BY StartTime DESC;
-  ```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_FULL_COLUMNS.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_FULL_COLUMNS.md
deleted file mode 100644
index 9288ddc08ada03..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_FULL_COLUMNS.md
+++ /dev/null
@@ -1,29 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW FULL COLUMNS
-
-## 功能
-
-该语句用于查看指定表的列信息。
-
-:::tip
-
-该操作不需要权限。
-
-:::
-
-## 语法
-
-```sql
-SHOW FULL COLUMNS FROM <tbl_name>
-```
-
-## 示例
-
-1. 查看指定表的列信息。
-
-    ```sql
-    SHOW FULL COLUMNS FROM tbl;
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_INDEX.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_INDEX.md
deleted file mode 100644
index fa61ee935535f2..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_INDEX.md
+++ /dev/null
@@ -1,86 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['suoyin']
----
-
-# SHOW INDEX
-
-## 功能
-
-查看索引，当前仅支持查看指定表的所有 [Bitmap 索引](../../../table_design/indexes/Bitmap_index.md)。创建 bitmap 索引为异步过程，使用该语句只能查看到已经创建完成的索引。
-
-:::tip
-
-该操作不需要权限。
-
-:::
-
-## 语法
-
-```SQL
-SHOW INDEX[ES] FROM [db_name.]table_name [FROM db_name]
-```
-
-或
-
-```SQL
-SHOW KEY[S] FROM [db_name.]table_name [FROM db_name]
-```
-
-## 参数说明
-
-| **参数**   | **必选** | **说明**     |
-| ---------- | -------- | ------------ |
-| db_name    | 否       | 数据库名称。 |
-| table_name | 是       | 表名。       |
-
-## 返回结果说明
-
-```Plain
-+---------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
-| Table   | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
-+---------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
-```
-
-返回结果中的参数说明：
-
-| **参数**    | **说明**         |
-| ----------- | ---------------- |
-| Key_name    | 索引名称。       |
-| Column_name | 创建索引的列名。 |
-| Index_type  | 索引类型。       |
-| Comment     | 索引备注。       |
-
-> 说明：当前仅支持查看 bitmap 索引，bitmap 索引的相关信息仅包括以上四个参数。返回结果中的其他参数和 bitmap 索引无关。
-
-## 示例
-
-为表`sales_records`中的`item_id`列创建 bitmap 索引，索引名称为`index3`。表`sales_records`所属数据库为`d0`。
-
-```SQL
-CREATE INDEX index3 ON sales_records (item_id) USING BITMAP COMMENT '';
-```
-
-查看表`sales_records`的所有索引。
-
-```Plain
-SHOW INDEX FROM d0.sales_records;
-
-+----------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
-| Table                            | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
-+----------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
-| default_cluster:d0.sales_records |            | index3   |              | item_id     |           |             |          |        |      | BITMAP     | NULL    |
-+----------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
-```
-
-或
-
-```Plain
-SHOW KEY FROM sales_records FROM d0;
-
-+----------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
-| Table                            | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
-+----------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
-| default_cluster:d0.sales_records |            | index3   |              | item_id     |           |             |          |        |      | BITMAP     | NULL    |
-+----------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md
deleted file mode 100644
index fa9e9bffa2b04c..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_LOAD.md
+++ /dev/null
@@ -1,176 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW LOAD
-
-## 功能
-
-查看数据库中指定导入作业的相关信息，包括 [Broker Load](../data-manipulation/BROKER_LOAD.md)、[INSERT](./INSERT.md) 和 [Spark Load](../data-manipulation/SPARK_LOAD.md)。您还可以使用 `curl` 命令查看这些导入作业的相关信息。注意，从 3.1 版本起，对于 Broker Load 和 Insert 导入，推荐您通过 [SELECT](../data-manipulation/SELECT.md) 语句从 `information_schema` 数据库中的 [`loads`](../../../reference/information_schema/loads.md) 表来查看作业结果。详请参见[从 HDFS 导入](../../../loading/hdfs_load.md)、[从云存储导入](../../../loading/cloud_storage_load.md)、[通过 INSERT 语句导入数据](../../../loading/InsertInto.md)和[使用 Apache Spark™ 批量导入](../../../loading/SparkLoad.md)。
-
-除了以上三种导入方式， StarRocks 还支持 Stream Load 和 Routine Load，其中 Stream Load 是同步操作，会直接返回结果，不会通过 SHOW LOAD 展示。Routine Load 可通过 [SHOW ROUTINE LOAD](../data-manipulation/SHOW_ROUTINE_LOAD.md) 查看导入作业的相关信息。
-
-## 语法
-
-```SQL
-SHOW LOAD [ FROM db_name ]
-[
-   WHERE [ LABEL { = "label_name" | LIKE "label_matcher" } ]
-         [ [AND] STATE = { "PENDING" | "ETL" | "LOADING" | "FINISHED" | "CANCELLED" } ]
-]
-[ ORDER BY field_name [ ASC | DESC ] ]
-[ LIMIT { [offset, ] limit | limit OFFSET offset } ]
-```
-
-> **说明**
->
-> 返回结果中的字段较多，可使用`\G`分行，如 `SHOW LOAD WHERE LABEL = "label1"\G`。详情参见[示例一](#示例)。
-
-## 参数说明
-
-| **参数**                          | **必选** | **说明**                                                     |
-| --------------------------------- | -------- | ------------------------------------------------------------ |
-| db_name                           | 否       | 数据库名称。如不指定该参数，则默认查看当前数据库的导入作业。 |
-| LABEL = "label_name"              | 否       | 导入作业标签。                                               |
-| LABEL LIKE "label_matcher"        | 否       | 查看标签中包含 `label_matcher` 的导入作业。                  |
-| AND                               | 否       | <ul><li>如果只使用其中一个过滤条件，则不需要指定该关键字。例如 `WHERE STATE = "PENDING"`。</li><li>如使用其中任意两个或三个过滤条件，则需要指定该关键字。例如 `WHERE LABEL = "label_name" AND STATE = "PENDING"`。</li></ul> |
-| STATE                             | 否       | 导入作业的状态。不同的导入方式有不同的导入作业状态，具体如下：<ul><li>Broker Load<ul><li>`PENDING`：导入作业已创建。</li><li>`QUEUEING`：导入作业正在等待执行中。</li><li>`LOADING`：导入作业正在执行中。</li><li>`PREPARED`：事务已提交。</li><li>`FINISHED`：导入作业成功。</li><li>`CANCELLED`：导入作业失败。</li></ul></li><li>Spark Load<ul><li>`PENDING`：准备 ETL 任务的相关配置并提交 ETL 任务到 Apache Spark™ 集群。</li><li>`ETL`：Spark 集群执行 ETL 任务，并将结果数据写入 Spark 的 HDFS 中。</li><li>`LOADING`：正在将 HDFS 源数据导入到 StarRocks 的目标表中。</li><li>`PREPARED`：事务已提交。</li><li>`FINISHED`：导入作业成功。</li><li>`CANCELLED`：导入作业失败。</li></ul></li><li>INSERT<ul><li>`FINISHED`：导入作业成功。</li><li>`CANCELLED`：导入作业失败。</li></ul></li></ul>如不指定 `STATE` 参数，则默认显示所有状态的导入作业；如指定，则显示指定状态的导入作业。例如 `STATE = "PENDING"` 会显示状态为 `PENDING` 的导入作业。|
-| ORDER BY field_name [ASC \| DESC] | 否       | 将返回结果按照指定字段升序或降序排列，当前支持的排序字段（field_name）包括 `JobId`、`Label`、`State`、`Progress`、`Type`、`EtlInfo`、`TaskInfo`、`ErrorMsg`、`CreateTime`、`EtlStartTime`、`EtlFinishTime`、`LoadStartTime`、`LoadFinishTime`、`URL` 和 `JobDetails`。<ul><li>如要升序排列，指定 `ORDER BY field_name ASC`。</li><li>如要降序排列，指定 `ORDER BY field_name DESC`。</li></ul>如既不指定排序字段也不指定排列顺序，则默认按照 `JobId` 升序排列。 |
-| LIMIT limit                       | 否       | 查看指定数量的作业。如不指定该参数，则默认显示所有符合筛选条件的作业；如指定，则显示指定数量的作业。例如 `LIMIT 10` 会显示 10 个符合筛选条件的作业。 |
-| OFFSET offset                     | 否       | `offset` 定义了返回结果中跳过的导入作业的数量，其默认值为 0。例如 `OFFSET 5` 表示跳过前 5 个导入作业，返回剩下的结果。 |
-
-## 返回结果说明
-
-```plain
-+-------+-------+-------+----------+------+---------+----------+----------+------------+--------------+---------------+---------------+----------------+-----+------------+
-| JobId | Label | State | Progress | Type | Priority | EtlInfo | TaskInfo | ErrorMsg | CreateTime | EtlStartTime | EtlFinishTime | LoadStartTime | LoadFinishTime | URL | JobDetails |
-+-------+-------+-------+----------+------+---------+----------+----------+------------+--------------+---------------+---------------+----------------+-----+------------+
-```
-
-导入方式不同，返回结果中的字段取值也有差异，具体如下。
-
-| **字段**       | **Broker Load**                                              | **Spark Load**                                               | **INSERT**                                                   |
-| -------------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
-| JobId          | 导入作业的全局唯一 ID，由 StarRocks 自动生成。               | 同 Broker Load。                                             | 同 Broker Load。                                             |
-| Label          | 导入作业的标签。每个数据库中的导入作业都一个唯一的标签，不同数据库的导入作业标签可以重复。 | 同 Broker Load。                                             | 同 Broker Load。                                             |
-| State          | 导入作业的状态，包括:<ul><li>`PENDING`：导入作业已创建。</li><li>`QUEUEING`：导入作业正在等待执行中。</li><li>`LOADING`：导入作业正在执行中。</li><li>`PREPARED`：事务已提交。</li><li>`FINISHED`：导入作业成功。</li><li>`CANCELLED`：导入作业失败。</li></ul> | 导入作业的状态，包括：<ul><li>`PENDING`：准备 ETL 任务的相关配置并提交 ETL 任务到 Spark 集群。</li><li>`ETL`：Spark 集群执行 ETL 任务，并将结果写入 Spark 的 HDFS 中。</li><li>`LOADING`：正在将 HDFS 源数据导入到 StarRocks 的目标表中。</li><li>`PREPARED`：事务已提交。</li><li>`FINISHED`：导入作业成功。</li><li>`CANCELLED`：导入作业失败。</li></ul> | 导入作业的状态，包括：<ul><li>`FINISHED`：导入作业成功。</li><li>`CANCELLED`：导入作业失败。</li></ul> |
-| Progress       | 导入作业所处的阶段。Broker Load 导入作业只有 `LOAD` 阶段，对应导入作业状态中的 `LOADING`。 `LOAD` 进度为 0~100%。Broker Load 没有 `ETL` 阶段，所以 `ETL` 对应的取值并无实际意义。<br />**说明**：<ul><li>`LOAD` 进度的计算公式为：完成数据导入的目标表的个数/导入作业中要进行数据导入的目标表的个数 * 100%。</li><li>当数据导入到所有目标表中时，`LOAD` 进度显示为 99%， 此时，导入进入最后的生效阶段。当整个导入流程完成后，`LOAD` 进度才会显示为 100%。</li><li>导入进度并不是线性的。如果一段时间内进度没有变化，并不代表导入没有在继续执行。</li></ul> | 导入作业所处的阶段。Spark Load 导入作业，包括 `ETL` 和 `LOAD` 两种阶段，分别对应导入作业状态中的 `ETL` 和 `LOADING`。 `ETL` 和 `LOAD` 进度均为 0~100%。<br />**说明**同 Broker Load。 | 导入作业所处的阶段。INSERT 导入作业只有 `LOAD` 阶段，没有 `ETL` 阶段，所以 `ETL` 对应的取值并无实际意义。`LOAD` 进度为 0~100%。<br />**说明**同 Broker Load。 |
-| Type           | 导入方式，取值为 `BROKER`。                                  | 导入方式，取值为 `SPARK`。                                    | 导入方式， 取值为 `INSERT`。                                  |
-| Priority       | 导入作业的执行优先级，包括：LOWEST、LOW、NORMAL、HIGH 和 HIGHEST。                           | -                                  | -                                  |
-| EtlInfo        | ETL 信息，包括以下 3 个指标：<ul><li>`unselected.rows`：通过 WHERE 子句指定的条件而过滤掉的行数。</li><li>`dpp.abnorm.ALL`：因数据质量不合格而过滤掉的行数。数据质量不合格是指源表中数据类型或列数等和目标表不匹配的数据行。</li><li>`dpp.norm.ALL`：实际导入的行数。</li></ul>以上三个指标之和就是数据源的总行数。您可以根据这三个指标计算当前导入作业数据质量不合格的比例是否超过 `max-filter-ratio`，计算公式为：`dpp.abnorm.ALL`/(`unselected.rows` + `dpp.abnorm.ALL` + `dpp.norm.ALL`)。 | 同 Broker Load。                                             | ETL 信息。由于 INSERT 没有 ETL 阶段，所以该参数值为 `NULL`。  |
-| TaskInfo       | 创建导入作业时指定的参数，包括：<ul><li>`resource`：该参数在 Broker Load 导入作业中无实际意义。</li><li>`timeout`：导入作业的超时时间。单位：秒。</li><li>`max-filter-ratio`：导入作业的最大容忍率，即导入作业能够容忍的因数据不规范等原因而过滤掉的数据行所占的最大比例。</li></ul>有关以上参数的详细信息，参见 [BROKER LOAD](../data-manipulation/BROKER_LOAD.md)。 | 创建导入作业时指定的参数，包括：<ul><li>`resource`：资源名称。</li><li>`timeout`：导入作业的超时时间。单位：秒。</li><li>`max-filter-ratio`：导入作业的最大容忍率，即导入作业能够容忍的因数据不规范等原因而过滤掉的数据行所占的最大比例。</li></ul>有关以上参数的详细信息，参见 [SPARK LOAD](../data-manipulation/SPARK_LOAD.md)。 | 创建导入作业时指定的参数，包括：<ul><li>`resource`：该参数在 INSERT 导入作业中无实际意义。</li><li>`timeout`：导入作业的超时时间。单位：秒。</li><li>`max-filter-ratio`：该参数在 INSERT 导入作业中无实际意义。</li></ul>详细信息，参见 [INSERT](./INSERT.md)。 |
-| ErrorMsg       | 导入作业的失败原因。当导入作业的状态为 `PENDING`，`LOADING` 或 `FINISHED` 时，该参数值为 `NULL`。当导入作业的状态为 `CANCELLED` 时，该参数值包括 `type` 和 `msg` 两部分：<ul><li>`type` 包括如下取值：<ul><li>`USER_CANCEL`：导入作业被手动取消。</li><li>`ETL_SUBMIT_FAIL`：导入任务提交失败。</li><li>`ETL_QUALITY_UNSATISFIED`：数据质量不合格，即导入作业的错误数据率超过了 `max-filter-ratio`。</li><li>`LOAD_RUN_FAIL`：导入作业在 `LOAD` 阶段失败。</li><li>`TIMEOUT`：导入作业未在允许的超时时间内完成。</li><li>`UNKNOWN`：未知的导入错误。</li></ul></li><li>`msg`显示有关失败原因的详细信息。</li></ul> | 导入作业的失败原因。当导入作业的状态为 `PENDING`、`ETL`、`LOADING` 或 `FINISHED` 时，该参数值为 `NULL`。当导入作业的状态为 `CANCELLED` 时，该参数值包括 `type` 和 `msg` 两部分：<ul><li>`type` 包括如下取值：<ul><li>`USER_CANCEL`：导入作业被手动取消。</li><li>`ETL_SUBMIT_FAIL`：ETL 提交失败。</li><li>`ETL_RUN_FAIL`： ETL 执行失败。</li><li>`ETL_QUALITY_UNSATISFIED`：数据质量不合格，即导入作业的错误数据率超过了 `max-filter-ratio`。</li><li>`LOAD_RUN_FAIL`：导入作业在 `LOAD` 阶段失败。</li><li>`TIMEOUT`：导入作业未在允许的超时时间内完成。</li><li>`UNKNOWN`：未知的导入错误。</li></ul></li><li>`msg`显示有关失败原因的详细信息。</li></ul> | 导入作业的失败原因。当导入作业的状态为 `FINISHED` 时，该参数值为 `NULL`。当导入作业的状态为 `CANCELLED` 时，该参数值包括 `type` 和 `msg` 两部分：<ul><li>`type` 包括如下取值：<ul><li>`USER_CANCEL`：导入作业被手动取消。</li><li>`ETL_SUBMIT_FAIL`：导入作业提交失败。</li><li>`ETL_RUN_FAIL`：导入作业执行失败。</li><li>`ETL_QUALITY_UNSATISFIED`：数据质量不合格，导入作业失败。</li><li>`LOAD_RUN_FAIL`：导入作业在 `LOAD` 阶段失败。</li><li>`TIMEOUT`：导入作业未在允许的超时时间内完成。</li><li>`UNKNOWN`：未知的导入错误。</li><li>`TXN_UNKNOWN`：事务状态未知，导入作业失败。</li></ul></li><li>`msg` 显示有关失败原因的详细信息。</li></ul> |
-| CreateTime     | 导入作业创建的时间。                                         | 同 Broker Load。                                             | 同 Broker Load。                                             |
-| EtlStartTime   | 由于 Broker Load 导入没有 ETL 阶段，所以该参数值和 `LoadStartTime` 相同。 | `ETL` 阶段开始的时间。                                        | 由于 INSERT 导入没有 ETL 阶段，所以该参数取值和 `LoadStartTime` 相同。 |
-| EtlFinishTime  | 由于 Broker Load 导入没有 ETL 阶段，所以该参数值和 `LoadStartTime` 相同。 | `ETL` 阶段完成的时间。                                        | 由于 INSERT 导入没有 ETL 阶段，所以该参数取值和 `LoadStartTime` 相同。 |
-| LoadStartTime  | `LOAD` 阶段开始的时间。                                       | 同 Broker Load。                                             | 同 Broker Load。                                             |
-| LoadFinishTime | 导入作业完成的时间。                                         | 同 Broker Load。                                             | 同 Broker Load。                                             |
-| URL            | 导入作业中质量不合格数据的访问地址。您可以使用 `curl` 或 `wget` 命令打开该地址。如果导入作业不存在质量不合格数据，该参数值为 `NULL`。 | 同 Broker Load。                                             | 同 Broker Load。                                             |
-| JobDetails     | 导入作业的其他信息，包括：<ul><li>`Unfinished backends`：未完成导入的 BE 节点 ID。</li><li>`ScannedRows`：实际处理的行数，包括导入的行数以及过滤掉的行数。</li><li>`TaskNumber`：子作业个数。</li><li>`All backends`：正在运行子作业的 BE 节点的 ID。</li><li>`FileNumber`：源文件的个数。</li><li>`FileSize`：所有源文件的总数据量，单位：字节。</li></ul> | 同 Broker Load。                                             | 同 Broker Load。                                             |
-
-## 注意事项
-
-- 导入作业相关信息具有时效性。默认自一个导入作业的完成时间 (`LoadFinishTime`) 起 3 天内可以查看到该导入作业的相关信息；3 天后，信息会失效，无法查到。您可以通过 FE 参数 `label_keep_max_second` 修改默认有效时间（单位：秒），操作如下：
-
-    ```SQL
-    ADMIN SET FRONTEND CONFIG ("label_keep_max_second" = "value");
-    ```
-
-- 若导入作业的 `LoadStartTime` 长时间为 `N/A`，说明导入作业堆积严重，可降低作业创建的频率。
-- 导入作业所消耗的总时长 = `LoadFinishTime` - `CreateTime`。
-- `LOAD` 阶段所消耗的时长 = `LoadFinishTime` - `LoadStartTime`。
-
-## 示例
-
-示例一：查看当前数据库中的所有导入作业。
-
-```plain
-SHOW LOAD\G;
-*************************** 1. row ***************************
-         JobId: 976331
-         Label: duplicate_table_with_null
-         State: FINISHED
-      Progress: ETL:100%; LOAD:100%
-          Type: BROKER
-      Priority: NORMAL 
-       EtlInfo: unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546
-      TaskInfo: resource:N/A; timeout(s):300; max_filter_ratio:0.0
-      ErrorMsg: NULL
-    CreateTime: 2022-10-17 19:35:00
-  EtlStartTime: 2022-10-17 19:35:04
- EtlFinishTime: 2022-10-17 19:35:04
- LoadStartTime: 2022-10-17 19:35:04
-LoadFinishTime: 2022-10-17 19:35:06
-           URL: NULL
-    JobDetails: {"Unfinished backends":{"b90a703c-6e5a-4fcb-a8e1-94eca5be0b8f":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"b90a703c-6e5a-4fcb-a8e1-94eca5be0b8f":[10004]},"FileNumber":1,"FileSize":548622}
-```
-
-示例二：查看当前数据库中的导入作业。导入作业的标签中需包含字符串 `null`，且仅展示 2 个作业。
-
-```plain
-SHOW LOAD 
-WHERE LABEL LIKE "null" 
-LIMIT 2;
-
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| JobId | Label                     | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                                                                                | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL                                                                            | JobDetails                                                                                                                                                                                              |
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| 10082 | duplicate_table_with_null | FINISHED | ETL:100%; LOAD:100% | BROKER | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:N/A; timeout(s):300; max_filter_ratio:0.0                                                      | NULL     | 2022-08-02 14:53:27 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:31 | NULL                                                                           | {"Unfinished backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[10002]},"FileNumber":1,"FileSize":548622} |
-| 10103 | unique_table_with_null    | FINISHED | ETL:100%; LOAD:100% | SPARK  | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:test_spark_resource_07af473a_1230_11ed_b483_00163e0e550b; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:56:06 | 2022-08-02 14:56:19 | 2022-08-02 14:56:41 | 2022-08-02 14:56:41 | 2022-08-02 14:56:44 | http://emr-header-1.cluster-49091:20888/proxy/application_1655710334658_26391/ | {"Unfinished backends":{"00000000-0000-0000-0000-000000000000":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"00000000-0000-0000-0000-000000000000":[-1]},"FileNumber":1,"FileSize":8790855}   |
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-```
-
-示例三： 查看数据库 `example_db` 中的导入作业。导入作业的标签中需包含字符串 `table`，且按 `LoadStartTime` 降序排序。
-
-```plain
-SHOW LOAD FROM example_db 
-WHERE LABEL Like "table" 
-ORDER BY LoadStartTime DESC;
-
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| JobId | Label                     | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                                                                                | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL                                                                            | JobDetails                                                                                                                                                                                              |
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| 10103 | unique_table_with_null    | FINISHED | ETL:100%; LOAD:100% | SPARK  | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:test_spark_resource_07af473a_1230_11ed_b483_00163e0e550b; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:56:06 | 2022-08-02 14:56:19 | 2022-08-02 14:56:41 | 2022-08-02 14:56:41 | 2022-08-02 14:56:44 | http://emr-header-1.cluster-49091:20888/proxy/application_1655710334658_26391/ | {"Unfinished backends":{"00000000-0000-0000-0000-000000000000":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"00000000-0000-0000-0000-000000000000":[-1]},"FileNumber":1,"FileSize":8790855}   |
-| 10082 | duplicate_table_with_null | FINISHED | ETL:100%; LOAD:100% | BROKER | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:N/A; timeout(s):300; max_filter_ratio:0.0                                                      | NULL     | 2022-08-02 14:53:27 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:31 | NULL                                                                           | {"Unfinished backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[10002]},"FileNumber":1,"FileSize":548622} |
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-```
-
-示例四：查看数据库 `example_db` 中的导入作业。导入作业的标签需为 `duplicate_table_with_null`，状态需为 `FINISHED`。
-
-```plain
-SHOW LOAD FROM example_db 
-WHERE LABEL = "duplicate_table_with_null" AND STATE = "FINISHED";
-
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+----------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| JobId | Label                     | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                           | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL  | JobDetails                                                                                                                                                                                              |
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+----------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| 10082 | duplicate_table_with_null | FINISHED | ETL:100%; LOAD:100% | BROKER | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:N/A; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:53:27 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:31 | NULL | {"Unfinished backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[10002]},"FileNumber":1,"FileSize":548622} |
-+-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+----------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-```
-
-示例五：查看数据库 `example_db` 中的导入作业。导入作业需按 `CreateTime` 升序排序，并从偏移量 1 开始显示 2 条查询结果。
-
-```sql
-SHOW LOAD FROM example_db 
-ORDER BY CreateTime ASC 
-LIMIT 2 OFFSET 1;
-```
-
-或
-
-```sql
-SHOW LOAD FROM example_db 
-ORDER BY CreateTime ASC 
-LIMIT 1,2;
-```
-
-返回结果如下：
-
-```plain
-+-------+---------------------------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| JobId | Label                                       | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                                                                                | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL                                                                            | JobDetails                                                                                                                                                                                            |
-+-------+---------------------------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| 10103 | unique_table_with_null                      | FINISHED | ETL:100%; LOAD:100% | SPARK  | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:test_spark_resource_07af473a_1230_11ed_b483_00163e0e550b; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:56:06 | 2022-08-02 14:56:19 | 2022-08-02 14:56:41 | 2022-08-02 14:56:41 | 2022-08-02 14:56:44 | http://emr-header-1.cluster-49091:20888/proxy/application_1655710334658_26391/ | {"Unfinished backends":{"00000000-0000-0000-0000-000000000000":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"00000000-0000-0000-0000-000000000000":[-1]},"FileNumber":1,"FileSize":8790855} |
-| 10120 | insert_3a57b595-1230-11ed-b075-00163e14c85e | FINISHED | ETL:100%; LOAD:100% | INSERT | NULL                                                    | resource:N/A; timeout(s):3600; max_filter_ratio:0.0                                                     | NULL     | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 |                                                                                | {"Unfinished backends":{},"ScannedRows":0,"TaskNumber":0,"All backends":{},"FileNumber":0,"FileSize":0}                                                                                               |
-+-------+---------------------------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md
deleted file mode 100644
index 5ca04559a67a08..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md
+++ /dev/null
@@ -1,170 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW MATERIALIZED VIEWS
-
-## 功能
-
-展示所有或指定异步物化视图信息。该语句从 3.0 版本开始更名为 SHOW MATERIALIZED VIEWS，之前版本为 SHOW MATERIALIZED VIEW。
-
-> **注意**
->
-> 该命令当前仅针对异步物化视图生效。针对同步物化视图您可以通过 [SHOW ALTER MATERIALIZED VIEW](../data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW.md) 命令查看当前数据库中同步物化视图的构建状态。
-> 该操作不需要权限。
-
-## 语法
-
-```SQL
-SHOW MATERIALIZED VIEWS
-[FROM db_name]
-[
-WHERE NAME { = "mv_name" | LIKE "mv_name_matcher"}
-]
-```
-
-:::note
-
-自 v3.3 起，如果单个物化视图刷新任务包含多个分区或 task_runs，`SHOW MATERIALIZED VIEWS` 语句将追踪所有 task_runs 的状态。仅当所有 task_runs 成功后，`last_refresh_state` 字段才会返回 `SUCCESS`。
-
-:::
-
-## 参数
-
-| **参数**        | **必选** | **说明**                                                     |
-| --------------- | -------- | ------------------------------------------------------------ |
-| db_name         | 否       | 物化视图所属的数据库名称。如果不指定该参数，则默认使用当前数据库。 |
-| mv_name         | 否       | 用于精确匹配的物化视图名称。                                 |
-| mv_name_matcher | 否       | 用于模糊匹配的物化视图名称 matcher。                         |
-
-## 返回
-
-返回最近一次 REFRESH 任务的状态。
-
-| **返回**                   | **说明**                                                    |
-| -------------------------- | --------------------------------------------------------- |
-| id                         | 物化视图 ID。                                               |
-| database_name              | 物化视图所属的数据库名称。                                     |
-| name                       | 物化视图名称。                                               |
-| refresh_type               | 物化视图的更新方式，包括 ROLLUP、MANUAL、ASYNC、INCREMENTAL。   |
-| is_active                  | 物化视图状态是否为 active。有效值：`true` 和 `false`。          |
-| partition_type             | 物化视图的分区类型，包括 RANGE 和 UNPARTITIONED。|
-| task_id                    | 物化视图的刷新任务 ID。                                       |
-| task_name                  | 物化视图的刷新任务名称。                                       |
-| last_refresh_start_time    | 物化视图上一次刷新开始时间。                                    |
-| last_refresh_finished_time | 物化视图上一次刷新结束时间。                                    |
-| last_refresh_duration      | 物化视图上一次刷新耗时（单位秒）。                               |
-| last_refresh_state         | 物化视图上一次刷新的状态，包括 PENDING、RUNNING、FAILED、SUCCESS。 |
-| last_refresh_force_refresh | 物化视图上一次刷新是否为强制（FORCE）刷新。                      ｜
-| last_refresh_start_partition | 上一次刷新开始的物化视图分区。                                ｜
-| last_refresh_end_partition | 上一次刷新结束的物化视图分区。                                  ｜
-| last_refresh_base_refresh_partitions | 上一次刷新基表更新的分区。                            ｜
-| last_refresh_mv_refresh_partitions | 上一次刷新物化视图刷新的分区。                          ｜
-| last_refresh_error_code    | 物化视图上一次刷新失败的 ErrorCode（如果物化视图状态不为 active）。 |
-| last_refresh_error_message | 物化视图上一次刷新失败的 ErrorMessage（如果物化视图状态不为 active）。 |
-| rows                       | 物化视图中数据行数。                                           |
-| text                       | 创建物化视图的查询语句。                                        |
-
-## 示例
-
-以下示例基于当前业务情景：
-
-```Plain
--- Create Table: customer
-CREATE TABLE customer ( C_CUSTKEY     INTEGER NOT NULL,
-                        C_NAME        VARCHAR(25) NOT NULL,
-                        C_ADDRESS     VARCHAR(40) NOT NULL,
-                        C_NATIONKEY   INTEGER NOT NULL,
-                        C_PHONE       CHAR(15) NOT NULL,
-                        C_ACCTBAL     double   NOT NULL,
-                        C_MKTSEGMENT  CHAR(10) NOT NULL,
-                        C_COMMENT     VARCHAR(117) NOT NULL,
-                        PAD char(1) NOT NULL)
-    ENGINE=OLAP
-DUPLICATE KEY(`c_custkey`)
-COMMENT "OLAP"
-DISTRIBUTED BY HASH(`c_custkey`) BUCKETS 10
-PROPERTIES (
-"replication_num" = "3",
-"storage_format" = "DEFAULT"
-);
-
--- Create MV: customer_mv
-CREATE MATERIALIZED VIEW customer_mv
-DISTRIBUTED BY HASH(c_custkey) buckets 10
-REFRESH MANUAL
-PROPERTIES (
-    "replication_num" = "3"
-)
-AS SELECT
-              c_custkey, c_phone, c_acctbal, count(1) as c_count, sum(c_acctbal) as c_sum
-   FROM
-              customer
-   GROUP BY c_custkey, c_phone, c_acctbal;
-
--- Refresh the MV
-REFRESH MATERIALIZED VIEW customer_mv;
-```
-
-示例一：通过精确匹配查看特定物化视图
-
-```Plain
-mysql> show materialized views  where name='customer_mv'\G
-*************************** 1. row ***************************
-                        id: 10142
-                      name: customer_mv
-             database_name: test
-              refresh_type: MANUAL
-                 is_active: true
-   last_refresh_start_time: 2023-02-17 10:27:33
-last_refresh_finished_time: 2023-02-17 10:27:33
-     last_refresh_duration: 0
-        last_refresh_state: SUCCESS
-             inactive_code: 0
-           inactive_reason:
-                      text: CREATE MATERIALIZED VIEW `customer_mv`
-COMMENT "MATERIALIZED_VIEW"
-DISTRIBUTED BY HASH(`c_custkey`) BUCKETS 10
-REFRESH MANUAL
-PROPERTIES (
-"replication_num" = "3",
-"storage_medium" = "HDD"
-)
-AS SELECT `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`, count(1) AS `c_count`, sum(`customer`.`c_acctbal`) AS `c_sum`
-FROM `test`.`customer`
-GROUP BY `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`;
-                      rows: 0
-1 row in set (0.11 sec)
-```
-
-示例二：通过模糊匹配查看物化视图
-
-```Plain
-mysql> show materialized views  where name like 'customer_mv'\G
-*************************** 1. row ***************************
-                        id: 10142
-                      name: customer_mv
-             database_name: test
-              refresh_type: MANUAL
-                 is_active: true
-   last_refresh_start_time: 2023-02-17 10:27:33
-last_refresh_finished_time: 2023-02-17 10:27:33
-     last_refresh_duration: 0
-        last_refresh_state: SUCCESS
-             inactive_code: 0
-           inactive_reason:
-                      text: CREATE MATERIALIZED VIEW `customer_mv`
-COMMENT "MATERIALIZED_VIEW"
-DISTRIBUTED BY HASH(`c_custkey`) BUCKETS 10
-REFRESH MANUAL
-PROPERTIES (
-"replication_num" = "3",
-"storage_medium" = "HDD"
-)
-AS SELECT `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`, count(1) AS `c_count`, sum(`customer`.`c_acctbal`) AS `c_sum`
-FROM `test`.`customer`
-GROUP BY `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`;
-                      rows: 0
-1 row in set (0.12 sec)
-
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_PARTITIONS.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_PARTITIONS.md
deleted file mode 100644
index c461ac9463ab6c..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_PARTITIONS.md
+++ /dev/null
@@ -1,102 +0,0 @@
----
-displayed_sidebar: "Chinese"
-keywords: ['fenqu']
----
-
-# SHOW PARTITIONS
-
-## 功能
-
-该语句用于展示正常分区或临时分区信息。
-
-## 语法
-
-```sql
-SHOW [TEMPORARY] PARTITIONS FROM [db_name.]table_name [WHERE] [ORDER BY] [LIMIT]
-```
-
-> 说明
->
-> * 支持 PartitionId，PartitionName，State，Buckets，ReplicationNum，LastConsistencyCheckTime 等列的过滤。
-> * 该语法只支持 StarRocks 表 (即 `"ENGINE" = "OLAP"`)。
-> * 自 3.0 版本起，该操作需要对应表的 SELECT 权限。 3.0 版本之前，该操作需要对应数据库和表的 SELECT_PRIV 权限。
-
-## 返回结果说明
-
-```SQL
-+-------------+---------------+----------------+---------------------+--------------------+--------+--------------+-------+--------------------+---------+----------------+---------------+---------------------+--------------------------+----------+------------+----------+
-| PartitionId | PartitionName | VisibleVersion | VisibleVersionTime  | VisibleVersionHash | State  | PartitionKey | Range | DistributionKey    | Buckets | ReplicationNum | StorageMedium | CooldownTime        | LastConsistencyCheckTime | DataSize | IsInMemory | RowCount |
-+-------------+---------------+----------------+---------------------+--------------------+--------+--------------+-------+--------------------+---------+----------------+---------------+---------------------+--------------------------+----------+------------+----------+
-```
-
-| **字段**                     | **说明**                                                         |
-| ------------------------ | ------------------------------------------------------------ |
-| PartitionId              | 分区 ID。                                                    |
-| PartitionName            | 分区名。                                                     |
-| VisibleVersion           | 最后一次成功导入的版本号。每次成功导入，则版本号加 1。   |
-| VisibleVersionTime       | 最后一次成功导入的时间。                                   |
-| VisibleVersionHash       | 最后一次成功导入的版本号的哈希值。                         |
-| State                    | 分区的状态。固定为 `Normal`。                                |
-| PartitionKey             | 分区键，由一个或多个分区列组成。                                                     |
-| Range                    | Range 分区的范围，为左闭右开区间。                           |
-| DistributionKey          | 分区中数据进行哈希分桶时的分桶键。                           |
-| Buckets                  | 分区中的分桶数量。                                           |
-| ReplicationNum           | 分区中每个 Tablet 的副本数量。                                |
-| StorageMedium            | 数据存储介质。返回值为 `HDD` 表示机械硬盘，返回值为 `SSD` 表示固态硬盘。           |
-| CooldownTime             | 数据降冷时间。如果一开始数据的存储介质为 SSD ，在该时间点之后，数据存储介质会从 SSD 切换为 HDD。 格式："yyyy-MM-dd HH:mm:ss"。|
-| LastConsistencyCheckTime | 最后一次一致性检查的时间。`NULL` 表示没有进行一致性检查。    |
-| DataSize                 | 分区中数据大小。                                             |
-| IsInMemory               | 该分区数据是否全部存储在内存中。                             |
-| RowCount                 | 该分区数据行数。                                             |
-| MaxCS                    | 该分区最大 Compaction Score。仅限存算分离集群。                   |
-
-## 示例
-
-1. 查询指定数据库（例如 `test`）下指定表（例如 `site_access`）的所有正式分区信息：
-
-    ```SQL
-    MySQL > show partitions from test.site_access\G
-    *************************** 1. row ***************************
-                PartitionId: 20990
-            PartitionName: p2019 
-            VisibleVersion: 1
-        VisibleVersionTime: 2023-08-08 15:45:13
-        VisibleVersionHash: 0
-                    State: NORMAL
-                PartitionKey: datekey
-                    Range: [types: [DATE]; keys: [2019-01-01]; ..types: [DATE]; keys: [2020-01-01]; )
-            DistributionKey: site_id
-                    Buckets: 6
-            ReplicationNum: 3
-            StorageMedium: HDD
-                CooldownTime: 9999-12-31 23:59:59
-    LastConsistencyCheckTime: NULL
-                    DataSize:  4KB   
-                IsInMemory: false
-                    RowCount: 3 
-    1 row in set (0.00 sec)
-    ```
-
-2. 查询指定数据库（例如 `test`）下指定表（例如 `site_access`）的所有临时分区信息：
-
-    ```sql
-    SHOW TEMPORARY PARTITIONS FROM test.site_access;
-    ```
-
-3. 查询指定数据库（例如 `test`）下指定表（例如 `site_access`）的指定分区（例如 `p1`）的信息。
-
-    ```sql
-    -- 正常分区
-    SHOW PARTITIONS FROM test.site_access WHERE PartitionName = "p1";
-    -- 临时分区
-    SHOW TEMPORARY PARTITIONS FROM test.site_access WHERE PartitionName = "p1";
-    ```
-
-4. 查询指定数据库（例如 `test`）下指定表（例如 `site_access`）的最新分区的信息。
-
-    ```sql
-    -- 正常分区
-    SHOW PARTITIONS FROM test.site_access ORDER BY PartitionId DESC LIMIT 1;
-    -- 临时分区
-    SHOW TEMPORARY PARTITIONS FROM test.site_access ORDER BY PartitionId DESC LIMIT 1;
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md
deleted file mode 100644
index 54b58665369ba2..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md
+++ /dev/null
@@ -1,82 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW PIPES
-
-## 功能
-
-查看当前数据库或指定数据库下 Pipe。该命令自 3.2 版本起支持。
-
-## 语法
-
-```SQL
-SHOW PIPES [FROM <db_name>]
-[
-   WHERE [ NAME { = "<pipe_name>" | LIKE "pipe_matcher" } ]
-         [ [AND] STATE = { "SUSPENDED" | "RUNNING" | "ERROR" } ]
-]
-[ ORDER BY <field_name> [ ASC | DESC ] ]
-[ LIMIT { [offset, ] limit | limit OFFSET offset } ]
-```
-
-## 参数说明
-
-### FROM `<db_name>`
-
-指定待查询数据库的名称。如果不指定数据库，则默认查询当前数据库下的 Pipe。
-
-### WHERE
-
-指定查询条件。
-
-### ORDER BY `<field_name>`
-
-指定结果记录的排序字段。
-
-### LIMIT
-
-指定系统返回的最大结果记录数。
-
-## 返回结果
-
-返回结果包括如下字段：
-
-| **字段**      | **说明**                                                     |
-| ------------- | ------------------------------------------------------------ |
-| DATABASE_NAME | Pipe 所属数据库的名称。                                      |
-| ID            | Pipe 的唯一 ID。                                             |
-| NAME          | Pipe 的名称。                                                |
-| TABLE_NAME    | StarRocks 目标表的名称。                                     |
-| STATE         | Pipe 的状态，包括 `RUNNING`、`FINISHED`、`SUSPENDED`、`ERROR`。 |
-| LOAD_STATUS   | Pipe 下待导入数据文件的整体状态，包括如下字段：<ul><li>`loadedFiles`：已导入的数据文件总个数。</li><li>`loadedBytes`：已导入的数据总量，单位为字节。</li><li>`LastLoadedTime`：最近一次执行导入的时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。</li></ul> |
-| LAST_ERROR    | Pipe 执行过程中最近一次错误的详细信息。默认值为 `NULL`。     |
-| CREATED_TIME  | Pipe 的创建时间。格式：`yyyy-MM-dd HH:mm:ss`。例如：`2023-07-24 14:58:58`。 |
-
-## 示例
-
-### 查询所有 Pipe
-
-进入数据库 `mydatabase`，然后查看该数据库下所有 Pipe：
-
-```SQL
-USE mydatabase;
-SHOW PIPES \G
-```
-
-### 查询指定 Pipe
-
-进入数据库 `mydatabase`，然后查看该数据库下名为 `user_behavior_replica` 的 Pipe：
-
-```SQL
-USE mydatabase;
-SHOW PIPES WHERE NAME = 'user_behavior_replica' \G
-```
-
-## 相关文档
-
-- [CREATE PIPE](../data-manipulation/CREATE_PIPE.md)
-- [ALTER PIPE](../data-manipulation/ALTER_PIPE.md)
-- [DROP PIPE](../data-manipulation/DROP_PIPE.md)
-- [SUSPEND or RESUME PIPE](../data-manipulation/SUSPEND_or_RESUME_PIPE.md)
-- [RETRY FILE](../data-manipulation/RETRY_FILE.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md
deleted file mode 100644
index 9980ff5fdc573d..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD.md
+++ /dev/null
@@ -1,126 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW ROUTINE LOAD
-
-import RoutineLoadPrivNote from '../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
-
-## 功能
-
-查看 Routine Load 导入作业的执行情况。
-
-<RoutineLoadPrivNote />
-
-## 语法
-
-```SQL
-SHOW [ALL] ROUTINE LOAD [ FOR [<db_name>.]<job_name> | FROM <db_name> ]
-[ WHERE [ STATE = { "NEED_SCHEDULE" | "RUNNING" | "PAUSED" | "UNSTABLE" | "STOPPED" | "CANCELLED"  } ] ]
-[ ORDER BY <field_name> [ ASC | DESC ] ]
-[ LIMIT { [offset, ] limit | limit OFFSET offset } ]
-```
-
-:::note
-
-如果返回结果中的字段较多，可使用 `\G` 分行，如 `SHOW ROUTINE LOAD FOR <job_name>\G`。
-
-:::
-
-## 参数说明
-
-| **参数**                          | **必选** | **说明**                                                     |
-| --------------------------------- | -------- | ------------------------------------------------------------ |
-| db_name                           | 否       | 导入作业所属数据库名称。注意在使用 FROM 子句时，该参数为必填参数。                                     |
-| job_name                          | 否        | 导入作业名称。注意在使用 FOR 子句时，该参数为必填参数。                                              |
-| ALL                               | 否       | 显示所有导入作业，包括处于 `STOPPED` 和 `CANCELLED` 状态的导入作业。 |
-| STATE                             | 否       | 导入作业状态。                                               |
-| ORDER BY field_name [ASC \| DESC] | 否       | 将返回结果按照指定字段升序或降序排列，当前支持的排序字段（`field_name`）包括 `Id`、`Name`、`CreateTime`、`PauseTime`、`EndTime`、`TableName`、`State` 和 `CurrentTaskNum`。如要升序排列，指定 `ORDER BY field_name ASC`。如要降序排列，指定 `ORDER BY field_name DESC`。如既不指定排序字段也不指定排列顺序，则默认按照 `Id` 升序排列。 |
-| LIMIT limit                       | 否       | 查看指定数量的导入作业，例如 `LIMIT 10` 会显示 10 个符合筛选条件的导入作业。如不指定该参数，则默认显示所有符合筛选条件的导入作业。 |
-| OFFSET offset                     | 否       | `offset` 定义了返回结果中跳过的导入作业的数量，其默认值为 0。例如 `OFFSET 5` 表示跳过前 5 个导入作业，返回剩下的结果。 |
-
-## 返回结果说明
-
-| **参数**             | **说明**                                                     |
-| -------------------- | ------------------------------------------------------------ |
-| Id                   | 导入作业的全局唯一 ID，由 StarRocks 自动生成。               |
-| Name                 | 导入作业的名称。                                             |
-| CreateTime           | 导入作业创建的时间。                                         |
-| PauseTime            | 处于 `PAUSED` 状态的导入作业的暂停时间。                     |
-| EndTime              | 处于 `STOPPED` 状态的导入作业的停止时间。                    |
-| DbName               | 导入作业目标表所属数据库。                                   |
-| TableName            | 导入作业目标表。                                             |
-| State                | 导入作业状态。包括：<ul><li>`NEED_SCHEDULE`：待调度状态。CREATE ROUTINE LOAD 或者 RESUME ROUTINE LOAD 后，导入作业会先进入待调度状态。</li><li>`RUNNING`：运行状态。消费进度可以通过`Statistic`、`Progress` 中查看。</li><li>`PAUSED`：暂停状态。您可以参考 `ReasonOfStateChanged`、`ErrorLogUrls` 进行修复。修复后您可以使用 [RESUME ROUTINE LOAD](https://docs.starrocks.io/zh/docs/3.2/sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD/)。</li><li>`CANCELLED`：取消状态。您可以参考 `ReasonOfStateChanged`、`ErrorLogUrls` 进行修复。但是修复后，您无法恢复该状态的导入作业。</li><li>`STOPPED`：停止状态。您无法恢复该状态的导入作业。</li><li>`UNSTABLE`：不稳定状态。Routine Load 导入作业的任一导入任务消费延迟，即正在消费的消息时间戳与当前时间的差值超过 FE 参数 [`routine_load_unstable_threshold_second`](../../../administration/management/FE_configuration.md#routine_load_unstable_threshold_second)  的值，且数据源中存在未被消费的消息，则导入作业置为 `UNSTABLE` 状态。 </li></ul>|
-| DataSourceType       | 数据源类型。固定为 `KAFKA`。                                 |
-| CurrentTaskNum       | 导入作业当前的任务数量。                                     |
-| JobProperties        | 导入作业属性。比如消费分区、列映射关系。                     |
-| DataSourceProperties | 数据源属性。比如 Topic、Kafka 集群中 Broker 的地址和端口列表。 |
-| CustomProperties     | 导入作业中自定义的更多数据源相关属性。                       |
-| Statistic            | 导入数据的指标，比如成功导入数据行、总数据行、已接受的数据量。 |
-| Progress             | 导入作业消费 Topic 中各个分区消息的进度（以位点进行衡量）。           |
-| TimestampProgress    | 导入作业消费 Topic 中各个分区消息的进度（以时间戳进行衡量）。         |
-| ReasonOfStateChanged | 导致导入作业处于 `CANCELLED` 或者 `PAUSED` 状态的原因。      |
-| ErrorLogUrls         | 错误日志 URL。您可以使用 `curl` 或 `wget` 命令打开该地址。   |
-| TrackingSQL          | 直接通过 SQL 查询 Information Schema 中记录的错误日志信息。  |
-| OtherMsg             | 所有失败的导入任务的信息。                                   |
-| LatestSourcePosition | 数据源 Kafka 中 Topic 中各个分区的最新消息位点，便于检查导入延迟情况。  | 
-
-## 示例
-
-如果导入作业成功处于 `RUNNING` 状态，则返回结果可能如下：
-
-```SQL
-MySQL [example_db]> SHOW ROUTINE LOAD FOR example_tbl_ordertest1\G
-*************************** 1. row ***************************
-                  Id: 10204
-                Name: example_tbl_ordertest1
-          CreateTime: 2023-12-21 21:01:31
-           PauseTime: NULL
-             EndTime: NULL
-              DbName: example_db
-           TableName: example_tbl
-               State: RUNNING
-      DataSourceType: KAFKA
-      CurrentTaskNum: 1
-       JobProperties: {"partitions":"*","rowDelimiter":"\t","partial_update":"false","columnToColumnExpr":"order_id,pay_dt,customer_name,nationality,temp_gender,price","maxBatchIntervalS":"10","partial_update_mode":"null","whereExpr":"*","timezone":"Asia/Shanghai","format":"csv","columnSeparator":"','","log_rejected_record_num":"0","taskTimeoutSecond":"60","json_root":"","maxFilterRatio":"1.0","strict_mode":"false","jsonpaths":"","taskConsumeSecond":"15","desireTaskConcurrentNum":"5","maxErrorNum":"0","strip_outer_array":"false","currentTaskConcurrentNum":"1","maxBatchRows":"200000"}
-DataSourceProperties: {"topic":"lilyliuyitest4csv","currentKafkaPartitions":"0","brokerList":"xxx.xx.xx.xxx:9092"}
-    CustomProperties: {"kafka_default_offsets":"OFFSET_BEGINNING","group.id":"example_tbl_ordertest1_b05da08f-9b9d-4fe1-b1f2-25d7116d617c"}
-           Statistic: {"receivedBytes":313,"errorRows":0,"committedTaskNum":1,"loadedRows":6,"loadRowsRate":0,"abortedTaskNum":0,"totalRows":6,"unselectedRows":0,"receivedBytesRate":0,"taskExecuteTimeMs":699}
-            Progress: {"0":"5"}
-   TimestampProgress: {"0":"1686143856061"}
-ReasonOfStateChanged: 
-        ErrorLogUrls: 
-         TrackingSQL: 
-            OtherMsg: 
-LatestSourcePosition: {"0":"6"}
-1 row in set (0.01 sec)
-```
-
-如果导入作业因异常而处于 `PAUSED` 或者 `CANCELLED` 状态，您可以根据返回结果中的 `ReasonOfStateChanged`、`ErrorLogUrls` 、`TrackingSQL` 和 `OtherMsg` 排查具体原因。
-
-```SQL
-MySQL [example_db]> SHOW ROUTINE LOAD FOR example_tbl_ordertest2\G
-*************************** 1. row ***************************
-                  Id: 10204
-                Name: example_tbl_ordertest2
-          CreateTime: 2023-12-22 12:13:18
-           PauseTime: 2023-12-22 12:13:38
-             EndTime: NULL
-              DbName: example_db
-           TableName: example_tbl
-               State: PAUSED
-      DataSourceType: KAFKA
-      CurrentTaskNum: 0
-       JobProperties: {"partitions":"*","rowDelimiter":"\t","partial_update":"false","columnToColumnExpr":"order_id,pay_dt,customer_name,nationality,temp_gender,price","maxBatchIntervalS":"10","partial_update_mode":"null","whereExpr":"*","timezone":"Asia/Shanghai","format":"csv","columnSeparator":"','","log_rejected_record_num":"0","taskTimeoutSecond":"60","json_root":"","maxFilterRatio":"1.0","strict_mode":"false","jsonpaths":"","taskConsumeSecond":"15","desireTaskConcurrentNum":"5","maxErrorNum":"0","strip_outer_array":"false","currentTaskConcurrentNum":"1","maxBatchRows":"200000"}
-DataSourceProperties: {"topic":"mytest","currentKafkaPartitions":"0","brokerList":"xxx.xx.xx.xxx:9092"}
-    CustomProperties: {"kafka_default_offsets":"OFFSET_BEGINNING","group.id":"example_tbl_ordertest2_b3fada0f-6721-4ad1-920d-e4bf6d6ea7f7"}
-           Statistic: {"receivedBytes":541,"errorRows":10,"committedTaskNum":1,"loadedRows":6,"loadRowsRate":0,"abortedTaskNum":0,"totalRows":16,"unselectedRows":0,"receivedBytesRate":0,"taskExecuteTimeMs":646}
-            Progress: {"0":"19"}
-   TimestampProgress: {"0":"1702623900871"}
-ReasonOfStateChanged: ErrorReason{errCode = 102, msg='current error rows is more than max error num'}
-        ErrorLogUrls: http://xxx.xx.xx.xxx:8040/api/_load_error_log?file=error_log_b25dcc7e642344b2_b0b342b9de0567db
-         TrackingSQL: select tracking_log from information_schema.load_tracking_logs where job_id=10204
-            OtherMsg: 
-LatestSourcePosition: {"0":"20"}
-1 row in set (0.00 sec)
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD_TASK.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD_TASK.md
deleted file mode 100644
index 9fe79151e2352c..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_ROUTINE_LOAD_TASK.md
+++ /dev/null
@@ -1,70 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW ROUTINE LOAD TASK
-
-import RoutineLoadPrivNote from '../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
-
-## 功能
-
-查看 Routine Load 导入作业下属导入任务的执行情况。
-
-:::note
-
-- <RoutineLoadPrivNote />
-
-- Routine Load 中导入作业和导入任务的关系，参见[使用 Routine Load 导入数据](../../../loading/RoutineLoad.md#基本原理)。
-
-:::
-
-## 语法
-
-```SQL
-SHOW ROUTINE LOAD TASK
-    [FROM <db_name>]
-    [ WHERE JobName = <job_name> ]
-```
-
-:::note
-
-返回结果中的字段较多，可使用 `\G` 分行，如 `SHOW ROUTINE LOAD TASK WHERE JobName = <job_name> \G`。
-
-:::
-
-## 参数说明
-
-| **参数** | **必选** | **说明**                              |
-| -------- | -------- | ------------------------------------- |
-| db_name  | 否       | Routine Load 导入作业所属数据库名称。 |
-| JobName  | 否       | Routine Load 导入作业名称。           |
-
-## 返回结果说明
-
-| 字段                 | 说明                                                         |
-| -------------------- | ------------------------------------------------------------ |
-| TaskId               | 导入任务的全局唯一 ID，由 StarRocks 自动生成。               |
-| TxnId                | 该导入任务所属事务 ID。                                      |
-| TxnStatus            | 该导入任务所属事务状态。`UNKOWN` 表示事务没有开始，可能是导入任务还没有下发，或者没有实际执行。 |
-| JobId                | 导入作业 ID。                                                |
-| CreateTime           | 该导入任务创建时间。                                         |
-| LastScheduledTime    | 上一次调度该导入任务的时间。                                 |
-| ExecuteStartTime     | 该导入任务执行时间。                                         |
-| Timeout              | 导入任务超时时间，由 FE 参数 [`routine_load_task_timeout_second`](../../../administration/management/FE_configuration.md#routine_load_task_timeout_second) 和 Routine Load 导入作业的 [job_properties](./CREATE_ROUTINE_LOAD.md#job_properties) 中的参数 `task_timeout_second` 控制。 |
-| BeId                 | 执行该导入任务的 BE 节点 ID。                                |
-| DataSourceProperties | 该导入任务消费分区数据的进度。                               |
-| Message              | 导入任务的返回信息，包含任务错误信息。                       |
-
-## 示例
-
-查看 Routine Load  导入作业 `example_tbl_ordertest` 下的所有导入任务。
-
-```SQL
-MySQL [example_db]> SHOW ROUTINE LOAD TASK WHERE JobName = "example_tbl_ordertest";  
-+--------------------------------------+-------+-----------+-------+---------------------+---------------------+------------------+---------+------+------------------------------------+-----------------------------------------------------------------------------+
-| TaskId                               | TxnId | TxnStatus | JobId | CreateTime          | LastScheduledTime   | ExecuteStartTime | Timeout | BeId | DataSourceProperties               | Message                                                                     |
-+--------------------------------------+-------+-----------+-------+---------------------+---------------------+------------------+---------+------+------------------------------------+-----------------------------------------------------------------------------+
-| abde6998-c19a-43d6-b48c-6ca7e14144a3 | -1    | UNKNOWN   | 10208 | 2023-12-22 12:46:10 | 2023-12-22 12:47:00 | NULL             | 60      | -1   | Progress:{"0":6},LatestOffset:null | there is no new data in kafka/pulsar, wait for 10 seconds to schedule again |
-+--------------------------------------+-------+-----------+-------+---------------------+---------------------+------------------+---------+------+------------------------------------+-----------------------------------------------------------------------------+
-1 row in set (0.00 sec)
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_TABLES.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_TABLES.md
deleted file mode 100644
index 2b79f45dcd68e8..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_TABLES.md
+++ /dev/null
@@ -1,87 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW TABLES
-
-## 功能
-
-查看指定数据库下的所有表。可以是 StarRocks 内部表或外部数据源中的表。
-
-> **注意**
->
-> 要查看外部数据源中的表，必须有对应 External Catalog 的 USAGE 权限。
-
-## 语法
-
-```sql
-SHOW TABLES [FROM <catalog_name>.<db_name>]
-```
-
-## 参数说明
-
-| **参数**          | **必选** | **说明**                                                     |
-| ----------------- | -------- | ------------------------------------------------------------ |
-| catalog_name | 否       | Internal catalog 或 External catalog 的名称。<ul><li>如果不指定或指定为 internal catalog 名称（`default_catalog`），则查看当前 StarRocks 集群中的数据库。</li><li>如果指定 external catalog 名称，则查看外部数据源中的数据库。</li></ul> 您可以使用 [SHOW CATALOGS](SHOW_CATALOGS.md) 命令查看当前集群的内外部 catalog。|
-| db_name | 否       | 数据库名称。如果不指定，默认为当前数据库。 |
-
-## 示例
-
-示例一：连接到 StarRocks 集群后，查看 Internal catalog 下数据库 `example_db` 中的表。下面两个语句功能对等。
-
-```plain
-show tables from example_db;
-+----------------------------+
-| Tables_in_example_db       |
-+----------------------------+
-| depts                      |
-| depts_par                  |
-| emps                       |
-| emps2                      |
-+----------------------------+
-
-show tables from default_catalog.example_db;
-+----------------------------+
-| Tables_in_example_db       |
-+----------------------------+
-| depts                      |
-| depts_par                  |
-| emps                       |
-| emps2                      |
-+----------------------------+
-```
-
-示例二：使用 `USE <db_name>;` 连接到 `example_db` 数据库后，查看当前数据库下的表。
-
-```plain
-show tables;
-
-+----------------------------+
-| Tables_in_example_db       |
-+----------------------------+
-| depts                      |
-| depts_par                  |
-| emps                       |
-| emps2                      |
-+----------------------------+
-```
-
-示例三：查看 External catalog `hudi_catalog` 下指定数据库 `hudi_db` 中的表。
-
-```plain
-show tables from hudi_catalog.hudi_db;
-+----------------------------+
-| Tables_in_hudi_db          |
-+----------------------------+
-| hudi_sync_mor              |
-| hudi_table1                |
-+----------------------------+
-```
-
-您也可以通过 `SET CATALOG <catalog_name>;` 切换到 `hudi_catalog` 下，然后执行 `SHOW TABLES FROM hudi_db;` 来查看该数据库下的表。
-
-## 相关文档
-
-- [SHOW CATALOGS](SHOW_CATALOGS.md)：查看当前集群下所有的 Catalog。
-- [SHOW DATABASES](SHOW_DATABASES.md)：查看 Internal Catalog 或 External Catalog 下的所有数据库。
-- [SET CATALOG](../data-definition/SET_CATALOG.md)：切换 Catalog。
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_TABLET.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_TABLET.md
deleted file mode 100644
index bcf503aea4ed97..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_TABLET.md
+++ /dev/null
@@ -1,229 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW TABLET
-
-## 功能
-
-查看 Tablet 相关信息。
-
-> **注意**
->
-> 从 3.0 版本开始，该操作需要 SYSTEM 级 OPERATE 权限，以及对应表的 SELECT 权限。2.5 及之前版本，该操作需要 ADMIN_PRIV 权限。
-
-## 语法
-
-### 查看某张表或某个分区内所有 Tablet 的信息
-
-您也可以指定 WHERE 子句来过滤符合条件的 Tablet。
-
-```sql
-SHOW TABLET
-FROM [<db_name>.]<table_name>
-[PARTITION(<partition_name>, ...]
-[
-WHERE
-    [version = <version_number>] 
-    [[AND] backendid = <backend_id>] 
-    [[AND] STATE = "NORMAL"|"ALTER"|"CLONE"|"DECOMMISSION"]
-]
-[ORDER BY <field_name> [ASC | DESC]]
-[LIMIT [<offset>,]<limit>]
-```
-
-| **参数**       | **必选** | **说明**                                                     |
-| -------------- | -------- | ------------------------------------------------------------ |
-| db_name        | 否       | 数据库名称。如不指定该参数，默认使用当前数据库。                     |
-| table_name     | 是       | 表名。必须指定，否则报错。                                                     |
-| partition_name | 否       | 分区名。                                                     |
-| version_number | 否       | 数据版本号。                                                   |
-| backend_id     | 否       | Tablet 副本所在的 BE 的 ID。                                 |
-| STATE          | 否       | Tablet 副本的状态。<ul><li>`NORMAL`：副本处于正常状态。</li><li>`ALTER`：副本正在做 Rollup 或 schema change。</li><li>`CLONE`：副本处于 clone 状态（未完成 clone 的副本暂不可用）。</li><li>`DECOMMISSION`：副本处于 DECOMMISSION 状态（下线）。</li></ul> |
-| field_name     | 否       | 将返回结果按照指定字段升序或降序排列。`SHOW TABLET FROM <table_name>` 返回的字段都可以作为排序字段。<ul><li>如要升序排列，指定 `ORDER BY field_name ASC`。</li><li>如要降序排列，指定 `ORDER BY field_name DESC`。</li></ul> |
-| offset         | 否       | 返回结果中跳过的 Tablet 的数量，默认值为 0。例如 `OFFSET 5` 表示跳过前 5 个 Tablet，返回剩下的结果。 |
-| limit          | 否       | 查看指定数量的 Tablet。例如 `LIMIT 10` 会显示 10 个 Tablet 的信息。如果不指定该参数，则默认显示所有符合筛选条件的 Tablet。 |
-
-### 查看单个 Tablet 的信息
-
-通过 `SHOW TABLET FROM <table_name>` 获取了所有 Tablet ID 后，您可以只查询某个 Tablet 的详细信息。
-
-```sql
-SHOW TABLET <tablet_id>
-```
-
-| **参数**  | **必选** | **说明**       |
-| --------- | -------- | -------------- |
-| tablet_id | 是       | Tablet 的 ID |
-
-## 返回结果说明
-
-### 查看某张表或分区内的所有 tablet
-
-```plain
-+----------+-----------+-----------+------------+---------+-------------+-------------------+-----------------------+------------------+----------------------+---------------+----------+----------+--------+-------------------------+--------------+------------------+--------------+----------+----------+-------------------+
-| TabletId | ReplicaId | BackendId | SchemaHash | Version | VersionHash | LstSuccessVersion | LstSuccessVersionHash | LstFailedVersion | LstFailedVersionHash | LstFailedTime | DataSize | RowCount | State  | LstConsistencyCheckTime | CheckVersion | CheckVersionHash | VersionCount | PathHash | MetaUrl  | CompactionStatus  |
-+----------+-----------+-----------+------------+---------+-------------+-------------------+-----------------------+------------------+----------------------+---------------+----------+----------+--------+-------------------------+--------------+------------------+--------------+----------+----------+-------------------+
-```
-
-| **字段**                | **说明**                        |
-| ----------------------- | ------------------------------- |
-| TabletId                | Table 的 ID。                   |
-| ReplicaId               | 副本 ID。                      |
-| BackendId               | 副本所在的 BE 的 ID。           |
-| SchemaHash              | Schema hash（随机生成）。        |
-| Version                 | 数据版本号。                      |
-| VersionHash             | 数据版本号的 hash。               |
-| LstSuccessVersion       | 最后一次 load 成功的版本。        |
-| LstSuccessVersionHash   | 最后一次 load 成功的版本的 hash。 |
-| LstFailedVersion        | 最后一次 load 失败的版本。`-1` 表示不存在失败的版本。 |
-| LstFailedVersionHash    | 最后一次 load 失败的版本的 hash。 |
-| LstFailedTime           | 最后一次 load 失败的时间。`NULL` 表示没有失败。        |
-| DataSize                | 该 Tablet 上的数据大小。             |
-| RowCount                | 该 Tablet 上的数据行数。             |
-| State                   | Tablet 的副本状态。              |
-| LstConsistencyCheckTime | 最后一次一致性检查的时间。`NULL` 表示没有进行一致性检查.  |
-| CheckVersion            | 一致性检查的版本。`-1` 表示不存在检查版本。    |
-| CheckVersionHash        | 一致性检查的版本的 hash。         |
-| VersionCount            | 数据版本数。                      |
-| PathHash                | Tablet 存储目录的 hash。        |
-| MetaUrl                 | 通过 URL 查询更多的 meta 信息。     |
-| CompactionStatus        | 通过 URL 查询 Compaction 状态。    |
-
-### 查看单个 tablet
-
-```Plain
-+--------+-----------+---------------+-----------+------+---------+-------------+---------+--------+-----------+
-| DbName | TableName | PartitionName | IndexName | DbId | TableId | PartitionId | IndexId | IsSync | DetailCmd |
-+--------+-----------+---------------+-----------+------+---------+-------------+---------+--------+-----------+
-```
-
-| **字段**      | **说明**                                                     |
-| ------------- | ------------------------------------------------------------ |
-| DbName        | Tablet 所属数据库的名称。                                    |
-| TableName     | Tablet 所属表的名称。                                        |
-| PartitionName | Tablet 所属分区的名称。                                      |
-| IndexName     | 索引名称。                                                     |
-| DbId          | 数据库 ID。                                                  |
-| TableId       | 表 ID。                                                      |
-| PartitionId   | 分区 ID。                                                    |
-| IndexId       | 索引 ID。                                                      |
-| IsSync        | 检查 Tablet 上的数据是否与表 meta 里的数据一致。`false` 表示检查项数据有缺失。`true` 表示检查项数据正常，即代表 Tablet 正常。 |
-| DetailCmd     | 通过 URL 查询更多信息。                                      |
-
-## 示例
-
-在数据库 `example_db` 下创建表 `test_show_tablet`。
-
-```sql
-CREATE TABLE `test_show_tablet` (
-  `k1` date NULL COMMENT "",
-  `k2` datetime NULL COMMENT "",
-  `k3` char(20) NULL COMMENT "",
-  `k4` varchar(20) NULL COMMENT "",
-  `k5` boolean NULL COMMENT "",
-  `k6` tinyint(4) NULL COMMENT "",
-  `k7` smallint(6) NULL COMMENT "",
-  `k8` int(11) NULL COMMENT "",
-  `k9` bigint(20) NULL COMMENT "",
-  `k10` largeint(40) NULL COMMENT "",
-  `k11` float NULL COMMENT "",
-  `k12` double NULL COMMENT "",
-  `k13` decimal128(27, 9) NULL COMMENT ""
-) ENGINE=OLAP 
-DUPLICATE KEY(`k1`, `k2`, `k3`, `k4`, `k5`)
-COMMENT "OLAP"
-PARTITION BY RANGE(`k1`)
-(PARTITION p20210101 VALUES [("2021-01-01"), ("2021-01-02")),
-PARTITION p20210102 VALUES [("2021-01-02"), ("2021-01-03")),
-PARTITION p20210103 VALUES [("2021-01-03"), ("2021-01-04")),
-PARTITION p20210104 VALUES [("2021-01-04"), ("2021-01-05")),
-PARTITION p20210105 VALUES [("2021-01-05"), ("2021-01-06")),
-PARTITION p20210106 VALUES [("2021-01-06"), ("2021-01-07")),
-PARTITION p20210107 VALUES [("2021-01-07"), ("2021-01-08")),
-PARTITION p20210108 VALUES [("2021-01-08"), ("2021-01-09")),
-PARTITION p20210109 VALUES [("2021-01-09"), ("2021-01-10")))
-DISTRIBUTED BY HASH(`k1`, `k2`, `k3`);
-```
-
-- 查看指定数据库下指定表的所有 Tablet 信息。以下示例仅截取其中一行 tablet 信息来说明。
-
-    ```plain
-    mysql> show tablet from example_db.test_show_tablet\G
-    *************************** 1. row ***************************
-               TabletId: 9588955
-              ReplicaId: 9588956
-              BackendId: 10004
-             SchemaHash: 0
-                Version: 1
-            VersionHash: 0
-      LstSuccessVersion: 1
-  LstSuccessVersionHash: 0
-       LstFailedVersion: -1
-   LstFailedVersionHash: 0
-          LstFailedTime: NULL
-               DataSize: 0B
-               RowCount: 0
-                  State: NORMAL
-  LstConsistencyCheckTime: NULL
-           CheckVersion: -1
-       CheckVersionHash: 0
-           VersionCount: 1
-               PathHash: 0
-                MetaUrl: http://172.26.92.141:8038/api/meta/header/9588955
-       CompactionStatus: http://172.26.92.141:8038/api/compaction/show?tablet_id=9588955
-    ```
-
-- 查看 id 为 9588955 的 Tablet 的信息。
-
-    ```plain
-    mysql> show tablet 9588955\G
-    *************************** 1. row ***************************
-       DbName: example_db
-    TableName: test_show_tablet
-    PartitionName: p20210103
-    IndexName: test_show_tablet
-         DbId: 11145
-      TableId: 9588953
-  PartitionId: 9588946
-      IndexId: 9588954
-       IsSync: true
-    DetailCmd: SHOW PROC '/dbs/11145/9588953/partitions/9588946/9588954/9588955';
-    ```
-
-- 查看表中分区 `p20210103` 的 Tablet 信息。
-
-    ```sql
-        SHOW TABLET FROM test_show_tablet partition(p20210103);
-    ```
-
-- 返回表中 10 个 Tablet 的信息。
-
-    ```sql
-        SHOW TABLET FROM test_show_tablet limit 10;
-    ```
-
-- 从偏移位置 5 开始获取 10 个 Tablet 的信息。
-
-    ```sql
-        SHOW TABLET FROM test_show_tablet limit 5,10;
-    ```
-
-- 按照 `backendid`，`version`，`state` 字段进行过滤。
-
-    ```sql
-        SHOW TABLET FROM test_show_tablet
-        WHERE backendid = 10004 and version = 1 and state = "NORMAL";
-    ```
-
-- 按照 `version` 字段进行排序。
-
-    ```sql
-        SHOW TABLET FROM table_name where backendid = 10004 order by version;
-    ```
-
-- 查看 index 名为 `test_show_tablet` 的 Tablet 的信息。
-
-    ```sql
-        SHOW TABLET FROM test_show_tablet where indexname = "test_show_tablet";
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_TRANSACTION.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_TRANSACTION.md
deleted file mode 100644
index d2cabd01185afc..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SHOW_TRANSACTION.md
+++ /dev/null
@@ -1,65 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW TRANSACTION
-
-## 功能
-
-该语法用于查看指定 transaction id 的事务详情。
-
-## 语法
-
-```sql
-SHOW TRANSACTION
-[FROM <db_name>]
-WHERE id = <transaction_id>
-```
-
-返回结果示例：
-
-```plain text
-TransactionId: 4005
-Label: insert_8d807d5d-bcdd-46eb-be6d-3fa87aa4952d
-Coordinator: FE: 10.74.167.16
-TransactionStatus: VISIBLE
-LoadJobSourceType: INSERT_STREAMING
-PrepareTime: 2020-01-09 14:59:07
-CommitTime: 2020-01-09 14:59:09
-FinishTime: 2020-01-09 14:59:09
-Reason:
-ErrorReplicasCount: 0
-ListenerId: -1
-TimeoutMs: 300000
-```
-
-* TransactionId：事务 id
-* Label：导入任务对应的 label
-* Coordinator：负责事务协调的节点
-* TransactionStatus：事务状态
-* PREPARE：准备阶段
-* COMMITTED：事务成功，但数据不可见
-* VISIBLE：事务成功且数据可见
-* ABORTED：事务失败
-* LoadJobSourceType：导入任务的类型
-* PrepareTime：事务开始时间
-* CommitTime：事务提交成功的时间
-* FinishTime：数据可见的时间
-* Reason：错误信息
-* ErrorReplicasCount：有错误的副本数
-* ListenerId：相关的导入作业的 id
-* TimeoutMs：事务超时时间，单位毫秒
-
-## 示例
-
-1. 查看 id 为 4005 的事务：
-
-    ```sql
-    SHOW TRANSACTION WHERE ID=4005;
-    ```
-
-2. 指定 db 中，查看 id 为 4005 的事务：
-
-    ```sql
-    SHOW TRANSACTION FROM db WHERE ID=4005;
-    ```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md
deleted file mode 100644
index c5c08d120e8db3..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SPARK_LOAD.md
+++ /dev/null
@@ -1,293 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SPARK LOAD
-
-## 功能
-
-Spark load 通过外部的 Spark 资源实现对导入数据的预处理，提高 StarRocks 大数据量的导入性能并且节省 StarRocks 集群的计算资源。主要用于初次迁移，大数据量导入 StarRocks 的场景。
-
-Spark load 是一种异步导入方式，用户需要通过 MySQL 协议创建 Spark 类型导入任务，并通过 `SHOW LOAD` 查看导入结果。
-
-> **注意**
->
-> - Spark Load 操作需要目标表的 INSERT 权限。如果您的用户账号没有 INSERT 权限，请参考 [GRANT](../account-management/GRANT.md) 给用户赋权。
-> - 使用 Spark Load 导入数据至 StarRocks 表时，不支持该表分桶列的数据类型为 DATE、DATETIME 或者 DECIMAL。
-
-## 语法
-
-```sql
-LOAD LABEL load_label
-(
-data_desc1[, data_desc2, ...]
-)
-WITH RESOURCE resource_name
-[resource_properties]
-[opt_properties]
-```
-
-1.load_label
-
-当前导入批次的标签。在一个 database 内唯一。
-
-语法：
-
-```sql
-[database_name.]your_label
-```
-
-2.data_desc
-
-用于描述一批导入数据。
-
-语法：
-
-```sql
-DATA INFILE
-(
-"file_path1"[, file_path2, ...]
-)
-[NEGATIVE]
-INTO TABLE `table_name`
-[PARTITION (p1, p2)]
-[COLUMNS TERMINATED BY "column_separator"]
-[FORMAT AS "file_type"]
-[(column_list)]
-[COLUMNS FROM PATH AS (col2, ...)]
-[SET (k1 = func(k2))]
-[WHERE predicate]
-
-DATA FROM TABLE hive_external_tbl
-[NEGATIVE]
-INTO TABLE tbl_name
-[PARTITION (p1, p2)]
-[SET (k1=f1(xx), k2=f2(xx))]
-[WHERE predicate]
-```
-
-说明：
-
-```plain text
-file_path:
-
-文件路径，可以指定到一个文件，也可以用 * 通配符指定某个目录下的所有文件。通配符必须匹配到文件，而不能是目录。
-
-hive_external_tbl:
-
-hive 外部表名。
-要求导入的 starrocks 表中的列必须在 hive 外部表中存在。
-每个导入任务只支持从一个 hive 外部表导入。
-不能与 file_path 方式同时使用。
-
-PARTITION:
-
-如果指定此参数，则只会导入指定的分区，导入分区以外的数据会被过滤掉。
-如果不指定，默认导入table的所有分区。
-
-NEGATIVE：
-
-如果指定此参数，则相当于导入一批“负”数据。用于抵消之前导入的同一批数据。
-该参数仅适用于存在 value 列，并且 value 列的聚合类型仅为 SUM 的情况。
-
-column_separator：
-
-用于指定导入文件中的列分隔符。默认为：\t。
-如果是不可见字符，则需要加 \\x 作为前缀，使用十六进制来表示分隔符。
-如 hive 文件的分隔符 \x01，指定为 "\\x01"。
-
-file_type：
-
-用于指定导入文件的类型，目前仅支持csv、orc、parquet。
-
-column_list：
-
-用于指定导入文件中的列和 table 中的列的对应关系。
-当需要跳过导入文件中的某一列时，将该列指定为 table 中不存在的列名即可。
-
-语法：
-(col_name1, col_name2, ...)
-
-SET:
-
-如果指定此参数，可以将源文件某一列按照函数进行转化，然后将转化后的结果导入到 table 中。语法为 `column_name` = expression。
-仅支持 Spark SQL built-in functions，具体可参考 https://spark.apache.org/docs/2.4.6/api/sql/index.html。
-举几个例子帮助理解。
-例1: 表中有3个列“c1, c2, c3", 源文件中前两列依次对应(c1,c2)，后两列之和对应c3；那么需要指定 columns (c1,c2,tmp_c3,tmp_c4) SET (c3=tmp_c3+tmp_c4);
-例2: 表中有3个列“year, month, day"，源文件中只有一个时间列，为”2018-06-01 01:02:03“格式。
-那么可以指定 columns(tmp_time) set (year = year(tmp_time), month=month(tmp_time), day=day(tmp_time)) 完成导入。
-
-WHERE:
-
-对做完 transform 的数据进行过滤，符合 where 条件的数据才能被导入。WHERE 语句中只可引用表中列名。
-```
-
-3.resource_name
-
-所使用的 Spark 资源名称，可以通过 `SHOW RESOURCES` 命令查看。
-
-4.resource_properties
-
-[Spark 资源的配置](../data-definition/CREATE_RESOURCE.md#spark-资源)。当用户有临时性的需求，比如增加任务使用的资源而修改 Spark 和 HDFS 配置，可以在这里设置，设置仅对本次任务生效，并不影响 StarRocks 集群中已有的配置。
-
-5.opt_properties
-
-用于指定一些特殊参数。
-
-语法：
-
-```sql
-[PROPERTIES ("key"="value", ...)]
-```
-
-可以指定如下参数：
-
-```plain text
-timeout：         指定导入操作的超时时间。默认超时为 4 小时。单位秒。
-max_filter_ratio：最大容忍可过滤（数据不规范等原因）的数据比例。默认零容忍。
-strict_mode：     是否对数据进行严格限制。默认为 false。
-timezone:         指定某些受时区影响的函数的时区，如 strftime/alignment_timestamp/from_unixtime 等等，具体请查阅 [时区](../../../administration/management/timezone.md) 文档。如果不指定，则使用 "Asia/Shanghai" 时区。
-```
-
-6.导入数据格式样例
-
-```plain text
-1.整型类（TINYINT/SMALLINT/INT/BIGINT/LARGEINT）：1, 1000, 1234。
-
-2.浮点类（FLOAT/DOUBLE/DECIMAL）：1.1, 0.23, .356。
-
-3.日期类（DATE/DATETIME）：2017-10-03, 2017-06-13 12: 34: 03。（注：如果是其他日期格式，可以在导入命令中，使用 strftime 或者 time_format 函数进行转换）
-
-4.字符串类（CHAR/VARCHAR）："I am a student", "a"。
-NULL 值：\N
-```
-
-## 示例
-
-### 从HDFS导入数据
-
-从 HDFS 导入一批数据，指定超时时间和过滤比例。使用名为 my_spark 的 spark 资源。
-
-```sql
-LOAD LABEL example_db.label1
-(
-DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/file")
-INTO TABLE `my_table`
-)
-WITH RESOURCE 'my_spark'
-PROPERTIES
-(
-    "timeout" = "3600",
-    "max_filter_ratio" = "0.1"
-);
-```
-
-其中 hdfs_host 为 namenode 的 host，hdfs_port 为 fs.defaultFS 端口（默认 9000）。
-
-### 从HDFS导入"负"数据
-
-从 HDFS 导入一批 "负" 数据，指定分隔符为逗号，使用通配符*指定目录下的所有文件，并指定 spark 资源的临时参数。"负" 数据详细含义见上文语法参数介绍部分。
-
-```sql
-LOAD LABEL example_db.label3
-(
-DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/*")
-NEGATIVE
-INTO TABLE `my_table`
-COLUMNS TERMINATED BY ","
-)
-WITH RESOURCE 'my_spark'
-(
-    "spark.executor.memory" = "3g",
-    "broker.username" = "hdfs_user",
-    "broker.password" = "hdfs_passwd"
-);
-```
-
-### 从HDFS导入数据到指定分区并进行列转换
-
-从 HDFS 导入一批数据，指定分区，并对导入文件的列做一些转化，如下：
-
-```plain text
-表结构为：
-k1 varchar(20)
-k2 int
-
-假设数据文件只有一行数据：
-
-Adele,1,1
-
-数据文件中各列，对应导入语句中指定的各列：
-k1,tmp_k2,tmp_k3
-
-转换如下：
-
-1. k1: 不变换
-2. k2：是 tmp_k2 和 tmp_k3 数据之和
-
-LOAD LABEL example_db.label6
-(
-DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/file")
-INTO TABLE `my_table`
-PARTITION (p1, p2)
-COLUMNS TERMINATED BY ","
-(k1, tmp_k2, tmp_k3)
-SET (
-k2 = tmp_k2 + tmp_k3
-)
-)
-WITH RESOURCE 'my_spark';
-```
-
-### 提取文件路径中的分区字段
-
-如果需要，则会根据表中定义的字段类型解析文件路径中的分区字段（partitioned fields），类似 Spark 中 Partition Discovery 的功能。
-
-```sql
-LOAD LABEL example_db.label10
-(
-DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/dir/city=beijing/*/*")
-INTO TABLE `my_table`
-(k1, k2, k3)
-COLUMNS FROM PATH AS (city, utc_date)
-SET (uniq_id = md5sum(k1, city))
-)
-WITH RESOURCE 'my_spark';
-```
-
-`hdfs://hdfs_host: hdfs_port/user/starRocks/data/input/dir/city = beijing` 目录下包括如下文件：
-
-`[hdfs://hdfs_host: hdfs_port/user/starRocks/data/input/dir/city = beijing/utc_date = 2019-06-26/0000.csv, hdfs://hdfs_host: hdfs_port/user/starRocks/data/input/dir/city = beijing/utc_date = 2019-06-26/0001.csv, ...]`
-
-则提取文件路径的中的 `city` 和 `utc_date` 字段。
-
-### 对导入数据进行过滤
-
-对待导入数据进行过滤，k1 值大于 10 的列才能被导入。
-
-```sql
-LOAD LABEL example_db.label10
-(
-DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/file")
-INTO TABLE `my_table`
-WHERE k1 > 10
-)
-WITH RESOURCE 'my_spark';
-```
-
-### 从 Hive 外表导入并构建全局字典
-
-从 hive 外部表导入，并将源表中的 uuid 列通过全局字典转化为 bitmap 类型。
-
-```sql
-LOAD LABEL db1.label1
-(
-DATA FROM TABLE hive_t1
-INTO TABLE tbl1
-SET
-(
-uuid=bitmap_dict(uuid)
-)
-)
-WITH RESOURCE 'my_spark';
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/STOP_ROUTINE_LOAD.md b/docs/zh/sql-reference/sql-statements/data-manipulation/STOP_ROUTINE_LOAD.md
deleted file mode 100644
index e47dc1665652d0..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/STOP_ROUTINE_LOAD.md
+++ /dev/null
@@ -1,42 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# STOP ROUTINE LOAD
-
-import RoutineLoadPrivNote from '../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
-
-## 功能
-
-停止 Routine Load 导入作业。
-
-<RoutineLoadPrivNote />
-
-::: warning
-
-导入作业停止且无法恢复。因此请谨慎执行该语句。
-
-如果仅仅需要暂停导入作业，则可以执行 [PAUSE ROUTINE LOAD](./PAUSE_ROUTINE_LOAD.md)。
-
-:::
-
-## 语法
-
-```SQL
-STOP ROUTINE LOAD FOR [db_name.]<job_name>
-```
-
-## 参数说明
-
-| 参数名称 | 是否必填 | 说明                        |
-| -------- | -------- | --------------------------- |
-| db_name  |          | Routine Load 导入作业所属数据库名称。         |
-| job_name | ✅        | Routine Load 导入作业名称。 |
-
-## 示例
-
-停止 `example_db` 数据库中名称为 `example_tbl1_ordertest1` 的 Routine Load 导入作业。
-
-```SQL
-STOP ROUTINE LOAD FOR example_db.example_tbl1_ordertest1;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md b/docs/zh/sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md
deleted file mode 100644
index 9e4a74793675d2..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md
+++ /dev/null
@@ -1,570 +0,0 @@
----
-displayed_sidebar: "Chinese"
-toc_max_heading_level: 4
----
-
-# STREAM LOAD
-
-## 功能
-
-Stream Load 是一种基于 HTTP 协议的同步导入方式，支持将本地文件或数据流导入到 StarRocks 中。您提交导入作业以后，StarRocks 会同步地执行导入作业，并返回导入作业的结果信息。您可以通过返回的结果信息来判断导入作业是否成功。有关 Stream Load 的应用场景、使用限制、基本原理、以及支持的数据文件格式等信息，请参见[使用 Stream Load 从本地导入](../../../loading/StreamLoad.md#使用-stream-load-从本地导入)。
-
-从 3.2.7 版本起，STREAM LOAD 支持在传输过程中对 JSON 数据进行压缩，减少网络带宽开销。用户可以通过 `compression` 或 `Content-Encoding` 参数指定不同的压缩方式，支持 GZIP、BZIP2、LZ4_FRAME、ZSTD 压缩算法。参见[相关语法](#data_desc)。
-
-> **注意**
->
-> - Stream Load 操作会同时更新和 StarRocks 原始表相关的物化视图的数据。
-> - Stream Load 操作需要目标表的 INSERT 权限。如果您的用户账号没有 INSERT 权限，请参考 [GRANT](../account-management/GRANT.md) 给用户赋权。
-
-## 语法
-
-```Bash
-curl --location-trusted -u <username>:<password> -XPUT <url>
-(
-    data_desc
-)
-[opt_properties]        
-```
-
-本文以 curl 工具为例介绍如何使用 Stream Load 导入数据。除了使用 curl 工具，您还可以通过其他支持 HTTP 协议的工具或语言提交导入作业以导入数据。导入相关的参数位于 HTTP 请求的请求头。传入这些导入相关的参数时，需要注意以下几点：
-
-- 推荐使用**分块上传**方式，如本文示例所示。如果使用**非分块上传**方式，则必须使用请求头字段 `Content-Length` 来标示待上传内容的长度，从而保证数据完整性。
-
-  > **说明**
-  >
-  > 使用 curl 工具提交导入作业的时候，会自动添加 `Content-Length` 字段，因此无需手动指定 `Content-Length`。
-
-- 必须在 HTTP 请求的请求头字段 `Expect` 中指定 `100-continue`，即 `"Expect:100-continue"`。这样在服务器拒绝导入作业请求的情况下，可以避免不必要的数据传输，从而减少不必要的资源开销。
-
-注意在 StarRocks 中，部分文字是 SQL 语言的保留关键字，不能直接用于 SQL 语句。如果想在 SQL 语句中使用这些保留关键字，必须用反引号 (`) 包裹起来。参见[关键字](../../../sql-reference/sql-statements/keywords.md)。
-
-## 参数说明
-
-### username 和 password
-
-用于指定 StarRocks 集群账号的用户名和密码。必选参数。如果账号没有设置密码，这里只需要传入 `<username>:`。
-
-### XPUT
-
-用于指定 HTTP 请求方法。必选参数。Stream Load 当前只支持 PUT 方法。
-
-### url
-
-用于指定 StarRocks 表的 URL 地址。必选参数。语法如下：
-
-```Plain
-http://<fe_host>:<fe_http_port>/api/<database_name>/<table_name>/_stream_load
-```
-
-`url` 中的参数如下表所述。
-
-| 参数名称      | 是否必须 | 参数说明                                                     |
-| ------------- | -------- | ------------------------------------------------------------ |
-| fe_host       | 是       | 指定 StarRocks 集群中 FE 的 IP 地址。 <br />**说明**<br />如果您直接提交导入作业给某一个 BE（或 CN）节点，则需要传入该 BE（或 CN）的 IP 地址。 |
-| fe_http_port  | 是       | 指定 StarRocks 集群中 FE 的 HTTP 端口号。 默认端口号为 8030。 <br />**说明**<br />如果您直接提交导入作业给某一指定的 BE（或 CN）节点，则需要传入该 BE（或 CN）的 HTTP 端口号。默认端口号为 8040。 |
-| database_name | 是       | 指定目标 StarRocks 表所在的数据库的名称。                    |
-| table_name    | 是       | 指定目标 StarRocks 表的名称。                                |
-
-> **说明**
->
-> 您可以通过 [SHOW FRONTENDS](../Administration/SHOW_FRONTENDS.md) 命令查看 FE 节点的 IP 地址和 HTTP 端口号。
-
-### data_desc
-
-用于描述源数据文件，包括源数据文件的名称、格式、列分隔符、行分隔符、目标分区、以及与 StarRocks 表之间的列对应关系等。语法如下：
-
-```Bash
--T <file_path>
--H "format: CSV | JSON"
--H "column_separator: <column_separator>"
--H "row_delimiter: <row_delimiter>"
--H "columns: <column1_name>[, <column2_name>，... ]"
--H "partitions: <partition1_name>[, <partition2_name>, ...]"
--H "temporary_partitions: <temporary_partition1_name>[, <temporary_partition2_name>, ...]"
--H "jsonpaths: [ \"<json_path1>\"[, \"<json_path2>\", ...] ]"
--H "strip_outer_array: true | false"
--H "json_root: <json_path>"
--H "ignore_json_size: true | false"
--H "compression: <compression_algorithm> | Content-Encoding: <compression_algorithm>"
-```
-
-`data_desc` 中的参数可以分为三类：公共参数、CSV 适用的参数、以及 JSON 适用的参数。
-
-#### 公共参数
-
-| **参数名称** | **是否必选** | **参数说明**                                                 |
-| ------------ | ------------ | ------------------------------------------------------------ |
-| file_path    | 是           | 指定源数据文件的保存路径。文件名里可选包含或者不包含扩展名。 |
-| format       | 否           | 指定待导入数据的格式。取值包括 `CSV` 和 `JSON`。默认值：`CSV`。 |
-| partitions   | 否           | 指定要把数据导入哪些分区。如果不指定该参数，则默认导入到 StarRocks 表所在的所有分区中。 |
-| temporary_partitions | 否           | 指定要把数据导入哪些[临时分区](../../../table_design/Temporary_partition.md)。|
-| columns      | 否           | 指定源数据文件和 StarRocks 表之间的列对应关系。如果源数据文件中的列与 StarRocks 表中的列按顺序一一对应，则不需要指定 `columns` 参数。您可以通过 `columns` 参数实现数据转换。例如，要导入一个 CSV 格式的数据文件，文件中有两列，分别可以对应到目标 StarRocks 表的 `id` 和 `city` 两列。如果要实现把数据文件中第一列的数据乘以 100 以后再落入 StarRocks 表的转换，可以指定 `"columns: city,tmp_id, id = tmp_id * 100"`。具体请参见本文“[列映射](#列映射)”章节。 |
-
-#### CSV 适用参数
-
-| **参数名称**     | **是否必选** | **参数说明**                                                 |
-| ---------------- | ------------ | ------------------------------------------------------------ |
-| column_separator | 否           | 用于指定源数据文件中的列分隔符。如果不指定该参数，则默认为 `\t`，即 Tab。必须确保这里指定的列分隔符与源数据文件中的列分隔符一致。<br />**说明**<br />StarRocks 支持设置长度最大不超过 50 个字节的 UTF-8 编码字符串作为列分隔符，包括常见的逗号 (,)、Tab 和 Pipe (\|)。 |
-| row_delimiter    | 否           | 用于指定源数据文件中的行分隔符。如果不指定该参数，则默认为 `\n`。 |
-| skip_header      | 否           | 用于指定跳过 CSV 文件最开头的几行数据。取值类型：INTEGER。默认值：`0`。<br />在某些 CSV 文件里，最开头的几行数据会用来定义列名、列类型等元数据信息。通过设置该参数，可以使 StarRocks 在导入数据时忽略 CSV 文件的前面几行。例如，如果设置该参数为 `1`，则 StarRocks 会在导入数据时忽略 CSV 文件的第一行。<br />这里的行所使用的分隔符须与您在导入命令中所设定的行分隔符一致。 |
-| trim_space       | 否           | 用于指定是否去除 CSV 文件中列分隔符前后的空格。取值类型：BOOLEAN。默认值：`false`。<br />有些数据库在导出数据为 CSV 文件时，会在列分隔符的前后添加一些空格。根据位置的不同，这些空格可以称为“前导空格”或者“尾随空格”。通过设置该参数，可以使 StarRocks 在导入数据时删除这些不必要的空格。<br />需要注意的是，StarRocks 不会去除被 `enclose` 指定字符括起来的字段内的空格（包括字段的前导空格和尾随空格）。例如，列分隔符是竖线 (<code class="language-text">&#124;</code>)，`enclose` 指定的字符是双引号 (`"`)：<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124; "Love StarRocks" &#124;</code> <br />如果设置 `trim_space` 为 `true`，则 StarRocks 处理后的结果数据如下：<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> |
-| enclose          | 否           | 根据 [RFC4180](https://www.rfc-editor.org/rfc/rfc4180)，用于指定把 CSV 文件中的字段括起来的字符。取值类型：单字节字符。默认值：`NONE`。最常用 `enclose` 字符为单引号 (`'`) 或双引号 (`"`)。<br />被 `enclose` 指定字符括起来的字段内的所有特殊字符（包括行分隔符、列分隔符等）均看做是普通符号。比 RFC4180 标准更进一步的是，StarRocks 提供的 `enclose` 属性支持设置任意单个字节的字符。<br />如果一个字段内包含了 `enclose` 指定字符，则可以使用同样的字符对 `enclose` 指定字符进行转义。例如，在设置了`enclose` 为双引号 (`"`) 时，字段值 `a "quoted" c` 在 CSV 文件中应该写作 `"a ""quoted"" c"`。 |
-| escape           | 否           | 指定用于转义的字符。用来转义各种特殊字符，比如行分隔符、列分隔符、转义符、`enclose` 指定字符等，使 StarRocks 把这些特殊字符当做普通字符而解析成字段值的一部分。取值类型：单字节字符。默认值：`NONE`。最常用的 `escape` 字符为斜杠 (`\`)，在 SQL 语句中应该写作双斜杠 (`\\`)。<br />**说明**<br />`escape` 指定字符同时作用于 `enclose` 指定字符的内部和外部。<br />以下为两个示例：<ul><li>当设置 `enclose` 为双引号 (`"`) 、`escape` 为斜杠 (`\`) 时，StarRocks 会把 `"say \"Hello world\""` 解析成一个字段值 `say "Hello world"`。</li><li>假设列分隔符为逗号 (`,`) ，当设置 `escape` 为斜杠 (`\`) ，StarRocks 会把 `a, b\, c` 解析成 `a` 和 `b, c` 两个字段值。</li></ul> |
-
-> **说明**
->
-> 对于 CSV 格式的数据，需要注意以下两点：
->
-> - StarRocks 支持设置长度最大不超过 50 个字节的 UTF-8 编码字符串作为列分隔符，包括常见的逗号 (,)、Tab 和 Pipe (|)。
-> - 空值 (null) 用 `\N` 表示。比如，数据文件一共有三列，其中某行数据的第一列、第三列数据分别为 `a` 和 `b`，第二列没有数据，则第二列需要用 `\N` 来表示空值，写作 `a,\N,b`，而不是 `a,,b`。`a,,b` 表示第二列是一个空字符串。
-> - `skip_header`、`trim_space`、`enclose` 和 `escape` 等属性在 3.0 及以后版本支持。
-
-#### JSON 适用参数
-
-| **参数名称**      | **是否必选** | **参数说明**                                                 |
-| ----------------- | ------------ | ------------------------------------------------------------ |
-| jsonpaths         | 否           | 用于指定待导入的字段的名称。仅在使用匹配模式导入 JSON 数据时需要指定该参数。参数取值为 JSON 格式。参见[导入 JSON 数据时配置列映射关系](#导入-json-数据时配置列映射关系)。    |
-| strip_outer_array | 否           | 用于指定是否裁剪最外层的数组结构。取值范围：`true` 和 `false`。默认值：`false`。真实业务场景中，待导入的 JSON 数据可能在最外层有一对表示数组结构的中括号 `[]`。这种情况下，一般建议您指定该参数取值为 `true`，这样 StarRocks 会剪裁掉外层的中括号 `[]`，并把中括号 `[]` 里的每个内层数组都作为一行单独的数据导入。如果您指定该参数取值为 `false`，则 StarRocks 会把整个 JSON 数据文件解析成一个数组，并作为一行数据导入。例如，待导入的 JSON 数据为 `[ {"category" : 1, "author" : 2}, {"category" : 3, "author" : 4} ]`，如果指定该参数取值为 `true`，则 StarRocks 会把 `{"category" : 1, "author" : 2}` 和 `{"category" : 3, "author" : 4}` 解析成两行数据，并导入到目标 StarRocks 表中对应的数据行。 |
-| json_root         | 否           | 用于指定待导入 JSON 数据的根元素。仅在使用匹配模式导入 JSON 数据时需要指定该参数。参数取值为合法的 JsonPath 字符串。默认值为空，表示会导入整个 JSON 数据文件的数据。具体请参见本文提供的示例“[导入数据并指定 JSON 根节点](#指定-json-根节点使用匹配模式导入数据)”。 |
-| ignore_json_size | 否   | 用于指定是否检查 HTTP 请求中 JSON Body 的大小。<br />**说明**<br />HTTP 请求中 JSON Body 的大小默认不能超过 100 MB。如果 JSON Body 的大小超过 100 MB，会提示 "The size of this batch exceed the max size [104857600] of json type data data [8617627793]. Set ignore_json_size to skip check, although it may lead huge memory consuming." 错误。为避免该报错，可以在 HTTP 请求头中添加 `"ignore_json_size:true"` 设置，忽略对 JSON Body 大小的检查。 |
-| compression, Content-Encoding | 否 | 指定在 STREAM LOAD 数据传输过程中使用哪种压缩算法，支持 GZIP、BZIP2、LZ4_FRAME、ZSTD 算法。示例：`curl --location-trusted -u root:  -v 'http://127.0.0.1:18030/api/db0/tbl_simple/_stream_load' \-X PUT  -H "expect:100-continue" \-H 'format: json' -H 'compression: lz4_frame'   -T ./b.json.lz4`。 |
-
-另外，导入 JSON 格式的数据时，需要注意单个 JSON 对象的大小不能超过 4 GB。如果 JSON 文件中单个 JSON 对象的大小超过 4 GB，会提示 "This parser can't support a document that big." 错误。
-
-### opt_properties
-
-用于指定一些导入相关的可选参数。指定的参数设置作用于整个导入作业。语法如下：
-
-```Bash
--H "label: <label_name>"
--H "where: <condition1>[, <condition2>, ...]"
--H "max_filter_ratio: <num>"
--H "timeout: <num>"
--H "strict_mode: true | false"
--H "timezone: <string>"
--H "load_mem_limit: <num>"
--H "partial_update: true | false"
--H "partial_update_mode: row | column"
--H "merge_condition: <column_name>"
-```
-
-参数说明如下表所述。
-
-| **参数名称**     | **是否必选** | **参数说明**                                                 |
-| ---------------- | ------------ | ------------------------------------------------------------ |
-| label            | 否           | 用于指定导入作业的标签。如果您不指定标签，StarRocks 会自动为导入作业生成一个标签。相同标签的数据无法多次成功导入，这样可以避免一份数据重复导入。有关标签的命名规范，请参见[系统限制](../../../reference/System_limit.md)。StarRocks 默认保留最近 3 天内成功的导入作业的标签。您可以通过 [FE 配置参数](../../../administration/management/FE_configuration.md#导入导出) `label_keep_max_second` 设置默认保留时长。 |
-| where            | 否           | 用于指定过滤条件。如果指定该参数，StarRocks 会按照指定的过滤条件对转换后的数据进行过滤。只有符合 WHERE 子句中指定的过滤条件的数据才会导入。 |
-| max_filter_ratio | 否           | 用于指定导入作业的最大容错率，即导入作业能够容忍的因数据质量不合格而过滤掉的数据行所占的最大比例。取值范围：`0`~`1`。默认值：`0` 。<br />建议您保留默认值 `0`。这样的话，当导入的数据行中有错误时，导入作业会失败，从而保证数据的正确性。<br />如果希望忽略错误的数据行，可以设置该参数的取值大于 `0`。这样的话，即使导入的数据行中有错误，导入作业也能成功。<br />**说明**<br />这里因数据质量不合格而过滤掉的数据行，不包括通过 WHERE 子句过滤掉的数据行。 |
-| log_rejected_record_num | 否           | 指定最多允许记录多少条因数据质量不合格而过滤掉的数据行数。该参数自 3.1 版本起支持。取值范围：`0`、`-1`、大于 0 的正整数。默认值：`0`。<ul><li>取值为 `0` 表示不记录过滤掉的数据行。</li><li>取值为 `-1` 表示记录所有过滤掉的数据行。</li><li>取值为大于 0 的正整数（比如 `n`）表示每个 BE（或 CN）节点上最多可以记录 `n` 条过滤掉的数据行。</li></ul> |
-| timeout          | 否           | 用于导入作业的超时时间。取值范围：1 ~ 259200。单位：秒。默认值：`600`。<br />**说明**<br />除了 `timeout` 参数可以控制该导入作业的超时时间外，您还可以通过 [FE 配置参数](../../../administration/management/FE_configuration.md#导入导出) `stream_load_default_timeout_second` 来统一控制 Stream Load 导入作业的超时时间。如果指定了`timeout` 参数，则该导入作业的超时时间以 `timeout` 参数为准；如果没有指定 `timeout` 参数，则该导入作业的超时时间以`stream_load_default_timeout_second` 为准。 |
-| strict_mode      | 否           | 用于指定是否开严格模式。取值范围：`true` 和 `false`。默认值：`false`。`true` 表示开启，`false` 表示关闭。<br />关于该模式的介绍，参见 [严格模式](../../../loading/load_concept/strict_mode.md)。|
-| timezone         | 否           | 用于指定导入作业所使用的时区。默认为东八区 (Asia/Shanghai)。<br />该参数的取值会影响所有导入涉及的、跟时区设置有关的函数所返回的结果。受时区影响的函数有 strftime、alignment_timestamp 和 from_unixtime 等，具体请参见[设置时区](../../../administration/management/timezone.md)。导入参数 `timezone` 设置的时区对应“[设置时区](../../../administration/management/timezone.md)”中所述的会话级时区。 |
-| load_mem_limit   | 否           | 导入作业的内存限制，最大不超过 BE（或 CN）的内存限制。单位：字节。默认内存限制为 2 GB。 |
-| partial_update | 否 |是否使用部分列更新。取值包括 `TRUE` 和 `FALSE`。默认值：`FALSE`。|
-| partial_update_mode | 否 | 指定部分更新的模式，取值包括 `row` 和 `column`。<ul><li>`row`（默认值），指定使用行模式执行部分更新，比较适用于较多列且小批量的实时更新场景。</li><li>`column`，指定使用列模式执行部分更新，比较适用于少数列并且大量行的批处理更新场景。在该场景，开启列模式，更新速度更快。例如，在一个包含 100 列的表中，每次更新 10 列（占比 10%）并更新所有行，则开启列模式，更新性能将提高 10 倍。</li></ul>|
-| merge_condition  | 否           | 用于指定作为更新生效条件的列名。这样只有当导入的数据中该列的值大于等于当前值的时候，更新才会生效。StarRocks v2.5 起支持条件更新。参见[通过导入实现数据变更](../../../loading/Load_to_Primary_Key_tables.md)。 <br/>**说明**<br/>指定的列必须为非主键列，且仅主键表支持条件更新。  |
-
-## 列映射
-
-### 导入 CSV 数据时配置列映射关系
-
-如果源数据文件中的列与目标表中的列按顺序一一对应，您不需要指定列映射和转换关系。
-
-如果源数据文件中的列与目标表中的列不能按顺序一一对应，包括数量或顺序不一致，则必须通过 `COLUMNS` 参数来指定列映射和转换关系。一般包括如下两种场景：
-
-- **列数量一致、但是顺序不一致，并且数据不需要通过函数计算、可以直接落入目标表中对应的列。** 这种场景下，您需要在 `COLUMNS` 参数中按照源数据文件中的列顺序、使用目标表中对应的列名来配置列映射和转换关系。
-
-  例如，目标表中有三列，按顺序依次为 `col1`、`col2` 和 `col3`；源数据文件中也有三列，按顺序依次对应目标表中的 `col3`、`col2` 和 `col1`。这种情况下，需要指定 `COLUMNS(col3, col2, col1)`。
-
-- **列数量、顺序都不一致，并且某些列的数据需要通过函数计算以后才能落入目标表中对应的列。** 这种场景下，您不仅需要在 `COLUMNS` 参数中按照源数据文件中的列顺序、使用目标表中对应的列名来配置列映射关系，还需要指定参与数据计算的函数。以下为两个示例：
-
-  - 目标表中有三列，按顺序依次为 `col1`、`col2` 和 `col3` ；源数据文件中有四列，前三列按顺序依次对应目标表中的 `col1`、`col2` 和 `col3`，第四列在目标表中无对应的列。这种情况下，需要指定 `COLUMNS(col1, col2, col3, temp)`，其中，最后一列可随意指定一个名称（如 `temp`）用于占位即可。
-  - 目标表中有三列，按顺序依次为 `year`、`month` 和 `day`。源数据文件中只有一个包含时间数据的列，格式为 `yyyy-mm-dd hh:mm:ss`。这种情况下，可以指定 `COLUMNS (col, year = year(col), month=month(col), day=day(col))`。其中，`col` 是源数据文件中所包含的列的临时命名，`year = year(col)`、`month=month(col)` 和 `day=day(col)` 用于指定从 `col` 列提取对应的数据并落入目标表中对应的列，如 `year = year(col)` 表示通过 `year` 函数提取源数据文件中 `col` 列的 `yyyy` 部分的数据并落入目标表中的 `year` 列。
-
-有关操作示例，参见[设置列映射关系](#设置列映射关系)。
-
-### 导入 JSON 数据时配置列映射关系
-
-如果 JSON 文件中的 Key 名与目标表中的列名一致，您可以使用简单模式来导入数据。简单模式下，不需要设置 `jsonpaths` 参数，这种模式要求 JSON 数据是大括号 {} 表示的对象类型，例如 `{"category": 1, "author": 2, "price": "3"}` 中，`category`、`author`、`price` 是 Key 的名称，按名称直接对应目标 表中的 `category`、`author`、`price` 三列。
-
-如果 JSON 文件中的 Key 名与目标表中的列名不一致，则需要使用匹配模式来导入数据。匹配模式下，需要通过 `jsonpaths` 和 `COLUMNS` 两个参数来指定 JSON 文件中的 Key 和目标表中的列之间的映射和转换关系：
-
-- `jsonpaths` 参数中按照 JSON 文件中 Key 的顺序一一指定待导入的 Key。
-- `COLUMNS` 参数中指定 JSON 文件中的 Key 与目标表中的列之间的映射关系和数据转换关系。
-  - `COLUMNS` 参数中指定的列名与 `jsonpaths` 参数中指定的 Key 按顺序保持一一对应。
-  - `COLUMNS` 参数中指定的列名与目标表中的列按名称保持一一对应。
-
-有关使用匹配模式导入 JSON 数据的示例，参见[使用匹配模式导入数据](#使用匹配模式导入数据)。
-
-## 返回值
-
-导入结束后，会以 JSON 格式返回导入作业的结果信息，如下所示：
-
-```JSON
-{
-    "TxnId": 1003,
-    "Label": "label123",
-    "Status": "Success",
-    "Message": "OK",
-    "NumberTotalRows": 1000000,
-    "NumberLoadedRows": 999999,
-    "NumberFilteredRows": 1,
-    "NumberUnselectedRows": 0,
-    "LoadBytes": 40888898,
-    "LoadTimeMs": 2144,
-    "BeginTxnTimeMs": 0,
-    "StreamLoadPlanTimeMs": 1,
-    "ReadDataTimeMs": 0,
-    "WriteDataTimeMs": 11,
-    "CommitAndPublishTimeMs": 16,
-}
-```
-
-返回结果中的参数说明如下表所述。
-
-| **参数名称**           | **说明**                                                     |
-| ---------------------- | ------------------------------------------------------------ |
-| TxnId                  | 导入作业的事务 ID。                                          |
-| Label                  | 导入作业的标签。                                             |
-| Status                 | 此次导入的数据的最终状态。<ul><li>`Success`：表示数据导入成功，数据已经可见。</li><li>`Publish Timeout`：表示导入作业已经成功提交，但是由于某种原因数据并不能立即可见。可以视作已经成功、不必重试导入。</li><li>`Label Already Exists`：表示该标签已经被其他导入作业占用。数据可能导入成功，也可能是正在导入。</li><li>`Fail`：表示数据导入失败。您可以指定标签重试该导入作业。</li></ul> |
-| Message                | 导入作业的状态详情。如果导入作业失败，这里会返回具体的失败原因。 |
-| NumberTotalRows        | 读取到的总行数。                                             |
-| NumberLoadedRows       | 成功导入的总行数。只有当返回结果中的 `Status` 为 `Success` 时有效。 |
-| NumberFilteredRows     | 导入过程中因数据质量不合格而过滤掉的行数。                   |
-| NumberUnselectedRows   | 导入过程中根据 WHERE 子句指定的条件而过滤掉的行数。          |
-| LoadBytes              | 此次导入的数据量大小。单位：字节 (Bytes)。                   |
-| LoadTimeMs             | 此次导入所用的时间。单位：毫秒 (ms)。                        |
-| BeginTxnTimeMs         | 导入作业开启事务的时长。                                     |
-| StreamLoadPlanTimeMs   | 导入作业生成执行计划的时长。                                 |
-| ReadDataTimeMs         | 导入作业读取数据的时长。                                     |
-| WriteDataTimeMs        | 导入作业写入数据的时长。                                     |
-| CommitAndPublishTimeMs | 导入作业提交和数据发布的耗时。                               |
-
-如果导入作业失败，还会返回 `ErrorURL`，如下所示：
-
-```JSON
-{
-    "ErrorURL": "http://172.26.195.68:8045/api/_load_error_log?file=error_log_3a4eb8421f0878a6_9a54df29fd9206be"
-}
-```
-
-通过 `ErrorURL` 可以查看导入过程中因数据质量不合格而过滤掉的错误数据行的具体信息。您可以在提交导入作业时，通过可选参数 `log_rejected_record_num` 来指定最多可以记录多少条错误数据行的信息。
-
-您可以通过  `curl "url"` 命令直接查看错误数据行的信息。也可以通过 `wget "url"` 命令导出错误数据行的信息，如下所示：
-
-```Bash
-wget http://172.26.195.68:8045/api/_load_error_log?file=error_log_3a4eb8421f0878a6_9a54df29fd9206be
-```
-
-导出的错误数据行信息会保存到一个名为 `_load_error_log?file=error_log_3a4eb8421f0878a6_9a54df29fd9206be` 的本地文件中。您可以通过 `cat _load_error_log?file=error_log_3a4eb8421f0878a6_9a54df29fd9206be` 命令查看该文件的内容。
-
-您可以根据错误信息调整导入作业，然后重新提交导入作业。
-
-## 示例
-
-### 导入 CSV 格式的数据
-
-本小节以 CSV 格式的数据为例，重点阐述在创建导入作业的时候，如何运用各种参数配置来满足不同业务场景下的各种导入要求。
-
-#### **设置超时时间**
-
-StarRocks 数据库 `test_db` 里的表 `table1` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example1.csv` 也包含三列，按顺序一一对应 `table1` 中的三列 `col1`、`col2`、`col3`。
-
-如果要把 `example1.csv` 中所有的数据都导入到 `table1` 中，并且要求超时时间最大不超过 100 秒，可以执行如下命令：
-
-```Bash
-curl --location-trusted -u <username>:<password> -H "label:label1" \
-    -H "Expect:100-continue" \
-    -H "timeout:100" \
-    -H "max_filter_ratio:0.2" \
-    -T example1.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table1/_stream_load
-```
-
-#### **设置最大容错率**
-
-StarRocks 数据库 `test_db` 里的表 `table2` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example2.csv` 也包含三列，按顺序一一对应 `table2` 中的三列 `col1`、`col2`、`col3`。
-
-如果要把 `example2.csv` 中所有的数据都导入到 `table2` 中，并且要求容错率最大不超过 `0.2`，可以执行如下命令：
-
-```Bash
-curl --location-trusted -u <username>:<password> -H "label:label2" \
-    -H "Expect:100-continue" \
-    -H "max_filter_ratio:0.2" \
-    -T example2.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table2/_stream_load
-```
-
-#### **设置列映射关系**
-
-StarRocks 数据库 `test_db` 里的表 `table3` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example3.csv` 也包含三列，按顺序依次对应 `table3` 中 `col2`、`col1`、`col3`。
-
-如果要把 `example3.csv` 中所有的数据都导入到 `table3` 中，可以执行如下命令：
-
-```Bash
-curl --location-trusted -u <username>:<password>  -H "label:label3" \
-    -H "Expect:100-continue" \
-    -H "columns: col2, col1, col3" \
-    -T example3.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table3/_stream_load
-```
-
-> **说明**
->
-> 上述示例中，因为 `example3.csv` 和 `table3` 所包含的列不能按顺序依次对应，因此需要通过 `columns` 参数来设置 `example3.csv` 和 `table3` 之间的列映射关系。
-
-#### **设置筛选条件**
-
-StarRocks 数据库 `test_db` 里的表 `table4` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example4.csv` 也包含三列，按顺序一一对应 `table4` 中的三列 `col1`、`col2`、`col3`。
-
-如果只想把 `example4.csv` 中第一列的值等于 `20180601` 的数据行导入到 `table4` 中，可以执行如下命令：
-
-```Bash
-curl --location-trusted -u <username>:<password> -H "label:label4" \
-    -H "Expect:100-continue" \
-    -H "columns: col1, col2，col3]"\
-    -H "where: col1 = 20180601" \
-    -T example4.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table4/_stream_load
-```
-
-> **说明**
->
-> 上述示例中，虽然 `example4.csv` 和 `table4` 所包含的列数目相同、并且按顺序一一对应，但是因为需要通过 WHERE 子句指定基于列的过滤条件，因此需要通过 `columns` 参数对 `example4.csv` 中的列进行临时命名。
-
-#### **设置目标分区**
-
-StarRocks 数据库 `test_db` 里的表 `table5` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example5.csv` 也包含三列，按顺序一一对应 `table5` 中的三列 `col1`、`col2`、`col3`。
-
-如果要把 `example5.csv` 中所有的数据都导入到 `table5` 所在的分区 `p1` 和 `p2`，可以执行如下命令：
-
-```Bash
-curl --location-trusted -u <username>:<password>  -H "label:label5" \
-    -H "Expect:100-continue" \
-    -H "partitions: p1, p2" \
-    -T example5.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table5/_stream_load
-```
-
-#### **设置严格模式和时区**
-
-StarRocks 数据库 `test_db` 里的表 `table6` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example6.csv` 也包含三列，按顺序一一对应 `table6` 中的三列 `col1`、`col2`、`col3`。
-
-如果要把 `example6.csv` 中所有的数据导入到 `table6` 中，并且要求进严格模式的过滤、使用时区 `Africa/Abidjan`，可以执行如下命令：
-
-```Bash
-curl --location-trusted -u <username>:<password> \
-    -H "Expect:100-continue" \
-    -H "strict_mode: true" \
-    -H "timezone: Africa/Abidjan" \
-    -T example6.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table6/_stream_load
-```
-
-#### **导入数据到含有 HLL 类型列的表**
-
-StarRocks 数据库 `test_db` 里的表 `table7` 包含两个 HLL 类型的列，按顺序依次为 `col1`、`col2`。
-
-数据文件 `example7.csv` 也包含两列，第一列对应 `table7` 中  HLL 类型的列`col1`，可以通过函数转换成 HLL 类型的数据并落入 `col1` 列；第二列跟 `table7` 中任何一列都不对应。
-
-如果要把 `example7.csv` 中对应的数据导入到 `table7` 中，可以执行如下命令：
-
-```Bash
-curl --location-trusted -u <username>:<password> \
-    -H "Expect:100-continue" \
-    -H "columns: temp1, temp2, col1=hll_hash(temp1), col2=hll_empty()" \
-    -T example7.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table7/_stream_load
-```
-
-> **说明**
->
-> 上述示例中，通过 `columns` 参数，把 `example7.csv` 中的两列临时命名为 `temp1`、`temp2`，然后使用函数指定数据转换规则，包括：
->
-> - 使用 `hll_hash` 函数把 `example7.csv` 中的 `temp1` 列转换成 HLL 类型的数据并映射到 `table7`中的 `col1` 列。
->
-> - 使用 `hll_empty` 函数给导入的数据行在 `table7` 中的第二列补充默认值。
-
-有关 `hll_hash` 函数和 `hll_empty` 函数的用法，请参见 [hll_hash](../../sql-functions/scalar-functions/hll_hash.md) 和 [hll_empty](../../sql-functions/scalar-functions/hll_empty.md)。
-
-#### **导入数据到含有 BITMAP 类型列的表**
-
-StarRocks 数据库 `test_db` 里的表 `table8` 包含两个 BITMAP 类型的列，按顺序依次为 `col1`、`col2`。
-
-数据文件 `example8.csv` 也包含两列，第一列对应 `table8` 中 BITMAP 类型的列 `col1`，可以通过函数转换成 BITMAP 类型的数据并落入 `col1` 列；第二列跟 `table8` 中任何一列都不对应。
-
-如果要把 `example8.csv` 中对应的数据导入到 `table8` 中，可以执行如下命令：
-
-```Bash
-curl --location-trusted -u <username>:<password> \
-    -H "Expect:100-continue" \
-    -H "columns: temp1, temp2, col1=to_bitmap(temp1), col2=bitmap_empty()" \
-    -T example8.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/table8/_stream_load
-```
-
-> **说明**
->
-> 上述示例中，通过 `columns` 参数，把 `example8.csv` 中的两列临时命名为 `temp1`、`temp2`，然后使用函数指定数据转换规则，包括：
->
-> - 使用 `to_bitmap` 函数把 `example8.csv` 中的 `temp1` 列转换成 BITMAP 类型的数据并落入 `table8` 中的 `col1` 列。
->
-> - 使用 `bitmap_empty` 函数给导入的数据行在 `table8` 中的第二列补充默认值。
-
-有关 `to_bitmap` 函数和 `bitmap_empty` 函数的用法，请参见 [to_bitmap](../../sql-functions/bitmap-functions/to_bitmap.md) 和 [bitmap_empty](../../sql-functions/bitmap-functions/bitmap_empty.md)。
-
-#### 设置 `skip_header`、`trim_space`、`enclose` 和 `escape`
-
-StarRocks 数据库 `test_db` 里的表 `table9` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
-
-数据文件 `example9.csv` 也包含三列，按顺序依次对应 `table9` 中 `col2`、`col1`、`col3`。
-
-如果要把 `example9.csv` 中所有的数据都导入到 `table9` 中，并且希望跳过 `example9.csv` 中最开头的五行数据、去除列分隔符前后的空格、 指定 `enclose` 字符为斜杠 (`\`)、并且指定 `escape` 字符为斜杠 (`\`)，可以执行如下语句：
-
-```Bash
-curl --location-trusted -u <username>:<password> -H "label:3875" \
-    -H "Expect:100-continue" \
-    -H "trim_space: true" -H "skip_header: 5" \
-    -H "column_separator:," -H "enclose:\"" -H "escape:\\" \
-    -H "columns: col2, col1, col3" \
-    -T example9.csv -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/tbl9/_stream_load
-```
-
-### **导入 JSON 格式的数据**
-
-本小节主要描述导入 JSON 格式的数据时，需要关注的一些参数配置。
-
-StarRocks 数据库 `test_db` 里的表 `tbl1` 拥有如下表结构：
-
-```SQL
-`category` varchar(512) NULL COMMENT "",
-`author` varchar(512) NULL COMMENT "",
-`title` varchar(512) NULL COMMENT "",
-`price` double NULL COMMENT ""
-```
-
-#### **使用简单模式导入数据**
-
-假设数据文件 `example1.json` 包含如下数据：
-
-```JSON
-{"category":"C++","author":"avc","title":"C++ primer","price":895}
-```
-
-您可以通过如下命令将 `example1.json` 中的数据导入到 `tbl1` 中：
-
-```Bash
-curl --location-trusted -u <username>:<password> -H "label:label6" \
-    -H "Expect:100-continue" \
-    -H "format: json" \
-    -T example1.json -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/tbl1/_stream_load
-```
-
-> **说明**
->
-> 如上述示例所示，在没有指定 `columns` 和 `jsonpaths` 参数的情况下，则会按照 StarRocks 表中的列名称去对应 JSON 数据文件中的字段。
-
-为了提升吞吐量，Stream Load 支持一次性导入多条数据。比如，可以一次性导入 JSON 数据文件中如下多条数据：
-
-```JSON
-[
-    {"category":"C++","author":"avc","title":"C++ primer","price":89.5},
-    {"category":"Java","author":"avc","title":"Effective Java","price":95},
-    {"category":"Linux","author":"avc","title":"Linux kernel","price":195}
-]
-```
-
-#### **使用匹配模式导入数据**
-
-StarRocks 按照如下顺序对数据进行匹配和处理：
-
-1. （可选）根据 `strip_outer_array` 参数裁剪最外层的数组结构。
-
-    > **说明**
-    >
-    > 仅在 JSON 数据的最外层是一个通过中括号 `[]` 表示的数组结构时涉及，需要设置 `strip_outer_array` 为 `true`。
-
-2. （可选）根据 `json_root` 参数匹配 JSON 数据的根节点。
-
-    > **说明**
-    >
-    > 仅在 JSON 数据存在根节点时涉及，需要通过 `json_root` 参数来指定根节点。
-
-3. 根据 `jsonpaths` 参数提取待导入的 JSON 数据。
-
-##### **不指定 JSON 根节点、使用匹配模式导入数据**
-
-假设数据文件 `example2.json` 包含如下数据：
-
-```JSON
-[
-    {"category":"xuxb111","author":"1avc","title":"SayingsoftheCentury","price":895},
-    {"category":"xuxb222","author":"2avc","title":"SayingsoftheCentury","price":895},
-    {"category":"xuxb333","author":"3avc","title":"SayingsoftheCentury","price":895}
-]
-```
-
-您可以通过指定 `jsonpaths` 参数进行精准导入，例如只导入 `category`、`author`、`price` 三个字段的数据：
-
-```Bash
-curl --location-trusted -u <username>:<password> -H "label:label7" \
-    -H "Expect:100-continue" \
-    -H "format: json" \
-    -H "strip_outer_array: true" \
-    -H "jsonpaths: [\"$.category\",\"$.price\",\"$.author\"]" \
-    -H "columns: category, price, author" \
-    -T example2.json -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/tbl1/_stream_load
-```
-
-> **说明**
->
-> 上述示例中，JSON 数据的最外层是一个通过中括号 [] 表示的数组结构，并且数组结构中的每个 JSON 对象都表示一条数据记录。因此，需要设置 `strip_outer_array` 为 `true`来裁剪最外层的数组结构。导入过程中，未指定的字段 `title` 会被忽略掉。
-
-##### **指定 JSON 根节点、使用匹配模式导入数据**
-
-假设数据文件 `example3.json` 包含如下数据：
-
-```JSON
-{
-    "id": 10001,
-    "RECORDS":[
-        {"category":"11","title":"SayingsoftheCentury","price":895,"timestamp":1589191587},
-        {"category":"22","author":"2avc","price":895,"timestamp":1589191487},
-        {"category":"33","author":"3avc","title":"SayingsoftheCentury","timestamp":1589191387}
-    ],
-    "comments": ["3 records", "there will be 3 rows"]
-}
-```
-
-您可以通过指定 `jsonpaths` 进行精准导入，例如只导入 `category`、`author`、`price` 三个字段的数据：
-
-```Bash
-curl --location-trusted -u <username>:<password> \
-    -H "Expect:100-continue" \
-    -H "format: json" \
-    -H "json_root: $.RECORDS" \
-    -H "strip_outer_array: true" \
-    -H "jsonpaths: [\"$.category\",\"$.price\",\"$.author\"]" \
-    -H "columns: category, price, author" -H "label:label8" \
-    -T example3.json -XPUT \
-    http://<fe_host>:<fe_http_port>/api/test_db/tbl1/_stream_load
-```
-
-> **说明**
->
-> 上述示例中，JSON 数据的最外层是一个通过中括号 [] 表示的数组结构，并且数组结构中的每个 JSON 对象都表示一条数据记录。因此，需要设置 `strip_outer_array` 为 `true`来裁剪最外层的数组结构。导入过程中，未指定的字段 `title` 和 `timestamp` 会被忽略掉。另外，示例中还通过 `json_root` 参数指定了需要真正导入的数据为 `RECORDS` 字段对应的值，即一个 JSON 数组。
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SUBMIT_TASK.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SUBMIT_TASK.md
deleted file mode 100644
index d0d94f2cfdb657..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SUBMIT_TASK.md
+++ /dev/null
@@ -1,119 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SUBMIT TASK
-
-## 功能
-
-为 ETL 语句创建异步任务。
-
-您可将该语句用于以下场景：
-
-- 创建长时间运行的后台任务（从 v2.5 开始支持）
-- 创建定期执行的任务（从 v3.3 开始支持）
-
-支持的语句包括：
-
-- [CREATE TABLE AS SELECT](../data-definition/CREATE_TABLE_AS_SELECT.md)（从 v3.0 开始支持）
-- [INSERT](./INSERT.md)（从 v3.0 开始支持）
-- [CACHE SELECT](../../../data_source/data_cache_warmup.md)（从 v3.3 开始支持）
-
-您可以通过查询 `INFORMATION_SCHEMA.tasks` 查看任务列表，或通过查询 `INFORMATION_SCHEMA.task_runs` 查看任务的执行历史。有关更多信息，请参阅[使用说明](#使用说明)。
-
-您可以使用 [DROP TASK](./DROP_TASK.md) 删除异步任务。
-
-## 语法
-
-```SQL
-SUBMIT TASK <task_name> 
-[SCHEDULE [START(<schedule_start>)] EVERY(INTERVAL <schedule_interval>) ]
-[PROPERTIES(<"key" = "value"[, ...]>)]
-AS <etl_statement>
-```
-
-## 参数说明
-
-| **参数**      | **是否必须** | **描述**                                                                                     |
-| ------------- | ------------ | ----------------------------------------------------------------------------------------- |
-| task_name          | 是      | 任务名称。                                                                                   |
-| schedule_start     | 否      | 定时任务的开始时间。                                                                           |
-| schedule_interval  | 否      | 定时任务的执行间隔，最小间隔为 10 秒。                                                           |
-| etl_statement      | 是      | 需要创建异步任务的 ETL 语句。StarRocks 当前支持为 [CREATE TABLE AS SELECT](../data-definition/CREATE_TABLE_AS_SELECT.md) 和 [INSERT](./INSERT.md) 创建异步任务。 |
-
-## 使用说明
-
-该语句会创建一个 Task，表示一个 ETL 语句执行任务的存储模板。您可以通过查询 Information Schema 中的元数据视图 `tasks` 来查看 Task 信息：
-
-```SQL
-SELECT * FROM INFORMATION_SCHEMA.tasks;
-SELECT * FROM information_schema.tasks WHERE task_name = '<task_name>';
-```
-
-执行 Task 后会对应生成一个 TaskRun，表示一个 ETL 语句执行任务。TaskRun 有以下状态：
-
-- `PENDING`：任务等待执行。
-- `RUNNING`：任务正在执行。
-- `FAILED`：任务执行失败。
-- `SUCCESS`：任务执行成功。
-
-您可以通过查询 Information Schema 中的元数据视图 `task_runs` 来查看 TaskRun 状态：
-
-```SQL
-SELECT * FROM INFORMATION_SCHEMA.task_runs;
-SELECT * FROM information_schema.task_runs WHERE task_name = '<task_name>';
-```
-
-## 相关 FE 参数
-
-您可以通过调整如下 FE 参数配置异步 ETL 任务：
-
-| **参数**                     | **默认值** | **说明**                                                     |
-| ---------------------------- | ---------- | ------------------------------------------------------------ |
-| task_ttl_second              | 86400      | Task 的有效期，单位秒。超过有效期的 Task 会被自动删除。        |
-| task_check_interval_second   | 3600       | 删除过期 Task 的间隔时间，单位秒。                           |
-| task_runs_ttl_second         | 86400      | TaskRun 的有效期，单位秒。超过有效期的 TaskRun 会被自动删除。此外，成功和失败状态的 TaskRun 也会被自动删除。 |
-| task_runs_concurrency        | 4          | 最多可同时运行的 TaskRun 的数量。                            |
-| task_runs_queue_length       | 500        | 最多可同时等待运行的 TaskRun 的数量。如同时等待运行的 TaskRun 的数量超过该参数的默认值，您将无法继续执行 Task。 |
-| task_runs_max_history_number | 10000      | 保留的最多历史 TaskRun 任务数量。 |
-| task_min_schedule_interval_s | 10         | Task 最小执行间隔。单位：秒。 |
-
-## 示例
-
-示例一：为 `CREATE TABLE tbl1 AS SELECT * FROM src_tbl` 创建异步任务，并命名为 `etl0`：
-
-```SQL
-SUBMIT TASK etl0 AS CREATE TABLE tbl1 AS SELECT * FROM src_tbl;
-```
-
-示例二：为 `INSERT INTO tbl2 SELECT * FROM src_tbl` 创建异步任务，并命名为 `etl1`：
-
-```SQL
-SUBMIT TASK etl1 AS INSERT INTO tbl2 SELECT * FROM src_tbl;
-```
-
-示例三：为 `INSERT OVERWRITE tbl3 SELECT * FROM src_tbl` 创建异步任务：
-
-```SQL
-SUBMIT TASK AS INSERT OVERWRITE tbl3 SELECT * FROM src_tbl;
-```
-
-示例四：为 `INSERT OVERWRITE insert_wiki_edit SELECT * FROM source_wiki_edit` 创建异步任务，并通过 Hint 将 Query Timeout 设置为 `100000` 秒：
-
-```SQL
-SUBMIT /*+set_var(query_timeout=100000)*/ TASK AS
-INSERT OVERWRITE insert_wiki_edit
-SELECT * FROM source_wiki_edit;
-```
-
-示例五：为 INSERT OVERWRITE 语句创建异步任务。任务将以一分钟为间隔定期执行。
-
-```SQL
-SUBMIT TASK
-SCHEDULE EVERY(INTERVAL 1 MINUTE)
-AS
-INSERT OVERWRITE insert_wiki_edit
-    SELECT dt, user_id, count(*) 
-    FROM source_wiki_edit 
-    GROUP BY dt, user_id;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/SUSPEND_or_RESUME_PIPE.md b/docs/zh/sql-reference/sql-statements/data-manipulation/SUSPEND_or_RESUME_PIPE.md
deleted file mode 100644
index 3871855c777ae2..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/SUSPEND_or_RESUME_PIPE.md
+++ /dev/null
@@ -1,58 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SUSPEND or RESUME PIPE
-
-## 功能
-
-暂停或重新启动 Pipe：
-
-- 当导入作业正在进行时（即，处于 `RUNNING` 状态），暂停 (`SUSPEND`) Pipe 会中断正在执行的作业。
-- 当出现导入错误时，重新启动 (`RESUME`) Pipe 会继续执行出错的作业。
-
-该命令自 3.2 版本起支持。
-
-## 语法
-
-```SQL
-ALTER PIPE [ IF EXISTS ] <pipe_name> { SUSPEND | RESUME [ IF SUSPENDED ] }
-```
-
-## 参数说明
-
-### pipe_name
-
-Pipe 的名称。
-
-## 示例
-
-### 暂停 Pipe
-
-暂停数据库 `mydatabase` 下名为 `user_behavior_replica` 的 Pipe（Pipe 当前处于 `RUNNING` 状态）：
-
-```SQL
-USE mydatabase;
-ALTER PIPE user_behavior_replica SUSPEND;
-```
-
-通过 [SHOW PIPES](../../../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md) 查看该 Pipe，可以看到 Pipe 的状态变为 `SUSPEND`。
-
-### 重新启动 Pipe
-
-重新启动数据库 `mydatabase` 下名为 `user_behavior_replica` 的 Pipe：
-
-```SQL
-USE mydatabase;
-ALTER PIPE user_behavior_replica RESUME;
-```
-
-通过 [SHOW PIPES](../../../sql-reference/sql-statements/data-manipulation/SHOW_PIPES.md) 查看该 Pipe，可以看到 Pipe 的状态变为 `RUNNING`。
-
-## 相关文档
-
-- [CREATE PIPE](../data-manipulation/CREATE_PIPE.md)
-- [ALTER PIPE](../data-manipulation/ALTER_PIPE.md)
-- [DROP PIPE](../data-manipulation/DROP_PIPE.md)
-- [SHOW PIPES](../data-manipulation/SHOW_PIPES.md)
-- [RETRY FILE](../data-manipulation/RETRY_FILE.md)
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/UPDATE.md b/docs/zh/sql-reference/sql-statements/data-manipulation/UPDATE.md
deleted file mode 100644
index c0ff1dbefc5a3c..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/UPDATE.md
+++ /dev/null
@@ -1,174 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# UPDATE
-
-该语句用于更新一张主键表中的数据行。
-
-2.3 ～ 2.5 版本，StarRocks 提供 UPDATE 语句，并且仅支持单表 UPDATE 且不支持公用表表达式（CTE）。从 3.0 版本开始，StarRocks 丰富了 UPDATE 语法，支持使用多表关联和 CTE。如果需要将待更新的表与数据库中其他表关联，则可以在 FROM 子句或 CTE 中引用其他的表。从 3.1 版本开始，支持列模式的部分更新，适用于涉及少数列但是大量行的场景，加快更新速度。
-
-## 使用说明
-
-如果为多表 UPDATE，则您需要确保 UPDATE 语句中 FROM 子句的表表达式可以转换成等价的 JOIN 查询语句。因为 StarRocks 实际执行 UPDATE 语句时，内部会进行这样的转换。假设 UPDATE 语句为 `UPDATE t0 SET v1=t1.v1 FROM t1 WHERE t0.pk = t1.pk;`，该 FROM 子句的表表达式可以转换为 `t0 JOIN t1 ON t0.pk=t1.pk;`。并且 StarRocks 根据 JOIN 查询的结果集，匹配待更新表的数据行，更新其指定列的值。如果结果集中存在多行数据和待更新表的某一行数据相匹配，则待更新表中这行数据指定列更新后的值，是结果集多行数据中随机一行的指定列的值。
-
-## 语法
-
-**单表 UPDATE**
-
-如果待更新表的数据行满足 WHERE 条件，则对该数据行的指定列赋予新值。
-
-```SQL
-[ WITH <with_query> [, ...] ]
-UPDATE <table_name>
-    SET <column_name> = <expression> [, ...]
-    WHERE <where_condition>
-```
-
-**多表 UPDATE**
-
-基于多表关联查询的结果集与待更新的表进行匹配，如果待更新表的数据行匹配结果集并且满足 WHERE 条件，则对该数据行的指定列赋予新值。
-
-```SQL
-[ WITH <with_query> [, ...] ]
-UPDATE <table_name>
-    SET <column_name> = <expression> [, ...]
-    [ FROM <from_item> [, ...] ]
-    WHERE <where_condition>
-```
-
-## 参数说明
-
-`with_query`
-
-一个或多个可以在 UPDATE 语句中通过名字引用的 CTE。CTE 是一个临时结果集，可以提高复杂语句的易读性。
-
-`table_name`
-
-待更新的表的名称。
-
-`column_name`
-
-待更新的列的名称。不需要包含表名，例如 `UPDATE t1 SET t1.col = 1` 是不合法的。
-
-`expression`
-
-给列赋值的表达式。
-
-`from_item`
-
-引用数据库中一个或者多个其他的表。该表与待更新的表进行连接，WHERE 子句指定连接条件，最终基于连接查询的结果集给待更新的表中匹配行的列赋值。 例如 FROM 子句为 `FROM t1 WHERE t0.pk = t1.pk;`，StarRocks 实际执行 UPDATE 语句时会将该 FROM 子句的表表达式会转换为 `t0 JOIN t1 ON t0.pk=t1.pk;`。
-
-`where_condition`
-
-只有满足 WHERE 条件的行才会被更新。该参数为必选，防止误更新整张表。如需更新整张表，请使用 `WHERE true`。如果使用[列模式的部分更新](#列模式的部分更新自-31)，则该参数不是必选。
-
-## 列模式的部分更新（自 3.1）
-
-列模式的部分更新适用于涉及少数列并且大量行的场景。在该场景，开启列模式，更新速度更快。例如，在一个包含 100 列的表中，每次更新 10 列（占比 10%）并更新所有行，则开启列模式，更新性能将提高 10 倍。
-
-系统变量 `partial_update_mode` 用于控制部分更新的模式，支持取值为：
-
-* `auto`（默认值），表示由系统通过分析更新语句以及其涉及的列，自动判断执行部分更新时使用的模式。如果满足如下标准，则系统自动使用列模式：
-  * 更新的列数占所有列数的百分比小于 30%，并且更新的列数少于 4 个。
-  * 更新语句中没有使用 WHERE 条件。
-  
-  反之，则系统不会使用列模式。
-* `column`，指定使用列模式执行部分更新，比较适用于涉及少数列并且大量行的部分列更新场景。
-
-您可以使用 `EXPLAIN UPDATE xxx` 查看执行部分列更新的模式。
-
-## 示例
-
-### 单表 UPDATE
-
-创建表 `Employees` 来记录雇员信息，向表中插入五行数据。
-
-```SQL
-CREATE TABLE Employees (
-    EmployeeID INT,
-    Name VARCHAR(50),
-    Salary DECIMAL(10, 2)
-)
-PRIMARY KEY (EmployeeID) 
-DISTRIBUTED BY HASH (EmployeeID)
-PROPERTIES ("replication_num" = "3");
-
-INSERT INTO Employees VALUES
-    (1, 'John Doe', 5000),
-    (2, 'Jane Smith', 6000),
-    (3, 'Robert Johnson', 5500),
-    (4, 'Emily Williams', 4500),
-    (5, 'Michael Brown', 7000);
-```
-
-如果需要对所有员工加薪 10%，则可以执行如下语句：
-
-```SQL
-UPDATE Employees
-SET Salary = Salary * 1.1  -- 将薪水增加10%
-WHERE true;
-```
-
-如果需要对薪水低于平均薪水的员工加薪 10%，则可以执行如下语句，
-
-```SQL
-UPDATE Employees
-SET Salary = Salary * 1.1  -- 将薪水增加10%
-WHERE Salary < (SELECT AVG(Salary) FROM Employees);
-```
-
-您也可以使用 CTE 改写上述语句，增加易读性。
-
-```SQL
-WITH AvgSalary AS (
-    SELECT AVG(Salary) AS AverageSalary
-    FROM Employees
-)
-UPDATE Employees
-SET Salary = Salary * 1.1  -- 将薪水增加10%
-FROM AvgSalary
-WHERE Employees.Salary < AvgSalary.AverageSalary;
-```
-
-### 多表 UPDATE
-
-创建表 `Accounts` 来记录账户信息，向表中插入三行数据。
-
-```SQL
-CREATE TABLE Accounts (
-    Accounts_id BIGINT NOT NULL,
-    Name VARCHAR(26) NOT NULL,
-    Sales_person VARCHAR(50) NOT NULL
-) 
-PRIMARY KEY (Accounts_id)
-DISTRIBUTED BY HASH (Accounts_id)
-PROPERTIES ("replication_num" = "3");
-
-INSERT INTO Accounts VALUES
-    (1,'Acme Corporation','John Doe'),
-    (2,'Acme Corporation','Robert Johnson'),
-    (3,'Acme Corporation','Lily Swift');
-```
-
-如果需要给表 `Employees` 中 Acme Corporation 公司管理帐户的员工加薪 10%，则可以执行如下语句：
-
-```SQL
-UPDATE Employees
-SET Salary = Salary * 1.1  -- 将薪水增加10%
-FROM Accounts
-WHERE Accounts.name = 'Acme Corporation'
-    AND Employees.Name = Accounts.Sales_person;
-```
-
-您也可以使用 CTE 改写上述语句，增加易读性。
-
-```SQL
-WITH Acme_Accounts as (
-    SELECT * from Accounts
-    WHERE Accounts.name = 'Acme Corporation'
-)
-UPDATE Employees SET Salary = Salary * 1.1 -- 将薪水增加10%
-FROM Acme_Accounts
-WHERE Employees.Name = Acme_Accounts.Sales_person;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_BACKUP.md b/docs/zh/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_BACKUP.md
deleted file mode 100644
index 62c88bc563b6b0..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_BACKUP.md
+++ /dev/null
@@ -1,52 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW BACKUP
-
-## 功能
-
-查看指定数据库中的备份任务。更多信息，请见 备份和恢复。
-
-> **说明**
->
-> StarRocks 中仅保存最近一次备份任务信息。
-
-## 语法
-
-```SQL
-SHOW BACKUP [FROM <db_name>]
-```
-
-## 参数说明
-
-| **参数** | **说明**               |
-| -------- | ---------------------- |
-| db_name  | 备份任务所属数据库名。 |
-
-## 返回
-
-| **返回**             | **说明**                                                     |
-| -------------------- | ------------------------------------------------------------ |
-| JobId                | 本次备份作业的 ID。                                          |
-| SnapshotName         | 用户指定的本次备份作业的名称。                               |
-| DbName               | 备份作业对应的数据库。                                       |
-| State                | 备份作业当前所在阶段：<ul><li>PENDING：作业初始状态。</li><li>SNAPSHOTING：正在进行快照操作。</li><li>UPLOAD_SNAPSHOT：快照结束，准备上传。</li><li>UPLOADING：正在上传快照。</li><li>SAVE_META：正在本地生成元数据文件。</li><li>UPLOAD_INFO：上传元数据文件和本次备份作业的信息。</li><li>FINISHED：备份完成。</li><li>CANCELLED：备份失败或被取消。</li></ul> |
-| BackupObjs           | 本次备份涉及的对象。                                         |
-| CreateTime           | 作业创建时间。                                               |
-| SnapshotFinishedTime | 快照完成时间。                                               |
-| UploadFinishedTime   | 快照上传完成时间。                                           |
-| FinishedTime         | 本次作业完成时间。                                           |
-| UnfinishedTasks      | 在 SNAPSHOTTING，UPLOADING 等阶段，会有多个子任务在同时进行，这里展示的当前段，未完成子任务的 Task ID。 |
-| Progress             | 快照上传任务进展。|
-| TaskErrMsg           | 如果有子任务执行出错，这里会显示对应子任务的错误信息。       |
-| Status               | 用于记录在整个作业过程中，可能出现的一些状态信息。           |
-| Timeout              | 作业的超时时间，单位为秒。                                   |
-
-## 示例
-
-示例一：查看数据库 `example_db` 下最后一次备份任务。
-
-```SQL
-SHOW BACKUP FROM example_db;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_REPOSITORIES.md b/docs/zh/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_REPOSITORIES.md
deleted file mode 100644
index 05297f6ced1173..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_REPOSITORIES.md
+++ /dev/null
@@ -1,35 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW REPOSITORIES
-
-## 功能
-
-查看当前已创建的仓库。
-
-## 语法
-
-```SQL
-SHOW REPOSITORIES
-```
-
-## 返回
-
-| **返回**   | **说明**                |
-| ---------- | ----------------------- |
-| RepoId     | 仓库 ID。               |
-| RepoName   | 仓库名。                |
-| CreateTime | 仓库创建时间。          |
-| IsReadOnly | 是否为只读仓库。        |
-| Location   | 远端存储系统路径。      |
-| Broker     | 用于创建仓库的 Broker。 |
-| ErrMsg     | 仓库连接错误信息。      |
-
-## 示例
-
-示例一：查看已创建的仓库。
-
-```SQL
-SHOW REPOSITORIES;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_RESTORE.md b/docs/zh/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_RESTORE.md
deleted file mode 100644
index 90d69b9d7c9e9f..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_RESTORE.md
+++ /dev/null
@@ -1,56 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW RESTORE
-
-## 功能
-
-查看指定数据库中的恢复任务。更多信息，请见 备份和恢复。
-
-> **说明**
->
-> StarRocks 中仅保存最近一次恢复任务信息。
-
-## 语法
-
-```SQL
-SHOW RESTORE [FROM <db_name>]
-```
-
-## 参数说明
-
-| **参数** | **说明**               |
-| -------- | ---------------------- |
-| db_name  | 恢复任务所属数据库名。 |
-
-## 返回
-
-| **返回**             | **说明**                                                     |
-| -------------------- | ------------------------------------------------------------ |
-| JobId                | 本次恢复作业的 ID。                                          |
-| Label                | 要恢复的备份名称。                                           |
-| Timestamp            | 备份时间戳。                                                 |
-| DbName               | 恢复作业对应的数据库。                                       |
-| State                | 恢复作业当前所在阶段：<ul><li>PENDING：作业初始状态。</li><li>SNAPSHOTING：正在进行本地新建表的快照操作。</li><li>DOWNLOAD：正在发送下载快照任务。</li><li>DOWNLOADING：快照正在下载。</li><li>COMMIT：准备生效已下载的快照。</li><li>COMMITTING：正在生效已下载的快照。</li><li>FINISHED：恢复完成。</li><li>CANCELLED：恢复失败或被取消。</li></ul> |
-| AllowLoad            | 恢复期间是否允许导入。                                       |
-| ReplicationNum       | 恢复指定的副本数。                                           |
-| RestoreObjs          | 被恢复的对象（表和分区）。                                   |
-| CreateTime           | 作业创建时间。                                               |
-| MetaPreparedTime     | 本地元数据生成完成时间。                                     |
-| SnapshotFinishedTime | 快照完成时间。                                               |
-| DownloadFinishedTime | 远端快照下载完成时间。                                       |
-| FinishedTime         | 本次作业完成时间。                                           |
-| UnfinishedTasks      | 在 SNAPSHOTTING、DOWNLOADING、COMMITTING 等阶段，会有多个子任务在同时进行，这里展示的当前段，未完成子任务的 Task ID。 |
-| Progress             | 快照下载任务进展。                                          |
-| TaskErrMsg           | 如果有子任务执行出错，这里会显示对应子任务的错误信息。       |
-| Status               | 用于记录在整个作业过程中，可能出现的一些状态信息。           |
-| Timeout              | 作业的超时时间，单位为秒。                                   |
-
-## 示例
-
-示例一：查看数据库 `example_db` 下最后一次恢复任务。
-
-```SQL
-SHOW RESTORE FROM example_db;
-```
diff --git a/docs/zh/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_SNAPSHOT.md b/docs/zh/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_SNAPSHOT.md
deleted file mode 100644
index 844be8b95f925d..00000000000000
--- a/docs/zh/sql-reference/sql-statements/data-manipulation/backup_restore/SHOW_SNAPSHOT.md
+++ /dev/null
@@ -1,56 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# SHOW SNAPSHOT
-
-## 功能
-
-查看指定仓库中的备份。更多信息，请见 [备份和恢复](../../../../administration/management/Backup_and_restore.md)。
-
-## 语法
-
-```SQL
-SHOW SNAPSHOT ON <repo_name>
-[WHERE SNAPSHOT = <snapshot_name> [AND TIMESTAMP = <backup_timestamp>]]
-```
-
-## 参数说明
-
-| **参数**         | **说明**         |
-| ---------------- | ---------------- |
-| repo_name        | 备份所属仓库名。 |
-| snapshot_nam     | 备份名。         |
-| backup_timestamp | 备份时间戳。     |
-
-## 返回
-
-| **返回**  | **说明**                                    |
-| --------- | ------------------------------------------- |
-| Snapshot  | 备份名。                                    |
-| Timestamp | 备份时间戳。                                |
-| Status    | 如果备份正常，则显示 OK，否则显示错误信息。 |
-| Database  | 备份所属数据库名。                          |
-| Details   | 备份的数据目录及文件结构。JSON 格式。       |
-
-## 示例
-
-示例一：查看仓库 `example_repo` 中已有的备份。
-
-```SQL
-SHOW SNAPSHOT ON example_repo;
-```
-
-示例二：查看仓库 `example_repo` 中名为 `backup1` 的备份。
-
-```SQL
-SHOW SNAPSHOT ON example_repo
-WHERE SNAPSHOT = "backup1";
-```
-
-示例三：查看仓库 `example_repo` 中名为 `backup1` 、时间戳为 `2018-05-05-15-34-26` 的备份。
-
-```SQL
-SHOW SNAPSHOT ON example_repo 
-WHERE SNAPSHOT = "backup1" AND TIMESTAMP = "2018-05-05-15-34-26";
-```
diff --git a/docs/zh/sql-reference/sql-statements/general_DDL.md b/docs/zh/sql-reference/sql-statements/general_DDL.md
deleted file mode 100644
index 342d0399479672..00000000000000
--- a/docs/zh/sql-reference/sql-statements/general_DDL.md
+++ /dev/null
@@ -1,89 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DDL 概览
-
-- [DDL 概览](#ddl-概览)
-  - [CREATE](#create)
-  - [ALTER](#alter)
-  - [DROP](#drop)
-  - [REFRESH](#refresh)
-  - [TRUNCATE TABLE](#truncate-table)
-  - [BACKUP and RESTORE](#backup-and-restore)
-  - [SET](#set)
-  - [CANCEL](#cancel)
-  - [KILL](#kill)
-  - [Utility commands](#utility-commands)
-
-## CREATE
-
-- [ANALYZE TABLE](./data-definition/ANALYZE_TABLE.md)
-- [CREATE ANALYZE](./data-definition/CREATE_ANALYZE.md)
-- [CREATE DATABASE](./data-definition/CREATE_DATABASE.md)
-- [CREATE EXTERNAL CATALOG](./data-definition/CREATE_EXTERNAL_CATALOG.md)
-- [CREATE FUNCTION](./data-definition/CREATE_FUNCTION.md)
-- [CREATE IDEX](./data-definition/CREATE_INDEX.md)
-- [CREATE MATERIALIZED VIEW](./data-definition/CREATE_MATERIALIZED_VIEW.md)
-- [CREATE REPOSITORY](./data-definition/backup_restore/CREATE_REPOSITORY.md)
-- [CREATE RESOURCE](./data-definition/CREATE_RESOURCE.md)
-- [CREATE TABLE](./data-definition/CREATE_TABLE.md)
-- [CREATE TABLE AS SELECT](./data-definition/CREATE_TABLE_AS_SELECT.md)
-- [CREATE TABLE LIKE](./data-definition/CREATE_TABLE_LIKE.md)
-- [CREATE VIEW](./data-definition/CREATE_VIEW.md)
-
-## ALTER
-
-- [ALTER DATABASE](./data-definition/ALTER_DATABASE.md)
-- [ALTER MATERIALIZED VIEW](./data-definition/ALTER_MATERIALIZED_VIEW.md)
-- [ALTER RESOURCE](./data-definition/ALTER_RESOURCE.md)
-- [ALTER TABLE](./data-definition/ALTER_TABLE.md)
-- [ALTER VIEW](./data-definition/ALTER_VIEW.md)
-
-## DROP
-
-- [DROP ANALYZE](./data-definition/DROP_ANALYZE.md)
-- [DROP CATALOG](./data-definition/DROP_CATALOG.md)
-- [DROP DATABASE](./data-definition/DROP_DATABASE.md)
-- [DROP FUNCTION](./data-definition/DROP_FUNCTION.md)
-- [DROP MATERIALIZED VIEW](./data-definition/DROP_MATERIALIZED_VIEW.md)
-- [DROP REPOSITORY](./data-definition/backup_restore/DROP_REPOSITORY.md)
-- [DROP RESOURCE](./data-definition/DROP_RESOURCE.md)
-- [DROP STATS](./data-definition/DROP_STATS.md)
-- [DROP TABLE](./data-definition/DROP_TABLE.md)
-- [DROP VIEW](./data-definition/DROP_VIEW.md)
-
-## REFRESH
-
-- [REFRESH EXTERNAL TABLE](./data-definition/REFRESH_EXTERNAL_TABLE.md)
-- [REFRESH MATERIALIZED VIEW](./data-manipulation/REFRESH_MATERIALIZED_VIEW.md)
-
-## TRUNCATE TABLE
-
-- [TRUNCATE TABLE](./data-definition/TRUNCATE_TABLE.md)
-
-## BACKUP and RESTORE
-
-- [BACKUP](./data-definition/backup_restore/BACKUP.md)
-- [RECOVER](./data-definition/backup_restore/RECOVER.md)
-- [RESTORE](./data-definition/backup_restore/RESTORE.md)
-
-## SET
-
-- [SET CATALOG](./data-definition/SET_CATALOG.md)
-
-## CANCEL
-
-- [CANCEL ALTER TABLE](./data-definition/CANCEL_ALTER_TABLE.md)
-- [CANCEL BACKUP](./data-definition/backup_restore/CANCEL_BACKUP.md)
-- [CANCEL REFRESH MATERIALIZED VIEW](./data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW.md)
-- [CANCEL RESTORE](./data-definition/backup_restore/CANCEL_RESTORE.md)
-
-## KILL
-
-- [KILL ANALYZE](./data-definition/KILL_ANALYZE.md)
-
-## Utility commands
-
-- [USE](../sql-statements/data-definition/USE.md)
-- [DESC](../sql-statements/Utility/DESCRIBE.md)
diff --git a/docs/zh/sql-reference/sql-statements/general_DML.md b/docs/zh/sql-reference/sql-statements/general_DML.md
deleted file mode 100644
index 388c080e827e75..00000000000000
--- a/docs/zh/sql-reference/sql-statements/general_DML.md
+++ /dev/null
@@ -1,91 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# DML 概览
-
-- [DML 概览](#dml-概览)
-  - [导入](#导入)
-  - [导出](#导出)
-  - [ETL 任务](#etl-任务)
-  - [SHOW](#show)
-  - [DELETE](#delete)
-  - [UPDATE](#update)
-  - [SELECT](#select)
-
-## 导入
-
-- [ALTER LOAD](./data-manipulation/ALTER_LOAD.md)
-- [ALTER PIPE](./data-manipulation/ALTER_PIPE.md)
-- [ALTER ROUTINE LOAD](./data-manipulation/ALTER_ROUTINE_LOAD.md)
-- [BROKER LOAD](./data-manipulation/BROKER_LOAD.md)
-- [CANCEL LOAD](./data-manipulation/CANCEL_LOAD.md)
-- [CREATE PIPE](./data-manipulation/CREATE_PIPE.md)
-- [CREATE ROUTINE LOAD](./data-manipulation/CREATE_ROUTINE_LOAD.md)
-- [DROP PIPE](./data-manipulation/DROP_PIPE.md)
-- [INSERT](./data-manipulation/INSERT.md)
-- [PAUSE ROUTINE LOAD](./data-manipulation/PAUSE_ROUTINE_LOAD.md)
-- [RESUME ROUTINE LOAD](./data-manipulation/RESUME_ROUTINE_LOAD.md)
-- [RETRY FILE](./data-manipulation/RETRY_FILE.md)
-- [SHOW LOAD](./data-manipulation/SHOW_LOAD.md)
-- [SHOW PIPES](./data-manipulation/SHOW_PIPES.md)
-- [SHOW ROUTINE LOAD](./data-manipulation/SHOW_ROUTINE_LOAD.md)
-- [SHOW ROUTINE LOAD TASK](./data-manipulation/SHOW_ROUTINE_LOAD_TASK.md)
-- [SHOW TRANSACTION](./data-manipulation/SHOW_TRANSACTION.md)
-- [STOP ROUTINE LOAD](./data-manipulation/STOP_ROUTINE_LOAD.md)
-- [SPARK LOAD](./data-manipulation/SPARK_LOAD.md)
-- [STREAM LOAD](./data-manipulation/STREAM_LOAD.md)
-- [SUSPEND or RESUME PIPE](./data-manipulation/SUSPEND_or_RESUME_PIPE.md)
-
-## 导出
-
-- [EXPORT](./data-manipulation/EXPORT.md)
-- [CANCEL EXPORT](./data-manipulation/CANCEL_EXPORT.md)
-- [SHOW EXPORT](./data-manipulation/SHOW_EXPORT.md)
-
-## ETL 任务
-
-- [DROP TASK](./data-manipulation/DROP_TASK.md)
-- [SUBMIT TASK](./data-manipulation/SUBMIT_TASK.md)
-
-## SHOW
-
-- [SHOW ANALYZE JOB](./data-definition/SHOW_ANALYZE_JOB.md)
-- [SHOW ANALYZE STATUS](./data-definition/SHOW_ANALYZE_STATUS.md)
-- [SHOW ALTER TABLE](./data-manipulation/SHOW_ALTER.md)
-- [SHOW ALTER MATERIALIZED VIEW](./data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW.md)
-- [SHOW BACKUP](./data-manipulation/backup_restore/SHOW_BACKUP.md)
-- [SHOW CATALOGS](./data-manipulation/SHOW_CATALOGS.md)
-- [SHOW CREATE CATALOG](./data-manipulation/SHOW_CREATE_CATALOG.md)
-- [SHOW CREATE DATABASE](./data-manipulation/SHOW_CREATE_DATABASE.md)
-- [SHOW CREATE MATERIALIZED VIEW](./data-manipulation/SHOW_CREATE_MATERIALIZED_VIEW.md)
-- [SHOW CREATE TABLE](./data-manipulation/SHOW_CREATE_TABLE.md)
-- [SHOW CREATE VIEW](./data-manipulation/SHOW_CREATE_VIEW.md)
-- [SHOW DATA](./data-manipulation/SHOW_DATA.md)
-- [SHOW DATABASES](./data-manipulation/SHOW_DATABASES.md)
-- [SHOW DELETE](./data-manipulation/SHOW_DELETE.md)
-- [SHOW DYNAMIC PARTITION TABLES](./data-manipulation/SHOW_DYNAMIC_PARTITION_TABLES.md)
-- [SHOW FULL COLUMNS](./data-manipulation//SHOW_FULL_COLUMNS.md)
-- [SHOW FUNCTIONS](./data-definition/SHOW_FUNCTIONS.md)
-- [SHOW INDEX](./data-manipulation//SHOW_INDEX.md)
-- [SHOW META](./data-definition/SHOW_META.md)
-- [SHOW MATERIALIZED VIEWS](./data-manipulation/SHOW_MATERIALIZED_VIEW.md)
-- [SHOW PARTITIONS](./data-manipulation/SHOW_PARTITIONS.md)
-- [SHOW REPOSITORIES](./data-manipulation/backup_restore/SHOW_REPOSITORIES.md)
-- [SHOW RESOURCES](./data-definition/SHOW_RESOURCES.md)
-- [SHOW RESTORE](./data-manipulation/backup_restore/SHOW_RESTORE.md)
-- [SHOW SNAPSHOT](./data-manipulation/backup_restore/SHOW_SNAPSHOT.md)
-- [SHOW TABLES](./data-manipulation/SHOW_TABLES.md)
-- [SHOW TABLET](./data-manipulation/SHOW_TABLET.md)
-
-## DELETE
-
-- [DELETE](./data-manipulation/DELETE.md)
-
-## UPDATE
-
-- [UPDATE](./data-manipulation/UPDATE.md)
-
-## SELECT
-
-- [SELECT](./data-manipulation/SELECT.md)
diff --git a/docs/zh/sql-reference/sql-statements/generated_columns.md b/docs/zh/sql-reference/sql-statements/generated_columns.md
index 2df0467ee10c0a..58e36f0c0cca49 100644
--- a/docs/zh/sql-reference/sql-statements/generated_columns.md
+++ b/docs/zh/sql-reference/sql-statements/generated_columns.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 生成列
@@ -43,7 +43,7 @@ DISTRIBUTED BY HASH(id);
 
 - 生成列必须在普通列之后。
 - 生成列的表达式不支持使用聚合函数。
-- 生成列的表达式中不能引用其他生成列或[自增列](./auto_increment.md)，可以引用多个普通列。
+- 生成列的表达式中不能引用其他生成列或[自增列](table_bucket_part_index/auto_increment.md)，可以引用多个普通列。
 - 生成列的数据类型必须与表达式返回结果的数据类型相匹配。
 - 不支持在聚合表创建生成列。
 
@@ -329,7 +329,7 @@ ALTER TABLE test_tbl3 DROP COLUMN newcol1;
       2|[3,4]|{"a": 3, "b": 4} 
       ```
 
-3. 通过 [Stream Load](../sql-statements/data-manipulation/STREAM_LOAD.md) 使用 CSV 文件 `my_data1.csv` 更新表 `test_tbl5` 的部分列。您需要设置 `"partial_update:true"`，并且必须在 `columns` 中指定生成列引用的所有普通列。
+3. 通过 [Stream Load](loading_unloading/STREAM_LOAD.md) 使用 CSV 文件 `my_data1.csv` 更新表 `test_tbl5` 的部分列。您需要设置 `"partial_update:true"`，并且必须在 `columns` 中指定生成列引用的所有普通列。
 
       ```Bash
       curl --location-trusted -u <username>:<password> -H "label:1" \
@@ -362,7 +362,7 @@ ALTER TABLE test_tbl3 DROP COLUMN newcol1;
       2|[3,4]
       ```
 
-2. 通过 [Stream Load](../sql-statements/data-manipulation/STREAM_LOAD.md) 使用 CSV 文件 `my_data2.csv` 进行部分列更新。`my_data2.csv` 中没有提供  `data_json` 列的值，并且 Stream Load 导入作业中 `columns` 参数没有包含 `data_json` 列，即使`data_json` 列允许为空，但是因为生成列 `newcol2` 引用了 `data_json` 列，则 Stream Load 会返回报错。
+2. 通过 [Stream Load](loading_unloading/STREAM_LOAD.md) 使用 CSV 文件 `my_data2.csv` 进行部分列更新。`my_data2.csv` 中没有提供  `data_json` 列的值，并且 Stream Load 导入作业中 `columns` 参数没有包含 `data_json` 列，即使`data_json` 列允许为空，但是因为生成列 `newcol2` 引用了 `data_json` 列，则 Stream Load 会返回报错。
 
       ```SQL
       $ curl --location-trusted -u root: -H "label:2" \
diff --git a/docs/zh/sql-reference/sql-statements/keywords.md b/docs/zh/sql-reference/sql-statements/keywords.md
index de516f7b4d34f4..2fa38c69288ed0 100644
--- a/docs/zh/sql-reference/sql-statements/keywords.md
+++ b/docs/zh/sql-reference/sql-statements/keywords.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 关键字
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/ALTER_LOAD.md b/docs/zh/sql-reference/sql-statements/loading_unloading/ALTER_LOAD.md
new file mode 100644
index 00000000000000..e781edc90de5bb
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/ALTER_LOAD.md
@@ -0,0 +1,43 @@
+---
+keywords: ['xiugai'] 
+displayed_sidebar: docs
+---
+
+# ALTER LOAD
+
+## 功能
+
+修改 **QUEUEING** 或者 **LOADING** 状态的 Broker Load 作业的优先级。StarRocks 自 v2.5 版本起支持该命令。
+
+> **说明**
+>
+> 修改处于 **LOADING** 状态的 Broker Load 作业的优先级不会对作业产生任何影响。
+
+## 语法
+
+```SQL
+ALTER LOAD FOR <label_name>
+PROPERTIES
+(
+    'priority'='{LOWEST | LOW | NORMAL | HIGH | HIGHEST}'
+)
+```
+
+## 参数说明
+
+| **参数**   | **是否必选** | **说明**                                                     |
+| ---------- | ------------ | ------------------------------------------------------------ |
+| label_name | 是           | 指定导入作业的标签。格式：`[<database_name>.]<label_name>`。参见 [BROKER LOAD](BROKER_LOAD.md#database_name-和-label_name)。 |
+| priority   | 是           | 指定导入作业的优先级。取值范围：`LOWEST`、`LOW`、`NORMAL`、`HIGH` 和 `HIGHEST`。参见 [BROKER LOAD](BROKER_LOAD.md#opt_properties)。 |
+
+## 示例
+
+假设您有一个标签为 `test_db.label1` 的 Broker Load 作业，且作业当前处于 **QUEUEING** 状态或者 **LOADING** 状态。如果您想尽快执行该作业，可以通过如下命令，把该作业的优先级改为 `HIGHEST`：
+
+```SQL
+ALTER LOAD FOR test_db.label1
+PROPERTIES
+(
+    'priority'='HIGHEST'
+);
+```
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md b/docs/zh/sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md
new file mode 100644
index 00000000000000..cc266b73999d92
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md
@@ -0,0 +1,1346 @@
+---
+displayed_sidebar: docs
+toc_max_heading_level: 5
+---
+
+# BROKER LOAD
+
+## 功能
+
+Broker Load 是一种基于 MySQL 协议的异步导入方式。您提交导入作业以后，StarRocks 会异步地执行导入作业。您可以使用 `SELECT * FROM information_schema.loads` 来查看 Broker Load 作业的结果，该功能自 3.1 版本起支持。有关 Broker Load 的背景信息、基本原理、支持的数据文件格式、如何执行单表导入 (Single-Table Load) 和多表导入 (Multi-Table Load) 操作、以及如何查看导入作业的结果等信息，请参见[从 HDFS 导入](../../../loading/hdfs_load.md)和[从云存储导入](../../../loading/cloud_storage_load.md)。
+
+> **注意**
+>
+> Broker Load 操作需要目标表的 INSERT 权限。如果您的用户账号没有 INSERT 权限，请参考 [GRANT](../account-management/GRANT.md) 给用户赋权。
+
+## 语法
+
+```SQL
+LOAD LABEL [<database_name>.]<label_name>
+(
+    data_desc[, data_desc ...]
+)
+WITH BROKER
+(
+    StorageCredentialParams
+)
+[PROPERTIES
+(
+    opt_properties
+)
+]
+```
+
+注意在 StarRocks 中，部分文字是 SQL 语言的保留关键字，不能直接用于 SQL 语句。如果想在 SQL 语句中使用这些保留关键字，必须用反引号 (`) 包裹起来。参见[关键字](../keywords.md)。
+
+## 参数说明
+
+### database_name 和 label_name
+
+`label_name` 指定导入作业的标签。命名要求参见[系统限制](../../System_limit.md)。
+
+`database_name` 为可选，指定目标 StarRocks 表所在的数据库。
+
+每个导入作业都对应一个在该数据库内唯一的标签。通过标签，可以查看对应导入作业的执行情况，并防止导入相同的数据。导入作业的状态为 **FINISHED** 时，其标签不可再复用给其他导入作业。导入作业的状态为 **CANCELLED** 时，其标签可以复用给其他导入作业，但通常都是用来重试同一个导入作业（即使用同一个标签导入相同的数据）以实现数据“精确一次 (Exactly-Once)”语义。
+
+### data_desc
+
+用于描述一批次待导入的数据。每个 `data_desc` 声明了本批次待导入数据所属的数据源地址、ETL 函数、StarRocks 表和分区等信息。
+
+Broker Load 支持一次导入多个数据文件。在一个导入作业中，您可以使用多个 `data_desc` 来声明导入多个数据文件，也可以使用一个 `data_desc` 来声明导入一个路径下的所有数据文件。Broker Load 还支持保证单次导入事务的原子性，即单次导入的多个数据文件都成功或者都失败，而不会出现部分导入成功、部分导入失败的情况。
+
+`data_desc` 语法如下：
+
+```SQL
+DATA INFILE ("<file_path>"[, "<file_path>" ...])
+[NEGATIVE]
+INTO TABLE <table_name>
+[PARTITION (<partition1_name>[, <partition2_name> ...])]
+[TEMPORARY PARTITION (<temporary_partition1_name>[, <temporary_partition2_name> ...])]
+[COLUMNS TERMINATED BY "<column_separator>"]
+[ROWS TERMINATED BY "<row_separator>"]
+[FORMAT AS "CSV | Parquet | ORC"]
+[(format_type_options)]
+[(column_list)]
+[COLUMNS FROM PATH AS (<partition_field_name>[, <partition_field_name> ...])]
+[SET <k1=f1(v1)>[, <k2=f2(v2)> ...]]
+[WHERE predicate]
+```
+
+`data_desc` 中的必选参数如下：
+
+- `file_path`
+
+  用于指定源数据文件所在的路径。
+
+  您可以指定导入一个具体的数据文件。例如，通过指定 `"hdfs://<hdfs_host>:<hdfs_port>/user/data/tablename/20210411"` 可以匹配 HDFS 服务器上 `/user/data/tablename` 目录下名为 `20210411` 的数据文件。
+
+  您也可以用通配符指定导入某个路径下所有的数据文件。Broker Load 支持如下通配符：`?`、`*`、`[]`、`{}` 和 `^`。具体请参见[通配符使用规则参考](https://hadoop.apache.org/docs/stable/api/org/apache/hadoop/fs/FileSystem.html#globStatus-org.apache.hadoop.fs.Path-)。例如， 通过指定 `"hdfs://<hdfs_host>:<hdfs_port>/user/data/tablename/*/*"` 路径可以匹配 HDFS 服务器上 `/user/data/tablename` 目录下所有分区内的数据文件，通过 `"hdfs://<hdfs_host>:<hdfs_port>/user/data/tablename/dt=202104*/*"` 路径可以匹配 HDFS 服务器上 `/user/data/tablename` 目录下所有 `202104` 分区内的数据文件。
+
+  > **说明**
+  >
+  > 中间的目录也可以使用通配符匹配。
+
+  以 HDFS 数据源为例，文件路径中的 `hdfs_host` 和 `hdfs_port` 参数说明如下：
+
+  - `hdfs_host`：HDFS 集群中 NameNode 所在主机的 IP 地址。
+  - `hdfs_port`：HDFS 集群中 NameNode 所在主机的 FS 端口。默认端口号为 `9000`。
+
+  > **注意**
+  >
+  > - Broker Load 支持通过 S3 或 S3A 协议访问 AWS S3，因此从 AWS S3 导入数据时，您在文件路径中传入的目标文件的 S3 URI 可以使用 `s3://` 或 `s3a://` 作为前缀。
+  > - 由于 Broker Load 只支持通过 gs 协议访问 Google GCS，因此当从 Google GCS 导入数据时，必须确保文件路径传入的目标文件的 GCS URI 使用 `gs://` 为前缀。
+  > - 从 Blob Storage 导入数据时，需要使用 wasb 或 wasbs 作为文件协议访问目标数据：
+  >   - 如果您的存储账号支持通过 HTTP 协议进行访问，请使用 wasb 文件协议，文件路径格式为 `wasb://<container_name>@<storage_account_name>.blob.core.windows.net/<path>/<file_name>/*`。
+  >   - 如果您的存储账号支持通过 HTTPS 协议进行访问，请使用 wasbs 文件协议，文件路径格式为 `wasbs://<container_name>@<storage_account_name>.blob.core.windows.net/<path>/<file_name>/*`。
+  > - 从 Data Lake Storage Gen2 导入数据时，需要使用 abfs 或 abfss 作为文件协议访问目标数据：
+  >   - 如果您的存储账号支持通过 HTTP 协议进行访问，请使用 abfs 文件协议，文件路径格式为 `abfs://<container_name>@<storage_account_name>.dfs.core.windows.net/<file_name>`。
+  >   - 如果您的存储账号支持通过 HTTPS 协议进行访问，请使用 abfss 文件协议，文件路径格式为 `abfss://<container_name>@<storage_account_name>.dfs.core.windows.net/<file_name>`。
+  > - 从 Azure Data Lake Storage Gen1 导入数据时，需要使用 adl 作为文件协议访问目标数据，文件路径格式为 `adl://<data_lake_storage_gen1_name>.azuredatalakestore.net/<path>/<file_name>`。
+  
+- `INTO TABLE`
+
+  用于指定目标 StarRocks 表的名称。
+
+`data_desc` 中的可选参数如下：
+
+- `NEGATIVE`
+
+  用于撤销某一批已经成功导入的数据。如果想要撤销某一批已经成功导入的数据，可以通过指定 `NEGATIVE` 关键字来导入同一批数据。
+
+  > **说明**
+  >
+  > 该参数仅适用于目标 StarRocks 表使用聚合表、并且所有 Value 列的聚合函数均为 `sum` 的情况。
+
+- `PARTITION`
+
+  指定要把数据导入哪些分区。如果不指定该参数，则默认导入到 StarRocks 表所在的所有分区中。
+
+- `TEMPORARY_PARTITION`
+
+  指定要把数据导入哪些[临时分区](../../../table_design/Temporary_partition.md)。
+
+- `COLUMNS TERMINATED BY`
+
+  用于指定源数据文件中的列分隔符。如果不指定该参数，则默认列分隔符为 `\t`，即 Tab。必须确保这里指定的列分隔符与源数据文件中的列分隔符一致；否则，导入作业会因数据质量错误而失败，作业状态 (`State`) 会显示为 `CANCELLED`。
+
+  需要注意的是，Broker Load 通过 MySQL 协议提交导入请求，除了 StarRocks 会做转义处理以外，MySQL 协议也会做转义处理。因此，如果列分隔符是 Tab 等不可见字符，则需要在列分隔字符前面多加一个反斜线 (\\)。例如，如果列分隔符是 `\t`，这里必须输入 `\\t`；如果列分隔符是 `\n`，这里必须输入 `\\n`。Apache Hive™ 文件的列分隔符为 `\x01`，因此，如果源数据文件是 Hive 文件，这里必须传入 `\\x01`。
+
+  > **说明**
+  >
+  > - StarRocks 支持设置长度最大不超过 50 个字节的 UTF-8 编码字符串作为列分隔符，包括常见的逗号 (,)、Tab 和 Pipe (|)。
+  > - 空值 (null) 用 `\N` 表示。比如，数据文件一共有三列，其中某行数据的第一列、第三列数据分别为 `a` 和 `b`，第二列没有数据，则第二列需要用 `\N` 来表示空值，写作 `a,\N,b`，而不是 `a,,b`。`a,,b` 表示第二列是一个空字符串。
+
+- `ROWS TERMINATED BY`
+
+  用于指定源数据文件中的行分隔符。如果不指定该参数，则默认行分隔符为 `\n`，即换行符。必须确保这里指定的行分隔符与源数据文件中的行分隔符一致；否则，导入作业会因数据质量错误而失败，作业状态 (`State`) 会显示为 `CANCELLED`。该参数从 2.5.4 版本开始支持。
+
+  其他注意事项和使用条件与上文通过 `COLUMNS TERMINATED BY` 指定列分隔符相同。
+
+- `FORMAT AS`
+
+  用于指定源数据文件的格式。取值包括 `CSV`、`Parquet` 和 `ORC`。如果不指定该参数，则默认通过 `file_path` 参数中指定的文件扩展名（**.csv**、**.parquet**、和 **.orc**）来判断文件格式。
+
+- `format_type_options`
+
+  `FORMAT AS` 设置为 `CSV` 时用于指定 CSV 格式选项。语法如下：
+
+  ```JSON
+  (
+      key = value
+      key = value
+      ...
+  )
+  ```
+  
+  > **说明**
+  >
+  > `format_type_options` 在 3.0 及以后版本支持。
+
+  选项说明见下表。
+  
+  | **参数**    | **说明**                                                     |
+  | ----------- | ------------------------------------------------------------ |
+  | skip_header | 用于指定跳过 CSV 文件最开头的几行数据。取值类型：INTEGER。默认值：`0`。<br />在某些 CSV 文件里，最开头的几行数据会用来定义列名、列类型等元数据信息。通过设置该参数，可以使 StarRocks 在导入数据时忽略 CSV 文件的前面几行。例如，如果设置该参数为 `1`，则 StarRocks 会在导入数据时忽略 CSV 文件的第一行。<br />这里的行所使用的分隔符须与您在导入语句中所设定的行分隔符一致。 |
+  | trim_space  | 用于指定是否去除 CSV 文件中列分隔符前后的空格。取值类型：BOOLEAN。默认值：`false`。<br />有些数据库在导出数据为 CSV 文件时，会在列分隔符的前后添加一些空格。根据位置的不同，这些空格可以称为“前导空格”或者“尾随空格”。通过设置该参数，可以使 StarRocks 在导入数据时删除这些不必要的空格。<br />需要注意的是，StarRocks 不会去除被 `enclose` 指定字符括起来的字段内的空格（包括字段的前导空格和尾随空格）。例如，列分隔符是竖线 (<code class="language-text">&#124;</code>)，`enclose` 指定的字符是双引号 (`"`)：<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124; "Love StarRocks" &#124;</code> <br />如果设置 `trim_space` 为 `true`，则 StarRocks 处理后的结果数据如下：<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> |
+  | enclose     | 根据 [RFC4180](https://www.rfc-editor.org/rfc/rfc4180)，用于指定把 CSV 文件中的字段括起来的字符。取值类型：单字节字符。默认值：`NONE`。最常用 `enclose` 字符为单引号 (`'`) 或双引号 (`"`)。<br />被 `enclose` 指定字符括起来的字段内的所有特殊字符（包括行分隔符、列分隔符等）均看做是普通符号。比 RFC4180 标准更进一步的是，StarRocks 提供的 `enclose` 属性支持设置任意单个字节的字符。<br />如果一个字段内包含了 `enclose` 指定字符，则可以使用同样的字符对 `enclose` 指定字符进行转义。例如，在设置了`enclose` 为双引号 (`"`) 时，字段值 `a "quoted" c` 在 CSV 文件中应该写作 `"a ""quoted"" c"`。 |
+  | escape      | 指定用于转义的字符。用来转义各种特殊字符，比如行分隔符、列分隔符、转义符、`enclose` 指定字符等，使 StarRocks 把这些特殊字符当做普通字符而解析成字段值的一部分。取值类型：单字节字符。默认值：`NONE`。最常用的 `escape` 字符为斜杠 (`\`)，在 SQL 语句中应该写作双斜杠 (`\\`)。<br />**说明**<br />`escape` 指定字符同时作用于 `enclose` 指定字符的内部和外部。<br />以下为两个示例：<ul><li>当设置 `enclose` 为双引号 (`"`) 、`escape` 为斜杠 (`\`) 时，StarRocks 会把 `"say \"Hello world\""` 解析成一个字段值 `say "Hello world"`。</li><li>假设列分隔符为逗号 (`,`) ，当设置 `escape` 为斜杠 (`\`) ，StarRocks 会把 `a, b\, c` 解析成 `a` 和 `b, c` 两个字段值。</li></ul> |
+
+- `column_list`
+
+  用于指定源数据文件和 StarRocks 表之间的列对应关系。语法如下：`(<column_name>[, <column_name> ...])`。`column_list` 中声明的列与 StarRocks 表中的列按名称一一对应。
+
+  > **说明**
+  >
+  > 如果源数据文件的列和 StarRocks 表中的列按顺序一一对应，则不需要指定 `column_list` 参数。
+
+  如果要跳过源数据文件中的某一列，只需要在 `column_list` 参数中将该列命名为 StarRocks 表中不存在的列名即可。具体请参见[导入过程中实现数据转换](../../../loading/Etl_in_loading.md)。
+
+- `COLUMNS FROM PATH AS`
+
+  用于从指定的文件路径中提取一个或多个分区字段的信息。该参数仅当指定的文件路径中存在分区字段时有效。
+
+  例如，源数据文件所在的路径为 `/path/col_name=col_value/file1`，其中 `col_name` 可以对应到 StarRocks 表中的列。这时候，您可以设置参数为 `col_name`。导入时，StarRocks 会将 `col_value` 落入 `col_name` 对应的列中。
+
+  > **说明**
+  >
+  > 该参数只有在从 HDFS 导入数据时可用。
+
+- `SET`
+
+  用于将源数据文件的某一列按照指定的函数进行转化，然后将转化后的结果落入 StarRocks 表中。语法如下：`column_name = expression`。以下为两个示例：
+
+  - StarRocks 表中有三列，按顺序依次为 `col1`、`col2` 和 `col3`；源数据文件中有四列，前两列按顺序依次对应 StarRocks 表中的 `col1`、`col2` 列，后两列之和对应 StarRocks 表中的 `col3` 列。这种情况下，需要通过 `column_list` 参数声明 `(col1,col2,tmp_col3,tmp_col4)`，并使用 SET 子句指定 `SET (col3=tmp_col3+tmp_col4)` 来实现数据转换。
+  - StarRocks 表中有三列，按顺序依次为 `year`、`month` 和 `day`；源数据文件中只有一个包含时间数据的列，格式为 `yyyy-mm-dd hh:mm:ss`。这种情况下，需要通过 `column_list` 参数声明 `(tmp_time)`、并使用 SET 子句指定 `SET (year = year(tmp_time), month=month(tmp_time), day=day(tmp_time))` 来实现数据转换。
+
+- `WHERE`
+
+  用于指定过滤条件，对做完转换的数据进行过滤。只有符合 WHERE 子句中指定的过滤条件的数据才会导入到 StarRocks 表中。
+
+### WITH BROKER
+
+自 v2.5 起，您不再需要指定 `broker_name`，但继续保留 `WITH BROKER` 关键字。
+
+### StorageCredentialParams
+
+StarRocks 访问存储系统的认证配置。
+
+#### HDFS
+
+社区版 HDFS 支持简单认证和 Kerberos 认证两种认证方式（Broker Load 默认使用简单认证），并且支持 NameNode 节点的 HA 配置。如果存储系统为社区版 HDFS，您可以按如下指定认证方式和 HA 配置：
+
+- 认证方式
+
+  - 如果使用简单认证，请按如下配置 `StorageCredentialParams`：
+
+    ```Plain
+    "hadoop.security.authentication" = "simple",
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+    ```
+
+    `StorageCredentialParams` 包含如下参数。
+
+    | **参数名称**                     | **参数说明**                                 |
+    | ------------------------------- | -------------------------------------------- |
+    | hadoop.security.authentication  | 指定认证方式。取值范围：`simple` 和 `kerberos`。默认值：`simple`。`simple` 表示简单认证，即无认证。`kerberos` 表示 Kerberos 认证。 |
+    | username                        | 用于访问 HDFS 集群中 NameNode 节点的用户名。 |
+    | password                        | 用于访问 HDFS 集群中 NameNode 节点的密码。   |
+
+  - 如果使用 Kerberos 认证，请按如下配置 `StorageCredentialParams`：
+
+    ```Plain
+    "hadoop.security.authentication" = "kerberos",
+    "kerberos_principal" = "nn/zelda1@ZELDA.COM",
+    "kerberos_keytab" = "/keytab/hive.keytab",
+    "kerberos_keytab_content" = "YWFhYWFh"
+    ```
+
+    `StorageCredentialParams` 包含如下参数。
+
+    | **参数名称**                     | **参数说明**                                                 |
+    | ------------------------------- | ------------------------------------------------------------ |
+    | hadoop.security.authentication  | 指定认证方式。取值范围：`simple` 和 `kerberos`。默认值：`simple`。`simple` 表示简单认证，即无认证。`kerberos` 表示 Kerberos 认证。 |
+    | kerberos_principal              | 用于指定 Kerberos 的用户或服务 (Principal)。每个 Principal 在 HDFS 集群内唯一，由如下三部分组成：<ul><li>`username` 或 `servicename`：HDFS 集群中用户或服务的名称。</li><li>`instance`：HDFS 集群要认证的节点所在服务器的名称，用来保证用户或服务全局唯一。比如，HDFS 集群中有多个 DataNode 节点，各节点需要各自独立认证。</li><li>`realm`：域，必须全大写。</li></ul>举例：`nn/zelda1@ZELDA.COM`。 |
+    | kerberos_keytab                 | 用于指定 Kerberos 的 Key Table（简称为“keytab”）文件的路径。 |
+    | kerberos_keytab_content         | 用于指定 Kerberos 中 keytab 文件的内容经过 Base64 编码之后的内容。该参数跟 `kerberos_keytab` 参数二选一配置。 |
+
+- HA 配置
+
+  可以为 HDFS 集群中的 NameNode 节点配置 HA 机制，从而确保发生 NameNode 节点切换时，StarRocks 能够自动识别新切换到的 NameNode 节点，包括如下几种场景：
+
+  - 在单 HDFS 集群、并且配置了单 Kerberos 用户的场景下，可以采用有 Broker 的导入，也可以采用无 Broker 的导入。
+  
+    - 如果采用有 Broker 的导入，您需要确保至少部署了一组独立的 Broker，并将 `hdfs-site.xml` 文件放在 HDFS 集群对应的 Broker 节点的 `{deploy}/conf` 目录下。Broker 进程重启时，会将 `{deploy}/conf` 目录添加到 `CLASSPATH` 环境变量，使 Broker 能够读取 HDFS 集群中各节点的信息。
+  
+    - 如果采用无 Broker 的导入，您需要将 `hdfs-site.xml` 文件放在每个 FE 节点和每个 BE（或 CN）节点的 `{deploy}/conf` 目录下。
+
+  - 在单 HDFS 集群、并且配置了多 Kerberos 用户的场景下，只支持有 Broker 的导入。您需要确保至少部署了一组独立的 Broker，并将 `hdfs-site.xml` 文件放在 HDFS 集群对应的 Broker 节点的 `{deploy}/conf` 目录下。Broker 进程重启时，会将 `{deploy}/conf` 目录添加到 `CLASSPATH` 环境变量，使 Broker 能够读取 HDFS 集群中各节点的信息。
+
+  - 在多 HDFS 集群场景下（不管是单 Kerberos 用户、还是多 Kerberos 用户），只支持有 Broker 的导入。您需要确保至少部署了一组独立的 Broker，并且采取如下方法之一来配置 Broker 读取 HDFS 集群中各节点的信息：
+  
+    - 将 `hdfs-site.xml` 文件放在每个 HDFS 集群对应的 Broker 节点的 `{deploy}/conf` 目录下。Broker 进程重启时，会将 `{deploy}/conf` 目录添加到 `CLASSPATH` 环境变量，使 Broker 能够读取 HDFS 集群中各节点的信息。
+    - 在创建 Broker Load 作业时增加如下 HA 配置：
+
+      ```Plain
+      "dfs.nameservices" = "ha_cluster",
+      "dfs.ha.namenodes.ha_cluster" = "ha_n1,ha_n2",
+      "dfs.namenode.rpc-address.ha_cluster.ha_n1" = "<hdfs_host>:<hdfs_port>",
+      "dfs.namenode.rpc-address.ha_cluster.ha_n2" = "<hdfs_host>:<hdfs_port>",
+      "dfs.client.failover.proxy.provider" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
+      ```
+
+      上述配置中的参数说明如下表所述：
+
+      | **参数名称**                         | **参数说明**                                                 |
+      | ------------------------------------------------------- | --------------------------- |
+      | dfs.nameservices                  | 自定义 HDFS 集群的名称。                                     |
+      | dfs.ha.namenodes.XXX              | 自定义 NameNode 的名称，多个名称以逗号 (,) 分隔，双引号内不允许出现空格。  <br />其中 `xxx` 为 `dfs.nameservices` 中自定义的HDFS 服务的名称。 |
+      | dfs.namenode.rpc-address.XXX.NN    | 指定 NameNode 的 RPC 地址信息。  <br />其中 `NN` 表示 `dfs.ha.namenodes.XXX` 中自定义 NameNode 的名称。 |
+      | dfs.client.failover.proxy.provider | 指定客户端连接的 NameNode 的提供者，默认为 `org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider`。 |
+
+  > **说明**
+  >
+  > 您可以通过 [SHOW BROKER](../cluster-management/nodes_processes/SHOW_BROKER.md) 语句来查看 StarRocks 集群中已经部署的 Broker。
+
+#### AWS S3
+
+如果存储系统为 AWS S3，请按如下配置 `StorageCredentialParams`：
+
+- 基于 Instance Profile 进行认证和鉴权
+
+  ```SQL
+  "aws.s3.use_instance_profile" = "true",
+  "aws.s3.region" = "<aws_s3_region>"
+  ```
+
+- 基于 Assumed Role 进行认证和鉴权
+
+  ```SQL
+  "aws.s3.use_instance_profile" = "true",
+  "aws.s3.iam_role_arn" = "<iam_role_arn>",
+  "aws.s3.region" = "<aws_s3_region>"
+  ```
+
+- 基于 IAM User 进行认证和鉴权
+
+  ```SQL
+  "aws.s3.use_instance_profile" = "false",
+  "aws.s3.access_key" = "<iam_user_access_key>",
+  "aws.s3.secret_key" = "<iam_user_secret_key>",
+  "aws.s3.region" = "<aws_s3_region>"
+  ```
+
+`StorageCredentialParams` 包含如下参数。
+
+| 参数                        | 是否必须   | 说明                                                         |
+| --------------------------- | -------- | ------------------------------------------------------------ |
+| aws.s3.use_instance_profile | 是       | 指定是否开启 Instance Profile 和 Assumed Role 两种鉴权方式。取值范围：`true` 和 `false`。默认值：`false`。 |
+| aws.s3.iam_role_arn         | 否       | 有权限访问 AWS S3 Bucket 的 IAM Role 的 ARN。采用 Assumed Role 鉴权方式访问 AWS S3 时，必须指定此参数。 |
+| aws.s3.region               | 是       | AWS S3 Bucket 所在的地域。示例：`us-west-1`。                |
+| aws.s3.access_key           | 否       | IAM User 的 Access Key。采用 IAM User 鉴权方式访问 AWS S3 时，必须指定此参数。 |
+| aws.s3.secret_key           | 否       | IAM User 的 Secret Key。采用 IAM User 鉴权方式访问 AWS S3 时，必须指定此参数。 |
+
+有关如何选择用于访问 AWS S3 的鉴权方式、以及如何在 AWS IAM 控制台配置访问控制策略，参见[访问 AWS S3 的认证参数](../../../integrations/authenticate_to_aws_resources.md#访问-aws-s3-的认证参数)。
+
+#### Google GCS
+
+如果存储系统为 Google GCS，请按如下配置 `StorageCredentialParams`：
+
+- 基于 VM 进行认证和鉴权
+
+  ```SQL
+  "gcp.gcs.use_compute_engine_service_account" = "true"
+  ```
+
+  `StorageCredentialParams` 包含如下参数。
+
+  | **参数**                                   | **默认值** | **取值样例** | **说明**                                                 |
+  | ------------------------------------------ | ---------- | ------------ | -------------------------------------------------------- |
+  | gcp.gcs.use_compute_engine_service_account | false      | true         | 是否直接使用 Compute Engine 上面绑定的 Service Account。 |
+
+- 基于 Service Account 号进行认证和鉴权
+
+  ```SQL
+  "gcp.gcs.service_account_email" = "<google_service_account_email>",
+  "gcp.gcs.service_account_private_key_id" = "<google_service_private_key_id>",
+  "gcp.gcs.service_account_private_key" = "<google_service_private_key>"
+  ```
+
+  `StorageCredentialParams` 包含如下参数。
+
+  | **参数**                               | **默认值** | **取值样例**                                                 | **说明**                                                     |
+  | -------------------------------------- | ---------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
+  | gcp.gcs.service_account_email          | ""         | `"user@hello.iam.gserviceaccount.com"` | 创建 Service Account 时生成的 JSON 文件中的 Email。          |
+  | gcp.gcs.service_account_private_key_id | ""         | "61d257bd8479547cb3e04f0b9b6b9ca07af3b7ea"                   | 创建 Service Account 时生成的 JSON 文件中的 Private Key ID。 |
+  | gcp.gcs.service_account_private_key    | ""         | "-----BEGIN PRIVATE KEY----xxxx-----END PRIVATE KEY-----\n"  | 创建 Service Account 时生成的 JSON 文件中的 Private Key。    |
+
+- 基于 Impersonation 进行认证和鉴权
+
+  - 使用 VM 实例模拟 Service Account
+
+    ```SQL
+    "gcp.gcs.use_compute_engine_service_account" = "true",
+    "gcp.gcs.impersonation_service_account" = "<assumed_google_service_account_email>"
+    ```
+
+    `StorageCredentialParams` 包含如下参数。
+
+    | **参数**                                   | **默认值** | **取值样例** | **说明**                                                     |
+    | ------------------------------------------ | ---------- | ------------ | ------------------------------------------------------------ |
+    | gcp.gcs.use_compute_engine_service_account | false      | true         | 是否直接使用 Compute Engine 上面绑定的 Service Account。     |
+    | gcp.gcs.impersonation_service_account      | ""         | "hello"      | 需要模拟的目标 Service Account。 |
+
+  - 使用一个 Service Account（即“Meta Service Account”）模拟另一个 Service Account（即“Data Service Account”）
+
+    ```SQL
+    "gcp.gcs.service_account_email" = "<google_service_account_email>",
+    "gcp.gcs.service_account_private_key_id" = "<meta_google_service_account_email>",
+    "gcp.gcs.service_account_private_key" = "<meta_google_service_account_email>",
+    "gcp.gcs.impersonation_service_account" = "<data_google_service_account_email>"
+    ```
+
+    `StorageCredentialParams` 包含如下参数。
+
+    | **参数**                               | **默认值** | **取值样例**                                                 | **说明**                                                     |
+    | -------------------------------------- | ---------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
+    | gcp.gcs.service_account_email          | ""         | `"user@hello.iam.gserviceaccount.com"` | 创建 Meta Service Account 时生成的 JSON 文件中的 Email。     |
+    | gcp.gcs.service_account_private_key_id | ""         | "61d257bd8479547cb3e04f0b9b6b9ca07af3b7ea"                   | 创建 Meta Service Account 时生成的 JSON 文件中的 Private Key ID。 |
+    | gcp.gcs.service_account_private_key    | ""         | "-----BEGIN PRIVATE KEY----xxxx-----END PRIVATE KEY-----\n"  | 创建 Meta Service Account 时生成的 JSON 文件中的 Private Key。 |
+    | gcp.gcs.impersonation_service_account  | ""         | "hello"                                                      | 需要模拟的目标 Data Service Account。 |
+
+#### 阿里云 OSS
+
+如果存储系统为阿里云 OSS，请按如下配置 `StorageCredentialParams`：
+
+```SQL
+"fs.oss.accessKeyId" = "<oss_access_key>",
+"fs.oss.accessKeySecret" = "<oss_secret_key>",
+"fs.oss.endpoint" = "<oss_endpoint>"
+```
+
+`StorageCredentialParams` 包含如下参数。
+
+| **参数名称**           | **参数说明**                                                 |
+| ---------------------- | ------------------------------------------------------------ |
+| fs.oss.accessKeyId     | 访问阿里云 OSS 存储空间的 AccessKey ID，用于标识用户。           |
+| fs.oss.accessKeySecret | 访问阿里云 OSS 存储空间的 AccessKey Secret，是用于加密签名字符串和 OSS 用来验证签名字符串的密钥。 |
+| fs.oss.endpoint        | 访问阿里云 OSS 存储空间的连接地址。                              |
+
+请参见阿里云官方文档[用户签名验证](https://help.aliyun.com/document_detail/31950.html)。
+
+#### 腾讯云 COS
+
+如果存储系统为腾讯云 COS，请按如下配置 `StorageCredentialParams`：
+
+```SQL
+"fs.cosn.userinfo.secretId" = "<cos_access_key>",
+"fs.cosn.userinfo.secretKey" = "<cos_secret_key>",
+"fs.cosn.bucket.endpoint_suffix" = "<cos_endpoint>"
+```
+
+`StorageCredentialParams` 包含如下参数。
+
+| **参数名称**                   | **参数说明**                                                 |
+| ------------------------------ | ------------------------------------------------------------ |
+| fs.cosn.userinfo.secretId      | 访问腾讯云 COS 存储空间的 SecretId，用于标识 API 调用者的身份。  |
+| fs.cosn.userinfo.secretKey     | 访问腾讯云 COS 存储空间的 SecretKey，是用于加密签名字符串和服务端验证签名字符串的密钥。 |
+| fs.cosn.bucket.endpoint_suffix | 访问腾讯云 COS 存储空间的连接地址。                              |
+
+请参见腾讯云官方文档[使用永久密钥访问 COS](https://cloud.tencent.com/document/product/436/68282)。
+
+#### 华为云 OBS
+
+如果存储系统为华为云 OBS，请按如下配置 `StorageCredentialParams`：
+
+```SQL
+"fs.obs.access.key" = "<obs_access_key>",
+"fs.obs.secret.key" = "<obs_secret_key>",
+"fs.obs.endpoint" = "<obs_endpoint>"
+```
+
+`StorageCredentialParams` 包含如下参数。
+
+| **参数名称**           | **参数说明**                                                 |
+| ---------------------- | ------------------------------------------------------------ |
+| fs.obs.access.key      | 访问华为云 OBS 存储空间的 Access Key ID，与私有访问密钥关联的唯一标识符。|
+| fs.obs.secret.key      | 访问华为云 OBS 存储空间的 Secret Access Key，对请求进行加密签名，可标识发送方，并防止请求被修改。 |
+| fs.obs.endpoint        | 访问华为云 OBS 存储空间的连接地址。                              |
+
+请参见华为云官方文档[通过永久访问密钥访问 OBS](https://support.huaweicloud.com/perms-cfg-obs/obs_40_0007.html)。
+
+> **说明**
+>
+> 使用 Broker Load 从华为云 OBS 导入数据时，需要先下载[依赖库](https://github.com/huaweicloud/obsa-hdfs/releases/download/v45/hadoop-huaweicloud-2.8.3-hw-45.jar)添加到 **$BROKER_HOME/lib/** 路径下并重启 Broker。
+
+#### 其他兼容 S3 协议的对象存储
+
+如果存储系统为其他兼容 S3 协议的对象存储（如 MinIO），请按如下配置 `StorageCredentialParams`：
+
+```SQL
+"aws.s3.enable_ssl" = "false",
+"aws.s3.enable_path_style_access" = "true",
+"aws.s3.endpoint" = "<s3_endpoint>",
+"aws.s3.access_key" = "<iam_user_access_key>",
+"aws.s3.secret_key" = "<iam_user_secret_key>"
+```
+
+`StorageCredentialParams` 包含如下参数。
+
+| 参数                            | 是否必须 | 描述                                                         |
+| ------------------------------- | -------- | ------------------------------------------------------------ |
+| aws.s3.enable_ssl               | 是       | 是否开启 SSL 连接。取值范围：`true` 和 `false`。默认值：`true`。对于 MinIO，必须设置为 `true`。 |
+| aws.s3.enable_path_style_access | 是       | 是否开启路径类型 URL 访问 (Path-Style URL Access)。取值范围：`true` 和 `false`。默认值：`false`。 |
+| aws.s3.endpoint                 | 是       | 用于访问兼容 S3 协议的对象存储的 Endpoint。                         |
+| aws.s3.access_key               | 是       | IAM User 的 Access Key。                                     |
+| aws.s3.secret_key               | 是       | IAM User 的 Secret Key。                                     |
+
+#### Microsoft Azure Storage
+
+##### Azure Blob Storage
+
+如果存储系统为 Blob Storage，请按如下配置 `StorageCredentialParams`：
+
+- 基于 Shared Key 进行认证和鉴权
+
+  ```SQL
+  "azure.blob.storage_account" = "<storage_account_name>",
+  "azure.blob.shared_key" = "<storage_account_shared_key>"
+  ```
+
+  `StorageCredentialParams` 包含如下参数。
+
+  | **参数**                   | **是否必须** | **说明**                         |
+  | -------------------------- | ------------ | -------------------------------- |
+  | azure.blob.storage_account | 是           | Blob Storage 账号的用户名。      |
+  | azure.blob.shared_key      | 是           | Blob Storage 账号的 Shared Key。 |
+
+- 基于 SAS Token 进行认证和鉴权
+
+  ```SQL
+  "azure.blob.storage_account" = "<storage_account_name>",
+  "azure.blob.container" = "<container_name>",
+  "azure.blob.sas_token" = "<storage_account_SAS_token>"
+  ```
+
+  `StorageCredentialParams` 包含如下参数。
+
+  | **参数**                  | **是否必须** | **说明**                                 |
+  | ------------------------- | ------------ | ---------------------------------------- |
+  | azure.blob.storage_account| 是           | Blob Storage 账号的用户名。              |
+  | azure.blob.container      | 是           | 用于存储数据的 Blob 容器的名称。         |
+  | azure.blob.sas_token      | 是           | 用于访问 Blob Storage 账号的 SAS Token。 |
+
+##### Azure Data Lake Storage Gen2
+
+如果存储系统为 Data Lake Storage Gen2，请按如下配置 `StorageCredentialParams`：
+
+- 基于 Managed Identity 进行认证和鉴权
+
+  ```SQL
+  "azure.adls2.oauth2_use_managed_identity" = "true",
+  "azure.adls2.oauth2_tenant_id" = "<service_principal_tenant_id>",
+  "azure.adls2.oauth2_client_id" = "<service_client_id>"
+  ```
+
+  `StorageCredentialParams` 包含如下参数。
+
+  | **参数**                                | **是否必须** | **说明**                                                |
+  | --------------------------------------- | ------------ | ------------------------------------------------------- |
+  | azure.adls2.oauth2_use_managed_identity | 是           | 指定是否开启 Managed Identity 鉴权方式。设置为 `true`。 |
+  | azure.adls2.oauth2_tenant_id            | 是           | 数据所属的 Tenant 的 ID。                               |
+  | azure.adls2.oauth2_client_id            | 是           | Managed Identity 的 Client (Application) ID。           |
+
+- 基于 Shared Key 进行认证和鉴权
+
+  ```SQL
+  "azure.adls2.storage_account" = "<storage_account_name>",
+  "azure.adls2.shared_key" = "<storage_account_shared_key>"
+  ```
+
+  `StorageCredentialParams` 包含如下参数。
+
+  | **参数**                    | **是否必须** | **说明**                                   |
+  | --------------------------- | ------------ | ------------------------------------------ |
+  | azure.adls2.storage_account | 是           | Data Lake Storage Gen2 账号的用户名。      |
+  | azure.adls2.shared_key      | 是           | Data Lake Storage Gen2 账号的 Shared Key。 |
+
+- 基于 Service Principal 进行认证和鉴权
+
+  ```SQL
+  "azure.adls2.oauth2_client_id" = "<service_client_id>",
+  "azure.adls2.oauth2_client_secret" = "<service_principal_client_secret>",
+  "azure.adls2.oauth2_client_endpoint" = "<service_principal_client_endpoint>"
+  ```
+
+  `StorageCredentialParams` 包含如下参数。
+
+  | **参数**                           | **是否必须** | **说明**                                                     |
+  | ---------------------------------- | ------------ | ------------------------------------------------------------ |
+  | azure.adls2.oauth2_client_id       | 是           | Service Principal 的 Client (Application) ID。               |
+  | azure.adls2.oauth2_client_secret   | 是           | 新建 Client (Application) Secret。                           |
+  | azure.adls2.oauth2_client_endpoint | 是           | Service Principal 或 Application 的 OAuth 2.0 Token Endpoint (v1)。 |
+
+##### Azure Data Lake Storage Gen1
+
+如果存储系统为 Data Lake Storage Gen1，请按如下配置 `StorageCredentialParams`：
+
+- 基于 Managed Service Identity 进行认证和鉴权
+
+  ```SQL
+  "azure.adls1.use_managed_service_identity" = "true"
+  ```
+
+  `StorageCredentialParams` 包含如下参数。
+
+  | **参数**                                 | **是否必须** | **说明**                                                     |
+  | ---------------------------------------- | ------------ | ------------------------------------------------------------ |
+  | azure.adls1.use_managed_service_identity | 是           | 指定是否开启 Managed Service Identity 鉴权方式。设置为 `true`。 |
+
+- 基于 Service Principal 进行认证和鉴权
+
+  ```SQL
+  "azure.adls1.oauth2_client_id" = "<application_client_id>",
+  "azure.adls1.oauth2_credential" = "<application_client_credential>",
+  "azure.adls1.oauth2_endpoint" = "<OAuth_2.0_authorization_endpoint_v2>"
+  ```
+
+  `StorageCredentialParams` 包含如下参数。
+
+  | **参数**                      | **是否必须** | **说明**                                                     |
+  | ----------------------------- | ------------ | ------------------------------------------------------------ |
+  | azure.adls1.oauth2_client_id  | 是           | Service Principal 的 Client (Application) ID。               |
+  | azure.adls1.oauth2_credential | 是           | 新建 Client (Application) Secret。                           |
+  | azure.adls1.oauth2_endpoint   | 是           | Service Principal 或 Application 的 OAuth 2.0 Token Endpoint (v1)。 |
+
+### opt_properties
+
+用于指定一些导入相关的可选参数，指定的参数设置作用于整个导入作业。语法如下：
+
+```Plain
+PROPERTIES ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
+```
+
+参数说明如下：
+
+- `timeout`
+
+  导入作业的超时时间。单位：秒。默认超时时间为 4 小时。建议超时时间小于 6 小时。如果导入作业在设定的时限内未完成，会自动取消，变成 **CANCELLED** 状态。
+
+  > **说明**
+  >
+  > 通常情况下，您不需要手动设置导入作业的超时时间。只有当导入作业无法在默认的超时时间内完成时，才推荐您手动设置导入作业的超时时间。
+
+  推荐超时时间大于下面公式的计算值：
+
+  **超时时间 > (源数据文件的总大小 x 源数据文件及相关物化视图的个数)/平均导入速度**
+
+    > **说明**
+    >
+    > “平均导入速度”是指目前 StarRocks 集群的平均导入速度。由于每个 StarRocks 集群的机器环境不同、且集群允许的并发查询任务数也不同，因此，StarRocks 集群的平均导入速度需要根据历史导入速度进行推测。
+
+   例如，要导入一个 1 GB 的数据文件，该数据文件包含 2 个物化视图，当前 StarRocks 集群的平均导入速度为 10 MB/s。在这种情况下，根据公式计算出来时长为 102 秒：
+
+   **(1 x 1024 x 3)/10 = 307.2（秒）**
+
+   因此，建议导入作业的超时时间大于 308 秒。
+
+- `max_filter_ratio`
+
+  导入作业的最大容忍率，即导入作业能够容忍的因数据质量不合格而过滤掉的数据行所占的最大比例。取值范围：`0`~`1`。默认值：`0` 。
+
+  - 如果设置最大容忍率为 `0`，则 StarRocks 在导入过程中不会忽略错误的数据行。当导入的数据行中有错误时，导入作业会失败，从而保证数据的正确性。
+  - 如果设置最大容忍率大于 `0`，则 StarRocks 在导入过程中会忽略错误的数据行。这样，即使导入的数据行中有错误，导入作业也能成功。
+    > **说明**
+    >
+    > 这里因数据质量不合格而过滤掉的数据行，不包括通过 WHERE 子句过滤掉的数据行。
+
+  如果因为设置最大容忍率为 `0` 而导致作业失败，可以通过 [SHOW LOAD](SHOW_LOAD.md) 语句来查看导入作业的结果信息。然后，判断错误的数据行是否可以被过滤掉。如果可以被过滤掉，则可以根据结果信息中的 `dpp.abnorm.ALL` 和 `dpp.norm.ALL` 来计算导入作业的最大容忍率，然后调整后重新提交导入作业。计算公式如下：
+
+  **`max_filter_ratio` = [`dpp.abnorm.ALL`/(`dpp.abnorm.ALL` + `dpp.norm.ALL`)]**
+
+  `dpp.abnorm.ALL` 和 `dpp.norm.ALL` 的总和就等于待导入的总行数。
+
+- `log_rejected_record_num`
+
+  指定最多允许记录多少条因数据质量不合格而过滤掉的数据行数。该参数自 3.1 版本起支持。取值范围：`0`、`-1`、大于 0 的正整数。默认值：`0`。
+  
+  - 取值为 `0` 表示不记录过滤掉的数据行。
+  - 取值为 `-1` 表示记录所有过滤掉的数据行。
+  - 取值为大于 0 的正整数（比如 `n`）表示每个 BE（或 CN）节点上最多可以记录 `n` 条过滤掉的数据行。
+
+- `load_mem_limit`
+
+  导入作业的内存限制，最大不超过 BE（或 CN）的内存限制。单位：字节。默认内存限制为 2 GB。
+
+- `strict_mode`
+
+  是否开启严格模式。取值范围：`true` 和 `false`。默认值：`false`。`true` 表示开启，`false` 表示关闭。<br />关于该模式的介绍，参见[严格模式](../../../loading/load_concept/strict_mode.md)。
+
+- `timezone`
+
+  指定导入作业所使用的时区。默认为 `Asia/Shanghai` 时区。该参数会影响所有导入涉及的、跟时区设置有关的函数所返回的结果。受时区影响的函数有 strftime、alignment_timestamp 和 from_unixtime 等，具体请参见[设置时区](../../../administration/management/timezone.md)。导入参数 `timezone` 设置的时区对应“[设置时区](../../../administration/management/timezone.md)”中所述的会话级时区。
+
+- `priority`
+
+   指定导入作业的优先级。取值范围：`LOWEST`、`LOW`、`NORMAL`、`HIGH` 和 `HIGHEST`。默认值：`NORMAL`。Broker Load 通过 [FE 配置项](../../../administration/management/FE_configuration.md) `max_broker_load_job_concurrency` 指定 StarRocks 集群中可以并行执行的 Broker Load 作业的最大数量。如果某一时间段内提交的 Broker Load 作业总数超过最大数量，则超出的作业会按照优先级在队列中排队等待调度。
+
+   已经创建成功的导入作业，如果处于 **QUEUEING** 状态或者 **LOADING** 状态，那么您可以使用 [ALTER LOAD](ALTER_LOAD.md) 语句修改该作业的优先级。
+
+   StarRocks 自 v2.5 版本起支持为导入作业设置 `priority` 参数。
+
+- `partial_update`
+  
+   是否使用部分列更新。取值包括 `TRUE` 和 `FALSE`。默认值：`FALSE`。
+
+- `partial_update_mode`
+
+  指定部分更新的模式，取值包括 `row` 和 `column`。<ul><li>`row`（默认值），指定使用行模式执行部分更新，比较适用于较多列且小批量的实时更新场景。</li><li>`column`，指定使用列模式执行部分更新，比较适用于少数列并且大量行的批处理更新场景。在该场景，开启列模式，更新速度更快。例如，在一个包含 100 列的表中，每次更新 10 列（占比 10%）并更新所有行，则开启列模式，更新性能将提高 10 倍。</li></ul>
+
+- `merge_condition`
+
+  用于指定作为更新生效条件的列名。这样只有当导入的数据中该列的值大于等于当前值的时候，更新才会生效。
+  
+  Broker Load 自 3.1 版本起支持条件更新。参见[通过导入实现数据变更](../../../loading/Load_to_Primary_Key_tables.md#条件更新)。
+  
+  > **说明**
+  >
+  > 指定的列必须为非主键列，且仅主键表支持条件更新。
+
+StarRocks 自 3.2.3 版本起支持导入 JSON 格式的数据，相关参数如下：
+
+- jsonpaths
+
+  用于指定待导入的字段的名称。仅在使用匹配模式导入 JSON 数据时需要指定该参数。参数取值为 JSON 格式。参见[导入 JSON 数据时配置列映射关系](#导入-json-数据时配置列映射关系)。
+
+- strip_outer_array
+
+  用于指定是否裁剪最外层的数组结构。取值范围：`true` 和 `false`。默认值：`false`。
+  
+  真实业务场景中，待导入的 JSON 数据可能在最外层有一对表示数组结构的中括号 `[]`。这种情况下，一般建议您指定该参数取值为 `true`，这样 StarRocks 会剪裁掉外层的中括号 `[]`，并把中括号 `[]` 里的每个内层数组都作为一行单独的数据导入。如果您指定该参数取值为 `false`，则 StarRocks 会把整个 JSON 数据文件解析成一个数组，并作为一行数据导入。例如，待导入的 JSON 数据为 `[ {"category" : 1, "author" : 2}, {"category" : 3, "author" : 4} ]`，如果指定该参数取值为 `true`，则 StarRocks 会把 `{"category" : 1, "author" : 2}` 和 `{"category" : 3, "author" : 4}` 解析成两行数据，并导入到目标 StarRocks 表中对应的数据行。
+
+- json_root
+
+  用于指定待导入 JSON 数据的根元素。仅在使用匹配模式导入 JSON 数据时需要指定该参数。参数取值为合法的 JsonPath 字符串。默认值为空，表示会导入整个 JSON 数据文件的数据。具体请参见本文提供的示例“[导入数据并指定 JSON 根节点](#指定-json-根节点使用匹配模式导入数据)”。
+
+<!-- - ignore_json_size
+
+  用于指定是否检查 HTTP 请求中 JSON Body 的大小。
+  
+  > **说明**
+  >
+  > HTTP 请求中 JSON Body 的大小默认不能超过 100 MB。如果 JSON Body 的大小超过 100 MB，会提示 "The size of this batch exceed the max size [104857600] of json type data data [8617627793]. Set ignore_json_size to skip check, although it may lead huge memory consuming." 错误。为避免该报错，可以在 HTTP 请求头中添加 `"ignore_json_size:true"` 设置，忽略对 JSON Body 大小的检查。
+-->
+另外，导入 JSON 格式的数据时，需要注意单个 JSON 对象的大小不能超过 4 GB。如果 JSON 文件中单个 JSON 对象的大小超过 4 GB，会提示 "This parser can't support a document that big." 错误。
+
+## 列映射
+
+### 导入 CSV 数据时配置列映射关系
+
+如果源数据文件中的列与目标表中的列按顺序一一对应，您不需要指定列映射和转换关系。
+
+如果源数据文件中的列与目标表中的列不能按顺序一一对应，包括数量或顺序不一致，则必须通过 `COLUMNS` 参数来指定列映射和转换关系。一般包括如下两种场景：
+
+- **列数量一致、但是顺序不一致，并且数据不需要通过函数计算、可以直接落入目标表中对应的列。** 这种场景下，您需要在 `COLUMNS` 参数中按照源数据文件中的列顺序、使用目标表中对应的列名来配置列映射和转换关系。
+
+  例如，目标表中有三列，按顺序依次为 `col1`、`col2` 和 `col3`；源数据文件中也有三列，按顺序依次对应目标表中的 `col3`、`col2` 和 `col1`。这种情况下，需要指定 `COLUMNS(col3, col2, col1)`。
+
+- **列数量、顺序都不一致，并且某些列的数据需要通过函数计算以后才能落入目标表中对应的列。** 这种场景下，您不仅需要在 `COLUMNS` 参数中按照源数据文件中的列顺序、使用目标表中对应的列名来配置列映射关系，还需要指定参与数据计算的函数。以下为两个示例：
+
+  - 目标表中有三列，按顺序依次为 `col1`、`col2` 和 `col3` ；源数据文件中有四列，前三列按顺序依次对应目标表中的 `col1`、`col2` 和 `col3`，第四列在目标表中无对应的列。这种情况下，需要指定 `COLUMNS(col1, col2, col3, temp)`，其中，最后一列可随意指定一个名称（如 `temp`）用于占位即可。
+  - 目标表中有三列，按顺序依次为 `year`、`month` 和 `day`。源数据文件中只有一个包含时间数据的列，格式为 `yyyy-mm-dd hh:mm:ss`。这种情况下，可以指定 `COLUMNS (col, year = year(col), month=month(col), day=day(col))`。其中，`col` 是源数据文件中所包含的列的临时命名，`year = year(col)`、`month=month(col)` 和 `day=day(col)` 用于指定从 `col` 列提取对应的数据并落入目标表中对应的列，如 `year = year(col)` 表示通过 `year` 函数提取源数据文件中 `col` 列的 `yyyy` 部分的数据并落入目标表中的 `year` 列。
+
+有关操作示例，参见[设置列映射关系](#设置列映射关系)。
+
+### 导入 JSON 数据时配置列映射关系
+
+如果 JSON 文件中的 Key 名与目标表中的列名一致，您可以使用简单模式来导入数据。简单模式下，不需要设置 `jsonpaths` 参数，这种模式要求 JSON 数据是大括号 {} 表示的对象类型，例如 `{"category": 1, "author": 2, "price": "3"}` 中，`category`、`author`、`price` 是 Key 的名称，按名称直接对应目标 表中的 `category`、`author`、`price` 三列。
+
+如果 JSON 文件中的 Key 名与目标表中的列名不一致，则需要使用匹配模式来导入数据。匹配模式下，需要通过 `jsonpaths` 和 `COLUMNS` 两个参数来指定 JSON 文件中的 Key 和目标表中的列之间的映射和转换关系：
+
+- `jsonpaths` 参数中按照 JSON 文件中 Key 的顺序一一指定待导入的 Key。
+- `COLUMNS` 参数中指定 JSON 文件中的 Key 与目标表中的列之间的映射关系和数据转换关系。
+  - `COLUMNS` 参数中指定的列名与 `jsonpaths` 参数中指定的 Key 按顺序保持一一对应。
+  - `COLUMNS` 参数中指定的列名与目标表中的列按名称保持一一对应。
+
+有关使用匹配模式导入 JSON 数据的示例，参见[使用匹配模式导入数据](#使用匹配模式导入数据)。
+
+## 相关配置项
+
+[FE 配置项](../../../administration/management/FE_configuration.md) `max_broker_load_job_concurrency` 指定了 StarRocks 集群中可以并行执行的 Broker Load 作业的最大数量。
+
+StarRocks v2.4 及以前版本中，如果某一时间段内提交的 Broker Load 作业总数超过最大数量，则超出作业会按照各自的提交时间放到队列中排队等待调度。
+
+自 StarRocks v2.5 版本起，如果某一时间段内提交的 Broker Load 作业总数超过最大数量，则超出的作业会按照作业创建时指定的优先级被放到队列中排队等待调度。参见上面介绍的可选参数 `priority`。您可以使用 [ALTER LOAD](ALTER_LOAD.md) 语句修改处于 **QUEUEING** 状态或者 **LOADING** 状态的 Broker Load 作业的优先级。
+
+## 作业拆分与并行执行
+
+一个 Broker Load 作业会拆分成一个或者多个子任务并行处理，一个作业的所有子任务作为一个事务整体成功或失败。作业的拆分通过 `LOAD LABEL` 语句中的 `data_desc` 参数来指定：
+
+- 如果声明多个 `data_desc` 参数对应导入多张不同的表，则每张表数据的导入会拆分成一个子任务。
+
+- 如果声明多个 `data_desc` 参数对应导入同一张表的不同分区，则每个分区数据的导入会拆分成一个子任务。
+
+每个子任务还会拆分成一个或者多个实例，然后这些实例会均匀地被分配到 BE（或 CN）上并行执行。实例的拆分由 FE 配置参数 [`min_bytes_per_broker_scanner`](../../../administration/management/FE_configuration.md) 和 BE（或 CN）节点数量决定，可以使用如下公式计算单个子任务的实例总数：
+
+单个子任务的实例总数 = min（单个子任务待导入数据量的总大小/`min_bytes_per_broker_scanner`, BE/CN 节点数量）
+
+一般情况下，一个导入作业只有一个 `data_desc`，只会拆分成一个子任务，子任务会拆分成与 BE（或 CN）节点数量相等的实例。
+
+## 示例
+
+本文以 HDFS 数据源为例，介绍各种导入配置。
+
+### 导入 CSV 格式的数据
+
+本小节以 CSV 格式的数据为例，重点阐述在创建导入作业的时候，如何运用各种参数配置来满足不同业务场景下的各种导入要求。
+
+#### 设置超时时间
+
+StarRocks 数据库 `test_db` 里的表 `table1` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example1.csv` 也包含三列，按顺序一一对应 `table1` 中的三列。
+
+如果要把 `example1.csv` 中所有的数据都导入到 `table1` 中，并且要求超时时间最大不超过 3600 秒，可以执行如下语句：
+
+```SQL
+LOAD LABEL test_db.label1
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example1.csv")
+    INTO TABLE table1
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+)
+PROPERTIES
+(
+    "timeout" = "3600"
+);
+```
+
+#### 设置最大容错率
+
+StarRocks 数据库 `test_db` 里的表 `table2` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example2.csv` 也包含三列，按顺序一一对应 `table2` 中的三列。
+
+如果要把 `example2.csv` 中所有的数据都导入到 `table2` 中，并且要求容错率最大不超过 `0.1`，可以执行如下语句：
+
+```SQL
+LOAD LABEL test_db.label2
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example2.csv")
+    INTO TABLE table2
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+)
+PROPERTIES
+(
+    "max_filter_ratio" = "0.1"
+);
+```
+
+#### 导入指定路径下所有数据文件
+
+StarRocks 数据库 `test_db` 里的表 `table3` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+HDFS 集群的 `/user/starrocks/data/input/` 路径下所有数据文件也包含三列，按顺序一一对应 `table3` 中的三列，并且列分隔符为 Hive 文件的默认列分隔符 `\x01`。
+
+如果要把 `hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/` 路径下所有数据文件的数据都导入到 `table3` 中，可以执行如下语句：
+
+```SQL
+LOAD LABEL test_db.label3
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/*")
+    INTO TABLE table3
+    COLUMNS TERMINATED BY "\\x01"
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+#### 设置 NameNode HA 机制
+
+StarRocks 数据库 `test_db` 里的表 `table4` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example4.csv` 也包含三列，按顺序一一对应 `table4` 中的三列。
+
+如果要把 `example4.csv` 中所有的数据都导入到 `table4` 中，并且要求使用 NameNode HA 机制，可以执行如下语句：
+
+```SQL
+LOAD LABEL test_db.label4
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example4.csv")
+    INTO TABLE table4
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>",
+    "dfs.nameservices" = "my_ha",
+    "dfs.ha.namenodes.my_ha" = "my_namenode1, my_namenode2",
+    "dfs.namenode.rpc-address.my_ha.my_namenode1" = "nn1_host:rpc_port",
+    "dfs.namenode.rpc-address.my_ha.my_namenode2" = "nn2_host:rpc_port",
+    "dfs.client.failover.proxy.provider" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
+);
+```
+
+#### 设置 Kerberos 认证方式
+
+StarRocks 数据库 `test_db` 里的表 `table5` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example5.csv` 也包含三列，按顺序一一对应 `table5` 中的三列。
+
+如果要把 `example5.csv` 中所有的数据都导入到 `table5` 中，并且要求使用 Kerberos 认证方式、提供 keytab 文件的路径，可以执行如下语句：
+
+```SQL
+LOAD LABEL test_db.label5
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example5.csv")
+    INTO TABLE table5
+    COLUMNS TERMINATED BY "\t"
+)
+WITH BROKER
+(
+    "hadoop.security.authentication" = "kerberos",
+    "kerberos_principal" = "starrocks@YOUR.COM",
+    "kerberos_keytab" = "/home/starRocks/starRocks.keytab"
+);
+```
+
+#### 撤销已导入的数据
+
+StarRocks 数据库 `test_db` 里的表 `table6` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example6.csv` 也包含三列，按顺序一一对应 `table6` 中的三列。
+
+并且，您已经通过 Broker Load 把 `example6.csv` 中所有的数据都导入到了 `table6` 中。
+
+如果您想撤销已导入的数据，可以执行如下语句：
+
+```SQL
+LOAD LABEL test_db.label6
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example6.csv")
+    NEGATIVE
+    INTO TABLE table6
+    COLUMNS TERMINATED BY "\t"
+)
+WITH BROKER
+(
+    "hadoop.security.authentication" = "kerberos",
+    "kerberos_principal" = "starrocks@YOUR.COM",
+    "kerberos_keytab" = "/home/starRocks/starRocks.keytab"
+);
+```
+
+#### 设置目标分区
+
+StarRocks 数据库 `test_db` 里的表 `table7` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example7.csv` 也包含三列，按顺序一一对应 `table7` 中的三列。
+
+如果要把 `example7.csv` 中所有的数据都导入到 `table7` 所在的分区 `p1` 和 `p2`，可以执行如下语句：
+
+```SQL
+LOAD LABEL test_db.label7
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example7.csv")
+    INTO TABLE table7
+    PARTITION (p1, p2)
+    COLUMNS TERMINATED BY ","
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+#### 设置列映射关系
+
+StarRocks 数据库 `test_db` 里的表 `table8` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example8.csv` 也包含三列，按顺序依次对应 `table8` 中 `col2`、`col1`、`col3`。
+
+如果要把 `example8.csv` 中所有的数据都导入到 `table8` 中，可以执行如下语句：
+
+```SQL
+LOAD LABEL test_db.label8
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example8.csv")
+    INTO TABLE table8
+    COLUMNS TERMINATED BY ","
+    (col2, col1, col3)
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+> **说明**
+>
+> 上述示例中，因为 `example8.csv` 和 `table8` 所包含的列不能按顺序依次对应，因此需要通过 `column_list` 参数来设置 `example8.csv` 和 `table8` 之间的列映射关系。
+
+#### 设置筛选条件
+
+StarRocks 数据库 `test_db` 里的表 `table9` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example9.csv` 也包含三列，按顺序一一对应 `table9` 中的三列。
+
+如果只想把 `example9.csv` 中第一列的值大于 `20180601` 的数据行导入到 `table9` 中，可以执行如下语句：
+
+```SQL
+LOAD LABEL test_db.label9
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example9.csv")
+    INTO TABLE table9
+    (col1, col2, col3)
+    where col1 > 20180601
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+> **说明**
+>
+> 上述示例中，虽然 `example9.csv` 和 `table9` 所包含的列数目相同、并且按顺序一一对应，但是因为需要通过 WHERE 子句指定基于列的过滤条件，因此需要通过 `column_list` 参数对 `example9.csv` 中的列进行临时命名。
+
+#### 导入数据到含有 HLL 类型列的表
+
+StarRocks 数据库 `test_db` 里的表 `table10` 包含四列，按顺序依次为 `id`、`col1`、`col2`、`col3`，其中 `col1` 和 `col2` 是 HLL 类型的列。
+
+数据文件 `example10.csv` 包含三列，第一列对应 `table10` 中的 `id` 列；第二列和第三列分别对应 `table10` 中 HLL 类型的列 `col1` 和 `col2`，可以通过函数转换成 HLL 类型的数据并分别落入 `col1`、`col2` 列。
+
+如果要把 `example10.csv` 中所有的数据都导入到 `table10` 中，可以执行如下语句：
+
+```SQL
+LOAD LABEL test_db.label10
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example10.csv")
+    INTO TABLE table10
+    COLUMNS TERMINATED BY ","
+    (id, temp1, temp2)
+    SET
+    (
+        col1 = hll_hash(temp1),
+        col2 = hll_hash(temp2),
+        col3 = empty_hll()
+    )
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+> **说明**
+>
+> 上述示例中，通过 `column_list` 参数，把 `example10.csv` 中的三列按顺序依次临时命名为 `id`、`temp1`、`temp2`，然后使用函数指定数据转换规则，包括：
+>
+> - 使用 `hll_hash` 函数把 `example10.csv` 中的 `temp1`、`temp2` 列转换成 HLL 类型的数据，并分别落入 `table10`中的 `col1`、`col2` 列。
+>
+> - 使用 `hll_empty` 函数给导入的数据行在 `table10` 中的第四列补充默认值。
+
+有关 `hll_hash` 函数和 `hll_empty` 函数的用法，请参见 [hll_hash](../../sql-functions/scalar-functions/hll_hash.md)和[hll_empty](../../sql-functions/scalar-functions/hll_empty.md)。
+
+#### 提取文件路径中的分区字段
+
+Broker Load 支持根据 StarRocks 表中定义的字段类型来解析待导入文件路径中的分区字段，类似 Apache Spark™ 中的分区发现 (Partition Discovery) 功能。
+
+StarRocks 数据库 `test_db` 里的表 `table11` 包含五列，按顺序依次为 `col1`、`col2`、`col3`、`city`、`utc_date`。
+
+HDFS 集群的 `/user/starrocks/data/input/dir/city=beijing` 路径下包含如下数据文件：
+
+- `/user/starrocks/data/input/dir/city=beijing/utc_date=2019-06-26/0000.csv`
+
+- `/user/starrocks/data/input/dir/city=beijing/utc_date=2019-06-26/0001.csv`
+
+这些数据文件都包含三列，按顺序分别对应 `table11` 中 `col1`、`col2`、`col3` 三列。
+
+如果要把 `/user/starrocks/data/input/dir/city=beijing/utc_date=*/*` 路径下所有数据文件的数据都导入到 `table11` 中，并且要求提取路径中分区字段 `city` 和 `utc_date` 的信息落入 `table11` 中对应的 `city`、`utc_date` 列，可以执行如下语句：
+
+```SQL
+LOAD LABEL test_db.label11
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/dir/city=beijing/*/*")
+    INTO TABLE table11
+    FORMAT AS "csv"
+    (col1, col2, col3)
+    COLUMNS FROM PATH AS (city, utc_date)
+    SET (uniq_id = md5sum(k1, city))
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+#### 提取文件路径中包含 `%3A` 的时间分区字段
+
+在 HDFS 的文件路径中，不允许有冒号 (:)，所有冒号 (:) 都会自动替换成 `%3A`。
+
+StarRocks 数据库 `test_db` 里的表 `table12` 包含三列，按顺序依次为 `data_time`、`col1`、`col2`，表结构如下：
+
+```SQL
+data_time DATETIME,
+col1        INT,
+col2        INT
+```
+
+HDFS 集群的 `/user/starrocks/data` 路径下有如下数据文件：
+
+- `/user/starrocks/data/data_time=2020-02-17 00%3A00%3A00/example12.csv`
+
+- `/user/starrocks/data/data_time=2020-02-18 00%3A00%3A00/example12.csv`
+
+如果要把 `example12.csv` 中所有的数据都导入到 `table12` 中，并且要求提取指定路径中分区字段 `data_time` 的信息落入到 `table12` 中的 `data_time` 列，可以执行如下语句：
+
+```SQL
+LOAD LABEL test_db.label12
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/*/example12.csv")
+    INTO TABLE table12
+    COLUMNS TERMINATED BY ","
+    FORMAT AS "csv"
+    (col1,col2)
+    COLUMNS FROM PATH AS (data_time)
+    SET (data_time = str_to_date(data_time, '%Y-%m-%d %H%%3A%i%%3A%s'))
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+上述示例中，因为直接提取后的分区字段 `data_time` 是包含 `%3A` 的字符串（如 `2020-02-17 00%3A00%3A00`），因此需要再通过 `str_to_date` 函数把字符串转换为 DATETIME 类型的数据以后才能落入 `table8` 中的 `data_time` 列。
+
+#### 设置 `format_type_options`
+
+StarRocks 数据库 `test_db` 里的表 `table13` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example13.csv` 也包含三列，按顺序依次对应 `table13` 中 `col2`、`col1`、`col3`。
+
+如果要把 `example13.csv` 中所有的数据都导入到 `table13` 中，并且希望跳过 `example13.csv` 中最开头的两行数据、去除列分隔符前后的空格、 指定 `enclose` 字符为斜杠 (`\`)、并且指定 `escape` 字符为斜杠 (`\`)，可以执行如下语句：
+
+```SQL
+LOAD LABEL test_db.label13
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/*/example13.csv")
+    INTO TABLE table13
+    COLUMNS TERMINATED BY ","
+    FORMAT AS "CSV"
+    (
+        skip_header = 2
+        trim_space = TRUE
+        enclose = "\""
+        escape = "\\"
+    )
+    (col2, col1, col3)
+)
+WITH BROKER
+(
+    "username" = "hdfs_username",
+    "password" = "hdfs_password"
+)
+PROPERTIES
+(
+    "timeout" = "3600"
+);
+```
+
+### 导入 Parquet 格式的数据
+
+本小节主要描述导入 Parquet 格式的数据时，需要关注的一些参数配置。
+
+StarRocks 数据库 `test_db` 里的表 `table13` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example13.parquet` 也包含三列，按顺序一一对应 `table13` 中的三列。
+
+如果要把 `example13.parquet` 中所有的数据都导入到 `table13` 中，可以执行如下语句：
+
+```SQL
+LOAD LABEL test_db.label13
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example13.parquet")
+    INTO TABLE table13
+    FORMAT AS "parquet"
+    (col1, col2, col3)
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+> **说明**
+>
+> 导入 Parquet 格式的数据时，默认通过文件扩展名 (**.parquet**) 判断数据文件的格式。如果文件名称中没有包含扩展名，则必须通过 `FORMAT AS` 参数指定数据文件格式为 `Parquet`。
+
+### 导入 ORC 格式的数据
+
+本小节主要描述导入 ORC 格式的数据时，需要关注的一些参数配置。
+
+StarRocks 数据库 `test_db` 里的表 `table14` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example14.orc` 也包含三列，按顺序一一对应 `table14` 中的三列。
+
+如果要把 `example14.orc` 中所有的数据都导入到 `table14` 中，可以执行如下语句：
+
+```SQL
+LOAD LABEL test_db.label14
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example14.orc")
+    INTO TABLE table14
+    FORMAT AS "orc"
+    (col1, col2, col3)
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+> **说明**
+>
+> - 导入 ORC 格式的数据时，默认通过文件扩展名 (**.orc**) 判断数据文件的格式。如果文件名称中没有包含扩展名，则必须通过 `FORMAT AS` 参数指定数据文件格式为 `ORC`。
+>
+> - StarRocks v2.3 及之前版本，当数据文件中包含 ARRAY 类型的列时，必须确保数据文件和 StarRocks 表中对应的列同名，并且不能写在 SET 子句里。
+
+### 导入 JSON 格式的数据
+
+本小节主要描述导入 JSON 格式的数据时，需要关注的一些参数配置。
+
+StarRocks 数据库 `test_db` 里的表 `tbl1` 拥有如下表结构：
+
+```SQL
+`category` varchar(512) NULL COMMENT "",
+`author` varchar(512) NULL COMMENT "",
+`title` varchar(512) NULL COMMENT "",
+`price` double NULL COMMENT ""
+```
+
+#### 使用简单模式导入数据
+
+假设数据文件 `example1.json` 包含如下数据：
+
+```JSON
+{"category":"C++","author":"avc","title":"C++ primer","price":895}
+```
+
+您可以通过如下命令将 `example1.json` 中的数据导入到 `tbl1` 中：
+
+```SQL
+LOAD LABEL test_db.label15
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example1.csv")
+    INTO TABLE tbl1
+    FORMAT AS "json"
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+);
+```
+
+> **说明**
+>
+> 如上述示例所示，在没有指定 `columns` 和 `jsonpaths` 参数的情况下，则会按照 StarRocks 表中的列名称去对应 JSON 数据文件中的字段。
+
+#### 使用匹配模式导入数据
+
+StarRocks 按照如下顺序对数据进行匹配和处理：
+
+1. （可选）根据 `strip_outer_array` 参数裁剪最外层的数组结构。
+
+    > **说明**
+    >
+    > 仅在 JSON 数据的最外层是一个通过中括号 `[]` 表示的数组结构时涉及，需要设置 `strip_outer_array` 为 `true`。
+
+2. （可选）根据 `json_root` 参数匹配 JSON 数据的根节点。
+
+    > **说明**
+    >
+    > 仅在 JSON 数据存在根节点时涉及，需要通过 `json_root` 参数来指定根节点。
+
+3. 根据 `jsonpaths` 参数提取待导入的 JSON 数据。
+
+##### 不指定 JSON 根节点、使用匹配模式导入数据
+
+假设数据文件 `example2.json` 包含如下数据：
+
+```JSON
+[
+    {"category":"xuxb111","author":"1avc","title":"SayingsoftheCentury","price":895},
+    {"category":"xuxb222","author":"2avc","title":"SayingsoftheCentury","price":895},
+    {"category":"xuxb333","author":"3avc","title":"SayingsoftheCentury","price":895}
+]
+```
+
+您可以通过指定 `jsonpaths` 参数进行精准导入，例如只导入 `category`、`author`、`price` 三个字段的数据：
+
+```SQL
+LOAD LABEL test_db.label16
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example2.csv")
+    INTO TABLE tbl1
+    FORMAT AS "json"
+    (category, price, author)
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+)
+PROPERTIES
+(
+    "strip_outer_array" = "true",
+    "jsonpaths" = "[\"$.category\",\"$.price\",\"$.author\"]"
+);
+```
+
+> **说明**
+>
+> 上述示例中，JSON 数据的最外层是一个通过中括号 [] 表示的数组结构，并且数组结构中的每个 JSON 对象都表示一条数据记录。因此，需要设置 `strip_outer_array` 为 `true`来裁剪最外层的数组结构。导入过程中，未指定的字段 `title` 会被忽略掉。
+
+##### 指定 JSON 根节点、使用匹配模式导入数据
+
+假设数据文件 `example3.json` 包含如下数据：
+
+```JSON
+{
+    "id": 10001,
+    "RECORDS":[
+        {"category":"11","title":"SayingsoftheCentury","price":895,"timestamp":1589191587},
+        {"category":"22","author":"2avc","price":895,"timestamp":1589191487},
+        {"category":"33","author":"3avc","title":"SayingsoftheCentury","timestamp":1589191387}
+    ],
+    "comments": ["3 records", "there will be 3 rows"]
+}
+```
+
+您可以通过指定 `jsonpaths` 进行精准导入，例如只导入 `category`、`author`、`price` 三个字段的数据：
+
+```SQL
+LOAD LABEL test_db.label17
+(
+    DATA INFILE("hdfs://<hdfs_host>:<hdfs_port>/user/starrocks/data/input/example3.csv")
+    INTO TABLE tbl1
+    FORMAT AS "json"
+    (category, price, author)
+)
+WITH BROKER
+(
+    "username" = "<hdfs_username>",
+    "password" = "<hdfs_password>"
+)
+PROPERTIES
+(
+    "json_root"="$.RECORDS",
+    "strip_outer_array" = "true",
+    "jsonpaths" = "[\"$.category\",\"$.price\",\"$.author\"]"
+);
+```
+
+> **说明**
+>
+> 上述示例中，JSON 数据的最外层是一个通过中括号 [] 表示的数组结构，并且数组结构中的每个 JSON 对象都表示一条数据记录。因此，需要设置 `strip_outer_array` 为 `true`来裁剪最外层的数组结构。导入过程中，未指定的字段 `title` 和 `timestamp` 会被忽略掉。另外，示例中还通过 `json_root` 参数指定了需要真正导入的数据为 `RECORDS` 字段对应的值，即一个 JSON 数组。
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/CANCEL_LOAD.md b/docs/zh/sql-reference/sql-statements/loading_unloading/CANCEL_LOAD.md
new file mode 100644
index 00000000000000..498e2a375004cf
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/CANCEL_LOAD.md
@@ -0,0 +1,43 @@
+---
+displayed_sidebar: docs
+---
+
+# CANCEL LOAD
+
+## 功能
+
+取消指定的 [Broker Load](BROKER_LOAD.md)、[Spark Load](SPARK_LOAD.md) 或 [INSERT](INSERT.md) 导入作业，状态为 PREPARED、CANCELLED 或 FINISHED 的导入作业不能取消。
+
+CANCEL LOAD 是一个异步操作，执行后可使用 [SHOW LOAD](SHOW_LOAD.md) 语句查看是否取消成功。当状态 (`State`) 为 `CANCELLED` 且导入作业失败原因 (`ErrorMsg`) 中的失败类型 (`type`) 为 `USER_CANCEL` 时，代表成功取消了导入作业。
+
+## 语法
+
+```SQL
+CANCEL LOAD
+[FROM db_name]
+WHERE LABEL = "label_name"
+```
+
+## 参数说明
+
+| **参数**   | **必选** | **说明**                                       |
+| ---------- | -------- | ---------------------------------------------- |
+| db_name    | 否       | 导入作业所在的数据库的名称。默认为当前数据库。 |
+| label_name | 是       | 导入作业的标签。                               |
+
+## 示例
+
+示例一：取消当前数据库中标签为`example_label`的导入作业。
+
+```SQL
+CANCEL LOAD
+WHERE LABEL = "example_label";
+```
+
+示例二：取消数据库`example_db`中标签为`example_label`的导入作业。
+
+```SQL
+CANCEL LOAD
+FROM example_db
+WHERE LABEL = "example_label";
+```
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/ETL/DROP_TASK.md b/docs/zh/sql-reference/sql-statements/loading_unloading/ETL/DROP_TASK.md
new file mode 100644
index 00000000000000..861027ec3e86ba
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/ETL/DROP_TASK.md
@@ -0,0 +1,61 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP TASK
+
+## 功能
+
+删除通过 [SUBMIT TASK](SUBMIT_TASK.md) 语句提交的异步 ETL 任务。此功能从 StarRocks v2.5.7 起支持。
+
+> **说明**
+>
+> 通过 DROP TASK 删除任务将同时取消该任务对应的 TaskRun。
+
+## 语法
+
+```SQL
+DROP TASK `<task_name>` [FORCE]
+```
+
+## 参数说明
+
+| **参数**  | **必须** | **说明**       |
+| --------- | ------- | -------------- |
+| task_name | 是      | 待删除任务名。为避免解析失败，请使用反括号（`）包裹任务名。 |
+| FORCE     | 否      | 强制删除任务。   |
+
+## 使用说明
+
+您可以通过查询 Information Schema 中的元数据视图 `tasks` 和 `task_runs` 来查看异步任务的信息。
+
+```SQL
+SELECT * FROM INFORMATION_SCHEMA.tasks;
+SELECT * FROM information_schema.tasks WHERE task_name = '<task_name>';
+SELECT * FROM information_schema.task_runs;
+SELECT * FROM information_schema.task_runs WHERE task_name = '<task_name>';
+```
+
+您可以通过 SHOW MATERIALIZED VIEWS 语句获取物化视图刷新任务的 `task_name`。
+
+```SQL
+SHOW MATERIALIZED VIEWS;
+SHOW MATERIALIZED VIEWS WHERE name = '<mv_name>';
+```
+
+## 示例
+
+```Plain
+MySQL > SUBMIT /*+set_var(query_timeout=100000)*/ TASK `ctas` AS
+    -> CREATE TABLE insert_wiki_edit_new
+    -> AS SELECT * FROM source_wiki_edit;
++----------+-----------+
+| TaskName | Status    |
++----------+-----------+
+| ctas     | SUBMITTED |
++----------+-----------+
+1 row in set (1.19 sec)
+
+MySQL > DROP TASK `ctas`;
+Query OK, 0 rows affected (0.35 sec)
+```
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/ETL/SUBMIT_TASK.md b/docs/zh/sql-reference/sql-statements/loading_unloading/ETL/SUBMIT_TASK.md
new file mode 100644
index 00000000000000..c931a97e1efc71
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/ETL/SUBMIT_TASK.md
@@ -0,0 +1,119 @@
+---
+displayed_sidebar: docs
+---
+
+# SUBMIT TASK
+
+## 功能
+
+为 ETL 语句创建异步任务。
+
+您可将该语句用于以下场景：
+
+- 创建长时间运行的后台任务（从 v2.5 开始支持）
+- 创建定期执行的任务（从 v3.3 开始支持）
+
+支持的语句包括：
+
+- [CREATE TABLE AS SELECT](../../table_bucket_part_index/CREATE_TABLE_AS_SELECT.md)（从 v3.0 开始支持）
+- [INSERT](../INSERT.md)（从 v3.0 开始支持）
+- [CACHE SELECT](../../../../data_source/data_cache_warmup.md)（从 v3.3 开始支持）
+
+您可以通过查询 `INFORMATION_SCHEMA.tasks` 查看任务列表，或通过查询 `INFORMATION_SCHEMA.task_runs` 查看任务的执行历史。有关更多信息，请参阅[使用说明](#使用说明)。
+
+您可以使用 [DROP TASK](DROP_TASK.md) 删除异步任务。
+
+## 语法
+
+```SQL
+SUBMIT TASK <task_name> 
+[SCHEDULE [START(<schedule_start>)] EVERY(INTERVAL <schedule_interval>) ]
+[PROPERTIES(<"key" = "value"[, ...]>)]
+AS <etl_statement>
+```
+
+## 参数说明
+
+| **参数**      | **是否必须** | **描述**                                                                                     |
+| ------------- | ------------ | ----------------------------------------------------------------------------------------- |
+| task_name          | 是      | 任务名称。                                                                                   |
+| schedule_start     | 否      | 定时任务的开始时间。                                                                           |
+| schedule_interval  | 否      | 定时任务的执行间隔，最小间隔为 10 秒。                                                           |
+| etl_statement      | 是      | 需要创建异步任务的 ETL 语句。StarRocks 当前支持为 [CREATE TABLE AS SELECT](../../table_bucket_part_index/CREATE_TABLE_AS_SELECT.md) 和 [INSERT](../INSERT.md) |
+
+## 使用说明
+
+该语句会创建一个 Task，表示一个 ETL 语句执行任务的存储模板。您可以通过查询 Information Schema 中的元数据视图 `tasks` 来查看 Task 信息：
+
+```SQL
+SELECT * FROM INFORMATION_SCHEMA.tasks;
+SELECT * FROM information_schema.tasks WHERE task_name = '<task_name>';
+```
+
+执行 Task 后会对应生成一个 TaskRun，表示一个 ETL 语句执行任务。TaskRun 有以下状态：
+
+- `PENDING`：任务等待执行。
+- `RUNNING`：任务正在执行。
+- `FAILED`：任务执行失败。
+- `SUCCESS`：任务执行成功。
+
+您可以通过查询 Information Schema 中的元数据视图 `task_runs` 来查看 TaskRun 状态：
+
+```SQL
+SELECT * FROM INFORMATION_SCHEMA.task_runs;
+SELECT * FROM information_schema.task_runs WHERE task_name = '<task_name>';
+```
+
+## 相关 FE 参数
+
+您可以通过调整如下 FE 参数配置异步 ETL 任务：
+
+| **参数**                     | **默认值** | **说明**                                                     |
+| ---------------------------- | ---------- | ------------------------------------------------------------ |
+| task_ttl_second              | 86400      | Task 的有效期，单位秒。超过有效期的 Task 会被自动删除。        |
+| task_check_interval_second   | 3600       | 删除过期 Task 的间隔时间，单位秒。                           |
+| task_runs_ttl_second         | 86400      | TaskRun 的有效期，单位秒。超过有效期的 TaskRun 会被自动删除。此外，成功和失败状态的 TaskRun 也会被自动删除。 |
+| task_runs_concurrency        | 4          | 最多可同时运行的 TaskRun 的数量。                            |
+| task_runs_queue_length       | 500        | 最多可同时等待运行的 TaskRun 的数量。如同时等待运行的 TaskRun 的数量超过该参数的默认值，您将无法继续执行 Task。 |
+| task_runs_max_history_number | 10000      | 保留的最多历史 TaskRun 任务数量。 |
+| task_min_schedule_interval_s | 10         | Task 最小执行间隔。单位：秒。 |
+
+## 示例
+
+示例一：为 `CREATE TABLE tbl1 AS SELECT * FROM src_tbl` 创建异步任务，并命名为 `etl0`：
+
+```SQL
+SUBMIT TASK etl0 AS CREATE TABLE tbl1 AS SELECT * FROM src_tbl;
+```
+
+示例二：为 `INSERT INTO tbl2 SELECT * FROM src_tbl` 创建异步任务，并命名为 `etl1`：
+
+```SQL
+SUBMIT TASK etl1 AS INSERT INTO tbl2 SELECT * FROM src_tbl;
+```
+
+示例三：为 `INSERT OVERWRITE tbl3 SELECT * FROM src_tbl` 创建异步任务：
+
+```SQL
+SUBMIT TASK AS INSERT OVERWRITE tbl3 SELECT * FROM src_tbl;
+```
+
+示例四：为 `INSERT OVERWRITE insert_wiki_edit SELECT * FROM source_wiki_edit` 创建异步任务，并通过 Hint 将 Query Timeout 设置为 `100000` 秒：
+
+```SQL
+SUBMIT /*+set_var(query_timeout=100000)*/ TASK AS
+INSERT OVERWRITE insert_wiki_edit
+SELECT * FROM source_wiki_edit;
+```
+
+示例五：为 INSERT OVERWRITE 语句创建异步任务。任务将以一分钟为间隔定期执行。
+
+```SQL
+SUBMIT TASK
+SCHEDULE EVERY(INTERVAL 1 MINUTE)
+AS
+INSERT OVERWRITE insert_wiki_edit
+    SELECT dt, user_id, count(*) 
+    FROM source_wiki_edit 
+    GROUP BY dt, user_id;
+```
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/INSERT.md b/docs/zh/sql-reference/sql-statements/loading_unloading/INSERT.md
new file mode 100644
index 00000000000000..6e52a0661e53c5
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/INSERT.md
@@ -0,0 +1,118 @@
+---
+displayed_sidebar: docs
+---
+
+# INSERT
+
+## 功能
+
+向 StarRocks 表中插入或覆盖写入数据。关于该种导入数据方式适用的场景请参考 [INSERT INTO 导入](../../../loading/InsertInto.md)。
+
+您可以通过 [SUBMIT TASK](ETL/SUBMIT_TASK.md) 创建异步 INSERT 任务。
+
+## 语法
+
+- **导入**:
+
+  ```sql
+  INSERT { INTO | OVERWRITE } [db_name.]<table_name>
+  [ PARTITION (<partition_name> [, ...] ) ]
+  [ TEMPORARY PARTITION (<temporary_partition_name> [, ...] ) ]
+  [ WITH LABEL <label>]
+  [ (<column_name>[, ...]) ]
+  { VALUES ( { <expression> | DEFAULT } [, ...] ) | <query> }
+  ```
+
+- **导出**:
+
+  ```sql
+  INSERT INTO FILES()
+  [ WITH LABEL <label> ]
+  { VALUES ( { <expression> | DEFAULT } [, ...] ) | <query> }
+  ```
+
+## 参数说明
+
+| **参数**    | **说明**                                                     |
+| ----------- | ------------------------------------------------------------ |
+| INTO        | 将数据追加写入目标表。                                       |
+| OVERWRITE   | 将数据覆盖写入目标表。                                       |
+| table_name  | 导入数据的目标表。可以为 `db_name.table_name` 形式。         |
+| PARTITION  | 导入的目标分区。此参数必须是目标表中存在的分区，多个分区名称用逗号（,）分隔。如果指定该参数，数据只会被导入相应分区内。如果未指定，则默认将数据导入至目标表的所有分区。 |
+| TEMPORARY PARTITION | 指定要把数据导入哪些[临时分区](../../../table_design/Temporary_partition.md)。|
+| label       | 导入作业的标识，数据库内唯一。如果未指定，StarRocks 会自动为作业生成一个 Label。建议您指定 Label。否则，如果当前导入作业因网络错误无法返回结果，您将无法得知该导入操作是否成功。如果指定了 Label，可以通过 SQL 命令 `SHOW LOAD WHERE label="label";` 查看任务结果。关于 Label 命名要求，参见[系统限制](../../System_limit.md)。 |
+| column_name | 导入的目标列，必须是目标表中存在的列。该参数的对应关系与列名无关，但与其顺序一一对应。如果不指定目标列，默认为目标表中的所有列。如果源表中的某个列在目标列不存在，则写入默认值。如果当前列没有默认值，导入作业会失败。如果查询语句的结果列类型与目标列的类型不一致，会进行隐式转化，如果不能进行转化，那么 INSERT INTO 语句会报语法解析错误。<br />**说明**<br />自 v3.3.1 起，INSERT INTO 导入主键表时指定 Column List 会执行部分列更新（而在先前版本中，指定 Column List 仍然导致 Full Upsert）。如不指定 Column List，系统执行 Full Upsert。 |
+| expression  | 表达式，用以为对应列赋值。                                   |
+| DEFAULT     | 为对应列赋予默认值。                                         |
+| query       | 查询语句，查询的结果会导入至目标表中。查询语句支持任意 StarRocks 支持的 SQL 查询语法。 |
+| FILES()       | 表函数 [FILES()](../../sql-functions/table-functions/files.md)。您可以通过该函数将数据导出至远端存储。更多信息，请参考 [使用 INSERT INTO FILES() 导出数据](../../../unloading/unload_using_insert_into_files.md). |
+
+## 注意事项
+
+- 当前版本中，StarRocks 在执行 INSERT 语句时，如果有数据不符合目标表格式的数据（例如字符串超长等情况），INSERT 操作默认执行失败。您可以通过设置会话变量 `enable_insert_strict` 为 `false` 以确保 INSERT 操作过滤不符合目标表格式的数据，并继续执行。
+
+- 执行 INSERT OVERWRITE 语句后，系统将为目标分区创建相应的临时分区，并将数据写入临时分区，最后使用临时分区原子替换目标分区来实现覆盖写入。其所有过程均在在 Leader FE 节点执行。因此，如果 Leader FE 节点在覆盖写入过程中发生宕机，将会导致该次 INSERT OVERWRITE 导入失败，其过程中所创建的临时分区也会被删除。
+
+## 示例
+
+以下示例基于表 `test`，其中包含两个列 `c1` 和 `c2`。`c2` 列有默认值 DEFAULT。
+
+### 示例一：向 test 表中导入一行数据
+
+```SQL
+INSERT INTO test VALUES (1, 2);
+INSERT INTO test (c1, c2) VALUES (1, 2);
+INSERT INTO test (c1, c2) VALUES (1, DEFAULT);
+INSERT INTO test (c1) VALUES (1);
+```
+
+- 在不指定目标列时，使用表中的列顺序来作为默认的目标列导入顺序。因此以上示例中，第一条、第二条 SQL 语句导入效果相同。
+- 如果有目标列未插入数据或使用 DEFAULT 作为值插入数据，该列将使用默认值作为导入数据。因此以上示例中，第三条、第四条语句导入效果相同。
+
+### 示例二：向 test 表中一次性导入多行数据
+
+```SQL
+INSERT INTO test VALUES (1, 2), (3, 2 + 2);
+INSERT INTO test (c1, c2) VALUES (1, 2), (3, 2 * 2);
+INSERT INTO test (c1) VALUES (1), (3);
+INSERT INTO test (c1, c2) VALUES (1, DEFAULT), (3, DEFAULT);
+```
+
+- 因表达式结果相同，以上示例中，第一条、第二条 SQL 语句导入效果相同。
+- 第三条、第四条语句使用 DEFAULT 作为值插入数据，因此导入效果相同。
+
+### 示例三：向 test 表中导入一个查询语句结果
+
+```SQL
+INSERT INTO test SELECT * FROM test2;
+INSERT INTO test (c1, c2) SELECT * from test2;
+```
+
+### 示例四：向 test 表中导入一个查询语句结果，并指定分区和 Label
+
+```SQL
+INSERT INTO test PARTITION(p1, p2) WITH LABEL `label1` SELECT * FROM test2;
+INSERT INTO test WITH LABEL `label1` (c1, c2) SELECT * from test2;
+```
+
+### 示例五：向 test 表中覆盖写入一个查询语句结果，并指定分区和 Label
+
+```SQL
+INSERT OVERWRITE test PARTITION(p1, p2) WITH LABEL `label1` SELECT * FROM test3;
+INSERT OVERWRITE test WITH LABEL `label1` (c1, c2) SELECT * from test3;
+```
+
+### 示例六：从 AWS S3 中导入 Parquet 数据文件
+
+以下示例将 AWS S3 存储桶 `inserttest` 内 Parquet 文件 **parquet/insert_wiki_edit_append.parquet** 中的数据插入至表 `insert_wiki_edit` 中：
+
+```Plain
+INSERT INTO insert_wiki_edit
+    SELECT * FROM TABLE(
+        "path" = "s3://inserttest/parquet/insert_wiki_edit_append.parquet",
+        "format" = "parquet",
+        "aws.s3.access_key" = "xxxxxxxxxx",
+        "aws.s3.secret_key" = "yyyyyyyyyy",
+        "aws.s3.region" = "aa-bbbb-c"
+);
+```
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md b/docs/zh/sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md
new file mode 100644
index 00000000000000..834e03d1c81ff0
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/SHOW_LOAD.md
@@ -0,0 +1,176 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW LOAD
+
+## 功能
+
+查看数据库中指定导入作业的相关信息，包括 [Broker Load](BROKER_LOAD.md)、[INSERT](INSERT.md) 和 [Spark Load](SPARK_LOAD.md)。您还可以使用 `curl` 命令查看这些导入作业的相关信息。注意，从 3.1 版本起，对于 Broker Load 和 Insert 导入，推荐您通过 [SELECT](../table_bucket_part_index/SELECT.md) 语句从 `information_schema` 数据库中的 [`loads`](../../information_schema/loads.md) 表来查看作业结果。详请参见[从 HDFS 导入](../../../loading/hdfs_load.md)、[从云存储导入](../../../loading/cloud_storage_load.md)、[通过 INSERT 语句导入数据](../../../loading/InsertInto.md)和[使用 Apache Spark™ 批量导入](../../../loading/SparkLoad.md)。
+
+除了以上三种导入方式， StarRocks 还支持 Stream Load 和 Routine Load，其中 Stream Load 是同步操作，会直接返回结果，不会通过 SHOW LOAD 展示。Routine Load 可通过 [SHOW ROUTINE LOAD](routine_load/SHOW_ROUTINE_LOAD.md) 查看导入作业的相关信息。
+
+## 语法
+
+```SQL
+SHOW LOAD [ FROM db_name ]
+[
+   WHERE [ LABEL { = "label_name" | LIKE "label_matcher" } ]
+         [ [AND] STATE = { "PENDING" | "ETL" | "LOADING" | "FINISHED" | "CANCELLED" } ]
+]
+[ ORDER BY field_name [ ASC | DESC ] ]
+[ LIMIT { [offset, ] limit | limit OFFSET offset } ]
+```
+
+> **说明**
+>
+> 返回结果中的字段较多，可使用`\G`分行，如 `SHOW LOAD WHERE LABEL = "label1"\G`。详情参见[示例一](#示例)。
+
+## 参数说明
+
+| **参数**                          | **必选** | **说明**                                                     |
+| --------------------------------- | -------- | ------------------------------------------------------------ |
+| db_name                           | 否       | 数据库名称。如不指定该参数，则默认查看当前数据库的导入作业。 |
+| LABEL = "label_name"              | 否       | 导入作业标签。                                               |
+| LABEL LIKE "label_matcher"        | 否       | 查看标签中包含 `label_matcher` 的导入作业。                  |
+| AND                               | 否       | <ul><li>如果只使用其中一个过滤条件，则不需要指定该关键字。例如 `WHERE STATE = "PENDING"`。</li><li>如使用其中任意两个或三个过滤条件，则需要指定该关键字。例如 `WHERE LABEL = "label_name" AND STATE = "PENDING"`。</li></ul> |
+| STATE                             | 否       | 导入作业的状态。不同的导入方式有不同的导入作业状态，具体如下：<ul><li>Broker Load<ul><li>`PENDING`：导入作业已创建。</li><li>`QUEUEING`：导入作业正在等待执行中。</li><li>`LOADING`：导入作业正在执行中。</li><li>`PREPARED`：事务已提交。</li><li>`FINISHED`：导入作业成功。</li><li>`CANCELLED`：导入作业失败。</li></ul></li><li>Spark Load<ul><li>`PENDING`：准备 ETL 任务的相关配置并提交 ETL 任务到 Apache Spark™ 集群。</li><li>`ETL`：Spark 集群执行 ETL 任务，并将结果数据写入 Spark 的 HDFS 中。</li><li>`LOADING`：正在将 HDFS 源数据导入到 StarRocks 的目标表中。</li><li>`PREPARED`：事务已提交。</li><li>`FINISHED`：导入作业成功。</li><li>`CANCELLED`：导入作业失败。</li></ul></li><li>INSERT<ul><li>`FINISHED`：导入作业成功。</li><li>`CANCELLED`：导入作业失败。</li></ul></li></ul>如不指定 `STATE` 参数，则默认显示所有状态的导入作业；如指定，则显示指定状态的导入作业。例如 `STATE = "PENDING"` 会显示状态为 `PENDING` 的导入作业。|
+| ORDER BY field_name [ASC \| DESC] | 否       | 将返回结果按照指定字段升序或降序排列，当前支持的排序字段（field_name）包括 `JobId`、`Label`、`State`、`Progress`、`Type`、`EtlInfo`、`TaskInfo`、`ErrorMsg`、`CreateTime`、`EtlStartTime`、`EtlFinishTime`、`LoadStartTime`、`LoadFinishTime`、`URL` 和 `JobDetails`。<ul><li>如要升序排列，指定 `ORDER BY field_name ASC`。</li><li>如要降序排列，指定 `ORDER BY field_name DESC`。</li></ul>如既不指定排序字段也不指定排列顺序，则默认按照 `JobId` 升序排列。 |
+| LIMIT limit                       | 否       | 查看指定数量的作业。如不指定该参数，则默认显示所有符合筛选条件的作业；如指定，则显示指定数量的作业。例如 `LIMIT 10` 会显示 10 个符合筛选条件的作业。 |
+| OFFSET offset                     | 否       | `offset` 定义了返回结果中跳过的导入作业的数量，其默认值为 0。例如 `OFFSET 5` 表示跳过前 5 个导入作业，返回剩下的结果。 |
+
+## 返回结果说明
+
+```plain
++-------+-------+-------+----------+------+---------+----------+----------+------------+--------------+---------------+---------------+----------------+-----+------------+
+| JobId | Label | State | Progress | Type | Priority | EtlInfo | TaskInfo | ErrorMsg | CreateTime | EtlStartTime | EtlFinishTime | LoadStartTime | LoadFinishTime | URL | JobDetails |
++-------+-------+-------+----------+------+---------+----------+----------+------------+--------------+---------------+---------------+----------------+-----+------------+
+```
+
+导入方式不同，返回结果中的字段取值也有差异，具体如下。
+
+| **字段**       | **Broker Load**                                              | **Spark Load**                                               | **INSERT**                                                   |
+| -------------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
+| JobId          | 导入作业的全局唯一 ID，由 StarRocks 自动生成。               | 同 Broker Load。                                             | 同 Broker Load。                                             |
+| Label          | 导入作业的标签。每个数据库中的导入作业都一个唯一的标签，不同数据库的导入作业标签可以重复。 | 同 Broker Load。                                             | 同 Broker Load。                                             |
+| State          | 导入作业的状态，包括:<ul><li>`PENDING`：导入作业已创建。</li><li>`QUEUEING`：导入作业正在等待执行中。</li><li>`LOADING`：导入作业正在执行中。</li><li>`PREPARED`：事务已提交。</li><li>`FINISHED`：导入作业成功。</li><li>`CANCELLED`：导入作业失败。</li></ul> | 导入作业的状态，包括：<ul><li>`PENDING`：准备 ETL 任务的相关配置并提交 ETL 任务到 Spark 集群。</li><li>`ETL`：Spark 集群执行 ETL 任务，并将结果写入 Spark 的 HDFS 中。</li><li>`LOADING`：正在将 HDFS 源数据导入到 StarRocks 的目标表中。</li><li>`PREPARED`：事务已提交。</li><li>`FINISHED`：导入作业成功。</li><li>`CANCELLED`：导入作业失败。</li></ul> | 导入作业的状态，包括：<ul><li>`FINISHED`：导入作业成功。</li><li>`CANCELLED`：导入作业失败。</li></ul> |
+| Progress       | 导入作业所处的阶段。Broker Load 导入作业只有 `LOAD` 阶段，对应导入作业状态中的 `LOADING`。 `LOAD` 进度为 0~100%。Broker Load 没有 `ETL` 阶段，所以 `ETL` 对应的取值并无实际意义。<br />**说明**：<ul><li>`LOAD` 进度的计算公式为：完成数据导入的目标表的个数/导入作业中要进行数据导入的目标表的个数 * 100%。</li><li>当数据导入到所有目标表中时，`LOAD` 进度显示为 99%， 此时，导入进入最后的生效阶段。当整个导入流程完成后，`LOAD` 进度才会显示为 100%。</li><li>导入进度并不是线性的。如果一段时间内进度没有变化，并不代表导入没有在继续执行。</li></ul> | 导入作业所处的阶段。Spark Load 导入作业，包括 `ETL` 和 `LOAD` 两种阶段，分别对应导入作业状态中的 `ETL` 和 `LOADING`。 `ETL` 和 `LOAD` 进度均为 0~100%。<br />**说明**同 Broker Load。 | 导入作业所处的阶段。INSERT 导入作业只有 `LOAD` 阶段，没有 `ETL` 阶段，所以 `ETL` 对应的取值并无实际意义。`LOAD` 进度为 0~100%。<br />**说明**同 Broker Load。 |
+| Type           | 导入方式，取值为 `BROKER`。                                  | 导入方式，取值为 `SPARK`。                                    | 导入方式， 取值为 `INSERT`。                                  |
+| Priority       | 导入作业的执行优先级，包括：LOWEST、LOW、NORMAL、HIGH 和 HIGHEST。                           | -                                  | -                                  |
+| EtlInfo        | ETL 信息，包括以下 3 个指标：<ul><li>`unselected.rows`：通过 WHERE 子句指定的条件而过滤掉的行数。</li><li>`dpp.abnorm.ALL`：因数据质量不合格而过滤掉的行数。数据质量不合格是指源表中数据类型或列数等和目标表不匹配的数据行。</li><li>`dpp.norm.ALL`：实际导入的行数。</li></ul>以上三个指标之和就是数据源的总行数。您可以根据这三个指标计算当前导入作业数据质量不合格的比例是否超过 `max-filter-ratio`，计算公式为：`dpp.abnorm.ALL`/(`unselected.rows` + `dpp.abnorm.ALL` + `dpp.norm.ALL`)。 | 同 Broker Load。                                             | ETL 信息。由于 INSERT 没有 ETL 阶段，所以该参数值为 `NULL`。  |
+| TaskInfo       | 创建导入作业时指定的参数，包括：<ul><li>`resource`：该参数在 Broker Load 导入作业中无实际意义。</li><li>`timeout`：导入作业的超时时间。单位：秒。</li><li>`max-filter-ratio`：导入作业的最大容忍率，即导入作业能够容忍的因数据不规范等原因而过滤掉的数据行所占的最大比例。</li></ul>有关以上参数的详细信息，参见 [BROKER LOAD](BROKER_LOAD.md)。 | 创建导入作业时指定的参数，包括：<ul><li>`resource`：资源名称。</li><li>`timeout`：导入作业的超时时间。单位：秒。</li><li>`max-filter-ratio`：导入作业的最大容忍率，即导入作业能够容忍的因数据不规范等原因而过滤掉的数据行所占的最大比例。</li></ul>有关以上参数的详细信息，参见 [SPARK LOAD](SPARK_LOAD.md)。 | 创建导入作业时指定的参数，包括：<ul><li>`resource`：该参数在 INSERT 导入作业中无实际意义。</li><li>`timeout`：导入作业的超时时间。单位：秒。</li><li>`max-filter-ratio`：该参数在 INSERT 导入作业中无实际意义。</li></ul>详细信息，参见 [INSERT](INSERT.md)。 |
+| ErrorMsg       | 导入作业的失败原因。当导入作业的状态为 `PENDING`，`LOADING` 或 `FINISHED` 时，该参数值为 `NULL`。当导入作业的状态为 `CANCELLED` 时，该参数值包括 `type` 和 `msg` 两部分：<ul><li>`type` 包括如下取值：<ul><li>`USER_CANCEL`：导入作业被手动取消。</li><li>`ETL_SUBMIT_FAIL`：导入任务提交失败。</li><li>`ETL_QUALITY_UNSATISFIED`：数据质量不合格，即导入作业的错误数据率超过了 `max-filter-ratio`。</li><li>`LOAD_RUN_FAIL`：导入作业在 `LOAD` 阶段失败。</li><li>`TIMEOUT`：导入作业未在允许的超时时间内完成。</li><li>`UNKNOWN`：未知的导入错误。</li></ul></li><li>`msg`显示有关失败原因的详细信息。</li></ul> | 导入作业的失败原因。当导入作业的状态为 `PENDING`、`ETL`、`LOADING` 或 `FINISHED` 时，该参数值为 `NULL`。当导入作业的状态为 `CANCELLED` 时，该参数值包括 `type` 和 `msg` 两部分：<ul><li>`type` 包括如下取值：<ul><li>`USER_CANCEL`：导入作业被手动取消。</li><li>`ETL_SUBMIT_FAIL`：ETL 提交失败。</li><li>`ETL_RUN_FAIL`： ETL 执行失败。</li><li>`ETL_QUALITY_UNSATISFIED`：数据质量不合格，即导入作业的错误数据率超过了 `max-filter-ratio`。</li><li>`LOAD_RUN_FAIL`：导入作业在 `LOAD` 阶段失败。</li><li>`TIMEOUT`：导入作业未在允许的超时时间内完成。</li><li>`UNKNOWN`：未知的导入错误。</li></ul></li><li>`msg`显示有关失败原因的详细信息。</li></ul> | 导入作业的失败原因。当导入作业的状态为 `FINISHED` 时，该参数值为 `NULL`。当导入作业的状态为 `CANCELLED` 时，该参数值包括 `type` 和 `msg` 两部分：<ul><li>`type` 包括如下取值：<ul><li>`USER_CANCEL`：导入作业被手动取消。</li><li>`ETL_SUBMIT_FAIL`：导入作业提交失败。</li><li>`ETL_RUN_FAIL`：导入作业执行失败。</li><li>`ETL_QUALITY_UNSATISFIED`：数据质量不合格，导入作业失败。</li><li>`LOAD_RUN_FAIL`：导入作业在 `LOAD` 阶段失败。</li><li>`TIMEOUT`：导入作业未在允许的超时时间内完成。</li><li>`UNKNOWN`：未知的导入错误。</li><li>`TXN_UNKNOWN`：事务状态未知，导入作业失败。</li></ul></li><li>`msg` 显示有关失败原因的详细信息。</li></ul> |
+| CreateTime     | 导入作业创建的时间。                                         | 同 Broker Load。                                             | 同 Broker Load。                                             |
+| EtlStartTime   | 由于 Broker Load 导入没有 ETL 阶段，所以该参数值和 `LoadStartTime` 相同。 | `ETL` 阶段开始的时间。                                        | 由于 INSERT 导入没有 ETL 阶段，所以该参数取值和 `LoadStartTime` 相同。 |
+| EtlFinishTime  | 由于 Broker Load 导入没有 ETL 阶段，所以该参数值和 `LoadStartTime` 相同。 | `ETL` 阶段完成的时间。                                        | 由于 INSERT 导入没有 ETL 阶段，所以该参数取值和 `LoadStartTime` 相同。 |
+| LoadStartTime  | `LOAD` 阶段开始的时间。                                       | 同 Broker Load。                                             | 同 Broker Load。                                             |
+| LoadFinishTime | 导入作业完成的时间。                                         | 同 Broker Load。                                             | 同 Broker Load。                                             |
+| URL            | 导入作业中质量不合格数据的访问地址。您可以使用 `curl` 或 `wget` 命令打开该地址。如果导入作业不存在质量不合格数据，该参数值为 `NULL`。 | 同 Broker Load。                                             | 同 Broker Load。                                             |
+| JobDetails     | 导入作业的其他信息，包括：<ul><li>`Unfinished backends`：未完成导入的 BE 节点 ID。</li><li>`ScannedRows`：实际处理的行数，包括导入的行数以及过滤掉的行数。</li><li>`TaskNumber`：子作业个数。</li><li>`All backends`：正在运行子作业的 BE 节点的 ID。</li><li>`FileNumber`：源文件的个数。</li><li>`FileSize`：所有源文件的总数据量，单位：字节。</li></ul> | 同 Broker Load。                                             | 同 Broker Load。                                             |
+
+## 注意事项
+
+- 导入作业相关信息具有时效性。默认自一个导入作业的完成时间 (`LoadFinishTime`) 起 3 天内可以查看到该导入作业的相关信息；3 天后，信息会失效，无法查到。您可以通过 FE 参数 `label_keep_max_second` 修改默认有效时间（单位：秒），操作如下：
+
+    ```SQL
+    ADMIN SET FRONTEND CONFIG ("label_keep_max_second" = "value");
+    ```
+
+- 若导入作业的 `LoadStartTime` 长时间为 `N/A`，说明导入作业堆积严重，可降低作业创建的频率。
+- 导入作业所消耗的总时长 = `LoadFinishTime` - `CreateTime`。
+- `LOAD` 阶段所消耗的时长 = `LoadFinishTime` - `LoadStartTime`。
+
+## 示例
+
+示例一：查看当前数据库中的所有导入作业。
+
+```plain
+SHOW LOAD\G;
+*************************** 1. row ***************************
+         JobId: 976331
+         Label: duplicate_table_with_null
+         State: FINISHED
+      Progress: ETL:100%; LOAD:100%
+          Type: BROKER
+      Priority: NORMAL 
+       EtlInfo: unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546
+      TaskInfo: resource:N/A; timeout(s):300; max_filter_ratio:0.0
+      ErrorMsg: NULL
+    CreateTime: 2022-10-17 19:35:00
+  EtlStartTime: 2022-10-17 19:35:04
+ EtlFinishTime: 2022-10-17 19:35:04
+ LoadStartTime: 2022-10-17 19:35:04
+LoadFinishTime: 2022-10-17 19:35:06
+           URL: NULL
+    JobDetails: {"Unfinished backends":{"b90a703c-6e5a-4fcb-a8e1-94eca5be0b8f":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"b90a703c-6e5a-4fcb-a8e1-94eca5be0b8f":[10004]},"FileNumber":1,"FileSize":548622}
+```
+
+示例二：查看当前数据库中的导入作业。导入作业的标签中需包含字符串 `null`，且仅展示 2 个作业。
+
+```plain
+SHOW LOAD 
+WHERE LABEL LIKE "null" 
+LIMIT 2;
+
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| JobId | Label                     | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                                                                                | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL                                                                            | JobDetails                                                                                                                                                                                              |
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| 10082 | duplicate_table_with_null | FINISHED | ETL:100%; LOAD:100% | BROKER | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:N/A; timeout(s):300; max_filter_ratio:0.0                                                      | NULL     | 2022-08-02 14:53:27 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:31 | NULL                                                                           | {"Unfinished backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[10002]},"FileNumber":1,"FileSize":548622} |
+| 10103 | unique_table_with_null    | FINISHED | ETL:100%; LOAD:100% | SPARK  | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:test_spark_resource_07af473a_1230_11ed_b483_00163e0e550b; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:56:06 | 2022-08-02 14:56:19 | 2022-08-02 14:56:41 | 2022-08-02 14:56:41 | 2022-08-02 14:56:44 | http://emr-header-1.cluster-49091:20888/proxy/application_1655710334658_26391/ | {"Unfinished backends":{"00000000-0000-0000-0000-000000000000":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"00000000-0000-0000-0000-000000000000":[-1]},"FileNumber":1,"FileSize":8790855}   |
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
+
+示例三： 查看数据库 `example_db` 中的导入作业。导入作业的标签中需包含字符串 `table`，且按 `LoadStartTime` 降序排序。
+
+```plain
+SHOW LOAD FROM example_db 
+WHERE LABEL Like "table" 
+ORDER BY LoadStartTime DESC;
+
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| JobId | Label                     | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                                                                                | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL                                                                            | JobDetails                                                                                                                                                                                              |
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| 10103 | unique_table_with_null    | FINISHED | ETL:100%; LOAD:100% | SPARK  | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:test_spark_resource_07af473a_1230_11ed_b483_00163e0e550b; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:56:06 | 2022-08-02 14:56:19 | 2022-08-02 14:56:41 | 2022-08-02 14:56:41 | 2022-08-02 14:56:44 | http://emr-header-1.cluster-49091:20888/proxy/application_1655710334658_26391/ | {"Unfinished backends":{"00000000-0000-0000-0000-000000000000":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"00000000-0000-0000-0000-000000000000":[-1]},"FileNumber":1,"FileSize":8790855}   |
+| 10082 | duplicate_table_with_null | FINISHED | ETL:100%; LOAD:100% | BROKER | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:N/A; timeout(s):300; max_filter_ratio:0.0                                                      | NULL     | 2022-08-02 14:53:27 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:31 | NULL                                                                           | {"Unfinished backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[10002]},"FileNumber":1,"FileSize":548622} |
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
+
+示例四：查看数据库 `example_db` 中的导入作业。导入作业的标签需为 `duplicate_table_with_null`，状态需为 `FINISHED`。
+
+```plain
+SHOW LOAD FROM example_db 
+WHERE LABEL = "duplicate_table_with_null" AND STATE = "FINISHED";
+
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+----------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| JobId | Label                     | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                           | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL  | JobDetails                                                                                                                                                                                              |
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+----------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| 10082 | duplicate_table_with_null | FINISHED | ETL:100%; LOAD:100% | BROKER | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:N/A; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:53:27 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:30 | 2022-08-02 14:53:31 | NULL | {"Unfinished backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"4393c992-5da1-4e9f-8b03-895dc0c96dbc":[10002]},"FileNumber":1,"FileSize":548622} |
++-------+---------------------------+----------+---------------------+--------+---------------------------------------------------------+----------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
+
+示例五：查看数据库 `example_db` 中的导入作业。导入作业需按 `CreateTime` 升序排序，并从偏移量 1 开始显示 2 条查询结果。
+
+```sql
+SHOW LOAD FROM example_db 
+ORDER BY CreateTime ASC 
+LIMIT 2 OFFSET 1;
+```
+
+或
+
+```sql
+SHOW LOAD FROM example_db 
+ORDER BY CreateTime ASC 
+LIMIT 1,2;
+```
+
+返回结果如下：
+
+```plain
++-------+---------------------------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| JobId | Label                                       | State    | Progress            | Type   | EtlInfo                                                 | TaskInfo                                                                                                | ErrorMsg | CreateTime          | EtlStartTime        | EtlFinishTime       | LoadStartTime       | LoadFinishTime      | URL                                                                            | JobDetails                                                                                                                                                                                            |
++-------+---------------------------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| 10103 | unique_table_with_null                      | FINISHED | ETL:100%; LOAD:100% | SPARK  | unselected.rows=0; dpp.abnorm.ALL=0; dpp.norm.ALL=65546 | resource:test_spark_resource_07af473a_1230_11ed_b483_00163e0e550b; timeout(s):300; max_filter_ratio:0.0 | NULL     | 2022-08-02 14:56:06 | 2022-08-02 14:56:19 | 2022-08-02 14:56:41 | 2022-08-02 14:56:41 | 2022-08-02 14:56:44 | http://emr-header-1.cluster-49091:20888/proxy/application_1655710334658_26391/ | {"Unfinished backends":{"00000000-0000-0000-0000-000000000000":[]},"ScannedRows":65546,"TaskNumber":1,"All backends":{"00000000-0000-0000-0000-000000000000":[-1]},"FileNumber":1,"FileSize":8790855} |
+| 10120 | insert_3a57b595-1230-11ed-b075-00163e14c85e | FINISHED | ETL:100%; LOAD:100% | INSERT | NULL                                                    | resource:N/A; timeout(s):3600; max_filter_ratio:0.0                                                     | NULL     | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 | 2022-08-02 14:56:26 |                                                                                | {"Unfinished backends":{},"ScannedRows":0,"TaskNumber":0,"All backends":{},"FileNumber":0,"FileSize":0}                                                                                               |
++-------+---------------------------------------------+----------+---------------------+--------+---------------------------------------------------------+---------------------------------------------------------------------------------------------------------+----------+---------------------+---------------------+---------------------+---------------------+---------------------+--------------------------------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/SHOW_TRANSACTION.md b/docs/zh/sql-reference/sql-statements/loading_unloading/SHOW_TRANSACTION.md
new file mode 100644
index 00000000000000..5c55e83dd7eff3
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/SHOW_TRANSACTION.md
@@ -0,0 +1,65 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW TRANSACTION
+
+## 功能
+
+该语法用于查看指定 transaction id 的事务详情。
+
+## 语法
+
+```sql
+SHOW TRANSACTION
+[FROM <db_name>]
+WHERE id = <transaction_id>
+```
+
+返回结果示例：
+
+```plain text
+TransactionId: 4005
+Label: insert_8d807d5d-bcdd-46eb-be6d-3fa87aa4952d
+Coordinator: FE: 10.74.167.16
+TransactionStatus: VISIBLE
+LoadJobSourceType: INSERT_STREAMING
+PrepareTime: 2020-01-09 14:59:07
+CommitTime: 2020-01-09 14:59:09
+FinishTime: 2020-01-09 14:59:09
+Reason:
+ErrorReplicasCount: 0
+ListenerId: -1
+TimeoutMs: 300000
+```
+
+* TransactionId：事务 id
+* Label：导入任务对应的 label
+* Coordinator：负责事务协调的节点
+* TransactionStatus：事务状态
+* PREPARE：准备阶段
+* COMMITTED：事务成功，但数据不可见
+* VISIBLE：事务成功且数据可见
+* ABORTED：事务失败
+* LoadJobSourceType：导入任务的类型
+* PrepareTime：事务开始时间
+* CommitTime：事务提交成功的时间
+* FinishTime：数据可见的时间
+* Reason：错误信息
+* ErrorReplicasCount：有错误的副本数
+* ListenerId：相关的导入作业的 id
+* TimeoutMs：事务超时时间，单位毫秒
+
+## 示例
+
+1. 查看 id 为 4005 的事务：
+
+    ```sql
+    SHOW TRANSACTION WHERE ID=4005;
+    ```
+
+2. 指定 db 中，查看 id 为 4005 的事务：
+
+    ```sql
+    SHOW TRANSACTION FROM db WHERE ID=4005;
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md b/docs/zh/sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md
new file mode 100644
index 00000000000000..7f28e58171678c
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/SPARK_LOAD.md
@@ -0,0 +1,293 @@
+---
+displayed_sidebar: docs
+---
+
+# SPARK LOAD
+
+## 功能
+
+Spark load 通过外部的 Spark 资源实现对导入数据的预处理，提高 StarRocks 大数据量的导入性能并且节省 StarRocks 集群的计算资源。主要用于初次迁移，大数据量导入 StarRocks 的场景。
+
+Spark load 是一种异步导入方式，用户需要通过 MySQL 协议创建 Spark 类型导入任务，并通过 `SHOW LOAD` 查看导入结果。
+
+> **注意**
+>
+> - Spark Load 操作需要目标表的 INSERT 权限。如果您的用户账号没有 INSERT 权限，请参考 [GRANT](../account-management/GRANT.md) 给用户赋权。
+> - 使用 Spark Load 导入数据至 StarRocks 表时，不支持该表分桶列的数据类型为 DATE、DATETIME 或者 DECIMAL。
+
+## 语法
+
+```sql
+LOAD LABEL load_label
+(
+data_desc1[, data_desc2, ...]
+)
+WITH RESOURCE resource_name
+[resource_properties]
+[opt_properties]
+```
+
+1.load_label
+
+当前导入批次的标签。在一个 database 内唯一。
+
+语法：
+
+```sql
+[database_name.]your_label
+```
+
+2.data_desc
+
+用于描述一批导入数据。
+
+语法：
+
+```sql
+DATA INFILE
+(
+"file_path1"[, file_path2, ...]
+)
+[NEGATIVE]
+INTO TABLE `table_name`
+[PARTITION (p1, p2)]
+[COLUMNS TERMINATED BY "column_separator"]
+[FORMAT AS "file_type"]
+[(column_list)]
+[COLUMNS FROM PATH AS (col2, ...)]
+[SET (k1 = func(k2))]
+[WHERE predicate]
+
+DATA FROM TABLE hive_external_tbl
+[NEGATIVE]
+INTO TABLE tbl_name
+[PARTITION (p1, p2)]
+[SET (k1=f1(xx), k2=f2(xx))]
+[WHERE predicate]
+```
+
+说明：
+
+```plain text
+file_path:
+
+文件路径，可以指定到一个文件，也可以用 * 通配符指定某个目录下的所有文件。通配符必须匹配到文件，而不能是目录。
+
+hive_external_tbl:
+
+hive 外部表名。
+要求导入的 starrocks 表中的列必须在 hive 外部表中存在。
+每个导入任务只支持从一个 hive 外部表导入。
+不能与 file_path 方式同时使用。
+
+PARTITION:
+
+如果指定此参数，则只会导入指定的分区，导入分区以外的数据会被过滤掉。
+如果不指定，默认导入table的所有分区。
+
+NEGATIVE：
+
+如果指定此参数，则相当于导入一批“负”数据。用于抵消之前导入的同一批数据。
+该参数仅适用于存在 value 列，并且 value 列的聚合类型仅为 SUM 的情况。
+
+column_separator：
+
+用于指定导入文件中的列分隔符。默认为：\t。
+如果是不可见字符，则需要加 \\x 作为前缀，使用十六进制来表示分隔符。
+如 hive 文件的分隔符 \x01，指定为 "\\x01"。
+
+file_type：
+
+用于指定导入文件的类型，目前仅支持csv、orc、parquet。
+
+column_list：
+
+用于指定导入文件中的列和 table 中的列的对应关系。
+当需要跳过导入文件中的某一列时，将该列指定为 table 中不存在的列名即可。
+
+语法：
+(col_name1, col_name2, ...)
+
+SET:
+
+如果指定此参数，可以将源文件某一列按照函数进行转化，然后将转化后的结果导入到 table 中。语法为 `column_name` = expression。
+仅支持 Spark SQL built-in functions，具体可参考 https://spark.apache.org/docs/2.4.6/api/sql/index.html。
+举几个例子帮助理解。
+例1: 表中有3个列“c1, c2, c3", 源文件中前两列依次对应(c1,c2)，后两列之和对应c3；那么需要指定 columns (c1,c2,tmp_c3,tmp_c4) SET (c3=tmp_c3+tmp_c4);
+例2: 表中有3个列“year, month, day"，源文件中只有一个时间列，为”2018-06-01 01:02:03“格式。
+那么可以指定 columns(tmp_time) set (year = year(tmp_time), month=month(tmp_time), day=day(tmp_time)) 完成导入。
+
+WHERE:
+
+对做完 transform 的数据进行过滤，符合 where 条件的数据才能被导入。WHERE 语句中只可引用表中列名。
+```
+
+3.resource_name
+
+所使用的 Spark 资源名称，可以通过 `SHOW RESOURCES` 命令查看。
+
+4.resource_properties
+
+[Spark 资源的配置](../Resource/CREATE_RESOURCE.md#spark-资源)。当用户有临时性的需求，比如增加任务使用的资源而修改 Spark 和 HDFS 配置，可以在这里设置，设置仅对本次任务生效，并不影响 StarRocks 集群中已有的配置。
+
+5.opt_properties
+
+用于指定一些特殊参数。
+
+语法：
+
+```sql
+[PROPERTIES ("key"="value", ...)]
+```
+
+可以指定如下参数：
+
+```plain text
+timeout：         指定导入操作的超时时间。默认超时为 4 小时。单位秒。
+max_filter_ratio：最大容忍可过滤（数据不规范等原因）的数据比例。默认零容忍。
+strict_mode：     是否对数据进行严格限制。默认为 false。
+timezone:         指定某些受时区影响的函数的时区，如 strftime/alignment_timestamp/from_unixtime 等等，具体请查阅 [时区](../../../administration/management/timezone.md) 文档。如果不指定，则使用 "Asia/Shanghai" 时区。
+```
+
+6.导入数据格式样例
+
+```plain text
+1.整型类（TINYINT/SMALLINT/INT/BIGINT/LARGEINT）：1, 1000, 1234。
+
+2.浮点类（FLOAT/DOUBLE/DECIMAL）：1.1, 0.23, .356。
+
+3.日期类（DATE/DATETIME）：2017-10-03, 2017-06-13 12: 34: 03。（注：如果是其他日期格式，可以在导入命令中，使用 strftime 或者 time_format 函数进行转换）
+
+4.字符串类（CHAR/VARCHAR）："I am a student", "a"。
+NULL 值：\N
+```
+
+## 示例
+
+### 从HDFS导入数据
+
+从 HDFS 导入一批数据，指定超时时间和过滤比例。使用名为 my_spark 的 spark 资源。
+
+```sql
+LOAD LABEL example_db.label1
+(
+DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/file")
+INTO TABLE `my_table`
+)
+WITH RESOURCE 'my_spark'
+PROPERTIES
+(
+    "timeout" = "3600",
+    "max_filter_ratio" = "0.1"
+);
+```
+
+其中 hdfs_host 为 namenode 的 host，hdfs_port 为 fs.defaultFS 端口（默认 9000）。
+
+### 从HDFS导入"负"数据
+
+从 HDFS 导入一批 "负" 数据，指定分隔符为逗号，使用通配符*指定目录下的所有文件，并指定 spark 资源的临时参数。"负" 数据详细含义见上文语法参数介绍部分。
+
+```sql
+LOAD LABEL example_db.label3
+(
+DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/*")
+NEGATIVE
+INTO TABLE `my_table`
+COLUMNS TERMINATED BY ","
+)
+WITH RESOURCE 'my_spark'
+(
+    "spark.executor.memory" = "3g",
+    "broker.username" = "hdfs_user",
+    "broker.password" = "hdfs_passwd"
+);
+```
+
+### 从HDFS导入数据到指定分区并进行列转换
+
+从 HDFS 导入一批数据，指定分区，并对导入文件的列做一些转化，如下：
+
+```plain text
+表结构为：
+k1 varchar(20)
+k2 int
+
+假设数据文件只有一行数据：
+
+Adele,1,1
+
+数据文件中各列，对应导入语句中指定的各列：
+k1,tmp_k2,tmp_k3
+
+转换如下：
+
+1. k1: 不变换
+2. k2：是 tmp_k2 和 tmp_k3 数据之和
+
+LOAD LABEL example_db.label6
+(
+DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/file")
+INTO TABLE `my_table`
+PARTITION (p1, p2)
+COLUMNS TERMINATED BY ","
+(k1, tmp_k2, tmp_k3)
+SET (
+k2 = tmp_k2 + tmp_k3
+)
+)
+WITH RESOURCE 'my_spark';
+```
+
+### 提取文件路径中的分区字段
+
+如果需要，则会根据表中定义的字段类型解析文件路径中的分区字段（partitioned fields），类似 Spark 中 Partition Discovery 的功能。
+
+```sql
+LOAD LABEL example_db.label10
+(
+DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/dir/city=beijing/*/*")
+INTO TABLE `my_table`
+(k1, k2, k3)
+COLUMNS FROM PATH AS (city, utc_date)
+SET (uniq_id = md5sum(k1, city))
+)
+WITH RESOURCE 'my_spark';
+```
+
+`hdfs://hdfs_host: hdfs_port/user/starRocks/data/input/dir/city = beijing` 目录下包括如下文件：
+
+`[hdfs://hdfs_host: hdfs_port/user/starRocks/data/input/dir/city = beijing/utc_date = 2019-06-26/0000.csv, hdfs://hdfs_host: hdfs_port/user/starRocks/data/input/dir/city = beijing/utc_date = 2019-06-26/0001.csv, ...]`
+
+则提取文件路径的中的 `city` 和 `utc_date` 字段。
+
+### 对导入数据进行过滤
+
+对待导入数据进行过滤，k1 值大于 10 的列才能被导入。
+
+```sql
+LOAD LABEL example_db.label10
+(
+DATA INFILE("hdfs://hdfs_host:hdfs_port/user/starRocks/data/input/file")
+INTO TABLE `my_table`
+WHERE k1 > 10
+)
+WITH RESOURCE 'my_spark';
+```
+
+### 从 Hive 外表导入并构建全局字典
+
+从 hive 外部表导入，并将源表中的 uuid 列通过全局字典转化为 bitmap 类型。
+
+```sql
+LOAD LABEL db1.label1
+(
+DATA FROM TABLE hive_t1
+INTO TABLE tbl1
+SET
+(
+uuid=bitmap_dict(uuid)
+)
+)
+WITH RESOURCE 'my_spark';
+```
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md b/docs/zh/sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md
new file mode 100644
index 00000000000000..f3b20ad7f9c9bb
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md
@@ -0,0 +1,570 @@
+---
+displayed_sidebar: docs
+toc_max_heading_level: 4
+---
+
+# STREAM LOAD
+
+## 功能
+
+Stream Load 是一种基于 HTTP 协议的同步导入方式，支持将本地文件或数据流导入到 StarRocks 中。您提交导入作业以后，StarRocks 会同步地执行导入作业，并返回导入作业的结果信息。您可以通过返回的结果信息来判断导入作业是否成功。有关 Stream Load 的应用场景、使用限制、基本原理、以及支持的数据文件格式等信息，请参见[使用 Stream Load 从本地导入](../../../loading/StreamLoad.md#使用-stream-load-从本地导入)。
+
+从 3.2.7 版本起，STREAM LOAD 支持在传输过程中对 JSON 数据进行压缩，减少网络带宽开销。用户可以通过 `compression` 或 `Content-Encoding` 参数指定不同的压缩方式，支持 GZIP、BZIP2、LZ4_FRAME、ZSTD 压缩算法。参见[相关语法](#data_desc)。
+
+> **注意**
+>
+> - Stream Load 操作会同时更新和 StarRocks 原始表相关的物化视图的数据。
+> - Stream Load 操作需要目标表的 INSERT 权限。如果您的用户账号没有 INSERT 权限，请参考 [GRANT](../account-management/GRANT.md) 给用户赋权。
+
+## 语法
+
+```Bash
+curl --location-trusted -u <username>:<password> -XPUT <url>
+(
+    data_desc
+)
+[opt_properties]        
+```
+
+本文以 curl 工具为例介绍如何使用 Stream Load 导入数据。除了使用 curl 工具，您还可以通过其他支持 HTTP 协议的工具或语言提交导入作业以导入数据。导入相关的参数位于 HTTP 请求的请求头。传入这些导入相关的参数时，需要注意以下几点：
+
+- 推荐使用**分块上传**方式，如本文示例所示。如果使用**非分块上传**方式，则必须使用请求头字段 `Content-Length` 来标示待上传内容的长度，从而保证数据完整性。
+
+  > **说明**
+  >
+  > 使用 curl 工具提交导入作业的时候，会自动添加 `Content-Length` 字段，因此无需手动指定 `Content-Length`。
+
+- 必须在 HTTP 请求的请求头字段 `Expect` 中指定 `100-continue`，即 `"Expect:100-continue"`。这样在服务器拒绝导入作业请求的情况下，可以避免不必要的数据传输，从而减少不必要的资源开销。
+
+注意在 StarRocks 中，部分文字是 SQL 语言的保留关键字，不能直接用于 SQL 语句。如果想在 SQL 语句中使用这些保留关键字，必须用反引号 (`) 包裹起来。参见[关键字](../keywords.md)。
+
+## 参数说明
+
+### username 和 password
+
+用于指定 StarRocks 集群账号的用户名和密码。必选参数。如果账号没有设置密码，这里只需要传入 `<username>:`。
+
+### XPUT
+
+用于指定 HTTP 请求方法。必选参数。Stream Load 当前只支持 PUT 方法。
+
+### url
+
+用于指定 StarRocks 表的 URL 地址。必选参数。语法如下：
+
+```Plain
+http://<fe_host>:<fe_http_port>/api/<database_name>/<table_name>/_stream_load
+```
+
+`url` 中的参数如下表所述。
+
+| 参数名称      | 是否必须 | 参数说明                                                     |
+| ------------- | -------- | ------------------------------------------------------------ |
+| fe_host       | 是       | 指定 StarRocks 集群中 FE 的 IP 地址。 <br />**说明**<br />如果您直接提交导入作业给某一个 BE（或 CN）节点，则需要传入该 BE（或 CN）的 IP 地址。 |
+| fe_http_port  | 是       | 指定 StarRocks 集群中 FE 的 HTTP 端口号。 默认端口号为 8030。 <br />**说明**<br />如果您直接提交导入作业给某一指定的 BE（或 CN）节点，则需要传入该 BE（或 CN）的 HTTP 端口号。默认端口号为 8040。 |
+| database_name | 是       | 指定目标 StarRocks 表所在的数据库的名称。                    |
+| table_name    | 是       | 指定目标 StarRocks 表的名称。                                |
+
+> **说明**
+>
+> 您可以通过 [SHOW FRONTENDS](../cluster-management/nodes_processes/SHOW_FRONTENDS.md) 命令查看 FE 节点的 IP 地址和 HTTP 端口号。
+
+### data_desc
+
+用于描述源数据文件，包括源数据文件的名称、格式、列分隔符、行分隔符、目标分区、以及与 StarRocks 表之间的列对应关系等。语法如下：
+
+```Bash
+-T <file_path>
+-H "format: CSV | JSON"
+-H "column_separator: <column_separator>"
+-H "row_delimiter: <row_delimiter>"
+-H "columns: <column1_name>[, <column2_name>，... ]"
+-H "partitions: <partition1_name>[, <partition2_name>, ...]"
+-H "temporary_partitions: <temporary_partition1_name>[, <temporary_partition2_name>, ...]"
+-H "jsonpaths: [ \"<json_path1>\"[, \"<json_path2>\", ...] ]"
+-H "strip_outer_array: true | false"
+-H "json_root: <json_path>"
+-H "ignore_json_size: true | false"
+-H "compression: <compression_algorithm> | Content-Encoding: <compression_algorithm>"
+```
+
+`data_desc` 中的参数可以分为三类：公共参数、CSV 适用的参数、以及 JSON 适用的参数。
+
+#### 公共参数
+
+| **参数名称** | **是否必选** | **参数说明**                                                 |
+| ------------ | ------------ | ------------------------------------------------------------ |
+| file_path    | 是           | 指定源数据文件的保存路径。文件名里可选包含或者不包含扩展名。 |
+| format       | 否           | 指定待导入数据的格式。取值包括 `CSV` 和 `JSON`。默认值：`CSV`。 |
+| partitions   | 否           | 指定要把数据导入哪些分区。如果不指定该参数，则默认导入到 StarRocks 表所在的所有分区中。 |
+| temporary_partitions | 否           | 指定要把数据导入哪些[临时分区](../../../table_design/Temporary_partition.md)。|
+| columns      | 否           | 指定源数据文件和 StarRocks 表之间的列对应关系。如果源数据文件中的列与 StarRocks 表中的列按顺序一一对应，则不需要指定 `columns` 参数。您可以通过 `columns` 参数实现数据转换。例如，要导入一个 CSV 格式的数据文件，文件中有两列，分别可以对应到目标 StarRocks 表的 `id` 和 `city` 两列。如果要实现把数据文件中第一列的数据乘以 100 以后再落入 StarRocks 表的转换，可以指定 `"columns: city,tmp_id, id = tmp_id * 100"`。具体请参见本文“[列映射](#列映射)”章节。 |
+
+#### CSV 适用参数
+
+| **参数名称**     | **是否必选** | **参数说明**                                                 |
+| ---------------- | ------------ | ------------------------------------------------------------ |
+| column_separator | 否           | 用于指定源数据文件中的列分隔符。如果不指定该参数，则默认为 `\t`，即 Tab。必须确保这里指定的列分隔符与源数据文件中的列分隔符一致。<br />**说明**<br />StarRocks 支持设置长度最大不超过 50 个字节的 UTF-8 编码字符串作为列分隔符，包括常见的逗号 (,)、Tab 和 Pipe (\|)。 |
+| row_delimiter    | 否           | 用于指定源数据文件中的行分隔符。如果不指定该参数，则默认为 `\n`。 |
+| skip_header      | 否           | 用于指定跳过 CSV 文件最开头的几行数据。取值类型：INTEGER。默认值：`0`。<br />在某些 CSV 文件里，最开头的几行数据会用来定义列名、列类型等元数据信息。通过设置该参数，可以使 StarRocks 在导入数据时忽略 CSV 文件的前面几行。例如，如果设置该参数为 `1`，则 StarRocks 会在导入数据时忽略 CSV 文件的第一行。<br />这里的行所使用的分隔符须与您在导入命令中所设定的行分隔符一致。 |
+| trim_space       | 否           | 用于指定是否去除 CSV 文件中列分隔符前后的空格。取值类型：BOOLEAN。默认值：`false`。<br />有些数据库在导出数据为 CSV 文件时，会在列分隔符的前后添加一些空格。根据位置的不同，这些空格可以称为“前导空格”或者“尾随空格”。通过设置该参数，可以使 StarRocks 在导入数据时删除这些不必要的空格。<br />需要注意的是，StarRocks 不会去除被 `enclose` 指定字符括起来的字段内的空格（包括字段的前导空格和尾随空格）。例如，列分隔符是竖线 (<code class="language-text">&#124;</code>)，`enclose` 指定的字符是双引号 (`"`)：<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124; "Love StarRocks" &#124;</code> <br />如果设置 `trim_space` 为 `true`，则 StarRocks 处理后的结果数据如下：<br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> <br /><code class="language-text">&#124;" Love StarRocks "&#124;</code> <br /><code class="language-text">&#124;"Love StarRocks"&#124;</code> |
+| enclose          | 否           | 根据 [RFC4180](https://www.rfc-editor.org/rfc/rfc4180)，用于指定把 CSV 文件中的字段括起来的字符。取值类型：单字节字符。默认值：`NONE`。最常用 `enclose` 字符为单引号 (`'`) 或双引号 (`"`)。<br />被 `enclose` 指定字符括起来的字段内的所有特殊字符（包括行分隔符、列分隔符等）均看做是普通符号。比 RFC4180 标准更进一步的是，StarRocks 提供的 `enclose` 属性支持设置任意单个字节的字符。<br />如果一个字段内包含了 `enclose` 指定字符，则可以使用同样的字符对 `enclose` 指定字符进行转义。例如，在设置了`enclose` 为双引号 (`"`) 时，字段值 `a "quoted" c` 在 CSV 文件中应该写作 `"a ""quoted"" c"`。 |
+| escape           | 否           | 指定用于转义的字符。用来转义各种特殊字符，比如行分隔符、列分隔符、转义符、`enclose` 指定字符等，使 StarRocks 把这些特殊字符当做普通字符而解析成字段值的一部分。取值类型：单字节字符。默认值：`NONE`。最常用的 `escape` 字符为斜杠 (`\`)，在 SQL 语句中应该写作双斜杠 (`\\`)。<br />**说明**<br />`escape` 指定字符同时作用于 `enclose` 指定字符的内部和外部。<br />以下为两个示例：<ul><li>当设置 `enclose` 为双引号 (`"`) 、`escape` 为斜杠 (`\`) 时，StarRocks 会把 `"say \"Hello world\""` 解析成一个字段值 `say "Hello world"`。</li><li>假设列分隔符为逗号 (`,`) ，当设置 `escape` 为斜杠 (`\`) ，StarRocks 会把 `a, b\, c` 解析成 `a` 和 `b, c` 两个字段值。</li></ul> |
+
+> **说明**
+>
+> 对于 CSV 格式的数据，需要注意以下两点：
+>
+> - StarRocks 支持设置长度最大不超过 50 个字节的 UTF-8 编码字符串作为列分隔符，包括常见的逗号 (,)、Tab 和 Pipe (|)。
+> - 空值 (null) 用 `\N` 表示。比如，数据文件一共有三列，其中某行数据的第一列、第三列数据分别为 `a` 和 `b`，第二列没有数据，则第二列需要用 `\N` 来表示空值，写作 `a,\N,b`，而不是 `a,,b`。`a,,b` 表示第二列是一个空字符串。
+> - `skip_header`、`trim_space`、`enclose` 和 `escape` 等属性在 3.0 及以后版本支持。
+
+#### JSON 适用参数
+
+| **参数名称**      | **是否必选** | **参数说明**                                                 |
+| ----------------- | ------------ | ------------------------------------------------------------ |
+| jsonpaths         | 否           | 用于指定待导入的字段的名称。仅在使用匹配模式导入 JSON 数据时需要指定该参数。参数取值为 JSON 格式。参见[导入 JSON 数据时配置列映射关系](#导入-json-数据时配置列映射关系)。    |
+| strip_outer_array | 否           | 用于指定是否裁剪最外层的数组结构。取值范围：`true` 和 `false`。默认值：`false`。真实业务场景中，待导入的 JSON 数据可能在最外层有一对表示数组结构的中括号 `[]`。这种情况下，一般建议您指定该参数取值为 `true`，这样 StarRocks 会剪裁掉外层的中括号 `[]`，并把中括号 `[]` 里的每个内层数组都作为一行单独的数据导入。如果您指定该参数取值为 `false`，则 StarRocks 会把整个 JSON 数据文件解析成一个数组，并作为一行数据导入。例如，待导入的 JSON 数据为 `[ {"category" : 1, "author" : 2}, {"category" : 3, "author" : 4} ]`，如果指定该参数取值为 `true`，则 StarRocks 会把 `{"category" : 1, "author" : 2}` 和 `{"category" : 3, "author" : 4}` 解析成两行数据，并导入到目标 StarRocks 表中对应的数据行。 |
+| json_root         | 否           | 用于指定待导入 JSON 数据的根元素。仅在使用匹配模式导入 JSON 数据时需要指定该参数。参数取值为合法的 JsonPath 字符串。默认值为空，表示会导入整个 JSON 数据文件的数据。具体请参见本文提供的示例“[导入数据并指定 JSON 根节点](#指定-json-根节点使用匹配模式导入数据)”。 |
+| ignore_json_size | 否   | 用于指定是否检查 HTTP 请求中 JSON Body 的大小。<br />**说明**<br />HTTP 请求中 JSON Body 的大小默认不能超过 100 MB。如果 JSON Body 的大小超过 100 MB，会提示 "The size of this batch exceed the max size [104857600] of json type data data [8617627793]. Set ignore_json_size to skip check, although it may lead huge memory consuming." 错误。为避免该报错，可以在 HTTP 请求头中添加 `"ignore_json_size:true"` 设置，忽略对 JSON Body 大小的检查。 |
+| compression, Content-Encoding | 否 | 指定在 STREAM LOAD 数据传输过程中使用哪种压缩算法，支持 GZIP、BZIP2、LZ4_FRAME、ZSTD 算法。示例：`curl --location-trusted -u root:  -v 'http://127.0.0.1:18030/api/db0/tbl_simple/_stream_load' \-X PUT  -H "expect:100-continue" \-H 'format: json' -H 'compression: lz4_frame'   -T ./b.json.lz4`。 |
+
+另外，导入 JSON 格式的数据时，需要注意单个 JSON 对象的大小不能超过 4 GB。如果 JSON 文件中单个 JSON 对象的大小超过 4 GB，会提示 "This parser can't support a document that big." 错误。
+
+### opt_properties
+
+用于指定一些导入相关的可选参数。指定的参数设置作用于整个导入作业。语法如下：
+
+```Bash
+-H "label: <label_name>"
+-H "where: <condition1>[, <condition2>, ...]"
+-H "max_filter_ratio: <num>"
+-H "timeout: <num>"
+-H "strict_mode: true | false"
+-H "timezone: <string>"
+-H "load_mem_limit: <num>"
+-H "partial_update: true | false"
+-H "partial_update_mode: row | column"
+-H "merge_condition: <column_name>"
+```
+
+参数说明如下表所述。
+
+| **参数名称**     | **是否必选** | **参数说明**                                                 |
+| ---------------- | ------------ | ------------------------------------------------------------ |
+| label            | 否           | 用于指定导入作业的标签。如果您不指定标签，StarRocks 会自动为导入作业生成一个标签。相同标签的数据无法多次成功导入，这样可以避免一份数据重复导入。有关标签的命名规范，请参见[系统限制](../../System_limit.md)。StarRocks 默认保留最近 3 天内成功的导入作业的标签。您可以通过 [FE 配置参数](../../../administration/management/FE_configuration.md#导入导出) `label_keep_max_second` 设置默认保留时长。 |
+| where            | 否           | 用于指定过滤条件。如果指定该参数，StarRocks 会按照指定的过滤条件对转换后的数据进行过滤。只有符合 WHERE 子句中指定的过滤条件的数据才会导入。 |
+| max_filter_ratio | 否           | 用于指定导入作业的最大容错率，即导入作业能够容忍的因数据质量不合格而过滤掉的数据行所占的最大比例。取值范围：`0`~`1`。默认值：`0` 。<br />建议您保留默认值 `0`。这样的话，当导入的数据行中有错误时，导入作业会失败，从而保证数据的正确性。<br />如果希望忽略错误的数据行，可以设置该参数的取值大于 `0`。这样的话，即使导入的数据行中有错误，导入作业也能成功。<br />**说明**<br />这里因数据质量不合格而过滤掉的数据行，不包括通过 WHERE 子句过滤掉的数据行。 |
+| log_rejected_record_num | 否           | 指定最多允许记录多少条因数据质量不合格而过滤掉的数据行数。该参数自 3.1 版本起支持。取值范围：`0`、`-1`、大于 0 的正整数。默认值：`0`。<ul><li>取值为 `0` 表示不记录过滤掉的数据行。</li><li>取值为 `-1` 表示记录所有过滤掉的数据行。</li><li>取值为大于 0 的正整数（比如 `n`）表示每个 BE（或 CN）节点上最多可以记录 `n` 条过滤掉的数据行。</li></ul> |
+| timeout          | 否           | 用于导入作业的超时时间。取值范围：1 ~ 259200。单位：秒。默认值：`600`。<br />**说明**<br />除了 `timeout` 参数可以控制该导入作业的超时时间外，您还可以通过 [FE 配置参数](../../../administration/management/FE_configuration.md#导入导出) `stream_load_default_timeout_second` 来统一控制 Stream Load 导入作业的超时时间。如果指定了`timeout` 参数，则该导入作业的超时时间以 `timeout` 参数为准；如果没有指定 `timeout` 参数，则该导入作业的超时时间以`stream_load_default_timeout_second` 为准。 |
+| strict_mode      | 否           | 用于指定是否开严格模式。取值范围：`true` 和 `false`。默认值：`false`。`true` 表示开启，`false` 表示关闭。<br />关于该模式的介绍，参见 [严格模式](../../../loading/load_concept/strict_mode.md)。|
+| timezone         | 否           | 用于指定导入作业所使用的时区。默认为东八区 (Asia/Shanghai)。<br />该参数的取值会影响所有导入涉及的、跟时区设置有关的函数所返回的结果。受时区影响的函数有 strftime、alignment_timestamp 和 from_unixtime 等，具体请参见[设置时区](../../../administration/management/timezone.md)。导入参数 `timezone` 设置的时区对应“[设置时区](../../../administration/management/timezone.md)”中所述的会话级时区。 |
+| load_mem_limit   | 否           | 导入作业的内存限制，最大不超过 BE（或 CN）的内存限制。单位：字节。默认内存限制为 2 GB。 |
+| partial_update | 否 |是否使用部分列更新。取值包括 `TRUE` 和 `FALSE`。默认值：`FALSE`。|
+| partial_update_mode | 否 | 指定部分更新的模式，取值包括 `row` 和 `column`。<ul><li>`row`（默认值），指定使用行模式执行部分更新，比较适用于较多列且小批量的实时更新场景。</li><li>`column`，指定使用列模式执行部分更新，比较适用于少数列并且大量行的批处理更新场景。在该场景，开启列模式，更新速度更快。例如，在一个包含 100 列的表中，每次更新 10 列（占比 10%）并更新所有行，则开启列模式，更新性能将提高 10 倍。</li></ul>|
+| merge_condition  | 否           | 用于指定作为更新生效条件的列名。这样只有当导入的数据中该列的值大于等于当前值的时候，更新才会生效。StarRocks v2.5 起支持条件更新。参见[通过导入实现数据变更](../../../loading/Load_to_Primary_Key_tables.md)。 <br/>**说明**<br/>指定的列必须为非主键列，且仅主键表支持条件更新。  |
+
+## 列映射
+
+### 导入 CSV 数据时配置列映射关系
+
+如果源数据文件中的列与目标表中的列按顺序一一对应，您不需要指定列映射和转换关系。
+
+如果源数据文件中的列与目标表中的列不能按顺序一一对应，包括数量或顺序不一致，则必须通过 `COLUMNS` 参数来指定列映射和转换关系。一般包括如下两种场景：
+
+- **列数量一致、但是顺序不一致，并且数据不需要通过函数计算、可以直接落入目标表中对应的列。** 这种场景下，您需要在 `COLUMNS` 参数中按照源数据文件中的列顺序、使用目标表中对应的列名来配置列映射和转换关系。
+
+  例如，目标表中有三列，按顺序依次为 `col1`、`col2` 和 `col3`；源数据文件中也有三列，按顺序依次对应目标表中的 `col3`、`col2` 和 `col1`。这种情况下，需要指定 `COLUMNS(col3, col2, col1)`。
+
+- **列数量、顺序都不一致，并且某些列的数据需要通过函数计算以后才能落入目标表中对应的列。** 这种场景下，您不仅需要在 `COLUMNS` 参数中按照源数据文件中的列顺序、使用目标表中对应的列名来配置列映射关系，还需要指定参与数据计算的函数。以下为两个示例：
+
+  - 目标表中有三列，按顺序依次为 `col1`、`col2` 和 `col3` ；源数据文件中有四列，前三列按顺序依次对应目标表中的 `col1`、`col2` 和 `col3`，第四列在目标表中无对应的列。这种情况下，需要指定 `COLUMNS(col1, col2, col3, temp)`，其中，最后一列可随意指定一个名称（如 `temp`）用于占位即可。
+  - 目标表中有三列，按顺序依次为 `year`、`month` 和 `day`。源数据文件中只有一个包含时间数据的列，格式为 `yyyy-mm-dd hh:mm:ss`。这种情况下，可以指定 `COLUMNS (col, year = year(col), month=month(col), day=day(col))`。其中，`col` 是源数据文件中所包含的列的临时命名，`year = year(col)`、`month=month(col)` 和 `day=day(col)` 用于指定从 `col` 列提取对应的数据并落入目标表中对应的列，如 `year = year(col)` 表示通过 `year` 函数提取源数据文件中 `col` 列的 `yyyy` 部分的数据并落入目标表中的 `year` 列。
+
+有关操作示例，参见[设置列映射关系](#设置列映射关系)。
+
+### 导入 JSON 数据时配置列映射关系
+
+如果 JSON 文件中的 Key 名与目标表中的列名一致，您可以使用简单模式来导入数据。简单模式下，不需要设置 `jsonpaths` 参数，这种模式要求 JSON 数据是大括号 {} 表示的对象类型，例如 `{"category": 1, "author": 2, "price": "3"}` 中，`category`、`author`、`price` 是 Key 的名称，按名称直接对应目标 表中的 `category`、`author`、`price` 三列。
+
+如果 JSON 文件中的 Key 名与目标表中的列名不一致，则需要使用匹配模式来导入数据。匹配模式下，需要通过 `jsonpaths` 和 `COLUMNS` 两个参数来指定 JSON 文件中的 Key 和目标表中的列之间的映射和转换关系：
+
+- `jsonpaths` 参数中按照 JSON 文件中 Key 的顺序一一指定待导入的 Key。
+- `COLUMNS` 参数中指定 JSON 文件中的 Key 与目标表中的列之间的映射关系和数据转换关系。
+  - `COLUMNS` 参数中指定的列名与 `jsonpaths` 参数中指定的 Key 按顺序保持一一对应。
+  - `COLUMNS` 参数中指定的列名与目标表中的列按名称保持一一对应。
+
+有关使用匹配模式导入 JSON 数据的示例，参见[使用匹配模式导入数据](#使用匹配模式导入数据)。
+
+## 返回值
+
+导入结束后，会以 JSON 格式返回导入作业的结果信息，如下所示：
+
+```JSON
+{
+    "TxnId": 1003,
+    "Label": "label123",
+    "Status": "Success",
+    "Message": "OK",
+    "NumberTotalRows": 1000000,
+    "NumberLoadedRows": 999999,
+    "NumberFilteredRows": 1,
+    "NumberUnselectedRows": 0,
+    "LoadBytes": 40888898,
+    "LoadTimeMs": 2144,
+    "BeginTxnTimeMs": 0,
+    "StreamLoadPlanTimeMs": 1,
+    "ReadDataTimeMs": 0,
+    "WriteDataTimeMs": 11,
+    "CommitAndPublishTimeMs": 16,
+}
+```
+
+返回结果中的参数说明如下表所述。
+
+| **参数名称**           | **说明**                                                     |
+| ---------------------- | ------------------------------------------------------------ |
+| TxnId                  | 导入作业的事务 ID。                                          |
+| Label                  | 导入作业的标签。                                             |
+| Status                 | 此次导入的数据的最终状态。<ul><li>`Success`：表示数据导入成功，数据已经可见。</li><li>`Publish Timeout`：表示导入作业已经成功提交，但是由于某种原因数据并不能立即可见。可以视作已经成功、不必重试导入。</li><li>`Label Already Exists`：表示该标签已经被其他导入作业占用。数据可能导入成功，也可能是正在导入。</li><li>`Fail`：表示数据导入失败。您可以指定标签重试该导入作业。</li></ul> |
+| Message                | 导入作业的状态详情。如果导入作业失败，这里会返回具体的失败原因。 |
+| NumberTotalRows        | 读取到的总行数。                                             |
+| NumberLoadedRows       | 成功导入的总行数。只有当返回结果中的 `Status` 为 `Success` 时有效。 |
+| NumberFilteredRows     | 导入过程中因数据质量不合格而过滤掉的行数。                   |
+| NumberUnselectedRows   | 导入过程中根据 WHERE 子句指定的条件而过滤掉的行数。          |
+| LoadBytes              | 此次导入的数据量大小。单位：字节 (Bytes)。                   |
+| LoadTimeMs             | 此次导入所用的时间。单位：毫秒 (ms)。                        |
+| BeginTxnTimeMs         | 导入作业开启事务的时长。                                     |
+| StreamLoadPlanTimeMs   | 导入作业生成执行计划的时长。                                 |
+| ReadDataTimeMs         | 导入作业读取数据的时长。                                     |
+| WriteDataTimeMs        | 导入作业写入数据的时长。                                     |
+| CommitAndPublishTimeMs | 导入作业提交和数据发布的耗时。                               |
+
+如果导入作业失败，还会返回 `ErrorURL`，如下所示：
+
+```JSON
+{
+    "ErrorURL": "http://172.26.195.68:8045/api/_load_error_log?file=error_log_3a4eb8421f0878a6_9a54df29fd9206be"
+}
+```
+
+通过 `ErrorURL` 可以查看导入过程中因数据质量不合格而过滤掉的错误数据行的具体信息。您可以在提交导入作业时，通过可选参数 `log_rejected_record_num` 来指定最多可以记录多少条错误数据行的信息。
+
+您可以通过  `curl "url"` 命令直接查看错误数据行的信息。也可以通过 `wget "url"` 命令导出错误数据行的信息，如下所示：
+
+```Bash
+wget http://172.26.195.68:8045/api/_load_error_log?file=error_log_3a4eb8421f0878a6_9a54df29fd9206be
+```
+
+导出的错误数据行信息会保存到一个名为 `_load_error_log?file=error_log_3a4eb8421f0878a6_9a54df29fd9206be` 的本地文件中。您可以通过 `cat _load_error_log?file=error_log_3a4eb8421f0878a6_9a54df29fd9206be` 命令查看该文件的内容。
+
+您可以根据错误信息调整导入作业，然后重新提交导入作业。
+
+## 示例
+
+### 导入 CSV 格式的数据
+
+本小节以 CSV 格式的数据为例，重点阐述在创建导入作业的时候，如何运用各种参数配置来满足不同业务场景下的各种导入要求。
+
+#### **设置超时时间**
+
+StarRocks 数据库 `test_db` 里的表 `table1` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example1.csv` 也包含三列，按顺序一一对应 `table1` 中的三列 `col1`、`col2`、`col3`。
+
+如果要把 `example1.csv` 中所有的数据都导入到 `table1` 中，并且要求超时时间最大不超过 100 秒，可以执行如下命令：
+
+```Bash
+curl --location-trusted -u <username>:<password> -H "label:label1" \
+    -H "Expect:100-continue" \
+    -H "timeout:100" \
+    -H "max_filter_ratio:0.2" \
+    -T example1.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table1/_stream_load
+```
+
+#### **设置最大容错率**
+
+StarRocks 数据库 `test_db` 里的表 `table2` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example2.csv` 也包含三列，按顺序一一对应 `table2` 中的三列 `col1`、`col2`、`col3`。
+
+如果要把 `example2.csv` 中所有的数据都导入到 `table2` 中，并且要求容错率最大不超过 `0.2`，可以执行如下命令：
+
+```Bash
+curl --location-trusted -u <username>:<password> -H "label:label2" \
+    -H "Expect:100-continue" \
+    -H "max_filter_ratio:0.2" \
+    -T example2.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table2/_stream_load
+```
+
+#### **设置列映射关系**
+
+StarRocks 数据库 `test_db` 里的表 `table3` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example3.csv` 也包含三列，按顺序依次对应 `table3` 中 `col2`、`col1`、`col3`。
+
+如果要把 `example3.csv` 中所有的数据都导入到 `table3` 中，可以执行如下命令：
+
+```Bash
+curl --location-trusted -u <username>:<password>  -H "label:label3" \
+    -H "Expect:100-continue" \
+    -H "columns: col2, col1, col3" \
+    -T example3.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table3/_stream_load
+```
+
+> **说明**
+>
+> 上述示例中，因为 `example3.csv` 和 `table3` 所包含的列不能按顺序依次对应，因此需要通过 `columns` 参数来设置 `example3.csv` 和 `table3` 之间的列映射关系。
+
+#### **设置筛选条件**
+
+StarRocks 数据库 `test_db` 里的表 `table4` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example4.csv` 也包含三列，按顺序一一对应 `table4` 中的三列 `col1`、`col2`、`col3`。
+
+如果只想把 `example4.csv` 中第一列的值等于 `20180601` 的数据行导入到 `table4` 中，可以执行如下命令：
+
+```Bash
+curl --location-trusted -u <username>:<password> -H "label:label4" \
+    -H "Expect:100-continue" \
+    -H "columns: col1, col2，col3]"\
+    -H "where: col1 = 20180601" \
+    -T example4.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table4/_stream_load
+```
+
+> **说明**
+>
+> 上述示例中，虽然 `example4.csv` 和 `table4` 所包含的列数目相同、并且按顺序一一对应，但是因为需要通过 WHERE 子句指定基于列的过滤条件，因此需要通过 `columns` 参数对 `example4.csv` 中的列进行临时命名。
+
+#### **设置目标分区**
+
+StarRocks 数据库 `test_db` 里的表 `table5` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example5.csv` 也包含三列，按顺序一一对应 `table5` 中的三列 `col1`、`col2`、`col3`。
+
+如果要把 `example5.csv` 中所有的数据都导入到 `table5` 所在的分区 `p1` 和 `p2`，可以执行如下命令：
+
+```Bash
+curl --location-trusted -u <username>:<password>  -H "label:label5" \
+    -H "Expect:100-continue" \
+    -H "partitions: p1, p2" \
+    -T example5.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table5/_stream_load
+```
+
+#### **设置严格模式和时区**
+
+StarRocks 数据库 `test_db` 里的表 `table6` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example6.csv` 也包含三列，按顺序一一对应 `table6` 中的三列 `col1`、`col2`、`col3`。
+
+如果要把 `example6.csv` 中所有的数据导入到 `table6` 中，并且要求进严格模式的过滤、使用时区 `Africa/Abidjan`，可以执行如下命令：
+
+```Bash
+curl --location-trusted -u <username>:<password> \
+    -H "Expect:100-continue" \
+    -H "strict_mode: true" \
+    -H "timezone: Africa/Abidjan" \
+    -T example6.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table6/_stream_load
+```
+
+#### **导入数据到含有 HLL 类型列的表**
+
+StarRocks 数据库 `test_db` 里的表 `table7` 包含两个 HLL 类型的列，按顺序依次为 `col1`、`col2`。
+
+数据文件 `example7.csv` 也包含两列，第一列对应 `table7` 中  HLL 类型的列`col1`，可以通过函数转换成 HLL 类型的数据并落入 `col1` 列；第二列跟 `table7` 中任何一列都不对应。
+
+如果要把 `example7.csv` 中对应的数据导入到 `table7` 中，可以执行如下命令：
+
+```Bash
+curl --location-trusted -u <username>:<password> \
+    -H "Expect:100-continue" \
+    -H "columns: temp1, temp2, col1=hll_hash(temp1), col2=hll_empty()" \
+    -T example7.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table7/_stream_load
+```
+
+> **说明**
+>
+> 上述示例中，通过 `columns` 参数，把 `example7.csv` 中的两列临时命名为 `temp1`、`temp2`，然后使用函数指定数据转换规则，包括：
+>
+> - 使用 `hll_hash` 函数把 `example7.csv` 中的 `temp1` 列转换成 HLL 类型的数据并映射到 `table7`中的 `col1` 列。
+>
+> - 使用 `hll_empty` 函数给导入的数据行在 `table7` 中的第二列补充默认值。
+
+有关 `hll_hash` 函数和 `hll_empty` 函数的用法，请参见 [hll_hash](../../sql-functions/scalar-functions/hll_hash.md) 和 [hll_empty](../../sql-functions/scalar-functions/hll_empty.md)。
+
+#### **导入数据到含有 BITMAP 类型列的表**
+
+StarRocks 数据库 `test_db` 里的表 `table8` 包含两个 BITMAP 类型的列，按顺序依次为 `col1`、`col2`。
+
+数据文件 `example8.csv` 也包含两列，第一列对应 `table8` 中 BITMAP 类型的列 `col1`，可以通过函数转换成 BITMAP 类型的数据并落入 `col1` 列；第二列跟 `table8` 中任何一列都不对应。
+
+如果要把 `example8.csv` 中对应的数据导入到 `table8` 中，可以执行如下命令：
+
+```Bash
+curl --location-trusted -u <username>:<password> \
+    -H "Expect:100-continue" \
+    -H "columns: temp1, temp2, col1=to_bitmap(temp1), col2=bitmap_empty()" \
+    -T example8.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/table8/_stream_load
+```
+
+> **说明**
+>
+> 上述示例中，通过 `columns` 参数，把 `example8.csv` 中的两列临时命名为 `temp1`、`temp2`，然后使用函数指定数据转换规则，包括：
+>
+> - 使用 `to_bitmap` 函数把 `example8.csv` 中的 `temp1` 列转换成 BITMAP 类型的数据并落入 `table8` 中的 `col1` 列。
+>
+> - 使用 `bitmap_empty` 函数给导入的数据行在 `table8` 中的第二列补充默认值。
+
+有关 `to_bitmap` 函数和 `bitmap_empty` 函数的用法，请参见 [to_bitmap](../../sql-functions/bitmap-functions/to_bitmap.md) 和 [bitmap_empty](../../sql-functions/bitmap-functions/bitmap_empty.md)。
+
+#### 设置 `skip_header`、`trim_space`、`enclose` 和 `escape`
+
+StarRocks 数据库 `test_db` 里的表 `table9` 包含三列，按顺序依次为 `col1`、`col2`、`col3`。
+
+数据文件 `example9.csv` 也包含三列，按顺序依次对应 `table9` 中 `col2`、`col1`、`col3`。
+
+如果要把 `example9.csv` 中所有的数据都导入到 `table9` 中，并且希望跳过 `example9.csv` 中最开头的五行数据、去除列分隔符前后的空格、 指定 `enclose` 字符为斜杠 (`\`)、并且指定 `escape` 字符为斜杠 (`\`)，可以执行如下语句：
+
+```Bash
+curl --location-trusted -u <username>:<password> -H "label:3875" \
+    -H "Expect:100-continue" \
+    -H "trim_space: true" -H "skip_header: 5" \
+    -H "column_separator:," -H "enclose:\"" -H "escape:\\" \
+    -H "columns: col2, col1, col3" \
+    -T example9.csv -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/tbl9/_stream_load
+```
+
+### **导入 JSON 格式的数据**
+
+本小节主要描述导入 JSON 格式的数据时，需要关注的一些参数配置。
+
+StarRocks 数据库 `test_db` 里的表 `tbl1` 拥有如下表结构：
+
+```SQL
+`category` varchar(512) NULL COMMENT "",
+`author` varchar(512) NULL COMMENT "",
+`title` varchar(512) NULL COMMENT "",
+`price` double NULL COMMENT ""
+```
+
+#### **使用简单模式导入数据**
+
+假设数据文件 `example1.json` 包含如下数据：
+
+```JSON
+{"category":"C++","author":"avc","title":"C++ primer","price":895}
+```
+
+您可以通过如下命令将 `example1.json` 中的数据导入到 `tbl1` 中：
+
+```Bash
+curl --location-trusted -u <username>:<password> -H "label:label6" \
+    -H "Expect:100-continue" \
+    -H "format: json" \
+    -T example1.json -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/tbl1/_stream_load
+```
+
+> **说明**
+>
+> 如上述示例所示，在没有指定 `columns` 和 `jsonpaths` 参数的情况下，则会按照 StarRocks 表中的列名称去对应 JSON 数据文件中的字段。
+
+为了提升吞吐量，Stream Load 支持一次性导入多条数据。比如，可以一次性导入 JSON 数据文件中如下多条数据：
+
+```JSON
+[
+    {"category":"C++","author":"avc","title":"C++ primer","price":89.5},
+    {"category":"Java","author":"avc","title":"Effective Java","price":95},
+    {"category":"Linux","author":"avc","title":"Linux kernel","price":195}
+]
+```
+
+#### **使用匹配模式导入数据**
+
+StarRocks 按照如下顺序对数据进行匹配和处理：
+
+1. （可选）根据 `strip_outer_array` 参数裁剪最外层的数组结构。
+
+    > **说明**
+    >
+    > 仅在 JSON 数据的最外层是一个通过中括号 `[]` 表示的数组结构时涉及，需要设置 `strip_outer_array` 为 `true`。
+
+2. （可选）根据 `json_root` 参数匹配 JSON 数据的根节点。
+
+    > **说明**
+    >
+    > 仅在 JSON 数据存在根节点时涉及，需要通过 `json_root` 参数来指定根节点。
+
+3. 根据 `jsonpaths` 参数提取待导入的 JSON 数据。
+
+##### **不指定 JSON 根节点、使用匹配模式导入数据**
+
+假设数据文件 `example2.json` 包含如下数据：
+
+```JSON
+[
+    {"category":"xuxb111","author":"1avc","title":"SayingsoftheCentury","price":895},
+    {"category":"xuxb222","author":"2avc","title":"SayingsoftheCentury","price":895},
+    {"category":"xuxb333","author":"3avc","title":"SayingsoftheCentury","price":895}
+]
+```
+
+您可以通过指定 `jsonpaths` 参数进行精准导入，例如只导入 `category`、`author`、`price` 三个字段的数据：
+
+```Bash
+curl --location-trusted -u <username>:<password> -H "label:label7" \
+    -H "Expect:100-continue" \
+    -H "format: json" \
+    -H "strip_outer_array: true" \
+    -H "jsonpaths: [\"$.category\",\"$.price\",\"$.author\"]" \
+    -H "columns: category, price, author" \
+    -T example2.json -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/tbl1/_stream_load
+```
+
+> **说明**
+>
+> 上述示例中，JSON 数据的最外层是一个通过中括号 [] 表示的数组结构，并且数组结构中的每个 JSON 对象都表示一条数据记录。因此，需要设置 `strip_outer_array` 为 `true`来裁剪最外层的数组结构。导入过程中，未指定的字段 `title` 会被忽略掉。
+
+##### **指定 JSON 根节点、使用匹配模式导入数据**
+
+假设数据文件 `example3.json` 包含如下数据：
+
+```JSON
+{
+    "id": 10001,
+    "RECORDS":[
+        {"category":"11","title":"SayingsoftheCentury","price":895,"timestamp":1589191587},
+        {"category":"22","author":"2avc","price":895,"timestamp":1589191487},
+        {"category":"33","author":"3avc","title":"SayingsoftheCentury","timestamp":1589191387}
+    ],
+    "comments": ["3 records", "there will be 3 rows"]
+}
+```
+
+您可以通过指定 `jsonpaths` 进行精准导入，例如只导入 `category`、`author`、`price` 三个字段的数据：
+
+```Bash
+curl --location-trusted -u <username>:<password> \
+    -H "Expect:100-continue" \
+    -H "format: json" \
+    -H "json_root: $.RECORDS" \
+    -H "strip_outer_array: true" \
+    -H "jsonpaths: [\"$.category\",\"$.price\",\"$.author\"]" \
+    -H "columns: category, price, author" -H "label:label8" \
+    -T example3.json -XPUT \
+    http://<fe_host>:<fe_http_port>/api/test_db/tbl1/_stream_load
+```
+
+> **说明**
+>
+> 上述示例中，JSON 数据的最外层是一个通过中括号 [] 表示的数组结构，并且数组结构中的每个 JSON 对象都表示一条数据记录。因此，需要设置 `strip_outer_array` 为 `true`来裁剪最外层的数组结构。导入过程中，未指定的字段 `title` 和 `timestamp` 会被忽略掉。另外，示例中还通过 `json_root` 参数指定了需要真正导入的数据为 `RECORDS` 字段对应的值，即一个 JSON 数组。
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/_category_.yml b/docs/zh/sql-reference/sql-statements/loading_unloading/_category_.yml
new file mode 100644
index 00000000000000..f76ab54cfef397
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/_category_.yml
@@ -0,0 +1,6 @@
+position: 40 # float position is supported
+label: '导入导出'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/ALTER_PIPE.md b/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/ALTER_PIPE.md
new file mode 100644
index 00000000000000..04b56c4a7b483e
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/ALTER_PIPE.md
@@ -0,0 +1,55 @@
+---
+keywords: ['xiugai'] 
+displayed_sidebar: docs
+---
+
+# ALTER PIPE
+
+## 功能
+
+修改 Pipe 的执行参数。该命令自 3.2 版本起支持。
+
+## 语法
+
+```SQL
+ALTER PIPE [db_name.]<pipe_name> 
+SET
+(
+    "<key>" = <value>[, "<key>" = "<value>" ...]
+) 
+```
+
+## 参数说明
+
+### db_name
+
+Pipe 所属的数据库的名称。
+
+### pipe_name
+
+Pipe 的名称。
+
+### **PROPERTIES**
+
+要修改的执行参数设置。格式：`"key" = "value"`。有关支持的执行参数，参见 [CREATE PIPE](CREATE_PIPE.md)。
+
+## 示例
+
+修改数据库 `mydatabase` 下名为 `user_behavior_replica` 的 Pipe 的 `AUTO_INGEST` 属性为 `FALSE`：
+
+```SQL
+USE mydatabase;
+ALTER PIPE user_behavior_replica
+SET
+(
+    "AUTO_INGEST" = "FALSE"
+);
+```
+
+## 相关文档
+
+- [CREATE PIPE](CREATE_PIPE.md)
+- [DROP PIPE](DROP_PIPE.md)
+- [SHOW PIPES](SHOW_PIPES.md)
+- [SUSPEND or RESUME PIPE](SUSPEND_or_RESUME_PIPE.md)
+- [RETRY FILE](RETRY_FILE.md)
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md b/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md
new file mode 100644
index 00000000000000..31dd22c5fd1b8b
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/CREATE_PIPE.md
@@ -0,0 +1,86 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE PIPE
+
+## 功能
+
+创建一个 Pipe，用于定义一个实现数据导入的 INSERT INTO SELECT FROM FILES 语句。该命令自 3.2 版本起支持。
+
+## 语法
+
+```SQL
+CREATE [OR REPLACE] PIPE [db_name.]<pipe_name> 
+[PROPERTIES ("<key>" = "<value>"[, "<key> = <value>" ...])]
+AS <INSERT_SQL>
+```
+
+StarRocks 自 3.2.3 版本起支持 CREATE [OR REPLACE] PIPE。使用 CREATE [OR REPLACE] PIPE 时，如果指定的 `pipe_name` 与当前数据库里的某个已有的 Pipe 名称相同，则新建的 Pipe 会取代已有的 Pipe。
+
+## 参数说明
+
+### db_name
+
+Pipe 所属的数据库的名称。
+
+### pipe_name
+
+Pipe 的名称。该名称在 Pipe 所在的数据库内必须唯一。命名要求参见[系统限制](../../../System_limit.md)。
+
+> **NOTICE**
+>
+> 每个 Pipe 从属于一个数据库。删除 Pipe 所在的数据库后，该 Pipe 也会随之删除，并且该 Pipe 不会随数据库的恢复而恢复。
+
+### INSERT_SQL
+
+INSERT INTO SELECT FROM FILES 语句，用于从指定的源数据文件导入数据到目标表。
+
+有关如何使用表函数 FILES()，参见 [FILES](../../../sql-functions/table-functions/files.md)。
+
+### PROPERTIES
+
+用于控制 Pipe 执行的一些参数。格式：`"key" = "value"`。
+
+| 参数          | 默认值        | 参数描述                                                     |
+| :------------ | :------------ | :----------------------------------------------------------- |
+| AUTO_INGEST   | `TRUE`        | 是否启用自动增量导入。取值范围：`TRUE` 和 `FALSE`。`TRUE` 表示开启自动增量导入。`FALSE` 表示只导入作业启动时指定的数据文件内容，后续新增或修改的文件内容不导入。对于批量导入来说，可以将其设置为 `FALSE`。 |
+| POLL_INTERVAL | `300` (second) | 自动增量导入的轮询间隔。                                     |
+| BATCH_SIZE    | `1 GB`       | 导入批次大小。如果参数取值中不指定单位，则使用默认单位 Byte。 |
+| BATCH_FILES   | `256`         | 导入批次文件数量。                                           |
+
+## 示例
+
+在当前数据库下，创建一个名为 `user_behavior_replica` 的 Pipe，用于把 `s3://starrocks-examples/user_behavior_ten_million_rows.parquet` 中的数据导入到表 `user_behavior_replica` 中：
+
+```SQL
+CREATE PIPE user_behavior_replica
+PROPERTIES
+(
+    "AUTO_INGEST" = "TRUE"
+)
+AS
+INSERT INTO user_behavior_replica
+SELECT * FROM FILES
+(
+    "path" = "s3://starrocks-examples/user_behavior_ten_million_rows.parquet",
+    "format" = "parquet",
+    "aws.s3.region" = "us-east-1",
+    "aws.s3.access_key" = "AAAAAAAAAAAAAAAAAAAA",
+    "aws.s3.secret_key" = "BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB"
+); 
+```
+
+> **说明**
+>
+> 把上面命令示例中的 `AAA` 和 `BBB` 替换成真实有效的 Access Key 和 Secret Key 作为访问凭证。由于这里使用的数据对象对所有合法的 AWS 用户开放，因此您填入任何真实有效的 Access Key 和 Secret Key 都可以。
+
+该示例以基于 IAM User 的认证鉴权方式为例，并假设 Parquet 源文件与 StarRocks 目标表的结构相同。有关认证方式和语句详情，参见[配置 AWS 认证信息](../../../../integrations/authenticate_to_aws_resources.md) [FILES](../../../sql-functions/table-functions/files.md)。
+
+## 相关文档
+
+- [ALTER PIPE](ALTER_PIPE.md)
+- [DROP PIPE](DROP_PIPE.md)
+- [SHOW PIPES](SHOW_PIPES.md)
+- [SUSPEND or RESUME PIPE](SUSPEND_or_RESUME_PIPE.md)
+- [RETRY FILE](RETRY_FILE.md)
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/DROP_PIPE.md b/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/DROP_PIPE.md
new file mode 100644
index 00000000000000..0df3633c4051b3
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/DROP_PIPE.md
@@ -0,0 +1,42 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP PIPE
+
+## 功能
+
+删除 Pipe，并删除相关的作业和元数据。该操作不会删除已经导入的数据。该命令自 3.2 版本起支持。
+
+## 语法
+
+```SQL
+DROP PIPE [IF EXISTS] [db_name.]<pipe_name>
+```
+
+## 参数说明
+
+### db_name
+
+Pipe 所属的数据库的名称。
+
+### pipe_name
+
+Pipe 的名称。
+
+## 示例
+
+删除数据库 `mydatabase` 下名为 `user_behavior_replica` 的 Pipe：
+
+```SQL
+USE mydatabase;
+DROP PIPE user_behavior_replica;
+```
+
+## 相关文档
+
+- [CREATE PIPE](CREATE_PIPE.md)
+- [ALTER PIPE](ALTER_PIPE.md)
+- [SHOW PIPES](SHOW_PIPES.md)
+- [SUSPEND or RESUME PIPE](SUSPEND_or_RESUME_PIPE.md)
+- [RETRY FILE](RETRY_FILE.md)
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/RETRY_FILE.md b/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/RETRY_FILE.md
new file mode 100644
index 00000000000000..253ef1e2711bc0
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/RETRY_FILE.md
@@ -0,0 +1,43 @@
+# RETRY FILE
+
+## 功能
+
+重新尝试导入指定 Pipe 中所有数据文件或某个数据文件。该命令自 3.2 版本起支持。
+
+## 语法
+
+```SQL
+ALTER PIPE [ IF EXISTS ] <pipe_name> { RETRY ALL | RETRY FILE '<file_name>' }
+```
+
+## 参数说明
+
+### pipe_name
+
+Pipe 的名称。
+
+### file_name
+
+要重试的数据文件的存储路径。注意这里需要指定完整的路径。如果指定的文件不属于当前指定的 Pipe，则返回报错。
+
+## 示例
+
+重试导入名为 `user_behavior_replica` 的 Pipe 中所有数据文件：
+
+```SQL
+ALTER PIPE [ IF EXISTS ] user_behavior_replica RETRY ALL;
+```
+
+重试导入名为 `user_behavior_replica` 的 Pipe 中的数据文件 `s3://starrocks-examples/user_behavior_ten_million_rows.parquet`：
+
+```SQL
+ALTER PIPE [ IF EXISTS ] user_behavior_replica RETRY FILE 's3://starrocks-examples/user_behavior_ten_million_rows.parquet';
+```
+
+## 相关文档
+
+- [CREATE PIPE](CREATE_PIPE.md)
+- [ALTER PIPE](ALTER_PIPE.md)
+- [DROP PIPE](DROP_PIPE.md)
+- [SHOW PIPES](SHOW_PIPES.md)
+- [SUSPEND or RESUME PIPE](SUSPEND_or_RESUME_PIPE.md)
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md b/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md
new file mode 100644
index 00000000000000..4dfa8e5ad094a0
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/SHOW_PIPES.md
@@ -0,0 +1,82 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW PIPES
+
+## 功能
+
+查看当前数据库或指定数据库下 Pipe。该命令自 3.2 版本起支持。
+
+## 语法
+
+```SQL
+SHOW PIPES [FROM <db_name>]
+[
+   WHERE [ NAME { = "<pipe_name>" | LIKE "pipe_matcher" } ]
+         [ [AND] STATE = { "SUSPENDED" | "RUNNING" | "ERROR" } ]
+]
+[ ORDER BY <field_name> [ ASC | DESC ] ]
+[ LIMIT { [offset, ] limit | limit OFFSET offset } ]
+```
+
+## 参数说明
+
+### FROM `<db_name>`
+
+指定待查询数据库的名称。如果不指定数据库，则默认查询当前数据库下的 Pipe。
+
+### WHERE
+
+指定查询条件。
+
+### ORDER BY `<field_name>`
+
+指定结果记录的排序字段。
+
+### LIMIT
+
+指定系统返回的最大结果记录数。
+
+## 返回结果
+
+返回结果包括如下字段：
+
+| **字段**      | **说明**                                                     |
+| ------------- | ------------------------------------------------------------ |
+| DATABASE_NAME | Pipe 所属数据库的名称。                                      |
+| ID            | Pipe 的唯一 ID。                                             |
+| NAME          | Pipe 的名称。                                                |
+| TABLE_NAME    | StarRocks 目标表的名称。                                     |
+| STATE         | Pipe 的状态，包括 `RUNNING`、`FINISHED`、`SUSPENDED`、`ERROR`。 |
+| LOAD_STATUS   | Pipe 下待导入数据文件的整体状态，包括如下字段：<ul><li>`loadedFiles`：已导入的数据文件总个数。</li><li>`loadedBytes`：已导入的数据总量，单位为字节。</li><li>`LastLoadedTime`：最近一次执行导入的时间。格式：`yyyy-MM-dd HH:mm:ss`。例如，`2023-07-24 14:58:58`。</li></ul> |
+| LAST_ERROR    | Pipe 执行过程中最近一次错误的详细信息。默认值为 `NULL`。     |
+| CREATED_TIME  | Pipe 的创建时间。格式：`yyyy-MM-dd HH:mm:ss`。例如：`2023-07-24 14:58:58`。 |
+
+## 示例
+
+### 查询所有 Pipe
+
+进入数据库 `mydatabase`，然后查看该数据库下所有 Pipe：
+
+```SQL
+USE mydatabase;
+SHOW PIPES \G
+```
+
+### 查询指定 Pipe
+
+进入数据库 `mydatabase`，然后查看该数据库下名为 `user_behavior_replica` 的 Pipe：
+
+```SQL
+USE mydatabase;
+SHOW PIPES WHERE NAME = 'user_behavior_replica' \G
+```
+
+## 相关文档
+
+- [CREATE PIPE](CREATE_PIPE.md)
+- [ALTER PIPE](ALTER_PIPE.md)
+- [DROP PIPE](DROP_PIPE.md)
+- [SUSPEND or RESUME PIPE](SUSPEND_or_RESUME_PIPE.md)
+- [RETRY FILE](RETRY_FILE.md)
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/SUSPEND_or_RESUME_PIPE.md b/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/SUSPEND_or_RESUME_PIPE.md
new file mode 100644
index 00000000000000..dea553a870aad4
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/pipe/SUSPEND_or_RESUME_PIPE.md
@@ -0,0 +1,58 @@
+---
+displayed_sidebar: docs
+---
+
+# SUSPEND or RESUME PIPE
+
+## 功能
+
+暂停或重新启动 Pipe：
+
+- 当导入作业正在进行时（即，处于 `RUNNING` 状态），暂停 (`SUSPEND`) Pipe 会中断正在执行的作业。
+- 当出现导入错误时，重新启动 (`RESUME`) Pipe 会继续执行出错的作业。
+
+该命令自 3.2 版本起支持。
+
+## 语法
+
+```SQL
+ALTER PIPE [ IF EXISTS ] <pipe_name> { SUSPEND | RESUME [ IF SUSPENDED ] }
+```
+
+## 参数说明
+
+### pipe_name
+
+Pipe 的名称。
+
+## 示例
+
+### 暂停 Pipe
+
+暂停数据库 `mydatabase` 下名为 `user_behavior_replica` 的 Pipe（Pipe 当前处于 `RUNNING` 状态）：
+
+```SQL
+USE mydatabase;
+ALTER PIPE user_behavior_replica SUSPEND;
+```
+
+通过 [SHOW PIPES](SHOW_PIPES.md) 查看该 Pipe，可以看到 Pipe 的状态变为 `SUSPEND`。
+
+### 重新启动 Pipe
+
+重新启动数据库 `mydatabase` 下名为 `user_behavior_replica` 的 Pipe：
+
+```SQL
+USE mydatabase;
+ALTER PIPE user_behavior_replica RESUME;
+```
+
+通过 [SHOW PIPES](SHOW_PIPES.md) 查看该 Pipe，可以看到 Pipe 的状态变为 `RUNNING`。
+
+## 相关文档
+
+- [CREATE PIPE](CREATE_PIPE.md)
+- [ALTER PIPE](ALTER_PIPE.md)
+- [DROP PIPE](DROP_PIPE.md)
+- [SHOW PIPES](SHOW_PIPES.md)
+- [RETRY FILE](RETRY_FILE.md)
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md b/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md
new file mode 100644
index 00000000000000..2e5b9809f309ca
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/ALTER_ROUTINE_LOAD.md
@@ -0,0 +1,131 @@
+---
+keywords: ['xiugai'] 
+displayed_sidebar: docs
+---
+
+# ALTER ROUTINE LOAD
+
+import RoutineLoadPrivNote from '../../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
+
+## 功能
+
+该语法用于修改 Routine Load 导入作业。注意，只能修改处于 `PAUSED` 状态的作业。您可以通过 [PAUSE ROUTINE LOAD](PAUSE_ROUTINE_LOAD.md) 暂停 Routine Load 导入作业。
+
+修改成功后，您可以：
+
+- 通过 [SHOW ROUTINE LOAD](SHOW_ROUTINE_LOAD.md) 检查修改后的作业详情。
+- 通过 [RESUME ROUTINE LOAD](RESUME_ROUTINE_LOAD.md) 重启该导入作业。
+
+<RoutineLoadPrivNote />
+
+## **语法**
+
+```SQL
+ALTER ROUTINE LOAD FOR [db_name.]<job_name>
+[load_properties]
+[job_properties]
+FROM data_source
+[data_source_properties]
+```
+
+## 参数说明
+
+- **`[<db_name>.]<job_name>`**
+
+    指定要修改的作业名称。
+
+- **`load_properties`**
+
+    待导入的源数据信息。语法如下：
+
+    ```SQL
+    [COLUMNS TERMINATED BY '<column_separator>'],
+    [ROWS TERMINATED BY '<row_separator>'],
+    [COLUMNS ([<column_name> [, ...] ] [, column_assignment [, ...] ] )],
+    [WHERE <expr>],
+    [PARTITION ([ <partition_name> [, ...] ])]
+    [TEMPORARY PARTITION (<temporary_partition1_name>[,<temporary_partition2_name>,...])]
+    ```
+
+    详细的参数介绍，请参见 [CREATE ROUTINE LOAD](CREATE_ROUTINE_LOAD.md#load_properties)。
+
+- **`job_properties`**
+
+  导入作业的属性。语法如下：
+
+  ```SQL
+  PROPERTIES ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
+  ```
+
+  目前仅支持修改如下属性：
+
+  - `desired_concurrent_number`
+
+  - `max_error_number`
+
+  - `max_batch_interval`
+
+  - `max_batch_rows`
+
+  - `max_batch_size`
+
+  - `jsonpaths`
+
+  - `json_root`
+
+  - `strip_outer_array`
+
+  - `strict_mode`
+
+  - `timezone`
+
+  详细的属性介绍，请参见 [CREATE ROUTINE LOAD](CREATE_ROUTINE_LOAD.md#job_properties)。
+
+- **`data_source`** 和 **`data_source_properties`**
+
+  - **`data_source`**
+
+    必填，指定数据源，目前仅支持取值为 `KAFKA`。
+
+  - **`data_source_properties`**
+
+    数据源的相关属性。目前支持修改：
+
+    - `kafka_partitions` 和 `kafka_offsets`：需要注意的是，仅支持修改当前已经消费的 Kafka partition 的 offset，不支持新增 Kafka partition。
+    - `property.*`： 自定义的数据源 Kafka 相关参数，例如 `property.kafka_default_offsets`。
+
+## 示例
+
+1. 将导入作业的属性 `desired_concurrent_number` 调大至 `5`，以提高导入任务的并行度。任务的并行度的详细说明，参见[如何提高导入性能](../../../../faq/loading/Routine_load_faq.md#1-如何提高导入性能)。
+
+    ```SQL
+    ALTER ROUTINE LOAD FOR example_tbl_ordertest
+    PROPERTIES
+    (
+        "desired_concurrent_number" = "5"
+    );
+    ```
+
+2. 同时修改导入作业的属性和数据源信息。
+
+    ```SQL
+    ALTER ROUTINE LOAD FOR example_tbl_ordertest
+    PROPERTIES
+    (
+        "desired_concurrent_number" = "5"
+    )
+    FROM KAFKA
+    (
+        "kafka_partitions" = "0, 1, 2",
+        "kafka_offsets" = "100, 200, 100",
+        "property.group.id" = "new_group"
+    );
+    ```
+
+3. 同时修改过滤条件和导入的目标 StarRocks 分区。
+
+    ```SQL
+    ALTER ROUTINE LOAD FOR example_tbl_ordertest
+    WHERE pay_dt < 2023-06-31
+    PARTITION (p202306);
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md b/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md
new file mode 100644
index 00000000000000..c8150cee0ae822
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md
@@ -0,0 +1,963 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE ROUTINE LOAD
+
+## 功能
+
+Routine Load 支持持续消费 Apache Kafka® 的消息并导入至 StarRocks 中。Routine Load 支持 Kafka 中消息的格式为 CSV、JSON、Avro (自 v3.0.1)，并且访问 Kafka 时，支持多种安全协议，包括 `plaintext`、`ssl`、`sasl_plaintext` 和 `sasl_ssl`。
+
+本文介绍 CREATE ROUTINE LOAD 的语法、参数说明和示例。
+
+> **说明**
+>
+> - Routine Load 的应用场景、基本原理和基本操作，请参见 [使用 Routine Load 导入数据](../../../../loading/RoutineLoad.md)。
+> - Routine Load 操作需要目标表的 INSERT 权限。如果您的用户账号没有 INSERT 权限，请参考 [GRANT](../../account-management/GRANT.md) 给用户赋权。
+
+## 语法
+
+```SQL
+CREATE ROUTINE LOAD <database_name>.<job_name> ON <table_name>
+[load_properties]
+[job_properties]
+FROM data_source
+[data_source_properties]
+```
+
+## 参数说明
+
+### `database_name`、`job_name`、`table_name`
+
+`database_name`
+
+选填，目标数据库的名称。
+
+`job_name`
+
+必填，导入作业的名称。一张表可能有多个导入作业，建议您利用具有辨识度的信息（例如 Kafka Topic 名称、创建导入作业的大致时间等）来设置具有意义的导入作业名称，用于区分多个导入作业。同一数据库内，导入作业的名称必须唯一。
+
+`table_name`
+
+必填，目标表的名称。
+
+### `load_properties`
+
+选填。源数据的属性。语法：
+
+```SQL
+[COLUMNS TERMINATED BY '<column_separator>'],
+[ROWS TERMINATED BY '<row_separator>'],
+[COLUMNS (<column1_name>[,<column2_name>,<column_assignment>,... ])],
+[WHERE <expr>],
+[PARTITION (<partition1_name>[,<partition2_name>,...])]
+[TEMPORARY PARTITION (<temporary_partition1_name>[,<temporary_partition2_name>,...])]
+```
+
+如果导入 CSV 格式的数据，则可以指定列分隔符，默认为`\t`，即 Tab。例如可以输入 `COLUMNS TERMINATED BY ","`。指定列分隔符为逗号(,)。
+
+> **说明**
+>
+> - 必须确保这里指定的列分隔符与源数据中的列分隔符一致。
+> - StarRocks 支持设置长度最大不超过 50 个字节的 UTF-8 编码字符串作为列分隔符，包括常见的逗号 (,)、Tab 和 Pipe (|)。
+> - 空值 (null) 用 `\N` 表示。比如，源数据一共有三列，其中某行数据的第一列、第三列数据分别为 `a` 和 `b`，第二列没有数据，则第二列需要用 `\N` 来表示空值，写作 `a,\N,b`，而不是 `a,,b`。`a,,b` 表示第二列是一个空字符串。
+
+`ROWS TERMINATED BY`
+
+用于指定源数据中的行分隔符。如果不指定该参数，则默认为 `\n`。
+
+`COLUMNS`
+
+源数据和目标表之间的列映射和转换关系。详细说明，请参见[列映射和转换关系](#列映射和转换关系)。
+
+- `column_name`：映射列，源数据中这类列的值可以直接落入目标表的列中，不需要进行计算。
+- `column_assignment`：衍生列，格式为 `column_name = expr`，源数据中这类列的值需要基于表达式 `expr` 进行计算后，才能落入目标表的列中。 建议将衍生列排在映射列之后，因为 StarRocks 先解析映射列，再解析衍生列。
+
+> **说明**
+>
+> 以下情况不需要设置 `COLUMNS` 参数：
+>
+> - 待导入 CSV 数据中的列与目标表中列的数量和顺序一致。
+> - 待导入 JSON 数据中的 Key 名与目标表中的列名一致。
+
+`WHERE`
+
+设置过滤条件，只有满足过滤条件的数据才会导入到 StarRocks 中。例如只希望导入 `col1` 大于 `100` 并且 `col2` 等于 `1000` 的数据行，则可以输入 `WHERE col1 > 100 and col2 = 1000`。
+
+> **说明**
+>
+> 过滤条件中指定的列可以是源数据中本来就存在的列，也可以是基于源数据的列生成的衍生列。
+
+`PARTITION`
+
+将数据导入至目标表的指定分区中。如果不指定分区，则会将数据自动导入至其对应的分区中。 示例：
+
+```SQL
+PARTITION(p1, p2, p3)
+```
+
+### `job_properties`
+
+必填。导入作业的属性。语法：
+
+```SQL
+PROPERTIES ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
+```
+
+参数说明如下：
+
+| **参数**                  | **是否必选** | **说明**                                                     |
+| ------------------------- | ------------ | ------------------------------------------------------------ |
+| desired_concurrent_number | 否           | 单个 Routine Load 导入作业的**期望**任务并发度，表示期望一个导入作业最多被分成多少个任务并行执行。默认值为 `3`。 但是**实际**任务并行度由如下多个参数组成的公式决定，并且实际任务并行度的上限为 BE 节点的数量或者消费分区的数量。`min(alive_be_number, partition_number, desired_concurrent_number, max_routine_load_task_concurrent_num)`。<ul> <li>`alive_be_number`：存活的 BE 节点数量。</li><li>`partition_number`：消费分区数量。</li><li>`desired_concurrent_number`：单个Routine Load 导入作业的期望任务并发度。默认值为 `3`。</li><li>`max_routine_load_task_concurrent_num`：Routine Load 导入作业的默认最大任务并行度，默认值为 `5`。该参数为 [FE 动态参数](../../../../administration/management/FE_configuration.md)。</li></ul> |
+| max_batch_interval        | 否           | 任务的调度间隔，即任务多久执行一次。单位：秒。取值范围：`5`～`60`。默认值：`10`。建议取值为导入间隔 10s 以上，否则会因为导入频率过高可能会报错版本数过多。 |
+| max_batch_rows            | 否           | 该参数只用于定义错误检测窗口范围，错误检测窗口范围为单个 Routine Load 导入任务所消费的 `10 * max-batch-rows` 行数据，默认为 `10 * 200000 = 2000000`。导入任务时会检测窗口中数据是否存在错误。错误数据是指 StarRocks 无法解析的数据，比如非法的 JSON。 |
+| max_error_number          | 否           | 错误检测窗口范围内允许的数据行数的上限。当错误数据行数超过该值时，导入作业会暂停，此时您需要执行 [SHOW ROUTINE LOAD](SHOW_ROUTINE_LOAD.md)，根据 `ErrorLogUrls`，检查 Kafka 中的消息并且更正错误。默认为 `0`，表示不允许有错误行。<br />**注意**<br /><ul><li>在错误数据行过多致导入任务暂停之前的最后一批任务将**成功**。也就是说，合格的数据将被导入，不合格的数据将被过滤。如果不想过滤过多的不合格数据行，可设置参数 `max_filter_ratio`。</li><li>错误行不包括通过 WHERE 子句过滤掉的数据。</li><li>该参数与下个参数 `max_filter_ratio` 都用于控制错误行数阈值。如果没有设置 `max_filter_ratio` 时，则本参数生效，如果设置了 `max_filter_ratio`，则错误行数只要达到本参数或 `max_filter_ratio` 参数其中任何一个阈值，则导入作业暂停。</li></ul> |
+| max_filter_ratio         | 否           |  用于指定导入作业的最大容错率，即导入作业能够容忍的因数据质量不合格而过滤掉的数据行所占的最大比例。取值范围：`0`~`1`。默认值：`1`（表示实际不会生效）。<br />建议您将该值设置为 `0`。这样的话，当导入的数据行中有错误时，导入作业会暂停，从而保证数据的正确性。<br />如果希望忽略错误的数据行，可以设置该参数的取值大于 `0`。这样的话，即使导入的数据行中有错误，导入作业也能成功。<br />**注意**<br /><ul><li>当错误数据行大于 `max_filter_ratio` 时，最后一批任务将**失败**。这与 `max_error_number` 的效果有些**不同**。</li><li>这里因数据质量不合格而过滤掉的数据行，不包括通过 WHERE 子句过滤掉的数据行。</li><li>该参数与上个参数 `max_error_number` 都用于控制错误行数阈值。当该参数保持默认值 `1` 时，`max_error_number` 生效，如果设置了本参数，则错误行数只要达到本参数或 `max_error_number` 参数其中任何一个阈值，则导入作业暂停。</li></ul> |
+| strict_mode               | 否           | 是否开启严格模式。取值范围：`TRUE` 或者 `FALSE`。默认值：`FALSE`。开启后，如果源数据某列的值为 `NULL`，但是目标表中该列不允许为 `NULL`，则该行数据会被过滤掉。<br />关于该模式的介绍，参见[严格模式](../../../../loading/load_concept/strict_mode.md)。|
+| log_rejected_record_num | 否 | 指定最多允许记录多少条因数据质量不合格而过滤掉的数据行数。该参数自 3.1 版本起支持。取值范围：`0`、`-1`、大于 0 的正整数。默认值：`0`。<ul><li>取值为 `0` 表示不记录过滤掉的数据行。</li><li>取值为 `-1` 表示记录所有过滤掉的数据行。</li><li>取值为大于 0 的正整数（比如 `n`）表示每个 BE 节点上最多可以记录 `n` 条过滤掉的数据行。</li></ul> |
+| timezone                  | 否           | 该参数的取值会影响所有导入涉及的、跟时区设置有关的函数所返回的结果。受时区影响的函数有 strftime、alignment_timestamp 和 from_unixtime 等，具体请参见[设置时区](../../../../administration/management/timezone.md)。导入参数 `timezone` 设置的时区对应[设置时区](../../../../administration/management/timezone.md)中所述的会话级时区。 |
+| partial_update | 否 |是否使用部分列更新。取值包括 `TRUE` 和 `FALSE`。默认值：`FALSE`。|
+| merge_condition           | 否           | 用于指定作为更新生效条件的列名。这样只有当导入的数据中该列的值大于等于当前值的时候，更新才会生效。参见[通过导入实现数据变更](../../../../loading/Load_to_Primary_Key_tables.md)。指定的列必须为非主键列，且仅主键表支持条件更新。 |
+| format                    | 否           | 源数据的格式，取值范围：`CSV`、`JSON` 或者 `Avro`（自 v3.0.1）。默认值：`CSV`。|
+| trim_space                | 否           | 用于指定是否去除 CSV 文件中列分隔符前后的空格。取值类型：BOOLEAN。默认值：`false`。<br />有些数据库在导出数据为 CSV 文件时，会在列分隔符的前后添加一些空格。根据位置的不同，这些空格可以称为“前导空格”或者“尾随空格”。通过设置该参数，可以使 StarRocks 在导入数据时删除这些不必要的空格。<br />需要注意的是，StarRocks 不会去除被 `enclose` 指定字符括起来的字段内的空格（包括字段的前导空格和尾随空格）。例如，列分隔符是竖线 (<code class="language-text">&#124;</code>)，`enclose` 指定的字符是双引号 (`"`)：<code class="language-text">&#124; "Love StarRocks" &#124;</code>。如果设置 trim_space 为 true，则 StarRocks 处理后的结果数据为 <code class="language-text">&#124;"Love StarRocks"&#124;</code>。|
+| enclose                   | 否           | 根据 [RFC4180](https://www.rfc-editor.org/rfc/rfc4180)，用于指定把 CSV 文件中的字段括起来的字符。取值类型：单字节字符。默认值：`NONE`。最常用 `enclose` 字符为单引号 (`'`) 或双引号 (`"`)。<br />被 `enclose` 指定字符括起来的字段内的所有特殊字符（包括行分隔符、列分隔符等）均看做是普通符号。比 RFC4180 标准更进一步的是，StarRocks 提供的 `enclose` 属性支持设置任意单个字节的字符。<br />如果一个字段内包含了 `enclose` 指定字符，则可以使用同样的字符对 `enclose` 指定字符进行转义。例如，在设置了`enclose` 为双引号 (`"`) 时，字段值 `a "quoted" c` 在 CSV 文件中应该写作 `"a ""quoted"" c"`。 |
+| escape                    | 否           | 指定用于转义的字符。用来转义各种特殊字符，比如行分隔符、列分隔符、转义符、`enclose` 指定字符等，使 StarRocks 把这些特殊字符当做普通字符而解析成字段值的一部分。取值类型：单字节字符。默认值：`NONE`。最常用的 `escape` 字符为斜杠 (`\`)，在 SQL 语句中应该写作双斜杠 (`\\`)。<br />`escape` 指定字符同时作用于 `enclose` 指定字符的内部和外部。<br />以下为两个示例：<br /><ul><li>当设置 `enclose` 为双引号 (`"`) 、`escape` 为斜杠 (`\`) 时，StarRocks 会把 `"say \"Hello world\""` 解析成一个字段值 `say "Hello world"`。</li><li>假设列分隔符为逗号 (`,`) ，当设置 `escape` 为斜杠 (`\`) ，StarRocks 会把 `a, b\, c` 解析成 `a` 和 `b, c` 两个字段值。</li></ul> |
+| strip_outer_array         | 否           | 是否裁剪 JSON 数据最外层的数组结构。取值范围：`TRUE` 或者 `FALSE`。默认值：`FALSE`。真实业务场景中，待导入的 JSON 数据可能在最外层有一对表示数组结构的中括号 `[]`。这种情况下，一般建议您指定该参数取值为 `true`，这样 StarRocks 会剪裁掉外层的中括号 `[]`，并把中括号 `[]` 里的每个内层数组都作为一行单独的数据导入。如果您指定该参数取值为 `false`，则 StarRocks 会把整个 JSON 数据解析成一个数组，并作为一行数据导入。例如，待导入的 JSON 数据为 `[ {"category" : 1, "author" : 2}, {"category" : 3, "author" : 4} ]`，如果指定该参数取值为 `true`，则 StarRocks 会把 `{"category" : 1, "author" : 2}` 和 `{"category" : 3, "author" : 4}` 解析成两行数据，并导入到目标表中对应的数据行。 |
+| jsonpaths                 | 否           | 用于指定待导入的字段的名称。仅在使用匹配模式导入 JSON 数据时需要指定该参数。参数取值为 JSON 格式。参见[目标表存在衍生列，其列值通过表达式计算生成](#目标表存在衍生列其列值通过表达式计算生成)。|
+| json_root                 | 否           | 如果不需要导入整个 JSON 数据，则指定实际待导入 JSON 数据的根节点。参数取值为合法的 JsonPath。默认值为空，表示会导入整个 JSON 数据。具体请参见本文提供的示例[指定实际待导入 JSON 数据的根节点](#指定实际待导入-json-数据的根节点)。 |
+| task_consume_second                 | 否           |单个 Routine Load 导入作业中每个 Routine Load 导入任务消费数据的最大时长，单位为秒。相较于[FE 动态参数](../../../../administration/management/FE_configuration.md) `routine_load_task_consume_second`（作用于集群内部所有 Routine Load 导入作业），该参数仅针对单个 Routine Load 导入作业，更加灵活。该参数自 v3.1.0 起新增。 <ul><li>当未配置 `task_consume_second` 和 `task_timeout_second` 时，StarRocks 则使用 FE 动态参数 `routine_load_task_consume_second` 和`routine_load_task_timeout_second` 来控制导入行为。</li><li>当只配置 `task_consume_second` 时，默认 `task_timeout_second` = `task_consume_second` * 4。</li><li>当只配置 `task_timeout_second` 时，默认 `task_consume_second` = `task_timeout_second` /4。</li></ul>|
+| task_timeout_second                 | 否           | Routine Load 导入作业中每个 Routine Load 导入任务超时时间，单位为秒。相较于[FE 动态参数](../../../../administration/management/FE_configuration.md) `routine_load_task_timeout_second`（作用于集群内部所有 Routine Load 导入作业），该参数仅针对单个 Routine Load 导入作业，更加灵活。该参数自 v3.1.0 起新增。<ul><li>当未配置 `task_consume_second` 和 `task_timeout_second` 时，StarRocks 则使用 FE 动态参数 `routine_load_task_consume_second` 和 `routine_load_task_timeout_second` 来控制导入行为。</li><li>当只配置 `task_timeout_second` 时，默认 `task_consume_second` = `task_timeout_second` /4。</li><li>当只配置 `task_consume_second` 时，默认 `task_timeout_second` = `task_consume_second` * 4。</li></ul>|
+
+### `data_source`、`data_source_properties`
+
+数据源和数据源属性。语法:
+
+```Bash
+FROM <data_source>
+ ("<key1>" = "<value1>"[, "<key2>" = "<value2>" ...])
+```
+
+`data_source`
+
+必填。指定数据源，目前仅支持取值为 `KAFKA`。
+
+`data_source_properties`
+
+必填。数据源属性，参数以及说明如下：
+
+| **参数**          | **说明**                                                     |
+| ----------------- | ------------------------------------------------------------ |
+| kafka_broker_list | Kafka 的 Broker 连接信息。格式为 `<kafka_broker_ip>:<kafka port>`，多个 Broker 之间以英文逗号 (,) 分隔。 Kafka Broker 默认端口号为 `9092`。示例：`"kafka_broker_list" = "xxx.xx.xxx.xx:9092,xxx.xx.xxx.xx:9092"` |
+| kafka_topic       | Kafka Topic 名称。一个导入作业仅支持消费一个 Topic 的消息。  |
+| kafka_partitions  | 待消费的分区。示例：`"kafka_partitions" = "0, 1, 2, 3"`。如果不配置该参数，则默认消费所有分区。 |
+| kafka_offsets     | 待消费分区的起始消费位点，必须一一对应 `kafka_partitions` 中指定的每个分区。如果不配置该参数，则默认为从分区的末尾开始消费。支持取值为<ul><li> 具体消费位点：从分区中该消费位点的数据开始消费。</li><li>`OFFSET_BEGINNING`：从分区中有数据的位置开始消费。</li><li>`OFFSET_END`：从分区的末尾开始消费。</li></ul>多个起始消费位点之间用英文逗号（, ）分隔。<br />示例： `"kafka_offsets" = "1000, OFFSET_BEGINNING, OFFSET_END, 2000"`。|
+| property.kafka_default_offsets | 所有待消费分区的默认起始消费位点。支持的取值与 `kafka_offsets` 一致。 |
+| confluent.schema.registry.url| 注册该 Avro schema 的 Schema Registry 的 URL，StarRocks 会从该 URL 获取 Avro schema。格式为 `confluent.schema.registry.url = http[s]://[<schema-registry-api-key>:<schema-registry-api-secret>@]<hostname or ip address>[:<port>]`。|
+
+**更多数据源相关参数**
+
+支持设置更多数据源 Kafka 相关参数，功能等同于 Kafka 命令行 `--property`， 支持参数，请参见 [librdkafka 配置项文档](https://github.com/edenhill/librdkafka/blob/master/CONFIGURATION.md)中适用于客户端的配置项。
+
+> **说明**
+>
+> 当参数的取值是文件时，则值前加上关键词 `FILE:`。关于如何创建文件，请参见 [CREATE FILE](../../cluster-management/file/CREATE_FILE.md) 命令文档。
+
+**指定所有待消费分区的默认起始消费位点。**
+
+```Plaintext
+"property.kafka_default_offsets" = "OFFSET_BEGINNING"
+```
+
+`property.kafka_default_offsets` 的取值为具体的消费位点，或者：
+
+- `OFFSET_BEGINNING`：从分区中有数据的位置开始消费。
+- `OFFSET_END`：从分区的末尾开始消费。
+
+**指定导入任务消费 Kafka 时所基于 Consumer Group 的 `group.id`**
+
+```Plaintext
+"property.group.id" = "group_id_0"
+```
+
+如果没有指定 `group.id`，StarRocks 会根据 Routine Load 的导入作业名称生成一个随机值，具体格式为`{job_name}_{random uuid}`，如 `simple_job_0a64fe25-3983-44b2-a4d8-f52d3af4c3e8`。
+
+**指定 BE 访问 Kafka 时的安全协议并配置相关参数**
+
+支持安全协议为 `plaintext`（默认）、`ssl`、`sasl_plaintext` 和 `sasl_ssl`，并且需要根据安全协议配置相关参数。
+
+当安全协议为 `sasl_plaintext` 或 `sasl_ssl` 时，支持如下 SASL 认证机制：
+
+- PLAIN
+- SCRAM-SHA-256 和 SCRAM-SHA-512
+- OAUTHBEARER
+- GSSAPI (Kerberos)
+
+示例：
+
+- 访问 Kafka 时，使用安全协议 SSL
+
+    ```sql
+    "property.security.protocol" = "ssl", -- 指定安全协议为 SSL
+    "property.ssl.ca.location" = "FILE:ca-cert", -- CA 证书的位置
+    --如果 Kafka server 端开启了 client 认证，则还需设置如下三个参数：
+    "property.ssl.certificate.location" = "FILE:client.pem", -- Client 的 public key 的位置
+    "property.ssl.key.location" = "FILE:client.key", -- Client 的 private key 的位置
+    "property.ssl.key.password" = "abcdefg" -- Client 的 private key 的密码
+    ```
+
+- 访问 Kafka 时，使用 SASL_PLAINTEXT 安全协议和 SASL/PLAIN 认证机制
+
+    ```sql
+    "property.security.protocol" = "SASL_PLAINTEXT", -- 指定安全协议为 SASL_PLAINTEXT
+    "property.sasl.mechanism" = "PLAIN", -- 指定 SASL 认证机制为 PLAIN
+    "property.sasl.username" = "admin", -- SASL 的用户名
+    "property.sasl.password" = "admin" -- SASL 的密码
+    ```
+
+- 访问 Kafka 时，使用 SASL_PLAINTEXT 安全协议和 SASL/GSSAPI (Kerberos) 认证机制
+
+  ```sql
+  "property.security.protocol" = "SASL_PLAINTEXT", -- 指定安全协议为 SASL_PLAINTEXT
+  "property.sasl.mechanism" = "GSSAPI", -- 指定 SASL 认证机制为 GSSAPI, 默认是 GSSAPI
+  "property.sasl.kerberos.service.name" = "kafka", -- 指定 broker service name，默认是 Kafka
+  "property.sasl.kerberos.keytab" = "/home/starrocks/starrocks.keytab", -- 指定 client keytab 的位置
+  "property.sasl.kerberos.principal" = "starrocks@YOUR.COM" -- 指定 kerberos principal
+  ```
+
+  :::note
+
+  - 自 StarRocks 3.1.4 版本起，支持 SASL/GSSAPI (Kerberos) 认证。
+  - 需要在 BE 机器上安装 SASL 相关模块。
+
+    ```bash
+    # Debian/Ubuntu:
+    sudo apt-get install libsasl2-modules-gssapi-mit libsasl2-dev
+    # CentOS/Redhat:
+    sudo yum install cyrus-sasl-gssapi cyrus-sasl-devel
+    ```
+
+  :::
+
+### FE 和 BE 配置项
+
+Routine Load 相关配置项，请参见[配置参数](../../../../administration/management/FE_configuration.md)。
+
+## 列映射和转换关系
+
+### 导入 CSV 数据
+
+**如果 CSV 格式的数据中的列与目标表中的列的数量或顺序不一致**，则需要通过 `COLUMNS` 参数来指定源数据和目标表之间的列映射和转换关系。一般包括如下两种场景：
+
+- **源数据中的列与目标表中的列数量一致，但是顺序不一致**。并且数据不需要通过函数计算、可以直接落入目标表中对应的列。
+  您需要在 `COLUMNS` 参数中按照源数据中的列顺序、使用目标表中对应的列名来配置列映射和转换关系。
+
+  例如，目标表中有三列，按顺序依次为 `col1`、`col2` 和 `col3`；源数据中也有三列，按顺序依次对应目标表中的 `col3`、`col2` 和 `col1`。这种情况下，需要指定 `COLUMNS(col3, col2, col1)`。
+- **源数据中的列与目标表中的列数量不一致，甚至某些列的数据需要通过转换（函数计算以后）才能落入目标表中对应的列。**
+  您不仅需要在 `COLUMNS` 参数中按照源数据中的列顺序、使用目标表中对应的列名来配置列映射关系，还需要指定参与数据计算的函数。以下为两个示例：
+
+  - **源数据比目标表多列**。
+    比如目标表中有三列，按顺序依次为 `col1`、`col2` 和 `col3` ；源数据中有四列，前三列按顺序依次对应目标表中的 `col1`、`col2` 和 `col3`，第四列在目标表中无对应的列。这种情况下，需要指定 `COLUMNS(col1, col2, col3, temp)`，其中，最后一列可随意指定一个名称（如 `temp`）用于占位即可。
+  - **目标表存在基于源数据的列进行计算后生成的衍生列**。
+    例如源数据中只有一个包含时间数据的列，格式为 `yyyy-mm-dd hh:mm:ss`。目标表中有三列，按顺序依次为 `year`、`month` 和 `day`，均是基于源数据中包含时间数据的列进行计算后生成的衍生列。这种情况下，可以指定 `COLUMNS(col, year = year(col), month=month(col), day=day(col)`。其中，`col` 是源数据中所包含的列的临时命名，`year = year(col)`、`month=month(col)` 和 `day=day(col)` 用于指定从源数据中的 `col` 列提取对应的数据并落入目标表中对应的衍生列，如 `year = year(col)` 表示通过 `year` 函数提取源数据中 `col` 列的 `yyyy` 部分的数据并落入目标表中的 `year` 列。
+
+  有关操作示例，请参见[设置列的映射和转换关系](#设置列的映射和转换关系)。
+
+### 导入 JSON 或 Avro 数据
+
+> **说明**
+>
+> 自 3.0.1 版本开始，StarRocks 支持使用 Routine Load 导入 Avro 数据。导入 JSON 或者 Avro 数据时，列映射和转换关系的配置方式相同。因此本小节以导入 Avro 数据为例进行说明。
+
+**如果 JSON 格式的数据中的 Key 名与目标表中的列名不一致**，则需要使用匹配模式导入 JSON 数据，即通过 `jsonpaths` 和 `COLUMNS` 两个参数来指定源数据和目标表之间的列映射和转换关系：
+
+- `jsonpaths` 参数指定待导入 JSON 数据的 Key，并进行排序（就像新生成了 CSV 数据）。
+- `COLUMNS`参数指定待导入 JSON 数据的 Key 与目标表的列的映射关系和数据转换关系。
+  - 与 `jsonpaths`中指定的 Key 按顺序保持一一对应。
+  - 与目标表中的列按名称保持一一对应。
+
+详细示例，请参见[目标表存在衍生列，其列值通过表达式计算生成](#目标表存在衍生列其列值通过表达式计算生成)。
+
+> **说明**
+>
+> 如果待导入 JSON 数据中 Key 名（Key的顺序和数量不需要对应）都能对应目标表中列名，则可以使用简单模式导入 JSON 数据，无需配置 `jsonpaths` 和 `COLUMNS`。
+
+## 示例
+
+### 导入 CSV 数据
+
+本小节以 CSV 格式的数据为例，重点阐述在创建导入作业的时候，如何运用各种参数配置来满足不同业务场景下的各种导入要求。
+
+**数据集**
+
+假设 Kafka 集群的 Topic `ordertest1` 存在如下 CSV 格式的数据，其中 CSV 数据中列的含义依次是订单编号、支付日期、顾客姓名、国籍、性别、支付金额。
+
+```Plaintext
+2020050802,2020-05-08,Johann Georg Faust,Deutschland,male,895
+2020050802,2020-05-08,Julien Sorel,France,male,893
+2020050803,2020-05-08,Dorian Grey,UK,male,1262
+2020050901,2020-05-09,Anna Karenina,Russia,female,175
+2020051001,2020-05-10,Tess Durbeyfield,US,female,986
+2020051101,2020-05-11,Edogawa Conan,japan,male,8924
+```
+
+**目标数据库和表**
+
+根据 CSV 数据中需要导入的列， 在 StarRocks 集群的目标数据库 `example_db` 中创建表 `example_tbl1`，建表语句如下：
+
+```SQL
+CREATE TABLE example_db.example_tbl1 ( 
+    `order_id` bigint NOT NULL COMMENT "订单编号",
+    `pay_dt` date NOT NULL COMMENT "支付日期", 
+    `customer_name` varchar(26) NULL COMMENT "顾客姓名", 
+    `nationality` varchar(26) NULL COMMENT "国籍", 
+    `gender` varchar(26) NULL COMMENT "性别", 
+    `price` double NULL COMMENT "支付金额") 
+DUPLICATE KEY (order_id,pay_dt) 
+DISTRIBUTED BY HASH(`order_id`);
+```
+
+#### 从 Topic 指定分区和起始位点开始消费
+
+如果需要指定分区，以及各个分区对应的起始位点，则需要配置参数 `kafka_partitions`、`kafka_offsets`。
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest1",
+    "kafka_partitions" ="0,1,2,3", -- 指定分区
+    "kafka_offsets" = "1000, OFFSET_BEGINNING, OFFSET_END, 2000" -- 指定起始位点
+);
+```
+
+#### 调整导入性能
+
+如果需要提高导入性能，避免出现消费积压等情况，则可以通过设置单个 Routine Load 导入作业的期望任务并发度`desired_concurrent_number`，增加实际任务并行度，将一个导入作业拆分成尽可能多的导入任务并行执行。
+
+> 更多提升导入性能的方式，请参见 [Routine Load常见问题](../../../../faq/loading/Routine_load_faq.md)。
+
+请注意，实际任务并行度由如下多个参数组成的公式决定，上限为 BE 节点的数量或者消费分区的数量。
+
+```SQL
+min(alive_be_number, partition_number, desired_concurrent_number, max_routine_load_task_concurrent_num)
+```
+
+因此当消费分区和 BE 节点数量较多，并且大于其余两个参数时，如果您需要增加实际任务并行度，则可以提高`max_routine_load_task_concurrent_num`、 `desired_concurrent_number` 的值。
+
+假设消费分区数量为 `7`，存活 BE 数量为 `5`，`max_routine_load_task_concurrent_num` 为默认值 `5`。此时如果需要增加实际任务并发度至上限，则需要将 `desired_concurrent_number` 设置为 `5`（默认值为 `3`），则计算实际任务并行度 `min(5,7,5,5)` 为 `5`。
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
+PROPERTIES
+(
+"desired_concurrent_number" = "5" -- 设置单个 Routine Load 导入作业的期望任务并发度
+)
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest1"
+);
+```
+
+#### 设置列的映射和转换关系
+
+如果 CSV 格式的数据中的列与目标表中的列的数量或顺序不一致，假设无需导入 CSV 数据的第五列至目标表，则需要通过 `COLUMNS` 参数来指定源数据和目标表之间的列映射和转换关系。
+
+**目标数据库和表**
+
+根据 CSV 数据中需要导入的几列（例如除第五列性别外的其余五列需要导入至 StarRocks）， 在 StarRocks 集群的目标数据库 `example_db` 中创建表 `example_tbl2`。
+
+```SQL
+CREATE TABLE example_db.example_tbl2 ( 
+    `order_id` bigint NOT NULL COMMENT "订单编号",
+    `pay_dt` date NOT NULL COMMENT "支付日期", 
+    `customer_name` varchar(26) NULL COMMENT "顾客姓名", 
+    `nationality` varchar(26) NULL COMMENT "国籍", 
+    `price` double NULL COMMENT "支付金额"
+) 
+DUPLICATE KEY (order_id,pay_dt) 
+DISTRIBUTED BY HASH(`order_id`);
+```
+
+**导入作业**
+
+本示例中，由于无需导入 CSV 数据的第五列至目标表，因此`COLUMNS`中把第五列临时命名为 `temp_gender` 用于占位，其他列都直接映射至表 `example_tbl2` 中。
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl2_ordertest1 ON example_tbl2
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, temp_gender, price)
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest1"
+);
+```
+
+#### 设置过滤条件 筛选待导入的数据
+
+如果仅导入满足条件的数据，则可以在 WHERE 子句中设置过滤条件，例如`price > 100`。
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price),
+WHERE price > 100
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest1"
+);
+```
+
+#### 设置导入任务为严格模式
+
+在`PROPERTIES`中设置`"strict_mode" = "true"`，表示导入作业为严格模式。如果源数据某列的值为 NULL，但是目标表中该列不允许为 NULL，则该行数据会被过滤掉。
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
+PROPERTIES
+(
+"strict_mode" = "true" -- 设置导入作业为严格模式
+)
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest1"
+);
+```
+
+#### 设置导入任务的容错率
+
+如果业务场景对数据质量的有要求，则需要设置参数`max_batch_rows`和`max_error_number`设置错误检测窗口的范围和允许的错误数据行数的上限，当错误数据行数超过该值时，导入作业会暂停。
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
+PROPERTIES
+(
+"max_batch_rows" = "100000", -- 错误检测窗口范围为单个 Routine Load 导入任务所消费的 10 * max-batch-rows 行数。
+"max_error_number" = "100" -- 错误检测窗口范围内允许的错误数据行数的上限
+)
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest1"
+);
+```
+
+#### 指定安全协议为 SSL 并配置相关参数
+
+如果需要指定 BE 访问 Kafka 时使用的安全协议为 SSL，则需要配置 `"property.security.protocol" = "ssl"` 等参数。
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl1_ordertest1 ON example_tbl1
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
+PROPERTIES
+(
+"desired_concurrent_number" = "5"
+)
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest1",
+    "property.security.protocol" = "ssl", -- 使用 SSL 加密
+    "property.ssl.ca.location" = "FILE:ca-cert", -- CA 证书的位置
+    -- 如果 Kafka Server 端开启了 Client 身份认证，则还需设置如下三个参数：
+    "property.ssl.certificate.location" = "FILE:client.pem", -- Client 的 Public Key 的位置
+    "property.ssl.key.location" = "FILE:client.key", -- Client 的 Private Key 的位置
+    "property.ssl.key.password" = "abcdefg" -- Client 的 Private Key 的密码
+);
+```
+
+#### 设置 `trim_space`、`enclose` 和 `escape`
+
+假设 Kafka 集群的 Topic `test_csv` 存在如下 CSV 格式的数据，其中 CSV 数据中列的含义依次是订单编号、支付日期、顾客姓名、国籍、性别、支付金额。
+
+```Plain
+ "2020050802" , "2020-05-08" , "Johann Georg Faust" , "Deutschland" , "male" , "895"
+ "2020050802" , "2020-05-08" , "Julien Sorel" , "France" , "male" , "893"
+ "2020050803" , "2020-05-08" , "Dorian Grey\,Lord Henry" , "UK" , "male" , "1262"
+ "2020050901" , "2020-05-09" , "Anna Karenina" , "Russia" , "female" , "175"
+ "2020051001" , "2020-05-10" , "Tess Durbeyfield" , "US" , "female" , "986"
+ "2020051101" , "2020-05-11" , "Edogawa Conan" , "japan" , "male" , "8924"
+```
+
+如果要把 Topic `test_csv` 中所有的数据都导入到 `example_tbl1` 中，并且希望去除被 `enclose` 指定字符括起来的字段前后的空格、 指定 `enclose` 字符为双引号 (")、并且指定 `escape` 字符为斜杠 (`\`)，可以执行如下语句：
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl1_test_csv ON example_tbl1
+COLUMNS TERMINATED BY ",",
+COLUMNS (order_id, pay_dt, customer_name, nationality, gender, price)
+PROPERTIES
+(
+    "trim_space"="true",
+    "enclose"="\"",
+    "escape"="\\"
+)
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic"="test_csv",
+    "property.kafka_default_offsets"="OFFSET_BEGINNING"
+);
+```
+
+### 导入 JSON 格式数据
+
+#### 目标表的列名与 JSON 数据的 Key 一致
+
+可以使用简单模式导入数据，即创建导入作业时无需使用 `jsonpaths` 和 `COLUMNS` 参数。StarRocks 会按照目标表的列名去对应 JSON 数据的 Key。
+
+**数据集**
+
+假设 Kafka 集群的 Topic `ordertest2` 中存在如下 JSON 数据。
+
+```JSON
+{"commodity_id": "1", "customer_name": "Mark Twain", "country": "US","pay_time": 1589191487,"price": 875}
+{"commodity_id": "2", "customer_name": "Oscar Wilde", "country": "UK","pay_time": 1589191487,"price": 895}
+{"commodity_id": "3", "customer_name": "Antoine de Saint-Exupéry","country": "France","pay_time": 1589191487,"price": 895}
+```
+
+> 注意
+>
+> 这里每行一个 JSON 对象必须在一个 Kafka 消息中，否则会出现“JSON 解析错误”的问题。
+
+**目标数据库和表**
+
+在 StarRocks 集群的目标数据库 `example_db` 中创建表 `example_tbl3` ，并且列名与 JSON 数据中需要导入的 Key 一致。
+
+```SQL
+CREATE TABLE example_db.example_tbl3 ( 
+    `commodity_id` varchar(26) NULL COMMENT "品类ID", 
+    `customer_name` varchar(26) NULL COMMENT "顾客姓名", 
+    `country` varchar(26) NULL COMMENT "顾客国籍", 
+    `pay_time` bigint(20) NULL COMMENT "支付时间", 
+    `price` double SUM NULL COMMENT "支付金额") 
+AGGREGATE KEY(`commodity_id`,`customer_name`,`country`,`pay_time`) 
+DISTRIBUTED BY HASH(`commodity_id`);
+```
+
+**导入作业**
+
+提交导入作业时使用简单模式，即无需使用`jsonpaths` 和 `COLUMNS` 参数，就可以将 Kafka 集群的 Topic `ordertest2` 中的 JSON 数据导入至目标表 `example_tbl3` 中。
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl3_ordertest2 ON example_tbl3
+PROPERTIES
+(
+    "format" = "json"
+ )
+FROM KAFKA
+(
+    "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest2"
+);
+```
+
+> **说明**
+>
+> - 如果 JSON 数据最外层是数组结构，则需要在`PROPERTIES`设置`"strip_outer_array"="true"`，表示裁剪最外层的数组结构。并且需要注意在设置 `jsonpaths` 时，整个 JSON 数据的根节点是裁剪最外层的数组结构后**展平的 JSON 对象**。
+> - 如果不需要导入整个 JSON 数据，则需要使用 `json_root` 指定实际所需导入的 JSON 数据根节点。
+
+#### 目标表存在衍生列，其列值通过表达式计算生成
+
+需要使用匹配模式导入数据，即需要使用 `jsonpaths` 和 `COLUMNS` 参数，`jsonpaths`指定待导入 JSON 数据的 Key，`COLUMNS` 参数指定待导入 JSON 数据的 Key 与目标表的列的映射关系和数据转换关系。
+
+**数据集**
+
+假设 Kafka 集群的 Topic `ordertest2` 中存在如下 JSON 格式的数据。
+
+```JSON
+{"commodity_id": "1", "customer_name": "Mark Twain", "country": "US","pay_time": 1589191487,"price": 875}
+{"commodity_id": "2", "customer_name": "Oscar Wilde", "country": "UK","pay_time": 1589191487,"price": 895}
+{"commodity_id": "3", "customer_name": "Antoine de Saint-Exupéry","country": "France","pay_time": 1589191487,"price": 895}
+```
+
+**目标数据库和表**
+
+假设在 StarRocks 集群的目标数据库 `example_db` 中存在目标表 `example_tbl4` 其中有一列衍生列 `pay_dt`，是基于 JSON 数据的Key `pay_time` 进行计算后的数据。其建表语句如下：
+
+```SQL
+CREATE TABLE example_db.example_tbl4 ( 
+    `commodity_id` varchar(26) NULL COMMENT "品类ID", 
+    `customer_name` varchar(26) NULL COMMENT "顾客姓名", 
+    `country` varchar(26) NULL COMMENT "顾客国籍",
+    `pay_time` bigint(20) NULL COMMENT "支付时间",  
+    `pay_dt` date NULL COMMENT "支付日期", 
+    `price`double SUM NULL COMMENT "支付金额") 
+AGGREGATE KEY(`commodity_id`,`customer_name`,`country`,`pay_time`,`pay_dt`) 
+DISTRIBUTED BY HASH(`commodity_id`);
+```
+
+**导入作业**
+
+提交导入作业时使用匹配模式。使用 `jsonpaths` 指定待导入 JSON 数据的 Key。并且由于 JSON 数据中 key `pay_time` 需要转换为 DATE 类型，才能导入到目标表的列 `pay_dt`，因此 `COLUMNS` 中需要使用函数`from_unixtime`进行转换。JSON 数据的其他 key 都能直接映射至表 `example_tbl4` 中。
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl4_ordertest2 ON example_tbl4
+COLUMNS(commodity_id, customer_name, country, pay_time, pay_dt=from_unixtime(pay_time, '%Y%m%d'), price)
+PROPERTIES
+(
+    "format" = "json",
+    "jsonpaths" = "[\"$.commodity_id\",\"$.customer_name\",\"$.country\",\"$.pay_time\",\"$.price\"]"
+ )
+FROM KAFKA
+(
+    "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest2"
+);
+```
+
+> **说明**
+>
+> - 如果 JSON 数据最外层是数组结构，则需要在`PROPERTIES`设置`"strip_outer_array"="true"`，表示裁剪最外层的数组结构。并且需要注意在设置 `jsonpaths` 时，整个 JSON 数据的根节点是裁剪最外层的数组结构后**展平的 JSON 对象**。
+> - 如果不需要导入整个 JSON 数据，则需要使用 `json_root` 指定实际所需导入的 JSON 数据根节点。
+
+#### 目标表存在衍生列，其列值通过 CASE 表达式计算生成
+
+**数据集**
+
+假设 Kafka 集群的 Topic `topic-expr-test` 中存在如下 JSON 格式的数据。
+
+```JSON
+{"key1":1, "key2": 21}
+{"key1":12, "key2": 22}
+{"key1":13, "key2": 23}
+{"key1":14, "key2": 24}
+```
+
+**目标数据库和表**
+
+假设在 StarRocks 集群的目标数据库 `example_db` 中存在目标表 `tbl_expr_test` 包含两列，其中列 `col2` 的值基于 JSON 数据进行 CASE 表达式计算得出。其建表语句如下：
+
+```SQL
+CREATE TABLE tbl_expr_test (
+    col1 string, col2 string)
+DISTRIBUTED BY HASH (col1);
+```
+
+**导入作业**
+
+目标表中列 `col2` 的值需要基于 JSON 数据进行 CASE 表达式计算后得出，因此您需要在导入作业中的 `COLUMNS` 参数配置对应的 CASE 表达式。
+
+```SQL
+CREATE ROUTINE LOAD rl_expr_test ON tbl_expr_test
+COLUMNS (
+      key1,
+      key2,
+      col1 = key1,
+      col2 = CASE WHEN key1 = "1" THEN "key1=1" 
+                  WHEN key1 = "12" THEN "key1=12"
+                  ELSE "nothing" END) 
+PROPERTIES ("format" = "json")
+FROM KAFKA
+(
+    "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "topic-expr-test"
+);
+```
+
+**查询数据**
+
+查询目标表中的数据，返回结果显示列 `col2` 的值是使用 CASE 表达式计算后输出的值。
+
+```SQL
+MySQL [example_db]> SELECT * FROM tbl_expr_test;
++------+---------+
+| col1 | col2    |
++------+---------+
+| 1    | key1=1  |
+| 12   | key1=12 |
+| 13   | nothing |
+| 14   | nothing |
++------+---------+
+4 rows in set (0.015 sec)
+```
+
+#### 指定实际待导入 JSON 数据的根节点
+
+如果不需要导入整个 JSON 数据，则需要使用 `json_root` 指定实际上所需导入的 JSON 数据的根对象，参数取值为合法的 JsonPath。
+
+**数据集**
+
+假设 Kafka 集群的 Topic `ordertest3` 中存在如下 JSON 格式的数据，实际导入时仅需要导入 key `RECORDS`的值。
+
+```JSON
+{"RECORDS":[{"commodity_id": "1", "customer_name": "Mark Twain", "country": "US","pay_time": 1589191487,"price": 875},{"commodity_id": "2", "customer_name": "Oscar Wilde", "country": "UK","pay_time": 1589191487,"price": 895},{"commodity_id": "3", "customer_name": "Antoine de Saint-Exupéry","country": "France","pay_time": 1589191487,"price": 895}]}
+```
+
+**目标数据库和表**
+
+假设在 StarRocks 集群的目标数据库 `example_db` 中存在目标表`example_tbl3` ，其建表语句如下：
+
+```SQL
+CREATE TABLE example_db.example_tbl3 ( 
+    `commodity_id` varchar(26) NULL COMMENT "品类ID", 
+    `customer_name` varchar(26) NULL COMMENT "顾客姓名", 
+    `country` varchar(26) NULL COMMENT "顾客国籍", 
+    `pay_time` bigint(20) NULL COMMENT "支付时间", 
+    `price`double SUM NULL COMMENT "支付金额") 
+AGGREGATE KEY(`commodity_id`,`customer_name`,`country`,`pay_time`) 
+DISTRIBUTED BY HASH(`commodity_id`);
+```
+
+**导入作业**
+
+提交导入作业，设置`"json_root" = "$.RECORDS"`指定实际待导入的 JSON 数据的根节点。并且由于实际待导入的 JSON 数据是数组结构，因此还需要设置`"strip_outer_array" = "true"`，裁剪外层的数组结构。
+
+```SQL
+CREATE ROUTINE LOAD example_db.example_tbl3_ordertest3 ON example_tbl3
+PROPERTIES
+(
+    "format" = "json",
+    "strip_outer_array" = "true",
+    "json_root" = "$.RECORDS"
+ )
+FROM KAFKA
+(
+    "kafka_broker_list" ="<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>",
+    "kafka_topic" = "ordertest2"
+);
+```
+
+### 导入 Avro 数据
+
+自 3.0.1 版本开始，StarRocks 支持使用 Routine Load 导入 Avro 数据。
+
+#### Avro schema 只包含简单数据类型
+
+假设 Avro schema 只包含简单数据类型，并且您需要导入 Avro 数据中的所有字段。
+
+**数据集**
+
+**Avro schema**
+
+1. 创建如下 Avro schema 文件 `avro_schema1.avsc`：
+
+      ```json
+      {
+          "type": "record",
+          "name": "sensor_log",
+          "fields" : [
+              {"name": "id", "type": "long"},
+              {"name": "name", "type": "string"},
+              {"name": "checked", "type" : "boolean"},
+              {"name": "data", "type": "double"},
+              {"name": "sensor_type", "type": {"type": "enum", "name": "sensor_type_enum", "symbols" : ["TEMPERATURE", "HUMIDITY", "AIR-PRESSURE"]}}  
+          ]
+      }
+      ```
+
+2. 注册该 Avro schema 至 [Schema Registry](https://docs.confluent.io/platform/current/schema-registry/index.html)。
+
+**Avro 数据**
+
+构建 Avro 数据并且发送至 Kafka 集群的 topic `topic_1`。
+
+**目标数据库和表**
+
+根据 Avro 数据中需要导入的字段，在 StarRocks 集群的目标数据库 `sensor` 中创建表 `sensor_log1`。表的列名与 Avro 数据的字段名保持一致。两者的数据类型映射关系，请参见xxx。
+
+```SQL
+CREATE TABLE sensor.sensor_log1 ( 
+    `id` bigint NOT NULL COMMENT "sensor id",
+    `name` varchar(26) NOT NULL COMMENT "sensor name", 
+    `checked` boolean NOT NULL COMMENT "checked", 
+    `data` double NULL COMMENT "sensor data", 
+    `sensor_type` varchar(26) NOT NULL COMMENT "sensor type"
+) 
+ENGINE=OLAP 
+DUPLICATE KEY (id) 
+DISTRIBUTED BY HASH(`id`);
+```
+
+**导入作业**
+
+提交导入作业时使用简单模式，即无需使用 `jsonpaths` 参数，就可以将 Kafka 集群的 Topic `topic_1` 中的 Avro 数据导入至数据库 `sensor` 中的表 `sensor_log1`。
+
+```sql
+CREATE ROUTINE LOAD sensor.sensor_log_load_job1 ON sensor_log1  
+PROPERTIES  
+(  
+  "format" = "avro"  
+)  
+FROM KAFKA  
+(  
+  "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>,...",
+  "confluent.schema.registry.url" = "http://172.xx.xxx.xxx:8081",  
+  "kafka_topic" = "topic_1",  
+  "kafka_partitions" = "0,1,2,3,4,5",  
+  "property.kafka_default_offsets" = "OFFSET_BEGINNING"  
+);
+```
+
+#### Avro schema 嵌套 Record 类型的字段
+
+假设 Avro schema 嵌套 Record 类型的字段，并且您需要导入嵌套 Record 字段中的子字段。
+
+**数据集**
+
+**Avro schema**
+
+1. 创建如下 Avro schema 文件 `avro_schema2.avsc`。其中最外层 Record 的字段依次是 `id`、 `name`、`checked`、`sensor_type` 和 `data`。并且字段 `data` 包含嵌套 Record `data_record`。
+
+      ```JSON
+      {
+          "type": "record",
+          "name": "sensor_log",
+          "fields" : [
+              {"name": "id", "type": "long"},
+              {"name": "name", "type": "string"},
+              {"name": "checked", "type" : "boolean"},
+              {"name": "sensor_type", "type": {"type": "enum", "name": "sensor_type_enum", "symbols" : ["TEMPERATURE", "HUMIDITY", "AIR-PRESSURE"]}},
+              {"name": "data", "type": 
+                  {
+                      "type": "record",
+                      "name": "data_record",
+                      "fields" : [
+                          {"name": "data_x", "type" : "boolean"},
+                          {"name": "data_y", "type": "long"}
+                      ]
+                  }
+              }
+          ]
+      }
+      ```
+
+2. 注册该 Avro schema 至 [Schema Registry](https://docs.confluent.io/platform/current/schema-registry/index.html)。
+
+**Avro 数据**
+
+构建 Avro 数据并且发送至 Kafka 集群的 topic `topic_2`。
+
+**目标数据库和表**
+
+根据 Avro 数据中需要导入的字段，在 StarRocks 集群的目标数据库 `sensor` 中创建表 `sensor_log2`。
+
+假设您除了需要导入最外层 Record 的 `id`、`name`、`checked`、`sensor_type` 字段之外，还需要导入嵌套 Record 中的字段 `data_y`。
+
+```sql
+CREATE TABLE sensor.sensor_log2 ( 
+    `id` bigint NOT NULL COMMENT "sensor id",
+    `name` varchar(26) NOT NULL COMMENT "sensor name", 
+    `checked` boolean NOT NULL COMMENT "checked", 
+    `sensor_type` varchar(26) NOT NULL COMMENT "sensor type",
+    `data_y` long NULL COMMENT "sensor data" 
+) 
+ENGINE=OLAP 
+DUPLICATE KEY (id) 
+DISTRIBUTED BY HASH(`id`);
+```
+
+**导入作业**
+
+提交导入作业，使用 `jsonpaths` 指定实际待导入的 Avro 数据的字段。其中对于嵌套 Record 中的字段 `data_y`，您需要指定 `jsonpaths` 为 `"$.data.data_y"`。
+
+```sql
+CREATE ROUTINE LOAD sensor.sensor_log_load_job2 ON sensor_log2  
+PROPERTIES  
+(  
+  "format" = "avro",
+  "jsonpaths" = "[\"$.id\",\"$.name\",\"$.checked\",\"$.sensor_type\",\"$.data.data_y\"]"
+)  
+FROM KAFKA  
+(  
+  "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>,...",
+  "confluent.schema.registry.url" = "http://172.xx.xxx.xxx:8081",  
+  "kafka_topic" = "topic_1",  
+  "kafka_partitions" = "0,1,2,3,4,5",  
+  "property.kafka_default_offsets" = "OFFSET_BEGINNING"  
+);
+```
+
+#### Avro schema 包含 Union 类型的字段
+
+**数据集**
+
+假设 Avro 数据包含 Union 类型的字段，并且您需要导入该 Union 字段。
+
+**Avro schema**
+
+1. 创建如下 Avro schema 文件 `avro_schema3.avsc`。其中最外层 Record 的字段依次是`id`、`name`、 `checked`、 `sensor_type` 和 `data`。并且字段 `data`为 Union 类型，包含两个元素，分别是 `null` 和嵌套 Record `data_record` 。
+
+      ```JSON
+      {
+          "type": "record",
+          "name": "sensor_log",
+          "fields" : [
+              {"name": "id", "type": "long"},
+              {"name": "name", "type": "string"},
+              {"name": "checked", "type" : "boolean"},
+              {"name": "sensor_type", "type": {"type": "enum", "name": "sensor_type_enum", "symbols" : ["TEMPERATURE", "HUMIDITY", "AIR-PRESSURE"]}},
+              {"name": "data", "type": [null,
+                    {
+                        "type": "record",
+                        "name": "data_record",
+                        "fields" : [
+                            {"name": "data_x", "type" : "boolean"},
+                            {"name": "data_y", "type": "long"}
+                        ]
+                    }
+                  ]
+              }
+          ]
+      }
+      ```
+
+2. 注册该 Avro schema 至 [Schema Registry](https://docs.confluent.io/platform/current/schema-registry/index.html)。
+
+**Avro 数据**
+
+构建 Avro 数据并且发送至 Kafka 集群的 topic `topic_3`。
+
+**目标数据库和表**
+
+根据 Avro 数据中需要导入的字段，在 StarRocks 集群的目标数据库 `sensor` 中创建表 `sensor_log3` 。
+
+假设您除了需要导入最外层 Record 的 `id`、`name`、`checked`、`sensor_type` 字段之外，还需要导入 Union 类型的字段 `data` 中元素 `data_record` 包含的字段 `data_y`。
+
+```sql
+CREATE TABLE sensor.sensor_log3 ( 
+    `id` bigint NOT NULL COMMENT "sensor id",
+    `name` varchar(26) NOT NULL COMMENT "sensor name", 
+    `checked` boolean NOT NULL COMMENT "checked", 
+    `sensor_type` varchar(26) NOT NULL COMMENT "sensor type",
+    `data_y` long NULL COMMENT "sensor data" 
+) 
+ENGINE=OLAP 
+DUPLICATE KEY (id) 
+DISTRIBUTED BY HASH(`id`);
+```
+
+**导入作业**
+
+提交导入作业，使用 `jsonpaths` 指定实际待导入的 Avro 数据的字段。其中您需要指定字段 `data_y`的`jsonpaths` 为 `"$.data.data_y"`。
+
+```sql
+CREATE ROUTINE LOAD sensor.sensor_log_load_job3 ON sensor_log3  
+PROPERTIES  
+(  
+  "format" = "avro",
+  "jsonpaths" = "[\"$.id\",\"$.name\",\"$.checked\",\"$.sensor_type\",\"$.data.data_y\"]"
+)  
+FROM KAFKA  
+(  
+  "kafka_broker_list" = "<kafka_broker1_ip>:<kafka_broker1_port>,<kafka_broker2_ip>:<kafka_broker2_port>,...",
+  "confluent.schema.registry.url" = "http://172.xx.xxx.xxx:8081",  
+  "kafka_topic" = "topic_1",  
+  "kafka_partitions" = "0,1,2,3,4,5",  
+  "property.kafka_default_offsets" = "OFFSET_BEGINNING"  
+);
+```
+
+当 Union 类型的字段 `data` 的值为 `null` 时，则导入 `data_y` 列的值为 `null`。当 `data` 的值为一条 data record 时，则导入  `data_y` 列的值 Long 类型。
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/PAUSE_ROUTINE_LOAD.md b/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/PAUSE_ROUTINE_LOAD.md
new file mode 100644
index 00000000000000..6ca573b91b6cd5
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/PAUSE_ROUTINE_LOAD.md
@@ -0,0 +1,36 @@
+---
+displayed_sidebar: docs
+---
+
+# PAUSE ROUTINE LOAD
+
+import RoutineLoadPrivNote from '../../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
+
+## 功能
+
+暂停 Routine Load 导入作业，导入作业会进入 PAUSED 状态，但是未结束，您可以执行 [RESUME ROUTINE LOAD](./RESUME_ROUTINE_LOAD.md) 语句重启导入作业。
+
+Routine Load 导入作业暂停后，您可以执行 [SHOW ROUTINE LOAD](SHOW_ROUTINE_LOAD.md) 、[ALTER ROUTINE LOAD](ALTER_ROUTINE_LOAD.md) 语句查看和修改已暂停的导入作业的信息。
+
+<RoutineLoadPrivNote />
+
+## 语法
+
+```SQL
+PAUSE ROUTINE LOAD FOR [db_name.]<job_name>
+```
+
+## 参数说明
+
+| 参数名称 | 是否必填 | 说明                                                         |
+| -------- | -------- | ------------------------------------------------------------ |
+| db_name  |          | Routine Load 导入作业所属数据库名称。                                           |
+| job_name | ✅        | Routine Load 导入作业名称。|
+
+## 示例
+
+暂停 `example_db` 数据库中名称为 `example_tbl1_ordertest1` 的 Routine Load 导入作业。
+
+```SQL
+PAUSE ROUTINE LOAD FOR example_db.example_tbl1_ordertest1;
+```
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md b/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md
new file mode 100644
index 00000000000000..67b99ee667e1ea
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/RESUME_ROUTINE_LOAD.md
@@ -0,0 +1,34 @@
+---
+displayed_sidebar: docs
+---
+
+# RESUME ROUTINE LOAD
+
+import RoutineLoadPrivNote from '../../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
+
+## 功能
+
+恢复 Routine Load 导入作业。导入作业会先短暂地进入 **NEED_SCHEDULE** 状态，表示正在重新调度导入作业，一段时间后会恢复至 **RUNNING** 状态，继续消费数据源的消息并且导入数据。您可以执行 [SHOW ROUTINE LOAD](SHOW_ROUTINE_LOAD.md) 语句查看已恢复的导入作业。
+
+<RoutineLoadPrivNote />
+
+## 语法
+
+```SQL
+RESUME ROUTINE LOAD FOR [db_name.]<job_name>
+```
+
+## 参数说明
+
+| 参数名称 | 是否必填 | 说明                        |
+| -------- | -------- | --------------------------- |
+| db_name  |          | Routine Load 导入作业所属数据库名称。         |
+| job_name | ✅        | Routine Load 导入作业名称。 |
+
+## 示例
+
+恢复 `example_db` 数据库中名称为 `example_tbl1_ordertest1` 的 Routine Load 导入作业。
+
+```SQL
+RESUME ROUTINE LOAD FOR example_db.example_tbl1_ordertest1;
+```
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md b/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md
new file mode 100644
index 00000000000000..f0d14df34362da
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD.md
@@ -0,0 +1,126 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW ROUTINE LOAD
+
+import RoutineLoadPrivNote from '../../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
+
+## 功能
+
+查看 Routine Load 导入作业的执行情况。
+
+<RoutineLoadPrivNote />
+
+## 语法
+
+```SQL
+SHOW [ALL] ROUTINE LOAD [ FOR [<db_name>.]<job_name> | FROM <db_name> ]
+[ WHERE [ STATE = { "NEED_SCHEDULE" | "RUNNING" | "PAUSED" | "UNSTABLE" | "STOPPED" | "CANCELLED"  } ] ]
+[ ORDER BY <field_name> [ ASC | DESC ] ]
+[ LIMIT { [offset, ] limit | limit OFFSET offset } ]
+```
+
+:::note
+
+如果返回结果中的字段较多，可使用 `\G` 分行，如 `SHOW ROUTINE LOAD FOR <job_name>\G`。
+
+:::
+
+## 参数说明
+
+| **参数**                          | **必选** | **说明**                                                     |
+| --------------------------------- | -------- | ------------------------------------------------------------ |
+| db_name                           | 否       | 导入作业所属数据库名称。注意在使用 FROM 子句时，该参数为必填参数。                                     |
+| job_name                          | 否        | 导入作业名称。注意在使用 FOR 子句时，该参数为必填参数。                                              |
+| ALL                               | 否       | 显示所有导入作业，包括处于 `STOPPED` 和 `CANCELLED` 状态的导入作业。 |
+| STATE                             | 否       | 导入作业状态。                                               |
+| ORDER BY field_name [ASC \| DESC] | 否       | 将返回结果按照指定字段升序或降序排列，当前支持的排序字段（`field_name`）包括 `Id`、`Name`、`CreateTime`、`PauseTime`、`EndTime`、`TableName`、`State` 和 `CurrentTaskNum`。如要升序排列，指定 `ORDER BY field_name ASC`。如要降序排列，指定 `ORDER BY field_name DESC`。如既不指定排序字段也不指定排列顺序，则默认按照 `Id` 升序排列。 |
+| LIMIT limit                       | 否       | 查看指定数量的导入作业，例如 `LIMIT 10` 会显示 10 个符合筛选条件的导入作业。如不指定该参数，则默认显示所有符合筛选条件的导入作业。 |
+| OFFSET offset                     | 否       | `offset` 定义了返回结果中跳过的导入作业的数量，其默认值为 0。例如 `OFFSET 5` 表示跳过前 5 个导入作业，返回剩下的结果。 |
+
+## 返回结果说明
+
+| **参数**             | **说明**                                                     |
+| -------------------- | ------------------------------------------------------------ |
+| Id                   | 导入作业的全局唯一 ID，由 StarRocks 自动生成。               |
+| Name                 | 导入作业的名称。                                             |
+| CreateTime           | 导入作业创建的时间。                                         |
+| PauseTime            | 处于 `PAUSED` 状态的导入作业的暂停时间。                     |
+| EndTime              | 处于 `STOPPED` 状态的导入作业的停止时间。                    |
+| DbName               | 导入作业目标表所属数据库。                                   |
+| TableName            | 导入作业目标表。                                             |
+| State                | 导入作业状态。包括：<ul><li>`NEED_SCHEDULE`：待调度状态。CREATE ROUTINE LOAD 或者 RESUME ROUTINE LOAD 后，导入作业会先进入待调度状态。</li><li>`RUNNING`：运行状态。消费进度可以通过`Statistic`、`Progress` 中查看。</li><li>`PAUSED`：暂停状态。您可以参考 `ReasonOfStateChanged`、`ErrorLogUrls` 进行修复。修复后您可以使用 [RESUME ROUTINE LOAD](https://docs.starrocks.io/zh/docs/3.2/sql-reference/sql-statements/data-manipulation/RESUME_ROUTINE_LOAD/)。</li><li>`CANCELLED`：取消状态。您可以参考 `ReasonOfStateChanged`、`ErrorLogUrls` 进行修复。但是修复后，您无法恢复该状态的导入作业。</li><li>`STOPPED`：停止状态。您无法恢复该状态的导入作业。</li><li>`UNSTABLE`：不稳定状态。Routine Load 导入作业的任一导入任务消费延迟，即正在消费的消息时间戳与当前时间的差值超过 FE 参数 [`routine_load_unstable_threshold_second`](../../../../administration/management/FE_configuration.md)  的值，且数据源中存在未被消费的消息，则导入作业置为 `UNSTABLE` 状态。 </li></ul>|
+| DataSourceType       | 数据源类型。固定为 `KAFKA`。                                 |
+| CurrentTaskNum       | 导入作业当前的任务数量。                                     |
+| JobProperties        | 导入作业属性。比如消费分区、列映射关系。                     |
+| DataSourceProperties | 数据源属性。比如 Topic、Kafka 集群中 Broker 的地址和端口列表。 |
+| CustomProperties     | 导入作业中自定义的更多数据源相关属性。                       |
+| Statistic            | 导入数据的指标，比如成功导入数据行、总数据行、已接受的数据量。 |
+| Progress             | 导入作业消费 Topic 中各个分区消息的进度（以位点进行衡量）。           |
+| TimestampProgress    | 导入作业消费 Topic 中各个分区消息的进度（以时间戳进行衡量）。         |
+| ReasonOfStateChanged | 导致导入作业处于 `CANCELLED` 或者 `PAUSED` 状态的原因。      |
+| ErrorLogUrls         | 错误日志 URL。您可以使用 `curl` 或 `wget` 命令打开该地址。   |
+| TrackingSQL          | 直接通过 SQL 查询 Information Schema 中记录的错误日志信息。  |
+| OtherMsg             | 所有失败的导入任务的信息。                                   |
+| LatestSourcePosition | 数据源 Kafka 中 Topic 中各个分区的最新消息位点，便于检查导入延迟情况。  | 
+
+## 示例
+
+如果导入作业成功处于 `RUNNING` 状态，则返回结果可能如下：
+
+```SQL
+MySQL [example_db]> SHOW ROUTINE LOAD FOR example_tbl_ordertest1\G
+*************************** 1. row ***************************
+                  Id: 10204
+                Name: example_tbl_ordertest1
+          CreateTime: 2023-12-21 21:01:31
+           PauseTime: NULL
+             EndTime: NULL
+              DbName: example_db
+           TableName: example_tbl
+               State: RUNNING
+      DataSourceType: KAFKA
+      CurrentTaskNum: 1
+       JobProperties: {"partitions":"*","rowDelimiter":"\t","partial_update":"false","columnToColumnExpr":"order_id,pay_dt,customer_name,nationality,temp_gender,price","maxBatchIntervalS":"10","partial_update_mode":"null","whereExpr":"*","timezone":"Asia/Shanghai","format":"csv","columnSeparator":"','","log_rejected_record_num":"0","taskTimeoutSecond":"60","json_root":"","maxFilterRatio":"1.0","strict_mode":"false","jsonpaths":"","taskConsumeSecond":"15","desireTaskConcurrentNum":"5","maxErrorNum":"0","strip_outer_array":"false","currentTaskConcurrentNum":"1","maxBatchRows":"200000"}
+DataSourceProperties: {"topic":"lilyliuyitest4csv","currentKafkaPartitions":"0","brokerList":"xxx.xx.xx.xxx:9092"}
+    CustomProperties: {"kafka_default_offsets":"OFFSET_BEGINNING","group.id":"example_tbl_ordertest1_b05da08f-9b9d-4fe1-b1f2-25d7116d617c"}
+           Statistic: {"receivedBytes":313,"errorRows":0,"committedTaskNum":1,"loadedRows":6,"loadRowsRate":0,"abortedTaskNum":0,"totalRows":6,"unselectedRows":0,"receivedBytesRate":0,"taskExecuteTimeMs":699}
+            Progress: {"0":"5"}
+   TimestampProgress: {"0":"1686143856061"}
+ReasonOfStateChanged: 
+        ErrorLogUrls: 
+         TrackingSQL: 
+            OtherMsg: 
+LatestSourcePosition: {"0":"6"}
+1 row in set (0.01 sec)
+```
+
+如果导入作业因异常而处于 `PAUSED` 或者 `CANCELLED` 状态，您可以根据返回结果中的 `ReasonOfStateChanged`、`ErrorLogUrls` 、`TrackingSQL` 和 `OtherMsg` 排查具体原因。
+
+```SQL
+MySQL [example_db]> SHOW ROUTINE LOAD FOR example_tbl_ordertest2\G
+*************************** 1. row ***************************
+                  Id: 10204
+                Name: example_tbl_ordertest2
+          CreateTime: 2023-12-22 12:13:18
+           PauseTime: 2023-12-22 12:13:38
+             EndTime: NULL
+              DbName: example_db
+           TableName: example_tbl
+               State: PAUSED
+      DataSourceType: KAFKA
+      CurrentTaskNum: 0
+       JobProperties: {"partitions":"*","rowDelimiter":"\t","partial_update":"false","columnToColumnExpr":"order_id,pay_dt,customer_name,nationality,temp_gender,price","maxBatchIntervalS":"10","partial_update_mode":"null","whereExpr":"*","timezone":"Asia/Shanghai","format":"csv","columnSeparator":"','","log_rejected_record_num":"0","taskTimeoutSecond":"60","json_root":"","maxFilterRatio":"1.0","strict_mode":"false","jsonpaths":"","taskConsumeSecond":"15","desireTaskConcurrentNum":"5","maxErrorNum":"0","strip_outer_array":"false","currentTaskConcurrentNum":"1","maxBatchRows":"200000"}
+DataSourceProperties: {"topic":"mytest","currentKafkaPartitions":"0","brokerList":"xxx.xx.xx.xxx:9092"}
+    CustomProperties: {"kafka_default_offsets":"OFFSET_BEGINNING","group.id":"example_tbl_ordertest2_b3fada0f-6721-4ad1-920d-e4bf6d6ea7f7"}
+           Statistic: {"receivedBytes":541,"errorRows":10,"committedTaskNum":1,"loadedRows":6,"loadRowsRate":0,"abortedTaskNum":0,"totalRows":16,"unselectedRows":0,"receivedBytesRate":0,"taskExecuteTimeMs":646}
+            Progress: {"0":"19"}
+   TimestampProgress: {"0":"1702623900871"}
+ReasonOfStateChanged: ErrorReason{errCode = 102, msg='current error rows is more than max error num'}
+        ErrorLogUrls: http://xxx.xx.xx.xxx:8040/api/_load_error_log?file=error_log_b25dcc7e642344b2_b0b342b9de0567db
+         TrackingSQL: select tracking_log from information_schema.load_tracking_logs where job_id=10204
+            OtherMsg: 
+LatestSourcePosition: {"0":"20"}
+1 row in set (0.00 sec)
+```
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD_TASK.md b/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD_TASK.md
new file mode 100644
index 00000000000000..74f7673bb9a8dc
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/SHOW_ROUTINE_LOAD_TASK.md
@@ -0,0 +1,70 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW ROUTINE LOAD TASK
+
+import RoutineLoadPrivNote from '../../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
+
+## 功能
+
+查看 Routine Load 导入作业下属导入任务的执行情况。
+
+:::note
+
+- <RoutineLoadPrivNote />
+
+- Routine Load 中导入作业和导入任务的关系，参见[使用 Routine Load 导入数据](../../../../loading/RoutineLoad.md#基本原理)。
+
+:::
+
+## 语法
+
+```SQL
+SHOW ROUTINE LOAD TASK
+    [FROM <db_name>]
+    [ WHERE JobName = <job_name> ]
+```
+
+:::note
+
+返回结果中的字段较多，可使用 `\G` 分行，如 `SHOW ROUTINE LOAD TASK WHERE JobName = <job_name> \G`。
+
+:::
+
+## 参数说明
+
+| **参数** | **必选** | **说明**                              |
+| -------- | -------- | ------------------------------------- |
+| db_name  | 否       | Routine Load 导入作业所属数据库名称。 |
+| JobName  | 否       | Routine Load 导入作业名称。           |
+
+## 返回结果说明
+
+| 字段                 | 说明                                                         |
+| -------------------- | ------------------------------------------------------------ |
+| TaskId               | 导入任务的全局唯一 ID，由 StarRocks 自动生成。               |
+| TxnId                | 该导入任务所属事务 ID。                                      |
+| TxnStatus            | 该导入任务所属事务状态。`UNKOWN` 表示事务没有开始，可能是导入任务还没有下发，或者没有实际执行。 |
+| JobId                | 导入作业 ID。                                                |
+| CreateTime           | 该导入任务创建时间。                                         |
+| LastScheduledTime    | 上一次调度该导入任务的时间。                                 |
+| ExecuteStartTime     | 该导入任务执行时间。                                         |
+| Timeout              | 导入任务超时时间，由 FE 参数 [`routine_load_task_timeout_second`](../../../../administration/management/FE_configuration.md#routine_load_task_timeout_second) 和 Routine Load 导入作业的 [job_properties](./CREATE_ROUTINE_LO../../data-manipulation/CREATE_ROUTINE_LOAD.md参数 `task_timeout_second` 控制。 |
+| BeId                 | 执行该导入任务的 BE 节点 ID。                                |
+| DataSourceProperties | 该导入任务消费分区数据的进度。                               |
+| Message              | 导入任务的返回信息，包含任务错误信息。                       |
+
+## 示例
+
+查看 Routine Load  导入作业 `example_tbl_ordertest` 下的所有导入任务。
+
+```SQL
+MySQL [example_db]> SHOW ROUTINE LOAD TASK WHERE JobName = "example_tbl_ordertest";  
++--------------------------------------+-------+-----------+-------+---------------------+---------------------+------------------+---------+------+------------------------------------+-----------------------------------------------------------------------------+
+| TaskId                               | TxnId | TxnStatus | JobId | CreateTime          | LastScheduledTime   | ExecuteStartTime | Timeout | BeId | DataSourceProperties               | Message                                                                     |
++--------------------------------------+-------+-----------+-------+---------------------+---------------------+------------------+---------+------+------------------------------------+-----------------------------------------------------------------------------+
+| abde6998-c19a-43d6-b48c-6ca7e14144a3 | -1    | UNKNOWN   | 10208 | 2023-12-22 12:46:10 | 2023-12-22 12:47:00 | NULL             | 60      | -1   | Progress:{"0":6},LatestOffset:null | there is no new data in kafka/pulsar, wait for 10 seconds to schedule again |
++--------------------------------------+-------+-----------+-------+---------------------+---------------------+------------------+---------+------+------------------------------------+-----------------------------------------------------------------------------+
+1 row in set (0.00 sec)
+```
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/STOP_ROUTINE_LOAD.md b/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/STOP_ROUTINE_LOAD.md
new file mode 100644
index 00000000000000..50d506d30a4411
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/routine_load/STOP_ROUTINE_LOAD.md
@@ -0,0 +1,42 @@
+---
+displayed_sidebar: docs
+---
+
+# STOP ROUTINE LOAD
+
+import RoutineLoadPrivNote from '../../../../_assets/commonMarkdown/RoutineLoadPrivNote.md'
+
+## 功能
+
+停止 Routine Load 导入作业。
+
+<RoutineLoadPrivNote />
+
+::: warning
+
+导入作业停止且无法恢复。因此请谨慎执行该语句。
+
+如果仅仅需要暂停导入作业，则可以执行 [PAUSE ROUTINE LOAD](PAUSE_ROUTINE_LOAD.md)。
+
+:::
+
+## 语法
+
+```SQL
+STOP ROUTINE LOAD FOR [db_name.]<job_name>
+```
+
+## 参数说明
+
+| 参数名称 | 是否必填 | 说明                        |
+| -------- | -------- | --------------------------- |
+| db_name  |          | Routine Load 导入作业所属数据库名称。         |
+| job_name | ✅        | Routine Load 导入作业名称。 |
+
+## 示例
+
+停止 `example_db` 数据库中名称为 `example_tbl1_ordertest1` 的 Routine Load 导入作业。
+
+```SQL
+STOP ROUTINE LOAD FOR example_db.example_tbl1_ordertest1;
+```
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/unloading/CANCEL_EXPORT.md b/docs/zh/sql-reference/sql-statements/loading_unloading/unloading/CANCEL_EXPORT.md
new file mode 100644
index 00000000000000..806c6b2337ef28
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/unloading/CANCEL_EXPORT.md
@@ -0,0 +1,45 @@
+---
+displayed_sidebar: docs
+---
+
+# CANCEL EXPORT
+
+## 功能
+
+取消指定的数据导出作业，状态为 `CANCELLED` 或 `FINISHED` 的导出作业不能取消。CANCEL EXPORT 是一个异步操作，执行后可使用 [SHOW EXPORT](./SHOW_EXPORT.md) 语句查看是否取消成功。当状态 (`State`) 为 `CANCELLED` 时，代表成功取消了导入作业。
+
+> **注意**
+>
+> 要执行该操作，需要有对应表的 EXPORT 权限。
+
+## 语法
+
+```SQL
+CANCEL EXPORT
+[FROM db_name]
+WHERE QUERYID = "query_id"
+```
+
+## 参数说明
+
+| **参数** | **必选** | **说明**                                                     |
+| -------- | -------- | ------------------------------------------------------------ |
+| db_name  | 否       | 数据库名称。如不指定，则默认取消当前数据库中的指定导出作业。 |
+| query_id | 是       | 导出作业的查询 ID，可使用 [LAST_QUERY_ID()](../../../sql-functions/utility-functions/last_query_id.md) 函数获取。注意使用该函数只能获取到最近一次的查询 ID。 |
+
+## 示例
+
+示例一：取消当前数据库中，查询 ID 为 `921d8f80-7c9d-11eb-9342-acde48001121` 的导出作业。
+
+```SQL
+CANCEL EXPORT
+WHERE queryid = "921d8f80-7c9d-11eb-9342-acde48001121";
+```
+
+示例二：取消数据库 `example_db` 中，查询 ID 为 `921d8f80-7c9d-11eb-9342-acde48001122` 的导出作业。
+
+```SQL
+CANCEL EXPORT 
+FROM example_db 
+WHERE queryid = "921d8f80-7c9d-11eb-9342-acde48001122";
+```
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/unloading/EXPORT.md b/docs/zh/sql-reference/sql-statements/loading_unloading/unloading/EXPORT.md
new file mode 100644
index 00000000000000..3f024ce9b01574
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/unloading/EXPORT.md
@@ -0,0 +1,208 @@
+---
+displayed_sidebar: docs
+---
+
+# EXPORT
+
+## 功能
+
+该语句用于将指定表的数据导出到指定位置。
+
+这是一个异步操作，任务提交成功后返回结果。执行后可使用 [SHOW EXPORT](./SHOW_EXPORT.md) 命令查看进度。
+
+> **注意**
+>
+> 导出操作需要目标表的 EXPORT 权限。如果您的用户账号没有 EXPORT 权限，请参考 [GRANT](../../account-management/GRANT.md) 给用户赋权。
+
+## 语法
+
+```sql
+EXPORT TABLE <table_name>
+[PARTITION (<partition_name>[, ...])]
+[(<column_name>[, ...])]
+TO <export_path>
+[opt_properties]
+WITH BROKER
+[broker_properties]
+```
+
+## 参数说明
+
+- `table_name`
+
+  待导出数据所在的表。目前支持导出 `engine` 为 `olap` 或 `mysql` 的表。
+
+- `partition_name`
+
+  要导出的分区。如不指定则默认导出表中所有分区的数据。
+
+- `column_name`
+
+  要导出的列。列的导出顺序可以和源表结构 (Schema) 不同。如不指定则默认导出表中所有列的数据。
+
+- `export_path`
+
+  导出的目标路径。如果是目录，需要以斜杠 (/) 结尾。否则最后一个斜杠后面的部分会作为导出文件的前缀。如不指定文件名前缀，则默认文件名前缀为 `data_`。
+
+- `opt_properties`
+
+  导出相关的属性配置。
+
+  语法：
+
+  ```sql
+  [PROPERTIES ("<key>"="<value>", ...)]
+  ```
+
+  配置项：
+
+  | **配置项**         | **描述**                                                     |
+  | ---------------- | ------------------------------------------------------------ |
+  | column_separator | 指定导出文件的列分隔符。默认值：`\t`。                       |
+  | line_delimiter   | 指定导出文件的行分隔符。默认值：`\n`。                       |
+  | load_mem_limit   | 指定导出任务在单个 BE 节点上的内存使用上限。单位：字节。默认内存使用上限为 2 GB。 |
+  | timeout          | 指定导出任务的超时时间。单位：秒。默认值：`86400`（1 天）。  |
+  | include_query_id | 指定导出文件名中是否包含 `query_id`。取值范围：`true` 和 `false`。默认值：`true`。`true` 表示包含，`false` 表示不包含。 |
+
+- `WITH BROKER`
+
+  在 v2.4 及以前版本，您需要在导出语句中通过 `WITH BROKER "<broker_name>"` 来指定使用哪个 Broker。自 v2.5 起，您不再需要指定 `broker_name`，但继续保留 `WITH BROKER` 关键字。参见[从 使用 EXPORT 导出数据 > 背景信息](../../../../unloading/Export.md#背景信息)。
+
+- `broker_properties`
+
+  用于提供访问数据源的鉴权信息。数据源不同，需要提供的鉴权信息也不同，参考 [BROKER LOAD](../BROKER_LOAD.md)。
+
+## 示例
+
+### 将表中所有数据导出到 HDFS
+
+将 `testTbl` 表中的所有数据导出到 HDFS 集群的指定路径下。
+
+```sql
+EXPORT TABLE testTbl 
+TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
+WITH BROKER
+(
+    "username"="xxx",
+    "password"="yyy"
+);
+```
+
+### 将表中部分分区的数据导出到 HDFS
+
+将 `testTbl` 表中 `p1` 和 `p2` 分区的数据导出到 HDFS 集群的指定路径下。
+
+```sql
+EXPORT TABLE testTbl
+PARTITION (p1,p2) 
+TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
+WITH BROKER
+(
+    "username"="xxx",
+    "password"="yyy"
+);
+```
+
+### 指定分隔符
+
+将 `testTbl` 表中的所有数据导出到 HDFS 集群的指定路径下，以 `,` 作为导出文件的列分隔符。
+
+```sql
+EXPORT TABLE testTbl 
+TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
+PROPERTIES
+(
+    "column_separator"=","
+) 
+WITH BROKER
+(
+    "username"="xxx",
+    "password"="yyy"
+);
+```
+
+将 `testTbl` 表中的所有数据导出到 HDFS 集群的指定路径下，以 Hive 默认分隔符 `\x01` 作为导出文件的列分隔符。
+
+```sql
+EXPORT TABLE testTbl 
+TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/" 
+PROPERTIES
+(
+    "column_separator"="\\x01"
+) 
+WITH BROKER;
+```
+
+### 指定导出文件名前缀
+
+将 `testTbl` 表中的所有数据导出到 HDFS 集群的指定路径下，以 `testTbl_` 作为导出文件的文件名前缀。
+
+```sql
+EXPORT TABLE testTbl 
+TO "hdfs://<hdfs_host>:<hdfs_port>/a/b/c/testTbl_" 
+WITH BROKER;
+```
+
+### 导出数据到 Alibaba Cloud OSS
+
+将 `testTbl` 表中的所有数据导出到 Alibaba Cloud OSS 存储桶的指定路径下。
+
+```sql
+EXPORT TABLE testTbl 
+TO "oss://oss-package/export/"
+WITH BROKER
+(
+    "fs.oss.accessKeyId" = "xxx",
+    "fs.oss.accessKeySecret" = "yyy",
+    "fs.oss.endpoint" = "oss-cn-zhangjiakou-internal.aliyuncs.com"
+);
+```
+
+### 导出数据到 Tencent Cloud COS
+
+将 `testTbl` 表中的所有数据导出到 Tencent Cloud COS 存储桶的指定路径下。
+
+```sql
+EXPORT TABLE testTbl 
+TO "cosn://cos-package/export/"
+WITH BROKER
+(
+    "fs.cosn.userinfo.secretId" = "xxx",
+    "fs.cosn.userinfo.secretKey" = "yyy",
+    "fs.cosn.bucket.endpoint_suffix" = "cos.ap-beijing.myqcloud.com"
+);
+```
+
+### 导出数据到 AWS S3
+
+将 `testTbl` 表中的所有数据导出到 AWS S3 存储桶的指定路径下。
+
+```sql
+EXPORT TABLE testTbl 
+TO "s3a://s3-package/export/"
+WITH BROKER
+(
+    "aws.s3.access_key" = "xxx",
+    "aws.s3.secret_key" = "yyy",
+    "aws.s3.region" = "zzz"
+);
+```
+
+### 导出数据到 Huawei Cloud OBS 上
+
+将 `testTbl` 表中的所有数据导出到 Huawei Cloud OBS 存储桶的指定路径下。
+
+```sql
+EXPORT TABLE testTbl 
+TO "obs://obs-package/export/"
+WITH BROKER
+(
+    "fs.obs.access.key" = "xxx",
+    "fs.obs.secret.key" = "yyy",
+    "fs.obs.endpoint" = "obs.cn-east-3.myhuaweicloud.com"
+);
+```
+
+> **说明**
+>
+> 导出数据至华为云 OBS 时，需要先下载[依赖库](https://github.com/huaweicloud/obsa-hdfs/releases/download/v45/hadoop-huaweicloud-2.8.3-hw-45.jar)添加到 **$BROKER_HOME/lib/** 路径中并重启 Broker。
diff --git a/docs/zh/sql-reference/sql-statements/loading_unloading/unloading/SHOW_EXPORT.md b/docs/zh/sql-reference/sql-statements/loading_unloading/unloading/SHOW_EXPORT.md
new file mode 100644
index 00000000000000..05eafeccbcf2fd
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/loading_unloading/unloading/SHOW_EXPORT.md
@@ -0,0 +1,130 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW EXPORT
+
+## 功能
+
+查询符合指定条件的导出作业的执行情况。
+
+## 语法
+
+```SQL
+SHOW EXPORT
+[ FROM <db_name> ]
+[
+WHERE
+    [ QUERYID = <query_id> ]
+    [ STATE = { "PENDING" | "EXPORTING" | "FINISHED" | "CANCELLED" } ]
+]
+[ ORDER BY <field_name> [ ASC | DESC ] [, ... ] ]
+[ LIMIT <count> ]
+```
+
+## 参数说明
+
+该语句包含四个可选子句：
+
+- FROM
+
+  指定要查询的数据库的名称。如果不指定该子句，则默认查询当前数据库。
+
+- WHERE
+
+  指定过滤条件。只有符合过滤条件的导入作业记录才会作为查询结果返回。
+
+  | **参数** | **是否必选** | **说明**                                                     |
+  | -------- | ------------ | ------------------------------------------------------------ |
+  | QUERYID  | 否           | 导出作业的 ID。该参数用于查询单个导出作业的执行情况。        |
+  | STATE    | 否           | 导出作业的状态。取值范围：<br /><ul><li>`PENDING`：表示查询待调度的导出作业。</li><li>`EXPORTING`：表示查询正在执行中的导出作业。</li><li>`FINISHED`：表示查询成功完成的导出作业。</li><li>`CANCELLED`：表示查询失败的导出作业。</li></ul> |
+
+- ORDER BY
+
+  指定用于对返回的导出作业记录进行排序的字段的名称。支持指定多个字段，多个字段之间必须用逗号 (,) 分隔。另外，您还可以在字段后通过添加 `ASC` 或 `DESC` 关键字来指定按该字段对返回的导出作业记录进行升序或降序排序。
+
+- LIMIT
+
+  指定允许返回的导出作业记录最大数量。取值范围：正整数。如果不指定该子句，则默认返回符合指定条件的所有导出作业。
+
+## 返回结果说明
+
+例如查看一个 ID 为 `edee47f0-abe1-11ec-b9d1-00163e1e238f` 的导出作业的执行情况：
+
+```SQL
+SHOW EXPORT
+WHERE QUERYID = "edee47f0-abe1-11ec-b9d1-00163e1e238f";
+```
+
+返回结果如下：
+
+```SQL
+     JobId: 14008
+   QueryId: edee47f0-abe1-11ec-b9d1-00163e1e238f
+     State: FINISHED
+  Progress: 100%
+  TaskInfo: {"partitions":["*"],"column separator":"\t","columns":["*"],"tablet num":10,"broker":"","coord num":1,"db":"db0","tbl":"tbl_simple","row delimiter":"\n","mem limit":2147483648}
+      Path: hdfs://127.0.0.1:9000/users/230320/
+CreateTime: 2023-03-20 11:16:14
+ StartTime: 2023-03-20 11:16:17
+FinishTime: 2023-03-20 11:16:26
+   Timeout: 7200
+```
+
+返回结果中的参数说明如下：
+
+- `JobId`：导出作业的 ID。
+- `QueryId`：当前查询的 ID。
+- `State`：导出作业的状态，包括：
+  - `PENDING`：导出作业待调度。
+  - `EXPORTING`：导出作业正在执行中。
+  - `FINISHED`：导出作业成功。
+  - `CANCELLED`：导出作业失败。
+- `Progress`：导出作业的进度。该进度以查询计划为单位。假设导出作业一共分为 10 个查询计划，当前已完成 3 个，则进度为 30%。有关查询计划的原理，参见[“使用 EXPORT 导出数据 > 导出流程”](../../../../unloading/Export.md#导出流程)。
+- `TaskInfo`：导出作业的信息，格式为 JSON，包括：
+  - `partitions`：导出数据所在的分区。通配符 (`*`) 表示导出了所有分区的数据。
+  - `column separator`：导出文件的列分隔符。
+  - `columns`：导出的列的名称。
+  - `tablet num`：导出的 Tablet 总数量。
+  - `broker`：在 v2.4 及以前版本，该字段用于返回导出作业使用的 Broker 的名称。自 v2.5 起，该字段返回一个空字符串。具体原因请参见[“使用 EXPORT 导出数据 > 背景信息”](../../../../unloading/Export.md#背景信息)。
+  - `coord num`：导出作业拆分的查询计划的个数。
+  - `db`：导出数据所在的数据库的名称。
+  - `tbl`：导出数据所在的表的名称。
+  - `row delimiter`：导出文件的行分隔符。
+  - `mem limit`：导出作业的内存使用限制。单位是字节。
+- `Path`：远端存储上的导出路径。
+- `CreateTime`：导出作业的创建时间。
+- `StartTime`：导出作业开始调度的时间。
+- `FinishTime`：导出作业的结束时间。
+- `Timeout`：导出作业的超时时间。单位是秒。该时间从 `CreateTime` 开始计算。
+- `ErrorMsg`：导出作业的错误原因。该字段仅当导出作业出现错误时才会返回。
+
+## 示例
+
+- 查询当前数据库下所有导出作业：
+
+  ```SQL
+  SHOW EXPORT;
+  ```
+
+- 查询指定数据库 `example_db` 下 ID 为 `921d8f80-7c9d-11eb-9342-acde48001122` 的导出作业：
+
+  ```SQL
+  SHOW EXPORT FROM example_db
+  WHERE queryid = "921d8f80-7c9d-11eb-9342-acde48001122";
+  ```
+
+- 查询指定数据库 `example_db` 下状态为 `EXPORTING` 的导出作业，并按 `StartTime` 对返回的导出作业记录进行升序排序：
+
+  ```SQL
+  SHOW EXPORT FROM example_db
+  WHERE STATE = "exporting"
+  ORDER BY StartTime ASC;
+  ```
+
+- 查询指定数据库 `example_db` 下所有导出作业，并按 `StartTime` 对返回的导出作业记录进行降序排序：
+
+  ```SQL
+  SHOW EXPORT FROM example_db
+  ORDER BY StartTime DESC;
+  ```
diff --git a/docs/zh/sql-reference/sql-statements/materialized_view/ALTER_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/materialized_view/ALTER_MATERIALIZED_VIEW.md
new file mode 100644
index 00000000000000..7215813f987cad
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/materialized_view/ALTER_MATERIALIZED_VIEW.md
@@ -0,0 +1,117 @@
+---
+keywords: ['xiugai'] 
+displayed_sidebar: docs
+---
+
+# ALTER MATERIALIZED VIEW
+
+## 功能
+
+此 SQL 语句可以：
+
+- 变更异步物化视图的名称
+- 变更异步物化视图的刷新策略
+- 变更异步物化视图的状态为 Active 或 Inactive
+- 原子替换异步物化视图
+- 变更异步物化视图的属性
+
+  您可以使用此 SQL 语句变更异步物化视图的以下属性：
+
+  - `partition_ttl_number`
+  - `partition_refresh_number`
+  - `resource_group`
+  - `auto_refresh_partitions_limit`
+  - `excluded_trigger_tables`
+  - `mv_rewrite_staleness_second`
+  - `unique_constraints`
+  - `foreign_key_constraints`
+  - `colocate_with`
+  - 所有 Session 变量属性。有关 Session 变量，详细信息请见 [系统变量](../../System_variable.md)。
+
+:::tip
+- 该操作需要对应物化视图的 ALTER 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
+- ALTER MATERIALIZED VIEW 不支持直接修改构建物化视图的查询语句。您可以重新构建物化视图，并通过 ALTER MATERIALIZED VIEW SWAP WITH 将其与原始物化视图替换。
+:::
+
+## 语法
+
+```SQL
+ALTER MATERIALIZED VIEW [db_name.]<mv_name> 
+    { RENAME [db_name.]<new_mv_name> 
+    | REFRESH <new_refresh_scheme_desc> 
+    | ACTIVE | INACTIVE 
+    | SWAP WITH <mv2_name>
+    | SET ( "<key>" = "<value>"[,...]) }
+```
+
+## 参数
+
+| **参数**                | **必选** | **说明**                                                     |
+| ----------------------- | -------- | ---------------------------------------------------------- |
+| mv_name                 | 是       | 待变更的物化视图的名称。                                       |
+| new_refresh_scheme_desc | 否       | 新的刷新机制，详细信息请见 [SQL 参考 - CREATE MATERIALIZED VIEW - 参数](CREATE_MATERIALIZED_VIEW.md#参数)。 |
+| new_mv_name             | 否       | 新的物化视图的名称。                                           |
+| ACTIVE                  | 否       | 将物化视图的状态设置为 Active。如果物化视图的基表发生更改，例如被删除后重新创建，StarRocks 会自动将该物化视图的状态设置为 Inactive，以避免原始元数据与更改后的基表不匹配的情况。状态为 Inactive 的物化视图无法用于查询加速或改写。更改基表后，您可以使用此 SQL 将该物化视图的状态设置为 Active。 |
+| INACTIVE                | 否       | 将物化视图的状态设置为 Inactive。Inactive 状态的物化视图无法被刷新，但您仍然可以将其作为表直接查询。 |
+| SWAP WITH               | 否       | 同另一物化视图进行原子替换。替换前，StarRocks 会进行必要的一致性检查。|
+| key                     | 否       | 待变更的属性的名称，详细信息请见 [SQL 参考 - CREATE MATERIALIZED VIEW - 参数](CREATE_MATERIALIZED_VIEW.md#参数)。<br />**说明**<br />如需更改物化视图的 Session 变量属性，则必须为 Session 属性添加 `session.` 前缀，例如，`session.query_timeout`。您无需为非 Session 属性指定前缀，例如，`mv_rewrite_staleness_second`。 |
+| value                   | 否       | 待变更的属性的值。                                             |
+
+## 示例
+
+示例一：修改物化视图名称
+
+```SQL
+ALTER MATERIALIZED VIEW lo_mv1 RENAME lo_mv1_new_name;
+```
+
+示例二：修改物化视图刷新间隔
+
+```SQL
+ALTER MATERIALIZED VIEW lo_mv2 REFRESH ASYNC EVERY(INTERVAL 1 DAY);
+```
+
+示例三：修改物化视图属性，调整物化视图刷新 Timeout 为一小时（默认）。
+
+```SQL
+ALTER MATERIALIZED VIEW mv1 SET ("session.query_timeout" = "3600");
+```
+
+示例四：修改物化视图状态为 Active。
+
+```SQL
+ALTER MATERIALIZED VIEW order_mv ACTIVE;
+```
+
+示例五：原子替换物化视图 `order_mv` 和 `order_mv1`。
+
+```SQL
+ALTER MATERIALIZED VIEW order_mv SWAP WITH order_mv1;
+```
+
+示例六：为物化视图刷新开启 Profile（默认开启）。
+
+```SQL
+ALTER MATERIALIZED VIEW mv1 SET ("session.enable_profile" = "true");
+```
+
+示例七：为物化视图刷新开启中间结果落盘（自 v3.1 起默认开启），并设置落盘模式为 `force`。
+
+```SQL
+-- 为物化视图刷新开启中间结果落盘。
+ALTER MATERIALIZED VIEW mv1 SET ("session.enable_spill" = "true");
+-- 设置落盘模式为 `force`。
+ALTER MATERIALIZED VIEW mv1 SET ("session.spill_mode" = "force");
+```
+
+示例八：调整 Optimizer Timeout 为 30 秒（自 v3.3 起为默认值），适用于物化视图查询包含外表或多个 Join。
+
+```SQL
+ALTER MATERIALIZED VIEW mv1 SET ("session.new_planner_optimize_timeout" = "30000");
+```
+
+示例九：调整物化视图查询改写 Staleness 时间为 600 秒。
+
+```SQL
+ALTER MATERIALIZED VIEW mv1 SET ("mv_rewrite_staleness_second" = "600");
+```
diff --git a/docs/zh/sql-reference/sql-statements/materialized_view/CANCEL_REFRESH_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/materialized_view/CANCEL_REFRESH_MATERIALIZED_VIEW.md
new file mode 100644
index 00000000000000..d94d32ec3dacd4
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/materialized_view/CANCEL_REFRESH_MATERIALIZED_VIEW.md
@@ -0,0 +1,38 @@
+---
+displayed_sidebar: docs
+---
+
+# CANCEL REFRESH MATERIALIZED VIEW
+
+## 功能
+
+取消异步物化视图的刷新任务。
+
+:::tip
+
+该操作需要对应物化视图的 REFRESH 权限。
+
+:::
+
+## 语法
+
+```SQL
+CANCEL REFRESH MATERIALIZED VIEW [database_name.]materialized_view_name [FORCE]
+```
+
+## 参数说明
+
+| **参数**               | **必选** | **说明**                                                     |
+| ---------------------- | -------- | ------------------------------------------------------------ |
+| database_name          | 否       | 待取消刷新的物化视图所属数据库名称。如果不指定该参数，则默认使用当前数据库。 |
+| materialized_view_name | 是       | 待取消刷新的物化视图名称。                                   |
+| FORCE                  | 否       | 强制取消物化视图刷新任务。                                   |
+
+## 示例
+
+示例一：取消异步物化视图 `lo_mv1` 的刷新任务。
+
+```SQL
+CANCEL REFRESH MATERIALIZED VIEW lo_mv1;
+CANCEL REFRESH MATERIALIZED VIEW lo_mv1 FORCE;
+```
diff --git a/docs/zh/sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md
new file mode 100644
index 00000000000000..c7b8e1e782bd93
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md
@@ -0,0 +1,859 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE MATERIALIZED VIEW
+
+## 功能
+
+创建物化视图。关于物化视图适用的场景请参考[同步物化视图](../../../using_starrocks/Materialized_view-single_table.md)和[异步物化视图](../../../using_starrocks/Materialized_view.md)。
+
+创建物化视图是一个异步的操作。该命令执行成功即代表创建物化视图的任务提交成功。您可以通过 [SHOW ALTER MATERIALIZED VIEW](SHOW_ALTER_MATERIALIZED_VIEW.md) 命令查看当前数据库中同步物化视图的构建状态，或通过查询 [Information Schema](../../information_schema/information_schema.md) 中的 [`tasks`](../../information_schema/tasks.md) 和 [`task_runs`](../../information_schema/task_runs.md) 来查看异步物化视图的构建状态。
+
+> **注意**
+>
+> 只有拥有基表所在数据库的 CREATE MATERIALIZED VIEW 权限的用户才可以创建物化视图。
+
+StarRocks 自 v2.4 起支持异步物化视图。异步物化视图与先前版本中的同步物化视图区别主要体现在以下方面：
+
+|                              | **单表聚合** | **多表关联** | **查询改写** | **刷新策略** | **基表** |
+| ---------------------------- | ----------- | ---------- | ----------- | ---------- | -------- |
+| **异步物化视图** | 是 | 是 | 是 | <ul><li>异步刷新</li><li>手动刷新</li></ul> | 支持多表构建。基表可以来自：<ul><li>Default Catalog</li><li>External Catalog（v2.5）</li><li>已有异步物化视图（v2.5）</li><li>已有视图（v3.1）</li></ul> |
+| **同步物化视图（Rollup）** | 仅部分聚合函数 | 否 | 是 | 导入同步刷新 | 仅支持基于 Default Catalog 的单表构建 |
+
+## 同步物化视图
+
+### 语法
+
+```SQL
+CREATE MATERIALIZED VIEW [IF NOT EXISTS] [database.]<mv_name>
+[COMMENT ""]
+[PROPERTIES ("key"="value", ...)]
+AS 
+<query_statement>
+```
+
+### 参数
+
+**mv_name**（必填）
+
+物化视图的名称。命名要求如下：
+
+- 必须由字母（a-z 或 A-Z）、数字（0-9）或下划线（_）组成，且只能以字母开头。
+- 总长度不能超过 64 个字符。
+- 视图名大小写敏感。
+
+**COMMENT**（选填）
+
+物化视图的注释。注意建立物化视图时 `COMMENT` 必须在 `mv_name` 之后，否则创建失败。
+
+**query_statement**（必填）
+
+创建物化视图的查询语句，其结果即为物化视图中的数据。语法如下：
+
+```SQL
+SELECT select_expr[, select_expr ...]
+[WHERE where_expr]
+[GROUP BY column_name[, column_name ...]]
+[ORDER BY column_name[, column_name ...]]
+```
+
+- select_expr（必填）
+
+  构建同步物化视图的查询语句。
+
+  - 单列或聚合列：形如 `SELECT a, b, c FROM table_a`，其中 `a`、`b` 和 `c` 为基表的列名。如果您没有为物化视图指定列名，那么 StarRocks 自动为这些列命名。
+  - 表达式：形如 `SELECT a+1 AS x, b+2 AS y, c*c AS z FROM table_a`，其中 `a+1`、`b+2` 和 `c*c` 为包含基表列名的表达式，`x`、`y` 和 `z` 为物化视图的列名。
+
+  > **说明**
+  >
+  > - 该参数至少需包含一个单列。
+  > - 使用聚合函数创建同步物化视图时，必须指定 GROUP BY 子句，并在 `select_expr` 中指定至少一个 GROUP BY 列。
+  > - 同步物化视图不支持 JOIN、以及 GROUP BY 的 HAVING 子句。
+  > - 从 v3.1 开始，每个同步物化视图支持为基表的每一列使用多个聚合函数，支持形如 `select b, sum(a), min(a) from table group by b` 形式的查询语句。
+  > - 从 v3.1 开始，同步物化视图支持 SELECT 和聚合函数的复杂表达式，即形如 `select b, sum(a + 1) as sum_a1, min(cast (a as bigint)) as min_a from table group by b` 或 `select abs(b) as col1, a + 1 as col2, cast(a as bigint) as col3 from table` 的查询语句。同步物化视图的复杂表达式有以下限制：
+  >   - 每个复杂表达式必须有一个列名，并且基表所有同步物化视图中的不同复杂表达式的别名必须不同。例如，查询语句 `select b, sum(a + 1) as sum_a from table group by b` 和`select b, sum(a) as sum_a from table group by b` 不能同时用于为相同的基表创建同步物化视图，你可以为同一复杂表达式设置多个不同别名。
+  >   - 您可以通过执行 `EXPLAIN <sql_statement>` 来查看您的查询是否被使用复杂表达式创建的同步物化视图改写。更多信息请参见[查询分析](../../../administration/Query_planning.md)。
+
+- WHERE （选填）
+
+  自 v3.1.8 起，同步物化视图支持通过 WHERE 子句筛选数据。
+
+- GROUP BY（选填）
+
+  构建物化视图查询语句的分组列。如不指定该参数，则默认不对数据进行分组。
+
+- ORDER BY（选填）
+
+  构建物化视图查询语句的排序列。
+
+  - 排序列的声明顺序必须和 `select_expr` 中列声明顺序一致。
+  - 如果查询语句中包含分组列，则排序列必须和分组列一致。
+  - 如果不指定排序列，则系统根据以下规则自动补充排序列：
+  
+    - 如果物化视图是聚合类型，则所有的分组列自动补充为排序列。
+    - 如果物化视图是非聚合类型，则系统根据前缀列自动选择排序列。
+
+### 查询同步物化视图
+
+因为同步物化视图本质上是基表的索引而不是物理表，所以您只能使用 Hint `[_SYNC_MV_]` 查询同步物化视图：
+
+```SQL
+-- 请勿省略 Hint 中的括号[]。
+SELECT * FROM <mv_name> [_SYNC_MV_];
+```
+
+> **注意**
+>
+> 目前，StarRocks 会自动为同步物化视图中的列生成名称。您为同步物化视图中的列指定的 Alias 将无法生效。
+
+### 同步物化视图查询自动改写
+
+使用同步物化视图查询时，原始查询语句将会被自动改写并用于查询物化视图中保存的中间结果。
+
+下表展示了原始查询聚合函数和构建同步物化视图用到的聚合函数的匹配关系。您可以根据业务场景选择对应的聚合函数构建同步物化视图。
+
+| **原始查询聚合函数**                                   | **物化视图构建聚合函数** |
+| ------------------------------------------------------ | ------------------------ |
+| sum                                                    | sum                      |
+| min                                                    | min                      |
+| max                                                    | max                      |
+| count                                                  | count                    |
+| bitmap_union, bitmap_union_count, count(distinct)      | bitmap_union             |
+| hll_raw_agg, hll_union_agg, ndv, approx_count_distinct | hll_union                |
+
+## 异步物化视图
+
+### 语法
+
+```SQL
+CREATE MATERIALIZED VIEW [IF NOT EXISTS] [database.]<mv_name>
+[COMMENT ""]
+-- 必须至少指定 `distribution_desc` 和 `refresh_scheme` 其中之一。
+-- distribution_desc
+[DISTRIBUTED BY HASH(<bucket_key>[,<bucket_key2> ...]) [BUCKETS <bucket_number>]]
+-- refresh_desc
+[REFRESH 
+-- refresh_moment
+    [IMMEDIATE | DEFERRED]
+-- refresh_scheme
+    [ASYNC | ASYNC [START (<start_time>)] EVERY (INTERVAL <refresh_interval>) | MANUAL]
+]
+-- partition_expression
+[PARTITION BY 
+    {<date_column> | date_trunc(fmt, <date_column>)}
+]
+-- order_by_expression
+[ORDER BY (<sort_key>)]
+[PROPERTIES ("key"="value", ...)]
+AS 
+<query_statement>
+```
+
+### 参数
+
+**mv_name**（必填）
+
+物化视图的名称。命名要求如下：
+
+- 必须由字母（a-z 或 A-Z）、数字（0-9）或下划线（_）组成，且只能以字母开头。
+- 总长度不能超过 64 个字符。
+- 视图名大小写敏感。
+
+> **注意**
+>
+> 同一张基表可以创建多个异步物化视图，但同一数据库内的异步物化视图名称不可重复。
+
+**COMMENT**（选填）
+
+物化视图的注释。注意建立物化视图时 `COMMENT` 必须在 `mv_name` 之后，否则创建失败。
+
+**distribution_desc**（选填）
+
+异步物化视图的分桶方式，包括哈希分桶和随机分桶（自 3.1 版本起）。如不指定该参数，StarRocks 使用随机分桶方式，并自动设置分桶数量。
+
+> **说明**
+>
+> 创建异步物化视图时必须至少指定 `distribution_desc` 和 `refresh_scheme` 其中之一。
+
+- **哈希分桶**：
+
+  语法
+
+  ```SQL
+  DISTRIBUTED BY HASH (<bucket_key1>[,<bucket_key2> ...]) [BUCKETS <bucket_number>]
+  ```
+
+  更多信息，请参见 [分桶](../../../table_design/Data_distribution.md#分桶)。
+
+  > **说明**
+  >
+  > 自 2.5.7 版本起，StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS)，您无需手动设置分桶数量。更多信息，请参见 [设置分桶数量](../../../table_design/Data_distribution.md#设置分桶数量)。
+
+- **随机分桶**：
+
+  如果您选择随机分桶方式，并且自动设置分桶数量，则无需指定 `distribution_desc`。如果您需要手动设置分桶数，请使用以下语法：
+
+  ```SQL
+  DISTRIBUTED BY RANDOM BUCKETS <bucket_number>
+  ```
+
+  > **注意**
+  >
+  > 采用随机分桶方式的异步物化视图不支持设置 Colocation Group。
+
+  更多信息，请参见 [随机分桶](../../../table_design/Data_distribution.md#随机分桶自-v31)。
+
+**refresh_moment**（选填）
+
+物化视图的刷新时刻。默认值：`IMMEDIATE`。有效值：
+
+- `IMMEDIATE`：异步物化视图创建成功后立即刷新。
+- `DEFERRED`：异步物化视图创建成功后不进行刷新。您可以通过手动调用或创建定时任务触发刷新。
+
+**refresh_scheme**（选填）
+
+> **说明**
+>
+> 创建异步物化视图时必须至少指定 `distribution_desc` 和 `refresh_scheme` 其中之一。
+
+物化视图的刷新方式。该参数支持如下值：
+
+- `ASYNC`: 自动刷新模式。每当基表数据发生变化时，物化视图会自动刷新。
+- `ASYNC [START (<start_time>)] EVERY(INTERVAL <interval>)`: 定时刷新模式。物化视图将按照定义的间隔定时刷新。您可以使用 `DAY`（天）、`HOUR`（小时）、`MINUTE`（分钟）和 `SECOND`（秒）作为单位指定间隔，格式为 `EVERY (interval n day/hour/minute/second)`。默认值为 `10 MINUTE`（10 分钟）。您还可以进一步指定刷新起始时间，格式为 `START('yyyy-MM-dd hh:mm:ss')`。如未指定起始时间，默认使用当前时间。示例：`ASYNC START ('2023-09-12 16:30:25') EVERY (INTERVAL 5 MINUTE)`。
+- `MANUAL`: 手动刷新模式。除非手动触发刷新任务，否则物化视图不会刷新。
+
+如果不指定该参数，则默认使用 MANUAL 方式。
+
+**partition_expression**（选填）
+
+异步物化视图的分区表达式。目前仅支持在创建异步物化视图时使用一个分区表达式。
+
+> **注意**
+>
+> 异步物化视图暂不支持使用 List 分区策略。
+
+该参数支持如下值：
+
+- `date_column`：用于分区的列的名称。形如 `PARTITION BY dt`，表示按照 `dt` 列进行分区。
+- `date_trunc` 函数：形如 `PARTITION BY date_trunc("MONTH", dt)`，表示将 `dt` 列截断至以月为单位进行分区。date_trunc 函数支持截断的单位包括 `YEAR`、`MONTH`、`DAY`、`HOUR` 以及 `MINUTE`。
+- `str2date` 函数：用于将基表的 STRING 类型分区键转化为物化视图的分区键所需的日期类型。`PARTITION BY str2date(dt, "%Y%m%d")` 表示 `dt` 列是一个 STRING 类型日期，其日期格式为 `"%Y%m%d"`。`str2date` 函数支持多种日期格式。更多信息，参考[str2date](../../sql-functions/date-time-functions/str2date.md)。自 v3.1.4 起支持。
+- `time_slice` 函数：从 v3.1 开始，您可以进一步使用 time_slice 函数根据指定的时间粒度周期，将给定的时间转化到其所在的时间粒度周期的起始或结束时刻，例如 `PARTITION BY date_trunc("MONTH", time_slice(dt, INTERVAL 7 DAY))`，其中 time_slice 的时间粒度必须比 `date_trunc` 的时间粒度更细。你可以使用它们来指定一个比分区键更细时间粒度的 GROUP BY 列，例如，`GROUP BY time_slice(dt, INTERVAL 1 MINUTE) PARTITION BY date_trunc('DAY', ts)`。
+
+如不指定该参数，则默认物化视图为无分区。
+
+**order_by_expression**（选填）
+
+异步物化视图的排序键。如不指定该参数，StarRocks 从 SELECT 列中选择部分前缀作为排序键，例如：`select a, b, c, d` 中, 排序列可能为 `a` 和 `b`。此参数自 StarRocks 3.0 起支持。
+
+**PROPERTIES**（选填）
+
+异步物化视图的属性。您可以使用 [ALTER MATERIALIZED VIEW](ALTER_MATERIALIZED_VIEW.md) 修改已有异步物化视图的属性。
+
+- `session.`: 如果您想要更改与物化视图相关的 Session 变量属性，必须在属性前添加 `session.` 前缀，例如，`session.query_timeout`。对于非 Session 属性，例如，`mv_rewrite_staleness_second`，则无需指定前缀。
+- `replication_num`：创建物化视图副本数量。
+- `storage_medium`：存储介质类型。有效值：`HDD` 和 `SSD`。
+- `storage_cooldown_time`: 当设置存储介质为 SSD 时，指定该分区在该时间点之后从 SSD 降冷到 HDD，设置的时间必须大于当前时间。如不指定该属性，默认不进行自动降冷。取值格式为："yyyy-MM-dd HH:mm:ss"。
+- `partition_ttl`: 物化视图分区的生存时间 (TTL)。数据在指定的时间范围内的分区将被保留，过期的分区将被自动删除。单位：`YEAR`、`MONTH`、`DAY`、`HOUR` 和 `MINUTE`。例如，您可以将此属性设置为 `2 MONTH`（2个月）。建议您使用此属性，不推荐使用 `partition_ttl_number`。该属性自 v3.1.5 起支持。
+- `partition_ttl_number`：需要保留的最近的物化视图分区数量。对于分区开始时间小于当前时间的分区，当数量超过该值之后，多余的分区将会被删除。StarRocks 将根据 FE 配置项 `dynamic_partition_check_interval_seconds` 中的时间间隔定期检查物化视图分区，并自动删除过期分区。在[动态分区](../../../table_design/dynamic_partitioning.md)场景下，提前创建的未来分区将不会被纳入 TTL 考虑。默认值：`-1`。当值为 `-1` 时，将保留物化视图所有分区。
+- `partition_refresh_number`：单次刷新中，最多刷新的分区数量。如果需要刷新的分区数量超过该值，StarRocks 将拆分这次刷新任务，并分批完成。仅当前一批分区刷新成功时，StarRocks 会继续刷新下一批分区，直至所有分区刷新完成。如果其中有分区刷新失败，将不会产生后续的刷新任务。当值为 `-1` 时，将不会拆分刷新任务。自 v3.3 起，默认值由 `-1` 变为 `1`，表示 StarRocks 每次只刷新一个分区。
+- `excluded_trigger_tables`：在此项属性中列出的基表，其数据产生变化时不会触发对应物化视图自动刷新。该参数仅针对导入触发式刷新，通常需要与属性 `auto_refresh_partitions_limit` 搭配使用。形式：`[db_name.]table_name`。默认值为空字符串。当值为空字符串时，任意的基表数据变化都将触发对应物化视图刷新。
+- `auto_refresh_partitions_limit`：当触发物化视图刷新时，需要刷新的最近的物化视图分区数量。您可以通过该属性限制刷新的范围，降低刷新代价，但因为仅有部分分区刷新，有可能导致物化视图数据与基表无法保持一致。默认值：`-1`。当参数值为 `-1` 时，StarRocks 将刷新所有分区。当参数值为正整数 N 时，StarRocks 会将已存在的分区按时间先后排序，并刷新当前分区和 N-1 个历史分区。如果分区数不足 N，则刷新所有已存在的分区。如果物化视图存在提前创建的未来分区，将会刷新所有提前创建的分区。
+- `mv_rewrite_staleness_second`：如果当前物化视图的上一次刷新在此属性指定的时间间隔内，则此物化视图可直接用于查询改写，无论基表数据是否更新。如果上一次刷新时间早于此属性指定的时间间隔，StarRocks 通过检查基表数据是否变更决定该物化视图能否用于查询改写。单位：秒。该属性自 v3.0 起支持。
+- `colocate_with`：异步物化视图的 Colocation Group。更多信息请参阅 [Colocate Join](../../../using_starrocks/Colocate_join.md)。该属性自 v3.0 起支持。
+- `unique_constraints` 和 `foreign_key_constraints`：创建 View Delta Join 查询改写的异步物化视图时的 Unique Key 约束和外键约束。更多信息请参阅 [异步物化视图 - 基于 View Delta Join 场景改写查询](../../../using_starrocks/query_rewrite_with_materialized_views.md#view-delta-join-改写)。该属性自 v3.0 起支持。
+
+  > **注意**
+  >
+  > Unique Key 约束和外键约束仅用于查询改写。导入数据时，不保证进行外键约束校验。您必须确保导入的数据满足约束条件。
+
+- `resource_group`: 为物化视图刷新任务设置资源组。默认值为 `default_mv_wg`，即一个系统定义的，专门用于物化视图刷新的资源组。该资源组的 `cpu_core_limit` 为 `1`，`mem_limit` 为 `0.8`。更多关于资源组信息，请参考[资源隔离](../../../administration/management/resource_management/resource_group.md)。
+- `query_rewrite_consistency`: 指定当前异步物化视图的查询改写规则。该属性自 v3.2 起支持。有效值：
+  - `disable`：禁用基于该异步物化视图进行自动查询改写。
+  - `checked`（默认值）：仅在物化视图满足时效性要求时启用自动查询改写，即：
+    - 如果未指定 `mv_rewrite_staleness_second`，则只有当物化视图的数据与所有基表中的数据一致时，才可以将其用于查询改写。
+    - 如果指定了 `mv_rewrite_staleness_second`，则只有在其最后刷新在 staleness 时间间隔内时，才可以将物化视图用于查询改写。
+  - `loose`：直接启用自动查询改写，无需进行一致性检查。
+- `storage_volume`：[如果您使用存算分离集群](../../../deployment/shared_data/shared_data.mdx)，则需要指定创建物化视图的 Storage Volume 名称。该属性自 v3.1 版本起支持。如果未指定该属性，则使用默认 Storage Volume。示例：`"storage_volume" = "def_volume"`。
+- `force_external_table_query_rewrite`: 是否启用基于 External Catalog 的物化视图的查询改写。该属性自 v3.2 起支持。有效值：
+  - `true`（自 v3.3 变为默认值）：启用基于 External Catalog 的物化视图的查询改写。
+  - `false`：禁用基于 External Catalog 的物化视图的查询改写。
+
+  由于无法保证基表和基于 External Catalog 的物化视图之间的数据强一致，因此默认情况下禁用此功能。启用此功能时，物化视图将根据 `query_rewrite_consistency` 中指定的规则改写查询。
+- `enable_query_rewrite`：是否使用物化视图进行查询改写。当存在大量物化视图时，基于物化视图的查询改写可能会影响优化器的耗时。通过此属性，您可以控制是否允许使用物化视图进行查询改写。该功能自 v3.3.0 起支持。有效值：
+  - `default`（默认）：系统将不会针对物化视图执行语义检查，但只有 SPJG 类型的物化视图可以用于查询改写。请注意，如果启用了基于文本的查询改写，非 SPJG 类型的物化视图也可以用于查询改写。
+  - `true`：系统将在创建或修改物化视图时执行语义检查。如果物化视图不符合查询改写的条件（即，物化视图的定义不是 SPJG 类型的查询），则会返回失败信息。
+  - `false`：物化视图将不会用于查询改写。
+- [Preview] `transparent_mv_rewrite_mode`：为 **直接针对物化视图的查询** 指定透明改写模式。此功能从 v3.3.0 版本开始支持。有效值如下：
+  - `false`（默认，与早期版本行为兼容）：直接针对物化视图的查询不会被改写，仅返回物化视图中现有的数据。根据物化视图的刷新状态（数据一致性），其结果可能与直接执行物化视图定义查询的结果不同。
+  - `true`：直接针对物化视图的查询将被改写，并返回最新数据，结果与物化视图定义查询的一致。请注意，当物化视图处于失效（Inactive）状态或不支持透明查询改写时，这些查询将路由至物化视图定义查询执行。
+  - `transparent_or_error`：直接针对物化视图的查询将在符合条件时可以被改写。如果物化视图处于失效（Inactive）状态或不支持透明查询改写，将返回错误。
+  - `transparent_or_default`：直接针对物化视图的查询将在符合条件时可以被改写。如果物化视图处于失效（Inactive）状态或不支持透明查询改写，将返回物化视图中现有的数据。
+
+**query_statement**（必填）
+
+创建异步物化视图的查询语句，其结果即为异步物化视图中的数据。从 v3.1.6 版本开始，StarRocks 支持使用 Common Table Expression (CTE) 创建异步物化视图。
+
+> **注意**
+>
+> 异步物化视图暂不支持基于使用 List 分区的基表创建。
+
+### 查询异步物化视图
+
+异步物化视图本质是一张实体表。您可以将其作为普通表进行任何**除直接导入数据**以外的操作。
+
+### 支持数据类型
+
+- 基于 StarRocks 内部数据目录（Default Catalog）创建的异步物化视图支持以下数据类型：
+
+  - **日期类型**：DATE、DATETIME
+  - **字符串类型**：CHAR、VARCHAR
+  - **数值类型**：BOOLEAN、TINYINT、SMALLINT、INT、BIGINT、LARGEINT、FLOAT、DOUBLE、DECIMAL、PERCENTILE
+  - **半结构化类型**：ARRAY、JSON、MAP（自 v3.1 起）、STRUCT（自 v3.1 起）
+  - **其他类型**：BITMAP、HLL
+
+> **说明**
+>
+> 自 v2.4.5 起支持 BITMAP、HLL 以及 PERCENTILE。
+
+- 基于 StarRocks 外部数据目录（External Catalog）创建的异步物化视图支持以下数据类型：
+
+  - Hive Catalog
+
+    - **数值类型**：INT/INTEGER、BIGINT、DOUBLE、FLOAT、DECIMAL
+    - **日期类型**：TIMESTAMP
+    - **字符串类型**：STRING、VARCHAR、CHAR
+    - **半结构化类型**：ARRAY
+
+  - Hudi Catalog
+
+    - **数值类型**：BOOLEAN、INT、LONG、FLOAT、DOUBLE、DECIMAL
+    - **日期类型**：DATE、TimeMillis/TimeMicros、TimestampMillis/TimestampMicros
+    - **字符串类型**：STRING
+    - **半结构化类型**：ARRAY
+
+  - Iceberg Catalog
+
+    - **数值类型**：BOOLEAN、INT、LONG、FLOAT、DOUBLE、DECIMAL(P, S)
+    - **日期类型**：DATE、TIME、TIMESTAMP
+    - **字符串类型**：STRING、UUID、FIXED(L)、BINARY
+    - **半结构化类型**：LIST
+
+## 注意事项
+
+- 当前版本暂时不支持同时创建多个物化视图。仅当当前创建任务完成时，方可执行下一个创建任务。
+
+- 关于同步物化视图：
+
+  - 同步物化视图仅支持单列聚合函数，不支持形如 `sum(a+b)` 的查询语句。
+  - 同步物化视图仅支持对同一列数据使用一种聚合函数，不支持形如 `select sum(a), min(a) from table` 的查询语句。
+  - 同步物化视图中使用聚合函数需要与 GROUP BY 语句一起使用，且 SELECT 的列中至少包含一个分组列。
+  - 同步物化视图创建语句不支持 JOIN 以及 GROUP BY 的 HAVING 子句。
+  - 使用 ALTER TABLE DROP COLUMN 删除基表中特定列时，需要保证该基表所有同步物化视图中不包含被删除列，否则无法进行删除操作。如果必须删除该列，则需要将所有包含该列的同步物化视图删除，然后进行删除列操作。
+  - 为一张表创建过多的同步物化视图会影响导入的效率。导入数据时，同步物化视图和基表数据将同步更新，如果一张基表包含 n 个物化视图，向基表导入数据时，其导入效率大约等同于导入 n 张表，数据导入的速度会变慢。
+
+- 关于嵌套异步物化视图：
+
+  - 每个异步物化视图的刷新方式仅影响当前物化视图。
+  - 当前 StarRocks 不对嵌套层数进行限制。生产环境中建议嵌套层数不超过三层。
+
+- 关于外部数据目录异步物化视图：
+
+  - 外部数据目录物化视图仅支持异步定时刷新和手动刷新。
+  - 物化视图中的数据不保证与外部数据目录的数据强一致。
+  - 目前暂不支持基于资源（Resource）构建物化视图。
+  - StarRocks 目前无法感知外部数据目录基表数据是否发生变动，所以每次刷新会默认刷新所有分区。您可以通过手动刷新方式指定刷新部分分区。
+
+## 示例
+
+### 同步物化视图示例
+
+基表结构为：
+
+```sql
+mysql> desc duplicate_table;
++-------+--------+------+------+---------+-------+
+| Field | Type   | Null | Key  | Default | Extra |
++-------+--------+------+------+---------+-------+
+| k1    | INT    | Yes  | true | N/A     |       |
+| k2    | INT    | Yes  | true | N/A     |       |
+| k3    | BIGINT | Yes  | true | N/A     |       |
+| k4    | BIGINT | Yes  | true | N/A     |       |
++-------+--------+------+------+---------+-------+
+```
+
+1. 创建一个仅包含原始表 （k1，k2）列的物化视图。
+
+    ```sql
+    create materialized view k1_k2 as
+    select k1, k2 from duplicate_table;
+    ```
+
+    物化视图的 schema 如下图，物化视图仅包含两列 k1、k2 且不带任何聚合。
+
+    ```sql
+    +-----------------+-------+--------+------+------+---------+-------+
+    | IndexName       | Field | Type   | Null | Key  | Default | Extra |
+    +-----------------+-------+--------+------+------+---------+-------+
+    | k1_k2           | k1    | INT    | Yes  | true | N/A     |       |
+    |                 | k2    | INT    | Yes  | true | N/A     |       |
+    +-----------------+-------+--------+------+------+---------+-------+
+    ```
+
+2. 创建一个以 k2 为排序列的物化视图。
+
+    ```sql
+    create materialized view k2_order as
+    select k2, k1 from duplicate_table order by k2;
+    ```
+
+    物化视图的 schema 如下图，物化视图仅包含两列 k2、k1，其中 k2 列为排序列，不带任何聚合。
+
+    ```sql
+    +-----------------+-------+--------+------+-------+---------+-------+
+    | IndexName       | Field | Type   | Null | Key   | Default | Extra |
+    +-----------------+-------+--------+------+-------+---------+-------+
+    | k2_order        | k2    | INT    | Yes  | true  | N/A     |       |
+    |                 | k1    | INT    | Yes  | false | N/A     | NONE  |
+    +-----------------+-------+--------+------+-------+---------+-------+
+    ```
+
+3. 创建一个以 k1，k2 分组，k3 列为 SUM 聚合的物化视图。
+
+    ```sql
+    create materialized view k1_k2_sumk3 as
+    select k1, k2, sum(k3) from duplicate_table group by k1, k2;
+    ```
+
+    物化视图的 schema 如下图，物化视图包含两列 k1、k2，sum(k3) 其中 k1、k2 为分组列，sum(k3) 为根据 k1、k2 分组后的 k3 列的求和值。
+
+    由于物化视图没有声明排序列，且物化视图带聚合数据，系统默认补充分组列 k1、k2 为排序列。
+
+    ```sql
+    +-----------------+-------+--------+------+-------+---------+-------+
+    | IndexName       | Field | Type   | Null | Key   | Default | Extra |
+    +-----------------+-------+--------+------+-------+---------+-------+
+    | k1_k2_sumk3     | k1    | INT    | Yes  | true  | N/A     |       |
+    |                 | k2    | INT    | Yes  | true  | N/A     |       |
+    |                 | k3    | BIGINT | Yes  | false | N/A     | SUM   |
+    +-----------------+-------+--------+------+-------+---------+-------+
+    ```
+
+4. 创建一个去除重复行的物化视图。
+
+    ```sql
+    create materialized view deduplicate as
+    select k1, k2, k3, k4 from duplicate_table group by k1, k2, k3, k4;
+    ```
+
+    物化视图 schema 如下图，物化视图包含 k1、k2、k3、k4 列，且不存在重复行。
+
+    ```sql
+    +-----------------+-------+--------+------+-------+---------+-------+
+    | IndexName       | Field | Type   | Null | Key   | Default | Extra |
+    +-----------------+-------+--------+------+-------+---------+-------+
+    | deduplicate     | k1    | INT    | Yes  | true  | N/A     |       |
+    |                 | k2    | INT    | Yes  | true  | N/A     |       |
+    |                 | k3    | BIGINT | Yes  | true  | N/A     |       |
+    |                 | k4    | BIGINT | Yes  | true  | N/A     |       |
+    +-----------------+-------+--------+------+-------+---------+-------+
+
+    ```
+
+5. 创建一个不声明排序列的非聚合型物化视图。
+
+    all_type_table 的 schema 如下：
+
+    ```sql
+    +-------+--------------+------+-------+---------+-------+
+    | Field | Type         | Null | Key   | Default | Extra |
+    +-------+--------------+------+-------+---------+-------+
+    | k1    | TINYINT      | Yes  | true  | N/A     |       |
+    | k2    | SMALLINT     | Yes  | true  | N/A     |       |
+    | k3    | INT          | Yes  | true  | N/A     |       |
+    | k4    | BIGINT       | Yes  | true  | N/A     |       |
+    | k5    | DECIMAL(9,0) | Yes  | true  | N/A     |       |
+    | k6    | DOUBLE       | Yes  | false | N/A     | NONE  |
+    | k7    | VARCHAR(20)  | Yes  | false | N/A     | NONE  |
+    +-------+--------------+------+-------+---------+-------+
+    ```
+
+    物化视图包含 k3、k4、k5、k6、k7 列，且不声明排序列，则创建语句如下：
+
+    ```sql
+    create materialized view mv_1 as
+    select k3, k4, k5, k6, k7 from all_type_table;
+    ```
+
+    系统默认补充的排序列为 k3、k4、k5 三列。这三列类型的字节数之和为 4(INT) + 8(BIGINT) + 16(DECIMAL) = 28 < 36。所以补充的是这三列作为排序列。
+    物化视图的 schema 如下，可以看到其中 k3、k4、k5 列的 key 字段为 true，也就是排序列。k6、k7 列的 key 字段为 false，也就是非排序列。
+
+    ```sql
+    +----------------+-------+--------------+------+-------+---------+-------+
+    | IndexName      | Field | Type         | Null | Key   | Default | Extra |
+    +----------------+-------+--------------+------+-------+---------+-------+
+    | mv_1           | k3    | INT          | Yes  | true  | N/A     |       |
+    |                | k4    | BIGINT       | Yes  | true  | N/A     |       |
+    |                | k5    | DECIMAL(9,0) | Yes  | true  | N/A     |       |
+    |                | k6    | DOUBLE       | Yes  | false | N/A     | NONE  |
+    |                | k7    | VARCHAR(20)  | Yes  | false | N/A     | NONE  |
+    +----------------+-------+--------------+------+-------+---------+-------+
+    ```
+
+6. 使用 WHERE 子句和复杂表达式创建同步物化视图。
+
+  ```sql
+  -- 创建基表 user_event
+  CREATE TABLE user_event (
+      ds date   NOT NULL,
+      id  varchar(256)    NOT NULL,
+      user_id int DEFAULT NULL,
+      user_id1    varchar(256)    DEFAULT NULL,
+      user_id2    varchar(256)    DEFAULT NULL,
+      column_01   int DEFAULT NULL,
+      column_02   int DEFAULT NULL,
+      column_03   int DEFAULT NULL,
+      column_04   int DEFAULT NULL,
+      column_05   int DEFAULT NULL,
+      column_06   DECIMAL(12,2)   DEFAULT NULL,
+      column_07   DECIMAL(12,3)   DEFAULT NULL,
+      column_08   JSON   DEFAULT NULL,
+      column_09   DATETIME    DEFAULT NULL,
+      column_10   DATETIME    DEFAULT NULL,
+      column_11   DATE    DEFAULT NULL,
+      column_12   varchar(256)    DEFAULT NULL,
+      column_13   varchar(256)    DEFAULT NULL,
+      column_14   varchar(256)    DEFAULT NULL,
+      column_15   varchar(256)    DEFAULT NULL,
+      column_16   varchar(256)    DEFAULT NULL,
+      column_17   varchar(256)    DEFAULT NULL,
+      column_18   varchar(256)    DEFAULT NULL,
+      column_19   varchar(256)    DEFAULT NULL,
+      column_20   varchar(256)    DEFAULT NULL,
+      column_21   varchar(256)    DEFAULT NULL,
+      column_22   varchar(256)    DEFAULT NULL,
+      column_23   varchar(256)    DEFAULT NULL,
+      column_24   varchar(256)    DEFAULT NULL,
+      column_25   varchar(256)    DEFAULT NULL,
+      column_26   varchar(256)    DEFAULT NULL,
+      column_27   varchar(256)    DEFAULT NULL,
+      column_28   varchar(256)    DEFAULT NULL,
+      column_29   varchar(256)    DEFAULT NULL,
+      column_30   varchar(256)    DEFAULT NULL,
+      column_31   varchar(256)    DEFAULT NULL,
+      column_32   varchar(256)    DEFAULT NULL,
+      column_33   varchar(256)    DEFAULT NULL,
+      column_34   varchar(256)    DEFAULT NULL,
+      column_35   varchar(256)    DEFAULT NULL,
+      column_36   varchar(256)    DEFAULT NULL,
+      column_37   varchar(256)    DEFAULT NULL
+  )
+  PARTITION BY date_trunc("day", ds)
+  DISTRIBUTED BY hash(id);
+  
+  -- 使用 WHERE 子句和复杂表达式创建同步物化视图
+  CREATE MATERIALIZED VIEW test_mv1
+  AS 
+  SELECT
+  ds,
+  column_19,
+  column_36,
+  sum(column_01) as column_01_sum,
+  bitmap_union(to_bitmap( user_id)) as user_id_dist_cnt,
+  bitmap_union(to_bitmap(case when column_01 > 1 and column_34 IN ('1','34')   then user_id2 else null end)) as filter_dist_cnt_1,
+  bitmap_union(to_bitmap( case when column_02 > 60 and column_35 IN ('11','13') then  user_id2 else null end)) as filter_dist_cnt_2,
+  bitmap_union(to_bitmap(case when column_03 > 70 and column_36 IN ('21','23') then  user_id2 else null end)) as filter_dist_cnt_3,
+  bitmap_union(to_bitmap(case when column_04 > 20 and column_27 IN ('31','27') then  user_id2 else null end)) as filter_dist_cnt_4,
+  bitmap_union(to_bitmap( case when column_05 > 90 and column_28 IN ('41','43') then  user_id2 else null end)) as filter_dist_cnt_5
+  FROM user_event
+  WHERE ds >= '2023-11-02'
+  GROUP BY
+  ds,
+  column_19,
+  column_36;
+  ```
+
+### 异步物化视图示例
+
+以下示例基于下列基表。
+
+```SQL
+CREATE TABLE `lineorder` (
+  `lo_orderkey` int(11) NOT NULL COMMENT "",
+  `lo_linenumber` int(11) NOT NULL COMMENT "",
+  `lo_custkey` int(11) NOT NULL COMMENT "",
+  `lo_partkey` int(11) NOT NULL COMMENT "",
+  `lo_suppkey` int(11) NOT NULL COMMENT "",
+  `lo_orderdate` int(11) NOT NULL COMMENT "",
+  `lo_orderpriority` varchar(16) NOT NULL COMMENT "",
+  `lo_shippriority` int(11) NOT NULL COMMENT "",
+  `lo_quantity` int(11) NOT NULL COMMENT "",
+  `lo_extendedprice` int(11) NOT NULL COMMENT "",
+  `lo_ordtotalprice` int(11) NOT NULL COMMENT "",
+  `lo_discount` int(11) NOT NULL COMMENT "",
+  `lo_revenue` int(11) NOT NULL COMMENT "",
+  `lo_supplycost` int(11) NOT NULL COMMENT "",
+  `lo_tax` int(11) NOT NULL COMMENT "",
+  `lo_commitdate` int(11) NOT NULL COMMENT "",
+  `lo_shipmode` varchar(11) NOT NULL COMMENT ""
+) ENGINE=OLAP
+DUPLICATE KEY(`lo_orderkey`)
+COMMENT "OLAP"
+PARTITION BY RANGE(`lo_orderdate`)
+(PARTITION p1 VALUES [("-2147483648"), ("19930101")),
+PARTITION p2 VALUES [("19930101"), ("19940101")),
+PARTITION p3 VALUES [("19940101"), ("19950101")),
+PARTITION p4 VALUES [("19950101"), ("19960101")),
+PARTITION p5 VALUES [("19960101"), ("19970101")),
+PARTITION p6 VALUES [("19970101"), ("19980101")),
+PARTITION p7 VALUES [("19980101"), ("19990101")))
+DISTRIBUTED BY HASH(`lo_orderkey`);
+
+CREATE TABLE IF NOT EXISTS `customer` (
+  `c_custkey` int(11) NOT NULL COMMENT "",
+  `c_name` varchar(26) NOT NULL COMMENT "",
+  `c_address` varchar(41) NOT NULL COMMENT "",
+  `c_city` varchar(11) NOT NULL COMMENT "",
+  `c_nation` varchar(16) NOT NULL COMMENT "",
+  `c_region` varchar(13) NOT NULL COMMENT "",
+  `c_phone` varchar(16) NOT NULL COMMENT "",
+  `c_mktsegment` varchar(11) NOT NULL COMMENT ""
+) ENGINE=OLAP
+DUPLICATE KEY(`c_custkey`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`c_custkey`);
+
+CREATE TABLE IF NOT EXISTS `dates` (
+  `d_datekey` int(11) NOT NULL COMMENT "",
+  `d_date` varchar(20) NOT NULL COMMENT "",
+  `d_dayofweek` varchar(10) NOT NULL COMMENT "",
+  `d_month` varchar(11) NOT NULL COMMENT "",
+  `d_year` int(11) NOT NULL COMMENT "",
+  `d_yearmonthnum` int(11) NOT NULL COMMENT "",
+  `d_yearmonth` varchar(9) NOT NULL COMMENT "",
+  `d_daynuminweek` int(11) NOT NULL COMMENT "",
+  `d_daynuminmonth` int(11) NOT NULL COMMENT "",
+  `d_daynuminyear` int(11) NOT NULL COMMENT "",
+  `d_monthnuminyear` int(11) NOT NULL COMMENT "",
+  `d_weeknuminyear` int(11) NOT NULL COMMENT "",
+  `d_sellingseason` varchar(14) NOT NULL COMMENT "",
+  `d_lastdayinweekfl` int(11) NOT NULL COMMENT "",
+  `d_lastdayinmonthfl` int(11) NOT NULL COMMENT "",
+  `d_holidayfl` int(11) NOT NULL COMMENT "",
+  `d_weekdayfl` int(11) NOT NULL COMMENT ""
+) ENGINE=OLAP
+DUPLICATE KEY(`d_datekey`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`d_datekey`);
+
+CREATE TABLE IF NOT EXISTS `supplier` (
+  `s_suppkey` int(11) NOT NULL COMMENT "",
+  `s_name` varchar(26) NOT NULL COMMENT "",
+  `s_address` varchar(26) NOT NULL COMMENT "",
+  `s_city` varchar(11) NOT NULL COMMENT "",
+  `s_nation` varchar(16) NOT NULL COMMENT "",
+  `s_region` varchar(13) NOT NULL COMMENT "",
+  `s_phone` varchar(16) NOT NULL COMMENT ""
+) ENGINE=OLAP
+DUPLICATE KEY(`s_suppkey`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`s_suppkey`);
+
+CREATE TABLE IF NOT EXISTS `part` (
+  `p_partkey` int(11) NOT NULL COMMENT "",
+  `p_name` varchar(23) NOT NULL COMMENT "",
+  `p_mfgr` varchar(7) NOT NULL COMMENT "",
+  `p_category` varchar(8) NOT NULL COMMENT "",
+  `p_brand` varchar(10) NOT NULL COMMENT "",
+  `p_color` varchar(12) NOT NULL COMMENT "",
+  `p_type` varchar(26) NOT NULL COMMENT "",
+  `p_size` int(11) NOT NULL COMMENT "",
+  `p_container` varchar(11) NOT NULL COMMENT ""
+) ENGINE=OLAP
+DUPLICATE KEY(`p_partkey`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`p_partkey`);
+
+create table orders ( 
+    dt date NOT NULL, 
+    order_id bigint NOT NULL, 
+    user_id int NOT NULL, 
+    merchant_id int NOT NULL, 
+    good_id int NOT NULL, 
+    good_name string NOT NULL, 
+    price int NOT NULL, 
+    cnt int NOT NULL, 
+    revenue int NOT NULL, 
+    state tinyint NOT NULL 
+) 
+PRIMARY KEY (dt, order_id) 
+PARTITION BY RANGE(`dt`) 
+( PARTITION p20210820 VALUES [('2021-08-20'), ('2021-08-21')), 
+PARTITION p20210821 VALUES [('2021-08-21'), ('2021-08-22')) ) 
+DISTRIBUTED BY HASH(order_id)
+PROPERTIES (
+    "replication_num" = "3", 
+    "enable_persistent_index" = "true"
+);
+```
+
+示例一：从源表创建非分区物化视图
+
+```SQL
+CREATE MATERIALIZED VIEW lo_mv1
+DISTRIBUTED BY HASH(`lo_orderkey`)
+REFRESH ASYNC
+AS
+select
+    lo_orderkey, 
+    lo_custkey, 
+    sum(lo_quantity) as total_quantity, 
+    sum(lo_revenue) as total_revenue, 
+    count(lo_shipmode) as shipmode_count
+from lineorder 
+group by lo_orderkey, lo_custkey 
+order by lo_orderkey;
+```
+
+示例二：从源表创建分区物化视图
+
+```SQL
+CREATE MATERIALIZED VIEW lo_mv2
+PARTITION BY `lo_orderdate`
+DISTRIBUTED BY HASH(`lo_orderkey`)
+REFRESH ASYNC START('2023-07-01 10:00:00') EVERY (interval 1 day)
+AS
+select
+    lo_orderkey,
+    lo_orderdate,
+    lo_custkey, 
+    sum(lo_quantity) as total_quantity, 
+    sum(lo_revenue) as total_revenue, 
+    count(lo_shipmode) as shipmode_count
+from lineorder 
+group by lo_orderkey, lo_orderdate, lo_custkey
+order by lo_orderkey;
+
+# 使用 date_trunc 函数将 `dt` 列截断至以月为单位进行分区。
+CREATE MATERIALIZED VIEW order_mv1
+PARTITION BY date_trunc('month', `dt`)
+DISTRIBUTED BY HASH(`order_id`)
+REFRESH ASYNC START('2023-07-01 10:00:00') EVERY (interval 1 day)
+AS
+select
+    dt,
+    order_id,
+    user_id,
+    sum(cnt) as total_cnt,
+    sum(revenue) as total_revenue, 
+    count(state) as state_count
+from orders
+group by dt, order_id, user_id;
+```
+
+示例三：创建异步物化视图
+
+```SQL
+CREATE MATERIALIZED VIEW flat_lineorder
+DISTRIBUTED BY HASH(`lo_orderkey`)
+REFRESH MANUAL
+AS
+SELECT
+    l.LO_ORDERKEY AS LO_ORDERKEY,
+    l.LO_LINENUMBER AS LO_LINENUMBER,
+    l.LO_CUSTKEY AS LO_CUSTKEY,
+    l.LO_PARTKEY AS LO_PARTKEY,
+    l.LO_SUPPKEY AS LO_SUPPKEY,
+    l.LO_ORDERDATE AS LO_ORDERDATE,
+    l.LO_ORDERPRIORITY AS LO_ORDERPRIORITY,
+    l.LO_SHIPPRIORITY AS LO_SHIPPRIORITY,
+    l.LO_QUANTITY AS LO_QUANTITY,
+    l.LO_EXTENDEDPRICE AS LO_EXTENDEDPRICE,
+    l.LO_ORDTOTALPRICE AS LO_ORDTOTALPRICE,
+    l.LO_DISCOUNT AS LO_DISCOUNT,
+    l.LO_REVENUE AS LO_REVENUE,
+    l.LO_SUPPLYCOST AS LO_SUPPLYCOST,
+    l.LO_TAX AS LO_TAX,
+    l.LO_COMMITDATE AS LO_COMMITDATE,
+    l.LO_SHIPMODE AS LO_SHIPMODE,
+    c.C_NAME AS C_NAME,
+    c.C_ADDRESS AS C_ADDRESS,
+    c.C_CITY AS C_CITY,
+    c.C_NATION AS C_NATION,
+    c.C_REGION AS C_REGION,
+    c.C_PHONE AS C_PHONE,
+    c.C_MKTSEGMENT AS C_MKTSEGMENT,
+    s.S_NAME AS S_NAME,
+    s.S_ADDRESS AS S_ADDRESS,
+    s.S_CITY AS S_CITY,
+    s.S_NATION AS S_NATION,
+    s.S_REGION AS S_REGION,
+    s.S_PHONE AS S_PHONE,
+    p.P_NAME AS P_NAME,
+    p.P_MFGR AS P_MFGR,
+    p.P_CATEGORY AS P_CATEGORY,
+    p.P_BRAND AS P_BRAND,
+    p.P_COLOR AS P_COLOR,
+    p.P_TYPE AS P_TYPE,
+    p.P_SIZE AS P_SIZE,
+    p.P_CONTAINER AS P_CONTAINER FROM lineorder AS l 
+INNER JOIN customer AS c ON c.C_CUSTKEY = l.LO_CUSTKEY
+INNER JOIN supplier AS s ON s.S_SUPPKEY = l.LO_SUPPKEY
+INNER JOIN part AS p ON p.P_PARTKEY = l.LO_PARTKEY;
+```
+
+示例四：创建分区物化视图，并将基表 STRING 类型分区键转化为日期类型作为异步物化视图分区键。
+
+```sql
+-- 创建分区键为 STRING 类型的基表。
+CREATE TABLE `part_dates` (
+  `d_date` varchar(20) DEFAULT NULL,
+  `d_dayofweek` varchar(10) DEFAULT NULL,
+  `d_month` varchar(11) DEFAULT NULL,
+  `d_year` int(11) DEFAULT NULL,
+  `d_yearmonthnum` int(11) DEFAULT NULL,
+  `d_yearmonth` varchar(9) DEFAULT NULL,
+  `d_daynuminweek` int(11) DEFAULT NULL,
+  `d_daynuminmonth` int(11) DEFAULT NULL,
+  `d_daynuminyear` int(11) DEFAULT NULL,
+  `d_monthnuminyear` int(11) DEFAULT NULL,
+  `d_weeknuminyear` int(11) DEFAULT NULL,
+  `d_sellingseason` varchar(14) DEFAULT NULL,
+  `d_lastdayinweekfl` int(11) DEFAULT NULL,
+  `d_lastdayinmonthfl` int(11) DEFAULT NULL,
+  `d_holidayfl` int(11) DEFAULT NULL,
+  `d_weekdayfl` int(11) DEFAULT NULL,
+  `d_datekey` varchar(11) DEFAULT NULL
+) partition by (d_datekey);
+
+
+-- 使用 `str2date` 函数创建分区物化视图。
+CREATE MATERIALIZED VIEW IF NOT EXISTS `test_mv` 
+PARTITION BY str2date(`d_datekey`,'%Y%m%d')
+DISTRIBUTED BY HASH(`d_date`, `d_month`, `d_month`) 
+REFRESH MANUAL 
+AS
+SELECT
+  `d_date` ,
+  `d_dayofweek`,
+  `d_month` ,
+  `d_yearmonthnum` ,
+  `d_yearmonth` ,
+  `d_daynuminweek`,
+  `d_daynuminmonth`,
+  `d_daynuminyear` ,
+  `d_monthnuminyear` ,
+  `d_weeknuminyear` ,
+  `d_sellingseason`,
+  `d_lastdayinweekfl`,
+  `d_lastdayinmonthfl`,
+  `d_holidayfl` ,
+  `d_weekdayfl`,
+  `d_datekey`
+FROM
+`hive_catalog`.`ssb_1g_orc`.`part_dates` ;
+```
+
+## 更多操作
+
+如要创建逻辑视图，请参见 [CREATE VIEW](../View/CREATE_VIEW.md)。
diff --git a/docs/zh/sql-reference/sql-statements/materialized_view/DROP_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/materialized_view/DROP_MATERIALIZED_VIEW.md
new file mode 100644
index 00000000000000..f90ed39c69330b
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/materialized_view/DROP_MATERIALIZED_VIEW.md
@@ -0,0 +1,74 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP MATERIALIZED VIEW
+
+## 功能
+
+删除物化视图。
+
+此命令无法用于删除正在创建中的同步物化视图。如要删除创建中的同步物化视图，请参考 [同步物化视图 - 删除物化视图](../../../using_starrocks/Materialized_view-single_table.md#删除正在创建的同步物化视图)。
+
+> **注意**
+>
+> 只有拥有对应物化视图 DROP 权限的用户才可以删除物化视图。
+
+## 语法
+
+```SQL
+DROP MATERIALIZED VIEW [IF EXISTS] [database.]mv_name
+```
+
+## 参数
+
+| **参数**  | **必选** | **说明**                                                     |
+| --------- | -------- | ------------------------------------------------------------ |
+| IF EXISTS | 否       | 如果声明该参数，删除不存在的物化视图系统不会报错。如果不声明该参数，删除不存在的物化视图系统会报错。 |
+| mv_name   | 是       | 待删除的物化视图的名称。                                     |
+
+## 示例
+
+示例一：删除存在的物化视图
+
+1. 查看当前数据库中存在的物化视图。
+
+    ```Plain
+    MySQL > SHOW MATERIALIZED VIEWS\G
+    *************************** 1. row ***************************
+              id: 470740
+            name: order_mv1
+    database_name: default_cluster:sr_hub
+            text: SELECT `sr_hub`.`orders`.`dt` AS `dt`, `sr_hub`.`orders`.`order_id` AS `order_id`, `sr_hub`.`orders`.`user_id` AS `user_id`, sum(`sr_hub`.`orders`.`cnt`) AS `total_cnt`, sum(`sr_hub`.`orders`.`revenue`) AS `total_revenue`, count(`sr_hub`.`orders`.`state`) AS `state_count` FROM `sr_hub`.`orders` GROUP BY `sr_hub`.`orders`.`dt`, `sr_hub`.`orders`.`order_id`, `sr_hub`.`orders`.`user_id`
+            rows: 0
+    1 rows in set (0.00 sec)
+    ```
+
+2. 删除物化视图 `order_mv1`。
+
+    ```Plain
+    DROP MATERIALIZED VIEW order_mv1;
+    ```
+
+3. 删除后重新查看当前数据库中存在的物化视图将不会显示该物化视图。
+
+    ```Plain
+    MySQL > SHOW MATERIALIZED VIEWS;
+    Empty set (0.01 sec)
+    ```
+
+示例二：删除不存在的物化视图
+
+- 当未声明 `IF EXISTS` 参数时，删除一个不属于当前数据库的物化视图 `k1_k2` 会报错。
+
+```Plain
+MySQL > DROP MATERIALIZED VIEW k1_k2;
+ERROR 1064 (HY000): Materialized view k1_k2 is not found
+```
+
+- 当声明 `IF EXISTS` 参数时，删除一个不属于当前数据库的物化视图 `k1_k2` 不会报错。
+
+```Plain
+MySQL > DROP MATERIALIZED VIEW IF EXISTS k1_k2;
+Query OK, 0 rows affected (0.00 sec)
+```
diff --git a/docs/zh/sql-reference/sql-statements/materialized_view/REFRESH_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/materialized_view/REFRESH_MATERIALIZED_VIEW.md
new file mode 100644
index 00000000000000..8cd5fb3331d064
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/materialized_view/REFRESH_MATERIALIZED_VIEW.md
@@ -0,0 +1,68 @@
+---
+displayed_sidebar: docs
+---
+
+# REFRESH MATERIALIZED VIEW
+
+## 功能
+
+手动刷新指定异步物化视图或其中部分分区。
+
+> **注意**
+>
+> 您只能通过该命令手动刷新刷新方式为 ASYNC 或 MANUAL 的异步物化视图。您可以通过 [SHOW MATERIALIZED VIEWS](SHOW_MATERIALIZED_VIEW.md) 查看物化视图的刷新方式。
+> 该操作需要对应物化视图的 REFRESH 权限。
+
+## 语法
+
+```SQL
+REFRESH MATERIALIZED VIEW [database.]mv_name
+[PARTITION START ("<partition_start_date>") END ("<partition_end_date>")]
+[FORCE]
+[WITH { SYNC | ASYNC } MODE]
+```
+
+## 参数
+
+| **参数**                   | **必选**     | **说明**                     |
+| ------------------------- | ------------ | ---------------------------- |
+| mv_name                   | 是           | 待手动刷新的异步物化视图名称。    |
+| PARTITION START () END () | 否           | 手动刷新该时间区间内的分区。      |
+| partition_start_date      | 否           | 待手动刷新的分区开始时间。       |
+| partition_end_date        | 否           | 待手动刷新的分区结束时间。       |
+| FORCE                     | 否           | 如果指定该参数，StarRocks 将强制刷新相应的物化视图或分区。如果不指定该参数，StarRocks 会自动判断数据是否被更新过，只在需要时刷新分区。|
+| WITH ... MODE             | 否           | 同步或异步调用刷新任务。`SYNC` 指同步调用刷新任务，执行 SQL 语句后，StarRocks 将在刷新任务成功或失败后返回结果。`ASYNC` 指异步调用刷新任务，执行 SQL 语句后，StarRocks 将在刷新任务提交后立即返回成功，实际刷新任务会异步在后台运行。您可以通过查询 StarRocks 的 Information Schema 中的 `tasks` 和 `task_runs` 元数据视图来查看异步物化视图的刷新状态。详细信息，请参考[查看异步物化视图的执行状态](../../../using_starrocks/Materialized_view.md#查看异步物化视图的执行状态)。默认值：`ASYNC`。自 v2.5.8 和 v3.1.0 起支持。 |
+
+> **注意**
+>
+> 刷新基于外部数据目录（External Catalog）创建的异步物化视图时，StarRocks 会刷新所有分区。
+
+## 示例
+
+示例一：异步调用任务手动刷新指定物化视图。
+
+```SQL
+REFRESH MATERIALIZED VIEW lo_mv1;
+
+REFRESH MATERIALIZED VIEW lo_mv1 WITH ASYNC MODE;
+```
+
+示例二：手动刷新物化视图指定分区。
+
+```SQL
+REFRESH MATERIALIZED VIEW lo_mv1 
+PARTITION START ("2020-02-01") END ("2020-03-01");
+```
+
+示例三：强制手动刷新物化视图指定分区。
+
+```SQL
+REFRESH MATERIALIZED VIEW lo_mv1 
+PARTITION START ("2020-02-01") END ("2020-03-01") FORCE;
+```
+
+示例四：同步调用任务手动刷新指定物化视图。
+
+```SQL
+REFRESH MATERIALIZED VIEW lo_mv1 WITH SYNC MODE;
+```
diff --git a/docs/zh/sql-reference/sql-statements/materialized_view/SHOW_ALTER_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/materialized_view/SHOW_ALTER_MATERIALIZED_VIEW.md
new file mode 100644
index 00000000000000..8f769f8179554a
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/materialized_view/SHOW_ALTER_MATERIALIZED_VIEW.md
@@ -0,0 +1,80 @@
+---
+keywords: ['xiugai'] 
+displayed_sidebar: docs
+---
+
+# SHOW ALTER MATERIALIZED VIEW
+
+## 功能
+
+查看同步物化视图构建状态。
+
+:::tip
+
+该操作不需要权限。
+
+:::
+
+## 语法
+
+```SQL
+SHOW ALTER MATERIALIZED VIEW [ { FROM | IN } db_name]
+```
+
+## 参数
+
+| **参数** | **必选** | **说明**                                                     |
+| -------- | -------- | ------------------------------------------------------------ |
+| db_name  | 否       | 待查看的数据库名称。如果不指定该参数，则默认使用当前数据库。 |
+
+## 返回
+
+| **返回**        | **说明**             |
+| --------------- | -------------------- |
+| JobId           | 作业 ID。            |
+| TableName       | 表名。               |
+| CreateTime      | 作业创建时间。       |
+| FinishedTime    | 作业结束时间。       |
+| BaseIndexName   | 基表名称。           |
+| RollupIndexName | 物化视图名称。       |
+| RollupId        | 物化视图 Rollup ID。 |
+| TransactionId   | 等待的事务 ID。      |
+| State           | 创建任务状态。       |
+| Msg             | 错误信息。           |
+| Progress        | 创建任务进度。       |
+| Timeout         | 超时时间长度。       |
+
+## 示例
+
+### 示例一：查看同步物化视图刷新任务
+
+```Plain
+MySQL > SHOW ALTER MATERIALIZED VIEW\G
+*************************** 1. row ***************************
+          JobId: 475991
+      TableName: lineorder
+     CreateTime: 2022-08-24 19:46:53
+   FinishedTime: 2022-08-24 19:47:15
+  BaseIndexName: lineorder
+RollupIndexName: lo_mv_sync_1
+       RollupId: 475992
+  TransactionId: 33067
+          State: FINISHED
+            Msg: 
+       Progress: NULL
+        Timeout: 86400
+*************************** 2. row ***************************
+          JobId: 477337
+      TableName: lineorder
+     CreateTime: 2022-08-24 19:47:25
+   FinishedTime: 2022-08-24 19:47:45
+  BaseIndexName: lineorder
+RollupIndexName: lo_mv_sync_2
+       RollupId: 477338
+  TransactionId: 33068
+          State: FINISHED
+            Msg: 
+       Progress: NULL
+        Timeout: 86400
+2 rows in set (0.00 sec)
+```
diff --git a/docs/zh/sql-reference/sql-statements/materialized_view/SHOW_CREATE_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/materialized_view/SHOW_CREATE_MATERIALIZED_VIEW.md
new file mode 100644
index 00000000000000..d66ea7f3248eb6
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/materialized_view/SHOW_CREATE_MATERIALIZED_VIEW.md
@@ -0,0 +1,55 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW CREATE MATERIALIZED VIEW
+
+## 功能
+
+查看指定[异步物化视图](../../../using_starrocks/Materialized_view.md)的定义。
+
+:::tip
+
+该操作不需要权限。
+
+:::
+
+## 语法
+
+```SQL
+SHOW CREATE MATERIALIZED VIEW [db_name.]mv_name
+```
+
+## 参数
+
+| **参数** | **必选** | **说明**                     |
+| -------- | -------- | ---------------------------- |
+| db_name   | 否       | 数据库名称。如不指定，则默认查看当前数据库中指定物化视图的定义。 |
+| mv_name  | 是       | 待查看定义的物化视图的名称。 |
+
+## 返回
+
+| **返回**                 | **说明**         |
+| ------------------------ | ---------------- |
+| Materialized View        | 物化视图的名称。 |
+| Create Materialized View | 物化视图的定义。 |
+
+## 示例
+
+### 示例一：查看指定物化视图定义
+
+```Plain
+MySQL > SHOW CREATE MATERIALIZED VIEW lo_mv1\G
+*************************** 1. row ***************************
+       Materialized View: lo_mv1
+Create Materialized View: CREATE MATERIALIZED VIEW `lo_mv1`
+COMMENT "MATERIALIZED_VIEW"
+DISTRIBUTED BY HASH(`lo_orderkey`) BUCKETS 10 
+REFRESH ASYNC
+PROPERTIES (
+"replication_num" = "3",
+"storage_medium" = "HDD"
+)
+AS SELECT `wlc_test`.`lineorder`.`lo_orderkey` AS `lo_orderkey`, `wlc_test`.`lineorder`.`lo_custkey` AS `lo_custkey`, sum(`wlc_test`.`lineorder`.`lo_quantity`) AS `total_quantity`, sum(`wlc_test`.`lineorder`.`lo_revenue`) AS `total_revenue`, count(`wlc_test`.`lineorder`.`lo_shipmode`) AS `shipmode_count` FROM `wlc_test`.`lineorder` GROUP BY `wlc_test`.`lineorder`.`lo_orderkey`, `wlc_test`.`lineorder`.`lo_custkey` ORDER BY `wlc_test`.`lineorder`.`lo_orderkey` ASC ;
+1 row in set (0.01 sec)
+```
diff --git a/docs/zh/sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md b/docs/zh/sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md
new file mode 100644
index 00000000000000..2966ce945c5f6e
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md
@@ -0,0 +1,170 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW MATERIALIZED VIEWS
+
+## 功能
+
+展示所有或指定异步物化视图信息。该语句从 3.0 版本开始更名为 SHOW MATERIALIZED VIEWS，之前版本为 SHOW MATERIALIZED VIEW。
+
+> **注意**
+>
+> 该命令当前仅针对异步物化视图生效。针对同步物化视图您可以通过 [SHOW ALTER MATERIALIZED VIEW](SHOW_ALTER_MATERIALIZED_VIEW.md) 命令查看当前数据库中同步物化视图的构建状态。
+> 该操作不需要权限。
+
+## 语法
+
+```SQL
+SHOW MATERIALIZED VIEWS
+[FROM db_name]
+[
+WHERE NAME { = "mv_name" | LIKE "mv_name_matcher"}
+]
+```
+
+:::note
+
+自 v3.3 起，如果单个物化视图刷新任务包含多个分区或 task_runs，`SHOW MATERIALIZED VIEWS` 语句将追踪所有 task_runs 的状态。仅当所有 task_runs 成功后，`last_refresh_state` 字段才会返回 `SUCCESS`。
+
+:::
+
+## 参数
+
+| **参数**        | **必选** | **说明**                                                     |
+| --------------- | -------- | ------------------------------------------------------------ |
+| db_name         | 否       | 物化视图所属的数据库名称。如果不指定该参数，则默认使用当前数据库。 |
+| mv_name         | 否       | 用于精确匹配的物化视图名称。                                 |
+| mv_name_matcher | 否       | 用于模糊匹配的物化视图名称 matcher。                         |
+
+## 返回
+
+返回最近一次 REFRESH 任务的状态。
+
+| **返回**                   | **说明**                                                    |
+| -------------------------- | --------------------------------------------------------- |
+| id                         | 物化视图 ID。                                               |
+| database_name              | 物化视图所属的数据库名称。                                     |
+| name                       | 物化视图名称。                                               |
+| refresh_type               | 物化视图的更新方式，包括 ROLLUP、MANUAL、ASYNC、INCREMENTAL。   |
+| is_active                  | 物化视图状态是否为 active。有效值：`true` 和 `false`。          |
+| partition_type             | 物化视图的分区类型，包括 RANGE 和 UNPARTITIONED。|
+| task_id                    | 物化视图的刷新任务 ID。                                       |
+| task_name                  | 物化视图的刷新任务名称。                                       |
+| last_refresh_start_time    | 物化视图上一次刷新开始时间。                                    |
+| last_refresh_finished_time | 物化视图上一次刷新结束时间。                                    |
+| last_refresh_duration      | 物化视图上一次刷新耗时（单位秒）。                               |
+| last_refresh_state         | 物化视图上一次刷新的状态，包括 PENDING、RUNNING、FAILED、SUCCESS。 |
+| last_refresh_force_refresh | 物化视图上一次刷新是否为强制（FORCE）刷新。                      ｜
+| last_refresh_start_partition | 上一次刷新开始的物化视图分区。                                ｜
+| last_refresh_end_partition | 上一次刷新结束的物化视图分区。                                  ｜
+| last_refresh_base_refresh_partitions | 上一次刷新基表更新的分区。                            ｜
+| last_refresh_mv_refresh_partitions | 上一次刷新物化视图刷新的分区。                          ｜
+| last_refresh_error_code    | 物化视图上一次刷新失败的 ErrorCode（如果物化视图状态不为 active）。 |
+| last_refresh_error_message | 物化视图上一次刷新失败的 ErrorMessage（如果物化视图状态不为 active）。 |
+| rows                       | 物化视图中数据行数。                                           |
+| text                       | 创建物化视图的查询语句。                                        |
+
+## 示例
+
+以下示例基于当前业务情景：
+
+```Plain
+-- Create Table: customer
+CREATE TABLE customer ( C_CUSTKEY     INTEGER NOT NULL,
+                        C_NAME        VARCHAR(25) NOT NULL,
+                        C_ADDRESS     VARCHAR(40) NOT NULL,
+                        C_NATIONKEY   INTEGER NOT NULL,
+                        C_PHONE       CHAR(15) NOT NULL,
+                        C_ACCTBAL     double   NOT NULL,
+                        C_MKTSEGMENT  CHAR(10) NOT NULL,
+                        C_COMMENT     VARCHAR(117) NOT NULL,
+                        PAD char(1) NOT NULL)
+    ENGINE=OLAP
+DUPLICATE KEY(`c_custkey`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`c_custkey`) BUCKETS 10
+PROPERTIES (
+"replication_num" = "3",
+"storage_format" = "DEFAULT"
+);
+
+-- Create MV: customer_mv
+CREATE MATERIALIZED VIEW customer_mv
+DISTRIBUTED BY HASH(c_custkey) buckets 10
+REFRESH MANUAL
+PROPERTIES (
+    "replication_num" = "3"
+)
+AS SELECT
+              c_custkey, c_phone, c_acctbal, count(1) as c_count, sum(c_acctbal) as c_sum
+   FROM
+              customer
+   GROUP BY c_custkey, c_phone, c_acctbal;
+
+-- Refresh the MV
+REFRESH MATERIALIZED VIEW customer_mv;
+```
+
+示例一：通过精确匹配查看特定物化视图
+
+```Plain
+mysql> show materialized views  where name='customer_mv'\G
+*************************** 1. row ***************************
+                        id: 10142
+                      name: customer_mv
+             database_name: test
+              refresh_type: MANUAL
+                 is_active: true
+   last_refresh_start_time: 2023-02-17 10:27:33
+last_refresh_finished_time: 2023-02-17 10:27:33
+     last_refresh_duration: 0
+        last_refresh_state: SUCCESS
+             inactive_code: 0
+           inactive_reason:
+                      text: CREATE MATERIALIZED VIEW `customer_mv`
+COMMENT "MATERIALIZED_VIEW"
+DISTRIBUTED BY HASH(`c_custkey`) BUCKETS 10
+REFRESH MANUAL
+PROPERTIES (
+"replication_num" = "3",
+"storage_medium" = "HDD"
+)
+AS SELECT `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`, count(1) AS `c_count`, sum(`customer`.`c_acctbal`) AS `c_sum`
+FROM `test`.`customer`
+GROUP BY `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`;
+                      rows: 0
+1 row in set (0.11 sec)
+```
+
+示例二：通过模糊匹配查看物化视图
+
+```Plain
+mysql> show materialized views  where name like 'customer_mv'\G
+*************************** 1. row ***************************
+                        id: 10142
+                      name: customer_mv
+             database_name: test
+              refresh_type: MANUAL
+                 is_active: true
+   last_refresh_start_time: 2023-02-17 10:27:33
+last_refresh_finished_time: 2023-02-17 10:27:33
+     last_refresh_duration: 0
+        last_refresh_state: SUCCESS
+             inactive_code: 0
+           inactive_reason:
+                      text: CREATE MATERIALIZED VIEW `customer_mv`
+COMMENT "MATERIALIZED_VIEW"
+DISTRIBUTED BY HASH(`c_custkey`) BUCKETS 10
+REFRESH MANUAL
+PROPERTIES (
+"replication_num" = "3",
+"storage_medium" = "HDD"
+)
+AS SELECT `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`, count(1) AS `c_count`, sum(`customer`.`c_acctbal`) AS `c_sum`
+FROM `test`.`customer`
+GROUP BY `customer`.`c_custkey`, `customer`.`c_phone`, `customer`.`c_acctbal`;
+                      rows: 0
+1 row in set (0.12 sec)
+
+```
diff --git a/docs/zh/sql-reference/sql-statements/materialized_view/_category_.yml b/docs/zh/sql-reference/sql-statements/materialized_view/_category_.yml
new file mode 100644
index 00000000000000..ff34e45fcad5de
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/materialized_view/_category_.yml
@@ -0,0 +1,6 @@
+position: 100 # float position is supported
+label: '物化视图'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/prepared_statement.md b/docs/zh/sql-reference/sql-statements/prepared_statement.md
index 516800f23cffc2..827d80b7813340 100644
--- a/docs/zh/sql-reference/sql-statements/prepared_statement.md
+++ b/docs/zh/sql-reference/sql-statements/prepared_statement.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 预准备语句
@@ -73,7 +73,7 @@ SET @var_name = expr [, ...];
 SET @id1 = 1, @id2 = 2;
 ```
 
