Iss3691

docs/guides/snippets/create_synthetic_data.md

@@ -5,7 +5,7 @@ title: Create Synthetic Data
 
 DuckDB allows you to quickly generate synthetic data sets. To do so, you may use:
 
-* [range functions]({% link docs/sql/functions/nested.md %}#range-functions)
+* [range functions]({% link docs/sql/functions/list.md %}#range-functions)
 * hash functions, e.g.,
   [`hash`]({% link docs/sql/functions/utility.md %}#hashvalue),
   [`md5`]({% link docs/sql/functions/utility.md %}#md5string),

docs/sql/data_types/array.md

@@ -13,7 +13,7 @@ To store variable-length lists, use the [`LIST` type]({% link docs/sql/data_type
 
 ## Creating Arrays
 
-Arrays can be created using the [`array_value(expr, ...)`]({% link docs/sql/functions/nested.md %}#list-functions) function.
+Arrays can be created using the [`array_value(expr, ...)` function]({% link docs/sql/functions/array.md %}#array_valueindex).
 
 Construct with the `array_value` function:
 
@@ -84,7 +84,7 @@ SELECT id, arr[1:2] AS elements FROM array_table;
 
 ## Functions
 
-All [`LIST` functions]({% link docs/sql/functions/nested.md %}#list-functions) work with the `ARRAY` type. Additionally, several `ARRAY`-native functions are also supported.
+All [`LIST` functions]({% link docs/sql/functions/list.md %}) work with the `ARRAY` type. Additionally, several `ARRAY`-native functions are also supported.
 See the [`ARRAY` functions]({% link docs/sql/functions/array.md %}#array-native-functions).
 
 ## Examples
@@ -120,4 +120,4 @@ The ordering of `ARRAY` instances is defined using a lexicographical order. `NUL
 
 ## See Also
 
-For more functions, see [List Functions]({% link docs/sql/functions/nested.md %}#list-functions).
+For more functions, see [List Functions]({% link docs/sql/functions/list.md %}).

docs/sql/data_types/list.md

@@ -5,15 +5,15 @@ title: List Type
 
 A `LIST` column encodes lists of values. Fields in the column can have values with different lengths, but they must all have the same underlying type. `LIST`s are typically used to store arrays of numbers, but can contain any uniform data type, including other `LIST`s and `STRUCT`s.
 
-`LIST`s are similar to PostgreSQL's `ARRAY` type. DuckDB uses the `LIST` terminology, but some [array functions]({% link docs/sql/functions/nested.md %}#list-functions) are provided for PostgreSQL compatibility.
+`LIST`s are similar to PostgreSQL's `ARRAY` type. DuckDB uses the `LIST` terminology, but some [`array_` functions]({% link docs/sql/functions/list.md %}) are provided for PostgreSQL compatibility.
 
 See the [data types overview]({% link docs/sql/data_types/overview.md %}) for a comparison between nested data types.
 
 > For storing fixed-length lists, DuckDB uses the [`ARRAY` type]({% link docs/sql/data_types/array.md %}).
 
 ## Creating Lists
 
-Lists can be created using the [`list_value(expr, ...)`]({% link docs/sql/functions/nested.md %}#list-functions) function or the equivalent bracket notation `[expr, ...]`. The expressions can be constants or arbitrary expressions. To create a list from a table column, use the [`list`]({% link docs/sql/functions/aggregates.md %}#general-aggregate-functions) aggregate function.
+Lists can be created using the [`list_value(expr, ...)`]({% link docs/sql/functions/list.md %}#list_valueany-) function or the equivalent bracket notation `[expr, ...]`. The expressions can be constants or arbitrary expressions. To create a list from a table column, use the [`list`]({% link docs/sql/functions/aggregates.md %}#general-aggregate-functions) aggregate function.
 
 List of integers:
 
@@ -47,7 +47,7 @@ CREATE TABLE list_table (int_list INTEGER[], varchar_list VARCHAR[]);
 
 ## Retrieving from Lists
 
-Retrieving one or more values from a list can be accomplished using brackets and slicing notation, or through [list functions]({% link docs/sql/functions/nested.md %}#list-functions) like `list_extract`. Multiple equivalent functions are provided as aliases for compatibility with systems that refer to lists as arrays. For example, the function `array_slice`.
+Retrieving one or more values from a list can be accomplished using brackets and slicing notation, or through [list functions]({% link docs/sql/functions/list.md %}) like `list_extract`. Multiple equivalent functions are provided as aliases for compatibility with systems that refer to lists as arrays. For example, the function `array_slice`.
 
 > We wrap the list creation in parenthesis so that it happens first.
 > This is only needed in our basic examples here, not when working with a list column.
@@ -130,4 +130,4 @@ If this is an unexpected constraint violation please double check with the known
 
 ## Functions
 
-See [Nested Functions]({% link docs/sql/functions/nested.md %}).
+See [List Functions]({% link docs/sql/functions/list.md %}).

docs/sql/data_types/map.md

@@ -93,4 +93,4 @@ and a `NULL` nested value member will compare above a non-`NULL` nested value me
 
 ## Functions
 
-See [Nested Functions]({% link docs/sql/functions/nested.md %}).
+See [Map Functions]({% link docs/sql/functions/map.md %}).

docs/sql/data_types/struct.md

@@ -7,15 +7,15 @@ Conceptually, a `STRUCT` column contains an ordered list of columns called “en
 
 `STRUCT`s are typically used to nest multiple columns into a single column, and the nested column can be of any type, including other `STRUCT`s and `LIST`s.
 
