[feature](hive)support hive catalog read json table. (#43469)

### What problem does this PR solve?

Problem Summary:
Support reading json format hive table like:
```mysql
mysql> show create table basic_json_table;
CREATE TABLE `basic_json_table`(
  `id` int,
  `name` string,
  `age` tinyint,
  `salary` float,
  `is_active` boolean,
  `join_date` date,
  `last_login` timestamp,
  `height` double,
  `profile` binary,
  `rating` decimal(10,2))
ROW FORMAT SERDE
  'org.apache.hive.hcatalog.data.JsonSerDe'
```

Behavior changed:
To implement this feature, this pr modifies `new_json_reader`.
Previously, `new_json_reader` could only insert data into columnString.
In order to support inserting data into columns of other types,
`DataTypeSerDe` is introduced to insert data into columns. To maintain
compatibility with previous versions, changes to this pr are triggered
only when reading hive json tables.

Limitation of Use:
1. Currently, only query is supported, and writing is not supported.
2. Currently, only the `ROW FORMAT SERDE
'org.apache.hive.hcatalog.data.JsonSerDe';` scenario is supported. For
some properties specified in `with serdeproperties`, Doris does not take
effect.
3. Since Hive does not allow columns with the same name but different
case when creating a table in Json format (including inside a Struct),
we convert the field names in the Json data to lowercase when reading
the Json data file, and then match according to the lowercase field
names. For field names that are duplicated after being converted to
lowercase in the data, the value of the last field is used (consistent
with Hive behavior).
example:
```
create table json_table(
    column int 
)ROW FORMAT SERDE 'org.apache.hive.hcatalog.data.JsonSerDe';

a.json:
{"column":1,"COLumn",2,"COLUMN":3}
{"column":10,"COLumn",20}
{"column":100}
in Hive : load a.json to table json_table

in Doris query:
---
3
20
100
---
```

Todo(in next pr):
Merge `serde` and `json_reader` ,because they have logical conflicts.

### Release note
Hive catalog support read json format table.

be/src/vec/data_types/serde/data_type_array_serde.h

@@ -101,6 +101,8 @@ class DataTypeArraySerDe : public DataTypeSerDe {
         nested_serde->set_return_object_as_string(value);
     }
 
+    virtual DataTypeSerDeSPtrs get_nested_serdes() const override { return {nested_serde}; }
+
 private:
     template <bool is_binary_format>
     Status _write_column_to_mysql(const IColumn& column, MysqlRowBuffer<is_binary_format>& result,

be/src/vec/data_types/serde/data_type_map_serde.h

@@ -96,6 +96,10 @@ class DataTypeMapSerDe : public DataTypeSerDe {
         value_serde->set_return_object_as_string(value);
     }
 
+    virtual DataTypeSerDeSPtrs get_nested_serdes() const override {
+        return {key_serde, value_serde};
+    }
+
 private:
     template <bool is_binary_format>
     Status _write_column_to_mysql(const IColumn& column, MysqlRowBuffer<is_binary_format>& result,

be/src/vec/data_types/serde/data_type_nullable_serde.h

@@ -99,6 +99,8 @@ class DataTypeNullableSerDe : public DataTypeSerDe {
                                   int64_t row_num) const override;
     Status read_one_cell_from_json(IColumn& column, const rapidjson::Value& result) const override;
 
+    virtual DataTypeSerDeSPtrs get_nested_serdes() const override { return {nested_serde}; }
+
 private:
     template <bool is_binary_format>
     Status _write_column_to_mysql(const IColumn& column, MysqlRowBuffer<is_binary_format>& result,

be/src/vec/data_types/serde/data_type_serde.h

@@ -100,6 +100,10 @@ class IColumn;
 class Arena;
 class IDataType;
 
+class DataTypeSerDe;
+using DataTypeSerDeSPtr = std::shared_ptr<DataTypeSerDe>;
+using DataTypeSerDeSPtrs = std::vector<DataTypeSerDeSPtr>;
+
 // Deserialize means read from different file format or memory format,
 // for example read from arrow, read from parquet.
 // Serialize means write the column cell or the total column into another
@@ -337,6 +341,11 @@ class DataTypeSerDe {
                                           Arena& mem_pool, int64_t row_num) const;
     virtual Status read_one_cell_from_json(IColumn& column, const rapidjson::Value& result) const;
 
+    virtual DataTypeSerDeSPtrs get_nested_serdes() const {
+        throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR,
+                               "Method get_nested_serdes is not supported for this serde");
+    }
+
 protected:
     bool _return_object_as_string = false;
     // This parameter indicates what level the serde belongs to and is mainly used for complex types
@@ -379,9 +388,6 @@ inline void checkArrowStatus(const arrow::Status& status, const std::string& col
     }
 }
 
-using DataTypeSerDeSPtr = std::shared_ptr<DataTypeSerDe>;
-using DataTypeSerDeSPtrs = std::vector<DataTypeSerDeSPtr>;
-
 DataTypeSerDeSPtrs create_data_type_serdes(
         const std::vector<std::shared_ptr<const IDataType>>& types);
 DataTypeSerDeSPtrs create_data_type_serdes(const std::vector<SlotDescriptor*>& slots);

be/src/vec/data_types/serde/data_type_struct_serde.h

@@ -172,6 +172,8 @@ class DataTypeStructSerDe : public DataTypeSerDe {
         }
     }
 
+    virtual DataTypeSerDeSPtrs get_nested_serdes() const override { return elem_serdes_ptrs; }
+
 private:
     std::optional<size_t> try_get_position_by_name(const String& name) const;