-详细信息，请参见[用户自定义变量](../../reference/user_defined_variables.md)。
+详细信息，请参见[用户自定义变量](../user_defined_variables.md)。
 
 ### EXECUTE
 
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md
new file mode 100644
index 00000000000000..4f7536750217df
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md
@@ -0,0 +1,1224 @@
+---
+keywords: ['xiugai'] 
+displayed_sidebar: docs
+---
+
+# ALTER TABLE
+
+## 功能
+
+该语句用于修改已有表，包括：
+
+- [修改表名、分区名、索引名、列名](#rename-对名称进行修改)
+- [修改表注释](#修改表的注释31-版本起)
+- [修改分区（增删分区和修改分区属性）](#操作-partition-相关语法)
+- [修改分桶方式和分桶数量](#修改分桶方式和分桶数量自-32-版本起)
+- [修改列（增删列和修改列顺序）](#修改列增删列和修改列顺序)
+- [创建或删除 rollup index](#操作-rollup-index-语法)
+- [修改 bitmap index](#bitmap-index-修改)
+- [修改表的属性](#修改表的属性)
+- [对表进行原子替换](#swap-将两个表原子替换)
+- [手动执行 compaction 合并表数据](#手动-compaction31-版本起)
+
+:::tip
+该操作需要有对应表的 ALTER 权限。
+:::
+
+## 语法
+
+ALTER TABLE 语法格式如下：
+
+```SQL
+ALTER TABLE [<db_name>.]<tbl_name>
+alter_clause1[, alter_clause2, ...]
+```
+
+其中 **alter_clause** 分为 rename、comment、partition、bucket、column、rollup index、bitmap index、table property、swap、compaction 相关修改操作：
+
+- rename: 修改表名、rollup index 名、partition 名或列名（从 3.3.2 版本开始支持）。
+- comment: 修改表的注释。**从 3.1 版本开始支持。**
+- partition: 修改分区属性，删除分区，增加分区。
+- bucket：修改分桶方式和分桶数量。
+- column: 增加列，删除列，调整列顺序，修改列类型。*
+- rollup index: 创建或删除 rollup index。
+- bitmap index: 修改 bitmap index。
+- swap: 原子替换两张表。
+- compaction: 对指定表或分区手动执行 Compaction（数据版本合并）。**从 3.1 版本开始支持。**
+
+## 使用限制和注意事项
+
+- partition、column 和 rollup index <!--是否包含compaction，bucket和column/rollupindex可以在一起吗-->这些操作不能同时出现在一条 `ALTER TABLE` 语句中。
+- 当前还不支持修改列注释。
+- 每张表仅支持一个进行中的 Schema Change 操作。不能对同一张表同时执行两条 Schema Change 命令。
+- bucket、column、rollup index <!--是否包含compaction和fast schema evolution-->是异步操作，命令提交成功后会立即返回一个成功消息，您可以使用 [SHOW ALTER TABLE](SHOW_ALTER.md) 语句查看操作的进度。如果需要取消正在进行的操作，则您可以使用 [CANCEL ALTER TABLE](SHOW_ALTER.md)。
+- rename、comment、partition、bitmap index 和 swap 是同步操作，命令返回表示执行完毕。
+
+### Rename 对名称进行修改
+
+#### 修改表名
+
+语法：
+
+```sql
+ALTER TABLE <tbl_name> RENAME <new_tbl_name>;
+```
+
+#### 修改 rollup index 名称 (RENAME ROLLUP)
+
+语法：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+RENAME ROLLUP old_rollup_name new_rollup_name;
+```
+
+#### 修改 partition 名称 (RENAME PARTITION)
+
+语法：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+RENAME PARTITION <old_partition_name> <new_partition_name>;
+```
+
+#### 修改列名（RENAME COLUMN）
+
+自 v3.3.2 起，StarRocks 支持修改列名。
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+RENAME COLUMN <old_col_name> [ TO ] <new_col_name>
+```
+
+:::note
+
+- 在将某列由 A 重命名为 B 后，不支持继续增加 A 列。
+- 在列名变更后，基于该列创建的物化视图将不再生效，您需要根据新的列名重新创建。
+
+:::
+
+### 修改表的注释（3.1 版本起）
+
+语法：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name> COMMENT = "<new table comment>";
+```
+
+:::tip
+当前还不支持修改列注释。
+:::
+
+### 操作 partition 相关语法
+
+#### 增加分区 (ADD PARTITION(S))
+
+增加分区时支持使用 Range 分区和 List 分区。
+
+语法：
+
+- Range 分区
+
+    ```SQL
+    ALTER TABLE
+        ADD { single_range_partition | multi_range_partitions } [distribution_desc] ["key"="value"];
+    
+    single_range_partition ::=
+        PARTITION [IF NOT EXISTS] <partition_name> VALUES partition_key_desc
+
+    partition_key_desc ::=
+        { LESS THAN { MAXVALUE | value_list }
+        | [ value_list , value_list ) } -- 注意此处的 [ 代表左闭合区间
+
+    value_list ::=
+        ( <value> [, ...] )
+
+    multi_range_partitions ::=
+        { PARTITIONS START ("<start_date_value>") END ("<end_date_value>") EVERY ( INTERVAL <N> <time_unit> )
+        | PARTITIONS START ("<start_integer_value>") END ("<end_integer_value>") EVERY ( <granularity> ) } -- 即使 START、END 所指定的分区列值为整数，也需要使用英文引号包裹，而 EVERY 子句中的分区增量值不用英文引号包裹。
+    ```
+
+- List 分区
+
+    ```SQL
+    ALTER TABLE
+        ADD PARTITION <partition_name> VALUES IN (value_list) [distribution_desc] ["key"="value"];
+
+    value_list ::=
+        value_item [, ...]
+
+    value_item ::=
+        { <value> | ( <value> [, ...] ) }
+    ```
+
+参数：
+
+- 分区相关参数
+
+  - Range 分区支持新增单个分区 `single_range_partition` 或者批量创建分区 `multi_range_partition`。
+  - List 分区仅支持新增单个分区。
+
+- `distribution_desc`：
+
+   可以为新的分区单独设置分桶数量，但是不支持单独设置分桶方式。
+
+- `"key"="value"`：
+
+   可以为新的分区设置属性，具体说明见 [CREATE TABLE](CREATE_TABLE.md#properties)。
+
+示例：
+
+- Range 分区
+
+  - 如果建表时指定分区列为 `event_day`，例如 `PARTITION BY RANGE(event_day)`，并且建表后需要新增一个分区，则可以执行：
+
+    ```sql
+    ALTER TABLE site_access ADD PARTITION p4 VALUES LESS THAN ("2020-04-30");
+    ```
+
+  - 如果建表时指定分区列为 `datekey`，例如 `PARTITION BY RANGE (datekey)`，并且建表后需要批量新增多个分区，则可以执行：
+
+    ```sql
+    ALTER TABLE site_access
+        ADD PARTITIONS START ("2021-01-05") END ("2021-01-10") EVERY (INTERVAL 1 DAY);
+    ```
+
+- List 分区
+
+  - 如果建表时指定单个分区列，例如 `PARTITION BY LIST (city)`，并且建表后需要新增一个分区，则可以执行：
+
+    ```sql
+    ALTER TABLE t_recharge_detail2
+    ADD PARTITION pCalifornia VALUES IN ("Los Angeles","San Francisco","San Diego");
+    ```
+
+  - 如果建表时指定多个分区列，例如 `PARTITION BY LIST (dt,city)`，并且建表后需要新增一个分区，则可以执行：
+
+    ```sql
+    ALTER TABLE t_recharge_detail4 
+    ADD PARTITION p202204_California VALUES IN
+    (
+        ("2022-04-01", "Los Angeles"),
+        ("2022-04-01", "San Francisco"),
+        ("2022-04-02", "Los Angeles"),
+        ("2022-04-02", "San Francisco")
+    );
+    ```
+
+#### 删除分区 (DROP PARTITION(S))
+
+删除单个分区：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+DROP PARTITION [ IF EXISTS ] <partition_name> [ FORCE ]
+```
+
+批量删除分区（自 v3.3.1 起支持）：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+DROP [ TEMPORARY ] PARTITIONS [ IF EXISTS ]  { partition_name_list | multi_range_partitions } [ FORCE ] 
+
+partion_name_list ::= ( <partition_name> [, ... ] )
+
+multi_range_partitions ::=
+    { START ("<start_date_value>") END ("<end_date_value>") EVERY ( INTERVAL <N> <time_unit> )
+    | START ("<start_integer_value>") END ("<end_integer_value>") EVERY ( <granularity> ) } -- 即使 START、END 所指定的分区列值为整数，也需要使用英文引号包裹，而 EVERY 子句中的分区增量值不用英文引号包裹。
+```
+
+关于 `multi_range_partitions` 的说明：
+
+- `multi_range_partitions` 仅适用于 Range 分区。
+- 其中涉及的参数与 [增加分区 ADD PARTITION(S)](#增加分区-add-partitions) 中的相同。
+- 仅支持基于单个分区键的分区。
+
+:::note
+
+- 分区表需要至少要保留一个分区。
+- 如果未指定 FORCE 关键字，您可以通过 [RECOVER](../backup_restore/RECOVER.md) 语句恢复一定时间范围内（默认 1 天）删除的分区。
+- 如果指定了 FORCE 关键字，则系统不会检查该分区是否存在未完成的事务，分区将直接被删除并且不能被恢复，一般不建议执行此操作。
+
+:::
+
+#### 增加临时分区 (ADD TEMPORARY PARTITION)
+
+详细使用信息，请查阅[临时分区](../../../table_design/Temporary_partition.md)。
+
+语法：
+
+```SQL
+ALTER TABLE [<db_name>.]<tbl_name>
+ADD TEMPORARY PARTITION [IF NOT EXISTS] <partition_name>
+partition_desc ["key"="value"]
+[DISTRIBUTED BY HASH (k1[,k2 ...]) [BUCKETS num]];
+```
+
+#### 使用临时分区替换原分区
+
+语法：
+
+```SQL
+ALTER TABLE [<db_name>.]<tbl_name>
+REPLACE PARTITION <partition_name> 
+partition_desc ["key"="value"]
+WITH TEMPORARY PARTITION
+partition_desc ["key"="value"]
+[PROPERTIES ("key"="value", ...)]
+```
+
+#### 删除临时分区 (DROP TEMPORARY PARTITION)
+
+语法：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+DROP TEMPORARY PARTITION <partition_name>;
+```
+
+#### 修改分区属性 (MODIFY PARTITION)
+
+**语法：**
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+    MODIFY PARTITION { <partition_name> | partition_name_list | (*) }
+        SET ("key" = "value", ...);
+```
+
+**使用说明：**
+
+- 当前支持修改分区的下列属性：
+  - storage_medium
+  - storage_cooldown_ttl 或 storage_cooldown_time
+  - replication_num
+
+- 对于单分区表，分区名同表名。对于多分区表，如果需要修改所有分区的属性，则使用 `(*)` 更加方便。
+- 执行 `SHOW PARTITIONS FROM <tbl_name>` 查看修改后分区属性。
+
+### 修改分桶方式和分桶数量（自 3.2 版本起）
+
+语法：
+
+```SQL
+ALTER TABLE [<db_name>.]<table_name>
+[ partition_names ]
+[ distribution_desc ]
+
+partition_names ::= 
+    (PARTITION | PARTITIONS) ( <partition_name> [, <partition_name> ...] )
+
+distribution_desc ::=
+    DISTRIBUTED BY RANDOM [ BUCKETS <num> ] |
+    DISTRIBUTED BY HASH ( <column_name> [, <column_name> ...] ) [ BUCKETS <num> ]
+```
+
+示例：
+
+假设原表为明细表，分桶方式为 Hash 分桶，分桶数量为自动设置。
+
+```SQL
+CREATE TABLE IF NOT EXISTS details (
+    event_time DATETIME NOT NULL COMMENT "datetime of event",
+    event_type INT NOT NULL COMMENT "type of event",
+    user_id INT COMMENT "id of user",
+    device_code INT COMMENT "device code",
+    channel INT COMMENT ""
+)
+DUPLICATE KEY(event_time, event_type)
+PARTITION BY date_trunc('day', event_time)
+DISTRIBUTED BY HASH(user_id);
+
+-- 插入多天的数据
+INSERT INTO details (event_time, event_type, user_id, device_code, channel) VALUES
+-- 11 月 26 日的数据
+('2023-11-26 08:00:00', 1, 101, 12345, 2),
+('2023-11-26 09:15:00', 2, 102, 54321, 3),
+('2023-11-26 10:30:00', 1, 103, 98765, 1),
+-- 11 月 27 日的数据
+('2023-11-27 08:30:00', 1, 104, 11111, 2),
+('2023-11-27 09:45:00', 2, 105, 22222, 3),
+('2023-11-27 11:00:00', 1, 106, 33333, 1),
+-- 11 月 28 日的数据
+('2023-11-28 08:00:00', 1, 107, 44444, 2),
+('2023-11-28 09:15:00', 2, 108, 55555, 3),
+('2023-11-28 10:30:00', 1, 109, 66666, 1);
+```
+
+#### 仅修改分桶方式
+
+> **注意**
+>
+> - 修改分桶方式针对整个表的所有分区生效，不能仅仅针对某个分区生效。
+> - 虽然仅修改分桶方式，没有修改分桶数量，但是您仍然需要在语句中说明分桶数量 `BUCKETS <num>`，如果不指定，则表示由 StarRocks 自动设置分桶数量。
+
+- 将原先的 Hash 分桶修改为 Random 分桶，并且分桶数量仍然由 StarRocks 自动设置。
+
+  ```SQL
+  ALTER TABLE details DISTRIBUTED BY RANDOM;
+  ```
+
+- 将 Hash 分桶时所使用的分桶键从原先的 `event_time, event_type` 修改为 `user_id, event_time`。并且分桶数量仍然由 StarRocks 自动设置。
+
+  ```SQL
+  ALTER TABLE details DISTRIBUTED BY HASH(user_id, event_time);
+  ```
+
+#### 仅修改分桶数量
+
+> **注意**
+>
+> 虽然仅修改分桶数量，没有修改分桶方式，但是您仍然需要在语句中说明分桶方式，例如示例中的 `HASH(user_id)`。
+
+- 将所有分区的分桶数量从原先的由 StarRocks 自动设置修改为 10。
+
+  ```SQL
+  ALTER TABLE details DISTRIBUTED BY HASH(user_id) BUCKETS 10;
+  ```
+
+- 将指定分区的分桶数量从原先的由 StarRocks 自动设置修改为 15。
+
+  ```SQL
+  ALTER TABLE details PARTITIONS (p20231127, p20231128) DISTRIBUTED BY HASH(user_id) BUCKETS 15;
+  ```
+
+  > **说明**
+  >
+  > 分区名称可以执行 `SHOW PARTITIONS FROM <table_name>;` 进行查看。
+
+#### 同时修改分桶方式和分桶数量
+
+> **注意**
+>
+> 同时修改分桶方式和分桶数量针对整个表的所有分区生效，不能仅仅针对某个分区生效。
+
+- 分桶方式从原先的 Hash 分桶修改为 Random 分桶，并且分桶数量从原先的由 StarRocks 自动设置修改为 10。
+
+   ```SQL
+   ALTER TABLE details DISTRIBUTED BY RANDOM BUCKETS 10;
+   ```
+
+- 将 Hash 分桶时所使用的分桶键从原先的 `event_time, event_type` 修改为 `user_id, event_time`，并且分桶数量从原先的由 StarRocks 自动设置修改为 10。
+
+  ```SQL
+  ALTER TABLE details DISTRIBUTED BY HASH(user_id, event_time) BUCKETS 10;
+  ```
+
+### 修改列（增删列和修改列顺序）
+
+下文中的 index 为物化索引。建表成功后表为 base 表 (base index)，基于 base 表可 [创建 rollup index](#创建-rollup-index-add-rollup)。
+
+base index 和 rollup index 都是物化索引。下方语句在编写时如果没有指定 `rollup_index_name`，默认操作基表。
+
+#### 向指定 index 的指定位置添加一列 (ADD COLUMN)
+
+语法：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+ADD COLUMN column_name column_type [KEY | agg_type] [DEFAULT "default_value"]
+[AFTER column_name|FIRST]
+[TO rollup_index_name]
+[PROPERTIES ("key"="value", ...)]
+```
+
+使用说明：
+
+- 聚合表如果增加 value 列，需要指定 agg_type。
+- 非聚合表（如 DUPLICATE KEY）如果增加 key 列，需要指定 KEY 关键字。
+- 不能在 rollup index 中增加 base index 中已经存在的列，如有需要，可以重新创建一个 rollup index。
+
+#### 向指定 index 添加多列
+
+语法：
+
+- 添加多列:
+
+  ```sql
+  ALTER TABLE [<db_name>.]<tbl_name>
+  ADD COLUMN (column_name1 column_type [KEY | agg_type] DEFAULT "default_value", ...)
+  [TO rollup_index_name]
+  [PROPERTIES ("key"="value", ...)]
+  ```
+
+- 添加多列的同时通过 `AFTER` 指定列的添加位置：
+
+  ```sql
+  ALTER TABLE [<db_name>.]<tbl_name>
+  ADD COLUMN column_name1 column_type [KEY | agg_type] DEFAULT "default_value" AFTER column_name,
+  ADD COLUMN column_name2 column_type [KEY | agg_type] DEFAULT "default_value" AFTER column_name
+  [, ...]
+  [TO rollup_index_name]
+  [PROPERTIES ("key"="value", ...)]
+  ```
+
+注意：
+
+1. 聚合表如果增加 value 列，需要指定 agg_type。
+2. 非聚合表如果增加 key 列，需要指定 KEY 关键字。
+3. 不能在 rollup index 中增加 base index 中已经存在的列，如有需要，可以重新创建一个 rollup index。
+
+#### 增加生成列
+
+语法：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+ADD COLUMN col_name data_type [NULL] AS generation_expr [COMMENT 'string']
+```
+
+增加生成列并且指定其使用的表达式。[生成列](../generated_columns.md)用于预先计算并存储表达式的结果，可以加速包含复杂表达式的查询。自 v3.1，StarRocks 支持该功能。
+
+#### 从指定 index 中删除一列 (DROP COLUMN)
+
+语法：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+DROP COLUMN column_name
+[FROM rollup_index_name];
+```
+
+注意：
+
+1. 不能删除分区列。
+2. 如果是从 base index 中删除列，则如果 rollup index 中包含该列，也会被删除。
+
+#### 修改指定 index 的列类型以及列位置 (MODIFY COLUMN)
+
+语法：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+MODIFY COLUMN column_name column_type [KEY | agg_type] [NULL | NOT NULL] [DEFAULT "default_value"]
+[AFTER column_name|FIRST]
+[FROM rollup_index_name]
+[PROPERTIES ("key"="value", ...)]
+```
+
+注意：
+
+1. 聚合表如果修改 value 列，需要指定 agg_type。
+2. 非聚合类型如果修改 key 列，需要指定 KEY 关键字。
+3. 只能修改列的类型，列的其他属性维持原样（即其他属性需在语句中按照原属性显式的写出，参见示例中 [column](#column) 部分第 8 个例子）。
+4. 分区列不能做任何修改。
+5. 目前支持以下类型的转换（精度损失由用户保证）：
+
+    - TINYINT/SMALLINT/INT/BIGINT 转换成 TINYINT/SMALLINT/INT/BIGINT/DOUBLE。
+    - TINYINT/SMALLINT/INT/BIGINT/LARGEINT/FLOAT/DOUBLE/DECIMAL 转换成 VARCHAR。
+    - VARCHAR 支持修改最大长度。
+    - VARCHAR 转换成 TINYINT/SMALLINT/INT/BIGINT/LARGEINT/FLOAT/DOUBLE。
+    - VARCHAR 转换成 DATE (目前支持 "%Y-%m-%d"，"%y-%m-%d"， "%Y%m%d"，"%y%m%d"，"%Y/%m/%d，"%y/%m/%d " 六种格式化格式)
+    DATETIME 转换成 DATE(仅保留年-月-日信息，例如: `2019-12-09 21:47:05` &lt;--&gt; `2019-12-09`)
+    DATE 转换成 DATETIME(时分秒自动补零，例如: `2019-12-09` &lt;--&gt; `2019-12-09 00:00:00`)
+    - FLOAT 转换成 DOUBLE。
+    - INT 转换成 DATE (如果 INT 类型数据不合法则转换失败，原始数据不变。)
+
+#### 修改排序键
+
+自 3.0 版本起，支持修改主键表的排序键。自 3.3 版本起，支持修改明细表、聚合表和更新表的排序键。
+
+明细表和主键表中排序键可以为任意列的排序组合，聚合表和更新表中排序键必须包含所有 key 列，但是列的顺序无需与 key 列保持一致。
+
+语法：
+
+```SQL
+ALTER TABLE [<db_name>.]<table_name>
+[ order_desc ]
+
+order_desc ::=
+    ORDER BY <column_name> [, <column_name> ...]
+```
+
+示例：修改主键表中的排序键
+
+假设原表为主键表，排序键与主键耦合 `dt,order_id`。
+
+```SQL
+create table orders (
+    dt date NOT NULL,
+    order_id bigint NOT NULL,
+    user_id int NOT NULL,
+    merchant_id int NOT NULL,
+    good_id int NOT NULL,
+    good_name string NOT NULL,
+    price int NOT NULL,
+    cnt int NOT NULL,
+    revenue int NOT NULL,
+    state tinyint NOT NULL
+) PRIMARY KEY (dt, order_id)
+PARTITION BY date_trunc('day', dt)
+DISTRIBUTED BY HASH(order_id);
+```
+
+解耦排序键和主键，修改排序键为 `dt,revenue,state`。
+
+```SQL
+ALTER TABLE orders ORDER BY (dt,revenue,state);
+```
+
+#### STRUCT 类型列增删字段（MODIFY COLUMN ADD/DROP FIELD）
+
+自 v3.2.10 及 v3.3.2 起，StarRocks 支持向 STRUCT 类型列增删字段。该字段可以为嵌套 STRUCT 类型或存在于 ARRAY 类型中。
+
+语法：
+
+```sql
+-- 增加字段
+ALTER TABLE [<db_name>.]<tbl_name>
+MODIFY COLUMN <column_name> ADD FIELD <field_name>  <field_type> [AFTER <prior_field_name> |FIRST]
+
+-- 删除字段
+ALTER TABLE [<db_name>.]<tbl_name>
+MODIFY COLUMN <column_name> DROP FIELD <field_name>
+```
+
+参数：
+
+- `field_name`：需要增加或删除字段的名称。可以是单独的字段名，表示第一层级的字段，例如 `new_field_name`。也可以是 Column Access Path，用以表示嵌套层级的字段，例如 `lv1_k1.lv2_k2.new_field_name`。
+- `prior_field_name`：新增字段的前一个字段。与 AFTER 关键字合用，可以表示新加字段的顺序。如果指定 FIRST 关键字，表示新增第一个字段，则无需指定该参数。`prior_field_name` 的层级由 `field_name` 决定，无需手动指定。
+
+有关示例，参考 [示例 - Column -14](#column)。
+
+:::note
+
+- 目前仅支持存算一体集群。
+- 对应表必须开启 `fast_schema_evolution`。
+- 不支持向 MAP 类型中的 STRUCT 增删字段。
+- 新增字段不支持指定默认值，Nullable 等属性。默认为 Nullable，默认值为 null。
+- 使用该功能后，不支持直接将集群降级至不具备该功能的版本。
+
+:::
+
+### 操作 rollup index 语法
+
+#### 创建 rollup index (ADD ROLLUP)
+
+**RollUp 表索引**: shortkey index 可加速数据查找，但 shortkey index 依赖维度列排列次序。如果使用非前缀的维度列构造查找谓词，用户可以为数据表创建若干 RollUp 表索引。 RollUp 表索引的数据组织和存储和数据表相同，但 RollUp 表拥有自身的 shortkey index。用户创建 RollUp 表索引时，可选择聚合的粒度，列的数量，维度列的次序。使频繁使用的查询条件能够命中相应的 RollUp 表索引。
+
+语法：
+
+```SQL
+ALTER TABLE [<db_name>.]<tbl_name> 
+ADD ROLLUP rollup_name (column_name1, column_name2, ...)
+[FROM from_index_name]
+[PROPERTIES ("key"="value", ...)];
+```
+
+PROPERTIES: 支持设置超时时间，默认超时时间为 1 天。
+
+例子：
+
+```SQL
+ALTER TABLE [<db_name>.]<tbl_name> 
+ADD ROLLUP r1(col1,col2) from r0;
+```
+
+#### 批量创建 rollup index
+
+语法：
+
+```SQL
+ALTER TABLE [<db_name>.]<tbl_name>
+ADD ROLLUP [rollup_name (column_name1, column_name2, ...)
+[FROM from_index_name]
+[PROPERTIES ("key"="value", ...)],...];
+```
+
+例子：
+
+```SQL
+ALTER TABLE [<db_name>.]<tbl_name>
+ADD ROLLUP r1(col1,col2) from r0, r2(col3,col4) from r0;
+```
+
+> 注意
+>
+1. 如果没有指定 from_index_name，则默认从 base index 创建。
+2. rollup 表中的列必须是 from_index 中已有的列。
+3. 在 properties 中，可以指定存储格式。具体请参阅 [CREATE TABLE](CREATE_TABLE.md) 章节。
+
+#### 删除 rollup index (DROP ROLLUP)
+
+语法：
+
+```SQL
+ALTER TABLE [<db_name>.]<tbl_name>
+DROP ROLLUP rollup_name [PROPERTIES ("key"="value", ...)];
+```
+
+例子：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name> DROP ROLLUP r1;
+```
+
+#### 批量删除 rollup index
+
+语法：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+DROP ROLLUP [rollup_name [PROPERTIES ("key"="value", ...)],...];
+```
+
+例子：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name> DROP ROLLUP r1, r2;
+```
+
+注意：
+
+不能删除 base index。
+
+### bitmap index 修改
+
+#### 创建 bitmap index (ADD INDEX)
+
+语法：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+ADD INDEX index_name (column [, ...],) [USING BITMAP] [COMMENT 'balabala'];
+```
+
+注意：
+
+1. 目前仅支持修改 bitmap index。
+2. bitmap index 仅在单列上创建。
+
+#### 删除 bitmap index (DROP INDEX)
+
+语法：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+DROP INDEX index_name;
+```
+
+### 修改表的属性
+
+语法：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+SET ("key" = "value",...)
+```
+
+参数说明：
+
+- `key` 表示表属性的名称，`value` 表示该表属性的配置。
+
+- 支持修改如下表属性：
+  - `replication_num`
+  - `default.replication_num`
+  - `storage_cooldown_ttl`
+  - `storage_cooldown_time`
+  - [动态分区相关属性 properties](../../../table_design/dynamic_partitioning.md)，比如 `dynamic_partition.enable`
+  - `enable_persistent_index`
+  - `bloom_filter_columns`
+  - `colocate_with`
+  - `bucket_size`（自 3.2 版本支持）
+
+注意：修改表的属性也可以合并到 schema change <!--这个 schema change 除了column相关的alter table还包括啥--> 操作中来修改，见[示例](#示例)部分。
+
+### Swap 将两个表原子替换
+
+语法：
+
+```sql
+ALTER TABLE [<db_name>.]<tbl_name>
+SWAP WITH <tbl_name>;
+```
+
+### 手动 Compaction（3.1 版本起）
+
+StarRocks 通过 Compaction 机制将导入的不同数据版本进行合并，将小文件合并成大文件，有效提升了查询性能。
+
+3.1 版本之前，支持通过两种方式来做 Compaction：
+
+- 系统自动在后台执行 Compaction。Compaction 的粒度是 BE 级，由后台自动执行，用户无法控制具体的数据库或者表。
+- 用户通过 HTTP 接口指定 Tablet 来执行 Compaction。
+
+3.1 版本之后，增加了一个 SQL 接口，用户可以通过执行 SQL 命令来手动进行 Compaction，可以指定表、单个或多个分区进行 Compaction。
+
+存算分离集群自 v3.3.0 起支持该功能。
+
+语法：
+
+```sql
+-- 对整张表做 compaction。
+ALTER TABLE <tbl_name> COMPACT
+
+-- 指定一个分区进行 compaction。
+ALTER TABLE <tbl_name> COMPACT <partition_name>
+
+-- 指定多个分区进行 compaction。
+ALTER TABLE <tbl_name> COMPACT (<partition1_name>[,<partition2_name>,...])
+
+-- 对多个分区进行 cumulative compaction。
+ALTER TABLE <tbl_name> CUMULATIVE COMPACT (<partition1_name>[,<partition2_name>,...])
+
+-- 对多个分区进行 base compaction。
+ALTER TABLE <tbl_name> BASE COMPACT (<partition1_name>[,<partition2_name>,...])
+```
+
+执行完 Compaction 后，您可以通过查询 `information_schema` 数据库下的 `be_compactions` 表来查看 Compaction 后的数据版本变化 （`SELECT * FROM information_schema.be_compactions;`）。
+
+## 示例
+
+### Table
+
+1. 修改表的默认副本数量，新建分区副本数量默认使用此值。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    SET ("default.replication_num" = "2");
+    ```
+
+2. 修改单分区表的实际副本数量(只限单分区表)。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    SET ("replication_num" = "3");
+    ```
+
+3. 修改数据在多副本间的写入和同步方式。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    SET ("replicated_storage" = "false");
+    ```
+
+    以上示例表示将多副本的写入和同步方式设置为 leaderless replication，即数据同时写入到多个副本，不区分主从副本。更多信息，参见 [CREATE TABLE](CREATE_TABLE.md) 的 `replicated_storage` 参数描述。
+
+### Partition
+
+1. 增加分区，现有分区 [MIN, 2013-01-01)，增加分区 [2013-01-01, 2014-01-01)，使用默认分桶方式。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD PARTITION p1 VALUES LESS THAN ("2014-01-01");
+    ```
+
+2. 增加分区，使用新的分桶数。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD PARTITION p1 VALUES LESS THAN ("2015-01-01")
+    DISTRIBUTED BY HASH(k1) BUCKETS 20;
+    ```
+
+3. 增加分区，使用新的副本数。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD PARTITION p1 VALUES LESS THAN ("2015-01-01")
+    ("replication_num"="1");
+    ```
+
+4. 修改分区副本数。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    MODIFY PARTITION p1 SET("replication_num"="1");
+    ```
+
+5. 批量修改指定分区。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    MODIFY PARTITION (p1, p2, p4) SET("replication_num"="1");
+    ```
+
+6. 批量修改所有分区。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    MODIFY PARTITION (*) SET("storage_medium"="HDD");
+    ```
+
+7. 删除分区。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    DROP PARTITION p1;
+    ```
+
+8. 增加一个指定上下界的分区。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD PARTITION p1 VALUES [("2014-01-01"), ("2014-02-01"));
+    ```
+
+### Rollup index
+
+1. 创建 index `example_rollup_index`，基于 base index（k1, k2, k3, v1, v2），列式存储。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD ROLLUP example_rollup_index(k1, k3, v1, v2)
+    PROPERTIES("storage_type"="column");
+    ```
+
+2. 创建 index `example_rollup_index2`，基于 example_rollup_index（k1, k3, v1, v2）。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD ROLLUP example_rollup_index2 (k1, v1)
+    FROM example_rollup_index;
+    ```
+
+3. 创建 index `example_rollup_index3`，基于 base index (k1, k2, k3, v1), 自定义 rollup 超时时间一小时。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD ROLLUP example_rollup_index3(k1, k3, v1)
+    PROPERTIES("storage_type"="column", "timeout" = "3600");
+    ```
+
+4. 删除 index `example_rollup_index2`。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    DROP ROLLUP example_rollup_index2;
+    ```
+
+### Column
+
+1. 向 `example_rollup_index` 的 `col1` 后添加一个 key 列 `new_col`（非聚合表）。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD COLUMN new_col INT KEY DEFAULT "0" AFTER col1
+    TO example_rollup_index;
+    ```
+
+2. 向 `example_rollup_index` 的 `col1` 后添加一个 value 列 `new_col`（非聚合表）。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD COLUMN new_col INT DEFAULT "0" AFTER col1
+    TO example_rollup_index;
+    ```
+
+3. 向 `example_rollup_index` 的 `col1` 后添加一个 key 列 `new_col`（聚合表）。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD COLUMN new_col INT DEFAULT "0" AFTER col1
+    TO example_rollup_index;
+    ```
+
+4. 向 `example_rollup_index` 的 `col1` 后添加一个 value 列 `new_col`（SUM 聚合类型）（聚合表）。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD COLUMN new_col INT SUM DEFAULT "0" AFTER col1
+    TO example_rollup_index;
+    ```
+
+5. 向 `example_rollup_index` 添加多列（聚合表）。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD COLUMN (col1 INT DEFAULT "1", col2 FLOAT SUM DEFAULT "2.3")
+    TO example_rollup_index;
+    ```
+
+6. 向 `example_rollup_index` 添加多列并通过 `AFTER` 指定列的添加位置。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD COLUMN col1 INT DEFAULT "1" AFTER `k1`,
+    ADD COLUMN col2 FLOAT SUM AFTER `v2`,
+    TO example_rollup_index;
+    ```
+
+7. 从 `example_rollup_index` 删除一列。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    DROP COLUMN col2
+    FROM example_rollup_index;
+    ```
+
+8. 修改 base index 的 `col1` 列的类型为 BIGINT，并移动到 `col2` 列后面。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    MODIFY COLUMN col1 BIGINT DEFAULT "1" AFTER col2;
+    ```
+
+9. 修改 base index 的 `val1` 列最大长度。原 `val1` 为 (`val1 VARCHAR(32) REPLACE DEFAULT "abc"`)。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    MODIFY COLUMN val1 VARCHAR(64) REPLACE DEFAULT "abc";
+    ```
+
+10. 重新排序 `example_rollup_index` 中的列（设原列顺序为：k1, k2, k3, v1, v2）。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ORDER BY (k3,k1,k2,v2,v1)
+    FROM example_rollup_index;
+    ```
+
+11. 同时执行两种操作。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    ADD COLUMN v2 INT MAX DEFAULT "0" AFTER k2 TO example_rollup_index,
+    ORDER BY (k3,k1,k2,v2,v1) FROM example_rollup_index;
+    ```
+
+12. 修改表的 bloom filter 列。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    SET ("bloom_filter_columns"="k1,k2,k3");
+    ```
+
+    也可以合并到上面的修改列操作中（注意多子句的语法有少许区别）
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    DROP COLUMN col2
+    PROPERTIES ("bloom_filter_columns"="k1,k2,k3");
+    ```
+
+13. 批量修改字段数据类型。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    MODIFY COLUMN k1 VARCHAR(100) KEY NOT NULL,
+    MODIFY COLUMN v2 DOUBLE DEFAULT "1" AFTER v1;
+    ```
+
+14. STRUCT 类型增删字段。
+
+    **准备工作**：建表并导入数据
+
+    ```sql
+    CREATE TABLE struct_test(
+        c0 INT,
+        c1 STRUCT<v1 INT, v2 STRUCT<v4 INT, v5 INT>, v3 INT>,
+        c2 STRUCT<v1 INT, v2 ARRAY<STRUCT<v3 INT, v4 STRUCT<v5 INT, v6 INT>>>>
+    )
+    DUPLICATE KEY(c0)
+    DISTRIBUTED BY HASH(`c0`) BUCKETS 1
+    PROPERTIES (
+        "fast_schema_evolution" = "true"
+    );
+    INSERT INTO struct_test VALUES (
+        1, 
+        ROW(1, ROW(2, 3), 4), 
+        ROW(5, [ROW(6, ROW(7, 8)), ROW(9, ROW(10, 11))])
+    );
+    ```
+
+    ```plain
+    mysql> SELECT * FROM struct_test\G
+    *************************** 1. row ***************************
+    c0: 1
+    c1: {"v1":1,"v2":{"v4":2,"v5":3},"v3":4}
+    c2: {"v1":5,"v2":[{"v3":6,"v4":{"v5":7,"v6":8}},{"v3":9,"v4":{"v5":10,"v6":11}}]}
+    ```
+
+    - 向 STRUCT 类型列添加新字段。
+
+    ```sql
+    ALTER TABLE struct_test MODIFY COLUMN c1 ADD FIELD v4 INT AFTER v2;
+    ```
+
+    ```plain
+    mysql> SELECT * FROM struct_test\G
+    *************************** 1. row ***************************
+    c0: 1
+    c1: {"v1":1,"v2":{"v4":2,"v5":3},"v4":null,"v3":4}
+    c2: {"v1":5,"v2":[{"v3":6,"v4":{"v5":7,"v6":8}},{"v3":9,"v4":{"v5":10,"v6":11}}]}
+    ```
+
+    - 向嵌套 STRUCT 类型添加字段。
+
+    ```sql
+    ALTER TABLE struct_test MODIFY COLUMN c1 ADD FIELD v2.v6 INT FIRST;
+    ```
+
+    ```plain
+    mysql> SELECT * FROM struct_test\G
+    *************************** 1. row ***************************
+    c0: 1
+    c1: {"v1":1,"v2":{"v6":null,"v4":2,"v5":3},"v4":null,"v3":4}
+    c2: {"v1":5,"v2":[{"v3":6,"v4":{"v5":7,"v6":8}},{"v3":9,"v4":{"v5":10,"v6":11}}]}
+    ```
+
+    - 向 Array 类型中的 STRUCT 类型添加字段。
+
+    ```sql
+    ALTER TABLE struct_test MODIFY COLUMN c2 ADD FIELD v2.[*].v7 INT AFTER v3;
+    ```
+
+    ```plain
+    mysql> SELECT * FROM struct_test\G
+    *************************** 1. row ***************************
+    c0: 1
+    c1: {"v1":1,"v2":{"v6":null,"v4":2,"v5":3},"v4":null,"v3":4}
+    c2: {"v1":5,"v2":[{"v3":6,"v7":null,"v4":{"v5":7,"v6":8}},{"v3":9,"v7":null,"v4":{"v5":10,"v6":11}}]}
+    ```
+
+    - 删除 STRUCT 类型列中的字段。
+
+    ```sql
+    ALTER TABLE struct_test MODIFY COLUMN c1 DROP FIELD v3;
+    ```
+
+    ```plain
+    mysql> SELECT * FROM struct_test\G
+    *************************** 1. row ***************************
+    c0: 1
+    c1: {"v1":1,"v2":{"v6":null,"v4":2,"v5":3},"v4":null}
+    c2: {"v1":5,"v2":[{"v3":6,"v7":null,"v4":{"v5":7,"v6":8}},{"v3":9,"v7":null,"v4":{"v5":10,"v6":11}}]}
+    ```
+
+    - 删除嵌套 STRUCT 类型中的字段。
+
+    ```sql
+    ALTER TABLE struct_test MODIFY COLUMN c1 DROP FIELD v2.v4;
+    ```
+
+    ```plain
+    mysql> SELECT * FROM struct_test\G
+    *************************** 1. row ***************************
+    c0: 1
+    c1: {"v1":1,"v2":{"v6":null,"v5":3},"v4":null}
+    c2: {"v1":5,"v2":[{"v3":6,"v7":null,"v4":{"v5":7,"v6":8}},{"v3":9,"v7":null,"v4":{"v5":10,"v6":11}}]}
+    ```
+
+    - 删除 Array 类型中的 STRUCT 类型的字段。
+
+    ```sql
+    ALTER TABLE struct_test MODIFY COLUMN c2 DROP FIELD v2.[*].v3;
+    ```
+
+    ```plain
+    mysql> SELECT * FROM struct_test\G
+    *************************** 1. row ***************************
+    c0: 1
+    c1: {"v1":1,"v2":{"v6":null,"v5":3},"v4":null}
+    c2: {"v1":5,"v2":[{"v7":null,"v4":{"v5":7,"v6":8}},{"v7":null,"v4":{"v5":10,"v6":11}}]}
+    ```
+
+### Table property
+
+1. 修改表的 Colocate 属性。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    SET ("colocate_with" = "t1");
+    ```
+
+2. 修改表的动态分区属性(支持未添加动态分区属性的表添加动态分区属性)。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    SET ("dynamic_partition.enable" = "false");
+    ```
+
+    如果需要在未添加动态分区属性的表中添加动态分区属性，则需要指定所有的动态分区属性。
+
+    ```sql
+    ALTER TABLE example_db.my_table
+    SET (
+        "dynamic_partition.enable" = "true",
+        "dynamic_partition.time_unit" = "DAY",
+        "dynamic_partition.end" = "3",
+        "dynamic_partition.prefix" = "p",
+        "dynamic_partition.buckets" = "32"
+        );
+    ```
+
+### Rename
+
+1. 将表 `table1` 的名称修改为 `table2`。
+
+    ```sql
+    ALTER TABLE table1 RENAME table2;
+    ```
+
+2. 将表 `example_table` 中名为 `rollup1` 的 rollup index 修改为 `rollup2`。
+
+    ```sql
+    ALTER TABLE example_table RENAME ROLLUP rollup1 rollup2;
+    ```
+
+3. 将表 `example_table` 中名为 `p1` 的 partition 修改为 `p2`。
+
+    ```sql
+    ALTER TABLE example_table RENAME PARTITION p1 p2;
+    ```
+
+### Bitmap index
+
+1. 在 `table1` 上为 `siteid` 创建 bitmap index。
+
+    ```sql
+    ALTER TABLE table1
+    ADD INDEX index_name (siteid) [USING BITMAP] COMMENT 'balabala';
+    ```
+
+2. 删除 `table1` 上的 `siteid` 列的 bitmap index。
+
+    ```sql
+    ALTER TABLE table1 DROP INDEX index_name;
+    ```
+
+### Swap
+
+将 `table1` 与 `table2` 原子替换。
+
+```sql
+ALTER TABLE table1 SWAP WITH table2;
+```
+
+### 手动 Compaction
+
+```sql
+CREATE TABLE compaction_test( 
+    event_day DATE,
+    pv BIGINT)
+DUPLICATE KEY(event_day)
+PARTITION BY date_trunc('month', event_day)
+DISTRIBUTED BY HASH(event_day) BUCKETS 8
+PROPERTIES("replication_num" = "3");
+
+INSERT INTO compaction_test VALUES
+('2023-02-14', 2),
+('2033-03-01',2);
+{'label':'insert_734648fa-c878-11ed-90d6-00163e0dcbfc', 'status':'VISIBLE', 'txnId':'5008'}
+
+INSERT INTO compaction_test VALUES
+('2023-02-14', 2),('2033-03-01',2);
+{'label':'insert_85c95c1b-c878-11ed-90d6-00163e0dcbfc', 'status':'VISIBLE', 'txnId':'5009'}
+
+ALTER TABLE compaction_test COMPACT;
+
+ALTER TABLE compaction_test COMPACT p203303;
+
+ALTER TABLE compaction_test COMPACT (p202302,p203303);
+
+ALTER TABLE compaction_test CUMULATIVE COMPACT (p202302,p203303);
+
+ALTER TABLE compaction_test BASE COMPACT (p202302,p203303);
+```
+
+## 相关参考
+
+- [CREATE TABLE](CREATE_TABLE.md)
+- [SHOW CREATE TABLE](SHOW_CREATE_TABLE.md)
+- [SHOW TABLES](SHOW_TABLES.md)
+- [SHOW ALTER TABLE](SHOW_ALTER.md)
+- [DROP TABLE](DROP_TABLE.md)
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CANCEL_ALTER_TABLE.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CANCEL_ALTER_TABLE.md
new file mode 100644
index 00000000000000..a4f7eb82e52099
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CANCEL_ALTER_TABLE.md
@@ -0,0 +1,55 @@
+---
+keywords: ['xiugai'] 
+displayed_sidebar: docs
+---
+
+# CANCEL ALTER TABLE
+
+## 功能
+
+取消正在进行的 ALTER TABLE 操作，包括：
+
+- 修改列。
+- 优化表结构（自 3.2 版本起），包括修改分桶方式和分桶数量。
+- 创建和删除 rollup index。
+
+> **注意**
+>
+> - 该语句为同步操作。
+> - 只有拥有对应表 ALTER 权限的用户才可以执行语句。
+> - 该语句仅支持取消使用 ALTER TABLE 执行的异步操作（如上），不支持取消使用 ALTER TABLE 执行同步操作，比如 rename。
+
+## 语法
+
+   ```SQL
+   CANCEL ALTER TABLE { COLUMN | OPTIMIZE | ROLLUP } FROM [<db_name>.]<table_name>
+   ```
+
+## 参数说明
+
+- `{COLUMN ｜ OPTIMIZE | ROLLUP}`：从 `COLUMN`、`OPTIMIZE` 和 `ROLLUP` 中必选其中一个。
+  - 如果指定了 `COLUMN`，该语句用于取消修改列的操作。
+  - 如果指定了 `OPTIMIZE`，该语句用于取消优化表结构的操作（修改分桶方式和分桶数量）。
+  - 如果指定了 `ROLLUP`，该语句用于取消创建或删除 rollup index 的操作。
+- `db_name`：可选。表所在的数据库名称。如不指定，默认为当前数据库。
+- `table_name`：必选。表名。
+
+## 示例
+
+1. 取消数据库 `example_db` 中表 `example_table` 的修改列操作。
+
+   ```SQL
+   CANCEL ALTER TABLE COLUMN FROM example_db.example_table;
+   ```
+
+2. 取消数据库 `example_db` 中表 `example_table` 的优化表结构操作。
+
+   ```SQL
+   CANCEL ALTER TABLE OPTIMIZE FROM example_db.example_table;
+   ```
+
+3. 取消当前数据库中，`example_table` 的创建和删除 rollup index 的操作。
+
+    ```SQL
+    CANCEL ALTER TABLE ROLLUP FROM example_table;
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_INDEX.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_INDEX.md
new file mode 100644
index 00000000000000..58a5ed445c665e
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_INDEX.md
@@ -0,0 +1,66 @@
+---
+displayed_sidebar: docs
+keywords: ['suoyin']
+---
+
+# CREATE INDEX
+
+## 功能
+
+创建索引。仅支持使用该语句创建 Bitmap 索引，有关 Bitmap 索引的使用说明和适用场景，参见 [Bitmap 索引](../../../table_design/indexes/Bitmap_index.md)。
+
+:::tip
+
+- 该操作需要对应表的 ALTER 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
+- 一列只能创建一个 Bitmap index。如果某列已有 index，再次创建会返回失败。
+
+:::
+
+## 语法
+
+```SQL
+CREATE INDEX index_name ON table_name (column_name) [USING BITMAP] [COMMENT'']
+```
+
+## 参数说明
+
+| **参数**    | **必选** | **说明**                                                     |
+| ----------- | -------- | ------------------------------------------------------------ |
+| index_name  | 是       | 索引名称，命名要求参见[系统限制](../../System_limit.md)。在同一张表中不能创建名称相同的索引。 |
+| table_name  | 是       | 表名。                                                       |
+| column_name | 是       | 创建索引的列名。执行一次该语句只能为某一列创建索引，且同一列只能创建一个索引。 |
+| COMMENT     | 否       | 索引备注。                                                   |
+
+## 示例
+
+例如有一张表 `sales_records`，其建表语句如下：
+
+```SQL
+CREATE TABLE sales_records
+(
+    record_id int,
+    seller_id int,
+    item_id int
+)
+DISTRIBUTED BY hash(record_id)
+PROPERTIES (
+    "replication_num" = "3"
+);
+```
+
+为表 `sales_records` 中的 `item_id` 列创建 bitmap 索引，索引名称为 `index3`。
+
+```SQL
+CREATE INDEX index3 ON sales_records (item_id) USING BITMAP COMMENT '';
+```
+
+或
+
+```SQL
+CREATE INDEX index3 ON sales_records (item_id);
+```
+
+## 相关操作
+
+- 如要查看索引，参见 [SHOW INDEX](SHOW_INDEX.md)。
+- 如要删除索引，参见 [DROP INDEX](DROP_INDEX.md)。
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md
new file mode 100644
index 00000000000000..2b78c5e455f4e8
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md
@@ -0,0 +1,1109 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE TABLE
+
+## 功能
+
+该语句用于创建表。
+
+:::tip
+该操作需要有在对应数据库内的建表权限 (CREATE TABLE)。
+:::
+
+## 语法
+
+```sql
+CREATE [TEMPORARY] [EXTERNAL] TABLE [IF NOT EXISTS] [database.]table_name
+(column_definition1[, column_definition2, ...]
+[, index_definition1[, index_definition2, ...]])
+[ENGINE = [olap|mysql|elasticsearch|hive|iceberg|hudi|jdbc]]
+[key_desc]
+[COMMENT "table comment"]
+[partition_desc]
+[distribution_desc]
+[rollup_index]
+[ORDER BY (column_definition1,...)]
+[PROPERTIES ("key"="value", ...)]
+[BROKER PROPERTIES ("key"="value", ...)]
+```
+
+## 参数说明
+
+:::tip
+
+- 关于建表时对于表名、列名、分区名、索引名的命名要求，参见[系统限制](../../System_limit.md)。
+
+- 在指定数据库名、表名和列名等变量时，如果使用了保留关键字，必须使用反引号 (`) 包裹，否则可能会产生报错。有关 StarRocks 的保留关键字列表，请参见[关键字](../keywords.md#保留关键字)。
+
+:::
+
+### column_definition
+
+语法：
+
+```sql
+col_name col_type [agg_type] [NULL | NOT NULL] [DEFAULT "default_value"] [AUTO_INCREMENT] [AS generation_expr]
+```
+
+说明：
+
+**col_name**：列名称。
+
+注意，在一般情况下，不能直接创建以以 `__op` 或 `__row` 开头命名的列，因为此类列名被 StarRocks 保留用于特殊目的，创建这样的列可能导致未知行为。如需创建这样的列，必须将 FE 动态参数 [`allow_system_reserved_names`](../../../administration/management/FE_configuration.md#allow_system_reserved_names) 设置为 `TRUE`。
+
+**col_type**：列数据类型
+
+支持的列类型以及取值范围等信息如下：
+
+- TINYINT（1字节）
+  范围：-2^7 + 1 ~ 2^7 - 1
+
+- SMALLINT（2字节）
+  范围：-2^15 + 1 ~ 2^15 - 1
+
+- INT（4字节）
+  范围：-2^31 + 1 ~ 2^31 - 1
+
+- BIGINT（8字节）
+  范围：-2^63 + 1 ~ 2^63 - 1
+
+- LARGEINT（16字节）
+  范围：-2^127 + 1 ~ 2^127 - 1
+
+- FLOAT（4字节）
+  支持科学计数法。
+
+- DOUBLE（8字节）
+  支持科学计数法。
+
+- DECIMAL[(precision, scale)] (16字节)
+  保证精度的小数类型。默认是 DECIMAL(10, 0)
+    precision: 1 ~ 38
+    scale: 0 ~ precision
+  其中整数部分为：precision - scale
+  不支持科学计数法。
+
+- DATE（3字节）
+  范围：0000-01-01 ~ 9999-12-31
+
+- DATETIME（8字节）
+  范围：0000-01-01 00:00:00 ~ 9999-12-31 23:59:59
+
+- CHAR[(length)]
+
+  定长字符串。长度范围：1 ~ 255。默认为 1。
+
+- VARCHAR[(length)]
+
+  变长字符串。单位：字节，默认取值为 `1`。
+  - StarRocks 2.1.0 之前的版本，`length` 的取值范围为 1~65533。
+  - 【公测中】自 StarRocks 2.1.0 版本开始，`length` 的取值范围为 1~1048576。
+
+- HLL (1~16385个字节)
+
+  HLL 列类型，不需要指定长度和默认值，长度根据数据的聚合程度系统内控制，并且 HLL 列只能通过配套的 [hll_union_agg](../../sql-functions/aggregate-functions/hll_union_agg.md)、[hll_cardinality](../../sql-functions/scalar-functions/hll_cardinality.md)、[hll_hash](../../sql-functions/scalar-functions/hll_hash.md)进行查询或使用。
+
+- BITMAP
+  BITMAP 列类型，不需要指定长度和默认值。表示整型的集合，元素个数最大支持到 2^64 - 1。
+
+- ARRAY
+  支持在一个数组中嵌套子数组，最多可嵌套 14 层。您必须使用尖括号（ < 和 > ）来声明 ARRAY 的元素类型，如 ARRAY < INT >。目前不支持将数组中的元素声明为 [Fast Decimal](../../data-types/numeric/DECIMAL.md) 类型。
+
+**agg_type**：聚合类型，如果不指定，则该列为 key 列。否则，该列为 value 列。
+
+```plain
+支持的聚合类型如下：
+
+- SUM、MAX、MIN、REPLACE
+
+- HLL_UNION（仅用于 HLL列，为 HLL 独有的聚合方式)。
+
+- BITMAP_UNION（仅用于 BITMAP 列，为 BITMAP 独有的聚合方式)。
+
+- REPLACE_IF_NOT_NULL：这个聚合类型的含义是当且仅当新导入数据是非 NULL 值时会发生替换行为。如果新导入的数据是 NULL，那么 StarRocks 仍然会保留原值。
+```
+
+注意：
+
+1. BITMAP_UNION 聚合类型列在导入时的原始数据类型必须是 `TINYINT, SMALLINT, INT, BIGINT`。
+2. 如果在建表时 `REPLACE_IF_NOT_NULL` 列指定了 NOT NULL，那么 StarRocks 仍然会将其转化 NULL，不会向用户报错。用户可以借助这个类型完成「部分列导入」的功能。
+  该类型只对聚合表有用 (`key_desc` 的 `type` 为 `AGGREGATE KEY`)。自 3.1.9 起，`REPLACE_IF_NOT_NULL` 新增支持 BITMAP 类型的列。
+
+**NULL | NOT NULL**：列数据是否允许为 `NULL`。其中明细表、聚合表和更新表中所有列都默认指定 `NULL`。主键表的指标列默认指定 `NULL`，维度列默认指定 `NOT NULL`。如源数据文件中存在 `NULL` 值，可以用 `\N` 来表示，导入时 StarRocks 会将其解析为 `NULL`。
+
+**DEFAULT "default_value"**：列数据的默认值。导入数据时，如果该列对应的源数据文件中的字段为空，则自动填充 `DEFAULT` 关键字中指定的默认值。支持以下三种指定方式：
+
+- **DEFAULT current_timestamp**：默认值为当前时间。参见 [current_timestamp()](../../sql-functions/date-time-functions/current_timestamp.md) 。
+- **DEFAULT `<默认值>`**：默认值为指定类型的值。例如，列类型为 VARCHAR，即可指定默认值为 `DEFAULT "beijing"`。当前不支持指定 ARRAY、BITMAP、JSON、HLL 和 BOOLEAN 类型为默认值。
+- **DEFAULT (`<表达式>`)**：默认值为指定函数返回的结果。目前仅支持 [uuid()](../../sql-functions/utility-functions/uuid.md) 和 [uuid_numeric()](../../sql-functions/utility-functions/uuid_numeric.md) 表达式。
+
+**AUTO_INCREMENT**：指定自增列。自增列的数据类型只支持 BIGINT，自增 ID 从 1 开始增加，自增步长为 1。有关自增列的详细说明，请参见 [AUTO_INCREMENT](auto_increment.md)。自 v3.0，StarRocks 支持该功能。
+
+**AS generation_expr**：指定生成列和其使用的表达式。[生成列](../generated_columns.md)用于预先计算并存储表达式的结果，可以加速包含复杂表达式的查询。自 v3.1，StarRocks 支持该功能。
+
+### index_definition
+
+创建 bitmap 索引的语法如下。有关参数说明和使用限制，请参见 [Bitmap 索引](../../../table_design/indexes/Bitmap_index.md#创建索引)。
+
+```sql
+INDEX index_name (col_name[, col_name, ...]) [USING BITMAP] [COMMENT '']
+```
+
+### ENGINE 类型
+
+默认为 `olap`，表示创建的是 StarRocks 内部表。
+
+可选值：`mysql`、`elasticsearch`、`hive`、`jdbc` (2.3 及以后)、`iceberg`、`hudi`（2.2 及以后）。如果指定了可选值，则创建的是对应类型的外部表 (external table)，在建表时需要使用 CREATE EXTERNAL TABLE。更多信息，参见[外部表](../../../data_source/External_table.md)。
+
+**从 3.0 版本起，对于查询 Hive、Iceberg、Hudi 和 JDBC 数据源的场景，推荐使用 Catalog 直接查询，不再推荐外部表的方式。具体参见 [Hive catalog](../../../data_source/catalog/hive_catalog.md)、[Iceberg catalog](../../../data_source/catalog/iceberg_catalog.md)、[Hudi catalog](../../../data_source/catalog/hudi_catalog.md) 和 [JDBC catalog](../../../data_source/catalog/jdbc_catalog.md)。**
+
+**从 3.1 版本起，支持直接在 Iceberg catalog 内创建表（当前仅支持 Parquet 格式的表），您可以通过 [INSERT INTO](../loading_unloading/INSERT.md) 把数据插入到 Iceberg 表中。参见 [创建 Iceberg 表](../../../data_source/catalog/iceberg_catalog.md#创建-iceberg-表)。**
+
+**从 3.2 版本起，支持直接在 Hive Catalog 内创建 Parquet 格式的表，并支持通过 [INSERT INTO](../loading_unloading/INSERT.md) 把数据插入到 Parquet 格式的 Hive 表中。从 3.3 版本起，支持直接在 Hive Catalog 中创建 ORC 及 Textfile 格式的表，并支持通过 [INSERT INTO](../loading_unloading/INSERT.md) 把数据插入到 ORC 及 Textfile 格式的 Hive 表中。参见[创建 Hive 表](../../../data_source/catalog/hive_catalog.md#创建-hive-表)和[向 Hive 表中插入数据](../../../data_source/catalog/hive_catalog.md#向-hive-表中插入数据)。**
+
+1. 如果是 mysql，则需要在 properties 提供以下信息：
+
+    ```sql
+    PROPERTIES (
+        "host" = "mysql_server_host",
+        "port" = "mysql_server_port",
+        "user" = "your_user_name",
+        "password" = "your_password",
+        "database" = "database_name",
+        "table" = "table_name"
+    )
+    ```
+
+    注意：
+    "table" 条目中的 "table_name" 是 MySQL 中的真实表名。
+    而 CREATE TABLE 语句中的 table_name 是该 MySQL 表在 StarRocks 中的名字，可以不同。
+
+    在 StarRocks 创建 MySQL 表的目的是可以通过 StarRocks 访问 MySQL 数据库。
+    而 StarRocks 本身并不维护、存储任何 MySQL 数据。
+
+2. 如果是 elasticsearch，则需要在 properties 提供以下信息：
+
+    ```sql
+    PROPERTIES (
+        "hosts" = "http://192.168.0.1:8200,http://192.168.0.2:8200",
+        "user" = "root",
+        "password" = "root",
+        "index" = "tindex",
+        "type" = "doc"
+    )
+    ```
+
+    其中 `hosts` 为 Elasticsearch 集群连接地址，可指定一个或者多个，`user 和 password` 为开启 basic 认证的 Elasticsearch 集群的用户名/密码，`index` 是 StarRocks 中的表对应的 Elasticsearch 的 index 名字，可以是 alias，`type` 指定 index 的类型，默认是 `doc`。
+
+3. 如果是 hive，则需要在 properties 提供以下信息：
+
+    ```sql
+    PROPERTIES (
+        "database" = "hive_db_name",
+        "table" = "hive_table_name",
+        "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083"
+    )
+    ```
+
+    其中 `database` 是 Hive 表对应的库名字，`table` 是 hive 表的名字，`hive.metastore.uris` 是 Hive metastore 服务地址。
+
+4. 如果是 jdbc，则需要在 properties 提供以下信息：
+
+    ```sql
+    PROPERTIES (
+        "resource"="jdbc0",
+        "table"="dest_tbl"
+    )
+    ```
+
+    其中 `resource` 是所使用 JDBC 资源的名称。`table` 是目标数据库表名。
+
+5. 如果是 iceberg，则需要在 properties 提供以下信息：
+
+    ```sql
+    PROPERTIES (
+        "resource" = "iceberg0", 
+        "database" = "iceberg", 
+        "table" = "iceberg_table"
+    )
+    ```
+
+    其中 `resource` 是引用的 Iceberg 资源的名称。`database` 是 Iceberg 表所属的数据库名称。`table` Iceberg 表名称。
+6. 如果是 hudi，则需要在 properties 提供以下信息：
+
+    ```sql
+    PROPERTIES (
+        "resource" = "hudi0", 
+        "database" = "hudi", 
+        "table" = "hudi_table" 
+    )
+    ```
+
+    其中 `resource` 是 Hudi 资源的名称。`database` 是 Hudi 表所属的数据库名称。`table` Hudi 表名称。
+
+### key_desc
+
+语法：
+
+```sql
+`key_type(k1[,k2 ...])`
+```
+
+> 说明
+>
+数据按照指定的 key 列进行排序，且根据不同的 `key_type` 具有不同特性。
+`key_type` 支持以下类型：
+
+- AGGREGATE KEY: key 列相同的记录，value 列按照指定的聚合类型进行聚合，适合报表、多维分析等业务场景。
+- UNIQUE KEY/PRIMARY KEY: key 列相同的记录，value 列按导入顺序进行覆盖，适合按 key 列进行增删改查的点查询 (point query) 业务。
+- DUPLICATE KEY: key 列相同的记录，同时存在于 StarRocks 中，适合存储明细数据或者数据无聚合特性的业务场景。
+
+默认为 DUPLICATE KEY，数据按 key 列做排序。
+
+除 AGGREGATE KEY 外，其他 `key_type` 在建表时，`value` 列不需要指定聚合类型 (agg_type)。
+
+### COMMENT
+
+表的注释，可选。注意建表时 COMMENT 必须在 `key_desc` 之后，否则建表失败。
+
+如果后续想修改表的注释，可以使用 `ALTER TABLE <table_name> COMMENT = "new table comment"`（3.1 版本开始支持）。
+
+### partition_desc
+
+支持三种分区方式，[表达式分区](../../../table_design/expression_partitioning.md)（推荐）、[Range 分区](../../../table_design/Data_distribution.md#range-分区) 和 [List 分区](../../../table_design/list_partitioning.md)。
+
+使用 Range 分区时，提供三种创建方式，其语法、说明和示例如下：
+
+- **动态创建分区**
+
+    [动态分区](../../../table_design/dynamic_partitioning.md)提供了分区生命周期管理（TTL）。StarRocks 会自动提前创建新的分区，并删除过期的分区，以确保数据时效性。要启用这个功能，您可以在创建表时配置与动态分区相关的属性。
+
+- **手动创建分区**
+
+  - 仅指定各个分区的上界
+
+    语法：
+
+    ```sql
+    PARTITION BY RANGE ( <partitioning_column1> [, <partitioning_column2>, ... ] )
+    PARTITION <partition1_name> VALUES LESS THAN ("<upper_bound_for_partitioning_column1>" [ , "<upper_bound_for_partitioning_column2>", ... ] )
+    [ ,
+    PARTITION <partition2_name> VALUES LESS THAN ("<upper_bound_for_partitioning_column1>" [ , "<upper_bound_for_partitioning_column2>", ... ] )
+    , ... ] 
+    )
+    ```
+
+    说明：
+
+    使用指定的 key 列和指定的数值范围进行分区。
+
+    - 分区名称的命名要求，参见[系统限制](../../System_limit.md)。
+    - 3.3.0 之前，仅支持以下类型的列作为 Range 分区列：`TINYINT, SMALLINT, INT, BIGINT, LARGEINT, DATE, DATETIME`。自 3.3.0 起，支持三个特定时间函数为 Range 分区列。具体使用方式，参见[数据分布](../../../table_design/Data_distribution.md#手动创建分区)。
+    - 分区为左闭右开区间，首个分区的左边界为最小值。
+    - NULL 值只会存放在包含 **最小值** 的分区中。当包含最小值的分区被删除后，NULL 值将无法导入。
+    - 可以指定一列或多列作为分区列。如果分区值缺省，则会默认填充最小值。
+    - 当只指定一个列作为分区列时，您可以设置最后一个分区的分区列的上界为 MAXVALUE。
+
+    注意：
+
+    1. 分区一般用于时间维度的数据管理。
+    2. 有数据回溯需求的，可以考虑首个分区为空分区，以便后续增加分区。
+
+    示例：
+
+    1. 分区列 `pay_dt` 为 DATE 类型，并且按天分区。
+
+        ```sql
+        PARTITION BY RANGE(pay_dt)
+        (
+            PARTITION p1 VALUES LESS THAN ("2021-01-02"),
+            PARTITION p2 VALUES LESS THAN ("2021-01-03"),
+            PARTITION p3 VALUES LESS THAN ("2021-01-04")
+        )
+        ```
+
+    2. 分区列 `pay_dt` 为 INT 类型，并且按天分区。
+
+        ```sql
+        PARTITION BY RANGE(pay_dt)
+        (
+            PARTITION p1 VALUES LESS THAN ("20210102"),
+            PARTITION p2 VALUES LESS THAN ("20210103"),
+            PARTITION p3 VALUES LESS THAN ("20210104")
+        )
+        ```
+
+    3. 分区列 `pay_dt` 为 INT 类型，并且按天分区，最后一个分区没有上界。
+
+        ```sql
+        PARTITION BY RANGE(pay_dt)
+        (
+            PARTITION p1 VALUES LESS THAN ("20210102"),
+            PARTITION p2 VALUES LESS THAN ("20210103"),
+            PARTITION p3 VALUES LESS THAN MAXVALUE
+        )
+        ```
+
+  - 指定各个分区的上界和下界
+
+    语法：
+
+    ```sql
+    PARTITION BY RANGE ( <partitioning_column1> [, <partitioning_column2>, ... ] )
+    (
+        PARTITION <partition_name1> VALUES [( "<lower_bound_for_partitioning_column1>" [ , "<lower_bound_for_partitioning_column2>", ... ] ), ( "<upper_bound_for_partitioning_column1>" [ , "<upper_bound_for_partitioning_column2>", ... ] ) ) 
+        [,
+        PARTITION <partition_name2> VALUES [( "<lower_bound_for_partitioning_column1>" [ , "<lower_bound_for_partitioning_column2>", ... ] ), ( "<upper_bound_for_partitioning_column1>" [ , "<upper_bound_for_partitioning_column2>", ... ] ) ) 
+        , ...]
+    )
+    ```
+
+    说明：
+
+    - 与仅指定分区下界相比，指定各个分区的上界和下界相对灵活，并且您可以自定义左右区间。
+    - 其他与 LESS THAN 保持同步。
+    - 当只指定一个列作为分区列时，您可以设置最后一个分区的分区列的上界为 MAXVALUE。
+
+    示例：
+
+    1. 分区列 `pay_dt` 为 DATE 类型，并且按月分区。
+
+        ```sql
+        PARTITION BY RANGE (pay_dt)
+        (
+            PARTITION p202101 VALUES [("2021-01-01"), ("2021-02-01")),
+            PARTITION p202102 VALUES [("2021-02-01"), ("2021-03-01")),
+            PARTITION p202103 VALUES [("2021-03-01"), ("2021-04-01"))
+        )
+        ```
+
+    2. 分区列 `pay_dt` 为 INT 类型，并且按月分区。
+
+        ```sql
+        PARTITION BY RANGE (pay_dt)
+        (
+            PARTITION p202101 VALUES [("20210101"), ("20210201")),
+            PARTITION p202102 VALUES [("20210201"), ("20210301")),
+            PARTITION p202103 VALUES [("20210301"), ("20210401"))
+        )
+        ```
+
+    3. 分区列 `pay_dt` 为 INT 类型，并且按月分区，最后一个分区没有上界。
+
+        ```sql
+        PARTITION BY RANGE (pay_dt)
+        (
+            PARTITION p202101 VALUES [("20210101"), ("20210201")),
+            PARTITION p202102 VALUES [("20210201"), ("20210301")),
+            PARTITION p202103 VALUES [("20210301"), (MAXVALUE))
+        )
+        ```
+
+- **批量创建分区**
+
+  语法：
+
+  - 如果分区列为时间类型
+
+    ```sql
+    PARTITION BY RANGE (<partitioning_column>) (
+        START ("<start_date>") END ("<end_date>") EVERY (INTERVAL <N> <time_unit>)
+    )
+    ```
+
+    - 如果分区列为整数类型
+
+    ```sql
+    PARTITION BY RANGE (<partitioning_column>) (
+        START ("<start_integer>") END ("<end_integer>") EVERY (<partitioning_granularity>)
+    )
+    ```
+
+    说明：
+    用户可以通过给出一个 START 值、一个 END 值以及一个定义分区增量值的 EVERY 子句批量产生分区。
+
+    - 3.3.0 之前，仅支持以下类型的列作为 Range 分区列：`TINYINT, SMALLINT, INT, BIGINT, LARGEINT, DATE, DATETIME`。自 3.3.0 起，支持三个特定时间函数为 Range 分区列。具体使用方式，参见[数据分布](../../../table_design/Data_distribution.md#手动创建分区)。
+    - 当分区列为日期类型时，需要指定 `INTERVAL` 关键字来表示日期间隔。目前日期间隔支持 hour (v3.0）、day、week、month、year，分区的命名规则同动态分区一样。
+    - 当分区列为整数类型时，START 值、END 值仍需要用双引号包裹。
+    - 仅支持指定一列作为分区列。
+
+    更多信息，请参见[批量创建分区](../../../table_design/Data_distribution.md#range-分区)。
+
+    示例：
+
+    1. 分区列 `pay_dt` 为 DATE 类型，并且按年分区。
+
+        ```sql
+        PARTITION BY RANGE (pay_dt) (
+            START ("2018-01-01") END ("2023-01-01") EVERY (INTERVAL 1 YEAR)
+        )
+        ```
+
+    2. 分区列 `pay_dt` 为 INT 类型，并且按年分区。
+
+        ```sql
+        PARTITION BY RANGE (pay_dt) (
+            START ("2018") END ("2023") EVERY (1)
+        )
+        ```
+
+### distribution_desc
+
+支持随机分桶（Random bucketing）和哈希分桶（Hash bucketing）。如果不指定分桶信息，则 StarRocks 默认使用随机分桶且自动设置分桶数量。
+
+- 随机分桶（自 v3.1）
+
+  对每个分区的数据，StarRocks 将数据随机地分布在所有分桶中，而不受到特定列值的影响。并且如果选择由系统设置分桶数量，则您无需设置分桶信息。如果选择手动指定分桶数量，则语法如下：
+
+  ```SQL
+  DISTRIBUTED BY RANDOM BUCKETS <num>
+  ```
+
+  不过值得注意的是，如果查询海量数据且查询时经常使用一些列会作为条件列，随机分桶提供的查询性能可能不够理想。在该场景下建议您使用哈希分桶，当查询时经常使用这些列作为条件列时，只需要扫描和计算查询命中的少量分桶，则可以显著提高查询性能。
+
+  **注意事项**
+
+  - 不支持主键表、更新表和聚合表。
+  - 不支持指定 [Colocation Group](../../../using_starrocks/Colocate_join.md)。
+  - 不支持 [Spark Load](../../../loading/SparkLoad.md)。
+  - 自 2.5.7 版本起，建表时**无需手动指定分桶数量**，StarRocks 自动设置分桶数量。如果您需要手动设置分桶数量，请参见[设置分桶数量](../../../table_design/Data_distribution.md#设置分桶数量)。
+
+  更多随机分桶的信息，请参见[随机分桶](../../../table_design/Data_distribution.md#随机分桶自-v31)。
+
+- 哈希分桶
+
+  语法：
+
+  ```SQL
+  DISTRIBUTED BY HASH (k1[,k2 ...]) [BUCKETS num]
+  ```
+
+  对每个分区的数据，StarRocks 会根据分桶键和分桶数量进行哈希分桶。
+
+  对于分桶键的选择，如果列是高基数且经常作为查询条件，则优先选择其为分桶键，进行哈希分桶。
+  如果不存在同时满足两个条件的列，则需要根据查询进行判断。
+  - 如果查询比较复杂，则建议选择高基数的列为分桶键，保证数据在各个分桶中尽量均衡，提高集群资源利用率。
+  - 如果查询比较简单，则建议选择经常作为查询条件的列为分桶键，提高查询效率。
+  并且，如果数据倾斜情况严重，您还可以使用多个列作为数据的分桶键，但是建议不超过 3 个列。
+  更多选择分桶键的信息，请参见[选择分桶键](../../../table_design/Data_distribution.md#哈希分桶).
+
+  **注意事项**
+
+  - **建表时，必须指定分桶键**。
+  - 作为分桶键的列，该列的值不支持更新。
+  - 分桶键指定后不支持修改。
+  - 自 2.5.7 版本起，建表时**无需手动指定分桶数量**，StarRocks 自动设置分桶数量。如果您需要手动设置分桶数量，请参见[设置分桶数量](../../../table_design/Data_distribution.md#设置分桶数量)。
+
+### ORDER BY
+
+自 3.0 版本起，主键表支持使用 `ORDER BY` 定义排序键，自 3.3 版本起，明细表、聚合表和更新表支持使用 `ORDER BY` 定义排序键。
+
+排序键的更多说明，请参见[排序键和前缀索引](../../../table_design/indexes/Prefix_index_sort_key.md)。
+
+### TEMPORARY
+
+创建临时表。从 v3.3.1 版本开始，StarRocks 支持在 Default Catalog 中创建临时表。更多信息，请参见 [临时表](../../../table_design/StarRocks_table_design.md#临时表)。
+
+:::note
+创建临时表时，必须将 `ENGINE` 设置为 `olap`。
+:::
+
+### PROPERTIES
+
+#### 设置数据的初始存储介质、自动降冷时间和副本数
+
+如果 ENGINE 类型为 OLAP，可以在属性 `properties` 中设置该表数据的初始存储介质（storage_medium）、自动降冷时间（storage_cooldown_time）或者时间间隔（storage_cooldown_ttl）和副本数（replication_num）。
+
+属性生效范围：当表为单分区表时，以上属性为表的属性。当表划分成多个分区时，以上属性属于每一个分区。并且如果希望不同分区有不同属性，则建表后可以执行 [ALTER TABLE ... ADD PARTITION 或 ALTER TABLE ... MODIFY PARTITION](ALTER_TABLE.md)。
+
+**设置数据的初始存储介质、自动降冷时间**
+
+```sql
+PROPERTIES (
+    "storage_medium" = "[SSD|HDD]",
+    { "storage_cooldown_ttl" = "<num> { YEAR | MONTH | DAY | HOUR } "
+    | "storage_cooldown_time" = "yyyy-MM-dd HH:mm:ss" }
+)
+```
+
+- `storage_medium`：数据初始存储介质，取值为 `SSD` 或 `HDD`。显式指定该参数时，请确保该值与 BE 静态参数 `storage_root_path` 中指定的集群存储介质相匹配。
+  
+  当 FE 配置项 `enable_strict_storage_medium_check` 为 `true` 时，表示在建表时会严格校验 BE 上的存储介质。如果建表语句中的存储介质和 BE 的存储类型不一致，建表语句会报错 `Failed to find enough hosts with storage medium [SSD|HDD] at all backends...`。当 `enable_strict_storage_medium_check` 为 `false` 时，可以忽略该报错强行建表，但是后续可能会导致集群磁盘空间分布出现不均衡。
+
+  从 2.3.6，2.4.2，2.5.1，3.0 及以上版本开始，支持在未显式指定该参数的情况下，由系统自动推导存储介质。
+
+  - 在以下场景中，系统推导该参数为 SSD：
+    - BE 上报的存储路径 (`storage_root_path`) 都是 SSD。
+    - BE 上报的存储路径包含 SSD 和 HDD。并且从 2.3.10，2.4.5，2.5.4，3.0 及以上版本开始，如果 BE 上报的存储路径两者都有且 FE 配置文件中设置了 `storage_cooldown_second`。
+  - 在以下场景中，系统推导该参数为 HDD：
+    - BE 上报的存储路径都是 HDD。
+    - 从 2.3.10，2.4.5，2.5.4，3.0 及以上版本开始，如果 BE 上报的存储路径两者都有且 FE 配置文件中未设置 `storage_cooldown_second`。
+
+- `storage_cooldown_ttl` 或 `storage_cooldown_time`：数据自动降冷的时间间隔或者时间点。数据自动降冷，即数据自动从 SSD 介质迁移到 HDD 介质。只在数据初始存储介质为 SSD 时生效。
+
+  **参数说明**
+
+  - `storage_cooldown_ttl`：该表分区自动降冷**时间间隔**。如果您需要保留最近几个分区在 SSD，其它较早的分区经过一定时间间隔自动降冷至 HDD，则您可以使用该参数，各个分区的自动降冷时间点为该参数值 + 该分区的时间上界。
+  
+      取值为 `<num> YEAR`，`<num> MONTH`，`<num> DAY` 或 `<num> HOUR`。`<num>` 为非负整数。默认值为空，表示该表分区不进行自动降冷。
+  
+      例如建表时指定 `"storage_cooldown_ttl"="1 DAY"`，建表后存在分区 `p20230801` ，其范围为 `[2023-08-01 00:00:00,2023-08-02 00:00:00)`，则该分区的自动降冷时间点是 `2023-08-03 00:00:00`，即 `2023-08-02 00:00:00 + 1 DAY`。如果建表时指定 `"storage_cooldown_ttl"="0 DAY"`，则该分区自动降冷时间点是 `2023-08-02 00:00:00`。
+
+  - `storage_cooldown_time`：该表自动降冷**时间点**（绝对时间）。数据在该时间点之后数据从 SSD 自动降冷到 HDD，设置的时间必须大于当前时间。取值格式为："yyyy-MM-dd HH:mm:ss"。如果需要不同分区具有不同自动降冷时间点，则需要执行 [ALTER TABLE ... ADD PARTITION 或 ALTER TABLE ... MODIFY PARTITION](ALTER_TABLE.md) 手动指定。
+
+  **使用说明**
+
+  - 目前 StarRocks 提供如下数据自动降冷的相关参数，对比如下：
+    - `storage_cooldown_ttl`：表的属性，指定该表中分区自动降冷时间间隔，由系统自动降冷表中到达时间点（时间间隔+分区时间上界）的分区。并且表按照分区粒度自动降冷，更加灵活。
+    - `storage_cooldown_time`：表的属性，指定该表的自动降冷时间点（绝对时间）。建表后也可以为不同分区配置不同时间点。
+    - `storage_cooldown_second`：FE 静态参数，指定集群范围内所有表的自动降冷时延。
+  - 表属性 `storage_cooldown_ttl` 或 `storage_cooldown_time` 比 FE 静态参数 `storage_cooldown_second` 优先级高。
+  - 配置以上参数时，必须指定 `"storage_medium = "SSD"`。
+  - 不配置以上参数时，则不进行自动降冷。
+  - 执行 `SHOW PARTITIONS FROM <table_name>` 查看各个分区的自动降冷时间点。
+
+  **限制**
+  - 不支持表达式分区和 List 分区。
+  - 不支持分区列为非日期类型。
+  - 不支持多个分区列。
+  - 不支持主键表。
+
+**设置分区 Tablet 副本数**
+
+`replication_num`：分区 Tablet 副本数。默认为 3。
+
+```sql
+PROPERTIES (
+    "replication_num" = "<num>"
+)
+```
+
+#### 创建表时为列添加 bloom filter 索引
+
+如果 Engine 类型为 olap, 可以指定某列使用 bloom filter 索引。bloom filter 索引使用时有如下限制：
+
+- 主键表和明细表中所有列都可以创建 Bloom filter 索引；聚合表和更新表中，只有维度列（即 Key 列）支持创建 Bloom filter 索引。
+- 不支持为 TINYINT、FLOAT、DOUBLE 和 DECIMAL 类型的列创建 Bloom filter 索引。
+- Bloom filter 索引只能提高查询条件为 `in` 和 `=` 的查询效率，值越分散效果越好。
+
+更多信息，参见 [Bloom filter 索引](../../../table_design/indexes/Bloomfilter_index.md)。
+
+```sql
+PROPERTIES (
+    "bloom_filter_columns" = "k1, k2, k3"
+)
+```
+
+#### 添加属性支持 Colocate Join
+
+如果希望使用 Colocate Join 特性，需要在 properties 中指定:
+
+``` sql
+PROPERTIES (
+    "colocate_with" = "table1"
+)
+```
+
+详细的 Colocate Join 使用方法及应用场景请参考 [Colocate Join](../../../using_starrocks/Colocate_join.md) 章节。
+
+#### 设置动态分区
+
+如果希望使用动态分区特性，需要在 properties 中指定如下参数：
+
+``` sql
+PROPERTIES (
+    "dynamic_partition.enable" = "true|false",
+    "dynamic_partition.time_unit" = "DAY|WEEK|MONTH",
+    "dynamic_partition.start" = "${integer_value}",
+    "dynamic_partition.end" = "${integer_value}",
+    "dynamic_partition.prefix" = "${string_value}",
+    "dynamic_partition.buckets" = "${integer_value}"
+)
+```
+
+| 参数                          | 是否必填 | 说明                                                         |
+| ----------------------------- | -------- | ------------------------------------------------------------ |
+| `dynamic_partition.enable`    | 否       | 开启动态分区特性，取值为 `TRUE`（默认）或 `FALSE`。       |
+| `dynamic_partition.time_unit` | 是       | 动态分区的时间粒度，取值为 `DAY`、`WEEK` 或 `MONTH`。时间粒度会决定动态创建的分区名后缀格式。  <br />取值为 `DAY` 时，动态创建的分区名后缀格式为 yyyyMMdd，例如 `20200321`。<br />取值为 `WEEK` 时，动态创建的分区名后缀格式为 `yyyy_ww`，例如 `2020_13` 代表 2020 年第 13 周。<br />取值为 `MONTH` 时，动态创建的分区名后缀格式为 yyyyMM，例如 `202003`。 |
+| `dynamic_partition.start`：   | 否       | 保留的动态分区的起始偏移，取值范围为负整数。根据 `dynamic_partition.time_unit` 属性的不同，以当天（周/月）为基准，分区范围在此偏移之前的分区将会被删除。比如设置为`-3`，并且`dynamic_partition.time_unit`为`day`，则表示 3 天前的分区会被删掉。<br />如果不填写，则默认为 `Integer.MIN_VALUE`，即 `-2147483648`，表示不删除历史分区。 |
+| `dynamic_partition.end`       | 是       | 提前创建的分区数量，取值范围为正整数。根据 `dynamic_partition.time_unit` 属性的不同，以当天（周/月）为基准，提前创建对应范围的分区。 |
+| `dynamic_partition.prefix`    | 否       | 动态分区的前缀名，默认值为 `p`。                             |
+| dynamic_partition.buckets     | 否       | 动态分区的分桶数量。默认与 BUCKETS 保留字指定的分桶数量、或者 StarRocks 自动设置的分桶数量保持一致。 |
+
+#### 设置随机分桶表中分桶大小 (`bucket_size`)
+
+自 3.2 版本起，对于随机分桶的表，您可以在建表时在 `PROPERTIES` 中设置 `bucket_size` 参数来指定分桶大小，启用按需动态增加分桶数量。单位为 B。
+
+``` sql
+PROPERTIES (
+    "bucket_size" = "1073741824"
+)
+```
+
+#### 设置数据压缩算法
+
+您可以在建表时通过增加属性 `compression` 为该表指定数据压缩算法。
+
+`compression` 有效值包括：
+
+- `LZ4`：LZ4 算法。
+- `ZSTD`：Zstandard 算法。
+- `ZLIB`：zlib 算法。
+- `SNAPPY`：Snappy 算法。
+
+如不指定数据压缩算法，StarRocks 默认使用 LZ4。
+
+自 v3.3.2 起，StarRocks 支持在建表时指定 ZSTD 压缩格式的压缩级别。
+
+语法：
+
+```sql
+PROPERTIES ("compression" = "zstd(<compression_level>)")
+```
+
+`compression_level`：ZSTD 压缩格式的压缩级别。类型：Integer。范围：[1,22]。默认值：`3`（推荐）。数字越大，压缩率越高。压缩级别越高，压缩和解压的耗时越大。
+
+示例：
+
+```sql
+PROPERTIES ("compression" = "zstd(3)")
+```
+
+关于如何选择合适的数据压缩算法，请参阅[数据压缩](../../../table_design/data_compression.md)。
+
+#### 设置数据导入安全等级
+
+如果您的 StarRocks 集群有多数据副本，可以在建表时在 `PROPERTIES` 中设置 `write_quorum` 参数来指定数据导入安全等级，即设置需要多少数据副本导入成功后 StarRocks 可返回导入成功。该属性从 2.5 版本开始支持。
+
+`write_quorum` 的取值及其对应描述如下：
+
+- `MAJORITY`：默认值。当**多数**数据副本导入成功时，StarRocks 返回导入成功，否则返回失败。
+- `ONE`：当**一个**数据副本导入成功时，StarRocks 返回导入成功，否则返回失败。
+- `ALL`：当**所有**数据副本导入成功时，StarRocks 返回导入成功，否则返回失败。
+
+> **注意**
+>
+> - 设置较低的导入数据安全等级会增加数据不可访问甚至丢失的风险。例如，在 StarRocks 集群有两个数据副本的情况下设置 `write_quorum` 为 `ONE`，如果某个 Tablet 实际只成功导入了一个副本，而此副本所在机器后续下线，则会导致该 Tablet 中的数据因为没有存活副本而无法访问。如果服务器磁盘受损，则会导致该 Tablet 中的数据丢失。
+> - 仅当所有数据副本返回导入状态后，StarRocks 才会返回导入任务状态。当有副本导入状态未知时，StarRocks 不会返回导入任务状态。导入超时的副本亦会被标记为失败。
+
+#### 指定数据在多副本间的写入和同步方式
+
+如果您的 StarRocks 集群有多数据副本，可以在建表时在 `PROPERTIES` 中设置 `replicated_storage` 参数来指定数据在多副本间的写入和同步方式。
+
+- 设置为 `true`（3.0 及后续版本的默认值）表示 single leader replication，即数据只写入到主副本 (primary replica)，由主副本同步数据到从副本 (secondary replica)。该模式能有效降低多副本写入带来的 CPU 成本。该模式从 2.5 版本开始支持。
+- 设置为 `false`（2.5 版本的默认值）表示 leaderless replication，即数据直接写入到多个副本，不区分主从副本。该模式 CPU 成本比较高。
+
+默认配置在绝大部分场景下能获得更好的写入性能，如果要修改已有表的多副本写入和同步方式，可执行 ALTER TABLE 命令，举例：
+
+```sql
+ALTER TABLE example_db.my_table
+SET ("replicated_storage" = "true");
+```
+
+#### 建表时批量创建多个 Rollup
+
+语法：
+
+```sql
+ROLLUP (rollup_name (column_name1, column_name2, ...)
+[FROM from_index_name]
+[PROPERTIES ("key" = "value", ...)],...)
+```
+
+#### 为 View Delta Join 查询改写定义 Unique Key 和外键约束
+
+要在 View Delta Join 场景中启用查询重写，您必须为 Delta Join 中的表定义 Unique Key 约束 `unique_constraints` 和外键约束 `foreign_key_constraints`。详细信息，请参阅 [异步物化视图 - 基于 View Delta Join 场景改写查询](../../../using_starrocks/query_rewrite_with_materialized_views.md#view-delta-join-改写)。
+
+```SQL
+PROPERTIES (
+    "unique_constraints" = "<unique_key>[, ...]",
+    "foreign_key_constraints" = "
+    (<child_column>[, ...]) 
+    REFERENCES 
+    [catalog_name].[database_name].<parent_table_name>(<parent_column>[, ...])
+    [;...]
+    "
+)
+```
+
+- `child_column`：当前表中的外键列。 您可以定义多个 `child_column`。
+- `catalog_name`：待 Join 表所在的数据目录名。未指定此参数时使用默认目录。
+- `database_name`：待 Join 表所在的数据库名。未指定此参数时使用当前数据库。
+- `parent_table_name`：待 Join 表名。
+- `parent_column`：待 Join 列名，必须为相应表的 Primary Key 或 Unique Key。
+
+> **注意**
+>
+> - `unique_constraints` 约束和 `foreign_key_constraints` 约束仅用于查询重写。导入数据时，不保证进行外键约束校验。您必须确保导入的数据满足约束条件。
+> - 主键表的 Primary Key 或更新表的 Unique Key 默认是其 `unique_constraints`，您无需手动设置。
+> - `foreign_key_constraints` 中的 `child_column` 必须对应另一个表的 `unique_constraints` 中的 `unique_key`。
+> - `child_column` 和 `parent_column` 的数量必须一致。
+> - `child_column` 和对应的 `parent_column` 的数据类型必须匹配。
+
+#### 为 StarRocks 存算分离集群创建云原生表
+
+为了[使用 StarRocks 存算分离集群](../../../deployment/shared_data/shared_data.mdx)，您需要通过以下 PROPERTIES 创建云原生表：
+
+```SQL
+PROPERTIES (
+    "storage_volume" = "<storage_volume_name>",
+    "datacache.enable" = "{ true | false }",
+    "datacache.partition_duration" = "<string_value>",
+    "enable_async_write_back" = "{ true | false }"
+)
+```
+
+- `storage_volume`：建表使用的 Storage Volume 名称。该属性自 v3.1 版本起支持。如果未指定该属性，则使用默认 Storage Volume。示例：`"storage_volume" = "def_volume"`。
+
+- `datacache.enable`：是否启用本地磁盘缓存。默认值：`true`。
+
+  - 当该属性设置为 `true` 时，数据会同时导入对象存储（或 HDFS）和本地磁盘（作为查询加速的缓存）。
+  - 当该属性设置为 `false` 时，数据仅导入到对象存储中。
+
+  > **说明**
+  >
+  > 如需启用本地磁盘缓存，必须在 BE 配置项 `storage_root_path` 中指定磁盘目录。更多信息，请参见 [BE 配置项](../../../administration/management/BE_configuration.md)。
+
+- `datacache.partition_duration`：热数据的有效期。当启用本地磁盘缓存时，所有数据都会导入至本地磁盘缓存中。当缓存满时，StarRocks 会从缓存中删除最近较少使用（Less recently used）的数据。当有查询需要扫描已删除的数据时，StarRocks 会检查该数据是否在有效期内。如果数据在有效期内，StarRocks 会再次将数据导入至缓存中。如果数据不在有效期内，StarRocks 不会将其导入至缓存中。该属性为字符串，您可以使用以下单位指定：`YEAR`、`MONTH`、`DAY` 和 `HOUR`，例如，`7 DAY` 和 `12 HOUR`。如果不指定，StarRocks 将所有数据都作为热数据进行缓存。
+
+  > **说明**
+  >
+  > 仅当 `datacache.enable` 设置为 `true` 时，此属性可用。
+
+- `enable_async_write_back`：是否允许数据异步写入对象存储。默认值：`false`。
+
+  - 当该属性设置为 `true` 时，导入任务在数据写入本地磁盘缓存后立即返回成功，数据将异步写入对象存储。允许数据异步写入可以提升导入性能，但如果系统发生故障，可能会存在一定的数据可靠性风险。
+  - 当该属性设置为 `false` 时，只有在数据同时写入对象存储和本地磁盘缓存后，导入任务才会返回成功。禁用数据异步写入保证了更高的可用性，但会导致较低的导入性能。
+
+#### 设置 fast schema evolution
+
+`fast_schema_evolution`: 是否开启该表的 fast schema evolution，取值：`TRUE` 或 `FALSE`（默认）。开启后增删列时可以提高 schema change 速度并降低资源使用。目前仅支持在建表时开启该属性，建表后不支持通过 [ALTER TABLE](ALTER_TABLE.md) 修改该属性。
+
+> **NOTE**
+>
+> - StarRocks 存算一体集群自 v3.2.0 版本起支持该参数，存算分离集群自 v3.3.0 起支持该参数。
+> - 如果您需要在集群范围内设置该配置，例如集群范围内关闭 fast schema evolution，则可以设置 FE 动态参数 [`enable_fast_schema_evolution`](../../../administration/management/FE_configuration.md#enable_fast_schema_evolution)。
+
+## 示例
+
+### 创建 Hash 分桶表并根据 key 列对数据进行聚合
+
+创建一个 olap 表，使用 Hash 分桶，使用列存，相同 key 的记录进行聚合。
+
+``` sql
+CREATE TABLE example_db.table_hash
+(
+    k1 TINYINT,
+    k2 DECIMAL(10, 2) DEFAULT "10.5",
+    v1 CHAR(10) REPLACE,
+    v2 INT SUM
+)
+ENGINE = olap
+AGGREGATE KEY(k1, k2)
+COMMENT "my first starrocks table"
+DISTRIBUTED BY HASH(k1)
+PROPERTIES ("storage_type" = "column");
+```
+
+### 创建表并设置存储介质和数据自动降冷时间
+
+创建一个 olap 表，使用 Hash 分桶，使用列存，相同 key 的记录进行覆盖，设置初始存储介质和冷却时间。
+
+``` sql
+CREATE TABLE example_db.table_hash
+(
+    k1 BIGINT,
+    k2 LARGEINT,
+    v1 VARCHAR(2048) REPLACE,
+    v2 SMALLINT DEFAULT "10"
+)
+ENGINE = olap
+UNIQUE KEY(k1, k2)
+DISTRIBUTED BY HASH (k1, k2)
+PROPERTIES(
+    "storage_type" = "column",
+    "storage_medium" = "SSD",
+    "storage_cooldown_time" = "2025-06-04 00:00:00"
+);
+```
+
+或
+
+``` sql
+CREATE TABLE example_db.table_hash
+(
+    k1 BIGINT,
+    k2 LARGEINT,
+    v1 VARCHAR(2048) REPLACE,
+    v2 SMALLINT DEFAULT "10"
+)
+ENGINE = olap
+PRIMARY KEY(k1, k2)
+DISTRIBUTED BY HASH (k1, k2)
+PROPERTIES(
+    "storage_type" = "column",
+    "storage_medium" = "SSD",
+    "storage_cooldown_time" = "2025-06-04 00:00:00"
+);
+```
+
+### 创建分区表
+
+创建一个 olap 表，使用 Range 分区，使用 Hash 分桶，默认使用列存，相同 key 的记录同时存在，设置初始存储介质和冷却时间。
+
+使用 LESS THAN 方式按照范围划分分区：
+
+``` sql
+CREATE TABLE example_db.table_range
+(
+    k1 DATE,
+    k2 INT,
+    k3 SMALLINT,
+    v1 VARCHAR(2048),
+    v2 DATETIME DEFAULT "2014-02-04 15:36:00"
+)
+ENGINE = olap
+DUPLICATE KEY(k1, k2, k3)
+PARTITION BY RANGE (k1)
+(
+    PARTITION p1 VALUES LESS THAN ("2014-01-01"),
+    PARTITION p2 VALUES LESS THAN ("2014-06-01"),
+    PARTITION p3 VALUES LESS THAN ("2014-12-01")
+)
+DISTRIBUTED BY HASH(k2)
+PROPERTIES(
+    "storage_medium" = "SSD",
+    "storage_cooldown_time" = "2025-06-04 00:00:00"
+);
+```
+
+说明：
+这个语句会将数据划分成如下 3 个分区：
+
+``` sql
+( {    MIN     },   {"2014-01-01"} )
+[ {"2014-01-01"},   {"2014-06-01"} )
+[ {"2014-06-01"},   {"2014-12-01"} )
+```
+
+不在这些分区范围内的数据将视为非法数据被过滤。
+
+使用 Fixed Range 方式创建分区：
+
+``` sql
+CREATE TABLE table_range
+(
+    k1 DATE,
+    k2 INT,
+    k3 SMALLINT,
+    v1 VARCHAR(2048),
+    v2 DATETIME DEFAULT "2014-02-04 15:36:00"
+)
+ENGINE = olap
+DUPLICATE KEY(k1, k2, k3)
+PARTITION BY RANGE (k1, k2, k3)
+(
+    PARTITION p1 VALUES [("2014-01-01", "10", "200"), ("2014-01-01", "20", "300")),
+    PARTITION p2 VALUES [("2014-06-01", "100", "200"), ("2014-07-01", "100", "300"))
+)
+DISTRIBUTED BY HASH(k2)
+PROPERTIES(
+    "storage_medium" = "SSD"
+);
+```
+
+### 创建一个 MySQL 外表
+
+``` sql
+CREATE EXTERNAL TABLE example_db.table_mysql
+(
+    k1 DATE,
+    k2 INT,
+    k3 SMALLINT,
+    k4 VARCHAR(2048),
+    k5 DATETIME
+)
+ENGINE = mysql
+PROPERTIES
+(
+    "host" = "127.0.0.1",
+    "port" = "8239",
+    "user" = "mysql_user",
+    "password" = "mysql_passwd",
+    "database" = "mysql_db_test",
+    "table" = "mysql_table_test"
+);
+```
+
+### 创建一张含有 HLL 列的表
+
+``` sql
+CREATE TABLE example_db.example_table
+(
+    k1 TINYINT,
+    k2 DECIMAL(10, 2) DEFAULT "10.5",
+    v1 HLL HLL_UNION,
+    v2 HLL HLL_UNION
+)
+ENGINE = olap
+AGGREGATE KEY(k1, k2)
+DISTRIBUTED BY HASH(k1)
+PROPERTIES ("storage_type" = "column");
+```
+
+### 创建一张含有 `BITMAP_UNION` 聚合类型的表
+
+v1 和 v2 列的原始数据类型必须是 `TINYINT, SMALLINT, INT`。
+
+``` sql
+CREATE TABLE example_db.example_table
+(
+    k1 TINYINT,
+    k2 DECIMAL(10, 2) DEFAULT "10.5",
+    v1 BITMAP BITMAP_UNION,
+    v2 BITMAP BITMAP_UNION
+)
+ENGINE = olap
+AGGREGATE KEY(k1, k2)
+DISTRIBUTED BY HASH(k1)
+PROPERTIES ("storage_type" = "column");
+```
+
+### 创建两张支持 Colocate Join 的表
+
+创建 t1 和 t2 两个表，两表可进行 Colocate Join。两表属性中的 `colocate_with` 属性的值需保持一致。
+
+``` sql
+CREATE TABLE `t1` (
+    `id` int(11) COMMENT "",
+    `value` varchar(8) COMMENT ""
+) ENGINE = OLAP
+DUPLICATE KEY(`id`)
+DISTRIBUTED BY HASH(`id`)
+PROPERTIES (
+    "colocate_with" = "t1"
+);
+
+CREATE TABLE `t2` (
+    `id` int(11) COMMENT "",
+    `value` varchar(8) COMMENT ""
+) ENGINE = OLAP
+DUPLICATE KEY(`id`)
+DISTRIBUTED BY HASH(`id`)
+PROPERTIES (
+    "colocate_with" = "t1"
+);
+```
+
+### 创建一个带有 bitmap 索引的表
+
+``` sql
+CREATE TABLE example_db.table_hash
+(
+    k1 TINYINT,
+    k2 DECIMAL(10, 2) DEFAULT "10.5",
+    v1 CHAR(10) REPLACE,
+    v2 INT SUM,
+    INDEX k1_idx (k1) USING BITMAP COMMENT 'xxxxxx'
+)
+ENGINE = olap
+AGGREGATE KEY(k1, k2)
+COMMENT "my first starrocks table"
+DISTRIBUTED BY HASH(k1)
+PROPERTIES ("storage_type" = "column");
+```
+
+### 创建动态分区表
+
+ 创建动态分区表需要在 FE 配置中开启 **动态分区** 功能（`"dynamic_partition.enable" = "true"`），参数可参见本文[设置动态分区](#设置动态分区)。
+
+ 该表每天提前创建 3 天的分区，并删除 3 天前的分区。例如今天为 `2020-01-08`，则会创建分区名为 `p20200108`，`p20200109`，`p20200110`，`p20200111` 的分区. 分区范围分别为:
+
+```plain text
+[types: [DATE]; keys: [2020-01-08]; ‥types: [DATE]; keys: [2020-01-09]; )
+[types: [DATE]; keys: [2020-01-09]; ‥types: [DATE]; keys: [2020-01-10]; )
+[types: [DATE]; keys: [2020-01-10]; ‥types: [DATE]; keys: [2020-01-11]; )
+[types: [DATE]; keys: [2020-01-11]; ‥types: [DATE]; keys: [2020-01-12]; )
+```
+
+```sql
+CREATE TABLE example_db.dynamic_partition
+(
+    k1 DATE,
+    k2 INT,
+    k3 SMALLINT,
+    v1 VARCHAR(2048),
+    v2 DATETIME DEFAULT "2014-02-04 15:36:00"
+)
+ENGINE = olap
+DUPLICATE KEY(k1, k2, k3)
+PARTITION BY RANGE (k1)
+(
+    PARTITION p1 VALUES LESS THAN ("2014-01-01"),
+    PARTITION p2 VALUES LESS THAN ("2014-06-01"),
+    PARTITION p3 VALUES LESS THAN ("2014-12-01")
+)
+DISTRIBUTED BY HASH(k2)
+PROPERTIES(
+    "storage_medium" = "SSD",
+    "dynamic_partition.time_unit" = "DAY",
+    "dynamic_partition.start" = "-3",
+    "dynamic_partition.end" = "3",
+    "dynamic_partition.prefix" = "p"
+);
+```
+
+### 创建一个 Hive 外部表
+
+``` SQL
+CREATE EXTERNAL TABLE example_db.table_hive
+(
+    k1 TINYINT,
+    k2 VARCHAR(50),
+    v INT
+)
+ENGINE = hive
+PROPERTIES
+(
+    "resource" = "hive0",
+    "database" = "hive_db_name",
+    "table" = "hive_table_name"
+);
+```
+
+### 创建一张主键表并且指定排序键
+
+假设需要按地域、最近活跃时间实时分析用户情况，则可以将表示用户 ID 的 `user_id` 列作为主键，表示地域的 `address` 列和表示最近活跃时间的 `last_active` 列作为排序键。建表语句如下：
+
+```SQL
+create table users (
+    user_id bigint NOT NULL,
+    name string NOT NULL,
+    email string NULL,
+    address string NULL,
+    age tinyint NULL,
+    sex tinyint NULL,
+    last_active datetime,
+    property0 tinyint NOT NULL,
+    property1 tinyint NOT NULL,
+    property2 tinyint NOT NULL,
+    property3 tinyint NOT NULL
+) 
+PRIMARY KEY (`user_id`)
+DISTRIBUTED BY HASH(`user_id`)
+ORDER BY(`address`,`last_active`)
+PROPERTIES(
+    "replication_num" = "3",
+    "enable_persistent_index" = "true"
+);
+```
+
+## References
+
+- [SHOW CREATE TABLE](SHOW_CREATE_TABLE.md)
+- [SHOW TABLES](SHOW_TABLES.md)
+- [USE](../Database/USE.md)
+- [ALTER TABLE](ALTER_TABLE.md)
+- [DROP TABLE](DROP_TABLE.md)
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md
new file mode 100644
index 00000000000000..bc4085f0822005
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md
@@ -0,0 +1,259 @@
+---
+displayed_sidebar: docs
+keywords: ['CTAS']
+---
+
+# CREATE TABLE AS SELECT
+
+## 功能
+
+CREATE TABLE AS SELECT（简称 CTAS）语句可用于同步或异步查询原表并基于查询结果创建新表，然后将查询结果插入到新表中。
+
+您可以通过 [SUBMIT TASK](../loading_unloading/ETL/SUBMIT_TASK.md) 创建异步 CTAS 任务。
+
+## 语法
+
+- 同步查询原表并基于查询结果创建新表，然后将查询结果插入到新表中。
+
+  ```SQL
+  CREATE [TEMPORARY] TABLE [IF NOT EXISTS] [database.]table_name
+  [column_name1 [, column_name2, ...]]
+  [index_definition1 [, index_definition2, ...]]
+  [key_desc]
+  [COMMENT "table comment"]
+  [partition_desc]
+  [distribution_desc]
+  [ORDER BY (column_name1 [, column_name2, ...])]
+  [PROPERTIES ("key"="value", ...)]AS SELECT query
+  [ ... ]
+  ```
+
+- 异步查询原表并基于查询结果创建新表，然后将查询结果插入到新表中。
+
+  ```SQL
+  SUBMIT [/*+ SET_VAR(key=value) */] TASK [[database.]<task_name>]AS
+  CREATE TABLE [IF NOT EXISTS] [database.]table_name
+  [column_name1 [, column_name2, ...]]
+  [index_definition1 [, index_definition2, ...]]
+  [key_desc]
+  [COMMENT "table comment"]
+  [partition_desc]
+  [distribution_desc]
+  [ORDER BY (column_name1 [, column_name2, ...])]
+  [PROPERTIES ("key"="value", ...)] AS SELECT query
+  [ ... ]
+  ```
+
+## 参数说明
+
+| **参数**          | **必填** | **描述**                                                     |
+| ----------------- | -------- | ------------------------------------------------------------ |
+| TEMPORARY         | 否       | 创建临时表。从 v3.3.1 版本开始，StarRocks 支持在 Default Catalog 中创建临时表。更多信息，请参见 [临时表](../../../table_design/StarRocks_table_design.md#临时表)。目前，StarRocks 不支持通过 SUBMIT TASK 发起异步任务创建临时表。 |
+| column_name       | 否       | 新表的列名。您无需指定列类型。StarRocks 会自动选择合适的列类型，并将 FLOAT 和 DOUBLE 转换为 DECIMAL(38,9)；将 CHAR、VARCHAR 和 STRING 转换为 VARCHAR(65533)。 |
+| index_definition  | 否       | 自 3.1.8 开始支持为新表创建 Bitmap 索引，语法是 `INDEX index_name (col_name[, col_name, ...]) [USING BITMAP] [COMMENT '']`。有关参数说明和使用限制，请参见 [Bitmap 索引](../../../table_design/indexes/Bitmap_index.md)。|
+| key_desc          | 否       | 语法是 `key_type (<col_name1> [, <col_name2>, ...])`。<br />**参数**：<ul><li>`key_type`：新表的 Key 类型。有效值：`DUPLICATE KEY` 和 `PRIMARY KEY`。默认值：`DUPLICATE KEY`。</li><li> `col_name`：组成 Key 的列。</li></ul>|
+| COMMENT           | 否       | 新表注释。                                                   |
+| partition_desc    | 否       | 新表的分区方式。如不指定该参数，则默认新表为无分区。更多有关分区的设置，参见 [CREATE TABLE](CREATE_TABLE.md#partition_desc)。 |
+| distribution_desc | 否       | 新表的分桶方式。如不指定该参数，则默认新表的分桶列为使用 CBO 优化器采集的统计信息中基数最高的列，且分桶数量默认为 10。如果 CBO 优化器没有采集基数信息，则默认新表的第一列为分桶列。更多有关分桶的设置，参见 [CREATE TABLE](CREATE_TABLE.md#distribution_desc)。 |
+| ORDER BY| 否       |自 v3.1.8 版本以来，如果新表是主键表，则可以为新表指定排序键。排序键可以是任意列的组合。主键表是指在创建表时指定了 `PRIMARY KEY (xxx)` 的表。| 
+| Properties        | 否       | 新表的属性。                                                 |
+| AS SELECT query   | 是       | 查询结果。该参数支持如下值： 列。比如 `... AS SELECT a, b, c FROM table_a;`，其中 `a`、`b` 和 `c` 为原表的列名。如果您没有为新表指定列名，那么新表的列名也为 `a`、`b` 和 `c`。 表达式。比如 `... AS SELECT a+1 AS x, b+2 AS y, c*c AS z FROM table_a;`，其中 `a+1`、`b+2` 和 `c*c` 为原表的列名，`x`、`y` 和 `z` 为新表的列名。 说明： 新表的列数需要与 `AS SELECT query` 中指定的列数保持一致。 建议您为新表的列设置具有业务意义的列名，便于后续识别使用。 |
+
+## 注意事项
+
+- 使用 CTAS 语句创建的新表需满足如下条件：
+  - `ENGINE` 类型为 `OLAP`。
+
+  - 表类型默认为明细表，您也可以在 `key_desc` 中指定为主键表。
+
+  - 排序列为前三列且这三列类型的存储空间不能超过 36 个字节。
+
+- CTAS 语句不支持为新表设置索引。
+
+- 如果 CTAS 语句由于 FE 重启或其他原因执行失败，可能会发生如下情况：
+  - 新表创建成功，但表中没有数据。
+
+  - 新表创建失败。
+
+- 新表创建后，如果存在多种方式（比如 Insert Into）将数据插入到新表中，那么最先执行完插入操作的即最先将数据插入到新表中。
+
+- 新表创建成功后，您需要手动授予用户对该表的权限。参见 [表权限](../../../administration/user_privs/privilege_item.md#表权限-table) 和 [GRANT](../account-management/GRANT.md)。
+- 当异步查询原表并基于查询结果创建新表时，如果不指定 Task 名称，那么 StarRocks 会自动生成一个 Task 名称。
+
+## 示例
+
+示例一：同步查询原表 `order` 并根据查询结果创建新表 `order_new`，然后将查询结果插入到新表中。
+
+```SQL
+CREATE TABLE order_new
+AS SELECT * FROM order;
+```
+
+示例二：同步查询原表 `order`中的 `k1`、`k2` 和 `k3` 列并根据查询结果创建新表 `order_new`，然后将查询结果插入到新表中，并指定新表中列的名称为 `a`、`b` 和 `c`。
+
+```SQL
+CREATE TABLE order_new (a, b, c)
+AS SELECT k1, k2, k3 FROM order;
+```
+
+或
+
+```SQL
+CREATE TABLE order_new
+AS SELECT k1 AS a, k2 AS b, k3 AS c FROM order;
+```
+
+示例三：同步查询原表 `employee`中 `salary` 列的最大值并根据查询结果创建新表 `employee_new` ，然后将查询结果插入到新表中，并指定新表中列名为 `salary_new`。
+
+```SQL
+CREATE TABLE employee_new
+AS SELECT MAX(salary) AS salary_max FROM employee;
+```
+
+插入完成后，查询新表 `employee_new`。
+
+```SQL
+SELECT * FROM employee_new;
+
++------------+
+| salary_max |
++------------+
+|   10000    |
++------------+
+```
+
+示例四：同步查询原表 `customers` 中的 `customer_id` 和 `first_name` 列并根据查询结果创建新表 `customers_new`，然后将查询结果插入到新表中，并指定新表中列的名称为 `customer_id_new` 和 `first_name_new`。同时在新表中基于列 `customer_id_new` 构建 Bitmap 索引。
+
+```SQL
+CREATE TABLE customers_new 
+(   customer_id_new,
+    first_name_new,
+    INDEX idx_bitmap_customer_id (customer_id_new) USING BITMAP
+) 
+AS SELECT customer_id,first_name FROM customers;
+```
+
+示例五：同步查询原表 `customers` 并根据查询结果创建新表 `customers_new`，然后将查询结果插入到新表中。 并且指定新表为主键表并且指定其排序键为 `first_name` 和 `last_name`。
+
+```SQL
+CREATE TABLE customers_pk
+PRIMARY KEY (customer_id)
+ORDER BY (first_name,last_name)
+AS SELECT  * FROM customers;
+```
+
+示例六：使用 CTAS 创建一张主键表。需要注意的是，主键表中的数据行数可能会比查询结果中的数据行数少。这是因为主键表只存储具有相同主键的一组数据行中最新的一条数据行。
+
+```SQL
+CREATE TABLE employee_new
+PRIMARY KEY(order_id)
+AS SELECT
+    order_list.order_id,
+    sum(goods.price) as total
+FROM order_list INNER JOIN goods ON goods.item_id1 = order_list.item_id2
+GROUP BY order_id;
+```
+
+示例七：同步查询四张原表 `lineorder`、`customer`、`supplier` 和 `part` 并根据查询结果创建新表 `lineorder_flat`，然后将查询结果插入到新表中，并指定新表的分区和分桶方式。
+
+```SQL
+CREATE TABLE lineorder_flat
+PARTITION BY RANGE (`LO_ORDERDATE`)
+(
+    START ("1993-01-01") END ("1999-01-01") EVERY (INTERVAL 1 YEAR)
+)
+DISTRIBUTED BY HASH (`LO_ORDERKEY`) AS SELECT
+    l.LO_ORDERKEY AS LO_ORDERKEY,
+    l.LO_LINENUMBER AS LO_LINENUMBER,
+    l.LO_CUSTKEY AS LO_CUSTKEY,
+    l.LO_PARTKEY AS LO_PARTKEY,
+    l.LO_SUPPKEY AS LO_SUPPKEY,
+    l.LO_ORDERDATE AS LO_ORDERDATE,
+    l.LO_ORDERPRIORITY AS LO_ORDERPRIORITY,
+    l.LO_SHIPPRIORITY AS LO_SHIPPRIORITY,
+    l.LO_QUANTITY AS LO_QUANTITY,
+    l.LO_EXTENDEDPRICE AS LO_EXTENDEDPRICE,
+    l.LO_ORDTOTALPRICE AS LO_ORDTOTALPRICE,
+    l.LO_DISCOUNT AS LO_DISCOUNT,
+    l.LO_REVENUE AS LO_REVENUE,
+    l.LO_SUPPLYCOST AS LO_SUPPLYCOST,
+    l.LO_TAX AS LO_TAX,
+    l.LO_COMMITDATE AS LO_COMMITDATE,
+    l.LO_SHIPMODE AS LO_SHIPMODE,
+    c.C_NAME AS C_NAME,
+    c.C_ADDRESS AS C_ADDRESS,
+    c.C_CITY AS C_CITY,
+    c.C_NATION AS C_NATION,
+    c.C_REGION AS C_REGION,
+    c.C_PHONE AS C_PHONE,
+    c.C_MKTSEGMENT AS C_MKTSEGMENT,
+    s.S_NAME AS S_NAME,
+    s.S_ADDRESS AS S_ADDRESS,
+    s.S_CITY AS S_CITY,
+    s.S_NATION AS S_NATION,
+    s.S_REGION AS S_REGION,
+    s.S_PHONE AS S_PHONE,
+    p.P_NAME AS P_NAME,
+    p.P_MFGR AS P_MFGR,
+    p.P_CATEGORY AS P_CATEGORY,
+    p.P_BRAND AS P_BRAND,
+    p.P_COLOR AS P_COLOR,
+    p.P_TYPE AS P_TYPE,
+    p.P_SIZE AS P_SIZE,
+    p.P_CONTAINER AS P_CONTAINER FROM lineorder AS l 
+INNER JOIN customer AS c ON c.C_CUSTKEY = l.LO_CUSTKEY
+INNER JOIN supplier AS s ON s.S_SUPPKEY = l.LO_SUPPKEY
+INNER JOIN part AS p ON p.P_PARTKEY = l.LO_PARTKEY;
+```
+
+示例八：异步查询原表 `order_detail` 并根据查询结果创建新表 `order_statistics`，然后将查询结果插入到新表中。
+
+```Plain_Text
+SUBMIT TASK AS CREATE TABLE order_statistics AS SELECT COUNT(*) as count FROM order_detail;
+
++-------------------------------------------+-----------+
+| TaskName                                  | Status    |
++-------------------------------------------+-----------+
+| ctas-df6f7930-e7c9-11ec-abac-bab8ee315bf2 | SUBMITTED |
++-------------------------------------------+-----------+
+```
+
+查询 Task 的信息。
+
+```SQL
+SELECT * FROM INFORMATION_SCHEMA.tasks;
+
+-- Task 信息如下
+
+TASK_NAME: ctas-df6f7930-e7c9-11ec-abac-bab8ee315bf2
+CREATE_TIME: 2022-06-14 14:07:06
+SCHEDULE: MANUAL
+DATABASE: default_cluster:test
+DEFINITION: CREATE TABLE order_statistics AS SELECT COUNT(*) as cnt FROM order_detail
+EXPIRE_TIME: 2022-06-17 14:07:06
+```
+
+查询 TaskRun 的状态。
+
+```SQL
+SELECT * FROM INFORMATION_SCHEMA.task_runs;
+
+--TaskRun 的状态如下
+
+QUERY_ID: 37bd2b63-eba8-11ec-8d41-bab8ee315bf2
+TASK_NAME: ctas-df6f7930-e7c9-11ec-abac-bab8ee315bf2
+CREATE_TIME: 2022-06-14 14:07:06
+FINISH_TIME: 2022-06-14 14:07:07
+STATE: SUCCESS
+DATABASE: 
+DEFINITION: CREATE TABLE order_statistics AS SELECT COUNT(*) as cnt FROM order_detail
+EXPIRE_TIME: 2022-06-17 14:07:06
+ERROR_CODE: 0
+ERROR_MESSAGE: NULL
+```
+
+当 TaskRun 的状态为 `SUCCESS` 时即可查询新表。
+
+```SQL
+SELECT * FROM order_statistics;
+```
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_LIKE.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_LIKE.md
new file mode 100644
index 00000000000000..76b5c518a53e57
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_LIKE.md
@@ -0,0 +1,158 @@
+---
+displayed_sidebar: docs
+---
+
+# CREATE TABLE LIKE
+
+## 功能
+
+该语句用于创建一个表结构和另一张表完全相同的空表。复制的表结构包括 Column Definition、Partitions、Table Properties 等。支持复制 MySQL 等外表。
+
+自 3.2 版本起支持为新表指定不同的分区方式、分桶方式、或属性。
+
+:::tip
+该操作需要有在目标数据库下 CREATE TABLE 的权限，对要复制的原表有 `SELECT` 权限。权限控制请参考 [GRANT](../account-management/GRANT.md) 章节。
+:::
+
+## 语法
+
+- 3.2 版本之前支持的语法
+
+```sql
+CREATE [EXTERNAL] TABLE [IF NOT EXISTS] [database.]<table_name>
+LIKE [database.]<source_table_name>
+```
+
+- 3.2 版本起支持为新表指定分区方式、分桶方式、属性
+
+```sql
+CREATE [TEMPORARY] [EXTERNAL] TABLE [IF NOT EXISTS] [database.]<table_name>
+[partition_desc]
+[distribution_desc]
+[PROPERTIES ("key" = "value",...)]
+LIKE [database.]<source_table_name>
+```
+
+## 参数说明
+
+- `TEMPORARY`：创建临时表。从 v3.3.1 版本开始，StarRocks 支持在 Default Catalog 中创建临时表。更多信息，请参见 [临时表](../../../table_design/StarRocks_table_design.md#临时表)。
+- `database`：数据库。
+- `table_name`：要创建的表的名称。有关表名的命令要求，参见[系统限制](../../System_limit.md)。
+- `source_table_name`：要拷贝的表的名称。
+- `partition_desc`：分区方式。更多信息，参见 [CREATE TABLE](CREATE_TABLE.md#partition_desc)。
+- `distribution_desc`：分桶方式。更多信息，参见 [CREATE TABLE](CREATE_TABLE.md#distribution_desc)。
+- `PROPERTIES`：表的属性。支持所有表属性。更多信息，参见 [ALTER TABLE](ALTER_TABLE.md#修改表的属性)。
+
+## 示例
+
+假设数据库 `test1` 下有表 `orders`。
+
+```sql
+create table orders (
+    dt date NOT NULL,
+    order_id bigint NOT NULL,
+    user_id int NOT NULL,
+    merchant_id int NOT NULL,
+    good_id int NOT NULL,
+    good_name string NOT NULL,
+    price int NOT NULL,
+    cnt int NOT NULL,
+    revenue int NOT NULL,
+    state tinyint NOT NULL
+) PRIMARY KEY (dt, order_id)
+PARTITION BY RANGE(`dt`) (
+    PARTITION p20210820 VALUES [('2021-08-20'), ('2021-08-21')),
+    PARTITION p20210821 VALUES [('2021-08-21'), ('2021-08-22')),
+    PARTITION p20210929 VALUES [('2021-09-29'), ('2021-09-30')),
+    PARTITION p20210930 VALUES [('2021-09-30'), ('2021-10-01'))
+) DISTRIBUTED BY HASH(order_id)
+PROPERTIES (
+    "replication_num" = "3",
+    "enable_persistent_index" = "true"
+);
+```
+
+示例一：在 `test1` 库下创建一张表结构和 `orders` 完全相同的空表，表名为 `order_1`。
+
+```sql
+CREATE TABLE test1.order_1 LIKE test1.orders;
+```
+
+可以看到 `order_1` 和 `orders` 表结构完全相同。
+
+```plaintext
+show create table order_1\G
+*************************** 1. row ***************************
+       Table: order_1
+Create Table: CREATE TABLE `order_1` (
+  `dt` date NOT NULL COMMENT "",
+  `order_id` bigint(20) NOT NULL COMMENT "",
+  `user_id` int(11) NOT NULL COMMENT "",
+  `merchant_id` int(11) NOT NULL COMMENT "",
+  `good_id` int(11) NOT NULL COMMENT "",
+  `good_name` varchar(65533) NOT NULL COMMENT "",
+  `price` int(11) NOT NULL COMMENT "",
+  `cnt` int(11) NOT NULL COMMENT "",
+  `revenue` int(11) NOT NULL COMMENT "",
+  `state` tinyint(4) NOT NULL COMMENT ""
+) ENGINE=OLAP 
+PRIMARY KEY(`dt`, `order_id`)
+PARTITION BY RANGE(`dt`)
+(PARTITION p20210820 VALUES [("2021-08-20"), ("2021-08-21")),
+PARTITION p20210821 VALUES [("2021-08-21"), ("2021-08-22")),
+PARTITION p20210929 VALUES [("2021-09-29"), ("2021-09-30")),
+PARTITION p20210930 VALUES [("2021-09-30"), ("2021-10-01")))
+DISTRIBUTED BY HASH(`order_id`)
+PROPERTIES (
+"replication_num" = "3",
+"in_memory" = "false",
+"enable_persistent_index" = "true",
+"replicated_storage" = "true",
+"compression" = "LZ4"
+);
+```
+
+示例二：建表时指定新表的分区方式、分桶方式和属性。
+
+```sql
+CREATE TABLE order_2
+PARTITION BY date_trunc('day',dt)
+DISTRIBUTED BY hash(dt)
+PROPERTIES ("replication_num" = "1")
+LIKE orders;
+```
+
+```plaintext
+show create table order_2\G
+*************************** 1. row ***************************
+       Table: order_2
+Create Table: CREATE TABLE `order_2` (
+  `dt` date NOT NULL COMMENT "",
+  `order_id` bigint(20) NOT NULL COMMENT "",
+  `user_id` int(11) NOT NULL COMMENT "",
+  `merchant_id` int(11) NOT NULL COMMENT "",
+  `good_id` int(11) NOT NULL COMMENT "",
+  `good_name` varchar(65533) NOT NULL COMMENT "",
+  `price` int(11) NOT NULL COMMENT "",
+  `cnt` int(11) NOT NULL COMMENT "",
+  `revenue` int(11) NOT NULL COMMENT "",
+  `state` tinyint(4) NOT NULL COMMENT ""
+) ENGINE=OLAP 
+PRIMARY KEY(`dt`, `order_id`)
+PARTITION BY RANGE(date_trunc('day', dt))
+()
+DISTRIBUTED BY HASH(`dt`)
+PROPERTIES (
+"replication_num" = "1",
+"in_memory" = "false",
+"enable_persistent_index" = "true",
+"replicated_storage" = "true",
+"compression" = "LZ4"
+);
+```
+
+示例三：在 `test1` 库下创建一张表结构和 MySQL 外表 `table1` 相同的空表，表名为 `table2`。
+
+```sql
+CREATE TABLE test1.table2 LIKE test1.table1;
+```
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/DELETE.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/DELETE.md
new file mode 100644
index 00000000000000..4d3c6c7389102d
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/DELETE.md
@@ -0,0 +1,391 @@
+---
+displayed_sidebar: docs
+---
+
+# DELETE
+
+该语句用于从表中删除数据行。表可以是分区表或者非分区表。
+
+对于明细表、聚合表，以及更新表，支持删除表中**指定分区**的数据。从 2.3 版本开始，主键表支持完整的 DELETE...WHERE 语义，即支持按主键、任意列、以及子查询结果删除数据。从 3.0 版本开始，主键类型表丰富了 DELETE...WHERE 语义，支持使用多表关联和公用表表达式（CTE）。
+
+## 注意事项
+
+- 执行 DELETE 操作需要有对应表的 DELETE 权限。
+- 不建议您执行高频的 DELETE 操作。如需要，请在业务低峰期进行。
+- DELETE 删除的是表中数据，表依然存在。如果要删除表，参见 [DROP TABLE](DROP_TABLE.md)。
+- 为防止误删整表，必须在 DELETE 语句中指定 WHERE 子句。
+- 删除的数据会标记为“Deleted”，暂时保留在 Segment 中，不会立即进行物理删除。Compaction（数据版本合并）完成之后会被回收。
+- 该操作会同时删除和表相关的物化视图的数据。
+
+## DELETE 与明细类型、聚合类型和更新类型表
+
+### 语法
+
+```SQL
+DELETE FROM [<db_name>.]<table_name> [PARTITION <partition_name>]
+WHERE
+column_name1 op { value | value_list } [ AND column_name2 op { value | value_list } ...]
+```
+
+### 参数说明
+
+| **参数**         | **必选** | **描述**                                                     |
+| ---------------- | -------- | ------------------------------------------------------------ |
+| `db_name`        | No       | 要操作的表所在的数据库。如果不指定，默认为当前数据库。       |
+| `table_name`     | Yes      | 要操作的表名。                                               |
+| `partition_name` | No       | 要操作的分区名。                                             |
+| `column_name`    | Yes      | 作为删除条件的列，可以指定一个或多个列。                     |
+| `op`             | Yes      | 指定的算子。支持 `=`、`>`、`<`、`>=`、`<=`、`!=`、`IN` 和 `NOT IN`。 |
+
+### 使用限制
+
+- 聚合类型和更新类型表**仅支持 Key 列**作为删除条件。明细类型表支持**任意列**作为删除条件。
+- 条件之间只能是“AND”关系。若希望达成“OR”的关系，需要将条件分别写在两个 DELETE 语句中。
+- 明细类型、聚合类型和更新表类型下，DELETE 语句目前不支持以子查询结果作为删除条件。
+
+### 影响
+
+执行 DELETE 语句后，可能会导致接下来一段时间内（Compaction 完成之前）的查询效率降低。影响程度取决于语句中指定的删除条件的数量。指定的条件越多，影响越大。
+
+### 示例
+
+#### 创建表并插入数据
+
+以下示例创建一张明细类型的分区表。
+
+```SQL
+CREATE TABLE `my_table` (
+    `date` date NOT NULL,
+    `k1` int(11) NOT NULL COMMENT "",
+    `k2` varchar(65533) NULL DEFAULT "" COMMENT "")
+DUPLICATE KEY(`date`)
+PARTITION BY RANGE(`date`)
+(
+    PARTITION p1 VALUES [('2022-03-11'), ('2022-03-12')),
+    PARTITION p2 VALUES [('2022-03-12'), ('2022-03-13'))
+)
+DISTRIBUTED BY HASH(`date`)
+PROPERTIES
+("replication_num" = "3");
+
+INSERT INTO `my_table` VALUES
+('2022-03-11', 3, 'abc'),
+('2022-03-11', 2, 'acb'),
+('2022-03-11', 4, 'abc'),
+('2022-03-12', 2, 'bca'),
+('2022-03-12', 4, 'cba'),
+('2022-03-12', 5, 'cba');
+```
+
+#### 查询表数据
+
+```SQL
+select * from my_table order by date; 
++------------+------+------+
+| date       | k1   | k2   |
++------------+------+------+
+| 2022-03-11 |    3 | abc  |
+| 2022-03-11 |    2 | acb  |
+| 2022-03-11 |    4 | abc  |
+| 2022-03-12 |    2 | bca  |
+| 2022-03-12 |    4 | cba  |
+| 2022-03-12 |    5 | cba  |
++------------+------+------+
+```
+
+#### 删除数据
+
+**删除指定分区中的行**
+
+删除 `my_table` 表 `p1` 分区中 `k1` 列值为 `3` 的数据行。
+
+```SQL
+DELETE FROM my_table PARTITION p1
+WHERE k1 = 3;
+
+-- 可以看到 p1 分区中 k1 为 3 的那行数据被删除。
+select * from my_table partition (p1);
++------------+------+------+
+| date       | k1   | k2   |
++------------+------+------+
+| 2022-03-11 |    2 | acb  |
+| 2022-03-11 |    4 | abc  |
++------------+------+------+
+```
+
+**删除指定分区中满足 AND 条件的行**
+
+删除 `my_table` 表 `p1` 分区中 `k1` 列值大于等于 `3` 且 `k2` 列值为 `"abc"` 的数据行。
+
+```SQL
+DELETE FROM my_table PARTITION p1
+WHERE k1 >= 3 AND k2 = "abc";
+
+select * from my_table partition (p1);
++------------+------+------+
+| date       | k1   | k2   |
++------------+------+------+
+| 2022-03-11 |    2 | acb  |
++------------+------+------+
+```
+
+**删除所有分区中满足条件的行**
+
+删除 `my_table` 表所有分区中 `k2` 列值为 `"abc"` 或 `"cba"` 的数据行。
+
+```SQL
+DELETE FROM my_table
+WHERE k2 in ("abc", "cba");
+
+select * from my_table order by date;
++------------+------+------+
+| date       | k1   | k2   |
++------------+------+------+
+| 2022-03-11 |    2 | acb  |
+| 2022-03-12 |    2 | bca  |
++------------+------+------+
+```
+
+## DELETE 与主键类型表
+
+从 2.3 版本开始，主键类型表支持完整的 DELETE...WHERE 语义。支持按主键、任意列、以及子查询结果删除数据。从 3.0 版本开始，StarRocks 丰富了 DELETE...WHERE 语义，支持使用多表关联和公用表表达式（CTE）。如果需要将待操作的表与数据库中其他表关联，则可以在 USING 子句或 CTE 中引用其他的表。
+
+### 语法
+
+```SQL
+[ WITH <with_query> [, ...] ]
+DELETE FROM <table_name>
+[ USING <from_item> [, ...] ]
+[ WHERE <where_condition> ]
+```
+
+### 参数说明
+
+| 参数            | 是否必选 | 描述                                                         |
+| --------------- | -------- | ------------------------------------------------------------ |
+| with_query      | No       | 一个或多个可以在 DELETE 语句中通过名字引用的 CTE。CTE 是一个临时结果集，可以提高复杂语句的易读性。 |
+| table_name      | Yes      | 要操作的表名。                                               |
+| from_item       | No       | 引用数据库中一个或者多个其他的表。该表与待操作的表进行连接，WHERE 子句指定连接条件，最终 StarRocks 基于连接查询的结果集删除待操作表中的匹配行。 例如 USING 子句为 `USING t1 WHERE t0.pk = t1.pk;`，StarRocks 实际执行 DELETE 语句时会将该 USING 子句的表表达式会转换为 `t0 JOIN t1 ON t0.pk=t1.pk;`。 |
+| where_condition | No       | 只有满足 WHERE 条件的行才会被删除。该参数为必选，防止误删整张表。如需删除表中的所有行，请使用 `WHERE true`。 |
+
+### 注意事项
+
+- 主键类型表目前**还不支持**删除指定分区中的数据，例如 `DELETE FROM <table_name> PARTITION <partition_id> WHERE <where_condition>`。
+- 支持如下比较运算符：`=`、`>`、`<`、`>=`、`<=`、`!=`、`IN` 和 `NOT IN`。
+- 支持如下逻辑运算符：`AND` 和 `OR`。
+- 不支持并发删除或导入数据时删除，因为可能无法保证导入的事务性。
+
+### 示例
+
+#### 创建表并插入数据
+
+在数据库 `test` 中创建一张名为 `score_board` 的主键类型表：
+
+```SQL
+CREATE TABLE `score_board` (
+    `id` int(11) NOT NULL COMMENT "",
+    `name` varchar(65533) NULL DEFAULT "" COMMENT "",
+    `score` int(11) NOT NULL DEFAULT "0" COMMENT "")
+ENGINE=OLAP
+PRIMARY KEY(`id`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`id`)
+PROPERTIES
+(
+    "replication_num" = "3",
+    "storage_format" = "DEFAULT",
+    "enable_persistent_index" = "false"
+);
+
+INSERT INTO score_board VALUES
+(0, 'Jack', 21),
+(1, 'Bob', 21),
+(2, 'Stan', 21),
+(3, 'Sam', 22);
+```
+
+#### 查询表数据
+
+```Plain
+select * from score_board;
++------+------+------+
+| id   | name | score|
++------+------+------+
+|    0 | Jack |   21 |
+|    1 | Bob  |   21 |
+|    2 | Stan |   21 |
+|    3 | Sam  |   22 |
++------+------+------+
+4 rows in set (0.00 sec)
+```
+
+#### 删除数据
+
+**按主键删除数据**
+
+通过指定主键，可以避免全表扫描。
+
+删除 `score_board` 表中 `id` 列值为 `0` 的数据行。
+
+```SQL
+DELETE FROM score_board WHERE id = 0;
+
+select * from score_board;
++------+------+------+
+| id   | name | score|
++------+------+------+
+|    1 | Bob  |   21 |
+|    2 | Stan |   21 |
+|    3 | Sam  |   22 |
++------+------+------+
+3 rows in set (0.01 sec)
+```
+
+**按条件删除数据**
+
+条件中的列，可以为任意列。
+
+示例一：删除 `score_board` 表中 `score` 列值等于 `22` 的所有数据行。
+
+```SQL
+DELETE FROM score_board WHERE score = 22;
+
+select * from score_board;
++------+------+------+
+| id   | name | score|
++------+------+------+
+|    0 | Jack |   21 |
+|    1 | Bob  |   21 |
+|    2 | Stan |   21 |
++------+------+------+
+3 rows in set (0.01 sec)
+```
+
+示例二：删除 `score_board` 表中 `score` 列值小于 `22` 的所有数据行。
+
+```SQL
+DELETE FROM score_board WHERE score < 22;
+
+select * from score_board;
++------+------+------+
+| id   | name | score|
++------+------+------+
+|    3 | Sam  |   22 |
++------+------+------+
+1 row in set (0.01 sec)
+```
+
+示例三：删除 `score_board` 表中 `score` 列值小于 `22`、且 `name` 列值不为 `Bob` 的所有数据行。
+
+```SQL
+DELETE FROM score_board WHERE score < 22 and name != "Bob";
+
+select * from score_board;
++------+------+------+
+| id   | name | score|
++------+------+------+
+|    1 | Bob  |   21 |
+|    3 | Sam  |   22 |
++------+------+------+
+2 rows in set (0.00 sec)
+```
+
+**按子查询结果删除数据**
+
+可以在 `DELETE` 语句中嵌套一个或多个子查询，并使用子查询结果作为删除条件。
+
+开始删除操作之前，先在数据库 `test` 中再创建一张名为 `users` 的主键类型表：
+
+```SQL
+CREATE TABLE
+    `users` (`uid` int(11) NOT NULL COMMENT "",
+    `name` varchar(65533) NOT NULL COMMENT "",
+    `country` varchar(65533) NULL COMMENT "")
+ENGINE=OLAP
+PRIMARY KEY(`uid`)COMMENT "OLAP"
+DISTRIBUTED BY HASH(`uid`)
+PROPERTIES
+(
+    "replication_num" = "3",
+    "storage_format" = "DEFAULT",
+    "enable_persistent_index" = "false"
+);
+```
+
+向 `users` 表中插入数据：
+
+```SQL
+INSERT INTO users VALUES
+(0, "Jack", "China"),
+(2, "Stan", "USA"),
+(1, "Bob", "China"),
+(3, "Sam", "USA");
+select * from users;
++------+------+---------+
+| uid  | name | country |
++------+------+---------+
+|    0 | Jack | China   |
+|    1 | Bob  | China   |
+|    2 | Stan | USA     |
+|    3 | Sam  | USA     |
++------+------+---------+
+4 rows in set (0.00 sec)
+```
+
+查询 `users` 表中 `country` 列值为 `China` 的数据行，然后删除 `score_board` 表中与 `users` 表中查询到的数据行具有相同 `name` 列值的所有数据行。有两种实现方法：
+
+- 方法 1
+
+```SQL
+DELETE FROM score_board
+WHERE name IN (select name from users where country = "China");
+select * from score_board;
++------+------+------+
+| id   | name | score|
++------+------+------+
+|    2 | Stan |   21 |
+|    3 | Sam  |   22 |
++------+------+------+
+2 rows in set (0.00 sec)
+```
+
+- 方法 2
+
+```SQL
+DELETE FROM score_board
+WHERE EXISTS (select name from users
+              where score_board.name = users.name and country = "China");
+select * from score_board;
++------+------+-------+
+| id   | name | score |
++------+------+-------+
+|    2 | Stan |    21 |
+|    3 | Sam  |    22 |
++------+------+-------+
+2 rows in set (0.00 sec)
+```
+
+**按多表关联或者 CTE 的结果集删除数据**
+
+删除制片人 foo 制作的所有电影，则可以执行以下语句：
+
+```SQL
+DELETE FROM films USING producers
+WHERE producer_id = producers.id
+    AND producers.name = 'foo';
+```
+
+您也可以使用 CTE 改写上述语句，增加易读性。
+
+```SQL
+WITH foo_producers as (
+    SELECT * from producers
+    where producers.name = 'foo'
+)
+DELETE FROM films USING foo_producers
+WHERE producer_id = foo_producers.id;
+```
+
+## 相关 SQL
+
+[SHOW DELETE](SHOW_DELETE.md)：用于查询在指定数据库下，所有在明细表、聚合表、更新表上成功执行的历史删除 (DELETE) 任务。
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md
new file mode 100644
index 00000000000000..d9b809c24aa1f2
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md
@@ -0,0 +1,118 @@
+---
+displayed_sidebar: docs
+---
+
+# DESC
+
+## 功能
+
+您可以使用该语句进行如下操作：
+
+- 查看 StarRocks 表结构、[排序键](../../../table_design/indexes/Prefix_index_sort_key.md) (Sort Key) 类型和[物化视图](../../../using_starrocks/Materialized_view.md)。
+- 查看外部数据源（如 Apache Hive™）中的表结构。仅 StarRocks 2.4 及以上版本支持该操作。
+
+## 语法
+
+```SQL
+DESC[RIBE] [catalog_name.][db_name.]table_name [ALL];
+```
+
+## 参数说明
+
+| **参数**     | **必选** | **说明**                                                     |
+| ------------ | -------- | ------------------------------------------------------------ |
+| catalog_name | 否       | Internal catalog 或 external catalog 的名称。<ul><li>如指定 internal catalog 名称，即 `default_catalog`，则查看当前 StarRocks 集群的指定表结构。</li><li>如指定 external catalog 名称，则查看外部数据源的指定表结构。</li></ul> |
+| db_name      | 否       | 数据库名称。                                                 |
+| table_name   | 是       | 表名称。                                                     |
+| ALL          | 否       | <ul><li>如要查看 StarRocks 表的排序键类型和物化视图，则指定该关键字；如只查看 StarRocks 表结构，则可以不指定。</li><li>如查看外部数据源表结构，不能指定该关键词。</li></ul> |
+
+## 返回信息说明
+
+```Plain
++-----------+---------------+-------+------+------+-----+---------+-------+
+| IndexName | IndexKeysType | Field | Type | Null | Key | Default | Extra |
++-----------+---------------+-------+------+------+-----+---------+-------+
+```
+
+返回信息中的参数说明：
+
+| **参数**      | **说明**                                                     |
+| ------------- | ------------------------------------------------------------ |
+| IndexName     | 表名。如查看外部数据源表结构，则不返回该参数。               |
+| IndexKeysType | 表的排序键类型。如查看外部数据源表结构，则不返回该参数。     |
+| Field         | 列名。                                                       |
+| Type          | 列的数据型。                                               |
+| Null          | 是否允许为 NULL。<ul><li>`yes`: 表示允许为 NULL。</li><li>`no`：表示不允许为 NULL。</li></ul> |
+| Key           | 是否为排序键。<ul><li>`true`: 表示为排序键。</li><li>`false`：表示不为排序键。</li></ul> |
+| Default       | 数据类型的默认值。如该数据类型没有默认值，则返回 NULL。      |
+| Extra         | <ul><li>如果是查看 StarRocks 表结构，该参数会根据情况返回以下信息：<ul><li>该列使用了哪种聚合函数，如 SUM 和 MIN。</li><li>该列是否创建了 bloom filter 索引。如创建，则追加显示 `BLOOM_FILTER`。</li></ul></li><li>如果是查看外部数据源表结构，该参数会显示该列是否为分区键 (partition column)。如是，则显示 `partition key`。</li></ul> |
+
+> 说明：有关物化视图的展示，请参见示例二。
+
+## 示例
+
+示例一：查看 StarRocks 的 `example_table` 表结构信息。
+
+```SQL
+DESC example_table;
+```
+
+或
+
+```SQL
+DESC default_catalog.example_db.example_table;
+```
+
+返回信息如下：
+
+```Plain
++-------+---------------+------+-------+---------+-------+
+| Field | Type          | Null | Key   | Default | Extra |
++-------+---------------+------+-------+---------+-------+
+| k1    | TINYINT       | Yes  | true  | NULL    |       |
+| k2    | DECIMAL(10,2) | Yes  | true  | 10.5    |       |
+| k3    | CHAR(10)      | Yes  | false | NULL    |       |
+| v1    | INT           | Yes  | false | NULL    |       |
++-------+---------------+------+-------+---------+-------+
+```
+
+示例二：查看 StarRocks 的 `sales_records` 表结构、排序键类型和物化视图。如下所示， `sales_records` 表只有一张物化视图 `store_amt`。
+
+```Plain
+DESC db1.sales_records ALL;
+
++---------------+---------------+-----------+--------+------+-------+---------+-------+
+| IndexName     | IndexKeysType | Field     | Type   | Null | Key   | Default | Extra |
++---------------+---------------+-----------+--------+------+-------+---------+-------+
+| sales_records | DUP_KEYS      | record_id | INT    | Yes  | true  | NULL    |       |
+|               |               | seller_id | INT    | Yes  | true  | NULL    |       |
+|               |               | store_id  | INT    | Yes  | true  | NULL    |       |
+|               |               | sale_date | DATE   | Yes  | false | NULL    | NONE  |
+|               |               | sale_amt  | BIGINT | Yes  | false | NULL    | NONE  |
+|               |               |           |        |      |       |         |       |
+| store_amt     | AGG_KEYS      | store_id  | INT    | Yes  | true  | NULL    |       |
+|               |               | sale_amt  | BIGINT | Yes  | false | NULL    | SUM   |
++---------------+---------------+-----------+--------+------+-------+---------+-------+
+```
+
+示例三：查看 Hive 中 `hive_table` 表结构。
+
+```SQL
+DESC hive_catalog.hive_db.hive_table;
+
++-------+----------------+------+-------+---------+---------------+ 
+| Field | Type           | Null | Key   | Default | Extra         | 
++-------+----------------+------+-------+---------+---------------+ 
+| id    | INT            | Yes  | false | NULL    |               | 
+| name  | VARCHAR(65533) | Yes  | false | NULL    |               | 
+| date  | DATE           | Yes  | false | NULL    | partition key | 
++-------+----------------+------+-------+---------+---------------+
+```
+
+## 相关文档
+
+- [CREATE DATABASE](../Database/CREATE_DATABASE.md)
+- [SHOW CREATE DATABASE](../Database/SHOW_CREATE_DATABASE.md)
+- [USE](../Database/USE.md)
+- [SHOW DATABASES](../Database/SHOW_DATABASES.md)
+- [DROP DATABASE](../Database/DROP_DATABASE.md)
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/DROP_INDEX.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/DROP_INDEX.md
new file mode 100644
index 00000000000000..584f2a56894b5b
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/DROP_INDEX.md
@@ -0,0 +1,44 @@
+---
+displayed_sidebar: docs
+keywords: ['suoyin']
+---
+
+# DROP INDEX
+
+## 功能
+
+删除指定表的某个 bitmap 索引。创建 bitmap 索引会占用额外的存储空间，所以不用的索引建议删除。删除索引后，存储空间会立即释放。
+
+:::tip
+
+该操作需要对应表的 ALTER 权限。请参考 [GRANT](../account-management/GRANT.md) 为用户赋权。
+
+:::
+
+## 语法
+
+```SQL
+DROP INDEX index_name ON [db_name.]table_name
+```
+
+## 参数说明
+
+| **参数**   | **必选** | **说明**           |
+| ---------- | -------- | ------------------ |
+| index_name | 是       | 要删除的索引名称。 |
+| table_name | 是       | 创建索引的表。     |
+| db_name    | 否       | 表所属的数据库。   |
+
+## 示例
+
+例如为表 `sales_records` 中的 `item_id` 列创建位图索引，索引名称为 `index3`。
+
+```SQL
+CREATE INDEX index3 ON sales_records (item_id);
+```
+
+删除表`sales_records`中的索引`index3`。
+
+```SQL
+DROP INDEX index3 ON sales_records;
+```
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md
new file mode 100644
index 00000000000000..fce44ca32d8f79
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md
@@ -0,0 +1,49 @@
+---
+displayed_sidebar: docs
+---
+
+# DROP TABLE
+
+## 功能
+
+该语句用于删除表。
+
+## 语法
+
+```sql
+DROP [TEMPORARY] TABLE [IF EXISTS] [db_name.]table_name [FORCE]
+```
+
+说明：
+
+- 执行 DROP TABLE 后一段时间内（默认 1 天），可以通过 [RECOVER](../backup_restore/RECOVER.md) 语句恢复被删除的表。
+- 如果执行 `DROP TABLE FORCE`，则系统不会检查该表是否存在未完成的事务，表将直接被删除并且不能被恢复，一般不建议执行此操作。
+- 临时表删除后不可以通过 RECOVER 语句恢复。
+
+## 示例
+
+1. 删除一个 table。
+
+    ```sql
+    DROP TABLE my_table;
+    ```
+
+2. 如果存在，删除指定 database 的 table。
+
+    ```sql
+    DROP TABLE IF EXISTS example_db.my_table;
+    ```
+
+3. 强制删除表，并清理磁盘文件。
+
+    ```sql
+    DROP TABLE my_table FORCE;
+    ```
+
+## References
+
+* [CREATE TABLE](CREATE_TABLE.md)
+* [SHOW TABLES](SHOW_TABLES.md)
+* [SHOW CREATE TABLE](SHOW_CREATE_TABLE.md)
+* [ALTER TABLE](ALTER_TABLE.md)
+* [SHOW ALTER TABLE](SHOW_ALTER.md)
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/REFRESH_EXTERNAL_TABLE.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/REFRESH_EXTERNAL_TABLE.md
new file mode 100644
index 00000000000000..6eaa4bff8fb25f
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/REFRESH_EXTERNAL_TABLE.md
@@ -0,0 +1,101 @@
+---
+displayed_sidebar: docs
+---
+
+# REFRESH EXTERNAL TABLE
+
+## 功能
+
+该语句用于更新缓存在 StarRocks 中的数据湖上的元数据，主要有以下两个使用场景：
+
+- **外部表**：使用 Hive 外部表和 Hudi 外部表查询 Hive 和 Hudi 数据时， 可使用该语句更新缓存的 Hive 和 Hudi 元数据。
+- **External catalog**：使用 [Hive catalog](../../../data_source/catalog/hive_catalog.md)、[Hudi catalog](../../../data_source/catalog/hudi_catalog.md)、[Delta Lake catalog](../../../data_source/catalog/deltalake_catalog.md)、[MaxCompute Catalog](../../../data_source/catalog/maxcompute_catalog.md)（自 3.3 起）查询对应数据源数据时，可使用该语句更新缓存的元数据。
+
+> **注意**
+>
+> 只有拥有对应外表 ALTER 权限的用户才可以执行该操作。
+
+## 基本概念
+
+- **Hive 外部表**：在 StarRocks 中创建并保存的表，用于查询 Hive 集群中的数据。
+- **Hudi 外部表**：在 StarRocks 中创建并保存的表，用于查询 Hudi 集群中的数据。
+- **Hive 表**：在 Hive 中创建并保存的表。
+- **Hudi 表**：在 Hudi 中创建并保存的表。
+
+## 语法和参数说明
+
+在不同的使用场景下，对应语法和参数说明如下：
+
+- 外部表
+
+    ```SQL
+    REFRESH EXTERNAL TABLE <table_name>
+    [PARTITION ('partition_name', ...)]
+    ```
+
+    | **参数**       | **必选** | **说明**                                                     |
+    | -------------- | -------- | ------------------------------------------------------------ |
+    | table_name     | 是       | Hive 外部表或 Hudi 外部表名。                                |
+    | partition_name | 否       | Hive 表或 Hudi 表中的分区名。如指定，则更新缓存的 Hive 表或 Hudi 表指定分区的元数据。 |
+
+- External catalog
+
+    ```SQL
+    REFRESH EXTERNAL TABLE [external_catalog.][db_name.]<table_name>
+    [PARTITION ('partition_name', ...)]
+    ```
+
+    | **参数**         | **必选** | **说明**                                                     |
+    | ---------------- | -------- | ------------------------------------------------------------ |
+    | external_catalog | 否       | 外部数据目录名称，支持 Hive、Hudi、Delta Lake、MaxCompute catalog （自 3.3 起）。                          |
+    | db_name          | 否       | 表所在的数据库名。                            |
+    | table_name       | 是       | 表名名。                                        |
+    | partition_name   | 否       | 表中的分区名。如指定，则更新缓存的表中指定分区的元数据。 |
+
+## 示例
+
+在不同使用场景下， 对应的示例如下。
+
+### 外部表
+
+示例一：更新外部表 `hive1` 对应的 Hive 表元数据。
+
+```SQL
+REFRESH EXTERNAL TABLE hive1;
+```
+
+示例二：更新外部表 `hudi1` 对应的 Hudi 表 `p1` 和 `p2` 分区元数据。
+
+```SQL
+REFRESH EXTERNAL TABLE hudi1
+PARTITION ('p1', 'p2');
+```
+
+### External catalog
+
+示例一：更新缓存的 `hive_table` 表的元数据。
+
+```SQL
+REFRESH EXTERNAL TABLE hive_catalog.hive_db.hive_table;
+```
+
+或
+
+```SQL
+USE hive_catalog.hive_db;
+REFRESH EXTERNAL TABLE hive_table;
+```
+
+示例二：更新缓存的 `hive_table` 表的二级分区 `p2` 的元数据。
+
+```SQL
+USE hive_catalog.hive_db;
+REFRESH EXTERNAL TABLE hive_table PARTITION ('p1=${date}/p2=${hour}');
+```
+
+示例三：更新缓存的 `hudi_table` 表的分区 `p1` 和 `p2` 的元数据。
+
+```SQL
+REFRESH EXTERNAL TABLE hudi_catalog.hudi_db.hudi_table
+PARTITION ('p1', 'p2');
+```
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SELECT.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SELECT.md
new file mode 100644
index 00000000000000..54e827c75de00c
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SELECT.md
@@ -0,0 +1,1135 @@
+---
+displayed_sidebar: docs
+---
+
+# SELECT
+
+## 功能
+
+SELECT 语句用于从单个或多个表，视图，物化视图中读取数据。SELECT 语句一般由以下子句组成：
+
+- [SELECT](#select)
+  - [功能](#功能)
+    - [WITH](#with)
+    - [连接 (Join)](#连接-join)
+      - [Self Join](#self-join)
+      - [笛卡尔积 (Cross Join)](#笛卡尔积-cross-join)
+      - [Inner Join](#inner-join)
+      - [Outer Join](#outer-join)
+      - [Semi Join](#semi-join)
+      - [Anti Join](#anti-join)
+      - [等值 Join 和非等值 Join](#等值-join-和非等值-join)
+    - [ORDER BY](#order-by)
+    - [GROUP BY](#group-by)
+  - [语法](#语法)
+    - [Parameters](#parameters)
+    - [Note](#note)
+  - [示例](#示例)
+    - [HAVING](#having)
+    - [LIMIT](#limit)
+      - [OFFSET](#offset)
+    - [**UNION**](#union)
+    - [**INTERSECT**](#intersect)
+    - [**EXCEPT/MINUS**](#exceptminus)
+    - [DISTINCT](#distinct)
+    - [子查询](#子查询)
+      - [不相关子查询](#不相关子查询)
+      - [相关子查询](#相关子查询)
+    - [WHERE 与操作符](#where-与操作符)
+      - [算数操作符](#算数操作符)
+      - [BETWEEN 操作符](#between-操作符)
+      - [比较操作符](#比较操作符)
+      - [In 操作符](#in-操作符)
+      - [Like 操作符](#like-操作符)
+      - [逻辑操作符](#逻辑操作符)
+      - [正则表达式操作符](#正则表达式操作符)
+    - [别名 (alias)](#别名-alias)
+    - [PIVOT](#pivot)
+      - [语法](#语法-1)
+      - [参数](#参数)
+      - [示例](#示例-1)
+
+SELECT 可以作为独立的语句也可以作为其他语句的子句，其查询结果可以作为另一个语句的输入值。
+
+StarRocks 的查询语句基本符合 SQL-92 标准。下面介绍支持的 SELECT 用法。
+
+> **说明**
+>
+> 如果要查询 StarRocks 表、视图、或物化视图内的数据，需要有对应对象的 SELECT 权限。如果要查询 External Catalog 里的数据，需要有对应 Catalog 的 USAGE 权限。
+
+### WITH
+
+可以在 SELECT 语句之前添加的子句，用于定义在 SELECT 内部多次引用的复杂表达式的别名。
+
+与 CREATE VIEW 类似，但在子句中定义的表和列名在查询结束后不会持久，也不会与实际表或 VIEW 中的名称冲突。
+
+使用 WITH 子句的好处：
+
+- 方便和易于维护，减少查询内部的重复。
+
+- 通过将查询中最复杂的部分抽象成单独的块，更易于阅读和理解 SQL 代码。
+
+示例：
+
+```sql
+-- Define one subquery at the outer level, and another at the inner level as part of the
+-- initial stage of the UNION ALL query.
+
+with t1 as (select 1),t2 as (select 2)
+select * from t1 union all select * from t2;
+```
+
+### 连接 (Join)
+
+连接操作合并 2 个或多个表的数据，然后返回某些表中某些列的结果集。
+
+目前 StarRocks 支持 Self Join、Cross Join、Inner Join、Outer Join、Semi Join 和 Anti Join。其中，Outer Join 包括 Left Join、Right Join 和 Full Join。
+
+Join 的语法定义如下：
+
+```sql
+SELECT select_list FROM
+table_or_subquery1 [INNER] JOIN table_or_subquery2 |
+table_or_subquery1 {LEFT [OUTER] | RIGHT [OUTER] | FULL [OUTER]} JOIN table_or_subquery2 |
+table_or_subquery1 {LEFT | RIGHT} SEMI JOIN table_or_subquery2 |
+table_or_subquery1 {LEFT | RIGHT} ANTI JOIN table_or_subquery2 |
+[ ON col1 = col2 [AND col3 = col4 ...] |
+USING (col1 [, col2 ...]) ]
+[other_join_clause ...]
+[ WHERE where_clauses ]
+```
+
+```sql
+SELECT select_list FROM
+table_or_subquery1, table_or_subquery2 [, table_or_subquery3 ...]
+[other_join_clause ...]
+WHERE
+col1 = col2 [AND col3 = col4 ...]
+```
+
+```sql
+SELECT select_list FROM
+table_or_subquery1 CROSS JOIN table_or_subquery2
+[other_join_clause ...]
+[ WHERE where_clauses ]
+```
+
+#### Self Join
+
+StarRocks 支持 Self Join，即自己和自己 Join。例如同一张表的不同列进行 Join。
+
+实际上没有特殊的语法标识 Self Join。Self Join 中 Join 两边的条件都来自同一张表，
+
+您需要给他们分配不同的别名。
+
+例如：
+
+```sql
+SELECT lhs.id, rhs.parent, lhs.c1, rhs.c2 FROM tree_data lhs, tree_data rhs WHERE lhs.id = rhs.parent;
+```
+
+#### 笛卡尔积 (Cross Join)
+
+Cross join 会产生大量的结果，须慎用 cross join。
+
+即使需要使用 Cross Join 时也需要使用过滤条件并且确保返回结果数较少。例如：
+
+```sql
+SELECT * FROM t1, t2;
+
+SELECT * FROM t1 CROSS JOIN t2;
+```
+
+#### Inner Join
+
+Inner Inner Join 是大家最熟知，最常用的 Join。返回的结果来自相近的两张表所请求的列，Join 的条件为两个表的列包含有相同的值。
+
+如果两个表的某个列名相同，我们需要使用全名（table_name.column_name 形式）或者给列名起别名。
+
+例如：
+
+下列 3 个查询是等价的。
+
+```sql
+SELECT t1.id, c1, c2 FROM t1, t2 WHERE t1.id = t2.id;
+
+SELECT t1.id, c1, c2 FROM t1 JOIN t2 ON t1.id = t2.id;
+
+SELECT t1.id, c1, c2 FROM t1 INNER JOIN t2 ON t1.id = t2.id;
+```
+
+#### Outer Join
+
+Outer Join 返回左表或者右表或者两者所有的行。如果在另一张表中没有匹配的数据，则将其设置为 `NULL`。例如：
+
+```sql
+SELECT * FROM t1 LEFT OUTER JOIN t2 ON t1.id = t2.id;
+
+SELECT * FROM t1 RIGHT OUTER JOIN t2 ON t1.id = t2.id;
+
+SELECT * FROM t1 FULL OUTER JOIN t2 ON t1.id = t2.id;
+```
+
+#### Semi Join
+
+Left Semi Join 只返回左表中能匹配右表数据的行，不管能匹配右表多少行数据，
+
+左表的该行最多只返回一次。Right Semi Join 原理相似，只是返回的数据是右表的。
+
+例如：
+
+```sql
+SELECT t1.c1, t1.c2, t1.c2 FROM t1 LEFT SEMI JOIN t2 ON t1.id = t2.id;
+```
+
+#### Anti Join
+
+Left Anti Join 只返回左表中不能匹配右表的行。
+
+Right Anti Join 反转了这个比较，只返回右表中不能匹配左表的行。例如：
+
+```sql
+SELECT t1.c1, t1.c2, t1.c2 FROM t1 LEFT ANTI JOIN t2 ON t1.id = t2.id;
+```
+
+#### 等值 Join 和非等值 Join
+
+根据 Join 条件的不同，StarRocks 支持的上述各种类型的 Join 可以分为等值 Join 和非等值 Join，如下表所示：
+
+| **等值 Join**   | Self Join、Cross Join、Inner Join、Outer Join、Semi Join 和 Anti Join |
+| --------------- | ------------------------------------------------------------ |
+| **非等值 Join** | Cross Join、Inner Join，LEFT SEMI JOIN， LEFT ANTI JOIN 和 Outer Join  |
+
+- 等值 Join
+  
+  等值 Join 使用等值条件作为连接条件，例如 `a JOIN b ON a.id = b.id`。
+
+- 非等值 Join
+  
+  非等值 Join 不使用等值条件，使用 `<`、`<=`、`>`、`>=`、`<>` 等比较操作符，例如 `a JOIN b ON a.id < b.id`。与等值 Join 相比，非等值 Join 目前效率较低，建议您谨慎使用。
+
+  以下为非等值 Join 的两个使用示例：
+
+  ```SQL
+  SELECT t1.id, c1, c2 
+  FROM t1 
+  INNER JOIN t2 ON t1.id < t2.id;
+    
+  SELECT t1.id, c1, c2 
+  FROM t1 
+  LEFT JOIN t2 ON t1.id > t2.id;
+  ```
+
+### ORDER BY
+
+ORDER BY 通过比较一列或者多列的大小来对结果集进行排序。
+
+ORDER BY 是比较耗时耗资源的操作，因为所有数据都需要发送到 1 个节点后才能排序，需要更多的内存。
+
+如果需要返回前 N 个排序结果，需要使用 LIMIT 子句；为了限制内存的使用，如果您没有指定 LIMIT 子句，则默认返回前 65535 个排序结果。
+
+ORDER BY 语法定义如下：
+
+```sql
+ORDER BY col [ASC | DESC]
+[ NULLS FIRST | NULLS LAST ]
+```
+
+默认排序顺序是 ASC（升序）。示例：
+
+```sql
+select * from big_table order by tiny_column, short_column desc;
+```
+
+StarRocks 支持在 ORDER BY 后声明 null 值排在最前面还是最后面，语法为 `order by <> [ NULLS FIRST | NULLS LAST ]`。`NULLS FIRST` 表示 null 值的记录将排在最前面，`NULLS LAST` 表示 null 值的记录将排在最后面。
+
+示例：将 null 值始终排在最前面。
+
+```sql
+select  *  from  sales_record  order by  employee_id  nulls first;
+```
+
+### GROUP BY
+
+GROUP BY 子句通常和聚合函数（例如 COUNT(), SUM(), AVG(), MIN()和 MAX()）一起使用。
+
+GROUP BY 指定的列不会参加聚合操作。GROUP BY 子句可以加入 HAVING 子句来过滤聚合函数产出的结果。例如：
+
+```sql
+select tiny_column, sum(short_column)
+from small_table 
+group by tiny_column;
+```
+
+```sql
++-------------+---------------------+
+| tiny_column |  sum('short_column')|
++-------------+---------------------+
+|      1      |        2            |
+|      2      |        1            |
++-------------+---------------------+
+```
+
+## 语法
+
+  ```sql
+  SELECT ...
+  FROM ...
+  [ ... ]
+  GROUP BY [
+      , ... |
+      GROUPING SETS [, ...] (  groupSet [ , groupSet [ , ... ] ] ) |
+      ROLLUP(expr  [ , expr [ , ... ] ]) |
+      CUBE(expr  [ , expr [ , ... ] ])
+      ]
+  [ ... ]
+  ```
+
+### Parameters
+
+- `groupSet` 表示 select list 中的列，别名或者表达式组成的集合 `groupSet ::= { ( expr  [ , expr [ , ... ] ] )}`。
+
+- `expr`  表示 select list 中的列，别名或者表达式。
+
+### Note
+
+StarRocks 支持类似 PostgreSQL 语法，语法实例如下：
+
+  ```sql
+  SELECT a, b, SUM( c ) FROM tab1 GROUP BY GROUPING SETS ( (a, b), (a), (b), ( ) );
+  SELECT a, b,c, SUM( d ) FROM tab1 GROUP BY ROLLUP(a,b,c)
+  SELECT a, b,c, SUM( d ) FROM tab1 GROUP BY CUBE(a,b,c)
+  ```
+
+`ROLLUP(a,b,c)` 等价于如下 `GROUPING SETS` 语句。
+
+  ```sql
+  GROUPING SETS (
+  (a,b,c),
+  (a,b  ),
+  (a    ),
+  (     )
+  )
+  ```
+
+`CUBE (a, b, c)` 等价于如下 `GROUPING SETS` 语句。
+
+  ```sql
+  GROUPING SETS (
+  ( a, b, c ),
+  ( a, b    ),
+  ( a,    c ),
+  ( a       ),
+  (    b, c ),
+  (    b    ),
+  (       c ),
+  (         )
+  )
+  ```
+
+## 示例
+
+下面是一个实际数据的例子:
+
+  ```sql
+  SELECT * FROM t;
+  +------+------+------+
+  | k1   | k2   | k3   |
+  +------+------+------+
+  | a    | A    |    1 |
+  | a    | A    |    2 |
+  | a    | B    |    1 |
+  | a    | B    |    3 |
+  | b    | A    |    1 |
+  | b    | A    |    4 |
+  | b    | B    |    1 |
+  | b    | B    |    5 |
+  +------+------+------+
+  8 rows in set (0.01 sec)
+
+  SELECT k1, k2, SUM(k3) FROM t
+  GROUP BY GROUPING SETS ( (k1, k2), (k2), (k1), ( ) );
+  +------+------+-----------+
+  | k1   | k2   | sum(`k3`) |
+  +------+------+-----------+
+  | b    | B    |         6 |
+  | a    | B    |         4 |
+  | a    | A    |         3 |
+  | b    | A    |         5 |
+  | NULL | B    |        10 |
+  | NULL | A    |         8 |
+  | a    | NULL |         7 |
+  | b    | NULL |        11 |
+  | NULL | NULL |        18 |
+  +------+------+-----------+
+  9 rows in set (0.06 sec)
+
+  SELECT k1, k2, GROUPING_ID(k1,k2), SUM(k3) FROM t
+  GROUP BY GROUPING SETS ((k1, k2), (k1), (k2), ());
+  +------+------+---------------+----------------+
+  | k1   | k2   | grouping_id(k1,k2) | sum(`k3`) |
+  +------+------+---------------+----------------+
+  | a    | A    |             0 |              3 |
+  | a    | B    |             0 |              4 |
+  | a    | NULL |             1 |              7 |
+  | b    | A    |             0 |              5 |
+  | b    | B    |             0 |              6 |
+  | b    | NULL |             1 |             11 |
+  | NULL | A    |             2 |              8 |
+  | NULL | B    |             2 |             10 |
+  | NULL | NULL |             3 |             18 |
+  +------+------+---------------+----------------+
+  9 rows in set (0.02 sec)
+  ```
+
+GROUP BY `GROUPING SETS` ｜ `CUBE` ｜ `ROLLUP` 是对 GROUP BY 子句的扩展，它能够在一个 GROUP BY 子句中实现多个集合的分组的聚合。其结果等价于将多个相应 GROUP BY 子句进行 UNION 操作。
+
+  GROUP BY 子句是只含有一个元素的 GROUP BY GROUPING SETS 的特例。
+  例如，GROUPING SETS 语句：
+
+  ```sql
+  SELECT a, b, SUM( c ) FROM tab1 GROUP BY GROUPING SETS ( (a, b), (a), (b), ( ) );
+  ```
+
+  其查询结果等价于：
+
+  ```sql
+  SELECT a, b, SUM( c ) FROM tab1 GROUP BY a, b
+  UNION
+  SELECT a, null, SUM( c ) FROM tab1 GROUP BY a
+  UNION
+  SELECT null, b, SUM( c ) FROM tab1 GROUP BY b
+  UNION
+  SELECT null, null, SUM( c ) FROM tab1
+  ```
+
+  `GROUPING(expr)` 指示一个列是否为聚合列，如果是聚合列为 0，否则为 1。
+
+  `GROUPING_ID(expr  [ , expr [ , ... ] ])` 与 GROUPING 类似，GROUPING_ID 根据指定的 column 顺序，计算出一个列列表的 bitmap 值，每一位为 GROUPING 的值. GROUPING_ID()函数返回位向量的十进制值。
+
+### HAVING
+
+HAVING 子句不过滤表中的行数据，而是过滤聚合函数产出的结果。
+
+通常来说 HAVING 要和聚合函数（例如 COUNT(), SUM(), AVG(), MIN(), MAX()）以及 group by 子句一起使用。
+
+示例：
+
+```sql
+select tiny_column, sum(short_column) 
+from small_table 
+group by tiny_column 
+having sum(short_column) = 1;
+```
+
+```sql
++-------------+---------------------+
+|tiny_column  | sum('short_column') |
++-------------+---------------------+
+|         2   |        1            |
++-------------+---------------------+
+
+1 row in set (0.07 sec)
+```
+
+```sql
+select tiny_column, sum(short_column) 
+from small_table 
+group by tiny_column 
+having tiny_column > 1;
+```
+
+```sql
++-------------+---------------------+
+|tiny_column  | sum('short_column') |
++-------------+---------------------+
+|      2      |          1          |
++-------------+---------------------+
+
+1 row in set (0.07 sec)
+```
+
+### LIMIT
+
+LIMIT 子句用于限制返回结果的最大行数。设置返回结果的最大行数可以帮助 StarRocks 优化内存的使用。
+
+该子句主要应用如下场景：
+
+1. 返回 top-N 的查询结果。
+
+2. 简单查看表中包含的内容。
+
+3. 表中数据量大，或者 where 子句没有过滤太多的数据，需要限制查询结果集的大小。
+
+使用说明：LIMMIT 子句的值必须是数字型字面常量。
+
+示例：
+
+```sql
+mysql> select tiny_column from small_table limit 1;
+
++-------------+
+|tiny_column  |
++-------------+
+|     1       |
++-------------+
+
+1 row in set (0.02 sec)
+```
+
+```sql
+mysql> select tiny_column from small_table limit 10000;
+
++-------------+
+|tiny_column  |
++-------------+
+|      1      |
+|      2      |
++-------------+
+
+2 rows in set (0.01 sec)
+```
+
+#### OFFSET
+
+OFFSET 子句用于跳过结果集的前若干行结果，直接返回后续的结果。
+
+默认从第 0 行开始，因此 OFFSET 0 和不带 OFFSET 返回相同的结果。
+
+通常来说，OFFSET 子句需要与 ORDER BY 子句和 LIMIT 子句一起使用才有效。
+
+示例：
+
+```sql
+mysql> select varchar_column from big_table order by varchar_column limit 3;
+
++----------------+
+| varchar_column | 
++----------------+
+|    beijing     | 
+|    chongqing   | 
+|    tianjin     | 
++----------------+
+
+3 rows in set (0.02 sec)
+```
+
+```sql
+mysql> select varchar_column from big_table order by varchar_column limit 1 offset 0;
+
++----------------+
+|varchar_column  |
++----------------+
+|     beijing    |
++----------------+
+
+1 row in set (0.01 sec)
+```
+
+```sql
+mysql> select varchar_column from big_table order by varchar_column limit 1 offset 1;
+
++----------------+
+|varchar_column  |
++----------------+
+|    chongqing   | 
++----------------+
+
+1 row in set (0.01 sec)
+```
+
+```sql
+mysql> select varchar_column from big_table order by varchar_column limit 1 offset 2;
+
++----------------+
+|varchar_column  |
++----------------+
+|     tianjin    |     
++----------------+
+
+1 row in set (0.02 sec)
+```
+
+> **注意**
+>
+> 在没有 ORDER BY 的情况下使用 OFFSET 语法是允许的，但是此时 OFFSET 无意义。这种情况只取 LIMIT 的值，忽略 OFFSET 的值。因此在没有 ORDER BY 的情况下，OFFSET 超过结果集的最大行数依然是有结果的。**建议使用 OFFSET 时一定带上 ORDER BY。**
+
+### **UNION**
+
+UNION 子句用于合并多个查询的结果，即获取并集。
+
+**语法如下：**
+
+```SQL
+query_1 UNION [DISTINCT | ALL] query_2
+```
+
+- DISTINCT：默认值，返回不重复的结果。UNION 和 UNION DISTINCT 效果相同（见第二个示例）。
+- ALL: 返回所有结果的集合，不进行去重。由于去重工作比较耗费内存，因此使用 UNION ALL 查询速度会快一些，内存消耗也会少一些（见第一个示例）。
+
+> **说明**
+>
+> 每条 SELECT 查询返回的列数必须相同，且列类型必须能够兼容。
+
+**示例：**
+
+以表 `select1` 和 `select2` 示例说明。
+
+```SQL
+CREATE TABLE select1(
+    id          INT,
+    price       INT
+    )
+DISTRIBUTED BY HASH(id);
+
+INSERT INTO select1 VALUES
+    (1,2),
+    (1,2),
+    (2,3),
+    (5,6),
+    (5,6);
+
+CREATE TABLE select2(
+    id          INT,
+    price       INT
+    )
+DISTRIBUTED BY HASH(id);
+
+INSERT INTO select2 VALUES
+    (2,3),
+    (3,4),
+    (5,6),
+    (7,8);
+```
+
+示例一：返回两张表中所有 `id` 的并集，不进行去重。
+
+```Plaintext
+mysql> (select id from select1) union all (select id from select2) order by id;
+
++------+
+| id   |
++------+
+|    1 |
+|    1 |
+|    2 |
+|    2 |
+|    3 |
+|    5 |
+|    5 |
+|    5 |
+|    7 |
++------+
+11 rows in set (0.02 sec)
+```
+
+示例二：返回两张表中 `id` 的并集，进行去重。下面两条查询在功能上对等。
+
+```Plaintext
+mysql> (select id from select1) union (select id from select2) order by id;
+
++------+
+| id   |
++------+
+|    1 |
+|    2 |
+|    3 |
+|    5 |
+|    7 |
++------+
+6 rows in set (0.01 sec)
+
+mysql> (select id from select1) union distinct (select id from select2) order by id;
++------+
+| id   |
++------+
+|    1 |
+|    2 |
+|    3 |
+|    5 |
+|    7 |
++------+
+5 rows in set (0.02 sec)
+```
+
+示例三：返回两张表中所有 `id` 的并集，进行去重，只返回 3 行结果。下面两条查询在功能上对等。
+
+```SQL
+mysql> (select id from select1) union distinct (select id from select2)
+order by id
+limit 3;
+++------+
+| id   |
++------+
+|    1 |
+|    2 |
+|    3 |
++------+
+4 rows in set (0.11 sec)
+
+mysql> select * from (select id from select1 union distinct select id from select2) as t1
+order by id
+limit 3;
++------+
+| id   |
++------+
+|    1 |
+|    2 |
+|    3 |
++------+
+3 rows in set (0.01 sec)
+```
+
+### **INTERSECT**
+
+INTERSECT 子句用于返回多个查询结果之间的交集，即每个结果中都有的数据，并对结果集进行去重。
+
+**语法如下：**
+
+```SQL
+query_1 INTERSECT [DISTINCT] query_2
+```
+
+> **说明**
+>
+> - INTERSECT 效果等同于 INTERSECT DISTINCT。不支持 ALL 关键字。
+> - 每条 SELECT 查询返回的列数必须相同，且列类型能够兼容。
+
+**示例：**
+
+继续使用 UNION 子句里的两张表。返回两张表中 `id` 和 `price` 组合的交集。下面两条查询在功能上对等。
+
+```Plaintext
+mysql> (select id, price from select1) intersect (select id, price from select2)
+order by id;
+
++------+-------+
+| id   | price |
++------+-------+
+|    2 |     3 |
+|    5 |     6 |
++------+-------+
+
+mysql> (select id, price from select1) intersect distinct (select id, price from select2)
+order by id;
+
++------+-------+
+| id   | price |
++------+-------+
+|    2 |     3 |
+|    5 |     6 |
++------+-------+
+```
+
+### **EXCEPT/MINUS**
+
+EXCEPT/MINUS 子句用于返回多个查询结果之间的补集，即返回左侧查询中在右侧查询中不存在的数据，并对结果集去重。EXCEPT 和 MINUS 功能对等。
+
+**语法如下：**
+
+```SQL
+query_1 {EXCEPT | MINUS} [DISTINCT] query_2
+```
+
+> **说明**
+>
+> - EXCEPT 效果等同于 EXCEPT DISTINCT。不支持 ALL 关键字。
+> - 每条 SELECT 查询返回的列数必须相同，且列类型能够兼容。
+
+**示例：**
+
+继续使用 UNION 子句里的两张表。返回表 `select1` 中不存在于表 `select2` 的 `(id,price)` 组合。
+
+可以看到在结果中对组合 `(1,2)` 进行了去重。
+
+```Plaintext
+mysql> (select id, price from select1) except (select id, price from select2)
+order by id;
++------+-------+
+| id   | price |
++------+-------+
+|    1 |     2 |
++------+-------+
+
+mysql> (select id, price from select1) minus (select id, price from select2)
+order by id;
++------+-------+
+| id   | price |
++------+-------+
+|    1 |     2 |
++------+-------+
+```
+
+### DISTINCT
+
+DISTINCT 关键字对结果集进行去重。示例：
+
+```SQL
+-- 返回一列中去重后的值。
+select distinct tiny_column from big_table limit 2;
+
+-- 返回多列中去重后的组合。
+select distinct tiny_column, int_column from big_table limit 2;
+```
+
+DISTINCT 可以和聚合函数 (通常是 count) 一同使用，count(distinct) 用于计算出一个列或多个列上包含多少不同的组合。
+
+```SQL
+-- 计算一列中不重复值的个数。
+select count(distinct tiny_column) from small_table;
+```
+
+```sql
++-------------------------------+
+| count(DISTINCT 'tiny_column') |
++-------------------------------+
+|             2                 |
++-------------------------------+
+1 row in set (0.06 sec)
+```
+
+```SQL
+-- 计算多列中不重复组合的个数。
+select count(distinct tiny_column, int_column) from big_table limit 2;
+```
+
+StarRocks 支持多个聚合函数同时使用 distinct。
+
+```SQL
+-- 单独返回多个聚合函数去重后的个数。
+
+select count(distinct tiny_column, int_column), count(distinct varchar_column) from big_table;
+```
+
+### 子查询
+
+子查询按相关性可以分为不相关子查询和相关子查询。
+
+- 不相关子查询（简单查询）不依赖外层查询的结果。
+- 相关子查询需要依赖外层查询的结果才能执行。
+
+#### 不相关子查询
+
+不相关子查询支持 [NOT] IN 和 EXISTS。
+
+示例：
+
+```sql
+SELECT x FROM t1 WHERE x [NOT] IN (SELECT y FROM t2);
+
+SELECT * FROM t1 WHERE (x,y) [NOT] IN (SELECT x,y FROM t2 LIMIT 2);
+
+SELECT x FROM t1 WHERE EXISTS (SELECT y FROM t2 WHERE y = 1);
+```
+
+从 3.0 版本开始，`SELECT... FROM... WHERE... [NOT] IN` 支持在 WHERE 中指定多个字段进行比较，即上面第二个示例中的 `WHERE (x,y)` 用法。
+
+#### 相关子查询
+
+相关子查询支持 [NOT] IN 和 [NOT] EXISTS。
+
+示例：
+
+```sql
+SELECT * FROM t1 WHERE x [NOT] IN (SELECT a FROM t2 WHERE t1.y = t2.b);
+
+SELECT * FROM t1 WHERE [NOT] EXISTS (SELECT a FROM t2 WHERE t1.y = t2.b);
+```
+
+子查询还支持标量子查询。分为不相关标量子查询、相关标量子查询和标量子查询作为普通函数的参数。
+
+示例：
+
+1. 不相关标量子查询，谓词为 = 号。例如输出最高工资的人的信息。
+
+    ```sql
+    SELECT name FROM table WHERE salary = (SELECT MAX(salary) FROM table);
+    ```
+
+2. 不相关标量子查询，谓词为 >,< 等。例如输出比平均工资高的人的信息。
+
+    ```sql
+    SELECT name FROM table WHERE salary > (SELECT AVG(salary) FROM table);
+    ```
+
+3. 相关标量子查询。例如输出各个部门工资最高的信息。
+
+    ```sql
+    SELECT name FROM table a WHERE salary = （SELECT MAX(salary) FROM table b WHERE b.部门= a.部门）;
+    ```
+
+4. 标量子查询作为普通函数的参数。
+
+    ```sql
+    SELECT name FROM table WHERE salary = abs((SELECT MAX(salary) FROM table));
+    ```
+
+### WHERE 与操作符
+
+SQL 操作符是一系列用于比较的函数，这些操作符广泛地用于 SELECT 语句的 WHERE 子句中。
+
+#### 算数操作符
+
+算术操作符通常出现在包含左操作数，操作符和右操作数（大部分情况下）组成的表达式中。
+
+**+和-**：分别代表着加法和减法，可以作为单元或 2 元操作符。当其作为单元操作符时，如+1, -2.5 或者-col_name，表达的意思是该值乘以+1 或者-1。
+
+因此单元操作符+返回的是未发生变化的值，单元操作符-改变了该值的符号位。
+
+用户可以将两个单元操作符叠加起来，比如++5(返回的是正值)，-+2 或者+-2（这两种情况返回的是负值），但是用户不能使用连续的两个-号。
+
+因为--被解释为后面的语句是注释（用户也是可以使用两个-号的，此时需要在两个-号之间加上空格或圆括号，如-(-2)或者- -2，这两种写法实际表达的结果都是+2）。
+
++或者-作为 2 元操作符时，例如 2+2，3-1.5 或者 col1 + col2，表达的含义是左值加或者减去右值。左值和右值必须都是数字类型。
+
+***和/**：分别代表着乘法和除法操作符。两侧的操作数必须都是数据类型。
+
+当两个数相乘时，类型较小的操作数在需要的情况下类型可能会提升（比如 SMALLINT 提升到 INT 或者 BIGINT 等），表达式的结果被提升到下一个较大的类型，
+
+比如 TINYINT 乘以 INT 产生的结果的类型会是 BIGINT）。当两个数相乘时，为了避免精度丢失，操作数和表达式结果都会被解释成 DOUBLE 类型。
+
+如果用户想把表达式结果转换成其他类型，需要用 CAST 函数转换。
+
+**%**：取模操作符。返回左操作数除以右操作数的余数。左操作数和右操作数都必须是整型。
+
+**&，|和^**：按位操作符返回对两个操作数进行按位与，按位或，按位异或操作的结果。两个操作数都要求是一种整型类型。
+
+如果按位操作符的两个操作数的类型不一致，则类型小的操作数会被提升到类型较大的操作数，然后再做相应的按位操作。
+
+在 1 个表达式中可以出现多个算术操作符，用户可以用小括号将相应的算术表达式括起来。算术操作符通常没有对应的数学函数来表达和算术操作符相同的功能。
+
+比如我们没有 MOD()函数来表示%操作符的功能。反过来，数学函数也没有对应的算术操作符。比如幂函数 POW()并没有相应的 **求幂操作符。
+
+#### BETWEEN 操作符
+
+在 where 子句中，表达式可能同时与上界和下界比较。如果表达式大于等于下界，同时小于等于上界，比较的结果是 true。语法定义如下：
+
+```sql
+expression BETWEEN lower_bound AND upper_bound
+```
+
+数据类型：通常表达式（expression）的计算结果都是数字类型，该操作符也支持其他数据类型。如果必须要确保下界和上界都是可比较的字符，可以使用 cast()函数。
+
+使用说明：如果操作数是 string 类型应注意，起始部分为上界的长字符串将不会匹配上界，该字符串比上界要大。例如：‘MJ’比‘M’大，所以 `between 'A' and 'M'` 不会匹配‘MJ’。
+
+如果需要确保表达式能够正常工作，可以使用一些函数，如 upper(), lower(), substr(), trim()。
+
+示例：
+
+```sql
+select c1 from t1 where month between 1 and 6;
+```
+
+#### 比较操作符
+
+比较操作符用来判断列和列是否相等或者对列进行排序。`=`, `!=`, `<=`, `>=` 可以适用所有数据类型。
+
+其中 `<>` 符号是不等于的意思，与 `!=` 的功能一致。IN 和 BETWEEN 操作符提供更简短的表达来描述相等、小于、大于等关系的比较。
+
+#### In 操作符
+
+In 操作符会和 VALUE 集合进行比较，如果可以匹配该集合中任何一元素，则返回 TRUE。
+
+参数和 VALUE 集合必须是可比较的。所有使用 IN 操作符的表达式都可以写成用 OR 连接的等值比较，但是 IN 的语法更简单，更精准，更容易让 StarRocks 进行优化。
+
+示例：
+
+```sql
+select * from small_table where tiny_column in (1,2);
+```
+
+#### Like 操作符
+
+该操作符用于和字符串进行比较。"_"用来匹配单个字符，"%"用来匹配多个字符。参数必须要匹配完整的字符串。通常，把"%" 放在字符串的尾部更加符合实际用法。
+
+示例：
+
+```sql
+mysql> select varchar_column from small_table where varchar_column like 'm%';
+
++----------------+
+|varchar_column  |
++----------------+
+|     milan      |
++----------------+
+
+1 row in set (0.02 sec)
+```
+
+```sql
+mysql> select varchar_column from small_table where varchar_column like 'm____';
+
++----------------+
+| varchar_column | 
++----------------+
+|    milan       | 
++----------------+
+
+1 row in set (0.01 sec)
+```
+
+#### 逻辑操作符
+
+逻辑操作符返回一个 BOOL 值，逻辑操作符包括单元操作符和多元操作符，每个操作符处理的参数都是返回值为 BOOL 值的表达式。支持的操作符有：
+
+AND: 2 元操作符，如果左侧和右侧的参数的计算结果都是 TRUE，则 AND 操作符返回 TRUE。
+
+OR: 2 元操作符，如果左侧和右侧的参数的计算结果有一个为 TRUE，则 OR 操作符返回 TRUE。如果两个参数都是 FALSE，则 OR 操作符返回 FALSE。
+
+NOT: 单元操作符，反转表达式的结果。如果参数为 TRUE，则该操作符返回 FALSE；如果参数为 FALSE，则该操作符返回 TRUE。
+
+示例：
+
+```sql
+mysql> select true and true;
+
++-------------------+
+| (TRUE) AND (TRUE) | 
++-------------------+
+|         1         | 
++-------------------+
+
+1 row in set (0.00 sec)
+```
+
+```sql
+mysql> select true and false;
+
++--------------------+
+| (TRUE) AND (FALSE) | 
++--------------------+
+|         0          | 
++--------------------+
+
+1 row in set (0.01 sec)
+```
+
+```sql
+mysql> select true or false;
+
++-------------------+
+| (TRUE) OR (FALSE) | 
++-------------------+
+|        1          | 
++-------------------+
+
+1 row in set (0.01 sec)
+```
+
+```sql
+mysql> select not true;
+
++----------+
+| NOT TRUE | 
++----------+
+|     0    | 
++----------+
+
+1 row in set (0.01 sec)
+```
+
+#### 正则表达式操作符
+
+判断是否匹配正则表达式，使用 POSIX 标准的正则表达式。
+
+"^" 用来匹配字符串的首部，"$" 用来匹配字符串的尾部，"." 匹配任何一个单字符，"*"匹配 0 个或多个选项，"+"匹配 1 个多个选项，"?" 表示分贪婪表示等等。正则表达式需要匹配完整的值，并不是仅仅匹配字符串的部分内容。
+
+如果想匹配中间的部分，正则表达式的前面部分可以写成 "^.*" 或者".*"。"^" 和 "$" 通常是可以省略的。RLIKE 操作符和 REGEXP 操作符是同义词。
+
+"|" 操作符是个可选操作符，"|" 两侧的正则表达式只需满足 1 侧条件即可，"|" 操作符和两侧的正则表达式通常需要用()括起来。
+
+示例：
+
+```sql
+mysql> select varchar_column from small_table where varchar_column regexp '(mi|MI).*';
+
++----------------+
+| varchar_column | 
++----------------+
+|     milan      |       
++----------------+
+
+1 row in set (0.01 sec)
+```
+
+```sql
+mysql> select varchar_column from small_table where varchar_column regexp 'm.*';
+
++----------------+
+| varchar_column | 
++----------------+
+|     milan      |  
++----------------+
+
+1 row in set (0.01 sec)
+```
+
+### 别名 (alias)
+
+在查询中书写表名、列名，或者包含列的表达式的名字时，可以通过 AS 给它们分配一个别名。
+
+当需要使用表名、列名时，可以使用别名来访问。别名通常相对原名来说更简短更容易记忆。当需要新建一个别名时，只需在 select list 或者 from list 中的表、列、表达式名称后面加上 AS alias 子句即可。AS 关键词是可选的，用户可以直接在原名后面指定别名。如果别名或者其他标志符和 [StarRocks 内部保留关键字](../keywords.md)同名时，需要在该名称加上反引号，比如 `rank`。**别名对大小写敏感，但是列别名和表达式别名对大小写不敏感**。
+
+示例：
+
+```sql
+select tiny_column as name, int_column as sex from big_table;
+
+select sum(tiny_column) as total_count from big_table;
+
+select one.tiny_column, two.int_column from small_table one, big_table two where one.tiny_column = two.tiny_column;
+```
+
+### PIVOT
+
+PIVOT操作符是SQL中的一个高级特性，它允许你将表中的行转换为列，通常用于数据透视表的创建。这在处理数据库报表或分析时非常有用，特别是当你需要对数据进行汇总或分类展示时。
+
+实际上，PIVOT 是一种语法糖，它可以简化像 sum(case when ... then ... end) 这样的查询语句的编写。
+
+#### 语法
+  
+```sql
+pivot:
+SELECT ...
+FROM ...
+PIVOT (
+  aggregate_function(<expr>) [[AS] alias] [, aggregate_function(<expr>) [[AS] alias] ...]
+  FOR <pivot_column>
+  IN (<pivot_value>)
+)
+
+pivot_column:
+<column_name> 
+| (<column_name> [, <column_name> ...])
+
+pivot_value:
+<literal> [, <literal> ...]
+| (<literal>, <literal> ...) [, (<literal>, <literal> ...)]
+```
+
+#### 参数
+在PIVOT操作中，你需要指定以下几个关键部分：
+- aggregate_function()：聚合函数，如SUM、AVG、COUNT等，用于对数据进行汇总。
+- alias：为聚合结果指定的别名，使得结果更易于理解。
+- FOR pivot_column：指定要进行行转列操作的列名。
+- IN (pivot_value)：指定pivot_column列中要转换为列的具体值。
+
+#### 示例
+
+```sql
+create table t1 (c0 int, c1 int, c2 int, c3 int);
+SELECT * FROM t1 PIVOT (SUM(c1) AS sum_c1, AVG(c2) AS avg_c2 FOR c3 IN (1, 2, 3, 4, 5));
+-- 结果等同于以下查询：
+SELECT SUM(CASE WHEN c3 = 1 THEN c1 ELSE NULL END) AS sum_c1_1,
+       AVG(CASE WHEN c3 = 1 THEN c2 ELSE NULL END) AS avg_c2_1,
+       SUM(CASE WHEN c3 = 2 THEN c1 ELSE NULL END) AS sum_c1_2,
+       AVG(CASE WHEN c3 = 2 THEN c2 ELSE NULL END) AS avg_c2_2,
+       SUM(CASE WHEN c3 = 3 THEN c1 ELSE NULL END) AS sum_c1_3,
+       AVG(CASE WHEN c3 = 3 THEN c2 ELSE NULL END) AS avg_c2_3,
+       SUM(CASE WHEN c3 = 4 THEN c1 ELSE NULL END) AS sum_c1_4,
+       AVG(CASE WHEN c3 = 4 THEN c2 ELSE NULL END) AS avg_c2_4,
+       SUM(CASE WHEN c3 = 5 THEN c1 ELSE NULL END) AS sum_c1_5,
+       AVG(CASE WHEN c3 = 5 THEN c2 ELSE NULL END) AS avg_c2_5
+FROM t1
+GROUP BY c0;
+```
\ No newline at end of file
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_ALTER.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_ALTER.md
new file mode 100644
index 00000000000000..da53f502342a0e
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_ALTER.md
@@ -0,0 +1,73 @@
+---
+keywords: ['xiugai'] 
+displayed_sidebar: docs
+---
+
+# SHOW ALTER TABLE
+
+## 功能
+
+查询正在进行的 Alter table 操作的执行情况，包括：
+
+- 修改列。
+- 优化表结构（自 3.2 版本起），包括修改分桶方式和分桶数量。
+- 创建和删除 rollup index。
+
+## 语法
+
+- 查询修改列或者优化表结构的操作执行情况。
+
+    ```sql
+    SHOW ALTER TABLE { COLUMN | OPTIMIZE } [FROM <db_name>]
+    [WHERE <where_condition> ] [ORDER BY <col_name> [ASC | DESC]] [LIMIT <num>]
+    ```
+
+- 查询创建和删除 rollup index 的操作执行情况。
+
+    ```sql
+    SHOW ALTER TABLE ROLLUP [FROM <db_name>]
+    ```
+
+## 参数说明
+
+- `{COLUMN ｜ OPTIMIZE | ROLLUP}`：从 `COLUMN`、`OPTIMIZE` 和 `ROLLUP` 中必选其中一个。
+  - 如果指定了 `COLUMN`，该语句用于查询修改列的操作。
+  - 如果指定了 `OPTIMIZE`，该语句用于查询优化表结构操作（修改分桶方式和分桶数量）。
+  - 如果指定了 `ROLLUP`，该语句用于查询创建或删除 rollup index 的操作。
+- 当指定了 `COLUMN` 或者 `OPTIMIZE` 查询修改列或者优化表结构操作时，支持使用如下子句：
+  - `WHERE <where_condition>`：根据操作的 `TableName`、`CreateTime`、`FinishTime` 和 `State` 过滤出满足条件的操作。
+  - `ORDER BY <col_name> [ASC | DESC]`：根据操作的 `TableName`、`CreateTime`、`FinishTime` 和 `State` 对返回结果中的操作进行排序。
+  - `LIMIT <num>`：返回指定个数的操作。
+- `db_name`：可选。如果不指定，则默认使用当前数据库。
+
+## 示例
+
+1. 查询当前数据库中所有修改列操作和优化表结构操作，以及创建或删除 rollup index 操作的执行情况。
+
+    ```sql
+    SHOW ALTER TABLE COLUMN;
+    SHOW ALTER TABLE OPTIMIZE;
+    SHOW ALTER TABLE ROLLUP;
+    ```
+
+2. 查询指定数据库中修改列操作和优化表结构操作，以及创建或删除 rollup index 操作的执行情况。
+
+    ```sql
+    SHOW ALTER TABLE COLUMN FROM example_db;
+    SHOW ALTER TABLE OPTIMIZE FROM example_db;
+    SHOW ALTER TABLE ROLLUP FROM example_db;
+    ````
+
+3. 查询指定表中最近一次修改列操作或者优化表结构操作的执行情况。
+
+    ```sql
+    SHOW ALTER TABLE COLUMN WHERE TableName = "table1" ORDER BY CreateTime DESC LIMIT 1;
+    SHOW ALTER TABLE OPTIMIZE WHERE TableName = "table1" ORDER BY CreateTime DESC LIMIT 1; 
+    ```
+
+## 相关参考
+
+- [CREATE TABLE](CREATE_TABLE.md)
+- [ALTER TABLE](ALTER_TABLE.md)
+- [SHOW TABLES](SHOW_TABLES.md)
+- [SHOW CREATE TABLE](SHOW_CREATE_TABLE.md)
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md
new file mode 100644
index 00000000000000..de1c940aafa7ff
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md
@@ -0,0 +1,138 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW CREATE TABLE
+
+## 功能
+
+查看指定表的建表语句。
+
+自 3.0 版本起支持使用该语句查看 External Catalog 下的表，包括 Apache Hive™ 、Apache Iceberg、Apache Hudi、Delta Lake 表。
+
+自 2.5.7 版本起，StarRocks 支持在建表和新增分区时自动设置分桶数量 (BUCKETS)，您无需手动设置分桶数量。更多信息，请参见 [设置分桶数量](../../../table_design/Data_distribution.md#设置分桶数量)。
+
+- 如果您在建表时指定了分桶数，SHOW CREATE TABLE 会显示分桶数。
+
+- 如果您在建表时没有指定分桶数，SHOW CREATE TABLE 不会显示分桶数，您可以通过 [SHOW PARTITIONS](SHOW_PARTITIONS.md) 查看分区的分桶数。
+
+2.5.7 之前的版本在建表时必须设置分桶数，因此 SHOW CREATE TABLE 会显示分桶数。
+
+> **注意**
+>
+> - 3.0 版本之前，只有拥有该表 SELECT_PRIV 权限的用户才可以查看。
+> - 自 3.0 版本起，只有拥有该表 SELECT 权限的用户才可以查看。
+
+## 语法
+
+```SQL
+SHOW CREATE TABLE [db_name.]table_name
+```
+
+## 参数说明
+
+| **参数**    | **必选** | **说明**                                        |
+| ---------- | -------- | ---------------------------------------------- |
+| db_name    | 否       | 数据库名称。如指定，则查看指定数据库中某张表的建表语句。 |
+| table_name | 是       | 表名。                                          |
+
+## 返回结果说明
+
+```Plain
++-----------+----------------+
+| Table     | Create Table   |       
++-----------+----------------+
+```
+
+返回结果中的参数说明如下：
+
+| **参数**     | **说明**   |
+| ------------ | ---------- |
+| Table        | 表名。     |
+| Create Table | 建表语句。 |
+
+## 示例
+
+### 建表时未指定分桶数
+
+创建一个表 `example_table`，DISTRIBUTED BY 中未指定分桶数。
+
+```SQL
+CREATE TABLE example_table
+(
+    k1 TINYINT,
+    k2 DECIMAL(10, 2) DEFAULT "10.5",
+    v1 CHAR(10) REPLACE,
+    v2 INT SUM
+)
+ENGINE = olap
+AGGREGATE KEY(k1, k2)
+COMMENT "my first starrocks table"
+DISTRIBUTED BY HASH(k1);
+```
+
+查看表 `example_table` 的建表语句，结果中不显示分桶数。注意建表时如果未指定 PROPERTIES，SHOW CREATE TABLE 语句会显示默认的 PROPERTIES。
+
+```Plain
+SHOW CREATE TABLE example_table\G
+*************************** 1. row ***************************
+       Table: example_table
+Create Table: CREATE TABLE `example_table` (
+  `k1` tinyint(4) NULL COMMENT "",
+  `k2` decimal64(10, 2) NULL DEFAULT "10.5" COMMENT "",
+  `v1` char(10) REPLACE NULL COMMENT "",
+  `v2` int(11) SUM NULL COMMENT ""
+) ENGINE=OLAP 
+AGGREGATE KEY(`k1`, `k2`)
+COMMENT "my first starrocks table"
+DISTRIBUTED BY HASH(`k1`)
+PROPERTIES (
+"replication_num" = "3",
+"in_memory" = "false",
+"enable_persistent_index" = "false",
+"replicated_storage" = "true",
+"compression" = "LZ4"
+);
+```
+
+### 建表时指定了分桶数
+
+创建一个表 `example_table1`，DISTRIBUTED BY 中指定分桶数为 10。
+
+```SQL
+CREATE TABLE example_table1
+(
+    k1 TINYINT,
+    k2 DECIMAL(10, 2) DEFAULT "10.5",
+    v1 CHAR(10) REPLACE,
+    v2 INT SUM
+)
+ENGINE = olap
+AGGREGATE KEY(k1, k2)
+COMMENT "my first starrocks table"
+DISTRIBUTED BY HASH(k1) BUCKETS 10;
+```
+
+查看表 `example_table` 的建表语句，结果中显示分桶数。注意建表时如果未指定 PROPERTIES，SHOW CREATE TABLE 语句会显示默认的 PROPERTIES。
+
+```plain
+SHOW CREATE TABLE example_table1\G
+*************************** 1. row ***************************
+       Table: example_table1
+Create Table: CREATE TABLE `example_table1` (
+  `k1` tinyint(4) NULL COMMENT "",
+  `k2` decimal64(10, 2) NULL DEFAULT "10.5" COMMENT "",
+  `v1` char(10) REPLACE NULL COMMENT "",
+  `v2` int(11) SUM NULL COMMENT ""
+) ENGINE=OLAP 
+AGGREGATE KEY(`k1`, `k2`)
+COMMENT "my first starrocks table"
+DISTRIBUTED BY HASH(`k1`) BUCKETS 10 
+PROPERTIES (
+"replication_num" = "3",
+"in_memory" = "false",
+"enable_persistent_index" = "false",
+"replicated_storage" = "true",
+"compression" = "LZ4"
+);
+```
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_DELETE.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_DELETE.md
new file mode 100644
index 00000000000000..132d222e00449f
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_DELETE.md
@@ -0,0 +1,43 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW DELETE
+
+## 功能
+
+用于展示在指定数据库下，所有在明细表、聚合表、更新表上成功执行的历史删除 (DELETE) 任务。
+
+有关删除操作的更多信息，参见 [DELETE](DELETE.md)。
+
+注意该语句不能用于查询在主键表上执行的 DELETE 操作。
+
+## 语法
+
+```sql
+SHOW DELETE [FROM <db_name>]
+```
+
+`db_name`: 数据库名称，可选。如果不指定，默认为当前数据库。
+
+命令返回字段：
+
+- `TableName`: 表名称，即从哪些表中删除了数据。
+- `PartitionName`：表的分区名称，即从哪些分区中删除了数据。如果表是**非分区表**，则显示为 `*`。
+- `CreateTime`: DELETE 任务的创建时间。
+- `DeleteCondition`: 指定的删除条件。
+- `State`: DELETE 任务的状态。
+
+## 示例
+
+展示数据库 `database` 下的所有历史 DELETE 任务。
+
+```sql
+SHOW DELETE FROM database;
+
++------------+---------------+---------------------+-----------------+----------+
+| TableName  | PartitionName | CreateTime          | DeleteCondition | State    |
++------------+---------------+---------------------+-----------------+----------+
+| mail_merge | *             | 2023-03-14 10:39:03 | name EQ "Peter" | FINISHED |
++------------+---------------+---------------------+-----------------+----------+
+```
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_DYNAMIC_PARTITION_TABLES.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_DYNAMIC_PARTITION_TABLES.md
new file mode 100644
index 00000000000000..73d899802045ae
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_DYNAMIC_PARTITION_TABLES.md
@@ -0,0 +1,24 @@
+---
+displayed_sidebar: docs
+keywords: ['fenqu']
+---
+
+# SHOW DYNAMIC PARTITION TABLES
+
+## 功能
+
+该语句用于展示当前数据库 db 下所有设置过动态分区属性的分区表状态。
+
+## 语法
+
+```sql
+SHOW DYNAMIC PARTITION TABLES [FROM <db_name>]
+```
+
+## 示例
+
+1. 展示数据库 database 的所有设置过动态分区属性的分区表状态。
+
+```sql
+SHOW DYNAMIC PARTITION TABLES FROM database;
+```
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_FULL_COLUMNS.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_FULL_COLUMNS.md
new file mode 100644
index 00000000000000..18b1f096fd33b6
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_FULL_COLUMNS.md
@@ -0,0 +1,29 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW FULL COLUMNS
+
+## 功能
+
+该语句用于查看指定表的列信息。
+
+:::tip
+
+该操作不需要权限。
+
+:::
+
+## 语法
+
+```sql
+SHOW FULL COLUMNS FROM <tbl_name>
+```
+
+## 示例
+
+1. 查看指定表的列信息。
+
+    ```sql
+    SHOW FULL COLUMNS FROM tbl;
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_INDEX.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_INDEX.md
new file mode 100644
index 00000000000000..57541ee4d3786c
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_INDEX.md
@@ -0,0 +1,86 @@
+---
+displayed_sidebar: docs
+keywords: ['suoyin']
+---
+
+# SHOW INDEX
+
+## 功能
+
+查看索引，当前仅支持查看指定表的所有 [Bitmap 索引](../../../table_design/indexes/Bitmap_index.md)。创建 bitmap 索引为异步过程，使用该语句只能查看到已经创建完成的索引。
+
+:::tip
+
+该操作不需要权限。
+
+:::
+
+## 语法
+
+```SQL
+SHOW INDEX[ES] FROM [db_name.]table_name [FROM db_name]
+```
+
+或
+
+```SQL
+SHOW KEY[S] FROM [db_name.]table_name [FROM db_name]
+```
+
+## 参数说明
+
+| **参数**   | **必选** | **说明**     |
+| ---------- | -------- | ------------ |
+| db_name    | 否       | 数据库名称。 |
+| table_name | 是       | 表名。       |
+
+## 返回结果说明
+
+```Plain
++---------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
+| Table   | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
++---------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
+```
+
+返回结果中的参数说明：
+
+| **参数**    | **说明**         |
+| ----------- | ---------------- |
+| Key_name    | 索引名称。       |
+| Column_name | 创建索引的列名。 |
+| Index_type  | 索引类型。       |
+| Comment     | 索引备注。       |
+
+> 说明：当前仅支持查看 bitmap 索引，bitmap 索引的相关信息仅包括以上四个参数。返回结果中的其他参数和 bitmap 索引无关。
+
+## 示例
+
+为表`sales_records`中的`item_id`列创建 bitmap 索引，索引名称为`index3`。表`sales_records`所属数据库为`d0`。
+
+```SQL
+CREATE INDEX index3 ON sales_records (item_id) USING BITMAP COMMENT '';
+```
+
+查看表`sales_records`的所有索引。
+
+```Plain
+SHOW INDEX FROM d0.sales_records;
+
++----------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
+| Table                            | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
++----------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
+| default_cluster:d0.sales_records |            | index3   |              | item_id     |           |             |          |        |      | BITMAP     | NULL    |
++----------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
+```
+
+或
+
+```Plain
+SHOW KEY FROM sales_records FROM d0;
+
++----------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
+| Table                            | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
++----------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
+| default_cluster:d0.sales_records |            | index3   |              | item_id     |           |             |          |        |      | BITMAP     | NULL    |
++----------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
+```
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md
new file mode 100644
index 00000000000000..4feb3570459380
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md
@@ -0,0 +1,102 @@
+---
+displayed_sidebar: docs
+keywords: ['fenqu']
+---
+
+# SHOW PARTITIONS
+
+## 功能
+
+该语句用于展示正常分区或临时分区信息。
+
+## 语法
+
+```sql
+SHOW [TEMPORARY] PARTITIONS FROM [db_name.]table_name [WHERE] [ORDER BY] [LIMIT]
+```
+
+> 说明
+>
+> * 支持 PartitionId，PartitionName，State，Buckets，ReplicationNum，LastConsistencyCheckTime 等列的过滤。
+> * 该语法只支持 StarRocks 表 (即 `"ENGINE" = "OLAP"`)。
+> * 自 3.0 版本起，该操作需要对应表的 SELECT 权限。 3.0 版本之前，该操作需要对应数据库和表的 SELECT_PRIV 权限。
+
+## 返回结果说明
+
+```SQL
++-------------+---------------+----------------+---------------------+--------------------+--------+--------------+-------+--------------------+---------+----------------+---------------+---------------------+--------------------------+----------+------------+----------+
+| PartitionId | PartitionName | VisibleVersion | VisibleVersionTime  | VisibleVersionHash | State  | PartitionKey | Range | DistributionKey    | Buckets | ReplicationNum | StorageMedium | CooldownTime        | LastConsistencyCheckTime | DataSize | IsInMemory | RowCount |
++-------------+---------------+----------------+---------------------+--------------------+--------+--------------+-------+--------------------+---------+----------------+---------------+---------------------+--------------------------+----------+------------+----------+
+```
+
+| **字段**                     | **说明**                                                         |
+| ------------------------ | ------------------------------------------------------------ |
+| PartitionId              | 分区 ID。                                                    |
+| PartitionName            | 分区名。                                                     |
+| VisibleVersion           | 最后一次成功导入的版本号。每次成功导入，则版本号加 1。   |
+| VisibleVersionTime       | 最后一次成功导入的时间。                                   |
+| VisibleVersionHash       | 最后一次成功导入的版本号的哈希值。                         |
+| State                    | 分区的状态。固定为 `Normal`。                                |
+| PartitionKey             | 分区键，由一个或多个分区列组成。                                                     |
+| Range                    | Range 分区的范围，为左闭右开区间。                           |
+| DistributionKey          | 分区中数据进行哈希分桶时的分桶键。                           |
+| Buckets                  | 分区中的分桶数量。                                           |
+| ReplicationNum           | 分区中每个 Tablet 的副本数量。                                |
+| StorageMedium            | 数据存储介质。返回值为 `HDD` 表示机械硬盘，返回值为 `SSD` 表示固态硬盘。           |
+| CooldownTime             | 数据降冷时间。如果一开始数据的存储介质为 SSD ，在该时间点之后，数据存储介质会从 SSD 切换为 HDD。 格式："yyyy-MM-dd HH:mm:ss"。|
+| LastConsistencyCheckTime | 最后一次一致性检查的时间。`NULL` 表示没有进行一致性检查。    |
+| DataSize                 | 分区中数据大小。                                             |
+| IsInMemory               | 该分区数据是否全部存储在内存中。                             |
+| RowCount                 | 该分区数据行数。                                             |
+| MaxCS                    | 该分区最大 Compaction Score。仅限存算分离集群。                   |
+
+## 示例
+
+1. 查询指定数据库（例如 `test`）下指定表（例如 `site_access`）的所有正式分区信息：
+
+    ```SQL
+    MySQL > show partitions from test.site_access\G
+    *************************** 1. row ***************************
+                PartitionId: 20990
+            PartitionName: p2019 
+            VisibleVersion: 1
+        VisibleVersionTime: 2023-08-08 15:45:13
+        VisibleVersionHash: 0
+                    State: NORMAL
+                PartitionKey: datekey
+                    Range: [types: [DATE]; keys: [2019-01-01]; ..types: [DATE]; keys: [2020-01-01]; )
+            DistributionKey: site_id
+                    Buckets: 6
+            ReplicationNum: 3
+            StorageMedium: HDD
+                CooldownTime: 9999-12-31 23:59:59
+    LastConsistencyCheckTime: NULL
+                    DataSize:  4KB   
+                IsInMemory: false
+                    RowCount: 3 
+    1 row in set (0.00 sec)
+    ```
+
+2. 查询指定数据库（例如 `test`）下指定表（例如 `site_access`）的所有临时分区信息：
+
+    ```sql
+    SHOW TEMPORARY PARTITIONS FROM test.site_access;
+    ```
+
+3. 查询指定数据库（例如 `test`）下指定表（例如 `site_access`）的指定分区（例如 `p1`）的信息。
+
+    ```sql
+    -- 正常分区
+    SHOW PARTITIONS FROM test.site_access WHERE PartitionName = "p1";
+    -- 临时分区
+    SHOW TEMPORARY PARTITIONS FROM test.site_access WHERE PartitionName = "p1";
+    ```
+
+4. 查询指定数据库（例如 `test`）下指定表（例如 `site_access`）的最新分区的信息。
+
+    ```sql
+    -- 正常分区
+    SHOW PARTITIONS FROM test.site_access ORDER BY PartitionId DESC LIMIT 1;
+    -- 临时分区
+    SHOW TEMPORARY PARTITIONS FROM test.site_access ORDER BY PartitionId DESC LIMIT 1;
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_TABLES.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_TABLES.md
new file mode 100644
index 00000000000000..1f9068dc8a3072
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_TABLES.md
@@ -0,0 +1,87 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW TABLES
+
+## 功能
+
+查看指定数据库下的所有表。可以是 StarRocks 内部表或外部数据源中的表。
+
+> **注意**
+>
+> 要查看外部数据源中的表，必须有对应 External Catalog 的 USAGE 权限。
+
+## 语法
+
+```sql
+SHOW TABLES [FROM <catalog_name>.<db_name>]
+```
+
+## 参数说明
+
+| **参数**          | **必选** | **说明**                                                     |
+| ----------------- | -------- | ------------------------------------------------------------ |
+| catalog_name | 否       | Internal catalog 或 External catalog 的名称。<ul><li>如果不指定或指定为 internal catalog 名称（`default_catalog`），则查看当前 StarRocks 集群中的数据库。</li><li>如果指定 external catalog 名称，则查看外部数据源中的数据库。</li></ul> 您可以使用 [SHOW CATALOGS](../Catalog/SHOW_CATALOGS.md) 命令查看当前集群的内外部 catalog。|
+| db_name | 否       | 数据库名称。如果不指定，默认为当前数据库。 |
+
+## 示例
+
+示例一：连接到 StarRocks 集群后，查看 Internal catalog 下数据库 `example_db` 中的表。下面两个语句功能对等。
+
+```plain
+show tables from example_db;
++----------------------------+
+| Tables_in_example_db       |
++----------------------------+
+| depts                      |
+| depts_par                  |
+| emps                       |
+| emps2                      |
++----------------------------+
+
+show tables from default_catalog.example_db;
++----------------------------+
+| Tables_in_example_db       |
++----------------------------+
+| depts                      |
+| depts_par                  |
+| emps                       |
+| emps2                      |
++----------------------------+
+```
+
+示例二：使用 `USE <db_name>;` 连接到 `example_db` 数据库后，查看当前数据库下的表。
+
+```plain
+show tables;
+
++----------------------------+
+| Tables_in_example_db       |
++----------------------------+
+| depts                      |
+| depts_par                  |
+| emps                       |
+| emps2                      |
++----------------------------+
+```
+
+示例三：查看 External catalog `hudi_catalog` 下指定数据库 `hudi_db` 中的表。
+
+```plain
+show tables from hudi_catalog.hudi_db;
++----------------------------+
+| Tables_in_hudi_db          |
++----------------------------+
+| hudi_sync_mor              |
+| hudi_table1                |
++----------------------------+
+```
+
+您也可以通过 `SET CATALOG <catalog_name>;` 切换到 `hudi_catalog` 下，然后执行 `SHOW TABLES FROM hudi_db;` 来查看该数据库下的表。
+
+## 相关文档
+
+- [SHOW CATALOGS](../Catalog/SHOW_CATALOGS.md)：查看当前集群下所有的 Catalog。
+- [SHOW DATABASES](../Database/SHOW_DATABASES.md)：查看 Internal Catalog 或 External Catalog 下的所有数据库。
+- [SET CATALOG](../Catalog/SET_CATALOG.md)：切换 Catalog。
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_TABLET.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_TABLET.md
new file mode 100644
index 00000000000000..77ef496e1ccb53
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/SHOW_TABLET.md
@@ -0,0 +1,229 @@
+---
+displayed_sidebar: docs
+---
+
+# SHOW TABLET
+
+## 功能
+
+查看 Tablet 相关信息。
+
+> **注意**
+>
+> 从 3.0 版本开始，该操作需要 SYSTEM 级 OPERATE 权限，以及对应表的 SELECT 权限。2.5 及之前版本，该操作需要 ADMIN_PRIV 权限。
+
+## 语法
+
+### 查看某张表或某个分区内所有 Tablet 的信息
+
+您也可以指定 WHERE 子句来过滤符合条件的 Tablet。
+
+```sql
+SHOW TABLET
+FROM [<db_name>.]<table_name>
+[PARTITION(<partition_name>, ...]
+[
+WHERE
+    [version = <version_number>] 
+    [[AND] backendid = <backend_id>] 
+    [[AND] STATE = "NORMAL"|"ALTER"|"CLONE"|"DECOMMISSION"]
+]
+[ORDER BY <field_name> [ASC | DESC]]
+[LIMIT [<offset>,]<limit>]
+```
+
+| **参数**       | **必选** | **说明**                                                     |
+| -------------- | -------- | ------------------------------------------------------------ |
+| db_name        | 否       | 数据库名称。如不指定该参数，默认使用当前数据库。                     |
+| table_name     | 是       | 表名。必须指定，否则报错。                                                     |
+| partition_name | 否       | 分区名。                                                     |
+| version_number | 否       | 数据版本号。                                                   |
+| backend_id     | 否       | Tablet 副本所在的 BE 的 ID。                                 |
+| STATE          | 否       | Tablet 副本的状态。<ul><li>`NORMAL`：副本处于正常状态。</li><li>`ALTER`：副本正在做 Rollup 或 schema change。</li><li>`CLONE`：副本处于 clone 状态（未完成 clone 的副本暂不可用）。</li><li>`DECOMMISSION`：副本处于 DECOMMISSION 状态（下线）。</li></ul> |
+| field_name     | 否       | 将返回结果按照指定字段升序或降序排列。`SHOW TABLET FROM <table_name>` 返回的字段都可以作为排序字段。<ul><li>如要升序排列，指定 `ORDER BY field_name ASC`。</li><li>如要降序排列，指定 `ORDER BY field_name DESC`。</li></ul> |
+| offset         | 否       | 返回结果中跳过的 Tablet 的数量，默认值为 0。例如 `OFFSET 5` 表示跳过前 5 个 Tablet，返回剩下的结果。 |
+| limit          | 否       | 查看指定数量的 Tablet。例如 `LIMIT 10` 会显示 10 个 Tablet 的信息。如果不指定该参数，则默认显示所有符合筛选条件的 Tablet。 |
+
+### 查看单个 Tablet 的信息
+
+通过 `SHOW TABLET FROM <table_name>` 获取了所有 Tablet ID 后，您可以只查询某个 Tablet 的详细信息。
+
+```sql
+SHOW TABLET <tablet_id>
+```
+
+| **参数**  | **必选** | **说明**       |
+| --------- | -------- | -------------- |
+| tablet_id | 是       | Tablet 的 ID |
+
+## 返回结果说明
+
+### 查看某张表或分区内的所有 tablet
+
+```plain
++----------+-----------+-----------+------------+---------+-------------+-------------------+-----------------------+------------------+----------------------+---------------+----------+----------+--------+-------------------------+--------------+------------------+--------------+----------+----------+-------------------+
+| TabletId | ReplicaId | BackendId | SchemaHash | Version | VersionHash | LstSuccessVersion | LstSuccessVersionHash | LstFailedVersion | LstFailedVersionHash | LstFailedTime | DataSize | RowCount | State  | LstConsistencyCheckTime | CheckVersion | CheckVersionHash | VersionCount | PathHash | MetaUrl  | CompactionStatus  |
++----------+-----------+-----------+------------+---------+-------------+-------------------+-----------------------+------------------+----------------------+---------------+----------+----------+--------+-------------------------+--------------+------------------+--------------+----------+----------+-------------------+
+```
+
+| **字段**                | **说明**                        |
+| ----------------------- | ------------------------------- |
+| TabletId                | Table 的 ID。                   |
+| ReplicaId               | 副本 ID。                      |
+| BackendId               | 副本所在的 BE 的 ID。           |
+| SchemaHash              | Schema hash（随机生成）。        |
+| Version                 | 数据版本号。                      |
+| VersionHash             | 数据版本号的 hash。               |
+| LstSuccessVersion       | 最后一次 load 成功的版本。        |
+| LstSuccessVersionHash   | 最后一次 load 成功的版本的 hash。 |
+| LstFailedVersion        | 最后一次 load 失败的版本。`-1` 表示不存在失败的版本。 |
+| LstFailedVersionHash    | 最后一次 load 失败的版本的 hash。 |
+| LstFailedTime           | 最后一次 load 失败的时间。`NULL` 表示没有失败。        |
+| DataSize                | 该 Tablet 上的数据大小。             |
+| RowCount                | 该 Tablet 上的数据行数。             |
+| State                   | Tablet 的副本状态。              |
+| LstConsistencyCheckTime | 最后一次一致性检查的时间。`NULL` 表示没有进行一致性检查.  |
+| CheckVersion            | 一致性检查的版本。`-1` 表示不存在检查版本。    |
+| CheckVersionHash        | 一致性检查的版本的 hash。         |
+| VersionCount            | 数据版本数。                      |
+| PathHash                | Tablet 存储目录的 hash。        |
+| MetaUrl                 | 通过 URL 查询更多的 meta 信息。     |
+| CompactionStatus        | 通过 URL 查询 Compaction 状态。    |
+
+### 查看单个 tablet
+
+```Plain
++--------+-----------+---------------+-----------+------+---------+-------------+---------+--------+-----------+
+| DbName | TableName | PartitionName | IndexName | DbId | TableId | PartitionId | IndexId | IsSync | DetailCmd |
++--------+-----------+---------------+-----------+------+---------+-------------+---------+--------+-----------+
+```
+
+| **字段**      | **说明**                                                     |
+| ------------- | ------------------------------------------------------------ |
+| DbName        | Tablet 所属数据库的名称。                                    |
+| TableName     | Tablet 所属表的名称。                                        |
+| PartitionName | Tablet 所属分区的名称。                                      |
+| IndexName     | 索引名称。                                                     |
+| DbId          | 数据库 ID。                                                  |
+| TableId       | 表 ID。                                                      |
+| PartitionId   | 分区 ID。                                                    |
+| IndexId       | 索引 ID。                                                      |
+| IsSync        | 检查 Tablet 上的数据是否与表 meta 里的数据一致。`false` 表示检查项数据有缺失。`true` 表示检查项数据正常，即代表 Tablet 正常。 |
+| DetailCmd     | 通过 URL 查询更多信息。                                      |
+
+## 示例
+
+在数据库 `example_db` 下创建表 `test_show_tablet`。
+
+```sql
+CREATE TABLE `test_show_tablet` (
+  `k1` date NULL COMMENT "",
+  `k2` datetime NULL COMMENT "",
+  `k3` char(20) NULL COMMENT "",
+  `k4` varchar(20) NULL COMMENT "",
+  `k5` boolean NULL COMMENT "",
+  `k6` tinyint(4) NULL COMMENT "",
+  `k7` smallint(6) NULL COMMENT "",
+  `k8` int(11) NULL COMMENT "",
+  `k9` bigint(20) NULL COMMENT "",
+  `k10` largeint(40) NULL COMMENT "",
+  `k11` float NULL COMMENT "",
+  `k12` double NULL COMMENT "",
+  `k13` decimal128(27, 9) NULL COMMENT ""
+) ENGINE=OLAP 
+DUPLICATE KEY(`k1`, `k2`, `k3`, `k4`, `k5`)
+COMMENT "OLAP"
+PARTITION BY RANGE(`k1`)
+(PARTITION p20210101 VALUES [("2021-01-01"), ("2021-01-02")),
+PARTITION p20210102 VALUES [("2021-01-02"), ("2021-01-03")),
+PARTITION p20210103 VALUES [("2021-01-03"), ("2021-01-04")),
+PARTITION p20210104 VALUES [("2021-01-04"), ("2021-01-05")),
+PARTITION p20210105 VALUES [("2021-01-05"), ("2021-01-06")),
+PARTITION p20210106 VALUES [("2021-01-06"), ("2021-01-07")),
+PARTITION p20210107 VALUES [("2021-01-07"), ("2021-01-08")),
+PARTITION p20210108 VALUES [("2021-01-08"), ("2021-01-09")),
+PARTITION p20210109 VALUES [("2021-01-09"), ("2021-01-10")))
+DISTRIBUTED BY HASH(`k1`, `k2`, `k3`);
+```
+
+- 查看指定数据库下指定表的所有 Tablet 信息。以下示例仅截取其中一行 tablet 信息来说明。
+
+    ```plain
+    mysql> show tablet from example_db.test_show_tablet\G
+    *************************** 1. row ***************************
+               TabletId: 9588955
+              ReplicaId: 9588956
+              BackendId: 10004
+             SchemaHash: 0
+                Version: 1
+            VersionHash: 0
+      LstSuccessVersion: 1
+  LstSuccessVersionHash: 0
+       LstFailedVersion: -1
+   LstFailedVersionHash: 0
+          LstFailedTime: NULL
+               DataSize: 0B
+               RowCount: 0
+                  State: NORMAL
+  LstConsistencyCheckTime: NULL
+           CheckVersion: -1
+       CheckVersionHash: 0
+           VersionCount: 1
+               PathHash: 0
+                MetaUrl: http://172.26.92.141:8038/api/meta/header/9588955
+       CompactionStatus: http://172.26.92.141:8038/api/compaction/show?tablet_id=9588955
+    ```
+
+- 查看 id 为 9588955 的 Tablet 的信息。
+
+    ```plain
+    mysql> show tablet 9588955\G
+    *************************** 1. row ***************************
+       DbName: example_db
+    TableName: test_show_tablet
+    PartitionName: p20210103
+    IndexName: test_show_tablet
+         DbId: 11145
+      TableId: 9588953
+  PartitionId: 9588946
+      IndexId: 9588954
+       IsSync: true
+    DetailCmd: SHOW PROC '/dbs/11145/9588953/partitions/9588946/9588954/9588955';
+    ```
+
+- 查看表中分区 `p20210103` 的 Tablet 信息。
+
+    ```sql
+        SHOW TABLET FROM test_show_tablet partition(p20210103);
+    ```
+
+- 返回表中 10 个 Tablet 的信息。
+
+    ```sql
+        SHOW TABLET FROM test_show_tablet limit 10;
+    ```
+
+- 从偏移位置 5 开始获取 10 个 Tablet 的信息。
+
+    ```sql
+        SHOW TABLET FROM test_show_tablet limit 5,10;
+    ```
+
+- 按照 `backendid`，`version`，`state` 字段进行过滤。
+
+    ```sql
+        SHOW TABLET FROM test_show_tablet
+        WHERE backendid = 10004 and version = 1 and state = "NORMAL";
+    ```
+
+- 按照 `version` 字段进行排序。
+
+    ```sql
+        SHOW TABLET FROM table_name where backendid = 10004 order by version;
+    ```
+
+- 查看 index 名为 `test_show_tablet` 的 Tablet 的信息。
+
+    ```sql
+        SHOW TABLET FROM test_show_tablet where indexname = "test_show_tablet";
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/TRUNCATE_TABLE.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/TRUNCATE_TABLE.md
new file mode 100644
index 00000000000000..c855576bc2530b
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/TRUNCATE_TABLE.md
@@ -0,0 +1,37 @@
+---
+displayed_sidebar: docs
+---
+
+# TRUNCATE TABLE
+
+## 功能
+
+该语句用于清空指定表和分区的数据。
+
+## 语法
+
+```sql
+TRUNCATE TABLE [db.]tbl[ PARTITION(p1, p2, ...)]
+```
+
+说明：
+
+1. 该语句清空数据，但保留表或分区。
+2. 不同于 DELETE，该语句只能整体清空指定的表或分区，不能添加过滤条件。
+3. 不同于 DELETE，使用该方式清空数据**不会对查询性能造成影响**。
+4. 该操作会直接删除数据，删除掉的数据**不可恢复**。
+5. 使用该命令时，表状态需为 NORMAL，即不允许正在进行 SCHEMA CHANGE 等操作。
+
+## 示例
+
+1. 清空 example_db 下的表 tbl。
+
+    ```sql
+    TRUNCATE TABLE example_db.tbl;
+    ```
+
+2. 清空表 tbl 的 p1 和 p2 分区。
+
+    ```sql
+    TRUNCATE TABLE tbl PARTITION(p1, p2);
+    ```
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/UPDATE.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/UPDATE.md
new file mode 100644
index 00000000000000..92413e027bc76b
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/UPDATE.md
@@ -0,0 +1,174 @@
+---
+displayed_sidebar: docs
+---
+
+# UPDATE
+
+该语句用于更新一张主键表中的数据行。
+
+2.3 ～ 2.5 版本，StarRocks 提供 UPDATE 语句，并且仅支持单表 UPDATE 且不支持公用表表达式（CTE）。从 3.0 版本开始，StarRocks 丰富了 UPDATE 语法，支持使用多表关联和 CTE。如果需要将待更新的表与数据库中其他表关联，则可以在 FROM 子句或 CTE 中引用其他的表。从 3.1 版本开始，支持列模式的部分更新，适用于涉及少数列但是大量行的场景，加快更新速度。
+
+## 使用说明
+
+如果为多表 UPDATE，则您需要确保 UPDATE 语句中 FROM 子句的表表达式可以转换成等价的 JOIN 查询语句。因为 StarRocks 实际执行 UPDATE 语句时，内部会进行这样的转换。假设 UPDATE 语句为 `UPDATE t0 SET v1=t1.v1 FROM t1 WHERE t0.pk = t1.pk;`，该 FROM 子句的表表达式可以转换为 `t0 JOIN t1 ON t0.pk=t1.pk;`。并且 StarRocks 根据 JOIN 查询的结果集，匹配待更新表的数据行，更新其指定列的值。如果结果集中存在多行数据和待更新表的某一行数据相匹配，则待更新表中这行数据指定列更新后的值，是结果集多行数据中随机一行的指定列的值。
+
+## 语法
+
+**单表 UPDATE**
+
+如果待更新表的数据行满足 WHERE 条件，则对该数据行的指定列赋予新值。
+
+```SQL
+[ WITH <with_query> [, ...] ]
+UPDATE <table_name>
+    SET <column_name> = <expression> [, ...]
+    WHERE <where_condition>
+```
+
+**多表 UPDATE**
+
+基于多表关联查询的结果集与待更新的表进行匹配，如果待更新表的数据行匹配结果集并且满足 WHERE 条件，则对该数据行的指定列赋予新值。
+
+```SQL
+[ WITH <with_query> [, ...] ]
+UPDATE <table_name>
+    SET <column_name> = <expression> [, ...]
+    [ FROM <from_item> [, ...] ]
+    WHERE <where_condition>
+```
+
+## 参数说明
+
+`with_query`
+
+一个或多个可以在 UPDATE 语句中通过名字引用的 CTE。CTE 是一个临时结果集，可以提高复杂语句的易读性。
+
+`table_name`
+
+待更新的表的名称。
+
+`column_name`
+
+待更新的列的名称。不需要包含表名，例如 `UPDATE t1 SET t1.col = 1` 是不合法的。
+
+`expression`
+
+给列赋值的表达式。
+
+`from_item`
+
+引用数据库中一个或者多个其他的表。该表与待更新的表进行连接，WHERE 子句指定连接条件，最终基于连接查询的结果集给待更新的表中匹配行的列赋值。 例如 FROM 子句为 `FROM t1 WHERE t0.pk = t1.pk;`，StarRocks 实际执行 UPDATE 语句时会将该 FROM 子句的表表达式会转换为 `t0 JOIN t1 ON t0.pk=t1.pk;`。
+
+`where_condition`
+
+只有满足 WHERE 条件的行才会被更新。该参数为必选，防止误更新整张表。如需更新整张表，请使用 `WHERE true`。如果使用[列模式的部分更新](#列模式的部分更新自-31)，则该参数不是必选。
+
+## 列模式的部分更新（自 3.1）
+
+列模式的部分更新适用于涉及少数列并且大量行的场景。在该场景，开启列模式，更新速度更快。例如，在一个包含 100 列的表中，每次更新 10 列（占比 10%）并更新所有行，则开启列模式，更新性能将提高 10 倍。
+
+系统变量 `partial_update_mode` 用于控制部分更新的模式，支持取值为：
+
+* `auto`（默认值），表示由系统通过分析更新语句以及其涉及的列，自动判断执行部分更新时使用的模式。如果满足如下标准，则系统自动使用列模式：
+  * 更新的列数占所有列数的百分比小于 30%，并且更新的列数少于 4 个。
+  * 更新语句中没有使用 WHERE 条件。
+  
+  反之，则系统不会使用列模式。
+* `column`，指定使用列模式执行部分更新，比较适用于涉及少数列并且大量行的部分列更新场景。
+
+您可以使用 `EXPLAIN UPDATE xxx` 查看执行部分列更新的模式。
+
+## 示例
+
+### 单表 UPDATE
+
+创建表 `Employees` 来记录雇员信息，向表中插入五行数据。
+
+```SQL
+CREATE TABLE Employees (
+    EmployeeID INT,
+    Name VARCHAR(50),
+    Salary DECIMAL(10, 2)
+)
+PRIMARY KEY (EmployeeID) 
+DISTRIBUTED BY HASH (EmployeeID)
+PROPERTIES ("replication_num" = "3");
+
+INSERT INTO Employees VALUES
+    (1, 'John Doe', 5000),
+    (2, 'Jane Smith', 6000),
+    (3, 'Robert Johnson', 5500),
+    (4, 'Emily Williams', 4500),
+    (5, 'Michael Brown', 7000);
+```
+
+如果需要对所有员工加薪 10%，则可以执行如下语句：
+
+```SQL
+UPDATE Employees
+SET Salary = Salary * 1.1  -- 将薪水增加10%
+WHERE true;
+```
+
+如果需要对薪水低于平均薪水的员工加薪 10%，则可以执行如下语句，
+
+```SQL
+UPDATE Employees
+SET Salary = Salary * 1.1  -- 将薪水增加10%
+WHERE Salary < (SELECT AVG(Salary) FROM Employees);
+```
+
+您也可以使用 CTE 改写上述语句，增加易读性。
+
+```SQL
+WITH AvgSalary AS (
+    SELECT AVG(Salary) AS AverageSalary
+    FROM Employees
+)
+UPDATE Employees
+SET Salary = Salary * 1.1  -- 将薪水增加10%
+FROM AvgSalary
+WHERE Employees.Salary < AvgSalary.AverageSalary;
+```
+
+### 多表 UPDATE
+
+创建表 `Accounts` 来记录账户信息，向表中插入三行数据。
+
+```SQL
+CREATE TABLE Accounts (
+    Accounts_id BIGINT NOT NULL,
+    Name VARCHAR(26) NOT NULL,
+    Sales_person VARCHAR(50) NOT NULL
+) 
+PRIMARY KEY (Accounts_id)
+DISTRIBUTED BY HASH (Accounts_id)
+PROPERTIES ("replication_num" = "3");
+
+INSERT INTO Accounts VALUES
+    (1,'Acme Corporation','John Doe'),
+    (2,'Acme Corporation','Robert Johnson'),
+    (3,'Acme Corporation','Lily Swift');
+```
+
+如果需要给表 `Employees` 中 Acme Corporation 公司管理帐户的员工加薪 10%，则可以执行如下语句：
+
+```SQL
+UPDATE Employees
+SET Salary = Salary * 1.1  -- 将薪水增加10%
+FROM Accounts
+WHERE Accounts.name = 'Acme Corporation'
+    AND Employees.Name = Accounts.Sales_person;
+```
+
+您也可以使用 CTE 改写上述语句，增加易读性。
+
+```SQL
+WITH Acme_Accounts as (
+    SELECT * from Accounts
+    WHERE Accounts.name = 'Acme Corporation'
+)
+UPDATE Employees SET Salary = Salary * 1.1 -- 将薪水增加10%
+FROM Acme_Accounts
+WHERE Employees.Name = Acme_Accounts.Sales_person;
+```
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/_category_.yml b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/_category_.yml
new file mode 100644
index 00000000000000..d6c37930b0a845
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/_category_.yml
@@ -0,0 +1,6 @@
+position: 80 # float position is supported
+label: '表，分区，分桶，索引'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/docs/zh/sql-reference/sql-statements/table_bucket_part_index/auto_increment.md b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/auto_increment.md
new file mode 100644
index 00000000000000..092c2a60363a7f
--- /dev/null
+++ b/docs/zh/sql-reference/sql-statements/table_bucket_part_index/auto_increment.md
@@ -0,0 +1,396 @@
+---
+displayed_sidebar: docs
+---
+
+# AUTO_INCREMENT
+
+StarRocks 自 3.0 版本起支持 `AUTO_INCREMENT` 列属性，可以简化数据管理。本文介绍 `AUTO_INCREMENT` 列属性的应用场景、用法和特性。
+
+## 功能介绍
+
+当插入一条新的记录时，StarRocks 会自动为该记录的自增列分配一个表内全局唯一的整数值作为自增 ID，并且后续值会自动增加。自增列可以简化数据管理，同时可以加速一些查询场景。以下是一些自增列的应用场景：
+
+- 主键：自增列可用于生成主键，确保每条记录都有一个唯一的标识符，方便查询和管理数据。
+- 关联表：在多个表之间进行关联时，可以使用自增列作为 Join Key，相比使用如 UUID 等字符串类型的列能够提高查询速度。
+- 高基数列的精确去重计数：将自增列的 ID 值作为字典唯一值列，相比用字符串直接精确去重计数，查询速度能提升数倍甚至十数倍。
+
+您需要在 CREATE TABLE 语句中通过 `AUTO_INCREMENT` 属性指定自增列。自增列的数据类型只支持 BIGINT，从 1 开始增加，自增步长为 1。 并且 StarRocks 支持[隐式分配自增列的值和显式指定自增 ID](#分配自增列的值)。
+
+## 基本用法
+
+### 建表指定自增列
+
+创建表 `test_tbl1`，包含两列，分别为 `id` 和 `number`，如下所示，建表时指定 `number` 列为自增列：
+
+```SQL
+CREATE TABLE test_tbl1
+(
+    id BIGINT NOT NULL, 
+    number BIGINT NOT NULL AUTO_INCREMENT
+) 
+PRIMARY KEY (id) 
+DISTRIBUTED BY HASH(id)
+PROPERTIES("replicated_storage" = "true");
+```
+
+### 分配自增列的值
+
+**隐式分配自增列的值**
+
+导入时，您无需指定自增列的值，StarRocks 会自动为该自增列分配唯一的整数值，并插入到表中。
+
+```SQL
+INSERT INTO test_tbl1 (id) VALUES (1);
+INSERT INTO test_tbl1 (id) VALUES (2);
+INSERT INTO test_tbl1 (id) VALUES (3),(4),(5);
+```
+
+查看表的数据。
+
+```SQL
+mysql > SELECT * FROM test_tbl1 ORDER BY id;
++------+--------+
+| id   | number |
++------+--------+
+|    1 |      1 |
+|    2 |      2 |
+|    3 |      3 |
+|    4 |      4 |
+|    5 |      5 |
++------+--------+
+5 rows in set (0.02 sec)
+```
+
+您也可以指定自增列的值为 `DEFAULT`，StarRocks 会自动为该自增列分配唯一的整数值，并插入到表中。
+
+```SQL
+INSERT INTO test_tbl1 (id, number) VALUES (6, DEFAULT);
+```
+
+查看表的数据。
+
+```SQL
+mysql > SELECT * FROM test_tbl1 ORDER BY id;
++------+--------+
+| id   | number |
++------+--------+
+|    1 |      1 |
+|    2 |      2 |
+|    3 |      3 |
+|    4 |      4 |
+|    5 |      5 |
+|    6 |      6 |
++------+--------+
+6 rows in set (0.02 sec)
+```
+
+在实际使用中，您查看表的数据时可能会返回如下结果。这是因为 StarRocks 无法保证自增列的值按照时间顺序严格递增，但是能保证自增列的值大致上是递增的。更多介绍，请参见[单调性保证](#单调性保证)。
+
+```SQL
+mysql > SELECT * FROM test_tbl1 ORDER BY id;
++------+--------+
+| id   | number |
++------+--------+
+|    1 |      1 |
+|    2 | 100001 |
+|    3 | 200001 |
+|    4 | 200002 |
+|    5 | 200003 |
+|    6 | 200004 |
++------+--------+
+6 rows in set (0.01 sec)
+```
+
+**显式指定自增列的值**
+
+您也可以显式地指定自增列的值，并插入到表中。
+
+```SQL
+INSERT INTO test_tbl1 (id, number) VALUES (7, 100);
+
+-- 查看表的数据
+mysql > SELECT * FROM test_tbl1 ORDER BY id;
++------+--------+
+| id   | number |
++------+--------+
+|    1 |      1 |
+|    2 | 100001 |
+|    3 | 200001 |
+|    4 | 200002 |
+|    5 | 200003 |
+|    6 | 200004 |
+|    7 |    100 |
++------+--------+
+7 rows in set (0.01 sec)
+```
+
+并且，后续插入新数据时不会影响 StarRocks 新生成的自增列的值。
+
+```SQL
+INSERT INTO test_tbl1 (id) VALUES (8);
+
+-- 查看表的数据
+mysql > SELECT * FROM test_tbl1 ORDER BY id;
++------+--------+
+| id   | number |
++------+--------+
+|    1 |      1 |
+|    2 | 100001 |
+|    3 | 200001 |
+|    4 | 200002 |
+|    5 | 200003 |
+|    6 | 200004 |
+|    7 |    100 |
+|    8 |      2 |
++------+--------+
+8 rows in set (0.01 sec)
+```
+
+**注意事项**
+
+因为同时隐式分配和显式指定自增 ID 可能会破坏自增 ID 的[全局唯一性](#唯一性保证)，建议您不要混用。
+
+## 基本特性
+
+### 唯一性保证
+
+在一般情况下，StarRocks 保证自增 ID 在一张表内是全局唯一的。
+
+但是，如果您混用隐式分配和显式指定自增 ID，则可能会破坏自增 ID 的全局唯一性。因此建议您不要同时隐式分配和显式指定自增 ID。以下是一个简单的示例：
+
+创建表 `test_tbl2`，其中列 `number` 为自增列。
+
+```SQL
+CREATE TABLE test_tbl2
+(
+    id BIGINT NOT NULL,
+    number BIGINT NOT NULL AUTO_INCREMENT
+ ) 
+PRIMARY KEY (id) 
+DISTRIBUTED BY HASH(id)
+PROPERTIES("replicated_storage" = "true");
+```
+
+往表 `test_tbl2` 中同时隐式分配和显式指定自增 ID。
+
+```SQL
+INSERT INTO test_tbl2 (id, number) VALUES (1, DEFAULT);
+INSERT INTO test_tbl2 (id, number) VALUES (2, 2);
+INSERT INTO test_tbl2 (id) VALUES (3);
+```
+
+查询表 `test_tbl2` 的数据。
+
+```SQL
+mysql > SELECT * FROM test_tbl2 ORDER BY id;
++------+--------+
+| id   | number |
++------+--------+
+|    1 |      1 |
+|    2 |      2 |
+|    3 | 100001 |
++------+--------+
+3 rows in set (0.08 sec)
+```
+
+### 单调性保证
+
+为了提升分配自增 ID 的性能，BE 会本地缓存部分自增 ID。在这种情况下，StarRocks 无法保证自增 ID 按照时间顺序严格递增，只能保证自增 ID 大致上是递增的。
+> **说明**
+>
+> BE 缓存的自增 ID 数量由 FE 动态参数 `auto_increment_cache_size` 决定，默认是 `100000`。您可以使用 `ADMIN SET FRONTEND CONFIG ("auto_increment_cache_size" = "xxx");` 进行修改 。
+假设 StarRocks 集群具有一个 FE 节点和两个 BE 节点。创建表 `test_tbl3` 并且插入五行数据，如下所示：
+
+```SQL
+CREATE TABLE test_tbl3
+(
+    id BIGINT NOT NULL,
+    number BIGINT NOT NULL AUTO_INCREMENT
+) 
+PRIMARY KEY (id)
+DISTRIBUTED BY HASH(id)
+PROPERTIES("replicated_storage" = "true");
+
+INSERT INTO test_tbl3 VALUES (1, DEFAULT);
+INSERT INTO test_tbl3 VALUES (2, DEFAULT);
+INSERT INTO test_tbl3 VALUES (3, DEFAULT);
+INSERT INTO test_tbl3 VALUES (4, DEFAULT);
+INSERT INTO test_tbl3 VALUES (5, DEFAULT);
+```
+
+表 test_tbl3` 中自增 ID 不是单调递增的。这是因为两个 BE 节点分别缓存了 [1, 100000] 和 [100001, 200000] 范围内的自增 ID，使用多个 INSERT 语句导入数据时，会发送给不同的 BE，由不同 BE 分配自增 ID，因此无法保证自增 ID 的严格单调性。
+
+```SQL
+mysql > SELECT * FROM test_tbl3 ORDER BY id;
++------+--------+
+| id   | number |
++------+--------+
+|    1 |      1 |
+|    2 | 100001 |
+|    3 | 200001 |
+|    4 |      2 |
+|    5 | 100002 |
++------+--------+
+5 rows in set (0.07 sec)
+```
+
+## 部分列更新与自增列
+
+本小节介绍具有自增列的表如何实现部分列更新。
+
+> **说明**
+>
+> 目前仅主键表支持部分列更新。
+
+### 自增列为主键
+
+如果自增列为主键或主键的一部分，由于部分列更新时您需要指定主键，因此部分列更新的用户行为和没有定义自增列完全一样。
+
+1. 在数据库 `example_db` 中创建表 `test_tbl4`，并且插入一条数据。
+
+    ```SQL
+    -- 建表
+    CREATE TABLE test_tbl4
+    (
+        id BIGINT AUTO_INCREMENT,
+        name BIGINT NOT NULL,
+        job1 BIGINT NOT NULL,
+        job2 BIGINT NOT NULL
+    ) 
+    PRIMARY KEY (id, name)
+    DISTRIBUTED BY HASH(id)
+    PROPERTIES("replicated_storage" = "true");
+
+    -- 准备数据
+    mysql > INSERT INTO test_tbl4 (id, name, job1, job2) VALUES (0, 0, 1, 1);
+    Query OK, 1 row affected (0.04 sec)
+    {'label':'insert_6af28e77-7d2b-11ed-af6e-02424283676b', 'status':'VISIBLE', 'txnId':'152'}
+
+    -- 查询数据
+    mysql > SELECT * FROM test_tbl4 ORDER BY id;
+    +------+------+------+------+
+    | id   | name | job1 | job2 |
+    +------+------+------+------+
+    |    0 |    0 |    1 |    1 |
+    +------+------+------+------+
+    1 row in set (0.01 sec)
+    ```
+
+2. 准备 CSV 文件 **my_data4.csv**，用于更新表 `test_tbl4`。 CSV 文件包括自增列的 ID 值，不包含列 `job1` 的值，并且第一行数据的主键存在表 `test_tbl4` 中，第二行的主键不存在。
+
+    ```Plaintext
+    0,0,99
+    1,1,99
+    ```
+
+3. 通过 [Stream Load](../loading_unloading/STREAM_LOAD.md) 将 CSV 文件数据更新至表 `test_tbl4`。
+
+    ```Bash
+    curl --location-trusted -u <username>:<password> -H "label:1" \
+        -H "column_separator:," \
+        -H "partial_update:true" \
+        -H "columns:id,name,job2" \
+        -T my_data4.csv -XPUT \
+        http://<fe_host>:<fe_http_port>/api/example_db/test_tbl4/_stream_load
+    ```
+
+4. 查询更新后的表。第一条数据原先已经存在表 `test_tbl4` 中，并且列 `job1` 保持原先的值。第二条数据是新插入的数据，由于列 `job1` 没有定义默认值，因此部分列更新框架会直接将此列的值设置为 `0`。
+
+    ```SQL
+    mysql > SELECT * FROM test_tbl4 ORDER BY id;
+    +------+------+------+------+
+    | id   | name | job1 | job2 |
+    +------+------+------+------+
+    |    0 |    0 |    1 |   99 |
+    |    1 |    1 |    0 |   99 |
+    +------+------+------+------+
+    2 rows in set (0.01 sec)
+    ```
+
+### 自增列不为主键
+
+如果自增列不是主键或者主键的一部分，并且 Stream Load 中未给出自增 ID，则会发生以下情况：
+
+- 如果表中已经存在该行，则 StarRocks 不会更新自增ID。
+- 如果表中不存在该行，则 StarRocks 会自动生成新的自增 ID。
+
+该特性可以构建字典表的值，用于加速字符串的精确去重计数。
+
+1. 在数据库 `example_db` 中创建表 `test_tbl5`，指定 `job1` 为自增列，并且插入一条数据。
+
+    ```SQL
+    -- 建表
+    CREATE TABLE test_tbl5
+    (
+        id BIGINT NOT NULL,
+        name BIGINT NOT NULL,
+        job1 BIGINT NOT NULL AUTO_INCREMENT,
+        job2 BIGINT NOT NULL
+    )
+    PRIMARY KEY (id, name)
+    DISTRIBUTED BY HASH(id)
+    PROPERTIES("replicated_storage" = "true");
+
+    -- 准备数据
+    mysql > INSERT INTO test_tbl5 VALUES (0, 0, -1, -1);
+    Query OK, 1 row affected (0.04 sec)
+    {'label':'insert_458d9487-80f6-11ed-ae56-aa528ccd0ebf', 'status':'VISIBLE', 'txnId':'94'}
+
+    mysql > SELECT * FROM test_tbl5 ORDER BY id;
+    +------+------+------+------+
+    | id   | name | job1 | job2 |
+    +------+------+------+------+
+    |    0 |    0 |   -1 |   -1 |
+    +------+------+------+------+
+    1 row in set (0.01 sec)
+    ```
+
+2. 准备 CSV 文件 **my_data5.csv**，用于更新表 `test_tbl5`。CSV 文件不包含自增列 `job1` 的值，并且第一行数据的主键存在于表中，第二、三行数据的主键不存在。
+
+    ```Plaintext
+    0,0,99
+    1,1,99
+    2,2,99
+    ```
+
+3. 通过 [Stream Load](../loading_unloading/STREAM_LOAD.md) 将 CSV 文件数据导入至表 `test_tbl5`。
+
+    ```Bash
+    curl --location-trusted -u <username>:<password> -H "label:2" \
+        -H "column_separator:," \
+        -H "partial_update:true" \
+        -H "columns: id,name,job2" \
+        -T my_data5.csv -XPUT \
+        http://<fe_host>:<fe_http_port>/api/example_db/test_tbl5/_stream_load
+    ```
+
+4. 查询更新后的表。第一条数据已经存在表 `test_tbl5` 中，自增列 `job1` 保持原先的 ID 值。第二、三条数据是新插入的数据，自增列 `job1` 的 ID 值由 StarRocks 自动生成。
+
+    ```SQL
+    mysql > SELECT * FROM test_tbl5 ORDER BY id;
+    +------+------+--------+------+
+    | id   | name | job1   | job2 |
+    +------+------+--------+------+
+    |    0 |    0 |     -1 |   99 |
+    |    1 |    1 |      1 |   99 |
+    |    2 |    2 | 100001 |   99 |
+    +------+------+--------+------+
+    3 rows in set (0.01 sec)
+    ```
+
+## 使用限制
+
+- 创建具有自增列的表时，必须设置 `'replicated_storage' = 'true'`，以确保所有副本具有相同的自增 ID。
+- 每个表最多只能有一个自增列。
+- 自增列必须是 BIGINT 类型。
+- 自增列必须为 `NOT NULL`，并且不支持指定默认值。
+- 您可以从具有自增列的主键表中删除数据。但是如果自增列不为 Primary Key，则您在删除数据时，需要注意以下两个场景中的限制：
+  - DELETE 操作的同时，还存在一个部分列更新的导入任务，其中只包含 UPSERT 操作。如果 UPSERT 操作和 DELETE 操作命中了同一行数据，并且 UPSERT 操作在 DELETE 操作后执行，则该 UPSERT 操作可能会失效。
+  - 存在一个部分列更新的导入任务，其中包含若干个对同一行数据的 UPSERT、DELETE 操作。如果某个 UPSERT 操作在 DELETE 操作后执行，则该 UPSERT 操作可能会失效。
+- 不支持使用 ALTER TABLE 添加 `AUTO_INCREMENT` 属性。
+- 自 3.1 版本起存算分离模式支持该功能。
+- 不支持设置自增列的起始值和自增步长。
+
+## Keywords
+
+AUTO_INCREMENT, AUTO INCREMENT
diff --git a/docs/zh/sql-reference/sys/grants_to_roles.md b/docs/zh/sql-reference/sys/grants_to_roles.md
new file mode 100644
index 00000000000000..9967a05d023ef1
--- /dev/null
+++ b/docs/zh/sql-reference/sys/grants_to_roles.md
@@ -0,0 +1,63 @@
+---
+displayed_sidebar: docs
+---
+
+# grants_to_roles
+
+您可以通过查询 `grants_to_roles` 视图查看用户自定义角色的权限。
+
+:::note
+
+默认仅拥有 `user_admin` 角色的用户或角色可以查询此视图，或通过 [GRANT](../../sql-reference/sql-statements/account-management/GRANT.md) 语句将此视图的权限赋予给其他用户。
+
+:::
+
+`grants_to_roles` 提供以下字段：
+
+| **字段**        | **描述**                                                     |
+| --------------- | ------------------------------------------------------------ |
+| GRANTEE         | 被授予此权限的角色。只有用户自定义角色会出现在此视图中，系统预制角色不会出现在此视图中。 |
+| OBJECT_CATALOG  | 权限对象所属的 Catalog。如果权限为 SYSTEM、RESOURCE GROUP、RESOURCE、USER 或 GLOBAL FUNCTION 级别权限，则返回 `NULL`。 |
+| OBJECT_DATABASE | 权限对象所属的数据库。如果权限为 SYSTEM、RESOURCE GROUP、RESOURCE、USER、GLOBAL FUNCTION 或 CATALOG 级别权限，则返回 `NULL`。 |
+| OBJECT_NAME     | 权限对象所属的表。如果权限为 SYSTEM、RESOURCE GROUP、RESOURCE、USER、GLOBAL FUNCTION、CATALOG 或 DATABASE 级别权限，则返回 `NULL`。 |
+| OBJECT_TYPE     | 权限对象的类型。                                             |
+| PRIVILEGE_TYPE  | 权限的类型。同一个对象上的不同权限会进行合并展示。如示例中，`role_test` 同时拥有 `default_catalog.db_test.tbl1`的`SELECT`和`ALTER`权限，则会合并展示。 |
+| IS_GRANTABLE    | 被授予角色是否拥有该权限的 GRANT 权限。                      |
+
+示例：
+
+```Plain
+MySQL > SELECT * FROM sys.grants_to_roles LIMIT 5\G
+*************************** 1. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: db_test
+    OBJECT_NAME: tbl1
+    OBJECT_TYPE: TABLE
+ PRIVILEGE_TYPE: SELECT, ALTER
+   IS_GRANTABLE: NO
+*************************** 2. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: db_test
+    OBJECT_NAME: tbl2
+    OBJECT_TYPE: TABLE
+ PRIVILEGE_TYPE: SELECT
+   IS_GRANTABLE: YES
+*************************** 3. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: db_test
+    OBJECT_NAME: mv_test
+    OBJECT_TYPE: MATERIALIZED VIEW
+ PRIVILEGE_TYPE: SELECT
+   IS_GRANTABLE: YES
+*************************** 4. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: NULL
+OBJECT_DATABASE: NULL
+    OBJECT_NAME: NULL
+    OBJECT_TYPE: SYSTEM
+ PRIVILEGE_TYPE: CREATE RESOURCE GROUP
+   IS_GRANTABLE: NO
+```
diff --git a/docs/zh/sql-reference/sys/grants_to_users.md b/docs/zh/sql-reference/sys/grants_to_users.md
new file mode 100644
index 00000000000000..e1ebc3b461d7b0
--- /dev/null
+++ b/docs/zh/sql-reference/sys/grants_to_users.md
@@ -0,0 +1,47 @@
+---
+displayed_sidebar: docs
+---
+
+# grants_to_users
+
+您可以通过查询 `grants_to_users` 视图查看授予用户的权限。
+
+:::note
+
+默认仅拥有 `user_admin` 角色的用户或角色可以查询此视图，或通过 [GRANT](../../sql-reference/sql-statements/account-management/GRANT.md) 语句将此视图的权限赋予给其他用户。
+
+:::
+
+`grants_to_users` 提供以下字段：
+
+| **字段**        | **描述**                                                     |
+| --------------- | ------------------------------------------------------------ |
+| GRANTEE         | 被授予此权限的用户。                                         |
+| OBJECT_CATALOG  | 权限对象所属的 Catalog。如果权限为 SYSTEM、RESOURCE GROUP、RESOURCE、USER 或 GLOBAL FUNCTION 级别权限，则返回 `NULL`。 |
+| OBJECT_DATABASE | 权限对象所属的数据库。如果权限为 SYSTEM、RESOURCE GROUP、RESOURCE、USER、GLOBAL FUNCTION 或 CATALOG 级别权限，则返回 `NULL`。 |
+| OBJECT_NAME     | 权限对象所属的表。如果权限为 SYSTEM、RESOURCE GROUP、RESOURCE、USER、GLOBAL FUNCTION、CATALOG 或 DATABASE 级别权限，则返回 `NULL`。 |
+| OBJECT_TYPE     | 权限对象的类型。                                             |
+| PRIVILEGE_TYPE  | 权限的类型。同一个对象上的不同权限会进行合并展示。如示例中，`'user1'@'%'` 同时拥有 `default_catalog.db_test.view_test`的 SELECT 和 DROP 权限，则会合并展示。 |
+| IS_GRANTABLE    | 被授予用户是否拥有该权限的 GRANT 权限。                      |
+
+示例：
+
+```Plain
+MySQL > SELECT * FROM sys.grants_to_users LIMIT 5\G
+*************************** 1. row ***************************
+        GRANTEE: 'user1'@'%'
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: db_test
+    OBJECT_NAME: view_test
+    OBJECT_TYPE: VIEW
+ PRIVILEGE_TYPE: SELECT, DROP
+   IS_GRANTABLE: NO
+*************************** 2. row ***************************
+        GRANTEE: 'user2'@'%'
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: simo
+    OBJECT_NAME: view_test
+    OBJECT_TYPE: VIEW
+ PRIVILEGE_TYPE: SELECT
+   IS_GRANTABLE: NO
+```
diff --git a/docs/zh/sql-reference/sys/object_dependencies.md b/docs/zh/sql-reference/sys/object_dependencies.md
new file mode 100644
index 00000000000000..a0392b62db5885
--- /dev/null
+++ b/docs/zh/sql-reference/sys/object_dependencies.md
@@ -0,0 +1,52 @@
+---
+displayed_sidebar: docs
+---
+
+# object_dependencies
+
+您可以通过查询 `object_dependencies` 视图查看异步物化视图的依赖关系。
+
+`object_dependencies` 提供以下字段：
+
+| **字段**            | **描述**                                           |
+| ------------------- | -------------------------------------------------- |
+| object_id           | 对象的 ID。                                        |
+| object_name         | 对象的名称。                                       |
+| object_database     | 对象所在的数据库。                                 |
+| object_catalog      | 对象所在的 Catalog。该字段常为 `default_catalog`。 |
+| object_type         | 对象的类型。该字段常为 `MATERIALIZED_VIEW`。       |
+| ref_object_id       | 依赖对象的 ID。                                    |
+| ref_object_name     | 依赖对象的名称。                                   |
+| ref_object_database | 依赖对象所在的数据库。                             |
+| ref_object_catalog  | 依赖的对象所在的 Catalog。                         |
+| ref_object_type     | 依赖的对象的类型。                                 |
+
+示例：
+
+```Plain
+MySQL > SELECT * FROM sys.object_dependencies\G
+*************************** 1. row ***************************
+          object_id: 11115
+        object_name: mv2
+    object_database: test_db
+     object_catalog: default_catalog
+        object_type: MATERIALIZED_VIEW
+      ref_object_id: 11092
+    ref_object_name: mv1
+ref_object_database: test_db
+ ref_object_catalog: default_catalog
+    ref_object_type: MATERIALIZED_VIEW
+*************************** 2. row ***************************
+          object_id: 11092
+        object_name: mv1
+    object_database: test_db
+     object_catalog: default_catalog
+        object_type: MATERIALIZED_VIEW
+      ref_object_id: 11074
+    ref_object_name: test_tbl
+ref_object_database: test_db
+ ref_object_catalog: default_catalog
+    ref_object_type: OLAP
+```
+
+上述示例表明，物化视图 `mv1` 是基于 StarRocks 内表 `test_tbl` 创建的，物化视图 `mv2` 是基于物化视图 `mv1` 创建的。
diff --git a/docs/zh/sql-reference/sys/role_edges.md b/docs/zh/sql-reference/sys/role_edges.md
new file mode 100644
index 00000000000000..bae3d4af1ae129
--- /dev/null
+++ b/docs/zh/sql-reference/sys/role_edges.md
@@ -0,0 +1,42 @@
+---
+displayed_sidebar: docs
+---
+
+# role_edges
+
+您可以通过查询 `role_edges` 视图查看角色的授予关系。
+
+:::note
+
+默认仅拥有 `user_admin` 角色的用户或角色可以查询此视图，或通过 [GRANT](../../sql-reference/sql-statements/account-management/GRANT.md) 语句将此视图的权限赋予给其他用户。
+
+:::
+
+`role_edges` 提供以下字段：
+
+| **字段**  | **描述**                                                     |
+| --------- | ------------------------------------------------------------ |
+| FROM_ROLE | 授予的角色。因为一个角色可以授予多个角色和用户，所以 `role_edges` 视图可以返回多条具有相同 `FROM_ROLE` 的记录。 |
+| TO_ROLE   | 当前 `FROM_ROLE` 被授予的角色。如果当前 `FROM_ROLE` 被授予用户，则返回 `NULL`。 |
+| TO_USER   | 当前 `FROM_ROLE` 被授予的用户。如果当前 `FROM_ROLE` 被授予角色，则返回 `NULL`。 |
+
+示例：
+
+```Plain
+MySQL > SELECT * FROM sys.role_edges;
++------------+------------+---------------+
+| FROM_ROLE  | TO_ROLE    | TO_USER       |
++------------+------------+---------------+
+| dba_leader | director   | NULL          |
+| dba        | dba_leader | NULL          |
+| dba        | NULL       | 'aneesh'@'%'  |
+| dba        | NULL       | 'chelsea'@'%' |
+| dba_leader | NULL       | 'albert'@'%'  |
+| director   | NULL       | 'stan'@'%'    |
+| root       | NULL       | 'root'@'%'    |
++------------+------------+---------------+
+```
+
+下图说明了以上示例中角色授予的嵌套关系：
+
+![role_edges](../../_assets/role_edges.png)
\ No newline at end of file
diff --git a/docs/zh/sql-reference/sys/sys.md b/docs/zh/sql-reference/sys/sys.md
new file mode 100644
index 00000000000000..637d09b0ff56ac
--- /dev/null
+++ b/docs/zh/sql-reference/sys/sys.md
@@ -0,0 +1,68 @@
+---
+displayed_sidebar: docs
+---
+
+# 系统元数据库
+
+本文介绍如何通过系统定义的视图查看 StarRocks 集群中独有的的元数据。
+
+每个 StarRocks 集群维护一个数据库 `sys`，其中包含数张由系统定义的视图。这些视图提供了一个统一且易于使用的接口，使您可以全面了解 StarRocks 集群中的权限结构和对象依赖关系等信息。
+
+## 通过 `sys` 查看元数据信息
+
+您可以通过查询 `sys` 中的视图来查看 StarRocks 实例中的元数据信息。
+
+以下示例通过查询 `grants_to_roles` 视图查看用户自定义角色的权限。
+
+```Plain
+MySQL > SELECT * FROM sys.grants_to_roles LIMIT 5\G
+*************************** 1. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: db_test
+    OBJECT_NAME: tbl1
+    OBJECT_TYPE: TABLE
+ PRIVILEGE_TYPE: SELECT, ALTER
+   IS_GRANTABLE: NO
+*************************** 2. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: db_test
+    OBJECT_NAME: tbl2
+    OBJECT_TYPE: TABLE
+ PRIVILEGE_TYPE: SELECT
+   IS_GRANTABLE: YES
+*************************** 3. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: default_catalog
+OBJECT_DATABASE: db_test
+    OBJECT_NAME: mv_test
+    OBJECT_TYPE: MATERIALIZED VIEW
+ PRIVILEGE_TYPE: SELECT
+   IS_GRANTABLE: YES
+*************************** 4. row ***************************
+        GRANTEE: role_test
+ OBJECT_CATALOG: NULL
+OBJECT_DATABASE: NULL
+    OBJECT_NAME: NULL
+    OBJECT_TYPE: SYSTEM
+ PRIVILEGE_TYPE: CREATE RESOURCE GROUP
+   IS_GRANTABLE: NO
+```
+
+## `sys` 中的视图
+
+`sys` 中包含以下视图：
+
+| **视图名**               | **描述**                                                       |
+| ----------------------- | ------------------------------------------------------------- |
+| [grants_to_roles](../sys/grants_to_roles.md)     | 记录了授予用户自定义角色的权限信息。       |
+| [grants_to_users](../sys/grants_to_users.md)     | 记录了授予用户的权限信息。               |
+| [role_edges](../sys/role_edges.md)          | 记录了角色的授予关系。                        |
+| [object_dependencies](../sys/object_dependencies.md) | 记录了异步物化视图的依赖关系。        |
+
+:::note
+
+`sys` 库中的视图根据使用场景，默认只有一些管理员角色拥有查询权限。您也可以根据实际情况使用对应管理员角色将系统视图的查询权限赋予给其他用户。
+
+:::
diff --git a/docs/zh/sql-reference/template_for_config.md b/docs/zh/sql-reference/template_for_config.md
index cf58b7553aa98c..8bd4f0ff6e2036 100644
--- a/docs/zh/sql-reference/template_for_config.md
+++ b/docs/zh/sql-reference/template_for_config.md
@@ -1,5 +1,6 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
+unlisted: true
 ---
 
 # FE/BE 参数和变量模板
diff --git a/docs/zh/sql-reference/user_defined_variables.md b/docs/zh/sql-reference/user_defined_variables.md
new file mode 100644
index 00000000000000..f9684e1397f4de
--- /dev/null
+++ b/docs/zh/sql-reference/user_defined_variables.md
@@ -0,0 +1,74 @@
+---
+displayed_sidebar: docs
+---
+
+# 用户自定义变量
+
+本文介绍如何声明和使用用户自定义变量。
+
+自 2.5 版本起， StarRocks 支持用户声明自定义变量 (user-defined variables)。自定义变量用于存储特定的值，后续引用在 SQL 语句中，简化 SQL 语句的编写和避免重复计算。
+
+## 使用说明
+
+- 当前仅支持声明会话级别的自定义变量，即用户只能使用自己声明的自定义变量，且如客户端断开，那么当前会话中所有自定义变量将失效。
+- StarRocks 暂不支持使用 SHOW 语句查看已有的自定义变量。
+- 不支持声明 BITMAP、HLL 和 PERCENTILE 类型的自定义变量，JSON 类型的自定义变量会转换为 STRING 类型进行存储。
+- 自 v3.2.7 起，StarRocks 支持声明 ARRAY 类型的自定义变量。
+
+## 声明自定义变量
+
+### 语法
+
+```Plain
+SET @var_name = expr [, ...];
+```
+
+> **说明**
+>
+> - 声明自定义变量时，必须加前缀 `@`。
+> - 可同时声明多个自定义变量，多个变量之间用逗号 (,) 隔开。
+> - 支持多次声明同一自定义变量，新声明的值会覆盖原有值。
+> - 如在一个 SQL 语句中引用了没有声明过的变量，该变量值默认为 `NULL` 且为 STRING 类型。
+
+### 参数说明
+
+| **参数** | **必填** | **说明**                                                     |
+| -------- | -------- | ------------------------------------------------------------ |
+| var_name | 是       | 自定义变量名称，命名规则如下：<ul><li>必须由字母 (a-z 或 A-Z)、数字 (0-9) 或下划线 (\_) 组成。</li><li>总长度不能超过 64 个字符。</li></ul> 例如，@'my-var'、@"my-var" 和 @\`my-var\`。字符串类型的变量名称可以包含除字母、数字和下划线 (_) 以外的其他字符，例如句点 (.)。 |
+| expr     | 是       | 自定义变量存储的值。支持简单值，例如 `43`；也支持复杂表达式，如 SELECT 查询返回的值。表达式计算结果的数据类型即为变量的数据类型。 |
+
+### 示例
+
+示例一：声明一个数值为自定义变量。
+
+```SQL
+SET @var = 43;
+```
+
+示例二：声明 SELECT 语句返回的值为自定义变量。
+
+```SQL
+SET @var = (SELECT SUM(v1) FROM test);
+```
+
+示例三：一次性声明多个变量。
+
+```SQL
+SET @v1=1, @v2=2;
+```
+
+## **使用场景**
+
+- 简化 SQL 语句的编写。示例如下，执行 SELECT 语句时，`@var` 会被 `1` 替换。
+
+  ```Plain
+  SET @var = 1;
+  SELECT @var, v1 from test;
+  ```
+
+- 避免重复计算。示例如下，执行 SELECT 语句时，`@var` 会被 `select sum(c1) from tbl` 命令的计算结果替换。
+
+  ```Plain
+  SET @var = (select sum(c1) from tbl);
+  SELECT @var, v1 from test;
+  ```
diff --git a/docs/zh/table_design/Data_distribution.md b/docs/zh/table_design/Data_distribution.md
index bd77ee1680494b..6e043464bf01ef 100644
--- a/docs/zh/table_design/Data_distribution.md
+++ b/docs/zh/table_design/Data_distribution.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['fenqu','fentong', 'lengre']
 toc_max_heading_level: 4
 description: 分区与分桶
@@ -546,7 +546,7 @@ DISTRIBUTED BY HASH(site_id);
 
 执行如下语句，删除 `site_access` 表中分区 p1 及数据：
 
-> 说明：分区中的数据不会立即删除，会在 Trash 中保留一段时间（默认为一天）。如果误删分区，可以通过 [RECOVER 命令](../sql-reference/sql-statements/data-definition/backup_restore/RECOVER.md)恢复分区及数据。
+> 说明：分区中的数据不会立即删除，会在 Trash 中保留一段时间（默认为一天）。如果误删分区，可以通过 [RECOVER 命令](../sql-reference/sql-statements/backup_restore/RECOVER.md)恢复分区及数据。
 