-`STRUCT`s are similar to PostgreSQL's `ROW` type. The key difference is that DuckDB `STRUCT`s require the same keys in each row of a `STRUCT` column. This allows DuckDB to provide significantly improved performance by fully utilizing its vectorized execution engine, and also enforces type consistency for improved correctness. DuckDB includes a `row` function as a special way to produce a `STRUCT`, but does not have a `ROW` data type. See an example below and the [nested functions docs]({% link docs/sql/functions/nested.md %}#struct-functions) for details.
+`STRUCT`s are similar to PostgreSQL's `ROW` type. The key difference is that DuckDB `STRUCT`s require the same keys in each row of a `STRUCT` column. This allows DuckDB to provide significantly improved performance by fully utilizing its vectorized execution engine, and also enforces type consistency for improved correctness. DuckDB includes a `row` function as a special way to produce a `STRUCT`, but does not have a `ROW` data type. See an example below and the [`STRUCT` functions documentation]({% link docs/sql/functions/struct.md %}) for details.
 
 `STRUCT`s have a fixed schema. It is not possible to change the schema of a `STRUCT` using `UPDATE` operations.
 
 See the [data types overview]({% link docs/sql/data_types/overview.md %}) for a comparison between nested data types.
 
 ### Creating Structs
 
-Structs can be created using the [`struct_pack(name := expr, ...)`]({% link docs/sql/functions/nested.md %}#struct-functions) function, the equivalent array notation `{'name': expr, ...}`, using a row variable, or using the `row` function.
+Structs can be created using the [`struct_pack(name := expr, ...)`]({% link docs/sql/functions/struct.md %}) function, the equivalent array notation `{'name': expr, ...}`, using a row variable, or using the `row` function.
 
 Create a struct using the `struct_pack` function. Note the lack of single quotes around the keys and the use of the `:=` operator:
 
@@ -73,7 +73,7 @@ SELECT struct_insert({'a': 1, 'b': 2, 'c': 3}, d := 4) AS s;
 
 ### Retrieving from Structs
 
-Retrieving a value from a struct can be accomplished using dot notation, bracket notation, or through [struct functions]({% link docs/sql/functions/nested.md %}#struct-functions) like `struct_extract`.
+Retrieving a value from a struct can be accomplished using dot notation, bracket notation, or through [struct functions]({% link docs/sql/functions/struct.md %}) like `struct_extract`.
 
 Use dot notation to retrieve the value at a key's location. In the following query, the subquery generates a struct column `a`, which we then query with `a.x`.
 
@@ -290,4 +290,4 @@ and type STRUCT(k2 INTEGER, k1 INTEGER) - an explicit cast is required
 
 ## Functions
 
-See [Nested Functions]({% link docs/sql/functions/nested.md %}).
+See [Struct Functions]({% link docs/sql/functions/struct.md %}).

docs/sql/data_types/union.md

@@ -9,7 +9,7 @@ A `UNION` *type* (not to be confused with the SQL [`UNION` operator]({% link doc
 
 Under the hood, `UNION` types are implemented on top of `STRUCT` types, and simply keep the “tag” as the first entry.
 
-`UNION` values can be created with the [`union_value(tag := expr)`]({% link docs/sql/functions/nested.md %}#union-functions) function or by [casting from a member type](#casting-to-unions).
+`UNION` values can be created with the [`union_value(tag := expr)`]({% link docs/sql/functions/union.md %}) function or by [casting from a member type](#casting-to-unions).
 
 ## Example
 
@@ -111,4 +111,4 @@ Since `UNION` types are implemented on top of `STRUCT` types internally, they ca
 
 ## Functions
 
-See [Nested Functions]({% link docs/sql/functions/nested.md %}#union-functions).
+See [Union Functions]({% link docs/sql/functions/union.md %}).

docs/sql/expressions/star.md

@@ -252,7 +252,7 @@ FROM (SELECT NULL a, 42 b, true c);
 
 The `*` expression can also be used to retrieve all keys from a struct as separate columns.
 This is particularly useful when a prior operation creates a struct of unknown shape, or if a query must handle any potential struct keys.
-See the [`STRUCT` data type]({% link docs/sql/data_types/struct.md %}) and [nested functions]({% link docs/sql/functions/nested.md %}) pages for more details on working with structs.
+See the [`STRUCT` data type]({% link docs/sql/data_types/struct.md %}) and [`STRUCT` functions]({% link docs/sql/functions/struct.md %}) pages for more details on working with structs.
 
 For example:
 

docs/sql/functions/array.md

@@ -5,7 +5,7 @@ title: Array Functions
 
 <!-- markdownlint-disable MD001 -->
 
-All [`LIST` functions]({% link docs/sql/functions/nested.md %}#list-functions) work with the [`ARRAY` data type]({% link docs/sql/data_types/array.md %}). Additionally, several `ARRAY`-native functions are also supported.
+All [`LIST` functions]({% link docs/sql/functions/list.md %}) work with the [`ARRAY` data type]({% link docs/sql/data_types/array.md %}). Additionally, several `ARRAY`-native functions are also supported.
 
 ## Array-Native Functions
 

docs/sql/query_syntax/unnest.md

@@ -151,7 +151,7 @@ SELECT unnest([[[1, 2], [3, 4]], [[5, 6], [7, 8, 9], []], [[10, 11]]], max_depth
 
 ### Keeping Track of List Entry Positions
 
-To keep track of each entry's position within the original list, `unnest` may be combined with [`generate_subscripts`]({% link docs/sql/functions/nested.md %}#generate_subscripts):
+To keep track of each entry's position within the original list, `unnest` may be combined with [`generate_subscripts`]({% link docs/sql/functions/list.md %}#generate_subscripts):
 
 ```sql
 SELECT unnest(l) as x, generate_subscripts(l, 1) AS index