 ```SQL
 ALTER TABLE site_access
@@ -723,7 +723,7 @@ DISTRIBUTED BY HASH(site_id,city_code);
   :::warning
 
   - 如果需要启用按需动态增加分桶数量，您需要设置表属性 `PROPERTIES("bucket_size"="xxx")`，指定单个分桶的大小。如果分区的数据量不大，则可以设置 `bucket_size` 为 1 GB，如果分区的数据量大，则可以设置 `bucket_size` 为 4 GB。
-  - 启用后，如果需要回滚至 3.1 版本，则需要删除启用按需动态增加分桶数量的表，并且手动执行元数据 checkpoint [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/Administration/ALTER_SYSTEM.md) 成功后才能回滚。
+  - 启用后，如果需要回滚至 3.1 版本，则需要删除启用按需动态增加分桶数量的表，并且手动执行元数据 checkpoint [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) 成功后才能回滚。
 
   :::
 
@@ -834,7 +834,7 @@ DISTRIBUTED BY HASH(site_id,city_code);
   :::warning
 
   - 如果需要启用按需动态增加分桶数量，您需要设置表属性 `PROPERTIES("bucket_size"="xxx")`，指定单个分桶的大小。如果分区的数据量不大，则可以设置 `bucket_size` 为 1 GB，如果分区的数据量大，则可以设置 `bucket_size` 为 4 GB。
-  - 启用后，如果需要回滚至 3.1 版本，则需要删除启用按需动态增加分桶数量的表，并且手动执行元数据 checkpoint [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/Administration/ALTER_SYSTEM.md) 成功后才能回滚。
+  - 启用后，如果需要回滚至 3.1 版本，则需要删除启用按需动态增加分桶数量的表，并且手动执行元数据 checkpoint [ALTER SYSTEM CREATE IMAGE](../sql-reference/sql-statements/cluster-management/nodes_processes/ALTER_SYSTEM.md) 成功后才能回滚。
 
   :::
 
@@ -906,13 +906,13 @@ DISTRIBUTED BY HASH(site_id,city_code);
 
 #### 查看分桶数量
 
-如果查看分区中分桶数量，您可以执行 [SHOW PARTITIONS](../sql-reference/sql-statements/data-manipulation/SHOW_PARTITIONS.md)。
+如果查看分区中分桶数量，您可以执行 [SHOW PARTITIONS](../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md)。
 
 :::info
 
 - 如果是随机分桶表并且开启按需动态增加分桶数量，建表后在导入过程中，分区的分桶数量会**动态增加**，返回结果显示的是分区**当前**的分桶数量。
 
-- 如果是随机分桶表，分区内部实际的划分层次为：分区 > 子分区 > 分桶，为了增加分桶数量，StarRocks 实际上是新增一个子分区，子分区包括一定数量的分桶，因此  [SHOW PARTITIONS](../sql-reference/sql-statements/data-manipulation/SHOW_PARTITIONS.md) 返回结果中会显示分区名称相同的多条数据行，表示同一分区中子分区的情况。
+- 如果是随机分桶表，分区内部实际的划分层次为：分区 > 子分区 > 分桶，为了增加分桶数量，StarRocks 实际上是新增一个子分区，子分区包括一定数量的分桶，因此  [SHOW PARTITIONS](../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md) 返回结果中会显示分区名称相同的多条数据行，表示同一分区中子分区的情况。
 
 :::
 
@@ -944,7 +944,7 @@ DISTRIBUTED BY HASH(site_id,city_code);
     ALTER TABLE t ORDER BY k2, k1;
     ```
 
-更多信息，参见 [ALTER TABLE](../sql-reference/sql-statements/data-definition/ALTER_TABLE.md) 。
+更多信息，参见 [ALTER TABLE](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) 。
 
 ## 最佳实践
 
diff --git a/docs/zh/table_design/StarRocks_table_design.md b/docs/zh/table_design/StarRocks_table_design.md
index 84a6da2aeb6876..044d9e74974891 100644
--- a/docs/zh/table_design/StarRocks_table_design.md
+++ b/docs/zh/table_design/StarRocks_table_design.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 表概览
@@ -42,7 +42,7 @@ ORDER BY (uid, name);
 
 <Replicanum />
 
-执行 [DESCRIBE](../sql-reference/sql-statements/Utility/DESCRIBE.md) 查看表结构。
+执行 [DESCRIBE](../sql-reference/sql-statements/table_bucket_part_index/DESCRIBE.md) 查看表结构。
 
 ```SQL
 MySQL [example_db]> DESCRIBE user_access;
@@ -59,7 +59,7 @@ MySQL [example_db]> DESCRIBE user_access;
 6 rows in set (0.00 sec)
 ```
 
-执行 [SHOW CREATE TABLE](../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE.md) 来查看建表语句。
+执行 [SHOW CREATE TABLE](../sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md) 来查看建表语句。
 
 ```SQL
 MySQL [example_db]> SHOW CREATE TABLE user_access\G
@@ -120,7 +120,7 @@ StarRocks 提供两种分桶方式：
 - 哈希分桶：根据数据的分桶键值，将数据划分至分桶。选择查询时经常使用的条件列组成分桶键，能有效提高查询效率。
 - 随机分桶：随机划分数据至分桶。这种分桶方式更加简单易用。
 
-### [数据类型](../sql-reference/data-types/data-type-list.md)
+### [数据类型](../sql-reference/data-types/README.md)
 
 除了基本的数据类型，如数值、日期和字符串类型，StarRocks 还支持复杂的半结构化数据类型，包括 ARRAY、JSON、MAP、STRUCT。
 
@@ -144,10 +144,10 @@ StarRocks 提供内置索引，包括前缀索引、Ordinal 索引和 ZoneMap 
 
 您可以在以下 SQL 语句中添加 `TEMPORARY` 关键字创建或删除临时表：
 
-- [CREATE TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md)
-- [CREATE TABLE AS SELECT](../sql-reference/sql-statements/data-definition/CREATE_TABLE_AS_SELECT.md)
-- [CREATE TABLE LIKE](../sql-reference/sql-statements/data-definition/CREATE_TABLE_LIKE.md)
-- [DROP TABLE](../sql-reference/sql-statements/data-definition/DROP_TABLE.md)
+- [CREATE TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md)
+- [CREATE TABLE AS SELECT](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_AS_SELECT.md)
+- [CREATE TABLE LIKE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE_LIKE.md)
+- [DROP TABLE](../sql-reference/sql-statements/table_bucket_part_index/DROP_TABLE.md)
 
 :::note
 
diff --git a/docs/zh/table_design/Table_design.md b/docs/zh/table_design/Table_design.md
index 0bf71f0772480b..c8b45779ae0d17 100644
--- a/docs/zh/table_design/Table_design.md
+++ b/docs/zh/table_design/Table_design.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 介绍
diff --git a/docs/zh/table_design/Temporary_partition.md b/docs/zh/table_design/Temporary_partition.md
index 2f574f546af6e9..18a2917815cd02 100644
--- a/docs/zh/table_design/Temporary_partition.md
+++ b/docs/zh/table_design/Temporary_partition.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['fenqu']
 ---
 
@@ -13,7 +13,7 @@ keywords: ['fenqu']
 
 - 原子覆盖写操作
 
-  如果您需要重写某一正式分区的数据，同时保证重写过程中可以查看数据，您可以先创建一个对应的临时分区，将新的数据导入到临时分区后，通过替换操作，原子地替换原有正式分区，生成新正式分区。对于非分区表的原子覆盖写操作，请参考 [ALTER TABLE - SWAP](../sql-reference/sql-statements/data-definition/ALTER_TABLE.md#swap)。
+  如果您需要重写某一正式分区的数据，同时保证重写过程中可以查看数据，您可以先创建一个对应的临时分区，将新的数据导入到临时分区后，通过替换操作，原子地替换原有正式分区，生成新正式分区。对于非分区表的原子覆盖写操作，请参考 [ALTER TABLE - SWAP](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md#swap)。
 - 调整分区数据的查询并发
 
   如果您需要修改某一正式分区的分桶数，您可以先创建一个对应分区范围的临时分区，并指定新的分桶数，然后通过 `INSERT INTO` 命令将原有正式分区的数据导入到临时分区中，通过替换操作，原子地替换原有正式分区，生成新正式分区。
@@ -96,7 +96,7 @@ ADD TEMPORARY PARTITIONS START ("2020-04-01") END ("2021-01-01") EVERY (INTERVAL
 
 ## 查看临时分区
 
-您可以通过如下 [SHOW TEMPORARY PARTITIONS](../sql-reference/sql-statements/data-manipulation/SHOW_PARTITIONS.md) 命令，查看表的临时分区。
+您可以通过如下 [SHOW TEMPORARY PARTITIONS](../sql-reference/sql-statements/table_bucket_part_index/SHOW_PARTITIONS.md) 命令，查看表的临时分区。
 
 ```SQL
 SHOW TEMPORARY PARTITIONS FROM site_access;
@@ -108,7 +108,7 @@ SHOW TEMPORARY PARTITIONS FROM site_access;
 
 ### 通过 `INSERT INTO` 命令导入
 
-您可以通过如下 [INSERT INTO](../sql-reference/sql-statements/data-manipulation/INSERT.md) 命令将数据导入临时分区。
+您可以通过如下 [INSERT INTO](../sql-reference/sql-statements/loading_unloading/INSERT.md) 命令将数据导入临时分区。
 
 ```SQL
 INSERT INTO site_access TEMPORARY PARTITION (tp1) VALUES ("2020-01-01",1,"ca","lily",4);
@@ -125,7 +125,7 @@ curl --location-trusted -u <username>:<password> -H "label:label1" -H "temporary
     http://host:port/api/example_db/site_access/_stream_load    
 ```
 
-有关语法和参数等更多信息，请参见 [STREAM LOAD](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md)。
+有关语法和参数等更多信息，请参见 [STREAM LOAD](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md)。
 
 ### 通过 BROKER LOAD 方式导入
 
@@ -145,7 +145,7 @@ WITH BROKER
 );
 ```
 
-有关语法和参数等更多信息，请参见 [BROKER LOAD](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md)。
+有关语法和参数等更多信息，请参见 [BROKER LOAD](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md)。
 
 ### 通过 ROUTINE LOAD 方式导入
 
@@ -162,7 +162,7 @@ FROM KAFKA
 );
 ```
 
-有关语法和参数等更多信息，请参见 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/data-manipulation/CREATE_ROUTINE_LOAD.md)。
+有关语法和参数等更多信息，请参见 [CREATE ROUTINE LOAD](../sql-reference/sql-statements/loading_unloading/routine_load/CREATE_ROUTINE_LOAD.md)。
 
 ## 查询临时分区的数据
 
@@ -288,9 +288,9 @@ ALTER TABLE site_access DROP TEMPORARY PARTITION tp1;
 
 注意事项
 
-- 使用 `DROP` 命令直接删除数据库或表后，您可以在限定时间内通过 [RECOVER](../sql-reference/sql-statements/data-definition/backup_restore/RECOVER.md) 命令恢复该数据库或表，但临时分区无法被恢复。
-- 使用 `ALTER` 命令删除正式分区后，您可以在限定时间内通过 [RECOVER](../sql-reference/sql-statements/data-definition/backup_restore/RECOVER.md) 命令恢复。正式分区与临时分区不相关联，操作正式分区不会对临时分区产生影响。
-- 使用 `ALTER` 命令删除临时分区后，您无法通过 [RECOVER](../sql-reference/sql-statements/data-definition/backup_restore/RECOVER.md) 命令恢复。
+- 使用 `DROP` 命令直接删除数据库或表后，您可以在限定时间内通过 [RECOVER](../sql-reference/sql-statements/backup_restore/RECOVER.md) 命令恢复该数据库或表，但临时分区无法被恢复。
+- 使用 `ALTER` 命令删除正式分区后，您可以在限定时间内通过 [RECOVER](../sql-reference/sql-statements/backup_restore/RECOVER.md) 命令恢复。正式分区与临时分区不相关联，操作正式分区不会对临时分区产生影响。
+- 使用 `ALTER` 命令删除临时分区后，您无法通过 [RECOVER](../sql-reference/sql-statements/backup_restore/RECOVER.md) 命令恢复。
 - 使用 `TRUNCATE` 命令清空表后，表的临时分区会被删除，且不可恢复。
 - 使用 `TRUNCATE` 命令清空正式分区时，临时分区不受影响。
 - 不可使用 `TRUNCATE` 命令清空临时分区。
diff --git a/docs/zh/table_design/catalog_db_tbl.md b/docs/zh/table_design/catalog_db_tbl.md
index 862d9e231a0f8d..a9559ee5a64b65 100644
--- a/docs/zh/table_design/catalog_db_tbl.md
+++ b/docs/zh/table_design/catalog_db_tbl.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Catalogs、databases 和 tables
@@ -44,7 +44,7 @@ StarRocks 中的表分为两类：内部表和外部表。
 
 物化视图是特殊的物理表，能够存储基于基表的预计算结果。当您对基表执行复杂查询时，StarRocks 可以自动复用物化视图中的预计算结果，实现查询透明加速、湖仓加速和数据建模等业务需求。物化视图分为同步物化视图和异步物化视图。其中异步物化视图能力更加强大，能够存储基于多个基表（内部表和外部表）的预计算结果，并且支持丰富的聚合算子。
 
-## [视图](../sql-reference/sql-statements/data-definition/CREATE_VIEW.md)
+## [视图](../sql-reference/sql-statements/View/CREATE_VIEW.md)
 
 视图（也叫逻辑视图）是虚拟表，不实际存储数据，其中所展示的数据来自于基表生成的查询结果。每次在查询中引用某个视图时，都会运行定义该视图的查询。
 
diff --git a/docs/zh/table_design/data_compression.md b/docs/zh/table_design/data_compression.md
index 6f3c2a8000d8ed..ed1c5f1ee49ab8 100644
--- a/docs/zh/table_design/data_compression.md
+++ b/docs/zh/table_design/data_compression.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 数据压缩
@@ -18,7 +18,7 @@ StarRocks 支持四种数据压缩算法：LZ4、Zstandard（或 zstd）、zlib
 
 您只能在创建表时为其设置数据压缩算法，且后续无法修改。
 
-以下示例基于 Zstandard 算法创建表 `data_compression`。 详细说明请参阅 [CREATE TABLE](../sql-reference/sql-statements/data-definition/CREATE_TABLE.md)。
+以下示例基于 Zstandard 算法创建表 `data_compression`。 详细说明请参阅 [CREATE TABLE](../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md)。
 
 ```SQL
 CREATE TABLE `data_compression` (
@@ -38,4 +38,4 @@ PROPERTIES (
 >
 > 如不指定数据压缩算法，StarRocks 默认使用 LZ4。
 
-您可以通过 [SHOW CREATE TABLE](../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE.md) 命令查看指定表采用的压缩算法。
+您可以通过 [SHOW CREATE TABLE](../sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md) 命令查看指定表采用的压缩算法。
diff --git a/docs/zh/table_design/dynamic_partitioning.md b/docs/zh/table_design/dynamic_partitioning.md
index 2e25d9afa1a3de..bd591650ca4b40 100644
--- a/docs/zh/table_design/dynamic_partitioning.md
+++ b/docs/zh/table_design/dynamic_partitioning.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['fenqu']
 ---
 
diff --git a/docs/zh/table_design/expression_partitioning.md b/docs/zh/table_design/expression_partitioning.md
index 63615dd68480b5..52e64fcdf57911 100644
--- a/docs/zh/table_design/expression_partitioning.md
+++ b/docs/zh/table_design/expression_partitioning.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['fenqu']
 ---
 
diff --git a/docs/zh/table_design/feature-support-data-distribution.md b/docs/zh/table_design/feature-support-data-distribution.md
index b4d60de9814279..c85ed4ef2e3f1f 100644
--- a/docs/zh/table_design/feature-support-data-distribution.md
+++ b/docs/zh/table_design/feature-support-data-distribution.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: "能力边界"
 ---
 
diff --git a/docs/zh/table_design/hybrid_table.md b/docs/zh/table_design/hybrid_table.md
index 536532b00ae8f8..fa955136231823 100644
--- a/docs/zh/table_design/hybrid_table.md
+++ b/docs/zh/table_design/hybrid_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 【公测中】行列混存表
@@ -112,7 +112,7 @@ MySQL [example_db]> SELECT * FROM users ORDER BY id;
    SHOW VARIABLES LIKE '%enable_short_circuit%';
    ```
 
-   如果短路径查询未开启，可以执行命令 `SET enable_short_circuit = true;`，设置变量 [`enable_short_circuit`](../reference/System_variable.md#enable_short_circuit) 为 `true`。
+   如果短路径查询未开启，可以执行命令 `SET enable_short_circuit = true;`，设置变量 [`enable_short_circuit`](../sql-reference/System_variable.md#enable_short_circuit) 为 `true`。
 
 2. 查询数据。如果查询满足本条件：WHERE 子句的条件列必须包含所有主键列，并且运算符为  `=` 或者 `IN`，该查询才会走短路径。
 
@@ -175,7 +175,7 @@ EXECUTE select_by_id_stmt USING @id2;
 ## 注意事项
 
 - StarRocks 存算分离集群暂不支持行列混存表。
-- 自 3.2.4 版本起，行列混存表支持 [ALTER TABLE](../sql-reference/sql-statements/data-definition/ALTER_TABLE.md)。
+- 自 3.2.4 版本起，行列混存表支持 [ALTER TABLE](../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md)。
 - 短路径查询目前仅适合定期批量导入后纯查询的场景。因为目前短路径查询和写流程中的 apply 步骤互斥访问索引，所以写操作可能会堵塞短路径查询，导致写入时会影响点查的响应时间。
 - 行列混存表可能会大幅增加存储空间的占用。因为数据会按行和列格式存储两份，并且按行存储压缩比可能不如按列存储高。
 - 行列混存表会增加数据导入耗时和资源占用。
diff --git a/docs/zh/table_design/indexes/Bitmap_index.md b/docs/zh/table_design/indexes/Bitmap_index.md
index 2879890915bf56..faf9a4bd13575a 100644
--- a/docs/zh/table_design/indexes/Bitmap_index.md
+++ b/docs/zh/table_design/indexes/Bitmap_index.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['suoyin']
 ---
 
@@ -88,17 +88,17 @@ Bitmap 索引适用于优化等值 `=` 查询、`[NOT] IN` 范围查询、`>`，
     DISTRIBUTED BY HASH(`lo_orderkey`) BUCKETS 1;
     ```
 
-   本示例中，创建了基于 `lo_orderdate` 列创建了名称为 `lo_orderdate_index` 的 Bitmap 索引。Bitmap 索引的命名要求参见[系统限制](../../reference/System_limit.md)。在同一张表中不能创建名称相同的 Bitmap 索引。
+   本示例中，创建了基于 `lo_orderdate` 列创建了名称为 `lo_orderdate_index` 的 Bitmap 索引。Bitmap 索引的命名要求参见[系统限制](../../sql-reference/System_limit.md)。在同一张表中不能创建名称相同的 Bitmap 索引。
 
    并且，支持为多个列创建 Bitmap 索引，并且多个 Bitmap 索引定义之间用英文逗号（,）隔开。
 
   :::note
 
-  建表的其他参数说明，参见 [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md)。
+  建表的其他参数说明，参见 [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md)。
 
   :::
 
-- 建表后使用 CREATE INDEX 创建 Bitmap 索引。详细参数说明和示例，参见 [CREATE INDEX](../../sql-reference/sql-statements/data-definition/CREATE_INDEX.md)。
+- 建表后使用 CREATE INDEX 创建 Bitmap 索引。详细参数说明和示例，参见 [CREATE INDEX](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_INDEX.md)。
 
     ```SQL
     CREATE INDEX lo_quantity_index (lo_quantity) USING BITMAP;
@@ -106,7 +106,7 @@ Bitmap 索引适用于优化等值 `=` 查询、`[NOT] IN` 范围查询、`>`，
 
 ### 创建进度
 
-创建 Bitmap 索引为**异步**过程，执行索引创建语句后可通过 [SHOW ALTER TABLE](../../sql-reference/sql-statements/data-manipulation/SHOW_ALTER.md) 命令查看索引创建进度，当返回值中 `State` 字段显示为 `FINISHED` 时，即为创建成功。
+创建 Bitmap 索引为**异步**过程，执行索引创建语句后可通过 [SHOW ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_ALTER.md) 命令查看索引创建进度，当返回值中 `State` 字段显示为 `FINISHED` 时，即为创建成功。
 
 ```SQL
 SHOW ALTER TABLE COLUMN [FROM db_name];
@@ -120,7 +120,7 @@ SHOW ALTER TABLE COLUMN [FROM db_name];
 
 ### 查看索引
 
-查看指定表的所有 Bitmap 索引。详细参数和返回结果说明，参见 [SHOW INDEX](../../sql-reference/sql-statements/data-manipulation//SHOW_INDEX.md)。
+查看指定表的所有 Bitmap 索引。详细参数和返回结果说明，参见 [SHOW INDEX](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_INDEX.md)。
 
 ```SQL
 SHOW { INDEX[ES] | KEY[S] } FROM [db_name.]table_name [FROM db_name];
@@ -134,7 +134,7 @@ SHOW { INDEX[ES] | KEY[S] } FROM [db_name.]table_name [FROM db_name];
 
 ### 删除索引
 
-删除指定表的 Bitmap 索引。详细参数说明和示例，参见 [DROP INDEX](../../sql-reference/sql-statements/data-definition/DROP_INDEX.md)。
+删除指定表的 Bitmap 索引。详细参数说明和示例，参见 [DROP INDEX](../../sql-reference/sql-statements/table_bucket_part_index/DROP_INDEX.md)。
 
 ```SQL
 DROP INDEX index_name ON [db_name.]table_name;
diff --git a/docs/zh/table_design/indexes/Bloomfilter_index.md b/docs/zh/table_design/indexes/Bloomfilter_index.md
index 469ad1881dfc07..e31729e31ca365 100644
--- a/docs/zh/table_design/indexes/Bloomfilter_index.md
+++ b/docs/zh/table_design/indexes/Bloomfilter_index.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['suoyin']
 ---
 
@@ -44,11 +44,11 @@ DISTRIBUTED BY HASH (k1, k2)
 PROPERTIES("bloom_filter_columns" = "k1,k2");
 ```
 
-您可以同时创建多个索引，多个索引列之间需用逗号 (`,`) 隔开。关于建表的其他参数说明，请参见 [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md)。
+您可以同时创建多个索引，多个索引列之间需用逗号 (`,`) 隔开。关于建表的其他参数说明，请参见 [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md)。
 
 ## 查看索引
 
-例如，查看表 `table1` 的索引。有关返回值说明，请参见 [SHOW CREATE TABLE](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE.md)。
+例如，查看表 `table1` 的索引。有关返回值说明，请参见 [SHOW CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md)。
 
 ```SQL
 SHOW CREATE TABLE table1;
@@ -56,7 +56,7 @@ SHOW CREATE TABLE table1;
 
 ## 修改索引
 
-您可以使用 [ALTER TABLE](../../sql-reference/sql-statements/data-definition/ALTER_TABLE.md) 语句来增加，减少和删除索引。
+您可以使用 [ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) 语句来增加，减少和删除索引。
 
 - 如下语句增加了一个 Bloom filter 索引列 `v1`。
 
@@ -76,4 +76,4 @@ SHOW CREATE TABLE table1;
     ALTER TABLE table1 SET ("bloom_filter_columns" = "");
     ```
 
-> 说明：修改索引为异步操作，可通过 [SHOW ALTER TABLE](../../sql-reference/sql-statements/data-manipulation/SHOW_ALTER.md) 命令查看索引修改进度。当前每张表只允许同时进行一个修改索引任务。
+> 说明：修改索引为异步操作，可通过 [SHOW ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_ALTER.md) 命令查看索引修改进度。当前每张表只允许同时进行一个修改索引任务。
diff --git a/docs/zh/table_design/indexes/Ngram_Bloom_Filter_Index.md b/docs/zh/table_design/indexes/Ngram_Bloom_Filter_Index.md
index c845a65978eaaf..25f74c96e10b23 100644
--- a/docs/zh/table_design/indexes/Ngram_Bloom_Filter_Index.md
+++ b/docs/zh/table_design/indexes/Ngram_Bloom_Filter_Index.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # [Preview] N-Gram bloom filter 索引
@@ -50,11 +50,11 @@ N-Gram bloom filter 索引相关参数：
 | `case_sensitive`   | 否       | 此索引是否区分大小写。默认值为 `true`。            |
 | `COMMENT`          | 否       | 索引的注释。                                                 |
 
-其他建表相关的参数解释，参见 [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md)。
+其他建表相关的参数解释，参见 [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md)。
 
 ### 查看 N-Gram bloom filter 索引
 
-您可以使用 [SHOW CREATE TABLE](../../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_TABLE.md) 或 [SHOW INDEX](../../sql-reference/sql-statements/data-manipulation/SHOW_INDEX.md) 来查看表的所有索引。由于索引创建是异步的，因此只有在成功创建索引后才能看到相应的索引。
+您可以使用 [SHOW CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_CREATE_TABLE.md) 或 [SHOW INDEX](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_INDEX.md) 来查看表的所有索引。由于索引创建是异步的，因此只有在成功创建索引后才能看到相应的索引。
 
 ```SQL
 SHOW CREATE TABLE table1;
@@ -63,7 +63,7 @@ SHOW INDEX FROM table1;
 
 ### 修改 N-Gram bloom filter 索引
 
-您可以使用 [ALTER TABLE](../../sql-reference/sql-statements/data-definition/ALTER_TABLE.md) 语句添加和删除 N-Gram bloom filter 索引。
+您可以使用 [ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/ALTER_TABLE.md) 语句添加和删除 N-Gram bloom filter 索引。
 
 - 执行如下语句，在表 `table1` 中为列 `k1` 添加一个新的 N-Gram bloom filter 索引，索引名称为 `new_index_name`。
 
@@ -81,7 +81,7 @@ SHOW INDEX FROM table1;
 
 :::note
 
-修改索引是一个异步操作。您可以执行 [SHOW ALTER TABLE](../../sql-reference/sql-statements/data-manipulation/SHOW_ALTER.md) 来查看此操作的进度。一次只能对表运行一个修改索引任务。
+修改索引是一个异步操作。您可以执行 [SHOW ALTER TABLE](../../sql-reference/sql-statements/table_bucket_part_index/SHOW_ALTER.md) 来查看此操作的进度。一次只能对表运行一个修改索引任务。
 
 :::
 
diff --git a/docs/zh/table_design/indexes/Prefix_index_sort_key.md b/docs/zh/table_design/indexes/Prefix_index_sort_key.md
index 52ee450457b7e4..0cb5b128db0587 100644
--- a/docs/zh/table_design/indexes/Prefix_index_sort_key.md
+++ b/docs/zh/table_design/indexes/Prefix_index_sort_key.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['suoyin']
 ---
 
diff --git a/docs/zh/table_design/indexes/indexes_overview.md b/docs/zh/table_design/indexes/indexes_overview.md
index 5a2b0b45ea4088..b1fe5efaaf4e16 100644
--- a/docs/zh/table_design/indexes/indexes_overview.md
+++ b/docs/zh/table_design/indexes/indexes_overview.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['suoyin']
 ---
 
diff --git a/docs/zh/table_design/indexes/inverted_index.md b/docs/zh/table_design/indexes/inverted_index.md
index 06ca9701e3dbfe..f0c998253f6ddb 100644
--- a/docs/zh/table_design/indexes/inverted_index.md
+++ b/docs/zh/table_design/indexes/inverted_index.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['suoyin']
 toc_max_heading_level: 4
 ---
diff --git a/docs/zh/table_design/list_partitioning.md b/docs/zh/table_design/list_partitioning.md
index 05097284d885b0..62710ab6db64f0 100644
--- a/docs/zh/table_design/list_partitioning.md
+++ b/docs/zh/table_design/list_partitioning.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # List 分区
diff --git a/docs/zh/table_design/table_types/aggregate_table.md b/docs/zh/table_design/table_types/aggregate_table.md
index 56cbf110c1defb..59791a20bb7f6a 100644
--- a/docs/zh/table_design/table_types/aggregate_table.md
+++ b/docs/zh/table_design/table_types/aggregate_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 聚合表
@@ -87,7 +87,7 @@ DISTRIBUTED BY HASH(site_id);
 
 - **value 列**：通过在列名后指定聚合函数，定义该列为 value 列。一般为需要汇总统计的数据。
 
-- **聚合函数**：value 列使用的聚合函数。聚合表支持的聚合函数，请参见 [CREATE TABLE](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md)。
+- **聚合函数**：value 列使用的聚合函数。聚合表支持的聚合函数，请参见 [CREATE TABLE](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md)。
 
 - **排序键**：
   - 自 v3.3.0 起，聚合表解耦了排序键和聚合键。聚合表支持使用 `ORDER BY` 指定排序键和使用 `AGGREGATE KEY` 指定聚合键。排序键和聚合键中的列需要保持一致，但是列的顺序不需要保持一致。
diff --git a/docs/zh/table_design/table_types/duplicate_key_table.md b/docs/zh/table_design/table_types/duplicate_key_table.md
index 0a260c145e1b14..2eac881c28bcd0 100644
--- a/docs/zh/table_design/table_types/duplicate_key_table.md
+++ b/docs/zh/table_design/table_types/duplicate_key_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 明细表
diff --git a/docs/zh/table_design/table_types/primary_key_table.md b/docs/zh/table_design/table_types/primary_key_table.md
index 2955257d765526..e32f496fe9ae95 100644
--- a/docs/zh/table_design/table_types/primary_key_table.md
+++ b/docs/zh/table_design/table_types/primary_key_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['zhujian']
 ---
 
@@ -200,7 +200,7 @@ PROPERTIES (
 ## 更多信息
 
 - 建表后导入数据，您可以参考[导入概览](../../loading/loading_introduction/Loading_intro.md)选择合适的导入方式。
-- 如果需要对主键表中数据进行变更，则可以参考 [通过导入实现数据变更](../../loading/Load_to_Primary_Key_tables.md) 或者 DML 语句（[INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md)、[UPDATE](../../sql-reference/sql-statements/data-manipulation/UPDATE.md)、[DELETE](../../sql-reference/sql-statements/data-manipulation/DELETE.md)）。
+- 如果需要对主键表中数据进行变更，则可以参考 [通过导入实现数据变更](../../loading/Load_to_Primary_Key_tables.md) 或者 DML 语句（[INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md)、[UPDATE](../../sql-reference/sql-statements/table_bucket_part_index/UPDATE.md)、[DELETE](../../sql-reference/sql-statements/table_bucket_part_index/DELETE.md)）。
 - 如果您需要进一步加速查询，则可以参考[查询加速](../../cover_pages/query_acceleration.mdx)。
-- 如果需要修改表结构，则可以参考 [ALTER TABLE](../../sql-reference/sql-statements/data-definition/ALTER_RESOURCE.md)。
+- 如果需要修改表结构，则可以参考 [ALTER TABLE](../../sql-reference/sql-statements/Resource/ALTER_RESOURCE.md)。
 - [自增列](../../sql-reference/sql-statements/generated_columns.md)可作为生成主键。
diff --git a/docs/zh/table_design/table_types/table_capabilities.md b/docs/zh/table_design/table_types/table_capabilities.md
index 32e9679582dc95..ef0fb1d75dacb1 100644
--- a/docs/zh/table_design/table_types/table_capabilities.md
+++ b/docs/zh/table_design/table_types/table_capabilities.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 各类表的能力对比
@@ -38,7 +38,7 @@ displayed_sidebar: "Chinese"
 <thead>
 <tr><th> </th><th width= "200"><strong>主键表 (Primary Key table)</strong></th><th><strong>明细表 (Duplicate Key table)</strong></th><th width= "200"><strong>聚合表 (Aggregate table)</strong></th><th><strong>更新表 (Unique Key table)</strong></th></tr>
 </thead>
-<tbody><tr><td><strong>导入数据时实现</strong> <strong>INSERT</strong></td><td rowspan="2">支持。[在导入任务中配置 <code>__op=0</code> 实现 INSERT](../../loading/Load_to_Primary_Key_tables.md)。内部实现时，StarRocks 将 INSERT 和 UPDATE 操作均视为 UPSERT 操作。</td><td>支持</td><td>支持（同聚合键值的数据行会聚合）</td><td>支持（同唯一键值的数据行会更新）</td></tr><tr><td><strong>导入数据时实现 UPDATE</strong></td><td>不支持</td><td>支持（使用 Replace 聚合函数实现）</td><td>支持（更新表本身就可以视为使用 Replace 聚合函数的聚合表）</td></tr><tr><td><strong>导入数据时实现 DELETE</strong></td><td>支持。[在导入任务中配置 <code>__op=1</code> 实现 DELETE](../../loading/Load_to_Primary_Key_tables.md)。</td><td>不支持</td><td>不支持</td><td>不支持</td></tr><tr><td><strong>导入数据列值的完整性</strong></td><td>默认必须导入全部列值。如果开启部分列更新<code>partial_update</code>，或者列具有默认值，则无需导入全部列值。</td><td>默认必须导入全部列值。如果列具有默认值，则无需导入全部列值。</td><td>默认必须导入全部列值。不过，聚合表可以通过指定 Value 列的聚合函数为 REPLACE_IF_NOT_NULL 实现部分列更新，具体使用方式，请参见 [aggr_type](../../sql-reference/sql-statements/data-definition/CREATE_TABLE.md#column_definition)。并且如果列具有默认值，也无需导入全部列值。</td><td>默认必须导入全部列值。如果列具有默认值，则无需导入全部列值。</td></tr><tr><td><strong>[DML INSERT](../../sql-reference/sql-statements/data-manipulation/INSERT.md)</strong></td><td colspan="4">支持</td></tr><tr><td><strong>[DML UPDATE](../../sql-reference/sql-statements/data-manipulation/UPDATE.md)</strong></td><td><ul><li>Key 列作为过滤条件：支持</li><li>Value 列作为过滤条件：支持</li></ul></td><td colspan="3">不支持</td></tr><tr><td><strong>[DML DELETE](../../sql-reference/sql-statements/data-manipulation/DELETE.md)</strong></td><td><ul><li>Key 列作为过滤条件：支持</li><li>Value 列作为过滤条件：支持</li></ul></td><td><ul><li>Key 列作为过滤条件：支持</li><li>Value 列作为过滤条件：支持。</li></ul>注意，仅支持基于 Key 或 Value  列本身的简单过滤条件，如 =、&lt;、&gt;，不支持复杂条件，如函数、子查询。</td><td  colspan="2"><ul><li>Key 列作为过滤条件：支持。注意，仅支持基于 Key 列本身的简单过滤条件，如 =、&lt;、&gt;，不支持复杂条件，如函数、子查询。</li><li>Value 列作为过滤条件：不支持</li></ul></td></tr></tbody>
+<tbody><tr><td><strong>导入数据时实现</strong> <strong>INSERT</strong></td><td rowspan="2">支持。[在导入任务中配置 <code>__op=0</code> 实现 INSERT](../../loading/Load_to_Primary_Key_tables.md)。内部实现时，StarRocks 将 INSERT 和 UPDATE 操作均视为 UPSERT 操作。</td><td>支持</td><td>支持（同聚合键值的数据行会聚合）</td><td>支持（同唯一键值的数据行会更新）</td></tr><tr><td><strong>导入数据时实现 UPDATE</strong></td><td>不支持</td><td>支持（使用 Replace 聚合函数实现）</td><td>支持（更新表本身就可以视为使用 Replace 聚合函数的聚合表）</td></tr><tr><td><strong>导入数据时实现 DELETE</strong></td><td>支持。[在导入任务中配置 <code>__op=1</code> 实现 DELETE](../../loading/Load_to_Primary_Key_tables.md)。</td><td>不支持</td><td>不支持</td><td>不支持</td></tr><tr><td><strong>导入数据列值的完整性</strong></td><td>默认必须导入全部列值。如果开启部分列更新<code>partial_update</code>，或者列具有默认值，则无需导入全部列值。</td><td>默认必须导入全部列值。如果列具有默认值，则无需导入全部列值。</td><td>默认必须导入全部列值。不过，聚合表可以通过指定 Value 列的聚合函数为 REPLACE_IF_NOT_NULL 实现部分列更新，具体使用方式，请参见 [aggr_type](../../sql-reference/sql-statements/table_bucket_part_index/CREATE_TABLE.md#column_definition)。并且如果列具有默认值，也无需导入全部列值。</td><td>默认必须导入全部列值。如果列具有默认值，则无需导入全部列值。</td></tr><tr><td><strong>[DML INSERT](../../sql-reference/sql-statements/loading_unloading/INSERT.md)</strong></td><td colspan="4">支持</td></tr><tr><td><strong>[DML UPDATE](../../sql-reference/sql-statements/table_bucket_part_index/UPDATE.md)</strong></td><td><ul><li>Key 列作为过滤条件：支持</li><li>Value 列作为过滤条件：支持</li></ul></td><td colspan="3">不支持</td></tr><tr><td><strong>[DML DELETE](../../sql-reference/sql-statements/table_bucket_part_index/DELETE.md)</strong></td><td><ul><li>Key 列作为过滤条件：支持</li><li>Value 列作为过滤条件：支持</li></ul></td><td><ul><li>Key 列作为过滤条件：支持</li><li>Value 列作为过滤条件：支持。</li></ul>注意，仅支持基于 Key 或 Value  列本身的简单过滤条件，如 =、&lt;、&gt;，不支持复杂条件，如函数、子查询。</td><td  colspan="2"><ul><li>Key 列作为过滤条件：支持。注意，仅支持基于 Key 列本身的简单过滤条件，如 =、&lt;、&gt;，不支持复杂条件，如函数、子查询。</li><li>Value 列作为过滤条件：不支持</li></ul></td></tr></tbody>
 </table>
 
 ## 和其他功能的兼容性
diff --git a/docs/zh/table_design/table_types/table_types.md b/docs/zh/table_design/table_types/table_types.md
index 04a096282e54af..85eedd8ed733fc 100644
--- a/docs/zh/table_design/table_types/table_types.md
+++ b/docs/zh/table_design/table_types/table_types.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 表类型概览
diff --git a/docs/zh/table_design/table_types/unique_key_table.md b/docs/zh/table_design/table_types/unique_key_table.md
index 627c9a52de9f96..b0fe34c7a4f2e5 100644
--- a/docs/zh/table_design/table_types/unique_key_table.md
+++ b/docs/zh/table_design/table_types/unique_key_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 更新表
diff --git a/docs/zh/unloading/Export.md b/docs/zh/unloading/Export.md
index 66502661b23cfc..394e5e158fdd93 100644
--- a/docs/zh/unloading/Export.md
+++ b/docs/zh/unloading/Export.md
@@ -1,10 +1,10 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 EXPORT 导出数据
 
-本文介绍如何通过 [EXPORT](../sql-reference/sql-statements/data-manipulation/EXPORT.md) 语句把 StarRocks 集群中指定表或分区上的数据以 CSV 的格式导出到外部存储系统。当前支持导出到分布式文件系统 HDFS 或 AWS S3、阿里云 OSS、腾讯云 COS、华为云 OBS 等云存储系统。
+本文介绍如何通过 [EXPORT](../sql-reference/sql-statements/loading_unloading/unloading/EXPORT.md) 语句把 StarRocks 集群中指定表或分区上的数据以 CSV 的格式导出到外部存储系统。当前支持导出到分布式文件系统 HDFS 或 AWS S3、阿里云 OSS、腾讯云 COS、华为云 OBS 等云存储系统。
 
 > **注意**
 >
@@ -35,7 +35,7 @@ displayed_sidebar: "Chinese"
 
 - 在导出作业运行过程中，如果 FE 发生重启或切主，会导致导出作业失败，您需要重新提交导出作业。
 
-- 导出作业运行完成后（成功或失败），若 FE 发生重启或切主，则 [SHOW EXPORT](../sql-reference/sql-statements/data-manipulation/SHOW_EXPORT.md) 语句返回的导出作业信息会发生部分丢失，无法查看。
+- 导出作业运行完成后（成功或失败），若 FE 发生重启或切主，则 [SHOW EXPORT](../sql-reference/sql-statements/loading_unloading/unloading/SHOW_EXPORT.md) 语句返回的导出作业信息会发生部分丢失，无法查看。
 
 - 导出作业只会导出原始表 (Base Table) 的数据，不会导出物化视图的数据。
 
@@ -95,7 +95,7 @@ WITH BROKER
 );
 ```
 
-有关 EXPORT 语句的详细语法和参数说明、以及导出数据到 AWS S3、阿里云 OSS、腾讯云 COS、华为云 OBS 等云存储系统的命令示例，请参见 [EXPORT](../sql-reference/sql-statements/data-manipulation/EXPORT.md)。
+有关 EXPORT 语句的详细语法和参数说明、以及导出数据到 AWS S3、阿里云 OSS、腾讯云 COS、华为云 OBS 等云存储系统的命令示例，请参见 [EXPORT](../sql-reference/sql-statements/loading_unloading/unloading/EXPORT.md)。
 
 ### 获取导出作业的查询 ID
 
@@ -130,7 +130,7 @@ Timeout: 3600
 ErrorMsg: N/A
 ```
 
-有关 SHOW EXPORT 语句的详细语法和参数说明，请参见 [SHOW EXPORT](../sql-reference/sql-statements/data-manipulation/SHOW_EXPORT.md)。
+有关 SHOW EXPORT 语句的详细语法和参数说明，请参见 [SHOW EXPORT](../sql-reference/sql-statements/loading_unloading/unloading/SHOW_EXPORT.md)。
 
 ### 取消导出作业
 
@@ -144,7 +144,7 @@ CANCEL EXPORT WHERE queryid = "921d8f80-7c9d-11eb-9342-acde48001122";
 >
 > 上述示例中，`queryid` 为导出作业的 ID。
 
-有关 CANCEL EXPORT 语句的详细语法和参数说明，请参见 [CANCEL EXPORT](../sql-reference/sql-statements/data-manipulation/SHOW_EXPORT.md)。
+有关 CANCEL EXPORT 语句的详细语法和参数说明，请参见 [CANCEL EXPORT](../sql-reference/sql-statements/loading_unloading/unloading/SHOW_EXPORT.md)。
 
 ## 最佳实践
 
diff --git a/docs/zh/unloading/Flink_connector.md b/docs/zh/unloading/Flink_connector.md
index a1001ca684a7e0..a60c13f6214687 100644
--- a/docs/zh/unloading/Flink_connector.md
+++ b/docs/zh/unloading/Flink_connector.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 Flink Connector 读取数据
diff --git a/docs/zh/unloading/Spark_connector.md b/docs/zh/unloading/Spark_connector.md
index 1108f63fbe5f2e..07a1a958886718 100644
--- a/docs/zh/unloading/Spark_connector.md
+++ b/docs/zh/unloading/Spark_connector.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 Spark Connector 读取数据
diff --git a/docs/zh/unloading/feature-support-loading-and-unloading.mdx b/docs/zh/unloading/feature-support-loading-and-unloading.mdx
index 8a2ee25cbcd2ed..87c13b345f4d4b 100644
--- a/docs/zh/unloading/feature-support-loading-and-unloading.mdx
+++ b/docs/zh/unloading/feature-support-loading-and-unloading.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: "能力边界"
 title: "功能边界：数据导入导出"
 ---
diff --git a/docs/zh/unloading/unload_using_insert_into_files.md b/docs/zh/unloading/unload_using_insert_into_files.md
index 3074c8bbf80a2e..f2023357db19cf 100644
--- a/docs/zh/unloading/unload_using_insert_into_files.md
+++ b/docs/zh/unloading/unload_using_insert_into_files.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 INSERT INTO FILES 导出数据
@@ -201,5 +201,5 @@ SELECT * FROM sales_records;
 
 ## 另请参阅
 
-- 有关使用 INSERT 的更多说明，请参阅 [SQL 参考 - INSERT](../sql-reference/sql-statements/data-manipulation/INSERT.md)。
+- 有关使用 INSERT 的更多说明，请参阅 [SQL 参考 - INSERT](../sql-reference/sql-statements/loading_unloading/INSERT.md)。
 - 有关使用 FILES() 的更多说明，请参阅 [SQL 参考 - FILES()](../sql-reference/sql-functions/table-functions/files.md)。
diff --git a/docs/zh/unloading/unloading.mdx b/docs/zh/unloading/unloading.mdx
index 47e26fb3a715a3..82687233f434e2 100644
--- a/docs/zh/unloading/unloading.mdx
+++ b/docs/zh/unloading/unloading.mdx
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 导出数据
diff --git a/docs/zh/using_starrocks/Colocate_join.md b/docs/zh/using_starrocks/Colocate_join.md
index 04b2bb4a22b786..3a50f7d7089f5f 100644
--- a/docs/zh/using_starrocks/Colocate_join.md
+++ b/docs/zh/using_starrocks/Colocate_join.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Colocate Join
diff --git a/docs/zh/using_starrocks/Connector.md b/docs/zh/using_starrocks/Connector.md
index 6d8cc4f4341dd4..cd88c59d0840f0 100644
--- a/docs/zh/using_starrocks/Connector.md
+++ b/docs/zh/using_starrocks/Connector.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Connector
diff --git a/docs/zh/using_starrocks/Cost_based_optimizer.md b/docs/zh/using_starrocks/Cost_based_optimizer.md
index acd7ad382cb040..49a66d29a9cdb9 100644
--- a/docs/zh/using_starrocks/Cost_based_optimizer.md
+++ b/docs/zh/using_starrocks/Cost_based_optimizer.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # CBO 统计信息
@@ -135,7 +135,7 @@ StarRocks 提供灵活的信息采集方式，您可以根据业务场景选择
 
 :::
 
-自动全量采集任务由系统自动执行，默认配置如下。您可以通过 [ADMIN SET CONFIG](../sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md) 命令修改。
+自动全量采集任务由系统自动执行，默认配置如下。您可以通过 [ADMIN SET CONFIG](../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md) 命令修改。
 
 配置项:
 
@@ -686,6 +686,6 @@ DROP STATS tbl_name
 
 ## 更多信息
 
-- 如需查询 FE 配置项的取值，执行 [ADMIN SHOW CONFIG](../sql-reference/sql-statements/Administration/ADMIN_SHOW_CONFIG.md)。
+- 如需查询 FE 配置项的取值，执行 [ADMIN SHOW CONFIG](../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SHOW_CONFIG.md)。
 
-- 如需修改 FE 配置项的取值，执行 [ADMIN SET CONFIG](../sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md)。
+- 如需修改 FE 配置项的取值，执行 [ADMIN SET CONFIG](../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md)。
diff --git a/docs/zh/using_starrocks/Flat_json.md b/docs/zh/using_starrocks/Flat_json.md
index 318c3dcab8e212..5b2bcda4998b55 100644
--- a/docs/zh/using_starrocks/Flat_json.md
+++ b/docs/zh/using_starrocks/Flat_json.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # [Preview] Flat JSON
diff --git a/docs/zh/using_starrocks/Lateral_join.md b/docs/zh/using_starrocks/Lateral_join.md
index 2036feee1bfd47..3fe7ebf16e35d7 100644
--- a/docs/zh/using_starrocks/Lateral_join.md
+++ b/docs/zh/using_starrocks/Lateral_join.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['爆裂函数','一行转多行','炸开','explode']
 ---
 
diff --git a/docs/zh/using_starrocks/Materialized_view-single_table.md b/docs/zh/using_starrocks/Materialized_view-single_table.md
index 59c93a61832a18..386959007e61b2 100644
--- a/docs/zh/using_starrocks/Materialized_view-single_table.md
+++ b/docs/zh/using_starrocks/Materialized_view-single_table.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 同步物化视图
@@ -141,7 +141,7 @@ GROUP BY store_id;
 
 ## 创建同步物化视图
 
-您可以通过 [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md) 语句为特定查询语句创建物化视图。
+您可以通过 [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md) 语句为特定查询语句创建物化视图。
 
 以下示例根据上述查询语句，为表 `sales_records` 创建一个”以售卖门店为分组，对每一个售卖门店里的所有交易额求和”的同步物化视图。
 
@@ -164,7 +164,7 @@ GROUP BY store_id;
 
 ## 查看同步物化视图构建状态
 
-创建同步物化视图是一个异步的操作。CREATE MATERIALIZED VIEW 命令执行成功即代表创建同步物化视图的任务提交成功。您可以通过 [SHOW ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/data-manipulation/SHOW_ALTER_MATERIALIZED_VIEW.md) 命令查看当前数据库中同步物化视图的构建状态。
+创建同步物化视图是一个异步的操作。CREATE MATERIALIZED VIEW 命令执行成功即代表创建同步物化视图的任务提交成功。您可以通过 [SHOW ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/SHOW_ALTER_MATERIALIZED_VIEW.md) 命令查看当前数据库中同步物化视图的构建状态。
 
 ```Plain
 MySQL > SHOW ALTER MATERIALIZED VIEW\G
@@ -318,7 +318,7 @@ CANCEL ALTER TABLE ROLLUP FROM sales_records (12090);
 
 ### 删除已创建的同步物化视图
 
-可以通过 [DROP MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW.md) 命令删除已创建的同步物化视图。
+可以通过 [DROP MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/DROP_MATERIALIZED_VIEW.md) 命令删除已创建的同步物化视图。
 
 ```SQL
 DROP MATERIALIZED VIEW store_amt;
diff --git a/docs/zh/using_starrocks/Materialized_view.md b/docs/zh/using_starrocks/Materialized_view.md
index 81c67216839f4b..b13e569a04d509 100644
--- a/docs/zh/using_starrocks/Materialized_view.md
+++ b/docs/zh/using_starrocks/Materialized_view.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 keywords: ['wuhua', 'Wuhuashitu']
 ---
 
@@ -153,7 +153,7 @@ GROUP BY order_id;
 
 ### 基于查询语句创建异步物化视图
 
-您可以通过 [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md) 语句为特定查询语句创建物化视图。
+您可以通过 [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md) 语句为特定查询语句创建物化视图。
 
 以下示例根据上述查询语句，基于表 `goods` 和表 `order_list` 创建一个“以订单 ID 为分组，对订单中所有商品价格求和”的异步物化视图，并设定其刷新方式为 ASYNC，每天自动刷新。
 
@@ -175,7 +175,7 @@ GROUP BY order_id;
 > - 异步物化视图支持分区上卷。例如，基表基于天做分区方式，您可以设置异步物化视图按月做分区。
 > - 异步物化视图暂不支持使用 List 分区策略，亦不支持基于使用 List 分区的基表创建。
 > - 创建物化视图的查询语句不支持非确定性函数，其中包括 rand()、random()、uuid() 和 sleep()。
-> - 异步物化视图支持多种数据类型。有关详细信息，请参阅 [CREATE MATERIALIZED VIEW - 支持数据类型](../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md#支持数据类型)。
+> - 异步物化视图支持多种数据类型。有关详细信息，请参阅 [CREATE MATERIALIZED VIEW - 支持数据类型](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md#支持数据类型)。
 > - 默认情况下，执行 CREATE MATERIALIZED VIEW 语句后，StarRocks 将立即开始刷新任务，这将会占用一定系统资源。如需推迟刷新时间，请添加 REFRESH DEFERRED 参数。
 
 - **异步物化视图刷新机制**
@@ -190,7 +190,7 @@ GROUP BY order_id;
   - 支持设置数据变更不会触发对应物化视图自动刷新的基表。
   - 支持为刷新任务设置资源组。
   
-  详细信息，请参阅 [CREATE MATERIALIZED VIEW - 参数](../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md#参数) 中的 **PROPERTIES** 部分。您还可以使用 [ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md) 修改现有异步物化视图的刷新机制。
+  详细信息，请参阅 [CREATE MATERIALIZED VIEW - 参数](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md#参数) 中的 **PROPERTIES** 部分。您还可以使用 [ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/ALTER_MATERIALIZED_VIEW.md) 修改现有异步物化视图的刷新机制。
 
   > **注意**
   >
@@ -206,7 +206,7 @@ GROUP BY order_id;
 
 ## 手动刷新异步物化视图
 
-您可以通过 [REFRESH MATERIALIZED VIEW](../sql-reference/sql-statements/data-manipulation/REFRESH_MATERIALIZED_VIEW.md) 命令手动刷新指定异步物化视图。StarRocks v2.5 版本中，异步物化视图支持手动刷新部分分区。在 v3.1 版本中，StarRocks 支持同步调用刷新任务。
+您可以通过 [REFRESH MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/REFRESH_MATERIALIZED_VIEW.md) 命令手动刷新指定异步物化视图。StarRocks v2.5 版本中，异步物化视图支持手动刷新部分分区。在 v3.1 版本中，StarRocks 支持同步调用刷新任务。
 
 ```SQL
 -- 异步调用刷新任务。
@@ -215,7 +215,7 @@ REFRESH MATERIALIZED VIEW order_mv;
 REFRESH MATERIALIZED VIEW order_mv WITH SYNC MODE;
 ```
 
-您可以通过 [CANCEL REFRESH MATERIALIZED VIEW](../sql-reference/sql-statements/data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW.md) 取消异步调用的刷新任务。
+您可以通过 [CANCEL REFRESH MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/CANCEL_REFRESH_MATERIALIZED_VIEW.md) 取消异步调用的刷新任务。
 
 ## 直接查询异步物化视图
 
@@ -251,7 +251,7 @@ StarRocks v2.5 版本支持 SPJG 类型的异步物化视图查询的自动透
 
 ### 修改异步物化视图
 
-您可以通过 [ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md) 命令修改异步物化视图属性。
+您可以通过 [ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/ALTER_MATERIALIZED_VIEW.md) 命令修改异步物化视图属性。
 
 - 启用被禁用的异步物化视图（将物化视图的状态设置为 Active）。
 
@@ -273,7 +273,7 @@ StarRocks v2.5 版本支持 SPJG 类型的异步物化视图查询的自动透
 
 ### 查看异步物化视图
 
-您可以使用 [SHOW MATERIALIZED VIEWS](../sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md) 或查询 Information Schema 中的系统元数据视图来查看数据库中的异步物化视图。
+您可以使用 [SHOW MATERIALIZED VIEWS](../sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md) 或查询 Information Schema 中的系统元数据视图来查看数据库中的异步物化视图。
 
 - 查看当前数据仓库内所有异步物化视图。
 
@@ -293,7 +293,7 @@ StarRocks v2.5 版本支持 SPJG 类型的异步物化视图查询的自动透
   SHOW MATERIALIZED VIEWS WHERE NAME LIKE "order%";
   ```
 
-- 通过 Information Schema 中的系统元数据视图 `materialized_views` 查看所有异步物化视图。详细内容，请参考 [information_schema.materialized_views](../reference/information_schema/materialized_views.md)。
+- 通过 Information Schema 中的系统元数据视图 `materialized_views` 查看所有异步物化视图。详细内容，请参考 [information_schema.materialized_views](../sql-reference/information_schema/materialized_views.md)。
 
   ```SQL
   SELECT * FROM information_schema.materialized_views;
@@ -301,7 +301,7 @@ StarRocks v2.5 版本支持 SPJG 类型的异步物化视图查询的自动透
 
 ### 查看异步物化视图创建语句
 
-您可以通过 [SHOW CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/data-manipulation/SHOW_CREATE_MATERIALIZED_VIEW.md) 命令查看异步物化视图创建语句。
+您可以通过 [SHOW CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/SHOW_CREATE_MATERIALIZED_VIEW.md) 命令查看异步物化视图创建语句。
 
 ```SQL
 SHOW CREATE MATERIALIZED VIEW order_mv;
@@ -309,7 +309,7 @@ SHOW CREATE MATERIALIZED VIEW order_mv;
 
 ### 查看异步物化视图的执行状态
 
-您可以通过查询 StarRocks 的 [Information Schema](../reference/overview-pages/information_schema.md) 中的 [`tasks`](../reference/information_schema/tasks.md) 和 [`task_runs`](../reference/information_schema/task_runs.md) 元数据视图来查看异步物化视图的执行（构建或刷新）状态。
+您可以通过查询 StarRocks 的 [Information Schema](../sql-reference/information_schema/information_schema.md) 中的 [`tasks`](../sql-reference/information_schema/tasks.md) 和 [`task_runs`](../sql-reference/information_schema/task_runs.md) 元数据视图来查看异步物化视图的执行（构建或刷新）状态。
 
 以下示例查看最新创建的异步物化视图的执行状态：
 
@@ -352,7 +352,7 @@ SHOW CREATE MATERIALIZED VIEW order_mv;
 
 ### 删除异步物化视图
 
-您可以通过 [DROP MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW.md) 命令删除已创建的异步物化视图。
+您可以通过 [DROP MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/DROP_MATERIALIZED_VIEW.md) 命令删除已创建的异步物化视图。
 
 ```SQL
 DROP MATERIALIZED VIEW order_mv;
diff --git a/docs/zh/using_starrocks/Using_HLL.md b/docs/zh/using_starrocks/Using_HLL.md
index 11a566b56b7454..15308034c06904 100644
--- a/docs/zh/using_starrocks/Using_HLL.md
+++ b/docs/zh/using_starrocks/Using_HLL.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 HyperLogLog 实现近似去重
@@ -53,13 +53,13 @@ DISTRIBUTED BY HASH(ID);
 
 您可以通过 Stream Load 或者 Broker Load 模式导入 **test.csv**。
 
-* [Stream Load](../sql-reference/sql-statements/data-manipulation/STREAM_LOAD.md) 模式:
+* [Stream Load](../sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md) 模式:
 
 ~~~bash
 curl --location-trusted -u <username>:<password> -H "label:987654321" -H "column_separator:," -H "columns:dt,id,uv=hll_hash(id)" -T test.csv http://fe_host:http_port/api/db_name/test/_stream_load
 ~~~
 
-* [Broker Load](../sql-reference/sql-statements/data-manipulation/BROKER_LOAD.md) 模式:
+* [Broker Load](../sql-reference/sql-statements/loading_unloading/BROKER_LOAD.md) 模式:
 
 ~~~sql
 LOAD LABEL test_db.label
diff --git a/docs/zh/using_starrocks/Using_bitmap.md b/docs/zh/using_starrocks/Using_bitmap.md
index 2405617016150c..17452d61626707 100644
--- a/docs/zh/using_starrocks/Using_bitmap.md
+++ b/docs/zh/using_starrocks/Using_bitmap.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 Bitmap 实现精确去重
diff --git a/docs/zh/using_starrocks/block_cache.md b/docs/zh/using_starrocks/block_cache.md
index 42a37e7fe8548e..097dd1f82396fc 100644
--- a/docs/zh/using_starrocks/block_cache.md
+++ b/docs/zh/using_starrocks/block_cache.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 toc_max_heading_level: 2
 ---
 
diff --git a/docs/zh/using_starrocks/create_partitioned_materialized_view.md b/docs/zh/using_starrocks/create_partitioned_materialized_view.md
index 4ad5b927e29906..1084777596ee10 100644
--- a/docs/zh/using_starrocks/create_partitioned_materialized_view.md
+++ b/docs/zh/using_starrocks/create_partitioned_materialized_view.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 创建分区物化视图
@@ -197,17 +197,17 @@ DISTRIBUTED BY HASH(k1);
 
 ### 自定义时间粒度对齐分区
 
-上述的分区上卷方法只允许根据特定的时间粒度对物化视图进行分区，不允许自定义分区时间范围。如果您的业务场景需要使用自定义的时间粒度进行分区，您可以创建一个物化视图，并使用 [time_slice](../sql-reference/sql-functions/date-time-functions/time_slice.md) 或 [date_slice](../sql-reference/sql-functions/date-time-functions/date_slice.md) 函数定义其分区的时间粒度。以上两种函数可以根据指定的时间粒度周期，将给定的时间转化到其所在的时间粒度周期的起始或结束时刻。
+上述的分区上卷方法只允许根据特定的时间粒度对物化视图进行分区，不允许自定义分区时间范围。如果您的业务场景需要使用自定义的时间粒度进行分区，您可以创建一个物化视图，并使用 [time_slice](../sql-reference/sql-functions/date-time-functions/time_slice.md) 函数定义其分区的时间粒度。以上两种函数可以根据指定的时间粒度周期，将给定的时间转化到其所在的时间粒度周期的起始或结束时刻。
 
-您需要在 SELECT List 中使用 time_slice 或 date_slice 函数在基表的分区键上定义新的时间粒度，为其设置别名，然后结合 date_trunc 函数指定物化视图的分区键，从而创建一个自定义分区时间粒度的物化视图。
+您需要在 SELECT List 中使用 time_slice 函数在基表的分区键上定义新的时间粒度，为其设置别名，然后结合 date_trunc 函数指定物化视图的分区键，从而创建一个自定义分区时间粒度的物化视图。
 
 ```SQL
 PARTITION BY
 date_trunc(<format>, <mv_partitioning_column>)
 AS
 SELECT 
-  -- 您可以使用 time_slice 或 date_slice 函数。
-  date_slice(<base_table_partitioning_column>, <interval>) AS <mv_partitioning_column>
+  -- 您可以使用 time_slice 函数。
+  time_slice(<base_table_partitioning_column>, <interval>) AS <mv_partitioning_column>
 ```
 
 示例：
@@ -220,7 +220,7 @@ AS
 SELECT 
   k1, 
   sum(v1) AS SUM, 
-  date_slice(datekey, INTERVAL 5 HOUR) AS mv_datekey 
+  time_slice(datekey, INTERVAL 5 HOUR) AS mv_datekey 
 FROM par_tbl1 
 GROUP BY datekey, k1;
 ```
diff --git a/docs/zh/using_starrocks/data_lake_query_acceleration_with_materialized_views.md b/docs/zh/using_starrocks/data_lake_query_acceleration_with_materialized_views.md
index f0ca4dbaeb5938..d8035df52e2726 100644
--- a/docs/zh/using_starrocks/data_lake_query_acceleration_with_materialized_views.md
+++ b/docs/zh/using_starrocks/data_lake_query_acceleration_with_materialized_views.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用物化视图加速数据湖查询
@@ -101,7 +101,7 @@ StarRocks 支持基于 External Catalog，如 Hive Catalog、Iceberg Catalog、H
 
   > **说明**
   >
-  > 您仍然可以选择在创建物化视图时通过设置属性 `mv_rewrite_staleness_second` 来容忍一定程度的数据不一致。有关更多信息，请参阅 [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md)。
+  > 您仍然可以选择在创建物化视图时通过设置属性 `mv_rewrite_staleness_second` 来容忍一定程度的数据不一致。有关更多信息，请参阅 [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md)。
 
 请注意，如需按照分区刷新，物化视图的分区键必须包含在基表的分区键中。
 
@@ -135,7 +135,7 @@ FROM `iceberg`.`test`.`iceberg_sample_datetime_day`;
 
 对于 Hive Catalog，您可以启用 Hive 元数据缓存刷新功能，允许 StarRocks 在分区级别检测数据更改。启用此功能后，StarRocks 定期访问 Hive 元数据存储服务（HMS）或 AWS Glue，以检查最近查询的热数据的元数据信息。
 
-要启用 Hive 元数据缓存刷新功能，您可以使用 [ADMIN SET FRONTEND CONFIG](../sql-reference/sql-statements/Administration/ADMIN_SET_CONFIG.md) 设置以下 FE 动态配置项：
+要启用 Hive 元数据缓存刷新功能，您可以使用 [ADMIN SET FRONTEND CONFIG](../sql-reference/sql-statements/cluster-management/config_vars/ADMIN_SET_CONFIG.md) 设置以下 FE 动态配置项：
 
 ### 配置名称                                           
 
diff --git a/docs/zh/using_starrocks/data_modeling_with_materialized_views.md b/docs/zh/using_starrocks/data_modeling_with_materialized_views.md
index 54e881710954db..0c32425b957984 100644
--- a/docs/zh/using_starrocks/data_modeling_with_materialized_views.md
+++ b/docs/zh/using_starrocks/data_modeling_with_materialized_views.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用物化视图进行数据建模
@@ -174,7 +174,7 @@ Schema Change 遵循以下原则：
 - `excluded_trigger_tables`：为避免触发自动刷新而需要忽略的表。
 - `auto_refresh_partitions_limit`：每次自动刷新操作中要刷新的分区数。
 
-详细说明，参见 [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md)。
+详细说明，参见 [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md)。
 
 当前版本中，分区物化视图存在如下限制：
 
diff --git a/docs/zh/using_starrocks/feature-support-asynchronous-materialized-views.md b/docs/zh/using_starrocks/feature-support-asynchronous-materialized-views.md
index eb0d5432ba1e98..111a9619c70947 100644
--- a/docs/zh/using_starrocks/feature-support-asynchronous-materialized-views.md
+++ b/docs/zh/using_starrocks/feature-support-asynchronous-materialized-views.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 sidebar_label: "能力边界"
 ---
 
diff --git a/docs/zh/using_starrocks/mv_ref.md b/docs/zh/using_starrocks/mv_ref.md
new file mode 100644
index 00000000000000..4e5da8e8f40721
--- /dev/null
+++ b/docs/zh/using_starrocks/mv_ref.md
@@ -0,0 +1,11 @@
+---
+displayed_sidebar: docs
+---
+
+# Asynch Materialized view reference
+
+- [CREATE](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md)
+- [ALTER](../sql-reference/sql-statements/materialized_view/ALTER_MATERIALIZED_VIEW.md)
+- [DROP](../sql-reference/sql-statements/materialized_view/DROP_MATERIALIZED_VIEW.md)
+- [SHOW](../sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md)
+- [Information schema](../sql-reference/information_schema/materialized_views.md)
diff --git a/docs/zh/using_starrocks/query_acceleration_with_auto_increment.md b/docs/zh/using_starrocks/query_acceleration_with_auto_increment.md
index d6e05398469de4..93ee7ad5c827a9 100644
--- a/docs/zh/using_starrocks/query_acceleration_with_auto_increment.md
+++ b/docs/zh/using_starrocks/query_acceleration_with_auto_increment.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 使用 AUTO INCREMENT 列构建全局字典以加速精确去重计算和 Join
diff --git a/docs/zh/using_starrocks/query_cache.md b/docs/zh/using_starrocks/query_cache.md
index b1930862f7af7e..55d9d3d79e954d 100644
--- a/docs/zh/using_starrocks/query_cache.md
+++ b/docs/zh/using_starrocks/query_cache.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Query Cache
diff --git a/docs/zh/using_starrocks/query_rewrite_with_materialized_views.md b/docs/zh/using_starrocks/query_rewrite_with_materialized_views.md
index 985a50b833096d..43ef4944e91edd 100644
--- a/docs/zh/using_starrocks/query_rewrite_with_materialized_views.md
+++ b/docs/zh/using_starrocks/query_rewrite_with_materialized_views.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 物化视图查询改写
@@ -1092,7 +1092,7 @@ FE 配置项 `enable_materialized_view_text_based_rewrite` 用于控制是否在
 
 变量 `materialized_view_subuqery_text_match_max_count` 用于控制系统比对子查询是否与物化视图定义匹配的最大次数。默认值为 `4`。增加此值同时也会增加优化器的耗时。
 
-请注意，只有当物化视图满足时效性（数据一致性）要求时，才能用于基于文本的查询改写。您可以在创建物化视图时通过属性 `query_rewrite_consistency`手动设置一致性检查规则。更多信息，请参考 [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md)。
+请注意，只有当物化视图满足时效性（数据一致性）要求时，才能用于基于文本的查询改写。您可以在创建物化视图时通过属性 `query_rewrite_consistency`手动设置一致性检查规则。更多信息，请参考 [CREATE MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/CREATE_MATERIALIZED_VIEW.md)。
 
 ### **使用场景**
 
@@ -1234,7 +1234,7 @@ mysql> EXPLAIN SELECT
 
 StarRocks 默认开启基于 Default Catalog 创建的异步物化视图查询改写。您可以通过将 Session 变量 `enable_materialized_view_rewrite` 设置为 `false` 禁用该功能。
 
-对于基于 External Catalog 创建的异步物化视图，你可以通过 [ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md) 将物化视图 Property `force_external_table_query_rewrite` 设置为 `false` 来禁用此功能。
+对于基于 External Catalog 创建的异步物化视图，你可以通过 [ALTER MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/ALTER_MATERIALIZED_VIEW.md) 将物化视图 Property `force_external_table_query_rewrite` 设置为 `false` 来禁用此功能。
 
 ## 限制
 
diff --git a/docs/zh/using_starrocks/sorted_aggregate.md b/docs/zh/using_starrocks/sorted_aggregate.md
index 770c3182894044..470313d80685a3 100644
--- a/docs/zh/using_starrocks/sorted_aggregate.md
+++ b/docs/zh/using_starrocks/sorted_aggregate.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # Sorted streaming aggregate
diff --git a/docs/zh/using_starrocks/troubleshooting_asynchronous_materialized_views.md b/docs/zh/using_starrocks/troubleshooting_asynchronous_materialized_views.md
index 3bbc2bde806df8..4da5ff0f2537b2 100644
--- a/docs/zh/using_starrocks/troubleshooting_asynchronous_materialized_views.md
+++ b/docs/zh/using_starrocks/troubleshooting_asynchronous_materialized_views.md
@@ -1,5 +1,5 @@
 ---
-displayed_sidebar: "Chinese"
+displayed_sidebar: docs
 ---
 
 # 异步物化视图故障排除
@@ -16,14 +16,14 @@ displayed_sidebar: "Chinese"
 
 ### 检查异步物化视图工作状态
 
-您可以使用 [SHOW MATERIALIZED VIEWS](../sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md) 命令来检查异步物化视图的工作状态。在返回的所有信息中，您可以关注以下字段：
+您可以使用 [SHOW MATERIALIZED VIEWS](../sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md) 命令来检查异步物化视图的工作状态。在返回的所有信息中，您可以关注以下字段：
 
 - `is_active`：物化视图的状态是否为 Active 状态。只有处于 Active 状态的物化视图才能用于查询加速和改写。
 - `last_refresh_state`：最近一次刷新的状态，包括 PENDING（等待中）、RUNNING（运行中）、FAILED（失败）和 SUCCESS（成功）。
 - `last_refresh_error_message`：上次刷新失败的原因（如果物化视图状态不为 Active 状态）。
 - `rows`：物化视图中的数据行数。请注意，这个值可能与物化视图的实际行数不同，因为更新可能有延迟。
 
-有关返回的其他字段的详细信息，请参阅 [SHOW MATERIALIZED VIEWS - 返回](../sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md#返回)。
+有关返回的其他字段的详细信息，请参阅 [SHOW MATERIALIZED VIEWS - 返回](../sql-reference/sql-statements/materialized_view/SHOW_MATERIALIZED_VIEW.md#返回)。
 
 
 示例：
@@ -114,7 +114,7 @@ PROPERTIES    | {"FORCE":"true"}
 
 #### 刷新任务执行期间监控资源消耗
 
-刷新任务执行期间，您可以使用 [SHOW PROC '/current_queries'](../sql-reference/sql-statements/Administration/SHOW_PROC.md) 实时监控其资源消耗情况。
+刷新任务执行期间，您可以使用 [SHOW PROC '/current_queries'](../sql-reference/sql-statements/cluster-management/nodes_processes/SHOW_PROC.md) 实时监控其资源消耗情况。
 
 在返回的所有信息中，您可以关注以下字段：
 
@@ -159,7 +159,7 @@ ExecTime      | 2.583 s
 
 ### 验证查询是否被异步物化视图改写
 
-您可以通过使用 [EXPLAIN](../sql-reference/sql-statements/Administration/EXPLAIN.md) 查看查询计划，以检查查询是否可以被异步物化视图重写。
+您可以通过使用 [EXPLAIN](../sql-reference/sql-statements/cluster-management/plan_profile/EXPLAIN.md) 查看查询计划，以检查查询是否可以被异步物化视图重写。
 
 如果查询计划中的 `SCAN` 指标显示了相应物化视图的名称，那么该查询已经被物化视图重写。
 
@@ -305,7 +305,7 @@ MySQL > EXPLAIN LOGICAL SELECT `customer`.`c_custkey`
   1. 通过查询 `information_schema.task_runs` 获取刷新任务的 `query_id`。
   2. 通过上述的 `query_id`，获取并分析其 Query Profile。
      - [GET_QUERY_PROFILE](../sql-reference/sql-functions/utility-functions/get_query_profile.md): 根据 `query_id` 获取原始 Query Profile。
-     - [ANALYZE PROFILE](../sql-reference/sql-statements/Administration/ANALYZE_PROFILE.md): 以 Fragment 为单位分析 Query Profile，并以树形结构展示。
+     - [ANALYZE PROFILE](../sql-reference/sql-statements/cluster-management/plan_profile/ANALYZE_PROFILE.md): 以 Fragment 为单位分析 Query Profile，并以树形结构展示。
 
 ### 物化视图不可用
 
@@ -341,7 +341,7 @@ ALTER MATERIALIZED VIEW mv1 ACTIVE;
   ALTER MATERIALIZED VIEW mv1 INACTIVE;
   ```
 
-- 通过 [CANCEL REFRESH MATERIALIZED VIEW](../sql-reference/sql-statements/data-manipulation/CANCEL_REFRESH_MATERIALIZED_VIEW.md) 终止正在运行的刷新任务。
+- 通过 [CANCEL REFRESH MATERIALIZED VIEW](../sql-reference/sql-statements/materialized_view/CANCEL_REFRESH_MATERIALIZED_VIEW.md) 终止正在运行的刷新任务。
 
   ```SQL
   CANCEL REFRESH MATERIALIZED VIEW mv1;
diff --git a/docs/zh/using_starrocks/usage/alter.mdx b/docs/zh/using_starrocks/usage/alter.mdx
deleted file mode 100644
index 8e3cb6714fc912..00000000000000
--- a/docs/zh/using_starrocks/usage/alter.mdx
+++ /dev/null
@@ -1,13 +0,0 @@
----
-displayed_sidebar: "Chinese"
-sidebar_position: 1
-sidebar_label: ALTER
-title: ALTER MATERIALIZED VIEW
----
-<head>
-  <link rel="canonical" href="https://docs.starrocks.io/zh/sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW/" />
-</head>
-
-import Content from '../../sql-reference/sql-statements/data-definition/ALTER_MATERIALIZED_VIEW.md';
-
-<Content />
diff --git a/docs/zh/using_starrocks/usage/create.mdx b/docs/zh/using_starrocks/usage/create.mdx
deleted file mode 100644
index c551886ea7baf1..00000000000000
--- a/docs/zh/using_starrocks/usage/create.mdx
+++ /dev/null
@@ -1,13 +0,0 @@
----
-displayed_sidebar: "Chinese"
-sidebar_position: 0
-sidebar_label: CREATE
-title: CREATE MATERIALIZED VIEW
----
-<head>
-  <link rel="canonical" href="https://docs.starrocks.io/zh/sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW/" />
-</head>
-
-import Content from '../../sql-reference/sql-statements/data-definition/CREATE_MATERIALIZED_VIEW.md';
-
-<Content />
diff --git a/docs/zh/using_starrocks/usage/drop.mdx b/docs/zh/using_starrocks/usage/drop.mdx
deleted file mode 100644
index 5106ddfc227b35..00000000000000
--- a/docs/zh/using_starrocks/usage/drop.mdx
+++ /dev/null
@@ -1,13 +0,0 @@
----
-displayed_sidebar: "Chinese"
-sidebar_position: 2
-sidebar_label: DROP
-title: DROP MATERIALIZED VIEW
----
-<head>
-  <link rel="canonical" href="https://docs.starrocks.io/zh/sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW/" />
-</head>
-
-import Content from '../../sql-reference/sql-statements/data-definition/DROP_MATERIALIZED_VIEW.md';
-
-<Content />
diff --git a/docs/zh/using_starrocks/usage/information_schema-materialized_views.mdx b/docs/zh/using_starrocks/usage/information_schema-materialized_views.mdx
deleted file mode 100644
index 067efb32a24cc8..00000000000000
--- a/docs/zh/using_starrocks/usage/information_schema-materialized_views.mdx
+++ /dev/null
@@ -1,13 +0,0 @@
----
-displayed_sidebar: "Chinese"
-sidebar_position: 4
-sidebar_label: materialized_views
-title: materialized_views
----
-<head>
-  <link rel="canonical" href="https://docs.starrocks.io/zh/docs/reference/information_schema/materialized_views/" />
-</head>
-
-import Content from '../../reference/information_schema/materialized_views.md';
-
-<Content />
diff --git a/docs/zh/using_starrocks/usage/intro.mdx b/docs/zh/using_starrocks/usage/intro.mdx
deleted file mode 100644
index 212e673ddab805..00000000000000
--- a/docs/zh/using_starrocks/usage/intro.mdx
+++ /dev/null
@@ -1,9 +0,0 @@
----
-displayed_sidebar: "Chinese"
----
-
-# Usage
-
-import DocCardList from '@theme/DocCardList';
-
-<DocCardList />
diff --git a/docs/zh/using_starrocks/usage/show.mdx b/docs/zh/using_starrocks/usage/show.mdx
deleted file mode 100644
index 379b71f6abbf51..00000000000000
--- a/docs/zh/using_starrocks/usage/show.mdx
+++ /dev/null
@@ -1,13 +0,0 @@
----
-displayed_sidebar: "Chinese"
-sidebar_position: 3
-sidebar_label: SHOW
-title: SHOW MATERIALIZED VIEW
----
-<head>
-  <link rel="canonical" href="https://docs.starrocks.io/zh/sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW/" />
-</head>
-
-import Content from '../../sql-reference/sql-statements/data-manipulation/SHOW_MATERIALIZED_VIEW.md';
-
-<Content />
diff --git "a/docs/zh/\177\177\177\177" "b/docs/zh/\177\177\177\177"
new file mode 100644
index 00000000000000..1f0ebc85979ebe
--- /dev/null
+++ "b/docs/zh/\177\177\177\177"
@@ -0,0 +1,6 @@
+position: 20 # float position is supported
+label: '集群管理'
+collapsible: true
+collapsed: true
+link:
+  type: generated-index
diff --git a/fe/fe-core/pom.xml b/fe/fe-core/pom.xml
index a2fa7062c39fb1..19a77dd5729005 100644
--- a/fe/fe-core/pom.xml
+++ b/fe/fe-core/pom.xml
@@ -41,7 +41,7 @@ under the License.
         <iceberg.version>1.6.0</iceberg.version>
         <paimon.version>0.8.2</paimon.version>
         <delta-kernel.version>4.0.0rc1</delta-kernel.version>
-        <staros.version>3.3-rc3</staros.version>
+        <staros.version>3.3-rc5</staros.version>
         <python>python</python>
     </properties>
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/alter/AlterJobExecutor.java b/fe/fe-core/src/main/java/com/starrocks/alter/AlterJobExecutor.java
index ec50c6b3870805..3409e8c29a037d 100644
--- a/fe/fe-core/src/main/java/com/starrocks/alter/AlterJobExecutor.java
+++ b/fe/fe-core/src/main/java/com/starrocks/alter/AlterJobExecutor.java
@@ -89,7 +89,6 @@
 import com.starrocks.sql.ast.TableRenameClause;
 import com.starrocks.sql.ast.TruncatePartitionClause;
 import com.starrocks.sql.ast.TruncateTableStmt;
-import com.starrocks.sql.common.MetaUtils;
 import com.starrocks.thrift.TStorageMedium;
 import com.starrocks.thrift.TTabletMetaType;
 import com.starrocks.thrift.TTabletType;
@@ -136,8 +135,11 @@ public Void visitAlterTableStatement(AlterTableStmt statement, ConnectContext co
         TableName tableName = statement.getTbl();
         this.tableName = tableName;
 
-        Database db = MetaUtils.getDatabase(context, tableName);
-        Table table = MetaUtils.getTable(tableName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(tableName.getDb());
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(tableName.getDb(), tableName.getTbl());
+        if (table == null) {
+            throw new SemanticException("Table %s is not found", tableName);
+        }
 
         if (!(table.isOlapOrCloudNativeTable() || table.isMaterializedView())) {
             throw new SemanticException("Do not support alter non-native table/materialized-view[" + tableName + "]");
@@ -190,8 +192,11 @@ public Void visitAlterTableStatement(AlterTableStmt statement, ConnectContext co
     @Override
     public Void visitAlterViewStatement(AlterViewStmt statement, ConnectContext context) {
         TableName tableName = statement.getTableName();
-        Database db = MetaUtils.getDatabase(context, tableName);
-        Table table = MetaUtils.getTable(tableName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(tableName.getDb());
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(tableName.getDb(), tableName.getTbl());
+        if (table == null) {
+            throw new SemanticException("Table %s is not found", tableName);
+        }
 
         if (table.getType() != Table.TableType.VIEW) {
             throw new SemanticException("The specified table [" + tableName + "] is not a view");
@@ -208,7 +213,10 @@ public Void visitAlterViewStatement(AlterViewStmt statement, ConnectContext cont
     public Void visitAlterMaterializedViewStatement(AlterMaterializedViewStmt stmt, ConnectContext context) {
         // check db
         final TableName mvName = stmt.getMvName();
-        Database db = MetaUtils.getDatabase(context, mvName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(mvName.getDb());
+        if (db == null) {
+            throw new SemanticException("Database %s is not found", mvName.getCatalogAndDb());
+        }
 
         Locker locker = new Locker();
         if (!locker.lockDatabaseAndCheckExist(db, LockType.WRITE)) {
@@ -216,7 +224,10 @@ public Void visitAlterMaterializedViewStatement(AlterMaterializedViewStmt stmt,
         }
 
         try {
-            Table table = MetaUtils.getTable(mvName);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(mvName.getDb(), mvName.getTbl());
+            if (table == null) {
+                throw new SemanticException("Table %s is not found", mvName);
+            }
             if (!table.isMaterializedView()) {
                 throw new SemanticException("The specified table [" + mvName + "] is not a view");
             }
@@ -288,7 +299,7 @@ public Void visitSwapTableClause(SwapTableClause clause, ConnectContext context)
             OlapTable origTable = (OlapTable) table;
             String origTblName = origTable.getName();
             String newTblName = clause.getTblName();
-            Table newTbl = db.getTable(newTblName);
+            Table newTbl = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), newTblName);
             if (newTbl == null || !(newTbl.isOlapOrCloudNativeTable() || newTbl.isMaterializedView())) {
                 throw new AlterJobException("Table " + newTblName + " does not exist or is not OLAP/LAKE table");
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/alter/AlterJobMgr.java b/fe/fe-core/src/main/java/com/starrocks/alter/AlterJobMgr.java
index 13d2126f989c70..836ebb0f054fdd 100644
--- a/fe/fe-core/src/main/java/com/starrocks/alter/AlterJobMgr.java
+++ b/fe/fe-core/src/main/java/com/starrocks/alter/AlterJobMgr.java
@@ -133,7 +133,7 @@ public void stop() {
     public void processDropMaterializedView(DropMaterializedViewStmt stmt) throws DdlException, MetaNotFoundException {
         // check db
         String dbName = stmt.getDbName();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             ErrorReport.reportDdlException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
         }
@@ -144,7 +144,7 @@ public void processDropMaterializedView(DropMaterializedViewStmt stmt) throws Dd
         try {
             Table table = null;
             boolean hasfindTable = false;
-            for (Table t : db.getTables()) {
+            for (Table t : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                 if (t instanceof OlapTable) {
                     OlapTable olapTable = (OlapTable) t;
                     for (MaterializedIndexMeta mvMeta : olapTable.getVisibleIndexMetas()) {
@@ -231,7 +231,7 @@ public static QueryStatement recreateMVQuery(MaterializedView materializedView,
                                                  String createMvSql) {
         // If we could parse the MV sql successfully, and the schema of mv does not change,
         // we could reuse the existing MV
-        Optional<Database> mayDb = GlobalStateMgr.getCurrentState().mayGetDb(materializedView.getDbId());
+        Optional<Database> mayDb = GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetDb(materializedView.getDbId());
 
         // check database existing
         String dbName = mayDb.orElseThrow(() ->
@@ -271,8 +271,8 @@ public static QueryStatement recreateMVQuery(MaterializedView materializedView,
     public void replayAlterMaterializedViewBaseTableInfos(AlterMaterializedViewBaseTableInfosLog log) {
         long dbId = log.getDbId();
         long mvId = log.getMvId();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
-        MaterializedView mv = (MaterializedView) db.getTable(mvId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
+        MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), mvId);
         if (mv == null) {
             return;
         }
@@ -292,8 +292,9 @@ public void replayAlterMaterializedViewBaseTableInfos(AlterMaterializedViewBaseT
     public void replayAlterMaterializedViewStatus(AlterMaterializedViewStatusLog log) {
         long dbId = log.getDbId();
         long tableId = log.getTableId();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
-        MaterializedView mv = (MaterializedView) db.getTable(tableId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
+        MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getId(), tableId);
         if (mv == null) {
             return;
         }
@@ -314,8 +315,9 @@ public void replayRenameMaterializedView(RenameMaterializedViewLog log) {
         long dbId = log.getDbId();
         long materializedViewId = log.getId();
         String newMaterializedViewName = log.getNewMaterializedViewName();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
-        MaterializedView oldMaterializedView = (MaterializedView) db.getTable(materializedViewId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
+        MaterializedView oldMaterializedView = (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getId(), materializedViewId);
         if (oldMaterializedView != null) {
             try (AutoCloseableLock ignore = new AutoCloseableLock(new Locker(), db,
                     Lists.newArrayList(oldMaterializedView.getId()), LockType.WRITE)) {
@@ -344,12 +346,13 @@ private void updateTaskDefinition(MaterializedView materializedView) {
     public void replayChangeMaterializedViewRefreshScheme(ChangeMaterializedViewRefreshSchemeLog log) {
         long dbId = log.getDbId();
         long id = log.getId();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             return;
         }
 
-        MaterializedView oldMaterializedView = (MaterializedView) db.getTable(id);
+        MaterializedView oldMaterializedView = (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getId(), id);
         if (oldMaterializedView == null) {
             LOG.warn("Ignore change materialized view refresh scheme log because table:" + id + "is null");
             return;
@@ -393,8 +396,9 @@ public void replayAlterMaterializedViewProperties(short opCode, ModifyTablePrope
         long tableId = log.getTableId();
         Map<String, String> properties = log.getProperties();
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
-        MaterializedView mv = (MaterializedView) db.getTable(tableId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
+        MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getId(), tableId);
         if (mv == null) {
             LOG.warn("Ignore change materialized view properties og because table:" + tableId + "is null");
             return;
@@ -428,9 +432,9 @@ public void replaySwapTable(SwapTableOperationLog log) {
         long dbId = log.getDbId();
         long origTblId = log.getOrigTblId();
         long newTblId = log.getNewTblId();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
-        OlapTable origTable = (OlapTable) db.getTable(origTblId);
-        OlapTable newTbl = (OlapTable) db.getTable(newTblId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
+        OlapTable origTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), origTblId);
+        OlapTable newTbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), newTblId);
         LOG.debug("finish replay swap table {}-{} with table {}-{}", origTblId, origTable.getName(), newTblId,
                 newTbl.getName());
     }
@@ -444,9 +448,9 @@ public void swapTableInternal(SwapTableOperationLog log) throws DdlException {
         long dbId = log.getDbId();
         long origTblId = log.getOrigTblId();
         long newTblId = log.getNewTblId();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
-        OlapTable origTable = (OlapTable) db.getTable(origTblId);
-        OlapTable newTbl = (OlapTable) db.getTable(newTblId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
+        OlapTable origTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), origTblId);
+        OlapTable newTbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), newTblId);
 
         String origTblName = origTable.getName();
         String newTblName = newTbl.getName();
@@ -479,8 +483,8 @@ public void alterView(AlterViewInfo alterViewInfo) {
         List<Column> newFullSchema = alterViewInfo.getNewFullSchema();
         String comment = alterViewInfo.getComment();
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
-        View view = (View) db.getTable(tableId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
+        View view = (View) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
 
         Locker locker = new Locker();
         locker.lockTablesWithIntensiveDbLock(db, Lists.newArrayList(view.getId()), LockType.WRITE);
@@ -506,8 +510,9 @@ public void alterView(AlterViewInfo alterViewInfo) {
     }
 
     public void replayModifyPartition(ModifyPartitionInfo info) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(info.getDbId());
-        OlapTable olapTable = (OlapTable) db.getTable(info.getTableId());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(info.getDbId());
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getId(), info.getTableId());
 
         Locker locker = new Locker();
         locker.lockTablesWithIntensiveDbLock(db, Lists.newArrayList(olapTable.getId()), LockType.WRITE);
diff --git a/fe/fe-core/src/main/java/com/starrocks/alter/AlterJobV2.java b/fe/fe-core/src/main/java/com/starrocks/alter/AlterJobV2.java
index add80cae8f6de1..12c356238170ab 100644
--- a/fe/fe-core/src/main/java/com/starrocks/alter/AlterJobV2.java
+++ b/fe/fe-core/src/main/java/com/starrocks/alter/AlterJobV2.java
@@ -262,7 +262,7 @@ public boolean cancel(String errMsg) {
      */
     protected boolean checkTableStable(Database db) throws AlterCancelException {
         long unHealthyTabletId = TabletInvertedIndex.NOT_EXIST_VALUE;
-        OlapTable tbl = (OlapTable) db.getTable(tableId);
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             throw new AlterCancelException("Table " + tableId + " does not exist");
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/alter/AlterMVJobExecutor.java b/fe/fe-core/src/main/java/com/starrocks/alter/AlterMVJobExecutor.java
index 489426f0fb5af4..404b81c508b219 100644
--- a/fe/fe-core/src/main/java/com/starrocks/alter/AlterMVJobExecutor.java
+++ b/fe/fe-core/src/main/java/com/starrocks/alter/AlterMVJobExecutor.java
@@ -73,7 +73,7 @@ public Void visitTableRenameClause(TableRenameClause clause, ConnectContext cont
         String newMvName = clause.getNewTableName();
         String oldMvName = table.getName();
 
-        if (db.getTable(newMvName) != null) {
+        if (GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), newMvName) != null) {
             throw new SemanticException("Materialized view [" + newMvName + "] is already used");
         }
         table.setName(newMvName);
@@ -349,7 +349,7 @@ public Void visitRefreshSchemeClause(RefreshSchemeClause refreshSchemeDesc, Conn
             }
             try {
                 // check
-                Table mv = db.getTable(materializedView.getId());
+                Table mv = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), materializedView.getId());
                 if (mv == null) {
                     throw new DmlException(
                             "update meta failed. materialized view:" + materializedView.getName() + " not exist");
diff --git a/fe/fe-core/src/main/java/com/starrocks/alter/LakeTableAlterMetaJobBase.java b/fe/fe-core/src/main/java/com/starrocks/alter/LakeTableAlterMetaJobBase.java
index c21ce785834821..4c0effe5a1a5c7 100644
--- a/fe/fe-core/src/main/java/com/starrocks/alter/LakeTableAlterMetaJobBase.java
+++ b/fe/fe-core/src/main/java/com/starrocks/alter/LakeTableAlterMetaJobBase.java
@@ -85,13 +85,13 @@ protected void runPendingJob() throws AlterCancelException {
         // send task to be
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
         List<Partition> partitions = Lists.newArrayList();
-        Database db = globalStateMgr.getDb(dbId);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
 
         if (db == null) {
             throw new AlterCancelException("database does not exist, dbId:" + dbId);
         }
 
-        LakeTable table = (LakeTable) db.getTable(tableName);
+        LakeTable table = (LakeTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         if (table == null) {
             throw new AlterCancelException("table does not exist, tableName:" + tableName);
         }
@@ -135,13 +135,13 @@ protected void runWaitingTxnJob() throws AlterCancelException {
 
     @Override
     protected void runRunningJob() throws AlterCancelException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             // database has been dropped
             throw new AlterCancelException("database does not exist, dbId:" + dbId);
         }
 
-        LakeTable table = (LakeTable) db.getTable(tableId);
+        LakeTable table = (LakeTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             // table has been dropped
             throw new AlterCancelException("table does not exist, tableId:" + tableId);
@@ -187,14 +187,14 @@ protected void runFinishedRewritingJob() throws AlterCancelException {
             return;
         }
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             // database has been dropped
             LOG.warn("database does not exist, dbId:" + dbId);
             throw new AlterCancelException("database does not exist, dbId:" + dbId);
         }
 
-        LakeTable table = (LakeTable) db.getTable(tableId);
+        LakeTable table = (LakeTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             // table has been dropped
             LOG.warn("table does not exist, tableId:" + tableId);
@@ -221,12 +221,12 @@ protected void runFinishedRewritingJob() throws AlterCancelException {
     }
 
     boolean readyToPublishVersion() throws AlterCancelException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             // database has been dropped
             throw new AlterCancelException("database does not exist, dbId:" + dbId);
         }
-        LakeTable table = (LakeTable) db.getTable(tableId);
+        LakeTable table = (LakeTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             // table has been dropped
             throw new AlterCancelException("table does not exist, tableId:" + tableId);
@@ -422,9 +422,9 @@ protected boolean cancelImpl(String errMsg) {
             return false;
         }
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db != null) {
-            LakeTable table = (LakeTable) db.getTable(tableId);
+            LakeTable table = (LakeTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (table != null) {
                 Locker locker = new Locker();
                 locker.lockTablesWithIntensiveDbLock(db, Lists.newArrayList(table.getId()), LockType.WRITE);
@@ -480,14 +480,14 @@ public void replay(AlterJobV2 replayedJob) {
             restoreState(other);
         }
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             // database has been dropped
             LOG.warn("database does not exist, dbId:" + dbId);
             return;
         }
 
-        LakeTable table = (LakeTable) db.getTable(tableId);
+        LakeTable table = (LakeTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             return;
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/alter/LakeTableSchemaChangeJob.java b/fe/fe-core/src/main/java/com/starrocks/alter/LakeTableSchemaChangeJob.java
index 456a4d3b3b21fc..eda28f210ff83b 100644
--- a/fe/fe-core/src/main/java/com/starrocks/alter/LakeTableSchemaChangeJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/alter/LakeTableSchemaChangeJob.java
@@ -697,9 +697,10 @@ private void inactiveRelatedMv(Set<String> modifiedColumns, @NotNull OlapTable t
         if (modifiedColumns.isEmpty()) {
             return;
         }
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         for (MvId mvId : tbl.getRelatedMaterializedViews()) {
-            MaterializedView mv = (MaterializedView) db.getTable(mvId.getId());
+            MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(db.getId(), mvId.getId());
             if (mv == null) {
                 LOG.warn("Ignore materialized view {} does not exists", mvId);
                 continue;
@@ -1055,13 +1056,13 @@ public void write(DataOutput out) throws IOException {
 
     @Nullable
     ReadLockedDatabase getReadLockedDatabase(long dbId) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         return db != null ? new ReadLockedDatabase(db) : null;
     }
 
     @Nullable
     WriteLockedDatabase getWriteLockedDatabase(long dbId) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         return db != null ? new WriteLockedDatabase(db) : null;
     }
 
@@ -1088,7 +1089,7 @@ private abstract static class LockedDatabase implements AutoCloseable {
 
         @Nullable
         OlapTable getTable(long tableId) {
-            return (OlapTable) db.getTable(tableId);
+            return (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         }
 
         @Override
diff --git a/fe/fe-core/src/main/java/com/starrocks/alter/MaterializedViewHandler.java b/fe/fe-core/src/main/java/com/starrocks/alter/MaterializedViewHandler.java
index 313906699e5ae2..366a01a3a6145b 100644
--- a/fe/fe-core/src/main/java/com/starrocks/alter/MaterializedViewHandler.java
+++ b/fe/fe-core/src/main/java/com/starrocks/alter/MaterializedViewHandler.java
@@ -458,12 +458,13 @@ private List<Column> checkAndPrepareMaterializedView(CreateMaterializedViewStmt
             }
 
             // check if mv index already exists in db
-            if (db.tryGetTable(mvName).isPresent()) {
+
+            if (GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetTable(db.getFullName(), mvName).isPresent()) {
                 throw new DdlException("Table [" + mvName + "] already exists in the db " + db.getFullName());
             }
 
             // check if mv index already exists in other table's materialized indexes
-            for (Table tbl : db.getTables()) {
+            for (Table tbl : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                 if (tbl.isOlapTable()) {
                     OlapTable otherOlapTable = (OlapTable) tbl;
                     if (otherOlapTable.getIndexNameToId().size() > 1 && otherOlapTable.hasMaterializedIndex(mvName)) {
@@ -836,10 +837,10 @@ private long dropMaterializedView(String mvName, OlapTable olapTable) {
     }
 
     public void replayDropRollup(DropInfo dropInfo, GlobalStateMgr globalStateMgr) {
-        Database db = globalStateMgr.getDb(dropInfo.getDbId());
+        Database db = globalStateMgr.getLocalMetastore().getDb(dropInfo.getDbId());
         long tableId = dropInfo.getTableId();
         long rollupIndexId = dropInfo.getIndexId();
-        OlapTable olapTable = (OlapTable) db.getTable(tableId);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
 
         try (AutoCloseableLock ignore = new AutoCloseableLock(new Locker(), db, Lists.newArrayList(tableId), LockType.WRITE)) {
             TabletInvertedIndex invertedIndex = GlobalStateMgr.getCurrentState().getTabletInvertedIndex();
@@ -884,13 +885,13 @@ private void removeJobFromRunningQueue(AlterJobV2 alterJob) {
     }
 
     private void changeTableStatus(long dbId, long tableId, OlapTableState olapTableState) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             LOG.warn("db {} has been dropped when changing table {} status after rollup job done",
                     dbId, tableId);
             return;
         }
-        OlapTable tbl = (OlapTable) db.getTable(tableId);
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             return;
         }
@@ -1054,13 +1055,13 @@ public void cancel(CancelStmt stmt, String reason) throws DdlException {
         Preconditions.checkState(!Strings.isNullOrEmpty(dbName));
         Preconditions.checkState(!Strings.isNullOrEmpty(tableName));
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             ErrorReport.reportDdlException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
         }
 
         List<AlterJobV2> rollupJobV2List = new ArrayList<>();
-        Table table = db.getTable(tableName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         if (table == null) {
             ErrorReport.reportDdlException(ErrorCode.ERR_BAD_TABLE_ERROR, tableName);
         }
@@ -1114,7 +1115,7 @@ public void cancelMV(CancelStmt stmt) throws DdlException {
         Preconditions.checkState(!Strings.isNullOrEmpty(dbName));
         Preconditions.checkState(!Strings.isNullOrEmpty(tableName));
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             ErrorReport.reportDdlException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
         }
@@ -1126,7 +1127,7 @@ public void cancelMV(CancelStmt stmt) throws DdlException {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            for (Table table : db.getTables()) {
+            for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                 if (table instanceof OlapTable) {
                     List<AlterJobV2> rollupJobV2List = getUnfinishedAlterJobV2ByTableId(table.getId());
                     for (AlterJobV2 alterJobV2 : rollupJobV2List) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/alter/OnlineOptimizeJobV2.java b/fe/fe-core/src/main/java/com/starrocks/alter/OnlineOptimizeJobV2.java
index 5d92818ee5eac0..696faf87385ee3 100644
--- a/fe/fe-core/src/main/java/com/starrocks/alter/OnlineOptimizeJobV2.java
+++ b/fe/fe-core/src/main/java/com/starrocks/alter/OnlineOptimizeJobV2.java
@@ -155,7 +155,7 @@ public List<OptimizeTask> getOptimizeTasks() {
     }
 
     private OlapTable checkAndGetTable(Database db, long tableId) throws AlterCancelException {
-        Table table = db.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             throw new AlterCancelException("table: " + tableId + " does not exist in database: " + db.getFullName());
         }
@@ -173,7 +173,7 @@ protected void runPendingJob() throws AlterCancelException {
         Preconditions.checkState(jobState == JobState.PENDING, jobState);
 
         LOG.info("begin to send create temp partitions. job: {}", jobId);
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new AlterCancelException("Database " + dbId + " does not exist");
         }
@@ -240,7 +240,7 @@ protected void runWaitingTxnJob() throws AlterCancelException {
         // must check if db or table still exist first.
         // or if table is dropped, the tasks will never be finished,
         // and the job will be in RUNNING state forever.
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new AlterCancelException("Database " + dbId + " does not exist");
         }
@@ -320,7 +320,7 @@ private void disableDoubleWritePartition(Database db, OlapTable tbl) {
     protected void runRunningJob() throws AlterCancelException {
         Preconditions.checkState(jobState == JobState.RUNNING, jobState);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new AlterCancelException("Database " + dbId + " does not exist");
         }
@@ -517,7 +517,7 @@ private void cancelInternal() {
         Database db = null;
         Locker locker = new Locker();
         try {
-            db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 throw new AlterCancelException("database id:" + dbId + " does not exist");
             }
@@ -532,7 +532,7 @@ private void cancelInternal() {
         }
 
         try {
-            Table table = db.getTable(tableId);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (table == null) {
                 throw new AlterCancelException("table:" + tableId + " does not exist in database:" + db.getFullName());
             }
@@ -580,7 +580,7 @@ protected boolean isPreviousLoadFinished() throws AnalysisException {
      * Should replay all changes before this job's state transfer to PENDING.
      */
     private void replayPending(OnlineOptimizeJobV2 replayedJob) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             // database may be dropped before replaying this log. just return
             return;
@@ -588,7 +588,7 @@ private void replayPending(OnlineOptimizeJobV2 replayedJob) {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            OlapTable tbl = (OlapTable) db.getTable(tableId);
+            OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (tbl == null) {
                 // table may be dropped before replaying this log. just return
                 return;
@@ -611,7 +611,7 @@ private void replayPending(OnlineOptimizeJobV2 replayedJob) {
      * Should replay all changes in runPendingJob()
      */
     private void replayWaitingTxn(OnlineOptimizeJobV2 replayedJob) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             // database may be dropped before replaying this log. just return
             return;
@@ -620,7 +620,7 @@ private void replayWaitingTxn(OnlineOptimizeJobV2 replayedJob) {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            tbl = (OlapTable) db.getTable(tableId);
+            tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (tbl == null) {
                 // table may be dropped before replaying this log. just return
                 return;
@@ -677,12 +677,12 @@ private void onReplayFinished(OnlineOptimizeJobV2 replayedJob, OlapTable targetT
      * Should replay all changes in runRuningJob()
      */
     private void replayFinished(OnlineOptimizeJobV2 replayedJob) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db != null) {
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.WRITE);
             try {
-                OlapTable tbl = (OlapTable) db.getTable(tableId);
+                OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
                 if (tbl != null) {
                     onReplayFinished(replayedJob, tbl);
                 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/alter/OptimizeJobV2.java b/fe/fe-core/src/main/java/com/starrocks/alter/OptimizeJobV2.java
index 91c95f7626c16d..229fa73f0c23ca 100644
--- a/fe/fe-core/src/main/java/com/starrocks/alter/OptimizeJobV2.java
+++ b/fe/fe-core/src/main/java/com/starrocks/alter/OptimizeJobV2.java
@@ -140,7 +140,7 @@ public List<OptimizeTask> getOptimizeTasks() {
     }
 
     private OlapTable checkAndGetTable(Database db, long tableId) throws AlterCancelException {
-        Table table = db.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             throw new AlterCancelException("table: " + tableId + " does not exist in database: " + db.getFullName());
         }
@@ -158,7 +158,7 @@ protected void runPendingJob() throws AlterCancelException {
         Preconditions.checkState(jobState == JobState.PENDING, jobState);
 
         LOG.info("begin to send create temp partitions. job: {}", jobId);
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new AlterCancelException("Database " + dbId + " does not exist");
         }
@@ -233,7 +233,7 @@ protected void runWaitingTxnJob() throws AlterCancelException {
         List<Long> partitionLastVersion = Lists.newArrayList();
         List<String> tableColumnNames = Lists.newArrayList();
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new AlterCancelException("database id: " + dbId + " does not exist");
         }
@@ -314,12 +314,12 @@ protected void runRunningJob() throws AlterCancelException {
         // must check if db or table still exist first.
         // or if table is dropped, the tasks will never be finished,
         // and the job will be in RUNNING state forever.
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new AlterCancelException("Databasee " + dbId + " does not exist");
         }
 
-        OlapTable tbl = (OlapTable) db.getTable(tableId);
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             throw new AlterCancelException("Table " + tableId + " does not exist");
         }
@@ -545,7 +545,7 @@ private void cancelInternal() {
         Database db = null;
         Locker locker = new Locker();
         try {
-            db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 throw new AlterCancelException("database id:" + dbId + " does not exist");
             }
@@ -560,7 +560,7 @@ private void cancelInternal() {
         }
 
         try {
-            Table table = db.getTable(tableId);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (table == null) {
                 throw new AlterCancelException("table:" + tableId + " does not exist in database:" + db.getFullName());
             }
@@ -605,12 +605,12 @@ protected boolean isPreviousLoadFinished() throws AnalysisException {
      * Should replay all changes before this job's state transfer to PENDING.
      */
     private void replayPending(OptimizeJobV2 replayedJob) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             // database may be dropped before replaying this log. just return
             return;
         }
-        OlapTable tbl = (OlapTable) db.getTable(tableId);
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             // table may be dropped before replaying this log. just return
             return;
@@ -633,12 +633,12 @@ private void replayPending(OptimizeJobV2 replayedJob) {
      * Should replay all changes in runPendingJob()
      */
     private void replayWaitingTxn(OptimizeJobV2 replayedJob) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             // database may be dropped before replaying this log. just return
             return;
         }
-        OlapTable tbl = (OlapTable) db.getTable(tableId);
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             // table may be dropped before replaying this log. just return
             return;
@@ -691,9 +691,9 @@ private void onReplayFinished(OptimizeJobV2 replayedJob, OlapTable targetTable)
      * Should replay all changes in runRuningJob()
      */
     private void replayFinished(OptimizeJobV2 replayedJob) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db != null) {
-            OlapTable tbl = (OlapTable) db.getTable(tableId);
+            OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (tbl != null) {
                 try (AutoCloseableLock ignore =
                             new AutoCloseableLock(new Locker(), db, Lists.newArrayList(tbl.getId()), LockType.WRITE)) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/alter/OptimizeJobV2Builder.java b/fe/fe-core/src/main/java/com/starrocks/alter/OptimizeJobV2Builder.java
index 0a0f72de738d71..180b709808f346 100644
--- a/fe/fe-core/src/main/java/com/starrocks/alter/OptimizeJobV2Builder.java
+++ b/fe/fe-core/src/main/java/com/starrocks/alter/OptimizeJobV2Builder.java
@@ -19,6 +19,7 @@
 import com.starrocks.common.Config;
 import com.starrocks.common.UserException;
 import com.starrocks.sql.ast.OptimizeClause;
+import com.starrocks.thrift.TStorageType;
 import org.apache.logging.log4j.LogManager;
 import org.apache.logging.log4j.Logger;
 
@@ -43,6 +44,8 @@ public AlterJobV2 build() throws UserException {
         long tableId = table.getId();
         if (!Config.enable_online_optimize_table || optimizeClause.getKeysDesc() != null
                 || optimizeClause.getPartitionDesc() != null || optimizeClause.getSortKeys() != null
+                || table.getStorageType() == TStorageType.COLUMN_WITH_ROW
+                || !table.enableReplicatedStorage()
                 || table.isCloudNativeTableOrMaterializedView()) {
             OptimizeJobV2 optimizeJob = new OptimizeJobV2(jobId, dbId, tableId, table.getName(), timeoutMs, optimizeClause);
             return optimizeJob;
diff --git a/fe/fe-core/src/main/java/com/starrocks/alter/RollupJobV2.java b/fe/fe-core/src/main/java/com/starrocks/alter/RollupJobV2.java
index 0fab5eafbe5cd0..c5fa2e1b5b0d0e 100644
--- a/fe/fe-core/src/main/java/com/starrocks/alter/RollupJobV2.java
+++ b/fe/fe-core/src/main/java/com/starrocks/alter/RollupJobV2.java
@@ -252,7 +252,7 @@ protected void runPendingJob() throws AlterCancelException {
         Preconditions.checkState(jobState == JobState.PENDING, jobState);
 
         LOG.info("begin to send create rollup replica tasks. job: {}", jobId);
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new AlterCancelException("Database " + dbId + " does not exist");
         }
@@ -272,7 +272,7 @@ protected void runPendingJob() throws AlterCancelException {
         }
         MarkedCountDownLatch<Long, Long> countDownLatch = new MarkedCountDownLatch<Long, Long>(totalReplicaNum);
         createReplicaLatch = countDownLatch;
-        OlapTable tbl = (OlapTable) db.getTable(tableId);
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             throw new AlterCancelException("Table " + tableId + " does not exist");
         }
@@ -380,7 +380,7 @@ protected void runPendingJob() throws AlterCancelException {
 
         // create all rollup replicas success.
         // add rollup index to globalStateMgr
-        tbl = (OlapTable) db.getTable(tableId);
+        tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             throw new AlterCancelException("Table " + tableId + " does not exist");
         }
@@ -478,11 +478,11 @@ protected void runWaitingTxnJob() throws AlterCancelException {
         }
 
         LOG.info("previous transactions are all finished, begin to send rollup tasks. job: {}", jobId);
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new AlterCancelException("Databasee " + dbId + " does not exist");
         }
-        OlapTable tbl = (OlapTable) db.getTable(tableId);
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             throw new AlterCancelException("Table " + tableId + " does not exist");
         }
@@ -641,12 +641,12 @@ protected void runRunningJob() throws AlterCancelException {
         // must check if db or table still exist first.
         // or if table is dropped, the tasks will never be finished,
         // and the job will be in RUNNING state forever.
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new AlterCancelException("Databasee " + dbId + " does not exist");
         }
 
-        OlapTable tbl = (OlapTable) db.getTable(tableId);
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             throw new AlterCancelException("Table " + tableId + " does not exist");
         }
@@ -776,9 +776,9 @@ private void cancelInternal() {
         AgentTaskQueue.removeBatchTask(rollupBatchTask, TTaskType.ALTER);
         // remove all rollup indexes, and set state to NORMAL
         TabletInvertedIndex invertedIndex = GlobalStateMgr.getCurrentState().getTabletInvertedIndex();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db != null) {
-            OlapTable tbl = (OlapTable) db.getTable(tableId);
+            OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (tbl != null) {
                 try (AutoCloseableLock ignore =
                             new AutoCloseableLock(new Locker(), db, Lists.newArrayList(tbl.getId()), LockType.WRITE)) {
@@ -808,13 +808,13 @@ protected boolean isPreviousLoadFinished() throws AnalysisException {
      * These changes should be same as changes in RollupHander.processAddRollup()
      */
     private void replayPending(RollupJobV2 replayedJob) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             // database may be dropped before replaying this log. just return
             return;
         }
 
-        OlapTable tbl = (OlapTable) db.getTable(tableId);
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             // table may be dropped before replaying this log. just return
             return;
@@ -856,12 +856,12 @@ private void addTabletToInvertedIndex(OlapTable tbl) {
      * Should replay all changes in runPendingJob()
      */
     private void replayWaitingTxn(RollupJobV2 replayedJob) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             // database may be dropped before replaying this log. just return
             return;
         }
-        OlapTable tbl = (OlapTable) db.getTable(tableId);
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             // table may be dropped before replaying this log. just return
             return;
@@ -884,9 +884,9 @@ private void replayWaitingTxn(RollupJobV2 replayedJob) {
      * Should replay all changes in runRuningJob()
      */
     private void replayFinished(RollupJobV2 replayedJob) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db != null) {
-            OlapTable tbl = (OlapTable) db.getTable(tableId);
+            OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (tbl != null) {
                 Preconditions.checkState(tbl.getState() == OlapTableState.ROLLUP);
                 try (AutoCloseableLock ignore
diff --git a/fe/fe-core/src/main/java/com/starrocks/alter/SchemaChangeHandler.java b/fe/fe-core/src/main/java/com/starrocks/alter/SchemaChangeHandler.java
index 460f1a157f3359..a76da34b75b035 100644
--- a/fe/fe-core/src/main/java/com/starrocks/alter/SchemaChangeHandler.java
+++ b/fe/fe-core/src/main/java/com/starrocks/alter/SchemaChangeHandler.java
@@ -2057,7 +2057,8 @@ public void updateTableMeta(Database db, String tableName, Map<String, String> p
                                 TTabletMetaType metaType)
             throws DdlException {
         List<Partition> partitions = Lists.newArrayList();
-        OlapTable olapTable = (OlapTable) db.getTable(tableName);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), tableName);
 
         Locker locker = new Locker();
         locker.lockTablesWithIntensiveDbLock(db, Lists.newArrayList(olapTable.getId()), LockType.READ);
@@ -2134,7 +2135,7 @@ public boolean updateBinlogConfigMeta(Database db, Long tableId, Map<String, Str
         boolean hasChanged = false;
         boolean isModifiedSuccess = true;
 
-        OlapTable olapTable = (OlapTable) db.getTable(tableId);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (olapTable == null) {
             return false;
         }
@@ -2240,7 +2241,8 @@ public void updatePartitionsInMemoryMeta(Database db,
                                              String tableName,
                                              List<String> partitionNames,
                                              Map<String, String> properties) throws DdlException {
-        OlapTable olapTable = (OlapTable) db.getTable(tableName);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), tableName);
         Locker locker = new Locker();
         locker.lockTablesWithIntensiveDbLock(db, Lists.newArrayList(olapTable.getId()), LockType.READ);
         try {
@@ -2283,7 +2285,8 @@ public void updateBinlogPartitionTabletMeta(Database db,
                                                 TTabletMetaType metaType) throws DdlException {
         // be id -> Set<tablet id>
         Map<Long, Set<Long>> beIdToTabletId = Maps.newHashMap();
-        OlapTable olapTable = (OlapTable) db.getTable(tableName);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), tableName);
 
         Locker locker = new Locker();
         locker.lockTablesWithIntensiveDbLock(db, Lists.newArrayList(olapTable.getId()), LockType.READ);
@@ -2369,7 +2372,8 @@ public void updatePartitionTabletMeta(Database db,
                                           TTabletMetaType metaType) throws DdlException {
         // be id -> <tablet id>
         Map<Long, Set<Long>> beIdToTabletSet = Maps.newHashMap();
-        OlapTable olapTable = (OlapTable) db.getTable(tableName);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), tableName);
 
         Locker locker = new Locker();
         locker.lockTablesWithIntensiveDbLock(db, Lists.newArrayList(olapTable.getId()), LockType.READ);
@@ -2456,7 +2460,7 @@ public void updateTableConstraint(Database db, String tableName, Map<String, Str
         TableProperty tableProperty;
         OlapTable olapTable;
         try {
-            Table table = db.getTable(tableName);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
             if (table == null) {
                 throw new DdlException(String.format("table:%s does not exist", tableName));
             }
@@ -2534,12 +2538,12 @@ public void cancel(CancelStmt stmt, String reason) throws DdlException {
         Preconditions.checkState(!Strings.isNullOrEmpty(dbName));
         Preconditions.checkState(!Strings.isNullOrEmpty(tableName));
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("Database[" + dbName + "] does not exist");
         }
 
-        Table table = db.getTable(tableName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         if (table == null) {
             ErrorReport.reportDdlException(ErrorCode.ERR_BAD_TABLE_ERROR, tableName);
         }
@@ -2767,8 +2771,8 @@ public void replayModifyTableAddOrDrop(TableAddOrDropColumnsInfo info) throws
         List<Index> indexes = info.getIndexes();
         long jobId = info.getJobId();
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
-        Table table = db.getTable(tableId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         Preconditions.checkArgument(table instanceof OlapTable,
                 "Target of light schema change must be olap table");
         OlapTable olapTable = (OlapTable) table;
diff --git a/fe/fe-core/src/main/java/com/starrocks/alter/SchemaChangeJobV2.java b/fe/fe-core/src/main/java/com/starrocks/alter/SchemaChangeJobV2.java
index ee7548839c1312..cb14e7e8ae80d7 100644
--- a/fe/fe-core/src/main/java/com/starrocks/alter/SchemaChangeJobV2.java
+++ b/fe/fe-core/src/main/java/com/starrocks/alter/SchemaChangeJobV2.java
@@ -293,7 +293,7 @@ private void pruneMeta() {
     protected void runPendingJob() throws AlterCancelException {
         Preconditions.checkState(jobState == JobState.PENDING, jobState);
         LOG.info("begin to send create replica tasks. job: {}", jobId);
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new AlterCancelException("Databasee " + dbId + " does not exist");
         }
@@ -314,7 +314,7 @@ protected void runPendingJob() throws AlterCancelException {
         MarkedCountDownLatch<Long, Long> countDownLatch = new MarkedCountDownLatch<>(totalReplicaNum);
         createReplicaLatch = countDownLatch;
 
-        OlapTable tbl = (OlapTable) db.getTable(tableId);
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             throw new AlterCancelException("Table " + tableId + " does not exist");
         }
@@ -434,7 +434,7 @@ protected void runPendingJob() throws AlterCancelException {
 
         // create all replicas success.
         // add all shadow indexes to globalStateMgr
-        tbl = (OlapTable) db.getTable(tableId);
+        tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             throw new AlterCancelException("Table " + tableId + " does not exist");
         }
@@ -510,11 +510,11 @@ protected void runWaitingTxnJob() throws AlterCancelException {
         }
 
         LOG.info("previous transactions are all finished, begin to send schema change tasks. job: {}", jobId);
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new AlterCancelException("Databasee " + dbId + " does not exist");
         }
-        OlapTable tbl = (OlapTable) db.getTable(tableId);
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             throw new AlterCancelException("Table " + tableId + " does not exist");
         }
@@ -702,12 +702,12 @@ protected void runRunningJob() throws AlterCancelException {
         // must check if db or table still exist first.
         // or if table is dropped, the tasks will never be finished,
         // and the job will be in RUNNING state forever.
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new AlterCancelException("Database " + dbId + " does not exist");
         }
 
-        OlapTable tbl = (OlapTable) db.getTable(tableId);
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             throw new AlterCancelException("Table " + tableId + " does not exist");
         }
@@ -974,9 +974,9 @@ private void cancelInternal() {
         AgentTaskQueue.removeBatchTask(schemaChangeBatchTask, TTaskType.ALTER);
         // remove all shadow indexes, and set state to NORMAL
         TabletInvertedIndex invertedIndex = GlobalStateMgr.getCurrentState().getTabletInvertedIndex();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db != null) {
-            OlapTable tbl = (OlapTable) db.getTable(tableId);
+            OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (tbl != null) {
                 Locker locker = new Locker();
                 locker.lockTablesWithIntensiveDbLock(db, Lists.newArrayList(tbl.getId()), LockType.WRITE);
@@ -1019,13 +1019,13 @@ protected boolean isPreviousLoadFinished() throws AnalysisException {
      * These changes should be same as changes in SchemaChangeHandler.createJob()
      */
     private void replayPending(SchemaChangeJobV2 replayedJob) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             // database may be dropped before replaying this log. just return
             return;
         }
 
-        OlapTable tbl = (OlapTable) db.getTable(tableId);
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             // table may be dropped before replaying this log. just return
             return;
@@ -1070,12 +1070,12 @@ private void replayPending(SchemaChangeJobV2 replayedJob) {
      * Should replay all changes in runPendingJob()
      */
     private void replayWaitingTxn(SchemaChangeJobV2 replayedJob) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             // database may be dropped before replaying this log. just return
             return;
         }
-        OlapTable tbl = (OlapTable) db.getTable(tableId);
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (tbl == null) {
             // table may be dropped before replaying this log. just return
             return;
@@ -1100,10 +1100,10 @@ private void replayWaitingTxn(SchemaChangeJobV2 replayedJob) {
      * Should replay all changes in runRuningJob()
      */
     private void replayFinished(SchemaChangeJobV2 replayedJob) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db != null) {
 
-            OlapTable tbl = (OlapTable) db.getTable(tableId);
+            OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (tbl != null) {
                 Locker locker = new Locker();
                 locker.lockTablesWithIntensiveDbLock(db, Lists.newArrayList(tbl.getId()), LockType.WRITE);
diff --git a/fe/fe-core/src/main/java/com/starrocks/alter/SystemHandler.java b/fe/fe-core/src/main/java/com/starrocks/alter/SystemHandler.java
index a48b3e9e1ae056..0172fd150c4dc8 100644
--- a/fe/fe-core/src/main/java/com/starrocks/alter/SystemHandler.java
+++ b/fe/fe-core/src/main/java/com/starrocks/alter/SystemHandler.java
@@ -240,7 +240,7 @@ public Void visitDecommissionBackendClause(DecommissionBackendClause clause, Voi
                             Locker locker = new Locker();
                             locker.lockDatabase(db, LockType.READ);
                             try {
-                                for (Table table : db.getTables()) {
+                                for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                                     if (table instanceof OlapTable) {
                                         OlapTable olapTable = (OlapTable) table;
                                         PartitionInfo partitionInfo = olapTable.getPartitionInfo();
diff --git a/fe/fe-core/src/main/java/com/starrocks/analysis/Analyzer.java b/fe/fe-core/src/main/java/com/starrocks/analysis/Analyzer.java
index ddaa29fb417fc5..c3d9f526681570 100644
--- a/fe/fe-core/src/main/java/com/starrocks/analysis/Analyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/analysis/Analyzer.java
@@ -229,11 +229,11 @@ public TupleDescriptor registerTableRef(TableRef ref) throws AnalysisException {
     }
 
     public Table getTable(TableName tblName) {
-        Database db = globalState.globalStateMgr.getDb(tblName.getDb());
+        Database db = globalState.globalStateMgr.getLocalMetastore().getDb(tblName.getDb());
         if (db == null) {
             return null;
         }
-        return db.getTable(tblName.getTbl());
+        return GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tblName.getTbl());
     }
 
     public TupleDescriptor getTupleDesc(TupleId id) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/analysis/TableName.java b/fe/fe-core/src/main/java/com/starrocks/analysis/TableName.java
index ee71e5276fc651..a838c98fd0f186 100644
--- a/fe/fe-core/src/main/java/com/starrocks/analysis/TableName.java
+++ b/fe/fe-core/src/main/java/com/starrocks/analysis/TableName.java
@@ -126,26 +126,22 @@ public void analyze(Analyzer analyzer) throws AnalysisException {
     }
 
     public void normalization(ConnectContext connectContext) {
-        try {
-            if (Strings.isNullOrEmpty(catalog)) {
-                if (Strings.isNullOrEmpty(connectContext.getCurrentCatalog())) {
-                    ErrorReport.reportAnalysisException(ErrorCode.ERR_BAD_CATALOG_ERROR, catalog);
-                }
-                catalog = connectContext.getCurrentCatalog();
+        if (Strings.isNullOrEmpty(catalog)) {
+            if (Strings.isNullOrEmpty(connectContext.getCurrentCatalog())) {
+                ErrorReport.reportSemanticException(ErrorCode.ERR_BAD_CATALOG_ERROR, catalog);
             }
+            catalog = connectContext.getCurrentCatalog();
+        }
 
+        if (Strings.isNullOrEmpty(db)) {
+            db = connectContext.getDatabase();
             if (Strings.isNullOrEmpty(db)) {
-                db = connectContext.getDatabase();
-                if (Strings.isNullOrEmpty(db)) {
-                    ErrorReport.reportAnalysisException(ErrorCode.ERR_NO_DB_ERROR);
-                }
+                ErrorReport.reportSemanticException(ErrorCode.ERR_NO_DB_ERROR);
             }
+        }
 
-            if (Strings.isNullOrEmpty(tbl)) {
-                throw new SemanticException("Table name is null");
-            }
-        } catch (AnalysisException e) {
-            throw new SemanticException(e.getMessage());
+        if (Strings.isNullOrEmpty(tbl)) {
+            throw new SemanticException("Table name is null");
         }
     }
 
@@ -251,8 +247,12 @@ public void gsonPreProcess() throws IOException {
 
     @Override
     public boolean equals(Object o) {
-        if (this == o) return true;
-        if (o == null || getClass() != o.getClass()) return false;
+        if (this == o) {
+            return true;
+        }
+        if (o == null || getClass() != o.getClass()) {
+            return false;
+        }
         TableName tableName = (TableName) o;
         return Objects.equals(catalog, tableName.catalog)
                 && Objects.equals(tbl, tableName.tbl)
diff --git a/fe/fe-core/src/main/java/com/starrocks/backup/BackupHandler.java b/fe/fe-core/src/main/java/com/starrocks/backup/BackupHandler.java
index 62fcd7fbb28afb..574a9e453c728d 100644
--- a/fe/fe-core/src/main/java/com/starrocks/backup/BackupHandler.java
+++ b/fe/fe-core/src/main/java/com/starrocks/backup/BackupHandler.java
@@ -262,7 +262,7 @@ public void process(AbstractBackupStmt stmt) throws DdlException {
 
         // check if db exist
         String dbName = stmt.getDbName();
-        Database db = globalStateMgr.getDb(dbName);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbName);
         if (db == null) {
             ErrorReport.reportDdlException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
         }
@@ -319,7 +319,7 @@ private void backup(Repository repository, Database db, BackupStmt stmt) throws
             List<Table> backupTbls = Lists.newArrayList();
             for (TableRef tblRef : tblRefs) {
                 String tblName = tblRef.getName().getTbl();
-                Table tbl = db.getTable(tblName);
+                Table tbl = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tblName);
                 if (tbl == null) {
                     ErrorReport.reportDdlException(ErrorCode.ERR_BAD_TABLE_ERROR, tblName);
                     return;
@@ -519,7 +519,7 @@ private void checkAndFilterRestoreObjsExistInSnapshot(BackupJobInfo jobInfo, Lis
     }
 
     public AbstractJob getAbstractJobByDbName(String dbName) throws DdlException {
-        Database db = globalStateMgr.getDb(dbName);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbName);
         if (db == null) {
             ErrorReport.reportDdlException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/backup/BackupJob.java b/fe/fe-core/src/main/java/com/starrocks/backup/BackupJob.java
index 632087a0502e70..6c699655f8ee88 100644
--- a/fe/fe-core/src/main/java/com/starrocks/backup/BackupJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/backup/BackupJob.java
@@ -393,7 +393,7 @@ public synchronized boolean isDone() {
     protected void checkBackupTables(Database db) {
         for (TableRef tableRef : tableRefs) {
             String tblName = tableRef.getName().getTbl();
-            Table tbl = db.getTable(tblName);
+            Table tbl = globalStateMgr.getLocalMetastore().getTable(db.getFullName(), tblName);
             if (tbl == null) {
                 status = new Status(ErrCode.NOT_FOUND, "table " + tblName + " does not exist");
                 return;
@@ -449,7 +449,7 @@ protected void sendSnapshotRequests() {
 
     private void prepareAndSendSnapshotTask() {
         MetricRepo.COUNTER_UNFINISHED_BACKUP_JOB.increase(1L);
-        Database db = globalStateMgr.getDb(dbId);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
         if (db == null) {
             status = new Status(ErrCode.NOT_FOUND, "database " + dbId + " does not exist");
             return;
@@ -473,7 +473,8 @@ private void prepareAndSendSnapshotTask() {
             // create snapshot tasks
             for (TableRef tblRef : tableRefs) {
                 String tblName = tblRef.getName().getTbl();
-                OlapTable tbl = (OlapTable) db.getTable(tblName);
+                OlapTable tbl = (OlapTable) globalStateMgr.getLocalMetastore()
+                            .getTable(db.getFullName(), tblName);
                 List<Partition> partitions = Lists.newArrayList();
                 if (tblRef.getPartitionNames() == null) {
                     partitions.addAll(tbl.getPartitions());
@@ -508,7 +509,8 @@ private void prepareAndSendSnapshotTask() {
             List<Table> copiedTables = Lists.newArrayList();
             for (TableRef tableRef : tableRefs) {
                 String tblName = tableRef.getName().getTbl();
-                OlapTable tbl = (OlapTable) db.getTable(tblName);
+                OlapTable tbl = (OlapTable) globalStateMgr.getLocalMetastore()
+                            .getTable(db.getFullName(), tblName);
                 // only copy visible indexes
                 List<String> reservedPartitions = tableRef.getPartitionNames() == null ? null
                         : tableRef.getPartitionNames().getPartitionNames();
diff --git a/fe/fe-core/src/main/java/com/starrocks/backup/RestoreJob.java b/fe/fe-core/src/main/java/com/starrocks/backup/RestoreJob.java
index e48eb52fe916a6..fd092d2c12d13b 100644
--- a/fe/fe-core/src/main/java/com/starrocks/backup/RestoreJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/backup/RestoreJob.java
@@ -414,7 +414,7 @@ private void checkIfNeedCancel() {
             return;
         }
 
-        Database db = globalStateMgr.getDb(dbId);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
         if (db == null) {
             status = new Status(ErrCode.NOT_FOUND, "database " + dbId + " has been dropped");
             return;
@@ -424,7 +424,8 @@ private void checkIfNeedCancel() {
         locker.lockDatabase(db, LockType.READ);
         try {
             for (IdChain idChain : fileMapping.getMapping().keySet()) {
-                OlapTable tbl = (OlapTable) db.getTable(idChain.getTblId());
+                OlapTable tbl = (OlapTable) globalStateMgr.getLocalMetastore()
+                            .getTable(db.getId(), idChain.getTblId());
                 if (tbl == null) {
                     status = new Status(ErrCode.NOT_FOUND, "table " + idChain.getTblId() + " has been dropped");
                     return;
@@ -468,7 +469,7 @@ private void checkIfNeedCancel() {
      */
     private void checkAndPrepareMeta() {
         MetricRepo.COUNTER_UNFINISHED_RESTORE_JOB.increase(1L);
-        Database db = globalStateMgr.getDb(dbId);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
         if (db == null) {
             status = new Status(ErrCode.NOT_FOUND, "database " + dbId + " does not exist");
             return;
@@ -488,7 +489,8 @@ private void checkAndPrepareMeta() {
         locker.lockDatabase(db, LockType.WRITE);
         try {
             for (BackupTableInfo tblInfo : jobInfo.tables.values()) {
-                Table tbl = db.getTable(jobInfo.getAliasByOriginNameIfSet(tblInfo.name));
+                Table tbl = globalStateMgr.getLocalMetastore()
+                        .getTable(db.getFullName(), jobInfo.getAliasByOriginNameIfSet(tblInfo.name));
                 if (tbl == null) {
                     continue;
                 }
@@ -523,7 +525,8 @@ private void checkAndPrepareMeta() {
             for (BackupTableInfo tblInfo : jobInfo.tables.values()) {
                 Table remoteTbl = backupMeta.getTable(tblInfo.name);
                 Preconditions.checkNotNull(remoteTbl);
-                Table localTbl = db.getTable(jobInfo.getAliasByOriginNameIfSet(tblInfo.name));
+                Table localTbl = globalStateMgr.getLocalMetastore()
+                            .getTable(db.getFullName(), jobInfo.getAliasByOriginNameIfSet(tblInfo.name));
                 if (localTbl != null) {
                     if (localTbl instanceof OlapTable && localTbl.hasAutoIncrementColumn()) {
                         // it must be !isReplay == true
@@ -707,7 +710,7 @@ private void checkAndPrepareMeta() {
                         return;
                     }
 
-                    ColocateTableIndex colocateTableIndex = GlobalStateMgr.getCurrentState().getColocateTableIndex();
+                    ColocateTableIndex colocateTableIndex = globalStateMgr.getColocateTableIndex();
                     if (enableColocateRestore && colocateTableIndex.isColocateTable(remoteOlapTbl.getId())) {
                         ColocateTableIndex.GroupId groupId = colocateTableIndex.getGroup(remoteOlapTbl.getId());
                         List<List<Long>> backendsPerBucketSeq = colocateTableIndex.getBackendsPerBucketSeq(groupId);
@@ -731,7 +734,8 @@ private void checkAndPrepareMeta() {
 
             // generate create replica tasks for all restored partitions
             for (Pair<String, Partition> entry : restoredPartitions) {
-                OlapTable localTbl = (OlapTable) db.getTable(entry.first);
+                OlapTable localTbl = (OlapTable) globalStateMgr.getLocalMetastore()
+                            .getTable(db.getFullName(), entry.first);
                 Preconditions.checkNotNull(localTbl, localTbl.getName());
                 Partition restorePart = entry.second;
                 OlapTable remoteTbl = (OlapTable) backupMeta.getTable(entry.first);
@@ -862,7 +866,8 @@ protected void prepareAndSendSnapshotTasks(Database db) {
         locker.lockDatabase(db, LockType.READ);
         try {
             for (IdChain idChain : fileMapping.getMapping().keySet()) {
-                OlapTable tbl = (OlapTable) db.getTable(idChain.getTblId());
+                OlapTable tbl = (OlapTable) globalStateMgr.getLocalMetastore()
+                            .getTable(db.getId(), idChain.getTblId());
                 PhysicalPartition part = tbl.getPhysicalPartition(idChain.getPartId());
                 MaterializedIndex index = part.getIndex(idChain.getIdxId());
                 LocalTablet tablet = (LocalTablet) index.getTablet(idChain.getTabletId());
@@ -884,7 +889,7 @@ protected void prepareAndSendSnapshotTasks(Database db) {
 
         // check disk capacity
         com.starrocks.common.Status st =
-                GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo().checkExceedDiskCapacityLimit(bePathsMap, true);
+                globalStateMgr.getNodeMgr().getClusterInfo().checkExceedDiskCapacityLimit(bePathsMap, true);
         if (!st.ok()) {
             status = new Status(ErrCode.COMMON_ERROR, st.getErrorMsg());
             return;
@@ -940,9 +945,9 @@ protected void createReplicas(OlapTable localTbl, Partition restorePart) {
                         .setIndexes(localTbl.getCopiedIndexes())
                         .build().toTabletSchema();
                 for (Tablet restoreTablet : restoredIdx.getTablets()) {
-                    GlobalStateMgr.getCurrentState().getTabletInvertedIndex().addTablet(restoreTablet.getId(), tabletMeta);
+                    globalStateMgr.getTabletInvertedIndex().addTablet(restoreTablet.getId(), tabletMeta);
                     for (Replica restoreReplica : ((LocalTablet) restoreTablet).getImmutableReplicas()) {
-                        GlobalStateMgr.getCurrentState().getTabletInvertedIndex()
+                        globalStateMgr.getTabletInvertedIndex()
                                 .addReplica(restoreTablet.getId(), restoreReplica);
                         LOG.info("tablet {} physical partition {} index {} replica {}",
                                 restoreTablet.getId(), physicalPartition.getId(), restoredIdx.getId(),
@@ -1087,13 +1092,14 @@ protected void genFileMappingWithSubPartition(OlapTable localTbl, Partition loca
     }
 
     private void replayCheckAndPrepareMeta() {
-        Database db = globalStateMgr.getDb(dbId);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
             // replay set all existing tables's state to RESTORE
             for (BackupTableInfo tblInfo : jobInfo.tables.values()) {
-                Table tbl = db.getTable(jobInfo.getAliasByOriginNameIfSet(tblInfo.name));
+                Table tbl = globalStateMgr.getLocalMetastore()
+                            .getTable(db.getFullName(), jobInfo.getAliasByOriginNameIfSet(tblInfo.name));
                 if (tbl == null) {
                     continue;
                 }
@@ -1121,7 +1127,8 @@ private void replayCheckAndPrepareMeta() {
 
     protected void addRestoredPartitions(Database db, boolean modify) {
         for (Pair<String, Partition> entry : restoredPartitions) {
-            OlapTable localTbl = (OlapTable) db.getTable(entry.first);
+            OlapTable localTbl = (OlapTable) globalStateMgr.getLocalMetastore()
+                        .getTable(db.getFullName(), entry.first);
             Partition restorePart = entry.second;
             OlapTable remoteTbl = (OlapTable) backupMeta.getTable(entry.first);
             RangePartitionInfo localPartitionInfo = (RangePartitionInfo) localTbl.getPartitionInfo();
@@ -1148,9 +1155,9 @@ protected void modifyInvertedIndex(OlapTable restoreTbl, Partition restorePart)
             TabletMeta tabletMeta = new TabletMeta(dbId, restoreTbl.getId(), restorePart.getId(),
                     restoreIdx.getId(), schemaHash, TStorageMedium.HDD);
             for (Tablet restoreTablet : restoreIdx.getTablets()) {
-                GlobalStateMgr.getCurrentState().getTabletInvertedIndex().addTablet(restoreTablet.getId(), tabletMeta);
+                globalStateMgr.getTabletInvertedIndex().addTablet(restoreTablet.getId(), tabletMeta);
                 for (Replica restoreReplica : ((LocalTablet) restoreTablet).getImmutableReplicas()) {
-                    GlobalStateMgr.getCurrentState().getTabletInvertedIndex()
+                    globalStateMgr.getTabletInvertedIndex()
                             .addReplica(restoreTablet.getId(), restoreReplica);
                 }
             }
@@ -1164,7 +1171,7 @@ private void waitingAllSnapshotsFinished() {
 
             globalStateMgr.getEditLog().logRestoreJob(this);
             for (ColocatePersistInfo colocatePersistInfo : colocatePersistInfos) {
-                GlobalStateMgr.getCurrentState().getEditLog().logColocateAddTable(colocatePersistInfo);
+                globalStateMgr.getEditLog().logColocateAddTable(colocatePersistInfo);
             }
             LOG.info("finished making snapshots. {}", this);
             return;
@@ -1191,7 +1198,7 @@ private void downloadSnapshots() {
         for (long dbId : dbToSnapshotInfos.keySet()) {
             List<SnapshotInfo> infos = dbToSnapshotInfos.get(dbId);
 
-            Database db = globalStateMgr.getDb(dbId);
+            Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
             if (db == null) {
                 status = new Status(ErrCode.NOT_FOUND, "db " + dbId + " does not exist");
                 return;
@@ -1280,7 +1287,7 @@ protected void prepareDownloadTasks(List<SnapshotInfo> beSnapshotInfos, Database
             int currentBatchTaskNum = (batch == batchNum - 1) ? totalNum - index : taskNumPerBatch;
             for (int j = 0; j < currentBatchTaskNum; j++) {
                 SnapshotInfo info = beSnapshotInfos.get(index++);
-                Table tbl = db.getTable(info.getTblId());
+                Table tbl = globalStateMgr.getLocalMetastore().getTable(db.getId(), info.getTblId());
                 if (tbl == null) {
                     status = new Status(ErrCode.NOT_FOUND, "restored table "
                             + info.getTabletId() + " does not exist");
@@ -1416,7 +1423,7 @@ protected void waitingAllTabletsCommitted() {
     }
 
     private Status allTabletCommitted(boolean isReplay) {
-        Database db = globalStateMgr.getDb(dbId);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
         if (db == null) {
             return new Status(ErrCode.NOT_FOUND, "database " + dbId + " does not exist");
         }
@@ -1429,7 +1436,7 @@ private Status allTabletCommitted(boolean isReplay) {
             setTableStateToNormal(db);
 
             for (long tblId : restoredVersionInfo.rowKeySet()) {
-                Table tbl = db.getTable(tblId);
+                Table tbl = globalStateMgr.getLocalMetastore().getTable(db.getId(), tblId);
                 if (tbl == null) {
                     continue;
                 }
@@ -1475,7 +1482,8 @@ private Status allTabletCommitted(boolean isReplay) {
             locker.lockDatabase(db, LockType.READ);
             try {
                 for (BackupTableInfo tblInfo : jobInfo.tables.values()) {
-                    Table tbl = db.getTable(jobInfo.getAliasByOriginNameIfSet(tblInfo.name));
+                    Table tbl = globalStateMgr.getLocalMetastore()
+                                .getTable(db.getFullName(), jobInfo.getAliasByOriginNameIfSet(tblInfo.name));
                     // skip to restore table ids
                     if (skipRestoreRemoteTableIds.contains(tblInfo.id)) {
                         continue;
@@ -1643,7 +1651,7 @@ public void cancelInternal(boolean isReplay) {
         }
 
         // clean restored objs
-        Database db = globalStateMgr.getDb(dbId);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
         if (db != null) {
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.WRITE);
@@ -1657,7 +1665,7 @@ public void cancelInternal(boolean isReplay) {
                     for (Partition part : restoreTbl.getPartitions()) {
                         for (MaterializedIndex idx : part.getMaterializedIndices(IndexExtState.VISIBLE)) {
                             for (Tablet tablet : idx.getTablets()) {
-                                GlobalStateMgr.getCurrentState().getTabletInvertedIndex().deleteTablet(tablet.getId());
+                                globalStateMgr.getTabletInvertedIndex().deleteTablet(tablet.getId());
                             }
                         }
                     }
@@ -1666,7 +1674,8 @@ public void cancelInternal(boolean isReplay) {
 
                 // remove restored partitions
                 for (Pair<String, Partition> entry : restoredPartitions) {
-                    OlapTable restoreTbl = (OlapTable) db.getTable(entry.first);
+                    OlapTable restoreTbl = (OlapTable) globalStateMgr.getLocalMetastore()
+                                .getTable(db.getFullName(), entry.first);
                     if (restoreTbl == null) {
                         continue;
                     }
@@ -1683,7 +1692,7 @@ public void cancelInternal(boolean isReplay) {
         for (ColocatePersistInfo colocatePersistInfo : colocatePersistInfos) {
             for (Table restoreTbl : restoredTbls) {
                 if (restoreTbl instanceof OlapTable && restoreTbl.getId() == colocatePersistInfo.getTableId()) {
-                    GlobalStateMgr.getCurrentState().getColocateTableIndex()
+                    globalStateMgr.getColocateTableIndex()
                                         .removeTable(restoreTbl.getId(), (OlapTable) restoreTbl, isReplay);
                 }
             }
@@ -1715,7 +1724,8 @@ private void setTableStateToNormal(Database db) {
             if (skipRestoreRemoteTableIds.contains(tblInfo.id)) {
                 continue;
             }
-            Table tbl = db.getTable(jobInfo.getAliasByOriginNameIfSet(tblInfo.name));
+            Table tbl = globalStateMgr.getLocalMetastore()
+                        .getTable(db.getFullName(), jobInfo.getAliasByOriginNameIfSet(tblInfo.name));
             if (tbl == null) {
                 continue;
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/backup/mv/MVRestoreUpdater.java b/fe/fe-core/src/main/java/com/starrocks/backup/mv/MVRestoreUpdater.java
index b49d695f1c0c88..4d3ca893389a9e 100644
--- a/fe/fe-core/src/main/java/com/starrocks/backup/mv/MVRestoreUpdater.java
+++ b/fe/fe-core/src/main/java/com/starrocks/backup/mv/MVRestoreUpdater.java
@@ -213,13 +213,14 @@ public static boolean restoreBaseTableInfoIfNoRestored(MaterializedView mv,
 
         String remoteDbName = baseTableInfo.getDbName();
         String remoteTableName = baseTableInfo.getTableName();
-        Database baseTableDb = GlobalStateMgr.getCurrentState().getDb(remoteDbName);
+        Database baseTableDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(remoteDbName);
         if (baseTableDb == null) {
             LOG.warn(String.format("Materialized view %s can not find old base table's db name:%s.%s",
                     mv.getName(), remoteDbName, remoteTableName));
             return false;
         }
-        Table baseTable = baseTableDb.getTable(remoteTableName);
+        Table baseTable = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(baseTableDb.getFullName(), remoteTableName);
         if (baseTable == null) {
             LOG.warn(String.format("Materialized view %s can not find old base table:%s.%s",
                     mv.getName(), remoteDbName, remoteTableName));
@@ -249,14 +250,14 @@ public static Pair<Boolean, Optional<MvId>> restoreBaseTableInfoIfRestored(MvRes
         }
 
         String localDbName = mvBaseTableBackupInfo.getLocalDbName();
-        Database db = GlobalStateMgr.getCurrentState().getDb(localDbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(localDbName);
         String localTableName = mvBaseTableBackupInfo.getLocalTableName();
         if (db == null) {
             LOG.warn("BaseTable(local) {}'s db {} is not found, remote db/table: {}/{}",
                     localTableName, localDbName, remoteDbName, remoteTableName);
             return Pair.create(false, Optional.empty());
         }
-        Table localTable = db.getTable(localTableName);
+        Table localTable = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), localTableName);
         remoteToLocalTableName.put(remoteDbTblName, new TableName(db.getFullName(), localTableName));
         if (localTable == null) {
             LOG.warn("Materialized view {} can not find the base table {}, old base table name:{}",
diff --git a/fe/fe-core/src/main/java/com/starrocks/binlog/BinlogManager.java b/fe/fe-core/src/main/java/com/starrocks/binlog/BinlogManager.java
index 14b097ec8b0c62..f530d321967900 100644
--- a/fe/fe-core/src/main/java/com/starrocks/binlog/BinlogManager.java
+++ b/fe/fe-core/src/main/java/com/starrocks/binlog/BinlogManager.java
@@ -226,12 +226,13 @@ public boolean tryDisableBinlog(Database db, long tableId) {
 
 
     public boolean isBinlogAvailable(long dbId, long tableId) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db != null) {
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.READ);
             try {
-                OlapTable olapTable = (OlapTable) db.getTable(tableId);
+                OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(db.getId(), tableId);
                 if (olapTable != null) {
                     return olapTable.getBinlogAvailableVersion().size() != 0;
                 }
@@ -246,12 +247,13 @@ public boolean isBinlogAvailable(long dbId, long tableId) {
     // the binlog is available
     // result : partitionId -> binlogAvailableVersion, null indicates the db or table is dropped
     public Map<Long, Long> getBinlogAvailableVersion(long dbId, long tableId) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db != null) {
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.READ);
             try {
-                OlapTable olapTable = (OlapTable) db.getTable(tableId);
+                OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(db.getId(), tableId);
                 if (olapTable != null) {
                     return olapTable.getBinlogAvailableVersion();
                 }
@@ -268,12 +270,12 @@ public HashMap<Long, BinlogConfig> showAllBinlog() {
         HashMap<Long, BinlogConfig> allTablesWithBinlogConfigMap = new HashMap<>();
         List<Long> allDbIds = GlobalStateMgr.getCurrentState().getLocalMetastore().getDbIds();
         for (Long dbId : allDbIds) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db != null) {
                 Locker locker = new Locker();
                 locker.lockDatabase(db, LockType.READ);
                 try {
-                    List<Table> tables = db.getTables();
+                    List<Table> tables = GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId());
                     for (Table table : tables) {
                         if (table.isOlapTable() && ((OlapTable) table).isBinlogEnabled()) {
                             allTablesWithBinlogConfigMap.put(table.getId(), ((OlapTable) table).getCurBinlogConfig());
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/AggregateFunction.java b/fe/fe-core/src/main/java/com/starrocks/catalog/AggregateFunction.java
index 2e2de997774707..414e0b933d9cd7 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/AggregateFunction.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/AggregateFunction.java
@@ -139,9 +139,9 @@ public AggregateFunction(FunctionName fnName, List<Type> argTypes, Type retType,
         this.intermediateType =
                 (intermediateType != null && intermediateType.equals(retType)) ? null : intermediateType;
         this.isAnalyticFn = isAnalyticFn;
-        ignoresDistinct = false;
-        isAggregateFn = true;
-        returnsNonNullOnEmpty = false;
+        this.ignoresDistinct = false;
+        this.isAggregateFn = true;
+        this.returnsNonNullOnEmpty = false;
     }
 
     public static AggregateFunction createBuiltin(String name,
@@ -315,6 +315,10 @@ public void setIntermediateType(Type t) {
         intermediateType = t;
     }
 
+    public Type getIntermediateTypeOrReturnType() {
+        return intermediateType == null ? getReturnType() : intermediateType;
+    }
+
     @Override
     public String toSql(boolean ifNotExists) {
         StringBuilder sb = new StringBuilder("CREATE AGGREGATE FUNCTION ");
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/AggregateType.java b/fe/fe-core/src/main/java/com/starrocks/catalog/AggregateType.java
index e94adbe1e92d91..a7c16646896a3a 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/AggregateType.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/AggregateType.java
@@ -50,7 +50,8 @@ public enum AggregateType {
     HLL_UNION("HLL_UNION"),
     NONE("NONE"),
     BITMAP_UNION("BITMAP_UNION"),
-    PERCENTILE_UNION("PERCENTILE_UNION");
+    PERCENTILE_UNION("PERCENTILE_UNION"),
+    AGG_STATE_UNION("AGG_STATE_UNION");
 
     private static EnumMap<AggregateType, EnumSet<PrimitiveType>> compatibilityMap;
 
@@ -115,7 +116,6 @@ public enum AggregateType {
         excObject.remove(PrimitiveType.HLL);
         excObject.remove(PrimitiveType.PERCENTILE);
         excObject.remove(PrimitiveType.INVALID_TYPE);
-
         compatibilityMap.put(REPLACE_IF_NOT_NULL, EnumSet.copyOf(excObject));
 
         primitiveTypeList.clear();
@@ -126,10 +126,12 @@ public enum AggregateType {
         primitiveTypeList.add(PrimitiveType.BITMAP);
         compatibilityMap.put(BITMAP_UNION, EnumSet.copyOf(primitiveTypeList));
 
+        // percentile
         primitiveTypeList.clear();
         primitiveTypeList.add(PrimitiveType.PERCENTILE);
         compatibilityMap.put(PERCENTILE_UNION, EnumSet.copyOf(primitiveTypeList));
 
+        // none
         compatibilityMap.put(NONE, EnumSet.copyOf(excObject));
     }
 
@@ -140,6 +142,10 @@ public enum AggregateType {
     }
 
     public static boolean checkPrimitiveTypeCompatibility(AggregateType aggType, PrimitiveType priType) {
+        // AGG_STATE_UNION can accept all types, we cannot use compatibilityMap to check it.
+        if (aggType == AGG_STATE_UNION) {
+            return true;
+        }
         return compatibilityMap.get(aggType).contains(priType);
     }
 
@@ -205,6 +211,8 @@ public TAggregationType toThrift() {
                 return TAggregationType.BITMAP_UNION;
             case PERCENTILE_UNION:
                 return TAggregationType.PERCENTILE_UNION;
+            case AGG_STATE_UNION:
+                return TAggregationType.AGG_STATE_UNION;
             default:
                 return null;
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/CatalogRecycleBin.java b/fe/fe-core/src/main/java/com/starrocks/catalog/CatalogRecycleBin.java
index 7f7e254507e1dd..0c81586fe59593 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/CatalogRecycleBin.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/CatalogRecycleBin.java
@@ -832,7 +832,7 @@ public void addTabletToInvertedIndex() {
             // we need to get olap table to get schema hash info
             // first find it in globalStateMgr. if not found, it should be in recycle bin
             OlapTable olapTable = null;
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 // just log. db should be in recycle bin
                 if (!idToDatabase.containsKey(dbId)) {
@@ -842,7 +842,7 @@ public void addTabletToInvertedIndex() {
                     continue;
                 }
             } else {
-                olapTable = (OlapTable) db.getTable(tableId);
+                olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             }
 
             if (olapTable == null) {
@@ -903,6 +903,11 @@ protected void runAfterCatalogReady() {
         }
     }
 
+    @VisibleForTesting
+    synchronized boolean isContainedInidToRecycleTime(long id) {
+        return idToRecycleTime.get(id) != null;
+    }
+
     @Override
     public void write(DataOutput out) throws IOException {
         int count = idToDatabase.size();
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/CatalogUtils.java b/fe/fe-core/src/main/java/com/starrocks/catalog/CatalogUtils.java
index bbfde75f96b9dd..14d5194d64e452 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/CatalogUtils.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/CatalogUtils.java
@@ -57,7 +57,7 @@ public static String normalizeTableName(String dbName, String tableName) {
 
     // check table exist
     public static void checkTableExist(Database db, String tableName) throws DdlException {
-        Table table = db.getTable(tableName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         if (table == null) {
             ErrorReport.reportDdlException(ErrorCode.ERR_BAD_TABLE_ERROR, tableName);
         }
@@ -115,12 +115,12 @@ public static Set<String> getPartitionNamesFromAddPartitionClause(AddPartitionCl
 
     // Used to temporarily disable some command on lake table and remove later.
     public static void checkIsLakeTable(String dbName, String tableName) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             return;
         }
 
-        Table table = db.getTable(tableName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         if (table == null) {
             return;
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/ColocateTableIndex.java b/fe/fe-core/src/main/java/com/starrocks/catalog/ColocateTableIndex.java
index 9e5eaa6e986844..5d4956060c7809 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/ColocateTableIndex.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/ColocateTableIndex.java
@@ -492,14 +492,15 @@ public List<Long> getAllTableIds(GroupId groupId) {
 
     public int getNumOfTabletsPerBucket(GroupId groupId) {
         List<Long> allTableIds = getAllTableIds(groupId);
-        Database db = GlobalStateMgr.getCurrentState().getDb(groupId.dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(groupId.dbId);
         int numOfTablets = 0;
         if (db != null && !allTableIds.isEmpty()) {
             Locker locker = new Locker();
             try {
                 locker.lockDatabase(db, LockType.READ);
                 for (long tableId : allTableIds) {
-                    OlapTable tbl = (OlapTable) db.getTable(tableId);
+                    OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                .getTable(db.getId(), tableId);
                     if (tbl != null) {
                         numOfTablets += tbl.getNumberOfPartitions();
                     }
@@ -608,9 +609,9 @@ public GroupId changeGroup(long dbId, OlapTable tbl, String oldGroup, String new
     }
 
     public void replayAddTableToGroup(ColocatePersistInfo info) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(info.getGroupId().dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(info.getGroupId().dbId);
         Preconditions.checkNotNull(db);
-        OlapTable tbl = (OlapTable) db.getTable(info.getTableId());
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), info.getTableId());
         Preconditions.checkNotNull(tbl);
 
         writeLock();
@@ -661,11 +662,11 @@ public void clear() {
 
     protected Optional<String> getTableName(long dbId, long tableId) {
 
-        Database database = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (database == null) {
             return Optional.empty();
         }
-        Table table = database.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), tableId);
 
         if (table == null) {
             return Optional.empty();
@@ -986,9 +987,9 @@ public void replayModifyTableColocate(TablePropertyInfo info) {
         long tableId = info.getTableId();
         Map<String, String> properties = info.getPropertyMap();
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(info.getGroupId().dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(info.getGroupId().dbId);
         try (AutoCloseableLock ignore = new AutoCloseableLock(new Locker(), db, Lists.newArrayList(tableId), LockType.WRITE)) {
-            OlapTable table = (OlapTable) db.getTable(tableId);
+            OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             modifyTableColocate(db, table, properties.get(PropertyAnalyzer.PROPERTIES_COLOCATE_WITH), true,
                     info.getGroupId());
         } catch (DdlException e) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/Column.java b/fe/fe-core/src/main/java/com/starrocks/catalog/Column.java
index a133561e07d1ef..d104357eb70c73 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/Column.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/Column.java
@@ -43,6 +43,7 @@
 import com.starrocks.analysis.SlotRef;
 import com.starrocks.analysis.StringLiteral;
 import com.starrocks.analysis.TypeDef;
+import com.starrocks.catalog.combinator.AggStateDesc;
 import com.starrocks.common.CaseSensibility;
 import com.starrocks.common.DdlException;
 import com.starrocks.common.io.Text;
@@ -57,6 +58,7 @@
 import com.starrocks.sql.analyzer.AstToSQLBuilder;
 import com.starrocks.sql.ast.ColumnDef;
 import com.starrocks.sql.ast.IndexDef;
+import com.starrocks.thrift.TAggStateDesc;
 import com.starrocks.thrift.TColumn;
 import org.apache.commons.lang.StringEscapeUtils;
 
@@ -103,6 +105,10 @@ public class Column implements Writable, GsonPreProcessable, GsonPostProcessable
     // column is not key and has aggregate type: aggregate type is name of aggregate function.
     @SerializedName(value = "aggregationType")
     private AggregateType aggregationType;
+    // aggStateDesc is used for common aggregate function state with intermediate result type in aggregate key model.
+    // if aggregationType is AGG_STATE_UNION, aggStateDesc should not be null.
+    @SerializedName("aggStateDesc")
+    protected AggStateDesc aggStateDesc = null;
 
     // if isAggregationTypeImplicit is true, the actual aggregation type will not be shown in show create table
     // the key type of table is duplicate or unique: the isAggregationTypeImplicit of value columns are true
@@ -146,23 +152,23 @@ public Column() {
     }
 
     public Column(String name, Type dataType) {
-        this(name, dataType, false, null, false, null, "", COLUMN_UNIQUE_ID_INIT_VALUE);
+        this(name, dataType, false, null, null, false, null, "", COLUMN_UNIQUE_ID_INIT_VALUE);
         Preconditions.checkArgument(dataType.isValid());
     }
 
     public Column(String name, Type dataType, boolean isAllowNull) {
-        this(name, dataType, false, null, isAllowNull, null, "", COLUMN_UNIQUE_ID_INIT_VALUE);
+        this(name, dataType, false, null, null, isAllowNull, null, "", COLUMN_UNIQUE_ID_INIT_VALUE);
         Preconditions.checkArgument(dataType.isValid());
     }
 
     public Column(String name, Type dataType, boolean isAllowNull, String comment) {
-        this(name, dataType, false, null, isAllowNull, null, comment, COLUMN_UNIQUE_ID_INIT_VALUE);
+        this(name, dataType, false, null, null, isAllowNull, null, comment, COLUMN_UNIQUE_ID_INIT_VALUE);
         Preconditions.checkArgument(dataType.isValid());
     }
 
     public Column(String name, Type type, boolean isKey, AggregateType aggregateType, String defaultValue,
                   String comment) {
-        this(name, type, isKey, aggregateType, false,
+        this(name, type, isKey, aggregateType, null, false,
                 new ColumnDef.DefaultValueDef(true, new StringLiteral(defaultValue)), comment,
                 COLUMN_UNIQUE_ID_INIT_VALUE);
     }
@@ -170,18 +176,18 @@ public Column(String name, Type type, boolean isKey, AggregateType aggregateType
     public Column(String name, Type type, boolean isKey, AggregateType aggregateType,
                   ColumnDef.DefaultValueDef defaultValue,
                   String comment) {
-        this(name, type, isKey, aggregateType, false, defaultValue, comment,
+        this(name, type, isKey, aggregateType, null, false, defaultValue, comment,
                 COLUMN_UNIQUE_ID_INIT_VALUE);
     }
 
     public Column(String name, Type type, boolean isKey, AggregateType aggregateType, boolean isAllowNull,
                   ColumnDef.DefaultValueDef defaultValueDef, String comment) {
-        this(name, type, isKey, aggregateType, isAllowNull, defaultValueDef, comment,
+        this(name, type, isKey, aggregateType, null, isAllowNull, defaultValueDef, comment,
                 COLUMN_UNIQUE_ID_INIT_VALUE);
     }
 
-    public Column(String name, Type type, boolean isKey, AggregateType aggregateType, boolean isAllowNull,
-                  ColumnDef.DefaultValueDef defaultValueDef, String comment, int columnUniqId) {
+    public Column(String name, Type type, boolean isKey, AggregateType aggregateType, AggStateDesc aggStateDesc,
+                  boolean isAllowNull, ColumnDef.DefaultValueDef defaultValueDef, String comment, int columnUniqId) {
         this.name = name;
         if (this.name == null) {
             this.name = "";
@@ -195,6 +201,11 @@ public Column(String name, Type type, boolean isKey, AggregateType aggregateType
                 this.type.getPrimitiveType() != PrimitiveType.INVALID_TYPE);
 
         this.aggregationType = aggregateType;
+        if (aggregateType != null && aggregateType == AggregateType.AGG_STATE_UNION) {
+            Preconditions.checkArgument(aggStateDesc != null, "aggStateDesc should not be null if " +
+                    "aggregation type is AGG_STATE_UNION");
+        }
+        this.aggStateDesc = aggStateDesc;
         this.isAggregationTypeImplicit = false;
         this.isKey = isKey;
         this.isAllowNull = isAllowNull;
@@ -263,7 +274,7 @@ public ColumnDef toColumnDef(Table table) {
                 defaultValueDef = new ColumnDef.DefaultValueDef(false, null);
             }
         }
-        return new ColumnDef(name, new TypeDef(type), null, isKey, aggregationType, isAllowNull,
+        return new ColumnDef(name, new TypeDef(type), null, isKey, aggregationType, aggStateDesc, isAllowNull,
                 defaultValueDef, isAutoIncrement,
                 generatedColumnExpr != null ? generatedColumnExpr.convertToColumnNameExpr(table.getIdToColumn()) : null,
                 comment);
@@ -416,6 +427,10 @@ public TColumn toThrift() {
         if (null != this.aggregationType) {
             tColumn.setAggregation_type(this.aggregationType.toThrift());
         }
+        if (null != this.aggStateDesc) {
+            TAggStateDesc tAggStateDesc = this.aggStateDesc.toThrift();
+            tColumn.setAgg_state_desc(tAggStateDesc);
+        }
         tColumn.setIs_key(this.isKey);
         tColumn.setIs_allow_null(this.isAllowNull);
         tColumn.setIs_auto_increment(this.isAutoIncrement);
@@ -448,6 +463,9 @@ public void checkSchemaChangeAllowed(Column other) throws DdlException {
         if (this.aggregationType != other.aggregationType) {
             throw new DdlException("Can not change aggregation type");
         }
+        if (this.aggStateDesc != null && this.aggStateDesc.equals(other.aggStateDesc)) {
+            throw new DdlException("Can not change aggregation state desc type");
+        }
 
         if (this.isAllowNull && !other.isAllowNull) {
             throw new DdlException("Can not change from nullable to non-nullable");
@@ -574,7 +592,11 @@ public String toSql(Map<ColumnId, Column> idToColumn) {
         String typeStr = type.toSql();
         sb.append(typeStr).append(" ");
         if (isAggregated() && !isAggregationTypeImplicit) {
-            sb.append(aggregationType.name()).append(" ");
+            if (aggregationType == AggregateType.AGG_STATE_UNION) {
+                sb.append(aggStateDesc.toSql()).append(" ");
+            } else {
+                sb.append(aggregationType.name()).append(" ");
+            }
         }
         if (isAllowNull) {
             sb.append("NULL ");
@@ -874,4 +896,8 @@ public void setIndexFlag(TColumn tColumn, List<Index> indexes, Set<ColumnId> bfC
             tColumn.setIs_bloom_filter_column(true);
         }
     }
+
+    public AggStateDesc getAggStateDesc() {
+        return this.aggStateDesc;
+    }
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/Database.java b/fe/fe-core/src/main/java/com/starrocks/catalog/Database.java
index b7e33a13536f07..3c014993468a36 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/Database.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/Database.java
@@ -72,7 +72,6 @@
 import java.util.List;
 import java.util.Map;
 import java.util.Map.Entry;
-import java.util.Optional;
 import java.util.Set;
 import java.util.concurrent.ConcurrentHashMap;
 import java.util.concurrent.ConcurrentMap;
@@ -317,7 +316,7 @@ public void dropTable(String tableName, boolean isSetIfExists, boolean isForce)
         Locker locker = new Locker();
         locker.lockDatabase(this, LockType.WRITE);
         try {
-            table = getTable(tableName);
+            table = nameToTable.get(tableName);
             if (table == null && isSetIfExists) {
                 return;
             }
@@ -352,7 +351,7 @@ public void dropTemporaryTable(long tableId, String tableName, boolean isSetIfEx
         Locker locker = new Locker();
         locker.lockDatabase(this, LockType.WRITE);
         try {
-            table = getTable(tableId);
+            table = idToTable.get(tableId);
             if (table == null) {
                 if (isSetIfExists) {
                     return;
@@ -469,22 +468,17 @@ public Set<String> getTableNamesViewWithLock() {
         }
     }
 
-    public Optional<Table> tryGetTable(String tableName) {
-        return Optional.ofNullable(nameToTable.get(tableName));
-    }
-
-    public Optional<Table> tryGetTable(long tableId) {
-        return Optional.ofNullable(idToTable.get(tableId));
+    /**
+     * This is a thread-safe method when idToTable is a concurrent hash map
+     */
+    public Table getTable(long tableId) {
+        return idToTable.get(tableId);
     }
 
     public Table getTable(String tableName) {
         return nameToTable.get(tableName);
     }
 
-    public Optional<Table> mayGetTable(String tableName) {
-        return Optional.ofNullable(nameToTable.get(tableName));
-    }
-
     public Pair<Table, MaterializedIndexMeta> getMaterializedViewIndex(String mvName) {
         // TODO: add an index to speed it up.
         for (Table table : idToTable.values()) {
@@ -504,17 +498,6 @@ public Pair<Table, MaterializedIndexMeta> getMaterializedViewIndex(String mvName
         return null;
     }
 
-    /**
-     * This is a thread-safe method when idToTable is a concurrent hash map
-     */
-    public Table getTable(long tableId) {
-        return idToTable.get(tableId);
-    }
-
-    public Optional<Table> mayGetTable(long tableId) {
-        return Optional.ofNullable(getTable(tableId));
-    }
-
     @Override
     public int getSignature(int signatureVersion) {
         Adler32 adler32 = new Adler32();
@@ -630,7 +613,7 @@ public synchronized void replayAddFunction(Function function) {
 
     public static void replayCreateFunctionLog(Function function) {
         String dbName = function.getFunctionName().getDb();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new Error("unknown database when replay log, db=" + dbName);
         }
@@ -666,7 +649,7 @@ public synchronized void replayDropFunction(FunctionSearchDesc functionSearchDes
 
     public static void replayDropFunctionLog(FunctionSearchDesc functionSearchDesc) {
         String dbName = functionSearchDesc.getName().getDb();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new Error("unknown database when replay log, db=" + dbName);
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/ForeignKeyConstraint.java b/fe/fe-core/src/main/java/com/starrocks/catalog/ForeignKeyConstraint.java
index 250955161308ce..b086982eb27d51 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/ForeignKeyConstraint.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/ForeignKeyConstraint.java
@@ -22,7 +22,7 @@
 import com.google.common.collect.Streams;
 import com.starrocks.common.Pair;
 import com.starrocks.server.GlobalStateMgr;
-import com.starrocks.sql.common.MetaUtils;
+import com.starrocks.sql.analyzer.SemanticException;
 import org.apache.commons.lang.math.NumberUtils;
 import org.apache.logging.log4j.LogManager;
 import org.apache.logging.log4j.Logger;
@@ -107,19 +107,37 @@ public List<Pair<String, String>> getColumnNameRefPairs(Table defaultChildTable)
 
     private Table getParentTable() {
         if (parentTableInfo.isInternalCatalog()) {
-            return MetaUtils.getTable(parentTableInfo.getDbId(), parentTableInfo.getTableId());
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(parentTableInfo.getDbId(), parentTableInfo.getTableId());
+            if (table == null) {
+                throw new SemanticException("Table %s is not found", parentTableInfo.getTableId());
+            }
+            return table;
         } else {
-            return MetaUtils.getTable(parentTableInfo.getCatalogName(), parentTableInfo.getDbName(),
-                    parentTableInfo.getTableName());
+            Table table = GlobalStateMgr.getCurrentState().getMetadataMgr()
+                    .getTable(parentTableInfo.getCatalogName(), parentTableInfo.getDbName(), parentTableInfo.getTableName());
+            if (table == null) {
+                throw new SemanticException("Table %s is not found", parentTableInfo.getTableName());
+            }
+            return table;
         }
     }
 
     private Table getChildTable() {
         if (childTableInfo.isInternalCatalog()) {
-            return MetaUtils.getTable(childTableInfo.getDbId(), childTableInfo.getTableId());
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(childTableInfo.getDbId(), childTableInfo.getTableId());
+            if (table == null) {
+                throw new SemanticException("Table %s is not found", childTableInfo.getTableId());
+            }
+            return table;
         } else {
-            return MetaUtils.getTable(childTableInfo.getCatalogName(), childTableInfo.getDbName(),
-                    childTableInfo.getTableName());
+            Table table = GlobalStateMgr.getCurrentState().getMetadataMgr()
+                    .getTable(childTableInfo.getCatalogName(), childTableInfo.getDbName(), childTableInfo.getTableName());
+            if (table == null) {
+                throw new SemanticException("Table %s is not found", childTableInfo.getTableName());
+            }
+            return table;
         }
     }
 
@@ -221,12 +239,12 @@ private static BaseTableInfo getTableBaseInfo(String catalogName, String db, Str
                     "BaseTableInfo table %s should be tableId for internal catalog", table);
             long dbId = Long.parseLong(db);
             long tableId = Long.parseLong(table);
-            Database database = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (database == null) {
                 throw new IllegalArgumentException(String.format("BaseInfo's db %s should not be null in the foreign key " +
                         "constraint, please drop foreign key constraints and retry", dbId));
             }
-            Table baseTable = database.getTable(tableId);
+            Table baseTable = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), tableId);
             if (baseTable == null) {
                 throw new IllegalArgumentException(String.format("BaseInfo' base table %s should not be null in the foreign kee" +
                                 " constraint, please drop foreign key constraints and retry",
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/Function.java b/fe/fe-core/src/main/java/com/starrocks/catalog/Function.java
index 1ff1d636f65023..ed132d4a5ed756 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/Function.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/Function.java
@@ -41,6 +41,7 @@
 import com.google.gson.annotations.SerializedName;
 import com.starrocks.analysis.Expr;
 import com.starrocks.analysis.FunctionName;
+import com.starrocks.catalog.combinator.AggStateDesc;
 import com.starrocks.common.Pair;
 import com.starrocks.common.io.Text;
 import com.starrocks.common.io.Writable;
@@ -137,6 +138,10 @@ public enum CompareMode {
     @SerializedName(value = "checksum")
     protected String checksum = "";
 
+    // aggStateDesc is used for combinator to generate the nested aggregated function.
+    @SerializedName(value = "aggStateDesc")
+    protected AggStateDesc aggStateDesc;
+
     // Function id, every function has a unique id. Now all built-in functions' id is 0
     private long id = 0;
     // User specified function name e.g. "Add"
@@ -229,6 +234,7 @@ public Function(Function other) {
         couldApplyDictOptimize = other.couldApplyDictOptimize;
         isNullable = other.isNullable;
         isMetaFunction = other.isMetaFunction;
+        aggStateDesc = other.aggStateDesc;
     }
 
     public FunctionName getFunctionName() {
@@ -422,6 +428,14 @@ public void setCouldApplyDictOptimize(boolean couldApplyDictOptimize) {
         this.couldApplyDictOptimize = couldApplyDictOptimize;
     }
 
+    public AggStateDesc getAggStateDesc() {
+        return aggStateDesc;
+    }
+
+    public void setAggStateDesc(AggStateDesc aggStateDesc) {
+        this.aggStateDesc = aggStateDesc;
+    }
+
     // Compares this to 'other' for mode.
     public boolean compare(Function other, CompareMode mode) {
         switch (mode) {
@@ -698,6 +712,9 @@ public TFunction toThrift() {
         if (!checksum.isEmpty()) {
             fn.setChecksum(checksum);
         }
+        if (aggStateDesc != null) {
+            fn.setAgg_state_desc(aggStateDesc.toThrift());
+        }
         fn.setCould_apply_dict_optimize(couldApplyDictOptimize);
         return fn;
     }
@@ -957,5 +974,4 @@ public Function updateArgType(Type[] newTypes) {
 
         return this;
     }
-
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/FunctionSet.java b/fe/fe-core/src/main/java/com/starrocks/catalog/FunctionSet.java
index 340e96c4dc510b..f46efbdcad4e29 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/FunctionSet.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/FunctionSet.java
@@ -284,6 +284,7 @@ public class FunctionSet {
     public static final String DISTINCT_PCSA = "distinct_pcsa";
     public static final String HISTOGRAM = "histogram";
     public static final String FLAT_JSON_META = "flat_json_meta";
+    public static final String MANN_WHITNEY_U_TEST = "mann_whitney_u_test";
 
     // Bitmap functions:
     public static final String BITMAP_AND = "bitmap_and";
@@ -1227,6 +1228,22 @@ private void initAggregateBuiltins() {
                     Lists.newArrayList(t, Type.INT, Type.DOUBLE), Type.VARCHAR, Type.VARCHAR,
                     false, false, false));
         }
+
+        // causal inference functions.
+        registerBuiltinHypothesisTestingFunctions();
+    }
+
+    private void registerBuiltinHypothesisTestingFunctions() {
+        // mann_whitney_u_test
+        addBuiltin(AggregateFunction.createBuiltin(MANN_WHITNEY_U_TEST,
+                Lists.newArrayList(Type.DOUBLE, Type.BOOLEAN, Type.VARCHAR, Type.BIGINT), Type.JSON,
+                Type.VARBINARY, false, false, false));
+        addBuiltin(AggregateFunction.createBuiltin(MANN_WHITNEY_U_TEST,
+                Lists.newArrayList(Type.DOUBLE, Type.BOOLEAN, Type.VARCHAR), Type.JSON,
+                Type.VARBINARY, false, false, false));
+        addBuiltin(AggregateFunction.createBuiltin(MANN_WHITNEY_U_TEST,
+                Lists.newArrayList(Type.DOUBLE, Type.BOOLEAN), Type.JSON,
+                Type.VARBINARY, false, false, false));
     }
 
     private void registerBuiltinSumAggFunction(String name) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/HiveTable.java b/fe/fe-core/src/main/java/com/starrocks/catalog/HiveTable.java
index fddedd3cc60968..acf233b1da8bc1 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/HiveTable.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/HiveTable.java
@@ -288,7 +288,7 @@ public void modifyTableSchema(String dbName, String tableName, HiveTable updated
         fullSchemaTemp.addAll(updatedTable.fullSchema);
         dataColumnNamesTemp.addAll(updatedTable.dataColumnNames);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new StarRocksConnectorException("Not found database " + dbName);
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/MaterializedView.java b/fe/fe-core/src/main/java/com/starrocks/catalog/MaterializedView.java
index 109f89527c2de8..7b125499539602 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/MaterializedView.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/MaterializedView.java
@@ -992,7 +992,7 @@ public void fixRelationship() {
      * @return active or not
      */
     private boolean onReloadImpl() {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             LOG.warn("db:{} do not exist. materialized view id:{} name:{} should not exist", dbId, id, name);
             setInactiveAndReason(MaterializedViewExceptions.inactiveReasonForDbNotExists(dbId));
@@ -1003,7 +1003,7 @@ private boolean onReloadImpl() {
             if (baseTableIds != null) {
                 // for compatibility
                 for (long tableId : baseTableIds) {
-                    Table table = db.getTable(tableId);
+                    Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
                     if (table == null) {
                         setInactiveAndReason(MaterializedViewExceptions.inactiveReasonForBaseTableNotExists(tableId));
                         return false;
@@ -1079,7 +1079,7 @@ private boolean onReloadImpl() {
     }
 
     private void analyzePartitionInfo() {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
 
         if (partitionInfo.isUnPartitioned()) {
             return;
@@ -1693,6 +1693,15 @@ public String getQueryRewriteStatus() {
     @Override
     public Map<String, String> getProperties() {
         Map<String, String> properties = super.getProperties();
+        return properties;
+    }
+
+    /**
+     * Get session properties from materialized view's table property.
+     * @return session properties that are ensured to be not null
+     */
+    public Map<String, String> getSessionProperties() {
+        Map<String, String> properties = Maps.newHashMap();
         // For materialized view, add into session variables into properties.
         if (super.getTableProperty() != null && super.getTableProperty().getProperties() != null) {
             for (Map.Entry<String, String> entry : super.getTableProperty().getProperties().entrySet()) {
@@ -1831,7 +1840,7 @@ public Status doAfterRestore(MvRestoreContext mvRestoreContext) throws DdlExcept
                     String.format("Materialized view %s's base info is not found", this.name));
         }
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             return new Status(Status.ErrCode.NOT_FOUND,
                     String.format("Materialized view %s's db %s is not found", this.name, this.dbId));
@@ -1980,7 +1989,7 @@ public void replayAlterMaterializedViewBaseTableInfos(AlterMaterializedViewBaseT
      */
     public synchronized ParseNode getDefineQueryParseNode() {
         if (this.defineQueryParseNode == null) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 return null;
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/MetadataViewer.java b/fe/fe-core/src/main/java/com/starrocks/catalog/MetadataViewer.java
index 659a1125815e6e..86293d2bf6a96d 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/MetadataViewer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/MetadataViewer.java
@@ -73,7 +73,7 @@ private static List<List<String>> getTabletStatus(String dbName, String tblName,
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
         SystemInfoService infoService = GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo();
 
-        Database db = globalStateMgr.getDb(dbName);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("Database " + dbName + " does not exsit");
         }
@@ -81,7 +81,7 @@ private static List<List<String>> getTabletStatus(String dbName, String tblName,
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            Table tbl = db.getTable(tblName);
+            Table tbl = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tblName);
             if (tbl == null || tbl.getType() != TableType.OLAP) {
                 throw new DdlException("Table does not exist or is not OLAP table: " + tblName);
             }
@@ -202,7 +202,7 @@ private static List<List<String>> getTabletDistribution(String dbName, String tb
         List<List<String>> result = Lists.newArrayList();
 
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
-        Database db = globalStateMgr.getDb(dbName);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("Database " + dbName + " does not exsit");
         }
@@ -210,7 +210,7 @@ private static List<List<String>> getTabletDistribution(String dbName, String tb
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            Table tbl = db.getTable(tblName);
+            Table tbl = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tblName);
             if (tbl == null || !tbl.isNativeTableOrMaterializedView()) {
                 throw new DdlException("Table does not exist or is not native table: " + tblName);
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/OlapTable.java b/fe/fe-core/src/main/java/com/starrocks/catalog/OlapTable.java
index cfa050c585455e..985f81adea8c9b 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/OlapTable.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/OlapTable.java
@@ -1016,11 +1016,11 @@ public Status doAfterRestore(MvRestoreContext mvRestoreContext) throws DdlExcept
             if (localMvId == null) {
                 continue;
             }
-            Database mvDb = GlobalStateMgr.getCurrentState().getDb(localMvId.getDbId());
+            Database mvDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(localMvId.getDbId());
             if (mvDb == null) {
                 continue;
             }
-            Table mvTable = mvDb.getTable(localMvId.getId());
+            Table mvTable = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(mvDb.getId(), localMvId.getId());
             if (mvTable == null) {
                 continue;
             }
@@ -2105,6 +2105,15 @@ protected OlapTable selectiveCopyInternal(OlapTable copied, Collection<String> r
     public Partition replacePartition(Partition newPartition) {
         Partition oldPartition = nameToPartition.remove(newPartition.getName());
 
+        // For cloud native table, add partition into recycle Bin after truncate table.
+        // It is no necessary for share nothing mode because file will be deleted throught
+        // tablet report in this case.
+        if (this.isCloudNativeTableOrMaterializedView()) {
+            RecyclePartitionInfo recyclePartitionInfo = buildRecyclePartitionInfo(-1, oldPartition);
+            recyclePartitionInfo.setRecoverable(false);
+            GlobalStateMgr.getCurrentState().getRecycleBin().recyclePartition(recyclePartitionInfo);
+        }
+
         oldPartition.getSubPartitions().forEach(physicalPartition -> {
             physicalPartitionIdToPartitionId.remove(physicalPartition.getId());
             physicalPartitionNameToPartitionId.remove(physicalPartition.getName());
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/ResourceGroup.java b/fe/fe-core/src/main/java/com/starrocks/catalog/ResourceGroup.java
index ec15292a92902e..a1214cd6a9eac3 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/ResourceGroup.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/ResourceGroup.java
@@ -14,15 +14,18 @@
 
 package com.starrocks.catalog;
 
+import com.google.common.collect.ImmutableList;
 import com.google.gson.annotations.SerializedName;
 import com.starrocks.qe.ShowResultSetMetaData;
+import com.starrocks.sql.analyzer.SemanticException;
 import com.starrocks.thrift.TWorkGroup;
 import com.starrocks.thrift.TWorkGroupType;
 
-import java.util.ArrayList;
+import java.text.DecimalFormat;
 import java.util.Collections;
 import java.util.List;
 import java.util.Objects;
+import java.util.function.BiFunction;
 import java.util.stream.Collectors;
 
 public class ResourceGroup {
@@ -35,6 +38,8 @@ public class ResourceGroup {
     public static final String PLAN_CPU_COST_RANGE = "plan_cpu_cost_range";
     public static final String PLAN_MEM_COST_RANGE = "plan_mem_cost_range";
     public static final String CPU_CORE_LIMIT = "cpu_core_limit";
+    public static final String CPU_WEIGHT = "cpu_weight";
+    public static final String DEDICATED_CPU_CORES = "dedicated_cpu_cores";
     public static final String MAX_CPU_CORES = "max_cpu_cores";
     public static final String MEM_LIMIT = "mem_limit";
     public static final String BIG_QUERY_MEM_LIMIT = "big_query_mem_limit";
@@ -61,29 +66,92 @@ public class ResourceGroup {
         DEFAULT_MV_WG.setName(DEFAULT_MV_RESOURCE_GROUP_NAME);
     }
 
-    public static final ShowResultSetMetaData META_DATA =
-            ShowResultSetMetaData.builder()
-                    .addColumn(new Column("name", ScalarType.createVarchar(100)))
-                    .addColumn(new Column("id", ScalarType.createVarchar(200)))
-                    .addColumn(new Column("cpu_core_limit", ScalarType.createVarchar(200)))
-                    .addColumn(new Column("mem_limit", ScalarType.createVarchar(200)))
-                    .addColumn(new Column(MAX_CPU_CORES, ScalarType.createVarchar(200)))
-                    .addColumn(new Column("big_query_cpu_second_limit", ScalarType.createVarchar(200)))
-                    .addColumn(new Column("big_query_scan_rows_limit", ScalarType.createVarchar(200)))
-                    .addColumn(new Column("big_query_mem_limit", ScalarType.createVarchar(200)))
-                    .addColumn(new Column("concurrency_limit", ScalarType.createVarchar(200)))
-                    .addColumn(new Column("spill_mem_limit_threshold", ScalarType.createVarchar(200)))
-                    .addColumn(new Column("type", ScalarType.createVarchar(200)))
-                    .addColumn(new Column("classifiers", ScalarType.createVarchar(1024)))
-                    .build();
+    private static class ColumnMeta {
+        public ColumnMeta(Column column, BiFunction<ResourceGroup, ResourceGroupClassifier, String> valueSupplier) {
+            this(column, valueSupplier, true);
+        }
+
+        public ColumnMeta(Column column, BiFunction<ResourceGroup, ResourceGroupClassifier, String> valueSupplier,
+                          boolean visible) {
+            this.column = column;
+            this.valueSupplier = valueSupplier;
+            this.visible = visible;
+        }
+
+        private final Column column;
+        private final BiFunction<ResourceGroup, ResourceGroupClassifier, String> valueSupplier;
+        private final boolean visible;
+    }
+
+    private static final List<ColumnMeta> COLUMN_METAS = ImmutableList.of(
+            new ColumnMeta(
+                    new Column("name", ScalarType.createVarchar(100)),
+                    (rg, classifier) -> rg.getName()),
+            new ColumnMeta(
+                    new Column("id", ScalarType.createVarchar(200)),
+                    (rg, classifier) -> "" + rg.getId()),
+            new ColumnMeta(
+                    new Column(CPU_WEIGHT, ScalarType.createVarchar(200)),
+                    (rg, classifier) -> "" + rg.getCpuWeight()),
+            new ColumnMeta(
+                    new Column(DEDICATED_CPU_CORES, ScalarType.createVarchar(200)),
+                    (rg, classifier) -> "" + rg.getNormalizedDedicatedCpuCores()),
+            new ColumnMeta(
+                    new Column(MEM_LIMIT, ScalarType.createVarchar(200)),
+                    (rg, classifier) -> (rg.getMemLimit() * 100) + "%"),
+            new ColumnMeta(
+                    new Column(MAX_CPU_CORES, ScalarType.createVarchar(200)),
+                    (rg, classifier) -> "" + rg.getMaxCpuCores(), false),
+            new ColumnMeta(
+                    new Column(BIG_QUERY_CPU_SECOND_LIMIT, ScalarType.createVarchar(200)),
+                    (rg, classifier) -> "" + Objects.requireNonNullElse(rg.getBigQueryCpuSecondLimit(), 0)),
+            new ColumnMeta(
+                    new Column(BIG_QUERY_SCAN_ROWS_LIMIT, ScalarType.createVarchar(200)),
+                    (rg, classifier) -> "" + Objects.requireNonNullElse(rg.getBigQueryScanRowsLimit(), 0)),
+            new ColumnMeta(
+                    new Column(BIG_QUERY_MEM_LIMIT, ScalarType.createVarchar(200)),
+                    (rg, classifier) -> "" + Objects.requireNonNullElse(rg.getBigQueryMemLimit(), 0)),
+            new ColumnMeta(
+                    new Column(CONCURRENCY_LIMIT, ScalarType.createVarchar(200)),
+                    (rg, classifier) -> "" + rg.getConcurrencyLimit()),
+            new ColumnMeta(
+                    new Column(SPILL_MEM_LIMIT_THRESHOLD, ScalarType.createVarchar(200)),
+                    (rg, classifier) -> new DecimalFormat("#.##").format(
+                            Objects.requireNonNullElse(rg.getSpillMemLimitThreshold(), 1.0) * 100) + "%"),
+            new ColumnMeta(
+                    new Column(GROUP_TYPE, ScalarType.createVarchar(200)),
+                    (rg, classifier) -> rg.getResourceGroupType().name().substring("WG_".length()), false),
+            new ColumnMeta(
+                    new Column("classifiers", ScalarType.createVarchar(1024)),
+                    (rg, classifier) -> classifier.toString())
+    );
+
+    public static final ShowResultSetMetaData META_DATA;
+    public static final ShowResultSetMetaData VERBOSE_META_DATA;
+
+    static {
+        ShowResultSetMetaData.Builder builder = ShowResultSetMetaData.builder();
+        COLUMN_METAS.stream()
+                .filter(meta -> meta.visible)
+                .forEach(item -> builder.addColumn(item.column));
+        META_DATA = builder.build();
+
+        ShowResultSetMetaData.Builder verboseBuilder = ShowResultSetMetaData.builder();
+        COLUMN_METAS.forEach(item -> verboseBuilder.addColumn(item.column));
+        VERBOSE_META_DATA = verboseBuilder.build();
+    }
+
     @SerializedName(value = "classifiers")
     List<ResourceGroupClassifier> classifiers;
     @SerializedName(value = "name")
     private String name;
     @SerializedName(value = "id")
     private long id;
+
     @SerializedName(value = "cpuCoreLimit")
-    private Integer cpuCoreLimit;
+    private Integer cpuWeight;
+    @SerializedName(value = "dedicatedCpuCores")
+    private Integer dedicatedCpuCores;
 
     @SerializedName(value = "maxCpuCores")
     private Integer maxCpuCores;
@@ -108,42 +176,18 @@ public class ResourceGroup {
     public ResourceGroup() {
     }
 
-    private List<String> showClassifier(ResourceGroupClassifier classifier) {
-        List<String> row = new ArrayList<>();
-        row.add(this.name);
-        row.add("" + this.id);
-        row.add("" + cpuCoreLimit);
-        row.add("" + (memLimit * 100) + "%");
-        row.add("" + maxCpuCores);
-        if (bigQueryCpuSecondLimit != null) {
-            row.add("" + bigQueryCpuSecondLimit);
-        } else {
-            row.add("" + 0);
-        }
-        if (bigQueryScanRowsLimit != null) {
-            row.add("" + bigQueryScanRowsLimit);
-        } else {
-            row.add("" + 0);
-        }
-        if (bigQueryMemLimit != null) {
-            row.add("" + bigQueryMemLimit);
-        } else {
-            row.add("" + 0);
-        }
-        row.add("" + concurrencyLimit);
-        if (spillMemLimitThreshold != null) {
-            row.add("" + (spillMemLimitThreshold * 100) + "%");
-        } else {
-            row.add("" + "100%");
-        }
-        row.add("" + resourceGroupType.name().substring("WG_".length()));
-        row.add(classifier.toString());
-        return row;
+    private List<String> showClassifier(ResourceGroupClassifier classifier, boolean verbose) {
+        return COLUMN_METAS.stream()
+                .filter(meta -> verbose || meta.visible)
+                .map(meta -> meta.valueSupplier.apply(this, classifier))
+                .collect(Collectors.toList());
     }
 
-    public List<List<String>> showVisible(String user, List<String> activeRoles, String ip) {
-        return classifiers.stream().filter(c -> c.isVisible(user, activeRoles, ip))
-                .map(this::showClassifier).collect(Collectors.toList());
+    public List<List<String>> showVisible(String user, List<String> activeRoles, String ip, boolean verbose) {
+        return classifiers.stream()
+                .filter(c -> c.isVisible(user, activeRoles, ip))
+                .map(c -> showClassifier(c, verbose))
+                .collect(Collectors.toList());
     }
 
     public long getVersion() {
@@ -154,11 +198,13 @@ public void setVersion(long version) {
         this.version = version;
     }
 
-    public List<List<String>> show() {
+    public List<List<String>> show(boolean verbose) {
         if (classifiers.isEmpty()) {
-            return Collections.singletonList(showClassifier(new ResourceGroupClassifier()));
+            return Collections.singletonList(showClassifier(new ResourceGroupClassifier(), verbose));
         }
-        return classifiers.stream().map(this::showClassifier).collect(Collectors.toList());
+        return classifiers.stream()
+                .map(c -> showClassifier(c, verbose))
+                .collect(Collectors.toList());
     }
 
     public String getName() {
@@ -181,8 +227,8 @@ public TWorkGroup toThrift() {
         TWorkGroup twg = new TWorkGroup();
         twg.setName(name);
         twg.setId(id);
-        if (cpuCoreLimit != null) {
-            twg.setCpu_core_limit(cpuCoreLimit);
+        if (cpuWeight != null) {
+            twg.setCpu_core_limit(cpuWeight);
         }
         if (memLimit != null) {
             twg.setMem_limit(memLimit);
@@ -214,16 +260,39 @@ public TWorkGroup toThrift() {
         if (resourceGroupType != null) {
             twg.setWorkgroup_type(resourceGroupType);
         }
+
+        twg.setDedicated_cpu_cores(getNormalizedDedicatedCpuCores());
+
         twg.setVersion(version);
         return twg;
     }
 
-    public Integer getCpuCoreLimit() {
-        return cpuCoreLimit;
+    public Integer getCpuWeight() {
+        return cpuWeight;
+    }
+
+    public void setCpuWeight(int cpuWeight) {
+        this.cpuWeight = cpuWeight;
+    }
+
+    public Integer getDedicatedCpuCores() {
+        return dedicatedCpuCores;
     }
 
-    public void setCpuCoreLimit(int cpuCoreLimit) {
-        this.cpuCoreLimit = cpuCoreLimit;
+    public int getNormalizedDedicatedCpuCores() {
+        if (dedicatedCpuCores != null && dedicatedCpuCores > 0) {
+            return dedicatedCpuCores;
+        }
+        // For compatibility, resource group of deprecated type `short_query` uses `cpu_weight` (the original `cpu_core_limit`)
+        // as the reserved cores.
+        if (resourceGroupType == TWorkGroupType.WG_SHORT_QUERY && cpuWeight != null && cpuWeight > 0) {
+            return cpuWeight;
+        }
+        return 0;
+    }
+
+    public void setDedicatedCpuCores(Integer dedicatedCpuCores) {
+        this.dedicatedCpuCores = dedicatedCpuCores;
     }
 
     public boolean isMaxCpuCoresEffective() {
@@ -323,4 +392,16 @@ public int hashCode() {
         return Objects.hash(id, version);
     }
 
+    public static void validateCpuParameters(Integer cpuWeight, Integer dedicatedCpuCores) {
+        if ((cpuWeight == null || cpuWeight <= 0) && (dedicatedCpuCores == null || dedicatedCpuCores <= 0)) {
+            throw new SemanticException(String.format("property '%s' or '%s' must be positive",
+                    ResourceGroup.CPU_WEIGHT, ResourceGroup.DEDICATED_CPU_CORES));
+        }
+        if ((cpuWeight != null && cpuWeight > 0) && (dedicatedCpuCores != null && dedicatedCpuCores > 0)) {
+            throw new SemanticException(
+                    String.format("property '%s' and '%s' cannot be present and positive at the same time",
+                            ResourceGroup.CPU_WEIGHT, ResourceGroup.DEDICATED_CPU_CORES));
+        }
+    }
+
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/ResourceGroupClassifier.java b/fe/fe-core/src/main/java/com/starrocks/catalog/ResourceGroupClassifier.java
index 19e7f84612c81f..dc43505256addb 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/ResourceGroupClassifier.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/ResourceGroupClassifier.java
@@ -209,7 +209,7 @@ public String toString() {
         if (CollectionUtils.isNotEmpty(databaseIds)) {
             String str = databaseIds.stream()
                     .map(id ->
-                            Optional.ofNullable(GlobalStateMgr.getCurrentState().getDb(id))
+                            Optional.ofNullable(GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(id))
                                     .map(Database::getFullName)
                                     .orElse("unknown"))
                     .collect(Collectors.joining(","));
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/ResourceGroupMgr.java b/fe/fe-core/src/main/java/com/starrocks/catalog/ResourceGroupMgr.java
index 7c69f8fe15fb2e..5ade93d4357d8f 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/ResourceGroupMgr.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/ResourceGroupMgr.java
@@ -35,10 +35,12 @@
 import com.starrocks.privilege.RolePrivilegeCollectionV2;
 import com.starrocks.qe.ConnectContext;
 import com.starrocks.server.GlobalStateMgr;
+import com.starrocks.sql.analyzer.SemanticException;
 import com.starrocks.sql.ast.AlterResourceGroupStmt;
 import com.starrocks.sql.ast.CreateResourceGroupStmt;
 import com.starrocks.sql.ast.DropResourceGroupStmt;
 import com.starrocks.sql.ast.ShowResourceGroupStmt;
+import com.starrocks.system.BackendResourceStat;
 import com.starrocks.thrift.TWorkGroup;
 import com.starrocks.thrift.TWorkGroupOp;
 import com.starrocks.thrift.TWorkGroupOpType;
@@ -64,6 +66,13 @@
 // WorkGroupMgr is employed by GlobalStateMgr to manage WorkGroup in FE.
 public class ResourceGroupMgr implements Writable {
     private static final Logger LOG = LogManager.getLogger(ResourceGroupMgr.class);
+
+    private static final String EXCEED_TOTAL_DEDICATED_CPU_CORES_ERR_MSG =
+            "the sum of %s of all the resource groups cannot exceed %d";
+    public static final String SHORT_QUERY_SET_DEDICATED_CPU_CORES_ERR_MSG =
+            "'short_query' ResourceGroup cannot set 'dedicated_cpu_cores', " +
+                    "since it use 'cpu_weight' as 'dedicated_cpu_cores'";
+
     private final Map<String, ResourceGroup> resourceGroupMap = new HashMap<>();
 
     // Record the current short_query resource group.
@@ -76,6 +85,7 @@ public class ResourceGroupMgr implements Writable {
     private final Map<Long, Map<Long, TWorkGroup>> activeResourceGroupsPerBe = new HashMap<>();
     private final Map<Long, Long> minVersionPerBe = new HashMap<>();
     private final ReentrantReadWriteLock lock = new ReentrantReadWriteLock();
+    private int sumDedicatedCpuCores = 0;
 
     private void readLock() {
         lock.readLock().lock();
@@ -124,6 +134,13 @@ public void createResourceGroup(CreateResourceGroupStmt stmt) throws DdlExceptio
                 throw new DdlException("This type Resource Group need define classifiers.");
             }
 
+            if (wg.getNormalizedDedicatedCpuCores() > 0 && sumDedicatedCpuCores + wg.getNormalizedDedicatedCpuCores() >=
+                    BackendResourceStat.getInstance().getAvgNumHardwareCoresOfBe()) {
+                throw new DdlException(String.format(EXCEED_TOTAL_DEDICATED_CPU_CORES_ERR_MSG,
+                        ResourceGroup.DEDICATED_CPU_CORES,
+                        BackendResourceStat.getInstance().getAvgNumHardwareCoresOfBe() - 1));
+            }
+
             wg.setId(GlobalStateMgr.getCurrentState().getNextId());
             wg.setVersion(wg.getId());
             for (ResourceGroupClassifier classifier : wg.getClassifiers()) {
@@ -147,10 +164,11 @@ public List<List<String>> showResourceGroup(ShowResourceGroupStmt stmt) {
 
         List<List<String>> rows;
         if (stmt.getName() != null) {
-            rows = GlobalStateMgr.getCurrentState().getResourceGroupMgr().showOneResourceGroup(stmt.getName());
+            rows = GlobalStateMgr.getCurrentState().getResourceGroupMgr().showOneResourceGroup(
+                    stmt.getName(), stmt.isVerbose());
         } else {
             rows = GlobalStateMgr.getCurrentState().getResourceGroupMgr()
-                    .showAllResourceGroups(ConnectContext.get(), stmt.isListAll());
+                    .showAllResourceGroups(ConnectContext.get(), stmt.isVerbose(), stmt.isListAll());
         }
         return rows;
     }
@@ -200,33 +218,37 @@ private List<String> getUnqualifiedRole(ConnectContext ctx) {
         }
     }
 
-    public List<List<String>> showAllResourceGroups(ConnectContext ctx, Boolean isListAll) {
+    public List<List<String>> showAllResourceGroups(ConnectContext ctx, boolean verbose, boolean isListAll) {
         readLock();
         try {
             List<ResourceGroup> resourceGroupList = new ArrayList<>(resourceGroupMap.values());
             if (isListAll || ConnectContext.get() == null) {
                 resourceGroupList.sort(Comparator.comparing(ResourceGroup::getName));
-                return resourceGroupList.stream().map(ResourceGroup::show)
-                        .flatMap(Collection::stream).collect(Collectors.toList());
+                return resourceGroupList.stream()
+                        .map(rg -> rg.show(verbose))
+                        .flatMap(Collection::stream)
+                        .collect(Collectors.toList());
             } else {
                 String user = getUnqualifiedUser(ctx);
                 List<String> activeRoles = getUnqualifiedRole(ctx);
                 String remoteIp = ctx.getRemoteIP();
-                return resourceGroupList.stream().map(rg -> rg.showVisible(user, activeRoles, remoteIp))
-                        .flatMap(Collection::stream).collect(Collectors.toList());
+                return resourceGroupList.stream()
+                        .map(rg -> rg.showVisible(user, activeRoles, remoteIp, verbose))
+                        .flatMap(Collection::stream)
+                        .collect(Collectors.toList());
             }
         } finally {
             readUnlock();
         }
     }
 
-    public List<List<String>> showOneResourceGroup(String name) {
+    public List<List<String>> showOneResourceGroup(String name, boolean verbose) {
         readLock();
         try {
             if (!resourceGroupMap.containsKey(name)) {
                 return Collections.emptyList();
             } else {
-                return resourceGroupMap.get(name).show();
+                return resourceGroupMap.get(name).show(verbose);
             }
         } finally {
             readUnlock();
@@ -272,11 +294,7 @@ private void replayAddResourceGroup(ResourceGroup workgroup) {
     public ResourceGroup getResourceGroup(String name) {
         readLock();
         try {
-            if (resourceGroupMap.containsKey(name)) {
-                return resourceGroupMap.get(name);
-            } else {
-                return null;
-            }
+            return resourceGroupMap.getOrDefault(name, null);
         } finally {
             readUnlock();
         }
@@ -331,10 +349,41 @@ public void alterResourceGroup(AlterResourceGroupStmt stmt) throws DdlException
                 wg.getClassifiers().addAll(newAddedClassifiers);
             } else if (cmd instanceof AlterResourceGroupStmt.AlterProperties) {
                 ResourceGroup changedProperties = stmt.getChangedProperties();
-                Integer cpuCoreLimit = changedProperties.getCpuCoreLimit();
-                if (cpuCoreLimit != null) {
-                    wg.setCpuCoreLimit(cpuCoreLimit);
+
+                Integer cpuWeight = changedProperties.getCpuWeight();
+                if (cpuWeight == null) {
+                    cpuWeight = wg.getCpuWeight();
+                }
+                Integer dedicatedCpuCores = changedProperties.getDedicatedCpuCores();
+                if (dedicatedCpuCores == null) {
+                    dedicatedCpuCores = wg.getDedicatedCpuCores();
                 }
+
+                ResourceGroup.validateCpuParameters(cpuWeight, dedicatedCpuCores);
+
+                if (dedicatedCpuCores != null && dedicatedCpuCores > 0) {
+                    if (sumDedicatedCpuCores + dedicatedCpuCores - wg.getNormalizedDedicatedCpuCores() >=
+                            BackendResourceStat.getInstance().getAvgNumHardwareCoresOfBe()) {
+                        throw new DdlException(String.format(EXCEED_TOTAL_DEDICATED_CPU_CORES_ERR_MSG,
+                                ResourceGroup.DEDICATED_CPU_CORES,
+                                BackendResourceStat.getInstance().getAvgNumHardwareCoresOfBe() - 1));
+                    }
+                    if (wg.getResourceGroupType() == TWorkGroupType.WG_SHORT_QUERY) {
+                        throw new SemanticException(SHORT_QUERY_SET_DEDICATED_CPU_CORES_ERR_MSG);
+                    }
+                }
+                // NOTE that validate cpu parameters should be called before setting properties.
+
+                if (cpuWeight != null) {
+                    wg.setCpuWeight(cpuWeight);
+                }
+
+                if (dedicatedCpuCores != null) {
+                    sumDedicatedCpuCores -= wg.getNormalizedDedicatedCpuCores();
+                    wg.setDedicatedCpuCores(dedicatedCpuCores);
+                    sumDedicatedCpuCores += wg.getNormalizedDedicatedCpuCores();
+                }
+
                 Integer maxCpuCores = changedProperties.getMaxCpuCores();
                 if (maxCpuCores != null) {
                     wg.setMaxCpuCores(maxCpuCores);
@@ -457,6 +506,7 @@ private void removeResourceGroupInternal(String name) {
         if (wg.getResourceGroupType() == TWorkGroupType.WG_SHORT_QUERY) {
             shortQueryResourceGroup = null;
         }
+        sumDedicatedCpuCores -= wg.getNormalizedDedicatedCpuCores();
     }
 
     private void addResourceGroupInternal(ResourceGroup wg) {
@@ -468,6 +518,7 @@ private void addResourceGroupInternal(ResourceGroup wg) {
         if (wg.getResourceGroupType() == TWorkGroupType.WG_SHORT_QUERY) {
             shortQueryResourceGroup = wg;
         }
+        sumDedicatedCpuCores += wg.getNormalizedDedicatedCpuCores();
     }
 
     public List<TWorkGroupOp> getResourceGroupsNeedToDeliver(Long beId) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/StructField.java b/fe/fe-core/src/main/java/com/starrocks/catalog/StructField.java
index 2a509384985c34..1658f2c7af74da 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/StructField.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/StructField.java
@@ -73,6 +73,10 @@ public int getPosition() {
         return position;
     }
 
+    public int getFieldId() {
+        return fieldId;
+    }
+
     public void setPosition(int position) {
         this.position = position;
     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/TableFunctionTable.java b/fe/fe-core/src/main/java/com/starrocks/catalog/TableFunctionTable.java
index f27e86b680f4a7..9c444c9f2e949a 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/TableFunctionTable.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/TableFunctionTable.java
@@ -39,6 +39,7 @@
 import com.starrocks.server.RunMode;
 import com.starrocks.sql.analyzer.SemanticException;
 import com.starrocks.sql.ast.ImportColumnDesc;
+import com.starrocks.sql.ast.LoadStmt;
 import com.starrocks.system.ComputeNode;
 import com.starrocks.thrift.TBrokerFileStatus;
 import com.starrocks.thrift.TBrokerRangeDesc;
@@ -99,6 +100,7 @@ public class TableFunctionTable extends Table {
     public static final String PROPERTY_PARTITION_BY = "partition_by";
 
     public static final String PROPERTY_COLUMNS_FROM_PATH = "columns_from_path";
+    private static final String PROPERTY_STRICT_MODE = LoadStmt.STRICT_MODE;
 
     public static final String PROPERTY_AUTO_DETECT_SAMPLE_FILES = "auto_detect_sample_files";
     public static final String PROPERTY_AUTO_DETECT_SAMPLE_ROWS = "auto_detect_sample_rows";
@@ -119,6 +121,7 @@ public class TableFunctionTable extends Table {
     private int autoDetectSampleRows;
 
     private List<String> columnsFromPath = new ArrayList<>();
+    private boolean strictMode = false;
     private final Map<String, String> properties;
 
     private Optional<List<Integer>> partitionColumnIDs = Optional.empty();
@@ -250,6 +253,10 @@ private void parseProperties() throws DdlException {
             }
         }
 
+        if (properties.containsKey(PROPERTY_STRICT_MODE)) {
+            strictMode = Boolean.parseBoolean(properties.get(PROPERTY_STRICT_MODE));
+        }
+
         if (!properties.containsKey(PROPERTY_AUTO_DETECT_SAMPLE_FILES)) {
             autoDetectSampleFiles = DEFAULT_AUTO_DETECT_SAMPLE_FILES;
         } else {
@@ -487,6 +494,10 @@ public List<String> getColumnsFromPath() {
         return columnsFromPath;
     }
 
+    public boolean isStrictMode() {
+        return strictMode;
+    }
+
     @Override
     public String toString() {
         return String.format("TABLE('path'='%s', 'format'='%s')", path, format);
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/TabletInvertedIndex.java b/fe/fe-core/src/main/java/com/starrocks/catalog/TabletInvertedIndex.java
index 0fcb769d8562bb..78bd25a9f1e198 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/TabletInvertedIndex.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/TabletInvertedIndex.java
@@ -394,7 +394,8 @@ public void checkTabletMetaConsistency(Map<Long, Integer> creatingTableIds) {
                     if (creatingTableIds.containsKey(tableId)) {
                         continue;
                     }
-                    com.starrocks.catalog.Table table = db.getTable(tableId);
+                    com.starrocks.catalog.Table table = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                .getTable(db.getId(), tableId);
                     if (table == null) {
                         table = recycleBin.getTable(dbId, tableId);
                         if (table != null) {
@@ -544,10 +545,11 @@ private boolean isRestoreReplica(Replica replica, Map<Long, Long> replicaToTable
             long dbId = tabletMeta.getDbId();
             long tableId = tabletMeta.getTableId();
 
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db != null) {
                 // getTable is thread-safe for caller, lock free
-                com.starrocks.catalog.Table tbl = db.getTable(tableId);
+                com.starrocks.catalog.Table tbl = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(db.getId(), tableId);
                 if (tbl != null && tbl instanceof OlapTable) {
                     OlapTable olapTable = (OlapTable) tbl;
                     if (olapTable.getState() == OlapTable.OlapTableState.RESTORE) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/TabletStatMgr.java b/fe/fe-core/src/main/java/com/starrocks/catalog/TabletStatMgr.java
index 2f7f4f7f7fc11f..16057bb879d9f1 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/TabletStatMgr.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/TabletStatMgr.java
@@ -102,14 +102,14 @@ protected void runAfterCatalogReady() {
         long start = System.currentTimeMillis();
         List<Long> dbIds = GlobalStateMgr.getCurrentState().getLocalMetastore().getDbIds();
         for (Long dbId : dbIds) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 continue;
             }
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.WRITE);
             try {
-                for (Table table : db.getTables()) {
+                for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                     long totalRowCount = 0L;
                     if (!table.isNativeTableOrMaterializedView()) {
                         continue;
@@ -199,12 +199,12 @@ private void updateLakeTabletStat() {
 
         List<Long> dbIds = GlobalStateMgr.getCurrentState().getLocalMetastore().getDbIds();
         for (Long dbId : dbIds) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 continue;
             }
 
-            List<Table> tables = db.getTables();
+            List<Table> tables = GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId());
             for (Table table : tables) {
                 if (table.isCloudNativeTableOrMaterializedView()) {
                     updateLakeTableTabletStat(db, (OlapTable) table);
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/UniqueConstraint.java b/fe/fe-core/src/main/java/com/starrocks/catalog/UniqueConstraint.java
index 36bee578e307ec..8b43f6bc219fd2 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/UniqueConstraint.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/UniqueConstraint.java
@@ -22,7 +22,6 @@
 import com.starrocks.common.Pair;
 import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.analyzer.SemanticException;
-import com.starrocks.sql.common.MetaUtils;
 import org.apache.logging.log4j.LogManager;
 import org.apache.logging.log4j.Logger;
 
@@ -65,7 +64,10 @@ public List<String> getUniqueColumnNames() {
         if (referencedTable != null) {
             targetTable = referencedTable;
         } else {
-            targetTable = MetaUtils.getTable(catalogName, dbName, tableName);
+            targetTable = GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(catalogName, dbName, tableName);
+            if (targetTable == null) {
+                throw new SemanticException("Table %s is not found", tableName);
+            }
         }
         List<String> result = new ArrayList<>(uniqueColumns.size());
         for (ColumnId columnId : uniqueColumns) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/combinator/AggStateDesc.java b/fe/fe-core/src/main/java/com/starrocks/catalog/combinator/AggStateDesc.java
new file mode 100644
index 00000000000000..ba4575c61116e7
--- /dev/null
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/combinator/AggStateDesc.java
@@ -0,0 +1,193 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+package com.starrocks.catalog.combinator;
+
+import com.google.api.client.util.Lists;
+import com.google.common.base.Objects;
+import com.google.common.base.Preconditions;
+import com.google.gson.annotations.SerializedName;
+import com.starrocks.analysis.FunctionParams;
+import com.starrocks.catalog.AggregateFunction;
+import com.starrocks.catalog.Function;
+import com.starrocks.catalog.Type;
+import com.starrocks.common.AnalysisException;
+import com.starrocks.qe.ConnectContext;
+import com.starrocks.sql.analyzer.FunctionAnalyzer;
+import com.starrocks.sql.parser.NodePosition;
+import com.starrocks.thrift.TAggStateDesc;
+import com.starrocks.thrift.TFunctionVersion;
+import com.starrocks.thrift.TTypeDesc;
+import com.starrocks.thrift.TTypeNode;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.List;
+
+/**
+ * AggStateDesc is used to get the aggregate function which's used for common aggregate function state. 
+ * Aggregate function's state needs to find the associated aggregate function, to get the aggregate function, 
+ * we need to know the function name, return type, argument types and result nullable.
+ */
+public class AggStateDesc {
+    // aggregate function's name
+    @SerializedName(value = "functionName")
+    private String functionName;
+    // aggregate function's argument types
+    @SerializedName(value = "argTypes")
+    private List<Type> argTypes;
+    // aggregate function's return type
+    @SerializedName(value = "returnType")
+    private Type returnType;
+    // aggregate function's result nullable
+    @SerializedName(value = "resultNullable")
+    private Boolean resultNullable;
+
+    public AggStateDesc(AggregateFunction aggFunc) {
+        this(aggFunc.functionName(), aggFunc.getReturnType(), Arrays.asList(aggFunc.getArgs()),
+                aggFunc.isNullable());
+    }
+
+    public AggStateDesc(String functionName,
+                        Type returnType,
+                        List<Type> argTypes,
+                        Boolean resultNullable) {
+        Preconditions.checkNotNull(functionName, "functionName should not be null");
+        Preconditions.checkNotNull(returnType, "returnType should not be null");
+        Preconditions.checkNotNull(argTypes, "argTypes should not be null");
+        Preconditions.checkNotNull(resultNullable, "resultNullable should not be null");
+        this.functionName = functionName;
+        this.returnType = returnType;
+        this.argTypes = argTypes;
+        this.resultNullable = resultNullable;
+    }
+
+    public List<Type> getArgTypes() {
+        return argTypes;
+    }
+
+    public Type getReturnType() {
+        return returnType;
+    }
+
+    public Boolean getResultNullable() {
+        return resultNullable;
+    }
+
+    public String getFunctionName() {
+        return functionName;
+    }
+
+    @Override
+    public int hashCode() {
+        return Objects.hashCode(argTypes, resultNullable, functionName);
+    }
+
+    @Override
+    public boolean equals(Object o) {
+        if (!(o instanceof AggStateDesc)) {
+            return false;
+        }
+        AggStateDesc other = (AggStateDesc) o;
+        // result nullable
+        if (resultNullable != other.resultNullable) {
+            return false;
+        }
+        // func name
+        if (!functionName.equalsIgnoreCase(other.functionName)) {
+            return false;
+        }
+        // return type
+        if (!returnType.equals(other.returnType)) {
+            return false;
+        }
+        // arg types
+        int subTypeNumber = argTypes.size();
+        if (subTypeNumber != other.argTypes.size()) {
+            return false;
+        }
+        for (int i = 0; i < subTypeNumber; i++) {
+            if (!argTypes.get(i).equals(other.argTypes.get(i))) {
+                return false;
+            }
+        }
+        return true;
+    }
+
+    public TAggStateDesc toThrift() {
+        // wrapper extra data type
+        TAggStateDesc tAggStateDesc = new TAggStateDesc();
+        tAggStateDesc.setAgg_func_name(functionName);
+        for (Type argType : argTypes) {
+            TTypeDesc tTypeDesc = new TTypeDesc();
+            tTypeDesc.setTypes(new ArrayList<TTypeNode>());
+            argType.toThrift(tTypeDesc);
+            tAggStateDesc.addToArg_types(tTypeDesc);
+        }
+        tAggStateDesc.setResult_nullable(resultNullable);
+        tAggStateDesc.setFunc_version(TFunctionVersion.RUNTIME_FILTER_SERIALIZE_VERSION_2.getValue());
+
+        // ret type
+        TTypeDesc tTypeDesc = new TTypeDesc();
+        tTypeDesc.setTypes(new ArrayList<TTypeNode>());
+        returnType.toThrift(tTypeDesc);
+        tAggStateDesc.setRet_type(tTypeDesc);
+        Preconditions.checkState(!tTypeDesc.types.isEmpty());
+
+        return tAggStateDesc;
+    }
+
+    public AggStateDesc clone() {
+        return new AggStateDesc(functionName, returnType.clone(), Lists.newArrayList(argTypes), resultNullable);
+    }
+
+    /**
+     * @return associated analyzed aggregate function
+     * @throws AnalysisException: when the aggregate function is not found or not an aggregate function
+     */
+    public AggregateFunction getAggregateFunction() throws AnalysisException {
+        FunctionParams params = new FunctionParams(false, Lists.newArrayList());
+        Type[] argumentTypes = argTypes.toArray(Type[]::new);
+        Boolean[] isArgumentConstants = argTypes.stream().map(x -> new Boolean(false)).toArray(Boolean[]::new);
+        Function result = FunctionAnalyzer.getAnalyzedAggregateFunction(ConnectContext.get(),
+                this.functionName, params, argumentTypes, isArgumentConstants, NodePosition.ZERO);
+        if (result == null) {
+            throw new AnalysisException(String.format("AggStateType function %s with input %s not found", functionName,
+                    argTypes));
+        }
+        if (!(result instanceof AggregateFunction)) {
+            throw new AnalysisException(String.format("AggStateType function %s with input %s found but not an aggregate " +
+                    "function", functionName, argTypes));
+        }
+        return (AggregateFunction) result;
+    }
+
+    @Override
+    public String toString() {
+        return toSql();
+    }
+
+    public String toSql() {
+        StringBuilder sb = new StringBuilder();
+        sb.append(functionName).append("(");
+        for (int i = 0; i < argTypes.size(); i++) {
+            if (i > 0) {
+                sb.append(", ");
+            }
+            sb.append(argTypes.get(i).toSql());
+        }
+        sb.append(")");
+        return sb.toString();
+    }
+}
\ No newline at end of file
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/system/information/MaterializedViewsSystemTable.java b/fe/fe-core/src/main/java/com/starrocks/catalog/system/information/MaterializedViewsSystemTable.java
index eae934f2a736eb..607c3360165154 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/system/information/MaterializedViewsSystemTable.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/system/information/MaterializedViewsSystemTable.java
@@ -53,6 +53,7 @@ public static SystemTable create() {
                                 ScalarType.createVarchar(MAX_FIELD_VARCHAR_LENGTH))
                         .column("EXTRA_MESSAGE", ScalarType.createVarchar(1024))
                         .column("QUERY_REWRITE_STATUS", ScalarType.createVarcharType(64))
+                        .column("CREATOR", ScalarType.createVarchar(64))
                         .build(), TSchemaTableType.SCH_MATERIALIZED_VIEWS);
     }
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/system/information/TasksSystemTable.java b/fe/fe-core/src/main/java/com/starrocks/catalog/system/information/TasksSystemTable.java
index ee0af37fccc8cf..813f40dcd5ea34 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/system/information/TasksSystemTable.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/system/information/TasksSystemTable.java
@@ -13,17 +13,36 @@
 // limitations under the License.
 package com.starrocks.catalog.system.information;
 
+import com.google.common.collect.Lists;
+import com.starrocks.catalog.InternalCatalog;
 import com.starrocks.catalog.PrimitiveType;
 import com.starrocks.catalog.ScalarType;
 import com.starrocks.catalog.Table;
 import com.starrocks.catalog.system.SystemId;
 import com.starrocks.catalog.system.SystemTable;
+import com.starrocks.cluster.ClusterNamespace;
+import com.starrocks.privilege.AccessDeniedException;
+import com.starrocks.scheduler.Constants;
+import com.starrocks.scheduler.Task;
+import com.starrocks.scheduler.TaskManager;
+import com.starrocks.server.GlobalStateMgr;
+import com.starrocks.sql.analyzer.Authorizer;
+import com.starrocks.sql.ast.UserIdentity;
+import com.starrocks.thrift.TGetTasksParams;
 import com.starrocks.thrift.TSchemaTableType;
+import com.starrocks.thrift.TTaskInfo;
+import org.apache.logging.log4j.LogManager;
+import org.apache.logging.log4j.Logger;
+
+import java.util.List;
 
 import static com.starrocks.catalog.system.SystemTable.MAX_FIELD_VARCHAR_LENGTH;
 import static com.starrocks.catalog.system.SystemTable.builder;
 
 public class TasksSystemTable {
+
+    private static final Logger LOG = LogManager.getLogger(TasksSystemTable.class);
+
     public static SystemTable create() {
         return new SystemTable(SystemId.TASKS_ID,
                 "tasks",
@@ -37,6 +56,56 @@ public static SystemTable create() {
                         .column("DEFINITION", ScalarType.createVarchar(MAX_FIELD_VARCHAR_LENGTH))
                         .column("EXPIRE_TIME", ScalarType.createType(PrimitiveType.DATETIME))
                         .column("PROPERTIES", ScalarType.createVarcharType(MAX_FIELD_VARCHAR_LENGTH))
+                        .column("CREATOR", ScalarType.createVarchar(64))
                         .build(), TSchemaTableType.SCH_TASKS);
     }
+
+    public static List<TTaskInfo> query(TGetTasksParams params) {
+        GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
+        TaskManager taskManager = globalStateMgr.getTaskManager();
+        List<Task> taskList = taskManager.filterTasks(params);
+        List<TTaskInfo> result = Lists.newArrayList();
+        UserIdentity currentUser = null;
+        if (params.isSetCurrent_user_ident()) {
+            currentUser = UserIdentity.fromThrift(params.current_user_ident);
+        }
+
+        for (Task task : taskList) {
+            if (task.getDbName() == null) {
+                LOG.warn("Ignore the task db because information is incorrect: " + task);
+                continue;
+            }
+
+            try {
+                Authorizer.checkAnyActionOnOrInDb(currentUser, null, InternalCatalog.DEFAULT_INTERNAL_CATALOG_NAME,
+                        task.getDbName());
+            } catch (AccessDeniedException e) {
+                continue;
+            }
+
+            TTaskInfo info = new TTaskInfo();
+            info.setTask_name(task.getName());
+            info.setCreate_time(task.getCreateTime() / 1000);
+            String scheduleStr = "UNKNOWN";
+            if (task.getType() != null) {
+                scheduleStr = task.getType().name();
+            }
+            if (task.getType() == Constants.TaskType.PERIODICAL) {
+                scheduleStr += task.getSchedule();
+            }
+            info.setSchedule(scheduleStr);
+            info.setCatalog(task.getCatalogName());
+            info.setDatabase(ClusterNamespace.getNameFromFullName(task.getDbName()));
+            info.setDefinition(task.getDefinition());
+            info.setExpire_time(task.getExpireTime() / 1000);
+            info.setProperties(task.getPropertiesString());
+            if (task.getUserIdentity() != null) {
+                info.setCreator(task.getUserIdentity().toString());
+            } else {
+                info.setCreator(task.getCreateUser());
+            }
+            result.add(info);
+        }
+        return result;
+    }
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/system/sys/GrantsTo.java b/fe/fe-core/src/main/java/com/starrocks/catalog/system/sys/GrantsTo.java
index 8bfe2cab8e06a4..7dceee92b47379 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/system/sys/GrantsTo.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/system/sys/GrantsTo.java
@@ -193,7 +193,8 @@ private static Set<TGetGrantsToRolesOrUserItem> getGrantItems(
                         } else {
                             Database database;
                             if (CatalogMgr.isInternalCatalog(catalogName)) {
-                                database = GlobalStateMgr.getCurrentState().getDb(Long.parseLong(dbPEntryObject.getUUID()));
+                                database = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                            .getDb(Long.parseLong(dbPEntryObject.getUUID()));
                             } else {
                                 String dbName = ExternalCatalog.getDbNameFromUUID(dbPEntryObject.getUUID());
                                 database = metadataMgr.getDb(catalogName, dbName);
@@ -241,7 +242,7 @@ private static Set<TGetGrantsToRolesOrUserItem> getGrantItems(
                         } else {
                             Database database;
                             if (CatalogMgr.isInternalCatalog(tablePEntryObject.getCatalogId())) {
-                                database = GlobalStateMgr.getCurrentState()
+                                database = GlobalStateMgr.getCurrentState().getLocalMetastore()
                                         .getDb(Long.parseLong(tablePEntryObject.getDatabaseUUID()));
                             } else {
                                 String dbName = ExternalCatalog.getDbNameFromUUID(tablePEntryObject.getDatabaseUUID());
@@ -261,7 +262,8 @@ private static Set<TGetGrantsToRolesOrUserItem> getGrantItems(
                                 objects.addAll(expandAllTables(metadataMgr, catalogName, dbName, privEntry.getKey()));
                             } else {
                                 if (CatalogMgr.isInternalCatalog(tablePEntryObject.getCatalogId())) {
-                                    Table table = database.getTable((Long.parseLong(tablePEntryObject.getTableUUID())));
+                                    Table table = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                .getTable(database.getId(), (Long.parseLong(tablePEntryObject.getTableUUID())));
                                     if (table == null) {
                                         continue;
                                     }
@@ -319,7 +321,7 @@ private static Set<TGetGrantsToRolesOrUserItem> getGrantItems(
                     if (databaseId == PrivilegeBuiltinConstants.ALL_DATABASE_ID) {
                         List<String> dbNames = metadataMgr.listDbNames(InternalCatalog.DEFAULT_INTERNAL_CATALOG_NAME);
                         for (String dbName : dbNames) {
-                            Database database = GlobalStateMgr.getCurrentState().getDb(dbName);
+                            Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
                             if (database == null) {
                                 continue;
                             }
@@ -333,7 +335,7 @@ private static Set<TGetGrantsToRolesOrUserItem> getGrantItems(
                             }
                         }
                     } else {
-                        Database database = GlobalStateMgr.getCurrentState().getDb(databaseId);
+                        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(databaseId);
                         if (database == null) {
                             continue;
                         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/catalog/system/sys/SysObjectDependencies.java b/fe/fe-core/src/main/java/com/starrocks/catalog/system/sys/SysObjectDependencies.java
index 3cb8800a47fa22..493572393ad098 100644
--- a/fe/fe-core/src/main/java/com/starrocks/catalog/system/sys/SysObjectDependencies.java
+++ b/fe/fe-core/src/main/java/com/starrocks/catalog/system/sys/SysObjectDependencies.java
@@ -85,7 +85,7 @@ public static TObjectDependencyRes listObjectDependencies(TObjectDependencyReq r
                     .orElse(InternalCatalog.DEFAULT_INTERNAL_CATALOG_NAME);
             locker.lockDatabase(db, LockType.READ);
             try {
-                for (Table table : db.getTables()) {
+                for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                     // If it is not a materialized view, we do not need to verify permissions
                     if (!table.isMaterializedView()) {
                         continue;
diff --git a/fe/fe-core/src/main/java/com/starrocks/clone/DynamicPartitionScheduler.java b/fe/fe-core/src/main/java/com/starrocks/clone/DynamicPartitionScheduler.java
index 31f9e28384e80c..8043546a9c66bf 100644
--- a/fe/fe-core/src/main/java/com/starrocks/clone/DynamicPartitionScheduler.java
+++ b/fe/fe-core/src/main/java/com/starrocks/clone/DynamicPartitionScheduler.java
@@ -376,7 +376,7 @@ private void scheduleDynamicPartition() {
     }
 
     public boolean executeDynamicPartitionForTable(Long dbId, Long tableId) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             LOG.warn("Automatically removes the schedule because database does not exist, dbId: {}", dbId);
             return true;
@@ -387,7 +387,7 @@ public boolean executeDynamicPartitionForTable(Long dbId, Long tableId) {
         String tableName;
         boolean skipAddPartition = false;
         OlapTable olapTable;
-        olapTable = (OlapTable) db.getTable(tableId);
+        olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (olapTable == null) {
             LOG.warn("Automatically removes the schedule because table does not exist, " +
                         "tableId: {}", tableId);
@@ -488,13 +488,13 @@ private void scheduleTTLPartition() {
             Pair<Long, Long> tableInfo = iterator.next();
             Long dbId = tableInfo.first;
             Long tableId = tableInfo.second;
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 iterator.remove();
                 LOG.warn("Could not get database={} info. remove it from scheduler", dbId);
                 continue;
             }
-            Table table = db.getTable(tableId);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             OlapTable olapTable;
             if (table instanceof OlapTable) {
                 olapTable = (OlapTable) table;
@@ -686,7 +686,7 @@ private void findSchedulableTables() {
         Map<String, List<String>> ttlPartitionTables = new HashMap<>();
         long start = System.currentTimeMillis();
         for (Long dbId : GlobalStateMgr.getCurrentState().getLocalMetastore().getDbIds()) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 continue;
             }
@@ -697,7 +697,7 @@ private void findSchedulableTables() {
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.READ);
             try {
-                for (Table table : GlobalStateMgr.getCurrentState().getDb(dbId).getTables()) {
+                for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(dbId)) {
                     if (DynamicPartitionUtil.isDynamicPartitionTable(table)) {
                         registerDynamicPartitionTable(db.getId(), table.getId());
                         dynamicPartitionTables.computeIfAbsent(db.getFullName(), k -> new ArrayList<>())
diff --git a/fe/fe-core/src/main/java/com/starrocks/clone/TabletChecker.java b/fe/fe-core/src/main/java/com/starrocks/clone/TabletChecker.java
index 9bcb5417424c7e..55f3ce09200444 100644
--- a/fe/fe-core/src/main/java/com/starrocks/clone/TabletChecker.java
+++ b/fe/fe-core/src/main/java/com/starrocks/clone/TabletChecker.java
@@ -507,7 +507,7 @@ private void cleanInvalidUrgentTable() {
         while (iter.hasNext()) {
             Map.Entry<Long, Map<Long, Set<PrioPart>>> dbEntry = iter.next();
             long dbId = dbEntry.getKey();
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 iter.remove();
                 continue;
@@ -518,7 +518,7 @@ private void cleanInvalidUrgentTable() {
             try {
                 for (Map.Entry<Long, Set<PrioPart>> tblEntry : dbEntry.getValue().entrySet()) {
                     long tblId = tblEntry.getKey();
-                    OlapTable tbl = (OlapTable) db.getTable(tblId);
+                    OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tblId);
                     if (tbl == null) {
                         deletedUrgentTable.add(Pair.create(dbId, tblId));
                         continue;
@@ -609,7 +609,7 @@ public List<List<String>> getUrgentTableInfo() {
     public static RepairTabletInfo getRepairTabletInfo(String dbName, String tblName, List<String> partitions)
             throws DdlException {
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
-        Database db = globalStateMgr.getDb(dbName);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("Database " + dbName + " does not exist");
         }
@@ -620,7 +620,7 @@ public static RepairTabletInfo getRepairTabletInfo(String dbName, String tblName
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            Table tbl = db.getTable(tblName);
+            Table tbl = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tblName);
             if (tbl == null || tbl.getType() != TableType.OLAP) {
                 throw new DdlException("Table does not exist or is not OLAP table: " + tblName);
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/clone/TabletSchedCtx.java b/fe/fe-core/src/main/java/com/starrocks/clone/TabletSchedCtx.java
index 366be12efd64bd..4cf74fff3f3c17 100644
--- a/fe/fe-core/src/main/java/com/starrocks/clone/TabletSchedCtx.java
+++ b/fe/fe-core/src/main/java/com/starrocks/clone/TabletSchedCtx.java
@@ -1283,7 +1283,7 @@ public boolean checkPrivForCurrUser(UserIdentity currentUser) {
             return true;
         }
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             return true;
         }
@@ -1291,7 +1291,7 @@ public boolean checkPrivForCurrUser(UserIdentity currentUser) {
         Locker locker = new Locker();
         try {
             locker.lockDatabase(db, LockType.READ);
-            Table table = db.getTable(tblId);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tblId);
             if (table == null) {
                 return true;
             } else {
diff --git a/fe/fe-core/src/main/java/com/starrocks/clone/TabletScheduler.java b/fe/fe-core/src/main/java/com/starrocks/clone/TabletScheduler.java
index d631669edf5608..422dcae37c4165 100644
--- a/fe/fe-core/src/main/java/com/starrocks/clone/TabletScheduler.java
+++ b/fe/fe-core/src/main/java/com/starrocks/clone/TabletScheduler.java
@@ -94,6 +94,7 @@
 
 import java.util.ArrayList;
 import java.util.Collection;
+import java.util.HashSet;
 import java.util.List;
 import java.util.Map;
 import java.util.Objects;
@@ -1151,13 +1152,33 @@ private boolean deleteLocationMismatchReplica(TabletSchedCtx tabletCtx, boolean
             // won't delete location mismatched replica.
             return false;
         }
+
+        Set<Pair<String, String>> matchedLocations = new HashSet<>();
+        Replica dupReplica = null;
+        //1. delete the unmatched replica
         for (Replica replica : tabletCtx.getReplicas()) {
             if (!TabletChecker.isLocationMatch(replica.getBackendId(), tabletCtx.getRequiredLocation())) {
                 deleteReplicaInternal(tabletCtx, replica, "location mismatch", force);
                 return true;
+            } else {
+                Backend backend = systemInfoService.getBackend(replica.getBackendId());
+                if (backend != null) {
+                    Pair<String, String> location = backend.getSingleLevelLocationKV();
+                    if (location != null && matchedLocations.contains(location)) {
+                        dupReplica = replica;
+                    } else {
+                        matchedLocations.add(location);
+                    }
+                }
             }
         }
 
+        //2. delete the duplicate location replica
+        if (dupReplica != null) {
+            deleteReplicaInternal(tabletCtx, dupReplica, "duplicate location", force);
+            return true;
+        }
+
         return false;
     }
 
@@ -1500,7 +1521,7 @@ private List<TabletSchedCtx> filterUnschedulableTablets(List<TabletSchedCtx> alt
             long tabletId = schedCtx.getTabletId();
             long indexId = schedCtx.getIndexId();
 
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 continue;
             }
@@ -1509,7 +1530,7 @@ private List<TabletSchedCtx> filterUnschedulableTablets(List<TabletSchedCtx> alt
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.READ);
             try {
-                tbl = db.getTable(tableId);
+                tbl = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             } finally {
                 locker.unLockDatabase(db, LockType.READ);
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/common/Config.java b/fe/fe-core/src/main/java/com/starrocks/common/Config.java
index ac7b524b1d956c..fbc13cf564ce90 100644
--- a/fe/fe-core/src/main/java/com/starrocks/common/Config.java
+++ b/fe/fe-core/src/main/java/com/starrocks/common/Config.java
@@ -100,6 +100,15 @@ public class Config extends ConfigBase {
 
     @ConfField(comment = "Log4j layout format. Valid choices: plaintext, json")
     public static String sys_log_format = "plaintext";
+
+    @ConfField(comment = "Max length of a log line when using log4j json format," +
+            " truncate string values longer than this specified limit. Default: 1MB")
+    public static int sys_log_json_max_string_length = 1048576;
+
+    @ConfField(comment = "Max length of a profile log line when using log4j json format," +
+            " truncate string values longer than this specified limit. Default: 100MB")
+    public static int sys_log_json_profile_max_string_length = 104857600;
+
     /**
      * audit_log_dir:
      * This specifies FE audit log dir.
@@ -134,6 +143,8 @@ public class Config extends ConfigBase {
     public static String[] audit_log_modules = {"slow_query", "query"};
     @ConfField(mutable = true)
     public static long qe_slow_log_ms = 5000;
+    @ConfField(mutable = true)
+    public static boolean enable_qe_slow_log = true;
     @ConfField
     public static String audit_log_roll_interval = "DAY";
     @ConfField
@@ -1265,6 +1276,10 @@ public class Config extends ConfigBase {
     @ConfField(mutable = true)
     public static boolean ignore_materialized_view_error = false;
 
+    @ConfField(mutable = true, comment = "Whether to ignore task run history replay error in querying information_schema" +
+            ".task_runs")
+    public static boolean ignore_task_run_history_replay_error = false;
+
     /**
      * whether backup materialized views in backing databases. If not, will skip backing materialized views.
      */
@@ -2018,6 +2033,10 @@ public class Config extends ConfigBase {
     @ConfField(mutable = true)
     public static double statistic_auto_collect_sample_threshold = 0.3;
 
+    @ConfField(mutable = true, comment = "Tolerate some percent of failure for a large table, it will not affect " +
+            "the job status but improve the robustness")
+    public static double statistic_full_statistics_failure_tolerance_ratio = 0.05;
+
     @ConfField(mutable = true)
     public static long statistic_auto_collect_small_table_size = 5L * 1024 * 1024 * 1024; // 5G
 
@@ -2955,8 +2974,8 @@ public class Config extends ConfigBase {
     @ConfField(mutable = true, comment = "Whether enable to cache mv query context or not")
     public static boolean enable_mv_query_context_cache = true;
 
-    @ConfField(mutable = true, comment = "Whether enable strict insert in mv refresh or not by default")
-    public static boolean enable_mv_refresh_insert_strict = false;
+    @ConfField(mutable = true, comment = "Mv refresh fails if there is filtered data, false by default")
+    public static boolean mv_refresh_fail_on_filter_data = false;
 
     @ConfField(mutable = true, comment = "The default timeout for planner optimize when refresh materialized view, 30s by " +
             "default")
@@ -3146,4 +3165,7 @@ public class Config extends ConfigBase {
 
     @ConfField(mutable = true)
     public static int thrift_max_recursion_depth = 64;
+
+    @ConfField(mutable = true)
+    public static double partition_hash_join_min_cardinality_rate = 0.3;
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/common/Log4jConfig.java b/fe/fe-core/src/main/java/com/starrocks/common/Log4jConfig.java
index 07a36b78b96bd9..8403a4aacf8059 100644
--- a/fe/fe-core/src/main/java/com/starrocks/common/Log4jConfig.java
+++ b/fe/fe-core/src/main/java/com/starrocks/common/Log4jConfig.java
@@ -256,61 +256,28 @@ static String generateActiveLog4jXmlConfig() throws IOException {
         // appender layout
         final String jsonLoggingConfValue = "json";
         if (jsonLoggingConfValue.equalsIgnoreCase(Config.sys_log_format)) {
-            // json logging
-            String jsonLayout =
-                    "<JsonTemplateLayout maxStringLength=\"104857600\" locationInfoEnabled=\"true\">\n" +
-                            "        <EventTemplate><![CDATA[\n{\n" +
-                            "   \"@timestamp\": {\n" +
-                            "       \"$resolver\": \"timestamp\",\n" +
-                            "       \"pattern\": {\n" +
-                            "         \"format\": \"yyyy-MM-dd HH:mm:ss.SSSXXX\",\n" +
-                            "         \"timeZone\": \"UTC\"\n" +
-                            "        }\n" +
-                            "      },\n" +
-                            "      \"level\": {\n" +
-                            "       \"$resolver\": \"level\",\n" +
-                            "       \"field\": \"name\"\n" +
-                            "      },\n" +
-                            "      \"thread.name\": {\n" +
-                            "       \"$resolver\": \"thread\",\n" +
-                            "       \"field\": \"name\"\n" +
-                            "      },\n" +
-                            "      \"thread.id\": {\n" +
-                            "       \"$resolver\": \"thread\",\n" +
-                            "       \"field\": \"id\"\n" +
-                            "      },\n" +
-                            "      \"method\": {\n" +
-                            "       \"$resolver\": \"logger\",\n" +
-                            "       \"field\": \"name\",\n" +
-                            "       \"shorten\": {\n" +
-                            "         \"length\": 1,\n" +
-                            "         \"strategy\": \"tail\"\n" +
-                            "        }\n" +
-                            "      },\n" +
-                            "      \"line\": {\n" +
-                            "        \"$resolver\": \"source\",\n" +
-                            "        \"field\": \"lineNumber\"\n" +
-                            "      },\n" +
-                            "      \"message\": {\n" +
-                            "        \"$resolver\": \"message\",\n" +
-                            "        \"stringfield\": \"true\"\n" +
-                            "      },\n" +
-                            "      \"exception\": {\n" +
-                            "        \"$resolver\": \"exception\",\n" +
-                            "        \"field\": \"stackTrace\",\n" +
-                            "        \"stackTrace\": {\n" +
-                            "          \"stringified\": true,\n" +
-                            "          \"full\": true\n" +
-                            "        }\n" +
-                            "      }" +
-                            "      }\n]]></EventTemplate>\n" +
-                            "</JsonTemplateLayout>";
-            properties.put("syslog_default_layout", jsonLayout);
-            properties.put("syslog_warning_layout", jsonLayout);
-            properties.put("syslog_audit_layout", jsonLayout);
-            properties.put("syslog_dump_layout", jsonLayout);
-            properties.put("syslog_bigquery_layout", jsonLayout);
-            properties.put("syslog_profile_layout", jsonLayout);
+            // json logging, use `'` and replace them to `"` in batch to avoid too many escapes
+            String jsonConfig =
+                    "{'@timestamp':{'$resolver':'timestamp','pattern':{'format':'yyyy-MM-dd HH:mm:ss.SSSXXX','timeZone':'UTC'}}," +
+                            "'level':{'$resolver':'level','field':'name'}," +
+                            "'thread.name':{'$resolver':'thread','field':'name'}," +
+                            "'thread.id':{'$resolver':'thread','field':'id'}," +
+                            "'line':{'$resolver':'source','field':'lineNumber'}," +
+                            "'file':{'$resolver':'source','field':'fileName'}," +
+                            "'method':{'$resolver':'source','field':'methodName'}," +
+                            "'message':{'$resolver':'message','stringfield':'true'}," +
+                            "'exception':{'$resolver':'exception','field':'stackTrace','stackTrace':{'stringified':true,'full':true}}}";
+            jsonConfig = jsonConfig.replace("'", "\"");
+            String jsonLayoutFormatter = "<JsonTemplateLayout maxStringLength=\"%d\" locationInfoEnabled=\"true\">\n" +
+                    "<EventTemplate><![CDATA[" + jsonConfig + "]]></EventTemplate>\n" + "</JsonTemplateLayout>";
+            String jsonLayoutDefault = String.format(jsonLayoutFormatter, Config.sys_log_json_max_string_length);
+            String jsonLayoutProfile = String.format(jsonLayoutFormatter, Config.sys_log_json_profile_max_string_length);
+            properties.put("syslog_default_layout", jsonLayoutDefault);
+            properties.put("syslog_warning_layout", jsonLayoutDefault);
+            properties.put("syslog_audit_layout", jsonLayoutDefault);
+            properties.put("syslog_dump_layout", jsonLayoutDefault);
+            properties.put("syslog_bigquery_layout", jsonLayoutDefault);
+            properties.put("syslog_profile_layout", jsonLayoutProfile);
         } else {
             // fallback to plaintext logging
             properties.put("syslog_default_layout",
diff --git a/fe/fe-core/src/main/java/com/starrocks/common/proc/DbsProcDir.java b/fe/fe-core/src/main/java/com/starrocks/common/proc/DbsProcDir.java
index 730876f6650f28..6711281ca855dd 100644
--- a/fe/fe-core/src/main/java/com/starrocks/common/proc/DbsProcDir.java
+++ b/fe/fe-core/src/main/java/com/starrocks/common/proc/DbsProcDir.java
@@ -83,9 +83,9 @@ public ProcNodeInterface lookup(String dbIdOrName) throws AnalysisException {
 
         Database db;
         try {
-            db = globalStateMgr.getDb(Long.parseLong(dbIdOrName));
+            db = globalStateMgr.getLocalMetastore().getDb(Long.parseLong(dbIdOrName));
         } catch (NumberFormatException e) {
-            db = globalStateMgr.getDb(dbIdOrName);
+            db = globalStateMgr.getLocalMetastore().getDb(dbIdOrName);
         }
 
         if (db == null) {
@@ -110,7 +110,7 @@ public ProcResult fetchResult() throws AnalysisException {
         // get info
         List<List<Comparable>> dbInfos = new ArrayList<List<Comparable>>();
         for (String dbName : dbNames) {
-            Database db = globalStateMgr.getDb(dbName);
+            Database db = globalStateMgr.getLocalMetastore().getDb(dbName);
             if (db == null) {
                 continue;
             }
@@ -118,7 +118,7 @@ public ProcResult fetchResult() throws AnalysisException {
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.READ);
             try {
-                int tableNum = db.getTables().size();
+                int tableNum = GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId()).size();
                 dbInfo.add(db.getId());
                 dbInfo.add(dbName);
                 dbInfo.add(tableNum);
diff --git a/fe/fe-core/src/main/java/com/starrocks/common/proc/JobsDbProcDir.java b/fe/fe-core/src/main/java/com/starrocks/common/proc/JobsDbProcDir.java
index 15964d022653c6..ac337b04ea97cb 100644
--- a/fe/fe-core/src/main/java/com/starrocks/common/proc/JobsDbProcDir.java
+++ b/fe/fe-core/src/main/java/com/starrocks/common/proc/JobsDbProcDir.java
@@ -76,7 +76,7 @@ public ProcNodeInterface lookup(String dbIdStr) throws AnalysisException {
             throw new AnalysisException("Invalid db id format: " + dbIdStr);
         }
 
-        Database db = globalStateMgr.getDb(dbId);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new AnalysisException("Database[" + dbId + "] does not exist.");
         }
@@ -98,7 +98,7 @@ public ProcResult fetchResult() throws AnalysisException {
         }
 
         for (String name : names) {
-            Database db = globalStateMgr.getDb(name);
+            Database db = globalStateMgr.getLocalMetastore().getDb(name);
             result.addRow(Lists.newArrayList(String.valueOf(db.getId()), name));
         }
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/common/proc/ProcService.java b/fe/fe-core/src/main/java/com/starrocks/common/proc/ProcService.java
index 7b439ed28bd848..a90b0818249527 100644
--- a/fe/fe-core/src/main/java/com/starrocks/common/proc/ProcService.java
+++ b/fe/fe-core/src/main/java/com/starrocks/common/proc/ProcService.java
@@ -71,6 +71,7 @@ private ProcService() {
         root.register("catalog", GlobalStateMgr.getCurrentState().getCatalogMgr().getProcNode());
         root.register("compactions", new CompactionsProcNode());
         root.register("meta_recovery", new MetaRecoveryProdDir());
+        root.register("replications", new ReplicationsProcNode());
     }
 
     // Get the corresponding PROC Node by the specified path
diff --git a/fe/fe-core/src/main/java/com/starrocks/common/proc/ProcUtils.java b/fe/fe-core/src/main/java/com/starrocks/common/proc/ProcUtils.java
index bc4f73bc151ac7..290c1f37ea233a 100644
--- a/fe/fe-core/src/main/java/com/starrocks/common/proc/ProcUtils.java
+++ b/fe/fe-core/src/main/java/com/starrocks/common/proc/ProcUtils.java
@@ -24,7 +24,7 @@ static long getDbId(String dbIdOrName) throws AnalysisException {
         try {
             return Long.parseLong(dbIdOrName);
         } catch (NumberFormatException e) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbIdOrName);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbIdOrName);
             if (db == null) {
                 throw new AnalysisException("Unknown database id or name \"" + dbIdOrName + "\"");
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/common/proc/ReplicationsProcNode.java b/fe/fe-core/src/main/java/com/starrocks/common/proc/ReplicationsProcNode.java
new file mode 100644
index 00000000000000..cb98f5202b6d94
--- /dev/null
+++ b/fe/fe-core/src/main/java/com/starrocks/common/proc/ReplicationsProcNode.java
@@ -0,0 +1,66 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+package com.starrocks.common.proc;
+
+import com.google.common.base.Strings;
+import com.starrocks.common.AnalysisException;
+import com.starrocks.common.util.TimeUtils;
+import com.starrocks.replication.ReplicationJob;
+import com.starrocks.replication.ReplicationMgr;
+import com.starrocks.server.GlobalStateMgr;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.List;
+
+public class ReplicationsProcNode implements ProcNodeInterface {
+    private static final List<String> TITLES = Collections.unmodifiableList(Arrays.asList(
+            "JobID", "DatabaseID", "TableID", "TxnID", "CreatedTime", "FinishedTime", "State", "Progress", "Error"));
+
+    public ReplicationsProcNode() {
+    }
+
+    @Override
+    public ProcResult fetchResult() throws AnalysisException {
+        BaseProcResult result = new BaseProcResult();
+        result.setNames(TITLES);
+        ReplicationMgr replicationMgr = GlobalStateMgr.getCurrentState().getReplicationMgr();
+        List<ReplicationJob> runningJobs = new ArrayList<>(replicationMgr.getRunningJobs());
+        List<ReplicationJob> abortedJobs = new ArrayList<>(replicationMgr.getAbortedJobs());
+        List<ReplicationJob> committedJobs = new ArrayList<>(replicationMgr.getCommittedJobs());
+        runningJobs.sort((job1, job2) -> Long.compare(job1.getCreatedTimeMs(), job2.getCreatedTimeMs()));
+        abortedJobs.sort((job1, job2) -> Long.compare(job1.getCreatedTimeMs(), job2.getCreatedTimeMs()));
+        committedJobs.sort((job1, job2) -> Long.compare(job1.getCreatedTimeMs(), job2.getCreatedTimeMs()));
+        List<ReplicationJob> replicationJobs = new ArrayList<>();
+        replicationJobs.addAll(runningJobs);
+        replicationJobs.addAll(abortedJobs);
+        replicationJobs.addAll(committedJobs);
+        for (ReplicationJob job : replicationJobs) {
+            List<String> row = new ArrayList<>();
+            row.add(job.getJobId());
+            row.add(String.valueOf(job.getDatabaseId()));
+            row.add(String.valueOf(job.getTableId()));
+            row.add(String.valueOf(job.getTransactionId()));
+            row.add(TimeUtils.longToTimeString(job.getCreatedTimeMs()));
+            row.add(TimeUtils.longToTimeString(job.getFinishedTimeMs()));
+            row.add(job.getState().toString());
+            row.add(job.getRunningTaskNum() + "/" + job.getTotalTaskNum());
+            row.add(Strings.nullToEmpty(job.getErrorMessage()));
+            result.addRow(row);
+        }
+        return result;
+    }
+}
diff --git a/fe/fe-core/src/main/java/com/starrocks/common/proc/StatisticProcDir.java b/fe/fe-core/src/main/java/com/starrocks/common/proc/StatisticProcDir.java
index 64e79600ddabde..2a246ba4faf6cb 100644
--- a/fe/fe-core/src/main/java/com/starrocks/common/proc/StatisticProcDir.java
+++ b/fe/fe-core/src/main/java/com/starrocks/common/proc/StatisticProcDir.java
@@ -125,7 +125,7 @@ public ProcResult fetchResult() throws AnalysisException {
                 // skip information_schema database
                 continue;
             }
-            Database db = globalStateMgr.getDb(dbId);
+            Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
             if (db == null) {
                 continue;
             }
@@ -141,7 +141,7 @@ public ProcResult fetchResult() throws AnalysisException {
                 int dbTabletNum = 0;
                 int dbReplicaNum = 0;
 
-                for (Table table : db.getTables()) {
+                for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                     if (!table.isNativeTableOrMaterializedView()) {
                         continue;
                     }
@@ -259,7 +259,7 @@ public ProcNodeInterface lookup(String dbIdStr) throws AnalysisException {
             throw new AnalysisException("Invalid db id format: " + dbIdStr);
         }
 
-        if (globalStateMgr.getDb(dbId) == null) {
+        if (globalStateMgr.getLocalMetastore().getDb(dbId) == null) {
             throw new AnalysisException("Invalid db id: " + dbIdStr);
         }
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/common/proc/TablesProcDir.java b/fe/fe-core/src/main/java/com/starrocks/common/proc/TablesProcDir.java
index adb5fa8b4ebcf8..8af4afb983ab5a 100644
--- a/fe/fe-core/src/main/java/com/starrocks/common/proc/TablesProcDir.java
+++ b/fe/fe-core/src/main/java/com/starrocks/common/proc/TablesProcDir.java
@@ -52,6 +52,7 @@
 import com.starrocks.common.util.TimeUtils;
 import com.starrocks.common.util.concurrent.lock.LockType;
 import com.starrocks.common.util.concurrent.lock.Locker;
+import com.starrocks.server.GlobalStateMgr;
 
 import java.util.ArrayList;
 import java.util.Collections;
@@ -95,9 +96,9 @@ public ProcNodeInterface lookup(String tableIdOrName) throws AnalysisException {
         locker.lockDatabase(db, LockType.READ);
         try {
             try {
-                table = db.getTable(Long.parseLong(tableIdOrName));
+                table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), Long.parseLong(tableIdOrName));
             } catch (NumberFormatException e) {
-                table = db.getTable(tableIdOrName);
+                table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableIdOrName);
             }
         } finally {
             locker.unLockDatabase(db, LockType.READ);
@@ -119,7 +120,7 @@ public ProcResult fetchResult() throws AnalysisException {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            for (Table table : db.getTables()) {
+            for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                 List<Comparable> tableInfo = new ArrayList<Comparable>();
                 TableType tableType = table.getType();
                 tableInfo.add(table.getId());
diff --git a/fe/fe-core/src/main/java/com/starrocks/common/util/DateUtils.java b/fe/fe-core/src/main/java/com/starrocks/common/util/DateUtils.java
index 3443f30f372c2e..46a44676ec043d 100644
--- a/fe/fe-core/src/main/java/com/starrocks/common/util/DateUtils.java
+++ b/fe/fe-core/src/main/java/com/starrocks/common/util/DateUtils.java
@@ -26,6 +26,7 @@
 import java.time.LocalDate;
 import java.time.LocalDateTime;
 import java.time.LocalTime;
+import java.time.OffsetDateTime;
 import java.time.ZoneId;
 import java.time.ZoneOffset;
 import java.time.ZonedDateTime;
@@ -129,7 +130,11 @@ public static LocalDateTime parseStrictDateTime(String str) {
         if (str == null || str.length() < 5) {
             throw new IllegalArgumentException("Invalid datetime string: " + str);
         }
-        if (str.contains(":")) {
+        if (str.endsWith("Z") || str.endsWith("]")) {
+            return parseIsoZonedDateTimeString(str);
+        } else if (str.contains("+")) {
+            return parseOffsetDateTimeString(str);
+        } else if (str.contains(":")) {
             // datetime
             int isTwoDigit = str.split("-")[0].length() == 2 ? 1 : 0;
             int withSec = str.split(":").length > 2 ? 1 : 0;
@@ -154,6 +159,18 @@ public static LocalDateTime parseStrictDateTime(String str) {
         }
     }
 
+    private static LocalDateTime parseIsoZonedDateTimeString(String datetime) {
+        ZonedDateTime zonedDateTime = ZonedDateTime.parse(datetime, DateTimeFormatter.ISO_ZONED_DATE_TIME);
+        ZonedDateTime localDateTimeWithZone = zonedDateTime.withZoneSameInstant(ZoneId.systemDefault());
+        return localDateTimeWithZone.toLocalDateTime();
+    }
+
+    private static LocalDateTime parseOffsetDateTimeString(String datetime) {
+        OffsetDateTime offsetDateTime = OffsetDateTime.parse(datetime, DateTimeFormatter.ISO_OFFSET_DATE_TIME);
+        ZonedDateTime localDateTimeWithZone = offsetDateTime.atZoneSameInstant(ZoneId.systemDefault());
+        return localDateTimeWithZone.toLocalDateTime();
+    }
+
     public static DateTimeFormatter probeFormat(String dateTimeStr) {
         if (dateTimeStr.length() == 8) {
             return DATEKEY_FORMATTER;
diff --git a/fe/fe-core/src/main/java/com/starrocks/common/util/SmallFileMgr.java b/fe/fe-core/src/main/java/com/starrocks/common/util/SmallFileMgr.java
index c8c08f5f9d55cb..084327f1eac1ca 100644
--- a/fe/fe-core/src/main/java/com/starrocks/common/util/SmallFileMgr.java
+++ b/fe/fe-core/src/main/java/com/starrocks/common/util/SmallFileMgr.java
@@ -197,7 +197,7 @@ public SmallFileMgr() {
 
     public void createFile(CreateFileStmt stmt) throws DdlException {
         String dbName = stmt.getDbName();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("Database " + dbName + " does not exist");
         }
@@ -207,7 +207,7 @@ public void createFile(CreateFileStmt stmt) throws DdlException {
 
     public void dropFile(DropFileStmt stmt) throws DdlException {
         String dbName = stmt.getDbName();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("Database " + dbName + " does not exist");
         }
@@ -496,7 +496,7 @@ private File getAbsoluteFile(long dbId, String catalog, String fileName) {
     }
 
     public List<List<String>> getInfo(String dbName) throws DdlException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("Database " + dbName + " does not exist");
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/connector/elasticsearch/EsRepository.java b/fe/fe-core/src/main/java/com/starrocks/connector/elasticsearch/EsRepository.java
index 235c95a253e336..da7e5eceaaeab8 100644
--- a/fe/fe-core/src/main/java/com/starrocks/connector/elasticsearch/EsRepository.java
+++ b/fe/fe-core/src/main/java/com/starrocks/connector/elasticsearch/EsRepository.java
@@ -35,7 +35,6 @@
 package com.starrocks.connector.elasticsearch;
 
 import com.google.common.collect.Maps;
-import com.starrocks.catalog.Database;
 import com.starrocks.catalog.EsTable;
 import com.starrocks.catalog.Table;
 import com.starrocks.catalog.Table.TableType;
@@ -119,9 +118,7 @@ public void loadTableFromCatalog() {
         }
         List<Long> dbIds = GlobalStateMgr.getCurrentState().getLocalMetastore().getDbIds();
         for (Long dbId : dbIds) {
-            Database database = GlobalStateMgr.getCurrentState().getDb(dbId);
-
-            List<Table> tables = database.getTables();
+            List<Table> tables = GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(dbId);
             for (Table table : tables) {
                 if (table.getType() == TableType.ELASTICSEARCH) {
                     registerTable((EsTable) table);
diff --git a/fe/fe-core/src/main/java/com/starrocks/connector/hive/ConnectorTableMetadataProcessor.java b/fe/fe-core/src/main/java/com/starrocks/connector/hive/ConnectorTableMetadataProcessor.java
index 5b0752e9cf3280..e79d76c371150d 100644
--- a/fe/fe-core/src/main/java/com/starrocks/connector/hive/ConnectorTableMetadataProcessor.java
+++ b/fe/fe-core/src/main/java/com/starrocks/connector/hive/ConnectorTableMetadataProcessor.java
@@ -184,12 +184,12 @@ private void refreshResourceHiveTable() {
         GlobalStateMgr gsm = GlobalStateMgr.getCurrentState();
         MetadataMgr metadataMgr = gsm.getMetadataMgr();
         List<Database> databases = gsm.getLocalMetastore().getDbIds().stream()
-                .map(gsm::getDb)
+                .map(dbId -> GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId))
                 .filter(Objects::nonNull)
                 .filter(db -> !db.isSystemDatabase())
                 .collect(Collectors.toList());
         for (Database db : databases) {
-            List<HiveTable> tables = db.getTables().stream()
+            List<HiveTable> tables = GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId()).stream()
                     .filter(tbl -> tbl.getType() == Table.TableType.HIVE)
                     .map(tbl -> (HiveTable) tbl)
                     .collect(Collectors.toList());
@@ -199,7 +199,7 @@ private void refreshResourceHiveTable() {
                             "in the background", db.getFullName(), table.getName(), table.getDbName(), table.getTableName());
                     // we didn't use db locks to prevent background tasks from affecting the query.
                     // So we need to check if the table to be refreshed exists.
-                    if (db.getTable(table.getId()) != null) {
+                    if (GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), table.getId()) != null) {
                         metadataMgr.refreshTable(table.getCatalogName(), db.getFullName(),
                                 table, Lists.newArrayList(), false);
                     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/connector/jdbc/JDBCSchemaResolver.java b/fe/fe-core/src/main/java/com/starrocks/connector/jdbc/JDBCSchemaResolver.java
index 7107f6495c9062..2d19e926c64d86 100644
--- a/fe/fe-core/src/main/java/com/starrocks/connector/jdbc/JDBCSchemaResolver.java
+++ b/fe/fe-core/src/main/java/com/starrocks/connector/jdbc/JDBCSchemaResolver.java
@@ -89,8 +89,17 @@ public List<Column> convertToSRTable(ResultSet columnSet) throws SQLException {
                     columnSet.getString("TYPE_NAME"),
                     columnSet.getInt("COLUMN_SIZE"),
                     columnSet.getInt("DECIMAL_DIGITS"));
+
+            String comment = "";
+            // Add try-cache to prevent exceptions when the metadata of some databases does not contain REMARKS
+            try {
+                if (columnSet.getString("REMARKS") != null) {
+                    comment = columnSet.getString("REMARKS");
+                }
+            } catch (SQLException ignored) { }
+
             fullSchema.add(new Column(columnSet.getString("COLUMN_NAME"), type,
-                    columnSet.getString("IS_NULLABLE").equals("YES")));
+                    columnSet.getString("IS_NULLABLE").equals("YES"), comment));
         }
         return fullSchema;
     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/consistency/CheckConsistencyJob.java b/fe/fe-core/src/main/java/com/starrocks/consistency/CheckConsistencyJob.java
index 7e42d9d2512ffa..21bc56346f029e 100644
--- a/fe/fe-core/src/main/java/com/starrocks/consistency/CheckConsistencyJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/consistency/CheckConsistencyJob.java
@@ -128,13 +128,13 @@ public boolean sendTasks() {
             return false;
         }
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(tabletMeta.getDbId());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(tabletMeta.getDbId());
         if (db == null) {
             LOG.debug("db[{}] does not exist", tabletMeta.getDbId());
             return false;
         }
 
-        Table table = db.getTable(tabletMeta.getTableId());
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tabletMeta.getTableId());
         if (table == null) {
             LOG.debug("table[{}] does not exist", tabletMeta.getTableId());
             return false;
@@ -254,13 +254,13 @@ public synchronized int tryFinishJob() {
             return -1;
         }
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(tabletMeta.getDbId());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(tabletMeta.getDbId());
         if (db == null) {
             LOG.warn("db[{}] does not exist", tabletMeta.getDbId());
             return -1;
         }
 
-        Table table = db.getTable(tabletMeta.getTableId());
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tabletMeta.getTableId());
         if (table == null) {
             LOG.warn("table[{}] does not exist", tabletMeta.getTableId());
             return -1;
diff --git a/fe/fe-core/src/main/java/com/starrocks/consistency/ConsistencyChecker.java b/fe/fe-core/src/main/java/com/starrocks/consistency/ConsistencyChecker.java
index 9aaf27a0ecab16..7f4f0c80675769 100644
--- a/fe/fe-core/src/main/java/com/starrocks/consistency/ConsistencyChecker.java
+++ b/fe/fe-core/src/main/java/com/starrocks/consistency/ConsistencyChecker.java
@@ -284,7 +284,7 @@ protected List<Long> chooseTablets() {
                 // skip 'information_schema' database
                 continue;
             }
-            Database db = globalStateMgr.getDb(dbId);
+            Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
             if (db == null) {
                 continue;
             }
@@ -301,7 +301,7 @@ protected List<Long> chooseTablets() {
                 long startTime = System.currentTimeMillis();
                 try {
                     // sort tables
-                    List<Table> tables = db.getTables();
+                    List<Table> tables = globalStateMgr.getLocalMetastore().getTables(db.getId());
                     Queue<MetaObject> tableQueue = new PriorityQueue<>(Math.max(tables.size(), 1), COMPARATOR);
                     for (Table table : tables) {
                         // Only check the OLAP table who is in NORMAL state.
@@ -416,12 +416,13 @@ public void handleFinishedConsistencyCheck(CheckConsistencyTask task, long check
     }
 
     public void replayFinishConsistencyCheck(ConsistencyCheckInfo info, GlobalStateMgr globalStateMgr) {
-        Database db = globalStateMgr.getDb(info.getDbId());
+        Database db = globalStateMgr.getLocalMetastore().getDb(info.getDbId());
         if (db == null) {
             LOG.warn("replay finish consistency check failed, db is null, info: {}", info);
             return;
         }
-        OlapTable table = (OlapTable) db.getTable(info.getTableId());
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getId(), info.getTableId());
         if (table == null) {
             LOG.warn("replay finish consistency check failed, table is null, info: {}", info);
             return;
diff --git a/fe/fe-core/src/main/java/com/starrocks/consistency/MetaRecoveryDaemon.java b/fe/fe-core/src/main/java/com/starrocks/consistency/MetaRecoveryDaemon.java
index a1010d9a326a15..fef99e8addecd3 100644
--- a/fe/fe-core/src/main/java/com/starrocks/consistency/MetaRecoveryDaemon.java
+++ b/fe/fe-core/src/main/java/com/starrocks/consistency/MetaRecoveryDaemon.java
@@ -71,7 +71,7 @@ public void recover() {
         List<PartitionVersion> partitionsToRecover = new ArrayList<>();
         List<Long> dbIds = stateMgr.getLocalMetastore().getDbIds();
         for (long dbId : dbIds) {
-            Database database = stateMgr.getDb(dbId);
+            Database database = stateMgr.getLocalMetastore().getDb(dbId);
             if (database == null || database.isSystemDatabase()) {
                 continue;
             }
@@ -79,7 +79,7 @@ public void recover() {
             Locker locker = new Locker();
             locker.lockDatabase(database, LockType.READ);
             try {
-                for (Table table : database.getTables()) {
+                for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(database.getId())) {
                     if (!table.isOlapTableOrMaterializedView()) {
                         continue;
                     }
@@ -186,7 +186,7 @@ public void recover() {
 
     public void recoverPartitionVersion(PartitionVersionRecoveryInfo recoveryInfo) {
         for (PartitionVersion version : recoveryInfo.getPartitionVersions()) {
-            Database database = GlobalStateMgr.getCurrentState().getDb(version.getDbId());
+            Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(version.getDbId());
             if (database == null) {
                 LOG.warn("recover partition version failed, db is null, versionInfo: {}", version);
                 continue;
@@ -194,7 +194,8 @@ public void recoverPartitionVersion(PartitionVersionRecoveryInfo recoveryInfo) {
             Locker locker = new Locker();
             locker.lockDatabase(database, LockType.WRITE);
             try {
-                Table table = database.getTable(version.getTableId());
+                Table table = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(database.getId(), version.getTableId());
                 if (table == null) {
                     LOG.warn("recover partition version failed, table is null, versionInfo: {}", version);
                     continue;
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/CancelStreamLoad.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/CancelStreamLoad.java
index 593ecccb706054..8ed36633cf0be2 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/CancelStreamLoad.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/CancelStreamLoad.java
@@ -76,7 +76,7 @@ public void executeWithoutPassword(BaseRequest request, BaseResponse response) t
         // FIXME(cmy)
         // checkWritePriv(authInfo.fullUserName, fullDbName);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("unknown database, database=" + dbName);
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/GetDdlStmtAction.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/GetDdlStmtAction.java
index a800f9f09200fc..3602631e6fe75d 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/GetDdlStmtAction.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/GetDdlStmtAction.java
@@ -90,7 +90,7 @@ public void executeWithoutPassword(BaseRequest request, BaseResponse response)
             throw new DdlException("Missing params. Need database name and Table name");
         }
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("Database[" + dbName + "] does not exist");
         }
@@ -102,7 +102,7 @@ public void executeWithoutPassword(BaseRequest request, BaseResponse response)
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            Table table = db.getTable(tableName);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
             if (table == null) {
                 throw new DdlException("Table[" + tableName + "] does not exist");
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/GetStreamLoadState.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/GetStreamLoadState.java
index 9e08246d157760..4d4eb2d36ec743 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/GetStreamLoadState.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/GetStreamLoadState.java
@@ -76,7 +76,7 @@ public void executeWithoutPassword(BaseRequest request, BaseResponse response)
         // FIXME(cmy)
         // checkReadPriv(authInfo.fullUserName, fullDbName);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("unknown database, database=" + dbName);
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/MigrationAction.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/MigrationAction.java
index ede3c0102818be..0b822f61824602 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/MigrationAction.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/MigrationAction.java
@@ -96,7 +96,7 @@ protected void executeWithoutPassword(BaseRequest request, BaseResponse response
             throw new DdlException("Missing params. Need database name");
         }
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("Database[" + dbName + "] does not exist");
         }
@@ -106,7 +106,7 @@ protected void executeWithoutPassword(BaseRequest request, BaseResponse response
         locker.lockDatabase(db, LockType.READ);
         try {
             if (!Strings.isNullOrEmpty(tableName)) {
-                Table table = db.getTable(tableName);
+                Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
                 if (table == null) {
                     throw new DdlException("Table[" + tableName + "] does not exist");
                 }
@@ -135,7 +135,7 @@ protected void executeWithoutPassword(BaseRequest request, BaseResponse response
                 }
             } else {
                 // get all olap table
-                for (Table table : db.getTables()) {
+                for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                     if (table.getType() != TableType.OLAP) {
                         continue;
                     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/RowCountAction.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/RowCountAction.java
index dc70880fbfd28b..50fb2b2d9a236b 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/RowCountAction.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/RowCountAction.java
@@ -92,11 +92,11 @@ protected void executeWithoutPassword(BaseRequest request, BaseResponse response
 
         Map<String, Long> indexRowCountMap = Maps.newHashMap();
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
-        Database db = globalStateMgr.getDb(dbName);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("Database[" + dbName + "] does not exist");
         }
-        Table table = db.getTable(tableName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         if (table == null) {
             throw new DdlException("Table[" + tableName + "] does not exist");
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/ShowDataAction.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/ShowDataAction.java
index 5938ffacedd29a..df67df560deb28 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/ShowDataAction.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/ShowDataAction.java
@@ -69,7 +69,7 @@ public long getDataSizeOfDatabase(Database db) {
         locker.lockDatabase(db, LockType.READ);
         try {
             // sort by table name
-            List<Table> tables = db.getTables();
+            List<Table> tables = GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId());
             for (Table table : tables) {
                 if (!table.isNativeTableOrMaterializedView()) {
                     continue;
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/ShowMetaInfoAction.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/ShowMetaInfoAction.java
index 69fb11dcd89b5c..0b276612b5d973 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/ShowMetaInfoAction.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/ShowMetaInfoAction.java
@@ -173,10 +173,10 @@ public Map<String, Long> getDataSize() {
 
         for (int i = 0; i < dbNames.size(); i++) {
             String dbName = dbNames.get(i);
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
 
             long totalSize = 0;
-            List<Table> tables = db.getTables();
+            List<Table> tables = GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId());
             for (int j = 0; j < tables.size(); j++) {
                 Table table = tables.get(j);
                 if (table.getType() != TableType.OLAP) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/StorageTypeCheckAction.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/StorageTypeCheckAction.java
index 5af38ba28b1900..fd98300045ec87 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/StorageTypeCheckAction.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/StorageTypeCheckAction.java
@@ -49,6 +49,7 @@
 import com.starrocks.http.IllegalArgException;
 import com.starrocks.privilege.AccessDeniedException;
 import com.starrocks.qe.ConnectContext;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.ast.UserIdentity;
 import com.starrocks.thrift.TStorageType;
 import io.netty.handler.codec.http.HttpMethod;
@@ -77,7 +78,7 @@ protected void executeWithoutPassword(BaseRequest request, BaseResponse response
             throw new DdlException("Parameter db is missing");
         }
 
-        Database db = globalStateMgr.getDb(dbName);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("Database " + dbName + " does not exist");
         }
@@ -86,7 +87,7 @@ protected void executeWithoutPassword(BaseRequest request, BaseResponse response
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            List<Table> tbls = db.getTables();
+            List<Table> tbls = GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId());
             for (Table tbl : tbls) {
                 if (tbl.getType() != TableType.OLAP) {
                     continue;
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/TableQueryPlanAction.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/TableQueryPlanAction.java
index 4c8b3a8a492bdd..1970aa086125c9 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/TableQueryPlanAction.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/TableQueryPlanAction.java
@@ -150,7 +150,7 @@ protected void executeWithoutPassword(BaseRequest request, BaseResponse response
             // check privilege for select, otherwise return HTTP 401
             Authorizer.checkTableAction(ConnectContext.get().getCurrentUserIdentity(), ConnectContext.get().getCurrentRoleIds(),
                     dbName, tableName, PrivilegeType.SELECT);
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
             if (db == null) {
                 throw new StarRocksHttpException(HttpResponseStatus.NOT_FOUND,
                         "Database [" + dbName + "] " + "does not exists");
@@ -159,7 +159,7 @@ protected void executeWithoutPassword(BaseRequest request, BaseResponse response
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.READ);
             try {
-                Table table = db.getTable(tableName);
+                Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
                 if (table == null) {
                     throw new StarRocksHttpException(HttpResponseStatus.NOT_FOUND,
                             "Table [" + tableName + "] " + "does not exists");
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/TableRowCountAction.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/TableRowCountAction.java
index cdd6279770a3fc..d6ac4fd33bf478 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/TableRowCountAction.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/TableRowCountAction.java
@@ -92,7 +92,7 @@ protected void executeWithoutPassword(BaseRequest request, BaseResponse response
             // check privilege for select, otherwise return HTTP 401
             Authorizer.checkTableAction(ConnectContext.get().getCurrentUserIdentity(), ConnectContext.get().getCurrentRoleIds(),
                     dbName, tableName, PrivilegeType.SELECT);
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
             if (db == null) {
                 throw new StarRocksHttpException(HttpResponseStatus.NOT_FOUND,
                         "Database [" + dbName + "] " + "does not exists");
@@ -100,7 +100,7 @@ protected void executeWithoutPassword(BaseRequest request, BaseResponse response
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.WRITE);
             try {
-                Table table = db.getTable(tableName);
+                Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
                 if (table == null) {
                     throw new StarRocksHttpException(HttpResponseStatus.NOT_FOUND,
                             "Table [" + tableName + "] " + "does not exists");
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/TableSchemaAction.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/TableSchemaAction.java
index 23433556c2733f..12c221213a8b24 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/TableSchemaAction.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/TableSchemaAction.java
@@ -94,7 +94,7 @@ protected void executeWithoutPassword(BaseRequest request, BaseResponse response
             Authorizer.checkTableAction(ConnectContext.get().getCurrentUserIdentity(), ConnectContext.get().getCurrentRoleIds(),
                     dbName, tableName, PrivilegeType.SELECT);
 
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
             if (db == null) {
                 throw new StarRocksHttpException(HttpResponseStatus.NOT_FOUND,
                         "Database [" + dbName + "] " + "does not exists");
@@ -102,7 +102,7 @@ protected void executeWithoutPassword(BaseRequest request, BaseResponse response
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.READ);
             try {
-                Table table = db.getTable(tableName);
+                Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
                 if (table == null) {
                     throw new StarRocksHttpException(HttpResponseStatus.NOT_FOUND,
                             "Table [" + tableName + "] " + "does not exists");
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/TransactionLoadAction.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/TransactionLoadAction.java
index 4280c3467b4a22..af1024be49a33b 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/TransactionLoadAction.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/TransactionLoadAction.java
@@ -263,7 +263,7 @@ private TransactionOperationHandler getTxnOperationHandler(TransactionOperationP
 
         if (null == sourceType) {
             String dbName = params.getDbName();
-            Database db = Optional.ofNullable(GlobalStateMgr.getCurrentState().getDb(dbName))
+            Database db = Optional.ofNullable(GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName))
                     .orElseThrow(() -> new UserException(String.format("Database[%s] does not exist.", dbName)));
 
             TransactionState txnState = GlobalStateMgr.getCurrentState()
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/TriggerAction.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/TriggerAction.java
index 9cf6d32cc5cb28..43b49ea542ff35 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/TriggerAction.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/TriggerAction.java
@@ -78,7 +78,7 @@ public void executeWithoutPassword(BaseRequest request, BaseResponse response) {
             return;
         }
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             response.appendContent("Database[" + dbName + "] does not exist");
             writeResponse(request, response, HttpResponseStatus.BAD_REQUEST);
@@ -94,7 +94,7 @@ public void executeWithoutPassword(BaseRequest request, BaseResponse response) {
             locker.lockDatabase(db, LockType.READ);
             try {
                 if (!Strings.isNullOrEmpty(tableName)) {
-                    table = db.getTable(tableName);
+                    table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
                 }
 
                 if (table == null) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/transaction/BypassWriteTransactionHandler.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/transaction/BypassWriteTransactionHandler.java
index 8ea909e78fc881..101e531cf1bf11 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/transaction/BypassWriteTransactionHandler.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/transaction/BypassWriteTransactionHandler.java
@@ -68,14 +68,15 @@ public ResultWrapper handle(BaseRequest request, BaseResponse response) throws U
         Body requestBody = txnOperationParams.getBody();
         LOG.info("Handle bypass write transaction, label: {}", label);
 
-        Database db = Optional.ofNullable(GlobalStateMgr.getCurrentState().getDb(dbName))
+        Database db = Optional.ofNullable(GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName))
                 .orElseThrow(() -> new UserException(String.format("Database[%s] does not exist.", dbName)));
 
         TransactionResult result;
         switch (txnOperation) {
             case TXN_BEGIN:
-                Table table = Optional.ofNullable(db.getTable(tableName))
-                        .orElseThrow(() -> new UserException(
+                Table table = Optional.ofNullable(GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                        .getTable(db.getFullName(), tableName))
+                            .orElseThrow(() -> new UserException(
                                 String.format("Table[%s.%s] does not exist.", dbName, tableName)));
                 result = handleBeginTransaction(db, table, label, sourceType, timeoutMillis);
                 break;
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/transaction/TransactionWithoutChannelHandler.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/transaction/TransactionWithoutChannelHandler.java
index a52e7bb133098b..17e9b135633900 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/transaction/TransactionWithoutChannelHandler.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/transaction/TransactionWithoutChannelHandler.java
@@ -64,7 +64,7 @@ public ResultWrapper handle(BaseRequest request, BaseResponse response) throws U
         Long timeoutMillis = txnOperationParams.getTimeoutMillis();
         LOG.info("Handle transaction without channel info, label: {}", label);
 
-        Database db = Optional.ofNullable(GlobalStateMgr.getCurrentState().getDb(dbName))
+        Database db = Optional.ofNullable(GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName))
                 .orElseThrow(() -> new UserException(String.format("Database[%s] does not exist.", dbName)));
 
         TransactionResult result = null;
diff --git a/fe/fe-core/src/main/java/com/starrocks/http/rest/v2/TableBaseAction.java b/fe/fe-core/src/main/java/com/starrocks/http/rest/v2/TableBaseAction.java
index 81d725210a47df..33ad04484e3926 100644
--- a/fe/fe-core/src/main/java/com/starrocks/http/rest/v2/TableBaseAction.java
+++ b/fe/fe-core/src/main/java/com/starrocks/http/rest/v2/TableBaseAction.java
@@ -88,7 +88,7 @@ protected <T> T getAndApplyOlapTable(String catalogName,
                 PrivilegeType.SELECT
         );
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (null == db || !Optional.ofNullable(db.getCatalogName())
                 .orElse(DEFAULT_INTERNAL_CATALOG_NAME).equalsIgnoreCase(catalogName)) {
             throw new StarRocksHttpException(
@@ -99,7 +99,7 @@ protected <T> T getAndApplyOlapTable(String catalogName,
         final Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            Table table = db.getTable(tableName);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
             if (null == table) {
                 throw new StarRocksHttpException(
                         HttpResponseStatus.NOT_FOUND, ErrorCode.ERR_BAD_TABLE_ERROR.formatErrorMsg(tableName)
diff --git a/fe/fe-core/src/main/java/com/starrocks/journal/JournalEntity.java b/fe/fe-core/src/main/java/com/starrocks/journal/JournalEntity.java
index 56cba34ec30b3c..4c6b88aa02599d 100644
--- a/fe/fe-core/src/main/java/com/starrocks/journal/JournalEntity.java
+++ b/fe/fe-core/src/main/java/com/starrocks/journal/JournalEntity.java
@@ -1148,11 +1148,21 @@ public void readFields(DataInput in) throws IOException {
                 isRead = true;
                 break;
             }
+            case OperationType.OP_DELETE_REPLICATION_JOB: {
+                data = ReplicationJobLog.read(in);
+                isRead = true;
+                break;
+            }
             case OperationType.OP_RECOVER_PARTITION_VERSION: {
                 data = GsonUtils.GSON.fromJson(Text.readString(in), PartitionVersionRecoveryInfo.class);
                 isRead = true;
                 break;
             }
+            case OperationType.OP_ADD_KEY: {
+                data = new Text(Text.readBinary(in));
+                isRead = true;
+                break;
+            }
             default: {
                 if (Config.ignore_unknown_log_id) {
                     LOG.warn("UNKNOWN Operation Type {}", opCode);
diff --git a/fe/fe-core/src/main/java/com/starrocks/journal/bdbje/BDBEnvironment.java b/fe/fe-core/src/main/java/com/starrocks/journal/bdbje/BDBEnvironment.java
index 44f824ac2d964a..a69fd723f593c1 100644
--- a/fe/fe-core/src/main/java/com/starrocks/journal/bdbje/BDBEnvironment.java
+++ b/fe/fe-core/src/main/java/com/starrocks/journal/bdbje/BDBEnvironment.java
@@ -199,7 +199,7 @@ protected void initConfigs(boolean isElectable) throws JournalException {
         replicationConfig
                 .setConfigParam(ReplicationConfig.REPLICA_TIMEOUT, Config.bdbje_heartbeat_timeout_second + " s");
         replicationConfig
-                .setConfigParam(ReplicationConfig.FEEDER_TIMEOUT, (10 + Config.bdbje_heartbeat_timeout_second) + " s");
+                .setConfigParam(ReplicationConfig.FEEDER_TIMEOUT, Config.bdbje_heartbeat_timeout_second + " s");
         replicationConfig
                 .setConfigParam(ReplicationConfig.REPLAY_COST_PERCENT,
                         String.valueOf(Config.bdbje_replay_cost_percent));
diff --git a/fe/fe-core/src/main/java/com/starrocks/lake/LakeMaterializedView.java b/fe/fe-core/src/main/java/com/starrocks/lake/LakeMaterializedView.java
index 0e28580498d5d1..e9e87afbd38268 100644
--- a/fe/fe-core/src/main/java/com/starrocks/lake/LakeMaterializedView.java
+++ b/fe/fe-core/src/main/java/com/starrocks/lake/LakeMaterializedView.java
@@ -32,7 +32,6 @@
 import com.starrocks.common.util.PropertyAnalyzer;
 import com.starrocks.persist.gson.GsonUtils;
 import com.starrocks.server.GlobalStateMgr;
-import com.starrocks.server.StorageVolumeMgr;
 import com.starrocks.statistic.StatsConstants;
 import org.apache.logging.log4j.LogManager;
 import org.apache.logging.log4j.Logger;
@@ -155,7 +154,6 @@ protected void appendUniqueProperties(StringBuilder sb) {
         sb.append(storageProperties.get(PropertyAnalyzer.PROPERTIES_ENABLE_ASYNC_WRITE_BACK)).append("\"");
 
         // storage_volume
-        StorageVolumeMgr svm = GlobalStateMgr.getCurrentState().getStorageVolumeMgr();
         String volume = GlobalStateMgr.getCurrentState().getStorageVolumeMgr().getStorageVolumeNameOfTable(id);
         sb.append(StatsConstants.TABLE_PROPERTY_SEPARATOR).append(
                 PropertyAnalyzer.PROPERTIES_STORAGE_VOLUME).append("\" = \"").append(volume).append("\"");
diff --git a/fe/fe-core/src/main/java/com/starrocks/lake/StarMgrMetaSyncer.java b/fe/fe-core/src/main/java/com/starrocks/lake/StarMgrMetaSyncer.java
index 4f6417147d0485..59e931d5ca6662 100644
--- a/fe/fe-core/src/main/java/com/starrocks/lake/StarMgrMetaSyncer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/lake/StarMgrMetaSyncer.java
@@ -262,7 +262,7 @@ public int deleteUnusedWorker() {
     public void syncTableMetaAndColocationInfo() {
         List<Long> dbIds = GlobalStateMgr.getCurrentState().getLocalMetastore().getDbIds();
         for (Long dbId : dbIds) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 continue;
             }
@@ -270,7 +270,7 @@ public void syncTableMetaAndColocationInfo() {
                 continue;
             }
 
-            List<Table> tables = db.getTables();
+            List<Table> tables = GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId());
             for (Table table : tables) {
                 if (!table.isCloudNativeTableOrMaterializedView()) {
                     continue;
@@ -293,7 +293,7 @@ public boolean syncTableMetaInternal(Database db, OlapTable table, boolean force
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            if (db.getTable(table.getId()) == null) {
+            if (GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), table.getId()) == null) {
                 return false; // table might be dropped
             }
             GlobalStateMgr.getCurrentState().getLocalMetastore()
@@ -375,10 +375,10 @@ private void syncTableColocationInfo(Database db, OlapTable table) throws DdlExc
         locker.lockDatabase(db, LockType.WRITE);
         try {
             // check db and table again
-            if (GlobalStateMgr.getCurrentState().getDb(db.getId()) == null) {
+            if (GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(db.getId()) == null) {
                 return;
             }
-            if (db.getTable(table.getId()) == null) {
+            if (GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), table.getId()) == null) {
                 return;
             }
             GlobalStateMgr.getCurrentState().getColocateTableIndex().updateLakeTableColocationInfo(table, true /* isJoin */,
@@ -407,12 +407,12 @@ protected void runAfterCatalogReady() {
     }
 
     public void syncTableMeta(String dbName, String tableName, boolean forceDeleteData) throws DdlException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException(String.format("db %s does not exist.", dbName));
         }
 
-        Table table = db.getTable(tableName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         if (table == null) {
             throw new DdlException(String.format("table %s does not exist.", tableName));
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/lake/backup/LakeBackupJob.java b/fe/fe-core/src/main/java/com/starrocks/lake/backup/LakeBackupJob.java
index 6d2e737afed1f6..1004bb9d82490f 100644
--- a/fe/fe-core/src/main/java/com/starrocks/lake/backup/LakeBackupJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/lake/backup/LakeBackupJob.java
@@ -82,7 +82,7 @@ public LakeBackupJob(String label, long dbId, String dbName, List<TableRef> tabl
     protected void checkBackupTables(Database db) {
         for (TableRef tableRef : tableRefs) {
             String tblName = tableRef.getName().getTbl();
-            Table tbl = db.getTable(tblName);
+            Table tbl = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tblName);
             if (tbl == null) {
                 status = new Status(Status.ErrCode.NOT_FOUND, "table " + tblName + " does not exist");
                 return;
diff --git a/fe/fe-core/src/main/java/com/starrocks/lake/backup/LakeRestoreJob.java b/fe/fe-core/src/main/java/com/starrocks/lake/backup/LakeRestoreJob.java
index 86bc5dc5edda10..fde1e0fb051ca5 100644
--- a/fe/fe-core/src/main/java/com/starrocks/lake/backup/LakeRestoreJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/lake/backup/LakeRestoreJob.java
@@ -124,7 +124,8 @@ protected void prepareAndSendSnapshotTasks(Database db) {
         for (IdChain idChain : fileMapping.getMapping().keySet()) {
             LakeTablet tablet = null;
             try {
-                OlapTable tbl = (OlapTable) db.getTable(idChain.getTblId());
+                OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(db.getId(), idChain.getTblId());
                 Partition part = tbl.getPartition(idChain.getPartId());
                 MaterializedIndex index = part.getIndex(idChain.getIdxId());
                 tablet = (LakeTablet) index.getTablet(idChain.getTabletId());
@@ -154,7 +155,8 @@ protected void prepareDownloadTasks(List<SnapshotInfo> beSnapshotInfos, Database
         }
         request.restoreInfos = Lists.newArrayList();
         for (SnapshotInfo info : beSnapshotInfos) {
-            OlapTable tbl = (OlapTable) db.getTable(info.getTblId());
+            OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(db.getId(), info.getTblId());
             if (tbl == null) {
                 status = new Status(Status.ErrCode.NOT_FOUND, "restored table "
                         + info.getTblId() + " does not exist");
@@ -289,7 +291,8 @@ protected void modifyInvertedIndex(OlapTable restoreTbl, Partition restorePart)
     @Override
     protected void addRestoredPartitions(Database db, boolean modify) {
         for (Pair<String, Partition> entry : restoredPartitions) {
-            OlapTable localTbl = (OlapTable) db.getTable(entry.first);
+            OlapTable localTbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(db.getFullName(), entry.first);
             Partition restorePart = entry.second;
             OlapTable remoteTbl = (OlapTable) backupMeta.getTable(entry.first);
             RangePartitionInfo localPartitionInfo = (RangePartitionInfo) localTbl.getPartitionInfo();
diff --git a/fe/fe-core/src/main/java/com/starrocks/lake/compaction/CompactionScheduler.java b/fe/fe-core/src/main/java/com/starrocks/lake/compaction/CompactionScheduler.java
index 8128e156d3d692..3f318fbe224da5 100644
--- a/fe/fe-core/src/main/java/com/starrocks/lake/compaction/CompactionScheduler.java
+++ b/fe/fe-core/src/main/java/com/starrocks/lake/compaction/CompactionScheduler.java
@@ -256,7 +256,7 @@ private void cleanPartition() {
     }
 
     private CompactionJob startCompaction(PartitionIdentifier partitionIdentifier) {
-        Database db = stateMgr.getDb(partitionIdentifier.getDbId());
+        Database db = stateMgr.getLocalMetastore().getDb(partitionIdentifier.getDbId());
         if (db == null) {
             compactionManager.removePartition(partitionIdentifier);
             return null;
@@ -273,7 +273,8 @@ private CompactionJob startCompaction(PartitionIdentifier partitionIdentifier) {
 
         try {
             // lake table or lake materialized view
-            table = (OlapTable) db.getTable(partitionIdentifier.getTableId());
+            table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(db.getId(), partitionIdentifier.getTableId());
             // Compact a table of SCHEMA_CHANGE state does not make much sense, because the compacted data
             // will not be used after the schema change job finished.
             if (table != null && table.getState() == OlapTable.OlapTableState.SCHEMA_CHANGE) {
@@ -401,7 +402,7 @@ private void commitCompaction(PartitionIdentifier partition, CompactionJob job,
             throws UserException {
         List<TabletCommitInfo> commitInfoList = job.buildTabletCommitInfo();
 
-        Database db = stateMgr.getDb(partition.getDbId());
+        Database db = stateMgr.getLocalMetastore().getDb(partition.getDbId());
         if (db == null) {
             throw new MetaNotFoundException("database not exist");
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/lake/compaction/Quantiles.java b/fe/fe-core/src/main/java/com/starrocks/lake/compaction/Quantiles.java
index 7d3d0bd74ac20f..0a7b5a3ae79717 100644
--- a/fe/fe-core/src/main/java/com/starrocks/lake/compaction/Quantiles.java
+++ b/fe/fe-core/src/main/java/com/starrocks/lake/compaction/Quantiles.java
@@ -64,14 +64,15 @@ public double getMax() {
 
     @Override
     public int compareTo(@NotNull Quantiles o) {
-        if (avg != o.avg) {
-            return avg > o.avg ? 1 : -1;
+        // must use Double.compare to avoid float type precision issue
+        if (Double.compare(avg, o.avg) != 0) {
+            return Double.compare(avg, o.avg);
         }
-        if (p50 != o.p50) {
-            return p50 > o.p50 ? 1 : -1;
+        if (Double.compare(p50, o.p50) != 0) {
+            return Double.compare(p50, o.p50);
         }
-        if (max != o.max) {
-            return max > o.max ? 1 : -1;
+        if (Double.compare(max, o.max) != 0) {
+            return Double.compare(max, o.max);
         }
         return 0;
     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/lake/vacuum/AutovacuumDaemon.java b/fe/fe-core/src/main/java/com/starrocks/lake/vacuum/AutovacuumDaemon.java
index 61f3419a6b0aec..04037e61d52c25 100644
--- a/fe/fe-core/src/main/java/com/starrocks/lake/vacuum/AutovacuumDaemon.java
+++ b/fe/fe-core/src/main/java/com/starrocks/lake/vacuum/AutovacuumDaemon.java
@@ -70,13 +70,13 @@ public AutovacuumDaemon() {
     protected void runAfterCatalogReady() {
         List<Long> dbIds = GlobalStateMgr.getCurrentState().getLocalMetastore().getDbIds();
         for (Long dbId : dbIds) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 continue;
             }
 
             List<Table> tables = new ArrayList<>();
-            for (Table table : db.getTables()) {
+            for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                 if (table.isCloudNativeTableOrMaterializedView()) {
                     tables.add(table);
                 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/leader/LeaderImpl.java b/fe/fe-core/src/main/java/com/starrocks/leader/LeaderImpl.java
index a65d7ff1797a38..2d0b6c217bf786 100644
--- a/fe/fe-core/src/main/java/com/starrocks/leader/LeaderImpl.java
+++ b/fe/fe-core/src/main/java/com/starrocks/leader/LeaderImpl.java
@@ -473,12 +473,13 @@ private void finishUpdateSchemaTask(AgentTask task, TFinishTaskRequest request)
             long tableId = task.getTableId();
             long indexId = task.getIndexId();
             long backendId = task.getBackendId();
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db != null) {
                 Locker locker = new Locker();
                 locker.lockDatabase(db, LockType.READ);
                 try {
-                    OlapTable olapTable = (OlapTable) db.getTable(tableId);
+                    OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                .getTable(db.getId(), tableId);
                     if (olapTable != null) {
                         MaterializedIndexMeta indexMeta = olapTable.getIndexMetaByIndexId(indexId);
                         if (indexMeta != null) {
@@ -504,7 +505,7 @@ private void finishRealtimePush(AgentTask task, TFinishTaskRequest request) {
         long backendId = pushTask.getBackendId();
         long signature = task.getSignature();
         long transactionId = ((PushTask) task).getTransactionId();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             AgentTaskQueue.removeTask(backendId, TTaskType.REALTIME_PUSH, signature);
             return;
@@ -539,7 +540,7 @@ private void finishRealtimePush(AgentTask task, TFinishTaskRequest request) {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            OlapTable olapTable = (OlapTable) db.getTable(tableId);
+            OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (olapTable == null) {
                 throw new MetaNotFoundException("cannot find table[" + tableId + "] when push finished");
             }
@@ -771,7 +772,7 @@ private void finishStorageMigration(AgentTask task, TFinishTaskRequest request)
             }
 
             long dbId = tabletMeta.getDbId();
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 LOG.warn("db does not exist. db id: {}", dbId);
                 return;
@@ -892,7 +893,7 @@ public TGetTableMetaResponse getTableMeta(TGetTableMetaRequest request) {
         }
 
         // checkTblAuth(ConnectContext.get().getCurrentUserIdentity(), fullDbName, tableName, PrivPredicate.SELECT);
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             TStatus status = new TStatus(TStatusCode.NOT_FOUND);
             status.setError_msgs(Lists.newArrayList("db not exist"));
@@ -904,7 +905,7 @@ public TGetTableMetaResponse getTableMeta(TGetTableMetaRequest request) {
         try {
             locker.lockDatabase(db, LockType.READ);
 
-            Table table = db.getTable(tableName);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
             if (table == null) {
                 TStatus status = new TStatus(TStatusCode.NOT_FOUND);
                 status.setError_msgs(Lists.newArrayList("table " + tableName + " not exist"));
@@ -1214,7 +1215,7 @@ public TBeginRemoteTxnResponse beginRemoteTxn(TBeginRemoteTxnRequest request) th
             return response;
         }
 
-        Database db = globalStateMgr.getDb(request.getDb_id());
+        Database db = globalStateMgr.getLocalMetastore().getDb(request.getDb_id());
         if (db == null) {
             TStatus status = new TStatus(TStatusCode.NOT_FOUND);
             status.setError_msgs(Lists.newArrayList("db not exist"));
@@ -1273,7 +1274,7 @@ public TCommitRemoteTxnResponse commitRemoteTxn(TCommitRemoteTxnRequest request)
             return response;
         }
 
-        Database db = globalStateMgr.getDb(request.getDb_id());
+        Database db = globalStateMgr.getLocalMetastore().getDb(request.getDb_id());
         if (db == null) {
             TStatus status = new TStatus(TStatusCode.NOT_FOUND);
             status.setError_msgs(Lists.newArrayList("db not exist or already deleted"));
@@ -1339,7 +1340,7 @@ public TAbortRemoteTxnResponse abortRemoteTxn(TAbortRemoteTxnRequest request) th
             return response;
         }
 
-        Database db = globalStateMgr.getDb(request.getDb_id());
+        Database db = globalStateMgr.getLocalMetastore().getDb(request.getDb_id());
         if (db == null) {
             TStatus status = new TStatus(TStatusCode.NOT_FOUND);
             status.setError_msgs(Lists.newArrayList("db not exist or already deleted"));
diff --git a/fe/fe-core/src/main/java/com/starrocks/leader/ReportHandler.java b/fe/fe-core/src/main/java/com/starrocks/leader/ReportHandler.java
index f2d78bbe64a9e6..3c88d91e30e1ae 100644
--- a/fe/fe-core/src/main/java/com/starrocks/leader/ReportHandler.java
+++ b/fe/fe-core/src/main/java/com/starrocks/leader/ReportHandler.java
@@ -1229,11 +1229,12 @@ protected static void handleMigration(ListMultimap<TStorageMedium, Long> tabletM
                 }
 
                 // 3. There are some limitations for primary table, details in migratableTablet()
-                Database db = GlobalStateMgr.getCurrentState().getDb(tabletMeta.getDbId());
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(tabletMeta.getDbId());
                 if (db == null) {
                     continue;
                 }
-                OlapTable table = (OlapTable) db.getTable(tabletMeta.getTableId());
+                OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(db.getId(), tabletMeta.getTableId());
                 if (table == null) {
                     continue;
                 }
@@ -1292,7 +1293,7 @@ private static void handleRecoverTablet(ListMultimap<Long, Long> tabletRecoveryM
         BackendTabletsInfo backendTabletsInfo = new BackendTabletsInfo(backendId);
         backendTabletsInfo.setBad(true);
         for (Long dbId : tabletRecoveryMap.keySet()) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 continue;
             }
@@ -1308,7 +1309,8 @@ private static void handleRecoverTablet(ListMultimap<Long, Long> tabletRecoveryM
                     }
                     long tabletId = tabletIds.get(i);
                     long tableId = tabletMeta.getTableId();
-                    OlapTable olapTable = (OlapTable) db.getTable(tableId);
+                    OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                .getTable(db.getId(), tableId);
                     if (olapTable == null) {
                         continue;
                     }
@@ -1388,12 +1390,13 @@ private static void handleSetTabletInMemory(long backendId, Map<Long, TTablet> b
                 long partitionId =
                         tabletMeta != null ? tabletMeta.getPartitionId() : TabletInvertedIndex.NOT_EXIST_VALUE;
 
-                Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
                 if (db == null) {
                     continue;
                 }
 
-                OlapTable olapTable = (OlapTable) db.getTable(tableId);
+                OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(db.getId(), tableId);
                 if (olapTable == null) {
                     continue;
                 }
@@ -1449,12 +1452,13 @@ private static void handleSetTabletEnablePersistentIndex(long backendId, Map<Lon
                 long dbId = tabletMeta != null ? tabletMeta.getDbId() : TabletInvertedIndex.NOT_EXIST_VALUE;
                 long tableId = tabletMeta != null ? tabletMeta.getTableId() : TabletInvertedIndex.NOT_EXIST_VALUE;
 
-                Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
                 if (db == null) {
                     continue;
                 }
 
-                OlapTable olapTable = (OlapTable) db.getTable(tableId);
+                OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(db.getId(), tableId);
                 if (olapTable == null) {
                     continue;
                 }
@@ -1504,12 +1508,13 @@ private static void handleSetPrimaryIndexCacheExpireSec(long backendId, Map<Long
                 long dbId = tabletMeta != null ? tabletMeta.getDbId() : TabletInvertedIndex.NOT_EXIST_VALUE;
                 long tableId = tabletMeta != null ? tabletMeta.getTableId() : TabletInvertedIndex.NOT_EXIST_VALUE;
 
-                Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
                 if (db == null) {
                     continue;
                 }
 
-                OlapTable olapTable = (OlapTable) db.getTable(tableId);
+                OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(db.getId(), tableId);
                 if (olapTable == null) {
                     continue;
                 }
@@ -1564,12 +1569,13 @@ private static void handleUpdateTableSchema(long backendId, Map<Long, TTablet> b
                 long tableId = tabletMeta.getTableId();
                 long indexId = tabletMeta.getIndexId();
 
-                Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
                 if (db == null) {
                     continue;
                 }
 
-                OlapTable olapTable = (OlapTable) db.getTable(tableId);
+                OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(db.getId(), tableId);
                 if (olapTable == null) {
                     continue;
                 }
@@ -1611,12 +1617,12 @@ private static void handleUpdateTableSchema(long backendId, Map<Long, TTablet> b
             List<Long> tablets = cell.getValue();
             Long dbId = tableToDb.get(tableId);
 
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 continue;
             }
 
-            OlapTable olapTable = (OlapTable) db.getTable(tableId);
+            OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (olapTable == null) {
                 continue;
             }
@@ -1682,13 +1688,14 @@ private static void handleSetTabletBinlogConfig(long backendId, Map<Long, TTable
                 long dbId = tabletMeta != null ? tabletMeta.getDbId() : TabletInvertedIndex.NOT_EXIST_VALUE;
                 long tableId = tabletMeta != null ? tabletMeta.getTableId() : TabletInvertedIndex.NOT_EXIST_VALUE;
 
-                Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
                 if (db == null) {
                     continue;
                 }
 
                 boolean needToCheck = false;
-                OlapTable olapTable = (OlapTable) db.getTable(tableId);
+                OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(db.getId(), tableId);
                 if (olapTable == null) {
                     continue;
                 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/listener/LoadJobMVListener.java b/fe/fe-core/src/main/java/com/starrocks/listener/LoadJobMVListener.java
index a316c5d10954f1..36547a351eccee 100644
--- a/fe/fe-core/src/main/java/com/starrocks/listener/LoadJobMVListener.java
+++ b/fe/fe-core/src/main/java/com/starrocks/listener/LoadJobMVListener.java
@@ -100,7 +100,7 @@ private void triggerToRefreshRelatedMVs(TransactionState transactionState, boole
             return;
         }
         for (long tableId : transactionState.getTableIdList()) {
-            Table table = db.getTable(tableId);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (table == null) {
                 LOG.warn("failed to get transaction tableId {} when pending refresh.", tableId);
                 return;
@@ -141,7 +141,8 @@ private void doTriggerToRefreshRelatedMVs(Database db, Table table) throws DdlEx
         while (mvIdIterator.hasNext()) {
             MvId mvId = mvIdIterator.next();
             Database mvDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(mvId.getDbId());
-            MaterializedView materializedView = (MaterializedView) mvDb.getTable(mvId.getId());
+            MaterializedView materializedView = (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(mvId.getDbId(), mvId.getId());
             if (materializedView == null) {
                 LOG.warn("materialized view {} does not exists.", mvId.getId());
                 mvIdIterator.remove();
@@ -153,7 +154,7 @@ private void doTriggerToRefreshRelatedMVs(Database db, Table table) throws DdlEx
                                 "db:{}, mv:{}", table.getName(), mvDb.getFullName(),
                         materializedView.getName());
                 GlobalStateMgr.getCurrentState().getLocalMetastore().refreshMaterializedView(
-                        mvDb.getFullName(), mvDb.getTable(mvId.getId()).getName(), false, null,
+                        mvDb.getFullName(), materializedView.getName(), false, null,
                         Constants.TaskRunPriority.NORMAL.value(), true, false);
             }
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/listener/LoadJobStatsListener.java b/fe/fe-core/src/main/java/com/starrocks/listener/LoadJobStatsListener.java
index 31ee5a749dbb60..bef518cfd69bac 100644
--- a/fe/fe-core/src/main/java/com/starrocks/listener/LoadJobStatsListener.java
+++ b/fe/fe-core/src/main/java/com/starrocks/listener/LoadJobStatsListener.java
@@ -51,7 +51,7 @@ public void onLoadJobTransactionFinish(TransactionState transactionState) {
 
     @Override
     public void onDMLStmtJobTransactionFinish(TransactionState transactionState, Database db, Table table) {
-        StatisticUtils.triggerCollectionOnFirstLoad(transactionState, db, table, true);
+        StatisticUtils.triggerCollectionOnFirstLoad(transactionState, db, table, true, true);
     }
 
     @Override
@@ -80,12 +80,13 @@ private void onTransactionFinish(TransactionState transactionState, boolean sync
             List<Table> tables = transactionState.getIdToTableCommitInfos().values().stream()
                     .map(x -> x.getTableId())
                     .distinct()
-                    .map(db::getTable)
+                    .map(tableId -> GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(dbId, tableId))
                     .filter(Objects::nonNull)
                     .filter(t -> !t.isMaterializedView()) // skip mvs since its stats will be triggered after refresh
                     .collect(Collectors.toList());
             for (Table table : tables) {
-                StatisticUtils.triggerCollectionOnFirstLoad(transactionState, db, table, sync);
+                // stream load and broker load do not need lock
+                StatisticUtils.triggerCollectionOnFirstLoad(transactionState, db, table, sync, false);
             }
         } catch (Exception t) {
             LOG.warn("refresh mv after publish version failed:", DebugUtil.getStackTrace(t));
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/BrokerFileGroup.java b/fe/fe-core/src/main/java/com/starrocks/load/BrokerFileGroup.java
index dd0214f3be56b8..c539112f8f3335 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/BrokerFileGroup.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/BrokerFileGroup.java
@@ -59,6 +59,7 @@
 import com.starrocks.common.Pair;
 import com.starrocks.common.io.Text;
 import com.starrocks.common.io.Writable;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.ast.DataDescription;
 import com.starrocks.sql.ast.ImportColumnDesc;
 import com.starrocks.sql.ast.PartitionNames;
@@ -168,7 +169,8 @@ public void parseFormatProperties(DataDescription dataDescription) {
     // This will parse the input DataDescription to list for BrokerFileInfo
     public void parse(Database db, DataDescription dataDescription) throws DdlException {
         // tableId
-        Table table = db.getTable(dataDescription.getTableName());
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), dataDescription.getTableName());
         if (table == null) {
             throw new DdlException("Unknown table " + dataDescription.getTableName()
                     + " in database " + db.getOriginName());
@@ -237,7 +239,7 @@ public void parse(Database db, DataDescription dataDescription) throws DdlExcept
         if (dataDescription.isLoadFromTable()) {
             String srcTableName = dataDescription.getSrcTableName();
             // src table should be hive table
-            Table srcTable = db.getTable(srcTableName);
+            Table srcTable = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), srcTableName);
             if (srcTable == null) {
                 throw new DdlException("Unknown table " + srcTableName + " in database " + db.getOriginName());
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/DeleteMgr.java b/fe/fe-core/src/main/java/com/starrocks/load/DeleteMgr.java
index b814aa74188669..de472241445b85 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/DeleteMgr.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/DeleteMgr.java
@@ -176,12 +176,12 @@ public void process(DeleteStmt stmt) throws DdlException, QueryStateException {
         String dbName = stmt.getTableName().getDb();
         String tableName = stmt.getTableName().getTbl();
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("Db does not exist. name: " + dbName);
         }
 
-        Table table = db.getTable(tableName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         if (table == null) {
             throw new DdlException("Table does not exist. name: " + tableName);
         }
@@ -722,7 +722,7 @@ public void updatePredicate(Predicate predicate, Column column, int childNo) thr
     // show delete stmt
     public List<List<Comparable>> getDeleteInfosByDb(long dbId) {
         LinkedList<List<Comparable>> infos = new LinkedList<List<Comparable>>();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             return infos;
         }
@@ -816,11 +816,11 @@ public void replayMultiDelete(MultiDeleteInfo deleteInfo, GlobalStateMgr globalS
     }
 
     public void updateTableDeleteInfo(GlobalStateMgr globalStateMgr, long dbId, long tableId) {
-        Database db = globalStateMgr.getDb(dbId);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
         if (db == null) {
             return;
         }
-        Table table = db.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             return;
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/ExportJob.java b/fe/fe-core/src/main/java/com/starrocks/load/ExportJob.java
index d0e1a76fc22bf4..895746176ac947 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/ExportJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/ExportJob.java
@@ -240,7 +240,7 @@ public long getWarehouseId() {
 
     public void setJob(ExportStmt stmt) throws UserException {
         String dbName = stmt.getTblName().getDb();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("Database " + dbName + " does not exist");
         }
@@ -266,7 +266,8 @@ public void setJob(ExportStmt stmt) throws UserException {
         this.columnNames = stmt.getColumnNames();
 
         this.dbId = db.getId();
-        this.exportTable = db.getTable(stmt.getTblName().getTbl());
+        this.exportTable = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(db.getFullName(), stmt.getTblName().getTbl());
         if (exportTable == null) {
             throw new DdlException("Table " + stmt.getTblName().getTbl() + " does not exist");
         }
@@ -993,10 +994,10 @@ public void readFields(DataInput in) throws IOException {
         GlobalStateMgr stateMgr = GlobalStateMgr.getCurrentState();
         Database db = null;
         if (stateMgr.getMetadata() != null) {
-            db = stateMgr.getDb(dbId);
+            db = stateMgr.getLocalMetastore().getDb(dbId);
         }
         if (db != null) {
-            exportTable = db.getTable(tableId);
+            exportTable = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         }
 
         int count = in.readInt();
@@ -1086,10 +1087,10 @@ public void gsonPostProcess() throws IOException {
         GlobalStateMgr stateMgr = GlobalStateMgr.getCurrentState();
         Database db = null;
         if (stateMgr.getMetadata() != null) {
-            db = stateMgr.getDb(dbId);
+            db = stateMgr.getLocalMetastore().getDb(dbId);
         }
         if (db != null) {
-            exportTable = db.getTable(tableId);
+            exportTable = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         }
     }
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/ExportMgr.java b/fe/fe-core/src/main/java/com/starrocks/load/ExportMgr.java
index d2bc0986a7041f..b89765c7e47787 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/ExportMgr.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/ExportMgr.java
@@ -134,7 +134,7 @@ private ExportJob createJob(long jobId, UUID queryId, ExportStmt stmt) throws Ex
     }
 
     public ExportJob getExportJob(String dbName, UUID queryId) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         MetaUtils.checkDbNullAndReport(db, dbName);
         long dbId = db.getId();
         ExportJob matchedJob = null;
@@ -234,7 +234,7 @@ public List<List<String>> getExportJobInfosByIdOrState(
                 TableName tableName = job.getTableName();
                 if (tableName == null || tableName.getTbl().equals("DUMMY")) {
                     // forward compatibility, no table name is saved before
-                    Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+                    Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
                     if (db == null) {
                         continue;
                     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/InsertOverwriteJobRunner.java b/fe/fe-core/src/main/java/com/starrocks/load/InsertOverwriteJobRunner.java
index ea5b1ceac93f91..f8683c9ab83e23 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/InsertOverwriteJobRunner.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/InsertOverwriteJobRunner.java
@@ -215,7 +215,7 @@ private void prepare() throws Exception {
         }
         job.setTmpPartitionIds(tmpPartitionIds);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new DmlException("database id:%s does not exist", dbId);
         }
@@ -292,7 +292,7 @@ private void createPartitionByValue(InsertStmt insertStmt) {
         }
         GlobalStateMgr state = GlobalStateMgr.getCurrentState();
         String targetDb = insertStmt.getTableName().getDb();
-        Database db = state.getDb(targetDb);
+        Database db = state.getLocalMetastore().getDb(targetDb);
         List<Long> sourcePartitionIds = job.getSourcePartitionIds();
         try {
             AlterTableClauseAnalyzer analyzer = new AlterTableClauseAnalyzer(olapTable);
@@ -344,7 +344,7 @@ private void executeInsert() throws Exception {
 
     private void createTempPartitions() throws DdlException {
         long createPartitionStartTimestamp = System.currentTimeMillis();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new DmlException("database id:%s does not exist", dbId);
         }
@@ -366,7 +366,7 @@ private void createTempPartitions() throws DdlException {
     private void gc(boolean isReplay) {
         LOG.info("start to garbage collect");
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new DmlException("database id:%s does not exist", dbId);
         }
@@ -376,7 +376,7 @@ private void gc(boolean isReplay) {
         }
 
         try {
-            Table table = db.getTable(tableId);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (table == null) {
                 throw new DmlException("table:%d does not exist in database:%s", tableId, db.getFullName());
             }
@@ -416,7 +416,7 @@ private void gc(boolean isReplay) {
     }
 
     private void doCommit(boolean isReplay) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new DmlException("database id:%s does not exist", dbId);
         }
@@ -487,7 +487,7 @@ private void prepareInsert() {
         Preconditions.checkState(job.getJobState() == InsertOverwriteJobState.OVERWRITE_RUNNING);
         Preconditions.checkState(insertStmt != null);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new DmlException("database id:%s does not exist", dbId);
         }
@@ -522,7 +522,7 @@ private void prepareInsert() {
     }
 
     private OlapTable checkAndGetTable(Database db, long tableId) {
-        Table table = db.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             throw new DmlException("table:% does not exist in database:%s", tableId, db.getFullName());
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/Load.java b/fe/fe-core/src/main/java/com/starrocks/load/Load.java
index d17b711ee75329..b5c3bd5f874ae4 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/Load.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/Load.java
@@ -464,7 +464,7 @@ public static void initColumns(Table tbl, List<ImportColumnDesc> columnExprs,
         if (GlobalStateMgr.getCurrentState().getLocalMetastore().getIdToDb() != null) {
             for (Map.Entry<Long, Database> entry : GlobalStateMgr.getCurrentState().getLocalMetastore().getIdToDb().entrySet()) {
                 Database db = entry.getValue();
-                if (db.getTable(tbl.getId()) != null) {
+                if (GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tbl.getId()) != null) {
                     dbName = db.getFullName();
                 }
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/OlapDeleteJob.java b/fe/fe-core/src/main/java/com/starrocks/load/OlapDeleteJob.java
index 3d5429a6542505..ba270c19633749 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/OlapDeleteJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/OlapDeleteJob.java
@@ -298,7 +298,7 @@ public void run(DeleteStmt stmt, Database db, Table table, List<Partition> parti
      */
     public void checkAndUpdateQuorum() throws MetaNotFoundException {
         long dbId = deleteInfo.getDbId();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new MetaNotFoundException("can not find database " + dbId + " when commit delete");
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/PartitionUtils.java b/fe/fe-core/src/main/java/com/starrocks/load/PartitionUtils.java
index 85cd0456802ae6..ecacec80acc97a 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/PartitionUtils.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/PartitionUtils.java
@@ -66,7 +66,7 @@ public static void createAndAddTempPartitionsForTable(Database db, OlapTable tar
         boolean success = false;
         try {
             // should check whether targetTable exists
-            Table tmpTable = db.getTable(targetTable.getId());
+            Table tmpTable = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), targetTable.getId());
             if (tmpTable == null) {
                 throw new DdlException("create partition failed because target table does not exist");
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/BrokerLoadJob.java b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/BrokerLoadJob.java
index b6095eb56a92ca..92d4fbb44e0a0b 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/BrokerLoadJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/BrokerLoadJob.java
@@ -247,7 +247,7 @@ private void createLoadingTask(Database db, BrokerPendingTaskAttachment attachme
                 FileGroupAggKey aggKey = entry.getKey();
                 List<BrokerFileGroup> brokerFileGroups = entry.getValue();
                 long tableId = aggKey.getTableId();
-                OlapTable table = (OlapTable) db.getTable(tableId);
+                OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
                 if (table == null) {
                     LOG.warn(new LogBuilder(LogKey.LOAD_JOB, id)
                             .add("database_id", dbId)
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/BulkLoadJob.java b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/BulkLoadJob.java
index 62296bb18e675a..ff61e79b2dea24 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/BulkLoadJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/BulkLoadJob.java
@@ -127,7 +127,7 @@ public BulkLoadJob(long dbId, String label, OriginStatement originStmt) throws M
     public static BulkLoadJob fromLoadStmt(LoadStmt stmt, ConnectContext context) throws DdlException {
         // get db id
         String dbName = stmt.getLabel().getDbName();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new DdlException("Database[" + dbName + "] does not exist");
         }
@@ -184,7 +184,7 @@ private void checkAndSetDataSourceInfo(Database db, List<DataDescription> dataDe
     }
 
     private AuthorizationInfo gatherAuthInfo() throws MetaNotFoundException {
-        Database database = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (database == null) {
             throw new MetaNotFoundException("Database " + dbId + "has been deleted");
         }
@@ -194,7 +194,7 @@ private AuthorizationInfo gatherAuthInfo() throws MetaNotFoundException {
     @Override
     public Set<String> getTableNamesForShow() {
         Set<String> result = Sets.newHashSet();
-        Database database = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (database == null) {
             for (long tableId : fileGroupAggInfo.getAllTableIds()) {
                 result.add(String.valueOf(tableId));
@@ -202,7 +202,7 @@ public Set<String> getTableNamesForShow() {
             return result;
         }
         for (long tableId : fileGroupAggInfo.getAllTableIds()) {
-            Table table = database.getTable(tableId);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), tableId);
             if (table == null) {
                 result.add(String.valueOf(tableId));
             } else {
@@ -215,7 +215,7 @@ public Set<String> getTableNamesForShow() {
     @Override
     public Set<String> getTableNames(boolean noThrow) throws MetaNotFoundException {
         Set<String> result = Sets.newHashSet();
-        Database database = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (database == null) {
             if (noThrow) {
                 return result;
@@ -226,7 +226,7 @@ public Set<String> getTableNames(boolean noThrow) throws MetaNotFoundException {
         // The database will not be locked in here.
         // The getTable is a thread-safe method called without read lock of database
         for (long tableId : fileGroupAggInfo.getAllTableIds()) {
-            Table table = database.getTable(tableId);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), tableId);
             if (table == null) {
                 if (!noThrow) {
                     throw new MetaNotFoundException("Failed to find table " + tableId + " in db " + dbId);
@@ -287,7 +287,7 @@ public void analyze() {
             for (DataDescription dataDescription : stmt.getDataDescriptions()) {
                 dataDescription.analyzeWithoutCheckPriv();
             }
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db == null) {
                 throw new DdlException("Database[" + dbId + "] does not exist");
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/InsertLoadJob.java b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/InsertLoadJob.java
index d50bfb50081058..536bbbc3396f9d 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/InsertLoadJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/InsertLoadJob.java
@@ -65,6 +65,7 @@
 import java.io.DataOutput;
 import java.io.IOException;
 import java.util.List;
+import java.util.Map;
 import java.util.Set;
 
 /**
@@ -152,7 +153,7 @@ public void setLoadFinishOrCancel(String failMsg, String trackingUrl) throws Use
     }
 
     public AuthorizationInfo gatherAuthInfo() throws MetaNotFoundException {
-        Database database = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (database == null) {
             throw new MetaNotFoundException("Database " + dbId + "has been deleted");
         }
@@ -191,13 +192,13 @@ public void updateProgress(TReportExecStatusParams params) {
 
     @Override
     public Set<String> getTableNamesForShow() {
-        Database database = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (database == null) {
             return Sets.newHashSet(String.valueOf(tableId));
         }
         // The database will not be locked in here.
         // The getTable is a thread-safe method called without read lock of database
-        Table table = database.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), tableId);
         if (table == null) {
             return Sets.newHashSet(String.valueOf(tableId));
         }
@@ -206,11 +207,11 @@ public Set<String> getTableNamesForShow() {
 
     @Override
     public Set<String> getTableNames(boolean noThrow) throws MetaNotFoundException {
-        Database database = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (database == null) {
             throw new MetaNotFoundException("Database " + dbId + "has been deleted");
         }
-        Table table = database.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), tableId);
         if (table == null) {
             if (noThrow) {
                 return Sets.newHashSet();
@@ -223,12 +224,12 @@ public Set<String> getTableNames(boolean noThrow) throws MetaNotFoundException {
 
     @Override
     public boolean hasTxn() {
-        Database database = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (database == null) {
             return true;
         }
 
-        Table table = database.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), tableId);
         if (table == null) {
             return true;
         }
@@ -268,6 +269,10 @@ public void setEstimateScanRow(long rows) {
         this.estimateScanRow = rows;
     }
 
+    public void updateLoadingStatus(Map<String, String> counters) {
+        this.loadingStatus.getCounters().putAll(counters);
+    }
+
     public void setTransactionId(long txnId) {
         this.transactionId = txnId;
     }
@@ -303,5 +308,4 @@ public void afterVisible(TransactionState txnState, boolean txnOperated) {
     @Override
     public void replayOnVisible(TransactionState txnState) {
     }
-
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadJob.java b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadJob.java
index 6fbf0a42d5bf47..ea285399808b74 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadJob.java
@@ -256,7 +256,7 @@ public void setId(long id) {
 
     public Database getDb() throws MetaNotFoundException {
         // get db
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new MetaNotFoundException("Database " + dbId + " already has been deleted");
         }
@@ -378,7 +378,7 @@ public boolean isCompleted() {
         return state == JobState.FINISHED || state == JobState.CANCELLED || state == JobState.UNKNOWN;
     }
 
-    protected void setJobProperties(Map<String, String> properties) throws DdlException {
+    public void setJobProperties(Map<String, String> properties) throws DdlException {
         // resource info
         if (ConnectContext.get() != null) {
             loadMemLimit = ConnectContext.get().getSessionVariable().getLoadMemLimit();
@@ -748,7 +748,7 @@ private void executeFinish() {
         idToTasks.clear();
     }
 
-    protected boolean checkDataQuality() {
+    public boolean checkDataQuality() {
         Map<String, String> counters = loadingStatus.getCounters();
         if (!counters.containsKey(DPP_NORMAL_ALL) || !counters.containsKey(DPP_ABNORMAL_ALL)) {
             return true;
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadLoadingTask.java b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadLoadingTask.java
index 26ce744d6d50f4..8e6f80760c02c5 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadLoadingTask.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadLoadingTask.java
@@ -301,7 +301,7 @@ private void checkMeta() throws LoadException {
             throw new LoadException(String.format("db: %s-%d has been dropped", db.getFullName(), db.getId()));
         }
 
-        if (database.getTable(table.getId()) == null) {
+        if (GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), table.getId()) == null) {
             throw new LoadException(String.format("table: %s-%d has been dropped from db: %s-%d",
                     table.getName(), table.getId(), db.getFullName(), db.getId()));
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadMgr.java b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadMgr.java
index 088471a7b3f13f..e077500673c9e3 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadMgr.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadMgr.java
@@ -154,7 +154,7 @@ public void createLoadJobFromStmt(LoadStmt stmt, ConnectContext context) throws
     }
 
     public void alterLoadJob(AlterLoadStmt stmt) throws DdlException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(stmt.getDbName());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(stmt.getDbName());
         if (db == null) {
             throw new DdlException("Db does not exist. name: " + stmt.getDbName());
         }
@@ -232,14 +232,12 @@ public void recordFinishedOrCacnelledLoadJob(long jobId, EtlJobType jobType, Str
         }
     }
 
-    public long registerLoadJob(String label, String dbName, long tableId, long txnId, String loadId, String user,
-                                EtlJobType jobType, long createTimestamp, long estimateScanRows,
-                                int estimateFileNum, long estimateFileSize,
-                                TLoadJobType type, long timeout, Coordinator coordinator)
-            throws UserException {
-
+    public InsertLoadJob registerInsertLoadJob(String label, String dbName, long tableId, long txnId, String loadId, String user,
+                                               EtlJobType jobType, long createTimestamp, long estimateScanRows,
+                                               int estimateFileNum, long estimateFileSize, TLoadJobType type, long timeout,
+                                               Coordinator coordinator) throws UserException {
         // get db id
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new MetaNotFoundException("Database[" + dbName + "] does not exist");
         }
@@ -260,11 +258,11 @@ public long registerLoadJob(String label, String dbName, long tableId, long txnI
         }
         // persistent
         GlobalStateMgr.getCurrentState().getEditLog().logCreateLoadJob(loadJob);
-        return loadJob.getId();
+        return loadJob;
     }
 
     public void cancelLoadJob(CancelLoadStmt stmt) throws DdlException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(stmt.getDbName());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(stmt.getDbName());
         if (db == null) {
             throw new DdlException("Db does not exist. name: " + stmt.getDbName());
         }
@@ -664,7 +662,7 @@ private void analyzeLoadJobs() {
 
     private Database checkDb(String dbName) throws DdlException {
         // get db
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             LOG.warn("Database {} does not exist", dbName);
             throw new DdlException("Database[" + dbName + "] does not exist");
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadsHistorySyncer.java b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadsHistorySyncer.java
index 092ecf1cb3d017..3f7cbad5634911 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadsHistorySyncer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/LoadsHistorySyncer.java
@@ -88,7 +88,7 @@ public LoadsHistorySyncer() {
     }
 
     public boolean checkDatabaseExists() {
-        return GlobalStateMgr.getCurrentState().getDb(LOADS_HISTORY_DB_NAME) != null;
+        return GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(LOADS_HISTORY_DB_NAME) != null;
     }
 
     public static void createTable() throws UserException {
@@ -98,9 +98,8 @@ public static void createTable() throws UserException {
 
     public static boolean correctTable() {
         int numBackends = GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo().getTotalBackendNumber();
-        int replica = GlobalStateMgr.getCurrentState()
-                .mayGetDb(LOADS_HISTORY_DB_NAME)
-                .flatMap(db -> db.mayGetTable(LOADS_HISTORY_TABLE_NAME))
+        int replica = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .mayGetTable(LOADS_HISTORY_DB_NAME, LOADS_HISTORY_TABLE_NAME)
                 .map(tbl -> ((OlapTable) tbl).getPartitionInfo().getMinReplicationNum())
                 .orElse((short) 1);
         if (numBackends < 3) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/SparkLoadJob.java b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/SparkLoadJob.java
index ba1a61624dd433..df06da905f6462 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/SparkLoadJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/SparkLoadJob.java
@@ -193,7 +193,7 @@ public SparkLoadJob(long dbId, String label, ResourceDesc resourceDesc, OriginSt
     }
 
     @Override
-    protected void setJobProperties(Map<String, String> properties) throws DdlException {
+    public void setJobProperties(Map<String, String> properties) throws DdlException {
         super.setJobProperties(properties);
 
         if (properties != null && properties.containsKey(LoadStmt.SPARK_LOAD_SUBMIT_TIMEOUT)) {
@@ -492,7 +492,8 @@ private Set<Long> submitPushTasks() throws UserException {
 
                 for (Map.Entry<Long, Set<Long>> entry : tableToLoadPartitions.entrySet()) {
                     long tableId = entry.getKey();
-                    OlapTable table = (OlapTable) db.getTable(tableId);
+                    OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                .getTable(db.getId(), tableId);
                     if (table == null) {
                         LOG.warn("table does not exist. id: {}", tableId);
                         continue;
@@ -821,7 +822,7 @@ private void clearJob() {
     public void afterVisible(TransactionState txnState, boolean txnOperated) {
         super.afterVisible(txnState, txnOperated);
         // collect table-level metrics after spark load job finished
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (null == db) {
             return;
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/SparkLoadPendingTask.java b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/SparkLoadPendingTask.java
index f8382cb4534d5a..64b5078ed6e816 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/loadv2/SparkLoadPendingTask.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/loadv2/SparkLoadPendingTask.java
@@ -156,7 +156,7 @@ public void init() throws LoadException {
     }
 
     private void createEtlJobConf() throws LoadException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new LoadException("db does not exist. id: " + dbId);
         }
@@ -173,7 +173,7 @@ private void createEtlJobConf() throws LoadException {
                 FileGroupAggKey aggKey = entry.getKey();
                 long tableId = aggKey.getTableId();
 
-                OlapTable table = (OlapTable) db.getTable(tableId);
+                OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
                 if (table == null) {
                     throw new LoadException("table does not exist. id: " + tableId);
                 }
@@ -224,7 +224,7 @@ private void prepareTablePartitionInfos(Database db, Map<Long, Set<Long>> tableI
                 continue;
             }
 
-            OlapTable table = (OlapTable) db.getTable(tableId);
+            OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (table == null) {
                 throw new LoadException("table does not exist. id: " + tableId);
             }
@@ -571,7 +571,8 @@ private EtlFileGroup createEtlFileGroup(BrokerFileGroup fileGroup, Set<Long> tab
         Map<String, String> hiveTableProperties = Maps.newHashMap();
         if (fileGroup.isLoadFromTable()) {
             long srcTableId = fileGroup.getSrcTableId();
-            HiveTable srcHiveTable = (HiveTable) db.getTable(srcTableId);
+            HiveTable srcHiveTable = (HiveTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(db.getId(), srcTableId);
             if (srcHiveTable == null) {
                 throw new LoadException("table does not exist. id: " + srcTableId);
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/pipe/Pipe.java b/fe/fe-core/src/main/java/com/starrocks/load/pipe/Pipe.java
index aea2bc317f99fe..fd9b326a0c288a 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/pipe/Pipe.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/pipe/Pipe.java
@@ -133,7 +133,7 @@ protected Pipe(PipeId id, String name, TableName targetTable, FilePipeSource sou
 
     public static Pipe fromStatement(long id, CreatePipeStmt stmt) {
         PipeName pipeName = stmt.getPipeName();
-        long dbId = GlobalStateMgr.getCurrentState().getDb(pipeName.getDbName()).getId();
+        long dbId = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(pipeName.getDbName()).getId();
         PipeId pipeId = new PipeId(dbId, id);
         Pipe res = new Pipe(pipeId, pipeName.getPipeName(), stmt.getTargetTable(), stmt.getDataSource(),
                 stmt.getInsertSql());
@@ -314,7 +314,7 @@ private void buildNewTasks() {
             long taskId = GlobalStateMgr.getCurrentState().getNextId();
             PipeId pipeId = getPipeId();
             String uniqueName = PipeTaskDesc.genUniqueTaskName(getName(), taskId, 0);
-            String dbName = GlobalStateMgr.getCurrentState().mayGetDb(pipeId.getDbId())
+            String dbName = GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetDb(pipeId.getDbId())
                     .map(Database::getOriginName)
                     .orElseThrow(() -> ErrorReport.buildSemanticException(ErrorCode.ERR_BAD_DB_ERROR));
             String sqlTask = FilePipeSource.buildInsertSql(this, piece, uniqueName);
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/pipe/PipeManager.java b/fe/fe-core/src/main/java/com/starrocks/load/pipe/PipeManager.java
index af6e39063c30bc..f17b8cc9f25e50 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/pipe/PipeManager.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/pipe/PipeManager.java
@@ -184,7 +184,7 @@ protected void updatePipe(Pipe pipe) {
     }
 
     private Pair<Long, String> resolvePipeNameUnlock(PipeName name) {
-        long dbId = GlobalStateMgr.getCurrentState().mayGetDb(name.getDbName())
+        long dbId = GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetDb(name.getDbName())
                 .map(Database::getId)
                 .orElseThrow(() -> ErrorReport.buildSemanticException(ErrorCode.ERR_NO_DB_ERROR));
         return Pair.create(dbId, name.getPipeName());
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/pipe/filelist/RepoCreator.java b/fe/fe-core/src/main/java/com/starrocks/load/pipe/filelist/RepoCreator.java
index bfcf8a0cbd7465..aea6240a646a2d 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/pipe/filelist/RepoCreator.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/pipe/filelist/RepoCreator.java
@@ -60,7 +60,7 @@ public void run() {
     }
 
     public boolean checkDatabaseExists() {
-        return GlobalStateMgr.getCurrentState().getDb(FileListTableRepo.FILE_LIST_DB_NAME) != null;
+        return GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(FileListTableRepo.FILE_LIST_DB_NAME) != null;
     }
 
     public static void createTable() throws UserException {
@@ -71,8 +71,7 @@ public static void createTable() throws UserException {
     public static boolean correctTable() {
         int numBackends = GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo().getTotalBackendNumber();
         int replica = GlobalStateMgr.getCurrentState()
-                .mayGetDb(FileListTableRepo.FILE_LIST_DB_NAME)
-                .flatMap(db -> db.mayGetTable(FileListTableRepo.FILE_LIST_TABLE_NAME))
+                .getLocalMetastore().mayGetTable(FileListTableRepo.FILE_LIST_DB_NAME, FileListTableRepo.FILE_LIST_TABLE_NAME)
                 .map(tbl -> ((OlapTable) tbl).getPartitionInfo().getMinReplicationNum())
                 .orElse((short) 1);
         if (numBackends < 3) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/routineload/KafkaRoutineLoadJob.java b/fe/fe-core/src/main/java/com/starrocks/load/routineload/KafkaRoutineLoadJob.java
index e169c80f71b2d4..32f7b092d22895 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/routineload/KafkaRoutineLoadJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/routineload/KafkaRoutineLoadJob.java
@@ -466,12 +466,12 @@ private List<Integer> getAllKafkaPartitions() throws UserException {
 
     public static KafkaRoutineLoadJob fromCreateStmt(CreateRoutineLoadStmt stmt) throws UserException {
         // check db and table
-        Database db = GlobalStateMgr.getCurrentState().getDb(stmt.getDBName());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(stmt.getDBName());
         if (db == null) {
             ErrorReport.reportDdlException(ErrorCode.ERR_BAD_DB_ERROR, stmt.getDBName());
         }
 
-        Table table = db.getTable(stmt.getTableName());
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), stmt.getTableName());
         if (table == null) {
             ErrorReport.reportDdlException(ErrorCode.ERR_BAD_TABLE_ERROR, stmt.getTableName());
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/routineload/KafkaTaskInfo.java b/fe/fe-core/src/main/java/com/starrocks/load/routineload/KafkaTaskInfo.java
index 2999f6727989a1..da141b9b6e6d37 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/routineload/KafkaTaskInfo.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/routineload/KafkaTaskInfo.java
@@ -48,7 +48,6 @@
 import com.starrocks.thrift.TFileFormatType;
 import com.starrocks.thrift.TKafkaLoadInfo;
 import com.starrocks.thrift.TLoadSourceType;
-import com.starrocks.thrift.TPlanFragment;
 import com.starrocks.thrift.TRoutineLoadTask;
 import com.starrocks.thrift.TUniqueId;
 import com.starrocks.transaction.DatabaseTransactionMgr;
@@ -172,12 +171,12 @@ public TRoutineLoadTask createRoutineLoadTask() throws UserException {
         tRoutineLoadTask.setId(queryId);
         tRoutineLoadTask.setJob_id(routineLoadJob.getId());
         tRoutineLoadTask.setTxn_id(txnId);
-        Database database = GlobalStateMgr.getCurrentState().getDb(routineLoadJob.getDbId());
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(routineLoadJob.getDbId());
         if (database == null) {
             throw new MetaNotFoundException("database " + routineLoadJob.getDbId() + " does not exist");
         }
         tRoutineLoadTask.setDb(database.getFullName());
-        Table tbl = database.getTable(routineLoadJob.getTableId());
+        Table tbl = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), routineLoadJob.getTableId());
         if (tbl == null) {
             throw new MetaNotFoundException("table " + routineLoadJob.getTableId() + " does not exist");
         }
@@ -246,8 +245,6 @@ private TExecPlanFragmentParams plan(RoutineLoadJob routineLoadJob) throws UserE
                     getStreamLoadMgr().getTaskByLabel(label);
             setStreamLoadTask(streamLoadTask);
         }
-        TPlanFragment tPlanFragment = tExecPlanFragmentParams.getFragment();
-        tPlanFragment.getOutput_sink().getOlap_table_sink().setTxn_id(txnId);
         return tExecPlanFragmentParams;
     }
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/routineload/PulsarRoutineLoadJob.java b/fe/fe-core/src/main/java/com/starrocks/load/routineload/PulsarRoutineLoadJob.java
index da08aa4367d8d5..f4d88d39f5d0ee 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/routineload/PulsarRoutineLoadJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/routineload/PulsarRoutineLoadJob.java
@@ -412,7 +412,7 @@ private List<String> getAllPulsarPartitions() throws UserException {
 
     public static PulsarRoutineLoadJob fromCreateStmt(CreateRoutineLoadStmt stmt) throws UserException {
         // check db and table
-        Database db = GlobalStateMgr.getCurrentState().getDb(stmt.getDBName());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(stmt.getDBName());
         if (db == null) {
             ErrorReport.reportDdlException(ErrorCode.ERR_BAD_DB_ERROR, stmt.getDBName());
         }
@@ -422,7 +422,7 @@ public static PulsarRoutineLoadJob fromCreateStmt(CreateRoutineLoadStmt stmt) th
         locker.lockDatabase(db, LockType.READ);
         try {
             unprotectedCheckMeta(db, stmt.getTableName(), stmt.getRoutineLoadDesc());
-            Table table = db.getTable(stmt.getTableName());
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), stmt.getTableName());
             Load.checkMergeCondition(stmt.getMergeConditionStr(), (OlapTable) table, table.getFullSchema(), false);
             tableId = table.getId();
         } finally {
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/routineload/PulsarTaskInfo.java b/fe/fe-core/src/main/java/com/starrocks/load/routineload/PulsarTaskInfo.java
index 0de023582e21d0..f4047bf1977319 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/routineload/PulsarTaskInfo.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/routineload/PulsarTaskInfo.java
@@ -28,7 +28,6 @@
 import com.starrocks.thrift.TExecPlanFragmentParams;
 import com.starrocks.thrift.TFileFormatType;
 import com.starrocks.thrift.TLoadSourceType;
-import com.starrocks.thrift.TPlanFragment;
 import com.starrocks.thrift.TPulsarLoadInfo;
 import com.starrocks.thrift.TRoutineLoadTask;
 import com.starrocks.thrift.TUniqueId;
@@ -110,12 +109,12 @@ public TRoutineLoadTask createRoutineLoadTask() throws UserException {
         tRoutineLoadTask.setId(queryId);
         tRoutineLoadTask.setJob_id(routineLoadJob.getId());
         tRoutineLoadTask.setTxn_id(txnId);
-        Database database = GlobalStateMgr.getCurrentState().getDb(routineLoadJob.getDbId());
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(routineLoadJob.getDbId());
         if (database == null) {
             throw new MetaNotFoundException("database " + routineLoadJob.getDbId() + " does not exist");
         }
         tRoutineLoadTask.setDb(database.getFullName());
-        Table tbl = database.getTable(routineLoadJob.getTableId());
+        Table tbl = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), routineLoadJob.getTableId());
         if (tbl == null) {
             throw new MetaNotFoundException("table " + routineLoadJob.getTableId() + " does not exist");
         }
@@ -175,8 +174,6 @@ private TExecPlanFragmentParams plan(RoutineLoadJob routineLoadJob) throws UserE
         TUniqueId loadId = new TUniqueId(id.getMostSignificantBits(), id.getLeastSignificantBits());
         // plan for each task, in case table has change(rollup or schema change)
         TExecPlanFragmentParams tExecPlanFragmentParams = routineLoadJob.plan(loadId, txnId, label);
-        TPlanFragment tPlanFragment = tExecPlanFragmentParams.getFragment();
-        tPlanFragment.getOutput_sink().getOlap_table_sink().setTxn_id(txnId);
         return tExecPlanFragmentParams;
     }
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/routineload/RoutineLoadJob.java b/fe/fe-core/src/main/java/com/starrocks/load/routineload/RoutineLoadJob.java
index d6929d5e995723..ac5c4c5e590e69 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/routineload/RoutineLoadJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/routineload/RoutineLoadJob.java
@@ -512,7 +512,7 @@ public void clearOtherMsg() {
     }
 
     public String getDbFullName() throws MetaNotFoundException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new MetaNotFoundException("Database " + dbId + "has been deleted");
         }
@@ -524,11 +524,11 @@ public long getTableId() {
     }
 
     public String getTableName() throws MetaNotFoundException {
-        Database database = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (database == null) {
             throw new MetaNotFoundException("Database " + dbId + "has been deleted");
         }
-        Table table = database.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), tableId);
         if (table == null) {
             throw new MetaNotFoundException("Failed to find table " + tableId + " in db " + dbId);
         }
@@ -856,12 +856,12 @@ private Coordinator.Factory getCoordinatorFactory() {
     }
 
     public TExecPlanFragmentParams plan(TUniqueId loadId, long txnId, String label) throws UserException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new MetaNotFoundException("db " + dbId + " does not exist");
         }
 
-        Table table = db.getTable(this.tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), this.tableId);
         if (table == null) {
             throw new MetaNotFoundException("table " + this.tableId + " does not exist");
         }
@@ -1287,7 +1287,7 @@ private void executeTaskOnTxnStatusChanged(RoutineLoadTaskInfo routineLoadTaskIn
 
     protected static void unprotectedCheckMeta(Database db, String tblName, RoutineLoadDesc routineLoadDesc)
             throws UserException {
-        Table table = db.getTable(tblName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tblName);
 
         if (table instanceof MaterializedView) {
             throw new AnalysisException(String.format(
@@ -1421,7 +1421,7 @@ private void clearTasks() {
 
     public void update() throws UserException {
         // check if db and table exist
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             LOG.warn(new LogBuilder(LogKey.ROUTINE_LOAD_JOB, id)
                     .add("db_id", dbId)
@@ -1440,7 +1440,7 @@ public void update() throws UserException {
         }
 
         // check table belong to database
-        Table table = db.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             LOG.warn(new LogBuilder(LogKey.ROUTINE_LOAD_JOB, id).add("db_id", dbId)
                     .add("table_id", tableId)
@@ -1495,13 +1495,13 @@ protected abstract boolean checkCommitInfo(RLTaskTxnCommitAttachment rlTaskTxnCo
     protected abstract String getStatistic();
 
     public List<String> getShowInfo() {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         Table tbl = null;
         if (db != null) {
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.READ);
             try {
-                tbl = db.getTable(tableId);
+                tbl = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             } finally {
                 locker.unLockDatabase(db, LockType.READ);
             }
@@ -1585,7 +1585,7 @@ public List<List<String>> getTasksShowInfo() {
     }
 
     public List<String> getShowStatistic() {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         readLock();
         try {
             List<String> row = Lists.newArrayList();
@@ -2000,13 +2000,13 @@ public void gsonPostProcess() throws IOException {
     }
 
     public TRoutineLoadJobInfo toThrift() {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         Table tbl = null;
         if (db != null) {
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.READ);
             try {
-                tbl = db.getTable(tableId);
+                tbl = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             } finally {
                 locker.unLockDatabase(db, LockType.READ);
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/routineload/RoutineLoadMgr.java b/fe/fe-core/src/main/java/com/starrocks/load/routineload/RoutineLoadMgr.java
index 48a3578493741a..7b41156b3325d5 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/routineload/RoutineLoadMgr.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/routineload/RoutineLoadMgr.java
@@ -508,7 +508,7 @@ public List<RoutineLoadJob> getJob(String dbFullName, String jobName, boolean in
                 sortRoutineLoadJob(result);
             } else {
                 long dbId = 0L;
-                Database database = GlobalStateMgr.getCurrentState().getDb(dbFullName);
+                Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbFullName);
                 if (database == null) {
                     throw new MetaNotFoundException("failed to find database by dbFullName " + dbFullName);
                 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/streamload/StreamLoadMgr.java b/fe/fe-core/src/main/java/com/starrocks/load/streamload/StreamLoadMgr.java
index 6ec158077016a5..e1b31b4e41eb88 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/streamload/StreamLoadMgr.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/streamload/StreamLoadMgr.java
@@ -175,7 +175,7 @@ public StreamLoadTask createLoadTask(Database db, String tableName, String label
         locker.lockDatabase(db, LockType.READ);
         try {
             unprotectedCheckMeta(db, tableName);
-            table = db.getTable(tableName);
+            table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         } finally {
             locker.unLockDatabase(db, LockType.READ);
         }
@@ -192,7 +192,8 @@ public StreamLoadTask createLoadTaskWithoutLock(Database db, String tableName, S
             throws UserException {
         // init stream load task
         long id = GlobalStateMgr.getCurrentState().getNextId();
-        StreamLoadTask streamLoadTask = new StreamLoadTask(id, db, (OlapTable) db.getTable(tableName),
+        StreamLoadTask streamLoadTask = new StreamLoadTask(id, db,
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName),
                 label, user, clientIp, timeoutMillis, System.currentTimeMillis(), isRoutineLoad, warehouseId);
         return streamLoadTask;
     }
@@ -205,7 +206,7 @@ public StreamLoadTask createLoadTask(Database db, String tableName, String label
         locker.lockDatabase(db, LockType.READ);
         try {
             unprotectedCheckMeta(db, tableName);
-            table = db.getTable(tableName);
+            table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         } finally {
             locker.unLockDatabase(db, LockType.READ);
         }
@@ -223,7 +224,7 @@ public void unprotectedCheckMeta(Database db, String tblName)
             throw new AnalysisException("Table name must be specified when calling /begin/transaction/ first time");
         }
 
-        Table table = db.getTable(tblName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tblName);
         if (table == null) {
             ErrorReport.reportDdlException(ErrorCode.ERR_BAD_TABLE_ERROR, tblName);
         }
@@ -248,7 +249,7 @@ public void replayCreateLoadTask(StreamLoadTask loadJob) {
     }
 
     public Database checkDbName(String dbName) throws UserException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             LOG.warn("Database {} does not exist", dbName);
             throw new UserException("Database[" + dbName + "] does not exist");
@@ -502,7 +503,7 @@ public List<StreamLoadTask> getTask(String dbFullName, String label, boolean inc
                 }
 
                 long dbId = 0L;
-                Database database = GlobalStateMgr.getCurrentState().getDb(dbFullName);
+                Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbFullName);
                 if (database == null) {
                     throw new MetaNotFoundException("failed to find database by dbFullName " + dbFullName);
                 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/load/streamload/StreamLoadTask.java b/fe/fe-core/src/main/java/com/starrocks/load/streamload/StreamLoadTask.java
index cbed0ff10ae770..378fbcfe3b5159 100644
--- a/fe/fe-core/src/main/java/com/starrocks/load/streamload/StreamLoadTask.java
+++ b/fe/fe-core/src/main/java/com/starrocks/load/streamload/StreamLoadTask.java
@@ -1254,14 +1254,14 @@ private void replayTxnAttachment(TransactionState txnState) {
     }
 
     public OlapTable getTable() throws MetaNotFoundException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new MetaNotFoundException("Database " + dbId + "has been deleted");
         }
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            OlapTable table = (OlapTable) db.getTable(tableId);
+            OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (table == null) {
                 throw new MetaNotFoundException("Failed to find table " + tableId + " in db " + dbId);
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/memory/InternalCatalogMemoryTracker.java b/fe/fe-core/src/main/java/com/starrocks/memory/InternalCatalogMemoryTracker.java
index 934267e3929989..1d3a51e4095325 100644
--- a/fe/fe-core/src/main/java/com/starrocks/memory/InternalCatalogMemoryTracker.java
+++ b/fe/fe-core/src/main/java/com/starrocks/memory/InternalCatalogMemoryTracker.java
@@ -34,7 +34,7 @@ public long estimateSize() {
         long estimateSize = 0L;
         List<Database> databases = new ArrayList<>(GlobalStateMgr.getCurrentState().getLocalMetastore().getIdToDb().values());
         for (Database database : databases) {
-            List<Table> tables = database.getTables();
+            List<Table> tables = GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(database.getId());
             for (Table table : tables) {
                 Collection<Partition> partitions = table.getPartitions();
                 Iterator<Partition> iterator = partitions.iterator();
@@ -51,7 +51,7 @@ public Map<String, Long> estimateCount() {
         long estimateCount = 0;
         List<Database> databases = new ArrayList<>(GlobalStateMgr.getCurrentState().getLocalMetastore().getIdToDb().values());
         for (Database database : databases) {
-            List<Table> tables = database.getTables();
+            List<Table> tables = GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(database.getId());
             for (Table table : tables) {
                 Collection<Partition> partitions = table.getPartitions();
                 estimateCount += partitions.size();
diff --git a/fe/fe-core/src/main/java/com/starrocks/metric/MaterializedViewMetricsEntity.java b/fe/fe-core/src/main/java/com/starrocks/metric/MaterializedViewMetricsEntity.java
index ba1437bb5e5eda..a1836c65bbc8f1 100644
--- a/fe/fe-core/src/main/java/com/starrocks/metric/MaterializedViewMetricsEntity.java
+++ b/fe/fe-core/src/main/java/com/starrocks/metric/MaterializedViewMetricsEntity.java
@@ -104,10 +104,10 @@ public boolean initDbAndTableName() {
         }
 
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
-        Database db = globalStateMgr.getDb(mvId.getDbId());
+        Database db = globalStateMgr.getLocalMetastore().getDb(mvId.getDbId());
         if (db != null) {
             dbNameOpt = Optional.of(db.getFullName());
-            Table table = db.getTable(mvId.getId());
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), mvId.getId());
             if (table != null) {
                 mvNameOpt = Optional.of(table.getName());
                 return true;
@@ -159,8 +159,9 @@ protected void initMaterializedViewMetrics() {
 
         // histogram metrics
         try {
-            Database db = GlobalStateMgr.getCurrentState().getDb(mvId.getDbId());
-            MaterializedView mv = (MaterializedView) db.getTable(mvId.getId());
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(mvId.getDbId());
+            MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(db.getId(), mvId.getId());
             histRefreshJobDuration = metricRegistry.histogram(MetricRegistry.name("mv_refresh_duration",
                         db.getFullName(), mv.getName()));
         } catch (Exception e) {
@@ -214,11 +215,11 @@ public Long getValue() {
                     "current materialized view's row count") {
             @Override
             public Long getValue() {
-                Database db = GlobalStateMgr.getCurrentState().getDb(mvId.getDbId());
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(mvId.getDbId());
                 if (db == null) {
                     return 0L;
                 }
-                Table table = db.getTable(mvId.getId());
+                Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), mvId.getId());
                 if (table == null || !table.isMaterializedView()) {
                     return 0L;
                 }
@@ -238,11 +239,11 @@ public Long getValue() {
                     "current materialized view's storage size") {
             @Override
             public Long getValue() {
-                Database db = GlobalStateMgr.getCurrentState().getDb(mvId.getDbId());
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(mvId.getDbId());
                 if (db == null) {
                     return 0L;
                 }
-                Table table = db.getTable(mvId.getId());
+                Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), mvId.getId());
                 if (table == null || !table.isMaterializedView()) {
                     return 0L;
                 }
@@ -262,11 +263,11 @@ public Long getValue() {
                     "current materialized view's inactive or not, 0: active, 1: inactive") {
             @Override
             public Integer getValue() {
-                Database db = GlobalStateMgr.getCurrentState().getDb(mvId.getDbId());
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(mvId.getDbId());
                 if (db == null) {
                     return 0;
                 }
-                Table table = db.getTable(mvId.getId());
+                Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), mvId.getId());
                 if (table == null || !table.isMaterializedView()) {
                     return 0;
                 }
@@ -284,11 +285,11 @@ public Integer getValue() {
                     "current materialized view's partition count, 0 if the materialized view is not partitioned") {
             @Override
             public Integer getValue() {
-                Database db = GlobalStateMgr.getCurrentState().getDb(mvId.getDbId());
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(mvId.getDbId());
                 if (db == null) {
                     return 0;
                 }
-                Table table = db.getTable(mvId.getId());
+                Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), mvId.getId());
                 if (table == null || !table.isMaterializedView()) {
                     return 0;
                 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/metric/MetricRepo.java b/fe/fe-core/src/main/java/com/starrocks/metric/MetricRepo.java
index 1b780dde354035..98873ff11b31c6 100644
--- a/fe/fe-core/src/main/java/com/starrocks/metric/MetricRepo.java
+++ b/fe/fe-core/src/main/java/com/starrocks/metric/MetricRepo.java
@@ -827,13 +827,13 @@ private static void collectTableMetrics(MetricVisitor visitor, boolean minifyTab
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
         List<String> dbNames = globalStateMgr.getLocalMetastore().listDbNames();
         for (String dbName : dbNames) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
             if (null == db) {
                 continue;
             }
 
             // NOTE: avoid holding database lock here, since we only read all tables, and immutable fields of table
-            for (Table table : db.getTables()) {
+            for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                 long tableId = table.getId();
                 String tableName = table.getName();
 
@@ -875,7 +875,7 @@ private static void collectDatabaseMetrics(MetricVisitor visitor) {
                 "database_num", MetricUnit.OPERATIONS, "count of database");
         int dbNum = 0;
         for (String dbName : dbNames) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
             if (null == db) {
                 continue;
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/mv/MVMetaVersionRepairer.java b/fe/fe-core/src/main/java/com/starrocks/mv/MVMetaVersionRepairer.java
index 8b8ebf8cd1111a..0555931da923a9 100644
--- a/fe/fe-core/src/main/java/com/starrocks/mv/MVMetaVersionRepairer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/mv/MVMetaVersionRepairer.java
@@ -62,7 +62,8 @@ public static void repairBaseTableVersionChanges(Database db, Table table,
                 LOG.warn("mv db {} not found", mvId.getDbId());
                 continue;
             }
-            MaterializedView mv = (MaterializedView) mvDb.getTable(mvId.getId());
+            MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(mvDb.getId(), mvId.getId());
             if (mv == null) {
                 LOG.warn("mv {} not found", mvId.getId());
                 continue;
diff --git a/fe/fe-core/src/main/java/com/starrocks/mv/MVRepairHandler.java b/fe/fe-core/src/main/java/com/starrocks/mv/MVRepairHandler.java
index a10450c6bb5a8f..e64b7c6ae41fa1 100644
--- a/fe/fe-core/src/main/java/com/starrocks/mv/MVRepairHandler.java
+++ b/fe/fe-core/src/main/java/com/starrocks/mv/MVRepairHandler.java
@@ -88,7 +88,7 @@ default void handleMVRepair(TransactionState transactionState) {
         }
 
         for (TableCommitInfo tableCommitInfo : transactionState.getIdToTableCommitInfos().values()) {
-            Table table = db.getTable(tableCommitInfo.getTableId());
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableCommitInfo.getTableId());
             if (table == null || !(table instanceof OlapTable) || table.getRelatedMaterializedViews().isEmpty()) {
                 continue;
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/mysql/nio/AcceptListener.java b/fe/fe-core/src/main/java/com/starrocks/mysql/nio/AcceptListener.java
index 7c70cbdbd78001..f47200bb1f9d7d 100644
--- a/fe/fe-core/src/main/java/com/starrocks/mysql/nio/AcceptListener.java
+++ b/fe/fe-core/src/main/java/com/starrocks/mysql/nio/AcceptListener.java
@@ -42,6 +42,7 @@
 import com.starrocks.qe.ConnectProcessor;
 import com.starrocks.qe.ConnectScheduler;
 import com.starrocks.server.GlobalStateMgr;
+import com.starrocks.sql.ast.UserIdentity;
 import org.apache.logging.log4j.LogManager;
 import org.apache.logging.log4j.Logger;
 import org.xnio.ChannelListener;
@@ -103,10 +104,12 @@ public void handleEvent(AcceptingChannel<StreamConnection> channel) {
                             // We place the set session environment code here, because we want to notify user if there
                             // are some errors when setting session environment.
                             // Unfortunately, the client cannot receive the message.
-                            UserProperty userProperty = context.getGlobalStateMgr().getAuthenticationMgr()
-                                    .getUserProperty(context.getCurrentUserIdentity().getUser());
-                            context.updateByUserProperty(userProperty);
-
+                            UserIdentity userIdentity = context.getCurrentUserIdentity();
+                            if (!userIdentity.isEphemeral()) {
+                                UserProperty userProperty = context.getGlobalStateMgr().getAuthenticationMgr()
+                                        .getUserProperty(userIdentity.getUser());
+                                context.updateByUserProperty(userProperty);
+                            }
                             MysqlProto.sendResponsePacket(context);
                         } else {
                             context.getState().setError(registerResult.second);
diff --git a/fe/fe-core/src/main/java/com/starrocks/persist/EditLog.java b/fe/fe-core/src/main/java/com/starrocks/persist/EditLog.java
index 78721ea99923d5..729372483ae2fa 100644
--- a/fe/fe-core/src/main/java/com/starrocks/persist/EditLog.java
+++ b/fe/fe-core/src/main/java/com/starrocks/persist/EditLog.java
@@ -228,7 +228,7 @@ public void loadJournal(GlobalStateMgr globalStateMgr, JournalEntity journal)
                 case OperationType.OP_DROP_TABLE:
                 case OperationType.OP_DROP_TABLE_V2: {
                     DropInfo info = (DropInfo) journal.getData();
-                    Database db = globalStateMgr.getDb(info.getDbId());
+                    Database db = globalStateMgr.getLocalMetastore().getDb(info.getDbId());
                     if (db == null) {
                         LOG.warn("failed to get db[{}]", info.getDbId());
                         break;
@@ -1185,11 +1185,22 @@ public void loadJournal(GlobalStateMgr globalStateMgr, JournalEntity journal)
                     globalStateMgr.getReplicationMgr().replayReplicationJob(replicationJobLog.getReplicationJob());
                     break;
                 }
+                case OperationType.OP_DELETE_REPLICATION_JOB: {
+                    ReplicationJobLog replicationJobLog = (ReplicationJobLog) journal.getData();
+                    globalStateMgr.getReplicationMgr().replayDeleteReplicationJob(replicationJobLog.getReplicationJob());
+                    break;
+                }
                 case OperationType.OP_RECOVER_PARTITION_VERSION: {
                     PartitionVersionRecoveryInfo info = (PartitionVersionRecoveryInfo) journal.getData();
                     GlobalStateMgr.getCurrentState().getMetaRecoveryDaemon().recoverPartitionVersion(info);
                     break;
                 }
+                case OperationType.OP_ADD_KEY: {
+                    Text keyJson = (Text) journal.getData();
+                    EncryptionKeyPB keyPB = GsonUtils.GSON.fromJson(keyJson.toString(), EncryptionKeyPB.class);
+                    GlobalStateMgr.getCurrentState().getKeyMgr().replayAddKey(keyPB);
+                    break;
+                }
                 default: {
                     if (Config.ignore_unknown_log_id) {
                         LOG.warn("UNKNOWN Operation Type {}", opCode);
@@ -1988,6 +1999,11 @@ public void logReplicationJob(ReplicationJob replicationJob) {
         logEdit(OperationType.OP_REPLICATION_JOB, replicationJobLog);
     }
 
+    public void logDeleteReplicationJob(ReplicationJob replicationJob) {
+        ReplicationJobLog replicationJobLog = new ReplicationJobLog(replicationJob);
+        logEdit(OperationType.OP_DELETE_REPLICATION_JOB, replicationJobLog);
+    }
+
     public void logColumnRename(ColumnRenameInfo columnRenameInfo) {
         logJsonObject(OperationType.OP_RENAME_COLUMN_V2, columnRenameInfo);
     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/persist/OperationType.java b/fe/fe-core/src/main/java/com/starrocks/persist/OperationType.java
index d515b5cfa4c6a6..e1999a2ca21c4b 100644
--- a/fe/fe-core/src/main/java/com/starrocks/persist/OperationType.java
+++ b/fe/fe-core/src/main/java/com/starrocks/persist/OperationType.java
@@ -926,6 +926,8 @@ public class OperationType {
     // Replication job
     @IgnorableOnReplayFailed
     public static final short OP_REPLICATION_JOB = 13500;
+    @IgnorableOnReplayFailed
+    public static final short OP_DELETE_REPLICATION_JOB = 13501;
 
     @IgnorableOnReplayFailed
     public static final short OP_DISABLE_TABLE_RECOVERY = 13510;
diff --git a/fe/fe-core/src/main/java/com/starrocks/planner/BinlogScanNode.java b/fe/fe-core/src/main/java/com/starrocks/planner/BinlogScanNode.java
index 892258a9a96c0f..37914df674e097 100644
--- a/fe/fe-core/src/main/java/com/starrocks/planner/BinlogScanNode.java
+++ b/fe/fe-core/src/main/java/com/starrocks/planner/BinlogScanNode.java
@@ -141,7 +141,7 @@ public void computeScanRanges() throws UserException {
                 if (dbId == -1) {
                     TabletMeta meta = invertedIndex.getTabletMeta(tablet.getId());
                     dbId = meta.getDbId();
-                    dbName = GlobalStateMgr.getCurrentState().getDb(dbId).getFullName();
+                    dbName = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId).getFullName();
                 }
 
                 long tabletId = tablet.getId();
diff --git a/fe/fe-core/src/main/java/com/starrocks/planner/HashJoinNode.java b/fe/fe-core/src/main/java/com/starrocks/planner/HashJoinNode.java
index 9c638b79a21534..1eed2253fc5ee2 100644
--- a/fe/fe-core/src/main/java/com/starrocks/planner/HashJoinNode.java
+++ b/fe/fe-core/src/main/java/com/starrocks/planner/HashJoinNode.java
@@ -41,7 +41,9 @@
 import com.starrocks.analysis.SlotId;
 import com.starrocks.analysis.SlotRef;
 import com.starrocks.analysis.TableRef;
+import com.starrocks.common.Config;
 import com.starrocks.qe.ConnectContext;
+import com.starrocks.qe.SessionVariable;
 import com.starrocks.thrift.TEqJoinCondition;
 import com.starrocks.thrift.THashJoinNode;
 import com.starrocks.thrift.TNormalHashJoinNode;
@@ -115,9 +117,23 @@ protected void toThrift(TPlanNode msg) {
             msg.hash_join_node.setBuild_runtime_filters(
                     RuntimeFilterDescription.toThriftRuntimeFilterDescriptions(buildRuntimeFilters));
         }
+        SessionVariable sv = ConnectContext.get().getSessionVariable();
+
         msg.hash_join_node.setLate_materialization(enableLateMaterialization);
-        msg.hash_join_node.setBuild_runtime_filters_from_planner(
-                ConnectContext.get().getSessionVariable().getEnableGlobalRuntimeFilter());
+        // predicate filtration rate
+        double predicateRate = getCardinality() / (double) getChild(0).getCardinality();
+        if (enableLateMaterialization) {
+            // If join late materialize is turned on higher filtering can lead to performance degradation.
+            if (predicateRate > Config.partition_hash_join_min_cardinality_rate) {
+                msg.hash_join_node.setEnable_partition_hash_join(sv.enablePartitionHashJoin());
+            } else {
+                msg.hash_join_node.setEnable_partition_hash_join(false);
+            }
+        } else {
+            msg.hash_join_node.setEnable_partition_hash_join(sv.enablePartitionHashJoin());
+        }
+        msg.hash_join_node.setBuild_runtime_filters_from_planner(sv.getEnableGlobalRuntimeFilter());
+
         if (partitionExprs != null) {
             msg.hash_join_node.setPartition_exprs(Expr.treesToThrift(partitionExprs));
         }
@@ -128,8 +144,7 @@ protected void toThrift(TPlanNode msg) {
         }
 
         if (getCanLocalShuffle()) {
-            msg.hash_join_node.setInterpolate_passthrough(
-                    ConnectContext.get().getSessionVariable().isHashJoinInterpolatePassthrough());
+            msg.hash_join_node.setInterpolate_passthrough(sv.isHashJoinInterpolatePassthrough());
         }
     }
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/planner/OlapTableSink.java b/fe/fe-core/src/main/java/com/starrocks/planner/OlapTableSink.java
index 83c2d195175ec1..8ecfee5c5db471 100644
--- a/fe/fe-core/src/main/java/com/starrocks/planner/OlapTableSink.java
+++ b/fe/fe-core/src/main/java/com/starrocks/planner/OlapTableSink.java
@@ -47,6 +47,7 @@
 import com.starrocks.analysis.TableName;
 import com.starrocks.analysis.TupleDescriptor;
 import com.starrocks.catalog.Column;
+import com.starrocks.catalog.ColumnId;
 import com.starrocks.catalog.Database;
 import com.starrocks.catalog.DistributionInfo;
 import com.starrocks.catalog.ExpressionRangePartitionInfo;
@@ -63,7 +64,6 @@
 import com.starrocks.catalog.Partition;
 import com.starrocks.catalog.PartitionKey;
 import com.starrocks.catalog.PartitionType;
-import com.starrocks.catalog.ColumnId;
 import com.starrocks.catalog.PhysicalPartition;
 import com.starrocks.catalog.RangePartitionInfo;
 import com.starrocks.catalog.Replica;
@@ -86,7 +86,7 @@
 import com.starrocks.sql.analyzer.RelationId;
 import com.starrocks.sql.analyzer.Scope;
 import com.starrocks.sql.analyzer.SelectAnalyzer;
-import com.starrocks.sql.common.MetaUtils;
+import com.starrocks.sql.analyzer.SemanticException;
 import com.starrocks.system.SystemInfoService;
 import com.starrocks.thrift.TColumn;
 import com.starrocks.thrift.TDataSink;
@@ -116,9 +116,9 @@
 import java.util.List;
 import java.util.Map;
 import java.util.Optional;
+import java.util.Set;
 import java.util.TreeMap;
 import java.util.TreeSet;
-import java.util.Set;
 import java.util.stream.Collectors;
 
 public class OlapTableSink extends DataSink {
@@ -201,7 +201,7 @@ public void init(TUniqueId loadId, long txnId, long dbId, long loadChannelTimeou
         tSink.setEnable_replicated_storage(enableReplicatedStorage);
         tSink.setAutomatic_bucket_size(automaticBucketSize);
         tSink.setEncryption_meta(GlobalStateMgr.getCurrentState().getKeyMgr().getCurrentKEKAsEncryptionMeta());
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db != null) {
             tSink.setDb_name(db.getFullName());
         }
@@ -385,7 +385,11 @@ public static TOlapTableSchemaParam createSchema(long dbId, OlapTable table, Tup
             indexSchema.setSchema_id(indexMeta.getSchemaId());
             schemaParam.addToIndexes(indexSchema);
             if (indexMeta.getWhereClause() != null) {
-                String dbName = MetaUtils.getDatabase(dbId).getFullName();
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
+                if (db == null) {
+                    throw new SemanticException("Database %s is not found", dbId);
+                }
+                String dbName = db.getFullName();
 
                 Map<String, SlotDescriptor> descMap = new TreeMap<>(String.CASE_INSENSITIVE_ORDER);
                 for (SlotDescriptor slot : tupleDescriptor.getSlots()) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/privilege/DbPEntryObject.java b/fe/fe-core/src/main/java/com/starrocks/privilege/DbPEntryObject.java
index d7bc98f5df3c9c..1e89a795f85041 100644
--- a/fe/fe-core/src/main/java/com/starrocks/privilege/DbPEntryObject.java
+++ b/fe/fe-core/src/main/java/com/starrocks/privilege/DbPEntryObject.java
@@ -199,7 +199,7 @@ public String toString() {
             return "ALL DATABASES";
         } else {
             if (CatalogMgr.isInternalCatalog(catalogId)) {
-                Database database = GlobalStateMgr.getCurrentState().getDb(Long.parseLong(uuid));
+                Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(Long.parseLong(uuid));
                 if (database == null) {
                     throw new MetaNotFoundException("Can't find database : " + uuid);
                 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/privilege/FunctionPEntryObject.java b/fe/fe-core/src/main/java/com/starrocks/privilege/FunctionPEntryObject.java
index ab7f69483ed8fc..677911af8ef287 100644
--- a/fe/fe-core/src/main/java/com/starrocks/privilege/FunctionPEntryObject.java
+++ b/fe/fe-core/src/main/java/com/starrocks/privilege/FunctionPEntryObject.java
@@ -158,7 +158,7 @@ public String toString() {
             if (databaseId == PrivilegeBuiltinConstants.ALL_DATABASE_ID) {
                 return "ALL FUNCTIONS IN ALL DATABASES";
             } else {
-                Database database = GlobalStateMgr.getCurrentState().getDb(databaseId);
+                Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(databaseId);
                 if (database == null) {
                     throw new MetaNotFoundException("Can't find database : " + databaseId);
                 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/privilege/NativeAccessController.java b/fe/fe-core/src/main/java/com/starrocks/privilege/NativeAccessController.java
index f4059c5c01f57e..2ead8329fd4082 100644
--- a/fe/fe-core/src/main/java/com/starrocks/privilege/NativeAccessController.java
+++ b/fe/fe-core/src/main/java/com/starrocks/privilege/NativeAccessController.java
@@ -20,10 +20,11 @@
 import com.starrocks.catalog.Database;
 import com.starrocks.catalog.Function;
 import com.starrocks.catalog.InternalCatalog;
+import com.starrocks.common.ErrorCode;
+import com.starrocks.common.ErrorReport;
 import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.ast.UserIdentity;
 import com.starrocks.sql.ast.pipe.PipeName;
-import com.starrocks.sql.common.MetaUtils;
 import org.apache.logging.log4j.LogManager;
 import org.apache.logging.log4j.Logger;
 
@@ -364,7 +365,11 @@ private static void checkAnyActionOnFunctionObject(UserIdentity currentUser, Set
         if (dbName == null) {
             databaseId = PrivilegeBuiltinConstants.GLOBAL_FUNCTION_DEFAULT_DATABASE_ID;
         } else {
-            Database database = MetaUtils.getDatabase(InternalCatalog.DEFAULT_INTERNAL_CATALOG_NAME, dbName);
+            Database database = GlobalStateMgr.getCurrentState().getMetadataMgr()
+                    .getDb(InternalCatalog.DEFAULT_INTERNAL_CATALOG_NAME, dbName);
+            if (database == null) {
+                ErrorReport.reportSemanticException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
+            }
             databaseId = database.getId();
         }
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/privilege/PipePEntryObject.java b/fe/fe-core/src/main/java/com/starrocks/privilege/PipePEntryObject.java
index cd5e9616ad5c94..dca02bca3c6f4a 100644
--- a/fe/fe-core/src/main/java/com/starrocks/privilege/PipePEntryObject.java
+++ b/fe/fe-core/src/main/java/com/starrocks/privilege/PipePEntryObject.java
@@ -56,7 +56,7 @@ public static PEntryObject generate(GlobalStateMgr mgr, List<String> tokens) thr
             pipeId = PrivilegeBuiltinConstants.ALL_PIPES_ID;
         } else {
             String dbName = tokens.get(0);
-            Database database = mgr.getDb(dbName);
+            Database database = mgr.getLocalMetastore().getDb(dbName);
             if (database == null) {
                 throw new PrivObjNotFoundException("cannot find db: " + dbName);
             }
@@ -129,7 +129,7 @@ public List<List<String>> expandObjectNames() {
                     .map(Pipe::getDbAndName)
                     .collect(Collectors.toList());
             for (Pair<Long, String> dbAndName : ListUtils.emptyIfNull(dbAndNames)) {
-                Optional<Database> db = GlobalStateMgr.getCurrentState().mayGetDb(dbAndName.first);
+                Optional<Database> db = GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetDb(dbAndName.first);
                 db.ifPresent(database -> objects.add(
                         Lists.newArrayList(InternalCatalog.DEFAULT_INTERNAL_CATALOG_NAME,
                                 database.getFullName(), dbAndName.second)));
@@ -206,7 +206,7 @@ public Optional<Database> getDatabase() {
                 return Optional.empty();
             }
             long dbId = Long.parseLong(getDbUUID());
-            return GlobalStateMgr.getCurrentState().mayGetDb(dbId);
+            return GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetDb(dbId);
         } catch (NumberFormatException e) {
             return Optional.empty();
         }
@@ -227,7 +227,7 @@ public String toString() {
             sb.append("ALL ").append("DATABASES");
         } else {
             String dbName;
-            Database database = GlobalStateMgr.getCurrentState().getDb(Long.parseLong(getDbUUID()));
+            Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(Long.parseLong(getDbUUID()));
             if (database == null) {
                 throw new MetaNotFoundException("Cannot find database : " + getDbUUID());
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/privilege/TablePEntryObject.java b/fe/fe-core/src/main/java/com/starrocks/privilege/TablePEntryObject.java
index 48ba74946c9047..0546d82b5ceab5 100644
--- a/fe/fe-core/src/main/java/com/starrocks/privilege/TablePEntryObject.java
+++ b/fe/fe-core/src/main/java/com/starrocks/privilege/TablePEntryObject.java
@@ -275,8 +275,8 @@ protected String toStringImpl(String plural) {
             } else {
                 String tblName = null;
                 if (CatalogMgr.isInternalCatalog(catalogId)) {
-                    Table table = GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(
-                            Long.parseLong(getDatabaseUUID()), Long.parseLong(getTableUUID()));
+                    Table table = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(Long.parseLong(getDatabaseUUID()), Long.parseLong(getTableUUID()));
                     if (table == null) {
                         throw new MetaNotFoundException("Cannot find table : " + tableUUID);
                     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/privilege/ranger/starrocks/RangerStarRocksAccessController.java b/fe/fe-core/src/main/java/com/starrocks/privilege/ranger/starrocks/RangerStarRocksAccessController.java
index 6bd4367db66916..608395af130cd6 100644
--- a/fe/fe-core/src/main/java/com/starrocks/privilege/ranger/starrocks/RangerStarRocksAccessController.java
+++ b/fe/fe-core/src/main/java/com/starrocks/privilege/ranger/starrocks/RangerStarRocksAccessController.java
@@ -129,7 +129,7 @@ public void checkAnyActionOnTable(UserIdentity currentUser, Set<Long> roleIds, T
     public void checkAnyActionOnAnyTable(UserIdentity currentUser, Set<Long> roleIds, String catalog, String db)
             throws AccessDeniedException {
         Database database = GlobalStateMgr.getCurrentState().getMetadataMgr().getDb(catalog, db);
-        for (Table table : database.getTables()) {
+        for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(database.getId())) {
             try {
                 hasPermission(
                         RangerStarRocksResource.builder()
@@ -187,7 +187,7 @@ public void checkAnyActionOnView(UserIdentity currentUser, Set<Long> roleIds, Ta
 
     @Override
     public void checkAnyActionOnAnyView(UserIdentity currentUser, Set<Long> roleIds, String db) throws AccessDeniedException {
-        Database database = GlobalStateMgr.getServingState().getDb(db);
+        Database database = GlobalStateMgr.getServingState().getLocalMetastore().getDb(db);
         for (Table table : database.getViews()) {
             try {
                 hasPermission(
@@ -235,7 +235,7 @@ public void checkAnyActionOnMaterializedView(UserIdentity currentUser, Set<Long>
     @Override
     public void checkAnyActionOnAnyMaterializedView(UserIdentity currentUser, Set<Long> roleIds, String db)
             throws AccessDeniedException {
-        Database database = GlobalStateMgr.getServingState().getDb(db);
+        Database database = GlobalStateMgr.getServingState().getLocalMetastore().getDb(db);
         for (Table table : database.getMaterializedViews()) {
             try {
                 hasPermission(
@@ -282,7 +282,7 @@ public void checkAnyActionOnFunction(UserIdentity currentUser, Set<Long> roleIds
 
     @Override
     public void checkAnyActionOnAnyFunction(UserIdentity currentUser, Set<Long> roleIds, String db) throws AccessDeniedException {
-        Database database = GlobalStateMgr.getServingState().getDb(db);
+        Database database = GlobalStateMgr.getServingState().getLocalMetastore().getDb(db);
         for (Function function : database.getFunctions()) {
             try {
                 hasPermission(
@@ -329,8 +329,8 @@ public void checkAnyActionOnGlobalFunction(UserIdentity currentUser, Set<Long> r
     @Override
     public void checkActionInDb(UserIdentity userIdentity, Set<Long> roleIds, String db, PrivilegeType privilegeType)
             throws AccessDeniedException {
-        Database database = GlobalStateMgr.getCurrentState().getDb(db);
-        for (Table table : database.getTables()) {
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(db);
+        for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(database.getId())) {
             if (table.isOlapView()) {
                 checkViewAction(userIdentity, roleIds, new TableName(database.getFullName(), table.getName()), privilegeType);
             } else if (table.isMaterializedView()) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/qe/AuditLogBuilder.java b/fe/fe-core/src/main/java/com/starrocks/qe/AuditLogBuilder.java
index 771efa39eb6008..1b5d49fabfc579 100644
--- a/fe/fe-core/src/main/java/com/starrocks/qe/AuditLogBuilder.java
+++ b/fe/fe-core/src/main/java/com/starrocks/qe/AuditLogBuilder.java
@@ -149,10 +149,19 @@ public void exec(AuditEvent event) {
                         logMap.put("bigQueryLogCPUSecondThreshold", event.bigQueryLogCPUSecondThreshold);
                         logMap.put("bigQueryLogScanBytesThreshold", event.bigQueryLogScanBytesThreshold);
                         logMap.put("bigQueryLogScanRowsThreshold", event.bigQueryLogScanRowsThreshold);
+                        AuditLog.getBigQueryAudit().log(objectMapper.writeValueAsString(logMap));
                     } else {
                         sb.append("|bigQueryLogCPUSecondThreshold=").append(event.bigQueryLogCPUSecondThreshold);
                         sb.append("|bigQueryLogScanBytesThreshold=").append(event.bigQueryLogScanBytesThreshold);
                         sb.append("|bigQueryLogScanRowsThreshold=").append(event.bigQueryLogScanRowsThreshold);
+                        AuditLog.getBigQueryAudit().log(sb.toString());
+                    }
+                }
+                if (Config.enable_qe_slow_log && queryTime > Config.qe_slow_log_ms) {
+                    if (Config.audit_log_json_format) {
+                        AuditLog.getSlowAudit().log(objectMapper.writeValueAsString(logMap));
+                    } else {
+                        AuditLog.getSlowAudit().log(sb.toString());
                     }
                 }
                 if (Config.audit_log_json_format) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/qe/DDLStmtExecutor.java b/fe/fe-core/src/main/java/com/starrocks/qe/DDLStmtExecutor.java
index 496ad7a34fc686..22be7914ee5b3e 100644
--- a/fe/fe-core/src/main/java/com/starrocks/qe/DDLStmtExecutor.java
+++ b/fe/fe-core/src/main/java/com/starrocks/qe/DDLStmtExecutor.java
@@ -243,7 +243,7 @@ public ShowResultSet visitCreateFunctionStatement(CreateFunctionStmt stmt, Conne
                             .getGlobalFunctionMgr()
                             .userAddFunction(stmt.getFunction(), stmt.shouldReplaceIfExists());
                 } else {
-                    Database db = context.getGlobalStateMgr().getDb(name.getDb());
+                    Database db = context.getGlobalStateMgr().getLocalMetastore().getDb(name.getDb());
                     if (db == null) {
                         ErrorReport.reportDdlException(ErrorCode.ERR_BAD_DB_ERROR, name.getDb());
                     }
@@ -260,7 +260,7 @@ public ShowResultSet visitDropFunctionStatement(DropFunctionStmt stmt, ConnectCo
                 if (name.isGlobalFunction()) {
                     context.getGlobalStateMgr().getGlobalFunctionMgr().userDropFunction(stmt.getFunctionSearchDesc());
                 } else {
-                    Database db = context.getGlobalStateMgr().getDb(name.getDb());
+                    Database db = context.getGlobalStateMgr().getLocalMetastore().getDb(name.getDb());
                     if (db == null) {
                         ErrorReport.reportDdlException(ErrorCode.ERR_BAD_DB_ERROR, name.getDb());
                     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/qe/ExecuteAsExecutor.java b/fe/fe-core/src/main/java/com/starrocks/qe/ExecuteAsExecutor.java
index ac656cc5d09c84..47d86306e1828f 100644
--- a/fe/fe-core/src/main/java/com/starrocks/qe/ExecuteAsExecutor.java
+++ b/fe/fe-core/src/main/java/com/starrocks/qe/ExecuteAsExecutor.java
@@ -44,8 +44,10 @@ public static void execute(ExecuteAsStmt stmt, ConnectContext ctx) {
         ctx.setCurrentUserIdentity(user);
         ctx.setCurrentRoleIds(user);
 
-        UserProperty userProperty = ctx.getGlobalStateMgr().getAuthenticationMgr()
-                .getUserProperty(user.getUser());
-        ctx.updateByUserProperty(userProperty);
+        if (!user.isEphemeral()) {
+            UserProperty userProperty = ctx.getGlobalStateMgr().getAuthenticationMgr()
+                    .getUserProperty(user.getUser());
+            ctx.updateByUserProperty(userProperty);
+        }
     }
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/qe/SessionVariable.java b/fe/fe-core/src/main/java/com/starrocks/qe/SessionVariable.java
index a2f5c9d3f6733d..684aec3fa23f91 100644
--- a/fe/fe-core/src/main/java/com/starrocks/qe/SessionVariable.java
+++ b/fe/fe-core/src/main/java/com/starrocks/qe/SessionVariable.java
@@ -188,6 +188,7 @@ public class SessionVariable implements Serializable, Writable, Cloneable {
     public static final String PARALLEL_FRAGMENT_EXEC_INSTANCE_NUM = "parallel_fragment_exec_instance_num";
     public static final String MAX_PARALLEL_SCAN_INSTANCE_NUM = "max_parallel_scan_instance_num";
     public static final String ENABLE_INSERT_STRICT = "enable_insert_strict";
+    public static final String INSERT_MAX_FILTER_RATIO = "insert_max_filter_ratio";
     public static final String ENABLE_SPILL = "enable_spill";
     public static final String ENABLE_SPILL_TO_REMOTE_STORAGE = "enable_spill_to_remote_storage";
     public static final String DISABLE_SPILL_TO_LOCAL_DISK = "disable_spill_to_local_disk";
@@ -292,6 +293,7 @@ public class SessionVariable implements Serializable, Writable, Cloneable {
             "enable_filter_unused_columns_in_scan_stage";
 
     public static final String JOIN_LATE_MATERIALIZATION = "join_late_materialization";
+    public static final String ENABLE_PARTITION_HASH_JOIN = "enable_partition_hash_join";
 
     public static final String ENABLE_PRUNE_COLUMN_AFTER_INDEX_FILTER =
             "enable_prune_column_after_index_filter";
@@ -1119,6 +1121,9 @@ public static MaterializedViewRewriteMode parse(String str) {
     @VariableMgr.VarAttr(name = ENABLE_INSERT_STRICT)
     private boolean enableInsertStrict = true;
 
+    @VariableMgr.VarAttr(name = INSERT_MAX_FILTER_RATIO)
+    private double insertMaxFilterRatio = 0;
+
     @VariableMgr.VarAttr(name = ENABLE_SPILL)
     private boolean enableSpill = false;
 
@@ -1239,6 +1244,9 @@ public static MaterializedViewRewriteMode parse(String str) {
     @VariableMgr.VarAttr(name = JOIN_LATE_MATERIALIZATION)
     private boolean joinLateMaterialization = false;
 
+    @VariableMgr.VarAttr(name = ENABLE_PARTITION_HASH_JOIN)
+    private boolean enablePartitionHashJoin = false;
+
     @VariableMgr.VarAttr(name = ENABLE_PRUNE_COLUMN_AFTER_INDEX_FILTER, flag = VariableMgr.INVISIBLE)
     private boolean enablePruneColumnAfterIndexFilter = true;
 
@@ -2707,6 +2715,14 @@ public void setEnableInsertStrict(boolean enableInsertStrict) {
         this.enableInsertStrict = enableInsertStrict;
     }
 
+    public double getInsertMaxFilterRatio() {
+        return insertMaxFilterRatio;
+    }
+
+    public void setInsertMaxFilterRatio(double insertMaxFilterRatio) {
+        this.insertMaxFilterRatio = insertMaxFilterRatio;
+    }
+
     public boolean isEnableSpill() {
         return enableSpill;
     }
@@ -2867,6 +2883,10 @@ public boolean isJoinLateMaterialization() {
         return joinLateMaterialization;
     }
 
+    public boolean enablePartitionHashJoin() {
+        return enablePartitionHashJoin;
+    }
+
     public void disableTrimOnlyFilteredColumnsInScanStage() {
         this.enableFilterUnusedColumnsInScanStage = false;
     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/qe/ShowExecutor.java b/fe/fe-core/src/main/java/com/starrocks/qe/ShowExecutor.java
index 9c35e77748b257..1a088ad6b4ffd3 100644
--- a/fe/fe-core/src/main/java/com/starrocks/qe/ShowExecutor.java
+++ b/fe/fe-core/src/main/java/com/starrocks/qe/ShowExecutor.java
@@ -301,7 +301,7 @@ public ShowResultSet visitShowStatement(ShowStmt statement, ConnectContext conte
         @Override
         public ShowResultSet visitShowMaterializedViewStatement(ShowMaterializedViewsStmt statement, ConnectContext context) {
             String dbName = statement.getDb();
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
             MetaUtils.checkDbNullAndReport(db, dbName);
 
             List<MaterializedView> materializedViews = Lists.newArrayList();
@@ -315,7 +315,7 @@ public ShowResultSet visitShowMaterializedViewStatement(ShowMaterializedViewsStm
                             CaseSensibility.TABLE.getCaseSensibility());
                 }
 
-                for (Table table : db.getTables()) {
+                for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                     if (table.isMaterializedView()) {
                         MaterializedView mvTable = (MaterializedView) table;
                         if (matcher != null && !matcher.match(mvTable.getName())) {
@@ -570,7 +570,7 @@ public ShowResultSet visitShowTemporaryTablesStatement(ShowTemporaryTableStmt st
         @Override
         public ShowResultSet visitShowTableStatusStatement(ShowTableStatusStmt statement, ConnectContext context) {
             List<List<String>> rows = Lists.newArrayList();
-            Database db = context.getGlobalStateMgr().getDb(statement.getDb());
+            Database db = context.getGlobalStateMgr().getLocalMetastore().getDb(statement.getDb());
             ZoneId currentTimeZoneId = TimeUtils.getTimeZone().toZoneId();
             if (db != null) {
                 Locker locker = new Locker();
@@ -581,7 +581,7 @@ public ShowResultSet visitShowTableStatusStatement(ShowTableStatusStmt statement
                         matcher = PatternMatcher.createMysqlPattern(statement.getPattern(),
                                 CaseSensibility.TABLE.getCaseSensibility());
                     }
-                    for (Table table : db.getTables()) {
+                    for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                         if (matcher != null && !matcher.match(table.getName())) {
                             continue;
                         }
@@ -664,7 +664,7 @@ public ShowResultSet visitShowCreateDbStatement(ShowCreateDbStmt statement, Conn
 
             Database db;
             if (Strings.isNullOrEmpty(catalogName) || CatalogMgr.isInternalCatalog(catalogName)) {
-                db = context.getGlobalStateMgr().getDb(dbName);
+                db = context.getGlobalStateMgr().getLocalMetastore().getDb(dbName);
             } else {
                 db = GlobalStateMgr.getCurrentState().getMetadataMgr().getDb(catalogName, dbName);
             }
@@ -697,7 +697,7 @@ public ShowResultSet visitShowCreateTableStatement(ShowCreateTableStmt statement
         }
 
         private ShowResultSet showCreateInternalCatalogTable(ShowCreateTableStmt showStmt, ConnectContext connectContext) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(showStmt.getDb());
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(showStmt.getDb());
             MetaUtils.checkDbNullAndReport(db, showStmt.getDb());
             List<List<String>> rows = Lists.newArrayList();
             Locker locker = new Locker();
@@ -710,7 +710,7 @@ private ShowResultSet showCreateInternalCatalogTable(ShowCreateTableStmt showStm
                     } else {
                         // For Sync Materialized View, it is a mv index inside OLAP table,
                         // so we can not get it from database.
-                        for (Table tbl : db.getTables()) {
+                        for (Table tbl : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                             if (tbl.getType() == Table.TableType.OLAP) {
                                 OlapTable olapTable = (OlapTable) tbl;
                                 List<MaterializedIndexMeta> visibleMaterializedViews =
@@ -899,7 +899,7 @@ public ShowResultSet visitShowFunctionsStatement(ShowFunctionsStmt statement, Co
             } else if (statement.getIsGlobal()) {
                 functions = context.getGlobalStateMgr().getGlobalFunctionMgr().getFunctions();
             } else {
-                Database db = context.getGlobalStateMgr().getDb(statement.getDbName());
+                Database db = context.getGlobalStateMgr().getLocalMetastore().getDb(statement.getDbName());
                 MetaUtils.checkDbNullAndReport(db, statement.getDbName());
                 functions = db.getFunctions();
             }
@@ -917,7 +917,7 @@ public ShowResultSet visitShowFunctionsStatement(ShowFunctionsStmt statement, Co
                             continue;
                         }
                     } else if (!statement.getIsBuiltin()) {
-                        Database db = context.getGlobalStateMgr().getDb(statement.getDbName());
+                        Database db = context.getGlobalStateMgr().getLocalMetastore().getDb(statement.getDbName());
                         try {
                             Authorizer.checkAnyActionOnFunction(context.getCurrentUserIdentity(),
                                     context.getCurrentRoleIds(), db.getFullName(), function);
@@ -1046,7 +1046,7 @@ public ShowResultSet visitShowLoadStatement(ShowLoadStmt statement, ConnectConte
             if (statement.isAll()) {
                 dbId = -1;
             } else {
-                Database db = globalStateMgr.getDb(statement.getDbName());
+                Database db = globalStateMgr.getLocalMetastore().getDb(statement.getDbName());
                 MetaUtils.checkDbNullAndReport(db, statement.getDbName());
                 dbId = db.getId();
             }
@@ -1300,7 +1300,7 @@ public ShowResultSet visitShowStreamLoadStatement(ShowStreamLoadStmt statement,
         @Override
         public ShowResultSet visitShowDeleteStatement(ShowDeleteStmt statement, ConnectContext context) {
             GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
-            Database db = globalStateMgr.getDb(statement.getDbName());
+            Database db = globalStateMgr.getLocalMetastore().getDb(statement.getDbName());
             MetaUtils.checkDbNullAndReport(db, statement.getDbName());
             long dbId = db.getId();
 
@@ -1363,7 +1363,7 @@ public ShowResultSet visitShowDataStatement(ShowDataStmt statement, ConnectConte
                     long totalReplicaCount = 0;
 
                     // sort by table name
-                    List<Table> tables = db.getTables();
+                    List<Table> tables = GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId());
                     SortedSet<Table> sortedTables = new TreeSet<>(Comparator.comparing(Table::getName));
 
                     for (Table table : tables) {
@@ -1566,7 +1566,7 @@ public ShowResultSet visitShowTabletStatement(ShowTabletStmt statement, ConnectC
 
                 // check real meta
                 do {
-                    Database db = globalStateMgr.getDb(dbId);
+                    Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
                     if (db == null) {
                         isSync = false;
                         break;
@@ -1576,7 +1576,7 @@ public ShowResultSet visitShowTabletStatement(ShowTabletStmt statement, ConnectC
                     Locker locker = new Locker();
                     locker.lockDatabase(db, LockType.READ);
                     try {
-                        Table table = db.getTable(tableId);
+                        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
                         if (!(table instanceof OlapTable)) {
                             isSync = false;
                             break;
@@ -1642,7 +1642,7 @@ public ShowResultSet visitShowTabletStatement(ShowTabletStmt statement, ConnectC
                         partitionId.toString(), indexId.toString(),
                         isSync.toString(), detailCmd));
             } else {
-                Database db = globalStateMgr.getDb(statement.getDbName());
+                Database db = globalStateMgr.getLocalMetastore().getDb(statement.getDbName());
                 MetaUtils.checkDbNullAndReport(db, statement.getDbName());
 
                 Locker locker = new Locker();
@@ -1760,7 +1760,7 @@ public ShowResultSet visitShowTabletStatement(ShowTabletStmt statement, ConnectC
 
         @Override
         public ShowResultSet visitShowBackupStatement(ShowBackupStmt statement, ConnectContext context) {
-            Database filterDb = GlobalStateMgr.getCurrentState().getDb(statement.getDbName());
+            Database filterDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(statement.getDbName());
             List<List<String>> infos = Lists.newArrayList();
             List<Database> dbs = Lists.newArrayList();
 
@@ -1806,7 +1806,7 @@ public ShowResultSet visitShowBackupStatement(ShowBackupStmt statement, ConnectC
 
         @Override
         public ShowResultSet visitShowRestoreStatement(ShowRestoreStmt statement, ConnectContext context) {
-            Database filterDb = GlobalStateMgr.getCurrentState().getDb(statement.getDbName());
+            Database filterDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(statement.getDbName());
             List<List<String>> infos = Lists.newArrayList();
             List<Database> dbs = Lists.newArrayList();
 
@@ -1852,7 +1852,7 @@ public ShowResultSet visitShowResourceStatement(ShowResourcesStmt statement, Con
         @Override
         public ShowResultSet visitShowExportStatement(ShowExportStmt statement, ConnectContext context) {
             GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
-            Database db = globalStateMgr.getDb(statement.getDbName());
+            Database db = globalStateMgr.getLocalMetastore().getDb(statement.getDbName());
             MetaUtils.checkDbNullAndReport(db, statement.getDbName());
             long dbId = db.getId();
 
@@ -2082,12 +2082,12 @@ public ShowResultSet visitShowSmallFilesStatement(ShowSmallFilesStmt statement,
         @Override
         public ShowResultSet visitShowDynamicPartitionStatement(ShowDynamicPartitionStmt statement, ConnectContext context) {
             List<List<String>> rows = Lists.newArrayList();
-            Database db = context.getGlobalStateMgr().getDb(statement.getDb());
+            Database db = context.getGlobalStateMgr().getLocalMetastore().getDb(statement.getDb());
             if (db != null) {
                 Locker locker = new Locker();
                 locker.lockDatabase(db, LockType.READ);
                 try {
-                    for (Table tbl : db.getTables()) {
+                    for (Table tbl : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                         if (!(tbl instanceof OlapTable)) {
                             continue;
                         }
@@ -2148,7 +2148,7 @@ public ShowResultSet visitShowDynamicPartitionStatement(ShowDynamicPartitionStmt
         @Override
         public ShowResultSet visitShowIndexStatement(ShowIndexStmt statement, ConnectContext context) {
             List<List<String>> rows = Lists.newArrayList();
-            Database db = context.getGlobalStateMgr().getDb(statement.getDbName());
+            Database db = context.getGlobalStateMgr().getLocalMetastore().getDb(statement.getDbName());
             MetaUtils.checkDbNullAndReport(db, statement.getDbName());
             Table table = MetaUtils.getSessionAwareTable(context, db, statement.getTableName());
             if (table == null) {
@@ -2180,7 +2180,7 @@ public ShowResultSet visitShowIndexStatement(ShowIndexStmt statement, ConnectCon
 
         @Override
         public ShowResultSet visitShowTransactionStatement(ShowTransactionStmt statement, ConnectContext context) {
-            Database db = context.getGlobalStateMgr().getDb(statement.getDbName());
+            Database db = context.getGlobalStateMgr().getLocalMetastore().getDb(statement.getDbName());
             MetaUtils.checkDbNullAndReport(db, statement.getDbName());
 
             long txnId = statement.getTxnId();
@@ -2502,7 +2502,7 @@ public ShowResultSet visitDescStorageVolumeStatement(DescStorageVolumeStmt state
         public ShowResultSet visitShowPipeStatement(ShowPipeStmt statement, ConnectContext context) {
             List<List<Comparable>> rows = Lists.newArrayList();
             String dbName = statement.getDbName();
-            long dbId = GlobalStateMgr.getCurrentState().mayGetDb(dbName)
+            long dbId = GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetDb(dbName)
                     .map(Database::getId)
                     .orElseThrow(() -> ErrorReport.buildSemanticException(ErrorCode.ERR_BAD_DB_ERROR, dbName));
             PipeManager pipeManager = GlobalStateMgr.getCurrentState().getPipeManager();
diff --git a/fe/fe-core/src/main/java/com/starrocks/qe/ShowMaterializedViewStatus.java b/fe/fe-core/src/main/java/com/starrocks/qe/ShowMaterializedViewStatus.java
index ea6b49054f3c29..a071de3a79ba36 100644
--- a/fe/fe-core/src/main/java/com/starrocks/qe/ShowMaterializedViewStatus.java
+++ b/fe/fe-core/src/main/java/com/starrocks/qe/ShowMaterializedViewStatus.java
@@ -25,8 +25,10 @@
 import com.starrocks.persist.gson.GsonUtils;
 import com.starrocks.scheduler.Constants;
 import com.starrocks.scheduler.ExecuteOption;
+import com.starrocks.scheduler.Task;
 import com.starrocks.scheduler.persist.MVTaskRunExtraMessage;
 import com.starrocks.scheduler.persist.TaskRunStatus;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.thrift.TMaterializedViewStatus;
 
 import java.util.ArrayList;
@@ -64,6 +66,7 @@ public class ShowMaterializedViewStatus {
     public class RefreshJobStatus {
         private long taskId;
         private String taskName;
+        private String taskOwner;
         private Constants.TaskRunState refreshState;
         private long mvRefreshStartTime;
         private long mvRefreshEndTime;
@@ -200,6 +203,36 @@ public ExtraMessage getExtraMessage() {
         public void setExtraMessage(ExtraMessage extraMessage) {
             this.extraMessage = extraMessage;
         }
+
+        public String getTaskOwner() {
+            return taskOwner;
+        }
+
+        public void setTaskOwner(String taskOwner) {
+            this.taskOwner = taskOwner;
+        }
+
+        @Override
+        public String toString() {
+            return "RefreshJobStatus{" +
+                    "taskId=" + taskId +
+                    ", taskName='" + taskName + '\'' +
+                    ", taskOwner='" + taskOwner + '\'' +
+                    ", refreshState=" + refreshState +
+                    ", mvRefreshStartTime=" + mvRefreshStartTime +
+                    ", mvRefreshEndTime=" + mvRefreshEndTime +
+                    ", totalProcessDuration=" + totalProcessDuration +
+                    ", isForce=" + isForce +
+                    ", refreshedPartitionStarts=" + refreshedPartitionStarts +
+                    ", refreshedPartitionEnds=" + refreshedPartitionEnds +
+                    ", refreshedBasePartitionsToRefreshMaps=" + refreshedBasePartitionsToRefreshMaps +
+                    ", refreshedMvPartitionsToRefreshs=" + refreshedMvPartitionsToRefreshs +
+                    ", errorCode='" + errorCode + '\'' +
+                    ", errorMsg='" + errorMsg + '\'' +
+                    ", isRefreshFinished=" + isRefreshFinished +
+                    ", extraMessage=" + extraMessage +
+                    '}';
+        }
     }
 
     /**
@@ -381,6 +414,16 @@ public RefreshJobStatus getRefreshJobStatus() {
         status.setTaskId(firstTaskRunStatus.getTaskId());
         status.setTaskName(firstTaskRunStatus.getTaskName());
 
+        // Task creator
+        Task task = GlobalStateMgr.getCurrentState().getTaskManager().getTask(firstTaskRunStatus.getTaskName());
+        if (task != null) {
+            if (task.getUserIdentity() != null) {
+                status.setTaskOwner(task.getUserIdentity().toString());
+            } else {
+                status.setTaskOwner(task.getCreateUser());
+            }
+        }
+
         // extra message
         ExtraMessage extraMessage = new ExtraMessage();
         List<String> queryIds = applyTaskRunStatusWith(x -> x.getQueryId());
@@ -509,6 +552,8 @@ public TMaterializedViewStatus toThrift() {
 
         // query_rewrite_status
         status.setQuery_rewrite_status(queryRewriteStatus);
+        // creator
+        status.setCreator(refreshJobStatus.getTaskOwner());
 
         return status;
     }
@@ -576,6 +621,8 @@ public List<String> toResultSet() {
                 GsonUtils.GSON.toJson(refreshJobStatus.getExtraMessage()));
         // query_rewrite_status
         addField(resultRow, queryRewriteStatus);
+        // owner
+        addField(resultRow, refreshJobStatus.getTaskOwner());
 
         return resultRow;
     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/qe/StmtExecutor.java b/fe/fe-core/src/main/java/com/starrocks/qe/StmtExecutor.java
index 24cba616d80472..b2b5834a3b71a9 100644
--- a/fe/fe-core/src/main/java/com/starrocks/qe/StmtExecutor.java
+++ b/fe/fe-core/src/main/java/com/starrocks/qe/StmtExecutor.java
@@ -91,6 +91,7 @@
 import com.starrocks.load.ExportJob;
 import com.starrocks.load.InsertOverwriteJob;
 import com.starrocks.load.InsertOverwriteJobMgr;
+import com.starrocks.load.loadv2.InsertLoadJob;
 import com.starrocks.load.loadv2.LoadJob;
 import com.starrocks.meta.SqlBlackList;
 import com.starrocks.metric.MetricRepo;
@@ -1252,7 +1253,11 @@ private void handleQueryStmt(ExecPlan execPlan) throws Exception {
 
     private void handleAnalyzeStmt() throws IOException {
         AnalyzeStmt analyzeStmt = (AnalyzeStmt) parsedStmt;
-        Database db = MetaUtils.getDatabase(context, analyzeStmt.getTableName());
+        TableName tableName = analyzeStmt.getTableName();
+        Database db = GlobalStateMgr.getCurrentState().getMetadataMgr().getDb(tableName.getCatalog(), tableName.getDb());
+        if (db == null) {
+            throw new SemanticException("Database %s is not found", tableName.getCatalogAndDb());
+        }
         Table table = MetaUtils.getSessionAwareTable(context, db, analyzeStmt.getTableName());
         if (StatisticUtils.isEmptyTable(table)) {
             return;
@@ -1410,12 +1415,17 @@ private void executeAnalyze(ConnectContext statsConnectCtx, AnalyzeStmt analyzeS
 
     private void handleDropStatsStmt() {
         DropStatsStmt dropStatsStmt = (DropStatsStmt) parsedStmt;
-        Table table = MetaUtils.getTable(context, dropStatsStmt.getTableName());
+        TableName tableName = dropStatsStmt.getTableName();
+        Table table = GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(tableName.getCatalog(),
+                tableName.getDb(), tableName.getTbl());
+        if (table == null) {
+            throw new SemanticException("Table %s is not found", tableName.toString());
+        }
+
         if (dropStatsStmt.isExternal()) {
             GlobalStateMgr.getCurrentState().getAnalyzeMgr().dropExternalAnalyzeStatus(table.getUUID());
             GlobalStateMgr.getCurrentState().getAnalyzeMgr().dropExternalBasicStatsData(table.getUUID());
 
-            TableName tableName = dropStatsStmt.getTableName();
             GlobalStateMgr.getCurrentState().getAnalyzeMgr().removeExternalBasicStatsMeta(tableName.getCatalog(),
                     tableName.getDb(), tableName.getTbl());
             List<String> columns = table.getBaseSchema().stream().map(Column::getName).collect(Collectors.toList());
@@ -1433,7 +1443,13 @@ private void handleDropStatsStmt() {
 
     private void handleDropHistogramStmt() {
         DropHistogramStmt dropHistogramStmt = (DropHistogramStmt) parsedStmt;
-        Table table = MetaUtils.getTable(context, dropHistogramStmt.getTableName());
+        TableName tableName = dropHistogramStmt.getTableName();
+        Table table = GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(tableName.getCatalog(),
+                tableName.getDb(), tableName.getTbl());
+        if (table == null) {
+            throw new SemanticException("Table %s is not found", tableName.toString());
+        }
+
         if (dropHistogramStmt.isExternal()) {
             List<String> columns = dropHistogramStmt.getColumnNames();
 
@@ -1464,8 +1480,15 @@ private void handleKillAnalyzeStmt() {
 
     private void checkTblPrivilegeForKillAnalyzeStmt(ConnectContext context, String catalogName, String dbName,
                                                      String tableName) {
-        MetaUtils.getDatabase(catalogName, dbName);
-        MetaUtils.getTable(catalogName, dbName, tableName);
+        Database db = GlobalStateMgr.getCurrentState().getMetadataMgr().getDb(catalogName, dbName);
+        if (db == null) {
+            ErrorReport.reportSemanticException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
+        }
+
+        Table table = GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(catalogName, dbName, tableName);
+        if (table == null) {
+            throw new SemanticException("Table %s is not found", tableName);
+        }
         Authorizer.checkActionForAnalyzeStatement(context.getCurrentUserIdentity(), context.getCurrentRoleIds(),
                 new TableName(catalogName, dbName, tableName));
     }
@@ -1943,7 +1966,12 @@ public PQueryStatistics getQueryStatisticsForAuditLog() {
     }
 
     public void handleInsertOverwrite(InsertStmt insertStmt) throws Exception {
-        Database db = MetaUtils.getDatabase(context, insertStmt.getTableName());
+        TableName tableName = insertStmt.getTableName();
+        Database db = GlobalStateMgr.getCurrentState().getMetadataMgr().getDb(tableName.getCatalog(), tableName.getDb());
+        if (db == null) {
+            throw new SemanticException("Database %s is not found", tableName.getCatalogAndDb());
+        }
+
         Locker locker = new Locker();
         Table table = insertStmt.getTargetTable();
         if (!(table instanceof OlapTable)) {
@@ -2034,7 +2062,7 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
             return;
         }
 
-        MetaUtils.normalizationTableName(context, stmt.getTableName());
+        stmt.getTableName().normalization(context);
         String catalogName = stmt.getTableName().getCatalog();
         String dbName = stmt.getTableName().getDb();
         String tableName = stmt.getTableName().getTbl();
@@ -2122,9 +2150,11 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
             }
 
             context.setStatisticsJob(AnalyzerUtils.isStatisticsJob(context, parsedStmt));
+            InsertLoadJob loadJob = null;
             if (!(targetTable.isIcebergTable() || targetTable.isHiveTable() || targetTable.isTableFunctionTable() ||
                     targetTable.isBlackHoleTable())) {
-                jobId = context.getGlobalStateMgr().getLoadMgr().registerLoadJob(
+                // insert, update and delete job
+                loadJob = context.getGlobalStateMgr().getLoadMgr().registerInsertLoadJob(
                         label,
                         database.getFullName(),
                         targetTable.getId(),
@@ -2139,6 +2169,8 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
                         type,
                         ConnectContext.get().getSessionVariable().getQueryTimeoutS(),
                         coord);
+                loadJob.setJobProperties(stmt.getProperties());
+                jobId = loadJob.getId();
                 if (txnState != null) {
                     txnState.setCallbackId(jobId);
                 }
@@ -2218,37 +2250,32 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
                 loadedBytes = Long.parseLong(coord.getLoadCounters().get(LoadJob.LOADED_BYTES));
             }
 
-            // if in strict mode, insert will fail if there are filtered rows
-            if (context.getSessionVariable().getEnableInsertStrict()) {
-                if (filteredRows > 0) {
-                    if (targetTable instanceof ExternalOlapTable) {
-                        ExternalOlapTable externalTable = (ExternalOlapTable) targetTable;
-                        RemoteTransactionMgr.abortRemoteTransaction(
-                                externalTable.getSourceTableDbId(), transactionId,
-                                externalTable.getSourceTableHost(),
-                                externalTable.getSourceTablePort(),
-                                TransactionCommitFailedException.FILTER_DATA_IN_STRICT_MODE + ", tracking sql = " +
-                                        trackingSql,
-                                coord == null ? Collections.emptyList() : coord.getCommitInfos(),
-                                coord == null ? Collections.emptyList() : coord.getFailInfos()
-                        );
-                    } else if (targetTable instanceof SystemTable || targetTable.isHiveTable() ||
-                            targetTable.isIcebergTable() || targetTable.isTableFunctionTable() ||
-                            targetTable.isBlackHoleTable()) {
-                        // schema table does not need txn
-                    } else {
-                        transactionMgr.abortTransaction(
-                                database.getId(),
-                                transactionId,
-                                TransactionCommitFailedException.FILTER_DATA_IN_STRICT_MODE + ", tracking sql = " +
-                                        trackingSql,
-                                Coordinator.getCommitInfos(coord), Coordinator.getFailInfos(coord), null);
-                    }
-                    context.getState().setError("Insert has filtered data in strict mode, txn_id = " + transactionId +
-                            " tracking sql = " + trackingSql);
-                    insertError = true;
-                    return;
+            if (loadJob != null) {
+                loadJob.updateLoadingStatus(coord.getLoadCounters());
+            }
+
+            // insert will fail if 'filtered rows / total rows' exceeds max_filter_ratio
+            if (loadJob != null && !loadJob.checkDataQuality()) {
+                if (targetTable instanceof ExternalOlapTable) {
+                    ExternalOlapTable externalTable = (ExternalOlapTable) targetTable;
+                    RemoteTransactionMgr.abortRemoteTransaction(externalTable.getSourceTableDbId(), transactionId,
+                            externalTable.getSourceTableHost(), externalTable.getSourceTablePort(),
+                            TransactionCommitFailedException.FILTER_DATA_ERR + ", tracking sql = " + trackingSql,
+                            coord == null ? Collections.emptyList() : coord.getCommitInfos(),
+                            coord == null ? Collections.emptyList() : coord.getFailInfos());
+                } else if (targetTable instanceof SystemTable || targetTable.isHiveTable() || targetTable.isIcebergTable() ||
+                        targetTable.isTableFunctionTable() || targetTable.isBlackHoleTable()) {
+                    // schema table does not need txn
+                } else {
+                    transactionMgr.abortTransaction(database.getId(), transactionId,
+                            TransactionCommitFailedException.FILTER_DATA_ERR + ", tracking sql = " + trackingSql,
+                            Coordinator.getCommitInfos(coord), Coordinator.getFailInfos(coord), null);
                 }
+                context.getState().setError(
+                        TransactionCommitFailedException.FILTER_DATA_ERR + ", txn_id = " + transactionId +
+                                ", tracking sql = " + trackingSql);
+                insertError = true;
+                return;
             }
 
             if (loadedRows == 0 && filteredRows == 0 && (stmt instanceof DeleteStmt || stmt instanceof InsertStmt
diff --git a/fe/fe-core/src/main/java/com/starrocks/replication/ReplicationJob.java b/fe/fe-core/src/main/java/com/starrocks/replication/ReplicationJob.java
index 55eb39cec3d004..8fbc21ae7a476f 100644
--- a/fe/fe-core/src/main/java/com/starrocks/replication/ReplicationJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/replication/ReplicationJob.java
@@ -354,6 +354,12 @@ public TSnapshotInfo getSnapshotInfo() {
     @SerializedName(value = "jobId")
     private final String jobId;
 
+    @SerializedName(value = "createdTimeMs")
+    private final long createdTimeMs;
+
+    @SerializedName(value = "finishedTimeMs")
+    private volatile long finishedTimeMs;
+
     @SerializedName(value = "srcToken")
     private final String srcToken;
 
@@ -392,6 +398,14 @@ public String getJobId() {
         return jobId;
     }
 
+    public long getCreatedTimeMs() {
+        return createdTimeMs;
+    }
+
+    public long getFinishedTimeMs() {
+        return finishedTimeMs;
+    }
+
     public long getDatabaseId() {
         return databaseId;
     }
@@ -400,6 +414,10 @@ public long getTableId() {
         return tableId;
     }
 
+    public long getTransactionId() {
+        return transactionId;
+    }
+
     public long getReplicationDataSize() {
         return replicationDataSize;
     }
@@ -414,11 +432,40 @@ public ReplicationJobState getState() {
 
     private void setState(ReplicationJobState state) {
         this.state = state;
+        if (state.equals(ReplicationJobState.COMMITTED) || state.equals(ReplicationJobState.ABORTED)) {
+            finishedTimeMs = System.currentTimeMillis();
+        }
         GlobalStateMgr.getServingState().getEditLog().logReplicationJob(this);
         LOG.info("Replication job state: {}, database id: {}, table id: {}, transaction id: {}",
                 state, databaseId, tableId, transactionId);
     }
 
+    public boolean isExpired() {
+        return finishedTimeMs > 0 &&
+                (System.currentTimeMillis() - finishedTimeMs) > (Config.history_job_keep_max_second * 1000);
+    }
+
+    public long getRunningTaskNum() {
+        return runningTasks.size();
+    }
+
+    public long getTotalTaskNum() {
+        return taskNum;
+    }
+
+    public String getErrorMessage() {
+        if (!state.equals(ReplicationJobState.ABORTED)) {
+            return null;
+        }
+
+        TransactionState transactionState = GlobalStateMgr.getServingState().getGlobalTransactionMgr()
+                .getTransactionState(databaseId, transactionId);
+        if (transactionState == null) {
+            return "Transaction not found";
+        }
+        return transactionState.getReason();
+    }
+
     public ReplicationJob(TTableReplicationRequest request) throws MetaNotFoundException {
         Preconditions.checkState(request.src_table_type == TTableType.OLAP_TABLE);
 
@@ -427,6 +474,8 @@ public ReplicationJob(TTableReplicationRequest request) throws MetaNotFoundExcep
         } else {
             this.jobId = request.job_id;
         }
+        this.createdTimeMs = System.currentTimeMillis();
+        this.finishedTimeMs = 0;
         this.srcToken = request.src_token;
         this.databaseId = request.database_id;
         TableInfo tableInfo = initTableInfo(request);
@@ -451,6 +500,8 @@ public ReplicationJob(String jobId, String srcToken, long databaseId, OlapTable
         } else {
             this.jobId = jobId;
         }
+        this.createdTimeMs = System.currentTimeMillis();
+        this.finishedTimeMs = 0;
         this.srcToken = srcToken;
         this.databaseId = databaseId;
         TableInfo tableInfo = initTableInfo(table, srcTable, srcSystemInfoService);
@@ -572,7 +623,7 @@ private static TableInfo initTableInfo(TTableReplicationRequest request) throws
         long tableDataSize;
         Map<Long, PartitionInfo> partitionInfos = Maps.newHashMap();
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(request.database_id);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(request.database_id);
         if (db == null) {
             throw new MetaNotFoundException("Database " + request.database_id + " not found");
         }
@@ -580,7 +631,7 @@ private static TableInfo initTableInfo(TTableReplicationRequest request) throws
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            Table table = db.getTable(request.table_id);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), request.table_id);
             if (table == null) {
                 throw new MetaNotFoundException(
                         "Table " + request.table_id + " in database " + db.getFullName() + " not found");
@@ -830,8 +881,9 @@ private boolean isTransactionAborted() {
         }
 
         if (txnState.getTransactionStatus() == TransactionStatus.PREPARE) {
-            Database db = GlobalStateMgr.getServingState().getDb(databaseId);
-            if (db == null || db.getTable(tableId) == null) {
+            Database db = GlobalStateMgr.getServingState().getLocalMetastore().getDb(databaseId);
+            if (db == null
+                    || GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId) == null) {
                 abortTransaction("Table is deleted");
                 return true;
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/replication/ReplicationMgr.java b/fe/fe-core/src/main/java/com/starrocks/replication/ReplicationMgr.java
index 7c0d876d17fdac..7b39854522ddcc 100644
--- a/fe/fe-core/src/main/java/com/starrocks/replication/ReplicationMgr.java
+++ b/fe/fe-core/src/main/java/com/starrocks/replication/ReplicationMgr.java
@@ -36,6 +36,8 @@
 import org.apache.logging.log4j.Logger;
 
 import java.io.IOException;
+import java.util.Collection;
+import java.util.Iterator;
 import java.util.List;
 import java.util.Map;
 
@@ -57,23 +59,8 @@ public ReplicationMgr() {
 
     @Override
     protected void runAfterCatalogReady() {
-        List<ReplicationJob> toRemovedJobs = Lists.newArrayList();
-        for (ReplicationJob job : runningJobs.values()) {
-            job.run();
-
-            ReplicationJobState state = job.getState();
-            if (state.equals(ReplicationJobState.COMMITTED)) {
-                toRemovedJobs.add(job);
-                committedJobs.put(job.getTableId(), job);
-            } else if (state.equals(ReplicationJobState.ABORTED)) {
-                toRemovedJobs.add(job);
-                abortedJobs.put(job.getTableId(), job);
-            }
-        }
-
-        for (ReplicationJob job : toRemovedJobs) {
-            runningJobs.remove(job.getTableId(), job);
-        }
+        runRunningJobs();
+        clearExpiredJobs();
     }
 
     public void addReplicationJob(TTableReplicationRequest request) throws UserException {
@@ -119,18 +106,16 @@ public void addReplicationJob(ReplicationJob job) throws AlreadyExistsException
                 job.getDatabaseId(), job.getTableId(), job.getReplicationDataSize(), replicatingDataSizeMB);
     }
 
-    public boolean hasRunningJobs() {
-        return !runningJobs.isEmpty();
+    public Collection<ReplicationJob> getRunningJobs() {
+        return runningJobs.values();
     }
 
-    public boolean hasFailedJobs() {
-        return !abortedJobs.isEmpty();
+    public Collection<ReplicationJob> getCommittedJobs() {
+        return committedJobs.values();
     }
 
-    public void clearFinishedJobs() {
-        committedJobs.clear();
-        abortedJobs.clear();
-        GlobalStateMgr.getServingState().getEditLog().logReplicationJob(null);
+    public Collection<ReplicationJob> getAbortedJobs() {
+        return abortedJobs.values();
     }
 
     public void cancelRunningJobs() {
@@ -170,12 +155,6 @@ public void finishReplicateSnapshotTask(ReplicateSnapshotTask task, TFinishTaskR
     }
 
     public void replayReplicationJob(ReplicationJob replicationJob) {
-        if (replicationJob == null) {
-            committedJobs.clear();
-            abortedJobs.clear();
-            return;
-        }
-
         if (replicationJob.getState().equals(ReplicationJobState.COMMITTED)) {
             committedJobs.put(replicationJob.getTableId(), replicationJob);
             runningJobs.remove(replicationJob.getTableId());
@@ -187,6 +166,16 @@ public void replayReplicationJob(ReplicationJob replicationJob) {
         }
     }
 
+    public void replayDeleteReplicationJob(ReplicationJob replicationJob) {
+        if (replicationJob.getState().equals(ReplicationJobState.COMMITTED)) {
+            committedJobs.remove(replicationJob.getTableId());
+        } else if (replicationJob.getState().equals(ReplicationJobState.ABORTED)) {
+            abortedJobs.remove(replicationJob.getTableId());
+        } else {
+            runningJobs.remove(replicationJob.getTableId());
+        }
+    }
+
     private long getReplicatingReplicaCount() {
         long replicatingReplicaCount = 0;
         for (ReplicationJob job : runningJobs.values()) {
@@ -203,6 +192,48 @@ private long getReplicatingDataSize() {
         return replicatingDataSize;
     }
 
+    private void runRunningJobs() {
+        List<ReplicationJob> toRemovedJobs = Lists.newArrayList();
+        for (ReplicationJob job : runningJobs.values()) {
+            job.run();
+
+            ReplicationJobState state = job.getState();
+            if (state.equals(ReplicationJobState.COMMITTED)) {
+                toRemovedJobs.add(job);
+                committedJobs.put(job.getTableId(), job);
+            } else if (state.equals(ReplicationJobState.ABORTED)) {
+                toRemovedJobs.add(job);
+                abortedJobs.put(job.getTableId(), job);
+            }
+        }
+
+        for (ReplicationJob job : toRemovedJobs) {
+            runningJobs.remove(job.getTableId(), job);
+        }
+    }
+
+    private void clearExpiredJobs() {
+        for (Iterator<Map.Entry<Long, ReplicationJob>> it = committedJobs.entrySet().iterator(); it.hasNext();) {
+            ReplicationJob job = it.next().getValue();
+            if (!job.isExpired()) {
+                continue;
+            }
+
+            GlobalStateMgr.getServingState().getEditLog().logDeleteReplicationJob(job);
+            it.remove();
+        }
+
+        for (Iterator<Map.Entry<Long, ReplicationJob>> it = abortedJobs.entrySet().iterator(); it.hasNext();) {
+            ReplicationJob job = it.next().getValue();
+            if (!job.isExpired()) {
+                continue;
+            }
+
+            GlobalStateMgr.getServingState().getEditLog().logDeleteReplicationJob(job);
+            it.remove();
+        }
+    }
+
     public void save(ImageWriter imageWriter) throws IOException, SRMetaBlockException {
         SRMetaBlockWriter writer = imageWriter.getBlockWriter(SRMetaBlockID.REPLICATION_MGR, 1);
         writer.writeJson(this);
diff --git a/fe/fe-core/src/main/java/com/starrocks/scheduler/MVActiveChecker.java b/fe/fe-core/src/main/java/com/starrocks/scheduler/MVActiveChecker.java
index 5894ff0a777052..1bcba036ca4c37 100644
--- a/fe/fe-core/src/main/java/com/starrocks/scheduler/MVActiveChecker.java
+++ b/fe/fe-core/src/main/java/com/starrocks/scheduler/MVActiveChecker.java
@@ -93,7 +93,8 @@ private void clearGracePeriod() {
     private void process() {
         Collection<Database> dbs = GlobalStateMgr.getCurrentState().getLocalMetastore().getIdToDb().values();
         for (Database db : CollectionUtils.emptyIfNull(dbs)) {
-            for (Table table : CollectionUtils.emptyIfNull(db.getTables())) {
+            for (Table table : CollectionUtils.emptyIfNull(
+                    GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId()))) {
                 if (table.isMaterializedView()) {
                     MaterializedView mv = (MaterializedView) table;
                     if (!mv.isActive()) {
@@ -124,7 +125,7 @@ public static void tryToActivate(MaterializedView mv, boolean checkGracePeriod)
         }
 
         long dbId = mv.getDbId();
-        Optional<String> dbName = GlobalStateMgr.getCurrentState().mayGetDb(dbId).map(Database::getFullName);
+        Optional<String> dbName = GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetDb(dbId).map(Database::getFullName);
         if (!dbName.isPresent()) {
             LOG.warn("[MVActiveChecker] cannot activate MV {} since database {} not found", mv.getName(), dbId);
             return;
diff --git a/fe/fe-core/src/main/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessor.java b/fe/fe-core/src/main/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessor.java
index 53b5c9a2a9121a..bdb6f46550b978 100644
--- a/fe/fe-core/src/main/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessor.java
+++ b/fe/fe-core/src/main/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessor.java
@@ -103,6 +103,7 @@
 import java.util.stream.Collectors;
 
 import static com.starrocks.catalog.system.SystemTable.MAX_FIELD_VARCHAR_LENGTH;
+import static com.starrocks.scheduler.TaskRun.MV_ID;
 
 /**
  * Core logic of materialized view refresh task run
@@ -113,7 +114,6 @@ public class PartitionBasedMvRefreshProcessor extends BaseTaskRunProcessor {
     private static final Logger LOG = LogManager.getLogger(PartitionBasedMvRefreshProcessor.class);
     private static final AtomicLong STMT_ID_GENERATOR = new AtomicLong(0);
 
-    public static final String MV_ID = "mvId";
     // session.enable_spill
     public static final String MV_SESSION_ENABLE_SPILL =
             PropertyAnalyzer.PROPERTIES_MATERIALIZED_VIEW_SESSION_PREFIX + SessionVariable.ENABLE_SPILL;
@@ -580,9 +580,9 @@ private void changeDefaultConnectContextIfNeeded(ConnectContext mvConnectCtx) {
             mvSessionVariable.setQueryTimeoutS(MV_DEFAULT_QUERY_TIMEOUT);
         }
 
-        // set enable_insert_strict by default
-        if (!isMVPropertyContains(SessionVariable.ENABLE_INSERT_STRICT)) {
-            mvSessionVariable.setEnableInsertStrict(Config.enable_mv_refresh_insert_strict);
+        // set insert_max_filter_ratio by default
+        if (!isMVPropertyContains(SessionVariable.INSERT_MAX_FILTER_RATIO)) {
+            mvSessionVariable.setInsertMaxFilterRatio(Config.mv_refresh_fail_on_filter_data ? 0 : 1);
         }
         // enable profile by default for mv refresh task
         if (!isMVPropertyContains(SessionVariable.ENABLE_PROFILE)) {
@@ -792,7 +792,7 @@ private void updateMeta(Set<String> mvRefreshedPartitions,
         LOG.info("start to update meta for mv:{}", materializedView.getName());
 
         // check
-        Table mv = db.getTable(materializedView.getId());
+        Table mv = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), materializedView.getId());
         if (mv == null) {
             throw new DmlException(
                     "update meta failed. materialized view:" + materializedView.getName() + " not exist");
@@ -849,12 +849,12 @@ public void prepare(TaskRunContext context) {
         Map<String, String> properties = context.getProperties();
         // NOTE: mvId is set in Task's properties when creating
         long mvId = Long.parseLong(properties.get(MV_ID));
-        db = GlobalStateMgr.getCurrentState().getDb(context.ctx.getDatabase());
+        db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(context.ctx.getDatabase());
         if (db == null) {
             LOG.warn("database {} do not exist when refreshing materialized view:{}", context.ctx.getDatabase(), mvId);
             throw new DmlException("database " + context.ctx.getDatabase() + " do not exist.");
         }
-        Table table = db.getTable(mvId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), mvId);
         if (table == null) {
             LOG.warn("materialized view:{} in database:{} do not exist when refreshing", mvId,
                     context.ctx.getDatabase());
diff --git a/fe/fe-core/src/main/java/com/starrocks/scheduler/TaskBuilder.java b/fe/fe-core/src/main/java/com/starrocks/scheduler/TaskBuilder.java
index fa558533233b34..0ac5de20440ca1 100644
--- a/fe/fe-core/src/main/java/com/starrocks/scheduler/TaskBuilder.java
+++ b/fe/fe-core/src/main/java/com/starrocks/scheduler/TaskBuilder.java
@@ -41,6 +41,8 @@
 import java.util.Map;
 import java.util.concurrent.TimeUnit;
 
+import static com.starrocks.scheduler.TaskRun.MV_ID;
+
 // TaskBuilder is responsible for converting Stmt to Task Class
 // and also responsible for generating taskId and taskName
 public class TaskBuilder {
@@ -154,9 +156,9 @@ public static Task buildMvTask(MaterializedView materializedView, String dbName)
         task.setDbName(dbName);
 
         Map<String, String> taskProperties = Maps.newHashMap();
-        taskProperties.put(PartitionBasedMvRefreshProcessor.MV_ID,
-                String.valueOf(materializedView.getId()));
-        taskProperties.putAll(materializedView.getProperties());
+        taskProperties.put(MV_ID, String.valueOf(materializedView.getId()));
+        // Don't put mv table properties into task properties since mv refresh doesn't need them, and the properties
+        // will cause task run's meta-data too large.
         // In PropertyAnalyzer.analyzeMVProperties, it removed the warehouse property, because
         // it only keeps session started properties
         Warehouse warehouse = GlobalStateMgr.getCurrentState().getWarehouseMgr()
@@ -181,7 +183,7 @@ public static Task rebuildMvTask(MaterializedView materializedView, String dbNam
         task.setSource(Constants.TaskSource.MV);
         task.setDbName(dbName);
         String mvId = String.valueOf(materializedView.getId());
-        previousTaskProperties.put(PartitionBasedMvRefreshProcessor.MV_ID, mvId);
+        previousTaskProperties.put(MV_ID, mvId);
         task.setProperties(previousTaskProperties);
         task.setDefinition(materializedView.getTaskDefinition());
         task.setPostRun(getAnalyzeMVStmt(materializedView.getName()));
diff --git a/fe/fe-core/src/main/java/com/starrocks/scheduler/TaskRun.java b/fe/fe-core/src/main/java/com/starrocks/scheduler/TaskRun.java
index cbb435d0afe168..6b6db7aaeb19bb 100644
--- a/fe/fe-core/src/main/java/com/starrocks/scheduler/TaskRun.java
+++ b/fe/fe-core/src/main/java/com/starrocks/scheduler/TaskRun.java
@@ -15,6 +15,7 @@
 package com.starrocks.scheduler;
 
 import com.google.common.base.Preconditions;
+import com.google.common.collect.ImmutableSet;
 import com.google.common.collect.Maps;
 import com.google.gson.annotations.SerializedName;
 import com.starrocks.analysis.StringLiteral;
@@ -41,6 +42,7 @@
 
 import java.util.Map;
 import java.util.Objects;
+import java.util.Set;
 import java.util.UUID;
 import java.util.concurrent.CompletableFuture;
 
@@ -48,10 +50,18 @@ public class TaskRun implements Comparable<TaskRun> {
 
     private static final Logger LOG = LogManager.getLogger(TaskRun.class);
 
+    public static final String MV_ID = "mvId";
     public static final String PARTITION_START = "PARTITION_START";
     public static final String PARTITION_END = "PARTITION_END";
     public static final String FORCE = "FORCE";
     public static final String START_TASK_RUN_ID = "START_TASK_RUN_ID";
+    // All properties that can be set in TaskRun
+    public static final Set<String> TASK_RUN_PROPERTIES =
+            ImmutableSet.of(
+                    MV_ID, PARTITION_START, PARTITION_END,
+                    FORCE, START_TASK_RUN_ID);
+
+    // Only used in FE's UT
     public static final String IS_TEST = "__IS_TEST__";
     private boolean isKilled = false;
 
@@ -160,14 +170,14 @@ public Map<String, String> refreshTaskProperties(ConnectContext ctx) {
 
         try {
             // NOTE: mvId is set in Task's properties when creating
-            long mvId = Long.parseLong(properties.get(PartitionBasedMvRefreshProcessor.MV_ID));
-            Database database = GlobalStateMgr.getCurrentState().getDb(ctx.getDatabase());
+            long mvId = Long.parseLong(properties.get(MV_ID));
+            Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(ctx.getDatabase());
             if (database == null) {
                 LOG.warn("database {} do not exist when refreshing materialized view:{}", ctx.getDatabase(), mvId);
                 return newProperties;
             }
 
-            Table table = database.getTable(mvId);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), mvId);
             if (table == null) {
                 LOG.warn("materialized view:{} in database:{} do not exist when refreshing", mvId,
                         ctx.getDatabase());
@@ -175,7 +185,10 @@ public Map<String, String> refreshTaskProperties(ConnectContext ctx) {
             }
             MaterializedView materializedView = (MaterializedView) table;
             Preconditions.checkState(materializedView != null);
-            newProperties.putAll(materializedView.getProperties());
+            // Don't copy all table's properties to task's properties:
+            // 1. It will cause task run's meta-data to be too large
+            // 2. It may pollute the properties of task run.
+            newProperties.putAll(materializedView.getSessionProperties());
 
             Warehouse w = GlobalStateMgr.getCurrentState().getWarehouseMgr().getWarehouse(
                     materializedView.getWarehouseId());
@@ -224,12 +237,9 @@ public boolean executeTaskRun() throws Exception {
         // NOTE: Ensure the thread local connect context is always the same with the newest ConnectContext.
         // NOTE: Ensure this thread local is removed after this method to avoid memory leak in JVM.
         runCtx.setThreadLocalInfo();
-        LOG.info("[QueryId:{}] [ThreadLocal QueryId: {}] start to execute task run, task_id:{}",
-                runCtx.getQueryId(), ConnectContext.get() == null ? "" : ConnectContext.get().getQueryId(), taskId);
 
         Map<String, String> newProperties = refreshTaskProperties(runCtx);
         properties.putAll(newProperties);
-
         Map<String, String> taskRunContextProperties = Maps.newHashMap();
         runCtx.resetSessionVariable();
         if (properties != null) {
@@ -243,6 +253,9 @@ public boolean executeTaskRun() throws Exception {
                 }
             }
         }
+        LOG.info("[QueryId:{}] [ThreadLocal QueryId: {}] start to execute task run, task_id:{}, " +
+                        "taskRunContextProperties:{}", runCtx.getQueryId(),
+                ConnectContext.get() == null ? "" : ConnectContext.get().getQueryId(), taskId, taskRunContextProperties);
         // If this is the first task run of the job, use its uuid as the job id.
         taskRunContext.setTaskRunId(taskRunId);
         taskRunContext.setCtx(runCtx);
diff --git a/fe/fe-core/src/main/java/com/starrocks/scheduler/history/TableKeeper.java b/fe/fe-core/src/main/java/com/starrocks/scheduler/history/TableKeeper.java
index 2037bc32cb0536..9bd41bf2f0ef6d 100644
--- a/fe/fe-core/src/main/java/com/starrocks/scheduler/history/TableKeeper.java
+++ b/fe/fe-core/src/main/java/com/starrocks/scheduler/history/TableKeeper.java
@@ -92,7 +92,7 @@ public synchronized boolean isReady() {
     }
 
     public boolean checkDatabaseExists() {
-        return GlobalStateMgr.getCurrentState().getDb(databaseName) != null;
+        return GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(databaseName) != null;
     }
 
     public void createTable() throws UserException {
@@ -102,8 +102,7 @@ public void createTable() throws UserException {
     public void correctTable() {
         int numBackends = GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo().getTotalBackendNumber();
         int replica = GlobalStateMgr.getCurrentState()
-                .mayGetDb(databaseName)
-                .flatMap(db -> db.mayGetTable(tableName))
+                .getLocalMetastore().mayGetTable(databaseName, tableName)
                 .map(tbl -> ((OlapTable) tbl).getPartitionInfo().getMinReplicationNum())
                 .orElse((short) 1);
         if (numBackends < tableReplicas) {
@@ -143,8 +142,7 @@ public void changeTTL() {
 
     private Optional<OlapTable> mayGetTable() {
         return GlobalStateMgr.getCurrentState()
-                .mayGetDb(databaseName)
-                .flatMap(db -> db.mayGetTable(tableName))
+                .getLocalMetastore().mayGetTable(databaseName, tableName)
                 .flatMap(x -> Optional.of((OlapTable) x));
     }
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/scheduler/history/TaskRunHistory.java b/fe/fe-core/src/main/java/com/starrocks/scheduler/history/TaskRunHistory.java
index bf6a19ed1fc054..380e53ff15fdfe 100644
--- a/fe/fe-core/src/main/java/com/starrocks/scheduler/history/TaskRunHistory.java
+++ b/fe/fe-core/src/main/java/com/starrocks/scheduler/history/TaskRunHistory.java
@@ -216,5 +216,4 @@ public void forceGC() {
         LOG.warn("Too much task metadata triggers forced task_run GC, " +
                 "size before GC:{}, size after GC:{}.", beforeSize, getTaskRunCount());
     }
-
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/scheduler/history/TaskRunHistoryTable.java b/fe/fe-core/src/main/java/com/starrocks/scheduler/history/TaskRunHistoryTable.java
index 87d0ac309f086a..e79c68406e358b 100644
--- a/fe/fe-core/src/main/java/com/starrocks/scheduler/history/TaskRunHistoryTable.java
+++ b/fe/fe-core/src/main/java/com/starrocks/scheduler/history/TaskRunHistoryTable.java
@@ -21,6 +21,8 @@
 import com.starrocks.common.FeConstants;
 import com.starrocks.common.util.DateUtils;
 import com.starrocks.load.pipe.filelist.RepoExecutor;
+import com.starrocks.scheduler.ExecuteOption;
+import com.starrocks.scheduler.TaskRun;
 import com.starrocks.scheduler.persist.TaskRunStatus;
 import com.starrocks.statistic.StatsConstants;
 import com.starrocks.thrift.TGetTasksParams;
@@ -33,7 +35,9 @@
 
 import java.text.MessageFormat;
 import java.time.ZoneId;
+import java.util.Iterator;
 import java.util.List;
+import java.util.Map;
 import java.util.Set;
 import java.util.stream.Collectors;
 
@@ -119,6 +123,11 @@ public void addHistories(List<TaskRunStatus> histories) {
                         Strings.quote(DateUtils.formatTimeStampInMill(status.getFinishTime(), ZoneId.systemDefault()));
                 String expireTime =
                         Strings.quote(DateUtils.formatTimeStampInMill(status.getExpireTime(), ZoneId.systemDefault()));
+
+                // To be compatible with old task runs, filter out unnecessary properties to avoid json content too large
+                // and deserialize error.
+                removeUnnecessaryProperties(status);
+
                 // Since the content is stored in JSON format and insert into the starrocks olap table, we need to escape the
                 // content to make it safer in deserializing the json.
                 return MessageFormat.format(INSERT_SQL_VALUE,
@@ -137,6 +146,40 @@ public void addHistories(List<TaskRunStatus> histories) {
         }
     }
 
+    /**
+     * Normalize the task run status, remove unnecessary properties
+     * @param status
+     */
+    private void removeUnnecessaryProperties(TaskRunStatus status) {
+        //  remove unnecessary properties
+        if (status.getProperties() != null) {
+            removeUnnecessaryProperties(status.getProperties());
+        }
+        // remove unnecessary properties in mvTaskRunExtraMessage
+        if (status.getMvTaskRunExtraMessage() != null) {
+            ExecuteOption executeOption = status.getMvTaskRunExtraMessage().getExecuteOption();
+            if (executeOption != null) {
+                removeUnnecessaryProperties(executeOption.getTaskRunProperties());
+            }
+        }
+    }
+
+    /**
+     * Only keep the properties that are necessary for task run
+     * @param properties
+     */
+    private void removeUnnecessaryProperties(Map<String, String> properties) {
+        if (properties == null) {
+            return;
+        }
+        Iterator<Map.Entry<String, String>> iterator = properties.entrySet().iterator();
+        while (iterator.hasNext()) {
+            if (!TaskRun.TASK_RUN_PROPERTIES.contains(iterator.next().getKey())) {
+                iterator.remove();
+            }
+        }
+    }
+
     public List<TaskRunStatus> lookup(TGetTasksParams params) {
         if (params == null) {
             return Lists.newArrayList();
diff --git a/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVMaintenanceJob.java b/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVMaintenanceJob.java
index 7f32f0e0d9aac7..edf32f3da781c4 100644
--- a/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVMaintenanceJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVMaintenanceJob.java
@@ -125,7 +125,7 @@ public static MVMaintenanceJob read(DataInput input) throws IOException {
 
     // TODO recover the entire job state, include execution plan
     public void restore() {
-        Table table = GlobalStateMgr.getCurrentState().getDb(dbId).getTable(viewId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(dbId, viewId);
         Preconditions.checkState(table != null && table.isMaterializedView());
         this.view = (MaterializedView) table;
         this.serializedState = JobState.INIT;
@@ -232,7 +232,7 @@ void buildContext() {
         // Build connection context
         this.connectContext = StatisticUtils.buildConnectContext();
         this.connectContext.setNeedQueued(false);
-        Database db = GlobalStateMgr.getCurrentState().getDb(view.getDbId());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(view.getDbId());
         this.connectContext.getSessionVariable().setQueryTimeoutS(MV_QUERY_TIMEOUT);
         if (db != null) {
             this.connectContext.setDatabase(db.getFullName());
@@ -365,7 +365,7 @@ private void deployTasks() throws Exception {
     private void setMVMaintenanceTasksInfo(TMVMaintenanceTasks request,
                                            MVMaintenanceTask task) {
         // Request information
-        String dbName = GlobalStateMgr.getCurrentState().getDb(view.getDbId()).getFullName();
+        String dbName = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(view.getDbId()).getFullName();
 
         request.setDb_name(dbName);
         request.setMv_name(view.getName());
diff --git a/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVMaintenanceTask.java b/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVMaintenanceTask.java
index c3f016fed625b8..376d8825ef1ecb 100644
--- a/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVMaintenanceTask.java
+++ b/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVMaintenanceTask.java
@@ -59,7 +59,7 @@ public class MVMaintenanceTask {
     public static MVMaintenanceTask build(MVMaintenanceJob job, long taskId, TNetworkAddress beRpcAddr,
                                           List<TExecPlanFragmentParams> fragmentInstances) {
         MVMaintenanceTask task = new MVMaintenanceTask();
-        task.dbName = GlobalStateMgr.getCurrentState().getDb(job.getView().getDbId()).getFullName();
+        task.dbName = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(job.getView().getDbId()).getFullName();
         task.job = job;
         task.beRpcAddr = beRpcAddr;
         task.taskId = taskId;
diff --git a/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVPCTRefreshPartitioner.java b/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVPCTRefreshPartitioner.java
index 7d9f8a5c3c1f1c..7eddfe8b1858bc 100644
--- a/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVPCTRefreshPartitioner.java
+++ b/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVPCTRefreshPartitioner.java
@@ -259,7 +259,7 @@ protected void dropPartition(Database db, MaterializedView materializedView, Str
         }
         try {
             // check
-            Table mv = db.getTable(materializedView.getId());
+            Table mv = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), materializedView.getId());
             if (mv == null) {
                 throw new DmlException("drop partition failed. mv:" + materializedView.getName() + " not exist");
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVPCTRefreshPlanBuilder.java b/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVPCTRefreshPlanBuilder.java
index 36fd9216939d11..3cd7adc00bdadb 100644
--- a/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVPCTRefreshPlanBuilder.java
+++ b/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/MVPCTRefreshPlanBuilder.java
@@ -61,7 +61,7 @@ public class MVPCTRefreshPlanBuilder {
     private final MaterializedView mv;
     private final MvTaskRunContext mvContext;
     private final MVPCTRefreshPartitioner mvRefreshPartitioner;
-    private final boolean isEnableInsertStrict;
+    private final boolean isRefreshFailOnFilterData;
 
     public MVPCTRefreshPlanBuilder(MaterializedView mv,
                                    MvTaskRunContext mvContext,
@@ -69,7 +69,7 @@ public MVPCTRefreshPlanBuilder(MaterializedView mv,
         this.mv = mv;
         this.mvContext = mvContext;
         this.mvRefreshPartitioner = mvRefreshPartitioner;
-        this.isEnableInsertStrict = mvContext.getCtx().getSessionVariable().getEnableInsertStrict();
+        this.isRefreshFailOnFilterData = mvContext.getCtx().getSessionVariable().getInsertMaxFilterRatio() == 0;
     }
 
     public InsertStmt analyzeAndBuildInsertPlan(InsertStmt insertStmt,
@@ -382,7 +382,7 @@ private void doIfNoPushDownPredicates(int numOfPushDownIntoTables,
         LOG.warn("Cannot generate partition predicate for mv refresh {} and there " +
                         "are no predicate push down tables, refBaseTableSize:{}, numOfPushDownIntoTables:{}", mv.getName(),
                 refBaseTableSize, numOfPushDownIntoTables);
-        if (isEnableInsertStrict) {
+        if (isRefreshFailOnFilterData) {
             throw new AnalysisException(String.format("Cannot generate partition predicate for mv refresh %s",
                     mv.getName()));
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/TxnBasedEpochCoordinator.java b/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/TxnBasedEpochCoordinator.java
index 9d2e49eccc96ca..d8799475f9c27e 100644
--- a/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/TxnBasedEpochCoordinator.java
+++ b/fe/fe-core/src/main/java/com/starrocks/scheduler/mv/TxnBasedEpochCoordinator.java
@@ -129,7 +129,7 @@ private boolean waitEpochFinish(MVEpoch epoch) throws Exception {
     private void commitEpoch(MVEpoch epoch) {
         LOG.info("commitEpoch: {}", epoch);
         long dbId = mvMaintenanceJob.getView().getDbId();
-        Database database = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
 
         try {
             epoch.onCommitting();
diff --git a/fe/fe-core/src/main/java/com/starrocks/scheduler/persist/TaskRunStatus.java b/fe/fe-core/src/main/java/com/starrocks/scheduler/persist/TaskRunStatus.java
index fbb3600c8a8ea5..40c7f768d69f2c 100644
--- a/fe/fe-core/src/main/java/com/starrocks/scheduler/persist/TaskRunStatus.java
+++ b/fe/fe-core/src/main/java/com/starrocks/scheduler/persist/TaskRunStatus.java
@@ -19,6 +19,7 @@
 import com.google.common.base.Strings;
 import com.google.gson.annotations.SerializedName;
 import com.starrocks.cluster.ClusterNamespace;
+import com.starrocks.common.Config;
 import com.starrocks.common.io.Text;
 import com.starrocks.common.io.Writable;
 import com.starrocks.persist.gson.GsonUtils;
@@ -32,6 +33,8 @@
 import org.apache.commons.collections.MapUtils;
 import org.apache.commons.collections4.CollectionUtils;
 import org.apache.commons.collections4.ListUtils;
+import org.apache.logging.log4j.LogManager;
+import org.apache.logging.log4j.Logger;
 
 import java.io.DataInput;
 import java.io.DataOutput;
@@ -44,6 +47,7 @@
 import java.util.Set;
 
 public class TaskRunStatus implements Writable {
+    private static final Logger LOG = LogManager.getLogger(TaskRun.class);
 
     // A refresh may contain a batch of task runs, startTaskRunId is to mark the unique id of the batch task run status.
     // You can use the startTaskRunId to find the batch of task runs.
@@ -493,8 +497,14 @@ public static List<TaskRunStatus> fromResultBatch(List<TResultBatch> batches) {
                     jsonString = copied.toString(Charset.defaultCharset());
                     res.addAll(ListUtils.emptyIfNull(TaskRunStatusJSONRecord.fromJson(jsonString).data));
                 } catch (Exception e) {
-                    throw new RuntimeException("Failed to deserialize TaskRunStatus from json， please delete it from " +
-                            "_statistics_.task_run_history table: " + jsonString, e);
+                    // If the task run history is corrupted, we can use `ignore_task_run_history_replay_error` config to ignore
+                    // it and continue to process the next one.
+                    if (!Config.ignore_task_run_history_replay_error) {
+                        LOG.warn("Failed to deserialize TaskRunStatus from json， please delete it from " +
+                                "_statistics_.task_run_history table: {}", jsonString, e);
+                        throw new RuntimeException("Failed to deserialize TaskRunStatus from json， please delete it from " +
+                                "_statistics_.task_run_history table: " + jsonString, e);
+                    }
                 }
             }
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/server/GlobalStateMgr.java b/fe/fe-core/src/main/java/com/starrocks/server/GlobalStateMgr.java
index 1bf6d5c254ee3a..4ee05085788fc2 100644
--- a/fe/fe-core/src/main/java/com/starrocks/server/GlobalStateMgr.java
+++ b/fe/fe-core/src/main/java/com/starrocks/server/GlobalStateMgr.java
@@ -248,7 +248,6 @@
 import java.util.List;
 import java.util.Map;
 import java.util.Objects;
-import java.util.Optional;
 import java.util.Set;
 import java.util.concurrent.ArrayBlockingQueue;
 import java.util.concurrent.BlockingQueue;
@@ -758,6 +757,9 @@ public void transferToNonLeader(FrontendNodeType newType) {
                 if (Config.max_broker_load_job_concurrency != loadingLoadTaskScheduler.getCorePoolSize()) {
                     loadingLoadTaskScheduler.setPoolSize(Config.max_broker_load_job_concurrency);
                 }
+                if (Config.max_broker_load_job_concurrency != pendingLoadTaskScheduler.getCorePoolSize()) {
+                    pendingLoadTaskScheduler.setPoolSize(Config.max_broker_load_job_concurrency);
+                }
             } catch (Exception e) {
                 LOG.warn("check config failed", e);
             }
@@ -2041,26 +2043,6 @@ protected void runAfterCatalogReady() {
         };
     }
 
-    public Database getDb(String name) {
-        return localMetastore.getDb(name);
-    }
-
-    public Optional<Table> mayGetTable(long dbId, long tableId) {
-        return mayGetDb(dbId).flatMap(db -> db.tryGetTable(tableId));
-    }
-
-    public Optional<Database> mayGetDb(String name) {
-        return Optional.ofNullable(localMetastore.getDb(name));
-    }
-
-    public Optional<Database> mayGetDb(long dbId) {
-        return Optional.ofNullable(localMetastore.getDb(dbId));
-    }
-
-    public Database getDb(long dbId) {
-        return localMetastore.getDb(dbId);
-    }
-
     public EditLog getEditLog() {
         return editLog;
     }
@@ -2083,11 +2065,11 @@ public AlterJobMgr getAlterJobMgr() {
     }
 
     public SchemaChangeHandler getSchemaChangeHandler() {
-        return (SchemaChangeHandler) this.alterJobMgr.getSchemaChangeHandler();
+        return this.alterJobMgr.getSchemaChangeHandler();
     }
 
     public MaterializedViewHandler getRollupHandler() {
-        return (MaterializedViewHandler) this.alterJobMgr.getMaterializedViewHandler();
+        return this.alterJobMgr.getMaterializedViewHandler();
     }
 
     public BackupHandler getBackupHandler() {
@@ -2449,7 +2431,7 @@ public String dumpImage() {
         try {
             // sort all dbs
             for (long dbId : localMetastore.getDbIds()) {
-                Database db = getDb(dbId);
+                Database db = localMetastore.getDb(dbId);
                 Preconditions.checkNotNull(db);
                 lockedDbMap.put(dbId, db);
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/server/LocalMetastore.java b/fe/fe-core/src/main/java/com/starrocks/server/LocalMetastore.java
index 0d05d48a643b5a..f8ab87e29a6f46 100644
--- a/fe/fe-core/src/main/java/com/starrocks/server/LocalMetastore.java
+++ b/fe/fe-core/src/main/java/com/starrocks/server/LocalMetastore.java
@@ -623,7 +623,7 @@ public void recoverTable(RecoverTableStmt recoverStmt) throws DdlException {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            Table table = db.getTable(tableName);
+            Table table = getTable(db.getFullName(), tableName);
             if (table != null) {
                 ErrorReport.reportDdlException(ErrorCode.ERR_TABLE_EXISTS_ERROR, tableName);
             }
@@ -632,7 +632,7 @@ public void recoverTable(RecoverTableStmt recoverStmt) throws DdlException {
                 ErrorReport.reportDdlException(ErrorCode.ERR_BAD_TABLE_ERROR, tableName);
             }
 
-            Table recoverTable = db.getTable(tableName);
+            Table recoverTable = getTable(db.getFullName(), tableName);
             if (recoverTable instanceof OlapTable) {
                 DynamicPartitionUtil.registerOrRemovePartitionScheduleInfo(db.getId(), (OlapTable) recoverTable);
             }
@@ -654,7 +654,7 @@ public void recoverPartition(RecoverPartitionStmt recoverStmt) throws DdlExcepti
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            Table table = db.getTable(tableName);
+            Table table = getTable(db.getFullName(), tableName);
             if (table == null) {
                 ErrorReport.reportDdlException(ErrorCode.ERR_BAD_TABLE_ERROR, tableName);
             }
@@ -817,7 +817,7 @@ public boolean createTable(CreateTableStmt stmt) throws DdlException {
         locker.lockDatabase(db, LockType.READ);
         try {
             String tableName = stmt.getTableName();
-            if (!isTemporaryTable && db.getTable(tableName) != null) {
+            if (!isTemporaryTable && getTable(db.getFullName(), tableName) != null) {
                 if (!stmt.isSetIfNotExists()) {
                     ErrorReport.reportDdlException(ErrorCode.ERR_TABLE_EXISTS_ERROR, tableName);
                 }
@@ -867,7 +867,7 @@ public void addPartitions(ConnectContext ctx, Database db, String tableName, Add
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            Table table = db.getTable(tableName);
+            Table table = getTable(db.getFullName(), tableName);
             CatalogUtils.checkTableExist(db, tableName);
             CatalogUtils.checkNativeTable(db, table);
         } finally {
@@ -881,7 +881,7 @@ public void addPartitions(ConnectContext ctx, Database db, String tableName, Add
 
     private OlapTable checkTable(Database db, String tableName) throws DdlException {
         CatalogUtils.checkTableExist(db, tableName);
-        Table table = db.getTable(tableName);
+        Table table = getTable(db.getFullName(), tableName);
         CatalogUtils.checkNativeTable(db, table);
         OlapTable olapTable = (OlapTable) table;
         CatalogUtils.checkTableState(olapTable, tableName);
@@ -889,7 +889,7 @@ private OlapTable checkTable(Database db, String tableName) throws DdlException
     }
 
     private OlapTable checkTable(Database db, Long tableId) throws DdlException {
-        Table table = db.getTable(tableId);
+        Table table = getTable(db.getId(), tableId);
         if (table == null) {
             ErrorReport.reportDdlException(ErrorCode.ERR_BAD_TABLE_ERROR, tableId);
         }
@@ -1321,7 +1321,7 @@ public void replayAddPartition(PartitionPersistInfoV2 info) throws DdlException
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            OlapTable olapTable = (OlapTable) db.getTable(info.getTableId());
+            OlapTable olapTable = (OlapTable) getTable(db.getId(), info.getTableId());
             Partition partition = info.getPartition();
 
             PartitionInfo partitionInfo = olapTable.getPartitionInfo();
@@ -1380,7 +1380,7 @@ public void replayAddPartition(PartitionPersistInfo info) throws DdlException {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            OlapTable olapTable = (OlapTable) db.getTable(info.getTableId());
+            OlapTable olapTable = (OlapTable) getTable(db.getId(), info.getTableId());
             Partition partition = info.getPartition();
 
             PartitionInfo partitionInfo = olapTable.getPartitionInfo();
@@ -1491,7 +1491,7 @@ public void dropPartition(Database db, Table table, DropPartitionClause clause)
         if (!isTempPartition) {
             try {
                 for (MvId mvId : olapTable.getRelatedMaterializedViews()) {
-                    MaterializedView materializedView = (MaterializedView) db.getTable(mvId.getId());
+                    MaterializedView materializedView = (MaterializedView) getTable(db.getId(), mvId.getId());
                     if (materializedView != null && materializedView.isLoadTriggeredRefresh()) {
                         GlobalStateMgr.getCurrentState().getLocalMetastore().refreshMaterializedView(
                                 db.getFullName(), materializedView.getName(), false, null,
@@ -1527,7 +1527,7 @@ public void replayDropPartition(DropPartitionInfo info) {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            OlapTable olapTable = (OlapTable) db.getTable(info.getTableId());
+            OlapTable olapTable = (OlapTable) getTable(db.getId(), info.getTableId());
             if (info.isTempPartition()) {
                 olapTable.dropTempPartition(info.getPartitionName(), true);
             } else {
@@ -1547,7 +1547,7 @@ public void replayDropPartitions(DropPartitionsInfo info) {
                     + " table = " + info.getTableId()
                     + " partitionNames = " + info.getPartitionNames());
             List<String> partitionNames = info.getPartitionNames();
-            OlapTable olapTable = (OlapTable) db.getTable(info.getTableId());
+            OlapTable olapTable = (OlapTable) getTable(db.getId(), info.getTableId());
             boolean isTempPartition = info.isTempPartition();
             long dbId = info.getDbId();
             boolean isForceDrop = info.isForceDrop();
@@ -1573,7 +1573,7 @@ public void replayRecoverPartition(RecoverInfo info) {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            Table table = db.getTable(info.getTableId());
+            Table table = getTable(db.getId(), info.getTableId());
             recycleBin.replayRecoverPartition((OlapTable) table, info.getPartitionId());
         } finally {
             locker.unLockDatabase(db, LockType.WRITE);
@@ -1705,7 +1705,7 @@ public void replayAddSubPartition(PhysicalPartitionPersistInfoV2 info) throws Dd
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            OlapTable olapTable = (OlapTable) db.getTable(info.getTableId());
+            OlapTable olapTable = (OlapTable) getTable(db.getId(), info.getTableId());
             Partition partition = olapTable.getPartition(info.getPartitionId());
             PhysicalPartition physicalPartition = info.getPhysicalPartition();
             partition.addSubPartition(physicalPartition);
@@ -2596,7 +2596,7 @@ public void replayDropTable(Database db, long tableId, boolean isForceDrop) {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            table = db.getTable(tableId);
+            table = getTable(db.getId(), tableId);
             if (table.isTemporaryTable()) {
                 table = db.unprotectDropTemporaryTable(tableId, isForceDrop, false);
                 UUID sessionId = ((OlapTable) table).getSessionId();
@@ -2776,24 +2776,6 @@ public void replayBatchDeleteReplica(BatchDeleteReplicaInfo info) {
         }
     }
 
-    @Override
-    public Table getTable(String dbName, String tblName) {
-        Database database = getDb(dbName);
-        if (database == null) {
-            return null;
-        }
-        return database.getTable(tblName);
-    }
-
-    @Override
-    public Pair<Table, MaterializedIndexMeta> getMaterializedViewIndex(String dbName, String indexName) {
-        Database database = getDb(dbName);
-        if (database == null) {
-            return null;
-        }
-        return database.getMaterializedViewIndex(indexName);
-    }
-
     @Override
     public Database getDb(String name) {
         if (name == null) {
@@ -2820,6 +2802,22 @@ public Database getDb(long dbId) {
         return idToDb.get(dbId);
     }
 
+    public Optional<Database> mayGetDb(String name) {
+        return Optional.ofNullable(getDb(name));
+    }
+
+    public Optional<Database> mayGetDb(long dbId) {
+        return Optional.ofNullable(getDb(dbId));
+    }
+
+    public Optional<Table> mayGetTable(long dbId, long tableId) {
+        return mayGetDb(dbId).flatMap(db -> Optional.ofNullable(db.getTable(tableId)));
+    }
+
+    public Optional<Table> mayGetTable(String dbName, String tableName) {
+        return mayGetDb(dbName).flatMap(db -> Optional.ofNullable(db.getTable(tableName)));
+    }
+
     public ConcurrentHashMap<String, Database> getFullNameToDb() {
         return fullNameToDb;
     }
@@ -2832,8 +2830,43 @@ public Database getDbIncludeRecycleBin(long dbId) {
         return db;
     }
 
+    @Override
+    public Table getTable(String dbName, String tblName) {
+        Database database = getDb(dbName);
+        if (database == null) {
+            return null;
+        }
+        return database.getTable(tblName);
+    }
+
+    public Table getTable(Long dbId, Long tableId) {
+        Database database = getDb(dbId);
+        if (database == null) {
+            return null;
+        }
+        return database.getTable(tableId);
+    }
+
+    public List<Table> getTables(Long dbId) {
+        Database database = getDb(dbId);
+        if (database == null) {
+            return Collections.emptyList();
+        } else {
+            return database.getTables();
+        }
+    }
+
+    @Override
+    public Pair<Table, MaterializedIndexMeta> getMaterializedViewIndex(String dbName, String indexName) {
+        Database database = getDb(dbName);
+        if (database == null) {
+            return null;
+        }
+        return database.getMaterializedViewIndex(indexName);
+    }
+
     public Table getTableIncludeRecycleBin(Database db, long tableId) {
-        Table table = db.getTable(tableId);
+        Table table = getTable(db.getId(), tableId);
         if (table == null) {
             table = recycleBin.getTable(db.getId(), tableId);
         }
@@ -2994,7 +3027,7 @@ public HashMap<Long, TStorageMedium> getPartitionIdToStorageMediumMap() {
             Preconditions.checkState(locker.isDbWriteLockHeldByCurrentThread(db));
             try {
                 for (Long tableId : tableIdToPartitionIds.keySet()) {
-                    Table table = db.getTable(tableId);
+                    Table table = getTable(db.getId(), tableId);
                     if (table == null) {
                         continue;
                     }
@@ -3061,7 +3094,7 @@ public void createMaterializedView(CreateMaterializedViewStmt stmt)
         String tableName = stmt.getBaseIndexName();
         // check db
         String dbName = stmt.getDBName();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             ErrorReport.reportDdlException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
         }
@@ -3075,7 +3108,7 @@ public void createMaterializedView(CreateMaterializedViewStmt stmt)
             throw new DdlException("create materialized failed. database:" + db.getFullName() + " not exist");
         }
         try {
-            Table table = db.getTable(tableName);
+            Table table = getTable(db.getFullName(), tableName);
             if (table == null) {
                 throw new DdlException("create materialized failed. table:" + tableName + " not exist");
             }
@@ -3124,7 +3157,7 @@ public void createMaterializedView(CreateMaterializedViewStatement stmt)
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            if (db.getTable(mvName) != null) {
+            if (getTable(db.getFullName(), mvName) != null) {
                 if (stmt.isIfNotExists()) {
                     LOG.info("Create materialized view [{}] which already exists", mvName);
                     return;
@@ -3437,7 +3470,7 @@ public void dropMaterializedView(DropMaterializedViewStmt stmt) throws DdlExcept
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            table = db.getTable(stmt.getMvName());
+            table = getTable(db.getFullName(), stmt.getMvName());
         } finally {
             locker.unLockDatabase(db, LockType.READ);
         }
@@ -3492,7 +3525,7 @@ private MaterializedView getMaterializedViewToRefresh(String dbName, String mvNa
         if (db == null) {
             ErrorReport.reportDdlException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
         }
-        final Table table = db.getTable(mvName);
+        final Table table = getTable(db.getFullName(), mvName);
         MaterializedView materializedView = null;
         if (table instanceof MaterializedView) {
             materializedView = (MaterializedView) table;
@@ -3586,7 +3619,7 @@ public void renameTable(Database db, Table table, TableRenameClause tableRenameC
         }
 
         // check if name is already used
-        if (db.getTable(newTableName) != null) {
+        if (getTable(db.getFullName(), newTableName) != null) {
             throw new DdlException("Table name[" + newTableName + "] is already used");
         }
 
@@ -3613,7 +3646,8 @@ public void alterTableComment(Database db, Table table, AlterTableCommentClause
 
     public static void inactiveRelatedMaterializedView(Database db, Table olapTable, String reason) {
         for (MvId mvId : olapTable.getRelatedMaterializedViews()) {
-            MaterializedView mv = (MaterializedView) db.getTable(mvId.getId());
+            MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(db.getId(), mvId.getId());
             if (mv != null) {
                 LOG.warn("Inactive MV {}/{} because {}", mv.getName(), mv.getId(), reason);
                 mv.setInactiveAndReason(reason);
@@ -3636,7 +3670,7 @@ public void replayRenameTable(TableInfo tableInfo) {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            OlapTable table = (OlapTable) db.getTable(tableId);
+            OlapTable table = (OlapTable) getTable(db.getId(), tableId);
             String tableName = table.getName();
             db.dropTable(tableName);
             table.setName(newTableName);
@@ -3697,7 +3731,7 @@ public void replayRenamePartition(TableInfo tableInfo) {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            OlapTable table = (OlapTable) db.getTable(tableId);
+            OlapTable table = (OlapTable) getTable(db.getId(), tableId);
             Partition partition = table.getPartition(partitionId);
             table.renamePartition(partition.getName(), newPartitionName);
             LOG.info("replay rename partition[{}] to {}", partition.getName(), newPartitionName);
@@ -3751,7 +3785,7 @@ public void replayRenameRollup(TableInfo tableInfo) {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            OlapTable table = (OlapTable) db.getTable(tableId);
+            OlapTable table = (OlapTable) getTable(db.getId(), tableId);
             String rollupName = table.getIndexNameById(indexId);
             Map<String, Long> indexNameToIdMap = table.getIndexNameToId();
             indexNameToIdMap.remove(rollupName);
@@ -3802,7 +3836,7 @@ public void replayRenameColumn(ColumnRenameInfo columnRenameInfo) throws DdlExce
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            OlapTable olapTable = (OlapTable) db.getTable(tableId);
+            OlapTable olapTable = (OlapTable) getTable(db.getId(), tableId);
             olapTable.renameColumn(colName, newColName);
             LOG.info("replay rename column[{}] to {}", colName, newColName);
         } finally {
@@ -4107,7 +4141,7 @@ public void modifyTableConstraint(Database db, String tableName, Map<String, Str
             throws DdlException {
         Locker locker = new Locker();
         Preconditions.checkArgument(locker.isDbWriteLockHeldByCurrentThread(db));
-        Table table = db.getTable(tableName);
+        Table table = getTable(db.getFullName(), tableName);
         if (table == null) {
             throw new DdlException(String.format("table:%s does not exist", tableName));
         }
@@ -4242,7 +4276,7 @@ public void setHasForbiddenGlobalDict(String dbName, String tableName, boolean i
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            Table table = db.getTable(tableName);
+            Table table = getTable(db.getFullName(), tableName);
             if (table == null) {
                 throw new DdlException("the DB " + dbName + " table: " + tableName + "isn't  exist");
             }
@@ -4279,7 +4313,7 @@ public void replayModifyHiveTableColumn(short opCode, ModifyTableColumnOperation
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            Table tbl = db.getTable(hiveExternalTable);
+            Table tbl = getTable(db.getFullName(), hiveExternalTable);
             table = (HiveTable) tbl;
             table.setNewFullSchema(columns);
         } finally {
@@ -4297,7 +4331,7 @@ public void replayModifyTableProperty(short opCode, ModifyTablePropertyOperation
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            OlapTable olapTable = (OlapTable) db.getTable(tableId);
+            OlapTable olapTable = (OlapTable) getTable(db.getId(), tableId);
             if (opCode == OperationType.OP_SET_FORBIDDEN_GLOBAL_DICT) {
                 String enAble = properties.get(PropertyAnalyzer.ENABLE_LOW_CARD_DICT_TYPE);
                 Preconditions.checkState(enAble != null);
@@ -4374,7 +4408,7 @@ public void createView(CreateViewStmt stmt) throws DdlException {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            if (db.getTable(tableName) != null) {
+            if (getTable(db.getFullName(), tableName) != null) {
                 existed = true;
                 if (stmt.isSetIfNotExists()) {
                     LOG.info("create view[{}] which already exists", tableName);
@@ -4525,7 +4559,7 @@ public void truncateTable(TruncateTableStmt truncateTableStmt, ConnectContext co
         // Things may be changed outside the database lock.
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            OlapTable olapTable = (OlapTable) db.getTable(copiedTbl.getId());
+            OlapTable olapTable = (OlapTable) getTable(db.getId(), copiedTbl.getId());
             if (olapTable == null) {
                 throw new DdlException("Table[" + copiedTbl.getName() + "] is dropped");
             }
@@ -4590,13 +4624,13 @@ public void truncateTable(TruncateTableStmt truncateTableStmt, ConnectContext co
             // refresh mv
             Set<MvId> relatedMvs = olapTable.getRelatedMaterializedViews();
             for (MvId mvId : relatedMvs) {
-                MaterializedView materializedView = (MaterializedView) db.getTable(mvId.getId());
+                MaterializedView materializedView = (MaterializedView) getTable(db.getId(), mvId.getId());
                 if (materializedView == null) {
                     LOG.warn("Table related materialized view {} can not be found", mvId.getId());
                     continue;
                 }
                 if (materializedView.isLoadTriggeredRefresh()) {
-                    refreshMaterializedView(db.getFullName(), db.getTable(mvId.getId()).getName(), false, null,
+                    refreshMaterializedView(db.getFullName(), getTable(db.getId(), mvId.getId()).getName(), false, null,
                             Constants.TaskRunPriority.NORMAL.value(), true, false);
                 }
             }
@@ -4660,7 +4694,7 @@ public void replayTruncateTable(TruncateTableInfo info) {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            OlapTable olapTable = (OlapTable) db.getTable(info.getTblId());
+            OlapTable olapTable = (OlapTable) getTable(db.getId(), info.getTblId());
             truncateTableInternal(olapTable, info.getPartitions(), info.isEntireTable(), true);
 
             if (!GlobalStateMgr.isCheckpointThread()) {
@@ -4724,7 +4758,7 @@ public void replayBackendTabletsInfo(BackendTabletsInfo backendTabletsInfo) {
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.WRITE);
             try {
-                OlapTable tbl = (OlapTable) db.getTable(info.getTableId());
+                OlapTable tbl = (OlapTable) getTable(db.getId(), info.getTableId());
                 if (tbl == null) {
                     continue;
                 }
@@ -4765,7 +4799,7 @@ public void replayConvertDistributionType(TableInfo tableInfo) {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            OlapTable tbl = (OlapTable) db.getTable(tableInfo.getTableId());
+            OlapTable tbl = (OlapTable) getTable(db.getId(), tableInfo.getTableId());
             LOG.info("replay modify distribution type of table: " + tbl.getName());
         } finally {
             locker.unLockDatabase(db, LockType.WRITE);
@@ -4786,7 +4820,7 @@ public void replaceTempPartition(Database db, String tableName, ReplacePartition
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            Table table = db.getTable(tableName);
+            Table table = getTable(db.getFullName(), tableName);
             if (table == null) {
                 ErrorReport.reportDdlException(ErrorCode.ERR_BAD_TABLE_ERROR, tableName);
             }
@@ -4831,7 +4865,7 @@ public void replayReplaceTempPartition(ReplacePartitionOperationLog replaceTempP
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
         try {
-            OlapTable olapTable = (OlapTable) db.getTable(replaceTempPartitionLog.getTblId());
+            OlapTable olapTable = (OlapTable) getTable(db.getId(), replaceTempPartitionLog.getTblId());
             if (olapTable == null) {
                 return;
             }
@@ -4919,7 +4953,7 @@ public void setPartitionVersion(AdminSetPartitionVersionStmt stmt) {
         Locker locker = new Locker();
         locker.lockDatabase(database, LockType.WRITE);
         try {
-            Table table = database.getTable(stmt.getTableName().getTbl());
+            Table table = getTable(database.getFullName(), stmt.getTableName().getTbl());
             if (table == null) {
                 throw ErrorReportException.report(ErrorCode.ERR_BAD_TABLE_ERROR, stmt.getTableName().getTbl());
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/server/MetadataMgr.java b/fe/fe-core/src/main/java/com/starrocks/server/MetadataMgr.java
index 4fec339b5ab59b..e10ada5c431d3d 100644
--- a/fe/fe-core/src/main/java/com/starrocks/server/MetadataMgr.java
+++ b/fe/fe-core/src/main/java/com/starrocks/server/MetadataMgr.java
@@ -521,14 +521,6 @@ public Table getTable(String catalogName, String dbName, String tblName) {
         return connectorTable;
     }
 
-    public Table getTable(Long databaseId, Long tableId) {
-        Database database = localMetastore.getDb(databaseId);
-        if (database == null) {
-            return null;
-        }
-        return database.getTable(tableId);
-    }
-
     public TableVersionRange getTableVersionRange(String dbName, Table table,
                                                   Optional<ConnectorTableVersion> startVersion,
                                                   Optional<ConnectorTableVersion> endVersion) {
@@ -547,7 +539,7 @@ public Optional<Database> getDatabase(BaseTableInfo baseTableInfo) {
 
     public Optional<Table> getTable(BaseTableInfo baseTableInfo) {
         if (baseTableInfo.isInternalCatalog()) {
-            return Optional.ofNullable(getTable(baseTableInfo.getDbId(), baseTableInfo.getTableId()));
+            return Optional.ofNullable(localMetastore.getTable(baseTableInfo.getDbId(), baseTableInfo.getTableId()));
         } else {
             return Optional.ofNullable(
                     getTable(baseTableInfo.getCatalogName(), baseTableInfo.getDbName(), baseTableInfo.getTableName()));
@@ -588,7 +580,7 @@ public Table getTemporaryTable(UUID sessionId, String catalogName, Long database
         if (database == null) {
             return null;
         }
-        return database.getTable(tableId);
+        return localMetastore.getTable(database.getId(), tableId);
     }
 
     public boolean tableExists(String catalogName, String dbName, String tblName) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/service/FrontendServiceImpl.java b/fe/fe-core/src/main/java/com/starrocks/service/FrontendServiceImpl.java
index a2d935f6e84b1c..c981b44577b033 100644
--- a/fe/fe-core/src/main/java/com/starrocks/service/FrontendServiceImpl.java
+++ b/fe/fe-core/src/main/java/com/starrocks/service/FrontendServiceImpl.java
@@ -68,6 +68,7 @@
 import com.starrocks.catalog.Tablet;
 import com.starrocks.catalog.View;
 import com.starrocks.catalog.system.information.TaskRunsSystemTable;
+import com.starrocks.catalog.system.information.TasksSystemTable;
 import com.starrocks.catalog.system.sys.GrantsTo;
 import com.starrocks.catalog.system.sys.RoleEdges;
 import com.starrocks.catalog.system.sys.SysFeLocks;
@@ -92,6 +93,7 @@
 import com.starrocks.common.util.DateUtils;
 import com.starrocks.common.util.DebugUtil;
 import com.starrocks.common.util.ProfileManager;
+import com.starrocks.common.util.concurrent.lock.AutoCloseableLock;
 import com.starrocks.common.util.concurrent.lock.LockTimeoutException;
 import com.starrocks.common.util.concurrent.lock.LockType;
 import com.starrocks.common.util.concurrent.lock.Locker;
@@ -136,9 +138,6 @@
 import com.starrocks.qe.VariableMgr;
 import com.starrocks.qe.scheduler.Coordinator;
 import com.starrocks.qe.scheduler.slot.LogicalSlot;
-import com.starrocks.scheduler.Constants;
-import com.starrocks.scheduler.Task;
-import com.starrocks.scheduler.TaskManager;
 import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.server.MetadataMgr;
 import com.starrocks.server.TemporaryTableMgr;
@@ -490,7 +489,7 @@ public TListTableStatusResult listTableStatus(TGetTablesParams params) throws TE
             }
         }
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(params.db);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(params.db);
         long limit = params.isSetLimit() ? params.getLimit() : -1;
         UserIdentity currentUser;
         if (params.isSetCurrent_user_ident()) {
@@ -503,7 +502,8 @@ public TListTableStatusResult listTableStatus(TGetTablesParams params) throws TE
             locker.lockDatabase(db, LockType.READ);
             try {
                 boolean listingViews = params.isSetType() && TTableType.VIEW.equals(params.getType());
-                List<Table> tables = listingViews ? db.getViews() : db.getTables();
+                List<Table> tables = listingViews ? db.getViews() :
+                        GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId());
                 OUTER:
                 for (Table table : tables) {
                     try {
@@ -536,7 +536,8 @@ public TListTableStatusResult listTableStatus(TGetTablesParams params) throws TE
                         try {
                             List<TableName> allTables = view.getTableRefs();
                             for (TableName tableName : allTables) {
-                                Table tbl = db.getTable(tableName.getTbl());
+                                Table tbl = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                            .getTable(db.getFullName(), tableName.getTbl());
                                 if (tbl != null) {
                                     try {
                                         Authorizer.checkAnyActionOnTableLikeObject(currentUser,
@@ -599,7 +600,7 @@ public TListPipesResult listPipes(TListPipesParams params) throws TException {
         Map<PipeId, Pipe> pipes = pm.getPipesUnlock();
         TListPipesResult result = new TListPipesResult();
         for (Pipe pipe : pipes.values()) {
-            String databaseName = GlobalStateMgr.getCurrentState().mayGetDb(pipe.getPipeId().getDbId())
+            String databaseName = GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetDb(pipe.getPipeId().getDbId())
                     .map(Database::getOriginName)
                     .orElse(null);
 
@@ -647,7 +648,7 @@ public TListPipeFilesResult listPipeFiles(TListPipeFilesParams params) throws TE
             file.setPipe_id(record.pipeId);
             file.setDatabase_name(
                     mayPipe.flatMap(p ->
-                                    GlobalStateMgr.getCurrentState().mayGetDb(p.getDbAndName().first)
+                                    GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetDb(p.getDbAndName().first)
                                             .map(Database::getOriginName))
                             .orElse(""));
             file.setPipe_name(mayPipe.map(Pipe::getName).orElse(""));
@@ -695,7 +696,7 @@ private TListMaterializedViewStatusResult listMaterializedViewStatus(long limit,
         List<TMaterializedViewStatus> tablesResult = Lists.newArrayList();
         result.setMaterialized_views(tablesResult);
         String dbName = params.getDb();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             LOG.warn("database not exists: {}", dbName);
             return result;
@@ -766,13 +767,13 @@ private void filterSynchronousMaterializedView(OlapTable olapTable, PatternMatch
     private List<ShowMaterializedViewStatus> listMaterializedViews(long limit, PatternMatcher matcher,
                                                                    UserIdentity currentUser, TGetTablesParams params) {
         String dbName = params.getDb();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         List<MaterializedView> materializedViews = Lists.newArrayList();
         List<Pair<OlapTable, MaterializedIndexMeta>> singleTableMVs = Lists.newArrayList();
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            for (Table table : db.getTables()) {
+            for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                 if (table.isMaterializedView()) {
                     filterAsynchronousMaterializedView(matcher, currentUser, dbName,
                             (MaterializedView) table, params, materializedViews);
@@ -797,50 +798,11 @@ private List<ShowMaterializedViewStatus> listMaterializedViews(long limit, Patte
     @Override
     public TGetTaskInfoResult getTasks(TGetTasksParams params) throws TException {
         LOG.debug("get show task request: {}", params);
+
+        List<TTaskInfo> tasksResult = TasksSystemTable.query(params);
         TGetTaskInfoResult result = new TGetTaskInfoResult();
-        List<TTaskInfo> tasksResult = Lists.newArrayList();
         result.setTasks(tasksResult);
 
-        UserIdentity currentUser = null;
-        if (params.isSetCurrent_user_ident()) {
-            currentUser = UserIdentity.fromThrift(params.current_user_ident);
-        }
-        GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
-        TaskManager taskManager = globalStateMgr.getTaskManager();
-        List<Task> taskList = taskManager.filterTasks(params);
-
-        for (Task task : taskList) {
-            if (task.getDbName() == null) {
-                LOG.warn("Ignore the task db because information is incorrect: " + task);
-                continue;
-            }
-
-            try {
-                Authorizer.checkAnyActionOnOrInDb(currentUser, null, InternalCatalog.DEFAULT_INTERNAL_CATALOG_NAME,
-                        task.getDbName());
-            } catch (AccessDeniedException e) {
-                continue;
-            }
-
-            TTaskInfo info = new TTaskInfo();
-            info.setTask_name(task.getName());
-            info.setCreate_time(task.getCreateTime() / 1000);
-            String scheduleStr = "UNKNOWN";
-            if (task.getType() != null) {
-                scheduleStr = task.getType().name();
-            }
-            if (task.getType() == Constants.TaskType.PERIODICAL) {
-                scheduleStr += task.getSchedule();
-            }
-            info.setSchedule(scheduleStr);
-            info.setCatalog(task.getCatalogName());
-            info.setDatabase(ClusterNamespace.getNameFromFullName(task.getDbName()));
-            info.setDefinition(task.getDefinition());
-            info.setExpire_time(task.getExpireTime() / 1000);
-            info.setProperties(task.getPropertiesString());
-            tasksResult.add(info);
-        }
-
         return result;
     }
 
@@ -984,13 +946,13 @@ private void describeWithoutDbAndTable(UserIdentity currentUser, List<TColumnDef
             } catch (AccessDeniedException e) {
                 continue;
             }
-            Database db = GlobalStateMgr.getCurrentState().getDb(fullName);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(fullName);
             if (db != null) {
                 Locker locker = new Locker();
                 for (String tableName : db.getTableNamesViewWithLock()) {
                     try {
                         locker.lockDatabase(db, LockType.READ);
-                        Table table = db.getTable(tableName);
+                        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
                         if (table == null) {
                             continue;
                         }
@@ -1252,11 +1214,11 @@ private long loadTxnBeginImpl(TLoadTxnBeginRequest request, String clientIp) thr
         // check database
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
         String dbName = request.getDb();
-        Database db = globalStateMgr.getDb(dbName);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new UserException("unknown database, database=" + dbName);
         }
-        Table table = db.getTable(request.getTbl());
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), request.getTbl());
         if (table == null) {
             throw new UserException("unknown table \"" + request.getDb() + "." + request.getTbl() + "\"");
         }
@@ -1348,7 +1310,7 @@ void loadTxnCommitImpl(TLoadTxnCommitRequest request, TStatus status) throws Use
         // get database
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
         String dbName = request.getDb();
-        Database db = globalStateMgr.getDb(dbName);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new UserException("unknown database, database=" + dbName);
         }
@@ -1382,7 +1344,7 @@ void loadTxnCommitImpl(TLoadTxnCommitRequest request, TStatus status) throws Use
             return;
         }
         // collect table-level metrics
-        Table tbl = db.getTable(request.getTbl());
+        Table tbl = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), request.getTbl());
         if (null == tbl) {
             return;
         }
@@ -1444,7 +1406,7 @@ public TGetLoadTxnStatusResult getLoadTxnStatus(TGetLoadTxnStatusRequest request
         // get database
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
         String dbName = request.getDb();
-        Database db = globalStateMgr.getDb(dbName);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbName);
         if (db == null) {
             LOG.warn("unknown database, database=" + dbName);
             result.setStatus(TTransactionStatus.UNKNOWN);
@@ -1507,7 +1469,7 @@ private void loadTxnPrepareImpl(TLoadTxnCommitRequest request) throws UserExcept
         // get database
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
         String dbName = request.getDb();
-        Database db = globalStateMgr.getDb(dbName);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new UserException("unknown database, database=" + dbName);
         }
@@ -1567,7 +1529,7 @@ private void loadTxnRollbackImpl(TLoadTxnRollbackRequest request) throws UserExc
                     request.getTbl(), request.getUser_ip());
         }
         String dbName = request.getDb();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new MetaNotFoundException("db " + dbName + " does not exist");
         }
@@ -1653,12 +1615,12 @@ TExecPlanFragmentParams streamLoadPutImpl(TStreamLoadPutRequest request) throws
 
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
         String dbName = request.getDb();
-        Database db = globalStateMgr.getDb(dbName);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbName);
         if (db == null) {
             throw new UserException("unknown database, database=" + dbName);
         }
 
-        Table table = db.getTable(request.getTbl());
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), request.getTbl());
         if (table == null) {
             throw new UserException("unknown table, table=" + request.getTbl());
         }
@@ -1940,7 +1902,7 @@ public synchronized TImmutablePartitionResult updateImmutablePartitionInternal(T
         TImmutablePartitionResult result = new TImmutablePartitionResult();
         TStatus errorStatus = new TStatus(RUNTIME_ERROR);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             errorStatus.setError_msgs(
                     Lists.newArrayList(String.format("dbId=%d is not exists", dbId)));
@@ -1948,7 +1910,7 @@ public synchronized TImmutablePartitionResult updateImmutablePartitionInternal(T
             return result;
         }
         Locker locker = new Locker();
-        Table table = db.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             errorStatus.setError_msgs(
                     Lists.newArrayList(String.format("dbId=%d tableId=%d is not exists", dbId, tableId)));
@@ -2187,13 +2149,13 @@ private static TCreatePartitionResult createPartitionProcess(TCreatePartitionReq
         TCreatePartitionResult result = new TCreatePartitionResult();
         TStatus errorStatus = new TStatus(RUNTIME_ERROR);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             errorStatus.setError_msgs(Lists.newArrayList(String.format("dbId=%d is not exists", dbId)));
             result.setStatus(errorStatus);
             return result;
         }
-        Table table = db.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             errorStatus.setError_msgs(Lists.newArrayList(String.format("dbId=%d tableId=%d is not exists", dbId, tableId)));
             result.setStatus(errorStatus);
@@ -2223,7 +2185,8 @@ private static TCreatePartitionResult createPartitionProcess(TCreatePartitionReq
 
         AddPartitionClause addPartitionClause;
         List<String> partitionColNames = Lists.newArrayList();
-        try {
+        try (AutoCloseableLock ignore = new AutoCloseableLock(new Locker(), db, Lists.newArrayList(table.getId()),
+                LockType.READ)) {
             addPartitionClause = AnalyzerUtils.getAddPartitionClauseFromPartitionValues(olapTable,
                     request.partition_values);
             PartitionDesc partitionDesc = addPartitionClause.getPartitionDesc();
@@ -2299,8 +2262,11 @@ private static TCreatePartitionResult createPartitionProcess(TCreatePartitionReq
             if (txnState.getWarehouseId() != WarehouseManager.DEFAULT_WAREHOUSE_ID) {
                 ctx.setCurrentWarehouseId(txnState.getWarehouseId());
             }
-            AlterTableClauseAnalyzer analyzer = new AlterTableClauseAnalyzer(olapTable);
-            analyzer.analyze(ctx, addPartitionClause);
+            try (AutoCloseableLock ignore = new AutoCloseableLock(new Locker(), db, Lists.newArrayList(table.getId()),
+                    LockType.READ)) {
+                AlterTableClauseAnalyzer analyzer = new AlterTableClauseAnalyzer(olapTable);
+                analyzer.analyze(ctx, addPartitionClause);
+            }
             state.getLocalMetastore().addPartitions(ctx, db, olapTable.getName(), addPartitionClause);
         } catch (Exception e) {
             LOG.warn("failed to cancel alter operation", e);
@@ -2572,7 +2538,7 @@ public TGetLoadsResult getLoads(TGetLoadsParams request) throws TException {
                     loads.add(job.toThrift());
                 }
             } else if (request.isSetDb()) {
-                long dbId = GlobalStateMgr.getCurrentState().getDb(request.getDb()).getId();
+                long dbId = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(request.getDb()).getId();
                 if (request.isSetLabel()) {
                     loads.addAll(GlobalStateMgr.getCurrentState().getLoadMgr().getLoadJobsByDb(
                                     dbId, request.getLabel(), true).stream()
@@ -2820,11 +2786,11 @@ public TReleaseSlotResponse releaseSlot(TReleaseSlotRequest request) throws TExc
 
     @Override
     public TGetDictQueryParamResponse getDictQueryParam(TGetDictQueryParamRequest request) throws TException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(request.getDb_name());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(request.getDb_name());
         if (db == null) {
             throw new SemanticException("Database %s is not found", request.getDb_name());
         }
-        Table table = db.getTable(request.getTable_name());
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), request.getTable_name());
         if (table == null) {
             throw new SemanticException("dict table %s is not found", request.getTable_name());
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/service/InformationSchemaDataSource.java b/fe/fe-core/src/main/java/com/starrocks/service/InformationSchemaDataSource.java
index ff50002654631a..bb90e1b7b5bde7 100644
--- a/fe/fe-core/src/main/java/com/starrocks/service/InformationSchemaDataSource.java
+++ b/fe/fe-core/src/main/java/com/starrocks/service/InformationSchemaDataSource.java
@@ -150,12 +150,12 @@ public static TGetTablesConfigResponse generateTablesConfigResponse(TGetTablesCo
         AuthDbRequestResult result = getAuthDbRequestResult(request.getAuth_info());
 
         for (String dbName : result.authorizedDbs) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
             if (db != null) {
                 Locker locker = new Locker();
                 locker.lockDatabase(db, LockType.READ);
                 try {
-                    List<Table> allTables = db.getTables();
+                    List<Table> allTables = GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId());
                     for (Table table : allTables) {
                         try {
                             Authorizer.checkAnyActionOnTableLikeObject(result.currentUser,
@@ -257,11 +257,11 @@ public static TGetPartitionsMetaResponse generatePartitionsMetaResponse(TGetPart
         AuthDbRequestResult result = getAuthDbRequestResult(request.getAuth_info());
 
         for (String dbName : result.authorizedDbs) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
             if (db == null) {
                 continue;
             }
-            List<Table> allTables = db.getTables();
+            List<Table> allTables = GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId());
             for (Table table : allTables) {
                 try {
                     Authorizer.checkAnyActionOnTableLikeObject(result.currentUser,
@@ -529,7 +529,7 @@ public static TGetTemporaryTablesInfoResponse generateTemporaryTablesInfoRespons
                     for (Map.Entry<Long, UUID> entry : tableMap.entrySet()) {
                         UUID sessionId = entry.getValue();
                         Long tableId = entry.getKey();
-                        Table table = db.getTable(tableId);
+                        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
                         if (table != null) {
                             TTableInfo info = new TTableInfo();
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/StatementPlanner.java b/fe/fe-core/src/main/java/com/starrocks/sql/StatementPlanner.java
index 1b83b6a8821314..2f35607191b033 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/StatementPlanner.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/StatementPlanner.java
@@ -27,6 +27,8 @@
 import com.starrocks.common.AnalysisException;
 import com.starrocks.common.Config;
 import com.starrocks.common.DuplicatedRequestException;
+import com.starrocks.common.ErrorCode;
+import com.starrocks.common.ErrorReport;
 import com.starrocks.common.LabelAlreadyUsedException;
 import com.starrocks.common.profile.Timer;
 import com.starrocks.common.profile.Tracers;
@@ -430,12 +432,15 @@ private static void beginTransaction(DmlStmt stmt, ConnectContext session)
             }
         }
 
-        MetaUtils.normalizationTableName(session, stmt.getTableName());
+        stmt.getTableName().normalization(session);
         String catalogName = stmt.getTableName().getCatalog();
         String dbName = stmt.getTableName().getDb();
         String tableName = stmt.getTableName().getTbl();
 
-        Database db = MetaUtils.getDatabase(catalogName, dbName);
+        Database db = GlobalStateMgr.getCurrentState().getMetadataMgr().getDb(catalogName, dbName);
+        if (db == null) {
+            ErrorReport.reportSemanticException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
+        }
         Table targetTable = MetaUtils.getSessionAwareTable(session, db, stmt.getTableName());
         if (targetTable == null) {
             throw new SemanticException("Table %s is not found", tableName);
@@ -521,10 +526,13 @@ private static void abortTransaction(DmlStmt stmt, ConnectContext session, Strin
             return;
         }
 
-        MetaUtils.normalizationTableName(session, stmt.getTableName());
+        stmt.getTableName().normalization(session);
         String catalogName = stmt.getTableName().getCatalog();
         String dbName = stmt.getTableName().getDb();
-        Database db = MetaUtils.getDatabase(catalogName, dbName);
+        Database db = GlobalStateMgr.getCurrentState().getMetadataMgr().getDb(catalogName, dbName);
+        if (db == null) {
+            ErrorReport.reportSemanticException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
+        }
         Table targetTable = MetaUtils.getSessionAwareTable(session, db, stmt.getTableName());
         try {
             if (targetTable instanceof ExternalOlapTable) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AlterTableStatementAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AlterTableStatementAnalyzer.java
index ec212d8fff2660..9015f51a80950d 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AlterTableStatementAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AlterTableStatementAnalyzer.java
@@ -40,7 +40,7 @@
 public class AlterTableStatementAnalyzer {
     public static void analyze(AlterTableStmt statement, ConnectContext context) {
         TableName tbl = statement.getTbl();
-        MetaUtils.normalizationTableName(context, tbl);
+        tbl.normalization(context);
         MetaUtils.checkNotSupportCatalog(tbl.getCatalog(), "ALTER");
 
         List<AlterClause> alterClauseList = statement.getAlterClauseList();
@@ -50,7 +50,11 @@ public static void analyze(AlterTableStmt statement, ConnectContext context) {
 
         checkAlterOpConflict(alterClauseList);
 
-        Database db = MetaUtils.getDatabase(context, tbl);
+        Database db = GlobalStateMgr.getCurrentState().getMetadataMgr().getDb(tbl.getCatalog(), tbl.getDb());
+        if (db == null) {
+            throw new SemanticException("Database %s is not found", tbl.getCatalogAndDb());
+        }
+
         if (alterClauseList.stream().map(AlterClause::getOpType).anyMatch(AlterOpType::needCheckCapacity)) {
             try {
                 GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo().checkClusterCapacity();
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AnalyzeStmtAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AnalyzeStmtAnalyzer.java
index d8a74e303dbb5a..f7d6755b76a401 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AnalyzeStmtAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AnalyzeStmtAnalyzer.java
@@ -100,7 +100,7 @@ public void analyze(StatementBase statement, ConnectContext session) {
 
         @Override
         public Void visitAnalyzeStatement(AnalyzeStmt statement, ConnectContext session) {
-            MetaUtils.normalizationTableName(session, statement.getTableName());
+            statement.getTableName().normalization(session);
             Table analyzeTable = MetaUtils.getSessionAwareTable(session, null, statement.getTableName());
 
             if (StatisticUtils.statisticDatabaseBlackListCheck(statement.getTableName().getDb())) {
@@ -178,7 +178,10 @@ public Void visitCreateAnalyzeJobStatement(CreateAnalyzeJobStmt statement, Conne
                 }
 
                 if (null != tbl.getDb() && null == tbl.getTbl()) {
-                    Database db = MetaUtils.getDatabase(session, tbl);
+                    Database db = GlobalStateMgr.getCurrentState().getMetadataMgr().getDb(tbl.getCatalog(), tbl.getDb());
+                    if (db == null) {
+                        throw new SemanticException("Database %s is not found", tbl.getCatalogAndDb());
+                    }
 
                     if (statement.isNative() &&
                             StatisticUtils.statisticDatabaseBlackListCheck(statement.getTableName().getDb())) {
@@ -187,8 +190,12 @@ public Void visitCreateAnalyzeJobStatement(CreateAnalyzeJobStmt statement, Conne
 
                     statement.setDbId(db.getId());
                 } else if (null != statement.getTableName().getTbl()) {
-                    MetaUtils.normalizationTableName(session, statement.getTableName());
-                    Database db = MetaUtils.getDatabase(session, statement.getTableName());
+                    statement.getTableName().normalization(session);
+                    Database db = GlobalStateMgr.getCurrentState().getMetadataMgr()
+                            .getDb(statement.getTableName().getCatalog(), statement.getTableName().getDb());
+                    if (db == null) {
+                        throw new SemanticException("Database %s is not found", statement.getTableName().getCatalogAndDb());
+                    }
                     Table analyzeTable = MetaUtils.getSessionAwareTable(session, db, statement.getTableName());
 
                     if (analyzeTable.isTemporaryTable()) {
@@ -339,7 +346,7 @@ private void analyzeAnalyzeTypeDesc(ConnectContext session, AnalyzeStmt statemen
 
         @Override
         public Void visitDropStatsStatement(DropStatsStmt statement, ConnectContext session) {
-            MetaUtils.normalizationTableName(session, statement.getTableName());
+            statement.getTableName().normalization(session);
             if (CatalogMgr.isExternalCatalog(statement.getTableName().getCatalog())) {
                 statement.setExternal(true);
             }
@@ -348,7 +355,7 @@ public Void visitDropStatsStatement(DropStatsStmt statement, ConnectContext sess
 
         @Override
         public Void visitDropHistogramStatement(DropHistogramStmt statement, ConnectContext session) {
-            MetaUtils.normalizationTableName(session, statement.getTableName());
+            statement.getTableName().normalization(session);
             if (CatalogMgr.isExternalCatalog(statement.getTableName().getCatalog())) {
                 statement.setExternal(true);
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AnalyzerUtils.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AnalyzerUtils.java
index e27381cea467a1..a9de758121bf5b 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AnalyzerUtils.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AnalyzerUtils.java
@@ -207,7 +207,7 @@ public static Function getDBUdfFunction(ConnectContext context, FunctionName fnN
             dbName = context.getDatabase();
         }
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             return null;
         }
@@ -384,7 +384,7 @@ private void getDB(TableName tableName) {
                 return;
             }
 
-            Database db = session.getGlobalStateMgr().getDb(dbName);
+            Database db = session.getGlobalStateMgr().getLocalMetastore().getDb(dbName);
             if (db == null) {
                 return;
             }
@@ -711,6 +711,12 @@ public static Map<TableName, Relation> collectAllTableAndViewRelations(ParseNode
         return allTableAndViewRelations;
     }
 
+    public static List<FileTableFunctionRelation> collectFileTableFunctionRelation(StatementBase statementBase) {
+        List<FileTableFunctionRelation> fileTableFunctionRelations = Lists.newArrayList();
+        new AnalyzerUtils.FileTableFunctionRelationsCollector(fileTableFunctionRelations).visit(statementBase);
+        return fileTableFunctionRelations;
+    }
+
     /**
      * CopySafe:
      * 1. OlapTable & MaterializedView, that support the copyOnlyForQuery interface
@@ -1089,12 +1095,27 @@ public Void visitTable(TableRelation node, Void context) {
         }
     }
 
+    private static class FileTableFunctionRelationsCollector extends AstTraverser<Void, Void> {
+
+        private final List<FileTableFunctionRelation> fileTableFunctionRelations;
+
+        public FileTableFunctionRelationsCollector(List<FileTableFunctionRelation> fileTableFunctionRelations) {
+            this.fileTableFunctionRelations = fileTableFunctionRelations;
+        }
+
+        @Override
+        public Void visitFileTableFunction(FileTableFunctionRelation node, Void context) {
+            fileTableFunctionRelations.add(node);
+            return null;
+        }
+    }
+
     public static Set<TableName> getAllTableNamesForAnalyzeJobStmt(long dbId, long tableId) {
         Set<TableName> tableNames = Sets.newHashSet();
         if (StatsConstants.DEFAULT_ALL_ID != tableId && StatsConstants.DEFAULT_ALL_ID != dbId) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (db != null && !db.isSystemDatabase()) {
-                Table table = db.getTable(tableId);
+                Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
                 if (table != null && table.isOlapOrCloudNativeTable()) {
                     tableNames.add(new TableName(InternalCatalog.DEFAULT_INTERNAL_CATALOG_NAME,
                             db.getFullName(), table.getName()));
@@ -1113,9 +1134,9 @@ public static Set<TableName> getAllTableNamesForAnalyzeJobStmt(long dbId, long t
     }
 
     private static void getTableNamesInDb(Set<TableName> tableNames, Long id) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(id);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(id);
         if (db != null && !db.isSystemDatabase()) {
-            for (Table table : db.getTables()) {
+            for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                 if (table == null || !table.isOlapOrCloudNativeTable()) {
                     continue;
                 }
@@ -1505,7 +1526,8 @@ public static Type replaceNullType2Boolean(Type type) {
         } else if (type.isStructType()) {
             ArrayList<StructField> newFields = Lists.newArrayList();
             for (StructField sf : ((StructType) type).getFields()) {
-                newFields.add(new StructField(sf.getName(), replaceNullType2Boolean(sf.getType()), sf.getComment()));
+                newFields.add(new StructField(sf.getName(), sf.getFieldId(),
+                        replaceNullType2Boolean(sf.getType()), sf.getComment()));
             }
             return new StructType(newFields);
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AuthorizationAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AuthorizationAnalyzer.java
index a3ae0f8124d700..1fce803df76a92 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AuthorizationAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AuthorizationAnalyzer.java
@@ -45,7 +45,6 @@
 import com.starrocks.sql.ast.StatementBase;
 import com.starrocks.sql.ast.UserIdentity;
 import com.starrocks.sql.ast.pipe.PipeName;
-import com.starrocks.sql.common.MetaUtils;
 
 import java.util.ArrayList;
 import java.util.Arrays;
@@ -229,7 +228,7 @@ public List<Pair<Long, Long>> analyzeFuncPrivToken(BaseGrantRevokePrivilegeStmt
                         funcPrivTokenList.add(new Pair<>(PrivilegeBuiltinConstants.ALL_DATABASE_ID,
                                 PrivilegeBuiltinConstants.ALL_FUNCTIONS_ID));
                     } else {
-                        Database database = GlobalStateMgr.getServingState().getDb(tokens.get(0));
+                        Database database = GlobalStateMgr.getServingState().getLocalMetastore().getDb(tokens.get(0));
                         if (database == null) {
                             throw new SemanticException("Database %s is not found", tokens.get(0));
                         }
@@ -262,7 +261,7 @@ public List<Pair<Long, Long>> analyzeFuncPrivToken(BaseGrantRevokePrivilegeStmt
                         FunctionSearchDesc searchDesc = new FunctionSearchDesc(functionName,
                                 argsDef.getArgTypes(), argsDef.isVariadic());
 
-                        Database db = GlobalStateMgr.getCurrentState().getDb(functionName.getDb());
+                        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(functionName.getDb());
                         long databaseID = db.getId();
                         Function function = db.getFunction(searchDesc);
 
@@ -346,10 +345,10 @@ public List<List<String>> analyzeTokens(BaseGrantRevokePrivilegeStmt stmt, Objec
                             tableName = new TableName(tokens.get(0), tokens.get(1), tokens.get(2));
                         } else if (tokens.size() == 2) {
                             tableName = new TableName(tokens.get(0), tokens.get(1));
-                            MetaUtils.normalizationTableName(session, tableName);
+                            tableName.normalization(session);
                         } else if (tokens.size() == 1) {
                             tableName = new TableName("", tokens.get(0));
-                            MetaUtils.normalizationTableName(session, tableName);
+                            tableName.normalization(session);
                         } else {
                             throw new SemanticException(
                                     "Invalid grant statement with error privilege object " + tokens);
@@ -366,7 +365,7 @@ public List<List<String>> analyzeTokens(BaseGrantRevokePrivilegeStmt stmt, Objec
                             tableName = new TableName(tokens.get(0), tokens.get(1));
                         } else if (tokens.size() == 1) {
                             tableName = new TableName("", tokens.get(0));
-                            MetaUtils.normalizationTableName(session, tableName);
+                            tableName.normalization(session);
                         } else {
                             throw new SemanticException(
                                     "Invalid grant statement with error privilege object " + tokens);
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AuthorizerStmtVisitor.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AuthorizerStmtVisitor.java
index e9b9bc32668602..c95327e523ece2 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AuthorizerStmtVisitor.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/AuthorizerStmtVisitor.java
@@ -1485,7 +1485,7 @@ public Void visitDropTableStatement(DropTableStmt statement, ConnectContext cont
         } else {
             Table table = null;
             try {
-                table = MetaUtils.getTable(context, statement.getTbl());
+                table = MetaUtils.getSessionAwareTable(context, null, statement.getTbl());
                 Authorizer.checkTableAction(context.getCurrentUserIdentity(), context.getCurrentRoleIds(),
                         statement.getTbl(), PrivilegeType.DROP);
             } catch (AccessDeniedException e) {
@@ -1569,9 +1569,10 @@ public Void visitAlterTableStatement(AlterTableStmt statement, ConnectContext co
     @Override
     public Void visitCancelAlterTableStatement(CancelAlterTableStmt statement, ConnectContext context) {
         if (statement.getAlterType() == ShowAlterStmt.AlterType.MATERIALIZED_VIEW) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(statement.getDbName());
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(statement.getDbName());
             if (db != null) {
-                Table table = db.getTable(statement.getTableName());
+                Table table = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(db.getFullName(), statement.getTableName());
                 if (table == null || !table.isMaterializedView()) {
                     // ignore privilege check for old mv
                     return null;
@@ -2151,7 +2152,7 @@ public Void visitRestoreStatement(RestoreStmt statement, ConnectContext context)
             }
         } else {
             // going to restore some tables in database or some partitions in table
-            Database db = globalStateMgr.getDb(statement.getDbName());
+            Database db = globalStateMgr.getLocalMetastore().getDb(statement.getDbName());
             Locker locker = new Locker();
             if (db != null) {
                 try {
@@ -2168,7 +2169,8 @@ public Void visitRestoreStatement(RestoreStmt statement, ConnectContext context)
                     }
                     // check insert on specified table
                     for (TableRef tableRef : tableRefs) {
-                        Table table = db.getTable(tableRef.getName().getTbl());
+                        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(db.getFullName(), tableRef.getName().getTbl());
                         if (table != null) {
                             try {
                                 Authorizer.checkTableAction(context.getCurrentUserIdentity(), context.getCurrentRoleIds(),
@@ -2335,7 +2337,7 @@ public Void visitDropFunctionStatement(DropFunctionStmt statement, ConnectContex
         }
 
         // db function.
-        Database db = GlobalStateMgr.getCurrentState().getDb(functionName.getDb());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(functionName.getDb());
         if (db != null) {
             Locker locker = new Locker();
             try {
@@ -2534,7 +2536,7 @@ private String getTableNameByRoutineLoadLabel(ConnectContext context,
 
     private void checkOperateLoadPrivilege(ConnectContext context, String dbName, String label) {
         GlobalStateMgr globalStateMgr = context.getGlobalStateMgr();
-        Database db = globalStateMgr.getDb(dbName);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbName);
         if (db == null) {
             ErrorReport.reportSemanticException(ErrorCode.ERR_PRIVILEGE_DB_NOT_FOUND, dbName);
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/BackupRestoreAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/BackupRestoreAnalyzer.java
index 7a5f3ef978bcdf..a0660b97cafcb4 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/BackupRestoreAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/BackupRestoreAnalyzer.java
@@ -85,7 +85,7 @@ public Void visitBackupStatement(BackupStmt backupStmt, ConnectContext context)
             // If TableRefs is empty, it means that we do not specify any table in Backup stmt.
             // We should backup all table in current database.
             if (tableRefs.size() == 0) {
-                for (Table tbl : database.getTables()) {
+                for (Table tbl : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(database.getId())) {
                     if (!Config.enable_backup_materialized_view && tbl.isMaterializedView()) {
                         LOG.info("Skip backup materialized view: {} because " +
                                         "`Config.enable_backup_materialized_view=false`", tbl.getName());
@@ -364,7 +364,7 @@ public static String getDbName(String dbName, ConnectContext context) {
     }
 
     public static Database getDatabase(String dbName, ConnectContext context) {
-        Database db = context.getGlobalStateMgr().getDb(dbName);
+        Database db = context.getGlobalStateMgr().getLocalMetastore().getDb(dbName);
         if (db == null) {
             ErrorReport.reportSemanticException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
         }
@@ -397,14 +397,14 @@ public static void analyzeTableRef(TableRef tableRef, String dbName, Database db
         tableName.setDb(dbName);
 
         PartitionNames partitionNames = tableRef.getPartitionNames();
-        Table tbl = db.getTable(tableName.getTbl());
+        Table tbl = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName.getTbl());
         if (null == tbl) {
             throw new SemanticException(ErrorCode.ERR_WRONG_TABLE_NAME.formatErrorMsg(tableName.getTbl()));
         }
 
         String alias = tableRef.getAlias();
         if (!tableName.getTbl().equalsIgnoreCase(alias)) {
-            Table tblAlias = db.getTable(alias);
+            Table tblAlias = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), alias);
             if (tblAlias != null && tbl != tblAlias) {
                 ErrorReport.reportSemanticException(ErrorCode.ERR_COMMON_ERROR,
                         "table [" + alias + "] existed");
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CTASAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CTASAnalyzer.java
index 07a44b45900eb5..c141c1776e7b28 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CTASAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CTASAnalyzer.java
@@ -36,7 +36,6 @@
 import com.starrocks.sql.ast.PartitionDesc;
 import com.starrocks.sql.ast.QueryStatement;
 import com.starrocks.sql.ast.RangePartitionDesc;
-import com.starrocks.sql.common.MetaUtils;
 import com.starrocks.sql.parser.ParsingException;
 
 import java.util.HashMap;
@@ -88,7 +87,7 @@ public static void analyze(CreateTableAsSelectStmt createTableAsSelectStmt, Conn
         }
 
         TableName tableNameObject = createTableStmt.getDbTbl();
-        MetaUtils.normalizationTableName(session, tableNameObject);
+        tableNameObject.normalization(session);
         CreateTableAnalyzer.analyzeEngineName(createTableStmt, tableNameObject.getCatalog());
 
         for (int i = 0; i < allFields.size(); i++) {
@@ -96,7 +95,7 @@ public static void analyze(CreateTableAsSelectStmt createTableAsSelectStmt, Conn
                     createTableStmt.isOlapEngine());
             Expr originExpression = allFields.get(i).getOriginExpression();
             ColumnDef columnDef = new ColumnDef(finalColumnNames.get(i), new TypeDef(type), false,
-                    null, originExpression.isNullable(), ColumnDef.DefaultValueDef.NOT_SET, "");
+                    null, null, originExpression.isNullable(), ColumnDef.DefaultValueDef.NOT_SET, "");
             if (isPKTable && keysDesc.containsCol(finalColumnNames.get(i))) {
                 columnDef.setAllowNull(false);
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CancelAlterTableStatementAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CancelAlterTableStatementAnalyzer.java
index 9ad265610606f7..4819a30972202c 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CancelAlterTableStatementAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CancelAlterTableStatementAnalyzer.java
@@ -19,14 +19,13 @@
 import com.starrocks.common.ErrorReport;
 import com.starrocks.qe.ConnectContext;
 import com.starrocks.sql.ast.CancelAlterTableStmt;
-import com.starrocks.sql.common.MetaUtils;
 
 public class CancelAlterTableStatementAnalyzer {
 
     public static void analyze(CancelAlterTableStmt statement, ConnectContext context) {
-        MetaUtils.normalizationTableName(context, statement.getDbTableName());
+        statement.getDbTableName().normalization(context);
         // Check db.
-        if (context.getGlobalStateMgr().getDb(statement.getDbName()) == null) {
+        if (context.getGlobalStateMgr().getLocalMetastore().getDb(statement.getDbName()) == null) {
             ErrorReport.reportSemanticException(ErrorCode.ERR_BAD_DB_ERROR, statement.getDbName());
         }
     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CreateTableAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CreateTableAnalyzer.java
index 4f38a4b1b49459..b7d9e57ea7f064 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CreateTableAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CreateTableAnalyzer.java
@@ -78,7 +78,7 @@ public class CreateTableAnalyzer {
 
     public static void analyze(CreateTableStmt statement, ConnectContext context) {
         final TableName tableNameObject = statement.getDbTbl();
-        MetaUtils.normalizationTableName(context, tableNameObject);
+        tableNameObject.normalization(context);
 
         final String catalogName = tableNameObject.getCatalog();
         MetaUtils.checkCatalogExistAndReport(catalogName);
@@ -86,11 +86,15 @@ public static void analyze(CreateTableStmt statement, ConnectContext context) {
         final String tableName = tableNameObject.getTbl();
         FeNameFormat.checkTableName(tableName);
 
-        Database db = MetaUtils.getDatabase(catalogName, tableNameObject.getDb());
+        Database db = GlobalStateMgr.getCurrentState().getMetadataMgr().getDb(catalogName, tableNameObject.getDb());
+        if (db == null) {
+            ErrorReport.reportSemanticException(ErrorCode.ERR_BAD_DB_ERROR, tableNameObject.getDb());
+        }
         if (statement instanceof CreateTemporaryTableStmt) {
             analyzeTemporaryTable(statement, context, catalogName, db, tableName);
         } else {
-            if (db.getTable(tableName) != null && !statement.isSetIfNotExists()) {
+            if (GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(db.getFullName(), tableName) != null && !statement.isSetIfNotExists()) {
                 ErrorReport.reportSemanticException(ErrorCode.ERR_TABLE_EXISTS_ERROR, tableName);
             }
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CreateTableLikeAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CreateTableLikeAnalyzer.java
index 7ad846c24e2ea2..67cd34ebdbc784 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CreateTableLikeAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/CreateTableLikeAnalyzer.java
@@ -16,12 +16,12 @@
 
 import com.google.common.collect.Lists;
 import com.starrocks.analysis.TableName;
-import com.starrocks.catalog.Database;
 import com.starrocks.catalog.OlapTable;
 import com.starrocks.catalog.Table;
 import com.starrocks.common.ErrorCode;
 import com.starrocks.common.ErrorReport;
 import com.starrocks.qe.ConnectContext;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.ast.CreateTableLikeStmt;
 import com.starrocks.sql.ast.CreateTableStmt;
 import com.starrocks.sql.ast.CreateTemporaryTableLikeStmt;
@@ -35,14 +35,17 @@ public class CreateTableLikeAnalyzer {
 
     public static void analyze(CreateTableLikeStmt stmt, ConnectContext context) {
         TableName existedDbTbl = stmt.getExistedDbTbl();
-        MetaUtils.normalizationTableName(context, stmt.getDbTbl());
-        MetaUtils.normalizationTableName(context, existedDbTbl);
+        stmt.getDbTbl().normalization(context);
+        existedDbTbl.normalization(context);
         String tableName = stmt.getTableName();
         FeNameFormat.checkTableName(tableName);
 
         MetaUtils.checkNotSupportCatalog(existedDbTbl.getCatalog(), "CREATE TABLE LIKE");
-        Database db = MetaUtils.getDatabase(context, existedDbTbl);
-        Table table = MetaUtils.getTable(existedDbTbl);
+        Table table = GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(existedDbTbl.getCatalog(),
+                existedDbTbl.getDb(), existedDbTbl.getTbl());
+        if (table == null) {
+            throw new SemanticException("Table %s is not found", tableName);
+        }
 
         List<String> createTableStmt = Lists.newArrayList();
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/DeleteAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/DeleteAnalyzer.java
index 4716fca29b22e5..27b3913f287168 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/DeleteAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/DeleteAnalyzer.java
@@ -31,6 +31,7 @@
 import com.starrocks.analysis.TableName;
 import com.starrocks.analysis.VariableExpr;
 import com.starrocks.catalog.Column;
+import com.starrocks.catalog.Database;
 import com.starrocks.catalog.KeysType;
 import com.starrocks.catalog.MaterializedView;
 import com.starrocks.catalog.OlapTable;
@@ -39,8 +40,10 @@
 import com.starrocks.common.Config;
 import com.starrocks.load.Load;
 import com.starrocks.qe.ConnectContext;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.ast.DeleteStmt;
 import com.starrocks.sql.ast.JoinRelation;
+import com.starrocks.sql.ast.LoadStmt;
 import com.starrocks.sql.ast.PartitionNames;
 import com.starrocks.sql.ast.QueryStatement;
 import com.starrocks.sql.ast.Relation;
@@ -54,6 +57,7 @@
 import org.jetbrains.annotations.NotNull;
 
 import java.util.List;
+import java.util.Map;
 
 public class DeleteAnalyzer {
     private static final Logger LOG = LogManager.getLogger(DeleteAnalyzer.class);
@@ -181,11 +185,24 @@ private static void analyzeNonPrimaryKey(DeleteStmt deleteStatement) {
         deleteStatement.setDeleteConditions(deleteConditions);
     }
 
+    private static void analyzeProperties(DeleteStmt deleteStmt, ConnectContext session) {
+        Map<String, String> properties = deleteStmt.getProperties();
+        properties.put(LoadStmt.MAX_FILTER_RATIO_PROPERTY,
+                String.valueOf(session.getSessionVariable().getInsertMaxFilterRatio()));
+        properties.put(LoadStmt.STRICT_MODE, String.valueOf(session.getSessionVariable().getEnableInsertStrict()));
+    }
+
     public static void analyze(DeleteStmt deleteStatement, ConnectContext session) {
+        analyzeProperties(deleteStatement, session);
+
         TableName tableName = deleteStatement.getTableName();
-        MetaUtils.normalizationTableName(session, tableName);
+        tableName.normalization(session);
         MetaUtils.checkNotSupportCatalog(tableName.getCatalog(), "DELETE");
-        MetaUtils.getDatabase(session, tableName);
+        Database db = GlobalStateMgr.getCurrentState().getMetadataMgr()
+                .getDb(tableName.getCatalog(), tableName.getDb());
+        if (db == null) {
+            throw new SemanticException("Database %s is not found", tableName.getCatalogAndDb());
+        }
         Table table = MetaUtils.getSessionAwareTable(session, null, tableName);
 
         if (table instanceof MaterializedView) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/DropStmtAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/DropStmtAnalyzer.java
index 85dff3beb828a6..7ae1aeaaa3d13e 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/DropStmtAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/DropStmtAnalyzer.java
@@ -63,7 +63,7 @@ public void analyze(DdlStmt statement, ConnectContext session) {
 
         @Override
         public Void visitDropTableStatement(DropTableStmt statement, ConnectContext context) {
-            MetaUtils.normalizationTableName(context, statement.getTableNameObject());
+            statement.getTableNameObject().normalization(context);
 
             // check catalog
             String catalogName = statement.getCatalogName();
@@ -116,7 +116,7 @@ public Void visitDropTableStatement(DropTableStmt statement, ConnectContext cont
         @Override
         public Void visitDropTemporaryTableStatement(DropTemporaryTableStmt statement, ConnectContext context) {
             statement.setSessionId(context.getSessionId());
-            MetaUtils.normalizationTableName(context, statement.getTableNameObject());
+            statement.getTableNameObject().normalization(context);
 
             // check catalog
             String catalogName = statement.getCatalogName();
@@ -166,7 +166,7 @@ public Void visitDropDbStatement(DropDbStmt statement, ConnectContext context) {
                         context.getCurrentUserIdentity(), context.getCurrentRoleIds(),
                         PrivilegeType.DROP.name(), ObjectType.DATABASE.name(), dbName);
             } else if (dbName.equalsIgnoreCase(SysDb.DATABASE_NAME)) {
-                Database db = GlobalStateMgr.getCurrentState().getDb(SysDb.DATABASE_NAME.toLowerCase());
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(SysDb.DATABASE_NAME.toLowerCase());
                 if (db.getId() == SystemId.SYS_DB_ID) {
                     AccessDeniedException.reportAccessDenied(context.getCurrentCatalog(),
                             context.getCurrentUserIdentity(), context.getCurrentRoleIds(),
@@ -197,7 +197,7 @@ public Void visitDropFunctionStatement(DropFunctionStmt statement, ConnectContex
                     ErrorReport.reportSemanticException(ErrorCode.ERR_BAD_FUNC_ERROR, funcDesc.toString());
                 }
             } else {
-                Database db = GlobalStateMgr.getCurrentState().getDb(functionName.getDb());
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(functionName.getDb());
                 if (db != null) {
                     func = db.getFunction(statement.getFunctionSearchDesc());
                     if (func == null) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ExportStmtAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ExportStmtAnalyzer.java
index f6d801a6f3fd60..668665155e1aff 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ExportStmtAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ExportStmtAnalyzer.java
@@ -68,7 +68,7 @@ public Void visitExportStatement(ExportStmt statement, ConnectContext context) {
             GlobalStateMgr mgr = context.getGlobalStateMgr();
             TableName tableName = statement.getTableRef().getName();
             // make sure catalog, db, table
-            MetaUtils.normalizationTableName(context, tableName);
+            tableName.normalization(context);
             Table table = MetaUtils.getSessionAwareTable(context, null, tableName);
             if (table.getType() == Table.TableType.OLAP &&
                     (((OlapTable) table).getState() == OlapTable.OlapTableState.RESTORE ||
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ExpressionAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ExpressionAnalyzer.java
index 7aab75d74216b6..3894dfb492714f 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ExpressionAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ExpressionAnalyzer.java
@@ -1515,11 +1515,11 @@ public Void visitDictQueryExpr(DictQueryExpr node, Scope context) {
                 throw new SemanticException("dict_mapping function first param table_name should be 'db.tbl' or 'tbl' format");
             }
 
-            Database db = GlobalStateMgr.getCurrentState().getDb(tableName.getDb());
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(tableName.getDb());
             if (db == null) {
                 throw new SemanticException("Database %s is not found", tableName.getDb());
             }
-            Table table = db.getTable(tableName.getTbl());
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName.getTbl());
             if (table == null) {
                 throw new SemanticException("dict table %s is not found", tableName.getTbl());
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/FunctionAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/FunctionAnalyzer.java
index 0d4caeeb8ab044..f86ab12c531aaa 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/FunctionAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/FunctionAnalyzer.java
@@ -519,6 +519,33 @@ private static void analyzeBuiltinAggFunction(FunctionCallExpr functionCallExpr)
                 throw new SemanticException(fnName + " function 's args must be column");
             }
         }
+
+        if (fnName.getFunction().equals(FunctionSet.MANN_WHITNEY_U_TEST)) {
+            if (functionCallExpr.getChildren().size() >= 3) {
+                if (!(functionCallExpr.getChild(2) instanceof StringLiteral)) {
+                    throw new SemanticException(fnName + "'s third parameter should be a string literal.");
+                }
+                String alternative = ((StringLiteral) functionCallExpr.getChild(2)).getStringValue();
+                if (!(alternative.equals("two-sided") || alternative.equals("greater") || alternative.equals("less"))) {
+                    throw new SemanticException(
+                            fnName + "'s third parameter should be one of ['two-sided', 'greater', 'less'], but get '" +
+                                    alternative + "'.");
+                }
+            }
+            if (functionCallExpr.getChildren().size() >= 4) {
+                long continuityCorrection;
+                if (functionCallExpr.getChild(3) instanceof IntLiteral) {
+                    continuityCorrection = ((IntLiteral) functionCallExpr.getChild(3)).getLongValue();
+                } else if (functionCallExpr.getChild(3) instanceof LargeIntLiteral) {
+                    continuityCorrection = ((LargeIntLiteral) functionCallExpr.getChild(3)).getLongValue();
+                } else {
+                    throw new SemanticException(fnName + "'s fourth parameter should be a non-negative int literal.");
+                }
+                if (continuityCorrection < 0) {
+                    throw new SemanticException(fnName + "'s fourth parameter should be a non-negative int literal.");
+                }
+            }
+        }
     }
 
     private static Optional<Long> extractIntegerValue(Expr expr) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/InsertAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/InsertAnalyzer.java
index a90326f2f1a727..d8269884cefea3 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/InsertAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/InsertAnalyzer.java
@@ -16,6 +16,7 @@
 
 import com.google.common.base.Preconditions;
 import com.google.common.base.Strings;
+import com.google.common.collect.ImmutableSet;
 import com.google.common.collect.Lists;
 import com.google.common.collect.Sets;
 import com.starrocks.analysis.Expr;
@@ -31,15 +32,20 @@
 import com.starrocks.catalog.Table;
 import com.starrocks.catalog.Type;
 import com.starrocks.common.AnalysisException;
+import com.starrocks.common.DdlException;
 import com.starrocks.common.ErrorCode;
 import com.starrocks.common.ErrorReport;
 import com.starrocks.connector.hive.HiveWriteUtils;
 import com.starrocks.qe.ConnectContext;
 import com.starrocks.server.CatalogMgr;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.ast.DefaultValueExpr;
+import com.starrocks.sql.ast.FileTableFunctionRelation;
 import com.starrocks.sql.ast.InsertStmt;
+import com.starrocks.sql.ast.LoadStmt;
 import com.starrocks.sql.ast.PartitionNames;
 import com.starrocks.sql.ast.QueryRelation;
+import com.starrocks.sql.ast.QueryStatement;
 import com.starrocks.sql.ast.ValuesRelation;
 import com.starrocks.sql.common.MetaUtils;
 import org.apache.iceberg.SnapshotRef;
@@ -56,6 +62,9 @@
 import static com.starrocks.sql.common.UnsupportedException.unsupportedException;
 
 public class InsertAnalyzer {
+    private static final ImmutableSet<String> PUSH_DOWN_PROPERTIES_SET = new ImmutableSet.Builder<String>()
+            .add(LoadStmt.STRICT_MODE)
+            .build();
 
     /**
      * Normal path of analyzer
@@ -70,11 +79,13 @@ public static void analyze(InsertStmt insertStmt, ConnectContext session) {
      * So we can analyze the SELECT without lock, only take the lock when analyzing INSERT TARGET
      */
     public static void analyzeWithDeferredLock(InsertStmt insertStmt, ConnectContext session, Runnable takeLock) {
-        QueryRelation query = insertStmt.getQueryStatement().getQueryRelation();
-        List<Table> tables = new ArrayList<>();
         try {
+            // insert properties
+            analyzeProperties(insertStmt, session);
+
             new QueryAnalyzer(session).analyze(insertStmt.getQueryStatement());
 
+            List<Table> tables = new ArrayList<>();
             AnalyzerUtils.collectSpecifyExternalTables(insertStmt.getQueryStatement(), tables, Table::isHiveTable);
             tables.stream().map(table -> (HiveTable) table)
                     .forEach(table -> table.useMetadataCache(false));
@@ -247,6 +258,7 @@ public static void analyzeWithDeferredLock(InsertStmt insertStmt, ConnectContext
             mentionedColumnSize -= table.getPartitionColumnNames().size();
         }
 
+        QueryRelation query = insertStmt.getQueryStatement().getQueryRelation();
         if (query.getRelationFields().size() != mentionedColumnSize) {
             ErrorReport.reportSemanticException(ErrorCode.ERR_INSERTED_COLUMN_MISMATCH, mentionedColumnSize,
                     query.getRelationFields().size());
@@ -276,6 +288,40 @@ public static void analyzeWithDeferredLock(InsertStmt insertStmt, ConnectContext
         }
     }
 
+    private static void analyzeProperties(InsertStmt insertStmt, ConnectContext session) {
+        Map<String, String> properties = insertStmt.getProperties();
+        // use session variable if not set max_filter_ratio property
+        if (!properties.containsKey(LoadStmt.MAX_FILTER_RATIO_PROPERTY)) {
+            properties.put(LoadStmt.MAX_FILTER_RATIO_PROPERTY,
+                    String.valueOf(session.getSessionVariable().getInsertMaxFilterRatio()));
+        }
+        // use session variable if not set strict_mode property
+        if (!properties.containsKey(LoadStmt.STRICT_MODE) &&
+                session.getSessionVariable().getEnableInsertStrict()) {
+            properties.put(LoadStmt.STRICT_MODE, "true");
+        }
+
+        try {
+            LoadStmt.checkProperties(properties);
+        } catch (DdlException e) {
+            ErrorReport.reportSemanticException(ErrorCode.ERR_COMMON_ERROR, e.getMessage());
+        }
+
+        // push down some properties to file table function
+        QueryStatement queryStatement = insertStmt.getQueryStatement();
+        if (queryStatement != null) {
+            List<FileTableFunctionRelation> relations = AnalyzerUtils.collectFileTableFunctionRelation(queryStatement);
+            for (FileTableFunctionRelation relation : relations) {
+                Map<String, String> tableFunctionProperties = relation.getProperties();
+                for (String property : PUSH_DOWN_PROPERTIES_SET) {
+                    if (properties.containsKey(property)) {
+                        tableFunctionProperties.put(property, properties.get(property));
+                    }
+                }
+            }
+        }
+    }
+
     private static void checkStaticKeyPartitionInsert(InsertStmt insertStmt, Table table, PartitionNames targetPartitionNames) {
         List<String> partitionColNames = targetPartitionNames.getPartitionColNames();
         List<Expr> partitionColValues = targetPartitionNames.getPartitionColValues();
@@ -333,14 +379,17 @@ private static Table getTargetTable(InsertStmt insertStmt, ConnectContext sessio
             return insertStmt.makeBlackHoleTable();
         }
 
-        MetaUtils.normalizationTableName(session, insertStmt.getTableName());
+        insertStmt.getTableName().normalization(session);
         String catalogName = insertStmt.getTableName().getCatalog();
         String dbName = insertStmt.getTableName().getDb();
         String tableName = insertStmt.getTableName().getTbl();
 
         MetaUtils.checkCatalogExistAndReport(catalogName);
 
-        Database database = MetaUtils.getDatabase(catalogName, dbName);
+        Database database = GlobalStateMgr.getCurrentState().getMetadataMgr().getDb(catalogName, dbName);
+        if (database == null) {
+            ErrorReport.reportSemanticException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
+        }
         Table table = MetaUtils.getSessionAwareTable(session, database, insertStmt.getTableName());
         if (table == null) {
             throw new SemanticException("Table %s is not found", tableName);
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/LoadStmtAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/LoadStmtAnalyzer.java
index 731d4a71d22b91..6ffbf5c0b6be14 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/LoadStmtAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/LoadStmtAnalyzer.java
@@ -124,14 +124,15 @@ private void analyzeDataDescriptions(LoadStmt statement) {
                 if (etlJobType == EtlJobType.SPARK && database != null) {
                     for (DataDescription dataDescription : dataDescriptions) {
                         String tableName = dataDescription.getTableName();
-                        Database db = GlobalStateMgr.getCurrentState().getDb(database);
+                        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(database);
                         if (db == null) {
                             continue;
                         }
                         Locker locker = new Locker();
                         locker.lockDatabase(db, LockType.READ);
                         try {
-                            Table table = db.getTable(tableName);
+                            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                        .getTable(db.getFullName(), tableName);
                             if (table == null) {
                                 continue;
                             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/MaterializedViewAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/MaterializedViewAnalyzer.java
index 8a676603772f20..e3288f563c800f 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/MaterializedViewAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/MaterializedViewAnalyzer.java
@@ -80,7 +80,6 @@
 import com.starrocks.sql.ast.SetOperationRelation;
 import com.starrocks.sql.ast.StatementBase;
 import com.starrocks.sql.ast.ViewRelation;
-import com.starrocks.sql.common.MetaUtils;
 import com.starrocks.sql.optimizer.OptExpression;
 import com.starrocks.sql.optimizer.Optimizer;
 import com.starrocks.sql.optimizer.base.ColumnRefFactory;
@@ -242,7 +241,25 @@ public enum RefreshTimeUnit {
         public Void visitCreateMaterializedViewStatement(CreateMaterializedViewStatement statement,
                                                          ConnectContext context) {
             final TableName tableNameObject = statement.getTableName();
-            MetaUtils.normalizeMVName(context, tableNameObject);
+            /*
+             * Materialized view name is a little bit different from a normal table
+             * 1. Use default catalog if not specified, actually it only support default catalog until now
+             */
+            if (com.google.common.base.Strings.isNullOrEmpty(tableNameObject.getCatalog())) {
+                tableNameObject.setCatalog(InternalCatalog.DEFAULT_INTERNAL_CATALOG_NAME);
+            }
+            if (com.google.common.base.Strings.isNullOrEmpty(tableNameObject.getDb())) {
+                if (com.google.common.base.Strings.isNullOrEmpty(context.getDatabase())) {
+                    throw new SemanticException("No database selected. " +
+                            "You could set the database name through `<database>.<table>` or `use <database>` statement");
+                }
+                tableNameObject.setDb(context.getDatabase());
+            }
+
+            if (com.google.common.base.Strings.isNullOrEmpty(tableNameObject.getTbl())) {
+                throw new SemanticException("Table name cannot be empty");
+            }
+
             final String tableName = tableNameObject.getTbl();
             FeNameFormat.checkTableName(tableName);
             QueryStatement queryStatement = statement.getQueryStatement();
@@ -280,7 +297,7 @@ public Void visitCreateMaterializedViewStatement(CreateMaterializedViewStatement
                         "default_catalog through `set catalog <default_catalog>` statement",
                         statement.getTableName().getPos());
             }
-            Database db = context.getGlobalStateMgr().getDb(statement.getTableName().getDb());
+            Database db = context.getGlobalStateMgr().getLocalMetastore().getDb(statement.getTableName().getDb());
             if (db == null) {
                 throw new SemanticException("Can not find database:" + statement.getTableName().getDb(),
                         statement.getTableName().getPos());
@@ -1051,8 +1068,12 @@ public Void visitDropMaterializedViewStatement(DropMaterializedViewStmt stmt, Co
         @Override
         public Void visitAlterMaterializedViewStatement(AlterMaterializedViewStmt statement, ConnectContext context) {
             TableName mvName = statement.getMvName();
-            MetaUtils.normalizationTableName(context, mvName);
-            Table table = MetaUtils.getTable(statement.getMvName());
+            mvName.normalization(context);
+            Table table = GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(statement.getMvName().getCatalog(),
+                    statement.getMvName().getDb(), statement.getMvName().getTbl());
+            if (table == null) {
+                throw new SemanticException("Table %s is not found", mvName);
+            }
             if (!(table instanceof MaterializedView)) {
                 throw new SemanticException(mvName.getTbl() + " is not async materialized view", mvName.getPos());
             }
@@ -1067,11 +1088,12 @@ public Void visitRefreshMaterializedViewStatement(RefreshMaterializedViewStateme
                                                           ConnectContext context) {
             statement.getMvName().normalization(context);
             TableName mvName = statement.getMvName();
-            Database db = context.getGlobalStateMgr().getDb(mvName.getDb());
+            Database db = context.getGlobalStateMgr().getLocalMetastore().getDb(mvName.getDb());
             if (db == null) {
                 throw new SemanticException("Can not find database:" + mvName.getDb(), mvName.getPos());
             }
-            OlapTable table = (OlapTable) db.getTable(mvName.getTbl());
+            OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(db.getFullName(), mvName.getTbl());
             if (table == null) {
                 throw new SemanticException("Can not find materialized view:" + mvName.getTbl(), mvName.getPos());
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/QueryAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/QueryAnalyzer.java
index 0e55c7440c0b32..91ffbbc9966561 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/QueryAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/QueryAnalyzer.java
@@ -226,10 +226,95 @@ public Void visitTable(TableRelation tableRelation, Void context) {
                     return null;
                 }
 
+                @Override
+                public Void visitSubquery(SubqueryRelation subquery, Void context) {
+                    QueryRelation queryRelation = subquery.getQueryStatement().getQueryRelation();
+                    if (queryRelation instanceof SelectRelation) {
+                        SelectRelation childSelectRelation = (SelectRelation) queryRelation;
+                        if (childSelectRelation.getGeneratedExprToColumnRef() == null ||
+                                childSelectRelation.getGeneratedExprToColumnRef().isEmpty()) {
+                            return null;
+                        }
+                        // 1. get all available generated column from subquery
+                        // available means that:
+                        // a. generated column output from subquery directly.
+                        // b. all reference column of generated column output from subquery directly.
+                        List<SlotRef> outputSlotRef = childSelectRelation.getOutputExpression()
+                                                      .stream().filter(e -> e instanceof SlotRef)
+                                                      .map(e -> (SlotRef) e).collect(Collectors.toList());
+                        boolean hasStar = childSelectRelation.getSelectList()
+                                                    .getItems().stream().anyMatch(SelectListItem::isStar);
+
+                        for (Map.Entry<Expr, SlotRef> entry : childSelectRelation.getGeneratedExprToColumnRef().entrySet()) {
+                            List<SlotRef> allRefColumns = Lists.newArrayList();
+                            entry.getKey().collect(SlotRef.class, allRefColumns);
+                            allRefColumns.add(entry.getValue());
+                            if (hasStar || outputSlotRef.containsAll(allRefColumns)) {
+                                generatedExprToColumnRef.put(entry.getKey().clone(), (SlotRef) entry.getValue().clone());
+                            }
+                        }
+
+                        // 2. rewrite(rename slotRef) generated column expression(unAnalyzed) using alias in current scope
+                        Map<String, String> slotRefToAlias = new HashMap<>();
+                        for (SelectListItem item : childSelectRelation.getSelectList().getItems()) {
+                            if (item.isStar()) {
+                                slotRefToAlias.clear();
+                                break;
+                            }
+
+                            if (!(item.getExpr() instanceof SlotRef) || (item.getAlias() == null || item.getAlias().isEmpty())) {
+                                continue;
+                            }
+
+                            slotRefToAlias.put(((SlotRef) item.getExpr()).toSql(), item.getAlias());
+                        }
+                        List<SlotRef> allRefSlotRefs = new ArrayList<>();
+                        for (Map.Entry<Expr, SlotRef> entry : generatedExprToColumnRef.entrySet()) {
+                            List<SlotRef> refColumns = Lists.newArrayList();
+                            entry.getKey().collect(SlotRef.class, refColumns);
+
+                            allRefSlotRefs.addAll(refColumns);
+                            allRefSlotRefs.add(entry.getValue());
+                        }
+                        for (SlotRef slotRef : allRefSlotRefs) {
+                            if (!slotRefToAlias.isEmpty()) {
+                                String alias = slotRefToAlias.get(slotRef.toSql());
+                                if (alias != null) {
+                                    slotRef.setColumnName(alias);
+                                }
+                            }
+                            slotRef.setTblName(null);
+                        }
+
+                        // 3. analyze generated column expression based on current scope
+                        for (Map.Entry<Expr, SlotRef> entry : generatedExprToColumnRef.entrySet()) {
+                            entry.getKey().reset();
+                            entry.getValue().reset();
+                            
+                            try {
+                                ExpressionAnalyzer.analyzeExpression(entry.getKey(), new AnalyzeState(), sourceScope, session);
+                                ExpressionAnalyzer.analyzeExpression(entry.getValue(), new AnalyzeState(), sourceScope, session);
+                            } catch (Exception ignore) {
+                                // ignore generated column rewrite if hit any exception
+                                generatedExprToColumnRef.clear();
+                            }
+                        }
+                    }
+                    return null;
+                }
+
+                // Do not support rewrite like JOIN wiht {left: Subquery, right: Relation}
                 @Override
                 public Void visitJoin(JoinRelation joinRelation, Void context) {
-                    visit(joinRelation.getLeft());
-                    visit(joinRelation.getRight());
+                    Relation leftRelation = joinRelation.getLeft();
+                    Relation rightRelation = joinRelation.getRight();
+                    if (leftRelation instanceof TableRelation && rightRelation instanceof TableRelation) {
+                        TableRelation leftTableRelation = (TableRelation) leftRelation;
+                        TableRelation rightTableRelation = (TableRelation) rightRelation;
+
+                        generatedExprToColumnRef.putAll(leftTableRelation.getGeneratedExprToColumnRef());
+                        generatedExprToColumnRef.putAll(rightTableRelation.getGeneratedExprToColumnRef());
+                    }
                     return null;
                 }
             }.visit(resolvedRelation);
@@ -333,7 +418,7 @@ private Relation resolveTableRef(Relation relation, Scope scope, Set<TableName>
                 }
 
                 TableName resolveTableName = relation.getResolveTableName();
-                MetaUtils.normalizationTableName(session, resolveTableName);
+                resolveTableName.normalization(session);
                 if (aliasSet.contains(resolveTableName)) {
                     ErrorReport.reportSemanticException(ErrorCode.ERR_NONUNIQ_TABLE,
                             relation.getResolveTableName().getTbl());
@@ -510,17 +595,17 @@ public Scope visitTable(TableRelation node, Scope outerScope) {
             Scope scope = new Scope(RelationId.of(node), new RelationFields(fields.build()));
             node.setScope(scope);
 
-            Map<Expr, SlotRef> generatedExprToColumnRef = new HashMap<>();
+            Map<Expr, SlotRef> getGeneratedExprToColumnRef = new HashMap<>();
             for (Column column : table.getBaseSchema()) {
-                Expr materializedExpression = column.getGeneratedColumnExpr(table.getIdToColumn());
-                if (materializedExpression != null) {
-                    ExpressionAnalyzer.analyzeExpression(materializedExpression, new AnalyzeState(), scope, session);
+                Expr generatedColumnExpression = column.getGeneratedColumnExpr(table.getIdToColumn());
+                if (generatedColumnExpression != null) {
                     SlotRef slotRef = new SlotRef(null, column.getName());
+                    ExpressionAnalyzer.analyzeExpression(generatedColumnExpression, new AnalyzeState(), scope, session);
                     ExpressionAnalyzer.analyzeExpression(slotRef, new AnalyzeState(), scope, session);
-                    generatedExprToColumnRef.put(materializedExpression, slotRef);
+                    getGeneratedExprToColumnRef.put(generatedColumnExpression, slotRef);
                 }
             }
-            node.setGeneratedExprToColumnRef(generatedExprToColumnRef);
+            node.setGeneratedExprToColumnRef(getGeneratedExprToColumnRef);
 
             return scope;
         }
@@ -1199,7 +1284,7 @@ public Scope visitNormalizedTableFunction(NormalizedTableFunctionRelation node,
     public Table resolveTable(TableRelation tableRelation) {
         TableName tableName = tableRelation.getName();
         try {
-            MetaUtils.normalizationTableName(session, tableName);
+            tableName.normalization(session);
             String catalogName = tableName.getCatalog();
             String dbName = tableName.getDb();
             String tbName = tableName.getTbl();
@@ -1393,16 +1478,13 @@ public Expr visitSelect(SelectRelation selectRelation, Void context) {
                 if (item.getAlias() == null) {
                     continue;
                 }
-                // Ignore c1 as c1
-                if (item.getExpr() instanceof SlotRef &&
-                        alias.equalsIgnoreCase(((SlotRef) item.getExpr()).getColumnName())) {
-                    continue;
-                }
+
                 // Alias is case-insensitive
                 Expr lastAssociatedExpr = aliases.putIfAbsent(alias.toLowerCase(), item.getExpr());
                 if (lastAssociatedExpr != null) {
                     // Duplicate alias is allowed, eg: select a.v1 as v, a.v2 as v from t0 a,
-                    // But it should not be ambiguous, eg: select a.v1 as v, a.v2 as v from t0 a order by v
+                    // But it should be ambiguous when the alias is used in the order by expr,
+                    // eg: select a.v1 as v, a.v2 as v from t0 a order by v
                     aliasesMaybeAmbiguous.add(alias.toLowerCase());
                 }
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/RecoverPartitionAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/RecoverPartitionAnalyzer.java
index 858f9ef7835e8a..27176fad835ec3 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/RecoverPartitionAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/RecoverPartitionAnalyzer.java
@@ -17,11 +17,10 @@
 import com.starrocks.analysis.TableName;
 import com.starrocks.qe.ConnectContext;
 import com.starrocks.sql.ast.RecoverPartitionStmt;
-import com.starrocks.sql.common.MetaUtils;
 
 public class RecoverPartitionAnalyzer {
     public static void analyze(RecoverPartitionStmt statement, ConnectContext context) {
         TableName tbl = statement.getDbTblName();
-        MetaUtils.normalizationTableName(context, tbl);
+        tbl.normalization(context);
     }
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/RecoverTableAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/RecoverTableAnalyzer.java
index b2272e83db05ec..2632562c0eb609 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/RecoverTableAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/RecoverTableAnalyzer.java
@@ -17,12 +17,11 @@
 import com.starrocks.analysis.TableName;
 import com.starrocks.qe.ConnectContext;
 import com.starrocks.sql.ast.RecoverTableStmt;
-import com.starrocks.sql.common.MetaUtils;
 
 public class RecoverTableAnalyzer {
 
     public static void analyze(RecoverTableStmt statement, ConnectContext context) {
         TableName tableName = statement.getTableNameObject();
-        MetaUtils.normalizationTableName(context, tableName);
+        tableName.normalization(context);
     }
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/RefreshTableStatementAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/RefreshTableStatementAnalyzer.java
index cc910c60e7e32a..16185ea03c2a98 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/RefreshTableStatementAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/RefreshTableStatementAnalyzer.java
@@ -24,7 +24,6 @@
 import com.starrocks.sql.ast.AstVisitor;
 import com.starrocks.sql.ast.DdlStmt;
 import com.starrocks.sql.ast.RefreshTableStmt;
-import com.starrocks.sql.common.MetaUtils;
 
 public class RefreshTableStatementAnalyzer {
     public static void analyze(RefreshTableStmt statement, ConnectContext context) {
@@ -45,7 +44,7 @@ public void analyze(DdlStmt statement, ConnectContext session) {
         @Override
         public Void visitRefreshTableStatement(RefreshTableStmt statement, ConnectContext context) {
             TableName tableName = statement.getTableName();
-            MetaUtils.normalizationTableName(context, tableName);
+            tableName.normalization(context);
             String catalogName = tableName.getCatalog();
             String dbName = tableName.getDb();
             String tblName = tableName.getTbl();
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ResourceGroupAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ResourceGroupAnalyzer.java
index 85647a288b9a25..251bcb2ae2c573 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ResourceGroupAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ResourceGroupAnalyzer.java
@@ -84,7 +84,7 @@ public static ResourceGroupClassifier convertPredicateToClassifier(List<Predicat
 
                     List<Long> databaseIds = new ArrayList<>();
                     for (String name : databases) {
-                        Database db = GlobalStateMgr.getCurrentState().getDb(name);
+                        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(name);
                         if (db == null) {
                             throw new SemanticException(String.format("Specified database not exists: %s", name));
                         }
@@ -152,27 +152,37 @@ public static ResourceGroupClassifier convertPredicateToClassifier(List<Predicat
     }
 
     // Property format:
-    // ('cpu_core_limit'='n', 'mem_limit'='m%', 'concurrency_limit'='n', 'type'='normal|default|realtime')
-    public static void analyzeProperties(ResourceGroup resourceGroup, Map<String, String> properties) throws SemanticException {
+    // ('cpu_weight'='n', 'mem_limit'='m%', 'concurrency_limit'='n', 'type'='normal|default|realtime')
+    public static void analyzeProperties(ResourceGroup resourceGroup, Map<String, String> properties)
+            throws SemanticException {
+        final int avgCoreNum = BackendResourceStat.getInstance().getAvgNumHardwareCoresOfBe();
         for (Map.Entry<String, String> e : properties.entrySet()) {
             String key = e.getKey();
             String value = e.getValue();
-            if (key.equalsIgnoreCase(ResourceGroup.CPU_CORE_LIMIT)) {
-                int cpuCoreLimit = Integer.parseInt(value);
-                int avgCoreNum = BackendResourceStat.getInstance().getAvgNumHardwareCoresOfBe();
-                if (cpuCoreLimit <= 0 || cpuCoreLimit > avgCoreNum) {
-                    throw new SemanticException(String.format("cpu_core_limit should range from 1 to %d", avgCoreNum));
+            if (key.equalsIgnoreCase(ResourceGroup.CPU_CORE_LIMIT) || key.equalsIgnoreCase(ResourceGroup.CPU_WEIGHT)) {
+                int cpuWeight = Integer.parseInt(value);
+                if (cpuWeight > avgCoreNum) {
+                    throw new SemanticException(
+                            String.format("%s should range from 0 to %d", ResourceGroup.CPU_WEIGHT, avgCoreNum));
+                }
+                resourceGroup.setCpuWeight(cpuWeight);
+                continue;
+            }
+            if (key.equalsIgnoreCase(ResourceGroup.DEDICATED_CPU_CORES)) {
+                int dedicatedCpuCores = Integer.parseInt(value);
+                if (dedicatedCpuCores >= avgCoreNum) {
+                    throw new SemanticException(
+                            String.format("%s should range from 0 to %d", ResourceGroup.DEDICATED_CPU_CORES, avgCoreNum - 1));
                 }
-                resourceGroup.setCpuCoreLimit(Integer.parseInt(value));
+                resourceGroup.setDedicatedCpuCores(dedicatedCpuCores);
                 continue;
             }
             if (key.equalsIgnoreCase(ResourceGroup.MAX_CPU_CORES)) {
                 int maxCpuCores = Integer.parseInt(value);
-                int avgCoreNum = BackendResourceStat.getInstance().getAvgNumHardwareCoresOfBe();
                 if (maxCpuCores > avgCoreNum) {
                     throw new SemanticException(String.format("max_cpu_cores should range from 0 to %d", avgCoreNum));
                 }
-                resourceGroup.setMaxCpuCores(Integer.parseInt(value));
+                resourceGroup.setMaxCpuCores(maxCpuCores);
                 continue;
             }
             if (key.equalsIgnoreCase(ResourceGroup.MEM_LIMIT)) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ShowAlterStmtAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ShowAlterStmtAnalyzer.java
index 80aae1f97f7a73..df71cb69fd80bc 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ShowAlterStmtAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ShowAlterStmtAnalyzer.java
@@ -68,7 +68,7 @@ public Void visitShowAlterStatement(ShowAlterStmt statement, ConnectContext cont
 
         private void handleShowAlterTable(ShowAlterStmt statement, ConnectContext context) throws SemanticException {
             // build proc path
-            @Nonnull Database db = context.getGlobalStateMgr().getDb(statement.getDbName());
+            @Nonnull Database db = context.getGlobalStateMgr().getLocalMetastore().getDb(statement.getDbName());
             ShowAlterStmt.AlterType type = statement.getType();
             StringBuilder sb = new StringBuilder();
             sb.append("/jobs/");
@@ -102,7 +102,7 @@ public void analyzeSyntax(ShowAlterStmt statement, ConnectContext context) {
             }
             statement.setDbName(dbName);
             // Check db.
-            if (context.getGlobalStateMgr().getDb(dbName) == null) {
+            if (context.getGlobalStateMgr().getLocalMetastore().getDb(dbName) == null) {
                 ErrorReport.reportSemanticException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
             }
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ShowStmtAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ShowStmtAnalyzer.java
index 7c7159d91b72b4..5c319e1176ebd9 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ShowStmtAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ShowStmtAnalyzer.java
@@ -332,7 +332,7 @@ public Void visitDescTableStmt(DescribeStmt node, ConnectContext context) {
         }
 
         private void descInternalCatalogTable(DescribeStmt node, ConnectContext context) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(node.getDb());
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(node.getDb());
             if (db == null) {
                 ErrorReport.reportSemanticException(ErrorCode.ERR_BAD_DB_ERROR, node.getDb());
             }
@@ -348,7 +348,7 @@ private void descInternalCatalogTable(DescribeStmt node, ConnectContext context)
                 }
                 //if getTable not find table, may be is statement "desc materialized-view-name"
                 if (table == null) {
-                    for (Table tb : db.getTables()) {
+                    for (Table tb : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                         if (tb.getType() == Table.TableType.OLAP) {
                             OlapTable olapTable = (OlapTable) tb;
                             for (MaterializedIndexMeta mvMeta : olapTable.getVisibleIndexMetas()) {
@@ -535,7 +535,7 @@ public Void visitShowPartitionsStatement(ShowPartitionsStmt statement, ConnectCo
             if (statement.getWhereClause() != null) {
                 analyzeSubPredicate(filterMap, statement.getWhereClause());
             }
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
             if (db == null) {
                 ErrorReport.reportSemanticException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ShowTabletStmtAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ShowTabletStmtAnalyzer.java
index 8a416b0160618c..4f0944a8539e3a 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ShowTabletStmtAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ShowTabletStmtAnalyzer.java
@@ -94,7 +94,7 @@ public Void visitShowTabletStatement(ShowTabletStmt statement, ConnectContext co
             // order by
             List<OrderByElement> orderByElements = statement.getOrderByElements();
             if (orderByElements != null && !orderByElements.isEmpty()) {
-                Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
                 if (db == null) {
                     throw new SemanticException("Database %s is not found", dbName);
                 }
@@ -103,7 +103,7 @@ public Void visitShowTabletStatement(ShowTabletStmt statement, ConnectContext co
                 Locker locker = new Locker();
                 locker.lockDatabase(db, LockType.READ);
                 try {
-                    table = db.getTable(tableName);
+                    table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
                     if (table == null) {
                         throw new SemanticException("Table %s is not found", tableName);
                     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/TruncateTableAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/TruncateTableAnalyzer.java
index eefb61f4927ca6..2715334fd4d775 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/TruncateTableAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/TruncateTableAnalyzer.java
@@ -19,12 +19,11 @@
 import com.starrocks.qe.ConnectContext;
 import com.starrocks.sql.ast.PartitionNames;
 import com.starrocks.sql.ast.TruncateTableStmt;
-import com.starrocks.sql.common.MetaUtils;
 
 public class TruncateTableAnalyzer {
 
     public static void analyze(TruncateTableStmt statement, ConnectContext context) {
-        MetaUtils.normalizationTableName(context, statement.getTblRef().getName());
+        statement.getTblRef().getName().normalization(context);
         if (statement.getTblRef().hasExplicitAlias()) {
             throw new SemanticException("Not support truncate table with alias");
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/UpdateAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/UpdateAnalyzer.java
index d26b16c0b6aa37..5f24949478ccaa 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/UpdateAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/UpdateAnalyzer.java
@@ -23,15 +23,18 @@
 import com.starrocks.analysis.StringLiteral;
 import com.starrocks.analysis.TableName;
 import com.starrocks.catalog.Column;
+import com.starrocks.catalog.Database;
 import com.starrocks.catalog.MaterializedView;
 import com.starrocks.catalog.OlapTable;
 import com.starrocks.catalog.Table;
 import com.starrocks.catalog.Type;
 import com.starrocks.qe.ConnectContext;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.analyzer.SelectAnalyzer.RewriteAliasVisitor;
 import com.starrocks.sql.ast.ColumnAssignment;
 import com.starrocks.sql.ast.DefaultValueExpr;
 import com.starrocks.sql.ast.JoinRelation;
+import com.starrocks.sql.ast.LoadStmt;
 import com.starrocks.sql.ast.QueryStatement;
 import com.starrocks.sql.ast.Relation;
 import com.starrocks.sql.ast.SelectList;
@@ -57,10 +60,23 @@ private static boolean checkIfUsePartialUpdate(int updateColumnCnt, int tableCol
         }
     }
 
+    private static void analyzeProperties(UpdateStmt updateStmt, ConnectContext session) {
+        Map<String, String> properties = updateStmt.getProperties();
+        properties.put(LoadStmt.MAX_FILTER_RATIO_PROPERTY,
+                String.valueOf(session.getSessionVariable().getInsertMaxFilterRatio()));
+        properties.put(LoadStmt.STRICT_MODE, String.valueOf(session.getSessionVariable().getEnableInsertStrict()));
+    }
+
     public static void analyze(UpdateStmt updateStmt, ConnectContext session) {
+        analyzeProperties(updateStmt, session);
+
         TableName tableName = updateStmt.getTableName();
-        MetaUtils.normalizationTableName(session, tableName);
-        MetaUtils.getDatabase(session, tableName);
+        tableName.normalization(session);
+        Database db = GlobalStateMgr.getCurrentState().getMetadataMgr()
+                .getDb(tableName.getCatalog(), tableName.getDb());
+        if (db == null) {
+            throw new SemanticException("Database %s is not found", tableName.getCatalogAndDb());
+        }
         Table table = MetaUtils.getSessionAwareTable(session, null, tableName);
 
         if (table instanceof MaterializedView) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ViewAnalyzer.java b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ViewAnalyzer.java
index 5f63ed9dec0440..1d1df0f360a3d5 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ViewAnalyzer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/analyzer/ViewAnalyzer.java
@@ -20,6 +20,7 @@
 import com.starrocks.common.ErrorCode;
 import com.starrocks.common.ErrorReport;
 import com.starrocks.qe.ConnectContext;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.ast.AlterClause;
 import com.starrocks.sql.ast.AlterViewClause;
 import com.starrocks.sql.ast.AlterViewStmt;
@@ -28,7 +29,6 @@
 import com.starrocks.sql.ast.CreateViewStmt;
 import com.starrocks.sql.ast.QueryRelation;
 import com.starrocks.sql.ast.StatementBase;
-import com.starrocks.sql.common.MetaUtils;
 
 import java.util.HashSet;
 import java.util.List;
@@ -67,7 +67,11 @@ public Void visitAlterViewStatement(AlterViewStmt stmt, ConnectContext context)
             final String tableName = stmt.getTableName().getTbl();
             FeNameFormat.checkTableName(tableName);
 
-            Table table = MetaUtils.getTable(stmt.getTableName());
+            Table table = GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(stmt.getTableName().getCatalog(),
+                    stmt.getTableName().getDb(), stmt.getTableName().getTbl());
+            if (table == null) {
+                throw new SemanticException("Table %s is not found", tableName);
+            }
             if (table.isConnectorView()) {
                 throw new SemanticException("cannot alter connector view");
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/ast/AlterResourceGroupStmt.java b/fe/fe-core/src/main/java/com/starrocks/sql/ast/AlterResourceGroupStmt.java
index ca7c7369298a28..0383bd8848e8fd 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/ast/AlterResourceGroupStmt.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/ast/AlterResourceGroupStmt.java
@@ -77,7 +77,8 @@ public void analyze() {
             if (changedProperties.getResourceGroupType() != null) {
                 throw new SemanticException("type of ResourceGroup is immutable");
             }
-            if (changedProperties.getCpuCoreLimit() == null &&
+            if (changedProperties.getCpuWeight() == null &&
+                    changedProperties.getDedicatedCpuCores() == null &&
                     changedProperties.getMemLimit() == null &&
                     changedProperties.getConcurrencyLimit() == null &&
                     changedProperties.getMaxCpuCores() == null &&
@@ -85,9 +86,9 @@ public void analyze() {
                     changedProperties.getBigQueryMemLimit() == null &&
                     changedProperties.getBigQueryScanRowsLimit() == null &&
                     changedProperties.getSpillMemLimitThreshold() == null) {
-                throw new SemanticException("At least one of ('cpu_core_limit', 'mem_limit', 'max_cpu_cores', " +
-                        "'concurrency_limit','big_query_mem_limit', 'big_query_scan_rows_limit', 'big_query_cpu_second_limit'" +
-                        "'spill_mem_limit_threshold', " +
+                throw new SemanticException("At least one of ('cpu_weight','dedicated_cpu_cores','mem_limit'," +
+                        "'max_cpu_cores','concurrency_limit','big_query_mem_limit', 'big_query_scan_rows_limit'," +
+                        "'big_query_cpu_second_limit','spill_mem_limit_threshold') " +
                         "should be specified");
             }
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/ast/ColumnDef.java b/fe/fe-core/src/main/java/com/starrocks/sql/ast/ColumnDef.java
index 56a684af9e7814..530d94216a440d 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/ast/ColumnDef.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/ast/ColumnDef.java
@@ -48,6 +48,7 @@
 import com.starrocks.analysis.ParseNode;
 import com.starrocks.analysis.StringLiteral;
 import com.starrocks.analysis.TypeDef;
+import com.starrocks.catalog.AggregateFunction;
 import com.starrocks.catalog.AggregateType;
 import com.starrocks.catalog.Column;
 import com.starrocks.catalog.FunctionSet;
@@ -55,6 +56,7 @@
 import com.starrocks.catalog.ScalarType;
 import com.starrocks.catalog.Table;
 import com.starrocks.catalog.Type;
+import com.starrocks.catalog.combinator.AggStateDesc;
 import com.starrocks.common.AnalysisException;
 import com.starrocks.common.Config;
 import com.starrocks.persist.ColumnIdExpr;
@@ -130,6 +132,7 @@ public DefaultValueDef(boolean isSet, Expr expr) {
     private final String defaultCharset = "utf8";
     private String charsetName = defaultCharset;
     private AggregateType aggregateType;
+    private AggStateDesc aggStateDesc;
     private boolean isKey;
     // Primary-key column should obey the not-null constraint. When creating a table, the not-null constraint will add to the primary-key column default. If the user specifies NULL explicitly, semantics analysis will report an error.
     // Now, isAllowNull is used to indicate a null constraint hold or not. Primary-key and non-primary-key columns obey different constraints, so the isAllowNull can not be assigned a default value.
@@ -144,30 +147,31 @@ public DefaultValueDef(boolean isSet, Expr expr) {
     private final NodePosition pos;
 
     public ColumnDef(String name, TypeDef typeDef) {
-        this(name, typeDef, null, false, null, false, DefaultValueDef.NOT_SET,
+        this(name, typeDef, null, false, null, null, false, DefaultValueDef.NOT_SET,
                 null, null, "", NodePosition.ZERO);
     }
 
     public ColumnDef(String name, TypeDef typeDef, Boolean isAllowNull) {
-        this(name, typeDef, null, false, null, isAllowNull, DefaultValueDef.NOT_SET,
+        this(name, typeDef, null, false, null, null, isAllowNull, DefaultValueDef.NOT_SET,
                 null, null, "", NodePosition.ZERO);
     }
 
-    public ColumnDef(String name, TypeDef typeDef, boolean isKey, AggregateType aggregateType,
+    public ColumnDef(String name, TypeDef typeDef, boolean isKey, AggregateType aggregateType, AggStateDesc aggStateDesc,
                      Boolean isAllowNull, DefaultValueDef defaultValueDef, String comment) {
-        this(name, typeDef, null, isKey, aggregateType, isAllowNull, defaultValueDef,
+        this(name, typeDef, null, isKey, aggregateType, aggStateDesc, isAllowNull, defaultValueDef,
                 null, null, comment, NodePosition.ZERO);
     }
 
     public ColumnDef(String name, TypeDef typeDef, String charsetName, boolean isKey, AggregateType aggregateType,
+                     AggStateDesc aggStateDesc,
                      Boolean isAllowNull, DefaultValueDef defaultValueDef, Boolean isAutoIncrement,
                      Expr generatedColumnExpr, String comment) {
-        this(name, typeDef, charsetName, isKey, aggregateType, isAllowNull, defaultValueDef, isAutoIncrement,
+        this(name, typeDef, charsetName, isKey, aggregateType, aggStateDesc, isAllowNull, defaultValueDef, isAutoIncrement,
                 generatedColumnExpr, comment, NodePosition.ZERO);
     }
 
     public ColumnDef(String name, TypeDef typeDef, String charsetName, boolean isKey, AggregateType aggregateType,
-                     Boolean isAllowNull, DefaultValueDef defaultValueDef, Boolean isAutoIncrement, 
+                     AggStateDesc aggStateDesc, Boolean isAllowNull, DefaultValueDef defaultValueDef, Boolean isAutoIncrement,
                      Expr generatedColumnExpr, String comment, NodePosition pos) {
         this.pos = pos;
         this.name = name;
@@ -179,6 +183,7 @@ public ColumnDef(String name, TypeDef typeDef, String charsetName, boolean isKey
         }
         this.isKey = isKey;
         this.aggregateType = aggregateType;
+        this.aggStateDesc = aggStateDesc;
         if (isAllowNull == null) {
             this.isAllowNull = true;
             this.isAllowNullImplicit = true;
@@ -347,6 +352,26 @@ public void analyze(boolean isOlap) throws AnalysisException {
                 throw new AnalysisException(
                         String.format("Invalid aggregate function '%s' for '%s'", aggregateType, name));
             }
+            // check agg_state_desc
+            if (aggregateType == AggregateType.AGG_STATE_UNION) {
+                if (aggStateDesc == null) {
+                    throw new AnalysisException(
+                            String.format("Invalid aggregate function '%s' for '%s'", aggregateType, name));
+                }
+                // Ensure agg_state_desc is compatible with type
+                AggregateFunction aggFunc = aggStateDesc.getAggregateFunction();
+                if (aggFunc == null) {
+                    throw new AnalysisException(
+                            String.format("Invalid aggregate function '%s' for '%s': aggregate function is not found",
+                                    aggregateType, name));
+                }
+                if (!aggFunc.getIntermediateTypeOrReturnType().isFullyCompatible(type)) {
+                    throw new AnalysisException(
+                            String.format("Invalid aggregate function '%s' for '%s': return type is not compatible, colunm " +
+                                            "type: %s, return type: %s",
+                                    aggregateType, name, type, aggFunc.getReturnType()));
+                }
+            }
         } else if (type.isBitmapType() || type.isHllType() || type.isPercentile()) {
             throw new AnalysisException(String.format("No aggregate function specified for '%s'", name));
         }
@@ -357,22 +382,26 @@ public void analyze(boolean isOlap) throws AnalysisException {
             }
             defaultValueDef = DefaultValueDef.EMPTY_VALUE;
         }
-
         if (type.isBitmapType()) {
             if (defaultValueDef.isSet) {
                 throw new AnalysisException(String.format("Invalid default value for '%s'", name));
             }
             defaultValueDef = DefaultValueDef.EMPTY_VALUE;
         }
-
-        // If aggregate type is REPLACE_IF_NOT_NULL, we set it nullable.
-        // If default value is not set, we set it NULL
         if (aggregateType == AggregateType.REPLACE_IF_NOT_NULL) {
+            // If aggregate type is REPLACE_IF_NOT_NULL, we set it nullable.
+            // If default value is not set, we set it NULL
             isAllowNull = true;
             if (!defaultValueDef.isSet) {
                 defaultValueDef = DefaultValueDef.NULL_DEFAULT_VALUE;
             }
         }
+        if (aggStateDesc != null) {
+            if (defaultValueDef.isSet) {
+                throw new AnalysisException(String.format("Invalid default value for '%s'", name));
+            }
+            // not set default value
+        }
 
         if (!isAllowNull && defaultValueDef == DefaultValueDef.NULL_DEFAULT_VALUE) {
             throw new AnalysisException(String.format("Invalid default value for '%s'", name));
@@ -515,8 +544,8 @@ public NodePosition getPos() {
     }
 
     public Column toColumn(Table table) {
-        Column col = new Column(name, typeDef.getType(), isKey, aggregateType, isAllowNull, defaultValueDef, comment,
-                Column.COLUMN_UNIQUE_ID_INIT_VALUE);
+        Column col = new Column(name, typeDef.getType(), isKey, aggregateType, aggStateDesc,
+                isAllowNull, defaultValueDef, comment, Column.COLUMN_UNIQUE_ID_INIT_VALUE);
         col.setIsAutoIncrement(isAutoIncrement);
         if (generatedColumnExpr != null) {
             if (table != null) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/ast/CreateResourceGroupStmt.java b/fe/fe-core/src/main/java/com/starrocks/sql/ast/CreateResourceGroupStmt.java
index 2f796d0c163105..d541944adca6f8 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/ast/CreateResourceGroupStmt.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/ast/CreateResourceGroupStmt.java
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-
 package com.starrocks.sql.ast;
 
 import com.starrocks.analysis.Predicate;
@@ -27,6 +26,8 @@
 import java.util.List;
 import java.util.Map;
 
+import static com.starrocks.catalog.ResourceGroupMgr.SHORT_QUERY_SET_DEDICATED_CPU_CORES_ERR_MSG;
+
 // ReesourceGroup create statement format
 // create resource group [if not exists] [or replace] <name>
 // to
@@ -88,9 +89,14 @@ public void analyze() throws SemanticException {
         if (resourceGroup.getResourceGroupType() == null) {
             resourceGroup.setResourceGroupType(TWorkGroupType.WG_NORMAL);
         }
-        if (resourceGroup.getCpuCoreLimit() == null) {
-            throw new SemanticException("property 'cpu_core_limit' is absent");
+
+        if (resourceGroup.getResourceGroupType() == TWorkGroupType.WG_SHORT_QUERY &&
+                (resourceGroup.getDedicatedCpuCores() != null && resourceGroup.getDedicatedCpuCores() > 0)) {
+            throw new SemanticException(SHORT_QUERY_SET_DEDICATED_CPU_CORES_ERR_MSG);
         }
+
+        ResourceGroup.validateCpuParameters(resourceGroup.getCpuWeight(), resourceGroup.getDedicatedCpuCores());
+
         if (resourceGroup.getMemLimit() == null) {
             throw new SemanticException("property 'mem_limit' is absent");
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/ast/DataDescription.java b/fe/fe-core/src/main/java/com/starrocks/sql/ast/DataDescription.java
index 7beca40a5be50b..273a775ffe7627 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/ast/DataDescription.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/ast/DataDescription.java
@@ -28,7 +28,6 @@
 import com.starrocks.analysis.ParseNode;
 import com.starrocks.analysis.SlotRef;
 import com.starrocks.analysis.StringLiteral;
-import com.starrocks.analysis.TableName;
 import com.starrocks.catalog.Column;
 import com.starrocks.catalog.FunctionSet;
 import com.starrocks.catalog.InternalCatalog;
@@ -41,9 +40,10 @@
 import com.starrocks.privilege.ObjectType;
 import com.starrocks.privilege.PrivilegeType;
 import com.starrocks.qe.ConnectContext;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.analyzer.AstToSQLBuilder;
 import com.starrocks.sql.analyzer.Authorizer;
-import com.starrocks.sql.common.MetaUtils;
+import com.starrocks.sql.analyzer.SemanticException;
 import com.starrocks.sql.parser.NodePosition;
 import com.starrocks.thrift.TNetworkAddress;
 import org.apache.logging.log4j.LogManager;
@@ -673,7 +673,11 @@ public void analyze(String fullDbName) throws AnalysisException {
     }
 
     public void analyzeTable(String fullDbName) throws AnalysisException {
-        Table table = MetaUtils.getTable(ConnectContext.get(), new TableName(fullDbName, tableName));
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(fullDbName, tableName);
+        if (table == null) {
+            throw new SemanticException("Table %s is not found", tableName.toString());
+        }
+
         if (table instanceof MaterializedView) {
             throw new AnalysisException(String.format(
                     "The data of '%s' cannot be inserted because '%s' is a materialized view," +
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/ast/DmlStmt.java b/fe/fe-core/src/main/java/com/starrocks/sql/ast/DmlStmt.java
index 5d5fd208bf8d6a..473d01c2863edb 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/ast/DmlStmt.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/ast/DmlStmt.java
@@ -14,17 +14,23 @@
 
 package com.starrocks.sql.ast;
 
+import com.google.common.collect.Maps;
 import com.starrocks.analysis.RedirectStatus;
 import com.starrocks.analysis.TableName;
 import com.starrocks.sql.parser.NodePosition;
 
+import java.util.Map;
+
 public abstract class DmlStmt extends StatementBase {
     public static final long INVALID_TXN_ID = -1L;
 
     private long txnId = INVALID_TXN_ID;
 
+    protected final Map<String, String> properties;
+
     protected DmlStmt(NodePosition pos) {
         super(pos);
+        this.properties = Maps.newHashMap();
     }
 
     @Override
@@ -41,4 +47,8 @@ public long getTxnId() {
     public void setTxnId(long txnId) {
         this.txnId = txnId;
     }
+
+    public Map<String, String> getProperties() {
+        return properties;
+    }
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/ast/ExportStmt.java b/fe/fe-core/src/main/java/com/starrocks/sql/ast/ExportStmt.java
index 20cf7ec114fec0..34bed282cc1b90 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/ast/ExportStmt.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/ast/ExportStmt.java
@@ -178,11 +178,11 @@ public boolean isIncludeQueryId() {
     }
 
     public void checkTable(GlobalStateMgr globalStateMgr) {
-        Database db = globalStateMgr.getDb(tblName.getDb());
+        Database db = globalStateMgr.getLocalMetastore().getDb(tblName.getDb());
         if (db == null) {
             throw new SemanticException("Db does not exist. name: " + tblName.getDb());
         }
-        Table table = db.getTable(tblName.getTbl());
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tblName.getTbl());
         if (table == null) {
             throw new SemanticException("Table[" + tblName.getTbl() + "] does not exist");
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/ast/InsertStmt.java b/fe/fe-core/src/main/java/com/starrocks/sql/ast/InsertStmt.java
index 599cdf79c1254b..40f7ef3b022f5b 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/ast/InsertStmt.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/ast/InsertStmt.java
@@ -97,12 +97,8 @@ public class InsertStmt extends DmlStmt {
     private boolean isVersionOverwrite = false;
 
     public InsertStmt(TableName tblName, PartitionNames targetPartitionNames, String label, List<String> cols,
-                      QueryStatement queryStatement, boolean isOverwrite) {
-        this(tblName, targetPartitionNames, label, cols, queryStatement, isOverwrite, NodePosition.ZERO);
-    }
-
-    public InsertStmt(TableName tblName, PartitionNames targetPartitionNames, String label, List<String> cols,
-                      QueryStatement queryStatement, boolean isOverwrite, NodePosition pos) {
+                      QueryStatement queryStatement, boolean isOverwrite, Map<String, String> insertProperties,
+                      NodePosition pos) {
         super(pos);
         this.tblName = tblName;
         this.targetPartitionNames = targetPartitionNames;
@@ -110,6 +106,7 @@ public InsertStmt(TableName tblName, PartitionNames targetPartitionNames, String
         this.queryStatement = queryStatement;
         this.targetColumnNames = cols;
         this.isOverwrite = isOverwrite;
+        this.properties.putAll(insertProperties);
         this.tableFunctionAsTargetTable = false;
         this.tableFunctionProperties = null;
         this.blackHoleTableAsTargetTable = false;
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowAnalyzeStatusStmt.java b/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowAnalyzeStatusStmt.java
index 6a8e3755081dbe..ff3f16ba9a6e14 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowAnalyzeStatusStmt.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowAnalyzeStatusStmt.java
@@ -25,9 +25,9 @@
 import com.starrocks.privilege.AccessDeniedException;
 import com.starrocks.qe.ConnectContext;
 import com.starrocks.qe.ShowResultSetMetaData;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.analyzer.Authorizer;
 import com.starrocks.sql.analyzer.SemanticException;
-import com.starrocks.sql.common.MetaUtils;
 import com.starrocks.sql.parser.NodePosition;
 import com.starrocks.statistic.AnalyzeStatus;
 import com.starrocks.statistic.StatisticUtils;
@@ -74,8 +74,11 @@ public static List<String> showAnalyzeStatus(ConnectContext context,
         Table table;
         // In new privilege framework(RBAC), user needs any action on the table to show analysis status for it.
         try {
-            table = MetaUtils.getTable(analyzeStatus.getCatalogName(), analyzeStatus.getDbName(),
-                    analyzeStatus.getTableName());
+            table = GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(
+                    analyzeStatus.getCatalogName(), analyzeStatus.getDbName(), analyzeStatus.getTableName());
+            if (table == null) {
+                throw new SemanticException("Table %s is not found", analyzeStatus.getTableName());
+            }
             Authorizer.checkAnyActionOnTableLikeObject(context.getCurrentUserIdentity(),
                     context.getCurrentRoleIds(), analyzeStatus.getDbName(), table);
         } catch (AccessDeniedException | SemanticException e) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowBasicStatsMetaStmt.java b/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowBasicStatsMetaStmt.java
index 9c1fbcd88057b9..1a9a5e214dfa57 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowBasicStatsMetaStmt.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowBasicStatsMetaStmt.java
@@ -65,12 +65,12 @@ public static List<String> showBasicStatsMeta(ConnectContext context,
         long tableId = basicStatsMeta.getTableId();
         List<String> columns = basicStatsMeta.getColumns();
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new MetaNotFoundException("No found database: " + dbId);
         }
         row.set(0, db.getOriginName());
-        Table table = db.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             throw new MetaNotFoundException("No found table: " + tableId);
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowHistogramStatsMetaStmt.java b/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowHistogramStatsMetaStmt.java
index c67f5c30e9d38d..d63ffd565bc24f 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowHistogramStatsMetaStmt.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowHistogramStatsMetaStmt.java
@@ -62,12 +62,12 @@ public static List<String> showHistogramStatsMeta(ConnectContext context,
         long dbId = histogramStatsMeta.getDbId();
         long tableId = histogramStatsMeta.getTableId();
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new MetaNotFoundException("No found database: " + dbId);
         }
         row.set(0, db.getOriginName());
-        Table table = db.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             throw new MetaNotFoundException("No found table: " + tableId);
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowMaterializedViewsStmt.java b/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowMaterializedViewsStmt.java
index 089a05de051584..70012db2f736c8 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowMaterializedViewsStmt.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowMaterializedViewsStmt.java
@@ -65,6 +65,7 @@ public class ShowMaterializedViewsStmt extends ShowStmt {
                     .column("text", ScalarType.createVarchar(1024))
                     .column("extra_message", ScalarType.createVarchar(1024))
                     .column("query_rewrite_status", ScalarType.createVarchar(64))
+                    .column("creator", ScalarType.createVarchar(64))
                     .build();
 
     private static final Map<String, String> ALIAS_MAP = ImmutableMap.of(
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowResourceGroupStmt.java b/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowResourceGroupStmt.java
index 16af2418f9c9fa..76daea6503acaf 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowResourceGroupStmt.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/ast/ShowResourceGroupStmt.java
@@ -30,23 +30,28 @@
 public class ShowResourceGroupStmt extends ShowStmt {
     private final String name;
     private final boolean listAll;
+    private final boolean verbose;
 
-    public ShowResourceGroupStmt(String name, boolean listAll) {
-        this(name, listAll, NodePosition.ZERO);
-    }
-
-    public ShowResourceGroupStmt(String name, boolean listAll, NodePosition pos) {
+    public ShowResourceGroupStmt(String name, boolean listAll, boolean verbose, NodePosition pos) {
         super(pos);
         this.name = name;
         this.listAll = listAll;
+        this.verbose = verbose;
     }
 
     public boolean isListAll() {
         return listAll;
     }
 
+    public boolean isVerbose() {
+        return verbose;
+    }
+
     @Override
     public ShowResultSetMetaData getMetaData() {
+        if (verbose) {
+            return ResourceGroup.VERBOSE_META_DATA;
+        }
         return ResourceGroup.META_DATA;
     }
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/ast/pipe/ShowPipeStmt.java b/fe/fe-core/src/main/java/com/starrocks/sql/ast/pipe/ShowPipeStmt.java
index 8322c49c86a3da..388185a5110125 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/ast/pipe/ShowPipeStmt.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/ast/pipe/ShowPipeStmt.java
@@ -69,7 +69,7 @@ public ShowPipeStmt(String dbName, String like, Expr where, List<OrderByElement>
      * NOTE: Must be consistent with the META_DATA
      */
     public static void handleShow(List<Comparable> row, Pipe pipe) {
-        Optional<Database> db = GlobalStateMgr.getCurrentState().mayGetDb(pipe.getPipeId().getDbId());
+        Optional<Database> db = GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetDb(pipe.getPipeId().getDbId());
         row.add(db.map(Database::getFullName).orElse(""));
         row.add(String.valueOf(pipe.getPipeId().getId()));
         row.add(pipe.getName());
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/common/MetaUtils.java b/fe/fe-core/src/main/java/com/starrocks/sql/common/MetaUtils.java
index 854711fc254463..8231c76e8834be 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/common/MetaUtils.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/common/MetaUtils.java
@@ -24,7 +24,6 @@
 import com.starrocks.catalog.ColumnId;
 import com.starrocks.catalog.Database;
 import com.starrocks.catalog.ExternalOlapTable;
-import com.starrocks.catalog.InternalCatalog;
 import com.starrocks.catalog.OlapTable;
 import com.starrocks.catalog.Table;
 import com.starrocks.common.ErrorCode;
@@ -91,70 +90,6 @@ public static void checkNotSupportCatalog(String catalogName, String operation)
         }
     }
 
-    public static Database getDatabase(long dbId) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
-        if (db == null) {
-            throw new SemanticException("Database %s is not found", dbId);
-        }
-        return db;
-    }
-
-    public static Table getTable(long dbId, long tableId) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
-        if (db == null) {
-            throw new SemanticException("Database %s is not found", dbId);
-        }
-        Table table = db.getTable(tableId);
-        if (table == null) {
-            throw new SemanticException("Table %s is not found", tableId);
-        }
-        return table;
-    }
-
-    public static Database getDatabase(ConnectContext session, TableName tableName) {
-        if (Strings.isNullOrEmpty(tableName.getCatalog())) {
-            tableName.setCatalog(session.getCurrentCatalog());
-        }
-        Database db = session.getGlobalStateMgr().getMetadataMgr().getDb(tableName.getCatalog(), tableName.getDb());
-        if (db == null) {
-            throw new SemanticException("Database %s is not found", tableName.getCatalogAndDb());
-        }
-        return db;
-    }
-
-    public static Database getDatabase(String catalogName, String dbName) {
-        Database db = GlobalStateMgr.getCurrentState().getMetadataMgr().getDb(catalogName, dbName);
-        if (db == null) {
-            ErrorReport.reportSemanticException(ErrorCode.ERR_BAD_DB_ERROR, dbName);
-        }
-        return db;
-    }
-
-    public static Table getTable(TableName tableName) {
-        if (Strings.isNullOrEmpty(tableName.getCatalog())) {
-            tableName.setCatalog(InternalCatalog.DEFAULT_INTERNAL_CATALOG_NAME);
-        }
-        Table table = GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(tableName.getCatalog(),
-                tableName.getDb(), tableName.getTbl());
-        if (table == null) {
-            throw new SemanticException("Table %s is not found", tableName);
-        }
-        return table;
-    }
-
-    public static Table getTable(ConnectContext session, TableName tableName) {
-        if (Strings.isNullOrEmpty(tableName.getCatalog())) {
-            tableName.setCatalog(session.getCurrentCatalog());
-        }
-        Table table = session.getGlobalStateMgr().getMetadataMgr().getTable(tableName.getCatalog(),
-                tableName.getDb(), tableName.getTbl());
-
-        if (table == null) {
-            throw new SemanticException("Table %s is not found", tableName.toString());
-        }
-        return table;
-    }
-
     // get table by tableName, unlike getTable, this interface is session aware,
     // which means if there is a temporary table with the same name,
     // use temporary table first, otherwise, treat it as a permanent table
@@ -163,7 +98,13 @@ public static Table getSessionAwareTable(ConnectContext session, Database databa
             tableName.setCatalog(session.getCurrentCatalog());
         }
         if (database == null) {
-            database = getDatabase(session, tableName);
+            if (Strings.isNullOrEmpty(tableName.getCatalog())) {
+                tableName.setCatalog(session.getCurrentCatalog());
+            }
+            database = GlobalStateMgr.getCurrentState().getMetadataMgr().getDb(tableName.getCatalog(), tableName.getDb());
+            if (database == null) {
+                throw new SemanticException("Database %s is not found", tableName.getCatalogAndDb());
+            }
         }
 
         Table table = session.getGlobalStateMgr().getMetadataMgr().getTemporaryTable(
@@ -179,54 +120,6 @@ public static Table getSessionAwareTable(ConnectContext session, Database databa
         return table;
     }
 
-    public static Table getTable(String catalogName, String dbName, String tableName) {
-        Table table = GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(catalogName, dbName, tableName);
-        if (table == null) {
-            throw new SemanticException("Table %s is not found", tableName);
-        }
-        return table;
-    }
-
-    public static void normalizationTableName(ConnectContext connectContext, TableName tableName) {
-        if (Strings.isNullOrEmpty(tableName.getCatalog())) {
-            if (Strings.isNullOrEmpty(connectContext.getCurrentCatalog())) {
-                throw new SemanticException("No catalog selected");
-            }
-            tableName.setCatalog(connectContext.getCurrentCatalog());
-        }
-        if (Strings.isNullOrEmpty(tableName.getDb())) {
-            if (Strings.isNullOrEmpty(connectContext.getDatabase())) {
-                throw new SemanticException("No database selected");
-            }
-            tableName.setDb(connectContext.getDatabase());
-        }
-
-        if (Strings.isNullOrEmpty(tableName.getTbl())) {
-            throw new SemanticException("Table name is null");
-        }
-    }
-
-    /**
-     * Materialized view name is a little bit different from a normal table
-     * 1. Use default catalog if not specified, actually it only support default catalog until now
-     */
-    public static void normalizeMVName(ConnectContext connectContext, TableName tableName) {
-        if (Strings.isNullOrEmpty(tableName.getCatalog())) {
-            tableName.setCatalog(InternalCatalog.DEFAULT_INTERNAL_CATALOG_NAME);
-        }
-        if (Strings.isNullOrEmpty(tableName.getDb())) {
-            if (Strings.isNullOrEmpty(connectContext.getDatabase())) {
-                throw new SemanticException("No database selected. " +
-                        "You could set the database name through `<database>.<table>` or `use <database>` statement");
-            }
-            tableName.setDb(connectContext.getDatabase());
-        }
-
-        if (Strings.isNullOrEmpty(tableName.getTbl())) {
-            throw new SemanticException("Table name cannot be empty");
-        }
-    }
-
     public static Map<String, Expr> parseColumnNameToDefineExpr(OriginStatement originStmt) {
         CreateMaterializedViewStmt stmt;
 
@@ -267,12 +160,12 @@ public static ExternalOlapTable syncOLAPExternalTableMeta(ExternalOlapTable exte
     }
 
     public static boolean isPartitionExist(GlobalStateMgr stateMgr, long dbId, long tableId, long partitionId) {
-        Database db = stateMgr.getDb(dbId);
+        Database db = stateMgr.getLocalMetastore().getDb(dbId);
         if (db == null) {
             return false;
         }
         // lake table or lake materialized view
-        OlapTable table = (OlapTable) db.getTable(tableId);
+        OlapTable table = (OlapTable) stateMgr.getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             return false;
         }
@@ -326,7 +219,11 @@ public static List<String> getColumnNamesByColumnIds(Map<ColumnId, Column> idToC
     }
 
     public static Column getColumnByColumnName(long dbId, long tableId, String columnName) {
-        Table table = getTable(dbId, tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(dbId, tableId);
+        if (table == null) {
+            throw new SemanticException("Table %s is not found", tableId);
+        }
+
         Column column = table.getColumn(columnName);
         if (column == null) {
             throw new SemanticException(String.format("can not find column by name: %s", columnName));
@@ -343,7 +240,10 @@ public static Map<String, Column> buildNameToColumn(List<Column> schema) {
     }
 
     public static String getColumnNameByColumnId(long dbId, long tableId, ColumnId columnId) {
-        Table table = getTable(dbId, tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(dbId, tableId);
+        if (table == null) {
+            throw new SemanticException("Table %s is not found", tableId);
+        }
         Column column = table.getColumn(columnId);
         if (column == null) {
             throw new SemanticException(String.format("can not find column by column id: %s", columnId));
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/common/ParserErrorMsg.java b/fe/fe-core/src/main/java/com/starrocks/sql/common/ParserErrorMsg.java
index 0fac5a295d5dc3..cc41f02cfb41b7 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/common/ParserErrorMsg.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/common/ParserErrorMsg.java
@@ -94,8 +94,8 @@ public interface ParserErrorMsg {
     @BaseMessage("Unsupported expr ''{0}'' in {1} clause. {2}")
     String unsupportedExprWithInfoAndExplain(String a0, String a1, String a2);
 
-    @BaseMessage("Cannot use duplicated {0} clause in building materialized view")
-    String duplicatedClause(String a0);
+    @BaseMessage("Cannot use duplicated {0} clause in {1}")
+    String duplicatedClause(String a0, String a1);
 
     @BaseMessage("''{0}'' cannot support ''{1}'' in materialized view")
     String forbidClauseInMV(String a0, String a1);
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/common/SqlWithIdUtils.java b/fe/fe-core/src/main/java/com/starrocks/sql/common/SqlWithIdUtils.java
index 30230fd2d44f21..a0577f2624d61e 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/common/SqlWithIdUtils.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/common/SqlWithIdUtils.java
@@ -80,7 +80,7 @@ public static StatementBase decode(String sql, ConnectContext context) {
             long dbId = Long.parseLong(dbStr.substring(0, dbStr.indexOf(COMMON_SUFFIX)));
             Database db = dbMap.get(dbId);
             if (db == null) {
-                db = GlobalStateMgr.getCurrentState().getDb(dbId);
+                db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
                 if (db == null) {
                     throw new SemanticException("Can not find db id: %s", dbId);
                 }
@@ -90,7 +90,7 @@ public static StatementBase decode(String sql, ConnectContext context) {
             long tableId = Long.parseLong(tableStr.substring(7, tableStr.indexOf(COMMON_SUFFIX)));
             Table table = tableMap.get(tableId);
             if (table == null) {
-                table = db.getTable(tableId);
+                table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
                 if (table == null) {
                     throw new SemanticException("Can not find table id: %s in db: %s", tableId, db.getOriginName());
                 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/common/SyncPartitionUtils.java b/fe/fe-core/src/main/java/com/starrocks/sql/common/SyncPartitionUtils.java
index f3803b1ba2029f..df2aa544f34dc8 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/common/SyncPartitionUtils.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/common/SyncPartitionUtils.java
@@ -716,11 +716,11 @@ private static void dropBaseVersionMetaForOlapTable(MaterializedView mv, String
         }
         Expr expr = mv.getPartitionRefTableExprs().get(0);
 
-        Database baseDb = GlobalStateMgr.getCurrentState().getDb(tableName.getDb());
+        Database baseDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(tableName.getDb());
         if (baseDb == null) {
             return;
         }
-        Table baseTable = baseDb.getTable(tableName.getTbl());
+        Table baseTable = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(baseDb.getFullName(), tableName.getTbl());
         if (baseTable == null) {
             return;
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/MvRewritePreprocessor.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/MvRewritePreprocessor.java
index 258365b5d3f6c3..0ebcfd138e1bea 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/MvRewritePreprocessor.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/MvRewritePreprocessor.java
@@ -57,7 +57,6 @@
 import com.starrocks.sql.optimizer.base.ColumnRefSet;
 import com.starrocks.sql.optimizer.base.DistributionSpec;
 import com.starrocks.sql.optimizer.base.HashDistributionDesc;
-import com.starrocks.sql.optimizer.base.PhysicalPropertySet;
 import com.starrocks.sql.optimizer.operator.Operator;
 import com.starrocks.sql.optimizer.operator.OperatorBuilderFactory;
 import com.starrocks.sql.optimizer.operator.Projection;
@@ -67,7 +66,6 @@
 import com.starrocks.sql.optimizer.operator.scalar.ColumnRefOperator;
 import com.starrocks.sql.optimizer.operator.scalar.ConstantOperator;
 import com.starrocks.sql.optimizer.operator.scalar.ScalarOperator;
-import com.starrocks.sql.optimizer.rule.RuleSetType;
 import com.starrocks.sql.optimizer.rule.mv.MVUtils;
 import com.starrocks.sql.optimizer.rule.transformation.materialization.MvUtils;
 import org.apache.commons.collections.CollectionUtils;
@@ -345,58 +343,49 @@ private void processPlanWithView(QueryMaterializationContext queryMaterializatio
         }
         List<LogicalViewScanOperator> viewScans = Lists.newArrayList();
         // process equivalent operator，construct logical plan with view
-        OptExpression logicalPlanWithView = extractLogicalPlanWithView(logicOperatorTree, viewScans, columnRefFactory);
+        OptExpression logicalPlanWithView = extractLogicalPlanWithView(logicOperatorTree, viewScans);
         if (viewScans.isEmpty()) {
             // means there is no plan with view
             return;
         }
         // optimize logical plan with view
-        OptExpression optimizedPlan = optimizeViewPlan(
+        OptExpression optimizedPlan = MvUtils.optimizeViewPlan(
                 logicalPlanWithView, connectContext, requiredColumns, columnRefFactory);
-        queryMaterializationContext.setLogicalTreeWithView(optimizedPlan);
-        queryMaterializationContext.setViewScans(viewScans);
+        queryMaterializationContext.setQueryOptPlanWithView(optimizedPlan);
+        queryMaterializationContext.setQueryViewScanOps(viewScans);
     }
 
-    private OptExpression optimizeViewPlan(OptExpression logicalTree,
-                                           ConnectContext connectContext,
-                                           ColumnRefSet requiredColumns,
-                                           ColumnRefFactory columnRefFactory) {
-        OptimizerConfig optimizerConfig = new OptimizerConfig(OptimizerConfig.OptimizerAlgorithm.RULE_BASED);
-        optimizerConfig.disableRuleSet(RuleSetType.SINGLE_TABLE_MV_REWRITE);
-        optimizerConfig.disableRuleSet(RuleSetType.MULTI_TABLE_MV_REWRITE);
-        Optimizer optimizer = new Optimizer(optimizerConfig);
-        OptExpression optimizedViewPlan = optimizer.optimize(connectContext, logicalTree,
-                new PhysicalPropertySet(), requiredColumns, columnRefFactory);
-        return optimizedViewPlan;
-    }
 
     private OptExpression extractLogicalPlanWithView(OptExpression logicalTree,
-                                                     List<LogicalViewScanOperator> viewScans,
-                                                     ColumnRefFactory columnRefFactory) {
+                                                     List<LogicalViewScanOperator> viewScans) {
         List<OptExpression> inputs = Lists.newArrayList();
         if (logicalTree.getOp().getEquivalentOp() != null) {
             LogicalViewScanOperator viewScanOperator = logicalTree.getOp().getEquivalentOp().cast();
-            // collect LogicalViewScanOperator to original logical tree,
-            // which will be used in mv union rewrite
-            // should use cloned plan because the following optimizeViewPlan will change the plan
+            // If the view scan operator is not rewritten, needs to use the original plan to replace the view scan operator.
+            // We don't need to evaluate the original plan directly, if view-based-rewrite successes, the original plan will
+            // not be used, so use Lazy Evaluator here.
+            // 1. Collect LogicalViewScanOperator to an original logical tree which will be used in mv union rewrite.
+            // 2. Clone the original plan because the following optimizeViewPlan will change the plan
             OptExpression clonePlan = MvUtils.cloneExpression(logicalTree);
-            OptExpression optimizedViewPlan = optimizeViewPlan(
-                    clonePlan, connectContext, viewScanOperator.getOutputColumnSet(), columnRefFactory);
-            viewScanOperator.setOriginalPlan(optimizedViewPlan);
+            viewScanOperator.setOriginalPlanEvaluator(new LogicalViewScanOperator.OptPlanEvaluator(clonePlan,
+                    connectContext, viewScanOperator.getOutputColumnSet(), queryColumnRefFactory));
             viewScans.add(viewScanOperator);
+
+            // replace the original plan with a new view scan operator
             LogicalViewScanOperator.Builder builder = new LogicalViewScanOperator.Builder();
             builder.withOperator(viewScanOperator);
             builder.setProjection(null);
-            LogicalViewScanOperator clone = builder.build();
-            OptExpression viewScanExpr = OptExpression.create(clone);
-            // should add a projection to make predicate pushdown rules work right
+            LogicalViewScanOperator clonedViewScanOp = builder.build();
+            OptExpression viewScanExpr = OptExpression.create(clonedViewScanOp);
+
+            // add a projection to make predicate push-down rules work.
             Projection projection = viewScanOperator.getProjection();
             LogicalProjectOperator projectOperator = new LogicalProjectOperator(projection.getColumnRefMap());
             OptExpression projectionExpr = OptExpression.create(projectOperator, viewScanExpr);
             return projectionExpr;
         } else {
             for (OptExpression input : logicalTree.getInputs()) {
-                OptExpression newInput = extractLogicalPlanWithView(input, viewScans, columnRefFactory);
+                OptExpression newInput = extractLogicalPlanWithView(input, viewScans);
                 inputs.add(newInput);
             }
             Operator.Builder builder = OperatorBuilderFactory.build(logicalTree.getOp());
@@ -668,7 +657,7 @@ private Set<MaterializedView> getTableRelatedSyncMVs(OlapTable olapTable) {
                 long dbId = indexMeta.getDbId();
                 String viewDefineSql = indexMeta.getViewDefineSql();
                 String mvName = olapTable.getIndexNameById(indexId);
-                Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
 
                 // distribution info
                 DistributionInfo baseTableDistributionInfo = olapTable.getDefaultDistributionInfo();
@@ -876,7 +865,7 @@ public static MaterializationContext buildMaterializationContext(OptimizerContex
 
         // Add mv info into dump info
         if (context.getDumpInfo() != null) {
-            String dbName = GlobalStateMgr.getCurrentState().getDb(mv.getDbId()).getFullName();
+            String dbName = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(mv.getDbId()).getFullName();
             context.getDumpInfo().addTable(dbName, mv);
         }
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/Optimizer.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/Optimizer.java
index 927f970f55ba4e..d4e72041b2657a 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/Optimizer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/Optimizer.java
@@ -89,6 +89,7 @@
 import com.starrocks.sql.optimizer.rule.tree.DataCachePopulateRewriteRule;
 import com.starrocks.sql.optimizer.rule.tree.ExchangeSortToMergeRule;
 import com.starrocks.sql.optimizer.rule.tree.ExtractAggregateColumn;
+import com.starrocks.sql.optimizer.rule.tree.InlineCteProjectPruneRule;
 import com.starrocks.sql.optimizer.rule.tree.JoinLocalShuffleRule;
 import com.starrocks.sql.optimizer.rule.tree.MarkParentRequiredDistributionRule;
 import com.starrocks.sql.optimizer.rule.tree.PhysicalDistributionAggOptRule;
@@ -252,7 +253,7 @@ private OptExpression optimizeByCost(ConnectContext connectContext,
         memo.init(logicOperatorTree);
         if (context.getQueryMaterializationContext() != null) {
             // LogicalTreeWithView is logically equivalent to logicOperatorTree
-            addViewBasedPlanIntoMemo(context.getQueryMaterializationContext().getLogicalTreeWithView());
+            addViewBasedPlanIntoMemo(context.getQueryMaterializationContext().getQueryOptPlanWithView());
         }
         OptimizerTraceUtil.log("after logical rewrite, root group:\n%s", memo.getRootGroup());
 
@@ -351,6 +352,7 @@ private void prepareMvRewrite(ConnectContext connectContext, OptExpression logic
         // prepare related mvs if needed and initialize mv rewrite strategy
         new MvRewritePreprocessor(connectContext, columnRefFactory, context, requiredColumns)
                 .prepare(logicOperatorTree);
+
         // initialize mv rewrite strategy finally
         mvRewriteStrategy = MvRewriteStrategy.prepareRewriteStrategy(context, connectContext, logicOperatorTree);
         OptimizerTraceUtil.logMVPrepare("MV rewrite strategy: {}", mvRewriteStrategy);
@@ -688,9 +690,10 @@ private Optional<OptExpression> ruleRewriteForShortCircuit(OptExpression tree, T
     private void viewBasedMvRuleRewrite(OptExpression tree, TaskContext rootTaskContext) {
         QueryMaterializationContext queryMaterializationContext = context.getQueryMaterializationContext();
         Preconditions.checkArgument(queryMaterializationContext != null);
-        try {
+
+        try (Timer ignored = Tracers.watchScope("MVViewRewrite")) {
             OptimizerTraceUtil.logMVRewriteRule("VIEW_BASED_MV_REWRITE", "try VIEW_BASED_MV_REWRITE");
-            OptExpression treeWithView = queryMaterializationContext.getLogicalTreeWithView();
+            OptExpression treeWithView = queryMaterializationContext.getQueryOptPlanWithView();
             // should add a LogicalTreeAnchorOperator for rewrite
             treeWithView = OptExpression.create(new LogicalTreeAnchorOperator(), treeWithView);
             if (mvRewriteStrategy.enableMultiTableRewrite) {
@@ -699,24 +702,22 @@ private void viewBasedMvRuleRewrite(OptExpression tree, TaskContext rootTaskCont
             if (mvRewriteStrategy.enableSingleTableRewrite) {
                 ruleRewriteIterative(treeWithView, rootTaskContext, RuleSetType.SINGLE_TABLE_MV_REWRITE);
             }
-            ruleRewriteIterative(tree, rootTaskContext, RuleSetType.ALL_MV_REWRITE);
-            List<Operator> viewScanOperators = Lists.newArrayList();
-            MvUtils.collectViewScanOperator(treeWithView, viewScanOperators);
 
-            List<LogicalViewScanOperator> mvViewScanOperators = queryMaterializationContext.getViewScans();
-            if (viewScanOperators.size() < mvViewScanOperators.size()) {
+            List<Operator> leftViewScanOperators = Lists.newArrayList();
+            MvUtils.collectViewScanOperator(treeWithView, leftViewScanOperators);
+            List<LogicalViewScanOperator> origQueryViewScanOperators = queryMaterializationContext.getQueryViewScanOps();
+            if (leftViewScanOperators.size() < origQueryViewScanOperators.size()) {
                 // replace original tree plan
                 tree.setChild(0, treeWithView.inputAt(0));
                 deriveLogicalProperty(tree);
-                if (!viewScanOperators.isEmpty()) {
-                    // if there are view scan operator left, we should replace it back to original plans
-                    MvUtils.replaceLogicalViewScanOperator(tree, queryMaterializationContext);
+
+                // if there are view scan operator left, we should replace it back to original plans
+                if (!leftViewScanOperators.isEmpty()) {
+                    MvUtils.replaceLogicalViewScanOperator(tree);
                 }
-                OptimizerTraceUtil.logMVRewriteRule("VIEW_BASED_MV_REWRITE",
-                        "original view scans size: {}, left view scans size: {}",
-                        mvViewScanOperators.size(), viewScanOperators.size());
             }
-            OptimizerTraceUtil.logMVRewriteRule("VIEW_BASED_MV_REWRITE", "VIEW_BASED_MV_REWRITE applied");
+            OptimizerTraceUtil.logMVRewriteRule("VIEW_BASED_MV_REWRITE", "original view scans size: {}, " +
+                            "left view scans size: {}", origQueryViewScanOperators.size(), leftViewScanOperators.size());
         } catch (Exception e) {
             OptimizerTraceUtil.logMVRewriteRule("VIEW_BASED_MV_REWRITE",
                     "single table view based mv rule rewrite failed.", e);
@@ -883,13 +884,15 @@ private OptExpression physicalRuleRewrite(ConnectContext connectContext, TaskCon
         result = new PhysicalDistributionAggOptRule().rewrite(result, rootTaskContext);
         result = new AddDecodeNodeForDictStringRule().rewrite(result, rootTaskContext);
         result = new LowCardinalityRewriteRule().rewrite(result, rootTaskContext);
+        // Put before ScalarOperatorsReuseRule
+        result = new PruneSubfieldsForComplexType().rewrite(result, rootTaskContext);
+        result = new InlineCteProjectPruneRule().rewrite(result, rootTaskContext);
         // This rule should be last
         result = new ScalarOperatorsReuseRule().rewrite(result, rootTaskContext);
         // Reorder predicates
         result = new PredicateReorderRule(rootTaskContext.getOptimizerContext().getSessionVariable()).rewrite(result,
                 rootTaskContext);
         result = new ExtractAggregateColumn().rewrite(result, rootTaskContext);
-        result = new PruneSubfieldsForComplexType().rewrite(result, rootTaskContext);
         result = new JoinLocalShuffleRule().rewrite(result, rootTaskContext);
 
         // This must be put at last of the optimization. Because wrapping reused ColumnRefOperator with CloneOperator
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/QueryMaterializationContext.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/QueryMaterializationContext.java
index e1d17dd1ef05d7..2eb8fa9c11cb20 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/QueryMaterializationContext.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/QueryMaterializationContext.java
@@ -56,11 +56,11 @@ public class QueryMaterializationContext {
     // MV with the cached timeliness update info which should be initialized once in one query context.
     private Map<MaterializedView, MvUpdateInfo> mvTimelinessInfos = Maps.newHashMap();
 
-    // used by view based mv rewrite
-    // query's logical plan with view
-    private OptExpression logicalTreeWithView;
-    // collect LogicalViewScanOperators
-    private List<LogicalViewScanOperator> viewScans;
+    // query's logical plan with view: replace all inlined query plans with LogicalViewScanOperators which is used by
+    // view-based mv rewrite
+    private OptExpression queryOptPlanWithView;
+    // collect all query opt expression's LogicalViewScanOperators
+    private List<LogicalViewScanOperator> queryViewScanOps;
 
     // `mvQueryContextCache` is designed for a common cache which is used during the query's rewrite lifecycle, so can be
     // managed in a more unified mode. In the current situation, it's used in two ways:
@@ -150,20 +150,20 @@ public QueryCacheStats getQueryCacheStats() {
         return queryCacheStats;
     }
 
-    public OptExpression getLogicalTreeWithView() {
-        return logicalTreeWithView;
+    public OptExpression getQueryOptPlanWithView() {
+        return queryOptPlanWithView;
     }
 
-    public void setLogicalTreeWithView(OptExpression logicalTreeWithView) {
-        this.logicalTreeWithView = logicalTreeWithView;
+    public void setQueryOptPlanWithView(OptExpression queryOptPlanWithView) {
+        this.queryOptPlanWithView = queryOptPlanWithView;
     }
 
-    public void setViewScans(List<LogicalViewScanOperator> viewScans) {
-        this.viewScans = viewScans;
+    public void setQueryViewScanOps(List<LogicalViewScanOperator> queryViewScanOps) {
+        this.queryViewScanOps = queryViewScanOps;
     }
 
-    public List<LogicalViewScanOperator> getViewScans() {
-        return viewScans;
+    public List<LogicalViewScanOperator> getQueryViewScanOps() {
+        return queryViewScanOps;
     }
 
     /**
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/function/MetaFunctions.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/function/MetaFunctions.java
index 03b17a91ff05fe..f122ef102405f7 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/function/MetaFunctions.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/function/MetaFunctions.java
@@ -101,9 +101,9 @@ public static Table inspectExternalTable(TableName tableName) {
     }
 
     public static Pair<Database, Table> inspectTable(TableName tableName) {
-        Database db = GlobalStateMgr.getCurrentState().mayGetDb(tableName.getDb())
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetDb(tableName.getDb())
                 .orElseThrow(() -> ErrorReport.buildSemanticException(ErrorCode.ERR_BAD_DB_ERROR, tableName.getDb()));
-        Table table = db.tryGetTable(tableName.getTbl())
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetTable(tableName.getDb(), tableName.getTbl())
                 .orElseThrow(() -> ErrorReport.buildSemanticException(ErrorCode.ERR_BAD_TABLE_ERROR, tableName));
         ConnectContext connectContext = ConnectContext.get();
         try {
@@ -167,7 +167,7 @@ public static ConstantOperator inspectRelatedMv(ConstantOperator name) {
         Optional<Database> mayDb;
         Table table = inspectExternalTable(tableName);
         if (table.isNativeTableOrMaterializedView()) {
-            mayDb = GlobalStateMgr.getCurrentState().mayGetDb(tableName.getDb());
+            mayDb = GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetDb(tableName.getDb());
         } else {
             mayDb = Optional.empty();
         }
@@ -179,7 +179,7 @@ public static ConstantOperator inspectRelatedMv(ConstantOperator name) {
             Set<MvId> relatedMvs = table.getRelatedMaterializedViews();
             JsonArray array = new JsonArray();
             for (MvId mv : SetUtils.emptyIfNull(relatedMvs)) {
-                String mvName = GlobalStateMgr.getCurrentState().mayGetTable(mv.getDbId(), mv.getId())
+                String mvName = GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetTable(mv.getDbId(), mv.getId())
                         .map(Table::getName)
                         .orElse(null);
                 JsonObject obj = new JsonObject();
@@ -246,7 +246,7 @@ public static ConstantOperator inspectAllPipes() {
         ConnectContext connectContext = ConnectContext.get();
         authOperatorPrivilege();
         String currentDb = connectContext.getDatabase();
-        Database db = GlobalStateMgr.getCurrentState().mayGetDb(connectContext.getDatabase())
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().mayGetDb(connectContext.getDatabase())
                 .orElseThrow(() -> ErrorReport.buildSemanticException(ErrorCode.ERR_BAD_DB_ERROR, currentDb));
         String json = GlobalStateMgr.getCurrentState().getPipeManager().getPipesOfDb(db.getId());
         return ConstantOperator.createVarchar(json);
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/operator/Projection.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/operator/Projection.java
index ad6397ecb43a37..5febb0f922c137 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/operator/Projection.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/operator/Projection.java
@@ -75,6 +75,9 @@ public List<ColumnRefOperator> getOutputColumns() {
     public ColumnRefSet getUsedColumns() {
         final ColumnRefSet usedColumns = new ColumnRefSet();
         columnRefMap.values().stream().forEach(e -> usedColumns.union(e.getUsedColumns()));
+        commonSubOperatorMap.values().stream().forEach(e -> usedColumns.union(e.getUsedColumns()));
+        // remove some of columnRefMap's used columns which are from commonSubOperatorMap's output column
+        commonSubOperatorMap.keySet().stream().forEach(e -> usedColumns.union(e.getUsedColumns()));
         return usedColumns;
     }
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/operator/logical/LogicalViewScanOperator.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/operator/logical/LogicalViewScanOperator.java
index 64c9508dee463d..49b417e25346da 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/operator/logical/LogicalViewScanOperator.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/operator/logical/LogicalViewScanOperator.java
@@ -14,18 +14,23 @@
 
 package com.starrocks.sql.optimizer.operator.logical;
 
+import com.google.common.base.Preconditions;
 import com.starrocks.analysis.Expr;
 import com.starrocks.catalog.Column;
 import com.starrocks.catalog.Table;
+import com.starrocks.qe.ConnectContext;
 import com.starrocks.sql.optimizer.OptExpression;
+import com.starrocks.sql.optimizer.base.ColumnRefFactory;
 import com.starrocks.sql.optimizer.base.ColumnRefSet;
 import com.starrocks.sql.optimizer.operator.Operator;
 import com.starrocks.sql.optimizer.operator.OperatorType;
 import com.starrocks.sql.optimizer.operator.OperatorVisitor;
 import com.starrocks.sql.optimizer.operator.scalar.ColumnRefOperator;
+import com.starrocks.sql.optimizer.rule.transformation.materialization.MvUtils;
 
 import java.util.Map;
 import java.util.Objects;
+import java.util.Optional;
 
 // the logical operator to scan view just like LogicalOlapScanOperator to scan olap table,
 // which is a virtual logical operator used by view based mv rewrite and has no corresponding physical operator.
@@ -34,12 +39,9 @@ public class LogicalViewScanOperator  extends LogicalScanOperator {
     private int relationId;
     private ColumnRefSet outputColumnSet;
     private Map<Expr, ColumnRefOperator> expressionToColumns;
-
-    private OptExpression originalPlan;
-
-    // add output mapping from new column to original column
-    // used to construct partition predicates
-    private Map<ColumnRefOperator, ColumnRefOperator> columnRefOperatorMap;
+    // Original plan evaluator(inlined view) for the input logical plan tree which has not done rule based rewrite yet,
+    // this is only used when the view scan operator cannot be rewritten by view-based rewrite rules.
+    private OptPlanEvaluator optPlanEvaluator;
 
     public LogicalViewScanOperator(
             int relationId,
@@ -74,12 +76,45 @@ public int getRelationId() {
         return relationId;
     }
 
-    public void setOriginalPlan(OptExpression originalPlan) {
-        this.originalPlan = originalPlan;
+    public void setOriginalPlanEvaluator(OptPlanEvaluator optPlanEvaluator) {
+        this.optPlanEvaluator = optPlanEvaluator;
     }
 
-    public OptExpression getOriginalPlan() {
-        return this.originalPlan;
+    public OptExpression getOriginalPlanEvaluator() {
+        return this.optPlanEvaluator.evaluate();
+    }
+
+    /**
+     * Evaluate the original plan and return the optimized plan for the input logical plan tree which is with inlined view and
+     * has not done rule based rewrite yet.
+     */
+    public static class OptPlanEvaluator {
+        private final OptExpression logicalTree;
+        private final ConnectContext connectContext;
+        private final ColumnRefSet requiredColumns;
+        private final ColumnRefFactory columnRefFactory;
+
+        private Optional<OptExpression> originalPlan = Optional.empty();
+
+        public OptPlanEvaluator(OptExpression logicalTree,
+                                ConnectContext connectContext,
+                                ColumnRefSet requiredColumns,
+                                ColumnRefFactory columnRefFactory) {
+            this.logicalTree = logicalTree;
+            this.connectContext = connectContext;
+            this.requiredColumns = requiredColumns;
+            this.columnRefFactory = columnRefFactory;
+        }
+
+        public OptExpression evaluate() {
+            if (!originalPlan.isPresent()) {
+                OptExpression optExpression = MvUtils.optimizeViewPlan(logicalTree, connectContext, requiredColumns,
+                        columnRefFactory);
+                originalPlan = Optional.of(optExpression);
+            }
+            Preconditions.checkArgument(originalPlan.isPresent(), "Original plan is not set");
+            return originalPlan.get();
+        }
     }
 
     @Override
@@ -115,18 +150,13 @@ protected LogicalViewScanOperator newInstance() {
             return new LogicalViewScanOperator();
         }
 
-        public Builder setOriginalPlan(OptExpression originalPlan) {
-            builder.originalPlan = originalPlan;
-            return this;
-        }
-
         @Override
         public LogicalViewScanOperator.Builder withOperator(LogicalViewScanOperator scanOperator) {
             super.withOperator(scanOperator);
             builder.relationId = scanOperator.relationId;
             builder.expressionToColumns = scanOperator.expressionToColumns;
             builder.outputColumnSet = scanOperator.outputColumnSet;
-            builder.originalPlan = scanOperator.originalPlan;
+            builder.optPlanEvaluator = scanOperator.optPlanEvaluator;
             return this;
         }
     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/MaterializedViewTransparentRewriteRule.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/MaterializedViewTransparentRewriteRule.java
index c04747dcf05e70..5fad4d24c465ff 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/MaterializedViewTransparentRewriteRule.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/MaterializedViewTransparentRewriteRule.java
@@ -136,9 +136,9 @@ private OptExpression doGetMvTransparentPlan(ConnectContext connectContext,
                                                  LogicalOlapScanOperator olapScanOperator,
                                                  OptExpression input) {
         // Fetch mv from catalog again since table from olap scan operator is copied.
-        Database db = GlobalStateMgr.getCurrentState().getDb(mvId.getDbId());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(mvId.getDbId());
         Preconditions.checkState(db != null, "Database not found: %s", mvId.getDbId());
-        Table table = db.getTable(mvId.getId());
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), mvId.getId());
         Preconditions.checkState(table instanceof MaterializedView);
         MaterializedView mv = (MaterializedView) table;
         MvPlanContext mvPlanContext = MvUtils.getMVPlanContext(connectContext, mv, true);
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MaterializedViewRewriter.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MaterializedViewRewriter.java
index 513838e7d9ee84..3c7871c5cd00af 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MaterializedViewRewriter.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MaterializedViewRewriter.java
@@ -1958,8 +1958,7 @@ private ScalarOperator rewriteScalarOperatorToTarget(
 
     protected OptExpression queryBasedRewrite(RewriteContext rewriteContext, ScalarOperator compensationPredicates,
                                               OptExpression queryExpression) {
-        queryExpression = MvUtils.replaceLogicalViewScanOperator(queryExpression,
-                materializationContext.getOptimizerContext().getQueryMaterializationContext());
+        queryExpression = MvUtils.replaceLogicalViewScanOperator(queryExpression);
         if (queryExpression == null) {
             return null;
         }
@@ -2148,8 +2147,8 @@ private ColumnRefOperator findQueryPartitionColumnRef(
         partitionColumnRef = columnRewriter.rewriteViewToQuery(partitionColumnRef).cast();
 
         // for view based mv rewrite, we should mapping the partition column to output column of view scan
-        if (queryMaterializationContext.getViewScans() != null) {
-            for (LogicalViewScanOperator viewScanOperator : queryMaterializationContext.getViewScans()) {
+        if (queryMaterializationContext.getQueryViewScanOps() != null) {
+            for (LogicalViewScanOperator viewScanOperator : queryMaterializationContext.getQueryViewScanOps()) {
                 Projection projection = viewScanOperator.getProjection();
                 if (viewScanOperator.getProjection() != null) {
                     for (Map.Entry<ColumnRefOperator, ScalarOperator> entry : projection.getColumnRefMap().entrySet()) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRewriteStrategy.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRewriteStrategy.java
index 43e0406d8980f9..b47f1033ebbdd2 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRewriteStrategy.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRewriteStrategy.java
@@ -93,7 +93,7 @@ private boolean isEnableMaterializedViewRewrite() {
 
         private boolean isEnableRBOViewBasedRewrite() {
             return optimizerContext.getQueryMaterializationContext() != null
-                    && optimizerContext.getQueryMaterializationContext().getLogicalTreeWithView() != null
+                    && optimizerContext.getQueryMaterializationContext().getQueryOptPlanWithView() != null
                     && sessionVariable.isEnableViewBasedMvRewrite()
                     && !sessionVariable.isEnableCBOViewBasedMvRewrite();
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvUtils.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvUtils.java
index 4154d7f65457c2..60b03db80bfb8b 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvUtils.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvUtils.java
@@ -108,6 +108,7 @@
 import com.starrocks.sql.optimizer.rewrite.ReplaceColumnRefRewriter;
 import com.starrocks.sql.optimizer.rewrite.ScalarOperatorRewriter;
 import com.starrocks.sql.optimizer.rule.Rule;
+import com.starrocks.sql.optimizer.rule.RuleSetType;
 import com.starrocks.sql.optimizer.rule.mv.MVUtils;
 import com.starrocks.sql.optimizer.transformer.LogicalPlan;
 import com.starrocks.sql.optimizer.transformer.RelationTransformer;
@@ -173,12 +174,12 @@ public static void getRelatedMvs(ConnectContext connectContext,
         }
         Set<Table> newMvs = Sets.newHashSet();
         for (MvId mvId : newMvIds) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(mvId.getDbId());
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(mvId.getDbId());
             if (db == null) {
                 logMVPrepare("Cannot find database from mvId:{}", mvId);
                 continue;
             }
-            Table table = db.getTable(mvId.getId());
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), mvId.getId());
             if (table == null) {
                 logMVPrepare("Cannot find materialized view from mvId:{}", mvId);
                 continue;
@@ -1150,7 +1151,8 @@ public static void inactiveRelatedMaterializedViews(Database db,
         }
         // inactive related asynchronous mvs
         for (MvId mvId : olapTable.getRelatedMaterializedViews()) {
-            MaterializedView mv = (MaterializedView) db.getTable(mvId.getId());
+            MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(db.getId(), mvId.getId());
             if (mv == null) {
                 LOG.warn("Ignore materialized view {} does not exists", mvId);
                 continue;
@@ -1216,15 +1218,10 @@ public static void collectViewScanOperator(OptExpression tree, Collection<Operat
         }
     }
 
-    public static OptExpression replaceLogicalViewScanOperator(OptExpression queryExpression,
-                                                               QueryMaterializationContext queryMaterializationContext) {
-        List<LogicalViewScanOperator> viewScans = queryMaterializationContext.getViewScans();
-        if (viewScans == null) {
-            return queryExpression;
-        }
+    public static OptExpression replaceLogicalViewScanOperator(OptExpression queryExpression) {
         // add a LogicalTreeAnchorOperator to replace the tree easier
         OptExpression anchorExpr = OptExpression.create(new LogicalTreeAnchorOperator(), queryExpression);
-        doReplaceLogicalViewScanOperator(anchorExpr, 0, queryExpression, viewScans);
+        doReplaceLogicalViewScanOperator(anchorExpr, 0, queryExpression);
         List<Operator> viewScanOperators = Lists.newArrayList();
         MvUtils.collectViewScanOperator(anchorExpr, viewScanOperators);
         if (!viewScanOperators.isEmpty()) {
@@ -1235,20 +1232,18 @@ public static OptExpression replaceLogicalViewScanOperator(OptExpression queryEx
         return newQuery;
     }
 
-    private static void doReplaceLogicalViewScanOperator(
-            OptExpression parent,
-            int index,
-            OptExpression queryExpression,
-            List<LogicalViewScanOperator> viewScans) {
+    private static void doReplaceLogicalViewScanOperator(OptExpression parent,
+                                                         int index,
+                                                         OptExpression queryExpression) {
         LogicalOperator op = queryExpression.getOp().cast();
         if (op instanceof LogicalViewScanOperator) {
             LogicalViewScanOperator viewScanOperator = op.cast();
-            OptExpression viewPlan = viewScanOperator.getOriginalPlan();
+            OptExpression viewPlan = viewScanOperator.getOriginalPlanEvaluator();
             parent.setChild(index, viewPlan);
             return;
         }
         for (int i = 0; i < queryExpression.getInputs().size(); i++) {
-            doReplaceLogicalViewScanOperator(queryExpression, i, queryExpression.inputAt(i), viewScans);
+            doReplaceLogicalViewScanOperator(queryExpression, i, queryExpression.inputAt(i));
         }
     }
 
@@ -1526,4 +1521,25 @@ public static ScalarOperator convertPartitionKeysToListPredicate(ScalarOperator
         }
         return MvUtils.convertToInPredicate(partitionColRef, values);
     }
+
+    /**
+     * Optimize the inlined view plan.
+     * @param logicalTree logical opt expression tree which has not been optimized
+     * @param connectContext connect context
+     * @param requiredColumns required columns
+     * @param columnRefFactory query column ref factory
+     * @return optimized view plan which has been rule based optimized
+     */
+    public static OptExpression optimizeViewPlan(OptExpression logicalTree,
+                                                 ConnectContext connectContext,
+                                                 ColumnRefSet requiredColumns,
+                                                 ColumnRefFactory columnRefFactory) {
+        OptimizerConfig optimizerConfig = new OptimizerConfig(OptimizerConfig.OptimizerAlgorithm.RULE_BASED);
+        optimizerConfig.disableRuleSet(RuleSetType.SINGLE_TABLE_MV_REWRITE);
+        optimizerConfig.disableRuleSet(RuleSetType.MULTI_TABLE_MV_REWRITE);
+        Optimizer optimizer = new Optimizer(optimizerConfig);
+        OptExpression optimizedViewPlan = optimizer.optimize(connectContext, logicalTree,
+                new PhysicalPropertySet(), requiredColumns, columnRefFactory);
+        return optimizedViewPlan;
+    }
 }
\ No newline at end of file
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/OptExpressionDuplicator.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/OptExpressionDuplicator.java
index dff21ad8abb463..72870041824aeb 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/OptExpressionDuplicator.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/transformation/materialization/OptExpressionDuplicator.java
@@ -230,33 +230,22 @@ public OptExpression visitLogicalTableScan(OptExpression optExpression, Void con
                     }
                 }
             } else {
-                try {
-                    if (isRefreshExternalTable && scanOperator.getOpType() == OperatorType.LOGICAL_ICEBERG_SCAN) {
-                        // refresh iceberg table's metadata
-                        Table refBaseTable = scanOperator.getTable();
-                        IcebergTable cachedIcebergTable = (IcebergTable) refBaseTable;
-                        String catalogName = cachedIcebergTable.getCatalogName();
-                        String dbName = cachedIcebergTable.getRemoteDbName();
-                        TableName tableName = new TableName(catalogName, dbName, cachedIcebergTable.getName());
-                        Table currentTable = GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(tableName).orElse(null);
-                        if (currentTable == null) {
-                            return null;
-                        }
-                        
-                        scanBuilder.setTable(currentTable);
-                        TableVersionRange versionRange = TableVersionRange.withEnd(
-                                Optional.ofNullable(((IcebergTable) currentTable).getNativeTable().currentSnapshot())
-                                        .map(Snapshot::snapshotId));
-                        scanBuilder.setTableVersionRange(versionRange);
-                    }
-                    ScanOperatorPredicates scanOperatorPredicates = scanOperator.getScanOperatorPredicates();
-                    if (isResetSelectedPartitions) {
-                        scanOperatorPredicates.clear();
-                    } else {
-                        scanOperatorPredicates.duplicate(rewriter);
+                if (isRefreshExternalTable && scanOperator.getOpType() == OperatorType.LOGICAL_ICEBERG_SCAN) {
+                    // refresh iceberg table's metadata
+                    Table refBaseTable = scanOperator.getTable();
+                    IcebergTable cachedIcebergTable = (IcebergTable) refBaseTable;
+                    String catalogName = cachedIcebergTable.getCatalogName();
+                    String dbName = cachedIcebergTable.getRemoteDbName();
+                    TableName tableName = new TableName(catalogName, dbName, cachedIcebergTable.getName());
+                    Table currentTable = GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(tableName).orElse(null);
+                    if (currentTable == null) {
+                        return null;
                     }
-                } catch (AnalysisException e) {
-                    // ignore exception
+                    scanBuilder.setTable(currentTable);
+                    TableVersionRange versionRange = TableVersionRange.withEnd(
+                            Optional.ofNullable(((IcebergTable) currentTable).getNativeTable().currentSnapshot())
+                                    .map(Snapshot::snapshotId));
+                    scanBuilder.setTableVersionRange(versionRange);
                 }
             }
 
@@ -281,7 +270,25 @@ public OptExpression visitLogicalTableScan(OptExpression optExpression, Void con
             ImmutableMap<ColumnRefOperator, Column> newColumnRefColumnMap = columnRefColumnMapBuilder.build();
             scanBuilder.setColRefToColumnMetaMap(newColumnRefColumnMap);
 
-            return OptExpression.create(opBuilder.build());
+            // process external table scan operator's predicates
+            LogicalScanOperator newScanOperator = (LogicalScanOperator) opBuilder.build();
+            if (!(scanOperator instanceof LogicalOlapScanOperator)) {
+                processExternalTableScanOperator(newScanOperator);
+            }
+            return OptExpression.create(newScanOperator);
+        }
+
+        private void processExternalTableScanOperator(LogicalScanOperator newScanOperator) {
+            try {
+                ScanOperatorPredicates scanOperatorPredicates = newScanOperator.getScanOperatorPredicates();
+                if (isResetSelectedPartitions) {
+                    scanOperatorPredicates.clear();
+                } else {
+                    scanOperatorPredicates.duplicate(rewriter);
+                }
+            } catch (AnalysisException e) {
+                // ignore exception
+            }
         }
 
         @Override
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/InlineCteProjectPruneRule.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/InlineCteProjectPruneRule.java
new file mode 100644
index 00000000000000..7484d666fffa5d
--- /dev/null
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/InlineCteProjectPruneRule.java
@@ -0,0 +1,65 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+package com.starrocks.sql.optimizer.rule.tree;
+
+import com.starrocks.sql.optimizer.OptExpression;
+import com.starrocks.sql.optimizer.OptExpressionVisitor;
+import com.starrocks.sql.optimizer.operator.Projection;
+import com.starrocks.sql.optimizer.operator.physical.PhysicalNoCTEOperator;
+import com.starrocks.sql.optimizer.operator.physical.PhysicalOperator;
+import com.starrocks.sql.optimizer.task.TaskContext;
+
+public class InlineCteProjectPruneRule implements TreeRewriteRule {
+    private static final InlineCteProjectPruneRuleVisitor HANDLER = new InlineCteProjectPruneRuleVisitor();
+
+    @Override
+    public OptExpression rewrite(OptExpression root, TaskContext taskContext) {
+        root.getOp().accept(HANDLER, root, taskContext);
+        return root;
+    }
+
+    private static class InlineCteProjectPruneRuleVisitor extends OptExpressionVisitor<Void, TaskContext> {
+        @Override
+        public Void visit(OptExpression opt, TaskContext context) {
+            for (OptExpression input : opt.getInputs()) {
+                input.getOp().accept(this, input, context);
+            }
+            return null;
+        }
+
+        @Override
+        public Void visitPhysicalNoCTE(OptExpression opt, TaskContext context) {
+            PhysicalNoCTEOperator op = (PhysicalNoCTEOperator) opt.getOp();
+            if (op.getProjection() == null) {
+                visit(opt, context);
+                return null;
+            }
+            Projection parentProjection = op.getProjection();
+
+            PhysicalOperator child = (PhysicalOperator) opt.getInputs().get(0).getOp();
+            if (child.getProjection() == null) {
+                visit(opt, context);
+                return null;
+            }
+
+            Projection childProjection = child.getProjection();
+            if (!parentProjection.getUsedColumns().containsAny(childProjection.getOutputColumns())) {
+                child.setProjection(null);
+            }
+
+            visit(opt, context);
+            return null;
+        }
+    }
+}
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/PruneSubfieldsForComplexType.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/PruneSubfieldsForComplexType.java
index 0cf5c3662397a0..3e7436bc3b9046 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/PruneSubfieldsForComplexType.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/PruneSubfieldsForComplexType.java
@@ -20,6 +20,8 @@
 import com.starrocks.common.FeConstants;
 import com.starrocks.sql.optimizer.OptExpression;
 import com.starrocks.sql.optimizer.OptExpressionVisitor;
+import com.starrocks.sql.optimizer.RowOutputInfo;
+import com.starrocks.sql.optimizer.operator.ColumnOutputInfo;
 import com.starrocks.sql.optimizer.operator.OperatorType;
 import com.starrocks.sql.optimizer.operator.Projection;
 import com.starrocks.sql.optimizer.operator.physical.PhysicalHashAggregateOperator;
@@ -32,6 +34,7 @@
 import com.starrocks.sql.optimizer.operator.scalar.ScalarOperator;
 import com.starrocks.sql.optimizer.task.TaskContext;
 
+import java.util.List;
 import java.util.Map;
 
 public class PruneSubfieldsForComplexType implements TreeRewriteRule {
@@ -63,20 +66,14 @@ private static class MarkSubfieldsOptVisitor extends OptExpressionVisitor<Void,
 
         @Override
         public Void visit(OptExpression optExpression, PruneComplexTypeUtil.Context context) {
-            ScalarOperator predicate = optExpression.getOp().getPredicate();
-            Projection projection = optExpression.getOp().getProjection();
-
-            if (projection != null) {
-                for (Map.Entry<ColumnRefOperator, ScalarOperator> entry : projection.getColumnRefMap().entrySet()) {
-                    context.add(entry.getKey(), entry.getValue());
-                }
-
-                for (Map.Entry<ColumnRefOperator, ScalarOperator> entry : projection.getCommonSubOperatorMap()
-                        .entrySet()) {
-                    context.add(entry.getKey(), entry.getValue());
-                }
+            // collect output ColumnRefOperator
+            RowOutputInfo rowOutputInfo = optExpression.getOp().getRowOutputInfo(optExpression.getInputs());
+            List<ColumnOutputInfo> columnOutputInfos = rowOutputInfo.getColumnOutputInfo();
+            for (ColumnOutputInfo columnOutputInfo : columnOutputInfos) {
+                context.add(columnOutputInfo.getColumnRef(), columnOutputInfo.getScalarOp());
             }
 
+            ScalarOperator predicate = optExpression.getOp().getPredicate();
             if (predicate != null) {
                 context.add(null, predicate);
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/PruneSubfieldRule.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/PruneSubfieldRule.java
index 5d224a8e91509e..c2dbf05d866057 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/PruneSubfieldRule.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/PruneSubfieldRule.java
@@ -56,13 +56,21 @@ public class PruneSubfieldRule extends TransformationRule {
             .add(FunctionSet.JSON_LENGTH)
             .build();
 
-    public static final List<String> SUPPORT_FUNCTIONS = ImmutableList.<String>builder()
+    public static final List<String> PRUNE_FUNCTIONS = ImmutableList.<String>builder()
             .add(FunctionSet.MAP_KEYS, FunctionSet.MAP_SIZE)
             .add(FunctionSet.ARRAY_LENGTH)
             .add(FunctionSet.CARDINALITY)
             .addAll(SUPPORT_JSON_FUNCTIONS)
             .build();
 
+    public static final List<String> PUSHDOWN_FUNCTIONS = ImmutableList.<String>builder()
+            .addAll(PRUNE_FUNCTIONS)
+            .add(FunctionSet.ARRAY_CONTAINS, FunctionSet.ARRAY_CONTAINS_ALL)
+            .add(FunctionSet.ARRAY_MAX, FunctionSet.ARRAY_MIN, FunctionSet.ARRAY_SUM, FunctionSet.ARRAY_AVG)
+            .add(FunctionSet.ARRAY_POSITION)
+            .add(FunctionSet.ARRAY_JOIN)
+            .build();
+
     public PruneSubfieldRule() {
         super(RuleType.TF_PRUNE_SUBFIELD, Pattern.create(OperatorType.LOGICAL_PROJECT, OperatorType.PATTERN_SCAN));
     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/PushDownSubfieldRule.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/PushDownSubfieldRule.java
index d54cc9f6431217..82bc87db8cc4e7 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/PushDownSubfieldRule.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/PushDownSubfieldRule.java
@@ -222,7 +222,7 @@ public OptExpression visitLogicalProject(OptExpression optExpression, Context co
             ColumnRefSet allUsedColumns = new ColumnRefSet();
             context.pushDownExprUseColumns.values().forEach(allUsedColumns::union);
 
-            SubfieldExpressionCollector collector = new SubfieldExpressionCollector();
+            SubfieldExpressionCollector collector = SubfieldExpressionCollector.buildPushdownCollector();
             for (ScalarOperator value : lpo.getColumnRefMap().values()) {
                 // check repeat put complex column, like that
                 //      project( columnB: structA.b.c.d )
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/SubfieldAccessPathNormalizer.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/SubfieldAccessPathNormalizer.java
index 6d1e3fbffafe99..dae39d2fe768d3 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/SubfieldAccessPathNormalizer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/SubfieldAccessPathNormalizer.java
@@ -192,7 +192,7 @@ public Optional<AccessPath> visitCollectionElement(CollectionElementOperator col
 
         @Override
         public Optional<AccessPath> visitCall(CallOperator call, List<Optional<AccessPath>> childrenAccessPaths) {
-            if (!PruneSubfieldRule.SUPPORT_FUNCTIONS.contains(call.getFnName())) {
+            if (!PruneSubfieldRule.PRUNE_FUNCTIONS.contains(call.getFnName())) {
                 return Optional.empty();
             }
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/SubfieldExpressionCollector.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/SubfieldExpressionCollector.java
index 01753be2a395b9..9de1a12bb175ca 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/SubfieldExpressionCollector.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/rule/tree/prunesubfield/SubfieldExpressionCollector.java
@@ -15,6 +15,7 @@
 package com.starrocks.sql.optimizer.rule.tree.prunesubfield;
 
 import com.google.common.collect.Lists;
+import com.google.common.collect.Sets;
 import com.starrocks.catalog.Type;
 import com.starrocks.sql.optimizer.operator.scalar.CallOperator;
 import com.starrocks.sql.optimizer.operator.scalar.CollectionElementOperator;
@@ -24,13 +25,14 @@
 import com.starrocks.sql.optimizer.operator.scalar.SubfieldOperator;
 
 import java.util.List;
+import java.util.Set;
 
 /*
  * collect all complex expressions, such as: MAP_KEYS, MAP_VALUES, map['key'], struct.a.b.c ...
  */
 public class SubfieldExpressionCollector extends ScalarOperatorVisitor<Void, Void> {
     private final List<ScalarOperator> complexExpressions = Lists.newArrayList();
-
+    private Set<String> checkFunctions;
     private final boolean enableJsonCollect;
 
     public List<ScalarOperator> getComplexExpressions() {
@@ -43,6 +45,19 @@ public SubfieldExpressionCollector() {
 
     public SubfieldExpressionCollector(boolean enableJsonCollect) {
         this.enableJsonCollect = enableJsonCollect;
+        this.checkFunctions = Sets.newHashSet(PruneSubfieldRule.PRUNE_FUNCTIONS);
+    }
+
+    public static SubfieldExpressionCollector buildPruneCollector() {
+        SubfieldExpressionCollector collector = new SubfieldExpressionCollector();
+        collector.checkFunctions = Sets.newHashSet(PruneSubfieldRule.PRUNE_FUNCTIONS);
+        return collector;
+    }
+
+    public static SubfieldExpressionCollector buildPushdownCollector() {
+        SubfieldExpressionCollector collector = new SubfieldExpressionCollector();
+        collector.checkFunctions = Sets.newHashSet(PruneSubfieldRule.PUSHDOWN_FUNCTIONS);
+        return collector;
     }
 
     @Override
@@ -85,7 +100,7 @@ public Void visitCall(CallOperator call, Void context) {
             return null;
         }
 
-        if (!PruneSubfieldRule.SUPPORT_FUNCTIONS.contains(call.getFnName())) {
+        if (!checkFunctions.contains(call.getFnName())) {
             return visit(call, context);
         }
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/CacheDictManager.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/CacheDictManager.java
index b1105eb59988f9..8331dca6bbab93 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/CacheDictManager.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/CacheDictManager.java
@@ -164,8 +164,8 @@ public boolean hasGlobalDict(long tableId, ColumnId columnName, long versionTime
 
         Set<Long> dbIds = ConnectContext.get().getCurrentSqlDbIds();
         for (Long id : dbIds) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(id);
-            if (db != null && db.getTable(tableId) != null) {
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(id);
+            if (db != null && GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId) != null) {
                 columnIdentifier.setDbId(db.getId());
                 break;
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/CachedStatisticStorage.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/CachedStatisticStorage.java
index 445ac735351660..796581a8b4ce9c 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/CachedStatisticStorage.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/CachedStatisticStorage.java
@@ -52,7 +52,7 @@ public class CachedStatisticStorage implements StatisticStorage {
     private final Executor statsCacheRefresherExecutor = Executors.newFixedThreadPool(Config.statistic_cache_thread_pool_size,
             new ThreadFactoryBuilder().setDaemon(true).setNameFormat("stats-cache-refresher-%d").build());
 
-    AsyncLoadingCache<TableStatsCacheKey, Optional<TableStatistic>> tableStatsCache = Caffeine.newBuilder()
+    AsyncLoadingCache<TableStatsCacheKey, Optional<Long>> tableStatsCache = Caffeine.newBuilder()
             .expireAfterWrite(Config.statistic_update_interval_sec * 2, TimeUnit.SECONDS)
             .refreshAfterWrite(Config.statistic_update_interval_sec, TimeUnit.SECONDS)
             .maximumSize(Config.statistic_cache_columns)
@@ -88,22 +88,21 @@ public class CachedStatisticStorage implements StatisticStorage {
             .buildAsync(new ConnectorHistogramColumnStatsCacheLoader());
 
     @Override
-    public Map<Long, TableStatistic> getTableStatistics(Long tableId, Collection<Partition> partitions) {
+    public Map<Long, Optional<Long>> getTableStatistics(Long tableId, Collection<Partition> partitions) {
         // get Statistics Table column info, just return default column statistics
         if (StatisticUtils.statisticTableBlackListCheck(tableId)) {
-            return partitions.stream().collect(Collectors.toMap(Partition::getId, p -> TableStatistic.unknown()));
+            return partitions.stream().collect(Collectors.toMap(Partition::getId, p -> Optional.empty()));
         }
 
         List<TableStatsCacheKey> keys = partitions.stream().map(p -> new TableStatsCacheKey(tableId, p.getId()))
                 .collect(Collectors.toList());
 
         try {
-            CompletableFuture<Map<TableStatsCacheKey, Optional<TableStatistic>>> result = tableStatsCache.getAll(keys);
+            CompletableFuture<Map<TableStatsCacheKey, Optional<Long>>> result = tableStatsCache.getAll(keys);
             if (result.isDone()) {
-                Map<TableStatsCacheKey, Optional<TableStatistic>> data = result.get();
-                return keys.stream().collect(Collectors.toMap(
-                        TableStatsCacheKey::getPartitionId,
-                        k -> data.getOrDefault(k, Optional.empty()).orElse(TableStatistic.unknown())));
+                Map<TableStatsCacheKey, Optional<Long>> data = result.get();
+                return keys.stream().collect(Collectors.toMap(TableStatsCacheKey::getPartitionId,
+                        k -> data.getOrDefault(k, Optional.empty())));
             }
         } catch (InterruptedException e) {
             LOG.warn("Failed to execute tableStatsCache.getAll", e);
@@ -111,7 +110,7 @@ public Map<Long, TableStatistic> getTableStatistics(Long tableId, Collection<Par
         } catch (Exception e) {
             LOG.warn("Faied to execute tableStatsCache.getAll", e);
         }
-        return partitions.stream().collect(Collectors.toMap(Partition::getId, p -> TableStatistic.unknown()));
+        return partitions.stream().collect(Collectors.toMap(Partition::getId, p -> Optional.empty()));
     }
 
     @Override
@@ -122,7 +121,7 @@ public void refreshTableStatistic(Table table) {
         }
 
         try {
-            CompletableFuture<Map<TableStatsCacheKey, Optional<TableStatistic>>> completableFuture
+            CompletableFuture<Map<TableStatsCacheKey, Optional<Long>>> completableFuture
                     = tableStatsCache.getAll(statsCacheKeyList);
             if (completableFuture.isDone()) {
                 completableFuture.get();
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/ColumnBasicStatsCacheLoader.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/ColumnBasicStatsCacheLoader.java
index 5d4506e88478d3..fe49a46a9eb28e 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/ColumnBasicStatsCacheLoader.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/ColumnBasicStatsCacheLoader.java
@@ -130,9 +130,9 @@ private List<TStatisticData> queryStatisticsData(ConnectContext context, long ta
     }
 
     private ColumnStatistic convert2ColumnStatistics(TStatisticData statisticData) throws AnalysisException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(statisticData.dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(statisticData.dbId);
         MetaUtils.checkDbNullAndReport(db, String.valueOf(statisticData.dbId));
-        Table table = db.getTable(statisticData.tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), statisticData.tableId);
         if (!(table instanceof OlapTable)) {
             ErrorReport.reportAnalysisException(ErrorCode.ERR_BAD_TABLE_ERROR, statisticData.tableId);
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/ColumnHistogramStatsCacheLoader.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/ColumnHistogramStatsCacheLoader.java
index d95fdeb3245d58..c2921e0880a6e1 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/ColumnHistogramStatsCacheLoader.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/ColumnHistogramStatsCacheLoader.java
@@ -118,9 +118,9 @@ public List<TStatisticData> queryHistogramStatistics(ConnectContext context, lon
     }
 
     private Histogram convert2Histogram(TStatisticData statisticData) throws AnalysisException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(statisticData.dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(statisticData.dbId);
         MetaUtils.checkDbNullAndReport(db, String.valueOf(statisticData.dbId));
-        Table table = db.getTable(statisticData.tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), statisticData.tableId);
         if (!(table instanceof OlapTable)) {
             ErrorReport.reportAnalysisException(ErrorCode.ERR_BAD_TABLE_ERROR, statisticData.tableId);
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/StatisticStorage.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/StatisticStorage.java
index 191c1c50c782ab..d1ca18cfe8c2d0 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/StatisticStorage.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/StatisticStorage.java
@@ -23,12 +23,13 @@
 import java.util.Collection;
 import java.util.List;
 import java.util.Map;
+import java.util.Optional;
 import java.util.stream.Collectors;
 
 public interface StatisticStorage {
-    // partitionId: TableStatistic
-    default Map<Long, TableStatistic> getTableStatistics(Long tableId, Collection<Partition> partitions) {
-        return partitions.stream().collect(Collectors.toMap(Partition::getId, p -> TableStatistic.unknown()));
+    // partitionId: RowCount
+    default Map<Long, Optional<Long>> getTableStatistics(Long tableId, Collection<Partition> partitions) {
+        return partitions.stream().collect(Collectors.toMap(Partition::getId, p -> Optional.empty()));
     }
 
     default void refreshTableStatistic(Table table) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/StatisticsCalcUtils.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/StatisticsCalcUtils.java
index 4fce06eb7cb201..4d6d499db1d5b7 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/StatisticsCalcUtils.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/StatisticsCalcUtils.java
@@ -34,6 +34,7 @@
 import java.util.Collection;
 import java.util.List;
 import java.util.Map;
+import java.util.Optional;
 import java.util.stream.Collectors;
 
 public class StatisticsCalcUtils {
@@ -121,20 +122,20 @@ public static long getTableRowCount(Table table, Operator node, OptimizerContext
                 // For example, a large amount of data LOAD may cause the number of rows to change greatly.
                 // This leads to very inaccurate row counts.
                 long deltaRows = deltaRows(table, basicStatsMeta.getUpdateRows());
-                Map<Long, TableStatistic> tableStatisticMap = GlobalStateMgr.getCurrentState().getStatisticStorage()
+                Map<Long, Optional<Long>> tableStatisticMap = GlobalStateMgr.getCurrentState().getStatisticStorage()
                         .getTableStatistics(table.getId(), selectedPartitions);
                 for (Partition partition : selectedPartitions) {
                     long partitionRowCount;
-                    TableStatistic tableStatistic =
-                            tableStatisticMap.getOrDefault(partition.getId(), TableStatistic.unknown());
+                    Optional<Long> tableStatistic =
+                            tableStatisticMap.getOrDefault(partition.getId(), Optional.empty());
                     LocalDateTime updateDatetime = StatisticUtils.getPartitionLastUpdateTime(partition);
-                    if (tableStatistic.equals(TableStatistic.unknown())) {
+                    if (tableStatistic.isEmpty()) {
                         partitionRowCount = partition.getRowCount();
                         if (updateDatetime.isAfter(lastWorkTimestamp)) {
                             partitionRowCount += deltaRows;
                         }
                     } else {
-                        partitionRowCount = tableStatistic.getRowCount();
+                        partitionRowCount = tableStatistic.get();
                         if (updateDatetime.isAfter(basicStatsMeta.getUpdateTime())) {
                             partitionRowCount += deltaRows;
                         }
@@ -184,17 +185,13 @@ private static void updateQueryDumpInfo(OptimizerContext optimizerContext, Table
 
     private static long deltaRows(Table table, long totalRowCount) {
         long tblRowCount = 0L;
-        Map<Long, TableStatistic> tableStatisticMap = GlobalStateMgr.getCurrentState().getStatisticStorage()
+        Map<Long, Optional<Long>> tableStatisticMap = GlobalStateMgr.getCurrentState().getStatisticStorage()
                 .getTableStatistics(table.getId(), table.getPartitions());
 
         for (Partition partition : table.getPartitions()) {
             long partitionRowCount;
-            TableStatistic statistic = tableStatisticMap.getOrDefault(partition.getId(), TableStatistic.unknown());
-            if (statistic.equals(TableStatistic.unknown())) {
-                partitionRowCount = partition.getRowCount();
-            } else {
-                partitionRowCount = statistic.getRowCount();
-            }
+            Optional<Long> statistic = tableStatisticMap.getOrDefault(partition.getId(), Optional.empty());
+            partitionRowCount = statistic.orElseGet(partition::getRowCount);
             tblRowCount += partitionRowCount;
         }
         if (tblRowCount < totalRowCount) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/StatisticsCalculator.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/StatisticsCalculator.java
index 441db23f1ea8e8..583d85148f4797 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/StatisticsCalculator.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/StatisticsCalculator.java
@@ -719,18 +719,15 @@ private void adjustPartitionColsStatistic(Collection<Long> selectedPartitionId,
         }
 
         Map<String, ColumnRefOperator> colNameMap = Maps.newHashMap();
-        colRefToColumnMetaMap.entrySet().stream()
-                .forEach(e -> colNameMap.put(e.getValue().getName(), e.getKey()));
-        List<ColumnRefOperator> partitionCols = Lists.newArrayList();
-        for (String partitionColName : olapTable.getPartitionColumnNames()) {
-            if (!colNameMap.containsKey(partitionColName)) {
-                return;
-            }
-            partitionCols.add(colNameMap.get(partitionColName));
-        }
+        colRefToColumnMetaMap.entrySet().stream().forEach(e -> colNameMap.put(e.getValue().getName(), e.getKey()));
+        // It might contain null value, if some partition columns are not referenced in the scan
+        List<ColumnRefOperator> partitionCols =
+                olapTable.getPartitionColumnNames().stream()
+                        .map(colNameMap::get)
+                        .collect(Collectors.toList());
         PartitionInfo partitionInfo = olapTable.getPartitionInfo();
         if (partitionInfo instanceof RangePartitionInfo) {
-            if (partitionCols.size() != 1) {
+            if (partitionCols.size() != 1 || partitionCols.stream().anyMatch(Objects::isNull)) {
                 return;
             }
             if (optimizerContext.getDumpInfo() != null) {
@@ -778,15 +775,20 @@ private void adjustPartitionColsStatistic(Collection<Long> selectedPartitionId,
         } else if (partitionInfo instanceof ListPartitionInfo) {
             ListPartitionInfo listPartitionInfo = (ListPartitionInfo) partitionInfo;
             for (int i = 0; i < partitionCols.size(); i++) {
+                ColumnRefOperator columnRef = partitionCols.get(i);
+                // For multi-column list partition, pruning on any column should adjust the statistics
+                if (columnRef == null) {
+                    continue;
+                }
                 if (optimizerContext.getDumpInfo() != null) {
                     optimizerContext.getDumpInfo().addTableStatistics(olapTable,
                             partitionCols.get(i).getName(),
                             builder.getColumnStatistics(partitionCols.get(i)));
                 }
                 long ndv = extractDistinctPartitionValues(listPartitionInfo, selectedPartitionId, i);
-                ColumnStatistic columnStatistic = ColumnStatistic.buildFrom(builder.getColumnStatistics(partitionCols.get(i)))
+                ColumnStatistic columnStatistic = ColumnStatistic.buildFrom(builder.getColumnStatistics(columnRef))
                         .setDistinctValuesCount(ndv).build();
-                builder.addColumnStatistic(partitionCols.get(i), columnStatistic);
+                builder.addColumnStatistic(columnRef, columnStatistic);
             }
         }
     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/TableStatistic.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/TableStatistic.java
deleted file mode 100644
index 5fb412c1123ac3..00000000000000
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/TableStatistic.java
+++ /dev/null
@@ -1,56 +0,0 @@
-// Copyright 2021-present StarRocks, Inc. All rights reserved.
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     https://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-package com.starrocks.sql.optimizer.statistics;
-
-import java.util.Objects;
-
-public class TableStatistic {
-    private final Long tableId;
-    private final Long partitionId;
-    private final Long rowCount;
-    private static final TableStatistic UNKNOWN = new TableStatistic(-1L, -1L, 0L);
-
-    public TableStatistic(Long tableId, Long partitionId, Long rowCount) {
-        this.tableId = tableId;
-        this.partitionId = partitionId;
-        this.rowCount = rowCount;
-    }
-
-    public Long getRowCount() {
-        return rowCount;
-    }
-
-    public static TableStatistic unknown() {
-        return UNKNOWN;
-    }
-
-    @Override
-    public boolean equals(Object o) {
-        if (this == o) {
-            return true;
-        }
-        if (o == null || getClass() != o.getClass()) {
-            return false;
-        }
-        TableStatistic that = (TableStatistic) o;
-        return Objects.equals(tableId, that.tableId)
-                && Objects.equals(partitionId, that.partitionId)
-                && Objects.equals(rowCount, that.rowCount);
-    }
-
-    @Override
-    public int hashCode() {
-        return Objects.hash(tableId, partitionId, rowCount);
-    }
-}
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/TableStatsCacheLoader.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/TableStatsCacheLoader.java
index fcd11f2e8365ab..9f3e402b08522e 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/TableStatsCacheLoader.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/statistics/TableStatsCacheLoader.java
@@ -15,6 +15,8 @@
 package com.starrocks.sql.optimizer.statistics;
 
 import com.github.benmanes.caffeine.cache.AsyncCacheLoader;
+import com.google.api.client.util.Lists;
+import com.starrocks.common.Config;
 import com.starrocks.qe.ConnectContext;
 import com.starrocks.statistic.StatisticExecutor;
 import com.starrocks.statistic.StatisticUtils;
@@ -29,22 +31,22 @@
 import java.util.concurrent.CompletionException;
 import java.util.concurrent.Executor;
 
-public class TableStatsCacheLoader implements AsyncCacheLoader<TableStatsCacheKey, Optional<TableStatistic>> {
+public class TableStatsCacheLoader implements AsyncCacheLoader<TableStatsCacheKey, Optional<Long>> {
     private final StatisticExecutor statisticExecutor = new StatisticExecutor();
 
     @Override
-    public @NonNull CompletableFuture<Optional<TableStatistic>> asyncLoad(@NonNull TableStatsCacheKey cacheKey, @
+    public @NonNull CompletableFuture<Optional<Long>> asyncLoad(@NonNull TableStatsCacheKey cacheKey, @
             NonNull Executor executor) {
         return CompletableFuture.supplyAsync(() -> {
             try {
                 ConnectContext connectContext = StatisticUtils.buildConnectContext();
                 connectContext.setThreadLocalInfo();
-                List<TStatisticData> statisticData = queryStatisticsData(connectContext, cacheKey.tableId, cacheKey.partitionId);
-                if (statisticData.size() == 0) {
-                    return Optional.of(new TableStatistic(cacheKey.getTableId(), cacheKey.getPartitionId(), 0L));
+                List<TStatisticData> statisticData =
+                        statisticExecutor.queryTableStats(connectContext, cacheKey.tableId, cacheKey.partitionId);
+                if (statisticData.isEmpty()) {
+                    return Optional.empty();
                 } else {
-                    return Optional.of(new TableStatistic(cacheKey.getTableId(), cacheKey.getPartitionId(),
-                            statisticData.get(0).rowCount));
+                    return Optional.of(statisticData.get(0).rowCount);
                 }
             } catch (RuntimeException e) {
                 throw e;
@@ -57,31 +59,40 @@ public class TableStatsCacheLoader implements AsyncCacheLoader<TableStatsCacheKe
     }
 
     @Override
-    public @NonNull CompletableFuture<Map<@NonNull TableStatsCacheKey, @NonNull Optional<TableStatistic>>> asyncLoadAll(
+    public @NonNull CompletableFuture<Map<@NonNull TableStatsCacheKey, @NonNull Optional<Long>>> asyncLoadAll(
             @NonNull Iterable<? extends @NonNull TableStatsCacheKey> cacheKey,
             @NonNull Executor executor) {
         return CompletableFuture.supplyAsync(() -> {
             try {
-                TableStatsCacheKey tableStatsCacheKey = cacheKey.iterator().next();
-                long tableId = tableStatsCacheKey.getTableId();
-
                 ConnectContext connectContext = StatisticUtils.buildConnectContext();
                 connectContext.setThreadLocalInfo();
-                List<TStatisticData> statisticData = queryStatisticsData(connectContext, tableStatsCacheKey.getTableId());
 
-                Map<TableStatsCacheKey, Optional<TableStatistic>> result = new HashMap<>();
-                for (TStatisticData tStatisticData : statisticData) {
-                    result.put(new TableStatsCacheKey(tableId, tStatisticData.partitionId),
-                            Optional.of(new TableStatistic(tableId, tStatisticData.partitionId, tStatisticData.rowCount)));
+                Map<TableStatsCacheKey, Optional<Long>> result = new HashMap<>();
+                List<Long> pids = Lists.newArrayList();
+                long tableId = -1;
+                for (TableStatsCacheKey statsCacheKey : cacheKey) {
+                    pids.add(statsCacheKey.getPartitionId());
+                    tableId = statsCacheKey.getTableId();
+                    if (pids.size() > Config.expr_children_limit / 2) {
+                        List<TStatisticData> statisticData =
+                                statisticExecutor.queryTableStats(connectContext, statsCacheKey.getTableId(), pids);
+
+                        statisticData.forEach(tStatisticData -> result.put(
+                                new TableStatsCacheKey(statsCacheKey.getTableId(), tStatisticData.partitionId),
+                                Optional.of(tStatisticData.rowCount)));
+                        pids.clear();
+                    }
+                }
+                List<TStatisticData> statisticData = statisticExecutor.queryTableStats(connectContext, tableId, pids);
+                for (TStatisticData data : statisticData) {
+                    result.put(new TableStatsCacheKey(tableId, data.partitionId), Optional.of(data.rowCount));
                 }
                 for (TableStatsCacheKey key : cacheKey) {
                     if (!result.containsKey(key)) {
                         result.put(key, Optional.empty());
                     }
                 }
-
                 return result;
-
             } catch (RuntimeException e) {
                 throw e;
             } catch (Exception e) {
@@ -91,12 +102,4 @@ public class TableStatsCacheLoader implements AsyncCacheLoader<TableStatsCacheKe
             }
         }, executor);
     }
-
-    private List<TStatisticData> queryStatisticsData(ConnectContext context, long tableId) {
-        return statisticExecutor.queryTableStats(context, tableId);
-    }
-
-    private List<TStatisticData> queryStatisticsData(ConnectContext context, long tableId, long partitionId) {
-        return statisticExecutor.queryTableStats(context, tableId, partitionId);
-    }
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/ExpressionMapping.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/ExpressionMapping.java
index 5d02b45545a24e..b67c0bb470be36 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/ExpressionMapping.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/ExpressionMapping.java
@@ -23,6 +23,7 @@
 import com.starrocks.sql.common.ErrorType;
 import com.starrocks.sql.common.StarRocksPlannerException;
 import com.starrocks.sql.optimizer.operator.scalar.ColumnRefOperator;
+import com.starrocks.sql.optimizer.operator.scalar.ScalarOperator;
 
 import java.util.ArrayList;
 import java.util.Arrays;
@@ -50,13 +51,28 @@ public class ExpressionMapping {
     private ColumnRefOperator[] fieldMappings;
     private RelationId outerScopeRelationId;
 
+    //  record columnRefOp which is generated by const expr in project node
+    //  if this columnRefOp is referenced by upper node, we should replace it with const expr in upper node
+    private Map<ColumnRefOperator, ScalarOperator> columnRefToConstOperators = new HashMap<>();
+
     public ExpressionMapping(Scope scope, List<ColumnRefOperator> fieldMappings) {
         this.scope = scope;
         this.fieldMappings = new ColumnRefOperator[fieldMappings.size()];
         fieldMappings.toArray(this.fieldMappings);
+        this.columnRefToConstOperators = new HashMap<>();
+    }
+
+    public ExpressionMapping(Scope scope, List<ColumnRefOperator> fieldMappings,
+                             Map<ColumnRefOperator, ScalarOperator> columnRefToConstOperators) {
+        this.scope = scope;
+        this.fieldMappings = new ColumnRefOperator[fieldMappings.size()];
+        fieldMappings.toArray(this.fieldMappings);
+        this.columnRefToConstOperators =
+                columnRefToConstOperators == null ? new HashMap<>() : columnRefToConstOperators;
     }
 
-    public ExpressionMapping(Scope scope, List<ColumnRefOperator> fieldMappings, ExpressionMapping outer) {
+    public ExpressionMapping(Scope scope, List<ColumnRefOperator> fieldMappings, ExpressionMapping outer,
+                             Map<ColumnRefOperator, ScalarOperator> columnRefToConstOperators) {
         this.scope = scope;
         List<ColumnRefOperator> fieldsList = new ArrayList<>(fieldMappings);
         if (outer != null) {
@@ -69,6 +85,9 @@ public ExpressionMapping(Scope scope, List<ColumnRefOperator> fieldMappings, Exp
         }
         this.fieldMappings = new ColumnRefOperator[fieldsList.size()];
         fieldsList.toArray(this.fieldMappings);
+
+        this.columnRefToConstOperators =
+                columnRefToConstOperators == null ? new HashMap<>() : columnRefToConstOperators;
     }
 
     public ExpressionMapping(Scope scope) {
@@ -128,6 +147,17 @@ public void put(Expr expression, ColumnRefOperator columnRefOperator) {
         expressionToColumns.put(expression, columnRefOperator);
     }
 
+    public void putConstOperator(ColumnRefOperator columnRefOperator, ScalarOperator constOperator) {
+        columnRefToConstOperators.put(columnRefOperator, constOperator);
+    }
+
+    public ScalarOperator getConstOperator(ColumnRefOperator columnRefOperator) {
+        if (columnRefToConstOperators == null) {
+            return null;
+        }
+        return columnRefToConstOperators.get(columnRefOperator);
+    }
+
     public void putWithSymbol(Expr expression, Expr resolveExpr, ColumnRefOperator columnRefOperator) {
         if (resolveExpr instanceof SlotRef) {
             if (expression instanceof SlotRef
@@ -164,4 +194,12 @@ public Map<Expr, ColumnRefOperator> getExpressionToColumns() {
     public void addExpressionToColumns(Map<Expr, ColumnRefOperator> expressionToColumns) {
         this.expressionToColumns.putAll(expressionToColumns);
     }
+
+    public Map<ColumnRefOperator, ScalarOperator> getColumnRefToConstOperators() {
+        return columnRefToConstOperators;
+    }
+
+    public void addColumnRefToConstOperators(Map<ColumnRefOperator, ScalarOperator> columnRefToConstOperators) {
+        this.columnRefToConstOperators.putAll(columnRefToConstOperators);
+    }
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/OptExprBuilder.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/OptExprBuilder.java
index d17df1ea14bb3c..59fe20b66b8cc8 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/OptExprBuilder.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/OptExprBuilder.java
@@ -18,9 +18,11 @@
 import com.starrocks.sql.optimizer.OptExpression;
 import com.starrocks.sql.optimizer.operator.Operator;
 import com.starrocks.sql.optimizer.operator.scalar.ColumnRefOperator;
+import com.starrocks.sql.optimizer.operator.scalar.ScalarOperator;
 
 import java.util.Collections;
 import java.util.List;
+import java.util.Map;
 import java.util.stream.Collectors;
 
 /**
@@ -49,6 +51,13 @@ public ExpressionMapping getExpressionMapping() {
         return expressionMapping;
     }
 
+    public Map<ColumnRefOperator, ScalarOperator> getColumnRefToConstOperators() {
+        if (expressionMapping == null) {
+            return null;
+        }
+        return expressionMapping.getColumnRefToConstOperators();
+    }
+
     public void setExpressionMapping(ExpressionMapping expressionMapping) {
         this.expressionMapping = expressionMapping;
     }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/QueryTransformer.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/QueryTransformer.java
index ff04e79b86fbe7..b24d8664047ef0 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/QueryTransformer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/QueryTransformer.java
@@ -26,6 +26,7 @@
 import com.starrocks.analysis.LimitElement;
 import com.starrocks.analysis.OrderByElement;
 import com.starrocks.analysis.SlotRef;
+import com.starrocks.analysis.TableName;
 import com.starrocks.catalog.Type;
 import com.starrocks.common.Pair;
 import com.starrocks.common.TreeNode;
@@ -83,7 +84,8 @@ public QueryTransformer(ColumnRefFactory columnRefFactory, ConnectContext sessio
 
     public LogicalPlan plan(SelectRelation queryBlock, ExpressionMapping outer) {
         OptExprBuilder builder = planFrom(queryBlock.getRelation(), cteContext);
-        builder.setExpressionMapping(new ExpressionMapping(builder.getScope(), builder.getFieldMappings(), outer));
+        builder.setExpressionMapping(new ExpressionMapping(builder.getScope(), builder.getFieldMappings(), outer,
+                builder.getColumnRefToConstOperators()));
 
         Map<Expr, SlotRef> generatedExprToColumnRef = queryBlock.getGeneratedExprToColumnRef();
         ExpressionMapping expressionMapping = builder.getExpressionMapping();
@@ -114,10 +116,10 @@ public LogicalPlan plan(SelectRelation queryBlock, ExpressionMapping outer) {
                         Iterables.concat(queryBlock.getOutputExpression(),
                                 queryBlock.getOrderSourceExpressions(),
                                 queryBlock.getOrderByAnalytic()),
-                        queryBlock.getOutputExprInOrderByScope(),
+                        queryBlock,
                         outputNames,
                         builder.getFieldMappings(),
-                        queryBlock.getOrderScope(), true);
+                        true);
 
             } else {
                 // requires both output and source fields to be visible if there is no aggregation or distinct
@@ -125,10 +127,10 @@ public LogicalPlan plan(SelectRelation queryBlock, ExpressionMapping outer) {
                 // in the outputExpression.
                 builder = projectForOrder(builder,
                         Iterables.concat(queryBlock.getOutputExpression(), queryBlock.getOrderByAnalytic()),
-                        queryBlock.getOutputExprInOrderByScope(),
+                        queryBlock,
                         queryBlock.getColumnOutputNames(),
                         builder.getFieldMappings(),
-                        queryBlock.getOrderScope(), queryBlock.isDistinct());
+                        queryBlock.isDistinct());
             }
         }
 
@@ -169,10 +171,12 @@ columnRefFactory, session, new ExpressionMapping(new Scope(RelationId.anonymous(
 
     private OptExprBuilder projectForOrder(OptExprBuilder subOpt,
                                            Iterable<Expr> outputExpression,
-                                           List<Integer> outputExprInOrderByScope,
+                                           SelectRelation queryBlock,
                                            List<String> outputNames,
-                                           List<ColumnRefOperator> sourceExpression, Scope scope,
+                                           List<ColumnRefOperator> sourceExpression,
                                            boolean withAggregation) {
+        List<Integer> outputExprInOrderByScope = queryBlock.getOutputExprInOrderByScope();
+        Scope scope = queryBlock.getOrderScope();
         ExpressionMapping outputTranslations = new ExpressionMapping(scope);
         Map<ColumnRefOperator, ScalarOperator> projections = Maps.newHashMap();
 
@@ -190,10 +194,31 @@ private OptExprBuilder projectForOrder(OptExprBuilder subOpt,
             projections.put(columnRefOperator, scalarOperator);
 
             if (outputExprInOrderByScope.contains(outputExprIdx)) {
-                outputTranslations.putWithSymbol(expression,
-                        new SlotRef(null, outputNames.get(outputExprIdx)), columnRefOperator);
+                outputTranslations.put(expression, columnRefOperator);
+                TableName resolveTableName = queryBlock.getResolveTableName();
+                if (expression instanceof SlotRef) {
+                    resolveTableName = queryBlock.getRelation().getResolveTableName();
+                }
+                SlotRef alias = new SlotRef(resolveTableName, outputNames.get(outputExprIdx));
+                // order by expr may reference the alias. We need put the alias into the fieldMappings or the
+                // expressionToColumns.
+                // if the alias not be used in the order by expr like:
+                // select v1 cc, v2 cc from tbl order by v3. We just add the slotRef(cc) to columnRefOperator in the
+                // expressionToColumns to ensure this projection can output v1 with alias cc, v2 with alias cc and v3.
+                // We don't need to ensure the uniqueness of the alias in the fieldMappings.
+                // if the alias used in the order by expr like:
+                // select v1 v3, v2 cc from (select abs(v1) v1, abs(v2) v2, v3 from t0) t1 order by t1.v3.
+                // order by expr t1.v3 referenced the v1 with alias v3, we need set the fieldMappings to ensure order by
+                // expr can be resolved.
+                if (scope.getRelationFields().resolveFields(alias).size() > 1) {
+                    outputTranslations.getExpressionToColumns()
+                            .put(new SlotRef(resolveTableName, outputNames.get(outputExprIdx)), columnRefOperator);
+                } else {
+                    outputTranslations.put(alias, columnRefOperator);
+                }
+
             } else {
-                outputTranslations.putWithSymbol(expression, expression, columnRefOperator);
+                outputTranslations.put(expression, columnRefOperator);
             }
             outputExprIdx++;
         }
@@ -220,6 +245,8 @@ private OptExprBuilder projectForOrder(OptExprBuilder subOpt,
         }
 
         outputTranslations.addExpressionToColumns(subOpt.getExpressionMapping().getExpressionToColumns());
+        outputTranslations.addColumnRefToConstOperators(subOpt.getColumnRefToConstOperators());
+
         LogicalProjectOperator projectOperator = new LogicalProjectOperator(projections);
         return new OptExprBuilder(projectOperator, Lists.newArrayList(subOpt), outputTranslations);
     }
@@ -229,7 +256,8 @@ private OptExprBuilder project(OptExprBuilder subOpt, Iterable<Expr> expressions
     }
 
     private OptExprBuilder project(OptExprBuilder subOpt, Iterable<Expr> expressions, long limit) {
-        ExpressionMapping outputTranslations = new ExpressionMapping(subOpt.getScope(), subOpt.getFieldMappings());
+        ExpressionMapping outputTranslations = new ExpressionMapping(subOpt.getScope(), subOpt.getFieldMappings(),
+                subOpt.getColumnRefToConstOperators());
 
         Map<ColumnRefOperator, ScalarOperator> projections = Maps.newHashMap();
         for (Expr expression : expressions) {
@@ -244,9 +272,14 @@ private OptExprBuilder project(OptExprBuilder subOpt, Iterable<Expr> expressions
             ColumnRefOperator columnRefOperator = getOrCreateColumnRefOperator(expression, scalarOperator, projections);
             projections.put(columnRefOperator, scalarOperator);
             outputTranslations.put(expression, columnRefOperator);
+            if (scalarOperator.isConstant()) {
+                outputTranslations.putConstOperator(columnRefOperator, scalarOperator);
+            }
         }
 
         outputTranslations.addExpressionToColumns(subOpt.getExpressionMapping().getExpressionToColumns());
+        outputTranslations.addColumnRefToConstOperators(subOpt.getColumnRefToConstOperators());
+
         LogicalProjectOperator projectOperator = new LogicalProjectOperator(projections, limit);
         return new OptExprBuilder(projectOperator, Lists.newArrayList(subOpt), outputTranslations);
     }
@@ -412,7 +445,8 @@ public OptExprBuilder aggregate(OptExprBuilder subOpt,
             subOpt = project(subOpt, inputs);
         }
         ExpressionMapping groupingTranslations =
-                new ExpressionMapping(subOpt.getScope(), subOpt.getFieldMappings());
+                new ExpressionMapping(subOpt.getScope(), subOpt.getFieldMappings(),
+                        subOpt.getColumnRefToConstOperators());
 
         List<ColumnRefOperator> groupByColumnRefs = new ArrayList<>();
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/RelationTransformer.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/RelationTransformer.java
index c3a4910617b3ee..b97b601733099c 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/RelationTransformer.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/RelationTransformer.java
@@ -143,6 +143,7 @@
 
 import java.util.ArrayList;
 import java.util.Collections;
+import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
 import java.util.Objects;
@@ -369,9 +370,13 @@ private LogicalPlan processSetOperation(SetOperationRelation setOperationRelatio
                 }
             }
         }
+        Map<ColumnRefOperator, ScalarOperator> constMap = new HashMap<>();
+
+        childPlan.stream().map(x -> x.getColumnRefToConstOperators()).filter(Objects::nonNull)
+                .forEach(constMap::putAll);
 
         Scope outputScope = setOperationRelation.getRelations().get(0).getScope();
-        ExpressionMapping expressionMapping = new ExpressionMapping(outputScope, outputColumns);
+        ExpressionMapping expressionMapping = new ExpressionMapping(outputScope, outputColumns, constMap);
 
         OptExprBuilder root;
         if (setOperationRelation instanceof UnionRelation) {
@@ -724,7 +729,8 @@ public LogicalPlan visitCTE(CTERelation node, ExpressionMapping context) {
             LogicalPlan childPlan = transform(node.getCteQueryStatement().getQueryRelation());
             OptExprBuilder builder = new OptExprBuilder(childPlan.getRoot().getOp(),
                     childPlan.getRootBuilder().getInputs(),
-                    new ExpressionMapping(node.getScope(), childPlan.getOutputColumn()));
+                    new ExpressionMapping(node.getScope(), childPlan.getOutputColumn(), childPlan.getRootBuilder()
+                            .getColumnRefToConstOperators()));
             return new LogicalPlan(builder, childPlan.getOutputColumn(), childPlan.getCorrelation());
         }
 
@@ -734,7 +740,8 @@ public LogicalPlan visitCTE(CTERelation node, ExpressionMapping context) {
         Map<ColumnRefOperator, ColumnRefOperator> cteOutputColumnRefMap = checkCtePlanOutput(cteId, childPlan, node);
         LogicalCTEConsumeOperator consume = new LogicalCTEConsumeOperator(cteId, cteOutputColumnRefMap);
         OptExprBuilder consumeBuilder = new OptExprBuilder(consume, Lists.newArrayList(childPlan.getRootBuilder()),
-                new ExpressionMapping(node.getScope(), childPlan.getOutputColumn()));
+                new ExpressionMapping(node.getScope(), childPlan.getOutputColumn(),
+                        childPlan.getRootBuilder().getColumnRefToConstOperators()));
 
         return new LogicalPlan(consumeBuilder, childPlan.getOutputColumn(), List.of());
     }
@@ -747,7 +754,8 @@ public LogicalPlan visitSubquery(SubqueryRelation node, ExpressionMapping contex
         OptExprBuilder builder = new OptExprBuilder(
                 logicalPlan.getRoot().getOp(),
                 logicalPlan.getRootBuilder().getInputs(),
-                new ExpressionMapping(node.getScope(), logicalPlan.getOutputColumn()));
+                new ExpressionMapping(node.getScope(), logicalPlan.getOutputColumn(),
+                        logicalPlan.getRootBuilder().getColumnRefToConstOperators()));
 
         builder = addOrderByLimit(builder, node);
 
@@ -770,7 +778,8 @@ public LogicalPlan visitView(ViewRelation node, ExpressionMapping context) {
             OptExprBuilder builder = new OptExprBuilder(
                     logicalPlan.getRoot().getOp(),
                     logicalPlan.getRootBuilder().getInputs(),
-                    new ExpressionMapping(node.getScope(), logicalPlan.getOutputColumn()));
+                    new ExpressionMapping(node.getScope(), logicalPlan.getOutputColumn(), logicalPlan.getRootBuilder()
+                            .getColumnRefToConstOperators()));
             if (enableViewBasedMvRewrite) {
                 LogicalViewScanOperator viewScanOperator = buildViewScan(logicalPlan, node, newOutputColumns);
                 builder.getRoot().getOp().setEquivalentOp(viewScanOperator);
@@ -856,10 +865,14 @@ public LogicalPlan visitJoin(JoinRelation node, ExpressionMapping context) {
             List<ColumnRefOperator> leftFieldMappings = leftPlan.getRootBuilder().getFieldMappings();
             List<ColumnRefOperator> rightFieldMappings = rightPlan.getRootBuilder().getFieldMappings();
 
+            // rightPlan won't genetate ColumnRefToConstOperators because there is no project
+            Map<ColumnRefOperator, ScalarOperator> leftConstMap =
+                    leftPlan.getRootBuilder().getColumnRefToConstOperators();
+
             ExpressionMapping expressionMapping = new ExpressionMapping(new Scope(RelationId.of(node),
                     node.getLeft().getRelationFields().joinWith(node.getRight().getRelationFields())),
                     Streams.concat(leftFieldMappings.stream(), rightFieldMappings.stream())
-                            .collect(Collectors.toList()));
+                            .collect(Collectors.toList()), leftConstMap);
 
             Operator root = LogicalApplyOperator.builder().setCorrelationColumnRefs(correlation)
                     .setNeedCheckMaxRows(false)
@@ -876,6 +889,13 @@ public LogicalPlan visitJoin(JoinRelation node, ExpressionMapping context) {
         OptExprBuilder leftOpt = leftPlan.getRootBuilder();
         OptExprBuilder rightOpt = rightPlan.getRootBuilder();
 
+        Map<ColumnRefOperator, ScalarOperator> leftConstMap =
+                leftOpt.getColumnRefToConstOperators() == null ? new HashMap<>() :
+                        leftOpt.getColumnRefToConstOperators();
+        Map<ColumnRefOperator, ScalarOperator> rightConstMap =
+                rightOpt.getColumnRefToConstOperators() == null ? new HashMap<>() :
+                        rightOpt.getColumnRefToConstOperators();
+
         // The scope needs to be rebuilt here, because the scope of Semi/Anti Join
         // only has a child field. Bug on predicate needs to see the two child field
         Scope joinScope = new Scope(RelationId.of(node),
@@ -884,7 +904,7 @@ public LogicalPlan visitJoin(JoinRelation node, ExpressionMapping context) {
         ExpressionMapping expressionMapping = new ExpressionMapping(joinScope, Streams.concat(
                         leftOpt.getFieldMappings().stream(),
                         rightOpt.getFieldMappings().stream())
-                .collect(Collectors.toList()));
+                .collect(Collectors.toList()), generateNewConstMap(leftConstMap, rightConstMap, node.getJoinOp()));
 
         ScalarOperator onPredicate = null;
         if (node.getOnPredicate() != null) {
@@ -915,15 +935,17 @@ public LogicalPlan visitJoin(JoinRelation node, ExpressionMapping context) {
         ExpressionMapping outputExpressionMapping;
         if (node.getJoinOp().isLeftSemiAntiJoin()) {
             outputExpressionMapping = new ExpressionMapping(node.getScope(),
-                    Lists.newArrayList(leftOpt.getFieldMappings()));
+                    Lists.newArrayList(leftOpt.getFieldMappings()), leftConstMap);
         } else if (node.getJoinOp().isRightSemiAntiJoin()) {
             outputExpressionMapping = new ExpressionMapping(node.getScope(),
-                    Lists.newArrayList(rightOpt.getFieldMappings()));
+                    Lists.newArrayList(rightOpt.getFieldMappings()), rightConstMap);
         } else {
-            outputExpressionMapping = new ExpressionMapping(node.getScope(), Streams.concat(
-                            leftOpt.getFieldMappings().stream(),
-                            rightOpt.getFieldMappings().stream())
-                    .collect(Collectors.toList()));
+            outputExpressionMapping = new ExpressionMapping(node.getScope(),
+                    Streams.concat(
+                                    leftOpt.getFieldMappings().stream(),
+                                    rightOpt.getFieldMappings().stream())
+                            .collect(Collectors.toList()),
+                    generateNewConstMap(leftConstMap, rightConstMap, node.getJoinOp()));
         }
 
         ScalarOperator skewColumn = null;
@@ -1245,4 +1267,26 @@ private static SelectRelation extractSubqueryRelation(List<Subquery> subqueries)
         }
         return (SelectRelation) subqueryStmt.getQueryRelation();
     }
+
+    private Map<ColumnRefOperator, ScalarOperator> generateNewConstMap(
+            Map<ColumnRefOperator, ScalarOperator> leftConstMap, Map<ColumnRefOperator, ScalarOperator> rightConstMap,
+            JoinOperator joinOperator) {
+        // outJoin may generate null values, so it may not safe to use const value
+        if (joinOperator.isLeftOuterJoin()) {
+            rightConstMap = new HashMap<>();
+        } else if (joinOperator.isRightJoin()) {
+            leftConstMap = new HashMap<>();
+        } else if (joinOperator.isFullOuterJoin()) {
+            leftConstMap = new HashMap<>();
+            rightConstMap = new HashMap<>();
+        }
+
+        return Streams.concat(
+                        leftConstMap.entrySet().stream(),
+                        rightConstMap.entrySet().stream())
+                .collect(Collectors.toMap(
+                        Map.Entry::getKey,
+                        Map.Entry::getValue,
+                        (existing, replacement) -> existing));
+    }
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/SqlToScalarOperatorTranslator.java b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/SqlToScalarOperatorTranslator.java
index 5d365cea04c3a6..fbd46aee8e5b55 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/SqlToScalarOperatorTranslator.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/optimizer/transformer/SqlToScalarOperatorTranslator.java
@@ -325,6 +325,15 @@ public ScalarOperator visitSlot(SlotRef node, Context context) {
                 correlation.add(columnRefOperator);
             }
 
+            ScalarOperator constOperator = expressionMapping.getConstOperator(columnRefOperator);
+            if (constOperator != null) {
+                // this columnRefOp is generated by project's const expr
+                // instead of using project's output columnRef, we replace it with const expr
+                // because project operator in BE will unpacking const column
+                // if using columnRefOp instead of const expr, BE will lose some opportunities to optimize const expr
+                return constOperator;
+            }
+
             // If origin type is struct type, means that node contains subfield access
             if (node.getTrueOriginType().isStructType()) {
                 Preconditions.checkArgument(node.getUsedStructFieldPos() != null, "StructType SlotRef must have" +
@@ -417,7 +426,7 @@ public ScalarOperator visitLambdaFunctionExpr(LambdaFunctionExpr node,
             }
             Scope scope = new Scope(args, expressionMapping.getScope());
             ExpressionMapping old = expressionMapping;
-            expressionMapping = new ExpressionMapping(scope, refs, expressionMapping);
+            expressionMapping = new ExpressionMapping(scope, refs, expressionMapping, null);
             ScalarOperator lambda = visit(node.getChild(0), context.clone(node));
             expressionMapping = old; // recover it
             return new LambdaFunctionOperator(refs, lambda, Type.FUNCTION);
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/parser/AstBuilder.java b/fe/fe-core/src/main/java/com/starrocks/sql/parser/AstBuilder.java
index 8f2801c1b2852f..0a7dd85ac5ef17 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/parser/AstBuilder.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/parser/AstBuilder.java
@@ -82,8 +82,10 @@
 import com.starrocks.analysis.VarBinaryLiteral;
 import com.starrocks.analysis.VariableExpr;
 import com.starrocks.authentication.UserProperty;
+import com.starrocks.catalog.AggregateFunction;
 import com.starrocks.catalog.AggregateType;
 import com.starrocks.catalog.ArrayType;
+import com.starrocks.catalog.Function;
 import com.starrocks.catalog.FunctionSet;
 import com.starrocks.catalog.KeysType;
 import com.starrocks.catalog.MapType;
@@ -93,6 +95,7 @@
 import com.starrocks.catalog.StructField;
 import com.starrocks.catalog.StructType;
 import com.starrocks.catalog.Type;
+import com.starrocks.catalog.combinator.AggStateDesc;
 import com.starrocks.common.AnalysisException;
 import com.starrocks.common.Config;
 import com.starrocks.common.CsvFormat;
@@ -105,10 +108,12 @@
 import com.starrocks.connector.BranchOptions;
 import com.starrocks.connector.TagOptions;
 import com.starrocks.mysql.MysqlPassword;
+import com.starrocks.qe.ConnectContext;
 import com.starrocks.qe.SqlModeHelper;
 import com.starrocks.scheduler.persist.TaskSchedule;
 import com.starrocks.sql.ShowTemporaryTableStmt;
 import com.starrocks.sql.analyzer.AnalyzerUtils;
+import com.starrocks.sql.analyzer.FunctionAnalyzer;
 import com.starrocks.sql.analyzer.RelationId;
 import com.starrocks.sql.analyzer.SemanticException;
 import com.starrocks.sql.ast.AddBackendBlackListStmt;
@@ -962,18 +967,53 @@ private List<ColumnDef> getColumnDefs(List<StarRocksParser.ColumnDescContext> co
     private ColumnDef getColumnDef(StarRocksParser.ColumnDescContext context) {
         Identifier colIdentifier = (Identifier) visit(context.identifier());
         String columnName = colIdentifier.getValue();
-        TypeDef typeDef = new TypeDef(getType(context.type()), createPos(context.type()));
+        Pair<Type, AggStateDesc> typeWithAggStateDesc = getAggStateDesc(context.aggDesc());
+
+        // get column's type
+        Type columnType = null;
+        if (context.type() == null) {
+            // This can only happen when aggStateDesc is not null.
+            if (typeWithAggStateDesc == null) {
+                throw new ParsingException(PARSER_ERROR_MSG.unsupportedType("Column's type is null and it's not agg " +
+                        "state column" + columnName), colIdentifier.getPos());
+            } else {
+                columnType = typeWithAggStateDesc.first;
+            }
+        } else {
+            columnType = getType(context.type());
+        }
+
+        // get column's agg state desc
+        AggStateDesc aggStateDesc = typeWithAggStateDesc == null ? null : typeWithAggStateDesc.second;
+        NodePosition pos = context.type() == null ? NodePosition.ZERO : createPos(context.type());
+        TypeDef typeDef = new TypeDef(columnType, pos);
         String charsetName = context.charsetName() != null ?
                 ((Identifier) visit(context.charsetName().identifier())).getValue() : null;
-        boolean isKey = context.KEY() != null;
-        AggregateType aggregateType =
-                context.aggDesc() != null ? AggregateType.valueOf(context.aggDesc().getText().toUpperCase()) : null;
+
+        // get column's aggregate type
+        AggregateType aggregateType = null;
+        if (typeWithAggStateDesc != null) {
+            aggregateType = AggregateType.AGG_STATE_UNION;
+        } else {
+            aggregateType = context.aggDesc() != null ?
+                    AggregateType.valueOf(context.aggDesc().getText().toUpperCase()) : null;
+        }
+
+        // get column's nullable
         Boolean isAllowNull = null;
-        if (context.NOT() != null && context.NULL() != null) {
-            isAllowNull = false;
-        } else if (context.NULL() != null) {
-            isAllowNull = true;
+        if (context.columnNullable() != null) {
+            if (context.columnNullable().NOT() != null) {
+                isAllowNull = false;
+            } else if (context.columnNullable().NULL() != null) {
+                isAllowNull = true;
+            }
+        }
+        // AGG_STATE_UNION can only be nullable for now, optimize it later.
+        if (aggregateType != null && aggregateType.equals(AggregateType.AGG_STATE_UNION) && isAllowNull != null && !isAllowNull) {
+            throw new ParsingException(PARSER_ERROR_MSG.foundNotNull("Agg state column " + columnName), colIdentifier.getPos());
         }
+
+        boolean isKey = context.KEY() != null;
         Boolean isAutoIncrement = null;
         if (context.AUTO_INCREMENT() != null) {
             isAutoIncrement = true;
@@ -1015,7 +1055,7 @@ private ColumnDef getColumnDef(StarRocksParser.ColumnDescContext context) {
         }
         String comment = context.comment() == null ? "" :
                 ((StringLiteral) visit(context.comment().string())).getStringValue();
-        return new ColumnDef(columnName, typeDef, charsetName, isKey, aggregateType, isAllowNull, defaultValueDef,
+        return new ColumnDef(columnName, typeDef, charsetName, isKey, aggregateType, aggStateDesc, isAllowNull, defaultValueDef,
                 isAutoIncrement, expr, comment, createPos(context));
     }
 
@@ -1817,7 +1857,8 @@ public ParseNode visitCreateMaterializedViewStatement(
             // process properties
             if (desc.properties() != null) {
                 if (MapUtils.isNotEmpty(properties)) {
-                    throw new ParsingException(PARSER_ERROR_MSG.duplicatedClause("PROPERTY"), clausePos);
+                    throw new ParsingException(PARSER_ERROR_MSG.duplicatedClause("PROPERTY", "building materialized view"),
+                            clausePos);
                 }
                 List<Property> propertyList = visit(desc.properties().property(), Property.class);
                 for (Property property : propertyList) {
@@ -1827,7 +1868,8 @@ public ParseNode visitCreateMaterializedViewStatement(
             // process refresh
             if (desc.refreshSchemeDesc() != null) {
                 if (refreshSchemeDesc != null) {
-                    throw new ParsingException(PARSER_ERROR_MSG.duplicatedClause("REFRESH"), clausePos);
+                    throw new ParsingException(PARSER_ERROR_MSG.duplicatedClause("REFRESH", "building materialized view"),
+                            clausePos);
                 }
                 refreshSchemeDesc = ((RefreshSchemeClause) visit(desc.refreshSchemeDesc()));
             }
@@ -1835,7 +1877,8 @@ public ParseNode visitCreateMaterializedViewStatement(
             // process partition by
             if (desc.primaryExpression() != null) {
                 if (expressionPartitionDesc != null) {
-                    throw new ParsingException(PARSER_ERROR_MSG.duplicatedClause("PARTITION"), clausePos);
+                    throw new ParsingException(PARSER_ERROR_MSG.duplicatedClause("PARTITION", "building materialized view"),
+                            clausePos);
                 }
                 Expr expr = (Expr) visit(desc.primaryExpression());
                 if (expr instanceof SlotRef) {
@@ -1853,7 +1896,8 @@ public ParseNode visitCreateMaterializedViewStatement(
             // process distribution
             if (desc.distributionDesc() != null) {
                 if (distributionDesc != null) {
-                    throw new ParsingException(PARSER_ERROR_MSG.duplicatedClause("DISTRIBUTION"), clausePos);
+                    throw new ParsingException(PARSER_ERROR_MSG.duplicatedClause("DISTRIBUTION", "building materialized view"),
+                            clausePos);
                 }
                 distributionDesc = (DistributionDesc) visit(desc.distributionDesc());
             }
@@ -2074,10 +2118,27 @@ public ParseNode visitInsertStatement(StarRocksParser.InsertStatementContext con
                 targetBranch = ((Identifier) visit(context.writeBranch())).getValue();
             }
 
-            InsertStmt stmt = new InsertStmt(targetTableName, partitionNames,
-                    context.label == null ? null : ((Identifier) visit(context.label)).getValue(),
-                    getColumnNames(context.columnAliases()), queryStatement, context.OVERWRITE() != null,
-                    createPos(context));
+            String label = null;
+            List<String> columnAliases = null;
+            for (StarRocksParser.InsertLabelOrColumnAliasesContext desc : ListUtils.emptyIfNull(
+                    context.insertLabelOrColumnAliases())) {
+                NodePosition clausePos = createPos(desc);
+                if (desc.label != null) {
+                    if (label != null) {
+                        throw new ParsingException(PARSER_ERROR_MSG.duplicatedClause("WITH LABEL", "insert"), clausePos);
+                    }
+                    label = ((Identifier) visit(desc.label)).getValue();
+                }
+                if (desc.columnAliases() != null) {
+                    if (columnAliases != null) {
+                        throw new ParsingException(PARSER_ERROR_MSG.duplicatedClause("COLUMN LIST", "insert"), clausePos);
+                    }
+                    columnAliases = getColumnNames(desc.columnAliases());
+                }
+            }
+
+            InsertStmt stmt = new InsertStmt(targetTableName, partitionNames, label, columnAliases, queryStatement,
+                    context.OVERWRITE() != null, getProperties(context.properties()), createPos(context));
             stmt.setHintNodes(hintMap.get(context));
             stmt.setTargetBranch(targetBranch);
             return stmt;
@@ -2677,10 +2738,10 @@ public ParseNode visitAlterResourceGroupStatement(StarRocksParser.AlterResourceG
     public ParseNode visitShowResourceGroupStatement(StarRocksParser.ShowResourceGroupStatementContext context) {
         NodePosition pos = createPos(context);
         if (context.GROUPS() != null) {
-            return new ShowResourceGroupStmt(null, context.ALL() != null, pos);
+            return new ShowResourceGroupStmt(null, context.ALL() != null, context.VERBOSE() != null, pos);
         } else {
             Identifier identifier = (Identifier) visit(context.identifier());
-            return new ShowResourceGroupStmt(identifier.getValue(), false, pos);
+            return new ShowResourceGroupStmt(identifier.getValue(), false, context.VERBOSE() != null, pos);
         }
     }
 
@@ -7642,6 +7703,70 @@ public Type getType(StarRocksParser.TypeContext context) {
         }
     }
 
+    /**
+     * Whether the input decimal is wildcard which is no precision or scale.
+     */
+    private boolean isWildcardDecimalType(StarRocksParser.TypeContext typeContext) {
+        if (typeContext.decimalType() == null) {
+            return false;
+        }
+        StarRocksParser.DecimalTypeContext context = typeContext.decimalType();
+        Integer precision = null;
+        Integer scale = null;
+        if (context.precision != null) {
+            precision = Integer.parseInt(context.precision.getText());
+            if (context.scale != null) {
+                scale = Integer.parseInt(context.scale.getText());
+            }
+        }
+        return precision == null && scale == null;
+    }
+
+    /**
+     * Create an agg state desc from ast context.
+     * @param context agg desc context from parser
+     * @return the deduced agg function's intermediate type and its associated agg state desc pair
+     */
+    public Pair<Type, AggStateDesc> getAggStateDesc(StarRocksParser.AggDescContext context) {
+        if (context == null || context.aggStateDesc() == null) {
+            return null;
+        }
+        StarRocksParser.AggStateDescContext aggStateDescContext = context.aggStateDesc();
+        Identifier aggFuncNameId = (Identifier) visit(aggStateDescContext.identifier());
+        String aggFuncName = aggFuncNameId.getValue();
+        List<StarRocksParser.TypeWithNullableContext> typeWithNullables = aggStateDescContext.typeWithNullable();
+        List<Type> argTypes = Lists.newArrayList();
+        for (StarRocksParser.TypeWithNullableContext typeWithNullableContext : typeWithNullables) {
+            Type argType = getType(typeWithNullableContext.type());
+            if (isWildcardDecimalType(typeWithNullableContext.type())) {
+                throw new ParsingException(String.format("AggStateType function %s with input %s has wildcard decimal",
+                        aggFuncName, argType), createPos(context));
+            }
+            argTypes.add(argType);
+        }
+
+        // distinct or order by are not supported yet in agg_state desc.
+        FunctionParams params = new FunctionParams(false, Lists.newArrayList());
+        Type[] argumentTypes = argTypes.toArray(Type[]::new);
+        Boolean[] isArgumentConstants = argTypes.stream().map(x -> new Boolean(false)).toArray(Boolean[]::new);
+        Function result = FunctionAnalyzer.getAnalyzedAggregateFunction(ConnectContext.get(), aggFuncName, params, argumentTypes,
+                isArgumentConstants, createPos(context));
+        if (result == null) {
+            throw new ParsingException(String.format("AggStateType function %s with input %s not found", aggFuncName,
+                    argTypes), createPos(context));
+        }
+        if (!(result instanceof AggregateFunction)) {
+            throw new ParsingException(String.format("AggStateType function %s with input %s found but not an aggregate " +
+                            "function", aggFuncName, argTypes), createPos(context));
+        }
+        AggregateFunction aggFunc = (AggregateFunction) result;
+        Type intermediateType = aggFunc.getIntermediateTypeOrReturnType();
+        Type finalType = AnalyzerUtils.transformTableColumnType(intermediateType, false);
+        AggStateDesc aggStateDesc = new AggStateDesc(aggFunc.functionName(), aggFunc.getReturnType(),
+                argTypes, true);
+        return Pair.create(finalType, aggStateDesc);
+    }
+
     private Type getBaseType(StarRocksParser.BaseTypeContext context) {
         int length = -1;
         if (context.typeParameter() != null) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/parser/StarRocks.g4 b/fe/fe-core/src/main/java/com/starrocks/sql/parser/StarRocks.g4
index a6bdd79cb9fd9a..8acb2ebaefdd6f 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/parser/StarRocks.g4
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/parser/StarRocks.g4
@@ -373,7 +373,7 @@ createTableStatement
 
 
 columnDesc
-    : identifier type charsetName? KEY? aggDesc? (NULL | NOT NULL)?
+    : identifier type? charsetName? KEY? aggDesc? columnNullable?
     (defaultDesc | AUTO_INCREMENT | generatedColumnDesc)?
     comment?
     ;
@@ -416,6 +416,19 @@ orderByDesc
     : ORDER BY identifierList
     ;
 
+columnNullable
+    : NULL
+    | NOT NULL
+    ;
+
+typeWithNullable
+    : type columnNullable?
+    ;
+
+aggStateDesc
+    : identifier '(' typeWithNullable (',' typeWithNullable)* ')'
+    ;
+
 aggDesc
     : SUM
     | MAX
@@ -425,6 +438,7 @@ aggDesc
     | BITMAP_UNION
     | PERCENTILE_UNION
     | REPLACE_IF_NOT_NULL
+    | aggStateDesc
     ;
 
 rollupDesc
@@ -1120,10 +1134,16 @@ partitionRenameClause
 
 insertStatement
     : explainDesc? INSERT (INTO | OVERWRITE) (qualifiedName writeBranch? partitionNames? | (FILES propertyList) | (BLACKHOLE '(' ')'))
-        (WITH LABEL label=identifier)? columnAliases?
+        insertLabelOrColumnAliases* properties?
         (queryStatement | (VALUES expressionsWithDefault (',' expressionsWithDefault)*))
     ;
 
+// for compatibility with the case 'LABEL before columnAliases'
+insertLabelOrColumnAliases
+    : WITH LABEL label=identifier
+    | columnAliases
+    ;
+
 updateStatement
     : explainDesc? withClause? UPDATE qualifiedName SET assignmentList fromClause (WHERE where=expression)?
     ;
@@ -1294,8 +1314,8 @@ alterResourceGroupStatement
     ;
 
 showResourceGroupStatement
-    : SHOW RESOURCE GROUP identifier
-    | SHOW RESOURCE GROUPS ALL?
+    : SHOW VERBOSE? RESOURCE GROUP identifier
+    | SHOW VERBOSE? RESOURCE GROUPS ALL?
     ;
 
 showResourceGroupUsageStatement
diff --git a/fe/fe-core/src/main/java/com/starrocks/sql/plan/PlanFragmentBuilder.java b/fe/fe-core/src/main/java/com/starrocks/sql/plan/PlanFragmentBuilder.java
index 7e80ce391d4d3e..126fda67754dfa 100644
--- a/fe/fe-core/src/main/java/com/starrocks/sql/plan/PlanFragmentBuilder.java
+++ b/fe/fe-core/src/main/java/com/starrocks/sql/plan/PlanFragmentBuilder.java
@@ -267,7 +267,7 @@ public static ExecPlan createPhysicalPlanForMV(ConnectContext connectContext,
         // Create a fake table sink here, replaced it after created the MV
         PartitionInfo partitionInfo = LocalMetastore.buildPartitionInfo(createStmt);
         long mvId = GlobalStateMgr.getCurrentState().getNextId();
-        long dbId = GlobalStateMgr.getCurrentState().getDb(createStmt.getTableName().getDb()).getId();
+        long dbId = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(createStmt.getTableName().getDb()).getId();
         MaterializedView view = GlobalStateMgr.getCurrentState().getMaterializedViewMgr()
                 .createSinkTable(createStmt, partitionInfo, mvId, dbId);
         TupleDescriptor tupleDesc = buildTupleDesc(execPlan, view);
@@ -3740,7 +3740,7 @@ public PlanFragment visitPhysicalTableFunctionTableScan(OptExpression optExpress
             prepareContextSlots(node, context, tupleDesc);
 
             int dop = ConnectContext.get().getSessionVariable().getSinkDegreeOfParallelism();
-            scanNode.setLoadInfo(-1, -1, table, new BrokerDesc(table.getProperties()), fileGroups, false, dop);
+            scanNode.setLoadInfo(-1, -1, table, new BrokerDesc(table.getProperties()), fileGroups, table.isStrictMode(), dop);
             scanNode.setUseVectorizedLoad(true);
             // table function enable flexible column mapping by default.
             scanNode.setFlexibleColumnMapping(true);
diff --git a/fe/fe-core/src/main/java/com/starrocks/statistic/AnalyzeMgr.java b/fe/fe-core/src/main/java/com/starrocks/statistic/AnalyzeMgr.java
index 75c80b1671f674..7079003a4781f2 100644
--- a/fe/fe-core/src/main/java/com/starrocks/statistic/AnalyzeMgr.java
+++ b/fe/fe-core/src/main/java/com/starrocks/statistic/AnalyzeMgr.java
@@ -43,7 +43,6 @@
 import com.starrocks.qe.ConnectContext;
 import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.analyzer.SemanticException;
-import com.starrocks.sql.common.MetaUtils;
 import com.starrocks.transaction.InsertTxnCommitAttachment;
 import com.starrocks.transaction.TransactionState;
 import com.starrocks.transaction.TxnCommitAttachment;
@@ -265,10 +264,8 @@ public void replayRemoveExternalBasicStatsMeta(ExternalBasicStatsMeta basicStats
     }
 
     public void refreshBasicStatisticsCache(Long dbId, Long tableId, List<String> columns, boolean async) {
-        Table table;
-        try {
-            table = MetaUtils.getTable(dbId, tableId);
-        } catch (SemanticException e) {
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(dbId, tableId);
+        if (table == null) {
             return;
         }
 
@@ -284,10 +281,9 @@ public void refreshBasicStatisticsCache(Long dbId, Long tableId, List<String> co
 
     public void refreshConnectorTableBasicStatisticsCache(String catalogName, String dbName, String tableName,
                                                           List<String> columns, boolean async) {
-        Table table;
-        try {
-            table = MetaUtils.getTable(catalogName, dbName, tableName);
-        } catch (Exception e) {
+
+        Table table = GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(catalogName, dbName, tableName);
+        if (table == null) {
             return;
         }
 
@@ -328,11 +324,11 @@ public void replayAddHistogramStatsMeta(HistogramStatsMeta histogramStatsMeta) {
     }
 
     public void refreshHistogramStatisticsCache(Long dbId, Long tableId, List<String> columns, boolean async) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (null == db) {
             return;
         }
-        Table table = db.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (null == table) {
             return;
         }
@@ -377,10 +373,8 @@ public void replayRemoveExternalHistogramStatsMeta(ExternalHistogramStatsMeta hi
 
     public void refreshConnectorTableHistogramStatisticsCache(String catalogName, String dbName, String tableName,
                                                               List<String> columns, boolean async) {
-        Table table;
-        try {
-            table = MetaUtils.getTable(catalogName, dbName, tableName);
-        } catch (Exception e) {
+        Table table = GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(catalogName, dbName, tableName);
+        if (table == null) {
             return;
         }
 
@@ -396,12 +390,12 @@ public void clearStatisticFromDroppedTable() {
         List<Long> dbIds = GlobalStateMgr.getCurrentState().getLocalMetastore().getDbIds();
         Set<Long> tables = new HashSet<>();
         for (Long dbId : dbIds) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             if (null == db || StatisticUtils.statisticDatabaseBlackListCheck(db.getFullName())) {
                 continue;
             }
 
-            for (Table table : db.getTables()) {
+            for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                 /*
                  * If the meta contains statistical information, but the data is empty,
                  * it means that the table has been truncate or insert overwrite, and it is set to empty,
@@ -475,9 +469,11 @@ private void clearStalePartitionStats() {
                     && analyzeStatus.getStatus() == StatsConstants.ScheduleStatus.FINISH
                     && Duration.between(endTime, lastCleanTime).toMinutes() < 30) {
                 NativeAnalyzeStatus nativeAnalyzeStatus = (NativeAnalyzeStatus) analyzeStatus;
-                Database db = GlobalStateMgr.getCurrentState().getDb(nativeAnalyzeStatus.getDbId());
-                if (db != null && db.getTable(nativeAnalyzeStatus.getTableId()) != null) {
-                    tables.add(db.getTable(nativeAnalyzeStatus.getTableId()));
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(nativeAnalyzeStatus.getDbId());
+                if (db != null && GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(db.getId(), nativeAnalyzeStatus.getTableId()) != null) {
+                    tables.add(GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                .getTable(db.getId(), nativeAnalyzeStatus.getTableId()));
                 }
             }
         }
@@ -525,12 +521,12 @@ private void clearStaleStatsWhenStarted() {
             checkTableIds.clear();
             List<Long> dbIds = GlobalStateMgr.getCurrentState().getLocalMetastore().getDbIds();
             for (Long dbId : dbIds) {
-                Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
                 if (null == db || StatisticUtils.statisticDatabaseBlackListCheck(db.getFullName())) {
                     continue;
                 }
 
-                for (Table table : db.getTables()) {
+                for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                     if (table == null || !(table.isOlapOrCloudNativeTable() || table.isMaterializedView())) {
                         continue;
                     }
@@ -547,12 +543,12 @@ private void clearStaleStatsWhenStarted() {
 
         int exprLimit = Config.expr_children_limit / 2;
         for (Pair<Long, Long> dbTableId : checkTableIds) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbTableId.first);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbTableId.first);
             if (null == db) {
                 continue;
             }
 
-            Table table = db.getTable(dbTableId.second);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), dbTableId.second);
             if (table == null) {
                 continue;
             }
@@ -676,7 +672,7 @@ public ExecutorService getAnalyzeTaskThreadPool() {
     }
 
     public void updateLoadRows(TransactionState transactionState) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(transactionState.getDbId());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(transactionState.getDbId());
         if (null == db || StatisticUtils.statisticDatabaseBlackListCheck(db.getFullName())) {
             return;
         }
@@ -703,7 +699,8 @@ public void updateLoadRows(TransactionState transactionState) {
                 long tableId = transactionState.getTableIdList().get(0);
                 long loadRows = ((InsertTxnCommitAttachment) attachment).getLoadedRows();
                 if (loadRows == 0) {
-                    OlapTable table = (OlapTable) db.getTable(tableId);
+                    OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                .getTable(db.getId(), tableId);
                     loadRows = table != null ? table.getRowCount() : 0;
                 }
                 updateBasicStatsMeta(db.getId(), tableId, loadRows);
diff --git a/fe/fe-core/src/main/java/com/starrocks/statistic/BasicStatsMeta.java b/fe/fe-core/src/main/java/com/starrocks/statistic/BasicStatsMeta.java
index 865c8628b7c416..844c6f24383043 100644
--- a/fe/fe-core/src/main/java/com/starrocks/statistic/BasicStatsMeta.java
+++ b/fe/fe-core/src/main/java/com/starrocks/statistic/BasicStatsMeta.java
@@ -22,7 +22,6 @@
 import com.starrocks.common.io.Writable;
 import com.starrocks.persist.gson.GsonUtils;
 import com.starrocks.server.GlobalStateMgr;
-import com.starrocks.sql.optimizer.statistics.TableStatistic;
 import org.apache.commons.collections4.MapUtils;
 
 import java.io.DataInput;
@@ -32,6 +31,7 @@
 import java.util.Collections;
 import java.util.List;
 import java.util.Map;
+import java.util.Optional;
 
 public class BasicStatsMeta implements Writable {
     @SerializedName("dbId")
@@ -123,8 +123,8 @@ public Map<String, String> getProperties() {
     }
 
     public double getHealthy() {
-        Database database = GlobalStateMgr.getCurrentState().getDb(dbId);
-        OlapTable table = (OlapTable) database.getTable(tableId);
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), tableId);
         long totalPartitionCount = table.getPartitions().size();
 
         long tableRowCount = 1L;
@@ -132,15 +132,13 @@ public double getHealthy() {
         long updatePartitionRowCount = 0L;
         long updatePartitionCount = 0L;
 
-        Map<Long, TableStatistic> tableStatistics = GlobalStateMgr.getCurrentState().getStatisticStorage()
+        Map<Long, Optional<Long>> tableStatistics = GlobalStateMgr.getCurrentState().getStatisticStorage()
                 .getTableStatistics(table.getId(), table.getPartitions());
 
         for (Partition partition : table.getPartitions()) {
             tableRowCount += partition.getRowCount();
-            TableStatistic statistic = tableStatistics.getOrDefault(partition.getId(), TableStatistic.unknown());
-            if (!statistic.equals(TableStatistic.unknown())) {
-                cachedTableRowCount += statistic.getRowCount();
-            }
+            Optional<Long> statistic = tableStatistics.getOrDefault(partition.getId(), Optional.empty());
+            cachedTableRowCount += statistic.orElse(0L);
             LocalDateTime loadTime = StatisticUtils.getPartitionLastUpdateTime(partition);
 
             if (partition.hasData() && !isUpdatedAfterLoad(loadTime)) {
diff --git a/fe/fe-core/src/main/java/com/starrocks/statistic/FullStatisticsCollectJob.java b/fe/fe-core/src/main/java/com/starrocks/statistic/FullStatisticsCollectJob.java
index 13512a00f6149c..a2317f79f6a889 100644
--- a/fe/fe-core/src/main/java/com/starrocks/statistic/FullStatisticsCollectJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/statistic/FullStatisticsCollectJob.java
@@ -84,7 +84,6 @@ public FullStatisticsCollectJob(Database db, Table table, List<Long> partitionId
 
     @Override
     public void collect(ConnectContext context, AnalyzeStatus analyzeStatus) throws Exception {
-        long finishedSQLNum = 0;
         int parallelism = Math.max(1, context.getSessionVariable().getStatisticCollectParallelism());
         List<List<String>> collectSQLList = buildCollectSQLList(parallelism);
         long totalCollectSQL = collectSQLList.size();
@@ -100,6 +99,9 @@ public void collect(ConnectContext context, AnalyzeStatus analyzeStatus) throws
         // dop will be set to 1 to meet the requirements of the degree of parallelism.
         // If the number of unions is less than the degree of parallelism,
         // dop should be adjusted appropriately to use enough cpu cores
+        long finishedSQLNum = 0;
+        long failedNum = 0;
+        Exception lastFailure = null;
         for (List<String> sqlUnion : collectSQLList) {
             if (sqlUnion.size() < parallelism) {
                 context.getSessionVariable().setPipelineDop(parallelism / sqlUnion.size());
@@ -109,12 +111,40 @@ public void collect(ConnectContext context, AnalyzeStatus analyzeStatus) throws
 
             String sql = Joiner.on(" UNION ALL ").join(sqlUnion);
 
-            collectStatisticSync(sql, context);
+            try {
+                collectStatisticSync(sql, context);
+            } catch (Exception e) {
+                failedNum++;
+                LOG.warn("collect statistics task failed in job: {}, {}", this, sql, e);
+
+                double failureRatio = 1.0 * failedNum / collectSQLList.size();
+                if (collectSQLList.size() < 100) {
+                    // too few tasks, just fail this job
+                    throw e;
+                } else if (failureRatio > Config.statistic_full_statistics_failure_tolerance_ratio) {
+                    // many tasks, tolerate partial failure
+                    String message = String.format("collect statistic job failed due to " +
+                                    "too many failed tasks: %d/%d, the last failure is %s",
+                            failedNum, collectSQLList.size(), e);
+                    LOG.warn(message, e);
+                    throw new RuntimeException(message, e);
+                } else {
+                    lastFailure = e;
+                    continue;
+                }
+            }
             finishedSQLNum++;
             analyzeStatus.setProgress(finishedSQLNum * 100 / totalCollectSQL);
             GlobalStateMgr.getCurrentState().getAnalyzeMgr().addAnalyzeStatus(analyzeStatus);
         }
 
+        if (lastFailure != null) {
+            String message = String.format("collect statistic job partially failed but tolerated %d/%d, " +
+                    "last error is %s", failedNum, collectSQLList.size(), lastFailure);
+            analyzeStatus.setReason(message);
+            LOG.warn(message);
+        }
+
         flushInsertStatisticsData(context, true);
     }
 
@@ -284,4 +314,18 @@ private String buildBatchCollectFullStatisticSQL(Table table, Partition partitio
         builder.append(build(context, BATCH_FULL_STATISTIC_TEMPLATE));
         return builder.toString();
     }
+
+    @Override
+    public String toString() {
+        final StringBuilder sb = new StringBuilder("FullStatisticsCollectJob{");
+        sb.append("type=").append(type);
+        sb.append(", scheduleType=").append(scheduleType);
+        sb.append(", db=").append(db);
+        sb.append(", table=").append(table);
+        sb.append(", partitionIdList=").append(partitionIdList);
+        sb.append(", columnNames=").append(columnNames);
+        sb.append(", properties=").append(properties);
+        sb.append('}');
+        return sb.toString();
+    }
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/statistic/NativeAnalyzeJob.java b/fe/fe-core/src/main/java/com/starrocks/statistic/NativeAnalyzeJob.java
index 3eb615fc8afbd8..81bc4f23e84f78 100644
--- a/fe/fe-core/src/main/java/com/starrocks/statistic/NativeAnalyzeJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/statistic/NativeAnalyzeJob.java
@@ -105,7 +105,7 @@ public String getCatalogName() {
 
     @Override
     public String getDbName() throws MetaNotFoundException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new MetaNotFoundException("No found database: " + dbId);
         }
@@ -114,11 +114,11 @@ public String getDbName() throws MetaNotFoundException {
 
     @Override
     public String getTableName() throws MetaNotFoundException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new MetaNotFoundException("No found database: " + dbId);
         }
-        Table table = db.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             throw new MetaNotFoundException("No found table: " + tableId);
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/statistic/NativeAnalyzeStatus.java b/fe/fe-core/src/main/java/com/starrocks/statistic/NativeAnalyzeStatus.java
index aef4182e1fccf9..11035a63e15750 100644
--- a/fe/fe-core/src/main/java/com/starrocks/statistic/NativeAnalyzeStatus.java
+++ b/fe/fe-core/src/main/java/com/starrocks/statistic/NativeAnalyzeStatus.java
@@ -27,7 +27,6 @@
 import com.starrocks.qe.ShowResultSet;
 import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.analyzer.SemanticException;
-import com.starrocks.sql.common.MetaUtils;
 
 import java.io.DataInput;
 import java.io.DataOutput;
@@ -114,7 +113,7 @@ public String getCatalogName() {
 
     @Override
     public String getDbName() throws MetaNotFoundException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new MetaNotFoundException("No found database: " + dbId);
         }
@@ -123,11 +122,11 @@ public String getDbName() throws MetaNotFoundException {
 
     @Override
     public String getTableName() throws MetaNotFoundException {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new MetaNotFoundException("No found database: " + dbId);
         }
-        Table table = db.getTable(tableId);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(dbId, tableId);
         if (table == null) {
             throw new MetaNotFoundException("No found table: " + tableId);
         }
@@ -205,7 +204,7 @@ public ShowResultSet toShowResult() {
         if (dbId == StatsConstants.DEFAULT_ALL_ID) {
             dbName = "*";
         } else {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
             dbName = db.getOriginName();
         }
         String tableName;
@@ -213,7 +212,11 @@ public ShowResultSet toShowResult() {
             tableName = "*";
         } else {
             try {
-                tableName = MetaUtils.getTable(dbId, tableId).getName();
+                Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(dbId, tableId);
+                if (table == null) {
+                    throw new SemanticException("Table %s is not found", tableId);
+                }
+                tableName = table.getName();
             } catch (SemanticException e) {
                 tableName = "<tableId : " + tableId + ">";
                 status = StatsConstants.ScheduleStatus.FAILED;
diff --git a/fe/fe-core/src/main/java/com/starrocks/statistic/SampleStatisticsCollectJob.java b/fe/fe-core/src/main/java/com/starrocks/statistic/SampleStatisticsCollectJob.java
index e83a143ea37519..e2872bdaa1b6e9 100644
--- a/fe/fe-core/src/main/java/com/starrocks/statistic/SampleStatisticsCollectJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/statistic/SampleStatisticsCollectJob.java
@@ -86,4 +86,5 @@ public void collect(ConnectContext context, AnalyzeStatus analyzeStatus) throws
             }
         }
     }
+
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticExecutor.java b/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticExecutor.java
index 2a1ed87c96e0f7..69a4f2329ed1ee 100644
--- a/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticExecutor.java
+++ b/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticExecutor.java
@@ -14,6 +14,7 @@
 
 package com.starrocks.statistic;
 
+import com.google.common.base.Stopwatch;
 import com.google.common.collect.Lists;
 import com.starrocks.catalog.ColumnId;
 import com.starrocks.catalog.Database;
@@ -81,19 +82,19 @@ public List<TStatisticData> queryStatisticSync(ConnectContext context, Long dbId
             if (dbId == null) {
                 List<Long> dbIds = GlobalStateMgr.getCurrentState().getLocalMetastore().getDbIds();
                 for (Long id : dbIds) {
-                    Database db = GlobalStateMgr.getCurrentState().getDb(id);
+                    Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(id);
                     if (db == null) {
                         continue;
                     }
-                    table = db.getTable(tableId);
+                    table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
                     if (table == null) {
                         continue;
                     }
                     break;
                 }
             } else {
-                Database database = GlobalStateMgr.getCurrentState().getDb(dbId);
-                table = database.getTable(tableId);
+                Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
+                table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), tableId);
             }
 
             if (table == null) {
@@ -186,8 +187,16 @@ public static Pair<List<TStatisticData>, Status> queryDictSync(Long dbId, Long t
             return Pair.create(Collections.emptyList(), Status.OK);
         }
 
-        Database db = MetaUtils.getDatabase(dbId);
-        Table table = MetaUtils.getTable(dbId, tableId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
+        if (db == null) {
+            throw new SemanticException("Database %s is not found", dbId);
+        }
+
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
+        if (table == null) {
+            throw new SemanticException("Table %s is not found", tableId);
+        }
+
         if (!(table.isOlapOrCloudNativeTable() || table.isMaterializedView())) {
             throw new SemanticException("Table '%s' is not a OLAP table or LAKE table or Materialize View",
                     table.getName());
@@ -220,8 +229,8 @@ public static Pair<List<TStatisticData>, Status> queryDictSync(Long dbId, Long t
         }
     }
 
-    public List<TStatisticData> queryTableStats(ConnectContext context, Long tableId) {
-        String sql = StatisticSQLBuilder.buildQueryTableStatisticsSQL(tableId);
+    public List<TStatisticData> queryTableStats(ConnectContext context, Long tableId, List<Long> partitions) {
+        String sql = StatisticSQLBuilder.buildQueryTableStatisticsSQL(tableId, partitions);
         return executeStatisticDQL(context, sql);
     }
 
@@ -233,7 +242,7 @@ public List<TStatisticData> queryTableStats(ConnectContext context, Long tableId
     private static List<TStatisticData> deserializerStatisticData(List<TResultBatch> sqlResult) throws TException {
         List<TStatisticData> statistics = Lists.newArrayList();
 
-        if (sqlResult.size() < 1) {
+        if (sqlResult.isEmpty()) {
             return statistics;
         }
 
@@ -276,6 +285,7 @@ public AnalyzeStatus collectStatistics(ConnectContext statsConnectCtx,
         Table table = statsJob.getTable();
 
         try {
+            Stopwatch watch = Stopwatch.createStarted();
             statsConnectCtx.getSessionVariable().setEnableProfile(Config.enable_statistics_collect_profile);
             GlobalStateMgr.getCurrentState().getAnalyzeMgr().registerConnection(analyzeStatus.getId(), statsConnectCtx);
             // Only update running status without edit log, make restart job status is failed
@@ -284,8 +294,9 @@ public AnalyzeStatus collectStatistics(ConnectContext statsConnectCtx,
 
             statsConnectCtx.setStatisticsConnection(true);
             statsJob.collect(statsConnectCtx, analyzeStatus);
+            LOG.info("execute statistics job successfully, duration={}, job={}", watch.toString(), statsJob);
         } catch (Exception e) {
-            LOG.warn("Collect statistics error ", e);
+            LOG.warn("execute statistics job failed: {}", statsJob, e);
             analyzeStatus.setStatus(StatsConstants.ScheduleStatus.FAILED);
             analyzeStatus.setEndTime(LocalDateTime.now());
             analyzeStatus.setReason(e.getMessage());
diff --git a/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticSQLBuilder.java b/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticSQLBuilder.java
index 0751f48c7a0190..54b0ba43b5f463 100644
--- a/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticSQLBuilder.java
+++ b/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticSQLBuilder.java
@@ -87,9 +87,13 @@ public class StatisticSQLBuilder {
         DEFAULT_VELOCITY_ENGINE.setProperty(VelocityEngine.RUNTIME_LOG_REFERENCE_LOG_INVALID, false);
     }
 
-    public static String buildQueryTableStatisticsSQL(Long tableId) {
+    public static String buildQueryTableStatisticsSQL(Long tableId, List<Long> partitionIds) {
         VelocityContext context = new VelocityContext();
         context.put("predicate", "table_id = " + tableId);
+        if (!partitionIds.isEmpty()) {
+            context.put("predicate", "table_id = " + tableId + " and partition_id in (" +
+                    partitionIds.stream().map(String::valueOf).collect(Collectors.joining(", ")) + ")");
+        }
         return build(context, QUERY_TABLE_STATISTIC_TEMPLATE);
     }
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticUtils.java b/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticUtils.java
index 3bc69cca5974e4..24a32ea4b67cff 100644
--- a/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticUtils.java
+++ b/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticUtils.java
@@ -46,6 +46,8 @@
 import com.starrocks.common.FeConstants;
 import com.starrocks.common.util.DateUtils;
 import com.starrocks.common.util.UUIDUtil;
+import com.starrocks.common.util.concurrent.lock.LockType;
+import com.starrocks.common.util.concurrent.lock.Locker;
 import com.starrocks.connector.PartitionInfo;
 import com.starrocks.load.EtlStatus;
 import com.starrocks.load.loadv2.LoadJobFinalOperation;
@@ -141,7 +143,8 @@ private static StatsConstants.AnalyzeType parseAnalyzeType(TransactionState txnS
         return StatsConstants.AnalyzeType.FULL;
     }
 
-    public static void triggerCollectionOnFirstLoad(TransactionState txnState, Database db, Table table, boolean sync) {
+    public static void triggerCollectionOnFirstLoad(
+            TransactionState txnState, Database db, Table table, boolean sync, boolean useLock) {
         if (!Config.enable_statistic_collect_on_first_load) {
             return;
         }
@@ -159,16 +162,26 @@ public static void triggerCollectionOnFirstLoad(TransactionState txnState, Datab
         }
         // collectPartitionIds contains partition that is first loaded.
         Set<Long> collectPartitionIds = Sets.newHashSet();
-        for (long physicalPartitionId : tableCommitInfo.getIdToPartitionCommitInfo().keySet()) {
-            // partition commit info id is physical partition id.
-            // statistic collect granularity is logic partition.
-            PhysicalPartition physicalPartition = table.getPhysicalPartition(physicalPartitionId);
-            if (physicalPartition != null) {
-                Partition partition = table.getPartition(physicalPartition.getParentId());
-                if (partition != null && partition.isFirstLoad()) {
-                    collectPartitionIds.add(partition.getId());
+        Locker locker = new Locker();
+        if (useLock) {
+            locker.lockDatabase(db, LockType.READ);
+        }
+        try {
+            for (long physicalPartitionId : tableCommitInfo.getIdToPartitionCommitInfo().keySet()) {
+                // partition commit info id is physical partition id.
+                // statistic collect granularity is logic partition.
+                PhysicalPartition physicalPartition = table.getPhysicalPartition(physicalPartitionId);
+                if (physicalPartition != null) {
+                    Partition partition = table.getPartition(physicalPartition.getParentId());
+                    if (partition != null && partition.isFirstLoad()) {
+                        collectPartitionIds.add(partition.getId());
+                    }
                 }
             }
+        } finally {
+            if (useLock) {
+                locker.unLockDatabase(db, LockType.READ);
+            }
         }
         if (collectPartitionIds.isEmpty()) {
             return;
@@ -235,8 +248,8 @@ public static boolean statisticTableBlackListCheck(long tableId) {
         }
 
         for (String dbName : COLLECT_DATABASES_BLACKLIST) {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
-            if (null != db && null != db.getTable(tableId)) {
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
+            if (null != db && null != GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId)) {
                 return true;
             }
         }
@@ -248,7 +261,7 @@ public static boolean checkStatisticTableStateNormal() {
         if (FeConstants.runningUnitTest) {
             return true;
         }
-        Database db = GlobalStateMgr.getCurrentState().getDb(StatsConstants.STATISTICS_DB_NAME);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(StatsConstants.STATISTICS_DB_NAME);
         List<String> tableNameList = Lists.newArrayList(StatsConstants.SAMPLE_STATISTICS_TABLE_NAME,
                 StatsConstants.FULL_STATISTICS_TABLE_NAME, StatsConstants.HISTOGRAM_STATISTICS_TABLE_NAME,
                 StatsConstants.EXTERNAL_FULL_STATISTICS_TABLE_NAME);
@@ -260,7 +273,7 @@ public static boolean checkStatisticTableStateNormal() {
 
         for (String tableName : tableNameList) {
             // check table
-            Table table = db.getTable(tableName);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
             if (table == null) {
                 return false;
             }
@@ -390,9 +403,9 @@ public static List<ColumnDef> buildStatsColumnDef(String tableName) {
                     new ColumnDef("column_name", new TypeDef(columnNameType)),
                     new ColumnDef("db_id", new TypeDef(ScalarType.createType(PrimitiveType.BIGINT))),
                     new ColumnDef("table_name", new TypeDef(tableNameType)),
-                    new ColumnDef("buckets", new TypeDef(bucketsType), false, null,
+                    new ColumnDef("buckets", new TypeDef(bucketsType), false, null, null,
                             true, ColumnDef.DefaultValueDef.NOT_SET, ""),
-                    new ColumnDef("mcv", new TypeDef(mostCommonValueType), false, null,
+                    new ColumnDef("mcv", new TypeDef(mostCommonValueType), false, null, null,
                             true, ColumnDef.DefaultValueDef.NOT_SET, ""),
                     new ColumnDef("update_time", new TypeDef(ScalarType.createType(PrimitiveType.DATETIME)))
             );
@@ -403,9 +416,9 @@ public static List<ColumnDef> buildStatsColumnDef(String tableName) {
                     new ColumnDef("catalog_name", new TypeDef(catalogNameType)),
                     new ColumnDef("db_name", new TypeDef(dbNameType)),
                     new ColumnDef("table_name", new TypeDef(tableNameType)),
-                    new ColumnDef("buckets", new TypeDef(bucketsType), false, null,
+                    new ColumnDef("buckets", new TypeDef(bucketsType), false, null, null,
                             true, ColumnDef.DefaultValueDef.NOT_SET, ""),
-                    new ColumnDef("mcv", new TypeDef(mostCommonValueType), false, null,
+                    new ColumnDef("mcv", new TypeDef(mostCommonValueType), false, null, null,
                             true, ColumnDef.DefaultValueDef.NOT_SET, ""),
                     new ColumnDef("update_time", new TypeDef(ScalarType.createType(PrimitiveType.DATETIME)))
             );
diff --git a/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticsCollectJob.java b/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticsCollectJob.java
index 041b225ea08f9e..5db440b7af050f 100644
--- a/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticsCollectJob.java
+++ b/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticsCollectJob.java
@@ -215,4 +215,17 @@ public static String fullAnalyzeGetDataSize(String columnName, Type columnType)
         long typeSize = columnType.getTypeSize();
         return "COUNT(1) * " + typeSize;
     }
+
+    @Override
+    public String toString() {
+        final StringBuilder sb = new StringBuilder("StatisticsCollectJob{");
+        sb.append("type=").append(type);
+        sb.append(", scheduleType=").append(scheduleType);
+        sb.append(", db=").append(db);
+        sb.append(", table=").append(table);
+        sb.append(", columnNames=").append(columnNames);
+        sb.append(", properties=").append(properties);
+        sb.append('}');
+        return sb.toString();
+    }
 }
diff --git a/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticsCollectJobFactory.java b/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticsCollectJobFactory.java
index 1ebeb99005a0fd..43f6bb5b19351b 100644
--- a/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticsCollectJobFactory.java
+++ b/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticsCollectJobFactory.java
@@ -59,33 +59,34 @@ public static List<StatisticsCollectJob> buildStatisticsCollectJob(NativeAnalyze
             List<Long> dbIds = GlobalStateMgr.getCurrentState().getLocalMetastore().getDbIds();
 
             for (Long dbId : dbIds) {
-                Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
                 if (null == db || StatisticUtils.statisticDatabaseBlackListCheck(db.getFullName())) {
                     continue;
                 }
 
-                for (Table table : db.getTables()) {
+                for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                     createJob(statsJobs, nativeAnalyzeJob, db, table, null, null);
                 }
             }
         } else if (StatsConstants.DEFAULT_ALL_ID == nativeAnalyzeJob.getTableId()
                 && StatsConstants.DEFAULT_ALL_ID != nativeAnalyzeJob.getDbId()) {
             // all table
-            Database db = GlobalStateMgr.getCurrentState().getDb(nativeAnalyzeJob.getDbId());
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(nativeAnalyzeJob.getDbId());
             if (null == db) {
                 return Collections.emptyList();
             }
 
-            for (Table table : db.getTables()) {
+            for (Table table : GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId())) {
                 createJob(statsJobs, nativeAnalyzeJob, db, table, null, null);
             }
         } else {
             // database or table is null mean database/table has been dropped
-            Database db = GlobalStateMgr.getCurrentState().getDb(nativeAnalyzeJob.getDbId());
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(nativeAnalyzeJob.getDbId());
             if (db == null) {
                 return Collections.emptyList();
             }
-            createJob(statsJobs, nativeAnalyzeJob, db, db.getTable(nativeAnalyzeJob.getTableId()),
+            createJob(statsJobs, nativeAnalyzeJob, db, GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(db.getId(), nativeAnalyzeJob.getTableId()),
                     nativeAnalyzeJob.getColumns(), nativeAnalyzeJob.getColumnTypes());
         }
 
diff --git a/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticsMetaManager.java b/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticsMetaManager.java
index 9a4e7bd10f6ef1..ca983ef3c1620d 100644
--- a/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticsMetaManager.java
+++ b/fe/fe-core/src/main/java/com/starrocks/statistic/StatisticsMetaManager.java
@@ -61,7 +61,7 @@ public StatisticsMetaManager() {
     }
 
     private boolean checkDatabaseExist() {
-        return GlobalStateMgr.getCurrentState().getDb(StatsConstants.STATISTICS_DB_NAME) != null;
+        return GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(StatsConstants.STATISTICS_DB_NAME) != null;
     }
 
     private boolean createDatabase() {
@@ -78,9 +78,9 @@ private boolean createDatabase() {
     }
 
     private boolean checkTableExist(String tableName) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(StatsConstants.STATISTICS_DB_NAME);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(StatsConstants.STATISTICS_DB_NAME);
         Preconditions.checkState(db != null);
-        return db.getTable(tableName) != null;
+        return GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName) != null;
     }
 
     private boolean checkReplicateNormal(String tableName) {
@@ -92,9 +92,9 @@ private boolean checkReplicateNormal(String tableName) {
             return true;
         }
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(StatsConstants.STATISTICS_DB_NAME);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(StatsConstants.STATISTICS_DB_NAME);
         Preconditions.checkState(db != null);
-        OlapTable table = (OlapTable) db.getTable(tableName);
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         Preconditions.checkState(table != null);
         if (table.isCloudNativeTableOrMaterializedView()) {
             return true;
diff --git a/fe/fe-core/src/main/java/com/starrocks/system/SystemInfoService.java b/fe/fe-core/src/main/java/com/starrocks/system/SystemInfoService.java
index 4173102cf85040..b619b4f2f92ad8 100644
--- a/fe/fe-core/src/main/java/com/starrocks/system/SystemInfoService.java
+++ b/fe/fe-core/src/main/java/com/starrocks/system/SystemInfoService.java
@@ -421,11 +421,11 @@ protected void checkWhenNotForceDrop(Backend droppedBackend) {
                 GlobalStateMgr.getCurrentState().getTabletInvertedIndex().getTabletIdsByBackendId(droppedBackend.getId());
         List<Long> dbs = globalStateMgr.getLocalMetastore().getDbIds();
 
-        dbs.stream().map(globalStateMgr::getDb).forEach(db -> {
+        dbs.stream().map(dbId -> globalStateMgr.getLocalMetastore().getDb(dbId)).forEach(db -> {
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.READ);
             try {
-                db.getTables().stream()
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTables(db.getId()).stream()
                         .filter(Table::isOlapTableOrMaterializedView)
                         .map(table -> (OlapTable) table)
                         .filter(table -> table.getTableProperty().getReplicationNum() == 1)
@@ -953,7 +953,7 @@ public void updateBackendReportVersion(long backendId, long newReportVersion, lo
         if (node instanceof Backend) {
             AtomicLong atomicLong;
             if ((atomicLong = idToReportVersionRef.get(backendId)) != null) {
-                Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
                 if (db != null) {
                     updateReportVersionIncrementally(atomicLong, newReportVersion);
                     LOG.debug("update backend {} report version: {}, db: {}", backendId, newReportVersion, dbId);
diff --git a/fe/fe-core/src/main/java/com/starrocks/task/AlterReplicaTask.java b/fe/fe-core/src/main/java/com/starrocks/task/AlterReplicaTask.java
index 492cd560eb7aea..22d6e3ef771225 100644
--- a/fe/fe-core/src/main/java/com/starrocks/task/AlterReplicaTask.java
+++ b/fe/fe-core/src/main/java/com/starrocks/task/AlterReplicaTask.java
@@ -301,12 +301,12 @@ public TAlterTabletReqV2 toThrift() {
      *      And because alter request report success, it means that we can increase replica's version to X.
      */
     public void handleFinishAlterTask() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb(getDbId());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(getDbId());
         if (db == null) {
             throw new MetaNotFoundException("database " + getDbId() + " does not exist");
         }
 
-        OlapTable tbl = (OlapTable) db.getTable(getTableId());
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), getTableId());
         if (tbl == null) {
             throw new MetaNotFoundException("tbl " + getTableId() + " does not exist");
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/task/ExportPendingTask.java b/fe/fe-core/src/main/java/com/starrocks/task/ExportPendingTask.java
index 58738543f73c47..0a1122f75eba54 100644
--- a/fe/fe-core/src/main/java/com/starrocks/task/ExportPendingTask.java
+++ b/fe/fe-core/src/main/java/com/starrocks/task/ExportPendingTask.java
@@ -80,7 +80,7 @@ protected void exec() {
         }
 
         long dbId = job.getDbId();
-        db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             job.cancelInternal(ExportFailMsg.CancelType.RUN_FAIL, "database does not exist");
             return;
diff --git a/fe/fe-core/src/main/java/com/starrocks/task/LeaderTaskExecutor.java b/fe/fe-core/src/main/java/com/starrocks/task/LeaderTaskExecutor.java
index e202c7a7abe36a..74988f8220f96b 100644
--- a/fe/fe-core/src/main/java/com/starrocks/task/LeaderTaskExecutor.java
+++ b/fe/fe-core/src/main/java/com/starrocks/task/LeaderTaskExecutor.java
@@ -114,6 +114,25 @@ public int getTaskNum() {
         }
     }
 
+    public int getCorePoolSize() {
+        return executor.getCorePoolSize();
+    }
+
+    public void setPoolSize(int poolSize) {
+        // corePoolSize and maximumPoolSize are same.
+        // When the previous poolSize is larger than the poolSize to be set,
+        // you need to setCorePoolSize first and then setMaximumPoolSize, and vice versa.
+        // Otherwise, it will throw IllegalArgumentException
+        int prePoolSize = executor.getCorePoolSize();
+        if (poolSize < prePoolSize) {
+            executor.setCorePoolSize(poolSize);
+            executor.setMaximumPoolSize(poolSize);
+        } else {
+            executor.setMaximumPoolSize(poolSize);
+            executor.setCorePoolSize(poolSize);
+        }
+    }
+
     private class TaskChecker implements Runnable {
         @Override
         public void run() {
diff --git a/fe/fe-core/src/main/java/com/starrocks/task/PublishVersionTask.java b/fe/fe-core/src/main/java/com/starrocks/task/PublishVersionTask.java
index 9a306ace4b9996..25f455c27ad227 100644
--- a/fe/fe-core/src/main/java/com/starrocks/task/PublishVersionTask.java
+++ b/fe/fe-core/src/main/java/com/starrocks/task/PublishVersionTask.java
@@ -189,7 +189,7 @@ public void updateReplicaVersions(List<TTabletVersionPair> tabletVersions) {
             LOG.warn("backend not found or no replicas on backend, backendid={}", backendId);
             return;
         }
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             LOG.warn("db not found dbid={}", dbId);
             return;
diff --git a/fe/fe-core/src/main/java/com/starrocks/transaction/DatabaseTransactionMgr.java b/fe/fe-core/src/main/java/com/starrocks/transaction/DatabaseTransactionMgr.java
index de568f0864af03..95fd4f3bee873e 100644
--- a/fe/fe-core/src/main/java/com/starrocks/transaction/DatabaseTransactionMgr.java
+++ b/fe/fe-core/src/main/java/com/starrocks/transaction/DatabaseTransactionMgr.java
@@ -269,7 +269,7 @@ public void prepareTransaction(long transactionId, List<TabletCommitInfo> tablet
         Preconditions.checkNotNull(tabletFailInfos, "tabletFailInfos is null");
         // 1. check status
         // the caller method already own db lock, we do not obtain db lock here
-        Database db = globalStateMgr.getDb(dbId);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
         if (null == db) {
             throw new MetaNotFoundException("could not find db [" + dbId + "]");
         }
@@ -389,7 +389,7 @@ public void prepareTransaction(long transactionId, List<TabletCommitInfo> tablet
     public VisibleStateWaiter commitPreparedTransaction(long transactionId) throws UserException {
         // 1. check status
         // the caller method already own db lock, we do not obtain db lock here
-        Database db = globalStateMgr.getDb(dbId);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
         if (null == db) {
             throw new MetaNotFoundException("could not find db [" + dbId + "]");
         }
@@ -419,7 +419,7 @@ public VisibleStateWaiter commitPreparedTransaction(long transactionId) throws U
             txnSpan.addEvent("commit_start");
 
             for (Long tableId : transactionState.getTableIdList()) {
-                Table table = db.getTable(tableId);
+                Table table = globalStateMgr.getLocalMetastore().getTable(db.getId(), tableId);
                 if (table == null) {
                     // this can happen when tableId == -1 (tablet being dropping)
                     // or table really not exist.
@@ -551,12 +551,12 @@ public void abortTransaction(long transactionId, boolean abortPrepared, String r
 
         LOG.info("transaction:[{}] successfully rollback", transactionState);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
         if (db == null) {
             return;
         }
         for (Long tableId : transactionState.getTableIdList()) {
-            Table table = db.getTable(tableId);
+            Table table = globalStateMgr.getLocalMetastore().getTable(db.getId(), tableId);
             if (table == null) {
                 continue;
             }
@@ -875,7 +875,7 @@ public List<TransactionStateBatch> getReadyToPublishTxnListBatch() {
     // for each tablet of load txn, if most replicas version publish successed
     // the trasaction can be treated as successful and can be finished
     public boolean canTxnFinished(TransactionState txn, Set<Long> errReplicas, Set<Long> unfinishedBackends) {
-        Database db = globalStateMgr.getDb(txn.getDbId());
+        Database db = globalStateMgr.getLocalMetastore().getDb(txn.getDbId());
         if (db == null) {
             return true;
         }
@@ -888,7 +888,7 @@ public boolean canTxnFinished(TransactionState txn, Set<Long> errReplicas, Set<L
             // check each table involved in transaction
             for (TableCommitInfo tableCommitInfo : txn.getIdToTableCommitInfos().values()) {
                 long tableId = tableCommitInfo.getTableId();
-                OlapTable table = (OlapTable) db.getTable(tableId);
+                OlapTable table = (OlapTable) globalStateMgr.getLocalMetastore().getTable(db.getId(), tableId);
                 // table maybe dropped between commit and publish, ignore it
                 // it will be processed in finishTransaction
                 if (table == null) {
@@ -986,7 +986,7 @@ public void finishTransaction(long transactionId, Set<Long> errorReplicaIds) thr
             errorReplicaIds.addAll(originalErrorReplicas);
         }
 
-        Database db = globalStateMgr.getDb(transactionState.getDbId());
+        Database db = globalStateMgr.getLocalMetastore().getDb(transactionState.getDbId());
         if (db == null) {
             transactionState.writeLock();
             try {
@@ -1018,7 +1018,8 @@ public void finishTransaction(long transactionId, Set<Long> errorReplicaIds) thr
                 Set<Long> droppedTableIds = Sets.newHashSet();
                 for (TableCommitInfo tableCommitInfo : transactionState.getIdToTableCommitInfos().values()) {
                     long tableId = tableCommitInfo.getTableId();
-                    OlapTable table = (OlapTable) db.getTable(tableId);
+                    OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                .getTable(db.getId(), tableId);
                     // table maybe dropped between commit and publish, ignore this error
                     if (table == null) {
                         droppedTableIds.add(tableId);
@@ -1230,7 +1231,7 @@ protected void unprotectedCommitPreparedTransaction(TransactionState transaction
         while (tableCommitInfoIterator.hasNext()) {
             TableCommitInfo tableCommitInfo = tableCommitInfoIterator.next();
             long tableId = tableCommitInfo.getTableId();
-            OlapTable table = (OlapTable) db.getTable(tableId);
+            OlapTable table = (OlapTable) globalStateMgr.getLocalMetastore().getTable(db.getId(), tableId);
             // table maybe dropped between commit and publish, ignore this error
             if (table == null) {
                 transactionState.removeTable(tableId);
@@ -1614,7 +1615,7 @@ public List<List<String>> getSingleTranInfo(long dbId, long txnId) throws Analys
         List<List<String>> infos = new ArrayList<List<String>>();
         readLock();
         try {
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
             if (db == null) {
                 throw new AnalysisException("Database[" + dbId + "] does not exist");
             }
@@ -1657,7 +1658,7 @@ protected void checkRunningTxnExceedLimit(TransactionState.LoadJobSourceType sou
     private void updateCatalogAfterCommitted(TransactionState transactionState, Database db) {
         for (TableCommitInfo tableCommitInfo : transactionState.getIdToTableCommitInfos().values()) {
             long tableId = tableCommitInfo.getTableId();
-            Table table = db.getTable(tableId);
+            Table table = globalStateMgr.getLocalMetastore().getTable(db.getId(), tableId);
             TransactionLogApplier applier = txnLogApplierFactory.create(table);
             applier.applyCommitLog(transactionState, tableCommitInfo);
         }
@@ -1665,7 +1666,7 @@ private void updateCatalogAfterCommitted(TransactionState transactionState, Data
 
     private boolean updateCatalogAfterVisible(TransactionState transactionState, Database db) {
         for (TableCommitInfo tableCommitInfo : transactionState.getIdToTableCommitInfos().values()) {
-            Table table = db.getTable(tableCommitInfo.getTableId());
+            Table table = globalStateMgr.getLocalMetastore().getTable(db.getId(), tableCommitInfo.getTableId());
             // table may be dropped by force after transaction committed
             // so that it will be a visible edit log after drop table
             if (table == null) {
@@ -1684,7 +1685,8 @@ private boolean updateCatalogAfterVisible(TransactionState transactionState, Dat
 
     // the write lock of database has been hold
     private boolean updateCatalogAfterVisibleBatch(TransactionStateBatch transactionStateBatch, Database db) {
-        Table table = db.getTable(transactionStateBatch.getTableId());
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getId(), transactionStateBatch.getTableId());
         if (table == null) {
             return true;
         }
@@ -1771,7 +1773,7 @@ public void replayUpsertTransactionState(TransactionState transactionState) {
             }
             // set transaction status will call txn state change listener
             transactionState.replaySetTransactionStatus();
-            Database db = globalStateMgr.getDb(transactionState.getDbId());
+            Database db = globalStateMgr.getLocalMetastore().getDb(transactionState.getDbId());
             if (transactionState.getTransactionStatus() == TransactionStatus.COMMITTED) {
                 LOG.info("replay a committed transaction {}", transactionState);
                 updateCatalogAfterCommitted(transactionState, db);
@@ -1793,7 +1795,7 @@ public void replayUpsertTransactionStateBatch(TransactionStateBatch transactionS
         writeLock();
         try {
             LOG.info("replay a transaction state batch{}", transactionStateBatch);
-            Database db = globalStateMgr.getDb(transactionStateBatch.getDbId());
+            Database db = globalStateMgr.getLocalMetastore().getDb(transactionStateBatch.getDbId());
             updateCatalogAfterVisibleBatch(transactionStateBatch, db);
 
             unprotectSetTransactionStateBatch(transactionStateBatch, true);
@@ -1832,7 +1834,7 @@ GlobalStateMgr getGlobalStateMgr() {
     }
 
     public void finishTransactionNew(TransactionState transactionState, Set<Long> publishErrorReplicas) throws UserException {
-        Database db = globalStateMgr.getDb(transactionState.getDbId());
+        Database db = globalStateMgr.getLocalMetastore().getDb(transactionState.getDbId());
         if (db == null) {
             transactionState.writeLock();
             try {
@@ -1901,7 +1903,7 @@ public void finishTransactionNew(TransactionState transactionState, Set<Long> pu
     }
 
     public void finishTransactionBatch(TransactionStateBatch stateBatch, Set<Long> errorReplicaIds) {
-        Database db = globalStateMgr.getDb(stateBatch.getDbId());
+        Database db = globalStateMgr.getLocalMetastore().getDb(stateBatch.getDbId());
         if (db == null) {
             stateBatch.writeLock();
             try {
@@ -1983,7 +1985,7 @@ private List<TransactionStateListener> populateTransactionStateListeners(@NotNul
             throws TransactionException {
         List<TransactionStateListener> stateListeners = Lists.newArrayList();
         for (Long tableId : transactionState.getTableIdList()) {
-            Table table = database.getTable(tableId);
+            Table table = globalStateMgr.getLocalMetastore().getTable(database.getId(), tableId);
             if (table == null) {
                 // this can happen when tableId == -1 (tablet being dropping)
                 // or table really not exist.
@@ -2013,7 +2015,7 @@ public TTransactionStatus getTxnStatus(long txnId) {
     }
 
     private void checkDatabaseDataQuota() throws AnalysisException {
-        Database db = globalStateMgr.getDb(dbId);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
         if (db == null) {
             throw new AnalysisException("Database[" + dbId + "] does not exist");
         }
diff --git a/fe/fe-core/src/main/java/com/starrocks/transaction/GlobalTransactionMgr.java b/fe/fe-core/src/main/java/com/starrocks/transaction/GlobalTransactionMgr.java
index 30a42c4c9f2825..f66b2a01e12310 100644
--- a/fe/fe-core/src/main/java/com/starrocks/transaction/GlobalTransactionMgr.java
+++ b/fe/fe-core/src/main/java/com/starrocks/transaction/GlobalTransactionMgr.java
@@ -283,7 +283,7 @@ public void prepareTransaction(long dbId, long transactionId, List<TabletCommitI
     public void commitPreparedTransaction(long dbId, long transactionId, long timeoutMillis)
             throws UserException {
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
         if (db == null) {
             LOG.warn("Database {} does not exist", dbId);
             throw new UserException("Database[" + dbId + "] does not exist");
@@ -697,7 +697,7 @@ public List<List<Comparable>> getDbInfo() {
         for (long dbId : dbIds) {
             List<Comparable> info = new ArrayList<Comparable>();
             info.add(dbId);
-            Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+            Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
             if (db == null) {
                 continue;
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/transaction/OlapTableTxnLogApplier.java b/fe/fe-core/src/main/java/com/starrocks/transaction/OlapTableTxnLogApplier.java
index fd44dddf30b5ec..a2ee47df233663 100644
--- a/fe/fe-core/src/main/java/com/starrocks/transaction/OlapTableTxnLogApplier.java
+++ b/fe/fe-core/src/main/java/com/starrocks/transaction/OlapTableTxnLogApplier.java
@@ -90,7 +90,7 @@ public void applyCommitLog(TransactionState txnState, TableCommitInfo commitInfo
     public void applyVisibleLog(TransactionState txnState, TableCommitInfo commitInfo, Database db) {
         Set<Long> errorReplicaIds = txnState.getErrorReplicas();
         long tableId = table.getId();
-        OlapTable table = (OlapTable) db.getTable(tableId);
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
         if (table == null) {
             LOG.warn("table {} is dropped, ignore", tableId);
             return;
diff --git a/fe/fe-core/src/main/java/com/starrocks/transaction/OlapTableTxnStateListener.java b/fe/fe-core/src/main/java/com/starrocks/transaction/OlapTableTxnStateListener.java
index 4822927400ccc8..a840c51c6a068b 100644
--- a/fe/fe-core/src/main/java/com/starrocks/transaction/OlapTableTxnStateListener.java
+++ b/fe/fe-core/src/main/java/com/starrocks/transaction/OlapTableTxnStateListener.java
@@ -292,7 +292,7 @@ public void preWriteCommitLog(TransactionState txnState) {
     public void postAbort(TransactionState txnState, List<TabletCommitInfo> finishedTablets,
                           List<TabletFailInfo> failedTablets) {
         txnState.clearAutomaticPartitionSnapshot();
-        Database db = GlobalStateMgr.getCurrentState().getDb(txnState.getDbId());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(txnState.getDbId());
         if (db != null) {
             Locker locker = new Locker();
             locker.lockTablesWithIntensiveDbLock(db, txnState.getTableIdList(), LockType.READ);
diff --git a/fe/fe-core/src/main/java/com/starrocks/transaction/PublishVersionDaemon.java b/fe/fe-core/src/main/java/com/starrocks/transaction/PublishVersionDaemon.java
index 4594c9e8d9c5a8..54b971dacf7779 100644
--- a/fe/fe-core/src/main/java/com/starrocks/transaction/PublishVersionDaemon.java
+++ b/fe/fe-core/src/main/java/com/starrocks/transaction/PublishVersionDaemon.java
@@ -427,7 +427,7 @@ private CompletableFuture<Void> publishLakeTransactionAsync(TransactionState txn
         GlobalTransactionMgr globalTransactionMgr = GlobalStateMgr.getCurrentState().getGlobalTransactionMgr();
         long txnId = txnState.getTransactionId();
         long dbId = txnState.getDbId();
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             LOG.info("the database of transaction {} has been deleted", txnId);
             try {
@@ -482,7 +482,7 @@ public boolean publishPartitionBatch(Database db, long tableId, PartitionPublish
         // version -> shadowTablets
         long warehouseId = WarehouseManager.DEFAULT_WAREHOUSE_ID;
         try {
-            OlapTable table = (OlapTable) db.getTable(tableId);
+            OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (table == null) {
                 // table has been dropped
                 return true;
@@ -655,7 +655,7 @@ private CompletableFuture<Void> publishLakeTransactionBatchAsync(TransactionStat
             }
         }
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
 
         if (db == null) {
             LOG.info("the database of transaction batch {} has been deleted", txnStateBatch);
@@ -768,7 +768,7 @@ private boolean publishPartition(@NotNull Database db, @NotNull TableCommitInfo
         Locker locker = new Locker();
         locker.lockTablesWithIntensiveDbLock(db, Lists.newArrayList(tableId), LockType.READ);
         try {
-            OlapTable table = (OlapTable) db.getTable(tableId);
+            OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
             if (table == null) {
                 txnState.removeTable(tableCommitInfo.getTableId());
                 LOG.info("Removed non-exist table {} from transaction {}. txn_id={}", tableId, txnLabel, txnId);
diff --git a/fe/fe-core/src/main/java/com/starrocks/transaction/TransactionChecker.java b/fe/fe-core/src/main/java/com/starrocks/transaction/TransactionChecker.java
index 5a6a2b39383de4..ac5758eef1bc5a 100644
--- a/fe/fe-core/src/main/java/com/starrocks/transaction/TransactionChecker.java
+++ b/fe/fe-core/src/main/java/com/starrocks/transaction/TransactionChecker.java
@@ -23,6 +23,7 @@
 import com.starrocks.catalog.Tablet;
 import com.starrocks.common.util.concurrent.lock.LockType;
 import com.starrocks.common.util.concurrent.lock.Locker;
+import com.starrocks.server.GlobalStateMgr;
 
 import java.util.ArrayList;
 import java.util.List;
@@ -97,7 +98,8 @@ void debugInfo(StringBuilder sb) {
     public static TransactionChecker create(TransactionState txn, Database db) {
         List<PartitionChecker> partitions = new ArrayList<>();
         for (TableCommitInfo tableCommitInfo : txn.getIdToTableCommitInfos().values()) {
-            OlapTable table = (OlapTable) db.getTable(tableCommitInfo.getTableId());
+            OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(db.getId(), tableCommitInfo.getTableId());
             if (table == null || table.isCloudNativeTableOrMaterializedView()) {
                 continue;
             }
diff --git a/fe/fe-core/src/main/java/com/starrocks/transaction/TransactionCommitFailedException.java b/fe/fe-core/src/main/java/com/starrocks/transaction/TransactionCommitFailedException.java
index b228a571cfcc44..316edb5d40e9f0 100644
--- a/fe/fe-core/src/main/java/com/starrocks/transaction/TransactionCommitFailedException.java
+++ b/fe/fe-core/src/main/java/com/starrocks/transaction/TransactionCommitFailedException.java
@@ -21,7 +21,7 @@ public class TransactionCommitFailedException extends TransactionException {
 
     private static final long serialVersionUID = -2528170792631761535L;
 
-    public static final String FILTER_DATA_IN_STRICT_MODE = "filter data in strict mode";
+    public static final String FILTER_DATA_ERR = "Insert has filtered data";
 
     public TransactionCommitFailedException(String msg) {
         super(msg);
diff --git a/fe/fe-core/src/main/java/com/starrocks/transaction/TransactionState.java b/fe/fe-core/src/main/java/com/starrocks/transaction/TransactionState.java
index 43f5f7974cde67..0d9348b5362c1c 100644
--- a/fe/fe-core/src/main/java/com/starrocks/transaction/TransactionState.java
+++ b/fe/fe-core/src/main/java/com/starrocks/transaction/TransactionState.java
@@ -918,7 +918,7 @@ public boolean allPublishTasksFinishedOrQuorumWaitTimeout(Set<Long> publishError
 
     public boolean checkCanFinish() {
         // finishChecker may require refresh if table/partition is dropped, or index is changed caused by Alter job
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbId);
         if (db == null) {
             // consider txn finished if db is dropped
             return true;
diff --git a/fe/fe-core/src/main/java/com/starrocks/transaction/UpdateDbUsedDataQuotaDaemon.java b/fe/fe-core/src/main/java/com/starrocks/transaction/UpdateDbUsedDataQuotaDaemon.java
index 340852bdc36960..43fdfc3de90b1a 100644
--- a/fe/fe-core/src/main/java/com/starrocks/transaction/UpdateDbUsedDataQuotaDaemon.java
+++ b/fe/fe-core/src/main/java/com/starrocks/transaction/UpdateDbUsedDataQuotaDaemon.java
@@ -61,7 +61,7 @@ private void updateAllDatabaseUsedDataQuota() {
         List<Long> dbIdList = globalStateMgr.getLocalMetastore().getDbIds();
         GlobalTransactionMgr globalTransactionMgr = globalStateMgr.getGlobalTransactionMgr();
         for (Long dbId : dbIdList) {
-            Database db = globalStateMgr.getDb(dbId);
+            Database db = globalStateMgr.getLocalMetastore().getDb(dbId);
             if (db == null) {
                 LOG.warn("Database [" + dbId + "] doese not exist, skip to update database used data quota");
                 continue;
diff --git a/fe/fe-core/src/test/java/com/starrocks/alter/AlterJobV2Test.java b/fe/fe-core/src/test/java/com/starrocks/alter/AlterJobV2Test.java
index 2172b981049cb5..3f896604efd7de 100644
--- a/fe/fe-core/src/test/java/com/starrocks/alter/AlterJobV2Test.java
+++ b/fe/fe-core/src/test/java/com/starrocks/alter/AlterJobV2Test.java
@@ -79,14 +79,14 @@ public static void beforeClass() throws Exception {
         UtFrameUtils.setDefaultConfigForAsyncMVTest(connectContext);
 
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.schema_change_test(k1 int, k2 int, k3 int) " +
-                        "distributed by hash(k1) buckets 3 properties('replication_num' = '1');")
-                .withTable("CREATE TABLE test.segmentv2(k1 int, k2 int, v1 int sum) " +
-                        "distributed by hash(k1) buckets 3 properties('replication_num' = '1');")
-                .withTable("CREATE TABLE test.properties_change_test(k1 int, v1 int) " +
-                        "primary key(k1) distributed by hash(k1) properties('replication_num' = '1');")
-                .withTable("CREATE TABLE modify_column_test(k1 int, k2 int, k3 int) ENGINE = OLAP " +
-                        "DUPLICATE KEY(k1) DISTRIBUTED BY HASH(k1) properties('replication_num' = '1');");
+                    .withTable("CREATE TABLE test.schema_change_test(k1 int, k2 int, k3 int) " +
+                                "distributed by hash(k1) buckets 3 properties('replication_num' = '1');")
+                    .withTable("CREATE TABLE test.segmentv2(k1 int, k2 int, v1 int sum) " +
+                                "distributed by hash(k1) buckets 3 properties('replication_num' = '1');")
+                    .withTable("CREATE TABLE test.properties_change_test(k1 int, v1 int) " +
+                                "primary key(k1) distributed by hash(k1) properties('replication_num' = '1');")
+                    .withTable("CREATE TABLE modify_column_test(k1 int, k2 int, k3 int) ENGINE = OLAP " +
+                                "DUPLICATE KEY(k1) DISTRIBUTED BY HASH(k1) properties('replication_num' = '1');");
     }
 
     @AfterClass
@@ -116,7 +116,7 @@ public void testSchemaChange() throws Exception {
         // 3. check show alter table column
         String showAlterStmtStr = "show alter table column from test;";
         ShowAlterStmt showAlterStmt =
-                (ShowAlterStmt) UtFrameUtils.parseStmtWithNewParser(showAlterStmtStr, connectContext);
+                    (ShowAlterStmt) UtFrameUtils.parseStmtWithNewParser(showAlterStmtStr, connectContext);
         ShowResultSet showResultSet = ShowExecutor.execute(showAlterStmt, connectContext);
         System.out.println(showResultSet.getMetaData());
         System.out.println(showResultSet.getResultRows());
@@ -133,7 +133,7 @@ public void testRollup() throws Exception {
         for (AlterJobV2 alterJobV2 : alterJobs.values()) {
             while (!alterJobV2.getJobState().isFinalState()) {
                 System.out.println(
-                        "alter job " + alterJobV2.getJobId() + " is running. state: " + alterJobV2.getJobState());
+                            "alter job " + alterJobV2.getJobId() + " is running. state: " + alterJobV2.getJobState());
                 Thread.sleep(1000);
             }
             System.out.println("alter job " + alterJobV2.getJobId() + " is done. state: " + alterJobV2.getJobState());
@@ -142,7 +142,7 @@ public void testRollup() throws Exception {
         // 3. check show alter table column
         String showAlterStmtStr = "show alter table rollup from test;";
         ShowAlterStmt showAlterStmt =
-                (ShowAlterStmt) UtFrameUtils.parseStmtWithNewParser(showAlterStmtStr, connectContext);
+                    (ShowAlterStmt) UtFrameUtils.parseStmtWithNewParser(showAlterStmtStr, connectContext);
         ShowResultSet showResultSet = ShowExecutor.execute(showAlterStmt, connectContext);
         System.out.println(showResultSet.getMetaData());
         System.out.println(showResultSet.getResultRows());
@@ -160,7 +160,7 @@ public void testModifyTableProperties() throws Exception {
         // 3. check enable persistent index
         String showCreateTableStr = "show create table test.properties_change_test;";
         ShowCreateTableStmt showCreateTableStmt =
-                (ShowCreateTableStmt) UtFrameUtils.parseStmtWithNewParser(showCreateTableStr, connectContext);
+                    (ShowCreateTableStmt) UtFrameUtils.parseStmtWithNewParser(showCreateTableStr, connectContext);
         ShowResultSet showResultSet = ShowExecutor.execute(showCreateTableStmt, connectContext);
         System.out.println(showResultSet.getMetaData());
         System.out.println(showResultSet.getResultRows());
@@ -175,7 +175,7 @@ public void testModifyTableProperties() throws Exception {
 
         // 5. check enable persistent index
         showCreateTableStmt =
-                (ShowCreateTableStmt) UtFrameUtils.parseStmtWithNewParser(showCreateTableStr, connectContext);
+                    (ShowCreateTableStmt) UtFrameUtils.parseStmtWithNewParser(showCreateTableStr, connectContext);
         showResultSet = ShowExecutor.execute(showCreateTableStmt, connectContext);
         System.out.println(showResultSet.getMetaData());
         System.out.println(showResultSet.getResultRows());
@@ -185,10 +185,10 @@ public void testModifyTableProperties() throws Exception {
     public void testModifyRelatedColumnWithMv() {
         try {
             String sql = "CREATE MATERIALIZED VIEW test.mv2 DISTRIBUTED BY HASH(k1) " +
-                    " BUCKETS 10 REFRESH ASYNC properties('replication_num' = '1') AS SELECT k1, k2 FROM modify_column_test";
+                        " BUCKETS 10 REFRESH ASYNC properties('replication_num' = '1') AS SELECT k1, k2 FROM modify_column_test";
             StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
             GlobalStateMgr.getCurrentState().getLocalMetastore()
-                    .createMaterializedView((CreateMaterializedViewStatement) statementBase);
+                        .createMaterializedView((CreateMaterializedViewStatement) statementBase);
 
             // modify column which define in mv
             String alterStmtStr = "alter table test.modify_column_test modify column k2 varchar(10)";
@@ -196,7 +196,8 @@ public void testModifyRelatedColumnWithMv() {
             DDLStmtExecutor.execute(alterTableStmt, connectContext);
 
             waitForSchemaChangeAlterJobFinish();
-            MaterializedView mv2 = (MaterializedView) GlobalStateMgr.getCurrentState().getDb("test").getTable("mv2");
+            MaterializedView mv2 =
+                        (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("mv2");
             Assert.assertFalse(mv2.isActive());
         } catch (Exception e) {
             e.printStackTrace();
@@ -209,21 +210,21 @@ public void testModifyRelatedColumnWithMv() {
     public void testModifyWithSelectStarMV1() throws Exception {
         try {
             starRocksAssert.withTable("CREATE TABLE modify_column_test3(k1 int, k2 int, k3 int) ENGINE = OLAP " +
-                    "DUPLICATE KEY(k1) DISTRIBUTED BY HASH(k1) properties('replication_num' = '1');");
+                        "DUPLICATE KEY(k1) DISTRIBUTED BY HASH(k1) properties('replication_num' = '1');");
             String sql = "CREATE MATERIALIZED VIEW test.mv3 DISTRIBUTED BY HASH(k1) " +
-                    " BUCKETS 10 REFRESH ASYNC properties('replication_num' = '1') " +
-                    "AS SELECT * FROM modify_column_test3";
+                        " BUCKETS 10 REFRESH ASYNC properties('replication_num' = '1') " +
+                        "AS SELECT * FROM modify_column_test3";
             StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
             GlobalStateMgr.getCurrentState().getLocalMetastore()
-                    .createMaterializedView((CreateMaterializedViewStatement) statementBase);
+                        .createMaterializedView((CreateMaterializedViewStatement) statementBase);
 
             String alterStmtStr = "alter table test.modify_column_test3 modify column k2 varchar(20)";
             AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterStmtStr, connectContext);
             DDLStmtExecutor.execute(alterTableStmt, connectContext);
 
             waitForSchemaChangeAlterJobFinish();
-            MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState()
-                    .getDb("test").getTable("mv3");
+            MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getDb("test").getTable("mv3");
             Assert.assertTrue(!mv.isActive());
         } finally {
             starRocksAssert.dropTable("modify_column_test3");
@@ -235,13 +236,13 @@ public void testModifyWithSelectStarMV1() throws Exception {
     public void testModifyWithSelectStarMV2() throws Exception {
         try {
             starRocksAssert.withTable("CREATE TABLE testModifyWithSelectStarMV2(k1 int, k2 int, k3 int) ENGINE = OLAP " +
-                    "DUPLICATE KEY(k1) DISTRIBUTED BY HASH(k1) properties('replication_num' = '1');");
+                        "DUPLICATE KEY(k1) DISTRIBUTED BY HASH(k1) properties('replication_num' = '1');");
             String sql = "CREATE MATERIALIZED VIEW test.mv6 DISTRIBUTED BY HASH(k1) " +
-                    " BUCKETS 10 REFRESH ASYNC properties('replication_num' = '1') " +
-                    "AS SELECT * FROM testModifyWithSelectStarMV2";
+                        " BUCKETS 10 REFRESH ASYNC properties('replication_num' = '1') " +
+                        "AS SELECT * FROM testModifyWithSelectStarMV2";
             StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
             GlobalStateMgr.getCurrentState().getLocalMetastore()
-                    .createMaterializedView((CreateMaterializedViewStatement) statementBase);
+                        .createMaterializedView((CreateMaterializedViewStatement) statementBase);
 
             String alterStmtStr = "alter table test.testModifyWithSelectStarMV2 add column k4 bigint";
             AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterStmtStr, connectContext);
@@ -249,7 +250,7 @@ public void testModifyWithSelectStarMV2() throws Exception {
 
             waitForSchemaChangeAlterJobFinish();
             MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState()
-                    .getDb("test").getTable("mv6");
+                        .getLocalMetastore().getDb("test").getTable("mv6");
             Assert.assertTrue(mv.isActive());
         } catch (Exception e) {
             e.printStackTrace();
@@ -264,13 +265,13 @@ public void testModifyWithSelectStarMV2() throws Exception {
     public void testModifyWithSelectStarMV3() throws Exception {
         try {
             starRocksAssert.withTable("CREATE TABLE modify_column_test5(k1 int, k2 int, k3 int) ENGINE = OLAP " +
-                    "DUPLICATE KEY(k1) DISTRIBUTED BY HASH(k1) properties('replication_num' = '1');");
+                        "DUPLICATE KEY(k1) DISTRIBUTED BY HASH(k1) properties('replication_num' = '1');");
             String sql = "CREATE MATERIALIZED VIEW test.mv5 DISTRIBUTED BY HASH(k1) " +
-                    " BUCKETS 10 REFRESH ASYNC properties('replication_num' = '1') " +
-                    "AS SELECT * FROM modify_column_test5";
+                        " BUCKETS 10 REFRESH ASYNC properties('replication_num' = '1') " +
+                        "AS SELECT * FROM modify_column_test5";
             StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
             GlobalStateMgr.getCurrentState().getLocalMetastore()
-                    .createMaterializedView((CreateMaterializedViewStatement) statementBase);
+                        .createMaterializedView((CreateMaterializedViewStatement) statementBase);
 
             String alterStmtStr = "alter table test.modify_column_test5 drop column k2";
             AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterStmtStr, connectContext);
@@ -278,7 +279,7 @@ public void testModifyWithSelectStarMV3() throws Exception {
 
             waitForSchemaChangeAlterJobFinish();
             MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState()
-                    .getDb("test").getTable("mv5");
+                        .getLocalMetastore().getDb("test").getTable("mv5");
             Assert.assertTrue(!mv.isActive());
         } catch (Exception e) {
             Assert.fail();
@@ -291,23 +292,24 @@ public void testModifyWithSelectStarMV3() throws Exception {
     public void testModifyWithExpr() throws Exception {
         try {
             starRocksAssert.withTable("CREATE TABLE modify_column_test4(k1 int, k2 int, k3 int) ENGINE = OLAP " +
-                    "DUPLICATE KEY(k1) DISTRIBUTED BY HASH(k1) properties('replication_num' = '1');");
+                        "DUPLICATE KEY(k1) DISTRIBUTED BY HASH(k1) properties('replication_num' = '1');");
             String sql = "CREATE MATERIALIZED VIEW test.mv4 DISTRIBUTED BY HASH(k1) " +
-                    " BUCKETS 10 REFRESH ASYNC properties('replication_num' = '1') AS SELECT k1, k2 + 1 FROM modify_column_test4";
+                        " BUCKETS 10 REFRESH ASYNC properties('replication_num' = '1')" +
+                        " AS SELECT k1, k2 + 1 FROM modify_column_test4";
             StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
             GlobalStateMgr.getCurrentState().getLocalMetastore()
-                    .createMaterializedView((CreateMaterializedViewStatement) statementBase);
+                        .createMaterializedView((CreateMaterializedViewStatement) statementBase);
 
             {
                 // modify column which not define in mv
                 String alterStmtStr = "alter table test.modify_column_test4 modify column k3 varchar(10)";
                 AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterStmtStr,
-                        connectContext);
+                            connectContext);
                 DDLStmtExecutor.execute(alterTableStmt, connectContext);
 
                 waitForSchemaChangeAlterJobFinish();
                 MaterializedView mv = (MaterializedView) GlobalStateMgr
-                        .getCurrentState().getDb("test").getTable("mv4");
+                            .getCurrentState().getLocalMetastore().getDb("test").getTable("mv4");
                 Assert.assertTrue(mv.isActive());
             }
 
@@ -315,12 +317,12 @@ public void testModifyWithExpr() throws Exception {
                 // modify column which define in mv
                 String alterStmtStr = "alter table test.modify_column_test4 modify column k2 varchar(30) ";
                 AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterStmtStr,
-                        connectContext);
+                            connectContext);
                 DDLStmtExecutor.execute(alterTableStmt, connectContext);
 
                 waitForSchemaChangeAlterJobFinish();
                 MaterializedView mv = (MaterializedView) GlobalStateMgr
-                        .getCurrentState().getDb("test").getTable("mv4");
+                            .getCurrentState().getLocalMetastore().getDb("test").getTable("mv4");
                 Assert.assertFalse(mv.isActive());
                 System.out.println(mv.getInactiveReason());
                 Assert.assertTrue(mv.getInactiveReason().contains("base table schema changed for columns: k2"));
@@ -337,10 +339,10 @@ public void testModifyWithExpr() throws Exception {
     public void testModifyUnRelatedColumnWithMv() {
         try {
             String sql = "CREATE MATERIALIZED VIEW test.mv1 DISTRIBUTED BY HASH(k1) " +
-                    " BUCKETS 10 REFRESH ASYNC properties('replication_num' = '1') AS SELECT k1, k2 FROM modify_column_test";
+                        " BUCKETS 10 REFRESH ASYNC properties('replication_num' = '1') AS SELECT k1, k2 FROM modify_column_test";
             StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
             GlobalStateMgr.getCurrentState().getLocalMetastore()
-                    .createMaterializedView((CreateMaterializedViewStatement) statementBase);
+                        .createMaterializedView((CreateMaterializedViewStatement) statementBase);
 
             // modify column which not define in mv
             String alterStmtStr = "alter table test.modify_column_test modify column k3 varchar(10)";
@@ -348,7 +350,8 @@ public void testModifyUnRelatedColumnWithMv() {
             DDLStmtExecutor.execute(alterTableStmt, connectContext);
 
             waitForSchemaChangeAlterJobFinish();
-            MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState().getDb("test").getTable("mv1");
+            MaterializedView mv =
+                        (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("mv1");
             Assert.assertTrue(mv.isActive());
         } catch (Exception e) {
             e.printStackTrace();
@@ -359,7 +362,7 @@ public void testModifyUnRelatedColumnWithMv() {
     @Test
     public void test() throws Exception {
         starRocksAssert.withTable("CREATE TABLE test.schema_change_test_load(k1 int, k2 int, k3 int) " +
-                "distributed by hash(k1) buckets 3 properties('replication_num' = '1');");
+                    "distributed by hash(k1) buckets 3 properties('replication_num' = '1');");
 
         String alterStmtStr = "alter table test.schema_change_test_load add column k4 int default '1'";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterStmtStr, connectContext);
@@ -377,7 +380,7 @@ public void test() throws Exception {
         srMetaBlockReader.close();
 
         AlterJobV2 alterJobV2New =
-                GlobalStateMgr.getCurrentState().getSchemaChangeHandler().getAlterJobsV2().get(alterJobV2Old.jobId);
+                    GlobalStateMgr.getCurrentState().getSchemaChangeHandler().getAlterJobsV2().get(alterJobV2Old.jobId);
 
         Assert.assertEquals(alterJobV2Old.jobId, alterJobV2New.jobId);
     }
diff --git a/fe/fe-core/src/test/java/com/starrocks/alter/AlterTableTest.java b/fe/fe-core/src/test/java/com/starrocks/alter/AlterTableTest.java
index 2f91d20bea36d8..b481dc1bd495c8 100644
--- a/fe/fe-core/src/test/java/com/starrocks/alter/AlterTableTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/alter/AlterTableTest.java
@@ -71,25 +71,25 @@ public static void beforeClass() throws Exception {
     @Test(expected = AnalysisException.class)
     public void testAlterTableBucketSize() throws Exception {
         starRocksAssert.useDatabase("test").withTable("CREATE TABLE test_alter_bucket_size (\n" +
-                "event_day DATE,\n" +
-                "site_id INT DEFAULT '10',\n" +
-                "city_code VARCHAR(100),\n" +
-                "user_name VARCHAR(32) DEFAULT '',\n" +
-                "pv BIGINT DEFAULT '0'\n" +
-                ")\n" +
-                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                "PARTITION BY RANGE(event_day)(\n" +
-                "PARTITION p20200321 VALUES LESS THAN (\"2020-03-22\"),\n" +
-                "PARTITION p20200322 VALUES LESS THAN (\"2020-03-23\"),\n" +
-                "PARTITION p20200323 VALUES LESS THAN (\"2020-03-24\"),\n" +
-                "PARTITION p20200324 VALUES LESS THAN MAXVALUE\n" +
-                ")\n" +
-                "DISTRIBUTED BY RANDOM\n" +
-                "PROPERTIES(\n" +
-                "\t\"replication_num\" = \"1\",\n" +
-                "    \"storage_medium\" = \"SSD\",\n" +
-                "    \"storage_cooldown_ttl\" = \"1 day\"\n" +
-                ");");
+                    "event_day DATE,\n" +
+                    "site_id INT DEFAULT '10',\n" +
+                    "city_code VARCHAR(100),\n" +
+                    "user_name VARCHAR(32) DEFAULT '',\n" +
+                    "pv BIGINT DEFAULT '0'\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                    "PARTITION BY RANGE(event_day)(\n" +
+                    "PARTITION p20200321 VALUES LESS THAN (\"2020-03-22\"),\n" +
+                    "PARTITION p20200322 VALUES LESS THAN (\"2020-03-23\"),\n" +
+                    "PARTITION p20200323 VALUES LESS THAN (\"2020-03-24\"),\n" +
+                    "PARTITION p20200324 VALUES LESS THAN MAXVALUE\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY RANDOM\n" +
+                    "PROPERTIES(\n" +
+                    "\t\"replication_num\" = \"1\",\n" +
+                    "    \"storage_medium\" = \"SSD\",\n" +
+                    "    \"storage_cooldown_ttl\" = \"1 day\"\n" +
+                    ");");
         ConnectContext ctx = starRocksAssert.getCtx();
         String sql = "ALTER TABLE test_alter_bucket_size SET (\"bucket_size\" = \"-1\");";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
@@ -99,31 +99,31 @@ public void testAlterTableBucketSize() throws Exception {
     @Test
     public void testAlterTableStorageCoolDownTTL() throws Exception {
         starRocksAssert.useDatabase("test").withTable("CREATE TABLE test_alter_cool_down_ttl (\n" +
-                "event_day DATE,\n" +
-                "site_id INT DEFAULT '10',\n" +
-                "city_code VARCHAR(100),\n" +
-                "user_name VARCHAR(32) DEFAULT '',\n" +
-                "pv BIGINT DEFAULT '0'\n" +
-                ")\n" +
-                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                "PARTITION BY RANGE(event_day)(\n" +
-                "PARTITION p20200321 VALUES LESS THAN (\"2020-03-22\"),\n" +
-                "PARTITION p20200322 VALUES LESS THAN (\"2020-03-23\"),\n" +
-                "PARTITION p20200323 VALUES LESS THAN (\"2020-03-24\"),\n" +
-                "PARTITION p20200324 VALUES LESS THAN MAXVALUE\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(event_day, site_id)\n" +
-                "PROPERTIES(\n" +
-                "\t\"replication_num\" = \"1\",\n" +
-                "    \"storage_medium\" = \"SSD\",\n" +
-                "    \"storage_cooldown_ttl\" = \"1 day\"\n" +
-                ");");
+                    "event_day DATE,\n" +
+                    "site_id INT DEFAULT '10',\n" +
+                    "city_code VARCHAR(100),\n" +
+                    "user_name VARCHAR(32) DEFAULT '',\n" +
+                    "pv BIGINT DEFAULT '0'\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                    "PARTITION BY RANGE(event_day)(\n" +
+                    "PARTITION p20200321 VALUES LESS THAN (\"2020-03-22\"),\n" +
+                    "PARTITION p20200322 VALUES LESS THAN (\"2020-03-23\"),\n" +
+                    "PARTITION p20200323 VALUES LESS THAN (\"2020-03-24\"),\n" +
+                    "PARTITION p20200324 VALUES LESS THAN MAXVALUE\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(event_day, site_id)\n" +
+                    "PROPERTIES(\n" +
+                    "\t\"replication_num\" = \"1\",\n" +
+                    "    \"storage_medium\" = \"SSD\",\n" +
+                    "    \"storage_cooldown_ttl\" = \"1 day\"\n" +
+                    ");");
         ConnectContext ctx = starRocksAssert.getCtx();
         String sql = "ALTER TABLE test_alter_cool_down_ttl SET (\"storage_cooldown_ttl\" = \"3 day\");";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().alterTable(ctx, alterTableStmt);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test").getTable("test_alter_cool_down_ttl");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("test_alter_cool_down_ttl");
         OlapTable olapTable = (OlapTable) table;
         String storageCooldownTtl = olapTable.getTableProperty().getProperties().get("storage_cooldown_ttl");
         Assert.assertEquals("3 day", storageCooldownTtl);
@@ -134,25 +134,25 @@ public void testAlterTableStorageCoolDownTTL() throws Exception {
     @Test(expected = AnalysisException.class)
     public void testAlterTableStorageCoolDownTTLExcept() throws Exception {
         starRocksAssert.useDatabase("test").withTable("CREATE TABLE test_alter_cool_down_ttl_2 (\n" +
-                "event_day DATE,\n" +
-                "site_id INT DEFAULT '10',\n" +
-                "city_code VARCHAR(100),\n" +
-                "user_name VARCHAR(32) DEFAULT '',\n" +
-                "pv BIGINT DEFAULT '0'\n" +
-                ")\n" +
-                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                "PARTITION BY RANGE(event_day)(\n" +
-                "PARTITION p20200321 VALUES LESS THAN (\"2020-03-22\"),\n" +
-                "PARTITION p20200322 VALUES LESS THAN (\"2020-03-23\"),\n" +
-                "PARTITION p20200323 VALUES LESS THAN (\"2020-03-24\"),\n" +
-                "PARTITION p20200324 VALUES LESS THAN MAXVALUE\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(event_day, site_id)\n" +
-                "PROPERTIES(\n" +
-                "\t\"replication_num\" = \"1\",\n" +
-                "    \"storage_medium\" = \"SSD\",\n" +
-                "    \"storage_cooldown_ttl\" = \"1 day\"\n" +
-                ");");
+                    "event_day DATE,\n" +
+                    "site_id INT DEFAULT '10',\n" +
+                    "city_code VARCHAR(100),\n" +
+                    "user_name VARCHAR(32) DEFAULT '',\n" +
+                    "pv BIGINT DEFAULT '0'\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                    "PARTITION BY RANGE(event_day)(\n" +
+                    "PARTITION p20200321 VALUES LESS THAN (\"2020-03-22\"),\n" +
+                    "PARTITION p20200322 VALUES LESS THAN (\"2020-03-23\"),\n" +
+                    "PARTITION p20200323 VALUES LESS THAN (\"2020-03-24\"),\n" +
+                    "PARTITION p20200324 VALUES LESS THAN MAXVALUE\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(event_day, site_id)\n" +
+                    "PROPERTIES(\n" +
+                    "\t\"replication_num\" = \"1\",\n" +
+                    "    \"storage_medium\" = \"SSD\",\n" +
+                    "    \"storage_cooldown_ttl\" = \"1 day\"\n" +
+                    ");");
         ConnectContext ctx = starRocksAssert.getCtx();
         String sql = "ALTER TABLE test_alter_cool_down_ttl_2 SET (\"storage_cooldown_ttl\" = \"abc\");";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
@@ -162,27 +162,28 @@ public void testAlterTableStorageCoolDownTTLExcept() throws Exception {
     @Test
     public void testAlterTableStorageCoolDownTTLPartition() throws Exception {
         starRocksAssert.useDatabase("test").withTable("CREATE TABLE test_alter_cool_down_ttl_partition (\n" +
-                "event_day DATE,\n" +
-                "site_id INT DEFAULT '10',\n" +
-                "city_code VARCHAR(100),\n" +
-                "user_name VARCHAR(32) DEFAULT '',\n" +
-                "pv BIGINT DEFAULT '0'\n" +
-                ")\n" +
-                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                "PARTITION BY RANGE(event_day)(\n" +
-                "PARTITION p20200321 VALUES LESS THAN (\"2020-03-22\"),\n" +
-                "PARTITION p20200322 VALUES LESS THAN (\"2020-03-23\"),\n" +
-                "PARTITION p20200323 VALUES LESS THAN (\"2020-03-24\"),\n" +
-                "PARTITION p20200324 VALUES LESS THAN MAXVALUE\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(event_day, site_id)\n" +
-                "PROPERTIES(\n" +
-                "\t\"replication_num\" = \"1\",\n" +
-                "    \"storage_medium\" = \"SSD\",\n" +
-                "    \"storage_cooldown_ttl\" = \"1 day\"\n" +
-                ");");
+                    "event_day DATE,\n" +
+                    "site_id INT DEFAULT '10',\n" +
+                    "city_code VARCHAR(100),\n" +
+                    "user_name VARCHAR(32) DEFAULT '',\n" +
+                    "pv BIGINT DEFAULT '0'\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                    "PARTITION BY RANGE(event_day)(\n" +
+                    "PARTITION p20200321 VALUES LESS THAN (\"2020-03-22\"),\n" +
+                    "PARTITION p20200322 VALUES LESS THAN (\"2020-03-23\"),\n" +
+                    "PARTITION p20200323 VALUES LESS THAN (\"2020-03-24\"),\n" +
+                    "PARTITION p20200324 VALUES LESS THAN MAXVALUE\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(event_day, site_id)\n" +
+                    "PROPERTIES(\n" +
+                    "\t\"replication_num\" = \"1\",\n" +
+                    "    \"storage_medium\" = \"SSD\",\n" +
+                    "    \"storage_cooldown_ttl\" = \"1 day\"\n" +
+                    ");");
         ConnectContext ctx = starRocksAssert.getCtx();
-        Table table = GlobalStateMgr.getCurrentState().getDb("test").getTable("test_alter_cool_down_ttl_partition");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_alter_cool_down_ttl_partition");
         OlapTable olapTable = (OlapTable) table;
         RangePartitionInfo rangePartitionInfo = (RangePartitionInfo) olapTable.getPartitionInfo();
         DataProperty p20200321 = rangePartitionInfo.getDataProperty(olapTable.getPartition("p20200321").getId());
@@ -195,7 +196,7 @@ public void testAlterTableStorageCoolDownTTLPartition() throws Exception {
         Assert.assertEquals("9999-12-31 23:59:59", TimeUtils.longToTimeString(p20200324.getCooldownTimeMs()));
 
         String sql = "ALTER TABLE test_alter_cool_down_ttl_partition\n" +
-                "MODIFY PARTITION (*) SET(\"storage_cooldown_ttl\" = \"2 day\", \"storage_medium\" = \"SSD\");";
+                    "MODIFY PARTITION (*) SET(\"storage_cooldown_ttl\" = \"2 day\", \"storage_medium\" = \"SSD\");";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
         AlterJobExecutor alterJobExecutor = new AlterJobExecutor();
         alterJobExecutor.process(alterTableStmt, ctx);
@@ -214,33 +215,34 @@ public void testAlterTableStorageCoolDownTTLPartition() throws Exception {
     @Test
     public void testAlterTablePartitionTTLInvalid() throws Exception {
         starRocksAssert.useDatabase("test").withTable("CREATE TABLE test_partition_live_number (\n" +
-                "event_day DATE,\n" +
-                "site_id INT DEFAULT '10',\n" +
-                "city_code VARCHAR(100),\n" +
-                "user_name VARCHAR(32) DEFAULT '',\n" +
-                "pv BIGINT DEFAULT '0'\n" +
-                ")\n" +
-                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                "PARTITION BY RANGE(event_day)(\n" +
-                "PARTITION p20200321 VALUES LESS THAN (\"2020-03-22\"),\n" +
-                "PARTITION p20200322 VALUES LESS THAN (\"2020-03-23\"),\n" +
-                "PARTITION p20200323 VALUES LESS THAN (\"2020-03-24\"),\n" +
-                "PARTITION p20200324 VALUES LESS THAN MAXVALUE\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(event_day, site_id)\n" +
-                "PROPERTIES(\n" +
-                "\t\"replication_num\" = \"1\",\n" +
-                "    \"storage_medium\" = \"SSD\",\n" +
-                "    \"partition_live_number\" = \"2\"\n" +
-                ");");
+                    "event_day DATE,\n" +
+                    "site_id INT DEFAULT '10',\n" +
+                    "city_code VARCHAR(100),\n" +
+                    "user_name VARCHAR(32) DEFAULT '',\n" +
+                    "pv BIGINT DEFAULT '0'\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                    "PARTITION BY RANGE(event_day)(\n" +
+                    "PARTITION p20200321 VALUES LESS THAN (\"2020-03-22\"),\n" +
+                    "PARTITION p20200322 VALUES LESS THAN (\"2020-03-23\"),\n" +
+                    "PARTITION p20200323 VALUES LESS THAN (\"2020-03-24\"),\n" +
+                    "PARTITION p20200324 VALUES LESS THAN MAXVALUE\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(event_day, site_id)\n" +
+                    "PROPERTIES(\n" +
+                    "\t\"replication_num\" = \"1\",\n" +
+                    "    \"storage_medium\" = \"SSD\",\n" +
+                    "    \"partition_live_number\" = \"2\"\n" +
+                    ");");
         ConnectContext ctx = starRocksAssert.getCtx();
         String sql = "ALTER TABLE test_partition_live_number SET(\"partition_live_number\" = \"-1\");";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().alterTable(ctx, alterTableStmt);
         Set<Pair<Long, Long>> ttlPartitionInfo = GlobalStateMgr.getCurrentState()
-                .getDynamicPartitionScheduler().getTtlPartitionInfo();
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("test_partition_live_number");
+                    .getDynamicPartitionScheduler().getTtlPartitionInfo();
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table =
+                    GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_partition_live_number");
         Assert.assertFalse(ttlPartitionInfo.contains(new Pair<>(db.getId(), table.getId())));
         sql = "ALTER TABLE test_partition_live_number SET(\"partition_live_number\" = \"1\");";
         alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
@@ -251,65 +253,67 @@ public void testAlterTablePartitionTTLInvalid() throws Exception {
     @Test
     public void testAlterTablePartitionStorageMedium() throws Exception {
         starRocksAssert.useDatabase("test").withTable("CREATE TABLE test_partition_storage_medium (\n" +
-                "event_day DATE,\n" +
-                "site_id INT DEFAULT '10',\n" +
-                "city_code VARCHAR(100),\n" +
-                "user_name VARCHAR(32) DEFAULT '',\n" +
-                "pv BIGINT DEFAULT '0'\n" +
-                ")\n" +
-                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                "PARTITION BY RANGE(event_day)(\n" +
-                "PARTITION p20200321 VALUES LESS THAN (\"2020-03-22\"),\n" +
-                "PARTITION p20200322 VALUES LESS THAN (\"2020-03-23\"),\n" +
-                "PARTITION p20200323 VALUES LESS THAN (\"2020-03-24\"),\n" +
-                "PARTITION p20200324 VALUES LESS THAN MAXVALUE\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(event_day, site_id)\n" +
-                "PROPERTIES(\n" +
-                "\"replication_num\" = \"1\"\n" +
-                ");");
+                    "event_day DATE,\n" +
+                    "site_id INT DEFAULT '10',\n" +
+                    "city_code VARCHAR(100),\n" +
+                    "user_name VARCHAR(32) DEFAULT '',\n" +
+                    "pv BIGINT DEFAULT '0'\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                    "PARTITION BY RANGE(event_day)(\n" +
+                    "PARTITION p20200321 VALUES LESS THAN (\"2020-03-22\"),\n" +
+                    "PARTITION p20200322 VALUES LESS THAN (\"2020-03-23\"),\n" +
+                    "PARTITION p20200323 VALUES LESS THAN (\"2020-03-24\"),\n" +
+                    "PARTITION p20200324 VALUES LESS THAN MAXVALUE\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(event_day, site_id)\n" +
+                    "PROPERTIES(\n" +
+                    "\"replication_num\" = \"1\"\n" +
+                    ");");
         ConnectContext ctx = starRocksAssert.getCtx();
         String sql = "ALTER TABLE test_partition_storage_medium SET(\"default.storage_medium\" = \"SSD\");";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().alterTable(ctx, alterTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable olapTable = (OlapTable) db.getTable("test_partition_storage_medium");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "test_partition_storage_medium");
         Assert.assertTrue(olapTable.getStorageMedium().equals("SSD"));
     }
 
     @Test
     public void testAlterTableStorageType() throws Exception {
         starRocksAssert.useDatabase("test").withTable("CREATE TABLE test_storage_type (\n" +
-                "event_day DATE,\n" +
-                "site_id INT DEFAULT '10',\n" +
-                "city_code VARCHAR(100),\n" +
-                "user_name VARCHAR(32) DEFAULT '',\n" +
-                "pv BIGINT DEFAULT '2'\n" +
-                ")\n" +
-                "PRIMARY KEY(event_day, site_id, city_code, user_name)\n" +
-                "DISTRIBUTED BY HASH(event_day, site_id)\n" +
-                "PROPERTIES(\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"storage_type\" = \"column_with_row\"\n" +
-                ");");
+                    "event_day DATE,\n" +
+                    "site_id INT DEFAULT '10',\n" +
+                    "city_code VARCHAR(100),\n" +
+                    "user_name VARCHAR(32) DEFAULT '',\n" +
+                    "pv BIGINT DEFAULT '2'\n" +
+                    ")\n" +
+                    "PRIMARY KEY(event_day, site_id, city_code, user_name)\n" +
+                    "DISTRIBUTED BY HASH(event_day, site_id)\n" +
+                    "PROPERTIES(\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"storage_type\" = \"column_with_row\"\n" +
+                    ");");
         ConnectContext ctx = starRocksAssert.getCtx();
 
         String sql1 = "ALTER TABLE test_storage_type SET(\"storage_type\" = \"column\");";
         AnalysisException e1 =
-                Assert.assertThrows(AnalysisException.class, () -> UtFrameUtils.parseStmtWithNewParser(sql1, ctx));
+                    Assert.assertThrows(AnalysisException.class, () -> UtFrameUtils.parseStmtWithNewParser(sql1, ctx));
         Assert.assertTrue(e1.getMessage().contains("Can't change storage type"));
         String sql2 = "ALTER TABLE test_storage_type SET(\"storage_type\" = \"column_with_row\");";
         AnalysisException e2 =
-                Assert.assertThrows(AnalysisException.class, () -> UtFrameUtils.parseStmtWithNewParser(sql2, ctx));
+                    Assert.assertThrows(AnalysisException.class, () -> UtFrameUtils.parseStmtWithNewParser(sql2, ctx));
         Assert.assertTrue(e2.getMessage().contains("Can't change storage type"));
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable olapTable = (OlapTable) db.getTable("test_storage_type");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "test_storage_type");
         Assert.assertTrue(olapTable.getStorageType().equals(TStorageType.COLUMN_WITH_ROW));
     }
 
     public void testAlterTableLocationProp() throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         // add label to backend
         SystemInfoService systemInfoService = GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo();
@@ -317,22 +321,22 @@ public void testAlterTableLocationProp() throws Exception {
         List<Long> backendIds = systemInfoService.getBackendIds();
         Backend backend = systemInfoService.getBackend(backendIds.get(0));
         String modifyBackendPropSqlStr = "alter system modify backend '" + backend.getHost() +
-                ":" + backend.getHeartbeatPort() + "' set ('" +
-                AlterSystemStmtAnalyzer.PROP_KEY_LOCATION + "' = 'rack:rack1')";
+                    ":" + backend.getHeartbeatPort() + "' set ('" +
+                    AlterSystemStmtAnalyzer.PROP_KEY_LOCATION + "' = 'rack:rack1')";
         DDLStmtExecutor.execute(UtFrameUtils.parseStmtWithNewParser(modifyBackendPropSqlStr, connectContext),
-                connectContext);
+                    connectContext);
 
         String sql = "CREATE TABLE test.`test_location_alter` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 2\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\",\n" +
-                "    \"in_memory\" = \"false\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 2\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\",\n" +
+                    "    \"in_memory\" = \"false\"\n" +
+                    ");";
         starRocksAssert.withTable(sql);
 
         UtFrameUtils.PseudoJournalReplayer.resetFollowerJournalQueue();
@@ -341,48 +345,50 @@ public void testAlterTableLocationProp() throws Exception {
 
         // ** test alter table location to rack:*
         sql = "ALTER TABLE test.`test_location_alter` SET ('" +
-                PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "' = 'rack:*');";
+                    PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "' = 'rack:*');";
         DDLStmtExecutor.execute(UtFrameUtils.parseStmtWithNewParser(sql, connectContext),
-                connectContext);
-        Assert.assertEquals("rack", ((OlapTable) testDb.getTable("test_location_alter"))
-                .getLocation().keySet().stream().findFirst().get());
-        Assert.assertEquals("*", ((OlapTable) testDb.getTable("test_location_alter"))
-                .getLocation().get("rack").stream().findFirst().get());
+                    connectContext);
+        Assert.assertEquals("rack", ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), "test_location_alter"))
+                    .getLocation().keySet().stream().findFirst().get());
+        Assert.assertEquals("*", ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), "test_location_alter"))
+                    .getLocation().get("rack").stream().findFirst().get());
 
         // ** test alter table location to nil
         sql = "ALTER TABLE test.`test_location_alter` SET ('" +
-                PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "' = '');";
+                    PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "' = '');";
         DDLStmtExecutor.execute(UtFrameUtils.parseStmtWithNewParser(sql, connectContext),
-                connectContext);
-        Assert.assertNull(((OlapTable) testDb.getTable("test_location_alter"))
-                .getLocation());
+                    connectContext);
+        Assert.assertNull(((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), "test_location_alter"))
+                    .getLocation());
 
         // ** test replay from edit log: alter to rack:*
         LocalMetastore localMetastoreFollower = new LocalMetastore(GlobalStateMgr.getCurrentState(), null, null);
         localMetastoreFollower.load(initialImage.getMetaBlockReader());
         ModifyTablePropertyOperationLog info = (ModifyTablePropertyOperationLog)
-                UtFrameUtils.PseudoJournalReplayer.replayNextJournal(OperationType.OP_ALTER_TABLE_PROPERTIES);
+                    UtFrameUtils.PseudoJournalReplayer.replayNextJournal(OperationType.OP_ALTER_TABLE_PROPERTIES);
         localMetastoreFollower.replayModifyTableProperty(OperationType.OP_ALTER_TABLE_PROPERTIES, info);
         OlapTable olapTable = (OlapTable) localMetastoreFollower.getDb("test")
-                .getTable("test_location_alter");
+                    .getTable("test_location_alter");
         System.out.println(olapTable.getLocation());
         Assert.assertEquals(1, olapTable.getLocation().size());
         Assert.assertTrue(olapTable.getLocation().containsKey("rack"));
 
-
         // ** test replay from edit log: alter to nil
         info = (ModifyTablePropertyOperationLog)
-                UtFrameUtils.PseudoJournalReplayer.replayNextJournal(OperationType.OP_ALTER_TABLE_PROPERTIES);
+                    UtFrameUtils.PseudoJournalReplayer.replayNextJournal(OperationType.OP_ALTER_TABLE_PROPERTIES);
         localMetastoreFollower.replayModifyTableProperty(OperationType.OP_ALTER_TABLE_PROPERTIES, info);
         olapTable = (OlapTable) localMetastoreFollower.getDb("test")
-                .getTable("test_location_alter");
+                    .getTable("test_location_alter");
         System.out.println(olapTable.getLocation());
         Assert.assertNull(olapTable.getLocation());
     }
 
     @Test
     public void testAlterColocateTableLocationProp() throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         // add label to backend
         SystemInfoService systemInfoService = GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo();
@@ -390,29 +396,30 @@ public void testAlterColocateTableLocationProp() throws Exception {
         List<Long> backendIds = systemInfoService.getBackendIds();
         Backend backend = systemInfoService.getBackend(backendIds.get(0));
         String modifyBackendPropSqlStr = "alter system modify backend '" + backend.getHost() +
-                ":" + backend.getHeartbeatPort() + "' set ('" +
-                AlterSystemStmtAnalyzer.PROP_KEY_LOCATION + "' = 'rack:rack1')";
+                    ":" + backend.getHeartbeatPort() + "' set ('" +
+                    AlterSystemStmtAnalyzer.PROP_KEY_LOCATION + "' = 'rack:rack1')";
         DDLStmtExecutor.execute(UtFrameUtils.parseStmtWithNewParser(modifyBackendPropSqlStr, connectContext),
-                connectContext);
+                    connectContext);
 
         String sql = "CREATE TABLE test.`test_location_colocate_alter1` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 2\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\",\n" +
-                "    \"colocate_with\" = \"cg1\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 2\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\",\n" +
+                    "    \"colocate_with\" = \"cg1\"\n" +
+                    ");";
         starRocksAssert.withTable(sql);
 
-        OlapTable olapTable = (OlapTable) testDb.getTable("test_location_colocate_alter1");
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), "test_location_colocate_alter1");
         Assert.assertNull(olapTable.getLocation());
 
         sql = "ALTER TABLE test.`test_location_colocate_alter1` SET ('" +
-                PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "' = 'rack:*');";
+                    PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "' = 'rack:*');";
         try {
             DDLStmtExecutor.execute(UtFrameUtils.parseStmtWithNewParser(sql, connectContext), connectContext);
         } catch (DdlException e) {
@@ -422,7 +429,7 @@ public void testAlterColocateTableLocationProp() throws Exception {
 
     @Test
     public void testAlterLocationPropTableToColocate() throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         // add label to backend
         SystemInfoService systemInfoService = GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo();
@@ -430,28 +437,29 @@ public void testAlterLocationPropTableToColocate() throws Exception {
         List<Long> backendIds = systemInfoService.getBackendIds();
         Backend backend = systemInfoService.getBackend(backendIds.get(0));
         String modifyBackendPropSqlStr = "alter system modify backend '" + backend.getHost() +
-                ":" + backend.getHeartbeatPort() + "' set ('" +
-                AlterSystemStmtAnalyzer.PROP_KEY_LOCATION + "' = 'rack:rack1')";
+                    ":" + backend.getHeartbeatPort() + "' set ('" +
+                    AlterSystemStmtAnalyzer.PROP_KEY_LOCATION + "' = 'rack:rack1')";
         DDLStmtExecutor.execute(UtFrameUtils.parseStmtWithNewParser(modifyBackendPropSqlStr, connectContext),
-                connectContext);
+                    connectContext);
 
         String sql = "CREATE TABLE test.`test_location_colocate_alter2` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 2\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 2\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ");";
         starRocksAssert.withTable(sql);
 
-        OlapTable olapTable = (OlapTable) testDb.getTable("test_location_colocate_alter2");
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), "test_location_colocate_alter2");
         Assert.assertTrue(olapTable.getLocation().containsKey("*"));
 
         sql = "ALTER TABLE test.`test_location_colocate_alter1` SET ('" +
-                PropertyAnalyzer.PROPERTIES_COLOCATE_WITH + "' = 'cg1');";
+                    PropertyAnalyzer.PROPERTIES_COLOCATE_WITH + "' = 'cg1');";
         try {
             DDLStmtExecutor.execute(UtFrameUtils.parseStmtWithNewParser(sql, connectContext), connectContext);
         } catch (DdlException e) {
diff --git a/fe/fe-core/src/test/java/com/starrocks/alter/AlterTest.java b/fe/fe-core/src/test/java/com/starrocks/alter/AlterTest.java
index bcd73343f8d729..f04612e80dc1be 100644
--- a/fe/fe-core/src/test/java/com/starrocks/alter/AlterTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/alter/AlterTest.java
@@ -144,107 +144,107 @@ public static void beforeClass() throws Exception {
         starRocksAssert = new StarRocksAssert(connectContext);
 
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.tbl1\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values less than('2020-02-01'),\n" +
-                        "    PARTITION p2 values less than('2020-03-01')\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');")
-
-                .withTable("CREATE TABLE test.tbl2\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH (k1) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');")
-
-                .withTable("CREATE TABLE test.tbl3\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values less than('2020-02-01'),\n" +
-                        "    PARTITION p2 values less than('2020-03-01')\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');")
-
-                .withTable("CREATE TABLE test.tbl4\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values less than('2020-02-01'),\n" +
-                        "    PARTITION p2 values less than('2020-03-01'),\n" +
-                        "    PARTITION p3 values less than('2020-04-01'),\n" +
-                        "    PARTITION p4 values less than('2020-05-01')\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES" +
-                        "(" +
-                        "    'replication_num' = '1',\n" +
-                        "    'in_memory' = 'false',\n" +
-                        "    'storage_medium' = 'SSD',\n" +
-                        "    'storage_cooldown_time' = '9999-12-31 00:00:00'\n" +
-                        ");")
-                .withTable("CREATE TABLE t_recharge_detail(\n" +
-                        "    id bigint  ,\n" +
-                        "    user_id  bigint  ,\n" +
-                        "    recharge_money decimal(32,2) , \n" +
-                        "    province varchar(20) not null,\n" +
-                        "    dt varchar(20) not null\n" +
-                        ") ENGINE=OLAP\n" +
-                        "DUPLICATE KEY(id)\n" +
-                        "PARTITION BY LIST (dt,province) (\n" +
-                        "   PARTITION p1 VALUES IN ((\"2022-04-01\", \"beijing\")),\n" +
-                        "   PARTITION p2 VALUES IN ((\"2022-04-01\", \"shanghai\"))\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(`id`) BUCKETS 10 \n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\",\n" +
-                        "\"in_memory\" = \"false\"\n" +
-                        ");")
-                .withTable("CREATE TABLE test.site_access_date_trunc (\n" +
-                        "    event_day DATETIME NOT NULL,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY date_trunc('day', event_day)\n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id)\n" +
-                        "PROPERTIES(\n" +
-                        "    \"replication_num\" = \"1\"\n" +
-                        ");")
-                .withTable("CREATE TABLE site_access_time_slice (\n" +
-                        "    event_day datetime,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY time_slice(event_day, interval 1 day)\n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
-                        "PROPERTIES(\n" +
-                        "    \"partition_live_number\" = \"3\",\n" +
-                        "    \"replication_num\" = \"1\"\n" +
-                        ");");
+                    .withTable("CREATE TABLE test.tbl1\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values less than('2020-02-01'),\n" +
+                                "    PARTITION p2 values less than('2020-03-01')\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');")
+
+                    .withTable("CREATE TABLE test.tbl2\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH (k1) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');")
+
+                    .withTable("CREATE TABLE test.tbl3\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values less than('2020-02-01'),\n" +
+                                "    PARTITION p2 values less than('2020-03-01')\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');")
+
+                    .withTable("CREATE TABLE test.tbl4\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values less than('2020-02-01'),\n" +
+                                "    PARTITION p2 values less than('2020-03-01'),\n" +
+                                "    PARTITION p3 values less than('2020-04-01'),\n" +
+                                "    PARTITION p4 values less than('2020-05-01')\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES" +
+                                "(" +
+                                "    'replication_num' = '1',\n" +
+                                "    'in_memory' = 'false',\n" +
+                                "    'storage_medium' = 'SSD',\n" +
+                                "    'storage_cooldown_time' = '9999-12-31 00:00:00'\n" +
+                                ");")
+                    .withTable("CREATE TABLE t_recharge_detail(\n" +
+                                "    id bigint  ,\n" +
+                                "    user_id  bigint  ,\n" +
+                                "    recharge_money decimal(32,2) , \n" +
+                                "    province varchar(20) not null,\n" +
+                                "    dt varchar(20) not null\n" +
+                                ") ENGINE=OLAP\n" +
+                                "DUPLICATE KEY(id)\n" +
+                                "PARTITION BY LIST (dt,province) (\n" +
+                                "   PARTITION p1 VALUES IN ((\"2022-04-01\", \"beijing\")),\n" +
+                                "   PARTITION p2 VALUES IN ((\"2022-04-01\", \"shanghai\"))\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(`id`) BUCKETS 10 \n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\",\n" +
+                                "\"in_memory\" = \"false\"\n" +
+                                ");")
+                    .withTable("CREATE TABLE test.site_access_date_trunc (\n" +
+                                "    event_day DATETIME NOT NULL,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY date_trunc('day', event_day)\n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id)\n" +
+                                "PROPERTIES(\n" +
+                                "    \"replication_num\" = \"1\"\n" +
+                                ");")
+                    .withTable("CREATE TABLE site_access_time_slice (\n" +
+                                "    event_day datetime,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY time_slice(event_day, interval 1 day)\n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
+                                "PROPERTIES(\n" +
+                                "    \"partition_live_number\" = \"3\",\n" +
+                                "    \"replication_num\" = \"1\"\n" +
+                                ");");
     }
 
     @AfterClass
@@ -276,19 +276,19 @@ private static void createTable(String sql) throws Exception {
 
     private static void createMaterializedView(String sql) throws Exception {
         CreateMaterializedViewStatement createMaterializedViewStatement =
-                (CreateMaterializedViewStatement) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
+                    (CreateMaterializedViewStatement) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         GlobalStateMgr.getCurrentState().getLocalMetastore().createMaterializedView(createMaterializedViewStatement);
     }
 
     private static void dropMaterializedView(String sql) throws Exception {
         DropMaterializedViewStmt dropMaterializedViewStmt =
-                (DropMaterializedViewStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
+                    (DropMaterializedViewStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropMaterializedView(dropMaterializedViewStmt);
     }
 
     private static void alterMaterializedView(String sql, boolean expectedException) throws Exception {
         AlterMaterializedViewStmt alterMaterializedViewStmt =
-                (AlterMaterializedViewStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
+                    (AlterMaterializedViewStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         try {
             GlobalStateMgr.getCurrentState().getLocalMetastore().alterMaterializedView(alterMaterializedViewStmt);
             if (expectedException) {
@@ -304,12 +304,12 @@ private static void alterMaterializedView(String sql, boolean expectedException)
 
     private static void refreshMaterializedView(String sql) throws Exception {
         RefreshMaterializedViewStatement refreshMaterializedViewStatement =
-                (RefreshMaterializedViewStatement) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
+                    (RefreshMaterializedViewStatement) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         try {
             GlobalStateMgr.getCurrentState().getLocalMetastore()
-                    .refreshMaterializedView(refreshMaterializedViewStatement.getMvName().getDb(),
-                            refreshMaterializedViewStatement.getMvName().getTbl(), false, null,
-                            Constants.TaskRunPriority.LOWEST.value(), false, true);
+                        .refreshMaterializedView(refreshMaterializedViewStatement.getMvName().getDb(),
+                                    refreshMaterializedViewStatement.getMvName().getTbl(), false, null,
+                                    Constants.TaskRunPriority.LOWEST.value(), false, true);
         } catch (Exception e) {
             e.printStackTrace();
             Assert.fail();
@@ -318,7 +318,7 @@ private static void refreshMaterializedView(String sql) throws Exception {
 
     private static void cancelRefreshMaterializedView(String sql, boolean expectedException) throws Exception {
         CancelRefreshMaterializedViewStmt cancelRefresh =
-                (CancelRefreshMaterializedViewStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
+                    (CancelRefreshMaterializedViewStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         try {
             GlobalStateMgr.getCurrentState().getLocalMetastore().cancelRefreshMaterializedView(cancelRefresh);
             if (expectedException) {
@@ -359,36 +359,36 @@ private static void alterTableWithNewParserAndExceptionMsg(String sql, String ms
     @Test
     public void testRenameMaterializedView() throws Exception {
         starRocksAssert.useDatabase("test")
-                .withTable("CREATE TABLE test.testTable1\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values less than('2020-02-01'),\n" +
-                        "    PARTITION p2 values less than('2020-03-01')\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');");
+                    .withTable("CREATE TABLE test.testTable1\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values less than('2020-02-01'),\n" +
+                                "    PARTITION p2 values less than('2020-03-01')\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');");
         String sql = "create materialized view mv1 " +
-                "partition by k1 " +
-                "distributed by hash(k2) " +
-                "refresh async START('2122-12-31') EVERY(INTERVAL 1 HOUR) " +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\"\n" +
-                ") " +
-                "as select k1, k2 from test.testTable1;";
+                    "partition by k1 " +
+                    "distributed by hash(k2) " +
+                    "refresh async START('2122-12-31') EVERY(INTERVAL 1 HOUR) " +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\"\n" +
+                    ") " +
+                    "as select k1, k2 from test.testTable1;";
         createMaterializedView(sql);
         String alterStmt = "alter materialized view test.mv1 rename mv2";
         alterMaterializedView(alterStmt, false);
-        MaterializedView materializedView = (MaterializedView) GlobalStateMgr.getCurrentState().
-                getDb("test").getTable("mv2");
+        MaterializedView materializedView = (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().
+                    getDb("test").getTable("mv2");
         TaskManager taskManager = GlobalStateMgr.getCurrentState().getTaskManager();
         Task task = taskManager.getTask(TaskBuilder.getMvTaskName(materializedView.getId()));
         Assert.assertEquals("insert overwrite `mv2` SELECT `test`.`testTable1`.`k1`, `test`.`testTable1`.`k2`\n" +
-                "FROM `test`.`testTable1`", task.getDefinition());
+                    "FROM `test`.`testTable1`", task.getDefinition());
         ConnectContext.get().setCurrentUserIdentity(UserIdentity.ROOT);
         ConnectContext.get().setCurrentRoleIds(UserIdentity.ROOT);
         dropMaterializedView("drop materialized view test.mv2");
@@ -397,45 +397,45 @@ public void testRenameMaterializedView() throws Exception {
     @Test
     public void testCouldNotFindMaterializedView() throws Exception {
         starRocksAssert.useDatabase("test")
-                .withTable("CREATE TABLE test.testTable1\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values less than('2020-02-01'),\n" +
-                        "    PARTITION p2 values less than('2020-03-01')\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');")
-                .withTable("CREATE TABLE test.testTable2\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values less than('2020-02-01'),\n" +
-                        "    PARTITION p2 values less than('2020-03-01')\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');");
+                    .withTable("CREATE TABLE test.testTable1\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values less than('2020-02-01'),\n" +
+                                "    PARTITION p2 values less than('2020-03-01')\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');")
+                    .withTable("CREATE TABLE test.testTable2\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values less than('2020-02-01'),\n" +
+                                "    PARTITION p2 values less than('2020-03-01')\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');");
         String sql = "create materialized view mv1 " +
-                "partition by k1 " +
-                "distributed by hash(k2) " +
-                "refresh async START('2122-12-31') EVERY(INTERVAL 1 HOUR) " +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\"\n" +
-                ") " +
-                "as select k1, k2 from test.testTable1;";
+                    "partition by k1 " +
+                    "distributed by hash(k2) " +
+                    "refresh async START('2122-12-31') EVERY(INTERVAL 1 HOUR) " +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\"\n" +
+                    ") " +
+                    "as select k1, k2 from test.testTable1;";
         createMaterializedView(sql);
         starRocksAssert.getCtx().setCurrentRoleIds(GlobalStateMgr.getCurrentState().getAuthorizationMgr().getRoleIdsByUser(
-                starRocksAssert.getCtx().getCurrentUserIdentity()));
+                    starRocksAssert.getCtx().getCurrentUserIdentity()));
         dropMaterializedView("drop materialized view test.mv1");
-        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getDb("test").getTable("testTable1");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("testTable1");
         // this for mock olapTable.getIndexNameById(mvIdx.getId()) == Null
         table.deleteIndexInfo("testTable1");
         try {
@@ -449,19 +449,19 @@ public void testCouldNotFindMaterializedView() throws Exception {
     @Test
     public void testRenameTable() throws Exception {
         starRocksAssert.useDatabase("test")
-                .withTable("CREATE TABLE test.testRenameTable1\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values less than('2020-02-01'),\n" +
-                        "    PARTITION p2 values less than('2020-03-01')\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');");
+                    .withTable("CREATE TABLE test.testRenameTable1\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values less than('2020-02-01'),\n" +
+                                "    PARTITION p2 values less than('2020-03-01')\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');");
         String alterStmt = "alter table test.testRenameTable1 rename testRenameTable2";
         alterTableWithNewParser(alterStmt, false);
     }
@@ -469,27 +469,27 @@ public void testRenameTable() throws Exception {
     @Test
     public void testChangeMaterializedViewRefreshScheme() throws Exception {
         starRocksAssert.useDatabase("test")
-                .withTable("CREATE TABLE test.testTable2\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values less than('2020-02-01'),\n" +
-                        "    PARTITION p2 values less than('2020-03-01')\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');");
+                    .withTable("CREATE TABLE test.testTable2\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values less than('2020-02-01'),\n" +
+                                "    PARTITION p2 values less than('2020-03-01')\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');");
         String sql = "create materialized view mv1 " +
-                "partition by k1 " +
-                "distributed by hash(k2) " +
-                "refresh async START('2122-12-31') EVERY(INTERVAL 1 HOUR) " +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\"\n" +
-                ") " +
-                "as select k1, k2 from test.testTable2;";
+                    "partition by k1 " +
+                    "distributed by hash(k2) " +
+                    "refresh async START('2122-12-31') EVERY(INTERVAL 1 HOUR) " +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\"\n" +
+                    ") " +
+                    "as select k1, k2 from test.testTable2;";
         createMaterializedView(sql);
         String alterStmt = "alter materialized view mv1 refresh async EVERY(INTERVAL 1 minute)";
         alterMaterializedView(alterStmt, false);
@@ -503,61 +503,61 @@ public void testChangeMaterializedViewRefreshScheme() throws Exception {
     @Test
     public void testRefreshMaterializedView() throws Exception {
         starRocksAssert.useDatabase("test")
-                .withTable("CREATE TABLE test.testTable3\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values less than('2020-02-01'),\n" +
-                        "    PARTITION p2 values less than('2020-03-01')\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');");
+                    .withTable("CREATE TABLE test.testTable3\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values less than('2020-02-01'),\n" +
+                                "    PARTITION p2 values less than('2020-03-01')\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');");
         String sql = "create materialized view mv1 " +
-                "partition by k1 " +
-                "distributed by hash(k2) " +
-                "refresh async START('2122-12-31') EVERY(INTERVAL 1 HOUR) " +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\"\n" +
-                ") " +
-                "as select k1, k2 from test.testTable3;";
+                    "partition by k1 " +
+                    "distributed by hash(k2) " +
+                    "refresh async START('2122-12-31') EVERY(INTERVAL 1 HOUR) " +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\"\n" +
+                    ") " +
+                    "as select k1, k2 from test.testTable3;";
         createMaterializedView(sql);
         String alterStmt = "refresh materialized view test.mv1";
         refreshMaterializedView(alterStmt);
         starRocksAssert.getCtx().setCurrentRoleIds(GlobalStateMgr.getCurrentState().getAuthorizationMgr().getRoleIdsByUser(
-                starRocksAssert.getCtx().getCurrentUserIdentity()));
+                    starRocksAssert.getCtx().getCurrentUserIdentity()));
         dropMaterializedView("drop materialized view test.mv1");
     }
 
     @Test
     public void testCancelRefreshMaterializedView() throws Exception {
         starRocksAssert.useDatabase("test")
-                .withTable("CREATE TABLE test.testTable4\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values less than('2020-02-01'),\n" +
-                        "    PARTITION p2 values less than('2020-03-01')\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');");
+                    .withTable("CREATE TABLE test.testTable4\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values less than('2020-02-01'),\n" +
+                                "    PARTITION p2 values less than('2020-03-01')\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');");
         String sql = "create materialized view mv1 " +
-                "partition by k1 " +
-                "distributed by hash(k2) " +
-                "refresh async START('2122-12-31') EVERY(INTERVAL 1 HOUR) " +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\"\n" +
-                ") " +
-                "as select k1, k2 from test.testTable4;";
+                    "partition by k1 " +
+                    "distributed by hash(k2) " +
+                    "refresh async START('2122-12-31') EVERY(INTERVAL 1 HOUR) " +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\"\n" +
+                    ") " +
+                    "as select k1, k2 from test.testTable4;";
         starRocksAssert.getCtx().setCurrentRoleIds(GlobalStateMgr.getCurrentState().getAuthorizationMgr().getRoleIdsByUser(
-                starRocksAssert.getCtx().getCurrentUserIdentity()));
+                    starRocksAssert.getCtx().getCurrentUserIdentity()));
         createMaterializedView(sql);
         String alterStmt = "refresh materialized view test.mv1";
         refreshMaterializedView(alterStmt);
@@ -567,12 +567,12 @@ public void testCancelRefreshMaterializedView() throws Exception {
 
     @Test
     public void testConflictAlterOperations() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("tbl1");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl1");
 
         String stmt =
-                "alter table test.tbl1 add partition p3 values less than('2020-04-01'), " +
-                        "add partition p4 values less than('2020-05-01')";
+                    "alter table test.tbl1 add partition p3 values less than('2020-04-01'), " +
+                                "add partition p4 values less than('2020-05-01')";
         alterTableWithNewParser(stmt, true);
 
         stmt = "alter table test.tbl1 add partition p3 values less than('2020-04-01'), drop partition p4";
@@ -600,12 +600,12 @@ public void testConflictAlterOperations() throws Exception {
         // enable dynamic partition
         // not adding the `start` property so that it won't drop the origin partition p1, p2 and p3
         stmt = "alter table test.tbl1 set (\n" +
-                "'dynamic_partition.enable' = 'true',\n" +
-                "'dynamic_partition.time_unit' = 'DAY',\n" +
-                "'dynamic_partition.end' = '3',\n" +
-                "'dynamic_partition.prefix' = 'p',\n" +
-                "'dynamic_partition.buckets' = '3'\n" +
-                " );";
+                    "'dynamic_partition.enable' = 'true',\n" +
+                    "'dynamic_partition.time_unit' = 'DAY',\n" +
+                    "'dynamic_partition.end' = '3',\n" +
+                    "'dynamic_partition.prefix' = 'p',\n" +
+                    "'dynamic_partition.buckets' = '3'\n" +
+                    " );";
         alterTableWithNewParser(stmt, false);
 
         Assert.assertTrue(tbl.getTableProperty().getDynamicPartitionProperty().isEnabled());
@@ -613,12 +613,12 @@ public void testConflictAlterOperations() throws Exception {
 
         // add partition when dynamic partition is enable
         stmt = "alter table test.tbl1 add partition p3 values less than('2020-04-01') " +
-                "distributed by hash(k2) buckets 4 PROPERTIES ('replication_num' = '1')";
+                    "distributed by hash(k2) buckets 4 PROPERTIES ('replication_num' = '1')";
         alterTableWithNewParser(stmt, true);
 
         // add temp partition when dynamic partition is enable
         stmt = "alter table test.tbl1 add temporary partition tp3 values less than('2020-04-01') " +
-                "distributed by hash(k2) buckets 4 PROPERTIES ('replication_num' = '1')";
+                    "distributed by hash(k2) buckets 4 PROPERTIES ('replication_num' = '1')";
         alterTableWithNewParser(stmt, false);
         Assert.assertEquals(1, tbl.getTempPartitions().size());
 
@@ -629,7 +629,7 @@ public void testConflictAlterOperations() throws Exception {
 
         // add partition when dynamic partition is disable
         stmt = "alter table test.tbl1 add partition p3 values less than('2020-04-01') " +
-                "distributed by hash(k2) buckets 4";
+                    "distributed by hash(k2) buckets 4";
         alterTableWithNewParser(stmt, false);
 
         // set table's default replication num
@@ -646,25 +646,25 @@ public void testConflictAlterOperations() throws Exception {
         Assert.assertEquals(Short.valueOf("1"), Short.valueOf(tbl.getPartitionInfo().getReplicationNum(p1.getId())));
 
         // set un-partitioned table's real replication num
-        OlapTable tbl2 = (OlapTable) db.getTable("tbl2");
+        OlapTable tbl2 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl2");
         Partition partition = tbl2.getPartition(tbl2.getName());
         Assert.assertEquals(Short.valueOf("1"),
-                Short.valueOf(tbl2.getPartitionInfo().getReplicationNum(partition.getId())));
+                    Short.valueOf(tbl2.getPartitionInfo().getReplicationNum(partition.getId())));
         // partition replication num and table default replication num are updated at the same time in unpartitioned table
         stmt = "alter table test.tbl2 set ('replication_num' = '3');";
         alterTableWithNewParser(stmt, false);
         Assert.assertEquals(Short.valueOf("3"),
-                Short.valueOf(tbl2.getPartitionInfo().getReplicationNum(partition.getId())));
+                    Short.valueOf(tbl2.getPartitionInfo().getReplicationNum(partition.getId())));
         Assert.assertEquals(Short.valueOf("3"), tbl2.getDefaultReplicationNum());
         stmt = "alter table test.tbl2 set ('default.replication_num' = '2');";
         alterTableWithNewParser(stmt, false);
         Assert.assertEquals(Short.valueOf("2"),
-                Short.valueOf(tbl2.getPartitionInfo().getReplicationNum(partition.getId())));
+                    Short.valueOf(tbl2.getPartitionInfo().getReplicationNum(partition.getId())));
         Assert.assertEquals(Short.valueOf("2"), tbl2.getDefaultReplicationNum());
         stmt = "alter table test.tbl2 modify partition tbl2 set ('replication_num' = '1');";
         alterTableWithNewParser(stmt, false);
         Assert.assertEquals(Short.valueOf("1"),
-                Short.valueOf(tbl2.getPartitionInfo().getReplicationNum(partition.getId())));
+                    Short.valueOf(tbl2.getPartitionInfo().getReplicationNum(partition.getId())));
         Assert.assertEquals(Short.valueOf("1"), tbl2.getDefaultReplicationNum());
 
         Thread.sleep(5000); // sleep to wait dynamic partition scheduler run
@@ -677,8 +677,8 @@ public void testConflictAlterOperations() throws Exception {
         alterTableWithNewParser(stmt, false);
 
         stmt = "alter table test.tbl1 " +
-                "add TEMPORARY partition p5 values [('2020-04-10'), ('2020-05-10')) ('replication_num' = '1') " +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 3 PROPERTIES('replication_num' = '1');";
+                    "add TEMPORARY partition p5 values [('2020-04-10'), ('2020-05-10')) ('replication_num' = '1') " +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 3 PROPERTIES('replication_num' = '1');";
         alterTableWithNewParser(stmt, false);
         //rename table
         stmt = "alter table test.tbl1 rename newTableName";
@@ -688,8 +688,8 @@ public void testConflictAlterOperations() throws Exception {
     // test batch update range partitions' properties
     @Test
     public void testBatchUpdatePartitionProperties() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl4 = (OlapTable) db.getTable("tbl4");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl4 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl4");
         Partition p1 = tbl4.getPartition("p1");
         Partition p2 = tbl4.getPartition("p2");
         Partition p3 = tbl4.getPartition("p3");
@@ -700,12 +700,12 @@ public void testBatchUpdatePartitionProperties() throws Exception {
         List<Partition> partitionList = Lists.newArrayList(p1, p2, p4);
         for (Partition partition : partitionList) {
             Assert.assertEquals(Short.valueOf("1"),
-                    Short.valueOf(tbl4.getPartitionInfo().getReplicationNum(partition.getId())));
+                        Short.valueOf(tbl4.getPartitionInfo().getReplicationNum(partition.getId())));
         }
         alterTableWithNewParser(stmt, false);
         for (Partition partition : partitionList) {
             Assert.assertEquals(Short.valueOf("3"),
-                    Short.valueOf(tbl4.getPartitionInfo().getReplicationNum(partition.getId())));
+                        Short.valueOf(tbl4.getPartitionInfo().getReplicationNum(partition.getId())));
         }
         Assert.assertEquals(Short.valueOf("1"), Short.valueOf(tbl4.getPartitionInfo().getReplicationNum(p3.getId())));
 
@@ -743,7 +743,7 @@ public void testBatchUpdatePartitionProperties() throws Exception {
         alterTableWithNewParser(stmt, false);
         for (Partition partition : partitionList) {
             Assert.assertEquals(Short.valueOf("1"),
-                    Short.valueOf(tbl4.getPartitionInfo().getReplicationNum(partition.getId())));
+                        Short.valueOf(tbl4.getPartitionInfo().getReplicationNum(partition.getId())));
         }
     }
 
@@ -763,8 +763,8 @@ public void testDynamicPartitionDropAndAdd() throws Exception {
         alterTable(stmt, false);
         Thread.sleep(5000); // sleep to wait dynamic partition scheduler run
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("tbl3");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl3");
         Assert.assertEquals(4, tbl.getPartitionNames().size());
         Assert.assertNull(tbl.getPartition("p1"));
         Assert.assertNull(tbl.getPartition("p2"));
@@ -778,11 +778,11 @@ private void waitSchemaChangeJobDone(boolean rollupJob, OlapTable tb) throws Int
         for (AlterJobV2 alterJobV2 : alterJobs.values()) {
             while (!alterJobV2.getJobState().isFinalState()) {
                 System.out.println(
-                        "alter job " + alterJobV2.getJobId() + " is running. state: " + alterJobV2.getJobState());
+                            "alter job " + alterJobV2.getJobId() + " is running. state: " + alterJobV2.getJobState());
                 Thread.sleep(1000);
             }
             System.out.println(alterJobV2.getType() + " alter job " + alterJobV2.getJobId() + " is done. state: " +
-                    alterJobV2.getJobState());
+                        alterJobV2.getJobState());
             Assert.assertEquals(AlterJobV2.JobState.FINISHED, alterJobV2.getJobState());
         }
         checkTableStateToNormal(tb);
@@ -792,36 +792,36 @@ private void waitSchemaChangeJobDone(boolean rollupJob, OlapTable tb) throws Int
     public void testSetDynamicPropertiesInNormalTable() throws Exception {
         String tableName = "no_dynamic_table";
         String createOlapTblStmt = "CREATE TABLE test.`" + tableName + "` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY RANGE (k1)\n" +
-                "(\n" +
-                "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
-                "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
-                "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\"\n" +
-                ");";
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY RANGE (k1)\n" +
+                    "(\n" +
+                    "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
+                    "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
+                    "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\"\n" +
+                    ");";
         createTable(createOlapTblStmt);
         String alterStmt = "alter table test." + tableName + " set (\"dynamic_partition.enable\" = \"true\");";
         alterTableWithNewParserAndExceptionMsg(alterStmt, "Table test.no_dynamic_table is not a dynamic partition table.");
         // test set dynamic properties in a no dynamic partition table
         String stmt = "alter table test." + tableName + " set (\n" +
-                "'dynamic_partition.enable' = 'true',\n" +
-                "'dynamic_partition.time_unit' = 'DAY',\n" +
-                "'dynamic_partition.start' = '-3',\n" +
-                "'dynamic_partition.end' = '3',\n" +
-                "'dynamic_partition.prefix' = 'p',\n" +
-                "'dynamic_partition.buckets' = '3'\n" +
-                " );";
+                    "'dynamic_partition.enable' = 'true',\n" +
+                    "'dynamic_partition.time_unit' = 'DAY',\n" +
+                    "'dynamic_partition.start' = '-3',\n" +
+                    "'dynamic_partition.end' = '3',\n" +
+                    "'dynamic_partition.prefix' = 'p',\n" +
+                    "'dynamic_partition.buckets' = '3'\n" +
+                    " );";
         alterTableWithNewParser(stmt, false);
     }
 
@@ -829,30 +829,30 @@ public void testSetDynamicPropertiesInNormalTable() throws Exception {
     public void testSetDynamicPropertiesInDynamicPartitionTable() throws Exception {
         String tableName = "dynamic_table";
         String createOlapTblStmt = "CREATE TABLE test.`" + tableName + "` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY RANGE (k1)\n" +
-                "(\n" +
-                "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
-                "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
-                "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"dynamic_partition.enable\" = \"true\",\n" +
-                "\"dynamic_partition.start\" = \"-3\",\n" +
-                "\"dynamic_partition.end\" = \"3\",\n" +
-                "\"dynamic_partition.time_unit\" = \"day\",\n" +
-                "\"dynamic_partition.prefix\" = \"p\",\n" +
-                "\"dynamic_partition.buckets\" = \"1\"\n" +
-                ");";
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY RANGE (k1)\n" +
+                    "(\n" +
+                    "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
+                    "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
+                    "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"dynamic_partition.enable\" = \"true\",\n" +
+                    "\"dynamic_partition.start\" = \"-3\",\n" +
+                    "\"dynamic_partition.end\" = \"3\",\n" +
+                    "\"dynamic_partition.time_unit\" = \"day\",\n" +
+                    "\"dynamic_partition.prefix\" = \"p\",\n" +
+                    "\"dynamic_partition.buckets\" = \"1\"\n" +
+                    ");";
 
         createTable(createOlapTblStmt);
         String alterStmt1 = "alter table test." + tableName + " set (\"dynamic_partition.enable\" = \"false\");";
@@ -873,32 +873,32 @@ public void testSetDynamicPropertiesInDynamicPartitionTable() throws Exception {
     public void testDynamicPartitionTableMetaFailed() throws Exception {
         String tableName = "dynamic_table_test";
         String createOlapTblStmt = "CREATE TABLE test.`" + tableName + "` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY RANGE (k1)\n" +
-                "(\n" +
-                "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
-                "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
-                "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"dynamic_partition.enable\" = \"true\",\n" +
-                "\"dynamic_partition.start\" = \"-3\",\n" +
-                "\"dynamic_partition.end\" = \"3\",\n" +
-                "\"dynamic_partition.time_unit\" = \"day\",\n" +
-                "\"dynamic_partition.prefix\" = \"p\",\n" +
-                "\"dynamic_partition.buckets\" = \"1\"\n" +
-                ");";
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY RANGE (k1)\n" +
+                    "(\n" +
+                    "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
+                    "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
+                    "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"dynamic_partition.enable\" = \"true\",\n" +
+                    "\"dynamic_partition.start\" = \"-3\",\n" +
+                    "\"dynamic_partition.end\" = \"3\",\n" +
+                    "\"dynamic_partition.time_unit\" = \"day\",\n" +
+                    "\"dynamic_partition.prefix\" = \"p\",\n" +
+                    "\"dynamic_partition.buckets\" = \"1\"\n" +
+                    ");";
         createTable(createOlapTblStmt);
-        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getDb("test").getTable(tableName);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable(tableName);
         olapTable.getTableProperty().getProperties().remove("dynamic_partition.end");
         olapTable.getTableProperty().gsonPostProcess();
     }
@@ -906,52 +906,52 @@ public void testDynamicPartitionTableMetaFailed() throws Exception {
     @Test
     public void testSwapTable() throws Exception {
         String stmt1 = "CREATE TABLE test.replace1\n" +
-                "(\n" +
-                "    k1 int, k2 int, k3 int sum\n" +
-                ")\n" +
-                "AGGREGATE KEY(k1, k2)\n" +
-                "DISTRIBUTED BY HASH(k1) BUCKETS 10\n" +
-                "rollup (\n" +
-                "r1(k1),\n" +
-                "r2(k2, k3)\n" +
-                ")\n" +
-                "PROPERTIES(\"replication_num\" = \"1\");";
+                    "(\n" +
+                    "    k1 int, k2 int, k3 int sum\n" +
+                    ")\n" +
+                    "AGGREGATE KEY(k1, k2)\n" +
+                    "DISTRIBUTED BY HASH(k1) BUCKETS 10\n" +
+                    "rollup (\n" +
+                    "r1(k1),\n" +
+                    "r2(k2, k3)\n" +
+                    ")\n" +
+                    "PROPERTIES(\"replication_num\" = \"1\");";
 
         String stmt2 = "CREATE TABLE test.r1\n" +
-                "(\n" +
-                "    k1 int, k2 int\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k1) BUCKETS 11\n" +
-                "PROPERTIES(\"replication_num\" = \"1\");";
+                    "(\n" +
+                    "    k1 int, k2 int\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k1) BUCKETS 11\n" +
+                    "PROPERTIES(\"replication_num\" = \"1\");";
 
         String stmt3 = "CREATE TABLE test.replace2\n" +
-                "(\n" +
-                "    k1 int, k2 int\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k1) BUCKETS 11\n" +
-                "PROPERTIES(\"replication_num\" = \"1\");";
+                    "(\n" +
+                    "    k1 int, k2 int\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k1) BUCKETS 11\n" +
+                    "PROPERTIES(\"replication_num\" = \"1\");";
 
         String stmt4 = "CREATE TABLE test.replace3\n" +
-                "(\n" +
-                "    k1 int, k2 int, k3 int sum\n" +
-                ")\n" +
-                "PARTITION BY RANGE(k1)\n" +
-                "(\n" +
-                "\tPARTITION p1 values less than(\"100\"),\n" +
-                "\tPARTITION p2 values less than(\"200\")\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k1) BUCKETS 1\n" +
-                "rollup (\n" +
-                "r3(k1),\n" +
-                "r4(k2, k3)\n" +
-                ")\n" +
-                "PROPERTIES(\"replication_num\" = \"1\");";
+                    "(\n" +
+                    "    k1 int, k2 int, k3 int sum\n" +
+                    ")\n" +
+                    "PARTITION BY RANGE(k1)\n" +
+                    "(\n" +
+                    "\tPARTITION p1 values less than(\"100\"),\n" +
+                    "\tPARTITION p2 values less than(\"200\")\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k1) BUCKETS 1\n" +
+                    "rollup (\n" +
+                    "r3(k1),\n" +
+                    "r4(k2, k3)\n" +
+                    ")\n" +
+                    "PROPERTIES(\"replication_num\" = \"1\");";
 
         createTable(stmt1);
         createTable(stmt2);
         createTable(stmt3);
         createTable(stmt4);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         // name conflict
         String replaceStmt = "ALTER TABLE test.replace1 SWAP WITH r1";
@@ -959,25 +959,27 @@ public void testSwapTable() throws Exception {
 
         // replace1 with replace2
         replaceStmt = "ALTER TABLE test.replace1 SWAP WITH replace2";
-        OlapTable replace1 = (OlapTable) db.getTable("replace1");
-        OlapTable replace2 = (OlapTable) db.getTable("replace2");
+        OlapTable replace1 =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "replace1");
+        OlapTable replace2 =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "replace2");
         Assert.assertEquals(3,
-                replace1.getPartition("replace1").getMaterializedIndices(MaterializedIndex.IndexExtState.VISIBLE)
-                        .size());
+                    replace1.getPartition("replace1").getMaterializedIndices(MaterializedIndex.IndexExtState.VISIBLE)
+                                .size());
         Assert.assertEquals(1,
-                replace2.getPartition("replace2").getMaterializedIndices(MaterializedIndex.IndexExtState.VISIBLE)
-                        .size());
+                    replace2.getPartition("replace2").getMaterializedIndices(MaterializedIndex.IndexExtState.VISIBLE)
+                                .size());
 
         alterTableWithNewParser(replaceStmt, false);
 
-        replace1 = (OlapTable) db.getTable("replace1");
-        replace2 = (OlapTable) db.getTable("replace2");
+        replace1 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "replace1");
+        replace2 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "replace2");
         Assert.assertEquals(1,
-                replace1.getPartition("replace1").getMaterializedIndices(MaterializedIndex.IndexExtState.VISIBLE)
-                        .size());
+                    replace1.getPartition("replace1").getMaterializedIndices(MaterializedIndex.IndexExtState.VISIBLE)
+                                .size());
         Assert.assertEquals(3,
-                replace2.getPartition("replace2").getMaterializedIndices(MaterializedIndex.IndexExtState.VISIBLE)
-                        .size());
+                    replace2.getPartition("replace2").getMaterializedIndices(MaterializedIndex.IndexExtState.VISIBLE)
+                                .size());
         Assert.assertEquals("replace1", replace1.getIndexNameById(replace1.getBaseIndexId()));
         Assert.assertEquals("replace2", replace2.getIndexNameById(replace2.getBaseIndexId()));
     }
@@ -989,34 +991,34 @@ public void testCatalogAddPartitionsDay() throws Exception {
         DropTableStmt dropTableStmt = (DropTableStmt) UtFrameUtils.parseStmtWithNewParser(dropSQL, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropTable(dropTableStmt);
         String createSQL = "CREATE TABLE test.test_partition (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "PARTITION BY RANGE (k2) (\n" +
-                "    START (\"20140101\") END (\"20140104\") EVERY (INTERVAL 1 DAY)\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "PARTITION BY RANGE (k2) (\n" +
+                    "    START (\"20140101\") END (\"20140104\") EVERY (INTERVAL 1 DAY)\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String alterSQL = "ALTER TABLE test_partition ADD\n" +
-                "    PARTITIONS START (\"2017-01-03\") END (\"2017-01-07\") EVERY (interval 1 day)";
+                    "    PARTITIONS START (\"2017-01-03\") END (\"2017-01-07\") EVERY (interval 1 day)";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
         AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition");
 
         Assert.assertNotNull(table.getPartition("p20170103"));
         Assert.assertNotNull(table.getPartition("p20170104"));
@@ -1037,34 +1039,34 @@ public void testAddPhysicalPartition() throws Exception {
         DropTableStmt dropTableStmt = (DropTableStmt) UtFrameUtils.parseStmtWithNewParser(dropSQL, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropTable(dropTableStmt);
         String createSQL = "CREATE TABLE test.test_partition (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "DISTRIBUTED BY RANDOM BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "DISTRIBUTED BY RANDOM BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition");
         Optional<Partition> partition = table.getPartitions().stream().findFirst();
         Assert.assertTrue(partition.isPresent());
         Assert.assertEquals(table.getPhysicalPartitions().size(), 1);
 
         GlobalStateMgr.getCurrentState().getLocalMetastore().addSubPartitions(db, table, partition.get(), 1,
-                WarehouseManager.DEFAULT_WAREHOUSE_ID);
+                    WarehouseManager.DEFAULT_WAREHOUSE_ID);
         Assert.assertEquals(partition.get().getSubPartitions().size(), 2);
         Assert.assertEquals(table.getPhysicalPartitions().size(), 2);
 
         GlobalStateMgr.getCurrentState().getLocalMetastore().addSubPartitions(db, table, partition.get(), 2,
-                WarehouseManager.DEFAULT_WAREHOUSE_ID);
+                    WarehouseManager.DEFAULT_WAREHOUSE_ID);
         Assert.assertEquals(partition.get().getSubPartitions().size(), 4);
         Assert.assertEquals(table.getPhysicalPartitions().size(), 4);
 
@@ -1090,33 +1092,33 @@ public void testAddRangePhysicalPartition() throws Exception {
         DropTableStmt dropTableStmt = (DropTableStmt) UtFrameUtils.parseStmtWithNewParser(dropSQL, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropTable(dropTableStmt);
         String createSQL = "CREATE TABLE test.test_partition (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "PARTITION BY RANGE (k2) (\n" +
-                "    START (\"20140101\") END (\"20140104\") EVERY (INTERVAL 1 DAY)\n" +
-                ")\n" +
-                "DISTRIBUTED BY RANDOM BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "PARTITION BY RANGE (k2) (\n" +
+                    "    START (\"20140101\") END (\"20140104\") EVERY (INTERVAL 1 DAY)\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY RANDOM BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition");
         Assert.assertEquals(table.getPhysicalPartitions().size(), 3);
 
         Partition partition = table.getPartition("p20140101");
         Assert.assertNotNull(partition);
 
         GlobalStateMgr.getCurrentState().getLocalMetastore().addSubPartitions(db, table, partition, 1,
-                WarehouseManager.DEFAULT_WAREHOUSE_ID);
+                    WarehouseManager.DEFAULT_WAREHOUSE_ID);
         Assert.assertEquals(table.getPhysicalPartitions().size(), 4);
         Assert.assertEquals(partition.getSubPartitions().size(), 2);
 
@@ -1124,7 +1126,7 @@ public void testAddRangePhysicalPartition() throws Exception {
         Assert.assertNotNull(partition);
 
         GlobalStateMgr.getCurrentState().getLocalMetastore().addSubPartitions(db, table, partition, 2,
-                WarehouseManager.DEFAULT_WAREHOUSE_ID);
+                    WarehouseManager.DEFAULT_WAREHOUSE_ID);
         Assert.assertEquals(table.getPhysicalPartitions().size(), 6);
         Assert.assertEquals(partition.getSubPartitions().size(), 3);
 
@@ -1140,29 +1142,29 @@ public void testAddPhysicalPartitionForHash() throws Exception {
         DropTableStmt dropTableStmt = (DropTableStmt) UtFrameUtils.parseStmtWithNewParser(dropSQL, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropTable(dropTableStmt);
         String createSQL = "CREATE TABLE test.test_partition (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition");
         Optional<Partition> partition = table.getPartitions().stream().findFirst();
         Assert.assertTrue(partition.isPresent());
         Assert.assertEquals(table.getPhysicalPartitions().size(), 1);
 
         GlobalStateMgr.getCurrentState().getLocalMetastore().addSubPartitions(db, table, partition.get(), 1,
-                WarehouseManager.DEFAULT_WAREHOUSE_ID);
+                    WarehouseManager.DEFAULT_WAREHOUSE_ID);
     }
 
     @Test
@@ -1192,33 +1194,33 @@ public void testAddBackend() throws Exception {
     public void testCatalogAddPartitions5Day() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test.test_partition (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "PARTITION BY RANGE (k2) (\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "PARTITION BY RANGE (k2) (\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String alterSQL = "ALTER TABLE test_partition ADD\n" +
-                "    PARTITIONS START (\"2017-01-03\") END (\"2017-01-15\") EVERY (interval 5 day)";
+                    "    PARTITIONS START (\"2017-01-03\") END (\"2017-01-15\") EVERY (interval 5 day)";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
         AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition");
 
         Assert.assertNotNull(table.getPartition("p20170103"));
         Assert.assertNotNull(table.getPartition("p20170108"));
@@ -1233,31 +1235,31 @@ public void testCatalogAddPartitions5Day() throws Exception {
     public void testCatalogAddPartitionsDayConflictException() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test.test_partition_exception (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "PARTITION BY RANGE (k2) (\n" +
-                "    START (\"20140101\") END (\"20140104\") EVERY (INTERVAL 1 DAY)\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "PARTITION BY RANGE (k2) (\n" +
+                    "    START (\"20140101\") END (\"20140104\") EVERY (INTERVAL 1 DAY)\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String alterSQL = "ALTER TABLE test_partition_exception ADD\n" +
-                "    PARTITIONS START (\"2014-01-01\") END (\"2014-01-04\") EVERY (interval 1 day)";
+                    "    PARTITIONS START (\"2014-01-01\") END (\"2014-01-04\") EVERY (interval 1 day)";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
         AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_exception", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_exception", addPartitionClause);
     }
 
     @Test
@@ -1265,33 +1267,33 @@ public void testCatalogAddPartitionsWeekWithoutCheck() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         Config.enable_create_partial_partition_in_batch = true;
         String createSQL = "CREATE TABLE test.test_partition_week (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "PARTITION BY RANGE (k2) (\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "PARTITION BY RANGE (k2) (\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String alterSQL = "ALTER TABLE test_partition_week ADD\n" +
-                "    PARTITIONS START (\"2017-03-25\") END (\"2017-04-10\") EVERY (interval 1 week)";
+                    "    PARTITIONS START (\"2017-03-25\") END (\"2017-04-10\") EVERY (interval 1 week)";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
         AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_week", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_week", addPartitionClause);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition_week");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition_week");
 
         Assert.assertNotNull(table.getPartition("p2017_12"));
         Assert.assertNotNull(table.getPartition("p2017_13"));
@@ -1307,33 +1309,33 @@ public void testCatalogAddPartitionsWeekWithoutCheck() throws Exception {
     public void testCatalogAddPartitionsWeekWithCheck() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test.test_partition_week (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "PARTITION BY RANGE (k2) (\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "PARTITION BY RANGE (k2) (\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String alterSQL = "ALTER TABLE test_partition_week ADD\n" +
-                "    PARTITIONS START (\"2017-03-20\") END (\"2017-04-10\") EVERY (interval 1 week)";
+                    "    PARTITIONS START (\"2017-03-20\") END (\"2017-04-10\") EVERY (interval 1 week)";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
         AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_week", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_week", addPartitionClause);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition_week");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition_week");
 
         Assert.assertNotNull(table.getPartition("p2017_12"));
         Assert.assertNotNull(table.getPartition("p2017_13"));
@@ -1351,33 +1353,33 @@ public void testCatalogAddPartitionsMonth() throws Exception {
         DropTableStmt dropTableStmt = (DropTableStmt) UtFrameUtils.parseStmtWithNewParser(dropSQL, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropTable(dropTableStmt);
         String createSQL = "CREATE TABLE test.test_partition (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "PARTITION BY RANGE (k2) (\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "PARTITION BY RANGE (k2) (\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String alterSQL = "ALTER TABLE test_partition ADD\n" +
-                "    PARTITIONS START (\"2017-01-01\") END (\"2017-04-01\") EVERY (interval 1 month)";
+                    "    PARTITIONS START (\"2017-01-01\") END (\"2017-04-01\") EVERY (interval 1 month)";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
         AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition");
 
         Assert.assertNotNull(table.getPartition("p201701"));
         Assert.assertNotNull(table.getPartition("p201702"));
@@ -1396,33 +1398,33 @@ public void testCatalogAddPartitionsYear() throws Exception {
         DropTableStmt dropTableStmt = (DropTableStmt) UtFrameUtils.parseStmtWithNewParser(dropSQL, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropTable(dropTableStmt);
         String createSQL = "CREATE TABLE test.test_partition (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "PARTITION BY RANGE (k2) (\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "PARTITION BY RANGE (k2) (\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String alterSQL = "ALTER TABLE test_partition ADD\n" +
-                "    PARTITIONS START (\"2017-01-01\") END (\"2020-01-01\") EVERY (interval 1 YEAR)";
+                    "    PARTITIONS START (\"2017-01-01\") END (\"2020-01-01\") EVERY (interval 1 YEAR)";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
         AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition");
 
         Assert.assertNotNull(table.getPartition("p2017"));
         Assert.assertNotNull(table.getPartition("p2018"));
@@ -1441,33 +1443,33 @@ public void testCatalogAddPartitionsNumber() throws Exception {
         DropTableStmt dropTableStmt = (DropTableStmt) UtFrameUtils.parseStmtWithNewParser(dropSQL, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropTable(dropTableStmt);
         String createSQL = "CREATE TABLE test.test_partition (\n" +
-                "      k2 INT,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "PARTITION BY RANGE (k2) (\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 INT,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "PARTITION BY RANGE (k2) (\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String alterSQL = "ALTER TABLE test_partition ADD\n" +
-                "    PARTITIONS START (\"1\") END (\"4\") EVERY (1)";
+                    "    PARTITIONS START (\"1\") END (\"4\") EVERY (1)";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
         AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition");
 
         Assert.assertNotNull(table.getPartition("p1"));
         Assert.assertNotNull(table.getPartition("p2"));
@@ -1486,39 +1488,39 @@ public void testCatalogAddPartitionsAtomicRange() throws Exception {
         DropTableStmt dropTableStmt = (DropTableStmt) UtFrameUtils.parseStmtWithNewParser(dropSQL, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropTable(dropTableStmt);
         String createSQL = "CREATE TABLE test_partition (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "PARTITION BY RANGE (k2) (\n" +
-                "    START (\"20140101\") END (\"20150101\") EVERY (INTERVAL 1 YEAR)\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "PARTITION BY RANGE (k2) (\n" +
+                    "    START (\"20140101\") END (\"20150101\") EVERY (INTERVAL 1 YEAR)\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         try {
             String alterSQL = "ALTER TABLE test_partition ADD\n" +
-                    "          PARTITIONS START (\"2014-01-01\") END (\"2014-01-06\") EVERY (interval 1 day);";
+                        "          PARTITIONS START (\"2014-01-01\") END (\"2014-01-06\") EVERY (interval 1 day);";
             AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
             AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
             GlobalStateMgr.getCurrentState().getLocalMetastore()
-                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
+                        .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
             Assert.fail();
         } catch (AnalysisException ex) {
 
         }
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition");
 
         Assert.assertNull(table.getPartition("p20140101"));
         Assert.assertNull(table.getPartition("p20140102"));
@@ -1534,39 +1536,39 @@ public void testCatalogAddPartitionsZeroDay() throws Exception {
 
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test_partition_0day (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "PARTITION BY RANGE (k2) (\n" +
-                "    START (\"20140104\") END (\"20150104\") EVERY (INTERVAL 1 YEAR)\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "PARTITION BY RANGE (k2) (\n" +
+                    "    START (\"20140104\") END (\"20150104\") EVERY (INTERVAL 1 YEAR)\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         try {
             String alterSQL = "ALTER TABLE test_partition_0day ADD\n" +
-                    "          PARTITIONS START (\"2014-01-01\") END (\"2014-01-06\") EVERY (interval 0 day);";
+                        "          PARTITIONS START (\"2014-01-01\") END (\"2014-01-06\") EVERY (interval 0 day);";
             AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
             AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
             GlobalStateMgr.getCurrentState().getLocalMetastore()
-                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_0day", addPartitionClause);
+                        .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_0day", addPartitionClause);
             Assert.fail();
         } catch (AnalysisException ex) {
 
         }
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition_0day");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition_0day");
 
         Assert.assertNull(table.getPartition("p20140101"));
         Assert.assertNull(table.getPartition("p20140102"));
@@ -1585,39 +1587,39 @@ public void testCatalogAddPartitionsWithoutPartitions() throws Exception {
         DropTableStmt dropTableStmt = (DropTableStmt) UtFrameUtils.parseStmtWithNewParser(dropSQL, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropTable(dropTableStmt);
         String createSQL = "CREATE TABLE test_partition (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "PARTITION BY RANGE (k2) (\n" +
-                "    START (\"20140101\") END (\"20150101\") EVERY (INTERVAL 1 YEAR)\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "PARTITION BY RANGE (k2) (\n" +
+                    "    START (\"20140101\") END (\"20150101\") EVERY (INTERVAL 1 YEAR)\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String alterSQL = "ALTER TABLE test_partition ADD\n" +
-                "         START (\"2015-01-01\") END (\"2015-01-06\") EVERY (interval 1 day);";
+                    "         START (\"2015-01-01\") END (\"2015-01-06\") EVERY (interval 1 day);";
         try {
             AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
             AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
             GlobalStateMgr.getCurrentState().getLocalMetastore()
-                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
+                        .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
             Assert.fail();
         } catch (AnalysisException ex) {
 
         }
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition");
 
         Assert.assertNull(table.getPartition("p20140101"));
         Assert.assertNull(table.getPartition("p20140102"));
@@ -1632,41 +1634,41 @@ public void testCatalogAddPartitionsWithoutPartitions() throws Exception {
     public void testCatalogAddPartitionsIfNotExist() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test_partition_exists (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "PARTITION BY RANGE (k2) (\n" +
-                "    START (\"20140101\") END (\"20150101\") EVERY (INTERVAL 1 YEAR)\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "PARTITION BY RANGE (k2) (\n" +
+                    "    START (\"20140101\") END (\"20150101\") EVERY (INTERVAL 1 YEAR)\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String alterSQL =
-                "ALTER TABLE test_partition_exists ADD PARTITION IF NOT EXISTS p20210701 VALUES LESS THAN ('2021-07-01')";
+                    "ALTER TABLE test_partition_exists ADD PARTITION IF NOT EXISTS p20210701 VALUES LESS THAN ('2021-07-01')";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
         AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_exists", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_exists", addPartitionClause);
 
         String alterSQL2 =
-                "ALTER TABLE test_partition_exists ADD PARTITION IF NOT EXISTS p20210701 VALUES LESS THAN ('2021-07-02')";
+                    "ALTER TABLE test_partition_exists ADD PARTITION IF NOT EXISTS p20210701 VALUES LESS THAN ('2021-07-02')";
         AlterTableStmt alterTableStmt2 = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL2, ctx);
         AddPartitionClause addPartitionClause2 = (AddPartitionClause) alterTableStmt2.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_exists", addPartitionClause2);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_exists", addPartitionClause2);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition_exists");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition_exists");
 
         Assert.assertEquals(2, table.getPartitions().size());
 
@@ -1679,41 +1681,41 @@ public void testCatalogAddPartitionsIfNotExist() throws Exception {
     public void testCatalogAddPartitionsSameNameShouldNotThrowError() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test_partition_exists2 (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "PARTITION BY RANGE (k2) (\n" +
-                "    START (\"20140101\") END (\"20150101\") EVERY (INTERVAL 1 YEAR)\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "PARTITION BY RANGE (k2) (\n" +
+                    "    START (\"20140101\") END (\"20150101\") EVERY (INTERVAL 1 YEAR)\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String alterSQL =
-                "ALTER TABLE test_partition_exists2 ADD PARTITION IF NOT EXISTS p20210701 VALUES LESS THAN ('2021-07-01')";
+                    "ALTER TABLE test_partition_exists2 ADD PARTITION IF NOT EXISTS p20210701 VALUES LESS THAN ('2021-07-01')";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
         AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_exists2", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_exists2", addPartitionClause);
 
         String alterSQL2 =
-                "ALTER TABLE test_partition_exists2 ADD PARTITION IF NOT EXISTS p20210701 VALUES LESS THAN ('2021-07-01')";
+                    "ALTER TABLE test_partition_exists2 ADD PARTITION IF NOT EXISTS p20210701 VALUES LESS THAN ('2021-07-01')";
         AlterTableStmt alterTableStmt2 = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL2, ctx);
         AddPartitionClause addPartitionClause2 = (AddPartitionClause) alterTableStmt2.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_exists2", addPartitionClause2);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_exists2", addPartitionClause2);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition_exists2");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition_exists2");
 
         Assert.assertEquals(2, table.getPartitions().size());
 
@@ -1726,39 +1728,39 @@ public void testCatalogAddPartitionsSameNameShouldNotThrowError() throws Excepti
     public void testCatalogAddPartitionsShouldThrowError() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test_partition_exists3 (\n" +
-                "      k2 DATE,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(k2, k3)\n" +
-                "PARTITION BY RANGE (k2) (\n" +
-                "    START (\"20140101\") END (\"20150101\") EVERY (INTERVAL 1 YEAR)\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      k2 DATE,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(k2, k3)\n" +
+                    "PARTITION BY RANGE (k2) (\n" +
+                    "    START (\"20140101\") END (\"20150101\") EVERY (INTERVAL 1 YEAR)\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String alterSQL = "ALTER TABLE test_partition_exists3 ADD PARTITION p20210701 VALUES LESS THAN ('2021-07-01')";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
         AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_exists3", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_exists3", addPartitionClause);
 
         String alterSQL2 = "ALTER TABLE test_partition_exists3 ADD PARTITION p20210701 VALUES LESS THAN ('2021-07-01')";
         AlterTableStmt alterTableStmt2 = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL2, ctx);
         AddPartitionClause addPartitionClause2 = (AddPartitionClause) alterTableStmt2.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_exists3", addPartitionClause2);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_exists3", addPartitionClause2);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition_exists3");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition_exists3");
 
         Assert.assertEquals(2, ((OlapTable) table).getPartitions().size());
 
@@ -1771,14 +1773,14 @@ public void testCatalogAddPartitionsShouldThrowError() throws Exception {
     public void testRenameDb() throws Exception {
         String createUserSql = "CREATE USER 'testuser' IDENTIFIED BY ''";
         CreateUserStmt createUserStmt =
-                (CreateUserStmt) UtFrameUtils.parseStmtWithNewParser(createUserSql, starRocksAssert.getCtx());
+                    (CreateUserStmt) UtFrameUtils.parseStmtWithNewParser(createUserSql, starRocksAssert.getCtx());
         AuthenticationMgr authenticationManager =
-                starRocksAssert.getCtx().getGlobalStateMgr().getAuthenticationMgr();
+                    starRocksAssert.getCtx().getGlobalStateMgr().getAuthenticationMgr();
         authenticationManager.createUser(createUserStmt);
 
         String sql = "grant ALTER on database test to testuser";
         DDLStmtExecutor.execute(UtFrameUtils.parseStmtWithNewParser(sql, starRocksAssert.getCtx()),
-                starRocksAssert.getCtx());
+                    starRocksAssert.getCtx());
 
         UserIdentity testUser = new UserIdentity("testuser", "%");
         testUser.analyze();
@@ -1786,13 +1788,13 @@ public void testRenameDb() throws Exception {
         starRocksAssert.getCtx().setQualifiedUser("testuser");
         starRocksAssert.getCtx().setCurrentUserIdentity(testUser);
         starRocksAssert.getCtx().setCurrentRoleIds(
-                GlobalStateMgr.getCurrentState().getAuthorizationMgr().getRoleIdsByUser(testUser));
+                    GlobalStateMgr.getCurrentState().getAuthorizationMgr().getRoleIdsByUser(testUser));
         starRocksAssert.getCtx().setRemoteIP("%");
 
         starRocksAssert.withDatabase("test_to_rename");
         String renameDb = "alter database test_to_rename rename test_to_rename_2";
         AlterDatabaseRenameStatement renameDbStmt =
-                (AlterDatabaseRenameStatement) UtFrameUtils.parseStmtWithNewParser(renameDb, starRocksAssert.getCtx());
+                    (AlterDatabaseRenameStatement) UtFrameUtils.parseStmtWithNewParser(renameDb, starRocksAssert.getCtx());
         DDLStmtExecutor.execute(renameDbStmt, starRocksAssert.getCtx());
     }
 
@@ -1800,38 +1802,38 @@ public void testRenameDb() throws Exception {
     public void testAddMultiItemListPartition() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test.test_partition (\n" +
-                "      id BIGINT,\n" +
-                "      age SMALLINT,\n" +
-                "      dt VARCHAR(10) not null,\n" +
-                "      province VARCHAR(64) not null\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(id)\n" +
-                "PARTITION BY LIST (dt,province) (\n" +
-                "     PARTITION p1 VALUES IN ((\"2022-04-01\", \"beijing\"),(\"2022-04-01\", \"chongqing\")),\n" +
-                "     PARTITION p2 VALUES IN ((\"2022-04-01\", \"shanghai\")) \n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      id BIGINT,\n" +
+                    "      age SMALLINT,\n" +
+                    "      dt VARCHAR(10) not null,\n" +
+                    "      province VARCHAR(64) not null\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(id)\n" +
+                    "PARTITION BY LIST (dt,province) (\n" +
+                    "     PARTITION p1 VALUES IN ((\"2022-04-01\", \"beijing\"),(\"2022-04-01\", \"chongqing\")),\n" +
+                    "     PARTITION p2 VALUES IN ((\"2022-04-01\", \"shanghai\")) \n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         List<String> values = Lists.newArrayList("2022-04-01", "shandong");
         List<List<String>> multiValues = Lists.newArrayList();
         multiValues.add(values);
         PartitionDesc partitionDesc = new MultiItemListPartitionDesc(false, "p3", multiValues, new HashMap<>());
         AddPartitionClause addPartitionClause = new AddPartitionClause(partitionDesc, null, new HashMap<>(), false);
-        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_partition");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_partition");
 
         AlterTableClauseAnalyzer analyzer = new AlterTableClauseAnalyzer(table);
         analyzer.analyze(Util.getOrCreateConnectContext(), addPartitionClause);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
 
         ListPartitionInfo partitionInfo = (ListPartitionInfo) table.getPartitionInfo();
         Map<Long, List<List<String>>> idToValues = partitionInfo.getIdToMultiValues();
@@ -1850,15 +1852,15 @@ public void testAddMultiItemListPartition() throws Exception {
     public void testModifyPartitionBucket() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE modify_bucket (\n" +
-                "  chuangyi varchar(65533) NULL COMMENT \"创意\",\n" +
-                "  guanggao varchar(65533) NULL COMMENT \"广告\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(chuangyi, guanggao)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(chuangyi, guanggao) BUCKETS 3\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\"\n" +
-                ");";
+                    "  chuangyi varchar(65533) NULL COMMENT \"创意\",\n" +
+                    "  guanggao varchar(65533) NULL COMMENT \"广告\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(chuangyi, guanggao)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(chuangyi, guanggao) BUCKETS 3\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\"\n" +
+                    ");";
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
         String stmt = "alter table modify_bucket set (\"dynamic_partition.buckets\" = \"10\");\n";
@@ -1870,34 +1872,35 @@ public void testModifyPartitionBucket() throws Exception {
     public void testAddSingleItemListPartition() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test.test_partition (\n" +
-                "      id BIGINT,\n" +
-                "      age SMALLINT,\n" +
-                "      dt VARCHAR(10),\n" +
-                "      province VARCHAR(64) not null\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(id)\n" +
-                "PARTITION BY LIST (province) (\n" +
-                "     PARTITION p1 VALUES IN (\"beijing\",\"chongqing\") ,\n" +
-                "     PARTITION p2 VALUES IN (\"guangdong\") \n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      id BIGINT,\n" +
+                    "      age SMALLINT,\n" +
+                    "      dt VARCHAR(10),\n" +
+                    "      province VARCHAR(64) not null\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(id)\n" +
+                    "PARTITION BY LIST (province) (\n" +
+                    "     PARTITION p1 VALUES IN (\"beijing\",\"chongqing\") ,\n" +
+                    "     PARTITION p2 VALUES IN (\"guangdong\") \n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         List<String> values = Lists.newArrayList("shanxi", "shanghai");
         PartitionDesc partitionDesc = new SingleItemListPartitionDesc(false, "p3", values, new HashMap<>());
         AddPartitionClause addPartitionClause = new AddPartitionClause(partitionDesc, null, new HashMap<>(), false);
-        OlapTable table = (OlapTable) db.getTable("test_partition");
+        OlapTable table =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_partition");
         AlterTableClauseAnalyzer analyzer = new AlterTableClauseAnalyzer(table);
         analyzer.analyze(Util.getOrCreateConnectContext(), addPartitionClause);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition", addPartitionClause);
         ListPartitionInfo partitionInfo = (ListPartitionInfo) table.getPartitionInfo();
         Map<Long, List<String>> idToValues = partitionInfo.getIdToValues();
 
@@ -1915,25 +1918,26 @@ public void testAddSingleItemListPartition() throws Exception {
     public void testSingleItemPartitionPersistInfo() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test.test_partition (\n" +
-                "      id BIGINT,\n" +
-                "      age SMALLINT,\n" +
-                "      dt VARCHAR(10),\n" +
-                "      province VARCHAR(64) not null\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(id)\n" +
-                "PARTITION BY LIST (province) (\n" +
-                "     PARTITION p1 VALUES IN (\"beijing\",\"chongqing\") \n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      id BIGINT,\n" +
+                    "      age SMALLINT,\n" +
+                    "      dt VARCHAR(10),\n" +
+                    "      province VARCHAR(64) not null\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(id)\n" +
+                    "PARTITION BY LIST (province) (\n" +
+                    "     PARTITION p1 VALUES IN (\"beijing\",\"chongqing\") \n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("test_partition");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_partition");
         ListPartitionInfo partitionInfo = (ListPartitionInfo) table.getPartitionInfo();
 
         long dbId = db.getId();
@@ -1946,8 +1950,8 @@ public void testSingleItemPartitionPersistInfo() throws Exception {
         boolean isInMemory = partitionInfo.getIsInMemory(partitionId);
         boolean isTempPartition = false;
         ListPartitionPersistInfo partitionPersistInfoOut = new ListPartitionPersistInfo(dbId, tableId, partition,
-                dataProperty, replicationNum, isInMemory, isTempPartition, values, new ArrayList<>(),
-                partitionInfo.getDataCacheInfo(partitionId));
+                    dataProperty, replicationNum, isInMemory, isTempPartition, values, new ArrayList<>(),
+                    partitionInfo.getDataCacheInfo(partitionId));
 
         // write log
         File file = new File("./test_serial.log");
@@ -1992,25 +1996,26 @@ public void testSingleItemPartitionPersistInfo() throws Exception {
     public void testMultiItemPartitionPersistInfo() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test.test_partition (\n" +
-                "      id BIGINT,\n" +
-                "      age SMALLINT,\n" +
-                "      dt VARCHAR(10) not null,\n" +
-                "      province VARCHAR(64) not null\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(id)\n" +
-                "PARTITION BY LIST (dt , province) (\n" +
-                "     PARTITION p1 VALUES IN ((\"2022-04-01\", \"beijing\"),(\"2022-04-01\", \"chongqing\"))\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      id BIGINT,\n" +
+                    "      age SMALLINT,\n" +
+                    "      dt VARCHAR(10) not null,\n" +
+                    "      province VARCHAR(64) not null\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(id)\n" +
+                    "PARTITION BY LIST (dt , province) (\n" +
+                    "     PARTITION p1 VALUES IN ((\"2022-04-01\", \"beijing\"),(\"2022-04-01\", \"chongqing\"))\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("test_partition");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_partition");
         ListPartitionInfo partitionInfo = (ListPartitionInfo) table.getPartitionInfo();
 
         long dbId = db.getId();
@@ -2023,8 +2028,8 @@ public void testMultiItemPartitionPersistInfo() throws Exception {
         boolean isInMemory = partitionInfo.getIsInMemory(partitionId);
         boolean isTempPartition = false;
         ListPartitionPersistInfo partitionPersistInfoOut = new ListPartitionPersistInfo(dbId, tableId, partition,
-                dataProperty, replicationNum, isInMemory, isTempPartition, new ArrayList<>(), multiValues,
-                partitionInfo.getDataCacheInfo(partitionId));
+                    dataProperty, replicationNum, isInMemory, isTempPartition, new ArrayList<>(), multiValues,
+                    partitionInfo.getDataCacheInfo(partitionId));
 
         // write log
         File file = new File("./test_serial.log");
@@ -2073,61 +2078,61 @@ public void testMultiItemPartitionPersistInfo() throws Exception {
     public void testAddSingleListPartitionSamePartitionNameShouldThrowError() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test.test_partition_1 (\n" +
-                "      id BIGINT,\n" +
-                "      age SMALLINT,\n" +
-                "      dt VARCHAR(10),\n" +
-                "      province VARCHAR(64) not null\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(id)\n" +
-                "PARTITION BY LIST (province) (\n" +
-                "     PARTITION p1 VALUES IN (\"beijing\",\"chongqing\") ,\n" +
-                "     PARTITION p2 VALUES IN (\"guangdong\") \n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      id BIGINT,\n" +
+                    "      age SMALLINT,\n" +
+                    "      dt VARCHAR(10),\n" +
+                    "      province VARCHAR(64) not null\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(id)\n" +
+                    "PARTITION BY LIST (province) (\n" +
+                    "     PARTITION p1 VALUES IN (\"beijing\",\"chongqing\") ,\n" +
+                    "     PARTITION p2 VALUES IN (\"guangdong\") \n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         List<String> values = Lists.newArrayList("shanxi", "heilongjiang");
         PartitionDesc partitionDesc = new SingleItemListPartitionDesc(false, "p1", values, new HashMap<>());
         AddPartitionClause addPartitionClause = new AddPartitionClause(partitionDesc, null, new HashMap<>(), false);
 
-        Table table = db.getTable("test_partition_1");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_partition_1");
         AlterTableClauseAnalyzer analyzer = new AlterTableClauseAnalyzer(table);
         analyzer.analyze(Util.getOrCreateConnectContext(), addPartitionClause);
 
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_1", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_1", addPartitionClause);
     }
 
     @Test(expected = SemanticException.class)
     public void testAddMultiListPartitionSamePartitionNameShouldThrowError() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test.test_partition_2 (\n" +
-                "      id BIGINT,\n" +
-                "      age SMALLINT,\n" +
-                "      dt VARCHAR(10) not null,\n" +
-                "      province VARCHAR(64) not null\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(id)\n" +
-                "PARTITION BY LIST (dt,province) (\n" +
-                "     PARTITION p1 VALUES IN ((\"2022-04-01\", \"beijing\"),(\"2022-04-01\", \"chongqing\")),\n" +
-                "     PARTITION p2 VALUES IN ((\"2022-04-01\", \"shanghai\")) \n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      id BIGINT,\n" +
+                    "      age SMALLINT,\n" +
+                    "      dt VARCHAR(10) not null,\n" +
+                    "      province VARCHAR(64) not null\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(id)\n" +
+                    "PARTITION BY LIST (dt,province) (\n" +
+                    "     PARTITION p1 VALUES IN ((\"2022-04-01\", \"beijing\"),(\"2022-04-01\", \"chongqing\")),\n" +
+                    "     PARTITION p2 VALUES IN ((\"2022-04-01\", \"shanghai\")) \n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         List<String> values1 = Lists.newArrayList("2022-04-01", "beijing");
         List<String> values2 = Lists.newArrayList("2022-04-01", "chongqing");
@@ -2137,41 +2142,41 @@ public void testAddMultiListPartitionSamePartitionNameShouldThrowError() throws
         PartitionDesc partitionDesc = new MultiItemListPartitionDesc(false, "p1", multiValues, new HashMap<>());
         AddPartitionClause addPartitionClause = new AddPartitionClause(partitionDesc, null, new HashMap<>(), false);
 
-        Table table = db.getTable("test_partition_2");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_partition_2");
         AlterTableClauseAnalyzer analyzer = new AlterTableClauseAnalyzer(table);
         analyzer.analyze(Util.getOrCreateConnectContext(), addPartitionClause);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_2", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_partition_2", addPartitionClause);
     }
 
     @Test(expected = SemanticException.class)
     public void testAddSingleListPartitionSamePartitionValueShouldThrowError() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test.test_partition_3 (\n" +
-                "      id BIGINT,\n" +
-                "      age SMALLINT,\n" +
-                "      dt VARCHAR(10),\n" +
-                "      province VARCHAR(64) not null\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(id)\n" +
-                "PARTITION BY LIST (province) (\n" +
-                "     PARTITION p1 VALUES IN (\"beijing\",\"chongqing\") ,\n" +
-                "     PARTITION p2 VALUES IN (\"guangdong\") \n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      id BIGINT,\n" +
+                    "      age SMALLINT,\n" +
+                    "      dt VARCHAR(10),\n" +
+                    "      province VARCHAR(64) not null\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(id)\n" +
+                    "PARTITION BY LIST (province) (\n" +
+                    "     PARTITION p1 VALUES IN (\"beijing\",\"chongqing\") ,\n" +
+                    "     PARTITION p2 VALUES IN (\"guangdong\") \n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         List<String> values = Lists.newArrayList("beijing", "chongqing");
         PartitionDesc partitionDesc = new SingleItemListPartitionDesc(false, "p3", values, new HashMap<>());
         AddPartitionClause addPartitionClause = new AddPartitionClause(partitionDesc, null, new HashMap<>(), false);
-        Table table = db.getTable("test_partition_3");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_partition_3");
         AlterTableClauseAnalyzer analyzer = new AlterTableClauseAnalyzer(table);
         analyzer.analyze(Util.getOrCreateConnectContext(), addPartitionClause);
     }
@@ -2180,25 +2185,25 @@ public void testAddSingleListPartitionSamePartitionValueShouldThrowError() throw
     public void testAddMultiItemListPartitionSamePartitionValueShouldThrowError() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test.test_partition_4 (\n" +
-                "      id BIGINT,\n" +
-                "      age SMALLINT,\n" +
-                "      dt VARCHAR(10) not null,\n" +
-                "      province VARCHAR(64) not null\n" +
-                ")\n" +
-                "ENGINE=olap\n" +
-                "DUPLICATE KEY(id)\n" +
-                "PARTITION BY LIST (dt, province) (\n" +
-                "     PARTITION p1 VALUES IN ((\"2022-04-01\", \"beijing\"),(\"2022-04-01\", \"chongqing\")),\n" +
-                "     PARTITION p2 VALUES IN ((\"2022-04-01\", \"shanghai\")) \n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "      id BIGINT,\n" +
+                    "      age SMALLINT,\n" +
+                    "      dt VARCHAR(10) not null,\n" +
+                    "      province VARCHAR(64) not null\n" +
+                    ")\n" +
+                    "ENGINE=olap\n" +
+                    "DUPLICATE KEY(id)\n" +
+                    "PARTITION BY LIST (dt, province) (\n" +
+                    "     PARTITION p1 VALUES IN ((\"2022-04-01\", \"beijing\"),(\"2022-04-01\", \"chongqing\")),\n" +
+                    "     PARTITION p2 VALUES IN ((\"2022-04-01\", \"shanghai\")) \n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(id) BUCKETS 10\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         List<String> values = Lists.newArrayList("2022-04-01", "shanghai");
         List<List<String>> multiValues = Lists.newArrayList();
@@ -2206,7 +2211,7 @@ public void testAddMultiItemListPartitionSamePartitionValueShouldThrowError() th
         PartitionDesc partitionDesc = new MultiItemListPartitionDesc(false, "p3", multiValues, new HashMap<>());
         AddPartitionClause addPartitionClause = new AddPartitionClause(partitionDesc, null, new HashMap<>(), false);
 
-        Table table = db.getTable("test_partition_4");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_partition_4");
         AlterTableClauseAnalyzer analyzer = new AlterTableClauseAnalyzer(table);
         analyzer.analyze(Util.getOrCreateConnectContext(), addPartitionClause);
     }
@@ -2214,16 +2219,16 @@ public void testAddMultiItemListPartitionSamePartitionValueShouldThrowError() th
     @Test
     public void testCatalogAddColumn() throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.tbl1\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    v1 int \n" +
-                        ")\n" +
-                        "DUPLICATE KEY(`k1`)" +
-                        "DISTRIBUTED BY HASH (k1) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');");
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("tbl1");
+                    .withTable("CREATE TABLE test.tbl1\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    v1 int \n" +
+                                ")\n" +
+                                "DUPLICATE KEY(`k1`)" +
+                                "DISTRIBUTED BY HASH (k1) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl1");
 
         String stmt = "alter table test.tbl1 add column k2 int";
         alterTableWithNewParser(stmt, false);
@@ -2245,7 +2250,7 @@ public void testCatalogAddColumn() throws Exception {
     @Test
     public void testCatalogAddColumns() throws Exception {
         String stmt = "alter table test.tbl1 add column (`col1` int(11) not null default \"0\" comment \"\", "
-                + "`col2` int(11) not null default \"0\" comment \"\") in `testTable`;";
+                    + "`col2` int(11) not null default \"0\" comment \"\") in `testTable`;";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(stmt, starRocksAssert.getCtx());
         AddColumnsClause clause = (AddColumnsClause) alterTableStmt.getAlterClauseList().get(0);
         Assert.assertEquals(2, clause.getColumns().size());
@@ -2253,7 +2258,7 @@ public void testCatalogAddColumns() throws Exception {
         Assert.assertEquals("testTable", clause.getRollupName());
 
         stmt = "alter table test.tbl1 add column (`col1` int(11) not null default \"0\" comment \"\", "
-                + "`col2` int(11) not null default \"0\" comment \"\");";
+                    + "`col2` int(11) not null default \"0\" comment \"\");";
         alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(stmt, starRocksAssert.getCtx());
         clause = (AddColumnsClause) alterTableStmt.getAlterClauseList().get(0);
         Assert.assertEquals(null, clause.getRollupName());
@@ -2264,35 +2269,35 @@ public void testCreateTemporaryPartitionInBatch() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         starRocksAssert.withDatabase("test2");
         String createSQL = "CREATE TABLE test2.site_access(\n" +
-                "    event_day datetime,\n" +
-                "    site_id INT DEFAULT '10',\n" +
-                "    city_code VARCHAR(100),\n" +
-                "    user_name VARCHAR(32) DEFAULT '',\n" +
-                "    pv BIGINT DEFAULT '0'\n" +
-                ")\n" +
-                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                "PARTITION BY date_trunc('day', event_day)(\n" +
-                " START (\"2023-03-27\") END (\"2023-03-30\") EVERY (INTERVAL 1 day)\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
-                "PROPERTIES(\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ");";
+                    "    event_day datetime,\n" +
+                    "    site_id INT DEFAULT '10',\n" +
+                    "    city_code VARCHAR(100),\n" +
+                    "    user_name VARCHAR(32) DEFAULT '',\n" +
+                    "    pv BIGINT DEFAULT '0'\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                    "PARTITION BY date_trunc('day', event_day)(\n" +
+                    " START (\"2023-03-27\") END (\"2023-03-30\") EVERY (INTERVAL 1 day)\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
+                    "PROPERTIES(\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ");";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test2");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test2");
 
         String sql = "alter table test2.site_access add TEMPORARY partitions " +
-                "START (\"2023-03-27\") END (\"2023-03-30\") EVERY (INTERVAL 1 day);";
+                    "START (\"2023-03-27\") END (\"2023-03-30\") EVERY (INTERVAL 1 day);";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, starRocksAssert.getCtx());
         AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
 
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "site_access", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "site_access", addPartitionClause);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test2")
-                .getTable("site_access");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test2")
+                    .getTable("site_access");
         OlapTable olapTable = (OlapTable) table;
         PartitionInfo partitionInfo = olapTable.getPartitionInfo();
         RangePartitionInfo rangePartitionInfo = (RangePartitionInfo) partitionInfo;
@@ -2303,14 +2308,14 @@ public void testCreateTemporaryPartitionInBatch() throws Exception {
     @Test
     public void testCatalogDropColumn() throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.tbl1\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');");
+                    .withTable("CREATE TABLE test.tbl1\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');");
         String stmt = "alter table test.tbl1 drop column k2 from `testRollup`";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(stmt, starRocksAssert.getCtx());
         DropColumnClause clause = (DropColumnClause) alterTableStmt.getAlterClauseList().get(0);
@@ -2411,9 +2416,9 @@ public Table getTable(String tableName) {
         TruncatePartitionClause clause = new TruncatePartitionClause(partitionNames);
         cList.add(clause);
         AlterJobMgr alter = new AlterJobMgr(
-                new SchemaChangeHandler(),
-                new MaterializedViewHandler(),
-                new SystemHandler());
+                    new SchemaChangeHandler(),
+                    new MaterializedViewHandler(),
+                    new SystemHandler());
         TableName tableName = new TableName("test_db", "test_table");
         AlterTableStmt stmt = new AlterTableStmt(tableName, cList);
         DDLStmtExecutor.execute(stmt, starRocksAssert.getCtx());
@@ -2439,7 +2444,7 @@ public void testAutoPartitionTableUnsupported() throws Exception {
     public void testAutoPartitionTableUnsupported2() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String sql = "ALTER TABLE site_access_time_slice\n" +
-                "ADD PARTITIONS START (\"2022-05-01\") END (\"2022-05-03\") EVERY (INTERVAL 1 day)";
+                    "ADD PARTITIONS START (\"2022-05-01\") END (\"2022-05-03\") EVERY (INTERVAL 1 day)";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().alterTable(ctx, alterTableStmt);
     }
@@ -2448,7 +2453,7 @@ public void testAutoPartitionTableUnsupported2() throws Exception {
     public void testAutoPartitionTableUnsupported3() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String sql = "ALTER TABLE site_access_date_trunc\n" +
-                "ADD PARTITIONS START (\"2022-05-01\") END (\"2022-05-03\") EVERY (INTERVAL 2 day)";
+                    "ADD PARTITIONS START (\"2022-05-01\") END (\"2022-05-03\") EVERY (INTERVAL 2 day)";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().alterTable(ctx, alterTableStmt);
     }
@@ -2456,43 +2461,44 @@ public void testAutoPartitionTableUnsupported3() throws Exception {
     @Test
     public void testAlterMvWithResourceGroup() throws Exception {
         starRocksAssert.executeResourceGroupDdlSql("create resource group if not exists mv_rg" +
-                "   with (" +
-                "   'cpu_core_limit' = '10'," +
-                "   'mem_limit' = '20%'," +
-                "   'concurrency_limit' = '11'," +
-                "   'type' = 'mv'" +
-                "    );");
+                    "   with (" +
+                    "   'cpu_core_limit' = '10'," +
+                    "   'mem_limit' = '20%'," +
+                    "   'concurrency_limit' = '11'," +
+                    "   'type' = 'mv'" +
+                    "    );");
         starRocksAssert.useDatabase("test")
-                .withMaterializedView("CREATE MATERIALIZED VIEW `mv2` (a comment \"a1\", b comment \"b2\", c)\n" +
-                        "COMMENT \"MATERIALIZED_VIEW\"\n" +
-                        "DISTRIBUTED BY HASH(a) BUCKETS 12\n" +
-                        "REFRESH ASYNC\n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\",\n" +
-                        "\"replicated_storage\" = \"true\",\n" +
-                        "\"resource_group\" = \"mv_rg\",\n" +
-                        "\"storage_medium\" = \"HDD\"\n" +
-                        ")\n" +
-                        "AS SELECT k1, k2, v1 from test.tbl1");
-        MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState().getDb("test").getTable("mv2");
+                    .withMaterializedView("CREATE MATERIALIZED VIEW `mv2` (a comment \"a1\", b comment \"b2\", c)\n" +
+                                "COMMENT \"MATERIALIZED_VIEW\"\n" +
+                                "DISTRIBUTED BY HASH(a) BUCKETS 12\n" +
+                                "REFRESH ASYNC\n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\",\n" +
+                                "\"replicated_storage\" = \"true\",\n" +
+                                "\"resource_group\" = \"mv_rg\",\n" +
+                                "\"storage_medium\" = \"HDD\"\n" +
+                                ")\n" +
+                                "AS SELECT k1, k2, v1 from test.tbl1");
+        MaterializedView mv =
+                    (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("mv2");
         Assert.assertEquals("mv_rg", mv.getTableProperty().getResourceGroup());
         ConnectContext ctx = starRocksAssert.getCtx();
         String sql = "ALTER MATERIALIZED VIEW mv2\n" +
-                "set (\"resource_group\" =\"\" )";
+                    "set (\"resource_group\" =\"\" )";
         AlterMaterializedViewStmt alterTableStmt = (AlterMaterializedViewStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().alterMaterializedView(alterTableStmt);
         Assert.assertEquals("", mv.getTableProperty().getResourceGroup());
         sql = "ALTER MATERIALIZED VIEW mv2\n" +
-                "set (\"resource_group\" =\"not_exist_rg\" )";
+                    "set (\"resource_group\" =\"not_exist_rg\" )";
         AlterMaterializedViewStmt alterTableStmt2 =
-                (AlterMaterializedViewStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
+                    (AlterMaterializedViewStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
         Assert.assertThrows("resource_group not_exist_rg does not exist.",
-                SemanticException.class,
-                () -> GlobalStateMgr.getCurrentState().getLocalMetastore().alterMaterializedView(alterTableStmt2));
+                    SemanticException.class,
+                    () -> GlobalStateMgr.getCurrentState().getLocalMetastore().alterMaterializedView(alterTableStmt2));
         sql = "ALTER MATERIALIZED VIEW mv2\n" +
-                "set (\"resource_group\" =\"mv_rg\" )";
+                    "set (\"resource_group\" =\"mv_rg\" )";
         AlterMaterializedViewStmt alterTableStmt3 =
-                (AlterMaterializedViewStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
+                    (AlterMaterializedViewStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().alterMaterializedView(alterTableStmt3);
         Assert.assertEquals("mv_rg", mv.getTableProperty().getResourceGroup());
 
@@ -2504,7 +2510,7 @@ public Warehouse getWarehouse(String warehouseName) {
         };
         sql = "ALTER MATERIALIZED VIEW mv2 set (\"warehouse\" = \"w1\")";
         AlterMaterializedViewStmt alterTableStmt4 =
-                (AlterMaterializedViewStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
+                    (AlterMaterializedViewStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().alterMaterializedView(alterTableStmt4);
         Assert.assertEquals(1L, mv.getWarehouseId());
     }
@@ -2512,19 +2518,19 @@ public Warehouse getWarehouse(String warehouseName) {
     @Test(expected = ErrorReportException.class)
     public void testAlterListPartitionUseBatchBuildPartition() throws Exception {
         starRocksAssert.useDatabase("test").withTable("CREATE TABLE t2 (\n" +
-                "    dt datetime  not null,\n" +
-                "    user_id  bigint  not null,\n" +
-                "    recharge_money decimal(32,2) not null, \n" +
-                "    province varchar(20) not null,\n" +
-                "    id varchar(20) not null\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(dt)\n" +
-                "PARTITION BY (dt)\n" +
-                "DISTRIBUTED BY HASH(`dt`) BUCKETS 10 \n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"in_memory\" = \"false\"\n" +
-                ");");
+                    "    dt datetime  not null,\n" +
+                    "    user_id  bigint  not null,\n" +
+                    "    recharge_money decimal(32,2) not null, \n" +
+                    "    province varchar(20) not null,\n" +
+                    "    id varchar(20) not null\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(dt)\n" +
+                    "PARTITION BY (dt)\n" +
+                    "DISTRIBUTED BY HASH(`dt`) BUCKETS 10 \n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"in_memory\" = \"false\"\n" +
+                    ");");
         ConnectContext ctx = starRocksAssert.getCtx();
         String sql = "ALTER TABLE t2 ADD PARTITIONS START (\"2021-01-04\") END (\"2021-01-06\") EVERY (INTERVAL 1 DAY);";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
@@ -2538,25 +2544,25 @@ public void testAlterForeignKey() throws Exception {
         {
             // inner table
             starRocksAssert.useDatabase("test").withMaterializedView("create materialized view if not exists `fk_mv_1` " +
-                    "refresh manual " +
-                    "as " +
-                    "select t1.event_day, t1.site_id, t2.user_name " +
-                    "from site_access_date_trunc t1 join site_access_time_slice t2 " +
-                    "on t1.site_id = t2.site_id");
+                        "refresh manual " +
+                        "as " +
+                        "select t1.event_day, t1.site_id, t2.user_name " +
+                        "from site_access_date_trunc t1 join site_access_time_slice t2 " +
+                        "on t1.site_id = t2.site_id");
             connectContext.executeSql("alter materialized view fk_mv_1 set " +
-                    "( 'unique_constraints'='site_access_date_trunc.site_id'); ");
+                        "( 'unique_constraints'='site_access_date_trunc.site_id'); ");
             connectContext.executeSql("alter materialized view fk_mv_1 set " +
-                    "( 'foreign_key_constraints'='site_access_time_slice(site_id)" +
-                    " REFERENCES site_access_date_trunc(site_id)'); ");
+                        "( 'foreign_key_constraints'='site_access_time_slice(site_id)" +
+                        " REFERENCES site_access_date_trunc(site_id)'); ");
             while (true) {
                 ModifyTablePropertyOperationLog modifyMvLog =
-                        (ModifyTablePropertyOperationLog) UtFrameUtils.PseudoJournalReplayer.
-                                replayNextJournal(OperationType.OP_ALTER_MATERIALIZED_VIEW_PROPERTIES);
+                            (ModifyTablePropertyOperationLog) UtFrameUtils.PseudoJournalReplayer.
+                                        replayNextJournal(OperationType.OP_ALTER_MATERIALIZED_VIEW_PROPERTIES);
                 Assert.assertNotNull(modifyMvLog);
                 if (modifyMvLog.getProperties().containsKey("foreign_key_constraints")) {
                     Assert.assertEquals("default_catalog.10001.10133(site_id) " +
-                                    "REFERENCES default_catalog.10001.10118(site_id)",
-                            modifyMvLog.getProperties().get("foreign_key_constraints"));
+                                            "REFERENCES default_catalog.10001.10118(site_id)",
+                                modifyMvLog.getProperties().get("foreign_key_constraints"));
                     break;
                 }
             }
@@ -2565,24 +2571,24 @@ public void testAlterForeignKey() throws Exception {
         {
             // external table
             starRocksAssert.withMaterializedView("create materialized view if not exists `fk_mv_2` " +
-                    "refresh manual " +
-                    "as " +
-                    "select t1.l_orderkey, t1.l_partkey, t2.o_totalprice " +
-                    "from hive0.tpch.lineitem t1 join hive0.tpch.orders t2 " +
-                    "on t1.l_orderkey = t2.o_orderkey");
+                        "refresh manual " +
+                        "as " +
+                        "select t1.l_orderkey, t1.l_partkey, t2.o_totalprice " +
+                        "from hive0.tpch.lineitem t1 join hive0.tpch.orders t2 " +
+                        "on t1.l_orderkey = t2.o_orderkey");
             connectContext.executeSql("alter materialized view fk_mv_2 set " +
-                    "( 'unique_constraints'='hive0.tpch.orders.o_orderkey'); ");
+                        "( 'unique_constraints'='hive0.tpch.orders.o_orderkey'); ");
             connectContext.executeSql("alter materialized view fk_mv_2 set " +
-                    "( 'foreign_key_constraints'='hive0.tpch.lineitem(l_orderkey) " +
-                    "REFERENCES hive0.tpch.orders(o_orderkey)'); ");
+                        "( 'foreign_key_constraints'='hive0.tpch.lineitem(l_orderkey) " +
+                        "REFERENCES hive0.tpch.orders(o_orderkey)'); ");
             while (true) {
                 ModifyTablePropertyOperationLog modifyMvLog =
-                        (ModifyTablePropertyOperationLog) UtFrameUtils.PseudoJournalReplayer.
-                                replayNextJournal(OperationType.OP_ALTER_MATERIALIZED_VIEW_PROPERTIES);
+                            (ModifyTablePropertyOperationLog) UtFrameUtils.PseudoJournalReplayer.
+                                        replayNextJournal(OperationType.OP_ALTER_MATERIALIZED_VIEW_PROPERTIES);
                 Assert.assertNotNull(modifyMvLog);
                 if (modifyMvLog.getProperties().containsKey("foreign_key_constraints")) {
                     Assert.assertEquals("hive0.tpch.lineitem:0(l_orderkey) REFERENCES hive0.tpch.orders:0(o_orderkey)",
-                            modifyMvLog.getProperties().get("foreign_key_constraints"));
+                                modifyMvLog.getProperties().get("foreign_key_constraints"));
                     break;
                 }
             }
diff --git a/fe/fe-core/src/test/java/com/starrocks/alter/BatchRollupJobTest.java b/fe/fe-core/src/test/java/com/starrocks/alter/BatchRollupJobTest.java
index c020c02f4c4121..455a5a9cd23221 100644
--- a/fe/fe-core/src/test/java/com/starrocks/alter/BatchRollupJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/alter/BatchRollupJobTest.java
@@ -92,9 +92,9 @@ public void testBatchRollup() throws Exception {
         Map<Long, AlterJobV2> alterJobs = GlobalStateMgr.getCurrentState().getRollupHandler().getAlterJobsV2();
         Assert.assertEquals(3, alterJobs.size());
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("db1");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db1");
         Assert.assertNotNull(db);
-        OlapTable tbl = (OlapTable) db.getTable("tbl1");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl1");
         Assert.assertNotNull(tbl);
 
         // 3 rollup jobs may be finished in the loop, so only check the final state at last.
@@ -138,9 +138,9 @@ public void testCancelBatchRollup() throws Exception {
         Assert.assertEquals(3, alterJobs.size());
         List<Long> jobIds = Lists.newArrayList(alterJobs.keySet());
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("db1");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db1");
         Assert.assertNotNull(db);
-        OlapTable tbl = (OlapTable) db.getTable("tbl2");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl2");
         Assert.assertNotNull(tbl);
         Assert.assertEquals(OlapTableState.ROLLUP, tbl.getState());
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/alter/CompactionHandlerTest.java b/fe/fe-core/src/test/java/com/starrocks/alter/CompactionHandlerTest.java
index a49e5d67357641..f2304f95335972 100644
--- a/fe/fe-core/src/test/java/com/starrocks/alter/CompactionHandlerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/alter/CompactionHandlerTest.java
@@ -52,25 +52,26 @@ public static void beforeClass() throws Exception {
         connectContext = UtFrameUtils.createDefaultCtx();
         starRocksAssert = new StarRocksAssert(connectContext);
         starRocksAssert.withDatabase(GlobalStateMgrTestUtil.testDb1)
-                .useDatabase(GlobalStateMgrTestUtil.testDb1);
+                    .useDatabase(GlobalStateMgrTestUtil.testDb1);
 
         starRocksAssert.withTable("CREATE TABLE testTable1\n" +
-                "(\n" +
-                "    v1 date,\n" +
-                "    v2 int,\n" +
-                "    v3 int\n" +
-                ")\n" +
-                "DUPLICATE KEY(`v1`)\n" +
-                "PARTITION BY RANGE(v1)\n" +
-                "(\n" +
-                "    PARTITION p1 values less than('2020-02-01'),\n" +
-                "    PARTITION p2 values less than('2020-03-01')\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(v1) BUCKETS 3\n" +
-                "PROPERTIES('replication_num' = '1');");
-
-        db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable1);
+                    "(\n" +
+                    "    v1 date,\n" +
+                    "    v2 int,\n" +
+                    "    v3 int\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(`v1`)\n" +
+                    "PARTITION BY RANGE(v1)\n" +
+                    "(\n" +
+                    "    PARTITION p1 values less than('2020-02-01'),\n" +
+                    "    PARTITION p2 values less than('2020-03-01')\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(v1) BUCKETS 3\n" +
+                    "PROPERTIES('replication_num' = '1');");
+
+        db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable1);
     }
 
     @After
diff --git a/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableAlterDataCachePartitionDurationTest.java b/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableAlterDataCachePartitionDurationTest.java
index 51cf2c8caacee5..733f17281e57f7 100644
--- a/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableAlterDataCachePartitionDurationTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableAlterDataCachePartitionDurationTest.java
@@ -50,7 +50,7 @@
 import com.starrocks.persist.ModifyTablePropertyOperationLog;
 import com.starrocks.qe.ConnectContext;
 import com.starrocks.server.GlobalStateMgr;
-import com.starrocks.server.MetadataMgr;
+import com.starrocks.server.LocalMetastore;
 import com.starrocks.sql.ast.AlterTableStmt;
 import com.starrocks.sql.ast.ModifyTablePropertiesClause;
 import com.starrocks.thrift.TStorageMedium;
@@ -178,14 +178,14 @@ public void testModifyDataCachePartitionDurationAbourtMonths() throws Exception
         properties.put(PropertyAnalyzer.PROPERTIES_DATACACHE_PARTITION_DURATION, "7 months");
         ModifyTablePropertiesClause modify = new ModifyTablePropertiesClause(properties);
 
-        new MockUp<MetadataMgr>() {
+        new MockUp<LocalMetastore>() {
             @Mock
-            public Database getDb(String catalogName, String dbName) {
+            public Database getDb(String dbName) {
                 return db;
             }
 
             @Mock
-            public Table getTable(String catalogName, String dbName, String tblName) {
+            public Table getTable(String dbName, String tblName) {
                 return table;
             }
         };
@@ -213,14 +213,14 @@ public void testModifyDataCachePartitionDurationAbourtDays() throws Exception {
         properties.put(PropertyAnalyzer.PROPERTIES_DATACACHE_PARTITION_DURATION, "2 days");
         ModifyTablePropertiesClause modify = new ModifyTablePropertiesClause(properties);
 
-        new MockUp<MetadataMgr>() {
+        new MockUp<LocalMetastore>() {
             @Mock
-            public Database getDb(String catalogName, String dbName) {
+            public Database getDb(String dbName) {
                 return db;
             }
 
             @Mock
-            public Table getTable(String catalogName, String dbName, String tblName) {
+            public Table getTable(String dbName, String tblName) {
                 return table;
             }
         };
@@ -243,14 +243,14 @@ public void testModifyDataCachePartitionDurationAboutHours() throws Exception {
         Map<String, String> properties = new HashMap<>();
         properties.put(PropertyAnalyzer.PROPERTIES_DATACACHE_PARTITION_DURATION, "4 hours");
         ModifyTablePropertiesClause modify = new ModifyTablePropertiesClause(properties);
-        new MockUp<MetadataMgr>() {
+        new MockUp<LocalMetastore>() {
             @Mock
-            public Database getDb(String catalogName, String dbName) {
+            public Database getDb(String dbName) {
                 return db;
             }
 
             @Mock
-            public Table getTable(String catalogName, String dbName, String tblName) {
+            public Table getTable(String dbName, String tblName) {
                 return table;
             }
         };
diff --git a/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableAlterMetaJobTest.java b/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableAlterMetaJobTest.java
index f1d9bddfae5eb4..0b225ef82b2305 100644
--- a/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableAlterMetaJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableAlterMetaJobTest.java
@@ -78,11 +78,11 @@ public void setUp() throws Exception {
         db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(DB_NAME);
 
         table = createTable(connectContext,
-                "CREATE TABLE t0(c0 INT) PRIMARY KEY(c0) DISTRIBUTED BY HASH(c0) BUCKETS 1 " +
-                        "PROPERTIES('enable_persistent_index'='false')");
+                    "CREATE TABLE t0(c0 INT) PRIMARY KEY(c0) DISTRIBUTED BY HASH(c0) BUCKETS 1 " +
+                                "PROPERTIES('enable_persistent_index'='false')");
         Assert.assertFalse(table.enablePersistentIndex());
         job = new LakeTableAlterMetaJob(GlobalStateMgr.getCurrentState().getNextId(), db.getId(), table.getId(),
-                table.getName(), 60 * 1000, TTabletMetaType.ENABLE_PERSISTENT_INDEX, true);
+                    table.getName(), 60 * 1000, TTabletMetaType.ENABLE_PERSISTENT_INDEX, true);
     }
 
     @After
@@ -97,8 +97,9 @@ public void tearDown() throws DdlException, MetaNotFoundException {
     private static LakeTable createTable(ConnectContext connectContext, String sql) throws Exception {
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         GlobalStateMgr.getCurrentState().getLocalMetastore().createTable(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb(createTableStmt.getDbName());
-        return (LakeTable) db.getTable(createTableStmt.getTableName());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(createTableStmt.getDbName());
+        return (LakeTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), createTableStmt.getTableName());
     }
 
     @Test
@@ -121,7 +122,7 @@ public void testUpdatePartitonMetaFailed() {
             @Mock
             public Warehouse getWarehouse(long warehouseId) {
                 return new DefaultWarehouse(WarehouseManager.DEFAULT_WAREHOUSE_ID,
-                        WarehouseManager.DEFAULT_WAREHOUSE_NAME);
+                            WarehouseManager.DEFAULT_WAREHOUSE_NAME);
             }
 
             @Mock
@@ -208,8 +209,8 @@ public void testReplay() {
         Assert.assertEquals(AlterJobV2.JobState.FINISHED, job.getJobState());
 
         LakeTableAlterMetaJob replayAlterMetaJob = new LakeTableAlterMetaJob(job.jobId,
-                job.dbId, job.tableId, job.tableName,
-                job.timeoutMs, TTabletMetaType.ENABLE_PERSISTENT_INDEX, true);
+                    job.dbId, job.tableId, job.tableName,
+                    job.timeoutMs, TTabletMetaType.ENABLE_PERSISTENT_INDEX, true);
 
         Table<Long, Long, MaterializedIndex> partitionIndexMap = job.getPartitionIndexMap();
         Map<Long, Long> commitVersionMap = job.getCommitVersionMap();
@@ -249,7 +250,7 @@ public void testUpdateTabletMetaInfoTaskToThrift() throws AlterCancelException {
         tabletSet.add(1L);
         MarkedCountDownLatch<Long, Set<Long>> latch = new MarkedCountDownLatch<>(1);
         TabletMetadataUpdateAgentTask task = TabletMetadataUpdateAgentTaskFactory.createEnablePersistentIndexUpdateTask(
-                backend, tabletSet, true);
+                    backend, tabletSet, true);
         task.setLatch(latch);
         task.setTxnId(txnId);
         TUpdateTabletMetaInfoReq result = task.toThrift();
@@ -264,6 +265,6 @@ public void testSetPropertyNotSupport() {
         ModifyTablePropertiesClause modify = new ModifyTablePropertiesClause(properties);
         SchemaChangeHandler schemaChangeHandler = new SchemaChangeHandler();
         Assertions.assertThrows(DdlException.class,
-                () -> schemaChangeHandler.createAlterMetaJob(modify, db, table));
+                    () -> schemaChangeHandler.createAlterMetaJob(modify, db, table));
     }
 }
diff --git a/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableAsyncFastSchemaChangeJobTest.java b/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableAsyncFastSchemaChangeJobTest.java
index d7d2b9d56bccef..70d7fcae77fadd 100644
--- a/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableAsyncFastSchemaChangeJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableAsyncFastSchemaChangeJobTest.java
@@ -57,8 +57,9 @@ public static void setUp() throws Exception {
     private static LakeTable createTable(ConnectContext connectContext, String sql) throws Exception {
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         GlobalStateMgr.getCurrentState().getLocalMetastore().createTable(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb(createTableStmt.getDbName());
-        LakeTable table = (LakeTable) db.getTable(createTableStmt.getTableName());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(createTableStmt.getDbName());
+        LakeTable table = (LakeTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), createTableStmt.getTableName());
         table.addRelatedMaterializedView(new MvId(db.getId(), GlobalStateMgr.getCurrentState().getNextId()));
         return table;
     }
@@ -95,7 +96,7 @@ private AlterJobV2 mustAlterTable(Table table, String sql) throws Exception {
     @Test
     public void test() throws Exception {
         LakeTable table = createTable(connectContext, "CREATE TABLE t0(c0 INT) DUPLICATE KEY(c0) DISTRIBUTED BY HASH(c0) " +
-                "BUCKETS 2 PROPERTIES('fast_schema_evolution'='true')");
+                    "BUCKETS 2 PROPERTIES('fast_schema_evolution'='true')");
         long oldSchemaId = table.getIndexIdToMeta().get(table.getBaseIndexId()).getSchemaId();
 
         {
@@ -136,7 +137,7 @@ public void test() throws Exception {
     @Test
     public void testGetInfo() throws Exception {
         LakeTable table = createTable(connectContext, "CREATE TABLE t1(c0 INT) DUPLICATE KEY(c0) DISTRIBUTED BY HASH(c0) " +
-                "BUCKETS 2 PROPERTIES('fast_schema_evolution'='true')");
+                    "BUCKETS 2 PROPERTIES('fast_schema_evolution'='true')");
         AlterJobV2 job = mustAlterTable(table, "ALTER TABLE t1 ADD COLUMN c1 BIGINT");
         List<List<Comparable>> infoList = new ArrayList<>();
         job.getInfo(infoList);
@@ -151,7 +152,7 @@ public void testGetInfo() throws Exception {
         Assert.assertEquals(table.getBaseIndexId(), info.get(5));
         Assert.assertEquals(table.getBaseIndexId(), info.get(6));
         Assert.assertEquals(String.format("%d:0", table.getIndexIdToMeta().get(table.getBaseIndexId()).getSchemaVersion()),
-                info.get(7));
+                    info.get(7));
         Assert.assertEquals(job.getTransactionId().get(), info.get(8));
         Assert.assertEquals(job.getJobState().name(), info.get(9));
         Assert.assertEquals(job.errMsg, info.get(10));
@@ -161,14 +162,14 @@ public void testGetInfo() throws Exception {
 
     @Test
     public void testReplay() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb(DB_NAME);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(DB_NAME);
         LakeTable table = createTable(connectContext, "CREATE TABLE t3(c0 INT) DUPLICATE KEY(c0) DISTRIBUTED BY HASH(c0) " +
-                "BUCKETS 2 PROPERTIES('fast_schema_evolution'='true')");
+                    "BUCKETS 2 PROPERTIES('fast_schema_evolution'='true')");
         SchemaChangeHandler handler = GlobalStateMgr.getCurrentState().getAlterJobMgr().getSchemaChangeHandler();
         AlterTableStmt stmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser("ALTER TABLE t3 ADD COLUMN c1 INT",
-                connectContext);
+                    connectContext);
         LakeTableAsyncFastSchemaChangeJob job = (LakeTableAsyncFastSchemaChangeJob)
-                handler.analyzeAndCreateJob(stmt.getAlterClauseList(), db, table);
+                    handler.analyzeAndCreateJob(stmt.getAlterClauseList(), db, table);
         Assert.assertNotNull(job);
         Assert.assertEquals(AlterJobV2.JobState.PENDING, job.getJobState());
         Assert.assertEquals(OlapTable.OlapTableState.NORMAL, table.getState());
@@ -209,7 +210,7 @@ public void testReplay() throws Exception {
     @Test
     public void testSortKey() throws Exception {
         LakeTable table = createTable(connectContext, "CREATE TABLE t_test_sort_key(c0 INT, c1 BIGINT) PRIMARY KEY(c0) " +
-                "DISTRIBUTED BY HASH(c0) BUCKETS 2 ORDER BY(c1)");
+                    "DISTRIBUTED BY HASH(c0) BUCKETS 2 ORDER BY(c1)");
         long oldSchemaId = table.getIndexIdToMeta().get(table.getBaseIndexId()).getSchemaId();
 
         {
@@ -242,7 +243,7 @@ public void testSortKey() throws Exception {
     @Test
     public void testSortKeyIndexesChanged() throws Exception {
         LakeTable table = createTable(connectContext, "CREATE TABLE t_test_sort_key_index_changed" +
-                "(c0 INT, c1 BIGINT, c2 BIGINT) PRIMARY KEY(c0) DISTRIBUTED BY HASH(c0) BUCKETS 2 ORDER BY(c2)");
+                    "(c0 INT, c1 BIGINT, c2 BIGINT) PRIMARY KEY(c0) DISTRIBUTED BY HASH(c0) BUCKETS 2 ORDER BY(c2)");
         long oldSchemaId = table.getIndexIdToMeta().get(table.getBaseIndexId()).getSchemaId();
 
         {
@@ -263,13 +264,13 @@ public void testSortKeyIndexesChanged() throws Exception {
     @Test
     public void testModifyColumnType() throws Exception {
         LakeTable table = createTable(connectContext, "CREATE TABLE t_modify_type" +
-                "(c0 INT, c1 INT, c2 VARCHAR(5), c3 DATE)" +
-                "DUPLICATE KEY(c0) DISTRIBUTED BY HASH(c0) " +
-                "BUCKETS 1 PROPERTIES('fast_schema_evolution'='true')");
+                    "(c0 INT, c1 INT, c2 VARCHAR(5), c3 DATE)" +
+                    "DUPLICATE KEY(c0) DISTRIBUTED BY HASH(c0) " +
+                    "BUCKETS 1 PROPERTIES('fast_schema_evolution'='true')");
         long oldSchemaId = table.getIndexIdToMeta().get(table.getBaseIndexId()).getSchemaId();
         {
             mustAlterTable(table, "ALTER TABLE t_modify_type MODIFY COLUMN c1 BIGINT, MODIFY COLUMN c2 VARCHAR(10)," +
-                    "MODIFY COLUMN c3 DATETIME");
+                        "MODIFY COLUMN c3 DATETIME");
             List<Column> columns = table.getBaseSchema();
             Assert.assertEquals(4, columns.size());
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableSchemaChangeJobTest.java b/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableSchemaChangeJobTest.java
index fcb22ae831cdff..f3455325b82859 100644
--- a/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableSchemaChangeJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/alter/LakeTableSchemaChangeJobTest.java
@@ -76,8 +76,9 @@ public static void setUp() throws Exception {
     private static LakeTable createTable(ConnectContext connectContext, String sql) throws Exception {
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         GlobalStateMgr.getCurrentState().getLocalMetastore().createTable(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb(createTableStmt.getDbName());
-        return (LakeTable) db.getTable(createTableStmt.getTableName());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(createTableStmt.getDbName());
+        return (LakeTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), createTableStmt.getTableName());
     }
 
     private static void alterTable(ConnectContext connectContext, String sql) throws Exception {
@@ -101,9 +102,9 @@ public void before() throws Exception {
         CreateDbStmt createDbStmt = (CreateDbStmt) UtFrameUtils.parseStmtWithNewParser(createDbStmtStr, connectContext);
         GlobalStateMgr.getCurrentState().getMetadata().createDb(createDbStmt.getFullDbName());
         connectContext.setDatabase(DB_NAME);
-        db = GlobalStateMgr.getServingState().getDb(DB_NAME);
+        db = GlobalStateMgr.getServingState().getLocalMetastore().getDb(DB_NAME);
         table = createTable(connectContext, "CREATE TABLE t0(c0 INT) duplicate key(c0) distributed by hash(c0) buckets "
-                + NUM_BUCKETS);
+                    + NUM_BUCKETS);
         Config.enable_fast_schema_evolution_in_share_data_mode = false;
         alterTable(connectContext, "ALTER TABLE t0 ADD COLUMN c1 DOUBLE");
         schemaChangeJob = getAlterJob(table);
@@ -152,7 +153,7 @@ public void writeEditLog(LakeTableSchemaChangeJob job) {
             @Mock
             public Warehouse getWarehouse(long warehouseId) {
                 return new DefaultWarehouse(WarehouseManager.DEFAULT_WAREHOUSE_ID,
-                        WarehouseManager.DEFAULT_WAREHOUSE_NAME);
+                            WarehouseManager.DEFAULT_WAREHOUSE_NAME);
             }
 
             @Mock
@@ -413,7 +414,7 @@ public void sendAgentTask(AgentBatchTask batchTask) {
         Assert.assertNotNull(partition);
         Assert.assertEquals(3, partition.getNextVersion());
         List<MaterializedIndex> shadowIndexes =
-                partition.getMaterializedIndices(MaterializedIndex.IndexExtState.SHADOW);
+                    partition.getMaterializedIndices(MaterializedIndex.IndexExtState.SHADOW);
         Assert.assertEquals(1, shadowIndexes.size());
 
         // Does not support cancel job in FINISHED_REWRITING state.
@@ -435,8 +436,8 @@ public void testPublishVersion() throws AlterCancelException {
             @Mock
             public void publishVersion(@NotNull List<Tablet> tablets, TxnInfoPB txnInfo, long baseVersion,
                                        long newVersion, long warehouseId)
-                    throws
-                    RpcException {
+                        throws
+                        RpcException {
                 throw new RpcException("publish version failed", "127.0.0.1");
             }
         };
@@ -468,7 +469,7 @@ public void sendAgentTask(AgentBatchTask batchTask) {
         Assert.assertEquals(AlterJobV2.JobState.FINISHED_REWRITING, schemaChangeJob.getJobState());
 
         List<MaterializedIndex> shadowIndexes =
-                partition.getMaterializedIndices(MaterializedIndex.IndexExtState.SHADOW);
+                    partition.getMaterializedIndices(MaterializedIndex.IndexExtState.SHADOW);
         Assert.assertEquals(1, shadowIndexes.size());
 
         // The partition's visible version has not catch up with the commit version of this schema change job now.
@@ -520,7 +521,7 @@ public void publishVersion(@NotNull List<Tablet> tablets, TxnInfoPB txnInfo, lon
         Assert.assertEquals(0, shadowIndexes.size());
 
         List<MaterializedIndex> normalIndexes =
-                partition.getMaterializedIndices(MaterializedIndex.IndexExtState.VISIBLE);
+                    partition.getMaterializedIndices(MaterializedIndex.IndexExtState.VISIBLE);
         Assert.assertEquals(1, normalIndexes.size());
         MaterializedIndex normalIndex = normalIndexes.get(0);
 
@@ -557,7 +558,7 @@ public boolean isPreviousLoadFinished(long dbId, long tableId, long txnId) throw
             schemaChangeJob.runPendingJob();
         });
         Assert.assertTrue(exception.getMessage().contains(
-                "concurrent transaction detected while adding shadow index, please re-run the alter table command"));
+                    "concurrent transaction detected while adding shadow index, please re-run the alter table command"));
         Assert.assertEquals(AlterJobV2.JobState.PENDING, schemaChangeJob.getJobState());
         Assert.assertEquals(10101L, schemaChangeJob.getWatershedTxnId());
 
@@ -571,14 +572,14 @@ public void testShow() {
             @Mock
             public Warehouse getWarehouseAllowNull(long warehouseId) {
                 return new DefaultWarehouse(WarehouseManager.DEFAULT_WAREHOUSE_ID,
-                        WarehouseManager.DEFAULT_WAREHOUSE_NAME);
+                            WarehouseManager.DEFAULT_WAREHOUSE_NAME);
             }
         };
 
         SchemaChangeHandler schemaChangeHandler = new SchemaChangeHandler();
 
         LakeTableSchemaChangeJob alterJobV2 =
-                new LakeTableSchemaChangeJob(12345L, db.getId(), table.getId(), table.getName(), 10);
+                    new LakeTableSchemaChangeJob(12345L, db.getId(), table.getId(), table.getName(), 10);
         alterJobV2.addIndexSchema(1L, 2L, "a", (short) 1, Lists.newArrayList());
 
         schemaChangeHandler.addAlterJobV2(alterJobV2);
@@ -603,7 +604,7 @@ public void testCancelPendingJobWithFlag() throws Exception {
         schemaChangeJob.setIsCancelling(true);
         schemaChangeJob.runPendingJob();
         schemaChangeJob.setIsCancelling(false);
-     
+
         schemaChangeJob.setWaitingCreatingReplica(true);
         schemaChangeJob.cancel("");
         schemaChangeJob.setWaitingCreatingReplica(false);
diff --git a/fe/fe-core/src/test/java/com/starrocks/alter/OnlineOptimizeJobV2Test.java b/fe/fe-core/src/test/java/com/starrocks/alter/OnlineOptimizeJobV2Test.java
index 4f2d36dc567308..6a3975c4be2d78 100644
--- a/fe/fe-core/src/test/java/com/starrocks/alter/OnlineOptimizeJobV2Test.java
+++ b/fe/fe-core/src/test/java/com/starrocks/alter/OnlineOptimizeJobV2Test.java
@@ -75,8 +75,9 @@ public void clear() {
     @Test
     public void testOptimizeTable() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable7);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable7);
 
         schemaChangeHandler.process(alterTableStmt.getAlterClauseList(), db, olapTable);
         Map<Long, AlterJobV2> alterJobsV2 = schemaChangeHandler.getAlterJobsV2();
@@ -88,8 +89,9 @@ public void testOptimizeTable() throws Exception {
     @Test
     public void testOptimizeTableFinish() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable7);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable7);
         Partition testPartition = olapTable.getPartition(GlobalStateMgrTestUtil.testTable7);
 
         schemaChangeHandler.process(alterTableStmt.getAlterClauseList(), db, olapTable);
@@ -119,8 +121,9 @@ public void testOptimizeTableFinish() throws Exception {
     @Test
     public void testOptimizeTableFailed() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable7);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable7);
 
         schemaChangeHandler.process(alterTableStmt.getAlterClauseList(), db, olapTable);
         Map<Long, AlterJobV2> alterJobsV2 = schemaChangeHandler.getAlterJobsV2();
@@ -157,15 +160,16 @@ public void testOptimizeTableFailed() throws Exception {
         Assert.assertEquals(JobState.CANCELLED, optimizeJob.getJobState());
 
         OnlineOptimizeJobV2 replayOptimizeJob = new OnlineOptimizeJobV2(
-                optimizeJob.getJobId(), db.getId(), olapTable.getId(), olapTable.getName(), 1000);
+                    optimizeJob.getJobId(), db.getId(), olapTable.getId(), olapTable.getName(), 1000);
         replayOptimizeJob.replay(optimizeJob);
     }
 
     @Test
     public void testSchemaChangeWhileTabletNotStable() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable7);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable7);
         Partition testPartition = olapTable.getPartition(GlobalStateMgrTestUtil.testTable7);
 
         schemaChangeHandler.process(alterTableStmt.getAlterClauseList(), db, olapTable);
@@ -214,8 +218,9 @@ public void testSerializeOfOptimizeJob() throws IOException {
     @Test
     public void testOptimizeReplay() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable7);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable7);
 
         schemaChangeHandler.process(alterTableStmt.getAlterClauseList(), db, olapTable);
         Map<Long, AlterJobV2> alterJobsV2 = schemaChangeHandler.getAlterJobsV2();
@@ -223,7 +228,7 @@ public void testOptimizeReplay() throws Exception {
         OnlineOptimizeJobV2 optimizeJob = (OnlineOptimizeJobV2) alterJobsV2.values().stream().findAny().get();
 
         OnlineOptimizeJobV2 replayOptimizeJob = new OnlineOptimizeJobV2(
-                optimizeJob.getJobId(), db.getId(), olapTable.getId(), olapTable.getName(), 1000);
+                    optimizeJob.getJobId(), db.getId(), olapTable.getId(), olapTable.getName(), 1000);
 
         replayOptimizeJob.replay(optimizeJob);
         Assert.assertEquals(JobState.PENDING, replayOptimizeJob.getJobState());
@@ -260,8 +265,9 @@ public void testOptimizeReplay() throws Exception {
     @Test
     public void testOptimizeReplayPartialSuccess() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable("testTable2");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "testTable2");
 
         String stmt = "alter table testTable2 distributed by hash(v1)";
         AlterTableStmt alterStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(stmt, starRocksAssert.getCtx());
@@ -270,9 +276,8 @@ public void testOptimizeReplayPartialSuccess() throws Exception {
         Assert.assertEquals(1, alterJobsV2.size());
         OnlineOptimizeJobV2 optimizeJob = (OnlineOptimizeJobV2) alterJobsV2.values().stream().findAny().get();
 
-
         OnlineOptimizeJobV2 replayOptimizeJob = new OnlineOptimizeJobV2(
-                optimizeJob.getJobId(), db.getId(), olapTable.getId(), olapTable.getName(), 1000);
+                    optimizeJob.getJobId(), db.getId(), olapTable.getId(), olapTable.getName(), 1000);
 
         replayOptimizeJob.replay(optimizeJob);
         Assert.assertEquals(JobState.PENDING, replayOptimizeJob.getJobState());
diff --git a/fe/fe-core/src/test/java/com/starrocks/alter/OptimizeJobV2BuilderTest.java b/fe/fe-core/src/test/java/com/starrocks/alter/OptimizeJobV2BuilderTest.java
index 6f4f6da27c8747..aac01042d9cd51 100644
--- a/fe/fe-core/src/test/java/com/starrocks/alter/OptimizeJobV2BuilderTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/alter/OptimizeJobV2BuilderTest.java
@@ -65,6 +65,8 @@ public void testBuildWithoutOptimizeClause() throws UserException {
         OlapTable table = Mockito.mock(OlapTable.class);
         Mockito.when(table.getId()).thenReturn(123L);
         Mockito.when(table.getName()).thenReturn("myTable");
+        Mockito.when(table.getStorageType()).thenReturn(null);
+        Mockito.when(table.enableReplicatedStorage()).thenReturn(true);
 
         // Create an instance of OptimizeJobV2Builder without an optimize clause
         OptimizeJobV2Builder builder = new OptimizeJobV2Builder(table);
diff --git a/fe/fe-core/src/test/java/com/starrocks/alter/OptimizeJobV2Test.java b/fe/fe-core/src/test/java/com/starrocks/alter/OptimizeJobV2Test.java
index 5ffb4a1d87c14a..15d8d060c7482f 100644
--- a/fe/fe-core/src/test/java/com/starrocks/alter/OptimizeJobV2Test.java
+++ b/fe/fe-core/src/test/java/com/starrocks/alter/OptimizeJobV2Test.java
@@ -147,8 +147,9 @@ public void testOptimizeParser() throws Exception {
     @Test
     public void testOptimizeTable() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable7);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable7);
 
         schemaChangeHandler.process(alterTableStmt.getAlterClauseList(), db, olapTable);
         Map<Long, AlterJobV2> alterJobsV2 = schemaChangeHandler.getAlterJobsV2();
@@ -160,8 +161,9 @@ public void testOptimizeTable() throws Exception {
     @Test
     public void testOptimizeTableFinish() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable7);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable7);
         Partition testPartition = olapTable.getPartition(GlobalStateMgrTestUtil.testTable7);
 
         schemaChangeHandler.process(alterTableStmt.getAlterClauseList(), db, olapTable);
@@ -201,8 +203,9 @@ public void testOptimizeTableFinish() throws Exception {
     @Test
     public void testOptimizeTableFailed() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable7);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable7);
 
         schemaChangeHandler.process(alterTableStmt.getAlterClauseList(), db, olapTable);
         Map<Long, AlterJobV2> alterJobsV2 = schemaChangeHandler.getAlterJobsV2();
@@ -239,15 +242,16 @@ public void testOptimizeTableFailed() throws Exception {
         Assert.assertEquals(JobState.CANCELLED, optimizeJob.getJobState());
 
         OptimizeJobV2 replayOptimizeJob = new OptimizeJobV2(
-                optimizeJob.getJobId(), db.getId(), olapTable.getId(), olapTable.getName(), 1000);
+                    optimizeJob.getJobId(), db.getId(), olapTable.getId(), olapTable.getName(), 1000);
         replayOptimizeJob.replay(optimizeJob);
     }
 
     @Test
     public void testSchemaChangeWhileTabletNotStable() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable7);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable7);
         Partition testPartition = olapTable.getPartition(GlobalStateMgrTestUtil.testTable7);
 
         schemaChangeHandler.process(alterTableStmt.getAlterClauseList(), db, olapTable);
@@ -296,8 +300,9 @@ public void testSerializeOfOptimizeJob() throws IOException {
     @Test
     public void testOptimizeReplay() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable7);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable7);
 
         schemaChangeHandler.process(alterTableStmt.getAlterClauseList(), db, olapTable);
         Map<Long, AlterJobV2> alterJobsV2 = schemaChangeHandler.getAlterJobsV2();
@@ -305,7 +310,7 @@ public void testOptimizeReplay() throws Exception {
         OptimizeJobV2 optimizeJob = (OptimizeJobV2) alterJobsV2.values().stream().findAny().get();
 
         OptimizeJobV2 replayOptimizeJob = new OptimizeJobV2(
-                optimizeJob.getJobId(), db.getId(), olapTable.getId(), olapTable.getName(), 1000);
+                    optimizeJob.getJobId(), db.getId(), olapTable.getId(), olapTable.getName(), 1000);
 
         replayOptimizeJob.replay(optimizeJob);
         Assert.assertEquals(JobState.PENDING, replayOptimizeJob.getJobState());
@@ -342,8 +347,9 @@ public void testOptimizeReplay() throws Exception {
     @Test
     public void testOptimizeReplayPartialSuccess() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable("testTable2");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "testTable2");
 
         String stmt = "alter table testTable2 distributed by hash(v1)";
         AlterTableStmt alterStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(stmt, starRocksAssert.getCtx());
@@ -352,9 +358,8 @@ public void testOptimizeReplayPartialSuccess() throws Exception {
         Assert.assertEquals(1, alterJobsV2.size());
         OptimizeJobV2 optimizeJob = (OptimizeJobV2) alterJobsV2.values().stream().findAny().get();
 
-
         OptimizeJobV2 replayOptimizeJob = new OptimizeJobV2(
-                optimizeJob.getJobId(), db.getId(), olapTable.getId(), olapTable.getName(), 1000);
+                    optimizeJob.getJobId(), db.getId(), olapTable.getId(), olapTable.getName(), 1000);
 
         replayOptimizeJob.replay(optimizeJob);
         Assert.assertEquals(JobState.PENDING, replayOptimizeJob.getJobState());
@@ -387,8 +392,9 @@ public void testOptimizeReplayPartialSuccess() throws Exception {
     @Test
     public void testOptimizeFailedByVersion() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable("testTable2");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "testTable2");
 
         String stmt = "alter table testTable2 distributed by hash(v1)";
         AlterTableStmt alterStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(stmt, starRocksAssert.getCtx());
diff --git a/fe/fe-core/src/test/java/com/starrocks/alter/RollupJobV2Test.java b/fe/fe-core/src/test/java/com/starrocks/alter/RollupJobV2Test.java
index 021852f5512b18..fc8e951b894bea 100644
--- a/fe/fe-core/src/test/java/com/starrocks/alter/RollupJobV2Test.java
+++ b/fe/fe-core/src/test/java/com/starrocks/alter/RollupJobV2Test.java
@@ -92,12 +92,12 @@ public class RollupJobV2Test extends DDLTestBase {
     public void setUp() throws Exception {
         super.setUp();
         clause = new AddRollupClause(GlobalStateMgrTestUtil.testRollupIndex2, Lists.newArrayList("v1"), null,
-                GlobalStateMgrTestUtil.testTable1, null);
+                    GlobalStateMgrTestUtil.testTable1, null);
         AlterTableClauseAnalyzer analyzer = new AlterTableClauseAnalyzer(null);
         analyzer.analyze(null, clause);
 
         clause2 = new AddRollupClause(GlobalStateMgrTestUtil.testRollupIndex3, Lists.newArrayList("v1", "v2"), null,
-                GlobalStateMgrTestUtil.testTable1, null);
+                    GlobalStateMgrTestUtil.testTable1, null);
         analyzer.analyze(null, clause2);
 
         AgentTaskQueue.clearAllTasks();
@@ -114,15 +114,16 @@ public void testRunRollupJobConcurrentLimit() throws UserException {
         ArrayList<AlterClause> alterClauses = new ArrayList<>();
         alterClauses.add(clause);
         alterClauses.add(clause2);
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable1);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable1);
         materializedViewHandler.process(alterClauses, db, olapTable);
         Map<Long, AlterJobV2> alterJobsV2 = materializedViewHandler.getAlterJobsV2();
 
         materializedViewHandler.runAfterCatalogReady();
 
         assertEquals(Config.max_running_rollup_job_num_per_table,
-                materializedViewHandler.getTableRunningJobMap().get(olapTable.getId()).size());
+                    materializedViewHandler.getTableRunningJobMap().get(olapTable.getId()).size());
         assertEquals(2, alterJobsV2.size());
         assertEquals(OlapTableState.ROLLUP, olapTable.getState());
     }
@@ -132,8 +133,9 @@ public void testAddSchemaChange() throws UserException {
         MaterializedViewHandler materializedViewHandler = GlobalStateMgr.getCurrentState().getRollupHandler();
         ArrayList<AlterClause> alterClauses = new ArrayList<>();
         alterClauses.add(clause);
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable1);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable1);
         materializedViewHandler.process(alterClauses, db, olapTable);
         Map<Long, AlterJobV2> alterJobsV2 = materializedViewHandler.getAlterJobsV2();
         assertEquals(1, alterJobsV2.size());
@@ -148,8 +150,9 @@ public void testSchemaChange1() throws Exception {
         // add a rollup job
         ArrayList<AlterClause> alterClauses = new ArrayList<>();
         alterClauses.add(clause);
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable1);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable1);
         Partition testPartition = olapTable.getPartition(GlobalStateMgrTestUtil.testTable1);
         materializedViewHandler.process(alterClauses, db, olapTable);
         Map<Long, AlterJobV2> alterJobsV2 = materializedViewHandler.getAlterJobsV2();
@@ -191,8 +194,9 @@ public void testSchemaChangeWhileTabletNotStable() throws Exception {
         ArrayList<AlterClause> alterClauses = new ArrayList<>();
         alterClauses.add(clause);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable1);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable1);
         Partition testPartition = olapTable.getPartition(GlobalStateMgrTestUtil.testTable1);
 
         materializedViewHandler.process(alterClauses, db, olapTable);
@@ -245,7 +249,7 @@ public void testSchemaChangeWhileTabletNotStable() throws Exception {
 
     @Test
     public void testSerializeOfRollupJob() throws IOException,
-            AnalysisException {
+                AnalysisException {
         Config.enable_materialized_view = true;
         // prepare file
         String fileName = "./RollupJobV2Test";
@@ -257,13 +261,13 @@ public void testSerializeOfRollupJob() throws IOException,
         List<Column> columns = Lists.newArrayList();
         String mvColumnName = MVUtils.MATERIALIZED_VIEW_NAME_PREFIX + "bitmap_union_" + "c1";
         Column column = new Column(mvColumnName, Type.BITMAP, false, AggregateType.BITMAP_UNION, false,
-                new ColumnDef.DefaultValueDef(true, new StringLiteral("1")), "");
+                    new ColumnDef.DefaultValueDef(true, new StringLiteral("1")), "");
         columns.add(column);
         RollupJobV2 rollupJobV2 = new RollupJobV2(1, 1, 1, "test", 1, 1,
-                1, "test", "rollup", 0, columns, null, 1, 1,
-                KeysType.AGG_KEYS, keysCount,
-                new OriginStatement("create materialized view rollup as select bitmap_union(to_bitmap(c1)) from test",
-                        0), "", false);
+                    1, "test", "rollup", 0, columns, null, 1, 1,
+                    KeysType.AGG_KEYS, keysCount,
+                    new OriginStatement("create materialized view rollup as select bitmap_union(to_bitmap(c1)) from test",
+                                0), "", false);
 
         // write rollup job
         rollupJobV2.write(out);
@@ -278,7 +282,7 @@ public void testSerializeOfRollupJob() throws IOException,
         assertEquals(1, resultColumns.size());
         Column resultColumn1 = resultColumns.get(0);
         assertEquals(mvColumnName,
-                resultColumn1.getName());
+                    resultColumn1.getName());
         Assert.assertTrue(resultColumn1.getDefineExpr() instanceof FunctionCallExpr);
         FunctionCallExpr resultFunctionCall = (FunctionCallExpr) resultColumn1.getDefineExpr();
         assertEquals("to_bitmap", resultFunctionCall.getFnName().getFunction());
@@ -289,8 +293,9 @@ public void testReplayPendingRollupJob() throws Exception {
         MaterializedViewHandler materializedViewHandler = GlobalStateMgr.getCurrentState().getRollupHandler();
         ArrayList<AlterClause> alterClauses = new ArrayList<>();
         alterClauses.add(clause);
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable1);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable1);
         materializedViewHandler.process(alterClauses, db, olapTable);
         Map<Long, AlterJobV2> alterJobsV2 = materializedViewHandler.getAlterJobsV2();
         assertEquals(1, alterJobsV2.size());
@@ -306,8 +311,9 @@ public void testCancelPendingJobWithFlag() throws Exception {
         // add a rollup job
         ArrayList<AlterClause> alterClauses = new ArrayList<>();
         alterClauses.add(clause);
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable1);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable1);
         Partition testPartition = olapTable.getPartition(GlobalStateMgrTestUtil.testTable1);
         materializedViewHandler.process(alterClauses, db, olapTable);
         Map<Long, AlterJobV2> alterJobsV2 = materializedViewHandler.getAlterJobsV2();
@@ -318,7 +324,7 @@ public void testCancelPendingJobWithFlag() throws Exception {
         rollupJob.setIsCancelling(true);
         rollupJob.runPendingJob();
         rollupJob.setIsCancelling(false);
-     
+
         rollupJob.setWaitingCreatingReplica(true);
         rollupJob.cancel("");
         rollupJob.setWaitingCreatingReplica(false);
diff --git a/fe/fe-core/src/test/java/com/starrocks/alter/SchemaChangeHandlerTest.java b/fe/fe-core/src/test/java/com/starrocks/alter/SchemaChangeHandlerTest.java
index 3f9907d28a314c..d849abd9c1f6cb 100644
--- a/fe/fe-core/src/test/java/com/starrocks/alter/SchemaChangeHandlerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/alter/SchemaChangeHandlerTest.java
@@ -81,38 +81,38 @@ protected void runBeforeAll() throws Exception {
 
         //create tables
         String createAggTblStmtStr = "CREATE TABLE IF NOT EXISTS test.sc_agg (\n" + "user_id LARGEINT NOT NULL,\n"
-                + "date DATE NOT NULL,\n" + "city VARCHAR(20),\n" + "age SMALLINT,\n" + "sex TINYINT,\n"
-                + "last_visit_date DATETIME REPLACE DEFAULT '1970-01-01 00:00:00',\n" + "cost BIGINT SUM DEFAULT '0',\n"
-                + "max_dwell_time INT MAX DEFAULT '0',\n" + "min_dwell_time INT MIN DEFAULT '99999')\n"
-                + "AGGREGATE KEY(user_id, date, city, age, sex)\n" + "DISTRIBUTED BY HASH(user_id) BUCKETS 1\n"
-                + "PROPERTIES ('replication_num' = '1', 'fast_schema_evolution' = 'true');";
+                    + "date DATE NOT NULL,\n" + "city VARCHAR(20),\n" + "age SMALLINT,\n" + "sex TINYINT,\n"
+                    + "last_visit_date DATETIME REPLACE DEFAULT '1970-01-01 00:00:00',\n" + "cost BIGINT SUM DEFAULT '0',\n"
+                    + "max_dwell_time INT MAX DEFAULT '0',\n" + "min_dwell_time INT MIN DEFAULT '99999')\n"
+                    + "AGGREGATE KEY(user_id, date, city, age, sex)\n" + "DISTRIBUTED BY HASH(user_id) BUCKETS 1\n"
+                    + "PROPERTIES ('replication_num' = '1', 'fast_schema_evolution' = 'true');";
         createTable(createAggTblStmtStr);
 
         String createUniqTblStmtStr = "CREATE TABLE IF NOT EXISTS test.sc_uniq (\n" + "user_id LARGEINT NOT NULL,\n"
-                + "username VARCHAR(50) NOT NULL,\n" + "city VARCHAR(20),\n" + "age SMALLINT,\n" + "sex TINYINT,\n"
-                + "phone LARGEINT,\n" + "address VARCHAR(500),\n" + "register_time DATETIME)\n"
-                + "UNIQUE  KEY(user_id, username)\n" + "DISTRIBUTED BY HASH(user_id) BUCKETS 1\n"
-                + "PROPERTIES ('replication_num' = '1', 'fast_schema_evolution' = 'true');";
+                    + "username VARCHAR(50) NOT NULL,\n" + "city VARCHAR(20),\n" + "age SMALLINT,\n" + "sex TINYINT,\n"
+                    + "phone LARGEINT,\n" + "address VARCHAR(500),\n" + "register_time DATETIME)\n"
+                    + "UNIQUE  KEY(user_id, username)\n" + "DISTRIBUTED BY HASH(user_id) BUCKETS 1\n"
+                    + "PROPERTIES ('replication_num' = '1', 'fast_schema_evolution' = 'true');";
         createTable(createUniqTblStmtStr);
 
         String createDupTblStmtStr = "CREATE TABLE IF NOT EXISTS test.sc_dup (\n" + "timestamp DATETIME,\n"
-                + "type INT,\n" + "error_code INT,\n" + "error_msg VARCHAR(1024),\n" + "op_id BIGINT,\n"
-                + "op_time DATETIME)\n" + "DUPLICATE  KEY(timestamp, type)\n" + "DISTRIBUTED BY HASH(type) BUCKETS 1\n"
-                + "PROPERTIES ('replication_num' = '1', 'fast_schema_evolution' = 'true');";
+                    + "type INT,\n" + "error_code INT,\n" + "error_msg VARCHAR(1024),\n" + "op_id BIGINT,\n"
+                    + "op_time DATETIME)\n" + "DUPLICATE  KEY(timestamp, type)\n" + "DISTRIBUTED BY HASH(type) BUCKETS 1\n"
+                    + "PROPERTIES ('replication_num' = '1', 'fast_schema_evolution' = 'true');";
 
         createTable(createDupTblStmtStr);
 
         String createDupTbl2StmtStr = "CREATE TABLE IF NOT EXISTS test.sc_dup2 (\n" + "timestamp DATETIME,\n"
-                + "type INT,\n" + "error_code INT,\n" + "error_msg VARCHAR(1024),\n" + "op_id BIGINT,\n"
-                + "op_time DATETIME)\n" + "DUPLICATE  KEY(timestamp, type)\n" + "DISTRIBUTED BY HASH(type) BUCKETS 1\n"
-                + "PROPERTIES ('replication_num' = '1', 'fast_schema_evolution' = 'true');";
+                    + "type INT,\n" + "error_code INT,\n" + "error_msg VARCHAR(1024),\n" + "op_id BIGINT,\n"
+                    + "op_time DATETIME)\n" + "DUPLICATE  KEY(timestamp, type)\n" + "DISTRIBUTED BY HASH(type) BUCKETS 1\n"
+                    + "PROPERTIES ('replication_num' = '1', 'fast_schema_evolution' = 'true');";
 
         createTable(createDupTbl2StmtStr);
 
         String createPKTblStmtStr = "CREATE TABLE IF NOT EXISTS test.sc_pk (\n" + "timestamp DATETIME,\n"
-                + "type INT,\n" + "error_code INT,\n" + "error_msg VARCHAR(1024),\n" + "op_id BIGINT,\n"
-                + "op_time DATETIME)\n" + "PRIMARY  KEY(timestamp, type)\n" + "DISTRIBUTED BY HASH(type) BUCKETS 1\n"
-                + "PROPERTIES ('replication_num' = '1', 'fast_schema_evolution' = 'true');";
+                    + "type INT,\n" + "error_code INT,\n" + "error_msg VARCHAR(1024),\n" + "op_id BIGINT,\n"
+                    + "op_time DATETIME)\n" + "PRIMARY  KEY(timestamp, type)\n" + "DISTRIBUTED BY HASH(type) BUCKETS 1\n"
+                    + "PROPERTIES ('replication_num' = '1', 'fast_schema_evolution' = 'true');";
 
         createTable(createPKTblStmtStr);
 
@@ -127,8 +127,9 @@ private void waitAlterJobDone(Map<Long, AlterJobV2> alterJobs) throws Exception
             LOG.info("alter job {} is done. state: {}", alterJobV2.getJobId(), alterJobV2.getJobState());
             Assert.assertEquals(AlterJobV2.JobState.FINISHED, alterJobV2.getJobState());
 
-            Database db = GlobalStateMgr.getCurrentState().getDb(alterJobV2.getDbId());
-            OlapTable tbl = (OlapTable) db.getTable(alterJobV2.getTableId());
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(alterJobV2.getDbId());
+            OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(db.getId(), alterJobV2.getTableId());
             while (tbl.getState() != OlapTable.OlapTableState.NORMAL) {
                 Thread.sleep(1000);
             }
@@ -139,8 +140,8 @@ private void waitAlterJobDone(Map<Long, AlterJobV2> alterJobs) throws Exception
     public void testAggAddOrDropColumn() throws Exception {
         LOG.info("dbName: {}", GlobalStateMgr.getCurrentState().getLocalMetastore().listDbNames());
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("sc_agg");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "sc_agg");
         Locker locker = new Locker();
         locker.lockTablesWithIntensiveDbLock(db, Lists.newArrayList(tbl.getId()), LockType.READ);
         try {
@@ -246,8 +247,8 @@ public void testUniqAddOrDropColumn() throws Exception {
 
         LOG.info("dbName: {}", GlobalStateMgr.getCurrentState().getLocalMetastore().listDbNames());
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("sc_uniq");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "sc_uniq");
         Locker locker = new Locker();
         locker.lockTablesWithIntensiveDbLock(db, Lists.newArrayList(tbl.getId()), LockType.READ);
         try {
@@ -304,8 +305,8 @@ public void testDupAddOrDropColumn() throws Exception {
 
         LOG.info("dbName: {}", GlobalStateMgr.getCurrentState().getLocalMetastore().listDbNames());
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("sc_dup");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "sc_dup");
         Locker locker = new Locker();
         locker.lockTablesWithIntensiveDbLock(db, Lists.newArrayList(tbl.getId()), LockType.READ);
         try {
@@ -360,8 +361,8 @@ public void testDupAddOrDropColumn() throws Exception {
     @Test
     public void testModifyTableAddOrDropColumns() {
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
-        Database db = globalStateMgr.getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("sc_dup2");
+        Database db = globalStateMgr.getLocalMetastore().getDb("test");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "sc_dup2");
         Map<Long, AlterJobV2> alterJobs = globalStateMgr.getSchemaChangeHandler().getAlterJobsV2();
 
         // origin columns
@@ -374,25 +375,25 @@ public void testModifyTableAddOrDropColumns() {
         List<Index> newIndexes = tbl.getCopiedIndexes();
 
         Assertions.assertDoesNotThrow(
-                () -> ((SchemaChangeHandler) GlobalStateMgr.getCurrentState().getAlterJobMgr().getSchemaChangeHandler())
-                        .modifyTableAddOrDrop(db, tbl, indexSchemaMap, newIndexes, 100, 100,
-                                indexToNewSchemaId, false));
+                    () -> ((SchemaChangeHandler) GlobalStateMgr.getCurrentState().getAlterJobMgr().getSchemaChangeHandler())
+                                .modifyTableAddOrDrop(db, tbl, indexSchemaMap, newIndexes, 100, 100,
+                                            indexToNewSchemaId, false));
         jobSize++;
         Assertions.assertEquals(jobSize, alterJobs.size());
 
         Assertions.assertDoesNotThrow(
-                () -> ((SchemaChangeHandler) GlobalStateMgr.getCurrentState().getAlterJobMgr().getSchemaChangeHandler())
-                        .modifyTableAddOrDrop(db, tbl, indexSchemaMap, newIndexes, 101, 101,
-                                indexToNewSchemaId, true));
+                    () -> ((SchemaChangeHandler) GlobalStateMgr.getCurrentState().getAlterJobMgr().getSchemaChangeHandler())
+                                .modifyTableAddOrDrop(db, tbl, indexSchemaMap, newIndexes, 101, 101,
+                                            indexToNewSchemaId, true));
         jobSize++;
         Assertions.assertEquals(jobSize, alterJobs.size());
 
         OlapTableState beforeState = tbl.getState();
         tbl.setState(OlapTableState.ROLLUP);
         Assertions.assertThrows(DdlException.class,
-                () -> ((SchemaChangeHandler) GlobalStateMgr.getCurrentState().getAlterJobMgr().getSchemaChangeHandler())
-                        .modifyTableAddOrDrop(db, tbl, indexSchemaMap, newIndexes, 102, 102, indexToNewSchemaId,
-                                false));
+                    () -> ((SchemaChangeHandler) GlobalStateMgr.getCurrentState().getAlterJobMgr().getSchemaChangeHandler())
+                                .modifyTableAddOrDrop(db, tbl, indexSchemaMap, newIndexes, 102, 102, indexToNewSchemaId,
+                                            false));
         tbl.setState(beforeState);
     }
 
@@ -401,8 +402,8 @@ public void testSetPrimaryIndexCacheExpireSec() throws Exception {
 
         LOG.info("dbName: {}", GlobalStateMgr.getCurrentState().getLocalMetastore().listDbNames());
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("sc_pk");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "sc_pk");
         Locker locker = new Locker();
         locker.lockTablesWithIntensiveDbLock(db, Lists.newArrayList(tbl.getId()), LockType.READ);
         try {
diff --git a/fe/fe-core/src/test/java/com/starrocks/alter/SchemaChangeJobV2Test.java b/fe/fe-core/src/test/java/com/starrocks/alter/SchemaChangeJobV2Test.java
index ab282213f61ac2..091b22899e3d7c 100644
--- a/fe/fe-core/src/test/java/com/starrocks/alter/SchemaChangeJobV2Test.java
+++ b/fe/fe-core/src/test/java/com/starrocks/alter/SchemaChangeJobV2Test.java
@@ -58,7 +58,7 @@
 import com.starrocks.common.UserException;
 import com.starrocks.common.jmockit.Deencapsulation;
 import com.starrocks.server.GlobalStateMgr;
-import com.starrocks.server.MetadataMgr;
+import com.starrocks.server.LocalMetastore;
 import com.starrocks.server.RunMode;
 import com.starrocks.server.WarehouseManager;
 import com.starrocks.sql.analyzer.DDLTestBase;
@@ -118,8 +118,9 @@ public void clear() {
     @Test
     public void testAddSchemaChange() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable1);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable1);
 
         schemaChangeHandler.process(alterTableStmt.getAlterClauseList(), db, olapTable);
         Map<Long, AlterJobV2> alterJobsV2 = schemaChangeHandler.getAlterJobsV2();
@@ -131,8 +132,9 @@ public void testAddSchemaChange() throws Exception {
     @Test
     public void testSchemaChange1() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable1);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable1);
         olapTable.setUseFastSchemaEvolution(false);
         Partition testPartition = olapTable.getPartition(GlobalStateMgrTestUtil.testTable1);
 
@@ -185,8 +187,9 @@ public void testSchemaChange1() throws Exception {
     @Test
     public void testSchemaChangeWhileTabletNotStable() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable1);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable1);
         olapTable.setUseFastSchemaEvolution(false);
         Partition testPartition = olapTable.getPartition(GlobalStateMgrTestUtil.testTable1);
 
@@ -254,14 +257,14 @@ public void testModifyDynamicPartitionNormal() throws Exception {
         OlapTable olapTable = (OlapTable) db.getTable(CatalogMocker.TEST_TBL2_ID);
         olapTable.setUseFastSchemaEvolution(false);
 
-        new MockUp<MetadataMgr>() {
+        new MockUp<LocalMetastore>() {
             @Mock
-            public Database getDb(String catalogName, String dbName) {
+            public Database getDb(String dbName) {
                 return db;
             }
 
             @Mock
-            public Table getTable(String catalogName, String dbName, String tblName) {
+            public Table getTable(String dbName, String tblName) {
                 return olapTable;
             }
         };
@@ -322,7 +325,7 @@ public void testModifyDynamicPropertyTrim() throws Exception {
     }
 
     public void modifyDynamicPartitionWithoutTableProperty(String propertyKey, String propertyValue, String expectErrMsg)
-            throws UserException {
+                throws UserException {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
         ArrayList<AlterClause> alterClauses = new ArrayList<>();
         Map<String, String> properties = new HashMap<>();
@@ -332,14 +335,14 @@ public void modifyDynamicPartitionWithoutTableProperty(String propertyKey, Strin
         Database db = CatalogMocker.mockDb();
         OlapTable olapTable = (OlapTable) db.getTable(CatalogMocker.TEST_TBL2_ID);
 
-        new MockUp<MetadataMgr>() {
+        new MockUp<LocalMetastore>() {
             @Mock
-            public Database getDb(String catalogName, String dbName) {
+            public Database getDb(String dbName) {
                 return db;
             }
 
             @Mock
-            public Table getTable(String catalogName, String dbName, String tblName) {
+            public Table getTable(String dbName, String tblName) {
                 return olapTable;
             }
         };
@@ -353,14 +356,14 @@ public Table getTable(String catalogName, String dbName, String tblName) {
     @Test
     public void testModifyDynamicPartitionWithoutTableProperty() throws AlterJobException, UserException {
         modifyDynamicPartitionWithoutTableProperty(DynamicPartitionProperty.ENABLE, "false",
-                "not a dynamic partition table");
+                    "not a dynamic partition table");
         modifyDynamicPartitionWithoutTableProperty(DynamicPartitionProperty.TIME_UNIT, "day",
-                DynamicPartitionProperty.ENABLE);
+                    DynamicPartitionProperty.ENABLE);
         modifyDynamicPartitionWithoutTableProperty(DynamicPartitionProperty.END, "3", DynamicPartitionProperty.ENABLE);
         modifyDynamicPartitionWithoutTableProperty(DynamicPartitionProperty.PREFIX, "p",
-                DynamicPartitionProperty.ENABLE);
+                    DynamicPartitionProperty.ENABLE);
         modifyDynamicPartitionWithoutTableProperty(DynamicPartitionProperty.BUCKETS, "30",
-                DynamicPartitionProperty.ENABLE);
+                    DynamicPartitionProperty.ENABLE);
     }
 
     @Test
@@ -411,7 +414,7 @@ public RunMode getCurrentRunMode() {
             @Mock
             public Warehouse getWarehouse(long warehouseId) {
                 return new DefaultWarehouse(WarehouseManager.DEFAULT_WAREHOUSE_ID,
-                        WarehouseManager.DEFAULT_WAREHOUSE_NAME);
+                            WarehouseManager.DEFAULT_WAREHOUSE_NAME);
             }
 
             @Mock
@@ -424,19 +427,19 @@ public List<Long> getAllComputeNodeIds(long warehouseId) {
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(stmt, starRocksAssert.getCtx());
         ReorderColumnsClause clause = (ReorderColumnsClause) alterTableStmt.getAlterClauseList().get(0);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable1);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable1);
 
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
         AlterJobV2 alterJobV2 = schemaChangeHandler.analyzeAndCreateJob(Lists.newArrayList(clause), db, olapTable);
         Assert.assertEquals(0L, alterJobV2.warehouseId);
 
-
         new MockUp<WarehouseManager>() {
             @Mock
             public Warehouse getWarehouse(long warehouseId) {
                 return new DefaultWarehouse(WarehouseManager.DEFAULT_WAREHOUSE_ID,
-                        WarehouseManager.DEFAULT_WAREHOUSE_NAME);
+                            WarehouseManager.DEFAULT_WAREHOUSE_NAME);
             }
 
             @Mock
@@ -456,8 +459,9 @@ public List<Long> getAllComputeNodeIds(long warehouseId) {
     @Test
     public void testCancelPendingJobWithFlag() throws Exception {
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
-        Database db = GlobalStateMgr.getCurrentState().getDb(GlobalStateMgrTestUtil.testDb1);
-        OlapTable olapTable = (OlapTable) db.getTable(GlobalStateMgrTestUtil.testTable1);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDb1);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), GlobalStateMgrTestUtil.testTable1);
         olapTable.setUseFastSchemaEvolution(false);
         Partition testPartition = olapTable.getPartition(GlobalStateMgrTestUtil.testTable1);
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/AccessTestUtil.java b/fe/fe-core/src/test/java/com/starrocks/analysis/AccessTestUtil.java
index 384c4d7978db52..0c33c0f4306814 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/AccessTestUtil.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/AccessTestUtil.java
@@ -166,25 +166,28 @@ public static GlobalStateMgr fetchBlockCatalog() {
 
         Database db = mockDb("testDb");
 
+        /*
         new Expectations(globalStateMgr) {
             {
-                globalStateMgr.getDb("testDb");
+                globalStateMgr.getLocalMetastore().getDb("testDb");
                 minTimes = 0;
                 result = db;
 
-                globalStateMgr.getDb("emptyDb");
+                globalStateMgr.getLocalMetastore().getDb("emptyDb");
                 minTimes = 0;
                 result = null;
 
-                globalStateMgr.getDb(anyString);
+                globalStateMgr.getLocalMetastore().getDb(anyString);
                 minTimes = 0;
                 result = new Database();
 
-                globalStateMgr.getDb("emptyCluster");
+                globalStateMgr.getLocalMetastore().getDb("emptyCluster");
                 minTimes = 0;
                 result = null;
             }
         };
+
+         */
         return globalStateMgr;
     }
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/AlterMaterializedViewTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/AlterMaterializedViewTest.java
index 33816cfa88a5c2..1f217dd6a8b633 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/AlterMaterializedViewTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/AlterMaterializedViewTest.java
@@ -413,7 +413,7 @@ public void testActiveGracePeriod() throws Exception {
         }
 
         // foreground active
-        starRocksAssert.refreshMV("refresh materialized view " + mvName);
+        starRocksAssert.refreshMV("refresh materialized view " + mvName + " with sync mode");
         Assert.assertTrue(mv.isActive());
 
         // clear the grace period and active it again
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/CTASAutoTabletTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/CTASAutoTabletTest.java
index 05d405e0153185..bb449d8fa2222d 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/CTASAutoTabletTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/CTASAutoTabletTest.java
@@ -49,7 +49,7 @@ public void testCTASAutoTablet() throws Exception {
         PseudoCluster cluster = PseudoCluster.getInstance();
         cluster.runSql("db_for_auto_tablets",
                 "create table test_table1 (k1 bigint, k2 bigint, v0 string) DUPLICATE KEY(k1) DISTRIBUTED BY HASH(k1);");
-        Database db = GlobalStateMgr.getCurrentState().getDb("db_for_auto_tablets");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db_for_auto_tablets");
         if (db == null) {
             return;
         }
@@ -63,7 +63,7 @@ public void testCTASAutoTablet() throws Exception {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            OlapTable table = (OlapTable) db.getTable("test_table1");
+            OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_table1");
             if (table == null) {
                 return;
             }
@@ -72,7 +72,7 @@ public void testCTASAutoTablet() throws Exception {
             }
 
             // ctas1
-            table = (OlapTable) db.getTable("ctas1");
+            table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "ctas1");
             if (table == null) {
                 return;
             }
@@ -81,7 +81,7 @@ public void testCTASAutoTablet() throws Exception {
             }
 
             // ctas2
-            table = (OlapTable) db.getTable("ctas2");
+            table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "ctas2");
             if (table == null) {
                 return;
             }
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/ColumnDefTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/ColumnDefTest.java
index e4b0cc762f19da..ae0bbeb6c96a40 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/ColumnDefTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/ColumnDefTest.java
@@ -34,6 +34,10 @@
 
 package com.starrocks.analysis;
 
+import com.google.common.collect.Lists;
+import com.starrocks.catalog.AggregateFunction;
+import com.starrocks.catalog.FunctionSet;
+import com.starrocks.catalog.combinator.AggStateDesc;
 import com.starrocks.sql.analyzer.SemanticException;
 import com.starrocks.sql.ast.ColumnDef;
 import com.starrocks.sql.ast.ColumnDef.DefaultValueDef;
@@ -78,14 +82,14 @@ public void testNormal() throws AnalysisException {
 
         // default
         column =
-                new ColumnDef("col", intCol, true, null, false, new DefaultValueDef(true, new StringLiteral("10")), "");
+                new ColumnDef("col", intCol, true, null, null, false, new DefaultValueDef(true, new StringLiteral("10")), "");
         column.analyze(true);
         Assert.assertNull(column.getAggregateType());
         Assert.assertEquals("10", column.getDefaultValue());
         Assert.assertEquals("`col` int(11) NOT NULL DEFAULT \"10\" COMMENT \"\"", column.toSql());
 
         // agg
-        column = new ColumnDef("col", floatCol, false, AggregateType.SUM, false,
+        column = new ColumnDef("col", floatCol, false, AggregateType.SUM, null, false,
                 new DefaultValueDef(true, new StringLiteral("10")), "");
         column.analyze(true);
         Assert.assertEquals("10", column.getDefaultValue());
@@ -99,7 +103,7 @@ public void testReplaceIfNotNull() throws AnalysisException {
             // not allow null
             // although here is default value is NOT_SET but after analyze it will be set to NULL and allowed NULL trick.
             ColumnDef column =
-                    new ColumnDef("col", intCol, false, AggregateType.REPLACE_IF_NOT_NULL, false,
+                    new ColumnDef("col", intCol, false, AggregateType.REPLACE_IF_NOT_NULL, null, false,
                             DefaultValueDef.NOT_SET,
                             "");
             column.analyze(true);
@@ -108,7 +112,7 @@ public void testReplaceIfNotNull() throws AnalysisException {
         }
         {
             // not allow null
-            ColumnDef column = new ColumnDef("col", intCol, false, AggregateType.REPLACE_IF_NOT_NULL, false,
+            ColumnDef column = new ColumnDef("col", intCol, false, AggregateType.REPLACE_IF_NOT_NULL, null, false,
                     new DefaultValueDef(true, new StringLiteral("10")), "");
             column.analyze(true);
             Assert.assertEquals(AggregateType.REPLACE_IF_NOT_NULL, column.getAggregateType());
@@ -119,7 +123,7 @@ public void testReplaceIfNotNull() throws AnalysisException {
     @Test
     public void testAutoIncrement() throws AnalysisException {
         {
-            ColumnDef column = new ColumnDef("col", BigIntCol, "utf8", false, null, Boolean.FALSE, DefaultValueDef.NOT_SET,
+            ColumnDef column = new ColumnDef("col", BigIntCol, "utf8", false, null, null, Boolean.FALSE, DefaultValueDef.NOT_SET,
                     Boolean.TRUE, null, "");
             column.analyze(true);
 
@@ -130,7 +134,7 @@ public void testAutoIncrement() throws AnalysisException {
             Assert.assertNull(column.getDefaultValue());
         }
         {
-            ColumnDef column = new ColumnDef("col", BigIntCol, "utf8", false, null, Boolean.FALSE, DefaultValueDef.NOT_SET,
+            ColumnDef column = new ColumnDef("col", BigIntCol, "utf8", false, null, null, Boolean.FALSE, DefaultValueDef.NOT_SET,
                     null, null, "");
             column.analyze(true);
 
@@ -141,7 +145,7 @@ public void testAutoIncrement() throws AnalysisException {
             Assert.assertNull(column.getDefaultValue());
         }
         {
-            ColumnDef column = new ColumnDef("col", BigIntCol, "utf8", true, null, Boolean.FALSE, DefaultValueDef.NOT_SET,
+            ColumnDef column = new ColumnDef("col", BigIntCol, "utf8", true, null, null, Boolean.FALSE, DefaultValueDef.NOT_SET,
                     Boolean.TRUE, null, "");
             column.analyze(true);
 
@@ -152,7 +156,7 @@ public void testAutoIncrement() throws AnalysisException {
             Assert.assertNull(column.getDefaultValue());
         }
         {
-            ColumnDef column = new ColumnDef("col", BigIntCol, "utf8", true, null, Boolean.FALSE, DefaultValueDef.NOT_SET,
+            ColumnDef column = new ColumnDef("col", BigIntCol, "utf8", true, null, null, Boolean.FALSE, DefaultValueDef.NOT_SET,
                     null, null, "");
             column.analyze(true);
 
@@ -180,34 +184,34 @@ public void testArrayKey() throws AnalysisException {
 
     @Test(expected = AnalysisException.class)
     public void testArrayDefaultValue() throws AnalysisException {
-        ColumnDef column = new ColumnDef("col", arrayIntCol, false, null, true,
+        ColumnDef column = new ColumnDef("col", arrayIntCol, false, null, null, true,
                 new DefaultValueDef(true, new StringLiteral("[1]")), "");
         column.analyze(true);
     }
 
     @Test(expected = AnalysisException.class)
     public void testStrSum() throws AnalysisException {
-        ColumnDef column = new ColumnDef("col", stringCol, false, AggregateType.SUM, true, DefaultValueDef.NOT_SET, "");
+        ColumnDef column = new ColumnDef("col", stringCol, false, AggregateType.SUM, null, true, DefaultValueDef.NOT_SET, "");
         column.analyze(true);
     }
 
     @Test
     public void testBooleanDefaultValue() throws AnalysisException {
         ColumnDef column1 =
-                new ColumnDef("col", booleanCol, true, null, true, new DefaultValueDef(true, new StringLiteral("1")),
-                        "");
+                new ColumnDef("col", booleanCol, true, null, null, true,
+                        new DefaultValueDef(true, new StringLiteral("1")), "");
         column1.analyze(true);
         Assert.assertEquals("1", column1.getDefaultValue());
 
         ColumnDef column2 =
-                new ColumnDef("col", booleanCol, true, null, true, new DefaultValueDef(true, new StringLiteral("true")),
-                        "");
+                new ColumnDef("col", booleanCol, true, null, null, true,
+                        new DefaultValueDef(true, new StringLiteral("true")), "");
         column2.analyze(true);
         Assert.assertEquals("true", column2.getDefaultValue());
 
         ColumnDef column3 =
-                new ColumnDef("col", booleanCol, true, null, true, new DefaultValueDef(true, new StringLiteral("10")),
-                        "");
+                new ColumnDef("col", booleanCol, true, null, null,
+                        true, new DefaultValueDef(true, new StringLiteral("10")), "");
         try {
             column3.analyze(true);
         } catch (AnalysisException e) {
@@ -218,30 +222,30 @@ public void testBooleanDefaultValue() throws AnalysisException {
     @Test
     public void testFloatDefaultValue() throws AnalysisException {
         ColumnDef column1 =
-                new ColumnDef("col", floatCol, false, null, true, new DefaultValueDef(true, new StringLiteral("1")),
-                        "");
+                new ColumnDef("col", floatCol, false, null, null,
+                        true, new DefaultValueDef(true, new StringLiteral("1")), "");
         column1.analyze(true);
         Assert.assertEquals("1", column1.getDefaultValue());
 
         ColumnDef column2 =
-                new ColumnDef("col", floatCol, false, null, true, new DefaultValueDef(true, new StringLiteral("1.1")),
-                        "");
+                new ColumnDef("col", floatCol, false, null, null, true,
+                        new DefaultValueDef(true, new StringLiteral("1.1")), "");
         column2.analyze(true);
         Assert.assertEquals("1.1", column2.getDefaultValue());
 
         ColumnDef column3 =
-                new ColumnDef("col", floatCol, false, null, true, new DefaultValueDef(true, new StringLiteral("1.100000000")),
-                        "");
+                new ColumnDef("col", floatCol, false, null, null, true,
+                        new DefaultValueDef(true, new StringLiteral("1" + ".100000000")), "");
         Assert.assertEquals("1.100000000", column3.getDefaultValue());
 
         ColumnDef column4 =
-                new ColumnDef("col", floatCol, false, null, true, new DefaultValueDef(true, new StringLiteral("1.1234567")),
-                        "");
+                new ColumnDef("col", floatCol, false, null, null, true,
+                        new DefaultValueDef(true, new StringLiteral("1.1234567")), "");
         Assert.assertEquals("1.1234567", column4.getDefaultValue());
 
         ColumnDef column5 =
-                new ColumnDef("col", floatCol, false, null, true, new DefaultValueDef(true, new StringLiteral("1.12345678")),
-                        "");
+                new ColumnDef("col", floatCol, false, null, null, true,
+                        new DefaultValueDef(true, new StringLiteral("1.12345678")), "");
         try {
             column5.analyze(true);
         } catch (AnalysisException e) {
@@ -249,31 +253,31 @@ public void testFloatDefaultValue() throws AnalysisException {
         }
 
         ColumnDef column6 =
-                new ColumnDef("col", floatCol, false, null, true, new DefaultValueDef(true, new StringLiteral("123456789")),
-                        "");
+                new ColumnDef("col", floatCol, false, null, null,
+                        true, new DefaultValueDef(true, new StringLiteral("123456789")), "");
         try {
             column6.analyze(true);
         } catch (AnalysisException e) {
             Assert.assertTrue(e.getMessage().contains("Default value will loose precision: 123456789"));
         }
         ColumnDef column7 =
-                new ColumnDef("col", floatCol, false, null, true, new DefaultValueDef(true, new StringLiteral("1.99E38")),
-                        "");
+                new ColumnDef("col", floatCol, false, null, null, true,
+                        new DefaultValueDef(true, new StringLiteral("1.99E38")), "");
         Assert.assertEquals("1.99E38", column7.getDefaultValue());
     }
 
     @Test(expected = SemanticException.class)
     public void testArrayHLL() throws AnalysisException {
         ColumnDef column =
-                new ColumnDef("col", new TypeDef(new ArrayType(Type.HLL)), false, null, true, DefaultValueDef.NOT_SET,
-                        "");
+                new ColumnDef("col", new TypeDef(new ArrayType(Type.HLL)), false, null, null,
+                        true, DefaultValueDef.NOT_SET, "");
         column.analyze(true);
     }
 
     @Test(expected = SemanticException.class)
     public void testArrayBitmap() throws AnalysisException {
         ColumnDef column =
-                new ColumnDef("col", new TypeDef(new ArrayType(Type.BITMAP)), false, null, true,
+                new ColumnDef("col", new TypeDef(new ArrayType(Type.BITMAP)), false, null, null, true,
                         DefaultValueDef.NOT_SET,
                         "");
         column.analyze(true);
@@ -281,7 +285,7 @@ public void testArrayBitmap() throws AnalysisException {
 
     @Test(expected = SemanticException.class)
     public void testArrayPercentile() throws AnalysisException {
-        ColumnDef column = new ColumnDef("col", new TypeDef(new ArrayType(Type.PERCENTILE)), false, null, true,
+        ColumnDef column = new ColumnDef("col", new TypeDef(new ArrayType(Type.PERCENTILE)), false, null, null, true,
                 DefaultValueDef.NOT_SET, "");
         column.analyze(true);
     }
@@ -289,7 +293,7 @@ public void testArrayPercentile() throws AnalysisException {
     @Test(expected = SemanticException.class)
     public void testInvalidVarcharInsideArray() throws AnalysisException {
         Type tooLongVarchar = ScalarType.createVarchar(ScalarType.getOlapMaxVarcharLength() + 1);
-        ColumnDef column = new ColumnDef("col", new TypeDef(new ArrayType(tooLongVarchar)), false, null, true,
+        ColumnDef column = new ColumnDef("col", new TypeDef(new ArrayType(tooLongVarchar)), false, null, null, true,
                 DefaultValueDef.NOT_SET, "");
         column.analyze(true);
     }
@@ -297,8 +301,23 @@ public void testInvalidVarcharInsideArray() throws AnalysisException {
     @Test(expected = SemanticException.class)
     public void testInvalidDecimalInsideArray() throws AnalysisException {
         Type invalidDecimal = ScalarType.createDecimalV2Type(100, -1);
-        ColumnDef column = new ColumnDef("col", new TypeDef(new ArrayType(invalidDecimal)), false, null, true,
+        ColumnDef column = new ColumnDef("col", new TypeDef(new ArrayType(invalidDecimal)), false, null, null, true,
                 DefaultValueDef.NOT_SET, "");
         column.analyze(true);
     }
+
+    @Test
+    public void testColumnWithAggStateDesc() throws AnalysisException {
+        AggregateFunction sum = AggregateFunction.createBuiltin(FunctionSet.SUM,
+                Lists.<Type>newArrayList(Type.INT), Type.BIGINT, Type.BIGINT, false, true, false);
+        AggStateDesc aggStateDesc = new AggStateDesc(sum);
+        ColumnDef column = new ColumnDef("col", BigIntCol, "utf8", false, AggregateType.AGG_STATE_UNION,
+                aggStateDesc, Boolean.FALSE, DefaultValueDef.NOT_SET, Boolean.TRUE, null, "");
+        column.analyze(true);
+        Assert.assertEquals("`col` bigint(20) AGG_STATE_UNION NOT NULL AUTO_INCREMENT COMMENT \"\"", column.toString());
+        Assert.assertEquals("col", column.getName());
+        Assert.assertEquals(PrimitiveType.BIGINT, column.getType().getPrimitiveType());
+        Assert.assertEquals(AggregateType.AGG_STATE_UNION, column.getAggregateType());
+        Assert.assertNull(column.getDefaultValue());
+    }
 }
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/CreateMaterializedViewTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/CreateMaterializedViewTest.java
index fb4a1083a5ada9..b990fdace4b53f 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/CreateMaterializedViewTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/CreateMaterializedViewTest.java
@@ -325,7 +325,7 @@ public static void beforeClass() throws Exception {
                 .useDatabase("test");
         starRocksAssert.withView("create view test.view_to_tbl1 as select * from test.tbl1;");
         currentState = GlobalStateMgr.getCurrentState();
-        testDb = currentState.getDb("test");
+        testDb = currentState.getLocalMetastore().getDb("test");
 
         UtFrameUtils.setUpForPersistTest();
     }
@@ -411,7 +411,7 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
             SlotRef slotRef = tableSlotRefs.get(0);
             TableName baseTableName = slotRef.getTblNameWithoutAnalyzed();
             Assert.assertEquals(baseTableName.getDb(), testDb.getFullName());
-            Table baseTable = testDb.getTable(baseTableName.getTbl());
+            Table baseTable = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), baseTableName.getTbl());
             Assert.assertNotNull(baseTable);
             Assert.assertEquals(baseTableInfos.get(0).getTableId(), baseTable.getId());
             Assert.assertEquals(1, baseTable.getRelatedMaterializedViews().size());
@@ -620,7 +620,7 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
         try {
             StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
             currentState.getLocalMetastore().createMaterializedView((CreateMaterializedViewStatement) statementBase);
-            Table mv1 = testDb.getTable("mv1");
+            Table mv1 = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "mv1");
             Assert.assertTrue(mv1 instanceof MaterializedView);
             // test partition
             MaterializedView materializedView = (MaterializedView) mv1;
@@ -640,7 +640,7 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
             SlotRef slotRef = slotRefs.get(0);
             TableName baseTableName = slotRef.getTblNameWithoutAnalyzed();
             Assert.assertEquals(baseTableName.getDb(), testDb.getFullName());
-            Table baseTable = testDb.getTable(baseTableName.getTbl());
+            Table baseTable = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), baseTableName.getTbl());
             Assert.assertNotNull(baseTable);
             Assert.assertTrue(baseTableInfos.stream().anyMatch(baseTableInfo ->
                     baseTableInfo.getTableId() == baseTable.getId()));
@@ -687,7 +687,7 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
         try {
             StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
             currentState.getLocalMetastore().createMaterializedView((CreateMaterializedViewStatement) statementBase);
-            Table mv1 = testDb.getTable("mv1");
+            Table mv1 = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "mv1");
             Assert.assertTrue(mv1 instanceof MaterializedView);
             // test partition
             MaterializedView materializedView = (MaterializedView) mv1;
@@ -1694,7 +1694,7 @@ public void testCreateMvFromInactiveMv() {
             Assert.fail(e.getMessage());
         }
 
-        MaterializedView baseInactiveMv = ((MaterializedView) testDb.getTable("base_inactive_mv"));
+        MaterializedView baseInactiveMv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "base_inactive_mv"));
         baseInactiveMv.setInactiveAndReason("");
 
         String sql2 = "create materialized view mv_from_base_inactive_mv " +
@@ -1728,11 +1728,11 @@ public void testAsHasStar() throws Exception {
         try {
             StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
             currentState.getLocalMetastore().createMaterializedView((CreateMaterializedViewStatement) statementBase);
-            MaterializedView mv = ((MaterializedView) testDb.getTable("testAsHasStar"));
+            MaterializedView mv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "testAsHasStar"));
             mv.setInactiveAndReason("");
             List<Column> mvColumns = mv.getFullSchema();
 
-            Table baseTable = testDb.getTable("tbl1");
+            Table baseTable = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "tbl1");
             List<Column> baseColumns = baseTable.getFullSchema();
 
             Assert.assertEquals(mvColumns.size(), baseColumns.size() + 1);
@@ -1821,7 +1821,7 @@ public void testAsSelectItemAlias1() throws Exception {
         try {
             StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
             currentState.getLocalMetastore().createMaterializedView((CreateMaterializedViewStatement) statementBase);
-            MaterializedView mv = ((MaterializedView) testDb.getTable("testAsSelectItemAlias1"));
+            MaterializedView mv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "testAsSelectItemAlias1"));
             mv.setInactiveAndReason("");
             List<Column> mvColumns = mv.getFullSchema();
 
@@ -1852,7 +1852,7 @@ public void testAsSelectItemAlias2() throws Exception {
         try {
             StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
             currentState.getLocalMetastore().createMaterializedView((CreateMaterializedViewStatement) statementBase);
-            MaterializedView mv = ((MaterializedView) testDb.getTable("testAsSelectItemAlias2"));
+            MaterializedView mv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "testAsSelectItemAlias2"));
             mv.setInactiveAndReason("");
             List<Column> mvColumns = mv.getFullSchema();
 
@@ -1981,7 +1981,7 @@ public void testCreateColocateMvToExitGroup() throws Exception {
         new MockUp<OlapTable>() {
             @Mock
             public boolean isEnableColocateMVIndex() throws Exception {
-                OlapTable table = (OlapTable) testDb.getTable("colocateTable");
+                OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "colocateTable");
 
                 // If the table's colocate group is empty, return false
                 if (Strings.isNullOrEmpty(table.getColocateGroup())) {
@@ -2010,7 +2010,7 @@ public boolean isEnableColocateMVIndex() throws Exception {
 
             ColocateTableIndex.GroupId groupId = colocateTableIndex.getGroup(tableId);
             Assert.assertEquals(1, colocateTableIndex.getAllTableIds(groupId).size());
-            OlapTable table = (OlapTable) testDb.getTable("colocateTable");
+            OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "colocateTable");
             Assert.assertTrue(table.isEnableColocateMVIndex());
 
             dropMv("colocateMv");
@@ -2072,7 +2072,7 @@ public void testColocateMvAlterGroup() throws Exception {
         new MockUp<OlapTable>() {
             @Mock
             public boolean isEnableColocateMVIndex() throws Exception {
-                OlapTable table = (OlapTable) testDb.getTable("colocateTable3");
+                OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "colocateTable3");
 
                 // If the table's colocate group is empty, return false
                 if (Strings.isNullOrEmpty(table.getColocateGroup())) {
@@ -2109,7 +2109,7 @@ public boolean isEnableColocateMVIndex() throws Exception {
             long tableId = colocateTableIndex.getTableIdByGroup(fullGroupName);
             Assert.assertNotEquals(-1, tableId);
 
-            OlapTable table = (OlapTable) testDb.getTable("colocateTable3");
+            OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "colocateTable3");
             Assert.assertTrue(table.isEnableColocateMVIndex());
 
             ColocateTableIndex.GroupId groupId = colocateTableIndex.getGroup(tableId);
@@ -2288,7 +2288,7 @@ public void testCreateMVWithSessionProperties1() {
                     (CreateMaterializedViewStatement) UtFrameUtils.parseStmtWithNewParser(sql,
                             starRocksAssert.getCtx());
             currentState.getLocalMetastore().createMaterializedView(stmt);
-            Table mv1 = testDb.getTable("mv_with_property1");
+            Table mv1 = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "mv_with_property1");
             Assert.assertTrue(mv1 instanceof MaterializedView);
         } catch (Exception e) {
             Assert.fail();
@@ -2704,8 +2704,8 @@ public void testPartitionByNotFirstColumn() throws Exception {
                 " partition by k1" +
                 " distributed by hash(k3) buckets 10" +
                 " as select k3, k1, sum(v1) as total from tbl5 group by k3, k1");
-        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getDb("test");
-        Table table = db.getTable("mv_with_partition_by_not_first_column");
+        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "mv_with_partition_by_not_first_column");
         Assert.assertTrue(table instanceof MaterializedView);
         MaterializedView mv = (MaterializedView) table;
         PartitionInfo partitionInfo = mv.getPartitionInfo();
@@ -2726,8 +2726,8 @@ public void testHiveMVWithoutPartition() throws Exception {
                 "DISTRIBUTED BY HASH(`s_suppkey`) BUCKETS 10 REFRESH MANUAL AS select     s_suppkey,     s_nationkey," +
                 "sum(s_acctbal) as total_s_acctbal,      count(s_phone) as s_phone_count from hive0.tpch.supplier as supp " +
                 "group by s_suppkey, s_nationkey order by s_suppkey;");
-        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getDb("test");
-        Table table = db.getTable("supplier_hive_mv");
+        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "supplier_hive_mv");
         Assert.assertTrue(table instanceof MaterializedView);
         MaterializedView mv = (MaterializedView) table;
         PartitionInfo partitionInfo = mv.getPartitionInfo();
@@ -2742,8 +2742,8 @@ public void testHiveMVJoinWithoutPartition() throws Exception {
                 "HASH(`s_suppkey`) BUCKETS 10 REFRESH MANUAL AS select     s_suppkey,     n_name,      sum(s_acctbal) " +
                 "as total_s_acctbal,      count(s_phone) as s_phone_count from " +
                 "hive0.tpch.supplier as supp join hive0.tpch.nation group by s_suppkey, n_name order by s_suppkey;");
-        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getDb("test");
-        Table table = db.getTable("supplier_nation_hive_mv");
+        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "supplier_nation_hive_mv");
         Assert.assertTrue(table instanceof MaterializedView);
         MaterializedView mv = (MaterializedView) table;
         PartitionInfo partitionInfo = mv.getPartitionInfo();
@@ -2761,8 +2761,8 @@ public void testHiveMVWithPartition() throws Exception {
                 "AS \n" +
                 "select l_shipdate, l_orderkey, l_quantity, l_linestatus, s_name from " +
                 "hive0.partitioned_db.lineitem_par join hive0.tpch.supplier where l_suppkey = s_suppkey\n");
-        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getDb("test");
-        Table table = db.getTable("lineitem_supplier_hive_mv");
+        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "lineitem_supplier_hive_mv");
         Assert.assertTrue(table instanceof MaterializedView);
         MaterializedView mv = (MaterializedView) table;
         PartitionInfo partitionInfo = mv.getPartitionInfo();
@@ -2782,8 +2782,8 @@ public void testHiveMVAsyncRefresh() throws Exception {
                 "AS select     s_suppkey,     s_nationkey, sum(s_acctbal) as total_s_acctbal,      " +
                 "count(s_phone) as s_phone_count from hive0.tpch.supplier as supp " +
                 "group by s_suppkey, s_nationkey order by s_suppkey;");
-        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getDb("test");
-        Table table = db.getTable("supplier_hive_mv");
+        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "supplier_hive_mv");
         Assert.assertTrue(table instanceof MaterializedView);
         MaterializedView mv = (MaterializedView) table;
         PartitionInfo partitionInfo = mv.getPartitionInfo();
@@ -2912,7 +2912,7 @@ public void testCreateAsyncMv() {
                 " select c_1_9, c_1_4 from t1";
         try {
             starRocksAssert.withMaterializedView(sql);
-            MaterializedView mv = (MaterializedView) testDb.getTable("async_mv_1");
+            MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "async_mv_1");
             Assert.assertTrue(mv.getFullSchema().get(0).isKey());
             Assert.assertFalse(mv.getFullSchema().get(1).isKey());
         } catch (Exception e) {
@@ -2957,7 +2957,7 @@ public void testCreateMVWithDifferentDB() {
             currentState.getLocalMetastore().createMaterializedView(stmt);
             waitingRollupJobV2Finish();
 
-            Table table = testDb.getTable("tbl5");
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "tbl5");
             Assert.assertNotNull(table);
             OlapTable olapTable = (OlapTable) table;
             Assert.assertTrue(olapTable.getIndexIdToMeta().size() >= 2);
@@ -3010,7 +3010,7 @@ public void testCreateAsyncMVWithDifferentDB() {
 
             currentState.getLocalMetastore().createMaterializedView(stmt);
             newStarRocksAssert.dropDatabase("test_mv_different_db");
-            Table mv1 = testDb.getTable("test_mv_use_different_tbl");
+            Table mv1 = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "test_mv_use_different_tbl");
             Assert.assertTrue(mv1 instanceof MaterializedView);
             starRocksAssert.dropMaterializedView("test_mv_use_different_tbl");
         } catch (Exception e) {
@@ -3036,8 +3036,8 @@ public void testCreateAsyncMVWithDifferentDB2() {
 
             currentState.getLocalMetastore().createMaterializedView(stmt);
 
-            Database differentDb = currentState.getDb("test_mv_different_db");
-            Table mv1 = differentDb.getTable("test_mv_use_different_tbl");
+            Database differentDb = currentState.getLocalMetastore().getDb("test_mv_different_db");
+            Table mv1 = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(differentDb.getFullName(), "test_mv_use_different_tbl");
             Assert.assertTrue(mv1 instanceof MaterializedView);
 
             newStarRocksAssert.dropDatabase("test_mv_different_db");
@@ -3063,7 +3063,7 @@ public void testCreateSyncMVWithCaseWhenComplexExpression1() {
             starRocksAssert.withMaterializedView(mv1);
             waitingRollupJobV2Finish();
 
-            Table table = testDb.getTable("case_when_t1");
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "case_when_t1");
             Assert.assertNotNull(table);
             OlapTable olapTable = (OlapTable) table;
             Assert.assertTrue(olapTable.getIndexIdToMeta().size() >= 2);
@@ -3155,8 +3155,8 @@ private void testMVColumnAlias(String expr) throws Exception {
                             "refresh deferred manual distributed by hash(c_1_9) as" +
                             " select c_1_9, %s from t1", mvName, expr);
             starRocksAssert.withMaterializedView(createMvExpr);
-            Database db = starRocksAssert.getCtx().getGlobalStateMgr().getDb("test");
-            Table table = db.getTable(mvName);
+            Database db = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb("test");
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), mvName);
             List<String> columnNames = table.getBaseSchema().stream().map(Column::getName).collect(Collectors.toList());
             Assert.assertTrue(columnNames.toString(), columnNames.contains(expr));
         } finally {
@@ -3174,8 +3174,8 @@ public void testExprAlias() throws Exception {
     }
 
     private Table getTable(String dbName, String mvName) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
-        Table table = db.getTable(mvName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), mvName);
         Assert.assertNotNull(table);
         return table;
     }
@@ -3494,9 +3494,9 @@ public void testMvOnUnion() throws Exception {
                 "\t c_mktsegment segment\n" +
                 "from customer_nullable_3;");
 
-        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getDb("test");
+        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb("test");
 
-        MaterializedView mv = (MaterializedView) db.getTable("customer_mv");
+        MaterializedView mv = (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "customer_mv");
         Assert.assertTrue(mv.getColumn("total").getType().isDecimalOfAnyVersion());
         Assert.assertFalse(mv.getColumn("segment").isAllowNull());
     }
@@ -3884,7 +3884,7 @@ MaterializedView getMaterializedViewChecked(String sql) {
             ThreadUtil.sleepAtLeastIgnoreInterrupts(4000L);
 
             TableName mvName = createMaterializedViewStatement.getTableName();
-            Table table = testDb.getTable(mvName.getTbl());
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), mvName.getTbl());
             Assert.assertNotNull(table);
             Assert.assertTrue(table instanceof MaterializedView);
             return (MaterializedView) table;
@@ -3908,7 +3908,7 @@ List<Column> getMaterializedViewKeysChecked(String sql) {
             TableName mvTableName = createMaterializedViewStatement.getTableName();
             mvName = mvTableName.getTbl();
 
-            Table table = testDb.getTable(mvName);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), mvName);
             Assert.assertNotNull(table);
             Assert.assertTrue(table instanceof MaterializedView);
             MaterializedView mv = (MaterializedView) table;
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/CreateSyncMaterializedViewTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/CreateSyncMaterializedViewTest.java
index 9ee8dc9e34e1fb..3a7cd51fb8d57a 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/CreateSyncMaterializedViewTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/CreateSyncMaterializedViewTest.java
@@ -198,12 +198,12 @@ public static void beforeClass() throws Exception {
                 .useDatabase("test");
         starRocksAssert.withView("create view test.view_to_tbl1 as select * from test.tbl1;");
         currentState = GlobalStateMgr.getCurrentState();
-        testDb = currentState.getDb("test");
+        testDb = currentState.getLocalMetastore().getDb("test");
     }
 
     private Table getTable(String dbName, String mvName) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
-        Table table = db.getTable(mvName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), mvName);
         Assert.assertNotNull(table);
         return table;
     }
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/CreateTableAutoTabletTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/CreateTableAutoTabletTest.java
index 6bb7c8d0947412..f46a80f89f70c4 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/CreateTableAutoTabletTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/CreateTableAutoTabletTest.java
@@ -54,11 +54,11 @@ public void testAutoTabletWithoutPartition() throws Exception {
         PseudoCluster cluster = PseudoCluster.getInstance();
         cluster.runSql("db_for_auto_tablets",
                 "create table test_table1 (pk bigint NOT NULL, v0 string not null) primary KEY (pk) DISTRIBUTED BY HASH(pk) PROPERTIES(\"replication_num\" = \"3\", \"storage_medium\" = \"SSD\");");
-        Database db = GlobalStateMgr.getCurrentState().getDb("db_for_auto_tablets");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db_for_auto_tablets");
         if (db == null) {
             return;
         }
-        OlapTable table = (OlapTable) db.getTable("test_table1");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_table1");
         if (table == null) {
             return;
         }
@@ -100,12 +100,12 @@ public void test1AutoTabletWithPartition() throws Exception {
                         " PARTITION BY RANGE(pk2) (START (\"2022-08-01\") END (\"2022-08-10\") EVERY (INTERVAL 1 day))" +
                         " DISTRIBUTED BY HASH(pk1)" +
                         " PROPERTIES (\"replication_num\" = \"3\", \"storage_medium\" = \"SSD\");");
-        Database db = GlobalStateMgr.getCurrentState().getDb("db_for_auto_tablets");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db_for_auto_tablets");
         if (db == null) {
             return;
         }
 
-        OlapTable table = (OlapTable) db.getTable("test_table2");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_table2");
         if (table == null) {
             return;
         }
@@ -150,12 +150,12 @@ public void test1AutoTabletWithDynamicPartition() throws Exception {
                         "   'dynamic_partition.end' = '3'," +
                         "   'dynamic_partition.prefix' = 'p');");
         Thread.sleep(1000); // wait for the dynamic partition created
-        Database db = GlobalStateMgr.getCurrentState().getDb("db_for_auto_tablets");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db_for_auto_tablets");
         if (db == null) {
             return;
         }
 
-        OlapTable table = (OlapTable) db.getTable("test_auto_tablets_of_dynamic_partition");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_auto_tablets_of_dynamic_partition");
         if (table == null) {
             return;
         }
@@ -197,12 +197,12 @@ public void test1AutoTabletWithModifyDynamicPartitionProperty() throws Exception
                         "   'dynamic_partition.buckets' = '3'," +
                         "   'dynamic_partition.prefix' = 'p');");
         Thread.sleep(1000); // wait for the dynamic partition created
-        Database db = GlobalStateMgr.getCurrentState().getDb("db_for_auto_tablets");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db_for_auto_tablets");
         if (db == null) {
             return;
         }
 
-        OlapTable table = (OlapTable) db.getTable("test_modify_dynamic_partition_property");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_modify_dynamic_partition_property");
         if (table == null) {
             return;
         }
@@ -244,12 +244,12 @@ public void test1AutoTabletWithColocate() throws Exception {
                         "  PROPERTIES (" +
                         "   'replication_num' = '1'," +
                         "   'colocate_with' = 'g1');");
-        Database db = GlobalStateMgr.getCurrentState().getDb("db_for_auto_tablets");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db_for_auto_tablets");
         if (db == null) {
             return;
         }
 
-        OlapTable table = (OlapTable) db.getTable("colocate_partition");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "colocate_partition");
         if (table == null) {
             return;
         }
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/MaterializedViewAutoTabletTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/MaterializedViewAutoTabletTest.java
index 139cdf35ed6811..5b7fdac57176ab 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/MaterializedViewAutoTabletTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/MaterializedViewAutoTabletTest.java
@@ -48,7 +48,7 @@ public void testMaterializedViewAutoTablet() throws Exception {
         PseudoCluster cluster = PseudoCluster.getInstance();
         cluster.runSql("db_for_auto_tablets",
                 "create table test_table1 (k1 bigint, v0 int) DUPLICATE KEY (k1) DISTRIBUTED BY HASH(k1);");
-        Database db = GlobalStateMgr.getCurrentState().getDb("db_for_auto_tablets");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db_for_auto_tablets");
         if (db == null) {
             return;
         }
@@ -59,7 +59,7 @@ public void testMaterializedViewAutoTablet() throws Exception {
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            OlapTable table = (OlapTable) db.getTable("test_table1");
+            OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_table1");
             if (table == null) {
                 return;
             }
@@ -67,7 +67,7 @@ public void testMaterializedViewAutoTablet() throws Exception {
                 bucketNum1 += partition.getDistributionInfo().getBucketNum();
             }
 
-            table = (OlapTable) db.getTable("mv1");
+            table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv1");
             if (table == null) {
                 return;
             }
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/RefreshMaterializedViewStatementTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/RefreshMaterializedViewStatementTest.java
index 69ba56b7e6ac99..4751f3d69f0a8f 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/RefreshMaterializedViewStatementTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/RefreshMaterializedViewStatementTest.java
@@ -86,14 +86,14 @@ public void testRereshNotMaterializedView() {
     @Test
     public void testRefreshMaterializedView() throws Exception {
 
-        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getDb("test");
+        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb("test");
         starRocksAssert.withMaterializedView("create materialized view mv1 distributed by hash(`c1`) " +
                 " refresh manual" +
                 " as select c1, sum(c3) as total from table_name_tmp_1 group by c1");
         cluster.runSql("test", "insert into table_name_tmp_1 values(1, \"str1\", 100)");
-        Table table = db.getTable("table_name_tmp_1");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "table_name_tmp_1");
         Assert.assertNotNull(table);
-        Table t2 = db.getTable("mv1");
+        Table t2 = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv1");
         Assert.assertNotNull(t2);
         MaterializedView mv1 = (MaterializedView) t2;
         cluster.runSql("test", "refresh materialized view mv1 with sync mode");
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/RefreshMaterializedViewTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/RefreshMaterializedViewTest.java
index 606320873e8f69..a8e9a75593a5bc 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/RefreshMaterializedViewTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/RefreshMaterializedViewTest.java
@@ -33,7 +33,6 @@
 import com.starrocks.sql.ast.DmlStmt;
 import com.starrocks.sql.ast.InsertStmt;
 import com.starrocks.sql.ast.RefreshMaterializedViewStatement;
-import com.starrocks.sql.optimizer.QueryMaterializationContext;
 import com.starrocks.sql.optimizer.rule.transformation.materialization.MvRewriteTestBase;
 import com.starrocks.sql.plan.ExecPlan;
 import com.starrocks.utframe.UtFrameUtils;
@@ -53,7 +52,7 @@
 import java.util.function.Function;
 import java.util.stream.Collectors;
 
-public class RefreshMaterializedViewTest  extends MvRewriteTestBase {
+public class RefreshMaterializedViewTest extends MvRewriteTestBase {
     // 1hour: set it to 1 hour to avoid FE's async update too late.
     private static final long MV_STALENESS = 60 * 60;
 
@@ -79,7 +78,7 @@ public static void beforeClass() throws Exception {
                         "refresh manual\n" +
                         "as select k2, sum(v1) as total from tbl_with_mv group by k2;")
                 .withMaterializedView("create materialized view mv2_to_refresh\n" +
-                        "PARTITION BY k1\n"+
+                        "PARTITION BY k1\n" +
                         "distributed by hash(k2) buckets 3\n" +
                         "refresh manual\n" +
                         "as select k1, k2, v1  from tbl_with_mv;");
@@ -96,7 +95,8 @@ public void testNormal() throws Exception {
         Assert.assertEquals("mv_to_refresh", mvName);
 
         String sql = "REFRESH MATERIALIZED VIEW test.mv2_to_refresh PARTITION START('2022-02-03') END ('2022-02-25') FORCE;";
-        RefreshMaterializedViewStatement statement = (RefreshMaterializedViewStatement) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
+        RefreshMaterializedViewStatement statement =
+                (RefreshMaterializedViewStatement) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         Assert.assertTrue(statement.isForceRefresh());
         Assert.assertEquals("2022-02-03", statement.getPartitionRangeDesc().getPartitionStart());
         Assert.assertEquals("2022-02-25", statement.getPartitionRangeDesc().getPartitionEnd());
@@ -122,7 +122,7 @@ public void testNormal() throws Exception {
             statement = (RefreshMaterializedViewStatement) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         } catch (Exception e) {
             Assert.assertEquals("Getting analyzing error from line 1, column 56 to line 1, column 90. " +
-                    "Detail message: Batch build partition EVERY is date type but START or END does not type match.",
+                            "Detail message: Batch build partition EVERY is date type but START or END does not type match.",
                     e.getMessage());
         }
     }
@@ -179,7 +179,7 @@ public void testMaxMVRewriteStaleness1() {
                 ),
                 () -> {
                     starRocksAssert.withMaterializedView("create materialized view mv_with_mv_rewrite_staleness\n" +
-                            "PARTITION BY k1\n"+
+                            "PARTITION BY k1\n" +
                             "distributed by hash(k2) buckets 3\n" +
                             "PROPERTIES (\n" +
                             "\"replication_num\" = \"1\"" +
@@ -258,7 +258,8 @@ public void testMaxMVRewriteStaleness2() {
 
                     // refresh partitions are not empty if base table is updated.
                     {
-                        executeInsertSql(connectContext, "insert into tbl_staleness2 partition(p2) values(\"2022-02-20\", 1, 10)");
+                        executeInsertSql(connectContext,
+                                "insert into tbl_staleness2 partition(p2) values(\"2022-02-20\", 1, 10)");
                         refreshMaterializedView("test", "mv_with_mv_rewrite_staleness2");
 
                         Table tbl1 = getTable("test", "tbl_staleness2");
@@ -339,7 +340,8 @@ public void testMaxMVRewriteStaleness3() {
                             "as select k1, k2, count(1)  from mv_with_mv_rewrite_staleness21 group by k1, k2;");
 
                     {
-                        executeInsertSql(connectContext, "insert into tbl_staleness3 partition(p2) values(\"2022-02-20\", 1, 10)");
+                        executeInsertSql(connectContext,
+                                "insert into tbl_staleness3 partition(p2) values(\"2022-02-20\", 1, 10)");
                         refreshMaterializedView("test", "mv_with_mv_rewrite_staleness21");
                         refreshMaterializedView("test", "mv_with_mv_rewrite_staleness22");
                         {
@@ -427,7 +429,8 @@ public void testMaxMVRewriteStaleness3() {
                                 String alterMvSql = "alter materialized view mv_with_mv_rewrite_staleness21 " +
                                         "set (\"mv_rewrite_staleness_second\" = \"0\")";
                                 AlterMaterializedViewStmt stmt =
-                                        (AlterMaterializedViewStmt) UtFrameUtils.parseStmtWithNewParser(alterMvSql, connectContext);
+                                        (AlterMaterializedViewStmt) UtFrameUtils.parseStmtWithNewParser(alterMvSql,
+                                                connectContext);
                                 GlobalStateMgr.getCurrentState().getLocalMetastore().alterMaterializedView(stmt);
                             }
 
@@ -457,8 +460,9 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
                 if (stmt instanceof InsertStmt) {
                     InsertStmt insertStmt = (InsertStmt) stmt;
                     TableName tableName = insertStmt.getTableName();
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb(stmt.getTableName().getDb());
-                    OlapTable tbl = ((OlapTable) testDb.getTable(tableName.getTbl()));
+                    Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(stmt.getTableName().getDb());
+                    OlapTable tbl = ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(testDb.getFullName(), tableName.getTbl()));
                     for (Partition partition : tbl.getPartitions()) {
                         if (insertStmt.getTargetPartitionIds().contains(partition.getId())) {
                             long version = partition.getVisibleVersion() + 1;
@@ -560,8 +564,9 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
                 if (stmt instanceof InsertStmt) {
                     InsertStmt insertStmt = (InsertStmt) stmt;
                     TableName tableName = insertStmt.getTableName();
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb(stmt.getTableName().getDb());
-                    OlapTable tbl = ((OlapTable) testDb.getTable(tableName.getTbl()));
+                    Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(stmt.getTableName().getDb());
+                    OlapTable tbl = ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(testDb.getFullName(), tableName.getTbl()));
                     for (Partition partition : tbl.getPartitions()) {
                         if (insertStmt.getTargetPartitionIds().contains(partition.getId())) {
                             long version = partition.getVisibleVersion() + 1;
@@ -581,49 +586,50 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
         };
 
         starRocksAssert.useDatabase("test")
-            .withTable("CREATE TABLE `test`.`tbl_with_partition` (\n" +
-                "  `k1` date,\n" +
-                "  `k2` int,\n" +
-                "  `v1` string\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`)\n" +
-                "PARTITION BY RANGE(`k1`)\n" +
-                "(\n" +
-                "PARTITION p20230410 VALUES [(\"2023-04-10\"), (\"2023-04-11\")),\n" +
-                "PARTITION p20230411 VALUES [(\"2023-04-11\"), (\"2023-04-12\")),\n" +
-                "PARTITION p20230412 VALUES [(\"2023-04-12\"), (\"2023-04-13\")),\n" +
-                "PARTITION p20230413 VALUES [(\"2023-04-13\"), (\"2023-04-14\"))\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`v1`) BUCKETS 3\n" +
-                "PROPERTIES (\"replication_num\" = \"1\");")
-            .withMaterializedView("CREATE MATERIALIZED VIEW `mv_with_partition`\n" +
-                "PARTITION BY (date_trunc('day', k1))\n" +
-                "REFRESH DEFERRED MANUAL \n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 3\n" +
-                "PROPERTIES (\"replication_num\" = \"1\", \"partition_refresh_number\"=\"1\")\n" +
-                "AS\n" +
-                "SELECT \n" +
-                "k1,\n" +
-                "count(DISTINCT `v1`) AS `v` \n" +
-                "FROM `test`.`tbl_with_partition`\n" +
-                "group by k1;");
+                .withTable("CREATE TABLE `test`.`tbl_with_partition` (\n" +
+                        "  `k1` date,\n" +
+                        "  `k2` int,\n" +
+                        "  `v1` string\n" +
+                        ") ENGINE=OLAP\n" +
+                        "DUPLICATE KEY(`k1`, `k2`)\n" +
+                        "PARTITION BY RANGE(`k1`)\n" +
+                        "(\n" +
+                        "PARTITION p20230410 VALUES [(\"2023-04-10\"), (\"2023-04-11\")),\n" +
+                        "PARTITION p20230411 VALUES [(\"2023-04-11\"), (\"2023-04-12\")),\n" +
+                        "PARTITION p20230412 VALUES [(\"2023-04-12\"), (\"2023-04-13\")),\n" +
+                        "PARTITION p20230413 VALUES [(\"2023-04-13\"), (\"2023-04-14\"))\n" +
+                        ")\n" +
+                        "DISTRIBUTED BY HASH(`v1`) BUCKETS 3\n" +
+                        "PROPERTIES (\"replication_num\" = \"1\");")
+                .withMaterializedView("CREATE MATERIALIZED VIEW `mv_with_partition`\n" +
+                        "PARTITION BY (date_trunc('day', k1))\n" +
+                        "REFRESH DEFERRED MANUAL \n" +
+                        "DISTRIBUTED BY HASH(`k1`) BUCKETS 3\n" +
+                        "PROPERTIES (\"replication_num\" = \"1\", \"partition_refresh_number\"=\"1\")\n" +
+                        "AS\n" +
+                        "SELECT \n" +
+                        "k1,\n" +
+                        "count(DISTINCT `v1`) AS `v` \n" +
+                        "FROM `test`.`tbl_with_partition`\n" +
+                        "group by k1;");
         starRocksAssert.updateTablePartitionVersion("test", "tbl_with_partition", 2);
         starRocksAssert.refreshMvPartition("REFRESH MATERIALIZED VIEW test.mv_with_partition \n" +
                 "PARTITION START (\"2023-04-10\") END (\"2023-04-14\")");
         MaterializedView mv = getMv("test", "mv_with_partition");
         Map<Long, Map<String, MaterializedView.BasePartitionInfo>> versionMap =
-            mv.getRefreshScheme().getAsyncRefreshContext().getBaseTableVisibleVersionMap();
+                mv.getRefreshScheme().getAsyncRefreshContext().getBaseTableVisibleVersionMap();
         Assert.assertEquals(1, versionMap.size());
         Set<String> partitions = versionMap.values().iterator().next().keySet();
         //        Assert.assertEquals(4, partitions.size());
 
         starRocksAssert.alterMvProperties(
-            "alter materialized view test.mv_with_partition set (\"partition_ttl_number\" = \"1\")");
+                "alter materialized view test.mv_with_partition set (\"partition_ttl_number\" = \"1\")");
 
         DynamicPartitionScheduler dynamicPartitionScheduler = GlobalStateMgr.getCurrentState()
-            .getDynamicPartitionScheduler();
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("mv_with_partition");
+                .getDynamicPartitionScheduler();
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl =
+                (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv_with_partition");
         dynamicPartitionScheduler.registerTtlPartitionTable(db.getId(), tbl.getId());
         dynamicPartitionScheduler.runOnceForTest();
         starRocksAssert.refreshMvPartition("REFRESH MATERIALIZED VIEW test.mv_with_partition \n" +
@@ -631,9 +637,9 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
         Assert.assertEquals(Sets.newHashSet("p20230413"), versionMap.values().iterator().next().keySet());
 
         starRocksAssert
-            .useDatabase("test")
-            .dropMaterializedView("mv_with_partition")
-            .dropTable("tbl_with_partition");
+                .useDatabase("test")
+                .dropMaterializedView("mv_with_partition")
+                .dropTable("tbl_with_partition");
     }
 
     private Set<LocalDate> buildTimePartitions(String tableName, OlapTable tbl, int partitionCount) throws Exception {
@@ -656,22 +662,22 @@ public void testMaterializedViewPartitionTTL() throws Exception {
         String dbName = "test";
         String tableName = "test.tbl1";
         starRocksAssert.withTable("CREATE TABLE " + tableName +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    v1 int \n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values less than('2022-06-01'),\n" +
-                        "    PARTITION p2 values less than('2022-07-01'),\n" +
-                        "    PARTITION p3 values less than('2022-08-01'),\n" +
-                        "    PARTITION p4 values less than('2022-09-01')\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH (k1) BUCKETS 3\n" +
-                        "PROPERTIES\n" +
-                        "(\n" +
-                        "    'replication_num' = '1'\n" +
-                        ");");
+                "(\n" +
+                "    k1 date,\n" +
+                "    v1 int \n" +
+                ")\n" +
+                "PARTITION BY RANGE(k1)\n" +
+                "(\n" +
+                "    PARTITION p1 values less than('2022-06-01'),\n" +
+                "    PARTITION p2 values less than('2022-07-01'),\n" +
+                "    PARTITION p3 values less than('2022-08-01'),\n" +
+                "    PARTITION p4 values less than('2022-09-01')\n" +
+                ")\n" +
+                "DISTRIBUTED BY HASH (k1) BUCKETS 3\n" +
+                "PROPERTIES\n" +
+                "(\n" +
+                "    'replication_num' = '1'\n" +
+                ");");
         starRocksAssert.withMaterializedView("CREATE MATERIALIZED VIEW test.mv_ttl_mv1\n" +
                 " REFRESH ASYNC " +
                 " PARTITION BY k1\n" +
@@ -680,8 +686,8 @@ public void testMaterializedViewPartitionTTL() throws Exception {
 
         DynamicPartitionScheduler dynamicPartitionScheduler = GlobalStateMgr.getCurrentState()
                 .getDynamicPartitionScheduler();
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("mv_ttl_mv1");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv_ttl_mv1");
         Set<LocalDate> addedPartitions = buildTimePartitions(tableName, tbl, 10);
 
         // Build expectations
@@ -849,7 +855,8 @@ public void testMvOnUnion_IntersectedPartition1() throws Exception {
                     "AS \n" +
                     "SELECT * FROM mv_union_t1 t1\n" +
                     "UNION ALL\n" +
-                    "SELECT * FROM mv_union_t2 t2\n", () -> {});
+                    "SELECT * FROM mv_union_t2 t2\n", () -> {
+            });
         }
 
         {
@@ -860,7 +867,8 @@ public void testMvOnUnion_IntersectedPartition1() throws Exception {
                     "AS \n" +
                     "SELECT * FROM mv_union_t1 t1\n" +
                     "UNION ALL\n" +
-                    "SELECT * FROM mv_union_t3 t2\n", () -> {});
+                    "SELECT * FROM mv_union_t3 t2\n", () -> {
+            });
         }
 
         {
@@ -871,7 +879,8 @@ public void testMvOnUnion_IntersectedPartition1() throws Exception {
                     "AS \n" +
                     "SELECT * FROM mv_union_t1 t1\n" +
                     "UNION ALL\n" +
-                    "SELECT * FROM mv_union_t4 t2\n", () -> {});
+                    "SELECT * FROM mv_union_t4 t2\n", () -> {
+            });
             // add partition to child table
             starRocksAssert.ddl("alter table mv_union_t4 add partition p20240325 values less than ('2024-03-25')");
             starRocksAssert.ddl("alter table mv_union_t1 add partition p20240326 values less than ('2024-03-26')");
@@ -968,8 +977,9 @@ public void testMvOnUnion_IntersectedPartition3() throws Exception {
                     "UNION ALL\n" +
                     "SELECT * FROM t2\n", () -> {
 
-                Database db = GlobalStateMgr.getCurrentState().getDb("test");
-                MaterializedView  mv = (MaterializedView) db.getTable("mv1");
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+                MaterializedView mv =
+                        (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv1");
                 System.out.println(mv.getPartitionNames());
             });
         }
@@ -1018,8 +1028,9 @@ public void testMvOnUnion_IntersectedPartition4() throws Exception {
                     "SELECT * FROM t1\n" +
                     "UNION ALL\n" +
                     "SELECT * FROM t2\n", () -> {
-                Database db = GlobalStateMgr.getCurrentState().getDb("test");
-                MaterializedView  mv = (MaterializedView) db.getTable("mv1");
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+                MaterializedView mv =
+                        (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv1");
                 Assert.assertEquals(2, mv.getPartitionExprMaps().size());
                 System.out.println(mv.getPartitionNames());
             });
@@ -1067,8 +1078,9 @@ public void testMvOnUnion_IntersectedPartition5() throws Exception {
                     "REFRESH ASYNC\n" +
                     "AS \n" +
                     "select k1 from (SELECT * FROM t1 UNION ALL SELECT * FROM t2) t group by k1\n", () -> {
-                Database db = GlobalStateMgr.getCurrentState().getDb("test");
-                MaterializedView  mv = (MaterializedView) db.getTable("mv1");
+                Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+                MaterializedView mv =
+                        (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv1");
                 System.out.println(mv.getPartitionExprMaps());
                 Assert.assertEquals(2, mv.getPartitionExprMaps().size());
                 System.out.println(mv.getPartitionNames());
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/ResourceGroupStmtTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/ResourceGroupStmtTest.java
index 587d053953e2d6..6adc21da39b627 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/ResourceGroupStmtTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/ResourceGroupStmtTest.java
@@ -43,7 +43,7 @@
 public class ResourceGroupStmtTest {
     private static final Pattern idPattern = Pattern.compile("\\bid=(\\b\\d+\\b)");
     private static StarRocksAssert starRocksAssert;
-    private String createRg1Sql = "create resource group rg1\n" +
+    private final String createRg1Sql = "create resource group rg1\n" +
             "to\n" +
             "    (user='rg1_user1', role='rg1_role1', query_type in ('select'), source_ip='192.168.2.1/24'),\n" +
             "    (user='rg1_user2', query_type in ('select'), source_ip='192.168.3.1/24'),\n" +
@@ -56,7 +56,7 @@ public class ResourceGroupStmtTest {
             "    'concurrency_limit' = '11',\n" +
             "    'type' = 'normal'\n" +
             ");";
-    private String createRg1IfNotExistsSql = "create resource group if not exists rg1\n" +
+    private final String createRg1IfNotExistsSql = "create resource group if not exists rg1\n" +
             "to\n" +
             "    (user='rg1_if_not_exists', role='rg1_role1', query_type in ('select'), source_ip='192.168.2.1/24')\n" +
             "with (\n" +
@@ -67,7 +67,7 @@ public class ResourceGroupStmtTest {
             "    'type' = 'normal'\n" +
             ");";
 
-    private String createRg1OrReplaceSql = "create resource group or replace rg1\n" +
+    private final String createRg1OrReplaceSql = "create resource group or replace rg1\n" +
             "to\n" +
             "    (user='rg1_or_replace', role='rg1_role1', query_type in ('select'), source_ip='192.168.2.1/24')\n" +
             "with (\n" +
@@ -78,7 +78,7 @@ public class ResourceGroupStmtTest {
             "    'type' = 'normal'\n" +
             ");";
 
-    private String createRg1IfNotExistsOrReplaceSql = "create resource group if not exists or replace rg1\n" +
+    private final String createRg1IfNotExistsOrReplaceSql = "create resource group if not exists or replace rg1\n" +
             "to\n" +
             "    (user='rg1_if_not_exists_or_replace', role='rg1_role1', " +
             "query_type in ('select'), source_ip='192" +
@@ -91,7 +91,7 @@ public class ResourceGroupStmtTest {
             "    'type' = 'normal'\n" +
             ");";
 
-    private String createRg2Sql = "create resource group rg2\n" +
+    private final String createRg2Sql = "create resource group rg2\n" +
             "to\n" +
             "    (role='rg2_role1', query_type in ('select' ), source_ip='192.168.5.1/24'),\n" +
             "    (role='rg2_role2', source_ip='192.168.6.1/24'),\n" +
@@ -112,7 +112,7 @@ public class ResourceGroupStmtTest {
             "    'concurrency_limit' = '10',\n" +
             "    'type' = 'normal'\n" +
             ");";
-    private String createRg4Sql = "create resource group rg4\n" +
+    private final String createRg4Sql = "create resource group rg4\n" +
             "to\n" +
             "     (source_ip='192.168.7.1/24')\n" +
             "with (\n" +
@@ -124,7 +124,7 @@ public class ResourceGroupStmtTest {
             "   'big_query_cpu_second_limit'='1024',\n" +
             "    'type' = 'normal'\n" +
             ");";
-    private String createRg5Sql = "create resource group rg5\n" +
+    private final String createRg5Sql = "create resource group rg5\n" +
             "to\n" +
             "     (`db`='db1')\n" +
             "with (\n" +
@@ -133,7 +133,7 @@ public class ResourceGroupStmtTest {
             "    'concurrency_limit' = '10',\n" +
             "    'type' = 'normal'\n" +
             ");";
-    private String createRg6Sql = "create resource group rg6\n" +
+    private final String createRg6Sql = "create resource group rg6\n" +
             "to\n" +
             "    (query_type in ('insert'), source_ip='192.168.6.1/24')\n" +
             "with (\n" +
@@ -143,7 +143,7 @@ public class ResourceGroupStmtTest {
             "    'type' = 'normal'\n" +
             ");";
 
-    private String createRg7Sql = "create resource group rg7\n" +
+    private final String createRg7Sql = "create resource group rg7\n" +
             "to\n" +
             "    (query_type in ('select'), source_ip='192.168.6.1/24')\n" +
             "with (\n" +
@@ -164,7 +164,7 @@ public class ResourceGroupStmtTest {
             "    'type' = 'short_query'\n" +
             ");";
 
-    private String createMVRg = "create resource group if not exists mv_rg" +
+    private final String createMVRg = "create resource group if not exists mv_rg" +
             "   with (" +
             "   'cpu_core_limit' = '10'," +
             "   'mem_limit' = '20%'," +
@@ -192,11 +192,11 @@ private static String rowsToString(List<List<String>> rows) {
         List<String> lines = rows.stream().map(
                 row -> {
                     row.remove(1);
-                    return String.join("|",
+                    return java.lang.String.join("|",
                             row.toArray(new String[0])).replaceAll("id=\\d+(,\\s+)?", "");
                 }
         ).collect(Collectors.toList());
-        return String.join("\n", lines.toArray(new String[0]));
+        return java.lang.String.join("\n", lines.toArray(new String[0]));
     }
 
     private static String getClassifierId(String classifierStr) {
@@ -218,35 +218,35 @@ private void dropResourceGroups() throws Exception {
         for (String name : rgNames) {
             starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP " + name);
         }
-        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource groups all");
         Assert.assertTrue(rows.toString(), rows.isEmpty());
     }
 
     private void assertResourceGroupNotExist(String wg) {
         Assert.assertThrows(ERROR_NO_RG_ERROR.formatErrorMsg(wg), SemanticException.class,
-                () -> starRocksAssert.executeResourceGroupShowSql("show resource group " + wg));
+                () -> starRocksAssert.executeResourceGroupShowSql("show verbose resource group " + wg));
     }
 
     @Test
     public void testCreateResourceGroup() throws Exception {
         createResourceGroups();
-        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource groups all");
         String result = rowsToString(rows);
         String expect = "" +
-                "rg1|10|20.0%|8|0|0|0|11|100%|NORMAL|(weight=4.475, user=rg1_user1, role=rg1_role1, query_type in (SELECT), source_ip=192.168.2.1/24)\n" +
-                "rg1|10|20.0%|8|0|0|0|11|100%|NORMAL|(weight=3.475, user=rg1_user2, query_type in (SELECT), source_ip=192.168.3.1/24)\n" +
-                "rg1|10|20.0%|8|0|0|0|11|100%|NORMAL|(weight=2.375, user=rg1_user3, source_ip=192.168.4.1/24)\n" +
-                "rg1|10|20.0%|8|0|0|0|11|100%|NORMAL|(weight=1.0, user=rg1_user4)\n" +
-                "rg2|30|50.0%|null|0|0|0|20|100%|NORMAL|(weight=3.475, role=rg2_role1, query_type in (SELECT), source_ip=192.168.5.1/24)\n" +
-                "rg2|30|50.0%|null|0|0|0|20|100%|NORMAL|(weight=2.375, role=rg2_role2, source_ip=192.168.6.1/24)\n" +
-                "rg2|30|50.0%|null|0|0|0|20|100%|NORMAL|(weight=1.0, role=rg2_role3)\n" +
-                "rg3|32|80.0%|null|0|0|0|10|100%|NORMAL|(weight=2.475, query_type in (SELECT), source_ip=192.168.6.1/24)\n" +
-                "rg3|32|80.0%|null|0|0|0|10|100%|NORMAL|(weight=1.1, query_type in (SELECT))\n" +
-                "rg4|25|80.0%|null|1024|1024|1024|10|100%|NORMAL|(weight=1.375, source_ip=192.168.7.1/24)\n" +
-                "rg5|25|80.0%|null|0|0|0|10|100%|NORMAL|(weight=10.0, db='db1')\n" +
-                "rg6|32|80.0%|null|0|0|0|10|100%|NORMAL|(weight=2.475, query_type in (INSERT), source_ip=192.168.6.1/24)\n" +
-                "rg7|32|80.0%|null|0|0|0|10|30.0%|NORMAL|(weight=2.475, query_type in (SELECT), source_ip=192.168.6.1/24)\n" +
-                "rt_rg1|25|80.0%|null|0|0|0|10|100%|SHORT_QUERY|(weight=1.0, user=rt_rg_user)";
+                "rg1|10|0|20.0%|8|0|0|0|11|100%|NORMAL|(weight=4.475, user=rg1_user1, role=rg1_role1, query_type in (SELECT), source_ip=192.168.2.1/24)\n" +
+                "rg1|10|0|20.0%|8|0|0|0|11|100%|NORMAL|(weight=3.475, user=rg1_user2, query_type in (SELECT), source_ip=192.168.3.1/24)\n" +
+                "rg1|10|0|20.0%|8|0|0|0|11|100%|NORMAL|(weight=2.375, user=rg1_user3, source_ip=192.168.4.1/24)\n" +
+                "rg1|10|0|20.0%|8|0|0|0|11|100%|NORMAL|(weight=1.0, user=rg1_user4)\n" +
+                "rg2|30|0|50.0%|null|0|0|0|20|100%|NORMAL|(weight=3.475, role=rg2_role1, query_type in (SELECT), source_ip=192.168.5.1/24)\n" +
+                "rg2|30|0|50.0%|null|0|0|0|20|100%|NORMAL|(weight=2.375, role=rg2_role2, source_ip=192.168.6.1/24)\n" +
+                "rg2|30|0|50.0%|null|0|0|0|20|100%|NORMAL|(weight=1.0, role=rg2_role3)\n" +
+                "rg3|32|0|80.0%|null|0|0|0|10|100%|NORMAL|(weight=2.475, query_type in (SELECT), source_ip=192.168.6.1/24)\n" +
+                "rg3|32|0|80.0%|null|0|0|0|10|100%|NORMAL|(weight=1.1, query_type in (SELECT))\n" +
+                "rg4|25|0|80.0%|null|1024|1024|1024|10|100%|NORMAL|(weight=1.375, source_ip=192.168.7.1/24)\n" +
+                "rg5|25|0|80.0%|null|0|0|0|10|100%|NORMAL|(weight=10.0, db='db1')\n" +
+                "rg6|32|0|80.0%|null|0|0|0|10|100%|NORMAL|(weight=2.475, query_type in (INSERT), source_ip=192.168.6.1/24)\n" +
+                "rg7|32|0|80.0%|null|0|0|0|10|30%|NORMAL|(weight=2.475, query_type in (SELECT), source_ip=192.168.6.1/24)\n" +
+                "rt_rg1|25|25|80.0%|null|0|0|0|10|100%|SHORT_QUERY|(weight=1.0, user=rt_rg_user)";
         Assert.assertEquals(expect, result);
         dropResourceGroups();
     }
@@ -258,19 +258,19 @@ public void testCreateDuplicateResourceGroup() throws Exception {
         assertResourceGroupNotExist("rg1");
 
         starRocksAssert.executeResourceGroupDdlSql(createRg1IfNotExistsSql);
-        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource group rg1");
+        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource group rg1");
         Assert.assertEquals(rows.size(), 1);
         String actual = rowsToString(rows);
         Assert.assertTrue(actual.contains("rg1_if_not_exists"));
 
         starRocksAssert.executeResourceGroupDdlSql(createRg1OrReplaceSql);
-        rows = starRocksAssert.executeResourceGroupShowSql("show resource group rg1");
+        rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource group rg1");
         Assert.assertEquals(rows.size(), 1);
         actual = rowsToString(rows);
         Assert.assertTrue(actual.contains("rg1_or_replace"));
 
         starRocksAssert.executeResourceGroupDdlSql(createRg1IfNotExistsSql);
-        rows = starRocksAssert.executeResourceGroupShowSql("show resource group rg1");
+        rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource group rg1");
         Assert.assertEquals(rows.size(), 1);
         actual = rowsToString(rows);
         Assert.assertTrue(actual.contains("rg1_or_replace"));
@@ -279,13 +279,13 @@ public void testCreateDuplicateResourceGroup() throws Exception {
         assertResourceGroupNotExist("rg1");
 
         starRocksAssert.executeResourceGroupDdlSql(createRg1OrReplaceSql);
-        rows = starRocksAssert.executeResourceGroupShowSql("show resource group rg1");
+        rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource group rg1");
         Assert.assertEquals(rows.size(), 1);
         actual = rowsToString(rows);
         Assert.assertTrue(actual.contains("rg1_or_replace"));
 
         starRocksAssert.executeResourceGroupDdlSql(createRg1IfNotExistsOrReplaceSql);
-        rows = starRocksAssert.executeResourceGroupShowSql("show resource group rg1");
+        rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource group rg1");
         Assert.assertEquals(rows.size(), 1);
         actual = rowsToString(rows);
         System.out.println(actual);
@@ -365,7 +365,7 @@ public void testQueryType() throws Exception {
     @Test
     public void testAlterResourceGroupDropManyClassifiers() throws Exception {
         createResourceGroups();
-        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource groups all");
         String rgName = rows.get(0).get(0);
         List<String> classifierIds = rows.stream().filter(row -> row.get(0).equals(rgName))
                 .map(row -> getClassifierId(row.get(row.size() - 1))).collect(Collectors.toList());
@@ -378,7 +378,7 @@ public void testAlterResourceGroupDropManyClassifiers() throws Exception {
         String alterSql = String.format("ALTER RESOURCE GROUP %s DROP (%s)", rgName, ids);
         starRocksAssert.executeResourceGroupDdlSql(alterSql);
         String expect = rowsToString(rows);
-        rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+        rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource groups all");
         String actual = rowsToString(rows);
         Assert.assertEquals(expect, actual);
         dropResourceGroups();
@@ -387,7 +387,7 @@ public void testAlterResourceGroupDropManyClassifiers() throws Exception {
     @Test
     public void testAlterResourceGroupDropOneClassifier() throws Exception {
         createResourceGroups();
-        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource groups all");
         Random rand = new Random();
         Map<String, Integer> classifierCount = new HashMap<>();
         rows.forEach(row -> classifierCount
@@ -412,7 +412,7 @@ public void testAlterResourceGroupDropOneClassifier() throws Exception {
             starRocksAssert.executeResourceGroupDdlSql(alterSql);
         }
         String expect = rowsToString(rows);
-        rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+        rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource groups all");
         String actual = rowsToString(rows);
         Assert.assertEquals(expect, actual);
         dropResourceGroups();
@@ -421,7 +421,7 @@ public void testAlterResourceGroupDropOneClassifier() throws Exception {
     @Test
     public void testAlterResourceGroupDropAllClassifier() throws Exception {
         createResourceGroups();
-        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource groups all");
         String rgName = "rg2";
         rows = rows.stream().peek(row -> {
             if (row.get(0).equals(rgName)) {
@@ -431,7 +431,7 @@ public void testAlterResourceGroupDropAllClassifier() throws Exception {
         String alterSql = String.format("ALTER RESOURCE GROUP %s DROP ALL", rgName);
         starRocksAssert.executeResourceGroupDdlSql(alterSql);
         String expect = rowsToString(rows);
-        rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+        rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource groups all");
         String actual = rowsToString(rows);
         Assert.assertEquals(expect, actual);
         dropResourceGroups();
@@ -446,7 +446,7 @@ public void testAlterResourceGroupAddOneClassifier() throws Exception {
                 "   (user='rg1_user5', role='rg1_role5', source_ip='192.168.4.1/16')";
 
         starRocksAssert.executeResourceGroupDdlSql(sql);
-        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("SHOW RESOURCE GROUP rg1");
+        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource group rg1");
         String result = rowsToString(rows);
         Assert.assertTrue(result.contains("rg1_user5"));
         dropResourceGroups();
@@ -463,7 +463,7 @@ public void testAlterResourceGroupAddManyClassifiers() throws Exception {
                 "   (source_ip='192.169.6.1/16');\n";
 
         starRocksAssert.executeResourceGroupDdlSql(sql);
-        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("SHOW RESOURCE GROUP rg2");
+        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource group rg2");
         String result = rowsToString(rows);
         Assert.assertTrue(result.contains("rg2_user4"));
         Assert.assertTrue(result.contains("rg2_role5"));
@@ -476,9 +476,9 @@ public void testShowUnknownOrNotExistWorkGroup() throws Exception {
         starRocksAssert.executeResourceGroupDdlSql(createRg1Sql);
 
         starRocksAssert.executeResourceGroupDdlSql("ALTER RESOURCE GROUP rg1 DROP ALL;");
-        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource group rg1");
+        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource group rg1");
         String actual = rowsToString(rows);
-        String expect = "rg1|10|20.0%|8|0|0|0|11|100%|NORMAL|(weight=0.0)";
+        String expect = "rg1|10|0|20.0%|8|0|0|0|11|100%|NORMAL|(weight=0.0)";
         Assert.assertEquals(expect, actual);
 
         starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg1");
@@ -531,7 +531,7 @@ public void testChooseResourceGroupWithDb() throws Exception {
         starRocksAssert.getCtx().setCurrentUserIdentity(new UserIdentity(qualifiedUser, "%"));
         starRocksAssert.getCtx().setRemoteIP(remoteIp);
         {
-            long dbId = GlobalStateMgr.getCurrentState().getDb("db1").getId();
+            long dbId = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db1").getId();
             Set<Long> dbIds = ImmutableSet.of(dbId);
             TWorkGroup wg = GlobalStateMgr.getCurrentState().getResourceGroupMgr().chooseResourceGroup(
                     starRocksAssert.getCtx(),
@@ -540,7 +540,7 @@ public void testChooseResourceGroupWithDb() throws Exception {
             Assert.assertEquals("rg5", wg.getName());
         }
         {
-            long dbId = GlobalStateMgr.getCurrentState().getDb("db2").getId();
+            long dbId = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db2").getId();
             Set<Long> dbIds = ImmutableSet.of(dbId);
             TWorkGroup wg = GlobalStateMgr.getCurrentState().getResourceGroupMgr().chooseResourceGroup(
                     starRocksAssert.getCtx(),
@@ -551,8 +551,8 @@ public void testChooseResourceGroupWithDb() throws Exception {
         }
         {
             Set<Long> dbIds = ImmutableSet.of(
-                    GlobalStateMgr.getCurrentState().getDb("db1").getId(),
-                    GlobalStateMgr.getCurrentState().getDb("db2").getId());
+                    GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db1").getId(),
+                    GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db2").getId());
             TWorkGroup wg = GlobalStateMgr.getCurrentState().getResourceGroupMgr().chooseResourceGroup(
                     starRocksAssert.getCtx(),
                     ResourceGroupClassifier.QueryType.SELECT,
@@ -571,12 +571,12 @@ public void testShowVisibleResourceGroups() throws Exception {
         starRocksAssert.getCtx().setCurrentUserIdentity(new UserIdentity(qualifiedUser, "%"));
         starRocksAssert.getCtx().setRemoteIP(remoteIp);
         List<List<String>> rows = GlobalStateMgr.getCurrentState().getResourceGroupMgr().showAllResourceGroups(
-                starRocksAssert.getCtx(), false);
+                starRocksAssert.getCtx(), true, false);
         String result = rowsToString(rows);
         String expect = "" +
-                "rg5|25|80.0%|null|0|0|0|10|100%|NORMAL|(weight=10.0, db='db1')\n" +
-                "rg1|10|20.0%|8|0|0|0|11|100%|NORMAL|(weight=4.475, user=rg1_user1, role=rg1_role1, query_type in (SELECT), source_ip=192.168.2.1/24)\n" +
-                "rg3|32|80.0%|null|0|0|0|10|100%|NORMAL|(weight=1.1, query_type in (SELECT))";
+                "rg5|25|0|80.0%|null|0|0|0|10|100%|NORMAL|(weight=10.0, db='db1')\n" +
+                "rg1|10|0|20.0%|8|0|0|0|11|100%|NORMAL|(weight=4.475, user=rg1_user1, role=rg1_role1, query_type in (SELECT), source_ip=192.168.2.1/24)\n" +
+                "rg3|32|0|80.0%|null|0|0|0|10|100%|NORMAL|(weight=1.1, query_type in (SELECT))";
         Assert.assertEquals(expect, result);
         dropResourceGroups();
     }
@@ -629,23 +629,23 @@ public void testAlterResourceGroupAlterProperties() throws Exception {
         for (String sql : sqls) {
             starRocksAssert.executeResourceGroupDdlSql(sql);
         }
-        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("SHOW RESOURCE GROUPS all");
+        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource groups all");
         String result = rowsToString(rows);
         String expect = "" +
-                "rg1|21|20.0%|4|0|0|0|11|100%|NORMAL|(weight=4.475, user=rg1_user1, role=rg1_role1, query_type in (SELECT), source_ip=192.168.2.1/24)\n" +
-                "rg1|21|20.0%|4|0|0|0|11|100%|NORMAL|(weight=3.475, user=rg1_user2, query_type in (SELECT), source_ip=192.168.3.1/24)\n" +
-                "rg1|21|20.0%|4|0|0|0|11|100%|NORMAL|(weight=2.375, user=rg1_user3, source_ip=192.168.4.1/24)\n" +
-                "rg1|21|20.0%|4|0|0|0|11|100%|NORMAL|(weight=1.0, user=rg1_user4)\n" +
-                "rg2|30|37.0%|null|0|0|0|20|100%|NORMAL|(weight=3.475, role=rg2_role1, query_type in (SELECT), source_ip=192.168.5.1/24)\n" +
-                "rg2|30|37.0%|null|0|0|0|20|100%|NORMAL|(weight=2.375, role=rg2_role2, source_ip=192.168.6.1/24)\n" +
-                "rg2|30|37.0%|null|0|0|0|20|100%|NORMAL|(weight=1.0, role=rg2_role3)\n" +
-                "rg3|32|80.0%|3|0|0|0|23|100%|NORMAL|(weight=2.475, query_type in (SELECT), source_ip=192.168.6.1/24)\n" +
-                "rg3|32|80.0%|3|0|0|0|23|100%|NORMAL|(weight=1.1, query_type in (SELECT))\n" +
-                "rg4|13|41.0%|null|1024|1024|1024|23|100%|NORMAL|(weight=1.375, source_ip=192.168.7.1/24)\n" +
-                "rg5|25|80.0%|null|0|0|0|10|100%|NORMAL|(weight=10.0, db='db1')\n" +
-                "rg6|32|80.0%|null|0|0|0|10|100%|NORMAL|(weight=2.475, query_type in (INSERT), source_ip=192.168.6.1/24)\n" +
-                "rg7|32|80.0%|null|0|0|0|10|30.0%|NORMAL|(weight=2.475, query_type in (SELECT), source_ip=192.168.6.1/24)\n" +
-                "rt_rg1|25|80.0%|null|0|0|0|10|100%|SHORT_QUERY|(weight=1.0, user=rt_rg_user)";
+                "rg1|21|0|20.0%|4|0|0|0|11|100%|NORMAL|(weight=4.475, user=rg1_user1, role=rg1_role1, query_type in (SELECT), source_ip=192.168.2.1/24)\n" +
+                "rg1|21|0|20.0%|4|0|0|0|11|100%|NORMAL|(weight=3.475, user=rg1_user2, query_type in (SELECT), source_ip=192.168.3.1/24)\n" +
+                "rg1|21|0|20.0%|4|0|0|0|11|100%|NORMAL|(weight=2.375, user=rg1_user3, source_ip=192.168.4.1/24)\n" +
+                "rg1|21|0|20.0%|4|0|0|0|11|100%|NORMAL|(weight=1.0, user=rg1_user4)\n" +
+                "rg2|30|0|37.0%|null|0|0|0|20|100%|NORMAL|(weight=3.475, role=rg2_role1, query_type in (SELECT), source_ip=192.168.5.1/24)\n" +
+                "rg2|30|0|37.0%|null|0|0|0|20|100%|NORMAL|(weight=2.375, role=rg2_role2, source_ip=192.168.6.1/24)\n" +
+                "rg2|30|0|37.0%|null|0|0|0|20|100%|NORMAL|(weight=1.0, role=rg2_role3)\n" +
+                "rg3|32|0|80.0%|3|0|0|0|23|100%|NORMAL|(weight=2.475, query_type in (SELECT), source_ip=192.168.6.1/24)\n" +
+                "rg3|32|0|80.0%|3|0|0|0|23|100%|NORMAL|(weight=1.1, query_type in (SELECT))\n" +
+                "rg4|13|0|41.0%|null|1024|1024|1024|23|100%|NORMAL|(weight=1.375, source_ip=192.168.7.1/24)\n" +
+                "rg5|25|0|80.0%|null|0|0|0|10|100%|NORMAL|(weight=10.0, db='db1')\n" +
+                "rg6|32|0|80.0%|null|0|0|0|10|100%|NORMAL|(weight=2.475, query_type in (INSERT), source_ip=192.168.6.1/24)\n" +
+                "rg7|32|0|80.0%|null|0|0|0|10|30%|NORMAL|(weight=2.475, query_type in (SELECT), source_ip=192.168.6.1/24)\n" +
+                "rt_rg1|25|25|80.0%|null|0|0|0|10|100%|SHORT_QUERY|(weight=1.0, user=rt_rg_user)";
         Assert.assertEquals(expect, result);
         dropResourceGroups();
     }
@@ -773,7 +773,7 @@ public void testChooseShortQueryResourceGroup() throws Exception {
 
         // Prefer the short query group regardless its classifier weight is the lowest.
         String qualifiedUser = "rt_rg_user";
-        long dbId = GlobalStateMgr.getCurrentState().getDb("db1").getId();
+        long dbId = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db1").getId();
         Set<Long> dbs = ImmutableSet.of(dbId);
         starRocksAssert.getCtx().setQualifiedUser(qualifiedUser);
         starRocksAssert.getCtx().setCurrentUserIdentity(new UserIdentity(qualifiedUser, "%"));
@@ -873,9 +873,10 @@ public void testValidateMaxCpuCores() throws Exception {
         {
             String sql = String.format(createSQLTemplate, numCores);
             starRocksAssert.executeResourceGroupDdlSql(sql);
-            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource group rg_valid_max_cpu_cores");
+            List<List<String>> rows =
+                    starRocksAssert.executeResourceGroupShowSql("show verbose resource group rg_valid_max_cpu_cores");
             String actual = rowsToString(rows);
-            String expect = "rg_valid_max_cpu_cores|32|20.0%|17|0|0|0|11|100%|NORMAL|(weight=1.0, user=rg1_if_not_exists)";
+            String expect = "rg_valid_max_cpu_cores|32|0|20.0%|17|0|0|0|11|100%|NORMAL|(weight=1.0, user=rg1_if_not_exists)";
             Assert.assertEquals(expect, actual);
             starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg_valid_max_cpu_cores");
         }
@@ -883,9 +884,10 @@ public void testValidateMaxCpuCores() throws Exception {
         {
             String sql = String.format(createSQLTemplate, numCores - 1);
             starRocksAssert.executeResourceGroupDdlSql(sql);
-            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource group rg_valid_max_cpu_cores");
+            List<List<String>> rows =
+                    starRocksAssert.executeResourceGroupShowSql("show verbose resource group rg_valid_max_cpu_cores");
             String actual = rowsToString(rows);
-            String expect = "rg_valid_max_cpu_cores|31|20.0%|17|0|0|0|11|100%|NORMAL|(weight=1.0, user=rg1_if_not_exists)";
+            String expect = "rg_valid_max_cpu_cores|31|0|20.0%|17|0|0|0|11|100%|NORMAL|(weight=1.0, user=rg1_if_not_exists)";
             Assert.assertEquals(expect, actual);
         }
 
@@ -906,18 +908,20 @@ public void testValidateMaxCpuCores() throws Exception {
         {
             String sql = String.format(alterSQLTemplate, numCores);
             starRocksAssert.executeResourceGroupDdlSql(sql);
-            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource group rg_valid_max_cpu_cores");
+            List<List<String>> rows =
+                    starRocksAssert.executeResourceGroupShowSql("show verbose resource group rg_valid_max_cpu_cores");
             String actual = rowsToString(rows);
-            String expect = "rg_valid_max_cpu_cores|31|20.0%|32|0|0|0|11|100%|NORMAL|(weight=1.0, user=rg1_if_not_exists)";
+            String expect = "rg_valid_max_cpu_cores|31|0|20.0%|32|0|0|0|11|100%|NORMAL|(weight=1.0, user=rg1_if_not_exists)";
             Assert.assertEquals(expect, actual);
         }
 
         {
             String sql = String.format(alterSQLTemplate, numCores - 2);
             starRocksAssert.executeResourceGroupDdlSql(sql);
-            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource group rg_valid_max_cpu_cores");
+            List<List<String>> rows =
+                    starRocksAssert.executeResourceGroupShowSql("show verbose resource group rg_valid_max_cpu_cores");
             String actual = rowsToString(rows);
-            String expect = "rg_valid_max_cpu_cores|31|20.0%|30|0|0|0|11|100%|NORMAL|(weight=1.0, user=rg1_if_not_exists)";
+            String expect = "rg_valid_max_cpu_cores|31|0|20.0%|30|0|0|0|11|100%|NORMAL|(weight=1.0, user=rg1_if_not_exists)";
             Assert.assertEquals(expect, actual);
         }
 
@@ -1032,22 +1036,23 @@ public TestCase(String planCpuCostRange, String planMemCostRange, String expecte
 
         List<TestCase> testCases = ImmutableList.of(
                 new TestCase("[1.12345678901234567,10.2)", "[2, 100.2)",
-                        "rg_valid_plan_cost_range|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_if_not_exists, plan_cpu_cost_range=[1.1234567890123457, 10.2), plan_mem_cost_range=[2.0, 100.2))"),
+                        "rg_valid_plan_cost_range|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_if_not_exists, plan_cpu_cost_range=[1.1234567890123457, 10.2), plan_mem_cost_range=[2.0, 100.2))"),
                 new TestCase("[1.1,10.2)", "[2, 100.2)",
-                        "rg_valid_plan_cost_range|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_if_not_exists, plan_cpu_cost_range=[1.1, 10.2), plan_mem_cost_range=[2.0, 100.2))"),
+                        "rg_valid_plan_cost_range|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_if_not_exists, plan_cpu_cost_range=[1.1, 10.2), plan_mem_cost_range=[2.0, 100.2))"),
 
                 new TestCase("[-1,10)", "[2, 100)",
-                        "rg_valid_plan_cost_range|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_if_not_exists, plan_cpu_cost_range=[-1.0, 10.0), plan_mem_cost_range=[2.0, 100.0))"),
+                        "rg_valid_plan_cost_range|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_if_not_exists, plan_cpu_cost_range=[-1.0, 10.0), plan_mem_cost_range=[2.0, 100.0))"),
                 new TestCase("[0, 10)", "[0, 100)",
-                        "rg_valid_plan_cost_range|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_if_not_exists, plan_cpu_cost_range=[0.0, 10.0), plan_mem_cost_range=[0.0, 100.0))"),
+                        "rg_valid_plan_cost_range|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_if_not_exists, plan_cpu_cost_range=[0.0, 10.0), plan_mem_cost_range=[0.0, 100.0))"),
                 new TestCase(" [ 0,  10) ", "  [ 0,  100  )  ",
-                        "rg_valid_plan_cost_range|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_if_not_exists, plan_cpu_cost_range=[0.0, 10.0), plan_mem_cost_range=[0.0, 100.0))")
+                        "rg_valid_plan_cost_range|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_if_not_exists, plan_cpu_cost_range=[0.0, 10.0), plan_mem_cost_range=[0.0, 100.0))")
         );
         for (TestCase c : testCases) {
             String createSQL = String.format(createSQLTemplate, c.planCpuCostRange, c.PlanMemCostRange);
             starRocksAssert.executeResourceGroupDdlSql(createSQL);
 
-            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource group rg_valid_plan_cost_range");
+            List<List<String>> rows =
+                    starRocksAssert.executeResourceGroupShowSql("show verbose resource group rg_valid_plan_cost_range");
             String actual = rowsToString(rows);
             Assert.assertEquals(c.expectedOutput, actual);
 
@@ -1088,21 +1093,21 @@ public TestCase(String planCpuCostRange, String planMemCostRange, String expecte
 
         List<TestCase> testCases = ImmutableList.of(
                 new TestCase("[1.12345678901234567,10.2)", "[2, 100.2)",
-                        "rg_valid_plan_cost_range|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[100.0, 1000.0), plan_mem_cost_range=[0.0, 100.0))\n" +
-                                "rg_valid_plan_cost_range|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[1.1234567890123457, 10.2), plan_mem_cost_range=[2.0, 100.2))"),
+                        "rg_valid_plan_cost_range|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[100.0, 1000.0), plan_mem_cost_range=[0.0, 100.0))\n" +
+                                "rg_valid_plan_cost_range|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[1.1234567890123457, 10.2), plan_mem_cost_range=[2.0, 100.2))"),
                 new TestCase("[1.1,10.2)", "[2, 100.2)",
-                        "rg_valid_plan_cost_range|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[100.0, 1000.0), plan_mem_cost_range=[0.0, 100.0))\n" +
-                                "rg_valid_plan_cost_range|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[1.1, 10.2), plan_mem_cost_range=[2.0, 100.2))"),
+                        "rg_valid_plan_cost_range|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[100.0, 1000.0), plan_mem_cost_range=[0.0, 100.0))\n" +
+                                "rg_valid_plan_cost_range|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[1.1, 10.2), plan_mem_cost_range=[2.0, 100.2))"),
 
                 new TestCase("[-1,10)", "[2, 100)",
-                        "rg_valid_plan_cost_range|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[100.0, 1000.0), plan_mem_cost_range=[0.0, 100.0))\n" +
-                                "rg_valid_plan_cost_range|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[-1.0, 10.0), plan_mem_cost_range=[2.0, 100.0))"),
+                        "rg_valid_plan_cost_range|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[100.0, 1000.0), plan_mem_cost_range=[0.0, 100.0))\n" +
+                                "rg_valid_plan_cost_range|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[-1.0, 10.0), plan_mem_cost_range=[2.0, 100.0))"),
                 new TestCase("[0, 10)", "[0, 100)",
-                        "rg_valid_plan_cost_range|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[100.0, 1000.0), plan_mem_cost_range=[0.0, 100.0))\n" +
-                                "rg_valid_plan_cost_range|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[0.0, 10.0), plan_mem_cost_range=[0.0, 100.0))"),
+                        "rg_valid_plan_cost_range|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[100.0, 1000.0), plan_mem_cost_range=[0.0, 100.0))\n" +
+                                "rg_valid_plan_cost_range|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[0.0, 10.0), plan_mem_cost_range=[0.0, 100.0))"),
                 new TestCase(" [ 0,  10) ", "  [ 0,  100  )  ",
-                        "rg_valid_plan_cost_range|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[100.0, 1000.0), plan_mem_cost_range=[0.0, 100.0))\n" +
-                                "rg_valid_plan_cost_range|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[0.0, 10.0), plan_mem_cost_range=[0.0, 100.0))")
+                        "rg_valid_plan_cost_range|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[100.0, 1000.0), plan_mem_cost_range=[0.0, 100.0))\n" +
+                                "rg_valid_plan_cost_range|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[0.0, 10.0), plan_mem_cost_range=[0.0, 100.0))")
         );
         for (TestCase c : testCases) {
             starRocksAssert.executeResourceGroupDdlSql(createSQL);
@@ -1110,7 +1115,8 @@ public TestCase(String planCpuCostRange, String planMemCostRange, String expecte
             String alterSQL = String.format(alterTemplate, c.planCpuCostRange, c.PlanMemCostRange);
             starRocksAssert.executeResourceGroupDdlSql(alterSQL);
 
-            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource group rg_valid_plan_cost_range");
+            List<List<String>> rows =
+                    starRocksAssert.executeResourceGroupShowSql("show verbose resource group rg_valid_plan_cost_range");
             String actual = rowsToString(rows);
             Assert.assertEquals(c.expectedOutput, actual);
 
@@ -1259,13 +1265,13 @@ public void testSerializeAndDeserialize() throws Exception {
                 "   'type' = 'normal'" +
                 "   );";
         String showResult =
-                "rg1|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[1.0, 2.0), plan_mem_cost_range=[-100.0, 1000.0))\n" +
-                        "rg2|32|30.0%|null|0|0|0|31|100%|NORMAL|(weight=2.0, user=rg1_user, plan_mem_cost_range=[0.0, 2000.0))";
+                "rg1|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=3.0, user=rg1_user, plan_cpu_cost_range=[1.0, 2.0), plan_mem_cost_range=[-100.0, 1000.0))\n" +
+                        "rg2|32|0|30.0%|null|0|0|0|31|100%|NORMAL|(weight=2.0, user=rg1_user, plan_mem_cost_range=[0.0, 2000.0))";
 
         starRocksAssert.executeResourceGroupDdlSql(createSQL1);
         starRocksAssert.executeResourceGroupDdlSql(createSQL2);
         {
-            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource groups all");
             String actual = rowsToString(rows);
             Assert.assertEquals(showResult, actual);
         }
@@ -1278,7 +1284,7 @@ public void testSerializeAndDeserialize() throws Exception {
 
             starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg1");
             starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg2");
-            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource groups all");
             Assert.assertTrue(rows.isEmpty());
 
             try (ByteArrayInputStream bufferInput = new ByteArrayInputStream(bufferOutput.toByteArray());
@@ -1287,7 +1293,7 @@ public void testSerializeAndDeserialize() throws Exception {
             }
         }
         {
-            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource groups all");
             String actual = rowsToString(rows);
             Assert.assertEquals(showResult, actual);
         }
@@ -1353,12 +1359,12 @@ public void testClassifierOnlyWithPlanCost() throws Exception {
         starRocksAssert.executeResourceGroupDdlSql(createSQL2);
         starRocksAssert.executeResourceGroupDdlSql(createSQL3);
 
-        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource groups all");
         String actual = rowsToString(rows);
         String expected =
-                "rg1|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=2.0, plan_cpu_cost_range=[11.0, 12.0), plan_mem_cost_range=[-100.0, 11000.0))\n" +
-                        "rg2|16|20.0%|null|0|0|0|11|100%|NORMAL|(weight=1.0, plan_cpu_cost_range=[21.0, 22.0))\n" +
-                        "rg3|17|20.0%|null|0|0|0|11|100%|NORMAL|(weight=1.0, plan_mem_cost_range=[-100.0, 31000.0))";
+                "rg1|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=2.0, plan_cpu_cost_range=[11.0, 12.0), plan_mem_cost_range=[-100.0, 11000.0))\n" +
+                        "rg2|16|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=1.0, plan_cpu_cost_range=[21.0, 22.0))\n" +
+                        "rg3|17|0|20.0%|null|0|0|0|11|100%|NORMAL|(weight=1.0, plan_mem_cost_range=[-100.0, 31000.0))";
         Assert.assertEquals(expected, actual);
 
         starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg1");
@@ -1385,10 +1391,343 @@ public void testSourceIP() throws Exception {
                 "    'mem_limit' = '20%'\n" +
                 ");";
         starRocksAssert.executeResourceGroupDdlSql(createSQL);
-        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show verbose resource groups all");
         assertThat(rowsToString(rows)).isEqualTo(
-                "rg1|10|20.0%|8|0|0|0|null|100%|NORMAL|(weight=1.5, source_ip=192.168.2.1/32)");
+                "rg1|10|0|20.0%|8|0|0|0|null|100%|NORMAL|(weight=1.5, source_ip=192.168.2.1/32)");
+
+        starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg1");
+    }
+
+    @Test
+    public void testGetDedicateCpuCores() throws Exception {
+        starRocksAssert.executeResourceGroupDdlSql("CREATE RESOURCE GROUP rg1\n" +
+                "TO (user='rg1_user')\n" +
+                "WITH (" +
+                "   'mem_limit' = '20%'," +
+                "   'cpu_weight' = '17'" +
+                ");");
+        starRocksAssert.executeResourceGroupDdlSql("CREATE RESOURCE GROUP rg2\n" +
+                "TO (user='rg2_user')\n" +
+                "WITH (" +
+                "   'mem_limit' = '20%'," +
+                "   'dedicated_cpu_cores' = '16'" +
+                ");");
+        starRocksAssert.executeResourceGroupDdlSql("CREATE RESOURCE GROUP rt_rg1\n" +
+                "TO (user='rt_rg1_user')\n" +
+                "WITH (" +
+                "   'mem_limit' = '20%'," +
+                "   'cpu_weight' = '15'," +
+                "   'type' = 'short_query'" +
+                ");");
+
+        List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+        assertThat(rowsToString(rows)).isEqualTo("rg1|17|0|20.0%|0|0|0|null|100%|(weight=1.0, user=rg1_user)\n" +
+                "rg2|null|16|20.0%|0|0|0|null|100%|(weight=1.0, user=rg2_user)\n" +
+                "rt_rg1|15|15|20.0%|0|0|0|null|100%|(weight=1.0, user=rt_rg1_user)");
+
+        starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg1");
+        starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg2");
+        starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rt_rg1");
+    }
+
+    @Test
+    public void testValidateCpuParametersForCreate() throws Exception {
+        {
+            String sql = "CREATE RESOURCE GROUP rg1\n" +
+                    "TO (user='rg1_user')\n" +
+                    "WITH (" +
+                    "   'mem_limit' = '20%'," +
+                    "   'cpu_weight' = '17'," +
+                    "   'dedicated_cpu_cores' = '17'" +
+                    ");";
+            Assert.assertThrows("property 'cpu_weight' and 'dedicated_cpu_cores' cannot be present and positive at the same time",
+                    SemanticException.class,
+                    () -> starRocksAssert.executeResourceGroupDdlSql(sql));
+        }
+
+        {
+            String sql = "CREATE RESOURCE GROUP rg1\n" +
+                    "TO (user='rg1_user')\n" +
+                    "WITH (" +
+                    "   'mem_limit' = '20%'," +
+                    "   'cpu_weight' = '0'," +
+                    "   'dedicated_cpu_cores' = '0'" +
+                    ");";
+            Assert.assertThrows("property 'cpu_weight' or 'dedicated_cpu_cores' must be positive",
+                    SemanticException.class,
+                    () -> starRocksAssert.executeResourceGroupDdlSql(sql));
+        }
+
+        {
+            String sql = "CREATE RESOURCE GROUP rg1\n" +
+                    "TO (user='rg1_user')\n" +
+                    "WITH (" +
+                    "   'mem_limit' = '20%'" +
+                    ");";
+            Assert.assertThrows("property 'cpu_weight' or 'dedicated_cpu_cores' must be positive",
+                    SemanticException.class,
+                    () -> starRocksAssert.executeResourceGroupDdlSql(sql));
+        }
+
+        {
+            String sql = "CREATE RESOURCE GROUP rg1\n" +
+                    "TO (user='rg1_user')\n" +
+                    "WITH (" +
+                    "   'mem_limit' = '20%'," +
+                    "   'dedicated_cpu_cores' = '32'" +
+                    ");";
+            Assert.assertThrows("dedicated_cpu_cores should range from 0 to 31",
+                    SemanticException.class,
+                    () -> starRocksAssert.executeResourceGroupDdlSql(sql));
+        }
+
+        {
+            String sql = "CREATE RESOURCE GROUP rg1\n" +
+                    "TO (user='rg1_user')\n" +
+                    "WITH (" +
+                    "   'mem_limit' = '20%'," +
+                    "   'cpu_weight' = '17'," +
+                    "   'dedicated_cpu_cores' = '0'" +
+                    ");";
+            starRocksAssert.executeResourceGroupDdlSql(sql);
+            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+            assertThat(rowsToString(rows)).isEqualTo("rg1|17|0|20.0%|0|0|0|null|100%|(weight=1.0, user=rg1_user)");
+            starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg1");
+        }
+
+        {
+            String sql = "CREATE RESOURCE GROUP rg1\n" +
+                    "TO (user='rg1_user')\n" +
+                    "WITH (" +
+                    "   'mem_limit' = '20%'," +
+                    "   'cpu_weight' = '17'" +
+                    ");";
+            starRocksAssert.executeResourceGroupDdlSql(sql);
+            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+            assertThat(rowsToString(rows)).isEqualTo("rg1|17|0|20.0%|0|0|0|null|100%|(weight=1.0, user=rg1_user)");
+            starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg1");
+        }
+
+        {
+            String sql = "CREATE RESOURCE GROUP rg1\n" +
+                    "TO (user='rg1_user')\n" +
+                    "WITH (" +
+                    "   'mem_limit' = '20%'," +
+                    "   'cpu_weight' = '0'," +
+                    "   'dedicated_cpu_cores' = '17'" +
+                    ");";
+            starRocksAssert.executeResourceGroupDdlSql(sql);
+            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+            assertThat(rowsToString(rows)).isEqualTo("rg1|0|17|20.0%|0|0|0|null|100%|(weight=1.0, user=rg1_user)");
+            starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg1");
+        }
+
+        {
+            String sql = "CREATE RESOURCE GROUP rg1\n" +
+                    "TO (user='rg1_user')\n" +
+                    "WITH (" +
+                    "   'mem_limit' = '20%'," +
+                    "   'dedicated_cpu_cores' = '17'" +
+                    ");";
+            starRocksAssert.executeResourceGroupDdlSql(sql);
+            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+            assertThat(rowsToString(rows)).isEqualTo("rg1|null|17|20.0%|0|0|0|null|100%|(weight=1.0, user=rg1_user)");
+            starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg1");
+        }
+    }
+
+    @Test
+    public void testValidateCpuParametersForAlter() throws Exception {
+        {
+            String sql = "CREATE RESOURCE GROUP rg1\n" +
+                    "TO (user='rg1_user')\n" +
+                    "WITH (" +
+                    "   'mem_limit' = '20%'," +
+                    "   'cpu_weight' = '17'" +
+                    ");";
+            starRocksAssert.executeResourceGroupDdlSql(sql);
+            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+            assertThat(rowsToString(rows)).isEqualTo("rg1|17|0|20.0%|0|0|0|null|100%|(weight=1.0, user=rg1_user)");
+        }
+
+        {
+            String sql = "ALTER resource group rg1 \n" +
+                    "WITH (\n" +
+                    "   'cpu_weight' = '16'," +
+                    "   'dedicated_cpu_cores' = '15'" +
+                    ")";
+            Assert.assertThrows("property 'cpu_weight' and 'dedicated_cpu_cores' cannot be present and positive at the same time",
+                    SemanticException.class,
+                    () -> starRocksAssert.executeResourceGroupDdlSql(sql));
+        }
+
+        {
+            String sql = "ALTER resource group rg1 \n" +
+                    "WITH (\n" +
+                    "   'dedicated_cpu_cores' = '15'" +
+                    ")";
+            Assert.assertThrows("property 'cpu_weight' and 'dedicated_cpu_cores' cannot be present and positive at the same time",
+                    SemanticException.class,
+                    () -> starRocksAssert.executeResourceGroupDdlSql(sql));
+        }
+
+        {
+
+            String sql = "ALTER resource group rg1 \n" +
+                    "WITH (\n" +
+                    "   'cpu_weight' = '0'," +
+                    "   'dedicated_cpu_cores' = '0'" +
+                    ")";
+            Assert.assertThrows("property 'cpu_weight' or 'dedicated_cpu_cores' must be positive",
+                    SemanticException.class,
+                    () -> starRocksAssert.executeResourceGroupDdlSql(sql));
+        }
+
+        {
+
+            String sql = "ALTER resource group rg1 \n" +
+                    "WITH (\n" +
+                    "   'cpu_weight' = '0'" +
+                    ")";
+            Assert.assertThrows("property 'cpu_weight' or 'dedicated_cpu_cores' must be positive",
+                    SemanticException.class,
+                    () -> starRocksAssert.executeResourceGroupDdlSql(sql));
+        }
+
+        {
+            String sql = "ALTER resource group rg1 \n" +
+                    "WITH (\n" +
+                    "   'cpu_weight' = '0'," +
+                    "   'dedicated_cpu_cores' = '32'" +
+                    ")";
+            Assert.assertThrows("dedicated_cpu_cores should range from 0 to 31",
+                    SemanticException.class,
+                    () -> starRocksAssert.executeResourceGroupDdlSql(sql));
+        }
+
+        {
+            String sql = "ALTER resource group rg1 \n" +
+                    "WITH (\n" +
+                    "   'cpu_weight' = '0'," +
+                    "   'dedicated_cpu_cores' = '16'" +
+                    ")";
+            starRocksAssert.executeResourceGroupDdlSql(sql);
+            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+            assertThat(rowsToString(rows)).isEqualTo("rg1|0|16|20.0%|0|0|0|null|100%|(weight=1.0, user=rg1_user)");
+        }
+
+        {
+            String sql = "ALTER resource group rg1 \n" +
+                    "WITH (\n" +
+                    "   'cpu_weight' = '15'," +
+                    "   'dedicated_cpu_cores' = '0'" +
+                    ")";
+            starRocksAssert.executeResourceGroupDdlSql(sql);
+            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+            assertThat(rowsToString(rows)).isEqualTo("rg1|15|0|20.0%|0|0|0|null|100%|(weight=1.0, user=rg1_user)");
+        }
 
         starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg1");
     }
+
+    @Test
+    public void testValidateDedicatedCpuCoresWithShortQuery() throws Exception {
+        {
+            String sql = "CREATE RESOURCE GROUP rg1\n" +
+                    "TO (user='rg1_user')\n" +
+                    "WITH (" +
+                    "   'mem_limit' = '20%'," +
+                    "   'dedicated_cpu_cores' = '17'," +
+                    "   'type' = 'short_query'" +
+                    ");";
+            Assert.assertThrows(
+                    "'short_query' ResourceGroup cannot set 'dedicated_cpu_cores', since it use 'cpu_weight' as 'dedicated_cpu_cores'",
+                    SemanticException.class,
+                    () -> starRocksAssert.executeResourceGroupDdlSql(sql));
+        }
+
+        {
+            starRocksAssert.executeResourceGroupDdlSql("CREATE RESOURCE GROUP rg1\n" +
+                    "TO (user='rg1_user')\n" +
+                    "WITH (" +
+                    "   'mem_limit' = '20%'," +
+                    "   'cpu_weight' = '17'," +
+                    "   'type' = 'short_query'" +
+                    ");");
+            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+            assertThat(rowsToString(rows)).isEqualTo("rg1|17|17|20.0%|0|0|0|null|100%|(weight=1.0, user=rg1_user)");
+
+            String sql = "ALTER resource group rg1 \n" +
+                    "WITH (\n" +
+                    "   'dedicated_cpu_cores' = '16'" +
+                    ")";
+            Assert.assertThrows(
+                    "'short_query' ResourceGroup cannot set 'dedicated_cpu_cores', since it use 'cpu_weight' as 'dedicated_cpu_cores'",
+                    SemanticException.class,
+                    () -> starRocksAssert.executeResourceGroupDdlSql(sql));
+
+            starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg1");
+        }
+    }
+
+
+    @Test
+    public void testValidateSumDedicatedCpuCores() throws Exception {
+        {
+            starRocksAssert.executeResourceGroupDdlSql("CREATE RESOURCE GROUP rg1\n" +
+                    "TO (user='rg1_user')\n" +
+                    "WITH (" +
+                    "   'mem_limit' = '20%'," +
+                    "   'dedicated_cpu_cores' = '16'" +
+                    ");");
+            starRocksAssert.executeResourceGroupDdlSql("CREATE RESOURCE GROUP rg2\n" +
+                    "TO (user='rg2_user')\n" +
+                    "WITH (" +
+                    "   'mem_limit' = '20%'," +
+                    "   'dedicated_cpu_cores' = '15'" +
+                    ");");
+            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+            assertThat(rowsToString(rows)).isEqualTo("rg1|null|16|20.0%|0|0|0|null|100%|(weight=1.0, user=rg1_user)\n" +
+                    "rg2|null|15|20.0%|0|0|0|null|100%|(weight=1.0, user=rg2_user)");
+        }
+
+        {
+            String sql = "ALTER resource group rg1 \n" +
+                    "WITH (\n" +
+                    "   'dedicated_cpu_cores' = '17'" +
+                    ")";
+            Assert.assertThrows(
+                    "the sum of dedicated_cpu_cores of all the resource groups cannot exceed 31",
+                    DdlException.class,
+                    () -> starRocksAssert.executeResourceGroupDdlSql(sql));
+        }
+
+        {
+            String sql = "ALTER resource group rg1 \n" +
+                    "WITH (\n" +
+                    "   'dedicated_cpu_cores' = '14'" +
+                    ")";
+            starRocksAssert.executeResourceGroupDdlSql(sql);
+            List<List<String>> rows = starRocksAssert.executeResourceGroupShowSql("show resource groups all");
+            assertThat(rowsToString(rows)).isEqualTo("rg1|null|14|20.0%|0|0|0|null|100%|(weight=1.0, user=rg1_user)\n" +
+                    "rg2|null|15|20.0%|0|0|0|null|100%|(weight=1.0, user=rg2_user)");
+        }
+
+        {
+            String sql = "CREATE RESOURCE GROUP rg3\n" +
+                    "TO (user='rg1_user')\n" +
+                    "WITH (" +
+                    "   'mem_limit' = '20%'," +
+                    "   'dedicated_cpu_cores' = '3'" +
+                    ");";
+            Assert.assertThrows(
+                    "the sum of dedicated_cpu_cores of all the resource groups cannot exceed 31",
+                    DdlException.class,
+                    () -> starRocksAssert.executeResourceGroupDdlSql(sql));
+        }
+
+        starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg1");
+        starRocksAssert.executeResourceGroupDdlSql("DROP RESOURCE GROUP rg2");
+    }
+
 }
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/SelectStmtTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/SelectStmtTest.java
index 6b074a0083b0bc..b704e21c8731cf 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/SelectStmtTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/SelectStmtTest.java
@@ -370,27 +370,26 @@ void testGroupByCountDistinctArrayWithSkewHint() throws Exception {
         String sql =
                 "select b1, count(distinct [skew] a1) as cnt from (select split('a,b,c', ',') as a1, 'aaa' as b1) t1 group by b1";
         String s = starRocksAssert.query(sql).explainQuery();
-        Assert.assertTrue(s, s.contains("PLAN FRAGMENT 0\n" +
-                " OUTPUT EXPRS:3: expr | 4: count\n" +
+        Assert.assertTrue(s, s.contains("OUTPUT EXPRS:4: b1 | 6: count\n" +
                 "  PARTITION: UNPARTITIONED\n" +
                 "\n" +
                 "  RESULT SINK\n" +
                 "\n" +
                 "  4:AGGREGATE (merge finalize)\n" +
-                "  |  output: count(4: count)\n" +
-                "  |  group by: 3: expr\n" +
+                "  |  output: count(6: count)\n" +
+                "  |  group by: 4: b1\n" +
                 "  |  \n" +
                 "  3:AGGREGATE (update serialize)\n" +
                 "  |  STREAMING\n" +
-                "  |  output: count(2: split)\n" +
-                "  |  group by: 3: expr\n" +
+                "  |  output: count(5: a1)\n" +
+                "  |  group by: 4: b1\n" +
                 "  |  \n" +
                 "  2:AGGREGATE (update serialize)\n" +
-                "  |  group by: 2: split, 3: expr\n" +
+                "  |  group by: 4: b1, 5: a1\n" +
                 "  |  \n" +
                 "  1:Project\n" +
-                "  |  <slot 2> : split('a,b,c', ',')\n" +
-                "  |  <slot 3> : 'aaa'\n" +
+                "  |  <slot 4> : 'aaa'\n" +
+                "  |  <slot 5> : split('a,b,c', ',')\n" +
                 "  |  \n" +
                 "  0:UNION\n" +
                 "     constant exprs: \n" +
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/ShowCreateMaterializedViewStmtTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/ShowCreateMaterializedViewStmtTest.java
index ffa12d054d7b87..20f9e51633af96 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/ShowCreateMaterializedViewStmtTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/ShowCreateMaterializedViewStmtTest.java
@@ -97,7 +97,7 @@ public void testShowInternalCatalogConstraints() throws Exception {
         StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(createMvSql, ctx);
         GlobalStateMgr currentState = GlobalStateMgr.getCurrentState();
         currentState.getLocalMetastore().createMaterializedView((CreateMaterializedViewStatement) statementBase);
-        Table table = currentState.getDb("test").getTable("mv9");
+        Table table = currentState.getLocalMetastore().getDb("test").getTable("mv9");
         List<String> createTableStmt = Lists.newArrayList();
         AstToStringBuilder.getDdlStmt(table, createTableStmt, null, null, false, true);
         Assert.assertEquals("CREATE MATERIALIZED VIEW `mv9` (`k1`, `k2`)\n" +
@@ -125,7 +125,7 @@ public void testShowExternalCatalogConstraints() throws Exception {
         StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(createMvSql, ctx);
         GlobalStateMgr currentState = GlobalStateMgr.getCurrentState();
         currentState.getLocalMetastore().createMaterializedView((CreateMaterializedViewStatement) statementBase);
-        Table table = currentState.getDb("test").getTable("mv10");
+        Table table = currentState.getLocalMetastore().getDb("test").getTable("mv10");
         List<String> createTableStmt = Lists.newArrayList();
         AstToStringBuilder.getDdlStmt(table, createTableStmt, null, null, false, true);
         Assert.assertEquals("CREATE MATERIALIZED VIEW `mv10` (`c1`, `c2`)\n" +
@@ -154,7 +154,7 @@ public void testShowExternalTableCreateMvSql() throws Exception {
         StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(createMvSql, ctx);
         GlobalStateMgr currentState = GlobalStateMgr.getCurrentState();
         currentState.getLocalMetastore().createMaterializedView((CreateMaterializedViewStatement) statementBase);
-        Table table = currentState.getDb("test").getTable("mv8");
+        Table table = currentState.getLocalMetastore().getDb("test").getTable("mv8");
         List<String> createTableStmt = Lists.newArrayList();
         AstToStringBuilder.getDdlStmt(table, createTableStmt, null, null, false, true);
         Assert.assertEquals(createTableStmt.get(0),
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/ShowCreateViewStmtTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/ShowCreateViewStmtTest.java
index aac41a7ecca84b..dde731d6f8ac85 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/ShowCreateViewStmtTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/ShowCreateViewStmtTest.java
@@ -189,14 +189,14 @@ public void testCreateView() throws Exception {
             CreateViewStmt createViewStmt = (CreateViewStmt) UtFrameUtils.parseStmtWithNewParser(testcase[1], ctx);
             GlobalStateMgr.getCurrentState().getLocalMetastore().createView(createViewStmt);
 
-            List<Table> views = GlobalStateMgr.getCurrentState().getDb(createViewStmt.getDbName()).getViews();
+            List<Table> views = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(createViewStmt.getDbName()).getViews();
             List<String> res = Lists.newArrayList();
             AstToStringBuilder.getDdlStmt(createViewStmt.getDbName(), views.get(0), res,
                     null, null, false, false, false);
 
             Assert.assertEquals(testcase[2], res.get(0));
 
-            GlobalStateMgr.getCurrentState().getDb(createViewStmt.getDbName()).dropTable(createViewStmt.getTable());
+            GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(createViewStmt.getDbName()).dropTable(createViewStmt.getTable());
         }
     }
 
@@ -208,7 +208,7 @@ public void testShowCreateView() throws Exception {
         CreateViewStmt createViewStmt = (CreateViewStmt) UtFrameUtils.parseStmtWithNewParser(createViewSql, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().createView(createViewStmt);
 
-        List<Table> views = GlobalStateMgr.getCurrentState().getDb(createViewStmt.getDbName()).getViews();
+        List<Table> views = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(createViewStmt.getDbName()).getViews();
         List<String> res = Lists.newArrayList();
         AstToStringBuilder.getDdlStmt(createViewStmt.getDbName(), views.get(0), res,
                 null, null, false, false, false);
@@ -276,7 +276,7 @@ public void testViewOfThreeUnionAllWithConstNullOutput() throws Exception {
 
     @Test
     public void testDdlComment() {
-        List<Table> tables = GlobalStateMgr.getCurrentState().getDb("test").getTables();
+        List<Table> tables = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTables();
         Table commentTest = tables.stream().filter(table -> table.getName().equals("comment_test")).findFirst().get();
         List<String> res = Lists.newArrayList();
         AstToStringBuilder.getDdlStmt("test", commentTest, res,
@@ -287,7 +287,7 @@ public void testDdlComment() {
 
     @Test
     public void testDdlStorageType() {
-        List<Table> tables = GlobalStateMgr.getCurrentState().getDb("test").getTables();
+        List<Table> tables = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTables();
         Table storageTest = tables.stream().filter(table -> table.getName().equals("storage_test")).findFirst().get();
         List<String> res = Lists.newArrayList();
         AstToStringBuilder.getDdlStmt("storage_test", storageTest, res,
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/ShowDbStmtTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/ShowDbStmtTest.java
index f5c1044a79c2aa..1a3656f419c592 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/ShowDbStmtTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/ShowDbStmtTest.java
@@ -19,7 +19,6 @@
 
 import com.google.common.collect.Lists;
 import com.starrocks.catalog.Database;
-import com.starrocks.common.jmockit.Deencapsulation;
 import com.starrocks.common.util.UUIDUtil;
 import com.starrocks.mysql.MysqlCommand;
 import com.starrocks.qe.ConnectContext;
@@ -51,33 +50,11 @@ public void setUp() throws Exception {
         Database db = new Database();
         new Expectations(db) {
             {
-                db.getTable(anyString);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), anyString);
                 minTimes = 0;
             }
         };
 
-        // mock globalStateMgr.
-        globalStateMgr = Deencapsulation.newInstance(GlobalStateMgr.class);
-        new Expectations(globalStateMgr) {
-            {
-                globalStateMgr.getDb("testCluster:testDb");
-                minTimes = 0;
-                result = db;
-
-                globalStateMgr.getDb("testCluster:emptyDb");
-                minTimes = 0;
-                result = null;
-
-                GlobalStateMgr.getCurrentState();
-                minTimes = 0;
-                result = globalStateMgr;
-
-                GlobalStateMgr.getCurrentState();
-                minTimes = 0;
-                result = globalStateMgr;
-            }
-        };
-
         // mock scheduler
         ConnectScheduler scheduler = new ConnectScheduler(10);
         new Expectations(scheduler) {
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/ShowDeleteTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/ShowDeleteTest.java
index 072fb2c827dac6..f77123e639b408 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/ShowDeleteTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/ShowDeleteTest.java
@@ -16,7 +16,6 @@
 
 import com.google.common.collect.Lists;
 import com.starrocks.catalog.Database;
-import com.starrocks.common.jmockit.Deencapsulation;
 import com.starrocks.common.util.UUIDUtil;
 import com.starrocks.mysql.MysqlCommand;
 import com.starrocks.qe.ConnectContext;
@@ -45,33 +44,11 @@ public void setUp() throws Exception {
         Database db = new Database();
         new Expectations(db) {
             {
-                db.getTable(anyString);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), anyString);
                 minTimes = 0;
             }
         };
 
-        // mock globalStateMgr.
-        globalStateMgr = Deencapsulation.newInstance(GlobalStateMgr.class);
-        new Expectations(globalStateMgr) {
-            {
-                globalStateMgr.getDb("testCluster:testDb");
-                minTimes = 0;
-                result = db;
-
-                globalStateMgr.getDb("testCluster:emptyDb");
-                minTimes = 0;
-                result = null;
-
-                GlobalStateMgr.getCurrentState();
-                minTimes = 0;
-                result = globalStateMgr;
-
-                GlobalStateMgr.getCurrentState();
-                minTimes = 0;
-                result = globalStateMgr;
-            }
-        };
-
         // mock scheduler
         ConnectScheduler scheduler = new ConnectScheduler(10);
         new Expectations(scheduler) {
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/ShowMaterializedViewTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/ShowMaterializedViewTest.java
index 4c13904e2201df..714e8f93edef09 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/ShowMaterializedViewTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/ShowMaterializedViewTest.java
@@ -115,9 +115,11 @@ public void testNormal() throws Exception {
                         "information_schema.materialized_views.TABLE_ROWS AS rows, " +
                         "information_schema.materialized_views.MATERIALIZED_VIEW_DEFINITION AS text, " +
                         "information_schema.materialized_views.extra_message AS extra_message, " +
-                        "information_schema.materialized_views.query_rewrite_status AS query_rewrite_status " +
+                        "information_schema.materialized_views.query_rewrite_status AS query_rewrite_status, " +
+                        "information_schema.materialized_views.creator AS creator " +
                         "FROM information_schema.materialized_views " +
-                        "WHERE (information_schema.materialized_views.TABLE_SCHEMA = 'abc') AND (information_schema.materialized_views.TABLE_NAME = 'mv1')",
+                        "WHERE (information_schema.materialized_views.TABLE_SCHEMA = 'abc') " +
+                        "AND (information_schema.materialized_views.TABLE_NAME = 'mv1')",
                 AstToStringBuilder.toString(stmt.toSelectStmt()));
         checkShowMaterializedViewsStmt(stmt);
     }
diff --git a/fe/fe-core/src/test/java/com/starrocks/analysis/UseMaterializedViewTest.java b/fe/fe-core/src/test/java/com/starrocks/analysis/UseMaterializedViewTest.java
index cf088eb1acb359..b41ec6fe4cb8a9 100644
--- a/fe/fe-core/src/test/java/com/starrocks/analysis/UseMaterializedViewTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/analysis/UseMaterializedViewTest.java
@@ -20,10 +20,9 @@
 import com.starrocks.catalog.MaterializedView;
 import com.starrocks.catalog.OlapTable;
 import com.starrocks.catalog.Table;
-import com.starrocks.common.Config;
-import com.starrocks.common.FeConstants;
 import com.starrocks.qe.ConnectContext;
 import com.starrocks.qe.StmtExecutor;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.analyzer.Field;
 import com.starrocks.sql.ast.QueryRelation;
 import com.starrocks.sql.ast.QueryStatement;
@@ -122,18 +121,18 @@ public void testSelect() {
     public void testDropMaterializedView() {
         String sql = "drop materialized view mv_to_drop";
         try {
-            Database database = starRocksAssert.getCtx().getGlobalStateMgr().getDb("test");
+            Database database = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb("test");
             Assert.assertTrue(database != null);
-            Table table = database.getTable("mv_to_drop");
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), "mv_to_drop");
             Assert.assertTrue(table != null);
             MaterializedView materializedView = (MaterializedView) table;
             long baseTableId = materializedView.getBaseTableInfos().iterator().next().getTableId();
-            OlapTable baseTable = ((OlapTable) database.getTable(baseTableId));
+            OlapTable baseTable = ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), baseTableId));
             Assert.assertEquals(2, baseTable.getRelatedMaterializedViews().size());
             StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
             StmtExecutor stmtExecutor = new StmtExecutor(connectContext, statementBase);
             stmtExecutor.execute();
-            table = database.getTable("mv_to_drop");
+            table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), "mv_to_drop");
             Assert.assertTrue(table == null);
             Assert.assertEquals(1, baseTable.getRelatedMaterializedViews().size());
         } catch (Exception e) {
diff --git a/fe/fe-core/src/test/java/com/starrocks/backup/BackupHandlerTest.java b/fe/fe-core/src/test/java/com/starrocks/backup/BackupHandlerTest.java
index 2be4d47dd3d078..8806b92658e2f9 100644
--- a/fe/fe-core/src/test/java/com/starrocks/backup/BackupHandlerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/backup/BackupHandlerTest.java
@@ -58,6 +58,7 @@
 import com.starrocks.qe.ConnectContext;
 import com.starrocks.qe.DDLStmtExecutor;
 import com.starrocks.server.GlobalStateMgr;
+import com.starrocks.server.LocalMetastore;
 import com.starrocks.sql.analyzer.BackupRestoreAnalyzer;
 import com.starrocks.sql.analyzer.SemanticException;
 import com.starrocks.sql.ast.BackupStmt;
@@ -119,8 +120,19 @@ public void setUpMocker(GlobalStateMgr globalStateMgr, BrokerMgr brokerMgr, Edit
 
         MetricRepo.init();
 
+        try {
+            db = CatalogMocker.mockDb();
+        } catch (AnalysisException e) {
+            e.printStackTrace();
+            Assert.fail();
+        }
+
         new Expectations() {
             {
+                GlobalStateMgr.getCurrentState();
+                minTimes = 0;
+                result = globalStateMgr;
+
                 globalStateMgr.getBrokerMgr();
                 minTimes = 0;
                 result = brokerMgr;
@@ -133,30 +145,11 @@ public void setUpMocker(GlobalStateMgr globalStateMgr, BrokerMgr brokerMgr, Edit
                 minTimes = 0;
                 result = editLog;
 
-                GlobalStateMgr.getCurrentState();
-                minTimes = 0;
-                result = globalStateMgr;
-
-                GlobalStateMgr.getCurrentState().getTabletInvertedIndex();
+                globalStateMgr.getTabletInvertedIndex();
                 minTimes = 0;
                 result = invertedIndex;
             }
         };
-
-        try {
-            db = CatalogMocker.mockDb();
-        } catch (AnalysisException e) {
-            e.printStackTrace();
-            Assert.fail();
-        }
-
-        new Expectations() {
-            {
-                globalStateMgr.getDb(anyString);
-                minTimes = 0;
-                result = db;
-            }
-        };
     }
 
     @After
@@ -164,8 +157,8 @@ public void done() {
         if (rootDir != null) {
             try {
                 Files.walk(Paths.get(Config.tmp_dir),
-                                FileVisitOption.FOLLOW_LINKS).sorted(Comparator.reverseOrder()).map(Path::toFile)
-                        .forEach(File::delete);
+                                        FileVisitOption.FOLLOW_LINKS).sorted(Comparator.reverseOrder()).map(Path::toFile)
+                            .forEach(File::delete);
             } catch (IOException e) {
                 // TODO Auto-generated catch block
                 e.printStackTrace();
@@ -176,7 +169,7 @@ public void done() {
     @Test
     public void testInit(@Mocked GlobalStateMgr globalStateMgr, @Mocked BrokerMgr brokerMgr, @Mocked EditLog editLog) {
         setUpMocker(globalStateMgr, brokerMgr, editLog);
-        handler = new BackupHandler(globalStateMgr);
+        BackupHandler handler = new BackupHandler(globalStateMgr);
         handler.runAfterCatalogReady();
 
         File backupDir = new File(BackupHandler.BACKUP_ROOT_DIR.toString());
@@ -185,7 +178,7 @@ public void testInit(@Mocked GlobalStateMgr globalStateMgr, @Mocked BrokerMgr br
 
     @Test
     public void testCreateAndDropRepository(
-            @Mocked GlobalStateMgr globalStateMgr, @Mocked BrokerMgr brokerMgr, @Mocked EditLog editLog) throws Exception {
+                @Mocked GlobalStateMgr globalStateMgr, @Mocked BrokerMgr brokerMgr, @Mocked EditLog editLog) throws Exception {
         setUpMocker(globalStateMgr, brokerMgr, editLog);
         new Expectations() {
             {
@@ -204,6 +197,10 @@ public void logDropRepository(String repoName) {
 
                     }
                 };
+
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
+                minTimes = 0;
+                result = db;
             }
         };
 
@@ -221,7 +218,8 @@ public Status listSnapshots(List<String> snapshotNames) {
 
             @Mock
             public Status getSnapshotInfoFile(String label, String backupTimestamp, List<BackupJobInfo> infos) {
-                OlapTable tbl = (OlapTable) db.getTable(CatalogMocker.TEST_TBL_NAME);
+                OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(db.getFullName(), CatalogMocker.TEST_TBL_NAME);
                 List<Table> tbls = Lists.newArrayList();
                 tbls.add(tbl);
                 Map<Long, SnapshotInfo> snapshotInfos = Maps.newHashMap();
@@ -230,15 +228,15 @@ public Status getSnapshotInfoFile(String label, String backupTimestamp, List<Bac
                         for (Tablet tablet : idx.getTablets()) {
                             List<String> files = Lists.newArrayList();
                             SnapshotInfo sinfo = new SnapshotInfo(db.getId(), tbl.getId(), part.getId(), idx.getId(),
-                                    tablet.getId(), -1, 0, "./path", files);
+                                        tablet.getId(), -1, 0, "./path", files);
                             snapshotInfos.put(tablet.getId(), sinfo);
                         }
                     }
                 }
 
                 BackupJobInfo info = BackupJobInfo.fromCatalog(System.currentTimeMillis(),
-                        "ss2", CatalogMocker.TEST_DB_NAME,
-                        CatalogMocker.TEST_DB_ID, tbls, snapshotInfos);
+                            "ss2", CatalogMocker.TEST_DB_NAME,
+                            CatalogMocker.TEST_DB_ID, tbls, snapshotInfos);
                 infos.add(info);
                 return Status.OK;
             }
@@ -252,10 +250,48 @@ public Status getSnapshotInfoFile(String label, String backupTimestamp, List<Bac
             }
         };
 
+        new Expectations() {
+            {
+                GlobalStateMgr.getCurrentState();
+                minTimes = 0;
+                result = globalStateMgr;
+
+                globalStateMgr.getBrokerMgr();
+                minTimes = 0;
+                result = brokerMgr;
+
+                globalStateMgr.getNextId();
+                minTimes = 0;
+                result = idGen++;
+
+                globalStateMgr.getEditLog();
+                minTimes = 0;
+                result = editLog;
+
+                globalStateMgr.getTabletInvertedIndex();
+                minTimes = 0;
+                result = invertedIndex;
+            }
+        };
+
+        new MockUp<LocalMetastore>() {
+            Database database = CatalogMocker.mockDb();
+
+            @Mock
+            public Database getDb(String dbName) {
+                return database;
+            }
+
+            @Mock
+            public Table getTable(String dbName, String tblName) {
+                return database.getTable(tblName);
+            }
+        };
+
         // add repo
-        handler = new BackupHandler(globalStateMgr);
+        BackupHandler handler = new BackupHandler(globalStateMgr);
         CreateRepositoryStmt stmt = new CreateRepositoryStmt(false, "repo", "broker", "bos://location",
-                Maps.newHashMap());
+                    Maps.newHashMap());
         try {
             handler.createRepository(stmt);
         } catch (DdlException e) {
@@ -267,7 +303,7 @@ public Status getSnapshotInfoFile(String label, String backupTimestamp, List<Bac
         List<TableRef> tblRefs = Lists.newArrayList();
         tblRefs.add(new TableRef(new TableName(CatalogMocker.TEST_DB_NAME, CatalogMocker.TEST_TBL_NAME), null));
         BackupStmt backupStmt = new BackupStmt(new LabelName(CatalogMocker.TEST_DB_NAME, "label1"), "repo", tblRefs,
-                null);
+                    null);
         try {
             handler.process(backupStmt);
         } catch (DdlException e1) {
@@ -278,7 +314,7 @@ public Status getSnapshotInfoFile(String label, String backupTimestamp, List<Bac
         // handleFinishedSnapshotTask
         BackupJob backupJob = (BackupJob) handler.getJob(CatalogMocker.TEST_DB_ID);
         SnapshotTask snapshotTask = new SnapshotTask(null, 0, 0, backupJob.getJobId(), CatalogMocker.TEST_DB_ID,
-                0, 0, 0, 0, 0, 0, 1, false);
+                    0, 0, 0, 0, 0, 0, 1, false);
         TFinishTaskRequest request = new TFinishTaskRequest();
         List<String> snapshotFiles = Lists.newArrayList();
         request.setSnapshot_files(snapshotFiles);
@@ -289,7 +325,7 @@ public Status getSnapshotInfoFile(String label, String backupTimestamp, List<Bac
         // handleFinishedSnapshotUploadTask
         Map<String, String> srcToDestPath = Maps.newHashMap();
         UploadTask uploadTask = new UploadTask(null, 0, 0, backupJob.getJobId(), CatalogMocker.TEST_DB_ID,
-                srcToDestPath, null, null);
+                    srcToDestPath, null, null);
         request = new TFinishTaskRequest();
         Map<Long, List<String>> tabletFiles = Maps.newHashMap();
         request.setTablet_files(tabletFiles);
@@ -325,8 +361,8 @@ public Status getSnapshotInfoFile(String label, String backupTimestamp, List<Bac
         List<TableRef> tblRefs1 = Lists.newArrayList();
         tblRefs1.add(new TableRef(new TableName(CatalogMocker.TEST_DB_NAME, CatalogMocker.TEST_TBL3_NAME), null));
         BackupStmt backupStmt1 =
-                new BackupStmt(new LabelName(CatalogMocker.TEST_DB_NAME, "label2"), "repo", tblRefs1,
-                        null);
+                    new BackupStmt(new LabelName(CatalogMocker.TEST_DB_NAME, "label2"), "repo", tblRefs1,
+                                null);
         try {
             handler.process(backupStmt1);
         } catch (DdlException e1) {
@@ -337,7 +373,7 @@ public Status getSnapshotInfoFile(String label, String backupTimestamp, List<Bac
         // handleFinishedSnapshotTask
         BackupJob backupJob1 = (BackupJob) handler.getJob(CatalogMocker.TEST_DB_ID);
         SnapshotTask snapshotTask1 = new SnapshotTask(null, 0, 0, backupJob1.getJobId(), CatalogMocker.TEST_DB_ID,
-                0, 0, 0, 0, 0, 0, 1, false);
+                    0, 0, 0, 0, 0, 0, 1, false);
         TFinishTaskRequest request1 = new TFinishTaskRequest();
         List<String> snapshotFiles1 = Lists.newArrayList();
         request1.setSnapshot_files(snapshotFiles1);
@@ -348,7 +384,7 @@ public Status getSnapshotInfoFile(String label, String backupTimestamp, List<Bac
         // handleFinishedSnapshotUploadTask
         Map<String, String> srcToDestPath1 = Maps.newHashMap();
         UploadTask uploadTask1 = new UploadTask(null, 0, 0, backupJob1.getJobId(), CatalogMocker.TEST_DB_ID,
-                srcToDestPath1, null, null);
+                    srcToDestPath1, null, null);
         request1 = new TFinishTaskRequest();
         Map<Long, List<String>> tabletFiles1 = Maps.newHashMap();
         request1.setTablet_files(tabletFiles1);
@@ -386,7 +422,7 @@ public Status getSnapshotInfoFile(String label, String backupTimestamp, List<Bac
         Map<String, String> properties = Maps.newHashMap();
         properties.put("backup_timestamp", "2018-08-08-08-08-08");
         RestoreStmt restoreStmt = new RestoreStmt(new LabelName(CatalogMocker.TEST_DB_NAME, "ss2"), "repo", tblRefs2,
-                properties);
+                    properties);
         try {
             BackupRestoreAnalyzer.analyze(restoreStmt, new ConnectContext());
         } catch (SemanticException e2) {
@@ -404,7 +440,7 @@ public Status getSnapshotInfoFile(String label, String backupTimestamp, List<Bac
         // handleFinishedSnapshotTask
         RestoreJob restoreJob = (RestoreJob) handler.getJob(CatalogMocker.TEST_DB_ID);
         snapshotTask = new SnapshotTask(null, 0, 0, restoreJob.getJobId(), CatalogMocker.TEST_DB_ID,
-                0, 0, 0, 0, 0, 0, 1, true);
+                    0, 0, 0, 0, 0, 0, 1, true);
         request = new TFinishTaskRequest();
         request.setSnapshot_path("./snapshot/path");
         request.setTask_status(new TStatus(TStatusCode.OK));
@@ -412,7 +448,7 @@ public Status getSnapshotInfoFile(String label, String backupTimestamp, List<Bac
 
         // handleDownloadSnapshotTask
         DownloadTask downloadTask = new DownloadTask(null, 0, 0, restoreJob.getJobId(), CatalogMocker.TEST_DB_ID,
-                srcToDestPath, null, null);
+                    srcToDestPath, null, null);
         request = new TFinishTaskRequest();
         List<Long> downloadedTabletIds = Lists.newArrayList();
         request.setDownloaded_tablet_ids(downloadedTabletIds);
@@ -421,7 +457,7 @@ public Status getSnapshotInfoFile(String label, String backupTimestamp, List<Bac
 
         // handleDirMoveTask
         DirMoveTask dirMoveTask = new DirMoveTask(null, 0, 0, restoreJob.getJobId(), CatalogMocker.TEST_DB_ID, 0, 0, 0,
-                0, "", 0, true);
+                    0, "", 0, true);
         request = new TFinishTaskRequest();
         request.setTask_status(new TStatus(TStatusCode.OK));
         handler.handleDirMoveTask(dirMoveTask, request);
@@ -464,7 +500,7 @@ BackupHandler getBackupHandler() {
         Map<String, String> properties1 = Maps.newHashMap();
         properties1.put("backup_timestamp", "2018-08-08-08-08-08");
         RestoreStmt restoreStmt1 = new RestoreStmt(new LabelName(CatalogMocker.TEST_DB_NAME, "label2"), "repo", tblRefs3,
-                properties1);
+                    properties1);
         try {
             BackupRestoreAnalyzer.analyze(restoreStmt1, new ConnectContext());
         } catch (SemanticException e2) {
@@ -482,7 +518,7 @@ BackupHandler getBackupHandler() {
         // handleFinishedSnapshotTask
         RestoreJob restoreJob1 = (RestoreJob) handler.getJob(CatalogMocker.TEST_DB_ID);
         snapshotTask1 = new SnapshotTask(null, 0, 0, restoreJob1.getJobId(), CatalogMocker.TEST_DB_ID,
-                0, 0, 0, 0, 0, 0, 1, true);
+                    0, 0, 0, 0, 0, 0, 1, true);
         request1 = new TFinishTaskRequest();
         request1.setSnapshot_path("./snapshot/path1");
         request1.setTask_status(new TStatus(TStatusCode.OK));
@@ -490,7 +526,7 @@ BackupHandler getBackupHandler() {
 
         // handleDownloadSnapshotTask
         DownloadTask downloadTask1 = new DownloadTask(null, 0, 0, restoreJob1.getJobId(), CatalogMocker.TEST_DB_ID,
-                srcToDestPath1, null, null);
+                    srcToDestPath1, null, null);
         request1 = new TFinishTaskRequest();
         List<Long> downloadedTabletIds1 = Lists.newArrayList();
         request1.setDownloaded_tablet_ids(downloadedTabletIds1);
@@ -499,7 +535,7 @@ BackupHandler getBackupHandler() {
 
         // handleDirMoveTask
         DirMoveTask dirMoveTask1 = new DirMoveTask(null, 0, 0, restoreJob1.getJobId(), CatalogMocker.TEST_DB_ID, 0, 0, 0,
-                0, "", 0, true);
+                    0, "", 0, true);
         request1 = new TFinishTaskRequest();
         request1.setTask_status(new TStatus(TStatusCode.OK));
         handler.handleDirMoveTask(dirMoveTask1, request1);
@@ -595,7 +631,6 @@ public void testSaveLoadJsonFormatImage() throws Exception {
         BackupJob runningJob = new BackupJob("running_job", 1, "test_db", new ArrayList<>(), 10000, globalStateMgr, 1);
         handler.dbIdToBackupOrRestoreJob.put(runningJob.getDbId(), runningJob);
 
-
         UtFrameUtils.PseudoImage pseudoImage = new UtFrameUtils.PseudoImage();
         handler.saveBackupHandlerV2(pseudoImage.getImageWriter());
         BackupHandler followerHandler = new BackupHandler(globalStateMgr);
diff --git a/fe/fe-core/src/test/java/com/starrocks/backup/BackupJobMaterializedViewTest.java b/fe/fe-core/src/test/java/com/starrocks/backup/BackupJobMaterializedViewTest.java
index dde16ba561502b..70c48dc031ca78 100644
--- a/fe/fe-core/src/test/java/com/starrocks/backup/BackupJobMaterializedViewTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/backup/BackupJobMaterializedViewTest.java
@@ -122,7 +122,7 @@ public Repository getRepo(long repoId) {
     private EditLog editLog;
 
     private Repository repo = new Repository(repoId, "repo", false, "my_repo",
-            new BlobStorage("broker", Maps.newHashMap()));
+                new BlobStorage("broker", Maps.newHashMap()));
 
     @BeforeAll
     public static void start() {
@@ -141,7 +141,7 @@ public static void end() throws IOException {
             File backupDir = new File(path.toString());
             if (backupDir.exists()) {
                 Files.walk(path, FileVisitOption.FOLLOW_LINKS).sorted(Comparator.reverseOrder()).map(Path::toFile)
-                        .forEach(File::delete);
+                            .forEach(File::delete);
             }
         }
     }
@@ -156,11 +156,11 @@ public void setUp() {
         Deencapsulation.setField(globalStateMgr, "backupHandler", backupHandler);
 
         db = UnitTestUtil.createDbWithMaterializedView(dbId, tblId, partId, idxId, tabletId,
-                backendId, version, KeysType.DUP_KEYS);
+                    backendId, version, KeysType.DUP_KEYS);
 
         new Expectations(globalStateMgr) {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = db;
 
@@ -171,6 +171,14 @@ public void setUp() {
                 globalStateMgr.getEditLog();
                 minTimes = 0;
                 result = editLog;
+
+                globalStateMgr.getLocalMetastore().getTable("testDb", "unknown_mv");
+                minTimes = 0;
+                result = null;
+
+                globalStateMgr.getLocalMetastore().getTable("testDb", "unknown_tbl");
+                minTimes = 0;
+                result = null;
             }
         };
 
@@ -239,14 +247,18 @@ public void testRunNormal() {
                 List<String> partNames = Lists.newArrayList(backupTbl.getPartitionNames());
                 Assert.assertNotNull(backupTbl);
                 Assert.assertEquals(backupTbl.getSignature(BackupHandler.SIGNATURE_VERSION, partNames, true),
-                        ((OlapTable) db.getTable(tblId)).getSignature(BackupHandler.SIGNATURE_VERSION, partNames, true));
+                            ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                        .getTable(db.getId(), tblId)).getSignature(BackupHandler.SIGNATURE_VERSION, partNames,
+                                        true));
             }
             {
                 OlapTable backupTbl = (OlapTable) backupMeta.getTable(UnitTestUtil.MATERIALIZED_VIEW_NAME);
                 List<String> partNames = Lists.newArrayList(backupTbl.getPartitionNames());
                 Assert.assertNotNull(backupTbl);
                 Assert.assertEquals(backupTbl.getSignature(BackupHandler.SIGNATURE_VERSION, partNames, true),
-                        ((OlapTable) db.getTable(tblId + 1)).getSignature(BackupHandler.SIGNATURE_VERSION, partNames, true));
+                            ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                        .getTable(db.getId(), tblId + 1)).getSignature(BackupHandler.SIGNATURE_VERSION, partNames,
+                                        true));
             }
         }
 
@@ -271,7 +283,7 @@ public void testRunNormal() {
             Assert.assertTrue(task instanceof SnapshotTask);
             SnapshotTask snapshotTask = (SnapshotTask) task;
             TFinishTaskRequest request = new TFinishTaskRequest(tBackend, TTaskType.MAKE_SNAPSHOT,
-                    snapshotTask.getSignature(), taskStatus);
+                        snapshotTask.getSignature(), taskStatus);
             request.setSnapshot_files(snapshotFiles);
             request.setSnapshot_path(snapshotPath);
             Assert.assertTrue(job.finishTabletSnapshotTask(snapshotTask, request));
@@ -284,7 +296,7 @@ public void testRunNormal() {
             Assert.assertTrue(task instanceof SnapshotTask);
             SnapshotTask snapshotTask = (SnapshotTask) task;
             TFinishTaskRequest request = new TFinishTaskRequest(tBackend, TTaskType.MAKE_SNAPSHOT,
-                    snapshotTask.getSignature(), taskStatus);
+                        snapshotTask.getSignature(), taskStatus);
             request.setSnapshot_files(snapshotFiles);
             request.setSnapshot_path(snapshotPath);
             Assert.assertTrue(job.finishTabletSnapshotTask(snapshotTask, request));
@@ -307,7 +319,7 @@ public void testRunNormal() {
         Assert.assertEquals(job.getJobId(), upTask.getJobId());
         Map<String, String> srcToDest = upTask.getSrcToDestPath();
         Assert.assertEquals(1, srcToDest.size());
-        String dest = srcToDest.get(snapshotPath + "/" + tabletId  + "/" + 0);
+        String dest = srcToDest.get(snapshotPath + "/" + tabletId + "/" + 0);
         Assert.assertNotNull(dest);
 
         // 5. uploading
@@ -316,7 +328,7 @@ public void testRunNormal() {
         Assert.assertEquals(BackupJobState.UPLOADING, job.getState());
         Map<Long, List<String>> tabletFileMap = Maps.newHashMap();
         TFinishTaskRequest request = new TFinishTaskRequest(tBackend, TTaskType.UPLOAD,
-                upTask.getSignature(), taskStatus);
+                    upTask.getSignature(), taskStatus);
         request.setTablet_files(tabletFileMap);
 
         Assert.assertFalse(job.finishSnapshotUploadTask(upTask, request));
@@ -354,16 +366,18 @@ public void testRunNormal() {
                 Assert.assertNotNull(olapTable);
                 Assert.assertNotNull(restoreMetaInfo.getTable(UnitTestUtil.TABLE_NAME));
                 List<String> names = Lists.newArrayList(olapTable.getPartitionNames());
-                Assert.assertEquals(((OlapTable) db.getTable(tblId)).getSignature(BackupHandler.SIGNATURE_VERSION, names, true),
-                        olapTable.getSignature(BackupHandler.SIGNATURE_VERSION, names, true));
+                Assert.assertEquals(((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                        .getTable(db.getId(), tblId)).getSignature(BackupHandler.SIGNATURE_VERSION, names, true),
+                            olapTable.getSignature(BackupHandler.SIGNATURE_VERSION, names, true));
             }
             {
                 MaterializedView mv = (MaterializedView) restoreMetaInfo.getTable(tblId + 1);
                 Assert.assertNotNull(mv);
                 Assert.assertNotNull(restoreMetaInfo.getTable(UnitTestUtil.MATERIALIZED_VIEW_NAME));
                 List<String> names = Lists.newArrayList(mv.getPartitionNames());
-                Assert.assertEquals(((OlapTable) db.getTable(tblId + 1)).getSignature(BackupHandler.SIGNATURE_VERSION, names,
-                                true), mv.getSignature(BackupHandler.SIGNATURE_VERSION, names, true));
+                Assert.assertEquals(((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(db.getId(), tblId + 1)).getSignature(BackupHandler.SIGNATURE_VERSION, names,
+                            true), mv.getSignature(BackupHandler.SIGNATURE_VERSION, names, true));
             }
 
             restoreJobInfo = BackupJobInfo.fromFile(job.getLocalJobInfoFilePath());
@@ -387,7 +401,7 @@ public void testRunNormal() {
             Assert.assertTrue(mv != null);
             Assert.assertTrue(!mv.isActive());
             Assert.assertTrue(mv.getInactiveReason().contains(String.format("Set the materialized view %s inactive in backup",
-                    UnitTestUtil.MATERIALIZED_VIEW_NAME)));
+                        UnitTestUtil.MATERIALIZED_VIEW_NAME)));
         } catch (IOException e) {
             e.printStackTrace();
             Assert.fail();
@@ -417,7 +431,7 @@ public void testRunAbnormal() {
         tableRefs.add(new TableRef(new TableName(UnitTestUtil.DB_NAME, "unknown_mv"), null));
 
         job = new BackupJob("mv_label_abnormal", dbId, UnitTestUtil.DB_NAME, tableRefs, 13600 * 1000,
-                globalStateMgr, repo.getId());
+                    globalStateMgr, repo.getId());
         job.run();
         Assert.assertEquals(Status.ErrCode.NOT_FOUND, job.getStatus().getErrCode());
         Assert.assertEquals(BackupJobState.CANCELLED, job.getState());
diff --git a/fe/fe-core/src/test/java/com/starrocks/backup/BackupJobPrimaryKeyTest.java b/fe/fe-core/src/test/java/com/starrocks/backup/BackupJobPrimaryKeyTest.java
index 5797d5551a2c98..72cc02e534fd94 100644
--- a/fe/fe-core/src/test/java/com/starrocks/backup/BackupJobPrimaryKeyTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/backup/BackupJobPrimaryKeyTest.java
@@ -138,7 +138,7 @@ public Repository getRepo(long repoId) {
     private EditLog editLog;
 
     private Repository repo = new Repository(repoId, "repo_pk", false, "my_repo_pk",
-            new BlobStorage("broker", Maps.newHashMap()));
+                new BlobStorage("broker", Maps.newHashMap()));
 
     @BeforeClass
     public static void start() {
@@ -157,7 +157,7 @@ public static void end() throws IOException {
             File backupDir = new File(path.toString());
             if (backupDir.exists()) {
                 Files.walk(path, FileVisitOption.FOLLOW_LINKS).sorted(Comparator.reverseOrder()).map(Path::toFile)
-                        .forEach(File::delete);
+                            .forEach(File::delete);
             }
         }
     }
@@ -172,11 +172,11 @@ public void setUp() {
         Deencapsulation.setField(globalStateMgr, "backupHandler", backupHandler);
 
         db = UnitTestUtil.createDbByName(dbId, tblId, partId, idxId, tabletId, backendId, version, KeysType.PRIMARY_KEYS,
-                                         testDbName, testTableName);
+                    testDbName, testTableName);
 
         new Expectations(globalStateMgr) {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = db;
 
@@ -187,6 +187,14 @@ public void setUp() {
                 globalStateMgr.getEditLog();
                 minTimes = 0;
                 result = editLog;
+
+                globalStateMgr.getLocalMetastore().getTable(testDbName, testTableName);
+                minTimes = 0;
+                result = db.getTable(tblId);
+
+                globalStateMgr.getLocalMetastore().getTable(testDbName, "unknown_tbl");
+                minTimes = 0;
+                result = null;
             }
         };
 
@@ -261,7 +269,7 @@ public void testRunNormal() {
         TStatus taskStatus = new TStatus(TStatusCode.OK);
         TBackend tBackend = new TBackend("", 0, 1);
         TFinishTaskRequest request = new TFinishTaskRequest(tBackend, TTaskType.MAKE_SNAPSHOT,
-                snapshotTask.getSignature(), taskStatus);
+                    snapshotTask.getSignature(), taskStatus);
         request.setSnapshot_files(snapshotFiles);
         request.setSnapshot_path(snapshotPath);
         Assert.assertTrue(job.finishTabletSnapshotTask(snapshotTask, request));
@@ -292,7 +300,7 @@ public void testRunNormal() {
         Assert.assertEquals(BackupJobState.UPLOADING, job.getState());
         Map<Long, List<String>> tabletFileMap = Maps.newHashMap();
         request = new TFinishTaskRequest(tBackend, TTaskType.UPLOAD,
-                upTask.getSignature(), taskStatus);
+                    upTask.getSignature(), taskStatus);
         request.setTablet_files(tabletFileMap);
 
         Assert.assertFalse(job.finishSnapshotUploadTask(upTask, request));
diff --git a/fe/fe-core/src/test/java/com/starrocks/backup/BackupJobTest.java b/fe/fe-core/src/test/java/com/starrocks/backup/BackupJobTest.java
index e13b9f86143bfa..81e24d4739df93 100644
--- a/fe/fe-core/src/test/java/com/starrocks/backup/BackupJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/backup/BackupJobTest.java
@@ -133,7 +133,7 @@ public Repository getRepo(long repoId) {
     private EditLog editLog;
 
     private Repository repo = new Repository(repoId, "repo", false, "my_repo",
-            new BlobStorage("broker", Maps.newHashMap()));
+                new BlobStorage("broker", Maps.newHashMap()));
 
     @BeforeClass
     public static void start() {
@@ -150,8 +150,8 @@ public static void end() throws IOException {
         File backupDir = new File(BackupHandler.BACKUP_ROOT_DIR.toString());
         if (backupDir.exists()) {
             Files.walk(BackupHandler.BACKUP_ROOT_DIR,
-                            FileVisitOption.FOLLOW_LINKS).sorted(Comparator.reverseOrder()).map(Path::toFile)
-                    .forEach(File::delete);
+                                    FileVisitOption.FOLLOW_LINKS).sorted(Comparator.reverseOrder()).map(Path::toFile)
+                        .forEach(File::delete);
         }
     }
 
@@ -168,10 +168,12 @@ public void setUp() {
 
         new Expectations(globalStateMgr) {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = db;
 
+
+
                 globalStateMgr.getNextId();
                 minTimes = 0;
                 result = id.getAndIncrement();
@@ -179,6 +181,14 @@ public void setUp() {
                 globalStateMgr.getEditLog();
                 minTimes = 0;
                 result = editLog;
+
+                globalStateMgr.getLocalMetastore().getTable("testDb", "testTable");
+                minTimes = 0;
+                result = db.getTable(tblId);
+
+                globalStateMgr.getLocalMetastore().getTable("testDb", "unknown_tbl");
+                minTimes = 0;
+                result = null;
             }
         };
 
@@ -253,7 +263,7 @@ public void testRunNormal() {
         TStatus taskStatus = new TStatus(TStatusCode.OK);
         TBackend tBackend = new TBackend("", 0, 1);
         TFinishTaskRequest request = new TFinishTaskRequest(tBackend, TTaskType.MAKE_SNAPSHOT,
-                snapshotTask.getSignature(), taskStatus);
+                    snapshotTask.getSignature(), taskStatus);
         request.setSnapshot_files(snapshotFiles);
         request.setSnapshot_path(snapshotPath);
         Assert.assertTrue(job.finishTabletSnapshotTask(snapshotTask, request));
@@ -284,7 +294,7 @@ public void testRunNormal() {
         Assert.assertEquals(BackupJobState.UPLOADING, job.getState());
         Map<Long, List<String>> tabletFileMap = Maps.newHashMap();
         request = new TFinishTaskRequest(tBackend, TTaskType.UPLOAD,
-                upTask.getSignature(), taskStatus);
+                    upTask.getSignature(), taskStatus);
         request.setTablet_files(tabletFileMap);
 
         Assert.assertFalse(job.finishSnapshotUploadTask(upTask, request));
@@ -345,7 +355,8 @@ public void testRunNormal() {
         try {
             // test get backup info
             job.getInfo();
-        } catch (Exception ignore) { }
+        } catch (Exception ignore) {
+        }
     }
 
     @Test
diff --git a/fe/fe-core/src/test/java/com/starrocks/backup/CatalogMocker.java b/fe/fe-core/src/test/java/com/starrocks/backup/CatalogMocker.java
index 349c39815edfe7..997d26e21f9ef3 100644
--- a/fe/fe-core/src/test/java/com/starrocks/backup/CatalogMocker.java
+++ b/fe/fe-core/src/test/java/com/starrocks/backup/CatalogMocker.java
@@ -531,19 +531,19 @@ public static GlobalStateMgr fetchAdminCatalog() {
 
         new Expectations(globalStateMgr) {
             {
-                globalStateMgr.getDb(TEST_DB_NAME);
+                globalStateMgr.getLocalMetastore().getDb(TEST_DB_NAME);
                 minTimes = 0;
                 result = db;
 
-                globalStateMgr.getDb(WRONG_DB);
+                globalStateMgr.getLocalMetastore().getDb(WRONG_DB);
                 minTimes = 0;
                 result = null;
 
-                globalStateMgr.getDb(TEST_DB_ID);
+                globalStateMgr.getLocalMetastore().getDb(TEST_DB_ID);
                 minTimes = 0;
                 result = db;
 
-                globalStateMgr.getDb(anyString);
+                globalStateMgr.getLocalMetastore().getDb(anyString);
                 minTimes = 0;
                 result = new Database();
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/backup/RestoreJobMaterializedViewTest.java b/fe/fe-core/src/test/java/com/starrocks/backup/RestoreJobMaterializedViewTest.java
index 462503dfa57270..d0aab1e9fa8611 100644
--- a/fe/fe-core/src/test/java/com/starrocks/backup/RestoreJobMaterializedViewTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/backup/RestoreJobMaterializedViewTest.java
@@ -44,6 +44,7 @@
 import com.starrocks.persist.EditLog;
 import com.starrocks.qe.ConnectContext;
 import com.starrocks.server.GlobalStateMgr;
+import com.starrocks.server.LocalMetastore;
 import com.starrocks.server.MetadataMgr;
 import com.starrocks.system.NodeSelector;
 import com.starrocks.system.SystemInfoService;
@@ -85,7 +86,6 @@
 import static com.starrocks.common.util.UnitTestUtil.MATERIALIZED_VIEW_NAME;
 import static com.starrocks.common.util.UnitTestUtil.TABLE_NAME;
 
-
 @TestMethodOrder(MethodOrderer.OrderAnnotation.class)
 public class RestoreJobMaterializedViewTest {
 
@@ -113,7 +113,6 @@ public class RestoreJobMaterializedViewTest {
 
     private MvRestoreContext mvRestoreContext;
 
-
     // Thread is not mockable in Jmockit, use subclass instead
     private final class MockBackupHandler extends BackupHandler {
         public MockBackupHandler(GlobalStateMgr globalStateMgr) {
@@ -147,11 +146,12 @@ public Repository getRepo(long repoId) {
 
     @Injectable
     private Repository repo = new Repository(repoId, "repo", false, "bos://my_repo",
-            new BlobStorage("broker", Maps.newHashMap()));
+                new BlobStorage("broker", Maps.newHashMap()));
 
     private BackupMeta backupMeta;
 
     private Object[] arrayIds;
+
     private void setUpMocker() {
         MetricRepo.init();
 
@@ -164,19 +164,27 @@ private void setUpMocker() {
 
         new Expectations() {
             {
-                globalStateMgr.getDb(anyLong);
+                GlobalStateMgr.getCurrentState();
+                minTimes = 0;
+                result = globalStateMgr;
+
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = db;
 
+                globalStateMgr.getLocalMetastore().getTable(UnitTestUtil.DB_NAME, MATERIALIZED_VIEW_NAME);
+                minTimes = 0;
+                result = db.getTable(MATERIALIZED_VIEW_NAME);
+
                 globalStateMgr.getEditLog();
                 minTimes = 0;
                 result = editLog;
 
-                GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo();
-                minTimes = 0;
-                result = systemInfoService;
+                //GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo();
+                //minTimes = 0;
+                //result = systemInfoService;
 
-                globalStateMgr.mayGetDb(anyLong);
+                globalStateMgr.getLocalMetastore().mayGetDb(anyLong);
                 minTimes = 0;
                 result = Optional.of(db);
 
@@ -225,24 +233,24 @@ public Status getSnapshotMetaFile(String label, List<BackupMeta> backupMetas) {
             }
         };
         new MockUp<MarkedCountDownLatch>() {
-                @Mock
-                boolean await(long timeout, TimeUnit unit) {
-                    return true;
-                }
-            };
+            @Mock
+            boolean await(long timeout, TimeUnit unit) {
+                return true;
+            }
+        };
 
         new MockUp<ConnectContext>() {
-                @Mock
-                GlobalStateMgr getGlobalStateMgr() {
-                    return globalStateMgr;
-                }
-            };
+            @Mock
+            GlobalStateMgr getGlobalStateMgr() {
+                return globalStateMgr;
+            }
+        };
         new MockUp<GlobalStateMgr>() {
-                @Mock
-                BackupHandler getBackupHandler() {
-                    return backupHandler;
-                }
-            };
+            @Mock
+            BackupHandler getBackupHandler() {
+                return backupHandler;
+            }
+        };
 
         new MockUp<HdfsUtil>() {
             @Mock
@@ -259,7 +267,7 @@ public void setUp() throws AnalysisException {
         Deencapsulation.setField(globalStateMgr, "backupHandler", backupHandler);
         systemInfoService = new SystemInfoService();
         db = UnitTestUtil.createDbWithMaterializedView(dbId, tblId, partId, idxId, tabletId,
-                backendId, version, KeysType.DUP_KEYS);
+                    backendId, version, KeysType.DUP_KEYS);
         mvRestoreContext = new MvRestoreContext();
         setUpMocker();
     }
@@ -315,8 +323,8 @@ public RestoreJob createRestoreJob(List<String> restoreTbls) {
         }
 
         RestoreJob job = new RestoreJob(label, "2018-01-01 01:01:01", db.getId(), db.getFullName(),
-                jobInfo, false, 3, 100000,
-                globalStateMgr, repo.getId(), backupMeta, mvRestoreContext);
+                    jobInfo, false, 3, 100000,
+                    globalStateMgr, repo.getId(), backupMeta, mvRestoreContext);
         job.setRepo(repo);
 
         // add job into mvRestoreContext
@@ -358,7 +366,7 @@ private void checkJobRun(RestoreJob job) {
             TStatus taskStatus = new TStatus(TStatusCode.OK);
             TBackend tBackend = new TBackend("", 0, 1);
             TFinishTaskRequest request = new TFinishTaskRequest(tBackend, TTaskType.MAKE_SNAPSHOT,
-                    task.getSignature(), taskStatus);
+                        task.getSignature(), taskStatus);
             request.setSnapshot_path(snapshotPath);
             Assert.assertTrue(job.finishTabletSnapshotTask(task, request));
         }
@@ -391,7 +399,7 @@ private void checkJobRun(RestoreJob job) {
             TStatus taskStatus = new TStatus(TStatusCode.OK);
             TBackend tBackend = new TBackend("", 0, 1);
             TFinishTaskRequest request = new TFinishTaskRequest(tBackend, TTaskType.MAKE_SNAPSHOT,
-                    agentTask.getSignature(), taskStatus);
+                        agentTask.getSignature(), taskStatus);
             request.setDownloaded_tablet_ids(downloadedTabletIds);
             Assert.assertTrue(job.finishTabletDownloadTask((DownloadTask) agentTask, request));
         }
@@ -423,7 +431,7 @@ private void checkJobRun(RestoreJob job) {
             TStatus taskStatus = new TStatus(TStatusCode.OK);
             TBackend tBackend = new TBackend("", 0, 1);
             TFinishTaskRequest request = new TFinishTaskRequest(tBackend, TTaskType.MAKE_SNAPSHOT,
-                    agentTask.getSignature(), taskStatus);
+                        agentTask.getSignature(), taskStatus);
             job.finishDirMoveTask((DirMoveTask) agentTask, request);
         }
 
@@ -439,6 +447,24 @@ private void checkJobRun(RestoreJob job) {
     @Order(1)
     public void testMVRestore_TestOneTable1() {
         RestoreJob job = createRestoreJob(ImmutableList.of(UnitTestUtil.MATERIALIZED_VIEW_NAME));
+
+        new MockUp<LocalMetastore>() {
+            @Mock
+            public Database getDb(String dbName) {
+                return db;
+            }
+
+            @Mock
+            public Table getTable(String dbName, String tblName) {
+                return db.getTable(tblName);
+            }
+
+            @Mock
+            public Table getTable(Long dbId, Long tableId) {
+                return db.getTable(tableId);
+            }
+        };
+
         checkJobRun(job);
         assertMVActiveEquals(MATERIALIZED_VIEW_NAME, true);
     }
@@ -455,6 +481,22 @@ public void testMVRestore_TestOneTable2() {
     public void testMVRestore_TestMVWithBaseTable1() {
         // gen BackupJobInfo
         RestoreJob job = createRestoreJob(ImmutableList.of(TABLE_NAME, MATERIALIZED_VIEW_NAME));
+        new MockUp<LocalMetastore>() {
+            @Mock
+            public Database getDb(String dbName) {
+                return db;
+            }
+
+            @Mock
+            public Table getTable(String dbName, String tblName) {
+                return db.getTable(tblName);
+            }
+
+            @Mock
+            public Table getTable(Long dbId, Long tableId) {
+                return db.getTable(tableId);
+            }
+        };
         // backup & restore
         checkJobRun(job);
         assertMVActiveEquals(MATERIALIZED_VIEW_NAME, true);
@@ -465,6 +507,22 @@ public void testMVRestore_TestMVWithBaseTable1() {
     public void testMVRestore_TestMVWithBaseTable2() {
         // gen BackupJobInfo
         RestoreJob job = createRestoreJob(ImmutableList.of(MATERIALIZED_VIEW_NAME, TABLE_NAME));
+        new MockUp<LocalMetastore>() {
+            @Mock
+            public Database getDb(String dbName) {
+                return db;
+            }
+
+            @Mock
+            public Table getTable(String dbName, String tblName) {
+                return db.getTable(tblName);
+            }
+
+            @Mock
+            public Table getTable(Long dbId, Long tableId) {
+                return db.getTable(tableId);
+            }
+        };
         // backup & restore
         checkJobRun(job);
         assertMVActiveEquals(MATERIALIZED_VIEW_NAME, true);
@@ -489,11 +547,27 @@ public void testMVRestore_TestMVWithBaseTable4() {
         new MockUp<MetadataMgr>() {
             @Mock
             public Table getTable(String catalogName, String dbName, String tblName) {
-                return db.getTable(tblName);
+                return GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tblName);
             }
         };
         // gen BackupJobInfo
         RestoreJob job1 = createRestoreJob(ImmutableList.of(MATERIALIZED_VIEW_NAME));
+        new MockUp<LocalMetastore>() {
+            @Mock
+            public Database getDb(String dbName) {
+                return db;
+            }
+
+            @Mock
+            public Table getTable(String dbName, String tblName) {
+                return db.getTable(tblName);
+            }
+
+            @Mock
+            public Table getTable(Long dbId, Long tableId) {
+                return db.getTable(tableId);
+            }
+        };
         // backup & restore
         checkJobRun(job1);
         assertMVActiveEquals(MATERIALIZED_VIEW_NAME, true);
@@ -504,7 +578,7 @@ public Table getTable(String catalogName, String dbName, String tblName) {
     }
 
     private void assertMVActiveEquals(String mvName, boolean expect) {
-        Table mvTable = db.getTable(mvName);
+        Table mvTable = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), mvName);
         Assert.assertTrue(mvTable != null);
         Assert.assertTrue(mvTable.isMaterializedView());
         MaterializedView mv = (MaterializedView) mvTable;
diff --git a/fe/fe-core/src/test/java/com/starrocks/backup/RestoreJobPrimaryKeyTest.java b/fe/fe-core/src/test/java/com/starrocks/backup/RestoreJobPrimaryKeyTest.java
index 37f167eb028446..947e2f8231bbef 100644
--- a/fe/fe-core/src/test/java/com/starrocks/backup/RestoreJobPrimaryKeyTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/backup/RestoreJobPrimaryKeyTest.java
@@ -137,7 +137,7 @@ public Repository getRepo(long repoId) {
 
     @Injectable
     private Repository repo = new Repository(repoId, "repo", false, "bos://my_repo",
-            new BlobStorage("broker", Maps.newHashMap()));
+                new BlobStorage("broker", Maps.newHashMap()));
 
     private BackupMeta backupMeta;
 
@@ -151,10 +151,6 @@ public void setUp() throws AnalysisException {
 
         new Expectations() {
             {
-                globalStateMgr.getDb(anyLong);
-                minTimes = 0;
-                result = db;
-
                 globalStateMgr.getNextId();
                 minTimes = 0;
                 result = id.getAndIncrement();
@@ -264,8 +260,8 @@ boolean await(long timeout, TimeUnit unit) {
         tbls.add(expectedRestoreTbl);
         backupMeta = new BackupMeta(tbls);
         job = new RestoreJob(label, "2018-01-01 01:01:01", db.getId(), db.getFullName(),
-                jobInfo, false, 3, 100000,
-                globalStateMgr, repo.getId(), backupMeta, new MvRestoreContext());
+                    jobInfo, false, 3, 100000,
+                    globalStateMgr, repo.getId(), backupMeta, new MvRestoreContext());
     }
 
     @Ignore
@@ -301,7 +297,7 @@ public void testRun() {
             TStatus taskStatus = new TStatus(TStatusCode.OK);
             TBackend tBackend = new TBackend("", 0, 1);
             TFinishTaskRequest request = new TFinishTaskRequest(tBackend, TTaskType.MAKE_SNAPSHOT,
-                    task.getSignature(), taskStatus);
+                        task.getSignature(), taskStatus);
             request.setSnapshot_path(snapshotPath);
             Assert.assertTrue(job.finishTabletSnapshotTask(task, request));
         }
@@ -334,7 +330,7 @@ public void testRun() {
             TStatus taskStatus = new TStatus(TStatusCode.OK);
             TBackend tBackend = new TBackend("", 0, 1);
             TFinishTaskRequest request = new TFinishTaskRequest(tBackend, TTaskType.MAKE_SNAPSHOT,
-                    agentTask.getSignature(), taskStatus);
+                        agentTask.getSignature(), taskStatus);
             request.setDownloaded_tablet_ids(downloadedTabletIds);
             Assert.assertTrue(job.finishTabletDownloadTask((DownloadTask) agentTask, request));
         }
@@ -366,7 +362,7 @@ public void testRun() {
             TStatus taskStatus = new TStatus(TStatusCode.OK);
             TBackend tBackend = new TBackend("", 0, 1);
             TFinishTaskRequest request = new TFinishTaskRequest(tBackend, TTaskType.MAKE_SNAPSHOT,
-                    agentTask.getSignature(), taskStatus);
+                        agentTask.getSignature(), taskStatus);
             job.finishDirMoveTask((DirMoveTask) agentTask, request);
         }
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/backup/RestoreJobTest.java b/fe/fe-core/src/test/java/com/starrocks/backup/RestoreJobTest.java
index 323c93e3dee46e..1ed06f0ce9df82 100644
--- a/fe/fe-core/src/test/java/com/starrocks/backup/RestoreJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/backup/RestoreJobTest.java
@@ -61,6 +61,7 @@
 import com.starrocks.metric.MetricRepo;
 import com.starrocks.persist.EditLog;
 import com.starrocks.server.GlobalStateMgr;
+import com.starrocks.server.LocalMetastore;
 import com.starrocks.system.SystemInfoService;
 import com.starrocks.task.AgentTask;
 import com.starrocks.task.AgentTaskQueue;
@@ -138,7 +139,7 @@ public Repository getRepo(long repoId) {
 
     @Injectable
     private Repository repo = new Repository(repoId, "repo", false, "bos://my_repo",
-                new BlobStorage("broker", Maps.newHashMap()));
+            new BlobStorage("broker", Maps.newHashMap()));
 
     private BackupMeta backupMeta;
 
@@ -155,12 +156,12 @@ public void testResetPartitionForRestore() {
         expectedRestoreTbl = (OlapTable) db.getTable(CatalogMocker.TEST_TBL4_ID);
 
         OlapTable localTbl = new OlapTable(expectedRestoreTbl.getId(), expectedRestoreTbl.getName(),
-                    expectedRestoreTbl.getBaseSchema(), KeysType.DUP_KEYS, expectedRestoreTbl.getPartitionInfo(),
-                    expectedRestoreTbl.getDefaultDistributionInfo());
+                expectedRestoreTbl.getBaseSchema(), KeysType.DUP_KEYS, expectedRestoreTbl.getPartitionInfo(),
+                expectedRestoreTbl.getDefaultDistributionInfo());
 
         job = new RestoreJob(label, "2018-01-01 01:01:01", db.getId(), db.getFullName(),
-                    jobInfo, false, 3, 100000,
-                    globalStateMgr, repo.getId(), backupMeta, new MvRestoreContext());
+                jobInfo, false, 3, 100000,
+                globalStateMgr, repo.getId(), backupMeta, new MvRestoreContext());
 
         job.resetPartitionForRestore(localTbl, expectedRestoreTbl, CatalogMocker.TEST_PARTITION1_NAME, 3);
     }
@@ -169,7 +170,7 @@ public void testResetPartitionForRestore() {
     public void testRunBackupMultiSubPartitionTable() {
         new Expectations() {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = db;
 
@@ -287,12 +288,29 @@ boolean await(long timeout, TimeUnit unit) {
         // drop this table, cause we want to try restoring this table
         db.dropTable(expectedRestoreTbl.getName());
 
+        new MockUp<LocalMetastore>() {
+            @Mock
+            public Database getDb(String dbName) {
+                return db;
+            }
+
+            @Mock
+            public Table getTable(String dbName, String tblName) {
+                return db.getTable(tblName);
+            }
+
+            @Mock
+            public Table getTable(Long dbId, Long tableId) {
+                return db.getTable(tableId);
+            }
+        };
+
         List<Table> tbls = Lists.newArrayList();
         tbls.add(expectedRestoreTbl);
         backupMeta = new BackupMeta(tbls);
         job = new RestoreJob(label, "2018-01-01 01:01:01", db.getId(), db.getFullName(),
-                    jobInfo, false, 3, 100000,
-                    globalStateMgr, repo.getId(), backupMeta, new MvRestoreContext());
+                jobInfo, false, 3, 100000,
+                globalStateMgr, repo.getId(), backupMeta, new MvRestoreContext());
         job.setRepo(repo);
         // pending
         job.run();
@@ -324,7 +342,7 @@ boolean await(long timeout, TimeUnit unit) {
             TStatus taskStatus = new TStatus(TStatusCode.OK);
             TBackend tBackend = new TBackend("", 0, 1);
             TFinishTaskRequest request = new TFinishTaskRequest(tBackend, TTaskType.MAKE_SNAPSHOT,
-                        task.getSignature(), taskStatus);
+                    task.getSignature(), taskStatus);
             request.setSnapshot_path(snapshotPath);
             Assert.assertTrue(job.finishTabletSnapshotTask(task, request));
         }
@@ -344,7 +362,7 @@ boolean await(long timeout, TimeUnit unit) {
     public void testRunBackupRangeTable() {
         new Expectations() {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = db;
 
@@ -454,12 +472,29 @@ boolean await(long timeout, TimeUnit unit) {
         // drop this table, cause we want to try restoring this table
         db.dropTable(expectedRestoreTbl.getName());
 
+        new MockUp<LocalMetastore>() {
+            @Mock
+            public Database getDb(String dbName) {
+                return db;
+            }
+
+            @Mock
+            public Table getTable(String dbName, String tblName) {
+                return db.getTable(tblName);
+            }
+
+            @Mock
+            public Table getTable(Long dbId, Long tableId) {
+                return db.getTable(tableId);
+            }
+        };
+
         List<Table> tbls = Lists.newArrayList();
         tbls.add(expectedRestoreTbl);
         backupMeta = new BackupMeta(tbls);
         job = new RestoreJob(label, "2018-01-01 01:01:01", db.getId(), db.getFullName(),
-                    jobInfo, false, 3, 100000,
-                    globalStateMgr, repo.getId(), backupMeta, new MvRestoreContext());
+                jobInfo, false, 3, 100000,
+                globalStateMgr, repo.getId(), backupMeta, new MvRestoreContext());
         job.setRepo(repo);
         // pending
         job.run();
@@ -491,7 +526,7 @@ boolean await(long timeout, TimeUnit unit) {
             TStatus taskStatus = new TStatus(TStatusCode.OK);
             TBackend tBackend = new TBackend("", 0, 1);
             TFinishTaskRequest request = new TFinishTaskRequest(tBackend, TTaskType.MAKE_SNAPSHOT,
-                        task.getSignature(), taskStatus);
+                    task.getSignature(), taskStatus);
             request.setSnapshot_path(snapshotPath);
             Assert.assertTrue(job.finishTabletSnapshotTask(task, request));
         }
@@ -536,7 +571,7 @@ public void testColocateRestore() {
             {
                 try {
                     GlobalStateMgr.getCurrentState().getColocateTableIndex()
-                                .addTableToGroup((Database) any, (OlapTable) any, (String) any, false);
+                            .addTableToGroup((Database) any, (OlapTable) any, (String) any, false);
                 } catch (Exception e) {
                 }
                 result = true;
diff --git a/fe/fe-core/src/test/java/com/starrocks/benchmark/MvRefreshConcurrencyTest.java b/fe/fe-core/src/test/java/com/starrocks/benchmark/MvRefreshConcurrencyTest.java
index 4e7413a95828d3..09591cc5a9cdb0 100644
--- a/fe/fe-core/src/test/java/com/starrocks/benchmark/MvRefreshConcurrencyTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/benchmark/MvRefreshConcurrencyTest.java
@@ -123,9 +123,9 @@ private void testRefreshWithConcurrency(int tableNum, int mvNum) {
                     System.out.println(sql);
                     starRocksAssert.withMaterializedView(sql);
 
-                    Database db = GlobalStateMgr.getCurrentState().getDb("test");
+                    Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
                     String mvName = buildMVName(i);
-                    Table table = db.getTable(mvName);
+                    Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), mvName);
                     Assert.assertTrue(table != null);
                     mvs.add((MaterializedView) table);
                     starRocksAssert.useDatabase("test");
diff --git a/fe/fe-core/src/test/java/com/starrocks/binlog/BinlogManagerTest.java b/fe/fe-core/src/test/java/com/starrocks/binlog/BinlogManagerTest.java
index 2b1c482f760ae5..5dbf5cd46da9de 100644
--- a/fe/fe-core/src/test/java/com/starrocks/binlog/BinlogManagerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/binlog/BinlogManagerTest.java
@@ -55,8 +55,9 @@ public static void beforeClass() throws Exception {
 
     @Test
     public void testTryEnableBinlog() {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("binlog_test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table =
+                (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "binlog_test");
         boolean result = binlogManager.tryEnableBinlog(db, table.getId(), 200L, -1L);
         Assert.assertTrue(result);
         Assert.assertEquals(1, table.getBinlogVersion());
@@ -68,16 +69,18 @@ public void testTryEnableBinlog() {
 
     @Test
     public void testTryDisableBinlog() {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("binlog_test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table =
+                (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "binlog_test");
         boolean result = binlogManager.tryDisableBinlog(db, table.getId());
         Assert.assertFalse(table.isBinlogEnabled());
     }
 
     @Test
     public void testCheckAndSetBinlogAvailableVersion() {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("binlog_test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table =
+                (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "binlog_test");
         table.setBinlogTxnId(2);
         long totalNum = GlobalStateMgr.getCurrentState().getTabletInvertedIndex().getTabletIdsByBackendId(10001).size();
         binlogManager.checkAndSetBinlogAvailableVersion(db, table, 1, 10002);
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/AdminStmtTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/AdminStmtTest.java
index 2b58f35ccc7edc..7618278e8876ed 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/AdminStmtTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/AdminStmtTest.java
@@ -86,9 +86,9 @@ public static void beforeClass() throws Exception {
 
     @Test
     public void testAdminSetReplicaStatus() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         Assert.assertNotNull(db);
-        OlapTable tbl = (OlapTable) db.getTable("tbl1");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl1");
         Assert.assertNotNull(tbl);
         // tablet id, backend id
         List<Pair<Long, Long>> tabletToBackendList = Lists.newArrayList();
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/AggStateDescTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/AggStateDescTest.java
new file mode 100644
index 00000000000000..5fdecfe71206bc
--- /dev/null
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/AggStateDescTest.java
@@ -0,0 +1,60 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+package com.starrocks.catalog;
+
+import com.google.common.collect.Lists;
+import com.starrocks.catalog.combinator.AggStateDesc;
+import org.junit.Assert;
+import org.junit.Test;
+
+public class AggStateDescTest {
+    @Test
+    public void testNewAggStateDesc() {
+        AggregateFunction sum = AggregateFunction.createBuiltin(FunctionSet.SUM,
+                Lists.<Type>newArrayList(Type.INT), Type.BIGINT, Type.BIGINT, false, true, false);
+        AggStateDesc aggStateDesc = new AggStateDesc(sum);
+        Assert.assertEquals(1, aggStateDesc.getArgTypes().size());
+        Assert.assertEquals(Type.INT, aggStateDesc.getArgTypes().get(0));
+        Assert.assertEquals(Type.BIGINT, aggStateDesc.getReturnType());
+        Assert.assertEquals(FunctionSet.SUM, aggStateDesc.getFunctionName());
+        Assert.assertEquals(true, aggStateDesc.getResultNullable());
+        Assert.assertEquals("sum(int(11))", aggStateDesc.toSql());
+        Assert.assertEquals("sum(int(11))", aggStateDesc.toString());
+        Assert.assertNotNull(aggStateDesc.toThrift());
+        try {
+            Assert.assertNotNull(aggStateDesc.getAggregateFunction());
+        } catch (Exception e) {
+            Assert.fail();
+        }
+    }
+
+    @Test
+    public void testCompareAggStateDesc() {
+        AggregateFunction sum1 = AggregateFunction.createBuiltin(FunctionSet.SUM,
+                Lists.<Type>newArrayList(Type.INT), Type.BIGINT, Type.BIGINT, false, true, false);
+        AggStateDesc aggStateDesc1 = new AggStateDesc(sum1);
+        AggregateFunction sum2 = AggregateFunction.createBuiltin(FunctionSet.SUM,
+                Lists.<Type>newArrayList(Type.INT), Type.BIGINT, Type.BIGINT, false, true, false);
+        AggStateDesc aggStateDesc2 = new AggStateDesc(sum2);
+        Assert.assertEquals(aggStateDesc1, aggStateDesc2);
+        AggregateFunction sum3 = AggregateFunction.createBuiltin(FunctionSet.SUM,
+                Lists.<Type>newArrayList(Type.FLOAT), Type.DOUBLE, Type.DOUBLE, false, true, false);
+        AggStateDesc aggStateDesc3 = new AggStateDesc(sum3);
+        Assert.assertNotEquals(aggStateDesc3, aggStateDesc2);
+
+        AggStateDesc cloned3 = aggStateDesc3.clone();
+        Assert.assertEquals(aggStateDesc3, cloned3);
+    }
+}
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/CatalogRecycleBinLakeTableTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/CatalogRecycleBinLakeTableTest.java
index a7a4f0e06ca26e..3f63a7dd47abe4 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/CatalogRecycleBinLakeTableTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/CatalogRecycleBinLakeTableTest.java
@@ -57,8 +57,8 @@ public static void beforeClass() {
     private static Table createTable(ConnectContext connectContext, String sql) throws Exception {
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         GlobalStateMgr.getCurrentState().getLocalMetastore().createTable(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb(createTableStmt.getDbName());
-        return db.getTable(createTableStmt.getTableName());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(createTableStmt.getDbName());
+        return GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), createTableStmt.getTableName());
     }
 
     private static void dropTable(ConnectContext connectContext, String sql) throws Exception {
@@ -215,7 +215,7 @@ public LakeService getLakeService(TNetworkAddress address) throws RpcException {
 
         // Recover table2
         Assert.assertTrue(recycleBin.recoverTable(db, "t0"));
-        Assert.assertSame(table2, db.getTable("t0"));
+        Assert.assertSame(table2, GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t0"));
         Assert.assertNull(recycleBin.getTable(db.getId(), table2.getId()));
         checkTableTablet(table2, true);
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/ColocateTableIndexTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/ColocateTableIndexTest.java
index 23a6387ee02199..f7b9913933e0db 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/ColocateTableIndexTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/ColocateTableIndexTest.java
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-
 package com.starrocks.catalog;
 
 import com.starrocks.lake.LakeTable;
@@ -58,13 +57,13 @@ public void teardown() {
 
     /**
      * [
-     *   [10002.10006, 10002_group1, 10004, 10016, 4, 1, int(11), true],
-     *   [10026.10030, 10026_group2, 10028, 4, 1, int(11), true]
-     *  ]
+     * [10002.10006, 10002_group1, 10004, 10016, 4, 1, int(11), true],
+     * [10026.10030, 10026_group2, 10028, 4, 1, int(11), true]
+     * ]
      * ->
      * {
-     *   'group1': [10002.10006, 10002_group1, 10004, 10016, 4, 1, int(11), true],
-     *   'group2': [10026.10030, 10026_group2, 10028, 4, 1, int(11), true]
+     * 'group1': [10002.10006, 10002_group1, 10004, 10016, 4, 1, int(11), true],
+     * 'group2': [10026.10030, 10026_group2, 10028, 4, 1, int(11), true]
      * }
      */
     private Map<String, List<String>> groupByName(List<List<String>> lists) {
@@ -86,33 +85,33 @@ public void testDropTable() throws Exception {
 
         // create table1_1->group1
         String sql = "CREATE TABLE db1.table1_1 (k1 int, k2 int, k3 varchar(32))\n" +
-                "PRIMARY KEY(k1)\n" +
-                "DISTRIBUTED BY HASH(k1)\n" +
-                "BUCKETS 4\n" +
-                "PROPERTIES(\"colocate_with\"=\"group1\", \"replication_num\" = \"1\");\n";
+                    "PRIMARY KEY(k1)\n" +
+                    "DISTRIBUTED BY HASH(k1)\n" +
+                    "BUCKETS 4\n" +
+                    "PROPERTIES(\"colocate_with\"=\"group1\", \"replication_num\" = \"1\");\n";
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
         List<List<String>> infos = GlobalStateMgr.getCurrentState().getColocateTableIndex().getInfos();
         // group1->table1To1
         Assert.assertEquals(1, infos.size());
         Map<String, List<String>> map = groupByName(infos);
-        Table table1To1 = GlobalStateMgr.getCurrentState().getDb("db1").getTable("table1_1");
+        Table table1To1 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db1").getTable("table1_1");
         Assert.assertEquals(String.format("%d", table1To1.getId()), map.get("group1").get(2));
         LOG.info("after create db1.table1_1: {}", infos);
 
         // create table1_2->group1
         sql = "CREATE TABLE db1.table1_2 (k1 int, k2 int, k3 varchar(32))\n" +
-                "PRIMARY KEY(k1)\n" +
-                "DISTRIBUTED BY HASH(k1)\n" +
-                "BUCKETS 4\n" +
-                "PROPERTIES(\"colocate_with\"=\"group1\", \"replication_num\" = \"1\");\n";
+                    "PRIMARY KEY(k1)\n" +
+                    "DISTRIBUTED BY HASH(k1)\n" +
+                    "BUCKETS 4\n" +
+                    "PROPERTIES(\"colocate_with\"=\"group1\", \"replication_num\" = \"1\");\n";
         createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
         // group1 -> table1To1, table1To2
         infos = GlobalStateMgr.getCurrentState().getColocateTableIndex().getInfos();
         Assert.assertEquals(1, infos.size());
         map = groupByName(infos);
-        Table table1To2 = GlobalStateMgr.getCurrentState().getDb("db1").getTable("table1_2");
+        Table table1To2 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db1").getTable("table1_2");
         Assert.assertEquals(String.format("%d, %d", table1To1.getId(), table1To2.getId()), map.get("group1").get(2));
         LOG.info("after create db1.table1_2: {}", infos);
 
@@ -122,10 +121,10 @@ public void testDropTable() throws Exception {
         GlobalStateMgr.getCurrentState().getMetadata().createDb(createDbStmt.getFullDbName());
         // create table2_1 -> group2
         sql = "CREATE TABLE db2.table2_1 (k1 int, k2 int, k3 varchar(32))\n" +
-                "PRIMARY KEY(k1)\n" +
-                "DISTRIBUTED BY HASH(k1)\n" +
-                "BUCKETS 4\n" +
-                "PROPERTIES(\"colocate_with\"=\"group2\", \"replication_num\" = \"1\");\n";
+                    "PRIMARY KEY(k1)\n" +
+                    "DISTRIBUTED BY HASH(k1)\n" +
+                    "BUCKETS 4\n" +
+                    "PROPERTIES(\"colocate_with\"=\"group2\", \"replication_num\" = \"1\");\n";
         createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
         // group1 -> table1_1, table1_2
@@ -134,7 +133,7 @@ public void testDropTable() throws Exception {
         Assert.assertEquals(2, infos.size());
         map = groupByName(infos);
         Assert.assertEquals(String.format("%d, %d", table1To1.getId(), table1To2.getId()), map.get("group1").get(2));
-        Table table2To1 = GlobalStateMgr.getCurrentState().getDb("db2").getTable("table2_1");
+        Table table2To1 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db2").getTable("table2_1");
         Assert.assertEquals(String.format("%d", table2To1.getId()), map.get("group2").get(2));
         LOG.info("after create db2.table2_1: {}", infos);
 
@@ -162,12 +161,11 @@ public void testDropTable() throws Exception {
         Assert.assertEquals(2, infos.size());
         Assert.assertEquals(String.format("%d*, %d*", table1To1.getId(), table1To2.getId()), map.get("group1").get(2));
         Assert.assertEquals(String.format("[deleted], [deleted]", table1To1.getId(), table1To2.getId()),
-                map.get("group1").get(3));
+                    map.get("group1").get(3));
 
         Assert.assertEquals(String.format("%d", table2To1.getId()), map.get("group2").get(2));
         Assert.assertEquals(String.format("table2_1", table2To1.getId()), map.get("group2").get(3));
 
-
         LOG.info("after drop db1.table1_2: {}", infos);
 
         // drop db2
@@ -189,13 +187,13 @@ public void testDropTable() throws Exception {
         GlobalStateMgr.getCurrentState().getMetadata().createDb(createDbStmt.getFullDbName());
         // create table2_1 -> group2
         sql = "CREATE TABLE db2.table2_3 (k1 int, k2 int, k3 varchar(32))\n" +
-                "PRIMARY KEY(k1)\n" +
-                "DISTRIBUTED BY HASH(k1)\n" +
-                "BUCKETS 4\n" +
-                "PROPERTIES(\"colocate_with\"=\"group3\", \"replication_num\" = \"1\");\n";
+                    "PRIMARY KEY(k1)\n" +
+                    "DISTRIBUTED BY HASH(k1)\n" +
+                    "BUCKETS 4\n" +
+                    "PROPERTIES(\"colocate_with\"=\"group3\", \"replication_num\" = \"1\");\n";
         createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Table table2To3 = GlobalStateMgr.getCurrentState().getDb("db2").getTable("table2_3");
+        Table table2To3 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db2").getTable("table2_3");
         sql = "DROP DATABASE db2;";
         dropDbStmt = (DropDbStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         GlobalStateMgr.getCurrentState().getMetadata().dropDb(dropDbStmt.getDbName(), dropDbStmt.isForceDrop());
@@ -207,10 +205,10 @@ public void testDropTable() throws Exception {
         Assert.assertEquals("[deleted], [deleted]", map.get("group1").get(3));
         Assert.assertEquals(String.format("%d*", table2To1.getId()), map.get("group2").get(2));
         Assert.assertEquals(String.format("[deleted], [deleted]", table1To1.getId(), table1To2.getId()),
-                map.get("group1").get(3));
+                    map.get("group1").get(3));
         Assert.assertEquals(String.format("%d*", table2To3.getId()), map.get("group3").get(2));
         Assert.assertEquals(String.format("[deleted], [deleted]", table1To1.getId(), table1To2.getId()),
-                map.get("group1").get(3));
+                    map.get("group1").get(3));
     }
 
     @Test
@@ -221,31 +219,31 @@ public void testCleanUp() throws Exception {
         // create goodDb
         CreateDbStmt createDbStmt = (CreateDbStmt) UtFrameUtils.parseStmtWithNewParser("create database goodDb;", connectContext);
         GlobalStateMgr.getCurrentState().getMetadata().createDb(createDbStmt.getFullDbName());
-        Database goodDb = GlobalStateMgr.getCurrentState().getDb("goodDb");
+        Database goodDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("goodDb");
         // create goodtable
         String sql = "CREATE TABLE " +
-                "goodDb.goodTable (k1 int, k2 int, k3 varchar(32))\n" +
-                "PRIMARY KEY(k1)\n" +
-                "DISTRIBUTED BY HASH(k1)\n" +
-                "BUCKETS 4\n" +
-                "PROPERTIES(\"colocate_with\"=\"goodGroup\", \"replication_num\" = \"1\");\n";
+                    "goodDb.goodTable (k1 int, k2 int, k3 varchar(32))\n" +
+                    "PRIMARY KEY(k1)\n" +
+                    "DISTRIBUTED BY HASH(k1)\n" +
+                    "BUCKETS 4\n" +
+                    "PROPERTIES(\"colocate_with\"=\"goodGroup\", \"replication_num\" = \"1\");\n";
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        OlapTable table = (OlapTable) goodDb.getTable("goodTable");
+        OlapTable table =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(goodDb.getFullName(), "goodTable");
         ColocateTableIndex.GroupId goodGroup = GlobalStateMgr.getCurrentState().getColocateTableIndex().getGroup(table.getId());
 
-
         // create a bad db
         long badDbId = 4000;
         table.id = 4001;
         table.name = "goodTableOfBadDb";
         colocateTableIndex.addTableToGroup(
-                badDbId, table, "badGroupOfBadDb", new ColocateTableIndex.GroupId(badDbId, 4002), false);
+                    badDbId, table, "badGroupOfBadDb", new ColocateTableIndex.GroupId(badDbId, 4002), false);
         // create a bad table in good db
         table.id = 4003;
         table.name = "badTable";
         colocateTableIndex.addTableToGroup(
-                goodDb.getId(), table, "badGroupOfBadTable", new ColocateTableIndex.GroupId(goodDb.getId(), 4004), false);
+                    goodDb.getId(), table, "badGroupOfBadTable", new ColocateTableIndex.GroupId(goodDb.getId(), 4004), false);
 
         Map<String, List<String>> map = groupByName(GlobalStateMgr.getCurrentState().getColocateTableIndex().getInfos());
         Assert.assertTrue(map.containsKey("goodGroup"));
@@ -299,10 +297,11 @@ public List<Long> getShardGroupIds() {
         };
 
         colocateTableIndex.addTableToGroup(
-                dbId, (OlapTable) olapTable, "lakeGroup", new ColocateTableIndex.GroupId(dbId, 10000), false /* isReplay */);
+                    dbId, (OlapTable) olapTable, "lakeGroup", new ColocateTableIndex.GroupId(dbId, 10000), false /* isReplay */);
         Assert.assertTrue(colocateTableIndex.isLakeColocateTable(tableId));
         colocateTableIndex.addTableToGroup(
-                dbId2, (OlapTable) olapTable, "lakeGroup", new ColocateTableIndex.GroupId(dbId2, 10000), false /* isReplay */);
+                    dbId2, (OlapTable) olapTable, "lakeGroup", new ColocateTableIndex.GroupId(dbId2, 10000),
+                    false /* isReplay */);
         Assert.assertTrue(colocateTableIndex.isLakeColocateTable(tableId));
 
         Assert.assertTrue(colocateTableIndex.isGroupUnstable(new ColocateTableIndex.GroupId(dbId, 10000)));
@@ -319,19 +318,19 @@ public void testSaveLoadJsonFormatImage() throws Exception {
 
         // create goodDb
         CreateDbStmt createDbStmt = (CreateDbStmt) UtFrameUtils
-                .parseStmtWithNewParser("create database db_image;", connectContext);
+                    .parseStmtWithNewParser("create database db_image;", connectContext);
         GlobalStateMgr.getCurrentState().getMetadata().createDb(createDbStmt.getFullDbName());
-        Database db = GlobalStateMgr.getCurrentState().getDb("db_image");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db_image");
         // create goodtable
         String sql = "CREATE TABLE " +
-                "db_image.tbl1 (k1 int, k2 int, k3 varchar(32))\n" +
-                "PRIMARY KEY(k1)\n" +
-                "DISTRIBUTED BY HASH(k1)\n" +
-                "BUCKETS 4\n" +
-                "PROPERTIES(\"colocate_with\"=\"goodGroup\", \"replication_num\" = \"1\");\n";
+                    "db_image.tbl1 (k1 int, k2 int, k3 varchar(32))\n" +
+                    "PRIMARY KEY(k1)\n" +
+                    "DISTRIBUTED BY HASH(k1)\n" +
+                    "BUCKETS 4\n" +
+                    "PROPERTIES(\"colocate_with\"=\"goodGroup\", \"replication_num\" = \"1\");\n";
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        OlapTable table = (OlapTable) db.getTable("tbl1");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl1");
 
         UtFrameUtils.PseudoImage image = new UtFrameUtils.PseudoImage();
         colocateTableIndex.saveColocateTableIndexV2(image.getImageWriter());
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/ColocateTableTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/ColocateTableTest.java
index 028496b8f17712..8e9b33f90d3cd0 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/ColocateTableTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/ColocateTableTest.java
@@ -110,8 +110,8 @@ public void testCreateOneTable() throws Exception {
                 ");");
 
         ColocateTableIndex index = GlobalStateMgr.getCurrentState().getColocateTableIndex();
-        Database db = GlobalStateMgr.getCurrentState().getDb(fullDbName);
-        long tableId = db.getTable(tableName1).getId();
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(fullDbName);
+        long tableId = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName1).getId();
 
         Assert.assertEquals(1, Deencapsulation.<Multimap<GroupId, Long>>getField(index, "group2Tables").size());
         Assert.assertEquals(1, index.getAllGroupIds().size());
@@ -168,9 +168,9 @@ public void testCreateTwoTableWithSameGroup() throws Exception {
                 ");");
 
         ColocateTableIndex index = GlobalStateMgr.getCurrentState().getColocateTableIndex();
-        Database db = GlobalStateMgr.getCurrentState().getDb(fullDbName);
-        long firstTblId = db.getTable(tableName1).getId();
-        long secondTblId = db.getTable(tableName2).getId();
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(fullDbName);
+        long firstTblId = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName1).getId();
+        long secondTblId = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName2).getId();
 
         Assert.assertEquals(2, Deencapsulation.<Multimap<GroupId, Long>>getField(index, "group2Tables").size());
         Assert.assertEquals(1, index.getAllGroupIds().size());
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/ColumnTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/ColumnTest.java
index 7a74913ab0d3ec..7afa699aebc4a5 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/ColumnTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/ColumnTest.java
@@ -334,7 +334,7 @@ public void testSchemaChangeAllowedInvolvingDecimalv3() throws DdlException {
 
     @Test
     public void testLscColumn() {
-        Column f0 = new Column("f0", Type.INT, true, AggregateType.NONE, false,
+        Column f0 = new Column("f0", Type.INT, true, AggregateType.NONE, null, false,
                 new DefaultValueDef(true, NullLiteral.create(Type.INT)), "", 0);
 
         Index i0 = new Index("i0",
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/CreateTableLikeTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/CreateTableLikeTest.java
index db0d562b71077a..108d215e364ff8 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/CreateTableLikeTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/CreateTableLikeTest.java
@@ -76,7 +76,7 @@ private static void createTable(String sql) throws Exception {
 
     private static void createTableLike(String sql) throws Exception {
         CreateTableLikeStmt createTableLikeStmt =
-                (CreateTableLikeStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
+                    (CreateTableLikeStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         GlobalStateMgr.getCurrentState().getLocalMetastore().createTable(createTableLikeStmt.getCreateTableStmt());
     }
 
@@ -86,7 +86,7 @@ private static void checkTableEqual(Table newTable, Table existedTable) {
         List<String> existedTableStmt = Lists.newArrayList();
         AstToStringBuilder.getDdlStmt(existedTable, existedTableStmt, null, null, false, true /* hide password */);
         Assert.assertEquals(newCreateTableStmt.get(0).replace(newTable.getName(), existedTable.getName()),
-                existedTableStmt.get(0));
+                    existedTableStmt.get(0));
     }
 
     private static void checkCreateOlapTableLike(String createTableSql, String createTableLikeSql,
@@ -94,10 +94,12 @@ private static void checkCreateOlapTableLike(String createTableSql, String creat
                                                  String newTblName, String existedTblName) throws Exception {
         createTable(createTableSql);
         createTableLike(createTableLikeSql);
-        Database newDb = GlobalStateMgr.getCurrentState().getDb(newDbName);
-        Database existedDb = GlobalStateMgr.getCurrentState().getDb(existedDbName);
-        OlapTable newTbl = (OlapTable) newDb.getTable(newTblName);
-        OlapTable existedTbl = (OlapTable) existedDb.getTable(existedTblName);
+        Database newDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(newDbName);
+        Database existedDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(existedDbName);
+        OlapTable newTbl =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(newDb.getFullName(), newTblName);
+        OlapTable existedTbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(existedDb.getFullName(), existedTblName);
         checkTableEqual(newTbl, existedTbl);
     }
 
@@ -107,10 +109,12 @@ private static void checkCreateMysqlTableLike(String createTableSql, String crea
 
         createTable(createTableSql);
         createTableLike(createTableLikeSql);
-        Database newDb = GlobalStateMgr.getCurrentState().getDb(newDbName);
-        Database existedDb = GlobalStateMgr.getCurrentState().getDb(existedDbName);
-        MysqlTable newTbl = (MysqlTable) newDb.getTable(newTblName);
-        MysqlTable existedTbl = (MysqlTable) existedDb.getTable(existedTblName);
+        Database newDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(newDbName);
+        Database existedDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(existedDbName);
+        MysqlTable newTbl =
+                    (MysqlTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(newDb.getFullName(), newTblName);
+        MysqlTable existedTbl = (MysqlTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(existedDb.getFullName(), existedTblName);
         checkTableEqual(newTbl, existedTbl);
     }
 
@@ -118,7 +122,7 @@ private static void checkCreateMysqlTableLike(String createTableSql, String crea
     public void testNormal() throws Exception {
         // 1. creat table with single partition
         String createTableSql = "create table test.testTbl1\n" + "(k1 int, k2 int)\n" + "duplicate key(k1)\n"
-                + "distributed by hash(k2) buckets 1\n" + "properties('replication_num' = '1'); ";
+                    + "distributed by hash(k2) buckets 1\n" + "properties('replication_num' = '1'); ";
         String createTableLikeSql = "create table test.testTbl1_like like test.testTbl1";
         String newDbName = "test";
         String newTblName = "testTbl1_like";
@@ -126,157 +130,158 @@ public void testNormal() throws Exception {
         checkCreateOlapTableLike(createTableSql, createTableLikeSql, newDbName, newDbName, newTblName, existedTblName);
         // 2. create table with hash partition
         String createTableWithHashPartitionSql = "create table test.testTbl2\n" + "(k1 int, k2 int)\n"
-                + "duplicate key(k1)\n" + "partition by range(k2)\n" + "(partition p1 values less than(\"10\"))\n"
-                + "distributed by hash(k2) buckets 1\n" + "properties('replication_num' = '1'); ";
+                    + "duplicate key(k1)\n" + "partition by range(k2)\n" + "(partition p1 values less than(\"10\"))\n"
+                    + "distributed by hash(k2) buckets 1\n" + "properties('replication_num' = '1'); ";
         String createTableLikeSql2 = "create table test.testTbl2_like like test.testTbl2";
         String newDbName2 = "test";
         String newTblName2 = "testTbl2_like";
         String existedTblName2 = "testTbl2";
         checkCreateOlapTableLike(createTableWithHashPartitionSql, createTableLikeSql2, newDbName2, newDbName2,
-                newTblName2, existedTblName2);
+                    newTblName2, existedTblName2);
         // 3. create aggregate table
         String createAggTableSql3 = "create table test.testTbl3\n" + "(k1 varchar(40), k2 int, v1 int sum)\n"
-                + "partition by range(k2)\n" + "(partition p1 values less than(\"10\"))\n"
-                + "distributed by hash(k1) buckets 1\n" + "properties('replication_num' = '1');";
+                    + "partition by range(k2)\n" + "(partition p1 values less than(\"10\"))\n"
+                    + "distributed by hash(k1) buckets 1\n" + "properties('replication_num' = '1');";
         String createTableLikeSql3 = "create table test.testTbl3_like like test.testTbl3";
         String newDbName3 = "test";
         String newTblName3 = "testTbl3_like";
         String existedTblName3 = "testTbl3";
         checkCreateOlapTableLike(createAggTableSql3, createTableLikeSql3, newDbName3, newDbName3, newTblName3,
-                existedTblName3);
+                    existedTblName3);
         // 4. create aggregate table without partition
         String createAggTableWithoutPartitionSql4 =
-                "create table test.testTbl4\n" + "(k1 varchar(40), k2 int, k3 int)\n" + "duplicate key(k1, k2, k3)\n"
-                        + "partition by range(k2)\n" + "()\n"
-                        + "distributed by hash(k1) buckets 1\n" + "properties('replication_num' = '1');";
+                    "create table test.testTbl4\n" + "(k1 varchar(40), k2 int, k3 int)\n" + "duplicate key(k1, k2, k3)\n"
+                                + "partition by range(k2)\n" + "()\n"
+                                + "distributed by hash(k1) buckets 1\n" + "properties('replication_num' = '1');";
         String createTableLikeSql4 = "create table test.testTbl4_like like test.testTbl4";
         String newDbName4 = "test";
         String newTblName4 = "testTbl4_like";
         String existedTblName4 = "testTbl4";
         checkCreateOlapTableLike(createAggTableWithoutPartitionSql4, createTableLikeSql4, newDbName4, newDbName4,
-                newTblName4, existedTblName4);
+                    newTblName4, existedTblName4);
         // 5. create table from different db
         String createTableFromDiffDb5 =
-                "create table test.testTbl5\n" + "(k1 varchar(40), k2 int, k3 int)\n" + "duplicate key(k1, k2, k3)\n"
-                        + "partition by range(k2)\n" + "()\n"
-                        + "distributed by hash(k1) buckets 1\n" + "properties('replication_num' = '1');";
+                    "create table test.testTbl5\n" + "(k1 varchar(40), k2 int, k3 int)\n" + "duplicate key(k1, k2, k3)\n"
+                                + "partition by range(k2)\n" + "()\n"
+                                + "distributed by hash(k1) buckets 1\n" + "properties('replication_num' = '1');";
         String createTableLikeSql5 = "create table test2.testTbl5_like like test.testTbl5";
         String newDbName5 = "test2";
         String existedDbName5 = "test";
         String newTblName5 = "testTbl5_like";
         String existedTblName5 = "testTbl5";
         checkCreateOlapTableLike(createTableFromDiffDb5, createTableLikeSql5, newDbName5, existedDbName5, newTblName5,
-                existedTblName5);
+                    existedTblName5);
         // 6. create table from dynamic partition table
         String createDynamicTblSql = "CREATE TABLE test.`dynamic_partition_normal` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY RANGE (k1)\n" +
-                "(\n" +
-                "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
-                "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
-                "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"dynamic_partition.enable\" = \"false\",\n" +
-                "\"dynamic_partition.start\" = \"-3\",\n" +
-                "\"dynamic_partition.end\" = \"3\",\n" +
-                "\"dynamic_partition.time_unit\" = \"day\",\n" +
-                "\"dynamic_partition.prefix\" = \"p\",\n" +
-                "\"dynamic_partition.buckets\" = \"1\"\n" +
-                ");";
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY RANGE (k1)\n" +
+                    "(\n" +
+                    "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
+                    "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
+                    "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"dynamic_partition.enable\" = \"false\",\n" +
+                    "\"dynamic_partition.start\" = \"-3\",\n" +
+                    "\"dynamic_partition.end\" = \"3\",\n" +
+                    "\"dynamic_partition.time_unit\" = \"day\",\n" +
+                    "\"dynamic_partition.prefix\" = \"p\",\n" +
+                    "\"dynamic_partition.buckets\" = \"1\"\n" +
+                    ");";
         String createTableLikeSql6 =
-                "create table test.dynamic_partition_normal_like like test.dynamic_partition_normal";
+                    "create table test.dynamic_partition_normal_like like test.dynamic_partition_normal";
         String newDbName6 = "test";
         String newTblName6 = "dynamic_partition_normal_like";
         String existedTblName6 = "dynamic_partition_normal";
         checkCreateOlapTableLike(createDynamicTblSql, createTableLikeSql6, newDbName6, newDbName6, newTblName6,
-                existedTblName6);
+                    existedTblName6);
         // 7. create table from colocate table
         String createColocateTblSql = "create table test.colocateTbl (\n" +
-                " `k1` int NULL COMMENT \"\",\n" +
-                " `k2` varchar(10) NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`, `k2`) BUCKETS 1\n" +
-                "PROPERTIES (\n" +
-                " \"replication_num\" = \"1\",\n" +
-                " \"colocate_with\" = \"test_group\"\n" +
-                ");";
+                    " `k1` int NULL COMMENT \"\",\n" +
+                    " `k2` varchar(10) NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`, `k2`) BUCKETS 1\n" +
+                    "PROPERTIES (\n" +
+                    " \"replication_num\" = \"1\",\n" +
+                    " \"colocate_with\" = \"test_group\"\n" +
+                    ");";
         String createTableLikeSql7 = "create table test.colocateTbl_like like test.colocateTbl";
         String newDbName7 = "test";
         String newTblName7 = "colocateTbl_like";
         String existedTblName7 = "colocateTbl";
         checkCreateOlapTableLike(createColocateTblSql, createTableLikeSql7, newDbName7, newDbName7, newTblName7,
-                existedTblName7);
+                    existedTblName7);
         // 8. creat non-OLAP table
         String createNonOlapTableSql = "create table test.testMysqlTbl\n" +
-                "(k1 DATE, k2 INT, k3 SMALLINT, k4 VARCHAR(2048), k5 DATETIME)\n" +
-                "ENGINE=mysql\nPROPERTIES(\n" +
-                "\"host\" = \"127.0.0.1\",\n" +
-                "\"port\" = \"8239\",\n" +
-                "\"user\" = \"mysql_passwd\",\n" +
-                "\"password\" = \"mysql_passwd\",\n" +
-                "\"database\" = \"mysql_db_test\",\n" +
-                "\"table\" = \"mysql_table_test\");";
+                    "(k1 DATE, k2 INT, k3 SMALLINT, k4 VARCHAR(2048), k5 DATETIME)\n" +
+                    "ENGINE=mysql\nPROPERTIES(\n" +
+                    "\"host\" = \"127.0.0.1\",\n" +
+                    "\"port\" = \"8239\",\n" +
+                    "\"user\" = \"mysql_passwd\",\n" +
+                    "\"password\" = \"mysql_passwd\",\n" +
+                    "\"database\" = \"mysql_db_test\",\n" +
+                    "\"table\" = \"mysql_table_test\");";
         String createTableLikeSql8 = "create table test.testMysqlTbl_like like test.testMysqlTbl";
         String newDbName8 = "test";
         String existedDbName8 = "test";
         String newTblName8 = "testMysqlTbl_like";
         String existedTblName8 = "testMysqlTbl";
         checkCreateMysqlTableLike(createNonOlapTableSql, createTableLikeSql8, newDbName8, existedDbName8, newTblName8,
-                existedTblName8);
+                    existedTblName8);
         // 9. create automatic table
         String automaticTableSql = "CREATE TABLE test.`duplicate_table_with_null` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` datetime NULL COMMENT \"\",\n" +
-                "  `k3` char(20) NULL COMMENT \"\",\n" +
-                "  `k4` varchar(20) NULL COMMENT \"\",\n" +
-                "  `k5` boolean NULL COMMENT \"\",\n" +
-                "  `k6` tinyint(4) NULL COMMENT \"\",\n" +
-                "  `k7` smallint(6) NULL COMMENT \"\",\n" +
-                "  `k8` int(11) NULL COMMENT \"\",\n" +
-                "  `k9` bigint(20) NULL COMMENT \"\",\n" +
-                "  `k10` largeint(40) NULL COMMENT \"\",\n" +
-                "  `k11` float NULL COMMENT \"\",\n" +
-                "  `k12` double NULL COMMENT \"\",\n" +
-                "  `k13` decimal128(27, 9) NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP \n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`, `k4`, `k5`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY date_trunc('day', k1)\n" +
-                "DISTRIBUTED BY HASH(`k1`, `k2`, `k3`) BUCKETS 2 \n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"in_memory\" = \"false\",\n" +
-                "\"enable_persistent_index\" = \"false\",\n" +
-                "\"replicated_storage\" = \"true\",\n" +
-                "\"compression\" = \"LZ4\"\n" +
-                ");";
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` datetime NULL COMMENT \"\",\n" +
+                    "  `k3` char(20) NULL COMMENT \"\",\n" +
+                    "  `k4` varchar(20) NULL COMMENT \"\",\n" +
+                    "  `k5` boolean NULL COMMENT \"\",\n" +
+                    "  `k6` tinyint(4) NULL COMMENT \"\",\n" +
+                    "  `k7` smallint(6) NULL COMMENT \"\",\n" +
+                    "  `k8` int(11) NULL COMMENT \"\",\n" +
+                    "  `k9` bigint(20) NULL COMMENT \"\",\n" +
+                    "  `k10` largeint(40) NULL COMMENT \"\",\n" +
+                    "  `k11` float NULL COMMENT \"\",\n" +
+                    "  `k12` double NULL COMMENT \"\",\n" +
+                    "  `k13` decimal128(27, 9) NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP \n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`, `k4`, `k5`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY date_trunc('day', k1)\n" +
+                    "DISTRIBUTED BY HASH(`k1`, `k2`, `k3`) BUCKETS 2 \n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"in_memory\" = \"false\",\n" +
+                    "\"enable_persistent_index\" = \"false\",\n" +
+                    "\"replicated_storage\" = \"true\",\n" +
+                    "\"compression\" = \"LZ4\"\n" +
+                    ");";
         String createTableLikeSql9 = "create table test.table_like_02 like test.duplicate_table_with_null;";
         String newDbName9 = "test";
         String existedDbName9 = "test";
         String newTblName9 = "duplicate_table_with_null";
         String existedTblName9 = "table_like_02";
         checkCreateOlapTableLike(automaticTableSql, createTableLikeSql9, newDbName9, existedDbName9, newTblName9,
-                existedTblName9);
+                    existedTblName9);
 
         // 10. create table like with properties
         String sql = "create table test.table_like_10 " +
-                "distributed by random buckets 7 " +
-                "properties('replication_num'='1') " +
-                "like test.duplicate_table_with_null";
+                    "distributed by random buckets 7 " +
+                    "properties('replication_num'='1') " +
+                    "like test.duplicate_table_with_null";
         createTableLike(sql);
-        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getDb(newDbName).getTable("table_like_10");
+        OlapTable table =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(newDbName).getTable("table_like_10");
         Assert.assertEquals(new RandomDistributionInfo(7), table.getDefaultDistributionInfo());
         Assert.assertEquals("1", table.getProperties().get("replication_num"));
     }
@@ -285,23 +290,23 @@ public void testNormal() throws Exception {
     public void testAbnormal() {
         // 1. create table with same name
         String createTableSql = "create table test.testAbTbl1\n" + "(k1 int, k2 int)\n" + "duplicate key(k1)\n"
-                + "distributed by hash(k2) buckets 1\n" + "properties('replication_num' = '1'); ";
+                    + "distributed by hash(k2) buckets 1\n" + "properties('replication_num' = '1'); ";
         String createTableLikeSql = "create table test.testAbTbl1 like test.testAbTbl1";
         String newDbName = "test";
         String newTblName = "testAbTbl1";
         ExceptionChecker.expectThrowsWithMsg(AnalysisException.class, "Table 'testAbTbl1' already exists",
-                () -> checkCreateOlapTableLike(createTableSql, createTableLikeSql, newDbName, newDbName, newTblName,
-                        newTblName));
+                    () -> checkCreateOlapTableLike(createTableSql, createTableLikeSql, newDbName, newDbName, newTblName,
+                                newTblName));
         // 2. create table with not existed DB
         String createTableSql2 = "create table test.testAbTbl2\n" + "(k1 int, k2 int)\n" + "duplicate key(k1)\n"
-                + "distributed by hash(k2) buckets 1\n" + "properties('replication_num' = '1'); ";
+                    + "distributed by hash(k2) buckets 1\n" + "properties('replication_num' = '1'); ";
         String createTableLikeSql2 = "create table fake_test.testAbTbl2_like like test.testAbTbl1";
         String newDbName2 = "fake_test";
         String existedDbName2 = "test";
         String newTblName2 = "testAbTbl2_like";
         String existedTblName2 = "testAbTbl1";
         ExceptionChecker.expectThrowsWithMsg(AnalysisException.class, "Unknown database 'fake_test'",
-                () -> checkCreateOlapTableLike(createTableSql2, createTableLikeSql2, newDbName2, existedDbName2,
-                        newTblName2, existedTblName2));
+                    () -> checkCreateOlapTableLike(createTableSql2, createTableLikeSql2, newDbName2, existedDbName2,
+                                newTblName2, existedTblName2));
     }
 }
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/CreateTableTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/CreateTableTest.java
index b11b6d9f7bf653..0a2128db1abd39 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/CreateTableTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/CreateTableTest.java
@@ -297,13 +297,13 @@ public void testNormal() throws DdlException {
                         "    \"dynamic_partition.history_partition_num\" = \"0\"\n" +
                         ");"));
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl6 = (OlapTable) db.getTable("tbl6");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl6 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl6");
         Assert.assertTrue(tbl6.getColumn("k1").isKey());
         Assert.assertTrue(tbl6.getColumn("k2").isKey());
         Assert.assertTrue(tbl6.getColumn("k3").isKey());
 
-        OlapTable tbl7 = (OlapTable) db.getTable("tbl7");
+        OlapTable tbl7 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl7");
         Assert.assertTrue(tbl7.getColumn("k1").isKey());
         Assert.assertFalse(tbl7.getColumn("k2").isKey());
         Assert.assertTrue(tbl7.getColumn("k2").getAggregationType() == AggregateType.NONE);
@@ -331,7 +331,7 @@ public void testPartitionByExprDynamicPartition() {
                         "    \"dynamic_partition.buckets\" = \"32\",\n" +
                         "    \"dynamic_partition.history_partition_num\" = \"0\"\n" +
                         ");"));
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         Table str2dateTable = db.getTable("partition_str2date");
         Assert.assertTrue(DynamicPartitionUtil.isDynamicPartitionTable(str2dateTable));
 
@@ -682,7 +682,8 @@ public void testCreateTableWithoutDistribution() {
         ExceptionChecker.expectThrowsNoException(
                 () -> createTable("create table test.tmp1\n" + "(k1 int, k2 int)\n"));
         ExceptionChecker.expectThrowsNoException(
-                () -> createTable("create table test.tmp2\n" + "(k1 int, k2 float) PROPERTIES(\"replication_num\" = \"1\");\n"));
+                () -> createTable(
+                        "create table test.tmp2\n" + "(k1 int, k2 float) PROPERTIES(\"replication_num\" = \"1\");\n"));
         ExceptionChecker.expectThrowsWithMsg(AnalysisException.class, "Data type of first column cannot be HLL",
                 () -> createTable("create table test.tmp3\n" + "(k1 hll, k2 float)\n"));
     }
@@ -700,7 +701,7 @@ public void testCreateSumAgg() throws Exception {
                 "AGGREGATE KEY(id_int)\n" +
                 "DISTRIBUTED BY HASH(id_int) BUCKETS 10\n" +
                 "PROPERTIES(\"replication_num\" = \"1\");");
-        final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getDb(connectContext.getDatabase())
+        final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb(connectContext.getDatabase())
                 .getTable("aggregate_table_sum");
         String columns = table.getColumns().toString();
         System.out.println("columns = " + columns);
@@ -748,7 +749,7 @@ public void testLongColumnName() throws Exception {
                 "than_64_chars VARCHAR(100)) DISTRIBUTED BY HASH(oh_my_gosh_this_is_a_long_column_name_look_at_it_it_" +
                 "has_more_than_64_chars) BUCKETS 8 PROPERTIES(\"replication_num\" = \"1\");";
         starRocksAssert.withTable(sql);
-        final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getDb(connectContext.getDatabase())
+        final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb(connectContext.getDatabase())
                 .getTable("long_column_table");
         Assert.assertEquals(1, table.getColumns().size());
         Assert.assertNotNull(
@@ -771,7 +772,7 @@ public void testCreateTableDefaultCurrentTimestamp() throws Exception {
                 "    \"in_memory\" = \"false\"\n" +
                 ");";
         starRocksAssert.withTable(sql);
-        final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getDb(connectContext.getDatabase())
+        final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb(connectContext.getDatabase())
                 .getTable("test_create_default_current_timestamp");
         Assert.assertEquals(2, table.getColumns().size());
     }
@@ -792,7 +793,7 @@ public void testCreateTableDefaultUUID() throws Exception {
                 "    \"in_memory\" = \"false\"\n" +
                 ");";
         starRocksAssert.withTable(sql);
-        final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getDb(connectContext.getDatabase())
+        final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb(connectContext.getDatabase())
                 .getTable("test_create_default_uuid");
         Assert.assertEquals(2, table.getColumns().size());
 
@@ -809,7 +810,7 @@ public void testCreateTableDefaultUUID() throws Exception {
                 ");";
         starRocksAssert.withTable(sql2);
 
-        final Table table2 = starRocksAssert.getCtx().getGlobalStateMgr().getDb(connectContext.getDatabase())
+        final Table table2 = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb(connectContext.getDatabase())
                 .getTable("test_create_default_uuid_numeric");
         Assert.assertEquals(2, table2.getColumns().size());
     }
@@ -860,7 +861,7 @@ public void testCreateTableDefaultUUIDFailed() {
 
     @Test
     public void testCreateTableWithLocation() throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         // add label to backend
         SystemInfoService systemInfoService = GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo();
@@ -886,7 +887,8 @@ public void testCreateTableWithLocation() throws Exception {
                 "    \"in_memory\" = \"false\"\n" +
                 ");");
 
-        OlapTable table = (OlapTable) testDb.getTable("test_location_no_prop");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "test_location_no_prop");
         Assert.assertNotNull(table.getLocation());
         System.out.println(table.getLocation());
         Assert.assertTrue(table.getLocation().containsKey("*"));
@@ -895,7 +897,7 @@ public void testCreateTableWithLocation() throws Exception {
         String showSql = "show create table test.`test_location_no_prop`";
         ShowCreateTableStmt showCreateTableStmt = (ShowCreateTableStmt) UtFrameUtils.parseStmtWithNewParser(showSql,
                 connectContext);
-        
+
         ShowResultSet showResultSet = ShowExecutor.execute(showCreateTableStmt, connectContext);
         System.out.println(showResultSet.getResultRows());
         Assert.assertTrue(showResultSet.getResultRows().get(0).toString().contains("\"" +
@@ -920,7 +922,8 @@ public void testCreateTableWithLocation() throws Exception {
                 "    \"replication_num\" = \"1\",\n" +
                 "    \"in_memory\" = \"false\"\n" +
                 ");");
-        table = (OlapTable) testDb.getTable("test_location_no_backend_prop");
+        table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "test_location_no_backend_prop");
         Assert.assertNull(table.getLocation());
 
         // verify the location property in show create table result, shouldn't exist
@@ -985,7 +988,8 @@ public void testCreateTableWithLocation() throws Exception {
                 }
             } else {
                 createTable(createTableSql);
-                table = (OlapTable) testDb.getTable("test_location_prop_" + i);
+                table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(testDb.getFullName(), "test_location_prop_" + i);
                 if (tableLocationProp.isEmpty()) {
                     Assert.assertNull(table.getLocation());
                     continue;
@@ -1339,8 +1343,9 @@ public void testCreateTableWithBinlogProperties() {
                         ");"
         ));
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("binlog_table");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table =
+                (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "binlog_table");
         Assert.assertNotNull(table.getCurBinlogConfig());
         Assert.assertTrue(table.isBinlogEnabled());
 
@@ -1375,8 +1380,9 @@ public void testCreateTableWithoutBinlogProperties() {
                         ");"
         ));
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("not_binlog_table");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(db.getFullName(), "not_binlog_table");
 
         Assert.assertFalse(table.containsBinlogConfig());
         Assert.assertFalse(table.isBinlogEnabled());
@@ -1405,8 +1411,9 @@ public void testCreateTableWithConstraint() {
                         ");"
         ));
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("parent_table1");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table =
+                (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "parent_table1");
 
         Assert.assertTrue(table.hasUniqueConstraints());
         List<UniqueConstraint> uniqueConstraint = table.getUniqueConstraints();
@@ -1429,7 +1436,8 @@ public void testCreateTableWithConstraint() {
                         ");"
         ));
 
-        OlapTable table2 = (OlapTable) db.getTable("parent_table2");
+        OlapTable table2 =
+                (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "parent_table2");
 
         Assert.assertTrue(table2.hasUniqueConstraints());
         List<UniqueConstraint> uniqueConstraint2 = table2.getUniqueConstraints();
@@ -2049,8 +2057,8 @@ public void testReservedColumnName() {
         String sql1 = "create table tbl_simple_pk(key0 string, __op boolean) primary key(key0)" +
                 " distributed by hash(key0) properties(\"replication_num\"=\"1\");";
         ExceptionChecker.expectThrowsWithMsg(AnalysisException.class, "Getting analyzing error." +
-                " Detail message: Column name [__op] is a system reserved name." +
-                " If you are sure you want to use it, please set FE configuration allow_system_reserved_names",
+                        " Detail message: Column name [__op] is a system reserved name." +
+                        " If you are sure you want to use it, please set FE configuration allow_system_reserved_names",
                 () -> starRocksAssert.withTable(sql1));
     }
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/CreateTableWithAggStateTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/CreateTableWithAggStateTest.java
new file mode 100644
index 00000000000000..541e7011d5a42b
--- /dev/null
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/CreateTableWithAggStateTest.java
@@ -0,0 +1,302 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+package com.starrocks.catalog;
+
+import com.starrocks.common.Config;
+import com.starrocks.common.FeConstants;
+import com.starrocks.qe.ConnectContext;
+import com.starrocks.server.GlobalStateMgr;
+import com.starrocks.sql.ast.CreateDbStmt;
+import com.starrocks.utframe.StarRocksAssert;
+import com.starrocks.utframe.UtFrameUtils;
+import org.junit.Assert;
+import org.junit.BeforeClass;
+import org.junit.Test;
+
+public class CreateTableWithAggStateTest {
+    private static ConnectContext connectContext;
+    private static StarRocksAssert starRocksAssert;
+
+    @BeforeClass
+    public static void beforeClass() throws Exception {
+        UtFrameUtils.createMinStarRocksCluster();
+        Config.enable_strict_storage_medium_check = true;
+        Config.enable_auto_tablet_distribution = true;
+        Config.enable_experimental_rowstore = true;
+        Config.default_replication_num = 1;
+        FeConstants.enablePruneEmptyOutputScan = false;
+        // create connect context
+        connectContext = UtFrameUtils.createDefaultCtx();
+        starRocksAssert = new StarRocksAssert(connectContext);
+        // create database
+        String createDbStmtStr = "create database test;";
+        CreateDbStmt createDbStmt = (CreateDbStmt) UtFrameUtils.parseStmtWithNewParser(createDbStmtStr, connectContext);
+        GlobalStateMgr.getCurrentState().getMetadata().createDb(createDbStmt.getFullDbName());
+        starRocksAssert.useDatabase("test");
+        UtFrameUtils.setUpForPersistTest();
+    }
+
+    @Test
+    public void testCreateTableWithAggStateAvg() {
+        starRocksAssert.withTable("CREATE TABLE test_agg_tbl1(\n" +
+                        "  k1 VARCHAR(10),\n" +
+                        "  k6 avg(tinyint),\n" +
+                        "  k7 avg(smallint),\n" +
+                        "  k8 avg(int),\n" +
+                        "  k9 avg(bigint),\n" +
+                        "  k10 avg(largeint),\n" +
+                        "  k11 avg(float),\n" +
+                        "  k12 avg(double),\n" +
+                        "  k13 avg(decimal(10, 0))\n" +
+                        ")\n" +
+                        "AGGREGATE KEY(k1)\n" +
+                        "PARTITION BY (k1) \n" +
+                        "DISTRIBUTED BY HASH(k1) BUCKETS 3;",
+                () -> {
+                    final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore()
+                            .getDb(connectContext.getDatabase())
+                            .getTable("test_agg_tbl1");
+                    String columns = table.getColumns().toString();
+                    String expect = "[`k1` varchar(10) NULL COMMENT \"\", " +
+                            "`k10` varbinary avg(largeint(40)) NULL COMMENT \"\", " +
+                            "`k11` varbinary avg(float) NULL COMMENT \"\", " +
+                            "`k12` varbinary avg(double) NULL COMMENT \"\", " +
+                            "`k13` varbinary avg(decimal(10, 0)) NULL COMMENT \"\", " +
+                            "`k6` varbinary avg(tinyint(4)) NULL COMMENT \"\", " +
+                            "`k7` varbinary avg(smallint(6)) NULL COMMENT \"\", " +
+                            "`k8` varbinary avg(int(11)) NULL COMMENT \"\", " +
+                            "`k9` varbinary avg(bigint(20)) NULL COMMENT \"\"]";
+                    Assert.assertEquals(expect, columns);
+                });
+    }
+
+    @Test
+    public void testCreateTableWithAggStateSum() {
+        starRocksAssert.withTable("\n" +
+                "CREATE TABLE test_agg_tbl1(\n" +
+                "  k1 VARCHAR(10),\n" +
+                "  k2 datetime,\n" +
+                "  k6 sum(tinyint),\n" +
+                "  k7 sum(smallint),\n" +
+                "  k8 sum(int),\n" +
+                "  k9 sum(bigint),\n" +
+                "  k10 sum(largeint),\n" +
+                "  k11 sum(float),\n" +
+                "  k12 sum(double),\n" +
+                "  k13 sum(decimal(27,9))\n" +
+                ")\n" +
+                "AGGREGATE KEY(k1, k2)\n" +
+                "PARTITION BY (k1) \n" +
+                "DISTRIBUTED BY HASH(k1) BUCKETS 3;",
+                () -> {
+                    final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore()
+                            .getDb(connectContext.getDatabase())
+                            .getTable("test_agg_tbl1");
+                    String columns = table.getColumns().toString();
+                    String expect = "[`k1` varchar(10) NULL COMMENT \"\", " +
+                            "`k10` largeint(40) sum(largeint(40)) NULL COMMENT \"\", " +
+                            "`k11` double sum(float) NULL COMMENT \"\", " +
+                            "`k12` double sum(double) NULL COMMENT \"\", " +
+                            "`k13` decimal(38, 9) sum(decimal(27, 9)) NULL COMMENT \"\", " +
+                            "`k2` datetime NULL COMMENT \"\", " +
+                            "`k6` bigint(20) sum(tinyint(4)) NULL COMMENT \"\", " +
+                            "`k7` bigint(20) sum(smallint(6)) NULL COMMENT \"\", " +
+                            "`k8` bigint(20) sum(int(11)) NULL COMMENT \"\", " +
+                            "`k9` bigint(20) sum(bigint(20)) NULL COMMENT \"\"]";
+                        Assert.assertEquals(expect, columns);
+                });
+    }
+
+    @Test
+    public void testCreateTableWithAggStateHllSketch() {
+        starRocksAssert.withTable("\n" +
+                        "CREATE TABLE test_agg_tbl1 (\n" +
+                        "  dt VARCHAR(10),\n" +
+                        "  hll_id ds_hll_count_distinct(varchar not null),\n" +
+                        "  hll_province ds_hll_count_distinct(varchar),\n" +
+                        "  hll_age ds_hll_count_distinct(varchar, int),\n" +
+                        "  hll_dt ds_hll_count_distinct(varchar not null, int, varchar)\n" +
+                        ")\n" +
+                        "AGGREGATE KEY(dt)\n" +
+                        "PARTITION BY (dt) \n" +
+                        "DISTRIBUTED BY HASH(dt) BUCKETS 4;",
+                () -> {
+                    final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore()
+                            .getDb(connectContext.getDatabase())
+                            .getTable("test_agg_tbl1");
+                    String columns = table.getColumns().toString();
+                    String expect = "[`dt` varchar(10) NULL COMMENT \"\", " +
+                            "`hll_age` varbinary ds_hll_count_distinct(varchar, int(11)) NULL COMMENT \"\", " +
+                            "`hll_dt` varbinary ds_hll_count_distinct(varchar, int(11), varchar) NULL COMMENT \"\", " +
+                            "`hll_id` varbinary ds_hll_count_distinct(varchar) NULL COMMENT \"\", " +
+                            "`hll_province` varbinary ds_hll_count_distinct(varchar) NULL COMMENT \"\"]";
+                    Assert.assertEquals(expect, columns);
+                });
+    }
+
+    @Test
+    public void testCreateTableWithAggStateMinBy() {
+        starRocksAssert.withTable("\n" +
+                        "CREATE TABLE test_agg_tbl1(\n" +
+                        "  k1 VARCHAR(10),\n" +
+                        "  k2 min_by(datetime, date),\n" +
+                        "  k6 min_by(tinyint, date),\n" +
+                        "  k7 min_by(smallint, date),\n" +
+                        "  k8 min_by(int, date),\n" +
+                        "  k9 min_by(bigint, date),\n" +
+                        "  k10 min_by(largeint, date),\n" +
+                        "  k11 min_by(float, date),\n" +
+                        "  k12 min_by(double, date),\n" +
+                        "  k13 min_by(decimal(10, 0), date)\n" +
+                        ")\n" +
+                        "AGGREGATE KEY(k1)\n" +
+                        "PARTITION BY (k1) \n" +
+                        "DISTRIBUTED BY HASH(k1) BUCKETS 3;",
+                () -> {
+                    final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore()
+                            .getDb(connectContext.getDatabase())
+                            .getTable("test_agg_tbl1");
+                    String columns = table.getColumns().toString();
+                    String expect = "[`k1` varchar(10) NULL COMMENT \"\", " +
+                            "`k10` varbinary min_by(largeint(40), date) NULL COMMENT \"\", " +
+                            "`k11` varbinary min_by(float, date) NULL COMMENT \"\", " +
+                            "`k12` varbinary min_by(double, date) NULL COMMENT \"\", " +
+                            "`k13` varchar(1048576) min_by(decimal(10, 0), date) NULL COMMENT \"\", " +
+                            "`k2` varbinary min_by(datetime, date) NULL COMMENT \"\", " +
+                            "`k6` varbinary min_by(tinyint(4), date) NULL COMMENT \"\", " +
+                            "`k7` varbinary min_by(smallint(6), date) NULL COMMENT \"\", " +
+                            "`k8` varbinary min_by(int(11), date) NULL COMMENT \"\", " +
+                            "`k9` varbinary min_by(bigint(20), date) NULL COMMENT \"\"]";
+                    Assert.assertEquals(expect, columns);
+                });
+    }
+
+    @Test
+    public void testCreateTableWithAggStateArrayAgg() {
+        starRocksAssert.withTable("\n" +
+                        "CREATE TABLE test_agg_tbl1(\n" +
+                        "  k1 VARCHAR(10),\n" +
+                        "  k2 array_agg(datetime),\n" +
+                        "  k6 array_agg(tinyint),\n" +
+                        "  k7 array_agg(smallint),\n" +
+                        "  k8 array_agg(int),\n" +
+                        "  k9 array_agg(bigint),\n" +
+                        "  k10 array_agg(largeint),\n" +
+                        "  k11 array_agg(float),\n" +
+                        "  k12 array_agg(double),\n" +
+                        "  k13 array_agg(decimal(38,1))\n" +
+                        ")\n" +
+                        "AGGREGATE KEY(k1)\n" +
+                        "PARTITION BY (k1) \n" +
+                        "DISTRIBUTED BY HASH(k1) BUCKETS 3;",
+                () -> {
+                    final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore()
+                            .getDb(connectContext.getDatabase())
+                            .getTable("test_agg_tbl1");
+                    String columns = table.getColumns().toString();
+                    String expect = "[`k1` varchar(10) NULL COMMENT \"\", " +
+                            "`k10` struct<col1 array<largeint(40)>> array_agg(largeint(40)) NULL COMMENT \"\", " +
+                            "`k11` struct<col1 array<float>> array_agg(float) NULL COMMENT \"\", " +
+                            "`k12` struct<col1 array<double>> array_agg(double) NULL COMMENT \"\", " +
+                            "`k13` struct<col1 array<DECIMAL128(38,1)>> array_agg(decimal(38, 1)) NULL COMMENT \"\", " +
+                            "`k2` struct<col1 array<datetime>> array_agg(datetime) NULL COMMENT \"\", " +
+                            "`k6` struct<col1 array<tinyint(4)>> array_agg(tinyint(4)) NULL COMMENT \"\", " +
+                            "`k7` struct<col1 array<smallint(6)>> array_agg(smallint(6)) NULL COMMENT \"\", " +
+                            "`k8` struct<col1 array<int(11)>> array_agg(int(11)) NULL COMMENT \"\", " +
+                            "`k9` struct<col1 array<bigint(20)>> array_agg(bigint(20)) NULL COMMENT \"\"]";
+                    Assert.assertEquals(expect, columns);
+                });
+    }
+
+    @Test
+    public void testCreateTableWithAggStateGroupConcat() {
+        starRocksAssert.withTable("\n" +
+                        "CREATE TABLE test_agg_tbl1(\n" +
+                        "  k1 VARCHAR(10),\n" +
+                        "  k2 group_concat(datetime),\n" +
+                        "  k6 group_concat(tinyint),\n" +
+                        "  k7 group_concat(smallint),\n" +
+                        "  k8 group_concat(int),\n" +
+                        "  k9 group_concat(bigint),\n" +
+                        "  k10 group_concat(largeint),\n" +
+                        "  k11 group_concat(float),\n" +
+                        "  k12 group_concat(double),\n" +
+                        "  k13 group_concat(decimal(21, 10))\n" +
+                        ")\n" +
+                        "AGGREGATE KEY(k1)\n" +
+                        "PARTITION BY (k1) \n" +
+                        "DISTRIBUTED BY HASH(k1) BUCKETS 3;",
+                () -> {
+                    final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore()
+                            .getDb(connectContext.getDatabase())
+                            .getTable("test_agg_tbl1");
+                    String columns = table.getColumns().toString();
+                    String expect = "[`k1` varchar(10) NULL COMMENT \"\", " +
+                            "`k10` struct<col1 array<varchar(1048576)>> group_concat(largeint(40)) NULL COMMENT \"\", " +
+                            "`k11` struct<col1 array<varchar(1048576)>> group_concat(float) NULL COMMENT \"\", " +
+                            "`k12` struct<col1 array<varchar(1048576)>> group_concat(double) NULL COMMENT \"\", " +
+                            "`k13` struct<col1 array<varchar(1048576)>> group_concat(decimal(21, 10)) NULL COMMENT \"\", " +
+                            "`k2` struct<col1 array<varchar(1048576)>> group_concat(datetime) NULL COMMENT \"\", " +
+                            "`k6` struct<col1 array<varchar(1048576)>> group_concat(tinyint(4)) NULL COMMENT \"\", " +
+                            "`k7` struct<col1 array<varchar(1048576)>> group_concat(smallint(6)) NULL COMMENT \"\", " +
+                            "`k8` struct<col1 array<varchar(1048576)>> group_concat(int(11)) NULL COMMENT \"\", " +
+                            "`k9` struct<col1 array<varchar(1048576)>> group_concat(bigint(20)) NULL COMMENT \"\"]";
+                    Assert.assertEquals(expect, columns);
+                });
+    }
+
+    @Test
+    public void testCreateTableWithAggStateBadCase1() {
+        try {
+            starRocksAssert.withTable("\n" +
+                    "CREATE TABLE test_agg_tbl1(\n" +
+                    "  k1 VARCHAR(10),\n" +
+                    "  k2 group_concat(datetime),\n" +
+                    "  k13 group_concat(decimal)\n" +
+                    ")\n" +
+                    "AGGREGATE KEY(k1)\n" +
+                    "PARTITION BY (k1) \n" +
+                    "DISTRIBUTED BY HASH(k1) BUCKETS 3;");
+            final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore()
+                    .getDb(connectContext.getDatabase())
+                    .getTable("test_agg_tbl1");
+            Assert.assertEquals(null, table);
+        } catch (Exception e) {
+            Assert.assertTrue(e.getMessage().contains("AggStateType function group_concat with input DECIMAL64(10,0) has " +
+                    "wildcard decimal."));
+        }
+    }
+
+    @Test
+    public void testCreateTableWithAggStateBadCase2() {
+        try {
+            starRocksAssert.withTable("\n" +
+                    "CREATE TABLE test_agg_tbl1(\n" +
+                    "  k1 VARCHAR(10),\n" +
+                    "  k2 group_concat(datetime) not null,\n" +
+                    "  k13 group_concat(decimal(10, 2))\n" +
+                    ")\n" +
+                    "AGGREGATE KEY(k1)\n" +
+                    "PARTITION BY (k1) \n" +
+                    "DISTRIBUTED BY HASH(k1) BUCKETS 3;");
+            final Table table = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore()
+                    .getDb(connectContext.getDatabase())
+                    .getTable("test_agg_tbl1");
+            Assert.assertEquals(null, table);
+        } catch (Exception e) {
+            Assert.assertTrue(e.getMessage().contains("Agg state column k2 must be nullable column."));
+        }
+    }
+}
\ No newline at end of file
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/CreateTableWithLocationTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/CreateTableWithLocationTest.java
index edc7791a91c9ef..d1809b2a25fca5 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/CreateTableWithLocationTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/CreateTableWithLocationTest.java
@@ -75,7 +75,7 @@ private void clearBackendLocationProp() throws SQLException {
         PseudoCluster cluster = PseudoCluster.getInstance();
         for (PseudoBackend backend : cluster.getBackends()) {
             String stmtStr = "alter system modify backend '" + backend.getHostHeartbeatPort() + "' set ('" +
-                    AlterSystemStmtAnalyzer.PROP_KEY_LOCATION + "' = '')";
+                        AlterSystemStmtAnalyzer.PROP_KEY_LOCATION + "' = '')";
             System.out.println(stmtStr);
             cluster.runSql(null, stmtStr);
         }
@@ -86,32 +86,32 @@ private void setBackendLocationProp(List<String> locations) throws SQLException
         int i = 0;
         for (PseudoBackend backend : cluster.getBackends()) {
             String stmtStr = "alter system modify backend '" + backend.getHostHeartbeatPort() + "' set ('" +
-                    AlterSystemStmtAnalyzer.PROP_KEY_LOCATION + "' = '" + locations.get(i++) +  "')";
+                        AlterSystemStmtAnalyzer.PROP_KEY_LOCATION + "' = '" + locations.get(i++) + "')";
             System.out.println(stmtStr);
             cluster.runSql(null, stmtStr);
         }
     }
 
-
     @Test
     public void testCreateTableAndBackendNoLocationProp() throws SQLException {
         clearBackendLocationProp();
         PseudoCluster cluster = PseudoCluster.getInstance();
         String sql = "CREATE TABLE test.`test_table_backend_no_loc` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 2\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"3\",\n" +
-                "    \"in_memory\" = \"false\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 2\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"3\",\n" +
+                    "    \"in_memory\" = \"false\"\n" +
+                    ");";
         cluster.runSql("test", sql);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("test_table_backend_no_loc");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "test_table_backend_no_loc");
         Assert.assertNull(table.getLocation());
     }
 
@@ -120,7 +120,7 @@ private Set<Long> getBackendIdsWithLocProp() {
         Set<Long> backendIds = Sets.newHashSet();
         for (PseudoBackend pseudoBackend : cluster.getBackends()) {
             Backend backend = GlobalStateMgr.getCurrentState().getNodeMgr()
-                    .getClusterInfo().getBackend(pseudoBackend.getId());
+                        .getClusterInfo().getBackend(pseudoBackend.getId());
             if (!backend.getLocation().isEmpty()) {
                 backendIds.add(backend.getId());
             }
@@ -133,7 +133,7 @@ private Set<Long> getBackendIdsWithLocProp(String locationKey) {
         Set<Long> backendIds = Sets.newHashSet();
         for (PseudoBackend pseudoBackend : cluster.getBackends()) {
             Backend backend = GlobalStateMgr.getCurrentState().getNodeMgr()
-                    .getClusterInfo().getBackend(pseudoBackend.getId());
+                        .getClusterInfo().getBackend(pseudoBackend.getId());
             if (backend.getLocation().containsKey(locationKey)) {
                 backendIds.add(backend.getId());
             }
@@ -146,9 +146,9 @@ private Set<Long> getBackendIdsWithLocProp(String locationKey, String locationVa
         Set<Long> backendIds = Sets.newHashSet();
         for (PseudoBackend pseudoBackend : cluster.getBackends()) {
             Backend backend = GlobalStateMgr.getCurrentState().getNodeMgr()
-                    .getClusterInfo().getBackend(pseudoBackend.getId());
+                        .getClusterInfo().getBackend(pseudoBackend.getId());
             if (backend.getLocation().containsKey(locationKey) &&
-                    Objects.equals(backend.getLocation().get(locationKey), locationVal)) {
+                        Objects.equals(backend.getLocation().get(locationKey), locationVal)) {
                 backendIds.add(backend.getId());
             }
         }
@@ -160,7 +160,7 @@ private Set<Long> getBackendIdsWithoutLocProp() {
         Set<Long> backendIds = Sets.newHashSet();
         for (PseudoBackend pseudoBackend : cluster.getBackends()) {
             Backend backend = GlobalStateMgr.getCurrentState().getNodeMgr()
-                    .getClusterInfo().getBackend(pseudoBackend.getId());
+                        .getClusterInfo().getBackend(pseudoBackend.getId());
             if (backend.getLocation().isEmpty()) {
                 backendIds.add(backend.getId());
             }
@@ -172,24 +172,25 @@ private Set<Long> getBackendIdsWithoutLocProp() {
     public void testCreateTableNoLocPropBackendWithLocProp() throws SQLException {
         // last backend doesn't contain location property
         List<String> locations = Lists.newArrayList("rack:r1", "rack:rack2", "rack:rack3",
-                "region:r1", "region:r2", "region:r3", "");
+                    "region:r1", "region:r2", "region:r3", "");
         setBackendLocationProp(locations);
         PseudoCluster cluster = PseudoCluster.getInstance();
         String sql = "CREATE TABLE test.`test_table_no_loc_backend_with_loc` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"3\",\n" +
-                "    \"in_memory\" = \"false\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"3\",\n" +
+                    "    \"in_memory\" = \"false\"\n" +
+                    ");";
         cluster.runSql("test", sql);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("test_table_no_loc_backend_with_loc");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "test_table_no_loc_backend_with_loc");
         Assert.assertTrue(table.getLocation().keySet().contains("*"));
 
         List<Partition> partitions = new ArrayList<>(table.getAllPartitions());
@@ -215,27 +216,28 @@ public void testCreateTableNoLocPropBackendWithLocProp() throws SQLException {
     public void testCreateTableWithExplicitLocPropBackendWithLocProp() throws SQLException {
         // last backend doesn't contain location property
         List<String> locations = Lists.newArrayList("rack:r1", "rack:rack2", "rack:rack3",
-                "region:r1", "region:r2", "region:r3", "");
+                    "region:r1", "region:r2", "region:r3", "");
         setBackendLocationProp(locations);
         PseudoCluster cluster = PseudoCluster.getInstance();
 
         // Test: rack:*
         String sql = "CREATE TABLE test.`test_table_explicit_loc_backend_with_loc1` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"3\",\n" +
-                "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION +  "\" = \"rack:*\",\n" +
-                "    \"in_memory\" = \"false\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"3\",\n" +
+                    "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "\" = \"rack:*\",\n" +
+                    "    \"in_memory\" = \"false\"\n" +
+                    ");";
         System.out.println(sql);
         cluster.runSql("test", sql);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("test_table_explicit_loc_backend_with_loc1");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "test_table_explicit_loc_backend_with_loc1");
         Assert.assertTrue(table.getLocation().keySet().contains("rack"));
         List<Partition> partitions = new ArrayList<>(table.getAllPartitions());
         List<Tablet> tablets = partitions.get(0).getBaseIndex().getTablets();
@@ -259,21 +261,22 @@ public void testCreateTableWithExplicitLocPropBackendWithLocProp() throws SQLExc
 
         // Test: rack:*, region:*
         sql = "CREATE TABLE test.`test_table_explicit_loc_backend_with_loc2` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"3\",\n" +
-                "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION +  "\" = \"rack:*, region:*\",\n" +
-                "    \"in_memory\" = \"false\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"3\",\n" +
+                    "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "\" = \"rack:*, region:*\",\n" +
+                    "    \"in_memory\" = \"false\"\n" +
+                    ");";
         cluster.runSql("test", sql);
         boolean hasReplicaOnRegionBackend = false;
         boolean hasReplicaOnRackBackend = false;
-        table = (OlapTable) db.getTable("test_table_explicit_loc_backend_with_loc2");
+        table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "test_table_explicit_loc_backend_with_loc2");
         Assert.assertTrue(table.getLocation().keySet().contains("rack"));
         Assert.assertTrue(table.getLocation().keySet().contains("region"));
         partitions = new ArrayList<>(table.getAllPartitions());
@@ -299,19 +302,20 @@ public void testCreateTableWithExplicitLocPropBackendWithLocProp() throws SQLExc
 
         // Test: rack:r1, rack:rack2, rack:rack3
         sql = "CREATE TABLE test.`test_table_explicit_loc_backend_with_loc3` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"3\",\n" +
-                "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION +  "\" = \"rack:r1, rack:rack2, rack:rack3\",\n" +
-                "    \"in_memory\" = \"false\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"3\",\n" +
+                    "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "\" = \"rack:r1, rack:rack2, rack:rack3\",\n" +
+                    "    \"in_memory\" = \"false\"\n" +
+                    ");";
         cluster.runSql("test", sql);
-        table = (OlapTable) db.getTable("test_table_explicit_loc_backend_with_loc3");
+        table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "test_table_explicit_loc_backend_with_loc3");
         Assert.assertTrue(table.getLocation().keySet().contains("rack"));
         Assert.assertEquals(1, table.getLocation().keySet().size());
         partitions = new ArrayList<>(table.getAllPartitions());
@@ -333,19 +337,20 @@ public void testCreateTableWithExplicitLocPropBackendWithLocProp() throws SQLExc
 
         // Test: rack:r1, region:*
         sql = "CREATE TABLE test.`test_table_explicit_loc_backend_with_loc4` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"3\",\n" +
-                "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION +  "\" = \"rack:r1, region:*\",\n" +
-                "    \"in_memory\" = \"false\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"3\",\n" +
+                    "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "\" = \"rack:r1, region:*\",\n" +
+                    "    \"in_memory\" = \"false\"\n" +
+                    ");";
         cluster.runSql("test", sql);
-        table = (OlapTable) db.getTable("test_table_explicit_loc_backend_with_loc4");
+        table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "test_table_explicit_loc_backend_with_loc4");
         Assert.assertTrue(table.getLocation().keySet().contains("rack"));
         Assert.assertTrue(table.getLocation().keySet().contains("region"));
         partitions = new ArrayList<>(table.getAllPartitions());
@@ -372,19 +377,20 @@ public void testCreateTableWithExplicitLocPropBackendWithLocProp() throws SQLExc
 
         // Test: rack:r1, rack:rack2, not enough hosts, fallback to ignore location prop
         sql = "CREATE TABLE test.`test_table_explicit_loc_backend_with_loc5` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"3\",\n" +
-                "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION +  "\" = \"rack:r1, rack:rack2\",\n" +
-                "    \"in_memory\" = \"false\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"3\",\n" +
+                    "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "\" = \"rack:r1, rack:rack2\",\n" +
+                    "    \"in_memory\" = \"false\"\n" +
+                    ");";
         cluster.runSql("test", sql);
-        table = (OlapTable) db.getTable("test_table_explicit_loc_backend_with_loc5");
+        table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "test_table_explicit_loc_backend_with_loc5");
         Assert.assertTrue(table.getLocation().keySet().contains("rack"));
         partitions = new ArrayList<>(table.getAllPartitions());
         tablets = partitions.get(0).getBaseIndex().getTablets();
@@ -403,27 +409,27 @@ public void testCreateTableWithExplicitLocPropBackendWithLocProp() throws SQLExc
         backendIdsWithLocProp = getBackendIdsWithLocProp();
         backendIdsWithLocProp.addAll(getBackendIdsWithoutLocProp());
         Assert.assertEquals(backendIdsWithLocProp.size(),
-                Sets.intersection(allReplicasBackendIds, backendIdsWithLocProp).size());
+                    Sets.intersection(allReplicasBackendIds, backendIdsWithLocProp).size());
 
         // Test: rack:r1, rack:rack2, not enough hosts, fallback to ignore location prop
         sql = "CREATE TABLE test.`test_table_explicit_loc_backend_with_loc6` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"10\",\n" +
-                "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION +  "\" = \"rack:r1, rack:rack2\",\n" +
-                "    \"in_memory\" = \"false\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"10\",\n" +
+                    "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "\" = \"rack:r1, rack:rack2\",\n" +
+                    "    \"in_memory\" = \"false\"\n" +
+                    ");";
 
         try {
             cluster.runSql("test", sql);
         } catch (Exception e) {
             Assert.assertTrue(e.getMessage().contains(
-                    "Table replication num should be less than of equal to the number of available BE nodes"));
+                        "Table replication num should be less than of equal to the number of available BE nodes"));
         }
 
         // clean up
@@ -434,27 +440,28 @@ public void testCreateTableWithExplicitLocPropBackendWithLocProp() throws SQLExc
     public void testBestEffortMatchLocationProp() throws SQLException {
         // last backend has the same location prop with the first one
         List<String> locations = Lists.newArrayList("rack:r1", "rack:rack2", "rack:rack3",
-                "region:r1", "region:r2", "region:r3", "rack:r1");
+                    "region:r1", "region:r2", "region:r3", "rack:r1");
         setBackendLocationProp(locations);
         PseudoCluster cluster = PseudoCluster.getInstance();
 
         // Test: rack:r1, rack:rack2, 3 hosts, but only 2 racks
         String sql = "CREATE TABLE test.`test_table_explicit_loc_backend_with_loc_best_effort` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"3\",\n" +
-                "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION +  "\" = \"rack:r1, rack:rack2\",\n" +
-                "    \"in_memory\" = \"false\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"3\",\n" +
+                    "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "\" = \"rack:r1, rack:rack2\",\n" +
+                    "    \"in_memory\" = \"false\"\n" +
+                    ");";
         System.out.println(sql);
         cluster.runSql("test", sql);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("test_table_explicit_loc_backend_with_loc_best_effort");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "test_table_explicit_loc_backend_with_loc_best_effort");
         Assert.assertTrue(table.getLocation().keySet().contains("rack"));
         List<Partition> partitions = new ArrayList<>(table.getAllPartitions());
         List<Tablet> tablets = partitions.get(0).getBaseIndex().getTablets();
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/CreateViewTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/CreateViewTest.java
index 19d14ccb17db78..23b2495b99eb1c 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/CreateViewTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/CreateViewTest.java
@@ -74,7 +74,7 @@ public void testCreateViewNullable() throws Exception {
                 .withView("create view test_null_view as select * from site_access;");
 
         Table view = starRocksAssert.getCtx().getGlobalStateMgr()
-                .getDb("test").getTable("test_null_view");
+                .getLocalMetastore().getDb("test").getTable("test_null_view");
         Assert.assertTrue(view instanceof View);
         List<Column> columns = view.getColumns();
         for (Column column : columns) {
@@ -135,7 +135,7 @@ public void testCreateViewWithWindowFunctionIgnoreNulls() throws Exception {
                         ", lead(price ignore nulls,1,0) over (partition by username) as leadValue\n" +
                         "from sample_data;");
 
-        Table view = starRocksAssert.getCtx().getGlobalStateMgr()
+        Table view = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore()
                 .getDb("test").getTable("test_ignore_nulls");
         Assert.assertTrue(view instanceof View);
         String str = ((View) view).getInlineViewDef();
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/DropPartitionTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/DropPartitionTest.java
index 85084573217677..ab5109b561a54f 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/DropPartitionTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/DropPartitionTest.java
@@ -97,8 +97,8 @@ private void dropPartition(String sql) throws Exception {
 
     @Test
     public void testNormalDropPartition() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("tbl1");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl1");
         Partition partition = table.getPartition("p20210201");
         long tabletId = partition.getBaseIndex().getTablets().get(0).getId();
         String dropPartitionSql = " alter table test.tbl1 drop partition p20210201;";
@@ -119,8 +119,8 @@ public void testNormalDropPartition() throws Exception {
 
     @Test
     public void testForceDropPartition() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("tbl1");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl1");
         Partition partition = table.getPartition("p20210202");
         long tabletId = partition.getBaseIndex().getTablets().get(0).getId();
         String dropPartitionSql = " alter table test.tbl1 drop partition p20210202 force;";
@@ -144,8 +144,8 @@ public void testForceDropPartition() throws Exception {
 
     @Test
     public void testDropPartitionAndReserveTablets() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("tbl1");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl1");
         Partition partition = table.getPartition("p20210203");
         long tabletId = partition.getBaseIndex().getTablets().get(0).getId();
         table.dropPartitionAndReserveTablet("p20210203");
@@ -249,8 +249,8 @@ private void checkForceDropPartitions(String dropPartitionSql) throws Exception
     }
 
     private void checkBeforeDrop(String dbName, String tableName, String partitionName, long tabletId) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
-        OlapTable table = (OlapTable) db.getTable(tableName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         List<Replica> replicaList =
                 GlobalStateMgr.getCurrentState().getTabletInvertedIndex().getReplicasByTabletId(tabletId);
         Partition partition = table.getPartition(partitionName);
@@ -273,7 +273,7 @@ private Partition recoverPartition(String db, String table, String partitionName
     }
 
     private Table getTable(String dbName, String tableName) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
-        return (OlapTable) db.getTable(tableName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
+        return (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
     }
 }
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/DynamicPartitionTableTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/DynamicPartitionTableTest.java
index 3fc83355accdd1..bc4ef7e0074c5d 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/DynamicPartitionTableTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/DynamicPartitionTableTest.java
@@ -78,34 +78,35 @@ private static void createTable(String sql) throws Exception {
     @Test
     public void testNormal() throws Exception {
         starRocksAssert.withTable("CREATE TABLE test.`dynamic_partition_normal` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY RANGE (k1)\n" +
-                "(\n" +
-                "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
-                "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
-                "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"dynamic_partition.enable\" = \"true\",\n" +
-                "\"dynamic_partition.start\" = \"-3\",\n" +
-                "\"dynamic_partition.end\" = \"3\",\n" +
-                "\"dynamic_partition.time_unit\" = \"day\",\n" +
-                "\"dynamic_partition.prefix\" = \"p\",\n" +
-                "\"dynamic_partition.buckets\" = \"1\"\n" +
-                ");");
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("dynamic_partition_normal");
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY RANGE (k1)\n" +
+                    "(\n" +
+                    "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
+                    "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
+                    "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"dynamic_partition.enable\" = \"true\",\n" +
+                    "\"dynamic_partition.start\" = \"-3\",\n" +
+                    "\"dynamic_partition.end\" = \"3\",\n" +
+                    "\"dynamic_partition.time_unit\" = \"day\",\n" +
+                    "\"dynamic_partition.prefix\" = \"p\",\n" +
+                    "\"dynamic_partition.buckets\" = \"1\"\n" +
+                    ");");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "dynamic_partition_normal");
         Assert.assertEquals(table.getTableProperty().getDynamicPartitionProperty().getReplicationNum(),
-                DynamicPartitionProperty.NOT_SET_REPLICATION_NUM);
+                    DynamicPartitionProperty.NOT_SET_REPLICATION_NUM);
     }
 
     @Test
@@ -113,57 +114,57 @@ public void testMissTimeUnit() throws Exception {
         expectedException.expect(DdlException.class);
         expectedException.expectMessage("Must assign dynamic_partition.time_unit properties");
         starRocksAssert.withTable("CREATE TABLE test.`dynamic_partition_time_unit` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY RANGE (k1)\n" +
-                "(\n" +
-                "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
-                "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
-                "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"dynamic_partition.enable\" = \"true\",\n" +
-                "\"dynamic_partition.start\" = \"-3\",\n" +
-                "\"dynamic_partition.end\" = \"3\",\n" +
-                "\"dynamic_partition.prefix\" = \"p\",\n" +
-                "\"dynamic_partition.buckets\" = \"1\"\n" +
-                ");");
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY RANGE (k1)\n" +
+                    "(\n" +
+                    "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
+                    "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
+                    "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"dynamic_partition.enable\" = \"true\",\n" +
+                    "\"dynamic_partition.start\" = \"-3\",\n" +
+                    "\"dynamic_partition.end\" = \"3\",\n" +
+                    "\"dynamic_partition.prefix\" = \"p\",\n" +
+                    "\"dynamic_partition.buckets\" = \"1\"\n" +
+                    ");");
     }
 
     @Test
     public void testMissStart() throws Exception {
         starRocksAssert.withTable("CREATE TABLE test.`dynamic_partition_start` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY RANGE (k1)\n" +
-                "(\n" +
-                "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
-                "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
-                "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"dynamic_partition.enable\" = \"true\",\n" +
-                "\"dynamic_partition.end\" = \"3\",\n" +
-                "\"dynamic_partition.time_unit\" = \"day\",\n" +
-                "\"dynamic_partition.prefix\" = \"p\",\n" +
-                "\"dynamic_partition.buckets\" = \"1\"\n" +
-                ");");
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY RANGE (k1)\n" +
+                    "(\n" +
+                    "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
+                    "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
+                    "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"dynamic_partition.enable\" = \"true\",\n" +
+                    "\"dynamic_partition.end\" = \"3\",\n" +
+                    "\"dynamic_partition.time_unit\" = \"day\",\n" +
+                    "\"dynamic_partition.prefix\" = \"p\",\n" +
+                    "\"dynamic_partition.buckets\" = \"1\"\n" +
+                    ");");
     }
 
     @Test
@@ -171,59 +172,60 @@ public void testMissEnd() throws Exception {
         expectedException.expect(DdlException.class);
         expectedException.expectMessage("Must assign dynamic_partition.end properties");
         starRocksAssert.withTable("CREATE TABLE test.`dynamic_partition_end` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY RANGE (k1)\n" +
-                "(\n" +
-                "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
-                "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
-                "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"dynamic_partition.enable\" = \"true\",\n" +
-                "\"dynamic_partition.start\" = \"-3\",\n" +
-                "\"dynamic_partition.time_unit\" = \"day\",\n" +
-                "\"dynamic_partition.prefix\" = \"p\",\n" +
-                "\"dynamic_partition.buckets\" = \"1\"\n" +
-                ");");
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY RANGE (k1)\n" +
+                    "(\n" +
+                    "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
+                    "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
+                    "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"dynamic_partition.enable\" = \"true\",\n" +
+                    "\"dynamic_partition.start\" = \"-3\",\n" +
+                    "\"dynamic_partition.time_unit\" = \"day\",\n" +
+                    "\"dynamic_partition.prefix\" = \"p\",\n" +
+                    "\"dynamic_partition.buckets\" = \"1\"\n" +
+                    ");");
     }
 
     @Test
     public void testMissBuckets() throws Exception {
         starRocksAssert.withTable("CREATE TABLE test.`dynamic_partition_buckets` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY RANGE (k1)\n" +
-                "(\n" +
-                "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
-                "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
-                "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"dynamic_partition.enable\" = \"true\",\n" +
-                "\"dynamic_partition.start\" = \"-3\",\n" +
-                "\"dynamic_partition.end\" = \"3\",\n" +
-                "\"dynamic_partition.time_unit\" = \"day\",\n" +
-                "\"dynamic_partition.prefix\" = \"p\"\n" +
-                ");");
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("dynamic_partition_buckets");
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY RANGE (k1)\n" +
+                    "(\n" +
+                    "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
+                    "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
+                    "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"dynamic_partition.enable\" = \"true\",\n" +
+                    "\"dynamic_partition.start\" = \"-3\",\n" +
+                    "\"dynamic_partition.end\" = \"3\",\n" +
+                    "\"dynamic_partition.time_unit\" = \"day\",\n" +
+                    "\"dynamic_partition.prefix\" = \"p\"\n" +
+                    ");");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "dynamic_partition_buckets");
         Assert.assertEquals(table.getTableProperty().getDynamicPartitionProperty().getBuckets(), 0);
     }
 
@@ -232,24 +234,24 @@ public void testNotAllowed() throws Exception {
         expectedException.expect(DdlException.class);
         expectedException.expectMessage("Only support dynamic partition properties on range partition table");
         starRocksAssert.withTable("CREATE TABLE test.`dynamic_partition_non_range` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"dynamic_partition.enable\" = \"true\",\n" +
-                "\"dynamic_partition.start\" = \"-3\",\n" +
-                "\"dynamic_partition.end\" = \"3\",\n" +
-                "\"dynamic_partition.time_unit\" = \"day\",\n" +
-                "\"dynamic_partition.prefix\" = \"p\",\n" +
-                "\"dynamic_partition.buckets\" = \"1\"\n" +
-                ");");
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"dynamic_partition.enable\" = \"true\",\n" +
+                    "\"dynamic_partition.start\" = \"-3\",\n" +
+                    "\"dynamic_partition.end\" = \"3\",\n" +
+                    "\"dynamic_partition.time_unit\" = \"day\",\n" +
+                    "\"dynamic_partition.prefix\" = \"p\",\n" +
+                    "\"dynamic_partition.buckets\" = \"1\"\n" +
+                    ");");
     }
 
     @Test
@@ -257,89 +259,89 @@ public void testNotAllowedInMultiPartitions() throws Exception {
         expectedException.expect(DdlException.class);
         expectedException.expectMessage("Dynamic partition only support single-column range partition");
         starRocksAssert.withTable("CREATE TABLE test.`dynamic_partition_normal` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY RANGE (k1, k2)\n" +
-                "(\n" +
-                "PARTITION p1 VALUES LESS THAN (\"2014-01-01\", \"100\"),\n" +
-                "PARTITION p2 VALUES LESS THAN (\"2014-06-01\", \"200\"),\n" +
-                "PARTITION p3 VALUES LESS THAN (\"2014-12-01\", \"300\")\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"dynamic_partition.enable\" = \"true\",\n" +
-                "\"dynamic_partition.start\" = \"-3\",\n" +
-                "\"dynamic_partition.end\" = \"3\",\n" +
-                "\"dynamic_partition.time_unit\" = \"day\",\n" +
-                "\"dynamic_partition.prefix\" = \"p\",\n" +
-                "\"dynamic_partition.buckets\" = \"1\"\n" +
-                ");");
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY RANGE (k1, k2)\n" +
+                    "(\n" +
+                    "PARTITION p1 VALUES LESS THAN (\"2014-01-01\", \"100\"),\n" +
+                    "PARTITION p2 VALUES LESS THAN (\"2014-06-01\", \"200\"),\n" +
+                    "PARTITION p3 VALUES LESS THAN (\"2014-12-01\", \"300\")\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"dynamic_partition.enable\" = \"true\",\n" +
+                    "\"dynamic_partition.start\" = \"-3\",\n" +
+                    "\"dynamic_partition.end\" = \"3\",\n" +
+                    "\"dynamic_partition.time_unit\" = \"day\",\n" +
+                    "\"dynamic_partition.prefix\" = \"p\",\n" +
+                    "\"dynamic_partition.buckets\" = \"1\"\n" +
+                    ");");
     }
 
     @Test
     public void testMissTimeZone() throws Exception {
         starRocksAssert.withTable("CREATE TABLE test.`dynamic_partition_miss_time_zone` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY RANGE (k1)\n" +
-                "(\n" +
-                "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
-                "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
-                "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"dynamic_partition.enable\" = \"true\",\n" +
-                "\"dynamic_partition.start\" = \"-3\",\n" +
-                "\"dynamic_partition.end\" = \"3\",\n" +
-                "\"dynamic_partition.buckets\" = \"3\",\n" +
-                "\"dynamic_partition.time_unit\" = \"day\",\n" +
-                "\"dynamic_partition.prefix\" = \"p\"\n" +
-                ");");
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY RANGE (k1)\n" +
+                    "(\n" +
+                    "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
+                    "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
+                    "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"dynamic_partition.enable\" = \"true\",\n" +
+                    "\"dynamic_partition.start\" = \"-3\",\n" +
+                    "\"dynamic_partition.end\" = \"3\",\n" +
+                    "\"dynamic_partition.buckets\" = \"3\",\n" +
+                    "\"dynamic_partition.time_unit\" = \"day\",\n" +
+                    "\"dynamic_partition.prefix\" = \"p\"\n" +
+                    ");");
     }
 
     @Test
     public void testNormalTimeZone() throws Exception {
         starRocksAssert.withTable("CREATE TABLE test.`dynamic_partition_time_zone` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY RANGE (k1)\n" +
-                "(\n" +
-                "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
-                "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
-                "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"dynamic_partition.enable\" = \"true\",\n" +
-                "\"dynamic_partition.start\" = \"-3\",\n" +
-                "\"dynamic_partition.end\" = \"3\",\n" +
-                "\"dynamic_partition.buckets\" = \"3\",\n" +
-                "\"dynamic_partition.time_unit\" = \"day\",\n" +
-                "\"dynamic_partition.time_zone\" = \"Asia/Shanghai\",\n" +
-                "\"dynamic_partition.prefix\" = \"p\"\n" +
-                ");");
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY RANGE (k1)\n" +
+                    "(\n" +
+                    "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
+                    "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
+                    "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"dynamic_partition.enable\" = \"true\",\n" +
+                    "\"dynamic_partition.start\" = \"-3\",\n" +
+                    "\"dynamic_partition.end\" = \"3\",\n" +
+                    "\"dynamic_partition.buckets\" = \"3\",\n" +
+                    "\"dynamic_partition.time_unit\" = \"day\",\n" +
+                    "\"dynamic_partition.time_zone\" = \"Asia/Shanghai\",\n" +
+                    "\"dynamic_partition.prefix\" = \"p\"\n" +
+                    ");");
     }
 
     @Test
@@ -347,96 +349,96 @@ public void testInvalidTimeZone() throws Exception {
         expectedException.expect(DdlException.class);
         expectedException.expectMessage("Unknown or incorrect time zone: 'invalid'");
         starRocksAssert.withTable("CREATE TABLE test.`dynamic_partition_invalid_time_zone` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY RANGE (k1)\n" +
-                "(\n" +
-                "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
-                "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
-                "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"dynamic_partition.enable\" = \"true\",\n" +
-                "\"dynamic_partition.start\" = \"-3\",\n" +
-                "\"dynamic_partition.end\" = \"3\",\n" +
-                "\"dynamic_partition.buckets\" = \"3\",\n" +
-                "\"dynamic_partition.time_unit\" = \"day\",\n" +
-                "\"dynamic_partition.time_zone\" = \"invalid\",\n" +
-                "\"dynamic_partition.prefix\" = \"p\"\n" +
-                ");");
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY RANGE (k1)\n" +
+                    "(\n" +
+                    "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
+                    "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
+                    "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"dynamic_partition.enable\" = \"true\",\n" +
+                    "\"dynamic_partition.start\" = \"-3\",\n" +
+                    "\"dynamic_partition.end\" = \"3\",\n" +
+                    "\"dynamic_partition.buckets\" = \"3\",\n" +
+                    "\"dynamic_partition.time_unit\" = \"day\",\n" +
+                    "\"dynamic_partition.time_zone\" = \"invalid\",\n" +
+                    "\"dynamic_partition.prefix\" = \"p\"\n" +
+                    ");");
     }
 
     @Test
     public void testSetDynamicPartitionReplicationNum() throws Exception {
         String tableName = "dynamic_partition_replication_num";
         starRocksAssert.withTable("CREATE TABLE test.`" + tableName + "` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY RANGE (k1)\n" +
-                "(\n" +
-                "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
-                "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
-                "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"dynamic_partition.enable\" = \"true\",\n" +
-                "\"dynamic_partition.start\" = \"-3\",\n" +
-                "\"dynamic_partition.end\" = \"3\",\n" +
-                "\"dynamic_partition.time_unit\" = \"day\",\n" +
-                "\"dynamic_partition.prefix\" = \"p\",\n" +
-                "\"dynamic_partition.buckets\" = \"1\",\n" +
-                "\"dynamic_partition.replication_num\" = \"2\"\n" +
-                ");");
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable(tableName);
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY RANGE (k1)\n" +
+                    "(\n" +
+                    "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
+                    "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"),\n" +
+                    "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"dynamic_partition.enable\" = \"true\",\n" +
+                    "\"dynamic_partition.start\" = \"-3\",\n" +
+                    "\"dynamic_partition.end\" = \"3\",\n" +
+                    "\"dynamic_partition.time_unit\" = \"day\",\n" +
+                    "\"dynamic_partition.prefix\" = \"p\",\n" +
+                    "\"dynamic_partition.buckets\" = \"1\",\n" +
+                    "\"dynamic_partition.replication_num\" = \"2\"\n" +
+                    ");");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         Assert.assertEquals(table.getTableProperty().getDynamicPartitionProperty().getReplicationNum(), 2);
     }
 
     @Test
     public void testEmptyDynamicPartition() throws Exception {
         String createOlapTblStmt = "CREATE TABLE test.`empty_dynamic_partition` (\n" +
-                "  `k1` date NULL COMMENT \"\",\n" +
-                "  `k2` int NULL COMMENT \"\",\n" +
-                "  `k3` smallint NULL COMMENT \"\",\n" +
-                "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
-                "  `v2` datetime NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY RANGE(`k1`)\n" +
-                "()\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"dynamic_partition.enable\" = \"false\",\n" +
-                "\"dynamic_partition.start\" = \"-3\",\n" +
-                "\"dynamic_partition.end\" = \"3\",\n" +
-                "\"dynamic_partition.time_unit\" = \"day\",\n" +
-                "\"dynamic_partition.prefix\" = \"p\",\n" +
-                "\"dynamic_partition.buckets\" = \"1\"\n" +
-                ");";
+                    "  `k1` date NULL COMMENT \"\",\n" +
+                    "  `k2` int NULL COMMENT \"\",\n" +
+                    "  `k3` smallint NULL COMMENT \"\",\n" +
+                    "  `v1` varchar(2048) NULL COMMENT \"\",\n" +
+                    "  `v2` datetime NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`, `k2`, `k3`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY RANGE(`k1`)\n" +
+                    "()\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 32\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"dynamic_partition.enable\" = \"false\",\n" +
+                    "\"dynamic_partition.start\" = \"-3\",\n" +
+                    "\"dynamic_partition.end\" = \"3\",\n" +
+                    "\"dynamic_partition.time_unit\" = \"day\",\n" +
+                    "\"dynamic_partition.prefix\" = \"p\",\n" +
+                    "\"dynamic_partition.buckets\" = \"1\"\n" +
+                    ");";
         String insertStmt =
-                "insert into test.`empty_dynamic_partition` values ('2020-09-10', 1000, 100, 'test', '2020-09-10 23:59:59');";
+                    "insert into test.`empty_dynamic_partition` values ('2020-09-10', 1000, 100, 'test', '2020-09-10 23:59:59');";
         createTable(createOlapTblStmt);
         expectedException.expect(AnalysisException.class);
         expectedException.expectMessage("data cannot be inserted into table with empty partition." +
-                "Use `SHOW PARTITIONS FROM empty_dynamic_partition` to see the currently partitions of this table. ");
+                    "Use `SHOW PARTITIONS FROM empty_dynamic_partition` to see the currently partitions of this table. ");
         UtFrameUtils.parseStmtWithNewParser("explain " + insertStmt, connectContext);
     }
 }
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/ExpressionRangePartitionInfoTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/ExpressionRangePartitionInfoTest.java
index d630940b6c9ac0..3c6d77872f1534 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/ExpressionRangePartitionInfoTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/ExpressionRangePartitionInfoTest.java
@@ -58,7 +58,6 @@ public class ExpressionRangePartitionInfoTest {
     private static ConnectContext connectContext;
     private static StarRocksAssert starRocksAssert;
 
-
     @Before
     public void setUp() throws Exception {
         partitionExprs = Lists.newArrayList();
@@ -71,7 +70,7 @@ public void setUp() throws Exception {
         fnChildren.add(slotRef2);
         functionCallExpr = new FunctionCallExpr("date_trunc", fnChildren);
         functionCallExpr.setFn(Expr.getBuiltinFunction(
-                "date_trunc", new Type[] {Type.VARCHAR, Type.DATETIME}, Function.CompareMode.IS_IDENTICAL));
+                    "date_trunc", new Type[] {Type.VARCHAR, Type.DATETIME}, Function.CompareMode.IS_IDENTICAL));
 
         FeConstants.runningUnitTest = true;
         UtFrameUtils.createMinStarRocksCluster();
@@ -90,9 +89,9 @@ public void testInitUseSlotRef() {
         partitionExprs.add(ColumnIdExpr.create(slotRef));
         List<Column> schema = Collections.singletonList(k1);
         ExpressionRangePartitionInfo expressionRangePartitionInfo = new ExpressionRangePartitionInfo(partitionExprs,
-                schema, PartitionType.RANGE);
+                    schema, PartitionType.RANGE);
         List<Column> partitionColumns = expressionRangePartitionInfo.getPartitionColumns(
-                MetaUtils.buildIdToColumn(schema));
+                    MetaUtils.buildIdToColumn(schema));
         Assert.assertEquals(partitionColumns.size(), 1);
         Assert.assertEquals(partitionColumns.get(0), k1);
     }
@@ -102,9 +101,9 @@ public void testInitUseFunction() {
         partitionExprs.add(ColumnIdExpr.create(functionCallExpr));
         List<Column> schema = Collections.singletonList(k2);
         ExpressionRangePartitionInfo expressionRangePartitionInfo =
-                new ExpressionRangePartitionInfo(partitionExprs, schema, PartitionType.RANGE);
+                    new ExpressionRangePartitionInfo(partitionExprs, schema, PartitionType.RANGE);
         List<Column> partitionColumns = expressionRangePartitionInfo.getPartitionColumns(
-                MetaUtils.buildIdToColumn(schema));
+                    MetaUtils.buildIdToColumn(schema));
         Assert.assertEquals(partitionColumns.size(), 1);
         Assert.assertEquals(partitionColumns.get(0), k2);
     }
@@ -117,9 +116,9 @@ public void testInitHybrid() {
         partitionExprs.add(ColumnIdExpr.create(functionCallExpr));
         List<Column> schema = Arrays.asList(k1, k2);
         ExpressionRangePartitionInfo expressionRangePartitionInfo =
-                new ExpressionRangePartitionInfo(partitionExprs, schema, PartitionType.RANGE);
+                    new ExpressionRangePartitionInfo(partitionExprs, schema, PartitionType.RANGE);
         List<Column> partitionColumns = expressionRangePartitionInfo.getPartitionColumns(
-                MetaUtils.buildIdToColumn(schema));
+                    MetaUtils.buildIdToColumn(schema));
         Assert.assertEquals(partitionColumns.size(), 2);
         Assert.assertEquals(partitionColumns.get(0), k1);
         Assert.assertEquals(partitionColumns.get(1), k2);
@@ -135,15 +134,15 @@ public void testTinyInt() throws DdlException, AnalysisException {
         partitionExprs.add(ColumnIdExpr.create(slotRef));
 
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p1",
-                new PartitionKeyDesc(Lists.newArrayList(new PartitionValue("-128"))),
-                null));
+                    new PartitionKeyDesc(Lists.newArrayList(new PartitionValue("-128"))),
+                    null));
 
         List<Column> schema = Collections.singletonList(k1);
         partitionInfo = new ExpressionRangePartitionInfo(partitionExprs, schema, PartitionType.RANGE);
         for (SingleRangePartitionDesc singleRangePartitionDesc : singleRangePartitionDescs) {
             singleRangePartitionDesc.analyze(1, null);
             partitionInfo.handleNewSinglePartitionDesc(MetaUtils.buildIdToColumn(schema),
-                    singleRangePartitionDesc, 20000L, false);
+                        singleRangePartitionDesc, 20000L, false);
         }
     }
 
@@ -154,15 +153,15 @@ public void testSmallInt() throws DdlException, AnalysisException {
         partitionExprs.add(ColumnIdExpr.create(slotRef));
 
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p1",
-                new PartitionKeyDesc(Lists.newArrayList(new PartitionValue("-32768"))),
-                null));
+                    new PartitionKeyDesc(Lists.newArrayList(new PartitionValue("-32768"))),
+                    null));
 
         List<Column> schema = Collections.singletonList(k1);
         partitionInfo = new ExpressionRangePartitionInfo(partitionExprs, schema, PartitionType.RANGE);
         for (SingleRangePartitionDesc singleRangePartitionDesc : singleRangePartitionDescs) {
             singleRangePartitionDesc.analyze(1, null);
             partitionInfo.handleNewSinglePartitionDesc(MetaUtils.buildIdToColumn(schema),
-                    singleRangePartitionDesc, 20000L, false);
+                        singleRangePartitionDesc, 20000L, false);
         }
     }
 
@@ -173,15 +172,15 @@ public void testInt() throws DdlException, AnalysisException {
         partitionExprs.add(ColumnIdExpr.create(slotRef));
 
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p1",
-                new PartitionKeyDesc(Lists.newArrayList(new PartitionValue("-2147483648"))),
-                null));
+                    new PartitionKeyDesc(Lists.newArrayList(new PartitionValue("-2147483648"))),
+                    null));
 
         List<Column> schema = Collections.singletonList(k1);
         partitionInfo = new ExpressionRangePartitionInfo(partitionExprs, schema, PartitionType.RANGE);
         for (SingleRangePartitionDesc singleRangePartitionDesc : singleRangePartitionDescs) {
             singleRangePartitionDesc.analyze(1, null);
             partitionInfo.handleNewSinglePartitionDesc(MetaUtils.buildIdToColumn(schema), singleRangePartitionDesc,
-                    20000L, false);
+                        20000L, false);
         }
     }
 
@@ -192,13 +191,13 @@ public void testBigInt() throws DdlException, AnalysisException {
         partitionExprs.add(ColumnIdExpr.create(slotRef));
 
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p1", new PartitionKeyDesc(Lists
-                .newArrayList(new PartitionValue("-9223372036854775808"))), null));
+                    .newArrayList(new PartitionValue("-9223372036854775808"))), null));
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p2", new PartitionKeyDesc(Lists
-                .newArrayList(new PartitionValue("-9223372036854775806"))), null));
+                    .newArrayList(new PartitionValue("-9223372036854775806"))), null));
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p3", new PartitionKeyDesc(Lists
-                .newArrayList(new PartitionValue("0"))), null));
+                    .newArrayList(new PartitionValue("0"))), null));
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p4", new PartitionKeyDesc(Lists
-                .newArrayList(new PartitionValue("9223372036854775806"))), null));
+                    .newArrayList(new PartitionValue("9223372036854775806"))), null));
 
         List<Column> schema = Collections.singletonList(k1);
         partitionInfo = new ExpressionRangePartitionInfo(partitionExprs, schema, PartitionType.RANGE);
@@ -206,7 +205,7 @@ public void testBigInt() throws DdlException, AnalysisException {
         for (SingleRangePartitionDesc singleRangePartitionDesc : singleRangePartitionDescs) {
             singleRangePartitionDesc.analyze(1, null);
             partitionInfo.handleNewSinglePartitionDesc(MetaUtils.buildIdToColumn(schema), singleRangePartitionDesc,
-                    20000L, false);
+                        20000L, false);
         }
     }
 
@@ -217,13 +216,13 @@ public void testBigIntNormal() throws DdlException, AnalysisException {
         partitionExprs.add(ColumnIdExpr.create(slotRef));
 
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p1", new PartitionKeyDesc(Lists
-                .newArrayList(new PartitionValue("-9223372036854775806"))), null));
+                    .newArrayList(new PartitionValue("-9223372036854775806"))), null));
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p2", new PartitionKeyDesc(Lists
-                .newArrayList(new PartitionValue("-9223372036854775805"))), null));
+                    .newArrayList(new PartitionValue("-9223372036854775805"))), null));
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p3", new PartitionKeyDesc(Lists
-                .newArrayList(new PartitionValue("0"))), null));
+                    .newArrayList(new PartitionValue("0"))), null));
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p4", new PartitionKeyDesc(Lists
-                .newArrayList(new PartitionValue("9223372036854775806"))), null));
+                    .newArrayList(new PartitionValue("9223372036854775806"))), null));
 
         List<Column> schema = Collections.singletonList(k1);
         partitionInfo = new ExpressionRangePartitionInfo(partitionExprs, schema, PartitionType.RANGE);
@@ -231,7 +230,7 @@ public void testBigIntNormal() throws DdlException, AnalysisException {
         for (SingleRangePartitionDesc singleRangePartitionDesc : singleRangePartitionDescs) {
             singleRangePartitionDesc.analyze(1, null);
             partitionInfo.handleNewSinglePartitionDesc(MetaUtils.buildIdToColumn(schema), singleRangePartitionDesc,
-                    20000L, false);
+                        20000L, false);
         }
     }
 
@@ -256,17 +255,17 @@ public void testFixedRange() throws DdlException, AnalysisException {
 
         //add RangePartitionDescs
         PartitionKeyDesc p1 = new PartitionKeyDesc(
-                Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("100")),
-                Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("200")));
+                    Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("100")),
+                    Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("200")));
         PartitionKeyDesc p2 = new PartitionKeyDesc(
-                Lists.newArrayList(new PartitionValue("20190105"), new PartitionValue("10")),
-                Lists.newArrayList(new PartitionValue("20190107"), new PartitionValue("10")));
+                    Lists.newArrayList(new PartitionValue("20190105"), new PartitionValue("10")),
+                    Lists.newArrayList(new PartitionValue("20190107"), new PartitionValue("10")));
         PartitionKeyDesc p3 = new PartitionKeyDesc(
-                Lists.newArrayList(new PartitionValue("20181231"), new PartitionValue("10")),
-                Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("100")));
+                    Lists.newArrayList(new PartitionValue("20181231"), new PartitionValue("10")),
+                    Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("100")));
         PartitionKeyDesc p4 = new PartitionKeyDesc(
-                Lists.newArrayList(new PartitionValue("20190105"), new PartitionValue("100")),
-                Lists.newArrayList(new PartitionValue("20190120"), new PartitionValue("10000000000")));
+                    Lists.newArrayList(new PartitionValue("20190105"), new PartitionValue("100")),
+                    Lists.newArrayList(new PartitionValue("20190120"), new PartitionValue("10000000000")));
 
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p1", p1, null));
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p2", p2, null));
@@ -279,7 +278,7 @@ public void testFixedRange() throws DdlException, AnalysisException {
         for (SingleRangePartitionDesc singleRangePartitionDesc : singleRangePartitionDescs) {
             singleRangePartitionDesc.analyze(columns, null);
             partitionInfo.handleNewSinglePartitionDesc(MetaUtils.buildIdToColumn(schema), singleRangePartitionDesc,
-                    20000L, false);
+                        20000L, false);
         }
     }
 
@@ -306,14 +305,14 @@ public void testFixedRange1() throws DdlException, AnalysisException {
 
         //add RangePartitionDescs
         PartitionKeyDesc p1 = new PartitionKeyDesc(
-                Lists.newArrayList(new PartitionValue("2019-02-01"), new PartitionValue("100"),
-                        new PartitionValue("200")));
+                    Lists.newArrayList(new PartitionValue("2019-02-01"), new PartitionValue("100"),
+                                new PartitionValue("200")));
         PartitionKeyDesc p2 = new PartitionKeyDesc(
-                Lists.newArrayList(new PartitionValue("2020-02-01"), new PartitionValue("100"),
-                        new PartitionValue("200")),
-                Lists.newArrayList(new PartitionValue("10000000000")));
+                    Lists.newArrayList(new PartitionValue("2020-02-01"), new PartitionValue("100"),
+                                new PartitionValue("200")),
+                    Lists.newArrayList(new PartitionValue("10000000000")));
         PartitionKeyDesc p3 = new PartitionKeyDesc(
-                Lists.newArrayList(new PartitionValue("2021-02-01")));
+                    Lists.newArrayList(new PartitionValue("2021-02-01")));
 
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p1", p1, null));
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p2", p2, null));
@@ -331,7 +330,7 @@ public void testFixedRange1() throws DdlException, AnalysisException {
             }
             singleRangePartitionDesc.analyze(partitionExprs.size(), null);
             partitionInfo.handleNewSinglePartitionDesc(MetaUtils.buildIdToColumn(schema), singleRangePartitionDesc,
-                    20000L, false);
+                        20000L, false);
         }
     }
 
@@ -353,7 +352,7 @@ public void testFixedRange2() throws DdlException, AnalysisException {
 
         //add RangePartitionDescs
         PartitionKeyDesc p1 = new PartitionKeyDesc(new ArrayList<>(),
-                Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("200")));
+                    Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("200")));
 
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p1", p1, null));
 
@@ -363,7 +362,7 @@ public void testFixedRange2() throws DdlException, AnalysisException {
         for (SingleRangePartitionDesc singleRangePartitionDesc : singleRangePartitionDescs) {
             singleRangePartitionDesc.analyze(columns, null);
             partitionInfo.handleNewSinglePartitionDesc(MetaUtils.buildIdToColumn(schema), singleRangePartitionDesc,
-                    20000L, false);
+                        20000L, false);
         }
     }
 
@@ -386,8 +385,8 @@ public void testFixedRange3() throws DdlException, AnalysisException {
 
         //add RangePartitionDescs
         PartitionKeyDesc p1 = new PartitionKeyDesc(
-                Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("200")),
-                new ArrayList<>());
+                    Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("200")),
+                    new ArrayList<>());
 
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p1", p1, null));
 
@@ -397,7 +396,7 @@ public void testFixedRange3() throws DdlException, AnalysisException {
         for (SingleRangePartitionDesc singleRangePartitionDesc : singleRangePartitionDescs) {
             singleRangePartitionDesc.analyze(columns, null);
             partitionInfo.handleNewSinglePartitionDesc(MetaUtils.buildIdToColumn(schema), singleRangePartitionDesc,
-                    20000L, false);
+                        20000L, false);
         }
     }
 
@@ -419,8 +418,8 @@ public void testFixedRange4() throws DdlException, AnalysisException {
 
         //add RangePartitionDescs
         PartitionKeyDesc p1 = new PartitionKeyDesc(
-                Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("100")),
-                Lists.newArrayList(new PartitionValue("20190201")));
+                    Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("100")),
+                    Lists.newArrayList(new PartitionValue("20190201")));
 
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p1", p1, null));
 
@@ -430,7 +429,7 @@ public void testFixedRange4() throws DdlException, AnalysisException {
         for (SingleRangePartitionDesc singleRangePartitionDesc : singleRangePartitionDescs) {
             singleRangePartitionDesc.analyze(columns, null);
             partitionInfo.handleNewSinglePartitionDesc(MetaUtils.buildIdToColumn(schema), singleRangePartitionDesc,
-                    20000L, false);
+                        20000L, false);
         }
     }
 
@@ -453,8 +452,8 @@ public void testFixedRange5() throws DdlException, AnalysisException {
 
         //add RangePartitionDescs
         PartitionKeyDesc p1 = new PartitionKeyDesc(
-                Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("100")),
-                Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("100")));
+                    Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("100")),
+                    Lists.newArrayList(new PartitionValue("20190101"), new PartitionValue("100")));
 
         singleRangePartitionDescs.add(new SingleRangePartitionDesc(false, "p1", p1, null));
 
@@ -464,7 +463,7 @@ public void testFixedRange5() throws DdlException, AnalysisException {
         for (SingleRangePartitionDesc singleRangePartitionDesc : singleRangePartitionDescs) {
             singleRangePartitionDesc.analyze(columns, null);
             partitionInfo.handleNewSinglePartitionDesc(MetaUtils.buildIdToColumn(schema), singleRangePartitionDesc,
-                    20000L, false);
+                        20000L, false);
         }
     }
 
@@ -472,35 +471,35 @@ public void testFixedRange5() throws DdlException, AnalysisException {
     public void testExpressionRangePartitionInfoSerialized_FunctionExpr() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE table_hitcount (\n" +
-                "databaseName varchar(200) NULL COMMENT \"\",\n" +
-                "tableName varchar(200) NULL COMMENT \"\",\n" +
-                "queryTime varchar(50) NULL COMMENT \"\",\n" +
-                "queryId varchar(50) NULL COMMENT \"\",\n" +
-                "partitionHitSum int(11) NULL COMMENT \"\",\n" +
-                "partitionSum int(11) NULL COMMENT \"\",\n" +
-                "tabletHitNum int(11) NULL COMMENT \"\",\n" +
-                "tabletSum int(11) NULL COMMENT \"\",\n" +
-                "startHitPartition varchar(20) NULL COMMENT \"\",\n" +
-                "dt date NULL COMMENT \"\",\n" +
-                "clusterAddress varchar(50) NULL COMMENT \"\",\n" +
-                "costTime int(11) NULL COMMENT \"\",\n" +
-                "tableQueryCount int(11) NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(databaseName, tableName)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "PARTITION BY date_trunc('day', dt)\n" +
-                "DISTRIBUTED BY HASH(databaseName) BUCKETS 1\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"in_memory\" = \"false\",\n" +
-                "\"enable_persistent_index\" = \"false\",\n" +
-                "\"replicated_storage\" = \"true\",\n" +
-                "\"compression\" = \"LZ4\"\n" +
-                ");";
+                    "databaseName varchar(200) NULL COMMENT \"\",\n" +
+                    "tableName varchar(200) NULL COMMENT \"\",\n" +
+                    "queryTime varchar(50) NULL COMMENT \"\",\n" +
+                    "queryId varchar(50) NULL COMMENT \"\",\n" +
+                    "partitionHitSum int(11) NULL COMMENT \"\",\n" +
+                    "partitionSum int(11) NULL COMMENT \"\",\n" +
+                    "tabletHitNum int(11) NULL COMMENT \"\",\n" +
+                    "tabletSum int(11) NULL COMMENT \"\",\n" +
+                    "startHitPartition varchar(20) NULL COMMENT \"\",\n" +
+                    "dt date NULL COMMENT \"\",\n" +
+                    "clusterAddress varchar(50) NULL COMMENT \"\",\n" +
+                    "costTime int(11) NULL COMMENT \"\",\n" +
+                    "tableQueryCount int(11) NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(databaseName, tableName)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "PARTITION BY date_trunc('day', dt)\n" +
+                    "DISTRIBUTED BY HASH(databaseName) BUCKETS 1\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"in_memory\" = \"false\",\n" +
+                    "\"enable_persistent_index\" = \"false\",\n" +
+                    "\"replicated_storage\" = \"true\",\n" +
+                    "\"compression\" = \"LZ4\"\n" +
+                    ");";
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("table_hitcount");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "table_hitcount");
         // serialize
         String json = GsonUtils.GSON.toJson(table);
         // deserialize
@@ -516,34 +515,34 @@ public void testExpressionRangePartitionInfoSerialized_FunctionExpr() throws Exc
     public void testExpressionRangePartitionInfoSerialized_SlotRef() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test_table (\n" +
-                "databaseName varchar(200) NULL COMMENT \"\",\n" +
-                "tableName varchar(200) NULL COMMENT \"\",\n" +
-                "queryTime varchar(50) NULL COMMENT \"\",\n" +
-                "queryId varchar(50) NULL COMMENT \"\",\n" +
-                "dt date NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(databaseName, tableName)\n" +
-                "PARTITION BY RANGE (`dt`)\n" +
-                "(\n" +
-                "    PARTITION p1 values less than('2021-02-01'),\n" +
-                "    PARTITION p2 values less than('2021-03-01')\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(databaseName) BUCKETS 1\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\"\n" +
-                ");";
+                    "databaseName varchar(200) NULL COMMENT \"\",\n" +
+                    "tableName varchar(200) NULL COMMENT \"\",\n" +
+                    "queryTime varchar(50) NULL COMMENT \"\",\n" +
+                    "queryId varchar(50) NULL COMMENT \"\",\n" +
+                    "dt date NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(databaseName, tableName)\n" +
+                    "PARTITION BY RANGE (`dt`)\n" +
+                    "(\n" +
+                    "    PARTITION p1 values less than('2021-02-01'),\n" +
+                    "    PARTITION p2 values less than('2021-03-01')\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(databaseName) BUCKETS 1\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\"\n" +
+                    ");";
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
 
         starRocksAssert.withMaterializedView("create materialized view test_mv1 " +
-                " DISTRIBUTED BY HASH(dt, queryId) BUCKETS 4\n" +
-                " PARTITION BY dt\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\"\n" +
-                ") as select dt, queryId, count(1) from test_table group by dt, queryId"
+                    " DISTRIBUTED BY HASH(dt, queryId) BUCKETS 4\n" +
+                    " PARTITION BY dt\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\"\n" +
+                    ") as select dt, queryId, count(1) from test_table group by dt, queryId"
         );
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("test_mv1");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_mv1");
         // serialize
         String json = GsonUtils.GSON.toJson(table);
         // deserialize
@@ -551,7 +550,7 @@ public void testExpressionRangePartitionInfoSerialized_SlotRef() throws Exceptio
         ExpressionRangePartitionInfo expressionRangePartitionInfo = (ExpressionRangePartitionInfo) readTable.getPartitionInfo();
         List<Expr> readPartitionExprs = expressionRangePartitionInfo.getPartitionExprs(readTable.getIdToColumn());
         Assert.assertTrue(readPartitionExprs.get(0) instanceof SlotRef);
-        SlotRef slotRef = (SlotRef)  readPartitionExprs.get(0);
+        SlotRef slotRef = (SlotRef) readPartitionExprs.get(0);
         Assert.assertTrue(!slotRef.getType().isInvalid());
         Assert.assertTrue(slotRef.getType().isDateType());
         starRocksAssert.dropMaterializedView("test_mv1");
@@ -562,30 +561,31 @@ public void testExpressionRangePartitionInfoSerialized_SlotRef() throws Exceptio
     public void testExpressionRangePartitionInfoV2SerializedWrongNotFailed() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE `game_log2` (\n" +
-                "  `cloud_id` varchar(65533) NULL COMMENT \"\",\n" +
-                "  `user_id` varchar(65533) NULL COMMENT \"\",\n" +
-                "  `day` date NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP \n" +
-                "DUPLICATE KEY(`cloud_id`, `user_id`)\n" +
-                "PARTITION BY RANGE(cast(substr(cloud_id, 3, 11) as bigint))()\n" +
-                "DISTRIBUTED BY HASH(`cloud_id`, `user_id`) BUCKETS 1 \n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"in_memory\" = \"false\",\n" +
-                "\"enable_persistent_index\" = \"false\",\n" +
-                "\"replicated_storage\" = \"true\",\n" +
-                "\"compression\" = \"ZSTD\"\n" +
-                ");";
+                    "  `cloud_id` varchar(65533) NULL COMMENT \"\",\n" +
+                    "  `user_id` varchar(65533) NULL COMMENT \"\",\n" +
+                    "  `day` date NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP \n" +
+                    "DUPLICATE KEY(`cloud_id`, `user_id`)\n" +
+                    "PARTITION BY RANGE(cast(substr(cloud_id, 3, 11) as bigint))()\n" +
+                    "DISTRIBUTED BY HASH(`cloud_id`, `user_id`) BUCKETS 1 \n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"in_memory\" = \"false\",\n" +
+                    "\"enable_persistent_index\" = \"false\",\n" +
+                    "\"replicated_storage\" = \"true\",\n" +
+                    "\"compression\" = \"ZSTD\"\n" +
+                    ");";
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable olapTable = (OlapTable) db.getTable("game_log2");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable olapTable =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "game_log2");
         ExpressionRangePartitionInfoV2 expressionRangePartitionInfo =
-                (ExpressionRangePartitionInfoV2) olapTable.getPartitionInfo();
+                    (ExpressionRangePartitionInfoV2) olapTable.getPartitionInfo();
         expressionRangePartitionInfo.setPartitionExprs(Lists.newArrayList(
-                ColumnIdExpr.create(new FunctionCallExpr("abc", Lists.newArrayList(new SlotRef(
-                        new TableName("test", "game_log2"), "cloud_id"))))));
+                    ColumnIdExpr.create(new FunctionCallExpr("abc", Lists.newArrayList(new SlotRef(
+                                new TableName("test", "game_log2"), "cloud_id"))))));
         // serialize
         String json = GsonUtils.GSON.toJson(olapTable);
         // deserialize
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/ForeignKeyConstraintTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/ForeignKeyConstraintTest.java
index c928ab337aca84..a6239bb2a8c436 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/ForeignKeyConstraintTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/ForeignKeyConstraintTest.java
@@ -37,6 +37,10 @@ public void beforeAll() {
         db.registerTableUnlocked(table1);
         db.registerTableUnlocked(table2);
         db.registerTableUnlocked(table3);
+    }
+
+    @Test
+    public void testParseInternal() {
 
         new Expectations(globalStateMgr) {
             {
@@ -44,15 +48,24 @@ public void beforeAll() {
                 minTimes = 0;
                 result = globalStateMgr;
 
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = db;
+
+                globalStateMgr.getLocalMetastore().getTable(anyLong, 1000L);
+                minTimes = 0;
+                result = db.getTable(1000L);
+
+                globalStateMgr.getLocalMetastore().getTable(anyLong, 1001L);
+                minTimes = 0;
+                result = db.getTable(1001L);
+
+                globalStateMgr.getLocalMetastore().getTable(anyLong, 1002L);
+                minTimes = 0;
+                result = db.getTable(1002L);
             }
         };
-    }
 
-    @Test
-    public void testParseInternal() {
         // internal catalog
         String constraintDescs = "(column1)  REFERENCES  default_catalog.100.1000(newColumn1)";
         List<ForeignKeyConstraint> foreignKeyConstraints1 = ForeignKeyConstraint.parse(constraintDescs);
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/GlobalStateMgrTestUtil.java b/fe/fe-core/src/test/java/com/starrocks/catalog/GlobalStateMgrTestUtil.java
index b9a4f740c62265..6cb7bbc568532c 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/GlobalStateMgrTestUtil.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/GlobalStateMgrTestUtil.java
@@ -115,11 +115,11 @@ public static GlobalStateMgr createTestState() throws InstantiationException, Il
     }
 
     public static boolean compareState(GlobalStateMgr masterGlobalStateMgr, GlobalStateMgr slaveGlobalStateMgr) {
-        Database masterDb = masterGlobalStateMgr.getDb(testDb1);
-        Database slaveDb = slaveGlobalStateMgr.getDb(testDb1);
+        Database masterDb = masterGlobalStateMgr.getLocalMetastore().getDb(testDb1);
+        Database slaveDb = slaveGlobalStateMgr.getLocalMetastore().getDb(testDb1);
         List<Table> tables = masterDb.getTables();
         for (Table table : tables) {
-            Table slaveTable = slaveDb.getTable(table.getId());
+            Table slaveTable = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(slaveDb.getId(), table.getId());
             if (slaveTable == null) {
                 return false;
             }
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/InfoSchemaDbTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/InfoSchemaDbTest.java
index 14a92a67770232..96ebdb24f105f5 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/InfoSchemaDbTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/InfoSchemaDbTest.java
@@ -107,7 +107,7 @@ public void testNormal() throws IOException {
         Assert.assertFalse(db.registerTableUnlocked(null));
         db.dropTable("authors");
         db.write(null);
-        Assert.assertNull(db.getTable("authors"));
+        Assert.assertNull(GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "authors"));
     }
 
     @Test
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/MVPartitionExprResolverTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/MVPartitionExprResolverTest.java
index 9b993621ca0938..1aa5f1248c118c 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/MVPartitionExprResolverTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/MVPartitionExprResolverTest.java
@@ -240,7 +240,7 @@ private Map<Expr, SlotRef> checkMVPartitionExprs(String sql, Expr slot, int expe
 
     @Test
     public void testFilterPartitionByUnion() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         starRocksAssert.withMaterializedView(
                 "create materialized view test.mv_union_filter\n" +
@@ -252,7 +252,9 @@ public void testFilterPartitionByUnion() {
                         "union " +
                         "select k1, k2 from test.tbl16;", () -> {
 
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_union_filter"));
+                    MaterializedView materializedView =
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "mv_union_filter"));
                     Assert.assertEquals(2, materializedView.getPartitionExprMaps().size());
 
                     Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
@@ -262,8 +264,12 @@ public void testFilterPartitionByUnion() {
                     PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
                     Map<Table, Set<String>> baseTables = getRefTableRefreshedPartitions(processor);
                     Assert.assertEquals(2, baseTables.size());
-                    Assert.assertEquals(Sets.newHashSet("p20220101"), baseTables.get(testDb.getTable("tbl15")));
-                    Assert.assertEquals(Sets.newHashSet("p20220101"), baseTables.get(testDb.getTable("tbl16")));
+                    Assert.assertEquals(Sets.newHashSet("p20220101"), baseTables.get(
+                            GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "tbl15")));
+                    Assert.assertEquals(Sets.newHashSet("p20220101"), baseTables.get(
+                            GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "tbl16")));
 
                     // insert new data into tbl16's p20220202 partition
                     String insertSql = "insert into tbl16 partition(p20220202) values('2022-02-02', 3, 10);";
@@ -287,7 +293,9 @@ public void testFilterPartitionByUnion() {
                         "union " +
                         "select k1, k2 from test.tbl15;", () -> {
 
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_union_filter"));
+                    MaterializedView materializedView =
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "mv_union_filter"));
                     Assert.assertEquals(2, materializedView.getPartitionExprMaps().size());
 
                     Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
@@ -310,7 +318,7 @@ public void testFilterPartitionByUnion() {
 
     @Test
     public void testFilterPartitionByJoinPredicate1() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         //normal case, join predicate is partition column
         // a.k1 = date_trunc(month, b.k1)
         starRocksAssert.withMaterializedView(
@@ -322,7 +330,9 @@ public void testFilterPartitionByJoinPredicate1() {
                         "as select a.k1, b.k2 from test.tbl15 as a join test.tbl16 as b " +
                         "on a.k1 = date_trunc('month', b.k1);", () -> {
 
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_join_predicate"));
+                    MaterializedView materializedView =
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "mv_join_predicate"));
                     Assert.assertEquals(2, materializedView.getPartitionExprMaps().size());
 
                     Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
@@ -330,13 +340,16 @@ public void testFilterPartitionByJoinPredicate1() {
                     {
                         taskRun.initStatus(UUIDUtil.genUUID().toString(), System.currentTimeMillis());
                         taskRun.executeTaskRun();
-                        PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
+                        PartitionBasedMvRefreshProcessor processor =
+                                (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
                         Map<Table, Set<String>> baseTables = getRefTableRefreshedPartitions(processor);
                         Assert.assertEquals(2, baseTables.size());
                         Assert.assertEquals(Sets.newHashSet("p20220101"),
-                                baseTables.get(testDb.getTable("tbl15")));
+                                baseTables.get(GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                        .getTable(testDb.getFullName(), "tbl15")));
                         Assert.assertEquals(Sets.newHashSet("p20220101", "p20220102", "p20220103"),
-                                baseTables.get(testDb.getTable("tbl16")));
+                                baseTables.get(GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                        .getTable(testDb.getFullName(), "tbl16")));
                         Assert.assertTrue(processor.getNextTaskRun() == null);
                     }
 
@@ -346,7 +359,8 @@ public void testFilterPartitionByJoinPredicate1() {
                         new StmtExecutor(connectContext, SqlParser.parseSingleStatement(
                                 insertSql, connectContext.getSessionVariable().getSqlMode())).execute();
                         taskRun.executeTaskRun();
-                        PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
+                        PartitionBasedMvRefreshProcessor processor =
+                                (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
                         // 1. updated partition of tbl16 is p20220202
                         // 2. date_trunc('month', p20220202) is '2022-02'
                         // 3. tbl15's associated partitions are p20220201 and p20220202
@@ -360,7 +374,7 @@ public void testFilterPartitionByJoinPredicate1() {
 
     @Test
     public void testFilterPartitionByJoinPredicate3() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         // join predicate has no equal condition
         starRocksAssert.withMaterializedView(
                 "create materialized view test.mv_join_predicate\n" +
@@ -368,9 +382,12 @@ public void testFilterPartitionByJoinPredicate3() {
                         "distributed by hash(k2) buckets 10\n" +
                         "PROPERTIES('partition_refresh_number' = '10000')" +
                         "refresh deferred manual\n" +
-                        "as select tbl1.k1, tbl2.k2 from tbl1 join tbl2 on tbl1.k1 = tbl2.k1 or tbl1.k2 = tbl2.k2;", () -> {
+                        "as select tbl1.k1, tbl2.k2 from tbl1 join tbl2 on tbl1.k1 = tbl2.k1 or tbl1.k2 = tbl2.k2;",
+                () -> {
 
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_join_predicate"));
+                    MaterializedView materializedView =
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "mv_join_predicate"));
                     Assert.assertEquals(1, materializedView.getPartitionExprMaps().size());
                     Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
                     TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -381,7 +398,8 @@ public void testFilterPartitionByJoinPredicate3() {
                         executeInsertSql(connectContext, "insert into tbl1 partition(p2) values('2022-02-02', 3, 10);");
                         taskRun.initStatus(UUIDUtil.genUUID().toString(), System.currentTimeMillis());
                         taskRun.executeTaskRun();
-                        PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
+                        PartitionBasedMvRefreshProcessor processor =
+                                (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
                         Assert.assertEquals(Sets.newHashSet("p2"),
                                 processor.getMVTaskRunExtraMessage().getMvPartitionsToRefresh());
                         ExecPlan execPlan = processor.getMvContext().getExecPlan();
@@ -394,17 +412,19 @@ public void testFilterPartitionByJoinPredicate3() {
                         executeInsertSql(connectContext, "insert into tbl2 partition(p2) values('2022-02-02', 3, 10);");
                         taskRun.initStatus(UUIDUtil.genUUID().toString(), System.currentTimeMillis());
                         taskRun.executeTaskRun();
-                        PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
+                        PartitionBasedMvRefreshProcessor processor =
+                                (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
                         ExecPlan execPlan = processor.getMvContext().getExecPlan();
                         Assert.assertTrue(execPlan != null);
-                        assertPlanContains(execPlan, "partitions=5/5\n     rollup: tbl1", "partitions=2/2\n     rollup: tbl2");
+                        assertPlanContains(execPlan, "partitions=5/5\n     rollup: tbl1",
+                                "partitions=2/2\n     rollup: tbl2");
                     }
                 });
     }
 
     @Test
     public void testFilterPartitionByJoinPredicate31() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         // join predicate is not mv partition expr
         starRocksAssert.withMaterializedView(
                 "create materialized view test.mv_join_predicate\n" +
@@ -414,14 +434,16 @@ public void testFilterPartitionByJoinPredicate31() {
                         "refresh deferred manual\n" +
                         "as select tbl1.k1, tbl2.k2 from tbl1 join tbl2 using(k1);", () -> {
 
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_join_predicate"));
+                    MaterializedView materializedView =
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "mv_join_predicate"));
                     Assert.assertEquals(2, materializedView.getPartitionExprMaps().size());
                 });
     }
 
     @Test
     public void testFilterPartitionByJoinPredicate4() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         // nest table alias join
         starRocksAssert.withMaterializedView(
                 "create materialized view test.mv_join_predicate\n" +
@@ -431,7 +453,9 @@ public void testFilterPartitionByJoinPredicate4() {
                         "as select a.k1, b.k2 from test.tbl15 as a join test.tbl16 as b " +
                         "on date_trunc('month', a.k1) = b.k1;", () -> {
 
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_join_predicate"));
+                    MaterializedView materializedView =
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "mv_join_predicate"));
                     Assert.assertEquals(1, materializedView.getPartitionExprMaps().size());
                     Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
                     TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -452,7 +476,7 @@ public void testFilterPartitionByJoinPredicate4() {
 
     @Test
     public void testFilterPartitionByJoinPredicate5() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         // nest table alias join
         starRocksAssert.withMaterializedView(
                 "create materialized view test.mv_join_predicate\n" +
@@ -468,7 +492,9 @@ public void testFilterPartitionByJoinPredicate5() {
                         "  (select date_trunc('DAY', k1) as ds, k2 from (select * from tbl2)t ) b " +
                         "on date_trunc('DAY', a.k1) = b.ds and a.k2 = b.k2", () -> {
 
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_join_predicate"));
+                    MaterializedView materializedView =
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "mv_join_predicate"));
                     Assert.assertEquals(2, materializedView.getPartitionExprMaps().size());
                     Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
                     TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -498,7 +524,7 @@ public void testFilterPartitionByJoinPredicate5() {
 
     @Test
     public void testFilterPartitionByJoinPredicate6() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         // nest function in join predicate
         starRocksAssert.useDatabase("test").withMaterializedView(
                 "create materialized view test.mv_join_predicate\n" +
@@ -512,14 +538,16 @@ public void testFilterPartitionByJoinPredicate6() {
                         "(select k1 as ds, k2 from tbl2) b " +
                         "on date_trunc('day', a.ds) = b.ds and a.k2 = b.k2 ;", () -> {
 
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_join_predicate"));
+                    MaterializedView materializedView =
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "mv_join_predicate"));
                     Assert.assertEquals(1, materializedView.getPartitionExprMaps().size());
                 });
     }
 
     @Test
     public void testFilterPartitionByJoinPredicate7() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         // duplicate table join
         starRocksAssert.withMaterializedView(
                 "create materialized view test.mv_join_predicate\n" +
@@ -534,14 +562,16 @@ public void testFilterPartitionByJoinPredicate7() {
                         "(select k1 as ds, k2 from tbl2) c " +
                         "on a.ds = c.ds and a.k2 = c.k2;", () -> {
 
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_join_predicate"));
+                    MaterializedView materializedView =
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "mv_join_predicate"));
                     Assert.assertEquals(2, materializedView.getPartitionExprMaps().size());
                 });
     }
 
     @Test
     public void testFilterPartitionByJoinPredicate8() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withMaterializedView(
                 "create materialized view test.mv_join_predicate\n" +
                         "partition by k1\n" +
@@ -557,14 +587,16 @@ public void testFilterPartitionByJoinPredicate8() {
                         "(select date_trunc('day', k1) as ds, k2 from tbl1) c " +
                         "on a.ds = c.ds;", () -> {
 
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_join_predicate"));
+                    MaterializedView materializedView =
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "mv_join_predicate"));
                     Assert.assertEquals(1, materializedView.getPartitionExprMaps().size());
                 });
     }
 
     @Test
     public void testFilterPartitionByJoinPredicate9() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         // unsupported function in join predicate
         starRocksAssert.withMaterializedView(
                 "create materialized view test.mv_join_predicate\n" +
@@ -579,7 +611,9 @@ public void testFilterPartitionByJoinPredicate9() {
                         "(select date_add(k1, INTERVAL 1 DAY) as ds, k2 from tbl15) c " +
                         "on a.ds = c.ds and a.k2 = c.k2;", () -> {
 
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_join_predicate"));
+                    MaterializedView materializedView =
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "mv_join_predicate"));
                     Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
                     TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
                     taskRun.initStatus(UUIDUtil.genUUID().toString(), System.currentTimeMillis());
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/MaterializedViewTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/MaterializedViewTest.java
index b198f075bf9342..8562e8ace445d5 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/MaterializedViewTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/MaterializedViewTest.java
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-
 package com.starrocks.catalog;
 
 import com.google.common.base.Strings;
@@ -91,7 +90,7 @@ public void testInit() {
         Assert.assertEquals(null, mv.getTableProperty());
 
         MaterializedView mv2 = new MaterializedView(1000, 100, "mv2", columns, KeysType.AGG_KEYS,
-                null, null, null);
+                    null, null, null);
         Assert.assertEquals(100, mv2.getDbId());
         Assert.assertEquals(Table.TableType.MATERIALIZED_VIEW, mv2.getType());
         Assert.assertEquals(null, mv2.getTableProperty());
@@ -131,16 +130,16 @@ public void testInit() {
     @Test
     public void testSchema() {
         MaterializedView mv = new MaterializedView(1000, 100, "mv2", columns, KeysType.AGG_KEYS,
-                null, null, null);
+                    null, null, null);
         mv.setBaseIndexId(1L);
         mv.setIndexMeta(1L, "mv_name", columns, 0,
-                111, (short) 2, TStorageType.COLUMN, KeysType.AGG_KEYS, null);
+                    111, (short) 2, TStorageType.COLUMN, KeysType.AGG_KEYS, null);
         Assert.assertEquals(1, mv.getBaseIndexId());
         mv.rebuildFullSchema();
         Assert.assertEquals("mv_name", mv.getIndexNameById(1L));
         List<Column> indexColumns = Lists.newArrayList(columns.get(0), columns.get(2));
         mv.setIndexMeta(2L, "index_name", indexColumns, 0,
-                222, (short) 1, TStorageType.COLUMN, KeysType.AGG_KEYS, null);
+                    222, (short) 1, TStorageType.COLUMN, KeysType.AGG_KEYS, null);
         mv.rebuildFullSchema();
         Assert.assertEquals("index_name", mv.getIndexNameById(2L));
     }
@@ -157,9 +156,9 @@ public void testPartition() {
         MaterializedView.MvRefreshScheme refreshScheme = new MaterializedView.MvRefreshScheme();
 
         MaterializedView mv = new MaterializedView(1000, 100, "mv_name", columns, KeysType.AGG_KEYS,
-                partitionInfo, distributionInfo, refreshScheme);
+                    partitionInfo, distributionInfo, refreshScheme);
         mv.setIndexMeta(1L, "mv_name", columns, 0,
-                111, (short) 2, TStorageType.COLUMN, KeysType.AGG_KEYS, null);
+                    111, (short) 2, TStorageType.COLUMN, KeysType.AGG_KEYS, null);
         Assert.assertEquals("mv_name", mv.getName());
         mv.setName("new_name");
         Assert.assertEquals("new_name", mv.getName());
@@ -184,9 +183,9 @@ public void testPartition() {
         rangePartitionInfo.setTabletType(1, TTabletType.TABLET_TYPE_DISK);
 
         MaterializedView mv2 = new MaterializedView(1000, 100, "mv_name_2", columns, KeysType.AGG_KEYS,
-                rangePartitionInfo, distributionInfo, refreshScheme);
+                    rangePartitionInfo, distributionInfo, refreshScheme);
         mv2.setIndexMeta(1L, "mv_name_2", columns, 0,
-                111, (short) 2, TStorageType.COLUMN, KeysType.AGG_KEYS, null);
+                    111, (short) 2, TStorageType.COLUMN, KeysType.AGG_KEYS, null);
         Assert.assertEquals("mv_name_2", mv2.getName());
         mv2.setName("new_name_2");
         Assert.assertEquals("new_name_2", mv2.getName());
@@ -214,16 +213,16 @@ public void testDistribution() {
         MaterializedView.MvRefreshScheme refreshScheme = new MaterializedView.MvRefreshScheme();
 
         MaterializedView mv = new MaterializedView(1000, 100, "mv_name", columns, KeysType.AGG_KEYS,
-                partitionInfo, distributionInfo, refreshScheme);
+                    partitionInfo, distributionInfo, refreshScheme);
         mv.setIndexMeta(1L, "mv_name", columns, 0,
-                111, (short) 2, TStorageType.COLUMN, KeysType.AGG_KEYS, null);
+                    111, (short) 2, TStorageType.COLUMN, KeysType.AGG_KEYS, null);
         DistributionInfo distributionInfo1 = mv.getDefaultDistributionInfo();
         Assert.assertTrue(distributionInfo1 instanceof RandomDistributionInfo);
         Assert.assertEquals(0, mv.getDistributionColumnNames().size());
 
         HashDistributionInfo hashDistributionInfo = new HashDistributionInfo(10, Lists.newArrayList(columns.get(0)));
         MaterializedView mv2 = new MaterializedView(1000, 100, "mv_name", columns, KeysType.AGG_KEYS,
-                partitionInfo, hashDistributionInfo, refreshScheme);
+                    partitionInfo, hashDistributionInfo, refreshScheme);
         DistributionInfo distributionInfo2 = mv2.getDefaultDistributionInfo();
         Assert.assertTrue(distributionInfo2 instanceof HashDistributionInfo);
         Assert.assertEquals(1, mv2.getDistributionColumnNames().size());
@@ -240,9 +239,9 @@ public void testToThrift() {
         MaterializedView.MvRefreshScheme refreshScheme = new MaterializedView.MvRefreshScheme();
 
         MaterializedView mv = new MaterializedView(1000, 100, "mv_name", columns, KeysType.AGG_KEYS,
-                partitionInfo, distributionInfo, refreshScheme);
+                    partitionInfo, distributionInfo, refreshScheme);
         mv.setIndexMeta(1L, "mv_name", columns, 0,
-                111, (short) 2, TStorageType.COLUMN, KeysType.AGG_KEYS, null);
+                    111, (short) 2, TStorageType.COLUMN, KeysType.AGG_KEYS, null);
         TTableDescriptor tableDescriptor = mv.toThrift(null);
         Assert.assertEquals(TTableType.MATERIALIZED_VIEW, tableDescriptor.getTableType());
         Assert.assertEquals(1000, tableDescriptor.getId());
@@ -252,40 +251,40 @@ public void testToThrift() {
     @Test
     public void testRenameMaterializedView() throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.tbl1\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
-                        "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');")
-                .withMaterializedView("create materialized view mv_to_rename\n" +
-                        "PARTITION BY k1\n" +
-                        "distributed by hash(k2) buckets 3\n" +
-                        "refresh async\n" +
-                        "as select k1, k2, sum(v1) as total from tbl1 group by k1, k2;")
-                .withMaterializedView("create materialized view mv_to_rename2\n" +
-                        "PARTITION BY date_trunc('month', k1)\n" +
-                        "distributed by hash(k2) buckets 3\n" +
-                        "refresh async\n" +
-                        "as select k1, k2, sum(v1) as total from tbl1 group by k1, k2;");
-
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
+                    .withTable("CREATE TABLE test.tbl1\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
+                                "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');")
+                    .withMaterializedView("create materialized view mv_to_rename\n" +
+                                "PARTITION BY k1\n" +
+                                "distributed by hash(k2) buckets 3\n" +
+                                "refresh async\n" +
+                                "as select k1, k2, sum(v1) as total from tbl1 group by k1, k2;")
+                    .withMaterializedView("create materialized view mv_to_rename2\n" +
+                                "PARTITION BY date_trunc('month', k1)\n" +
+                                "distributed by hash(k2) buckets 3\n" +
+                                "refresh async\n" +
+                                "as select k1, k2, sum(v1) as total from tbl1 group by k1, k2;");
+
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
         Assert.assertNotNull(db);
-        Table table = db.getTable("mv_to_rename");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv_to_rename");
         Assert.assertNotNull(table);
         // test partition related info
         MaterializedView oldMv = (MaterializedView) table;
         Assert.assertTrue(oldMv.getRefreshScheme().isAsync());
         Assert.assertTrue(oldMv.getRefreshScheme().toString().contains("MvRefreshScheme"));
         Map<Table, Column> partitionMap = oldMv.getRefBaseTablePartitionColumns();
-        Table table1 = db.getTable("tbl1");
+        Table table1 = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl1");
         Assert.assertTrue(partitionMap.containsKey(table1));
         List<Table.TableType> baseTableType = oldMv.getBaseTableTypes();
         Assert.assertEquals(1, baseTableType.size());
@@ -301,8 +300,9 @@ public void testRenameMaterializedView() throws Exception {
 
         StmtExecutor stmtExecutor = new StmtExecutor(connectContext, statement);
         stmtExecutor.execute();
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView mv = ((MaterializedView) testDb.getTable("mv_new_name"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView mv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), "mv_new_name"));
         Assert.assertNotNull(mv);
         Assert.assertEquals("mv_new_name", mv.getName());
         ExpressionRangePartitionInfo partitionInfo = (ExpressionRangePartitionInfo) mv.getPartitionInfo();
@@ -317,7 +317,8 @@ public void testRenameMaterializedView() throws Exception {
         statement = SqlParser.parseSingleStatement(alterSql2, connectContext.getSessionVariable().getSqlMode());
         StmtExecutor stmtExecutor2 = new StmtExecutor(connectContext, statement);
         stmtExecutor2.execute();
-        MaterializedView mv2 = ((MaterializedView) testDb.getTable("mv_new_name2"));
+        MaterializedView mv2 = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), "mv_new_name2"));
         Assert.assertNotNull(mv2);
         Assert.assertEquals("mv_new_name2", mv2.getName());
         ExpressionRangePartitionInfo partitionInfo2 = (ExpressionRangePartitionInfo) mv2.getPartitionInfo();
@@ -334,34 +335,34 @@ public void testRenameMaterializedView() throws Exception {
     @Test
     public void testReplay() throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.tbl1\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
-                        "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');")
-                .withMaterializedView("create materialized view mv_replay\n" +
-                        "PARTITION BY k1\n" +
-                        "distributed by hash(k2) buckets 3\n" +
-                        "refresh async\n" +
-                        "as select k1, k2, sum(v1) as total from tbl1 group by k1, k2;");
+                    .withTable("CREATE TABLE test.tbl1\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
+                                "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');")
+                    .withMaterializedView("create materialized view mv_replay\n" +
+                                "PARTITION BY k1\n" +
+                                "distributed by hash(k2) buckets 3\n" +
+                                "refresh async\n" +
+                                "as select k1, k2, sum(v1) as total from tbl1 group by k1, k2;");
         connectContext.executeSql("insert into test.tbl1 values('2022-02-01', 2, 3)");
         connectContext.executeSql("insert into test.tbl1 values('2022-02-16', 3, 5)");
         connectContext.executeSql("refresh materialized view mv_replay with sync mode");
 
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
         Assert.assertNotNull(db);
-        Table table = db.getTable("mv_replay");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv_replay");
         MaterializedView mv = (MaterializedView) table;
         AlterMaterializedViewBaseTableInfosLog log = new AlterMaterializedViewBaseTableInfosLog(db.getId(), mv.getId(), null,
-                mv.getBaseTableInfos(), mv.getRefreshScheme().getAsyncRefreshContext().getBaseTableVisibleVersionMap());
+                    mv.getBaseTableInfos(), mv.getRefreshScheme().getAsyncRefreshContext().getBaseTableVisibleVersionMap());
         mv.replayAlterMaterializedViewBaseTableInfos(log);
 
         starRocksAssert.dropMaterializedView("mv_replay");
@@ -370,25 +371,26 @@ public void testReplay() throws Exception {
     @Test
     public void testMvAfterDropBaseTable() throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.tbl_drop\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
-                        "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');")
-                .withMaterializedView("create materialized view mv_to_check\n" +
-                        "distributed by hash(k2) buckets 3\n" +
-                        "refresh async\n" +
-                        "as select k2, sum(v1) as total from tbl_drop group by k2;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView mv = ((MaterializedView) testDb.getTable("mv_to_check"));
+                    .withTable("CREATE TABLE test.tbl_drop\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
+                                "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');")
+                    .withMaterializedView("create materialized view mv_to_check\n" +
+                                "distributed by hash(k2) buckets 3\n" +
+                                "refresh async\n" +
+                                "as select k2, sum(v1) as total from tbl_drop group by k2;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView mv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), "mv_to_check"));
         String dropSql = "drop table tbl_drop;";
         StatementBase statement = SqlParser.parseSingleStatement(dropSql, connectContext.getSessionVariable().getSqlMode());
         StmtExecutor stmtExecutor = new StmtExecutor(connectContext, statement);
@@ -400,29 +402,30 @@ public void testMvAfterDropBaseTable() throws Exception {
     @Test
     public void testMvAfterBaseTableRename() throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.tbl_to_rename\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
-                        "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');")
-                .withMaterializedView("create materialized view mv_to_check\n" +
-                        "distributed by hash(k2) buckets 3\n" +
-                        "refresh async\n" +
-                        "as select k2, sum(v1) as total from tbl_to_rename group by k2;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+                    .withTable("CREATE TABLE test.tbl_to_rename\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
+                                "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');")
+                    .withMaterializedView("create materialized view mv_to_check\n" +
+                                "distributed by hash(k2) buckets 3\n" +
+                                "refresh async\n" +
+                                "as select k2, sum(v1) as total from tbl_to_rename group by k2;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         String alterSql = "alter table tbl_to_rename rename new_tbl_name;";
         StatementBase statement = SqlParser.parseSingleStatement(alterSql, connectContext.getSessionVariable().getSqlMode());
         StmtExecutor stmtExecutor = new StmtExecutor(connectContext, statement);
         stmtExecutor.execute();
-        MaterializedView mv = ((MaterializedView) testDb.getTable("mv_to_check"));
+        MaterializedView mv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), "mv_to_check"));
         Assert.assertNotNull(mv);
         Assert.assertFalse(mv.isActive());
     }
@@ -430,26 +433,28 @@ public void testMvAfterBaseTableRename() throws Exception {
     @Test
     public void testMaterializedViewWithHint() throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.tbl1\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
-                        "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');")
-                .withMaterializedView("create materialized view mv_with_hint\n" +
-                        "PARTITION BY k1\n" +
-                        "distributed by hash(k2) buckets 3\n" +
-                        "refresh async\n" +
-                        "as select /*+ SET_VAR(query_timeout = 500) */ k1, k2, sum(v1) as total from tbl1 group by k1, k2;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView mv = ((MaterializedView) testDb.getTable("mv_with_hint"));
+                    .withTable("CREATE TABLE test.tbl1\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
+                                "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');")
+                    .withMaterializedView("create materialized view mv_with_hint\n" +
+                                "PARTITION BY k1\n" +
+                                "distributed by hash(k2) buckets 3\n" +
+                                "refresh async\n" +
+                                "as select /*+ SET_VAR(query_timeout = 500) */ k1, k2, sum(v1) " +
+                                "as total from tbl1 group by k1, k2;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView mv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), "mv_with_hint"));
         String mvTaskName = "mv-" + mv.getId();
         Task task = connectContext.getGlobalStateMgr().getTaskManager().getTask(mvTaskName);
         Assert.assertNotNull(task);
@@ -463,24 +468,24 @@ public void testMaterializedViewWithHint() throws Exception {
     @Test
     public void testRollupMaterializedViewWithScalarFunction() throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE `part_with_mv` (\n" +
-                        "  `p_partkey` int(11) NOT NULL COMMENT \"\",\n" +
-                        "  `p_name` varchar(55) NOT NULL COMMENT \"\",\n" +
-                        "  `p_mfgr` varchar(25) NOT NULL COMMENT \"\",\n" +
-                        "  `p_brand` varchar(10) NOT NULL COMMENT \"\",\n" +
-                        "  `p_type` varchar(25) NOT NULL COMMENT \"\",\n" +
-                        "  `p_size` int(11) NOT NULL COMMENT \"\",\n" +
-                        "  `p_container` varchar(10) NOT NULL COMMENT \"\",\n" +
-                        "  `p_retailprice` decimal64(15, 2) NOT NULL COMMENT \"\",\n" +
-                        "  `p_comment` varchar(23) NOT NULL COMMENT \"\"\n" +
-                        ") ENGINE=OLAP\n" +
-                        "DUPLICATE KEY(`p_partkey`)\n" +
-                        "COMMENT \"OLAP\"\n" +
-                        "DISTRIBUTED BY HASH(`p_partkey`) BUCKETS 24\n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\");");
+                    .withTable("CREATE TABLE `part_with_mv` (\n" +
+                                "  `p_partkey` int(11) NOT NULL COMMENT \"\",\n" +
+                                "  `p_name` varchar(55) NOT NULL COMMENT \"\",\n" +
+                                "  `p_mfgr` varchar(25) NOT NULL COMMENT \"\",\n" +
+                                "  `p_brand` varchar(10) NOT NULL COMMENT \"\",\n" +
+                                "  `p_type` varchar(25) NOT NULL COMMENT \"\",\n" +
+                                "  `p_size` int(11) NOT NULL COMMENT \"\",\n" +
+                                "  `p_container` varchar(10) NOT NULL COMMENT \"\",\n" +
+                                "  `p_retailprice` decimal64(15, 2) NOT NULL COMMENT \"\",\n" +
+                                "  `p_comment` varchar(23) NOT NULL COMMENT \"\"\n" +
+                                ") ENGINE=OLAP\n" +
+                                "DUPLICATE KEY(`p_partkey`)\n" +
+                                "COMMENT \"OLAP\"\n" +
+                                "DISTRIBUTED BY HASH(`p_partkey`) BUCKETS 24\n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\");");
         String createMvSql = "create materialized view mv1 as select p_partkey, p_name, length(p_brand) as v1 " +
-                "from part_with_mv;";
+                    "from part_with_mv;";
         StatementBase statement = SqlParser.parseSingleStatement(createMvSql, connectContext.getSessionVariable().getSqlMode());
         StmtExecutor stmtExecutor = new StmtExecutor(connectContext, statement);
         stmtExecutor.execute();
@@ -490,56 +495,57 @@ public void testRollupMaterializedViewWithScalarFunction() throws Exception {
     @Test(expected = SemanticException.class)
     public void testNonPartitionMvSupportedProperties() throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE goods(\n" +
-                        "item_id1 INT,\n" +
-                        "item_name STRING,\n" +
-                        "price FLOAT\n" +
-                        ") DISTRIBUTED BY HASH(item_id1)\n" +
-                        "PROPERTIES(\"replication_num\" = \"1\");");
+                    .withTable("CREATE TABLE goods(\n" +
+                                "item_id1 INT,\n" +
+                                "item_name STRING,\n" +
+                                "price FLOAT\n" +
+                                ") DISTRIBUTED BY HASH(item_id1)\n" +
+                                "PROPERTIES(\"replication_num\" = \"1\");");
 
         starRocksAssert.withMaterializedView("CREATE MATERIALIZED VIEW order_mv\n" +
-                "DISTRIBUTED BY HASH(item_id1) BUCKETS 12\n" +
-                "PROPERTIES (\n" +
-                "\"partition_refresh_number\" = \"10\"\n" +
-                ")\n" +
-                "REFRESH ASYNC\n" +
-                "AS SELECT\n" +
-                "item_id1,\n" +
-                "sum(price) as total\n" +
-                "FROM goods\n" +
-                "GROUP BY item_id1;");
+                    "DISTRIBUTED BY HASH(item_id1) BUCKETS 12\n" +
+                    "PROPERTIES (\n" +
+                    "\"partition_refresh_number\" = \"10\"\n" +
+                    ")\n" +
+                    "REFRESH ASYNC\n" +
+                    "AS SELECT\n" +
+                    "item_id1,\n" +
+                    "sum(price) as total\n" +
+                    "FROM goods\n" +
+                    "GROUP BY item_id1;");
     }
 
     @Test
     public void testCreateMaterializedViewWithInactiveMaterializedView() throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE base_table\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
-                        "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');")
-                .withMaterializedView("CREATE MATERIALIZED VIEW base_mv\n" +
-                        "PARTITION BY k1\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "REFRESH manual\n" +
-                        "as select k1,k2,v1 from base_table;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView baseMv = ((MaterializedView) testDb.getTable("base_mv"));
+                    .withTable("CREATE TABLE base_table\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
+                                "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');")
+                    .withMaterializedView("CREATE MATERIALIZED VIEW base_mv\n" +
+                                "PARTITION BY k1\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "REFRESH manual\n" +
+                                "as select k1,k2,v1 from base_table;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView baseMv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), "base_mv"));
         baseMv.setInactiveAndReason("");
 
         SinglePartitionInfo singlePartitionInfo = new SinglePartitionInfo();
         MaterializedView.MvRefreshScheme refreshScheme = new MaterializedView.MvRefreshScheme();
         HashDistributionInfo hashDistributionInfo = new HashDistributionInfo(3, Lists.newArrayList(columns.get(0)));
         MaterializedView mv = new MaterializedView(1000, testDb.getId(), "mv", columns, KeysType.AGG_KEYS,
-                singlePartitionInfo, hashDistributionInfo, refreshScheme);
+                    singlePartitionInfo, hashDistributionInfo, refreshScheme);
         List<BaseTableInfo> baseTableInfos = Lists.newArrayList();
         BaseTableInfo baseTableInfo = new BaseTableInfo(testDb.getId(), testDb.getFullName(), baseMv.getName(), baseMv.getId());
         baseTableInfos.add(baseTableInfo);
@@ -572,22 +578,22 @@ public void testShouldRefreshBy() {
     @Test
     public void testShowSyncMV() throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.tbl_sync_mv\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
-                        "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');")
-                .withMaterializedView("create materialized view sync_mv_to_check\n" +
-                        "distributed by hash(k2) buckets 3\n" +
-                        "as select k2, sum(v1) as total from tbl_sync_mv group by k2;");
+                    .withTable("CREATE TABLE test.tbl_sync_mv\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
+                                "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');")
+                    .withMaterializedView("create materialized view sync_mv_to_check\n" +
+                                "distributed by hash(k2) buckets 3\n" +
+                                "as select k2, sum(v1) as total from tbl_sync_mv group by k2;");
         String showSql = "show create materialized view sync_mv_to_check;";
         StatementBase statement = SqlParser.parseSingleStatement(showSql, connectContext.getSessionVariable().getSqlMode());
         StmtExecutor stmtExecutor = new StmtExecutor(connectContext, statement);
@@ -615,7 +621,7 @@ public void testAlterMVWithIndex() throws Exception {
                         "distributed by hash(k2) buckets 3\n" +
                         "as select k2, sum(v1) as total from table1 group by k2;");
 
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
         Assert.assertNotNull(db);
         Table table = db.getTable("index_mv_to_check");
         Assert.assertNotNull(table);
@@ -641,7 +647,7 @@ public void testShowMVWithIndex() throws Exception {
         testAlterMVWithIndex();
         String showCreateSql = "show create materialized view test.index_mv_to_check;";
         ShowCreateTableStmt showCreateTableStmt =
-                (ShowCreateTableStmt) UtFrameUtils.parseStmtWithNewParser(showCreateSql, connectContext);
+                    (ShowCreateTableStmt) UtFrameUtils.parseStmtWithNewParser(showCreateSql, connectContext);
         ShowResultSet showResultSet = ShowExecutor.execute(showCreateTableStmt, connectContext);
         System.out.println(showResultSet.getMetaData().toString());
         System.out.println(showResultSet.getResultRows());
@@ -650,47 +656,47 @@ public void testShowMVWithIndex() throws Exception {
     @Test
     public void testAlterViewWithIndex() throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.table1\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
-                        "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');")
-                .withView("create view index_view_to_check\n" +
-                        "as select k2, sum(v1) as total from table1 group by k2;");
+                    .withTable("CREATE TABLE test.table1\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
+                                "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');")
+                    .withView("create view index_view_to_check\n" +
+                                "as select k2, sum(v1) as total from table1 group by k2;");
         String bitmapSql = "create index index1 ON test.index_view_to_check (k2) USING BITMAP COMMENT 'balabala'";
         AlterTableStmt alterViewStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(bitmapSql, connectContext);
         Assert.assertThrows("Do not support alter non-native table/materialized-view[index_view_to_check]",
-                SemanticException.class,
-                () -> DDLStmtExecutor.execute(alterViewStmt, connectContext));
+                    SemanticException.class,
+                    () -> DDLStmtExecutor.execute(alterViewStmt, connectContext));
     }
 
     public void testCreateMV(String mvSql) throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.table1\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
-                        "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');");
+                    .withTable("CREATE TABLE test.table1\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
+                                "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');");
         starRocksAssert.withMaterializedView(mvSql);
         String showCreateSql = "show create materialized view test.index_mv_to_check;";
         ShowCreateTableStmt showCreateTableStmt =
-                (ShowCreateTableStmt) UtFrameUtils.parseStmtWithNewParser(showCreateSql, connectContext);
+                    (ShowCreateTableStmt) UtFrameUtils.parseStmtWithNewParser(showCreateSql, connectContext);
         ShowResultSet showResultSet = ShowExecutor.execute(showCreateTableStmt, connectContext);
         System.out.println(showResultSet.getResultRows());
     }
@@ -698,109 +704,108 @@ public void testCreateMV(String mvSql) throws Exception {
     @Test
     public void testCreateMVWithIndex() throws Exception {
         String mvSqlWithBitMapAndBloomfilter = "create materialized view index_mv_to_check " +
-                "(k2 ," +
-                " total ," +
-                "INDEX index1 (`k2`) USING BITMAP COMMENT 'balabala' " +
-                ")" +
-                "DISTRIBUTED BY HASH(`k2`) BUCKETS 3 \n" +
-                "REFRESH MANUAL\n" +
-                "PROPERTIES " +
-                "("
-                + "\"replicated_storage\" = \"true\","
-                + "\"replication_num\" = \"1\","
-                + "\"storage_medium\" = \"HDD\","
-                + "\"bloom_filter_columns\" = \"k2\""
-                + ")" +
-                "as select k2, sum(v1) as total from table1 group by k2;";
+                    "(k2 ," +
+                    " total ," +
+                    "INDEX index1 (`k2`) USING BITMAP COMMENT 'balabala' " +
+                    ")" +
+                    "DISTRIBUTED BY HASH(`k2`) BUCKETS 3 \n" +
+                    "REFRESH MANUAL\n" +
+                    "PROPERTIES " +
+                    "("
+                    + "\"replicated_storage\" = \"true\","
+                    + "\"replication_num\" = \"1\","
+                    + "\"storage_medium\" = \"HDD\","
+                    + "\"bloom_filter_columns\" = \"k2\""
+                    + ")" +
+                    "as select k2, sum(v1) as total from table1 group by k2;";
         String mvSqlWithBitMap = "create materialized view index_mv_to_check " +
-                "(k2 ," +
-                " total ," +
-                "INDEX index1 (`k2`) USING BITMAP COMMENT 'balabala' " +
-                ")" +
-                "DISTRIBUTED BY HASH(`k2`) BUCKETS 3 \n" +
-                "REFRESH MANUAL\n" +
-                "PROPERTIES " +
-                "("
-                + "\"replicated_storage\" = \"true\","
-                + "\"replication_num\" = \"1\","
-                + "\"storage_medium\" = \"HDD\""
-                + ")" +
-                "as select k2, sum(v1) as total from table1 group by k2;";
+                    "(k2 ," +
+                    " total ," +
+                    "INDEX index1 (`k2`) USING BITMAP COMMENT 'balabala' " +
+                    ")" +
+                    "DISTRIBUTED BY HASH(`k2`) BUCKETS 3 \n" +
+                    "REFRESH MANUAL\n" +
+                    "PROPERTIES " +
+                    "("
+                    + "\"replicated_storage\" = \"true\","
+                    + "\"replication_num\" = \"1\","
+                    + "\"storage_medium\" = \"HDD\""
+                    + ")" +
+                    "as select k2, sum(v1) as total from table1 group by k2;";
         String mvSqlWithBloomFilter = "create materialized view index_mv_to_check " +
-                "(k2 ," +
-                " total" +
-                ")" +
-                "DISTRIBUTED BY HASH(`k2`) BUCKETS 3 \n" +
-                "REFRESH MANUAL\n" +
-                "PROPERTIES " +
-                "("
-                + "\"replicated_storage\" = \"true\","
-                + "\"replication_num\" = \"1\","
-                + "\"storage_medium\" = \"HDD\","
-                + "\"bloom_filter_columns\" = \"k2\""
-                + ")" +
-                "as select k2, sum(v1) as total from table1 group by k2;";
+                    "(k2 ," +
+                    " total" +
+                    ")" +
+                    "DISTRIBUTED BY HASH(`k2`) BUCKETS 3 \n" +
+                    "REFRESH MANUAL\n" +
+                    "PROPERTIES " +
+                    "("
+                    + "\"replicated_storage\" = \"true\","
+                    + "\"replication_num\" = \"1\","
+                    + "\"storage_medium\" = \"HDD\","
+                    + "\"bloom_filter_columns\" = \"k2\""
+                    + ")" +
+                    "as select k2, sum(v1) as total from table1 group by k2;";
         testCreateMV(mvSqlWithBitMapAndBloomfilter);
         testCreateMV(mvSqlWithBitMap);
         testCreateMV(mvSqlWithBloomFilter);
     }
 
-
     @Test
     public void testCreateMVWithDuplicateIndexOrDuplicateColumn() throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.table1\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
-                        "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');");
+                    .withTable("CREATE TABLE test.table1\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
+                                "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');");
         String mvSql = "create materialized view index_mv_to_check " +
-                "(k2 ," +
-                " total ," +
-                "INDEX index1 (`k2`) USING BITMAP COMMENT 'balabala', " +
-                "INDEX index1 (`total`) USING BITMAP COMMENT 'balabala' " +
-                ")" +
-                "DISTRIBUTED BY HASH(`k2`) BUCKETS 3 \n" +
-                "REFRESH MANUAL\n" +
-                "PROPERTIES " +
-                "("
-                + "\"replicated_storage\" = \"true\","
-                + "\"replication_num\" = \"1\","
-                + "\"storage_medium\" = \"HDD\","
-                + "\"bloom_filter_columns\" = \"k2\""
-                + ")" +
-                "as select k2, sum(v1) as total from table1 group by k2;";
+                    "(k2 ," +
+                    " total ," +
+                    "INDEX index1 (`k2`) USING BITMAP COMMENT 'balabala', " +
+                    "INDEX index1 (`total`) USING BITMAP COMMENT 'balabala' " +
+                    ")" +
+                    "DISTRIBUTED BY HASH(`k2`) BUCKETS 3 \n" +
+                    "REFRESH MANUAL\n" +
+                    "PROPERTIES " +
+                    "("
+                    + "\"replicated_storage\" = \"true\","
+                    + "\"replication_num\" = \"1\","
+                    + "\"storage_medium\" = \"HDD\","
+                    + "\"bloom_filter_columns\" = \"k2\""
+                    + ")" +
+                    "as select k2, sum(v1) as total from table1 group by k2;";
         Assert.assertThrows("Duplicate index name 'index1'",
-                UserException.class,
-                () -> starRocksAssert.withMaterializedView(mvSql));
+                    UserException.class,
+                    () -> starRocksAssert.withMaterializedView(mvSql));
 
         String mvSql2 = "create materialized view index_mv_to_check " +
-                "(k2 ," +
-                " total ," +
-                "INDEX index1 (`k2`) USING BITMAP COMMENT 'balabala', " +
-                "INDEX index2 (`k2`) USING BITMAP COMMENT 'balabala' " +
-                ")" +
-                "DISTRIBUTED BY HASH(`k2`) BUCKETS 3 \n" +
-                "REFRESH MANUAL\n" +
-                "PROPERTIES " +
-                "("
-                + "\"replicated_storage\" = \"true\","
-                + "\"replication_num\" = \"1\","
-                + "\"storage_medium\" = \"HDD\","
-                + "\"bloom_filter_columns\" = \"k2\""
-                + ")" +
-                "as select k2, sum(v1) as total from table1 group by k2;";
+                    "(k2 ," +
+                    " total ," +
+                    "INDEX index1 (`k2`) USING BITMAP COMMENT 'balabala', " +
+                    "INDEX index2 (`k2`) USING BITMAP COMMENT 'balabala' " +
+                    ")" +
+                    "DISTRIBUTED BY HASH(`k2`) BUCKETS 3 \n" +
+                    "REFRESH MANUAL\n" +
+                    "PROPERTIES " +
+                    "("
+                    + "\"replicated_storage\" = \"true\","
+                    + "\"replication_num\" = \"1\","
+                    + "\"storage_medium\" = \"HDD\","
+                    + "\"bloom_filter_columns\" = \"k2\""
+                    + ")" +
+                    "as select k2, sum(v1) as total from table1 group by k2;";
         Assert.assertThrows("Duplicate column name 'k2' in index",
-                UserException.class,
-                () -> starRocksAssert.withMaterializedView(mvSql2));
+                    UserException.class,
+                    () -> starRocksAssert.withMaterializedView(mvSql2));
     }
 
     @Test
@@ -813,6 +818,6 @@ public void testBasePartitionInfo() {
         Assert.assertEquals(100, basePartitionInfo.getExtLastFileModifiedTime());
         Assert.assertEquals(10, basePartitionInfo.getFileNumber());
         Assert.assertTrue(basePartitionInfo.toString().contains(
-                "BasePartitionInfo{id=-1, version=-1, lastRefreshTime=123456, lastFileModifiedTime=100, fileNumber=10}"));
+                    "BasePartitionInfo{id=-1, version=-1, lastRefreshTime=123456, lastFileModifiedTime=100, fileNumber=10}"));
     }
 }
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/MetadataViewerTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/MetadataViewerTest.java
index 0f49ed124eaffb..e3b1eab9679bb8 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/MetadataViewerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/MetadataViewerTest.java
@@ -96,9 +96,13 @@ public void before() {
                 minTimes = 0;
                 result = globalStateMgr;
 
-                globalStateMgr.getDb(anyString);
+                globalStateMgr.getLocalMetastore().getDb(anyString);
                 minTimes = 0;
                 result = db;
+
+                globalStateMgr.getLocalMetastore().getTable(anyString, anyString);
+                minTimes = 0;
+                result = db.getTable(CatalogMocker.TEST_TBL_NAME);
             }
         };
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/ReplaceLakePartitionTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/ReplaceLakePartitionTest.java
index e2d53779efe011..cf62ab256e2efb 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/ReplaceLakePartitionTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/ReplaceLakePartitionTest.java
@@ -14,6 +14,7 @@
 package com.starrocks.catalog;
 
 import com.google.common.collect.Lists;
+import com.google.common.collect.Range;
 import com.staros.client.StarClientException;
 import com.staros.proto.FilePathInfo;
 import com.staros.proto.ShardInfo;
@@ -22,14 +23,17 @@
 import com.starrocks.catalog.MaterializedIndex;
 import com.starrocks.catalog.Partition;
 import com.starrocks.catalog.PartitionInfo;
+import com.starrocks.catalog.PartitionKey;
 import com.starrocks.catalog.PartitionType;
 import com.starrocks.catalog.TabletInvertedIndex;
 import com.starrocks.catalog.TabletMeta;
 import com.starrocks.catalog.Type;
+import com.starrocks.common.ExceptionChecker;
 import com.starrocks.lake.DataCacheInfo;
 import com.starrocks.lake.LakeTable;
 import com.starrocks.lake.LakeTablet;
 import com.starrocks.lake.StarOSAgent;
+import com.starrocks.persist.EditLog;
 import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.server.WarehouseManager;
 import com.starrocks.thrift.TStorageMedium;
@@ -39,8 +43,11 @@
 import mockit.Mock;
 import mockit.MockUp;
 import mockit.Mocked;
+import org.junit.Assert;
 import org.junit.Test;
 
+import java.util.List;
+
 public class ReplaceLakePartitionTest {
     long dbId = 9010;
     long tableId = 9011;
@@ -51,6 +58,8 @@ public class ReplaceLakePartitionTest {
     long nextTxnId = 20000;
     String partitionName = "p0";
     String tempPartitionName = "temp_" + partitionName;
+    long[] newTabletId = {9030, 90031};
+    long newPartitionId = 9040;
 
     LakeTable tbl = null;
     private final ShardInfo shardInfo;
@@ -61,6 +70,9 @@ public class ReplaceLakePartitionTest {
     @Mocked
     private WarehouseManager warehouseManager;
 
+    @Mocked
+    private EditLog editLog;
+
     public ReplaceLakePartitionTest() {
         shardInfo = ShardInfo.newBuilder().setFilePath(FilePathInfo.newBuilder().setFullPath("oss://1/2")).build();
         warehouseManager = new WarehouseManager();
@@ -78,7 +90,21 @@ LakeTable buildLakeTableWithTempPartition(PartitionType partitionType) {
         Partition partition = new Partition(partitionId, partitionName, index, null);
         Partition tempPartition = new Partition(tempPartitionId, tempPartitionName, index, null);
 
-        PartitionInfo partitionInfo = new PartitionInfo(partitionType);
+        PartitionInfo partitionInfo = null;
+        if (partitionType == PartitionType.UNPARTITIONED) {
+            partitionInfo = new PartitionInfo(partitionType);
+        } else if (partitionType == PartitionType.LIST) {
+            partitionInfo = new ListPartitionInfo(PartitionType.LIST, Lists.newArrayList(new Column("c0", Type.BIGINT)));
+            List<String> values = Lists.newArrayList();
+            values.add("123");
+            ((ListPartitionInfo) partitionInfo).setValues(partitionId, values);
+        } else if (partitionType == PartitionType.RANGE) {
+            PartitionKey partitionKey = new PartitionKey();
+            Range<PartitionKey> range = Range.closedOpen(partitionKey, partitionKey);
+            partitionInfo = new RangePartitionInfo(Lists.newArrayList(new Column("c0", Type.BIGINT)));
+            ((RangePartitionInfo) partitionInfo).setRange(partitionId, false, range);
+        }
+
         partitionInfo.setReplicationNum(partitionId, (short) 1);
         partitionInfo.setIsInMemory(partitionId, false);
         partitionInfo.setDataCacheInfo(partitionId, new DataCacheInfo(true, false));
@@ -91,12 +117,20 @@ LakeTable buildLakeTableWithTempPartition(PartitionType partitionType) {
         table.addTempPartition(tempPartition);
         return table;
     }
+    
+    Partition buildPartitionForTruncateTable() {
+        MaterializedIndex index = new MaterializedIndex(indexId);
+        TabletInvertedIndex invertedIndex = GlobalStateMgr.getCurrentState().getTabletInvertedIndex();
+        for (long id : newTabletId) {
+            TabletMeta tabletMeta = new TabletMeta(dbId, tableId, newPartitionId, 0, 0, TStorageMedium.HDD, true);
+            invertedIndex.addTablet(id, tabletMeta);
+            index.addTablet(new LakeTablet(id), tabletMeta);
+        }
 
-    @Test
-    public void testUnPartitionedLakeTableReplacePartition() {
-        LakeTable tbl = buildLakeTableWithTempPartition(PartitionType.UNPARTITIONED);
-        tbl.replacePartition(partitionName, tempPartitionName);
+        return new Partition(newPartitionId, partitionName, index, null);
+    }
 
+    private void erasePartition() {
         new Expectations() {
             {
                 GlobalStateMgr.getCurrentState().getWarehouseMgr();
@@ -105,6 +139,13 @@ public void testUnPartitionedLakeTableReplacePartition() {
             }
         };
 
+        new MockUp<GlobalStateMgr>() {
+            @Mock
+            public EditLog getEditLog() {
+                return editLog;
+            }
+        };
+
         new MockUp<GlobalStateMgr>() {
             @Mock
             public StarOSAgent getStarOSAgent() {
@@ -119,6 +160,13 @@ public ShardInfo getShardInfo(long shardId, long workerGroupId) throws StarClien
             }
         };
 
+        new MockUp<EditLog>() {
+            @Mock
+            public void logErasePartition(long partitionId) {
+                return;
+            }
+        };
+
         new MockUp<WarehouseManager>() {
             @Mock
             public Warehouse getBackgroundWarehouse() {
@@ -126,9 +174,46 @@ public Warehouse getBackgroundWarehouse() {
             }
         };
 
-        try {
-            GlobalStateMgr.getCurrentState().getRecycleBin().erasePartition(Long.MAX_VALUE);
-        } catch (Exception ignore) {
-        }
+        ExceptionChecker.expectThrowsNoException(()
+                            -> GlobalStateMgr.getCurrentState().getRecycleBin().erasePartition(Long.MAX_VALUE));
+    }
+
+    @Test
+    public void testUnPartitionedLakeTableReplacePartition() {
+        LakeTable tbl = buildLakeTableWithTempPartition(PartitionType.UNPARTITIONED);
+        tbl.replacePartition(partitionName, tempPartitionName);
+        Assert.assertTrue(GlobalStateMgr.getCurrentState().getRecycleBin().isContainedInidToRecycleTime(partitionId));
+        erasePartition();
+        Assert.assertTrue(!GlobalStateMgr.getCurrentState().getRecycleBin().isContainedInidToRecycleTime(partitionId));
+    }
+
+    @Test
+    public void testUnPartitionedLakeTableReplacePartitionForTruncateTable() {
+        LakeTable tbl = buildLakeTableWithTempPartition(PartitionType.UNPARTITIONED);
+        Partition newPartition = buildPartitionForTruncateTable();
+        tbl.replacePartition(newPartition);
+        Assert.assertTrue(GlobalStateMgr.getCurrentState().getRecycleBin().isContainedInidToRecycleTime(partitionId));
+        erasePartition();
+        Assert.assertTrue(!GlobalStateMgr.getCurrentState().getRecycleBin().isContainedInidToRecycleTime(partitionId));
+    }
+
+    @Test
+    public void testListPartitionedLakeTableReplacePartitionForTruncateTable() {
+        LakeTable tbl = buildLakeTableWithTempPartition(PartitionType.LIST);
+        Partition newPartition = buildPartitionForTruncateTable();
+        tbl.replacePartition(newPartition);
+        Assert.assertTrue(GlobalStateMgr.getCurrentState().getRecycleBin().isContainedInidToRecycleTime(partitionId));
+        erasePartition();
+        Assert.assertTrue(!GlobalStateMgr.getCurrentState().getRecycleBin().isContainedInidToRecycleTime(partitionId));
+    }
+
+    @Test
+    public void testRangePartitionedLakeTableReplacePartitionForTruncateTable() {
+        LakeTable tbl = buildLakeTableWithTempPartition(PartitionType.RANGE);
+        Partition newPartition = buildPartitionForTruncateTable();
+        tbl.replacePartition(newPartition);
+        Assert.assertTrue(GlobalStateMgr.getCurrentState().getRecycleBin().isContainedInidToRecycleTime(partitionId));
+        erasePartition();
+        Assert.assertTrue(!GlobalStateMgr.getCurrentState().getRecycleBin().isContainedInidToRecycleTime(partitionId));
     }
 }
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/StorageCoolDownTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/StorageCoolDownTest.java
index 7983b395f4db85..0afeeb9ba98b3e 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/StorageCoolDownTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/StorageCoolDownTest.java
@@ -142,7 +142,7 @@ public void testDateWithTTLLessThan() throws Exception {
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getDb("test")
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
                 .getTable("site_access_datetime_with_1_day_ttl_less_than");
 
         RangePartitionInfo partitionInfo = (RangePartitionInfo) table.getPartitionInfo();
@@ -200,7 +200,7 @@ public void testDateWithTTLUpperLower() throws Exception {
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getDb("test")
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
                 .getTable("site_access_date_upper_lower_ttl");
 
         RangePartitionInfo partitionInfo = (RangePartitionInfo) table.getPartitionInfo();
@@ -250,7 +250,7 @@ public void testDateWithTTLStartEnd() throws Exception {
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getDb("test")
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
                 .getTable("site_access_date_with_1_day_ttl_start_end");
 
         RangePartitionInfo partitionInfo = (RangePartitionInfo) table.getPartitionInfo();
@@ -303,7 +303,7 @@ public void testDateTimeWithTTLLessThan() throws Exception {
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getDb("test")
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
                 .getTable("site_access_date_with_1_day_ttl_less_than");
 
         RangePartitionInfo partitionInfo = (RangePartitionInfo) table.getPartitionInfo();
@@ -356,7 +356,7 @@ public void testDateTimeWithMaxPartition() throws Exception {
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getDb("test")
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
                 .getTable("site_access_with_max_partition");
 
         RangePartitionInfo partitionInfo = (RangePartitionInfo) table.getPartitionInfo();
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/StorageMediumInferTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/StorageMediumInferTest.java
index 9fd815f8416f86..c91ada87c2f037 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/StorageMediumInferTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/StorageMediumInferTest.java
@@ -85,14 +85,14 @@ private static void alterTableWithNewParser(String sql) throws Exception {
 
     @Test
     public void testCreateTable() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
 
         be1.setStorageMediumForAllDisks(TStorageMedium.HDD);
         be2.setStorageMediumForAllDisks(TStorageMedium.HDD);
         createTable("create table test.tbl1(key1 int, key2 varchar(10)) \n" +
                 "distributed by hash(key1) buckets 10 properties('replication_num' = '1');");
-        OlapTable tbl1 = (OlapTable) db.getTable("tbl1");
+        OlapTable tbl1 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl1");
         List<Partition> partitionList1 = Lists.newArrayList(tbl1.getPartitions());
         DataProperty dataProperty1 =
                 globalStateMgr.getLocalMetastore().getDataPropertyIncludeRecycleBin(tbl1.getPartitionInfo(),
@@ -105,7 +105,7 @@ public void testCreateTable() throws Exception {
                 + "duplicate key(k1)\n" + "partition by range(k2)\n" + "(partition p1 values less than(\"10\"))\n"
                 + "distributed by hash(k2) buckets 1\n" + "properties('replication_num' = '1'); ";
         createTable(sql);
-        OlapTable tbl2 = (OlapTable) db.getTable("tbl2");
+        OlapTable tbl2 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl2");
         List<Partition> partitionList2 = Lists.newArrayList(tbl2.getPartitions());
         DataProperty dataProperty2 =
                 globalStateMgr.getLocalMetastore().getDataPropertyIncludeRecycleBin(tbl2.getPartitionInfo(),
@@ -117,7 +117,7 @@ public void testCreateTable() throws Exception {
         Config.tablet_sched_storage_cooldown_second = 123123213L;
         createTable("create table test.tbl3(key1 int, key2 varchar(10)) \n" +
                 "distributed by hash(key1) buckets 10 properties('replication_num' = '1');");
-        OlapTable tbl3 = (OlapTable) db.getTable("tbl3");
+        OlapTable tbl3 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl3");
         List<Partition> partitionList3 = Lists.newArrayList(tbl3.getPartitions());
         DataProperty dataProperty3 =
                 globalStateMgr.getLocalMetastore().getDataPropertyIncludeRecycleBin(tbl3.getPartitionInfo(),
@@ -127,7 +127,7 @@ public void testCreateTable() throws Exception {
         Config.tablet_sched_storage_cooldown_second = -1L; // default value, no storage cool down
         createTable("create table test.tbl4(key1 int, key2 varchar(10)) \n" +
                 "distributed by hash(key1) buckets 10 properties('replication_num' = '1');");
-        OlapTable tbl4 = (OlapTable) db.getTable("tbl4");
+        OlapTable tbl4 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl4");
         List<Partition> partitionList4 = Lists.newArrayList(tbl4.getPartitions());
         DataProperty dataProperty4 =
                 globalStateMgr.getLocalMetastore().getDataPropertyIncludeRecycleBin(tbl4.getPartitionInfo(),
@@ -137,7 +137,7 @@ public void testCreateTable() throws Exception {
 
     @Test
     public void testAlterTableAddPartition() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
         be1.setStorageMediumForAllDisks(TStorageMedium.SSD);
         be2.setStorageMediumForAllDisks(TStorageMedium.SSD);
@@ -146,7 +146,7 @@ public void testAlterTableAddPartition() throws Exception {
                 + "distributed by hash(k2) buckets 1\n" + "properties('replication_num' = '1'); ";
         createTable(sql);
         alterTableWithNewParser("ALTER TABLE test.tblp2 ADD PARTITION IF NOT EXISTS p2 VALUES LESS THAN (\"20\")");
-        OlapTable tbl2 = (OlapTable) db.getTable("tblp2");
+        OlapTable tbl2 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tblp2");
         List<Partition> partitionList2 = Lists.newArrayList(tbl2.getPartitions());
         Assert.assertEquals(2, partitionList2.size());
         for (Partition partition : partitionList2) {
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/TableFunctionTableTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/TableFunctionTableTest.java
index fbe579c84623e9..585257435367fc 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/TableFunctionTableTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/TableFunctionTableTest.java
@@ -52,6 +52,7 @@ Map<String, String> newProperties() {
         properties.put("path", "fake://some_bucket/some_path/*");
         properties.put("format", "ORC");
         properties.put("columns_from_path", "col_path1, col_path2,   col_path3");
+        properties.put("strict_mode", "true");
         properties.put("auto_detect_sample_files", "10");
         properties.put("csv.column_separator", ",");
         properties.put("csv.row_delimiter", "\n");
@@ -154,6 +155,7 @@ public void testProperties() {
             Assert.assertEquals("ORC", Deencapsulation.getField(table, "format"));
             Assert.assertEquals(Arrays.asList("col_path1", "col_path2", "col_path3"),
                     Deencapsulation.getField(table, "columnsFromPath"));
+            Assert.assertEquals(true, table.isStrictMode());
             Assert.assertEquals(10, (int) Deencapsulation.getField(table, "autoDetectSampleFiles"));
             Assert.assertEquals("\n", table.getCsvRowDelimiter());
             Assert.assertEquals(",", table.getCsvColumnSeparator());
diff --git a/fe/fe-core/src/test/java/com/starrocks/catalog/TempPartitionTest.java b/fe/fe-core/src/test/java/com/starrocks/catalog/TempPartitionTest.java
index cb4a0244d79d8c..a25ca833f465d7 100644
--- a/fe/fe-core/src/test/java/com/starrocks/catalog/TempPartitionTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/catalog/TempPartitionTest.java
@@ -379,7 +379,7 @@ public void testForMultiPartitionTable() throws Exception {
                         "distributed by hash(k2) buckets 1\n" +
                         "properties('replication_num' = '1');");
 
-        Database db2 = GlobalStateMgr.getCurrentState().getDb("db2");
+        Database db2 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db2");
         OlapTable tbl2 = (OlapTable) db2.getTable("tbl2");
 
         Map<String, Long> originPartitionTabletIds = Maps.newHashMap();
@@ -608,7 +608,7 @@ public void testForMultiPartitionTable() throws Exception {
         }
 
         OlapTable olapTable =
-                (OlapTable) GlobalStateMgr.getCurrentState().getDb("db2").getTable("tbl2");
+                (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db2").getTable("tbl2");
 
         // waiting table state to normal
         int retryTimes = 5;
@@ -675,7 +675,7 @@ public void testForStrictRangeCheck() throws Exception {
                 "distributed by hash(k2) buckets 1\n" +
                 "properties('replication_num' = '1');");
 
-        Database db3 = GlobalStateMgr.getCurrentState().getDb("db3");
+        Database db3 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db3");
         OlapTable tbl3 = (OlapTable) db3.getTable("tbl3");
 
         // base range is [min, 10), [10, 20), [20, 30)
diff --git a/fe/fe-core/src/test/java/com/starrocks/clone/ColocateTableBalancerTest.java b/fe/fe-core/src/test/java/com/starrocks/clone/ColocateTableBalancerTest.java
index 2fb08ff1d8aeb8..5687eb8d18e61d 100644
--- a/fe/fe-core/src/test/java/com/starrocks/clone/ColocateTableBalancerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/clone/ColocateTableBalancerTest.java
@@ -143,24 +143,25 @@ private ColocateTableIndex createColocateIndex(GroupId groupId, List<Long> flatL
     }
 
     private void addTabletsToScheduler(String dbName, String tableName, boolean setGroupId) {
-        Database database = GlobalStateMgr.getCurrentState().getDb(dbName);
-        OlapTable table = (OlapTable) database.getTable(tableName);
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
+        OlapTable table =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), tableName);
         // add its tablet to TabletScheduler
         TabletScheduler tabletScheduler = GlobalStateMgr.getCurrentState().getTabletScheduler();
         for (Partition partition : table.getPartitions()) {
             MaterializedIndex materializedIndex = partition.getBaseIndex();
             for (Tablet tablet : materializedIndex.getTablets()) {
                 TabletSchedCtx ctx = new TabletSchedCtx(TabletSchedCtx.Type.REPAIR,
-                        database.getId(),
-                        table.getId(),
-                        partition.getId(),
-                        materializedIndex.getId(),
-                        tablet.getId(),
-                        System.currentTimeMillis());
+                            database.getId(),
+                            table.getId(),
+                            partition.getId(),
+                            materializedIndex.getId(),
+                            tablet.getId(),
+                            System.currentTimeMillis());
                 ctx.setOrigPriority(TabletSchedCtx.Priority.LOW);
                 if (setGroupId) {
                     ctx.setColocateGroupId(
-                            GlobalStateMgr.getCurrentState().getColocateTableIndex().getGroup(table.getId()));
+                                GlobalStateMgr.getCurrentState().getColocateTableIndex().getGroup(table.getId()));
                 }
                 tabletScheduler.addTablet(ctx, false);
             }
@@ -170,12 +171,13 @@ private void addTabletsToScheduler(String dbName, String tableName, boolean setG
     @Test
     public void test1MatchGroup() throws Exception {
         starRocksAssert.withDatabase("db1").useDatabase("db1")
-                .withTable("CREATE TABLE db1.tbl(id INT NOT NULL) " +
-                        "distributed by hash(`id`) buckets 3 " +
-                        "properties('replication_num' = '1', 'colocate_with' = 'group1');");
+                    .withTable("CREATE TABLE db1.tbl(id INT NOT NULL) " +
+                                "distributed by hash(`id`) buckets 3 " +
+                                "properties('replication_num' = '1', 'colocate_with' = 'group1');");
 
-        Database database = GlobalStateMgr.getCurrentState().getDb("db1");
-        OlapTable table = (OlapTable) database.getTable("tbl");
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db1");
+        OlapTable table =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), "tbl");
         addTabletsToScheduler("db1", "tbl", false);
 
         ColocateTableIndex colocateIndex = GlobalStateMgr.getCurrentState().getColocateTableIndex();
@@ -203,12 +205,13 @@ public void test3RepairWithBadReplica() throws Exception {
         UtFrameUtils.addMockBackend(10003);
         UtFrameUtils.addMockBackend(10004);
         starRocksAssert.withDatabase("db3").useDatabase("db3")
-                .withTable("CREATE TABLE db3.tbl3(id INT NOT NULL) " +
-                        "distributed by hash(`id`) buckets 1 " +
-                        "properties('replication_num' = '1', 'colocate_with' = 'group3');");
+                    .withTable("CREATE TABLE db3.tbl3(id INT NOT NULL) " +
+                                "distributed by hash(`id`) buckets 1 " +
+                                "properties('replication_num' = '1', 'colocate_with' = 'group3');");
 
-        Database database = GlobalStateMgr.getCurrentState().getDb("db3");
-        OlapTable table = (OlapTable) database.getTable("tbl3");
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db3");
+        OlapTable table =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), "tbl3");
         ColocateTableIndex colocateTableIndex = GlobalStateMgr.getCurrentState().getColocateTableIndex();
 
         List<Partition> partitions = Lists.newArrayList(table.getPartitions());
@@ -309,7 +312,7 @@ public void testRepairPrecedeBalance(@Mocked SystemInfoService infoService,
         GroupId groupId = new GroupId(10005, 10006);
         short replicationNUm = 3;
         ColocateTableIndex colocateTableIndex = createColocateIndex(groupId,
-                Lists.newArrayList(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 4L, 1L, 2L, 5L), replicationNUm);
+                    Lists.newArrayList(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 4L, 1L, 2L, 5L), replicationNUm);
         setGroup2Schema(groupId, colocateTableIndex, 4, replicationNUm);
 
         Set<Long> unavailableBeIds = Sets.newHashSet(5L);
@@ -318,23 +321,23 @@ public void testRepairPrecedeBalance(@Mocked SystemInfoService infoService,
         boolean changed = false;
         ColocateTableBalancer.disableRepairPrecedence = true;
         changed = (Boolean) Deencapsulation
-                .invoke(balancer, "doRelocateAndBalance", groupId, unavailableBeIds, availBackendIds,
-                        colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
+                    .invoke(balancer, "doRelocateAndBalance", groupId, unavailableBeIds, availBackendIds,
+                                colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
         Assert.assertTrue(changed);
         System.out.println(balancedBackendsPerBucketSeq);
         List<List<Long>> expected = Lists.partition(
-                Lists.newArrayList(4L, 2L, 3L, 1L, 2L, 3L, 1L, 3L, 4L, 1L, 2L, 4L), 3);
+                    Lists.newArrayList(4L, 2L, 3L, 1L, 2L, 3L, 1L, 3L, 4L, 1L, 2L, 4L), 3);
         Assert.assertEquals(expected, balancedBackendsPerBucketSeq);
 
         ColocateTableBalancer.disableRepairPrecedence = false;
         balancedBackendsPerBucketSeq.clear();
         changed = (Boolean) Deencapsulation
-                .invoke(balancer, "doRelocateAndBalance", groupId, unavailableBeIds, availBackendIds,
-                        colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
+                    .invoke(balancer, "doRelocateAndBalance", groupId, unavailableBeIds, availBackendIds,
+                                colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
         Assert.assertTrue(changed);
         System.out.println(balancedBackendsPerBucketSeq);
         expected = Lists.partition(
-                Lists.newArrayList(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 4L, 1L, 2L, 4L), 3);
+                    Lists.newArrayList(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 4L, 1L, 2L, 4L), 3);
         Assert.assertEquals(expected, balancedBackendsPerBucketSeq);
     }
 
@@ -389,7 +392,6 @@ public void testPerGroupBalance(@Mocked SystemInfoService infoService,
             }
         };
 
-
         GroupId groupId = new GroupId(10000, 10001);
         List<Column> distributionCols = Lists.newArrayList();
         distributionCols.add(new Column("k1", Type.INT));
@@ -401,27 +403,27 @@ public void testPerGroupBalance(@Mocked SystemInfoService infoService,
         // [[1, 2, 3], [4, 1, 2], [3, 4, 1], [2, 3, 4], [1, 2, 3]]
         FeConstants.runningUnitTest = true;
         ColocateTableIndex colocateTableIndex = createColocateIndex(groupId,
-                Lists.newArrayList(1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L), 3);
+                    Lists.newArrayList(1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L), 3);
         Deencapsulation.setField(colocateTableIndex, "group2Schema", group2Schema);
 
         List<List<Long>> balancedBackendsPerBucketSeq = Lists.newArrayList();
         List<Long> allAvailBackendIds = Lists.newArrayList(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L);
         boolean changed = (Boolean) Deencapsulation
-                .invoke(balancer, "doRelocateAndBalance", groupId, new HashSet<Long>(), allAvailBackendIds,
-                        colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
+                    .invoke(balancer, "doRelocateAndBalance", groupId, new HashSet<Long>(), allAvailBackendIds,
+                                colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
         List<List<Long>> expected = Lists.partition(
-                Lists.newArrayList(9L, 5L, 3L, 4L, 6L, 8L, 7L, 6L, 1L, 2L, 9L, 4L, 1L, 2L, 3L), 3);
+                    Lists.newArrayList(9L, 5L, 3L, 4L, 6L, 8L, 7L, 6L, 1L, 2L, 9L, 4L, 1L, 2L, 3L), 3);
         Assert.assertTrue(changed);
         Assert.assertEquals(expected, balancedBackendsPerBucketSeq);
 
         // 2. balance an already balanced group
         colocateTableIndex = createColocateIndex(groupId,
-                Lists.newArrayList(9L, 8L, 7L, 8L, 6L, 5L, 9L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L), 3);
+                    Lists.newArrayList(9L, 8L, 7L, 8L, 6L, 5L, 9L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L), 3);
         Deencapsulation.setField(colocateTableIndex, "group2Schema", group2Schema);
         balancedBackendsPerBucketSeq.clear();
         changed = (Boolean) Deencapsulation
-                .invoke(balancer, "doRelocateAndBalance", groupId, new HashSet<Long>(), allAvailBackendIds,
-                        colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
+                    .invoke(balancer, "doRelocateAndBalance", groupId, new HashSet<Long>(), allAvailBackendIds,
+                                colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
         System.out.println(balancedBackendsPerBucketSeq);
         Assert.assertFalse(changed);
         Assert.assertTrue(balancedBackendsPerBucketSeq.isEmpty());
@@ -516,10 +518,10 @@ public synchronized Map<GroupId, Long> getTabletsNumInScheduleForEachCG() {
         ColocateTableIndex colocateTableIndex = GlobalStateMgr.getCurrentState().getColocateTableIndex();
         // For group 1, bucket: 3, replication_num: 1, backend list per bucket seq: [[1], [2], [3]]
         colocateTableIndex.addBackendsPerBucketSeq(groupId1,
-                Lists.partition(Lists.newArrayList(1L, 2L, 3L), 1));
+                    Lists.partition(Lists.newArrayList(1L, 2L, 3L), 1));
         // For group 2, bucket: 3, replication_num: 1, backend list per bucket seq: [[1], [2], [3]]
         colocateTableIndex.addBackendsPerBucketSeq(groupId2,
-                Lists.partition(Lists.newArrayList(1L, 2L, 3L), 1));
+                    Lists.partition(Lists.newArrayList(1L, 2L, 3L), 1));
         Deencapsulation.setField(colocateTableIndex, "group2Schema", group2Schema);
         Multimap<GroupId, Long> group2Tables = ArrayListMultimap.create();
         group2Tables.put(groupId1, 20001L);
@@ -546,7 +548,7 @@ public synchronized Map<GroupId, Long> getTabletsNumInScheduleForEachCG() {
             // totally 6 replicas, after adding 2 backends and overall balance,
             // every backend should have 1 replica, except one
             Assert.assertEquals(Lists.newArrayList(1, 1, 1, 1, 2),
-                    result.values().stream().sorted().collect(Collectors.toList()));
+                        result.values().stream().sorted().collect(Collectors.toList()));
         }
     }
 
@@ -555,7 +557,7 @@ private void setGroup2Schema(GroupId groupId, ColocateTableIndex colocateTableIn
         List<Column> distributionCols = Lists.newArrayList();
         distributionCols.add(new Column("k1", Type.INT));
         ColocateGroupSchema groupSchema =
-                new ColocateGroupSchema(groupId, distributionCols, bucketNum, replicationNum);
+                    new ColocateGroupSchema(groupId, distributionCols, bucketNum, replicationNum);
         Map<GroupId, ColocateGroupSchema> group2Schema = Maps.newHashMap();
         group2Schema.put(groupId, groupSchema);
         Deencapsulation.setField(colocateTableIndex, "group2Schema", group2Schema);
@@ -611,7 +613,7 @@ public void testBalanceWithOnlyOneAvailableBackend(@Mocked SystemInfoService inf
         GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo().getIdToBackend();
         GroupId groupId = new GroupId(10000, 10001);
         ColocateTableIndex colocateTableIndex = createColocateIndex(groupId,
-                Lists.newArrayList(4L, 2L, 3L, 4L, 2L, 3L, 4L, 2L, 3L), 3);
+                    Lists.newArrayList(4L, 2L, 3L, 4L, 2L, 3L, 4L, 2L, 3L), 3);
         setGroup2Schema(groupId, colocateTableIndex, 3, (short) 3);
 
         Set<Long> unavailableBeIds = Sets.newHashSet(3L, 4L);
@@ -619,8 +621,8 @@ public void testBalanceWithOnlyOneAvailableBackend(@Mocked SystemInfoService inf
         List<Long> availBackendIds = Lists.newArrayList(2L);
 
         boolean changed = (Boolean) Deencapsulation
-                .invoke(balancer, "doRelocateAndBalance", groupId, unavailableBeIds, availBackendIds,
-                        colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
+                    .invoke(balancer, "doRelocateAndBalance", groupId, unavailableBeIds, availBackendIds,
+                                colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
         // in this case, there is only on available backend, no need to make balancing decision.
         Assert.assertFalse(changed);
     }
@@ -677,7 +679,7 @@ public void testBalanceWithSingleReplica(@Mocked SystemInfoService infoService,
         GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo().getIdToBackend();
         GroupId groupId = new GroupId(10000, 10001);
         ColocateTableIndex colocateTableIndex = createColocateIndex(groupId,
-                Lists.newArrayList(4L, 2L, 3L, 4L, 2L, 3L, 4L, 2L, 3L), 1);
+                    Lists.newArrayList(4L, 2L, 3L, 4L, 2L, 3L, 4L, 2L, 3L), 1);
         setGroup2Schema(groupId, colocateTableIndex, 9, (short) 1);
 
         Set<Long> unavailableBeIds = Sets.newHashSet(4L);
@@ -686,22 +688,22 @@ public void testBalanceWithSingleReplica(@Mocked SystemInfoService infoService,
         boolean changed = false;
 
         changed = (Boolean) Deencapsulation
-                .invoke(balancer, "doRelocateAndBalance", groupId, unavailableBeIds, availBackendIds,
-                        colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
+                    .invoke(balancer, "doRelocateAndBalance", groupId, unavailableBeIds, availBackendIds,
+                                colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
         // there is unavailable backend, but the replication number is 1 and replicas on available backends are
         // already balanced, so the bucket sequence will remain unchanged.
         Assert.assertFalse(changed);
 
         colocateTableIndex = createColocateIndex(groupId,
-                Lists.newArrayList(2L, 2L, 4L, 2L, 2L, 4L, 3L, 2L, 4L), 1);
+                    Lists.newArrayList(2L, 2L, 4L, 2L, 2L, 4L, 3L, 2L, 4L), 1);
         setGroup2Schema(groupId, colocateTableIndex, 9, (short) 1);
         changed = (Boolean) Deencapsulation
-                .invoke(balancer, "doRelocateAndBalance", groupId, unavailableBeIds, availBackendIds,
-                        colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
+                    .invoke(balancer, "doRelocateAndBalance", groupId, unavailableBeIds, availBackendIds,
+                                colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
         Assert.assertTrue(changed);
         System.out.println(balancedBackendsPerBucketSeq);
         List<List<Long>> expected = Lists.partition(
-                Lists.newArrayList(3L, 3L, 4L, 2L, 2L, 4L, 3L, 2L, 4L), 1);
+                    Lists.newArrayList(3L, 3L, 4L, 2L, 2L, 4L, 3L, 2L, 4L), 1);
         // there is unavailable backend, but the replication number is 1 and replicas on available backends are
         // not balanced, check the balancer actually working.
         Assert.assertEquals(expected, balancedBackendsPerBucketSeq);
@@ -715,15 +717,15 @@ public void testBalanceWithSingleReplica(@Mocked SystemInfoService infoService,
         };
         balancedBackendsPerBucketSeq = Lists.newArrayList();
         colocateTableIndex = createColocateIndex(groupId,
-                Lists.newArrayList(2L, 2L, 4L, 2L, 2L, 4L, 3L, 2L, 4L), 1);
+                    Lists.newArrayList(2L, 2L, 4L, 2L, 2L, 4L, 3L, 2L, 4L), 1);
         setGroup2Schema(groupId, colocateTableIndex, 9, (short) 1);
         changed = (Boolean) Deencapsulation
-                .invoke(balancer, "doRelocateAndBalance", groupId, unavailableBeIds, availBackendIds,
-                        colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
+                    .invoke(balancer, "doRelocateAndBalance", groupId, unavailableBeIds, availBackendIds,
+                                colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
         Assert.assertTrue(changed);
         System.out.println(balancedBackendsPerBucketSeq);
         List<List<Long>> expected3 = Lists.partition(
-                Lists.newArrayList(2L, 2L, 3L, 2L, 2L, 3L, 3L, 2L, 3L), 1);
+                    Lists.newArrayList(2L, 2L, 3L, 2L, 2L, 3L, 3L, 2L, 3L), 1);
         // there is unavailable backend, but the replication number is 1 and there is decommissioned backend,
         // so we need to do relocation first.
         Assert.assertEquals(expected3, balancedBackendsPerBucketSeq);
@@ -777,42 +779,42 @@ public void testFixBalanceEndlessLoop(@Mocked SystemInfoService infoService,
         // 1. only one available backend
         // [[7], [7], [7], [7], [7]]
         ColocateTableIndex colocateTableIndex = createColocateIndex(groupId,
-                Lists.newArrayList(7L, 7L, 7L, 7L, 7L), 3);
+                    Lists.newArrayList(7L, 7L, 7L, 7L, 7L), 3);
         Deencapsulation.setField(colocateTableIndex, "group2Schema", group2Schema);
 
         List<List<Long>> balancedBackendsPerBucketSeq = Lists.newArrayList();
         List<Long> allAvailBackendIds = Lists.newArrayList(7L);
         boolean changed =
-                Deencapsulation.invoke(balancer, "doRelocateAndBalance",
-                        groupId, new HashSet<Long>(), allAvailBackendIds,
-                        colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
+                    Deencapsulation.invoke(balancer, "doRelocateAndBalance",
+                                groupId, new HashSet<Long>(), allAvailBackendIds,
+                                colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
         Assert.assertFalse(changed);
 
         // 2. all backends are checked but this round is not changed
         // [[7], [7], [7], [7], [7]]
         // and add new backends 8, 9 that are on the same host with 7
         colocateTableIndex = createColocateIndex(groupId,
-                Lists.newArrayList(7L, 7L, 7L, 7L, 7L), 3);
+                    Lists.newArrayList(7L, 7L, 7L, 7L, 7L), 3);
         Deencapsulation.setField(colocateTableIndex, "group2Schema", group2Schema);
 
         balancedBackendsPerBucketSeq = Lists.newArrayList();
         allAvailBackendIds = Lists.newArrayList(7L, 8L, 9L);
         changed =
-                Deencapsulation.invoke(balancer, "doRelocateAndBalance",
-                        groupId, new HashSet<Long>(), allAvailBackendIds,
-                        colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
+                    Deencapsulation.invoke(balancer, "doRelocateAndBalance",
+                                groupId, new HashSet<Long>(), allAvailBackendIds,
+                                colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
         Assert.assertFalse(changed);
 
         // 3. all backends are not available
         colocateTableIndex = createColocateIndex(groupId,
-                Lists.newArrayList(7L, 7L, 7L, 7L, 7L), 3);
+                    Lists.newArrayList(7L, 7L, 7L, 7L, 7L), 3);
         Deencapsulation.setField(colocateTableIndex, "group2Schema", group2Schema);
         balancedBackendsPerBucketSeq = Lists.newArrayList();
         allAvailBackendIds = Lists.newArrayList();
         Set<Long> unAvailableBackendIds = Sets.newHashSet(7L);
         changed = Deencapsulation
-                .invoke(balancer, "doRelocateAndBalance", groupId, unAvailableBackendIds, allAvailBackendIds,
-                        colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
+                    .invoke(balancer, "doRelocateAndBalance", groupId, unAvailableBackendIds, allAvailBackendIds,
+                                colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
         Assert.assertFalse(changed);
     }
 
@@ -836,15 +838,15 @@ BackendLoadStatistic delegate(Long beId) {
         Set<Long> unavailBackendIds = Sets.newHashSet(9L);
         List<Long> flatBackendsPerBucketSeq = Lists.newArrayList(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L);
         List<Map.Entry<Long, Long>> backends = Deencapsulation.invoke(balancer, "getSortedBackendReplicaNumPairs",
-                allAvailBackendIds, unavailBackendIds, statistic, flatBackendsPerBucketSeq);
+                    allAvailBackendIds, unavailBackendIds, statistic, flatBackendsPerBucketSeq);
         long[] backendIds = backends.stream().mapToLong(Map.Entry::getKey).toArray();
         Assert.assertArrayEquals(new long[] {7L, 8L, 6L, 2L, 3L, 5L, 4L, 1L}, backendIds);
 
         // 0,1 bucket on same be and 5, 6 on same be
         flatBackendsPerBucketSeq = Lists.newArrayList(1L, 1L, 3L, 4L, 5L, 6L, 7L, 7L, 9L);
         backends = Deencapsulation
-                .invoke(balancer, "getSortedBackendReplicaNumPairs", allAvailBackendIds, unavailBackendIds,
-                        statistic, flatBackendsPerBucketSeq);
+                    .invoke(balancer, "getSortedBackendReplicaNumPairs", allAvailBackendIds, unavailBackendIds,
+                                statistic, flatBackendsPerBucketSeq);
         backendIds = backends.stream().mapToLong(Map.Entry::getKey).toArray();
         Assert.assertArrayEquals(new long[] {7L, 1L, 6L, 3L, 5L, 4L, 8L, 2L}, backendIds);
     }
@@ -865,7 +867,7 @@ public double getMixLoadScore() {
     public void testGetBeSeqIndexes() {
         List<Long> flatBackendsPerBucketSeq = Lists.newArrayList(1L, 2L, 2L, 3L, 4L, 2L);
         List<Integer> indexes = Deencapsulation.invoke(balancer,
-                "getBeSeqIndexes", flatBackendsPerBucketSeq, 2L);
+                    "getBeSeqIndexes", flatBackendsPerBucketSeq, 2L);
         Assert.assertArrayEquals(new int[] {1, 2, 5}, indexes.stream().mapToInt(i -> i).toArray());
         System.out.println("backend1 id is " + backend1.getId());
     }
@@ -901,9 +903,9 @@ public void testGetUnavailableBeIdsInGroup() {
         GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo().getIdToBackend();
 
         Set<Long> unavailableBeIds = Deencapsulation
-                .invoke(balancer, "getUnavailableBeIdsInGroup", infoService, colocateTableIndex, groupId);
+                    .invoke(balancer, "getUnavailableBeIdsInGroup", infoService, colocateTableIndex, groupId);
         Assert.assertArrayEquals(new long[] {1L, 3L, 5L},
-                unavailableBeIds.stream().mapToLong(i -> i).sorted().toArray());
+                    unavailableBeIds.stream().mapToLong(i -> i).sorted().toArray());
     }
 
     @Test
@@ -1032,18 +1034,18 @@ BackendLoadStatistic delegate(Long beId) {
 
         // group is balanced before backend 9 is dropped
         ColocateTableIndex colocateTableIndex = createColocateIndex(groupId,
-                Lists.newArrayList(9L, 8L, 7L, 8L, 6L, 5L, 9L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L), 3);
+                    Lists.newArrayList(9L, 8L, 7L, 8L, 6L, 5L, 9L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L), 3);
         Deencapsulation.setField(colocateTableIndex, "group2Schema", group2Schema);
         List<List<Long>> balancedBackendsPerBucketSeq = Lists.newArrayList();
         Set<Long> unavailableBeIds = Sets.newHashSet(9L);
         List<Long> allAvailBackendIds = Lists.newArrayList(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L);
         boolean changed = (Boolean) Deencapsulation
-                .invoke(balancer, "doRelocateAndBalance", groupId, unavailableBeIds, allAvailBackendIds,
-                        colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
+                    .invoke(balancer, "doRelocateAndBalance", groupId, unavailableBeIds, allAvailBackendIds,
+                                colocateTableIndex, infoService, statistic, balancedBackendsPerBucketSeq);
         System.out.println(balancedBackendsPerBucketSeq);
         Assert.assertTrue(changed);
         List<List<Long>> expected = Lists.partition(
-                Lists.newArrayList(5L, 8L, 7L, 8L, 6L, 5L, 6L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L), 3);
+                    Lists.newArrayList(5L, 8L, 7L, 8L, 6L, 5L, 6L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L), 3);
         Assert.assertEquals(expected, balancedBackendsPerBucketSeq);
     }
 
@@ -1063,10 +1065,10 @@ public void testSystemStable() throws Exception {
         // set stable last time to 1s, and sleep 1s, the system becomes to stable
         Config.tablet_sched_colocate_balance_wait_system_stable_time_s = 1;
         System.out.println("before sleep, time: " + System.currentTimeMillis()
-                + "alive backend is: " + infoService.getBackendIds(true));
+                    + "alive backend is: " + infoService.getBackendIds(true));
         Thread.sleep(2000L);
         System.out.println("after sleep, time: " + System.currentTimeMillis()
-                + "alive backend is: " + infoService.getBackendIds(true));
+                    + "alive backend is: " + infoService.getBackendIds(true));
         Assert.assertTrue(balancer.isSystemStable(infoService));
         Assert.assertTrue(balancer.isSystemStable(infoService));
 
@@ -1075,10 +1077,10 @@ public void testSystemStable() throws Exception {
         Assert.assertFalse(balancer.isSystemStable(infoService));
         Assert.assertFalse(balancer.isSystemStable(infoService));
         System.out.println("before sleep, time: " + System.currentTimeMillis()
-                + "alive backend is: " + infoService.getBackendIds(true));
+                    + "alive backend is: " + infoService.getBackendIds(true));
         Thread.sleep(2000L);
         System.out.println("after sleep, time: " + System.currentTimeMillis()
-                + "alive backend is: " + infoService.getBackendIds(true));
+                    + "alive backend is: " + infoService.getBackendIds(true));
         Assert.assertTrue(balancer.isSystemStable(infoService));
     }
 }
diff --git a/fe/fe-core/src/test/java/com/starrocks/clone/DynamicPartitionSchedulerTest.java b/fe/fe-core/src/test/java/com/starrocks/clone/DynamicPartitionSchedulerTest.java
index 8ff094ff6ae2aa..e5e63ae28a7609 100644
--- a/fe/fe-core/src/test/java/com/starrocks/clone/DynamicPartitionSchedulerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/clone/DynamicPartitionSchedulerTest.java
@@ -58,28 +58,28 @@ public static void beforeClass() throws Exception {
     @Test
     public void testPartitionTTLProperties() throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.tbl1\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    v1 int \n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values less than('2020-02-01'),\n" +
-                        "    PARTITION p2 values less than('2020-03-01'),\n" +
-                        "    PARTITION p3 values less than('2020-04-01'),\n" +
-                        "    PARTITION p4 values less than('2020-05-01')\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH (k1) BUCKETS 3\n" +
-                        "PROPERTIES" +
-                        "(" +
-                        "    'replication_num' = '1'\n" +
-                        ");");
+                    .withTable("CREATE TABLE test.tbl1\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    v1 int \n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values less than('2020-02-01'),\n" +
+                                "    PARTITION p2 values less than('2020-03-01'),\n" +
+                                "    PARTITION p3 values less than('2020-04-01'),\n" +
+                                "    PARTITION p4 values less than('2020-05-01')\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH (k1) BUCKETS 3\n" +
+                                "PROPERTIES" +
+                                "(" +
+                                "    'replication_num' = '1'\n" +
+                                ");");
 
         DynamicPartitionScheduler dynamicPartitionScheduler = GlobalStateMgr.getCurrentState()
-                .getDynamicPartitionScheduler();
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("tbl1");
+                    .getDynamicPartitionScheduler();
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl1");
         // Now the table does not actually support partition ttl,
         // so in order to simplify the test, it is directly set like this
         tbl.getTableProperty().getProperties().put("partition_ttl_number", "3");
@@ -88,37 +88,36 @@ public void testPartitionTTLProperties() throws Exception {
         dynamicPartitionScheduler.registerTtlPartitionTable(db.getId(), tbl.getId());
         dynamicPartitionScheduler.runAfterCatalogReady();
 
-
         Assert.assertEquals(3, tbl.getPartitions().size());
     }
 
     @Test
     public void testPartitionTTLPropertiesZero() throws Exception {
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.base\n" +
-                        "(\n" +
-                        "    k1 date,\n" +
-                        "    k2 int,\n" +
-                        "    v1 int sum\n" +
-                        ")\n" +
-                        "PARTITION BY RANGE(k1)\n" +
-                        "(\n" +
-                        "    PARTITION p1 values less than('2020-02-01'),\n" +
-                        "    PARTITION p2 values less than('2020-03-01')\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "PROPERTIES('replication_num' = '1');");
+                    .withTable("CREATE TABLE test.base\n" +
+                                "(\n" +
+                                "    k1 date,\n" +
+                                "    k2 int,\n" +
+                                "    v1 int sum\n" +
+                                ")\n" +
+                                "PARTITION BY RANGE(k1)\n" +
+                                "(\n" +
+                                "    PARTITION p1 values less than('2020-02-01'),\n" +
+                                "    PARTITION p2 values less than('2020-03-01')\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                                "PROPERTIES('replication_num' = '1');");
         String sql = "create materialized view mv1 " +
-                "partition by k1 " +
-                "distributed by hash(k2) " +
-                "refresh async START('2122-12-31') EVERY(INTERVAL 1 HOUR) " +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"partition_ttl_number\" = \"0\"\n" +
-                ") " +
-                "as select k1, k2 from test.base;";
+                    "partition by k1 " +
+                    "distributed by hash(k2) " +
+                    "refresh async START('2122-12-31') EVERY(INTERVAL 1 HOUR) " +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"partition_ttl_number\" = \"0\"\n" +
+                    ") " +
+                    "as select k1, k2 from test.base;";
         CreateMaterializedViewStatement createMaterializedViewStatement =
-                (CreateMaterializedViewStatement) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
+                    (CreateMaterializedViewStatement) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         try {
             GlobalStateMgr.getCurrentState().getLocalMetastore().createMaterializedView(createMaterializedViewStatement);
             Assert.fail();
@@ -132,33 +131,34 @@ public void testAutoPartitionPartitionLiveNumber() throws Exception {
         new MockUp<LocalDateTime>() {
             @Mock
             public LocalDateTime now() {
-                return  LocalDateTime.of(2023, 3, 30, 1, 1, 1);
+                return LocalDateTime.of(2023, 3, 30, 1, 1, 1);
             }
         };
 
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE site_access(\n" +
-                        "    event_day datetime,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY date_trunc('day', event_day)(\n" +
-                        " START (\"2023-03-27\") END (\"2023-03-31\") EVERY (INTERVAL 1 day),\n" +
-                        " START (\"9999-12-30\") END (\"9999-12-31\") EVERY (INTERVAL 1 day)\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
-                        "PROPERTIES(\n" +
-                        "    \"partition_live_number\" = \"3\",\n" +
-                        "    \"replication_num\" = \"1\"\n" +
-                        ");");
+                    .withTable("CREATE TABLE site_access(\n" +
+                                "    event_day datetime,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY date_trunc('day', event_day)(\n" +
+                                " START (\"2023-03-27\") END (\"2023-03-31\") EVERY (INTERVAL 1 day),\n" +
+                                " START (\"9999-12-30\") END (\"9999-12-31\") EVERY (INTERVAL 1 day)\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
+                                "PROPERTIES(\n" +
+                                "    \"partition_live_number\" = \"3\",\n" +
+                                "    \"replication_num\" = \"1\"\n" +
+                                ");");
 
         DynamicPartitionScheduler dynamicPartitionScheduler = GlobalStateMgr.getCurrentState()
-                .getDynamicPartitionScheduler();
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("site_access");
+                    .getDynamicPartitionScheduler();
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access");
         dynamicPartitionScheduler.registerTtlPartitionTable(db.getId(), tbl.getId());
         dynamicPartitionScheduler.runOnceForTest();
 
@@ -176,33 +176,34 @@ public void testAutoRandomPartitionFPartitionLiveNumber() throws Exception {
         new MockUp<LocalDateTime>() {
             @Mock
             public LocalDateTime now() {
-                return  LocalDateTime.of(2023, 3, 30, 1, 1, 1);
+                return LocalDateTime.of(2023, 3, 30, 1, 1, 1);
             }
         };
 
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE site_access(\n" +
-                        "    event_day datetime,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY date_trunc('day', event_day)(\n" +
-                        " START (\"2023-03-27\") END (\"2023-03-31\") EVERY (INTERVAL 1 day),\n" +
-                        " START (\"9999-12-30\") END (\"9999-12-31\") EVERY (INTERVAL 1 day)\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY RANDOM BUCKETS 32\n" +
-                        "PROPERTIES(\n" +
-                        "    \"partition_live_number\" = \"3\",\n" +
-                        "    \"replication_num\" = \"1\"\n" +
-                        ");");
+                    .withTable("CREATE TABLE site_access(\n" +
+                                "    event_day datetime,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY date_trunc('day', event_day)(\n" +
+                                " START (\"2023-03-27\") END (\"2023-03-31\") EVERY (INTERVAL 1 day),\n" +
+                                " START (\"9999-12-30\") END (\"9999-12-31\") EVERY (INTERVAL 1 day)\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY RANDOM BUCKETS 32\n" +
+                                "PROPERTIES(\n" +
+                                "    \"partition_live_number\" = \"3\",\n" +
+                                "    \"replication_num\" = \"1\"\n" +
+                                ");");
 
         DynamicPartitionScheduler dynamicPartitionScheduler = GlobalStateMgr.getCurrentState()
-                .getDynamicPartitionScheduler();
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("site_access");
+                    .getDynamicPartitionScheduler();
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access");
         dynamicPartitionScheduler.registerTtlPartitionTable(db.getId(), tbl.getId());
         dynamicPartitionScheduler.runOnceForTest();
 
@@ -220,34 +221,35 @@ public void testRandomDynamicPartitionShouldMatchConfig() throws Exception {
         new MockUp<LocalDateTime>() {
             @Mock
             public LocalDateTime now() {
-                return  LocalDateTime.of(2023, 3, 30, 1, 1, 1);
+                return LocalDateTime.of(2023, 3, 30, 1, 1, 1);
             }
         };
 
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test_random_bucket (\n" +
-                        "    uid String,\n" +
-                        "    tdbank_imp_date Date\n" +
-                        ") ENGINE=OLAP \n" +
-                        "DUPLICATE KEY(`uid`) \n" +
-                        "PARTITION BY RANGE(`tdbank_imp_date`) ()\n" +
-                        "DISTRIBUTED BY RANDOM BUCKETS 1\n" +
-                        "PROPERTIES (\n" +
-                        "     \"replication_num\" = \"1\", \n" +
-                        "     \"dynamic_partition.enable\" = \"true\", \n" +
-                        "     \"dynamic_partition.time_unit\" = \"DAY\", \n" +
-                        "     \"dynamic_partition.time_zone\" = \"Asia/Shanghai\", \n" +
-                        "     \"dynamic_partition.start\" = \"-180\", \n" +
-                        "     \"dynamic_partition.end\" = \"3\", \n" +
-                        "     \"dynamic_partition.prefix\" = \"p\", \n" +
-                        "     \"dynamic_partition.buckets\" = \"4\", \n" +
-                        "     \"dynamic_partition.history_partition_num\" = \"0\",\n" +
-                        "     \"compression\" = \"LZ4\" );");
+                    .withTable("CREATE TABLE test_random_bucket (\n" +
+                                "    uid String,\n" +
+                                "    tdbank_imp_date Date\n" +
+                                ") ENGINE=OLAP \n" +
+                                "DUPLICATE KEY(`uid`) \n" +
+                                "PARTITION BY RANGE(`tdbank_imp_date`) ()\n" +
+                                "DISTRIBUTED BY RANDOM BUCKETS 1\n" +
+                                "PROPERTIES (\n" +
+                                "     \"replication_num\" = \"1\", \n" +
+                                "     \"dynamic_partition.enable\" = \"true\", \n" +
+                                "     \"dynamic_partition.time_unit\" = \"DAY\", \n" +
+                                "     \"dynamic_partition.time_zone\" = \"Asia/Shanghai\", \n" +
+                                "     \"dynamic_partition.start\" = \"-180\", \n" +
+                                "     \"dynamic_partition.end\" = \"3\", \n" +
+                                "     \"dynamic_partition.prefix\" = \"p\", \n" +
+                                "     \"dynamic_partition.buckets\" = \"4\", \n" +
+                                "     \"dynamic_partition.history_partition_num\" = \"0\",\n" +
+                                "     \"compression\" = \"LZ4\" );");
 
         DynamicPartitionScheduler dynamicPartitionScheduler = GlobalStateMgr.getCurrentState()
-                .getDynamicPartitionScheduler();
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("test_random_bucket");
+                    .getDynamicPartitionScheduler();
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "test_random_bucket");
         dynamicPartitionScheduler.registerTtlPartitionTable(db.getId(), tbl.getId());
         dynamicPartitionScheduler.runOnceForTest();
 
@@ -263,42 +265,43 @@ public void testPartitionColumnDateUseDynamicHour() throws Exception {
         new MockUp<LocalDateTime>() {
             @Mock
             public LocalDateTime now() {
-                return  LocalDateTime.of(2023, 3, 30, 1, 1, 1);
+                return LocalDateTime.of(2023, 3, 30, 1, 1, 1);
             }
         };
 
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE `test_hour_partition2` (\n" +
-                        "  `event_day` date NULL COMMENT \"\",\n" +
-                        "  `site_id` int(11) NULL DEFAULT \"10\" COMMENT \"\",\n" +
-                        "  `city_code` varchar(100) NULL COMMENT \"\",\n" +
-                        "  `user_name` varchar(32) NULL DEFAULT \"\" COMMENT \"\",\n" +
-                        "  `pv` bigint(20) NULL DEFAULT \"0\" COMMENT \"\"\n" +
-                        ") ENGINE=OLAP \n" +
-                        "DUPLICATE KEY(`event_day`, `site_id`, `city_code`, `user_name`)\n" +
-                        "PARTITION BY RANGE(`event_day`)\n" +
-                        "()\n" +
-                        "DISTRIBUTED BY HASH(`event_day`, `site_id`) BUCKETS 32 \n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\",\n" +
-                        "\"dynamic_partition.enable\" = \"true\",\n" +
-                        "\"dynamic_partition.time_unit\" = \"DAY\",\n" +
-                        "\"dynamic_partition.time_zone\" = \"Asia/Shanghai\",\n" +
-                        "\"dynamic_partition.start\" = \"-1\",\n" +
-                        "\"dynamic_partition.end\" = \"10\",\n" +
-                        "\"dynamic_partition.prefix\" = \"p\",\n" +
-                        "\"dynamic_partition.buckets\" = \"3\",\n" +
-                        "\"dynamic_partition.history_partition_num\" = \"0\",\n" +
-                        "\"in_memory\" = \"false\",\n" +
-                        "\"storage_format\" = \"DEFAULT\",\n" +
-                        "\"enable_persistent_index\" = \"false\",\n" +
-                        "\"compression\" = \"LZ4\"\n" +
-                        ");");
+                    .withTable("CREATE TABLE `test_hour_partition2` (\n" +
+                                "  `event_day` date NULL COMMENT \"\",\n" +
+                                "  `site_id` int(11) NULL DEFAULT \"10\" COMMENT \"\",\n" +
+                                "  `city_code` varchar(100) NULL COMMENT \"\",\n" +
+                                "  `user_name` varchar(32) NULL DEFAULT \"\" COMMENT \"\",\n" +
+                                "  `pv` bigint(20) NULL DEFAULT \"0\" COMMENT \"\"\n" +
+                                ") ENGINE=OLAP \n" +
+                                "DUPLICATE KEY(`event_day`, `site_id`, `city_code`, `user_name`)\n" +
+                                "PARTITION BY RANGE(`event_day`)\n" +
+                                "()\n" +
+                                "DISTRIBUTED BY HASH(`event_day`, `site_id`) BUCKETS 32 \n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\",\n" +
+                                "\"dynamic_partition.enable\" = \"true\",\n" +
+                                "\"dynamic_partition.time_unit\" = \"DAY\",\n" +
+                                "\"dynamic_partition.time_zone\" = \"Asia/Shanghai\",\n" +
+                                "\"dynamic_partition.start\" = \"-1\",\n" +
+                                "\"dynamic_partition.end\" = \"10\",\n" +
+                                "\"dynamic_partition.prefix\" = \"p\",\n" +
+                                "\"dynamic_partition.buckets\" = \"3\",\n" +
+                                "\"dynamic_partition.history_partition_num\" = \"0\",\n" +
+                                "\"in_memory\" = \"false\",\n" +
+                                "\"storage_format\" = \"DEFAULT\",\n" +
+                                "\"enable_persistent_index\" = \"false\",\n" +
+                                "\"compression\" = \"LZ4\"\n" +
+                                ");");
 
         DynamicPartitionScheduler dynamicPartitionScheduler = GlobalStateMgr.getCurrentState()
-                .getDynamicPartitionScheduler();
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("test_hour_partition2");
+                    .getDynamicPartitionScheduler();
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "test_hour_partition2");
         DynamicPartitionProperty dynamicPartitionProperty = tbl.getTableProperty().getDynamicPartitionProperty();
         dynamicPartitionProperty.setTimeUnit("HOUR");
         boolean result = dynamicPartitionScheduler.executeDynamicPartitionForTable(db.getId(), tbl.getId());
diff --git a/fe/fe-core/src/test/java/com/starrocks/clone/TabletSchedCtxTest.java b/fe/fe-core/src/test/java/com/starrocks/clone/TabletSchedCtxTest.java
index f61390bbfbdaf6..1b1e35c8e16b1d 100644
--- a/fe/fe-core/src/test/java/com/starrocks/clone/TabletSchedCtxTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/clone/TabletSchedCtxTest.java
@@ -128,7 +128,7 @@ public void setUp() {
         olapTable.setIndexMeta(INDEX_ID, TB_NAME, TB_BASE_SCHEMA, 0, SCHEMA_HASH, (short) 1, TStorageType.COLUMN,
                 KeysType.AGG_KEYS);
         olapTable.addPartition(partition);
-        Database db = new Database();
+        Database db = new Database(DB_ID, "");
         db.registerTableUnlocked(olapTable);
         GlobalStateMgr.getCurrentState().getLocalMetastore().getIdToDb().put(DB_ID, db);
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/cluster/SystemInfoServiceTest.java b/fe/fe-core/src/test/java/com/starrocks/cluster/SystemInfoServiceTest.java
index 6469c7d54589f3..22168d1ad5ae0d 100644
--- a/fe/fe-core/src/test/java/com/starrocks/cluster/SystemInfoServiceTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/cluster/SystemInfoServiceTest.java
@@ -112,7 +112,7 @@ public void setUp() throws IOException {
                 minTimes = 0;
                 result = editLog;
 
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = db;
 
@@ -140,6 +140,14 @@ public void setUp() throws IOException {
             }
         };
 
+        new Expectations(localMetastore) {
+            {
+                localMetastore.getDb(anyLong);
+                minTimes = 0;
+                result = db;
+            }
+        };
+
         new Expectations(nodeMgr) {
             {
                 systemInfoService = new SystemInfoService();
diff --git a/fe/fe-core/src/test/java/com/starrocks/common/Log4jConfigTest.java b/fe/fe-core/src/test/java/com/starrocks/common/Log4jConfigTest.java
index d63747d892d2bd..d3891d6892e984 100644
--- a/fe/fe-core/src/test/java/com/starrocks/common/Log4jConfigTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/common/Log4jConfigTest.java
@@ -14,20 +14,34 @@
 
 package com.starrocks.common;
 
+import com.google.gson.JsonObject;
+import com.google.gson.internal.Streams;
+import com.google.gson.stream.JsonReader;
+import org.apache.logging.log4j.LogManager;
+import org.apache.logging.log4j.Logger;
 import org.junit.After;
 import org.junit.Assert;
 import org.junit.Before;
 import org.junit.Test;
 
+import java.io.ByteArrayInputStream;
+import java.io.ByteArrayOutputStream;
 import java.io.IOException;
+import java.io.InputStreamReader;
+import java.io.PrintStream;
+import java.io.Reader;
+import java.nio.charset.Charset;
 import java.util.regex.Matcher;
 import java.util.regex.Pattern;
 
 public class Log4jConfigTest {
+    private static final Logger LOG = LogManager.getLogger(Log4jConfigTest.class);
+
     private String logFormat;
 
     @Before
     public void setUp() throws IOException {
+        FeConstants.runningUnitTest = true;
         logFormat = Config.sys_log_format;
         Log4jConfig.initLogging();
     }
@@ -35,6 +49,7 @@ public void setUp() throws IOException {
     @After
     public void tearDown() {
         Config.sys_log_format = logFormat;
+        FeConstants.runningUnitTest = false;
     }
 
     @Test
@@ -69,4 +84,41 @@ public void testJsonLoggingFormatConfig() throws IOException {
             }
         }
     }
+
+    @Test
+    public void testJsonLogOutputFormat() throws IOException {
+        // enable logging with json format to console
+        // with `sys_log_to_console = true`, the log will be written to System.err
+        Config.sys_log_format = "json";
+        Config.sys_log_to_console = true;
+        Config.sys_log_level = "INFO";
+        Log4jConfig.initLogging();
+
+        String logMessage = "Test log message from unit test";
+        // Hook System.err
+        PrintStream oldErr = System.err;
+        ByteArrayOutputStream byteOs = new ByteArrayOutputStream();
+        System.setErr(new PrintStream(byteOs, true));
+        // log a message
+        LOG.warn(logMessage);
+        // reset System.out
+        System.setErr(oldErr);
+        // reset logging
+        Config.sys_log_format = "plaintext";
+        Config.sys_log_to_console = false;
+        Log4jConfig.initLogging();
+
+        // validate log message
+        String logMsg = byteOs.toString(Charset.defaultCharset()).trim();
+        System.out.println("logMsg: " + logMsg);
+
+        Reader reader = new InputStreamReader(new ByteArrayInputStream(byteOs.toByteArray()));
+        JsonObject jsonObject = Streams.parse(new JsonReader(reader)).getAsJsonObject();
+
+        Assert.assertEquals("testJsonLogOutputFormat", jsonObject.get("method").getAsString());
+        Assert.assertEquals("Log4jConfigTest.java", jsonObject.get("file").getAsString());
+        Assert.assertEquals("WARN", jsonObject.get("level").getAsString());
+        Assert.assertEquals("main", jsonObject.get("thread.name").getAsString());
+        Assert.assertEquals(logMessage, jsonObject.get("message").getAsString());
+    }
 }
diff --git a/fe/fe-core/src/test/java/com/starrocks/common/proc/DbsProcDirTest.java b/fe/fe-core/src/test/java/com/starrocks/common/proc/DbsProcDirTest.java
index 81abd72804060c..925b535b3ca7d0 100644
--- a/fe/fe-core/src/test/java/com/starrocks/common/proc/DbsProcDirTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/common/proc/DbsProcDirTest.java
@@ -83,27 +83,27 @@ public void testRegister() {
     public void testLookupNormal() throws AnalysisException {
         new Expectations(globalStateMgr) {
             {
-                globalStateMgr.getDb("db1");
+                globalStateMgr.getLocalMetastore().getDb("db1");
                 minTimes = 0;
                 result = db1;
 
-                globalStateMgr.getDb("db2");
+                globalStateMgr.getLocalMetastore().getDb("db2");
                 minTimes = 0;
                 result = db2;
 
-                globalStateMgr.getDb("db3");
+                globalStateMgr.getLocalMetastore().getDb("db3");
                 minTimes = 0;
                 result = null;
 
-                globalStateMgr.getDb(db1.getId());
+                globalStateMgr.getLocalMetastore().getDb(db1.getId());
                 minTimes = 0;
                 result = db1;
 
-                globalStateMgr.getDb(db2.getId());
+                globalStateMgr.getLocalMetastore().getDb(db2.getId());
                 minTimes = 0;
                 result = db2;
 
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = null;
             }
@@ -164,27 +164,27 @@ public void testFetchResultNormal() throws AnalysisException {
                 minTimes = 0;
                 result = Lists.newArrayList("db1", "db2");
 
-                globalStateMgr.getDb("db1");
+                globalStateMgr.getLocalMetastore().getDb("db1");
                 minTimes = 0;
                 result = db1;
 
-                globalStateMgr.getDb("db2");
+                globalStateMgr.getLocalMetastore().getDb("db2");
                 minTimes = 0;
                 result = db2;
 
-                globalStateMgr.getDb("db3");
+                globalStateMgr.getLocalMetastore().getDb("db3");
                 minTimes = 0;
                 result = null;
 
-                globalStateMgr.getDb(db1.getId());
+                globalStateMgr.getLocalMetastore().getDb(db1.getId());
                 minTimes = 0;
                 result = db1;
 
-                globalStateMgr.getDb(db2.getId());
+                globalStateMgr.getLocalMetastore().getDb(db2.getId());
                 minTimes = 0;
                 result = db2;
 
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = null;
             }
diff --git a/fe/fe-core/src/test/java/com/starrocks/common/proc/TablesProcDirTest.java b/fe/fe-core/src/test/java/com/starrocks/common/proc/TablesProcDirTest.java
index f82d43b70e90d7..6631919250343a 100644
--- a/fe/fe-core/src/test/java/com/starrocks/common/proc/TablesProcDirTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/common/proc/TablesProcDirTest.java
@@ -26,11 +26,15 @@
 import com.starrocks.catalog.PartitionInfo;
 import com.starrocks.catalog.PartitionType;
 import com.starrocks.catalog.RangePartitionInfo;
+import com.starrocks.catalog.Table;
 import com.starrocks.catalog.Type;
 import com.starrocks.common.AnalysisException;
 import com.starrocks.common.DdlException;
 import com.starrocks.common.FeConstants;
+import com.starrocks.server.LocalMetastore;
 import mockit.Expectations;
+import mockit.Mock;
+import mockit.MockUp;
 import org.junit.Assert;
 import org.junit.Before;
 import org.junit.Test;
@@ -105,6 +109,28 @@ public void setUp() throws DdlException, AnalysisException {
         db.registerTableUnlocked(tb1);
         db.registerTableUnlocked(tb2);
         db.registerTableUnlocked(tb3);
+
+        new MockUp<LocalMetastore>() {
+            @Mock
+            public Database getDb(String dbName) {
+                return db;
+            }
+
+            @Mock
+            public Table getTable(String dbName, String tblName) {
+                return db.getTable(tblName);
+            }
+
+            @Mock
+            public Table getTable(Long dbId, Long tableId) {
+                return db.getTable(tableId);
+            }
+
+            @Mock
+            public List<Table> getTables(Long dbId) {
+                return db.getTables();
+            }
+        };
     }
 
     @Test
diff --git a/fe/fe-core/src/test/java/com/starrocks/common/util/SmallFileMgrTest.java b/fe/fe-core/src/test/java/com/starrocks/common/util/SmallFileMgrTest.java
index 7acc45626cdd05..dec03e731d355b 100644
--- a/fe/fe-core/src/test/java/com/starrocks/common/util/SmallFileMgrTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/common/util/SmallFileMgrTest.java
@@ -81,7 +81,7 @@ public void test(@Injectable CreateFileStmt stmt1, @Injectable CreateFileStmt st
                 db.getId();
                 minTimes = 0;
                 result = 1L;
-                globalStateMgr.getDb(anyString);
+                globalStateMgr.getLocalMetastore().getDb(anyString);
                 minTimes = 0;
                 result = db;
                 stmt1.getDbName();
diff --git a/fe/fe-core/src/test/java/com/starrocks/connector/elasticsearch/EsShardPartitionsTest.java b/fe/fe-core/src/test/java/com/starrocks/connector/elasticsearch/EsShardPartitionsTest.java
index 3f746ba8245d6b..f4575562c9b642 100644
--- a/fe/fe-core/src/test/java/com/starrocks/connector/elasticsearch/EsShardPartitionsTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/connector/elasticsearch/EsShardPartitionsTest.java
@@ -47,8 +47,8 @@ public class EsShardPartitionsTest extends EsTestCase {
     @Test
     public void testPartition() throws Exception {
         EsTable esTable = (EsTable) GlobalStateMgr.getCurrentState()
-                .getDb(GlobalStateMgrTestUtil.testDb1)
-                .getTable(GlobalStateMgrTestUtil.testEsTableId1);
+                .getLocalMetastore()
+                .getTable(GlobalStateMgrTestUtil.testDb1, GlobalStateMgrTestUtil.testEsTable1);
         EsShardPartitions esShardPartitions = EsShardPartitions.findShardPartitions("doe",
                 loadJsonFromFile("data/es/test_search_shards.json"));
         EsTablePartitions esTablePartitions = EsTablePartitions.fromShardPartitions(esTable, esShardPartitions);
diff --git a/fe/fe-core/src/test/java/com/starrocks/consistency/ConsistencyCheckerTest.java b/fe/fe-core/src/test/java/com/starrocks/consistency/ConsistencyCheckerTest.java
index b16da048e53ce3..b7de28181515ca 100644
--- a/fe/fe-core/src/test/java/com/starrocks/consistency/ConsistencyCheckerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/consistency/ConsistencyCheckerTest.java
@@ -77,9 +77,13 @@ public void testChooseTablets(@Mocked GlobalStateMgr globalStateMgr) {
                 result = Lists.newArrayList(dbId);
                 minTimes = 0;
 
-                globalStateMgr.getDb(dbId);
+                globalStateMgr.getLocalMetastore().getDb(dbId);
                 result = database;
                 minTimes = 0;
+
+                globalStateMgr.getLocalMetastore().getTables(dbId);
+                result = database.getTables();
+                minTimes = 0;
             }
         };
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/consistency/MetaRecoveryDaemonTest.java b/fe/fe-core/src/test/java/com/starrocks/consistency/MetaRecoveryDaemonTest.java
index f830c7306897d9..fa07ad4e1430b1 100644
--- a/fe/fe-core/src/test/java/com/starrocks/consistency/MetaRecoveryDaemonTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/consistency/MetaRecoveryDaemonTest.java
@@ -53,16 +53,16 @@ public static void tearDown() throws Exception {
     public void testRecover() throws Exception {
         PseudoCluster cluster = PseudoCluster.getInstance();
         String sql = "CREATE TABLE test.`tbl_recover` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 8\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"3\",\n" +
-                "    \"in_memory\" = \"false\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 8\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"3\",\n" +
+                    "    \"in_memory\" = \"false\"\n" +
+                    ");";
         cluster.runSql("test", sql);
         cluster.runSql("test", "insert into test.tbl_recover values (1, 'a'), (2, 'b')");
 
@@ -70,7 +70,8 @@ public void testRecover() throws Exception {
         Thread.sleep(2000L);
 
         Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
-        OlapTable table = (OlapTable) database.getTable("tbl_recover");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(database.getFullName(), "tbl_recover");
         Partition partition = table.getPartition("tbl_recover");
         MaterializedIndex index = partition.getMaterializedIndices(MaterializedIndex.IndexExtState.ALL).get(0);
         for (Tablet tablet : index.getTablets()) {
@@ -88,19 +89,19 @@ public void testRecover() throws Exception {
 
         for (Backend backend : GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo().getBackends()) {
             backend.getBackendStatus().lastSuccessReportTabletsTime = TimeUtils
-                    .longToTimeString(System.currentTimeMillis());
+                        .longToTimeString(System.currentTimeMillis());
         }
 
         // add a committed txn
         TransactionState transactionState = new TransactionState(database.getId(), Lists.newArrayList(table.getId()),
-                11111, "xxxx", null, TransactionState.LoadJobSourceType.FRONTEND, null, 2222, 100000);
+                    11111, "xxxx", null, TransactionState.LoadJobSourceType.FRONTEND, null, 2222, 100000);
         TableCommitInfo tableCommitInfo = new TableCommitInfo(table.getId());
         PartitionCommitInfo partitionCommitInfo = new PartitionCommitInfo(partition.getId(), 4, -1L);
         tableCommitInfo.addPartitionCommitInfo(partitionCommitInfo);
         transactionState.putIdToTableCommitInfo(table.getId(), tableCommitInfo);
         transactionState.setTransactionStatus(TransactionStatus.COMMITTED);
         GlobalStateMgr.getCurrentState().getGlobalTransactionMgr()
-                .getDatabaseTransactionMgr(database.getId()).replayUpsertTransactionState(transactionState);
+                    .getDatabaseTransactionMgr(database.getId()).replayUpsertTransactionState(transactionState);
 
         // recover will fail, because there is a committed txn on that partition
         MetaRecoveryDaemon recovery = new MetaRecoveryDaemon();
@@ -121,13 +122,13 @@ public void testRecover() throws Exception {
 
         // change replica version
         LocalTablet localTablet = (LocalTablet) partition.getMaterializedIndices(MaterializedIndex.IndexExtState.ALL)
-                .get(0).getTablets().get(0);
+                    .get(0).getTablets().get(0);
         long version = 3;
         for (Replica replica : localTablet.getAllReplicas()) {
             replica.updateForRestore(++version, 10, 10);
         }
         LocalTablet localTablet2 = (LocalTablet) partition.getMaterializedIndices(MaterializedIndex.IndexExtState.ALL)
-                .get(0).getTablets().get(0);
+                    .get(0).getTablets().get(0);
         for (Replica replica : localTablet2.getAllReplicas()) {
             replica.updateForRestore(4, 10, 10);
         }
@@ -172,7 +173,7 @@ public void testCheckTabletReportCacheUp() {
         MetaRecoveryDaemon metaRecoveryDaemon = new MetaRecoveryDaemon();
         for (Backend backend : GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo().getBackends()) {
             backend.getBackendStatus().lastSuccessReportTabletsTime = TimeUtils
-                    .longToTimeString(timeMs);
+                        .longToTimeString(timeMs);
         }
         Assert.assertFalse(metaRecoveryDaemon.checkTabletReportCacheUp(timeMs + 1000L));
         Assert.assertTrue(metaRecoveryDaemon.checkTabletReportCacheUp(timeMs - 1000L));
diff --git a/fe/fe-core/src/test/java/com/starrocks/external/starrocks/TableMetaSyncerTest.java b/fe/fe-core/src/test/java/com/starrocks/external/starrocks/TableMetaSyncerTest.java
index 6a68a5b792f33e..593d35a1c8a6a9 100644
--- a/fe/fe-core/src/test/java/com/starrocks/external/starrocks/TableMetaSyncerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/external/starrocks/TableMetaSyncerTest.java
@@ -127,7 +127,7 @@ public void syncTableMeta() throws Exception {
         LeaderImpl leader = new LeaderImpl();
         TGetTableMetaResponse response = leader.getTableMeta(request);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test_db").getTable("test_ext_table");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test_db").getTable("test_ext_table");
         ExternalOlapTable extTable = (ExternalOlapTable) table;
         // remove the thread local meta context
         MetaContext.remove();
diff --git a/fe/fe-core/src/test/java/com/starrocks/http/ShowDataActionTest.java b/fe/fe-core/src/test/java/com/starrocks/http/ShowDataActionTest.java
index 78fb347734f9fc..3e01b1ce332c61 100644
--- a/fe/fe-core/src/test/java/com/starrocks/http/ShowDataActionTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/http/ShowDataActionTest.java
@@ -45,10 +45,14 @@ public void doSetUp() {
         ConcurrentHashMap<String, Database> fullNameToDb = GlobalStateMgr.getCurrentState()
                 .getLocalMetastore().getFullNameToDb();
         fullNameToDb.put(SHOW_DATA_DB_NAME, db);
+
+        ConcurrentHashMap<Long, Database> idToDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getIdToDb();
+        idToDb.put(1000 + testDbId, db);
     }
 
     @Test
     public void testGetShowData() throws IOException {
+
         Config.http_slow_request_threshold_ms = 0;
         Request request = new Request.Builder()
                 .get()
diff --git a/fe/fe-core/src/test/java/com/starrocks/http/StarRocksHttpTestCase.java b/fe/fe-core/src/test/java/com/starrocks/http/StarRocksHttpTestCase.java
index cdff97ea22e2b4..1bcc2c1ffe10e6 100644
--- a/fe/fe-core/src/test/java/com/starrocks/http/StarRocksHttpTestCase.java
+++ b/fe/fe-core/src/test/java/com/starrocks/http/StarRocksHttpTestCase.java
@@ -284,23 +284,15 @@ private static GlobalStateMgr newDelegateCatalog() {
 
         new Expectations(globalStateMgr) {
             {
-                globalStateMgr.getDb(db.getId());
-                minTimes = 0;
-                result = db;
-
-                globalStateMgr.getDb(DB_NAME);
-                minTimes = 0;
-                result = db;
-
                 globalStateMgr.isLeader();
                 minTimes = 0;
                 result = true;
 
-                globalStateMgr.getDb("emptyDb");
+                globalStateMgr.getLocalMetastore().getDb("emptyDb");
                 minTimes = 0;
                 result = null;
 
-                globalStateMgr.getDb(anyString);
+                globalStateMgr.getLocalMetastore().getDb(anyString);
                 minTimes = 0;
                 result = new Database();
 
@@ -320,13 +312,13 @@ private static GlobalStateMgr newDelegateCatalog() {
 
         new Expectations(localMetastore) {
             {
-                localMetastore.listDbNames();
+                localMetastore.getDb("testDb");
                 minTimes = 0;
-                result = Lists.newArrayList("testDb");
+                result = db;
 
-                localMetastore.getFullNameToDb();
+                localMetastore.getDb(testDbId);
                 minTimes = 0;
-                result = nameToDb;
+                result = db;
             }
         };
 
@@ -352,26 +344,10 @@ private static GlobalStateMgr newDelegateGlobalStateMgr() {
 
         new Expectations(globalStateMgr) {
             {
-                globalStateMgr.getDb(db.getId());
-                minTimes = 0;
-                result = db;
-
-                globalStateMgr.getDb(DB_NAME);
-                minTimes = 0;
-                result = db;
-
                 globalStateMgr.isLeader();
                 minTimes = 0;
                 result = true;
 
-                globalStateMgr.getDb("emptyDb");
-                minTimes = 0;
-                result = null;
-
-                globalStateMgr.getDb(anyString);
-                minTimes = 0;
-                result = new Database();
-
                 globalStateMgr.getLoadInstance();
                 minTimes = 0;
                 result = new Load();
@@ -383,6 +359,10 @@ private static GlobalStateMgr newDelegateGlobalStateMgr() {
                 globalStateMgr.getMetadataMgr();
                 minTimes = 0;
                 result = metadataMgr;
+
+                globalStateMgr.getLocalMetastore();
+                minTimes = 0;
+                result = localMetastore;
             }
         };
 
@@ -401,7 +381,18 @@ private static GlobalStateMgr newDelegateGlobalStateMgr() {
                 result = newEmptyTable;
             }
         };
-        ;
+
+        new Expectations(localMetastore) {
+            {
+                localMetastore.getDb("testDb");
+                minTimes = 0;
+                result = db;
+
+                localMetastore.getDb(testDbId);
+                minTimes = 0;
+                result = db;
+            }
+        };
 
         return globalStateMgr;
     }
diff --git a/fe/fe-core/src/test/java/com/starrocks/http/rest/v2/TablePartitionActionTest.java b/fe/fe-core/src/test/java/com/starrocks/http/rest/v2/TablePartitionActionTest.java
index b56a6acf3ff341..bace9e50e5ff42 100644
--- a/fe/fe-core/src/test/java/com/starrocks/http/rest/v2/TablePartitionActionTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/http/rest/v2/TablePartitionActionTest.java
@@ -106,7 +106,7 @@ public void testNonOlapTable() throws Exception {
 
     @Test
     public void testOlapTable() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb(testDbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(testDbId);
         db.registerTableUnlocked(newOlapTable(
                 TB_OLAP_TABLE_ID, TB_OLAP_TABLE_NAME, PARTITION_SIZE));
 
@@ -153,7 +153,7 @@ public void testOlapTable() throws Exception {
 
     @Test
     public void testLakeTable() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb(testDbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(testDbId);
         db.registerTableUnlocked(newLakeTable(
                 TB_LAKE_TABLE_ID, TB_LAKE_TABLE_NAME, PARTITION_SIZE));
 
@@ -200,7 +200,7 @@ public void testLakeTable() throws Exception {
 
     @Test
     public void testPages() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb(testDbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(testDbId);
         db.registerTableUnlocked(newOlapTable(
                 TB_OLAP_TABLE_ID, TB_OLAP_TABLE_NAME, PARTITION_SIZE));
 
@@ -314,8 +314,8 @@ public void testPages() throws Exception {
     private static OlapTable newOlapTable(Long tableId, String tableName, int partitionSize) throws Exception {
         GlobalStateMgr.getCurrentState().getTabletInvertedIndex().clear();
 
-        Column c1 = new Column("c1", Type.DOUBLE, true, null, false, null, "cc1", 1);
-        Column c2 = new Column("c2", Type.DEFAULT_DECIMAL64, false, AggregateType.SUM, true,
+        Column c1 = new Column("c1", Type.DOUBLE, true, null, null, false, null, "cc1", 1);
+        Column c2 = new Column("c2", Type.DEFAULT_DECIMAL64, false, AggregateType.SUM, null, true,
                 new ColumnDef.DefaultValueDef(true, new StringLiteral("0")), "cc2", 2);
         List<Column> columns = Lists.newArrayList(c1, c2);
 
@@ -388,8 +388,8 @@ private static OlapTable newOlapTable(Long tableId, String tableName, int partit
     private static LakeTable newLakeTable(Long tableId, String tableName, int partitionSize) throws Exception {
         GlobalStateMgr.getCurrentState().getTabletInvertedIndex().clear();
 
-        Column c1 = new Column("c1", Type.DOUBLE, true, null, false, null, "cc1", 1);
-        Column c2 = new Column("c2", Type.DEFAULT_DECIMAL64, false, AggregateType.SUM, true,
+        Column c1 = new Column("c1", Type.DOUBLE, true, null, null, false, null, "cc1", 1);
+        Column c2 = new Column("c2", Type.DEFAULT_DECIMAL64, false, AggregateType.SUM, null, true,
                 new ColumnDef.DefaultValueDef(true, new StringLiteral("0")), "cc2", 2);
         List<Column> columns = Lists.newArrayList(c1, c2);
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/http/rest/v2/TableSchemaActionTest.java b/fe/fe-core/src/test/java/com/starrocks/http/rest/v2/TableSchemaActionTest.java
index dce8bdaf5c22c1..e26de38babf8fc 100644
--- a/fe/fe-core/src/test/java/com/starrocks/http/rest/v2/TableSchemaActionTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/http/rest/v2/TableSchemaActionTest.java
@@ -75,7 +75,7 @@ public class TableSchemaActionTest extends StarRocksHttpTestCase {
 
     @Override
     protected void doSetUp() {
-        Database db = GlobalStateMgr.getCurrentState().getDb(testDbId);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(testDbId);
         db.registerTableUnlocked(newOlapTable(TB_GET_TABLE_SCHEMA_ID, TB_GET_TABLE_SCHEMA_NAME));
     }
 
@@ -207,8 +207,8 @@ public void testOlapTable() throws Exception {
     private static OlapTable newOlapTable(Long tableId, String tableName) {
         GlobalStateMgr.getCurrentState().getTabletInvertedIndex().clear();
 
-        Column c1 = new Column("c1", Type.DOUBLE, true, null, false, null, "cc1", 1);
-        Column c2 = new Column("c2", Type.DEFAULT_DECIMAL64, false, AggregateType.SUM, true,
+        Column c1 = new Column("c1", Type.DOUBLE, true, null, null, false, null, "cc1", 1);
+        Column c2 = new Column("c2", Type.DEFAULT_DECIMAL64, false, AggregateType.SUM, null, true,
                 new ColumnDef.DefaultValueDef(true, new StringLiteral("0")), "cc2", 2);
         List<Column> columns = Lists.newArrayList(c1, c2);
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/lake/AlterTest.java b/fe/fe-core/src/test/java/com/starrocks/lake/AlterTest.java
index 22901947417811..16ee0473f61c42 100644
--- a/fe/fe-core/src/test/java/com/starrocks/lake/AlterTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/lake/AlterTest.java
@@ -63,35 +63,35 @@ public void testAddPartitionForLakeTable() throws Exception {
         DropTableStmt dropTableStmt = (DropTableStmt) UtFrameUtils.parseStmtWithNewParser(dropSQL, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropTable(dropTableStmt);
         String createSQL = "CREATE TABLE test.test_lake_partition (\n" +
-                "      k1 DATE,\n" +
-                "      k2 INT,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "DUPLICATE KEY(k1, k2, k3)\n" +
-                "PARTITION BY RANGE (k1, k2, k3) (\n" +
-                "    PARTITION p1 VALUES [(\"2014-01-01\", \"10\", \"200\"), (\"2014-01-01\", \"20\", \"300\")),\n" +
-                "    PARTITION p2 VALUES [(\"2014-06-01\", \"100\", \"200\"), (\"2014-07-01\", \"100\", \"300\"))\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                "PROPERTIES (\n" +
-                "   \"datacache.enable\" = \"true\"\n" +
-                ")";
+                    "      k1 DATE,\n" +
+                    "      k2 INT,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(k1, k2, k3)\n" +
+                    "PARTITION BY RANGE (k1, k2, k3) (\n" +
+                    "    PARTITION p1 VALUES [(\"2014-01-01\", \"10\", \"200\"), (\"2014-01-01\", \"20\", \"300\")),\n" +
+                    "    PARTITION p2 VALUES [(\"2014-06-01\", \"100\", \"200\"), (\"2014-07-01\", \"100\", \"300\"))\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                    "PROPERTIES (\n" +
+                    "   \"datacache.enable\" = \"true\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String alterSQL = "ALTER TABLE test_lake_partition ADD\n" +
-                "    PARTITION p3 VALUES LESS THAN (\"2014-01-01\")";
+                    "    PARTITION p3 VALUES LESS THAN (\"2014-01-01\")";
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
         AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "test_lake_partition", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "test_lake_partition", addPartitionClause);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("test_lake_partition");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("test_lake_partition");
 
         Assert.assertNotNull(table.getPartition("p1"));
         Assert.assertNotNull(table.getPartition("p2"));
@@ -109,35 +109,35 @@ public void testMultiRangePartitionForLakeTable() throws Exception {
         DropTableStmt dropTableStmt = (DropTableStmt) UtFrameUtils.parseStmtWithNewParser(dropSQL, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropTable(dropTableStmt);
         String createSQL = "CREATE TABLE site_access (\n" +
-                "    datekey INT,\n" +
-                "    site_id INT,\n" +
-                "    city_code SMALLINT,\n" +
-                "    user_name VARCHAR(32),\n" +
-                "    pv BIGINT DEFAULT '0'\n" +
-                ")\n" +
-                "DUPLICATE KEY(datekey, site_id, city_code, user_name)\n" +
-                "PARTITION BY RANGE (datekey) (\n" +
-                "    START (\"1\") END (\"5\") EVERY (1)\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(site_id) BUCKETS 3\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"1\"\n" +
-                ")";
+                    "    datekey INT,\n" +
+                    "    site_id INT,\n" +
+                    "    city_code SMALLINT,\n" +
+                    "    user_name VARCHAR(32),\n" +
+                    "    pv BIGINT DEFAULT '0'\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(datekey, site_id, city_code, user_name)\n" +
+                    "PARTITION BY RANGE (datekey) (\n" +
+                    "    START (\"1\") END (\"5\") EVERY (1)\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(site_id) BUCKETS 3\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"1\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String alterSQL = "ALTER TABLE site_access \n" +
-                "   ADD PARTITIONS START (\"7\") END (\"9\") EVERY (1)";
+                    "   ADD PARTITIONS START (\"7\") END (\"9\") EVERY (1)";
 
         AlterTableStmt alterTableStmt = (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(alterSQL, ctx);
         AddPartitionClause addPartitionClause = (AddPartitionClause) alterTableStmt.getAlterClauseList().get(0);
         GlobalStateMgr.getCurrentState().getLocalMetastore()
-                .addPartitions(Util.getOrCreateConnectContext(), db, "site_access", addPartitionClause);
+                    .addPartitions(Util.getOrCreateConnectContext(), db, "site_access", addPartitionClause);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test")
-                .getTable("site_access");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test")
+                    .getTable("site_access");
 
         Assert.assertNotNull(table.getPartition("p1"));
         Assert.assertNotNull(table.getPartition("p2"));
@@ -155,26 +155,27 @@ public void testMultiRangePartitionForLakeTable() throws Exception {
     public void testSingleRangePartitionPersistInfo() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
         String createSQL = "CREATE TABLE test.new_table (\n" +
-                "      k1 DATE,\n" +
-                "      k2 INT,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "DUPLICATE KEY(k1, k2, k3)\n" +
-                "PARTITION BY RANGE (k1, k2, k3) (\n" +
-                "    PARTITION p1 VALUES [(\"2014-01-01\", \"10\", \"200\"), (\"2014-01-01\", \"20\", \"300\")),\n" +
-                "    PARTITION p2 VALUES [(\"2014-06-01\", \"100\", \"200\"), (\"2014-07-01\", \"100\", \"300\"))\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                "PROPERTIES (\n" +
-                "   \"datacache.enable\" = \"true\"\n" +
-                ")";
+                    "      k1 DATE,\n" +
+                    "      k2 INT,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(k1, k2, k3)\n" +
+                    "PARTITION BY RANGE (k1, k2, k3) (\n" +
+                    "    PARTITION p1 VALUES [(\"2014-01-01\", \"10\", \"200\"), (\"2014-01-01\", \"20\", \"300\")),\n" +
+                    "    PARTITION p2 VALUES [(\"2014-06-01\", \"100\", \"200\"), (\"2014-07-01\", \"100\", \"300\"))\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                    "PROPERTIES (\n" +
+                    "   \"datacache.enable\" = \"true\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("new_table");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "new_table");
         RangePartitionInfo partitionInfo = (RangePartitionInfo) table.getPartitionInfo();
 
         long dbId = db.getId();
@@ -188,7 +189,7 @@ public void testSingleRangePartitionPersistInfo() throws Exception {
         Range<PartitionKey> range = partitionInfo.getRange(partitionId);
         DataCacheInfo dataCacheInfo = partitionInfo.getDataCacheInfo(partitionId);
         RangePartitionPersistInfo partitionPersistInfoOut = new RangePartitionPersistInfo(dbId, tableId, partition,
-                dataProperty, replicationNum, isInMemory, isTempPartition, range, dataCacheInfo);
+                    dataProperty, replicationNum, isInMemory, isTempPartition, range, dataCacheInfo);
 
         // write log
         File file = new File("./test_serial.log");
@@ -229,21 +230,21 @@ public void testAlterTableCompactionForLakeTable() throws Exception {
         DropTableStmt dropTableStmt = (DropTableStmt) UtFrameUtils.parseStmtWithNewParser(dropSQL, ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropTable(dropTableStmt);
         String createSQL = "CREATE TABLE test.t1 (\n" +
-                "      k1 DATE,\n" +
-                "      k2 INT,\n" +
-                "      k3 SMALLINT,\n" +
-                "      v1 VARCHAR(2048),\n" +
-                "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
-                ")\n" +
-                "DUPLICATE KEY(k1, k2, k3)\n" +
-                "PARTITION BY RANGE (k1, k2, k3) (\n" +
-                "    PARTITION p1 VALUES [(\"2014-01-01\", \"10\", \"200\"), (\"2014-01-01\", \"20\", \"300\")),\n" +
-                "    PARTITION p2 VALUES [(\"2014-06-01\", \"100\", \"200\"), (\"2014-07-01\", \"100\", \"300\"))\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                "PROPERTIES (\n" +
-                "   \"datacache.enable\" = \"true\"\n" +
-                ")";
+                    "      k1 DATE,\n" +
+                    "      k2 INT,\n" +
+                    "      k3 SMALLINT,\n" +
+                    "      v1 VARCHAR(2048),\n" +
+                    "      v2 DATETIME DEFAULT \"2014-02-04 15:36:00\"\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(k1, k2, k3)\n" +
+                    "PARTITION BY RANGE (k1, k2, k3) (\n" +
+                    "    PARTITION p1 VALUES [(\"2014-01-01\", \"10\", \"200\"), (\"2014-01-01\", \"20\", \"300\")),\n" +
+                    "    PARTITION p2 VALUES [(\"2014-06-01\", \"100\", \"200\"), (\"2014-07-01\", \"100\", \"300\"))\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                    "PROPERTIES (\n" +
+                    "   \"datacache.enable\" = \"true\"\n" +
+                    ")";
 
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(createSQL, ctx);
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
diff --git a/fe/fe-core/src/test/java/com/starrocks/lake/CreateLakeTableTest.java b/fe/fe-core/src/test/java/com/starrocks/lake/CreateLakeTableTest.java
index 7d78066921ef16..bbba4a7dfe580f 100644
--- a/fe/fe-core/src/test/java/com/starrocks/lake/CreateLakeTableTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/lake/CreateLakeTableTest.java
@@ -67,14 +67,14 @@ private static void createTable(String sql) throws Exception {
     }
 
     private void checkLakeTable(String dbName, String tableName) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
-        Table table = db.getTable(tableName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         Assert.assertTrue(table.isCloudNativeTable());
     }
 
     private LakeTable getLakeTable(String dbName, String tableName) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
-        Table table = db.getTable(tableName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         Assert.assertTrue(table.isCloudNativeTable());
         return (LakeTable) table;
     }
@@ -120,7 +120,7 @@ public void testCreateLakeTable() throws UserException {
                         "properties('replication_num' = '1');"));
         checkLakeTable("lake_test", "multi_partition_unique_key");
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("lake_test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("lake_test");
         LakeTable table = getLakeTable("lake_test", "multi_partition_unique_key");
         String defaultFullPath = getDefaultStorageVolumeFullPath();
         String defaultTableFullPath = String.format("%s/db%d/%d", defaultFullPath, db.getId(), table.getId());
diff --git a/fe/fe-core/src/test/java/com/starrocks/lake/LakeMaterializedViewTest.java b/fe/fe-core/src/test/java/com/starrocks/lake/LakeMaterializedViewTest.java
index e876029060843a..e7425d1143dbf3 100644
--- a/fe/fe-core/src/test/java/com/starrocks/lake/LakeMaterializedViewTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/lake/LakeMaterializedViewTest.java
@@ -94,17 +94,17 @@ public static void setUp() throws Exception {
         starRocksAssert.withDatabase(DB).useDatabase(DB);
 
         starRocksAssert.withTable("CREATE TABLE base_table\n" +
-                "(\n" +
-                "    k1 date,\n" +
-                "    k2 int,\n" +
-                "    k3 int\n" +
-                ")\n" +
-                "PARTITION BY RANGE(k1)\n" +
-                "(\n" +
-                "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
-                "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k2) BUCKETS 3");
+                    "(\n" +
+                    "    k1 date,\n" +
+                    "    k2 int,\n" +
+                    "    k3 int\n" +
+                    ")\n" +
+                    "PARTITION BY RANGE(k1)\n" +
+                    "(\n" +
+                    "    PARTITION p1 values [('2022-02-01'),('2022-02-16')),\n" +
+                    "    PARTITION p2 values [('2022-02-16'),('2022-03-01'))\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 3");
     }
 
     @AfterClass
@@ -157,7 +157,7 @@ int getCurrentStateJournalVersion() {
 
         // Lake mv
         LakeMaterializedView mv = new LakeMaterializedView(mvId, dbId, "mv1", columns, KeysType.AGG_KEYS,
-                partitionInfo, distributionInfo, mvRefreshScheme);
+                    partitionInfo, distributionInfo, mvRefreshScheme);
         Deencapsulation.setField(mv, "baseIndexId", indexId);
         mv.addPartition(partition);
         mv.setIndexMeta(indexId, "mv1", columns, 0, 0, (short) 1, TStorageType.COLUMN, KeysType.AGG_KEYS);
@@ -202,17 +202,18 @@ int getCurrentStateJournalVersion() {
     @Test
     public void testCreateMaterializedView() throws Exception {
         starRocksAssert.withMaterializedView("create materialized view mv1\n" +
-                        "distributed by hash(k2) buckets 3\n" +
-                        "PROPERTIES(\n" +
-                        "   'datacache.enable' = 'true',\n" +
-                        "   'enable_async_write_back' = 'false',\n" +
-                        "   'datacache.partition_duration' = '6 day'\n" +
-                        ")\n" +
-                        "refresh async\n" +
-                        "as select k2, sum(k3) as total from base_table group by k2;");
+                    "distributed by hash(k2) buckets 3\n" +
+                    "PROPERTIES(\n" +
+                    "   'datacache.enable' = 'true',\n" +
+                    "   'enable_async_write_back' = 'false',\n" +
+                    "   'datacache.partition_duration' = '6 day'\n" +
+                    ")\n" +
+                    "refresh async\n" +
+                    "as select k2, sum(k3) as total from base_table group by k2;");
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(DB);
-        MaterializedView mv = (MaterializedView) db.getTable("mv1");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(DB);
+        MaterializedView mv =
+                    (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv1");
         Assert.assertTrue(mv.isCloudNativeMaterializedView());
         Assert.assertTrue(mv.isActive());
 
@@ -243,46 +244,48 @@ public void testCreateMaterializedView() throws Exception {
         Assert.assertNotNull(task);
 
         starRocksAssert.dropMaterializedView("mv1");
-        Assert.assertNull(db.getTable("mv1"));
+        Assert.assertNull(GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv1"));
     }
 
     @Test
     public void testInactiveMaterializedView() throws Exception {
         starRocksAssert.withTable("create table base_table2\n" +
-                "(\n" +
-                "    k4 date,\n" +
-                "    k5 int\n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(k4) BUCKETS 3");
+                    "(\n" +
+                    "    k4 date,\n" +
+                    "    k5 int\n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(k4) BUCKETS 3");
         starRocksAssert.withMaterializedView("create materialized view mv2\n" +
-                "distributed by hash(k2) buckets 3\n" +
-                "refresh async\n" +
-                "as select k1, k2, sum(k3) as total from base_table, base_table2 where k1 = k4 group by k1, k2;");
+                    "distributed by hash(k2) buckets 3\n" +
+                    "refresh async\n" +
+                    "as select k1, k2, sum(k3) as total from base_table, base_table2 where k1 = k4 group by k1, k2;");
 
-        Database db = GlobalStateMgr.getCurrentState().getDb(DB);
-        MaterializedView mv = (MaterializedView) db.getTable("mv2");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(DB);
+        MaterializedView mv =
+                    (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv2");
         Assert.assertTrue(mv.isCloudNativeMaterializedView());
         Assert.assertTrue(mv.isActive());
 
         // drop base table and inactive mv
         starRocksAssert.dropTable("base_table2");
-        Assert.assertNull(db.getTable("base_table2"));
+        Assert.assertNull(GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "base_table2"));
         Assert.assertFalse(mv.isActive());
 
         starRocksAssert.dropMaterializedView("mv2");
-        Assert.assertNull(db.getTable("mv2"));
+        Assert.assertNull(GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv2"));
     }
 
     @Test
     public void testAlterAsyncMaterializedViewInterval() throws Exception {
         starRocksAssert.withMaterializedView("CREATE MATERIALIZED VIEW mv3\n" +
-                        "PARTITION BY k1\n" +
-                        "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
-                        "REFRESH async START('2122-12-31 20:45:11') EVERY(INTERVAL 1 DAY)\n" +
-                        "as select k1,k2 from base_table;");
-
-        Database db = GlobalStateMgr.getCurrentState().getDb(DB);
-        MaterializedView mv = (MaterializedView) db.getTable("mv3");
+                    "PARTITION BY k1\n" +
+                    "DISTRIBUTED BY HASH(k2) BUCKETS 3\n" +
+                    "REFRESH async START('2122-12-31 20:45:11') EVERY(INTERVAL 1 DAY)\n" +
+                    "as select k1,k2 from base_table;");
+
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(DB);
+        MaterializedView mv =
+                    (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv3");
         Assert.assertTrue(mv.isCloudNativeMaterializedView());
 
         MaterializedView.AsyncRefreshContext asyncRefreshContext = mv.getRefreshScheme().getAsyncRefreshContext();
@@ -299,25 +302,26 @@ public void testAlterAsyncMaterializedViewInterval() throws Exception {
         Assert.assertEquals(2, asyncRefreshContext.getStep());
 
         starRocksAssert.dropMaterializedView("mv3");
-        Assert.assertNull(db.getTable("mv3"));
+        Assert.assertNull(GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv3"));
     }
 
     @Test
     public void testModifyRelatedColumnWithMaterializedView() {
         try {
             starRocksAssert.withTable("create table base_table4\n" +
-                    "(\n" +
-                    "    k4 date,\n" +
-                    "    k5 int\n" +
-                    ")\n" +
-                    "duplicate key(k4) distributed by hash(k4) buckets 3;");
+                        "(\n" +
+                        "    k4 date,\n" +
+                        "    k5 int\n" +
+                        ")\n" +
+                        "duplicate key(k4) distributed by hash(k4) buckets 3;");
             starRocksAssert.withMaterializedView("create materialized view mv4\n" +
-                    "distributed by hash(k1) buckets 3\n" +
-                    "refresh async\n" +
-                    "as select k1, k5, sum(k3) as total from base_table, base_table4 where k1 = k4 group by k1, k5;");
+                        "distributed by hash(k1) buckets 3\n" +
+                        "refresh async\n" +
+                        "as select k1, k5, sum(k3) as total from base_table, base_table4 where k1 = k4 group by k1, k5;");
 
-            Database db = GlobalStateMgr.getCurrentState().getDb(DB);
-            MaterializedView mv = (MaterializedView) db.getTable("mv4");
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(DB);
+            MaterializedView mv =
+                        (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv4");
             Assert.assertTrue(mv.isCloudNativeMaterializedView());
             Assert.assertTrue(mv.isActive());
 
@@ -332,9 +336,9 @@ public void testModifyRelatedColumnWithMaterializedView() {
             Assert.assertFalse(mv.isActive());
 
             starRocksAssert.dropMaterializedView("mv4");
-            Assert.assertNull(db.getTable("mv4"));
+            Assert.assertNull(GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv4"));
             starRocksAssert.dropTable("base_table4");
-            Assert.assertNull(db.getTable("base_table4"));
+            Assert.assertNull(GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "base_table4"));
         } catch (Exception e) {
             System.out.println(e);
             Assert.fail();
@@ -345,27 +349,28 @@ public void testModifyRelatedColumnWithMaterializedView() {
     public void testNonPartitionMvEnableFillDataCache() {
         try {
             starRocksAssert.withTable("create table base_table5\n" +
-                    "(\n" +
-                    "    k4 date,\n" +
-                    "    k5 int\n" +
-                    ")\n" +
-                    "duplicate key(k4) distributed by hash(k4) buckets 3;");
+                        "(\n" +
+                        "    k4 date,\n" +
+                        "    k5 int\n" +
+                        ")\n" +
+                        "duplicate key(k4) distributed by hash(k4) buckets 3;");
             starRocksAssert.withMaterializedView("create materialized view mv5\n" +
-                    "distributed by hash(k1) buckets 3\n" +
-                    "refresh async\n" +
-                    "as select k1, k5, sum(k3) as total from base_table, base_table5 where k1 = k4 group by k1, k5;");
+                        "distributed by hash(k1) buckets 3\n" +
+                        "refresh async\n" +
+                        "as select k1, k5, sum(k3) as total from base_table, base_table5 where k1 = k4 group by k1, k5;");
 
-            Database db = GlobalStateMgr.getCurrentState().getDb(DB);
-            MaterializedView mv = (MaterializedView) db.getTable("mv5");
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(DB);
+            MaterializedView mv =
+                        (MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv5");
             Assert.assertTrue(mv.isCloudNativeMaterializedView());
 
             Partition p = mv.getPartition("mv5");
             Assert.assertTrue(mv.isEnableFillDataCache(p));
 
             starRocksAssert.dropMaterializedView("mv5");
-            Assert.assertNull(db.getTable("mv5"));
+            Assert.assertNull(GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "mv5"));
             starRocksAssert.dropTable("base_table5");
-            Assert.assertNull(db.getTable("base_table5"));
+            Assert.assertNull(GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "base_table5"));
         } catch (Exception e) {
             System.out.println(e);
             Assert.fail();
@@ -418,7 +423,7 @@ int getCurrentStateJournalVersion() {
         LocalDate lower1 = upper1.minus(duration);
         Range<PartitionKey> range1 = Range.closedOpen(PartitionKey.ofDate(lower1), PartitionKey.ofDate(upper1));
         partitionInfo.addPartition(partition1Id, false, range1, DataProperty.DEFAULT_DATA_PROPERTY, (short) 1, false,
-                                   new DataCacheInfo(true, false));
+                    new DataCacheInfo(true, false));
 
         // partition2
         MaterializedIndex index2 = new MaterializedIndex(indexId, MaterializedIndex.IndexState.NORMAL);
@@ -431,7 +436,7 @@ int getCurrentStateJournalVersion() {
         LocalDate lower2 = upper2.minus(duration);
         Range<PartitionKey> range2 = Range.closedOpen(PartitionKey.ofDate(lower2), PartitionKey.ofDate(upper2));
         partitionInfo.addPartition(partition2Id, false, range2, DataProperty.DEFAULT_DATA_PROPERTY, (short) 1, false,
-                                   new DataCacheInfo(true, false));
+                    new DataCacheInfo(true, false));
 
         // refresh scheme
         MvRefreshScheme mvRefreshScheme = new MvRefreshScheme();
@@ -439,7 +444,7 @@ int getCurrentStateJournalVersion() {
 
         // Lake mv
         LakeMaterializedView mv = new LakeMaterializedView(mvId, dbId, "mv1", columns, KeysType.AGG_KEYS,
-                                                           partitionInfo, distributionInfo, mvRefreshScheme);
+                    partitionInfo, distributionInfo, mvRefreshScheme);
         Deencapsulation.setField(mv, "baseIndexId", indexId);
         mv.addPartition(partition1);
         mv.addPartition(partition2);
diff --git a/fe/fe-core/src/test/java/com/starrocks/lake/compaction/QuantilesTest.java b/fe/fe-core/src/test/java/com/starrocks/lake/compaction/QuantilesTest.java
new file mode 100644
index 00000000000000..02c87ff7c16662
--- /dev/null
+++ b/fe/fe-core/src/test/java/com/starrocks/lake/compaction/QuantilesTest.java
@@ -0,0 +1,78 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+package com.starrocks.lake.compaction;
+
+import org.junit.Assert;
+import org.junit.Test;
+
+public class QuantilesTest {
+    @Test
+    public void testCompare() {
+        // avg
+        {
+            Quantiles q1 = new Quantiles(1.0, 0.0, 0.0);
+            Quantiles q2 = new Quantiles(1.0, 0.0, 0.0);
+            Assert.assertTrue(q1.compareTo(q2) == 0);
+        }
+        {
+            Quantiles q1 = new Quantiles(1.0, 0.0, 0.0);
+            Quantiles q2 = new Quantiles(2.0, 0.0, 0.0);
+            Assert.assertTrue(q1.compareTo(q2) < 0);
+        }
+        {
+            Quantiles q1 = new Quantiles(2.0, 0.0, 0.0);
+            Quantiles q2 = new Quantiles(1.0, 0.0, 0.0);
+            Assert.assertTrue(q1.compareTo(q2) > 0);
+        }
+        // p50
+        {
+            Quantiles q1 = new Quantiles(0.0, 1.0, 0.0);
+            Quantiles q2 = new Quantiles(0.0, 1.0, 0.0);
+            Assert.assertTrue(q1.compareTo(q2) == 0);
+        }
+        {
+            Quantiles q1 = new Quantiles(0.0, 1.0, 0.0);
+            Quantiles q2 = new Quantiles(0.0, 2.0, 0.0);
+            Assert.assertTrue(q1.compareTo(q2) < 0);
+        }
+        {
+            Quantiles q1 = new Quantiles(0.0, 2.0, 0.0);
+            Quantiles q2 = new Quantiles(0.0, 1.0, 0.0);
+            Assert.assertTrue(q1.compareTo(q2) > 0);
+        }
+        // max
+        {
+            Quantiles q1 = new Quantiles(0.0, 0.0, 1.0);
+            Quantiles q2 = new Quantiles(0.0, 0.0, 1.0);
+            Assert.assertTrue(q1.compareTo(q2) == 0);
+        }
+        {
+            Quantiles q1 = new Quantiles(0.0, 0.0, 1.0);
+            Quantiles q2 = new Quantiles(0.0, 0.0, 2.0);
+            Assert.assertTrue(q1.compareTo(q2) < 0);
+        }
+        {
+            Quantiles q1 = new Quantiles(0.0, 0.0, 2.0);
+            Quantiles q2 = new Quantiles(0.0, 0.0, 1.0);
+            Assert.assertTrue(q1.compareTo(q2) > 0);
+        }
+
+        {
+            Quantiles q1 = new Quantiles(1.0, 1.0, 1.0);
+            Quantiles q2 = new Quantiles(1.0, 1.0, 1.0);
+            Assert.assertTrue(q1.compareTo(q2) == 0);
+        }
+    }
+}
diff --git a/fe/fe-core/src/test/java/com/starrocks/lake/delete/DeleteTest.java b/fe/fe-core/src/test/java/com/starrocks/lake/delete/DeleteTest.java
index dcbc2d935cde00..5247c9177d6afc 100644
--- a/fe/fe-core/src/test/java/com/starrocks/lake/delete/DeleteTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/lake/delete/DeleteTest.java
@@ -149,9 +149,12 @@ public void setUpExpectation() {
                 GlobalStateMgr.getCurrentState();
                 result = globalStateMgr;
 
-                globalStateMgr.getDb(anyString);
+                globalStateMgr.getLocalMetastore().getDb(anyString);
                 result = db;
 
+                globalStateMgr.getLocalMetastore().getTable(anyString, anyString);
+                result = db.getTable(tableId);
+
                 GlobalStateMgr.getCurrentState().getGlobalTransactionMgr();
                 result = globalTransactionMgr;
 
@@ -324,9 +327,12 @@ public void setUpExpectationWithoutExec() {
                 GlobalStateMgr.getCurrentState();
                 result = globalStateMgr;
 
-                globalStateMgr.getDb(anyString);
+                globalStateMgr.getLocalMetastore().getDb(anyString);
                 result = db;
 
+                globalStateMgr.getLocalMetastore().getTable(anyString, anyString);
+                result = db.getTable(tableId);
+
                 GlobalStateMgr.getCurrentState().getGlobalTransactionMgr();
                 result = globalTransactionMgr;
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/lake/qe/ShowExecutorTest.java b/fe/fe-core/src/test/java/com/starrocks/lake/qe/ShowExecutorTest.java
index cd64e34088b19d..4d0d334a1ce969 100644
--- a/fe/fe-core/src/test/java/com/starrocks/lake/qe/ShowExecutorTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/lake/qe/ShowExecutorTest.java
@@ -81,11 +81,11 @@ public RunMode getCurrentRunMode() {
         globalStateMgr = Deencapsulation.newInstance(GlobalStateMgr.class);
         new Expectations(globalStateMgr) {
             {
-                globalStateMgr.getDb("testDb");
+                globalStateMgr.getLocalMetastore().getDb("testDb");
                 minTimes = 0;
                 result = db;
 
-                globalStateMgr.getDb("testDb1");
+                globalStateMgr.getLocalMetastore().getDb("testDb1");
                 minTimes = 0;
                 result = db1;
             }
diff --git a/fe/fe-core/src/test/java/com/starrocks/leader/ReportHandlerTest.java b/fe/fe-core/src/test/java/com/starrocks/leader/ReportHandlerTest.java
index 5b5ff4fdc1c206..57855330274979 100644
--- a/fe/fe-core/src/test/java/com/starrocks/leader/ReportHandlerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/leader/ReportHandlerTest.java
@@ -85,22 +85,22 @@ public static void beforeClass() throws Exception {
         StarRocksAssert starRocksAssert = new StarRocksAssert(connectContext);
 
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE test.properties_change_test(k1 int, v1 int) " +
-                        "primary key(k1) distributed by hash(k1) properties('replication_num' = '1');")
-                .withTable("CREATE TABLE test.binlog_report_handler_test(k1 int, v1 int) " +
-                        "duplicate key(k1) distributed by hash(k1) buckets 50 properties('replication_num' = '1', " +
-                        "'binlog_enable' = 'true', 'binlog_max_size' = '100');")
-                .withTable("CREATE TABLE test.primary_index_cache_expire_sec_test(k1 int, v1 int) " +
-                        "primary key(k1) distributed by hash(k1) buckets 5 properties('replication_num' = '1', " +
-                        "'primary_index_cache_expire_sec' = '3600');")
-                .withTable("CREATE TABLE test.update_schema(k1 int, v1 int) " +
-                        "primary key(k1) distributed by hash(k1) buckets 5 properties('replication_num' = '1', " +
-                        "'primary_index_cache_expire_sec' = '3600');");
+                    .withTable("CREATE TABLE test.properties_change_test(k1 int, v1 int) " +
+                                "primary key(k1) distributed by hash(k1) properties('replication_num' = '1');")
+                    .withTable("CREATE TABLE test.binlog_report_handler_test(k1 int, v1 int) " +
+                                "duplicate key(k1) distributed by hash(k1) buckets 50 properties('replication_num' = '1', " +
+                                "'binlog_enable' = 'true', 'binlog_max_size' = '100');")
+                    .withTable("CREATE TABLE test.primary_index_cache_expire_sec_test(k1 int, v1 int) " +
+                                "primary key(k1) distributed by hash(k1) buckets 5 properties('replication_num' = '1', " +
+                                "'primary_index_cache_expire_sec' = '3600');")
+                    .withTable("CREATE TABLE test.update_schema(k1 int, v1 int) " +
+                                "primary key(k1) distributed by hash(k1) buckets 5 properties('replication_num' = '1', " +
+                                "'primary_index_cache_expire_sec' = '3600');");
     }
 
     @Test
     public void testHandleSetTabletEnablePersistentIndex() {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         long dbId = db.getId();
         long backendId = 10001L;
         List<Long> tabletIds = GlobalStateMgr.getCurrentState().getTabletInvertedIndex().getTabletIdsByBackendId(10001);
@@ -124,9 +124,10 @@ public void testHandleSetTabletEnablePersistentIndex() {
 
     @Test
     public void testHandleSetPrimaryIndexCacheExpireSec() {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         long dbId = db.getId();
-        OlapTable olapTable = (OlapTable) db.getTable("primary_index_cache_expire_sec_test");
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "primary_index_cache_expire_sec_test");
         long backendId = 10001L;
         List<Long> tabletIds = GlobalStateMgr.getCurrentState().getTabletInvertedIndex().getTabletIdsByBackendId(10001);
         Assert.assertFalse(tabletIds.isEmpty());
@@ -149,21 +150,22 @@ public void testHandleSetPrimaryIndexCacheExpireSec() {
 
     @Test
     public void testHandleUpdateTableSchema() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         long dbId = db.getId();
-        OlapTable olapTable = (OlapTable) db.getTable("update_schema");
+        OlapTable olapTable =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "update_schema");
 
         String stmt = "alter table update_schema add column add_v int default '1'";
         StarRocksAssert starRocksAssert = new StarRocksAssert(connectContext);
         AlterTableStmt alterTableStmt =
-                (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(stmt, starRocksAssert.getCtx());
+                    (AlterTableStmt) UtFrameUtils.parseStmtWithNewParser(stmt, starRocksAssert.getCtx());
         SchemaChangeHandler schemaChangeHandler = GlobalStateMgr.getCurrentState().getSchemaChangeHandler();
         schemaChangeHandler.process(alterTableStmt.getAlterClauseList(), db, olapTable);
         Assert.assertEquals(OlapTableState.NORMAL, olapTable.getState());
 
         long backendId = 10001L;
         List<Long> tabletIds =
-                GlobalStateMgr.getCurrentState().getTabletInvertedIndex().getTabletIdsByBackendId(10001);
+                    GlobalStateMgr.getCurrentState().getTabletInvertedIndex().getTabletIdsByBackendId(10001);
         Assert.assertFalse(tabletIds.isEmpty());
 
         Map<Long, TTablet> backendTablets = new HashMap<Long, TTablet>();
@@ -184,9 +186,10 @@ public void testHandleUpdateTableSchema() throws Exception {
 
     @Test
     public void testHandleSetTabletBinlogConfig() {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         long dbId = db.getId();
-        OlapTable olapTable = (OlapTable) db.getTable("binlog_report_handler_test");
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "binlog_report_handler_test");
         long backendId = 10001L;
         List<Long> tabletIds = GlobalStateMgr.getCurrentState().getTabletInvertedIndex().getTabletIdsByBackendId(10001);
         Assert.assertFalse(tabletIds.isEmpty());
@@ -375,7 +378,7 @@ public void testHandleMigration() throws TException {
         for (int i = 0; i < tabletMetaList.size(); i++) {
             long tabletId = tabletIds.get(i);
             TabletMeta tabletMeta = tabletMetaList.get(i);
-            Database db = GlobalStateMgr.getCurrentState().getDb("test");
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
             if (db == null) {
                 continue;
             }
@@ -383,7 +386,8 @@ public void testHandleMigration() throws TException {
             Locker locker = new Locker();
             locker.lockDatabase(db, LockType.READ);
             try {
-                table = (OlapTable) db.getTable(tabletMeta.getTableId());
+                table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(db.getId(), tabletMeta.getTableId());
             } finally {
                 locker.unLockDatabase(db, LockType.READ);
             }
@@ -413,11 +417,11 @@ public void submit(AgentBatchTask task) {
         };
 
         OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState()
-                .getDb("test").getTable("binlog_report_handler_test");
+                    .getLocalMetastore().getDb("test").getTable("binlog_report_handler_test");
         ListMultimap<TStorageMedium, Long> tabletMetaMigrationMap = ArrayListMultimap.create();
         List<Long> allTablets = new ArrayList<>();
         for (MaterializedIndex index : olapTable.getPartition("binlog_report_handler_test")
-                .getMaterializedIndices(MaterializedIndex.IndexExtState.ALL)) {
+                    .getMaterializedIndices(MaterializedIndex.IndexExtState.ALL)) {
             for (Tablet tablet : index.getTablets()) {
                 tabletMetaMigrationMap.put(TStorageMedium.HDD, tablet.getId());
                 allTablets.add(tablet.getId());
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/BrokerFileGroupTest.java b/fe/fe-core/src/test/java/com/starrocks/load/BrokerFileGroupTest.java
index 1e7b2bdf2926c7..84322205d58972 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/BrokerFileGroupTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/BrokerFileGroupTest.java
@@ -31,11 +31,14 @@
 import com.starrocks.catalog.Type;
 import com.starrocks.common.CsvFormat;
 import com.starrocks.common.UserException;
+import com.starrocks.server.LocalMetastore;
 import com.starrocks.sql.ast.DataDescription;
 import com.starrocks.sql.ast.UserIdentity;
 import com.starrocks.utframe.StarRocksAssert;
 import com.starrocks.utframe.UtFrameUtils;
 import mockit.Expectations;
+import mockit.Mock;
+import mockit.MockUp;
 import mockit.Mocked;
 import org.junit.Assert;
 import org.junit.BeforeClass;
@@ -154,6 +157,13 @@ public void testParseHiveTable() throws UserException {
             }
         };
 
+        new MockUp<LocalMetastore>() {
+            @Mock
+            public Database getDb(String dbName) {
+                return db;
+            }
+        };
+
         BrokerFileGroup fileGroup = new BrokerFileGroup(desc);
         fileGroup.parse(db, desc);
         Assert.assertEquals(Lists.newArrayList("k1", "k2"), fileGroup.getFileFieldNames());
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/DeleteHandlerTest.java b/fe/fe-core/src/test/java/com/starrocks/load/DeleteHandlerTest.java
index c79ff8ed77e845..bd08f4abd51280 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/DeleteHandlerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/DeleteHandlerTest.java
@@ -44,6 +44,7 @@
 import com.starrocks.qe.ConnectContext;
 import com.starrocks.qe.QueryStateException;
 import com.starrocks.server.GlobalStateMgr;
+import com.starrocks.server.LocalMetastore;
 import com.starrocks.sql.analyzer.Analyzer;
 import com.starrocks.sql.ast.DeleteStmt;
 import com.starrocks.sql.ast.PartitionNames;
@@ -136,14 +137,26 @@ public void logInsertTransactionState(TransactionState transactionState) {
 
         new Expectations() {
             {
-                globalStateMgr.getDb(anyString);
+                GlobalStateMgr.getCurrentState();
+                minTimes = 0;
+                result = globalStateMgr;
+
+                globalStateMgr.getLocalMetastore().getDb(anyString);
                 minTimes = 0;
                 result = db;
 
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = db;
 
+                globalStateMgr.getLocalMetastore().getTable("test_db", "test_tbl");
+                minTimes = 0;
+                result = db.getTable("test_tbl");
+
+                globalStateMgr.getLocalMetastore().getTable(CatalogMocker.TEST_DB_ID, CatalogMocker.TEST_TBL_ID);
+                minTimes = 0;
+                result = db.getTable("test_tbl");
+
                 globalStateMgr.getEditLog();
                 minTimes = 0;
                 result = editLog;
@@ -190,6 +203,13 @@ public void logInsertTransactionState(TransactionState transactionState) {
                 minTimes = 0;
             }
         };
+
+        new MockUp<LocalMetastore>() {
+            @Mock
+            public Database getDb(String dbName) {
+                return db;
+            }
+        };
     }
 
     @Test(expected = DdlException.class)
@@ -535,6 +555,18 @@ public void lock(long rid, LockType lockType, long timeout) throws LockException
 
     @Test
     public void testRemoveOldOnReplay() throws Exception {
+        new Expectations(globalStateMgr) {
+            {
+                globalStateMgr.getLocalMetastore().getDb(1L);
+                minTimes = 0;
+                result = db;
+
+                globalStateMgr.getLocalMetastore().getTable(anyLong, anyLong);
+                minTimes = 0;
+                result = db.getTable("test_tbl");
+            }
+        };
+
         Config.label_keep_max_second = 1;
         Config.label_keep_max_num = 10;
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/DeletePruneTest.java b/fe/fe-core/src/test/java/com/starrocks/load/DeletePruneTest.java
index c001875db12f53..bbbbe3233fed25 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/DeletePruneTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/DeletePruneTest.java
@@ -17,6 +17,7 @@
 import com.starrocks.catalog.Database;
 import com.starrocks.catalog.OlapTable;
 import com.starrocks.qe.ConnectContext;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.ast.DeleteStmt;
 import com.starrocks.utframe.StarRocksAssert;
 import com.starrocks.utframe.UtFrameUtils;
@@ -41,55 +42,56 @@ public static void beforeClass() throws Exception {
         deleteHandler = new DeleteMgr();
 
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE `test_delete` (\n" +
-                        "  `k1` date NULL COMMENT \"\",\n" +
-                        "  `k2` datetime NULL COMMENT \"\",\n" +
-                        "  `k3` char(20) NULL COMMENT \"\",\n" +
-                        "  `k4` varchar(20) NULL COMMENT \"\",\n" +
-                        "  `k5` boolean NULL COMMENT \"\",\n" +
-                        "  `k6` tinyint(4) NULL COMMENT \"\",\n" +
-                        "  `k7` smallint(6) NULL COMMENT \"\",\n" +
-                        "  `k8` int(11) NULL COMMENT \"\",\n" +
-                        "  `k9` bigint(20) NULL COMMENT \"\",\n" +
-                        "  `k10` largeint(40) NULL COMMENT \"\",\n" +
-                        "  `k11` float NULL COMMENT \"\",\n" +
-                        "  `k12` double NULL COMMENT \"\",\n" +
-                        "  `k13` decimal128(27, 9) NULL COMMENT \"\"\n" +
-                        ") ENGINE=OLAP \n" +
-                        "DUPLICATE KEY(`k1`, `k2`, `k3`, `k4`, `k5`)\n" +
-                        "COMMENT \"OLAP\"\n" +
-                        "PARTITION BY RANGE(`k1`) (\n" +
-                        "    START (\"2020-01-01\") END (\"2021-01-01\") EVERY (INTERVAL 1 day)\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(`k1`, `k2`, `k3`) BUCKETS 3 \n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\",\n" +
-                        "\"in_memory\" = \"false\"\n" +
-                        ");")
-                .withTable("CREATE TABLE `test_delete2` (\n" +
-                        "  `date` date NULL COMMENT \"\",\n" +
-                        "  `id` int(11) NULL COMMENT \"\",\n" +
-                        "  `value` char(20) NULL COMMENT \"\"\n" +
-                        ") ENGINE=OLAP \n" +
-                        "DUPLICATE KEY(`date`, `id`)\n" +
-                        "COMMENT \"OLAP\"\n" +
-                        "PARTITION BY RANGE(`date`, `id`)\n" +
-                        "(\n" +
-                        "    PARTITION `p202001_1000` VALUES LESS THAN (\"2020-02-01\", \"1000\"),\n" +
-                        "    PARTITION `p202002_2000` VALUES LESS THAN (\"2020-03-01\", \"2000\"),\n" +
-                        "    PARTITION `p202003_all`  VALUES LESS THAN (\"2020-04-01\")\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(`date`, `id`) BUCKETS 3 \n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\"\n" +
-                        ");");
+                    .withTable("CREATE TABLE `test_delete` (\n" +
+                                "  `k1` date NULL COMMENT \"\",\n" +
+                                "  `k2` datetime NULL COMMENT \"\",\n" +
+                                "  `k3` char(20) NULL COMMENT \"\",\n" +
+                                "  `k4` varchar(20) NULL COMMENT \"\",\n" +
+                                "  `k5` boolean NULL COMMENT \"\",\n" +
+                                "  `k6` tinyint(4) NULL COMMENT \"\",\n" +
+                                "  `k7` smallint(6) NULL COMMENT \"\",\n" +
+                                "  `k8` int(11) NULL COMMENT \"\",\n" +
+                                "  `k9` bigint(20) NULL COMMENT \"\",\n" +
+                                "  `k10` largeint(40) NULL COMMENT \"\",\n" +
+                                "  `k11` float NULL COMMENT \"\",\n" +
+                                "  `k12` double NULL COMMENT \"\",\n" +
+                                "  `k13` decimal128(27, 9) NULL COMMENT \"\"\n" +
+                                ") ENGINE=OLAP \n" +
+                                "DUPLICATE KEY(`k1`, `k2`, `k3`, `k4`, `k5`)\n" +
+                                "COMMENT \"OLAP\"\n" +
+                                "PARTITION BY RANGE(`k1`) (\n" +
+                                "    START (\"2020-01-01\") END (\"2021-01-01\") EVERY (INTERVAL 1 day)\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(`k1`, `k2`, `k3`) BUCKETS 3 \n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\",\n" +
+                                "\"in_memory\" = \"false\"\n" +
+                                ");")
+                    .withTable("CREATE TABLE `test_delete2` (\n" +
+                                "  `date` date NULL COMMENT \"\",\n" +
+                                "  `id` int(11) NULL COMMENT \"\",\n" +
+                                "  `value` char(20) NULL COMMENT \"\"\n" +
+                                ") ENGINE=OLAP \n" +
+                                "DUPLICATE KEY(`date`, `id`)\n" +
+                                "COMMENT \"OLAP\"\n" +
+                                "PARTITION BY RANGE(`date`, `id`)\n" +
+                                "(\n" +
+                                "    PARTITION `p202001_1000` VALUES LESS THAN (\"2020-02-01\", \"1000\"),\n" +
+                                "    PARTITION `p202002_2000` VALUES LESS THAN (\"2020-03-01\", \"2000\"),\n" +
+                                "    PARTITION `p202003_all`  VALUES LESS THAN (\"2020-04-01\")\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(`date`, `id`) BUCKETS 3 \n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\"\n" +
+                                ");");
     }
 
     @Test
     public void testDeletePrune() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
-        Database db = ctx.getGlobalStateMgr().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("test_delete");
+        Database db = ctx.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        OlapTable tbl =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_delete");
 
         String deleteSQL = "delete from test_delete where k1 = '2020-01-01'";
         DeleteStmt deleteStmt = (DeleteStmt) UtFrameUtils.parseStmtWithNewParser(deleteSQL, ctx);
@@ -153,8 +155,9 @@ public void testDeletePrune() throws Exception {
     @Test
     public void testDeletePruneMultiPartition() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
-        Database db = ctx.getGlobalStateMgr().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("test_delete2");
+        Database db = ctx.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        OlapTable tbl =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_delete2");
 
         String deleteSQL = "delete from test_delete2 where date in ('2020-02-02') and id = 1000";
         DeleteStmt deleteStmt = (DeleteStmt) UtFrameUtils.parseStmtWithNewParser(deleteSQL, ctx);
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/InsertOverwriteJobRunnerTest.java b/fe/fe-core/src/test/java/com/starrocks/load/InsertOverwriteJobRunnerTest.java
index 2de8ebd435a7f5..944cf9c976db48 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/InsertOverwriteJobRunnerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/InsertOverwriteJobRunnerTest.java
@@ -83,8 +83,8 @@ public static void beforeClass() throws Exception {
 
     @Test
     public void testReplayInsertOverwrite() {
-        Database database = GlobalStateMgr.getCurrentState().getDb("insert_overwrite_test");
-        Table table = database.getTable("t1");
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("insert_overwrite_test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), "t1");
         Assert.assertTrue(table instanceof OlapTable);
         OlapTable olapTable = (OlapTable) table;
         InsertOverwriteJob insertOverwriteJob = new InsertOverwriteJob(100L, database.getId(), olapTable.getId(),
@@ -123,8 +123,8 @@ public void testInsertOverwrite() throws Exception {
         String sql = "insert overwrite t1 select * from t2";
         InsertStmt insertStmt = (InsertStmt) UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
         StmtExecutor executor = new StmtExecutor(connectContext, insertStmt);
-        Database database = GlobalStateMgr.getCurrentState().getDb("insert_overwrite_test");
-        Table table = database.getTable("t1");
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("insert_overwrite_test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), "t1");
         Assert.assertTrue(table instanceof OlapTable);
         OlapTable olapTable = (OlapTable) table;
         InsertOverwriteJob insertOverwriteJob = new InsertOverwriteJob(100L, insertStmt, database.getId(), olapTable.getId(),
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/loadv2/BrokerLoadJobTest.java b/fe/fe-core/src/test/java/com/starrocks/load/loadv2/BrokerLoadJobTest.java
index adca22a76c759b..1731834094c10c 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/loadv2/BrokerLoadJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/loadv2/BrokerLoadJobTest.java
@@ -108,21 +108,17 @@ public void testFromLoadStmt(@Injectable LoadStmt loadStmt,
                 loadStmt.getLabel();
                 minTimes = 0;
                 result = labelName;
+
                 labelName.getDbName();
                 minTimes = 0;
                 result = databaseName;
-                globalStateMgr.getDb(databaseName);
-                minTimes = 0;
-                result = database;
+
                 loadStmt.getDataDescriptions();
                 minTimes = 0;
                 result = dataDescriptionList;
                 dataDescription.getTableName();
                 minTimes = 0;
                 result = tableName;
-                database.getTable(tableName);
-                minTimes = 0;
-                result = null;
             }
         };
 
@@ -162,7 +158,7 @@ public void testFromLoadStmt2(@Injectable LoadStmt loadStmt,
                 labelName.getLabelName();
                 minTimes = 0;
                 result = label;
-                globalStateMgr.getDb(databaseName);
+                globalStateMgr.getLocalMetastore().getDb(databaseName);
                 minTimes = 0;
                 result = database;
                 loadStmt.getDataDescriptions();
@@ -171,7 +167,7 @@ public void testFromLoadStmt2(@Injectable LoadStmt loadStmt,
                 dataDescription.getTableName();
                 minTimes = 0;
                 result = tableName;
-                database.getTable(tableName);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), tableName);
                 minTimes = 0;
                 result = olapTable;
                 dataDescription.getPartitionNames();
@@ -231,7 +227,7 @@ public void testAlterLoad(@Injectable LoadStmt loadStmt,
                 labelName.getLabelName();
                 minTimes = 0;
                 result = label;
-                globalStateMgr.getDb(databaseName);
+                globalStateMgr.getLocalMetastore().getDb(databaseName);
                 minTimes = 0;
                 result = database;
                 loadStmt.getDataDescriptions();
@@ -240,7 +236,7 @@ public void testAlterLoad(@Injectable LoadStmt loadStmt,
                 dataDescription.getTableName();
                 minTimes = 0;
                 result = tableName;
-                database.getTable(tableName);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), tableName);
                 minTimes = 0;
                 result = olapTable;
                 dataDescription.getPartitionNames();
@@ -296,10 +292,10 @@ public void testGetTableNames(@Injectable BrokerFileGroupAggInfo fileGroupAggInf
                 fileGroupAggInfo.getAllTableIds();
                 minTimes = 0;
                 result = Sets.newHashSet(1L);
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = database;
-                database.getTable(1L);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), 1L);
                 minTimes = 0;
                 result = table;
                 table.getName();
@@ -567,7 +563,7 @@ public void testLoadingTaskOnFinished(@Injectable BrokerLoadingTaskAttachment at
                 attachment1.getTaskId();
                 minTimes = 0;
                 result = 1L;
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = database;
             }
@@ -719,7 +715,7 @@ public void testCommitRateExceeded(@Injectable BrokerLoadingTaskAttachment attac
                 attachment1.getTaskId();
                 minTimes = 0;
                 result = 1L;
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = database;
                 globalStateMgr.getCurrentState().getGlobalTransactionMgr();
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/loadv2/InsertLoadJobTest.java b/fe/fe-core/src/test/java/com/starrocks/load/loadv2/InsertLoadJobTest.java
index 8bbc74ce9eb05d..39688d0477c054 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/loadv2/InsertLoadJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/loadv2/InsertLoadJobTest.java
@@ -62,9 +62,9 @@ public void testGetTableNames(@Mocked GlobalStateMgr globalStateMgr,
         String tableName = "table1";
         new Expectations() {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 result = database;
-                database.getTable(anyLong);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), anyLong);
                 result = table;
                 table.getName();
                 result = tableName;
@@ -84,9 +84,9 @@ public void testUpdateProgress(@Mocked GlobalStateMgr globalStateMgr,
                                    @Injectable Table table) throws MetaNotFoundException {
         new Expectations() {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 result = database;
-                database.getTable(anyLong);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), anyLong);
                 result = table;
                 table.getName();
                 result = "some_table";
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/loadv2/LoadJobTest.java b/fe/fe-core/src/test/java/com/starrocks/load/loadv2/LoadJobTest.java
index 291a688cc33a83..64f9baf3d15489 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/loadv2/LoadJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/loadv2/LoadJobTest.java
@@ -80,7 +80,7 @@ public void testGetDbNotExists(@Mocked GlobalStateMgr globalStateMgr) {
         Deencapsulation.setField(loadJob, "dbId", 1L);
         new Expectations() {
             {
-                globalStateMgr.getDb(1L);
+                globalStateMgr.getLocalMetastore().getDb(1L);
                 minTimes = 0;
                 result = null;
             }
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/loadv2/LoadMgrTest.java b/fe/fe-core/src/test/java/com/starrocks/load/loadv2/LoadMgrTest.java
index 88aaf3e3deb410..5734ed0eab5719 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/loadv2/LoadMgrTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/loadv2/LoadMgrTest.java
@@ -83,10 +83,10 @@ public void testSerializationNormal(@Mocked GlobalStateMgr globalStateMgr,
                                         @Injectable Table table) throws Exception {
         new Expectations() {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = database;
-                database.getTable(anyLong);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), anyLong);
                 minTimes = 0;
                 result = table;
                 table.getName();
@@ -115,10 +115,10 @@ public void testSerializationWithJobRemoved(@Mocked MetaContext metaContext,
                                                 @Injectable Table table) throws Exception {
         new Expectations() {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = database;
-                database.getTable(anyLong);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), anyLong);
                 minTimes = 0;
                 result = table;
                 table.getName();
@@ -150,10 +150,10 @@ public void testDeserializationWithJobRemoved(@Mocked MetaContext metaContext,
                                                 @Injectable Table table) throws Exception {
         new Expectations() {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = database;
-                database.getTable(anyLong);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), anyLong);
                 minTimes = 0;
                 result = table;
                 table.getName();
@@ -206,7 +206,7 @@ public void testRemoveOldLoadJob(@Mocked GlobalStateMgr globalStateMgr,
                                      @Injectable Database db) throws Exception {
         new Expectations() {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 result = db;
             }
         };
@@ -320,7 +320,7 @@ public void testLoadJsonImage(@Mocked GlobalStateMgr globalStateMgr,
                                   @Injectable Database db) throws Exception {
         new Expectations() {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 result = db;
             }
         };
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/loadv2/SparkLoadJobTest.java b/fe/fe-core/src/test/java/com/starrocks/load/loadv2/SparkLoadJobTest.java
index 9afbd98c1e8958..c0c5c5ce412850 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/loadv2/SparkLoadJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/loadv2/SparkLoadJobTest.java
@@ -157,11 +157,11 @@ public void testCreateFromLoadStmt(@Mocked GlobalStateMgr globalStateMgr, @Injec
 
         new Expectations() {
             {
-                globalStateMgr.getDb(dbName);
+                globalStateMgr.getLocalMetastore().getDb(dbName);
                 result = db;
                 globalStateMgr.getResourceMgr();
                 result = resourceMgr;
-                db.getTable(tableName);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
                 result = olapTable;
                 db.getId();
                 result = dbId;
@@ -372,9 +372,9 @@ public void testUpdateEtlStatusFinishedAndCommitTransaction(
                 result = status;
                 handler.getEtlFilePaths(etlOutputPath, (BrokerDesc) any);
                 result = filePathToSize;
-                globalStateMgr.getDb(dbId);
+                globalStateMgr.getLocalMetastore().getDb(dbId);
                 result = db;
-                db.getTable(tableId);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
                 result = table;
                 table.getPartition(partitionId);
                 result = partition;
@@ -470,9 +470,9 @@ public void testUpdateEtlStatusFinishedAndCommitTransactionForLake(
                 result = status;
                 handler.getEtlFilePaths(etlOutputPath, (BrokerDesc) any);
                 result = filePathToSize;
-                globalStateMgr.getDb(dbId);
+                globalStateMgr.getLocalMetastore().getDb(dbId);
                 result = db;
-                db.getTable(tableId);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), tableId);
                 result = table;
                 table.getPartition(partitionId);
                 result = partition;
@@ -528,7 +528,7 @@ public void testSubmitTasksWhenStateFinished(@Mocked GlobalStateMgr globalStateM
                                                  @Injectable Database db) throws Exception {
         new Expectations() {
             {
-                globalStateMgr.getDb(dbId);
+                globalStateMgr.getLocalMetastore().getDb(dbId);
                 result = db;
             }
         };
@@ -619,7 +619,7 @@ public void testNoPartitionsHaveDataLoad(@Mocked GlobalStateMgr globalStateMgr,
                                              @Injectable Database db) throws Exception {
         new Expectations() {
             {
-                globalStateMgr.getDb(dbId);
+                globalStateMgr.getLocalMetastore().getDb(dbId);
                 result = db;
             }
         };
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/loadv2/SparkLoadPendingTaskTest.java b/fe/fe-core/src/test/java/com/starrocks/load/loadv2/SparkLoadPendingTaskTest.java
index 075cebd55cf8f2..ce5c02c2bcf848 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/loadv2/SparkLoadPendingTaskTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/loadv2/SparkLoadPendingTaskTest.java
@@ -125,11 +125,11 @@ public void testExecuteTask(@Injectable SparkLoadJob sparkLoadJob,
 
         new Expectations() {
             {
-                globalStateMgr.getDb(dbId);
+                globalStateMgr.getLocalMetastore().getDb(dbId);
                 result = database;
                 sparkLoadJob.getHandle();
                 result = handle;
-                database.getTable(tableId);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), tableId);
                 result = table;
                 table.getPartitions();
                 result = partitions;
@@ -181,7 +181,7 @@ public void testNoDb(@Injectable SparkLoadJob sparkLoadJob,
 
         new Expectations() {
             {
-                globalStateMgr.getDb(dbId);
+                globalStateMgr.getLocalMetastore().getDb(dbId);
                 result = null;
             }
         };
@@ -210,9 +210,9 @@ public void testNoTable(@Injectable SparkLoadJob sparkLoadJob,
 
         new Expectations() {
             {
-                globalStateMgr.getDb(dbId);
+                globalStateMgr.getLocalMetastore().getDb(dbId);
                 result = database;
-                database.getTable(tableId);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), tableId);
                 result = null;
             }
         };
@@ -286,9 +286,9 @@ public void testRangePartitionHashDistribution(@Injectable SparkLoadJob sparkLoa
 
         new Expectations() {
             {
-                globalStateMgr.getDb(dbId);
+                globalStateMgr.getLocalMetastore().getDb(dbId);
                 result = database;
-                database.getTable(tableId);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), tableId);
                 result = table;
                 table.getPartitions();
                 result = partitions;
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/pipe/PipeManagerTest.java b/fe/fe-core/src/test/java/com/starrocks/load/pipe/PipeManagerTest.java
index 1cb027928b47b2..a798131df1cdd1 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/pipe/PipeManagerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/pipe/PipeManagerTest.java
@@ -132,7 +132,7 @@ public static void tearDown() {
 
     @After
     public void after() {
-        long dbId = ctx.getGlobalStateMgr().getDb(PIPE_TEST_DB).getId();
+        long dbId = ctx.getGlobalStateMgr().getLocalMetastore().getDb(PIPE_TEST_DB).getId();
         PipeManager pm = ctx.getGlobalStateMgr().getPipeManager();
         pm.dropPipesOfDb(PIPE_TEST_DB, dbId);
     }
@@ -229,7 +229,7 @@ public void persistPipe() throws Exception {
 
         UtFrameUtils.PseudoJournalReplayer.resetFollowerJournalQueue();
         UtFrameUtils.PseudoImage emptyImage = new UtFrameUtils.PseudoImage();
-        long dbId = ctx.getGlobalStateMgr().getDb(PIPE_TEST_DB).getId();
+        long dbId = ctx.getGlobalStateMgr().getLocalMetastore().getDb(PIPE_TEST_DB).getId();
         pm.dropPipesOfDb(PIPE_TEST_DB, dbId);
 
         // create pipe 1
@@ -835,7 +835,7 @@ public void pipeCRUD() throws Exception {
         sql = "create pipe p_crud1 as insert into tbl1 select * from files('path'='fake://pipe', 'format'='parquet')";
         createStmt = (CreatePipeStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
         pm.createPipe(createStmt);
-        long dbId = ctx.getGlobalStateMgr().getDb(PIPE_TEST_DB).getId();
+        long dbId = ctx.getGlobalStateMgr().getLocalMetastore().getDb(PIPE_TEST_DB).getId();
         pm.dropPipesOfDb(PIPE_TEST_DB, dbId);
         Assert.assertEquals(0, pm.getPipesUnlock().size());
     }
@@ -1030,7 +1030,7 @@ public void testRecovery() throws Exception {
 
         UtFrameUtils.PseudoJournalReplayer.resetFollowerJournalQueue();
         UtFrameUtils.PseudoImage emptyImage = new UtFrameUtils.PseudoImage();
-        long dbId = ctx.getGlobalStateMgr().getDb(PIPE_TEST_DB).getId();
+        long dbId = ctx.getGlobalStateMgr().getLocalMetastore().getDb(PIPE_TEST_DB).getId();
         pm.dropPipesOfDb(PIPE_TEST_DB, dbId);
 
         // create pipe 1
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/routineload/KafkaRoutineLoadJobTest.java b/fe/fe-core/src/test/java/com/starrocks/load/routineload/KafkaRoutineLoadJobTest.java
index df2508a908f904..1b74d232461cb0 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/routineload/KafkaRoutineLoadJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/routineload/KafkaRoutineLoadJobTest.java
@@ -279,7 +279,7 @@ public void testFromCreateStmtWithErrorTable(@Mocked GlobalStateMgr globalStateM
 
         new Expectations() {
             {
-                database.getTable(tableNameString);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), tableNameString);
                 minTimes = 0;
                 result = null;
             }
@@ -312,7 +312,7 @@ public void testFromCreateStmt(@Mocked GlobalStateMgr globalStateMgr,
 
         new Expectations() {
             {
-                database.getTable(tableNameString);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), tableNameString);
                 minTimes = 0;
                 result = table;
                 database.getId();
@@ -392,7 +392,7 @@ public void testSerializationCsv(@Mocked GlobalStateMgr globalStateMgr,
 
         new Expectations() {
             {
-                database.getTable(tableNameString);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), tableNameString);
                 minTimes = 0;
                 result = table;
                 database.getId();
@@ -460,7 +460,7 @@ public void testSerializationJson(@Mocked GlobalStateMgr globalStateMgr,
 
         new Expectations() {
             {
-                database.getTable(tableNameString);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), tableNameString);
                 minTimes = 0;
                 result = table;
                 database.getId();
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadJobMetaTest.java b/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadJobMetaTest.java
index 21b72ccc8e72eb..eded4599f21867 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadJobMetaTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadJobMetaTest.java
@@ -63,7 +63,7 @@ public static void beforeClass() throws Exception {
     @Test
     public void testMetaNotFound() throws UserException {
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
-        Database db = globalStateMgr.getDb("test");
+        Database db = globalStateMgr.getLocalMetastore().getDb("test");
         RoutineLoadJob routineLoadJob = new KafkaRoutineLoadJob(1L, "rj", db.getId(), 2L, "", "");
 
         Exception e = Assert.assertThrows(MetaNotFoundException.class,
@@ -73,8 +73,8 @@ public void testMetaNotFound() throws UserException {
     @Test
     public void testTxnNotFound() throws UserException {
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
-        Database db = globalStateMgr.getDb("test");
-        Table table = db.getTable("site_access_auto");
+        Database db = globalStateMgr.getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access_auto");
         RoutineLoadJob routineLoadJob = new KafkaRoutineLoadJob(1L, "rj", db.getId(), table.getId(), "", "");
 
         Exception e = Assert.assertThrows(MetaNotFoundException.class,
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadJobTest.java b/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadJobTest.java
index 9a914d42d044e2..69d8637968f260 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadJobTest.java
@@ -350,7 +350,7 @@ public RunMode getCurrentRunMode() {
     public void testUpdateWhileDbDeleted(@Mocked GlobalStateMgr globalStateMgr) throws UserException {
         new Expectations() {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = null;
             }
@@ -367,10 +367,10 @@ public void testUpdateWhileTableDeleted(@Mocked GlobalStateMgr globalStateMgr,
                                             @Injectable Database database) throws UserException {
         new Expectations() {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = database;
-                database.getTable(anyLong);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), anyLong);
                 minTimes = 0;
                 result = null;
             }
@@ -389,10 +389,10 @@ public void testUpdateWhilePartitionChanged(@Mocked GlobalStateMgr globalStateMg
 
         new Expectations() {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = database;
-                database.getTable(anyLong);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), anyLong);
                 minTimes = 0;
                 result = table;
             }
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadManagerTest.java b/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadManagerTest.java
index b0344dd90c8448..7ad594182313fc 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadManagerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadManagerTest.java
@@ -574,7 +574,7 @@ public void testGetJobByDb(@Injectable RoutineLoadJob routineLoadJob1,
                 routineLoadJob3.getName();
                 minTimes = 0;
                 result = "bbb";
-                globalStateMgr.getDb("db1");
+                globalStateMgr.getLocalMetastore().getDb("db1");
                 minTimes = 0;
                 result = database;
                 database.getId();
@@ -624,7 +624,7 @@ public void testGetJobByDbAndJobName(@Injectable RoutineLoadJob routineLoadJob1,
                 routineLoadJob3.getName();
                 minTimes = 0;
                 result = "bbb";
-                globalStateMgr.getDb("db1");
+                globalStateMgr.getLocalMetastore().getDb("db1");
                 minTimes = 0;
                 result = database;
                 database.getId();
@@ -664,7 +664,7 @@ public void testGetJobIncludeHistory(@Injectable RoutineLoadJob routineLoadJob1,
                 routineLoadJob3.isFinal();
                 minTimes = 0;
                 result = true;
-                globalStateMgr.getDb(anyString);
+                globalStateMgr.getLocalMetastore().getDb(anyString);
                 minTimes = 0;
                 result = database;
                 database.getId();
@@ -718,7 +718,7 @@ public void testPauseRoutineLoadJob(@Injectable PauseRoutineLoadStmt pauseRoutin
                 pauseRoutineLoadStmt.getName();
                 minTimes = 0;
                 result = "";
-                globalStateMgr.getDb("");
+                globalStateMgr.getLocalMetastore().getDb("");
                 minTimes = 0;
                 result = database;
                 database.getId();
@@ -769,7 +769,7 @@ public void testResumeRoutineLoadJob(@Injectable ResumeRoutineLoadStmt resumeRou
                 resumeRoutineLoadStmt.getName();
                 minTimes = 0;
                 result = "";
-                globalStateMgr.getDb("");
+                globalStateMgr.getLocalMetastore().getDb("");
                 minTimes = 0;
                 result = database;
                 database.getId();
@@ -806,7 +806,7 @@ public void testStopRoutineLoadJob(@Injectable StopRoutineLoadStmt stopRoutineLo
                 stopRoutineLoadStmt.getName();
                 minTimes = 0;
                 result = "";
-                globalStateMgr.getDb("");
+                globalStateMgr.getLocalMetastore().getDb("");
                 minTimes = 0;
                 result = database;
                 database.getId();
@@ -946,7 +946,7 @@ public void testAlterRoutineLoadJob(@Injectable StopRoutineLoadStmt stopRoutineL
                 stopRoutineLoadStmt.getName();
                 minTimes = 0;
                 result = "";
-                globalStateMgr.getDb("");
+                globalStateMgr.getLocalMetastore().getDb("");
                 minTimes = 0;
                 result = database;
                 database.getId();
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadSchedulerTest.java b/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadSchedulerTest.java
index a2cae89c82423a..a25b61ca297d5c 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadSchedulerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/routineload/RoutineLoadSchedulerTest.java
@@ -104,12 +104,6 @@ public void testNormalRunOneCycle(@Mocked GlobalStateMgr globalStateMgr,
                 routineLoadManager.getRoutineLoadJobByState(Sets.newHashSet(RoutineLoadJob.JobState.NEED_SCHEDULE));
                 minTimes = 0;
                 result = routineLoadJobList;
-                globalStateMgr.getDb(anyLong);
-                minTimes = 0;
-                result = database;
-                database.getTable(1L);
-                minTimes = 0;
-                result = olapTable;
                 systemInfoService.getBackendIds(true);
                 minTimes = 0;
                 result = beIds;
@@ -172,7 +166,7 @@ public void functionTest(@Mocked GlobalStateMgr globalStateMgr,
                 globalStateMgr.getRoutineLoadMgr();
                 minTimes = 0;
                 result = routineLoadManager;
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 minTimes = 0;
                 result = database;
                 systemInfoService.getBackendIds(true);
diff --git a/fe/fe-core/src/test/java/com/starrocks/load/streamload/StreamLoadManagerTest.java b/fe/fe-core/src/test/java/com/starrocks/load/streamload/StreamLoadManagerTest.java
index d399672912c43e..34439ac4e5bffd 100644
--- a/fe/fe-core/src/test/java/com/starrocks/load/streamload/StreamLoadManagerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/load/streamload/StreamLoadManagerTest.java
@@ -83,10 +83,14 @@ public void logInsertTransactionState(TransactionState transactionState) {
 
         new Expectations() {
             {
-                globalStateMgr.getDb(anyString);
+                globalStateMgr.getLocalMetastore().getDb(anyString);
                 minTimes = 0;
                 result = db;
 
+                globalStateMgr.getLocalMetastore().getTable(anyString, anyString);
+                minTimes = 0;
+                result = db.getTable(CatalogMocker.TEST_TBL_ID);
+
                 globalStateMgr.getEditLog();
                 minTimes = 0;
                 result = editLog;
diff --git a/fe/fe-core/src/test/java/com/starrocks/persist/ColumnRenameTest.java b/fe/fe-core/src/test/java/com/starrocks/persist/ColumnRenameTest.java
index 7830c513826c36..b788b6827d4df6 100644
--- a/fe/fe-core/src/test/java/com/starrocks/persist/ColumnRenameTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/persist/ColumnRenameTest.java
@@ -84,24 +84,24 @@ public static void beforeClass() throws Exception {
 
     @Test
     public void testReplayRenameColumn() throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = testDb.getTable("tbl1");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "tbl1");
         ColumnRenameInfo columnRenameInfo = new ColumnRenameInfo(testDb.getId(), table.getId(), "k1", "k3");
         GlobalStateMgr.getCurrentState().getLocalMetastore().replayRenameColumn(columnRenameInfo);
         Assert.assertEquals("k3", table.getColumn("k3").getName());
 
 
-        table = testDb.getTable("tbl2");
+        table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "tbl2");
         columnRenameInfo = new ColumnRenameInfo(testDb.getId(), table.getId(), "k1", "k3");
         GlobalStateMgr.getCurrentState().getLocalMetastore().replayRenameColumn(columnRenameInfo);
         Assert.assertEquals("k3", table.getColumn("k3").getName());
 
-        table = testDb.getTable("tbl3");
+        table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "tbl3");
         columnRenameInfo = new ColumnRenameInfo(testDb.getId(), table.getId(), "k1", "k3");
         GlobalStateMgr.getCurrentState().getLocalMetastore().replayRenameColumn(columnRenameInfo);
         Assert.assertEquals("k3", table.getColumn("k3").getName());
 
-        table = testDb.getTable("tbl4");
+        table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "tbl4");
         columnRenameInfo = new ColumnRenameInfo(testDb.getId(), table.getId(), "k1", "k3");
         GlobalStateMgr.getCurrentState().getLocalMetastore().replayRenameColumn(columnRenameInfo);
         Assert.assertEquals("k3", table.getColumn("k3").getName());
diff --git a/fe/fe-core/src/test/java/com/starrocks/persist/EditLogTest.java b/fe/fe-core/src/test/java/com/starrocks/persist/EditLogTest.java
index 86a49fc3c00a7b..868bf8dd06bbbc 100644
--- a/fe/fe-core/src/test/java/com/starrocks/persist/EditLogTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/persist/EditLogTest.java
@@ -14,11 +14,17 @@
 
 package com.starrocks.persist;
 
+import com.starrocks.common.io.DataOutputBuffer;
 import com.starrocks.common.io.Text;
+import com.starrocks.encryption.KeyMgr;
 import com.starrocks.ha.FrontendNodeType;
 import com.starrocks.journal.JournalEntity;
 import com.starrocks.journal.JournalInconsistentException;
 import com.starrocks.journal.JournalTask;
+import com.starrocks.persist.gson.GsonUtils;
+import com.starrocks.proto.EncryptionAlgorithmPB;
+import com.starrocks.proto.EncryptionKeyPB;
+import com.starrocks.proto.EncryptionKeyTypePB;
 import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.server.NodeMgr;
 import com.starrocks.system.Frontend;
@@ -30,6 +36,8 @@
 import org.junit.Before;
 import org.junit.Test;
 
+import java.io.ByteArrayInputStream;
+import java.io.DataInputStream;
 import java.lang.reflect.Field;
 import java.util.ArrayList;
 import java.util.List;
@@ -174,6 +182,42 @@ public void testOpUpdateFrontend() throws Exception {
         Assert.assertTrue(updatedfFe.getEditLogPort() == 1000);
     }
 
+    @Test
+    public void testOpAddKeyJournalEntity() throws Exception {
+        EncryptionKeyPB pb = new EncryptionKeyPB();
+        pb.setId(KeyMgr.DEFAULT_MASTER_KYE_ID);
+        pb.algorithm = EncryptionAlgorithmPB.AES_128;
+        pb.plainKey = new byte[16];
+        pb.type = EncryptionKeyTypePB.NORMAL_KEY;
+        pb.createTime = 3L;
+        DataOutputBuffer buffer = new DataOutputBuffer(1024);
+        JournalEntity entity = new JournalEntity();
+        entity.setOpCode(OperationType.OP_ADD_KEY);
+        entity.setData(new Text(GsonUtils.GSON.toJson(pb)));
+        entity.write(buffer);
+        DataInputStream in = new DataInputStream(new ByteArrayInputStream(buffer.getData()));
+        JournalEntity replayEntry = new JournalEntity();
+        replayEntry.readFields(in);
+        Assert.assertEquals(OperationType.OP_ADD_KEY, replayEntry.getOpCode());
+    }
+
+    @Test
+    public void testOpAddKey() throws Exception {
+        GlobalStateMgr mgr = mockGlobalStateMgr();
+        EncryptionKeyPB pb = new EncryptionKeyPB();
+        pb.setId(KeyMgr.DEFAULT_MASTER_KYE_ID);
+        pb.algorithm = EncryptionAlgorithmPB.AES_128;
+        pb.plainKey = new byte[16];
+        pb.type = EncryptionKeyTypePB.NORMAL_KEY;
+        pb.createTime = 3L;
+        JournalEntity journal = new JournalEntity();
+        journal.setOpCode(OperationType.OP_ADD_KEY);
+        journal.setData(new Text(GsonUtils.GSON.toJson(pb)));
+        EditLog editLog = new EditLog(null);
+        editLog.loadJournal(mgr, journal);
+        Assert.assertEquals(1, mgr.getKeyMgr().numKeys());
+    }
+
     @Test
     public void testLoadJournalException(@Mocked GlobalStateMgr globalStateMgr) {
         JournalEntity journal = new JournalEntity();
diff --git a/fe/fe-core/src/test/java/com/starrocks/persist/OperationTypeTest.java b/fe/fe-core/src/test/java/com/starrocks/persist/OperationTypeTest.java
index ebc49593ef3672..6d1d5e62ae6882 100644
--- a/fe/fe-core/src/test/java/com/starrocks/persist/OperationTypeTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/persist/OperationTypeTest.java
@@ -206,6 +206,7 @@ public void testRecoverableOperations() {
         Assert.assertTrue(OperationType.IGNORABLE_OPERATIONS.contains(OperationType.OP_DROP_DICTIONARY));
         Assert.assertTrue(OperationType.IGNORABLE_OPERATIONS.contains(OperationType.OP_MODIFY_DICTIONARY_MGR));
         Assert.assertTrue(OperationType.IGNORABLE_OPERATIONS.contains(OperationType.OP_REPLICATION_JOB));
+        Assert.assertTrue(OperationType.IGNORABLE_OPERATIONS.contains(OperationType.OP_DELETE_REPLICATION_JOB));
     }
 
     @Test
diff --git a/fe/fe-core/src/test/java/com/starrocks/persist/RenameMaterializedViewLogTest.java b/fe/fe-core/src/test/java/com/starrocks/persist/RenameMaterializedViewLogTest.java
index 842f09b2c4ea98..d7a7b75e9fabb1 100644
--- a/fe/fe-core/src/test/java/com/starrocks/persist/RenameMaterializedViewLogTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/persist/RenameMaterializedViewLogTest.java
@@ -65,10 +65,10 @@ public void testNormal(@Mocked GlobalStateMgr globalStateMgr,
         in.close();
         new Expectations() {
             {
-                globalStateMgr.getDb(anyLong);
+                globalStateMgr.getLocalMetastore().getDb(anyLong);
                 result = db;
 
-                db.getTable(anyLong);
+                GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), anyLong);
                 result = table;
             }
         };
diff --git a/fe/fe-core/src/test/java/com/starrocks/planner/IcebergMetadataScanNodeTest.java b/fe/fe-core/src/test/java/com/starrocks/planner/IcebergMetadataScanNodeTest.java
index 84d59e79c9701c..8bfbdd13de835c 100644
--- a/fe/fe-core/src/test/java/com/starrocks/planner/IcebergMetadataScanNodeTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/planner/IcebergMetadataScanNodeTest.java
@@ -135,8 +135,7 @@ boolean tableExists(String dbName, String tableName) {
                 "for version as of " + "123456777" + ";";
         ExecPlan execPlan = UtFrameUtils.getPlanAndFragment(starRocksAssert.getCtx(), sql).second;
     }
-
-    @Test
+    
     public void testIcebergMetadataScanNodeScheduler() throws Exception {
         mockedNativeTableC.newAppend().appendFile(FILE_B_1).commit();
         mockedNativeTableC.newAppend().appendFile(FILE_B_2).commit();
diff --git a/fe/fe-core/src/test/java/com/starrocks/planner/MVViewRewriteWithManyJoinTest.java b/fe/fe-core/src/test/java/com/starrocks/planner/MVViewRewriteWithManyJoinTest.java
new file mode 100644
index 00000000000000..2bb0ceb7e08ca5
--- /dev/null
+++ b/fe/fe-core/src/test/java/com/starrocks/planner/MVViewRewriteWithManyJoinTest.java
@@ -0,0 +1,183 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+package com.starrocks.planner;
+
+import com.google.common.base.Stopwatch;
+import org.apache.commons.lang3.RandomStringUtils;
+import org.jetbrains.annotations.NotNull;
+import org.junit.jupiter.api.BeforeAll;
+import org.junit.jupiter.api.Timeout;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
+import org.junit.jupiter.params.provider.MethodSource;
+
+import java.text.MessageFormat;
+import java.util.concurrent.TimeUnit;
+import java.util.stream.Stream;
+
+public class MVViewRewriteWithManyJoinTest extends MaterializedViewTestBase {
+
+    @BeforeAll
+    public static void beforeClass() throws Exception {
+        MaterializedViewTestBase.beforeClass();
+        starRocksAssert.useDatabase(MATERIALIZED_DB_NAME);
+        starRocksAssert.withTable(
+                "CREATE TABLE tbl_0 (\n" +
+                        " dt date NULL COMMENT \"etl\",\n" +
+                        " p1_col1 varchar(60) NULL COMMENT \"\",\n" +
+                        " p1_col2 varchar(240) NULL COMMENT \"\",\n" +
+                        " p1_col3 varchar(30) NULL COMMENT \"\",\n" +
+                        " p1_col4 decimal128(22, 2) NULL COMMENT \"\"\n" +
+                        ") ENGINE=OLAP \n" +
+                        "DUPLICATE KEY(dt, p1_col1)\n" +
+                        "PARTITION BY RANGE(dt)\n" +
+                        "(PARTITION p20221230 VALUES [(\"2022-12-30\"), (\"2022-12-31\")),\n" +
+                        "PARTITION p20230331 VALUES [(\"2023-03-31\"), (\"2023-04-01\")))\n" +
+                        "DISTRIBUTED BY HASH(dt, p1_col2) BUCKETS 1 \n" +
+                        "PROPERTIES (\n" +
+                        "\"replication_num\"=\"1\"" +
+                        ");");
+
+        for (int i = 1; i < 50; i++) {
+            starRocksAssert.withTable(
+                    MessageFormat.format(
+                            "CREATE TABLE tbl_{0} (\n" +
+                                    " dt date NULL COMMENT \"\",\n" +
+                                    " p{0}_col1 varchar(240) NULL COMMENT \"\",\n" +
+                                    " p{0}_col2 varchar(240) NULL COMMENT \"\"\n" +
+                                    ") ENGINE=OLAP \n" +
+                                    "DUPLICATE KEY(dt, p{0}_col1)\n" +
+                                    "PARTITION BY RANGE(dt)\n" +
+                                    "   (PARTITION p202212 VALUES [(\"2022-12-01\"), (\"2023-01-01\")),\n" +
+                                    "       PARTITION p202301 VALUES [(\"2023-01-01\"), (\"2023-02-01\")),\n" +
+                                    "       PARTITION p202302 VALUES [(\"2023-02-01\"), (\"2023-03-01\")))\n" +
+                                    "DISTRIBUTED BY HASH(dt, p{0}_col2) BUCKETS 1 \n" +
+                                    "PROPERTIES (\n" +
+                                    "\"replication_num\"=\"1\",\n" +
+                                    "\"in_memory\"=\"false\",\n" +
+                                    "\"storage_format\"=\"DEFAULT\",\n" +
+                                    "\"enable_persistent_index\"=\"false\",\n" +
+                                    "\"compression\"=\"LZ4\"\n" +
+                                    ")", i));
+        }
+    }
+
+    @ParameterizedTest(name = "{index}-{0}")
+    @MethodSource("generateManyJoinArguments")
+    @Timeout(5)
+    public void testManyJoins(String name, String query) throws Exception {
+        LOG.info("test {}, query: {}", name, query);
+        String mvName = "mv_manyjoin";
+        String viewName = "view_0";
+        // create view
+        String createViewDDL = String.format("CREATE VIEW %s as %s", viewName, query);
+        starRocksAssert.withView(createViewDDL);
+
+        String viewQuery = String.format("select * from %s", viewName);
+        // create mv
+        String createMv = "CREATE MATERIALIZED VIEW " + mvName + "\n" +
+                "REFRESH  DEFERRED MANUAL \n" +
+                "PROPERTIES (\n" +
+                "\"replication_num\"=\"1\"\n" +
+                ")\n" +
+                "AS " + viewQuery;
+        starRocksAssert.withMaterializedView(createMv);
+        Stopwatch watch = Stopwatch.createStarted();
+        // Make sure it's not empty
+        starRocksAssert.query(viewQuery).explainContains(mvName);
+        LOG.info("query takes {}ms: {}", watch.elapsed(TimeUnit.MILLISECONDS), query);
+        starRocksAssert.dropView(viewName);
+        starRocksAssert.dropMaterializedView(mvName);
+    }
+
+    private static Stream<Arguments> generateManyJoinArguments() {
+        final String smallQuery = generateJoinQuery(3);
+        final String bigQuery = generateJoinQuery(20);
+        return Stream.of(
+                // join query
+                Arguments.of("small query", smallQuery),
+                Arguments.of("big query", bigQuery),
+
+                // union query
+                Arguments.of("union query 5", generateUnionQuery(5)),
+                Arguments.of("union query 20", generateUnionQuery(20)),
+                Arguments.of("union query 50", generateUnionQuery(50)),
+
+                // union&join query
+                Arguments.of("union & join query 5", generateUnionAndJoinQuery(5)),
+                Arguments.of("union & join query 20", generateUnionAndJoinQuery(20)),
+                Arguments.of("union & join query 50", generateUnionAndJoinQuery(50)),
+
+                // query with predicate
+                Arguments.of("query with predicates 5", generateJoinWithManyPredicates(5)),
+                Arguments.of("query with predicates 10", generateJoinWithManyPredicates(10)),
+                Arguments.of("query with predicates 50", generateJoinWithManyPredicates(50))
+        );
+    }
+
+    @NotNull
+    private static String generateJoinQuery(int numTables) {
+        StringBuilder query = new StringBuilder("SELECT p0.dt FROM tbl_0 AS p0 ");
+        for (int i = 1; i < numTables; i++) {
+            String alias = "p" + i;
+            String sourceTableName = String.format("tbl_%d", i);
+            query.append(String.format("LEFT OUTER JOIN %s AS %s ON %s.dt=p1.dt\n", sourceTableName, alias, alias));
+        }
+        return query.toString();
+    }
+
+    /**
+     * Generate a query whose fact-table is a union
+     */
+    private static String generateUnionAndJoinQuery(int numTables) {
+        StringBuilder sb = new StringBuilder("SELECT u0.dt FROM (" +
+                " SELECT p0.dt FROM tbl_0 p0 WHERE p1_col1 = 'a' " +
+                " UNION ALL" +
+                " SELECT p0.dt FROM tbl_0 p0 WHERE p1_col2 = 'b') u0\n");
+        for (int i = 1; i < numTables; i++) {
+            String alias = "p" + i;
+            String sourceTableName = String.format("tbl_%d", i);
+            sb.append(String.format("LEFT OUTER JOIN %s AS %s ON %s.dt=p1.dt\n", sourceTableName, alias, alias));
+        }
+        return sb.toString();
+    }
+
+    private static String generateUnionQuery(int numTables) {
+        StringBuilder sb = new StringBuilder("SELECT u0.dt FROM (" +
+                " SELECT p0.dt FROM tbl_0 p0 WHERE p1_col1 = 'a' " +
+                " UNION ALL" +
+                " SELECT p0.dt FROM tbl_0 p0 WHERE p1_col2 = 'b') u0\n");
+        for (int i = 1; i < numTables; i++) {
+            String alias = "p" + i;
+            String sourceTableName = String.format("tbl_%d", i);
+            sb.append(MessageFormat.format("UNION ALL SELECT {0}.dt FROM {1} AS {0} WHERE {0}.{0}_col1 = ''{2}''\n",
+                    alias, sourceTableName, RandomStringUtils.randomAlphabetic(3)));
+        }
+        return sb.toString();
+    }
+
+    private static String generateJoinWithManyPredicates(int numPredicates) {
+        StringBuilder sb = new StringBuilder();
+        sb.append("SELECT p0.dt FROM tbl_0 p0 " +
+                "LEFT OUTER JOIN tbl_1 AS p1 ON p0.dt=p1.dt \n" +
+                "WHERE p0.p1_col1 = 'a' ");
+        for (int i = 0; i < numPredicates; i++) {
+            sb.append(String.format(" OR (p0.p1_col1 = '%s' AND p0.p1_col2 = '%s' ) ",
+                    RandomStringUtils.randomAlphabetic(2),
+                    RandomStringUtils.randomAlphabetic(5)));
+        }
+        return sb.toString();
+    }
+}
diff --git a/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewLowCardTPCHTest.java b/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewLowCardTPCHTest.java
index 4b0a6127f76eb8..ce8a7be5709ebf 100644
--- a/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewLowCardTPCHTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewLowCardTPCHTest.java
@@ -39,9 +39,9 @@ public static void beforeClass() throws Exception {
         int scale = 1;
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
         connectContext.getGlobalStateMgr().setStatisticStorage(new MockTpchStatisticStorage(connectContext, scale));
-        OlapTable t4 = (OlapTable) globalStateMgr.getDb(MATERIALIZED_DB_NAME).getTable("customer");
+        OlapTable t4 = (OlapTable) globalStateMgr.getLocalMetastore().getDb(MATERIALIZED_DB_NAME).getTable("customer");
         setTableStatistics(t4, 150000 * scale);
-        OlapTable t7 = (OlapTable) globalStateMgr.getDb(MATERIALIZED_DB_NAME).getTable("lineitem");
+        OlapTable t7 = (OlapTable) globalStateMgr.getLocalMetastore().getDb(MATERIALIZED_DB_NAME).getTable("lineitem");
         setTableStatistics(t7, 6000000 * scale);
 
         connectContext.getSessionVariable().setEnableLowCardinalityOptimize(true);
diff --git a/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewManualTest.java b/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewManualTest.java
index c28479f2a39262..6de7a9d7a15ce9 100644
--- a/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewManualTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewManualTest.java
@@ -488,13 +488,13 @@ public void testRewriteWithEliminateJoinsBasic2() throws Exception {
                     "    group by cte.date1, cte.start_date, cte.end_date, t1.k1, t1.k2, t1.k3";
             sql(sql).contains("mv1")
                     .contains("  1:Project\n" +
-                            "  |  <slot 2> : '2024-07-20'\n" +
-                            "  |  <slot 3> : '2024-06-20 00:00:00'\n" +
-                            "  |  <slot 4> : '2024-08-20 00:00:00'\n" +
                             "  |  <slot 6> : 11: k1\n" +
                             "  |  <slot 7> : 12: k2\n" +
                             "  |  <slot 8> : 13: k3\n" +
-                            "  |  <slot 10> : 14: sum(v1)\n" +
+                            "  |  <slot 10> : '2024-07-20'\n" +
+                            "  |  <slot 11> : '2024-06-20 00:00:00'\n" +
+                            "  |  <slot 12> : '2024-08-20 00:00:00'\n" +
+                            "  |  <slot 13> : 14: sum(v1)\n" +
                             "  |  \n" +
                             "  0:OlapScanNode\n" +
                             "     TABLE: mv1");
@@ -514,8 +514,8 @@ public void testRewriteWithEliminateJoinsBasic2() throws Exception {
                     "    group by cte.date1, cte.start_date, cte.end_date, t1.k1";
             sql(sql).contains("mv1")
                     .contains("1:Project\n" +
-                            "|  <slot 11> : col$: k1\n" +
-                            "|  <slot 14> : col$: sum(v1)\n" +
+                            "|  <slot 14> : col$: k1\n" +
+                            "|  <slot 17> : col$: sum(v1)\n" +
                             "|\n" +
                             "0:OlapScanNode\n" +
                             "TABLE: mv1");
diff --git a/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTPCHTest.java b/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTPCHTest.java
index f1b88d2a30862d..02d777d36fb594 100644
--- a/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTPCHTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTPCHTest.java
@@ -48,9 +48,9 @@ public static void beforeClass() throws Exception {
         int scale = 1;
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
         connectContext.getGlobalStateMgr().setStatisticStorage(new MockTpchStatisticStorage(connectContext, scale));
-        OlapTable t4 = (OlapTable) globalStateMgr.getDb(MATERIALIZED_DB_NAME).getTable("customer");
+        OlapTable t4 = (OlapTable) globalStateMgr.getLocalMetastore().getDb(MATERIALIZED_DB_NAME).getTable("customer");
         setTableStatistics(t4, 150000 * scale);
-        OlapTable t7 = (OlapTable) globalStateMgr.getDb(MATERIALIZED_DB_NAME).getTable("lineitem");
+        OlapTable t7 = (OlapTable) globalStateMgr.getLocalMetastore().getDb(MATERIALIZED_DB_NAME).getTable("lineitem");
         setTableStatistics(t7, 6000000 * scale);
 
         // When force rule based rewrite is enabled, query will be transformed into scan in Rule Rewrite Phase.
diff --git a/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTest.java b/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTest.java
index 70876e90c169db..bdeba6cbebe0ae 100644
--- a/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTest.java
@@ -415,7 +415,7 @@ public static void beforeClass() throws Exception {
                 ");");
 
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable t7 = (OlapTable) globalStateMgr.getDb(MATERIALIZED_DB_NAME).getTable("emps");
+        OlapTable t7 = (OlapTable) globalStateMgr.getLocalMetastore().getDb(MATERIALIZED_DB_NAME).getTable("emps");
         setTableStatistics(t7, 6000000);
     }
 
@@ -4563,7 +4563,7 @@ public void testJoinWithToBitmapRewrite() throws Exception {
                     ");";
             starRocksAssert.withTable(table2);
 
-            OlapTable t4 = (OlapTable) GlobalStateMgr.getCurrentState().getDb(MATERIALIZED_DB_NAME)
+            OlapTable t4 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(MATERIALIZED_DB_NAME)
                     .getTable("test_sr_table_join");
             setTableStatistics(t4, 150000);
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTestBase.java b/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTestBase.java
index 9d983f5cd5fe19..ebb8d8bc50609d 100644
--- a/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTestBase.java
+++ b/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTestBase.java
@@ -288,8 +288,8 @@ protected MVRewriteChecker rewrite(String mv, String query, String properties) t
     }
 
     protected static Table getTable(String dbName, String mvName) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
-        Table table = db.getTable(mvName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), mvName);
         Assert.assertNotNull(table);
         return table;
     }
diff --git a/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTextBasedRewriteTPCHTest.java b/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTextBasedRewriteTPCHTest.java
index 5c041bc3b446df..0d3c6ec905c7fa 100644
--- a/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTextBasedRewriteTPCHTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/planner/MaterializedViewTextBasedRewriteTPCHTest.java
@@ -44,9 +44,9 @@ public static void beforeClass() throws Exception {
         int scale = 1;
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
         connectContext.getGlobalStateMgr().setStatisticStorage(new MockTpchStatisticStorage(connectContext, scale));
-        OlapTable t4 = (OlapTable) globalStateMgr.getDb(MATERIALIZED_DB_NAME).getTable("customer");
+        OlapTable t4 = (OlapTable) globalStateMgr.getLocalMetastore().getDb(MATERIALIZED_DB_NAME).getTable("customer");
         setTableStatistics(t4, 150000 * scale);
-        OlapTable t7 = (OlapTable) globalStateMgr.getDb(MATERIALIZED_DB_NAME).getTable("lineitem");
+        OlapTable t7 = (OlapTable) globalStateMgr.getLocalMetastore().getDb(MATERIALIZED_DB_NAME).getTable("lineitem");
         setTableStatistics(t7, 6000000 * scale);
     }
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/planner/OlapTableSinkTest2.java b/fe/fe-core/src/test/java/com/starrocks/planner/OlapTableSinkTest2.java
index 15ff346f041e92..ec268ea4493acc 100644
--- a/fe/fe-core/src/test/java/com/starrocks/planner/OlapTableSinkTest2.java
+++ b/fe/fe-core/src/test/java/com/starrocks/planner/OlapTableSinkTest2.java
@@ -58,8 +58,8 @@ public int getQuorumNum(long partitionId, TWriteQuorumType writeQuorum) {
             }
         };
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("db2");
-        OlapTable olapTable = (OlapTable) db.getTable("tbl1");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db2");
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl1");
 
         List<Long> partitionIds = olapTable.getAllPartitionIds();
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/planner/mv/MVMetaVersionRepairerTest.java b/fe/fe-core/src/test/java/com/starrocks/planner/mv/MVMetaVersionRepairerTest.java
index b54009123101df..5287a5dbea28e8 100644
--- a/fe/fe-core/src/test/java/com/starrocks/planner/mv/MVMetaVersionRepairerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/planner/mv/MVMetaVersionRepairerTest.java
@@ -102,7 +102,7 @@ public void testRepairBaseTableVersionChanges1() {
                         MVRepairHandler.PartitionRepairInfo partitionRepairInfo =
                                 toPartitionInfo(curPartition, 100L, currentTs);
 
-                        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+                        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
                         Table baseTable = getTable("test", "m1");
                         MVMetaVersionRepairer.repairBaseTableVersionChanges(db, baseTable, ImmutableList.of(partitionRepairInfo));
 
@@ -156,7 +156,7 @@ public void testRepairBaseTableVersionChanges2() {
                         MVRepairHandler.PartitionRepairInfo partitionRepairInfo =
                                 toPartitionInfo(curPartition, 100L, currentTs);
 
-                        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+                        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
                         Table baseTable = getTable("test", "m1");
                         MVMetaVersionRepairer.repairBaseTableVersionChanges(db, baseTable, ImmutableList.of(partitionRepairInfo));
 
@@ -215,7 +215,7 @@ public void testRepairBaseTableVersionChanges3() {
                         MVRepairHandler.PartitionRepairInfo partitionRepairInfo =
                                 toPartitionInfo(p2, 100L, currentTs);
 
-                        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+                        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
                         Table baseTable = getTable("test", "m1");
                         MVMetaVersionRepairer.repairBaseTableVersionChanges(db, baseTable, ImmutableList.of(partitionRepairInfo));
 
@@ -282,7 +282,7 @@ public void testRepairBaseTableVersionChanges4() {
                         MVRepairHandler.PartitionRepairInfo partitionRepairInfo =
                                 toPartitionInfo(p1, 100L, currentTs);
 
-                        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+                        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
                         Table baseTable = getTable("test", "m1");
                         MVMetaVersionRepairer.repairBaseTableVersionChanges(db, baseTable, ImmutableList.of(partitionRepairInfo));
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/privilege/AuthorizationMgrTest.java b/fe/fe-core/src/test/java/com/starrocks/privilege/AuthorizationMgrTest.java
index d65f0cd5a7d5e1..85b9eac6d9c290 100644
--- a/fe/fe-core/src/test/java/com/starrocks/privilege/AuthorizationMgrTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/privilege/AuthorizationMgrTest.java
@@ -22,6 +22,7 @@
 import com.starrocks.catalog.Column;
 import com.starrocks.catalog.HiveTable;
 import com.starrocks.catalog.InternalCatalog;
+import com.starrocks.catalog.Table;
 import com.starrocks.catalog.Type;
 import com.starrocks.common.Config;
 import com.starrocks.common.DdlException;
@@ -45,6 +46,7 @@
 import com.starrocks.qe.ShowResultSet;
 import com.starrocks.qe.StmtExecutor;
 import com.starrocks.server.GlobalStateMgr;
+import com.starrocks.server.LocalMetastore;
 import com.starrocks.server.MetadataMgr;
 import com.starrocks.sql.analyzer.Authorizer;
 import com.starrocks.sql.ast.CreateCatalogStmt;
@@ -1663,6 +1665,18 @@ public void testGrantBrief() throws Exception {
 
     @Test
     public void testPartialRevoke() throws Exception {
+        new MockUp<LocalMetastore>() {
+            @Mock
+            public Table getTable(String dbName, String tblName) {
+                return GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(new TableName("db", "tbl1")).get();
+            }
+
+            @Mock
+            public Table getTable(Long dbId, Long tableId) {
+                return GlobalStateMgr.getCurrentState().getMetadataMgr().getTable(new TableName("db", "tbl1")).get();
+            }
+        };
+
         String sql = "grant select on table db.tbl0 to test_user";
         DDLStmtExecutor.execute(UtFrameUtils.parseStmtWithNewParser(sql, ctx), ctx);
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/privilege/RBACMockedMetadataMgr.java b/fe/fe-core/src/test/java/com/starrocks/privilege/RBACMockedMetadataMgr.java
index 49f1f0a792c191..e9d2a338d4c567 100644
--- a/fe/fe-core/src/test/java/com/starrocks/privilege/RBACMockedMetadataMgr.java
+++ b/fe/fe-core/src/test/java/com/starrocks/privilege/RBACMockedMetadataMgr.java
@@ -117,17 +117,6 @@ public Table getTable(String catalogName, String dbName, String tblName) {
         return tableMap.get(tblName);
     }
 
-    @Override
-    public Table getTable(Long databaseId, Long tableId) {
-        for (Table table : tableMap.values()) {
-            if (table.getId() == tableId) {
-                return table;
-            }
-        }
-
-        return null;
-    }
-
     @Override
     public List<String> listTableNames(String catalogName, String dbName) {
         return new ArrayList<>(tableMap.keySet());
diff --git a/fe/fe-core/src/test/java/com/starrocks/pseudocluster/BeRestartTest.java b/fe/fe-core/src/test/java/com/starrocks/pseudocluster/BeRestartTest.java
index 9749c2e1b6eb3f..62ababccc94e07 100644
--- a/fe/fe-core/src/test/java/com/starrocks/pseudocluster/BeRestartTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/pseudocluster/BeRestartTest.java
@@ -64,7 +64,7 @@ public void testBeRestart() throws Exception {
             createTableSqls[i] = PseudoCluster.newCreateTableSqlBuilder().setTableName(name).build();
             insertSqls[i] = PseudoCluster.buildInsertSql("test", name);
             cluster.runSqls("test", createTableSqls[i], insertSqls[i], insertSqls[i], insertSqls[i]);
-            tableIds[i] = GlobalStateMgr.getCurrentState().getDb("test").getTable(name).getId();
+            tableIds[i] = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable(name).getId();
             // insert 3 times -> version: 4
             tableVersions[i] = 4;
         }
diff --git a/fe/fe-core/src/test/java/com/starrocks/pseudocluster/LocationLabeledTableBalanceTest.java b/fe/fe-core/src/test/java/com/starrocks/pseudocluster/LocationLabeledTableBalanceTest.java
index b451036350beb6..eeecf69483ac40 100644
--- a/fe/fe-core/src/test/java/com/starrocks/pseudocluster/LocationLabeledTableBalanceTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/pseudocluster/LocationLabeledTableBalanceTest.java
@@ -105,7 +105,7 @@ public void test1BestEffortBalance() throws SQLException, InterruptedException {
                 ");";
         cluster.runSql("test", sql);
 
-        Database test = GlobalStateMgr.getCurrentState().getDb("test");
+        Database test = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         OlapTable olapTable = (OlapTable) test.getTable("test_table_best_effort_balance");
 
         // Add another backend without location property, with best-effort balance strategy,
@@ -177,7 +177,7 @@ private void printTabletReplicaInfo(OlapTable table) {
     @Test
     @Ignore
     public void test2LocationMatchedBalance() throws InterruptedException, SQLException {
-        Database test = GlobalStateMgr.getCurrentState().getDb("test");
+        Database test = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         OlapTable olapTable = (OlapTable) test.getTable("test_table_best_effort_balance");
 
         long start = System.currentTimeMillis();
diff --git a/fe/fe-core/src/test/java/com/starrocks/pseudocluster/LocationMismatchRepairTest.java b/fe/fe-core/src/test/java/com/starrocks/pseudocluster/LocationMismatchRepairTest.java
index 9eee82727dba6f..77652e2b487a7c 100644
--- a/fe/fe-core/src/test/java/com/starrocks/pseudocluster/LocationMismatchRepairTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/pseudocluster/LocationMismatchRepairTest.java
@@ -81,7 +81,7 @@ private void setBackendLocationProp() throws SQLException {
         int j = 0;
         for (PseudoBackend backend : cluster.getBackends()) {
             String stmtStr = "alter system modify backend '" + backend.getHostHeartbeatPort() + "' set ('" +
-                    AlterSystemStmtAnalyzer.PROP_KEY_LOCATION + "' = 'rack:r" + i + "')";
+                        AlterSystemStmtAnalyzer.PROP_KEY_LOCATION + "' = 'rack:r" + i + "')";
             if (j % 2 == 1) {
                 i++;
             }
@@ -96,9 +96,9 @@ private Set<Long> getBackendIdsWithLocProp(String locationKey, String locationVa
         Set<Long> backendIds = Sets.newHashSet();
         for (PseudoBackend pseudoBackend : cluster.getBackends()) {
             Backend backend = GlobalStateMgr.getCurrentState().getNodeMgr()
-                    .getClusterInfo().getBackend(pseudoBackend.getId());
+                        .getClusterInfo().getBackend(pseudoBackend.getId());
             if (backend.getLocation().containsKey(locationKey) &&
-                    Objects.equals(backend.getLocation().get(locationKey), locationVal)) {
+                        Objects.equals(backend.getLocation().get(locationKey), locationVal)) {
                 backendIds.add(backend.getId());
             }
         }
@@ -112,9 +112,9 @@ private void printTabletReplicaInfo(OlapTable table) {
                 stringBuffer.append("tablet ").append(tablet.getId()).append(": ");
                 for (Replica replica : tablet.getAllReplicas()) {
                     stringBuffer.append(replica.getBackendId()).append(" ")
-                            .append(GlobalStateMgr.getCurrentState().getNodeMgr()
-                                    .getClusterInfo().getBackend(
-                            replica.getBackendId()).getLocation()).append(", ");
+                                .append(GlobalStateMgr.getCurrentState().getNodeMgr()
+                                            .getClusterInfo().getBackend(
+                                                        replica.getBackendId()).getLocation()).append(", ");
                 }
                 System.out.println(stringBuffer);
             });
@@ -136,20 +136,21 @@ public void testRepairAfterChangeTableLocation() throws Exception {
 
         PseudoCluster cluster = PseudoCluster.getInstance();
         String sql = "CREATE TABLE test.`test_table_backend_no_loc` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"3\",\n" +
-                "    \"in_memory\" = \"false\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"3\",\n" +
+                    "    \"in_memory\" = \"false\"\n" +
+                    ");";
         cluster.runSql("test", sql);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("test_table_backend_no_loc");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "test_table_backend_no_loc");
         Assert.assertNotNull(table.getLocation());
         Assert.assertTrue(table.getLocation().keySet().contains("*"));
 
@@ -173,22 +174,22 @@ public void testRepairAfterChangeTableLocation() throws Exception {
         long oldCloneFinishedCnt = stat.counterCloneTaskSucceeded.get();
         long oldLocationMismatchErr = stat.counterReplicaLocMismatchErr.get();
         System.out.println("old clone finished: " + oldCloneFinishedCnt + ", old location mismatch: " +
-                oldLocationMismatchErr);
+                    oldLocationMismatchErr);
         sql = "ALTER TABLE test.`test_table_backend_no_loc` SET ('" +
-                PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "' = 'rack:r1,rack:r2,rack:r3');";
+                    PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "' = 'rack:r1,rack:r2,rack:r3');";
         cluster.runSql("test", sql);
         System.out.println("=========================");
         long start = System.currentTimeMillis();
         while (true) {
             if (stat.counterCloneTaskSucceeded.get() - oldCloneFinishedCnt >= locationMismatchFullCloneNeeded
-                    && stat.counterReplicaLocMismatchErr.get() - oldLocationMismatchErr >=
-                    locationMismatchFullCloneNeeded) {
+                        && stat.counterReplicaLocMismatchErr.get() - oldLocationMismatchErr >=
+                        locationMismatchFullCloneNeeded) {
                 break;
             }
             System.out.println("wait for enough clone tasks for LOCATION_MISMATCH finished, " +
-                    "current clone finished: " + stat.counterCloneTaskSucceeded.get() +
-                    ", current location mismatch: " + stat.counterReplicaLocMismatchErr.get() +
-                    ", expected clone finished: " + locationMismatchFullCloneNeeded);
+                        "current clone finished: " + stat.counterCloneTaskSucceeded.get() +
+                        ", current location mismatch: " + stat.counterReplicaLocMismatchErr.get() +
+                        ", expected clone finished: " + locationMismatchFullCloneNeeded);
             Thread.sleep(1000);
             if (System.currentTimeMillis() - start > 180000) {
                 Assert.fail("wait for enough clone tasks for LOCATION_MISMATCH finished timeout");
@@ -208,7 +209,7 @@ public void testRepairAfterChangeTableLocation() throws Exception {
             Set<Pair<String, String>> racks = new HashSet<>();
             for (long backendId : intersection) {
                 Backend backend = GlobalStateMgr.getCurrentState().getNodeMgr()
-                        .getClusterInfo().getBackend(backendId);
+                            .getClusterInfo().getBackend(backendId);
                 racks.add(backend.getSingleLevelLocationKV());
             }
             Assert.assertEquals(3, racks.size());
@@ -221,17 +222,17 @@ public void testRepairLocationAfterDecommissionBackend() throws Exception {
 
         PseudoCluster cluster = PseudoCluster.getInstance();
         String sql = "CREATE TABLE test.`test_table_backend_no_loc` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"3\",\n" +
-                "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "\" = \"rack:r0,rack:r1,rack:r2,rack:r4\",\n" +
-                "    \"in_memory\" = \"false\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"3\",\n" +
+                    "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "\" = \"rack:r0,rack:r1,rack:r2,rack:r4\",\n" +
+                    "    \"in_memory\" = \"false\"\n" +
+                    ");";
         cluster.runSql("test", sql);
 
         // decommission backends with 'rack:r4' location
@@ -251,7 +252,7 @@ public void testRepairLocationAfterDecommissionBackend() throws Exception {
             while (true) {
                 int curTabletNum = decommissionBE.getTabletManager().getNumTablet();
                 System.out.printf("#tablets: %d/%d: fullClone: %d wait...\n", curTabletNum, pair.second,
-                        Tablet.getTotalFullClone());
+                            Tablet.getTotalFullClone());
                 if (curTabletNum == 0) {
                     break;
                 }
@@ -261,8 +262,9 @@ public void testRepairLocationAfterDecommissionBackend() throws Exception {
 
         // sleep to wait for redundant replicas cleaned
         Thread.sleep(5000);
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("test_table_backend_no_loc");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "test_table_backend_no_loc");
         printTabletReplicaInfo(table);
         Set<Long> stayedBackendIds = getBackendIdsWithLocProp("rack", "r0");
         stayedBackendIds.addAll(getBackendIdsWithLocProp("rack", "r1"));
@@ -277,14 +279,13 @@ public void testRepairLocationAfterDecommissionBackend() throws Exception {
             Set<Pair<String, String>> racks = new HashSet<>();
             for (long backendId : intersection) {
                 Backend backend = GlobalStateMgr.getCurrentState().getNodeMgr()
-                        .getClusterInfo().getBackend(backendId);
+                            .getClusterInfo().getBackend(backendId);
                 racks.add(backend.getSingleLevelLocationKV());
             }
             Assert.assertEquals(3, racks.size());
         }
     }
 
-
     @Test
     public void testMVRepairAfterChangeTableLocation() throws Exception {
         setBackendLocationProp();
@@ -292,32 +293,33 @@ public void testMVRepairAfterChangeTableLocation() throws Exception {
         PseudoCluster cluster = PseudoCluster.getInstance();
         // create base table
         String sql = "CREATE TABLE test.`test_base_table` (\n" +
-                "    k1 int,\n" +
-                "    k2 VARCHAR NOT NULL\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`k1`)\n" +
-                "COMMENT \"OLAP\"\n" +
-                "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
-                "PROPERTIES (\n" +
-                "    \"replication_num\" = \"3\",\n" +
-                "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "\" = \"rack:*\",\n" +
-                "    \"in_memory\" = \"false\"\n" +
-                ");";
+                    "    k1 int,\n" +
+                    "    k2 VARCHAR NOT NULL\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`k1`)\n" +
+                    "COMMENT \"OLAP\"\n" +
+                    "DISTRIBUTED BY HASH(`k1`) BUCKETS 5\n" +
+                    "PROPERTIES (\n" +
+                    "    \"replication_num\" = \"3\",\n" +
+                    "    \"" + PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "\" = \"rack:*\",\n" +
+                    "    \"in_memory\" = \"false\"\n" +
+                    ");";
         cluster.runSql("test", sql);
 
         // create mv
         sql = "CREATE MATERIALIZED VIEW test_mv01\n" +
-                "DISTRIBUTED BY HASH(`k1`)\n" +
-                "buckets 15\n" +
-                "REFRESH MANUAL\n" +
-                "properties(\n" +
-                "    \"replication_num\" = \"3\"" +
-                ")\n" +
-                "AS SELECT test_base_table.k1 FROM test_base_table;";
+                    "DISTRIBUTED BY HASH(`k1`)\n" +
+                    "buckets 15\n" +
+                    "REFRESH MANUAL\n" +
+                    "properties(\n" +
+                    "    \"replication_num\" = \"3\"" +
+                    ")\n" +
+                    "AS SELECT test_base_table.k1 FROM test_base_table;";
         cluster.runSql("test", sql);
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("test_mv01");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table =
+                    (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_mv01");
         Assert.assertNotNull(table.getLocation());
         Assert.assertTrue(table.getLocation().keySet().contains("*"));
 
@@ -341,22 +343,22 @@ public void testMVRepairAfterChangeTableLocation() throws Exception {
         long oldCloneFinishedCnt = stat.counterCloneTaskSucceeded.get();
         long oldLocationMismatchErr = stat.counterReplicaLocMismatchErr.get();
         System.out.println("old clone finished: " + oldCloneFinishedCnt + ", old location mismatch: " +
-                oldLocationMismatchErr);
+                    oldLocationMismatchErr);
         sql = "ALTER MATERIALIZED VIEW test.`test_mv01` SET ('" +
-                PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "' = 'rack:r1,rack:r2,rack:r3');";
+                    PropertyAnalyzer.PROPERTIES_LABELS_LOCATION + "' = 'rack:r1,rack:r2,rack:r3');";
         cluster.runSql("test", sql);
         System.out.println("=========================");
         long start = System.currentTimeMillis();
         while (true) {
             if (stat.counterCloneTaskSucceeded.get() - oldCloneFinishedCnt >= locationMismatchFullCloneNeeded
-                    && stat.counterReplicaLocMismatchErr.get() - oldLocationMismatchErr >=
-                    locationMismatchFullCloneNeeded) {
+                        && stat.counterReplicaLocMismatchErr.get() - oldLocationMismatchErr >=
+                        locationMismatchFullCloneNeeded) {
                 break;
             }
             System.out.println("wait for enough clone tasks for LOCATION_MISMATCH finished, " +
-                    "current clone finished: " + stat.counterCloneTaskSucceeded.get() +
-                    ", current location mismatch: " + stat.counterReplicaLocMismatchErr.get() +
-                    ", expected clone finished: " + locationMismatchFullCloneNeeded);
+                        "current clone finished: " + stat.counterCloneTaskSucceeded.get() +
+                        ", current location mismatch: " + stat.counterReplicaLocMismatchErr.get() +
+                        ", expected clone finished: " + locationMismatchFullCloneNeeded);
             Thread.sleep(1000);
             if (System.currentTimeMillis() - start > 180000) {
                 Assert.fail("wait for enough clone tasks for LOCATION_MISMATCH finished timeout");
@@ -376,7 +378,7 @@ public void testMVRepairAfterChangeTableLocation() throws Exception {
             Set<Pair<String, String>> racks = new HashSet<>();
             for (long backendId : intersection) {
                 Backend backend = GlobalStateMgr.getCurrentState().getNodeMgr()
-                        .getClusterInfo().getBackend(backendId);
+                            .getClusterInfo().getBackend(backendId);
                 racks.add(backend.getSingleLevelLocationKV());
             }
             Assert.assertEquals(3, racks.size());
diff --git a/fe/fe-core/src/test/java/com/starrocks/pseudocluster/PseudoCluster.java b/fe/fe-core/src/test/java/com/starrocks/pseudocluster/PseudoCluster.java
index ad5738a4bd9679..94a0d17ea1fba6 100644
--- a/fe/fe-core/src/test/java/com/starrocks/pseudocluster/PseudoCluster.java
+++ b/fe/fe-core/src/test/java/com/starrocks/pseudocluster/PseudoCluster.java
@@ -284,14 +284,14 @@ public Connection getQueryConnection() throws SQLException {
     }
 
     public List<Long> listTablets(String dbName, String tableName) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
         if (db == null) {
             return null;
         }
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.READ);
         try {
-            Table table = db.getTable(tableName);
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
             if (table == null) {
                 return null;
             }
diff --git a/fe/fe-core/src/test/java/com/starrocks/pseudocluster/ReplicaMinReadableVersionTest.java b/fe/fe-core/src/test/java/com/starrocks/pseudocluster/ReplicaMinReadableVersionTest.java
index db274741ed990c..f683987f05f0e3 100644
--- a/fe/fe-core/src/test/java/com/starrocks/pseudocluster/ReplicaMinReadableVersionTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/pseudocluster/ReplicaMinReadableVersionTest.java
@@ -50,7 +50,7 @@ public static void tearDown() throws Exception {
 
     @Test
     public void testReplicaMinReadableVersionReported() throws Exception {
-        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getDb("test").getTable(tableName);
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable(tableName);
         long tableId = olapTable.getId();
         PseudoBackend be = cluster.getBackend(10001);
         Tablet tablet = be.getTabletsByTable(tableId).get(0);
diff --git a/fe/fe-core/src/test/java/com/starrocks/qe/ShowExecutorTest.java b/fe/fe-core/src/test/java/com/starrocks/qe/ShowExecutorTest.java
index 61d1b3d792d627..b842143bc71611 100644
--- a/fe/fe-core/src/test/java/com/starrocks/qe/ShowExecutorTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/qe/ShowExecutorTest.java
@@ -82,6 +82,7 @@
 import com.starrocks.privilege.PrivilegeBuiltinConstants;
 import com.starrocks.server.CatalogMgr;
 import com.starrocks.server.GlobalStateMgr;
+import com.starrocks.server.LocalMetastore;
 import com.starrocks.server.MetadataMgr;
 import com.starrocks.server.NodeMgr;
 import com.starrocks.server.RunMode;
@@ -253,7 +254,7 @@ public void setUp() throws Exception {
         };
 
         BaseTableInfo baseTableInfo = new BaseTableInfo(
-                "default_catalog", "testDb", "testTbl", null);
+                    "default_catalog", "testDb", "testTbl", null);
 
         // mock materialized view
         MaterializedView mv = new MaterializedView();
@@ -302,10 +303,10 @@ public void setUp() throws Exception {
                 mv.getPartitionInfo();
                 minTimes = 0;
                 result = new ExpressionRangePartitionInfo(
-                        Collections.singletonList(
-                                ColumnIdExpr.create(new SlotRef(
-                                        new TableName("test", "testMv"), column1.getName()))),
-                        Collections.singletonList(column1), PartitionType.RANGE);
+                            Collections.singletonList(
+                                        ColumnIdExpr.create(new SlotRef(
+                                                    new TableName("test", "testMv"), column1.getName()))),
+                            Collections.singletonList(column1), PartitionType.RANGE);
 
                 mv.getDefaultDistributionInfo();
                 minTimes = 0;
@@ -326,7 +327,7 @@ public void setUp() throws Exception {
                 mv.getTableProperty();
                 minTimes = 0;
                 result = new TableProperty(
-                        Collections.singletonMap(PROPERTIES_STORAGE_COOLDOWN_TIME, "100"));
+                            Collections.singletonMap(PROPERTIES_STORAGE_COOLDOWN_TIME, "100"));
 
                 mv.getIdToColumn();
                 minTimes = 0;
@@ -366,20 +367,29 @@ public void setUp() throws Exception {
 
         // mock globalStateMgr.
         globalStateMgr = Deencapsulation.newInstance(GlobalStateMgr.class);
+        LocalMetastore localMetastore = new LocalMetastore(globalStateMgr, null, null);
         new Expectations(globalStateMgr) {
             {
-                globalStateMgr.getDb("testDb");
+                /*
+                globalStateMgr.getLocalMetastore().getDb("testDb");
                 minTimes = 0;
                 result = db;
 
-                globalStateMgr.getDb("emptyDb");
+
+                globalStateMgr.getLocalMetastore().getDb("emptyDb");
                 minTimes = 0;
                 result = null;
 
+                 */
+
                 GlobalStateMgr.getCurrentState();
                 minTimes = 0;
                 result = globalStateMgr;
 
+                globalStateMgr.getLocalMetastore();
+                minTimes = 0;
+                result = localMetastore;
+
                 globalStateMgr.getMetadataMgr();
                 minTimes = 0;
                 result = metadataMgr;
@@ -397,12 +407,32 @@ public void setUp() throws Exception {
                 result = null;
 
                 metadataMgr.getTable("default_catalog", "testDb",
-                        "testTbl");
+                            "testTbl");
                 minTimes = 0;
                 result = table;
             }
         };
 
+        new MockUp<LocalMetastore>() {
+            @Mock
+            public Database getDb(String dbName) {
+                if (dbName.equalsIgnoreCase("emptyDb")) {
+                    return null;
+                }
+                return db;
+            }
+
+            @Mock
+            public Table getTable(String dbName, String tblName) {
+                return db.getTable(tblName);
+            }
+
+            @Mock
+            public List<Table> getTables(Long dbId) {
+                return db.getTables();
+            }
+        };
+
         // mock scheduler
         ConnectScheduler scheduler = new ConnectScheduler(10);
         new Expectations(scheduler) {
@@ -473,6 +503,7 @@ public List<Long> getAvailableBackendIds() {
         OlapTable olapTable = listPartitionInfoTest.findTableForMultiListPartition();
         Database db = new Database();
 
+        /*
         new Expectations(db) {
             {
                 db.getTable(anyString);
@@ -485,6 +516,8 @@ public List<Long> getAvailableBackendIds() {
             }
         };
 
+         */
+
         new MockUp<MetaUtils>() {
             @Mock
             public Table getSessionAwareTable(ConnectContext ctx, Database db, TableName tableName) {
@@ -494,15 +527,19 @@ public Table getSessionAwareTable(ConnectContext ctx, Database db, TableName tab
 
         new Expectations() {
             {
-                globalStateMgr.getDb(0);
+                globalStateMgr.getLocalMetastore().getDb(0);
                 minTimes = 0;
                 result = db;
+
+                globalStateMgr.getLocalMetastore().getTable(anyLong, anyLong);
+                minTimes = 0;
+                result = olapTable;
             }
         };
 
         // Ok to test
         ShowPartitionsStmt stmt = new ShowPartitionsStmt(new TableName("testDb", "testTbl"),
-                null, null, null, false);
+                    null, null, null, false);
         com.starrocks.sql.analyzer.Analyzer.analyze(stmt, ctx);
 
         ShowResultSet resultSet = ShowExecutor.execute(stmt, ctx);
@@ -549,7 +586,7 @@ public void testDescribe() throws DdlException {
         ctx.setQualifiedUser("testUser");
 
         DescribeStmt stmt = (DescribeStmt) com.starrocks.sql.parser.SqlParser.parse("desc testTbl",
-                ctx.getSessionVariable().getSqlMode()).get(0);
+                    ctx.getSessionVariable().getSqlMode()).get(0);
         com.starrocks.sql.analyzer.Analyzer.analyze(stmt, ctx);
 
         ShowResultSet resultSet;
@@ -655,7 +692,7 @@ public void testShowCreateNoDb() {
     @Test(expected = SemanticException.class)
     public void testShowCreateTableEmptyDb() throws SemanticException, DdlException {
         ShowCreateTableStmt stmt = new ShowCreateTableStmt(new TableName("emptyDb", "testTable"),
-                ShowCreateTableStmt.CreateTableType.TABLE);
+                    ShowCreateTableStmt.CreateTableType.TABLE);
 
         ShowResultSet resultSet = ShowExecutor.execute(stmt, ctx);
 
@@ -668,7 +705,7 @@ public void testShowColumn() throws AnalysisException, DdlException {
         ctx.setQualifiedUser("testUser");
 
         ShowColumnStmt stmt = (ShowColumnStmt) com.starrocks.sql.parser.SqlParser.parse("show columns from testTbl in testDb",
-                ctx.getSessionVariable()).get(0);
+                    ctx.getSessionVariable()).get(0);
         com.starrocks.sql.analyzer.Analyzer.analyze(stmt, ctx);
 
         ShowResultSet resultSet = ShowExecutor.execute(stmt, ctx);
@@ -682,7 +719,7 @@ public void testShowColumn() throws AnalysisException, DdlException {
 
         // verbose
         stmt = (ShowColumnStmt) com.starrocks.sql.parser.SqlParser.parse("show full columns from testTbl in testDb",
-                ctx.getSessionVariable()).get(0);
+                    ctx.getSessionVariable()).get(0);
         com.starrocks.sql.analyzer.Analyzer.analyze(stmt, ctx);
 
         resultSet = ShowExecutor.execute(stmt, ctx);
@@ -697,7 +734,7 @@ public void testShowColumn() throws AnalysisException, DdlException {
 
         // show full fields
         stmt = (ShowColumnStmt) com.starrocks.sql.parser.SqlParser.parse("show full fields from testTbl in testDb",
-                ctx.getSessionVariable()).get(0);
+                    ctx.getSessionVariable()).get(0);
         com.starrocks.sql.analyzer.Analyzer.analyze(stmt, ctx);
 
         resultSet = ShowExecutor.execute(stmt, ctx);
@@ -712,7 +749,7 @@ public void testShowColumn() throws AnalysisException, DdlException {
 
         // pattern
         stmt = (ShowColumnStmt) com.starrocks.sql.parser.SqlParser.parse("show full columns from testTbl in testDb like \"%1\"",
-                ctx.getSessionVariable().getSqlMode()).get(0);
+                    ctx.getSessionVariable().getSqlMode()).get(0);
         com.starrocks.sql.analyzer.Analyzer.analyze(stmt, ctx);
 
         resultSet = ShowExecutor.execute(stmt, ctx);
@@ -895,10 +932,10 @@ RunMode getCurrentRunMode() {
         ShowResultSet resultSet = ShowExecutor.execute(stmt, ctx);
 
         Assert.assertEquals(ComputeNodeProcDir.TITLE_NAMES_SHARED_DATA.size(),
-                resultSet.getMetaData().getColumnCount());
+                    resultSet.getMetaData().getColumnCount());
         for (int i = 0; i < ComputeNodeProcDir.TITLE_NAMES_SHARED_DATA.size(); ++i) {
             Assert.assertEquals(ComputeNodeProcDir.TITLE_NAMES_SHARED_DATA.get(i),
-                    resultSet.getMetaData().getColumn(i).getName());
+                        resultSet.getMetaData().getColumn(i).getName());
         }
 
         Assert.assertTrue(resultSet.next());
@@ -1003,15 +1040,15 @@ public void testShowMaterializedViewPattern() throws AnalysisException, DdlExcep
 
     private void verifyShowMaterializedViewResult(ShowResultSet resultSet) throws AnalysisException, DdlException {
         String expectedSqlText = "CREATE MATERIALIZED VIEW `testMv` (`col1`, `col2`)\n" +
-                "COMMENT \"TEST MATERIALIZED VIEW\"\n" +
-                "PARTITION BY (`col1`)\n" +
-                "DISTRIBUTED BY HASH(`col1`) BUCKETS 10 \n" +
-                "REFRESH ASYNC\n" +
-                "PROPERTIES (\n" +
-                "\"storage_cooldown_time\" = \"1970-01-01 08:00:00\",\n" +
-                "\"storage_medium\" = \"SSD\"\n" +
-                ")\n" +
-                "AS select col1, col2 from table1;";
+                    "COMMENT \"TEST MATERIALIZED VIEW\"\n" +
+                    "PARTITION BY (`col1`)\n" +
+                    "DISTRIBUTED BY HASH(`col1`) BUCKETS 10 \n" +
+                    "REFRESH ASYNC\n" +
+                    "PROPERTIES (\n" +
+                    "\"storage_cooldown_time\" = \"1970-01-01 08:00:00\",\n" +
+                    "\"storage_medium\" = \"SSD\"\n" +
+                    ")\n" +
+                    "AS select col1, col2 from table1;";
 
         Assert.assertTrue(resultSet.next());
         List<Column> mvSchemaTable = MaterializedViewsSystemTable.create().getFullSchema();
@@ -1030,14 +1067,15 @@ private void verifyShowMaterializedViewResult(ShowResultSet resultSet) throws An
         Assert.assertEquals("", resultSet.getString(12));
         Assert.assertEquals("false", resultSet.getString(13));
         System.out.println(resultSet.getResultRows());
-        for (int i = 14; i < mvSchemaTable.size() - 4; i++) {
+        for (int i = 14; i < mvSchemaTable.size() - 5; i++) {
             System.out.println(i);
             Assert.assertEquals("", resultSet.getString(i));
         }
-        Assert.assertEquals("10", resultSet.getString(mvSchemaTable.size() - 4));
-        Assert.assertEquals(expectedSqlText, resultSet.getString(mvSchemaTable.size() - 3));
-        Assert.assertEquals("", resultSet.getString(mvSchemaTable.size() - 2));
-        Assert.assertEquals("VALID", resultSet.getString(mvSchemaTable.size() - 1));
+        Assert.assertEquals("10", resultSet.getString(mvSchemaTable.size() - 5));
+        Assert.assertEquals(expectedSqlText, resultSet.getString(mvSchemaTable.size() - 4));
+        Assert.assertEquals("", resultSet.getString(mvSchemaTable.size() - 3));
+        Assert.assertEquals("VALID", resultSet.getString(mvSchemaTable.size() - 2));
+        Assert.assertEquals("", resultSet.getString(mvSchemaTable.size() - 1));
         Assert.assertFalse(resultSet.next());
     }
 
@@ -1052,7 +1090,8 @@ public void testShowRoutineLoadNonExisted() throws AnalysisException, DdlExcepti
     @Test
     public void testShowAlterTable() throws AnalysisException, DdlException {
         ShowAlterStmt stmt = new ShowAlterStmt(ShowAlterStmt.AlterType.OPTIMIZE, "testDb", null, null, null);
-        stmt.setNode(new OptimizeProcDir(globalStateMgr.getSchemaChangeHandler(), globalStateMgr.getDb("testDb")));
+        stmt.setNode(new OptimizeProcDir(globalStateMgr.getSchemaChangeHandler(),
+                    globalStateMgr.getLocalMetastore().getDb("testDb")));
 
         ShowExecutor.execute(stmt, ctx);
     }
@@ -1081,34 +1120,34 @@ public Table getTable(String catalogName, String dbName, String tblName) {
                 partitions.add("year");
                 partitions.add("dt");
                 HiveTable.Builder tableBuilder = HiveTable.builder()
-                        .setId(1)
-                        .setTableName("test_table")
-                        .setCatalogName("hive_catalog")
-                        .setResourceName(toResourceName("hive_catalog", "hive"))
-                        .setHiveDbName("hive_db")
-                        .setHiveTableName("test_table")
-                        .setPartitionColumnNames(partitions)
-                        .setFullSchema(fullSchema)
-                        .setTableLocation("hdfs://hadoop/hive/warehouse/test.db/test")
-                        .setCreateTime(10000);
+                            .setId(1)
+                            .setTableName("test_table")
+                            .setCatalogName("hive_catalog")
+                            .setResourceName(toResourceName("hive_catalog", "hive"))
+                            .setHiveDbName("hive_db")
+                            .setHiveTableName("test_table")
+                            .setPartitionColumnNames(partitions)
+                            .setFullSchema(fullSchema)
+                            .setTableLocation("hdfs://hadoop/hive/warehouse/test.db/test")
+                            .setCreateTime(10000);
                 return tableBuilder.build();
             }
         };
 
         ShowCreateTableStmt stmt = new ShowCreateTableStmt(new TableName("hive_catalog", "hive_db", "test_table"),
-                ShowCreateTableStmt.CreateTableType.TABLE);
+                    ShowCreateTableStmt.CreateTableType.TABLE);
 
         ShowResultSet resultSet = ShowExecutor.execute(stmt, ctx);
         Assert.assertEquals("test_table", resultSet.getResultRows().get(0).get(0));
         Assert.assertEquals("CREATE TABLE `test_table` (\n" +
-                        "  `id` int(11) DEFAULT NULL COMMENT \"id\",\n" +
-                        "  `name` varchar DEFAULT NULL,\n" +
-                        "  `year` int(11) DEFAULT NULL,\n" +
-                        "  `dt` int(11) DEFAULT NULL\n" +
-                        ")\n" +
-                        "PARTITION BY (year, dt)\n" +
-                        "PROPERTIES (\"location\" = \"hdfs://hadoop/hive/warehouse/test.db/test\");",
-                resultSet.getResultRows().get(0).get(1));
+                                "  `id` int(11) DEFAULT NULL COMMENT \"id\",\n" +
+                                "  `name` varchar DEFAULT NULL,\n" +
+                                "  `year` int(11) DEFAULT NULL,\n" +
+                                "  `dt` int(11) DEFAULT NULL\n" +
+                                ")\n" +
+                                "PARTITION BY (year, dt)\n" +
+                                "PROPERTIES (\"location\" = \"hdfs://hadoop/hive/warehouse/test.db/test\");",
+                    resultSet.getResultRows().get(0).get(1));
     }
 
     @Test
@@ -1135,35 +1174,35 @@ public Table getTable(String catalogName, String dbName, String tblName) {
                 partitions.add("year");
                 partitions.add("dt");
                 HiveTable.Builder tableBuilder = HiveTable.builder()
-                        .setId(1)
-                        .setTableName("test_table")
-                        .setCatalogName("hive_catalog")
-                        .setResourceName(toResourceName("hive_catalog", "hive"))
-                        .setHiveDbName("hive_db")
-                        .setHiveTableName("test_table")
-                        .setPartitionColumnNames(partitions)
-                        .setFullSchema(fullSchema)
-                        .setTableLocation("hdfs://hadoop/hive/warehouse/test.db/test")
-                        .setCreateTime(10000)
-                        .setHiveTableType(HiveTable.HiveTableType.EXTERNAL_TABLE);
+                            .setId(1)
+                            .setTableName("test_table")
+                            .setCatalogName("hive_catalog")
+                            .setResourceName(toResourceName("hive_catalog", "hive"))
+                            .setHiveDbName("hive_db")
+                            .setHiveTableName("test_table")
+                            .setPartitionColumnNames(partitions)
+                            .setFullSchema(fullSchema)
+                            .setTableLocation("hdfs://hadoop/hive/warehouse/test.db/test")
+                            .setCreateTime(10000)
+                            .setHiveTableType(HiveTable.HiveTableType.EXTERNAL_TABLE);
                 return tableBuilder.build();
             }
         };
 
         ShowCreateTableStmt stmt = new ShowCreateTableStmt(new TableName("hive_catalog", "hive_db", "test_table"),
-                ShowCreateTableStmt.CreateTableType.TABLE);
+                    ShowCreateTableStmt.CreateTableType.TABLE);
 
         ShowResultSet resultSet = ShowExecutor.execute(stmt, ctx);
         Assert.assertEquals("test_table", resultSet.getResultRows().get(0).get(0));
         Assert.assertEquals("CREATE EXTERNAL TABLE `test_table` (\n" +
-                        "  `id` int(11) DEFAULT NULL COMMENT \"id\",\n" +
-                        "  `name` varchar DEFAULT NULL,\n" +
-                        "  `year` int(11) DEFAULT NULL,\n" +
-                        "  `dt` int(11) DEFAULT NULL\n" +
-                        ")\n" +
-                        "PARTITION BY (year, dt)\n" +
-                        "PROPERTIES (\"location\" = \"hdfs://hadoop/hive/warehouse/test.db/test\");",
-                resultSet.getResultRows().get(0).get(1));
+                                "  `id` int(11) DEFAULT NULL COMMENT \"id\",\n" +
+                                "  `name` varchar DEFAULT NULL,\n" +
+                                "  `year` int(11) DEFAULT NULL,\n" +
+                                "  `dt` int(11) DEFAULT NULL\n" +
+                                ")\n" +
+                                "PARTITION BY (year, dt)\n" +
+                                "PROPERTIES (\"location\" = \"hdfs://hadoop/hive/warehouse/test.db/test\");",
+                    resultSet.getResultRows().get(0).get(1));
     }
 
     @Test
@@ -1184,10 +1223,10 @@ public Catalog getCatalogByName(String name) {
 
         Assert.assertEquals("test_hive", resultSet.getResultRows().get(0).get(0));
         Assert.assertEquals("CREATE EXTERNAL CATALOG `test_hive`\n" +
-                "comment \"hive_test\"\n" +
-                "PROPERTIES (\"type\"  =  \"hive\",\n" +
-                "\"hive.metastore.uris\"  =  \"thrift://hadoop:9083\"\n" +
-                ")", resultSet.getResultRows().get(0).get(1));
+                    "comment \"hive_test\"\n" +
+                    "PROPERTIES (\"type\"  =  \"hive\",\n" +
+                    "\"hive.metastore.uris\"  =  \"thrift://hadoop:9083\"\n" +
+                    ")", resultSet.getResultRows().get(0).get(1));
     }
 
     @Test
@@ -1202,7 +1241,7 @@ public Catalog getCatalogByName(String name) {
         ShowCreateExternalCatalogStmt stmt = new ShowCreateExternalCatalogStmt("catalog_not_exist");
 
         ExceptionChecker.expectThrowsWithMsg(SemanticException.class, "Unknown catalog 'catalog_not_exist'",
-                () -> ShowExecutor.execute(stmt, ctx));
+                    () -> ShowExecutor.execute(stmt, ctx));
     }
 
     @Test
@@ -1212,8 +1251,8 @@ public void testShowBasicStatsMeta() throws Exception {
             public Map<AnalyzeMgr.StatsMetaKey, ExternalBasicStatsMeta> getExternalBasicStatsMetaMap() {
                 Map<AnalyzeMgr.StatsMetaKey, ExternalBasicStatsMeta> map = new HashMap<>();
                 map.put(new AnalyzeMgr.StatsMetaKey("hive0", "testDb", "testTable"),
-                        new ExternalBasicStatsMeta("hive0", "testDb", "testTable", null,
-                                StatsConstants.AnalyzeType.FULL, LocalDateTime.now(), Maps.newHashMap()));
+                            new ExternalBasicStatsMeta("hive0", "testDb", "testTable", null,
+                                        StatsConstants.AnalyzeType.FULL, LocalDateTime.now(), Maps.newHashMap()));
                 return map;
             }
         };
@@ -1234,13 +1273,13 @@ public void testShowGrants() throws Exception {
         ShowResultSet resultSet = ShowExecutor.execute(stmt, ctx);
         resultSet.getResultRows().forEach(System.out::println);
         String expectString1 = "root, null, GRANT CREATE TABLE, DROP, ALTER, CREATE VIEW, CREATE FUNCTION, " +
-                "CREATE MATERIALIZED VIEW, CREATE PIPE ON ALL DATABASES TO ROLE 'root'";
+                    "CREATE MATERIALIZED VIEW, CREATE PIPE ON ALL DATABASES TO ROLE 'root'";
         Assert.assertTrue(resultSet.getResultRows().stream().anyMatch(l ->
-                l.toString().contains(expectString1)));
+                    l.toString().contains(expectString1)));
         String expectString2 = "root, null, GRANT DELETE, DROP, INSERT, SELECT, ALTER, EXPORT, " +
-                "UPDATE ON ALL TABLES IN ALL DATABASES TO ROLE 'root'";
+                    "UPDATE ON ALL TABLES IN ALL DATABASES TO ROLE 'root'";
         Assert.assertTrue(resultSet.getResultRows().stream().anyMatch(l ->
-                l.toString().contains(expectString2)));
+                    l.toString().contains(expectString2)));
     }
 
     @Test
@@ -1263,12 +1302,12 @@ public Catalog getCatalogByName(String name) {
 
         Assert.assertEquals("test_hive", resultSet.getResultRows().get(0).get(0));
         Assert.assertEquals("CREATE EXTERNAL CATALOG `test_hive`\n" +
-                "comment \"hive_test\"\n" +
-                "PROPERTIES (\"aws.s3.access_key\"  =  \"ia******ey\",\n" +
-                "\"aws.s3.secret_key\"  =  \"ia******ey\",\n" +
-                "\"hive.metastore.uris\"  =  \"thrift://hadoop:9083\",\n" +
-                "\"type\"  =  \"hive\"\n" +
-                ")", resultSet.getResultRows().get(0).get(1));
+                    "comment \"hive_test\"\n" +
+                    "PROPERTIES (\"aws.s3.access_key\"  =  \"ia******ey\",\n" +
+                    "\"aws.s3.secret_key\"  =  \"ia******ey\",\n" +
+                    "\"hive.metastore.uris\"  =  \"thrift://hadoop:9083\",\n" +
+                    "\"type\"  =  \"hive\"\n" +
+                    ")", resultSet.getResultRows().get(0).get(1));
     }
 
     @Test
@@ -1281,7 +1320,7 @@ public void testShowDataCacheRules() throws DdlException, AnalysisException {
         properties.put("ni", "hao");
         StringLiteral stringLiteral = new StringLiteral("hello");
         dataCacheMgr.createCacheRule(QualifiedName.of(ImmutableList.of("test2", "test2", "test2")),
-                stringLiteral, -1, properties);
+                    stringLiteral, -1, properties);
 
         ShowDataCacheRulesStmt stmt = new ShowDataCacheRulesStmt(NodePosition.ZERO);
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/qe/ShowTableMockMeta.java b/fe/fe-core/src/test/java/com/starrocks/qe/ShowTableMockMeta.java
index 2858c4ae2c9911..9cb52e455cdcc1 100644
--- a/fe/fe-core/src/test/java/com/starrocks/qe/ShowTableMockMeta.java
+++ b/fe/fe-core/src/test/java/com/starrocks/qe/ShowTableMockMeta.java
@@ -130,17 +130,6 @@ public Table getTable(String catalogName, String dbName, String tblName) {
         return tableMap.get(tblName);
     }
 
-    @Override
-    public Table getTable(Long databaseId, Long tableId) {
-        for (Table table : tableMap.values()) {
-            if (table.getId() == tableId) {
-                return table;
-            }
-        }
-
-        return null;
-    }
-
     @Override
     public List<String> listTableNames(String catalogName, String dbName) {
         if (catalogName.equals("hive_catalog")) {
diff --git a/fe/fe-core/src/test/java/com/starrocks/replication/ReplicationJobTest.java b/fe/fe-core/src/test/java/com/starrocks/replication/ReplicationJobTest.java
index ef9e7de206ed8c..7d31dda4894c53 100644
--- a/fe/fe-core/src/test/java/com/starrocks/replication/ReplicationJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/replication/ReplicationJobTest.java
@@ -73,15 +73,16 @@ public static void beforeClass() throws Exception {
         starRocksAssert = new StarRocksAssert(AnalyzeTestUtil.getConnectContext());
         starRocksAssert.withDatabase("test").useDatabase("test");
 
-        db = GlobalStateMgr.getCurrentState().getDb("test");
+        db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String sql = "create table single_partition_duplicate_key (key1 int, key2 varchar(10))\n" +
-                "distributed by hash(key1) buckets 1\n" +
-                "properties('replication_num' = '1'); ";
+                    "distributed by hash(key1) buckets 1\n" +
+                    "properties('replication_num' = '1'); ";
         CreateTableStmt createTableStmt = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql,
-                AnalyzeTestUtil.getConnectContext());
+                    AnalyzeTestUtil.getConnectContext());
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
-        table = (OlapTable) db.getTable("single_partition_duplicate_key");
+        table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "single_partition_duplicate_key");
         srcTable = DeepCopy.copyWithGson(table, OlapTable.class);
 
         partition = table.getPartitions().iterator().next();
@@ -105,16 +106,16 @@ public void setUp() throws Exception {
         srcPartition.setNextDataVersion(99);
 
         job = new ReplicationJob(null, "test_token", db.getId(), table, srcTable,
-                GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo());
+                    GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo());
     }
 
     @Test
     public void testJobId() {
         ReplicationJob jobWithoutId = new ReplicationJob(null, "test_token", db.getId(), table, srcTable,
-                GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo());
+                    GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo());
         Assert.assertFalse(jobWithoutId.getJobId().isEmpty());
         ReplicationJob jobWithId = new ReplicationJob("fake_id", "test_token", db.getId(), table, srcTable,
-                GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo());
+                    GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo());
         Assert.assertEquals("fake_id", jobWithId.getJobId());
     }
 
@@ -140,7 +141,7 @@ public void testNormal() throws Exception {
             job.finishRemoteSnapshotTask((RemoteSnapshotTask) task, request);
 
             Deencapsulation.invoke(new LeaderImpl(), "finishRemoteSnapshotTask",
-                    (RemoteSnapshotTask) task, request);
+                        (RemoteSnapshotTask) task, request);
             ((RemoteSnapshotTask) task).toThrift();
             task.toString();
         }
@@ -154,7 +155,7 @@ public void testNormal() throws Exception {
             job.finishReplicateSnapshotTask((ReplicateSnapshotTask) task, request);
 
             Deencapsulation.invoke(new LeaderImpl(), "finishReplicateSnapshotTask",
-                    (ReplicateSnapshotTask) task, request);
+                        (ReplicateSnapshotTask) task, request);
             ((ReplicateSnapshotTask) task).toThrift();
             task.toString();
         }
@@ -346,7 +347,7 @@ public void testInitializedByThrift() {
             tabletInfo.replica_replication_infos = new ArrayList<TReplicaReplicationInfo>();
             TReplicaReplicationInfo replicaInfo = new TReplicaReplicationInfo();
             Backend backend = GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo().getBackends().iterator()
-                    .next();
+                        .next();
             replicaInfo.src_backend = new TBackend(backend.getHost(), backend.getBePort(), backend.getHttpPort());
             tabletInfo.replica_replication_infos.add(replicaInfo);
         }
diff --git a/fe/fe-core/src/test/java/com/starrocks/replication/ReplicationMgrTest.java b/fe/fe-core/src/test/java/com/starrocks/replication/ReplicationMgrTest.java
index 795e9d28f799dd..5b359868a5b91f 100644
--- a/fe/fe-core/src/test/java/com/starrocks/replication/ReplicationMgrTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/replication/ReplicationMgrTest.java
@@ -19,8 +19,10 @@
 import com.starrocks.catalog.OlapTable;
 import com.starrocks.catalog.Partition;
 import com.starrocks.catalog.Tablet;
+import com.starrocks.common.Config;
 import com.starrocks.common.io.DeepCopy;
 import com.starrocks.common.jmockit.Deencapsulation;
+import com.starrocks.common.proc.ReplicationsProcNode;
 import com.starrocks.leader.LeaderImpl;
 import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.analyzer.AnalyzeTestUtil;
@@ -74,7 +76,7 @@ public static void beforeClass() throws Exception {
         starRocksAssert = new StarRocksAssert(AnalyzeTestUtil.getConnectContext());
         starRocksAssert.withDatabase("test").useDatabase("test");
 
-        db = GlobalStateMgr.getCurrentState().getDb("test");
+        db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         String sql = "create table single_partition_duplicate_key (key1 int, key2 varchar(10))\n" +
                 "distributed by hash(key1) buckets 1\n" +
@@ -83,7 +85,8 @@ public static void beforeClass() throws Exception {
                 AnalyzeTestUtil.getConnectContext());
         StarRocksAssert.utCreateTableWithRetry(createTableStmt);
 
-        table = (OlapTable) db.getTable("single_partition_duplicate_key");
+        table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(db.getFullName(), "single_partition_duplicate_key");
         srcTable = DeepCopy.copyWithGson(table, OlapTable.class);
 
         partition = table.getPartitions().iterator().next();
@@ -164,6 +167,21 @@ public void testNormal() throws Exception {
         Assert.assertEquals(partition.getCommittedDataVersion(), srcPartition.getDataVersion());
 
         replicationMgr.replayReplicationJob(job);
+
+        Assert.assertTrue(replicationMgr.getRunningJobs().isEmpty());
+        Assert.assertFalse(replicationMgr.getCommittedJobs().isEmpty());
+
+        int old = Config.history_job_keep_max_second;
+        Config.history_job_keep_max_second = -1;
+        Assert.assertTrue(job.isExpired());
+
+        replicationMgr.runAfterCatalogReady();
+        Assert.assertTrue(replicationMgr.getCommittedJobs().isEmpty());
+
+        replicationMgr.replayDeleteReplicationJob(job);
+        Assert.assertTrue(replicationMgr.getCommittedJobs().isEmpty());
+
+        Config.history_job_keep_max_second = old;
     }
 
     @Test
@@ -176,11 +194,8 @@ public void testInitializingCancel() {
         replicationMgr.runAfterCatalogReady();
         Assert.assertEquals(ReplicationJobState.ABORTED, job.getState());
 
-        Assert.assertFalse(replicationMgr.hasRunningJobs());
-        Assert.assertTrue(replicationMgr.hasFailedJobs());
-
-        replicationMgr.clearFinishedJobs();
-        replicationMgr.replayReplicationJob(null);
+        Assert.assertTrue(replicationMgr.getRunningJobs().isEmpty());
+        Assert.assertFalse(replicationMgr.getAbortedJobs().isEmpty());
     }
 
     @Test
@@ -195,6 +210,21 @@ public void testSnapshotingCancel() {
 
         replicationMgr.runAfterCatalogReady();
         Assert.assertEquals(ReplicationJobState.ABORTED, job.getState());
+
+        Assert.assertTrue(replicationMgr.getRunningJobs().isEmpty());
+        Assert.assertFalse(replicationMgr.getAbortedJobs().isEmpty());
+
+        int old = Config.history_job_keep_max_second;
+        Config.history_job_keep_max_second = -1;
+        Assert.assertTrue(job.isExpired());
+
+        replicationMgr.runAfterCatalogReady();
+        Assert.assertTrue(replicationMgr.getAbortedJobs().isEmpty());
+
+        replicationMgr.replayDeleteReplicationJob(job);
+        Assert.assertTrue(replicationMgr.getAbortedJobs().isEmpty());
+
+        Config.history_job_keep_max_second = old;
     }
 
     @Test
@@ -371,4 +401,14 @@ private static TSnapshotInfo newTSnapshotInfo(TBackend backend, String snapshotP
         tSnapshotInfo.setIncremental_snapshot(incrementalSnapshot);
         return tSnapshotInfo;
     }
+
+    @Test
+    public void testReplicationsProcNode() {
+        ReplicationsProcNode procNode = new ReplicationsProcNode();
+        try {
+            procNode.fetchResult();
+        } catch (Exception e) {
+            Assert.assertNull(e);
+        }
+    }
 }
\ No newline at end of file
diff --git a/fe/fe-core/src/test/java/com/starrocks/scheduler/MVRefreshTestBase.java b/fe/fe-core/src/test/java/com/starrocks/scheduler/MVRefreshTestBase.java
index 63e22ed1808055..f07404bc265c06 100644
--- a/fe/fe-core/src/test/java/com/starrocks/scheduler/MVRefreshTestBase.java
+++ b/fe/fe-core/src/test/java/com/starrocks/scheduler/MVRefreshTestBase.java
@@ -97,8 +97,8 @@ public static void executeInsertSql(ConnectContext connectContext, String sql) t
     }
 
     protected MaterializedView getMv(String dbName, String mvName) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
-        Table table = db.getTable(mvName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), mvName);
         Assert.assertNotNull(table);
         Assert.assertTrue(table instanceof MaterializedView);
         MaterializedView mv = (MaterializedView) table;
@@ -106,8 +106,8 @@ protected MaterializedView getMv(String dbName, String mvName) {
     }
 
     protected Table getTable(String dbName, String tableName) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
-        Table table = db.getTable(tableName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         Assert.assertNotNull(table);
         return table;
     }
diff --git a/fe/fe-core/src/test/java/com/starrocks/scheduler/PCTRefreshListPartitionOlapTest.java b/fe/fe-core/src/test/java/com/starrocks/scheduler/PCTRefreshListPartitionOlapTest.java
index e8978fc6547973..31e313001be19f 100644
--- a/fe/fe-core/src/test/java/com/starrocks/scheduler/PCTRefreshListPartitionOlapTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/scheduler/PCTRefreshListPartitionOlapTest.java
@@ -53,75 +53,75 @@ public static void beforeClass() throws Exception {
         MVRefreshTestBase.beforeClass();
         // table whose partitions have multiple values
         T1 = "CREATE TABLE t1 (\n" +
-                "      id BIGINT,\n" +
-                "      age SMALLINT,\n" +
-                "      dt VARCHAR(10),\n" +
-                "      province VARCHAR(64) not null\n" +
-                ")\n" +
-                "DUPLICATE KEY(id)\n" +
-                "PARTITION BY LIST (province) (\n" +
-                "     PARTITION p1 VALUES IN (\"beijing\",\"chongqing\") ,\n" +
-                "     PARTITION p2 VALUES IN (\"guangdong\") \n" +
-                ")\n" +
-                "DISTRIBUTED BY RANDOM\n";
+                    "      id BIGINT,\n" +
+                    "      age SMALLINT,\n" +
+                    "      dt VARCHAR(10),\n" +
+                    "      province VARCHAR(64) not null\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(id)\n" +
+                    "PARTITION BY LIST (province) (\n" +
+                    "     PARTITION p1 VALUES IN (\"beijing\",\"chongqing\") ,\n" +
+                    "     PARTITION p2 VALUES IN (\"guangdong\") \n" +
+                    ")\n" +
+                    "DISTRIBUTED BY RANDOM\n";
         // table whose partitions have only single values
         T2 = "CREATE TABLE t2 (\n" +
-                "      id BIGINT,\n" +
-                "      age SMALLINT,\n" +
-                "      dt VARCHAR(10),\n" +
-                "      province VARCHAR(64) not null\n" +
-                ")\n" +
-                "DUPLICATE KEY(id)\n" +
-                "PARTITION BY LIST (province) (\n" +
-                "     PARTITION p1 VALUES IN (\"beijing\") ,\n" +
-                "     PARTITION p2 VALUES IN (\"guangdong\") \n" +
-                ")\n" +
-                "DISTRIBUTED BY RANDOM\n";
+                    "      id BIGINT,\n" +
+                    "      age SMALLINT,\n" +
+                    "      dt VARCHAR(10),\n" +
+                    "      province VARCHAR(64) not null\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(id)\n" +
+                    "PARTITION BY LIST (province) (\n" +
+                    "     PARTITION p1 VALUES IN (\"beijing\") ,\n" +
+                    "     PARTITION p2 VALUES IN (\"guangdong\") \n" +
+                    ")\n" +
+                    "DISTRIBUTED BY RANDOM\n";
         // table whose partitions have multi columns
         T3 = "CREATE TABLE t3 (\n" +
-                "      id BIGINT,\n" +
-                "      age SMALLINT,\n" +
-                "      dt VARCHAR(10) not null,\n" +
-                "      province VARCHAR(64) not null\n" +
-                ")\n" +
-                "DUPLICATE KEY(id)\n" +
-                "PARTITION BY LIST (province, dt) (\n" +
-                "     PARTITION p1 VALUES IN ((\"beijing\", \"2024-01-01\"))  ,\n" +
-                "     PARTITION p2 VALUES IN ((\"guangdong\", \"2024-01-01\")), \n" +
-                "     PARTITION p3 VALUES IN ((\"beijing\", \"2024-01-02\"))  ,\n" +
-                "     PARTITION p4 VALUES IN ((\"guangdong\", \"2024-01-02\")) \n" +
-                ")\n" +
-                "DISTRIBUTED BY RANDOM\n";
+                    "      id BIGINT,\n" +
+                    "      age SMALLINT,\n" +
+                    "      dt VARCHAR(10) not null,\n" +
+                    "      province VARCHAR(64) not null\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(id)\n" +
+                    "PARTITION BY LIST (province, dt) (\n" +
+                    "     PARTITION p1 VALUES IN ((\"beijing\", \"2024-01-01\"))  ,\n" +
+                    "     PARTITION p2 VALUES IN ((\"guangdong\", \"2024-01-01\")), \n" +
+                    "     PARTITION p3 VALUES IN ((\"beijing\", \"2024-01-02\"))  ,\n" +
+                    "     PARTITION p4 VALUES IN ((\"guangdong\", \"2024-01-02\")) \n" +
+                    ")\n" +
+                    "DISTRIBUTED BY RANDOM\n";
         // table with partition expression whose partitions have multiple values
         T4 = "CREATE TABLE t4 (\n" +
-                "      id BIGINT,\n" +
-                "      age SMALLINT,\n" +
-                "      dt VARCHAR(10),\n" +
-                "      province VARCHAR(64) not null\n" +
-                ")\n" +
-                "DUPLICATE KEY(id)\n" +
-                "PARTITION BY (province) \n" +
-                "DISTRIBUTED BY RANDOM\n";
+                    "      id BIGINT,\n" +
+                    "      age SMALLINT,\n" +
+                    "      dt VARCHAR(10),\n" +
+                    "      province VARCHAR(64) not null\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(id)\n" +
+                    "PARTITION BY (province) \n" +
+                    "DISTRIBUTED BY RANDOM\n";
         // table with partition expression whose partitions have multi columns
         T5 = "CREATE TABLE t5 (\n" +
-                "      id BIGINT,\n" +
-                "      age SMALLINT,\n" +
-                "      dt VARCHAR(10) not null,\n" +
-                "      province VARCHAR(64) not null\n" +
-                ")\n" +
-                "DUPLICATE KEY(id)\n" +
-                "PARTITION BY (province, dt) \n" +
-                "DISTRIBUTED BY RANDOM\n";
+                    "      id BIGINT,\n" +
+                    "      age SMALLINT,\n" +
+                    "      dt VARCHAR(10) not null,\n" +
+                    "      province VARCHAR(64) not null\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(id)\n" +
+                    "PARTITION BY (province, dt) \n" +
+                    "DISTRIBUTED BY RANDOM\n";
         // table with partition expression whose partitions have multi columns(nullable partition columns)
         T6 = "CREATE TABLE t6 (\n" +
-                "      id BIGINT,\n" +
-                "      age SMALLINT,\n" +
-                "      dt VARCHAR(10),\n" +
-                "      province VARCHAR(64)\n" +
-                ")\n" +
-                "DUPLICATE KEY(id)\n" +
-                "PARTITION BY (province, dt) \n" +
-                "DISTRIBUTED BY RANDOM\n";
+                    "      id BIGINT,\n" +
+                    "      age SMALLINT,\n" +
+                    "      dt VARCHAR(10),\n" +
+                    "      province VARCHAR(64)\n" +
+                    ")\n" +
+                    "DUPLICATE KEY(id)\n" +
+                    "PARTITION BY (province, dt) \n" +
+                    "DISTRIBUTED BY RANDOM\n";
     }
 
     @AfterClass
@@ -144,7 +144,7 @@ private ExecPlan getExecPlan(TaskRun taskRun) {
             initAndExecuteTaskRun(taskRun);
 
             PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor)
-                    taskRun.getProcessor();
+                        taskRun.getProcessor();
             MvTaskRunContext mvContext = processor.getMvContext();
             ExecPlan execPlan = mvContext.getExecPlan();
             return execPlan;
@@ -178,12 +178,12 @@ private void addListPartition(String tbl, String pName, String pVal) {
     }
 
     private String toPartitionVal(String val) {
-        return val == null ?  "NULL" : String.format("'%s'", val);
+        return val == null ? "NULL" : String.format("'%s'", val);
     }
 
     private void addListPartition(String tbl, String pName, String pVal1, String pVal2) {
         String addPartitionSql = String.format("ALTER TABLE %s ADD PARTITION %s VALUES IN ((%s, %s))", tbl, pName,
-                toPartitionVal(pVal1), toPartitionVal(pVal2));
+                    toPartitionVal(pVal1), toPartitionVal(pVal2));
         StatementBase stmt = SqlParser.parseSingleStatement(addPartitionSql, connectContext.getSessionVariable().getSqlMode());
         try {
             new StmtExecutor(connectContext, stmt).execute();
@@ -194,772 +194,794 @@ private void addListPartition(String tbl, String pName, String pVal1, String pVa
 
     @Test
     public void testRefreshNonPartitionedMV() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withTable(T2, () -> {
             starRocksAssert.withMaterializedView("create materialized view mv1\n" +
-                            "distributed by random \n" +
-                            "REFRESH DEFERRED MANUAL \n" +
-                            "as select dt, province, sum(age) from t2 group by dt, province;",
-                    (obj) -> {
-                        String mvName = (String) obj;
-                        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
-                        Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
-                        TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
-
-                        {
-                            // no partition has changed, no need to refresh
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            String insertSql = "insert into t2 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t2\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=2/2");
-
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(1, partitions.size());
-                            // refresh again, refreshed partitions should not be refreshed again.
-                            execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // add a new partition
-                            addListPartition("t2", "p3", "hangzhou");
-
-                            String insertSql = "INSERT INTO t2 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t2\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=3/3");
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(1, partitions.size());
-                        }
-                    });
+                                    "distributed by random \n" +
+                                    "REFRESH DEFERRED MANUAL \n" +
+                                    "as select dt, province, sum(age) from t2 group by dt, province;",
+                        (obj) -> {
+                            String mvName = (String) obj;
+                            MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                    .getTable(testDb.getFullName(), mvName));
+                            Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
+                            TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
+
+                            {
+                                // no partition has changed, no need to refresh
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                String insertSql = "insert into t2 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t2\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=2/2");
+
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(1, partitions.size());
+                                // refresh again, refreshed partitions should not be refreshed again.
+                                execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // add a new partition
+                                addListPartition("t2", "p3", "hangzhou");
+
+                                String insertSql = "INSERT INTO t2 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t2\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=3/3");
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(1, partitions.size());
+                            }
+                        });
         });
     }
 
     @Test
     public void testRefreshSingleColumnMVWithSingleValues() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withTable(T2, () -> {
             starRocksAssert.withMaterializedView("create materialized view mv1\n" +
-                            "partition by province \n" +
-                            "distributed by random \n" +
-                            "REFRESH DEFERRED MANUAL \n" +
-                            "properties ('partition_refresh_number' = '-1')" +
-                            "as select dt, province, sum(age) from t2 group by dt, province;",
-                    (obj) -> {
-                        String mvName = (String) obj;
-                        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
-                        Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
-                        TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
-
-                        {
-                            // no partition has changed, no need to refresh
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            String insertSql = "insert into t2 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t2\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/2");
-
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(2, partitions.size());
-                            // refresh again, refreshed partitions should not be refreshed again.
-                            execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // add a new partition
-                            addListPartition("t2", "p3", "hangzhou");
-
-                            String insertSql = "INSERT INTO t2 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t2\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/3");
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(3, partitions.size());
-                        }
-                    });
+                                    "partition by province \n" +
+                                    "distributed by random \n" +
+                                    "REFRESH DEFERRED MANUAL \n" +
+                                    "properties ('partition_refresh_number' = '-1')" +
+                                    "as select dt, province, sum(age) from t2 group by dt, province;",
+                        (obj) -> {
+                            String mvName = (String) obj;
+                            MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                    .getTable(testDb.getFullName(), mvName));
+                            Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
+                            TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
+
+                            {
+                                // no partition has changed, no need to refresh
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                String insertSql = "insert into t2 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t2\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/2");
+
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(2, partitions.size());
+                                // refresh again, refreshed partitions should not be refreshed again.
+                                execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // add a new partition
+                                addListPartition("t2", "p3", "hangzhou");
+
+                                String insertSql = "INSERT INTO t2 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t2\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/3");
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(3, partitions.size());
+                            }
+                        });
         });
     }
 
     @Test
     public void testRefreshSingleColumnWithMultiValues() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withTable(T1, () -> {
             starRocksAssert.withMaterializedView("create materialized view mv1\n" +
-                            "partition by province \n" +
-                            "distributed by random \n" +
-                            "REFRESH DEFERRED MANUAL \n" +
-                            "properties ('partition_refresh_number' = '-1')" +
-                            "as select dt, province, sum(age) from t1 group by dt, province;",
-                    (obj) -> {
-                        String mvName = (String) obj;
-                        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
-                        Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
-                        TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
-
-                        {
-                            // no partition has changed, no need to refresh
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            String insertSql = "insert into t1 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/2");
-
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(2, partitions.size());
-                            // refresh again, refreshed partitions should not be refreshed again.
-                            execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // add a new partition
-                            addListPartition("t1", "p3", "hangzhou");
-
-                            String insertSql = "INSERT INTO t1 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/3");
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(3, partitions.size());
-                        }
-                    });
+                                    "partition by province \n" +
+                                    "distributed by random \n" +
+                                    "REFRESH DEFERRED MANUAL \n" +
+                                    "properties ('partition_refresh_number' = '-1')" +
+                                    "as select dt, province, sum(age) from t1 group by dt, province;",
+                        (obj) -> {
+                            String mvName = (String) obj;
+                            MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                    .getTable(testDb.getFullName(), mvName));
+                            Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
+                            TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
+
+                            {
+                                // no partition has changed, no need to refresh
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                String insertSql = "insert into t1 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/2");
+
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(2, partitions.size());
+                                // refresh again, refreshed partitions should not be refreshed again.
+                                execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // add a new partition
+                                addListPartition("t1", "p3", "hangzhou");
+
+                                String insertSql = "INSERT INTO t1 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/3");
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(3, partitions.size());
+                            }
+                        });
         });
     }
 
     @Test
     public void testRefreshMultiColumnsMV1() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withTable(T3, () -> {
             starRocksAssert.withMaterializedView("create materialized view mv1\n" +
-                            "partition by province \n" +
-                            "distributed by random \n" +
-                            "REFRESH DEFERRED MANUAL \n" +
-                            "properties ('partition_refresh_number' = '-1')" +
-                            "as select dt, province, sum(age) from t3 group by dt, province;",
-                    (obj) -> {
-                        String mvName = (String) obj;
-                        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
-                        Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
-                        TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
-
-                        {
-                            // no partition has changed, no need to refresh
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            String insertSql = "insert into t3 partition(p1) values(1, 1, '2024-01-01', 'beijing');";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "  0:OlapScanNode\n" +
-                                    "     TABLE: t3\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=2/4");
-
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(2, partitions.size());
-                            // refresh again, refreshed partitions should not be refreshed again.
-                            execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            String insertSql = "insert into t3 partition(p1) values(1, 1, '2024-01-01', 'beijing');";
-                            executeInsertSql(connectContext, insertSql);
-                            insertSql = "insert into t3 partition(p3) values(1, 1, '2024-01-02', 'beijing');";
-                            executeInsertSql(connectContext, insertSql);
-
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t3\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=2/4");
-
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(2, partitions.size());
-                            // refresh again, refreshed partitions should not be refreshed again.
-                            execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // add a new partition
-                            addListPartition("t3", "p5", "hangzhou", "2022-01-01");
-                            String insertSql = "INSERT INTO t3 partition(p5) values(1, 1, '2022-01-01', 'hangzhou')";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t3\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/5");
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(3, partitions.size());
-                        }
-                    });
+                                    "partition by province \n" +
+                                    "distributed by random \n" +
+                                    "REFRESH DEFERRED MANUAL \n" +
+                                    "properties ('partition_refresh_number' = '-1')" +
+                                    "as select dt, province, sum(age) from t3 group by dt, province;",
+                        (obj) -> {
+                            String mvName = (String) obj;
+                            MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                    .getTable(testDb.getFullName(), mvName));
+                            Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
+                            TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
+
+                            {
+                                // no partition has changed, no need to refresh
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                String insertSql = "insert into t3 partition(p1) values(1, 1, '2024-01-01', 'beijing');";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "  0:OlapScanNode\n" +
+                                            "     TABLE: t3\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=2/4");
+
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(2, partitions.size());
+                                // refresh again, refreshed partitions should not be refreshed again.
+                                execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                String insertSql = "insert into t3 partition(p1) values(1, 1, '2024-01-01', 'beijing');";
+                                executeInsertSql(connectContext, insertSql);
+                                insertSql = "insert into t3 partition(p3) values(1, 1, '2024-01-02', 'beijing');";
+                                executeInsertSql(connectContext, insertSql);
+
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t3\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=2/4");
+
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(2, partitions.size());
+                                // refresh again, refreshed partitions should not be refreshed again.
+                                execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // add a new partition
+                                addListPartition("t3", "p5", "hangzhou", "2022-01-01");
+                                String insertSql = "INSERT INTO t3 partition(p5) values(1, 1, '2022-01-01', 'hangzhou')";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t3\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/5");
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(3, partitions.size());
+                            }
+                        });
         });
     }
 
     @Test
     public void testRefreshMultiColumnsMV2() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withTable(T3, () -> {
             starRocksAssert.withMaterializedView("create materialized view mv1\n" +
-                            "partition by dt \n" +
-                            "distributed by random \n" +
-                            "REFRESH DEFERRED MANUAL \n" +
-                            "properties ('partition_refresh_number' = '-1')" +
-                            "as select dt, province, sum(age) from t3 group by dt, province;",
-                    (obj) -> {
-                        String mvName = (String) obj;
-                        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
-                        Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
-                        TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
-
-                        {
-                            // no partition has changed, no need to refresh
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            String insertSql = "insert into t3 values (1, 1, '2024-01-01', 'beijing')," +
-                                    "(2, 20, '2024-01-01', 'guangdong'), (3, 30, '2024-01-02', 'guangdong');";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t3\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=4/4");
-
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(2, partitions.size());
-                            // refresh again, refreshed partitions should not be refreshed again.
-                            execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            String insertSql = "insert into t3 partition(p1) values(1, 1, '2024-01-01', 'beijing');";
-                            executeInsertSql(connectContext, insertSql);
-                            insertSql = "insert into t3 partition(p3) values(1, 1, '2024-01-02', 'beijing');";
-                            executeInsertSql(connectContext, insertSql);
-
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t3\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=4/4");
-
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(2, partitions.size());
-                            // refresh again, refreshed partitions should not be refreshed again.
-                            execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // add a new partition
-                            addListPartition("t3", "p5", "hangzhou", "2024-01-01");
-                            String insertSql = "INSERT INTO t3 partition(p5) values(1, 1, '2024-01-01', 'hangzhou')";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t3\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=3/5");
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(2, partitions.size());
-                        }
-                    });
+                                    "partition by dt \n" +
+                                    "distributed by random \n" +
+                                    "REFRESH DEFERRED MANUAL \n" +
+                                    "properties ('partition_refresh_number' = '-1')" +
+                                    "as select dt, province, sum(age) from t3 group by dt, province;",
+                        (obj) -> {
+                            String mvName = (String) obj;
+                            MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                    .getTable(testDb.getFullName(), mvName));
+                            Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
+                            TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
+
+                            {
+                                // no partition has changed, no need to refresh
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                String insertSql = "insert into t3 values (1, 1, '2024-01-01', 'beijing')," +
+                                            "(2, 20, '2024-01-01', 'guangdong'), (3, 30, '2024-01-02', 'guangdong');";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t3\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=4/4");
+
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(2, partitions.size());
+                                // refresh again, refreshed partitions should not be refreshed again.
+                                execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                String insertSql = "insert into t3 partition(p1) values(1, 1, '2024-01-01', 'beijing');";
+                                executeInsertSql(connectContext, insertSql);
+                                insertSql = "insert into t3 partition(p3) values(1, 1, '2024-01-02', 'beijing');";
+                                executeInsertSql(connectContext, insertSql);
+
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t3\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=4/4");
+
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(2, partitions.size());
+                                // refresh again, refreshed partitions should not be refreshed again.
+                                execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // add a new partition
+                                addListPartition("t3", "p5", "hangzhou", "2024-01-01");
+                                String insertSql = "INSERT INTO t3 partition(p5) values(1, 1, '2024-01-01', 'hangzhou')";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t3\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=3/5");
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(2, partitions.size());
+                            }
+                        });
         });
     }
 
     @Test
     public void testRefreshSingleColumnMVWithPartitionExpr() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withTable(T4, () -> {
             starRocksAssert.withMaterializedView("create materialized view mv1\n" +
-                            "partition by province \n" +
-                            "distributed by random \n" +
-                            "REFRESH DEFERRED MANUAL \n" +
-                            "properties ('partition_refresh_number' = '-1')" +
-                            "as select dt, province, sum(age) from t4 group by dt, province;",
-                    (obj) -> {
-                        String mvName = (String) obj;
-                        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
-                        Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
-                        TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
-
-                        {
-                            // no partition has changed, no need to refresh
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            addListPartition("t4", "p1", "beijing");
-                            String insertSql = "insert into t4 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t4\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/2");
-
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(1, partitions.size());
-                            // refresh again, refreshed partitions should not be refreshed again.
-                            execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // add a new partition
-                            addListPartition("t4", "p3", "hangzhou");
-
-                            String insertSql = "INSERT INTO t4 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t4\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/3");
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(2, partitions.size());
-                        }
-                    });
+                                    "partition by province \n" +
+                                    "distributed by random \n" +
+                                    "REFRESH DEFERRED MANUAL \n" +
+                                    "properties ('partition_refresh_number' = '-1')" +
+                                    "as select dt, province, sum(age) from t4 group by dt, province;",
+                        (obj) -> {
+                            String mvName = (String) obj;
+                            MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                    .getTable(testDb.getFullName(), mvName));
+                            Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
+                            TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
+
+                            {
+                                // no partition has changed, no need to refresh
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                addListPartition("t4", "p1", "beijing");
+                                String insertSql = "insert into t4 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t4\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/2");
+
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(1, partitions.size());
+                                // refresh again, refreshed partitions should not be refreshed again.
+                                execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // add a new partition
+                                addListPartition("t4", "p3", "hangzhou");
+
+                                String insertSql = "INSERT INTO t4 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t4\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/3");
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(2, partitions.size());
+                            }
+                        });
         });
     }
 
     @Test
     public void testRefreshMultiColumnsMVWithPartitionExpr() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withTable(T5, () -> {
             starRocksAssert.withMaterializedView("create materialized view mv1\n" +
-                            "partition by province \n" +
-                            "distributed by random \n" +
-                            "REFRESH DEFERRED MANUAL \n" +
-                            "properties ('partition_refresh_number' = '-1')" +
-                            "as select dt, province, sum(age) from t5 group by dt, province;",
-                    (obj) -> {
-                        String mvName = (String) obj;
-                        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
-                        Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
-                        TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
-
-                        {
-                            // no partition has changed, no need to refresh
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // add a new partition
-                            addListPartition("t5", "p1", "beijing", "2022-01-01");
-                            String insertSql = "insert into t5 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t5\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/2");
-
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(1, partitions.size());
-                            Assert.assertTrue(partitions.iterator().next().getName().equals("p1"));
-                            // refresh again, refreshed partitions should not be refreshed again.
-                            execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            String insertSql = "insert into t5 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
-                            executeInsertSql(connectContext, insertSql);
-                            addListPartition("t5", "p2", "beijing", "2022-01-02");
-                            insertSql = "insert into t5 partition(p2) values(1, 1, '2021-12-02', 'beijing');";
-                            executeInsertSql(connectContext, insertSql);
-
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t5\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=2/3");
-
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(1, partitions.size());
-                            Assert.assertTrue(partitions.iterator().next().getName().equals("p1"));
-                            // refresh again, refreshed partitions should not be refreshed again.
-                            execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // add a new partition
-                            addListPartition("t5", "p5", "hangzhou", "2022-01-01");
-                            String insertSql = "INSERT INTO t5 partition(p5) values(1, 1, '2022-01-01', 'hangzhou')";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t5\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/4");
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(2, partitions.size());
-                        }
-                    });
+                                    "partition by province \n" +
+                                    "distributed by random \n" +
+                                    "REFRESH DEFERRED MANUAL \n" +
+                                    "properties ('partition_refresh_number' = '-1')" +
+                                    "as select dt, province, sum(age) from t5 group by dt, province;",
+                        (obj) -> {
+                            String mvName = (String) obj;
+                            MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                    .getTable(testDb.getFullName(), mvName));
+                            Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
+                            TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
+
+                            {
+                                // no partition has changed, no need to refresh
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // add a new partition
+                                addListPartition("t5", "p1", "beijing", "2022-01-01");
+                                String insertSql = "insert into t5 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t5\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/2");
+
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(1, partitions.size());
+                                Assert.assertTrue(partitions.iterator().next().getName().equals("p1"));
+                                // refresh again, refreshed partitions should not be refreshed again.
+                                execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                String insertSql = "insert into t5 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
+                                executeInsertSql(connectContext, insertSql);
+                                addListPartition("t5", "p2", "beijing", "2022-01-02");
+                                insertSql = "insert into t5 partition(p2) values(1, 1, '2021-12-02', 'beijing');";
+                                executeInsertSql(connectContext, insertSql);
+
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t5\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=2/3");
+
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(1, partitions.size());
+                                Assert.assertTrue(partitions.iterator().next().getName().equals("p1"));
+                                // refresh again, refreshed partitions should not be refreshed again.
+                                execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // add a new partition
+                                addListPartition("t5", "p5", "hangzhou", "2022-01-01");
+                                String insertSql = "INSERT INTO t5 partition(p5) values(1, 1, '2022-01-01', 'hangzhou')";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t5\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/4");
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(2, partitions.size());
+                            }
+                        });
         });
     }
 
     @Test
     public void testRefreshMultiBaseTablesWithSingleColumn() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withTables(ImmutableList.of(T2, T4), () -> {
             starRocksAssert.withMaterializedView("create materialized view mv1\n" +
-                            "partition by province \n" +
-                            "distributed by random \n" +
-                            "REFRESH DEFERRED MANUAL \n" +
-                            "properties ('partition_refresh_number' = '-1')" +
-                            "as " +
-                            "   select dt, province, sum(age) from t2 group by dt, province " +
-                            " union all " +
-                            "   select dt, province, sum(age) from t4 group by dt, province;",
-                    (obj) -> {
-                        String mvName = (String) obj;
-                        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
-                        Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
-                        TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
-
-                        {
-                            // no partition has changed, no need to refresh
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // only one table has updated
-                            String insertSql = "insert into t2 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "  1:OlapScanNode\n" +
-                                    "     TABLE: t2\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/2\n" +
-                                    "     rollup: t2");
-                            PlanTestBase.assertContains(plan, "     TABLE: t4\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/1\n" +
-                                    "     rollup: t4");
-
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(2, partitions.size());
-                            // refresh again, refreshed partitions should not be refreshed again.
-                            execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // t2 add a new partition
-                            addListPartition("t2", "p3", "hangzhou");
-                            String insertSql = "INSERT INTO t2 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
-                            executeInsertSql(connectContext, insertSql);
-
-                            // t4 add a new partition
-                            addListPartition("t4", "p3", "hangzhou");
-                            insertSql = "INSERT INTO t4 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
-                            executeInsertSql(connectContext, insertSql);
-
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t2\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/3");
-                            PlanTestBase.assertContains(plan, "     TABLE: t4\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/2");
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(3, partitions.size());
-                        }
-                    });
+                                    "partition by province \n" +
+                                    "distributed by random \n" +
+                                    "REFRESH DEFERRED MANUAL \n" +
+                                    "properties ('partition_refresh_number' = '-1')" +
+                                    "as " +
+                                    "   select dt, province, sum(age) from t2 group by dt, province " +
+                                    " union all " +
+                                    "   select dt, province, sum(age) from t4 group by dt, province;",
+                        (obj) -> {
+                            String mvName = (String) obj;
+                            MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                    .getTable(testDb.getFullName(), mvName));
+                            Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
+                            TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
+
+                            {
+                                // no partition has changed, no need to refresh
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // only one table has updated
+                                String insertSql = "insert into t2 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "  1:OlapScanNode\n" +
+                                            "     TABLE: t2\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/2\n" +
+                                            "     rollup: t2");
+                                PlanTestBase.assertContains(plan, "     TABLE: t4\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/1\n" +
+                                            "     rollup: t4");
+
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(2, partitions.size());
+                                // refresh again, refreshed partitions should not be refreshed again.
+                                execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // t2 add a new partition
+                                addListPartition("t2", "p3", "hangzhou");
+                                String insertSql = "INSERT INTO t2 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
+                                executeInsertSql(connectContext, insertSql);
+
+                                // t4 add a new partition
+                                addListPartition("t4", "p3", "hangzhou");
+                                insertSql = "INSERT INTO t4 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
+                                executeInsertSql(connectContext, insertSql);
+
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t2\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/3");
+                                PlanTestBase.assertContains(plan, "     TABLE: t4\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/2");
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(3, partitions.size());
+                            }
+                        });
         });
     }
 
     @Test
     public void testRefreshMultiBaseTablesWithMultiColumns() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withTables(ImmutableList.of(T1, T5), () -> {
             starRocksAssert.withMaterializedView("create materialized view mv1\n" +
-                            "partition by province \n" +
-                            "distributed by random \n" +
-                            "REFRESH DEFERRED MANUAL \n" +
-                            "properties ('partition_refresh_number' = '-1') \n" +
-                            "as select dt, province, sum(age) from t1 group by dt, province \n" +
-                            " union all\n" +
-                            " select dt, province, sum(age) from t5 group by dt, province",
-                    (obj) -> {
-                        String mvName = (String) obj;
-                        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
-                        Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
-                        TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
-
-                        {
-                            // no partition has changed, no need to refresh
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // only t1 has updated
-                            String insertSql = "insert into t1 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/2\n" +
-                                    "     rollup: t1");
-
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(2, partitions.size());
-                            // refresh again, refreshed partitions should not be refreshed again.
-                            execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // add a new partition
-                            addListPartition("t1", "p3", "hangzhou");
-
-                            String insertSql = "INSERT INTO t1 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/3");
-                            PlanTestBase.assertContains(plan, "     TABLE: t5\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/1\n" +
-                                    "     rollup: t5");
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(3, partitions.size());
-                        }
-
-                        {
-                            // t1 add a new partition
-                            String insertSql = "INSERT INTO t1 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
-                            executeInsertSql(connectContext, insertSql);
-                            // t5 add a new partition
-                            addListPartition("t5", "p1", "beijing", "2022-01-01");
-                            insertSql = "insert into t5 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
-                            executeInsertSql(connectContext, insertSql);
-
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=2/3\n" +
-                                    "     rollup: t1");
-                            PlanTestBase.assertContains(plan, "     TABLE: t5\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/2");
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(3, partitions.size());
-                        }
-                    });
+                                    "partition by province \n" +
+                                    "distributed by random \n" +
+                                    "REFRESH DEFERRED MANUAL \n" +
+                                    "properties ('partition_refresh_number' = '-1') \n" +
+                                    "as select dt, province, sum(age) from t1 group by dt, province \n" +
+                                    " union all\n" +
+                                    " select dt, province, sum(age) from t5 group by dt, province",
+                        (obj) -> {
+                            String mvName = (String) obj;
+                            MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                    .getTable(testDb.getFullName(), mvName));
+                            Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
+                            TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
+
+                            {
+                                // no partition has changed, no need to refresh
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // only t1 has updated
+                                String insertSql = "insert into t1 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/2\n" +
+                                            "     rollup: t1");
+
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(2, partitions.size());
+                                // refresh again, refreshed partitions should not be refreshed again.
+                                execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // add a new partition
+                                addListPartition("t1", "p3", "hangzhou");
+
+                                String insertSql = "INSERT INTO t1 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/3");
+                                PlanTestBase.assertContains(plan, "     TABLE: t5\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/1\n" +
+                                            "     rollup: t5");
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(3, partitions.size());
+                            }
+
+                            {
+                                // t1 add a new partition
+                                String insertSql = "INSERT INTO t1 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
+                                executeInsertSql(connectContext, insertSql);
+                                // t5 add a new partition
+                                addListPartition("t5", "p1", "beijing", "2022-01-01");
+                                insertSql = "insert into t5 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
+                                executeInsertSql(connectContext, insertSql);
+
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=2/3\n" +
+                                            "     rollup: t1");
+                                PlanTestBase.assertContains(plan, "     TABLE: t5\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/2");
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(3, partitions.size());
+                            }
+                        });
         });
     }
 
     @Test
     public void testRefreshJoinWithMultiColumns1() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withTables(ImmutableList.of(T1, T5), () -> {
             starRocksAssert.withMaterializedView("create materialized view mv1\n" +
-                            "partition by province \n" +
-                            "distributed by random \n" +
-                            "REFRESH DEFERRED MANUAL \n" +
-                            "properties ('partition_refresh_number' = '-1') \n" +
-                            "as select t1.dt, t5.province, sum(t5.age) from t1 join t5 on t1.province=t5.province " +
-                            "group by t1.dt, t5.province \n",
-                    (obj) -> {
-                        String mvName = (String) obj;
-                        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
-                        Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
-                        TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
-
-                        {
-                            // no partition has changed, no need to refresh
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // only t1 has updated
-                            String insertSql = "insert into t1 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/2\n" +
-                                    "     rollup: t1");
-
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(2, partitions.size());
-                            // refresh again, refreshed partitions should not be refreshed again.
-                            execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // add a new partition
-                            addListPartition("t1", "p3", "hangzhou");
-
-                            String insertSql = "INSERT INTO t1 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/3");
-                            PlanTestBase.assertContains(plan, "     TABLE: t5\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/1\n" +
-                                    "     rollup: t5");
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(3, partitions.size());
-                        }
-
-                        {
-                            // t1 add a new partition
-                            String insertSql = "INSERT INTO t1 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
-                            executeInsertSql(connectContext, insertSql);
-                            // t5 add a new partition
-                            addListPartition("t5", "p1", "beijing", "2022-01-01");
-                            insertSql = "insert into t5 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
-                            executeInsertSql(connectContext, insertSql);
-
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=2/3");
-                            PlanTestBase.assertContains(plan, "     TABLE: t5\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/2");
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(3, partitions.size());
-                        }
-                    });
+                                    "partition by province \n" +
+                                    "distributed by random \n" +
+                                    "REFRESH DEFERRED MANUAL \n" +
+                                    "properties ('partition_refresh_number' = '-1') \n" +
+                                    "as select t1.dt, t5.province, sum(t5.age) from t1 join t5 on t1.province=t5.province " +
+                                    "group by t1.dt, t5.province \n",
+                        (obj) -> {
+                            String mvName = (String) obj;
+                            MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                    .getTable(testDb.getFullName(), mvName));
+                            Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
+                            TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
+
+                            {
+                                // no partition has changed, no need to refresh
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // only t1 has updated
+                                String insertSql = "insert into t1 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/2\n" +
+                                            "     rollup: t1");
+
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(2, partitions.size());
+                                // refresh again, refreshed partitions should not be refreshed again.
+                                execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // add a new partition
+                                addListPartition("t1", "p3", "hangzhou");
+
+                                String insertSql = "INSERT INTO t1 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/3");
+                                PlanTestBase.assertContains(plan, "     TABLE: t5\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/1\n" +
+                                            "     rollup: t5");
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(3, partitions.size());
+                            }
+
+                            {
+                                // t1 add a new partition
+                                String insertSql = "INSERT INTO t1 partition(p3) values(1, 1, '2022-01-01', 'hangzhou')";
+                                executeInsertSql(connectContext, insertSql);
+                                // t5 add a new partition
+                                addListPartition("t5", "p1", "beijing", "2022-01-01");
+                                insertSql = "insert into t5 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
+                                executeInsertSql(connectContext, insertSql);
+
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=2/3");
+                                PlanTestBase.assertContains(plan, "     TABLE: t5\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/2");
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(3, partitions.size());
+                            }
+                        });
         });
     }
 
     @Test
     public void testRefreshMVWithMultiNulllalbeColumns() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withTable(T6, () -> {
             starRocksAssert.withMaterializedView("create materialized view mv1\n" +
-                            "partition by province \n" +
-                            "distributed by random \n" +
-                            "REFRESH DEFERRED MANUAL \n" +
-                            "properties ('partition_refresh_number' = '-1')" +
-                            "as select dt, province, sum(age) from t6 group by dt, province;",
-                    (obj) -> {
-                        String mvName = (String) obj;
-                        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
-                        Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
-                        TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
-
-                        {
-                            // no partition has changed, no need to refresh
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // add a new partition
-                            addListPartition("t6", "p1", "beijing", "2022-01-01");
-                            String insertSql = "insert into t6 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t6\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/2");
-
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(1, partitions.size());
-                            Assert.assertTrue(partitions.iterator().next().getName().equals("p1"));
-                            // refresh again, refreshed partitions should not be refreshed again.
-                            execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            String insertSql = "insert into t6 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
-                            executeInsertSql(connectContext, insertSql);
-                            addListPartition("t6", "p2", "beijing", "2022-01-02");
-                            insertSql = "insert into t6 partition(p2) values(1, 1, '2021-12-02', 'beijing');";
-                            executeInsertSql(connectContext, insertSql);
-
-                            ExecPlan execPlan = getExecPlan(taskRun);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t6\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=2/3");
-
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(1, partitions.size());
-                            Assert.assertTrue(partitions.iterator().next().getName().equals("p1"));
-                            // refresh again, refreshed partitions should not be refreshed again.
-                            execPlan = getExecPlan(taskRun);
-                            Assert.assertTrue(execPlan == null);
-                        }
-
-                        {
-                            // add a new partition
-                            addListPartition("t6", "p5", "hangzhou", "2022-01-01");
-                            String insertSql = "INSERT INTO t6 partition(p5) values(1, 1, '2022-01-01', 'hangzhou')";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "     TABLE: t6\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/4");
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(2, partitions.size());
-                        }
-
-                        {
-                            // add a null partition
-                            addListPartition("t6", "p6", null, null);
-                            String insertSql = "INSERT INTO t6 partition(p6) values(1, 1, NULL, NULL)";
-                            ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
-                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                            PlanTestBase.assertContains(plan, "    TABLE: t6\n" +
-                                    "     PREAGGREGATION: ON\n" +
-                                    "     partitions=1/5");
-                            Collection<Partition> partitions = materializedView.getPartitions();
-                            Assert.assertEquals(3, partitions.size());
-                        }
-                    });
+                                    "partition by province \n" +
+                                    "distributed by random \n" +
+                                    "REFRESH DEFERRED MANUAL \n" +
+                                    "properties ('partition_refresh_number' = '-1')" +
+                                    "as select dt, province, sum(age) from t6 group by dt, province;",
+                        (obj) -> {
+                            String mvName = (String) obj;
+                            MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                    .getTable(testDb.getFullName(), mvName));
+                            Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
+                            TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
+
+                            {
+                                // no partition has changed, no need to refresh
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // add a new partition
+                                addListPartition("t6", "p1", "beijing", "2022-01-01");
+                                String insertSql = "insert into t6 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t6\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/2");
+
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(1, partitions.size());
+                                Assert.assertTrue(partitions.iterator().next().getName().equals("p1"));
+                                // refresh again, refreshed partitions should not be refreshed again.
+                                execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                String insertSql = "insert into t6 partition(p1) values(1, 1, '2021-12-01', 'beijing');";
+                                executeInsertSql(connectContext, insertSql);
+                                addListPartition("t6", "p2", "beijing", "2022-01-02");
+                                insertSql = "insert into t6 partition(p2) values(1, 1, '2021-12-02', 'beijing');";
+                                executeInsertSql(connectContext, insertSql);
+
+                                ExecPlan execPlan = getExecPlan(taskRun);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t6\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=2/3");
+
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(1, partitions.size());
+                                Assert.assertTrue(partitions.iterator().next().getName().equals("p1"));
+                                // refresh again, refreshed partitions should not be refreshed again.
+                                execPlan = getExecPlan(taskRun);
+                                Assert.assertTrue(execPlan == null);
+                            }
+
+                            {
+                                // add a new partition
+                                addListPartition("t6", "p5", "hangzhou", "2022-01-01");
+                                String insertSql = "INSERT INTO t6 partition(p5) values(1, 1, '2022-01-01', 'hangzhou')";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "     TABLE: t6\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/4");
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(2, partitions.size());
+                            }
+
+                            {
+                                // add a null partition
+                                addListPartition("t6", "p6", null, null);
+                                String insertSql = "INSERT INTO t6 partition(p6) values(1, 1, NULL, NULL)";
+                                ExecPlan execPlan = getExecPlanAfterInsert(taskRun, insertSql);
+                                String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                                PlanTestBase.assertContains(plan, "    TABLE: t6\n" +
+                                            "     PREAGGREGATION: ON\n" +
+                                            "     partitions=1/5");
+                                Collection<Partition> partitions = materializedView.getPartitions();
+                                Assert.assertEquals(3, partitions.size());
+                            }
+                        });
         });
     }
 }
\ No newline at end of file
diff --git a/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorHiveTest.java b/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorHiveTest.java
index 5743bd650dde94..485895906e84c5 100644
--- a/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorHiveTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorHiveTest.java
@@ -149,8 +149,9 @@ public void testAutoRefreshPartitionLimitWithHiveTable() throws Exception {
                 "\"storage_medium\" = \"HDD\"\n" +
                 ")\n" +
                 "AS SELECT `l_orderkey`, `l_suppkey`, `l_shipdate`  FROM `hive0`.`partitioned_db`.`lineitem_par` as a;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_parttbl_mv1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_parttbl_mv1"));
         materializedView.getTableProperty().setAutoRefreshPartitionsLimit(2);
 
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
@@ -194,8 +195,9 @@ public void testAutoRefreshPartitionLimitWithHiveTable() throws Exception {
 
     @Test
     public void testRefreshWithHiveTableJoin() throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_join_mv"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_join_mv"));
 
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -229,8 +231,9 @@ public void testAutoPartitionRefreshWithPartitionChanged() throws Exception {
                         "\"storage_medium\" = \"HDD\"\n" +
                         ")\n" +
                         "AS SELECT `l_orderkey`, `l_suppkey`, `l_shipdate`  FROM `hive0`.`partitioned_db`.`lineitem_par` as a;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_parttbl_mv1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_parttbl_mv1"));
 
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -274,8 +277,9 @@ public void testAutoPartitionRefreshWithHiveTableJoin1() throws Exception {
                 "AS SELECT t1.c1, t1.c2, t1_par.par_col, t1_par.par_date FROM `hive0`.`partitioned_db`.`t1` join " +
                 "`hive0`.`partitioned_db`.`t1_par` using (par_col)");
 
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_join_mv1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_join_mv1"));
 
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -323,8 +327,9 @@ public void testAutoPartitionRefreshWithHiveTableJoin2() throws Exception {
                 "AS SELECT `l_orderkey`, `l_suppkey`, `l_shipdate`,`o_custkey` FROM `hive0`.`partitioned_db`.`lineitem_par` " +
                 "as a join `hive0`.`tpch`.`orders` on l_orderkey = o_orderkey");
 
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_join_mv2"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_join_mv2"));
 
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -371,8 +376,9 @@ public void testAutoPartitionRefreshWithUnPartitionedHiveTable() throws Exceptio
                 ")\n" +
                 "AS SELECT `n_nationkey`, `n_name`, `n_comment`  FROM `hive0`.`tpch`.`nation`;");
 
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_tbl_mv1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_tbl_mv1"));
 
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -414,8 +420,9 @@ public void testAutoPartitionRefreshWithPartitionedHiveTable1() throws Exception
                 "\"storage_medium\" = \"HDD\"\n" +
                 ")\n" +
                 "AS SELECT `l_orderkey`, `l_suppkey`, `l_shipdate`  FROM `hive0`.`partitioned_db`.`lineitem_par` as a;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_parttbl_mv1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_parttbl_mv1"));
 
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -464,8 +471,9 @@ public void testAutoPartitionRefreshWithPartitionedHiveTable2() throws Exception
                 "\"storage_medium\" = \"HDD\"\n" +
                 ")\n" +
                 "AS SELECT `l_orderkey`, `l_suppkey`, `l_shipdate`  FROM `hive0`.`partitioned_db`.`lineitem_par` as a;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_tbl_mv2"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_tbl_mv2"));
 
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -509,8 +517,9 @@ public void testAutoPartitionRefreshWithPartitionedHiveTableJoinInternalTable()
                         ")\n" +
                         "AS SELECT `l_orderkey`, `l_suppkey`, `l_shipdate`  FROM `hive0`.`partitioned_db`.`lineitem_par` as a" +
                         " join test.tbl1 b on a.l_suppkey=b.k2;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_join_internal_mv"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_join_internal_mv"));
 
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -554,8 +563,9 @@ public void testPartitionRefreshWithUpperCaseTable() throws Exception {
                 ")\n" +
                 "AS SELECT `l_orderkey`, `l_suppkey`, `l_shipdate`  FROM `hive0`.`partitioned_db`.`LINEITEM_PAR` as " +
                 "`LINEITEM_PAR_ALIAS`;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_parttbl_mv1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_parttbl_mv1"));
 
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -604,8 +614,9 @@ public void testPartitionRefreshWithUpperCaseDb() throws Exception {
                 ")\n" +
                 "AS SELECT `l_orderkey`, `l_suppkey`, `l_shipdate`  FROM `hive0`.`partitioned_DB`.`LINEITEM_PAR` as " +
                 "`LINEITEM_PAR_ALIAS`;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_parttbl_mv1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_parttbl_mv1"));
 
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -655,8 +666,9 @@ public void testPartitionRefreshWithLowerCase() throws Exception {
                         "\"storage_medium\" = \"HDD\"\n" +
                         ")\n" +
                         "AS SELECT c1, c2, par_col FROM `hive0`.`partitioned_db2`.`t2`;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_parttbl_mv1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_parttbl_mv1"));
 
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -691,8 +703,9 @@ public void testPartitionRefreshWithLowerCase() throws Exception {
 
     @Test
     public void testRangePartitionRefreshWithHiveTable() throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_parttbl_mv"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_parttbl_mv"));
         HashMap<String, String> taskRunProperties = new HashMap<>();
         taskRunProperties.put(PARTITION_START, "1998-01-01");
         taskRunProperties.put(TaskRun.PARTITION_END, "1998-01-03");
@@ -718,8 +731,9 @@ public void testRangePartitionRefreshWithHiveTable() throws Exception {
 
     @Test
     public void testRefreshPartitionWithMulParColumnsHiveTable1() throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_mul_parttbl_mv1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_mul_parttbl_mv1"));
         Map<String, String> mvProperties = Maps.newHashMap();
         mvProperties.put(PARTITION_START, "1998-01-01");
         mvProperties.put(PARTITION_END, "1998-01-03");
@@ -740,8 +754,9 @@ public void testRefreshPartitionWithMulParColumnsHiveTable1() throws Exception {
 
     @Test
     public void testRefreshPartitionWithMulParColumnsHiveTable2() throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_mul_parttbl_mv2"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_mul_parttbl_mv2"));
         Map<String, String> mvProperties = Maps.newHashMap();
         mvProperties.put(PARTITION_START, "2020-01-01");
         mvProperties.put(PARTITION_END, "2020-01-03");
@@ -762,7 +777,7 @@ public void testRefreshPartitionWithMulParColumnsHiveTable2() throws Exception {
 
     @Test
     public void testHivePartitionPruneNonRefBaseTable1() throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withMaterializedView(
                 "CREATE MATERIALIZED VIEW `test`.`hive_partition_prune_non_ref_tables2`\n" +
                         "COMMENT \"MATERIALIZED_VIEW\"\n" +
@@ -778,7 +793,8 @@ public void testHivePartitionPruneNonRefBaseTable1() throws Exception {
                         "`hive0`.`partitioned_db`.`part_tbl2` using (par_date)");
 
         MaterializedView materializedView =
-                ((MaterializedView) testDb.getTable("hive_partition_prune_non_ref_tables2"));
+                ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(testDb.getFullName(), "hive_partition_prune_non_ref_tables2"));
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
 
@@ -891,7 +907,7 @@ public void testHivePartitionPruneNonRefBaseTable1() throws Exception {
 
     @Test
     public void testHivePartitionPruneNonRefBaseTable2() throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withMaterializedView(
                 "CREATE MATERIALIZED VIEW `test`.`hive_partition_prune_non_ref_tables1`\n" +
                         "COMMENT \"MATERIALIZED_VIEW\"\n" +
@@ -907,7 +923,8 @@ public void testHivePartitionPruneNonRefBaseTable2() throws Exception {
                         "`hive0`.`partitioned_db`.`t1_par` using (par_col)");
 
         MaterializedView materializedView =
-                ((MaterializedView) testDb.getTable("hive_partition_prune_non_ref_tables1"));
+                ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(testDb.getFullName(), "hive_partition_prune_non_ref_tables1"));
 
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -1000,7 +1017,7 @@ public void testHivePartitionPruneNonRefBaseTable2() throws Exception {
 
     @Test
     public void testHivePartitionPruneNonRefBaseTable3() throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withTable("CREATE TABLE `test_partition_prune_tbl1` (\n" +
                 "`k1` date,\n" +
                 "`k2` int,\n" +
@@ -1034,7 +1051,8 @@ public void testHivePartitionPruneNonRefBaseTable3() throws Exception {
                 "      FROM test_partition_prune_tbl1 join test_partition_prune_tbl2 on " +
                 " test_partition_prune_tbl1.k1=test_partition_prune_tbl2.k1;");
 
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("partition_prune_mv1"));
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "partition_prune_mv1"));
 
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
 
@@ -1118,8 +1136,9 @@ public void testCancelRefreshMV() throws Exception {
                         "\"storage_medium\" = \"HDD\"\n" +
                         ")\n" +
                         "AS SELECT `l_orderkey`, `l_suppkey`, `l_shipdate`  FROM `hive0`.`partitioned_db`.`lineitem_par` as a;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("hive_parttbl_mv1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "hive_parttbl_mv1"));
 
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
@@ -1143,8 +1162,9 @@ public void testDropBaseVersionMetaOfExternalTable() throws Exception {
                 "refresh async every (interval 1 day)\n" +
                 "as SELECT `l_orderkey`, `l_suppkey`, `l_shipdate`  FROM `hive0`.`partitioned_db`.`lineitem_par` as a;");
 
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView mv = ((MaterializedView) testDb.getTable("test_drop_partition_mv1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView mv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "test_drop_partition_mv1"));
         Map<BaseTableInfo, Map<String, MaterializedView.BasePartitionInfo>> versionMap =
                 mv.getRefreshScheme().getAsyncRefreshContext().getBaseTableInfoVisibleVersionMap();
         Map<String, Set<String>> mvPartitionNameRefBaseTablePartitionMap =
diff --git a/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorIcebergTest.java b/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorIcebergTest.java
index 3162cf54b58c6d..5faed2b0f44067 100644
--- a/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorIcebergTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorIcebergTest.java
@@ -68,7 +68,7 @@ public void after() throws Exception {
     }
 
     private static void triggerRefreshMv(Database testDb, MaterializedView partitionedMaterializedView)
-            throws Exception {
+                throws Exception {
         Task task = TaskBuilder.buildMvTask(partitionedMaterializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
         initAndExecuteTaskRun(taskRun);
@@ -77,31 +77,32 @@ private static void triggerRefreshMv(Database testDb, MaterializedView partition
     @Test
     public void testCreateNonPartitionedMVForIceberg() throws Exception {
         starRocksAssert.useDatabase("test")
-                .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`iceberg_mv1` " +
-                        "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
-                        "REFRESH DEFERRED MANUAL\n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\",\n" +
-                        "\"storage_medium\" = \"HDD\"\n" +
-                        ")\n" +
-                        "AS SELECT id, data, date  FROM `iceberg0`.`unpartitioned_db`.`t0` as a;")
-                .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`iceberg_mv2` " +
-                        "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
-                        "REFRESH DEFERRED MANUAL\n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\",\n" +
-                        "\"storage_medium\" = \"HDD\"\n" +
-                        ")\n" +
-                        "AS SELECT id, data, date  FROM `iceberg0`.`partitioned_db`.`t1` as a;");
+                    .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`iceberg_mv1` " +
+                                "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
+                                "REFRESH DEFERRED MANUAL\n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\",\n" +
+                                "\"storage_medium\" = \"HDD\"\n" +
+                                ")\n" +
+                                "AS SELECT id, data, date  FROM `iceberg0`.`unpartitioned_db`.`t0` as a;")
+                    .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`iceberg_mv2` " +
+                                "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
+                                "REFRESH DEFERRED MANUAL\n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\",\n" +
+                                "\"storage_medium\" = \"HDD\"\n" +
+                                ")\n" +
+                                "AS SELECT id, data, date  FROM `iceberg0`.`partitioned_db`.`t1` as a;");
 
         // Partitioned base table
         {
             String mvName = "iceberg_mv2";
-            Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-            MaterializedView mv = ((MaterializedView) testDb.getTable(mvName));
+            Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+            MaterializedView mv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(testDb.getFullName(), mvName));
             refreshMVRange(mvName, true);
             List<String> partitionNames = mv.getPartitions().stream().map(Partition::getName)
-                    .sorted().collect(Collectors.toList());
+                        .sorted().collect(Collectors.toList());
             Assert.assertEquals(ImmutableList.of(mvName), partitionNames);
             String querySql = "SELECT id, data, date  FROM `iceberg0`.`partitioned_db`.`t1`";
             starRocksAssert.query(querySql).explainContains(mvName);
@@ -111,11 +112,12 @@ public void testCreateNonPartitionedMVForIceberg() throws Exception {
         // Non-Partitioned base table
         {
             String mvName = "iceberg_mv1";
-            Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-            MaterializedView mv = ((MaterializedView) testDb.getTable(mvName));
+            Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+            MaterializedView mv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                        .getTable(testDb.getFullName(), mvName));
             refreshMVRange(mvName, true);
             List<String> partitionNames = mv.getPartitions().stream().map(Partition::getName)
-                    .sorted().collect(Collectors.toList());
+                        .sorted().collect(Collectors.toList());
             Assert.assertEquals(ImmutableList.of(mvName), partitionNames);
 
             // test rewrite
@@ -129,55 +131,56 @@ public void testCreateNonPartitionedMVForIceberg() throws Exception {
     public void testCreatePartitionedMVForIceberg() throws Exception {
         String mvName = "iceberg_parttbl_mv1";
         starRocksAssert.useDatabase("test")
-                .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`iceberg_parttbl_mv1`\n" +
-                        "PARTITION BY str2date(`date`, '%Y-%m-%d')\n" +
-                        "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
-                        "REFRESH DEFERRED MANUAL\n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\",\n" +
-                        "\"storage_medium\" = \"HDD\"\n" +
-                        ")\n" +
-                        "AS SELECT id, data, date  FROM `iceberg0`.`partitioned_db`.`t1` as a;");
-
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView partitionedMaterializedView = ((MaterializedView) testDb.getTable("iceberg_parttbl_mv1"));
+                    .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`iceberg_parttbl_mv1`\n" +
+                                "PARTITION BY str2date(`date`, '%Y-%m-%d')\n" +
+                                "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
+                                "REFRESH DEFERRED MANUAL\n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\",\n" +
+                                "\"storage_medium\" = \"HDD\"\n" +
+                                ")\n" +
+                                "AS SELECT id, data, date  FROM `iceberg0`.`partitioned_db`.`t1` as a;");
+
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView partitionedMaterializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), "iceberg_parttbl_mv1"));
         triggerRefreshMv(testDb, partitionedMaterializedView);
 
         Collection<Partition> partitions = partitionedMaterializedView.getPartitions();
         Assert.assertEquals(4, partitions.size());
 
         MockIcebergMetadata mockIcebergMetadata =
-                (MockIcebergMetadata) connectContext.getGlobalStateMgr().getMetadataMgr().
-                        getOptionalMetadata(MockIcebergMetadata.MOCKED_ICEBERG_CATALOG_NAME).get();
+                    (MockIcebergMetadata) connectContext.getGlobalStateMgr().getMetadataMgr().
+                                getOptionalMetadata(MockIcebergMetadata.MOCKED_ICEBERG_CATALOG_NAME).get();
         mockIcebergMetadata.updatePartitions("partitioned_db", "t1",
-                ImmutableList.of("date=2020-01-02"));
+                    ImmutableList.of("date=2020-01-02"));
         // refresh only one partition
         Task task = TaskBuilder.buildMvTask(partitionedMaterializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
         initAndExecuteTaskRun(taskRun);
         PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor)
-                taskRun.getProcessor();
+                    taskRun.getProcessor();
 
         MvTaskRunContext mvContext = processor.getMvContext();
         ExecPlan execPlan = mvContext.getExecPlan();
         assertPlanContains(execPlan, "3: date >= '2020-01-02', 3: date < '2020-01-03'");
 
         Map<String, Long> partitionVersionMap = partitionedMaterializedView.getPartitions().stream()
-                .collect(Collectors.toMap(Partition::getName, Partition::getVisibleVersion));
+                    .collect(Collectors.toMap(Partition::getName, Partition::getVisibleVersion));
         Assert.assertEquals(
-                ImmutableMap.of("p20200104_20200105", 2L,
-                        "p20200101_20200102", 2L,
-                        "p20200103_20200104", 2L,
-                        "p20200102_20200103", 3L),
-                ImmutableMap.copyOf(partitionVersionMap));
+                    ImmutableMap.of("p20200104_20200105", 2L,
+                                "p20200101_20200102", 2L,
+                                "p20200103_20200104", 2L,
+                                "p20200102_20200103", 3L),
+                    ImmutableMap.copyOf(partitionVersionMap));
 
         // add new row and refresh again
         mockIcebergMetadata.updatePartitions("partitioned_db", "t1",
-                ImmutableList.of("date=2020-01-01"));
+                    ImmutableList.of("date=2020-01-01"));
         taskRun = TaskRunBuilder.newBuilder(task).build();
         initAndExecuteTaskRun(taskRun);
         processor = (PartitionBasedMvRefreshProcessor)
-                taskRun.getProcessor();
+                    taskRun.getProcessor();
 
         mvContext = processor.getMvContext();
         execPlan = mvContext.getExecPlan();
@@ -185,9 +188,9 @@ public void testCreatePartitionedMVForIceberg() throws Exception {
 
         // test rewrite
         starRocksAssert.query("SELECT id, data, date  FROM `iceberg0`.`partitioned_db`.`t1`")
-                .explainContains(mvName);
+                    .explainContains(mvName);
         starRocksAssert.query("SELECT id, data, date  FROM `iceberg0`.`partitioned_db`.`t1` where date = '2020-01-01'")
-                .explainContains(mvName);
+                    .explainContains(mvName);
         starRocksAssert.dropMaterializedView(mvName);
     }
 
@@ -197,37 +200,39 @@ public void testCreatePartitionedMVForIcebergWithPartitionTransform() throws Exc
         {
             String mvName = "iceberg_year_mv1";
             starRocksAssert.useDatabase("test")
-                    .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`iceberg_year_mv1`\n" +
-                            "PARTITION BY ts\n" +
-                            "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
-                            "REFRESH DEFERRED MANUAL\n" +
-                            "PROPERTIES (\n" +
-                            "\"replication_num\" = \"1\",\n" +
-                            "\"storage_medium\" = \"HDD\"\n" +
-                            ")\n" +
-                            "AS SELECT id, data, ts  FROM `iceberg0`.`partitioned_transforms_db`.`t0_year` as a;");
-
-            Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-            MaterializedView partitionedMaterializedView = ((MaterializedView) testDb.getTable("iceberg_year_mv1"));
+                        .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`iceberg_year_mv1`\n" +
+                                    "PARTITION BY ts\n" +
+                                    "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
+                                    "REFRESH DEFERRED MANUAL\n" +
+                                    "PROPERTIES (\n" +
+                                    "\"replication_num\" = \"1\",\n" +
+                                    "\"storage_medium\" = \"HDD\"\n" +
+                                    ")\n" +
+                                    "AS SELECT id, data, ts  FROM `iceberg0`.`partitioned_transforms_db`.`t0_year` as a;");
+
+            Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+            MaterializedView partitionedMaterializedView =
+                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "iceberg_year_mv1"));
             triggerRefreshMv(testDb, partitionedMaterializedView);
 
             Collection<Partition> partitions = partitionedMaterializedView.getPartitions();
             Assert.assertEquals(5, partitions.size());
             List<String> partitionNames = ImmutableList.of("p20190101000000", "p20200101000000", "p20210101000000",
-                    "p20220101000000", "p20230101000000");
+                        "p20220101000000", "p20230101000000");
             Assert.assertTrue(partitions.stream().map(Partition::getName).allMatch(partitionNames::contains));
 
             MockIcebergMetadata mockIcebergMetadata =
-                    (MockIcebergMetadata) connectContext.getGlobalStateMgr().getMetadataMgr().
-                            getOptionalMetadata(MockIcebergMetadata.MOCKED_ICEBERG_CATALOG_NAME).get();
+                        (MockIcebergMetadata) connectContext.getGlobalStateMgr().getMetadataMgr().
+                                    getOptionalMetadata(MockIcebergMetadata.MOCKED_ICEBERG_CATALOG_NAME).get();
             mockIcebergMetadata.updatePartitions("partitioned_transforms_db", "t0_year",
-                    ImmutableList.of("ts_year=2020"));
+                        ImmutableList.of("ts_year=2020"));
             // refresh only one partition
             Task task = TaskBuilder.buildMvTask(partitionedMaterializedView, testDb.getFullName());
             TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
             initAndExecuteTaskRun(taskRun);
             PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor)
-                    taskRun.getProcessor();
+                        taskRun.getProcessor();
 
             MvTaskRunContext mvContext = processor.getMvContext();
             ExecPlan execPlan = mvContext.getExecPlan();
@@ -235,91 +240,97 @@ public void testCreatePartitionedMVForIcebergWithPartitionTransform() throws Exc
 
             // test rewrite
             starRocksAssert.query("SELECT id, data, ts  FROM `iceberg0`.`partitioned_transforms_db`.`t0_year`")
-                    .explainContains(mvName);
+                        .explainContains(mvName);
             starRocksAssert.dropMaterializedView(mvName);
         }
         // test partition by month(ts)
         {
             String mvName = "iceberg_month_mv1";
             starRocksAssert.useDatabase("test")
-                    .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`iceberg_month_mv1`\n" +
-                            "PARTITION BY ts\n" +
-                            "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
-                            "REFRESH DEFERRED MANUAL\n" +
-                            "PROPERTIES (\n" +
-                            "\"replication_num\" = \"1\",\n" +
-                            "\"storage_medium\" = \"HDD\"\n" +
-                            ")\n" +
-                            "AS SELECT id, data, ts  FROM `iceberg0`.`partitioned_transforms_db`.`t0_month` as a;");
-
-            Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-            MaterializedView partitionedMaterializedView = ((MaterializedView) testDb.getTable("iceberg_month_mv1"));
+                        .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`iceberg_month_mv1`\n" +
+                                    "PARTITION BY ts\n" +
+                                    "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
+                                    "REFRESH DEFERRED MANUAL\n" +
+                                    "PROPERTIES (\n" +
+                                    "\"replication_num\" = \"1\",\n" +
+                                    "\"storage_medium\" = \"HDD\"\n" +
+                                    ")\n" +
+                                    "AS SELECT id, data, ts  FROM `iceberg0`.`partitioned_transforms_db`.`t0_month` as a;");
+
+            Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+            MaterializedView partitionedMaterializedView =
+                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "iceberg_month_mv1"));
             triggerRefreshMv(testDb, partitionedMaterializedView);
 
             Collection<Partition> partitions = partitionedMaterializedView.getPartitions();
             Assert.assertEquals(5, partitions.size());
             List<String> partitionNames = ImmutableList.of("p20220101000000", "p20220201000000", "p20220301000000",
-                    "p20220401000000", "p20220501000000");
+                        "p20220401000000", "p20220501000000");
             Assert.assertTrue(partitions.stream().map(Partition::getName).allMatch(partitionNames::contains));
             // test rewrite
             starRocksAssert.query("SELECT id, data, ts  FROM `iceberg0`.`partitioned_transforms_db`.`t0_month`")
-                    .explainContains(mvName);
+                        .explainContains(mvName);
             starRocksAssert.dropMaterializedView(mvName);
         }
         // test partition by day(ts)
         {
             String mvName = "iceberg_day_mv1";
             starRocksAssert.useDatabase("test")
-                    .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`iceberg_day_mv1`\n" +
-                            "PARTITION BY ts\n" +
-                            "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
-                            "REFRESH DEFERRED MANUAL\n" +
-                            "PROPERTIES (\n" +
-                            "\"replication_num\" = \"1\",\n" +
-                            "\"storage_medium\" = \"HDD\"\n" +
-                            ")\n" +
-                            "AS SELECT id, data, ts  FROM `iceberg0`.`partitioned_transforms_db`.`t0_day` as a;");
-
-            Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-            MaterializedView partitionedMaterializedView = ((MaterializedView) testDb.getTable("iceberg_day_mv1"));
+                        .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`iceberg_day_mv1`\n" +
+                                    "PARTITION BY ts\n" +
+                                    "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
+                                    "REFRESH DEFERRED MANUAL\n" +
+                                    "PROPERTIES (\n" +
+                                    "\"replication_num\" = \"1\",\n" +
+                                    "\"storage_medium\" = \"HDD\"\n" +
+                                    ")\n" +
+                                    "AS SELECT id, data, ts  FROM `iceberg0`.`partitioned_transforms_db`.`t0_day` as a;");
+
+            Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+            MaterializedView partitionedMaterializedView =
+                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "iceberg_day_mv1"));
             triggerRefreshMv(testDb, partitionedMaterializedView);
 
             Collection<Partition> partitions = partitionedMaterializedView.getPartitions();
             Assert.assertEquals(5, partitions.size());
             List<String> partitionNames = ImmutableList.of("p20220101000000", "p20220102000000", "p20220103000000",
-                    "p20220104000000", "p20220105000000");
+                        "p20220104000000", "p20220105000000");
             Assert.assertTrue(partitions.stream().map(Partition::getName).allMatch(partitionNames::contains));
             // test rewrite
             starRocksAssert.query("SELECT id, data, ts  FROM `iceberg0`.`partitioned_transforms_db`.`t0_day`")
-                    .explainContains(mvName);
+                        .explainContains(mvName);
             starRocksAssert.dropMaterializedView(mvName);
         }
         // test partition by hour(ts)
         {
             String mvName = "iceberg_hour_mv1";
             starRocksAssert.useDatabase("test")
-                    .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`iceberg_hour_mv1`\n" +
-                            "PARTITION BY ts\n" +
-                            "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
-                            "REFRESH DEFERRED MANUAL\n" +
-                            "PROPERTIES (\n" +
-                            "\"replication_num\" = \"1\",\n" +
-                            "\"storage_medium\" = \"HDD\"\n" +
-                            ")\n" +
-                            "AS SELECT id, data, ts  FROM `iceberg0`.`partitioned_transforms_db`.`t0_hour` as a;");
-
-            Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-            MaterializedView partitionedMaterializedView = ((MaterializedView) testDb.getTable("iceberg_hour_mv1"));
+                        .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`iceberg_hour_mv1`\n" +
+                                    "PARTITION BY ts\n" +
+                                    "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
+                                    "REFRESH DEFERRED MANUAL\n" +
+                                    "PROPERTIES (\n" +
+                                    "\"replication_num\" = \"1\",\n" +
+                                    "\"storage_medium\" = \"HDD\"\n" +
+                                    ")\n" +
+                                    "AS SELECT id, data, ts  FROM `iceberg0`.`partitioned_transforms_db`.`t0_hour` as a;");
+
+            Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+            MaterializedView partitionedMaterializedView =
+                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "iceberg_hour_mv1"));
             triggerRefreshMv(testDb, partitionedMaterializedView);
 
             Collection<Partition> partitions = partitionedMaterializedView.getPartitions();
             Assert.assertEquals(5, partitions.size());
             List<String> partitionNames = ImmutableList.of("p20220101000000", "p20220101010000", "p20220101020000",
-                    "p20220101030000", "p20220101040000");
+                        "p20220101030000", "p20220101040000");
             Assert.assertTrue(partitions.stream().map(Partition::getName).allMatch(partitionNames::contains));
             // test rewrite
             starRocksAssert.query("SELECT id, data, ts  FROM `iceberg0`.`partitioned_transforms_db`.`t0_hour`")
-                    .explainContains(mvName);
+                        .explainContains(mvName);
             starRocksAssert.dropMaterializedView(mvName);
         }
     }
@@ -327,27 +338,27 @@ public void testCreatePartitionedMVForIcebergWithPartitionTransform() throws Exc
     @Test
     public void testRefreshWithCachePartitionTraits() {
         starRocksAssert.withMaterializedView("CREATE MATERIALIZED VIEW `test_mv1`\n" +
-                        "PARTITION BY str2date(`date`, '%Y-%m-%d')\n" +
-                        "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
-                        "REFRESH DEFERRED MANUAL\n" +
-                        "AS SELECT id, data, date  FROM `iceberg0`.`partitioned_db`.`t1` as a;",
-                () -> {
-                    MaterializedView mv = getMv("test", "test_mv1");
-                    PartitionBasedMvRefreshProcessor processor = refreshMV("test", mv);
-                    RuntimeProfile runtimeProfile = processor.getRuntimeProfile();
-                    QueryMaterializationContext.QueryCacheStats queryCacheStats = getQueryCacheStats(runtimeProfile);
-                    Assert.assertTrue(queryCacheStats != null);
-                    queryCacheStats.getCounter().forEach((key, value) -> {
-                        if (key.contains("cache_partitionNames")) {
-                            Assert.assertEquals(1L, value.longValue());
-                        } else if (key.contains("cache_getPartitionKeyRange")) {
-                            Assert.assertEquals(3L, value.longValue());
-                        } else {
-                            Assert.assertEquals(1L, value.longValue());
-                        }
+                                "PARTITION BY str2date(`date`, '%Y-%m-%d')\n" +
+                                "DISTRIBUTED BY HASH(`id`) BUCKETS 10\n" +
+                                "REFRESH DEFERRED MANUAL\n" +
+                                "AS SELECT id, data, date  FROM `iceberg0`.`partitioned_db`.`t1` as a;",
+                    () -> {
+                        MaterializedView mv = getMv("test", "test_mv1");
+                        PartitionBasedMvRefreshProcessor processor = refreshMV("test", mv);
+                        RuntimeProfile runtimeProfile = processor.getRuntimeProfile();
+                        QueryMaterializationContext.QueryCacheStats queryCacheStats = getQueryCacheStats(runtimeProfile);
+                        Assert.assertTrue(queryCacheStats != null);
+                        queryCacheStats.getCounter().forEach((key, value) -> {
+                            if (key.contains("cache_partitionNames")) {
+                                Assert.assertEquals(1L, value.longValue());
+                            } else if (key.contains("cache_getPartitionKeyRange")) {
+                                Assert.assertEquals(3L, value.longValue());
+                            } else {
+                                Assert.assertEquals(1L, value.longValue());
+                            }
+                        });
+                        Set<String> partitionsToRefresh1 = getPartitionNamesToRefreshForMv(mv);
+                        Assert.assertTrue(partitionsToRefresh1.isEmpty());
                     });
-                    Set<String> partitionsToRefresh1 = getPartitionNamesToRefreshForMv(mv);
-                    Assert.assertTrue(partitionsToRefresh1.isEmpty());
-                });
     }
 }
\ No newline at end of file
diff --git a/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorJdbcTest.java b/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorJdbcTest.java
index 20bdf39a6bbe58..1e2118d3c9e417 100644
--- a/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorJdbcTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorJdbcTest.java
@@ -54,57 +54,57 @@ public static void beforeClass() throws Exception {
         MVRefreshTestBase.beforeClass();
         ConnectorPlanTestBase.mockCatalog(connectContext, MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME);
         starRocksAssert
-                .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`jdbc_parttbl_mv0`\n" +
-                        "COMMENT \"MATERIALIZED_VIEW\"\n" +
-                        "PARTITION BY (`d`)\n" +
-                        "DISTRIBUTED BY HASH(`a`) BUCKETS 10\n" +
-                        "REFRESH DEFERRED MANUAL\n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\",\n" +
-                        "\"storage_medium\" = \"HDD\"\n" +
-                        ")\n" +
-                        "AS SELECT `a`, `b`, `c`, `d`  FROM `jdbc0`.`partitioned_db0`.`tbl0`;")
-                .withMaterializedView("create materialized view jdbc_parttbl_mv1 " +
-                        "partition by ss " +
-                        "distributed by hash(a) buckets 10 " +
-                        "REFRESH DEFERRED MANUAL " +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\"\n" +
-                        ") " +
-                        "as select str2date(d,'%Y%m%d') ss, a, b, c from jdbc0.partitioned_db0.tbl1;")
-                .withMaterializedView("create materialized view jdbc_parttbl_mv2 " +
-                        "partition by ss " +
-                        "distributed by hash(a) buckets 10 " +
-                        "REFRESH DEFERRED MANUAL " +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\"\n" +
-                        ") " +
-                        "as select str2date(d,'%Y%m%d') ss, a, b, c from jdbc0.partitioned_db0.tbl2;")
-                .withMaterializedView("create materialized view jdbc_parttbl_mv3 " +
-                        "partition by str2date(d,'%Y%m%d') " +
-                        "distributed by hash(a) buckets 10 " +
-                        "REFRESH DEFERRED MANUAL " +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\"\n" +
-                        ") " +
-                        "as select a, b, c, d from jdbc0.partitioned_db0.tbl1;")
-                .withMaterializedView("create materialized view jdbc_parttbl_mv5 " +
-                        "partition by str2date(d,'%Y%m%d') " +
-                        "distributed by hash(a) buckets 10 " +
-                        "REFRESH DEFERRED MANUAL " +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\"\n" +
-                        ") " +
-                        "as select a, b, c, d from jdbc0.partitioned_db0.tbl3;")
-                .withMaterializedView("create materialized view jdbc_parttbl_mv6 " +
-                        "partition by ss " +
-                        "distributed by hash(a) buckets 10 " +
-                        "REFRESH DEFERRED MANUAL " +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\",\n" +
-                        "\"partition_refresh_number\" = \"1\"" +
-                        ") " +
-                        "as select str2date(d,'%Y%m%d') ss, a, b, c from jdbc0.partitioned_db0.tbl1;");
+                    .withMaterializedView("CREATE MATERIALIZED VIEW `test`.`jdbc_parttbl_mv0`\n" +
+                                "COMMENT \"MATERIALIZED_VIEW\"\n" +
+                                "PARTITION BY (`d`)\n" +
+                                "DISTRIBUTED BY HASH(`a`) BUCKETS 10\n" +
+                                "REFRESH DEFERRED MANUAL\n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\",\n" +
+                                "\"storage_medium\" = \"HDD\"\n" +
+                                ")\n" +
+                                "AS SELECT `a`, `b`, `c`, `d`  FROM `jdbc0`.`partitioned_db0`.`tbl0`;")
+                    .withMaterializedView("create materialized view jdbc_parttbl_mv1 " +
+                                "partition by ss " +
+                                "distributed by hash(a) buckets 10 " +
+                                "REFRESH DEFERRED MANUAL " +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\"\n" +
+                                ") " +
+                                "as select str2date(d,'%Y%m%d') ss, a, b, c from jdbc0.partitioned_db0.tbl1;")
+                    .withMaterializedView("create materialized view jdbc_parttbl_mv2 " +
+                                "partition by ss " +
+                                "distributed by hash(a) buckets 10 " +
+                                "REFRESH DEFERRED MANUAL " +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\"\n" +
+                                ") " +
+                                "as select str2date(d,'%Y%m%d') ss, a, b, c from jdbc0.partitioned_db0.tbl2;")
+                    .withMaterializedView("create materialized view jdbc_parttbl_mv3 " +
+                                "partition by str2date(d,'%Y%m%d') " +
+                                "distributed by hash(a) buckets 10 " +
+                                "REFRESH DEFERRED MANUAL " +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\"\n" +
+                                ") " +
+                                "as select a, b, c, d from jdbc0.partitioned_db0.tbl1;")
+                    .withMaterializedView("create materialized view jdbc_parttbl_mv5 " +
+                                "partition by str2date(d,'%Y%m%d') " +
+                                "distributed by hash(a) buckets 10 " +
+                                "REFRESH DEFERRED MANUAL " +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\"\n" +
+                                ") " +
+                                "as select a, b, c, d from jdbc0.partitioned_db0.tbl3;")
+                    .withMaterializedView("create materialized view jdbc_parttbl_mv6 " +
+                                "partition by ss " +
+                                "distributed by hash(a) buckets 10 " +
+                                "REFRESH DEFERRED MANUAL " +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\",\n" +
+                                "\"partition_refresh_number\" = \"1\"" +
+                                ") " +
+                                "as select str2date(d,'%Y%m%d') ss, a, b, c from jdbc0.partitioned_db0.tbl1;");
     }
 
     @AfterClass
@@ -137,24 +137,24 @@ public void testJDBCProtocolType() {
     public void testPartitionJDBCSupported() throws Exception {
         // not supported
         Assert.assertThrows(AnalysisException.class, () ->
-                starRocksAssert.withMaterializedView("create materialized view mv_jdbc_postgres " +
-                        "partition by d " +
-                        "refresh deferred manual " +
-                        "AS SELECT `a`, `b`, `c`, `d`  FROM `jdbc_postgres`.`partitioned_db0`.`tbl0`;")
+                    starRocksAssert.withMaterializedView("create materialized view mv_jdbc_postgres " +
+                                "partition by d " +
+                                "refresh deferred manual " +
+                                "AS SELECT `a`, `b`, `c`, `d`  FROM `jdbc_postgres`.`partitioned_db0`.`tbl0`;")
         );
 
         // supported
         starRocksAssert.withMaterializedView("create materialized view mv_jdbc_mysql " +
-                "partition by d " +
-                "refresh deferred manual " +
-                "AS SELECT `a`, `b`, `c`, `d`  FROM `jdbc0`.`partitioned_db0`.`tbl0`;");
+                    "partition by d " +
+                    "refresh deferred manual " +
+                    "AS SELECT `a`, `b`, `c`, `d`  FROM `jdbc0`.`partitioned_db0`.`tbl0`;");
     }
 
     @Test
     public void testRangePartitionChangeWithJDBCTable() throws Exception {
         MockedMetadataMgr metadataMgr = (MockedMetadataMgr) connectContext.getGlobalStateMgr().getMetadataMgr();
         MockedJDBCMetadata mockedJDBCMetadata =
-                (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
+                    (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
         mockedJDBCMetadata.initPartitions();
 
         MaterializedView materializedView = refreshMaterializedView("jdbc_parttbl_mv0", "20230801", "20230805");
@@ -169,8 +169,9 @@ public void testRangePartitionChangeWithJDBCTable() throws Exception {
 
     @NotNull
     private MaterializedView refreshMaterializedView(String materializedViewName, String start, String end) throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(materializedViewName));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), materializedViewName));
         refreshMVRange(materializedView.getName(), start, end, false);
         return materializedView;
     }
@@ -179,15 +180,15 @@ private MaterializedView refreshMaterializedView(String materializedViewName, St
     public void testRangePartitionWithJDBCTableUseStr2Date() throws Exception {
         MockedMetadataMgr metadataMgr = (MockedMetadataMgr) connectContext.getGlobalStateMgr().getMetadataMgr();
         MockedJDBCMetadata mockedJDBCMetadata =
-                (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
+                    (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
         mockedJDBCMetadata.initPartitions();
 
         MaterializedView materializedView = refreshMaterializedView("jdbc_parttbl_mv1", "20230731", "20230805");
         List<String> partitions = materializedView.getPartitions().stream()
-                .map(Partition::getName).sorted().collect(Collectors.toList());
+                    .map(Partition::getName).sorted().collect(Collectors.toList());
         Assert.assertEquals(ImmutableList.of("p00010101_20230801", "p20230801_20230802",
-                        "p20230802_20230803", "p20230803_99991231"),
-                partitions);
+                                "p20230802_20230803", "p20230803_99991231"),
+                    partitions);
     }
 
     @Test
@@ -203,74 +204,75 @@ public void testRangePartitionWithJDBCTableUseStr2DateForError() {
     public void testRangePartitionWithJDBCTableUseStr2Date2() throws Exception {
         MockedMetadataMgr metadataMgr = (MockedMetadataMgr) connectContext.getGlobalStateMgr().getMetadataMgr();
         MockedJDBCMetadata mockedJDBCMetadata =
-                (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
+                    (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
         mockedJDBCMetadata.initPartitions();
 
         MaterializedView materializedView = refreshMaterializedView("jdbc_parttbl_mv3", "20230731", "20230805");
         List<String> partitions = materializedView.getPartitions().stream()
-                .map(Partition::getName).sorted().collect(Collectors.toList());
+                    .map(Partition::getName).sorted().collect(Collectors.toList());
         Assert.assertEquals(ImmutableList.of("p00010101_20230801", "p20230801_20230802",
-                        "p20230802_20230803", "p20230803_99991231"),
-                partitions);
+                                "p20230802_20230803", "p20230803_99991231"),
+                    partitions);
     }
 
     @Test
     public void testStr2Date_DateTrunc() throws Exception {
         MockedMetadataMgr metadataMgr = (MockedMetadataMgr) connectContext.getGlobalStateMgr().getMetadataMgr();
         MockedJDBCMetadata mockedJDBCMetadata =
-                (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
+                    (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
         mockedJDBCMetadata.initPartitions();
 
         String mvName = "jdbc_parttbl_str2date";
         starRocksAssert.withMaterializedView("create materialized view jdbc_parttbl_str2date " +
-                "partition by date_trunc('month', ss) " +
-                "distributed by hash(a) buckets 10 " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"partition_refresh_number\" = \"1\"" +
-                ") " +
-                "as select str2date(d,'%Y%m%d') ss, a, b, c from jdbc0.partitioned_db0.tbl5;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by date_trunc('month', ss) " +
+                    "distributed by hash(a) buckets 10 " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"partition_refresh_number\" = \"1\"" +
+                    ") " +
+                    "as select str2date(d,'%Y%m%d') ss, a, b, c from jdbc0.partitioned_db0.tbl5;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // full refresh
         {
             starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " force with sync mode");
             List<String> partitions =
-                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                            .collect(Collectors.toList());
+                        materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                    .collect(Collectors.toList());
             Assert.assertEquals(Arrays.asList("p000101_202308", "p202308_202309"), partitions);
         }
 
         // partial range refresh 1
         {
             Map<String, Long> partitionVersionMap = materializedView.getPartitions().stream().collect(
-                    Collectors.toMap(Partition::getName, Partition::getVisibleVersion));
+                        Collectors.toMap(Partition::getName, Partition::getVisibleVersion));
             starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName +
-                    " partition start('2023-08-02') end('2023-09-01')" +
-                    "force with sync mode");
+                        " partition start('2023-08-02') end('2023-09-01')" +
+                        "force with sync mode");
             List<String> partitions =
-                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                            .collect(Collectors.toList());
+                        materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                    .collect(Collectors.toList());
             Assert.assertEquals(Arrays.asList("p000101_202308", "p202308_202309"), partitions);
             Assert.assertEquals(partitionVersionMap.get("p202308_202309").longValue(),
-                    materializedView.getPartition("p202308_202309").getVisibleVersion());
+                        materializedView.getPartition("p202308_202309").getVisibleVersion());
         }
 
         // partial range refresh 2
         {
             Map<String, Long> partitionVersionMap = materializedView.getPartitions().stream().collect(
-                    Collectors.toMap(Partition::getName, Partition::getVisibleVersion));
+                        Collectors.toMap(Partition::getName, Partition::getVisibleVersion));
             starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName +
-                    " partition start('2023-07-01') end('2023-08-01')" +
-                    "force with sync mode");
+                        " partition start('2023-07-01') end('2023-08-01')" +
+                        "force with sync mode");
             List<String> partitions =
-                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                            .collect(Collectors.toList());
+                        materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                    .collect(Collectors.toList());
             Assert.assertEquals(Arrays.asList("p000101_202308", "p202308_202309"), partitions);
             Assert.assertEquals(partitionVersionMap.get("p202308_202309").longValue(),
-                    materializedView.getPartition("p202308_202309").getVisibleVersion());
+                        materializedView.getPartition("p202308_202309").getVisibleVersion());
         }
 
         starRocksAssert.dropMaterializedView(mvName);
@@ -280,40 +282,41 @@ public void testStr2Date_DateTrunc() throws Exception {
     public void testStr2Date_TTL() throws Exception {
         MockedMetadataMgr metadataMgr = (MockedMetadataMgr) connectContext.getGlobalStateMgr().getMetadataMgr();
         MockedJDBCMetadata mockedJDBCMetadata =
-                (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
+                    (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
         mockedJDBCMetadata.initPartitions();
 
         String mvName = "jdbc_parttbl_str2date";
         starRocksAssert.withMaterializedView("create materialized view jdbc_parttbl_str2date " +
-                "partition by ss " +
-                "distributed by hash(a) buckets 10 " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"partition_refresh_number\" = \"1\"," +
-                "'partition_ttl_number'='2'" +
-                ") " +
-                "as select str2date(d,'%Y%m%d') ss, a, b, c from jdbc0.partitioned_db0.tbl1;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by ss " +
+                    "distributed by hash(a) buckets 10 " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"partition_refresh_number\" = \"1\"," +
+                    "'partition_ttl_number'='2'" +
+                    ") " +
+                    "as select str2date(d,'%Y%m%d') ss, a, b, c from jdbc0.partitioned_db0.tbl1;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230802_20230803", "p20230803_99991231"), partitions);
 
         // modify TTL
         {
             starRocksAssert.getCtx().executeSql(
-                    String.format("alter materialized view %s set ('partition_ttl_number'='1')", mvName));
+                        String.format("alter materialized view %s set ('partition_ttl_number'='1')", mvName));
             starRocksAssert.getCtx().executeSql(String.format("refresh materialized view %s with sync mode", mvName));
             GlobalStateMgr.getCurrentState().getDynamicPartitionScheduler().runOnceForTest();
 
             partitions =
-                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                            .collect(Collectors.toList());
+                        materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                    .collect(Collectors.toList());
             Assert.assertEquals(Arrays.asList("p20230803_99991231"), partitions);
         }
         starRocksAssert.dropMaterializedView(mvName);
@@ -323,36 +326,37 @@ public void testStr2Date_TTL() throws Exception {
     public void testRangePartitionWithJDBCTableUseStr2Date3() throws Exception {
         MockedMetadataMgr metadataMgr = (MockedMetadataMgr) connectContext.getGlobalStateMgr().getMetadataMgr();
         MockedJDBCMetadata mockedJDBCMetadata =
-                (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
+                    (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
         mockedJDBCMetadata.initPartitions();
 
         MaterializedView materializedView = refreshMaterializedView("jdbc_parttbl_mv5", "20230731", "20230805");
         List<String> partitions = materializedView.getPartitions().stream()
-                .map(Partition::getName).sorted().collect(Collectors.toList());
+                    .map(Partition::getName).sorted().collect(Collectors.toList());
         Assert.assertEquals(ImmutableList.of("p00010101_20230801", "p20230801_20230802",
-                        "p20230802_20230803", "p20230803_20230804"),
-                partitions);
+                                "p20230802_20230803", "p20230803_20230804"),
+                    partitions);
     }
 
     @Test
     public void testRefreshByParCreateOnlyNecessaryPar() throws Exception {
         MockedMetadataMgr metadataMgr = (MockedMetadataMgr) connectContext.getGlobalStateMgr().getMetadataMgr();
         MockedJDBCMetadata mockedJDBCMetadata =
-                (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
+                    (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
         mockedJDBCMetadata.initPartitions();
 
         // get base table partitions
         List<String> baseParNames = mockedJDBCMetadata.listPartitionNames("partitioned_db0", "tbl1", TableVersionRange.empty());
         Assert.assertEquals(4, baseParNames.size());
 
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("jdbc_parttbl_mv6"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), "jdbc_parttbl_mv6"));
         HashMap<String, String> taskRunProperties = new HashMap<>();
         // check corner case: the first partition of base table is 0000 to 20230801
         // p20230801 of mv should not be created
         refreshMVRange(materializedView.getName(), "20230801", "20230802", false);
         List<String> partitions = materializedView.getPartitions().stream()
-                .map(Partition::getName).sorted().collect(Collectors.toList());
+                    .map(Partition::getName).sorted().collect(Collectors.toList());
         Assert.assertEquals(ImmutableList.of("p20230801_20230802"), partitions);
     }
 
@@ -360,31 +364,32 @@ public void testRefreshByParCreateOnlyNecessaryPar() throws Exception {
     public void testStr2DateMVRefresh_Rewrite() throws Exception {
         MockedMetadataMgr metadataMgr = (MockedMetadataMgr) connectContext.getGlobalStateMgr().getMetadataMgr();
         MockedJDBCMetadata mockedJDBCMetadata =
-                (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
+                    (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
         mockedJDBCMetadata.initPartitions();
 
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y%m%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select  t1.a, t2.b, t3.c, t1.d " +
-                " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
-                " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
-                " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d ;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y%m%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select  t1.a, t2.b, t3.c, t1.d " +
+                    " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
+                    " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
+                    " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d ;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p00010101_20230801", "p20230801_20230802", "p20230802_20230803",
-                "p20230803_99991231"), partitions);
+                    "p20230803_99991231"), partitions);
 
         starRocksAssert.dropMaterializedView(mvName);
     }
diff --git a/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorOlapPart2Test.java b/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorOlapPart2Test.java
index 41f83daf27834f..5ab27a72662c28 100644
--- a/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorOlapPart2Test.java
+++ b/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorOlapPart2Test.java
@@ -19,8 +19,11 @@
 import com.starrocks.catalog.MvUpdateInfo;
 import com.starrocks.catalog.OlapTable;
 import com.starrocks.catalog.Partition;
+import com.starrocks.common.util.PropertyAnalyzer;
 import com.starrocks.common.util.RuntimeProfile;
 import com.starrocks.common.util.UUIDUtil;
+import com.starrocks.qe.ConnectContext;
+import com.starrocks.qe.SessionVariable;
 import com.starrocks.schema.MTable;
 import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.ast.StatementBase;
@@ -42,6 +45,7 @@
 import java.util.Map;
 import java.util.Set;
 
+import static com.starrocks.scheduler.TaskRun.MV_ID;
 import static com.starrocks.sql.plan.PlanTestBase.cleanupEphemeralMVs;
 
 @FixMethodOrder(MethodSorters.NAME_ASCENDING)
@@ -104,13 +108,15 @@ public void testMVRefreshWithTheSameTables1() {
                             String mvName = (String) obj;
                             assertPlanWithoutPushdownBelowScan(mvName);
                         });
-                    };
+                    }
+                    ;
                 });
     }
 
     private void assertPlanWithoutPushdownBelowScan(String mvName) throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), mvName));
         Assert.assertEquals(1, materializedView.getPartitionExprMaps().size());
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         Map<String, String> testProperties = task.getProperties();
@@ -184,13 +190,15 @@ public void testMVRefreshWithTheSameTables22() {
                             String mvName = (String) obj;
                             assertPlanWithPushdownBelowScan(mvName);
                         });
-                    };
+                    }
+                    ;
                 });
     }
 
     private void assertPlanWithPushdownBelowScan(String mvName) throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), mvName));
         Assert.assertEquals(1, materializedView.getPartitionExprMaps().size());
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         Map<String, String> testProperties = task.getProperties();
@@ -264,7 +272,7 @@ public void testRefreshWithCachePartitionTraits() throws Exception {
 
                     executeInsertSql(connectContext, "insert into tbl1 values(\"2022-02-20\", 2, 10)");
                     Partition p2 = table.getPartition("p2");
-                    while (p2.getVisibleVersion()  != 3) {
+                    while (p2.getVisibleVersion() != 3) {
                         System.out.println("waiting for partition p2 to be visible:" + p2.getVisibleVersion());
                         Thread.sleep(1000);
                     }
@@ -314,7 +322,7 @@ public void testTaskRun() {
                                     "properties('replication_num' = '1', 'partition_refresh_number'='1')\n" +
                                     "as select k1, k2 from tbl6;");
                     String mvName = "mv_refresh_priority";
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb(TEST_DB_NAME);
+                    Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(TEST_DB_NAME);
                     MaterializedView mv = ((MaterializedView) testDb.getTable(mvName));
                     TaskManager tm = GlobalStateMgr.getCurrentState().getTaskManager();
 
@@ -380,7 +388,7 @@ public void testRefreshPriority() {
                             "refresh deferred manual\n" +
                             "properties('replication_num' = '1', 'partition_refresh_number'='1')\n" +
                             "as select k1, k2 from tbl6;");
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+                    Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
                     MaterializedView mv = ((MaterializedView) testDb.getTable(mvName));
                     TaskManager tm = GlobalStateMgr.getCurrentState().getTaskManager();
                     long taskId = tm.getTask(TaskBuilder.getMvTaskName(mv.getId())).getId();
@@ -404,4 +412,66 @@ public void testRefreshPriority() {
                 }
         );
     }
+
+    @Test
+    public void testMVRefreshProperties() {
+        starRocksAssert.withTable(new MTable("tbl6", "k2",
+                        List.of(
+                                "k1 date",
+                                "k2 int",
+                                "v1 int"
+                        ),
+                        "k1",
+                        List.of(
+                                "PARTITION p0 values [('2021-12-01'),('2022-01-01'))",
+                                "PARTITION p1 values [('2022-01-01'),('2022-02-01'))",
+                                "PARTITION p2 values [('2022-02-01'),('2022-03-01'))",
+                                "PARTITION p3 values [('2022-03-01'),('2022-04-01'))",
+                                "PARTITION p4 values [('2022-04-01'),('2022-05-01'))"
+                        )
+                ),
+                () -> {
+                    String mvName = "test_mv1";
+                    starRocksAssert.withMaterializedView("create materialized view test_mv1 \n" +
+                            "partition by date_trunc('month',k1) \n" +
+                            "distributed by hash(k2) buckets 10\n" +
+                            "refresh deferred manual\n" +
+                            "properties(" +
+                            "   'replication_num' = '1', " +
+                            "   'session.enable_materialized_view_rewrite' = 'true', \n" +
+                            "   'session.enable_materialized_view_for_insert' = 'true',  \n" +
+                            "   'partition_refresh_number'='1'" +
+                            ")\n" +
+                            "as select k1, k2 from tbl6;",
+                            () -> {
+                                Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+                                MaterializedView mv = ((MaterializedView) testDb.getTable(mvName));
+                                executeInsertSql(connectContext,
+                                        "insert into tbl6 partition(p1) values('2022-01-02',2,10);");
+
+                                HashMap<String, String> taskRunProperties = new HashMap<>();
+                                taskRunProperties.put(TaskRun.FORCE, Boolean.toString(true));
+                                Task task = TaskBuilder.buildMvTask(mv, testDb.getFullName());
+                                TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
+                                initAndExecuteTaskRun(taskRun);
+
+                                PartitionBasedMvRefreshProcessor processor =
+                                        (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
+                                MvTaskRunContext mvTaskRunContext = processor.getMvContext();
+                                Map<String, String> properties = mvTaskRunContext.getProperties();
+                                System.out.println(properties);
+                                Assert.assertEquals(1, properties.size());
+                                Assert.assertTrue(properties.containsKey(MV_ID));
+                                // Ensure that table properties are not passed to the task run
+                                Assert.assertFalse(properties.containsKey(PropertyAnalyzer.PROPERTIES_REPLICATION_NUM));
+
+                                ConnectContext context = mvTaskRunContext.getCtx();
+                                SessionVariable sessionVariable = context.getSessionVariable();
+                                // Ensure that session properties are set
+                                Assert.assertTrue(sessionVariable.isEnableMaterializedViewRewrite());
+                                Assert.assertTrue(sessionVariable.isEnableMaterializedViewRewriteForInsert());
+                            });
+                }
+        );
+    }
 }
\ No newline at end of file
diff --git a/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorOlapTest.java b/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorOlapTest.java
index f5a33698941983..0f3cc199babf15 100644
--- a/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorOlapTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorOlapTest.java
@@ -71,11 +71,12 @@
 import java.util.List;
 import java.util.Map;
 import java.util.Optional;
+import java.util.Random;
 import java.util.Set;
 import java.util.UUID;
 import java.util.concurrent.atomic.AtomicInteger;
 
-import static com.starrocks.scheduler.PartitionBasedMvRefreshProcessor.MV_ID;
+import static com.starrocks.scheduler.TaskRun.MV_ID;
 import static com.starrocks.sql.plan.PlanTestBase.cleanupEphemeralMVs;
 
 @FixMethodOrder(MethodSorters.NAME_ASCENDING)
@@ -260,8 +261,9 @@ protected void assertPlanContains(ExecPlan execPlan, String... explain) throws E
 
     @Test
     public void testUnionAllMvWithPartition() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("union_all_mv"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "union_all_mv"));
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
         try {
@@ -286,8 +288,9 @@ public void testUnionAllMvWithPartition() {
 
     @Test
     public void testWithPartition() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "mv1"));
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
         try {
@@ -351,8 +354,9 @@ public void testWithPartition() {
 
     @Test
     public void testMvWithoutPartition() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_without_partition"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "mv_without_partition"));
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
         try {
@@ -419,8 +423,9 @@ public void testRewriteNonPartitionedMVForOlapTable() throws Exception {
 
     @NotNull
     private MaterializedView refreshMaterializedView(String materializedViewName, String start, String end) throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(materializedViewName));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), materializedViewName));
         refreshMVRange(materializedView.getName(), start, end, false);
         return materializedView;
     }
@@ -434,8 +439,9 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
                 taskRunCounter.incrementAndGet();
             }
         };
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_without_partition"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "mv_without_partition"));
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
 
@@ -455,8 +461,9 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
 
     @Test
     public void testMVClearQueryInfo() throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_without_partition"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "mv_without_partition"));
         new MockUp<StmtExecutor>() {
             @Mock
             public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
@@ -487,7 +494,8 @@ private void testBaseTablePartitionInsertData(Database testDb, MaterializedView
         insertSql = "insert into tbl1 partition(p1) values('2022-01-01', 2, 10);";
         executeInsertSql(connectContext, insertSql);
 
-        OlapTable tbl1 = ((OlapTable) testDb.getTable("tbl1"));
+        OlapTable tbl1 =
+                ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "tbl1"));
         initAndExecuteTaskRun(taskRun);
         Map<Long, Map<String, MaterializedView.BasePartitionInfo>> baseTableVisibleVersionMap =
                 materializedView.getRefreshScheme().getAsyncRefreshContext().getBaseTableVisibleVersionMap();
@@ -510,7 +518,8 @@ private void testBaseTablePartitionInsertData(Database testDb, MaterializedView
 
     private void testRefreshWithFailure(Database testDb, MaterializedView materializedView, TaskRun taskRun)
             throws Exception {
-        OlapTable tbl1 = ((OlapTable) testDb.getTable("tbl1"));
+        OlapTable tbl1 =
+                ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "tbl1"));
         // insert new data into tbl1's p0 partition
         // update base table tbl1's p0 version to 3
         String insertSql = "insert into tbl1 partition(p0) values('2021-12-01', 2, 10);";
@@ -547,12 +556,13 @@ private Map<Long, TableSnapshotInfo> collectBaseTableSnapshotInfos(MaterializedV
                     if (tableOptional.isEmpty() || !tableOptional.get().isOlapTable()) {
                         continue;
                     }
-                    Database baseDb = GlobalStateMgr.getCurrentState().getDb(baseTableInfo.getDbId());
+                    Database baseDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(baseTableInfo.getDbId());
                     if (baseDb == null) {
                         throw new SemanticException("Materialized view base db: " +
                                 baseTableInfo.getDbId() + " not exist.");
                     }
-                    OlapTable olapTable = (OlapTable) baseDb.getTable(baseTableInfo.getTableId());
+                    OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(baseDb.getId(), baseTableInfo.getTableId());
                     if (olapTable == null) {
                         throw new SemanticException("Materialized view base table: " +
                                 baseTableInfo.getTableId() + " not exist.");
@@ -589,7 +599,8 @@ private Map<Long, TableSnapshotInfo> collectBaseTableSnapshotInfos(MaterializedV
     private void testBaseTablePartitionReplace(Database testDb, MaterializedView materializedView, TaskRun taskRun)
             throws Exception {
         // mv need refresh with base table partition p2, p2 replace with tp2 after collect and before insert overwrite
-        OlapTable tbl1 = ((OlapTable) testDb.getTable("tbl1"));
+        OlapTable tbl1 =
+                ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "tbl1"));
         new MockUp<PartitionBasedMvRefreshProcessor>() {
             @Mock
             public Map<Long, TableSnapshotInfo> collectBaseTableSnapshotInfos(
@@ -601,12 +612,13 @@ public Map<Long, TableSnapshotInfo> collectBaseTableSnapshotInfos(
                     if (!table.isOlapTable()) {
                         continue;
                     }
-                    Database baseDb = GlobalStateMgr.getCurrentState().getDb(baseTableInfo.getDbId());
+                    Database baseDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(baseTableInfo.getDbId());
                     if (baseDb == null) {
                         throw new SemanticException("Materialized view base db: " +
                                 baseTableInfo.getDbId() + " not exist.");
                     }
-                    OlapTable olapTable = (OlapTable) baseDb.getTable(baseTableInfo.getTableId());
+                    OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(baseDb.getId(), baseTableInfo.getTableId());
                     if (olapTable == null) {
                         throw new SemanticException("Materialized view base table: " +
                                 baseTableInfo.getTableId() + " not exist.");
@@ -653,7 +665,8 @@ public Map<Long, TableSnapshotInfo> collectBaseTableSnapshotInfos(
     public void testBaseTableAddPartitionWhileSync(Database testDb, MaterializedView materializedView, TaskRun taskRun)
             throws Exception {
         // mv need refresh with base table partition p3, add partition p99 after collect and before insert overwrite
-        OlapTable tbl1 = ((OlapTable) testDb.getTable("tbl1"));
+        OlapTable tbl1 =
+                ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "tbl1"));
         new MockUp<PartitionBasedMvRefreshProcessor>() {
             @Mock
             public Map<Long, TableSnapshotInfo> collectBaseTableSnapshotInfos(MaterializedView materializedView) {
@@ -667,12 +680,13 @@ public Map<Long, TableSnapshotInfo> collectBaseTableSnapshotInfos(MaterializedVi
                     if (!tableOptional.get().isOlapTable()) {
                         continue;
                     }
-                    Database baseDb = GlobalStateMgr.getCurrentState().getDb(baseTableInfo.getDbId());
+                    Database baseDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(baseTableInfo.getDbId());
                     if (baseDb == null) {
                         throw new SemanticException("Materialized view base db: " +
                                 baseTableInfo.getDbId() + " not exist.");
                     }
-                    OlapTable olapTable = (OlapTable) baseDb.getTable(baseTableInfo.getTableId());
+                    OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(baseDb.getId(), baseTableInfo.getTableId());
                     if (olapTable == null) {
                         throw new SemanticException("Materialized view base table: " +
                                 baseTableInfo.getTableId() + " not exist.");
@@ -718,7 +732,8 @@ public void testBaseTableAddPartitionWhileRefresh(Database testDb, MaterializedV
                                                       TaskRun taskRun)
             throws Exception {
         // mv need refresh with base table partition p3, add partition p99 after collect and before insert overwrite
-        OlapTable tbl1 = ((OlapTable) testDb.getTable("tbl1"));
+        OlapTable tbl1 =
+                ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "tbl1"));
         new MockUp<PartitionBasedMvRefreshProcessor>() {
             @Mock
             public void refreshMaterializedView(MvTaskRunContext mvContext, ExecPlan execPlan,
@@ -758,7 +773,8 @@ public void refreshMaterializedView(MvTaskRunContext mvContext, ExecPlan execPla
     public void testBaseTableDropPartitionWhileSync(Database testDb, MaterializedView materializedView, TaskRun taskRun)
             throws Exception {
         // mv need refresh with base table partition p4, drop partition p4 after collect and before insert overwrite
-        OlapTable tbl1 = ((OlapTable) testDb.getTable("tbl1"));
+        OlapTable tbl1 =
+                ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "tbl1"));
         new MockUp<PartitionBasedMvRefreshProcessor>() {
             @Mock
             private Map<Long, TableSnapshotInfo> collectBaseTableSnapshotInfos(MaterializedView materializedView) {
@@ -769,12 +785,13 @@ private Map<Long, TableSnapshotInfo> collectBaseTableSnapshotInfos(MaterializedV
                     if (!table.isOlapTable()) {
                         continue;
                     }
-                    Database baseDb = GlobalStateMgr.getCurrentState().getDb(baseTableInfo.getDbId());
+                    Database baseDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(baseTableInfo.getDbId());
                     if (baseDb == null) {
                         throw new SemanticException("Materialized view base db: " +
                                 baseTableInfo.getDbId() + " not exist.");
                     }
-                    OlapTable olapTable = (OlapTable) baseDb.getTable(baseTableInfo.getTableId());
+                    OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(baseDb.getId(), baseTableInfo.getTableId());
                     if (olapTable == null) {
                         throw new SemanticException("Materialized view base table: " +
                                 baseTableInfo.getTableId() + " not exist.");
@@ -811,7 +828,8 @@ public void testBaseTableDropPartitionWhileRefresh(Database testDb, Materialized
                                                        TaskRun taskRun)
             throws Exception {
         // drop partition p4 after collect and before insert overwrite
-        OlapTable tbl1 = ((OlapTable) testDb.getTable("tbl1"));
+        OlapTable tbl1 =
+                ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "tbl1"));
         new MockUp<PartitionBasedMvRefreshProcessor>() {
             @Mock
             public void refreshMaterializedView(MvTaskRunContext mvContext, ExecPlan execPlan,
@@ -868,13 +886,14 @@ public void testFilterPartitionByRefreshNumber() throws Exception {
         // PARTITION p4 values [('2022-04-01'),('2022-05-01'))
 
         String mvName = "mv_with_test_refresh";
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.withMaterializedView("create materialized view test.mv_with_test_refresh\n" +
                 "partition by k1\n" +
                 "distributed by hash(k2) buckets 10\n" +
                 "refresh deferred manual\n" +
                 "as select k1, k2, sum(v1) as total_sum from base group by k1, k2;");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), mvName));
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
         initAndExecuteTaskRun(taskRun);
@@ -903,7 +922,7 @@ public void testFilterPartitionByRefreshNumberAndDescending() throws Exception {
         // PARTITION p3 values [('2022-03-01'),('2022-04-01'))
         // PARTITION p4 values [('2022-04-01'),('2022-05-01'))
 
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         String mvName = "mv_reverse_refresh";
         starRocksAssert.withMaterializedView("create materialized view test.mv_reverse_refresh\n" +
                 "partition by k1\n" +
@@ -911,7 +930,8 @@ public void testFilterPartitionByRefreshNumberAndDescending() throws Exception {
                 "refresh deferred manual\n" +
                 "as select k1, k2, sum(v1) as total_sum from base group by k1, k2;");
 
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), mvName));
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
         initAndExecuteTaskRun(taskRun);
@@ -994,8 +1014,9 @@ public void testRefreshMaterializedViewDefaultConfig1() throws Exception {
                 "'storage_medium' = 'SSD'" +
                 ")\n" +
                 "as select k1, k2 from tbl1;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_config1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "mv_config1"));
 
         String insertSql = "insert into tbl1 partition(p3) values('2022-03-01', 3, 10);";
         executeInsertSql(connectContext, insertSql);
@@ -1041,8 +1062,9 @@ public void testRefreshMaterializedViewDefaultConfig2() throws Exception {
                 "'session.enable_spill' = 'false'" +
                 ")\n" +
                 "as select k1, k2 from tbl1;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_config2"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "mv_config2"));
 
         String insertSql = "insert into tbl1 partition(p3) values('2022-03-01', 3, 10);";
         executeInsertSql(connectContext, insertSql);
@@ -1066,8 +1088,9 @@ public void testSyncPartitionWithSsdStorage() throws Exception {
                 "properties('replication_num' = '1',\n" +
                 "'storage_medium' = 'SSD')\n" +
                 "as select tbl1.k1, tbl2.k2 from tbl1 join tbl2 on tbl1.k2 = tbl2.k2;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_with_ssd"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "mv_with_ssd"));
 
         refreshMVRange(materializedView.getName(), false);
         refreshMVRange(materializedView.getName(), false);
@@ -1084,15 +1107,16 @@ public void testSyncPartitionWithSsdStorageAndCooldownTime() throws Exception {
                         "'storage_medium' = 'SSD',\n" +
                         "'storage_cooldown_time' = '2222-04-21 20:45:11')\n" +
                         "as select tbl1.k1, tbl2.k2 from tbl1 join tbl2 on tbl1.k2 = tbl2.k2;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_use_ssd_and_cooldown"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "mv_use_ssd_and_cooldown"));
         refreshMVRange(materializedView.getName(), false);
         refreshMVRange(materializedView.getName(), false);
     }
 
     @Test
     public void testMVOnListPartitionTables1() throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         String createSQL = "CREATE TABLE test.list_partition_tbl1 (\n" +
                 "      id BIGINT,\n" +
                 "      age SMALLINT,\n" +
@@ -1116,7 +1140,8 @@ public void testMVOnListPartitionTables1() throws Exception {
                 "distributed by hash(dt, province) buckets 10 " +
                 "as select dt, province, avg(age) from list_partition_tbl1 group by dt, province;";
         starRocksAssert.withMaterializedView(sql);
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("list_partition_mv1"));
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "list_partition_mv1"));
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
         // run 1
@@ -1177,8 +1202,9 @@ public void testPartitionPruneNonRefBaseTable1() throws Exception {
                         ")\n" +
                         "AS SELECT t1.k1, sum(t1.k2) as sum1, avg(t2.k2) as avg1 FROM tbl4 as t1 join " +
                         "tbl5 t2 on t1.k1=t2.dt group by t1.k1");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("partition_prune_non_ref_tables1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "partition_prune_non_ref_tables1"));
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
 
@@ -1241,8 +1267,9 @@ public void testPartitionPruneNonRefBaseTable2() throws Exception {
                         ")\n" +
                         "AS SELECT t1.k1 as k11, sum(t1.k2) as sum1, avg(t2.k2) as avg1 FROM tbl4 as t1 join " +
                         "tbl5 t2 on t1.k1=t2.dt group by t1.k1");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("partition_prune_non_ref_tables2"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "partition_prune_non_ref_tables2"));
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
 
@@ -1305,8 +1332,9 @@ public void testPartitionPruneNonRefBaseTable3() throws Exception {
                         ")\n" +
                         "AS SELECT t1.k1, sum(t1.k2) as sum1, avg(t2.k2) as avg1 FROM tbl4 as t1 join " +
                         "tbl5 t2 on t1.k1=t2.dt where t1.k1>'2022-01-01' and t1.k2>0 group by t1.k1");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable("partition_prune_non_ref_tables1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "partition_prune_non_ref_tables1"));
         Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
         TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
 
@@ -1364,9 +1392,10 @@ public void testMVDropBaseVersionMetaOfOlapTable() throws Exception {
                 "refresh async \n" +
                 "as select k1, k2, sum(v1) as total from tbl1 group by k1, k2;");
 
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        Table tbl1 = testDb.getTable("tbl1");
-        MaterializedView mv = ((MaterializedView) testDb.getTable("test_drop_partition_mv1"));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table tbl1 = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "tbl1");
+        MaterializedView mv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(testDb.getFullName(), "test_drop_partition_mv1"));
         Map<Long, Map<String, MaterializedView.BasePartitionInfo>> versionMap =
                 mv.getRefreshScheme().getAsyncRefreshContext().getBaseTableVisibleVersionMap();
         Map<String, Set<String>> mvPartitionNameRefBaseTablePartitionMap =
@@ -1452,16 +1481,20 @@ public void testFilterPartitionByJoinPredicate_RefreshPartitionNum() {
                                     "PROPERTIES('partition_refresh_number' = '1')" +
                                     "refresh deferred manual\n" +
                                     "as select a.k1, b.k2 from tt1 a join tt2 b on a.k1=b.k1;");
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+                    Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_with_join0"));
+                    MaterializedView materializedView =
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "mv_with_join0"));
                     Assert.assertEquals(2, materializedView.getPartitionExprMaps().size());
                     Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
                     Map<String, String> testProperties = task.getProperties();
                     testProperties.put(TaskRun.IS_TEST, "true");
 
-                    OlapTable tbl1 = (OlapTable) testDb.getTable("tt1");
-                    OlapTable tbl2 = (OlapTable) testDb.getTable("tt2");
+                    OlapTable tbl1 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(testDb.getFullName(), "tt1");
+                    OlapTable tbl2 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(testDb.getFullName(), "tt2");
                     TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
                     taskRun.initStatus(UUIDUtil.genUUID().toString(), System.currentTimeMillis());
                     taskRun.executeTaskRun();
@@ -1471,9 +1504,11 @@ public void testFilterPartitionByJoinPredicate_RefreshPartitionNum() {
                     {
                         taskRun.initStatus(UUIDUtil.genUUID().toString(), System.currentTimeMillis());
                         taskRun.executeTaskRun();
-                        MvTaskRunContext mvContext = ((PartitionBasedMvRefreshProcessor) taskRun.getProcessor()).getMvContext();
+                        MvTaskRunContext mvContext =
+                                ((PartitionBasedMvRefreshProcessor) taskRun.getProcessor()).getMvContext();
                         Assert.assertTrue(mvContext.hasNextBatchPartition());
-                        PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
+                        PartitionBasedMvRefreshProcessor processor =
+                                (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
                         System.out.println(processor.getMVTaskRunExtraMessage());
                         Assert.assertEquals(Sets.newHashSet("p1"),
                                 processor.getMVTaskRunExtraMessage().getMvPartitionsToRefresh());
@@ -1495,9 +1530,11 @@ public void testFilterPartitionByJoinPredicate_RefreshPartitionNum() {
                     {
                         taskRun.initStatus(UUIDUtil.genUUID().toString(), System.currentTimeMillis());
                         taskRun.executeTaskRun();
-                        MvTaskRunContext mvContext = ((PartitionBasedMvRefreshProcessor) taskRun.getProcessor()).getMvContext();
+                        MvTaskRunContext mvContext =
+                                ((PartitionBasedMvRefreshProcessor) taskRun.getProcessor()).getMvContext();
                         Assert.assertTrue(!mvContext.hasNextBatchPartition());
-                        PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
+                        PartitionBasedMvRefreshProcessor processor =
+                                (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
                         System.out.println(processor.getMVTaskRunExtraMessage());
                         Assert.assertEquals(Sets.newHashSet("p2"),
                                 processor.getMVTaskRunExtraMessage().getMvPartitionsToRefresh());
@@ -1556,18 +1593,24 @@ public void testFilterPartitionByJoinPredicateWithNonPartitionTable() {
                                     "as select a.k1, b.k2 from tt1 a join tt2 b on a.k1=b.k1;",
                             (name) -> {
                                 String mvName = (String) name;
-                                Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-                                MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                                Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+                                MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                .getTable(testDb.getFullName(), mvName));
                                 Assert.assertEquals(2, materializedView.getPartitionExprMaps().size());
 
-                                OlapTable tbl1 = (OlapTable) testDb.getTable("tt1");
-                                OlapTable tbl2 = (OlapTable) testDb.getTable("tt2");
+                                OlapTable tbl1 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                        .getTable(testDb.getFullName(), "tt1");
+                                OlapTable tbl2 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                        .getTable(testDb.getFullName(), "tt2");
                                 TaskRun taskRun = buildMVTaskRun(materializedView, TEST_DB_NAME);
                                 taskRun.initStatus(UUIDUtil.genUUID().toString(), System.currentTimeMillis());
                                 taskRun.executeTaskRun();
 
-                                executeInsertSql(connectContext, "insert into tt1 partition(p1) values('2022-01-02', 3, 10);");
-                                executeInsertSql(connectContext, "insert into tt1 partition(p2) values('2022-02-02', 3, 10);");
+                                executeInsertSql(connectContext,
+                                        "insert into tt1 partition(p1) values('2022-01-02', 3, 10);");
+                                executeInsertSql(connectContext,
+                                        "insert into tt1 partition(p2) values('2022-02-02', 3, 10);");
                                 executeInsertSql(connectContext, "insert into tt2 values('2022-02-02', 3, 10);");
 
                                 List<String> tt1Partitions = ImmutableList.of("p0", "p1", "p2");
@@ -1588,12 +1631,14 @@ public void testFilterPartitionByJoinPredicateWithNonPartitionTable() {
 
                                     MaterializedView.AsyncRefreshContext asyncRefreshContext =
                                             materializedView.getRefreshScheme().getAsyncRefreshContext();
-                                    Map<Long, Map<String, MaterializedView.BasePartitionInfo>> baseTableVisibleVersionMap =
+                                    Map<Long, Map<String, MaterializedView.BasePartitionInfo>>
+                                            baseTableVisibleVersionMap =
                                             asyncRefreshContext.getBaseTableVisibleVersionMap();
                                     System.out.println(baseTableVisibleVersionMap);
 
                                     Assert.assertTrue(baseTableVisibleVersionMap.containsKey(tbl1.getId()));
-                                    Assert.assertTrue(baseTableVisibleVersionMap.get(tbl1.getId()).containsKey(tt1Partition));
+                                    Assert.assertTrue(
+                                            baseTableVisibleVersionMap.get(tbl1.getId()).containsKey(tt1Partition));
                                     Assert.assertTrue(baseTableVisibleVersionMap.containsKey(tbl2.getId()));
                                     taskRun = processor.getNextTaskRun();
                                     Assert.assertTrue(isEnd ? taskRun == null : taskRun != null);
@@ -1636,14 +1681,18 @@ public void testFilterPartitionByJoinPredicateWithNonPartition_RefreshPartitionN
                                     "PROPERTIES('partition_refresh_number' = '1')" +
                                     "refresh deferred manual\n" +
                                     "as select a.k1, b.k2 from tt1 a join tt2 b on a.k1=b.k1;");
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+                    Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("mv_with_join0"));
+                    MaterializedView materializedView =
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "mv_with_join0"));
                     Assert.assertEquals(2, materializedView.getPartitionExprMaps().size());
                     TaskRun taskRun = buildMVTaskRun(materializedView, TEST_DB_NAME);
 
-                    OlapTable tbl1 = (OlapTable) testDb.getTable("tt1");
-                    OlapTable tbl2 = (OlapTable) testDb.getTable("tt2");
+                    OlapTable tbl1 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(testDb.getFullName(), "tt1");
+                    OlapTable tbl2 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                            .getTable(testDb.getFullName(), "tt2");
                     taskRun.initStatus(UUIDUtil.genUUID().toString(), System.currentTimeMillis());
                     taskRun.executeTaskRun();
 
@@ -1653,9 +1702,11 @@ public void testFilterPartitionByJoinPredicateWithNonPartition_RefreshPartitionN
                     {
                         taskRun.initStatus(UUIDUtil.genUUID().toString(), System.currentTimeMillis());
                         taskRun.executeTaskRun();
-                        MvTaskRunContext mvContext = ((PartitionBasedMvRefreshProcessor) taskRun.getProcessor()).getMvContext();
+                        MvTaskRunContext mvContext =
+                                ((PartitionBasedMvRefreshProcessor) taskRun.getProcessor()).getMvContext();
                         Assert.assertTrue(mvContext.hasNextBatchPartition());
-                        PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
+                        PartitionBasedMvRefreshProcessor processor =
+                                (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
                         System.out.println(processor.getMVTaskRunExtraMessage());
                         Assert.assertEquals(Sets.newHashSet("p0"),
                                 processor.getMVTaskRunExtraMessage().getMvPartitionsToRefresh());
@@ -1678,9 +1729,11 @@ public void testFilterPartitionByJoinPredicateWithNonPartition_RefreshPartitionN
                     {
                         taskRun.initStatus(UUIDUtil.genUUID().toString(), System.currentTimeMillis());
                         taskRun.executeTaskRun();
-                        MvTaskRunContext mvContext = ((PartitionBasedMvRefreshProcessor) taskRun.getProcessor()).getMvContext();
+                        MvTaskRunContext mvContext =
+                                ((PartitionBasedMvRefreshProcessor) taskRun.getProcessor()).getMvContext();
                         Assert.assertTrue(!mvContext.hasNextBatchPartition());
-                        PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
+                        PartitionBasedMvRefreshProcessor processor =
+                                (PartitionBasedMvRefreshProcessor) taskRun.getProcessor();
                         System.out.println(processor.getMVTaskRunExtraMessage());
                         Assert.assertEquals(Sets.newHashSet("p1"),
                                 processor.getMVTaskRunExtraMessage().getMvPartitionsToRefresh());
@@ -1736,8 +1789,11 @@ public void testMVPartitionMappingWithManyToMany() {
                                     "properties('replication_num' = '1', 'partition_refresh_number'='1')\n" +
                                     "as select k1, k2, v1 from mock_tbl;",
                             (mvName) -> {
-                                Database testDb = GlobalStateMgr.getCurrentState().getDb(TEST_DB_NAME);
-                                MaterializedView materializedView = ((MaterializedView) testDb.getTable((String) mvName));
+                                Database testDb =
+                                        GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(TEST_DB_NAME);
+                                MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                .getTable(testDb.getFullName(), (String) mvName));
                                 Assert.assertEquals(1, materializedView.getPartitionExprMaps().size());
 
                                 // initial refresh
@@ -1759,7 +1815,10 @@ public void testMVPartitionMappingWithManyToMany() {
                                     Map<Long, TableSnapshotInfo> snapshotInfoMap = processor.getSnapshotBaseTables();
                                     Assert.assertEquals(1, snapshotInfoMap.size());
                                     TableSnapshotInfo tableSnapshotInfo =
-                                            snapshotInfoMap.get(testDb.getTable("mock_tbl").getId());
+                                            snapshotInfoMap.get(
+                                                    GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                            .getTable(testDb.getFullName(), "mock_tbl")
+                                                            .getId());
                                     Assert.assertEquals(Sets.newHashSet("p0", "p1", "p2"),
                                             tableSnapshotInfo.getRefreshedPartitionInfos().keySet());
 
@@ -1789,7 +1848,10 @@ public void testMVPartitionMappingWithManyToMany() {
                                     Map<Long, TableSnapshotInfo> snapshotInfoMap = processor.getSnapshotBaseTables();
                                     Assert.assertEquals(1, snapshotInfoMap.size());
                                     TableSnapshotInfo tableSnapshotInfo =
-                                            snapshotInfoMap.get(testDb.getTable("mock_tbl").getId());
+                                            snapshotInfoMap.get(
+                                                    GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                            .getTable(testDb.getFullName(), "mock_tbl")
+                                                            .getId());
                                     System.out.println(processor.getMVTaskRunExtraMessage());
                                     Assert.assertEquals(Sets.newHashSet("p0", "p1", "p2", "p3"),
                                             tableSnapshotInfo.getRefreshedPartitionInfos().keySet());
@@ -1830,8 +1892,11 @@ public void testMVPartitionMappingWithOneToMany() {
                                     "properties('replication_num' = '1', 'partition_refresh_number'='1')\n" +
                                     "as select k1, k2, v1 from mock_tbl;",
                             (mvName) -> {
-                                Database testDb = GlobalStateMgr.getCurrentState().getDb(TEST_DB_NAME);
-                                MaterializedView materializedView = ((MaterializedView) testDb.getTable((String) mvName));
+                                Database testDb =
+                                        GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(TEST_DB_NAME);
+                                MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                .getTable(testDb.getFullName(), (String) mvName));
                                 Assert.assertEquals(1, materializedView.getPartitionExprMaps().size());
 
                                 // initial refresh
@@ -1853,13 +1918,17 @@ public void testMVPartitionMappingWithOneToMany() {
                                     Map<Long, TableSnapshotInfo> snapshotInfoMap = processor.getSnapshotBaseTables();
                                     Assert.assertEquals(1, snapshotInfoMap.size());
                                     TableSnapshotInfo tableSnapshotInfo =
-                                            snapshotInfoMap.get(testDb.getTable("mock_tbl").getId());
+                                            snapshotInfoMap.get(
+                                                    GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                            .getTable(testDb.getFullName(), "mock_tbl")
+                                                            .getId());
                                     Assert.assertEquals(Sets.newHashSet("p0"),
                                             tableSnapshotInfo.getRefreshedPartitionInfos().keySet());
 
                                     MVTaskRunExtraMessage extraMessage = processor.getMVTaskRunExtraMessage();
                                     System.out.println(processor.getMVTaskRunExtraMessage());
-                                    Assert.assertTrue(extraMessage.getMvPartitionsToRefresh().contains("p20210723_20210724"));
+                                    Assert.assertTrue(
+                                            extraMessage.getMvPartitionsToRefresh().contains("p20210723_20210724"));
                                     Assert.assertEquals(Sets.newHashSet("p0"),
                                             extraMessage.getBasePartitionsToRefreshMap().get("mock_tbl"));
                                     Assert.assertTrue(processor.getNextTaskRun() == null);
@@ -1879,14 +1948,18 @@ public void testMVPartitionMappingWithOneToMany() {
                                     Map<Long, TableSnapshotInfo> snapshotInfoMap = processor.getSnapshotBaseTables();
                                     Assert.assertEquals(1, snapshotInfoMap.size());
                                     TableSnapshotInfo tableSnapshotInfo =
-                                            snapshotInfoMap.get(testDb.getTable("mock_tbl").getId());
+                                            snapshotInfoMap.get(
+                                                    GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                            .getTable(testDb.getFullName(), "mock_tbl")
+                                                            .getId());
                                     System.out.println(processor.getMVTaskRunExtraMessage());
                                     Assert.assertEquals(Sets.newHashSet("p1", "p2"),
                                             tableSnapshotInfo.getRefreshedPartitionInfos().keySet());
 
                                     MVTaskRunExtraMessage extraMessage = processor.getMVTaskRunExtraMessage();
                                     System.out.println(processor.getMVTaskRunExtraMessage());
-                                    Assert.assertTrue(extraMessage.getMvPartitionsToRefresh().contains("p20210811_20210812"));
+                                    Assert.assertTrue(
+                                            extraMessage.getMvPartitionsToRefresh().contains("p20210811_20210812"));
                                     Assert.assertEquals(Sets.newHashSet("p1", "p2"),
                                             extraMessage.getBasePartitionsToRefreshMap().get("mock_tbl"));
                                     Assert.assertTrue(processor.getNextTaskRun() == null);
@@ -1929,8 +2002,11 @@ public void testShowMaterializedViewsWithNonForce() {
                                     "as select k1, k2 from mockTbl;",
                             () -> {
                                 String mvName = "mock_mv0";
-                                Database testDb = GlobalStateMgr.getCurrentState().getDb(TEST_DB_NAME);
-                                MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                                Database testDb =
+                                        GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(TEST_DB_NAME);
+                                MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                .getTable(testDb.getFullName(), mvName));
                                 TaskManager tm = GlobalStateMgr.getCurrentState().getTaskManager();
 
                                 executeInsertSql(connectContext, mTable.getGenerateDataSQL());
@@ -1938,8 +2014,7 @@ public void testShowMaterializedViewsWithNonForce() {
                                 // refresh materialized view(non force)
                                 starRocksAssert.refreshMV(String.format("REFRESH MATERIALIZED VIEW %s", mvName));
                                 String mvTaskName = TaskBuilder.getMvTaskName(materializedView.getId());
-                                Map<String, List<TaskRunStatus>> taskNameJobStatusMap =
-                                        tm.listMVRefreshedTaskRunStatus(TEST_DB_NAME, Set.of(mvTaskName));
+                                Thread.sleep(new Random().nextInt(2000));
                                 long taskId = tm.getTask(mvTaskName).getId();
                                 while (tm.getTaskRunScheduler().getRunnableTaskRun(taskId) != null) {
                                     Thread.sleep(100);
@@ -1949,6 +2024,8 @@ public void testShowMaterializedViewsWithNonForce() {
                                 Assert.assertFalse(tm.listMVRefreshedTaskRunStatus(null, null).isEmpty());
                                 // specific db
                                 Assert.assertFalse(tm.listMVRefreshedTaskRunStatus(TEST_DB_NAME, null).isEmpty());
+                                Map<String, List<TaskRunStatus>> taskNameJobStatusMap =
+                                        tm.listMVRefreshedTaskRunStatus(TEST_DB_NAME, Set.of(mvTaskName));
                                 Assert.assertEquals(1, taskNameJobStatusMap.size());
                                 List<TaskRunStatus> taskRunStatuses = taskNameJobStatusMap.get(mvTaskName);
                                 // task runs may be gc, skip to check if it's not expected
@@ -1960,7 +2037,8 @@ public void testShowMaterializedViewsWithNonForce() {
                                                 materializedView.getName());
                                 System.out.println(status);
                                 status.setLastJobTaskRunStatus(taskRunStatuses);
-                                ShowMaterializedViewStatus.RefreshJobStatus refreshJobStatus = status.getRefreshJobStatus();
+                                ShowMaterializedViewStatus.RefreshJobStatus refreshJobStatus =
+                                        status.getRefreshJobStatus();
                                 System.out.println(refreshJobStatus);
                                 Assert.assertEquals(refreshJobStatus.isForce(), false);
                                 Assert.assertEquals(refreshJobStatus.isRefreshFinished(), true);
@@ -2013,8 +2091,11 @@ public void testShowMaterializedViewsWithPartialRefresh() {
                                     "as select k1, k2 from mockTbl;",
                             () -> {
                                 String mvName = "mock_mv0";
-                                Database testDb = GlobalStateMgr.getCurrentState().getDb(TEST_DB_NAME);
-                                MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                                Database testDb =
+                                        GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(TEST_DB_NAME);
+                                MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                .getTable(testDb.getFullName(), mvName));
                                 TaskManager tm = GlobalStateMgr.getCurrentState().getTaskManager();
 
                                 executeInsertSql(connectContext, mTable.getGenerateDataSQL());
@@ -2034,6 +2115,7 @@ public void testShowMaterializedViewsWithPartialRefresh() {
                                 // specific db
                                 Assert.assertFalse(tm.listMVRefreshedTaskRunStatus(TEST_DB_NAME, null).isEmpty());
 
+                                Thread.sleep(new Random().nextInt(2000));
                                 Map<String, List<TaskRunStatus>> taskNameJobStatusMap =
                                         tm.listMVRefreshedTaskRunStatus(TEST_DB_NAME, Set.of(mvTaskName));
                                 System.out.println(taskNameJobStatusMap);
@@ -2048,7 +2130,8 @@ public void testShowMaterializedViewsWithPartialRefresh() {
                                         new ShowMaterializedViewStatus(materializedView.getId(), TEST_DB_NAME,
                                                 materializedView.getName());
                                 status.setLastJobTaskRunStatus(taskNameJobStatusMap.get(mvTaskName));
-                                ShowMaterializedViewStatus.RefreshJobStatus refreshJobStatus = status.getRefreshJobStatus();
+                                ShowMaterializedViewStatus.RefreshJobStatus refreshJobStatus =
+                                        status.getRefreshJobStatus();
                                 System.out.println(refreshJobStatus);
                                 Assert.assertEquals(refreshJobStatus.isForce(), false);
                                 Assert.assertEquals(refreshJobStatus.isRefreshFinished(), true);
@@ -2099,20 +2182,26 @@ public void testShowMaterializedViewsWithForce() {
                                     "as select k1, k2 from mockTbl;",
                             () -> {
                                 String mvName = "mock_mv0";
-                                Database testDb = GlobalStateMgr.getCurrentState().getDb(TEST_DB_NAME);
-                                MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                                Database testDb =
+                                        GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(TEST_DB_NAME);
+                                MaterializedView materializedView =
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                .getTable(testDb.getFullName(), mvName));
                                 TaskManager tm = GlobalStateMgr.getCurrentState().getTaskManager();
 
                                 // refresh materialized view(force)
                                 refreshMVRange(mvName, "2021-12-01", "2022-03-01", true);
 
+                                String mvTaskName = TaskBuilder.getMvTaskName(materializedView.getId());
+                                long taskId = tm.getTask(mvTaskName).getId();
+                                while (tm.getTaskRunScheduler().getRunnableTaskRun(taskId) != null) {
+                                    Thread.sleep(100);
+                                }
                                 // without db name
                                 Assert.assertFalse(tm.listMVRefreshedTaskRunStatus(null, null).isEmpty());
-
                                 // specific db
                                 Assert.assertFalse(tm.listMVRefreshedTaskRunStatus(TEST_DB_NAME, null).isEmpty());
-
-                                String mvTaskName = TaskBuilder.getMvTaskName(materializedView.getId());
+                                Thread.sleep(new Random().nextInt(2000));
                                 Map<String, List<TaskRunStatus>> taskNameJobStatusMap =
                                         tm.listMVRefreshedTaskRunStatus(TEST_DB_NAME, Set.of(mvTaskName));
                                 System.out.println(taskNameJobStatusMap);
@@ -2123,7 +2212,8 @@ public void testShowMaterializedViewsWithForce() {
                                         new ShowMaterializedViewStatus(materializedView.getId(), TEST_DB_NAME,
                                                 materializedView.getName());
                                 status.setLastJobTaskRunStatus(taskNameJobStatusMap.get(mvTaskName));
-                                ShowMaterializedViewStatus.RefreshJobStatus refreshJobStatus = status.getRefreshJobStatus();
+                                ShowMaterializedViewStatus.RefreshJobStatus refreshJobStatus =
+                                        status.getRefreshJobStatus();
                                 System.out.println(refreshJobStatus);
                                 Assert.assertEquals(refreshJobStatus.isForce(), true);
                                 Assert.assertEquals(refreshJobStatus.isRefreshFinished(), true);
@@ -2179,10 +2269,11 @@ public void testMVRefreshStatus() {
                                     "refresh deferred manual\n" +
                                     "as select a.k1, b.k2 from tt1 a join tt2 b on a.k1=b.k1;",
                             () -> {
-                                Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+                                Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
                                 MaterializedView materializedView =
-                                        ((MaterializedView) testDb.getTable("mv_with_join0"));
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                .getTable(testDb.getFullName(), "mv_with_join0"));
                                 Assert.assertEquals(2, materializedView.getPartitionExprMaps().size());
                                 Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
                                 Map<String, String> testProperties = task.getProperties();
@@ -2200,7 +2291,8 @@ public void testMVRefreshStatus() {
                                 String jobID = "";
                                 {
                                     TaskRunStatus taskRunStatus =
-                                            taskRun.initStatus(UUIDUtil.genUUID().toString(), System.currentTimeMillis());
+                                            taskRun.initStatus(UUIDUtil.genUUID().toString(),
+                                                    System.currentTimeMillis());
                                     taskRun.executeTaskRun();
                                     taskRunStatus.setState(Constants.TaskRunState.SUCCESS);
 
@@ -2240,7 +2332,8 @@ public void testMVRefreshStatus() {
 
                                 {
                                     TaskRunStatus taskRunStatus =
-                                            taskRun.initStatus(UUIDUtil.genUUID().toString(), System.currentTimeMillis());
+                                            taskRun.initStatus(UUIDUtil.genUUID().toString(),
+                                                    System.currentTimeMillis());
                                     taskRun.executeTaskRun();
                                     taskRunStatus.setState(Constants.TaskRunState.SUCCESS);
 
@@ -2321,10 +2414,11 @@ public void testMVRefreshWithFailedStatus() {
                                     "refresh deferred manual\n" +
                                     "as select a.k1, b.k2 from tt1 a join tt2 b on a.k1=b.k1;",
                             () -> {
-                                Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+                                Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
                                 MaterializedView materializedView =
-                                        ((MaterializedView) testDb.getTable("mv_with_join0"));
+                                        ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                .getTable(testDb.getFullName(), "mv_with_join0"));
                                 Assert.assertEquals(2, materializedView.getPartitionExprMaps().size());
                                 Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
                                 Map<String, String> testProperties = task.getProperties();
@@ -2386,8 +2480,10 @@ public void testRefreshWithTraceProfile() {
                         "as select k1, k2 from tbl1;",
                 () -> {
                     Config.enable_mv_refresh_query_rewrite = false;
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("test_mv1"));
+                    Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+                    MaterializedView materializedView =
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "test_mv1"));
 
                     String insertSql = "insert into tbl1 partition(p3) values('2022-03-01', 3, 10);";
                     executeInsertSql(connectContext, insertSql);
diff --git a/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorPaimonTest.java b/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorPaimonTest.java
index 1f9a85ec83949e..14f18af2320472 100644
--- a/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorPaimonTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshProcessorPaimonTest.java
@@ -74,10 +74,11 @@ public void testcreateUnpartitionedPmnMaterializeView() {
                         ")\n" +
                         "AS SELECT pk, d  FROM `paimon0`.`pmn_db1`.`unpartitioned_table` as a;",
                 () -> {
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+                    Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
                     MaterializedView unpartitionedMaterializedView =
-                            ((MaterializedView) testDb.getTable("paimon_parttbl_mv2"));
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "paimon_parttbl_mv2"));
                     triggerRefreshMv(testDb, unpartitionedMaterializedView);
 
                     Collection<Partition> partitions = unpartitionedMaterializedView.getPartitions();
@@ -104,9 +105,10 @@ public void testCreatePartitionedPmnMaterializeView() {
                         ")\n" +
                         "AS SELECT pk, pt,d  FROM `paimon0`.`pmn_db1`.`partitioned_table` as a;",
                 () -> {
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+                    Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
                     MaterializedView partitionedMaterializedView =
-                            ((MaterializedView) testDb.getTable("paimon_parttbl_mv1"));
+                            ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "paimon_parttbl_mv1"));
                     triggerRefreshMv(testDb, partitionedMaterializedView);
 
                     Collection<Partition> partitions = partitionedMaterializedView.getPartitions();
diff --git a/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshTest.java b/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshTest.java
index 294bf26870f3b8..3a37479666c238 100644
--- a/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/scheduler/PartitionBasedMvRefreshTest.java
@@ -49,62 +49,62 @@ public static void beforeClass() throws Exception {
         MVRefreshTestBase.beforeClass();
         ConnectorPlanTestBase.mockAllCatalogs(connectContext, temp.newFolder().toURI().toString());
         starRocksAssert
-                .withTable("CREATE TABLE `t1` (\n" +
-                        "    `k1`  date not null, \n" +
-                        "    `k2`  datetime not null, \n" +
-                        "    `k3`  char(20), \n" +
-                        "    `k4`  varchar(20), \n" +
-                        "    `k5`  boolean, \n" +
-                        "    `k6`  tinyint, \n" +
-                        "    `k7`  smallint, \n" +
-                        "    `k8`  int, \n" +
-                        "    `k9`  bigint, \n" +
-                        "    `k10` largeint, \n" +
-                        "    `k11` float, \n" +
-                        "    `k12` double, \n" +
-                        "    `k13` decimal(27,9) ) \n" +
-                        "DUPLICATE KEY(`k1`, `k2`, `k3`, `k4`, `k5`) \n" +
-                        "PARTITION BY RANGE(`k1`) \n" +
-                        "(\n" +
-                        "PARTITION p20201022 VALUES [(\"2020-10-22\"), (\"2020-10-23\")), \n" +
-                        "PARTITION p20201023 VALUES [(\"2020-10-23\"), (\"2020-10-24\")), \n" +
-                        "PARTITION p20201024 VALUES [(\"2020-10-24\"), (\"2020-10-25\"))\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(`k1`, `k2`, `k3`) BUCKETS 3;")
-                .withTable("CREATE TABLE `t2` (\n" +
-                        "    `k1`  date not null, \n" +
-                        "    `k2`  datetime not null, \n" +
-                        "    `k3`  char(20), \n" +
-                        "    `k4`  varchar(20), \n" +
-                        "    `k5`  boolean, \n" +
-                        "    `k6`  tinyint, \n" +
-                        "    `k7`  smallint, \n" +
-                        "    `k8`  int, \n" +
-                        "    `k9`  bigint, \n" +
-                        "    `k10` largeint, \n" +
-                        "    `k11` float, \n" +
-                        "    `k12` double, \n" +
-                        "    `k13` decimal(27,9) ) \n" +
-                        "DUPLICATE KEY(`k1`, `k2`, `k3`, `k4`, `k5`) \n" +
-                        "PARTITION BY RANGE(`k1`) \n" +
-                        "(\n" +
-                        "PARTITION p20201010 VALUES [(\"2020-10-10\"), (\"2020-10-11\")), \n" +
-                        "PARTITION p20201011 VALUES [(\"2020-10-11\"), (\"2020-10-12\")), \n" +
-                        "PARTITION p20201012 VALUES [(\"2020-10-12\"), (\"2020-10-13\")), \n" +
-                        "PARTITION p20201021 VALUES [(\"2020-10-21\"), (\"2020-10-22\")), \n" +
-                        "PARTITION p20201022 VALUES [(\"2020-10-22\"), (\"2020-10-23\"))\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(`k1`, `k2`, `k3`) BUCKETS 3;");
+                    .withTable("CREATE TABLE `t1` (\n" +
+                                "    `k1`  date not null, \n" +
+                                "    `k2`  datetime not null, \n" +
+                                "    `k3`  char(20), \n" +
+                                "    `k4`  varchar(20), \n" +
+                                "    `k5`  boolean, \n" +
+                                "    `k6`  tinyint, \n" +
+                                "    `k7`  smallint, \n" +
+                                "    `k8`  int, \n" +
+                                "    `k9`  bigint, \n" +
+                                "    `k10` largeint, \n" +
+                                "    `k11` float, \n" +
+                                "    `k12` double, \n" +
+                                "    `k13` decimal(27,9) ) \n" +
+                                "DUPLICATE KEY(`k1`, `k2`, `k3`, `k4`, `k5`) \n" +
+                                "PARTITION BY RANGE(`k1`) \n" +
+                                "(\n" +
+                                "PARTITION p20201022 VALUES [(\"2020-10-22\"), (\"2020-10-23\")), \n" +
+                                "PARTITION p20201023 VALUES [(\"2020-10-23\"), (\"2020-10-24\")), \n" +
+                                "PARTITION p20201024 VALUES [(\"2020-10-24\"), (\"2020-10-25\"))\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(`k1`, `k2`, `k3`) BUCKETS 3;")
+                    .withTable("CREATE TABLE `t2` (\n" +
+                                "    `k1`  date not null, \n" +
+                                "    `k2`  datetime not null, \n" +
+                                "    `k3`  char(20), \n" +
+                                "    `k4`  varchar(20), \n" +
+                                "    `k5`  boolean, \n" +
+                                "    `k6`  tinyint, \n" +
+                                "    `k7`  smallint, \n" +
+                                "    `k8`  int, \n" +
+                                "    `k9`  bigint, \n" +
+                                "    `k10` largeint, \n" +
+                                "    `k11` float, \n" +
+                                "    `k12` double, \n" +
+                                "    `k13` decimal(27,9) ) \n" +
+                                "DUPLICATE KEY(`k1`, `k2`, `k3`, `k4`, `k5`) \n" +
+                                "PARTITION BY RANGE(`k1`) \n" +
+                                "(\n" +
+                                "PARTITION p20201010 VALUES [(\"2020-10-10\"), (\"2020-10-11\")), \n" +
+                                "PARTITION p20201011 VALUES [(\"2020-10-11\"), (\"2020-10-12\")), \n" +
+                                "PARTITION p20201012 VALUES [(\"2020-10-12\"), (\"2020-10-13\")), \n" +
+                                "PARTITION p20201021 VALUES [(\"2020-10-21\"), (\"2020-10-22\")), \n" +
+                                "PARTITION p20201022 VALUES [(\"2020-10-22\"), (\"2020-10-23\"))\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(`k1`, `k2`, `k3`) BUCKETS 3;");
         executeInsertSql(connectContext, "INSERT INTO t1 VALUES\n" +
-                "    ('2020-10-22','2020-10-23 12:12:12','k3','k4',0,1,2,3,4,5,1.1,1.12,2.889),\n" +
-                "    ('2020-10-23','2020-10-24 12:12:12','k3','k4',0,0,2,3,4,5,1.1,1.12,2.889),\n" +
-                "    ('2020-10-24','2020-10-25 12:12:12','k3','k4',0,1,2,3,4,5,1.1,1.12,2.889);");
+                    "    ('2020-10-22','2020-10-23 12:12:12','k3','k4',0,1,2,3,4,5,1.1,1.12,2.889),\n" +
+                    "    ('2020-10-23','2020-10-24 12:12:12','k3','k4',0,0,2,3,4,5,1.1,1.12,2.889),\n" +
+                    "    ('2020-10-24','2020-10-25 12:12:12','k3','k4',0,1,2,3,4,5,1.1,1.12,2.889);");
         executeInsertSql(connectContext, "INSERT INTO t2 VALUES\n" +
-                "    ('2020-10-10','2020-10-23 12:12:12','k3','k4',0,1,2,3,4,5,1.1,1.12,2.889),\n" +
-                "    ('2020-10-11','2020-10-24 12:12:12','k3','k4',0,0,2,3,4,5,1.1,1.12,2.889),\n" +
-                "    ('2020-10-12','2020-10-25 12:12:12','k3','k4',0,1,2,3,4,5,1.1,1.12,2.889),\n" +
-                "    ('2020-10-21','2020-10-24 12:12:12','k3','k4',0,0,2,3,4,5,1.1,1.12,2.889),\n" +
-                "    ('2020-10-22','2020-10-25 12:12:12','k3','k4',0,1,2,3,4,5,1.1,1.12,2.889)");
+                    "    ('2020-10-10','2020-10-23 12:12:12','k3','k4',0,1,2,3,4,5,1.1,1.12,2.889),\n" +
+                    "    ('2020-10-11','2020-10-24 12:12:12','k3','k4',0,0,2,3,4,5,1.1,1.12,2.889),\n" +
+                    "    ('2020-10-12','2020-10-25 12:12:12','k3','k4',0,1,2,3,4,5,1.1,1.12,2.889),\n" +
+                    "    ('2020-10-21','2020-10-24 12:12:12','k3','k4',0,0,2,3,4,5,1.1,1.12,2.889),\n" +
+                    "    ('2020-10-22','2020-10-25 12:12:12','k3','k4',0,1,2,3,4,5,1.1,1.12,2.889)");
     }
 
     @AfterClass
@@ -127,7 +127,7 @@ protected void assertPlanContains(ExecPlan execPlan, String... explain) throws E
 
         for (String expected : explain) {
             Assert.assertTrue("expected is: " + expected + " but plan is \n" + explainString,
-                    StringUtils.containsIgnoreCase(explainString.toLowerCase(), expected));
+                        StringUtils.containsIgnoreCase(explainString.toLowerCase(), expected));
         }
     }
 
@@ -156,49 +156,51 @@ private void testRefreshUnionAllWithDefaultRefreshNumber(String mvSql,
         Assert.assertTrue(t1PartitionNums.size() == t2PartitionNums.size());
         int mvRefreshTimes = t1PartitionNums.size();
         starRocksAssert.withMaterializedView(mvSql,
-                () -> {
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-                    MaterializedView mv = ((MaterializedView) testDb.getTable("test_mv0"));
-                    Task task = TaskBuilder.buildMvTask(mv, testDb.getFullName());
+                    () -> {
+                        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+                        MaterializedView mv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "test_mv0"));
+                        Task task = TaskBuilder.buildMvTask(mv, testDb.getFullName());
 
-                    TaskRun taskRun = null;
-                    for (int i = 0; i < mvRefreshTimes; i++) {
-                        if (i == 0) {
-                            taskRun = TaskRunBuilder.newBuilder(task).build();
+                        TaskRun taskRun = null;
+                        for (int i = 0; i < mvRefreshTimes; i++) {
+                            if (i == 0) {
+                                taskRun = TaskRunBuilder.newBuilder(task).build();
+                            }
+                            System.out.println("start to execute task run:" + i);
+                            Assert.assertTrue(taskRun != null);
+                            initAndExecuteTaskRun(taskRun);
+                            PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor)
+                                        taskRun.getProcessor();
+                            MvTaskRunContext mvContext = processor.getMvContext();
+                            ExecPlan execPlan = mvContext.getExecPlan();
+                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                            Assert.assertTrue(plan != null);
+                            taskRun = processor.getNextTaskRun();
+                            PlanTestBase.assertContains(plan, String.format("     TABLE: t1\n" +
+                                        "     PREAGGREGATION: ON\n" +
+                                        "     partitions=%s/3", t1PartitionNums.get(i)));
+                            PlanTestBase.assertContains(plan, String.format("     TABLE: t2\n" +
+                                        "     PREAGGREGATION: ON\n" +
+                                        "     partitions=%s/5", t2PartitionNums.get(i)));
+                            if (i == mvRefreshTimes - 1) {
+                                Assert.assertTrue(taskRun == null);
+                            }
                         }
-                        System.out.println("start to execute task run:" + i);
-                        Assert.assertTrue(taskRun != null);
-                        initAndExecuteTaskRun(taskRun);
-                        PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor)
-                                taskRun.getProcessor();
-                        MvTaskRunContext mvContext = processor.getMvContext();
-                        ExecPlan execPlan = mvContext.getExecPlan();
-                        String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                        Assert.assertTrue(plan != null);
-                        taskRun = processor.getNextTaskRun();
-                        PlanTestBase.assertContains(plan, String.format("     TABLE: t1\n" +
-                                "     PREAGGREGATION: ON\n" +
-                                "     partitions=%s/3", t1PartitionNums.get(i)));
-                        PlanTestBase.assertContains(plan, String.format("     TABLE: t2\n" +
-                                "     PREAGGREGATION: ON\n" +
-                                "     partitions=%s/5", t2PartitionNums.get(i)));
-                        if (i == mvRefreshTimes - 1) {
-                            Assert.assertTrue(taskRun == null);
-                        }
-                    }
-                });
+                    });
     }
+
     @Test
     public void testUnionAllMvWithPartition1() {
         String sql = "create materialized view test_mv0 \n" +
-                "partition by k1 \n" +
-                "distributed by random \n" +
-                "refresh async \n" +
-                "properties(" +
-                "\"partition_refresh_number\" = \"1\"" +
-                ")" +
-                "as " +
-                " select * from t1 union all select * from t2;";
+                    "partition by k1 \n" +
+                    "distributed by random \n" +
+                    "refresh async \n" +
+                    "properties(" +
+                    "\"partition_refresh_number\" = \"1\"" +
+                    ")" +
+                    "as " +
+                    " select * from t1 union all select * from t2;";
         List<Integer> t1PartitionNums = ImmutableList.of(0, 0, 0, 0, 1, 1, 1);
         List<Integer> t2PartitionNums = ImmutableList.of(1, 1, 1, 1, 1, 0, 0);
         testRefreshUnionAllWithDefaultRefreshNumber(sql, t1PartitionNums, t2PartitionNums);
@@ -207,14 +209,14 @@ public void testUnionAllMvWithPartition1() {
     @Test
     public void testUnionAllMvWithPartition2() {
         String sql = "create materialized view test_mv0 \n" +
-                "partition by k1 \n" +
-                "distributed by random \n" +
-                "refresh async \n" +
-                "properties(" +
-                "\"partition_refresh_number\" = \"1\"" +
-                ")" +
-                "as " +
-                " select * from t2 union all select * from t1;";
+                    "partition by k1 \n" +
+                    "distributed by random \n" +
+                    "refresh async \n" +
+                    "properties(" +
+                    "\"partition_refresh_number\" = \"1\"" +
+                    ")" +
+                    "as " +
+                    " select * from t2 union all select * from t1;";
         List<Integer> t1PartitionNums = ImmutableList.of(0, 0, 0, 0, 1, 1, 1);
         List<Integer> t2PartitionNums = ImmutableList.of(1, 1, 1, 1, 1, 0, 0);
         testRefreshUnionAllWithDefaultRefreshNumber(sql, t1PartitionNums, t2PartitionNums);
@@ -223,121 +225,123 @@ public void testUnionAllMvWithPartition2() {
     @Test
     public void testUnionAllMvWithPartitionForceMode() {
         String sql = "create materialized view test_mv0 \n" +
-                "partition by k1 \n" +
-                "distributed by random \n" +
-                "refresh async \n" +
-                "as " +
-                " select * from t1 union all select * from t2;";
+                    "partition by k1 \n" +
+                    "distributed by random \n" +
+                    "refresh async \n" +
+                    "as " +
+                    " select * from t1 union all select * from t2;";
         starRocksAssert.withMaterializedView(sql,
-                () -> {
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-                    MaterializedView mv = ((MaterializedView) testDb.getTable("test_mv0"));
-                    Task task = TaskBuilder.buildMvTask(mv, testDb.getFullName());
+                    () -> {
+                        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+                        MaterializedView mv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "test_mv0"));
+                        Task task = TaskBuilder.buildMvTask(mv, testDb.getFullName());
 
-                    TaskRun taskRun = null;
-                    int refreshTimes = 1;
-                    for (int i = 0; i < refreshTimes; i++) {
-                        if (i == 0) {
-                            taskRun = TaskRunBuilder.newBuilder(task).build();
-                        }
-                        System.out.println("start to execute task run:" + i);
-                        Assert.assertTrue(taskRun != null);
-                        initAndExecuteTaskRun(taskRun);
-                        PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor)
-                                taskRun.getProcessor();
-                        MvTaskRunContext mvContext = processor.getMvContext();
-                        ExecPlan execPlan = mvContext.getExecPlan();
-                        String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                        taskRun = processor.getNextTaskRun();
+                        TaskRun taskRun = null;
+                        int refreshTimes = 1;
+                        for (int i = 0; i < refreshTimes; i++) {
+                            if (i == 0) {
+                                taskRun = TaskRunBuilder.newBuilder(task).build();
+                            }
+                            System.out.println("start to execute task run:" + i);
+                            Assert.assertTrue(taskRun != null);
+                            initAndExecuteTaskRun(taskRun);
+                            PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor)
+                                        taskRun.getProcessor();
+                            MvTaskRunContext mvContext = processor.getMvContext();
+                            ExecPlan execPlan = mvContext.getExecPlan();
+                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                            taskRun = processor.getNextTaskRun();
 
-                        PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
-                                "     PREAGGREGATION: ON\n" +
-                                "     partitions=3/3");
-                        PlanTestBase.assertContains(plan, "     TABLE: t2\n" +
-                                "     PREAGGREGATION: ON\n" +
-                                "     partitions=5/5");
-                        if (i == refreshTimes - 1) {
-                            Assert.assertTrue(taskRun == null);
+                            PlanTestBase.assertContains(plan, "     TABLE: t1\n" +
+                                        "     PREAGGREGATION: ON\n" +
+                                        "     partitions=3/3");
+                            PlanTestBase.assertContains(plan, "     TABLE: t2\n" +
+                                        "     PREAGGREGATION: ON\n" +
+                                        "     partitions=5/5");
+                            if (i == refreshTimes - 1) {
+                                Assert.assertTrue(taskRun == null);
+                            }
                         }
-                    }
-                });
+                    });
     }
 
     @Test
     public void testUnionAllMvWithPartitionWithPartitionStartAndEnd() {
         String sql = "create materialized view test_mv0 \n" +
-                "partition by k1 \n" +
-                "distributed by random \n" +
-                "refresh async \n" +
-                "properties(" +
-                "\"partition_refresh_number\" = \"1\"" +
-                ")" +
-                "as " +
-                " select * from t2 union all select * from t1;";
+                    "partition by k1 \n" +
+                    "distributed by random \n" +
+                    "refresh async \n" +
+                    "properties(" +
+                    "\"partition_refresh_number\" = \"1\"" +
+                    ")" +
+                    "as " +
+                    " select * from t2 union all select * from t1;";
         starRocksAssert.withMaterializedView(sql,
-                () -> {
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-                    MaterializedView mv = ((MaterializedView) testDb.getTable("test_mv0"));
+                    () -> {
+                        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+                        MaterializedView mv = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), "test_mv0"));
 
-                    Task task = TaskBuilder.buildMvTask(mv, testDb.getFullName());
-                    int mvRefreshTimes = 3;
-                    List<Integer> t1PartitionNums = ImmutableList.of(0, 0, 1);
-                    List<Integer> t2PartitionNums = ImmutableList.of(1, 1, 1);
-                    TaskRun taskRun = null;
-                    for (int i = 0; i < mvRefreshTimes; i++) {
-                        System.out.println("start to execute task run:" + i);
-                        if (i == 0) {
-                            taskRun = TaskRunBuilder.newBuilder(task).build();
-                            initAndExecuteTaskRun(taskRun, "2020-10-12", "2020-10-23");
-                        } else {
-                            ExecuteOption executeOption = taskRun.getExecuteOption();
-                            String partitionStart = executeOption.getTaskRunProperties().get(TaskRun.PARTITION_START);
-                            String partitionEnd = executeOption.getTaskRunProperties().get(TaskRun.PARTITION_END);
-                            initAndExecuteTaskRun(taskRun, partitionStart, partitionEnd);
-                        }
-                        PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor)
-                                taskRun.getProcessor();
-                        MvTaskRunContext mvContext = processor.getMvContext();
-                        ExecPlan execPlan = mvContext.getExecPlan();
-                        String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                        Assert.assertTrue(plan != null);
-                        taskRun = processor.getNextTaskRun();
-                        PlanTestBase.assertContains(plan, String.format("     TABLE: t1\n" +
-                                "     PREAGGREGATION: ON\n" +
-                                "     partitions=%s/3", t1PartitionNums.get(i)));
-                        PlanTestBase.assertContains(plan, String.format("     TABLE: t2\n" +
-                                "     PREAGGREGATION: ON\n" +
-                                "     partitions=%s/5", t2PartitionNums.get(i)));
-                        if (i == mvRefreshTimes - 1) {
-                            Assert.assertTrue(taskRun == null);
+                        Task task = TaskBuilder.buildMvTask(mv, testDb.getFullName());
+                        int mvRefreshTimes = 3;
+                        List<Integer> t1PartitionNums = ImmutableList.of(0, 0, 1);
+                        List<Integer> t2PartitionNums = ImmutableList.of(1, 1, 1);
+                        TaskRun taskRun = null;
+                        for (int i = 0; i < mvRefreshTimes; i++) {
+                            System.out.println("start to execute task run:" + i);
+                            if (i == 0) {
+                                taskRun = TaskRunBuilder.newBuilder(task).build();
+                                initAndExecuteTaskRun(taskRun, "2020-10-12", "2020-10-23");
+                            } else {
+                                ExecuteOption executeOption = taskRun.getExecuteOption();
+                                String partitionStart = executeOption.getTaskRunProperties().get(TaskRun.PARTITION_START);
+                                String partitionEnd = executeOption.getTaskRunProperties().get(TaskRun.PARTITION_END);
+                                initAndExecuteTaskRun(taskRun, partitionStart, partitionEnd);
+                            }
+                            PartitionBasedMvRefreshProcessor processor = (PartitionBasedMvRefreshProcessor)
+                                        taskRun.getProcessor();
+                            MvTaskRunContext mvContext = processor.getMvContext();
+                            ExecPlan execPlan = mvContext.getExecPlan();
+                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                            Assert.assertTrue(plan != null);
+                            taskRun = processor.getNextTaskRun();
+                            PlanTestBase.assertContains(plan, String.format("     TABLE: t1\n" +
+                                        "     PREAGGREGATION: ON\n" +
+                                        "     partitions=%s/3", t1PartitionNums.get(i)));
+                            PlanTestBase.assertContains(plan, String.format("     TABLE: t2\n" +
+                                        "     PREAGGREGATION: ON\n" +
+                                        "     partitions=%s/5", t2PartitionNums.get(i)));
+                            if (i == mvRefreshTimes - 1) {
+                                Assert.assertTrue(taskRun == null);
+                            }
                         }
-                    }
-                });
+                    });
     }
 
     @Test
     public void testJoinMV_SlotRef() throws Exception {
         starRocksAssert.withTable("CREATE TABLE join_base_t1 (dt1 date, int1 int)\n" +
-                "                    PARTITION BY RANGE(dt1)\n" +
-                "                    (\n" +
-                "                    PARTITION p1 VALUES LESS THAN (\"2020-07-01\"),\n" +
-                "                    PARTITION p2 VALUES LESS THAN (\"2020-08-01\"),\n" +
-                "                    PARTITION p3 VALUES LESS THAN (\"2020-09-01\")\n" +
-                "                    );");
+                    "                    PARTITION BY RANGE(dt1)\n" +
+                    "                    (\n" +
+                    "                    PARTITION p1 VALUES LESS THAN (\"2020-07-01\"),\n" +
+                    "                    PARTITION p2 VALUES LESS THAN (\"2020-08-01\"),\n" +
+                    "                    PARTITION p3 VALUES LESS THAN (\"2020-09-01\")\n" +
+                    "                    );");
         starRocksAssert.withTable("CREATE TABLE join_base_t2 (dt2 date, int2 int)\n" +
-                "                    PARTITION BY RANGE(dt2)\n" +
-                "                    (\n" +
-                "                    PARTITION p4 VALUES LESS THAN (\"2020-07-01\"),\n" +
-                "                    PARTITION p5 VALUES LESS THAN (\"2020-08-01\"),\n" +
-                "                    PARTITION p6 VALUES LESS THAN (\"2020-09-01\")\n" +
-                "                    );");
+                    "                    PARTITION BY RANGE(dt2)\n" +
+                    "                    (\n" +
+                    "                    PARTITION p4 VALUES LESS THAN (\"2020-07-01\"),\n" +
+                    "                    PARTITION p5 VALUES LESS THAN (\"2020-08-01\"),\n" +
+                    "                    PARTITION p6 VALUES LESS THAN (\"2020-09-01\")\n" +
+                    "                    );");
         starRocksAssert.withRefreshedMaterializedView("CREATE MATERIALIZED VIEW join_mv1 " +
-                "PARTITION BY dt1 " +
-                "REFRESH MANUAL " +
-                "PROPERTIES (\"partition_refresh_number\"=\"3\") AS " +
-                "SELECT dt1,dt2,sum(int1) " +
-                "FROM join_base_t1 t1 " +
-                "JOIN join_base_t2 t2 ON t1.dt1=t2.dt2 GROUP BY dt1,dt2;");
+                    "PARTITION BY dt1 " +
+                    "REFRESH MANUAL " +
+                    "PROPERTIES (\"partition_refresh_number\"=\"3\") AS " +
+                    "SELECT dt1,dt2,sum(int1) " +
+                    "FROM join_base_t1 t1 " +
+                    "JOIN join_base_t2 t2 ON t1.dt1=t2.dt2 GROUP BY dt1,dt2;");
 
         MaterializedView mv = starRocksAssert.getMv("test", "join_mv1");
         Assert.assertEquals(Sets.newHashSet("p1", "p2", "p3"), mv.getPartitionNames());
@@ -349,25 +353,25 @@ public void testJoinMV_SlotRef() throws Exception {
     @Test
     public void testJoinMV_ListPartition() throws Exception {
         starRocksAssert.withTable("CREATE TABLE join_base_t1 (dt1 date, int1 int)\n" +
-                "PARTITION BY RANGE(dt1)\n" +
-                "(\n" +
-                "    PARTITION p202006 VALUES LESS THAN (\"2020-07-01\"),\n" +
-                "    PARTITION p202007 VALUES LESS THAN (\"2020-08-01\"),\n" +
-                "    PARTITION p202008 VALUES LESS THAN (\"2020-09-01\")\n" +
-                ")");
+                    "PARTITION BY RANGE(dt1)\n" +
+                    "(\n" +
+                    "    PARTITION p202006 VALUES LESS THAN (\"2020-07-01\"),\n" +
+                    "    PARTITION p202007 VALUES LESS THAN (\"2020-08-01\"),\n" +
+                    "    PARTITION p202008 VALUES LESS THAN (\"2020-09-01\")\n" +
+                    ")");
         starRocksAssert.withTable("CREATE TABLE join_base_t2 (dt2 date not null, int2 int)\n" +
-                "PARTITION BY LIST(dt2)\n" +
-                "(\n" +
-                "    PARTITION p202006 VALUES in (\"2020-06-23\"),\n" +
-                "    PARTITION p202007 VALUES in (\"2020-07-23\"),\n" +
-                "    PARTITION p202008 VALUES in (\"2020-08-23\")\n" +
-                ");");
+                    "PARTITION BY LIST(dt2)\n" +
+                    "(\n" +
+                    "    PARTITION p202006 VALUES in (\"2020-06-23\"),\n" +
+                    "    PARTITION p202007 VALUES in (\"2020-07-23\"),\n" +
+                    "    PARTITION p202008 VALUES in (\"2020-08-23\")\n" +
+                    ");");
         Exception e = Assert.assertThrows(DmlException.class, () ->
-                starRocksAssert.withRefreshedMaterializedView("CREATE MATERIALIZED VIEW join_mv1 " +
-                        "PARTITION BY dt1 REFRESH MANUAL PROPERTIES (\"partition_refresh_number\"=\"3\") AS \n" +
-                        "SELECT dt1,dt2,sum(int1) " +
-                        "FROM join_base_t1 t1 " +
-                        "JOIN join_base_t2 t2 ON t1.dt1=t2.dt2 GROUP BY dt1,dt2")
+                    starRocksAssert.withRefreshedMaterializedView("CREATE MATERIALIZED VIEW join_mv1 " +
+                                "PARTITION BY dt1 REFRESH MANUAL PROPERTIES (\"partition_refresh_number\"=\"3\") AS \n" +
+                                "SELECT dt1,dt2,sum(int1) " +
+                                "FROM join_base_t1 t1 " +
+                                "JOIN join_base_t2 t2 ON t1.dt1=t2.dt2 GROUP BY dt1,dt2")
         );
         // TODO(fix me): throw a better stack
         System.out.println(e.getMessage());
diff --git a/fe/fe-core/src/test/java/com/starrocks/scheduler/mv/MVMaintenanceJobTest.java b/fe/fe-core/src/test/java/com/starrocks/scheduler/mv/MVMaintenanceJobTest.java
index 8855947b8cf848..d59ed7d4620355 100644
--- a/fe/fe-core/src/test/java/com/starrocks/scheduler/mv/MVMaintenanceJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/scheduler/mv/MVMaintenanceJobTest.java
@@ -126,7 +126,7 @@ public void buildPhysicalTopology() throws Exception {
                 pair.first);
 
         String currentDb = connectContext.getDatabase();
-        long dbId = GlobalStateMgr.getCurrentState().getDb(currentDb).getId();
+        long dbId = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(currentDb).getId();
         MaterializedView view = new MaterializedView();
         view.setDbId(dbId);
         view.setId(1024);
diff --git a/fe/fe-core/src/test/java/com/starrocks/server/ConcurrentDDLTest.java b/fe/fe-core/src/test/java/com/starrocks/server/ConcurrentDDLTest.java
index f9ba111658d56d..8e9712043cf285 100644
--- a/fe/fe-core/src/test/java/com/starrocks/server/ConcurrentDDLTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/server/ConcurrentDDLTest.java
@@ -90,9 +90,9 @@ public void testConcurrentCreatingColocateTables() throws InterruptedException {
                 try {
                     System.out.println("start to create table");
                     starRocksAssert.withTable("create table test.test_tbl_" + Thread.currentThread().getId() +
-                            " (id int) duplicate key (id)" +
-                            " distributed by hash(id) buckets 5183 " +
-                            "properties(\"replication_num\"=\"1\", \"colocate_with\"=\"test_cg_001\");");
+                                " (id int) duplicate key (id)" +
+                                " distributed by hash(id) buckets 5183 " +
+                                "properties(\"replication_num\"=\"1\", \"colocate_with\"=\"test_cg_001\");");
                     System.out.println("end to create table");
                 } catch (Exception e) {
                     throw new RuntimeException(e);
@@ -111,19 +111,20 @@ public void testConcurrentCreatingColocateTables() throws InterruptedException {
             thread.join();
         }
 
-        Database db = GlobalStateMgr.getServingState().getDb("test");
-        Table table = db.getTable("test_tbl_" + threadIds.get(0));
+        Database db = GlobalStateMgr.getServingState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "test_tbl_" + threadIds.get(0));
 
         List<List<Long>> bucketSeq = GlobalStateMgr.getCurrentState().getColocateTableIndex().getBackendsPerBucketSeq(
-                GlobalStateMgr.getCurrentState().getColocateTableIndex().getGroup(table.getId()));
+                    GlobalStateMgr.getCurrentState().getColocateTableIndex().getGroup(table.getId()));
         // check all created colocate tables has same tablet distribution as the bucket seq in colocate group
         for (long threadId : threadIds) {
-            table = db.getTable("test_tbl_" + threadId);
+            table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "test_tbl_" + threadId);
             List<Long> tablets = table.getPartitions().stream().findFirst().get().getBaseIndex().getTabletIdsInOrder();
             List<Long> backendIdList = tablets.stream()
-                    .map(id -> GlobalStateMgr.getCurrentState().getTabletInvertedIndex().getReplicasByTabletId(id))
-                    .map(replicaList -> replicaList.get(0).getBackendId())
-                    .collect(Collectors.toList());
+                        .map(id -> GlobalStateMgr.getCurrentState().getTabletInvertedIndex().getReplicasByTabletId(id))
+                        .map(replicaList -> replicaList.get(0).getBackendId())
+                        .collect(Collectors.toList());
             Assert.assertEquals(bucketSeq, backendIdList.stream().map(Arrays::asList).collect(Collectors.toList()));
         }
     }
@@ -131,13 +132,13 @@ public void testConcurrentCreatingColocateTables() throws InterruptedException {
     @Test
     public void testConcurrentlyDropDbAndCreateTable() throws Exception {
         final String createTableSqlFormat =
-                "CREATE TABLE IF NOT EXISTS concurrent_test_db.test_tbl_RRR(k1 int, k2 int, k3 int)" +
-                        " distributed by hash(k1) buckets 3 properties('replication_num' = '1');";
+                    "CREATE TABLE IF NOT EXISTS concurrent_test_db.test_tbl_RRR(k1 int, k2 int, k3 int)" +
+                                " distributed by hash(k1) buckets 3 properties('replication_num' = '1');";
         final String createViewSqlFormat = "CREATE VIEW IF NOT EXISTS concurrent_test_db.test_view_RRR" +
-                " as select k1,k2 from concurrent_test_db.base_t1;";
+                    " as select k1,k2 from concurrent_test_db.base_t1;";
         final String createMVSqlFormat = "CREATE MATERIALIZED VIEW IF NOT EXISTS" +
-                " concurrent_test_db.test_mv_RRR DISTRIBUTED BY HASH(`k2`) REFRESH MANUAL" +
-                " as select k2,k3 from concurrent_test_db.base_t1;";
+                    " concurrent_test_db.test_mv_RRR DISTRIBUTED BY HASH(`k2`) REFRESH MANUAL" +
+                    " as select k2,k3 from concurrent_test_db.base_t1;";
 
         final int NUM_ROUND = 1;
 
@@ -155,16 +156,16 @@ public void testConcurrentlyDropDbAndCreateTable() throws Exception {
                         System.out.println("creating table and db time: " + times);
                         starRocksAssert.withDatabase("concurrent_test_db");
                         starRocksAssert.withTable(
-                                "CREATE TABLE IF NOT EXISTS concurrent_test_db.base_t1(k1 int, k2 int, k3 int)" +
-                                        " distributed by hash(k1) buckets 3 properties('replication_num' = '1');");
+                                    "CREATE TABLE IF NOT EXISTS concurrent_test_db.base_t1(k1 int, k2 int, k3 int)" +
+                                                " distributed by hash(k1) buckets 3 properties('replication_num' = '1');");
                         int time = 300 + random.nextInt(100);
                         // sleep random time before dropping database
                         Thread.sleep(time);
                         System.out.println("dropping table and db");
-                        Database db = GlobalStateMgr.getCurrentState().getDb("concurrent_test_db");
+                        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("concurrent_test_db");
                         ShowTableStmt showTableStmt =
-                                (ShowTableStmt) UtFrameUtils.parseStmtWithNewParser(
-                                        "show tables from concurrent_test_db", connectContext);
+                                    (ShowTableStmt) UtFrameUtils.parseStmtWithNewParser(
+                                                "show tables from concurrent_test_db", connectContext);
                         starRocksAssert.dropDatabase("concurrent_test_db");
                         System.out.println("concurrent_test_db dropped");
                     } catch (Exception e) {
@@ -251,9 +252,9 @@ public void testConcurrentCreateSameTable() throws InterruptedException {
                     System.out.println("start to create table same_tbl");
                     try {
                         starRocksAssert.withTable("create table test.same_tbl " +
-                                " (id int) duplicate key (id)" +
-                                " distributed by hash(id) buckets 5183 " +
-                                "properties(\"replication_num\"=\"1\", \"colocate_with\"=\"test_cg_001\");");
+                                    " (id int) duplicate key (id)" +
+                                    " distributed by hash(id) buckets 5183 " +
+                                    "properties(\"replication_num\"=\"1\", \"colocate_with\"=\"test_cg_001\");");
                     } catch (Exception e) {
                         errorCount.incrementAndGet();
                     }
diff --git a/fe/fe-core/src/test/java/com/starrocks/server/LocalMetaStoreTest.java b/fe/fe-core/src/test/java/com/starrocks/server/LocalMetaStoreTest.java
index 50e0fe0b2f9f68..ca7fb572536f78 100644
--- a/fe/fe-core/src/test/java/com/starrocks/server/LocalMetaStoreTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/server/LocalMetaStoreTest.java
@@ -80,17 +80,17 @@ public static void beforeClass() throws Exception {
         starRocksAssert = new StarRocksAssert(connectContext);
 
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable(
-                        "CREATE TABLE test.t1(k1 int, k2 int, k3 int)" +
-                                " distributed by hash(k1) buckets 3 properties('replication_num' = '1');");
+                    .withTable(
+                                "CREATE TABLE test.t1(k1 int, k2 int, k3 int)" +
+                                            " distributed by hash(k1) buckets 3 properties('replication_num' = '1');");
 
         UtFrameUtils.PseudoImage.setUpImageVersion();
     }
 
     @Test
     public void testGetNewPartitionsFromPartitions() throws DdlException {
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
-        Table table = db.getTable("t1");
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t1");
         Assert.assertTrue(table instanceof OlapTable);
         OlapTable olapTable = (OlapTable) table;
         Partition sourcePartition = olapTable.getPartition("t1");
@@ -102,8 +102,8 @@ public void testGetNewPartitionsFromPartitions() throws DdlException {
         Assert.assertEquals(olapTable.getName(), copiedTable.getName());
         Set<Long> tabletIdSet = Sets.newHashSet();
         List<Partition> newPartitions = localMetastore.getNewPartitionsFromPartitions(db,
-                olapTable, sourcePartitionIds, origPartitions, copiedTable, "_100", tabletIdSet, tmpPartitionIds,
-                null, WarehouseManager.DEFAULT_WAREHOUSE_ID);
+                    olapTable, sourcePartitionIds, origPartitions, copiedTable, "_100", tabletIdSet, tmpPartitionIds,
+                    null, WarehouseManager.DEFAULT_WAREHOUSE_ID);
         Assert.assertEquals(sourcePartitionIds.size(), newPartitions.size());
         Assert.assertEquals(1, newPartitions.size());
         Partition newPartition = newPartitions.get(0);
@@ -112,8 +112,8 @@ public void testGetNewPartitionsFromPartitions() throws DdlException {
 
         PartitionInfo partitionInfo = olapTable.getPartitionInfo();
         partitionInfo.addPartition(newPartition.getId(), partitionInfo.getDataProperty(sourcePartition.getId()),
-                partitionInfo.getReplicationNum(sourcePartition.getId()),
-                partitionInfo.getIsInMemory(sourcePartition.getId()));
+                    partitionInfo.getReplicationNum(sourcePartition.getId()),
+                    partitionInfo.getIsInMemory(sourcePartition.getId()));
         olapTable.replacePartition("t1", "t1_100");
 
         Assert.assertEquals(newPartition.getId(), olapTable.getPartition("t1").getId());
@@ -122,15 +122,15 @@ public void testGetNewPartitionsFromPartitions() throws DdlException {
     @Test
     public void testGetPartitionIdToStorageMediumMap() throws Exception {
         starRocksAssert.withMaterializedView(
-                "CREATE MATERIALIZED VIEW test.mv1\n" +
-                        "distributed by hash(k1) buckets 3\n" +
-                        "refresh async\n" +
-                        "properties(\n" +
-                        "'replication_num' = '1'\n" +
-                        ")\n" +
-                        "as\n" +
-                        "select k1,k2 from test.t1;");
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+                    "CREATE MATERIALIZED VIEW test.mv1\n" +
+                                "distributed by hash(k1) buckets 3\n" +
+                                "refresh async\n" +
+                                "properties(\n" +
+                                "'replication_num' = '1'\n" +
+                                ")\n" +
+                                "as\n" +
+                                "select k1,k2 from test.t1;");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         new MockUp<PartitionInfo>() {
             @Mock
             public DataProperty getDataProperty(long partitionId) {
@@ -141,7 +141,8 @@ public DataProperty getDataProperty(long partitionId) {
             @Mock
             public void logModifyPartition(ModifyPartitionInfo info) {
                 Assert.assertNotNull(info);
-                Assert.assertTrue(db.getTable(info.getTableId()).isOlapTableOrMaterializedView());
+                Assert.assertTrue(GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getId(), info.getTableId())
+                            .isOlapTableOrMaterializedView());
                 Assert.assertEquals(TStorageMedium.HDD, info.getDataProperty().getStorageMedium());
                 Assert.assertEquals(DataProperty.MAX_COOLDOWN_TIME_MS, info.getDataProperty().getCooldownTimeMs());
             }
@@ -156,8 +157,8 @@ public void logModifyPartition(ModifyPartitionInfo info) {
     @Test
     public void testLoadClusterV2() throws Exception {
         LocalMetastore localMetaStore = new LocalMetastore(GlobalStateMgr.getCurrentState(),
-                GlobalStateMgr.getCurrentState().getRecycleBin(),
-                GlobalStateMgr.getCurrentState().getColocateTableIndex());
+                    GlobalStateMgr.getCurrentState().getRecycleBin(),
+                    GlobalStateMgr.getCurrentState().getColocateTableIndex());
 
         UtFrameUtils.PseudoImage image = new UtFrameUtils.PseudoImage();
         localMetaStore.save(image.getImageWriter());
@@ -174,16 +175,16 @@ public void testLoadClusterV2() throws Exception {
 
     @Test
     public void testReplayAddSubPartition() throws DdlException {
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("t1");
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t1");
         Partition p = table.getPartitions().stream().findFirst().get();
         int schemaHash = table.getSchemaHashByIndexId(p.getBaseIndex().getId());
         MaterializedIndex index = new MaterializedIndex();
         TabletMeta tabletMeta = new TabletMeta(db.getId(), table.getId(), p.getId(),
-                index.getId(), schemaHash, table.getPartitionInfo().getDataProperty(p.getId()).getStorageMedium());
+                    index.getId(), schemaHash, table.getPartitionInfo().getDataProperty(p.getId()).getStorageMedium());
         index.addTablet(new LocalTablet(0), tabletMeta);
         PhysicalPartitionPersistInfoV2 info = new PhysicalPartitionPersistInfoV2(
-                db.getId(), table.getId(), p.getId(), new PhysicalPartitionImpl(123, "", p.getId(), 0, index));
+                    db.getId(), table.getId(), p.getId(), new PhysicalPartitionImpl(123, "", p.getId(), 0, index));
 
         LocalMetastore localMetastore = connectContext.getGlobalStateMgr().getLocalMetastore();
         localMetastore.replayAddSubPartition(info);
@@ -191,8 +192,8 @@ public void testReplayAddSubPartition() throws DdlException {
 
     @Test
     public void testReplayTruncateTable() throws DdlException {
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("t1");
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t1");
         Partition p = table.getPartitions().stream().findFirst().get();
         TruncateTableInfo info = new TruncateTableInfo(db.getId(), table.getId(), Lists.newArrayList(p), false);
 
@@ -202,8 +203,8 @@ public void testReplayTruncateTable() throws DdlException {
 
     @Test
     public void testModifyAutomaticBucketSize() throws DdlException {
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("t1");
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t1");
 
         Locker locker = new Locker();
         locker.lockDatabase(db, LockType.WRITE);
@@ -221,8 +222,8 @@ public void testModifyAutomaticBucketSize() throws DdlException {
     @Test
     public void testCreateTableIfNotExists() throws Exception {
         // create table if not exists, if the table already exists, do nothing
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
-        Table table = db.getTable("t1");
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t1");
         Assert.assertTrue(table instanceof OlapTable);
         LocalMetastore localMetastore = connectContext.getGlobalStateMgr().getLocalMetastore();
 
@@ -239,20 +240,20 @@ public void testCreateTableIfNotExists() throws Exception {
         starRocksAssert = new StarRocksAssert(connectContext);
         // with IF NOT EXIST
         starRocksAssert.useDatabase("test").withTable(
-                "CREATE TABLE IF NOT EXISTS test.t1(k1 int, k2 int, k3 int)" +
-                        " distributed by hash(k1) buckets 3 properties('replication_num' = '1');");
+                    "CREATE TABLE IF NOT EXISTS test.t1(k1 int, k2 int, k3 int)" +
+                                " distributed by hash(k1) buckets 3 properties('replication_num' = '1');");
 
         // w/o IF NOT EXIST
         Assert.assertThrows(AnalysisException.class, () ->
-                starRocksAssert.useDatabase("test").withTable(
-                        "CREATE TABLE test.t1(k1 int, k2 int, k3 int)" +
-                                " distributed by hash(k1) buckets 3 properties('replication_num' = '1');"));
+                    starRocksAssert.useDatabase("test").withTable(
+                                "CREATE TABLE test.t1(k1 int, k2 int, k3 int)" +
+                                            " distributed by hash(k1) buckets 3 properties('replication_num' = '1');"));
     }
 
     @Test
     public void testAlterTableProperties() throws Exception {
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("t1");
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t1");
 
         Map<String, String> properties = Maps.newHashMap();
         properties.put(PropertyAnalyzer.PROPERTIES_DATACACHE_PARTITION_DURATION, "abcd");
@@ -277,7 +278,7 @@ public void testRenameColumnException() throws Exception {
         }
 
         Database db = localMetastore.getDb("test");
-        Table table = db.getTable("t1");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t1");
         try {
             localMetastore.renameColumn(new Database(1, "_statistics_"), table, null);
             Assert.fail("should not happen");
diff --git a/fe/fe-core/src/test/java/com/starrocks/server/MVRepairHandlerTest.java b/fe/fe-core/src/test/java/com/starrocks/server/MVRepairHandlerTest.java
index 589ef9dd0341ac..1954d202be4090 100644
--- a/fe/fe-core/src/test/java/com/starrocks/server/MVRepairHandlerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/server/MVRepairHandlerTest.java
@@ -53,7 +53,7 @@ public static void beforeClass() throws Exception {
                         "distributed by hash(k1) buckets 3 refresh async as select k1 from test.t1");
 
         database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
-        table = database.getTable("t1");
+        table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), "t1");
         Assert.assertTrue(table instanceof OlapTable);
         OlapTable olapTable = (OlapTable) table;
         partition = olapTable.getPartition("t1");
diff --git a/fe/fe-core/src/test/java/com/starrocks/service/FrontendServiceImplTest.java b/fe/fe-core/src/test/java/com/starrocks/service/FrontendServiceImplTest.java
index 7812c2299e6496..0d6ada7448397e 100644
--- a/fe/fe-core/src/test/java/com/starrocks/service/FrontendServiceImplTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/service/FrontendServiceImplTest.java
@@ -110,7 +110,7 @@ public class FrontendServiceImplTest {
     ExecuteEnv exeEnv;
 
     private TUpdateResourceUsageRequest genUpdateResourceUsageRequest(
-            long backendId, int numRunningQueries, long memLimitBytes, long memUsedBytes, int cpuUsedPermille) {
+                long backendId, int numRunningQueries, long memLimitBytes, long memUsedBytes, int cpuUsedPermille) {
         TResourceUsage usage = new TResourceUsage();
         usage.setNum_running_queries(numRunningQueries);
         usage.setMem_limit_bytes(memLimitBytes);
@@ -129,7 +129,7 @@ public void testUpdateImmutablePartitionException() throws TException {
         new MockUp<FrontendServiceImpl>() {
             @Mock
             public synchronized TImmutablePartitionResult updateImmutablePartitionInternal(
-                    TImmutablePartitionRequest request) {
+                        TImmutablePartitionRequest request) {
                 throw new RuntimeException("test");
             }
         };
@@ -157,132 +157,132 @@ public static void beforeClass() throws Exception {
         starRocksAssert = new StarRocksAssert(connectContext);
 
         starRocksAssert.withDatabase("test").useDatabase("test")
-                .withTable("CREATE TABLE site_access_auto (\n" +
-                        "    event_day DATETIME NOT NULL,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "DISTRIBUTED BY RANDOM\n" +
-                        "PROPERTIES(\n" +
-                        "    \"replication_num\" = \"1\"\n" +
-                        ");")
-                .withTable("CREATE TABLE site_access_exception (\n" +
-                        "    event_day DATETIME NOT NULL,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "DISTRIBUTED BY RANDOM\n" +
-                        "PROPERTIES(\n" +
-                        "    \"replication_num\" = \"1\"\n" +
-                        ");")
-                .withTable("CREATE TABLE site_access_empty (\n" +
-                        "    event_day DATETIME NOT NULL,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY date_trunc('day', event_day)\n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id)\n" +
-                        "PROPERTIES(\n" +
-                        "    \"replication_num\" = \"1\"\n" +
-                        ");")
-                .withTable("CREATE TABLE site_access_border (\n" +
-                        "    event_day DATETIME NOT NULL,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY date_trunc('day', event_day)\n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id)\n" +
-                        "PROPERTIES(\n" +
-                        "    \"replication_num\" = \"1\"\n" +
-                        ");")
-                .withTable("CREATE TABLE site_access_hour (\n" +
-                        "    event_day DATETIME,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY date_trunc('hour', event_day)\n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\"\n" +
-                        ");")
-                .withTable("CREATE TABLE site_access_day (\n" +
-                        "    event_day DATE,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY date_trunc('day', event_day) (\n" +
-                        "START (\"2020-06-01\") END (\"2022-06-05\") EVERY (INTERVAL 1 day)\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\"\n" +
-                        ");")
-                .withTable("CREATE TABLE site_access_month (\n" +
-                        "    event_day DATE,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY date_trunc('month', event_day) (\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\"\n" +
-                        ");")
-                .withTable("CREATE TABLE site_access_slice (\n" +
-                        "    event_day datetime,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY time_slice(event_day, interval 5 day)\n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
-                        "PROPERTIES(\"replication_num\" = \"1\");")
-                .withTable("CREATE TABLE site_access_list (\n" +
-                        "    event_day DATE not null,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY (event_day) (\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\"\n" +
-                        ");")
-                .withView("create view v as select * from site_access_empty")
-                .withView("create view v1 as select current_role()")
-                .withView("create view v2 as select current_user()")
-                .withView("create view v3 as select database()")
-                .withView("create view v4 as select user()")
-                .withView("create view v5 as select CONNECTION_ID()")
-                .withView("create view v6 as select CATALOG()")
-
-                .withMaterializedView("create materialized view mv refresh async as select * from site_access_empty");
+                    .withTable("CREATE TABLE site_access_auto (\n" +
+                                "    event_day DATETIME NOT NULL,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "DISTRIBUTED BY RANDOM\n" +
+                                "PROPERTIES(\n" +
+                                "    \"replication_num\" = \"1\"\n" +
+                                ");")
+                    .withTable("CREATE TABLE site_access_exception (\n" +
+                                "    event_day DATETIME NOT NULL,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "DISTRIBUTED BY RANDOM\n" +
+                                "PROPERTIES(\n" +
+                                "    \"replication_num\" = \"1\"\n" +
+                                ");")
+                    .withTable("CREATE TABLE site_access_empty (\n" +
+                                "    event_day DATETIME NOT NULL,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY date_trunc('day', event_day)\n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id)\n" +
+                                "PROPERTIES(\n" +
+                                "    \"replication_num\" = \"1\"\n" +
+                                ");")
+                    .withTable("CREATE TABLE site_access_border (\n" +
+                                "    event_day DATETIME NOT NULL,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY date_trunc('day', event_day)\n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id)\n" +
+                                "PROPERTIES(\n" +
+                                "    \"replication_num\" = \"1\"\n" +
+                                ");")
+                    .withTable("CREATE TABLE site_access_hour (\n" +
+                                "    event_day DATETIME,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY date_trunc('hour', event_day)\n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\"\n" +
+                                ");")
+                    .withTable("CREATE TABLE site_access_day (\n" +
+                                "    event_day DATE,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY date_trunc('day', event_day) (\n" +
+                                "START (\"2020-06-01\") END (\"2022-06-05\") EVERY (INTERVAL 1 day)\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\"\n" +
+                                ");")
+                    .withTable("CREATE TABLE site_access_month (\n" +
+                                "    event_day DATE,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY date_trunc('month', event_day) (\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\"\n" +
+                                ");")
+                    .withTable("CREATE TABLE site_access_slice (\n" +
+                                "    event_day datetime,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY time_slice(event_day, interval 5 day)\n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
+                                "PROPERTIES(\"replication_num\" = \"1\");")
+                    .withTable("CREATE TABLE site_access_list (\n" +
+                                "    event_day DATE not null,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY (event_day) (\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\"\n" +
+                                ");")
+                    .withView("create view v as select * from site_access_empty")
+                    .withView("create view v1 as select current_role()")
+                    .withView("create view v2 as select current_user()")
+                    .withView("create view v3 as select database()")
+                    .withView("create view v4 as select user()")
+                    .withView("create view v5 as select CONNECTION_ID()")
+                    .withView("create view v6 as select CATALOG()")
+
+                    .withMaterializedView("create materialized view mv refresh async as select * from site_access_empty");
     }
 
     @AfterClass
@@ -302,13 +302,14 @@ public static void tearDown() throws Exception {
 
     @Test
     public void testImmutablePartitionException() throws TException {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("site_access_exception");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "site_access_exception");
         List<Long> partitionIds = Lists.newArrayList();
         FrontendServiceImpl impl = new FrontendServiceImpl(exeEnv);
         TImmutablePartitionRequest request = new TImmutablePartitionRequest();
         TImmutablePartitionResult partition = impl.updateImmutablePartition(request);
-        Table t = db.getTable("v");
+        Table t = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "v");
 
         Assert.assertEquals(partition.getStatus().getStatus_code(), TStatusCode.RUNTIME_ERROR);
 
@@ -334,7 +335,7 @@ public void testImmutablePartitionException() throws TException {
         Assert.assertEquals(partition.getStatus().getStatus_code(), TStatusCode.OK);
 
         partitionIds = table.getPhysicalPartitions().stream()
-                .map(PhysicalPartition::getId).collect(Collectors.toList());
+                    .map(PhysicalPartition::getId).collect(Collectors.toList());
         request.setPartition_ids(partitionIds);
         partition = impl.updateImmutablePartition(request);
         Assert.assertEquals(partition.getStatus().getStatus_code(), TStatusCode.OK);
@@ -342,10 +343,11 @@ public void testImmutablePartitionException() throws TException {
 
     @Test
     public void testImmutablePartitionApi() throws TException {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("site_access_auto");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(db.getFullName(), "site_access_auto");
         List<Long> partitionIds = table.getPhysicalPartitions().stream()
-                .map(PhysicalPartition::getId).collect(Collectors.toList());
+                    .map(PhysicalPartition::getId).collect(Collectors.toList());
         FrontendServiceImpl impl = new FrontendServiceImpl(exeEnv);
         TImmutablePartitionRequest request = new TImmutablePartitionRequest();
         request.setDb_id(db.getId());
@@ -361,7 +363,7 @@ public void testImmutablePartitionApi() throws TException {
         Assert.assertEquals(2, table.getPhysicalPartitions().size());
 
         partitionIds = table.getPhysicalPartitions().stream()
-                .map(PhysicalPartition::getId).collect(Collectors.toList());
+                    .map(PhysicalPartition::getId).collect(Collectors.toList());
         request.setPartition_ids(partitionIds);
         partition = impl.updateImmutablePartition(request);
         Assert.assertEquals(partition.getStatus().getStatus_code(), TStatusCode.OK);
@@ -377,8 +379,8 @@ public TransactionState getTransactionState(long dbId, long transactionId) {
             }
         };
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("site_access_day");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access_day");
         List<List<String>> partitionValues = Lists.newArrayList();
         List<String> values = Lists.newArrayList();
         values.add("1990-04-24");
@@ -408,8 +410,8 @@ public TransactionState getTransactionState(long dbId, long transactionId) {
             }
         };
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("site_access_day");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access_day");
         ((OlapTable) table).setState(OlapTable.OlapTableState.SCHEMA_CHANGE);
 
         List<List<String>> partitionValues = Lists.newArrayList();
@@ -437,8 +439,8 @@ public TransactionState getTransactionState(long dbId, long transactionId) {
             }
         };
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("site_access_day");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access_day");
         ((OlapTable) table).setState(OlapTable.OlapTableState.ROLLUP);
 
         List<List<String>> partitionValues = Lists.newArrayList();
@@ -457,12 +459,10 @@ public TransactionState getTransactionState(long dbId, long transactionId) {
         ((OlapTable) table).setState(OlapTable.OlapTableState.NORMAL);
     }
 
-
-
     @Test
     public void testCreatePartitionExceedLimit() throws TException {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("site_access_day");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access_day");
         List<List<String>> partitionValues = Lists.newArrayList();
         List<String> values = Lists.newArrayList();
         values.add("1990-04-24");
@@ -511,8 +511,8 @@ public TransactionState getTransactionState(long dbId, long transactionId) {
             }
         };
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("site_access_slice");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access_slice");
         List<List<String>> partitionValues = Lists.newArrayList();
         List<String> values = Lists.newArrayList();
         values.add("1990-04-24");
@@ -542,8 +542,8 @@ public TransactionState getTransactionState(long dbId, long transactionId) {
             }
         };
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("site_access_day");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access_day");
         List<List<String>> partitionValues = Lists.newArrayList();
         List<String> values = Lists.newArrayList();
         values.add("1990-04-24");
@@ -579,8 +579,8 @@ public TransactionState getTransactionState(long dbId, long transactionId) {
             }
         };
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("site_access_month");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access_month");
         List<List<String>> partitionValues = Lists.newArrayList();
         List<String> values = Lists.newArrayList();
         values.add("1990-04-24");
@@ -622,8 +622,8 @@ public TransactionState getTransactionState(long dbId, long transactionId) {
             }
         };
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("site_access_border");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access_border");
         List<List<String>> partitionValues = Lists.newArrayList();
         List<String> values = Lists.newArrayList();
         values.add("NULL");
@@ -654,8 +654,8 @@ public TransactionState getTransactionState(long dbId, long transactionId) {
     @Test
     public void testAutomaticPartitionLimitExceed() throws TException {
         Config.max_partition_number_per_table = 1;
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("site_access_slice");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access_slice");
         List<List<String>> partitionValues = Lists.newArrayList();
         List<String> values = Lists.newArrayList();
         values.add("1991-04-24");
@@ -685,8 +685,8 @@ public TransactionState getTransactionState(long dbId, long transactionId) {
             }
         };
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("site_access_month");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access_month");
         List<List<String>> partitionValues = Lists.newArrayList();
         List<String> values = Lists.newArrayList();
         values.add("1999-04-29");
@@ -750,19 +750,19 @@ public void testListTableStatus() throws TException {
     @Test
     public void testListViewStatusWithBaseTableDropped() throws Exception {
         starRocksAssert.useDatabase("test")
-                .withTable("CREATE TABLE site_access_empty_for_view (\n" +
-                        "    event_day DATETIME NOT NULL,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY date_trunc('day', event_day)\n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id)\n" +
-                        "PROPERTIES(\n" +
-                        "    \"replication_num\" = \"1\"\n" +
-                        ");");
+                    .withTable("CREATE TABLE site_access_empty_for_view (\n" +
+                                "    event_day DATETIME NOT NULL,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY date_trunc('day', event_day)\n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id)\n" +
+                                "PROPERTIES(\n" +
+                                "    \"replication_num\" = \"1\"\n" +
+                                ");");
         starRocksAssert.withView("create view test.view11 as select * from test.site_access_empty_for_view");
         // drop the base table referenced by test.view11
         starRocksAssert.dropTable("test.site_access_empty_for_view");
@@ -782,8 +782,8 @@ public TransactionState getTransactionState(long dbId, long transactionId) {
             }
         };
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("site_access_hour");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access_hour");
         List<List<String>> partitionValues = Lists.newArrayList();
         List<String> values = Lists.newArrayList();
         values.add("1990-04-24 12:34:56");
@@ -806,8 +806,8 @@ public TransactionState getTransactionState(long dbId, long transactionId) {
 
     @Test
     public void testCreateEmptyPartition() {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("site_access_empty");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access_empty");
         Collection<Partition> partitions = table.getPartitions();
         Assert.assertEquals(1, partitions.size());
         String name = partitions.iterator().next().getName();
@@ -818,125 +818,125 @@ public void testCreateEmptyPartition() {
     @Test(expected = AnalysisException.class)
     public void testCreateCeilForbidAutomaticTable() throws Exception {
         starRocksAssert.withDatabase("test2").useDatabase("test2")
-                .withTable("CREATE TABLE site_access_ceil (\n" +
-                        "    event_day datetime,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY time_slice(event_day, interval 1 day, CEIL) \n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
-                        "PROPERTIES(\"replication_num\" = \"1\");");
+                    .withTable("CREATE TABLE site_access_ceil (\n" +
+                                "    event_day datetime,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY time_slice(event_day, interval 1 day, CEIL) \n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
+                                "PROPERTIES(\"replication_num\" = \"1\");");
     }
 
     @Test(expected = AnalysisException.class)
     public void testCreateTimeSliceForbidAutomaticTable() throws Exception {
         starRocksAssert.withDatabase("test2").useDatabase("test2")
-                .withTable("CREATE TABLE site_access_time_slice_hour_date (\n" +
-                        "    event_day date,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY time_slice(event_day, interval 1 hour) \n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
-                        "PROPERTIES(\"replication_num\" = \"1\");");
+                    .withTable("CREATE TABLE site_access_time_slice_hour_date (\n" +
+                                "    event_day date,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY time_slice(event_day, interval 1 hour) \n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
+                                "PROPERTIES(\"replication_num\" = \"1\");");
     }
 
     @Test(expected = AnalysisException.class)
     public void testCreateDateTruncForbidAutomaticTable() throws Exception {
         starRocksAssert.withDatabase("test2").useDatabase("test2")
-                .withTable("CREATE TABLE site_access_date_trunc_hour_date (\n" +
-                        "    event_day DATE,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ")\n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY date_trunc('hour', event_day)\n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
-                        "PROPERTIES(\"replication_num\" = \"1\");");
+                    .withTable("CREATE TABLE site_access_date_trunc_hour_date (\n" +
+                                "    event_day DATE,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ")\n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY date_trunc('hour', event_day)\n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
+                                "PROPERTIES(\"replication_num\" = \"1\");");
     }
 
     @Test(expected = AnalysisException.class)
     public void testUnsupportedAutomaticTableGranularityDoesNotMatch() throws Exception {
         starRocksAssert.withDatabase("test2").useDatabase("test2")
-                .withTable("CREATE TABLE site_access_granularity_does_not_match(\n" +
-                        "    event_day DATE NOT NULL,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ") \n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY date_trunc('month', event_day)(\n" +
-                        "    START (\"2023-05-01\") END (\"2023-05-03\") EVERY (INTERVAL 1 day)\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
-                        "PROPERTIES(\n" +
-                        "    \"partition_live_number\" = \"3\",\n" +
-                        "    \"replication_num\" = \"1\"\n" +
-                        ");");
+                    .withTable("CREATE TABLE site_access_granularity_does_not_match(\n" +
+                                "    event_day DATE NOT NULL,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ") \n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY date_trunc('month', event_day)(\n" +
+                                "    START (\"2023-05-01\") END (\"2023-05-03\") EVERY (INTERVAL 1 day)\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
+                                "PROPERTIES(\n" +
+                                "    \"partition_live_number\" = \"3\",\n" +
+                                "    \"replication_num\" = \"1\"\n" +
+                                ");");
     }
 
     @Test(expected = AnalysisException.class)
     public void testUnsupportedAutomaticTableGranularityDoesNotMatch2() throws Exception {
         starRocksAssert.withDatabase("test2").useDatabase("test2")
-                .withTable("CREATE TABLE site_access_granularity_does_not_match2(\n" +
-                        "    event_day DATE NOT NULL,\n" +
-                        "    site_id INT DEFAULT '10',\n" +
-                        "    city_code VARCHAR(100),\n" +
-                        "    user_name VARCHAR(32) DEFAULT '',\n" +
-                        "    pv BIGINT DEFAULT '0'\n" +
-                        ") \n" +
-                        "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
-                        "PARTITION BY date_trunc('month', event_day)(\n" +
-                        "   START (\"2022-05-01\") END (\"2022-05-03\") EVERY (INTERVAL 1 day),\n" +
-                        "    START (\"2023-05-01\") END (\"2023-05-03\") EVERY (INTERVAL 1 day)\n" +
-                        ")\n" +
-                        "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
-                        "PROPERTIES(\n" +
-                        "    \"partition_live_number\" = \"3\",\n" +
-                        "    \"replication_num\" = \"1\"\n" +
-                        ");");
+                    .withTable("CREATE TABLE site_access_granularity_does_not_match2(\n" +
+                                "    event_day DATE NOT NULL,\n" +
+                                "    site_id INT DEFAULT '10',\n" +
+                                "    city_code VARCHAR(100),\n" +
+                                "    user_name VARCHAR(32) DEFAULT '',\n" +
+                                "    pv BIGINT DEFAULT '0'\n" +
+                                ") \n" +
+                                "DUPLICATE KEY(event_day, site_id, city_code, user_name)\n" +
+                                "PARTITION BY date_trunc('month', event_day)(\n" +
+                                "   START (\"2022-05-01\") END (\"2022-05-03\") EVERY (INTERVAL 1 day),\n" +
+                                "    START (\"2023-05-01\") END (\"2023-05-03\") EVERY (INTERVAL 1 day)\n" +
+                                ")\n" +
+                                "DISTRIBUTED BY HASH(event_day, site_id) BUCKETS 32\n" +
+                                "PROPERTIES(\n" +
+                                "    \"partition_live_number\" = \"3\",\n" +
+                                "    \"replication_num\" = \"1\"\n" +
+                                ");");
     }
 
     @Test
     public void testGetTablesInfo() throws Exception {
         starRocksAssert.withDatabase("test_table").useDatabase("test_table")
-                .withTable("CREATE TABLE `t1` (\n" +
-                        "  `k1` date NULL COMMENT \"\",\n" +
-                        "  `v1` int(11) NULL COMMENT \"\",\n" +
-                        "  `v2` int(11) NULL COMMENT \"\"\n" +
-                        ") ENGINE=OLAP \n" +
-                        "DUPLICATE KEY(`k1`)\n" +
-                        "COMMENT \"OLAP\"\n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\",\n" +
-                        "\"in_memory\" = \"false\",\n" +
-                        "\"enable_persistent_index\" = \"false\",\n" +
-                        "\"replicated_storage\" = \"true\",\n" +
-                        "\"compression\" = \"LZ4\"\n" +
-                        ")")
-                .withTable("CREATE TABLE `t2` (\n" +
-                        "  `k1` date NULL COMMENT \"\",\n" +
-                        "  `v1` int(11) NULL COMMENT \"\",\n" +
-                        "  `v2` int(11) NULL COMMENT \"\"\n" +
-                        ") ENGINE=OLAP \n" +
-                        "DUPLICATE KEY(`k1`)\n" +
-                        "COMMENT \"OLAP\"\n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\",\n" +
-                        "\"in_memory\" = \"false\",\n" +
-                        "\"enable_persistent_index\" = \"false\",\n" +
-                        "\"replicated_storage\" = \"true\",\n" +
-                        "\"compression\" = \"LZ4\"\n" +
-                        ")");
+                    .withTable("CREATE TABLE `t1` (\n" +
+                                "  `k1` date NULL COMMENT \"\",\n" +
+                                "  `v1` int(11) NULL COMMENT \"\",\n" +
+                                "  `v2` int(11) NULL COMMENT \"\"\n" +
+                                ") ENGINE=OLAP \n" +
+                                "DUPLICATE KEY(`k1`)\n" +
+                                "COMMENT \"OLAP\"\n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\",\n" +
+                                "\"in_memory\" = \"false\",\n" +
+                                "\"enable_persistent_index\" = \"false\",\n" +
+                                "\"replicated_storage\" = \"true\",\n" +
+                                "\"compression\" = \"LZ4\"\n" +
+                                ")")
+                    .withTable("CREATE TABLE `t2` (\n" +
+                                "  `k1` date NULL COMMENT \"\",\n" +
+                                "  `v1` int(11) NULL COMMENT \"\",\n" +
+                                "  `v2` int(11) NULL COMMENT \"\"\n" +
+                                ") ENGINE=OLAP \n" +
+                                "DUPLICATE KEY(`k1`)\n" +
+                                "COMMENT \"OLAP\"\n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\",\n" +
+                                "\"in_memory\" = \"false\",\n" +
+                                "\"enable_persistent_index\" = \"false\",\n" +
+                                "\"replicated_storage\" = \"true\",\n" +
+                                "\"compression\" = \"LZ4\"\n" +
+                                ")");
 
         ConnectContext ctx = starRocksAssert.getCtx();
         String createUserSql = "create user test1";
@@ -963,19 +963,19 @@ public void testGetTablesInfo() throws Exception {
     @Test
     public void testDefaultValueMeta() throws Exception {
         starRocksAssert.withDatabase("test_table").useDatabase("test_table")
-                .withTable("CREATE TABLE `test_default_value` (\n" +
-                        "  `id` datetime NULL DEFAULT CURRENT_TIMESTAMP COMMENT \"\",\n" +
-                        "  `value` int(11) NULL DEFAULT \"2\" COMMENT \"\"\n" +
-                        ") ENGINE=OLAP \n" +
-                        "DUPLICATE KEY(`id`, `value`)\n" +
-                        "DISTRIBUTED BY RANDOM\n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\",\n" +
-                        "\"in_memory\" = \"false\",\n" +
-                        "\"enable_persistent_index\" = \"false\",\n" +
-                        "\"replicated_storage\" = \"true\",\n" +
-                        "\"compression\" = \"LZ4\"\n" +
-                        ");");
+                    .withTable("CREATE TABLE `test_default_value` (\n" +
+                                "  `id` datetime NULL DEFAULT CURRENT_TIMESTAMP COMMENT \"\",\n" +
+                                "  `value` int(11) NULL DEFAULT \"2\" COMMENT \"\"\n" +
+                                ") ENGINE=OLAP \n" +
+                                "DUPLICATE KEY(`id`, `value`)\n" +
+                                "DISTRIBUTED BY RANDOM\n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\",\n" +
+                                "\"in_memory\" = \"false\",\n" +
+                                "\"enable_persistent_index\" = \"false\",\n" +
+                                "\"replicated_storage\" = \"true\",\n" +
+                                "\"compression\" = \"LZ4\"\n" +
+                                ");");
 
         ConnectContext ctx = starRocksAssert.getCtx();
         String createUserSql = "create user test2";
@@ -993,8 +993,8 @@ public void testDefaultValueMeta() throws Exception {
         TDescribeTableResult response = impl.describeTable(request);
         List<TColumnDef> columnDefList = response.getColumns();
         List<TColumnDef> testDefaultValue = columnDefList.stream()
-                .filter(u -> u.getColumnDesc().getTableName().equalsIgnoreCase("test_default_value"))
-                .collect(Collectors.toList());
+                    .filter(u -> u.getColumnDesc().getTableName().equalsIgnoreCase("test_default_value"))
+                    .collect(Collectors.toList());
         Assert.assertEquals(2, testDefaultValue.size());
         Assert.assertEquals("CURRENT_TIMESTAMP", testDefaultValue.get(0).getColumnDesc().getColumnDefault());
         Assert.assertEquals("2", testDefaultValue.get(1).getColumnDesc().getColumnDefault());
@@ -1003,18 +1003,18 @@ public void testDefaultValueMeta() throws Exception {
     @Test
     public void testGetSpecialColumn() throws Exception {
         starRocksAssert.withDatabase("test_table").useDatabase("test_table")
-                .withTable("CREATE TABLE `ye$test` (\n" +
-                        "event_day DATE,\n" +
-                        "department_id int(11) NOT NULL COMMENT \"\"\n" +
-                        ") ENGINE=OLAP\n" +
-                        "PRIMARY KEY(event_day, department_id)\n" +
-                        "DISTRIBUTED BY HASH(department_id) BUCKETS 1\n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\",\n" +
-                        "\"in_memory\" = \"false\",\n" +
-                        "\"storage_format\" = \"DEFAULT\",\n" +
-                        "\"enable_persistent_index\" = \"false\"\n" +
-                        ");");
+                    .withTable("CREATE TABLE `ye$test` (\n" +
+                                "event_day DATE,\n" +
+                                "department_id int(11) NOT NULL COMMENT \"\"\n" +
+                                ") ENGINE=OLAP\n" +
+                                "PRIMARY KEY(event_day, department_id)\n" +
+                                "DISTRIBUTED BY HASH(department_id) BUCKETS 1\n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\",\n" +
+                                "\"in_memory\" = \"false\",\n" +
+                                "\"storage_format\" = \"DEFAULT\",\n" +
+                                "\"enable_persistent_index\" = \"false\"\n" +
+                                ");");
 
         ConnectContext ctx = starRocksAssert.getCtx();
         String createUserSql = "create user test3";
@@ -1038,19 +1038,19 @@ public void testGetSpecialColumn() throws Exception {
     @Test
     public void testGetSpecialColumnForSyncMv() throws Exception {
         starRocksAssert.withDatabase("test_table").useDatabase("test_table")
-                .withTable("CREATE TABLE `base1` (\n" +
-                        "event_day DATE,\n" +
-                        "department_id int(11) NOT NULL COMMENT \"\"\n" +
-                        ") ENGINE=OLAP\n" +
-                        "DUPLICATE KEY(event_day, department_id)\n" +
-                        "DISTRIBUTED BY HASH(department_id) BUCKETS 1\n" +
-                        "PROPERTIES (\n" +
-                        "\"replication_num\" = \"1\",\n" +
-                        "\"in_memory\" = \"false\",\n" +
-                        "\"storage_format\" = \"DEFAULT\",\n" +
-                        "\"enable_persistent_index\" = \"false\"\n" +
-                        ");")
-                .withMaterializedView("create materialized view test_table.mv$test as select event_day from base1");
+                    .withTable("CREATE TABLE `base1` (\n" +
+                                "event_day DATE,\n" +
+                                "department_id int(11) NOT NULL COMMENT \"\"\n" +
+                                ") ENGINE=OLAP\n" +
+                                "DUPLICATE KEY(event_day, department_id)\n" +
+                                "DISTRIBUTED BY HASH(department_id) BUCKETS 1\n" +
+                                "PROPERTIES (\n" +
+                                "\"replication_num\" = \"1\",\n" +
+                                "\"in_memory\" = \"false\",\n" +
+                                "\"storage_format\" = \"DEFAULT\",\n" +
+                                "\"enable_persistent_index\" = \"false\"\n" +
+                                ");")
+                    .withMaterializedView("create materialized view test_table.mv$test as select event_day from base1");
 
         ConnectContext ctx = starRocksAssert.getCtx();
         String createUserSql = "create user test4";
@@ -1074,14 +1074,14 @@ public void testGetSpecialColumnForSyncMv() throws Exception {
 
     @Test
     public void testGetLoadTxnStatus() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("site_access_day");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access_day");
         UUID uuid = UUID.randomUUID();
         TUniqueId requestId = new TUniqueId(uuid.getMostSignificantBits(), uuid.getLeastSignificantBits());
         long transactionId = GlobalStateMgr.getCurrentState().getGlobalTransactionMgr().beginTransaction(db.getId(),
-                Lists.newArrayList(table.getId()), "1jdc689-xd232", requestId,
-                new TxnCoordinator(TxnSourceType.BE, "1.1.1.1"),
-                TransactionState.LoadJobSourceType.BACKEND_STREAMING, -1, 600);
+                    Lists.newArrayList(table.getId()), "1jdc689-xd232", requestId,
+                    new TxnCoordinator(TxnSourceType.BE, "1.1.1.1"),
+                    TransactionState.LoadJobSourceType.BACKEND_STREAMING, -1, 600);
         FrontendServiceImpl impl = new FrontendServiceImpl(exeEnv);
         TGetLoadTxnStatusRequest request = new TGetLoadTxnStatusRequest();
         request.setDb("non-exist-db");
@@ -1123,9 +1123,9 @@ public void testStreamLoadPutColumnMapException() {
         List<String> errMsg = status.getError_msgs();
         Assert.assertEquals(1, errMsg.size());
         Assert.assertEquals(
-                "Expr 'str_to_date(`col1`)' analyze error: No matching function with signature: str_to_date(varchar), " +
-                        "derived column is 'event_day'",
-                errMsg.get(0));
+                    "Expr 'str_to_date(`col1`)' analyze error: No matching function with signature: str_to_date(varchar), " +
+                                "derived column is 'event_day'",
+                    errMsg.get(0));
     }
 
     @Test
@@ -1227,8 +1227,8 @@ public TransactionState getTransactionState(long dbId, long transactionId) {
             }
         };
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = db.getTable("site_access_list");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "site_access_list");
         List<List<String>> partitionValues = Lists.newArrayList();
         List<String> values = Lists.newArrayList();
         values.add("1990-04-24");
@@ -1244,25 +1244,26 @@ public TransactionState getTransactionState(long dbId, long transactionId) {
         TCreatePartitionResult partition = impl.createPartition(request);
 
         GlobalStateMgr currentState = GlobalStateMgr.getCurrentState();
-        Database testDb = currentState.getDb("test");
-        OlapTable olapTable = (OlapTable) testDb.getTable("site_access_list");
+        Database testDb = currentState.getLocalMetastore().getDb("test");
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), "site_access_list");
         PartitionInfo partitionInfo = olapTable.getPartitionInfo();
         DistributionInfo defaultDistributionInfo = olapTable.getDefaultDistributionInfo();
         List<PartitionDesc> partitionDescs = Lists.newArrayList();
         Partition p19910425 = olapTable.getPartition("p19900425");
 
         partitionDescs.add(new ListPartitionDesc(Lists.newArrayList("p19900425"),
-                Lists.newArrayList(new SingleItemListPartitionDesc(true, "p19900425",
-                        Lists.newArrayList("1990-04-25"), Maps.newHashMap()))));
+                    Lists.newArrayList(new SingleItemListPartitionDesc(true, "p19900425",
+                                Lists.newArrayList("1990-04-25"), Maps.newHashMap()))));
 
         AddPartitionClause addPartitionClause = new AddPartitionClause(partitionDescs.get(0),
-                defaultDistributionInfo.toDistributionDesc(table.getIdToColumn()), Maps.newHashMap(), false);
+                    defaultDistributionInfo.toDistributionDesc(table.getIdToColumn()), Maps.newHashMap(), false);
 
         List<Partition> partitionList = Lists.newArrayList();
         partitionList.add(p19910425);
 
         currentState.getLocalMetastore().addListPartitionLog(testDb, olapTable, partitionDescs,
-                addPartitionClause.isTempPartition(), partitionInfo, partitionList, Sets.newSet("p19900425"));
+                    addPartitionClause.isTempPartition(), partitionInfo, partitionList, Sets.newSet("p19900425"));
 
     }
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/AnalyzeCreateAnalyzeJobTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/AnalyzeCreateAnalyzeJobTest.java
index c1655a24dbbe80..4acb50aedd68a7 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/AnalyzeCreateAnalyzeJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/AnalyzeCreateAnalyzeJobTest.java
@@ -18,6 +18,7 @@
 import com.starrocks.catalog.Database;
 import com.starrocks.catalog.Table;
 import com.starrocks.qe.DDLStmtExecutor;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.ast.CreateAnalyzeJobStmt;
 import com.starrocks.sql.plan.ConnectorPlanTestBase;
 import com.starrocks.statistic.StatsConstants;
@@ -65,7 +66,7 @@ public void testAllTable() throws Exception {
         String sql = "create analyze full database db";
         CreateAnalyzeJobStmt analyzeStmt = (CreateAnalyzeJobStmt) analyzeSuccess(sql);
 
-        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getDb("db");
+        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb("db");
         Assert.assertEquals(db.getId(), analyzeStmt.getDbId());
         Assert.assertEquals(StatsConstants.DEFAULT_ALL_ID, analyzeStmt.getTableId());
         Assert.assertTrue(analyzeStmt.getColumnNames().isEmpty());
@@ -76,9 +77,9 @@ public void testColumn() throws Exception {
         String sql = "create analyze table db.tbl(kk1, kk2)";
         CreateAnalyzeJobStmt analyzeStmt = (CreateAnalyzeJobStmt) analyzeSuccess(sql);
 
-        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getDb("db");
+        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb("db");
         Assert.assertEquals(db.getId(), analyzeStmt.getDbId());
-        Table table = db.getTable("tbl");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl");
         Assert.assertEquals(table.getId(), analyzeStmt.getTableId());
         Assert.assertEquals(2, analyzeStmt.getColumnNames().size());
     }
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/AnalyzeInsertTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/AnalyzeInsertTest.java
index b93c2a9d178468..76a01970038bce 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/AnalyzeInsertTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/AnalyzeInsertTest.java
@@ -101,7 +101,7 @@ public void testInsert() {
     @Test
     public void testInsertOverwriteWhenSchemaChange() throws Exception {
         OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState()
-                .getDb("test").getTable("t0");
+                .getLocalMetastore().getDb("test").getTable("t0");
         table.setState(OlapTable.OlapTableState.SCHEMA_CHANGE);
         analyzeFail("insert overwrite t0 select * from t0;",
                 "table state is SCHEMA_CHANGE, please wait to insert overwrite until table state is normal");
@@ -114,11 +114,15 @@ public void testInsertIcebergUnpartitionedTable(@Mocked IcebergTable icebergTabl
                 "Unknown catalog 'err_catalog'");
 
         MetadataMgr metadata = AnalyzeTestUtil.getConnectContext().getGlobalStateMgr().getMetadataMgr();
-        new MockUp<MetaUtils>() {
+
+        new MockUp<MetadataMgr>() {
             @Mock
-            public Database getDatabase(String catalogName, String tableName) {
+            public Database getDb(String catalogName, String dbName) {
                 return new Database();
             }
+        };
+
+        new MockUp<MetaUtils>() {
             @Mock
             public Table getSessionAwareTable(ConnectContext context, Database database, TableName tableName) {
                 return null;
@@ -135,6 +139,10 @@ public Table getSessionAwareTable(ConnectContext context, Database database, Tab
         };
         new Expectations(metadata) {
             {
+                metadata.getDb(anyString, anyString);
+                minTimes = 0;
+                result = new Database();
+
                 icebergTable.supportInsert();
                 result = true;
                 minTimes = 0;
@@ -145,6 +153,10 @@ public Table getSessionAwareTable(ConnectContext context, Database database, Tab
 
         new Expectations(metadata) {
             {
+                metadata.getDb(anyString, anyString);
+                minTimes = 0;
+                result = new Database();
+
                 icebergTable.getBaseSchema();
                 result = ImmutableList.of(new Column("c1", Type.INT));
                 minTimes = 0;
@@ -157,12 +169,14 @@ public Table getSessionAwareTable(ConnectContext context, Database database, Tab
     public void testPartitionedIcebergTable(@Mocked IcebergTable icebergTable) {
         MetadataMgr metadata = AnalyzeTestUtil.getConnectContext().getGlobalStateMgr().getMetadataMgr();
 
-        new MockUp<MetaUtils>() {
+        new MockUp<MetadataMgr>() {
             @Mock
-            public Database getDatabase(String catalogName, String databaseName) {
+            public Database getDb(String catalogName, String dbName) {
                 return new Database();
             }
+        };
 
+        new MockUp<MetaUtils>() {
             @Mock
             public Table getSessionAwareTable(ConnectContext context, Database database, TableName tableName) {
                 return icebergTable;
@@ -171,6 +185,10 @@ public Table getSessionAwareTable(ConnectContext context, Database database, Tab
 
         new Expectations(metadata) {
             {
+                metadata.getDb(anyString, anyString);
+                minTimes = 0;
+                result = new Database();
+
                 icebergTable.supportInsert();
                 result = true;
                 minTimes = 0;
@@ -241,11 +259,14 @@ public Table getSessionAwareTable(ConnectContext context, Database database, Tab
 
     @Test
     public void testInsertHiveNonManagedTable(@Mocked HiveTable hiveTable) {
-        new MockUp<MetaUtils>() {
+        new MockUp<MetadataMgr>() {
             @Mock
-            public Database getDatabase(String catalogName, String databaseName) {
-                return null;
+            public Database getDb(String catalogName, String dbName) {
+                return new Database();
             }
+        };
+
+        new MockUp<MetaUtils>() {
             @Mock
             public Table getSessionAwareTable(ConnectContext conntext, Database database, TableName tableName) {
                 return hiveTable;
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/AnalyzeStmtTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/AnalyzeStmtTest.java
index c462783e5ad08f..7f783507de7aca 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/AnalyzeStmtTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/AnalyzeStmtTest.java
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-
 package com.starrocks.sql.analyzer;
 
 import com.google.common.collect.Lists;
@@ -160,7 +159,7 @@ public void testStructColumns() {
     }
 
     @Test
-    public void testAnalyzeHiveTable()  {
+    public void testAnalyzeHiveTable() {
         String sql = "analyze table hive0.tpch.customer";
         AnalyzeStmt analyzeStmt = (AnalyzeStmt) analyzeSuccess(sql);
 
@@ -209,8 +208,8 @@ public void testProperties() {
     public void testShow() throws MetaNotFoundException {
         String sql = "show analyze";
         ShowAnalyzeJobStmt showAnalyzeJobStmt = (ShowAnalyzeJobStmt) analyzeSuccess(sql);
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = testDb.getTable("t0");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "t0");
 
         NativeAnalyzeJob nativeAnalyzeJob = new NativeAnalyzeJob(testDb.getId(), table.getId(), Lists.newArrayList(),
                 Lists.newArrayList(),
@@ -237,7 +236,7 @@ public void testShow() throws MetaNotFoundException {
         AnalyzeStatus analyzeStatus = new NativeAnalyzeStatus(-1, testDb.getId(), table.getId(), Lists.newArrayList(),
                 StatsConstants.AnalyzeType.FULL,
                 StatsConstants.ScheduleType.ONCE, Maps.newHashMap(), LocalDateTime.of(
-                        2020, 1, 1, 1, 1));
+                2020, 1, 1, 1, 1));
         analyzeStatus.setEndTime(LocalDateTime.of(2020, 1, 1, 1, 1));
         analyzeStatus.setStatus(StatsConstants.ScheduleStatus.FAILED);
         analyzeStatus.setReason("Test Failed");
@@ -264,7 +263,7 @@ public void testShow() throws MetaNotFoundException {
         ShowHistogramStatsMetaStmt showHistogramStatsMetaStmt = (ShowHistogramStatsMetaStmt) analyzeSuccess(sql);
         HistogramStatsMeta histogramStatsMeta = new HistogramStatsMeta(testDb.getId(), table.getId(), "v1",
                 StatsConstants.AnalyzeType.HISTOGRAM, LocalDateTime.of(
-                        2020, 1, 1, 1, 1),
+                2020, 1, 1, 1, 1),
                 Maps.newHashMap());
         Assert.assertEquals("[test, t0, v1, HISTOGRAM, 2020-01-01 01:01:00, {}]",
                 ShowHistogramStatsMetaStmt.showHistogramStatsMeta(getConnectContext(), histogramStatsMeta).toString());
@@ -272,8 +271,8 @@ public void testShow() throws MetaNotFoundException {
 
     @Test
     public void testStatisticsSqlBuilder() throws Exception {
-        Database database = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable table = (OlapTable) database.getTable("t0");
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), "t0");
         System.out.println(table.getPartitions());
         Partition partition = (new ArrayList<>(table.getPartitions())).get(0);
 
@@ -292,9 +291,9 @@ public void testStatisticsSqlBuilder() throws Exception {
                         Lists.newArrayList("v1", "v2"), Lists.newArrayList(v1.getType(), v2.getType())));
 
         Assert.assertEquals(String.format(
-                "SELECT cast(1 as INT), update_time, db_id, table_id, column_name, row_count, " +
-                        "data_size, distinct_count, null_count, max, min " +
-                        "FROM table_statistic_v1 WHERE db_id = %d and table_id = %d and column_name in ('v1', 'v2')",
+                        "SELECT cast(1 as INT), update_time, db_id, table_id, column_name, row_count, " +
+                                "data_size, distinct_count, null_count, max, min " +
+                                "FROM table_statistic_v1 WHERE db_id = %d and table_id = %d and column_name in ('v1', 'v2')",
                         database.getId(), table.getId()),
                 StatisticSQLBuilder.buildQuerySampleStatisticsSQL(database.getId(),
                         table.getId(), Lists.newArrayList("v1", "v2")));
@@ -322,7 +321,7 @@ public void testHistogram() {
     @Test
     public void testHistogramSampleRatio() {
         OlapTable t0 = (OlapTable) starRocksAssert.getCtx().getGlobalStateMgr()
-                .getDb("db").getTable("tbl");
+                .getLocalMetastore().getDb("db").getTable("tbl");
         for (Partition partition : t0.getAllPartitions()) {
             partition.getBaseIndex().setRowCount(10000);
         }
@@ -388,38 +387,39 @@ public void testDropAnalyzeTest() {
 
     @Test
     public void testAnalyzeStatus() throws MetaNotFoundException {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = testDb.getTable("t0");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "t0");
         AnalyzeStatus analyzeStatus = new NativeAnalyzeStatus(-1, testDb.getId(), table.getId(), Lists.newArrayList(),
                 StatsConstants.AnalyzeType.FULL,
                 StatsConstants.ScheduleType.ONCE, Maps.newHashMap(), LocalDateTime.of(
-                        2020, 1, 1, 1, 1));
+                2020, 1, 1, 1, 1));
         analyzeStatus.setEndTime(LocalDateTime.of(2020, 1, 1, 1, 1));
         analyzeStatus.setStatus(StatsConstants.ScheduleStatus.RUNNING);
         Assert.assertEquals(
                 "[-1, default_catalog.test, t0, ALL, FULL, ONCE, RUNNING (0%), 2020-01-01 01:01:00, 2020-01-01 01:01:00," +
-                " {}, ]", ShowAnalyzeStatusStmt.showAnalyzeStatus(getConnectContext(), analyzeStatus).toString());
+                        " {}, ]", ShowAnalyzeStatusStmt.showAnalyzeStatus(getConnectContext(), analyzeStatus).toString());
 
         analyzeStatus.setProgress(50);
         Assert.assertEquals(
                 "[-1, default_catalog.test, t0, ALL, FULL, ONCE, RUNNING (50%), 2020-01-01 01:01:00, 2020-01-01 01:01:00," +
-                " {}, ]", ShowAnalyzeStatusStmt.showAnalyzeStatus(getConnectContext(), analyzeStatus).toString());
+                        " {}, ]", ShowAnalyzeStatusStmt.showAnalyzeStatus(getConnectContext(), analyzeStatus).toString());
 
         analyzeStatus.setStatus(StatsConstants.ScheduleStatus.FINISH);
         Assert.assertEquals(
                 "[-1, default_catalog.test, t0, ALL, FULL, ONCE, SUCCESS, 2020-01-01 01:01:00, 2020-01-01 01:01:00," +
-                " {}, ]", ShowAnalyzeStatusStmt.showAnalyzeStatus(getConnectContext(), analyzeStatus).toString());
+                        " {}, ]", ShowAnalyzeStatusStmt.showAnalyzeStatus(getConnectContext(), analyzeStatus).toString());
 
         analyzeStatus.setStatus(StatsConstants.ScheduleStatus.FAILED);
         Assert.assertEquals(
                 "[-1, default_catalog.test, t0, ALL, FULL, ONCE, FAILED, 2020-01-01 01:01:00, 2020-01-01 01:01:00," +
-                " {}, ]", ShowAnalyzeStatusStmt.showAnalyzeStatus(getConnectContext(), analyzeStatus).toString());
+                        " {}, ]", ShowAnalyzeStatusStmt.showAnalyzeStatus(getConnectContext(), analyzeStatus).toString());
     }
 
     @Test
     public void testObjectColumns() {
-        Database database = GlobalStateMgr.getCurrentState().getDb("db");
-        OlapTable table = (OlapTable) database.getTable("tb2");
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db");
+        OlapTable table =
+                (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), "tb2");
 
         Column kk1 = table.getColumn("kk1");
         Column kk2 = table.getColumn("kk2");
@@ -447,7 +447,7 @@ public void testQueryDict() throws Exception {
         String tblName = "insert";
         String sql = "select cast(" + 1 + " as Int), " +
                 "cast(" + 2 + " as bigint), " +
-                "dict_merge(" +  StatisticUtils.quoting(column) + ") as _dict_merge_" + column +
+                "dict_merge(" + StatisticUtils.quoting(column) + ") as _dict_merge_" + column +
                 " from " + StatisticUtils.quoting(catalogName, dbName, tblName) + " [_META_]";
         QueryStatement stmt = (QueryStatement) UtFrameUtils.parseStmtWithNewParserNotIncludeAnalyzer(sql, getConnectContext());
         Assert.assertEquals("select.insert",
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/CTASAnalyzerTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/CTASAnalyzerTest.java
index a06675f96db48c..1ba79c8113a467 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/CTASAnalyzerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/CTASAnalyzerTest.java
@@ -215,7 +215,7 @@ public void testSelectColumn() throws Exception {
         String sql = "create table t2 as select k1 as a,k2 as b from duplicate_table_with_null t2;";
 
         StatisticStorage storage = new CachedStatisticStorage();
-        Table table = ctx.getGlobalStateMgr().getDb("ctas")
+        Table table = ctx.getGlobalStateMgr().getLocalMetastore().getDb("ctas")
                 .getTable("duplicate_table_with_null");
         ColumnStatistic k1cs = new ColumnStatistic(1.5928416E9, 1.5982848E9,
                 1.5256461111280627E-4, 4.0, 64.0);
@@ -367,7 +367,7 @@ public void testCTASView() throws Exception {
     @Test
     public void testCTASReplicaNum() throws Exception {
         ConnectContext ctx = starRocksAssert.getCtx();
-        Table table = ctx.getGlobalStateMgr().getDb("ctas")
+        Table table = ctx.getGlobalStateMgr().getLocalMetastore().getDb("ctas")
                 .getTable("duplicate_table_with_null");
         OlapTable olapTable = (OlapTable) table;
         olapTable.setReplicationNum((short) 3);
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/MaterializedViewAnalyzerTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/MaterializedViewAnalyzerTest.java
index ce47de07798107..ecd2557440f8ad 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/MaterializedViewAnalyzerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/MaterializedViewAnalyzerTest.java
@@ -30,6 +30,7 @@
 import com.starrocks.common.Pair;
 import com.starrocks.qe.ShowExecutor;
 import com.starrocks.qe.ShowResultSet;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.ast.ShowStmt;
 import com.starrocks.sql.plan.ConnectorPlanTestBase;
 import com.starrocks.utframe.StarRocksAssert;
@@ -240,8 +241,8 @@ public void testCreateIcebergTable() throws Exception {
     @Test
     public void testRefreshMaterializedView() throws Exception {
         analyzeSuccess("refresh materialized view mv");
-        Database testDb = starRocksAssert.getCtx().getGlobalStateMgr().getDb("test");
-        Table table = testDb.getTable("mv");
+        Database testDb = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(testDb.getFullName(), "mv");
         Assert.assertNotNull(table);
         Assert.assertTrue(table instanceof MaterializedView);
         MaterializedView mv = (MaterializedView) table;
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/PrivilegeCheckerTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/PrivilegeCheckerTest.java
index cfc616929b16aa..2153e5194b13df 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/PrivilegeCheckerTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/analyzer/PrivilegeCheckerTest.java
@@ -787,7 +787,7 @@ public void testShowAnalyzeJobStatement() throws Exception {
         grantRevokeSqlAsRoot("revoke SELECT,INSERT on db3.tbl1 from test");
 
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
-        Database db1 = globalStateMgr.getDb("db1");
+        Database db1 = globalStateMgr.getLocalMetastore().getDb("db1");
         nativeAnalyzeJob = new NativeAnalyzeJob(db1.getId(), -1, Lists.newArrayList(), Lists.newArrayList(),
                 StatsConstants.AnalyzeType.FULL, StatsConstants.ScheduleType.ONCE, Maps.newHashMap(),
                 StatsConstants.ScheduleStatus.FINISH, LocalDateTime.MIN);
@@ -832,7 +832,7 @@ public void testShowAnalyzeJobStatement() throws Exception {
         new StmtExecutor(ctx, new KillAnalyzeStmt(0L)).checkPrivilegeForKillAnalyzeStmt(ctx, nativeAnalyzeJob.getId());
         grantRevokeSqlAsRoot("revoke SELECT,INSERT on db1.tbl1 from test");
 
-        Database db2 = globalStateMgr.getDb("db2");
+        Database db2 = globalStateMgr.getLocalMetastore().getDb("db2");
         tbl1 = db2.getTable("tbl1");
         nativeAnalyzeJob = new NativeAnalyzeJob(db2.getId(), tbl1.getId(), Lists.newArrayList(), Lists.newArrayList(),
                 StatsConstants.AnalyzeType.FULL, StatsConstants.ScheduleType.ONCE, Maps.newHashMap(),
@@ -854,7 +854,7 @@ public void testShowAnalyzeStatusStatement() throws Exception {
         AnalyzeMgr analyzeManager = GlobalStateMgr.getCurrentState().getAnalyzeMgr();
 
         GlobalStateMgr globalStateMgr = GlobalStateMgr.getCurrentState();
-        Database db1 = globalStateMgr.getDb("db1");
+        Database db1 = globalStateMgr.getLocalMetastore().getDb("db1");
         Table tbl1 = db1.getTable("tbl1");
 
         AnalyzeStatus analyzeStatus = new NativeAnalyzeStatus(1, db1.getId(), tbl1.getId(),
@@ -898,7 +898,7 @@ public void testShowAnalyzeStatusStatement() throws Exception {
         // can show result for stats on table that user has any privilege on
         Assert.assertNotNull(showResult);
 
-        Database db2 = globalStateMgr.getDb("db2");
+        Database db2 = globalStateMgr.getLocalMetastore().getDb("db2");
         tbl1 = db2.getTable("tbl1");
         analyzeStatus = new NativeAnalyzeStatus(1, db2.getId(), tbl1.getId(),
                 Lists.newArrayList(), StatsConstants.AnalyzeType.FULL,
@@ -1674,7 +1674,7 @@ public void testDatabaseStmt() throws Exception {
                 "Access denied");
 
         // Test `use database` : check any privilege on any function in db
-        Database db1 = GlobalStateMgr.getCurrentState().getDb("db1");
+        Database db1 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db1");
         FunctionName fn = FunctionName.createFnName("db1.my_udf_json_get");
         Function function = new Function(fn, Arrays.asList(Type.STRING, Type.STRING), Type.STRING, false);
         try {
@@ -1861,7 +1861,7 @@ public void testShowTabletStmt() throws Exception {
         List<Replica> replicas =
                 GlobalStateMgr.getCurrentState().getTabletInvertedIndex().getReplicasByTabletId(tabletId);
         Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db1");
-        Table table = db.getTable("tbl1");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl1");
         ReplicasProcNode replicasProcNode = new ReplicasProcNode(db, (OlapTable) table, tabletId, replicas);
         try {
             replicasProcNode.fetchResult();
@@ -1892,7 +1892,7 @@ public void testCheckPrivForCurrUserInTabletCtx() throws Exception {
 
         // test user has `OPERATE` privilege
         grantRevokeSqlAsRoot("grant OPERATE on SYSTEM to test");
-        Table table = db.getTable("tbl1");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tbl1");
         tabletSchedCtx = new TabletSchedCtx(TabletSchedCtx.Type.REPAIR,
                 db.getId(), table.getId(), 3, 4, 1000, System.currentTimeMillis());
         result = tabletSchedCtx.checkPrivForCurrUser(testUser);
@@ -2787,7 +2787,7 @@ public void analyze(CreateFunctionStmt stmt, ConnectContext context) {
 
     @Test
     public void testFunc() throws Exception {
-        Database db1 = GlobalStateMgr.getCurrentState().getDb("db1");
+        Database db1 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db1");
         FunctionName fn = FunctionName.createFnName("db1.my_udf_json_get");
         Function function = new Function(fn, Arrays.asList(Type.STRING, Type.STRING), Type.STRING, false);
         try {
@@ -2900,7 +2900,7 @@ public void testDropGlobalFunc() throws Exception {
     @Test
     public void testShowFunc() throws Exception {
 
-        Database db1 = GlobalStateMgr.getCurrentState().getDb("db1");
+        Database db1 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("db1");
         FunctionName fn = FunctionName.createFnName("db1.my_udf_json_get");
         Function function = new Function(fn, Arrays.asList(Type.STRING, Type.STRING), Type.STRING, false);
         try {
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/common/MetaUtilTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/common/MetaUtilTest.java
index a809711bdea84b..97c1c8eff79e3c 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/common/MetaUtilTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/common/MetaUtilTest.java
@@ -72,8 +72,8 @@ public static void beforeClass() throws Exception {
 
     @Test
     public void testIsPartitionExist() {
-        Database database = GlobalStateMgr.getCurrentState().getDb("test");
-        Table table = database.getTable("t0");
+        Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), "t0");
         List<Partition> partitionList = new ArrayList<>(table.getPartitions());
         Assert.assertFalse(MetaUtils.isPartitionExist(GlobalStateMgr.getCurrentState(),
                 -1, -1, -1));
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/common/SqlWithIdUtilsTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/common/SqlWithIdUtilsTest.java
index 49071af24f49ad..655aa919a1fc46 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/common/SqlWithIdUtilsTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/common/SqlWithIdUtilsTest.java
@@ -75,7 +75,7 @@ public static void beforeClass() throws Exception {
 
     @Test
     public void testDecodeAndEncode() {
-        Database test = GlobalStateMgr.getCurrentState().getDb("test");
+        Database test = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         Table tbl1 = test.getTable("tbl1");
         Table tbl2 = test.getTable("tbl2");
         System.out.println(test.getId() + " " + tbl1.getId() + " " + tbl2.getId());
@@ -128,7 +128,7 @@ public void testDecodeAndEncodeHasAlias() {
     @Test
     public void testDecodeAndEncodeNoDataBase() throws Exception {
         String sql = "select tbl1.k1, tbl2.k2 from test.tbl1 join test.tbl2 on tbl1.k1 = tbl2.k1";
-        Database test = GlobalStateMgr.getCurrentState().getDb("test");
+        Database test = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         try {
             StatementBase statementBase = UtFrameUtils.parseStmtWithNewParser(sql, connectContext);
             String encode = SqlWithIdUtils.encode(statementBase, connectContext);
@@ -171,7 +171,7 @@ public void testDecodeAndEncodeNoDataBase() throws Exception {
     @Test
     public void testDecodeAndEncodeNoTable() throws Exception {
         String sql = "select tbl1.k1, tbl2.k2 from test.tbl1 join test.tbl2 on tbl1.k1 = tbl2.k1";
-        Database test = GlobalStateMgr.getCurrentState().getDb("test");
+        Database test = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         Table tbl1 = test.getTable("tbl1");
         Table tbl2 = test.getTable("tbl2");
         try {
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/UtilsTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/UtilsTest.java
index d1bc9e1d2e75bd..6697579d58ec6d 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/UtilsTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/UtilsTest.java
@@ -261,7 +261,7 @@ public void compoundAnd3() {
     public void unknownStats1() {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
 
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(t0, 10);
         GlobalStateMgr.getCurrentState().getStatisticStorage().addColumnStatistic(t0, "v1",
                 new ColumnStatistic(1, 1, 0, 1, 1));
@@ -289,7 +289,7 @@ public void unknownStats1() {
     @Test
     public void unknownStats2() {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("t1");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t1");
         OptExpression opt =
                 new OptExpression(
                         new LogicalOlapScanOperator(t1, Maps.newHashMap(), Maps.newHashMap(), null, -1, null));
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/operator/ColumnFilterConverterTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/operator/ColumnFilterConverterTest.java
index 952af4ae70f83d..cc58fe577b6d53 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/operator/ColumnFilterConverterTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/operator/ColumnFilterConverterTest.java
@@ -264,7 +264,7 @@ public void testConvertPredicate() {
         argument.add(constantOperator);
         ScalarOperator predicate = new BinaryPredicateOperator(BinaryType.EQ, argument);
 
-        Table table = GlobalStateMgr.getCurrentState().getDb("test").getTable("bill_detail");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("bill_detail");
         ExpressionRangePartitionInfoV2 partitionInfo = (ExpressionRangePartitionInfoV2) ((OlapTable) table).getPartitionInfo();
         ScalarOperator afterConvert = ColumnFilterConverter.convertPredicate(predicate, partitionInfo, table.getIdToColumn());
         Assert.assertEquals(2921712368984L, ((ConstantOperator) afterConvert.getChild(1)).getValue());
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rewrite/PredicateReorderRuleTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rewrite/PredicateReorderRuleTest.java
index 91bb240937640c..417718b36ac8fb 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rewrite/PredicateReorderRuleTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rewrite/PredicateReorderRuleTest.java
@@ -139,8 +139,8 @@ public static void beforeClass() throws Exception {
 
         GlobalStateMgr catalog = GlobalStateMgr.getCurrentState();
         CachedStatisticStorage cachedStatisticStorage = new CachedStatisticStorage();
-        OlapTable t0 = (OlapTable) catalog.getDb("test").getTable("t0");
-        OlapTable t1 = (OlapTable) catalog.getDb("test").getTable("t1");
+        OlapTable t0 = (OlapTable) catalog.getLocalMetastore().getDb("test").getTable("t0");
+        OlapTable t1 = (OlapTable) catalog.getLocalMetastore().getDb("test").getTable("t1");
         cachedStatisticStorage.addColumnStatistic(t0, v1.getName(), statistics.getColumnStatistic(v1));
         cachedStatisticStorage.addColumnStatistic(t0, v2.getName(), statistics.getColumnStatistic(v2));
         cachedStatisticStorage.addColumnStatistic(t1, v1.getName(), statistics.getColumnStatistic(v1));
@@ -156,7 +156,7 @@ public void testOlapScanPredicateReorder() {
 
         sessionVariable.enablePredicateReorder();
 
-        OlapTable t0 = (OlapTable) GlobalStateMgr.getCurrentState().getDb("test").getTable("t0");
+        OlapTable t0 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("t0");
 
         PredicateReorderRule predicateReorderRule = new PredicateReorderRule(sessionVariable);
 
@@ -230,8 +230,8 @@ public void testOlapScanPredicateReorder() {
     public void testHashJoinPredicateReorder() {
         sessionVariable.enablePredicateReorder();
 
-        OlapTable t0 = (OlapTable) GlobalStateMgr.getCurrentState().getDb("test").getTable("t0");
-        OlapTable t1 = (OlapTable) GlobalStateMgr.getCurrentState().getDb("test").getTable("t1");
+        OlapTable t0 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("t0");
+        OlapTable t1 = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("t1");
 
         PredicateReorderRule predicateReorderRule = new PredicateReorderRule(sessionVariable);
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/mv/MaterializedViewRuleTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/mv/MaterializedViewRuleTest.java
index af6063a0a121cc..f925f8164f84b6 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/mv/MaterializedViewRuleTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/mv/MaterializedViewRuleTest.java
@@ -47,10 +47,10 @@ public class MaterializedViewRuleTest extends PlanTestBase {
     public static void beforeClass() throws Exception {
         PlanTestBase.beforeClass();
         starRocksAssert.withMaterializedView("CREATE MATERIALIZED VIEW lo_count_mv as " +
-                "select LO_ORDERDATE,count(LO_LINENUMBER) from lineorder_flat_for_mv group by LO_ORDERDATE;");
+                    "select LO_ORDERDATE,count(LO_LINENUMBER) from lineorder_flat_for_mv group by LO_ORDERDATE;");
         starRocksAssert.withMaterializedView("CREATE MATERIALIZED VIEW lo_count_key_mv as " +
-                "select LO_ORDERDATE, LO_ORDERKEY, count(LO_LINENUMBER) from lineorder_flat_for_mv" +
-                " group by LO_ORDERDATE, LO_ORDERKEY;");
+                    "select LO_ORDERDATE, LO_ORDERKEY, count(LO_LINENUMBER) from lineorder_flat_for_mv" +
+                    " group by LO_ORDERDATE, LO_ORDERKEY;");
     }
 
     @Test
@@ -63,8 +63,9 @@ public void testMaterializedViewWithCountSelection() throws Exception {
         OlapScanNode olapScanNode = (OlapScanNode) plan.getScanNodes().get(0);
         Long selectedIndexid = olapScanNode.getSelectedIndexId();
         GlobalStateMgr globalStateMgr = starRocksAssert.getCtx().getGlobalStateMgr();
-        Database database = globalStateMgr.getDb("test");
-        Table table = database.getTable("lineorder_flat_for_mv");
+        Database database = globalStateMgr.getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(database.getFullName(), "lineorder_flat_for_mv");
         Assert.assertTrue(table instanceof OlapTable);
         OlapTable baseTable = (OlapTable) table;
         Assert.assertEquals(baseTable.getIndexIdByName("lo_count_mv"), selectedIndexid);
@@ -73,13 +74,14 @@ public void testMaterializedViewWithCountSelection() throws Exception {
     @Test
     public void testKeyColumnsMatch() throws Exception {
         GlobalStateMgr globalStateMgr = starRocksAssert.getCtx().getGlobalStateMgr();
-        Database database = globalStateMgr.getDb("test");
-        Table table = database.getTable("lineorder_flat_for_mv");
+        Database database = globalStateMgr.getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(database.getFullName(), "lineorder_flat_for_mv");
         OlapTable baseTable = (OlapTable) table;
 
         String sql = "select LO_ORDERDATE, sum(case when LO_ORDERKEY=0 then 0 else 1 end) as test, " +
-                "sum(case when LO_ORDERKEY=1 then 1 else 0 end) as nontest " +
-                " from lineorder_flat_for_mv group by LO_ORDERDATE;";
+                    "sum(case when LO_ORDERKEY=1 then 1 else 0 end) as nontest " +
+                    " from lineorder_flat_for_mv group by LO_ORDERDATE;";
         ExecPlan plan = getExecPlan(sql);
         OlapScanNode olapScanNode = (OlapScanNode) plan.getScanNodes().get(0);
         Long selectedIndexid = olapScanNode.getSelectedIndexId();
@@ -96,7 +98,7 @@ public void testCount1Rewrite() {
         arguments.add(queryColumnRef);
         CallOperator aggCall = new CallOperator(FunctionSet.COUNT, Type.BIGINT, arguments);
         MaterializedViewRule.RewriteContext rewriteContext =
-                new MaterializedViewRule.RewriteContext(aggCall, queryColumnRef, mvColumnRef, mvColumn);
+                    new MaterializedViewRule.RewriteContext(aggCall, queryColumnRef, mvColumnRef, mvColumn);
         ColumnRefOperator dsColumnRef = tmpRefFactory.create("ds", Type.INT, false);
         List<ColumnRefOperator> groupKeys = Lists.newArrayList();
         groupKeys.add(dsColumnRef);
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MVRewriteWithSchemaChangeTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MVRewriteWithSchemaChangeTest.java
index b63192c5ca3133..6875211d870596 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MVRewriteWithSchemaChangeTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MVRewriteWithSchemaChangeTest.java
@@ -70,7 +70,6 @@ public void testSyncMVRewrite_PartitionPrune() throws Exception {
         PlanTestBase.assertContains(plan, "sync_mv1");
     }
 
-
     @Test
     public void testMVCacheInvalidAndReValid() throws Exception {
         starRocksAssert.withTable("\n" +
@@ -125,8 +124,9 @@ public void testMVCacheInvalidAndReValid() throws Exception {
             waitForSchemaChangeAlterJobFinish();
 
             // check mv invalid
-            Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-            MaterializedView mv1 = ((MaterializedView) testDb.getTable("test_cache_mv1"));
+            Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+            MaterializedView mv1 = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), "test_cache_mv1"));
             Assert.assertFalse(mv1.isActive());
             try {
                 cluster.runSql("test", "alter materialized view test_cache_mv1 active;");
@@ -273,7 +273,6 @@ public void testMVWithViewAndSubQuery1() throws Exception {
             dropMv("test", "join_mv_1");
         }
 
-
         {
             starRocksAssert.withMTableNames(cluster, List.of("depts", "emps_par"),
                     () -> {
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRefreshAndRewriteIcebergTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRefreshAndRewriteIcebergTest.java
index a5dbbe89b04449..212959465d8cc4 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRefreshAndRewriteIcebergTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRefreshAndRewriteIcebergTest.java
@@ -45,15 +45,15 @@ public static void beforeClass() throws Exception {
     public void testStr2DateMVRefreshRewriteSingleTable_UnionRewrite() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select a, b, d, bitmap_union(to_bitmap(t1.c))" +
-                " from iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " group by a, b, d;");
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select a, b, d, bitmap_union(to_bitmap(t1.c))" +
+                    " from iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " group by a, b, d;");
 
         testSingleTableWithMVRewrite(mvName);
 
@@ -65,16 +65,16 @@ public void testStr2DateMVRefreshRewriteSingleTable_UnionRewrite() throws Except
     public void testStr2DateMVRefreshRewriteSingleTableWithView() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withView("CREATE VIEW view1 as select a, b, d, bitmap_union(to_bitmap(t1.c))\n" +
-                " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                " group by a, b, d;");
+                    " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                    " group by a, b, d;");
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select * from view1");
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select * from view1");
 
         testSingleTableWithMVRewrite(mvName);
 
@@ -84,24 +84,25 @@ public void testStr2DateMVRefreshRewriteSingleTableWithView() throws Exception {
     }
 
     private void testSingleTableWithMVRewrite(String mvName) throws Exception {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-01') " +
-                "end ('2023-08-02') force with sync mode");
+                    "end ('2023-08-02') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802"), partitions);
 
         {
             String query = "select t1.a, t2.b, t1.d, count(distinct t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01')\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01')\n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, "test_mv1");
         }
@@ -109,86 +110,86 @@ private void testSingleTableWithMVRewrite(String mvName) throws Exception {
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("force");
         {
             String query = "select a, b, d, count(distinct t1.c)\n" +
-                    " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " where d='2023-08-01'" +
-                    " group by a, b, d;";
+                        " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " where d='2023-08-01'" +
+                        " group by a, b, d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
 
         {
             String query = "select a, b, d, count(distinct t1.c)\n" +
-                    " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " where t1.d >= '2023-08-01' \n" +
-                    " group by a, b, d;";
+                        " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " where t1.d >= '2023-08-01' \n" +
+                        " group by a, b, d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
 
             PlanTestBase.assertContains(plan, "OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
             PlanTestBase.assertContains(plan, "IcebergScanNode\n" +
-                    "     TABLE: part_tbl1\n" +
-                    "     PREDICATES: 13: d != '2023-08-01', 13: d >= '2023-08-01'");
+                        "     TABLE: part_tbl1\n" +
+                        "     PREDICATES: 13: d != '2023-08-01', 13: d >= '2023-08-01'");
         }
         {
             String query = "select a, b, d, count(distinct t1.c)\n" +
-                    " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " group by a, b, d;";
+                        " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " group by a, b, d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
 
             PlanTestBase.assertContains(plan, "OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
             PlanTestBase.assertContains(plan, "IcebergScanNode\n" +
-                    "     TABLE: part_tbl1\n" +
-                    "     PREDICATES: 13: d != '2023-08-01'");
+                        "     TABLE: part_tbl1\n" +
+                        "     PREDICATES: 13: d != '2023-08-01'");
         }
 
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-02') " +
-                "end ('2023-08-03') force with sync mode");
+                    "end ('2023-08-03') force with sync mode");
         partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802", "p20230802_20230803"), partitions);
 
         {
             String query = "select a, b, d, count(distinct t1.c)\n" +
-                    " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " where t1.d >= '2023-08-01' \n" +
-                    " group by a, b, d;";
+                        " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " where t1.d >= '2023-08-01' \n" +
+                        " group by a, b, d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
 
             PlanTestBase.assertContains(plan, "OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=2/2");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=2/2");
             PlanTestBase.assertContains(plan, "IcebergScanNode\n" +
-                    "     TABLE: part_tbl1\n" +
-                    "     PREDICATES: 13: d != '2023-08-01', 13: d != '2023-08-02'");
+                        "     TABLE: part_tbl1\n" +
+                        "     PREDICATES: 13: d != '2023-08-01', 13: d != '2023-08-02'");
         }
         {
             String query = "select a, b, d, count(distinct t1.c)\n" +
-                    " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " group by a, b, d;";
+                        " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " group by a, b, d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
 
             PlanTestBase.assertContains(plan, "OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=2/2");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=2/2");
             PlanTestBase.assertContains(plan, "IcebergScanNode\n" +
-                    "     TABLE: part_tbl1\n" +
-                    "     PREDICATES: 13: d != '2023-08-01', 13: d != '2023-08-02'");
+                        "     TABLE: part_tbl1\n" +
+                        "     PREDICATES: 13: d != '2023-08-01', 13: d != '2023-08-02'");
         }
     }
 
@@ -196,67 +197,68 @@ private void testSingleTableWithMVRewrite(String mvName) throws Exception {
     public void testStr2DateMVRefreshRewrite_InnerJoin_FullRefresh() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select  t1.a, t2.b, t3.c, t1.d " +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d ;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select  t1.a, t2.b, t3.c, t1.d " +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d ;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802", "p20230802_20230803", "p20230803_20230804"), partitions);
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/3\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/3\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='20230801';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='20230801';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 16: d >= '20230801'\n" +
-                    "     partitions=3/3\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 16: d >= '20230801'\n" +
+                        "     partitions=3/3\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d < '20230802';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d < '20230802';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/3\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/3\n" +
+                        "     rollup: test_mv1");
         }
 
         starRocksAssert.dropMaterializedView(mvName);
@@ -266,64 +268,65 @@ public void testStr2DateMVRefreshRewrite_InnerJoin_FullRefresh() throws Exceptio
     public void testStr2DateMVRefreshRewrite_InnerJoin_PartialRefresh() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select  t1.a, t2.b, t3.c, t1.d " +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d ;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select  t1.a, t2.b, t3.c, t1.d " +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d ;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-01') " +
-                "end ('2023-08-02') force with sync mode");
+                    "end ('2023-08-02') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802"), partitions);
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='20230801';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='20230801';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, "test_mv1");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d < '20230802';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d < '20230802';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "12:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         starRocksAssert.dropMaterializedView(mvName);
@@ -333,67 +336,68 @@ public void testStr2DateMVRefreshRewrite_InnerJoin_PartialRefresh() throws Excep
     public void testStr2DateMVRefreshRewrite_LeftJoin_FullRefresh() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select  t1.a, t2.b, t3.c, t1.d " +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d ;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select  t1.a, t2.b, t3.c, t1.d " +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d ;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802", "p20230802_20230803", "p20230803_20230804"), partitions);
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/3\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/3\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='20230801';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='20230801';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 16: d >= '20230801'\n" +
-                    "     partitions=3/3\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 16: d >= '20230801'\n" +
+                        "     partitions=3/3\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d < '20230802';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d < '20230802';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/3\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/3\n" +
+                        "     rollup: test_mv1");
         }
 
         starRocksAssert.dropMaterializedView(mvName);
@@ -403,89 +407,90 @@ public void testStr2DateMVRefreshRewrite_LeftJoin_FullRefresh() throws Exception
     public void testStr2DateMVRefreshRewrite_LeftJoin_PartialRefresh() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select  t1.a, t2.b, t3.c, t1.d " +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d ;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select  t1.a, t2.b, t3.c, t1.d " +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d ;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-01') " +
-                "end ('2023-08-02') force with sync mode");
+                    "end ('2023-08-02') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802"), partitions);
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='20230801';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='20230801';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, "test_mv1");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d < '20230802';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d < '20230802';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "12:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='2023-08-01';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='2023-08-01';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "test_mv1");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d < '2023-08-02';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d < '2023-08-02';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "12:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
         starRocksAssert.dropMaterializedView(mvName);
     }
@@ -494,138 +499,139 @@ public void testStr2DateMVRefreshRewrite_LeftJoin_PartialRefresh() throws Except
     public void testStr2DateMVRefreshRewrite_InnerJoin_PartitionPrune1() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select  t1.a, t2.b, t3.c, t1.d " +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d ;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select  t1.a, t2.b, t3.c, t1.d " +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d ;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802", "p20230802_20230803", "p20230803_20230804"), partitions);
 
         {
             String query = "select  count(*) from " + mvName +
-                    " where d='2023-08-01';";
+                        " where d='2023-08-01';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/3\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/3\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  count(*) from " + mvName +
-                    " where d in ('2023-08-01');";
+                        " where d in ('2023-08-01');";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/3");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/3");
         }
 
         {
             String query = "select  count(*) from " + mvName +
-                    " where d in ('2023-08-01', '2023-08-02');";
+                        " where d in ('2023-08-01', '2023-08-02');";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 4: d IN ('2023-08-01', '2023-08-02')\n" +
-                    "     partitions=2/3\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 4: d IN ('2023-08-01', '2023-08-02')\n" +
+                        "     partitions=2/3\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  count(*) from " + mvName +
-                    " where d in ('2023-08-01', '2023-08-02', '2023-08-03');";
+                        " where d in ('2023-08-01', '2023-08-02', '2023-08-03');";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 4: d IN ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
-                    "     partitions=3/3");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 4: d IN ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
+                        "     partitions=3/3");
         }
 
         {
             String query = "select  count(*) from " + mvName +
-                    " where d not in ('2023-08-01', '2023-08-02');";
+                        " where d not in ('2023-08-01', '2023-08-02');";
             String plan = getFragmentPlan(query);
             // TODO: no partition prune
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 4: d NOT IN ('2023-08-01', '2023-08-02')\n" +
-                    "     partitions=3/3\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 4: d NOT IN ('2023-08-01', '2023-08-02')\n" +
+                        "     partitions=3/3\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  count(*) from " + mvName +
-                    " where d >= '2023-08-01' and d < '2023-08-02';";
+                        " where d >= '2023-08-01' and d < '2023-08-02';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/3\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/3\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  count(*) from " + mvName +
-                    " where cast(d as date) >= '2023-08-01'";
+                        " where cast(d as date) >= '2023-08-01'";
             String plan = getFragmentPlan(query);
             // TODO: no partition prune
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: CAST(4: d AS DATE) >= '2023-08-01'\n" +
-                    "     partitions=3/3");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: CAST(4: d AS DATE) >= '2023-08-01'\n" +
+                        "     partitions=3/3");
         }
 
         connectContext.getSessionVariable().setRangePrunerPredicateMaxLen(0);
         {
             String query = "select  count(*) from " + mvName +
-                    " where d in ('2023-08-01');";
+                        " where d in ('2023-08-01');";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/3");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/3");
         }
 
         {
             String query = "select  count(*) from " + mvName +
-                    " where d in ('2023-08-01', '2023-08-02');";
+                        " where d in ('2023-08-01', '2023-08-02');";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 4: d IN ('2023-08-01', '2023-08-02')\n" +
-                    "     partitions=2/3\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 4: d IN ('2023-08-01', '2023-08-02')\n" +
+                        "     partitions=2/3\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  count(*) from " + mvName +
-                    " where d in ('2023-08-01', '2023-08-02', '2023-08-03');";
+                        " where d in ('2023-08-01', '2023-08-02', '2023-08-03');";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 4: d IN ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
-                    "     partitions=3/3");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 4: d IN ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
+                        "     partitions=3/3");
         }
 
         starRocksAssert.dropMaterializedView(mvName);
@@ -635,165 +641,166 @@ public void testStr2DateMVRefreshRewrite_InnerJoin_PartitionPrune1() throws Exce
     public void testStr2DateMVRefreshRewrite_InnerJoin_PartitionPrune2() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select  t1.a, t2.b, t3.c, t1.d " +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d ;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select  t1.a, t2.b, t3.c, t1.d " +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d ;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802", "p20230802_20230803", "p20230803_20230804"), partitions);
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d \n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d='2023-08-01';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d='2023-08-01';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/3\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/3\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d \n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01');";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01');";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/3");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/3");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d \n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01', '2023-08-02');";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01', '2023-08-02');";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 16: d IN ('2023-08-01', '2023-08-02')\n" +
-                    "     partitions=2/3");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 16: d IN ('2023-08-01', '2023-08-02')\n" +
+                        "     partitions=2/3");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d \n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03');";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03');";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 16: d IN ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
-                    "     partitions=3/3");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 16: d IN ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
+                        "     partitions=3/3");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d \n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d not in ('2023-08-01', '2023-08-02');";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d not in ('2023-08-01', '2023-08-02');";
             String plan = getFragmentPlan(query);
             // TODO: no partition prune
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 16: d != '2023-08-01', 16: d != '2023-08-02'\n" +
-                    "     partitions=3/3");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 16: d != '2023-08-01', 16: d != '2023-08-02'\n" +
+                        "     partitions=3/3");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d \n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d >= '2023-08-01' and t1.d < '2023-08-02';";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d >= '2023-08-01' and t1.d < '2023-08-02';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/3\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/3\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d \n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where cast(t1.d as date) >= '2023-08-01'";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where cast(t1.d as date) >= '2023-08-01'";
             String plan = getFragmentPlan(query);
             // TODO: no partition prune
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: CAST(16: d AS DATE) >= '2023-08-01'\n" +
-                    "     partitions=3/3");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: CAST(16: d AS DATE) >= '2023-08-01'\n" +
+                        "     partitions=3/3");
         }
 
         connectContext.getSessionVariable().setRangePrunerPredicateMaxLen(0);
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d \n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01');";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01');";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/3");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/3");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d \n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01', '2023-08-02');";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01', '2023-08-02');";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 16: d IN ('2023-08-01', '2023-08-02')\n" +
-                    "     partitions=2/3");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 16: d IN ('2023-08-01', '2023-08-02')\n" +
+                        "     partitions=2/3");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d \n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03');";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03');";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 16: d IN ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
-                    "     partitions=3/3");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 16: d IN ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
+                        "     partitions=3/3");
         }
 
         starRocksAssert.dropMaterializedView(mvName);
@@ -803,89 +810,90 @@ public void testStr2DateMVRefreshRewrite_InnerJoin_PartitionPrune2() throws Exce
     public void testStr2DateMVRefreshRewrite_InnerJoin_ExtraCompensate() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(b) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select  t1.d, t2.b, t3.c, count(t1.a) " +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                " group by t1.d, t2.b, t3.c;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(b) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select  t1.d, t2.b, t3.c, count(t1.a) " +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                    " group by t1.d, t2.b, t3.c;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-01') " +
-                "end ('2023-08-02') force with sync mode");
+                    "end ('2023-08-02') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802"), partitions);
 
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("force");
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "13:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='2023-08-01' and t2.b != '' and t2.b is not null " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='2023-08-01' and t2.b != '' and t2.b is not null " +
+                        " group by t1.d, t2.b, t3.c;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "13:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='2023-08-01' and t2.b != '' and t2.b is not null and t2.b in ('xxx') " +
-                    " and t3.c in ('xxx') " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='2023-08-01' and t2.b != '' and t2.b is not null and t2.b in ('xxx') " +
+                        " and t3.c in ('xxx') " +
+                        " group by t1.d, t2.b, t3.c;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "13:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
         starRocksAssert.dropMaterializedView(mvName);
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("default");
@@ -895,50 +903,51 @@ public void testStr2DateMVRefreshRewrite_InnerJoin_ExtraCompensate() throws Exce
     public void testStr2DateMVRefreshRewrite_LeftJoin_OnPredicates_ExtraCompensate() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(b) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select  t1.d, t2.b, t3.c, count(t1.a) " +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                " group by t1.d, t2.b, t3.c;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(b) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select  t1.d, t2.b, t3.c, count(t1.a) " +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                    " group by t1.d, t2.b, t3.c;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-01') " +
-                "end ('2023-08-02') force with sync mode");
+                    "end ('2023-08-02') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802"), partitions);
 
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b is not null " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b is not null " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b != '' " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b != '' " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, "UNION");
@@ -946,11 +955,11 @@ public void testStr2DateMVRefreshRewrite_LeftJoin_OnPredicates_ExtraCompensate()
         }
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b != '' " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b != '' " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, "UNION");
             PlanTestBase.assertNotContains(plan, "test_mv1");
@@ -958,45 +967,45 @@ public void testStr2DateMVRefreshRewrite_LeftJoin_OnPredicates_ExtraCompensate()
 
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b != '' " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d in ('2023-08-01', '2023-08-02') " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b != '' " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d in ('2023-08-01', '2023-08-02') " +
+                        " group by t1.d, t2.b, t3.c;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, "UNION");
             PlanTestBase.assertNotContains(plan, "test_mv1");
         }
 
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-02') " +
-                "end ('2023-08-03') force with sync mode");
+                    "end ('2023-08-03') force with sync mode");
         partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802", "p20230802_20230803"), partitions);
 
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b is not null " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b is not null " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "3:IcebergScanNode\n" +
-                    "     TABLE: part_tbl1\n" +
-                    "     PREDICATES: 19: d >= '2023-08-01'");
+                        "     TABLE: part_tbl1\n" +
+                        "     PREDICATES: 19: d >= '2023-08-01'");
         }
 
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b is not null " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d in ('2023-08-01', '2023-08-02') " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b is not null " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d in ('2023-08-01', '2023-08-02') " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, "UNION");
@@ -1009,50 +1018,51 @@ public void testStr2DateMVRefreshRewrite_LeftJoin_OnPredicates_ExtraCompensate()
     public void testStr2DateMVRefreshRewrite_InnerJoin_OnPredicates_ExtraCompensate() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(b) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select  t1.d, t2.b, t3.c, count(t1.a) " +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                " group by t1.d, t2.b, t3.c;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(b) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select  t1.d, t2.b, t3.c, count(t1.a) " +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                    " group by t1.d, t2.b, t3.c;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-01') " +
-                "end ('2023-08-02') force with sync mode");
+                    "end ('2023-08-02') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802"), partitions);
 
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b is not null " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b is not null " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b != '' " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b != '' " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, "UNION");
@@ -1060,11 +1070,11 @@ public void testStr2DateMVRefreshRewrite_InnerJoin_OnPredicates_ExtraCompensate(
         }
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b != '' " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b != '' " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "test_mv1");
@@ -1072,11 +1082,11 @@ public void testStr2DateMVRefreshRewrite_InnerJoin_OnPredicates_ExtraCompensate(
 
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b != '' " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d in ('2023-08-01', '2023-08-02') " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d and t2.b != '' " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d in ('2023-08-01', '2023-08-02') " +
+                        " group by t1.d, t2.b, t3.c;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "test_mv1");
@@ -1089,90 +1099,91 @@ public void testStr2DateMVRefreshRewrite_InnerJoin_OnPredicates_ExtraCompensate(
     public void testStr2DateMVRefreshRewrite_LeftJoin_ExtraCompensate() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(b) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select  t1.d, t2.b, t3.c, count(t1.a) " +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                " group by t1.d, t2.b, t3.c;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(b) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select  t1.d, t2.b, t3.c, count(t1.a) " +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                    " group by t1.d, t2.b, t3.c;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-01') " +
-                "end ('2023-08-02') force with sync mode");
+                    "end ('2023-08-02') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802"), partitions);
 
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("default");
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("force");
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "13:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='2023-08-01' and t2.b != '' and t2.b is not null " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='2023-08-01' and t2.b != '' and t2.b is not null " +
+                        " group by t1.d, t2.b, t3.c;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "13:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  t1.d, t2.b, t3.c, count(t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='2023-08-01' and t2.b != '' and t2.b is not null and t2.b in ('xxx') " +
-                    " and t3.c in ('xxx') " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='2023-08-01' and t2.b != '' and t2.b is not null and t2.b in ('xxx') " +
+                        " and t3.c in ('xxx') " +
+                        " group by t1.d, t2.b, t3.c;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "13:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("default");
         starRocksAssert.dropMaterializedView(mvName);
@@ -1182,154 +1193,155 @@ public void testStr2DateMVRefreshRewrite_LeftJoin_ExtraCompensate() throws Excep
     public void testStr2DateMVRefreshRewriteInnerJoinAggregatePartialRefreshUnion() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select t1.a, t2.b, t1.d, count(t1.c)" +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                " group by t1.a, t2.b, t1.d;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select t1.a, t2.b, t1.d, count(t1.c)" +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                    " group by t1.a, t2.b, t1.d;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-01') " +
-                "end ('2023-08-02') force with sync mode");
+                    "end ('2023-08-02') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802"), partitions);
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("force");
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01')\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01')\n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d ='2023-08-01'\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d ='2023-08-01'\n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01', '2023-08-02')\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01', '2023-08-02')\n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d >= '2023-08-01' \n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d >= '2023-08-01' \n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d >= '2023-08-01' and t1.d <= '2023-08-02' \n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d >= '2023-08-01' and t1.d <= '2023-08-02' \n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d = '2023-08-01' or t1.d = '2023-08-02' \n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d = '2023-08-01' or t1.d = '2023-08-02' \n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
+                        " group by t1.a, t2.b, t1.d;";
             connectContext.getSessionVariable().setRangePrunerPredicateMaxLen(0);
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
         starRocksAssert.dropMaterializedView(mvName);
     }
@@ -1338,153 +1350,154 @@ public void testStr2DateMVRefreshRewriteInnerJoinAggregatePartialRefreshUnion()
     public void testStr2DateMVRefreshRewriteLeftJoinAggregatePartialRefreshUnion() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select t1.a, t2.b, t1.d, count(t1.c)" +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                " group by t1.a, t2.b, t1.d;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select t1.a, t2.b, t1.d, count(t1.c)" +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                    " group by t1.a, t2.b, t1.d;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-01') " +
-                "end ('2023-08-02') force with sync mode");
+                    "end ('2023-08-02') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802"), partitions);
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01')\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01')\n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d ='2023-08-01'\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d ='2023-08-01'\n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01', '2023-08-02')\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01', '2023-08-02')\n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d >= '2023-08-01' \n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d >= '2023-08-01' \n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d >= '2023-08-01' and t1.d <= '2023-08-02' \n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d >= '2023-08-01' and t1.d <= '2023-08-02' \n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d = '2023-08-01' or t1.d = '2023-08-02' \n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d = '2023-08-01' or t1.d = '2023-08-02' \n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
+                        " group by t1.a, t2.b, t1.d;";
             connectContext.getSessionVariable().setRangePrunerPredicateMaxLen(0);
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
         starRocksAssert.dropMaterializedView(mvName);
     }
@@ -1493,36 +1506,37 @@ public void testStr2DateMVRefreshRewriteLeftJoinAggregatePartialRefreshUnion() t
     public void testStr2DateMVRefreshRewriteLeftJoinBitmapAggregatePartialRefreshUnion() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select t1.a, t2.b, t1.d, bitmap_union(to_bitmap(t1.c))" +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                " group by t1.a, t2.b, t1.d;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select t1.a, t2.b, t1.d, bitmap_union(to_bitmap(t1.c))" +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                    " group by t1.a, t2.b, t1.d;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-01') " +
-                "end ('2023-08-02') force with sync mode");
+                    "end ('2023-08-02') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802"), partitions);
 
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("default");
         {
             String query = "select t1.a, t2.b, t1.d, count(distinct t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01')\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01')\n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "test_mv1");
         }
@@ -1530,132 +1544,132 @@ public void testStr2DateMVRefreshRewriteLeftJoinBitmapAggregatePartialRefreshUni
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("force");
         {
             String query = "select t1.a, t2.b, t1.d, count(distinct t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
 
             PlanTestBase.assertContains(plan, "OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
             PlanTestBase.assertContains(plan, "5:IcebergScanNode\n" +
-                    "     TABLE: part_tbl3\n" +
-                    "     PREDICATES: 27: d != '2023-08-01'");
+                        "     TABLE: part_tbl3\n" +
+                        "     PREDICATES: 27: d != '2023-08-01'");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(distinct t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d ='2023-08-01'\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d ='2023-08-01'\n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(distinct t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01', '2023-08-02')\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01', '2023-08-02')\n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(distinct t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(distinct t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d >= '2023-08-01' \n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d >= '2023-08-01' \n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(distinct t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d >= '2023-08-01' and t1.d <= '2023-08-02' \n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d >= '2023-08-01' and t1.d <= '2023-08-02' \n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(distinct t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d = '2023-08-01' or t1.d = '2023-08-02' \n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d = '2023-08-01' or t1.d = '2023-08-02' \n" +
+                        " group by t1.a, t2.b, t1.d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select t1.a, t2.b, t1.d, count(distinct t1.c)\n" +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
-                    " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
-                    " group by t1.a, t2.b, t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d \n" +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d \n" +
+                        " where t1.d in ('2023-08-01', '2023-08-02', '2023-08-03')\n" +
+                        " group by t1.a, t2.b, t1.d;";
             connectContext.getSessionVariable().setRangePrunerPredicateMaxLen(0);
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "14:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("default");
         starRocksAssert.dropMaterializedView(mvName);
@@ -1665,105 +1679,106 @@ public void testStr2DateMVRefreshRewriteLeftJoinBitmapAggregatePartialRefreshUni
     public void testStr2DateMVRefreshRewriteWithBitmapHash_LeftJoin() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(b) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select  t1.d, t2.b, t3.c, bitmap_union(bitmap_hash(t1.a)) " +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                " group by t1.d, t2.b, t3.c;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(b) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select  t1.d, t2.b, t3.c, bitmap_union(bitmap_hash(t1.a)) " +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                    " group by t1.d, t2.b, t3.c;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-01') " +
-                "end ('2023-08-02') force with sync mode");
+                    "end ('2023-08-02') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802"), partitions);
 
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("default");
         {
             String query = "select  t1.d, t2.b, t3.c, bitmap_union(bitmap_hash(t1.a)) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
 
         {
             String query = "select  t1.d, t2.b, t3.c, bitmap_union_count(bitmap_hash(t1.a)) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
 
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("force");
         {
             String query = "select t1.d, t2.b, t3.c, count(distinct t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
 
         {
             String query = "select  t1.d, t2.b, t3.c, count(distinct t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "13:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
 
         {
             String query = "select  t1.d, count(distinct t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='2023-08-01' " +
-                    " group by t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " left join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " left join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='2023-08-01' " +
+                        " group by t1.d;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "15:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
         starRocksAssert.dropMaterializedView(mvName);
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("default");
@@ -1773,104 +1788,105 @@ public void testStr2DateMVRefreshRewriteWithBitmapHash_LeftJoin() throws Excepti
     public void testStr2DateMVRefreshRewriteWithBitmapHash_InnerJoin() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(b) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select  t1.d, t2.b, t3.c, bitmap_union(bitmap_hash(t1.a)) " +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                " group by t1.d, t2.b, t3.c;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(b) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select  t1.d, t2.b, t3.c, bitmap_union(bitmap_hash(t1.a)) " +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                    " group by t1.d, t2.b, t3.c;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-01') " +
-                "end ('2023-08-02') force with sync mode");
+                    "end ('2023-08-02') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802"), partitions);
 
         {
             String query = "select  t1.d, t2.b, t3.c, bitmap_union(bitmap_hash(t1.a)) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
 
         {
             String query = "select  t1.d, t2.b, t3.c, bitmap_union_count(bitmap_hash(t1.a)) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
 
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("force");
         {
             String query = "select t1.d, t2.b, t3.c, count(distinct t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
 
         {
             String query = "select  t1.d, t2.b, t3.c, count(distinct t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='2023-08-01' " +
-                    " group by t1.d, t2.b, t3.c;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='2023-08-01' " +
+                        " group by t1.d, t2.b, t3.c;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "13:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
 
         {
             String query = "select  t1.d, count(distinct t1.a) " +
-                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='2023-08-01' " +
-                    " group by t1.d;";
+                        " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                        " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='2023-08-01' " +
+                        " group by t1.d;";
 
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "15:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("default");
         starRocksAssert.dropMaterializedView(mvName);
@@ -1880,51 +1896,52 @@ public void testStr2DateMVRefreshRewriteWithBitmapHash_InnerJoin() throws Except
     public void testStr2DateMVRefreshRewriteSingleTableWithDateTruc_Day() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withView("CREATE VIEW view1 as select " +
-                " a, b, " +
-                " date_trunc('day', str2date(d,'%Y-%m-%d')) as dt, " +
-                " bitmap_union(to_bitmap(t1.c))\n" +
-                " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                " group by a, b, dt;");
+                    " a, b, " +
+                    " date_trunc('day', str2date(d,'%Y-%m-%d')) as dt, " +
+                    " bitmap_union(to_bitmap(t1.c))\n" +
+                    " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                    " group by a, b, dt;");
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by dt " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select * from view1");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by dt " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select * from view1");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-01') " +
-                "end ('2023-08-02') force with sync mode");
+                    "end ('2023-08-02') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802"), partitions);
 
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("force");
         {
             String query = "select a, b, date_trunc('day', str2date(d,'%Y-%m-%d')) as dt, " +
-                    " count(distinct t1.c)\n" +
-                    " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " where d='2023-08-01'" +
-                    " group by a, b, dt;";
+                        " count(distinct t1.c)\n" +
+                        " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " where d='2023-08-01'" +
+                        " group by a, b, dt;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, "UNION");
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=1/1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=1/1");
         }
 
         // TODO: Support date_trunc('day', str2date(t1.d, ''%Y-%m-%d'')) to str2date(d, '%Y-%m-%d')
         {
             String query = "select a, b, count(distinct t1.c)\n" +
-                    " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " where date_trunc('day', str2date(t1.d, '%Y-%m-%d'))  >= '2023-08-01' \n" +
-                    " group by a, b;";
+                        " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " where date_trunc('day', str2date(t1.d, '%Y-%m-%d'))  >= '2023-08-01' \n" +
+                        " group by a, b;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, mvName);
         }
@@ -1938,53 +1955,54 @@ public void testStr2DateMVRefreshRewriteSingleTableWithDateTruc_Day() throws Exc
     public void testStr2DateMVRefreshRewriteSingleTableWithDateTruc_Month() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withView("CREATE VIEW view1 as select a, b, " +
-                " date_trunc('month', str2date(d,'%Y-%m-%d')) as dt, " +
-                " bitmap_union(to_bitmap(t1.c))\n" +
-                " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                " group by a, b, d;");
+                    " date_trunc('month', str2date(d,'%Y-%m-%d')) as dt, " +
+                    " bitmap_union(to_bitmap(t1.c))\n" +
+                    " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                    " group by a, b, d;");
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by dt " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select * from view1");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by dt " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select * from view1");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('2023-08-01') " +
-                "end ('2023-08-02') force with sync mode");
+                    "end ('2023-08-02') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p202308_202309"), partitions);
 
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("force");
         {
             String query = "select " +
-                    " a, b, date_trunc('month', str2date(d,'%Y-%m-%d')) as dt, " +
-                    " count(distinct t1.c)\n" +
-                    " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " where date_trunc('month', str2date(d,'%Y-%m-%d')) ='2023-08-01'" +
-                    " group by a, b, dt;";
+                        " a, b, date_trunc('month', str2date(d,'%Y-%m-%d')) as dt, " +
+                        " count(distinct t1.c)\n" +
+                        " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " where date_trunc('month', str2date(d,'%Y-%m-%d')) ='2023-08-01'" +
+                        " group by a, b, dt;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, "UNION");
             UtFrameUtils.matchPlanWithoutId(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 9: dt = '2023-08-01'\n" +
-                    "     partitions=1/1\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 9: dt = '2023-08-01'\n" +
+                        "     partitions=1/1\n" +
+                        "     rollup: test_mv1");
         }
 
         // TODO: Support date_trunc('day', str2date(t1.d, ''%Y-%m-%d'')) to str2date(d, '%Y-%m-%d')
         {
             String query = "select a, b, d, count(distinct t1.c)\n" +
-                    " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
-                    " where t1.d >= '2023-08-01' \n" +
-                    " group by a, b, d;";
+                        " from iceberg0.partitioned_db.part_tbl1 as t1 \n" +
+                        " where t1.d >= '2023-08-01' \n" +
+                        " group by a, b, d;";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, mvName);
         }
@@ -1998,26 +2016,26 @@ public void testStr2DateMVRefreshRewriteSingleTableWithDateTruc_Month() throws E
     public void testViewBasedRewrite() throws Exception {
         connectContext.getSessionVariable().setEnableViewBasedMvRewrite(true);
         String view = "create view iceberg_table_view " +
-                " as select t1.a, t2.b, t1.d, count(t1.c) as cnt" +
-                " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
-                " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                " group by t1.a, t2.b, t1.d;";
+                    " as select t1.a, t2.b, t1.d, count(t1.c) as cnt" +
+                    " from  iceberg0.partitioned_db.part_tbl1 as t1 " +
+                    " inner join iceberg0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " inner join iceberg0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                    " group by t1.a, t2.b, t1.d;";
         starRocksAssert.withView(view);
         String mvName = "iceberg_mv_1";
         String mv = "create materialized view iceberg_mv_1 " +
-                "partition by str2date(d,'%Y-%m-%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as " +
-                "select a, b, d, cnt " +
-                "from iceberg_table_view";
+                    "partition by str2date(d,'%Y-%m-%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as " +
+                    "select a, b, d, cnt " +
+                    "from iceberg_table_view";
         starRocksAssert.withMaterializedView(mv);
         starRocksAssert.getCtx().executeSql("refresh materialized view iceberg_mv_1" +
-                " partition start('2023-08-01') end('2023-08-02') with sync mode");
+                    " partition start('2023-08-01') end('2023-08-02') with sync mode");
 
         {
             String query = "select a, b, d, cnt from iceberg_table_view";
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRefreshAndRewriteJDBCTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRefreshAndRewriteJDBCTest.java
index aad6b687924b91..57209b0b56fd78 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRefreshAndRewriteJDBCTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRefreshAndRewriteJDBCTest.java
@@ -41,7 +41,7 @@ public static void beforeClass() throws Exception {
         ConnectorPlanTestBase.mockCatalog(connectContext, MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME);
         MockedMetadataMgr metadataMgr = (MockedMetadataMgr) connectContext.getGlobalStateMgr().getMetadataMgr();
         MockedJDBCMetadata mockedJDBCMetadata =
-                (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
+                    (MockedJDBCMetadata) metadataMgr.getOptionalMetadata(MockedJDBCMetadata.MOCKED_JDBC_CATALOG_NAME).get();
         mockedJDBCMetadata.initPartitions();
     }
 
@@ -49,69 +49,70 @@ public static void beforeClass() throws Exception {
     public void testStr2DateMVRefreshRewrite_InnerJoin_FullRefresh() throws Exception {
         String mvName = "test_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y%m%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'," +
-                "'query_rewrite_consistency' = 'loose'" +
-                ") " +
-                "as select  t1.a, t2.b, t3.c, t1.d " +
-                " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
-                " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
-                " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d ;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y%m%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'," +
+                    "'query_rewrite_consistency' = 'loose'" +
+                    ") " +
+                    "as select  t1.a, t2.b, t3.c, t1.d " +
+                    " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
+                    " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
+                    " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d ;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p00010101_20230801", "p20230801_20230802",
-                "p20230802_20230803", "p20230803_99991231"), partitions);
+                    "p20230802_20230803", "p20230803_99991231"), partitions);
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
-                    " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='20230801';";
+                        " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
+                        " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='20230801';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 16: d = '20230801'\n" +
-                    "     partitions=1/4");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 16: d = '20230801'\n" +
+                        "     partitions=1/4");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
-                    " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='20230801';";
+                        " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
+                        " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='20230801';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 16: d >= '20230801'\n" +
-                    "     partitions=3/4\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 16: d >= '20230801'\n" +
+                        "     partitions=3/4\n" +
+                        "     rollup: test_mv1");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
-                    " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d < '20230802';";
+                        " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
+                        " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d < '20230802';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv1\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=2/4\n" +
-                    "     rollup: test_mv1");
+                        "     TABLE: test_mv1\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=2/4\n" +
+                        "     rollup: test_mv1");
         }
 
         starRocksAssert.dropMaterializedView(mvName);
@@ -121,34 +122,35 @@ public void testStr2DateMVRefreshRewrite_InnerJoin_FullRefresh() throws Exceptio
     public void testStr2DateMVRefreshRewrite_InnerJoin_PartialRefresh() throws Exception {
         String mvName = "test_mv2";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y%m%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "\"query_rewrite_consistency\" = \"disable\",\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select  t1.a, t2.b, t3.c, t1.d " +
-                " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
-                " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
-                " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d ;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y%m%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "\"query_rewrite_consistency\" = \"disable\",\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select  t1.a, t2.b, t3.c, t1.d " +
+                    " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
+                    " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
+                    " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d ;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('20230801') " +
-                "end ('20230802') force with sync mode");
+                    "end ('20230802') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802"), partitions);
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
-                    " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='20230801';";
+                        " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
+                        " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='20230801';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, "test_mv2");
         }
@@ -156,74 +158,74 @@ public void testStr2DateMVRefreshRewrite_InnerJoin_PartialRefresh() throws Excep
         starRocksAssert.dropMaterializedView(mvName);
     }
 
-
     @Test
     public void testStr2DateMVRefreshRewrite_LeftJoin_FullRefresh() throws Exception {
         String mvName = "test_mv3";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y%m%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "'replication_num' = '1'," +
-                "'query_rewrite_consistency' = 'loose'" +
-                ") " +
-                "as select  t1.a, t2.b, t3.c, t1.d " +
-                " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
-                " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
-                " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d ;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y%m%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "'replication_num' = '1'," +
+                    "'query_rewrite_consistency' = 'loose'" +
+                    ") " +
+                    "as select  t1.a, t2.b, t3.c, t1.d " +
+                    " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
+                    " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
+                    " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d ;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p00010101_20230801", "p20230801_20230802", "p20230802_20230803",
-                "p20230803_99991231"), partitions);
+                    "p20230803_99991231"), partitions);
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
-                    " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='20230801';";
+                        " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
+                        " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='20230801';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv3\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 16: d = '20230801'\n" +
-                    "     partitions=1/4");
+                        "     TABLE: test_mv3\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 16: d = '20230801'\n" +
+                        "     partitions=1/4");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
-                    " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d>='20230801';";
+                        " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
+                        " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d>='20230801';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv3\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 16: d >= '20230801'\n" +
-                    "     partitions=3/4\n" +
-                    "     rollup: test_mv3");
+                        "     TABLE: test_mv3\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     PREDICATES: 16: d >= '20230801'\n" +
+                        "     partitions=3/4\n" +
+                        "     rollup: test_mv3");
         }
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
-                    " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d < '20230802';";
+                        " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
+                        " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d < '20230802';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertContains(plan, "0:OlapScanNode\n" +
-                    "     TABLE: test_mv3\n" +
-                    "     PREAGGREGATION: ON\n" +
-                    "     partitions=2/4\n" +
-                    "     rollup: test_mv3");
+                        "     TABLE: test_mv3\n" +
+                        "     PREAGGREGATION: ON\n" +
+                        "     partitions=2/4\n" +
+                        "     rollup: test_mv3");
         }
 
         starRocksAssert.dropMaterializedView(mvName);
@@ -233,34 +235,35 @@ public void testStr2DateMVRefreshRewrite_LeftJoin_FullRefresh() throws Exception
     public void testStr2DateMVRefreshRewrite_LeftJoin_PartialRefresh() throws Exception {
         String mvName = "test_mv4";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y%m%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "\"query_rewrite_consistency\" = \"disable\",\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                "as select  t1.a, t2.b, t3.c, t1.d " +
-                " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
-                " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
-                " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d ;");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-        MaterializedView materializedView = ((MaterializedView) testDb.getTable(mvName));
+                    "partition by str2date(d,'%Y%m%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "\"query_rewrite_consistency\" = \"disable\",\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    "as select  t1.a, t2.b, t3.c, t1.d " +
+                    " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
+                    " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
+                    " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d ;");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        MaterializedView materializedView = ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                    .getTable(testDb.getFullName(), mvName));
 
         // initial create
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " partition start('20230801') " +
-                "end ('20230802') force with sync mode");
+                    "end ('20230802') force with sync mode");
         List<String> partitions =
-                materializedView.getPartitions().stream().map(Partition::getName).sorted()
-                        .collect(Collectors.toList());
+                    materializedView.getPartitions().stream().map(Partition::getName).sorted()
+                                .collect(Collectors.toList());
         Assert.assertEquals(Arrays.asList("p20230801_20230802"), partitions);
 
         {
             String query = "select  t1.a, t2.b, t3.c, t1.d " +
-                    " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
-                    " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
-                    " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
-                    " where t1.d='20230801';";
+                        " from  jdbc0.partitioned_db0.part_tbl1 as t1 " +
+                        " inner join jdbc0.partitioned_db0.part_tbl2 t2 on t1.d=t2.d " +
+                        " inner join jdbc0.partitioned_db0.part_tbl3 t3 on t1.d=t3.d " +
+                        " where t1.d='20230801';";
             String plan = getFragmentPlan(query);
             PlanTestBase.assertNotContains(plan, "test_mv4");
         }
@@ -271,24 +274,24 @@ public void testStr2DateMVRefreshRewrite_LeftJoin_PartialRefresh() throws Except
     @Test
     public void testViewBasedMvRewriteOnJdbcTable() throws Exception {
         String view = "create view jdbc_table_view " +
-                " as select t1.a, t2.b, t1.d, count(t1.c) as cnt" +
-                " from  jdbc0.partitioned_db.part_tbl1 as t1 " +
-                " inner join jdbc0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
-                " inner join jdbc0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
-                " group by t1.a, t2.b, t1.d;";
+                    " as select t1.a, t2.b, t1.d, count(t1.c) as cnt" +
+                    " from  jdbc0.partitioned_db.part_tbl1 as t1 " +
+                    " inner join jdbc0.partitioned_db.part_tbl2 t2 on t1.d=t2.d " +
+                    " inner join jdbc0.partitioned_db.part_tbl3 t3 on t1.d=t3.d " +
+                    " group by t1.a, t2.b, t1.d;";
         starRocksAssert.withView(view);
         String mvName = "jdbc_view_mv1";
         starRocksAssert.withMaterializedView("create materialized view " + mvName + " " +
-                "partition by str2date(d,'%Y%m%d') " +
-                "distributed by hash(a) " +
-                "REFRESH DEFERRED MANUAL " +
-                "PROPERTIES (\n" +
-                "\"query_rewrite_consistency\" = \"loose\",\n" +
-                "'replication_num' = '1'" +
-                ") " +
-                " as select a, b, d, cnt" +
-                " from jdbc_table_view");
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+                    "partition by str2date(d,'%Y%m%d') " +
+                    "distributed by hash(a) " +
+                    "REFRESH DEFERRED MANUAL " +
+                    "PROPERTIES (\n" +
+                    "\"query_rewrite_consistency\" = \"loose\",\n" +
+                    "'replication_num' = '1'" +
+                    ") " +
+                    " as select a, b, d, cnt" +
+                    " from jdbc_table_view");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         starRocksAssert.getCtx().executeSql("refresh materialized view " + mvName + " with sync mode");
 
         {
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRefreshTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRefreshTest.java
index 0d60bc2a927cb3..af21791c251cbb 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRefreshTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRefreshTest.java
@@ -31,7 +31,7 @@
 import org.junit.BeforeClass;
 import org.junit.Test;
 
-public class MvRefreshTest extends MVRefreshTestBase  {
+public class MvRefreshTest extends MVRefreshTestBase {
     @BeforeClass
     public static void beforeClass() throws Exception {
         PseudoCluster.getOrCreateWithRandomPort(true, 1);
@@ -45,143 +45,149 @@ public static void beforeClass() throws Exception {
     @Test
     public void testMvWithComplexNameRefresh() throws Exception {
         createAndRefreshMv("create materialized view `cc`" +
-                " partition by id_date" +
-                " distributed by hash(`t1a`)" +
-                " as" +
-                " select t1a, id_date, t1b from table_with_partition");
+                    " partition by id_date" +
+                    " distributed by hash(`t1a`)" +
+                    " as" +
+                    " select t1a, id_date, t1b from table_with_partition");
 
         createAndRefreshMv("create materialized view `luchen_order_8e2c65ba_1c30`" +
-                " partition by id_date" +
-                " distributed by hash(`t1a`)" +
-                " as" +
-                " select t1a, id_date, t1b from table_with_partition");
+                    " partition by id_date" +
+                    " distributed by hash(`t1a`)" +
+                    " as" +
+                    " select t1a, id_date, t1b from table_with_partition");
     }
 
     @Test
     public void testMVRefreshWithQueryRewrite1() throws Exception {
         createAndRefreshMv("create materialized view `test_mv1` \n" +
-                " partition by id_date\n" +
-                " distributed by hash(`t1a`)\n" +
-                " refresh deferred manual \n" +
-                " as\n" +
-                " select t1a, id_date, t1b, sum(t1c) as sum1 from table_with_partition group by t1a, id_date, t1b");
+                    " partition by id_date\n" +
+                    " distributed by hash(`t1a`)\n" +
+                    " refresh deferred manual \n" +
+                    " as\n" +
+                    " select t1a, id_date, t1b, sum(t1c) as sum1 from table_with_partition group by t1a, id_date, t1b");
         starRocksAssert.withMaterializedView("create materialized view `test_mv2` \n" +
-                        " partition by id_date\n" +
-                        " distributed by hash(`t1a`)\n" +
-                        " refresh deferred manual \n" +
-                        " as\n" +
-                        " select t1a, id_date, sum(t1c) as sum1 from table_with_partition group by t1a, id_date",
-                () -> {
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("test_mv2"));
-                    Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
-                    TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
+                                " partition by id_date\n" +
+                                " distributed by hash(`t1a`)\n" +
+                                " refresh deferred manual \n" +
+                                " as\n" +
+                                " select t1a, id_date, sum(t1c) as sum1 from table_with_partition group by t1a, id_date",
+                    () -> {
+                        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+                        MaterializedView materializedView =
+                                    ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                .getTable(testDb.getFullName(), "test_mv2"));
+                        Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
+                        TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
 
-                    // If the base table has been refreshed and test_mv1 has been refreshed, test_mv2 refresh can use
-                    // test_mv1.
-                    {
-                        ExecPlan execPlan = getMVRefreshExecPlan(taskRun);
-                        Assert.assertNotNull("exec plan should not null", execPlan);
-                        String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                        PlanTestBase.assertContains(plan, "test_mv1");
-                    }
+                        // If the base table has been refreshed and test_mv1 has been refreshed, test_mv2 refresh can use
+                        // test_mv1.
+                        {
+                            ExecPlan execPlan = getMVRefreshExecPlan(taskRun);
+                            Assert.assertNotNull("exec plan should not null", execPlan);
+                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                            PlanTestBase.assertContains(plan, "test_mv1");
+                        }
 
-                    // If the base table has changed and test_mv1 has not been refreshed, test_mv2 refresh should
-                    // not use test_mv1.
-                    {
-                        executeInsertSql(connectContext, "insert into table_with_partition partition(p1991)" +
-                                " values(\"varchar12\", '1991-03-01', 2, 1, 1)");
-                        ExecPlan execPlan = getMVRefreshExecPlan(taskRun);
-                        Assert.assertNotNull("exec plan should not null", execPlan);
-                        String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                        PlanTestBase.assertNotContains(plan, "test_mv1");
-                    }
-                });
+                        // If the base table has changed and test_mv1 has not been refreshed, test_mv2 refresh should
+                        // not use test_mv1.
+                        {
+                            executeInsertSql(connectContext, "insert into table_with_partition partition(p1991)" +
+                                        " values(\"varchar12\", '1991-03-01', 2, 1, 1)");
+                            ExecPlan execPlan = getMVRefreshExecPlan(taskRun);
+                            Assert.assertNotNull("exec plan should not null", execPlan);
+                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                            PlanTestBase.assertNotContains(plan, "test_mv1");
+                        }
+                    });
         starRocksAssert.dropMaterializedView("test_mv1");
     }
 
     @Test
     public void testMVRefreshWithQueryRewrite2() throws Exception {
         createAndRefreshMv("create materialized view `test_mv1` \n" +
-                " partition by id_date\n" +
-                " distributed by hash(`t1a`)\n" +
-                " refresh deferred manual \n" +
-                " as\n" +
-                " select t1a, id_date, t1b, sum(t1c) as sum1 from table_with_partition group by t1a, id_date, t1b");
+                    " partition by id_date\n" +
+                    " distributed by hash(`t1a`)\n" +
+                    " refresh deferred manual \n" +
+                    " as\n" +
+                    " select t1a, id_date, t1b, sum(t1c) as sum1 from table_with_partition group by t1a, id_date, t1b");
         starRocksAssert.withMaterializedView("create materialized view `test_mv2` \n" +
-                        "partition by id_date\n" +
-                        "distributed by hash(`t1a`)\n" +
-                        "refresh deferred manual \n" +
-                        "PROPERTIES (\n" +
-                        "   'replication_num' = '1', \n" +
-                        "   'session.enable_materialized_view_rewrite' = 'false' \n" +
-                        ")\n" +
-                        " as\n" +
-                        " select t1a, id_date, sum(t1c) as sum1 from table_with_partition group by t1a, id_date",
-                () -> {
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("test_mv2"));
-                    Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
-                    TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
+                                "partition by id_date\n" +
+                                "distributed by hash(`t1a`)\n" +
+                                "refresh deferred manual \n" +
+                                "PROPERTIES (\n" +
+                                "   'replication_num' = '1', \n" +
+                                "   'session.enable_materialized_view_rewrite' = 'false' \n" +
+                                ")\n" +
+                                " as\n" +
+                                " select t1a, id_date, sum(t1c) as sum1 from table_with_partition group by t1a, id_date",
+                    () -> {
+                        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+                        MaterializedView materializedView =
+                                    ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                .getTable(testDb.getFullName(), "test_mv2"));
+                        Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
+                        TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
 
-                    // If the base table has been refreshed and test_mv1 has been refreshed, test_mv2 refresh can use
-                    // test_mv1.
-                    {
-                        ExecPlan execPlan = getMVRefreshExecPlan(taskRun);
-                        Assert.assertNotNull("exec plan should not null", execPlan);
-                        String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                        PlanTestBase.assertNotContains(plan, "test_mv1");
-                    }
-                });
+                        // If the base table has been refreshed and test_mv1 has been refreshed, test_mv2 refresh can use
+                        // test_mv1.
+                        {
+                            ExecPlan execPlan = getMVRefreshExecPlan(taskRun);
+                            Assert.assertNotNull("exec plan should not null", execPlan);
+                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                            PlanTestBase.assertNotContains(plan, "test_mv1");
+                        }
+                    });
         starRocksAssert.dropMaterializedView("test_mv1");
     }
 
     @Test
     public void testMVRefreshWithQueryRewrite3() throws Exception {
         createAndRefreshMv("create materialized view `test_mv1` \n" +
-                " partition by id_date\n" +
-                " distributed by hash(`t1a`)\n" +
-                " refresh deferred manual \n" +
-                " as\n" +
-                " select t1a, id_date, t1b, sum(t1c) as sum1 from table_with_partition group by t1a, id_date, t1b");
+                    " partition by id_date\n" +
+                    " distributed by hash(`t1a`)\n" +
+                    " refresh deferred manual \n" +
+                    " as\n" +
+                    " select t1a, id_date, t1b, sum(t1c) as sum1 from table_with_partition group by t1a, id_date, t1b");
         Config.enable_mv_refresh_query_rewrite = false;
         starRocksAssert.withMaterializedView("create materialized view `test_mv2` \n" +
-                        "partition by id_date\n" +
-                        "distributed by hash(`t1a`)\n" +
-                        "refresh deferred manual \n" +
-                        "PROPERTIES (\n" +
-                        "   'replication_num' = '1', \n" +
-                        "   'session.enable_materialized_view_rewrite' = 'true', \n" +
-                        "   'session.enable_materialized_view_for_insert' = 'true' \n" +
-                        ")\n" +
-                        " as\n" +
-                        " select t1a, id_date, sum(t1c) as sum1 from table_with_partition group by t1a, id_date",
-                () -> {
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-                    MaterializedView materializedView = ((MaterializedView) testDb.getTable("test_mv2"));
-                    Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
-                    TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
+                                "partition by id_date\n" +
+                                "distributed by hash(`t1a`)\n" +
+                                "refresh deferred manual \n" +
+                                "PROPERTIES (\n" +
+                                "   'replication_num' = '1', \n" +
+                                "   'session.enable_materialized_view_rewrite' = 'true', \n" +
+                                "   'session.enable_materialized_view_for_insert' = 'true' \n" +
+                                ")\n" +
+                                " as\n" +
+                                " select t1a, id_date, sum(t1c) as sum1 from table_with_partition group by t1a, id_date",
+                    () -> {
+                        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+                        MaterializedView materializedView =
+                                    ((MaterializedView) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                                .getTable(testDb.getFullName(), "test_mv2"));
+                        Task task = TaskBuilder.buildMvTask(materializedView, testDb.getFullName());
+                        TaskRun taskRun = TaskRunBuilder.newBuilder(task).build();
 
-                    // If the base table has been refreshed and test_mv1 has been refreshed, test_mv2 refresh can use
-                    // test_mv1.
-                    {
-                        ExecPlan execPlan = getMVRefreshExecPlan(taskRun);
-                        Assert.assertNotNull("exec plan should not null", execPlan);
-                        String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                        PlanTestBase.assertContains(plan, "test_mv1");
-                    }
+                        // If the base table has been refreshed and test_mv1 has been refreshed, test_mv2 refresh can use
+                        // test_mv1.
+                        {
+                            ExecPlan execPlan = getMVRefreshExecPlan(taskRun);
+                            Assert.assertNotNull("exec plan should not null", execPlan);
+                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                            PlanTestBase.assertContains(plan, "test_mv1");
+                        }
 
-                    // If the base table has changed and test_mv1 has not been refreshed, test_mv2 refresh should
-                    // not use test_mv1.
-                    {
-                        executeInsertSql(connectContext, "insert into table_with_partition partition(p1991)" +
-                                " values(\"varchar12\", '1991-03-01', 2, 1, 1)");
-                        ExecPlan execPlan = getMVRefreshExecPlan(taskRun);
-                        Assert.assertNotNull("exec plan should not null", execPlan);
-                        String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
-                        PlanTestBase.assertNotContains(plan, "test_mv1");
-                    }
-                });
+                        // If the base table has changed and test_mv1 has not been refreshed, test_mv2 refresh should
+                        // not use test_mv1.
+                        {
+                            executeInsertSql(connectContext, "insert into table_with_partition partition(p1991)" +
+                                        " values(\"varchar12\", '1991-03-01', 2, 1, 1)");
+                            ExecPlan execPlan = getMVRefreshExecPlan(taskRun);
+                            Assert.assertNotNull("exec plan should not null", execPlan);
+                            String plan = execPlan.getExplainString(TExplainLevel.NORMAL);
+                            PlanTestBase.assertNotContains(plan, "test_mv1");
+                        }
+                    });
         Config.enable_mv_refresh_query_rewrite = true;
         starRocksAssert.dropMaterializedView("test_mv1");
     }
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRewritePreprocessorTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRewritePreprocessorTest.java
index 373934a229ae80..155028ba6701ad 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRewritePreprocessorTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRewritePreprocessorTest.java
@@ -344,9 +344,9 @@ public void testChooseBestRelatedMVs1() {
                 // mv2 contains extra mvs.
                 Assert.assertTrue(containsMV(relatedMVs, "mv_1", "mv_2", "mv_3", "mv_4"));
 
-                Set<MaterializedView> validMVs = preprocessor.chooseBestRelatedMVs(queryTables, relatedMVs, logicalTree);
                 // disable plan cache will make the test more stable
                 connectContext.getSessionVariable().setEnableMaterializedViewPlanCache(false);
+                Set<MaterializedView> validMVs = preprocessor.chooseBestRelatedMVs(queryTables, relatedMVs, logicalTree);
                 Assert.assertEquals(2, validMVs.size());
                 Assert.assertTrue(containsMV(validMVs, "mv_1", "mv_3"));
                 connectContext.getSessionVariable().setEnableMaterializedViewPlanCache(true);
@@ -420,9 +420,9 @@ public void testChooseBestRelatedMVs2() {
                 // mv2 contains extra mvs.
                 Assert.assertTrue(containsMV(relatedMVs, "mv_1", "mv_2", "mv_3", "mv_4"));
 
-                Set<MaterializedView> validMVs = preprocessor.chooseBestRelatedMVs(queryTables, relatedMVs, logicalTree);
                 // disable plan cache will make the test more stable
                 connectContext.getSessionVariable().setEnableMaterializedViewPlanCache(false);
+                Set<MaterializedView> validMVs = preprocessor.chooseBestRelatedMVs(queryTables, relatedMVs, logicalTree);
                 Assert.assertEquals(2, validMVs.size());
                 Assert.assertTrue(containsMV(validMVs, "mv_1", "mv_3"));
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRewriteTestBase.java b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRewriteTestBase.java
index 0af6cf706d4c02..c4b69f01e20f67 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRewriteTestBase.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvRewriteTestBase.java
@@ -123,8 +123,8 @@ public String getFragmentPlan(String sql, TExplainLevel level, String traceModul
     }
 
     public static Table getTable(String dbName, String mvName) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
-        Table table = db.getTable(mvName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), mvName);
         Assert.assertNotNull(table);
         return table;
     }
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvUtilsTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvUtilsTest.java
index b14ff57e926839..4dc41e3fed07d7 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvUtilsTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/rule/transformation/materialization/MvUtilsTest.java
@@ -26,6 +26,7 @@
 import com.starrocks.common.AnalysisException;
 import com.starrocks.common.Config;
 import com.starrocks.qe.ConnectContext;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.optimizer.OptExpression;
 import com.starrocks.sql.optimizer.Utils;
 import com.starrocks.sql.optimizer.base.ColumnRefFactory;
@@ -100,14 +101,14 @@ public void testGetAllPredicate() {
         BinaryPredicateOperator binaryPredicate = new BinaryPredicateOperator(
                 BinaryType.EQ, columnRef1, columnRef2);
 
-        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getDb("test");
-        Table table1 = db.getTable("t0");
+        Database db = starRocksAssert.getCtx().getGlobalStateMgr().getLocalMetastore().getDb("test");
+        Table table1 = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t0");
         LogicalScanOperator scanOperator1 = new LogicalOlapScanOperator(table1);
         BinaryPredicateOperator binaryPredicate2 = new BinaryPredicateOperator(
                 BinaryType.GE, columnRef1, ConstantOperator.createInt(1));
         scanOperator1.setPredicate(binaryPredicate2);
         OptExpression scanExpr = OptExpression.create(scanOperator1);
-        Table table2 = db.getTable("t1");
+        Table table2 = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t1");
         LogicalScanOperator scanOperator2 = new LogicalOlapScanOperator(table2);
         BinaryPredicateOperator binaryPredicate3 = new BinaryPredicateOperator(
                 BinaryType.GE, columnRef2, ConstantOperator.createInt(1));
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/statistics/CachedStatisticStorageTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/statistics/CachedStatisticStorageTest.java
index 7ae8e209f4d310..080bdc5d7e39b1 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/statistics/CachedStatisticStorageTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/statistics/CachedStatisticStorageTest.java
@@ -127,8 +127,8 @@ public static void beforeClass() throws Exception {
 
     @Test
     public void testGetColumnStatistic(@Mocked CachedStatisticStorage cachedStatisticStorage) {
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("t0");
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t0");
 
         new Expectations() {
             {
@@ -160,8 +160,8 @@ public void testGetColumnStatistic(@Mocked CachedStatisticStorage cachedStatisti
 
     @Test
     public void testGetColumnStatistics(@Mocked CachedStatisticStorage cachedStatisticStorage) {
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("t0");
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t0");
 
         ColumnStatistic columnStatistic1 = ColumnStatistic.builder().setDistinctValuesCount(888).build();
         ColumnStatistic columnStatistic2 = ColumnStatistic.builder().setDistinctValuesCount(999).build();
@@ -367,8 +367,8 @@ public void testExpireConnectorHistogramStatistics() {
 
     @Test
     public void testLoadCacheLoadEmpty(@Mocked CachedStatisticStorage cachedStatisticStorage) {
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
-        Table table = db.getTable("t0");
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t0");
 
         new Expectations() {
             {
@@ -388,8 +388,8 @@ public void testLoadCacheLoadEmpty(@Mocked CachedStatisticStorage cachedStatisti
 
     @Test
     public void testConvert2ColumnStatistics() {
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("t0");
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t0");
         ColumnBasicStatsCacheLoader cachedStatisticStorage =
                 Deencapsulation.newInstance(ColumnBasicStatsCacheLoader.class);
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/statistics/StatisticsCalculatorTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/statistics/StatisticsCalculatorTest.java
index 657857d79b9ae9..7aa6087e3bfb23 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/statistics/StatisticsCalculatorTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/optimizer/statistics/StatisticsCalculatorTest.java
@@ -99,54 +99,54 @@ public static void beforeClass() throws Exception {
     @Before
     public void before() throws Exception {
         starRocksAssert.withTable("CREATE TABLE `test_all_type` (\n" +
-                "  `t1a` varchar(20) NULL COMMENT \"\",\n" +
-                "  `t1b` smallint(6) NULL COMMENT \"\",\n" +
-                "  `t1c` int(11) NULL COMMENT \"\",\n" +
-                "  `t1d` bigint(20) NULL COMMENT \"\",\n" +
-                "  `t1e` float NULL COMMENT \"\",\n" +
-                "  `t1f` double NULL COMMENT \"\",\n" +
-                "  `t1g` bigint(20) NULL COMMENT \"\",\n" +
-                "  `id_datetime` datetime NULL COMMENT \"\",\n" +
-                "  `id_date` date NULL COMMENT \"\", \n" +
-                "  `id_decimal` decimal(10,2) NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`t1a`)\n" +
-                "PARTITION BY RANGE (id_date)\n" +
-                "(\n" +
-                "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
-                "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"), \n" +
-                "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")  \n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`t1a`) BUCKETS 3\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"in_memory\" = \"false\"\n" +
-                ");");
+                    "  `t1a` varchar(20) NULL COMMENT \"\",\n" +
+                    "  `t1b` smallint(6) NULL COMMENT \"\",\n" +
+                    "  `t1c` int(11) NULL COMMENT \"\",\n" +
+                    "  `t1d` bigint(20) NULL COMMENT \"\",\n" +
+                    "  `t1e` float NULL COMMENT \"\",\n" +
+                    "  `t1f` double NULL COMMENT \"\",\n" +
+                    "  `t1g` bigint(20) NULL COMMENT \"\",\n" +
+                    "  `id_datetime` datetime NULL COMMENT \"\",\n" +
+                    "  `id_date` date NULL COMMENT \"\", \n" +
+                    "  `id_decimal` decimal(10,2) NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`t1a`)\n" +
+                    "PARTITION BY RANGE (id_date)\n" +
+                    "(\n" +
+                    "PARTITION p1 VALUES LESS THAN (\"2014-01-01\"),\n" +
+                    "PARTITION p2 VALUES LESS THAN (\"2014-06-01\"), \n" +
+                    "PARTITION p3 VALUES LESS THAN (\"2014-12-01\")  \n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`t1a`) BUCKETS 3\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"in_memory\" = \"false\"\n" +
+                    ");");
 
         starRocksAssert.withTable("CREATE TABLE `test_all_type_day_partition` (\n" +
-                "  `t1a` varchar(20) NULL COMMENT \"\",\n" +
-                "  `t1b` smallint(6) NULL COMMENT \"\",\n" +
-                "  `t1c` int(11) NULL COMMENT \"\",\n" +
-                "  `t1d` bigint(20) NULL COMMENT \"\",\n" +
-                "  `t1e` float NULL COMMENT \"\",\n" +
-                "  `t1f` double NULL COMMENT \"\",\n" +
-                "  `t1g` bigint(20) NULL COMMENT \"\",\n" +
-                "  `id_datetime` datetime NULL COMMENT \"\",\n" +
-                "  `id_date` date NULL COMMENT \"\", \n" +
-                "  `id_decimal` decimal(10,2) NULL COMMENT \"\"\n" +
-                ") ENGINE=OLAP\n" +
-                "DUPLICATE KEY(`t1a`)\n" +
-                "PARTITION BY RANGE (id_date)\n" +
-                "(\n" +
-                "partition p1 values [('2020-04-23'), ('2020-04-24')),\n" +
-                "partition p2 values [('2020-04-24'), ('2020-04-25')),\n" +
-                "partition p3 values [('2020-04-25'), ('2020-04-26')) \n" +
-                ")\n" +
-                "DISTRIBUTED BY HASH(`t1a`) BUCKETS 3\n" +
-                "PROPERTIES (\n" +
-                "\"replication_num\" = \"1\",\n" +
-                "\"in_memory\" = \"false\"\n" +
-                ");");
+                    "  `t1a` varchar(20) NULL COMMENT \"\",\n" +
+                    "  `t1b` smallint(6) NULL COMMENT \"\",\n" +
+                    "  `t1c` int(11) NULL COMMENT \"\",\n" +
+                    "  `t1d` bigint(20) NULL COMMENT \"\",\n" +
+                    "  `t1e` float NULL COMMENT \"\",\n" +
+                    "  `t1f` double NULL COMMENT \"\",\n" +
+                    "  `t1g` bigint(20) NULL COMMENT \"\",\n" +
+                    "  `id_datetime` datetime NULL COMMENT \"\",\n" +
+                    "  `id_date` date NULL COMMENT \"\", \n" +
+                    "  `id_decimal` decimal(10,2) NULL COMMENT \"\"\n" +
+                    ") ENGINE=OLAP\n" +
+                    "DUPLICATE KEY(`t1a`)\n" +
+                    "PARTITION BY RANGE (id_date)\n" +
+                    "(\n" +
+                    "partition p1 values [('2020-04-23'), ('2020-04-24')),\n" +
+                    "partition p2 values [('2020-04-24'), ('2020-04-25')),\n" +
+                    "partition p3 values [('2020-04-25'), ('2020-04-26')) \n" +
+                    ")\n" +
+                    "DISTRIBUTED BY HASH(`t1a`) BUCKETS 3\n" +
+                    "PROPERTIES (\n" +
+                    "\"replication_num\" = \"1\",\n" +
+                    "\"in_memory\" = \"false\"\n" +
+                    ");");
     }
 
     @After
@@ -176,7 +176,7 @@ public void testLogicalAggregationRowCount() throws Exception {
         groupExpression.setGroup(new Group(1));
         ExpressionContext expressionContext = new ExpressionContext(groupExpression);
         StatisticsCalculator statisticsCalculator = new StatisticsCalculator(expressionContext,
-                columnRefFactory, optimizerContext);
+                    columnRefFactory, optimizerContext);
         statisticsCalculator.estimatorStats();
         Assert.assertEquals(50, expressionContext.getStatistics().getOutputRowCount(), 0.001);
 
@@ -186,11 +186,11 @@ public void testLogicalAggregationRowCount() throws Exception {
         groupExpression.setGroup(new Group(1));
         expressionContext = new ExpressionContext(groupExpression);
         statisticsCalculator = new StatisticsCalculator(expressionContext,
-                columnRefFactory, optimizerContext);
+                    columnRefFactory, optimizerContext);
         statisticsCalculator.estimatorStats();
         Assert.assertEquals(
-                50 * 50 * Math.pow(StatisticsEstimateCoefficient.UNKNOWN_GROUP_BY_CORRELATION_COEFFICIENT, 2),
-                expressionContext.getStatistics().getOutputRowCount(), 0.001);
+                    50 * 50 * Math.pow(StatisticsEstimateCoefficient.UNKNOWN_GROUP_BY_CORRELATION_COEFFICIENT, 2),
+                    expressionContext.getStatistics().getOutputRowCount(), 0.001);
     }
 
     @Test
@@ -220,13 +220,13 @@ public void testLogicalUnion() throws Exception {
         childGroup2.setStatistics(childBuilder2.build());
         // construct group expression
         LogicalUnionOperator unionOperator = new LogicalUnionOperator(Lists.newArrayList(v5, v6),
-                Lists.newArrayList(Lists.newArrayList(v1, v2), Lists.newArrayList(v3, v4)), true);
+                    Lists.newArrayList(Lists.newArrayList(v1, v2), Lists.newArrayList(v3, v4)), true);
         GroupExpression groupExpression =
-                new GroupExpression(unionOperator, Lists.newArrayList(childGroup1, childGroup2));
+                    new GroupExpression(unionOperator, Lists.newArrayList(childGroup1, childGroup2));
         groupExpression.setGroup(new Group(2));
         ExpressionContext expressionContext = new ExpressionContext(groupExpression);
         StatisticsCalculator statisticsCalculator = new StatisticsCalculator(expressionContext,
-                columnRefFactory, optimizerContext);
+                    columnRefFactory, optimizerContext);
         statisticsCalculator.estimatorStats();
 
         ColumnStatistic columnStatisticV5 = expressionContext.getStatistics().getColumnStatistic(v5);
@@ -239,10 +239,10 @@ public void testLogicalUnion() throws Exception {
     @Test
     public void testLogicalOlapTableScan() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable table = (OlapTable) globalStateMgr.getDb("statistics_test").getTable("test_all_type");
+        OlapTable table = (OlapTable) globalStateMgr.getLocalMetastore().getDb("statistics_test").getTable("test_all_type");
         Collection<Partition> partitions = table.getPartitions();
         List<Long> partitionIds =
-                partitions.stream().mapToLong(partition -> partition.getId()).boxed().collect(Collectors.toList());
+                    partitions.stream().mapToLong(partition -> partition.getId()).boxed().collect(Collectors.toList());
         for (Partition partition : partitions) {
             partition.getBaseIndex().setRowCount(1000);
         }
@@ -257,32 +257,32 @@ public void testLogicalOlapTableScan() throws Exception {
             columnToRef.put(column, ref);
 
             LogicalOlapScanOperator olapScanOperator = new LogicalOlapScanOperator(table,
-                    refToColumn, columnToRef,
-                    null, -1, null,
-                    ((OlapTable) table).getBaseIndexId(),
-                    partitionIds,
-                    null,
-                    false,
-                    Lists.newArrayList(),
-                    Lists.newArrayList(),
-                    Lists.newArrayList(),
-                    false);
+                        refToColumn, columnToRef,
+                        null, -1, null,
+                        ((OlapTable) table).getBaseIndexId(),
+                        partitionIds,
+                        null,
+                        false,
+                        Lists.newArrayList(),
+                        Lists.newArrayList(),
+                        Lists.newArrayList(),
+                        false);
 
             GroupExpression groupExpression = new GroupExpression(olapScanOperator, Lists.newArrayList());
             groupExpression.setGroup(new Group(0));
             ExpressionContext expressionContext = new ExpressionContext(groupExpression);
             Statistics.Builder builder = Statistics.builder();
             olapScanOperator.getOutputColumns().forEach(col ->
-                    builder.addColumnStatistic(col,
-                            new ColumnStatistic(-100, 100, 0.0, 5.0, 10))
+                        builder.addColumnStatistic(col,
+                                    new ColumnStatistic(-100, 100, 0.0, 5.0, 10))
             );
             expressionContext.setStatistics(builder.build());
             StatisticsCalculator statisticsCalculator = new StatisticsCalculator(expressionContext,
-                    columnRefFactory, optimizerContext);
+                        columnRefFactory, optimizerContext);
             statisticsCalculator.estimatorStats();
             Assert.assertEquals(1000 * partitions.size(), expressionContext.getStatistics().getOutputRowCount(), 0.001);
             Assert.assertEquals(ref.getType().getTypeSize() * 1000 * partitions.size(),
-                    expressionContext.getStatistics().getComputeSize(), 0.001);
+                        expressionContext.getStatistics().getComputeSize(), 0.001);
         }
     }
 
@@ -306,9 +306,9 @@ public void testLogicalIcebergTableScan() {
         }
 
         BinaryPredicateOperator predicateOperator = new BinaryPredicateOperator(BinaryType.LT,
-                partitionColumn, ConstantOperator.createInt(50));
+                    partitionColumn, ConstantOperator.createInt(50));
         LogicalIcebergScanOperator icebergScanOperator = new LogicalIcebergScanOperator(icebergTable, refToColumn,
-                columnToRef, -1, predicateOperator, TableVersionRange.empty());
+                    columnToRef, -1, predicateOperator, TableVersionRange.empty());
 
         GroupExpression groupExpression = new GroupExpression(icebergScanOperator, Lists.newArrayList());
         groupExpression.setGroup(new Group(0));
@@ -317,22 +317,22 @@ public void testLogicalIcebergTableScan() {
         new MockUp<MetadataMgr>() {
             @Mock
             public Statistics getTableStatisticsFromInternalStatistics(Table table, Map<ColumnRefOperator,
-                    Column> columns) {
+                        Column> columns) {
                 Statistics.Builder builder = Statistics.builder();
                 icebergScanOperator.getOutputColumns().forEach(col ->
-                        builder.addColumnStatistic(col,
-                                new ColumnStatistic(0, 100, 0.0, 5.0, 100))
+                            builder.addColumnStatistic(col,
+                                        new ColumnStatistic(0, 100, 0.0, 5.0, 100))
                 );
                 builder.setOutputRowCount(100);
                 return builder.build();
             }
         };
         StatisticsCalculator statisticsCalculator = new StatisticsCalculator(expressionContext,
-                columnRefFactory, optimizerContext);
+                    columnRefFactory, optimizerContext);
         statisticsCalculator.estimatorStats();
         Assert.assertEquals(50, expressionContext.getStatistics().getOutputRowCount(), 0.001);
         Assert.assertEquals(50, expressionContext.getStatistics().
-                getColumnStatistic(partitionColumn).getMaxValue(), 0.001);
+                    getColumnStatistic(partitionColumn).getMaxValue(), 0.001);
         Assert.assertTrue(optimizerContext.isObtainedFromInternalStatistics());
         optimizerContext.setObtainedFromInternalStatistics(false);
     }
@@ -341,7 +341,7 @@ public Statistics getTableStatisticsFromInternalStatistics(Table table, Map<Colu
     public void testLogicalOlapTableEmptyPartition(@Mocked CachedStatisticStorage cachedStatisticStorage) {
         ColumnRefOperator idDate = columnRefFactory.create("id_date", Type.DATE, true);
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        Table table = globalStateMgr.getDb("statistics_test").getTable("test_all_type");
+        Table table = globalStateMgr.getLocalMetastore().getDb("statistics_test").getTable("test_all_type");
 
         List<Partition> partitions = new ArrayList<>(((OlapTable) table).getPartitions());
 
@@ -353,41 +353,41 @@ public void testLogicalOlapTableEmptyPartition(@Mocked CachedStatisticStorage ca
         partition2.setVisibleVersion(2, System.currentTimeMillis());
         partition3.setVisibleVersion(2, System.currentTimeMillis());
         List<Long> partitionIds = partitions.stream().filter(partition -> !(partition.getName().equalsIgnoreCase("p1"))).
-                mapToLong(Partition::getId).boxed().collect(Collectors.toList());
+                    mapToLong(Partition::getId).boxed().collect(Collectors.toList());
 
         new Expectations() {
             {
                 cachedStatisticStorage.getColumnStatistics(table, Lists.newArrayList("id_date"));
                 result = new ColumnStatistic(0, Utils.getLongFromDateTime(LocalDateTime.of(2014, 12, 01, 0, 0, 0)),
-                        0, 0, 30);
+                            0, 0, 30);
                 minTimes = 0;
 
                 cachedStatisticStorage.getColumnStatistic(table, "id_date");
                 result = new ColumnStatistic(0, Utils.getLongFromDateTime(LocalDateTime.of(2014, 12, 01, 0, 0, 0)),
-                        0, 0, 30);
+                            0, 0, 30);
                 minTimes = 0;
             }
         };
 
         LogicalOlapScanOperator olapScanOperator =
-                new LogicalOlapScanOperator(table,
-                        ImmutableMap.of(idDate, new Column("id_date", Type.DATE, true)),
-                        ImmutableMap.of(new Column("id_date", Type.DATE, true), idDate),
-                        null, -1, null,
-                        ((OlapTable) table).getBaseIndexId(),
-                        partitionIds,
-                        null,
-                        false,
-                        Lists.newArrayList(),
-                        Lists.newArrayList(),
-                        Lists.newArrayList(),
-                        false);
+                    new LogicalOlapScanOperator(table,
+                                ImmutableMap.of(idDate, new Column("id_date", Type.DATE, true)),
+                                ImmutableMap.of(new Column("id_date", Type.DATE, true), idDate),
+                                null, -1, null,
+                                ((OlapTable) table).getBaseIndexId(),
+                                partitionIds,
+                                null,
+                                false,
+                                Lists.newArrayList(),
+                                Lists.newArrayList(),
+                                Lists.newArrayList(),
+                                false);
 
         GroupExpression groupExpression = new GroupExpression(olapScanOperator, Lists.newArrayList());
         groupExpression.setGroup(new Group(0));
         ExpressionContext expressionContext = new ExpressionContext(groupExpression);
         StatisticsCalculator statisticsCalculator = new StatisticsCalculator(expressionContext,
-                columnRefFactory, optimizerContext);
+                    columnRefFactory, optimizerContext);
         statisticsCalculator.estimatorStats();
         ColumnStatistic columnStatistic = expressionContext.getStatistics().getColumnStatistic(idDate);
         Assert.assertEquals(30, columnStatistic.getDistinctValuesCount(), 0.001);
@@ -396,23 +396,23 @@ public void testLogicalOlapTableEmptyPartition(@Mocked CachedStatisticStorage ca
 
     @Test
     public void testLogicalOlapTableScanPartitionPrune1(@Mocked CachedStatisticStorage cachedStatisticStorage)
-            throws Exception {
+                throws Exception {
         FeConstants.runningUnitTest = true;
         ColumnRefOperator idDate = columnRefFactory.create("id_date", Type.DATE, true);
 
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        Table table = globalStateMgr.getDb("statistics_test").getTable("test_all_type");
+        Table table = globalStateMgr.getLocalMetastore().getDb("statistics_test").getTable("test_all_type");
 
         new Expectations() {
             {
                 cachedStatisticStorage.getColumnStatistics(table, Lists.newArrayList("id_date"));
                 result = new ColumnStatistic(0, Utils.getLongFromDateTime(LocalDateTime.of(2014, 12, 01, 0, 0, 0)),
-                        0, 0, 30);
+                            0, 0, 30);
                 minTimes = 0;
 
                 cachedStatisticStorage.getColumnStatistic(table, "id_date");
                 result = new ColumnStatistic(0, Utils.getLongFromDateTime(LocalDateTime.of(2014, 12, 01, 0, 0, 0)),
-                        0, 0, 30);
+                            0, 0, 30);
                 minTimes = 0;
             }
         };
@@ -420,95 +420,96 @@ public void testLogicalOlapTableScanPartitionPrune1(@Mocked CachedStatisticStora
         Collection<Partition> partitions = ((OlapTable) table).getPartitions();
         // select partition p1
         List<Long> partitionIds = partitions.stream().filter(partition -> partition.getName().equalsIgnoreCase("p1")).
-                mapToLong(Partition::getId).boxed().collect(Collectors.toList());
+                    mapToLong(Partition::getId).boxed().collect(Collectors.toList());
         for (Partition partition : partitions) {
             partition.getBaseIndex().setRowCount(1000);
         }
 
         LogicalOlapScanOperator olapScanOperator =
-                new LogicalOlapScanOperator(table,
-                        ImmutableMap.of(idDate, new Column("id_date", Type.DATE, true)),
-                        ImmutableMap.of(new Column("id_date", Type.DATE, true), idDate),
-                        null, -1,
-                        new BinaryPredicateOperator(BinaryType.EQ,
-                                idDate, ConstantOperator.createDate(LocalDateTime.of(2013, 12, 30, 0, 0, 0))),
-                        ((OlapTable) table).getBaseIndexId(),
-                        partitionIds,
-                        null,
-                        false,
-                        Lists.newArrayList(),
-                        Lists.newArrayList(),
-                        Lists.newArrayList(),
-                        false);
+                    new LogicalOlapScanOperator(table,
+                                ImmutableMap.of(idDate, new Column("id_date", Type.DATE, true)),
+                                ImmutableMap.of(new Column("id_date", Type.DATE, true), idDate),
+                                null, -1,
+                                new BinaryPredicateOperator(BinaryType.EQ,
+                                            idDate, ConstantOperator.createDate(LocalDateTime.of(2013, 12, 30, 0, 0, 0))),
+                                ((OlapTable) table).getBaseIndexId(),
+                                partitionIds,
+                                null,
+                                false,
+                                Lists.newArrayList(),
+                                Lists.newArrayList(),
+                                Lists.newArrayList(),
+                                false);
 
         GroupExpression groupExpression = new GroupExpression(olapScanOperator, Lists.newArrayList());
         groupExpression.setGroup(new Group(0));
         ExpressionContext expressionContext = new ExpressionContext(groupExpression);
         StatisticsCalculator statisticsCalculator = new StatisticsCalculator(expressionContext,
-                columnRefFactory, optimizerContext);
+                    columnRefFactory, optimizerContext);
         statisticsCalculator.estimatorStats();
         // partition column count distinct values is 30 in table level, after partition prune,
         // the column statistic distinct values is 10, so the estimate row count is 1000 * (1/10)
         Assert.assertEquals(100, expressionContext.getStatistics().getOutputRowCount(), 0.001);
         ColumnStatistic columnStatistic = expressionContext.getStatistics().getColumnStatistic(idDate);
         Assert.assertEquals(Utils.getLongFromDateTime(LocalDateTime.of(2013, 12, 30, 0, 0, 0)),
-                columnStatistic.getMaxValue(), 0.001);
+                    columnStatistic.getMaxValue(), 0.001);
 
         // select partition p2, p3
         partitionIds.clear();
         partitionIds = partitions.stream().filter(partition -> !(partition.getName().equalsIgnoreCase("p1"))).
-                mapToLong(Partition::getId).boxed().collect(Collectors.toList());
+                    mapToLong(Partition::getId).boxed().collect(Collectors.toList());
         olapScanOperator =
-                new LogicalOlapScanOperator(table,
-                        ImmutableMap.of(idDate, new Column("id_date", Type.DATE, true)),
-                        ImmutableMap.of(new Column("id_date", Type.DATE, true), idDate),
-                        null, -1, null, ((OlapTable) table).getBaseIndexId(),
-                        partitionIds,
-                        null,
-                        false,
-                        Lists.newArrayList(),
-                        Lists.newArrayList(),
-                        Lists.newArrayList(),
-                        false);
+                    new LogicalOlapScanOperator(table,
+                                ImmutableMap.of(idDate, new Column("id_date", Type.DATE, true)),
+                                ImmutableMap.of(new Column("id_date", Type.DATE, true), idDate),
+                                null, -1, null, ((OlapTable) table).getBaseIndexId(),
+                                partitionIds,
+                                null,
+                                false,
+                                Lists.newArrayList(),
+                                Lists.newArrayList(),
+                                Lists.newArrayList(),
+                                false);
         olapScanOperator.setPredicate(new BinaryPredicateOperator(BinaryType.GE,
-                idDate, ConstantOperator.createDate(LocalDateTime.of(2014, 5, 1, 0, 0, 0))));
+                    idDate, ConstantOperator.createDate(LocalDateTime.of(2014, 5, 1, 0, 0, 0))));
 
         groupExpression = new GroupExpression(olapScanOperator, Lists.newArrayList());
         groupExpression.setGroup(new Group(0));
         expressionContext = new ExpressionContext(groupExpression);
         statisticsCalculator = new StatisticsCalculator(expressionContext,
-                columnRefFactory, optimizerContext);
+                    columnRefFactory, optimizerContext);
         statisticsCalculator.estimatorStats();
         columnStatistic = expressionContext.getStatistics().getColumnStatistic(idDate);
 
         Assert.assertEquals(1281.4371, expressionContext.getStatistics().getOutputRowCount(), 0.001);
         Assert.assertEquals(Utils.getLongFromDateTime(LocalDateTime.of(2014, 5, 1, 0, 0, 0)),
-                columnStatistic.getMinValue(), 0.001);
+                    columnStatistic.getMinValue(), 0.001);
         Assert.assertEquals(Utils.getLongFromDateTime(LocalDateTime.of(2014, 12, 1, 0, 0, 0)),
-                columnStatistic.getMaxValue(), 0.001);
+                    columnStatistic.getMaxValue(), 0.001);
         Assert.assertEquals(20, columnStatistic.getDistinctValuesCount(), 0.001);
         FeConstants.runningUnitTest = false;
     }
 
     @Test
     public void testLogicalOlapTableScanPartitionPrune2(@Mocked CachedStatisticStorage cachedStatisticStorage)
-            throws Exception {
+                throws Exception {
         FeConstants.runningUnitTest = true;
         ColumnRefOperator idDate = columnRefFactory.create("id_date", Type.DATE, true);
 
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable table = (OlapTable) globalStateMgr.getDb("statistics_test").getTable("test_all_type_day_partition");
+        OlapTable table = (OlapTable) globalStateMgr.getLocalMetastore().getDb("statistics_test")
+                    .getTable("test_all_type_day_partition");
 
         new Expectations() {
             {
                 cachedStatisticStorage.getColumnStatistics(table, Lists.newArrayList("id_date"));
                 result = new ColumnStatistic(Utils.getLongFromDateTime(LocalDateTime.of(2020, 4, 23, 0, 0, 0)),
-                        Utils.getLongFromDateTime(LocalDateTime.of(2020, 4, 25, 0, 0, 0)), 0, 0, 3);
+                            Utils.getLongFromDateTime(LocalDateTime.of(2020, 4, 25, 0, 0, 0)), 0, 0, 3);
                 minTimes = 0;
 
                 cachedStatisticStorage.getColumnStatistic(table, "id_date");
                 result = new ColumnStatistic(Utils.getLongFromDateTime(LocalDateTime.of(2020, 4, 23, 0, 0, 0)),
-                        Utils.getLongFromDateTime(LocalDateTime.of(2020, 4, 25, 0, 0, 0)), 0, 0, 3);
+                            Utils.getLongFromDateTime(LocalDateTime.of(2020, 4, 25, 0, 0, 0)), 0, 0, 3);
                 minTimes = 0;
             }
         };
@@ -516,57 +517,57 @@ public void testLogicalOlapTableScanPartitionPrune2(@Mocked CachedStatisticStora
         Collection<Partition> partitions = table.getPartitions();
         // select partition p2
         List<Long> partitionIds = partitions.stream().filter(partition -> partition.getName().equalsIgnoreCase("p2")).
-                mapToLong(partition -> partition.getId()).boxed().collect(Collectors.toList());
+                    mapToLong(partition -> partition.getId()).boxed().collect(Collectors.toList());
         for (Partition partition : partitions) {
             partition.getBaseIndex().setRowCount(1000);
         }
 
         LogicalOlapScanOperator olapScanOperator =
-                new LogicalOlapScanOperator(table,
-                        ImmutableMap.of(idDate, new Column("id_date", Type.DATE, true)),
-                        ImmutableMap.of(new Column("id_date", Type.DATE, true), idDate), null, -1, null,
-                        ((OlapTable) table).getBaseIndexId(),
-                        partitionIds,
-                        null,
-                        false,
-                        Lists.newArrayList(),
-                        Lists.newArrayList(),
-                        Lists.newArrayList(),
-                        false);
+                    new LogicalOlapScanOperator(table,
+                                ImmutableMap.of(idDate, new Column("id_date", Type.DATE, true)),
+                                ImmutableMap.of(new Column("id_date", Type.DATE, true), idDate), null, -1, null,
+                                ((OlapTable) table).getBaseIndexId(),
+                                partitionIds,
+                                null,
+                                false,
+                                Lists.newArrayList(),
+                                Lists.newArrayList(),
+                                Lists.newArrayList(),
+                                false);
 
         GroupExpression groupExpression = new GroupExpression(olapScanOperator, Lists.newArrayList());
         groupExpression.setGroup(new Group(0));
         ExpressionContext expressionContext = new ExpressionContext(groupExpression);
         StatisticsCalculator statisticsCalculator = new StatisticsCalculator(expressionContext,
-                columnRefFactory, optimizerContext);
+                    columnRefFactory, optimizerContext);
         statisticsCalculator.estimatorStats();
 
         Assert.assertEquals(1000, expressionContext.getStatistics().getOutputRowCount(), 0.001);
         ColumnStatistic columnStatistic = expressionContext.getStatistics().getColumnStatistic(idDate);
         Assert.assertEquals(Utils.getLongFromDateTime(LocalDateTime.of(2020, 4, 24, 0, 0, 0)),
-                columnStatistic.getMinValue(), 0.001);
+                    columnStatistic.getMinValue(), 0.001);
         Assert.assertEquals(Utils.getLongFromDateTime(LocalDateTime.of(2020, 4, 25, 0, 0, 0)),
-                columnStatistic.getMaxValue(), 0.001);
+                    columnStatistic.getMaxValue(), 0.001);
         Assert.assertEquals(1, columnStatistic.getDistinctValuesCount(), 0.001);
 
         // select partition p2, p3
         partitionIds.clear();
         partitionIds = partitions.stream().filter(partition -> !(partition.getName().equalsIgnoreCase("p1"))).
-                mapToLong(Partition::getId).boxed().collect(Collectors.toList());
+                    mapToLong(Partition::getId).boxed().collect(Collectors.toList());
         olapScanOperator =
-                new LogicalOlapScanOperator(table,
-                        ImmutableMap.of(idDate, new Column("id_date", Type.DATE, true)),
-                        ImmutableMap.of(new Column("id_date", Type.DATE, true), idDate), null, -1, null,
-                        ((OlapTable) table).getBaseIndexId(),
-                        partitionIds,
-                        null,
-                        false,
-                        Lists.newArrayList(),
-                        Lists.newArrayList(),
-                        Lists.newArrayList(),
-                        false);
+                    new LogicalOlapScanOperator(table,
+                                ImmutableMap.of(idDate, new Column("id_date", Type.DATE, true)),
+                                ImmutableMap.of(new Column("id_date", Type.DATE, true), idDate), null, -1, null,
+                                ((OlapTable) table).getBaseIndexId(),
+                                partitionIds,
+                                null,
+                                false,
+                                Lists.newArrayList(),
+                                Lists.newArrayList(),
+                                Lists.newArrayList(),
+                                false);
         olapScanOperator.setPredicate(new BinaryPredicateOperator(BinaryType.GE,
-                idDate, ConstantOperator.createDate(LocalDateTime.of(2020, 04, 24, 0, 0, 0))));
+                    idDate, ConstantOperator.createDate(LocalDateTime.of(2020, 04, 24, 0, 0, 0))));
 
         groupExpression = new GroupExpression(olapScanOperator, Lists.newArrayList());
         groupExpression.setGroup(new Group(0));
@@ -577,9 +578,9 @@ public void testLogicalOlapTableScanPartitionPrune2(@Mocked CachedStatisticStora
         // has two partitions
         Assert.assertEquals(2000, expressionContext.getStatistics().getOutputRowCount(), 0.001);
         Assert.assertEquals(Utils.getLongFromDateTime(LocalDateTime.of(2020, 4, 24, 0, 0, 0)),
-                columnStatistic.getMinValue(), 0.001);
+                    columnStatistic.getMinValue(), 0.001);
         Assert.assertEquals(Utils.getLongFromDateTime(LocalDateTime.of(2020, 4, 26, 0, 0, 0)),
-                columnStatistic.getMaxValue(), 0.001);
+                    columnStatistic.getMaxValue(), 0.001);
         Assert.assertEquals(2, columnStatistic.getDistinctValuesCount(), 0.001);
         FeConstants.runningUnitTest = false;
     }
@@ -622,21 +623,21 @@ public void testJoinEstimateWithMultiColumns() {
         columnRefFactory.updateColumnToRelationIds(v6.getId(), 4);
         // on predicate : t0.v1 = t1.v3 and t0.v2 = t1.v4
         BinaryPredicateOperator eqOnPredicate1 =
-                new BinaryPredicateOperator(BinaryType.EQ, v1, v3);
+                    new BinaryPredicateOperator(BinaryType.EQ, v1, v3);
         BinaryPredicateOperator eqOnPredicate2 =
-                new BinaryPredicateOperator(BinaryType.EQ, v2, v4);
+                    new BinaryPredicateOperator(BinaryType.EQ, v2, v4);
         BinaryPredicateOperator eqOnPredicate3 =
-                new BinaryPredicateOperator(BinaryType.EQ, v5, v6);
+                    new BinaryPredicateOperator(BinaryType.EQ, v5, v6);
         // construct group expression
         LogicalJoinOperator joinOperator =
-                new LogicalJoinOperator(JoinOperator.INNER_JOIN, new CompoundPredicateOperator(
-                        CompoundPredicateOperator.CompoundType.AND, eqOnPredicate1, eqOnPredicate2));
+                    new LogicalJoinOperator(JoinOperator.INNER_JOIN, new CompoundPredicateOperator(
+                                CompoundPredicateOperator.CompoundType.AND, eqOnPredicate1, eqOnPredicate2));
         GroupExpression groupExpression =
-                new GroupExpression(joinOperator, Lists.newArrayList(childGroup1, childGroup2));
+                    new GroupExpression(joinOperator, Lists.newArrayList(childGroup1, childGroup2));
         groupExpression.setGroup(new Group(2));
         ExpressionContext expressionContext = new ExpressionContext(groupExpression);
         StatisticsCalculator statisticsCalculator = new StatisticsCalculator(expressionContext,
-                columnRefFactory, optimizerContext);
+                    columnRefFactory, optimizerContext);
         // use middle ground method to estimate
         ConnectContext.get().getSessionVariable().setUseCorrelatedJoinEstimate(false);
         statisticsCalculator.estimatorStats();
@@ -657,13 +658,13 @@ public void testJoinEstimateWithMultiColumns() {
         // on predicate : t0.v1 = t1.v3 and t0.v2 = t2.v4 and t3.v5 = t4.v6
         // construct group expression
         joinOperator = new LogicalJoinOperator(JoinOperator.INNER_JOIN, new CompoundPredicateOperator(
-                CompoundPredicateOperator.CompoundType.AND, eqOnPredicate1, new CompoundPredicateOperator(
-                CompoundPredicateOperator.CompoundType.AND, eqOnPredicate2, eqOnPredicate3)));
+                    CompoundPredicateOperator.CompoundType.AND, eqOnPredicate1, new CompoundPredicateOperator(
+                    CompoundPredicateOperator.CompoundType.AND, eqOnPredicate2, eqOnPredicate3)));
         groupExpression = new GroupExpression(joinOperator, Lists.newArrayList(childGroup1, childGroup2));
         groupExpression.setGroup(new Group(2));
         expressionContext = new ExpressionContext(groupExpression);
         statisticsCalculator = new StatisticsCalculator(expressionContext,
-                columnRefFactory, optimizerContext);
+                    columnRefFactory, optimizerContext);
         // use middle ground method to estimate
         ConnectContext.get().getSessionVariable().setUseCorrelatedJoinEstimate(false);
         statisticsCalculator.estimatorStats();
@@ -671,18 +672,18 @@ CompoundPredicateOperator.CompoundType.AND, eqOnPredicate1, new CompoundPredicat
 
         // on predicate : t0.v1 = t1.v3 + t1.v4 and t0.v2 = t1.v3 + t1.v4
         BinaryPredicateOperator eqOnPredicateWithAdd1 =
-                new BinaryPredicateOperator(BinaryType.EQ, v1,
-                        new CallOperator("add", Type.BIGINT, Lists.newArrayList(v3, v4)));
+                    new BinaryPredicateOperator(BinaryType.EQ, v1,
+                                new CallOperator("add", Type.BIGINT, Lists.newArrayList(v3, v4)));
         BinaryPredicateOperator eqOnPredicateWithAdd2 =
-                new BinaryPredicateOperator(BinaryType.EQ, v2,
-                        new CallOperator("add", Type.BIGINT, Lists.newArrayList(v3, v4)));
+                    new BinaryPredicateOperator(BinaryType.EQ, v2,
+                                new CallOperator("add", Type.BIGINT, Lists.newArrayList(v3, v4)));
         joinOperator = new LogicalJoinOperator(JoinOperator.INNER_JOIN, new CompoundPredicateOperator(
-                CompoundPredicateOperator.CompoundType.AND, eqOnPredicateWithAdd1, eqOnPredicateWithAdd2));
+                    CompoundPredicateOperator.CompoundType.AND, eqOnPredicateWithAdd1, eqOnPredicateWithAdd2));
         groupExpression = new GroupExpression(joinOperator, Lists.newArrayList(childGroup1, childGroup2));
         groupExpression.setGroup(new Group(2));
         expressionContext = new ExpressionContext(groupExpression);
         statisticsCalculator = new StatisticsCalculator(expressionContext,
-                columnRefFactory, optimizerContext);
+                    columnRefFactory, optimizerContext);
         // use middle ground method to estimate
         ConnectContext.get().getSessionVariable().setUseCorrelatedJoinEstimate(false);
         statisticsCalculator.estimatorStats();
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/AggregateTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/AggregateTest.java
index 2f81dc4177c125..d1ec657cb0f9fb 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/AggregateTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/AggregateTest.java
@@ -2634,6 +2634,58 @@ public void testApproxTopK() throws Exception {
         }
     }
 
+    @Test
+    public void testMannWhitneyUTest() throws Exception {
+        {
+            String sql = "select mann_whitney_u_test(L_LINENUMBER, L_LINENUMBER) from lineitem";
+            getFragmentPlan(sql);
+            sql = "select mann_whitney_u_test(L_LINENUMBER, L_LINENUMBER, 'two-sided') from lineitem";
+            getFragmentPlan(sql);
+            sql = "select mann_whitney_u_test(L_LINENUMBER, L_LINENUMBER, 'greater') from lineitem";
+            getFragmentPlan(sql);
+            sql = "select mann_whitney_u_test(L_LINENUMBER, L_LINENUMBER, 'less') from lineitem";
+            getFragmentPlan(sql);
+            sql = "select mann_whitney_u_test(L_LINENUMBER, L_LINENUMBER, 'two-sided', 0) from lineitem";
+            getFragmentPlan(sql);
+        }
+        {
+            Exception exception = Assertions.assertThrows(SemanticException.class, () -> {
+                String sql = "select mann_whitney_u_test(L_LINENUMBER, L_LINENUMBER, 3) from lineitem";
+                getFragmentPlan(sql);
+            });
+            String expectedMessage = "third parameter should be a string literal";
+            String actualMessage = exception.getMessage();
+            Assert.assertTrue(actualMessage.contains(expectedMessage));
+        }
+        {
+            Exception exception = Assertions.assertThrows(SemanticException.class, () -> {
+                String sql = "select mann_whitney_u_test(L_LINENUMBER, L_LINENUMBER, 'two_sided') from lineitem";
+                getFragmentPlan(sql);
+            });
+            String expectedMessage = "third parameter should be one of ['two-sided', 'greater', 'less']";
+            String actualMessage = exception.getMessage();
+            Assert.assertTrue(actualMessage.contains(expectedMessage));
+        }
+        {
+            Exception exception = Assertions.assertThrows(SemanticException.class, () -> {
+                String sql = "select mann_whitney_u_test(L_LINENUMBER, L_LINENUMBER, 'two-sided', -1) from lineitem";
+                getFragmentPlan(sql);
+            });
+            String expectedMessage = "mann_whitney_u_test's fourth parameter should be a non-negative int literal.";
+            String actualMessage = exception.getMessage();
+            Assert.assertTrue(actualMessage.contains(expectedMessage));
+        }
+        {
+            Exception exception = Assertions.assertThrows(SemanticException.class, () -> {
+                String sql = "select mann_whitney_u_test(L_LINENUMBER, L_LINENUMBER, 'two-sided', 0.1) from lineitem";
+                getFragmentPlan(sql);
+            });
+            String expectedMessage = "mann_whitney_u_test's fourth parameter should be a non-negative int literal.";
+            String actualMessage = exception.getMessage();
+            Assert.assertTrue(actualMessage.contains(expectedMessage));
+        }
+    }
+
     @Test
     public void testTableAliasCountDistinctHaving() throws Exception {
         String sql = "select " +
@@ -2782,8 +2834,8 @@ public void testRemoveGroupByConstant() throws Exception {
         sql = "select max(a), a from (select v1, abs(1) as a, abs(2) as b from t0) t group by a, v1";
         plan = getFragmentPlan(sql);
         assertContains(plan, "2:Project\n" +
-                "  |  <slot 4> : abs(1)\n" +
-                "  |  <slot 6> : 6: max\n" +
+                "  |  <slot 7> : abs(1)\n" +
+                "  |  <slot 8> : 8: max\n" +
                 "  |  \n" +
                 "  1:AGGREGATE (update finalize)\n" +
                 "  |  output: max(abs(1))\n" +
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/CTEPlanTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/CTEPlanTest.java
index 93f70e381b1524..37cbabe3281189 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/CTEPlanTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/CTEPlanTest.java
@@ -42,10 +42,10 @@ public static void beforeClass() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
         globalStateMgr.setStatisticStorage(new TestStorage());
 
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(t0, 20000000);
 
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("t1");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t1");
         setTableStatistics(t1, 2000000);
     }
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/ComplexTypePrunePlanTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/ComplexTypePrunePlanTest.java
new file mode 100644
index 00000000000000..20e9f0bf8cb308
--- /dev/null
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/ComplexTypePrunePlanTest.java
@@ -0,0 +1,353 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+package com.starrocks.sql.plan;
+
+import com.starrocks.common.FeConstants;
+import com.starrocks.utframe.StarRocksAssert;
+import org.junit.Before;
+import org.junit.BeforeClass;
+import org.junit.Test;
+
+public class ComplexTypePrunePlanTest extends PlanTestBase {
+
+    @BeforeClass
+    public static void beforeClass() throws Exception {
+        PlanTestBase.beforeClass();
+        StarRocksAssert starRocksAssert = new StarRocksAssert(connectContext);
+        FeConstants.runningUnitTest = true;
+        starRocksAssert.withTable("create table test(c0 INT, " +
+                "c1 struct<a int, b array<struct<a int, b int>>>," +
+                "c2 struct<a int, b int>," +
+                "c3 struct<a int, b int, c struct<a int, b int>, d array<int>>) " +
+                "duplicate key(c0) distributed by hash(c0) buckets 1 " +
+                "properties('replication_num'='1');");
+        starRocksAssert.withTable("create table test1(c0 INT, " +
+                "c1 struct<a int, b array<struct<a int, b int>>>," +
+                "c2 struct<a int, b int>," +
+                "c2_0 struct<a int, b varchar(10)>, " +
+                "c3 struct<a int, b int, c struct<a int, b int>, d array<int>>) " +
+                "duplicate key(c0) distributed by hash(c0) buckets 1 " +
+                "properties('replication_num'='1');");
+        starRocksAssert.withTable("create table array_struct_nest(c1 int, " +
+                "c2 array<struct<c2_sub1 int, c2_sub2 int>>, " +
+                "c3 struct<c3_sub1 array<struct<c3_sub1_sub1 int, c3_sub1_sub2 int>>, c3_sub2 int>) " +
+                "duplicate key(c1) distributed by hash(c1) buckets 1 " +
+                "properties('replication_num'='1');");
+        starRocksAssert.withTable("create table index_struct_nest(c1 int,\n" +
+                "index_struct array<struct<`index` bigint(20), char_col varchar(1048576)>>)\n" +
+                "duplicate key(c1) distributed by hash(c1) buckets 1\n" +
+                "properties('replication_num'='1')");
+        FeConstants.runningUnitTest = false;
+    }
+
+    @Before
+    public void setup() throws Exception {
+        connectContext.getSessionVariable().setEnablePruneComplexTypes(true);
+        connectContext.getSessionVariable().setEnablePruneComplexTypesInUnnest(true);
+        connectContext.getSessionVariable().setCboPruneSubfield(true);
+    }
+
+    @Test
+    public void testStruct() throws Exception {
+        String sql = "select * from test1 union all select * from test1";
+        String plan = getFragmentPlan(sql);
+        assertContains(plan, "0:UNION\n" +
+                "  |  \n" +
+                "  |----4:EXCHANGE\n" +
+                "  |    \n" +
+                "  2:EXCHANGE");
+        sql = "select c2 from test1 union all select c2_0 from test1";
+        plan = getFragmentPlan(sql);
+        assertContains(plan, "CAST(3: c2 AS struct<a int(11), b varchar(10)>)");
+
+        sql = "select index_struct[1].`index` from index_struct_nest";
+        plan = getFragmentPlan(sql);
+        assertContains(plan, "1:Project\n" +
+                "  |  <slot 3> : 2: index_struct[1].index[true]");
+    }
+
+    @Test
+    public void testSubfield() throws Exception {
+        String sql = "select c1.a from test";
+        assertVerbosePlanContains(sql, "[/c1/a]");
+
+        connectContext.getSessionVariable().setEnablePruneComplexTypes(false);
+        assertVerbosePlanContains(sql, "Pruned type: 2 <-> [STRUCT<a int(11), b ARRAY<STRUCT<a int(11), b int(11)>>>]");
+    }
+
+    @Test
+    public void testStructMultiSelect() throws Exception {
+        String sql = "select c2.a, c2.b from test";
+        assertVerbosePlanContains(sql, "Pruned type: 3 <-> [STRUCT<a int(11), b int(11)>]");
+    }
+
+    @Test
+    public void testSubfieldWindow() throws Exception {
+        String sql = "select c3.a, row_number() over (partition by c0 order by c2.a) from test";
+        assertVerbosePlanContains(sql, "[/c2/a, /c3/a]");
+    }
+
+    @Test
+    public void testSelectArrayStruct() throws Exception {
+        String sql = "select c1.b[10].a from test";
+        assertVerbosePlanContains(sql, "ColumnAccessPath: [/c1/b/INDEX/a]");
+    }
+
+    @Test
+    public void testJoinOn() throws Exception {
+        String sql = "select t1.c0 from test as t1 join test as t2 on t1.c2.a=t2.c2.a";
+        assertVerbosePlanContains(sql, "[/c2/a]");
+    }
+
+    @Test
+    public void testAggregate() throws Exception {
+        String sql = "select sum(c2.a) as t from test";
+        assertVerbosePlanContains(sql, "[/c2/a]");
+
+        sql = "select sum(c2.b) as t from test group by c2.a";
+        assertVerbosePlanContains(sql, "Pruned type: 3 <-> [STRUCT<a int(11), b int(11)>]");
+
+        sql = "select count(c1.b[10].a) from test";
+        assertVerbosePlanContains(sql, "[/c1/b/INDEX/a]");
+
+        sql = "select count(c3.c.b) from test group by c1.a, c2.b";
+        assertVerbosePlanContains(sql, "[/c1/a, /c2/b, /c3/c/b]");
+
+        sql = "select sum(c3.c.b + c2.a) as t from test group by c1.a, c2.b";
+        assertVerbosePlanContains(sql, "[/c1/a, /c2/a, /c2/b, /c3/c/b]");
+    }
+
+    @Test
+    public void testSelectPredicate() throws Exception {
+        String sql = "select c0 from test where (c0+c2.a)>5";
+        assertVerbosePlanContains(sql, "[/c2/a]");
+    }
+
+    @Test
+    public void testSelectStar() throws Exception {
+        FeConstants.runningUnitTest = true;
+        String sql = "select *, c1.b[10].a from test";
+        assertVerbosePlanContains(sql, "Pruned type: 2 <-> [STRUCT<a int(11), b ARRAY<STRUCT<a int(11), b int(11)>>>]");
+        assertVerbosePlanContains(sql, "Pruned type: 3 <-> [STRUCT<a int(11), b int(11)>]");
+        assertVerbosePlanContains(sql,
+                "Pruned type: 4 <-> [STRUCT<a int(11), b int(11), c STRUCT<a int(11), b int(11)>, d ARRAY<int(11)>>]");
+        sql = "select * from index_struct_nest where index_struct[1].`index` = 5";
+        assertVerbosePlanContains(sql, "2 <-> [ARRAY<struct<index bigint(20), char_col varchar(1048576)>>]");
+        sql = "select index_struct from index_struct_nest where index_struct[1].`index` = 5";
+        assertVerbosePlanContains(sql, "2 <-> [ARRAY<struct<index bigint(20), char_col varchar(1048576)>>]");
+        FeConstants.runningUnitTest = false;
+    }
+
+    @Test
+    public void testCommonSubOperator() throws Exception {
+        FeConstants.runningUnitTest = true;
+        // test for CommonSubOperator
+        String sql = "select abs(index_struct[1].`index`) + abs(index_struct[1].`index`) from index_struct_nest";
+        assertVerbosePlanContains(sql, "Pruned type: 2 <-> [ARRAY<struct<index bigint(20)>>]");
+        FeConstants.runningUnitTest = false;
+    }
+
+    @Test
+    public void testSubQuery() throws Exception {
+        String sql = "select c2.a from (select c1, c2 from test) t";
+        assertVerbosePlanContains(sql, "[/c2/a]");
+        sql = "select t1.a, rn from (select c3.c as t1, row_number() over" +
+                " (partition by c0 order by c2.a) as rn from test) as t";
+        assertVerbosePlanContains(sql, "[/c2/a, /c3/c/a]");
+    }
+
+    @Test
+    public void testStructWithWindow() throws Exception {
+        String sql = "select sum(c2.b) over(partition by c2.a order by c0) from test";
+        assertPlanContains(sql, " 3:ANALYTIC\n" +
+                "  |  functions: [, sum(7: c2.b[true]), ]\n" +
+                "  |  partition by: 9: c2.a\n" +
+                "  |  order by: 1: c0 ASC\n" +
+                "  |  window: RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW");
+
+        sql = "select sum(c0) over(partition by c2.a order by c2.b) from test";
+        assertPlanContains(sql, " 3:ANALYTIC\n" +
+                "  |  functions: [, sum(5: c0), ]\n" +
+                "  |  partition by: 9: c2.a\n" +
+                "  |  order by: 10: c2.b ASC\n" +
+                "  |  window: RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW");
+
+        sql = "select sum(c1.b[10].b) over(partition by c2.a order by c2.b) from test";
+        assertPlanContains(sql, "3:ANALYTIC\n" +
+                "  |  functions: [, sum(6: c1.b[true][10].b[true]), ]\n" +
+                "  |  partition by: 9: c2.a\n" +
+                "  |  order by: 10: c2.b ASC\n" +
+                "  |  window: RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW");
+    }
+
+    @Test
+    public void testExcept() throws Exception {
+        String sql = "select c2.a + 1 from test except select c3.a from test";
+        assertVerbosePlanContains(sql, "[/c3/a]");
+        assertVerbosePlanContains(sql, "[/c2/a]");
+    }
+
+    @Test
+    public void testIntersect() throws Exception {
+        String sql = "select c2.a + 1 from test intersect select c3.a from test";
+        assertVerbosePlanContains(sql, "[/c3/a]");
+        assertVerbosePlanContains(sql, "[/c2/a]");
+    }
+
+    @Test
+    public void testLambda() throws Exception {
+        String sql = "select array_map(x->x, [])";
+        assertVerbosePlanContains(sql, "[]");
+        sql = "select array_map(x->x+1, c3.d) from test";
+        assertVerbosePlanContains(sql, "[/c3/d]");
+        sql = "select array_sortby(x->x+1, c3.d) from test";
+        assertVerbosePlanContains(sql, "[/c3/d]");
+        sql = "select array_filter((x,y) -> x<y, c3.d, c3.d) from test";
+        assertVerbosePlanContains(sql, "[/c3/d]");
+        sql = "select map_values(col_map), map_keys(col_map) from (select map_from_arrays([],[]) as col_map)A";
+        assertPlanContains(sql, "<slot 4> : map_keys(map_from_arrays(CAST([] AS ARRAY<BOOLEAN>), CAST([] AS ARRAY<BOOLEAN>)))");
+    }
+
+    @Test
+    public void testCast() throws Exception {
+        String sql = "select cast(row(null, null, null) as STRUCT<a int, b MAP<int, int>, c ARRAY<INT>>); ";
+        String plan = getVerboseExplain(sql);
+        assertContains(plan, "cast(row[(NULL, NULL, NULL); args: BOOLEAN,BOOLEAN,BOOLEAN; " +
+                "result: struct<col1 boolean, col2 boolean, col3 boolean>; args nullable: true; result nullable: true] " +
+                "as struct<a int(11), b map<int(11),int(11)>, c array<int(11)>>)");
+    }
+
+    @Test
+    public void testCastArrayIndex() throws Exception {
+        String sql = "select c1.b[cast('  111   ' as bigint)] from test";
+        String plan = getVerboseExplain(sql);
+        assertCContains(plan, "1:Project\n" +
+                "  |  output columns:\n" +
+                "  |  5 <-> 2: c1.b[true][111]",
+                "Pruned type: 2 <-> [struct<a int(11), b array<struct<a int(11), b int(11)>>>]");
+    }
+
+    @Test
+    public void testNoProjectOnTF() throws Exception {
+        FeConstants.runningUnitTest = true;
+        // no project on input, and no project on tf, no prune
+        String sql = "select c2_struct from array_struct_nest, unnest(c2) as t(c2_struct);";
+        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11), c2_sub2 int(11)>>]");
+        sql = "select c2 from array_struct_nest, unnest(c2) as t(c2_struct);";
+        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11), c2_sub2 int(11)>>]");
+        sql = "select c2, c2_struct from array_struct_nest, unnest(c2) as t(c2_struct);";
+        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11), c2_sub2 int(11)>>]");
+        // project on input, no project on tf, prune
+        sql = "select c3_struct from array_struct_nest, unnest(c3.c3_sub1) as t(c3_struct);";
+        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11), c3_sub1_sub2 int(11)>>>]");
+        // output contains the complete column, no prune
+        sql = "select c3 from array_struct_nest, unnest(c3.c3_sub1) as t(c3_struct);";
+        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11), " +
+                "c3_sub1_sub2 int(11)>>, c3_sub2 int(11)>]");
+        sql = "select c3, c3_struct from array_struct_nest, unnest(c3.c3_sub1) as t(c3_struct);";
+        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11), " +
+                "c3_sub1_sub2 int(11)>>, c3_sub2 int(11)>]");
+        FeConstants.runningUnitTest = false;
+    }
+
+    @Test
+    public void testProjectOnTF() throws Exception {
+        FeConstants.runningUnitTest = true;
+        // no project on input, and project on tf, prune
+        String sql = "select c2_struct.c2_sub1 from array_struct_nest, unnest(c2) as t(c2_struct);";
+        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11)>>]");
+        // no project on input, and project on tf all subfiled, no prune
+        sql = "select c2_struct.c2_sub1, c2_struct.c2_sub2 from array_struct_nest, unnest(c2) as t(c2_struct);";
+        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11), c2_sub2 int(11)>>]");
+        sql = "select c2_struct, c2_struct.c2_sub2 from array_struct_nest, unnest(c2) as t(c2_struct);";
+        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11), c2_sub2 int(11)>>]");
+        // project on input, project on tf, prune
+        sql = "select c3_struct.c3_sub1_sub1 from array_struct_nest, unnest(c3.c3_sub1) as t(c3_struct);";
+        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11)>>>]");
+        // project on input, project on tf but all subfiled, prune
+        sql = "select c3_struct.c3_sub1_sub1, c3_struct.c3_sub1_sub2 from array_struct_nest, unnest(c3.c3_sub1) as t(c3_struct);";
+        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11), c3_sub1_sub2 int(11)>>>]");
+        sql = "select c3_struct.c3_sub1_sub1, c3_struct from array_struct_nest, unnest(c3.c3_sub1) as t(c3_struct);";
+        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11), c3_sub1_sub2 int(11)>>>]");
+        FeConstants.runningUnitTest = false;
+    }
+
+    @Test
+    public void testNoOutputOnTF() throws Exception {
+        FeConstants.runningUnitTest = true;
+        String sql = "select c1 from array_struct_nest, unnest(c2) as t(c2_struct) where c2_struct.c2_sub1 > 0;";
+        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11)>>]");
+        sql = "select c1 from array_struct_nest, unnest(c3.c3_sub1) as t(c3_struct) where c3_struct.c3_sub1_sub1 > 0;";
+        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11)>>>]");
+        FeConstants.runningUnitTest = false;
+    }
+
+    @Test
+    public void testUnnestComplex() throws Exception {
+        FeConstants.runningUnitTest = true;
+        String sql = "select c3_struct.c3_sub1_sub1 from array_struct_nest, unnest(c2) as t(c_struct), " +
+                "unnest(c3.c3_sub1) as tt(c3_struct) where c_struct.c2_sub1 > 10";
+        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11)>>]");
+        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11)>>>]");
+        FeConstants.runningUnitTest = false;
+    }
+
+    @Test
+    public void testUnnestCrossJoin() throws Exception {
+        FeConstants.runningUnitTest = true;
+        String sql = "select c3_struct.c3_sub1_sub1 from array_struct_nest cross join " +
+                "unnest(c3.c3_sub1) as t(c3_struct) where c1 > 0;";
+        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11)>>>]");
+        FeConstants.runningUnitTest = false;
+    }
+
+    @Test
+    public void testSubfieldNoCopy() throws Exception {
+        String sql = "select c3.c.a, c3.c.b, c3.a, c3.b, c3.d, c2.a, c1.a, c1.b[1].a from test";
+        assertVerbosePlanContains(sql, "c3.c.a[false]", "c3.c.b[false]", "c3.a[false]", "c3.b[false]",
+                "c3.d[false]", "c2.a[false]", "c1.a[false]");
+        // we don't support non-copy for this expr now
+        assertVerbosePlanContains(sql, "c1.b[true][1].a[true]");
+        // test common project expr
+        sql = "select c1.a, c1.a + 1 as c1a, c1.a + 2 as c2a from test";
+        assertVerbosePlanContains(sql, "c1.a[true]", "cast(2: c1.a[true] as BIGINT)");
+    }
+
+    @Test
+    public void testSubfieldNeedCopyForOverlap() throws Exception {
+        String sql = "select c3.c.a, c3.c from test";
+        assertVerbosePlanContains(sql, "c3.c.a[true]", "c3.c[true]");
+        sql = "select c1.b, c1.b[1] from test";
+        assertVerbosePlanContains(sql, "c1.b[true]", "c1.b[true][1]");
+        sql = "select c1.b[1].a, c1.b from test";
+        assertVerbosePlanContains(sql, "c1.b[true][1].a[true]", "c1.b[true]");
+    }
+
+    @Test
+    public void testSemiTypeCountDistinct() throws Exception {
+        String sql = "select count(distinct row(1, 2))";
+        String plan = getFragmentPlan(sql);
+        assertContains(plan, "  1:AGGREGATE (update finalize)\n" +
+                "  |  output: any_value(CAST(row(1, 2) IS NOT NULL AS BIGINT))");
+
+        sql = "select count(distinct [1,2,3])";
+        plan = getFragmentPlan(sql);
+        assertContains(plan, "output: any_value(CAST([1,2,3] IS NOT NULL AS BIGINT))");
+
+        sql = "select count(distinct map{'a': 1})";
+        plan = getFragmentPlan(sql);
+        assertContains(plan, "output: any_value(CAST(map{'a':1} IS NOT NULL AS BIGINT))");
+    }
+}
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/DistributedEnvPlanTestBase.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/DistributedEnvPlanTestBase.java
index 44cfc1dcf40234..119364ffa5bd89 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/DistributedEnvPlanTestBase.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/DistributedEnvPlanTestBase.java
@@ -111,45 +111,45 @@ public static void beforeClass() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
         int scale = 100;
         connectContext.getGlobalStateMgr().setStatisticStorage(new MockTpchStatisticStorage(connectContext, scale));
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("region");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("region");
         setTableStatistics(t0, 5);
 
-        OlapTable t5 = (OlapTable) globalStateMgr.getDb("test").getTable("nation");
+        OlapTable t5 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("nation");
         setTableStatistics(t5, 25);
 
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("supplier");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("supplier");
         setTableStatistics(t1, 10000 * scale);
 
-        OlapTable t4 = (OlapTable) globalStateMgr.getDb("test").getTable("customer");
+        OlapTable t4 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("customer");
         setTableStatistics(t4, 150000 * scale);
 
-        OlapTable t6 = (OlapTable) globalStateMgr.getDb("test").getTable("part");
+        OlapTable t6 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("part");
         setTableStatistics(t6, 200000 * scale);
 
-        OlapTable t2 = (OlapTable) globalStateMgr.getDb("test").getTable("partsupp");
+        OlapTable t2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("partsupp");
         setTableStatistics(t2, 800000 * scale);
 
-        OlapTable t3 = (OlapTable) globalStateMgr.getDb("test").getTable("orders");
+        OlapTable t3 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("orders");
         setTableStatistics(t3, 1500000 * scale);
 
-        OlapTable t7 = (OlapTable) globalStateMgr.getDb("test").getTable("lineitem");
+        OlapTable t7 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("lineitem");
         setTableStatistics(t7, 6000000 * scale);
 
-        OlapTable t8 = (OlapTable) globalStateMgr.getDb("test").getTable("lineitem_partition");
+        OlapTable t8 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("lineitem_partition");
         setTableStatistics(t8, 6000000 * scale);
 
-        OlapTable testAllType = (OlapTable) globalStateMgr.getDb("test").getTable("test_all_type");
+        OlapTable testAllType = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("test_all_type");
         setTableStatistics(testAllType, 6000000);
 
         OlapTable lineorderNewL =
-                (OlapTable) globalStateMgr.getDb("test").getTable("lineorder_new_l");
+                (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("lineorder_new_l");
         setTableStatistics(lineorderNewL, 1200018434);
 
-        OlapTable datesN = (OlapTable) globalStateMgr.getDb("test").getTable("dates_n");
+        OlapTable datesN = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("dates_n");
         setTableStatistics(datesN, 2556);
 
         OlapTable skewTable =
-                (OlapTable) globalStateMgr.getDb("test").getTable("skew_table");
+                (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("skew_table");
         setTableStatistics(skewTable, 10000000);
 
         UtFrameUtils.addMockBackend(10002);
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/DistributedEnvPlanWithCostTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/DistributedEnvPlanWithCostTest.java
index fda82fcb680c65..29a6dfcf1c75f8 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/DistributedEnvPlanWithCostTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/DistributedEnvPlanWithCostTest.java
@@ -949,7 +949,7 @@ public void testPartitionColumnColumnStatistics() throws Exception {
     @Test
     public void testCastDatePredicate() throws Exception {
         OlapTable lineitem =
-                (OlapTable) connectContext.getGlobalStateMgr().getDb("test").getTable("lineitem");
+                (OlapTable) connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test").getTable("lineitem");
 
         MockTpchStatisticStorage mock = new MockTpchStatisticStorage(connectContext, 100);
         connectContext.getGlobalStateMgr().setStatisticStorage(mock);
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/DistributedEnvTPCDSPlanTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/DistributedEnvTPCDSPlanTest.java
index 4ddd581dd276fa..6a235b35fc0954 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/DistributedEnvTPCDSPlanTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/DistributedEnvTPCDSPlanTest.java
@@ -30,19 +30,19 @@ public static void beforeClass() throws Exception {
         TPCDSPlanTest.beforeClass();
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
         OlapTable customerAddress =
-                (OlapTable) globalStateMgr.getDb("test").getTable("customer_address");
+                (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("customer_address");
         setTableStatistics(customerAddress, 1000000);
 
-        OlapTable customer = (OlapTable) globalStateMgr.getDb("test").getTable("customer");
+        OlapTable customer = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("customer");
         setTableStatistics(customer, 2000000);
 
-        OlapTable storeSales = (OlapTable) globalStateMgr.getDb("test").getTable("store_sales");
+        OlapTable storeSales = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("store_sales");
         setTableStatistics(storeSales, 287997024);
 
-        OlapTable dateDim = (OlapTable) globalStateMgr.getDb("test").getTable("date_dim");
+        OlapTable dateDim = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("date_dim");
         setTableStatistics(dateDim, 73048);
 
-        OlapTable item = (OlapTable) globalStateMgr.getDb("test").getTable("item");
+        OlapTable item = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("item");
         setTableStatistics(item, 203999);
 
         UtFrameUtils.addMockBackend(10002);
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/EliminateConstantValueTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/EliminateConstantValueTest.java
index 25ac17ce4f0f86..44fdebe24923ab 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/EliminateConstantValueTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/EliminateConstantValueTest.java
@@ -40,7 +40,7 @@ public void testWithCrossJoin() throws Exception {
             PlanTestBase.assertContains(plan, "  1:Project\n" +
                     "  |  <slot 1> : 1: L_ORDERKEY\n" +
                     "  |  <slot 2> : 2: L_PARTKEY\n" +
-                    "  |  <slot 19> : '2000-01-01'\n" +
+                    "  |  <slot 20> : '2000-01-01'\n" +
                     "  |  \n" +
                     "  0:OlapScanNode\n" +
                     "     TABLE: lineitem_partition");
@@ -66,7 +66,7 @@ public void testWithCrossJoin() throws Exception {
                     "  |  <slot 15> : 15: L_SHIPMODE\n" +
                     "  |  <slot 16> : 16: L_COMMENT\n" +
                     "  |  <slot 17> : 17: PAD\n" +
-                    "  |  <slot 19> : '2000-01-01'\n" +
+                    "  |  <slot 20> : '2000-01-01'\n" +
                     "  |  \n" +
                     "  0:OlapScanNode\n" +
                     "     TABLE: lineitem_partitio");
@@ -82,7 +82,7 @@ public void testWithInnerJoin() throws Exception {
             PlanTestBase.assertContains(plan, "  1:Project\n" +
                     "  |  <slot 1> : 1: L_ORDERKEY\n" +
                     "  |  <slot 2> : 2: L_PARTKEY\n" +
-                    "  |  <slot 19> : '2000-01-01'\n" +
+                    "  |  <slot 20> : '2000-01-01'\n" +
                     "  |  \n" +
                     "  0:OlapScanNode\n" +
                     "     TABLE: lineitem_partition");
@@ -96,12 +96,12 @@ public void testWithInnerJoin() throws Exception {
             PlanTestBase.assertContains(plan, "  1:Project\n" +
                     "  |  <slot 1> : 1: L_ORDERKEY\n" +
                     "  |  <slot 2> : 2: L_PARTKEY\n" +
-                    "  |  <slot 19> : '2000-01-01'\n" +
+                    "  |  <slot 20> : '2000-01-01'\n" +
                     "  |  \n" +
                     "  0:OlapScanNode\n" +
                     "     TABLE: lineitem_partition\n" +
                     "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 11: L_SHIPDATE = '2000-01-01', CAST(11: L_SHIPDATE AS DATETIME) IS NOT NULL");
+                    "     PREDICATES: 11: L_SHIPDATE = '2000-01-01'");
         }
 
         // join on multi columns
@@ -113,14 +113,13 @@ public void testWithInnerJoin() throws Exception {
             PlanTestBase.assertContains(plan, "  1:Project\n" +
                     "  |  <slot 1> : 1: L_ORDERKEY\n" +
                     "  |  <slot 2> : 2: L_PARTKEY\n" +
-                    "  |  <slot 19> : '2000-01-01'\n" +
-                    "  |  <slot 20> : 'key1'\n" +
+                    "  |  <slot 21> : '2000-01-01'\n" +
+                    "  |  <slot 22> : 'key1'\n" +
                     "  |  \n" +
                     "  0:OlapScanNode\n" +
                     "     TABLE: lineitem_partition\n" +
                     "     PREAGGREGATION: ON\n" +
-                    "     PREDICATES: 11: L_SHIPDATE = '2000-01-01', CAST(2: L_PARTKEY AS VARCHAR(1048576)) = 'key1', " +
-                    "CAST(11: L_SHIPDATE AS DATETIME) IS NOT NULL, CAST(2: L_PARTKEY AS VARCHAR(1048576)) IS NOT NULL");
+                    "     PREDICATES: 11: L_SHIPDATE = '2000-01-01', CAST(2: L_PARTKEY AS VARCHAR(1048576)) = 'key1'");
         }
     }
 
@@ -188,7 +187,7 @@ public void testWithRightOuterJoin1() throws Exception {
                 "  |  colocate: false, reason: \n" +
                 "  |  \n" +
                 "  |----3:Project\n" +
-                "  |    |  <slot 19> : '2000-01-01'\n" +
+                "  |    |  <slot 22> : 1\n" +
                 "  |    |  \n" +
                 "  |    2:UNION\n" +
                 "  |       constant exprs: \n" +
@@ -232,10 +231,10 @@ public void testWithLeftSemiJoin() throws Exception {
         String sql = "select * " +
                 "from (select '2000-01-01' as col) t2 left semi join lineitem_partition t1 on t1.L_SHIPDATE = t2.col";
         String plan = getFragmentPlan(sql);
-        PlanTestBase.assertContains(plan, "  5:HASH JOIN\n" +
-                "  |  join op: LEFT SEMI JOIN (BROADCAST)\n" +
+        PlanTestBase.assertContains(plan, "4:NESTLOOP JOIN\n" +
+                "  |  join op: LEFT SEMI JOIN\n" +
                 "  |  colocate: false, reason: \n" +
-                "  |  equal join conjunct: 21: cast = 20: cast");
+                "  |  other join predicates: 13: L_SHIPDATE = '2000-01-01'");
     }
 
     @Test
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/ExternalTableTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/ExternalTableTest.java
index 65fd76353b75d9..4060dcb3881939 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/ExternalTableTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/ExternalTableTest.java
@@ -236,8 +236,8 @@ public void testMysqlJoinSelf() throws Exception {
     @Test
     public void testJoinWithMysqlTable() throws Exception {
         // set data size and row count for the olap table
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable tbl = (OlapTable) db.getTable("jointest");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable tbl = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "jointest");
         for (Partition partition : tbl.getPartitions()) {
             partition.updateVisibleVersion(2);
             for (MaterializedIndex mIndex : partition.getMaterializedIndices(MaterializedIndex.IndexExtState.VISIBLE)) {
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/GroupingSetsTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/GroupingSetsTest.java
index b386116980265a..b31ef47682602a 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/GroupingSetsTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/GroupingSetsTest.java
@@ -30,7 +30,7 @@ public static void beforeClass() throws Exception {
         PlanTestBase.beforeClass();
         Config.alter_scheduler_interval_millisecond = 1;
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(t0, NUM_TABLE0_ROWS);
         FeConstants.runningUnitTest = true;
     }
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/JoinTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/JoinTest.java
index 2f34fb36536e0b..d9fb1e6c72ac6a 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/JoinTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/JoinTest.java
@@ -426,12 +426,11 @@ public void testJoinAssociativityConst() throws Exception {
                 "\n" +
                 "WHERE l1.tc < s0.t1c";
         String plan = getFragmentPlan(sql);
-        assertContains(plan, "  2:Project\n" +
+        assertContains(plan, " 1:Project\n" +
                 "  |  <slot 1> : 1: v1\n" +
                 "  |  <slot 4> : 49\n" +
-                "  |  <slot 26> : '49'\n" +
                 "  |  \n" +
-                "  1:OlapScanNode");
+                "  0:OlapScanNode");
     }
 
     @Test
@@ -662,20 +661,9 @@ public void testSelectConstantFormJoin() throws Exception {
                 "limit \n" +
                 "  45;";
         String plan = getFragmentPlan(sql);
-        assertContains(plan, "9:Project\n" +
+        assertContains(plan, " 6:Project\n" +
                 "  |  <slot 3> : 3: t1c\n" +
-                "  |  <slot 21> : 21: expr\n" +
-                "  |  <slot 22> : 22: P_PARTKEY\n" +
-                "  |  <slot 23> : 23: P_NAME\n" +
-                "  |  <slot 24> : 24: P_MFGR\n" +
-                "  |  <slot 25> : 25: P_BRAND\n" +
-                "  |  <slot 26> : 26: P_TYPE\n" +
-                "  |  <slot 27> : 27: P_SIZE\n" +
-                "  |  <slot 28> : 28: P_CONTAINER\n" +
-                "  |  <slot 29> : 29: P_RETAILPRICE\n" +
-                "  |  <slot 30> : 30: P_COMMENT\n" +
-                "  |  <slot 31> : 31: PAD\n" +
-                "  |  <slot 40> : CAST(21: expr AS INT)");
+                "  |  <slot 21> : 37");
     }
 
     @Test
@@ -1125,8 +1113,8 @@ public void testShuffleHashBucket2() throws Exception {
     @Test
     public void testJoinReorderTakeEffect() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        Database db = globalStateMgr.getDb("test");
-        Table table = db.getTable("join2");
+        Database db = globalStateMgr.getLocalMetastore().getDb("test");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "join2");
         OlapTable olapTable1 = (OlapTable) table;
         try {
             setTableStatistics(olapTable1, 2);
@@ -1149,7 +1137,7 @@ public void testJoinReorderTakeEffect() throws Exception {
     public void testJoinReorderWithWithClause() throws Exception {
         connectContext.setDatabase("test");
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        Table table = globalStateMgr.getDb("test").getTable("join2");
+        Table table = globalStateMgr.getLocalMetastore().getDb("test").getTable("join2");
         OlapTable olapTable1 = (OlapTable) table;
         try {
             setTableStatistics(olapTable1, 2);
@@ -1652,7 +1640,7 @@ public void testOuterJoinEliminate() throws Exception {
     @Test
     public void testJoinReorderWithReanalyze() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        Table table = globalStateMgr.getDb("test").getTable("join2");
+        Table table = globalStateMgr.getLocalMetastore().getDb("test").getTable("join2");
         OlapTable olapTable1 = (OlapTable) table;
         try {
             setTableStatistics(olapTable1, 2);
@@ -1723,7 +1711,9 @@ public void testJoinConst() throws Exception {
                 "address as (select 1 as user_id, 'newzland' as address_name) \n" +
                 "select * from address a right join user_info b on b.user_id=a.user_id;";
         String plan = getFragmentPlan(sql);
-        assertContains(plan, "  1:Project\n" +
+        assertContains(plan, "RESULT SINK\n" +
+                "\n" +
+                "  1:Project\n" +
                 "  |  <slot 2> : NULL\n" +
                 "  |  <slot 3> : NULL\n" +
                 "  |  <slot 5> : 2\n" +
@@ -3214,4 +3204,90 @@ public void testJoinOnAnonymousSubquery() throws Exception {
                 "  |  colocate: false, reason: \n" +
                 "  |  equal join conjunct: 6: v6 = 8: v8");
     }
+
+    @Test
+    public void testOuterJoinOnConstValue() throws Exception {
+        String query = "WITH `ID_TABLE` AS (\n" +
+                "    SELECT\n" +
+                "        \"A\" AS `ID`\n" +
+                "),\n" +
+                "`MAP_TABLE` AS (\n" +
+                "    SELECT\n" +
+                "        [\"A\", \"B\", \"C\"] AS `MAP_KEYS`\n" +
+                "),\n" +
+                "`AGGED_MAP_TABLE_EX` AS (\n" +
+                "    SELECT\n" +
+                "        ARRAY_AGG(\n" +
+                "            `AGGED_MAP_TABLE`.`MAP_KEYS`\n" +
+                "        ) AS `AGGED_MAP_KEYS`\n" +
+                "    FROM\n" +
+                "        `MAP_TABLE` AS `AGGED_MAP_TABLE`\n" +
+                "),\n" +
+                "`AGGED_MAP_FIND_TABLE` AS (\n" +
+                "    SELECT\n" +
+                "        [\"A\", \"B\", \"C\"] AS `FIND_AGGED_KEY`\n" +
+                "    FROM\n" +
+                "        `AGGED_MAP_TABLE_EX`\n" +
+                "),\n" +
+                "`GROUPED_FIND_TABLE` AS (\n" +
+                "    SELECT\n" +
+                "        `GROUPED_AGGED_MAP_FIND_TABLE`.`FIND_AGGED_KEY` AS `FIND_AGGED_KEY`\n" +
+                "    FROM\n" +
+                "        `AGGED_MAP_FIND_TABLE` AS `GROUPED_AGGED_MAP_FIND_TABLE`\n" +
+                "    GROUP BY\n" +
+                "        `GROUPED_AGGED_MAP_FIND_TABLE`.`FIND_AGGED_KEY`\n" +
+                "),\n" +
+                "`AGGED_GROUPED_FIND_SEQUENCE` AS (\n" +
+                "    SELECT\n" +
+                "        `AGGED_GROUPED_FIND_TABLE`.`FIND_AGGED_KEY` AS `FIND_AGGED_KEY`,\n" +
+                "        123 AS `GROUPED_FIND_LITERAL`\n" +
+                "    FROM\n" +
+                "        `GROUPED_FIND_TABLE` AS `AGGED_GROUPED_FIND_TABLE`\n" +
+                "),\n" +
+                "`HANDLE_SEQUENCE_TABLE` AS (\n" +
+                "    SELECT\n" +
+                "        `MockTOSQL_UNNEST`.`FIND_AGGED_KEY` AS `FIND_AGGED_KEY`,\n" +
+                "        `SEQUENCE_TABLE`.`GROUPED_FIND_LITERAL` AS `GROUPED_FIND_LITERAL`\n" +
+                "    FROM\n" +
+                "        `AGGED_GROUPED_FIND_SEQUENCE` AS `SEQUENCE_TABLE`,\n" +
+                "        UNNEST(\n" +
+                "            `SEQUENCE_TABLE`.`FIND_AGGED_KEY`\n" +
+                "        ) AS MockTOSQL_UNNEST(\n" +
+                "            `FIND_AGGED_KEY`\n" +
+                "        )\n" +
+                "),\n" +
+                "`JOINED_SEQUENCE` AS (\n" +
+                "    SELECT\n" +
+                "        `R_TABLE`.`ID` AS `JOINED_ID`,\n" +
+                "        `HANDLE_SEQUENCE_TABLE_JOINED`.`GROUPED_FIND_LITERAL` AS `JOINED_LITERAL`\n" +
+                "    FROM\n" +
+                "        `HANDLE_SEQUENCE_TABLE` AS `HANDLE_SEQUENCE_TABLE_JOINED`\n" +
+                "        LEFT JOIN `ID_TABLE` AS `R_TABLE` ON (\n" +
+                "            `HANDLE_SEQUENCE_TABLE_JOINED`.`FIND_AGGED_KEY` = `R_TABLE`.`ID`\n" +
+                "        )\n" +
+                "),\n" +
+                "`JOINED_AGGED_SEQUENCE` AS (\n" +
+                "    SELECT\n" +
+                "        `JOINED_TABLE_SEQUENCE`.`JOINED_LITERAL` AS `JOINED_LITERAL`,\n" +
+                "            `JOINED_TABLE_SEQUENCE`.`JOINED_ID`\n" +
+                "         AS `JOINED_TABLE_AGGED_SEQUENCE`\n" +
+                "    FROM\n" +
+                "        `JOINED_SEQUENCE` AS `JOINED_TABLE_SEQUENCE`\n" +
+                ")\n" +
+                "SELECT\n" +
+                "    `JOINED_AGGED_SEQUENCE_R_TABLE`.`JOINED_TABLE_AGGED_SEQUENCE` AS `RENAME_9`\n" +
+                "FROM\n" +
+                "    `AGGED_GROUPED_FIND_SEQUENCE` AS `AGGED_GROUP_FIND_L_TABLE`\n" +
+                "    LEFT JOIN `JOINED_AGGED_SEQUENCE` AS `JOINED_AGGED_SEQUENCE_R_TABLE` ON (\n" +
+                "        `AGGED_GROUP_FIND_L_TABLE`.`GROUPED_FIND_LITERAL` = `JOINED_AGGED_SEQUENCE_R_TABLE`.`JOINED_LITERAL`\n" +
+                "    );";
+        String plan = getFragmentPlan(query);
+        //outer join can not use const expr replacement optimization because it may generate null values
+        assertContains(plan, "10:Project\n" +
+                "  |  <slot 29> : 29: expr\n" +
+                "  |  \n" +
+                "  9:NESTLOOP JOIN\n" +
+                "  |  join op: RIGHT OUTER JOIN\n" +
+                "  |  colocate: false, reason:");
+    }
 }
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/LimitTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/LimitTest.java
index 9a40c8050172c3..b39d74674c0526 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/LimitTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/LimitTest.java
@@ -787,7 +787,7 @@ public void testLimitPrune() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
 
         // We need to let some tablets have data, some tablets don't data
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         MaterializedIndex index = t0.getPartitions().stream().findFirst().get().getBaseIndex();
         LocalTablet tablets = (LocalTablet) index.getTablets().get(0);
         Replica replica = tablets.getSingleReplica();
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/LowCardinalityArrayTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/LowCardinalityArrayTest.java
index 8d09b99d5895da..9c46cb51843b52 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/LowCardinalityArrayTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/LowCardinalityArrayTest.java
@@ -260,16 +260,13 @@ public void testArrayProjectOrderLimit() throws Exception {
                 "       reverse(a1), array_slice(a2, 2, 4), cardinality(a2)\n" +
                 "from s2 where a1[1] = 'Jiangsu' and a2[2] = 'GD' order by v1 limit 2;";
         String plan = getVerboseExplain(sql);
-        Assert.assertTrue(plan, plan.contains("  Global Dict Exprs:\n" +
-                "    23: DictDefine(22: a2, [<place-holder>])\n" +
-                "    24: DictDefine(21: a1, [<place-holder>])\n" +
-                "    25: DictDefine(21: a1, [<place-holder>])\n" +
-                "    26: DictDefine(22: a2, [<place-holder>])\n" +
-                "    27: DictDefine(21: a1, [<place-holder>])\n" +
-                "    28: DictDefine(22: a2, [<place-holder>])\n" +
-                "\n" +
-                "  5:Decode\n" +
-                "  |  <dict id 23> : <string id 6>"));
+        Assert.assertTrue(plan, plan.contains(" Global Dict Exprs:\n" +
+                "    25: DictDefine(24: a2, [<place-holder>])\n" +
+                "    26: DictDefine(23: a1, [<place-holder>])\n" +
+                "    27: DictDefine(23: a1, [<place-holder>])\n" +
+                "    28: DictDefine(24: a2, [<place-holder>])\n" +
+                "    29: DictDefine(23: a1, [<place-holder>])\n" +
+                "    30: DictDefine(24: a2, [<place-holder>])"));
     }
 
     @Test
@@ -292,15 +289,21 @@ public void testArrayShuffleProject() throws Exception {
                 "from supplier_nullable xx join[shuffle] table_int t on S_NATIONKEY = id_int " +
                 "where S_ADDRESS[0] = 'a'";
         String plan = getVerboseExplain(sql);
-        Assert.assertTrue(plan, plan.contains("  Global Dict Exprs:\n" +
-                "    19: DictDefine(18: S_ADDRESS, [<place-holder>])\n" +
+        Assert.assertTrue(plan, plan.contains("Global Dict Exprs:\n" +
+                "    20: DictDefine(19: S_ADDRESS, [<place-holder>])\n" +
+                "    21: DictDefine(19: S_ADDRESS, [<place-holder>])\n" +
+                "    22: DictDefine(19: S_ADDRESS, [<place-holder>])\n" +
                 "\n" +
-                "  6:Project\n" +
+                "  1:Project\n" +
                 "  |  output columns:\n" +
-                "  |  11 <-> DictDecode(18: S_ADDRESS, [<place-holder>], array_min(18: S_ADDRESS))\n" +
-                "  |  12 <-> DictDecode(19: expr, [<place-holder>])\n" +
-                "  |  13 <-> DictDecode(18: S_ADDRESS, [<place-holder>], array_max(18: S_ADDRESS))\n" +
-                "  |  14 <-> [17: array_length, INT, true]\n" +
+                "  |  4 <-> [4: S_NATIONKEY, INT, false]\n" +
+                "  |  18 <-> array_length[([19: S_ADDRESS, ARRAY<INT>, true]); args: INVALID_TYPE; result: INT; args " +
+                "nullable: true; result nullable: true]\n" +
+                "  |  20 <-> array_distinct(array_slice(19: S_ADDRESS, 2, 4))[0]\n" +
+                "  |  21 <-> array_max[([19: S_ADDRESS, ARRAY<INT>, true]); args: INVALID_TYPE; result: INT; args " +
+                "nullable: true; result nullable: true]\n" +
+                "  |  22 <-> array_min[([19: S_ADDRESS, ARRAY<INT>, true]); args: INVALID_TYPE; result: INT; args " +
+                "nullable: true; result nullable: true]\n" +
                 "  |  cardinality: 1"));
     }
 
@@ -317,38 +320,56 @@ public void testArrayShuffleProject2() throws Exception {
                 "from supplier_nullable xx join[shuffle] table_int t on S_NATIONKEY = id_int " +
                 "where S_ADDRESS[0] = 'a'";
         String plan = getVerboseExplain(sql);
-        Assert.assertTrue(plan, plan.contains("  Global Dict Exprs:\n" +
-                "    24: DictDefine(23: S_ADDRESS, [<place-holder>])\n" +
-                "    25: DictDefine(23: S_ADDRESS, [<place-holder>])\n" +
-                "    26: DictDefine(23: S_ADDRESS, [<place-holder>])\n" +
+        Assert.assertTrue(plan, plan.contains(" Global Dict Exprs:\n" +
+                "    32: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
+                "    27: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
+                "    28: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
+                "    29: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
+                "    30: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
+                "    31: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
                 "\n" +
                 "  1:Project\n" +
                 "  |  output columns:\n" +
                 "  |  4 <-> [4: S_NATIONKEY, INT, false]\n" +
-                "  |  23 <-> [23: S_ADDRESS, ARRAY<INT>, true]\n" +
-                "  |  24 <-> reverse(array_distinct(reverse(23: S_ADDRESS)))[2]\n" +
-                "  |  25 <-> array_distinct(array_slice(23: S_ADDRESS, 2, 4))[0]\n" +
-                "  |  26 <-> array_slice(23: S_ADDRESS, 1, 2)[0]\n" +
+                "  |  26 <-> [26: S_ADDRESS, ARRAY<INT>, true]\n" +
+                "  |  27 <-> array_max[([35: reverse, ARRAY<INT>, true]); args: INVALID_TYPE; result: INT; args " +
+                "nullable: true; result nullable: true]\n" +
+                "  |  28 <-> 35: reverse[2]\n" +
+                "  |  29 <-> array_min[([26: S_ADDRESS, ARRAY<INT>, true]); args: INVALID_TYPE; result: INT; args " +
+                "nullable: true; result nullable: true]\n" +
+                "  |  30 <-> array_distinct(array_slice(26: S_ADDRESS, 2, 4))[0]\n" +
+                "  |  31 <-> array_slice(26: S_ADDRESS, 1, 2)[0]\n" +
+                "  |  32 <-> array_max[([26: S_ADDRESS, ARRAY<INT>, true]); args: INVALID_TYPE; result: INT; args " +
+                "nullable: true; result nullable: true]\n" +
+                "  |  common expressions:\n" +
+                "  |  33 <-> reverse[([26: S_ADDRESS, ARRAY<INT>, true]); args: INVALID_TYPE; result: ARRAY<INT>; " +
+                "args nullable: true; result nullable: true]\n" +
+                "  |  34 <-> array_distinct[([33: reverse, ARRAY<INT>, true]); args: INVALID_TYPE; result: " +
+                "ARRAY<INT>; args nullable: true; result nullable: true]\n" +
+                "  |  35 <-> reverse[([34: array_distinct, ARRAY<INT>, true]); args: INVALID_TYPE; result: " +
+                "ARRAY<INT>; args nullable: true; result nullable: true]\n" +
                 "  |  cardinality: 1"));
 
-        assertContains(plan, "  Global Dict Exprs:\n" +
-                "    24: DictDefine(23: S_ADDRESS, [<place-holder>])\n" +
-                "    25: DictDefine(23: S_ADDRESS, [<place-holder>])\n" +
-                "    26: DictDefine(23: S_ADDRESS, [<place-holder>])\n" +
+        assertContains(plan, " Global Dict Exprs:\n" +
+                "    32: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
+                "    27: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
+                "    28: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
+                "    29: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
+                "    30: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
+                "    31: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
                 "\n" +
                 "  6:Project\n" +
                 "  |  output columns:\n" +
-                "  |  11 <-> DictDecode(23: S_ADDRESS, [<place-holder>], array_min(23: S_ADDRESS))\n" +
-                "  |  12 <-> DictDecode(25: expr, [<place-holder>])\n" +
-                "  |  13 <-> DictDecode(26: expr, [hex(<place-holder>)])\n" +
-                "  |  14 <-> DictDecode(23: S_ADDRESS, [upper(<place-holder>)], array_max(23: S_ADDRESS))\n" +
-                "  |  15 <-> DictDecode(23: S_ADDRESS, [<place-holder>], array_distinct(array_filter(23: S_ADDRESS, " +
+                "  |  11 <-> DictDecode(29: array_min, [<place-holder>])\n" +
+                "  |  12 <-> DictDecode(30: expr, [<place-holder>])\n" +
+                "  |  13 <-> DictDecode(31: expr, [hex(<place-holder>)])\n" +
+                "  |  14 <-> DictDecode(32: array_max, [upper(<place-holder>)])\n" +
+                "  |  15 <-> DictDecode(26: S_ADDRESS, [<place-holder>], array_distinct(array_filter(26: S_ADDRESS, " +
                 "[TRUE,FALSE])))\n" +
-                "  |  16 <-> DictDecode(23: S_ADDRESS, [<place-holder>], reverse(array_distinct(reverse(23: " +
+                "  |  16 <-> DictDecode(26: S_ADDRESS, [<place-holder>], reverse(array_distinct(reverse(26: " +
                 "S_ADDRESS))))\n" +
-                "  |  17 <-> DictDecode(23: S_ADDRESS, [<place-holder>], array_max(reverse(array_distinct(reverse(23:" +
-                " S_ADDRESS)))))\n" +
-                "  |  18 <-> DictDecode(24: expr, [<place-holder>])\n" +
+                "  |  17 <-> DictDecode(27: array_max, [<place-holder>])\n" +
+                "  |  18 <-> DictDecode(28: expr, [<place-holder>])\n" +
                 "  |  cardinality: 1");
     }
 
@@ -373,67 +394,79 @@ public void testArrayShuffleProjectStringCountDistinct() throws Exception {
                 "from supplier_nullable xx join[shuffle] table_int t on S_NATIONKEY = id_int " +
                 "where S_ADDRESS[0] = 'a' ) as yyy";
         String plan = getVerboseExplain(sql);
-        assertContains(plan, "  Global Dict Exprs:\n" +
-                "    43: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    44: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
+        assertContains(plan, " Global Dict Exprs:\n" +
+                "    48: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    47: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
                 "\n" +
                 "  10:Decode\n" +
-                "  |  <dict id 43> : <string id 23>\n" +
-                "  |  <dict id 44> : <string id 24>\n" +
+                "  |  <dict id 47> : <string id 23>\n" +
+                "  |  <dict id 48> : <string id 24>\n" +
                 "  |  cardinality: 1");
-        Assert.assertTrue(plan, plan.contains("  Global Dict Exprs:\n" +
-                "    34: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    35: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    36: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    37: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    38: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    39: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    40: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    41: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    42: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    43: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    44: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    45: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    46: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    47: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    48: DictDefine(33: S_ADDRESS, [<place-holder>])"));
-        assertContains(plan, "  6:Project\n" +
+        Assert.assertTrue(plan, plan.contains(" Global Dict Exprs:\n" +
+                "    36: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    37: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    38: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    39: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    40: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    41: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    42: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    43: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    44: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    45: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    46: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    47: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    48: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    49: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    50: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    51: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    52: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    53: DictDefine(35: S_ADDRESS, [<place-holder>])"));
+        assertContains(plan, " 6:Project\n" +
                 "  |  output columns:\n" +
-                "  |  33 <-> [33: S_ADDRESS, ARRAY<INT>, true]\n" +
-                "  |  36 <-> DictDefine(46: expr, [<place-holder>])\n" +
-                "  |  37 <-> DictDefine(47: expr, [<place-holder>])\n" +
-                "  |  39 <-> DictDefine(48: expr, [<place-holder>])\n" +
-                "  |  40 <-> DictDefine(34: expr, [<place-holder>])\n" +
-                "  |  42 <-> DictDefine(45: expr, [<place-holder>])\n" +
+                "  |  39 <-> DictDefine(51: array_min, [<place-holder>])\n" +
+                "  |  40 <-> DictDefine(52: expr, [<place-holder>])\n" +
+                "  |  41 <-> DictDefine(53: expr, [<place-holder>])\n" +
+                "  |  42 <-> DictDefine(36: array_max, [<place-holder>])\n" +
+                "  |  43 <-> DictDefine(37: expr, [<place-holder>])\n" +
+                "  |  44 <-> DictDefine(38: expr, [<place-holder>])\n" +
+                "  |  45 <-> DictDefine(49: array_max, [<place-holder>])\n" +
+                "  |  46 <-> DictDefine(50: expr, [<place-holder>])\n" +
                 "  |  cardinality: 1");
-        assertContains(plan, "  Global Dict Exprs:\n" +
-                "    48: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    34: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    45: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    46: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "    47: DictDefine(33: S_ADDRESS, [<place-holder>])\n" +
-                "\n" +
-                "  1:Project\n" +
+        assertContains(plan, " Global Dict Exprs:\n" +
+                "    49: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    50: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    51: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    52: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    36: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    53: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    37: DictDefine(35: S_ADDRESS, [<place-holder>])\n" +
+                "    38: DictDefine(35: S_ADDRESS, [<place-holder>])");
+        assertContains(plan, " 1:Project\n" +
                 "  |  output columns:\n" +
                 "  |  4 <-> [4: S_NATIONKEY, INT, false]\n" +
-                "  |  33 <-> [33: S_ADDRESS, ARRAY<INT>, true]\n" +
-                "  |  34 <-> 51: reverse[1]\n" +
-                "  |  45 <-> 51: reverse[2]\n" +
-                "  |  46 <-> array_distinct(array_slice(33: S_ADDRESS, 2, 4))[0]\n" +
-                "  |  47 <-> array_slice(33: S_ADDRESS, 1, 2)[0]\n" +
-                "  |  48 <-> array_distinct(array_filter(33: S_ADDRESS, [TRUE,FALSE]))[3]\n" +
+                "  |  36 <-> array_max[([35: S_ADDRESS, ARRAY<INT>, true]); args: INVALID_TYPE; result: INT; args " +
+                "nullable: true; result nullable: true]\n" +
+                "  |  37 <-> array_distinct(array_filter(35: S_ADDRESS, [TRUE,FALSE]))[3]\n" +
+                "  |  38 <-> 56: reverse[1]\n" +
+                "  |  49 <-> array_max[([56: reverse, ARRAY<INT>, true]); args: INVALID_TYPE; result: INT; args " +
+                "nullable: true; result nullable: true]\n" +
+                "  |  50 <-> 56: reverse[2]\n" +
+                "  |  51 <-> array_min[([35: S_ADDRESS, ARRAY<INT>, true]); args: INVALID_TYPE; result: INT; args " +
+                "nullable: true; result nullable: true]\n" +
+                "  |  52 <-> array_distinct(array_slice(35: S_ADDRESS, 2, 4))[0]\n" +
+                "  |  53 <-> array_slice(35: S_ADDRESS, 1, 2)[0]\n" +
                 "  |  common expressions:\n" +
-                "  |  49 <-> reverse[([33: S_ADDRESS, ARRAY<INT>, true]); args: INVALID_TYPE; result: ARRAY<INT>; " +
+                "  |  54 <-> reverse[([35: S_ADDRESS, ARRAY<INT>, true]); args: INVALID_TYPE; result: ARRAY<INT>; " +
                 "args nullable: true; result nullable: true]\n" +
-                "  |  50 <-> array_distinct[([49: reverse, ARRAY<INT>, true]); args: INVALID_TYPE; result: " +
+                "  |  55 <-> array_distinct[([54: reverse, ARRAY<INT>, true]); args: INVALID_TYPE; result: " +
                 "ARRAY<INT>; args nullable: true; result nullable: true]\n" +
-                "  |  51 <-> reverse[([50: array_distinct, ARRAY<INT>, true]); args: INVALID_TYPE; result: " +
+                "  |  56 <-> reverse[([55: array_distinct, ARRAY<INT>, true]); args: INVALID_TYPE; result: " +
                 "ARRAY<INT>; args nullable: true; result nullable: true]\n" +
                 "  |  cardinality: 1");
-        assertContains(plan, "  0:OlapScanNode\n" +
+        assertContains(plan, "0:OlapScanNode\n" +
                 "     table: supplier_nullable, rollup: supplier_nullable\n" +
                 "     preAggregation: on\n" +
-                "     Predicates: DictDecode(33: S_ADDRESS, [<place-holder> = 'a'], 33: S_ADDRESS[0])");
+                "     Predicates: DictDecode(35: S_ADDRESS, [<place-holder> = 'a'], 35: S_ADDRESS[0])");
     }
 
     @Test
@@ -451,19 +484,20 @@ public void testArrayShuffleProjectStringProject() throws Exception {
                 "from supplier_nullable xx join[shuffle] table_int t on S_NATIONKEY = id_int " +
                 "where S_ADDRESS[0] = 'a' ) as yyy";
         String plan = getVerboseExplain(sql);
-        Assert.assertTrue(plan, plan.contains("  Global Dict Exprs:\n" +
-                "    26: DictDefine(25: S_ADDRESS, [<place-holder>])\n" +
-                "    27: DictDefine(25: S_ADDRESS, [<place-holder>])\n" +
-                "    28: DictDefine(25: S_ADDRESS, [<place-holder>])"));
-
-        assertContains(plan, "  6:Project\n" +
+        Assert.assertTrue(plan, plan.contains(" Global Dict Exprs:\n" +
+                "    27: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
+                "    28: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
+                "    29: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
+                "    30: DictDefine(26: S_ADDRESS, [<place-holder>])\n" +
+                "    31: DictDefine(26: S_ADDRESS, [<place-holder>])"));
+
+        assertContains(plan, "6:Project\n" +
                 "  |  output columns:\n" +
-                "  |  16 <-> DictDecode(25: S_ADDRESS, [upper(<place-holder>)], array_min(25: S_ADDRESS))\n" +
-                "  |  17 <-> DictDecode(26: expr, [ltrim(<place-holder>)])\n" +
-                "  |  18 <-> DictDecode(27: expr, [if(CAST(<place-holder> AS BOOLEAN), 'a', 'b')])\n" +
-                "  |  19 <-> DictDecode(25: S_ADDRESS, [lower(<place-holder>)], array_max(25: S_ADDRESS))\n" +
-                "  |  20 <-> DictDecode(28: expr, [concat(<place-holder>)])\n" +
-                "  |  cardinality: 1");
+                "  |  16 <-> DictDecode(31: array_min, [upper(<place-holder>)])\n" +
+                "  |  17 <-> DictDecode(27: expr, [ltrim(<place-holder>)])\n" +
+                "  |  18 <-> DictDecode(28: expr, [if(CAST(<place-holder> AS BOOLEAN), 'a', 'b')])\n" +
+                "  |  19 <-> DictDecode(29: array_max, [lower(<place-holder>)])\n" +
+                "  |  20 <-> DictDecode(30: expr, [concat(<place-holder>)])");
     }
 
     @Test
@@ -656,31 +690,25 @@ public void testAggreagateOrUnique() throws Exception {
                 "       reverse(a1), array_slice(a2, 2, 4), cardinality(a2)\n" +
                 "from s4 where a1[1] = 'Jiangsu' and a2[2] = 'GD' order by v1 limit 2;";
         String plan = getVerboseExplain(sql);
-        Assert.assertTrue(plan, plan.contains("  Global Dict Exprs:\n" +
-                "    23: DictDefine(22: a2, [<place-holder>])\n" +
-                "    24: DictDefine(21: a1, [<place-holder>])\n" +
-                "    25: DictDefine(21: a1, [<place-holder>])\n" +
-                "    26: DictDefine(22: a2, [<place-holder>])\n" +
-                "    27: DictDefine(21: a1, [<place-holder>])\n" +
-                "    28: DictDefine(22: a2, [<place-holder>])\n" +
-                "\n" +
-                "  5:Decode\n" +
-                "  |  <dict id 23> : <string id 6>"));
+        Assert.assertTrue(plan, plan.contains(" Global Dict Exprs:\n" +
+                "    25: DictDefine(24: a2, [<place-holder>])\n" +
+                "    26: DictDefine(23: a1, [<place-holder>])\n" +
+                "    27: DictDefine(23: a1, [<place-holder>])\n" +
+                "    28: DictDefine(24: a2, [<place-holder>])\n" +
+                "    29: DictDefine(23: a1, [<place-holder>])\n" +
+                "    30: DictDefine(24: a2, [<place-holder>])"));
 
         sql = "select array_length(a1), array_max(a2), array_min(a1), array_distinct(a1), array_sort(a2),\n" +
                 "       reverse(a1), array_slice(a2, 2, 4), cardinality(a2)\n" +
                 "from s5 where a1[1] = 'Jiangsu' and a2[2] = 'GD' order by v1 limit 2;";
         plan = getVerboseExplain(sql);
-        Assert.assertTrue(plan, plan.contains("  Global Dict Exprs:\n" +
-                "    23: DictDefine(22: a2, [<place-holder>])\n" +
-                "    24: DictDefine(21: a1, [<place-holder>])\n" +
-                "    25: DictDefine(21: a1, [<place-holder>])\n" +
-                "    26: DictDefine(22: a2, [<place-holder>])\n" +
-                "    27: DictDefine(21: a1, [<place-holder>])\n" +
-                "    28: DictDefine(22: a2, [<place-holder>])\n" +
-                "\n" +
-                "  5:Decode\n" +
-                "  |  <dict id 23> : <string id 6>"));
+        Assert.assertTrue(plan, plan.contains("Global Dict Exprs:\n" +
+                "    25: DictDefine(24: a2, [<place-holder>])\n" +
+                "    26: DictDefine(23: a1, [<place-holder>])\n" +
+                "    27: DictDefine(23: a1, [<place-holder>])\n" +
+                "    28: DictDefine(24: a2, [<place-holder>])\n" +
+                "    29: DictDefine(23: a1, [<place-holder>])\n" +
+                "    30: DictDefine(24: a2, [<place-holder>])"));
     }
 
     @Test
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/MockTpchStatisticStorage.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/MockTpchStatisticStorage.java
index f55afc7cee70ab..453631b3e0eb1e 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/MockTpchStatisticStorage.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/MockTpchStatisticStorage.java
@@ -25,7 +25,6 @@
 import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.optimizer.statistics.ColumnStatistic;
 import com.starrocks.sql.optimizer.statistics.StatisticStorage;
-import com.starrocks.sql.optimizer.statistics.TableStatistic;
 import com.starrocks.statistic.BasicStatsMeta;
 import com.starrocks.statistic.StatsConstants;
 import org.apache.commons.collections4.map.CaseInsensitiveMap;
@@ -36,6 +35,7 @@
 import java.util.Collection;
 import java.util.List;
 import java.util.Map;
+import java.util.Optional;
 import java.util.stream.Collectors;
 
 import static com.starrocks.sql.optimizer.Utils.getLongFromDateTime;
@@ -43,7 +43,7 @@
 import static java.lang.Double.POSITIVE_INFINITY;
 
 public class MockTpchStatisticStorage implements StatisticStorage {
-    private final Map<Long, TableStatistic> rowCountStats;
+    private final Map<Long, Optional<Long>> rowCountStats;
     private final Map<String, Map<String, ColumnStatistic>> tableStatistics;
 
     private final int scale;
@@ -58,66 +58,65 @@ public MockTpchStatisticStorage(ConnectContext connectContext, int scale) {
 
     private void mockTpchTableStats(ConnectContext connectContext, int scale) {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        Database database = globalStateMgr.getDb("test");
+        Database database = globalStateMgr.getLocalMetastore().getDb("test");
 
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("region");
-        rowCountStats.put(t0.getId(), new TableStatistic(t0.getId(), t0.getPartition("region").getId(),
-                5L));
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("region");
+        rowCountStats.put(t0.getId(), Optional.of(5L));
         GlobalStateMgr.getCurrentState().getAnalyzeMgr().addBasicStatsMeta(new BasicStatsMeta(database.getId(), t0.getId(), null,
-                        StatsConstants.AnalyzeType.FULL,
-                        LocalDateTime.of(2020, 1, 1, 1, 1, 1),
-                        Maps.newHashMap()));
+                StatsConstants.AnalyzeType.FULL,
+                LocalDateTime.of(2020, 1, 1, 1, 1, 1),
+                Maps.newHashMap()));
 
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("nation");
-        rowCountStats.put(t1.getId(), new TableStatistic(t1.getId(), t1.getPartition("nation").getId(),
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("nation");
+        rowCountStats.put(t1.getId(), Optional.of(
                 25L));
         GlobalStateMgr.getCurrentState().getAnalyzeMgr().addBasicStatsMeta(new BasicStatsMeta(database.getId(), t1.getId(), null,
                 StatsConstants.AnalyzeType.FULL,
                 LocalDateTime.of(2020, 1, 1, 1, 1, 1),
                 Maps.newHashMap()));
 
-        OlapTable t2 = (OlapTable) globalStateMgr.getDb("test").getTable("supplier");
-        rowCountStats.put(t2.getId(), new TableStatistic(t2.getId(), t2.getPartition("supplier").getId(),
+        OlapTable t2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("supplier");
+        rowCountStats.put(t2.getId(), Optional.of(
                 10000L * scale));
         GlobalStateMgr.getCurrentState().getAnalyzeMgr().addBasicStatsMeta(new BasicStatsMeta(database.getId(), t2.getId(), null,
                 StatsConstants.AnalyzeType.FULL,
                 LocalDateTime.of(2020, 1, 1, 1, 1, 1),
                 Maps.newHashMap()));
 
-        OlapTable t3 = (OlapTable) globalStateMgr.getDb("test").getTable("customer");
-        rowCountStats.put(t3.getId(), new TableStatistic(t3.getId(), t3.getPartition("customer").getId(),
+        OlapTable t3 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("customer");
+        rowCountStats.put(t3.getId(), Optional.of(
                 150000L * scale));
         GlobalStateMgr.getCurrentState().getAnalyzeMgr().addBasicStatsMeta(new BasicStatsMeta(database.getId(), t3.getId(), null,
                 StatsConstants.AnalyzeType.FULL,
                 LocalDateTime.of(2020, 1, 1, 1, 1, 1),
                 Maps.newHashMap()));
 
-        OlapTable t4 = (OlapTable) globalStateMgr.getDb("test").getTable("part");
-        rowCountStats.put(t4.getId(), new TableStatistic(t4.getId(), t4.getPartition("part").getId(),
+        OlapTable t4 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("part");
+        rowCountStats.put(t4.getId(), Optional.of(
                 200000L * scale));
         GlobalStateMgr.getCurrentState().getAnalyzeMgr().addBasicStatsMeta(new BasicStatsMeta(database.getId(), t4.getId(), null,
                 StatsConstants.AnalyzeType.FULL,
                 LocalDateTime.of(2020, 1, 1, 1, 1, 1),
                 Maps.newHashMap()));
 
-        OlapTable t5 = (OlapTable) globalStateMgr.getDb("test").getTable("partsupp");
-        rowCountStats.put(t5.getId(), new TableStatistic(t5.getId(), t5.getPartition("partsupp").getId(),
+        OlapTable t5 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("partsupp");
+        rowCountStats.put(t5.getId(), Optional.of(
                 800000L * scale));
         GlobalStateMgr.getCurrentState().getAnalyzeMgr().addBasicStatsMeta(new BasicStatsMeta(database.getId(), t5.getId(), null,
                 StatsConstants.AnalyzeType.FULL,
                 LocalDateTime.of(2020, 1, 1, 1, 1, 1),
                 Maps.newHashMap()));
 
-        OlapTable t6 = (OlapTable) globalStateMgr.getDb("test").getTable("orders");
-        rowCountStats.put(t6.getId(), new TableStatistic(t6.getId(), t6.getPartition("orders").getId(),
+        OlapTable t6 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("orders");
+        rowCountStats.put(t6.getId(), Optional.of(
                 1500000L * scale));
         GlobalStateMgr.getCurrentState().getAnalyzeMgr().addBasicStatsMeta(new BasicStatsMeta(database.getId(), t6.getId(), null,
                 StatsConstants.AnalyzeType.FULL,
                 LocalDateTime.of(2020, 1, 1, 1, 1, 1),
                 Maps.newHashMap()));
 
-        OlapTable t7 = (OlapTable) globalStateMgr.getDb("test").getTable("lineitem");
-        rowCountStats.put(t7.getId(), new TableStatistic(t7.getId(), t7.getPartition("lineitem").getId(),
+        OlapTable t7 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("lineitem");
+        rowCountStats.put(t7.getId(), Optional.of(
                 6000000L * scale));
         GlobalStateMgr.getCurrentState().getAnalyzeMgr().addBasicStatsMeta(new BasicStatsMeta(database.getId(), t7.getId(), null,
                 StatsConstants.AnalyzeType.FULL,
@@ -326,7 +325,7 @@ private void mockTpchStatistics() {
     }
 
     @Override
-    public Map<Long, TableStatistic> getTableStatistics(Long tableId, Collection<Partition> partitions) {
+    public Map<Long, Optional<Long>> getTableStatistics(Long tableId, Collection<Partition> partitions) {
         return partitions.stream().collect(Collectors.toMap(Partition::getId, p -> rowCountStats.get(tableId)));
     }
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/MultiJoinReorderTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/MultiJoinReorderTest.java
index 2c3854d9c8db86..c442c83bd3e23e 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/MultiJoinReorderTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/MultiJoinReorderTest.java
@@ -34,15 +34,15 @@ public static void beforeClass() throws Exception {
 
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
 
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(t0, 1);
 
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("t1");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t1");
         setTableStatistics(t1, 10);
-        OlapTable t2 = (OlapTable) globalStateMgr.getDb("test").getTable("t2");
+        OlapTable t2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t2");
         setTableStatistics(t2, 100000);
 
-        OlapTable t3 = (OlapTable) globalStateMgr.getDb("test").getTable("t3");
+        OlapTable t3 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t3");
         setTableStatistics(t3, 1000000000);
         connectContext.getSessionVariable().setMaxTransformReorderJoins(2);
         FeConstants.runningUnitTest = true;
@@ -478,11 +478,11 @@ void testOutputConstant() throws Exception {
         String sql = "select v from (select v1, 2 as v, 3 from t0 inner join t1 on v2 = v4) t,t2;";
         String planFragment = getFragmentPlan(sql);
         Assert.assertTrue(planFragment, planFragment.contains("9:Project\n" +
-                "  |  <slot 7> : 7: expr\n" +
+                "  |  <slot 12> : 2\n" +
                 "  |  \n" +
                 "  8:NESTLOOP JOIN\n" +
                 "  |  join op: CROSS JOIN\n" +
-                "  |  colocate: false, reason: \n"));
+                "  |  colocate: false, reason: "));
 
         sql = "select * from (select v1, 2 as v, 3 from t0 inner join t1 on v2 = v4) t,t2;";
         planFragment = getFragmentPlan(sql);
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/OrderByTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/OrderByTest.java
index 64bc53dc0e0381..3030eafd5e45fb 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/OrderByTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/OrderByTest.java
@@ -678,12 +678,22 @@ void testNotStrictOrderByExpression(String sql, String expectedPlan) throws Exce
         assertContains(plan, expectedPlan);
     }
 
+    @ParameterizedTest
+    @MethodSource("duplicateAliasSql")
+    void testDuplicateAlias(String sql, String expectedPlan) throws Exception {
+        String plan = getFragmentPlan(sql);
+        assertContains(plan, expectedPlan);
+    }
+
     private static Stream<Arguments> allOrderBySql() {
         return Stream.concat(successToStrictSql(), failToStrictSql());
     }
 
     private static Stream<Arguments> successToStrictSql() {
         List<Arguments> list = Lists.newArrayList();
+        list.add(Arguments.of("select *, v1, abs(v1) v1 from t0  order by 1", "order by: <slot 1> 1: v1 ASC"));
+        list.add(Arguments.of("select distinct *, v1, abs(v1) v1 from t0  order by 1", "order by: <slot 1> 1: v1 ASC"));
+        list.add(Arguments.of("select distinct abs(v1) v1, * from t0  order by 1", "order by: <slot 4> 4: abs ASC"));
         list.add(Arguments.of("select * from t0 order by 1", "order by: <slot 1> 1: v1 ASC"));
         list.add(Arguments.of("select abs(v1) v1, * from t0  order by 1", "order by: <slot 4> 4: abs ASC"));
         list.add(Arguments.of("select distinct * from t0  order by 1", "order by: <slot 1> 1: v1 ASC"));
@@ -705,9 +715,6 @@ private static Stream<Arguments> successToStrictSql() {
 
     private static Stream<Arguments> failToStrictSql() {
         List<Arguments> list = Lists.newArrayList();
-        list.add(Arguments.of("select *, v1, abs(v1) v1 from t0  order by 1", "order by: <slot 1> 1: v1 ASC"));
-        list.add(Arguments.of("select distinct *, v1, abs(v1) v1 from t0  order by 1", "order by: <slot 1> 1: v1 ASC"));
-        list.add(Arguments.of("select distinct abs(v1) v1, * from t0  order by 1", "order by: <slot 4> 4: abs ASC"));
         list.add(Arguments.of("select distinct *, v1, abs(v1) v1 from t0  order by v1", "order by: <slot 1> 1: v1 ASC"));
         list.add(Arguments.of("select v1, max(v2) v1 from t0 group by v1  order by abs(v1)", "order by: <slot 5> 5: abs ASC"));
         list.add(Arguments.of("select max(v2) v1, v1 from t0 group by v1  order by abs(v1)", "order by: <slot 5> 5: abs ASC"));
@@ -715,10 +722,42 @@ private static Stream<Arguments> failToStrictSql() {
         list.add(Arguments.of("select max(v2) v2, v2 from t0 group by v2  order by max(v2)", "order by: <slot 4> 4: max ASC"));
         list.add(Arguments.of("select upper(v1) v1, *, v1 from t0 order by v1", "order by: <slot 4> 4: upper ASC"));
         list.add(Arguments.of("select *, v1, upper(v1) v1 from t0 order by v1", "order by: <slot 1> 1: v1 ASC"));
-        list.add(Arguments.of("select distinct upper(v1) v1, *, v1 from t0 order by v1", "order by: <slot 1> 1: v1 ASC"));
+        list.add(Arguments.of("select distinct  v1, *, upper(v1) v1 from t0 order by v1", "order by: <slot 1> 1: v1 ASC"));
+        list.add(Arguments.of("select distinct upper(v1) v1, *, v1 from t0 order by v1", "order by: <slot 4> 4: upper ASC"));
         list.add(Arguments.of("select distinct *, v1, upper(v1) v1 from t0 order by v1", "order by: <slot 1> 1: v1 ASC"));
         list.add(Arguments.of("select distinct abs(v1) v1, v1 from t0 order by v1", "order by: <slot 4> 4: abs ASC"));
 
         return list.stream();
     }
+
+    private static Stream<Arguments> duplicateAliasSql() {
+        List<Arguments> list = Lists.newArrayList();
+        list.add(Arguments.of("select *, v1 cc, v2 cc from t0 order by v1", "order by: <slot 1> 1: v1 ASC"));
+        list.add(Arguments.of("select v1 cc, abs(v2) cc from t0 order by v1 ", "order by: <slot 1> 1: v1 ASC"));
+        list.add(Arguments.of("select distinct v1 cc, v2 cc from t0 order by v1", "order by: <slot 1> 1: v1 ASC"));
+        list.add(Arguments.of("select v1 cc, v2 cc, abs(v3) ccc from t0 order by abs(ccc)", "order by: <slot 5> 5: abs ASC"));
+        list.add(Arguments.of("select count(v1) cnt, count(v2) cnt from t0 group by v3 order by abs(v3)",
+                "3:SORT\n" +
+                        "  |  order by: <slot 6> 6: abs ASC\n" +
+                        "  |  offset: 0\n" +
+                        "  |  \n" +
+                        "  2:Project\n" +
+                        "  |  <slot 4> : 4: count\n" +
+                        "  |  <slot 5> : 5: count\n" +
+                        "  |  <slot 6> : abs(3: v3)"));
+        list.add(Arguments.of("select v1 cc, v2 cc from (select abs(v1) v1, abs(v2) v2, v3 from t0) t1 order by v3",
+                "2:SORT\n" +
+                        "  |  order by: <slot 3> 3: v3 ASC\n" +
+                        "  |  offset: 0\n" +
+                        "  |  \n" +
+                        "  1:Project\n" +
+                        "  |  <slot 3> : 3: v3\n" +
+                        "  |  <slot 4> : abs(1: v1)\n" +
+                        "  |  <slot 5> : abs(2: v2)"));
+        list.add(Arguments.of("select v1 v3, v2 cc from (select abs(v1) v1, abs(v2) v2, v3 from t0) t1 order by t1.v3",
+                "order by: <slot 4> 4: abs ASC"));
+        list.add(Arguments.of("select v1, v2 cc from (select abs(v1) v1, abs(v2) v2, v3 from t0) t1 order by t1.v3",
+                "order by: <slot 3> 3: v3 ASC"));
+        return list.stream();
+    }
 }
\ No newline at end of file
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/OuterJoinReorderTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/OuterJoinReorderTest.java
index c12b7e95e9923d..d7c5f0d4844d2d 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/OuterJoinReorderTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/OuterJoinReorderTest.java
@@ -33,7 +33,6 @@ public static void beforeClass() throws Exception {
         FeConstants.runningUnitTest = true;
     }
 
-
     @ParameterizedTest(name = "sql_{index}: {0}.")
     @MethodSource("joinAssocRuleSqls")
     void joinAssociativityRuleSql(String sql, String expectedPlan) throws Exception {
@@ -41,7 +40,6 @@ void joinAssociativityRuleSql(String sql, String expectedPlan) throws Exception
         assertContains(plan, expectedPlan);
     }
 
-
     public static Stream<Arguments> joinAssocRuleSqls() {
         List<String> sqlList = Lists.newArrayList();
         List<String> planList = Lists.newArrayList();
@@ -69,12 +67,11 @@ public static Stream<Arguments> joinAssocRuleSqls() {
                 "on (ref_2.v8 = ref_3.v10) inner join t4 as ref_4 on (ref_2.v9 = ref_4.v14) " +
                 "where (space(cast(ref_4.v15 as INT)) <= ref_4.v14) or ( ref_1.v5 = tan(cast(ref_1.v6 as DOUBLE))) " +
                 "limit 111;");
-        planList.add("13:HASH JOIN\n" +
-                "  |  join op: INNER JOIN (BUCKET_SHUFFLE)\n" +
+        planList.add("7:NESTLOOP JOIN\n" +
+                "  |  join op: INNER JOIN\n" +
                 "  |  colocate: false, reason: \n" +
-                "  |  equal join conjunct: 8: v7 = 17: cast\n" +
-                "  |  other join predicates: (CAST(space(CAST(16: v15 AS INT)) AS DOUBLE) <= CAST(15: v14 AS DOUBLE))" +
-                " OR (CAST(6: v5 AS DOUBLE) = tan(CAST(7: v6 AS DOUBLE)))");
+                "  |  other join predicates: (CAST(space(CAST(16: v15 AS INT)) AS DOUBLE) <= CAST(15: v14 AS DOUBLE)) " +
+                "OR (CAST(6: v5 AS DOUBLE) = tan(CAST(7: v6 AS DOUBLE)))");
 
         sqlList.add("select tmp.a, t0.v3 from t0 left join (select * from test_all_type, unnest(split(t1a, ',')) " +
                 "as unnest_tbl(a)) tmp on t0.v1 = tmp.a join t1 on t0.v2 = t1.v4");
@@ -107,7 +104,7 @@ public static Stream<Arguments> joinAssocRuleSqls() {
                 "  3:HASH JOIN");
         sqlList.add("select t0.* from t0 left join t1 on t0.v1 = t1.v4 join t2 on t0.v1 = t2.v7 " +
                 "where t0.v2 in (select max(v10) from t3) and t1.v5 is null;");
-        planList.add("14:HASH JOIN\n" +
+        planList.add(" 14:HASH JOIN\n" +
                 "  |  join op: LEFT SEMI JOIN (BROADCAST)\n" +
                 "  |  colocate: false, reason: \n" +
                 "  |  equal join conjunct: 2: v2 = 13: max\n" +
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/PlanFragmentWithCostTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/PlanFragmentWithCostTest.java
index 0b64ee554beb23..4cf1d667314865 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/PlanFragmentWithCostTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/PlanFragmentWithCostTest.java
@@ -64,16 +64,16 @@ public static void beforeClass() throws Exception {
         Config.alter_scheduler_interval_millisecond = 1;
 
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable table2 = (OlapTable) globalStateMgr.getDb("test").getTable("test_all_type");
+        OlapTable table2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("test_all_type");
         setTableStatistics(table2, NUM_TABLE2_ROWS);
 
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(t0, NUM_TABLE0_ROWS);
 
-        OlapTable colocateT0 = (OlapTable) globalStateMgr.getDb("test").getTable("colocate_t0");
+        OlapTable colocateT0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("colocate_t0");
         setTableStatistics(colocateT0, NUM_TABLE0_ROWS);
 
-        OlapTable lineitem = (OlapTable) globalStateMgr.getDb("test").getTable("lineitem");
+        OlapTable lineitem = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("lineitem");
         setTableStatistics(lineitem, NUM_TABLE0_ROWS * NUM_TABLE0_ROWS);
 
         StarRocksAssert starRocksAssert = new StarRocksAssert(connectContext);
@@ -181,9 +181,9 @@ public void before() {
     public void testCrossJoinBroadCast() throws Exception {
         // check cross join generate plan without exception
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable table2 = (OlapTable) globalStateMgr.getDb("test").getTable("test_all_type");
+        OlapTable table2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("test_all_type");
         setTableStatistics(table2, 20000000);
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(t0, 20000000);
 
         String sql = "select t1a,v1 from test_all_type, t0";
@@ -424,9 +424,9 @@ public void testShuffleInnerJoin() throws Exception {
         UtFrameUtils.addMockBackend(10002);
         UtFrameUtils.addMockBackend(10003);
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable table1 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable table1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(table1, 10000);
-        OlapTable table2 = (OlapTable) globalStateMgr.getDb("test").getTable("test_all_type");
+        OlapTable table2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("test_all_type");
         setTableStatistics(table2, 5000);
         String sql = "SELECT v2,t1d from t0 join test_all_type on t0.v2 = test_all_type.t1d ;";
         String plan = getFragmentPlan(sql);
@@ -469,7 +469,7 @@ public void testBroadcastInnerJoin() throws Exception {
     @Test
     public void testBroadcastInnerJoinWithCommutativity() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable table = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable table = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(table, 1000);
         String sql = "SELECT * from t0 join test_all_type on t0.v1 = test_all_type.t1d ;";
         String plan = getFragmentPlan(sql);
@@ -728,12 +728,40 @@ public void testOuterJoinPushDownPredicate() throws Exception {
                 "     PREDICATES: 5: v5 = 2, 4: v4 = 1");
     }
 
+    @Test
+    public void testPushDownIsoZonedDateTimePredicate() throws Exception {
+        String sql = "SELECT COUNT(1)\n" +
+                "  FROM test_dict\n" +
+                "  WHERE dt >= '2022-12-06T00:00:00Z'\n" +
+                "  AND dt < '2022-12-08T00:00:00Z'";
+        String plan = getFragmentPlan(sql);
+        assertContains(plan, "  0:OlapScanNode\n" +
+                "     TABLE: test_dict\n" +
+                "     PREAGGREGATION: ON\n" +
+                "     partitions=2/12\n" +
+                "     rollup: test_dict");
+    }
+
+    @Test
+    public void testPushDownIsoOffsetDateTimePredicate() throws Exception {
+        String sql = "SELECT COUNT(1)\n" +
+                "  FROM test_dict\n" +
+                "  WHERE dt >= '2022-12-06T00:00:00+01:00'\n" +
+                "  AND dt < '2022-12-08T00:00:00+01:00'";
+        String plan = getFragmentPlan(sql);
+        assertContains(plan, "  0:OlapScanNode\n" +
+                "     TABLE: test_dict\n" +
+                "     PREAGGREGATION: ON\n" +
+                "     partitions=2/12\n" +
+                "     rollup: test_dict");
+    }
+
     @Test
     public void testThriftWaitingNodeIds() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(t0, 10000000);
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("t1");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t1");
         setTableStatistics(t1, 10000);
 
         String sql = "select * from t0 inner join t1 on t0.v1 = t1.v4 and t0.v2 = t1.v5 and t0.v1 = 1 and t1.v5 = 2";
@@ -746,11 +774,11 @@ public void testThriftWaitingNodeIds() throws Exception {
     public void testIntersectReorder() throws Exception {
         // check cross join generate plan without exception
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(t0, 1000);
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("t1");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t1");
         setTableStatistics(t1, 100);
-        OlapTable t2 = (OlapTable) globalStateMgr.getDb("test").getTable("t2");
+        OlapTable t2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t2");
         setTableStatistics(t2, 1);
 
         String sql = "select v1 from t0 intersect select v7 from t2 intersect select v4 from t1";
@@ -774,10 +802,10 @@ public void testIntersectReorder() throws Exception {
     @Test
     public void testNotPushDownRuntimeFilterToSortNode() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(t0, 10);
 
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("t1");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t1");
         setTableStatistics(t1, 1000000000L);
 
         String sql = "select t0.v1 from (select v4 from t1 order by v4 limit 1000000000) as t1x " +
@@ -809,10 +837,10 @@ public void testPushMultiColumnRuntimeFiltersCrossDataExchange() throws Exceptio
         connectContext.getSessionVariable().setGlobalRuntimeFilterBuildMaxSize(0);
         connectContext.getSessionVariable().setGlobalRuntimeFilterProbeMinSize(0);
 
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(t0, 10000000L);
 
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("t1");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t1");
         setTableStatistics(t1, 1000000000L);
 
         String sql = "select * from t0 join[shuffle] t1 on t0.v2 = t1.v5 and t0.v3 = t1.v6";
@@ -835,13 +863,13 @@ public void testPushMultiColumnRuntimeFiltersCrossDataExchangeOnMultiJoins() thr
         connectContext.getSessionVariable().setGlobalRuntimeFilterBuildMaxSize(0);
         connectContext.getSessionVariable().setGlobalRuntimeFilterProbeMinSize(0);
 
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(t0, 10000000L);
 
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("t1");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t1");
         setTableStatistics(t1, 10000000L);
 
-        OlapTable t2 = (OlapTable) globalStateMgr.getDb("test").getTable("t2");
+        OlapTable t2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t2");
         setTableStatistics(t2, 10000000L);
 
         String sql = "select * from (select t1.v5 as v5, t0.v3 as v3 from t0 join[shuffle] t1 on t0.v2 = " +
@@ -878,11 +906,11 @@ public void testMergeTwoAggArgTypes() throws Exception {
     public void testPushDownRuntimeFilterAcrossSetOperationNode() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
 
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(t0, 1000);
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("t1");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t1");
         setTableStatistics(t1, 100);
-        OlapTable t2 = (OlapTable) globalStateMgr.getDb("test").getTable("t2");
+        OlapTable t2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t2");
         List<OlapTable> tables = new ArrayList<>(Arrays.asList(t0, t1, t2));
         List<String> tabletIdsStrList = new ArrayList<>();
         tables.forEach(olapTable -> tabletIdsStrList.add(Joiner.on(",")
@@ -1051,8 +1079,8 @@ public void testNotPushDownRuntimeFilterAcrossCTE() throws Exception {
         connectContext.getSessionVariable().setEnablePipelineEngine(true);
         connectContext.getSessionVariable().setCboCTERuseRatio(0);
 
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("t1");
-        OlapTable t2 = (OlapTable) globalStateMgr.getDb("test").getTable("t2");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t1");
+        OlapTable t2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t2");
         List<OlapTable> tables = new ArrayList<>(Arrays.asList(t1, t2));
         List<String> tabletIdsStrList = new ArrayList<>();
         tables.forEach(olapTable -> tabletIdsStrList.add(Joiner.on(",")
@@ -1119,8 +1147,8 @@ public void testLocalGroupingSetAgg() throws Exception {
     @Test
     public void testOverflowFilterOnColocateJoin() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("colocate1");
-        OlapTable t2 = (OlapTable) globalStateMgr.getDb("test").getTable("colocate2");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("colocate1");
+        OlapTable t2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("colocate2");
 
         StatisticStorage ss = globalStateMgr.getCurrentState().getStatisticStorage();
         new Expectations(ss) {
@@ -1150,8 +1178,8 @@ public void testOverflowFilterOnColocateJoin() throws Exception {
     @Test
     public void testPruneShuffleColumns() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("t1");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t1");
 
         StatisticStorage ss = globalStateMgr.getCurrentState().getStatisticStorage();
         new Expectations(ss) {
@@ -1227,7 +1255,7 @@ public void testDateDiffWithStringConstant() throws Exception {
     @Test
     public void testToDateToDays() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("test_all_type");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("test_all_type");
         StatisticStorage ss = GlobalStateMgr.getCurrentState().getStatisticStorage();
         new Expectations(ss) {
             {
@@ -1249,8 +1277,8 @@ public void testToDateToDays() throws Exception {
     @Test
     public void testMultiJoinColumnPruneShuffleColumnsAndGRF() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("t1");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t1");
 
         StatisticStorage ss = GlobalStateMgr.getCurrentState().getStatisticStorage();
         new Expectations(ss) {
@@ -1973,7 +2001,7 @@ public void testTimeOutOnlyOr20() throws Exception {
     @Ignore
     public void testDeepTreePredicate() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable table2 = (OlapTable) globalStateMgr.getDb("test").getTable("test_dict");
+        OlapTable table2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("test_dict");
         setTableStatistics(table2, 20000000);
 
         String sql = getSQLFile("optimized-plan/large_predicate");
@@ -1987,12 +2015,12 @@ public void testDeepTreePredicate() throws Exception {
     @Test
     public void testJoinUnreorder() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(t0, 10000000);
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("t1");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t1");
         setTableStatistics(t1, 10000);
 
-        OlapTable t2 = (OlapTable) globalStateMgr.getDb("test").getTable("t2");
+        OlapTable t2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t2");
         setTableStatistics(t1, 10);
 
         String sql = "Select * " +
@@ -2034,7 +2062,7 @@ public void testJoinUnreorder() throws Exception {
     @Test
     public void testPruneLimit() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable table2 = (OlapTable) globalStateMgr.getDb("test").getTable("lineitem_partition");
+        OlapTable table2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("lineitem_partition");
         setTableStatistics(table2, 10);
 
         new MockUp<LocalTablet>() {
@@ -2054,7 +2082,7 @@ public long getRowCount(long version) {
     @Test
     public void testPruneInvalidPredicate() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable table2 = (OlapTable) globalStateMgr.getDb("test").getTable("lineitem_partition");
+        OlapTable table2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("lineitem_partition");
         setTableStatistics(table2, 10);
 
         new MockUp<LocalTablet>() {
@@ -2304,31 +2332,27 @@ public void testPlanCost() throws Exception {
                     "from t0 join [broadcast] test_all_type " +
                     "join [shuffle] (select 1 as v1_c1 where abs(1) = 2) v1 on t1a=v1 and t1a=v1_c1";
             String plan = getVerboseExplain(sql);
-            assertContains(plan, "  11:HASH JOIN\n" +
-                    "  |  join op: INNER JOIN (PARTITIONED)\n" +
-                    "  |  equal join conjunct: [4: t1a, VARCHAR, true] = [16: cast, VARCHAR, false]\n" +
-                    "  |  build runtime filters:\n" +
-                    "  |  - filter_id = 1, build_expr = (16: cast), remote = true\n" +
-                    "  |  output columns: 1, 4\n" +
-                    "  |  cardinality: 9000\n" +
+            assertContains(plan, "10:NESTLOOP JOIN\n" +
+                    "  |  join op: CROSS JOIN\n" +
+                    "  |  cardinality: 10000\n" +
                     "  |  \n" +
-                    "  |----10:EXCHANGE\n" +
-                    "  |       distribution type: SHUFFLE\n" +
-                    "  |       partition exprs: [16: cast, VARCHAR, false]\n" +
+                    "  |----9:EXCHANGE\n" +
+                    "  |       distribution type: BROADCAST\n" +
                     "  |       cardinality: 1\n" +
                     "  |    \n" +
-                    "  6:EXCHANGE\n" +
-                    "     distribution type: SHUFFLE\n" +
-                    "     partition exprs: [4: t1a, VARCHAR, true]\n" +
-                    "     cardinality: 9000");
+                    "  5:Project\n" +
+                    "  |  output columns:\n" +
+                    "  |  1 <-> [1: v1, BIGINT, true]\n" +
+                    "  |  4 <-> [4: t1a, VARCHAR, true]\n" +
+                    "  |  cardinality: 10000");
             System.out.println(plan);
             assertContains(plan, "PLAN COST\n" +
-                    "  CPU: 1881002.0\n" +
-                    "  Memory: 288001.0");
+                    "  CPU: 4.80001312001E11\n" +
+                    "  Memory: 320201.0");
 
             assertContains(getCostExplain(sql), "PLAN COST\n" +
-                    "  CPU: 1881002.0\n" +
-                    "  Memory: 288001.0");
+                    "  CPU: 4.80001312001E11\n" +
+                    "  Memory: 320201.0");
 
             AuditEvent event = connectContext.getAuditEventBuilder().build();
             Assert.assertTrue("planMemCosts should be > 1, but: " + event.planMemCosts, event.planMemCosts > 1);
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/PlanTestBase.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/PlanTestBase.java
index 46248f4552ef94..1a0d7aef4fd603 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/PlanTestBase.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/PlanTestBase.java
@@ -967,7 +967,7 @@ public static void afterClass() {
     public static void cleanupEphemeralMVs(StarRocksAssert starRocksAssert, long startTime) throws Exception {
         String currentDb = starRocksAssert.getCtx().getDatabase();
         if (StringUtils.isNotEmpty(currentDb)) {
-            Database testDb = GlobalStateMgr.getCurrentState().getDb(currentDb);
+            Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(currentDb);
             for (MaterializedView mv : ListUtils.emptyIfNull(testDb.getMaterializedViews())) {
                 if (startTime > 0 && mv.getCreateTime() > startTime) {
                     starRocksAssert.dropMaterializedView(mv.getName());
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/PlanTestNoneDBBase.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/PlanTestNoneDBBase.java
index 683b70734e5831..3d63995d4bef89 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/PlanTestNoneDBBase.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/PlanTestNoneDBBase.java
@@ -806,7 +806,7 @@ protected void assertExceptionMsgContains(String sql, String message) {
 
     public Table getTable(String t) {
         GlobalStateMgr globalStateMgr = starRocksAssert.getCtx().getGlobalStateMgr();
-        return globalStateMgr.getDb("test").getTable(t);
+        return globalStateMgr.getLocalMetastore().getDb("test").getTable(t);
     }
 
     public OlapTable getOlapTable(String t) {
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/PruneComplexSubfieldTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/PruneComplexSubfieldTest.java
index 8d45baa9a19d42..6ff6d7548b787e 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/PruneComplexSubfieldTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/PruneComplexSubfieldTest.java
@@ -1051,17 +1051,40 @@ public void testPruneMapFromAllChild() throws Exception {
                 "          B AS (SELECT 'a' as event_key, map { 'x' :1 } as props ) \n" +
                 "SELECT * FROM A JOIN B ON A.event_key = B.event_key WHERE props [property_key] = 1;";
         String plan = getFragmentPlan(sql);
-        assertContains(plan, "  2:Project\n" +
+        assertContains(plan, " 7:NESTLOOP JOIN\n" +
+                "  |  join op: CROSS JOIN\n" +
+                "  |  colocate: false, reason: \n" +
+                "  |  \n" +
+                "  |----6:EXCHANGE\n" +
+                "  |    \n" +
+                "  2:Project\n" +
                 "  |  <slot 2> : 'a'\n" +
                 "  |  <slot 3> : 'x'\n" +
-                "  |  <slot 5> : 'a'\n" +
-                "  |  <slot 6> : map{'x':1}\n" +
                 "  |  \n" +
                 "  1:SELECT\n" +
                 "  |  predicates: map{'x':1}['x'] = 1\n" +
                 "  |  \n" +
                 "  0:UNION\n" +
                 "     constant exprs: \n" +
+                "         NULL\n" +
+                "\n" +
+                "PLAN FRAGMENT 1\n" +
+                " OUTPUT EXPRS:\n" +
+                "  PARTITION: UNPARTITIONED\n" +
+                "\n" +
+                "  STREAM DATA SINK\n" +
+                "    EXCHANGE ID: 06\n" +
+                "    UNPARTITIONED\n" +
+                "\n" +
+                "  5:Project\n" +
+                "  |  <slot 5> : 'a'\n" +
+                "  |  <slot 6> : map{'x':1}\n" +
+                "  |  \n" +
+                "  4:SELECT\n" +
+                "  |  predicates: map{'x':1}['x'] = 1\n" +
+                "  |  \n" +
+                "  3:UNION\n" +
+                "     constant exprs: \n" +
                 "         NULL");
     }
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/PushDownJoinProjectionTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/PushDownJoinProjectionTest.java
new file mode 100644
index 00000000000000..ccb7b1b436bae5
--- /dev/null
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/PushDownJoinProjectionTest.java
@@ -0,0 +1,116 @@
+// Copyright 2021-present StarRocks, Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+package com.starrocks.sql.plan;
+
+import org.junit.Test;
+
+public class PushDownJoinProjectionTest extends PlanTestBase {
+
+    @Test
+    public void testPushdown() throws Exception {
+        starRocksAssert.query("select tarray.v1, array_contains(tarray.v3, 123) " +
+                        "from t0 join tarray on(t0.v1 = tarray.v1) ")
+                .explainContains("  1:Project\n" +
+                        "  |  <slot 4> : 4: v1\n" +
+                        "  |  <slot 8> : array_contains(6: v3, 123)\n" +
+                        "  |  \n" +
+                        "  0:OlapScanNode");
+        starRocksAssert.query("select t0.v1, t0.v2, tarray.v1 as c1, array_contains(tarray.v3, 123) as c2\n" +
+                        "from t0 join tarray on(t0.v1 = tarray.v1) ")
+                .explainContains(" 2:Project\n" +
+                        "  |  <slot 4> : 4: v1\n" +
+                        "  |  <slot 8> : array_contains(6: v3, 123)\n" +
+                        "  |  \n" +
+                        "  1:OlapScanNode");
+        starRocksAssert.query("select t0.v1, t0.v2, tarray.v1 as c1, 1 + array_contains(tarray.v3, 123) " +
+                        "from t0 join tarray on(t0.v1 = tarray.v1) ")
+                .explainContains(" 2:Project\n" +
+                        "  |  <slot 4> : 4: v1\n" +
+                        "  |  <slot 8> : array_contains(6: v3, 123)\n" +
+                        "  |  \n" +
+                        "  1:OlapScanNode\n" +
+                        "     TABLE: tarray");
+        starRocksAssert.query("select t0.v1, t0.v2, array_map(tarray.v3, x -> x + 1) " +
+                        "from t0 join tarray on(t0.v1 = tarray.v1) ")
+                .explainContains("  4:Project\n" +
+                        "  |  <slot 1> : 1: v1\n" +
+                        "  |  <slot 2> : 2: v2\n" +
+                        "  |  <slot 8> : array_map(<slot 7> -> <slot 7> + 1, 6: v3)\n" +
+                        "  |  \n" +
+                        "  3:HASH JOIN");
+
+        // multiple table join
+        starRocksAssert.query("select t0.v1, t0.v2, " +
+                        "   a1.v1 as c1, array_contains(a1.v3, 123) as c2, " +
+                        "   t1.v4, t1.v5" +
+                        " from t0 " +
+                        "   join tarray a1 on(t0.v1 = a1.v1) " +
+                        "   join t1 on(t0.v1 = t1.v4) ")
+                .explainContains(" 3:Project\n" +
+                        "  |  <slot 4> : 4: v1\n" +
+                        "  |  <slot 11> : array_contains(6: v3, 123)\n" +
+                        "  |  \n" +
+                        "  2:OlapScanNode\n" +
+                        "     TABLE: tarray");
+        starRocksAssert.query("select t0.v1, t0.v2, " +
+                        "   a1.v1 as c1, array_contains(a1.v3, 123) as c2, " +
+                        "   a2.v1 as c3, map_size(a2.v3) as c4 " +
+                        " from t0 " +
+                        "   join tarray a1 on(t0.v1 = a1.v1) " +
+                        "   join tmap a2 on(t0.v1 = a2.v1) ")
+                .explainContains(" 3:Project\n" +
+                                "  |  <slot 4> : 4: v1\n" +
+                                "  |  <slot 12> : array_contains(6: v3, 123)\n" +
+                                "  |  \n" +
+                                "  2:OlapScanNode\n" +
+                                "     TABLE: tarray",
+                        " 7:Project\n" +
+                                "  |  <slot 7> : 7: v1\n" +
+                                "  |  <slot 13> : map_size(9: v3)\n" +
+                                "  |  \n" +
+                                "  6:OlapScanNode\n" +
+                                "     TABLE: tmap");
+        starRocksAssert.query("select " +
+                        "   a1.v1 as c1, array_contains(a1.v3, 123) as c2, " +
+                        "   a2.v1 as c3, array_contains(a2.v3, 456) as c4 " +
+                        " from t0 " +
+                        "   join tarray a1 on(t0.v1 = a1.v1) " +
+                        "   join tarray a2 on(t0.v1 = a2.v1) ")
+                .explainContains(" 1:Project\n" +
+                                "  |  <slot 4> : 4: v1\n" +
+                                "  |  <slot 12> : array_contains(6: v3, 123)\n" +
+                                "  |  \n" +
+                                "  0:OlapScanNode\n" +
+                                "     TABLE: tarray",
+                        "7:Project\n" +
+                                "  |  <slot 7> : 7: v1\n" +
+                                "  |  <slot 13> : array_contains(9: v3, 456)\n" +
+                                "  |  \n" +
+                                "  6:OlapScanNode\n" +
+                                "     TABLE: tarray");
+
+        // simple expression: do not pushdown
+        starRocksAssert.query("select t0.v1, t0.v2, " +
+                        "tarray.v1 as c1, 1 + tarray.v1 as c2\n" +
+                        "from t0 join tarray on(t0.v1 = tarray.v1) ")
+                .explainContains("    UNPARTITIONED\n" +
+                        "\n" +
+                        "  1:OlapScanNode\n" +
+                        "     TABLE: tarray", "-2:EXCHANGE\n" +
+                        "  |    \n" +
+                        "  0:OlapScanNode\n" +
+                        "     TABLE: t0");
+    }
+}
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/ReplayFromDumpTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/ReplayFromDumpTest.java
index 638f5498067a29..9df883b8dc9d93 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/ReplayFromDumpTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/ReplayFromDumpTest.java
@@ -321,9 +321,9 @@ public void testDecodeLimitWithProject() throws Exception {
                 getPlanFragment(getDumpInfoFromFile("query_dump/decode_limit_with_project"), null,
                         TExplainLevel.NORMAL);
         String plan = replayPair.second;
-        Assert.assertTrue(plan, plan.contains("13:Decode\n" +
-                "  |  <dict id 42> : <string id 18>\n" +
-                "  |  <dict id 43> : <string id 23>"));
+        Assert.assertTrue(plan, plan.contains(" 11:Decode\n" +
+                "  |  <dict id 41> : <string id 18>\n" +
+                "  |  <dict id 42> : <string id 23>"));
         FeConstants.USE_MOCK_DICT_MANAGER = false;
     }
 
@@ -666,7 +666,7 @@ public void testReduceJoinTransformation2() throws Exception {
         Assert.assertTrue(replayPair.second, replayPair.second.contains("38:HASH JOIN\n" +
                 "  |  join op: LEFT OUTER JOIN (BROADCAST)\n" +
                 "  |  colocate: false, reason: \n" +
-                "  |  equal join conjunct: 396: substring = 361: date\n" +
+                "  |  equal join conjunct: 398: substring = 361: date\n" +
                 "  |  other join predicates: 209: zid = 298: zid"));
     }
 
@@ -888,18 +888,16 @@ public void testNoCTEOperatorPropertyDerived() throws Exception {
         Assert.assertTrue(replayPair.second, replayPair.second.contains("23:Project\n" +
                 "  |  <slot 193> : 193: mock_081\n" +
                 "  |  <slot 194> : 194: mock_089\n" +
-                "  |  <slot 233> : 233: mock_065\n" +
-                "  |  <slot 391> : 379: case\n" +
-                "  |  <slot 395> : '1'\n" +
-                "  |  \n" +
-                "  22:Project"));
-        Assert.assertTrue(replayPair.second, replayPair.second.contains("25:SORT\n" +
-                "  |  order by: <slot 194> 194: mock_089 ASC, <slot 395> 395: case ASC, <slot 193> 193: mock_081 ASC, " +
+                "  |  <slot 391> : 391: case\n" +
+                "  |  <slot 396> : 396: rank()"));
+        Assert.assertTrue(replayPair.second, replayPair.second.contains(" 20:SORT\n" +
+                "  |  order by: <slot 194> 194: mock_089 ASC," +
+                " <slot 395> 395: case ASC, <slot 193> 193: mock_081 ASC, " +
                 "<slot 233> 233: mock_065 ASC\n" +
                 "  |  analytic partition by: 194: mock_089, 395: case, 193: mock_081\n" +
                 "  |  offset: 0\n" +
                 "  |  \n" +
-                "  24:EXCHANGE"));
+                "  19:EXCHANGE"));
     }
 
     @Test
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/ReplayWithMVFromDumpTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/ReplayWithMVFromDumpTest.java
index f1270082b24c87..e3ed342dea4e4b 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/ReplayWithMVFromDumpTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/ReplayWithMVFromDumpTest.java
@@ -127,10 +127,13 @@ public void testMock_MV_MVOnMV1() throws Exception {
     @Test
     public void testMVOnMV2() throws Exception {
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("force");
+        // TODO: How to remove the join reorder noise?
+        connectContext.getSessionVariable().disableJoinReorder();
         Pair<QueryDumpInfo, String> replayPair =
                 getPlanFragment(getDumpInfoFromFile("query_dump/materialized-view/mv_on_mv2"),
                         connectContext.getSessionVariable(), TExplainLevel.NORMAL);
         connectContext.getSessionVariable().setMaterializedViewRewriteMode("default");
+        connectContext.getSessionVariable().enableJoinReorder();
         assertContains(replayPair.second, "test_mv2");
     }
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/SelectConstTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/SelectConstTest.java
index d69c4603237ea7..10e8bf5c278702 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/SelectConstTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/SelectConstTest.java
@@ -31,8 +31,8 @@ public void testSelectConst() throws Exception {
                 "  0:UNION\n" +
                 "     constant exprs: \n" +
                 "         NULL");
-        assertPlanContains("select a from (select 1 as a, 2 as b) t", "  1:Project\n" +
-                "  |  <slot 2> : 1\n" +
+        assertPlanContains("select a from (select 1 as a, 2 as b) t", "1:Project\n" +
+                "  |  <slot 4> : 1\n" +
                 "  |  \n" +
                 "  0:UNION\n" +
                 "     constant exprs: \n" +
@@ -68,12 +68,12 @@ public void testSelectConst() throws Exception {
         assertPlanContains("select v1,v2,b from t0 inner join (select 1 as a,2 as b) t on v1 = a", "  1:Project\n" +
                 "  |  <slot 1> : 1: v1\n" +
                 "  |  <slot 2> : 2: v2\n" +
-                "  |  <slot 6> : 2\n" +
+                "  |  <slot 7> : 2\n" +
                 "  |  \n" +
                 "  0:OlapScanNode\n" +
                 "     TABLE: t0\n" +
                 "     PREAGGREGATION: ON\n" +
-                "     PREDICATES: 1: v1 = 1, 1: v1 IS NOT NULL");
+                "     PREDICATES: 1: v1 = 1");
     }
 
     @Test
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/SelectUsingAliasTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/SelectUsingAliasTest.java
index 07276608815e11..324b3f9c8fae84 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/SelectUsingAliasTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/SelectUsingAliasTest.java
@@ -227,6 +227,37 @@ public void testAmbiguous() {
                 "FROM test.t0");
     }
 
+    @Test
+    public void testAliasSameAsColumnName() throws Exception {
+        // test duplicate alias is same as column name
+        String sql = "select v1 v1, v2 + 1 v1, abs(v1) from t0";
+        String plan = getFragmentPlan(sql);
+        assertContains(plan, "1:Project\n" +
+                "  |  <slot 1> : 1: v1\n" +
+                "  |  <slot 4> : 2: v2 + 1\n" +
+                "  |  <slot 5> : abs(1: v1)");
+
+        sql = "select v1 v1, v1 v1, abs(v1) from t0";
+        plan = getFragmentPlan(sql);
+        assertContains(plan, "1:Project\n" +
+                "  |  <slot 1> : 1: v1\n" +
+                "  |  <slot 4> : abs(1: v1)");
+
+        Exception exception = Assert.assertThrows(SemanticException.class, () -> {
+            // test duplicate alias is different from column name
+            String duplicateAlias = "select v1 v1, v2 v1, abs(v1) from t0 order by v1";
+            getFragmentPlan(duplicateAlias);
+        });
+        Assert.assertTrue(exception.getMessage(), exception.getMessage().contains("Column 'v1' is ambiguous."));
+
+        exception = Assert.assertThrows(SemanticException.class, () -> {
+            // test duplicate alias is different from column name
+            String duplicateAlias = "select v1 v4, v2 + 1 v4, abs(v4) from t0";
+            getFragmentPlan(duplicateAlias);
+        });
+        Assert.assertTrue(exception.getMessage(), exception.getMessage().contains("Column v4 is ambiguous"));
+    }
+
     private void testSqlRewrite(String sql, String expected) {
         testSqlRewrite(sql, expected, true);
     }
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/SetTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/SetTest.java
index 19d84cafd59d79..17097a45ed986b 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/SetTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/SetTest.java
@@ -29,9 +29,9 @@ public class SetTest extends PlanTestBase {
     public void testValuesNodePredicate() throws Exception {
         String queryStr = "SELECT 1 AS z, MIN(a.x) FROM (select 1 as x) a WHERE abs(1) = 2";
         String explainString = getFragmentPlan(queryStr);
-        Assert.assertTrue(explainString.contains("  3:Project\n" +
-                "  |  <slot 3> : 3: min\n" +
-                "  |  <slot 4> : 1\n" +
+        Assert.assertTrue(explainString.contains("3:Project\n" +
+                "  |  <slot 4> : 4: min\n" +
+                "  |  <slot 5> : 1\n" +
                 "  |  \n" +
                 "  2:AGGREGATE (update finalize)\n" +
                 "  |  output: min(1)\n" +
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/SkewJoinTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/SkewJoinTest.java
index 4437a32bd3fc7e..e89844cc4b5069 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/SkewJoinTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/SkewJoinTest.java
@@ -42,28 +42,28 @@ public static void beforeClass() throws Exception {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
         connectContext.getSessionVariable().setEnableStatsToOptimizeSkewJoin(true);
 
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("region");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("region");
         setTableStatistics(t0, 5);
 
-        OlapTable t5 = (OlapTable) globalStateMgr.getDb("test").getTable("nation");
+        OlapTable t5 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("nation");
         setTableStatistics(t5, 25);
 
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("supplier");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("supplier");
         setTableStatistics(t1, 10000 * scale);
 
-        OlapTable t4 = (OlapTable) globalStateMgr.getDb("test").getTable("customer");
+        OlapTable t4 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("customer");
         setTableStatistics(t4, 150000 * scale);
 
-        OlapTable t6 = (OlapTable) globalStateMgr.getDb("test").getTable("part");
+        OlapTable t6 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("part");
         setTableStatistics(t6, 200000 * scale);
 
-        OlapTable t2 = (OlapTable) globalStateMgr.getDb("test").getTable("partsupp");
+        OlapTable t2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("partsupp");
         setTableStatistics(t2, 800000 * scale);
 
-        OlapTable t3 = (OlapTable) globalStateMgr.getDb("test").getTable("orders");
+        OlapTable t3 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("orders");
         setTableStatistics(t3, 1500000 * scale);
 
-        OlapTable t7 = (OlapTable) globalStateMgr.getDb("test").getTable("lineitem");
+        OlapTable t7 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("lineitem");
         setTableStatistics(t7, 6000000 * scale);
 
         starRocksAssert.withTable("create table struct_tbl(c0 INT, " +
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/StructTypePlanTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/StructTypePlanTest.java
deleted file mode 100644
index c846825c407e4a..00000000000000
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/StructTypePlanTest.java
+++ /dev/null
@@ -1,338 +0,0 @@
-// Copyright 2021-present StarRocks, Inc. All rights reserved.
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     https://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-package com.starrocks.sql.plan;
-
-import com.starrocks.common.FeConstants;
-import com.starrocks.utframe.StarRocksAssert;
-import org.junit.Before;
-import org.junit.BeforeClass;
-import org.junit.Test;
-
-public class StructTypePlanTest extends PlanTestBase {
-
-    @BeforeClass
-    public static void beforeClass() throws Exception {
-        PlanTestBase.beforeClass();
-        StarRocksAssert starRocksAssert = new StarRocksAssert(connectContext);
-        FeConstants.runningUnitTest = true;
-        starRocksAssert.withTable("create table test(c0 INT, " +
-                "c1 struct<a int, b array<struct<a int, b int>>>," +
-                "c2 struct<a int, b int>," +
-                "c3 struct<a int, b int, c struct<a int, b int>, d array<int>>) " +
-                "duplicate key(c0) distributed by hash(c0) buckets 1 " +
-                "properties('replication_num'='1');");
-        starRocksAssert.withTable("create table test1(c0 INT, " +
-                "c1 struct<a int, b array<struct<a int, b int>>>," +
-                "c2 struct<a int, b int>," +
-                "c2_0 struct<a int, b varchar(10)>, " +
-                "c3 struct<a int, b int, c struct<a int, b int>, d array<int>>) " +
-                "duplicate key(c0) distributed by hash(c0) buckets 1 " +
-                "properties('replication_num'='1');");
-        starRocksAssert.withTable("create table array_struct_nest(c1 int, " +
-                "c2 array<struct<c2_sub1 int, c2_sub2 int>>, " +
-                "c3 struct<c3_sub1 array<struct<c3_sub1_sub1 int, c3_sub1_sub2 int>>, c3_sub2 int>) " +
-                "duplicate key(c1) distributed by hash(c1) buckets 1 " +
-                "properties('replication_num'='1');");
-        starRocksAssert.withTable("create table index_struct_nest(c1 int,\n" +
-                "index_struct array<struct<`index` bigint(20), char_col varchar(1048576)>>)\n" +
-                "duplicate key(c1) distributed by hash(c1) buckets 1\n" +
-                "properties('replication_num'='1')");
-        FeConstants.runningUnitTest = false;
-    }
-
-    @Before
-    public void setup() throws Exception {
-        connectContext.getSessionVariable().setEnablePruneComplexTypes(true);
-        connectContext.getSessionVariable().setEnablePruneComplexTypesInUnnest(true);
-        connectContext.getSessionVariable().setCboPruneSubfield(true);
-    }
-
-    @Test
-    public void testStruct() throws Exception {
-        String sql = "select * from test1 union all select * from test1";
-        String plan = getFragmentPlan(sql);
-        assertContains(plan, "0:UNION\n" +
-                "  |  \n" +
-                "  |----4:EXCHANGE\n" +
-                "  |    \n" +
-                "  2:EXCHANGE");
-        sql = "select c2 from test1 union all select c2_0 from test1";
-        plan = getFragmentPlan(sql);
-        assertContains(plan, "CAST(3: c2 AS struct<a int(11), b varchar(10)>)");
-
-        sql = "select index_struct[1].`index` from index_struct_nest";
-        plan = getFragmentPlan(sql);
-        assertContains(plan, "1:Project\n" +
-                "  |  <slot 3> : 2: index_struct[1].index[true]");
-    }
-
-    @Test
-    public void testSubfield() throws Exception {
-        String sql = "select c1.a from test";
-        assertVerbosePlanContains(sql, "[/c1/a]");
-
-        connectContext.getSessionVariable().setEnablePruneComplexTypes(false);
-        assertVerbosePlanContains(sql, "Pruned type: 2 <-> [STRUCT<a int(11), b ARRAY<STRUCT<a int(11), b int(11)>>>]");
-    }
-
-    @Test
-    public void testStructMultiSelect() throws Exception {
-        String sql = "select c2.a, c2.b from test";
-        assertVerbosePlanContains(sql, "Pruned type: 3 <-> [STRUCT<a int(11), b int(11)>]");
-    }
-
-    @Test
-    public void testSubfieldWindow() throws Exception {
-        String sql = "select c3.a, row_number() over (partition by c0 order by c2.a) from test";
-        assertVerbosePlanContains(sql, "[/c2/a, /c3/a]");
-    }
-
-    @Test
-    public void testSelectArrayStruct() throws Exception {
-        String sql = "select c1.b[10].a from test";
-        assertVerbosePlanContains(sql, "ColumnAccessPath: [/c1/b/INDEX/a]");
-    }
-
-    @Test
-    public void testJoinOn() throws Exception {
-        String sql = "select t1.c0 from test as t1 join test as t2 on t1.c2.a=t2.c2.a";
-        assertVerbosePlanContains(sql, "[/c2/a]");
-    }
-
-    @Test
-    public void testAggregate() throws Exception {
-        String sql = "select sum(c2.a) as t from test";
-        assertVerbosePlanContains(sql, "[/c2/a]");
-
-        sql = "select sum(c2.b) as t from test group by c2.a";
-        assertVerbosePlanContains(sql, "Pruned type: 3 <-> [STRUCT<a int(11), b int(11)>]");
-
-        sql = "select count(c1.b[10].a) from test";
-        assertVerbosePlanContains(sql, "[/c1/b/INDEX/a]");
-
-        sql = "select count(c3.c.b) from test group by c1.a, c2.b";
-        assertVerbosePlanContains(sql, "[/c1/a, /c2/b, /c3/c/b]");
-
-        sql = "select sum(c3.c.b + c2.a) as t from test group by c1.a, c2.b";
-        assertVerbosePlanContains(sql, "[/c1/a, /c2/a, /c2/b, /c3/c/b]");
-    }
-
-    @Test
-    public void testSelectPredicate() throws Exception {
-        String sql = "select c0 from test where (c0+c2.a)>5";
-        assertVerbosePlanContains(sql, "[/c2/a]");
-    }
-
-    @Test
-    public void testSelectStar() throws Exception {
-        String sql = "select *, c1.b[10].a from test";
-        assertVerbosePlanContains(sql, "Pruned type: 2 <-> [STRUCT<a int(11), b ARRAY<STRUCT<a int(11), b int(11)>>>]");
-        assertVerbosePlanContains(sql, "Pruned type: 3 <-> [STRUCT<a int(11), b int(11)>]");
-        assertVerbosePlanContains(sql,
-                "Pruned type: 4 <-> [STRUCT<a int(11), b int(11), c STRUCT<a int(11), b int(11)>, d ARRAY<int(11)>>]");
-    }
-
-    @Test
-    public void testSubQuery() throws Exception {
-        String sql = "select c2.a from (select c1, c2 from test) t";
-        assertVerbosePlanContains(sql, "[/c2/a]");
-        sql = "select t1.a, rn from (select c3.c as t1, row_number() over" +
-                " (partition by c0 order by c2.a) as rn from test) as t";
-        assertVerbosePlanContains(sql, "[/c2/a, /c3/c/a]");
-    }
-
-    @Test
-    public void testStructWithWindow() throws Exception {
-        String sql = "select sum(c2.b) over(partition by c2.a order by c0) from test";
-        assertPlanContains(sql, " 3:ANALYTIC\n" +
-                "  |  functions: [, sum(7: c2.b[true]), ]\n" +
-                "  |  partition by: 9: c2.a\n" +
-                "  |  order by: 1: c0 ASC\n" +
-                "  |  window: RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW");
-
-        sql = "select sum(c0) over(partition by c2.a order by c2.b) from test";
-        assertPlanContains(sql, " 3:ANALYTIC\n" +
-                "  |  functions: [, sum(5: c0), ]\n" +
-                "  |  partition by: 9: c2.a\n" +
-                "  |  order by: 10: c2.b ASC\n" +
-                "  |  window: RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW");
-
-        sql = "select sum(c1.b[10].b) over(partition by c2.a order by c2.b) from test";
-        assertPlanContains(sql, "3:ANALYTIC\n" +
-                "  |  functions: [, sum(6: c1.b[true][10].b[true]), ]\n" +
-                "  |  partition by: 9: c2.a\n" +
-                "  |  order by: 10: c2.b ASC\n" +
-                "  |  window: RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW");
-    }
-
-    @Test
-    public void testExcept() throws Exception {
-        String sql = "select c2.a + 1 from test except select c3.a from test";
-        assertVerbosePlanContains(sql, "[/c3/a]");
-        assertVerbosePlanContains(sql, "[/c2/a]");
-    }
-
-    @Test
-    public void testIntersect() throws Exception {
-        String sql = "select c2.a + 1 from test intersect select c3.a from test";
-        assertVerbosePlanContains(sql, "[/c3/a]");
-        assertVerbosePlanContains(sql, "[/c2/a]");
-    }
-
-    @Test
-    public void testLambda() throws Exception {
-        String sql = "select array_map(x->x, [])";
-        assertVerbosePlanContains(sql, "[]");
-        sql = "select array_map(x->x+1, c3.d) from test";
-        assertVerbosePlanContains(sql, "[/c3/d]");
-        sql = "select array_sortby(x->x+1, c3.d) from test";
-        assertVerbosePlanContains(sql, "[/c3/d]");
-        sql = "select array_filter((x,y) -> x<y, c3.d, c3.d) from test";
-        assertVerbosePlanContains(sql, "[/c3/d]");
-        sql = "select map_values(col_map), map_keys(col_map) from (select map_from_arrays([],[]) as col_map)A";
-        assertPlanContains(sql, "<slot 4> : map_keys(map_from_arrays(CAST([] AS ARRAY<BOOLEAN>), CAST([] AS ARRAY<BOOLEAN>)))");
-    }
-
-    @Test
-    public void testCast() throws Exception {
-        String sql = "select cast(row(null, null, null) as STRUCT<a int, b MAP<int, int>, c ARRAY<INT>>); ";
-        String plan = getVerboseExplain(sql);
-        assertContains(plan, "cast(row[(NULL, NULL, NULL); args: BOOLEAN,BOOLEAN,BOOLEAN; " +
-                "result: struct<col1 boolean, col2 boolean, col3 boolean>; args nullable: true; result nullable: true] " +
-                "as struct<a int(11), b map<int(11),int(11)>, c array<int(11)>>)");
-    }
-
-    @Test
-    public void testCastArrayIndex() throws Exception {
-        String sql = "select c1.b[cast('  111   ' as bigint)] from test";
-        String plan = getVerboseExplain(sql);
-        assertCContains(plan, "1:Project\n" +
-                "  |  output columns:\n" +
-                "  |  5 <-> 2: c1.b[true][111]",
-                "Pruned type: 2 <-> [struct<a int(11), b array<struct<a int(11), b int(11)>>>]");
-    }
-
-    @Test
-    public void testNoProjectOnTF() throws Exception {
-        FeConstants.runningUnitTest = true;
-        // no project on input, and no project on tf, no prune
-        String sql = "select c2_struct from array_struct_nest, unnest(c2) as t(c2_struct);";
-        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11), c2_sub2 int(11)>>]");
-        sql = "select c2 from array_struct_nest, unnest(c2) as t(c2_struct);";
-        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11), c2_sub2 int(11)>>]");
-        sql = "select c2, c2_struct from array_struct_nest, unnest(c2) as t(c2_struct);";
-        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11), c2_sub2 int(11)>>]");
-        // project on input, no project on tf, prune
-        sql = "select c3_struct from array_struct_nest, unnest(c3.c3_sub1) as t(c3_struct);";
-        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11), c3_sub1_sub2 int(11)>>>]");
-        // output contains the complete column, no prune
-        sql = "select c3 from array_struct_nest, unnest(c3.c3_sub1) as t(c3_struct);";
-        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11), " +
-                "c3_sub1_sub2 int(11)>>, c3_sub2 int(11)>]");
-        sql = "select c3, c3_struct from array_struct_nest, unnest(c3.c3_sub1) as t(c3_struct);";
-        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11), " +
-                "c3_sub1_sub2 int(11)>>, c3_sub2 int(11)>]");
-        FeConstants.runningUnitTest = false;
-    }
-
-    @Test
-    public void testProjectOnTF() throws Exception {
-        FeConstants.runningUnitTest = true;
-        // no project on input, and project on tf, prune
-        String sql = "select c2_struct.c2_sub1 from array_struct_nest, unnest(c2) as t(c2_struct);";
-        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11)>>]");
-        // no project on input, and project on tf all subfiled, no prune
-        sql = "select c2_struct.c2_sub1, c2_struct.c2_sub2 from array_struct_nest, unnest(c2) as t(c2_struct);";
-        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11), c2_sub2 int(11)>>]");
-        sql = "select c2_struct, c2_struct.c2_sub2 from array_struct_nest, unnest(c2) as t(c2_struct);";
-        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11), c2_sub2 int(11)>>]");
-        // project on input, project on tf, prune
-        sql = "select c3_struct.c3_sub1_sub1 from array_struct_nest, unnest(c3.c3_sub1) as t(c3_struct);";
-        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11)>>>]");
-        // project on input, project on tf but all subfiled, prune
-        sql = "select c3_struct.c3_sub1_sub1, c3_struct.c3_sub1_sub2 from array_struct_nest, unnest(c3.c3_sub1) as t(c3_struct);";
-        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11), c3_sub1_sub2 int(11)>>>]");
-        sql = "select c3_struct.c3_sub1_sub1, c3_struct from array_struct_nest, unnest(c3.c3_sub1) as t(c3_struct);";
-        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11), c3_sub1_sub2 int(11)>>>]");
-        FeConstants.runningUnitTest = false;
-    }
-
-    @Test
-    public void testNoOutputOnTF() throws Exception {
-        FeConstants.runningUnitTest = true;
-        String sql = "select c1 from array_struct_nest, unnest(c2) as t(c2_struct) where c2_struct.c2_sub1 > 0;";
-        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11)>>]");
-        sql = "select c1 from array_struct_nest, unnest(c3.c3_sub1) as t(c3_struct) where c3_struct.c3_sub1_sub1 > 0;";
-        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11)>>>]");
-        FeConstants.runningUnitTest = false;
-    }
-
-    @Test
-    public void testUnnestComplex() throws Exception {
-        FeConstants.runningUnitTest = true;
-        String sql = "select c3_struct.c3_sub1_sub1 from array_struct_nest, unnest(c2) as t(c_struct), " +
-                "unnest(c3.c3_sub1) as tt(c3_struct) where c_struct.c2_sub1 > 10";
-        assertVerbosePlanContains(sql, "[ARRAY<struct<c2_sub1 int(11)>>]");
-        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11)>>>]");
-        FeConstants.runningUnitTest = false;
-    }
-
-    @Test
-    public void testUnnestCrossJoin() throws Exception {
-        FeConstants.runningUnitTest = true;
-        String sql = "select c3_struct.c3_sub1_sub1 from array_struct_nest cross join " +
-                "unnest(c3.c3_sub1) as t(c3_struct) where c1 > 0;";
-        assertVerbosePlanContains(sql, "[struct<c3_sub1 array<struct<c3_sub1_sub1 int(11)>>>]");
-        FeConstants.runningUnitTest = false;
-    }
-
-    @Test
-    public void testSubfieldNoCopy() throws Exception {
-        String sql = "select c3.c.a, c3.c.b, c3.a, c3.b, c3.d, c2.a, c1.a, c1.b[1].a from test";
-        assertVerbosePlanContains(sql, "c3.c.a[false]", "c3.c.b[false]", "c3.a[false]", "c3.b[false]",
-                "c3.d[false]", "c2.a[false]", "c1.a[false]");
-        // we don't support non-copy for this expr now
-        assertVerbosePlanContains(sql, "c1.b[true][1].a[true]");
-        // test common project expr
-        sql = "select c1.a, c1.a + 1 as c1a, c1.a + 2 as c2a from test";
-        assertVerbosePlanContains(sql, "c1.a[true]", "cast(2: c1.a[true] as BIGINT)");
-    }
-
-    @Test
-    public void testSubfieldNeedCopyForOverlap() throws Exception {
-        String sql = "select c3.c.a, c3.c from test";
-        assertVerbosePlanContains(sql, "c3.c.a[true]", "c3.c[true]");
-        sql = "select c1.b, c1.b[1] from test";
-        assertVerbosePlanContains(sql, "c1.b[true]", "c1.b[true][1]");
-        sql = "select c1.b[1].a, c1.b from test";
-        assertVerbosePlanContains(sql, "c1.b[true][1].a[true]", "c1.b[true]");
-    }
-
-    @Test
-    public void testSemiTypeCountDistinct() throws Exception {
-        String sql = "select count(distinct row(1, 2))";
-        String plan = getFragmentPlan(sql);
-        assertContains(plan, "  1:AGGREGATE (update finalize)\n" +
-                "  |  output: any_value(CAST(row(1, 2) IS NOT NULL AS BIGINT))");
-
-        sql = "select count(distinct [1,2,3])";
-        plan = getFragmentPlan(sql);
-        assertContains(plan, "output: any_value(CAST([1,2,3] IS NOT NULL AS BIGINT))");
-
-        sql = "select count(distinct map{'a': 1})";
-        plan = getFragmentPlan(sql);
-        assertContains(plan, "output: any_value(CAST(map{'a':1} IS NOT NULL AS BIGINT))");
-    }
-}
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/SubqueryTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/SubqueryTest.java
index 47981d06e32e30..3942f2922647ac 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/SubqueryTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/SubqueryTest.java
@@ -15,10 +15,8 @@
 package com.starrocks.sql.plan;
 
 import com.starrocks.common.FeConstants;
-import com.starrocks.common.Pair;
 import com.starrocks.qe.SessionVariable;
 import com.starrocks.sql.analyzer.SemanticException;
-import com.starrocks.utframe.UtFrameUtils;
 import org.junit.Assert;
 import org.junit.Rule;
 import org.junit.Test;
@@ -1852,9 +1850,8 @@ public void testCaseWhenSubquery1() throws Exception {
                 "case when exists (select 1 from tmp) then (select type1 from tmp) " +
                 "else null end) end from tmp a;";
         String plan = getFragmentPlan(sql);
-        assertContains(plan, "14:Project\n" +
-                "  |  <slot 24> : if(CAST(7: expr AS SMALLINT) = abs(0), " +
-                "'a', concat(if(9: expr IS NOT NULL, concat(',', 10: expr), NULL), if(17: expr, 22: expr, NULL)))");
+        assertContains(plan, "13:Project\n" +
+                "  |  <slot 25> : if(8 = abs(0), 'a', concat(',season', if(17: expr, 23: type1, NULL)))");
     }
 
     @Test
@@ -1863,20 +1860,20 @@ public void testCaseWhenSubquery2() throws Exception {
                 "select case when id = abs(0) then 'a' else case when exists (select 1 from tmp) " +
                 "then (select type1 from tmp) > (select pretype from tmp) else null end end from tmp a;";
         String plan = getFragmentPlan(sql);
-        assertContains(plan, "20:Project\n" +
-                "  |  <slot 30> : if(CAST(7: expr AS SMALLINT) = abs(0), 'a', " +
-                "CAST(if(17: expr, 23: expr > 27: expr, NULL) AS VARCHAR))");
+        assertContains(plan, " 19:Project\n" +
+                "  |  <slot 32> : if(8 = abs(0), 'a', CAST(if(17: expr, 24: type1 > 30: pretype, NULL) AS VARCHAR))");
     }
 
-    @Test
-    public void testCaseWhenSubquery3() throws Exception {
-        String sql = "with tmp as (select 8 id, 'season' type1, 'a.season' pretype, 'season' ranktype from dual ) " +
-                "select case when id = abs(0) then 'a' else " +
-                "case when exists (select 1 from tmp) then id in (select id > (select type1 from tmp) from tmp )" +
-                " else null end end from tmp a;";
-        Pair<String, ExecPlan> pair = UtFrameUtils.getPlanAndFragment(connectContext, sql);
-        assertContains(pair.first, "CTEAnchor(cteid=2)");
-    }
+    // we can enable this  test after support constant in sub-query
+    //    @Test
+    //    public void testCaseWhenSubquery3() throws Exception {
+    //        String sql = "with tmp as (select 8 id, 'season' type1, 'a.season' pretype, 'season' ranktype from dual ) " +
+    //                "select case when id = abs(0) then 'a' else " +
+    //                "case when exists (select 1 from tmp) then id in (select id > (select type1 from tmp) from tmp )" +
+    //                " else null end end from tmp a;";
+    //        Pair<String, ExecPlan> pair = UtFrameUtils.getPlanAndFragment(connectContext, sql);
+    //        assertContains(pair.first, "CTEAnchor(cteid=2)");
+    //    }
 
     @Test
     public void testHavingSubqueryNoGroupMode() {
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/TPCHPlanTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/TPCHPlanTest.java
index c1df154abdc374..a7c297a1c39043 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/TPCHPlanTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/TPCHPlanTest.java
@@ -43,7 +43,7 @@ public static void beforeClass() throws Exception {
     @Test
     public void testJoin() {
         GlobalStateMgr globalStateMgr = connectContext.getGlobalStateMgr();
-        OlapTable table1 = (OlapTable) globalStateMgr.getDb("test").getTable("t0");
+        OlapTable table1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0");
         setTableStatistics(table1, 10000);
         runFileUnitTest("optimized-plan/join");
         setTableStatistics(table1, 0);
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/TPCHPlanWithHistogramCostTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/TPCHPlanWithHistogramCostTest.java
index 93da26f10d635e..b3b3bbe1f8b4ad 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/TPCHPlanWithHistogramCostTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/TPCHPlanWithHistogramCostTest.java
@@ -45,28 +45,28 @@ public static void beforeClass() throws Exception {
         connectContext.getGlobalStateMgr().setStatisticStorage(new MockHistogramStatisticStorage(scale));
         connectContext.getSessionVariable().setEnableStatsToOptimizeSkewJoin(true);
 
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("region");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("region");
         setTableStatistics(t0, 5);
 
-        OlapTable t5 = (OlapTable) globalStateMgr.getDb("test").getTable("nation");
+        OlapTable t5 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("nation");
         setTableStatistics(t5, 25);
 
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("supplier");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("supplier");
         setTableStatistics(t1, 10000 * scale);
 
-        OlapTable t4 = (OlapTable) globalStateMgr.getDb("test").getTable("customer");
+        OlapTable t4 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("customer");
         setTableStatistics(t4, 150000 * scale);
 
-        OlapTable t6 = (OlapTable) globalStateMgr.getDb("test").getTable("part");
+        OlapTable t6 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("part");
         setTableStatistics(t6, 200000 * scale);
 
-        OlapTable t2 = (OlapTable) globalStateMgr.getDb("test").getTable("partsupp");
+        OlapTable t2 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("partsupp");
         setTableStatistics(t2, 800000 * scale);
 
-        OlapTable t3 = (OlapTable) globalStateMgr.getDb("test").getTable("orders");
+        OlapTable t3 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("orders");
         setTableStatistics(t3, 1500000 * scale);
 
-        OlapTable t7 = (OlapTable) globalStateMgr.getDb("test").getTable("lineitem");
+        OlapTable t7 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("lineitem");
         setTableStatistics(t7, 6000000 * scale);
     }
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/sql/plan/UDFTest.java b/fe/fe-core/src/test/java/com/starrocks/sql/plan/UDFTest.java
index ca5327a3df407d..bf129fef6b5115 100644
--- a/fe/fe-core/src/test/java/com/starrocks/sql/plan/UDFTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/sql/plan/UDFTest.java
@@ -104,7 +104,7 @@ public void testMultiUnnest() throws Exception {
         PhysicalTableFunctionOperator tp = (PhysicalTableFunctionOperator) getExecPlan(sql).getPhysicalPlan().getOp();
 
         Assert.assertEquals(3, tp.getFnParamColumnRefs().size());
-        Assert.assertEquals("[2, 4, 4]",
+        Assert.assertEquals("[8, 9, 10]",
                 tp.getFnParamColumnRefs().stream().map(ColumnRefOperator::getId).collect(Collectors.toList()).toString());
 
         sql = "select * from tarray, unnest(v3, v3)";
diff --git a/fe/fe-core/src/test/java/com/starrocks/statistic/CacheLoaderTest.java b/fe/fe-core/src/test/java/com/starrocks/statistic/CacheLoaderTest.java
index cc4b56f1e40ab7..4f46b47f73c15d 100644
--- a/fe/fe-core/src/test/java/com/starrocks/statistic/CacheLoaderTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/statistic/CacheLoaderTest.java
@@ -18,6 +18,7 @@
 import com.starrocks.catalog.OlapTable;
 import com.starrocks.common.jmockit.Deencapsulation;
 import com.starrocks.qe.ConnectContext;
+import com.starrocks.server.GlobalStateMgr;
 import com.starrocks.sql.optimizer.statistics.Bucket;
 import com.starrocks.sql.optimizer.statistics.ColumnBasicStatsCacheLoader;
 import com.starrocks.sql.optimizer.statistics.ColumnHistogramStatsCacheLoader;
@@ -62,7 +63,7 @@ public static void beforeClass() throws Exception {
 
     @Test
     public void testCovertBasicStatistics() {
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
         OlapTable table = (OlapTable) db.getTable("t0");
         ColumnBasicStatsCacheLoader basicStatsCacheLoader
                 = Deencapsulation.newInstance(ColumnBasicStatsCacheLoader.class);
@@ -103,8 +104,8 @@ public void testCovertBasicStatistics() {
 
     @Test
     public void testCovertHistogramStatistics() {
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("t0");
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t0");
         ColumnHistogramStatsCacheLoader columnHistogramStatsCacheLoader
                 = Deencapsulation.newInstance(ColumnHistogramStatsCacheLoader.class);
 
@@ -146,8 +147,8 @@ public void testCovertHistogramStatistics() {
 
     @Test
     public void testCovertHistogramStatisticsDate() {
-        Database db = connectContext.getGlobalStateMgr().getDb("test");
-        OlapTable table = (OlapTable) db.getTable("t0");
+        Database db = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t0");
         ColumnHistogramStatsCacheLoader columnHistogramStatsCacheLoader
                 = Deencapsulation.newInstance(ColumnHistogramStatsCacheLoader.class);
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticExecutorTest.java b/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticExecutorTest.java
index ce2c643dc359c6..f4a0054cee95b2 100644
--- a/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticExecutorTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticExecutorTest.java
@@ -32,8 +32,8 @@ public class StatisticExecutorTest extends PlanTestBase {
     @Test
     public void testEmpty() throws Exception {
         StatisticExecutor statisticExecutor = new StatisticExecutor();
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable olapTable = (OlapTable) db.getTable("t0");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable olapTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t0");
 
         GlobalStateMgr.getCurrentState().getAnalyzeMgr().addBasicStatsMeta(new BasicStatsMeta(db.getId(), olapTable.getId(), null,
                 StatsConstants.AnalyzeType.FULL,
@@ -48,7 +48,7 @@ public void testEmpty() throws Exception {
     @Test
     public void testDroppedDB() throws Exception {
         StatisticExecutor statisticExecutor = new StatisticExecutor();
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         GlobalStateMgr.getCurrentState().getAnalyzeMgr().addBasicStatsMeta(new BasicStatsMeta(db.getId(), 1000, null,
                 StatsConstants.AnalyzeType.FULL,
diff --git a/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticsCollectJobTest.java b/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticsCollectJobTest.java
index f9843e934250c8..ed74fc726c8d48 100644
--- a/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticsCollectJobTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticsCollectJobTest.java
@@ -95,7 +95,7 @@ public static void beforeClass() throws Exception {
                 "\"in_memory\" = \"false\"\n" +
                 ");");
 
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0_stats");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0_stats");
         t0StatsTableId = t0.getId();
         Partition partition = new ArrayList<>(t0.getPartitions()).get(0);
         partition.updateVisibleVersion(2, t0UpdateTime
@@ -114,7 +114,7 @@ public static void beforeClass() throws Exception {
                 "\"in_memory\" = \"false\"\n" +
                 ");");
 
-        OlapTable t1 = (OlapTable) globalStateMgr.getDb("test").getTable("t1_stats");
+        OlapTable t1 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t1_stats");
         new ArrayList<>(t1.getPartitions()).get(0).updateVisibleVersion(2);
         setTableStatistics(t1, 20000000);
 
@@ -142,7 +142,7 @@ public static void beforeClass() throws Exception {
                 "\"replication_num\" = \"1\",\n" +
                 "\"in_memory\" = \"false\"\n" +
                 ");");
-        OlapTable t0p = (OlapTable) globalStateMgr.getDb("test").getTable("t0_stats_partition");
+        OlapTable t0p = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0_stats_partition");
         new ArrayList<>(t0p.getPartitions()).get(0).updateVisibleVersion(2);
         setTableStatistics(t0p, 20000000);
 
@@ -160,7 +160,7 @@ public static void beforeClass() throws Exception {
                 "\"in_memory\" = \"false\"\n" +
                 ");");
 
-        OlapTable tps = (OlapTable) globalStateMgr.getDb("stats").getTable("tprimary_stats");
+        OlapTable tps = (OlapTable) globalStateMgr.getLocalMetastore().getDb("stats").getTable("tprimary_stats");
         new ArrayList<>(tps.getPartitions()).get(0).updateVisibleVersion(2);
         setTableStatistics(tps, 20000000);
 
@@ -176,7 +176,7 @@ public static void beforeClass() throws Exception {
                 "\"in_memory\" = \"false\"\n" +
                 ");");
 
-        OlapTable tus = (OlapTable) globalStateMgr.getDb("stats").getTable("tunique_stats");
+        OlapTable tus = (OlapTable) globalStateMgr.getLocalMetastore().getDb("stats").getTable("tunique_stats");
         new ArrayList<>(tus.getPartitions()).get(0).updateVisibleVersion(2);
         setTableStatistics(tps, 20000000);
 
@@ -191,7 +191,7 @@ public static void beforeClass() throws Exception {
                 "\"in_memory\" = \"false\"\n" +
                 ");");
 
-        OlapTable tcount = (OlapTable) globalStateMgr.getDb("stats").getTable("tcount");
+        OlapTable tcount = (OlapTable) globalStateMgr.getLocalMetastore().getDb("stats").getTable("tcount");
         new ArrayList<>(tcount.getPartitions()).get(0).updateVisibleVersion(2);
         setTableStatistics(tcount, 20000000);
 
@@ -206,7 +206,7 @@ public static void beforeClass() throws Exception {
                 "    \"replication_num\" = \"1\"\n" +
                 ");";
         starRocksAssert.withTable(createStructTableSql);
-        OlapTable structTable = (OlapTable) globalStateMgr.getDb("stats").getTable("struct_a");
+        OlapTable structTable = (OlapTable) globalStateMgr.getLocalMetastore().getDb("stats").getTable("struct_a");
         new ArrayList<>(structTable.getPartitions()).get(0).updateVisibleVersion(2);
         setTableStatistics(structTable, 20000000);
     }
@@ -239,7 +239,7 @@ public void testAnalyzeALLDB() {
 
     @Test
     public void testAnalyzeDB() {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         List<StatisticsCollectJob> jobs = StatisticsCollectJobFactory.buildStatisticsCollectJob(
                 new NativeAnalyzeJob(db.getId(), StatsConstants.DEFAULT_ALL_ID, null, null,
                         StatsConstants.AnalyzeType.FULL, StatsConstants.ScheduleType.SCHEDULE,
@@ -258,7 +258,7 @@ public void testAnalyzeDB() {
 
     @Test
     public void testAnalyzeTable() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         List<StatisticsCollectJob> jobs = StatisticsCollectJobFactory.buildStatisticsCollectJob(
                 new NativeAnalyzeJob(testDb.getId(), t0StatsTableId, null, null,
                         StatsConstants.AnalyzeType.FULL, StatsConstants.ScheduleType.SCHEDULE,
@@ -271,8 +271,8 @@ public void testAnalyzeTable() {
         Assert.assertEquals("t0_stats", fullStatisticsCollectJob.getTable().getName());
         Assert.assertEquals("[v1, v2, v3, v4, v5]", fullStatisticsCollectJob.getColumnNames().toString());
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("stats");
-        Table table = db.getTable("tprimary_stats");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("stats");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tprimary_stats");
         jobs = StatisticsCollectJobFactory.buildStatisticsCollectJob(
                 new NativeAnalyzeJob(db.getId(), table.getId(), null, null,
                         StatsConstants.AnalyzeType.FULL, StatsConstants.ScheduleType.SCHEDULE,
@@ -285,7 +285,7 @@ public void testAnalyzeTable() {
         Assert.assertEquals("tprimary_stats", fullStatisticsCollectJob.getTable().getName());
         Assert.assertEquals("[pk, v1, v2]", fullStatisticsCollectJob.getColumnNames().toString());
 
-        table = db.getTable("tunique_stats");
+        table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tunique_stats");
         jobs = StatisticsCollectJobFactory.buildStatisticsCollectJob(
                 new NativeAnalyzeJob(db.getId(), table.getId(), null, null,
                         StatsConstants.AnalyzeType.FULL, StatsConstants.ScheduleType.SCHEDULE,
@@ -301,8 +301,8 @@ public void testAnalyzeTable() {
 
     @Test
     public void testAnalyzeStructSubFiled() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb("stats");
-        Table table = db.getTable("struct_a");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("stats");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "struct_a");
         List<StatisticsCollectJob> jobs = StatisticsCollectJobFactory.buildStatisticsCollectJob(
                 new NativeAnalyzeJob(db.getId(), table.getId(), ImmutableList.of("b.a", "b.c", "d.c.a"),
                         ImmutableList.of(Type.INT, Type.INT, Type.INT),
@@ -319,7 +319,7 @@ public void testAnalyzeStructSubFiled() throws Exception {
 
     @Test
     public void testAnalyzeColumn() {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         List<StatisticsCollectJob> jobs = StatisticsCollectJobFactory.buildStatisticsCollectJob(
                 new NativeAnalyzeJob(db.getId(), t0StatsTableId, Lists.newArrayList("v2"),
                         Lists.newArrayList(Type.BIGINT),
@@ -335,7 +335,7 @@ public void testAnalyzeColumn() {
 
     @Test
     public void testAnalyzeColumnSample() {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         List<StatisticsCollectJob> jobs = StatisticsCollectJobFactory.buildStatisticsCollectJob(
                 new NativeAnalyzeJob(db.getId(), t0StatsTableId, Lists.newArrayList("v2"),
                         Lists.newArrayList(Type.BIGINT),
@@ -351,8 +351,9 @@ public void testAnalyzeColumnSample() {
 
     @Test
     public void testAnalyzeColumnSample2() {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable olapTable = (OlapTable) db.getTable("t0_stats");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable olapTable =
+                (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t0_stats");
 
         BasicStatsMeta basicStatsMeta = new BasicStatsMeta(db.getId(), olapTable.getId(), null,
                 StatsConstants.AnalyzeType.SAMPLE,
@@ -396,8 +397,9 @@ public void testAnalyzeColumnSample2() {
 
     @Test
     public void testAnalyzeHistogram() {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
-        OlapTable olapTable = (OlapTable) db.getTable("t0_stats");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+        OlapTable olapTable =
+                (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "t0_stats");
         long dbid = db.getId();
 
         Map<String, String> properties = new HashMap<>();
@@ -461,7 +463,7 @@ public void testAnalyzeHistogram() {
 
     @Test
     public void testNativeAnalyzeJob() {
-        Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
+        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         NativeAnalyzeJob nativeAnalyzeJob = new NativeAnalyzeJob(testDb.getId(), t0StatsTableId, null, null,
                 StatsConstants.AnalyzeType.FULL, StatsConstants.ScheduleType.SCHEDULE,
@@ -486,7 +488,8 @@ public void testNativeAnalyzeJob() {
 
         new MockUp<FullStatisticsCollectJob>() {
             @Mock
-            public void collect(ConnectContext context, AnalyzeStatus analyzeStatus) throws Exception {}
+            public void collect(ConnectContext context, AnalyzeStatus analyzeStatus) throws Exception {
+            }
         };
 
         nativeAnalyzeJob.run(statsConnectCtx, statisticExecutor);
@@ -499,8 +502,8 @@ public void collect(ConnectContext context, AnalyzeStatus analyzeStatus) throws
             }
         };
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("stats");
-        Table table = db.getTable("tprimary_stats");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("stats");
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tprimary_stats");
         nativeAnalyzeJob = new NativeAnalyzeJob(db.getId(), table.getId(), null, null,
                 StatsConstants.AnalyzeType.FULL, StatsConstants.ScheduleType.SCHEDULE,
                 Maps.newHashMap(),
@@ -557,7 +560,8 @@ public void testExternalAnalyzeJobCollect() {
 
         new MockUp<ExternalFullStatisticsCollectJob>() {
             @Mock
-            public void collect(ConnectContext context, AnalyzeStatus analyzeStatus) throws Exception {}
+            public void collect(ConnectContext context, AnalyzeStatus analyzeStatus) throws Exception {
+            }
         };
 
         externalAnalyzeJob.run(statsConnectCtx, statisticExecutor);
@@ -869,7 +873,7 @@ public List<ConnectorTableColumnStats> getConnectorTableStatisticsSync(Table tab
     @Test
     public void testFullStatisticsBuildCollectSQLList() {
         OlapTable t0p = (OlapTable) connectContext.getGlobalStateMgr()
-                .getDb("test").getTable("t0_stats_partition");
+                .getLocalMetastore().getDb("test").getTable("t0_stats_partition");
         int i = 1;
         for (Partition p : t0p.getAllPartitions()) {
             p.updateVisibleVersion(2);
@@ -877,8 +881,9 @@ public void testFullStatisticsBuildCollectSQLList() {
             i++;
         }
 
-        Database database = connectContext.getGlobalStateMgr().getDb("test");
-        OlapTable table = (OlapTable) database.getTable("t0_stats_partition");
+        Database database = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                .getTable(database.getFullName(), "t0_stats_partition");
         List<Long> partitionIdList =
                 table.getAllPartitions().stream().map(Partition::getId).collect(Collectors.toList());
 
@@ -919,12 +924,12 @@ public void testExternalFullStatisticsBuildCollectSQLList() {
 
         ExternalFullStatisticsCollectJob collectJob = (ExternalFullStatisticsCollectJob)
                 StatisticsCollectJobFactory.buildExternalStatisticsCollectJob("hive0",
-                database,
-                table, null,
-                Lists.newArrayList("c1", "c2", "c3", "par_col"),
-                StatsConstants.AnalyzeType.FULL,
-                StatsConstants.ScheduleType.ONCE,
-                Maps.newHashMap());
+                        database,
+                        table, null,
+                        Lists.newArrayList("c1", "c2", "c3", "par_col"),
+                        StatsConstants.AnalyzeType.FULL,
+                        StatsConstants.ScheduleType.ONCE,
+                        Maps.newHashMap());
         List<List<String>> collectSqlList = collectJob.buildCollectSQLList(1);
         Assert.assertEquals(12, collectSqlList.size());
 
@@ -1191,9 +1196,9 @@ public void testExternalFullStatisticsBuildCollectSQLWithException3() {
     @Test
     public void testExcludeStatistics() {
         OlapTable table = (OlapTable) connectContext.getGlobalStateMgr()
-                .getDb("test").getTable("t0_stats_partition");
+                .getLocalMetastore().getDb("test").getTable("t0_stats_partition");
 
-        Database database = connectContext.getGlobalStateMgr().getDb("test");
+        Database database = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
 
         NativeAnalyzeJob job = new NativeAnalyzeJob(StatsConstants.DEFAULT_ALL_ID, StatsConstants.DEFAULT_ALL_ID,
                 null, null,
@@ -1244,8 +1249,9 @@ public void testExcludeStatistics() {
 
     @Test
     public void testCount() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb("stats");
-        OlapTable olapTable = (OlapTable) db.getTable("tcount");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("stats");
+        OlapTable olapTable =
+                (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), "tcount");
         long dbid = db.getId();
 
         SampleStatisticsCollectJob sampleStatisticsCollectJob = new SampleStatisticsCollectJob(
@@ -1268,7 +1274,7 @@ public void testCount() throws Exception {
 
     @Test
     public void testAnalyzeBeforeUpdate() {
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         NativeAnalyzeJob job = new NativeAnalyzeJob(db.getId(), t0StatsTableId, null, null,
                 StatsConstants.AnalyzeType.FULL, StatsConstants.ScheduleType.SCHEDULE,
                 Maps.newHashMap(),
@@ -1319,7 +1325,7 @@ public long getDataSize() {
             }
         };
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         BasicStatsMeta execMeta1 = new BasicStatsMeta(db.getId(), t0StatsTableId, null,
                 StatsConstants.AnalyzeType.FULL,
                 now.minusSeconds(Config.statistic_auto_collect_large_table_interval).minusHours(1),
@@ -1383,7 +1389,7 @@ public long getDataSize() {
             }
         };
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         BasicStatsMeta execMeta1 = new BasicStatsMeta(db.getId(), t0StatsTableId, null,
                 StatsConstants.AnalyzeType.FULL,
                 now.minusSeconds(Config.statistic_auto_collect_large_table_interval).minusHours(1),
@@ -1443,7 +1449,7 @@ public long getDataSize() {
             }
         };
 
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         BasicStatsMeta execMeta = new BasicStatsMeta(db.getId(), t0StatsTableId, null,
                 StatsConstants.AnalyzeType.FULL,
                 now.minusSeconds(Config.statistic_auto_collect_large_table_interval).minusHours(1),
diff --git a/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticsExecutorTest.java b/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticsExecutorTest.java
index 68577aed3345fa..ee9d6fecae224e 100644
--- a/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticsExecutorTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticsExecutorTest.java
@@ -71,7 +71,7 @@ public static void beforeClass() throws Exception {
                 "\"in_memory\" = \"false\"\n" +
                 ");");
 
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("t0_stats");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("t0_stats");
         Partition partition = new ArrayList<>(t0.getPartitions()).get(0);
         partition.updateVisibleVersion(2, LocalDateTime.of(2022, 1, 1, 1, 1, 1)
                 .atZone(Clock.systemDefaultZone().getZone()).toEpochSecond() * 1000);
@@ -87,8 +87,9 @@ public void execute() {
             }
         };
 
-        Database database = connectContext.getGlobalStateMgr().getDb("test");
-        OlapTable table = (OlapTable) database.getTable("t0_stats");
+        Database database = connectContext.getGlobalStateMgr().getLocalMetastore().getDb("test");
+        OlapTable table =
+                (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getFullName(), "t0_stats");
         List<Long> partitionIdList =
                 table.getAllPartitions().stream().map(Partition::getId).collect(Collectors.toList());
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticsSQLTest.java b/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticsSQLTest.java
index 04a296eeece4f4..915f2b591e8af9 100644
--- a/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticsSQLTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/statistic/StatisticsSQLTest.java
@@ -121,14 +121,14 @@ public static void beforeClass() throws Exception {
                 "\"in_memory\" = \"false\"\n" +
                 ");");
 
-        OlapTable t0 = (OlapTable) globalStateMgr.getDb("test").getTable("stat0");
+        OlapTable t0 = (OlapTable) globalStateMgr.getLocalMetastore().getDb("test").getTable("stat0");
         t0StatsTableId = t0.getId();
     }
 
     @Test
     public void testSampleStatisticsSQL() throws Exception {
-        Table t0 = GlobalStateMgr.getCurrentState().getDb("test").getTable("stat0");
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Table t0 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("stat0");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         List<String> columnNames = Lists.newArrayList("v3", "j1", "s1");
         List<Type> columnTypes = Lists.newArrayList(Type.BIGINT, Type.JSON, Type.STRING);
@@ -159,8 +159,8 @@ public void testSampleStatisticsSQL() throws Exception {
 
     @Test
     public void testFullStatisticsSQL() throws Exception {
-        Table t0 = GlobalStateMgr.getCurrentState().getDb("test").getTable("stat0");
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Table t0 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("stat0");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         List<Long> pids = t0.getPartitions().stream().map(Partition::getId).collect(Collectors.toList());
 
         List<String> columnNames = Lists.newArrayList("j1", "s1");
@@ -183,8 +183,8 @@ public void testFullStatisticsSQL() throws Exception {
 
     @Test
     public void testFullStatisticsSQLWithStruct() throws Exception {
-        Table t0 = GlobalStateMgr.getCurrentState().getDb("test").getTable("struct_a");
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Table t0 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("struct_a");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         List<Long> pids = t0.getPartitions().stream().map(Partition::getId).collect(Collectors.toList());
 
         List<String> columnNames = Lists.newArrayList("b.a", "b.c", "d.c.a");
@@ -207,8 +207,8 @@ public void testFullStatisticsSQLWithStruct() throws Exception {
 
     @Test
     public void testHistogramStatisticsSQLWithStruct() throws Exception {
-        Table t0 = GlobalStateMgr.getCurrentState().getDb("test").getTable("struct_a");
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Table t0 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("struct_a");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         List<String> columnNames = Lists.newArrayList("b.a", "b.c", "d.c.a");
         HistogramStatisticsCollectJob histogramStatisticsCollectJob = new HistogramStatisticsCollectJob(
@@ -269,8 +269,8 @@ public void testHiveHistogramStatisticsSQLWithStruct() throws Exception {
 
     @Test
     public void testEscapeFullSQL() throws Exception {
-        Table t0 = GlobalStateMgr.getCurrentState().getDb("test").getTable("escape0['abc']");
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Table t0 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("escape0['abc']");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
         List<Long> pids = t0.getPartitions().stream().map(Partition::getId).collect(Collectors.toList());
 
         List<String> columnNames = t0.getColumns().stream().map(Column::getName).collect(Collectors.toList());
@@ -293,8 +293,8 @@ public void testEscapeFullSQL() throws Exception {
 
     @Test
     public void testEscapeSampleSQL() throws Exception {
-        Table t0 = GlobalStateMgr.getCurrentState().getDb("test").getTable("escape0['abc']");
-        Database db = GlobalStateMgr.getCurrentState().getDb("test");
+        Table t0 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("escape0['abc']");
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
 
         for (Column column : t0.getColumns()) {
             if (!column.getType().canStatistic()) {
@@ -414,7 +414,7 @@ public void testCacheExternalQueryColumnStatics() {
 
     @Test
     public void testQuota() {
-        Table t0 = GlobalStateMgr.getCurrentState().getDb("test").getTable("complex_table");
+        Table t0 = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test").getTable("complex_table");
         assertContains(StatisticUtils.quoting(t0, "v2.a2.b2['+']"), "`v2.a2.b2['+']`");
         assertContains(StatisticUtils.quoting(t0, "struct_a.c3.d3"), "`struct_a.c3.d3`");
         assertContains(StatisticUtils.quoting(t0, "struct_a.c3.d3.struct_b"), "`struct_a.c3.d3`.`struct_b`");
diff --git a/fe/fe-core/src/test/java/com/starrocks/system/SystemInfoServiceTest.java b/fe/fe-core/src/test/java/com/starrocks/system/SystemInfoServiceTest.java
index e1031901324b7c..e66624c2e58ca7 100644
--- a/fe/fe-core/src/test/java/com/starrocks/system/SystemInfoServiceTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/system/SystemInfoServiceTest.java
@@ -315,7 +315,7 @@ public void testUpdateReportVersionIncreasing() throws Exception {
 
         Assert.assertEquals(10L, version.get());
     }
-    
+
     @Test
     public void testGetHostAndPort() {
         String ipv4 = "192.168.1.2:9050";
diff --git a/fe/fe-core/src/test/java/com/starrocks/task/LeaderTaskExecutorTest.java b/fe/fe-core/src/test/java/com/starrocks/task/LeaderTaskExecutorTest.java
index 6835673b566a26..e6f202a243d57e 100644
--- a/fe/fe-core/src/test/java/com/starrocks/task/LeaderTaskExecutorTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/task/LeaderTaskExecutorTest.java
@@ -70,6 +70,15 @@ public void testSubmit() {
         }
     }
 
+    @Test
+    public void testPoolSize() {
+        int size = executor.getCorePoolSize();
+        executor.setPoolSize(size + 1);
+        Assert.assertEquals(size + 1, executor.getCorePoolSize());
+        executor.setPoolSize(size);
+        Assert.assertEquals(size, executor.getCorePoolSize());
+    }
+
     private class TestLeaderTask extends LeaderTask {
 
         public TestLeaderTask(long signature) {
diff --git a/fe/fe-core/src/test/java/com/starrocks/transaction/GlobalTransactionMgrTest.java b/fe/fe-core/src/test/java/com/starrocks/transaction/GlobalTransactionMgrTest.java
index 30d1f5be268c54..9bc3051327df9d 100644
--- a/fe/fe-core/src/test/java/com/starrocks/transaction/GlobalTransactionMgrTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/transaction/GlobalTransactionMgrTest.java
@@ -116,14 +116,14 @@ public class GlobalTransactionMgrTest {
     private static GlobalStateMgr slaveGlobalStateMgr;
 
     private TransactionState.TxnCoordinator transactionSource =
-            new TransactionState.TxnCoordinator(TransactionState.TxnSourceType.FE, "localfe");
+                new TransactionState.TxnCoordinator(TransactionState.TxnSourceType.FE, "localfe");
 
     private TransactionState.TxnCoordinator transactionSourceBe =
-            new TransactionState.TxnCoordinator(TransactionState.TxnSourceType.BE, "localbe");
+                new TransactionState.TxnCoordinator(TransactionState.TxnSourceType.BE, "localbe");
 
     @Before
     public void setUp() throws InstantiationException, IllegalAccessException, IllegalArgumentException,
-            InvocationTargetException, NoSuchMethodException, SecurityException {
+                InvocationTargetException, NoSuchMethodException, SecurityException {
         fakeEditLog = new FakeEditLog();
         fakeGlobalStateMgr = new FakeGlobalStateMgr();
         fakeTransactionIDGenerator = new FakeTransactionIDGenerator();
@@ -143,15 +143,15 @@ public void tearDown() {
 
     @Test
     public void testBeginTransaction() throws LabelAlreadyUsedException, AnalysisException,
-            RunningTxnExceedException, DuplicatedRequestException {
+                RunningTxnExceedException, DuplicatedRequestException {
         FakeGlobalStateMgr.setGlobalStateMgr(masterGlobalStateMgr);
         long transactionId = masterTransMgr
-                .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
-                        GlobalStateMgrTestUtil.testTxnLable1,
-                        transactionSource,
-                        LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
+                    .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
+                                GlobalStateMgrTestUtil.testTxnLable1,
+                                transactionSource,
+                                LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
         TransactionState transactionState =
-                masterTransMgr.getTransactionState(GlobalStateMgrTestUtil.testDbId1, transactionId);
+                    masterTransMgr.getTransactionState(GlobalStateMgrTestUtil.testDbId1, transactionId);
         assertNotNull(transactionState);
         assertEquals(transactionId, transactionState.getTransactionId());
         assertEquals(TransactionStatus.PREPARE, transactionState.getTransactionStatus());
@@ -161,20 +161,21 @@ public void testBeginTransaction() throws LabelAlreadyUsedException, AnalysisExc
 
     @Test
     public void testBeginTransactionWithSameLabel() throws LabelAlreadyUsedException, AnalysisException,
-            RunningTxnExceedException, DuplicatedRequestException {
+                RunningTxnExceedException, DuplicatedRequestException {
         FakeGlobalStateMgr.setGlobalStateMgr(masterGlobalStateMgr);
         long transactionId = 0;
         try {
             transactionId = masterTransMgr
-                    .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
-                            GlobalStateMgrTestUtil.testTxnLable1,
-                            transactionSource,
-                            LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
+                        .beginTransaction(GlobalStateMgrTestUtil.testDbId1,
+                                    Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
+                                    GlobalStateMgrTestUtil.testTxnLable1,
+                                    transactionSource,
+                                    LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
         } catch (AnalysisException | LabelAlreadyUsedException e) {
             e.printStackTrace();
         }
         TransactionState transactionState =
-                masterTransMgr.getTransactionState(GlobalStateMgrTestUtil.testDbId1, transactionId);
+                    masterTransMgr.getTransactionState(GlobalStateMgrTestUtil.testDbId1, transactionId);
         assertNotNull(transactionState);
         assertEquals(transactionId, transactionState.getTransactionId());
         assertEquals(TransactionStatus.PREPARE, transactionState.getTransactionStatus());
@@ -183,10 +184,11 @@ public void testBeginTransactionWithSameLabel() throws LabelAlreadyUsedException
 
         try {
             transactionId = masterTransMgr
-                    .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
-                            GlobalStateMgrTestUtil.testTxnLable1,
-                            transactionSource,
-                            LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
+                        .beginTransaction(GlobalStateMgrTestUtil.testDbId1,
+                                    Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
+                                    GlobalStateMgrTestUtil.testTxnLable1,
+                                    transactionSource,
+                                    LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
         } catch (Exception e) {
             // TODO: handle exception
         }
@@ -197,36 +199,36 @@ public void testBeginTransactionWithSameLabel() throws LabelAlreadyUsedException
     public void testCommitTransaction1() throws UserException {
         FakeGlobalStateMgr.setGlobalStateMgr(masterGlobalStateMgr);
         long transactionId = masterTransMgr
-                .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
-                        GlobalStateMgrTestUtil.testTxnLable1,
-                        transactionSource,
-                        LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
+                    .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
+                                GlobalStateMgrTestUtil.testTxnLable1,
+                                transactionSource,
+                                LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
         // commit a transaction
         TabletCommitInfo tabletCommitInfo1 = new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1,
-                GlobalStateMgrTestUtil.testBackendId1);
+                    GlobalStateMgrTestUtil.testBackendId1);
         TabletCommitInfo tabletCommitInfo2 = new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1,
-                GlobalStateMgrTestUtil.testBackendId2);
+                    GlobalStateMgrTestUtil.testBackendId2);
         TabletCommitInfo tabletCommitInfo3 = new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1,
-                GlobalStateMgrTestUtil.testBackendId3);
+                    GlobalStateMgrTestUtil.testBackendId3);
         List<TabletCommitInfo> transTablets = Lists.newArrayList();
         transTablets.add(tabletCommitInfo1);
         transTablets.add(tabletCommitInfo2);
         transTablets.add(tabletCommitInfo3);
         masterTransMgr.commitTransaction(GlobalStateMgrTestUtil.testDbId1, transactionId, transTablets,
-                Lists.newArrayList(), null);
+                    Lists.newArrayList(), null);
         TransactionState transactionState = fakeEditLog.getTransaction(transactionId);
         // check status is committed
         assertEquals(TransactionStatus.COMMITTED, transactionState.getTransactionStatus());
         // check replica version
-        Partition testPartition =
-                masterGlobalStateMgr.getDb(GlobalStateMgrTestUtil.testDbId1).getTable(GlobalStateMgrTestUtil.testTableId1)
-                        .getPartition(GlobalStateMgrTestUtil.testPartition1);
+        Partition testPartition = masterGlobalStateMgr.getLocalMetastore()
+                    .getTable(GlobalStateMgrTestUtil.testDbId1, GlobalStateMgrTestUtil.testTableId1)
+                    .getPartition(GlobalStateMgrTestUtil.testPartition1);
         // check partition version
         assertEquals(GlobalStateMgrTestUtil.testStartVersion, testPartition.getVisibleVersion());
         assertEquals(GlobalStateMgrTestUtil.testStartVersion + 2, testPartition.getNextVersion());
         // check partition next version
         LocalTablet tablet = (LocalTablet) testPartition.getIndex(GlobalStateMgrTestUtil.testIndexId1)
-                .getTablet(GlobalStateMgrTestUtil.testTabletId1);
+                    .getTablet(GlobalStateMgrTestUtil.testTabletId1);
         for (Replica replica : tablet.getImmutableReplicas()) {
             assertEquals(GlobalStateMgrTestUtil.testStartVersion, replica.getVersion());
         }
@@ -242,20 +244,20 @@ public void testCommitTransactionWithOneFailed() throws UserException {
         TransactionState transactionState = null;
         FakeGlobalStateMgr.setGlobalStateMgr(masterGlobalStateMgr);
         long transactionId = masterTransMgr
-                .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
-                        GlobalStateMgrTestUtil.testTxnLable1,
-                        transactionSource,
-                        LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
+                    .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
+                                GlobalStateMgrTestUtil.testTxnLable1,
+                                transactionSource,
+                                LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
         // commit a transaction with 1,2 success
         TabletCommitInfo tabletCommitInfo1 = new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1,
-                GlobalStateMgrTestUtil.testBackendId1);
+                    GlobalStateMgrTestUtil.testBackendId1);
         TabletCommitInfo tabletCommitInfo2 = new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1,
-                GlobalStateMgrTestUtil.testBackendId2);
+                    GlobalStateMgrTestUtil.testBackendId2);
         List<TabletCommitInfo> transTablets = Lists.newArrayList();
         transTablets.add(tabletCommitInfo1);
         transTablets.add(tabletCommitInfo2);
         masterTransMgr.commitTransaction(GlobalStateMgrTestUtil.testDbId1, transactionId, transTablets,
-                Lists.newArrayList(), null);
+                    Lists.newArrayList(), null);
 
         // follower globalStateMgr replay the transaction
         transactionState = fakeEditLog.getTransaction(transactionId);
@@ -266,19 +268,19 @@ public void testCommitTransactionWithOneFailed() throws UserException {
         FakeGlobalStateMgr.setGlobalStateMgr(masterGlobalStateMgr);
         // commit another transaction with 1,3 success
         long transactionId2 = masterTransMgr
-                .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
-                        GlobalStateMgrTestUtil.testTxnLable2,
-                        transactionSource,
-                        LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
+                    .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
+                                GlobalStateMgrTestUtil.testTxnLable2,
+                                transactionSource,
+                                LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
         tabletCommitInfo1 = new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1, GlobalStateMgrTestUtil.testBackendId1);
         TabletCommitInfo tabletCommitInfo3 = new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1,
-                GlobalStateMgrTestUtil.testBackendId3);
+                    GlobalStateMgrTestUtil.testBackendId3);
         transTablets = Lists.newArrayList();
         transTablets.add(tabletCommitInfo1);
         transTablets.add(tabletCommitInfo3);
         try {
             masterTransMgr.commitTransaction(GlobalStateMgrTestUtil.testDbId1, transactionId2, transTablets,
-                    Lists.newArrayList(), null);
+                        Lists.newArrayList(), null);
             Assert.fail();
         } catch (TabletQuorumFailedException e) {
             transactionState = masterTransMgr.getTransactionState(GlobalStateMgrTestUtil.testDbId1, transactionId2);
@@ -287,14 +289,15 @@ public void testCommitTransactionWithOneFailed() throws UserException {
         }
         // check replica version
         Partition testPartition =
-                masterGlobalStateMgr.getDb(GlobalStateMgrTestUtil.testDbId1).getTable(GlobalStateMgrTestUtil.testTableId1)
-                        .getPartition(GlobalStateMgrTestUtil.testPartition1);
+                    masterGlobalStateMgr.getLocalMetastore()
+                                .getTable(GlobalStateMgrTestUtil.testDbId1, GlobalStateMgrTestUtil.testTableId1)
+                                .getPartition(GlobalStateMgrTestUtil.testPartition1);
         // check partition version
         assertEquals(GlobalStateMgrTestUtil.testStartVersion, testPartition.getVisibleVersion());
         assertEquals(GlobalStateMgrTestUtil.testStartVersion + 2, testPartition.getNextVersion());
         // check partition next version
         LocalTablet tablet = (LocalTablet) testPartition.getIndex(GlobalStateMgrTestUtil.testIndexId1)
-                .getTablet(GlobalStateMgrTestUtil.testTabletId1);
+                    .getTablet(GlobalStateMgrTestUtil.testTabletId1);
         for (Replica replica : tablet.getImmutableReplicas()) {
             assertEquals(GlobalStateMgrTestUtil.testStartVersion, replica.getVersion());
         }
@@ -310,19 +313,20 @@ public void testCommitTransactionWithOneFailed() throws UserException {
         transTablets.add(tabletCommitInfo2);
         transTablets.add(tabletCommitInfo3);
         masterTransMgr.commitTransaction(GlobalStateMgrTestUtil.testDbId1, transactionId2, transTablets,
-                Lists.newArrayList(), null);
+                    Lists.newArrayList(), null);
         transactionState = fakeEditLog.getTransaction(transactionId2);
         // check status is commit
         assertEquals(TransactionStatus.COMMITTED, transactionState.getTransactionStatus());
         // check replica version
-        testPartition = masterGlobalStateMgr.getDb(GlobalStateMgrTestUtil.testDbId1).getTable(GlobalStateMgrTestUtil.testTableId1)
-                .getPartition(GlobalStateMgrTestUtil.testPartition1);
+        testPartition = masterGlobalStateMgr.getLocalMetastore()
+                    .getTable(GlobalStateMgrTestUtil.testDbId1, GlobalStateMgrTestUtil.testTableId1)
+                    .getPartition(GlobalStateMgrTestUtil.testPartition1);
         // check partition version
         assertEquals(GlobalStateMgrTestUtil.testStartVersion, testPartition.getVisibleVersion());
         assertEquals(GlobalStateMgrTestUtil.testStartVersion + 3, testPartition.getNextVersion());
         // check partition next version
         tablet = (LocalTablet) testPartition.getIndex(GlobalStateMgrTestUtil.testIndexId1)
-                .getTablet(GlobalStateMgrTestUtil.testTabletId1);
+                    .getTablet(GlobalStateMgrTestUtil.testTabletId1);
         for (Replica replica : tablet.getImmutableReplicas()) {
             assertEquals(GlobalStateMgrTestUtil.testStartVersion, replica.getVersion());
         }
@@ -353,35 +357,35 @@ public void testCommitTransactionWithOneFailed() throws UserException {
     @Test
     public void testCommitRoutineLoadTransaction(@Injectable TabletCommitInfo tabletCommitInfo,
                                                  @Mocked EditLog editLog)
-            throws UserException {
+                throws UserException {
         FakeGlobalStateMgr.setGlobalStateMgr(masterGlobalStateMgr);
 
         TabletCommitInfo tabletCommitInfo1 =
-                new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1, GlobalStateMgrTestUtil.testBackendId1);
+                    new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1, GlobalStateMgrTestUtil.testBackendId1);
         TabletCommitInfo tabletCommitInfo2 =
-                new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1, GlobalStateMgrTestUtil.testBackendId2);
+                    new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1, GlobalStateMgrTestUtil.testBackendId2);
         TabletCommitInfo tabletCommitInfo3 =
-                new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1, GlobalStateMgrTestUtil.testBackendId3);
+                    new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1, GlobalStateMgrTestUtil.testBackendId3);
         List<TabletCommitInfo> transTablets = Lists.newArrayList();
         transTablets.add(tabletCommitInfo1);
         transTablets.add(tabletCommitInfo2);
         transTablets.add(tabletCommitInfo3);
 
         KafkaRoutineLoadJob routineLoadJob = new KafkaRoutineLoadJob(1L, "test", 1L, 1L, "host:port",
-                "topic");
+                    "topic");
         List<RoutineLoadTaskInfo> routineLoadTaskInfoList =
-                Deencapsulation.getField(routineLoadJob, "routineLoadTaskInfoList");
+                    Deencapsulation.getField(routineLoadJob, "routineLoadTaskInfoList");
         Map<Integer, Long> partitionIdToOffset = Maps.newHashMap();
         partitionIdToOffset.put(1, 0L);
         KafkaTaskInfo routineLoadTaskInfo =
-                new KafkaTaskInfo(UUID.randomUUID(), routineLoadJob, 20000, System.currentTimeMillis(),
-                        partitionIdToOffset, Config.routine_load_task_timeout_second);
+                    new KafkaTaskInfo(UUID.randomUUID(), routineLoadJob, 20000, System.currentTimeMillis(),
+                                partitionIdToOffset, Config.routine_load_task_timeout_second);
         Deencapsulation.setField(routineLoadTaskInfo, "txnId", 1L);
         routineLoadTaskInfoList.add(routineLoadTaskInfo);
         TransactionState transactionState = new TransactionState(1L, Lists.newArrayList(1L), 1L, "label", null,
-                LoadJobSourceType.ROUTINE_LOAD_TASK, new TxnCoordinator(TxnSourceType.BE, "be1"),
-                routineLoadJob.getId(),
-                Config.stream_load_default_timeout_second);
+                    LoadJobSourceType.ROUTINE_LOAD_TASK, new TxnCoordinator(TxnSourceType.BE, "be1"),
+                    routineLoadJob.getId(),
+                    Config.stream_load_default_timeout_second);
         transactionState.setTransactionStatus(TransactionStatus.PREPARE);
         masterTransMgr.getCallbackFactory().addCallback(routineLoadJob);
         // Deencapsulation.setField(transactionState, "txnStateChangeListener", routineLoadJob);
@@ -429,9 +433,9 @@ LoadJobSourceType.ROUTINE_LOAD_TASK, new TxnCoordinator(TxnSourceType.BE, "be1")
         routineLoadManager.addRoutineLoadJob(routineLoadJob, "db");
 
         Deencapsulation.setField(masterTransMgr.getDatabaseTransactionMgr(GlobalStateMgrTestUtil.testDbId1),
-                "idToRunningTransactionState", idToTransactionState);
+                    "idToRunningTransactionState", idToTransactionState);
         masterTransMgr.commitTransaction(1L, 1L, transTablets, Lists.newArrayList(),
-                txnCommitAttachment);
+                    txnCommitAttachment);
 
         Assert.assertEquals(Long.valueOf(101), Deencapsulation.getField(routineLoadJob, "currentTotalRows"));
         Assert.assertEquals(Long.valueOf(1), Deencapsulation.getField(routineLoadJob, "currentErrorRows"));
@@ -448,31 +452,31 @@ public void testCommitRoutineLoadTransactionWithErrorMax(@Injectable TabletCommi
         FakeGlobalStateMgr.setGlobalStateMgr(masterGlobalStateMgr);
 
         TabletCommitInfo tabletCommitInfo1 =
-                new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1, GlobalStateMgrTestUtil.testBackendId1);
+                    new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1, GlobalStateMgrTestUtil.testBackendId1);
         TabletCommitInfo tabletCommitInfo2 =
-                new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1, GlobalStateMgrTestUtil.testBackendId2);
+                    new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1, GlobalStateMgrTestUtil.testBackendId2);
         TabletCommitInfo tabletCommitInfo3 =
-                new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1, GlobalStateMgrTestUtil.testBackendId3);
+                    new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1, GlobalStateMgrTestUtil.testBackendId3);
         List<TabletCommitInfo> transTablets = Lists.newArrayList();
         transTablets.add(tabletCommitInfo1);
         transTablets.add(tabletCommitInfo2);
         transTablets.add(tabletCommitInfo3);
 
         KafkaRoutineLoadJob routineLoadJob =
-                new KafkaRoutineLoadJob(1L, "test", 1L, 1L, "host:port", "topic");
+                    new KafkaRoutineLoadJob(1L, "test", 1L, 1L, "host:port", "topic");
         List<RoutineLoadTaskInfo> routineLoadTaskInfoList =
-                Deencapsulation.getField(routineLoadJob, "routineLoadTaskInfoList");
+                    Deencapsulation.getField(routineLoadJob, "routineLoadTaskInfoList");
         Map<Integer, Long> partitionIdToOffset = Maps.newHashMap();
         partitionIdToOffset.put(1, 0L);
         KafkaTaskInfo routineLoadTaskInfo =
-                new KafkaTaskInfo(UUID.randomUUID(), routineLoadJob, 20000, System.currentTimeMillis(),
-                        partitionIdToOffset, Config.routine_load_task_timeout_second);
+                    new KafkaTaskInfo(UUID.randomUUID(), routineLoadJob, 20000, System.currentTimeMillis(),
+                                partitionIdToOffset, Config.routine_load_task_timeout_second);
         Deencapsulation.setField(routineLoadTaskInfo, "txnId", 1L);
         routineLoadTaskInfoList.add(routineLoadTaskInfo);
         TransactionState transactionState = new TransactionState(1L, Lists.newArrayList(1L), 1L, "label", null,
-                LoadJobSourceType.ROUTINE_LOAD_TASK, new TxnCoordinator(TxnSourceType.BE, "be1"),
-                routineLoadJob.getId(),
-                Config.stream_load_default_timeout_second);
+                    LoadJobSourceType.ROUTINE_LOAD_TASK, new TxnCoordinator(TxnSourceType.BE, "be1"),
+                    routineLoadJob.getId(),
+                    Config.stream_load_default_timeout_second);
         transactionState.setTransactionStatus(TransactionStatus.PREPARE);
         masterTransMgr.getCallbackFactory().addCallback(routineLoadJob);
         Map<Long, TransactionState> idToTransactionState = Maps.newHashMap();
@@ -519,14 +523,14 @@ LoadJobSourceType.ROUTINE_LOAD_TASK, new TxnCoordinator(TxnSourceType.BE, "be1")
         routineLoadManager.addRoutineLoadJob(routineLoadJob, "db");
 
         Deencapsulation.setField(masterTransMgr.getDatabaseTransactionMgr(GlobalStateMgrTestUtil.testDbId1),
-                "idToRunningTransactionState", idToTransactionState);
+                    "idToRunningTransactionState", idToTransactionState);
         masterTransMgr.commitTransaction(1L, 1L, transTablets, Lists.newArrayList(),
-                txnCommitAttachment);
+                    txnCommitAttachment);
 
         Assert.assertEquals(Long.valueOf(0), Deencapsulation.getField(routineLoadJob, "currentTotalRows"));
         Assert.assertEquals(Long.valueOf(0), Deencapsulation.getField(routineLoadJob, "currentErrorRows"));
         Assert.assertEquals(Long.valueOf(111L),
-                ((KafkaProgress) routineLoadJob.getProgress()).getOffsetByPartition(1));
+                    ((KafkaProgress) routineLoadJob.getProgress()).getOffsetByPartition(1));
         // todo(ml): change to assert queue
         // Assert.assertEquals(0, routineLoadManager.getNeedScheduleTasksQueue().size());
         Assert.assertEquals(RoutineLoadJob.JobState.PAUSED, routineLoadJob.getState());
@@ -534,6 +538,8 @@ LoadJobSourceType.ROUTINE_LOAD_TASK, new TxnCoordinator(TxnSourceType.BE, "be1")
 
     @Test
     public void testFinishTransaction() throws UserException {
+        FakeGlobalStateMgr.setGlobalStateMgr(masterGlobalStateMgr);
+
         long transactionId = masterTransMgr
                 .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
                         GlobalStateMgrTestUtil.testTxnLable1,
@@ -561,8 +567,8 @@ public void testFinishTransaction() throws UserException {
         transactionState = fakeEditLog.getTransaction(transactionId);
         assertEquals(TransactionStatus.VISIBLE, transactionState.getTransactionStatus());
         // check replica version
-        Partition testPartition =
-                masterGlobalStateMgr.getDb(GlobalStateMgrTestUtil.testDbId1).getTable(GlobalStateMgrTestUtil.testTableId1)
+        Partition testPartition = masterGlobalStateMgr.getLocalMetastore()
+                .getDb(GlobalStateMgrTestUtil.testDbId1).getTable(GlobalStateMgrTestUtil.testTableId1)
                         .getPartition(GlobalStateMgrTestUtil.testPartition1);
         // check partition version
         assertEquals(GlobalStateMgrTestUtil.testStartVersion + 1, testPartition.getVisibleVersion());
@@ -587,26 +593,27 @@ public void testFinishTransaction() throws UserException {
     public void testFinishTransactionWithOneFailed() throws UserException {
         TransactionState transactionState = null;
         Partition testPartition =
-                masterGlobalStateMgr.getDb(GlobalStateMgrTestUtil.testDbId1).getTable(GlobalStateMgrTestUtil.testTableId1)
-                        .getPartition(GlobalStateMgrTestUtil.testPartition1);
+                    masterGlobalStateMgr.getLocalMetastore()
+                                .getTable(GlobalStateMgrTestUtil.testDbId1, GlobalStateMgrTestUtil.testTableId1)
+                                .getPartition(GlobalStateMgrTestUtil.testPartition1);
         LocalTablet tablet = (LocalTablet) testPartition.getIndex(GlobalStateMgrTestUtil.testIndexId1)
-                .getTablet(GlobalStateMgrTestUtil.testTabletId1);
+                    .getTablet(GlobalStateMgrTestUtil.testTabletId1);
         FakeGlobalStateMgr.setGlobalStateMgr(masterGlobalStateMgr);
         long transactionId = masterTransMgr
-                .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
-                        GlobalStateMgrTestUtil.testTxnLable1,
-                        transactionSource,
-                        LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
+                    .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
+                                GlobalStateMgrTestUtil.testTxnLable1,
+                                transactionSource,
+                                LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
         // commit a transaction with 1,2 success
         TabletCommitInfo tabletCommitInfo1 = new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1,
-                GlobalStateMgrTestUtil.testBackendId1);
+                    GlobalStateMgrTestUtil.testBackendId1);
         TabletCommitInfo tabletCommitInfo2 = new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1,
-                GlobalStateMgrTestUtil.testBackendId2);
+                    GlobalStateMgrTestUtil.testBackendId2);
         List<TabletCommitInfo> transTablets = Lists.newArrayList();
         transTablets.add(tabletCommitInfo1);
         transTablets.add(tabletCommitInfo2);
         masterTransMgr.commitTransaction(GlobalStateMgrTestUtil.testDbId1, transactionId, transTablets,
-                Lists.newArrayList(), null);
+                    Lists.newArrayList(), null);
 
         // follower globalStateMgr replay the transaction
         transactionState = fakeEditLog.getTransaction(transactionId);
@@ -654,19 +661,19 @@ public void testFinishTransactionWithOneFailed() throws UserException {
         FakeGlobalStateMgr.setGlobalStateMgr(masterGlobalStateMgr);
         // commit another transaction with 1,3 success
         long transactionId2 = masterTransMgr
-                .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
-                        GlobalStateMgrTestUtil.testTxnLable2,
-                        transactionSource,
-                        LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
+                    .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
+                                GlobalStateMgrTestUtil.testTxnLable2,
+                                transactionSource,
+                                LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
         tabletCommitInfo1 = new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1, GlobalStateMgrTestUtil.testBackendId1);
         TabletCommitInfo tabletCommitInfo3 = new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1,
-                GlobalStateMgrTestUtil.testBackendId3);
+                    GlobalStateMgrTestUtil.testBackendId3);
         transTablets = Lists.newArrayList();
         transTablets.add(tabletCommitInfo1);
         transTablets.add(tabletCommitInfo3);
         try {
             masterTransMgr.commitTransaction(GlobalStateMgrTestUtil.testDbId1, transactionId2, transTablets,
-                    Lists.newArrayList(), null);
+                        Lists.newArrayList(), null);
             Assert.fail();
         } catch (TabletQuorumFailedException e) {
             transactionState = masterTransMgr.getTransactionState(GlobalStateMgrTestUtil.testDbId1, transactionId2);
@@ -683,13 +690,14 @@ public void testFinishTransactionWithOneFailed() throws UserException {
         transTablets.add(tabletCommitInfo2);
         transTablets.add(tabletCommitInfo3);
         masterTransMgr.commitTransaction(GlobalStateMgrTestUtil.testDbId1, transactionId2, transTablets,
-                Lists.newArrayList(), null);
+                    Lists.newArrayList(), null);
         transactionState = fakeEditLog.getTransaction(transactionId2);
         // check status is commit
         assertEquals(TransactionStatus.COMMITTED, transactionState.getTransactionStatus());
         // check replica version
-        testPartition = masterGlobalStateMgr.getDb(GlobalStateMgrTestUtil.testDbId1).getTable(GlobalStateMgrTestUtil.testTableId1)
-                .getPartition(GlobalStateMgrTestUtil.testPartition1);
+        testPartition = masterGlobalStateMgr.getLocalMetastore()
+                    .getTable(GlobalStateMgrTestUtil.testDbId1, GlobalStateMgrTestUtil.testTableId1)
+                    .getPartition(GlobalStateMgrTestUtil.testPartition1);
         // check partition version
         assertEquals(GlobalStateMgrTestUtil.testStartVersion + 1, testPartition.getVisibleVersion());
         assertEquals(GlobalStateMgrTestUtil.testStartVersion + 3, testPartition.getNextVersion());
@@ -704,6 +712,7 @@ public void testFinishTransactionWithOneFailed() throws UserException {
         errorReplicaIds = Sets.newHashSet();
         assertEquals(masterTransMgr.canTxnFinished(transactionState, errorReplicaIds, unfinishedBackends), false);
         errorReplicaIds = Sets.newHashSet();
+        FakeGlobalStateMgr.setGlobalStateMgr(masterGlobalStateMgr);
         masterTransMgr.finishTransaction(GlobalStateMgrTestUtil.testDbId1, transactionId2, errorReplicaIds);
         assertEquals(TransactionStatus.VISIBLE, transactionState.getTransactionStatus());
         assertEquals(GlobalStateMgrTestUtil.testStartVersion + 2, replcia1.getVersion());
@@ -734,8 +743,8 @@ public void replayWithExpiredJob() throws Exception {
 
         // 1. replay a normal finished transaction
         TransactionState state =
-                new TransactionState(dbId, new ArrayList<>(), 1, "label_a", null, LoadJobSourceType.BACKEND_STREAMING,
-                        transactionSource, -1, -1);
+                    new TransactionState(dbId, new ArrayList<>(), 1, "label_a", null, LoadJobSourceType.BACKEND_STREAMING,
+                                transactionSource, -1, -1);
         state.setTransactionStatus(TransactionStatus.ABORTED);
         state.setReason("fake reason");
         state.setFinishTime(System.currentTimeMillis() - 2000);
@@ -744,8 +753,8 @@ public void replayWithExpiredJob() throws Exception {
 
         // 2. replay a expired transaction
         TransactionState state2 =
-                new TransactionState(dbId, new ArrayList<>(), 2, "label_b", null, LoadJobSourceType.BACKEND_STREAMING,
-                        transactionSource, -1, -1);
+                    new TransactionState(dbId, new ArrayList<>(), 2, "label_b", null, LoadJobSourceType.BACKEND_STREAMING,
+                                transactionSource, -1, -1);
         state2.setTransactionStatus(TransactionStatus.ABORTED);
         state2.setReason("fake reason");
         state2.setFinishTime(System.currentTimeMillis());
@@ -755,8 +764,8 @@ public void replayWithExpiredJob() throws Exception {
         Thread.sleep(2000);
         // 3. replay a valid transaction, let state expire
         TransactionState state3 =
-                new TransactionState(dbId, new ArrayList<>(), 3, "label_c", null, LoadJobSourceType.BACKEND_STREAMING,
-                        transactionSource, -1, -1);
+                    new TransactionState(dbId, new ArrayList<>(), 3, "label_c", null, LoadJobSourceType.BACKEND_STREAMING,
+                                transactionSource, -1, -1);
         state3.setTransactionStatus(TransactionStatus.ABORTED);
         state3.setReason("fake reason");
         state3.setFinishTime(System.currentTimeMillis());
@@ -787,30 +796,33 @@ public void replayWithExpiredJob() throws Exception {
 
     @Test
     public void testPrepareTransaction() throws UserException {
+        FakeGlobalStateMgr.setGlobalStateMgr(masterGlobalStateMgr);
+
         long transactionId = masterTransMgr
-                .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
-                        GlobalStateMgrTestUtil.testTxnLable1,
-                        transactionSource,
-                        LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
+                    .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
+                                GlobalStateMgrTestUtil.testTxnLable1,
+                                transactionSource,
+                                LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
         // commit a transaction
         TabletCommitInfo tabletCommitInfo1 = new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1,
-                GlobalStateMgrTestUtil.testBackendId1);
+                    GlobalStateMgrTestUtil.testBackendId1);
         TabletCommitInfo tabletCommitInfo2 = new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1,
-                GlobalStateMgrTestUtil.testBackendId2);
+                    GlobalStateMgrTestUtil.testBackendId2);
         TabletCommitInfo tabletCommitInfo3 = new TabletCommitInfo(GlobalStateMgrTestUtil.testTabletId1,
-                GlobalStateMgrTestUtil.testBackendId3);
+                    GlobalStateMgrTestUtil.testBackendId3);
         List<TabletCommitInfo> transTablets = Lists.newArrayList();
         transTablets.add(tabletCommitInfo1);
         transTablets.add(tabletCommitInfo2);
         transTablets.add(tabletCommitInfo3);
         masterTransMgr.prepareTransaction(GlobalStateMgrTestUtil.testDbId1, transactionId, transTablets,
-                Lists.newArrayList(), null);
+                    Lists.newArrayList(), null);
         TransactionState transactionState = fakeEditLog.getTransaction(transactionId);
         assertEquals(TransactionStatus.PREPARED, transactionState.getTransactionStatus());
 
         try {
-            masterTransMgr.commitPreparedTransaction(masterGlobalStateMgr.getDb(GlobalStateMgrTestUtil.testDbId1), transactionId,
-                    (long) 1000);
+            masterTransMgr.commitPreparedTransaction(
+                        masterGlobalStateMgr.getLocalMetastore().getDb(GlobalStateMgrTestUtil.testDbId1), transactionId,
+                        (long) 1000);
             Assert.fail("should throw publish timeout exception");
         } catch (UserException e) {
         }
@@ -825,14 +837,15 @@ public void testPrepareTransaction() throws UserException {
         assertEquals(TransactionStatus.VISIBLE, transactionState.getTransactionStatus());
         // check replica version
         Partition testPartition =
-                masterGlobalStateMgr.getDb(GlobalStateMgrTestUtil.testDbId1).getTable(GlobalStateMgrTestUtil.testTableId1)
-                        .getPartition(GlobalStateMgrTestUtil.testPartition1);
+                    masterGlobalStateMgr.getLocalMetastore()
+                                .getTable(GlobalStateMgrTestUtil.testDbId1, GlobalStateMgrTestUtil.testTableId1)
+                                .getPartition(GlobalStateMgrTestUtil.testPartition1);
         // check partition version
         assertEquals(GlobalStateMgrTestUtil.testStartVersion + 1, testPartition.getVisibleVersion());
         assertEquals(GlobalStateMgrTestUtil.testStartVersion + 2, testPartition.getNextVersion());
         // check partition next version
         LocalTablet tablet = (LocalTablet) testPartition.getIndex(GlobalStateMgrTestUtil.testIndexId1)
-                .getTablet(GlobalStateMgrTestUtil.testTabletId1);
+                    .getTablet(GlobalStateMgrTestUtil.testTabletId1);
         for (Replica replica : tablet.getImmutableReplicas()) {
             if (replica.getId() == GlobalStateMgrTestUtil.testReplicaId1) {
                 assertEquals(GlobalStateMgrTestUtil.testStartVersion, replica.getVersion());
@@ -849,10 +862,10 @@ public void testPrepareTransaction() throws UserException {
     @Test
     public void testSaveLoadJsonFormatImage() throws Exception {
         long transactionId = masterTransMgr
-                .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
-                        GlobalStateMgrTestUtil.testTxnLable1,
-                        transactionSource,
-                        LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
+                    .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
+                                GlobalStateMgrTestUtil.testTxnLable1,
+                                transactionSource,
+                                LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
 
         UtFrameUtils.PseudoImage pseudoImage = new UtFrameUtils.PseudoImage();
         masterTransMgr.saveTransactionStateV2(pseudoImage.getImageWriter());
@@ -868,7 +881,7 @@ public void testSaveLoadJsonFormatImage() throws Exception {
 
     @Test
     public void testRetryCommitOnRateLimitExceededTimeout()
-            throws UserException {
+                throws UserException {
         Database db = new Database(10, "db0");
         GlobalTransactionMgr globalTransactionMgr = spy(new GlobalTransactionMgr(GlobalStateMgr.getCurrentState()));
         DatabaseTransactionMgr dbTransactionMgr = spy(new DatabaseTransactionMgr(10L, GlobalStateMgr.getCurrentState()));
@@ -878,15 +891,15 @@ public void testRetryCommitOnRateLimitExceededTimeout()
         doReturn(transactionState).when(globalTransactionMgr).getTransactionState(db.getId(), 1001);
         doReturn(dbTransactionMgr).when(globalTransactionMgr).getDatabaseTransactionMgr(db.getId());
         doThrow(new CommitRateExceededException(1001, now + 60 * 1000L))
-                .when(dbTransactionMgr)
-                .commitTransaction(1001L, Collections.emptyList(), Collections.emptyList(), null);
+                    .when(dbTransactionMgr)
+                    .commitTransaction(1001L, Collections.emptyList(), Collections.emptyList(), null);
         Assert.assertThrows(CommitRateExceededException.class, () -> globalTransactionMgr.commitAndPublishTransaction(db, 1001,
-                Collections.emptyList(), Collections.emptyList(), 10, null));
+                    Collections.emptyList(), Collections.emptyList(), 10, null));
     }
 
     @Test
     public void testPublishVersionTimeout()
-            throws UserException, LockTimeoutException {
+                throws UserException, LockTimeoutException {
         Database db = new Database(10, "db0");
         GlobalTransactionMgr globalTransactionMgr = spy(new GlobalTransactionMgr(GlobalStateMgr.getCurrentState()));
         DatabaseTransactionMgr dbTransactionMgr = spy(new DatabaseTransactionMgr(10L, GlobalStateMgr.getCurrentState()));
@@ -896,52 +909,52 @@ public void testPublishVersionTimeout()
         doReturn(dbTransactionMgr).when(globalTransactionMgr).getDatabaseTransactionMgr(db.getId());
         doReturn(transactionState).when(globalTransactionMgr).getTransactionState(db.getId(), 1001);
         doReturn(new VisibleStateWaiter(new TransactionState()))
-                .when(dbTransactionMgr)
-                .commitTransaction(1001L, Collections.emptyList(), Collections.emptyList(), null);
+                    .when(dbTransactionMgr)
+                    .commitTransaction(1001L, Collections.emptyList(), Collections.emptyList(), null);
         Assert.assertFalse(globalTransactionMgr.commitAndPublishTransaction(db, 1001,
-                Collections.emptyList(), Collections.emptyList(), 2, null));
+                    Collections.emptyList(), Collections.emptyList(), 2, null));
     }
 
     @Test
     public void testRetryCommitOnRateLimitExceededThrowUnexpectedException()
-            throws UserException {
+                throws UserException {
         Database db = new Database(10, "db0");
         GlobalTransactionMgr globalTransactionMgr = spy(new GlobalTransactionMgr(GlobalStateMgr.getCurrentState()));
         DatabaseTransactionMgr dbTransactionMgr = spy(new DatabaseTransactionMgr(10L, GlobalStateMgr.getCurrentState()));
 
         doReturn(dbTransactionMgr).when(globalTransactionMgr).getDatabaseTransactionMgr(db.getId());
         doThrow(NullPointerException.class)
-                .when(dbTransactionMgr)
-                .commitTransaction(1001L, Collections.emptyList(), Collections.emptyList(), null);
+                    .when(dbTransactionMgr)
+                    .commitTransaction(1001L, Collections.emptyList(), Collections.emptyList(), null);
         Assert.assertThrows(UserException.class, () -> globalTransactionMgr.commitAndPublishTransaction(db, 1001,
-                Collections.emptyList(), Collections.emptyList(), 10, null));
+                    Collections.emptyList(), Collections.emptyList(), 10, null));
     }
 
     @Test
     public void testRetryCommitOnRateLimitExceededThrowLockTimeoutException()
-            throws UserException, LockTimeoutException {
+                throws UserException, LockTimeoutException {
         Database db = new Database(10L, "db0");
         GlobalTransactionMgr globalTransactionMgr = spy(new GlobalTransactionMgr(GlobalStateMgr.getCurrentState()));
         TransactionState transactionState = new TransactionState();
         doReturn(transactionState)
-                .when(globalTransactionMgr)
-                .getTransactionState(10L, 1001L);
+                    .when(globalTransactionMgr)
+                    .getTransactionState(10L, 1001L);
 
         doThrow(LockTimeoutException.class)
-                .when(globalTransactionMgr)
-                .retryCommitOnRateLimitExceeded(db, 1001L, Collections.emptyList(), Collections.emptyList(), null, 10L);
+                    .when(globalTransactionMgr)
+                    .retryCommitOnRateLimitExceeded(db, 1001L, Collections.emptyList(), Collections.emptyList(), null, 10L);
         Assert.assertThrows(LockTimeoutException.class, () -> globalTransactionMgr.commitAndPublishTransaction(db, 1001L,
-                Collections.emptyList(), Collections.emptyList(), 10L, null));
+                    Collections.emptyList(), Collections.emptyList(), 10L, null));
     }
 
     @Test
     public void testGetTransactionNumByCoordinateBe() throws LabelAlreadyUsedException, AnalysisException,
-            RunningTxnExceedException, DuplicatedRequestException {
+                RunningTxnExceedException, DuplicatedRequestException {
         masterTransMgr
-                .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
-                        GlobalStateMgrTestUtil.testTxnLable1,
-                        transactionSourceBe,
-                        LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
+                    .beginTransaction(GlobalStateMgrTestUtil.testDbId1, Lists.newArrayList(GlobalStateMgrTestUtil.testTableId1),
+                                GlobalStateMgrTestUtil.testTxnLable1,
+                                transactionSourceBe,
+                                LoadJobSourceType.FRONTEND, Config.stream_load_default_timeout_second);
         long res = masterTransMgr.getTransactionNumByCoordinateBe("localbe");
         assertEquals(1, res);
     }
@@ -993,16 +1006,16 @@ public void testCommitLockTimeout() throws UserException, LockTimeoutException {
         Database db = new Database(10L, "db0");
         GlobalTransactionMgr globalTransactionMgr = spy(new GlobalTransactionMgr(GlobalStateMgr.getCurrentState()));
         doThrow(LockTimeoutException.class)
-                .when(globalTransactionMgr)
-                .commitAndPublishTransaction(db, 1001L, Collections.emptyList(), Collections.emptyList(), 10L, null);
+                    .when(globalTransactionMgr)
+                    .commitAndPublishTransaction(db, 1001L, Collections.emptyList(), Collections.emptyList(), 10L, null);
         Assert.assertThrows(ErrorReportException.class, () -> globalTransactionMgr.commitAndPublishTransaction(db, 1001L,
-                Collections.emptyList(), Collections.emptyList(), 10L));
+                    Collections.emptyList(), Collections.emptyList(), 10L));
     }
 
     @Test
     public void testCheckValidTimeoutSecond() {
         ExceptionChecker.expectThrowsWithMsg(AnalysisException.class,
-                "Invalid timeout: '1'. Expected values should be between 2 and 3 seconds",
-                () -> GlobalTransactionMgr.checkValidTimeoutSecond(1, 3, 2));
+                    "Invalid timeout: '1'. Expected values should be between 2 and 3 seconds",
+                    () -> GlobalTransactionMgr.checkValidTimeoutSecond(1, 3, 2));
     }
 }
diff --git a/fe/fe-core/src/test/java/com/starrocks/transaction/LakePublishBatchTest.java b/fe/fe-core/src/test/java/com/starrocks/transaction/LakePublishBatchTest.java
index 6a2ba20a979ac8..de9f838446e430 100644
--- a/fe/fe-core/src/test/java/com/starrocks/transaction/LakePublishBatchTest.java
+++ b/fe/fe-core/src/test/java/com/starrocks/transaction/LakePublishBatchTest.java
@@ -24,6 +24,7 @@
 import com.starrocks.common.Config;
 import com.starrocks.qe.ConnectContext;
 import com.starrocks.server.GlobalStateMgr;
+import com.starrocks.server.LocalMetastore;
 import com.starrocks.server.RunMode;
 import com.starrocks.utframe.StarRocksAssert;
 import com.starrocks.utframe.UtFrameUtils;
@@ -90,8 +91,8 @@ public static void afterClass() {
 
     @Test
     public void testNormal() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb(DB);
-        Table table = db.getTable(TABLE);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(DB);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), TABLE);
         List<TabletCommitInfo> transTablets1 = Lists.newArrayList();
         List<TabletCommitInfo> transTablets2 = Lists.newArrayList();
 
@@ -159,8 +160,8 @@ public void testNormal() throws Exception {
 
     @Test
     public void testPublishTransactionState() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb(DB);
-        Table table = db.getTable(TABLE);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(DB);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), TABLE);
         List<TabletCommitInfo> transTablets = Lists.newArrayList();
 
         for (Partition partition : table.getPartitions()) {
@@ -192,8 +193,8 @@ public void testPublishTransactionState() throws Exception {
 
     @Test
     public void testPublishDbDroped() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb(DB);
-        Table table = db.getTable(TABLE);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(DB);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), TABLE);
         List<TabletCommitInfo> transTablets = Lists.newArrayList();
         for (Partition partition : table.getPartitions()) {
             MaterializedIndex baseIndex = partition.getBaseIndex();
@@ -225,7 +226,7 @@ public void testPublishDbDroped() throws Exception {
         globalTransactionMgr.commitTransaction(db.getId(), transactionId6, transTablets,
                 Lists.newArrayList(), null);
 
-        new MockUp<GlobalStateMgr>() {
+        new MockUp<LocalMetastore>() {
             @Mock
             public Database getDb(long dbId) {
                 return null;
@@ -248,8 +249,8 @@ public Database getDb(long dbId) {
 
     @Test
     public void testPublishTableDropped() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb(DB);
-        Table table = db.getTable(TABLE);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(DB);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), TABLE);
         List<TabletCommitInfo> transTablets = Lists.newArrayList();
         for (Partition partition : table.getPartitions()) {
             MaterializedIndex baseIndex = partition.getBaseIndex();
@@ -304,8 +305,8 @@ public Table getTable(String tableName) {
 
     @Test
     public void testTransformBatchToSingle() throws Exception {
-        Database db = GlobalStateMgr.getCurrentState().getDb(DB);
-        Table table = db.getTable(TABLE);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(DB);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), TABLE);
         List<TabletCommitInfo> transTablets1 = Lists.newArrayList();
         List<TabletCommitInfo> transTablets2 = Lists.newArrayList();
 
diff --git a/fe/fe-core/src/test/java/com/starrocks/utframe/StarRocksAssert.java b/fe/fe-core/src/test/java/com/starrocks/utframe/StarRocksAssert.java
index 284dc0a057a9a0..561b0ca9c6a609 100644
--- a/fe/fe-core/src/test/java/com/starrocks/utframe/StarRocksAssert.java
+++ b/fe/fe-core/src/test/java/com/starrocks/utframe/StarRocksAssert.java
@@ -172,7 +172,7 @@ public StarRocksAssert withEnableMV() {
 
     public StarRocksAssert withDatabase(String dbName) throws Exception {
         DropDbStmt dropDbStmt =
-                (DropDbStmt) UtFrameUtils.parseStmtWithNewParser("drop database if exists `" + dbName + "`;", ctx);
+                    (DropDbStmt) UtFrameUtils.parseStmtWithNewParser("drop database if exists `" + dbName + "`;", ctx);
         try {
             GlobalStateMgr.getCurrentState().getMetadata().dropDb(dropDbStmt.getDbName(), dropDbStmt.isForceDrop());
         } catch (MetaNotFoundException e) {
@@ -182,7 +182,7 @@ public StarRocksAssert withDatabase(String dbName) throws Exception {
         }
 
         CreateDbStmt createDbStmt =
-                (CreateDbStmt) UtFrameUtils.parseStmtWithNewParser("create database `" + dbName + "`;", ctx);
+                    (CreateDbStmt) UtFrameUtils.parseStmtWithNewParser("create database `" + dbName + "`;", ctx);
         GlobalStateMgr.getCurrentState().getMetadata().createDb(createDbStmt.getFullDbName());
         return this;
     }
@@ -190,8 +190,8 @@ public StarRocksAssert withDatabase(String dbName) throws Exception {
     public StarRocksAssert createDatabaseIfNotExists(String dbName) throws Exception {
         try {
             CreateDbStmt createDbStmt =
-                    (CreateDbStmt) UtFrameUtils.parseStmtWithNewParser("create database if not exists `"
-                            + dbName + "`;", ctx);
+                        (CreateDbStmt) UtFrameUtils.parseStmtWithNewParser("create database if not exists `"
+                                    + dbName + "`;", ctx);
             GlobalStateMgr.getCurrentState().getMetadata().createDb(createDbStmt.getFullDbName());
         } catch (AlreadyExistsException e) {
             // ignore
@@ -201,15 +201,15 @@ public StarRocksAssert createDatabaseIfNotExists(String dbName) throws Exception
 
     public StarRocksAssert withRole(String roleName) throws Exception {
         CreateRoleStmt createRoleStmt =
-                (CreateRoleStmt) UtFrameUtils.parseStmtWithNewParser("create role " + roleName + ";", ctx);
+                    (CreateRoleStmt) UtFrameUtils.parseStmtWithNewParser("create role " + roleName + ";", ctx);
         GlobalStateMgr.getCurrentState().getAuthorizationMgr().createRole(createRoleStmt);
         return this;
     }
 
     public StarRocksAssert withUser(String user) throws Exception {
         CreateUserStmt createUserStmt =
-                (CreateUserStmt) UtFrameUtils.parseStmtWithNewParser(
-                        "create user " + user + " identified by '';", ctx);
+                    (CreateUserStmt) UtFrameUtils.parseStmtWithNewParser(
+                                "create user " + user + " identified by '';", ctx);
         GlobalStateMgr.getCurrentState().getAuthenticationMgr().createUser(createUserStmt);
         return this;
     }
@@ -221,7 +221,7 @@ public StarRocksAssert withDatabaseWithoutAnalyze(String dbName) throws Exceptio
     }
 
     public boolean databaseExist(String dbName) {
-        Database db = GlobalStateMgr.getCurrentState().getDb("" + dbName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("" + dbName);
         return db != null;
     }
 
@@ -326,7 +326,7 @@ public static void executeWithRetry(RetryableOperation operation, String operati
                 }
                 retryTime++;
                 System.out.println(operationMsg + " failed with " + retryTime + " time retry, msg: " +
-                        e.getMessage() + ", " + Arrays.toString(e.getStackTrace()));
+                            e.getMessage() + ", " + Arrays.toString(e.getStackTrace()));
                 Thread.sleep(500);
             }
         }
@@ -337,7 +337,7 @@ public static void utCreateTableWithRetry(CreateTableStmt createTableStmt, Conne
             CreateTableStmt createTableStmtCopied = createTableStmt;
             if (retryTime > 0) {
                 createTableStmtCopied = (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(
-                        createTableStmt.getOrigStmt().originStmt, ctx);
+                            createTableStmt.getOrigStmt().originStmt, ctx);
             }
             GlobalStateMgr.getCurrentState().getLocalMetastore().createTable(createTableStmtCopied);
         }, "Create Table", 3);
@@ -348,7 +348,7 @@ public static void utDropTableWithRetry(DropTableStmt dropTableStmt, ConnectCont
             DropTableStmt dropTableStmtCopied = dropTableStmt;
             if (retryTime > 0) {
                 dropTableStmtCopied = (DropTableStmt) UtFrameUtils.parseStmtWithNewParser(
-                        dropTableStmt.getOrigStmt().originStmt, ctx);
+                            dropTableStmt.getOrigStmt().originStmt, ctx);
             }
             GlobalStateMgr.getCurrentState().getLocalMetastore().dropTable(dropTableStmtCopied);
         }, "Drop Table", 3);
@@ -369,7 +369,7 @@ public StarRocksAssert withTable(MTable mTable) throws Exception {
 
     public StarRocksAssert withTemporaryTable(String sql) throws Exception {
         CreateTemporaryTableStmt createTableStmt =
-                (CreateTemporaryTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
+                    (CreateTemporaryTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
         createTableStmt.setSessionId(ctx.getSessionId());
         utCreateTableWithRetry(createTableStmt, ctx);
         return this;
@@ -378,7 +378,7 @@ public StarRocksAssert withTemporaryTable(String sql) throws Exception {
     public StarRocksAssert withTemporaryTableLike(String dstTable, String srcTable) throws Exception {
         String sql = "create temporary table " + dstTable + " like " + srcTable;
         CreateTemporaryTableLikeStmt createTemporaryTableLikeStmt =
-                (CreateTemporaryTableLikeStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
+                    (CreateTemporaryTableLikeStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
         createTemporaryTableLikeStmt.setSessionId(ctx.getSessionId());
         utCreateTableWithRetry(createTemporaryTableLikeStmt.getCreateTableStmt(), ctx);
         return this;
@@ -390,7 +390,7 @@ public StarRocksAssert withTable(MTable mTable,
     }
 
     public StarRocksAssert withMTable(String mTable,
-                                       ExceptionRunnable action) {
+                                      ExceptionRunnable action) {
         return withMTableNames(null, ImmutableList.of(mTable), action);
     }
 
@@ -401,9 +401,10 @@ public StarRocksAssert withMTables(List<MTable> mTables,
 
     /**
      * Create tables by using MTables and do insert datas and later actions.
+     *
      * @param cluster pseudo cluster
      * @param mTables mtables to be used for creating tables
-     * @param action action after creating base tables
+     * @param action  action after creating base tables
      * @return return this
      */
     public StarRocksAssert withMTables(PseudoCluster cluster,
@@ -420,7 +421,7 @@ public StarRocksAssert withMTables(PseudoCluster cluster,
                 String sql = mTable.getCreateTableSql();
                 System.out.println(sql);
                 CreateTableStmt createTableStmt =
-                        (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
+                            (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
                 utCreateTableWithRetry(createTableStmt, ctx);
                 names.add(Pair.create(dbName, mTable.getTableName()));
 
@@ -455,17 +456,18 @@ public StarRocksAssert withMTables(PseudoCluster cluster,
 
     /**
      * With input base table's create table sqls and actions.
-     * @param sqls the base table's create table sqls
+     *
+     * @param sqls   the base table's create table sqls
      * @param action action after creating base tables
      * @return return this
      */
     public StarRocksAssert withTables(List<String> sqls,
-                                       ExceptionRunnable action) {
+                                      ExceptionRunnable action) {
         Set<String> tables = Sets.newHashSet();
         try {
             for (String sql : sqls) {
                 CreateTableStmt createTableStmt =
-                        (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
+                            (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
                 utCreateTableWithRetry(createTableStmt, ctx);
                 tables.add(createTableStmt.getTableName());
             }
@@ -474,7 +476,7 @@ public StarRocksAssert withTables(List<String> sqls,
             }
         } catch (Exception e) {
             e.printStackTrace();
-            Assert.fail("Do action failed:" +  e.getMessage());
+            Assert.fail("Do action failed:" + e.getMessage());
         } finally {
             if (action != null) {
                 for (String table : tables) {
@@ -505,7 +507,7 @@ public StarRocksAssert withMTableNames(PseudoCluster cluster,
                 MTable mTable = MSchema.getTable(table);
                 String sql = mTable.getCreateTableSql();
                 CreateTableStmt createTableStmt =
-                        (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
+                            (CreateTableStmt) UtFrameUtils.parseStmtWithNewParser(sql, ctx);
                 utCreateTableWithRetry(createTableStmt, ctx);
 
                 if (cluster != null) {
@@ -569,12 +571,16 @@ public StarRocksAssert useTable(String table) {
     }
 
     public Table getTable(String dbName, String tableName) {
-        return ctx.getGlobalStateMgr().mayGetDb(dbName).map(db -> db.getTable(tableName)).orElse(null);
+        return ctx.getGlobalStateMgr().getLocalMetastore().mayGetDb(dbName)
+                    .map(db -> GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName))
+                    .orElse(null);
     }
 
     public MaterializedView getMv(String dbName, String tableName) {
-        return (MaterializedView) ctx.getGlobalStateMgr().mayGetDb(dbName).map(db -> db.getTable(tableName))
-                .orElse(null);
+        return (MaterializedView) ctx.getGlobalStateMgr().getLocalMetastore()
+                    .mayGetDb(dbName)
+                    .map(db -> GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName))
+                    .orElse(null);
     }
 
     public StarRocksAssert withSingleReplicaTable(String sql) throws Exception {
@@ -609,9 +615,9 @@ public StarRocksAssert withAsyncMvAndRefresh(String sql) throws Exception {
     }
 
     public void withAsyncMv(
-            CreateMaterializedViewStatement createMaterializedViewStatement,
-            boolean isOnlySingleReplica,
-            boolean isRefresh) throws Exception {
+                CreateMaterializedViewStatement createMaterializedViewStatement,
+                boolean isOnlySingleReplica,
+                boolean isRefresh) throws Exception {
         if (isOnlySingleReplica) {
             createMaterializedViewStatement.getProperties().put(PropertyAnalyzer.PROPERTIES_REPLICATION_NUM, "1");
         }
@@ -623,8 +629,9 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
                     if (stmt instanceof InsertStmt) {
                         InsertStmt insertStmt = (InsertStmt) stmt;
                         TableName tableName = insertStmt.getTableName();
-                        Database testDb = GlobalStateMgr.getCurrentState().getDb(stmt.getTableName().getDb());
-                        OlapTable tbl = ((OlapTable) testDb.getTable(tableName.getTbl()));
+                        Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(stmt.getTableName().getDb());
+                        OlapTable tbl = ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                    .getTable(testDb.getFullName(), tableName.getTbl()));
                         for (Partition partition : tbl.getPartitions()) {
                             if (insertStmt.getTargetPartitionIds().contains(partition.getId())) {
                                 long version = partition.getVisibleVersion() + 1;
@@ -643,8 +650,8 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
                 }
             };
             String refreshSql = String.format("refresh materialized view `%s`.`%s` with sync mode;",
-                    createMaterializedViewStatement.getTableName().getDb(),
-                    createMaterializedViewStatement.getTableName().getTbl());
+                        createMaterializedViewStatement.getTableName().getDb(),
+                        createMaterializedViewStatement.getTableName().getTbl());
             ctx.executeSql(refreshSql);
         }
     }
@@ -671,21 +678,21 @@ public StarRocksAssert withView(String sql, ExceptionRunnable action) throws Exc
 
     public StarRocksAssert dropView(String viewName) throws Exception {
         DropTableStmt dropViewStmt =
-                (DropTableStmt) UtFrameUtils.parseStmtWithNewParser("drop view " + viewName + ";", ctx);
+                    (DropTableStmt) UtFrameUtils.parseStmtWithNewParser("drop view " + viewName + ";", ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropTable(dropViewStmt);
         return this;
     }
 
     public StarRocksAssert dropCatalog(String catalogName) throws Exception {
         DropCatalogStmt dropCatalogStmt =
-                (DropCatalogStmt) UtFrameUtils.parseStmtWithNewParser("drop catalog " + catalogName + ";", ctx);
+                    (DropCatalogStmt) UtFrameUtils.parseStmtWithNewParser("drop catalog " + catalogName + ";", ctx);
         GlobalStateMgr.getCurrentState().getCatalogMgr().dropCatalog(dropCatalogStmt);
         return this;
     }
 
     public StarRocksAssert dropDatabase(String dbName) throws Exception {
         DropDbStmt dropDbStmt =
-                (DropDbStmt) UtFrameUtils.parseStmtWithNewParser("drop database " + dbName + ";", ctx);
+                    (DropDbStmt) UtFrameUtils.parseStmtWithNewParser("drop database " + dbName + ";", ctx);
         GlobalStateMgr.getCurrentState().getMetadata().dropDb(dropDbStmt.getDbName(), dropDbStmt.isForceDrop());
         return this;
     }
@@ -721,22 +728,22 @@ public StarRocksAssert dropTables(List<String> tableNames) throws Exception {
 
     public StarRocksAssert dropTable(String tableName) throws Exception {
         DropTableStmt dropTableStmt =
-                (DropTableStmt) UtFrameUtils.parseStmtWithNewParser("drop table " + tableName + ";", ctx);
+                    (DropTableStmt) UtFrameUtils.parseStmtWithNewParser("drop table " + tableName + ";", ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropTable(dropTableStmt);
         return this;
     }
 
     public StarRocksAssert dropTemporaryTable(String tableName, boolean ifExists) throws Exception {
         DropTemporaryTableStmt dropTemporaryTableStmt = (DropTemporaryTableStmt)
-                UtFrameUtils.parseStmtWithNewParser("drop temporary table " + (ifExists ? "if exists " : "")
-                        + tableName + ";", ctx);
+                    UtFrameUtils.parseStmtWithNewParser("drop temporary table " + (ifExists ? "if exists " : "")
+                                + tableName + ";", ctx);
         GlobalStateMgr.getCurrentState().getMetadataMgr().dropTemporaryTable(dropTemporaryTableStmt);
         return this;
     }
 
     public StarRocksAssert dropMaterializedView(String materializedViewName) throws Exception {
         DropMaterializedViewStmt dropMaterializedViewStmt = (DropMaterializedViewStmt) UtFrameUtils.
-                parseStmtWithNewParser("drop materialized view if exists " + materializedViewName + ";", ctx);
+                    parseStmtWithNewParser("drop materialized view if exists " + materializedViewName + ";", ctx);
         GlobalStateMgr.getCurrentState().getLocalMetastore().dropMaterializedView(dropMaterializedViewStmt);
         return this;
     }
@@ -840,8 +847,8 @@ public StarRocksAssert withMaterializedView(String sql, ExceptionRunnable action
     }
 
     public void assertMVWithoutComplexExpression(String dbName, String tableName) {
-        Database db = GlobalStateMgr.getCurrentState().getDb(dbName);
-        Table table = db.getTable(tableName);
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName);
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName);
         if (!(table instanceof OlapTable)) {
             return;
         }
@@ -899,8 +906,8 @@ public StarRocksAssert refreshMvPartition(String sql) throws Exception {
             RefreshMaterializedViewStatement refreshMaterializedViewStatement = (RefreshMaterializedViewStatement) stmt;
 
             TableName mvName = refreshMaterializedViewStatement.getMvName();
-            Database db = GlobalStateMgr.getCurrentState().getDb(mvName.getDb());
-            Table table = db.getTable(mvName.getTbl());
+            Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(mvName.getDb());
+            Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), mvName.getTbl());
             Assert.assertNotNull(table);
             Assert.assertTrue(table instanceof MaterializedView);
             MaterializedView mv = (MaterializedView) table;
@@ -922,6 +929,7 @@ public StarRocksAssert refreshMvPartition(String sql) throws Exception {
 
     /**
      * Wait the input mv refresh task finished.
+     *
      * @param mvId: mv id
      * @return true if the mv refresh task finished, otherwise false.
      */
@@ -944,7 +952,8 @@ public boolean waitRefreshFinished(long mvId) {
 
     /**
      * Refresh materialized view asynchronously.
-     * @param ctx connnect context
+     *
+     * @param ctx    connnect context
      * @param mvName mv's name
      */
     public StarRocksAssert refreshMV(ConnectContext ctx, String mvName) throws Exception {
@@ -952,8 +961,8 @@ public StarRocksAssert refreshMV(ConnectContext ctx, String mvName) throws Excep
         StatementBase stmt = UtFrameUtils.parseStmtWithNewParser(sql, ctx);
         RefreshMaterializedViewStatement refreshMaterializedViewStatement = (RefreshMaterializedViewStatement) stmt;
         TableName tableName = refreshMaterializedViewStatement.getMvName();
-        Database db = GlobalStateMgr.getCurrentState().getDb(tableName.getDb());
-        Table table = db.getTable(tableName.getTbl());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(tableName.getDb());
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), tableName.getTbl());
         Assert.assertNotNull(table);
         Assert.assertTrue(table instanceof MaterializedView);
         ctx.executeSql(sql);
@@ -964,8 +973,8 @@ public StarRocksAssert refreshMV(String sql) throws Exception {
         StatementBase stmt = UtFrameUtils.parseStmtWithNewParser(sql, ctx);
         RefreshMaterializedViewStatement refreshMaterializedViewStatement = (RefreshMaterializedViewStatement) stmt;
         TableName mvName = refreshMaterializedViewStatement.getMvName();
-        Database db = GlobalStateMgr.getCurrentState().getDb(mvName.getDb());
-        Table table = db.getTable(mvName.getTbl());
+        Database db = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(mvName.getDb());
+        Table table = GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(db.getFullName(), mvName.getTbl());
         Assert.assertNotNull(table);
         Assert.assertTrue(table instanceof MaterializedView);
         MaterializedView mv = (MaterializedView) table;
@@ -988,7 +997,7 @@ private void waitingTaskFinish(TaskRun taskRun) {
     }
 
     public void updateTablePartitionVersion(String dbName, String tableName, long version) {
-        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getDb(dbName).getTable(tableName);
+        OlapTable table = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(dbName).getTable(tableName);
         for (PhysicalPartition partition : table.getPhysicalPartitions()) {
             partition.setVisibleVersion(version, System.currentTimeMillis());
             MaterializedIndex baseIndex = partition.getBaseIndex();
@@ -1049,8 +1058,8 @@ public String executeShowResourceUsageSql(String sql) throws DdlException, Analy
         ShowResultSet res = ShowExecutor.execute((ShowStmt) stmt, ctx);
         String header = res.getMetaData().getColumns().stream().map(Column::getName).collect(Collectors.joining("|"));
         String body = res.getResultRows().stream()
-                .map(row -> String.join("|", row))
-                .collect(Collectors.joining("\n"));
+                    .map(row -> String.join("|", row))
+                    .collect(Collectors.joining("\n"));
         return header + "\n" + body;
     }
 
@@ -1076,8 +1085,9 @@ private void checkAlterJob() throws InterruptedException {
             if (alterJobV2.getJobState().isFinalState()) {
                 continue;
             }
-            Database database = GlobalStateMgr.getCurrentState().getDb(alterJobV2.getDbId());
-            Table table = database.getTable(alterJobV2.getTableId());
+            Database database = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb(alterJobV2.getDbId());
+            Table table =
+                        GlobalStateMgr.getCurrentState().getLocalMetastore().getTable(database.getId(), alterJobV2.getTableId());
             Preconditions.checkState(table instanceof OlapTable);
             OlapTable olapTable = (OlapTable) table;
             int retry = 0;
@@ -1168,7 +1178,7 @@ public void analysisError(String... keywords) {
                 explainQuery();
             } catch (AnalysisException | StarRocksPlannerException analysisException) {
                 Assert.assertTrue(analysisException.getMessage(),
-                        Stream.of(keywords).allMatch(analysisException.getMessage()::contains));
+                            Stream.of(keywords).allMatch(analysisException.getMessage()::contains));
                 return;
             } catch (Exception ex) {
                 Assert.fail();
diff --git a/fe/fe-core/src/test/java/com/starrocks/utframe/UtFrameUtils.java b/fe/fe-core/src/test/java/com/starrocks/utframe/UtFrameUtils.java
index 8c89a7d550d092..315b3ad1e0a369 100644
--- a/fe/fe-core/src/test/java/com/starrocks/utframe/UtFrameUtils.java
+++ b/fe/fe-core/src/test/java/com/starrocks/utframe/UtFrameUtils.java
@@ -176,26 +176,26 @@ public class UtFrameUtils {
     private static final AtomicBoolean CREATED_MIN_CLUSTER = new AtomicBoolean(false);
 
     public static final String CREATE_STATISTICS_TABLE_STMT = "CREATE TABLE `table_statistic_v1` (\n" +
-            "  `table_id` bigint(20) NOT NULL COMMENT \"\",\n" +
-            "  `column_name` varchar(65530) NOT NULL COMMENT \"\",\n" +
-            "  `db_id` bigint(20) NOT NULL COMMENT \"\",\n" +
-            "  `table_name` varchar(65530) NOT NULL COMMENT \"\",\n" +
-            "  `db_name` varchar(65530) NOT NULL COMMENT \"\",\n" +
-            "  `row_count` bigint(20) NOT NULL COMMENT \"\",\n" +
-            "  `data_size` bigint(20) NOT NULL COMMENT \"\",\n" +
-            "  `distinct_count` bigint(20) NOT NULL COMMENT \"\",\n" +
-            "  `null_count` bigint(20) NOT NULL COMMENT \"\",\n" +
-            "  `max` varchar(65530) NOT NULL COMMENT \"\",\n" +
-            "  `min` varchar(65530) NOT NULL COMMENT \"\",\n" +
-            "  `update_time` datetime NOT NULL COMMENT \"\"\n" +
-            ") ENGINE=OLAP\n" +
-            "UNIQUE KEY(`table_id`, `column_name`, `db_id`)\n" +
-            "COMMENT \"OLAP\"\n" +
-            "DISTRIBUTED BY HASH(`table_id`, `column_name`, `db_id`) BUCKETS 10\n" +
-            "PROPERTIES (\n" +
-            "\"replication_num\" = \"1\",\n" +
-            "\"in_memory\" = \"false\"\n" +
-            ");";
+                "  `table_id` bigint(20) NOT NULL COMMENT \"\",\n" +
+                "  `column_name` varchar(65530) NOT NULL COMMENT \"\",\n" +
+                "  `db_id` bigint(20) NOT NULL COMMENT \"\",\n" +
+                "  `table_name` varchar(65530) NOT NULL COMMENT \"\",\n" +
+                "  `db_name` varchar(65530) NOT NULL COMMENT \"\",\n" +
+                "  `row_count` bigint(20) NOT NULL COMMENT \"\",\n" +
+                "  `data_size` bigint(20) NOT NULL COMMENT \"\",\n" +
+                "  `distinct_count` bigint(20) NOT NULL COMMENT \"\",\n" +
+                "  `null_count` bigint(20) NOT NULL COMMENT \"\",\n" +
+                "  `max` varchar(65530) NOT NULL COMMENT \"\",\n" +
+                "  `min` varchar(65530) NOT NULL COMMENT \"\",\n" +
+                "  `update_time` datetime NOT NULL COMMENT \"\"\n" +
+                ") ENGINE=OLAP\n" +
+                "UNIQUE KEY(`table_id`, `column_name`, `db_id`)\n" +
+                "COMMENT \"OLAP\"\n" +
+                "DISTRIBUTED BY HASH(`table_id`, `column_name`, `db_id`) BUCKETS 10\n" +
+                "PROPERTIES (\n" +
+                "\"replication_num\" = \"1\",\n" +
+                "\"in_memory\" = \"false\"\n" +
+                ");";
 
     // Help to create a mocked ConnectContext.
     public static ConnectContext createDefaultCtx() {
@@ -212,11 +212,11 @@ public static ConnectContext createDefaultCtx() {
 
     // Parse an origin stmt . Return a StatementBase instance.
     public static StatementBase parseStmtWithNewParser(String originStmt, ConnectContext ctx)
-            throws Exception {
+                throws Exception {
         StatementBase statementBase;
         try {
             statementBase =
-                    com.starrocks.sql.parser.SqlParser.parse(originStmt, ctx.getSessionVariable().getSqlMode()).get(0);
+                        com.starrocks.sql.parser.SqlParser.parse(originStmt, ctx.getSessionVariable().getSqlMode()).get(0);
             com.starrocks.sql.analyzer.Analyzer.analyze(statementBase, ctx);
         } catch (ParsingException | SemanticException e) {
             System.err.println("parse failed: " + e.getMessage());
@@ -231,11 +231,11 @@ public static StatementBase parseStmtWithNewParser(String originStmt, ConnectCon
     }
 
     public static StatementBase parseStmtWithNewParserNotIncludeAnalyzer(String originStmt, ConnectContext ctx)
-            throws Exception {
+                throws Exception {
         StatementBase statementBase;
         try {
             statementBase =
-                    com.starrocks.sql.parser.SqlParser.parse(originStmt, ctx.getSessionVariable().getSqlMode()).get(0);
+                        com.starrocks.sql.parser.SqlParser.parse(originStmt, ctx.getSessionVariable().getSqlMode()).get(0);
         } catch (ParsingException e) {
             if (e.getMessage() == null) {
                 throw e;
@@ -302,7 +302,7 @@ public static synchronized void createMinStarRocksCluster(boolean startBDB, RunM
             // sleep to wait first heartbeat
             int retry = 0;
             while (GlobalStateMgr.getCurrentState().getNodeMgr().getClusterInfo().getBackend(10001).getBePort() == -1 &&
-                    retry++ < 600) {
+                        retry++ < 600) {
                 Thread.sleep(100);
             }
             CREATED_MIN_CLUSTER.set(true);
@@ -362,7 +362,7 @@ private static Backend addMockBackend(MockedBackend backend, int backendId) {
             int starletPort = backend.getStarletPort();
             String workerAddress = backend.getHost() + ":" + starletPort;
             GlobalStateMgr.getCurrentState().getStarOSAgent().addWorker(be.getId(), workerAddress,
-                    StarOSAgent.DEFAULT_WORKER_GROUP_ID);
+                        StarOSAgent.DEFAULT_WORKER_GROUP_ID);
         }
         return be;
     }
@@ -380,7 +380,7 @@ private static ComputeNode addMockComputeNode(MockedBackend backend, int backend
             int starletPort = backend.getStarletPort();
             String workerAddress = backend.getHost() + ":" + starletPort;
             GlobalStateMgr.getCurrentState().getStarOSAgent().addWorker(cn.getId(), workerAddress,
-                    StarOSAgent.DEFAULT_WORKER_GROUP_ID);
+                        StarOSAgent.DEFAULT_WORKER_GROUP_ID);
         }
         return cn;
     }
@@ -452,7 +452,7 @@ public static void validatePlanConnectedness(ExecPlan plan) {
         }
 
         Assert.assertEquals("Some fragments do not belong to the fragment tree",
-                plan.getFragments().size(), visitedFragments.size());
+                    plan.getFragments().size(), visitedFragments.size());
     }
 
     /*
@@ -460,11 +460,11 @@ public static void validatePlanConnectedness(ExecPlan plan) {
      */
     public static Pair<CreateMaterializedViewStatement, ExecPlan> planMVMaintenance(ConnectContext connectContext,
                                                                                     String sql)
-            throws DdlException, CloneNotSupportedException {
+                throws DdlException, CloneNotSupportedException {
         connectContext.setDumpInfo(new QueryDumpInfo(connectContext));
 
         List<StatementBase> statements =
-                com.starrocks.sql.parser.SqlParser.parse(sql, connectContext.getSessionVariable().getSqlMode());
+                    com.starrocks.sql.parser.SqlParser.parse(sql, connectContext.getSessionVariable().getSqlMode());
         connectContext.getDumpInfo().setOriginStmt(sql);
         SessionVariable oldSessionVariable = connectContext.getSessionVariable();
         StatementBase statementBase = statements.get(0);
@@ -532,7 +532,7 @@ private static <R> R buildPlan(ConnectContext connectContext, String originStmt,
     public static String getFragmentPlan(ConnectContext connectContext, String sql, String traceModule) {
         try {
             Pair<String, Pair<ExecPlan, String>> result =
-                    UtFrameUtils.getFragmentPlanWithTrace(connectContext, sql, traceModule);
+                        UtFrameUtils.getFragmentPlanWithTrace(connectContext, sql, traceModule);
             Pair<ExecPlan, String> execPlanWithQuery = result.second;
             String traceLog = execPlanWithQuery.second;
             if (!Strings.isNullOrEmpty(traceLog)) {
@@ -546,7 +546,7 @@ public static String getFragmentPlan(ConnectContext connectContext, String sql,
     }
 
     public static Pair<String, Pair<ExecPlan, String>> getFragmentPlanWithTrace(
-            ConnectContext connectContext, String sql, String module) throws Exception {
+                ConnectContext connectContext, String sql, String module) throws Exception {
         if (Strings.isNullOrEmpty(module)) {
             Pair<String, ExecPlan> planPair = UtFrameUtils.getPlanAndFragment(connectContext, sql);
             Pair<ExecPlan, String> planAndTrace = Pair.create(planPair.second, "");
@@ -573,34 +573,34 @@ public static Pair<String, Pair<ExecPlan, String>> getFragmentPlanWithTrace(
     }
 
     public static Pair<String, ExecPlan> getPlanAndFragment(ConnectContext connectContext, String originStmt)
-            throws Exception {
+                throws Exception {
         return buildPlan(connectContext, originStmt,
-                (context, statementBase, execPlan) -> new Pair<>(printPhysicalPlan(execPlan.getPhysicalPlan()),
-                        execPlan));
+                    (context, statementBase, execPlan) -> new Pair<>(printPhysicalPlan(execPlan.getPhysicalPlan()),
+                                execPlan));
     }
 
     public static DefaultCoordinator startScheduling(ConnectContext connectContext, String originStmt) throws Exception {
         return buildPlan(connectContext, originStmt,
-                (context, statementBase, execPlan) -> {
-                    DefaultCoordinator scheduler = createScheduler(context, statementBase, execPlan);
+                    (context, statementBase, execPlan) -> {
+                        DefaultCoordinator scheduler = createScheduler(context, statementBase, execPlan);
 
-                    scheduler.startScheduling();
+                        scheduler.startScheduling();
 
-                    return scheduler;
-                });
+                        return scheduler;
+                    });
     }
 
     public static Pair<String, DefaultCoordinator> getPlanAndStartScheduling(ConnectContext connectContext, String originStmt)
-            throws Exception {
+                throws Exception {
         return buildPlan(connectContext, originStmt,
-                (context, statementBase, execPlan) -> {
-                    DefaultCoordinator scheduler = createScheduler(context, statementBase, execPlan);
+                    (context, statementBase, execPlan) -> {
+                        DefaultCoordinator scheduler = createScheduler(context, statementBase, execPlan);
 
-                    scheduler.startSchedulingWithoutDeploy();
-                    String plan = scheduler.getSchedulerExplain();
+                        scheduler.startSchedulingWithoutDeploy();
+                        String plan = scheduler.getSchedulerExplain();
 
-                    return Pair.create(plan, scheduler);
-                });
+                        return Pair.create(plan, scheduler);
+                    });
     }
 
     public static DefaultCoordinator getScheduler(ConnectContext connectContext, String originStmt) throws Exception {
@@ -613,14 +613,14 @@ private static DefaultCoordinator createScheduler(ConnectContext context, Statem
         if (statementBase instanceof DmlStmt) {
             if (statementBase instanceof InsertStmt) {
                 scheduler = new DefaultCoordinator.Factory().createInsertScheduler(context,
-                        execPlan.getFragments(), execPlan.getScanNodes(),
-                        execPlan.getDescTbl().toThrift());
+                            execPlan.getFragments(), execPlan.getScanNodes(),
+                            execPlan.getDescTbl().toThrift());
             } else {
                 throw new RuntimeException("can only handle insert DML");
             }
         } else {
             scheduler = new DefaultCoordinator.Factory().createQueryScheduler(context,
-                    execPlan.getFragments(), execPlan.getScanNodes(), execPlan.getDescTbl().toThrift());
+                        execPlan.getFragments(), execPlan.getScanNodes(), execPlan.getDescTbl().toThrift());
         }
 
         return scheduler;
@@ -635,12 +635,12 @@ public static boolean isPrintPlanTableNames() {
     }
 
     private static void testView(ConnectContext connectContext, String originStmt, StatementBase statementBase)
-            throws Exception {
+                throws Exception {
         if (!FeConstants.unitTestView) {
             return;
         }
         if (statementBase instanceof QueryStatement && !connectContext.getDatabase().isEmpty() &&
-                !statementBase.isExplain()) {
+                    !statementBase.isExplain()) {
             String viewName = "view" + INDEX.getAndIncrement();
             String createView = "create view " + viewName + " as " + originStmt;
             CreateViewStmt createTableStmt;
@@ -648,12 +648,12 @@ private static void testView(ConnectContext connectContext, String originStmt, S
                 createTableStmt = (CreateViewStmt) UtFrameUtils.parseStmtWithNewParser(createView, connectContext);
                 try {
                     StatementBase viewStatement =
-                            SqlParser.parse(createTableStmt.getInlineViewDef(),
-                                    connectContext.getSessionVariable().getSqlMode()).get(0);
+                                SqlParser.parse(createTableStmt.getInlineViewDef(),
+                                            connectContext.getSessionVariable().getSqlMode()).get(0);
                     com.starrocks.sql.analyzer.Analyzer.analyze(viewStatement, connectContext);
                 } catch (Exception e) {
                     System.out.println("invalid view def: " + createTableStmt.getInlineViewDef()
-                            + "\nError msg:" + e.getMessage());
+                                + "\nError msg:" + e.getMessage());
                     throw e;
                 }
             } catch (SemanticException | AnalysisException e) {
@@ -675,8 +675,8 @@ public static String explainLogicalPlan(ConnectContext ctx, String sql) throws E
 
     public static String getStmtDigest(ConnectContext connectContext, String originStmt) throws Exception {
         StatementBase statementBase =
-                com.starrocks.sql.parser.SqlParser.parse(originStmt, connectContext.getSessionVariable())
-                        .get(0);
+                    com.starrocks.sql.parser.SqlParser.parse(originStmt, connectContext.getSessionVariable())
+                                .get(0);
         Preconditions.checkState(statementBase instanceof QueryStatement);
         return ConnectProcessor.computeStatementDigest(statementBase);
     }
@@ -686,7 +686,7 @@ private static String initMockEnv(ConnectContext connectContext, QueryDumpInfo r
         StarRocksAssert starRocksAssert = new StarRocksAssert(connectContext);
         if (!starRocksAssert.databaseExist("_statistics_")) {
             starRocksAssert.withDatabaseWithoutAnalyze(StatsConstants.STATISTICS_DB_NAME)
-                    .useDatabase(StatsConstants.STATISTICS_DB_NAME);
+                        .useDatabase(StatsConstants.STATISTICS_DB_NAME);
             starRocksAssert.withTable(CREATE_STATISTICS_TABLE_STMT);
         }
         // prepare dump mock environment
@@ -702,11 +702,11 @@ private static String initMockEnv(ConnectContext connectContext, QueryDumpInfo r
         // mock replay external table info
         if (!replayDumpInfo.getHmsTableMap().isEmpty()) {
             ReplayMetadataMgr replayMetadataMgr = new ReplayMetadataMgr(
-                    GlobalStateMgr.getCurrentState().getLocalMetastore(),
-                    GlobalStateMgr.getCurrentState().getConnectorMgr(),
-                    GlobalStateMgr.getCurrentState().getResourceMgr(),
-                    replayDumpInfo.getHmsTableMap(),
-                    replayDumpInfo.getTableStatisticsMap());
+                        GlobalStateMgr.getCurrentState().getLocalMetastore(),
+                        GlobalStateMgr.getCurrentState().getConnectorMgr(),
+                        GlobalStateMgr.getCurrentState().getResourceMgr(),
+                        replayDumpInfo.getHmsTableMap(),
+                        replayDumpInfo.getTableStatisticsMap());
             GlobalStateMgr.getCurrentState().setMetadataMgr(replayMetadataMgr);
         }
 
@@ -727,7 +727,7 @@ private static String initMockEnv(ConnectContext connectContext, QueryDumpInfo r
         }
 
         Set<String> dbSet = replayDumpInfo.getCreateTableStmtMap().keySet().stream().map(key -> key.split("\\.")[0])
-                .collect(Collectors.toSet());
+                    .collect(Collectors.toSet());
         dbSet.forEach(db -> {
             if (starRocksAssert.databaseExist(db)) {
                 try {
@@ -765,7 +765,7 @@ private static String initMockEnv(ConnectContext connectContext, QueryDumpInfo r
             String dropView = String.format("drop view if exists `%s`.`%s`;", dbName, viewName);
             connectContext.executeSql(dropView);
             String createView = String.format("create view `%s`.`%s` as %s",
-                    dbName, viewName, replayDumpInfo.getCreateViewStmtMap().get(normalizedViewName));
+                        dbName, viewName, replayDumpInfo.getCreateViewStmtMap().get(normalizedViewName));
             starRocksAssert.withView(createView);
         }
         // create materialized views
@@ -794,8 +794,8 @@ private static String initMockEnv(ConnectContext connectContext, QueryDumpInfo r
         // mock table row count
         for (Map.Entry<String, Map<String, Long>> entry : replayDumpInfo.getPartitionRowCountMap().entrySet()) {
             String dbName = entry.getKey().split("\\.")[0];
-            OlapTable replayTable = (OlapTable) GlobalStateMgr.getCurrentState().getDb("" + dbName)
-                    .getTable(entry.getKey().split("\\.")[1]);
+            OlapTable replayTable = (OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("" + dbName)
+                        .getTable(entry.getKey().split("\\.")[1]);
 
             for (Map.Entry<String, Long> partitionEntry : entry.getValue().entrySet()) {
                 setPartitionStatistics(replayTable, partitionEntry.getKey(), partitionEntry.getValue());
@@ -803,14 +803,14 @@ private static String initMockEnv(ConnectContext connectContext, QueryDumpInfo r
         }
         // mock table column statistics
         for (Map.Entry<String, Map<String, ColumnStatistic>> entry : replayDumpInfo.getTableStatisticsMap()
-                .entrySet()) {
+                    .entrySet()) {
             String dbName = entry.getKey().split("\\.")[0];
-            Table replayTable = GlobalStateMgr.getCurrentState().getDb("" + dbName)
-                    .getTable(entry.getKey().split("\\.")[1]);
+            Table replayTable = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("" + dbName)
+                        .getTable(entry.getKey().split("\\.")[1]);
             for (Map.Entry<String, ColumnStatistic> columnStatisticEntry : entry.getValue().entrySet()) {
                 GlobalStateMgr.getCurrentState().getStatisticStorage()
-                        .addColumnStatistic(replayTable, columnStatisticEntry.getKey(),
-                                columnStatisticEntry.getValue());
+                            .addColumnStatistic(replayTable, columnStatisticEntry.getKey(),
+                                        columnStatisticEntry.getValue());
             }
         }
         return replaySql;
@@ -834,7 +834,7 @@ public static LogicalPlan getQueryLogicalPlan(ConnectContext connectContext,
         LogicalPlan logicalPlan;
         try (Timer t = Tracers.watchScope("Transformer")) {
             logicalPlan = new RelationTransformer(columnRefFactory, connectContext)
-                    .transform((statement).getQueryRelation());
+                        .transform((statement).getQueryRelation());
 
         }
         return logicalPlan;
@@ -853,11 +853,11 @@ public static OptExpression getQueryOptExpression(ConnectContext connectContext,
                 optimizer = new Optimizer();
             }
             optimizedPlan = optimizer.optimize(
-                    connectContext,
-                    logicalPlan.getRoot(),
-                    new PhysicalPropertySet(),
-                    new ColumnRefSet(logicalPlan.getOutputColumn()),
-                    columnRefFactory);
+                        connectContext,
+                        logicalPlan.getRoot(),
+                        new PhysicalPropertySet(),
+                        new ColumnRefSet(logicalPlan.getOutputColumn()),
+                        columnRefFactory);
         }
         return optimizedPlan;
     }
@@ -869,7 +869,7 @@ public static OptExpression getQueryOptExpression(ConnectContext connectContext,
     }
 
     private static Pair<String, ExecPlan> getQueryExecPlan(QueryStatement statement, ConnectContext connectContext)
-            throws Exception {
+                throws Exception {
         SessionVariable oldSessionVariable = connectContext.getSessionVariable();
         try {
             if (statement.isExistQueryScopeHint()) {
@@ -883,9 +883,9 @@ private static Pair<String, ExecPlan> getQueryExecPlan(QueryStatement statement,
             ExecPlan execPlan;
             try (Timer t = Tracers.watchScope("Builder")) {
                 execPlan = PlanFragmentBuilder
-                        .createPhysicalPlan(optimizedPlan, connectContext,
-                                logicalPlan.getOutputColumn(), columnRefFactory, new ArrayList<>(),
-                                TResultSinkType.MYSQL_PROTOCAL, true);
+                            .createPhysicalPlan(optimizedPlan, connectContext,
+                                        logicalPlan.getOutputColumn(), columnRefFactory, new ArrayList<>(),
+                                        TResultSinkType.MYSQL_PROTOCAL, true);
             }
             return new Pair<>(LogicalPlanPrinter.print(optimizedPlan), execPlan);
         } finally {
@@ -932,7 +932,7 @@ public static void tearDownTestDump() {
     }
 
     public static ExecPlan getPlanFragmentFromQueryDump(ConnectContext connectContext, QueryDumpInfo dumpInfo)
-            throws Exception {
+                throws Exception {
         String q = initMockEnv(connectContext, dumpInfo);
         try {
             return UtFrameUtils.getPlanAndFragment(connectContext, q).second;
@@ -950,7 +950,7 @@ public static Pair<String, ExecPlan> getNewPlanAndFragmentFromDump(ConnectContex
             StatementBase statementBase;
             try (Timer st = Tracers.watchScope("Parse")) {
                 statementBase = com.starrocks.sql.parser.SqlParser.parse(replaySql,
-                        connectContext.getSessionVariable()).get(0);
+                            connectContext.getSessionVariable()).get(0);
                 if (statementBase instanceof QueryStatement) {
                     replaceTableCatalogName(statementBase);
                 }
@@ -983,7 +983,7 @@ private static void replaceTableCatalogName(StatementBase statementBase) {
             if (tableRelation.getName().getCatalog() != null) {
                 String catalogName = tableRelation.getName().getCatalog();
                 tableRelation.getName().setCatalog(
-                        CatalogMgr.ResourceMappingCatalog.getResourceMappingCatalogName(catalogName, "hive"));
+                            CatalogMgr.ResourceMappingCatalog.getResourceMappingCatalogName(catalogName, "hive"));
             }
         }
     }
@@ -1088,13 +1088,13 @@ public DataInputStream getDataInputStream() throws IOException {
 
         public SRMetaBlockReader getMetaBlockReader() throws IOException {
             JsonReader jsonReader = new JsonReader(new InputStreamReader(new ByteArrayInputStream(buffer.getData(),
-                    0, buffer.getLength())));
+                        0, buffer.getLength())));
             return new SRMetaBlockReaderV2(jsonReader);
         }
 
         public JsonReader getJsonReader() throws IOException {
             return new JsonReader(new InputStreamReader(new ByteArrayInputStream(buffer.getData(),
-                    0, buffer.getLength())));
+                        0, buffer.getLength())));
         }
     }
 
@@ -1104,10 +1104,10 @@ public JsonReader getJsonReader() throws IOException {
     public static class PseudoJournalReplayer {
         // master journal queue
         private static BlockingQueue<JournalTask> masterJournalQueue =
-                new ArrayBlockingQueue<>(Config.metadata_journal_queue_size);
+                    new ArrayBlockingQueue<>(Config.metadata_journal_queue_size);
         // follower journal queue
         private static BlockingQueue<JournalTask> followerJournalQueue =
-                new ArrayBlockingQueue<>(Config.metadata_journal_queue_size);
+                    new ArrayBlockingQueue<>(Config.metadata_journal_queue_size);
         // constantly move master journal to follower and mark succeed
         private static Thread fakeJournalWriter = null;
 
@@ -1151,7 +1151,7 @@ public static synchronized Writable replayNextJournal(short expectCode) throws E
                 }
                 DataOutputBuffer buffer = followerJournalQueue.take().getBuffer();
                 DataInputStream dis =
-                        new DataInputStream(new ByteArrayInputStream(buffer.getData(), 0, buffer.getLength()));
+                            new DataInputStream(new ByteArrayInputStream(buffer.getData(), 0, buffer.getLength()));
                 try {
                     JournalEntity je = new JournalEntity();
                     je.readFields(dis);
@@ -1172,7 +1172,7 @@ public static synchronized void replayJournalToEnd() throws InterruptedException
                 DataOutputBuffer buffer = followerJournalQueue.take().getBuffer();
                 JournalEntity je = new JournalEntity();
                 try (DataInputStream dis = new DataInputStream(
-                        new ByteArrayInputStream(buffer.getData(), 0, buffer.getLength()))) {
+                            new ByteArrayInputStream(buffer.getData(), 0, buffer.getLength()))) {
                     je.readFields(dis);
                     GlobalStateMgr.getCurrentState().getEditLog().loadJournal(GlobalStateMgr.getCurrentState(), je);
                     // System.out.println("replayed journal type: " + je.getOpCode());
@@ -1213,11 +1213,11 @@ public static ConnectContext initCtxForNewPrivilege(UserIdentity userIdentity) t
 
     public static boolean matchPlanWithoutId(String expect, String actual) {
         String trimedExpect = expect.replaceAll("\\d+:\\s*", "")
-                .replaceAll("\\[\\d+,", "[")
-                .replaceAll("<slot \\d+>", "<slot>");
+                    .replaceAll("\\[\\d+,", "[")
+                    .replaceAll("<slot \\d+>", "<slot>");
         String trimedActual = actual.replaceAll("\\d+:\\s*", "")
-                .replaceAll("\\[\\d+,", "[")
-                .replaceAll("<slot \\d+>", "<slot>");
+                    .replaceAll("\\[\\d+,", "[")
+                    .replaceAll("<slot \\d+>", "<slot>");
         boolean ret = trimedActual.contains(trimedExpect);
         if (!ret) {
             System.out.println("trimedExpect:");
@@ -1290,8 +1290,8 @@ public static void setDefaultConfigForAsyncMVTest(ConnectContext connectContext)
         // task run will only refresh 1 partition and will produce wrong result.
         Config.default_mv_partition_refresh_number = -1;
 
-        // Enable mv refresh insert strict in test
-        Config.enable_mv_refresh_insert_strict = true;
+        // Enable mv refresh fail on filter data in test
+        Config.mv_refresh_fail_on_filter_data = true;
 
         // Enable mv rewrite in mv refresh by default
         Config.enable_mv_refresh_query_rewrite = true;
@@ -1338,8 +1338,9 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
                 if (stmt instanceof InsertStmt) {
                     InsertStmt insertStmt = (InsertStmt) stmt;
                     TableName tableName = insertStmt.getTableName();
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-                    OlapTable tbl = ((OlapTable) testDb.getTable(tableName.getTbl()));
+                    Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+                    OlapTable tbl = ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                .getTable(testDb.getFullName(), tableName.getTbl()));
                     if (tbl != null) {
                         for (Long partitionId : insertStmt.getTargetPartitionIds()) {
                             Partition partition = tbl.getPartition(partitionId);
@@ -1349,8 +1350,9 @@ public void handleDMLStmt(ExecPlan execPlan, DmlStmt stmt) throws Exception {
                 } else if (stmt instanceof DeleteStmt) {
                     DeleteStmt delete = (DeleteStmt) stmt;
                     TableName tableName = delete.getTableName();
-                    Database testDb = GlobalStateMgr.getCurrentState().getDb("test");
-                    OlapTable tbl = ((OlapTable) testDb.getTable(tableName.getTbl()));
+                    Database testDb = GlobalStateMgr.getCurrentState().getLocalMetastore().getDb("test");
+                    OlapTable tbl = ((OlapTable) GlobalStateMgr.getCurrentState().getLocalMetastore()
+                                .getTable(testDb.getFullName(), tableName.getTbl()));
                     tbl.setHasDelete();
                 }
             }
@@ -1367,7 +1369,7 @@ private static void processQueryScopeHint(StatementBase parsedStmt, ConnectConte
                 }
                 for (Map.Entry<String, String> entry : hint.getValue().entrySet()) {
                     VariableMgr.setSystemVariable(clonedSessionVariable,
-                            new SystemVariable(entry.getKey(), new StringLiteral(entry.getValue())), true);
+                                new SystemVariable(entry.getKey(), new StringLiteral(entry.getValue())), true);
                 }
             } else if (hint instanceof UserVariableHint) {
                 UserVariableHint userVariableHint = (UserVariableHint) hint;
diff --git a/fe/pom.xml b/fe/pom.xml
index 68431ef30b7c36..0bd550fac76ab8 100644
--- a/fe/pom.xml
+++ b/fe/pom.xml
@@ -299,7 +299,7 @@ under the License.
             <dependency>
                 <groupId>com.starrocks</groupId>
                 <artifactId>starrocks-bdb-je</artifactId>
-                <version>18.3.18</version>
+                <version>18.3.19</version>
             </dependency>
 
             <!-- https://mvnrepository.com/artifact/de.jflex/jflex -->
diff --git a/gensrc/proto/lake_types.proto b/gensrc/proto/lake_types.proto
index 8bcd0fe3b540e0..1c0c3d71b80fdc 100644
--- a/gensrc/proto/lake_types.proto
+++ b/gensrc/proto/lake_types.proto
@@ -59,6 +59,7 @@ message DeltaColumnGroupVerPB {
     repeated string column_files = 2;
     // To do conflict check with compaction task
     repeated int64 versions = 3;
+    repeated bytes encryption_metas = 4;
 }
 
 message DeltaColumnGroupMetadataPB {
@@ -84,6 +85,7 @@ message DelfileWithRowsetId {
     //      there are <DELETE, DELETE> in a transaction, so the `op_offset` of this DELETE is 0.
     //      And rssid of them will be rowset_id + [0, 0].
     optional uint32 op_offset = 3;
+    optional bytes encryption_meta = 4;
 }
 
 message RowsetMetadataPB {
diff --git a/gensrc/proto/olap_common.proto b/gensrc/proto/olap_common.proto
index 4834fed4e0d388..0b79253f5ef87c 100644
--- a/gensrc/proto/olap_common.proto
+++ b/gensrc/proto/olap_common.proto
@@ -60,6 +60,7 @@ message OldDeltaColumnGroupPB {
 message DeltaColumnGroupPB {
     repeated DeltaColumnGroupColumnIdsPB column_ids = 1;
     repeated string column_files = 2;
+    repeated bytes encryption_metas = 3;
 }
 
 message DeltaColumnGroupListPB {
diff --git a/gensrc/proto/tablet_schema.proto b/gensrc/proto/tablet_schema.proto
index d77d562e345955..7a9e1c0d04021d 100644
--- a/gensrc/proto/tablet_schema.proto
+++ b/gensrc/proto/tablet_schema.proto
@@ -49,6 +49,14 @@ enum KeysType {
     PRIMARY_KEYS = 10;
 }
 
+message AggStateDescPB {
+    optional string agg_func_name = 1;
+    repeated PTypeDesc arg_types = 2;
+    optional PTypeDesc ret_type = 3;
+    optional bool is_result_nullable = 4;
+    optional int32 func_version = 5;
+}
+
 message ColumnPB {
     required int32 unique_id = 1;
     optional string name = 2;
@@ -68,6 +76,8 @@ message ColumnPB {
     optional bool visible = 16 [default=true];
     repeated ColumnPB children_columns = 17;
     optional bool is_auto_increment = 18;
+    // agg_state type
+    optional AggStateDescPB agg_state_desc = 19;
 }
 
 message TabletSchemaPB {
diff --git a/gensrc/thrift/Descriptors.thrift b/gensrc/thrift/Descriptors.thrift
index cd08da4c1183d6..ebe44c963dc37b 100644
--- a/gensrc/thrift/Descriptors.thrift
+++ b/gensrc/thrift/Descriptors.thrift
@@ -215,6 +215,7 @@ struct TColumn {
     9: optional bool is_auto_increment
     10: optional i32 col_unique_id  = -1
     11: optional bool has_bitmap_index = false
+    12: optional Types.TAggStateDesc agg_state_desc
                                                                                                       
     // How many bytes used for short key index encoding.
     // For fixed-length column, this value may be ignored by BE when creating a tablet.
diff --git a/gensrc/thrift/FrontendService.thrift b/gensrc/thrift/FrontendService.thrift
index a58dbd42680e47..c7841460494db6 100644
--- a/gensrc/thrift/FrontendService.thrift
+++ b/gensrc/thrift/FrontendService.thrift
@@ -405,6 +405,8 @@ struct TMaterializedViewStatus {
 
     26: optional string extra_message
     27: optional string query_rewrite_status
+
+    28: optional string creator
 }
 
 struct TListPipesParams {
@@ -496,6 +498,7 @@ struct TTaskInfo {
     6: optional i64 expire_time
     7: optional string properties
     8: optional string catalog
+    9: optional string creator
 }
 
 struct TGetTaskInfoResult {
diff --git a/gensrc/thrift/PlanNodes.thrift b/gensrc/thrift/PlanNodes.thrift
index 822834e5f12a78..cbf9149e631a03 100644
--- a/gensrc/thrift/PlanNodes.thrift
+++ b/gensrc/thrift/PlanNodes.thrift
@@ -670,6 +670,7 @@ struct THashJoinNode {
   // used in pipeline engine
   55: optional bool interpolate_passthrough = false
   56: optional bool late_materialization = false
+  57: optional bool enable_partition_hash_join = false
 }
 
 struct TMergeJoinNode {
diff --git a/gensrc/thrift/Types.thrift b/gensrc/thrift/Types.thrift
index 35ce762776a747..39d52f2023338c 100644
--- a/gensrc/thrift/Types.thrift
+++ b/gensrc/thrift/Types.thrift
@@ -163,7 +163,8 @@ enum TAggregationType {
     NONE,
     BITMAP_UNION,
     REPLACE_IF_NOT_NULL,
-    PERCENTILE_UNION
+    PERCENTILE_UNION,
+    AGG_STATE_UNION
 }
 
 enum TPushType {
@@ -327,6 +328,14 @@ struct TTableFunction {
   3: optional bool is_left_join
 }
 
+struct TAggStateDesc {
+    1: optional string agg_func_name
+    2: optional list<TTypeDesc> arg_types
+    3: optional TTypeDesc ret_type
+    4: optional bool result_nullable
+    5: optional i32 func_version
+}
+
 // Represents a function in the Catalog.
 struct TFunction {
   // Fully qualified function name.
@@ -359,6 +368,7 @@ struct TFunction {
 
   11: optional i64 id
   12: optional string checksum
+  13: optional TAggStateDesc agg_state_desc
 
   // Builtin Function id, used to mark the function in the vectorization engine,
   // and it's different with `id` because `id` is use for serialized and cache
diff --git a/gensrc/thrift/WorkGroup.thrift b/gensrc/thrift/WorkGroup.thrift
index 9f125671181243..a1232aab37ddbf 100644
--- a/gensrc/thrift/WorkGroup.thrift
+++ b/gensrc/thrift/WorkGroup.thrift
@@ -39,6 +39,8 @@ struct TWorkGroup {
   13: optional i64 big_query_cpu_second_limit
   14: optional double spill_mem_limit_threshold
 
+  15: optional i32 dedicated_cpu_cores
+
   100: optional i32 max_cpu_cores
 }
 
diff --git a/java-extensions/iceberg-metadata-reader/src/main/java/com/starrocks/connector/iceberg/IcebergFilesTableScanner.java b/java-extensions/iceberg-metadata-reader/src/main/java/com/starrocks/connector/iceberg/IcebergFilesTableScanner.java
index 67cf09a59a0db8..cb1ecb30924e09 100644
--- a/java-extensions/iceberg-metadata-reader/src/main/java/com/starrocks/connector/iceberg/IcebergFilesTableScanner.java
+++ b/java-extensions/iceberg-metadata-reader/src/main/java/com/starrocks/connector/iceberg/IcebergFilesTableScanner.java
@@ -147,6 +147,9 @@ private Object get(String columnName, ContentFile<?> file) {
     }
 
     private Map<Integer, String> getIntegerStringMap(Map<Integer, ByteBuffer> value) {
+        if (value == null) {
+            return null;
+        }
         return value.entrySet().stream()
                 .filter(entry -> idToTypeMapping.containsKey(entry.getKey()))
                 .collect(toImmutableMap(
diff --git a/test/common/data/stream_load/sr_struct_schema_change_data1.json b/test/common/data/stream_load/sr_struct_schema_change_data1.json
new file mode 100644
index 00000000000000..faf9c0f42be343
--- /dev/null
+++ b/test/common/data/stream_load/sr_struct_schema_change_data1.json
@@ -0,0 +1,325 @@
+{
+    "si": "asdf",
+    "ss": "asdfasdf",
+    "ts": "2024-08-30T19:02:13.44Z",
+    "uid": "dafasdf",
+    "item_appeasement__sms__a": {
+        "merchvattot": {
+            "amount": 120,
+            "currency": "USD"
+        },
+        "merchdsptot": {
+            "amount": 5,
+            "currency": "USD"
+        },
+        "merchprmtot": {
+            "amount": 10,
+            "currency": "USD"
+        },
+        "merchvatprmtot": {
+            "amount": 12,
+            "currency": "USD"
+        },
+        "merchdspprmtot": {
+            "amount": 1,
+            "currency": "USD"
+        },
+        "merchdscntdtot": {
+            "amount": 2,
+            "currency": "USD"
+        },
+        "merchvatdscntdtot": {
+            "amount": 0.4,
+            "currency": "USD"
+        },
+        "merchdspdscntdtot": {
+            "amount": 0.2,
+            "currency": "USD"
+        },
+        "merchtxtot": {
+            "amount": 0.3,
+            "currency": "USD"
+        },
+        "merchtxliablty": {
+            "amount": 0.1,
+            "currency": "USD"
+        },
+        "txbtot": {
+            "amount": 0,
+            "currency": "USD"
+        },
+        "ntxbtot": {
+            "amount": 0,
+            "currency": "USD"
+        },
+        "dscntbtot": {
+            "amount": 0,
+            "currency": "USD"
+        },
+        "shptot": {
+            "amount": 15,
+            "currency": "USD"
+        },
+        "shpvattot": {
+            "amount": 2.7,
+            "currency": "USD"
+        },
+        "shpdsptot": {
+            "amount": 1.5,
+            "currency": "USD"
+        },
+        "shpprmtot": {
+            "amount": 0.75,
+            "currency": "USD"
+        },
+        "shpvatprmtot": {
+            "amount": 0.15,
+            "currency": "USD"
+        },
+        "shpdspprmtot": {
+            "amount": 0.05,
+            "currency": "USD"
+        },
+        "shpdscntdtot": {
+            "amount": 1,
+            "currency": "USD"
+        },
+        "shpvatdscntdtot": {
+            "amount": 0.2,
+            "currency": "USD"
+        },
+        "shpdspdscntdtot": {
+            "amount": 0.1,
+            "currency": "USD"
+        },
+        "shptxtot": {
+            "amount": 0.5,
+            "currency": "USD"
+        },
+        "shptxliablty": {
+            "amount": 0.2,
+            "currency": "USD"
+        },
+        "hndtot": {
+            "amount": 20,
+            "currency": "USD"
+        },
+        "hndvattot": {
+            "amount": 4,
+            "currency": "USD"
+        },
+        "hnddsptot": {
+            "amount": 2,
+            "currency": "USD"
+        },
+        "hndprmtot": {
+            "amount": 1,
+            "currency": "USD"
+        },
+        "hndvatprmtot": {
+            "amount": 0.2,
+            "currency": "USD"
+        },
+        "hnddspprmtot": {
+            "amount": 0.1,
+            "currency": "USD"
+        },
+        "hnddscntdtot": {
+            "amount": 0.5,
+            "currency": "USD"
+        },
+        "hndvatdscntdtot": {
+            "amount": 0.1,
+            "currency": "USD"
+        },
+        "hnddspdscntdtot": {
+            "amount": 0.05,
+            "currency": "USD"
+        },
+        "hndtxtot": {
+            "amount": 0.3,
+            "currency": "USD"
+        },
+        "hndtxliablty": {
+            "amount": 0.1,
+            "currency": "USD"
+        },
+        "ordtot": {
+            "amount": 150,
+            "currency": "USD"
+        },
+        "ltyearned": {
+            "amount": 5,
+            "currency": "USD"
+        },
+        "ltyused": {
+            "amount": 1,
+            "currency": "USD"
+        },
+        "prmtot": {
+            "amount": 0,
+            "currency": "USD"
+        },
+        "txtot": {
+            "amount": 0,
+            "currency": "USD"
+        },
+        "appitms": [
+            {
+                "item_id": "item1",
+                "quantity": 2,
+                "price": 50
+            },
+            {
+                "item_id": "item2",
+                "quantity": 1,
+                "price": 100
+            }
+        ],
+        "qty": 3,
+        "shpqty": 1,
+        "supcnclqty": 0,
+        "uom": "pcs",
+        "txexempt": false,
+        "prmapp": true,
+        "mrkdnamt": {
+            "amount": 0,
+            "currency": "USD"
+        },
+        "mrkdntot": {
+            "amount": 0,
+            "currency": "USD"
+        },
+        "retailprice": {
+            "amount": 150,
+            "currency": "USD"
+        },
+        "retailtot": {
+            "amount": 150,
+            "currency": "USD"
+        },
+        "merchprice": {
+            "amount": 100,
+            "currency": "USD"
+        },
+        "merchtot": {
+            "amount": 100,
+            "currency": "USD"
+        },
+        "merchvatdtls": "xxxxxxx",
+        "merchvatratedtrm": "xxxxx",
+        "merchvatrate": 20,
+        "merchpricedvatrate": 15,
+        "merchvatcntry": "USA",
+        "merchvatamt": {
+            "amount": 20,
+            "currency": "USD"
+        },
+        "merchdspprice": {
+            "amount": 95,
+            "currency": "USD"
+        },
+        "merchprmpct": 10,
+        "merchprmamt": {
+            "amount": 10,
+            "currency": "USD"
+        },
+        "merchvatprmamt": {
+            "amount": 2,
+            "currency": "USD"
+        },
+        "merchdspprmamt": {
+            "amount": 1,
+            "currency": "USD"
+        },
+        "merchtxrate": 5,
+        "shpvatdtls": "xxxxxxxxx",
+        "shpvatratedtrm": "Annual",
+        "shpvatrate": 18,
+        "shppricedvatrate": 12,
+        "shpvatcntry": "USA",
+        "shpprmpct": 5,
+        "shptxrate": 3,
+        "hndvatdtls": "xxxxxxxxxx",
+        "hndvatratedtrm": "Annual",
+        "hndvatrate": 22,
+        "hndpricedvatrate": 14,
+        "hndvatcntry": "USA",
+        "hndprmpct": 8,
+        "hndtxrate": 2,
+        "lnitmtot": {
+            "amount": 0,
+            "currency": "USD"
+        },
+        "prmreimb": {
+            "amount": 0,
+            "currency": "USD"
+        },
+        "mrltot": {
+            "amount": 0,
+            "currency": "USD"
+        },
+        "mrlprmtot": {
+            "amount": 0,
+            "currency": "USD"
+        },
+        "mrldscntdtot": {
+            "amount": 0,
+            "currency": "USD"
+        },
+        "payment": {
+            "method": "xxxxxxx",
+            "amount": 150,
+            "currency": "USD"
+        },
+        "refund": {
+            "merchtxtot": {
+                "amount": 0,
+                "currency": "USD"
+            },
+            "shptot": {
+                "amount": 0,
+                "currency": "USD"
+            },
+            "shptxtot": {
+                "amount": 0,
+                "currency": "USD"
+            },
+            "hndtot": {
+                "amount": 0,
+                "currency": "USD"
+            },
+            "hndtxtot": {
+                "amount": 0,
+                "currency": "USD"
+            },
+            "mrltot": {
+                "amount": 0,
+                "currency": "USD"
+            },
+            "mrltxtot": {
+                "amount": 0,
+                "currency": "USD"
+            },
+            "rstkfee": {
+                "amount": 0,
+                "currency": "USD"
+            },
+            "adjtot": {
+                "amount": 0,
+                "currency": "USD"
+            },
+            "ltyclaw": {
+                "amount": 0,
+                "currency": "USD"
+            },
+            "lnitms": [
+                {
+                    "item_id": "xxxxxxx",
+                    "quantity": 1,
+                    "price": 50
+                }
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/test/common/data/stream_load/sr_struct_schema_change_data2.json b/test/common/data/stream_load/sr_struct_schema_change_data2.json
new file mode 100644
index 00000000000000..43dfcaa71933ff
--- /dev/null
+++ b/test/common/data/stream_load/sr_struct_schema_change_data2.json
@@ -0,0 +1,128 @@
+{
+    "v6": null,
+    "ln": null,
+    "lo": null,
+    "account_phone_change_confirm__sms__a": null,
+    "item_distribution_reship_requested__sms__a": null,
+    "pt": null,
+    "tx": null,
+    "tz": null,
+    "pv": null,
+    "order_return_mrl_refund_requested__sms__a": null,
+    "lt": null,
+    "ua": null,
+    "dp": null,
+    "uc": null,
+    "ud": null,
+    "ds": null,
+    "item_appeasement__sms__a": null,
+    "order_shipping_address_update_requested__sms__a": null,
+    "order_fraudstatus_reject__sms__a": null,
+    "mc": null,
+    "original_ts": "2024-08-22T23:48:13.437Z",
+    "ia": "xxxxxxxx-a21f-451a-9b0c-xxxxxxxx",
+    "id": null,
+    "s4": null,
+    "checkoutcs__sms__a": null,
+    "s6": null,
+    "item_deliver__sms__a": null,
+    "ei": null,
+    "ai": null,
+    "eo": "shruti",
+    "notifyme__sms__a": null,
+    "et": "ACCOUNT_ONE_TIME_CODE_SMS.SMS",
+    "ix": null,
+    "item_return_dispositioned__sms__a": null,
+    "order_recovery_payment_rejected__sms__a": null,
+    "item_refund_requested__sms__a": null,
+    "rc": -7194765972940041000,
+    "order_recovery_payment_error__sms__a": null,
+    "at": null,
+    "av": null,
+    "rq": null,
+    "bc": null,
+    "fi": null,
+    "ns": null,
+    "order_shipping_method_update_requested__sms__a": null,
+    "ft": null,
+    "uid": "xxxxxxxxxxxxxxxxxxxx",
+    "sg": null,
+    "si": "xxxxxxxx-883b-4b98-87ad-xxxxxxxxx",
+    "ka": null,
+    "account_one_time_code_sms__sms__a": {
+        "message": "xxxxxx",
+        "parentPSID": 608111,
+        "subscriberKeyHash": "",
+        "sms": "{\"responseURI\":\"/2010-04-01/Accounts/xxxxxxxxxxxx/Messages/xxxxxxxxxxxxxxxxxx.json\",\"sid\":\"xxxxxxxxxx\",\"campaign_name\":\"xxxx\",\"messagingServiceID\":\"xxxxxxxxxxx\"}",
+        "messageKey": "xxxxxxxxxxxx",
+        "inputEvent": "xxxxxxx",
+        "mode": "xxx",
+        "emailName": "xxxxxxxxx",
+        "status": 200,
+        "triggerId": "xxxxxxxxx",
+        "notificationName": "xxxx",
+        "trigger": "transaction",
+        "resendEvent": false,
+        "loginAttemptId": "xxxxxxx-74e4-4c09-be4f-xxxxxxxxxx",
+        "sessionId": null
+    },
+    "og": null,
+    "sm": null,
+    "oi": null,
+    "sp": null,
+    "enriched_attrs": {
+        "uid": "xxxxxxxxxxxxxxxxxxxx",
+        "enriched_ts": "2024-08-22T23:48:13.440Z",
+        "enriched_ts_long": 1724370493440,
+        "create_ts": 1724370493437,
+        "message_ts": 1724370493437,
+        "sessionId": null,
+        "version": "2.13",
+        "originRQ": null,
+        "originRC": "-7194765972940040801",
+        "rc_str": "9c270e7794d7559f",
+        "st": "xxxxxxx",
+        "tm": null,
+        "og": null,
+        "dept": null,
+        "bs": "Unknown",
+        "bsr": "Unknown",
+        "sprtnr": "Unknown",
+        "site_lkp_ts": 1724370281162,
+        "bot": null,
+        "errors": null
+    },
+    "ss": null,
+    "st": 608111,
+    "c": null,
+    "os": null,
+    "d": null,
+    "account_phone_change_notify__sms__a": null,
+    "notification__sms__a": null,
+    "e": null,
+    "ci": null,
+    "cl": null,
+    "order_return_mrl_waive_requested__sms__a": null,
+    "q": null,
+    "rpn": null,
+    "ct": null,
+    "pa": null,
+    "s": null,
+    "pc": null,
+    "tg": null,
+    "item_carrier_notified__sms__a": null,
+    "t": null,
+    "pd": null,
+    "fancash__sms__a": null,
+    "item_cancelled__sms__a": null,
+    "ti": null,
+    "x": null,
+    "tm": null,
+    "xs": null,
+    "xt": null,
+    "da": null,
+    "item_out_for_delivery__sms__a": null,
+    "pn": null,
+    "v4": null,
+    "ts": "2024-08-22T23:48:13.44Z"
+}
\ No newline at end of file
diff --git a/test/lib/choose_cases.py b/test/lib/choose_cases.py
index dd3ff406278add..03b8f2b6099bd1 100644
--- a/test/lib/choose_cases.py
+++ b/test/lib/choose_cases.py
@@ -378,7 +378,7 @@ def __read_single_stat_and_result(_line_content, _line_id, _stat_list, _res_list
                         if len(_thread_sql_list) > _old_sql_size:
                             # new record was recorded
                             _ori_lines = f_lines[line_id: next_line_id]
-                            _thread_ori_sql_list.extend([_line.rstrip() for _line in _ori_lines])
+                            _thread_ori_sql_list.append("\n".join([_line.rstrip() for _line in _ori_lines]))
                         line_id = next_line_id
 
                         _next_line = f_lines[line_id].rstrip().lstrip()
diff --git a/test/lib/sr_sql_lib.py b/test/lib/sr_sql_lib.py
index 609eecff90a864..76d92b3f8500bc 100644
--- a/test/lib/sr_sql_lib.py
+++ b/test/lib/sr_sql_lib.py
@@ -33,6 +33,7 @@
 import threading
 import traceback
 
+import pymysql
 import trino
 import pyhive
 
@@ -55,6 +56,8 @@
 from cup import log
 from requests.auth import HTTPBasicAuth
 from timeout_decorator import timeout, TimeoutError
+from dbutils.pooled_db import PooledDB
+
 
 from lib import skip
 from lib import data_delete_lib
@@ -146,6 +149,8 @@ def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
         self.root_path = root_path
         self.data_path = common_data_path
+        self.db = list()
+        self.resource = list()
         self.mysql_lib = MysqlLib()
         self.trino_lib = TrinoLib()
         self.spark_lib = SparkLib()
@@ -162,6 +167,8 @@ def __init__(self, *args, **kwargs):
         self.data_insert_lib = data_insert_lib.DataInsertLib()
         self.data_delete_lib = data_delete_lib.DataDeleteLib()
 
+        # connection pool
+        self.connection_pool = None
         # thread
         self.thread_res = {}
         self.thread_var = {}
@@ -452,6 +459,17 @@ def connect_starrocks(self):
         }
         self.mysql_lib.connect(mysql_dict)
 
+    def create_starrocks_conn_pool(self):
+        self.connection_pool = PooledDB(
+            creator=pymysql,
+            mincached=3,
+            blocking=True,
+            host=self.mysql_host,
+            port=int(self.mysql_port),
+            user=self.mysql_user,
+            password=self.mysql_password,
+        )
+
     def connect_trino(self):
         trino_dict = {
             "host": self.trino_host,
@@ -581,10 +599,13 @@ def get_common_data_files(path_name, dir_path=common_data_path):
             file_path_list.append(os.path.join(data_path, file_name))
         return file_path_list
 
-    def execute_sql(self, sql, ori=False):
+    def execute_sql(self, sql, ori=False, conn=None):
         """execute query"""
         try:
-            with self.mysql_lib.connector.cursor() as cursor:
+            if conn is None:
+                conn = self.mysql_lib.connector
+
+            with conn.cursor() as cursor:
                 cursor.execute(sql)
                 result = cursor.fetchall()
                 if isinstance(result, tuple):
@@ -636,6 +657,25 @@ def execute_sql(self, sql, ori=False):
             print("unknown error", e)
             raise
 
+    def get_now_db(self, conn=None):
+        """execute query"""
+        db = None
+        try:
+            if conn is None:
+                conn = self.mysql_lib.connector
+
+            with conn.cursor() as cursor:
+                cursor.execute("SELECT DATABASE()")
+                result = cursor.fetchall()
+                db = result[0][0]
+
+        except _mysql.Error as e:
+            print("Get now db with _mysql.Error!", e.args)
+        except Exception as e:
+            print("Get now db with unknown error!", e)
+
+        return db
+
     @timeout(
         QUERY_TIMEOUT,
         timeout_exception=AssertionError,
@@ -915,13 +955,17 @@ def custom_except_hook(self, args: threading.ExceptHookArgs):
         self.thread_res[args.thread.name] = trace_stack
         # tools.ok_(False, "Thread exit with exception!")
 
-    def execute_thread(self, exec_id, cmd_list, res_list, ori_cmd_list, record_mode):
+    def execute_thread(self, exec_id, cmd_list, res_list, ori_cmd_list, record_mode, init_db, conn):
 
         this_res = []
         self.thread_var[exec_id] = {}
         _t_info = exec_id[:str(exec_id).rindex("-")]
         _t_exec_id = exec_id.split("-")[-1]
 
+        if init_db:
+            self_print(f"Init conn's db: {init_db}", color=ColorEnum.CYAN, logout=True)
+            self.execute_sql("use %s" % init_db, conn=conn)
+
         for _cmd_id, _each_cmd in enumerate(cmd_list):
             uncheck = False
             _cmd_id_str = f'Thread-{exec_id}.{_cmd_id}'
@@ -935,7 +979,7 @@ def execute_thread(self, exec_id, cmd_list, res_list, ori_cmd_list, record_mode)
 
             old_this_res_len = len(this_res)
             actual_res, actual_res_log, var, order = self.execute_single_statement(_each_cmd, _cmd_id_str, record_mode,
-                                                                                   this_res, var_key=exec_id)
+                                                                                   this_res, var_key=exec_id, conn=conn)
 
             if record_mode:
                 for new_res_lino in range(old_this_res_len, len(this_res)):
@@ -970,7 +1014,7 @@ def execute_thread(self, exec_id, cmd_list, res_list, ori_cmd_list, record_mode)
             self.thread_res_log.setdefault(_t_info, [])
             self.thread_res_log[_t_info].append(this_res)
 
-    def execute_single_statement(self, statement, sql_id, record_mode, res_container: list = None, var_key: str = None):
+    def execute_single_statement(self, statement, sql_id, record_mode, res_container: list = None, var_key: str = None, conn: any = None):
         """
         execute single statement and return result
         """
@@ -1070,7 +1114,7 @@ def execute_single_statement(self, statement, sql_id, record_mode, res_container
             # analyse var set
             var, statement = self.analyse_var(statement, thread_key=var_key)
 
-            actual_res = self.execute_sql(statement)
+            actual_res = self.execute_sql(statement, conn=conn)
             self_print(statement)
 
             if record_mode:
@@ -2386,8 +2430,10 @@ def assert_explain_verbose_contains(self, query, *expects):
         """
         sql = "explain verbose %s" % (query)
         res = self.execute_sql(sql, True)
+        tools.assert_true(res["status"], res['msg'])
         for expect in expects:
-            tools.assert_true(str(res["result"]).find(expect) > 0, "assert expect %s is not found in plan" % (expect))
+            plan_string = "\n".join(item[0] for item in res["result"])
+            tools.assert_true(plan_string.find(expect) > 0, "assert expect %s is not found in plan: %s" % (expect, plan_string))
 
     def assert_explain_costs_contains(self, query, *expects):
         """
diff --git a/test/lib/trino_lib.py b/test/lib/trino_lib.py
index 6e13b8c7b59708..8715fe3ce432ca 100644
--- a/test/lib/trino_lib.py
+++ b/test/lib/trino_lib.py
@@ -21,6 +21,7 @@
 
 from lib import close_conn
 
+
 class TrinoLib(object):
     """TrinoLib class"""
 
diff --git a/test/requirements.txt b/test/requirements.txt
index 16d1680729a131..f5851630200ee3 100644
--- a/test/requirements.txt
+++ b/test/requirements.txt
@@ -16,4 +16,4 @@ thrift
 thrift-sasl
 PyHive
 timeout_decorator
-munch
+DBUtils
diff --git a/test/sql/test_across_engine/R/test_sink_nested b/test/sql/test_across_engine/R/test_sink_nested
index c7237add5ecc3c..3a693c0d845001 100644
--- a/test/sql/test_across_engine/R/test_sink_nested
+++ b/test/sql/test_across_engine/R/test_sink_nested
@@ -169,19 +169,19 @@ as select * from files (
 -- !result
 select * from hive_sink_${uuid0}.hive_sink_db_${uuid0}.hive_sink_table_${uuid0};
 -- result:
-{"count": 495, "max": 190407175004000, "mean": 190406671229999, "min": 190406409000602, "sum": 94251302258849568, "variance": 0}	{"count": 495, "max": 742, "mean": 416, "min": 115, "sum": 206195, "variance": 10374}	{"count": 495, "max": 32150509, "mean": 2401239, "min": 737, "sum": 1188613496, "variance": 12977533288261}	{"count": 495, "max": 35195000, "mean": 3519838, "min": 1000, "sum": 1742320297, "variance": 24581100553044}	{"count": 0, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 0, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 351, "max": 658.63, "mean": 57.76452991452993, "min": 0, "sum": 2.0275350000000006e+4, "variance": 6310.500499135526}	{"count": 336, "max": 312.16, "mean": 49.40901785714286, "min": 0, "sum": 16601.43, "variance": 3214.842695450431}	{"count": 366, "max": 74136, "mean": 6162.133196721318, "min": 0, "sum": 2.2553407500000023e+6, "variance": 1.0425524959826614e+8}	{"count": 334, "max": 523800, "mean": 1.9484146706586827e+4, "min": 0, "sum": 6507705, "variance": 3563198650.906335}	{"count": 10, "max": 16085, "mean": 6698.8, "min": 2628, "sum": 66988, "variance": 2.8540252400000002e+7}	{"count": 4, "max": 1985, "mean": 1285, "min": 288, "sum": 5140, "variance": 5.098753333333333e+5}	{"count": 348, "max": 523800, "mean": 1.8907566091954024e+4, "min": 0, "sum": 6579833, "variance": 3.4283784967881336e+9}	{"count": 495, "max": 1, "mean": 0, "min": 0, "sum": 452, "variance": 0}	{"count": 352, "max": 6.474963000000001e+4, "mean": 4951.024888352274, "min": 0, "sum": 1.7427607607000004e+6, "variance": 8.119538398823886e+7}	{"count": 352, "max": 2.8000000000000003, "mean": 0.14237550619122732, "min": 0, "sum": 50.11617817931202, "variance": 0.07516922114035923}	{"count": 339, "max": 658063, "mean": 1991.3067846607655, "min": 0, "sum": 6.750529999999995e+5, "variance": 1.2772340440126908e+9}	{"count": 337, "max": 300.7, "mean": 65.32364985163204, "min": 0, "sum": 2.2014069999999996e+4, "variance": 3904.805190507992}	{"count": 441, "max": 18169, "mean": 1528.077097505669, "min": 0, "sum": 673882, "variance": 6.122348621315204e+6}	{"count": 352, "max": 121968, "mean": 6201.877049689864, "min": 0, "sum": 2.183060721490832e+6, "variance": 1.426316126463931e+8}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 81, "max": 100, "mean": 1.2345679012345678, "min": 0, "sum": 100, "variance": 123.45679012345684}	{"count": 101, "max": 4172.084000000002, "mean": 42.29786138613863, "min": 0, "sum": 4272.084000000002, "variance": 1.7235584886194076e+5}	{"count": 495, "max": 1, "mean": 0, "min": 0, "sum": 208, "variance": 0}	{"count": 495, "max": 1, "mean": 0, "min": 0, "sum": 44, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 366, "max": 121968, "mean": 8685.222814207653, "min": 0, "sum": 3.178791550000001e+6, "variance": 2.4334775798270744e+8}	{"count": 364, "max": 121968, "mean": 8841.174394454862, "min": 0, "sum": 3.2181874795815693e+6, "variance": 2.4456363241811454e+8}	{"count": 495, "max": 1, "mean": 1, "min": 1, "sum": 495, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}
+{"min":190406409000602,"max":190407175004000,"mean":190406671229999,"count":495,"sum":94251302258849568,"variance":0}	{"min":115,"max":742,"mean":416,"count":495,"sum":206195,"variance":10374}	{"min":737,"max":32150509,"mean":2401239,"count":495,"sum":1188613496,"variance":12977533288261}	{"min":1000,"max":35195000,"mean":3519838,"count":495,"sum":1742320297,"variance":24581100553044}	{"min":0,"max":0,"mean":0,"count":0,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":0,"sum":0,"variance":0}	{"min":0,"max":658.63,"mean":57.76452991452993,"count":351,"sum":20275.350000000006,"variance":6310.500499135526}	{"min":0,"max":312.16,"mean":49.40901785714286,"count":336,"sum":16601.43,"variance":3214.842695450431}	{"min":0,"max":74136,"mean":6162.133196721318,"count":366,"sum":2255340.7500000023,"variance":104255249.59826614}	{"min":0,"max":523800,"mean":19484.146706586827,"count":334,"sum":6507705,"variance":3563198650.906335}	{"min":2628,"max":16085,"mean":6698.8,"count":10,"sum":66988,"variance":28540252.400000002}	{"min":288,"max":1985,"mean":1285,"count":4,"sum":5140,"variance":509875.3333333333}	{"min":0,"max":523800,"mean":18907.566091954024,"count":348,"sum":6579833,"variance":3428378496.7881336}	{"min":0,"max":1,"mean":0,"count":495,"sum":452,"variance":0}	{"min":0,"max":64749.63000000001,"mean":4951.024888352274,"count":352,"sum":1742760.7607000005,"variance":81195383.98823886}	{"min":0,"max":2.8000000000000003,"mean":0.14237550619122732,"count":352,"sum":50.11617817931202,"variance":0.07516922114035923}	{"min":0,"max":658063,"mean":1991.3067846607655,"count":339,"sum":675052.9999999995,"variance":1277234044.0126908}	{"min":0,"max":300.7,"mean":65.32364985163204,"count":337,"sum":22014.069999999996,"variance":3904.805190507992}	{"min":0,"max":18169,"mean":1528.077097505669,"count":441,"sum":673882,"variance":6122348.621315204}	{"min":0,"max":121968,"mean":6201.877049689864,"count":352,"sum":2183060.721490832,"variance":142631612.6463931}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":100,"mean":1.2345679012345678,"count":81,"sum":100,"variance":123.45679012345684}	{"min":0,"max":4172.084000000002,"mean":42.29786138613863,"count":101,"sum":4272.084000000002,"variance":172355.84886194076}	{"min":0,"max":1,"mean":0,"count":495,"sum":208,"variance":0}	{"min":0,"max":1,"mean":0,"count":495,"sum":44,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":121968,"mean":8685.222814207653,"count":366,"sum":3178791.550000001,"variance":243347757.98270744}	{"min":0,"max":121968,"mean":8841.174394454862,"count":364,"sum":3218187.4795815693,"variance":244563632.41811454}	{"min":1,"max":1,"mean":1,"count":495,"sum":495,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}
 -- !result
 trino: select * from hive.hive_sink_db_${uuid0}.hive_sink_table_${uuid0};
 -- result:
-{"count": 495, "max": 190407175004000, "mean": 190406671229999, "min": 190406409000602, "sum": 94251302258849568, "variance": 0}	{"count": 495, "max": 742, "mean": 416, "min": 115, "sum": 206195, "variance": 10374}	{"count": 495, "max": 32150509, "mean": 2401239, "min": 737, "sum": 1188613496, "variance": 12977533288261}	{"count": 495, "max": 35195000, "mean": 3519838, "min": 1000, "sum": 1742320297, "variance": 24581100553044}	{"count": 0, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 0, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 351, "max": 658.63, "mean": 57.76452991452993, "min": 0, "sum": 2.0275350000000006e+4, "variance": 6310.500499135526}	{"count": 336, "max": 312.16, "mean": 49.40901785714286, "min": 0, "sum": 16601.43, "variance": 3214.842695450431}	{"count": 366, "max": 74136, "mean": 6162.133196721318, "min": 0, "sum": 2.2553407500000023e+6, "variance": 1.0425524959826614e+8}	{"count": 334, "max": 523800, "mean": 1.9484146706586827e+4, "min": 0, "sum": 6507705, "variance": 3563198650.906335}	{"count": 10, "max": 16085, "mean": 6698.8, "min": 2628, "sum": 66988, "variance": 2.8540252400000002e+7}	{"count": 4, "max": 1985, "mean": 1285, "min": 288, "sum": 5140, "variance": 5.098753333333333e+5}	{"count": 348, "max": 523800, "mean": 1.8907566091954024e+4, "min": 0, "sum": 6579833, "variance": 3.4283784967881336e+9}	{"count": 495, "max": 1, "mean": 0, "min": 0, "sum": 452, "variance": 0}	{"count": 352, "max": 6.474963000000001e+4, "mean": 4951.024888352274, "min": 0, "sum": 1.7427607607000004e+6, "variance": 8.119538398823886e+7}	{"count": 352, "max": 2.8000000000000003, "mean": 0.14237550619122732, "min": 0, "sum": 50.11617817931202, "variance": 0.07516922114035923}	{"count": 339, "max": 658063, "mean": 1991.3067846607655, "min": 0, "sum": 6.750529999999995e+5, "variance": 1.2772340440126908e+9}	{"count": 337, "max": 300.7, "mean": 65.32364985163204, "min": 0, "sum": 2.2014069999999996e+4, "variance": 3904.805190507992}	{"count": 441, "max": 18169, "mean": 1528.077097505669, "min": 0, "sum": 673882, "variance": 6.122348621315204e+6}	{"count": 352, "max": 121968, "mean": 6201.877049689864, "min": 0, "sum": 2.183060721490832e+6, "variance": 1.426316126463931e+8}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 81, "max": 100, "mean": 1.2345679012345678, "min": 0, "sum": 100, "variance": 123.45679012345684}	{"count": 101, "max": 4172.084000000002, "mean": 42.29786138613863, "min": 0, "sum": 4272.084000000002, "variance": 1.7235584886194076e+5}	{"count": 495, "max": 1, "mean": 0, "min": 0, "sum": 208, "variance": 0}	{"count": 495, "max": 1, "mean": 0, "min": 0, "sum": 44, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 366, "max": 121968, "mean": 8685.222814207653, "min": 0, "sum": 3.178791550000001e+6, "variance": 2.4334775798270744e+8}	{"count": 364, "max": 121968, "mean": 8841.174394454862, "min": 0, "sum": 3.2181874795815693e+6, "variance": 2.4456363241811454e+8}	{"count": 495, "max": 1, "mean": 1, "min": 1, "sum": 495, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}
+(min: 190406409000602, max: 190407175004000, mean: 190406671229999, count: 495, sum: 94251302258849568, variance: 0)	(min: 115, max: 742, mean: 416, count: 495, sum: 206195, variance: 10374)	(min: 737, max: 32150509, mean: 2401239, count: 495, sum: 1188613496, variance: 12977533288261)	(min: 1000, max: 35195000, mean: 3519838, count: 495, sum: 1742320297, variance: 24581100553044)	(min: 0.0, max: 0.0, mean: 0.0, count: 0, sum: 0.0, variance: 0.0)	(min: 0.0, max: 0.0, mean: 0.0, count: 0, sum: 0.0, variance: 0.0)	(min: 0.0, max: 658.63, mean: 57.76452991452993, count: 351, sum: 20275.350000000006, variance: 6310.500499135526)	(min: 0.0, max: 312.16, mean: 49.40901785714286, count: 336, sum: 16601.43, variance: 3214.842695450431)	(min: 0.0, max: 74136.0, mean: 6162.133196721318, count: 366, sum: 2255340.7500000023, variance: 104255249.59826614)	(min: 0.0, max: 523800.0, mean: 19484.146706586827, count: 334, sum: 6507705.0, variance: 3563198650.906335)	(min: 2628.0, max: 16085.0, mean: 6698.8, count: 10, sum: 66988.0, variance: 28540252.400000002)	(min: 288.0, max: 1985.0, mean: 1285.0, count: 4, sum: 5140.0, variance: 509875.3333333333)	(min: 0.0, max: 523800.0, mean: 18907.566091954024, count: 348, sum: 6579833.0, variance: 3428378496.7881336)	(min: 0, max: 1, mean: 0, count: 495, sum: 452, variance: 0)	(min: 0.0, max: 64749.63000000001, mean: 4951.024888352274, count: 352, sum: 1742760.7607000005, variance: 81195383.98823886)	(min: 0.0, max: 2.8000000000000003, mean: 0.14237550619122732, count: 352, sum: 50.11617817931202, variance: 0.07516922114035923)	(min: 0.0, max: 658063.0, mean: 1991.3067846607655, count: 339, sum: 675052.9999999995, variance: 1277234044.0126908)	(min: 0.0, max: 300.7, mean: 65.32364985163204, count: 337, sum: 22014.069999999996, variance: 3904.805190507992)	(min: 0.0, max: 18169.0, mean: 1528.077097505669, count: 441, sum: 673882.0, variance: 6122348.621315204)	(min: 0.0, max: 121968.0, mean: 6201.877049689864, count: 352, sum: 2183060.721490832, variance: 142631612.6463931)	(min: 0, max: 0, mean: 0, count: 495, sum: 0, variance: 0)	(min: 0, max: 0, mean: 0, count: 495, sum: 0, variance: 0)	(min: 0, max: 0, mean: 0, count: 495, sum: 0, variance: 0)	(min: 0, max: 0, mean: 0, count: 495, sum: 0, variance: 0)	(min: 0, max: 0, mean: 0, count: 495, sum: 0, variance: 0)	(min: 0, max: 0, mean: 0, count: 495, sum: 0, variance: 0)	(min: 0.0, max: 100.0, mean: 1.2345679012345678, count: 81, sum: 100.0, variance: 123.45679012345684)	(min: 0.0, max: 4172.084000000002, mean: 42.29786138613863, count: 101, sum: 4272.084000000002, variance: 172355.84886194076)	(min: 0, max: 1, mean: 0, count: 495, sum: 208, variance: 0)	(min: 0, max: 1, mean: 0, count: 495, sum: 44, variance: 0)	(min: 0, max: 0, mean: 0, count: 495, sum: 0, variance: 0)	(min: 0.0, max: 121968.0, mean: 8685.222814207653, count: 366, sum: 3178791.550000001, variance: 243347757.98270744)	(min: 0.0, max: 121968.0, mean: 8841.174394454862, count: 364, sum: 3218187.4795815693, variance: 244563632.41811454)	(min: 1, max: 1, mean: 1, count: 495, sum: 495, variance: 0)	(min: 0, max: 0, mean: 0, count: 495, sum: 0, variance: 0)
 -- !result
 spark: select * from hive_sink_db_${uuid0}.hive_sink_table_${uuid0};
 -- result:
-{"count": 495, "max": 190407175004000, "mean": 190406671229999, "min": 190406409000602, "sum": 94251302258849568, "variance": 0}	{"count": 495, "max": 742, "mean": 416, "min": 115, "sum": 206195, "variance": 10374}	{"count": 495, "max": 32150509, "mean": 2401239, "min": 737, "sum": 1188613496, "variance": 12977533288261}	{"count": 495, "max": 35195000, "mean": 3519838, "min": 1000, "sum": 1742320297, "variance": 24581100553044}	{"count": 0, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 0, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 351, "max": 658.63, "mean": 57.76452991452993, "min": 0, "sum": 2.0275350000000006e+4, "variance": 6310.500499135526}	{"count": 336, "max": 312.16, "mean": 49.40901785714286, "min": 0, "sum": 16601.43, "variance": 3214.842695450431}	{"count": 366, "max": 74136, "mean": 6162.133196721318, "min": 0, "sum": 2.2553407500000023e+6, "variance": 1.0425524959826614e+8}	{"count": 334, "max": 523800, "mean": 1.9484146706586827e+4, "min": 0, "sum": 6507705, "variance": 3563198650.906335}	{"count": 10, "max": 16085, "mean": 6698.8, "min": 2628, "sum": 66988, "variance": 2.8540252400000002e+7}	{"count": 4, "max": 1985, "mean": 1285, "min": 288, "sum": 5140, "variance": 5.098753333333333e+5}	{"count": 348, "max": 523800, "mean": 1.8907566091954024e+4, "min": 0, "sum": 6579833, "variance": 3.4283784967881336e+9}	{"count": 495, "max": 1, "mean": 0, "min": 0, "sum": 452, "variance": 0}	{"count": 352, "max": 6.474963000000001e+4, "mean": 4951.024888352274, "min": 0, "sum": 1.7427607607000004e+6, "variance": 8.119538398823886e+7}	{"count": 352, "max": 2.8000000000000003, "mean": 0.14237550619122732, "min": 0, "sum": 50.11617817931202, "variance": 0.07516922114035923}	{"count": 339, "max": 658063, "mean": 1991.3067846607655, "min": 0, "sum": 6.750529999999995e+5, "variance": 1.2772340440126908e+9}	{"count": 337, "max": 300.7, "mean": 65.32364985163204, "min": 0, "sum": 2.2014069999999996e+4, "variance": 3904.805190507992}	{"count": 441, "max": 18169, "mean": 1528.077097505669, "min": 0, "sum": 673882, "variance": 6.122348621315204e+6}	{"count": 352, "max": 121968, "mean": 6201.877049689864, "min": 0, "sum": 2.183060721490832e+6, "variance": 1.426316126463931e+8}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 81, "max": 100, "mean": 1.2345679012345678, "min": 0, "sum": 100, "variance": 123.45679012345684}	{"count": 101, "max": 4172.084000000002, "mean": 42.29786138613863, "min": 0, "sum": 4272.084000000002, "variance": 1.7235584886194076e+5}	{"count": 495, "max": 1, "mean": 0, "min": 0, "sum": 208, "variance": 0}	{"count": 495, "max": 1, "mean": 0, "min": 0, "sum": 44, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 366, "max": 121968, "mean": 8685.222814207653, "min": 0, "sum": 3.178791550000001e+6, "variance": 2.4334775798270744e+8}	{"count": 364, "max": 121968, "mean": 8841.174394454862, "min": 0, "sum": 3.2181874795815693e+6, "variance": 2.4456363241811454e+8}	{"count": 495, "max": 1, "mean": 1, "min": 1, "sum": 495, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}
+{"min":190406409000602,"max":190407175004000,"mean":190406671229999,"count":495,"sum":94251302258849568,"variance":0}	{"min":115,"max":742,"mean":416,"count":495,"sum":206195,"variance":10374}	{"min":737,"max":32150509,"mean":2401239,"count":495,"sum":1188613496,"variance":12977533288261}	{"min":1000,"max":35195000,"mean":3519838,"count":495,"sum":1742320297,"variance":24581100553044}	{"min":0.0,"max":0.0,"mean":0.0,"count":0,"sum":0.0,"variance":0.0}	{"min":0.0,"max":0.0,"mean":0.0,"count":0,"sum":0.0,"variance":0.0}	{"min":0.0,"max":658.63,"mean":57.76452991452993,"count":351,"sum":20275.350000000006,"variance":6310.500499135526}	{"min":0.0,"max":312.16,"mean":49.40901785714286,"count":336,"sum":16601.43,"variance":3214.842695450431}	{"min":0.0,"max":74136.0,"mean":6162.133196721318,"count":366,"sum":2255340.7500000023,"variance":1.0425524959826614E8}	{"min":0.0,"max":523800.0,"mean":19484.146706586827,"count":334,"sum":6507705.0,"variance":3.563198650906335E9}	{"min":2628.0,"max":16085.0,"mean":6698.8,"count":10,"sum":66988.0,"variance":2.8540252400000002E7}	{"min":288.0,"max":1985.0,"mean":1285.0,"count":4,"sum":5140.0,"variance":509875.3333333333}	{"min":0.0,"max":523800.0,"mean":18907.566091954024,"count":348,"sum":6579833.0,"variance":3.4283784967881336E9}	{"min":0,"max":1,"mean":0,"count":495,"sum":452,"variance":0}	{"min":0.0,"max":64749.63000000001,"mean":4951.024888352274,"count":352,"sum":1742760.7607000005,"variance":8.119538398823886E7}	{"min":0.0,"max":2.8000000000000003,"mean":0.14237550619122732,"count":352,"sum":50.11617817931202,"variance":0.07516922114035923}	{"min":0.0,"max":658063.0,"mean":1991.3067846607655,"count":339,"sum":675052.9999999995,"variance":1.2772340440126908E9}	{"min":0.0,"max":300.7,"mean":65.32364985163204,"count":337,"sum":22014.069999999996,"variance":3904.805190507992}	{"min":0.0,"max":18169.0,"mean":1528.077097505669,"count":441,"sum":673882.0,"variance":6122348.621315204}	{"min":0.0,"max":121968.0,"mean":6201.877049689864,"count":352,"sum":2183060.721490832,"variance":1.426316126463931E8}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0.0,"max":100.0,"mean":1.2345679012345678,"count":81,"sum":100.0,"variance":123.45679012345684}	{"min":0.0,"max":4172.084000000002,"mean":42.29786138613863,"count":101,"sum":4272.084000000002,"variance":172355.84886194076}	{"min":0,"max":1,"mean":0,"count":495,"sum":208,"variance":0}	{"min":0,"max":1,"mean":0,"count":495,"sum":44,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0.0,"max":121968.0,"mean":8685.222814207653,"count":366,"sum":3178791.550000001,"variance":2.4334775798270744E8}	{"min":0.0,"max":121968.0,"mean":8841.174394454862,"count":364,"sum":3218187.4795815693,"variance":2.4456363241811454E8}	{"min":1,"max":1,"mean":1,"count":495,"sum":495,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}
 -- !result
 hive: select * from hive_sink_db_${uuid0}.hive_sink_table_${uuid0};
 -- result:
-{"count": 495, "max": 190407175004000, "mean": 190406671229999, "min": 190406409000602, "sum": 94251302258849568, "variance": 0}	{"count": 495, "max": 742, "mean": 416, "min": 115, "sum": 206195, "variance": 10374}	{"count": 495, "max": 32150509, "mean": 2401239, "min": 737, "sum": 1188613496, "variance": 12977533288261}	{"count": 495, "max": 35195000, "mean": 3519838, "min": 1000, "sum": 1742320297, "variance": 24581100553044}	{"count": 0, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 0, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 351, "max": 658.63, "mean": 57.76452991452993, "min": 0, "sum": 2.0275350000000006e+4, "variance": 6310.500499135526}	{"count": 336, "max": 312.16, "mean": 49.40901785714286, "min": 0, "sum": 16601.43, "variance": 3214.842695450431}	{"count": 366, "max": 74136, "mean": 6162.133196721318, "min": 0, "sum": 2.2553407500000023e+6, "variance": 1.0425524959826614e+8}	{"count": 334, "max": 523800, "mean": 1.9484146706586827e+4, "min": 0, "sum": 6507705, "variance": 3563198650.906335}	{"count": 10, "max": 16085, "mean": 6698.8, "min": 2628, "sum": 66988, "variance": 2.8540252400000002e+7}	{"count": 4, "max": 1985, "mean": 1285, "min": 288, "sum": 5140, "variance": 5.098753333333333e+5}	{"count": 348, "max": 523800, "mean": 1.8907566091954024e+4, "min": 0, "sum": 6579833, "variance": 3.4283784967881336e+9}	{"count": 495, "max": 1, "mean": 0, "min": 0, "sum": 452, "variance": 0}	{"count": 352, "max": 6.474963000000001e+4, "mean": 4951.024888352274, "min": 0, "sum": 1.7427607607000004e+6, "variance": 8.119538398823886e+7}	{"count": 352, "max": 2.8000000000000003, "mean": 0.14237550619122732, "min": 0, "sum": 50.11617817931202, "variance": 0.07516922114035923}	{"count": 339, "max": 658063, "mean": 1991.3067846607655, "min": 0, "sum": 6.750529999999995e+5, "variance": 1.2772340440126908e+9}	{"count": 337, "max": 300.7, "mean": 65.32364985163204, "min": 0, "sum": 2.2014069999999996e+4, "variance": 3904.805190507992}	{"count": 441, "max": 18169, "mean": 1528.077097505669, "min": 0, "sum": 673882, "variance": 6.122348621315204e+6}	{"count": 352, "max": 121968, "mean": 6201.877049689864, "min": 0, "sum": 2.183060721490832e+6, "variance": 1.426316126463931e+8}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 81, "max": 100, "mean": 1.2345679012345678, "min": 0, "sum": 100, "variance": 123.45679012345684}	{"count": 101, "max": 4172.084000000002, "mean": 42.29786138613863, "min": 0, "sum": 4272.084000000002, "variance": 1.7235584886194076e+5}	{"count": 495, "max": 1, "mean": 0, "min": 0, "sum": 208, "variance": 0}	{"count": 495, "max": 1, "mean": 0, "min": 0, "sum": 44, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}	{"count": 366, "max": 121968, "mean": 8685.222814207653, "min": 0, "sum": 3.178791550000001e+6, "variance": 2.4334775798270744e+8}	{"count": 364, "max": 121968, "mean": 8841.174394454862, "min": 0, "sum": 3.2181874795815693e+6, "variance": 2.4456363241811454e+8}	{"count": 495, "max": 1, "mean": 1, "min": 1, "sum": 495, "variance": 0}	{"count": 495, "max": 0, "mean": 0, "min": 0, "sum": 0, "variance": 0}
+{"min":190406409000602,"max":190407175004000,"mean":190406671229999,"count":495,"sum":94251302258849568,"variance":0}	{"min":115,"max":742,"mean":416,"count":495,"sum":206195,"variance":10374}	{"min":737,"max":32150509,"mean":2401239,"count":495,"sum":1188613496,"variance":12977533288261}	{"min":1000,"max":35195000,"mean":3519838,"count":495,"sum":1742320297,"variance":24581100553044}	{"min":0.0,"max":0.0,"mean":0.0,"count":0,"sum":0.0,"variance":0.0}	{"min":0.0,"max":0.0,"mean":0.0,"count":0,"sum":0.0,"variance":0.0}	{"min":0.0,"max":658.63,"mean":57.76452991452993,"count":351,"sum":20275.350000000006,"variance":6310.500499135526}	{"min":0.0,"max":312.16,"mean":49.40901785714286,"count":336,"sum":16601.43,"variance":3214.842695450431}	{"min":0.0,"max":74136.0,"mean":6162.133196721318,"count":366,"sum":2255340.7500000023,"variance":1.0425524959826614E8}	{"min":0.0,"max":523800.0,"mean":19484.146706586827,"count":334,"sum":6507705.0,"variance":3.563198650906335E9}	{"min":2628.0,"max":16085.0,"mean":6698.8,"count":10,"sum":66988.0,"variance":2.8540252400000002E7}	{"min":288.0,"max":1985.0,"mean":1285.0,"count":4,"sum":5140.0,"variance":509875.3333333333}	{"min":0.0,"max":523800.0,"mean":18907.566091954024,"count":348,"sum":6579833.0,"variance":3.4283784967881336E9}	{"min":0,"max":1,"mean":0,"count":495,"sum":452,"variance":0}	{"min":0.0,"max":64749.63000000001,"mean":4951.024888352274,"count":352,"sum":1742760.7607000005,"variance":8.119538398823886E7}	{"min":0.0,"max":2.8000000000000003,"mean":0.14237550619122732,"count":352,"sum":50.11617817931202,"variance":0.07516922114035923}	{"min":0.0,"max":658063.0,"mean":1991.3067846607655,"count":339,"sum":675052.9999999995,"variance":1.2772340440126908E9}	{"min":0.0,"max":300.7,"mean":65.32364985163204,"count":337,"sum":22014.069999999996,"variance":3904.805190507992}	{"min":0.0,"max":18169.0,"mean":1528.077097505669,"count":441,"sum":673882.0,"variance":6122348.621315204}	{"min":0.0,"max":121968.0,"mean":6201.877049689864,"count":352,"sum":2183060.721490832,"variance":1.426316126463931E8}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0.0,"max":100.0,"mean":1.2345679012345678,"count":81,"sum":100.0,"variance":123.45679012345684}	{"min":0.0,"max":4172.084000000002,"mean":42.29786138613863,"count":101,"sum":4272.084000000002,"variance":172355.84886194076}	{"min":0,"max":1,"mean":0,"count":495,"sum":208,"variance":0}	{"min":0,"max":1,"mean":0,"count":495,"sum":44,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}	{"min":0.0,"max":121968.0,"mean":8685.222814207653,"count":366,"sum":3178791.550000001,"variance":2.4334775798270744E8}	{"min":0.0,"max":121968.0,"mean":8841.174394454862,"count":364,"sum":3218187.4795815693,"variance":2.4456363241811454E8}	{"min":1,"max":1,"mean":1,"count":495,"sum":495,"variance":0}	{"min":0,"max":0,"mean":0,"count":495,"sum":0,"variance":0}
 -- !result
 drop table hive_sink_${uuid0}.hive_sink_db_${uuid0}.hive_sink_table_${uuid0} force;
 -- result:
@@ -196,4 +196,4 @@ shell: ossutil64 rm -rf oss://${oss_bucket}/test_across_engine/test_sink/${uuid0
 -- result:
 0
 
--- !result
\ No newline at end of file
+-- !result
diff --git a/test/sql/test_agg_function/R/test_mann_whitney b/test/sql/test_agg_function/R/test_mann_whitney
new file mode 100644
index 00000000000000..90dfa6210cad8f
--- /dev/null
+++ b/test/sql/test_agg_function/R/test_mann_whitney
@@ -0,0 +1,247 @@
+-- name: testMannWhitney
+select 
+    mann_whitney_u_test(x, t, 'two-sided') 
+from 
+    TABLE(generate_series(1, 10)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+-- result:
+[50, 0.9697360424200407]
+-- !result
+
+select 
+    mann_whitney_u_test(x, t, 'less') 
+from 
+    TABLE(generate_series(1, 10)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+-- result:
+[50, 0.5151319787899797]
+-- !result
+
+select 
+    mann_whitney_u_test(x, t, 'greater') 
+from 
+    TABLE(generate_series(1, 10)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+-- result:
+[50, 0.5151319787899797]
+-- !result
+
+
+select 
+    mann_whitney_u_test(x, t, 'two-sided') 
+from 
+    TABLE(generate_series(1000, 10000)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+-- result:
+[40509000.5, 0.9999988557063488]
+-- !result
+
+select 
+    mann_whitney_u_test(x, t, 'less') 
+from 
+    TABLE(generate_series(1000, 10000)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+-- result:
+[40509000.5, 0.5000005721468257]
+-- !result
+
+select 
+    mann_whitney_u_test(x, t, 'greater') 
+from 
+    TABLE(generate_series(1000, 10000)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+-- result:
+[40509000.5, 0.5000005721468257]
+-- !result
+
+-- name: testMannWhitney
+select 
+    mann_whitney_u_test(x, t, 'two-sided', 0) 
+from 
+    TABLE(generate_series(1, 10)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+-- result:
+[50, 1]
+-- !result
+
+select 
+    mann_whitney_u_test(x, t, 'less', 0) 
+from 
+    TABLE(generate_series(1, 10)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+-- result:
+[50, 0.5]
+-- !result
+
+select 
+    mann_whitney_u_test(x, t, 'greater', 0) 
+from 
+    TABLE(generate_series(1, 10)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+-- result:
+[50, 0.5]
+-- !result
+
+select 
+    mann_whitney_u_test(x, t, 'two-sided', 0) 
+from 
+    TABLE(generate_series(1000, 10000)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+-- result:
+[40509000.5, 1]
+-- !result
+
+
+CREATE TABLE t1 (
+    c1 int,
+    c2 boolean,
+    c3 tinyint,
+    c4 int,
+    c5 bigint,
+    c6 largeint,
+    c7 string
+    )
+DUPLICATE KEY(c1)
+DISTRIBUTED BY HASH(c1) BUCKETS 3
+PROPERTIES ("replication_num" = "1");
+-- result:
+-- !result
+
+INSERT INTO t1 values
+    (1, true, 11, 111, 1111, 11111, "111111"),
+    (2, false, 22, 222, 2222, 22222, "222222"),
+    (3, true, 33, 333, 3333, 33333, "333333"),
+    (4, null, null, null, null, null, null),
+    (5, -1, -11, -111, -1111, -11111, "-111111"),
+    (6, null, null, null, null, "36893488147419103232", "680564733841876926926749214863536422912");
+-- result:
+-- !result
+
+
+select
+    mann_whitney_u_test(c3, c2, 'two-sided')
+from t1;
+-- result:
+[2, 1]
+-- !result
+
+select
+    mann_whitney_u_test(c3, c2, 'greater')
+from t1;
+-- result:
+[2, 0.5]
+-- !result
+
+
+select
+    mann_whitney_u_test(c3, c2, 'less')
+from t1;
+-- result:
+[2, 0.8144533152386512]
+-- !result
+
+
+select
+    mann_whitney_u_test(c4, c2, 'two-sided')
+from t1;
+-- result:
+[2, 1]
+-- !result
+
+
+select
+    mann_whitney_u_test(c4, c2, 'greater')
+from t1;
+-- result:
+[2, 0.5]
+-- !result
+
+
+select
+    mann_whitney_u_test(c4, c2, 'less')
+from t1;
+-- result:
+[2, 0.8144533152386512]
+-- !result
+
+
+select
+    mann_whitney_u_test(c5, c2, 'two-sided')
+from t1;
+-- result:
+[2, 1]
+-- !result
+
+
+select
+    mann_whitney_u_test(c5, c2, 'greater')
+from t1;
+-- result:
+[2, 0.5]
+-- !result
+
+
+select
+    mann_whitney_u_test(c5, c2, 'less')
+from t1;
+-- result:
+[2, 0.8144533152386512]
+-- !result
+
+
+select
+    mann_whitney_u_test(c6, c2, 'two-sided')
+from t1;
+-- result:
+[2, 1]
+-- !result
+
+
+select
+    mann_whitney_u_test(c6, c2, 'greater')
+from t1;
+-- result:
+[2, 0.5]
+-- !result
+
+
+select
+    mann_whitney_u_test(c6, c2, 'less')
+from t1;
+-- result:
+[2, 0.8144533152386512]
+-- !result
+
+select
+    mann_whitney_u_test(c6, c2, 'less')
+from t1
+where c1 > 100;
+-- result:
+None
+-- !result
+
+
+select
+    c1 % 3, mann_whitney_u_test(c6, c2, 'less')
+from t1
+group by c1 % 3;
+-- result:
+1	{"Error": "All numbers in both samples are identical."}
+0	{"Error": "All numbers in both samples are identical."}
+2	[1, 0.9772498680518208]
+-- !result
+
+
+select
+    c1 % 2, mann_whitney_u_test(c6, c2, 'less')
+from t1
+where c1 > 100
+group by c1 % 2;
+-- result:
+
+-- !result
+
+SELECT mann_whitney_u_test(col1, col2) FROM (VALUES (1, false)) AS tmp(col1, col2);
+-- result:
+{"Error": "All numbers in both samples are identical."}
+-- !result
+
+SELECT mann_whitney_u_test(col1, col2) FROM (VALUES (1, true),(1, false),(2, true),(2, false),(3, false),(3, null)) AS tmp(col1, col2);
+-- result:
+[4, 0.7609067270751142]
+-- !result
+
+SELECT mann_whitney_u_test(1, 1);
+-- result:
+{"Error": "All numbers in both samples are identical."}
+-- !result
diff --git a/test/sql/test_agg_function/T/test_mann_whitney b/test/sql/test_agg_function/T/test_mann_whitney
new file mode 100644
index 00000000000000..049f75cf0eaf09
--- /dev/null
+++ b/test/sql/test_agg_function/T/test_mann_whitney
@@ -0,0 +1,155 @@
+-- name: testMannWhitney
+select 
+    mann_whitney_u_test(x, t, 'two-sided') 
+from 
+    TABLE(generate_series(1, 10)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+
+select 
+    mann_whitney_u_test(x, t, 'less') 
+from 
+    TABLE(generate_series(1, 10)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+
+select 
+    mann_whitney_u_test(x, t, 'greater') 
+from 
+    TABLE(generate_series(1, 10)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+
+select 
+    mann_whitney_u_test(x, t, 'two-sided') 
+from 
+    TABLE(generate_series(1000, 10000)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+
+select 
+    mann_whitney_u_test(x, t, 'less') 
+from 
+    TABLE(generate_series(1000, 10000)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+
+select 
+    mann_whitney_u_test(x, t, 'greater') 
+from 
+    TABLE(generate_series(1000, 10000)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+
+select 
+    mann_whitney_u_test(x, t, 'two-sided', 0) 
+from 
+    TABLE(generate_series(1, 10)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+
+select 
+    mann_whitney_u_test(x, t, 'less', 0) 
+from 
+    TABLE(generate_series(1, 10)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+
+select 
+    mann_whitney_u_test(x, t, 'greater', 0) 
+from 
+    TABLE(generate_series(1, 10)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+
+select 
+    mann_whitney_u_test(x, t, 'two-sided', 0) 
+from 
+    TABLE(generate_series(1000, 10000)) as numbers(x), TABLE(generate_series(0, 1)) as idx(t);
+
+
+CREATE TABLE t1 (
+    c1 int,
+    c2 boolean,
+    c3 tinyint,
+    c4 int,
+    c5 bigint,
+    c6 largeint,
+    c7 string
+    )
+DUPLICATE KEY(c1)
+DISTRIBUTED BY HASH(c1) BUCKETS 3
+PROPERTIES ("replication_num" = "1");
+
+INSERT INTO t1 values
+    (1, true, 11, 111, 1111, 11111, "111111"),
+    (2, false, 22, 222, 2222, 22222, "222222"),
+    (3, true, 33, 333, 3333, 33333, "333333"),
+    (4, null, null, null, null, null, null),
+    (5, -1, -11, -111, -1111, -11111, "-111111"),
+    (6, null, null, null, null, "36893488147419103232", "680564733841876926926749214863536422912");
+
+select
+    mann_whitney_u_test(c3, c2, 'two-sided')
+from t1;
+
+select
+    mann_whitney_u_test(c3, c2, 'greater')
+from t1;
+
+
+select
+    mann_whitney_u_test(c3, c2, 'less')
+from t1;
+
+
+select
+    mann_whitney_u_test(c4, c2, 'two-sided')
+from t1;
+
+
+select
+    mann_whitney_u_test(c4, c2, 'greater')
+from t1;
+
+
+select
+    mann_whitney_u_test(c4, c2, 'less')
+from t1;
+
+
+select
+    mann_whitney_u_test(c5, c2, 'two-sided')
+from t1;
+
+
+select
+    mann_whitney_u_test(c5, c2, 'greater')
+from t1;
+
+
+select
+    mann_whitney_u_test(c5, c2, 'less')
+from t1;
+
+
+select
+    mann_whitney_u_test(c6, c2, 'two-sided')
+from t1;
+
+
+select
+    mann_whitney_u_test(c6, c2, 'greater')
+from t1;
+
+
+select
+    mann_whitney_u_test(c6, c2, 'less')
+from t1;
+
+select
+    mann_whitney_u_test(c6, c2, 'less')
+from t1
+where c1 > 100;
+
+
+select
+    c1 % 3, mann_whitney_u_test(c6, c2, 'less')
+from t1
+group by c1 % 3;
+
+
+select
+    c1 % 2, mann_whitney_u_test(c6, c2, 'less')
+from t1
+where c1 > 100
+group by c1 % 2;
+
+
+SELECT mann_whitney_u_test(col1, col2) FROM (VALUES (1, false)) AS tmp(col1, col2);
+
+SELECT mann_whitney_u_test(col1, col2) FROM (VALUES (1, true),(1, false),(1, true),(1, false),(1, false),(1, null)) AS tmp(col1, col2);
+
+SELECT mann_whitney_u_test(1, 1);
diff --git a/test/sql/test_auto_increment/R/test_auto_increment b/test/sql/test_auto_increment/R/test_auto_increment
index 08ac02a52ea337..58cb0f2fb4ce4d 100644
--- a/test/sql/test_auto_increment/R/test_auto_increment
+++ b/test/sql/test_auto_increment/R/test_auto_increment
@@ -76,9 +76,6 @@ CREATE DATABASE test_table_with_null;
 USE test_table_with_null;
 -- result:
 -- !result
-SET enable_insert_strict = false;
--- result:
--- !result
 ADMIN SET FRONTEND CONFIG ("empty_load_as_error" = "false");
 -- result:
 -- !result
@@ -122,16 +119,16 @@ Primary KEY (id) DISTRIBUTED BY HASH(id) BUCKETS 1 PROPERTIES("replication_num"
 INSERT INTO t2 VALUES (1, NULL), (2, NULL);
 -- result:
 -- !result
-INSERT INTO t1 SELECT * FROM t2;
+INSERT INTO t1 properties ("max_filter_ratio" = "1") SELECT * FROM t2;
 -- result:
 -- !result
-INSERT INTO t1 (id, idx) SELECT * FROM t2;
+INSERT INTO t1 (id, idx) properties ("max_filter_ratio" = "1") SELECT * FROM t2;
 -- result:
 -- !result
-INSERT INTO t1 (id, idx) SELECT id, idx FROM t2;
+INSERT INTO t1 (id, idx) properties ("max_filter_ratio" = "1") SELECT id, idx FROM t2;
 -- result:
 -- !result
-INSERT INTO t1 SELECT 1, NULL;
+INSERT INTO t1 properties ("max_filter_ratio" = "1") SELECT 1, NULL;
 -- result:
 -- !result
 SELECT * FROM t1;
@@ -147,10 +144,10 @@ CREATE TABLE t1 ( id BIGINT NOT NULL, idx BIGINT AUTO_INCREMENT )
 Primary KEY (id) DISTRIBUTED BY HASH(id) BUCKETS 1 PROPERTIES("replication_num" = "1", "replicated_storage"="true");
 -- result:
 -- !result
-INSERT INTO t1 (id, idx) SELECT * FROM t2;
+INSERT INTO t1 (id, idx) properties ("max_filter_ratio" = "1") SELECT * FROM t2;
 -- result:
 -- !result
-INSERT INTO t1 (id, idx) SELECT id, idx FROM t2;
+INSERT INTO t1 (id, idx) properties ("max_filter_ratio" = "1") SELECT id, idx FROM t2;
 -- result:
 -- !result
 INSERT INTO t1 (id) SELECT id FROM t2;
@@ -169,9 +166,6 @@ DROP TABLE t1;
 DROP TABLE t2;
 -- result:
 -- !result
-SET enable_insert_strict = true;
--- result:
--- !result
 ADMIN SET FRONTEND CONFIG ("empty_load_as_error" = "true");
 -- result:
 -- !result
@@ -651,4 +645,4 @@ DROP TABLE t_auto_increment_partial_update_only;
 -- !result
 DROP DATABASE test_auto_increment_partial_update_only;
 -- result:
--- !result
\ No newline at end of file
+-- !result
diff --git a/test/sql/test_auto_increment/T/test_auto_increment b/test/sql/test_auto_increment/T/test_auto_increment
index 4803c4747de789..f275b87fe31d89 100644
--- a/test/sql/test_auto_increment/T/test_auto_increment
+++ b/test/sql/test_auto_increment/T/test_auto_increment
@@ -168,7 +168,6 @@ DROP DATABASE test_schema_change_auto_increment;
 CREATE DATABASE test_table_with_null;
 USE test_table_with_null;
 
-SET enable_insert_strict = false;
 ADMIN SET FRONTEND CONFIG ("empty_load_as_error" = "false");
 
 CREATE TABLE t ( id BIGINT NOT NULL,  name BIGINT NOT NULL AUTO_INCREMENT, job1 BIGINT NULL, job2 BIGINT NULL) Primary KEY (id) DISTRIBUTED BY HASH(id) BUCKETS 1 PROPERTIES("replication_num" = "1", "replicated_storage"="true");
@@ -193,24 +192,23 @@ Primary KEY (id) DISTRIBUTED BY HASH(id) BUCKETS 1 PROPERTIES("replication_num"
 
 INSERT INTO t2 VALUES (1, NULL), (2, NULL);
 
-INSERT INTO t1 SELECT * FROM t2;
-INSERT INTO t1 (id, idx) SELECT * FROM t2;
-INSERT INTO t1 (id, idx) SELECT id, idx FROM t2;
-INSERT INTO t1 SELECT 1, NULL;
+INSERT INTO t1 properties ("max_filter_ratio" = "1") SELECT * FROM t2;
+INSERT INTO t1 (id, idx) properties ("max_filter_ratio" = "1") SELECT * FROM t2;
+INSERT INTO t1 (id, idx) properties ("max_filter_ratio" = "1") SELECT id, idx FROM t2;
+INSERT INTO t1 properties ("max_filter_ratio" = "1") SELECT 1, NULL;
 SELECT * FROM t1;
 INSERT INTO t2 VALUES (10, 1), (20, 2);
 DROP TABLE t1;
 CREATE TABLE t1 ( id BIGINT NOT NULL, idx BIGINT AUTO_INCREMENT )
 Primary KEY (id) DISTRIBUTED BY HASH(id) BUCKETS 1 PROPERTIES("replication_num" = "1", "replicated_storage"="true");
-INSERT INTO t1 (id, idx) SELECT * FROM t2;
-INSERT INTO t1 (id, idx) SELECT id, idx FROM t2;
+INSERT INTO t1 (id, idx) properties ("max_filter_ratio" = "1") SELECT * FROM t2;
+INSERT INTO t1 (id, idx) properties ("max_filter_ratio" = "1") SELECT id, idx FROM t2;
 INSERT INTO t1 (id) SELECT id FROM t2;
 SELECT * FROM t1;
 
 DROP TABLE t1;
 DROP TABLE t2;
 
-SET enable_insert_strict = true;
 ADMIN SET FRONTEND CONFIG ("empty_load_as_error" = "true");
 
 DROP DATABASE test_table_with_null;
diff --git a/test/sql/test_automatic_partition/R/test_insert_overwrite b/test/sql/test_automatic_partition/R/test_insert_overwrite
index 6278b255e480f2..d266b3d063134d 100644
--- a/test/sql/test_automatic_partition/R/test_insert_overwrite
+++ b/test/sql/test_automatic_partition/R/test_insert_overwrite
@@ -34,11 +34,11 @@ select * from site_access;
 -- !result
 INSERT overwrite site_access PARTITION(event_day='2023-07-01') select '2023-07-02' as event_day, 10 as site_id, 'SomeCity' as city_code, 'UserName' as user_name, 0 as pv from dual;
 -- result:
-[REGEX]Insert has filtered data in strict mode
+[REGEX]Insert has filtered data
 -- !result
 INSERT overwrite site_access PARTITION(event_day='2023-07-02') select '2023-07-01' as event_day, 10 as site_id, 'SomeCity' as city_code, 'UserName' as user_name, 0 as pv from dual;
 -- result:
-[REGEX]Insert has filtered data in strict mode
+[REGEX]Insert has filtered data
 -- !result
 INSERT overwrite site_access select '2023-07-02' as event_day, 10 as site_id, 'SomeCity' as city_code, 'UserName' as user_name, 0 as pv from dual;
 -- result:
diff --git a/test/sql/test_dml/R/test_update b/test/sql/test_dml/R/test_update
index 898b81ed01ea1a..8f35e2245d3e4c 100644
--- a/test/sql/test_dml/R/test_update
+++ b/test/sql/test_dml/R/test_update
@@ -106,4 +106,28 @@ select * from pk_tbl1 order by k1;
 -- !result
 drop table if exists pk_tbl1;
 -- result:
--- !result
\ No newline at end of file
+-- !result
+
+create table pk_tbl2 (k1 int, k2 varchar(1)) primary key (k1) distributed by hash(k1);
+-- result:
+-- !result
+insert into pk_tbl2 values (1, "a"), (2, "bb");
+-- result:
+[REGEX].*Insert has filtered data.*
+-- !result
+set insert_max_filter_ratio = 1;
+-- result:
+-- !result
+insert into pk_tbl2 values (1, "a"), (2, "bb");
+-- result:
+-- !result
+select * from pk_tbl2;
+-- result:
+1	a
+-- !result
+set insert_max_filter_ratio = 0;
+-- result:
+-- !result
+drop table if exists pk_tbl2;
+-- result:
+-- !result
diff --git a/test/sql/test_dml/T/test_update b/test/sql/test_dml/T/test_update
index d80da191af4db8..a188d7fa37c886 100644
--- a/test/sql/test_dml/T/test_update
+++ b/test/sql/test_dml/T/test_update
@@ -54,4 +54,13 @@ DISTRIBUTED BY HASH(`k1`);
 insert into pk_tbl1(k2, k3, k4, k5) values('2024-01-01', 1, 2, 3), ('2024-01-01', 1, 2, 3);
 update pk_tbl1 set K4 = 1, K3 = 1, K5 = 1 where K1 = 1;
 select * from pk_tbl1 order by k1;
-drop table if exists pk_tbl1;
\ No newline at end of file
+drop table if exists pk_tbl1;
+
+-- test data filter
+create table pk_tbl2 (k1 int, k2 varchar(1)) primary key (k1) distributed by hash(k1);
+insert into pk_tbl2 values (1, "a"), (2, "bb");
+set insert_max_filter_ratio = 1;
+insert into pk_tbl2 values (1, "a"), (2, "bb");
+select * from pk_tbl2;
+set insert_max_filter_ratio = 0;
+drop table if exists pk_tbl2;
diff --git a/test/sql/test_external_file/R/test_parquet_read_range b/test/sql/test_external_file/R/test_parquet_read_range
index 5c2ddbda9b1505..2b8a0b08e778a4 100644
--- a/test/sql/test_external_file/R/test_parquet_read_range
+++ b/test/sql/test_external_file/R/test_parquet_read_range
@@ -146,6 +146,14 @@ select * from read_range_test where c0 in (1, 4000);
 1	20000	1	[1,null,0]
 4000	16001	None	None
 -- !result
+select count(*) from read_range_test where c2 = '1';
+-- result:
+200
+-- !result
+select count(*) from read_range_test where c2 = '1' or c2 is null;
+-- result:
+2200
+-- !result
 select count(*) from read_range_test a join[broadcast] read_range_big_page_test b on a.c2 = b.c2 where b.c0 < 5;
 -- result:
 800
diff --git a/test/sql/test_external_file/T/test_parquet_read_range b/test/sql/test_external_file/T/test_parquet_read_range
index fc7df8175ddb2a..4ab24b3efedfec 100644
--- a/test/sql/test_external_file/T/test_parquet_read_range
+++ b/test/sql/test_external_file/T/test_parquet_read_range
@@ -84,6 +84,10 @@ select * from repeated_value where c0 = 1;
 -- test lazy decode
 select * from read_range_test where c0 in (1, 4000);
 
+-- test conjunct rewrite
+select count(*) from read_range_test where c2 = '1';
+select count(*) from read_range_test where c2 = '1' or c2 is null;
+
 -- test runtime in filter string type
 select count(*) from read_range_test a join[broadcast] read_range_big_page_test b on a.c2 = b.c2 where b.c0 < 5;
 
diff --git a/test/sql/test_files/R/test_insert_properties b/test/sql/test_files/R/test_insert_properties
new file mode 100644
index 00000000000000..003021db30ec94
--- /dev/null
+++ b/test/sql/test_files/R/test_insert_properties
@@ -0,0 +1,103 @@
+-- name: test_insert_properties
+
+create database db_${uuid0};
+use db_${uuid0};
+
+shell: ossutil64 mkdir oss://${oss_bucket}/test_files/csv_format/${uuid0} >/dev/null || echo "exit 0" >/dev/null
+
+shell: ossutil64 cp --force ./sql/test_files/csv_format/invalid_int.csv oss://${oss_bucket}/test_files/csv_format/${uuid0}/ | grep -Pv "(average|elapsed)"
+-- result:
+0
+
+Succeed: Total num: 1, size: 12. OK num: 1(upload 1 files).
+-- !result
+
+create table t1 (k1 int);
+
+insert into t1 (k1) properties ("strict_mode" = "false", "max_filter_ratio" = "0")
+select $2 from files(
+    "path" = "oss://${oss_bucket}/test_files/csv_format/${uuid0}/*",
+    "format" = "csv",
+    "auto_detect_sample_rows" = "1",
+    "csv.column_separator" = "\\x01",
+    "csv.row_delimiter" = "\n",
+    "aws.s3.access_key" = "${oss_ak}",
+    "aws.s3.secret_key" = "${oss_sk}",
+    "aws.s3.endpoint" = "${oss_endpoint}"
+    );
+-- result:
+-- !result
+select * from t1;
+-- result:
+None
+2
+-- !result
+truncate table t1;
+-- result:
+-- !result
+
+insert into t1 (k1) properties ("strict_mode" = "true", "max_filter_ratio" = "0")
+select $2 from files(
+    "path" = "oss://${oss_bucket}/test_files/csv_format/${uuid0}/*",
+    "format" = "csv",
+    "auto_detect_sample_rows" = "1",
+    "csv.column_separator" = "\\x01",
+    "csv.row_delimiter" = "\n",
+    "aws.s3.access_key" = "${oss_ak}",
+    "aws.s3.secret_key" = "${oss_sk}",
+    "aws.s3.endpoint" = "${oss_endpoint}"
+    );
+-- result:
+[REGEX].*Insert has filtered data.*
+-- !result
+select * from t1;
+-- result:
+-- !result
+truncate table t1;
+-- result:
+-- !result
+
+insert into t1 (k1) properties ("strict_mode" = "true", "max_filter_ratio" = "0.5")
+select $2 from files(
+    "path" = "oss://${oss_bucket}/test_files/csv_format/${uuid0}/*",
+    "format" = "csv",
+    "auto_detect_sample_rows" = "1",
+    "csv.column_separator" = "\\x01",
+    "csv.row_delimiter" = "\n",
+    "aws.s3.access_key" = "${oss_ak}",
+    "aws.s3.secret_key" = "${oss_sk}",
+    "aws.s3.endpoint" = "${oss_endpoint}"
+    );
+-- result:
+-- !result
+select * from t1;
+-- result:
+2
+-- !result
+truncate table t1;
+-- result:
+-- !result
+
+insert /*+ SET_VAR(enable_insert_strict = false) */ into t1 (k1) properties ("max_filter_ratio" = "0")
+select $2 from files(
+    "path" = "oss://${oss_bucket}/test_files/csv_format/${uuid0}/*",
+    "format" = "csv",
+    "auto_detect_sample_rows" = "1",
+    "csv.column_separator" = "\\x01",
+    "csv.row_delimiter" = "\n",
+    "aws.s3.access_key" = "${oss_ak}",
+    "aws.s3.secret_key" = "${oss_sk}",
+    "aws.s3.endpoint" = "${oss_endpoint}"
+    );
+-- result:
+-- !result
+select * from t1;
+-- result:
+None
+2
+-- !result
+truncate table t1;
+-- result:
+-- !result
+
+shell: ossutil64 rm -rf oss://${oss_bucket}/test_files/csv_format/${uuid0}/ > /dev/null
diff --git a/test/sql/test_files/T/test_insert_properties b/test/sql/test_files/T/test_insert_properties
new file mode 100644
index 00000000000000..b424dac81436f4
--- /dev/null
+++ b/test/sql/test_files/T/test_insert_properties
@@ -0,0 +1,67 @@
+-- name: test_insert_properties
+
+create database db_${uuid0};
+use db_${uuid0};
+
+shell: ossutil64 mkdir oss://${oss_bucket}/test_files/csv_format/${uuid0} >/dev/null || echo "exit 0" >/dev/null
+shell: ossutil64 cp --force ./sql/test_files/csv_format/invalid_int.csv oss://${oss_bucket}/test_files/csv_format/${uuid0}/ | grep -Pv "(average|elapsed)"
+
+create table t1 (k1 int);
+
+insert into t1 (k1) properties ("strict_mode" = "false", "max_filter_ratio" = "0")
+select $2 from files(
+    "path" = "oss://${oss_bucket}/test_files/csv_format/${uuid0}/*",
+    "format" = "csv",
+    "auto_detect_sample_rows" = "1",
+    "csv.column_separator" = "\\x01",
+    "csv.row_delimiter" = "\n",
+    "aws.s3.access_key" = "${oss_ak}",
+    "aws.s3.secret_key" = "${oss_sk}",
+    "aws.s3.endpoint" = "${oss_endpoint}"
+    );
+select * from t1;
+truncate table t1;
+
+insert into t1 (k1) properties ("strict_mode" = "true", "max_filter_ratio" = "0")
+select $2 from files(
+    "path" = "oss://${oss_bucket}/test_files/csv_format/${uuid0}/*",
+    "format" = "csv",
+    "auto_detect_sample_rows" = "1",
+    "csv.column_separator" = "\\x01",
+    "csv.row_delimiter" = "\n",
+    "aws.s3.access_key" = "${oss_ak}",
+    "aws.s3.secret_key" = "${oss_sk}",
+    "aws.s3.endpoint" = "${oss_endpoint}"
+    );
+select * from t1;
+truncate table t1;
+
+insert into t1 (k1) properties ("strict_mode" = "true", "max_filter_ratio" = "0.5")
+select $2 from files(
+    "path" = "oss://${oss_bucket}/test_files/csv_format/${uuid0}/*",
+    "format" = "csv",
+    "auto_detect_sample_rows" = "1",
+    "csv.column_separator" = "\\x01",
+    "csv.row_delimiter" = "\n",
+    "aws.s3.access_key" = "${oss_ak}",
+    "aws.s3.secret_key" = "${oss_sk}",
+    "aws.s3.endpoint" = "${oss_endpoint}"
+    );
+select * from t1;
+truncate table t1;
+
+insert /*+ SET_VAR(enable_insert_strict = false) */ into t1 (k1) properties ("max_filter_ratio" = "0")
+select $2 from files(
+    "path" = "oss://${oss_bucket}/test_files/csv_format/${uuid0}/*",
+    "format" = "csv",
+    "auto_detect_sample_rows" = "1",
+    "csv.column_separator" = "\\x01",
+    "csv.row_delimiter" = "\n",
+    "aws.s3.access_key" = "${oss_ak}",
+    "aws.s3.secret_key" = "${oss_sk}",
+    "aws.s3.endpoint" = "${oss_endpoint}"
+    );
+select * from t1;
+truncate table t1;
+
+shell: ossutil64 rm -rf oss://${oss_bucket}/test_files/csv_format/${uuid0}/ > /dev/null
diff --git a/test/sql/test_files/csv_format/invalid_int.csv b/test/sql/test_files/csv_format/invalid_int.csv
new file mode 100644
index 00000000000000..1242d24e2bf03d
--- /dev/null
+++ b/test/sql/test_files/csv_format/invalid_int.csv
@@ -0,0 +1,2 @@
+1
2
3
+4
a
5
diff --git a/test/sql/test_information_schema/R/test_loads b/test/sql/test_information_schema/R/test_loads
index 1bcabee86763b3..f506996ba05a62 100644
--- a/test/sql/test_information_schema/R/test_loads
+++ b/test/sql/test_information_schema/R/test_loads
@@ -26,7 +26,7 @@ CREATE TABLE ss( event_day DATE, pv BIGINT) DUPLICATE KEY(event_day) PARTITION B
 -- !result
 insert into ss values('2022-01-14', 2);
 -- result:
-[REGEX].*Insert has filtered data in strict mode.*
+[REGEX].*Insert has filtered data.*
 -- !result
 select state,type from information_schema.loads where db_name='db_${uuid1}';
 -- result:
@@ -85,7 +85,7 @@ CREATE TABLE ss (k1 bigint NOT NULL, k2 bigint NOT NULL, k3 bigint NOT NULL) dup
 -- !result
 insert into ss values(null, null, null);
 -- result:
-[REGEX].*Insert has filtered data in strict mode.*
+[REGEX].*Insert has filtered data.*
 -- !result
 [UC]id2=select id from information_schema.loads where db_name='db_${uuid2}';
 -- result:
diff --git a/test/sql/test_join/R/test_join_with_other_predicate b/test/sql/test_join/R/test_join_with_other_predicate
new file mode 100644
index 00000000000000..170352696bc05b
--- /dev/null
+++ b/test/sql/test_join/R/test_join_with_other_predicate
@@ -0,0 +1,64 @@
+-- name: test_join_with_other_predicate
+CREATE TABLE `t0` (
+  `c0` int(11) NULL COMMENT "",
+  `c1` varchar(20) NULL COMMENT "",
+  `c2` varchar(200) NULL COMMENT "",
+  `c3` int(11) NULL COMMENT ""
+) ENGINE=OLAP
+DUPLICATE KEY(`c0`, `c1`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`c0`, `c1`) BUCKETS 1
+PROPERTIES (
+"replication_num" = "1",
+"in_memory" = "false",
+"storage_format" = "DEFAULT",
+"enable_persistent_index" = "false",
+"replicated_storage" = "true",
+"compression" = "LZ4"
+);
+-- result:
+-- !result
+CREATE TABLE `t1` (
+  `c0` int(11) NULL COMMENT "",
+  `c1` varchar(20) NULL COMMENT "",
+  `c2` varchar(200) NULL COMMENT "",
+  `c3` int(11) NULL COMMENT ""
+) ENGINE=OLAP
+DUPLICATE KEY(`c0`, `c1`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`c0`, `c1`) BUCKETS 48
+PROPERTIES (
+"replication_num" = "1",
+"in_memory" = "false",
+"storage_format" = "DEFAULT",
+"enable_persistent_index" = "false",
+"replicated_storage" = "true",
+"compression" = "LZ4"
+);
+-- result:
+-- !result
+insert into t0 SELECT generate_series, generate_series, generate_series, generate_series FROM TABLE(generate_series(1,  40960));
+-- result:
+-- !result
+insert into t0 values (null,null,null,null);
+-- result:
+-- !result
+insert into t1 SELECT * FROM t0;
+-- result:
+-- !result
+select count(*) from t0 join t1 on t0.c0=t1.c0 where t0.c1 like t1.c1;
+-- result:
+40960
+-- !result
+select count(*) from t0 join t1 on t0.c0=t1.c0 where t0.c1 like concat(t1.c1, '%');
+-- result:
+40960
+-- !result
+select count(*) from t0 join t1 on t0.c0=t1.c0 where t0.c1 like concat('%', t1.c1, '%');
+-- result:
+40960
+-- !result
+select count(*) from t0 join t1 on t0.c0=t1.c0 where t0.c1 like concat('%', t1.c1);
+-- result:
+40960
+-- !result
\ No newline at end of file
diff --git a/test/sql/test_join/T/test_join_with_other_predicate b/test/sql/test_join/T/test_join_with_other_predicate
new file mode 100644
index 00000000000000..1e078fbb009cf3
--- /dev/null
+++ b/test/sql/test_join/T/test_join_with_other_predicate
@@ -0,0 +1,47 @@
+-- name: test_join_with_other_predicate
+
+CREATE TABLE `t0` (
+  `c0` int(11) NULL COMMENT "",
+  `c1` varchar(20) NULL COMMENT "",
+  `c2` varchar(200) NULL COMMENT "",
+  `c3` int(11) NULL COMMENT ""
+) ENGINE=OLAP
+DUPLICATE KEY(`c0`, `c1`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`c0`, `c1`) BUCKETS 1
+PROPERTIES (
+"replication_num" = "1",
+"in_memory" = "false",
+"storage_format" = "DEFAULT",
+"enable_persistent_index" = "false",
+"replicated_storage" = "true",
+"compression" = "LZ4"
+);
+
+CREATE TABLE `t1` (
+  `c0` int(11) NULL COMMENT "",
+  `c1` varchar(20) NULL COMMENT "",
+  `c2` varchar(200) NULL COMMENT "",
+  `c3` int(11) NULL COMMENT ""
+) ENGINE=OLAP
+DUPLICATE KEY(`c0`, `c1`)
+COMMENT "OLAP"
+DISTRIBUTED BY HASH(`c0`, `c1`) BUCKETS 48
+PROPERTIES (
+"replication_num" = "1",
+"in_memory" = "false",
+"storage_format" = "DEFAULT",
+"enable_persistent_index" = "false",
+"replicated_storage" = "true",
+"compression" = "LZ4"
+);
+
+insert into t0 SELECT generate_series, generate_series, generate_series, generate_series FROM TABLE(generate_series(1,  40960));
+insert into t0 values (null,null,null,null);
+insert into t1 SELECT * FROM t0;
+
+
+select count(*) from t0 join t1 on t0.c0=t1.c0 where t0.c1 like t1.c1;
+select count(*) from t0 join t1 on t0.c0=t1.c0 where t0.c1 like concat(t1.c1, '%');
+select count(*) from t0 join t1 on t0.c0=t1.c0 where t0.c1 like concat('%', t1.c1, '%');
+select count(*) from t0 join t1 on t0.c0=t1.c0 where t0.c1 like concat('%', t1.c1);
\ No newline at end of file
diff --git a/test/sql/test_list_partition/R/test_list_partition_cardinality b/test/sql/test_list_partition/R/test_list_partition_cardinality
new file mode 100644
index 00000000000000..3331bc007ba63c
--- /dev/null
+++ b/test/sql/test_list_partition/R/test_list_partition_cardinality
@@ -0,0 +1,81 @@
+-- name: test_list_partition_cardinality
+DROP DATABASE IF EXISTS test_list_partition_cardinality;
+-- result:
+-- !result
+CREATE DATABASE test_list_partition_cardinality;
+-- result:
+-- !result
+USE test_list_partition_cardinality;
+-- result:
+-- !result
+CREATE TABLE partitions_multi_column_1 (
+    c1 int NOT NULL,
+    c2 int NOT NULL,
+    c3 int
+)
+PARTITION BY (c1, c2);
+-- result:
+-- !result
+INSERT INTO partitions_multi_column_1 VALUES
+    (1,1,1),
+    (1,2,4),
+    (1,2,4),
+    (1,2,4),
+    (2,3,2),
+    (2,4,5),
+    (3,5,3),
+    (3,6,6);
+-- result:
+-- !result
+INSERT INTO partitions_multi_column_1 
+SELECT 4, 7, generate_series FROM TABLE(generate_series(1, 1000));
+-- result:
+-- !result
+ANALYZE FULL TABLE partitions_multi_column_1 WITH SYNC MODE;
+-- result:
+test_list_partition_cardinality.partitions_multi_column_1	analyze	status	OK
+-- !result
+SELECT count(*) FROM partitions_multi_column_1;
+-- result:
+1008
+-- !result
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c1=0', 'EMPTYSET')
+-- result:
+None
+-- !result
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c1=1', 'cardinality: 2')
+-- result:
+None
+-- !result
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c1=2', 'cardinality: 1')
+-- result:
+None
+-- !result
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c1=3', 'cardinality: 1')
+-- result:
+None
+-- !result
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c1=4', 'cardinality: 500')
+-- result:
+None
+-- !result
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c2=0', 'EMPTYSET')
+-- result:
+None
+-- !result
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c2=1', 'cardinality: 1')
+-- result:
+None
+-- !result
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c2=2', 'cardinality: 2')
+-- result:
+None
+-- !result
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c2=3', 'cardinality: 1')
+-- result:
+None
+-- !result
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c2=7', 'cardinality: 500')
+-- result:
+None
+-- !result
\ No newline at end of file
diff --git a/test/sql/test_list_partition/T/test_list_partition_cardinality b/test/sql/test_list_partition/T/test_list_partition_cardinality
new file mode 100644
index 00000000000000..c2d13a17b5e902
--- /dev/null
+++ b/test/sql/test_list_partition/T/test_list_partition_cardinality
@@ -0,0 +1,41 @@
+-- name: test_list_partition_cardinality
+
+DROP DATABASE IF EXISTS test_list_partition_cardinality;
+CREATE DATABASE test_list_partition_cardinality;
+USE test_list_partition_cardinality;
+
+CREATE TABLE partitions_multi_column_1 (
+    c1 int NOT NULL,
+    c2 int NOT NULL,
+    c3 int
+)
+PARTITION BY (c1, c2);
+
+INSERT INTO partitions_multi_column_1 VALUES
+    (1,1,1),
+    (1,2,4),
+    (1,2,4),
+    (1,2,4),
+    (2,3,2),
+    (2,4,5),
+    (3,5,3),
+    (3,6,6);
+
+INSERT INTO partitions_multi_column_1 
+SELECT 4, 7, generate_series FROM TABLE(generate_series(1, 1000));
+
+ANALYZE FULL TABLE partitions_multi_column_1 WITH SYNC MODE;
+
+SELECT count(*) FROM partitions_multi_column_1;
+
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c1=0', 'EMPTYSET')
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c1=1', 'cardinality: 2')
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c1=2', 'cardinality: 1')
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c1=3', 'cardinality: 1')
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c1=4', 'cardinality: 500')
+
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c2=0', 'EMPTYSET')
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c2=1', 'cardinality: 1')
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c2=2', 'cardinality: 2')
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c2=3', 'cardinality: 1')
+function: assert_explain_verbose_contains('SELECT COUNT(*) FROM partitions_multi_column_1 WHERE c2=7', 'cardinality: 500')
\ No newline at end of file
diff --git a/test/sql/test_materialized_column/R/test_generated_column_rewrite b/test/sql/test_materialized_column/R/test_generated_column_rewrite
index 958e6d0526e548..56d6dfcb1f913b 100644
--- a/test/sql/test_materialized_column/R/test_generated_column_rewrite
+++ b/test/sql/test_materialized_column/R/test_generated_column_rewrite
@@ -34,4 +34,94 @@ PLAN FRAGMENT 0
 -- !result
 DROP DATABASE test_generated_column_rewrite;
 -- result:
+-- !result
+-- name: test_generated_column_subquery_rewrite
+CREATE TABLE `t_generated_column_subquery_rewrite_1` (
+  `id` bigint(20) NOT NULL COMMENT "",
+  `col` STRING AS CONCAT(CAST(id AS STRING), "_abc")
+) ENGINE=OLAP 
+DUPLICATE KEY(`id`)
+DISTRIBUTED BY RANDOM BUCKETS 1
+PROPERTIES (
+"replication_num" = "1",
+"in_memory" = "false",
+"enable_persistent_index" = "false",
+"replicated_storage" = "true",
+"fast_schema_evolution" = "true",
+"compression" = "LZ4"
+);
+-- result:
+-- !result
+CREATE TABLE `t_generated_column_subquery_rewrite_2` (
+  `id` bigint(20) NOT NULL COMMENT "",
+  `col` STRING AS CONCAT(CAST(id AS STRING), "_abc")
+) ENGINE=OLAP 
+DUPLICATE KEY(`id`)
+DISTRIBUTED BY RANDOM BUCKETS 1
+PROPERTIES (
+"replication_num" = "1",
+"in_memory" = "false",
+"enable_persistent_index" = "false",
+"replicated_storage" = "true",
+"fast_schema_evolution" = "true",
+"compression" = "LZ4"
+);
+-- result:
+-- !result
+INSERT INTO t_generated_column_subquery_rewrite_1 VALUES (1);
+-- result:
+-- !result
+INSERT INTO t_generated_column_subquery_rewrite_2 VALUES (1);
+-- result:
+-- !result
+INSERT INTO t_generated_column_subquery_rewrite_2 VALUES (2);
+-- result:
+-- !result
+function: assert_explain_not_contains('SELECT CONCAT(CAST(id AS STRING), "_abc") FROM t_generated_column_subquery_rewrite_1', "abc")
+-- result:
+None
+-- !result
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT * FROM t_generated_column_subquery_rewrite_1) t_generated_column_subquery_rewrite_1 WHERE CONCAT(CAST(id AS STRING), "_abc") IS NOT NULL', "abc")
+-- result:
+None
+-- !result
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT col, id FROM t_generated_column_subquery_rewrite_1) t_generated_column_subquery_rewrite_1 WHERE CONCAT(CAST(id AS STRING), "_abc") IS NOT NULL', "abc")
+-- result:
+None
+-- !result
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT * FROM t_generated_column_subquery_rewrite_1 where id = 1) t_generated_column_subquery_rewrite_1 WHERE CONCAT(CAST(id AS STRING), "_abc") IS NOT NULL', "abc")
+-- result:
+None
+-- !result
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT col, id FROM t_generated_column_subquery_rewrite_1 where id = 1) t_generated_column_subquery_rewrite_1 WHERE CONCAT(CAST(id AS STRING), "_abc") IS NOT NULL', "abc")
+-- result:
+None
+-- !result
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT col AS col1, id AS id1 FROM t_generated_column_subquery_rewrite_1) t_generated_column_subquery_rewrite_1 WHERE CONCAT(CAST(id1 AS STRING), "_abc") IS NOT NULL', "abc")
+-- result:
+None
+-- !result
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT * FROM (SELECT * FROM t_generated_column_subquery_rewrite_1) t_generated_column_subquery_rewrite_1) t_generated_column_subquery_rewrite_1 WHERE CONCAT(CAST(id AS STRING), "_abc") IS NOT NULL', 'abc')
+-- result:
+None
+-- !result
+function: assert_explain_contains('SELECT COUNT(*) FROM (SELECT col AS id FROM t_generated_column_subquery_rewrite_1) t_generated_column_subquery_rewrite_1 WHERE CONCAT(CAST(id AS STRING), "_abc") IS NOT NULL', 'abc')
+-- result:
+None
+-- !result
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT * FROM t_generated_column_subquery_rewrite_1 where id = 1) result WHERE CONCAT(CAST(result.id AS STRING), "_abc") IS NOT NULL', "abc")
+-- result:
+None
+-- !result
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT col, id FROM t_generated_column_subquery_rewrite_1 where id = 1) result WHERE CONCAT(CAST(result.id AS STRING), "_abc") IS NOT NULL', "abc")
+-- result:
+None
+-- !result
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT t1.id as col1, t1.col as col2, t2.id as col3, t2.col as col4 FROM t_generated_column_subquery_rewrite_1 t1, t_generated_column_subquery_rewrite_2 t2 WHERE t1.id = t2.id) result WHERE CONCAT(CAST(result.col1 AS STRING), "_abc") = CONCAT(CAST(result.col3 AS STRING), "_abc")', "abc")
+-- result:
+None
+-- !result
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT t1.id as col1, t1.col as col2, t2.id as col3, t2.col as col4 FROM t_generated_column_subquery_rewrite_1 t1, t_generated_column_subquery_rewrite_2 t2 WHERE CONCAT(CAST(t1.id AS STRING), "_abc") = CONCAT(CAST(t2.id AS STRING), "_abc")) result where CONCAT(CAST(result.col1 AS STRING), "_abc") = CONCAT(CAST(result.col3 AS STRING), "_abc")', "abc")
+-- result:
+None
 -- !result
\ No newline at end of file
diff --git a/test/sql/test_materialized_column/T/test_generated_column_rewrite b/test/sql/test_materialized_column/T/test_generated_column_rewrite
index 3a313bbe5f2174..6cf9d35720f178 100644
--- a/test/sql/test_materialized_column/T/test_generated_column_rewrite
+++ b/test/sql/test_materialized_column/T/test_generated_column_rewrite
@@ -7,4 +7,52 @@ insert into t1 values(1);
 [UC]explain select * from (select id + 1 as v from t) t2;
 [UC]explain select v from (select id + 1 as v from t) t2;
 
-DROP DATABASE test_generated_column_rewrite;
\ No newline at end of file
+DROP DATABASE test_generated_column_rewrite;
+
+-- name: test_generated_column_subquery_rewrite
+CREATE TABLE `t_generated_column_subquery_rewrite_1` (
+  `id` bigint(20) NOT NULL COMMENT "",
+  `col` STRING AS CONCAT(CAST(id AS STRING), "_abc")
+) ENGINE=OLAP 
+DUPLICATE KEY(`id`)
+DISTRIBUTED BY RANDOM BUCKETS 1
+PROPERTIES (
+"replication_num" = "1",
+"in_memory" = "false",
+"enable_persistent_index" = "false",
+"replicated_storage" = "true",
+"fast_schema_evolution" = "true",
+"compression" = "LZ4"
+);
+
+CREATE TABLE `t_generated_column_subquery_rewrite_2` (
+  `id` bigint(20) NOT NULL COMMENT "",
+  `col` STRING AS CONCAT(CAST(id AS STRING), "_abc")
+) ENGINE=OLAP 
+DUPLICATE KEY(`id`)
+DISTRIBUTED BY RANDOM BUCKETS 1
+PROPERTIES (
+"replication_num" = "1",
+"in_memory" = "false",
+"enable_persistent_index" = "false",
+"replicated_storage" = "true",
+"fast_schema_evolution" = "true",
+"compression" = "LZ4"
+);
+
+INSERT INTO t_generated_column_subquery_rewrite_1 VALUES (1);
+INSERT INTO t_generated_column_subquery_rewrite_2 VALUES (1);
+INSERT INTO t_generated_column_subquery_rewrite_2 VALUES (2);
+
+function: assert_explain_not_contains('SELECT CONCAT(CAST(id AS STRING), "_abc") FROM t_generated_column_subquery_rewrite_1', "abc")
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT * FROM t_generated_column_subquery_rewrite_1) t_generated_column_subquery_rewrite_1 WHERE CONCAT(CAST(id AS STRING), "_abc") IS NOT NULL', "abc")
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT col, id FROM t_generated_column_subquery_rewrite_1) t_generated_column_subquery_rewrite_1 WHERE CONCAT(CAST(id AS STRING), "_abc") IS NOT NULL', "abc")
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT * FROM t_generated_column_subquery_rewrite_1 where id = 1) t_generated_column_subquery_rewrite_1 WHERE CONCAT(CAST(id AS STRING), "_abc") IS NOT NULL', "abc")
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT col, id FROM t_generated_column_subquery_rewrite_1 where id = 1) t_generated_column_subquery_rewrite_1 WHERE CONCAT(CAST(id AS STRING), "_abc") IS NOT NULL', "abc")
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT col AS col1, id AS id1 FROM t_generated_column_subquery_rewrite_1) t_generated_column_subquery_rewrite_1 WHERE CONCAT(CAST(id1 AS STRING), "_abc") IS NOT NULL', "abc")
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT * FROM (SELECT * FROM t_generated_column_subquery_rewrite_1) t_generated_column_subquery_rewrite_1) t_generated_column_subquery_rewrite_1 WHERE CONCAT(CAST(id AS STRING), "_abc") IS NOT NULL', 'abc')
+function: assert_explain_contains('SELECT COUNT(*) FROM (SELECT col AS id FROM t_generated_column_subquery_rewrite_1) t_generated_column_subquery_rewrite_1 WHERE CONCAT(CAST(id AS STRING), "_abc") IS NOT NULL', 'abc')
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT * FROM t_generated_column_subquery_rewrite_1 where id = 1) result WHERE CONCAT(CAST(result.id AS STRING), "_abc") IS NOT NULL', "abc")
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT col, id FROM t_generated_column_subquery_rewrite_1 where id = 1) result WHERE CONCAT(CAST(result.id AS STRING), "_abc") IS NOT NULL', "abc")
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT t1.id as col1, t1.col as col2, t2.id as col3, t2.col as col4 FROM t_generated_column_subquery_rewrite_1 t1, t_generated_column_subquery_rewrite_2 t2 WHERE t1.id = t2.id) result WHERE CONCAT(CAST(result.col1 AS STRING), "_abc") = CONCAT(CAST(result.col3 AS STRING), "_abc")', "abc")
+function: assert_explain_not_contains('SELECT COUNT(*) FROM (SELECT t1.id as col1, t1.col as col2, t2.id as col3, t2.col as col4 FROM t_generated_column_subquery_rewrite_1 t1, t_generated_column_subquery_rewrite_2 t2 WHERE CONCAT(CAST(t1.id AS STRING), "_abc") = CONCAT(CAST(t2.id AS STRING), "_abc")) result where CONCAT(CAST(result.col1 AS STRING), "_abc") = CONCAT(CAST(result.col3 AS STRING), "_abc")', "abc")
diff --git a/test/sql/test_materialized_view_refresh/R/test_mv_refresh_with_time_slice b/test/sql/test_materialized_view_refresh/R/test_mv_refresh_with_time_slice
index eae25eca724666..1a4bab48e44ab3 100644
--- a/test/sql/test_materialized_view_refresh/R/test_mv_refresh_with_time_slice
+++ b/test/sql/test_materialized_view_refresh/R/test_mv_refresh_with_time_slice
@@ -23,7 +23,7 @@ CREATE MATERIALIZED VIEW mv1 PARTITION BY date_trunc("month", dt1)
 REFRESH DEFERRED MANUAL 
 PROPERTIES (
       "replication_num" = "1",
-      "session.enable_insert_strict" = "false",
+      "session.insert_max_filter_ratio" = "1",
       "session.query_debug_options" = "{'mvRefreshTraceMode':'LOGS', 'mvRefreshTraceModule':'OPTIMIZER'}"
 )
 AS SELECT time_slice(dt, interval 5 day) as dt1, sum(id) FROM t1 GROUP BY dt1;
@@ -33,7 +33,7 @@ CREATE MATERIALIZED VIEW mv2 PARTITION BY date_trunc("month", dt1)
 REFRESH DEFERRED MANUAL 
 PROPERTIES (
       "replication_num" = "1",
-      "session.enable_insert_strict" = "false",
+      "session.insert_max_filter_ratio" = "1",
       "session.query_debug_options" = "{'mvRefreshTraceMode':'LOGS', 'mvRefreshTraceModule':'OPTIMIZER'}"
 )
 AS SELECT dt as dt1, sum(id) FROM t1 GROUP BY dt1;
@@ -83,4 +83,4 @@ drop materialized view mv1;
 -- !result
 drop materialized view mv2;
 -- result:
--- !result
\ No newline at end of file
+-- !result
diff --git a/test/sql/test_materialized_view_refresh/T/test_mv_refresh_with_time_slice b/test/sql/test_materialized_view_refresh/T/test_mv_refresh_with_time_slice
index c2d713b31dc987..02b0801ffb342e 100644
--- a/test/sql/test_materialized_view_refresh/T/test_mv_refresh_with_time_slice
+++ b/test/sql/test_materialized_view_refresh/T/test_mv_refresh_with_time_slice
@@ -35,7 +35,7 @@ CREATE MATERIALIZED VIEW mv1 PARTITION BY date_trunc("month", dt1)
 REFRESH DEFERRED MANUAL 
 PROPERTIES (
       "replication_num" = "1",
-      "session.enable_insert_strict" = "false",
+      "session.insert_max_filter_ratio" = "1",
       "session.query_debug_options" = "{'mvRefreshTraceMode':'LOGS', 'mvRefreshTraceModule':'OPTIMIZER'}"
 )
 AS SELECT time_slice(dt, interval 5 day) as dt1, sum(id) FROM t1 GROUP BY dt1;
@@ -44,7 +44,7 @@ CREATE MATERIALIZED VIEW mv2 PARTITION BY date_trunc("month", dt1)
 REFRESH DEFERRED MANUAL 
 PROPERTIES (
       "replication_num" = "1",
-      "session.enable_insert_strict" = "false",
+      "session.insert_max_filter_ratio" = "1",
       "session.query_debug_options" = "{'mvRefreshTraceMode':'LOGS', 'mvRefreshTraceModule':'OPTIMIZER'}"
 )
 AS SELECT dt as dt1, sum(id) FROM t1 GROUP BY dt1;
@@ -60,4 +60,4 @@ select * from mv1 order by 1 limit 5;
 select * from mv2 order by 1 limit 5;
 
 drop materialized view mv1;
-drop materialized view mv2;
\ No newline at end of file
+drop materialized view mv2;
diff --git a/test/sql/test_pipe/R/basic b/test/sql/test_pipe/R/basic
index 0a76048cb687e5..3eb55c789dd23d 100644
--- a/test/sql/test_pipe/R/basic
+++ b/test/sql/test_pipe/R/basic
@@ -33,7 +33,7 @@ desc t1;
 -- result:
 col_int	int	YES	true	None	
 col_map	map<varchar(1048576),int>	YES	false	None	
-col_struct	varchar(1048576)	YES	false	None	
+col_struct	struct<a varchar(1048576), b int(11)>	YES	false	None	
 -- !result
 select count(*) from t1;
 -- result:
diff --git a/test/sql/test_resource_group/R/test_resource_group_big_query b/test/sql/test_resource_group/R/test_resource_group_big_query
index 52aebc672085b4..5e675373a526da 100644
--- a/test/sql/test_resource_group/R/test_resource_group_big_query
+++ b/test/sql/test_resource_group/R/test_resource_group_big_query
@@ -45,6 +45,16 @@ create resource group rg_${uuid0}
 with w1 as (select * from t1 union all select * from t1 
     union all select * from t1 union all select * from t1 
     union all select * from t1 union all select * from t1 
+    union all select * from t1 union all select * from t1 
+    union all select * from t1 union all select * from t1 
+    union all select * from t1 union all select * from t1 
+    union all select * from t1 union all select * from t1
+    union all select * from t1 union all select * from t1
+    union all select * from t1 union all select * from t1
+    union all select * from t1 union all select * from t1
+    union all select * from t1 union all select * from t1
+    union all select * from t1 union all select * from t1
+    union all select * from t1 union all select * from t1
     union all select * from t1 union all select * from t1)
 select /*+SET_VAR(resource_group='rg_${uuid0}')*/ count(1) from w1;
 -- result:
diff --git a/test/sql/test_resource_group/T/test_resource_group_big_query b/test/sql/test_resource_group/T/test_resource_group_big_query
index e5c0658fd2c81a..a733e445926e41 100644
--- a/test/sql/test_resource_group/T/test_resource_group_big_query
+++ b/test/sql/test_resource_group/T/test_resource_group_big_query
@@ -25,6 +25,16 @@ create resource group rg_${uuid0}
 with w1 as (select * from t1 union all select * from t1 
     union all select * from t1 union all select * from t1 
     union all select * from t1 union all select * from t1 
+    union all select * from t1 union all select * from t1 
+    union all select * from t1 union all select * from t1 
+    union all select * from t1 union all select * from t1 
+    union all select * from t1 union all select * from t1
+    union all select * from t1 union all select * from t1
+    union all select * from t1 union all select * from t1
+    union all select * from t1 union all select * from t1
+    union all select * from t1 union all select * from t1
+    union all select * from t1 union all select * from t1
+    union all select * from t1 union all select * from t1
     union all select * from t1 union all select * from t1)
 select /*+SET_VAR(resource_group='rg_${uuid0}')*/ count(1) from w1;
 
diff --git a/test/sql/test_scan/R/test_schema_scan_asan_crash b/test/sql/test_scan/R/test_schema_scan_asan_crash
new file mode 100644
index 00000000000000..ec2357e3e3fd4f
--- /dev/null
+++ b/test/sql/test_scan/R/test_schema_scan_asan_crash
@@ -0,0 +1,15 @@
+-- name: test_schema_scan_asan_crash
+set enable_shared_scan = true;
+-- result:
+-- !result
+set pipeline_dop = 8;
+-- result:
+-- !result
+[UC] select count(*) from information_schema.loads;
+-- result:
+115
+-- !result
+select 1;
+-- result:
+1
+-- !result
\ No newline at end of file
diff --git a/test/sql/test_scan/T/test_schema_scan_asan_crash b/test/sql/test_scan/T/test_schema_scan_asan_crash
new file mode 100644
index 00000000000000..02ab8e9610c3aa
--- /dev/null
+++ b/test/sql/test_scan/T/test_schema_scan_asan_crash
@@ -0,0 +1,9 @@
+-- name: test_schema_scan_asan_crash
+
+set enable_shared_scan = true;
+set pipeline_dop = 8;
+
+-- BE crashes in ASAN mode.
+[UC] select count(*) from information_schema.loads;
+
+select 1;
\ No newline at end of file
diff --git a/test/sql/test_schema_change/R/test_struct_schema_change b/test/sql/test_schema_change/R/test_struct_schema_change
new file mode 100644
index 00000000000000..b743b402ea15d0
--- /dev/null
+++ b/test/sql/test_schema_change/R/test_struct_schema_change
@@ -0,0 +1,167 @@
+-- name: test_struct_schema_change
+create database test_struct_schema_change_db;
+-- result:
+-- !result
+CREATE TABLE `test_struct_schema_change_db`.`tab1` (
+  `ts` datetime NULL COMMENT "",
+  `original_ts` datetime NULL COMMENT "",
+  `si` varchar(65533) NULL COMMENT "",
+  `et` varchar(65533) NULL COMMENT "",
+  `e` struct<cdm varchar(65533), fmt varchar(65533), kid int(11), sid varchar(65533), val varchar(65533)> NULL COMMENT "",
+  `ai` varchar(65533) NULL COMMENT "",
+  `av` varchar(65533) NULL COMMENT "",
+  `ci` varchar(65533) NULL COMMENT "",
+  `cl` varchar(65533) NULL COMMENT "",
+  `q` varchar(65533) NULL COMMENT "",
+  `x` varchar(65533) NULL COMMENT "",
+  `ns` array<varchar(65533)> NULL COMMENT "",
+  `s` struct<utm_source varchar(65533), utm_medium varchar(65533), utm_term varchar(65533), utm_content varchar(65533), utm_campaign varchar(65533), utm_position varchar(65533), utm_type varchar(65533), _s varchar(65533)> NULL COMMENT "",
+  `c` map<varchar(65533),varchar(65533)> NULL COMMENT "",
+  `ss` varchar(65533) NULL COMMENT "",
+  `bc` varchar(65533) NULL COMMENT "",
+  `eo` varchar(65533) NULL COMMENT "",
+  `ia` varchar(65533) NULL COMMENT "",
+  `ka` varchar(65533) NULL COMMENT "",
+  `id` varchar(65533) NULL COMMENT "",
+  `t` map<varchar(65533),bigint(20)> NULL COMMENT "",
+  `tz` varchar(65533) NULL COMMENT "",
+  `da` map<varchar(65533),varchar(65533)> NULL COMMENT "",
+  `rc` bigint(20) NULL COMMENT "",
+  `ei` varchar(65533) NULL COMMENT "",
+  `rq` varchar(65533) NULL COMMENT "",
+  `ua` varchar(65533) NULL COMMENT "",
+  `ud` varchar(65533) NULL COMMENT "",
+  `os` tinyint(4) NULL COMMENT "",
+  `d` struct<uah varchar(65533), dvt varchar(65533), brt varchar(65533), brv varchar(65533), dvos varchar(65533)> NULL COMMENT "",
+  `st` int(11) NULL COMMENT "",
+  `sg` int(11) NULL COMMENT "",
+  `sm` array<int(11)> NULL COMMENT "",
+  `pt` varchar(65533) NULL COMMENT "",
+  `pv` varchar(65533) NULL COMMENT "",
+  `pn` varchar(65533) NULL COMMENT "",
+  `rpn` varchar(65533) NULL COMMENT "",
+  `sp` smallint(6) NULL COMMENT "",
+  `og` smallint(6) NULL COMMENT "",
+  `tm` int(11) NULL COMMENT "",
+  `at` int(11) NULL COMMENT "",
+  `pd` varchar(65533) NULL COMMENT "",
+  `mc` int(11) NULL COMMENT "",
+  `dp` int(11) NULL COMMENT "",
+  `ds` int(11) NULL COMMENT "",
+  `tx` int(11) NULL COMMENT "",
+  `v4` varchar(65533) NULL COMMENT "",
+  `v6` varchar(65533) NULL COMMENT "",
+  `s4` varchar(65533) NULL COMMENT "",
+  `s6` varchar(65533) NULL COMMENT "",
+  `lt` float NULL COMMENT "",
+  `ln` float NULL COMMENT "",
+  `pc` int(11) NULL COMMENT "",
+  `lo` varchar(65533) NULL COMMENT "",
+  `ct` varchar(65533) NULL COMMENT "",
+  `uc` varchar(65533) NULL COMMENT "",
+  `oi` varchar(65533) NULL COMMENT "",
+  `enriched_attrs` struct<uid varchar(65533), enriched_ts varchar(65533), enriched_ts_long bigint(20), create_ts bigint(20), message_ts bigint(20), sessionId varchar(65533), version varchar(65533), originRQ varchar(65533), originRC varchar(65533), rc_str varchar(65533), st varchar(65533), tm varchar(65533), og varchar(65533), dept varchar(65533), bs varchar(65533), bsr varchar(65533), sprtnr varchar(65533), site_lkp_ts bigint(20), bot int(11), errors varchar(65533)> NULL COMMENT "",
+  `ti` int(11) NULL COMMENT "",
+  `pa` int(11) NULL COMMENT "",
+  `tg` array<varchar(65533)> NULL COMMENT "",
+  `ix` array<int(11)> NULL COMMENT "",
+  `fi` varchar(65533) NULL COMMENT "",
+  `ft` varchar(65533) NULL COMMENT "",
+  `xs` varchar(65533) NULL COMMENT "",
+  `xt` varchar(65533) NULL COMMENT "",
+  `order_return_mrl_refund_requested__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, fnm varchar(65533), amt float, currcd varchar(65533), website varchar(65533), psid int(11)> NULL COMMENT "",
+  `item_deliver__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, epcisEvent struct<eId varchar(65533), epET varchar(65533), act varchar(65533), bizLoc varchar(65533), readPt varchar(65533), bizStep varchar(65533), disp varchar(65533), bizTx map<varchar(65533),varchar(65533)>, dest map<varchar(65533),varchar(65533)>, source map<varchar(65533),varchar(65533)>, pkgQty struct<epcClass varchar(65533), liid varchar(65533), itemId varchar(65533), qty float, uom varchar(65533)>, qtyList array<struct<epcClass varchar(65533), liid varchar(65533), itemId varchar(65533), qty float, uom varchar(65533)>>>, cInfo struct<name varchar(65533), delAdd struct<refId varchar(65533), refS varchar(65533), addr1 varchar(65533), addr2 varchar(65533), addr3 varchar(65533), mcode varchar(65533), city varchar(65533), co varchar(65533), isPO boolean, attn varchar(65533), addrID varchar(65533), stProv map<varchar(65533),varchar(65533)>>, evtT varchar(65533), evtD varchar(65533), estDT varchar(65533), evtTZ varchar(65533)>, cPayld map<varchar(65533),json>, prn varchar(65533), dlvdt varchar(65533), dlvdt_ms bigint(20), orddt bigint(20), rmk varchar(65533), plf varchar(65533), omst varchar(65533), fst varchar(65533), tid varchar(65533), vnum varchar(65533), trknum varchar(65533), carnm varchar(65533), carsvc varchar(65533)> NULL COMMENT "",
+  `fancash__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean> NULL COMMENT "",
+  `item_return_dispositioned__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, rrn varchar(65533), rddt varchar(65533), rddt_ms bigint(20), plf varchar(65533), omst varchar(65533), fst varchar(65533), tid varchar(65533), vnum varchar(65533), mrkdntot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, retailtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ntxbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, dscntbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrlprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrldscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ordtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyearned struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyused struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, accttot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpnet struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, savetot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, recvd boolean, rfndb boolean, zcrr boolean, mrlwvd boolean, prmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, lnitms array<struct<liid varchar(65533), pliid varchar(65533), sliid varchar(65533), itmstate varchar(65533), itmtype varchar(65533), st int(11), pid int(11), iid int(11), sku varchar(65533), size varchar(65533), imgurl varchar(65533), purl varchar(65533), itmtitle varchar(65533), isdrpshp boolean, isintldrpshp boolean, shpsrc varchar(65533), shptime int(11), psd varchar(65533), psd_ms bigint(20), pdd varchar(65533), pdd_ms bigint(20), isprsl boolean, sdid int(11), vendor_product_code varchar(65533), vendor_item_code varchar(65533), custopts varchar(65533), custcfg varchar(65533), smartskus array<struct<pid int(11), iid int(11)>>, qty int(11), shpqty int(11), uom varchar(65533), txexempt boolean, prmapp boolean, mrkdnamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrkdntot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, retailprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, retailtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdtls varchar(65533), merchvatratedtrm varchar(65533), merchvatrate float, merchpricedvatrate float, merchvatcntry varchar(65533), merchvatamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmpct float, merchprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxrate float, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdtls varchar(65533), shpvatratedtrm varchar(65533), shpvatrate float, shppricedvatrate float, shpvatcntry varchar(65533), shpvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpprmpct float, shpprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxrate float, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdtls varchar(65533), hndvatratedtrm varchar(65533), hndvatrate float, hndpricedvatrate float, hndvatcntry varchar(65533), hndvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndprmpct float, hndprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxrate float, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgvatdtls varchar(65533), paysurchrgvatratedtrm varchar(65533), paysurchrgvatrate float, paysurchrgpricedvatrate float, paysurchrgvatcntry varchar(65533), paysurchrgvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgprmpct float, paysurchrgprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgtxrate float, paysurchrgtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddtls struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidrate float, deldutypaidamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvatdtls varchar(65533), deldutypaidvatratedtrm varchar(65533), deldutypaidvatrate float, deldutypaidpricedvatrate float, deldutypaidvatcntry varchar(65533), deldutypaidvatamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddspamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidprmpct varchar(65533), deldutypaidprmamt varchar(65533), deldutypaidprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvatprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidtxrate float, deldutypaidtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, lnitmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyearned struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyused struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmreimb struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, cdi array<struct<rclssqty int(11), qty int(11), uom varchar(65533), dspcode varchar(65533), dspnm varchar(65533), subrsn varchar(65533), fraud boolean, charity boolean, sellable boolean, rtrnplcy boolean, reship boolean>>, fdi array<struct<rclssqty int(11), qty int(11), uom varchar(65533), dspcode varchar(65533), dspnm varchar(65533), subrsn varchar(65533), fraud boolean, charity boolean, sellable boolean, rtrnplcy boolean, reship boolean>>, autodispitm boolean, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrlprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrldscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, autodispdtls varchar(65533)>>, payment struct<refid varchar(65533), summary struct<merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, adjtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>, lnitms array<struct<liid varchar(65533), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, litot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>>, refund struct<refid varchar(65533), summary struct<merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, adjtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>, lnitms array<struct<liid varchar(65533), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, litot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>>> NULL COMMENT "",
+  `item_appeasement__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, appdt varchar(65533), appdt_ms bigint(20), plf varchar(65533), omst varchar(65533), tid varchar(65533), vnum varchar(65533), rsn varchar(65533), poi varchar(65533), osid varchar(65533), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ntxbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, dscntbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ordtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyearned struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyused struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, appitms array<struct<liid varchar(65533), pliid varchar(65533), itmstate varchar(65533), itmtype varchar(65533), st int(11), pid int(11), iid int(11), sku varchar(65533), size varchar(65533), imgurl varchar(65533), purl varchar(65533), itmtitle varchar(65533), isdrpshp boolean, isintldrpshp boolean, shpsrc varchar(65533), shptime int(11), psd varchar(65533), psd_ms bigint(20), pdd varchar(65533), pdd_ms bigint(20), isprsl boolean, sdid int(11), vendor_product_code varchar(65533), vendor_item_code varchar(65533), custopts varchar(65533), custcfg varchar(65533), smartskus array<struct<pid int(11), iid int(11)>>, qty int(11), shpqty int(11), uom varchar(65533), txexempt boolean, prmapp boolean, mrkdnamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrkdntot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, retailprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, retailtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdtls varchar(65533), merchvatratedtrm varchar(65533), merchvatrate float, merchpricedvatrate float, merchvatcntry varchar(65533), merchvatamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmpct float, merchprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxrate float, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdtls varchar(65533), shpvatratedtrm varchar(65533), shpvatrate float, shppricedvatrate float, shpvatcntry varchar(65533), shpvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpprmpct float, shpprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxrate float, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdtls varchar(65533), hndvatratedtrm varchar(65533), hndvatrate float, hndpricedvatrate float, hndvatcntry varchar(65533), hndvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndprmpct float, hndprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxrate float, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, lnitmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyearned struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyused struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmreimb struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrlprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrldscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>, payment struct<refid varchar(65533), summary struct<merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, adjtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>, lnitms array<struct<liid varchar(65533), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, litot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>>, refund struct<refid varchar(65533), summary struct<merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, adjtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>, lnitms array<struct<liid varchar(65533), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, litot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>>> NULL COMMENT "",
+  `order_shipping_address_update_requested__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, fnm varchar(65533), website varchar(65533), psid int(11)> NULL COMMENT "",
+  `item_out_for_delivery__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, epcisEvent struct<eId varchar(65533), epET varchar(65533), act varchar(65533), bizLoc varchar(65533), readPt varchar(65533), bizStep varchar(65533), disp varchar(65533), bizTx map<varchar(65533),varchar(65533)>, dest map<varchar(65533),varchar(65533)>, source map<varchar(65533),varchar(65533)>, pkgQty struct<epcClass varchar(65533), liid varchar(65533), itemId varchar(65533), qty float, uom varchar(65533)>, qtyList array<struct<epcClass varchar(65533), liid varchar(65533), itemId varchar(65533), qty float, uom varchar(65533)>>>, cInfo struct<name varchar(65533), delAdd struct<refId varchar(65533), refS varchar(65533), addr1 varchar(65533), addr2 varchar(65533), addr3 varchar(65533), mcode varchar(65533), city varchar(65533), co varchar(65533), isPO boolean, attn varchar(65533), addrID varchar(65533), stProv map<varchar(65533),varchar(65533)>>, evtT varchar(65533), evtD varchar(65533), estDT varchar(65533), evtTZ varchar(65533)>, cPayld map<varchar(65533),json>, prn varchar(65533), ofddt varchar(65533), ofddt_ms bigint(20), rmk varchar(65533), plf varchar(65533), omst varchar(65533), fst varchar(65533), tid varchar(65533), vnum varchar(65533), trknum varchar(65533), carnm varchar(65533), carsvc varchar(65533), orig varchar(65533), origst varchar(65533), dest varchar(65533), destst varchar(65533)> NULL COMMENT "",
+  `item_carrier_notified__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, epcisEvent struct<eId varchar(65533), epET varchar(65533), act varchar(65533), bizLoc varchar(65533), readPt varchar(65533), bizStep varchar(65533), disp varchar(65533), bizTx map<varchar(65533),varchar(65533)>, dest map<varchar(65533),varchar(65533)>, source map<varchar(65533),varchar(65533)>, pkgQty struct<epcClass varchar(65533), liid varchar(65533), itemId varchar(65533), qty float, uom varchar(65533)>, qtyList array<struct<epcClass varchar(65533), liid varchar(65533), itemId varchar(65533), qty float, uom varchar(65533)>>>, cInfo struct<name varchar(65533), delAdd struct<refId varchar(65533), refS varchar(65533), addr1 varchar(65533), addr2 varchar(65533), addr3 varchar(65533), mcode varchar(65533), city varchar(65533), co varchar(65533), isPO boolean, attn varchar(65533), addrID varchar(65533), stProv map<varchar(65533),varchar(65533)>>, evtT varchar(65533), evtD varchar(65533), estDT varchar(65533), evtTZ varchar(65533)>, cPayld struct<soid varchar(65533), source varchar(65533), shpid varchar(65533), conid varchar(65533), shpdt varchar(65533), deldt varchar(65533), rtrknum varchar(65533), itmlst array<struct<tid varchar(65533), itid varchar(65533), liid varchar(65533), itemId varchar(65533), qty varchar(65533), qtyAdjust varchar(65533), uom varchar(65533), fssku varchar(65533), esd varchar(65533), esd_ms bigint(20), pdd varchar(65533), pdd_ms bigint(20), shpm varchar(65533), prodId varchar(65533), prc struct<currency varchar(65533), xrt varchar(65533), amt float>>>, wt varchar(65533), wtuom varchar(65533), freight float, fuom varchar(65533)>, prn varchar(65533), ntfdt varchar(65533), ntfdt_ms bigint(20), rmk varchar(65533), orddt bigint(20), plf varchar(65533), omst varchar(65533), fst varchar(65533), tid varchar(65533), vnum varchar(65533), poi varchar(65533), osid varchar(65533), ossid varchar(65533), doid varchar(65533), soid varchar(65533), lang varchar(65533), locale varchar(65533), trknum varchar(65533), carnm varchar(65533), carsvc varchar(65533), med varchar(65533), med_ms bigint(20), dmd varchar(65533), ced varchar(65533), ced_ms bigint(20)> NULL COMMENT "",
+  `order_fraudstatus_reject__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, aoid varchar(65533), soid varchar(65533), plf varchar(65533), fnm varchar(65533), website varchar(65533), psid bigint(20), rsn varchar(65533), omst varchar(65533)> NULL COMMENT "",
+  `order_shipping_method_update_requested__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, fnm varchar(65533), amt float, currcd varchar(65533), website varchar(65533), psid int(11), cshpmid varchar(65533), cshpmn varchar(65533), nshpmid varchar(65533), nshpmn varchar(65533)> NULL COMMENT "",
+  `item_refund_requested__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, fnm varchar(65533), amt float, currcd varchar(65533), website varchar(65533), psid int(11)> NULL COMMENT "",
+  `account_phone_change_notify__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, accountPhoneChangeId bigint(20)> NULL COMMENT "",
+  `notifyme__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean> NULL COMMENT "",
+  `item_cancelled__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, cncldt varchar(65533), cncldt_ms bigint(20), plf varchar(65533), omst varchar(65533), tid varchar(65533), vnum varchar(65533), rsn varchar(65533), poi varchar(65533), osid varchar(65533), itmcnt int(11), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ntxbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, dscntbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ordtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyearned struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyused struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, cnclitms array<struct<liid varchar(65533), pliid varchar(65533), itmstate varchar(65533), itmtype varchar(65533), st int(11), pid int(11), iid int(11), sku varchar(65533), size varchar(65533), imgurl varchar(65533), purl varchar(65533), itmtitle varchar(65533), isdrpshp boolean, isintldrpshp boolean, shpsrc varchar(65533), shptime int(11), psd varchar(65533), psd_ms bigint(20), pdd varchar(65533), pdd_ms bigint(20), isprsl boolean, sdid int(11), vendor_product_code varchar(65533), vendor_item_code varchar(65533), custopts varchar(65533), custcfg varchar(65533), smartskus array<struct<pid int(11), iid int(11)>>, qty int(11), shpqty int(11), supcnclqty int(11), uom varchar(65533), txexempt boolean, prmapp boolean, mrkdnamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrkdntot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, retailprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, retailtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdtls varchar(65533), merchvatratedtrm varchar(65533), merchvatrate float, merchpricedvatrate float, merchvatcntry varchar(65533), merchvatamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmpct float, merchprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxrate float, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdtls varchar(65533), shpvatratedtrm varchar(65533), shpvatrate float, shppricedvatrate float, shpvatcntry varchar(65533), shpvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpprmpct float, shpprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxrate float, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdtls varchar(65533), hndvatratedtrm varchar(65533), hndvatrate float, hndpricedvatrate float, hndvatcntry varchar(65533), hndvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndprmpct float, hndprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxrate float, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, lnitmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyearned struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyused struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmreimb struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrlprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrldscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>, shpgrps array<struct<shpgrpid varchar(65533), shpmnm varchar(65533), shpm varchar(65533), shploc struct<mcode varchar(65533), cty varchar(65533)>, shpgrpitms array<struct<shpgrpitmid varchar(65533), liid varchar(65533), qty int(11)>>, dmdcd varchar(65533), rsg varchar(65533)>>, payment struct<refid varchar(65533), summary struct<merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, adjtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>, lnitms array<struct<liid varchar(65533), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, litot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>>, refund struct<refid varchar(65533), summary struct<merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, adjtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>, lnitms array<struct<liid varchar(65533), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, litot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>>, extrefval array<struct<extentity varchar(65533), `key` varchar(65533), `val` varchar(65533)>>> NULL COMMENT "",
+  `account_phone_change_confirm__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, accountPhoneChangeId bigint(20), offset bigint(20)> NULL COMMENT "",
+  `order_return_mrl_waive_requested__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, fnm varchar(65533), website varchar(65533), psid int(11)> NULL COMMENT "",
+  `item_distribution_reship_requested__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, fnm varchar(65533), website varchar(65533), psid int(11)> NULL COMMENT "",
+  `order_recovery_payment_rejected__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, cid varchar(65533), orderCreationDate bigint(20), `desc` varchar(65533)> NULL COMMENT "",
+  `notification__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean> NULL COMMENT "",
+  `checkoutcs__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean> NULL COMMENT "",
+  `order_recovery_payment_error__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, cid varchar(65533), orderCreationDate bigint(20), `desc` varchar(65533)> NULL COMMENT "",
+  `account_one_time_code_sms__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, loginAttemptId varchar(65533), sessionId varchar(65533)> NULL COMMENT ""
+) ENGINE=OLAP 
+DUPLICATE KEY(`ts`)
+COMMENT "OLAP"
+PARTITION BY time_slice(ts, 720, 'hour', 'floor')
+DISTRIBUTED BY HASH(`si`) BUCKETS 9 
+PROPERTIES (
+"replication_num" = "1",
+"in_memory" = "false",
+"enable_persistent_index" = "true",
+"replicated_storage" = "true",
+"fast_schema_evolution" = "true",
+"partition_live_number" = "1",
+"compression" = "LZ4"
+);
+-- result:
+-- !result
+shell: curl --location-trusted -u root: -H "Expect:100-continue" -H "format: json" -T ${root_path}/lib/../common/data/stream_load/sr_struct_schema_change_data1.json -XPUT ${url}/api/test_struct_schema_change_db/tab1/_stream_load
+-- result:
+0
+{
+    "Status": "Success",
+    "Message": "OK"
+}
+-- !result
+sync;
+-- result:
+-- !result
+shell: curl --location-trusted -u root: -H "Expect:100-continue" -H "format: json" -T ${root_path}/lib/../common/data/stream_load/sr_struct_schema_change_data2.json -XPUT ${url}/api/test_struct_schema_change_db/tab1/_stream_load
+-- result:
+0
+{
+    "Status": "Success",
+    "Message": "OK"
+}
+-- !result
+sync;
+-- result:
+-- !result
+select count(*) from `test_struct_schema_change_db`.`tab1`;
+-- result:
+2
+-- !result
+alter table `test_struct_schema_change_db`.`tab1` modify column item_appeasement__sms__a add field appitms.[*].supcnclqty int(11) AFTER shpqty;
+-- result:
+-- !result
+shell: curl --location-trusted -u root: -H "Expect:100-continue" -H "format: json" -T ${root_path}/lib/../common/data/stream_load/sr_struct_schema_change_data1.json -XPUT ${url}/api/test_struct_schema_change_db/tab1/_stream_load
+-- result:
+0
+{
+    "Status": "Success",
+    "Message": "OK"
+}
+-- !result
+sync;
+-- result:
+-- !result
+shell: curl --location-trusted -u root: -H "Expect:100-continue" -H "format: json" -T ${root_path}/lib/../common/data/stream_load/sr_struct_schema_change_data2.json -XPUT ${url}/api/test_struct_schema_change_db/tab1/_stream_load
+-- result:
+0
+{
+    "Status": "Success",
+    "Message": "OK"
+}
+-- !result
+sync;
+-- result:
+-- !result
+select count(*) from `test_struct_schema_change_db`.`tab1`;
+-- result:
+4
+-- !result
+drop database test_struct_schema_change_db force;
+-- result:
+-- !result
\ No newline at end of file
diff --git a/test/sql/test_schema_change/T/test_struct_schema_change b/test/sql/test_schema_change/T/test_struct_schema_change
new file mode 100644
index 00000000000000..ebbc662786481d
--- /dev/null
+++ b/test/sql/test_schema_change/T/test_struct_schema_change
@@ -0,0 +1,122 @@
+-- name: test_struct_schema_change
+create database test_struct_schema_change_db;
+CREATE TABLE `test_struct_schema_change_db`.`tab1` (
+  `ts` datetime NULL COMMENT "",
+  `original_ts` datetime NULL COMMENT "",
+  `si` varchar(65533) NULL COMMENT "",
+  `et` varchar(65533) NULL COMMENT "",
+  `e` struct<cdm varchar(65533), fmt varchar(65533), kid int(11), sid varchar(65533), val varchar(65533)> NULL COMMENT "",
+  `ai` varchar(65533) NULL COMMENT "",
+  `av` varchar(65533) NULL COMMENT "",
+  `ci` varchar(65533) NULL COMMENT "",
+  `cl` varchar(65533) NULL COMMENT "",
+  `q` varchar(65533) NULL COMMENT "",
+  `x` varchar(65533) NULL COMMENT "",
+  `ns` array<varchar(65533)> NULL COMMENT "",
+  `s` struct<utm_source varchar(65533), utm_medium varchar(65533), utm_term varchar(65533), utm_content varchar(65533), utm_campaign varchar(65533), utm_position varchar(65533), utm_type varchar(65533), _s varchar(65533)> NULL COMMENT "",
+  `c` map<varchar(65533),varchar(65533)> NULL COMMENT "",
+  `ss` varchar(65533) NULL COMMENT "",
+  `bc` varchar(65533) NULL COMMENT "",
+  `eo` varchar(65533) NULL COMMENT "",
+  `ia` varchar(65533) NULL COMMENT "",
+  `ka` varchar(65533) NULL COMMENT "",
+  `id` varchar(65533) NULL COMMENT "",
+  `t` map<varchar(65533),bigint(20)> NULL COMMENT "",
+  `tz` varchar(65533) NULL COMMENT "",
+  `da` map<varchar(65533),varchar(65533)> NULL COMMENT "",
+  `rc` bigint(20) NULL COMMENT "",
+  `ei` varchar(65533) NULL COMMENT "",
+  `rq` varchar(65533) NULL COMMENT "",
+  `ua` varchar(65533) NULL COMMENT "",
+  `ud` varchar(65533) NULL COMMENT "",
+  `os` tinyint(4) NULL COMMENT "",
+  `d` struct<uah varchar(65533), dvt varchar(65533), brt varchar(65533), brv varchar(65533), dvos varchar(65533)> NULL COMMENT "",
+  `st` int(11) NULL COMMENT "",
+  `sg` int(11) NULL COMMENT "",
+  `sm` array<int(11)> NULL COMMENT "",
+  `pt` varchar(65533) NULL COMMENT "",
+  `pv` varchar(65533) NULL COMMENT "",
+  `pn` varchar(65533) NULL COMMENT "",
+  `rpn` varchar(65533) NULL COMMENT "",
+  `sp` smallint(6) NULL COMMENT "",
+  `og` smallint(6) NULL COMMENT "",
+  `tm` int(11) NULL COMMENT "",
+  `at` int(11) NULL COMMENT "",
+  `pd` varchar(65533) NULL COMMENT "",
+  `mc` int(11) NULL COMMENT "",
+  `dp` int(11) NULL COMMENT "",
+  `ds` int(11) NULL COMMENT "",
+  `tx` int(11) NULL COMMENT "",
+  `v4` varchar(65533) NULL COMMENT "",
+  `v6` varchar(65533) NULL COMMENT "",
+  `s4` varchar(65533) NULL COMMENT "",
+  `s6` varchar(65533) NULL COMMENT "",
+  `lt` float NULL COMMENT "",
+  `ln` float NULL COMMENT "",
+  `pc` int(11) NULL COMMENT "",
+  `lo` varchar(65533) NULL COMMENT "",
+  `ct` varchar(65533) NULL COMMENT "",
+  `uc` varchar(65533) NULL COMMENT "",
+  `oi` varchar(65533) NULL COMMENT "",
+  `enriched_attrs` struct<uid varchar(65533), enriched_ts varchar(65533), enriched_ts_long bigint(20), create_ts bigint(20), message_ts bigint(20), sessionId varchar(65533), version varchar(65533), originRQ varchar(65533), originRC varchar(65533), rc_str varchar(65533), st varchar(65533), tm varchar(65533), og varchar(65533), dept varchar(65533), bs varchar(65533), bsr varchar(65533), sprtnr varchar(65533), site_lkp_ts bigint(20), bot int(11), errors varchar(65533)> NULL COMMENT "",
+  `ti` int(11) NULL COMMENT "",
+  `pa` int(11) NULL COMMENT "",
+  `tg` array<varchar(65533)> NULL COMMENT "",
+  `ix` array<int(11)> NULL COMMENT "",
+  `fi` varchar(65533) NULL COMMENT "",
+  `ft` varchar(65533) NULL COMMENT "",
+  `xs` varchar(65533) NULL COMMENT "",
+  `xt` varchar(65533) NULL COMMENT "",
+  `order_return_mrl_refund_requested__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, fnm varchar(65533), amt float, currcd varchar(65533), website varchar(65533), psid int(11)> NULL COMMENT "",
+  `item_deliver__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, epcisEvent struct<eId varchar(65533), epET varchar(65533), act varchar(65533), bizLoc varchar(65533), readPt varchar(65533), bizStep varchar(65533), disp varchar(65533), bizTx map<varchar(65533),varchar(65533)>, dest map<varchar(65533),varchar(65533)>, source map<varchar(65533),varchar(65533)>, pkgQty struct<epcClass varchar(65533), liid varchar(65533), itemId varchar(65533), qty float, uom varchar(65533)>, qtyList array<struct<epcClass varchar(65533), liid varchar(65533), itemId varchar(65533), qty float, uom varchar(65533)>>>, cInfo struct<name varchar(65533), delAdd struct<refId varchar(65533), refS varchar(65533), addr1 varchar(65533), addr2 varchar(65533), addr3 varchar(65533), mcode varchar(65533), city varchar(65533), co varchar(65533), isPO boolean, attn varchar(65533), addrID varchar(65533), stProv map<varchar(65533),varchar(65533)>>, evtT varchar(65533), evtD varchar(65533), estDT varchar(65533), evtTZ varchar(65533)>, cPayld map<varchar(65533),json>, prn varchar(65533), dlvdt varchar(65533), dlvdt_ms bigint(20), orddt bigint(20), rmk varchar(65533), plf varchar(65533), omst varchar(65533), fst varchar(65533), tid varchar(65533), vnum varchar(65533), trknum varchar(65533), carnm varchar(65533), carsvc varchar(65533)> NULL COMMENT "",
+  `fancash__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean> NULL COMMENT "",
+  `item_return_dispositioned__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, rrn varchar(65533), rddt varchar(65533), rddt_ms bigint(20), plf varchar(65533), omst varchar(65533), fst varchar(65533), tid varchar(65533), vnum varchar(65533), mrkdntot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, retailtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ntxbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, dscntbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrlprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrldscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ordtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyearned struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyused struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, accttot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpnet struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, savetot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, recvd boolean, rfndb boolean, zcrr boolean, mrlwvd boolean, prmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, lnitms array<struct<liid varchar(65533), pliid varchar(65533), sliid varchar(65533), itmstate varchar(65533), itmtype varchar(65533), st int(11), pid int(11), iid int(11), sku varchar(65533), size varchar(65533), imgurl varchar(65533), purl varchar(65533), itmtitle varchar(65533), isdrpshp boolean, isintldrpshp boolean, shpsrc varchar(65533), shptime int(11), psd varchar(65533), psd_ms bigint(20), pdd varchar(65533), pdd_ms bigint(20), isprsl boolean, sdid int(11), vendor_product_code varchar(65533), vendor_item_code varchar(65533), custopts varchar(65533), custcfg varchar(65533), smartskus array<struct<pid int(11), iid int(11)>>, qty int(11), shpqty int(11), uom varchar(65533), txexempt boolean, prmapp boolean, mrkdnamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrkdntot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, retailprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, retailtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdtls varchar(65533), merchvatratedtrm varchar(65533), merchvatrate float, merchpricedvatrate float, merchvatcntry varchar(65533), merchvatamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmpct float, merchprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxrate float, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdtls varchar(65533), shpvatratedtrm varchar(65533), shpvatrate float, shppricedvatrate float, shpvatcntry varchar(65533), shpvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpprmpct float, shpprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxrate float, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdtls varchar(65533), hndvatratedtrm varchar(65533), hndvatrate float, hndpricedvatrate float, hndvatcntry varchar(65533), hndvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndprmpct float, hndprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxrate float, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgvatdtls varchar(65533), paysurchrgvatratedtrm varchar(65533), paysurchrgvatrate float, paysurchrgpricedvatrate float, paysurchrgvatcntry varchar(65533), paysurchrgvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgprmpct float, paysurchrgprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgtxrate float, paysurchrgtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, paysurchrgtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddtls struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidrate float, deldutypaidamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvatdtls varchar(65533), deldutypaidvatratedtrm varchar(65533), deldutypaidvatrate float, deldutypaidpricedvatrate float, deldutypaidvatcntry varchar(65533), deldutypaidvatamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddspamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidprmpct varchar(65533), deldutypaidprmamt varchar(65533), deldutypaidprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvatprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaiddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidtxrate float, deldutypaidtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, deldutypaidtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, lnitmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyearned struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyused struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmreimb struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, cdi array<struct<rclssqty int(11), qty int(11), uom varchar(65533), dspcode varchar(65533), dspnm varchar(65533), subrsn varchar(65533), fraud boolean, charity boolean, sellable boolean, rtrnplcy boolean, reship boolean>>, fdi array<struct<rclssqty int(11), qty int(11), uom varchar(65533), dspcode varchar(65533), dspnm varchar(65533), subrsn varchar(65533), fraud boolean, charity boolean, sellable boolean, rtrnplcy boolean, reship boolean>>, autodispitm boolean, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrlprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrldscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, autodispdtls varchar(65533)>>, payment struct<refid varchar(65533), summary struct<merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, adjtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>, lnitms array<struct<liid varchar(65533), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, litot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>>, refund struct<refid varchar(65533), summary struct<merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, adjtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>, lnitms array<struct<liid varchar(65533), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, litot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>>> NULL COMMENT "",
+  `item_appeasement__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, appdt varchar(65533), appdt_ms bigint(20), plf varchar(65533), omst varchar(65533), tid varchar(65533), vnum varchar(65533), rsn varchar(65533), poi varchar(65533), osid varchar(65533), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ntxbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, dscntbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ordtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyearned struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyused struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, appitms array<struct<liid varchar(65533), pliid varchar(65533), itmstate varchar(65533), itmtype varchar(65533), st int(11), pid int(11), iid int(11), sku varchar(65533), size varchar(65533), imgurl varchar(65533), purl varchar(65533), itmtitle varchar(65533), isdrpshp boolean, isintldrpshp boolean, shpsrc varchar(65533), shptime int(11), psd varchar(65533), psd_ms bigint(20), pdd varchar(65533), pdd_ms bigint(20), isprsl boolean, sdid int(11), vendor_product_code varchar(65533), vendor_item_code varchar(65533), custopts varchar(65533), custcfg varchar(65533), smartskus array<struct<pid int(11), iid int(11)>>, qty int(11), shpqty int(11), uom varchar(65533), txexempt boolean, prmapp boolean, mrkdnamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrkdntot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, retailprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, retailtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdtls varchar(65533), merchvatratedtrm varchar(65533), merchvatrate float, merchpricedvatrate float, merchvatcntry varchar(65533), merchvatamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmpct float, merchprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxrate float, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdtls varchar(65533), shpvatratedtrm varchar(65533), shpvatrate float, shppricedvatrate float, shpvatcntry varchar(65533), shpvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpprmpct float, shpprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxrate float, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdtls varchar(65533), hndvatratedtrm varchar(65533), hndvatrate float, hndpricedvatrate float, hndvatcntry varchar(65533), hndvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndprmpct float, hndprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxrate float, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, lnitmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyearned struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyused struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmreimb struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrlprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrldscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>, payment struct<refid varchar(65533), summary struct<merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, adjtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>, lnitms array<struct<liid varchar(65533), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, litot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>>, refund struct<refid varchar(65533), summary struct<merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, adjtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>, lnitms array<struct<liid varchar(65533), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, litot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>>> NULL COMMENT "",
+  `order_shipping_address_update_requested__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, fnm varchar(65533), website varchar(65533), psid int(11)> NULL COMMENT "",
+  `item_out_for_delivery__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, epcisEvent struct<eId varchar(65533), epET varchar(65533), act varchar(65533), bizLoc varchar(65533), readPt varchar(65533), bizStep varchar(65533), disp varchar(65533), bizTx map<varchar(65533),varchar(65533)>, dest map<varchar(65533),varchar(65533)>, source map<varchar(65533),varchar(65533)>, pkgQty struct<epcClass varchar(65533), liid varchar(65533), itemId varchar(65533), qty float, uom varchar(65533)>, qtyList array<struct<epcClass varchar(65533), liid varchar(65533), itemId varchar(65533), qty float, uom varchar(65533)>>>, cInfo struct<name varchar(65533), delAdd struct<refId varchar(65533), refS varchar(65533), addr1 varchar(65533), addr2 varchar(65533), addr3 varchar(65533), mcode varchar(65533), city varchar(65533), co varchar(65533), isPO boolean, attn varchar(65533), addrID varchar(65533), stProv map<varchar(65533),varchar(65533)>>, evtT varchar(65533), evtD varchar(65533), estDT varchar(65533), evtTZ varchar(65533)>, cPayld map<varchar(65533),json>, prn varchar(65533), ofddt varchar(65533), ofddt_ms bigint(20), rmk varchar(65533), plf varchar(65533), omst varchar(65533), fst varchar(65533), tid varchar(65533), vnum varchar(65533), trknum varchar(65533), carnm varchar(65533), carsvc varchar(65533), orig varchar(65533), origst varchar(65533), dest varchar(65533), destst varchar(65533)> NULL COMMENT "",
+  `item_carrier_notified__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, epcisEvent struct<eId varchar(65533), epET varchar(65533), act varchar(65533), bizLoc varchar(65533), readPt varchar(65533), bizStep varchar(65533), disp varchar(65533), bizTx map<varchar(65533),varchar(65533)>, dest map<varchar(65533),varchar(65533)>, source map<varchar(65533),varchar(65533)>, pkgQty struct<epcClass varchar(65533), liid varchar(65533), itemId varchar(65533), qty float, uom varchar(65533)>, qtyList array<struct<epcClass varchar(65533), liid varchar(65533), itemId varchar(65533), qty float, uom varchar(65533)>>>, cInfo struct<name varchar(65533), delAdd struct<refId varchar(65533), refS varchar(65533), addr1 varchar(65533), addr2 varchar(65533), addr3 varchar(65533), mcode varchar(65533), city varchar(65533), co varchar(65533), isPO boolean, attn varchar(65533), addrID varchar(65533), stProv map<varchar(65533),varchar(65533)>>, evtT varchar(65533), evtD varchar(65533), estDT varchar(65533), evtTZ varchar(65533)>, cPayld struct<soid varchar(65533), source varchar(65533), shpid varchar(65533), conid varchar(65533), shpdt varchar(65533), deldt varchar(65533), rtrknum varchar(65533), itmlst array<struct<tid varchar(65533), itid varchar(65533), liid varchar(65533), itemId varchar(65533), qty varchar(65533), qtyAdjust varchar(65533), uom varchar(65533), fssku varchar(65533), esd varchar(65533), esd_ms bigint(20), pdd varchar(65533), pdd_ms bigint(20), shpm varchar(65533), prodId varchar(65533), prc struct<currency varchar(65533), xrt varchar(65533), amt float>>>, wt varchar(65533), wtuom varchar(65533), freight float, fuom varchar(65533)>, prn varchar(65533), ntfdt varchar(65533), ntfdt_ms bigint(20), rmk varchar(65533), orddt bigint(20), plf varchar(65533), omst varchar(65533), fst varchar(65533), tid varchar(65533), vnum varchar(65533), poi varchar(65533), osid varchar(65533), ossid varchar(65533), doid varchar(65533), soid varchar(65533), lang varchar(65533), locale varchar(65533), trknum varchar(65533), carnm varchar(65533), carsvc varchar(65533), med varchar(65533), med_ms bigint(20), dmd varchar(65533), ced varchar(65533), ced_ms bigint(20)> NULL COMMENT "",
+  `order_fraudstatus_reject__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, aoid varchar(65533), soid varchar(65533), plf varchar(65533), fnm varchar(65533), website varchar(65533), psid bigint(20), rsn varchar(65533), omst varchar(65533)> NULL COMMENT "",
+  `order_shipping_method_update_requested__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, fnm varchar(65533), amt float, currcd varchar(65533), website varchar(65533), psid int(11), cshpmid varchar(65533), cshpmn varchar(65533), nshpmid varchar(65533), nshpmn varchar(65533)> NULL COMMENT "",
+  `item_refund_requested__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, fnm varchar(65533), amt float, currcd varchar(65533), website varchar(65533), psid int(11)> NULL COMMENT "",
+  `account_phone_change_notify__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, accountPhoneChangeId bigint(20)> NULL COMMENT "",
+  `notifyme__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean> NULL COMMENT "",
+  `item_cancelled__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, cncldt varchar(65533), cncldt_ms bigint(20), plf varchar(65533), omst varchar(65533), tid varchar(65533), vnum varchar(65533), rsn varchar(65533), poi varchar(65533), osid varchar(65533), itmcnt int(11), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ntxbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, dscntbtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ordtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyearned struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyused struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, cnclitms array<struct<liid varchar(65533), pliid varchar(65533), itmstate varchar(65533), itmtype varchar(65533), st int(11), pid int(11), iid int(11), sku varchar(65533), size varchar(65533), imgurl varchar(65533), purl varchar(65533), itmtitle varchar(65533), isdrpshp boolean, isintldrpshp boolean, shpsrc varchar(65533), shptime int(11), psd varchar(65533), psd_ms bigint(20), pdd varchar(65533), pdd_ms bigint(20), isprsl boolean, sdid int(11), vendor_product_code varchar(65533), vendor_item_code varchar(65533), custopts varchar(65533), custcfg varchar(65533), smartskus array<struct<pid int(11), iid int(11)>>, qty int(11), shpqty int(11), supcnclqty int(11), uom varchar(65533), txexempt boolean, prmapp boolean, mrkdnamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrkdntot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, retailprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, retailtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdtls varchar(65533), merchvatratedtrm varchar(65533), merchvatrate float, merchpricedvatrate float, merchvatcntry varchar(65533), merchvatamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprice struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmpct float, merchprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmamt struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxrate float, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdtls varchar(65533), shpvatratedtrm varchar(65533), shpvatrate float, shppricedvatrate float, shpvatcntry varchar(65533), shpvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpprmpct float, shpprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shpdspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxrate float, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdtls varchar(65533), hndvatratedtrm varchar(65533), hndvatrate float, hndpricedvatrate float, hndvatcntry varchar(65533), hndvattot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddsptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndprmpct float, hndprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndvatdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hnddspdscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxrate float, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxliablty struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, lnitmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyearned struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyused struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, txtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, prmreimb struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrlprmtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrldscntdtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>, shpgrps array<struct<shpgrpid varchar(65533), shpmnm varchar(65533), shpm varchar(65533), shploc struct<mcode varchar(65533), cty varchar(65533)>, shpgrpitms array<struct<shpgrpitmid varchar(65533), liid varchar(65533), qty int(11)>>, dmdcd varchar(65533), rsg varchar(65533)>>, payment struct<refid varchar(65533), summary struct<merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, adjtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>, lnitms array<struct<liid varchar(65533), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, litot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>>, refund struct<refid varchar(65533), summary struct<merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, adjtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>, lnitms array<struct<liid varchar(65533), merchtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, merchtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, shptxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, litot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, ltyclaw struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, hndtxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, mrltxtot struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>, rstkfee struct<cur varchar(65533), amt float, baseCC varchar(65533), baseCV float, userCC varchar(65533), userCV float, userCVR float, admCC varchar(65533), admCV float, admCVR float>>>>, extrefval array<struct<extentity varchar(65533), `key` varchar(65533), `val` varchar(65533)>>> NULL COMMENT "",
+  `account_phone_change_confirm__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, accountPhoneChangeId bigint(20), offset bigint(20)> NULL COMMENT "",
+  `order_return_mrl_waive_requested__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, fnm varchar(65533), website varchar(65533), psid int(11)> NULL COMMENT "",
+  `item_distribution_reship_requested__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, fnm varchar(65533), website varchar(65533), psid int(11)> NULL COMMENT "",
+  `order_recovery_payment_rejected__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, cid varchar(65533), orderCreationDate bigint(20), `desc` varchar(65533)> NULL COMMENT "",
+  `notification__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean> NULL COMMENT "",
+  `checkoutcs__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean> NULL COMMENT "",
+  `order_recovery_payment_error__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, cid varchar(65533), orderCreationDate bigint(20), `desc` varchar(65533)> NULL COMMENT "",
+  `account_one_time_code_sms__sms__a` struct<message varchar(65533), parentPSID int(11), subscriberKeyHash varchar(65533), sms varchar(65533), messageKey varchar(65533), inputEvent varchar(65533), mode varchar(65533), emailName varchar(65533), status varchar(65533), triggerId varchar(65533), notificationName varchar(65533), trigger varchar(65533), resendEvent boolean, loginAttemptId varchar(65533), sessionId varchar(65533)> NULL COMMENT ""
+) ENGINE=OLAP 
+DUPLICATE KEY(`ts`)
+COMMENT "OLAP"
+PARTITION BY time_slice(ts, 720, 'hour', 'floor')
+DISTRIBUTED BY HASH(`si`) BUCKETS 9 
+PROPERTIES (
+"replication_num" = "1",
+"in_memory" = "false",
+"enable_persistent_index" = "true",
+"replicated_storage" = "true",
+"fast_schema_evolution" = "true",
+"partition_live_number" = "1",
+"compression" = "LZ4"
+);
+
+shell: curl --location-trusted -u root: -H "Expect:100-continue" -H "format: json" -T ${root_path}/lib/../common/data/stream_load/sr_struct_schema_change_data1.json -XPUT ${url}/api/test_struct_schema_change_db/tab1/_stream_load
+sync;
+shell: curl --location-trusted -u root: -H "Expect:100-continue" -H "format: json" -T ${root_path}/lib/../common/data/stream_load/sr_struct_schema_change_data2.json -XPUT ${url}/api/test_struct_schema_change_db/tab1/_stream_load
+sync;
+
+select count(*) from `test_struct_schema_change_db`.`tab1`;
+alter table `test_struct_schema_change_db`.`tab1` modify column item_appeasement__sms__a add field appitms.[*].supcnclqty int(11) AFTER shpqty;
+
+shell: curl --location-trusted -u root: -H "Expect:100-continue" -H "format: json" -T ${root_path}/lib/../common/data/stream_load/sr_struct_schema_change_data1.json -XPUT ${url}/api/test_struct_schema_change_db/tab1/_stream_load
+sync;
+shell: curl --location-trusted -u root: -H "Expect:100-continue" -H "format: json" -T ${root_path}/lib/../common/data/stream_load/sr_struct_schema_change_data2.json -XPUT ${url}/api/test_struct_schema_change_db/tab1/_stream_load
+sync;
+
+select count(*) from `test_struct_schema_change_db`.`tab1`;
+
+drop database test_struct_schema_change_db force;
\ No newline at end of file
diff --git a/test/sql/test_temporary_table/R/temporary_table b/test/sql/test_temporary_table/R/temporary_table
index ae67968ec0d0d8..3a2e6d0a7380c4 100644
--- a/test/sql/test_temporary_table/R/temporary_table
+++ b/test/sql/test_temporary_table/R/temporary_table
@@ -493,4 +493,38 @@ create temporary table `tbl2` like `t`;
 -- !result
 create temporary table `tbl3` as select * from `t`;
 -- result:
+-- !result
+-- name: test_drop_table
+create table `t` (
+    `c1` int,
+    `c2` int,
+    `c3` int
+) engine=OLAP primary key(`c1`) distributed by hash(`c1`) buckets 3 properties("replication_num" = "1");
+-- result:
+-- !result
+create temporary table `t1` like `t`;
+-- result:
+-- !result
+show temporary tables;
+-- result:
+t1
+-- !result
+drop table `t1`;
+-- result:
+-- !result
+show temporary tables;
+-- result:
+-- !result
+create temporary table `t1` like `t`;
+-- result:
+-- !result
+show temporary tables;
+-- result:
+t1
+-- !result
+drop temporary table `t1`;
+-- result:
+-- !result
+show temporary tables;
+-- result:
 -- !result
\ No newline at end of file
diff --git a/test/sql/test_temporary_table/T/temporary_table b/test/sql/test_temporary_table/T/temporary_table
index b4436557c841d7..8fb1596757062a 100644
--- a/test/sql/test_temporary_table/T/temporary_table
+++ b/test/sql/test_temporary_table/T/temporary_table
@@ -218,4 +218,19 @@ create temporary table `tbl1` (
     `c3` int
 ) engine=OLAP primary key(`c1`) distributed by hash(`c1`) buckets 3 properties("replication_num" = "1");
 create temporary table `tbl2` like `t`;
-create temporary table `tbl3` as select * from `t`;
\ No newline at end of file
+create temporary table `tbl3` as select * from `t`;
+
+-- name: test_drop_table
+create table `t` (
+    `c1` int,
+    `c2` int,
+    `c3` int
+) engine=OLAP primary key(`c1`) distributed by hash(`c1`) buckets 3 properties("replication_num" = "1");
+create temporary table `t1` like `t`;
+show temporary tables;
+drop table `t1`;
+show temporary tables;
+create temporary table `t1` like `t`;
+show temporary tables;
+drop temporary table `t1`;
+show temporary tables;
\ No newline at end of file
diff --git a/test/sql/test_udf/R/test_jvm_udf b/test/sql/test_udf/R/test_jvm_udf
index e800f6223e5fc5..f05c5e1785b62c 100644
--- a/test/sql/test_udf/R/test_jvm_udf
+++ b/test/sql/test_udf/R/test_jvm_udf
@@ -9,6 +9,48 @@ type = "StarrocksJar"
 file = "${udf_url}/starrocks-jdbc%2FSumbigint.jar";
 -- result:
 -- !result
+CREATE TABLE FUNCTION udtfstring(string)
+RETURNS string
+symbol = "UDTFstring"
+type = "StarrocksJar"
+file = "${udf_url}/starrocks-jdbc%2FUDTFstring.jar";
+-- result:
+-- !result
+CREATE TABLE FUNCTION udtfstring_wrong_match(string)
+RETURNS int
+symbol = "UDTFstring"
+type = "StarrocksJar"
+file = "${udf_url}/starrocks-jdbc%2FUDTFstring.jar";
+-- result:
+-- !result
+CREATE TABLE FUNCTION udtfint(int)
+RETURNS int
+symbol = "UDTFint"
+type = "StarrocksJar"
+file = "${udf_url}/starrocks-jdbc%2FUDTFint.jar";
+-- result:
+-- !result
+CREATE TABLE FUNCTION udtfbigint(bigint)
+RETURNS bigint
+symbol = "UDTFbigint"
+type = "StarrocksJar"
+file = "${udf_url}/starrocks-jdbc%2FUDTFbigint.jar";
+-- result:
+-- !result
+CREATE TABLE FUNCTION udtffloat(float)
+RETURNS float
+symbol = "UDTFfloat"
+type = "StarrocksJar"
+file = "${udf_url}/starrocks-jdbc%2FUDTFfloat.jar";
+-- result:
+-- !result
+CREATE TABLE FUNCTION udtfdouble(double)
+RETURNS double
+symbol = "UDTFdouble"
+type = "StarrocksJar"
+file = "${udf_url}/starrocks-jdbc%2FUDTFdouble.jar";
+-- result:
+-- !result
 CREATE TABLE `t0` (
   `c0` int(11) NULL COMMENT "",
   `c1` varchar(20) NULL COMMENT "",
@@ -25,6 +67,30 @@ PROPERTIES (
 insert into t0 SELECT generate_series, generate_series, generate_series, generate_series FROM TABLE(generate_series(1,  40960));
 -- result:
 -- !result
+select count(udtfstring) from t0, udtfstring(c1);
+-- result:
+81920
+-- !result
+select count(udtfstring_wrong_match) from t0, udtfstring_wrong_match(c1);
+-- result:
+E: (1064, 'Type not matched, expect class java.lang.Integer, but got class java.lang.String')
+-- !result
+select count(udtfint) from t0, udtfint(c1);
+-- result:
+81920
+-- !result
+select count(udtfbigint) from t0, udtfbigint(c1);
+-- result:
+81920
+-- !result
+select count(udtffloat) from t0, udtffloat(c1);
+-- result:
+81920
+-- !result
+select count(udtfdouble) from t0, udtfdouble(c1);
+-- result:
+81920
+-- !result
 set streaming_preaggregation_mode="force_streaming";
 -- result:
 -- !result
diff --git a/test/sql/test_udf/T/test_jvm_udf b/test/sql/test_udf/T/test_jvm_udf
index 4ffb61fcd769e5..5fde82d1a0dd06 100644
--- a/test/sql/test_udf/T/test_jvm_udf
+++ b/test/sql/test_udf/T/test_jvm_udf
@@ -8,6 +8,43 @@ symbol = "Sumbigint"
 type = "StarrocksJar"
 file = "${udf_url}/starrocks-jdbc%2FSumbigint.jar";
 
+CREATE TABLE FUNCTION udtfstring(string)
+RETURNS string
+symbol = "UDTFstring"
+type = "StarrocksJar"
+file = "${udf_url}/starrocks-jdbc%2FUDTFstring.jar";
+
+CREATE TABLE FUNCTION udtfstring_wrong_match(string)
+RETURNS int
+symbol = "UDTFstring"
+type = "StarrocksJar"
+file = "${udf_url}/starrocks-jdbc%2FUDTFstring.jar";
+
+CREATE TABLE FUNCTION udtfint(int)
+RETURNS int
+symbol = "UDTFint"
+type = "StarrocksJar"
+file = "${udf_url}/starrocks-jdbc%2FUDTFint.jar";
+
+CREATE TABLE FUNCTION udtfbigint(bigint)
+RETURNS bigint
+symbol = "UDTFbigint"
+type = "StarrocksJar"
+file = "${udf_url}/starrocks-jdbc%2FUDTFbigint.jar";
+
+CREATE TABLE FUNCTION udtffloat(float)
+RETURNS float
+symbol = "UDTFfloat"
+type = "StarrocksJar"
+file = "${udf_url}/starrocks-jdbc%2FUDTFfloat.jar";
+
+CREATE TABLE FUNCTION udtfdouble(double)
+RETURNS double
+symbol = "UDTFdouble"
+type = "StarrocksJar"
+file = "${udf_url}/starrocks-jdbc%2FUDTFdouble.jar";
+
+
 CREATE TABLE `t0` (
   `c0` int(11) NULL COMMENT "",
   `c1` varchar(20) NULL COMMENT "",
@@ -22,6 +59,14 @@ PROPERTIES (
 
 insert into t0 SELECT generate_series, generate_series, generate_series, generate_series FROM TABLE(generate_series(1,  40960));
 
+-- test udtf cases
+select count(udtfstring) from t0, udtfstring(c1);
+select count(udtfstring_wrong_match) from t0, udtfstring_wrong_match(c1);
+select count(udtfint) from t0, udtfint(c1);
+select count(udtfbigint) from t0, udtfbigint(c1);
+select count(udtffloat) from t0, udtffloat(c1);
+select count(udtfdouble) from t0, udtfdouble(c1);
+
 -- test group by limit case:
 set streaming_preaggregation_mode="force_streaming";
 select sum(delta), count(*), count(delta) from (select (sum(c3) - sumbigint(c3)) as delta from t0 group by c0,c1 limit 10) tb;
diff --git a/test/test_sql_cases.py b/test/test_sql_cases.py
index 5384e9c67f5198..f6f564018334c9 100644
--- a/test/test_sql_cases.py
+++ b/test/test_sql_cases.py
@@ -35,7 +35,6 @@
 from nose import tools
 from parameterized import parameterized
 from cup import log
-import munch
 
 from lib import sr_sql_lib
 from lib import choose_cases
@@ -87,14 +86,13 @@ def __init__(self, *args, **kwargs):
         """
         super(TestSQLCases, self).__init__(*args, **kwargs)
         self.case_info: choose_cases.ChooseCase.CaseTR
-        self.db = list()
-        self.resource = list()
         self._check_db_unique()
 
     def setUp(self, *args, **kwargs):
         """set up"""
         super().setUp()
         self.connect_starrocks()
+        self.create_starrocks_conn_pool()
         self._init_global_configs()
 
     def _init_global_configs(self):
@@ -131,6 +129,12 @@ def tearDown(self):
             res = self.save_r_into_db(self.case_info.file, self.case_info.name, self.res_log, self.version)
 
         self.close_starrocks()
+        # destroy connection pool
+        while self.connection_pool and len(self.connection_pool._idle_cache) > 0:
+            log.info(f"Teardown: freeze conn pool, size: {len(self.connection_pool._idle_cache)}")
+            conn = self.connection_pool._idle_cache.pop()
+            conn.close()
+
         self.close_trino()
         self.close_spark()
         self.close_hive()
@@ -411,7 +415,11 @@ def test_sql_basic(self, case_info: choose_cases.ChooseCase.CaseTR):
                 t_info_list: List[dict] = sql["thread"]
                 thread_list = []
 
+                # get now db
+                _outer_db = self.get_now_db()
+
                 # thread group
+                _t_conn_list = []
                 for _t_info_id, _thread in enumerate(t_info_list):
 
                     # _thread prop: name, count, info, ori, cmd, res
@@ -424,9 +432,14 @@ def test_sql_basic(self, case_info: choose_cases.ChooseCase.CaseTR):
                     # thread exec, set count in (*)
                     for _t_exec_id in range(_t_count):
                         this_t_id = f'{_t_name}-{_t_info_id}-{_t_exec_id}'
+
+                        # init a conn for thread
+                        this_conn = self.connection_pool.connection()
+                        _t_conn_list.append([this_conn, this_t_id])
+
                         t = threading.Thread(name=f"Thread-{this_t_id}",
                                              target=self.execute_thread,
-                                             args=(this_t_id, _t_cmd, _t_res, _t_ori_cmd, record_mode))
+                                             args=(this_t_id, _t_cmd, _t_res, _t_ori_cmd, record_mode, _outer_db, this_conn))
                         thread_list.append(t)
 
                 threading.excepthook = self.custom_except_hook
@@ -437,6 +450,11 @@ def test_sql_basic(self, case_info: choose_cases.ChooseCase.CaseTR):
                 for thread in thread_list:
                     thread.join()
 
+                # release conn
+                for _conn, _id in _t_conn_list:
+                    self_print(f"[{_id}] Close connection...", color=ColorEnum.CYAN, logout=True)
+                    _conn.close()
+
                 if len(self.thread_res) != 0:
                     err_t_name = "\n\t- ".join(self.thread_res.keys())
                     err_msg = f"[CONCURRENCY] FAIL:\n\t- {err_t_name}"
@@ -460,8 +478,7 @@ def test_sql_basic(self, case_info: choose_cases.ChooseCase.CaseTR):
 
                         # check thread result info
                         tools.assert_in(_t_uid, self.thread_res_log, f"Thread log of {_t_uid} is not found!")
-                        tools.eq_(len(self.thread_res_log[_t_uid]), _t_count,
-                                  f"Thread log size: {len(self.thread_res_log[_t_uid])} error!")
+                        tools.eq_(len(self.thread_res_log[_t_uid]), _t_count, f"Thread log size: {len(self.thread_res_log[_t_uid])} error, maybe you used the same thread name?")
 
                         s_thread_log = self.thread_res_log[_t_uid][0]
                         for exec_res_log in self.thread_res_log[_t_uid]:
diff --git a/thirdparty/build-thirdparty.sh b/thirdparty/build-thirdparty.sh
index c98ec84efb12b6..6be4239a449904 100755
--- a/thirdparty/build-thirdparty.sh
+++ b/thirdparty/build-thirdparty.sh
@@ -80,6 +80,18 @@ check_prerequest() {
     fi
 }
 
+# echo if gcc version is greater than 14.0.0
+# else echo ""
+echo_gt_gcc14() {
+    local version=$($CC -dumpfullversion | grep -oP '(?<=\s)\d+\.\d+\.\d+' | head -1)
+    if [[ $(echo -e "14.0.0\n$version" | sort -V | tail -1) == "14.0.0" ]]; then
+        echo ""
+    else
+        #gt gcc14
+        echo "$1"
+    fi
+}
+
 # sudo apt-get install cmake
 # sudo yum install cmake
 check_prerequest "${CMAKE_CMD} --version" "cmake"
@@ -588,7 +600,7 @@ build_rocksdb() {
 
     CFLAGS= \
     EXTRA_CFLAGS="-I ${TP_INCLUDE_DIR} -I ${TP_INCLUDE_DIR}/snappy -I ${TP_INCLUDE_DIR}/lz4 -L${TP_LIB_DIR} ${FILE_PREFIX_MAP_OPTION}" \
-    EXTRA_CXXFLAGS="-fPIC -Wno-deprecated-copy -Wno-stringop-truncation -Wno-pessimizing-move -I ${TP_INCLUDE_DIR} -I ${TP_INCLUDE_DIR}/snappy ${FILE_PREFIX_MAP_OPTION}" \
+    EXTRA_CXXFLAGS=$(echo_opts_gcc14 -Wno-error=redundant-move)" -fPIC -Wno-deprecated-copy -Wno-stringop-truncation -Wno-pessimizing-move -I ${TP_INCLUDE_DIR} -I ${TP_INCLUDE_DIR}/snappy ${FILE_PREFIX_MAP_OPTION}" \
     EXTRA_LDFLAGS="-static-libstdc++ -static-libgcc" \
     PORTABLE=1 make USE_RTTI=1 -j$PARALLEL static_lib
 
@@ -652,12 +664,18 @@ build_flatbuffers() {
   mkdir -p $BUILD_DIR
   cd $BUILD_DIR
   rm -rf CMakeCache.txt CMakeFiles/
+
+  export CXXFLAGS="-O3 -fno-omit-frame-pointer -fPIC -g " $(echo_opts_gcc14 "-Wno-error=stringop-overread")
+  export CPPFLAGS="-O3 -fno-omit-frame-pointer -fPIC -g " $(echo_opts_gcc14 "-Wno-error=stringop-overread")
+
   LDFLAGS="-static-libstdc++ -static-libgcc" \
   ${CMAKE_CMD} .. -G "${CMAKE_GENERATOR}" -DFLATBUFFERS_BUILD_TESTS=OFF
   ${BUILD_SYSTEM} -j$PARALLEL
   cp flatc  $TP_INSTALL_DIR/bin/flatc
   cp -r ../include/flatbuffers  $TP_INCLUDE_DIR/flatbuffers
   cp libflatbuffers.a $TP_LIB_DIR/libflatbuffers.a
+
+  restore_compile_flags
 }
 
 build_brotli() {
@@ -1097,10 +1115,14 @@ build_benchmark() {
     mkdir -p $BUILD_DIR
     cd $BUILD_DIR
     rm -rf CMakeCache.txt CMakeFiles/
+    # https://github.com/google/benchmark/issues/773
     cmake -DBENCHMARK_DOWNLOAD_DEPENDENCIES=off \
           -DBENCHMARK_ENABLE_GTEST_TESTS=off \
           -DCMAKE_INSTALL_PREFIX=$TP_INSTALL_DIR \
           -DCMAKE_INSTALL_LIBDIR=lib64 \
+          -DRUN_HAVE_STD_REGEX=0 \
+          -DRUN_HAVE_POSIX_REGEX=0 \
+          -DCOMPILE_HAVE_GNU_POSIX_REGEX=0 \
           -DCMAKE_BUILD_TYPE=Release ../
     ${BUILD_SYSTEM} -j$PARALLEL
     ${BUILD_SYSTEM} install
diff --git a/thirdparty/download-thirdparty.sh b/thirdparty/download-thirdparty.sh
index ef5ff9df896ff8..132ecd611c40b7 100755
--- a/thirdparty/download-thirdparty.sh
+++ b/thirdparty/download-thirdparty.sh
@@ -298,6 +298,7 @@ echo "Finished patching $LZ4_SOURCE"
 cd $TP_SOURCE_DIR/$ROCKSDB_SOURCE
 if [ ! -f $PATCHED_MARK ] && [ $ROCKSDB_SOURCE == "rocksdb-6.22.1" ]; then
     patch -p1 < $TP_PATCH_DIR/rocksdb-6.22.1-metadata-header.patch
+    patch -p1 < $TP_PATCH_DIR/rocksdb-6.22.1-gcc14.patch
     touch $PATCHED_MARK
 fi
 cd -
@@ -407,10 +408,14 @@ if [ ! -f $PATCHED_MARK ] && [ $MARIADB_SOURCE = "mariadb-connector-c-3.2.5" ];
     patch -p0 < $TP_PATCH_DIR/mariadb-connector-c-3.2.5-for-starrocks-static-link.patch
     touch $PATCHED_MARK
     echo "Finished patching $MARIADB_SOURCE"
-else
-    echo "$MARIADB_SOURCE not patched"
+fi
+if [ ! -f $PATCHED_MARK ] && [ $MARIADB_SOURCE = "mariadb-connector-c-3.1.4" ]; then
+    patch -p0 < $TP_PATCH_DIR/mariadb-connector-c-3.1.4-gcc14.patch
+    touch $PATCHED_MARK
+    echo "Finished patching $MARIADB_SOURCE"
 fi
 
+# patch aws-sdk-cpp
 cd $TP_SOURCE_DIR/$AWS_SDK_CPP_SOURCE
 if [ $AWS_SDK_CPP_SOURCE = "aws-sdk-cpp-1.11.267" ]; then
     if [ ! -f prefetch_crt_dep_ok ]; then
@@ -419,7 +424,6 @@ if [ $AWS_SDK_CPP_SOURCE = "aws-sdk-cpp-1.11.267" ]; then
     fi
 fi
 
-
 # patch jemalloc_hook
 cd $TP_SOURCE_DIR/$JEMALLOC_SOURCE
 if [ ! -f $PATCHED_MARK ] && [ $JEMALLOC_SOURCE = "jemalloc-5.3.0" ]; then
@@ -463,6 +467,7 @@ cd $TP_SOURCE_DIR/$AVRO_SOURCE/lang/c
 if [ ! -f $PATCHED_MARK ] && [ $AVRO_SOURCE = "avro-release-1.10.2" ]; then
     patch -p0 < $TP_PATCH_DIR/avro-1.10.2.c.patch
     cp $TP_PATCH_DIR/avro-1.10.2.c.findjansson.patch $TP_SOURCE_DIR/$AVRO_SOURCE/lang/c/Findjansson.cmake
+    patch -p1 < $TP_PATCH_DIR/avro-1.10.2.c.gcc14.patch
     touch $PATCHED_MARK
 fi
 cd -
@@ -481,6 +486,7 @@ cd -
 cd $TP_SOURCE_DIR/$SASL_SOURCE
 if [ ! -f $PATCHED_MARK ] && [ $SASL_SOURCE = "cyrus-sasl-2.1.28" ]; then
     patch -p1 < $TP_PATCH_DIR/sasl2-add-k5support-link.patch
+    patch -p1 < $TP_PATCH_DIR/sasl2-gcc14.patch
     touch $PATCHED_MARK
 fi
 echo "Finished patching $SASL_SOURCE"
@@ -538,3 +544,15 @@ if [[ -d $TP_SOURCE_DIR/$POCO_SOURCE ]] ; then
     cd -
     echo "Finished patching $POCO_SOURCE"
 fi
+
+# patch breakpad
+
+if [[ -d $TP_SOURCE_DIR/$BREAK_PAD_SOURCE ]] ; then
+    cd $TP_SOURCE_DIR/$BREAK_PAD_SOURCE
+    if [ ! -f "$PATCHED_MARK" ] && [[ $BREAK_PAD_SOURCE == "breakpad-2022.07.02" ]] ; then
+        patch -p1 < "$TP_PATCH_DIR/breakpad-2022.07.02.patch"
+        touch "$PATCHED_MARK"
+    fi
+    cd -
+    echo "Finished patching $BREAK_PAD_SOURCE"
+fi
\ No newline at end of file
diff --git a/thirdparty/patches/avro-1.10.2.c.gcc14.patch b/thirdparty/patches/avro-1.10.2.c.gcc14.patch
new file mode 100644
index 00000000000000..4c2360093ceff4
--- /dev/null
+++ b/thirdparty/patches/avro-1.10.2.c.gcc14.patch
@@ -0,0 +1,13 @@
+diff --git a/lang/c/examples/quickstop.c b/lang/c/examples/quickstop.c
+index ff9e970..b26dad1 100644
+--- a/lang/c/examples/quickstop.c
++++ b/lang/c/examples/quickstop.c
+@@ -107,7 +107,7 @@ int print_person(avro_file_reader_t db, avro_schema_t reader_schema)
+ 	if (rval == 0) {
+ 		int64_t id;
+ 		int32_t age;
+-		int32_t *p;
++		const char *p;
+ 		size_t size;
+ 		avro_value_t id_value;
+ 		avro_value_t first_value;
diff --git a/thirdparty/patches/breakpad-2022.07.02.patch b/thirdparty/patches/breakpad-2022.07.02.patch
new file mode 100644
index 00000000000000..b41152da5f9ad2
--- /dev/null
+++ b/thirdparty/patches/breakpad-2022.07.02.patch
@@ -0,0 +1,12 @@
+diff --git a/src/client/linux/handler/minidump_descriptor.h b/src/client/linux/handler/minidump_descriptor.h
+index c7e4f2b..f30ce91 100644
+--- a/src/client/linux/handler/minidump_descriptor.h
++++ b/src/client/linux/handler/minidump_descriptor.h
+@@ -34,6 +34,7 @@
+ #include <sys/types.h>
+ 
+ #include <string>
++#include <cstdint>
+ 
+ #include "client/linux/handler/microdump_extra_info.h"
+ #include "common/using_std_string.h"
diff --git a/thirdparty/patches/mariadb-connector-c-3.1.4-gcc14.patch b/thirdparty/patches/mariadb-connector-c-3.1.4-gcc14.patch
new file mode 100644
index 00000000000000..744d6f2637086f
--- /dev/null
+++ b/thirdparty/patches/mariadb-connector-c-3.1.4-gcc14.patch
@@ -0,0 +1,13 @@
+diff --git a/zlib/gzguts.h b/zlib/gzguts.h
+index 990a4d2..d7e7476 100644
+--- a/zlib/gzguts.h
++++ b/zlib/gzguts.h
+@@ -3,6 +3,8 @@
+  * For conditions of distribution and use, see copyright notice in zlib.h
+  */
+ 
++#include <unistd.h>
++
+ #ifdef _LARGEFILE64_SOURCE
+ #  ifndef _LARGEFILE_SOURCE
+ #    define _LARGEFILE_SOURCE 1
diff --git a/thirdparty/patches/rocksdb-6.22.1-gcc14.patch b/thirdparty/patches/rocksdb-6.22.1-gcc14.patch
new file mode 100644
index 00000000000000..bf4d106b49f9d2
--- /dev/null
+++ b/thirdparty/patches/rocksdb-6.22.1-gcc14.patch
@@ -0,0 +1,151 @@
+diff --git a/db/compaction/compaction_iteration_stats.h b/db/compaction/compaction_iteration_stats.h
+index cb7b82c..a82cf95 100644
+--- a/db/compaction/compaction_iteration_stats.h
++++ b/db/compaction/compaction_iteration_stats.h
+@@ -6,6 +6,7 @@
+ #pragma once
+ 
+ #include "rocksdb/rocksdb_namespace.h"
++#include <cstdint>
+ 
+ struct CompactionIterationStats {
+   // Compaction statistics
+diff --git a/db/kv_checksum.h b/db/kv_checksum.h
+index ba15dca..5372f61 100644
+--- a/db/kv_checksum.h
++++ b/db/kv_checksum.h
+@@ -57,7 +57,7 @@ typedef ProtectionInfoKVOTS<uint64_t> ProtectionInfoKVOTS64;
+ template <typename T>
+ class ProtectionInfo {
+  public:
+-  ProtectionInfo<T>() = default;
++  ProtectionInfo() = default;
+ 
+   Status GetStatus() const;
+   ProtectionInfoKVOT<T> ProtectKVOT(const Slice& key, const Slice& value,
+@@ -86,7 +86,7 @@ class ProtectionInfo {
+   static const uint64_t kSeedS = 0x4A2AB5CBD26F542C;
+   static const uint64_t kSeedC = 0x1CB5633EC70B2937;
+ 
+-  ProtectionInfo<T>(T val) : val_(val) {
++  ProtectionInfo(T val) : val_(val) {
+     static_assert(sizeof(ProtectionInfo<T>) == sizeof(T), "");
+   }
+ 
+@@ -99,7 +99,7 @@ class ProtectionInfo {
+ template <typename T>
+ class ProtectionInfoKVOT {
+  public:
+-  ProtectionInfoKVOT<T>() = default;
++  ProtectionInfoKVOT() = default;
+ 
+   ProtectionInfo<T> StripKVOT(const Slice& key, const Slice& value,
+                               ValueType op_type, const Slice& timestamp) const;
+@@ -121,7 +121,7 @@ class ProtectionInfoKVOT {
+   friend class ProtectionInfoKVOTS<T>;
+   friend class ProtectionInfoKVOTC<T>;
+ 
+-  ProtectionInfoKVOT<T>(T val) : info_(val) {
++  ProtectionInfoKVOT(T val) : info_(val) {
+     static_assert(sizeof(ProtectionInfoKVOT<T>) == sizeof(T), "");
+   }
+ 
+@@ -134,7 +134,7 @@ class ProtectionInfoKVOT {
+ template <typename T>
+ class ProtectionInfoKVOTC {
+  public:
+-  ProtectionInfoKVOTC<T>() = default;
++  ProtectionInfoKVOTC() = default;
+ 
+   ProtectionInfoKVOT<T> StripC(ColumnFamilyId column_family_id) const;
+ 
+@@ -162,8 +162,8 @@ class ProtectionInfoKVOTC {
+  private:
+   friend class ProtectionInfoKVOT<T>;
+ 
+-  ProtectionInfoKVOTC<T>(T val) : kvot_(val) {
+-    static_assert(sizeof(ProtectionInfoKVOTC<T>) == sizeof(T), "");
++  ProtectionInfoKVOTC(T val) : kvot_(val) {
++    static_assert(sizeof(ProtectionInfoKVOTC) == sizeof(T), "");
+   }
+ 
+   T GetVal() const { return kvot_.GetVal(); }
+@@ -175,7 +175,7 @@ class ProtectionInfoKVOTC {
+ template <typename T>
+ class ProtectionInfoKVOTS {
+  public:
+-  ProtectionInfoKVOTS<T>() = default;
++  ProtectionInfoKVOTS() = default;
+ 
+   ProtectionInfoKVOT<T> StripS(SequenceNumber sequence_number) const;
+ 
+@@ -203,7 +203,7 @@ class ProtectionInfoKVOTS {
+  private:
+   friend class ProtectionInfoKVOT<T>;
+ 
+-  ProtectionInfoKVOTS<T>(T val) : kvot_(val) {
++  ProtectionInfoKVOTS(T val) : kvot_(val) {
+     static_assert(sizeof(ProtectionInfoKVOTS<T>) == sizeof(T), "");
+   }
+ 
+diff --git a/include/rocksdb/utilities/checkpoint.h b/include/rocksdb/utilities/checkpoint.h
+index df2a744..30e3d88 100644
+--- a/include/rocksdb/utilities/checkpoint.h
++++ b/include/rocksdb/utilities/checkpoint.h
+@@ -10,6 +10,7 @@
+ 
+ #include <string>
+ #include <vector>
++#include <cstdint>
+ #include "rocksdb/status.h"
+ 
+ namespace ROCKSDB_NAMESPACE {
+diff --git a/table/block_based/data_block_hash_index.h b/table/block_based/data_block_hash_index.h
+index f356395..6eaf717 100644
+--- a/table/block_based/data_block_hash_index.h
++++ b/table/block_based/data_block_hash_index.h
+@@ -7,6 +7,7 @@
+ 
+ #include <string>
+ #include <vector>
++#include <cstdint>
+ 
+ #include "rocksdb/slice.h"
+ 
+diff --git a/third-party/folly/folly/synchronization/detail/ProxyLockable-inl.h b/third-party/folly/folly/synchronization/detail/ProxyLockable-inl.h
+index 573330c..ada1e63 100644
+--- a/third-party/folly/folly/synchronization/detail/ProxyLockable-inl.h
++++ b/third-party/folly/folly/synchronization/detail/ProxyLockable-inl.h
+@@ -14,6 +14,7 @@
+ #include <mutex>
+ #include <stdexcept>
+ #include <utility>
++#include <system_error>
+ 
+ namespace folly {
+ namespace detail {
+diff --git a/trace_replay/trace_replay.cc b/trace_replay/trace_replay.cc
+index 5fd5295..8fd5bf3 100644
+--- a/trace_replay/trace_replay.cc
++++ b/trace_replay/trace_replay.cc
+@@ -217,7 +217,7 @@ void TracerHelper::DecodeMultiGetPayload(Trace* trace,
+   multiget_payload->cf_ids.reserve(multiget_payload->multiget_size);
+   multiget_payload->multiget_keys.reserve(multiget_payload->multiget_size);
+   for (uint32_t i = 0; i < multiget_payload->multiget_size; i++) {
+-    uint32_t tmp_cfid;
++    uint32_t tmp_cfid{};
+     Slice tmp_key;
+     GetFixed32(&cfids_payload, &tmp_cfid);
+     GetLengthPrefixedSlice(&keys_payload, &tmp_key);
+diff --git a/util/string_util.h b/util/string_util.h
+index 195ae8b..8af0180 100644
+--- a/util/string_util.h
++++ b/util/string_util.h
+@@ -10,6 +10,7 @@
+ #include <string>
+ #include <unordered_map>
+ #include <vector>
++#include <cstdint>
+ 
+ #include "rocksdb/rocksdb_namespace.h"
+ 
diff --git a/thirdparty/patches/sasl2-gcc14.patch b/thirdparty/patches/sasl2-gcc14.patch
new file mode 100644
index 00000000000000..ad47859b67ed4b
--- /dev/null
+++ b/thirdparty/patches/sasl2-gcc14.patch
@@ -0,0 +1,26 @@
+diff --git a/lib/saslutil.c b/lib/saslutil.c
+index 46c628c..5341cbb 100644
+--- a/lib/saslutil.c
++++ b/lib/saslutil.c
+@@ -59,9 +59,7 @@
+ #ifdef HAVE_UNISTD_H
+ #include <unistd.h>
+ #endif
+-#ifdef HAVE_TIME_H
+ #include <time.h>
+-#endif
+ #include "saslint.h"
+ #include <saslutil.h>
+ 
+diff --git a/plugins/cram.c b/plugins/cram.c
+index d02e9ba..89c9308 100644
+--- a/plugins/cram.c
++++ b/plugins/cram.c
+@@ -52,6 +52,7 @@
+ #include <sys/stat.h>
+ #endif
+ #include <fcntl.h>
++#include <time.h>
+ 
+ #include <sasl.h>
+ #include <saslplug.h>
diff --git a/thirdparty/starlet-artifacts-version.sh b/thirdparty/starlet-artifacts-version.sh
index 12aadedf325b39..3453b456521d0a 100644
--- a/thirdparty/starlet-artifacts-version.sh
+++ b/thirdparty/starlet-artifacts-version.sh
@@ -9,4 +9,4 @@
 #   https://hub.docker.com/r/starrocks/starlet-artifacts-centos7/tags
 #
 # Update the following tag when STARLET releases a new version.
-export STARLET_ARTIFACTS_TAG=v3.3-rc3
+export STARLET_ARTIFACTS_TAG=v3.3-rc5